{
"tiddlers": {
"$:/Acknowledgements": {
"title": "$:/Acknowledgements",
"type": "text/vnd.tiddlywiki",
"text": "TiddlyWiki incorporates code from these fine OpenSource projects:\n\n* [[The Stanford Javascript Crypto Library|http://bitwiseshiftleft.github.io/sjcl/]]\n* [[The Jasmine JavaScript Test Framework|http://pivotal.github.io/jasmine/]]\n* [[Normalize.css by Nicolas Gallagher|http://necolas.github.io/normalize.css/]]\n\nAnd media from these projects:\n\n* World flag icons from [[Wikipedia|http://commons.wikimedia.org/wiki/Category:SVG_flags_by_country]]\n"
},
"$:/core/copyright.txt": {
"title": "$:/core/copyright.txt",
"type": "text/plain",
"text": "TiddlyWiki created by Jeremy Ruston, (jeremy [at] jermolene [dot] com)\n\nCopyright © Jeremy Ruston 2004-2007\nCopyright © UnaMesa Association 2007-2016\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\nRedistributions of source code must retain the above copyright notice, this\nlist of conditions and the following disclaimer.\n\nRedistributions in binary form must reproduce the above copyright notice, this\nlist of conditions and the following disclaimer in the documentation and/or other\nmaterials provided with the distribution.\n\nNeither the name of the UnaMesa Association nor the names of its contributors may be\nused to endorse or promote products derived from this software without specific\nprior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 'AS IS' AND ANY\nEXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES\nOF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT\nSHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,\nINCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED\nTO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR\nBUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\nCONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN\nANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH\nDAMAGE.\n"
},
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"tags": "$:/tags/Image",
"title": "$:/core/images/up-arrow",
"text": "<svg class=\"tc-image-up-arrow tc-image-button\" width=\"22pt\" height=\"22pt\" viewBox=\"0 0 128 128\">\n<path transform=\"rotate(-135, 63.8945, 64.1752)\" d=\"m109.07576,109.35336c-1.43248,1.43361 -3.41136,2.32182 -5.59717,2.32182l-79.16816,0c-4.36519,0 -7.91592,-3.5444 -7.91592,-7.91666c0,-4.36337 3.54408,-7.91667 7.91592,-7.91667l71.25075,0l0,-71.25074c0,-4.3652 3.54442,-7.91592 7.91667,-7.91592c4.36336,0 7.91667,3.54408 7.91667,7.91592l0,79.16815c0,2.1825 -0.88602,4.16136 -2.3185,5.59467l-0.00027,-0.00056l0.00001,-0.00001z\" />\n</svg>\n \n"
},
"$:/core/images/video": {
"title": "$:/core/images/video",
"tags": "$:/tags/Image",
"text": "<svg class=\"tc-image-video tc-image-button\" width=\"22pt\" height=\"22pt\" viewBox=\"0 0 128 128\">\n <g fill-rule=\"evenodd\">\n <path d=\"M64,12 C29.0909091,12 8.72727273,14.9166667 5.81818182,17.8333333 C2.90909091,20.75 1.93784382e-15,41.1666667 0,64.5 C1.93784382e-15,87.8333333 2.90909091,108.25 5.81818182,111.166667 C8.72727273,114.083333 29.0909091,117 64,117 C98.9090909,117 119.272727,114.083333 122.181818,111.166667 C125.090909,108.25 128,87.8333333 128,64.5 C128,41.1666667 125.090909,20.75 122.181818,17.8333333 C119.272727,14.9166667 98.9090909,12 64,12 Z M54.9161194,44.6182253 C51.102648,42.0759111 48.0112186,43.7391738 48.0112186,48.3159447 L48.0112186,79.6840553 C48.0112186,84.2685636 51.109784,85.9193316 54.9161194,83.3817747 L77.0838806,68.6032672 C80.897352,66.0609529 80.890216,61.9342897 77.0838806,59.3967328 L54.9161194,44.6182253 Z\"></path>\n </g>\n</svg>"
},
"$:/core/images/warning": {
"title": "$:/core/images/warning",
"tags": "$:/tags/Image",
"text": "<svg class=\"tc-image-warning tc-image-button\" width=\"22pt\" height=\"22pt\" viewBox=\"0 0 128 128\">\n <g fill-rule=\"evenodd\">\n <path d=\"M57.0717968,11 C60.1509982,5.66666667 67.8490018,5.66666667 70.9282032,11 L126.353829,107 C129.433031,112.333333 125.584029,119 119.425626,119 L8.57437416,119 C2.41597129,119 -1.43303051,112.333333 1.64617093,107 L57.0717968,11 Z M64,37 C59.581722,37 56,40.5820489 56,44.9935776 L56,73.0064224 C56,77.4211534 59.5907123,81 64,81 C68.418278,81 72,77.4179511 72,73.0064224 L72,44.9935776 C72,40.5788466 68.4092877,37 64,37 Z M64,104 C68.418278,104 72,100.418278 72,96 C72,91.581722 68.418278,88 64,88 C59.581722,88 56,91.581722 56,96 C56,100.418278 59.581722,104 64,104 Z\"></path>\n </g>\n</svg>"
},
"$:/language/Buttons/AdvancedSearch/Caption": {
"title": "$:/language/Buttons/AdvancedSearch/Caption",
"text": "advanced search"
},
"$:/language/Buttons/AdvancedSearch/Hint": {
"title": "$:/language/Buttons/AdvancedSearch/Hint",
"text": "Advanced search"
},
"$:/language/Buttons/Cancel/Caption": {
"title": "$:/language/Buttons/Cancel/Caption",
"text": "cancel"
},
"$:/language/Buttons/Cancel/Hint": {
"title": "$:/language/Buttons/Cancel/Hint",
"text": "Discard changes to this tiddler"
},
"$:/language/Buttons/Clone/Caption": {
"title": "$:/language/Buttons/Clone/Caption",
"text": "clone"
},
"$:/language/Buttons/Clone/Hint": {
"title": "$:/language/Buttons/Clone/Hint",
"text": "Clone this tiddler"
},
"$:/language/Buttons/Close/Caption": {
"title": "$:/language/Buttons/Close/Caption",
"text": "close"
},
"$:/language/Buttons/Close/Hint": {
"title": "$:/language/Buttons/Close/Hint",
"text": "Close this tiddler"
},
"$:/language/Buttons/CloseAll/Caption": {
"title": "$:/language/Buttons/CloseAll/Caption",
"text": "close all"
},
"$:/language/Buttons/CloseAll/Hint": {
"title": "$:/language/Buttons/CloseAll/Hint",
"text": "Close all tiddlers"
},
"$:/language/Buttons/CloseOthers/Caption": {
"title": "$:/language/Buttons/CloseOthers/Caption",
"text": "close others"
},
"$:/language/Buttons/CloseOthers/Hint": {
"title": "$:/language/Buttons/CloseOthers/Hint",
"text": "Close other tiddlers"
},
"$:/language/Buttons/ControlPanel/Caption": {
"title": "$:/language/Buttons/ControlPanel/Caption",
"text": "control panel"
},
"$:/language/Buttons/ControlPanel/Hint": {
"title": "$:/language/Buttons/ControlPanel/Hint",
"text": "Open control panel"
},
"$:/language/Buttons/Delete/Caption": {
"title": "$:/language/Buttons/Delete/Caption",
"text": "delete"
},
"$:/language/Buttons/Delete/Hint": {
"title": "$:/language/Buttons/Delete/Hint",
"text": "Delete this tiddler"
},
"$:/language/Buttons/Edit/Caption": {
"title": "$:/language/Buttons/Edit/Caption",
"text": "edit"
},
"$:/language/Buttons/Edit/Hint": {
"title": "$:/language/Buttons/Edit/Hint",
"text": "Edit this tiddler"
},
"$:/language/Buttons/Encryption/Caption": {
"title": "$:/language/Buttons/Encryption/Caption",
"text": "encryption"
},
"$:/language/Buttons/Encryption/Hint": {
"title": "$:/language/Buttons/Encryption/Hint",
"text": "Set or clear a password for saving this wiki"
},
"$:/language/Buttons/Encryption/ClearPassword/Caption": {
"title": "$:/language/Buttons/Encryption/ClearPassword/Caption",
"text": "clear password"
},
"$:/language/Buttons/Encryption/ClearPassword/Hint": {
"title": "$:/language/Buttons/Encryption/ClearPassword/Hint",
"text": "Clear the password and save this wiki without encryption"
},
"$:/language/Buttons/Encryption/SetPassword/Caption": {
"title": "$:/language/Buttons/Encryption/SetPassword/Caption",
"text": "set password"
},
"$:/language/Buttons/Encryption/SetPassword/Hint": {
"title": "$:/language/Buttons/Encryption/SetPassword/Hint",
"text": "Set a password for saving this wiki with encryption"
},
"$:/language/Buttons/ExportPage/Caption": {
"title": "$:/language/Buttons/ExportPage/Caption",
"text": "export all"
},
"$:/language/Buttons/ExportPage/Hint": {
"title": "$:/language/Buttons/ExportPage/Hint",
"text": "Export all tiddlers"
},
"$:/language/Buttons/ExportTiddler/Caption": {
"title": "$:/language/Buttons/ExportTiddler/Caption",
"text": "export tiddler"
},
"$:/language/Buttons/ExportTiddler/Hint": {
"title": "$:/language/Buttons/ExportTiddler/Hint",
"text": "Export tiddler"
},
"$:/language/Buttons/ExportTiddlers/Caption": {
"title": "$:/language/Buttons/ExportTiddlers/Caption",
"text": "export tiddlers"
},
"$:/language/Buttons/ExportTiddlers/Hint": {
"title": "$:/language/Buttons/ExportTiddlers/Hint",
"text": "Export tiddlers"
},
"$:/language/Buttons/Fold/Caption": {
"title": "$:/language/Buttons/Fold/Caption",
"text": "fold tiddler"
},
"$:/language/Buttons/Fold/Hint": {
"title": "$:/language/Buttons/Fold/Hint",
"text": "Fold the body of this tiddler"
},
"$:/language/Buttons/Fold/FoldBar/Caption": {
"title": "$:/language/Buttons/Fold/FoldBar/Caption",
"text": "fold-bar"
},
"$:/language/Buttons/Fold/FoldBar/Hint": {
"title": "$:/language/Buttons/Fold/FoldBar/Hint",
"text": "Optional bars to fold and unfold tiddlers"
},
"$:/language/Buttons/Unfold/Caption": {
"title": "$:/language/Buttons/Unfold/Caption",
"text": "unfold tiddler"
},
"$:/language/Buttons/Unfold/Hint": {
"title": "$:/language/Buttons/Unfold/Hint",
"text": "Unfold the body of this tiddler"
},
"$:/language/Buttons/FoldOthers/Caption": {
"title": "$:/language/Buttons/FoldOthers/Caption",
"text": "fold other tiddlers"
},
"$:/language/Buttons/FoldOthers/Hint": {
"title": "$:/language/Buttons/FoldOthers/Hint",
"text": "Fold the bodies of other opened tiddlers"
},
"$:/language/Buttons/FoldAll/Caption": {
"title": "$:/language/Buttons/FoldAll/Caption",
"text": "fold all tiddlers"
},
"$:/language/Buttons/FoldAll/Hint": {
"title": "$:/language/Buttons/FoldAll/Hint",
"text": "Fold the bodies of all opened tiddlers"
},
"$:/language/Buttons/UnfoldAll/Caption": {
"title": "$:/language/Buttons/UnfoldAll/Caption",
"text": "unfold all tiddlers"
},
"$:/language/Buttons/UnfoldAll/Hint": {
"title": "$:/language/Buttons/UnfoldAll/Hint",
"text": "Unfold the bodies of all opened tiddlers"
},
"$:/language/Buttons/FullScreen/Caption": {
"title": "$:/language/Buttons/FullScreen/Caption",
"text": "full-screen"
},
"$:/language/Buttons/FullScreen/Hint": {
"title": "$:/language/Buttons/FullScreen/Hint",
"text": "Enter or leave full-screen mode"
},
"$:/language/Buttons/Help/Caption": {
"title": "$:/language/Buttons/Help/Caption",
"text": "help"
},
"$:/language/Buttons/Help/Hint": {
"title": "$:/language/Buttons/Help/Hint",
"text": "Show help panel"
},
"$:/language/Buttons/Import/Caption": {
"title": "$:/language/Buttons/Import/Caption",
"text": "import"
},
"$:/language/Buttons/Import/Hint": {
"title": "$:/language/Buttons/Import/Hint",
"text": "Import many types of file including text, image, TiddlyWiki or JSON"
},
"$:/language/Buttons/Info/Caption": {
"title": "$:/language/Buttons/Info/Caption",
"text": "info"
},
"$:/language/Buttons/Info/Hint": {
"title": "$:/language/Buttons/Info/Hint",
"text": "Show information for this tiddler"
},
"$:/language/Buttons/Home/Caption": {
"title": "$:/language/Buttons/Home/Caption",
"text": "home"
},
"$:/language/Buttons/Home/Hint": {
"title": "$:/language/Buttons/Home/Hint",
"text": "Open the default tiddlers"
},
"$:/language/Buttons/Language/Caption": {
"title": "$:/language/Buttons/Language/Caption",
"text": "language"
},
"$:/language/Buttons/Language/Hint": {
"title": "$:/language/Buttons/Language/Hint",
"text": "Choose the user interface language"
},
"$:/language/Buttons/More/Caption": {
"title": "$:/language/Buttons/More/Caption",
"text": "more"
},
"$:/language/Buttons/More/Hint": {
"title": "$:/language/Buttons/More/Hint",
"text": "More actions"
},
"$:/language/Buttons/NewHere/Caption": {
"title": "$:/language/Buttons/NewHere/Caption",
"text": "new here"
},
"$:/language/Buttons/NewHere/Hint": {
"title": "$:/language/Buttons/NewHere/Hint",
"text": "Create a new tiddler tagged with this one"
},
"$:/language/Buttons/NewJournal/Caption": {
"title": "$:/language/Buttons/NewJournal/Caption",
"text": "new journal"
},
"$:/language/Buttons/NewJournal/Hint": {
"title": "$:/language/Buttons/NewJournal/Hint",
"text": "Create a new journal tiddler"
},
"$:/language/Buttons/NewJournalHere/Caption": {
"title": "$:/language/Buttons/NewJournalHere/Caption",
"text": "new journal here"
},
"$:/language/Buttons/NewJournalHere/Hint": {
"title": "$:/language/Buttons/NewJournalHere/Hint",
"text": "Create a new journal tiddler tagged with this one"
},
"$:/language/Buttons/NewImage/Caption": {
"title": "$:/language/Buttons/NewImage/Caption",
"text": "new image"
},
"$:/language/Buttons/NewImage/Hint": {
"title": "$:/language/Buttons/NewImage/Hint",
"text": "Create a new image tiddler"
},
"$:/language/Buttons/NewMarkdown/Caption": {
"title": "$:/language/Buttons/NewMarkdown/Caption",
"text": "new Markdown tiddler"
},
"$:/language/Buttons/NewMarkdown/Hint": {
"title": "$:/language/Buttons/NewMarkdown/Hint",
"text": "Create a new Markdown tiddler"
},
"$:/language/Buttons/NewTiddler/Caption": {
"title": "$:/language/Buttons/NewTiddler/Caption",
"text": "new tiddler"
},
"$:/language/Buttons/NewTiddler/Hint": {
"title": "$:/language/Buttons/NewTiddler/Hint",
"text": "Create a new tiddler"
},
"$:/language/Buttons/OpenWindow/Caption": {
"title": "$:/language/Buttons/OpenWindow/Caption",
"text": "open in new window"
},
"$:/language/Buttons/OpenWindow/Hint": {
"title": "$:/language/Buttons/OpenWindow/Hint",
"text": "Open tiddler in new window"
},
"$:/language/Buttons/Palette/Caption": {
"title": "$:/language/Buttons/Palette/Caption",
"text": "palette"
},
"$:/language/Buttons/Palette/Hint": {
"title": "$:/language/Buttons/Palette/Hint",
"text": "Choose the colour palette"
},
"$:/language/Buttons/Permalink/Caption": {
"title": "$:/language/Buttons/Permalink/Caption",
"text": "permalink"
},
"$:/language/Buttons/Permalink/Hint": {
"title": "$:/language/Buttons/Permalink/Hint",
"text": "Set browser address bar to a direct link to this tiddler"
},
"$:/language/Buttons/Permaview/Caption": {
"title": "$:/language/Buttons/Permaview/Caption",
"text": "permaview"
},
"$:/language/Buttons/Permaview/Hint": {
"title": "$:/language/Buttons/Permaview/Hint",
"text": "Set browser address bar to a direct link to all the tiddlers in this story"
},
"$:/language/Buttons/Refresh/Caption": {
"title": "$:/language/Buttons/Refresh/Caption",
"text": "refresh"
},
"$:/language/Buttons/Refresh/Hint": {
"title": "$:/language/Buttons/Refresh/Hint",
"text": "Perform a full refresh of the wiki"
},
"$:/language/Buttons/Save/Caption": {
"title": "$:/language/Buttons/Save/Caption",
"text": "ok"
},
"$:/language/Buttons/Save/Hint": {
"title": "$:/language/Buttons/Save/Hint",
"text": "Confirm changes to this tiddler"
},
"$:/language/Buttons/SaveWiki/Caption": {
"title": "$:/language/Buttons/SaveWiki/Caption",
"text": "save changes"
},
"$:/language/Buttons/SaveWiki/Hint": {
"title": "$:/language/Buttons/SaveWiki/Hint",
"text": "Save changes"
},
"$:/language/Buttons/StoryView/Caption": {
"title": "$:/language/Buttons/StoryView/Caption",
"text": "storyview"
},
"$:/language/Buttons/StoryView/Hint": {
"title": "$:/language/Buttons/StoryView/Hint",
"text": "Choose the story visualisation"
},
"$:/language/Buttons/HideSideBar/Caption": {
"title": "$:/language/Buttons/HideSideBar/Caption",
"text": "hide sidebar"
},
"$:/language/Buttons/HideSideBar/Hint": {
"title": "$:/language/Buttons/HideSideBar/Hint",
"text": "Hide sidebar"
},
"$:/language/Buttons/ShowSideBar/Caption": {
"title": "$:/language/Buttons/ShowSideBar/Caption",
"text": "show sidebar"
},
"$:/language/Buttons/ShowSideBar/Hint": {
"title": "$:/language/Buttons/ShowSideBar/Hint",
"text": "Show sidebar"
},
"$:/language/Buttons/TagManager/Caption": {
"title": "$:/language/Buttons/TagManager/Caption",
"text": "tag manager"
},
"$:/language/Buttons/TagManager/Hint": {
"title": "$:/language/Buttons/TagManager/Hint",
"text": "Open tag manager"
},
"$:/language/Buttons/Theme/Caption": {
"title": "$:/language/Buttons/Theme/Caption",
"text": "theme"
},
"$:/language/Buttons/Theme/Hint": {
"title": "$:/language/Buttons/Theme/Hint",
"text": "Choose the display theme"
},
"$:/language/Buttons/Bold/Caption": {
"title": "$:/language/Buttons/Bold/Caption",
"text": "bold"
},
"$:/language/Buttons/Bold/Hint": {
"title": "$:/language/Buttons/Bold/Hint",
"text": "Apply bold formatting to selection"
},
"$:/language/Buttons/Clear/Caption": {
"title": "$:/language/Buttons/Clear/Caption",
"text": "clear"
},
"$:/language/Buttons/Clear/Hint": {
"title": "$:/language/Buttons/Clear/Hint",
"text": "Clear image to solid colour"
},
"$:/language/Buttons/EditorHeight/Caption": {
"title": "$:/language/Buttons/EditorHeight/Caption",
"text": "editor height"
},
"$:/language/Buttons/EditorHeight/Caption/Auto": {
"title": "$:/language/Buttons/EditorHeight/Caption/Auto",
"text": "Automatically adjust height to fit content"
},
"$:/language/Buttons/EditorHeight/Caption/Fixed": {
"title": "$:/language/Buttons/EditorHeight/Caption/Fixed",
"text": "Fixed height:"
},
"$:/language/Buttons/EditorHeight/Hint": {
"title": "$:/language/Buttons/EditorHeight/Hint",
"text": "Choose the height of the text editor"
},
"$:/language/Buttons/Excise/Caption": {
"title": "$:/language/Buttons/Excise/Caption",
"text": "excise"
},
"$:/language/Buttons/Excise/Caption/Excise": {
"title": "$:/language/Buttons/Excise/Caption/Excise",
"text": "Perform excision"
},
"$:/language/Buttons/Excise/Caption/MacroName": {
"title": "$:/language/Buttons/Excise/Caption/MacroName",
"text": "Macro name:"
},
"$:/language/Buttons/Excise/Caption/NewTitle": {
"title": "$:/language/Buttons/Excise/Caption/NewTitle",
"text": "Title of new tiddler:"
},
"$:/language/Buttons/Excise/Caption/Replace": {
"title": "$:/language/Buttons/Excise/Caption/Replace",
"text": "Replace excised text with:"
},
"$:/language/Buttons/Excise/Caption/Replace/Macro": {
"title": "$:/language/Buttons/Excise/Caption/Replace/Macro",
"text": "macro"
},
"$:/language/Buttons/Excise/Caption/Replace/Link": {
"title": "$:/language/Buttons/Excise/Caption/Replace/Link",
"text": "link"
},
"$:/language/Buttons/Excise/Caption/Replace/Transclusion": {
"title": "$:/language/Buttons/Excise/Caption/Replace/Transclusion",
"text": "transclusion"
},
"$:/language/Buttons/Excise/Caption/Tag": {
"title": "$:/language/Buttons/Excise/Caption/Tag",
"text": "Tag new tiddler with the title of this tiddler"
},
"$:/language/Buttons/Excise/Caption/TiddlerExists": {
"title": "$:/language/Buttons/Excise/Caption/TiddlerExists",
"text": "Warning: tiddler already exists"
},
"$:/language/Buttons/Excise/Hint": {
"title": "$:/language/Buttons/Excise/Hint",
"text": "Excise the selected text into a new tiddler"
},
"$:/language/Buttons/Heading1/Caption": {
"title": "$:/language/Buttons/Heading1/Caption",
"text": "heading 1"
},
"$:/language/Buttons/Heading1/Hint": {
"title": "$:/language/Buttons/Heading1/Hint",
"text": "Apply heading level 1 formatting to lines containing selection"
},
"$:/language/Buttons/Heading2/Caption": {
"title": "$:/language/Buttons/Heading2/Caption",
"text": "heading 2"
},
"$:/language/Buttons/Heading2/Hint": {
"title": "$:/language/Buttons/Heading2/Hint",
"text": "Apply heading level 2 formatting to lines containing selection"
},
"$:/language/Buttons/Heading3/Caption": {
"title": "$:/language/Buttons/Heading3/Caption",
"text": "heading 3"
},
"$:/language/Buttons/Heading3/Hint": {
"title": "$:/language/Buttons/Heading3/Hint",
"text": "Apply heading level 3 formatting to lines containing selection"
},
"$:/language/Buttons/Heading4/Caption": {
"title": "$:/language/Buttons/Heading4/Caption",
"text": "heading 4"
},
"$:/language/Buttons/Heading4/Hint": {
"title": "$:/language/Buttons/Heading4/Hint",
"text": "Apply heading level 4 formatting to lines containing selection"
},
"$:/language/Buttons/Heading5/Caption": {
"title": "$:/language/Buttons/Heading5/Caption",
"text": "heading 5"
},
"$:/language/Buttons/Heading5/Hint": {
"title": "$:/language/Buttons/Heading5/Hint",
"text": "Apply heading level 5 formatting to lines containing selection"
},
"$:/language/Buttons/Heading6/Caption": {
"title": "$:/language/Buttons/Heading6/Caption",
"text": "heading 6"
},
"$:/language/Buttons/Heading6/Hint": {
"title": "$:/language/Buttons/Heading6/Hint",
"text": "Apply heading level 6 formatting to lines containing selection"
},
"$:/language/Buttons/Italic/Caption": {
"title": "$:/language/Buttons/Italic/Caption",
"text": "italic"
},
"$:/language/Buttons/Italic/Hint": {
"title": "$:/language/Buttons/Italic/Hint",
"text": "Apply italic formatting to selection"
},
"$:/language/Buttons/LineWidth/Caption": {
"title": "$:/language/Buttons/LineWidth/Caption",
"text": "line width"
},
"$:/language/Buttons/LineWidth/Hint": {
"title": "$:/language/Buttons/LineWidth/Hint",
"text": "Set line width for painting"
},
"$:/language/Buttons/Link/Caption": {
"title": "$:/language/Buttons/Link/Caption",
"text": "link"
},
"$:/language/Buttons/Link/Hint": {
"title": "$:/language/Buttons/Link/Hint",
"text": "Create wikitext link"
},
"$:/language/Buttons/ListBullet/Caption": {
"title": "$:/language/Buttons/ListBullet/Caption",
"text": "bulleted list"
},
"$:/language/Buttons/ListBullet/Hint": {
"title": "$:/language/Buttons/ListBullet/Hint",
"text": "Apply bulleted list formatting to lines containing selection"
},
"$:/language/Buttons/ListNumber/Caption": {
"title": "$:/language/Buttons/ListNumber/Caption",
"text": "numbered list"
},
"$:/language/Buttons/ListNumber/Hint": {
"title": "$:/language/Buttons/ListNumber/Hint",
"text": "Apply numbered list formatting to lines containing selection"
},
"$:/language/Buttons/MonoBlock/Caption": {
"title": "$:/language/Buttons/MonoBlock/Caption",
"text": "monospaced block"
},
"$:/language/Buttons/MonoBlock/Hint": {
"title": "$:/language/Buttons/MonoBlock/Hint",
"text": "Apply monospaced block formatting to lines containing selection"
},
"$:/language/Buttons/MonoLine/Caption": {
"title": "$:/language/Buttons/MonoLine/Caption",
"text": "monospaced"
},
"$:/language/Buttons/MonoLine/Hint": {
"title": "$:/language/Buttons/MonoLine/Hint",
"text": "Apply monospaced character formatting to selection"
},
"$:/language/Buttons/Opacity/Caption": {
"title": "$:/language/Buttons/Opacity/Caption",
"text": "opacity"
},
"$:/language/Buttons/Opacity/Hint": {
"title": "$:/language/Buttons/Opacity/Hint",
"text": "Set painting opacity"
},
"$:/language/Buttons/Paint/Caption": {
"title": "$:/language/Buttons/Paint/Caption",
"text": "paint colour"
},
"$:/language/Buttons/Paint/Hint": {
"title": "$:/language/Buttons/Paint/Hint",
"text": "Set painting colour"
},
"$:/language/Buttons/Picture/Caption": {
"title": "$:/language/Buttons/Picture/Caption",
"text": "picture"
},
"$:/language/Buttons/Picture/Hint": {
"title": "$:/language/Buttons/Picture/Hint",
"text": "Insert picture"
},
"$:/language/Buttons/Preview/Caption": {
"title": "$:/language/Buttons/Preview/Caption",
"text": "preview"
},
"$:/language/Buttons/Preview/Hint": {
"title": "$:/language/Buttons/Preview/Hint",
"text": "Show preview pane"
},
"$:/language/Buttons/PreviewType/Caption": {
"title": "$:/language/Buttons/PreviewType/Caption",
"text": "preview type"
},
"$:/language/Buttons/PreviewType/Hint": {
"title": "$:/language/Buttons/PreviewType/Hint",
"text": "Choose preview type"
},
"$:/language/Buttons/Quote/Caption": {
"title": "$:/language/Buttons/Quote/Caption",
"text": "quote"
},
"$:/language/Buttons/Quote/Hint": {
"title": "$:/language/Buttons/Quote/Hint",
"text": "Apply quoted text formatting to lines containing selection"
},
"$:/language/Buttons/Size/Caption": {
"title": "$:/language/Buttons/Size/Caption",
"text": "image size"
},
"$:/language/Buttons/Size/Caption/Height": {
"title": "$:/language/Buttons/Size/Caption/Height",
"text": "Height:"
},
"$:/language/Buttons/Size/Caption/Resize": {
"title": "$:/language/Buttons/Size/Caption/Resize",
"text": "Resize image"
},
"$:/language/Buttons/Size/Caption/Width": {
"title": "$:/language/Buttons/Size/Caption/Width",
"text": "Width:"
},
"$:/language/Buttons/Size/Hint": {
"title": "$:/language/Buttons/Size/Hint",
"text": "Set image size"
},
"$:/language/Buttons/Stamp/Caption": {
"title": "$:/language/Buttons/Stamp/Caption",
"text": "stamp"
},
"$:/language/Buttons/Stamp/Caption/New": {
"title": "$:/language/Buttons/Stamp/Caption/New",
"text": "Add your own"
},
"$:/language/Buttons/Stamp/Hint": {
"title": "$:/language/Buttons/Stamp/Hint",
"text": "Insert a preconfigured snippet of text"
},
"$:/language/Buttons/Stamp/New/Title": {
"title": "$:/language/Buttons/Stamp/New/Title",
"text": "Name as shown in menu"
},
"$:/language/Buttons/Stamp/New/Text": {
"title": "$:/language/Buttons/Stamp/New/Text",
"text": "Text of snippet. (Remember to add a descriptive title in the caption field)."
},
"$:/language/Buttons/Strikethrough/Caption": {
"title": "$:/language/Buttons/Strikethrough/Caption",
"text": "strikethrough"
},
"$:/language/Buttons/Strikethrough/Hint": {
"title": "$:/language/Buttons/Strikethrough/Hint",
"text": "Apply strikethrough formatting to selection"
},
"$:/language/Buttons/Subscript/Caption": {
"title": "$:/language/Buttons/Subscript/Caption",
"text": "subscript"
},
"$:/language/Buttons/Subscript/Hint": {
"title": "$:/language/Buttons/Subscript/Hint",
"text": "Apply subscript formatting to selection"
},
"$:/language/Buttons/Superscript/Caption": {
"title": "$:/language/Buttons/Superscript/Caption",
"text": "superscript"
},
"$:/language/Buttons/Superscript/Hint": {
"title": "$:/language/Buttons/Superscript/Hint",
"text": "Apply superscript formatting to selection"
},
"$:/language/Buttons/Underline/Caption": {
"title": "$:/language/Buttons/Underline/Caption",
"text": "underline"
},
"$:/language/Buttons/Underline/Hint": {
"title": "$:/language/Buttons/Underline/Hint",
"text": "Apply underline formatting to selection"
},
"$:/language/ControlPanel/Advanced/Caption": {
"title": "$:/language/ControlPanel/Advanced/Caption",
"text": "Advanced"
},
"$:/language/ControlPanel/Advanced/Hint": {
"title": "$:/language/ControlPanel/Advanced/Hint",
"text": "Internal information about this TiddlyWiki"
},
"$:/language/ControlPanel/Appearance/Caption": {
"title": "$:/language/ControlPanel/Appearance/Caption",
"text": "Appearance"
},
"$:/language/ControlPanel/Appearance/Hint": {
"title": "$:/language/ControlPanel/Appearance/Hint",
"text": "Ways to customise the appearance of your TiddlyWiki."
},
"$:/language/ControlPanel/Basics/AnimDuration/Prompt": {
"title": "$:/language/ControlPanel/Basics/AnimDuration/Prompt",
"text": "Animation duration:"
},
"$:/language/ControlPanel/Basics/Caption": {
"title": "$:/language/ControlPanel/Basics/Caption",
"text": "Basics"
},
"$:/language/ControlPanel/Basics/DefaultTiddlers/BottomHint": {
"title": "$:/language/ControlPanel/Basics/DefaultTiddlers/BottomHint",
"text": "Use [[double square brackets]] for titles with spaces. Or you can choose to <$button set=\"$:/DefaultTiddlers\" setTo=\"[list[$:/StoryList]]\">retain story ordering</$button>"
},
"$:/language/ControlPanel/Basics/DefaultTiddlers/Prompt": {
"title": "$:/language/ControlPanel/Basics/DefaultTiddlers/Prompt",
"text": "Default tiddlers:"
},
"$:/language/ControlPanel/Basics/DefaultTiddlers/TopHint": {
"title": "$:/language/ControlPanel/Basics/DefaultTiddlers/TopHint",
"text": "Choose which tiddlers are displayed at startup:"
},
"$:/language/ControlPanel/Basics/Language/Prompt": {
"title": "$:/language/ControlPanel/Basics/Language/Prompt",
"text": "Hello! Current language:"
},
"$:/language/ControlPanel/Basics/NewJournal/Title/Prompt": {
"title": "$:/language/ControlPanel/Basics/NewJournal/Title/Prompt",
"text": "Title of new journal tiddlers"
},
"$:/language/ControlPanel/Basics/NewJournal/Tags/Prompt": {
"title": "$:/language/ControlPanel/Basics/NewJournal/Tags/Prompt",
"text": "Tags for new journal tiddlers"
},
"$:/language/ControlPanel/Basics/OverriddenShadowTiddlers/Prompt": {
"title": "$:/language/ControlPanel/Basics/OverriddenShadowTiddlers/Prompt",
"text": "Number of overridden shadow tiddlers:"
},
"$:/language/ControlPanel/Basics/ShadowTiddlers/Prompt": {
"title": "$:/language/ControlPanel/Basics/ShadowTiddlers/Prompt",
"text": "Number of shadow tiddlers:"
},
"$:/language/ControlPanel/Basics/Subtitle/Prompt": {
"title": "$:/language/ControlPanel/Basics/Subtitle/Prompt",
"text": "Subtitle:"
},
"$:/language/ControlPanel/Basics/SystemTiddlers/Prompt": {
"title": "$:/language/ControlPanel/Basics/SystemTiddlers/Prompt",
"text": "Number of system tiddlers:"
},
"$:/language/ControlPanel/Basics/Tags/Prompt": {
"title": "$:/language/ControlPanel/Basics/Tags/Prompt",
"text": "Number of tags:"
},
"$:/language/ControlPanel/Basics/Tiddlers/Prompt": {
"title": "$:/language/ControlPanel/Basics/Tiddlers/Prompt",
"text": "Number of tiddlers:"
},
"$:/language/ControlPanel/Basics/Title/Prompt": {
"title": "$:/language/ControlPanel/Basics/Title/Prompt",
"text": "Title of this ~TiddlyWiki:"
},
"$:/language/ControlPanel/Basics/Username/Prompt": {
"title": "$:/language/ControlPanel/Basics/Username/Prompt",
"text": "Username for signing edits:"
},
"$:/language/ControlPanel/Basics/Version/Prompt": {
"title": "$:/language/ControlPanel/Basics/Version/Prompt",
"text": "~TiddlyWiki version:"
},
"$:/language/ControlPanel/EditorTypes/Caption": {
"title": "$:/language/ControlPanel/EditorTypes/Caption",
"text": "Editor Types"
},
"$:/language/ControlPanel/EditorTypes/Editor/Caption": {
"title": "$:/language/ControlPanel/EditorTypes/Editor/Caption",
"text": "Editor"
},
"$:/language/ControlPanel/EditorTypes/Hint": {
"title": "$:/language/ControlPanel/EditorTypes/Hint",
"text": "These tiddlers determine which editor is used to edit specific tiddler types."
},
"$:/language/ControlPanel/EditorTypes/Type/Caption": {
"title": "$:/language/ControlPanel/EditorTypes/Type/Caption",
"text": "Type"
},
"$:/language/ControlPanel/Info/Caption": {
"title": "$:/language/ControlPanel/Info/Caption",
"text": "Info"
},
"$:/language/ControlPanel/Info/Hint": {
"title": "$:/language/ControlPanel/Info/Hint",
"text": "Information about this TiddlyWiki"
},
"$:/language/ControlPanel/KeyboardShortcuts/Add/Prompt": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Add/Prompt",
"text": "Type shortcut here"
},
"$:/language/ControlPanel/KeyboardShortcuts/Add/Caption": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Add/Caption",
"text": "add shortcut"
},
"$:/language/ControlPanel/KeyboardShortcuts/Caption": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Caption",
"text": "Keyboard Shortcuts"
},
"$:/language/ControlPanel/KeyboardShortcuts/Hint": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Hint",
"text": "Manage keyboard shortcut assignments"
},
"$:/language/ControlPanel/KeyboardShortcuts/NoShortcuts/Caption": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/NoShortcuts/Caption",
"text": "No keyboard shortcuts assigned"
},
"$:/language/ControlPanel/KeyboardShortcuts/Remove/Hint": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Remove/Hint",
"text": "remove keyboard shortcut"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/All": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/All",
"text": "All platforms"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/Mac": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/Mac",
"text": "Macintosh platform only"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/NonMac": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/NonMac",
"text": "Non-Macintosh platforms only"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/Linux": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/Linux",
"text": "Linux platform only"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/NonLinux": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/NonLinux",
"text": "Non-Linux platforms only"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/Windows": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/Windows",
"text": "Windows platform only"
},
"$:/language/ControlPanel/KeyboardShortcuts/Platform/NonWindows": {
"title": "$:/language/ControlPanel/KeyboardShortcuts/Platform/NonWindows",
"text": "Non-Windows platforms only"
},
"$:/language/ControlPanel/LoadedModules/Caption": {
"title": "$:/language/ControlPanel/LoadedModules/Caption",
"text": "Loaded Modules"
},
"$:/language/ControlPanel/LoadedModules/Hint": {
"title": "$:/language/ControlPanel/LoadedModules/Hint",
"text": "These are the currently loaded tiddler modules linked to their source tiddlers. Any italicised modules lack a source tiddler, typically because they were setup during the boot process."
},
"$:/language/ControlPanel/Palette/Caption": {
"title": "$:/language/ControlPanel/Palette/Caption",
"text": "Palette"
},
"$:/language/ControlPanel/Palette/Editor/Clone/Caption": {
"title": "$:/language/ControlPanel/Palette/Editor/Clone/Caption",
"text": "clone"
},
"$:/language/ControlPanel/Palette/Editor/Clone/Prompt": {
"title": "$:/language/ControlPanel/Palette/Editor/Clone/Prompt",
"text": "It is recommended that you clone this shadow palette before editing it"
},
"$:/language/ControlPanel/Palette/Editor/Prompt/Modified": {
"title": "$:/language/ControlPanel/Palette/Editor/Prompt/Modified",
"text": "This shadow palette has been modified"
},
"$:/language/ControlPanel/Palette/Editor/Prompt": {
"title": "$:/language/ControlPanel/Palette/Editor/Prompt",
"text": "Editing"
},
"$:/language/ControlPanel/Palette/Editor/Reset/Caption": {
"title": "$:/language/ControlPanel/Palette/Editor/Reset/Caption",
"text": "reset"
},
"$:/language/ControlPanel/Palette/HideEditor/Caption": {
"title": "$:/language/ControlPanel/Palette/HideEditor/Caption",
"text": "hide editor"
},
"$:/language/ControlPanel/Palette/Prompt": {
"title": "$:/language/ControlPanel/Palette/Prompt",
"text": "Current palette:"
},
"$:/language/ControlPanel/Palette/ShowEditor/Caption": {
"title": "$:/language/ControlPanel/Palette/ShowEditor/Caption",
"text": "show editor"
},
"$:/language/ControlPanel/Parsing/Caption": {
"title": "$:/language/ControlPanel/Parsing/Caption",
"text": "Parsing"
},
"$:/language/ControlPanel/Parsing/Hint": {
"title": "$:/language/ControlPanel/Parsing/Hint",
"text": "Here you can globally disable individual wiki parser rules. Take care as disabling some parser rules can prevent ~TiddlyWiki functioning correctly (you can restore normal operation with [[safe mode|http://tiddlywiki.com/#SafeMode]] )"
},
"$:/language/ControlPanel/Parsing/Block/Caption": {
"title": "$:/language/ControlPanel/Parsing/Block/Caption",
"text": "Block Parse Rules"
},
"$:/language/ControlPanel/Parsing/Inline/Caption": {
"title": "$:/language/ControlPanel/Parsing/Inline/Caption",
"text": "Inline Parse Rules"
},
"$:/language/ControlPanel/Parsing/Pragma/Caption": {
"title": "$:/language/ControlPanel/Parsing/Pragma/Caption",
"text": "Pragma Parse Rules"
},
"$:/language/ControlPanel/Plugins/Add/Caption": {
"title": "$:/language/ControlPanel/Plugins/Add/Caption",
"text": "Get more plugins"
},
"$:/language/ControlPanel/Plugins/Add/Hint": {
"title": "$:/language/ControlPanel/Plugins/Add/Hint",
"text": "Install plugins from the official library"
},
"$:/language/ControlPanel/Plugins/AlreadyInstalled/Hint": {
"title": "$:/language/ControlPanel/Plugins/AlreadyInstalled/Hint",
"text": "This plugin is already installed at version <$text text=<<installedVersion>>/>"
},
"$:/language/ControlPanel/Plugins/Caption": {
"title": "$:/language/ControlPanel/Plugins/Caption",
"text": "Plugins"
},
"$:/language/ControlPanel/Plugins/Disable/Caption": {
"title": "$:/language/ControlPanel/Plugins/Disable/Caption",
"text": "disable"
},
"$:/language/ControlPanel/Plugins/Disable/Hint": {
"title": "$:/language/ControlPanel/Plugins/Disable/Hint",
"text": "Disable this plugin when reloading page"
},
"$:/language/ControlPanel/Plugins/Disabled/Status": {
"title": "$:/language/ControlPanel/Plugins/Disabled/Status",
"text": "(disabled)"
},
"$:/language/ControlPanel/Plugins/Empty/Hint": {
"title": "$:/language/ControlPanel/Plugins/Empty/Hint",
"text": "None"
},
"$:/language/ControlPanel/Plugins/Enable/Caption": {
"title": "$:/language/ControlPanel/Plugins/Enable/Caption",
"text": "enable"
},
"$:/language/ControlPanel/Plugins/Enable/Hint": {
"title": "$:/language/ControlPanel/Plugins/Enable/Hint",
"text": "Enable this plugin when reloading page"
},
"$:/language/ControlPanel/Plugins/Install/Caption": {
"title": "$:/language/ControlPanel/Plugins/Install/Caption",
"text": "install"
},
"$:/language/ControlPanel/Plugins/Installed/Hint": {
"title": "$:/language/ControlPanel/Plugins/Installed/Hint",
"text": "Currently installed plugins:"
},
"$:/language/ControlPanel/Plugins/Languages/Caption": {
"title": "$:/language/ControlPanel/Plugins/Languages/Caption",
"text": "Languages"
},
"$:/language/ControlPanel/Plugins/Languages/Hint": {
"title": "$:/language/ControlPanel/Plugins/Languages/Hint",
"text": "Language pack plugins"
},
"$:/language/ControlPanel/Plugins/NoInfoFound/Hint": {
"title": "$:/language/ControlPanel/Plugins/NoInfoFound/Hint",
"text": "No ''\"<$text text=<<currentTab>>/>\"'' found"
},
"$:/language/ControlPanel/Plugins/NoInformation/Hint": {
"title": "$:/language/ControlPanel/Plugins/NoInformation/Hint",
"text": "No information provided"
},
"$:/language/ControlPanel/Plugins/NotInstalled/Hint": {
"title": "$:/language/ControlPanel/Plugins/NotInstalled/Hint",
"text": "This plugin is not currently installed"
},
"$:/language/ControlPanel/Plugins/OpenPluginLibrary": {
"title": "$:/language/ControlPanel/Plugins/OpenPluginLibrary",
"text": "open plugin library"
},
"$:/language/ControlPanel/Plugins/Plugins/Caption": {
"title": "$:/language/ControlPanel/Plugins/Plugins/Caption",
"text": "Plugins"
},
"$:/language/ControlPanel/Plugins/Plugins/Hint": {
"title": "$:/language/ControlPanel/Plugins/Plugins/Hint",
"text": "Plugins"
},
"$:/language/ControlPanel/Plugins/Reinstall/Caption": {
"title": "$:/language/ControlPanel/Plugins/Reinstall/Caption",
"text": "reinstall"
},
"$:/language/ControlPanel/Plugins/Themes/Caption": {
"title": "$:/language/ControlPanel/Plugins/Themes/Caption",
"text": "Themes"
},
"$:/language/ControlPanel/Plugins/Themes/Hint": {
"title": "$:/language/ControlPanel/Plugins/Themes/Hint",
"text": "Theme plugins"
},
"$:/language/ControlPanel/Saving/Caption": {
"title": "$:/language/ControlPanel/Saving/Caption",
"text": "Saving"
},
"$:/language/ControlPanel/Saving/Heading": {
"title": "$:/language/ControlPanel/Saving/Heading",
"text": "Saving"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Advanced/Heading": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Advanced/Heading",
"text": "Advanced Settings"
},
"$:/language/ControlPanel/Saving/TiddlySpot/BackupDir": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/BackupDir",
"text": "Backup Directory"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Backups": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Backups",
"text": "Backups"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Description": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Description",
"text": "These settings are only used when saving to http://tiddlyspot.com or a compatible remote server"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Filename": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Filename",
"text": "Upload Filename"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Heading": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Heading",
"text": "~TiddlySpot"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Hint": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Hint",
"text": "//The server URL defaults to `http://<wikiname>.tiddlyspot.com/store.cgi` and can be changed to use a custom server address, e.g. `http://example.com/store.php`.//"
},
"$:/language/ControlPanel/Saving/TiddlySpot/Password": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/Password",
"text": "Password"
},
"$:/language/ControlPanel/Saving/TiddlySpot/ServerURL": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/ServerURL",
"text": "Server URL"
},
"$:/language/ControlPanel/Saving/TiddlySpot/UploadDir": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/UploadDir",
"text": "Upload Directory"
},
"$:/language/ControlPanel/Saving/TiddlySpot/UserName": {
"title": "$:/language/ControlPanel/Saving/TiddlySpot/UserName",
"text": "Wiki Name"
},
"$:/language/ControlPanel/Settings/AutoSave/Caption": {
"title": "$:/language/ControlPanel/Settings/AutoSave/Caption",
"text": "Autosave"
},
"$:/language/ControlPanel/Settings/AutoSave/Disabled/Description": {
"title": "$:/language/ControlPanel/Settings/AutoSave/Disabled/Description",
"text": "Do not save changes automatically"
},
"$:/language/ControlPanel/Settings/AutoSave/Enabled/Description": {
"title": "$:/language/ControlPanel/Settings/AutoSave/Enabled/Description",
"text": "Save changes automatically"
},
"$:/language/ControlPanel/Settings/AutoSave/Hint": {
"title": "$:/language/ControlPanel/Settings/AutoSave/Hint",
"text": "Automatically save changes during editing"
},
"$:/language/ControlPanel/Settings/CamelCase/Caption": {
"title": "$:/language/ControlPanel/Settings/CamelCase/Caption",
"text": "Camel Case Wiki Links"
},
"$:/language/ControlPanel/Settings/CamelCase/Hint": {
"title": "$:/language/ControlPanel/Settings/CamelCase/Hint",
"text": "You can globally disable automatic linking of ~CamelCase phrases. Requires reload to take effect"
},
"$:/language/ControlPanel/Settings/CamelCase/Description": {
"title": "$:/language/ControlPanel/Settings/CamelCase/Description",
"text": "Enable automatic ~CamelCase linking"
},
"$:/language/ControlPanel/Settings/Caption": {
"title": "$:/language/ControlPanel/Settings/Caption",
"text": "Settings"
},
"$:/language/ControlPanel/Settings/EditorToolbar/Caption": {
"title": "$:/language/ControlPanel/Settings/EditorToolbar/Caption",
"text": "Editor Toolbar"
},
"$:/language/ControlPanel/Settings/EditorToolbar/Hint": {
"title": "$:/language/ControlPanel/Settings/EditorToolbar/Hint",
"text": "Enable or disable the editor toolbar:"
},
"$:/language/ControlPanel/Settings/EditorToolbar/Description": {
"title": "$:/language/ControlPanel/Settings/EditorToolbar/Description",
"text": "Show editor toolbar"
},
"$:/language/ControlPanel/Settings/Hint": {
"title": "$:/language/ControlPanel/Settings/Hint",
"text": "These settings let you customise the behaviour of TiddlyWiki."
},
"$:/language/ControlPanel/Settings/NavigationAddressBar/Caption": {
"title": "$:/language/ControlPanel/Settings/NavigationAddressBar/Caption",
"text": "Navigation Address Bar"
},
"$:/language/ControlPanel/Settings/NavigationAddressBar/Hint": {
"title": "$:/language/ControlPanel/Settings/NavigationAddressBar/Hint",
"text": "Behaviour of the browser address bar when navigating to a tiddler:"
},
"$:/language/ControlPanel/Settings/NavigationAddressBar/No/Description": {
"title": "$:/language/ControlPanel/Settings/NavigationAddressBar/No/Description",
"text": "Do not update the address bar"
},
"$:/language/ControlPanel/Settings/NavigationAddressBar/Permalink/Description": {
"title": "$:/language/ControlPanel/Settings/NavigationAddressBar/Permalink/Description",
"text": "Include the target tiddler"
},
"$:/language/ControlPanel/Settings/NavigationAddressBar/Permaview/Description": {
"title": "$:/language/ControlPanel/Settings/NavigationAddressBar/Permaview/Description",
"text": "Include the target tiddler and the current story sequence"
},
"$:/language/ControlPanel/Settings/NavigationHistory/Caption": {
"title": "$:/language/ControlPanel/Settings/NavigationHistory/Caption",
"text": "Navigation History"
},
"$:/language/ControlPanel/Settings/NavigationHistory/Hint": {
"title": "$:/language/ControlPanel/Settings/NavigationHistory/Hint",
"text": "Update browser history when navigating to a tiddler:"
},
"$:/language/ControlPanel/Settings/NavigationHistory/No/Description": {
"title": "$:/language/ControlPanel/Settings/NavigationHistory/No/Description",
"text": "Do not update history"
},
"$:/language/ControlPanel/Settings/NavigationHistory/Yes/Description": {
"title": "$:/language/ControlPanel/Settings/NavigationHistory/Yes/Description",
"text": "Update history"
},
"$:/language/ControlPanel/Settings/PerformanceInstrumentation/Caption": {
"title": "$:/language/ControlPanel/Settings/PerformanceInstrumentation/Caption",
"text": "Performance Instrumentation"
},
"$:/language/ControlPanel/Settings/PerformanceInstrumentation/Hint": {
"title": "$:/language/ControlPanel/Settings/PerformanceInstrumentation/Hint",
"text": "Displays performance statistics in the browser developer console. Requires reload to take effect"
},
"$:/language/ControlPanel/Settings/PerformanceInstrumentation/Description": {
"title": "$:/language/ControlPanel/Settings/PerformanceInstrumentation/Description",
"text": "Enable performance instrumentation"
},
"$:/language/ControlPanel/Settings/ToolbarButtonStyle/Caption": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtonStyle/Caption",
"text": "Toolbar Button Style"
},
"$:/language/ControlPanel/Settings/ToolbarButtonStyle/Hint": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtonStyle/Hint",
"text": "Choose the style for toolbar buttons:"
},
"$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Borderless": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Borderless",
"text": "Borderless"
},
"$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Boxed": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Boxed",
"text": "Boxed"
},
"$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Rounded": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Rounded",
"text": "Rounded"
},
"$:/language/ControlPanel/Settings/ToolbarButtons/Caption": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtons/Caption",
"text": "Toolbar Buttons"
},
"$:/language/ControlPanel/Settings/ToolbarButtons/Hint": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtons/Hint",
"text": "Default toolbar button appearance:"
},
"$:/language/ControlPanel/Settings/ToolbarButtons/Icons/Description": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtons/Icons/Description",
"text": "Include icon"
},
"$:/language/ControlPanel/Settings/ToolbarButtons/Text/Description": {
"title": "$:/language/ControlPanel/Settings/ToolbarButtons/Text/Description",
"text": "Include text"
},
"$:/language/ControlPanel/Settings/DefaultSidebarTab/Caption": {
"title": "$:/language/ControlPanel/Settings/DefaultSidebarTab/Caption",
"text": "Default Sidebar Tab"
},
"$:/language/ControlPanel/Settings/DefaultSidebarTab/Hint": {
"title": "$:/language/ControlPanel/Settings/DefaultSidebarTab/Hint",
"text": "Specify which sidebar tab is displayed by default"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/Caption": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/Caption",
"text": "Tiddler Opening Behaviour"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/InsideRiver/Hint": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/InsideRiver/Hint",
"text": "Navigation from //within// the story river"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/OutsideRiver/Hint": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/OutsideRiver/Hint",
"text": "Navigation from //outside// the story river"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAbove": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAbove",
"text": "Open above the current tiddler"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/OpenBelow": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/OpenBelow",
"text": "Open below the current tiddler"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAtTop": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAtTop",
"text": "Open at the top of the story river"
},
"$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAtBottom": {
"title": "$:/language/ControlPanel/Settings/LinkToBehaviour/OpenAtBottom",
"text": "Open at the bottom of the story river"
},
"$:/language/ControlPanel/Settings/TitleLinks/Caption": {
"title": "$:/language/ControlPanel/Settings/TitleLinks/Caption",
"text": "Tiddler Titles"
},
"$:/language/ControlPanel/Settings/TitleLinks/Hint": {
"title": "$:/language/ControlPanel/Settings/TitleLinks/Hint",
"text": "Optionally display tiddler titles as links"
},
"$:/language/ControlPanel/Settings/TitleLinks/No/Description": {
"title": "$:/language/ControlPanel/Settings/TitleLinks/No/Description",
"text": "Do not display tiddler titles as links"
},
"$:/language/ControlPanel/Settings/TitleLinks/Yes/Description": {
"title": "$:/language/ControlPanel/Settings/TitleLinks/Yes/Description",
"text": "Display tiddler titles as links"
},
"$:/language/ControlPanel/Settings/MissingLinks/Caption": {
"title": "$:/language/ControlPanel/Settings/MissingLinks/Caption",
"text": "Wiki Links"
},
"$:/language/ControlPanel/Settings/MissingLinks/Hint": {
"title": "$:/language/ControlPanel/Settings/MissingLinks/Hint",
"text": "Choose whether to link to tiddlers that do not exist yet"
},
"$:/language/ControlPanel/Settings/MissingLinks/Description": {
"title": "$:/language/ControlPanel/Settings/MissingLinks/Description",
"text": "Enable links to missing tiddlers"
},
"$:/language/ControlPanel/StoryView/Caption": {
"title": "$:/language/ControlPanel/StoryView/Caption",
"text": "Story View"
},
"$:/language/ControlPanel/StoryView/Prompt": {
"title": "$:/language/ControlPanel/StoryView/Prompt",
"text": "Current view:"
},
"$:/language/ControlPanel/Theme/Caption": {
"title": "$:/language/ControlPanel/Theme/Caption",
"text": "Theme"
},
"$:/language/ControlPanel/Theme/Prompt": {
"title": "$:/language/ControlPanel/Theme/Prompt",
"text": "Current theme:"
},
"$:/language/ControlPanel/TiddlerFields/Caption": {
"title": "$:/language/ControlPanel/TiddlerFields/Caption",
"text": "Tiddler Fields"
},
"$:/language/ControlPanel/TiddlerFields/Hint": {
"title": "$:/language/ControlPanel/TiddlerFields/Hint",
"text": "This is the full set of TiddlerFields in use in this wiki (including system tiddlers but excluding shadow tiddlers)."
},
"$:/language/ControlPanel/Toolbars/Caption": {
"title": "$:/language/ControlPanel/Toolbars/Caption",
"text": "Toolbars"
},
"$:/language/ControlPanel/Toolbars/EditToolbar/Caption": {
"title": "$:/language/ControlPanel/Toolbars/EditToolbar/Caption",
"text": "Edit Toolbar"
},
"$:/language/ControlPanel/Toolbars/EditToolbar/Hint": {
"title": "$:/language/ControlPanel/Toolbars/EditToolbar/Hint",
"text": "Choose which buttons are displayed for tiddlers in edit mode"
},
"$:/language/ControlPanel/Toolbars/Hint": {
"title": "$:/language/ControlPanel/Toolbars/Hint",
"text": "Select which toolbar buttons are displayed"
},
"$:/language/ControlPanel/Toolbars/PageControls/Caption": {
"title": "$:/language/ControlPanel/Toolbars/PageControls/Caption",
"text": "Page Toolbar"
},
"$:/language/ControlPanel/Toolbars/PageControls/Hint": {
"title": "$:/language/ControlPanel/Toolbars/PageControls/Hint",
"text": "Choose which buttons are displayed on the main page toolbar"
},
"$:/language/ControlPanel/Toolbars/EditorToolbar/Caption": {
"title": "$:/language/ControlPanel/Toolbars/EditorToolbar/Caption",
"text": "Editor Toolbar"
},
"$:/language/ControlPanel/Toolbars/EditorToolbar/Hint": {
"title": "$:/language/ControlPanel/Toolbars/EditorToolbar/Hint",
"text": "Choose which buttons are displayed in the editor toolbar. Note that some buttons will only appear when editing tiddlers of a certain type"
},
"$:/language/ControlPanel/Toolbars/ViewToolbar/Caption": {
"title": "$:/language/ControlPanel/Toolbars/ViewToolbar/Caption",
"text": "View Toolbar"
},
"$:/language/ControlPanel/Toolbars/ViewToolbar/Hint": {
"title": "$:/language/ControlPanel/Toolbars/ViewToolbar/Hint",
"text": "Choose which buttons are displayed for tiddlers in view mode"
},
"$:/language/ControlPanel/Tools/Download/Full/Caption": {
"title": "$:/language/ControlPanel/Tools/Download/Full/Caption",
"text": "Download full wiki"
},
"$:/language/Date/DaySuffix/1": {
"title": "$:/language/Date/DaySuffix/1",
"text": "st"
},
"$:/language/Date/DaySuffix/2": {
"title": "$:/language/Date/DaySuffix/2",
"text": "nd"
},
"$:/language/Date/DaySuffix/3": {
"title": "$:/language/Date/DaySuffix/3",
"text": "rd"
},
"$:/language/Date/DaySuffix/4": {
"title": "$:/language/Date/DaySuffix/4",
"text": "th"
},
"$:/language/Date/DaySuffix/5": {
"title": "$:/language/Date/DaySuffix/5",
"text": "th"
},
"$:/language/Date/DaySuffix/6": {
"title": "$:/language/Date/DaySuffix/6",
"text": "th"
},
"$:/language/Date/DaySuffix/7": {
"title": "$:/language/Date/DaySuffix/7",
"text": "th"
},
"$:/language/Date/DaySuffix/8": {
"title": "$:/language/Date/DaySuffix/8",
"text": "th"
},
"$:/language/Date/DaySuffix/9": {
"title": "$:/language/Date/DaySuffix/9",
"text": "th"
},
"$:/language/Date/DaySuffix/10": {
"title": "$:/language/Date/DaySuffix/10",
"text": "th"
},
"$:/language/Date/DaySuffix/11": {
"title": "$:/language/Date/DaySuffix/11",
"text": "th"
},
"$:/language/Date/DaySuffix/12": {
"title": "$:/language/Date/DaySuffix/12",
"text": "th"
},
"$:/language/Date/DaySuffix/13": {
"title": "$:/language/Date/DaySuffix/13",
"text": "th"
},
"$:/language/Date/DaySuffix/14": {
"title": "$:/language/Date/DaySuffix/14",
"text": "th"
},
"$:/language/Date/DaySuffix/15": {
"title": "$:/language/Date/DaySuffix/15",
"text": "th"
},
"$:/language/Date/DaySuffix/16": {
"title": "$:/language/Date/DaySuffix/16",
"text": "th"
},
"$:/language/Date/DaySuffix/17": {
"title": "$:/language/Date/DaySuffix/17",
"text": "th"
},
"$:/language/Date/DaySuffix/18": {
"title": "$:/language/Date/DaySuffix/18",
"text": "th"
},
"$:/language/Date/DaySuffix/19": {
"title": "$:/language/Date/DaySuffix/19",
"text": "th"
},
"$:/language/Date/DaySuffix/20": {
"title": "$:/language/Date/DaySuffix/20",
"text": "th"
},
"$:/language/Date/DaySuffix/21": {
"title": "$:/language/Date/DaySuffix/21",
"text": "st"
},
"$:/language/Date/DaySuffix/22": {
"title": "$:/language/Date/DaySuffix/22",
"text": "nd"
},
"$:/language/Date/DaySuffix/23": {
"title": "$:/language/Date/DaySuffix/23",
"text": "rd"
},
"$:/language/Date/DaySuffix/24": {
"title": "$:/language/Date/DaySuffix/24",
"text": "th"
},
"$:/language/Date/DaySuffix/25": {
"title": "$:/language/Date/DaySuffix/25",
"text": "th"
},
"$:/language/Date/DaySuffix/26": {
"title": "$:/language/Date/DaySuffix/26",
"text": "th"
},
"$:/language/Date/DaySuffix/27": {
"title": "$:/language/Date/DaySuffix/27",
"text": "th"
},
"$:/language/Date/DaySuffix/28": {
"title": "$:/language/Date/DaySuffix/28",
"text": "th"
},
"$:/language/Date/DaySuffix/29": {
"title": "$:/language/Date/DaySuffix/29",
"text": "th"
},
"$:/language/Date/DaySuffix/30": {
"title": "$:/language/Date/DaySuffix/30",
"text": "th"
},
"$:/language/Date/DaySuffix/31": {
"title": "$:/language/Date/DaySuffix/31",
"text": "st"
},
"$:/language/Date/Long/Day/0": {
"title": "$:/language/Date/Long/Day/0",
"text": "Sunday"
},
"$:/language/Date/Long/Day/1": {
"title": "$:/language/Date/Long/Day/1",
"text": "Monday"
},
"$:/language/Date/Long/Day/2": {
"title": "$:/language/Date/Long/Day/2",
"text": "Tuesday"
},
"$:/language/Date/Long/Day/3": {
"title": "$:/language/Date/Long/Day/3",
"text": "Wednesday"
},
"$:/language/Date/Long/Day/4": {
"title": "$:/language/Date/Long/Day/4",
"text": "Thursday"
},
"$:/language/Date/Long/Day/5": {
"title": "$:/language/Date/Long/Day/5",
"text": "Friday"
},
"$:/language/Date/Long/Day/6": {
"title": "$:/language/Date/Long/Day/6",
"text": "Saturday"
},
"$:/language/Date/Long/Month/1": {
"title": "$:/language/Date/Long/Month/1",
"text": "January"
},
"$:/language/Date/Long/Month/2": {
"title": "$:/language/Date/Long/Month/2",
"text": "February"
},
"$:/language/Date/Long/Month/3": {
"title": "$:/language/Date/Long/Month/3",
"text": "March"
},
"$:/language/Date/Long/Month/4": {
"title": "$:/language/Date/Long/Month/4",
"text": "April"
},
"$:/language/Date/Long/Month/5": {
"title": "$:/language/Date/Long/Month/5",
"text": "May"
},
"$:/language/Date/Long/Month/6": {
"title": "$:/language/Date/Long/Month/6",
"text": "June"
},
"$:/language/Date/Long/Month/7": {
"title": "$:/language/Date/Long/Month/7",
"text": "July"
},
"$:/language/Date/Long/Month/8": {
"title": "$:/language/Date/Long/Month/8",
"text": "August"
},
"$:/language/Date/Long/Month/9": {
"title": "$:/language/Date/Long/Month/9",
"text": "September"
},
"$:/language/Date/Long/Month/10": {
"title": "$:/language/Date/Long/Month/10",
"text": "October"
},
"$:/language/Date/Long/Month/11": {
"title": "$:/language/Date/Long/Month/11",
"text": "November"
},
"$:/language/Date/Long/Month/12": {
"title": "$:/language/Date/Long/Month/12",
"text": "December"
},
"$:/language/Date/Period/am": {
"title": "$:/language/Date/Period/am",
"text": "am"
},
"$:/language/Date/Period/pm": {
"title": "$:/language/Date/Period/pm",
"text": "pm"
},
"$:/language/Date/Short/Day/0": {
"title": "$:/language/Date/Short/Day/0",
"text": "Sun"
},
"$:/language/Date/Short/Day/1": {
"title": "$:/language/Date/Short/Day/1",
"text": "Mon"
},
"$:/language/Date/Short/Day/2": {
"title": "$:/language/Date/Short/Day/2",
"text": "Tue"
},
"$:/language/Date/Short/Day/3": {
"title": "$:/language/Date/Short/Day/3",
"text": "Wed"
},
"$:/language/Date/Short/Day/4": {
"title": "$:/language/Date/Short/Day/4",
"text": "Thu"
},
"$:/language/Date/Short/Day/5": {
"title": "$:/language/Date/Short/Day/5",
"text": "Fri"
},
"$:/language/Date/Short/Day/6": {
"title": "$:/language/Date/Short/Day/6",
"text": "Sat"
},
"$:/language/Date/Short/Month/1": {
"title": "$:/language/Date/Short/Month/1",
"text": "Jan"
},
"$:/language/Date/Short/Month/2": {
"title": "$:/language/Date/Short/Month/2",
"text": "Feb"
},
"$:/language/Date/Short/Month/3": {
"title": "$:/language/Date/Short/Month/3",
"text": "Mar"
},
"$:/language/Date/Short/Month/4": {
"title": "$:/language/Date/Short/Month/4",
"text": "Apr"
},
"$:/language/Date/Short/Month/5": {
"title": "$:/language/Date/Short/Month/5",
"text": "May"
},
"$:/language/Date/Short/Month/6": {
"title": "$:/language/Date/Short/Month/6",
"text": "Jun"
},
"$:/language/Date/Short/Month/7": {
"title": "$:/language/Date/Short/Month/7",
"text": "Jul"
},
"$:/language/Date/Short/Month/8": {
"title": "$:/language/Date/Short/Month/8",
"text": "Aug"
},
"$:/language/Date/Short/Month/9": {
"title": "$:/language/Date/Short/Month/9",
"text": "Sep"
},
"$:/language/Date/Short/Month/10": {
"title": "$:/language/Date/Short/Month/10",
"text": "Oct"
},
"$:/language/Date/Short/Month/11": {
"title": "$:/language/Date/Short/Month/11",
"text": "Nov"
},
"$:/language/Date/Short/Month/12": {
"title": "$:/language/Date/Short/Month/12",
"text": "Dec"
},
"$:/language/RelativeDate/Future/Days": {
"title": "$:/language/RelativeDate/Future/Days",
"text": "<<period>> days from now"
},
"$:/language/RelativeDate/Future/Hours": {
"title": "$:/language/RelativeDate/Future/Hours",
"text": "<<period>> hours from now"
},
"$:/language/RelativeDate/Future/Minutes": {
"title": "$:/language/RelativeDate/Future/Minutes",
"text": "<<period>> minutes from now"
},
"$:/language/RelativeDate/Future/Months": {
"title": "$:/language/RelativeDate/Future/Months",
"text": "<<period>> months from now"
},
"$:/language/RelativeDate/Future/Second": {
"title": "$:/language/RelativeDate/Future/Second",
"text": "1 second from now"
},
"$:/language/RelativeDate/Future/Seconds": {
"title": "$:/language/RelativeDate/Future/Seconds",
"text": "<<period>> seconds from now"
},
"$:/language/RelativeDate/Future/Years": {
"title": "$:/language/RelativeDate/Future/Years",
"text": "<<period>> years from now"
},
"$:/language/RelativeDate/Past/Days": {
"title": "$:/language/RelativeDate/Past/Days",
"text": "<<period>> days ago"
},
"$:/language/RelativeDate/Past/Hours": {
"title": "$:/language/RelativeDate/Past/Hours",
"text": "<<period>> hours ago"
},
"$:/language/RelativeDate/Past/Minutes": {
"title": "$:/language/RelativeDate/Past/Minutes",
"text": "<<period>> minutes ago"
},
"$:/language/RelativeDate/Past/Months": {
"title": "$:/language/RelativeDate/Past/Months",
"text": "<<period>> months ago"
},
"$:/language/RelativeDate/Past/Second": {
"title": "$:/language/RelativeDate/Past/Second",
"text": "1 second ago"
},
"$:/language/RelativeDate/Past/Seconds": {
"title": "$:/language/RelativeDate/Past/Seconds",
"text": "<<period>> seconds ago"
},
"$:/language/RelativeDate/Past/Years": {
"title": "$:/language/RelativeDate/Past/Years",
"text": "<<period>> years ago"
},
"$:/language/Docs/ModuleTypes/animation": {
"title": "$:/language/Docs/ModuleTypes/animation",
"text": "Animations that may be used with the RevealWidget."
},
"$:/language/Docs/ModuleTypes/command": {
"title": "$:/language/Docs/ModuleTypes/command",
"text": "Commands that can be executed under Node.js."
},
"$:/language/Docs/ModuleTypes/config": {
"title": "$:/language/Docs/ModuleTypes/config",
"text": "Data to be inserted into `$tw.config`."
},
"$:/language/Docs/ModuleTypes/filteroperator": {
"title": "$:/language/Docs/ModuleTypes/filteroperator",
"text": "Individual filter operator methods."
},
"$:/language/Docs/ModuleTypes/global": {
"title": "$:/language/Docs/ModuleTypes/global",
"text": "Global data to be inserted into `$tw`."
},
"$:/language/Docs/ModuleTypes/isfilteroperator": {
"title": "$:/language/Docs/ModuleTypes/isfilteroperator",
"text": "Operands for the ''is'' filter operator."
},
"$:/language/Docs/ModuleTypes/macro": {
"title": "$:/language/Docs/ModuleTypes/macro",
"text": "JavaScript macro definitions."
},
"$:/language/Docs/ModuleTypes/parser": {
"title": "$:/language/Docs/ModuleTypes/parser",
"text": "Parsers for different content types."
},
"$:/language/Docs/ModuleTypes/saver": {
"title": "$:/language/Docs/ModuleTypes/saver",
"text": "Savers handle different methods for saving files from the browser."
},
"$:/language/Docs/ModuleTypes/startup": {
"title": "$:/language/Docs/ModuleTypes/startup",
"text": "Startup functions."
},
"$:/language/Docs/ModuleTypes/storyview": {
"title": "$:/language/Docs/ModuleTypes/storyview",
"text": "Story views customise the animation and behaviour of list widgets."
},
"$:/language/Docs/ModuleTypes/tiddlerdeserializer": {
"title": "$:/language/Docs/ModuleTypes/tiddlerdeserializer",
"text": "Converts different content types into tiddlers."
},
"$:/language/Docs/ModuleTypes/tiddlerfield": {
"title": "$:/language/Docs/ModuleTypes/tiddlerfield",
"text": "Defines the behaviour of an individual tiddler field."
},
"$:/language/Docs/ModuleTypes/tiddlermethod": {
"title": "$:/language/Docs/ModuleTypes/tiddlermethod",
"text": "Adds methods to the `$tw.Tiddler` prototype."
},
"$:/language/Docs/ModuleTypes/upgrader": {
"title": "$:/language/Docs/ModuleTypes/upgrader",
"text": "Applies upgrade processing to tiddlers during an upgrade/import."
},
"$:/language/Docs/ModuleTypes/utils": {
"title": "$:/language/Docs/ModuleTypes/utils",
"text": "Adds methods to `$tw.utils`."
},
"$:/language/Docs/ModuleTypes/utils-node": {
"title": "$:/language/Docs/ModuleTypes/utils-node",
"text": "Adds Node.js-specific methods to `$tw.utils`."
},
"$:/language/Docs/ModuleTypes/widget": {
"title": "$:/language/Docs/ModuleTypes/widget",
"text": "Widgets encapsulate DOM rendering and refreshing."
},
"$:/language/Docs/ModuleTypes/wikimethod": {
"title": "$:/language/Docs/ModuleTypes/wikimethod",
"text": "Adds methods to `$tw.Wiki`."
},
"$:/language/Docs/ModuleTypes/wikirule": {
"title": "$:/language/Docs/ModuleTypes/wikirule",
"text": "Individual parser rules for the main WikiText parser."
},
"$:/language/Docs/PaletteColours/alert-background": {
"title": "$:/language/Docs/PaletteColours/alert-background",
"text": "Alert background"
},
"$:/language/Docs/PaletteColours/alert-border": {
"title": "$:/language/Docs/PaletteColours/alert-border",
"text": "Alert border"
},
"$:/language/Docs/PaletteColours/alert-highlight": {
"title": "$:/language/Docs/PaletteColours/alert-highlight",
"text": "Alert highlight"
},
"$:/language/Docs/PaletteColours/alert-muted-foreground": {
"title": "$:/language/Docs/PaletteColours/alert-muted-foreground",
"text": "Alert muted foreground"
},
"$:/language/Docs/PaletteColours/background": {
"title": "$:/language/Docs/PaletteColours/background",
"text": "General background"
},
"$:/language/Docs/PaletteColours/blockquote-bar": {
"title": "$:/language/Docs/PaletteColours/blockquote-bar",
"text": "Blockquote bar"
},
"$:/language/Docs/PaletteColours/button-background": {
"title": "$:/language/Docs/PaletteColours/button-background",
"text": "Default button background"
},
"$:/language/Docs/PaletteColours/button-border": {
"title": "$:/language/Docs/PaletteColours/button-border",
"text": "Default button border"
},
"$:/language/Docs/PaletteColours/button-foreground": {
"title": "$:/language/Docs/PaletteColours/button-foreground",
"text": "Default button foreground"
},
"$:/language/Docs/PaletteColours/dirty-indicator": {
"title": "$:/language/Docs/PaletteColours/dirty-indicator",
"text": "Unsaved changes indicator"
},
"$:/language/Docs/PaletteColours/code-background": {
"title": "$:/language/Docs/PaletteColours/code-background",
"text": "Code background"
},
"$:/language/Docs/PaletteColours/code-border": {
"title": "$:/language/Docs/PaletteColours/code-border",
"text": "Code border"
},
"$:/language/Docs/PaletteColours/code-foreground": {
"title": "$:/language/Docs/PaletteColours/code-foreground",
"text": "Code foreground"
},
"$:/language/Docs/PaletteColours/download-background": {
"title": "$:/language/Docs/PaletteColours/download-background",
"text": "Download button background"
},
"$:/language/Docs/PaletteColours/download-foreground": {
"title": "$:/language/Docs/PaletteColours/download-foreground",
"text": "Download button foreground"
},
"$:/language/Docs/PaletteColours/dragger-background": {
"title": "$:/language/Docs/PaletteColours/dragger-background",
"text": "Dragger background"
},
"$:/language/Docs/PaletteColours/dragger-foreground": {
"title": "$:/language/Docs/PaletteColours/dragger-foreground",
"text": "Dragger foreground"
},
"$:/language/Docs/PaletteColours/dropdown-background": {
"title": "$:/language/Docs/PaletteColours/dropdown-background",
"text": "Dropdown background"
},
"$:/language/Docs/PaletteColours/dropdown-border": {
"title": "$:/language/Docs/PaletteColours/dropdown-border",
"text": "Dropdown border"
},
"$:/language/Docs/PaletteColours/dropdown-tab-background-selected": {
"title": "$:/language/Docs/PaletteColours/dropdown-tab-background-selected",
"text": "Dropdown tab background for selected tabs"
},
"$:/language/Docs/PaletteColours/dropdown-tab-background": {
"title": "$:/language/Docs/PaletteColours/dropdown-tab-background",
"text": "Dropdown tab background"
},
"$:/language/Docs/PaletteColours/dropzone-background": {
"title": "$:/language/Docs/PaletteColours/dropzone-background",
"text": "Dropzone background"
},
"$:/language/Docs/PaletteColours/external-link-background-hover": {
"title": "$:/language/Docs/PaletteColours/external-link-background-hover",
"text": "External link background hover"
},
"$:/language/Docs/PaletteColours/external-link-background-visited": {
"title": "$:/language/Docs/PaletteColours/external-link-background-visited",
"text": "External link background visited"
},
"$:/language/Docs/PaletteColours/external-link-background": {
"title": "$:/language/Docs/PaletteColours/external-link-background",
"text": "External link background"
},
"$:/language/Docs/PaletteColours/external-link-foreground-hover": {
"title": "$:/language/Docs/PaletteColours/external-link-foreground-hover",
"text": "External link foreground hover"
},
"$:/language/Docs/PaletteColours/external-link-foreground-visited": {
"title": "$:/language/Docs/PaletteColours/external-link-foreground-visited",
"text": "External link foreground visited"
},
"$:/language/Docs/PaletteColours/external-link-foreground": {
"title": "$:/language/Docs/PaletteColours/external-link-foreground",
"text": "External link foreground"
},
"$:/language/Docs/PaletteColours/foreground": {
"title": "$:/language/Docs/PaletteColours/foreground",
"text": "General foreground"
},
"$:/language/Docs/PaletteColours/message-background": {
"title": "$:/language/Docs/PaletteColours/message-background",
"text": "Message box background"
},
"$:/language/Docs/PaletteColours/message-border": {
"title": "$:/language/Docs/PaletteColours/message-border",
"text": "Message box border"
},
"$:/language/Docs/PaletteColours/message-foreground": {
"title": "$:/language/Docs/PaletteColours/message-foreground",
"text": "Message box foreground"
},
"$:/language/Docs/PaletteColours/modal-backdrop": {
"title": "$:/language/Docs/PaletteColours/modal-backdrop",
"text": "Modal backdrop"
},
"$:/language/Docs/PaletteColours/modal-background": {
"title": "$:/language/Docs/PaletteColours/modal-background",
"text": "Modal background"
},
"$:/language/Docs/PaletteColours/modal-border": {
"title": "$:/language/Docs/PaletteColours/modal-border",
"text": "Modal border"
},
"$:/language/Docs/PaletteColours/modal-footer-background": {
"title": "$:/language/Docs/PaletteColours/modal-footer-background",
"text": "Modal footer background"
},
"$:/language/Docs/PaletteColours/modal-footer-border": {
"title": "$:/language/Docs/PaletteColours/modal-footer-border",
"text": "Modal footer border"
},
"$:/language/Docs/PaletteColours/modal-header-border": {
"title": "$:/language/Docs/PaletteColours/modal-header-border",
"text": "Modal header border"
},
"$:/language/Docs/PaletteColours/muted-foreground": {
"title": "$:/language/Docs/PaletteColours/muted-foreground",
"text": "General muted foreground"
},
"$:/language/Docs/PaletteColours/notification-background": {
"title": "$:/language/Docs/PaletteColours/notification-background",
"text": "Notification background"
},
"$:/language/Docs/PaletteColours/notification-border": {
"title": "$:/language/Docs/PaletteColours/notification-border",
"text": "Notification border"
},
"$:/language/Docs/PaletteColours/page-background": {
"title": "$:/language/Docs/PaletteColours/page-background",
"text": "Page background"
},
"$:/language/Docs/PaletteColours/pre-background": {
"title": "$:/language/Docs/PaletteColours/pre-background",
"text": "Preformatted code background"
},
"$:/language/Docs/PaletteColours/pre-border": {
"title": "$:/language/Docs/PaletteColours/pre-border",
"text": "Preformatted code border"
},
"$:/language/Docs/PaletteColours/primary": {
"title": "$:/language/Docs/PaletteColours/primary",
"text": "General primary"
},
"$:/language/Docs/PaletteColours/sidebar-button-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-button-foreground",
"text": "Sidebar button foreground"
},
"$:/language/Docs/PaletteColours/sidebar-controls-foreground-hover": {
"title": "$:/language/Docs/PaletteColours/sidebar-controls-foreground-hover",
"text": "Sidebar controls foreground hover"
},
"$:/language/Docs/PaletteColours/sidebar-controls-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-controls-foreground",
"text": "Sidebar controls foreground"
},
"$:/language/Docs/PaletteColours/sidebar-foreground-shadow": {
"title": "$:/language/Docs/PaletteColours/sidebar-foreground-shadow",
"text": "Sidebar foreground shadow"
},
"$:/language/Docs/PaletteColours/sidebar-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-foreground",
"text": "Sidebar foreground"
},
"$:/language/Docs/PaletteColours/sidebar-muted-foreground-hover": {
"title": "$:/language/Docs/PaletteColours/sidebar-muted-foreground-hover",
"text": "Sidebar muted foreground hover"
},
"$:/language/Docs/PaletteColours/sidebar-muted-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-muted-foreground",
"text": "Sidebar muted foreground"
},
"$:/language/Docs/PaletteColours/sidebar-tab-background-selected": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-background-selected",
"text": "Sidebar tab background for selected tabs"
},
"$:/language/Docs/PaletteColours/sidebar-tab-background": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-background",
"text": "Sidebar tab background"
},
"$:/language/Docs/PaletteColours/sidebar-tab-border-selected": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-border-selected",
"text": "Sidebar tab border for selected tabs"
},
"$:/language/Docs/PaletteColours/sidebar-tab-border": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-border",
"text": "Sidebar tab border"
},
"$:/language/Docs/PaletteColours/sidebar-tab-divider": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-divider",
"text": "Sidebar tab divider"
},
"$:/language/Docs/PaletteColours/sidebar-tab-foreground-selected": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-foreground-selected",
"text": "Sidebar tab foreground for selected tabs"
},
"$:/language/Docs/PaletteColours/sidebar-tab-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-tab-foreground",
"text": "Sidebar tab foreground"
},
"$:/language/Docs/PaletteColours/sidebar-tiddler-link-foreground-hover": {
"title": "$:/language/Docs/PaletteColours/sidebar-tiddler-link-foreground-hover",
"text": "Sidebar tiddler link foreground hover"
},
"$:/language/Docs/PaletteColours/sidebar-tiddler-link-foreground": {
"title": "$:/language/Docs/PaletteColours/sidebar-tiddler-link-foreground",
"text": "Sidebar tiddler link foreground"
},
"$:/language/Docs/PaletteColours/site-title-foreground": {
"title": "$:/language/Docs/PaletteColours/site-title-foreground",
"text": "Site title foreground"
},
"$:/language/Docs/PaletteColours/static-alert-foreground": {
"title": "$:/language/Docs/PaletteColours/static-alert-foreground",
"text": "Static alert foreground"
},
"$:/language/Docs/PaletteColours/tab-background-selected": {
"title": "$:/language/Docs/PaletteColours/tab-background-selected",
"text": "Tab background for selected tabs"
},
"$:/language/Docs/PaletteColours/tab-background": {
"title": "$:/language/Docs/PaletteColours/tab-background",
"text": "Tab background"
},
"$:/language/Docs/PaletteColours/tab-border-selected": {
"title": "$:/language/Docs/PaletteColours/tab-border-selected",
"text": "Tab border for selected tabs"
},
"$:/language/Docs/PaletteColours/tab-border": {
"title": "$:/language/Docs/PaletteColours/tab-border",
"text": "Tab border"
},
"$:/language/Docs/PaletteColours/tab-divider": {
"title": "$:/language/Docs/PaletteColours/tab-divider",
"text": "Tab divider"
},
"$:/language/Docs/PaletteColours/tab-foreground-selected": {
"title": "$:/language/Docs/PaletteColours/tab-foreground-selected",
"text": "Tab foreground for selected tabs"
},
"$:/language/Docs/PaletteColours/tab-foreground": {
"title": "$:/language/Docs/PaletteColours/tab-foreground",
"text": "Tab foreground"
},
"$:/language/Docs/PaletteColours/table-border": {
"title": "$:/language/Docs/PaletteColours/table-border",
"text": "Table border"
},
"$:/language/Docs/PaletteColours/table-footer-background": {
"title": "$:/language/Docs/PaletteColours/table-footer-background",
"text": "Table footer background"
},
"$:/language/Docs/PaletteColours/table-header-background": {
"title": "$:/language/Docs/PaletteColours/table-header-background",
"text": "Table header background"
},
"$:/language/Docs/PaletteColours/tag-background": {
"title": "$:/language/Docs/PaletteColours/tag-background",
"text": "Tag background"
},
"$:/language/Docs/PaletteColours/tag-foreground": {
"title": "$:/language/Docs/PaletteColours/tag-foreground",
"text": "Tag foreground"
},
"$:/language/Docs/PaletteColours/tiddler-background": {
"title": "$:/language/Docs/PaletteColours/tiddler-background",
"text": "Tiddler background"
},
"$:/language/Docs/PaletteColours/tiddler-border": {
"title": "$:/language/Docs/PaletteColours/tiddler-border",
"text": "Tiddler border"
},
"$:/language/Docs/PaletteColours/tiddler-controls-foreground-hover": {
"title": "$:/language/Docs/PaletteColours/tiddler-controls-foreground-hover",
"text": "Tiddler controls foreground hover"
},
"$:/language/Docs/PaletteColours/tiddler-controls-foreground-selected": {
"title": "$:/language/Docs/PaletteColours/tiddler-controls-foreground-selected",
"text": "Tiddler controls foreground for selected controls"
},
"$:/language/Docs/PaletteColours/tiddler-controls-foreground": {
"title": "$:/language/Docs/PaletteColours/tiddler-controls-foreground",
"text": "Tiddler controls foreground"
},
"$:/language/Docs/PaletteColours/tiddler-editor-background": {
"title": "$:/language/Docs/PaletteColours/tiddler-editor-background",
"text": "Tiddler editor background"
},
"$:/language/Docs/PaletteColours/tiddler-editor-border-image": {
"title": "$:/language/Docs/PaletteColours/tiddler-editor-border-image",
"text": "Tiddler editor border image"
},
"$:/language/Docs/PaletteColours/tiddler-editor-border": {
"title": "$:/language/Docs/PaletteColours/tiddler-editor-border",
"text": "Tiddler editor border"
},
"$:/language/Docs/PaletteColours/tiddler-editor-fields-even": {
"title": "$:/language/Docs/PaletteColours/tiddler-editor-fields-even",
"text": "Tiddler editor background for even fields"
},
"$:/language/Docs/PaletteColours/tiddler-editor-fields-odd": {
"title": "$:/language/Docs/PaletteColours/tiddler-editor-fields-odd",
"text": "Tiddler editor background for odd fields"
},
"$:/language/Docs/PaletteColours/tiddler-info-background": {
"title": "$:/language/Docs/PaletteColours/tiddler-info-background",
"text": "Tiddler info panel background"
},
"$:/language/Docs/PaletteColours/tiddler-info-border": {
"title": "$:/language/Docs/PaletteColours/tiddler-info-border",
"text": "Tiddler info panel border"
},
"$:/language/Docs/PaletteColours/tiddler-info-tab-background": {
"title": "$:/language/Docs/PaletteColours/tiddler-info-tab-background",
"text": "Tiddler info panel tab background"
},
"$:/language/Docs/PaletteColours/tiddler-link-background": {
"title": "$:/language/Docs/PaletteColours/tiddler-link-background",
"text": "Tiddler link background"
},
"$:/language/Docs/PaletteColours/tiddler-link-foreground": {
"title": "$:/language/Docs/PaletteColours/tiddler-link-foreground",
"text": "Tiddler link foreground"
},
"$:/language/Docs/PaletteColours/tiddler-subtitle-foreground": {
"title": "$:/language/Docs/PaletteColours/tiddler-subtitle-foreground",
"text": "Tiddler subtitle foreground"
},
"$:/language/Docs/PaletteColours/tiddler-title-foreground": {
"title": "$:/language/Docs/PaletteColours/tiddler-title-foreground",
"text": "Tiddler title foreground"
},
"$:/language/Docs/PaletteColours/toolbar-new-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-new-button",
"text": "Toolbar 'new tiddler' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-options-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-options-button",
"text": "Toolbar 'options' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-save-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-save-button",
"text": "Toolbar 'save' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-info-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-info-button",
"text": "Toolbar 'info' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-edit-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-edit-button",
"text": "Toolbar 'edit' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-close-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-close-button",
"text": "Toolbar 'close' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-delete-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-delete-button",
"text": "Toolbar 'delete' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-cancel-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-cancel-button",
"text": "Toolbar 'cancel' button foreground"
},
"$:/language/Docs/PaletteColours/toolbar-done-button": {
"title": "$:/language/Docs/PaletteColours/toolbar-done-button",
"text": "Toolbar 'done' button foreground"
},
"$:/language/Docs/PaletteColours/untagged-background": {
"title": "$:/language/Docs/PaletteColours/untagged-background",
"text": "Untagged pill background"
},
"$:/language/Docs/PaletteColours/very-muted-foreground": {
"title": "$:/language/Docs/PaletteColours/very-muted-foreground",
"text": "Very muted foreground"
},
"$:/language/EditTemplate/Body/External/Hint": {
"title": "$:/language/EditTemplate/Body/External/Hint",
"text": "This is an external tiddler stored outside of the main TiddlyWiki file. You can edit the tags and fields but cannot directly edit the content itself"
},
"$:/language/EditTemplate/Body/Placeholder": {
"title": "$:/language/EditTemplate/Body/Placeholder",
"text": "Type the text for this tiddler"
},
"$:/language/EditTemplate/Body/Preview/Type/Output": {
"title": "$:/language/EditTemplate/Body/Preview/Type/Output",
"text": "output"
},
"$:/language/EditTemplate/Field/Remove/Caption": {
"title": "$:/language/EditTemplate/Field/Remove/Caption",
"text": "remove field"
},
"$:/language/EditTemplate/Field/Remove/Hint": {
"title": "$:/language/EditTemplate/Field/Remove/Hint",
"text": "Remove field"
},
"$:/language/EditTemplate/Fields/Add/Button": {
"title": "$:/language/EditTemplate/Fields/Add/Button",
"text": "add"
},
"$:/language/EditTemplate/Fields/Add/Name/Placeholder": {
"title": "$:/language/EditTemplate/Fields/Add/Name/Placeholder",
"text": "field name"
},
"$:/language/EditTemplate/Fields/Add/Prompt": {
"title": "$:/language/EditTemplate/Fields/Add/Prompt",
"text": "Add a new field:"
},
"$:/language/EditTemplate/Fields/Add/Value/Placeholder": {
"title": "$:/language/EditTemplate/Fields/Add/Value/Placeholder",
"text": "field value"
},
"$:/language/EditTemplate/Fields/Add/Dropdown/System": {
"title": "$:/language/EditTemplate/Fields/Add/Dropdown/System",
"text": "System fields"
},
"$:/language/EditTemplate/Fields/Add/Dropdown/User": {
"title": "$:/language/EditTemplate/Fields/Add/Dropdown/User",
"text": "User fields"
},
"$:/language/EditTemplate/Shadow/Warning": {
"title": "$:/language/EditTemplate/Shadow/Warning",
"text": "This is a shadow tiddler. Any changes you make will override the default version from the plugin <<pluginLink>>"
},
"$:/language/EditTemplate/Shadow/OverriddenWarning": {
"title": "$:/language/EditTemplate/Shadow/OverriddenWarning",
"text": "This is a modified shadow tiddler. You can revert to the default version in the plugin <<pluginLink>> by deleting this tiddler"
},
"$:/language/EditTemplate/Tags/Add/Button": {
"title": "$:/language/EditTemplate/Tags/Add/Button",
"text": "add"
},
"$:/language/EditTemplate/Tags/Add/Placeholder": {
"title": "$:/language/EditTemplate/Tags/Add/Placeholder",
"text": "tag name"
},
"$:/language/EditTemplate/Tags/Dropdown/Caption": {
"title": "$:/language/EditTemplate/Tags/Dropdown/Caption",
"text": "tag list"
},
"$:/language/EditTemplate/Tags/Dropdown/Hint": {
"title": "$:/language/EditTemplate/Tags/Dropdown/Hint",
"text": "Show tag list"
},
"$:/language/EditTemplate/Title/BadCharacterWarning": {
"title": "$:/language/EditTemplate/Title/BadCharacterWarning",
"text": "Warning: avoid using any of the characters <<bad-chars>> in tiddler titles"
},
"$:/language/EditTemplate/Type/Dropdown/Caption": {
"title": "$:/language/EditTemplate/Type/Dropdown/Caption",
"text": "content type list"
},
"$:/language/EditTemplate/Type/Dropdown/Hint": {
"title": "$:/language/EditTemplate/Type/Dropdown/Hint",
"text": "Show content type list"
},
"$:/language/EditTemplate/Type/Delete/Caption": {
"title": "$:/language/EditTemplate/Type/Delete/Caption",
"text": "delete content type"
},
"$:/language/EditTemplate/Type/Delete/Hint": {
"title": "$:/language/EditTemplate/Type/Delete/Hint",
"text": "Delete content type"
},
"$:/language/EditTemplate/Type/Placeholder": {
"title": "$:/language/EditTemplate/Type/Placeholder",
"text": "content type"
},
"$:/language/EditTemplate/Type/Prompt": {
"title": "$:/language/EditTemplate/Type/Prompt",
"text": "Type:"
},
"$:/language/Exporters/StaticRiver": {
"title": "$:/language/Exporters/StaticRiver",
"text": "Static HTML"
},
"$:/language/Exporters/JsonFile": {
"title": "$:/language/Exporters/JsonFile",
"text": "JSON file"
},
"$:/language/Exporters/CsvFile": {
"title": "$:/language/Exporters/CsvFile",
"text": "CSV file"
},
"$:/language/Exporters/TidFile": {
"title": "$:/language/Exporters/TidFile",
"text": "\".tid\" file"
},
"$:/language/Docs/Fields/_canonical_uri": {
"title": "$:/language/Docs/Fields/_canonical_uri",
"text": "The full URI of an external image tiddler"
},
"$:/language/Docs/Fields/bag": {
"title": "$:/language/Docs/Fields/bag",
"text": "The name of the bag from which a tiddler came"
},
"$:/language/Docs/Fields/caption": {
"title": "$:/language/Docs/Fields/caption",
"text": "The text to be displayed on a tab or button"
},
"$:/language/Docs/Fields/color": {
"title": "$:/language/Docs/Fields/color",
"text": "The CSS color value associated with a tiddler"
},
"$:/language/Docs/Fields/component": {
"title": "$:/language/Docs/Fields/component",
"text": "The name of the component responsible for an [[alert tiddler|AlertMechanism]]"
},
"$:/language/Docs/Fields/current-tiddler": {
"title": "$:/language/Docs/Fields/current-tiddler",
"text": "Used to cache the top tiddler in a [[history list|HistoryMechanism]]"
},
"$:/language/Docs/Fields/created": {
"title": "$:/language/Docs/Fields/created",
"text": "The date a tiddler was created"
},
"$:/language/Docs/Fields/creator": {
"title": "$:/language/Docs/Fields/creator",
"text": "The name of the person who created a tiddler"
},
"$:/language/Docs/Fields/dependents": {
"title": "$:/language/Docs/Fields/dependents",
"text": "For a plugin, lists the dependent plugin titles"
},
"$:/language/Docs/Fields/description": {
"title": "$:/language/Docs/Fields/description",
"text": "The descriptive text for a plugin, or a modal dialogue"
},
"$:/language/Docs/Fields/draft.of": {
"title": "$:/language/Docs/Fields/draft.of",
"text": "For draft tiddlers, contains the title of the tiddler of which this is a draft"
},
"$:/language/Docs/Fields/draft.title": {
"title": "$:/language/Docs/Fields/draft.title",
"text": "For draft tiddlers, contains the proposed new title of the tiddler"
},
"$:/language/Docs/Fields/footer": {
"title": "$:/language/Docs/Fields/footer",
"text": "The footer text for a wizard"
},
"$:/language/Docs/Fields/hack-to-give-us-something-to-compare-against": {
"title": "$:/language/Docs/Fields/hack-to-give-us-something-to-compare-against",
"text": "A temporary storage field used in [[$:/core/templates/static.content]]"
},
"$:/language/Docs/Fields/icon": {
"title": "$:/language/Docs/Fields/icon",
"text": "The title of the tiddler containing the icon associated with a tiddler"
},
"$:/language/Docs/Fields/library": {
"title": "$:/language/Docs/Fields/library",
"text": "If set to \"yes\" indicates that a tiddler should be saved as a JavaScript library"
},
"$:/language/Docs/Fields/list": {
"title": "$:/language/Docs/Fields/list",
"text": "An ordered list of tiddler titles associated with a tiddler"
},
"$:/language/Docs/Fields/list-before": {
"title": "$:/language/Docs/Fields/list-before",
"text": "If set, the title of a tiddler before which this tiddler should be added to the ordered list of tiddler titles, or at the start of the list if this field is present but empty"
},
"$:/language/Docs/Fields/list-after": {
"title": "$:/language/Docs/Fields/list-after",
"text": "If set, the title of the tiddler after which this tiddler should be added to the ordered list of tiddler titles"
},
"$:/language/Docs/Fields/modified": {
"title": "$:/language/Docs/Fields/modified",
"text": "The date and time at which a tiddler was last modified"
},
"$:/language/Docs/Fields/modifier": {
"title": "$:/language/Docs/Fields/modifier",
"text": "The tiddler title associated with the person who last modified a tiddler"
},
"$:/language/Docs/Fields/name": {
"title": "$:/language/Docs/Fields/name",
"text": "The human readable name associated with a plugin tiddler"
},
"$:/language/Docs/Fields/plugin-priority": {
"title": "$:/language/Docs/Fields/plugin-priority",
"text": "A numerical value indicating the priority of a plugin tiddler"
},
"$:/language/Docs/Fields/plugin-type": {
"title": "$:/language/Docs/Fields/plugin-type",
"text": "The type of plugin in a plugin tiddler"
},
"$:/language/Docs/Fields/revision": {
"title": "$:/language/Docs/Fields/revision",
"text": "The revision of the tiddler held at the server"
},
"$:/language/Docs/Fields/released": {
"title": "$:/language/Docs/Fields/released",
"text": "Date of a TiddlyWiki release"
},
"$:/language/Docs/Fields/source": {
"title": "$:/language/Docs/Fields/source",
"text": "The source URL associated with a tiddler"
},
"$:/language/Docs/Fields/subtitle": {
"title": "$:/language/Docs/Fields/subtitle",
"text": "The subtitle text for a wizard"
},
"$:/language/Docs/Fields/tags": {
"title": "$:/language/Docs/Fields/tags",
"text": "A list of tags associated with a tiddler"
},
"$:/language/Docs/Fields/text": {
"title": "$:/language/Docs/Fields/text",
"text": "The body text of a tiddler"
},
"$:/language/Docs/Fields/title": {
"title": "$:/language/Docs/Fields/title",
"text": "The unique name of a tiddler"
},
"$:/language/Docs/Fields/type": {
"title": "$:/language/Docs/Fields/type",
"text": "The content type of a tiddler"
},
"$:/language/Docs/Fields/version": {
"title": "$:/language/Docs/Fields/version",
"text": "Version information for a plugin"
},
"$:/language/Filters/AllTiddlers": {
"title": "$:/language/Filters/AllTiddlers",
"text": "All tiddlers except system tiddlers"
},
"$:/language/Filters/RecentSystemTiddlers": {
"title": "$:/language/Filters/RecentSystemTiddlers",
"text": "Recently modified tiddlers, including system tiddlers"
},
"$:/language/Filters/RecentTiddlers": {
"title": "$:/language/Filters/RecentTiddlers",
"text": "Recently modified tiddlers"
},
"$:/language/Filters/AllTags": {
"title": "$:/language/Filters/AllTags",
"text": "All tags except system tags"
},
"$:/language/Filters/Missing": {
"title": "$:/language/Filters/Missing",
"text": "Missing tiddlers"
},
"$:/language/Filters/Drafts": {
"title": "$:/language/Filters/Drafts",
"text": "Draft tiddlers"
},
"$:/language/Filters/Orphans": {
"title": "$:/language/Filters/Orphans",
"text": "Orphan tiddlers"
},
"$:/language/Filters/SystemTiddlers": {
"title": "$:/language/Filters/SystemTiddlers",
"text": "System tiddlers"
},
"$:/language/Filters/ShadowTiddlers": {
"title": "$:/language/Filters/ShadowTiddlers",
"text": "Shadow tiddlers"
},
"$:/language/Filters/OverriddenShadowTiddlers": {
"title": "$:/language/Filters/OverriddenShadowTiddlers",
"text": "Overridden shadow tiddlers"
},
"$:/language/Filters/SystemTags": {
"title": "$:/language/Filters/SystemTags",
"text": "System tags"
},
"$:/language/Filters/TypedTiddlers": {
"title": "$:/language/Filters/TypedTiddlers",
"text": "Non wiki-text tiddlers"
},
"GettingStarted": {
"title": "GettingStarted",
"text": "\\define lingo-base() $:/language/ControlPanel/Basics/\nWelcome to ~TiddlyWiki and the ~TiddlyWiki community\n\nBefore you start storing important information in ~TiddlyWiki it is important to make sure that you can reliably save changes. See http://tiddlywiki.com/#GettingStarted for details\n\n!! Set up this ~TiddlyWiki\n\n<div class=\"tc-control-panel\">\n\n|<$link to=\"$:/SiteTitle\"><<lingo Title/Prompt>></$link> |<$edit-text tiddler=\"$:/SiteTitle\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/SiteSubtitle\"><<lingo Subtitle/Prompt>></$link> |<$edit-text tiddler=\"$:/SiteSubtitle\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/DefaultTiddlers\"><<lingo DefaultTiddlers/Prompt>></$link> |<<lingo DefaultTiddlers/TopHint>><br> <$edit tag=\"textarea\" tiddler=\"$:/DefaultTiddlers\"/><br>//<<lingo DefaultTiddlers/BottomHint>>// |\n</div>\n\nSee the [[control panel|$:/ControlPanel]] for more options.\n"
},
"$:/language/Help/build": {
"title": "$:/language/Help/build",
"description": "Automatically run configured commands",
"text": "Build the specified build targets for the current wiki. If no build targets are specified then all available targets will be built.\n\n```\n--build <target> [<target> ...]\n```\n\nBuild targets are defined in the `tiddlywiki.info` file of a wiki folder.\n\n"
},
"$:/language/Help/clearpassword": {
"title": "$:/language/Help/clearpassword",
"description": "Clear a password for subsequent crypto operations",
"text": "Clear the password for subsequent crypto operations\n\n```\n--clearpassword\n```\n"
},
"$:/language/Help/default": {
"title": "$:/language/Help/default",
"text": "\\define commandTitle()\n$:/language/Help/$(command)$\n\\end\n```\nusage: tiddlywiki [<wikifolder>] [--<command> [<args>...]...]\n```\n\nAvailable commands:\n\n<ul>\n<$list filter=\"[commands[]sort[title]]\" variable=\"command\">\n<li><$link to=<<commandTitle>>><$macrocall $name=\"command\" $type=\"text/plain\" $output=\"text/plain\"/></$link>: <$transclude tiddler=<<commandTitle>> field=\"description\"/></li>\n</$list>\n</ul>\n\nTo get detailed help on a command:\n\n```\ntiddlywiki --help <command>\n```\n"
},
"$:/language/Help/editions": {
"title": "$:/language/Help/editions",
"description": "Lists the available editions of TiddlyWiki",
"text": "Lists the names and descriptions of the available editions. You can create a new wiki of a specified edition with the `--init` command.\n\n```\n--editions\n```\n"
},
"$:/language/Help/help": {
"title": "$:/language/Help/help",
"description": "Display help for TiddlyWiki commands",
"text": "Displays help text for a command:\n\n```\n--help [<command>]\n```\n\nIf the command name is omitted then a list of available commands is displayed.\n"
},
"$:/language/Help/init": {
"title": "$:/language/Help/init",
"description": "Initialise a new wiki folder",
"text": "Initialise an empty [[WikiFolder|WikiFolders]] with a copy of the specified edition.\n\n```\n--init <edition> [<edition> ...]\n```\n\nFor example:\n\n```\ntiddlywiki ./MyWikiFolder --init empty\n```\n\nNote:\n\n* The wiki folder directory will be created if necessary\n* The \"edition\" defaults to ''empty''\n* The init command will fail if the wiki folder is not empty\n* The init command removes any `includeWikis` definitions in the edition's `tiddlywiki.info` file\n* When multiple editions are specified, editions initialised later will overwrite any files shared with earlier editions (so, the final `tiddlywiki.info` file will be copied from the last edition)\n* `--editions` returns a list of available editions\n"
},
"$:/language/Help/load": {
"title": "$:/language/Help/load",
"description": "Load tiddlers from a file",
"text": "Load tiddlers from 2.x.x TiddlyWiki files (`.html`), `.tiddler`, `.tid`, `.json` or other files\n\n```\n--load <filepath>\n```\n\nTo load tiddlers from an encrypted TiddlyWiki file you should first specify the password with the PasswordCommand. For example:\n\n```\ntiddlywiki ./MyWiki --password pa55w0rd --load my_encrypted_wiki.html\n```\n\nNote that TiddlyWiki will not load an older version of an already loaded plugin.\n"
},
"$:/language/Help/makelibrary": {
"title": "$:/language/Help/makelibrary",
"description": "Construct library plugin required by upgrade process",
"text": "Constructs the `$:/UpgradeLibrary` tiddler for the upgrade process.\n\nThe upgrade library is formatted as an ordinary plugin tiddler with the plugin type `library`. It contains a copy of each of the plugins, themes and language packs available within the TiddlyWiki5 repository.\n\nThis command is intended for internal use; it is only relevant to users constructing a custom upgrade procedure.\n\n```\n--makelibrary <title>\n```\n\nThe title argument defaults to `$:/UpgradeLibrary`.\n"
},
"$:/language/Help/notfound": {
"title": "$:/language/Help/notfound",
"text": "No such help item"
},
"$:/language/Help/output": {
"title": "$:/language/Help/output",
"description": "Set the base output directory for subsequent commands",
"text": "Sets the base output directory for subsequent commands. The default output directory is the `output` subdirectory of the edition directory.\n\n```\n--output <pathname>\n```\n\nIf the specified pathname is relative then it is resolved relative to the current working directory. For example `--output .` sets the output directory to the current working directory.\n\n"
},
"$:/language/Help/password": {
"title": "$:/language/Help/password",
"description": "Set a password for subsequent crypto operations",
"text": "Set a password for subsequent crypto operations\n\n```\n--password <password>\n```\n\n''Note'': This should not be used for serving TiddlyWiki with password protection. Instead, see the password option under the [[ServerCommand]].\n"
},
"$:/language/Help/rendertiddler": {
"title": "$:/language/Help/rendertiddler",
"description": "Render an individual tiddler as a specified ContentType",
"text": "Render an individual tiddler as a specified ContentType, defaulting to `text/html` and save it to the specified filename. Optionally a template can be specified, in which case the template tiddler is rendered with the \"currentTiddler\" variable set to the tiddler that is being rendered (the first parameter value).\n\n```\n--rendertiddler <title> <filename> [<type>] [<template>]\n```\n\nBy default, the filename is resolved relative to the `output` subdirectory of the edition directory. The `--output` command can be used to direct output to a different directory.\n\nAny missing directories in the path to the filename are automatically created.\n"
},
"$:/language/Help/rendertiddlers": {
"title": "$:/language/Help/rendertiddlers",
"description": "Render tiddlers matching a filter to a specified ContentType",
"text": "Render a set of tiddlers matching a filter to separate files of a specified ContentType (defaults to `text/html`) and extension (defaults to `.html`).\n\n```\n--rendertiddlers <filter> <template> <pathname> [<type>] [<extension>] [\"noclean\"]\n```\n\nFor example:\n\n```\n--rendertiddlers [!is[system]] $:/core/templates/static.tiddler.html ./static text/plain\n```\n\nBy default, the pathname is resolved relative to the `output` subdirectory of the edition directory. The `--output` command can be used to direct output to a different directory.\n\nAny files in the target directory are deleted unless the ''noclean'' flag is specified. The target directory is recursively created if it is missing.\n"
},
"$:/language/Help/savetiddler": {
"title": "$:/language/Help/savetiddler",
"description": "Saves a raw tiddler to a file",
"text": "Saves an individual tiddler in its raw text or binary format to the specified filename.\n\n```\n--savetiddler <title> <filename>\n```\n\nBy default, the filename is resolved relative to the `output` subdirectory of the edition directory. The `--output` command can be used to direct output to a different directory.\n\nAny missing directories in the path to the filename are automatically created.\n"
},
"$:/language/Help/savetiddlers": {
"title": "$:/language/Help/savetiddlers",
"description": "Saves a group of raw tiddlers to a directory",
"text": "Saves a group of tiddlers in their raw text or binary format to the specified directory.\n\n```\n--savetiddlers <filter> <pathname> [\"noclean\"]\n```\n\nBy default, the pathname is resolved relative to the `output` subdirectory of the edition directory. The `--output` command can be used to direct output to a different directory.\n\nThe output directory is cleared of existing files before saving the specified files. The deletion can be disabled by specifying the ''noclean'' flag.\n\nAny missing directories in the pathname are automatically created.\n"
},
"$:/language/Help/server": {
"title": "$:/language/Help/server",
"description": "Provides an HTTP server interface to TiddlyWiki",
"text": "The server built in to TiddlyWiki5 is very simple. Although compatible with TiddlyWeb it doesn't support many of the features needed for robust Internet-facing usage.\n\nAt the root, it serves a rendering of a specified tiddler. Away from the root, it serves individual tiddlers encoded in JSON, and supports the basic HTTP operations for `GET`, `PUT` and `DELETE`.\n\n```\n--server <port> <roottiddler> <rendertype> <servetype> <username> <password> <host> <pathprefix>\n```\n\nThe parameters are:\n\n* ''port'' - port number to serve from (defaults to \"8080\")\n* ''roottiddler'' - the tiddler to serve at the root (defaults to \"$:/core/save/all\")\n* ''rendertype'' - the content type to which the root tiddler should be rendered (defaults to \"text/plain\")\n* ''servetype'' - the content type with which the root tiddler should be served (defaults to \"text/html\")\n* ''username'' - the default username for signing edits\n* ''password'' - optional password for basic authentication\n* ''host'' - optional hostname to serve from (defaults to \"127.0.0.1\" aka \"localhost\")\n* ''pathprefix'' - optional prefix for paths\n\nIf the password parameter is specified then the browser will prompt the user for the username and password. Note that the password is transmitted in plain text so this implementation isn't suitable for general use.\n\nFor example:\n\n```\n--server 8080 $:/core/save/all text/plain text/html MyUserName passw0rd\n```\n\nThe username and password can be specified as empty strings if you need to set the hostname or pathprefix and don't want to require a password:\n\n```\n--server 8080 $:/core/save/all text/plain text/html \"\" \"\" 192.168.0.245\n```\n\nTo run multiple TiddlyWiki servers at the same time you'll need to put each one on a different port.\n"
},
"$:/language/Help/setfield": {
"title": "$:/language/Help/setfield",
"description": "Prepares external tiddlers for use",
"text": "//Note that this command is experimental and may change or be replaced before being finalised//\n\nSets the specified field of a group of tiddlers to the result of wikifying a template tiddler with the `currentTiddler` variable set to the tiddler.\n\n```\n--setfield <filter> <fieldname> <templatetitle> <rendertype>\n```\n\nThe parameters are:\n\n* ''filter'' - filter identifying the tiddlers to be affected\n* ''fieldname'' - the field to modify (defaults to \"text\")\n* ''templatetitle'' - the tiddler to wikify into the specified field. If blank or missing then the specified field is deleted\n* ''rendertype'' - the text type to render (defaults to \"text/plain\"; \"text/html\" can be used to include HTML tags)\n"
},
"$:/language/Help/unpackplugin": {
"title": "$:/language/Help/unpackplugin",
"description": "Unpack the payload tiddlers from a plugin",
"text": "Extract the payload tiddlers from a plugin, creating them as ordinary tiddlers:\n\n```\n--unpackplugin <title>\n```\n"
},
"$:/language/Help/verbose": {
"title": "$:/language/Help/verbose",
"description": "Triggers verbose output mode",
"text": "Triggers verbose output, useful for debugging\n\n```\n--verbose\n```\n"
},
"$:/language/Help/version": {
"title": "$:/language/Help/version",
"description": "Displays the version number of TiddlyWiki",
"text": "Displays the version number of TiddlyWiki.\n\n```\n--version\n```\n"
},
"$:/language/Import/Imported/Hint": {
"title": "$:/language/Import/Imported/Hint",
"text": "The following tiddlers were imported:"
},
"$:/language/Import/Listing/Cancel/Caption": {
"title": "$:/language/Import/Listing/Cancel/Caption",
"text": "Cancel"
},
"$:/language/Import/Listing/Hint": {
"title": "$:/language/Import/Listing/Hint",
"text": "These tiddlers are ready to import:"
},
"$:/language/Import/Listing/Import/Caption": {
"title": "$:/language/Import/Listing/Import/Caption",
"text": "Import"
},
"$:/language/Import/Listing/Select/Caption": {
"title": "$:/language/Import/Listing/Select/Caption",
"text": "Select"
},
"$:/language/Import/Listing/Status/Caption": {
"title": "$:/language/Import/Listing/Status/Caption",
"text": "Status"
},
"$:/language/Import/Listing/Title/Caption": {
"title": "$:/language/Import/Listing/Title/Caption",
"text": "Title"
},
"$:/language/Import/Upgrader/Plugins/Suppressed/Incompatible": {
"title": "$:/language/Import/Upgrader/Plugins/Suppressed/Incompatible",
"text": "Blocked incompatible or obsolete plugin"
},
"$:/language/Import/Upgrader/Plugins/Suppressed/Version": {
"title": "$:/language/Import/Upgrader/Plugins/Suppressed/Version",
"text": "Blocked plugin (due to incoming <<incoming>> being older than existing <<existing>>)"
},
"$:/language/Import/Upgrader/Plugins/Upgraded": {
"title": "$:/language/Import/Upgrader/Plugins/Upgraded",
"text": "Upgraded plugin from <<incoming>> to <<upgraded>>"
},
"$:/language/Import/Upgrader/State/Suppressed": {
"title": "$:/language/Import/Upgrader/State/Suppressed",
"text": "Blocked temporary state tiddler"
},
"$:/language/Import/Upgrader/System/Suppressed": {
"title": "$:/language/Import/Upgrader/System/Suppressed",
"text": "Blocked system tiddler"
},
"$:/language/Import/Upgrader/ThemeTweaks/Created": {
"title": "$:/language/Import/Upgrader/ThemeTweaks/Created",
"text": "Migrated theme tweak from <$text text=<<from>>/>"
},
"$:/language/AboveStory/ClassicPlugin/Warning": {
"title": "$:/language/AboveStory/ClassicPlugin/Warning",
"text": "It looks like you are trying to load a plugin designed for ~TiddlyWiki Classic. Please note that [[these plugins do not work with TiddlyWiki version 5.x.x|http://tiddlywiki.com/#TiddlyWikiClassic]]. ~TiddlyWiki Classic plugins detected:"
},
"$:/language/BinaryWarning/Prompt": {
"title": "$:/language/BinaryWarning/Prompt",
"text": "This tiddler contains binary data"
},
"$:/language/ClassicWarning/Hint": {
"title": "$:/language/ClassicWarning/Hint",
"text": "This tiddler is written in TiddlyWiki Classic wiki text format, which is not fully compatible with TiddlyWiki version 5. See http://tiddlywiki.com/static/Upgrading.html for more details."
},
"$:/language/ClassicWarning/Upgrade/Caption": {
"title": "$:/language/ClassicWarning/Upgrade/Caption",
"text": "upgrade"
},
"$:/language/CloseAll/Button": {
"title": "$:/language/CloseAll/Button",
"text": "close all"
},
"$:/language/ColourPicker/Recent": {
"title": "$:/language/ColourPicker/Recent",
"text": "Recent:"
},
"$:/language/ConfirmCancelTiddler": {
"title": "$:/language/ConfirmCancelTiddler",
"text": "Do you wish to discard changes to the tiddler \"<$text text=<<title>>/>\"?"
},
"$:/language/ConfirmDeleteTiddler": {
"title": "$:/language/ConfirmDeleteTiddler",
"text": "Do you wish to delete the tiddler \"<$text text=<<title>>/>\"?"
},
"$:/language/ConfirmOverwriteTiddler": {
"title": "$:/language/ConfirmOverwriteTiddler",
"text": "Do you wish to overwrite the tiddler \"<$text text=<<title>>/>\"?"
},
"$:/language/ConfirmEditShadowTiddler": {
"title": "$:/language/ConfirmEditShadowTiddler",
"text": "You are about to edit a ShadowTiddler. Any changes will override the default system making future upgrades non-trivial. Are you sure you want to edit \"<$text text=<<title>>/>\"?"
},
"$:/language/Count": {
"title": "$:/language/Count",
"text": "count"
},
"$:/language/DefaultNewTiddlerTitle": {
"title": "$:/language/DefaultNewTiddlerTitle",
"text": "New Tiddler"
},
"$:/language/DropMessage": {
"title": "$:/language/DropMessage",
"text": "Drop here (or use the 'Escape' key to cancel)"
},
"$:/language/Encryption/Cancel": {
"title": "$:/language/Encryption/Cancel",
"text": "Cancel"
},
"$:/language/Encryption/ConfirmClearPassword": {
"title": "$:/language/Encryption/ConfirmClearPassword",
"text": "Do you wish to clear the password? This will remove the encryption applied when saving this wiki"
},
"$:/language/Encryption/PromptSetPassword": {
"title": "$:/language/Encryption/PromptSetPassword",
"text": "Set a new password for this TiddlyWiki"
},
"$:/language/Encryption/Username": {
"title": "$:/language/Encryption/Username",
"text": "Username"
},
"$:/language/Encryption/Password": {
"title": "$:/language/Encryption/Password",
"text": "Password"
},
"$:/language/Encryption/RepeatPassword": {
"title": "$:/language/Encryption/RepeatPassword",
"text": "Repeat password"
},
"$:/language/Encryption/PasswordNoMatch": {
"title": "$:/language/Encryption/PasswordNoMatch",
"text": "Passwords do not match"
},
"$:/language/Encryption/SetPassword": {
"title": "$:/language/Encryption/SetPassword",
"text": "Set password"
},
"$:/language/Error/Caption": {
"title": "$:/language/Error/Caption",
"text": "Error"
},
"$:/language/Error/Filter": {
"title": "$:/language/Error/Filter",
"text": "Filter error"
},
"$:/language/Error/FilterSyntax": {
"title": "$:/language/Error/FilterSyntax",
"text": "Syntax error in filter expression"
},
"$:/language/Error/IsFilterOperator": {
"title": "$:/language/Error/IsFilterOperator",
"text": "Filter Error: Unknown operand for the 'is' filter operator"
},
"$:/language/Error/LoadingPluginLibrary": {
"title": "$:/language/Error/LoadingPluginLibrary",
"text": "Error loading plugin library"
},
"$:/language/Error/RecursiveTransclusion": {
"title": "$:/language/Error/RecursiveTransclusion",
"text": "Recursive transclusion error in transclude widget"
},
"$:/language/Error/RetrievingSkinny": {
"title": "$:/language/Error/RetrievingSkinny",
"text": "Error retrieving skinny tiddler list"
},
"$:/language/Error/SavingToTWEdit": {
"title": "$:/language/Error/SavingToTWEdit",
"text": "Error saving to TWEdit"
},
"$:/language/Error/WhileSaving": {
"title": "$:/language/Error/WhileSaving",
"text": "Error while saving"
},
"$:/language/Error/XMLHttpRequest": {
"title": "$:/language/Error/XMLHttpRequest",
"text": "XMLHttpRequest error code"
},
"$:/language/InternalJavaScriptError/Title": {
"title": "$:/language/InternalJavaScriptError/Title",
"text": "Internal JavaScript Error"
},
"$:/language/InternalJavaScriptError/Hint": {
"title": "$:/language/InternalJavaScriptError/Hint",
"text": "Well, this is embarrassing. It is recommended that you restart TiddlyWiki by refreshing your browser"
},
"$:/language/InvalidFieldName": {
"title": "$:/language/InvalidFieldName",
"text": "Illegal characters in field name \"<$text text=<<fieldName>>/>\". Fields can only contain lowercase letters, digits and the characters underscore (`_`), hyphen (`-`) and period (`.`)"
},
"$:/language/LazyLoadingWarning": {
"title": "$:/language/LazyLoadingWarning",
"text": "<p>Loading external text from ''<$text text={{!!_canonical_uri}}/>''</p><p>If this message doesn't disappear you may be using a browser that doesn't support external text in this configuration. See http://tiddlywiki.com/#ExternalText</p>"
},
"$:/language/LoginToTiddlySpace": {
"title": "$:/language/LoginToTiddlySpace",
"text": "Login to TiddlySpace"
},
"$:/language/MissingTiddler/Hint": {
"title": "$:/language/MissingTiddler/Hint",
"text": "Missing tiddler \"<$text text=<<currentTiddler>>/>\" - click {{$:/core/images/edit-button}} to create"
},
"$:/language/No": {
"title": "$:/language/No",
"text": "No"
},
"$:/language/OfficialPluginLibrary": {
"title": "$:/language/OfficialPluginLibrary",
"text": "Official ~TiddlyWiki Plugin Library"
},
"$:/language/OfficialPluginLibrary/Hint": {
"title": "$:/language/OfficialPluginLibrary/Hint",
"text": "The official ~TiddlyWiki plugin library at tiddlywiki.com. Plugins, themes and language packs are maintained by the core team."
},
"$:/language/PluginReloadWarning": {
"title": "$:/language/PluginReloadWarning",
"text": "Please save {{$:/core/ui/Buttons/save-wiki}} and reload {{$:/core/ui/Buttons/refresh}} to allow changes to plugins to take effect"
},
"$:/language/RecentChanges/DateFormat": {
"title": "$:/language/RecentChanges/DateFormat",
"text": "DDth MMM YYYY"
},
"$:/language/SystemTiddler/Tooltip": {
"title": "$:/language/SystemTiddler/Tooltip",
"text": "This is a system tiddler"
},
"$:/language/TagManager/Colour/Heading": {
"title": "$:/language/TagManager/Colour/Heading",
"text": "Colour"
},
"$:/language/TagManager/Count/Heading": {
"title": "$:/language/TagManager/Count/Heading",
"text": "Count"
},
"$:/language/TagManager/Icon/Heading": {
"title": "$:/language/TagManager/Icon/Heading",
"text": "Icon"
},
"$:/language/TagManager/Info/Heading": {
"title": "$:/language/TagManager/Info/Heading",
"text": "Info"
},
"$:/language/TagManager/Tag/Heading": {
"title": "$:/language/TagManager/Tag/Heading",
"text": "Tag"
},
"$:/language/Tiddler/DateFormat": {
"title": "$:/language/Tiddler/DateFormat",
"text": "DDth MMM YYYY at hh12:0mmam"
},
"$:/language/UnsavedChangesWarning": {
"title": "$:/language/UnsavedChangesWarning",
"text": "You have unsaved changes in TiddlyWiki"
},
"$:/language/Yes": {
"title": "$:/language/Yes",
"text": "Yes"
},
"$:/language/Modals/Download": {
"title": "$:/language/Modals/Download",
"type": "text/vnd.tiddlywiki",
"subtitle": "Download changes",
"footer": "<$button message=\"tm-close-tiddler\">Close</$button>",
"help": "http://tiddlywiki.com/static/DownloadingChanges.html",
"text": "Your browser only supports manual saving.\n\nTo save your modified wiki, right click on the download link below and select \"Download file\" or \"Save file\", and then choose the folder and filename.\n\n//You can marginally speed things up by clicking the link with the control key (Windows) or the options/alt key (Mac OS X). You will not be prompted for the folder or filename, but your browser is likely to give it an unrecognisable name -- you may need to rename the file to include an `.html` extension before you can do anything useful with it.//\n\nOn smartphones that do not allow files to be downloaded you can instead bookmark the link, and then sync your bookmarks to a desktop computer from where the wiki can be saved normally.\n"
},
"$:/language/Modals/SaveInstructions": {
"title": "$:/language/Modals/SaveInstructions",
"type": "text/vnd.tiddlywiki",
"subtitle": "Save your work",
"footer": "<$button message=\"tm-close-tiddler\">Close</$button>",
"help": "http://tiddlywiki.com/static/SavingChanges.html",
"text": "Your changes to this wiki need to be saved as a ~TiddlyWiki HTML file.\n\n!!! Desktop browsers\n\n# Select ''Save As'' from the ''File'' menu\n# Choose a filename and location\n#* Some browsers also require you to explicitly specify the file saving format as ''Webpage, HTML only'' or similar\n# Close this tab\n\n!!! Smartphone browsers\n\n# Create a bookmark to this page\n#* If you've got iCloud or Google Sync set up then the bookmark will automatically sync to your desktop where you can open it and save it as above\n# Close this tab\n\n//If you open the bookmark again in Mobile Safari you will see this message again. If you want to go ahead and use the file, just click the ''close'' button below//\n"
},
"$:/config/NewJournal/Title": {
"title": "$:/config/NewJournal/Title",
"text": "DDth MMM YYYY"
},
"$:/config/NewJournal/Tags": {
"title": "$:/config/NewJournal/Tags",
"text": "Journal"
},
"$:/language/Notifications/Save/Done": {
"title": "$:/language/Notifications/Save/Done",
"text": "Saved wiki"
},
"$:/language/Notifications/Save/Starting": {
"title": "$:/language/Notifications/Save/Starting",
"text": "Starting to save wiki"
},
"$:/language/Search/DefaultResults/Caption": {
"title": "$:/language/Search/DefaultResults/Caption",
"text": "List"
},
"$:/language/Search/Filter/Caption": {
"title": "$:/language/Search/Filter/Caption",
"text": "Filter"
},
"$:/language/Search/Filter/Hint": {
"title": "$:/language/Search/Filter/Hint",
"text": "Search via a [[filter expression|http://tiddlywiki.com/static/Filters.html]]"
},
"$:/language/Search/Filter/Matches": {
"title": "$:/language/Search/Filter/Matches",
"text": "//<small><<resultCount>> matches</small>//"
},
"$:/language/Search/Matches": {
"title": "$:/language/Search/Matches",
"text": "//<small><<resultCount>> matches</small>//"
},
"$:/language/Search/Matches/All": {
"title": "$:/language/Search/Matches/All",
"text": "All matches:"
},
"$:/language/Search/Matches/Title": {
"title": "$:/language/Search/Matches/Title",
"text": "Title matches:"
},
"$:/language/Search/Search": {
"title": "$:/language/Search/Search",
"text": "Search"
},
"$:/language/Search/Shadows/Caption": {
"title": "$:/language/Search/Shadows/Caption",
"text": "Shadows"
},
"$:/language/Search/Shadows/Hint": {
"title": "$:/language/Search/Shadows/Hint",
"text": "Search for shadow tiddlers"
},
"$:/language/Search/Shadows/Matches": {
"title": "$:/language/Search/Shadows/Matches",
"text": "//<small><<resultCount>> matches</small>//"
},
"$:/language/Search/Standard/Caption": {
"title": "$:/language/Search/Standard/Caption",
"text": "Standard"
},
"$:/language/Search/Standard/Hint": {
"title": "$:/language/Search/Standard/Hint",
"text": "Search for standard tiddlers"
},
"$:/language/Search/Standard/Matches": {
"title": "$:/language/Search/Standard/Matches",
"text": "//<small><<resultCount>> matches</small>//"
},
"$:/language/Search/System/Caption": {
"title": "$:/language/Search/System/Caption",
"text": "System"
},
"$:/language/Search/System/Hint": {
"title": "$:/language/Search/System/Hint",
"text": "Search for system tiddlers"
},
"$:/language/Search/System/Matches": {
"title": "$:/language/Search/System/Matches",
"text": "//<small><<resultCount>> matches</small>//"
},
"$:/language/SideBar/All/Caption": {
"title": "$:/language/SideBar/All/Caption",
"text": "All"
},
"$:/language/SideBar/Contents/Caption": {
"title": "$:/language/SideBar/Contents/Caption",
"text": "Contents"
},
"$:/language/SideBar/Drafts/Caption": {
"title": "$:/language/SideBar/Drafts/Caption",
"text": "Drafts"
},
"$:/language/SideBar/Missing/Caption": {
"title": "$:/language/SideBar/Missing/Caption",
"text": "Missing"
},
"$:/language/SideBar/More/Caption": {
"title": "$:/language/SideBar/More/Caption",
"text": "More"
},
"$:/language/SideBar/Open/Caption": {
"title": "$:/language/SideBar/Open/Caption",
"text": "Open"
},
"$:/language/SideBar/Orphans/Caption": {
"title": "$:/language/SideBar/Orphans/Caption",
"text": "Orphans"
},
"$:/language/SideBar/Recent/Caption": {
"title": "$:/language/SideBar/Recent/Caption",
"text": "Recent"
},
"$:/language/SideBar/Shadows/Caption": {
"title": "$:/language/SideBar/Shadows/Caption",
"text": "Shadows"
},
"$:/language/SideBar/System/Caption": {
"title": "$:/language/SideBar/System/Caption",
"text": "System"
},
"$:/language/SideBar/Tags/Caption": {
"title": "$:/language/SideBar/Tags/Caption",
"text": "Tags"
},
"$:/language/SideBar/Tags/Untagged/Caption": {
"title": "$:/language/SideBar/Tags/Untagged/Caption",
"text": "untagged"
},
"$:/language/SideBar/Tools/Caption": {
"title": "$:/language/SideBar/Tools/Caption",
"text": "Tools"
},
"$:/language/SideBar/Types/Caption": {
"title": "$:/language/SideBar/Types/Caption",
"text": "Types"
},
"$:/SiteSubtitle": {
"title": "$:/SiteSubtitle",
"text": "a non-linear personal web notebook"
},
"$:/SiteTitle": {
"title": "$:/SiteTitle",
"text": "My ~TiddlyWiki"
},
"$:/language/Snippets/ListByTag": {
"title": "$:/language/Snippets/ListByTag",
"tags": "$:/tags/TextEditor/Snippet",
"caption": "List of tiddlers by tag",
"text": "<<list-links \"[tag[task]sort[title]]\">>\n"
},
"$:/language/Snippets/MacroDefinition": {
"title": "$:/language/Snippets/MacroDefinition",
"tags": "$:/tags/TextEditor/Snippet",
"caption": "Macro definition",
"text": "\\define macroName(param1:\"default value\",param2)\nText of the macro\n\\end\n"
},
"$:/language/Snippets/Table4x3": {
"title": "$:/language/Snippets/Table4x3",
"tags": "$:/tags/TextEditor/Snippet",
"caption": "Table with 4 columns by 3 rows",
"text": "|! |!Alpha |!Beta |!Gamma |!Delta |\n|!One | | | | |\n|!Two | | | | |\n|!Three | | | | |\n"
},
"$:/language/Snippets/TableOfContents": {
"title": "$:/language/Snippets/TableOfContents",
"tags": "$:/tags/TextEditor/Snippet",
"caption": "Table of Contents",
"text": "<div class=\"tc-table-of-contents\">\n\n<<toc-selective-expandable 'TableOfContents'>>\n\n</div>"
},
"$:/language/ThemeTweaks/ThemeTweaks": {
"title": "$:/language/ThemeTweaks/ThemeTweaks",
"text": "Theme Tweaks"
},
"$:/language/ThemeTweaks/ThemeTweaks/Hint": {
"title": "$:/language/ThemeTweaks/ThemeTweaks/Hint",
"text": "You can tweak certain aspects of the ''Vanilla'' theme."
},
"$:/language/ThemeTweaks/Options": {
"title": "$:/language/ThemeTweaks/Options",
"text": "Options"
},
"$:/language/ThemeTweaks/Options/SidebarLayout": {
"title": "$:/language/ThemeTweaks/Options/SidebarLayout",
"text": "Sidebar layout"
},
"$:/language/ThemeTweaks/Options/SidebarLayout/Fixed-Fluid": {
"title": "$:/language/ThemeTweaks/Options/SidebarLayout/Fixed-Fluid",
"text": "Fixed story, fluid sidebar"
},
"$:/language/ThemeTweaks/Options/SidebarLayout/Fluid-Fixed": {
"title": "$:/language/ThemeTweaks/Options/SidebarLayout/Fluid-Fixed",
"text": "Fluid story, fixed sidebar"
},
"$:/language/ThemeTweaks/Options/StickyTitles": {
"title": "$:/language/ThemeTweaks/Options/StickyTitles",
"text": "Sticky titles"
},
"$:/language/ThemeTweaks/Options/StickyTitles/Hint": {
"title": "$:/language/ThemeTweaks/Options/StickyTitles/Hint",
"text": "Causes tiddler titles to \"stick\" to the top of the browser window. Caution: Does not work at all with Chrome, and causes some layout issues in Firefox"
},
"$:/language/ThemeTweaks/Options/CodeWrapping": {
"title": "$:/language/ThemeTweaks/Options/CodeWrapping",
"text": "Wrap long lines in code blocks"
},
"$:/language/ThemeTweaks/Settings": {
"title": "$:/language/ThemeTweaks/Settings",
"text": "Settings"
},
"$:/language/ThemeTweaks/Settings/FontFamily": {
"title": "$:/language/ThemeTweaks/Settings/FontFamily",
"text": "Font family"
},
"$:/language/ThemeTweaks/Settings/CodeFontFamily": {
"title": "$:/language/ThemeTweaks/Settings/CodeFontFamily",
"text": "Code font family"
},
"$:/language/ThemeTweaks/Settings/BackgroundImage": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImage",
"text": "Page background image"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageAttachment": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageAttachment",
"text": "Page background image attachment"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageAttachment/Scroll": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageAttachment/Scroll",
"text": "Scroll with tiddlers"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageAttachment/Fixed": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageAttachment/Fixed",
"text": "Fixed to window"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageSize": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageSize",
"text": "Page background image size"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageSize/Auto": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageSize/Auto",
"text": "Auto"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageSize/Cover": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageSize/Cover",
"text": "Cover"
},
"$:/language/ThemeTweaks/Settings/BackgroundImageSize/Contain": {
"title": "$:/language/ThemeTweaks/Settings/BackgroundImageSize/Contain",
"text": "Contain"
},
"$:/language/ThemeTweaks/Metrics": {
"title": "$:/language/ThemeTweaks/Metrics",
"text": "Sizes"
},
"$:/language/ThemeTweaks/Metrics/FontSize": {
"title": "$:/language/ThemeTweaks/Metrics/FontSize",
"text": "Font size"
},
"$:/language/ThemeTweaks/Metrics/LineHeight": {
"title": "$:/language/ThemeTweaks/Metrics/LineHeight",
"text": "Line height"
},
"$:/language/ThemeTweaks/Metrics/BodyFontSize": {
"title": "$:/language/ThemeTweaks/Metrics/BodyFontSize",
"text": "Font size for tiddler body"
},
"$:/language/ThemeTweaks/Metrics/BodyLineHeight": {
"title": "$:/language/ThemeTweaks/Metrics/BodyLineHeight",
"text": "Line height for tiddler body"
},
"$:/language/ThemeTweaks/Metrics/StoryLeft": {
"title": "$:/language/ThemeTweaks/Metrics/StoryLeft",
"text": "Story left position"
},
"$:/language/ThemeTweaks/Metrics/StoryLeft/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/StoryLeft/Hint",
"text": "how far the left margin of the story river<br>(tiddler area) is from the left of the page"
},
"$:/language/ThemeTweaks/Metrics/StoryTop": {
"title": "$:/language/ThemeTweaks/Metrics/StoryTop",
"text": "Story top position"
},
"$:/language/ThemeTweaks/Metrics/StoryTop/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/StoryTop/Hint",
"text": "how far the top margin of the story river<br>is from the top of the page"
},
"$:/language/ThemeTweaks/Metrics/StoryRight": {
"title": "$:/language/ThemeTweaks/Metrics/StoryRight",
"text": "Story right"
},
"$:/language/ThemeTweaks/Metrics/StoryRight/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/StoryRight/Hint",
"text": "how far the left margin of the sidebar <br>is from the left of the page"
},
"$:/language/ThemeTweaks/Metrics/StoryWidth": {
"title": "$:/language/ThemeTweaks/Metrics/StoryWidth",
"text": "Story width"
},
"$:/language/ThemeTweaks/Metrics/StoryWidth/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/StoryWidth/Hint",
"text": "the overall width of the story river"
},
"$:/language/ThemeTweaks/Metrics/TiddlerWidth": {
"title": "$:/language/ThemeTweaks/Metrics/TiddlerWidth",
"text": "Tiddler width"
},
"$:/language/ThemeTweaks/Metrics/TiddlerWidth/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/TiddlerWidth/Hint",
"text": "within the story river"
},
"$:/language/ThemeTweaks/Metrics/SidebarBreakpoint": {
"title": "$:/language/ThemeTweaks/Metrics/SidebarBreakpoint",
"text": "Sidebar breakpoint"
},
"$:/language/ThemeTweaks/Metrics/SidebarBreakpoint/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/SidebarBreakpoint/Hint",
"text": "the minimum page width at which the story<br>river and sidebar will appear side by side"
},
"$:/language/ThemeTweaks/Metrics/SidebarWidth": {
"title": "$:/language/ThemeTweaks/Metrics/SidebarWidth",
"text": "Sidebar width"
},
"$:/language/ThemeTweaks/Metrics/SidebarWidth/Hint": {
"title": "$:/language/ThemeTweaks/Metrics/SidebarWidth/Hint",
"text": "the width of the sidebar in fluid-fixed layout"
},
"$:/language/TiddlerInfo/Advanced/Caption": {
"title": "$:/language/TiddlerInfo/Advanced/Caption",
"text": "Advanced"
},
"$:/language/TiddlerInfo/Advanced/PluginInfo/Empty/Hint": {
"title": "$:/language/TiddlerInfo/Advanced/PluginInfo/Empty/Hint",
"text": "none"
},
"$:/language/TiddlerInfo/Advanced/PluginInfo/Heading": {
"title": "$:/language/TiddlerInfo/Advanced/PluginInfo/Heading",
"text": "Plugin Details"
},
"$:/language/TiddlerInfo/Advanced/PluginInfo/Hint": {
"title": "$:/language/TiddlerInfo/Advanced/PluginInfo/Hint",
"text": "This plugin contains the following shadow tiddlers:"
},
"$:/language/TiddlerInfo/Advanced/ShadowInfo/Heading": {
"title": "$:/language/TiddlerInfo/Advanced/ShadowInfo/Heading",
"text": "Shadow Status"
},
"$:/language/TiddlerInfo/Advanced/ShadowInfo/NotShadow/Hint": {
"title": "$:/language/TiddlerInfo/Advanced/ShadowInfo/NotShadow/Hint",
"text": "The tiddler <$link to=<<infoTiddler>>><$text text=<<infoTiddler>>/></$link> is not a shadow tiddler"
},
"$:/language/TiddlerInfo/Advanced/ShadowInfo/Shadow/Hint": {
"title": "$:/language/TiddlerInfo/Advanced/ShadowInfo/Shadow/Hint",
"text": "The tiddler <$link to=<<infoTiddler>>><$text text=<<infoTiddler>>/></$link> is a shadow tiddler"
},
"$:/language/TiddlerInfo/Advanced/ShadowInfo/Shadow/Source": {
"title": "$:/language/TiddlerInfo/Advanced/ShadowInfo/Shadow/Source",
"text": "It is defined in the plugin <$link to=<<pluginTiddler>>><$text text=<<pluginTiddler>>/></$link>"
},
"$:/language/TiddlerInfo/Advanced/ShadowInfo/OverriddenShadow/Hint": {
"title": "$:/language/TiddlerInfo/Advanced/ShadowInfo/OverriddenShadow/Hint",
"text": "It is overridden by an ordinary tiddler"
},
"$:/language/TiddlerInfo/Fields/Caption": {
"title": "$:/language/TiddlerInfo/Fields/Caption",
"text": "Fields"
},
"$:/language/TiddlerInfo/List/Caption": {
"title": "$:/language/TiddlerInfo/List/Caption",
"text": "List"
},
"$:/language/TiddlerInfo/List/Empty": {
"title": "$:/language/TiddlerInfo/List/Empty",
"text": "This tiddler does not have a list"
},
"$:/language/TiddlerInfo/Listed/Caption": {
"title": "$:/language/TiddlerInfo/Listed/Caption",
"text": "Listed"
},
"$:/language/TiddlerInfo/Listed/Empty": {
"title": "$:/language/TiddlerInfo/Listed/Empty",
"text": "This tiddler is not listed by any others"
},
"$:/language/TiddlerInfo/References/Caption": {
"title": "$:/language/TiddlerInfo/References/Caption",
"text": "References"
},
"$:/language/TiddlerInfo/References/Empty": {
"title": "$:/language/TiddlerInfo/References/Empty",
"text": "No tiddlers link to this one"
},
"$:/language/TiddlerInfo/Tagging/Caption": {
"title": "$:/language/TiddlerInfo/Tagging/Caption",
"text": "Tagging"
},
"$:/language/TiddlerInfo/Tagging/Empty": {
"title": "$:/language/TiddlerInfo/Tagging/Empty",
"text": "No tiddlers are tagged with this one"
},
"$:/language/TiddlerInfo/Tools/Caption": {
"title": "$:/language/TiddlerInfo/Tools/Caption",
"text": "Tools"
},
"$:/language/Docs/Types/application/javascript": {
"title": "$:/language/Docs/Types/application/javascript",
"description": "JavaScript code",
"name": "application/javascript",
"group": "Developer"
},
"$:/language/Docs/Types/application/json": {
"title": "$:/language/Docs/Types/application/json",
"description": "JSON data",
"name": "application/json",
"group": "Developer"
},
"$:/language/Docs/Types/application/x-tiddler-dictionary": {
"title": "$:/language/Docs/Types/application/x-tiddler-dictionary",
"description": "Data dictionary",
"name": "application/x-tiddler-dictionary",
"group": "Developer"
},
"$:/language/Docs/Types/image/gif": {
"title": "$:/language/Docs/Types/image/gif",
"description": "GIF image",
"name": "image/gif",
"group": "Image"
},
"$:/language/Docs/Types/image/jpeg": {
"title": "$:/language/Docs/Types/image/jpeg",
"description": "JPEG image",
"name": "image/jpeg",
"group": "Image"
},
"$:/language/Docs/Types/image/png": {
"title": "$:/language/Docs/Types/image/png",
"description": "PNG image",
"name": "image/png",
"group": "Image"
},
"$:/language/Docs/Types/image/svg+xml": {
"title": "$:/language/Docs/Types/image/svg+xml",
"description": "Structured Vector Graphics image",
"name": "image/svg+xml",
"group": "Image"
},
"$:/language/Docs/Types/image/x-icon": {
"title": "$:/language/Docs/Types/image/x-icon",
"description": "ICO format icon file",
"name": "image/x-icon",
"group": "Image"
},
"$:/language/Docs/Types/text/css": {
"title": "$:/language/Docs/Types/text/css",
"description": "Static stylesheet",
"name": "text/css",
"group": "Developer"
},
"$:/language/Docs/Types/text/html": {
"title": "$:/language/Docs/Types/text/html",
"description": "HTML markup",
"name": "text/html",
"group": "Text"
},
"$:/language/Docs/Types/text/plain": {
"title": "$:/language/Docs/Types/text/plain",
"description": "Plain text",
"name": "text/plain",
"group": "Text"
},
"$:/language/Docs/Types/text/vnd.tiddlywiki": {
"title": "$:/language/Docs/Types/text/vnd.tiddlywiki",
"description": "TiddlyWiki 5",
"name": "text/vnd.tiddlywiki",
"group": "Text"
},
"$:/language/Docs/Types/text/x-tiddlywiki": {
"title": "$:/language/Docs/Types/text/x-tiddlywiki",
"description": "TiddlyWiki Classic",
"name": "text/x-tiddlywiki",
"group": "Text"
},
"$:/languages/en-GB/icon": {
"title": "$:/languages/en-GB/icon",
"type": "image/svg+xml",
"text": "<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 60 30\" width=\"1200\" height=\"600\">\n<clipPath id=\"t\">\n\t<path d=\"M30,15 h30 v15 z v15 h-30 z h-30 v-15 z v-15 h30 z\"/>\n</clipPath>\n<path d=\"M0,0 v30 h60 v-30 z\" fill=\"#00247d\"/>\n<path d=\"M0,0 L60,30 M60,0 L0,30\" stroke=\"#fff\" stroke-width=\"6\"/>\n<path d=\"M0,0 L60,30 M60,0 L0,30\" clip-path=\"url(#t)\" stroke=\"#cf142b\" stroke-width=\"4\"/>\n<path d=\"M30,0 v30 M0,15 h60\" stroke=\"#fff\" stroke-width=\"10\"/>\n<path d=\"M30,0 v30 M0,15 h60\" stroke=\"#cf142b\" stroke-width=\"6\"/>\n</svg>\n"
},
"$:/languages/en-GB": {
"title": "$:/languages/en-GB",
"name": "en-GB",
"description": "English (British)",
"author": "JeremyRuston",
"core-version": ">=5.0.0\"",
"text": "Stub pseudo-plugin for the default language"
},
"$:/core/modules/commander.js": {
"text": "/*\\\ntitle: $:/core/modules/commander.js\ntype: application/javascript\nmodule-type: global\n\nThe $tw.Commander class is a command interpreter\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nParse a sequence of commands\n\tcommandTokens: an array of command string tokens\n\twiki: reference to the wiki store object\n\tstreams: {output:, error:}, each of which has a write(string) method\n\tcallback: a callback invoked as callback(err) where err is null if there was no error\n*/\nvar Commander = function(commandTokens,callback,wiki,streams) {\n\tvar path = require(\"path\");\n\tthis.commandTokens = commandTokens;\n\tthis.nextToken = 0;\n\tthis.callback = callback;\n\tthis.wiki = wiki;\n\tthis.streams = streams;\n\tthis.outputPath = path.resolve($tw.boot.wikiPath,$tw.config.wikiOutputSubDir);\n};\n\n/*\nAdd a string of tokens to the command queue\n*/\nCommander.prototype.addCommandTokens = function(commandTokens) {\n\tvar params = commandTokens.slice(0);\n\tparams.unshift(0);\n\tparams.unshift(this.nextToken);\n\tArray.prototype.splice.apply(this.commandTokens,params);\n};\n\n/*\nExecute the sequence of commands and invoke a callback on completion\n*/\nCommander.prototype.execute = function() {\n\tthis.executeNextCommand();\n};\n\n/*\nExecute the next command in the sequence\n*/\nCommander.prototype.executeNextCommand = function() {\n\tvar self = this;\n\t// Invoke the callback if there are no more commands\n\tif(this.nextToken >= this.commandTokens.length) {\n\t\tthis.callback(null);\n\t} else {\n\t\t// Get and check the command token\n\t\tvar commandName = this.commandTokens[this.nextToken++];\n\t\tif(commandName.substr(0,2) !== \"--\") {\n\t\t\tthis.callback(\"Missing command: \" + commandName);\n\t\t} else {\n\t\t\tcommandName = commandName.substr(2); // Trim off the --\n\t\t\t// Accumulate the parameters to the command\n\t\t\tvar params = [];\n\t\t\twhile(this.nextToken < this.commandTokens.length && \n\t\t\t\tthis.commandTokens[this.nextToken].substr(0,2) !== \"--\") {\n\t\t\t\tparams.push(this.commandTokens[this.nextToken++]);\n\t\t\t}\n\t\t\t// Get the command info\n\t\t\tvar command = $tw.commands[commandName],\n\t\t\t\tc,err;\n\t\t\tif(!command) {\n\t\t\t\tthis.callback(\"Unknown command: \" + commandName);\n\t\t\t} else {\n\t\t\t\tif(this.verbose) {\n\t\t\t\t\tthis.streams.output.write(\"Executing command: \" + commandName + \" \" + params.join(\" \") + \"\\n\");\n\t\t\t\t}\n\t\t\t\tif(command.info.synchronous) {\n\t\t\t\t\t// Synchronous command\n\t\t\t\t\tc = new command.Command(params,this);\n\t\t\t\t\terr = c.execute();\n\t\t\t\t\tif(err) {\n\t\t\t\t\t\tthis.callback(err);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tthis.executeNextCommand();\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\t// Asynchronous command\n\t\t\t\t\tc = new command.Command(params,this,function(err) {\n\t\t\t\t\t\tif(err) {\n\t\t\t\t\t\t\tself.callback(err);\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\tself.executeNextCommand();\n\t\t\t\t\t\t}\n\t\t\t\t\t});\n\t\t\t\t\terr = c.execute();\n\t\t\t\t\tif(err) {\n\t\t\t\t\t\tthis.callback(err);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n};\n\nCommander.initCommands = function(moduleType) {\n\tmoduleType = moduleType || \"command\";\n\t$tw.commands = {};\n\t$tw.modules.forEachModuleOfType(moduleType,function(title,module) {\n\t\tvar c = $tw.commands[module.info.name] = {};\n\t\t// Add the methods defined by the module\n\t\tfor(var f in module) {\n\t\t\tif($tw.utils.hop(module,f)) {\n\t\t\t\tc[f] = module[f];\n\t\t\t}\n\t\t}\n\t});\n};\n\nexports.Commander = Commander;\n\n})();\n",
"title": "$:/core/modules/commander.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/commands/build.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/build.js\ntype: application/javascript\nmodule-type: command\n\nCommand to build a build target\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"build\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\t// Get the build targets defined in the wiki\n\tvar buildTargets = $tw.boot.wikiInfo.build;\n\tif(!buildTargets) {\n\t\treturn \"No build targets defined\";\n\t}\n\t// Loop through each of the specified targets\n\tvar targets;\n\tif(this.params.length > 0) {\n\t\ttargets = this.params;\n\t} else {\n\t\ttargets = Object.keys(buildTargets);\n\t}\n\tfor(var targetIndex=0; targetIndex<targets.length; targetIndex++) {\n\t\tvar target = targets[targetIndex],\n\t\t\tcommands = buildTargets[target];\n\t\tif(!commands) {\n\t\t\treturn \"Build target '\" + target + \"' not found\";\n\t\t}\n\t\t// Add the commands to the queue\n\t\tthis.commander.addCommandTokens(commands);\n\t}\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/build.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/clearpassword.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/clearpassword.js\ntype: application/javascript\nmodule-type: command\n\nClear password for crypto operations\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"clearpassword\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\t$tw.crypto.setPassword(null);\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/clearpassword.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/editions.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/editions.js\ntype: application/javascript\nmodule-type: command\n\nCommand to list the available editions\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"editions\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\tvar self = this;\n\t// Output the list\n\tthis.commander.streams.output.write(\"Available editions:\\n\\n\");\n\tvar editionInfo = $tw.utils.getEditionInfo();\n\t$tw.utils.each(editionInfo,function(info,name) {\n\t\tself.commander.streams.output.write(\" \" + name + \": \" + info.description + \"\\n\");\n\t});\n\tthis.commander.streams.output.write(\"\\n\");\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/editions.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/help.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/help.js\ntype: application/javascript\nmodule-type: command\n\nHelp command\n\n\\*/\n(function(){\n\n/*jshint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"help\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\tvar subhelp = this.params[0] || \"default\",\n\t\thelpBase = \"$:/language/Help/\",\n\t\ttext;\n\tif(!this.commander.wiki.getTiddler(helpBase + subhelp)) {\n\t\tsubhelp = \"notfound\";\n\t}\n\t// Wikify the help as formatted text (ie block elements generate newlines)\n\ttext = this.commander.wiki.renderTiddler(\"text/plain-formatted\",helpBase + subhelp);\n\t// Remove any leading linebreaks\n\ttext = text.replace(/^(\\r?\\n)*/g,\"\");\n\tthis.commander.streams.output.write(text);\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/help.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/init.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/init.js\ntype: application/javascript\nmodule-type: command\n\nCommand to initialise an empty wiki folder\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"init\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\tvar fs = require(\"fs\"),\n\t\tpath = require(\"path\");\n\t// Check that we don't already have a valid wiki folder\n\tif($tw.boot.wikiTiddlersPath || ($tw.utils.isDirectory($tw.boot.wikiPath) && !$tw.utils.isDirectoryEmpty($tw.boot.wikiPath))) {\n\t\treturn \"Wiki folder is not empty\";\n\t}\n\t// Loop through each of the specified editions\n\tvar editions = this.params.length > 0 ? this.params : [\"empty\"];\n\tfor(var editionIndex=0; editionIndex<editions.length; editionIndex++) {\n\t\tvar editionName = editions[editionIndex];\n\t\t// Check the edition exists\n\t\tvar editionPath = $tw.findLibraryItem(editionName,$tw.getLibraryItemSearchPaths($tw.config.editionsPath,$tw.config.editionsEnvVar));\n\t\tif(!$tw.utils.isDirectory(editionPath)) {\n\t\t\treturn \"Edition '\" + editionName + \"' not found\";\n\t\t}\n\t\t// Copy the edition content\n\t\tvar err = $tw.utils.copyDirectory(editionPath,$tw.boot.wikiPath);\n\t\tif(!err) {\n\t\t\tthis.commander.streams.output.write(\"Copied edition '\" + editionName + \"' to \" + $tw.boot.wikiPath + \"\\n\");\n\t\t} else {\n\t\t\treturn err;\n\t\t}\n\t}\n\t// Tweak the tiddlywiki.info to remove any included wikis\n\tvar packagePath = $tw.boot.wikiPath + \"/tiddlywiki.info\",\n\t\tpackageJson = JSON.parse(fs.readFileSync(packagePath));\n\tdelete packageJson.includeWikis;\n\tfs.writeFileSync(packagePath,JSON.stringify(packageJson,null,$tw.config.preferences.jsonSpaces));\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/init.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/load.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/load.js\ntype: application/javascript\nmodule-type: command\n\nCommand to load tiddlers from a file\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"load\",\n\tsynchronous: false\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\");\n\tif(this.params.length < 1) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar ext = path.extname(self.params[0]);\n\tfs.readFile(this.params[0],$tw.utils.getTypeEncoding(ext),function(err,data) {\n\t\tif (err) {\n\t\t\tself.callback(err);\n\t\t} else {\n\t\t\tvar fields = {title: self.params[0]},\n\t\t\t\ttype = path.extname(self.params[0]);\n\t\t\tvar tiddlers = self.commander.wiki.deserializeTiddlers(type,data,fields);\n\t\t\tif(!tiddlers) {\n\t\t\t\tself.callback(\"No tiddlers found in file \\\"\" + self.params[0] + \"\\\"\");\n\t\t\t} else {\n\t\t\t\tfor(var t=0; t<tiddlers.length; t++) {\n\t\t\t\t\tself.commander.wiki.importTiddler(new $tw.Tiddler(tiddlers[t]));\n\t\t\t\t}\n\t\t\t\tself.callback(null);\t\n\t\t\t}\n\t\t}\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/load.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/makelibrary.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/makelibrary.js\ntype: application/javascript\nmodule-type: command\n\nCommand to pack all of the plugins in the library into a plugin tiddler of type \"library\"\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"makelibrary\",\n\tsynchronous: true\n};\n\nvar UPGRADE_LIBRARY_TITLE = \"$:/UpgradeLibrary\";\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tvar wiki = this.commander.wiki,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\tupgradeLibraryTitle = this.params[0] || UPGRADE_LIBRARY_TITLE,\n\t\ttiddlers = {};\n\t// Collect up the library plugins\n\tvar collectPlugins = function(folder) {\n\t\t\tvar pluginFolders = fs.readdirSync(folder);\n\t\t\tfor(var p=0; p<pluginFolders.length; p++) {\n\t\t\t\tif(!$tw.boot.excludeRegExp.test(pluginFolders[p])) {\n\t\t\t\t\tpluginFields = $tw.loadPluginFolder(path.resolve(folder,\"./\" + pluginFolders[p]));\n\t\t\t\t\tif(pluginFields && pluginFields.title) {\n\t\t\t\t\t\ttiddlers[pluginFields.title] = pluginFields;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t},\n\t\tcollectPublisherPlugins = function(folder) {\n\t\t\tvar publisherFolders = fs.readdirSync(folder);\n\t\t\tfor(var t=0; t<publisherFolders.length; t++) {\n\t\t\t\tif(!$tw.boot.excludeRegExp.test(publisherFolders[t])) {\n\t\t\t\t\tcollectPlugins(path.resolve(folder,\"./\" + publisherFolders[t]));\n\t\t\t\t}\n\t\t\t}\n\t\t};\n\tcollectPublisherPlugins(path.resolve($tw.boot.corePath,$tw.config.pluginsPath));\n\tcollectPublisherPlugins(path.resolve($tw.boot.corePath,$tw.config.themesPath));\n\tcollectPlugins(path.resolve($tw.boot.corePath,$tw.config.languagesPath));\n\t// Save the upgrade library tiddler\n\tvar pluginFields = {\n\t\ttitle: upgradeLibraryTitle,\n\t\ttype: \"application/json\",\n\t\t\"plugin-type\": \"library\",\n\t\t\"text\": JSON.stringify({tiddlers: tiddlers},null,$tw.config.preferences.jsonSpaces)\n\t};\n\twiki.addTiddler(new $tw.Tiddler(pluginFields));\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/makelibrary.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/output.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/output.js\ntype: application/javascript\nmodule-type: command\n\nCommand to set the default output location (defaults to current working directory)\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"output\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tvar fs = require(\"fs\"),\n\t\tpath = require(\"path\");\n\tif(this.params.length < 1) {\n\t\treturn \"Missing output path\";\n\t}\n\tthis.commander.outputPath = path.resolve(process.cwd(),this.params[0]);\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/output.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/password.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/password.js\ntype: application/javascript\nmodule-type: command\n\nSave password for crypto operations\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"password\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 1) {\n\t\treturn \"Missing password\";\n\t}\n\t$tw.crypto.setPassword(this.params[0]);\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/password.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/rendertiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/rendertiddler.js\ntype: application/javascript\nmodule-type: command\n\nCommand to render a tiddler and save it to a file\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"rendertiddler\",\n\tsynchronous: false\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 2) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\ttitle = this.params[0],\n\t\tfilename = path.resolve(this.commander.outputPath,this.params[1]),\n\t\ttype = this.params[2] || \"text/html\",\n\t\ttemplate = this.params[3],\n\t\tvariables = {};\n\t$tw.utils.createFileDirectories(filename);\n\tif(template) {\n\t\tvariables.currentTiddler = title;\n\t\ttitle = template;\n\t}\n\tfs.writeFile(filename,this.commander.wiki.renderTiddler(type,title,{variables: variables}),\"utf8\",function(err) {\n\t\tself.callback(err);\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/rendertiddler.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/rendertiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/rendertiddlers.js\ntype: application/javascript\nmodule-type: command\n\nCommand to render several tiddlers to a folder of files\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nexports.info = {\n\tname: \"rendertiddlers\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 2) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\twiki = this.commander.wiki,\n\t\tfilter = this.params[0],\n\t\ttemplate = this.params[1],\n\t\toutputPath = this.commander.outputPath,\n\t\tpathname = path.resolve(outputPath,this.params[2]),\t\t\n\t\ttype = this.params[3] || \"text/html\",\n\t\textension = this.params[4] || \".html\",\n\t\tdeleteDirectory = (this.params[5] || \"\").toLowerCase() !== \"noclean\",\n\t\ttiddlers = wiki.filterTiddlers(filter);\n\tif(deleteDirectory) {\n\t\t$tw.utils.deleteDirectory(pathname);\n\t}\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar parser = wiki.parseTiddler(template),\n\t\t\twidgetNode = wiki.makeWidget(parser,{variables: {currentTiddler: title}}),\n\t\t\tcontainer = $tw.fakeDocument.createElement(\"div\");\n\t\twidgetNode.render(container,null);\n\t\tvar text = type === \"text/html\" ? container.innerHTML : container.textContent,\n\t\t\texportPath = null;\n\t\tif($tw.utils.hop($tw.macros,\"tv-get-export-path\")) {\n\t\t\tvar macroPath = $tw.macros[\"tv-get-export-path\"].run.apply(self,[title]);\n\t\t\tif(macroPath) {\n\t\t\t\texportPath = path.resolve(outputPath,macroPath + extension);\n\t\t\t}\n\t\t}\n\t\tvar finalPath = exportPath || path.resolve(pathname,encodeURIComponent(title) + extension);\n\t\t$tw.utils.createFileDirectories(finalPath);\n\t\tfs.writeFileSync(finalPath,text,\"utf8\");\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/rendertiddlers.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/savelibrarytiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/savelibrarytiddlers.js\ntype: application/javascript\nmodule-type: command\n\nCommand to save the subtiddlers of a bundle tiddler as a series of JSON files\n\n--savelibrarytiddlers <tiddler> <pathname> <skinnylisting>\n\nThe tiddler identifies the bundle tiddler that contains the subtiddlers.\n\nThe pathname specifies the pathname to the folder in which the JSON files should be saved. The filename is the URL encoded title of the subtiddler.\n\nThe skinnylisting specifies the title of the tiddler to which a JSON catalogue of the subtiddlers will be saved. The JSON file contains the same data as the bundle tiddler but with the `text` field removed.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"savelibrarytiddlers\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 2) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\tcontainerTitle = this.params[0],\n\t\tfilter = this.params[1],\n\t\tbasepath = this.params[2],\n\t\tskinnyListTitle = this.params[3];\n\t// Get the container tiddler as data\n\tvar containerData = self.commander.wiki.getTiddlerDataCached(containerTitle,undefined);\n\tif(!containerData) {\n\t\treturn \"'\" + containerTitle + \"' is not a tiddler bundle\";\n\t}\n\t// Filter the list of plugins\n\tvar pluginList = [];\n\t$tw.utils.each(containerData.tiddlers,function(tiddler,title) {\n\t\tpluginList.push(title);\n\t});\n\tvar filteredPluginList;\n\tif(filter) {\n\t\tfilteredPluginList = self.commander.wiki.filterTiddlers(filter,null,self.commander.wiki.makeTiddlerIterator(pluginList));\n\t} else {\n\t\tfilteredPluginList = pluginList;\n\t}\n\t// Iterate through the plugins\n\tvar skinnyList = [];\n\t$tw.utils.each(filteredPluginList,function(title) {\n\t\tvar tiddler = containerData.tiddlers[title];\n\t\t// Save each JSON file and collect the skinny data\n\t\tvar pathname = path.resolve(self.commander.outputPath,basepath + encodeURIComponent(title) + \".json\");\n\t\t$tw.utils.createFileDirectories(pathname);\n\t\tfs.writeFileSync(pathname,JSON.stringify(tiddler,null,$tw.config.preferences.jsonSpaces),\"utf8\");\n\t\t// Collect the skinny list data\n\t\tvar pluginTiddlers = JSON.parse(tiddler.text),\n\t\t\treadmeContent = (pluginTiddlers.tiddlers[title + \"/readme\"] || {}).text,\n\t\t\ticonTiddler = pluginTiddlers.tiddlers[title + \"/icon\"] || {},\n\t\t\ticonType = iconTiddler.type,\n\t\t\ticonText = iconTiddler.text,\n\t\t\ticonContent;\n\t\tif(iconType && iconText) {\n\t\t\ticonContent = $tw.utils.makeDataUri(iconText,iconType);\n\t\t}\n\t\tskinnyList.push($tw.utils.extend({},tiddler,{text: undefined, readme: readmeContent, icon: iconContent}));\n\t});\n\t// Save the catalogue tiddler\n\tif(skinnyListTitle) {\n\t\tself.commander.wiki.setTiddlerData(skinnyListTitle,skinnyList);\n\t}\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/savelibrarytiddlers.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/savetiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/savetiddler.js\ntype: application/javascript\nmodule-type: command\n\nCommand to save the content of a tiddler to a file\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"savetiddler\",\n\tsynchronous: false\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 2) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\ttitle = this.params[0],\n\t\tfilename = path.resolve(this.commander.outputPath,this.params[1]),\n\t\ttiddler = this.commander.wiki.getTiddler(title);\n\tif(tiddler) {\n\t\tvar type = tiddler.fields.type || \"text/vnd.tiddlywiki\",\n\t\t\tcontentTypeInfo = $tw.config.contentTypeInfo[type] || {encoding: \"utf8\"};\n\t\t$tw.utils.createFileDirectories(filename);\n\t\tfs.writeFile(filename,tiddler.fields.text,contentTypeInfo.encoding,function(err) {\n\t\t\tself.callback(err);\n\t\t});\n\t} else {\n\t\treturn \"Missing tiddler: \" + title;\n\t}\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/savetiddler.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/savetiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/savetiddlers.js\ntype: application/javascript\nmodule-type: command\n\nCommand to save several tiddlers to a folder of files\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nexports.info = {\n\tname: \"savetiddlers\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 1) {\n\t\treturn \"Missing filename\";\n\t}\n\tvar self = this,\n\t\tfs = require(\"fs\"),\n\t\tpath = require(\"path\"),\n\t\twiki = this.commander.wiki,\n\t\tfilter = this.params[0],\n\t\tpathname = path.resolve(this.commander.outputPath,this.params[1]),\n\t\tdeleteDirectory = (this.params[2] || \"\").toLowerCase() !== \"noclean\",\n\t\ttiddlers = wiki.filterTiddlers(filter);\n\tif(deleteDirectory) {\n\t\t$tw.utils.deleteDirectory(pathname);\n\t}\n\t$tw.utils.createDirectory(pathname);\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar tiddler = self.commander.wiki.getTiddler(title),\n\t\t\ttype = tiddler.fields.type || \"text/vnd.tiddlywiki\",\n\t\t\tcontentTypeInfo = $tw.config.contentTypeInfo[type] || {encoding: \"utf8\"},\n\t\t\tfilename = path.resolve(pathname,encodeURIComponent(title));\n\t\tfs.writeFileSync(filename,tiddler.fields.text,contentTypeInfo.encoding);\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/savetiddlers.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/server.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/server.js\ntype: application/javascript\nmodule-type: command\n\nServe tiddlers over http\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nif($tw.node) {\n\tvar util = require(\"util\"),\n\t\tfs = require(\"fs\"),\n\t\turl = require(\"url\"),\n\t\tpath = require(\"path\"),\n\t\thttp = require(\"http\");\n}\n\nexports.info = {\n\tname: \"server\",\n\tsynchronous: true\n};\n\n/*\nA simple HTTP server with regexp-based routes\n*/\nfunction SimpleServer(options) {\n\tthis.routes = options.routes || [];\n\tthis.wiki = options.wiki;\n\tthis.variables = options.variables || {};\n}\n\nSimpleServer.prototype.set = function(obj) {\n\tvar self = this;\n\t$tw.utils.each(obj,function(value,name) {\n\t\tself.variables[name] = value;\n\t});\n};\n\nSimpleServer.prototype.get = function(name) {\n\treturn this.variables[name];\n};\n\nSimpleServer.prototype.addRoute = function(route) {\n\tthis.routes.push(route);\n};\n\nSimpleServer.prototype.findMatchingRoute = function(request,state) {\n\tvar pathprefix = this.get(\"pathprefix\") || \"\";\n\tfor(var t=0; t<this.routes.length; t++) {\n\t\tvar potentialRoute = this.routes[t],\n\t\t\tpathRegExp = potentialRoute.path,\n\t\t\tpathname = state.urlInfo.pathname,\n\t\t\tmatch;\n\t\tif(pathprefix) {\n\t\t\tif(pathname.substr(0,pathprefix.length) === pathprefix) {\n\t\t\t\tpathname = pathname.substr(pathprefix.length);\n\t\t\t\tmatch = potentialRoute.path.exec(pathname);\n\t\t\t} else {\n\t\t\t\tmatch = false;\n\t\t\t}\n\t\t} else {\n\t\t\tmatch = potentialRoute.path.exec(pathname);\n\t\t}\n\t\tif(match && request.method === potentialRoute.method) {\n\t\t\tstate.params = [];\n\t\t\tfor(var p=1; p<match.length; p++) {\n\t\t\t\tstate.params.push(match[p]);\n\t\t\t}\n\t\t\treturn potentialRoute;\n\t\t}\n\t}\n\treturn null;\n};\n\nSimpleServer.prototype.checkCredentials = function(request,incomingUsername,incomingPassword) {\n\tvar header = request.headers.authorization || \"\",\n\t\ttoken = header.split(/\\s+/).pop() || \"\",\n\t\tauth = $tw.utils.base64Decode(token),\n\t\tparts = auth.split(/:/),\n\t\tusername = parts[0],\n\t\tpassword = parts[1];\n\tif(incomingUsername === username && incomingPassword === password) {\n\t\treturn \"ALLOWED\";\n\t} else {\n\t\treturn \"DENIED\";\n\t}\n};\n\nSimpleServer.prototype.listen = function(port,host) {\n\tvar self = this;\n\thttp.createServer(function(request,response) {\n\t\t// Compose the state object\n\t\tvar state = {};\n\t\tstate.wiki = self.wiki;\n\t\tstate.server = self;\n\t\tstate.urlInfo = url.parse(request.url);\n\t\t// Find the route that matches this path\n\t\tvar route = self.findMatchingRoute(request,state);\n\t\t// Check for the username and password if we've got one\n\t\tvar username = self.get(\"username\"),\n\t\t\tpassword = self.get(\"password\");\n\t\tif(username && password) {\n\t\t\t// Check they match\n\t\t\tif(self.checkCredentials(request,username,password) !== \"ALLOWED\") {\n\t\t\t\tvar servername = state.wiki.getTiddlerText(\"$:/SiteTitle\") || \"TiddlyWiki5\";\n\t\t\t\tresponse.writeHead(401,\"Authentication required\",{\n\t\t\t\t\t\"WWW-Authenticate\": 'Basic realm=\"Please provide your username and password to login to ' + servername + '\"'\n\t\t\t\t});\n\t\t\t\tresponse.end();\n\t\t\t\treturn;\n\t\t\t}\n\t\t}\n\t\t// Return a 404 if we didn't find a route\n\t\tif(!route) {\n\t\t\tresponse.writeHead(404);\n\t\t\tresponse.end();\n\t\t\treturn;\n\t\t}\n\t\t// Set the encoding for the incoming request\n\t\t// TODO: Presumably this would need tweaking if we supported PUTting binary tiddlers\n\t\trequest.setEncoding(\"utf8\");\n\t\t// Dispatch the appropriate method\n\t\tswitch(request.method) {\n\t\t\tcase \"GET\": // Intentional fall-through\n\t\t\tcase \"DELETE\":\n\t\t\t\troute.handler(request,response,state);\n\t\t\t\tbreak;\n\t\t\tcase \"PUT\":\n\t\t\t\tvar data = \"\";\n\t\t\t\trequest.on(\"data\",function(chunk) {\n\t\t\t\t\tdata += chunk.toString();\n\t\t\t\t});\n\t\t\t\trequest.on(\"end\",function() {\n\t\t\t\t\tstate.data = data;\n\t\t\t\t\troute.handler(request,response,state);\n\t\t\t\t});\n\t\t\t\tbreak;\n\t\t}\n\t}).listen(port,host);\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n\t// Set up server\n\tthis.server = new SimpleServer({\n\t\twiki: this.commander.wiki\n\t});\n\t// Add route handlers\n\tthis.server.addRoute({\n\t\tmethod: \"PUT\",\n\t\tpath: /^\\/recipes\\/default\\/tiddlers\\/(.+)$/,\n\t\thandler: function(request,response,state) {\n\t\t\tvar title = decodeURIComponent(state.params[0]),\n\t\t\t\tfields = JSON.parse(state.data);\n\t\t\t// Pull up any subfields in the `fields` object\n\t\t\tif(fields.fields) {\n\t\t\t\t$tw.utils.each(fields.fields,function(field,name) {\n\t\t\t\t\tfields[name] = field;\n\t\t\t\t});\n\t\t\t\tdelete fields.fields;\n\t\t\t}\n\t\t\t// Remove any revision field\n\t\t\tif(fields.revision) {\n\t\t\t\tdelete fields.revision;\n\t\t\t}\n\t\t\tstate.wiki.addTiddler(new $tw.Tiddler(state.wiki.getCreationFields(),fields,{title: title},state.wiki.getModificationFields()));\n\t\t\tvar changeCount = state.wiki.getChangeCount(title).toString();\n\t\t\tresponse.writeHead(204, \"OK\",{\n\t\t\t\tEtag: \"\\\"default/\" + encodeURIComponent(title) + \"/\" + changeCount + \":\\\"\",\n\t\t\t\t\"Content-Type\": \"text/plain\"\n\t\t\t});\n\t\t\tresponse.end();\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"DELETE\",\n\t\tpath: /^\\/bags\\/default\\/tiddlers\\/(.+)$/,\n\t\thandler: function(request,response,state) {\n\t\t\tvar title = decodeURIComponent(state.params[0]);\n\t\t\tstate.wiki.deleteTiddler(title);\n\t\t\tresponse.writeHead(204, \"OK\", {\n\t\t\t\t\"Content-Type\": \"text/plain\"\n\t\t\t});\n\t\t\tresponse.end();\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"GET\",\n\t\tpath: /^\\/$/,\n\t\thandler: function(request,response,state) {\n\t\t\tresponse.writeHead(200, {\"Content-Type\": state.server.get(\"serveType\")});\n\t\t\tvar text = state.wiki.renderTiddler(state.server.get(\"renderType\"),state.server.get(\"rootTiddler\"));\n\t\t\tresponse.end(text,\"utf8\");\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"GET\",\n\t\tpath: /^\\/status$/,\n\t\thandler: function(request,response,state) {\n\t\t\tresponse.writeHead(200, {\"Content-Type\": \"application/json\"});\n\t\t\tvar text = JSON.stringify({\n\t\t\t\tusername: state.server.get(\"username\"),\n\t\t\t\tspace: {\n\t\t\t\t\trecipe: \"default\"\n\t\t\t\t},\n\t\t\t\ttiddlywiki_version: $tw.version\n\t\t\t});\n\t\t\tresponse.end(text,\"utf8\");\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"GET\",\n\t\tpath: /^\\/favicon.ico$/,\n\t\thandler: function(request,response,state) {\n\t\t\tresponse.writeHead(200, {\"Content-Type\": \"image/x-icon\"});\n\t\t\tvar buffer = state.wiki.getTiddlerText(\"$:/favicon.ico\",\"\");\n\t\t\tresponse.end(buffer,\"base64\");\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"GET\",\n\t\tpath: /^\\/recipes\\/default\\/tiddlers.json$/,\n\t\thandler: function(request,response,state) {\n\t\t\tresponse.writeHead(200, {\"Content-Type\": \"application/json\"});\n\t\t\tvar tiddlers = [];\n\t\t\tstate.wiki.forEachTiddler({sortField: \"title\"},function(title,tiddler) {\n\t\t\t\tvar tiddlerFields = {};\n\t\t\t\t$tw.utils.each(tiddler.fields,function(field,name) {\n\t\t\t\t\tif(name !== \"text\") {\n\t\t\t\t\t\ttiddlerFields[name] = tiddler.getFieldString(name);\n\t\t\t\t\t}\n\t\t\t\t});\n\t\t\t\ttiddlerFields.revision = state.wiki.getChangeCount(title);\n\t\t\t\ttiddlerFields.type = tiddlerFields.type || \"text/vnd.tiddlywiki\";\n\t\t\t\ttiddlers.push(tiddlerFields);\n\t\t\t});\n\t\t\tvar text = JSON.stringify(tiddlers);\n\t\t\tresponse.end(text,\"utf8\");\n\t\t}\n\t});\n\tthis.server.addRoute({\n\t\tmethod: \"GET\",\n\t\tpath: /^\\/recipes\\/default\\/tiddlers\\/(.+)$/,\n\t\thandler: function(request,response,state) {\n\t\t\tvar title = decodeURIComponent(state.params[0]),\n\t\t\t\ttiddler = state.wiki.getTiddler(title),\n\t\t\t\ttiddlerFields = {},\n\t\t\t\tknownFields = [\n\t\t\t\t\t\"bag\", \"created\", \"creator\", \"modified\", \"modifier\", \"permissions\", \"recipe\", \"revision\", \"tags\", \"text\", \"title\", \"type\", \"uri\"\n\t\t\t\t];\n\t\t\tif(tiddler) {\n\t\t\t\t$tw.utils.each(tiddler.fields,function(field,name) {\n\t\t\t\t\tvar value = tiddler.getFieldString(name);\n\t\t\t\t\tif(knownFields.indexOf(name) !== -1) {\n\t\t\t\t\t\ttiddlerFields[name] = value;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ttiddlerFields.fields = tiddlerFields.fields || {};\n\t\t\t\t\t\ttiddlerFields.fields[name] = value;\n\t\t\t\t\t}\n\t\t\t\t});\n\t\t\t\ttiddlerFields.revision = state.wiki.getChangeCount(title);\n\t\t\t\ttiddlerFields.type = tiddlerFields.type || \"text/vnd.tiddlywiki\";\n\t\t\t\tresponse.writeHead(200, {\"Content-Type\": \"application/json\"});\n\t\t\t\tresponse.end(JSON.stringify(tiddlerFields),\"utf8\");\n\t\t\t} else {\n\t\t\t\tresponse.writeHead(404);\n\t\t\t\tresponse.end();\n\t\t\t}\n\t\t}\n\t});\n};\n\nCommand.prototype.execute = function() {\n\tif(!$tw.boot.wikiTiddlersPath) {\n\t\t$tw.utils.warning(\"Warning: Wiki folder '\" + $tw.boot.wikiPath + \"' does not exist or is missing a tiddlywiki.info file\");\n\t}\n\tvar port = this.params[0] || \"8080\",\n\t\trootTiddler = this.params[1] || \"$:/core/save/all\",\n\t\trenderType = this.params[2] || \"text/plain\",\n\t\tserveType = this.params[3] || \"text/html\",\n\t\tusername = this.params[4],\n\t\tpassword = this.params[5],\n\t\thost = this.params[6] || \"127.0.0.1\",\n\t\tpathprefix = this.params[7];\n\tthis.server.set({\n\t\trootTiddler: rootTiddler,\n\t\trenderType: renderType,\n\t\tserveType: serveType,\n\t\tusername: username,\n\t\tpassword: password,\n\t\tpathprefix: pathprefix\n\t});\n\tthis.server.listen(port,host);\n\tconsole.log(\"Serving on \" + host + \":\" + port);\n\tconsole.log(\"(press ctrl-C to exit)\");\n\t// Warn if required plugins are missing\n\tif(!$tw.wiki.getTiddler(\"$:/plugins/tiddlywiki/tiddlyweb\") || !$tw.wiki.getTiddler(\"$:/plugins/tiddlywiki/filesystem\")) {\n\t\t$tw.utils.warning(\"Warning: Plugins required for client-server operation (\\\"tiddlywiki/filesystem\\\" and \\\"tiddlywiki/tiddlyweb\\\") are missing from tiddlywiki.info file\");\n\t}\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/server.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/setfield.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/setfield.js\ntype: application/javascript\nmodule-type: command\n\nCommand to modify selected tiddlers to set a field to the text of a template tiddler that has been wikified with the selected tiddler as the current tiddler.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nexports.info = {\n\tname: \"setfield\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 4) {\n\t\treturn \"Missing parameters\";\n\t}\n\tvar self = this,\n\t\twiki = this.commander.wiki,\n\t\tfilter = this.params[0],\n\t\tfieldname = this.params[1] || \"text\",\n\t\ttemplatetitle = this.params[2],\n\t\trendertype = this.params[3] || \"text/plain\",\n\t\ttiddlers = wiki.filterTiddlers(filter);\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar parser = wiki.parseTiddler(templatetitle),\n\t\t\tnewFields = {},\n\t\t\ttiddler = wiki.getTiddler(title);\n\t\tif(parser) {\n\t\t\tvar widgetNode = wiki.makeWidget(parser,{variables: {currentTiddler: title}});\n\t\t\tvar container = $tw.fakeDocument.createElement(\"div\");\n\t\t\twidgetNode.render(container,null);\n\t\t\tnewFields[fieldname] = rendertype === \"text/html\" ? container.innerHTML : container.textContent;\n\t\t} else {\n\t\t\tnewFields[fieldname] = undefined;\n\t\t}\n\t\twiki.addTiddler(new $tw.Tiddler(tiddler,newFields));\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/setfield.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/unpackplugin.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/unpackplugin.js\ntype: application/javascript\nmodule-type: command\n\nCommand to extract the shadow tiddlers from within a plugin\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"unpackplugin\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 1) {\n\t\treturn \"Missing plugin name\";\n\t}\n\tvar self = this,\n\t\ttitle = this.params[0],\n\t\tpluginData = this.commander.wiki.getTiddlerDataCached(title);\n\tif(!pluginData) {\n\t\treturn \"Plugin '\" + title + \"' not found\";\n\t}\n\t$tw.utils.each(pluginData.tiddlers,function(tiddler) {\n\t\tself.commander.wiki.addTiddler(new $tw.Tiddler(tiddler));\n\t});\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/unpackplugin.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/verbose.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/verbose.js\ntype: application/javascript\nmodule-type: command\n\nVerbose command\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"verbose\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\tthis.commander.verbose = true;\n\t// Output the boot message log\n\tthis.commander.streams.output.write(\"Boot log:\\n \" + $tw.boot.logMessages.join(\"\\n \") + \"\\n\");\n\treturn null; // No error\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/verbose.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/commands/version.js": {
"text": "/*\\\ntitle: $:/core/modules/commands/version.js\ntype: application/javascript\nmodule-type: command\n\nVersion command\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"version\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander) {\n\tthis.params = params;\n\tthis.commander = commander;\n};\n\nCommand.prototype.execute = function() {\n\tthis.commander.streams.output.write($tw.version + \"\\n\");\n\treturn null; // No error\n};\n\nexports.Command = Command;\n\n})();\n",
"title": "$:/core/modules/commands/version.js",
"type": "application/javascript",
"module-type": "command"
},
"$:/core/modules/config.js": {
"text": "/*\\\ntitle: $:/core/modules/config.js\ntype: application/javascript\nmodule-type: config\n\nCore configuration constants\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.preferences = {};\n\nexports.preferences.notificationDuration = 3 * 1000;\nexports.preferences.jsonSpaces = 4;\n\nexports.textPrimitives = {\n\tupperLetter: \"[A-Z\\u00c0-\\u00d6\\u00d8-\\u00de\\u0150\\u0170]\",\n\tlowerLetter: \"[a-z\\u00df-\\u00f6\\u00f8-\\u00ff\\u0151\\u0171]\",\n\tanyLetter: \"[A-Za-z0-9\\u00c0-\\u00d6\\u00d8-\\u00de\\u00df-\\u00f6\\u00f8-\\u00ff\\u0150\\u0170\\u0151\\u0171]\",\n\tblockPrefixLetters:\t\"[A-Za-z0-9-_\\u00c0-\\u00d6\\u00d8-\\u00de\\u00df-\\u00f6\\u00f8-\\u00ff\\u0150\\u0170\\u0151\\u0171]\"\n};\n\nexports.textPrimitives.unWikiLink = \"~\";\nexports.textPrimitives.wikiLink = exports.textPrimitives.upperLetter + \"+\" +\n\texports.textPrimitives.lowerLetter + \"+\" +\n\texports.textPrimitives.upperLetter +\n\texports.textPrimitives.anyLetter + \"*\";\n\nexports.htmlEntities = {quot:34, amp:38, apos:39, lt:60, gt:62, nbsp:160, iexcl:161, cent:162, pound:163, curren:164, yen:165, brvbar:166, sect:167, uml:168, copy:169, ordf:170, laquo:171, not:172, shy:173, reg:174, macr:175, deg:176, plusmn:177, sup2:178, sup3:179, acute:180, micro:181, para:182, middot:183, cedil:184, sup1:185, ordm:186, raquo:187, frac14:188, frac12:189, frac34:190, iquest:191, Agrave:192, Aacute:193, Acirc:194, Atilde:195, Auml:196, Aring:197, AElig:198, Ccedil:199, Egrave:200, Eacute:201, Ecirc:202, Euml:203, Igrave:204, Iacute:205, Icirc:206, Iuml:207, ETH:208, Ntilde:209, Ograve:210, Oacute:211, Ocirc:212, Otilde:213, Ouml:214, times:215, Oslash:216, Ugrave:217, Uacute:218, Ucirc:219, Uuml:220, Yacute:221, THORN:222, szlig:223, agrave:224, aacute:225, acirc:226, atilde:227, auml:228, aring:229, aelig:230, ccedil:231, egrave:232, eacute:233, ecirc:234, euml:235, igrave:236, iacute:237, icirc:238, iuml:239, eth:240, ntilde:241, ograve:242, oacute:243, ocirc:244, otilde:245, ouml:246, divide:247, oslash:248, ugrave:249, uacute:250, ucirc:251, uuml:252, yacute:253, thorn:254, yuml:255, OElig:338, oelig:339, Scaron:352, scaron:353, Yuml:376, fnof:402, circ:710, tilde:732, Alpha:913, Beta:914, Gamma:915, Delta:916, Epsilon:917, Zeta:918, Eta:919, Theta:920, Iota:921, Kappa:922, Lambda:923, Mu:924, Nu:925, Xi:926, Omicron:927, Pi:928, Rho:929, Sigma:931, Tau:932, Upsilon:933, Phi:934, Chi:935, Psi:936, Omega:937, alpha:945, beta:946, gamma:947, delta:948, epsilon:949, zeta:950, eta:951, theta:952, iota:953, kappa:954, lambda:955, mu:956, nu:957, xi:958, omicron:959, pi:960, rho:961, sigmaf:962, sigma:963, tau:964, upsilon:965, phi:966, chi:967, psi:968, omega:969, thetasym:977, upsih:978, piv:982, ensp:8194, emsp:8195, thinsp:8201, zwnj:8204, zwj:8205, lrm:8206, rlm:8207, ndash:8211, mdash:8212, lsquo:8216, rsquo:8217, sbquo:8218, ldquo:8220, rdquo:8221, bdquo:8222, dagger:8224, Dagger:8225, bull:8226, hellip:8230, permil:8240, prime:8242, Prime:8243, lsaquo:8249, rsaquo:8250, oline:8254, frasl:8260, euro:8364, image:8465, weierp:8472, real:8476, trade:8482, alefsym:8501, larr:8592, uarr:8593, rarr:8594, darr:8595, harr:8596, crarr:8629, lArr:8656, uArr:8657, rArr:8658, dArr:8659, hArr:8660, forall:8704, part:8706, exist:8707, empty:8709, nabla:8711, isin:8712, notin:8713, ni:8715, prod:8719, sum:8721, minus:8722, lowast:8727, radic:8730, prop:8733, infin:8734, ang:8736, and:8743, or:8744, cap:8745, cup:8746, int:8747, there4:8756, sim:8764, cong:8773, asymp:8776, ne:8800, equiv:8801, le:8804, ge:8805, sub:8834, sup:8835, nsub:8836, sube:8838, supe:8839, oplus:8853, otimes:8855, perp:8869, sdot:8901, lceil:8968, rceil:8969, lfloor:8970, rfloor:8971, lang:9001, rang:9002, loz:9674, spades:9824, clubs:9827, hearts:9829, diams:9830 };\n\nexports.htmlVoidElements = \"area,base,br,col,command,embed,hr,img,input,keygen,link,meta,param,source,track,wbr\".split(\",\");\n\nexports.htmlBlockElements = \"address,article,aside,audio,blockquote,canvas,dd,div,dl,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,hr,li,noscript,ol,output,p,pre,section,table,tfoot,ul,video\".split(\",\");\n\nexports.htmlUnsafeElements = \"script\".split(\",\");\n\n})();\n",
"title": "$:/core/modules/config.js",
"type": "application/javascript",
"module-type": "config"
},
"$:/core/modules/deserializers.js": {
"text": "/*\\\ntitle: $:/core/modules/deserializers.js\ntype: application/javascript\nmodule-type: tiddlerdeserializer\n\nFunctions to deserialise tiddlers from a block of text\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nUtility function to parse an old-style tiddler DIV in a *.tid file. It looks like this:\n\n<div title=\"Title\" creator=\"JoeBloggs\" modifier=\"JoeBloggs\" created=\"201102111106\" modified=\"201102111310\" tags=\"myTag [[my long tag]]\">\n<pre>The text of the tiddler (without the expected HTML encoding).\n</pre>\n</div>\n\nNote that the field attributes are HTML encoded, but that the body of the <PRE> tag is not encoded.\n\nWhen these tiddler DIVs are encountered within a TiddlyWiki HTML file then the body is encoded in the usual way.\n*/\nvar parseTiddlerDiv = function(text /* [,fields] */) {\n\t// Slot together the default results\n\tvar result = {};\n\tif(arguments.length > 1) {\n\t\tfor(var f=1; f<arguments.length; f++) {\n\t\t\tvar fields = arguments[f];\n\t\t\tfor(var t in fields) {\n\t\t\t\tresult[t] = fields[t];\t\t\n\t\t\t}\n\t\t}\n\t}\n\t// Parse the DIV body\n\tvar startRegExp = /^\\s*<div\\s+([^>]*)>(\\s*<pre>)?/gi,\n\t\tendRegExp,\n\t\tmatch = startRegExp.exec(text);\n\tif(match) {\n\t\t// Old-style DIVs don't have the <pre> tag\n\t\tif(match[2]) {\n\t\t\tendRegExp = /<\\/pre>\\s*<\\/div>\\s*$/gi;\n\t\t} else {\n\t\t\tendRegExp = /<\\/div>\\s*$/gi;\n\t\t}\n\t\tvar endMatch = endRegExp.exec(text);\n\t\tif(endMatch) {\n\t\t\t// Extract the text\n\t\t\tresult.text = text.substring(match.index + match[0].length,endMatch.index);\n\t\t\t// Process the attributes\n\t\t\tvar attrRegExp = /\\s*([^=\\s]+)\\s*=\\s*(?:\"([^\"]*)\"|'([^']*)')/gi,\n\t\t\t\tattrMatch;\n\t\t\tdo {\n\t\t\t\tattrMatch = attrRegExp.exec(match[1]);\n\t\t\t\tif(attrMatch) {\n\t\t\t\t\tvar name = attrMatch[1];\n\t\t\t\t\tvar value = attrMatch[2] !== undefined ? attrMatch[2] : attrMatch[3];\n\t\t\t\t\tresult[name] = value;\n\t\t\t\t}\n\t\t\t} while(attrMatch);\n\t\t\treturn result;\n\t\t}\n\t}\n\treturn undefined;\n};\n\nexports[\"application/x-tiddler-html-div\"] = function(text,fields) {\n\treturn [parseTiddlerDiv(text,fields)];\n};\n\nexports[\"application/json\"] = function(text,fields) {\n\tvar incoming = JSON.parse(text),\n\t\tresults = [];\n\tif($tw.utils.isArray(incoming)) {\n\t\tfor(var t=0; t<incoming.length; t++) {\n\t\t\tvar incomingFields = incoming[t],\n\t\t\t\tfields = {};\n\t\t\tfor(var f in incomingFields) {\n\t\t\t\tif(typeof incomingFields[f] === \"string\") {\n\t\t\t\t\tfields[f] = incomingFields[f];\n\t\t\t\t}\n\t\t\t}\n\t\t\tresults.push(fields);\n\t\t}\n\t}\n\treturn results;\n};\n\n/*\nParse an HTML file into tiddlers. There are three possibilities:\n# A TiddlyWiki classic HTML file containing `text/x-tiddlywiki` tiddlers\n# A TiddlyWiki5 HTML file containing `text/vnd.tiddlywiki` tiddlers\n# An ordinary HTML file\n*/\nexports[\"text/html\"] = function(text,fields) {\n\t// Check if we've got a store area\n\tvar storeAreaMarkerRegExp = /<div id=[\"']?storeArea['\"]?( style=[\"']?display:none;[\"']?)?>/gi,\n\t\tmatch = storeAreaMarkerRegExp.exec(text);\n\tif(match) {\n\t\t// If so, it's either a classic TiddlyWiki file or an unencrypted TW5 file\n\t\t// First read the normal tiddlers\n\t\tvar results = deserializeTiddlyWikiFile(text,storeAreaMarkerRegExp.lastIndex,!!match[1],fields);\n\t\t// Then any system tiddlers\n\t\tvar systemAreaMarkerRegExp = /<div id=[\"']?systemArea['\"]?( style=[\"']?display:none;[\"']?)?>/gi,\n\t\t\tsysMatch = systemAreaMarkerRegExp.exec(text);\n\t\tif(sysMatch) {\n\t\t\tresults.push.apply(results,deserializeTiddlyWikiFile(text,systemAreaMarkerRegExp.lastIndex,!!sysMatch[1],fields));\n\t\t}\n\t\treturn results;\n\t} else {\n\t\t// Check whether we've got an encrypted file\n\t\tvar encryptedStoreArea = $tw.utils.extractEncryptedStoreArea(text);\n\t\tif(encryptedStoreArea) {\n\t\t\t// If so, attempt to decrypt it using the current password\n\t\t\treturn $tw.utils.decryptStoreArea(encryptedStoreArea);\n\t\t} else {\n\t\t\t// It's not a TiddlyWiki so we'll return the entire HTML file as a tiddler\n\t\t\treturn deserializeHtmlFile(text,fields);\n\t\t}\n\t}\n};\n\nfunction deserializeHtmlFile(text,fields) {\n\tvar result = {};\n\t$tw.utils.each(fields,function(value,name) {\n\t\tresult[name] = value;\n\t});\n\tresult.text = text;\n\tresult.type = \"text/html\";\n\treturn [result];\n}\n\nfunction deserializeTiddlyWikiFile(text,storeAreaEnd,isTiddlyWiki5,fields) {\n\tvar results = [],\n\t\tendOfDivRegExp = /(<\\/div>\\s*)/gi,\n\t\tstartPos = storeAreaEnd,\n\t\tdefaultType = isTiddlyWiki5 ? undefined : \"text/x-tiddlywiki\";\n\tendOfDivRegExp.lastIndex = startPos;\n\tvar match = endOfDivRegExp.exec(text);\n\twhile(match) {\n\t\tvar endPos = endOfDivRegExp.lastIndex,\n\t\t\ttiddlerFields = parseTiddlerDiv(text.substring(startPos,endPos),fields,{type: defaultType});\n\t\tif(!tiddlerFields) {\n\t\t\tbreak;\n\t\t}\n\t\t$tw.utils.each(tiddlerFields,function(value,name) {\n\t\t\tif(typeof value === \"string\") {\n\t\t\t\ttiddlerFields[name] = $tw.utils.htmlDecode(value);\n\t\t\t}\n\t\t});\n\t\tif(tiddlerFields.text !== null) {\n\t\t\tresults.push(tiddlerFields);\n\t\t}\n\t\tstartPos = endPos;\n\t\tmatch = endOfDivRegExp.exec(text);\n\t}\n\treturn results;\n}\n\n})();\n",
"title": "$:/core/modules/deserializers.js",
"type": "application/javascript",
"module-type": "tiddlerdeserializer"
},
"$:/core/modules/editor/engines/framed.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/engines/framed.js\ntype: application/javascript\nmodule-type: library\n\nText editor engine based on a simple input or textarea within an iframe. This is done so that the selection is preserved even when clicking away from the textarea\n\n\\*/\n(function(){\n\n/*jslint node: true,browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar HEIGHT_VALUE_TITLE = \"$:/config/TextEditor/EditorHeight/Height\";\n\nfunction FramedEngine(options) {\n\t// Save our options\n\toptions = options || {};\n\tthis.widget = options.widget;\n\tthis.value = options.value;\n\tthis.parentNode = options.parentNode;\n\tthis.nextSibling = options.nextSibling;\n\t// Create our hidden dummy text area for reading styles\n\tthis.dummyTextArea = this.widget.document.createElement(\"textarea\");\n\tif(this.widget.editClass) {\n\t\tthis.dummyTextArea.className = this.widget.editClass;\n\t}\n\tthis.dummyTextArea.setAttribute(\"hidden\",\"true\");\n\tthis.parentNode.insertBefore(this.dummyTextArea,this.nextSibling);\n\tthis.widget.domNodes.push(this.dummyTextArea);\n\t// Create the iframe\n\tthis.iframeNode = this.widget.document.createElement(\"iframe\");\n\tthis.parentNode.insertBefore(this.iframeNode,this.nextSibling);\n\tthis.iframeDoc = this.iframeNode.contentWindow.document;\n\t// (Firefox requires us to put some empty content in the iframe)\n\tthis.iframeDoc.open();\n\tthis.iframeDoc.write(\"\");\n\tthis.iframeDoc.close();\n\t// Style the iframe\n\tthis.iframeNode.className = this.dummyTextArea.className;\n\tthis.iframeNode.style.border = \"none\";\n\tthis.iframeNode.style.padding = \"0\";\n\tthis.iframeNode.style.resize = \"none\";\n\tthis.iframeDoc.body.style.margin = \"0\";\n\tthis.iframeDoc.body.style.padding = \"0\";\n\tthis.widget.domNodes.push(this.iframeNode);\n\t// Construct the textarea or input node\n\tvar tag = this.widget.editTag;\n\tif($tw.config.htmlUnsafeElements.indexOf(tag) !== -1) {\n\t\ttag = \"input\";\n\t}\n\tthis.domNode = this.iframeDoc.createElement(tag);\n\t// Set the text\n\tif(this.widget.editTag === \"textarea\") {\n\t\tthis.domNode.appendChild(this.iframeDoc.createTextNode(this.value));\n\t} else {\n\t\tthis.domNode.value = this.value;\n\t}\n\t// Set the attributes\n\tif(this.widget.editType) {\n\t\tthis.domNode.setAttribute(\"type\",this.widget.editType);\n\t}\n\tif(this.widget.editPlaceholder) {\n\t\tthis.domNode.setAttribute(\"placeholder\",this.widget.editPlaceholder);\n\t}\n\tif(this.widget.editSize) {\n\t\tthis.domNode.setAttribute(\"size\",this.widget.editSize);\n\t}\n\tif(this.widget.editRows) {\n\t\tthis.domNode.setAttribute(\"rows\",this.widget.editRows);\n\t}\n\t// Copy the styles from the dummy textarea\n\tthis.copyStyles();\n\t// Add event listeners\n\t$tw.utils.addEventListeners(this.domNode,[\n\t\t{name: \"input\",handlerObject: this,handlerMethod: \"handleInputEvent\"},\n\t\t{name: \"keydown\",handlerObject: this.widget,handlerMethod: \"handleKeydownEvent\"}\n\t]);\n\t// Insert the element into the DOM\n\tthis.iframeDoc.body.appendChild(this.domNode);\n}\n\n/*\nCopy styles from the dummy text area to the textarea in the iframe\n*/\nFramedEngine.prototype.copyStyles = function() {\n\t// Copy all styles\n\t$tw.utils.copyStyles(this.dummyTextArea,this.domNode);\n\t// Override the ones that should not be set the same as the dummy textarea\n\tthis.domNode.style.display = \"block\";\n\tthis.domNode.style.width = \"100%\";\n\tthis.domNode.style.margin = \"0\";\n\t// In Chrome setting -webkit-text-fill-color overrides the placeholder text colour\n\tthis.domNode.style[\"-webkit-text-fill-color\"] = \"currentcolor\";\n};\n\n/*\nSet the text of the engine if it doesn't currently have focus\n*/\nFramedEngine.prototype.setText = function(text,type) {\n\tif(!this.domNode.isTiddlyWikiFakeDom) {\n\t\tif(this.domNode.ownerDocument.activeElement !== this.domNode) {\n\t\t\tthis.domNode.value = text;\n\t\t}\n\t\t// Fix the height if needed\n\t\tthis.fixHeight();\n\t}\n};\n\n/*\nGet the text of the engine\n*/\nFramedEngine.prototype.getText = function() {\n\treturn this.domNode.value;\n};\n\n/*\nFix the height of textarea to fit content\n*/\nFramedEngine.prototype.fixHeight = function() {\n\t// Make sure styles are updated\n\tthis.copyStyles();\n\t// Adjust height\n\tif(this.widget.editTag === \"textarea\") {\n\t\tif(this.widget.editAutoHeight) {\n\t\t\tif(this.domNode && !this.domNode.isTiddlyWikiFakeDom) {\n\t\t\t\tvar newHeight = $tw.utils.resizeTextAreaToFit(this.domNode,this.widget.editMinHeight);\n\t\t\t\tthis.iframeNode.style.height = (newHeight + 14) + \"px\"; // +14 for the border on the textarea\n\t\t\t}\n\t\t} else {\n\t\t\tvar fixedHeight = parseInt(this.widget.wiki.getTiddlerText(HEIGHT_VALUE_TITLE,\"400px\"),10);\n\t\t\tfixedHeight = Math.max(fixedHeight,20);\n\t\t\tthis.domNode.style.height = fixedHeight + \"px\";\n\t\t\tthis.iframeNode.style.height = (fixedHeight + 14) + \"px\";\n\t\t}\n\t}\n};\n\n/*\nFocus the engine node\n*/\nFramedEngine.prototype.focus = function() {\n\tif(this.domNode.focus && this.domNode.select) {\n\t\tthis.domNode.focus();\n\t\tthis.domNode.select();\n\t}\n};\n\n/*\nHandle a dom \"input\" event which occurs when the text has changed\n*/\nFramedEngine.prototype.handleInputEvent = function(event) {\n\tthis.widget.saveChanges(this.getText());\n\tthis.fixHeight();\n\treturn true;\n};\n\n/*\nCreate a blank structure representing a text operation\n*/\nFramedEngine.prototype.createTextOperation = function() {\n\tvar operation = {\n\t\ttext: this.domNode.value,\n\t\tselStart: this.domNode.selectionStart,\n\t\tselEnd: this.domNode.selectionEnd,\n\t\tcutStart: null,\n\t\tcutEnd: null,\n\t\treplacement: null,\n\t\tnewSelStart: null,\n\t\tnewSelEnd: null\n\t};\n\toperation.selection = operation.text.substring(operation.selStart,operation.selEnd);\n\treturn operation;\n};\n\n/*\nExecute a text operation\n*/\nFramedEngine.prototype.executeTextOperation = function(operation) {\n\t// Perform the required changes to the text area and the underlying tiddler\n\tvar newText = operation.text;\n\tif(operation.replacement !== null) {\n\t\tnewText = operation.text.substring(0,operation.cutStart) + operation.replacement + operation.text.substring(operation.cutEnd);\n\t\t// Attempt to use a execCommand to modify the value of the control\n\t\tif(this.iframeDoc.queryCommandSupported(\"insertText\") && this.iframeDoc.queryCommandSupported(\"delete\") && !$tw.browser.isFirefox) {\n\t\t\tthis.domNode.focus();\n\t\t\tthis.domNode.setSelectionRange(operation.cutStart,operation.cutEnd);\n\t\t\tif(operation.replacement === \"\") {\n\t\t\t\tthis.iframeDoc.execCommand(\"delete\",false,\"\");\n\t\t\t} else {\n\t\t\t\tthis.iframeDoc.execCommand(\"insertText\",false,operation.replacement);\n\t\t\t}\n\t\t} else {\n\t\t\tthis.domNode.value = newText;\n\t\t}\n\t\tthis.domNode.focus();\n\t\tthis.domNode.setSelectionRange(operation.newSelStart,operation.newSelEnd);\n\t}\n\tthis.domNode.focus();\n\treturn newText;\n};\n\nexports.FramedEngine = FramedEngine;\n\n})();\n",
"title": "$:/core/modules/editor/engines/framed.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/core/modules/editor/engines/simple.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/engines/simple.js\ntype: application/javascript\nmodule-type: library\n\nText editor engine based on a simple input or textarea tag\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar HEIGHT_VALUE_TITLE = \"$:/config/TextEditor/EditorHeight/Height\";\n\nfunction SimpleEngine(options) {\n\t// Save our options\n\toptions = options || {};\n\tthis.widget = options.widget;\n\tthis.value = options.value;\n\tthis.parentNode = options.parentNode;\n\tthis.nextSibling = options.nextSibling;\n\t// Construct the textarea or input node\n\tvar tag = this.widget.editTag;\n\tif($tw.config.htmlUnsafeElements.indexOf(tag) !== -1) {\n\t\ttag = \"input\";\n\t}\n\tthis.domNode = this.widget.document.createElement(tag);\n\t// Set the text\n\tif(this.widget.editTag === \"textarea\") {\n\t\tthis.domNode.appendChild(this.widget.document.createTextNode(this.value));\n\t} else {\n\t\tthis.domNode.value = this.value;\n\t}\n\t// Set the attributes\n\tif(this.widget.editType) {\n\t\tthis.domNode.setAttribute(\"type\",this.widget.editType);\n\t}\n\tif(this.widget.editPlaceholder) {\n\t\tthis.domNode.setAttribute(\"placeholder\",this.widget.editPlaceholder);\n\t}\n\tif(this.widget.editSize) {\n\t\tthis.domNode.setAttribute(\"size\",this.widget.editSize);\n\t}\n\tif(this.widget.editRows) {\n\t\tthis.domNode.setAttribute(\"rows\",this.widget.editRows);\n\t}\n\tif(this.widget.editClass) {\n\t\tthis.domNode.className = this.widget.editClass;\n\t}\n\t// Add an input event handler\n\t$tw.utils.addEventListeners(this.domNode,[\n\t\t{name: \"focus\", handlerObject: this, handlerMethod: \"handleFocusEvent\"},\n\t\t{name: \"input\", handlerObject: this, handlerMethod: \"handleInputEvent\"}\n\t]);\n\t// Insert the element into the DOM\n\tthis.parentNode.insertBefore(this.domNode,this.nextSibling);\n\tthis.widget.domNodes.push(this.domNode);\n}\n\n/*\nSet the text of the engine if it doesn't currently have focus\n*/\nSimpleEngine.prototype.setText = function(text,type) {\n\tif(!this.domNode.isTiddlyWikiFakeDom) {\n\t\tif(this.domNode.ownerDocument.activeElement !== this.domNode) {\n\t\t\tthis.domNode.value = text;\n\t\t}\n\t\t// Fix the height if needed\n\t\tthis.fixHeight();\n\t}\n};\n\n/*\nGet the text of the engine\n*/\nSimpleEngine.prototype.getText = function() {\n\treturn this.domNode.value;\n};\n\n/*\nFix the height of textarea to fit content\n*/\nSimpleEngine.prototype.fixHeight = function() {\n\tif(this.widget.editTag === \"textarea\") {\n\t\tif(this.widget.editAutoHeight) {\n\t\t\tif(this.domNode && !this.domNode.isTiddlyWikiFakeDom) {\n\t\t\t\t$tw.utils.resizeTextAreaToFit(this.domNode,this.widget.editMinHeight);\n\t\t\t}\n\t\t} else {\n\t\t\tvar fixedHeight = parseInt(this.widget.wiki.getTiddlerText(HEIGHT_VALUE_TITLE,\"400px\"),10);\n\t\t\tfixedHeight = Math.max(fixedHeight,20);\n\t\t\tthis.domNode.style.height = fixedHeight + \"px\";\n\t\t}\n\t}\n};\n\n/*\nFocus the engine node\n*/\nSimpleEngine.prototype.focus = function() {\n\tif(this.domNode.focus && this.domNode.select) {\n\t\tthis.domNode.focus();\n\t\tthis.domNode.select();\n\t}\n};\n\n/*\nHandle a dom \"input\" event which occurs when the text has changed\n*/\nSimpleEngine.prototype.handleInputEvent = function(event) {\n\tthis.widget.saveChanges(this.getText());\n\tthis.fixHeight();\n\treturn true;\n};\n\n/*\nHandle a dom \"focus\" event\n*/\nSimpleEngine.prototype.handleFocusEvent = function(event) {\n\tif(this.widget.editFocusPopup) {\n\t\t$tw.popup.triggerPopup({\n\t\t\tdomNode: this.domNode,\n\t\t\ttitle: this.widget.editFocusPopup,\n\t\t\twiki: this.widget.wiki,\n\t\t\tforce: true\n\t\t});\n\t}\n\treturn true;\n};\n\n/*\nCreate a blank structure representing a text operation\n*/\nSimpleEngine.prototype.createTextOperation = function() {\n\treturn null;\n};\n\n/*\nExecute a text operation\n*/\nSimpleEngine.prototype.executeTextOperation = function(operation) {\n};\n\nexports.SimpleEngine = SimpleEngine;\n\n})();\n",
"title": "$:/core/modules/editor/engines/simple.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/core/modules/editor/factory.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/factory.js\ntype: application/javascript\nmodule-type: library\n\nFactory for constructing text editor widgets with specified engines for the toolbar and non-toolbar cases\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar DEFAULT_MIN_TEXT_AREA_HEIGHT = \"100px\"; // Minimum height of textareas in pixels\n\n// Configuration tiddlers\nvar HEIGHT_MODE_TITLE = \"$:/config/TextEditor/EditorHeight/Mode\";\nvar ENABLE_TOOLBAR_TITLE = \"$:/config/TextEditor/EnableToolbar\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nfunction editTextWidgetFactory(toolbarEngine,nonToolbarEngine) {\n\n\tvar EditTextWidget = function(parseTreeNode,options) {\n\t\t// Initialise the editor operations if they've not been done already\n\t\tif(!this.editorOperations) {\n\t\t\tEditTextWidget.prototype.editorOperations = {};\n\t\t\t$tw.modules.applyMethods(\"texteditoroperation\",this.editorOperations);\n\t\t}\n\t\tthis.initialise(parseTreeNode,options);\n\t};\n\n\t/*\n\tInherit from the base widget class\n\t*/\n\tEditTextWidget.prototype = new Widget();\n\n\t/*\n\tRender this widget into the DOM\n\t*/\n\tEditTextWidget.prototype.render = function(parent,nextSibling) {\n\t\t// Save the parent dom node\n\t\tthis.parentDomNode = parent;\n\t\t// Compute our attributes\n\t\tthis.computeAttributes();\n\t\t// Execute our logic\n\t\tthis.execute();\n\t\t// Create the wrapper for the toolbar and render its content\n\t\tif(this.editShowToolbar) {\n\t\t\tthis.toolbarNode = this.document.createElement(\"div\");\n\t\t\tthis.toolbarNode.className = \"tc-editor-toolbar\";\n\t\t\tparent.insertBefore(this.toolbarNode,nextSibling);\n\t\t\tthis.renderChildren(this.toolbarNode,null);\n\t\t\tthis.domNodes.push(this.toolbarNode);\n\t\t}\n\t\t// Create our element\n\t\tvar editInfo = this.getEditInfo(),\n\t\t\tEngine = this.editShowToolbar ? toolbarEngine : nonToolbarEngine;\n\t\tthis.engine = new Engine({\n\t\t\t\twidget: this,\n\t\t\t\tvalue: editInfo.value,\n\t\t\t\ttype: editInfo.type,\n\t\t\t\tparentNode: parent,\n\t\t\t\tnextSibling: nextSibling\n\t\t\t});\n\t\t// Call the postRender hook\n\t\tif(this.postRender) {\n\t\t\tthis.postRender();\n\t\t}\n\t\t// Fix height\n\t\tthis.engine.fixHeight();\n\t\t// Focus if required\n\t\tif(this.editFocus === \"true\" || this.editFocus === \"yes\") {\n\t\t\tthis.engine.focus();\n\t\t}\n\t\t// Add widget message listeners\n\t\tthis.addEventListeners([\n\t\t\t{type: \"tm-edit-text-operation\", handler: \"handleEditTextOperationMessage\"}\n\t\t]);\n\t};\n\n\t/*\n\tGet the tiddler being edited and current value\n\t*/\n\tEditTextWidget.prototype.getEditInfo = function() {\n\t\t// Get the edit value\n\t\tvar self = this,\n\t\t\tvalue,\n\t\t\ttype = \"text/plain\",\n\t\t\tupdate;\n\t\tif(this.editIndex) {\n\t\t\tvalue = this.wiki.extractTiddlerDataItem(this.editTitle,this.editIndex,this.editDefault);\n\t\t\tupdate = function(value) {\n\t\t\t\tvar data = self.wiki.getTiddlerData(self.editTitle,{});\n\t\t\t\tif(data[self.editIndex] !== value) {\n\t\t\t\t\tdata[self.editIndex] = value;\n\t\t\t\t\tself.wiki.setTiddlerData(self.editTitle,data);\n\t\t\t\t}\n\t\t\t};\n\t\t} else {\n\t\t\t// Get the current tiddler and the field name\n\t\t\tvar tiddler = this.wiki.getTiddler(this.editTitle);\n\t\t\tif(tiddler) {\n\t\t\t\t// If we've got a tiddler, the value to display is the field string value\n\t\t\t\tvalue = tiddler.getFieldString(this.editField);\n\t\t\t\tif(this.editField === \"text\") {\n\t\t\t\t\ttype = tiddler.fields.type || \"text/vnd.tiddlywiki\";\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\t// Otherwise, we need to construct a default value for the editor\n\t\t\t\tswitch(this.editField) {\n\t\t\t\t\tcase \"text\":\n\t\t\t\t\t\tvalue = \"Type the text for the tiddler '\" + this.editTitle + \"'\";\n\t\t\t\t\t\ttype = \"text/vnd.tiddlywiki\";\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase \"title\":\n\t\t\t\t\t\tvalue = this.editTitle;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tdefault:\n\t\t\t\t\t\tvalue = \"\";\n\t\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t\tif(this.editDefault !== undefined) {\n\t\t\t\t\tvalue = this.editDefault;\n\t\t\t\t}\n\t\t\t}\n\t\t\tupdate = function(value) {\n\t\t\t\tvar tiddler = self.wiki.getTiddler(self.editTitle),\n\t\t\t\t\tupdateFields = {\n\t\t\t\t\t\ttitle: self.editTitle\n\t\t\t\t\t};\n\t\t\t\tupdateFields[self.editField] = value;\n\t\t\t\tself.wiki.addTiddler(new $tw.Tiddler(self.wiki.getCreationFields(),tiddler,updateFields,self.wiki.getModificationFields()));\n\t\t\t};\n\t\t}\n\t\tif(this.editType) {\n\t\t\ttype = this.editType;\n\t\t}\n\t\treturn {value: value || \"\", type: type, update: update};\n\t};\n\n\t/*\n\tHandle an edit text operation message from the toolbar\n\t*/\n\tEditTextWidget.prototype.handleEditTextOperationMessage = function(event) {\n\t\t// Prepare information about the operation\n\t\tvar operation = this.engine.createTextOperation();\n\t\t// Invoke the handler for the selected operation\n\t\tvar handler = this.editorOperations[event.param];\n\t\tif(handler) {\n\t\t\thandler.call(this,event,operation);\n\t\t}\n\t\t// Execute the operation via the engine\n\t\tvar newText = this.engine.executeTextOperation(operation);\n\t\t// Fix the tiddler height and save changes\n\t\tthis.engine.fixHeight();\n\t\tthis.saveChanges(newText);\n\t};\n\n\t/*\n\tCompute the internal state of the widget\n\t*/\n\tEditTextWidget.prototype.execute = function() {\n\t\t// Get our parameters\n\t\tthis.editTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\t\tthis.editField = this.getAttribute(\"field\",\"text\");\n\t\tthis.editIndex = this.getAttribute(\"index\");\n\t\tthis.editDefault = this.getAttribute(\"default\");\n\t\tthis.editClass = this.getAttribute(\"class\");\n\t\tthis.editPlaceholder = this.getAttribute(\"placeholder\");\n\t\tthis.editSize = this.getAttribute(\"size\");\n\t\tthis.editRows = this.getAttribute(\"rows\");\n\t\tthis.editAutoHeight = this.wiki.getTiddlerText(HEIGHT_MODE_TITLE,\"auto\");\n\t\tthis.editAutoHeight = this.getAttribute(\"autoHeight\",this.editAutoHeight === \"auto\" ? \"yes\" : \"no\") === \"yes\";\n\t\tthis.editMinHeight = this.getAttribute(\"minHeight\",DEFAULT_MIN_TEXT_AREA_HEIGHT);\n\t\tthis.editFocusPopup = this.getAttribute(\"focusPopup\");\n\t\tthis.editFocus = this.getAttribute(\"focus\");\n\t\t// Get the default editor element tag and type\n\t\tvar tag,type;\n\t\tif(this.editField === \"text\") {\n\t\t\ttag = \"textarea\";\n\t\t} else {\n\t\t\ttag = \"input\";\n\t\t\tvar fieldModule = $tw.Tiddler.fieldModules[this.editField];\n\t\t\tif(fieldModule && fieldModule.editTag) {\n\t\t\t\ttag = fieldModule.editTag;\n\t\t\t}\n\t\t\tif(fieldModule && fieldModule.editType) {\n\t\t\t\ttype = fieldModule.editType;\n\t\t\t}\n\t\t\ttype = type || \"text\";\n\t\t}\n\t\t// Get the rest of our parameters\n\t\tthis.editTag = this.getAttribute(\"tag\",tag);\n\t\tthis.editType = this.getAttribute(\"type\",type);\n\t\t// Make the child widgets\n\t\tthis.makeChildWidgets();\n\t\t// Determine whether to show the toolbar\n\t\tthis.editShowToolbar = this.wiki.getTiddlerText(ENABLE_TOOLBAR_TITLE,\"yes\");\n\t\tthis.editShowToolbar = (this.editShowToolbar === \"yes\") && !!(this.children && this.children.length > 0);\n\t};\n\n\t/*\n\tSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n\t*/\n\tEditTextWidget.prototype.refresh = function(changedTiddlers) {\n\t\tvar changedAttributes = this.computeAttributes();\n\t\t// Completely rerender if any of our attributes have changed\n\t\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.index || changedAttributes[\"default\"] || changedAttributes[\"class\"] || changedAttributes.placeholder || changedAttributes.size || changedAttributes.autoHeight || changedAttributes.minHeight || changedAttributes.focusPopup || changedAttributes.rows || changedTiddlers[HEIGHT_MODE_TITLE] || changedTiddlers[ENABLE_TOOLBAR_TITLE]) {\n\t\t\tthis.refreshSelf();\n\t\t\treturn true;\n\t\t} else if(changedTiddlers[this.editTitle]) {\n\t\t\tvar editInfo = this.getEditInfo();\n\t\t\tthis.updateEditor(editInfo.value,editInfo.type);\n\t\t}\n\t\tthis.engine.fixHeight();\n\t\tif(this.editShowToolbar) {\n\t\t\treturn this.refreshChildren(changedTiddlers);\t\t\t\n\t\t} else {\n\t\t\treturn false;\n\t\t}\n\t};\n\n\t/*\n\tUpdate the editor with new text. This method is separate from updateEditorDomNode()\n\tso that subclasses can override updateEditor() and still use updateEditorDomNode()\n\t*/\n\tEditTextWidget.prototype.updateEditor = function(text,type) {\n\t\tthis.updateEditorDomNode(text,type);\n\t};\n\n\t/*\n\tUpdate the editor dom node with new text\n\t*/\n\tEditTextWidget.prototype.updateEditorDomNode = function(text,type) {\n\t\tthis.engine.setText(text,type);\n\t};\n\n\t/*\n\tSave changes back to the tiddler store\n\t*/\n\tEditTextWidget.prototype.saveChanges = function(text) {\n\t\tvar editInfo = this.getEditInfo();\n\t\tif(text !== editInfo.value) {\n\t\t\teditInfo.update(text);\n\t\t}\n\t};\n\n\t/*\n\tHandle a dom \"keydown\" event, which we'll bubble up to our container for the keyboard widgets benefit\n\t*/\n\tEditTextWidget.prototype.handleKeydownEvent = function(event) {\n\t\t// Check for a keyboard shortcut\n\t\tif(this.toolbarNode) {\n\t\t\tvar shortcutElements = this.toolbarNode.querySelectorAll(\"[data-tw-keyboard-shortcut]\");\n\t\t\tfor(var index=0; index<shortcutElements.length; index++) {\n\t\t\t\tvar el = shortcutElements[index],\n\t\t\t\t\tshortcutData = el.getAttribute(\"data-tw-keyboard-shortcut\"),\n\t\t\t\t\tkeyInfoArray = $tw.keyboardManager.parseKeyDescriptors(shortcutData,{\n\t\t\t\t\t\twiki: this.wiki\n\t\t\t\t\t});\n\t\t\t\tif($tw.keyboardManager.checkKeyDescriptors(event,keyInfoArray)) {\n\t\t\t\t\tvar clickEvent = this.document.createEvent(\"Events\");\n\t\t\t\t clickEvent.initEvent(\"click\",true,false);\n\t\t\t\t el.dispatchEvent(clickEvent);\n\t\t\t\t\tevent.preventDefault();\n\t\t\t\t\tevent.stopPropagation();\n\t\t\t\t\treturn true;\t\t\t\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t// Propogate the event to the container\n\t\tif(this.propogateKeydownEvent(event)) {\n\t\t\t// Ignore the keydown if it was already handled\n\t\t\tevent.preventDefault();\n\t\t\tevent.stopPropagation();\n\t\t\treturn true;\n\t\t}\n\t\t// Otherwise, process the keydown normally\n\t\treturn false;\n\t};\n\n\t/*\n\tPropogate keydown events to our container for the keyboard widgets benefit\n\t*/\n\tEditTextWidget.prototype.propogateKeydownEvent = function(event) {\n\t\tvar newEvent = this.document.createEventObject ? this.document.createEventObject() : this.document.createEvent(\"Events\");\n\t\tif(newEvent.initEvent) {\n\t\t\tnewEvent.initEvent(\"keydown\", true, true);\n\t\t}\n\t\tnewEvent.keyCode = event.keyCode;\n\t\tnewEvent.which = event.which;\n\t\tnewEvent.metaKey = event.metaKey;\n\t\tnewEvent.ctrlKey = event.ctrlKey;\n\t\tnewEvent.altKey = event.altKey;\n\t\tnewEvent.shiftKey = event.shiftKey;\n\t\treturn !this.parentDomNode.dispatchEvent(newEvent);\n\t};\n\n\treturn EditTextWidget;\n\n}\n\nexports.editTextWidgetFactory = editTextWidgetFactory;\n\n})();\n",
"title": "$:/core/modules/editor/factory.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/core/modules/editor/operations/bitmap/clear.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/bitmap/clear.js\ntype: application/javascript\nmodule-type: bitmapeditoroperation\n\nBitmap editor operation to clear the image\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"clear\"] = function(event) {\n\tvar ctx = this.canvasDomNode.getContext(\"2d\");\n\tctx.globalAlpha = 1;\n\tctx.fillStyle = event.paramObject.colour || \"white\";\n\tctx.fillRect(0,0,this.canvasDomNode.width,this.canvasDomNode.height);\n\t// Save changes\n\tthis.strokeEnd();\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/bitmap/clear.js",
"type": "application/javascript",
"module-type": "bitmapeditoroperation"
},
"$:/core/modules/editor/operations/bitmap/resize.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/bitmap/resize.js\ntype: application/javascript\nmodule-type: bitmapeditoroperation\n\nBitmap editor operation to resize the image\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"resize\"] = function(event) {\n\t// Get the new width\n\tvar newWidth = parseInt(event.paramObject.width || this.canvasDomNode.width,10),\n\t\tnewHeight = parseInt(event.paramObject.height || this.canvasDomNode.height,10);\n\t// Update if necessary\n\tif(newWidth > 0 && newHeight > 0 && !(newWidth === this.currCanvas.width && newHeight === this.currCanvas.height)) {\n\t\tthis.changeCanvasSize(newWidth,newHeight);\n\t}\n\t// Update the input controls\n\tthis.refreshToolbar();\n\t// Save the image into the tiddler\n\tthis.saveChanges();\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/bitmap/resize.js",
"type": "application/javascript",
"module-type": "bitmapeditoroperation"
},
"$:/core/modules/editor/operations/text/excise.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/excise.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to excise the selection to a new tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"excise\"] = function(event,operation) {\n\tvar editTiddler = this.wiki.getTiddler(this.editTitle),\n\t\teditTiddlerTitle = this.editTitle;\n\tif(editTiddler && editTiddler.fields[\"draft.of\"]) {\n\t\teditTiddlerTitle = editTiddler.fields[\"draft.of\"];\n\t}\n\tvar excisionTitle = event.paramObject.title || this.wiki.generateNewTitle(\"New Excision\");\n\tthis.wiki.addTiddler(new $tw.Tiddler(\n\t\tthis.wiki.getCreationFields(),\n\t\tthis.wiki.getModificationFields(),\n\t\t{\n\t\t\ttitle: excisionTitle,\n\t\t\ttext: operation.selection,\n\t\t\ttags: event.paramObject.tagnew === \"yes\" ? [editTiddlerTitle] : []\n\t\t}\n\t));\n\toperation.replacement = excisionTitle;\n\tswitch(event.paramObject.type || \"transclude\") {\n\t\tcase \"transclude\":\n\t\t\toperation.replacement = \"{{\" + operation.replacement+ \"}}\";\n\t\t\tbreak;\n\t\tcase \"link\":\n\t\t\toperation.replacement = \"[[\" + operation.replacement+ \"]]\";\n\t\t\tbreak;\n\t\tcase \"macro\":\n\t\t\toperation.replacement = \"<<\" + (event.paramObject.macro || \"translink\") + \" \\\"\\\"\\\"\" + operation.replacement + \"\\\"\\\"\\\">>\";\n\t\t\tbreak;\n\t}\n\toperation.cutStart = operation.selStart;\n\toperation.cutEnd = operation.selEnd;\n\toperation.newSelStart = operation.selStart;\n\toperation.newSelEnd = operation.selStart + operation.replacement.length;\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/excise.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/make-link.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/make-link.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to make a link\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"make-link\"] = function(event,operation) {\n\tif(operation.selection) {\n\t\toperation.replacement = \"[[\" + operation.selection + \"|\" + event.paramObject.text + \"]]\";\n\t\toperation.cutStart = operation.selStart;\n\t\toperation.cutEnd = operation.selEnd;\n\t} else {\n\t\toperation.replacement = \"[[\" + event.paramObject.text + \"]]\";\n\t\toperation.cutStart = operation.selStart;\n\t\toperation.cutEnd = operation.selEnd;\n\t}\n\toperation.newSelStart = operation.selStart + operation.replacement.length;\n\toperation.newSelEnd = operation.newSelStart;\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/make-link.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/prefix-lines.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/prefix-lines.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to add a prefix to the selected lines\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"prefix-lines\"] = function(event,operation) {\n\t// Cut just past the preceding line break, or the start of the text\n\toperation.cutStart = $tw.utils.findPrecedingLineBreak(operation.text,operation.selStart);\n\t// Cut to just past the following line break, or to the end of the text\n\toperation.cutEnd = $tw.utils.findFollowingLineBreak(operation.text,operation.selEnd);\n\t// Compose the required prefix\n\tvar prefix = $tw.utils.repeat(event.paramObject.character,event.paramObject.count);\n\t// Process each line\n\tvar lines = operation.text.substring(operation.cutStart,operation.cutEnd).split(/\\r?\\n/mg);\n\t$tw.utils.each(lines,function(line,index) {\n\t\t// Remove and count any existing prefix characters\n\t\tvar count = 0;\n\t\twhile(line.charAt(0) === event.paramObject.character) {\n\t\t\tline = line.substring(1);\n\t\t\tcount++;\n\t\t}\n\t\t// Remove any whitespace\n\t\twhile(line.charAt(0) === \" \") {\n\t\t\tline = line.substring(1);\n\t\t}\n\t\t// We're done if we removed the exact required prefix, otherwise add it\n\t\tif(count !== event.paramObject.count) {\n\t\t\t// Apply the prefix\n\t\t\tline = prefix + \" \" + line;\n\t\t}\n\t\t// Save the modified line\n\t\tlines[index] = line;\n\t});\n\t// Stitch the replacement text together and set the selection\n\toperation.replacement = lines.join(\"\\n\");\n\tif(lines.length === 1) {\n\t\toperation.newSelStart = operation.cutStart + operation.replacement.length;\n\t\toperation.newSelEnd = operation.newSelStart;\n\t} else {\n\t\toperation.newSelStart = operation.cutStart;\n\t\toperation.newSelEnd = operation.newSelStart + operation.replacement.length;\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/prefix-lines.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/replace-all.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/replace-all.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to replace the entire text\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"replace-all\"] = function(event,operation) {\n\toperation.cutStart = 0;\n\toperation.cutEnd = operation.text.length;\n\toperation.replacement = event.paramObject.text;\n\toperation.newSelStart = 0;\n\toperation.newSelEnd = operation.replacement.length;\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/replace-all.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/replace-selection.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/replace-selection.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to replace the selection\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"replace-selection\"] = function(event,operation) {\n\toperation.replacement = event.paramObject.text;\n\toperation.cutStart = operation.selStart;\n\toperation.cutEnd = operation.selEnd;\n\toperation.newSelStart = operation.selStart;\n\toperation.newSelEnd = operation.selStart + operation.replacement.length;\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/replace-selection.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/wrap-lines.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/wrap-lines.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to wrap the selected lines with a prefix and suffix\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"wrap-lines\"] = function(event,operation) {\n\t// Cut just past the preceding line break, or the start of the text\n\toperation.cutStart = $tw.utils.findPrecedingLineBreak(operation.text,operation.selStart);\n\t// Cut to just past the following line break, or to the end of the text\n\toperation.cutEnd = $tw.utils.findFollowingLineBreak(operation.text,operation.selEnd);\n\t// Add the prefix and suffix\n\toperation.replacement = event.paramObject.prefix + \"\\n\" +\n\t\t\t\toperation.text.substring(operation.cutStart,operation.cutEnd) + \"\\n\" +\n\t\t\t\tevent.paramObject.suffix + \"\\n\";\n\toperation.newSelStart = operation.cutStart + event.paramObject.prefix.length + 1;\n\toperation.newSelEnd = operation.newSelStart + (operation.cutEnd - operation.cutStart);\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/wrap-lines.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/editor/operations/text/wrap-selection.js": {
"text": "/*\\\ntitle: $:/core/modules/editor/operations/text/wrap-selection.js\ntype: application/javascript\nmodule-type: texteditoroperation\n\nText editor operation to wrap the selection with the specified prefix and suffix\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports[\"wrap-selection\"] = function(event,operation) {\n\tif(operation.selStart === operation.selEnd) {\n\t\t// No selection; check if we're within the prefix/suffix\n\t\tif(operation.text.substring(operation.selStart - event.paramObject.prefix.length,operation.selStart + event.paramObject.suffix.length) === event.paramObject.prefix + event.paramObject.suffix) {\n\t\t\t// Remove the prefix and suffix unless they comprise the entire text\n\t\t\tif(operation.selStart > event.paramObject.prefix.length || (operation.selEnd + event.paramObject.suffix.length) < operation.text.length ) {\n\t\t\t\toperation.cutStart = operation.selStart - event.paramObject.prefix.length;\n\t\t\t\toperation.cutEnd = operation.selEnd + event.paramObject.suffix.length;\n\t\t\t\toperation.replacement = \"\";\n\t\t\t\toperation.newSelStart = operation.cutStart;\n\t\t\t\toperation.newSelEnd = operation.newSelStart;\n\t\t\t}\n\t\t} else {\n\t\t\t// Wrap the cursor instead\n\t\t\toperation.cutStart = operation.selStart;\n\t\t\toperation.cutEnd = operation.selEnd;\n\t\t\toperation.replacement = event.paramObject.prefix + event.paramObject.suffix;\n\t\t\toperation.newSelStart = operation.selStart + event.paramObject.prefix.length;\n\t\t\toperation.newSelEnd = operation.newSelStart;\n\t\t}\n\t} else if(operation.text.substring(operation.selStart,operation.selStart + event.paramObject.prefix.length) === event.paramObject.prefix && operation.text.substring(operation.selEnd - event.paramObject.suffix.length,operation.selEnd) === event.paramObject.suffix) {\n\t\t// Prefix and suffix are already present, so remove them\n\t\toperation.cutStart = operation.selStart;\n\t\toperation.cutEnd = operation.selEnd;\n\t\toperation.replacement = operation.selection.substring(event.paramObject.prefix.length,operation.selection.length - event.paramObject.suffix.length);\n\t\toperation.newSelStart = operation.selStart;\n\t\toperation.newSelEnd = operation.selStart + operation.replacement.length;\n\t} else {\n\t\t// Add the prefix and suffix\n\t\toperation.cutStart = operation.selStart;\n\t\toperation.cutEnd = operation.selEnd;\n\t\toperation.replacement = event.paramObject.prefix + operation.selection + event.paramObject.suffix;\n\t\toperation.newSelStart = operation.selStart;\n\t\toperation.newSelEnd = operation.selStart + operation.replacement.length;\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/editor/operations/text/wrap-selection.js",
"type": "application/javascript",
"module-type": "texteditoroperation"
},
"$:/core/modules/filters/addprefix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/addprefix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for adding a prefix to each title in the list. This is\nespecially useful in contexts where only a filter expression is allowed\nand macro substitution isn't available.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.addprefix = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(operator.operand + title);\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/addprefix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/addsuffix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/addsuffix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for adding a suffix to each title in the list. This is\nespecially useful in contexts where only a filter expression is allowed\nand macro substitution isn't available.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.addsuffix = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title + operator.operand);\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/addsuffix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/after.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/after.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning the tiddler from the current list that is after the tiddler named in the operand.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.after = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\tvar index = results.indexOf(operator.operand);\n\tif(index === -1 || index > (results.length - 2)) {\n\t\treturn [];\n\t} else {\n\t\treturn [results[index + 1]];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/filters/after.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/all/current.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all/current.js\ntype: application/javascript\nmodule-type: allfilteroperator\n\nFilter function for [all[current]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.current = function(source,prefix,options) {\n\tvar currTiddlerTitle = options.widget && options.widget.getVariable(\"currentTiddler\");\n\tif(currTiddlerTitle) {\n\t\treturn [currTiddlerTitle];\n\t} else {\n\t\treturn [];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/filters/all/current.js",
"type": "application/javascript",
"module-type": "allfilteroperator"
},
"$:/core/modules/filters/all/missing.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all/missing.js\ntype: application/javascript\nmodule-type: allfilteroperator\n\nFilter function for [all[missing]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.missing = function(source,prefix,options) {\n\treturn options.wiki.getMissingTitles();\n};\n\n})();\n",
"title": "$:/core/modules/filters/all/missing.js",
"type": "application/javascript",
"module-type": "allfilteroperator"
},
"$:/core/modules/filters/all/orphans.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all/orphans.js\ntype: application/javascript\nmodule-type: allfilteroperator\n\nFilter function for [all[orphans]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.orphans = function(source,prefix,options) {\n\treturn options.wiki.getOrphanTitles();\n};\n\n})();\n",
"title": "$:/core/modules/filters/all/orphans.js",
"type": "application/javascript",
"module-type": "allfilteroperator"
},
"$:/core/modules/filters/all/shadows.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all/shadows.js\ntype: application/javascript\nmodule-type: allfilteroperator\n\nFilter function for [all[shadows]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.shadows = function(source,prefix,options) {\n\treturn options.wiki.allShadowTitles();\n};\n\n})();\n",
"title": "$:/core/modules/filters/all/shadows.js",
"type": "application/javascript",
"module-type": "allfilteroperator"
},
"$:/core/modules/filters/all/tiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all/tiddlers.js\ntype: application/javascript\nmodule-type: allfilteroperator\n\nFilter function for [all[tiddlers]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tiddlers = function(source,prefix,options) {\n\treturn options.wiki.allTitles();\n};\n\n})();\n",
"title": "$:/core/modules/filters/all/tiddlers.js",
"type": "application/javascript",
"module-type": "allfilteroperator"
},
"$:/core/modules/filters/all.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/all.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for selecting tiddlers\n\n[all[shadows+tiddlers]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar allFilterOperators;\n\nfunction getAllFilterOperators() {\n\tif(!allFilterOperators) {\n\t\tallFilterOperators = {};\n\t\t$tw.modules.applyMethods(\"allfilteroperator\",allFilterOperators);\n\t}\n\treturn allFilterOperators;\n}\n\n/*\nExport our filter function\n*/\nexports.all = function(source,operator,options) {\n\t// Get our suboperators\n\tvar allFilterOperators = getAllFilterOperators();\n\t// Cycle through the suboperators accumulating their results\n\tvar results = [],\n\t\tsubops = operator.operand.split(\"+\");\n\t// Check for common optimisations\n\tif(subops.length === 1 && subops[0] === \"\") {\n\t\treturn source;\n\t} else if(subops.length === 1 && subops[0] === \"tiddlers\") {\n\t\treturn options.wiki.each;\n\t} else if(subops.length === 1 && subops[0] === \"shadows\") {\n\t\treturn options.wiki.eachShadow;\n\t} else if(subops.length === 2 && subops[0] === \"tiddlers\" && subops[1] === \"shadows\") {\n\t\treturn options.wiki.eachTiddlerPlusShadows;\n\t} else if(subops.length === 2 && subops[0] === \"shadows\" && subops[1] === \"tiddlers\") {\n\t\treturn options.wiki.eachShadowPlusTiddlers;\n\t}\n\t// Do it the hard way\n\tfor(var t=0; t<subops.length; t++) {\n\t\tvar subop = allFilterOperators[subops[t]];\n\t\tif(subop) {\n\t\t\t$tw.utils.pushTop(results,subop(source,operator.prefix,options));\n\t\t}\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/all.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/backlinks.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/backlinks.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning all the backlinks from a tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.backlinks = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\t$tw.utils.pushTop(results,options.wiki.getTiddlerBacklinks(title));\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/backlinks.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/before.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/before.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning the tiddler from the current list that is before the tiddler named in the operand.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.before = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\tvar index = results.indexOf(operator.operand);\n\tif(index <= 0) {\n\t\treturn [];\n\t} else {\n\t\treturn [results[index - 1]];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/filters/before.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/commands.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/commands.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the commands available in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.commands = function(source,operator,options) {\n\tvar results = [];\n\t$tw.utils.each($tw.commands,function(commandInfo,name) {\n\t\tresults.push(name);\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/commands.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/days.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/days.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator that selects tiddlers with a specified date field within a specified date interval.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.days = function(source,operator,options) {\n\tvar results = [],\n\t\tfieldName = operator.suffix || \"modified\",\n\t\tdayInterval = (parseInt(operator.operand,10)||0),\n\t\tdayIntervalSign = $tw.utils.sign(dayInterval),\n\t\ttargetTimeStamp = (new Date()).setHours(0,0,0,0) + 1000*60*60*24*dayInterval,\n\t\tisWithinDays = function(dateField) {\n\t\t\tvar sign = $tw.utils.sign(targetTimeStamp - (new Date(dateField)).setHours(0,0,0,0));\n\t\t\treturn sign === 0 || sign === dayIntervalSign;\n\t\t};\n\n\tif(operator.prefix === \"!\") {\n\t\ttargetTimeStamp = targetTimeStamp - 1000*60*60*24*dayIntervalSign;\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && tiddler.fields[fieldName]) {\n\t\t\t\tif(!isWithinDays($tw.utils.parseDate(tiddler.fields[fieldName]))) {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && tiddler.fields[fieldName]) {\n\t\t\t\tif(isWithinDays($tw.utils.parseDate(tiddler.fields[fieldName]))) {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/days.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/each.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/each.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator that selects one tiddler for each unique value of the specified field.\nWith suffix \"list\", selects all tiddlers that are values in a specified list field.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.each = function(source,operator,options) {\n\tvar results =[] ,\n\t\tvalue,values = {},\n\t\tfield = operator.operand || \"title\";\n\tif(operator.suffix !== \"list-item\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler) {\n\t\t\t\tvalue = (field === \"title\") ? title : tiddler.getFieldString(field);\n\t\t\t\tif(!$tw.utils.hop(values,value)) {\n\t\t\t\t\tvalues[value] = true;\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler) {\n\t\t\t\t$tw.utils.each(\n\t\t\t\t\toptions.wiki.getTiddlerList(title,field),\n\t\t\t\t\tfunction(value) {\n\t\t\t\t\t\tif(!$tw.utils.hop(values,value)) {\n\t\t\t\t\t\t\tvalues[value] = true;\n\t\t\t\t\t\t\tresults.push(value);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/each.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/eachday.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/eachday.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator that selects one tiddler for each unique day covered by the specified date field\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.eachday = function(source,operator,options) {\n\tvar results = [],\n\t\tvalues = [],\n\t\tfieldName = operator.operand || \"modified\";\n\t// Function to convert a date/time to a date integer\n\tvar toDate = function(value) {\n\t\tvalue = (new Date(value)).setHours(0,0,0,0);\n\t\treturn value+0;\n\t};\n\tsource(function(tiddler,title) {\n\t\tif(tiddler && tiddler.fields[fieldName]) {\n\t\t\tvar value = toDate($tw.utils.parseDate(tiddler.fields[fieldName]));\n\t\t\tif(values.indexOf(value) === -1) {\n\t\t\t\tvalues.push(value);\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/eachday.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/editiondescription.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/editiondescription.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the descriptions of the specified edition names\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.editiondescription = function(source,operator,options) {\n\tvar results = [],\n\t\teditionInfo = $tw.utils.getEditionInfo();\n\tif(editionInfo) {\n\t\tsource(function(tiddler,title) {\n\t\t\tif($tw.utils.hop(editionInfo,title)) {\n\t\t\t\tresults.push(editionInfo[title].description || \"\");\t\t\t\t\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/editiondescription.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/editions.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/editions.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the available editions in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.editions = function(source,operator,options) {\n\tvar results = [],\n\t\teditionInfo = $tw.utils.getEditionInfo();\n\tif(editionInfo) {\n\t\t$tw.utils.each(editionInfo,function(info,name) {\n\t\t\tresults.push(name);\n\t\t});\n\t}\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/editions.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/field.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/field.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for comparing fields for equality\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.field = function(source,operator,options) {\n\tvar results = [],\n\t\tfieldname = (operator.suffix || operator.operator || \"title\").toLowerCase();\n\tif(operator.prefix === \"!\") {\n\t\tif(operator.regexp) {\n\t\t\tsource(function(tiddler,title) {\n\t\t\t\tif(tiddler) {\n\t\t\t\t\tvar text = tiddler.getFieldString(fieldname);\n\t\t\t\t\tif(text !== null && !operator.regexp.exec(text)) {\n\t\t\t\t\t\tresults.push(title);\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t});\n\t\t} else {\n\t\t\tsource(function(tiddler,title) {\n\t\t\t\tif(tiddler) {\n\t\t\t\t\tvar text = tiddler.getFieldString(fieldname);\n\t\t\t\t\tif(text !== null && text !== operator.operand) {\n\t\t\t\t\t\tresults.push(title);\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t} else {\n\t\tif(operator.regexp) {\n\t\t\tsource(function(tiddler,title) {\n\t\t\t\tif(tiddler) {\n\t\t\t\t\tvar text = tiddler.getFieldString(fieldname);\n\t\t\t\t\tif(text !== null && !!operator.regexp.exec(text)) {\n\t\t\t\t\t\tresults.push(title);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t});\n\t\t} else {\n\t\t\tsource(function(tiddler,title) {\n\t\t\t\tif(tiddler) {\n\t\t\t\t\tvar text = tiddler.getFieldString(fieldname);\n\t\t\t\t\tif(text !== null && text === operator.operand) {\n\t\t\t\t\t\tresults.push(title);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/field.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/fields.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/fields.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the fields on the selected tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.fields = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tif(tiddler) {\n\t\t\tfor(var fieldName in tiddler.fields) {\n\t\t\t\t$tw.utils.pushTop(results,fieldName);\n\t\t\t}\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/fields.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/get.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/get.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for replacing tiddler titles by the value of the field specified in the operand.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.get = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tif(tiddler) {\n\t\t\tvar value = tiddler.getFieldString(operator.operand);\n\t\t\tif(value) {\n\t\t\t\tresults.push(value);\n\t\t\t}\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/get.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/getindex.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/getindex.js\ntype: application/javascript\nmodule-type: filteroperator\n\nreturns the value at a given index of datatiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.getindex = function(source,operator,options) {\n\tvar data,title,results = [];\n\tif(operator.operand){\n\t\tsource(function(tiddler,title) {\n\t\t\ttitle = tiddler ? tiddler.fields.title : title;\n\t\t\tdata = options.wiki.extractTiddlerDataItem(tiddler,operator.operand);\n\t\t\tif(data) {\n\t\t\t\tresults.push(data);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/getindex.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/has.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/has.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for checking if a tiddler has the specified field\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.has = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!tiddler || (tiddler && (!$tw.utils.hop(tiddler.fields,operator.operand) || tiddler.fields[operator.operand] === \"\"))) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && $tw.utils.hop(tiddler.fields,operator.operand) && !(tiddler.fields[operator.operand] === \"\" || tiddler.fields[operator.operand].length === 0)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/has.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/haschanged.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/haschanged.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returns tiddlers from the list that have a non-zero changecount.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.haschanged = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.getChangeCount(title) === 0) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.getChangeCount(title) > 0) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/haschanged.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/indexes.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/indexes.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the indexes of a data tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.indexes = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tvar data = options.wiki.getTiddlerDataCached(title);\n\t\tif(data) {\n\t\t\t$tw.utils.pushTop(results,Object.keys(data));\n\t\t}\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/indexes.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/is/current.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/current.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[current]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.current = function(source,prefix,options) {\n\tvar results = [],\n\t\tcurrTiddlerTitle = options.widget && options.widget.getVariable(\"currentTiddler\");\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title !== currTiddlerTitle) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title === currTiddlerTitle) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/current.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/image.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/image.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[image]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.image = function(source,prefix,options) {\n\tvar results = [];\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!options.wiki.isImageTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.isImageTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/image.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/missing.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/missing.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[missing]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.missing = function(source,prefix,options) {\n\tvar results = [];\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.tiddlerExists(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!options.wiki.tiddlerExists(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/missing.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/orphan.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/orphan.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[orphan]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.orphan = function(source,prefix,options) {\n\tvar results = [],\n\t\torphanTitles = options.wiki.getOrphanTitles();\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(orphanTitles.indexOf(title) === -1) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(orphanTitles.indexOf(title) !== -1) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/orphan.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/shadow.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/shadow.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[shadow]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.shadow = function(source,prefix,options) {\n\tvar results = [];\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!options.wiki.isShadowTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.isShadowTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/shadow.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/system.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/system.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[system]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.system = function(source,prefix,options) {\n\tvar results = [];\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!options.wiki.isSystemTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.isSystemTiddler(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/system.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/tag.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/tag.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[tag]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tag = function(source,prefix,options) {\n\tvar results = [],\n\t\ttagMap = options.wiki.getTagMap();\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!$tw.utils.hop(tagMap,title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif($tw.utils.hop(tagMap,title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/tag.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is/tiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is/tiddler.js\ntype: application/javascript\nmodule-type: isfilteroperator\n\nFilter function for [is[tiddler]]\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tiddler = function(source,prefix,options) {\n\tvar results = [];\n\tif(prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!options.wiki.tiddlerExists(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(options.wiki.tiddlerExists(title)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/is/tiddler.js",
"type": "application/javascript",
"module-type": "isfilteroperator"
},
"$:/core/modules/filters/is.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/is.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for checking tiddler properties\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar isFilterOperators;\n\nfunction getIsFilterOperators() {\n\tif(!isFilterOperators) {\n\t\tisFilterOperators = {};\n\t\t$tw.modules.applyMethods(\"isfilteroperator\",isFilterOperators);\n\t}\n\treturn isFilterOperators;\n}\n\n/*\nExport our filter function\n*/\nexports.is = function(source,operator,options) {\n\t// Dispatch to the correct isfilteroperator\n\tvar isFilterOperators = getIsFilterOperators();\n\tvar isFilterOperator = isFilterOperators[operator.operand];\n\tif(isFilterOperator) {\n\t\treturn isFilterOperator(source,operator.prefix,options);\n\t} else {\n\t\treturn [$tw.language.getString(\"Error/IsFilterOperator\")];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/filters/is.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/limit.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/limit.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for chopping the results to a specified maximum number of entries\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.limit = function(source,operator,options) {\n\tvar results = [];\n\t// Convert to an array\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\t// Slice the array if necessary\n\tvar limit = Math.min(results.length,parseInt(operator.operand,10));\n\tif(operator.prefix === \"!\") {\n\t\tresults = results.slice(-limit);\n\t} else {\n\t\tresults = results.slice(0,limit);\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/limit.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/links.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/links.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning all the links from a tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.links = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\t$tw.utils.pushTop(results,options.wiki.getTiddlerLinks(title));\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/links.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/list.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/list.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning the tiddlers whose title is listed in the operand tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.list = function(source,operator,options) {\n\tvar results = [],\n\t\ttr = $tw.utils.parseTextReference(operator.operand),\n\t\tcurrTiddlerTitle = options.widget && options.widget.getVariable(\"currentTiddler\"),\n\t\tlist = options.wiki.getTiddlerList(tr.title || currTiddlerTitle,tr.field,tr.index);\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(list.indexOf(title) === -1) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tresults = list;\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/list.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/listed.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/listed.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning all tiddlers that have the selected tiddlers in a list\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.listed = function(source,operator,options) {\n\tvar field = operator.operand || \"list\",\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\t$tw.utils.pushTop(results,options.wiki.findListingsOfTiddler(title,field));\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/listed.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/listops.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/listops.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operators for manipulating the current selection list\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nReverse list\n*/\nexports.reverse = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.unshift(title);\n\t});\n\treturn results;\n};\n\n/*\nFirst entry/entries in list\n*/\nexports.first = function(source,operator,options) {\n\tvar count = parseInt(operator.operand) || 1,\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results.slice(0,count);\n};\n\n/*\nLast entry/entries in list\n*/\nexports.last = function(source,operator,options) {\n\tvar count = parseInt(operator.operand) || 1,\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results.slice(-count);\n};\n\n/*\nAll but the first entry/entries of the list\n*/\nexports.rest = function(source,operator,options) {\n\tvar count = parseInt(operator.operand) || 1,\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results.slice(count);\n};\nexports.butfirst = exports.rest;\nexports.bf = exports.rest;\n\n/*\nAll but the last entry/entries of the list\n*/\nexports.butlast = function(source,operator,options) {\n\tvar count = parseInt(operator.operand) || 1,\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results.slice(0,-count);\n};\nexports.bl = exports.butlast;\n\n/*\nThe nth member of the list\n*/\nexports.nth = function(source,operator,options) {\n\tvar count = parseInt(operator.operand) || 1,\n\t\tresults = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results.slice(count - 1,count);\n};\n\n})();\n",
"title": "$:/core/modules/filters/listops.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/modules.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/modules.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the titles of the modules of a given type in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.modules = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\t$tw.utils.each($tw.modules.types[title],function(moduleInfo,moduleName) {\n\t\t\tresults.push(moduleName);\n\t\t});\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/modules.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/moduletypes.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/moduletypes.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the module types in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.moduletypes = function(source,operator,options) {\n\tvar results = [];\n\t$tw.utils.each($tw.modules.types,function(moduleInfo,type) {\n\t\tresults.push(type);\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/moduletypes.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/next.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/next.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning the tiddler whose title occurs next in the list supplied in the operand tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.next = function(source,operator,options) {\n\tvar results = [],\n\t\tlist = options.wiki.getTiddlerList(operator.operand);\n\tsource(function(tiddler,title) {\n\t\tvar match = list.indexOf(title);\n\t\t// increment match and then test if result is in range\n\t\tmatch++;\n\t\tif(match > 0 && match < list.length) {\n\t\t\tresults.push(list[match]);\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/next.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/plugintiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/plugintiddlers.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the titles of the shadow tiddlers within a plugin\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.plugintiddlers = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tvar pluginInfo = options.wiki.getPluginInfo(title) || options.wiki.getTiddlerDataCached(title,{tiddlers:[]});\n\t\tif(pluginInfo && pluginInfo.tiddlers) {\n\t\t\t$tw.utils.each(pluginInfo.tiddlers,function(fields,title) {\n\t\t\t\tresults.push(title);\n\t\t\t});\n\t\t}\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/plugintiddlers.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/prefix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/prefix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for checking if a title starts with a prefix\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.prefix = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title.substr(0,operator.operand.length) !== operator.operand) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title.substr(0,operator.operand.length) === operator.operand) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/prefix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/previous.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/previous.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning the tiddler whose title occurs immediately prior in the list supplied in the operand tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.previous = function(source,operator,options) {\n\tvar results = [],\n\t\tlist = options.wiki.getTiddlerList(operator.operand);\n\tsource(function(tiddler,title) {\n\t\tvar match = list.indexOf(title);\n\t\t// increment match and then test if result is in range\n\t\tmatch--;\n\t\tif(match >= 0) {\n\t\t\tresults.push(list[match]);\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/previous.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/regexp.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/regexp.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for regexp matching\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.regexp = function(source,operator,options) {\n\tvar results = [],\n\t\tfieldname = (operator.suffix || \"title\").toLowerCase(),\n\t\tregexpString, regexp, flags = \"\", match,\n\t\tgetFieldString = function(tiddler,title) {\n\t\t\tif(tiddler) {\n\t\t\t\treturn tiddler.getFieldString(fieldname);\n\t\t\t} else if(fieldname === \"title\") {\n\t\t\t\treturn title;\n\t\t\t} else {\n\t\t\t\treturn null;\n\t\t\t}\n\t\t};\n\t// Process flags and construct regexp\n\tregexpString = operator.operand;\n\tmatch = /^\\(\\?([gim]+)\\)/.exec(regexpString);\n\tif(match) {\n\t\tflags = match[1];\n\t\tregexpString = regexpString.substr(match[0].length);\n\t} else {\n\t\tmatch = /\\(\\?([gim]+)\\)$/.exec(regexpString);\n\t\tif(match) {\n\t\t\tflags = match[1];\n\t\t\tregexpString = regexpString.substr(0,regexpString.length - match[0].length);\n\t\t}\n\t}\n\ttry {\n\t\tregexp = new RegExp(regexpString,flags);\n\t} catch(e) {\n\t\treturn [\"\" + e];\n\t}\n\t// Process the incoming tiddlers\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tvar text = getFieldString(tiddler,title);\n\t\t\tif(text !== null) {\n\t\t\t\tif(!regexp.exec(text)) {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tvar text = getFieldString(tiddler,title);\n\t\t\tif(text !== null) {\n\t\t\t\tif(!!regexp.exec(text)) {\n\t\t\t\t\tresults.push(title);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/regexp.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/removeprefix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/removeprefix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for removing a prefix from each title in the list. Titles that do not start with the prefix are removed.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.removeprefix = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tif(title.substr(0,operator.operand.length) === operator.operand) {\n\t\t\tresults.push(title.substr(operator.operand.length));\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/removeprefix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/removesuffix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/removesuffix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for removing a suffix from each title in the list. Titles that do not end with the suffix are removed.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.removesuffix = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tif(title.substr(-operator.operand.length) === operator.operand) {\n\t\t\tresults.push(title.substr(0,title.length - operator.operand.length));\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/removesuffix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/sameday.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/sameday.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator that selects tiddlers with a modified date field on the same day as the provided value.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.sameday = function(source,operator,options) {\n\tvar results = [],\n\t\tfieldName = operator.suffix || \"modified\",\n\t\ttargetDate = (new Date($tw.utils.parseDate(operator.operand))).setHours(0,0,0,0);\n\t// Function to convert a date/time to a date integer\n\tvar isSameDay = function(dateField) {\n\t\t\treturn (new Date(dateField)).setHours(0,0,0,0) === targetDate;\n\t\t};\n\tsource(function(tiddler,title) {\n\t\tif(tiddler && tiddler.fields[fieldName]) {\n\t\t\tif(isSameDay($tw.utils.parseDate(tiddler.fields[fieldName]))) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/sameday.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/search.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/search.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for searching for the text in the operand tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.search = function(source,operator,options) {\n\tvar invert = operator.prefix === \"!\";\n\tif(operator.suffix) {\n\t\treturn options.wiki.search(operator.operand,{\n\t\t\tsource: source,\n\t\t\tinvert: invert,\n\t\t\tfield: operator.suffix\n\t\t});\n\t} else {\n\t\treturn options.wiki.search(operator.operand,{\n\t\t\tsource: source,\n\t\t\tinvert: invert\n\t\t});\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/filters/search.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/shadowsource.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/shadowsource.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the source plugins for shadow tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.shadowsource = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tvar source = options.wiki.getShadowSource(title);\n\t\tif(source) {\n\t\t\t$tw.utils.pushTop(results,source);\n\t\t}\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/shadowsource.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/sort.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/sort.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for sorting\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.sort = function(source,operator,options) {\n\tvar results = prepare_results(source);\n\toptions.wiki.sortTiddlers(results,operator.operand || \"title\",operator.prefix === \"!\",false,false);\n\treturn results;\n};\n\nexports.nsort = function(source,operator,options) {\n\tvar results = prepare_results(source);\n\toptions.wiki.sortTiddlers(results,operator.operand || \"title\",operator.prefix === \"!\",false,true);\n\treturn results;\n};\n\nexports.sortcs = function(source,operator,options) {\n\tvar results = prepare_results(source);\n\toptions.wiki.sortTiddlers(results,operator.operand || \"title\",operator.prefix === \"!\",true,false);\n\treturn results;\n};\n\nexports.nsortcs = function(source,operator,options) {\n\tvar results = prepare_results(source);\n\toptions.wiki.sortTiddlers(results,operator.operand || \"title\",operator.prefix === \"!\",true,true);\n\treturn results;\n};\n\nvar prepare_results = function (source) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tresults.push(title);\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/sort.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/splitbefore.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/splitbefore.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator that splits each result on the first occurance of the specified separator and returns the unique values.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.splitbefore = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\tvar parts = title.split(operator.operand);\n\t\tif(parts.length === 1) {\n\t\t\t$tw.utils.pushTop(results,parts[0]);\n\t\t} else {\n\t\t\t$tw.utils.pushTop(results,parts[0] + operator.operand);\n\t\t}\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/splitbefore.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/storyviews.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/storyviews.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the story views in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.storyviews = function(source,operator,options) {\n\tvar results = [],\n\t\tstoryviews = {};\n\t$tw.modules.applyMethods(\"storyview\",storyviews);\n\t$tw.utils.each(storyviews,function(info,name) {\n\t\tresults.push(name);\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/storyviews.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/suffix.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/suffix.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for checking if a title ends with a suffix\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.suffix = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title.substr(-operator.operand.length) !== operator.operand) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(title.substr(-operator.operand.length) === operator.operand) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/suffix.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/tag.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/tag.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for checking for the presence of a tag\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tag = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && !tiddler.hasTag(operator.operand)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && tiddler.hasTag(operator.operand)) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t\tresults = options.wiki.sortByList(results,operator.operand);\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/tag.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/tagging.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/tagging.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning all tiddlers that are tagged with the selected tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tagging = function(source,operator,options) {\n\tvar results = [];\n\tsource(function(tiddler,title) {\n\t\t$tw.utils.pushTop(results,options.wiki.getTiddlersWithTag(title));\n\t});\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/tagging.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/tags.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/tags.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning all the tags of the selected tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.tags = function(source,operator,options) {\n\tvar tags = {};\n\tsource(function(tiddler,title) {\n\t\tvar t, length;\n\t\tif(tiddler && tiddler.fields.tags) {\n\t\t\tfor(t=0, length=tiddler.fields.tags.length; t<length; t++) {\n\t\t\t\ttags[tiddler.fields.tags[t]] = true;\n\t\t\t}\n\t\t}\n\t});\n\treturn Object.keys(tags);\n};\n\n})();\n",
"title": "$:/core/modules/filters/tags.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/title.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/title.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for comparing title fields for equality\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.title = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && tiddler.fields.title !== operator.operand) {\n\t\t\t\tresults.push(title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tresults.push(operator.operand);\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/title.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/untagged.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/untagged.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator returning all the selected tiddlers that are untagged\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.untagged = function(source,operator,options) {\n\tvar results = [];\n\tif(operator.prefix === \"!\") {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(tiddler && $tw.utils.isArray(tiddler.fields.tags) && tiddler.fields.tags.length > 0) {\n\t\t\t\t$tw.utils.pushTop(results,title);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tsource(function(tiddler,title) {\n\t\t\tif(!tiddler || !tiddler.hasField(\"tags\") || ($tw.utils.isArray(tiddler.fields.tags) && tiddler.fields.tags.length === 0)) {\n\t\t\t\t$tw.utils.pushTop(results,title);\n\t\t\t}\n\t\t});\n\t}\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/untagged.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/wikiparserrules.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/wikiparserrules.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for returning the names of the wiki parser rules in this wiki\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.wikiparserrules = function(source,operator,options) {\n\tvar results = [];\n\t$tw.utils.each($tw.modules.types.wikirule,function(mod) {\n\t\tvar exp = mod.exports;\n\t\tif(exp.types[operator.operand]) {\n\t\t\tresults.push(exp.name);\n\t\t}\n\t});\n\tresults.sort();\n\treturn results;\n};\n\n})();\n",
"title": "$:/core/modules/filters/wikiparserrules.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters/x-listops.js": {
"text": "/*\\\ntitle: $:/core/modules/filters/x-listops.js\ntype: application/javascript\nmodule-type: filteroperator\n\nExtended filter operators to manipulate the current list.\n\n\\*/\n(function () {\n\n /*jslint node: true, browser: true */\n /*global $tw: false */\n \"use strict\";\n\n /*\n Fetch titles from the current list\n */\n var prepare_results = function (source) {\n var results = [];\n source(function (tiddler, title) {\n results.push(title);\n });\n return results;\n };\n\n /*\n Moves a number of items from the tail of the current list before the item named in the operand\n */\n exports.putbefore = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand),\n count = parseInt(operator.suffix) || 1;\n return (index === -1) ?\n results.slice(0, -1) :\n results.slice(0, index).concat(results.slice(-count)).concat(results.slice(index, -count));\n };\n\n /*\n Moves a number of items from the tail of the current list after the item named in the operand\n */\n exports.putafter = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand),\n count = parseInt(operator.suffix) || 1;\n return (index === -1) ?\n results.slice(0, -1) :\n results.slice(0, index + 1).concat(results.slice(-count)).concat(results.slice(index + 1, -count));\n };\n\n /*\n Replaces the item named in the operand with a number of items from the tail of the current list\n */\n exports.replace = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand),\n count = parseInt(operator.suffix) || 1;\n return (index === -1) ?\n results.slice(0, -count) :\n results.slice(0, index).concat(results.slice(-count)).concat(results.slice(index + 1, -count));\n };\n\n /*\n Moves a number of items from the tail of the current list to the head of the list\n */\n exports.putfirst = function (source, operator) {\n var results = prepare_results(source),\n count = parseInt(operator.suffix) || 1;\n return results.slice(-count).concat(results.slice(0, -count));\n };\n\n /*\n Moves a number of items from the head of the current list to the tail of the list\n */\n exports.putlast = function (source, operator) {\n var results = prepare_results(source),\n count = parseInt(operator.suffix) || 1;\n return results.slice(count).concat(results.slice(0, count));\n };\n\n /*\n Moves the item named in the operand a number of places forward or backward in the list\n */\n exports.move = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand),\n count = parseInt(operator.suffix) || 1,\n marker = results.splice(index, 1);\n return results.slice(0, index + count).concat(marker).concat(results.slice(index + count));\n };\n\n /*\n Returns the items from the current list that are after the item named in the operand\n */\n exports.allafter = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand);\n return (index === -1 || index > (results.length - 2)) ? [] :\n (operator.suffix) ? results.slice(index) :\n results.slice(index + 1);\n };\n\n /*\n Returns the items from the current list that are before the item named in the operand\n */\n exports.allbefore = function (source, operator) {\n var results = prepare_results(source),\n index = results.indexOf(operator.operand);\n return (index <= 0) ? [] :\n (operator.suffix) ? results.slice(0, index + 1) :\n results.slice(0, index);\n };\n\n /*\n Appends the items listed in the operand array to the tail of the current list\n */\n exports.append = function (source, operator) {\n var append = $tw.utils.parseStringArray(operator.operand, \"true\"),\n results = prepare_results(source),\n count = parseInt(operator.suffix) || append.length;\n return (append.length === 0) ? results :\n (operator.prefix) ? results.concat(append.slice(-count)) :\n results.concat(append.slice(0, count));\n };\n\n /*\n Prepends the items listed in the operand array to the head of the current list\n */\n exports.prepend = function (source, operator) {\n var prepend = $tw.utils.parseStringArray(operator.operand, \"true\"),\n results = prepare_results(source),\n count = parseInt(operator.suffix) || prepend.length;\n return (prepend.length === 0) ? results :\n (operator.prefix) ? prepend.slice(-count).concat(results) :\n prepend.slice(0, count).concat(results);\n };\n\n /*\n Returns all items from the current list except the items listed in the operand array\n */\n exports.remove = function (source, operator) {\n var array = $tw.utils.parseStringArray(operator.operand, \"true\"),\n results = prepare_results(source),\n count = parseInt(operator.suffix) || array.length,\n p,\n len,\n index;\n len = array.length - 1;\n for (p = 0; p < count; ++p) {\n if (operator.prefix) {\n index = results.indexOf(array[len - p]);\n } else {\n index = results.indexOf(array[p]);\n }\n if (index !== -1) {\n results.splice(index, 1);\n }\n }\n return results;\n };\n\n /*\n Returns all items from the current list sorted in the order of the items in the operand array\n */\n exports.sortby = function (source, operator) {\n var results = prepare_results(source);\n if (!results || results.length < 2) {\n return results;\n }\n var lookup = $tw.utils.parseStringArray(operator.operand, \"true\");\n results.sort(function (a, b) {\n return lookup.indexOf(a) - lookup.indexOf(b);\n });\n return results;\n };\n\n /*\n Removes all duplicate items from the current list\n */\n exports.unique = function (source, operator) {\n var results = prepare_results(source);\n var set = results.reduce(function (a, b) {\n if (a.indexOf(b) < 0) {\n a.push(b);\n }\n return a;\n }, []);\n return set;\n };\n})();\n",
"title": "$:/core/modules/filters/x-listops.js",
"type": "application/javascript",
"module-type": "filteroperator"
},
"$:/core/modules/filters.js": {
"text": "/*\\\ntitle: $:/core/modules/filters.js\ntype: application/javascript\nmodule-type: wikimethod\n\nAdds tiddler filtering methods to the $tw.Wiki object.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nParses an operation (i.e. a run) within a filter string\n\toperators: Array of array of operator nodes into which results should be inserted\n\tfilterString: filter string\n\tp: start position within the string\nReturns the new start position, after the parsed operation\n*/\nfunction parseFilterOperation(operators,filterString,p) {\n\tvar operator, operand, bracketPos, curlyBracketPos;\n\t// Skip the starting square bracket\n\tif(filterString.charAt(p++) !== \"[\") {\n\t\tthrow \"Missing [ in filter expression\";\n\t}\n\t// Process each operator in turn\n\tdo {\n\t\toperator = {};\n\t\t// Check for an operator prefix\n\t\tif(filterString.charAt(p) === \"!\") {\n\t\t\toperator.prefix = filterString.charAt(p++);\n\t\t}\n\t\t// Get the operator name\n\t\tvar nextBracketPos = filterString.substring(p).search(/[\\[\\{<\\/]/);\n\t\tif(nextBracketPos === -1) {\n\t\t\tthrow \"Missing [ in filter expression\";\n\t\t}\n\t\tnextBracketPos += p;\n\t\tvar bracket = filterString.charAt(nextBracketPos);\n\t\toperator.operator = filterString.substring(p,nextBracketPos);\n\t\t\n\t\t// Any suffix?\n\t\tvar colon = operator.operator.indexOf(':');\n\t\tif(colon > -1) {\n\t\t\toperator.suffix = operator.operator.substring(colon + 1);\n\t\t\toperator.operator = operator.operator.substring(0,colon) || \"field\";\n\t\t}\n\t\t// Empty operator means: title\n\t\telse if(operator.operator === \"\") {\n\t\t\toperator.operator = \"title\";\n\t\t}\n\n\t\tp = nextBracketPos + 1;\n\t\tswitch (bracket) {\n\t\t\tcase \"{\": // Curly brackets\n\t\t\t\toperator.indirect = true;\n\t\t\t\tnextBracketPos = filterString.indexOf(\"}\",p);\n\t\t\t\tbreak;\n\t\t\tcase \"[\": // Square brackets\n\t\t\t\tnextBracketPos = filterString.indexOf(\"]\",p);\n\t\t\t\tbreak;\n\t\t\tcase \"<\": // Angle brackets\n\t\t\t\toperator.variable = true;\n\t\t\t\tnextBracketPos = filterString.indexOf(\">\",p);\n\t\t\t\tbreak;\n\t\t\tcase \"/\": // regexp brackets\n\t\t\t\tvar rex = /^((?:[^\\\\\\/]*|\\\\.)*)\\/(?:\\(([mygi]+)\\))?/g,\n\t\t\t\t\trexMatch = rex.exec(filterString.substring(p));\n\t\t\t\tif(rexMatch) {\n\t\t\t\t\toperator.regexp = new RegExp(rexMatch[1], rexMatch[2]);\n// DEPRECATION WARNING\nconsole.log(\"WARNING: Filter\",operator.operator,\"has a deprecated regexp operand\",operator.regexp);\n\t\t\t\t\tnextBracketPos = p + rex.lastIndex - 1;\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tthrow \"Unterminated regular expression in filter expression\";\n\t\t\t\t}\n\t\t\t\tbreak;\n\t\t}\n\t\t\n\t\tif(nextBracketPos === -1) {\n\t\t\tthrow \"Missing closing bracket in filter expression\";\n\t\t}\n\t\tif(!operator.regexp) {\n\t\t\toperator.operand = filterString.substring(p,nextBracketPos);\n\t\t}\n\t\tp = nextBracketPos + 1;\n\t\t\t\n\t\t// Push this operator\n\t\toperators.push(operator);\n\t} while(filterString.charAt(p) !== \"]\");\n\t// Skip the ending square bracket\n\tif(filterString.charAt(p++) !== \"]\") {\n\t\tthrow \"Missing ] in filter expression\";\n\t}\n\t// Return the parsing position\n\treturn p;\n}\n\n/*\nParse a filter string\n*/\nexports.parseFilter = function(filterString) {\n\tfilterString = filterString || \"\";\n\tvar results = [], // Array of arrays of operator nodes {operator:,operand:}\n\t\tp = 0, // Current position in the filter string\n\t\tmatch;\n\tvar whitespaceRegExp = /(\\s+)/mg,\n\t\toperandRegExp = /((?:\\+|\\-)?)(?:(\\[)|(?:\"([^\"]*)\")|(?:'([^']*)')|([^\\s\\[\\]]+))/mg;\n\twhile(p < filterString.length) {\n\t\t// Skip any whitespace\n\t\twhitespaceRegExp.lastIndex = p;\n\t\tmatch = whitespaceRegExp.exec(filterString);\n\t\tif(match && match.index === p) {\n\t\t\tp = p + match[0].length;\n\t\t}\n\t\t// Match the start of the operation\n\t\tif(p < filterString.length) {\n\t\t\toperandRegExp.lastIndex = p;\n\t\t\tmatch = operandRegExp.exec(filterString);\n\t\t\tif(!match || match.index !== p) {\n\t\t\t\tthrow $tw.language.getString(\"Error/FilterSyntax\");\n\t\t\t}\n\t\t\tvar operation = {\n\t\t\t\tprefix: \"\",\n\t\t\t\toperators: []\n\t\t\t};\n\t\t\tif(match[1]) {\n\t\t\t\toperation.prefix = match[1];\n\t\t\t\tp++;\n\t\t\t}\n\t\t\tif(match[2]) { // Opening square bracket\n\t\t\t\tp = parseFilterOperation(operation.operators,filterString,p);\n\t\t\t} else {\n\t\t\t\tp = match.index + match[0].length;\n\t\t\t}\n\t\t\tif(match[3] || match[4] || match[5]) { // Double quoted string, single quoted string or unquoted title\n\t\t\t\toperation.operators.push(\n\t\t\t\t\t{operator: \"title\", operand: match[3] || match[4] || match[5]}\n\t\t\t\t);\n\t\t\t}\n\t\t\tresults.push(operation);\n\t\t}\n\t}\n\treturn results;\n};\n\nexports.getFilterOperators = function() {\n\tif(!this.filterOperators) {\n\t\t$tw.Wiki.prototype.filterOperators = {};\n\t\t$tw.modules.applyMethods(\"filteroperator\",this.filterOperators);\n\t}\n\treturn this.filterOperators;\n};\n\nexports.filterTiddlers = function(filterString,widget,source) {\n\tvar fn = this.compileFilter(filterString);\n\treturn fn.call(this,source,widget);\n};\n\n/*\nCompile a filter into a function with the signature fn(source,widget) where:\nsource: an iterator function for the source tiddlers, called source(iterator), where iterator is called as iterator(tiddler,title)\nwidget: an optional widget node for retrieving the current tiddler etc.\n*/\nexports.compileFilter = function(filterString) {\n\tvar filterParseTree;\n\ttry {\n\t\tfilterParseTree = this.parseFilter(filterString);\n\t} catch(e) {\n\t\treturn function(source,widget) {\n\t\t\treturn [$tw.language.getString(\"Error/Filter\") + \": \" + e];\n\t\t};\n\t}\n\t// Get the hashmap of filter operator functions\n\tvar filterOperators = this.getFilterOperators();\n\t// Assemble array of functions, one for each operation\n\tvar operationFunctions = [];\n\t// Step through the operations\n\tvar self = this;\n\t$tw.utils.each(filterParseTree,function(operation) {\n\t\t// Create a function for the chain of operators in the operation\n\t\tvar operationSubFunction = function(source,widget) {\n\t\t\tvar accumulator = source,\n\t\t\t\tresults = [],\n\t\t\t\tcurrTiddlerTitle = widget && widget.getVariable(\"currentTiddler\");\n\t\t\t$tw.utils.each(operation.operators,function(operator) {\n\t\t\t\tvar operand = operator.operand,\n\t\t\t\t\toperatorFunction;\n\t\t\t\tif(!operator.operator) {\n\t\t\t\t\toperatorFunction = filterOperators.title;\n\t\t\t\t} else if(!filterOperators[operator.operator]) {\n\t\t\t\t\toperatorFunction = filterOperators.field;\n\t\t\t\t} else {\n\t\t\t\t\toperatorFunction = filterOperators[operator.operator];\n\t\t\t\t}\n\t\t\t\tif(operator.indirect) {\n\t\t\t\t\toperand = self.getTextReference(operator.operand,\"\",currTiddlerTitle);\n\t\t\t\t}\n\t\t\t\tif(operator.variable) {\n\t\t\t\t\toperand = widget.getVariable(operator.operand,{defaultValue: \"\"});\n\t\t\t\t}\n\t\t\t\t// Invoke the appropriate filteroperator module\n\t\t\t\tresults = operatorFunction(accumulator,{\n\t\t\t\t\t\t\toperator: operator.operator,\n\t\t\t\t\t\t\toperand: operand,\n\t\t\t\t\t\t\tprefix: operator.prefix,\n\t\t\t\t\t\t\tsuffix: operator.suffix,\n\t\t\t\t\t\t\tregexp: operator.regexp\n\t\t\t\t\t\t},{\n\t\t\t\t\t\t\twiki: self,\n\t\t\t\t\t\t\twidget: widget\n\t\t\t\t\t\t});\n\t\t\t\tif($tw.utils.isArray(results)) {\n\t\t\t\t\taccumulator = self.makeTiddlerIterator(results);\n\t\t\t\t} else {\n\t\t\t\t\taccumulator = results;\n\t\t\t\t}\n\t\t\t});\n\t\t\tif($tw.utils.isArray(results)) {\n\t\t\t\treturn results;\n\t\t\t} else {\n\t\t\t\tvar resultArray = [];\n\t\t\t\tresults(function(tiddler,title) {\n\t\t\t\t\tresultArray.push(title);\n\t\t\t\t});\n\t\t\t\treturn resultArray;\n\t\t\t}\n\t\t};\n\t\t// Wrap the operator functions in a wrapper function that depends on the prefix\n\t\toperationFunctions.push((function() {\n\t\t\tswitch(operation.prefix || \"\") {\n\t\t\t\tcase \"\": // No prefix means that the operation is unioned into the result\n\t\t\t\t\treturn function(results,source,widget) {\n\t\t\t\t\t\t$tw.utils.pushTop(results,operationSubFunction(source,widget));\n\t\t\t\t\t};\n\t\t\t\tcase \"-\": // The results of this operation are removed from the main result\n\t\t\t\t\treturn function(results,source,widget) {\n\t\t\t\t\t\t$tw.utils.removeArrayEntries(results,operationSubFunction(source,widget));\n\t\t\t\t\t};\n\t\t\t\tcase \"+\": // This operation is applied to the main results so far\n\t\t\t\t\treturn function(results,source,widget) {\n\t\t\t\t\t\t// This replaces all the elements of the array, but keeps the actual array so that references to it are preserved\n\t\t\t\t\t\tsource = self.makeTiddlerIterator(results);\n\t\t\t\t\t\tresults.splice(0,results.length);\n\t\t\t\t\t\t$tw.utils.pushTop(results,operationSubFunction(source,widget));\n\t\t\t\t\t};\n\t\t\t}\n\t\t})());\n\t});\n\t// Return a function that applies the operations to a source iterator of tiddler titles\n\treturn $tw.perf.measure(\"filter\",function filterFunction(source,widget) {\n\t\tif(!source) {\n\t\t\tsource = self.each;\n\t\t} else if(typeof source === \"object\") { // Array or hashmap\n\t\t\tsource = self.makeTiddlerIterator(source);\n\t\t}\n\t\tvar results = [];\n\t\t$tw.utils.each(operationFunctions,function(operationFunction) {\n\t\t\toperationFunction(results,source,widget);\n\t\t});\n\t\treturn results;\n\t});\n};\n\n})();\n",
"title": "$:/core/modules/filters.js",
"type": "application/javascript",
"module-type": "wikimethod"
},
"$:/core/modules/info/platform.js": {
"text": "/*\\\ntitle: $:/core/modules/info/platform.js\ntype: application/javascript\nmodule-type: info\n\nInitialise basic platform $:/info/ tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.getInfoTiddlerFields = function() {\n\tvar mapBoolean = function(value) {return value ? \"yes\" : \"no\";},\n\t\tinfoTiddlerFields = [];\n\t// Basics\n\tinfoTiddlerFields.push({title: \"$:/info/browser\", text: mapBoolean(!!$tw.browser)});\n\tinfoTiddlerFields.push({title: \"$:/info/node\", text: mapBoolean(!!$tw.node)});\n\treturn infoTiddlerFields;\n};\n\n})();\n",
"title": "$:/core/modules/info/platform.js",
"type": "application/javascript",
"module-type": "info"
},
"$:/core/modules/keyboard.js": {
"text": "/*\\\ntitle: $:/core/modules/keyboard.js\ntype: application/javascript\nmodule-type: global\n\nKeyboard handling utilities\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar namedKeys = {\n\t\"cancel\": 3,\n\t\"help\": 6,\n\t\"backspace\": 8,\n\t\"tab\": 9,\n\t\"clear\": 12,\n\t\"return\": 13,\n\t\"enter\": 13,\n\t\"pause\": 19,\n\t\"escape\": 27,\n\t\"space\": 32,\n\t\"page_up\": 33,\n\t\"page_down\": 34,\n\t\"end\": 35,\n\t\"home\": 36,\n\t\"left\": 37,\n\t\"up\": 38,\n\t\"right\": 39,\n\t\"down\": 40,\n\t\"printscreen\": 44,\n\t\"insert\": 45,\n\t\"delete\": 46,\n\t\"0\": 48,\n\t\"1\": 49,\n\t\"2\": 50,\n\t\"3\": 51,\n\t\"4\": 52,\n\t\"5\": 53,\n\t\"6\": 54,\n\t\"7\": 55,\n\t\"8\": 56,\n\t\"9\": 57,\n\t\"firefoxsemicolon\": 59,\n\t\"firefoxequals\": 61,\n\t\"a\": 65,\n\t\"b\": 66,\n\t\"c\": 67,\n\t\"d\": 68,\n\t\"e\": 69,\n\t\"f\": 70,\n\t\"g\": 71,\n\t\"h\": 72,\n\t\"i\": 73,\n\t\"j\": 74,\n\t\"k\": 75,\n\t\"l\": 76,\n\t\"m\": 77,\n\t\"n\": 78,\n\t\"o\": 79,\n\t\"p\": 80,\n\t\"q\": 81,\n\t\"r\": 82,\n\t\"s\": 83,\n\t\"t\": 84,\n\t\"u\": 85,\n\t\"v\": 86,\n\t\"w\": 87,\n\t\"x\": 88,\n\t\"y\": 89,\n\t\"z\": 90,\n\t\"numpad0\": 96,\n\t\"numpad1\": 97,\n\t\"numpad2\": 98,\n\t\"numpad3\": 99,\n\t\"numpad4\": 100,\n\t\"numpad5\": 101,\n\t\"numpad6\": 102,\n\t\"numpad7\": 103,\n\t\"numpad8\": 104,\n\t\"numpad9\": 105,\n\t\"multiply\": 106,\n\t\"add\": 107,\n\t\"separator\": 108,\n\t\"subtract\": 109,\n\t\"decimal\": 110,\n\t\"divide\": 111,\n\t\"f1\": 112,\n\t\"f2\": 113,\n\t\"f3\": 114,\n\t\"f4\": 115,\n\t\"f5\": 116,\n\t\"f6\": 117,\n\t\"f7\": 118,\n\t\"f8\": 119,\n\t\"f9\": 120,\n\t\"f10\": 121,\n\t\"f11\": 122,\n\t\"f12\": 123,\n\t\"f13\": 124,\n\t\"f14\": 125,\n\t\"f15\": 126,\n\t\"f16\": 127,\n\t\"f17\": 128,\n\t\"f18\": 129,\n\t\"f19\": 130,\n\t\"f20\": 131,\n\t\"f21\": 132,\n\t\"f22\": 133,\n\t\"f23\": 134,\n\t\"f24\": 135,\n\t\"firefoxminus\": 173,\n\t\"semicolon\": 186,\n\t\"equals\": 187,\n\t\"comma\": 188,\n\t\"dash\": 189,\n\t\"period\": 190,\n\t\"slash\": 191,\n\t\"backquote\": 192,\n\t\"openbracket\": 219,\n\t\"backslash\": 220,\n\t\"closebracket\": 221,\n\t\"quote\": 222\n};\n\nfunction KeyboardManager(options) {\n\tvar self = this;\n\toptions = options || \"\";\n\t// Save the named key hashmap\n\tthis.namedKeys = namedKeys;\n\t// Create a reverse mapping of code to keyname\n\tthis.keyNames = [];\n\t$tw.utils.each(namedKeys,function(keyCode,name) {\n\t\tself.keyNames[keyCode] = name.substr(0,1).toUpperCase() + name.substr(1);\n\t});\n\t// Save the platform-specific name of the \"meta\" key\n\tthis.metaKeyName = $tw.platform.isMac ? \"cmd-\" : \"win-\";\n}\n\n/*\nReturn an array of keycodes for the modifier keys ctrl, shift, alt, meta\n*/\nKeyboardManager.prototype.getModifierKeys = function() {\n\treturn [\n\t\t16, // Shift\n\t\t17, // Ctrl\n\t\t18, // Alt\n\t\t20, // CAPS LOCK\n\t\t91, // Meta (left)\n\t\t93, // Meta (right)\n\t\t224 // Meta (Firefox)\n\t]\n};\n\n/*\nParses a key descriptor into the structure:\n{\n\tkeyCode: numeric keycode\n\tshiftKey: boolean\n\taltKey: boolean\n\tctrlKey: boolean\n\tmetaKey: boolean\n}\nKey descriptors have the following format:\n\tctrl+enter\n\tctrl+shift+alt+A\n*/\nKeyboardManager.prototype.parseKeyDescriptor = function(keyDescriptor) {\n\tvar components = keyDescriptor.split(/\\+|\\-/),\n\t\tinfo = {\n\t\t\tkeyCode: 0,\n\t\t\tshiftKey: false,\n\t\t\taltKey: false,\n\t\t\tctrlKey: false,\n\t\t\tmetaKey: false\n\t\t};\n\tfor(var t=0; t<components.length; t++) {\n\t\tvar s = components[t].toLowerCase(),\n\t\t\tc = s.charCodeAt(0);\n\t\t// Look for modifier keys\n\t\tif(s === \"ctrl\") {\n\t\t\tinfo.ctrlKey = true;\n\t\t} else if(s === \"shift\") {\n\t\t\tinfo.shiftKey = true;\n\t\t} else if(s === \"alt\") {\n\t\t\tinfo.altKey = true;\n\t\t} else if(s === \"meta\" || s === \"cmd\" || s === \"win\") {\n\t\t\tinfo.metaKey = true;\n\t\t}\n\t\t// Replace named keys with their code\n\t\tif(this.namedKeys[s]) {\n\t\t\tinfo.keyCode = this.namedKeys[s];\n\t\t}\n\t}\n\tif(info.keyCode) {\n\t\treturn info;\n\t} else {\n\t\treturn null;\n\t}\n};\n\n/*\nParse a list of key descriptors into an array of keyInfo objects. The key descriptors can be passed as an array of strings or a space separated string\n*/\nKeyboardManager.prototype.parseKeyDescriptors = function(keyDescriptors,options) {\n\tvar self = this;\n\toptions = options || {};\n\toptions.stack = options.stack || [];\n\tvar wiki = options.wiki || $tw.wiki;\n\tif(typeof keyDescriptors === \"string\" && keyDescriptors === \"\") {\n\t\treturn [];\n\t}\n\tif(!$tw.utils.isArray(keyDescriptors)) {\n\t\tkeyDescriptors = keyDescriptors.split(\" \");\n\t}\n\tvar result = [];\n\t$tw.utils.each(keyDescriptors,function(keyDescriptor) {\n\t\t// Look for a named shortcut\n\t\tif(keyDescriptor.substr(0,2) === \"((\" && keyDescriptor.substr(-2,2) === \"))\") {\n\t\t\tif(options.stack.indexOf(keyDescriptor) === -1) {\n\t\t\t\toptions.stack.push(keyDescriptor);\n\t\t\t\tvar name = keyDescriptor.substring(2,keyDescriptor.length - 2),\n\t\t\t\t\tlookupName = function(configName) {\n\t\t\t\t\t\tvar keyDescriptors = wiki.getTiddlerText(\"$:/config/\" + configName + \"/\" + name);\n\t\t\t\t\t\tif(keyDescriptors) {\n\t\t\t\t\t\t\tresult.push.apply(result,self.parseKeyDescriptors(keyDescriptors,options));\n\t\t\t\t\t\t}\n\t\t\t\t\t};\n\t\t\t\tlookupName(\"shortcuts\");\n\t\t\t\tlookupName($tw.platform.isMac ? \"shortcuts-mac\" : \"shortcuts-not-mac\");\n\t\t\t\tlookupName($tw.platform.isWindows ? \"shortcuts-windows\" : \"shortcuts-not-windows\");\n\t\t\t\tlookupName($tw.platform.isLinux ? \"shortcuts-linux\" : \"shortcuts-not-linux\");\n\t\t\t}\n\t\t} else {\n\t\t\tresult.push(self.parseKeyDescriptor(keyDescriptor));\n\t\t}\n\t});\n\treturn result;\n};\n\nKeyboardManager.prototype.getPrintableShortcuts = function(keyInfoArray) {\n\tvar self = this,\n\t\tresult = [];\n\t$tw.utils.each(keyInfoArray,function(keyInfo) {\n\t\tif(keyInfo) {\n\t\t\tresult.push((keyInfo.ctrlKey ? \"ctrl-\" : \"\") + \n\t\t\t\t (keyInfo.shiftKey ? \"shift-\" : \"\") + \n\t\t\t\t (keyInfo.altKey ? \"alt-\" : \"\") + \n\t\t\t\t (keyInfo.metaKey ? self.metaKeyName : \"\") + \n\t\t\t\t (self.keyNames[keyInfo.keyCode]));\n\t\t}\n\t});\n\treturn result;\n}\n\nKeyboardManager.prototype.checkKeyDescriptor = function(event,keyInfo) {\n\treturn keyInfo &&\n\t\t\tevent.keyCode === keyInfo.keyCode && \n\t\t\tevent.shiftKey === keyInfo.shiftKey && \n\t\t\tevent.altKey === keyInfo.altKey && \n\t\t\tevent.ctrlKey === keyInfo.ctrlKey && \n\t\t\tevent.metaKey === keyInfo.metaKey;\n};\n\nKeyboardManager.prototype.checkKeyDescriptors = function(event,keyInfoArray) {\n\tfor(var t=0; t<keyInfoArray.length; t++) {\n\t\tif(this.checkKeyDescriptor(event,keyInfoArray[t])) {\n\t\t\treturn true;\n\t\t}\n\t}\n\treturn false;\n};\n\nexports.KeyboardManager = KeyboardManager;\n\n})();\n",
"title": "$:/core/modules/keyboard.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/language.js": {
"text": "/*\\\ntitle: $:/core/modules/language.js\ntype: application/javascript\nmodule-type: global\n\nThe $tw.Language() manages translateable strings\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nCreate an instance of the language manager. Options include:\nwiki: wiki from which to retrieve translation tiddlers\n*/\nfunction Language(options) {\n\toptions = options || \"\";\n\tthis.wiki = options.wiki || $tw.wiki;\n}\n\n/*\nReturn a wikified translateable string. The title is automatically prefixed with \"$:/language/\"\nOptions include:\nvariables: optional hashmap of variables to supply to the language wikification\n*/\nLanguage.prototype.getString = function(title,options) {\n\toptions = options || {};\n\ttitle = \"$:/language/\" + title;\n\treturn this.wiki.renderTiddler(\"text/plain\",title,{variables: options.variables});\n};\n\n/*\nReturn a raw, unwikified translateable string. The title is automatically prefixed with \"$:/language/\"\n*/\nLanguage.prototype.getRawString = function(title) {\n\ttitle = \"$:/language/\" + title;\n\treturn this.wiki.getTiddlerText(title);\n};\n\nexports.Language = Language;\n\n})();\n",
"title": "$:/core/modules/language.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/macros/changecount.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/changecount.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to return the changecount for the current tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"changecount\";\n\nexports.params = [];\n\n/*\nRun the macro\n*/\nexports.run = function() {\n\treturn this.wiki.getChangeCount(this.getVariable(\"currentTiddler\")) + \"\";\n};\n\n})();\n",
"title": "$:/core/modules/macros/changecount.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/contrastcolour.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/contrastcolour.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to choose which of two colours has the highest contrast with a base colour\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"contrastcolour\";\n\nexports.params = [\n\t{name: \"target\"},\n\t{name: \"fallbackTarget\"},\n\t{name: \"colourA\"},\n\t{name: \"colourB\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(target,fallbackTarget,colourA,colourB) {\n\tvar rgbTarget = $tw.utils.parseCSSColor(target) || $tw.utils.parseCSSColor(fallbackTarget);\n\tif(!rgbTarget) {\n\t\treturn colourA;\n\t}\n\tvar rgbColourA = $tw.utils.parseCSSColor(colourA),\n\t\trgbColourB = $tw.utils.parseCSSColor(colourB);\n\tif(rgbColourA && !rgbColourB) {\n\t\treturn rgbColourA;\n\t}\n\tif(rgbColourB && !rgbColourA) {\n\t\treturn rgbColourB;\n\t}\n\tif(!rgbColourA && !rgbColourB) {\n\t\t// If neither colour is readable, return a crude inverse of the target\n\t\treturn [255 - rgbTarget[0],255 - rgbTarget[1],255 - rgbTarget[2],rgbTarget[3]];\n\t}\n\t// Colour brightness formula derived from http://www.w3.org/WAI/ER/WD-AERT/#color-contrast\n\tvar brightnessTarget = rgbTarget[0] * 0.299 + rgbTarget[1] * 0.587 + rgbTarget[2] * 0.114,\n\t\tbrightnessA = rgbColourA[0] * 0.299 + rgbColourA[1] * 0.587 + rgbColourA[2] * 0.114,\n\t\tbrightnessB = rgbColourB[0] * 0.299 + rgbColourB[1] * 0.587 + rgbColourB[2] * 0.114;\n\treturn Math.abs(brightnessTarget - brightnessA) > Math.abs(brightnessTarget - brightnessB) ? colourA : colourB;\n};\n\n})();\n",
"title": "$:/core/modules/macros/contrastcolour.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/csvtiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/csvtiddlers.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to output tiddlers matching a filter to CSV\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"csvtiddlers\";\n\nexports.params = [\n\t{name: \"filter\"},\n\t{name: \"format\"},\n];\n\n/*\nRun the macro\n*/\nexports.run = function(filter,format) {\n\tvar self = this,\n\t\ttiddlers = this.wiki.filterTiddlers(filter),\n\t\ttiddler,\n\t\tfields = [],\n\t\tt,f;\n\t// Collect all the fields\n\tfor(t=0;t<tiddlers.length; t++) {\n\t\ttiddler = this.wiki.getTiddler(tiddlers[t]);\n\t\tfor(f in tiddler.fields) {\n\t\t\tif(fields.indexOf(f) === -1) {\n\t\t\t\tfields.push(f);\n\t\t\t}\n\t\t}\n\t}\n\t// Sort the fields and bring the standard ones to the front\n\tfields.sort();\n\t\"title text modified modifier created creator\".split(\" \").reverse().forEach(function(value,index) {\n\t\tvar p = fields.indexOf(value);\n\t\tif(p !== -1) {\n\t\t\tfields.splice(p,1);\n\t\t\tfields.unshift(value)\n\t\t}\n\t});\n\t// Output the column headings\n\tvar output = [], row = [];\n\tfields.forEach(function(value) {\n\t\trow.push(quoteAndEscape(value))\n\t});\n\toutput.push(row.join(\",\"));\n\t// Output each tiddler\n\tfor(var t=0;t<tiddlers.length; t++) {\n\t\trow = [];\n\t\ttiddler = this.wiki.getTiddler(tiddlers[t]);\n\t\t\tfor(f=0; f<fields.length; f++) {\n\t\t\t\trow.push(quoteAndEscape(tiddler ? tiddler.getFieldString(fields[f]) || \"\" : \"\"));\n\t\t\t}\n\t\toutput.push(row.join(\",\"));\n\t}\n\treturn output.join(\"\\n\");\n};\n\nfunction quoteAndEscape(value) {\n\treturn \"\\\"\" + value.replace(/\"/mg,\"\\\"\\\"\") + \"\\\"\";\n}\n\n})();\n",
"title": "$:/core/modules/macros/csvtiddlers.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/displayshortcuts.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/displayshortcuts.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to display a list of keyboard shortcuts in human readable form. Notably, it resolves named shortcuts like `((bold))` to the underlying keystrokes.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"displayshortcuts\";\n\nexports.params = [\n\t{name: \"shortcuts\"},\n\t{name: \"prefix\"},\n\t{name: \"separator\"},\n\t{name: \"suffix\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(shortcuts,prefix,separator,suffix) {\n\tvar shortcutArray = $tw.keyboardManager.getPrintableShortcuts($tw.keyboardManager.parseKeyDescriptors(shortcuts,{\n\t\twiki: this.wiki\n\t}));\n\tif(shortcutArray.length > 0) {\n\t\tshortcutArray.sort(function(a,b) {\n\t\t return a.toLowerCase().localeCompare(b.toLowerCase());\n\t\t})\n\t\treturn prefix + shortcutArray.join(separator) + suffix;\n\t} else {\n\t\treturn \"\";\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/macros/displayshortcuts.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/dumpvariables.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/dumpvariables.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to dump all active variable values\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"dumpvariables\";\n\nexports.params = [\n];\n\n/*\nRun the macro\n*/\nexports.run = function() {\n\tvar output = [\"|!Variable |!Value |\"],\n\t\tvariables = [], variable;\n\tfor(variable in this.variables) {\n\t\tvariables.push(variable);\n\t}\n\tvariables.sort();\n\tfor(var index=0; index<variables.length; index++) {\n\t\tvar variable = variables[index];\n\t\toutput.push(\"|\" + variable + \" |<input size=50 value=<<\" + variable + \">>/> |\")\n\t}\n\treturn output.join(\"\\n\");\n};\n\n})();\n",
"title": "$:/core/modules/macros/dumpvariables.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/jsontiddlers.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/jsontiddlers.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to output tiddlers matching a filter to JSON\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"jsontiddlers\";\n\nexports.params = [\n\t{name: \"filter\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(filter) {\n\tvar tiddlers = this.wiki.filterTiddlers(filter),\n\t\tdata = [];\n\tfor(var t=0;t<tiddlers.length; t++) {\n\t\tvar tiddler = this.wiki.getTiddler(tiddlers[t]);\n\t\tif(tiddler) {\n\t\t\tvar fields = new Object();\n\t\t\tfor(var field in tiddler.fields) {\n\t\t\t\tfields[field] = tiddler.getFieldString(field);\n\t\t\t}\n\t\t\tdata.push(fields);\n\t\t}\n\t}\n\treturn JSON.stringify(data,null,$tw.config.preferences.jsonSpaces);\n};\n\n})();\n",
"title": "$:/core/modules/macros/jsontiddlers.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/makedatauri.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/makedatauri.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to convert a string of text to a data URI\n\n<<makedatauri text:\"Text to be converted\" type:\"text/vnd.tiddlywiki\">>\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"makedatauri\";\n\nexports.params = [\n\t{name: \"text\"},\n\t{name: \"type\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(text,type) {\n\treturn $tw.utils.makeDataUri(text,type);\n};\n\n})();\n",
"title": "$:/core/modules/macros/makedatauri.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/now.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/now.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to return a formatted version of the current time\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"now\";\n\nexports.params = [\n\t{name: \"format\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(format) {\n\treturn $tw.utils.formatDateString(new Date(),format || \"0hh:0mm, DDth MMM YYYY\");\n};\n\n})();\n",
"title": "$:/core/modules/macros/now.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/qualify.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/qualify.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to qualify a state tiddler title according\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"qualify\";\n\nexports.params = [\n\t{name: \"title\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(title) {\n\treturn title + \"-\" + this.getStateQualifier();\n};\n\n})();\n",
"title": "$:/core/modules/macros/qualify.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/resolvepath.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/resolvepath.js\ntype: application/javascript\nmodule-type: macro\n\nResolves a relative path for an absolute rootpath.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"resolvepath\";\n\nexports.params = [\n\t{name: \"source\"},\n\t{name: \"root\"}\n];\n\n/*\nRun the macro\n*/\nexports.run = function(source, root) {\n\treturn $tw.utils.resolvePath(source, root);\n};\n\n})();\n",
"title": "$:/core/modules/macros/resolvepath.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/macros/version.js": {
"text": "/*\\\ntitle: $:/core/modules/macros/version.js\ntype: application/javascript\nmodule-type: macro\n\nMacro to return the TiddlyWiki core version number\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInformation about this macro\n*/\n\nexports.name = \"version\";\n\nexports.params = [];\n\n/*\nRun the macro\n*/\nexports.run = function() {\n\treturn $tw.version;\n};\n\n})();\n",
"title": "$:/core/modules/macros/version.js",
"type": "application/javascript",
"module-type": "macro"
},
"$:/core/modules/parsers/audioparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/audioparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe audio parser parses an audio tiddler into an embeddable HTML element\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar AudioParser = function(type,text,options) {\n\tvar element = {\n\t\t\ttype: \"element\",\n\t\t\ttag: \"audio\",\n\t\t\tattributes: {\n\t\t\t\tcontrols: {type: \"string\", value: \"controls\"}\n\t\t\t}\n\t\t},\n\t\tsrc;\n\tif(options._canonical_uri) {\n\t\telement.attributes.src = {type: \"string\", value: options._canonical_uri};\n\t} else if(text) {\n\t\telement.attributes.src = {type: \"string\", value: \"data:\" + type + \";base64,\" + text};\n\t}\n\tthis.tree = [element];\n};\n\nexports[\"audio/ogg\"] = AudioParser;\nexports[\"audio/mpeg\"] = AudioParser;\nexports[\"audio/mp3\"] = AudioParser;\nexports[\"audio/mp4\"] = AudioParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/audioparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/csvparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/csvparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe CSV text parser processes CSV files into a table wrapped in a scrollable widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar CsvParser = function(type,text,options) {\n\t// Table framework\n\tthis.tree = [{\n\t\t\"type\": \"scrollable\", \"children\": [{\n\t\t\t\"type\": \"element\", \"tag\": \"table\", \"children\": [{\n\t\t\t\t\"type\": \"element\", \"tag\": \"tbody\", \"children\": []\n\t\t\t}], \"attributes\": {\n\t\t\t\t\"class\": {\"type\": \"string\", \"value\": \"tc-csv-table\"}\n\t\t\t}\n\t\t}]\n\t}];\n\t// Split the text into lines\n\tvar lines = text.split(/\\r?\\n/mg),\n\t\ttag = \"th\";\n\tfor(var line=0; line<lines.length; line++) {\n\t\tvar lineText = lines[line];\n\t\tif(lineText) {\n\t\t\tvar row = {\n\t\t\t\t\t\"type\": \"element\", \"tag\": \"tr\", \"children\": []\n\t\t\t\t};\n\t\t\tvar columns = lineText.split(\",\");\n\t\t\tfor(var column=0; column<columns.length; column++) {\n\t\t\t\trow.children.push({\n\t\t\t\t\t\t\"type\": \"element\", \"tag\": tag, \"children\": [{\n\t\t\t\t\t\t\t\"type\": \"text\",\n\t\t\t\t\t\t\t\"text\": columns[column]\n\t\t\t\t\t\t}]\n\t\t\t\t\t});\n\t\t\t}\n\t\t\ttag = \"td\";\n\t\t\tthis.tree[0].children[0].children[0].children.push(row);\n\t\t}\n\t}\n};\n\nexports[\"text/csv\"] = CsvParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/csvparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/htmlparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/htmlparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe HTML parser displays text as raw HTML\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar HtmlParser = function(type,text,options) {\n\tvar src;\n\tif(options._canonical_uri) {\n\t\tsrc = options._canonical_uri;\n\t} else if(text) {\n\t\tsrc = \"data:text/html;charset=utf-8,\" + encodeURIComponent(text);\n\t}\n\tthis.tree = [{\n\t\ttype: \"element\",\n\t\ttag: \"iframe\",\n\t\tattributes: {\n\t\t\tsrc: {type: \"string\", value: src},\n\t\t\tsandbox: {type: \"string\", value: \"\"}\n\t\t}\n\t}];\n};\n\nexports[\"text/html\"] = HtmlParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/htmlparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/imageparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/imageparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe image parser parses an image into an embeddable HTML element\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar ImageParser = function(type,text,options) {\n\tvar element = {\n\t\t\ttype: \"element\",\n\t\t\ttag: \"img\",\n\t\t\tattributes: {}\n\t\t},\n\t\tsrc;\n\tif(options._canonical_uri) {\n\t\telement.attributes.src = {type: \"string\", value: options._canonical_uri};\n\t\tif(type === \"application/pdf\" || type === \".pdf\") {\n\t\t\telement.tag = \"embed\";\n\t\t}\n\t} else if(text) {\n\t\tif(type === \"application/pdf\" || type === \".pdf\") {\n\t\t\telement.attributes.src = {type: \"string\", value: \"data:application/pdf;base64,\" + text};\n\t\t\telement.tag = \"embed\";\n\t\t} else if(type === \"image/svg+xml\" || type === \".svg\") {\n\t\t\telement.attributes.src = {type: \"string\", value: \"data:image/svg+xml,\" + encodeURIComponent(text)};\n\t\t} else {\n\t\t\telement.attributes.src = {type: \"string\", value: \"data:\" + type + \";base64,\" + text};\n\t\t}\n\t}\n\tthis.tree = [element];\n};\n\nexports[\"image/svg+xml\"] = ImageParser;\nexports[\"image/jpg\"] = ImageParser;\nexports[\"image/jpeg\"] = ImageParser;\nexports[\"image/png\"] = ImageParser;\nexports[\"image/gif\"] = ImageParser;\nexports[\"application/pdf\"] = ImageParser;\nexports[\"image/x-icon\"] = ImageParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/imageparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/utils/parseutils.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/parseutils.js\ntype: application/javascript\nmodule-type: utils\n\nUtility functions concerned with parsing text into tokens.\n\nMost functions have the following pattern:\n\n* The parameters are:\n** `source`: the source string being parsed\n** `pos`: the current parse position within the string\n** Any further parameters are used to identify the token that is being parsed\n* The return value is:\n** null if the token was not found at the specified position\n** an object representing the token with the following standard fields:\n*** `type`: string indicating the type of the token\n*** `start`: start position of the token in the source string\n*** `end`: end position of the token in the source string\n*** Any further fields required to describe the token\n\nThe exception is `skipWhiteSpace`, which just returns the position after the whitespace.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nLook for a whitespace token. Returns null if not found, otherwise returns {type: \"whitespace\", start:, end:,}\n*/\nexports.parseWhiteSpace = function(source,pos) {\n\tvar p = pos,c;\n\twhile(true) {\n\t\tc = source.charAt(p);\n\t\tif((c === \" \") || (c === \"\\f\") || (c === \"\\n\") || (c === \"\\r\") || (c === \"\\t\") || (c === \"\\v\") || (c === \"\\u00a0\")) { // Ignores some obscure unicode spaces\n\t\t\tp++;\n\t\t} else {\n\t\t\tbreak;\n\t\t}\n\t}\n\tif(p === pos) {\n\t\treturn null;\n\t} else {\n\t\treturn {\n\t\t\ttype: \"whitespace\",\n\t\t\tstart: pos,\n\t\t\tend: p\n\t\t}\n\t}\n};\n\n/*\nConvenience wrapper for parseWhiteSpace. Returns the position after the whitespace\n*/\nexports.skipWhiteSpace = function(source,pos) {\n\tvar c;\n\twhile(true) {\n\t\tc = source.charAt(pos);\n\t\tif((c === \" \") || (c === \"\\f\") || (c === \"\\n\") || (c === \"\\r\") || (c === \"\\t\") || (c === \"\\v\") || (c === \"\\u00a0\")) { // Ignores some obscure unicode spaces\n\t\t\tpos++;\n\t\t} else {\n\t\t\treturn pos;\n\t\t}\n\t}\n};\n\n/*\nLook for a given string token. Returns null if not found, otherwise returns {type: \"token\", value:, start:, end:,}\n*/\nexports.parseTokenString = function(source,pos,token) {\n\tvar match = source.indexOf(token,pos) === pos;\n\tif(match) {\n\t\treturn {\n\t\t\ttype: \"token\",\n\t\t\tvalue: token,\n\t\t\tstart: pos,\n\t\t\tend: pos + token.length\n\t\t};\n\t}\n\treturn null;\n};\n\n/*\nLook for a token matching a regex. Returns null if not found, otherwise returns {type: \"regexp\", match:, start:, end:,}\n*/\nexports.parseTokenRegExp = function(source,pos,reToken) {\n\tvar node = {\n\t\ttype: \"regexp\",\n\t\tstart: pos\n\t};\n\treToken.lastIndex = pos;\n\tnode.match = reToken.exec(source);\n\tif(node.match && node.match.index === pos) {\n\t\tnode.end = pos + node.match[0].length;\n\t\treturn node;\n\t} else {\n\t\treturn null;\n\t}\n};\n\n/*\nLook for a string literal. Returns null if not found, otherwise returns {type: \"string\", value:, start:, end:,}\n*/\nexports.parseStringLiteral = function(source,pos) {\n\tvar node = {\n\t\ttype: \"string\",\n\t\tstart: pos\n\t};\n\tvar reString = /(?:\"\"\"([\\s\\S]*?)\"\"\"|\"([^\"]*)\")|(?:'([^']*)')/g;\n\treString.lastIndex = pos;\n\tvar match = reString.exec(source);\n\tif(match && match.index === pos) {\n\t\tnode.value = match[1] !== undefined ? match[1] :(\n\t\t\tmatch[2] !== undefined ? match[2] : match[3] \n\t\t\t\t\t);\n\t\tnode.end = pos + match[0].length;\n\t\treturn node;\n\t} else {\n\t\treturn null;\n\t}\n};\n\n/*\nLook for a macro invocation parameter. Returns null if not found, or {type: \"macro-parameter\", name:, value:, start:, end:}\n*/\nexports.parseMacroParameter = function(source,pos) {\n\tvar node = {\n\t\ttype: \"macro-parameter\",\n\t\tstart: pos\n\t};\n\t// Define our regexp\n\tvar reMacroParameter = /(?:([A-Za-z0-9\\-_]+)\\s*:)?(?:\\s*(?:\"\"\"([\\s\\S]*?)\"\"\"|\"([^\"]*)\"|'([^']*)'|\\[\\[([^\\]]*)\\]\\]|([^\\s>\"'=]+)))/g;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for the parameter\n\tvar token = $tw.utils.parseTokenRegExp(source,pos,reMacroParameter);\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Get the parameter details\n\tnode.value = token.match[2] !== undefined ? token.match[2] : (\n\t\t\t\t\ttoken.match[3] !== undefined ? token.match[3] : (\n\t\t\t\t\t\ttoken.match[4] !== undefined ? token.match[4] : (\n\t\t\t\t\t\t\ttoken.match[5] !== undefined ? token.match[5] : (\n\t\t\t\t\t\t\t\ttoken.match[6] !== undefined ? token.match[6] : (\n\t\t\t\t\t\t\t\t\t\"\"\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t)\n\t\t\t\t\t\t)\n\t\t\t\t\t)\n\t\t\t\t);\n\tif(token.match[1]) {\n\t\tnode.name = token.match[1];\n\t}\n\t// Update the end position\n\tnode.end = pos;\n\treturn node;\n};\n\n/*\nLook for a macro invocation. Returns null if not found, or {type: \"macrocall\", name:, parameters:, start:, end:}\n*/\nexports.parseMacroInvocation = function(source,pos) {\n\tvar node = {\n\t\ttype: \"macrocall\",\n\t\tstart: pos,\n\t\tparams: []\n\t};\n\t// Define our regexps\n\tvar reMacroName = /([^\\s>\"'=]+)/g;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for a double less than sign\n\tvar token = $tw.utils.parseTokenString(source,pos,\"<<\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Get the macro name\n\tvar name = $tw.utils.parseTokenRegExp(source,pos,reMacroName);\n\tif(!name) {\n\t\treturn null;\n\t}\n\tnode.name = name.match[1];\n\tpos = name.end;\n\t// Process parameters\n\tvar parameter = $tw.utils.parseMacroParameter(source,pos);\n\twhile(parameter) {\n\t\tnode.params.push(parameter);\n\t\tpos = parameter.end;\n\t\t// Get the next parameter\n\t\tparameter = $tw.utils.parseMacroParameter(source,pos);\n\t}\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for a double greater than sign\n\ttoken = $tw.utils.parseTokenString(source,pos,\">>\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Update the end position\n\tnode.end = pos;\n\treturn node;\n};\n\n/*\nLook for an HTML attribute definition. Returns null if not found, otherwise returns {type: \"attribute\", name:, valueType: \"string|indirect|macro\", value:, start:, end:,}\n*/\nexports.parseAttribute = function(source,pos) {\n\tvar node = {\n\t\tstart: pos\n\t};\n\t// Define our regexps\n\tvar reAttributeName = /([^\\/\\s>\"'=]+)/g,\n\t\treUnquotedAttribute = /([^\\/\\s<>\"'=]+)/g,\n\t\treIndirectValue = /\\{\\{([^\\}]+)\\}\\}/g;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Get the attribute name\n\tvar name = $tw.utils.parseTokenRegExp(source,pos,reAttributeName);\n\tif(!name) {\n\t\treturn null;\n\t}\n\tnode.name = name.match[1];\n\tpos = name.end;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for an equals sign\n\tvar token = $tw.utils.parseTokenString(source,pos,\"=\");\n\tif(token) {\n\t\tpos = token.end;\n\t\t// Skip whitespace\n\t\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t\t// Look for a string literal\n\t\tvar stringLiteral = $tw.utils.parseStringLiteral(source,pos);\n\t\tif(stringLiteral) {\n\t\t\tpos = stringLiteral.end;\n\t\t\tnode.type = \"string\";\n\t\t\tnode.value = stringLiteral.value;\n\t\t} else {\n\t\t\t// Look for an indirect value\n\t\t\tvar indirectValue = $tw.utils.parseTokenRegExp(source,pos,reIndirectValue);\n\t\t\tif(indirectValue) {\n\t\t\t\tpos = indirectValue.end;\n\t\t\t\tnode.type = \"indirect\";\n\t\t\t\tnode.textReference = indirectValue.match[1];\n\t\t\t} else {\n\t\t\t\t// Look for a unquoted value\n\t\t\t\tvar unquotedValue = $tw.utils.parseTokenRegExp(source,pos,reUnquotedAttribute);\n\t\t\t\tif(unquotedValue) {\n\t\t\t\t\tpos = unquotedValue.end;\n\t\t\t\t\tnode.type = \"string\";\n\t\t\t\t\tnode.value = unquotedValue.match[1];\n\t\t\t\t} else {\n\t\t\t\t\t// Look for a macro invocation value\n\t\t\t\t\tvar macroInvocation = $tw.utils.parseMacroInvocation(source,pos);\n\t\t\t\t\tif(macroInvocation) {\n\t\t\t\t\t\tpos = macroInvocation.end;\n\t\t\t\t\t\tnode.type = \"macro\";\n\t\t\t\t\t\tnode.value = macroInvocation;\n\t\t\t\t\t} else {\n\t\t\t\t\t\tnode.type = \"string\";\n\t\t\t\t\t\tnode.value = \"true\";\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t} else {\n\t\tnode.type = \"string\";\n\t\tnode.value = \"true\";\n\t}\n\t// Update the end position\n\tnode.end = pos;\n\treturn node;\n};\n\n})();\n",
"title": "$:/core/modules/utils/parseutils.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/parsers/textparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/textparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe plain text parser processes blocks of source text into a degenerate parse tree consisting of a single text node\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar TextParser = function(type,text,options) {\n\tthis.tree = [{\n\t\ttype: \"codeblock\",\n\t\tattributes: {\n\t\t\tcode: {type: \"string\", value: text},\n\t\t\tlanguage: {type: \"string\", value: type}\n\t\t}\n\t}];\n};\n\nexports[\"text/plain\"] = TextParser;\nexports[\"text/x-tiddlywiki\"] = TextParser;\nexports[\"application/javascript\"] = TextParser;\nexports[\"application/json\"] = TextParser;\nexports[\"text/css\"] = TextParser;\nexports[\"application/x-tiddler-dictionary\"] = TextParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/textparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/videoparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/videoparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe video parser parses a video tiddler into an embeddable HTML element\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar AudioParser = function(type,text,options) {\n\tvar element = {\n\t\t\ttype: \"element\",\n\t\t\ttag: \"video\",\n\t\t\tattributes: {\n\t\t\t\tcontrols: {type: \"string\", value: \"controls\"}\n\t\t\t}\n\t\t},\n\t\tsrc;\n\tif(options._canonical_uri) {\n\t\telement.attributes.src = {type: \"string\", value: options._canonical_uri};\n\t} else if(text) {\n\t\telement.attributes.src = {type: \"string\", value: \"data:\" + type + \";base64,\" + text};\n\t}\n\tthis.tree = [element];\n};\n\nexports[\"video/mp4\"] = AudioParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/videoparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/wikiparser/rules/codeblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/codeblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for code blocks. For example:\n\n```\n\t```\n\tThis text will not be //wikified//\n\t```\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"codeblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match and get language if defined\n\tthis.matchRegExp = /```([\\w-]*)\\r?\\n/mg;\n};\n\nexports.parse = function() {\n\tvar reEnd = /(\\r?\\n```$)/mg;\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Look for the end of the block\n\treEnd.lastIndex = this.parser.pos;\n\tvar match = reEnd.exec(this.parser.source),\n\t\ttext;\n\t// Process the block\n\tif(match) {\n\t\ttext = this.parser.source.substring(this.parser.pos,match.index);\n\t\tthis.parser.pos = match.index + match[0].length;\n\t} else {\n\t\ttext = this.parser.source.substr(this.parser.pos);\n\t\tthis.parser.pos = this.parser.sourceLength;\n\t}\n\t// Return the $codeblock widget\n\treturn [{\n\t\t\ttype: \"codeblock\",\n\t\t\tattributes: {\n\t\t\t\t\tcode: {type: \"string\", value: text},\n\t\t\t\t\tlanguage: {type: \"string\", value: this.match[1]}\n\t\t\t}\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/codeblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/codeinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/codeinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for code runs. For example:\n\n```\n\tThis is a `code run`.\n\tThis is another ``code run``\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"codeinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /(``?)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tvar reEnd = new RegExp(this.match[1], \"mg\");\n\t// Look for the end marker\n\treEnd.lastIndex = this.parser.pos;\n\tvar match = reEnd.exec(this.parser.source),\n\t\ttext;\n\t// Process the text\n\tif(match) {\n\t\ttext = this.parser.source.substring(this.parser.pos,match.index);\n\t\tthis.parser.pos = match.index + match[0].length;\n\t} else {\n\t\ttext = this.parser.source.substr(this.parser.pos);\n\t\tthis.parser.pos = this.parser.sourceLength;\n\t}\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"code\",\n\t\tchildren: [{\n\t\t\ttype: \"text\",\n\t\t\ttext: text\n\t\t}]\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/codeinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/commentblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/commentblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for HTML comments. For example:\n\n```\n<!-- This is a comment -->\n```\n\nNote that the syntax for comments is simplified to an opening \"<!--\" sequence and a closing \"-->\" sequence -- HTML itself implements a more complex format (see http://ostermiller.org/findhtmlcomment.html)\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"commentblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\tthis.matchRegExp = /<!--/mg;\n\tthis.endMatchRegExp = /-->/mg;\n};\n\nexports.findNextMatch = function(startPos) {\n\tthis.matchRegExp.lastIndex = startPos;\n\tthis.match = this.matchRegExp.exec(this.parser.source);\n\tif(this.match) {\n\t\tthis.endMatchRegExp.lastIndex = startPos + this.match[0].length;\n\t\tthis.endMatch = this.endMatchRegExp.exec(this.parser.source);\n\t\tif(this.endMatch) {\n\t\t\treturn this.match.index;\n\t\t}\n\t}\n\treturn undefined;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.endMatchRegExp.lastIndex;\n\t// Don't return any elements\n\treturn [];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/commentblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/commentinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/commentinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for HTML comments. For example:\n\n```\n<!-- This is a comment -->\n```\n\nNote that the syntax for comments is simplified to an opening \"<!--\" sequence and a closing \"-->\" sequence -- HTML itself implements a more complex format (see http://ostermiller.org/findhtmlcomment.html)\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"commentinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\tthis.matchRegExp = /<!--/mg;\n\tthis.endMatchRegExp = /-->/mg;\n};\n\nexports.findNextMatch = function(startPos) {\n\tthis.matchRegExp.lastIndex = startPos;\n\tthis.match = this.matchRegExp.exec(this.parser.source);\n\tif(this.match) {\n\t\tthis.endMatchRegExp.lastIndex = startPos + this.match[0].length;\n\t\tthis.endMatch = this.endMatchRegExp.exec(this.parser.source);\n\t\tif(this.endMatch) {\n\t\t\treturn this.match.index;\n\t\t}\n\t}\n\treturn undefined;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.endMatchRegExp.lastIndex;\n\t// Don't return any elements\n\treturn [];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/commentinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/dash.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/dash.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for dashes. For example:\n\n```\nThis is an en-dash: --\n\nThis is an em-dash: ---\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"dash\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /-{2,3}(?!-)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tvar dash = this.match[0].length === 2 ? \"–\" : \"—\";\n\treturn [{\n\t\ttype: \"entity\",\n\t\tentity: dash\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/dash.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/bold.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/bold.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - bold. For example:\n\n```\n\tThis is ''bold'' text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except bold \n\\rules only bold \n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"bold\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /''/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/''/mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"strong\",\n\t\tchildren: tree\n\t}];\n};\n\n})();",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/bold.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/italic.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/italic.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - italic. For example:\n\n```\n\tThis is //italic// text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except italic\n\\rules only italic\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"italic\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\/\\//mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/\\/\\//mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"em\",\n\t\tchildren: tree\n\t}];\n};\n\n})();",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/italic.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/strikethrough.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/strikethrough.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - strikethrough. For example:\n\n```\n\tThis is ~~strikethrough~~ text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except strikethrough \n\\rules only strikethrough \n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"strikethrough\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /~~/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/~~/mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"strike\",\n\t\tchildren: tree\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/strikethrough.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/subscript.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/subscript.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - subscript. For example:\n\n```\n\tThis is ,,subscript,, text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except subscript \n\\rules only subscript \n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"subscript\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /,,/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/,,/mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"sub\",\n\t\tchildren: tree\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/subscript.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/superscript.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/superscript.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - superscript. For example:\n\n```\n\tThis is ^^superscript^^ text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except superscript \n\\rules only superscript \n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"superscript\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\^\\^/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/\\^\\^/mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"sup\",\n\t\tchildren: tree\n\t}];\n};\n\n})();",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/superscript.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/emphasis/underscore.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/emphasis/underscore.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for emphasis - underscore. For example:\n\n```\n\tThis is __underscore__ text\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except underscore \n\\rules only underscore\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"underscore\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /__/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\n\t// Parse the run including the terminator\n\tvar tree = this.parser.parseInlineRun(/__/mg,{eatTerminator: true});\n\n\t// Return the classed span\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"u\",\n\t\tchildren: tree\n\t}];\n};\n\n})();",
"title": "$:/core/modules/parsers/wikiparser/rules/emphasis/underscore.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/entity.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/entity.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for HTML entities. For example:\n\n```\n\tThis is a copyright symbol: ©\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"entity\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /(&#?[a-zA-Z0-9]{2,8};)/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Get all the details of the match\n\tvar entityString = this.match[1];\n\t// Move past the macro call\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Return the entity\n\treturn [{type: \"entity\", entity: this.match[0]}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/entity.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/extlink.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/extlink.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for external links. For example:\n\n```\nAn external link: http://www.tiddlywiki.com/\n\nA suppressed external link: ~http://www.tiddlyspace.com/\n```\n\nExternal links can be suppressed by preceding them with `~`.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"extlink\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /~?(?:file|http|https|mailto|ftp|irc|news|data|skype):[^\\s<>{}\\[\\]`|\"\\\\^]+(?:\\/|\\b)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Create the link unless it is suppressed\n\tif(this.match[0].substr(0,1) === \"~\") {\n\t\treturn [{type: \"text\", text: this.match[0].substr(1)}];\n\t} else {\n\t\treturn [{\n\t\t\ttype: \"element\",\n\t\t\ttag: \"a\",\n\t\t\tattributes: {\n\t\t\t\thref: {type: \"string\", value: this.match[0]},\n\t\t\t\t\"class\": {type: \"string\", value: \"tc-tiddlylink-external\"},\n\t\t\t\ttarget: {type: \"string\", value: \"_blank\"},\n\t\t\t\trel: {type: \"string\", value: \"noopener noreferrer\"}\n\t\t\t},\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\", text: this.match[0]\n\t\t\t}]\n\t\t}];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/extlink.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/filteredtranscludeblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/filteredtranscludeblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for block-level filtered transclusion. For example:\n\n```\n{{{ [tag[docs]] }}}\n{{{ [tag[docs]] |tooltip}}}\n{{{ [tag[docs]] ||TemplateTitle}}}\n{{{ [tag[docs]] |tooltip||TemplateTitle}}}\n{{{ [tag[docs]] }}width:40;height:50;}.class.class\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"filteredtranscludeblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\{\\{\\{([^\\|]+?)(?:\\|([^\\|\\{\\}]+))?(?:\\|\\|([^\\|\\{\\}]+))?\\}\\}([^\\}]*)\\}(?:\\.(\\S+))?(?:\\r?\\n|$)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Get the match details\n\tvar filter = this.match[1],\n\t\ttooltip = this.match[2],\n\t\ttemplate = $tw.utils.trim(this.match[3]),\n\t\tstyle = this.match[4],\n\t\tclasses = this.match[5];\n\t// Return the list widget\n\tvar node = {\n\t\ttype: \"list\",\n\t\tattributes: {\n\t\t\tfilter: {type: \"string\", value: filter}\n\t\t},\n\t\tisBlock: true\n\t};\n\tif(tooltip) {\n\t\tnode.attributes.tooltip = {type: \"string\", value: tooltip};\n\t}\n\tif(template) {\n\t\tnode.attributes.template = {type: \"string\", value: template};\n\t}\n\tif(style) {\n\t\tnode.attributes.style = {type: \"string\", value: style};\n\t}\n\tif(classes) {\n\t\tnode.attributes.itemClass = {type: \"string\", value: classes.split(\".\").join(\" \")};\n\t}\n\treturn [node];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/filteredtranscludeblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/filteredtranscludeinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/filteredtranscludeinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for inline filtered transclusion. For example:\n\n```\n{{{ [tag[docs]] }}}\n{{{ [tag[docs]] |tooltip}}}\n{{{ [tag[docs]] ||TemplateTitle}}}\n{{{ [tag[docs]] |tooltip||TemplateTitle}}}\n{{{ [tag[docs]] }}width:40;height:50;}.class.class\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"filteredtranscludeinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\{\\{\\{([^\\|]+?)(?:\\|([^\\|\\{\\}]+))?(?:\\|\\|([^\\|\\{\\}]+))?\\}\\}([^\\}]*)\\}(?:\\.(\\S+))?/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Get the match details\n\tvar filter = this.match[1],\n\t\ttooltip = this.match[2],\n\t\ttemplate = $tw.utils.trim(this.match[3]),\n\t\tstyle = this.match[4],\n\t\tclasses = this.match[5];\n\t// Return the list widget\n\tvar node = {\n\t\ttype: \"list\",\n\t\tattributes: {\n\t\t\tfilter: {type: \"string\", value: filter}\n\t\t}\n\t};\n\tif(tooltip) {\n\t\tnode.attributes.tooltip = {type: \"string\", value: tooltip};\n\t}\n\tif(template) {\n\t\tnode.attributes.template = {type: \"string\", value: template};\n\t}\n\tif(style) {\n\t\tnode.attributes.style = {type: \"string\", value: style};\n\t}\n\tif(classes) {\n\t\tnode.attributes.itemClass = {type: \"string\", value: classes.split(\".\").join(\" \")};\n\t}\n\treturn [node];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/filteredtranscludeinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/hardlinebreaks.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/hardlinebreaks.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for marking areas with hard line breaks. For example:\n\n```\n\"\"\"\nThis is some text\nThat is set like\nIt is a Poem\nWhen it is\nClearly\nNot\n\"\"\"\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"hardlinebreaks\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\"\"\"(?:\\r?\\n)?/mg;\n};\n\nexports.parse = function() {\n\tvar reEnd = /(\"\"\")|(\\r?\\n)/mg,\n\t\ttree = [],\n\t\tmatch;\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tdo {\n\t\t// Parse the run up to the terminator\n\t\ttree.push.apply(tree,this.parser.parseInlineRun(reEnd,{eatTerminator: false}));\n\t\t// Redo the terminator match\n\t\treEnd.lastIndex = this.parser.pos;\n\t\tmatch = reEnd.exec(this.parser.source);\n\t\tif(match) {\n\t\t\tthis.parser.pos = reEnd.lastIndex;\n\t\t\t// Add a line break if the terminator was a line break\n\t\t\tif(match[2]) {\n\t\t\t\ttree.push({type: \"element\", tag: \"br\"});\n\t\t\t}\n\t\t}\n\t} while(match && !match[1]);\n\t// Return the nodes\n\treturn tree;\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/hardlinebreaks.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/heading.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/heading.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for headings\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"heading\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /(!{1,6})/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Get all the details of the match\n\tvar headingLevel = this.match[1].length;\n\t// Move past the !s\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Parse any classes, whitespace and then the heading itself\n\tvar classes = this.parser.parseClasses();\n\tthis.parser.skipWhitespace({treatNewlinesAsNonWhitespace: true});\n\tvar tree = this.parser.parseInlineRun(/(\\r?\\n)/mg);\n\t// Return the heading\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"h\" + headingLevel, \n\t\tattributes: {\n\t\t\t\"class\": {type: \"string\", value: classes.join(\" \")}\n\t\t},\n\t\tchildren: tree\n\t}];\n};\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/heading.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/horizrule.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/horizrule.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for rules. For example:\n\n```\n---\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"horizrule\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /-{3,}\\r?(?:\\n|$)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\treturn [{type: \"element\", tag: \"hr\"}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/horizrule.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/html.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/html.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki rule for HTML elements and widgets. For example:\n\n{{{\n<aside>\nThis is an HTML5 aside element\n</aside>\n\n<$slider target=\"MyTiddler\">\nThis is a widget invocation\n</$slider>\n\n}}}\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"html\";\nexports.types = {inline: true, block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n};\n\nexports.findNextMatch = function(startPos) {\n\t// Find the next tag\n\tthis.nextTag = this.findNextTag(this.parser.source,startPos,{\n\t\trequireLineBreak: this.is.block\n\t});\n\treturn this.nextTag ? this.nextTag.start : undefined;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Retrieve the most recent match so that recursive calls don't overwrite it\n\tvar tag = this.nextTag;\n\tthis.nextTag = null;\n\t// Advance the parser position to past the tag\n\tthis.parser.pos = tag.end;\n\t// Check for an immediately following double linebreak\n\tvar hasLineBreak = !tag.isSelfClosing && !!$tw.utils.parseTokenRegExp(this.parser.source,this.parser.pos,/([^\\S\\n\\r]*\\r?\\n(?:[^\\S\\n\\r]*\\r?\\n|$))/g);\n\t// Set whether we're in block mode\n\ttag.isBlock = this.is.block || hasLineBreak;\n\t// Parse the body if we need to\n\tif(!tag.isSelfClosing && $tw.config.htmlVoidElements.indexOf(tag.tag) === -1) {\n\t\t\tvar reEndString = \"</\" + $tw.utils.escapeRegExp(tag.tag) + \">\",\n\t\t\t\treEnd = new RegExp(\"(\" + reEndString + \")\",\"mg\");\n\t\tif(hasLineBreak) {\n\t\t\ttag.children = this.parser.parseBlocks(reEndString);\n\t\t} else {\n\t\t\ttag.children = this.parser.parseInlineRun(reEnd);\n\t\t}\n\t\treEnd.lastIndex = this.parser.pos;\n\t\tvar endMatch = reEnd.exec(this.parser.source);\n\t\tif(endMatch && endMatch.index === this.parser.pos) {\n\t\t\tthis.parser.pos = endMatch.index + endMatch[0].length;\n\t\t}\n\t}\n\t// Return the tag\n\treturn [tag];\n};\n\n/*\nLook for an HTML tag. Returns null if not found, otherwise returns {type: \"element\", name:, attributes: [], isSelfClosing:, start:, end:,}\n*/\nexports.parseTag = function(source,pos,options) {\n\toptions = options || {};\n\tvar token,\n\t\tnode = {\n\t\t\ttype: \"element\",\n\t\t\tstart: pos,\n\t\t\tattributes: {}\n\t\t};\n\t// Define our regexps\n\tvar reTagName = /([a-zA-Z0-9\\-\\$]+)/g;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for a less than sign\n\ttoken = $tw.utils.parseTokenString(source,pos,\"<\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Get the tag name\n\ttoken = $tw.utils.parseTokenRegExp(source,pos,reTagName);\n\tif(!token) {\n\t\treturn null;\n\t}\n\tnode.tag = token.match[1];\n\tif(node.tag.charAt(0) === \"$\") {\n\t\tnode.type = node.tag.substr(1);\n\t}\n\tpos = token.end;\n\t// Process attributes\n\tvar attribute = $tw.utils.parseAttribute(source,pos);\n\twhile(attribute) {\n\t\tnode.attributes[attribute.name] = attribute;\n\t\tpos = attribute.end;\n\t\t// Get the next attribute\n\t\tattribute = $tw.utils.parseAttribute(source,pos);\n\t}\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for a closing slash\n\ttoken = $tw.utils.parseTokenString(source,pos,\"/\");\n\tif(token) {\n\t\tpos = token.end;\n\t\tnode.isSelfClosing = true;\n\t}\n\t// Look for a greater than sign\n\ttoken = $tw.utils.parseTokenString(source,pos,\">\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Check for a required line break\n\tif(options.requireLineBreak) {\n\t\ttoken = $tw.utils.parseTokenRegExp(source,pos,/([^\\S\\n\\r]*\\r?\\n(?:[^\\S\\n\\r]*\\r?\\n|$))/g);\n\t\tif(!token) {\n\t\t\treturn null;\n\t\t}\n\t}\n\t// Update the end position\n\tnode.end = pos;\n\treturn node;\n};\n\nexports.findNextTag = function(source,pos,options) {\n\t// A regexp for finding candidate HTML tags\n\tvar reLookahead = /<([a-zA-Z\\-\\$]+)/g;\n\t// Find the next candidate\n\treLookahead.lastIndex = pos;\n\tvar match = reLookahead.exec(source);\n\twhile(match) {\n\t\t// Try to parse the candidate as a tag\n\t\tvar tag = this.parseTag(source,match.index,options);\n\t\t// Return success\n\t\tif(tag && this.isLegalTag(tag)) {\n\t\t\treturn tag;\n\t\t}\n\t\t// Look for the next match\n\t\treLookahead.lastIndex = match.index + 1;\n\t\tmatch = reLookahead.exec(source);\n\t}\n\t// Failed\n\treturn null;\n};\n\nexports.isLegalTag = function(tag) {\n\t// Widgets are always OK\n\tif(tag.type !== \"element\") {\n\t\treturn true;\n\t// If it's an HTML tag that starts with a dash then it's not legal\n\t} else if(tag.tag.charAt(0) === \"-\") {\n\t\treturn false;\n\t} else {\n\t\t// Otherwise it's OK\n\t\treturn true;\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/html.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/image.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/image.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for embedding images. For example:\n\n```\n[img[http://tiddlywiki.com/fractalveg.jpg]]\n[img width=23 height=24 [http://tiddlywiki.com/fractalveg.jpg]]\n[img width={{!!width}} height={{!!height}} [http://tiddlywiki.com/fractalveg.jpg]]\n[img[Description of image|http://tiddlywiki.com/fractalveg.jpg]]\n[img[TiddlerTitle]]\n[img[Description of image|TiddlerTitle]]\n```\n\nGenerates the `<$image>` widget.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"image\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n};\n\nexports.findNextMatch = function(startPos) {\n\t// Find the next tag\n\tthis.nextImage = this.findNextImage(this.parser.source,startPos);\n\treturn this.nextImage ? this.nextImage.start : undefined;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.nextImage.end;\n\tvar node = {\n\t\ttype: \"image\",\n\t\tattributes: this.nextImage.attributes\n\t};\n\treturn [node];\n};\n\n/*\nFind the next image from the current position\n*/\nexports.findNextImage = function(source,pos) {\n\t// A regexp for finding candidate HTML tags\n\tvar reLookahead = /(\\[img)/g;\n\t// Find the next candidate\n\treLookahead.lastIndex = pos;\n\tvar match = reLookahead.exec(source);\n\twhile(match) {\n\t\t// Try to parse the candidate as a tag\n\t\tvar tag = this.parseImage(source,match.index);\n\t\t// Return success\n\t\tif(tag) {\n\t\t\treturn tag;\n\t\t}\n\t\t// Look for the next match\n\t\treLookahead.lastIndex = match.index + 1;\n\t\tmatch = reLookahead.exec(source);\n\t}\n\t// Failed\n\treturn null;\n};\n\n/*\nLook for an image at the specified position. Returns null if not found, otherwise returns {type: \"image\", attributes: [], isSelfClosing:, start:, end:,}\n*/\nexports.parseImage = function(source,pos) {\n\tvar token,\n\t\tnode = {\n\t\t\ttype: \"image\",\n\t\t\tstart: pos,\n\t\t\tattributes: {}\n\t\t};\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for the `[img`\n\ttoken = $tw.utils.parseTokenString(source,pos,\"[img\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Process attributes\n\tif(source.charAt(pos) !== \"[\") {\n\t\tvar attribute = $tw.utils.parseAttribute(source,pos);\n\t\twhile(attribute) {\n\t\t\tnode.attributes[attribute.name] = attribute;\n\t\t\tpos = attribute.end;\n\t\t\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t\t\tif(source.charAt(pos) !== \"[\") {\n\t\t\t\t// Get the next attribute\n\t\t\t\tattribute = $tw.utils.parseAttribute(source,pos);\n\t\t\t} else {\n\t\t\t\tattribute = null;\n\t\t\t}\n\t\t}\n\t}\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for the `[` after the attributes\n\ttoken = $tw.utils.parseTokenString(source,pos,\"[\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Get the source up to the terminating `]]`\n\ttoken = $tw.utils.parseTokenRegExp(source,pos,/(?:([^|\\]]*?)\\|)?([^\\]]+?)\\]\\]/g);\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\tif(token.match[1]) {\n\t\tnode.attributes.tooltip = {type: \"string\", value: token.match[1].trim()};\n\t}\n\tnode.attributes.source = {type: \"string\", value: (token.match[2] || \"\").trim()};\n\t// Update the end position\n\tnode.end = pos;\n\treturn node;\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/image.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/list.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/list.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for lists. For example:\n\n```\n* This is an unordered list\n* It has two items\n\n# This is a numbered list\n## With a subitem\n# And a third item\n\n; This is a term that is being defined\n: This is the definition of that term\n```\n\nNote that lists can be nested arbitrarily:\n\n```\n#** One\n#* Two\n#** Three\n#**** Four\n#**# Five\n#**## Six\n## Seven\n### Eight\n## Nine\n```\n\nA CSS class can be applied to a list item as follows:\n\n```\n* List item one\n*.active List item two has the class `active`\n* List item three\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"list\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /([\\*#;:>]+)/mg;\n};\n\nvar listTypes = {\n\t\"*\": {listTag: \"ul\", itemTag: \"li\"},\n\t\"#\": {listTag: \"ol\", itemTag: \"li\"},\n\t\";\": {listTag: \"dl\", itemTag: \"dt\"},\n\t\":\": {listTag: \"dl\", itemTag: \"dd\"},\n\t\">\": {listTag: \"blockquote\", itemTag: \"p\"}\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Array of parse tree nodes for the previous row of the list\n\tvar listStack = [];\n\t// Cycle through the items in the list\n\twhile(true) {\n\t\t// Match the list marker\n\t\tvar reMatch = /([\\*#;:>]+)/mg;\n\t\treMatch.lastIndex = this.parser.pos;\n\t\tvar match = reMatch.exec(this.parser.source);\n\t\tif(!match || match.index !== this.parser.pos) {\n\t\t\tbreak;\n\t\t}\n\t\t// Check whether the list type of the top level matches\n\t\tvar listInfo = listTypes[match[0].charAt(0)];\n\t\tif(listStack.length > 0 && listStack[0].tag !== listInfo.listTag) {\n\t\t\tbreak;\n\t\t}\n\t\t// Move past the list marker\n\t\tthis.parser.pos = match.index + match[0].length;\n\t\t// Walk through the list markers for the current row\n\t\tfor(var t=0; t<match[0].length; t++) {\n\t\t\tlistInfo = listTypes[match[0].charAt(t)];\n\t\t\t// Remove any stacked up element if we can't re-use it because the list type doesn't match\n\t\t\tif(listStack.length > t && listStack[t].tag !== listInfo.listTag) {\n\t\t\t\tlistStack.splice(t,listStack.length - t);\n\t\t\t}\n\t\t\t// Construct the list element or reuse the previous one at this level\n\t\t\tif(listStack.length <= t) {\n\t\t\t\tvar listElement = {type: \"element\", tag: listInfo.listTag, children: [\n\t\t\t\t\t{type: \"element\", tag: listInfo.itemTag, children: []}\n\t\t\t\t]};\n\t\t\t\t// Link this list element into the last child item of the parent list item\n\t\t\t\tif(t) {\n\t\t\t\t\tvar prevListItem = listStack[t-1].children[listStack[t-1].children.length-1];\n\t\t\t\t\tprevListItem.children.push(listElement);\n\t\t\t\t}\n\t\t\t\t// Save this element in the stack\n\t\t\t\tlistStack[t] = listElement;\n\t\t\t} else if(t === (match[0].length - 1)) {\n\t\t\t\tlistStack[t].children.push({type: \"element\", tag: listInfo.itemTag, children: []});\n\t\t\t}\n\t\t}\n\t\tif(listStack.length > match[0].length) {\n\t\t\tlistStack.splice(match[0].length,listStack.length - match[0].length);\n\t\t}\n\t\t// Process the body of the list item into the last list item\n\t\tvar lastListChildren = listStack[listStack.length-1].children,\n\t\t\tlastListItem = lastListChildren[lastListChildren.length-1],\n\t\t\tclasses = this.parser.parseClasses();\n\t\tthis.parser.skipWhitespace({treatNewlinesAsNonWhitespace: true});\n\t\tvar tree = this.parser.parseInlineRun(/(\\r?\\n)/mg);\n\t\tlastListItem.children.push.apply(lastListItem.children,tree);\n\t\tif(classes.length > 0) {\n\t\t\t$tw.utils.addClassToParseTreeNode(lastListItem,classes.join(\" \"));\n\t\t}\n\t\t// Consume any whitespace following the list item\n\t\tthis.parser.skipWhitespace();\n\t}\n\t// Return the root element of the list\n\treturn [listStack[0]];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/list.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/macrocallblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/macrocallblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki rule for block macro calls\n\n```\n<<name value value2>>\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"macrocallblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /<<([^>\\s]+)(?:\\s*)((?:[^>]|(?:>(?!>)))*?)>>(?:\\r?\\n|$)/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Get all the details of the match\n\tvar macroName = this.match[1],\n\t\tparamString = this.match[2];\n\t// Move past the macro call\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tvar params = [],\n\t\treParam = /\\s*(?:([A-Za-z0-9\\-_]+)\\s*:)?(?:\\s*(?:\"\"\"([\\s\\S]*?)\"\"\"|\"([^\"]*)\"|'([^']*)'|\\[\\[([^\\]]*)\\]\\]|([^\"'\\s]+)))/mg,\n\t\tparamMatch = reParam.exec(paramString);\n\twhile(paramMatch) {\n\t\t// Process this parameter\n\t\tvar paramInfo = {\n\t\t\tvalue: paramMatch[2] || paramMatch[3] || paramMatch[4] || paramMatch[5] || paramMatch[6]\n\t\t};\n\t\tif(paramMatch[1]) {\n\t\t\tparamInfo.name = paramMatch[1];\n\t\t}\n\t\tparams.push(paramInfo);\n\t\t// Find the next match\n\t\tparamMatch = reParam.exec(paramString);\n\t}\n\treturn [{\n\t\ttype: \"macrocall\",\n\t\tname: macroName,\n\t\tparams: params,\n\t\tisBlock: true\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/macrocallblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/macrocallinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/macrocallinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki rule for macro calls\n\n```\n<<name value value2>>\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"macrocallinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /<<([^\\s>]+)\\s*([\\s\\S]*?)>>/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Get all the details of the match\n\tvar macroName = this.match[1],\n\t\tparamString = this.match[2];\n\t// Move past the macro call\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tvar params = [],\n\t\treParam = /\\s*(?:([A-Za-z0-9\\-_]+)\\s*:)?(?:\\s*(?:\"\"\"([\\s\\S]*?)\"\"\"|\"([^\"]*)\"|'([^']*)'|\\[\\[([^\\]]*)\\]\\]|([^\"'\\s]+)))/mg,\n\t\tparamMatch = reParam.exec(paramString);\n\twhile(paramMatch) {\n\t\t// Process this parameter\n\t\tvar paramInfo = {\n\t\t\tvalue: paramMatch[2] || paramMatch[3] || paramMatch[4] || paramMatch[5]|| paramMatch[6]\n\t\t};\n\t\tif(paramMatch[1]) {\n\t\t\tparamInfo.name = paramMatch[1];\n\t\t}\n\t\tparams.push(paramInfo);\n\t\t// Find the next match\n\t\tparamMatch = reParam.exec(paramString);\n\t}\n\treturn [{\n\t\ttype: \"macrocall\",\n\t\tname: macroName,\n\t\tparams: params\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/macrocallinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/macrodef.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/macrodef.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki pragma rule for macro definitions\n\n```\n\\define name(param:defaultvalue,param2:defaultvalue)\ndefinition text, including $param$ markers\n\\end\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"macrodef\";\nexports.types = {pragma: true};\n\n/*\nInstantiate parse rule\n*/\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /^\\\\define\\s+([^(\\s]+)\\(\\s*([^)]*)\\)(\\s*\\r?\\n)?/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Move past the macro name and parameters\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Parse the parameters\n\tvar paramString = this.match[2],\n\t\tparams = [];\n\tif(paramString !== \"\") {\n\t\tvar reParam = /\\s*([A-Za-z0-9\\-_]+)(?:\\s*:\\s*(?:\"\"\"([\\s\\S]*?)\"\"\"|\"([^\"]*)\"|'([^']*)'|\\[\\[([^\\]]*)\\]\\]|([^\"'\\s]+)))?/mg,\n\t\t\tparamMatch = reParam.exec(paramString);\n\t\twhile(paramMatch) {\n\t\t\t// Save the parameter details\n\t\t\tvar paramInfo = {name: paramMatch[1]},\n\t\t\t\tdefaultValue = paramMatch[2] || paramMatch[3] || paramMatch[4] || paramMatch[5] || paramMatch[6];\n\t\t\tif(defaultValue) {\n\t\t\t\tparamInfo[\"default\"] = defaultValue;\n\t\t\t}\n\t\t\tparams.push(paramInfo);\n\t\t\t// Look for the next parameter\n\t\t\tparamMatch = reParam.exec(paramString);\n\t\t}\n\t}\n\t// Is this a multiline definition?\n\tvar reEnd;\n\tif(this.match[3]) {\n\t\t// If so, the end of the body is marked with \\end\n\t\treEnd = /(\\r?\\n\\\\end[^\\S\\n\\r]*(?:$|\\r?\\n))/mg;\n\t} else {\n\t\t// Otherwise, the end of the definition is marked by the end of the line\n\t\treEnd = /(\\r?\\n)/mg;\n\t\t// Move past any whitespace\n\t\tthis.parser.pos = $tw.utils.skipWhiteSpace(this.parser.source,this.parser.pos);\n\t}\n\t// Find the end of the definition\n\treEnd.lastIndex = this.parser.pos;\n\tvar text,\n\t\tendMatch = reEnd.exec(this.parser.source);\n\tif(endMatch) {\n\t\ttext = this.parser.source.substring(this.parser.pos,endMatch.index);\n\t\tthis.parser.pos = endMatch.index + endMatch[0].length;\n\t} else {\n\t\t// We didn't find the end of the definition, so we'll make it blank\n\t\ttext = \"\";\n\t}\n\t// Save the macro definition\n\treturn [{\n\t\ttype: \"set\",\n\t\tattributes: {\n\t\t\tname: {type: \"string\", value: this.match[1]},\n\t\t\tvalue: {type: \"string\", value: text}\n\t\t},\n\t\tchildren: [],\n\t\tparams: params\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/macrodef.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/prettyextlink.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/prettyextlink.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for external links. For example:\n\n```\n[ext[http://tiddlywiki.com/fractalveg.jpg]]\n[ext[Tooltip|http://tiddlywiki.com/fractalveg.jpg]]\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"prettyextlink\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n};\n\nexports.findNextMatch = function(startPos) {\n\t// Find the next tag\n\tthis.nextLink = this.findNextLink(this.parser.source,startPos);\n\treturn this.nextLink ? this.nextLink.start : undefined;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.nextLink.end;\n\treturn [this.nextLink];\n};\n\n/*\nFind the next link from the current position\n*/\nexports.findNextLink = function(source,pos) {\n\t// A regexp for finding candidate links\n\tvar reLookahead = /(\\[ext\\[)/g;\n\t// Find the next candidate\n\treLookahead.lastIndex = pos;\n\tvar match = reLookahead.exec(source);\n\twhile(match) {\n\t\t// Try to parse the candidate as a link\n\t\tvar link = this.parseLink(source,match.index);\n\t\t// Return success\n\t\tif(link) {\n\t\t\treturn link;\n\t\t}\n\t\t// Look for the next match\n\t\treLookahead.lastIndex = match.index + 1;\n\t\tmatch = reLookahead.exec(source);\n\t}\n\t// Failed\n\treturn null;\n};\n\n/*\nLook for an link at the specified position. Returns null if not found, otherwise returns {type: \"element\", tag: \"a\", attributes: [], isSelfClosing:, start:, end:,}\n*/\nexports.parseLink = function(source,pos) {\n\tvar token,\n\t\ttextNode = {\n\t\t\ttype: \"text\"\n\t\t},\n\t\tnode = {\n\t\t\ttype: \"element\",\n\t\t\ttag: \"a\",\n\t\t\tstart: pos,\n\t\t\tattributes: {\n\t\t\t\t\"class\": {type: \"string\", value: \"tc-tiddlylink-external\"},\n\t\t\t},\n\t\t\tchildren: [textNode]\n\t\t};\n\t// Skip whitespace\n\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t// Look for the `[ext[`\n\ttoken = $tw.utils.parseTokenString(source,pos,\"[ext[\");\n\tif(!token) {\n\t\treturn null;\n\t}\n\tpos = token.end;\n\t// Look ahead for the terminating `]]`\n\tvar closePos = source.indexOf(\"]]\",pos);\n\tif(closePos === -1) {\n\t\treturn null;\n\t}\n\t// Look for a `|` separating the tooltip\n\tvar splitPos = source.indexOf(\"|\",pos);\n\tif(splitPos === -1 || splitPos > closePos) {\n\t\tsplitPos = null;\n\t}\n\t// Pull out the tooltip and URL\n\tvar tooltip, URL;\n\tif(splitPos) {\n\t\tURL = source.substring(splitPos + 1,closePos).trim();\n\t\ttextNode.text = source.substring(pos,splitPos).trim();\n\t} else {\n\t\tURL = source.substring(pos,closePos).trim();\n\t\ttextNode.text = URL;\n\t}\n\tnode.attributes.href = {type: \"string\", value: URL};\n\tnode.attributes.target = {type: \"string\", value: \"_blank\"};\n\tnode.attributes.rel = {type: \"string\", value: \"noopener noreferrer\"};\n\t// Update the end position\n\tnode.end = closePos + 2;\n\treturn node;\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/prettyextlink.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/prettylink.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/prettylink.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for pretty links. For example:\n\n```\n[[Introduction]]\n\n[[Link description|TiddlerTitle]]\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"prettylink\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\[\\[(.*?)(?:\\|(.*?))?\\]\\]/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Process the link\n\tvar text = this.match[1],\n\t\tlink = this.match[2] || text;\n\tif($tw.utils.isLinkExternal(link)) {\n\t\treturn [{\n\t\t\ttype: \"element\",\n\t\t\ttag: \"a\",\n\t\t\tattributes: {\n\t\t\t\thref: {type: \"string\", value: link},\n\t\t\t\t\"class\": {type: \"string\", value: \"tc-tiddlylink-external\"},\n\t\t\t\ttarget: {type: \"string\", value: \"_blank\"},\n\t\t\t\trel: {type: \"string\", value: \"noopener noreferrer\"}\n\t\t\t},\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\", text: text\n\t\t\t}]\n\t\t}];\n\t} else {\n\t\treturn [{\n\t\t\ttype: \"link\",\n\t\t\tattributes: {\n\t\t\t\tto: {type: \"string\", value: link}\n\t\t\t},\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\", text: text\n\t\t\t}]\n\t\t}];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/prettylink.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/quoteblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/quoteblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for quote blocks. For example:\n\n```\n\t<<<.optionalClass(es) optional cited from\n\ta quote\n\t<<<\n\t\n\t<<<.optionalClass(es)\n\ta quote\n\t<<< optional cited from\n```\n\nQuotes can be quoted by putting more <s\n\n```\n\t<<<\n\tQuote Level 1\n\t\n\t<<<<\n\tQuoteLevel 2\n\t<<<<\n\t\n\t<<<\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"quoteblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /(<<<+)/mg;\n};\n\nexports.parse = function() {\n\tvar classes = [\"tc-quote\"];\n\t// Get all the details of the match\n\tvar reEndString = \"^\" + this.match[1] + \"(?!<)\";\n\t// Move past the <s\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t\n\t// Parse any classes, whitespace and then the optional cite itself\n\tclasses.push.apply(classes, this.parser.parseClasses());\n\tthis.parser.skipWhitespace({treatNewlinesAsNonWhitespace: true});\n\tvar cite = this.parser.parseInlineRun(/(\\r?\\n)/mg);\n\t// before handling the cite, parse the body of the quote\n\tvar tree= this.parser.parseBlocks(reEndString);\n\t// If we got a cite, put it before the text\n\tif(cite.length > 0) {\n\t\ttree.unshift({\n\t\t\ttype: \"element\",\n\t\t\ttag: \"cite\",\n\t\t\tchildren: cite\n\t\t});\n\t}\n\t// Parse any optional cite\n\tthis.parser.skipWhitespace({treatNewlinesAsNonWhitespace: true});\n\tcite = this.parser.parseInlineRun(/(\\r?\\n)/mg);\n\t// If we got a cite, push it\n\tif(cite.length > 0) {\n\t\ttree.push({\n\t\t\ttype: \"element\",\n\t\t\ttag: \"cite\",\n\t\t\tchildren: cite\n\t\t});\n\t}\n\t// Return the blockquote element\n\treturn [{\n\t\ttype: \"element\",\n\t\ttag: \"blockquote\",\n\t\tattributes: {\n\t\t\tclass: { type: \"string\", value: classes.join(\" \") },\n\t\t},\n\t\tchildren: tree\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/quoteblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/rules.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/rules.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki pragma rule for rules specifications\n\n```\n\\rules except ruleone ruletwo rulethree\n\\rules only ruleone ruletwo rulethree\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"rules\";\nexports.types = {pragma: true};\n\n/*\nInstantiate parse rule\n*/\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /^\\\\rules[^\\S\\n]/mg;\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Move past the pragma invocation\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Parse whitespace delimited tokens terminated by a line break\n\tvar reMatch = /[^\\S\\n]*(\\S+)|(\\r?\\n)/mg,\n\t\ttokens = [];\n\treMatch.lastIndex = this.parser.pos;\n\tvar match = reMatch.exec(this.parser.source);\n\twhile(match && match.index === this.parser.pos) {\n\t\tthis.parser.pos = reMatch.lastIndex;\n\t\t// Exit if we've got the line break\n\t\tif(match[2]) {\n\t\t\tbreak;\n\t\t}\n\t\t// Process the token\n\t\tif(match[1]) {\n\t\t\ttokens.push(match[1]);\n\t\t}\n\t\t// Match the next token\n\t\tmatch = reMatch.exec(this.parser.source);\n\t}\n\t// Process the tokens\n\tif(tokens.length > 0) {\n\t\tthis.parser.amendRules(tokens[0],tokens.slice(1));\n\t}\n\t// No parse tree nodes to return\n\treturn [];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/rules.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/styleblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/styleblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for assigning styles and classes to paragraphs and other blocks. For example:\n\n```\n@@.myClass\n@@background-color:red;\nThis paragraph will have the CSS class `myClass`.\n\n* The `<ul>` around this list will also have the class `myClass`\n* List item 2\n\n@@\n```\n\nNote that classes and styles can be mixed subject to the rule that styles must precede classes. For example\n\n```\n@@.myFirstClass.mySecondClass\n@@width:100px;.myThirdClass\nThis is a paragraph\n@@\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"styleblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /@@((?:[^\\.\\r\\n\\s:]+:[^\\r\\n;]+;)+)?(?:\\.([^\\r\\n\\s]+))?\\r?\\n/mg;\n};\n\nexports.parse = function() {\n\tvar reEndString = \"^@@(?:\\\\r?\\\\n)?\";\n\tvar classes = [], styles = [];\n\tdo {\n\t\t// Get the class and style\n\t\tif(this.match[1]) {\n\t\t\tstyles.push(this.match[1]);\n\t\t}\n\t\tif(this.match[2]) {\n\t\t\tclasses.push(this.match[2].split(\".\").join(\" \"));\n\t\t}\n\t\t// Move past the match\n\t\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t\t// Look for another line of classes and styles\n\t\tthis.match = this.matchRegExp.exec(this.parser.source);\n\t} while(this.match && this.match.index === this.parser.pos);\n\t// Parse the body\n\tvar tree = this.parser.parseBlocks(reEndString);\n\tfor(var t=0; t<tree.length; t++) {\n\t\tif(classes.length > 0) {\n\t\t\t$tw.utils.addClassToParseTreeNode(tree[t],classes.join(\" \"));\n\t\t}\n\t\tif(styles.length > 0) {\n\t\t\t$tw.utils.addAttributeToParseTreeNode(tree[t],\"style\",styles.join(\"\"));\n\t\t}\n\t}\n\treturn tree;\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/styleblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/styleinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/styleinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for assigning styles and classes to inline runs. For example:\n\n```\n@@.myClass This is some text with a class@@\n@@background-color:red;This is some text with a background colour@@\n@@width:100px;.myClass This is some text with a class and a width@@\n```\n\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"styleinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /@@((?:[^\\.\\r\\n\\s:]+:[^\\r\\n;]+;)+)?(\\.(?:[^\\r\\n\\s]+)\\s+)?/mg;\n};\n\nexports.parse = function() {\n\tvar reEnd = /@@/g;\n\t// Get the styles and class\n\tvar stylesString = this.match[1],\n\t\tclassString = this.match[2] ? this.match[2].split(\".\").join(\" \") : undefined;\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Parse the run up to the terminator\n\tvar tree = this.parser.parseInlineRun(reEnd,{eatTerminator: true});\n\t// Return the classed span\n\tvar node = {\n\t\ttype: \"element\",\n\t\ttag: \"span\",\n\t\tattributes: {\n\t\t\t\"class\": {type: \"string\", value: \"tc-inline-style\"}\n\t\t},\n\t\tchildren: tree\n\t};\n\tif(classString) {\n\t\t$tw.utils.addClassToParseTreeNode(node,classString);\n\t}\n\tif(stylesString) {\n\t\t$tw.utils.addAttributeToParseTreeNode(node,\"style\",stylesString);\n\t}\n\treturn [node];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/styleinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/syslink.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/syslink.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for system tiddler links.\nCan be suppressed preceding them with `~`.\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"syslink\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /~?\\$:\\/[a-zA-Z0-9/.\\-_]+/mg;\n};\n\nexports.parse = function() {\n\tvar match = this.match[0];\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Create the link unless it is suppressed\n\tif(match.substr(0,1) === \"~\") {\n\t\treturn [{type: \"text\", text: match.substr(1)}];\n\t} else {\n\t\treturn [{\n\t\t\ttype: \"link\",\n\t\t\tattributes: {\n\t\t\t\tto: {type: \"string\", value: match}\n\t\t\t},\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\",\n\t\t\t\ttext: match\n\t\t\t}]\n\t\t}];\n\t}\n};\n\n})();",
"title": "$:/core/modules/parsers/wikiparser/rules/syslink.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/table.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/table.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text block rule for tables.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"table\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /^\\|(?:[^\\n]*)\\|(?:[fhck]?)\\r?(?:\\n|$)/mg;\n};\n\nvar processRow = function(prevColumns) {\n\tvar cellRegExp = /(?:\\|([^\\n\\|]*)\\|)|(\\|[fhck]?\\r?(?:\\n|$))/mg,\n\t\tcellTermRegExp = /((?:\\x20*)\\|)/mg,\n\t\ttree = [],\n\t\tcol = 0,\n\t\tcolSpanCount = 1,\n\t\tprevCell,\n\t\tvAlign;\n\t// Match a single cell\n\tcellRegExp.lastIndex = this.parser.pos;\n\tvar cellMatch = cellRegExp.exec(this.parser.source);\n\twhile(cellMatch && cellMatch.index === this.parser.pos) {\n\t\tif(cellMatch[1] === \"~\") {\n\t\t\t// Rowspan\n\t\t\tvar last = prevColumns[col];\n\t\t\tif(last) {\n\t\t\t\tlast.rowSpanCount++;\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(last.element,\"rowspan\",last.rowSpanCount);\n\t\t\t\tvAlign = $tw.utils.getAttributeValueFromParseTreeNode(last.element,\"valign\",\"center\");\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(last.element,\"valign\",vAlign);\n\t\t\t\tif(colSpanCount > 1) {\n\t\t\t\t\t$tw.utils.addAttributeToParseTreeNode(last.element,\"colspan\",colSpanCount);\n\t\t\t\t\tcolSpanCount = 1;\n\t\t\t\t}\n\t\t\t}\n\t\t\t// Move to just before the `|` terminating the cell\n\t\t\tthis.parser.pos = cellRegExp.lastIndex - 1;\n\t\t} else if(cellMatch[1] === \">\") {\n\t\t\t// Colspan\n\t\t\tcolSpanCount++;\n\t\t\t// Move to just before the `|` terminating the cell\n\t\t\tthis.parser.pos = cellRegExp.lastIndex - 1;\n\t\t} else if(cellMatch[1] === \"<\" && prevCell) {\n\t\t\tcolSpanCount = 1 + $tw.utils.getAttributeValueFromParseTreeNode(prevCell,\"colspan\",1);\n\t\t\t$tw.utils.addAttributeToParseTreeNode(prevCell,\"colspan\",colSpanCount);\n\t\t\tcolSpanCount = 1;\n\t\t\t// Move to just before the `|` terminating the cell\n\t\t\tthis.parser.pos = cellRegExp.lastIndex - 1;\n\t\t} else if(cellMatch[2]) {\n\t\t\t// End of row\n\t\t\tif(prevCell && colSpanCount > 1) {\n\t\t\t\tif(prevCell.attributes && prevCell.attributes && prevCell.attributes.colspan) {\n\t\t\t\t\t\tcolSpanCount += prevCell.attributes.colspan.value;\n\t\t\t\t} else {\n\t\t\t\t\tcolSpanCount -= 1;\n\t\t\t\t}\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(prevCell,\"colspan\",colSpanCount);\n\t\t\t}\n\t\t\tthis.parser.pos = cellRegExp.lastIndex - 1;\n\t\t\tbreak;\n\t\t} else {\n\t\t\t// For ordinary cells, step beyond the opening `|`\n\t\t\tthis.parser.pos++;\n\t\t\t// Look for a space at the start of the cell\n\t\t\tvar spaceLeft = false;\n\t\t\tvAlign = null;\n\t\t\tif(this.parser.source.substr(this.parser.pos).search(/^\\^([^\\^]|\\^\\^)/) === 0) {\n\t\t\t\tvAlign = \"top\";\n\t\t\t} else if(this.parser.source.substr(this.parser.pos).search(/^,([^,]|,,)/) === 0) {\n\t\t\t\tvAlign = \"bottom\";\n\t\t\t}\n\t\t\tif(vAlign) {\n\t\t\t\tthis.parser.pos++;\n\t\t\t}\n\t\t\tvar chr = this.parser.source.substr(this.parser.pos,1);\n\t\t\twhile(chr === \" \") {\n\t\t\t\tspaceLeft = true;\n\t\t\t\tthis.parser.pos++;\n\t\t\t\tchr = this.parser.source.substr(this.parser.pos,1);\n\t\t\t}\n\t\t\t// Check whether this is a heading cell\n\t\t\tvar cell;\n\t\t\tif(chr === \"!\") {\n\t\t\t\tthis.parser.pos++;\n\t\t\t\tcell = {type: \"element\", tag: \"th\", children: []};\n\t\t\t} else {\n\t\t\t\tcell = {type: \"element\", tag: \"td\", children: []};\n\t\t\t}\n\t\t\ttree.push(cell);\n\t\t\t// Record information about this cell\n\t\t\tprevCell = cell;\n\t\t\tprevColumns[col] = {rowSpanCount:1,element:cell};\n\t\t\t// Check for a colspan\n\t\t\tif(colSpanCount > 1) {\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(cell,\"colspan\",colSpanCount);\n\t\t\t\tcolSpanCount = 1;\n\t\t\t}\n\t\t\t// Parse the cell\n\t\t\tcell.children = this.parser.parseInlineRun(cellTermRegExp,{eatTerminator: true});\n\t\t\t// Set the alignment for the cell\n\t\t\tif(vAlign) {\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(cell,\"valign\",vAlign);\n\t\t\t}\n\t\t\tif(this.parser.source.substr(this.parser.pos - 2,1) === \" \") { // spaceRight\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(cell,\"align\",spaceLeft ? \"center\" : \"left\");\n\t\t\t} else if(spaceLeft) {\n\t\t\t\t$tw.utils.addAttributeToParseTreeNode(cell,\"align\",\"right\");\n\t\t\t}\n\t\t\t// Move back to the closing `|`\n\t\t\tthis.parser.pos--;\n\t\t}\n\t\tcol++;\n\t\tcellRegExp.lastIndex = this.parser.pos;\n\t\tcellMatch = cellRegExp.exec(this.parser.source);\n\t}\n\treturn tree;\n};\n\nexports.parse = function() {\n\tvar rowContainerTypes = {\"c\":\"caption\", \"h\":\"thead\", \"\":\"tbody\", \"f\":\"tfoot\"},\n\t\ttable = {type: \"element\", tag: \"table\", children: []},\n\t\trowRegExp = /^\\|([^\\n]*)\\|([fhck]?)\\r?(?:\\n|$)/mg,\n\t\trowTermRegExp = /(\\|(?:[fhck]?)\\r?(?:\\n|$))/mg,\n\t\tprevColumns = [],\n\t\tcurrRowType,\n\t\trowContainer,\n\t\trowCount = 0;\n\t// Match the row\n\trowRegExp.lastIndex = this.parser.pos;\n\tvar rowMatch = rowRegExp.exec(this.parser.source);\n\twhile(rowMatch && rowMatch.index === this.parser.pos) {\n\t\tvar rowType = rowMatch[2];\n\t\t// Check if it is a class assignment\n\t\tif(rowType === \"k\") {\n\t\t\t$tw.utils.addClassToParseTreeNode(table,rowMatch[1]);\n\t\t\tthis.parser.pos = rowMatch.index + rowMatch[0].length;\n\t\t} else {\n\t\t\t// Otherwise, create a new row if this one is of a different type\n\t\t\tif(rowType !== currRowType) {\n\t\t\t\trowContainer = {type: \"element\", tag: rowContainerTypes[rowType], children: []};\n\t\t\t\ttable.children.push(rowContainer);\n\t\t\t\tcurrRowType = rowType;\n\t\t\t}\n\t\t\t// Is this a caption row?\n\t\t\tif(currRowType === \"c\") {\n\t\t\t\t// If so, move past the opening `|` of the row\n\t\t\t\tthis.parser.pos++;\n\t\t\t\t// Move the caption to the first row if it isn't already\n\t\t\t\tif(table.children.length !== 1) {\n\t\t\t\t\ttable.children.pop(); // Take rowContainer out of the children array\n\t\t\t\t\ttable.children.splice(0,0,rowContainer); // Insert it at the bottom\t\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t// Set the alignment - TODO: figure out why TW did this\n//\t\t\t\trowContainer.attributes.align = rowCount === 0 ? \"top\" : \"bottom\";\n\t\t\t\t// Parse the caption\n\t\t\t\trowContainer.children = this.parser.parseInlineRun(rowTermRegExp,{eatTerminator: true});\n\t\t\t} else {\n\t\t\t\t// Create the row\n\t\t\t\tvar theRow = {type: \"element\", tag: \"tr\", children: []};\n\t\t\t\t$tw.utils.addClassToParseTreeNode(theRow,rowCount%2 ? \"oddRow\" : \"evenRow\");\n\t\t\t\trowContainer.children.push(theRow);\n\t\t\t\t// Process the row\n\t\t\t\ttheRow.children = processRow.call(this,prevColumns);\n\t\t\t\tthis.parser.pos = rowMatch.index + rowMatch[0].length;\n\t\t\t\t// Increment the row count\n\t\t\t\trowCount++;\n\t\t\t}\n\t\t}\n\t\trowMatch = rowRegExp.exec(this.parser.source);\n\t}\n\treturn [table];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/table.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/transcludeblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/transcludeblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for block-level transclusion. For example:\n\n```\n{{MyTiddler}}\n{{MyTiddler||TemplateTitle}}\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"transcludeblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\{\\{([^\\{\\}\\|]*)(?:\\|\\|([^\\|\\{\\}]+))?\\}\\}(?:\\r?\\n|$)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Get the match details\n\tvar template = $tw.utils.trim(this.match[2]),\n\t\ttextRef = $tw.utils.trim(this.match[1]);\n\t// Prepare the transclude widget\n\tvar transcludeNode = {\n\t\t\ttype: \"transclude\",\n\t\t\tattributes: {},\n\t\t\tisBlock: true\n\t\t};\n\t// Prepare the tiddler widget\n\tvar tr, targetTitle, targetField, targetIndex, tiddlerNode;\n\tif(textRef) {\n\t\ttr = $tw.utils.parseTextReference(textRef);\n\t\ttargetTitle = tr.title;\n\t\ttargetField = tr.field;\n\t\ttargetIndex = tr.index;\n\t\ttiddlerNode = {\n\t\t\ttype: \"tiddler\",\n\t\t\tattributes: {\n\t\t\t\ttiddler: {type: \"string\", value: targetTitle}\n\t\t\t},\n\t\t\tisBlock: true,\n\t\t\tchildren: [transcludeNode]\n\t\t};\n\t}\n\tif(template) {\n\t\ttranscludeNode.attributes.tiddler = {type: \"string\", value: template};\n\t\tif(textRef) {\n\t\t\treturn [tiddlerNode];\n\t\t} else {\n\t\t\treturn [transcludeNode];\n\t\t}\n\t} else {\n\t\tif(textRef) {\n\t\t\ttranscludeNode.attributes.tiddler = {type: \"string\", value: targetTitle};\n\t\t\tif(targetField) {\n\t\t\t\ttranscludeNode.attributes.field = {type: \"string\", value: targetField};\n\t\t\t}\n\t\t\tif(targetIndex) {\n\t\t\t\ttranscludeNode.attributes.index = {type: \"string\", value: targetIndex};\n\t\t\t}\n\t\t\treturn [tiddlerNode];\n\t\t} else {\n\t\t\treturn [transcludeNode];\n\t\t}\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/transcludeblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/transcludeinline.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/transcludeinline.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for inline-level transclusion. For example:\n\n```\n{{MyTiddler}}\n{{MyTiddler||TemplateTitle}}\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"transcludeinline\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\{\\{([^\\{\\}\\|]*)(?:\\|\\|([^\\|\\{\\}]+))?\\}\\}/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Get the match details\n\tvar template = $tw.utils.trim(this.match[2]),\n\t\ttextRef = $tw.utils.trim(this.match[1]);\n\t// Prepare the transclude widget\n\tvar transcludeNode = {\n\t\t\ttype: \"transclude\",\n\t\t\tattributes: {}\n\t\t};\n\t// Prepare the tiddler widget\n\tvar tr, targetTitle, targetField, targetIndex, tiddlerNode;\n\tif(textRef) {\n\t\ttr = $tw.utils.parseTextReference(textRef);\n\t\ttargetTitle = tr.title;\n\t\ttargetField = tr.field;\n\t\ttargetIndex = tr.index;\n\t\ttiddlerNode = {\n\t\t\ttype: \"tiddler\",\n\t\t\tattributes: {\n\t\t\t\ttiddler: {type: \"string\", value: targetTitle}\n\t\t\t},\n\t\t\tchildren: [transcludeNode]\n\t\t};\n\t}\n\tif(template) {\n\t\ttranscludeNode.attributes.tiddler = {type: \"string\", value: template};\n\t\tif(textRef) {\n\t\t\treturn [tiddlerNode];\n\t\t} else {\n\t\t\treturn [transcludeNode];\n\t\t}\n\t} else {\n\t\tif(textRef) {\n\t\t\ttranscludeNode.attributes.tiddler = {type: \"string\", value: targetTitle};\n\t\t\tif(targetField) {\n\t\t\t\ttranscludeNode.attributes.field = {type: \"string\", value: targetField};\n\t\t\t}\n\t\t\tif(targetIndex) {\n\t\t\t\ttranscludeNode.attributes.index = {type: \"string\", value: targetIndex};\n\t\t\t}\n\t\t\treturn [tiddlerNode];\n\t\t} else {\n\t\t\treturn [transcludeNode];\n\t\t}\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/transcludeinline.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/typedblock.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/typedblock.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text rule for typed blocks. For example:\n\n```\n$$$.js\nThis will be rendered as JavaScript\n$$$\n\n$$$.svg\n<svg xmlns=\"http://www.w3.org/2000/svg\" width=\"150\" height=\"100\">\n <circle cx=\"100\" cy=\"50\" r=\"40\" stroke=\"black\" stroke-width=\"2\" fill=\"red\" />\n</svg>\n$$$\n\n$$$text/vnd.tiddlywiki>text/html\nThis will be rendered as an //HTML representation// of WikiText\n$$$\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nexports.name = \"typedblock\";\nexports.types = {block: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\$\\$\\$([^ >\\r\\n]*)(?: *> *([^ \\r\\n]+))?\\r?\\n/mg;\n};\n\nexports.parse = function() {\n\tvar reEnd = /\\r?\\n\\$\\$\\$\\r?(?:\\n|$)/mg;\n\t// Save the type\n\tvar parseType = this.match[1],\n\t\trenderType = this.match[2];\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Look for the end of the block\n\treEnd.lastIndex = this.parser.pos;\n\tvar match = reEnd.exec(this.parser.source),\n\t\ttext;\n\t// Process the block\n\tif(match) {\n\t\ttext = this.parser.source.substring(this.parser.pos,match.index);\n\t\tthis.parser.pos = match.index + match[0].length;\n\t} else {\n\t\ttext = this.parser.source.substr(this.parser.pos);\n\t\tthis.parser.pos = this.parser.sourceLength;\n\t}\n\t// Parse the block according to the specified type\n\tvar parser = this.parser.wiki.parseText(parseType,text,{defaultType: \"text/plain\"});\n\t// If there's no render type, just return the parse tree\n\tif(!renderType) {\n\t\treturn parser.tree;\n\t} else {\n\t\t// Otherwise, render to the rendertype and return in a <PRE> tag\n\t\tvar widgetNode = this.parser.wiki.makeWidget(parser),\n\t\t\tcontainer = $tw.fakeDocument.createElement(\"div\");\n\t\twidgetNode.render(container,null);\n\t\ttext = renderType === \"text/html\" ? container.innerHTML : container.textContent;\n\t\treturn [{\n\t\t\ttype: \"element\",\n\t\t\ttag: \"pre\",\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\",\n\t\t\t\ttext: text\n\t\t\t}]\n\t\t}];\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/typedblock.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/rules/wikilink.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/wikilink.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for wiki links. For example:\n\n```\nAWikiLink\nAnotherLink\n~SuppressedLink\n```\n\nPrecede a camel case word with `~` to prevent it from being recognised as a link.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"wikilink\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = new RegExp($tw.config.textPrimitives.unWikiLink + \"?\" + $tw.config.textPrimitives.wikiLink,\"mg\");\n};\n\n/*\nParse the most recent match\n*/\nexports.parse = function() {\n\t// Get the details of the match\n\tvar linkText = this.match[0];\n\t// Move past the macro call\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// If the link starts with the unwikilink character then just output it as plain text\n\tif(linkText.substr(0,1) === $tw.config.textPrimitives.unWikiLink) {\n\t\treturn [{type: \"text\", text: linkText.substr(1)}];\n\t}\n\t// If the link has been preceded with a blocked letter then don't treat it as a link\n\tif(this.match.index > 0) {\n\t\tvar preRegExp = new RegExp($tw.config.textPrimitives.blockPrefixLetters,\"mg\");\n\t\tpreRegExp.lastIndex = this.match.index-1;\n\t\tvar preMatch = preRegExp.exec(this.parser.source);\n\t\tif(preMatch && preMatch.index === this.match.index-1) {\n\t\t\treturn [{type: \"text\", text: linkText}];\n\t\t}\n\t}\n\treturn [{\n\t\ttype: \"link\",\n\t\tattributes: {\n\t\t\tto: {type: \"string\", value: linkText}\n\t\t},\n\t\tchildren: [{\n\t\t\ttype: \"text\",\n\t\t\ttext: linkText\n\t\t}]\n\t}];\n};\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/wikilink.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/core/modules/parsers/wikiparser/wikiparser.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/wikiparser.js\ntype: application/javascript\nmodule-type: parser\n\nThe wiki text parser processes blocks of source text into a parse tree.\n\nThe parse tree is made up of nested arrays of these JavaScript objects:\n\n\t{type: \"element\", tag: <string>, attributes: {}, children: []} - an HTML element\n\t{type: \"text\", text: <string>} - a text node\n\t{type: \"entity\", value: <string>} - an entity\n\t{type: \"raw\", html: <string>} - raw HTML\n\nAttributes are stored as hashmaps of the following objects:\n\n\t{type: \"string\", value: <string>} - literal string\n\t{type: \"indirect\", textReference: <textReference>} - indirect through a text reference\n\t{type: \"macro\", macro: <TBD>} - indirect through a macro invocation\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar WikiParser = function(type,text,options) {\n\tthis.wiki = options.wiki;\n\tvar self = this;\n\t// Check for an externally linked tiddler\n\tif($tw.browser && (text || \"\") === \"\" && options._canonical_uri) {\n\t\tthis.loadRemoteTiddler(options._canonical_uri);\n\t\ttext = $tw.language.getRawString(\"LazyLoadingWarning\");\n\t}\n\t// Initialise the classes if we don't have them already\n\tif(!this.pragmaRuleClasses) {\n\t\tWikiParser.prototype.pragmaRuleClasses = $tw.modules.createClassesFromModules(\"wikirule\",\"pragma\",$tw.WikiRuleBase);\n\t\tthis.setupRules(WikiParser.prototype.pragmaRuleClasses,\"$:/config/WikiParserRules/Pragmas/\");\n\t}\n\tif(!this.blockRuleClasses) {\n\t\tWikiParser.prototype.blockRuleClasses = $tw.modules.createClassesFromModules(\"wikirule\",\"block\",$tw.WikiRuleBase);\n\t\tthis.setupRules(WikiParser.prototype.blockRuleClasses,\"$:/config/WikiParserRules/Block/\");\n\t}\n\tif(!this.inlineRuleClasses) {\n\t\tWikiParser.prototype.inlineRuleClasses = $tw.modules.createClassesFromModules(\"wikirule\",\"inline\",$tw.WikiRuleBase);\n\t\tthis.setupRules(WikiParser.prototype.inlineRuleClasses,\"$:/config/WikiParserRules/Inline/\");\n\t}\n\t// Save the parse text\n\tthis.type = type || \"text/vnd.tiddlywiki\";\n\tthis.source = text || \"\";\n\tthis.sourceLength = this.source.length;\n\t// Set current parse position\n\tthis.pos = 0;\n\t// Instantiate the pragma parse rules\n\tthis.pragmaRules = this.instantiateRules(this.pragmaRuleClasses,\"pragma\",0);\n\t// Instantiate the parser block and inline rules\n\tthis.blockRules = this.instantiateRules(this.blockRuleClasses,\"block\",0);\n\tthis.inlineRules = this.instantiateRules(this.inlineRuleClasses,\"inline\",0);\n\t// Parse any pragmas\n\tthis.tree = [];\n\tvar topBranch = this.parsePragmas();\n\t// Parse the text into inline runs or blocks\n\tif(options.parseAsInline) {\n\t\ttopBranch.push.apply(topBranch,this.parseInlineRun());\n\t} else {\n\t\ttopBranch.push.apply(topBranch,this.parseBlocks());\n\t}\n\t// Return the parse tree\n};\n\n/*\n*/\nWikiParser.prototype.loadRemoteTiddler = function(url) {\n\tvar self = this;\n\t$tw.utils.httpRequest({\n\t\turl: url,\n\t\ttype: \"GET\",\n\t\tcallback: function(err,data) {\n\t\t\tif(!err) {\n\t\t\t\tvar tiddlers = self.wiki.deserializeTiddlers(\".tid\",data,self.wiki.getCreationFields());\n\t\t\t\t$tw.utils.each(tiddlers,function(tiddler) {\n\t\t\t\t\ttiddler[\"_canonical_uri\"] = url;\n\t\t\t\t});\n\t\t\t\tif(tiddlers) {\n\t\t\t\t\tself.wiki.addTiddlers(tiddlers);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t});\n};\n\n/*\n*/\nWikiParser.prototype.setupRules = function(proto,configPrefix) {\n\tvar self = this;\n\tif(!$tw.safemode) {\n\t\t$tw.utils.each(proto,function(object,name) {\n\t\t\tif(self.wiki.getTiddlerText(configPrefix + name,\"enable\") !== \"enable\") {\n\t\t\t\tdelete proto[name];\n\t\t\t}\n\t\t});\n\t}\n};\n\n/*\nInstantiate an array of parse rules\n*/\nWikiParser.prototype.instantiateRules = function(classes,type,startPos) {\n\tvar rulesInfo = [],\n\t\tself = this;\n\t$tw.utils.each(classes,function(RuleClass) {\n\t\t// Instantiate the rule\n\t\tvar rule = new RuleClass(self);\n\t\trule.is = {};\n\t\trule.is[type] = true;\n\t\trule.init(self);\n\t\tvar matchIndex = rule.findNextMatch(startPos);\n\t\tif(matchIndex !== undefined) {\n\t\t\trulesInfo.push({\n\t\t\t\trule: rule,\n\t\t\t\tmatchIndex: matchIndex\n\t\t\t});\n\t\t}\n\t});\n\treturn rulesInfo;\n};\n\n/*\nSkip any whitespace at the current position. Options are:\n\ttreatNewlinesAsNonWhitespace: true if newlines are NOT to be treated as whitespace\n*/\nWikiParser.prototype.skipWhitespace = function(options) {\n\toptions = options || {};\n\tvar whitespaceRegExp = options.treatNewlinesAsNonWhitespace ? /([^\\S\\n]+)/mg : /(\\s+)/mg;\n\twhitespaceRegExp.lastIndex = this.pos;\n\tvar whitespaceMatch = whitespaceRegExp.exec(this.source);\n\tif(whitespaceMatch && whitespaceMatch.index === this.pos) {\n\t\tthis.pos = whitespaceRegExp.lastIndex;\n\t}\n};\n\n/*\nGet the next match out of an array of parse rule instances\n*/\nWikiParser.prototype.findNextMatch = function(rules,startPos) {\n\t// Find the best matching rule by finding the closest match position\n\tvar matchingRule,\n\t\tmatchingRulePos = this.sourceLength;\n\t// Step through each rule\n\tfor(var t=0; t<rules.length; t++) {\n\t\tvar ruleInfo = rules[t];\n\t\t// Ask the rule to get the next match if we've moved past the current one\n\t\tif(ruleInfo.matchIndex !== undefined && ruleInfo.matchIndex < startPos) {\n\t\t\truleInfo.matchIndex = ruleInfo.rule.findNextMatch(startPos);\n\t\t}\n\t\t// Adopt this match if it's closer than the current best match\n\t\tif(ruleInfo.matchIndex !== undefined && ruleInfo.matchIndex <= matchingRulePos) {\n\t\t\tmatchingRule = ruleInfo;\n\t\t\tmatchingRulePos = ruleInfo.matchIndex;\n\t\t}\n\t}\n\treturn matchingRule;\n};\n\n/*\nParse any pragmas at the beginning of a block of parse text\n*/\nWikiParser.prototype.parsePragmas = function() {\n\tvar currentTreeBranch = this.tree;\n\twhile(true) {\n\t\t// Skip whitespace\n\t\tthis.skipWhitespace();\n\t\t// Check for the end of the text\n\t\tif(this.pos >= this.sourceLength) {\n\t\t\tbreak;\n\t\t}\n\t\t// Check if we've arrived at a pragma rule match\n\t\tvar nextMatch = this.findNextMatch(this.pragmaRules,this.pos);\n\t\t// If not, just exit\n\t\tif(!nextMatch || nextMatch.matchIndex !== this.pos) {\n\t\t\tbreak;\n\t\t}\n\t\t// Process the pragma rule\n\t\tvar subTree = nextMatch.rule.parse();\n\t\tif(subTree.length > 0) {\n\t\t\t// Quick hack; we only cope with a single parse tree node being returned, which is true at the moment\n\t\t\tcurrentTreeBranch.push.apply(currentTreeBranch,subTree);\n\t\t\tsubTree[0].children = [];\n\t\t\tcurrentTreeBranch = subTree[0].children;\n\t\t}\n\t}\n\treturn currentTreeBranch;\n};\n\n/*\nParse a block from the current position\n\tterminatorRegExpString: optional regular expression string that identifies the end of plain paragraphs. Must not include capturing parenthesis\n*/\nWikiParser.prototype.parseBlock = function(terminatorRegExpString) {\n\tvar terminatorRegExp = terminatorRegExpString ? new RegExp(\"(\" + terminatorRegExpString + \"|\\\\r?\\\\n\\\\r?\\\\n)\",\"mg\") : /(\\r?\\n\\r?\\n)/mg;\n\tthis.skipWhitespace();\n\tif(this.pos >= this.sourceLength) {\n\t\treturn [];\n\t}\n\t// Look for a block rule that applies at the current position\n\tvar nextMatch = this.findNextMatch(this.blockRules,this.pos);\n\tif(nextMatch && nextMatch.matchIndex === this.pos) {\n\t\treturn nextMatch.rule.parse();\n\t}\n\t// Treat it as a paragraph if we didn't find a block rule\n\treturn [{type: \"element\", tag: \"p\", children: this.parseInlineRun(terminatorRegExp)}];\n};\n\n/*\nParse a series of blocks of text until a terminating regexp is encountered or the end of the text\n\tterminatorRegExpString: terminating regular expression\n*/\nWikiParser.prototype.parseBlocks = function(terminatorRegExpString) {\n\tif(terminatorRegExpString) {\n\t\treturn this.parseBlocksTerminated(terminatorRegExpString);\n\t} else {\n\t\treturn this.parseBlocksUnterminated();\n\t}\n};\n\n/*\nParse a block from the current position to the end of the text\n*/\nWikiParser.prototype.parseBlocksUnterminated = function() {\n\tvar tree = [];\n\twhile(this.pos < this.sourceLength) {\n\t\ttree.push.apply(tree,this.parseBlock());\n\t}\n\treturn tree;\n};\n\n/*\nParse blocks of text until a terminating regexp is encountered\n*/\nWikiParser.prototype.parseBlocksTerminated = function(terminatorRegExpString) {\n\tvar terminatorRegExp = new RegExp(\"(\" + terminatorRegExpString + \")\",\"mg\"),\n\t\ttree = [];\n\t// Skip any whitespace\n\tthis.skipWhitespace();\n\t// Check if we've got the end marker\n\tterminatorRegExp.lastIndex = this.pos;\n\tvar match = terminatorRegExp.exec(this.source);\n\t// Parse the text into blocks\n\twhile(this.pos < this.sourceLength && !(match && match.index === this.pos)) {\n\t\tvar blocks = this.parseBlock(terminatorRegExpString);\n\t\ttree.push.apply(tree,blocks);\n\t\t// Skip any whitespace\n\t\tthis.skipWhitespace();\n\t\t// Check if we've got the end marker\n\t\tterminatorRegExp.lastIndex = this.pos;\n\t\tmatch = terminatorRegExp.exec(this.source);\n\t}\n\tif(match && match.index === this.pos) {\n\t\tthis.pos = match.index + match[0].length;\n\t}\n\treturn tree;\n};\n\n/*\nParse a run of text at the current position\n\tterminatorRegExp: a regexp at which to stop the run\n\toptions: see below\nOptions available:\n\teatTerminator: move the parse position past any encountered terminator (default false)\n*/\nWikiParser.prototype.parseInlineRun = function(terminatorRegExp,options) {\n\tif(terminatorRegExp) {\n\t\treturn this.parseInlineRunTerminated(terminatorRegExp,options);\n\t} else {\n\t\treturn this.parseInlineRunUnterminated(options);\n\t}\n};\n\nWikiParser.prototype.parseInlineRunUnterminated = function(options) {\n\tvar tree = [];\n\t// Find the next occurrence of an inline rule\n\tvar nextMatch = this.findNextMatch(this.inlineRules,this.pos);\n\t// Loop around the matches until we've reached the end of the text\n\twhile(this.pos < this.sourceLength && nextMatch) {\n\t\t// Process the text preceding the run rule\n\t\tif(nextMatch.matchIndex > this.pos) {\n\t\t\ttree.push({type: \"text\", text: this.source.substring(this.pos,nextMatch.matchIndex)});\n\t\t\tthis.pos = nextMatch.matchIndex;\n\t\t}\n\t\t// Process the run rule\n\t\ttree.push.apply(tree,nextMatch.rule.parse());\n\t\t// Look for the next run rule\n\t\tnextMatch = this.findNextMatch(this.inlineRules,this.pos);\n\t}\n\t// Process the remaining text\n\tif(this.pos < this.sourceLength) {\n\t\ttree.push({type: \"text\", text: this.source.substr(this.pos)});\n\t}\n\tthis.pos = this.sourceLength;\n\treturn tree;\n};\n\nWikiParser.prototype.parseInlineRunTerminated = function(terminatorRegExp,options) {\n\toptions = options || {};\n\tvar tree = [];\n\t// Find the next occurrence of the terminator\n\tterminatorRegExp.lastIndex = this.pos;\n\tvar terminatorMatch = terminatorRegExp.exec(this.source);\n\t// Find the next occurrence of a inlinerule\n\tvar inlineRuleMatch = this.findNextMatch(this.inlineRules,this.pos);\n\t// Loop around until we've reached the end of the text\n\twhile(this.pos < this.sourceLength && (terminatorMatch || inlineRuleMatch)) {\n\t\t// Return if we've found the terminator, and it precedes any inline rule match\n\t\tif(terminatorMatch) {\n\t\t\tif(!inlineRuleMatch || inlineRuleMatch.matchIndex >= terminatorMatch.index) {\n\t\t\t\tif(terminatorMatch.index > this.pos) {\n\t\t\t\t\ttree.push({type: \"text\", text: this.source.substring(this.pos,terminatorMatch.index)});\n\t\t\t\t}\n\t\t\t\tthis.pos = terminatorMatch.index;\n\t\t\t\tif(options.eatTerminator) {\n\t\t\t\t\tthis.pos += terminatorMatch[0].length;\n\t\t\t\t}\n\t\t\t\treturn tree;\n\t\t\t}\n\t\t}\n\t\t// Process any inline rule, along with the text preceding it\n\t\tif(inlineRuleMatch) {\n\t\t\t// Preceding text\n\t\t\tif(inlineRuleMatch.matchIndex > this.pos) {\n\t\t\t\ttree.push({type: \"text\", text: this.source.substring(this.pos,inlineRuleMatch.matchIndex)});\n\t\t\t\tthis.pos = inlineRuleMatch.matchIndex;\n\t\t\t}\n\t\t\t// Process the inline rule\n\t\t\ttree.push.apply(tree,inlineRuleMatch.rule.parse());\n\t\t\t// Look for the next inline rule\n\t\t\tinlineRuleMatch = this.findNextMatch(this.inlineRules,this.pos);\n\t\t\t// Look for the next terminator match\n\t\t\tterminatorRegExp.lastIndex = this.pos;\n\t\t\tterminatorMatch = terminatorRegExp.exec(this.source);\n\t\t}\n\t}\n\t// Process the remaining text\n\tif(this.pos < this.sourceLength) {\n\t\ttree.push({type: \"text\", text: this.source.substr(this.pos)});\n\t}\n\tthis.pos = this.sourceLength;\n\treturn tree;\n};\n\n/*\nParse zero or more class specifiers `.classname`\n*/\nWikiParser.prototype.parseClasses = function() {\n\tvar classRegExp = /\\.([^\\s\\.]+)/mg,\n\t\tclassNames = [];\n\tclassRegExp.lastIndex = this.pos;\n\tvar match = classRegExp.exec(this.source);\n\twhile(match && match.index === this.pos) {\n\t\tthis.pos = match.index + match[0].length;\n\t\tclassNames.push(match[1]);\n\t\tmatch = classRegExp.exec(this.source);\n\t}\n\treturn classNames;\n};\n\n/*\nAmend the rules used by this instance of the parser\n\ttype: `only` keeps just the named rules, `except` keeps all but the named rules\n\tnames: array of rule names\n*/\nWikiParser.prototype.amendRules = function(type,names) {\n\tnames = names || [];\n\t// Define the filter function\n\tvar keepFilter;\n\tif(type === \"only\") {\n\t\tkeepFilter = function(name) {\n\t\t\treturn names.indexOf(name) !== -1;\n\t\t};\n\t} else if(type === \"except\") {\n\t\tkeepFilter = function(name) {\n\t\t\treturn names.indexOf(name) === -1;\n\t\t};\n\t} else {\n\t\treturn;\n\t}\n\t// Define a function to process each of our rule arrays\n\tvar processRuleArray = function(ruleArray) {\n\t\tfor(var t=ruleArray.length-1; t>=0; t--) {\n\t\t\tif(!keepFilter(ruleArray[t].rule.name)) {\n\t\t\t\truleArray.splice(t,1);\n\t\t\t}\n\t\t}\n\t};\n\t// Process each rule array\n\tprocessRuleArray(this.pragmaRules);\n\tprocessRuleArray(this.blockRules);\n\tprocessRuleArray(this.inlineRules);\n};\n\nexports[\"text/vnd.tiddlywiki\"] = WikiParser;\n\n})();\n\n",
"title": "$:/core/modules/parsers/wikiparser/wikiparser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/core/modules/parsers/wikiparser/rules/wikirulebase.js": {
"text": "/*\\\ntitle: $:/core/modules/parsers/wikiparser/rules/wikirulebase.js\ntype: application/javascript\nmodule-type: global\n\nBase class for wiki parser rules\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nThis constructor is always overridden with a blank constructor, and so shouldn't be used\n*/\nvar WikiRuleBase = function() {\n};\n\n/*\nTo be overridden by individual rules\n*/\nWikiRuleBase.prototype.init = function(parser) {\n\tthis.parser = parser;\n};\n\n/*\nDefault implementation of findNextMatch uses RegExp matching\n*/\nWikiRuleBase.prototype.findNextMatch = function(startPos) {\n\tthis.matchRegExp.lastIndex = startPos;\n\tthis.match = this.matchRegExp.exec(this.parser.source);\n\treturn this.match ? this.match.index : undefined;\n};\n\nexports.WikiRuleBase = WikiRuleBase;\n\n})();\n",
"title": "$:/core/modules/parsers/wikiparser/rules/wikirulebase.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/pluginswitcher.js": {
"text": "/*\\\ntitle: $:/core/modules/pluginswitcher.js\ntype: application/javascript\nmodule-type: global\n\nManages switching plugins for themes and languages.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\noptions:\nwiki: wiki store to be used\npluginType: type of plugin to be switched\ncontrollerTitle: title of tiddler used to control switching of this resource\ndefaultPlugins: array of default plugins to be used if nominated plugin isn't found\n*/\nfunction PluginSwitcher(options) {\n\tthis.wiki = options.wiki;\n\tthis.pluginType = options.pluginType;\n\tthis.controllerTitle = options.controllerTitle;\n\tthis.defaultPlugins = options.defaultPlugins || [];\n\t// Switch to the current plugin\n\tthis.switchPlugins();\n\t// Listen for changes to the selected plugin\n\tvar self = this;\n\tthis.wiki.addEventListener(\"change\",function(changes) {\n\t\tif($tw.utils.hop(changes,self.controllerTitle)) {\n\t\t\tself.switchPlugins();\n\t\t}\n\t});\n}\n\nPluginSwitcher.prototype.switchPlugins = function() {\n\t// Get the name of the current theme\n\tvar selectedPluginTitle = this.wiki.getTiddlerText(this.controllerTitle);\n\t// If it doesn't exist, then fallback to one of the default themes\n\tvar index = 0;\n\twhile(!this.wiki.getTiddler(selectedPluginTitle) && index < this.defaultPlugins.length) {\n\t\tselectedPluginTitle = this.defaultPlugins[index++];\n\t}\n\t// Accumulate the titles of the plugins that we need to load\n\tvar plugins = [],\n\t\tself = this,\n\t\taccumulatePlugin = function(title) {\n\t\t\tvar tiddler = self.wiki.getTiddler(title);\n\t\t\tif(tiddler && tiddler.isPlugin() && plugins.indexOf(title) === -1) {\n\t\t\t\tplugins.push(title);\n\t\t\t\tvar pluginInfo = JSON.parse(self.wiki.getTiddlerText(title)),\n\t\t\t\t\tdependents = $tw.utils.parseStringArray(tiddler.fields.dependents || \"\");\n\t\t\t\t$tw.utils.each(dependents,function(title) {\n\t\t\t\t\taccumulatePlugin(title);\n\t\t\t\t});\n\t\t\t}\n\t\t};\n\taccumulatePlugin(selectedPluginTitle);\n\t// Unregister any existing theme tiddlers\n\tvar unregisteredTiddlers = $tw.wiki.unregisterPluginTiddlers(this.pluginType);\n\t// Register any new theme tiddlers\n\tvar registeredTiddlers = $tw.wiki.registerPluginTiddlers(this.pluginType,plugins);\n\t// Unpack the current theme tiddlers\n\t$tw.wiki.unpackPluginTiddlers();\n};\n\nexports.PluginSwitcher = PluginSwitcher;\n\n})();\n",
"title": "$:/core/modules/pluginswitcher.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/saver-handler.js": {
"text": "/*\\\ntitle: $:/core/modules/saver-handler.js\ntype: application/javascript\nmodule-type: global\n\nThe saver handler tracks changes to the store and handles saving the entire wiki via saver modules.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInstantiate the saver handler with the following options:\nwiki: wiki to be synced\ndirtyTracking: true if dirty tracking should be performed\n*/\nfunction SaverHandler(options) {\n\tvar self = this;\n\tthis.wiki = options.wiki;\n\tthis.dirtyTracking = options.dirtyTracking;\n\tthis.pendingAutoSave = false;\n\t// Make a logger\n\tthis.logger = new $tw.utils.Logger(\"saver-handler\");\n\t// Initialise our savers\n\tif($tw.browser) {\n\t\tthis.initSavers();\n\t}\n\t// Only do dirty tracking if required\n\tif($tw.browser && this.dirtyTracking) {\n\t\t// Compile the dirty tiddler filter\n\t\tthis.filterFn = this.wiki.compileFilter(this.wiki.getTiddlerText(this.titleSyncFilter));\n\t\t// Count of changes that have not yet been saved\n\t\tthis.numChanges = 0;\n\t\t// Listen out for changes to tiddlers\n\t\tthis.wiki.addEventListener(\"change\",function(changes) {\n\t\t\t// Filter the changes so that we only count changes to tiddlers that we care about\n\t\t\tvar filteredChanges = self.filterFn.call(self.wiki,function(callback) {\n\t\t\t\t$tw.utils.each(changes,function(change,title) {\n\t\t\t\t\tvar tiddler = self.wiki.getTiddler(title);\n\t\t\t\t\tcallback(tiddler,title);\n\t\t\t\t});\n\t\t\t});\n\t\t\t// Adjust the number of changes\n\t\t\tself.numChanges += filteredChanges.length;\n\t\t\tself.updateDirtyStatus();\n\t\t\t// Do any autosave if one is pending and there's no more change events\n\t\t\tif(self.pendingAutoSave && self.wiki.getSizeOfTiddlerEventQueue() === 0) {\n\t\t\t\t// Check if we're dirty\n\t\t\t\tif(self.numChanges > 0) {\n\t\t\t\t\tself.saveWiki({\n\t\t\t\t\t\tmethod: \"autosave\",\n\t\t\t\t\t\tdownloadType: \"text/plain\"\n\t\t\t\t\t});\n\t\t\t\t}\n\t\t\t\tself.pendingAutoSave = false;\n\t\t\t}\n\t\t});\n\t\t// Listen for the autosave event\n\t\t$tw.rootWidget.addEventListener(\"tm-auto-save-wiki\",function(event) {\n\t\t\t// Do the autosave unless there are outstanding tiddler change events\n\t\t\tif(self.wiki.getSizeOfTiddlerEventQueue() === 0) {\n\t\t\t\t// Check if we're dirty\n\t\t\t\tif(self.numChanges > 0) {\n\t\t\t\t\tself.saveWiki({\n\t\t\t\t\t\tmethod: \"autosave\",\n\t\t\t\t\t\tdownloadType: \"text/plain\"\n\t\t\t\t\t});\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\t// Otherwise put ourselves in the \"pending autosave\" state and wait for the change event before we do the autosave\n\t\t\t\tself.pendingAutoSave = true;\n\t\t\t}\n\t\t});\n\t\t// Set up our beforeunload handler\n\t\t$tw.addUnloadTask(function(event) {\n\t\t\tvar confirmationMessage;\n\t\t\tif(self.isDirty()) {\n\t\t\t\tconfirmationMessage = $tw.language.getString(\"UnsavedChangesWarning\");\n\t\t\t\tevent.returnValue = confirmationMessage; // Gecko\n\t\t\t}\n\t\t\treturn confirmationMessage;\n\t\t});\n\t}\n\t// Install the save action handlers\n\tif($tw.browser) {\n\t\t$tw.rootWidget.addEventListener(\"tm-save-wiki\",function(event) {\n\t\t\tself.saveWiki({\n\t\t\t\ttemplate: event.param,\n\t\t\t\tdownloadType: \"text/plain\",\n\t\t\t\tvariables: event.paramObject\n\t\t\t});\n\t\t});\n\t\t$tw.rootWidget.addEventListener(\"tm-download-file\",function(event) {\n\t\t\tself.saveWiki({\n\t\t\t\tmethod: \"download\",\n\t\t\t\ttemplate: event.param,\n\t\t\t\tdownloadType: \"text/plain\",\n\t\t\t\tvariables: event.paramObject\n\t\t\t});\n\t\t});\n\t}\n}\n\nSaverHandler.prototype.titleSyncFilter = \"$:/config/SaverFilter\";\nSaverHandler.prototype.titleAutoSave = \"$:/config/AutoSave\";\nSaverHandler.prototype.titleSavedNotification = \"$:/language/Notifications/Save/Done\";\n\n/*\nSelect the appropriate saver modules and set them up\n*/\nSaverHandler.prototype.initSavers = function(moduleType) {\n\tmoduleType = moduleType || \"saver\";\n\t// Instantiate the available savers\n\tthis.savers = [];\n\tvar self = this;\n\t$tw.modules.forEachModuleOfType(moduleType,function(title,module) {\n\t\tif(module.canSave(self)) {\n\t\t\tself.savers.push(module.create(self.wiki));\n\t\t}\n\t});\n\t// Sort the savers into priority order\n\tthis.savers.sort(function(a,b) {\n\t\tif(a.info.priority < b.info.priority) {\n\t\t\treturn -1;\n\t\t} else {\n\t\t\tif(a.info.priority > b.info.priority) {\n\t\t\t\treturn +1;\n\t\t\t} else {\n\t\t\t\treturn 0;\n\t\t\t}\n\t\t}\n\t});\n};\n\n/*\nSave the wiki contents. Options are:\n\tmethod: \"save\", \"autosave\" or \"download\"\n\ttemplate: the tiddler containing the template to save\n\tdownloadType: the content type for the saved file\n*/\nSaverHandler.prototype.saveWiki = function(options) {\n\toptions = options || {};\n\tvar self = this,\n\t\tmethod = options.method || \"save\",\n\t\tvariables = options.variables || {},\n\t\ttemplate = options.template || \"$:/core/save/all\",\n\t\tdownloadType = options.downloadType || \"text/plain\",\n\t\ttext = this.wiki.renderTiddler(downloadType,template,options),\n\t\tcallback = function(err) {\n\t\t\tif(err) {\n\t\t\t\talert($tw.language.getString(\"Error/WhileSaving\") + \":\\n\\n\" + err);\n\t\t\t} else {\n\t\t\t\t// Clear the task queue if we're saving (rather than downloading)\n\t\t\t\tif(method !== \"download\") {\n\t\t\t\t\tself.numChanges = 0;\n\t\t\t\t\tself.updateDirtyStatus();\n\t\t\t\t}\n\t\t\t\t$tw.notifier.display(self.titleSavedNotification);\n\t\t\t\tif(options.callback) {\n\t\t\t\t\toptions.callback();\n\t\t\t\t}\n\t\t\t}\n\t\t};\n\t// Ignore autosave if disabled\n\tif(method === \"autosave\" && this.wiki.getTiddlerText(this.titleAutoSave,\"yes\") !== \"yes\") {\n\t\treturn false;\n\t}\n\t// Call the highest priority saver that supports this method\n\tfor(var t=this.savers.length-1; t>=0; t--) {\n\t\tvar saver = this.savers[t];\n\t\tif(saver.info.capabilities.indexOf(method) !== -1 && saver.save(text,method,callback,{variables: {filename: variables.filename}})) {\n\t\t\tthis.logger.log(\"Saving wiki with method\",method,\"through saver\",saver.info.name);\n\t\t\treturn true;\n\t\t}\n\t}\n\treturn false;\n};\n\n/*\nChecks whether the wiki is dirty (ie the window shouldn't be closed)\n*/\nSaverHandler.prototype.isDirty = function() {\n\treturn this.numChanges > 0;\n};\n\n/*\nUpdate the document body with the class \"tc-dirty\" if the wiki has unsaved/unsynced changes\n*/\nSaverHandler.prototype.updateDirtyStatus = function() {\n\tif($tw.browser) {\n\t\t$tw.utils.toggleClass(document.body,\"tc-dirty\",this.isDirty());\n\t}\n};\n\nexports.SaverHandler = SaverHandler;\n\n})();\n",
"title": "$:/core/modules/saver-handler.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/savers/andtidwiki.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/andtidwiki.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via the AndTidWiki Android app\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false, netscape: false, Components: false */\n\"use strict\";\n\nvar AndTidWiki = function(wiki) {\n};\n\nAndTidWiki.prototype.save = function(text,method,callback) {\n\t// Get the pathname of this document\n\tvar pathname = decodeURIComponent(document.location.toString().split(\"#\")[0]);\n\t// Strip the file://\n\tif(pathname.indexOf(\"file://\") === 0) {\n\t\tpathname = pathname.substr(7);\n\t}\n\t// Strip any query or location part\n\tvar p = pathname.indexOf(\"?\");\n\tif(p !== -1) {\n\t\tpathname = pathname.substr(0,p);\n\t}\n\tp = pathname.indexOf(\"#\");\n\tif(p !== -1) {\n\t\tpathname = pathname.substr(0,p);\n\t}\n\t// Save the file\n\twindow.twi.saveFile(pathname,text);\n\t// Call the callback\n\tcallback(null);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nAndTidWiki.prototype.info = {\n\tname: \"andtidwiki\",\n\tpriority: 1600,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn !!window.twi && !!window.twi.saveFile;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new AndTidWiki(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/andtidwiki.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/download.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/download.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via HTML5's download APIs\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar DownloadSaver = function(wiki) {\n};\n\nDownloadSaver.prototype.save = function(text,method,callback,options) {\n\toptions = options || {};\n\t// Get the current filename\n\tvar filename = options.variables.filename;\n\tif(!filename) {\n\t\tvar p = document.location.pathname.lastIndexOf(\"/\");\n\t\tif(p !== -1) {\n\t\t\tfilename = document.location.pathname.substr(p+1);\n\t\t}\n\t}\n\tif(!filename) {\n\t\tfilename = \"tiddlywiki.html\";\n\t}\n\t// Set up the link\n\tvar link = document.createElement(\"a\");\n\tlink.setAttribute(\"target\",\"_blank\");\n\tlink.setAttribute(\"rel\",\"noopener noreferrer\");\n\tif(Blob !== undefined) {\n\t\tvar blob = new Blob([text], {type: \"text/html\"});\n\t\tlink.setAttribute(\"href\", URL.createObjectURL(blob));\n\t} else {\n\t\tlink.setAttribute(\"href\",\"data:text/html,\" + encodeURIComponent(text));\n\t}\n\tlink.setAttribute(\"download\",filename);\n\tdocument.body.appendChild(link);\n\tlink.click();\n\tdocument.body.removeChild(link);\n\t// Callback that we succeeded\n\tcallback(null);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nDownloadSaver.prototype.info = {\n\tname: \"download\",\n\tpriority: 100,\n\tcapabilities: [\"save\", \"download\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn document.createElement(\"a\").download !== undefined;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new DownloadSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/download.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/fsosaver.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/fsosaver.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via MS FileSystemObject ActiveXObject\n\nNote: Since TiddlyWiki's markup contains the MOTW, the FileSystemObject normally won't be available. \nHowever, if the wiki is loaded as an .HTA file (Windows HTML Applications) then the FSO can be used.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar FSOSaver = function(wiki) {\n};\n\nFSOSaver.prototype.save = function(text,method,callback) {\n\t// Get the pathname of this document\n\tvar pathname = unescape(document.location.pathname);\n\t// Test for a Windows path of the form /x:\\blah...\n\tif(/^\\/[A-Z]\\:\\\\[^\\\\]+/i.test(pathname)) {\t// ie: ^/[a-z]:/[^/]+\n\t\t// Remove the leading slash\n\t\tpathname = pathname.substr(1);\n\t} else if(document.location.hostname !== \"\" && /^\\/\\\\[^\\\\]+\\\\[^\\\\]+/i.test(pathname)) {\t// test for \\\\server\\share\\blah... - ^/[^/]+/[^/]+\n\t\t// Remove the leading slash\n\t\tpathname = pathname.substr(1);\n\t\t// reconstruct UNC path\n\t\tpathname = \"\\\\\\\\\" + document.location.hostname + pathname;\n\t} else {\n\t\treturn false;\n\t}\n\t// Save the file (as UTF-16)\n\tvar fso = new ActiveXObject(\"Scripting.FileSystemObject\");\n\tvar file = fso.OpenTextFile(pathname,2,-1,-1);\n\tfile.Write(text);\n\tfile.Close();\n\t// Callback that we succeeded\n\tcallback(null);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nFSOSaver.prototype.info = {\n\tname: \"FSOSaver\",\n\tpriority: 120,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\ttry {\n\t\treturn (window.location.protocol === \"file:\") && !!(new ActiveXObject(\"Scripting.FileSystemObject\"));\n\t} catch(e) { return false; }\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new FSOSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/fsosaver.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/manualdownload.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/manualdownload.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via HTML5's download APIs\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Title of the tiddler containing the download message\nvar downloadInstructionsTitle = \"$:/language/Modals/Download\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar ManualDownloadSaver = function(wiki) {\n};\n\nManualDownloadSaver.prototype.save = function(text,method,callback) {\n\t$tw.modal.display(downloadInstructionsTitle,{\n\t\tdownloadLink: \"data:text/html,\" + encodeURIComponent(text)\n\t});\n\t// Callback that we succeeded\n\tcallback(null);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nManualDownloadSaver.prototype.info = {\n\tname: \"manualdownload\",\n\tpriority: 0,\n\tcapabilities: [\"save\", \"download\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn true;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new ManualDownloadSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/manualdownload.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/msdownload.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/msdownload.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via window.navigator.msSaveBlob()\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar MsDownloadSaver = function(wiki) {\n};\n\nMsDownloadSaver.prototype.save = function(text,method,callback) {\n\t// Get the current filename\n\tvar filename = \"tiddlywiki.html\",\n\t\tp = document.location.pathname.lastIndexOf(\"/\");\n\tif(p !== -1) {\n\t\tfilename = document.location.pathname.substr(p+1);\n\t}\n\t// Set up the link\n\tvar blob = new Blob([text], {type: \"text/html\"});\n\twindow.navigator.msSaveBlob(blob,filename);\n\t// Callback that we succeeded\n\tcallback(null);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nMsDownloadSaver.prototype.info = {\n\tname: \"msdownload\",\n\tpriority: 110,\n\tcapabilities: [\"save\", \"download\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn !!window.navigator.msSaveBlob;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new MsDownloadSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/msdownload.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/put.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/put.js\ntype: application/javascript\nmodule-type: saver\n\nSaves wiki by performing a PUT request to the server\n\nWorks with any server which accepts a PUT request\nto the current URL, such as a WebDAV server.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar PutSaver = function(wiki) {\n\tthis.wiki = wiki;\n\tvar self = this;\n\t// Async server probe. Until probe finishes, save will fail fast\n\t// See also https://github.com/Jermolene/TiddlyWiki5/issues/2276\n\tvar req = new XMLHttpRequest();\n\treq.open(\"OPTIONS\",encodeURI(document.location.protocol + \"//\" + document.location.hostname + \":\" + document.location.port + document.location.pathname));\n\treq.onload = function() {\n\t\t// Check DAV header http://www.webdav.org/specs/rfc2518.html#rfc.section.9.1\n\t\tself.serverAcceptsPuts = (this.status === 200 && !!this.getResponseHeader('dav'));\n\t};\n\treq.send();\n};\n\nPutSaver.prototype.save = function(text,method,callback) {\n\tif (!this.serverAcceptsPuts) {\n\t\treturn false;\n\t}\n\tvar req = new XMLHttpRequest();\n\t// TODO: store/check ETags if supported by server, to protect against overwrites\n\t// Prompt: Do you want to save over this? Y/N\n\t// Merging would be ideal, and may be possible using future generic merge flow\n\treq.onload = function() {\n\t\tif (this.status === 200 || this.status === 201) {\n\t\t\tcallback(null); // success\n\t\t}\n\t\telse {\n\t\t\tcallback(this.responseText); // fail\n\t\t}\n\t};\n\treq.open(\"PUT\", encodeURI(window.location.href));\n\treq.setRequestHeader(\"Content-Type\", \"text/html;charset=UTF-8\");\n\treq.send(text);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nPutSaver.prototype.info = {\n\tname: \"put\",\n\tpriority: 2000,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn /^https?:/.test(location.protocol);\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new PutSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/put.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/tiddlyfox.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/tiddlyfox.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via the TiddlyFox file extension\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false, netscape: false, Components: false */\n\"use strict\";\n\nvar TiddlyFoxSaver = function(wiki) {\n};\n\nTiddlyFoxSaver.prototype.save = function(text,method,callback) {\n\tvar messageBox = document.getElementById(\"tiddlyfox-message-box\");\n\tif(messageBox) {\n\t\t// Get the pathname of this document\n\t\tvar pathname = document.location.toString().split(\"#\")[0];\n\t\t// Replace file://localhost/ with file:///\n\t\tif(pathname.indexOf(\"file://localhost/\") === 0) {\n\t\t\tpathname = \"file://\" + pathname.substr(16);\n\t\t}\n\t\t// Windows path file:///x:/blah/blah --> x:\\blah\\blah\n\t\tif(/^file\\:\\/\\/\\/[A-Z]\\:\\//i.test(pathname)) {\n\t\t\t// Remove the leading slash and convert slashes to backslashes\n\t\t\tpathname = pathname.substr(8).replace(/\\//g,\"\\\\\");\n\t\t// Firefox Windows network path file://///server/share/blah/blah --> //server/share/blah/blah\n\t\t} else if(pathname.indexOf(\"file://///\") === 0) {\n\t\t\tpathname = \"\\\\\\\\\" + unescape(pathname.substr(10)).replace(/\\//g,\"\\\\\");\n\t\t// Mac/Unix local path file:///path/path --> /path/path\n\t\t} else if(pathname.indexOf(\"file:///\") === 0) {\n\t\t\tpathname = unescape(pathname.substr(7));\n\t\t// Mac/Unix local path file:/path/path --> /path/path\n\t\t} else if(pathname.indexOf(\"file:/\") === 0) {\n\t\t\tpathname = unescape(pathname.substr(5));\n\t\t// Otherwise Windows networth path file://server/share/path/path --> \\\\server\\share\\path\\path\n\t\t} else {\n\t\t\tpathname = \"\\\\\\\\\" + unescape(pathname.substr(7)).replace(new RegExp(\"/\",\"g\"),\"\\\\\");\n\t\t}\n\t\t// Create the message element and put it in the message box\n\t\tvar message = document.createElement(\"div\");\n\t\tmessage.setAttribute(\"data-tiddlyfox-path\",decodeURIComponent(pathname));\n\t\tmessage.setAttribute(\"data-tiddlyfox-content\",text);\n\t\tmessageBox.appendChild(message);\n\t\t// Add an event handler for when the file has been saved\n\t\tmessage.addEventListener(\"tiddlyfox-have-saved-file\",function(event) {\n\t\t\tcallback(null);\n\t\t}, false);\n\t\t// Create and dispatch the custom event to the extension\n\t\tvar event = document.createEvent(\"Events\");\n\t\tevent.initEvent(\"tiddlyfox-save-file\",true,false);\n\t\tmessage.dispatchEvent(event);\n\t\treturn true;\n\t} else {\n\t\treturn false;\n\t}\n};\n\n/*\nInformation about this saver\n*/\nTiddlyFoxSaver.prototype.info = {\n\tname: \"tiddlyfox\",\n\tpriority: 1500,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn (window.location.protocol === \"file:\");\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new TiddlyFoxSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/tiddlyfox.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/tiddlyie.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/tiddlyie.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via Internet Explorer BHO extenion (TiddlyIE)\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar TiddlyIESaver = function(wiki) {\n};\n\nTiddlyIESaver.prototype.save = function(text,method,callback) {\n\t// Check existence of TiddlyIE BHO extension (note: only works after document is complete)\n\tif(typeof(window.TiddlyIE) != \"undefined\") {\n\t\t// Get the pathname of this document\n\t\tvar pathname = unescape(document.location.pathname);\n\t\t// Test for a Windows path of the form /x:/blah...\n\t\tif(/^\\/[A-Z]\\:\\/[^\\/]+/i.test(pathname)) {\t// ie: ^/[a-z]:/[^/]+ (is this better?: ^/[a-z]:/[^/]+(/[^/]+)*\\.[^/]+ )\n\t\t\t// Remove the leading slash\n\t\t\tpathname = pathname.substr(1);\n\t\t\t// Convert slashes to backslashes\n\t\t\tpathname = pathname.replace(/\\//g,\"\\\\\");\n\t\t} else if(document.hostname !== \"\" && /^\\/[^\\/]+\\/[^\\/]+/i.test(pathname)) {\t// test for \\\\server\\share\\blah... - ^/[^/]+/[^/]+\n\t\t\t// Convert slashes to backslashes\n\t\t\tpathname = pathname.replace(/\\//g,\"\\\\\");\n\t\t\t// reconstruct UNC path\n\t\t\tpathname = \"\\\\\\\\\" + document.location.hostname + pathname;\n\t\t} else return false;\n\t\t// Prompt the user to save the file\n\t\twindow.TiddlyIE.save(pathname, text);\n\t\t// Callback that we succeeded\n\t\tcallback(null);\n\t\treturn true;\n\t} else {\n\t\treturn false;\n\t}\n};\n\n/*\nInformation about this saver\n*/\nTiddlyIESaver.prototype.info = {\n\tname: \"tiddlyiesaver\",\n\tpriority: 1500,\n\tcapabilities: [\"save\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn (window.location.protocol === \"file:\");\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new TiddlyIESaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/tiddlyie.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/twedit.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/twedit.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via the TWEdit iOS app\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false, netscape: false, Components: false */\n\"use strict\";\n\nvar TWEditSaver = function(wiki) {\n};\n\nTWEditSaver.prototype.save = function(text,method,callback) {\n\t// Bail if we're not running under TWEdit\n\tif(typeof DeviceInfo !== \"object\") {\n\t\treturn false;\n\t}\n\t// Get the pathname of this document\n\tvar pathname = decodeURIComponent(document.location.pathname);\n\t// Strip any query or location part\n\tvar p = pathname.indexOf(\"?\");\n\tif(p !== -1) {\n\t\tpathname = pathname.substr(0,p);\n\t}\n\tp = pathname.indexOf(\"#\");\n\tif(p !== -1) {\n\t\tpathname = pathname.substr(0,p);\n\t}\n\t// Remove the leading \"/Documents\" from path\n\tvar prefix = \"/Documents\";\n\tif(pathname.indexOf(prefix) === 0) {\n\t\tpathname = pathname.substr(prefix.length);\n\t}\n\t// Error handler\n\tvar errorHandler = function(event) {\n\t\t// Error\n\t\tcallback($tw.language.getString(\"Error/SavingToTWEdit\") + \": \" + event.target.error.code);\n\t};\n\t// Get the file system\n\twindow.requestFileSystem(LocalFileSystem.PERSISTENT,0,function(fileSystem) {\n\t\t// Now we've got the filesystem, get the fileEntry\n\t\tfileSystem.root.getFile(pathname, {create: true}, function(fileEntry) {\n\t\t\t// Now we've got the fileEntry, create the writer\n\t\t\tfileEntry.createWriter(function(writer) {\n\t\t\t\twriter.onerror = errorHandler;\n\t\t\t\twriter.onwrite = function() {\n\t\t\t\t\tcallback(null);\n\t\t\t\t};\n\t\t\t\twriter.position = 0;\n\t\t\t\twriter.write(text);\n\t\t\t},errorHandler);\n\t\t}, errorHandler);\n\t}, errorHandler);\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nTWEditSaver.prototype.info = {\n\tname: \"twedit\",\n\tpriority: 1600,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn true;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new TWEditSaver(wiki);\n};\n\n/////////////////////////// Hack\n// HACK: This ensures that TWEdit recognises us as a TiddlyWiki document\nif($tw.browser) {\n\twindow.version = {title: \"TiddlyWiki\"};\n}\n\n})();\n",
"title": "$:/core/modules/savers/twedit.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/savers/upload.js": {
"text": "/*\\\ntitle: $:/core/modules/savers/upload.js\ntype: application/javascript\nmodule-type: saver\n\nHandles saving changes via upload to a server.\n\nDesigned to be compatible with BidiX's UploadPlugin at http://tiddlywiki.bidix.info/#UploadPlugin\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSelect the appropriate saver module and set it up\n*/\nvar UploadSaver = function(wiki) {\n\tthis.wiki = wiki;\n};\n\nUploadSaver.prototype.save = function(text,method,callback) {\n\t// Get the various parameters we need\n\tvar backupDir = this.wiki.getTextReference(\"$:/UploadBackupDir\") || \".\",\n\t\tusername = this.wiki.getTextReference(\"$:/UploadName\"),\n\t\tpassword = $tw.utils.getPassword(\"upload\"),\n\t\tuploadDir = this.wiki.getTextReference(\"$:/UploadDir\") || \".\",\n\t\tuploadFilename = this.wiki.getTextReference(\"$:/UploadFilename\") || \"index.html\",\n\t\turl = this.wiki.getTextReference(\"$:/UploadURL\");\n\t// Bail out if we don't have the bits we need\n\tif(!username || username.toString().trim() === \"\" || !password || password.toString().trim() === \"\") {\n\t\treturn false;\n\t}\n\t// Construct the url if not provided\n\tif(!url) {\n\t\turl = \"http://\" + username + \".tiddlyspot.com/store.cgi\";\n\t}\n\t// Assemble the header\n\tvar boundary = \"---------------------------\" + \"AaB03x\";\t\n\tvar uploadFormName = \"UploadPlugin\";\n\tvar head = [];\n\thead.push(\"--\" + boundary + \"\\r\\nContent-disposition: form-data; name=\\\"UploadPlugin\\\"\\r\\n\");\n\thead.push(\"backupDir=\" + backupDir + \";user=\" + username + \";password=\" + password + \";uploaddir=\" + uploadDir + \";;\"); \n\thead.push(\"\\r\\n\" + \"--\" + boundary);\n\thead.push(\"Content-disposition: form-data; name=\\\"userfile\\\"; filename=\\\"\" + uploadFilename + \"\\\"\");\n\thead.push(\"Content-Type: text/html;charset=UTF-8\");\n\thead.push(\"Content-Length: \" + text.length + \"\\r\\n\");\n\thead.push(\"\");\n\t// Assemble the tail and the data itself\n\tvar tail = \"\\r\\n--\" + boundary + \"--\\r\\n\",\n\t\tdata = head.join(\"\\r\\n\") + text + tail;\n\t// Do the HTTP post\n\tvar http = new XMLHttpRequest();\n\thttp.open(\"POST\",url,true,username,password);\n\thttp.setRequestHeader(\"Content-Type\",\"multipart/form-data; charset=UTF-8; boundary=\" + boundary);\n\thttp.onreadystatechange = function() {\n\t\tif(http.readyState == 4 && http.status == 200) {\n\t\t\tif(http.responseText.substr(0,4) === \"0 - \") {\n\t\t\t\tcallback(null);\n\t\t\t} else {\n\t\t\t\tcallback(http.responseText);\n\t\t\t}\n\t\t}\n\t};\n\ttry {\n\t\thttp.send(data);\n\t} catch(ex) {\n\t\treturn callback($tw.language.getString(\"Error/Caption\") + \":\" + ex);\n\t}\n\t$tw.notifier.display(\"$:/language/Notifications/Save/Starting\");\n\treturn true;\n};\n\n/*\nInformation about this saver\n*/\nUploadSaver.prototype.info = {\n\tname: \"upload\",\n\tpriority: 2000,\n\tcapabilities: [\"save\", \"autosave\"]\n};\n\n/*\nStatic method that returns true if this saver is capable of working\n*/\nexports.canSave = function(wiki) {\n\treturn true;\n};\n\n/*\nCreate an instance of this saver\n*/\nexports.create = function(wiki) {\n\treturn new UploadSaver(wiki);\n};\n\n})();\n",
"title": "$:/core/modules/savers/upload.js",
"type": "application/javascript",
"module-type": "saver"
},
"$:/core/modules/browser-messaging.js": {
"text": "/*\\\ntitle: $:/core/modules/browser-messaging.js\ntype: application/javascript\nmodule-type: startup\n\nBrowser message handling\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"browser-messaging\";\nexports.platforms = [\"browser\"];\nexports.after = [\"startup\"];\nexports.synchronous = true;\n\n/*\nLoad a specified url as an iframe and call the callback when it is loaded. If the url is already loaded then the existing iframe instance is used\n*/\nfunction loadIFrame(url,callback) {\n\t// Check if iframe already exists\n\tvar iframeInfo = $tw.browserMessaging.iframeInfoMap[url];\n\tif(iframeInfo) {\n\t\t// We've already got the iframe\n\t\tcallback(null,iframeInfo);\n\t} else {\n\t\t// Create the iframe and save it in the list\n\t\tvar iframe = document.createElement(\"iframe\"),\n\t\t\tiframeInfo = {\n\t\t\t\turl: url,\n\t\t\t\tstatus: \"loading\",\n\t\t\t\tdomNode: iframe\n\t\t\t};\n\t\t$tw.browserMessaging.iframeInfoMap[url] = iframeInfo;\n\t\tsaveIFrameInfoTiddler(iframeInfo);\n\t\t// Add the iframe to the DOM and hide it\n\t\tiframe.style.display = \"none\";\n\t\tdocument.body.appendChild(iframe);\n\t\t// Set up onload\n\t\tiframe.onload = function() {\n\t\t\tiframeInfo.status = \"loaded\";\n\t\t\tsaveIFrameInfoTiddler(iframeInfo);\n\t\t\tcallback(null,iframeInfo);\n\t\t};\n\t\tiframe.onerror = function() {\n\t\t\tcallback(\"Cannot load iframe\");\n\t\t};\n\t\ttry {\n\t\t\tiframe.src = url;\n\t\t} catch(ex) {\n\t\t\tcallback(ex);\n\t\t}\n\t}\n}\n\nfunction saveIFrameInfoTiddler(iframeInfo) {\n\t$tw.wiki.addTiddler(new $tw.Tiddler($tw.wiki.getCreationFields(),{\n\t\ttitle: \"$:/temp/ServerConnection/\" + iframeInfo.url,\n\t\ttext: iframeInfo.status,\n\t\ttags: [\"$:/tags/ServerConnection\"],\n\t\turl: iframeInfo.url\n\t},$tw.wiki.getModificationFields()));\n}\n\nexports.startup = function() {\n\t// Initialise the store of iframes we've created\n\t$tw.browserMessaging = {\n\t\tiframeInfoMap: {} // Hashmap by URL of {url:,status:\"loading/loaded\",domNode:}\n\t};\n\t// Listen for widget messages to control loading the plugin library\n\t$tw.rootWidget.addEventListener(\"tm-load-plugin-library\",function(event) {\n\t\tvar paramObject = event.paramObject || {},\n\t\t\turl = paramObject.url;\n\t\tif(url) {\n\t\t\tloadIFrame(url,function(err,iframeInfo) {\n\t\t\t\tif(err) {\n\t\t\t\t\talert($tw.language.getString(\"Error/LoadingPluginLibrary\") + \": \" + url);\n\t\t\t\t} else {\n\t\t\t\t\tiframeInfo.domNode.contentWindow.postMessage({\n\t\t\t\t\t\tverb: \"GET\",\n\t\t\t\t\t\turl: \"recipes/library/tiddlers.json\",\n\t\t\t\t\t\tcookies: {\n\t\t\t\t\t\t\ttype: \"save-info\",\n\t\t\t\t\t\t\tinfoTitlePrefix: paramObject.infoTitlePrefix || \"$:/temp/RemoteAssetInfo/\",\n\t\t\t\t\t\t\turl: url\n\t\t\t\t\t\t}\n\t\t\t\t\t},\"*\");\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t});\n\t$tw.rootWidget.addEventListener(\"tm-load-plugin-from-library\",function(event) {\n\t\tvar paramObject = event.paramObject || {},\n\t\t\turl = paramObject.url,\n\t\t\ttitle = paramObject.title;\n\t\tif(url && title) {\n\t\t\tloadIFrame(url,function(err,iframeInfo) {\n\t\t\t\tif(err) {\n\t\t\t\t\talert($tw.language.getString(\"Error/LoadingPluginLibrary\") + \": \" + url);\n\t\t\t\t} else {\n\t\t\t\t\tiframeInfo.domNode.contentWindow.postMessage({\n\t\t\t\t\t\tverb: \"GET\",\n\t\t\t\t\t\turl: \"recipes/library/tiddlers/\" + encodeURIComponent(title) + \".json\",\n\t\t\t\t\t\tcookies: {\n\t\t\t\t\t\t\ttype: \"save-tiddler\",\n\t\t\t\t\t\t\turl: url\n\t\t\t\t\t\t}\n\t\t\t\t\t},\"*\");\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t});\n\t// Listen for window messages from other windows\n\twindow.addEventListener(\"message\",function listener(event){\n\t\tconsole.log(\"browser-messaging: \",document.location.toString())\n\t\tconsole.log(\"browser-messaging: Received message from\",event.origin);\n\t\tconsole.log(\"browser-messaging: Message content\",event.data);\n\t\tswitch(event.data.verb) {\n\t\t\tcase \"GET-RESPONSE\":\n\t\t\t\tif(event.data.status.charAt(0) === \"2\") {\n\t\t\t\t\tif(event.data.cookies) {\n\t\t\t\t\t\tif(event.data.cookies.type === \"save-info\") {\n\t\t\t\t\t\t\tvar tiddlers = JSON.parse(event.data.body);\n\t\t\t\t\t\t\t$tw.utils.each(tiddlers,function(tiddler) {\n\t\t\t\t\t\t\t\t$tw.wiki.addTiddler(new $tw.Tiddler($tw.wiki.getCreationFields(),tiddler,{\n\t\t\t\t\t\t\t\t\ttitle: event.data.cookies.infoTitlePrefix + event.data.cookies.url + \"/\" + tiddler.title,\n\t\t\t\t\t\t\t\t\t\"original-title\": tiddler.title,\n\t\t\t\t\t\t\t\t\ttext: \"\",\n\t\t\t\t\t\t\t\t\ttype: \"text/vnd.tiddlywiki\",\n\t\t\t\t\t\t\t\t\t\"original-type\": tiddler.type,\n\t\t\t\t\t\t\t\t\t\"plugin-type\": undefined,\n\t\t\t\t\t\t\t\t\t\"original-plugin-type\": tiddler[\"plugin-type\"],\n\t\t\t\t\t\t\t\t\t\"module-type\": undefined,\n\t\t\t\t\t\t\t\t\t\"original-module-type\": tiddler[\"module-type\"],\n\t\t\t\t\t\t\t\t\ttags: [\"$:/tags/RemoteAssetInfo\"],\n\t\t\t\t\t\t\t\t\t\"original-tags\": $tw.utils.stringifyList(tiddler.tags || []),\n\t\t\t\t\t\t\t\t\t\"server-url\": event.data.cookies.url\n\t\t\t\t\t\t\t\t},$tw.wiki.getModificationFields()));\n\t\t\t\t\t\t\t});\n\t\t\t\t\t\t} else if(event.data.cookies.type === \"save-tiddler\") {\n\t\t\t\t\t\t\tvar tiddler = JSON.parse(event.data.body);\n\t\t\t\t\t\t\t$tw.wiki.addTiddler(new $tw.Tiddler(tiddler));\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tbreak;\n\t\t}\n\t},false);\n};\n\n})();\n",
"title": "$:/core/modules/browser-messaging.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/commands.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/commands.js\ntype: application/javascript\nmodule-type: startup\n\nCommand processing\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"commands\";\nexports.platforms = [\"node\"];\nexports.after = [\"story\"];\nexports.synchronous = false;\n\nexports.startup = function(callback) {\n\t// On the server, start a commander with the command line arguments\n\tvar commander = new $tw.Commander(\n\t\t$tw.boot.argv,\n\t\tfunction(err) {\n\t\t\tif(err) {\n\t\t\t\treturn $tw.utils.error(\"Error: \" + err);\n\t\t\t}\n\t\t\tcallback();\n\t\t},\n\t\t$tw.wiki,\n\t\t{output: process.stdout, error: process.stderr}\n\t);\n\tcommander.execute();\n};\n\n})();\n",
"title": "$:/core/modules/startup/commands.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/favicon.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/favicon.js\ntype: application/javascript\nmodule-type: startup\n\nFavicon handling\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"favicon\";\nexports.platforms = [\"browser\"];\nexports.after = [\"startup\"];\nexports.synchronous = true;\n\t\t\n// Favicon tiddler\nvar FAVICON_TITLE = \"$:/favicon.ico\";\n\nexports.startup = function() {\n\t// Set up the favicon\n\tsetFavicon();\n\t// Reset the favicon when the tiddler changes\n\t$tw.wiki.addEventListener(\"change\",function(changes) {\n\t\tif($tw.utils.hop(changes,FAVICON_TITLE)) {\n\t\t\tsetFavicon();\n\t\t}\n\t});\n};\n\nfunction setFavicon() {\n\tvar tiddler = $tw.wiki.getTiddler(FAVICON_TITLE);\n\tif(tiddler) {\n\t\tvar faviconLink = document.getElementById(\"faviconLink\");\n\t\tfaviconLink.setAttribute(\"href\",\"data:\" + tiddler.fields.type + \";base64,\" + tiddler.fields.text);\n\t}\n}\n\n})();\n",
"title": "$:/core/modules/startup/favicon.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/info.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/info.js\ntype: application/javascript\nmodule-type: startup\n\nInitialise $:/info tiddlers via $:/temp/info-plugin pseudo-plugin\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"info\";\nexports.before = [\"startup\"];\nexports.after = [\"load-modules\"];\nexports.synchronous = true;\n\nexports.startup = function() {\n\t// Collect up the info tiddlers\n\tvar infoTiddlerFields = {};\n\t// Give each info module a chance to fill in as many info tiddlers as they want\n\t$tw.modules.forEachModuleOfType(\"info\",function(title,moduleExports) {\n\t\tif(moduleExports && moduleExports.getInfoTiddlerFields) {\n\t\t\tvar tiddlerFieldsArray = moduleExports.getInfoTiddlerFields(infoTiddlerFields);\n\t\t\t$tw.utils.each(tiddlerFieldsArray,function(fields) {\n\t\t\t\tif(fields) {\n\t\t\t\t\tinfoTiddlerFields[fields.title] = fields;\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t});\n\t// Bake the info tiddlers into a plugin\n\tvar fields = {\n\t\ttitle: \"$:/temp/info-plugin\",\n\t\ttype: \"application/json\",\n\t\t\"plugin-type\": \"info\",\n\t\ttext: JSON.stringify({tiddlers: infoTiddlerFields},null,$tw.config.preferences.jsonSpaces)\n\t};\n\t$tw.wiki.addTiddler(new $tw.Tiddler(fields));\n\t$tw.wiki.readPluginInfo();\n\t$tw.wiki.registerPluginTiddlers(\"info\");\n\t$tw.wiki.unpackPluginTiddlers();\n};\n\n})();\n",
"title": "$:/core/modules/startup/info.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/load-modules.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/load-modules.js\ntype: application/javascript\nmodule-type: startup\n\nLoad core modules\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"load-modules\";\nexports.synchronous = true;\n\nexports.startup = function() {\n\t// Load modules\n\t$tw.modules.applyMethods(\"utils\",$tw.utils);\n\tif($tw.node) {\n\t\t$tw.modules.applyMethods(\"utils-node\",$tw.utils);\n\t}\n\t$tw.modules.applyMethods(\"global\",$tw);\n\t$tw.modules.applyMethods(\"config\",$tw.config);\n\t$tw.Tiddler.fieldModules = $tw.modules.getModulesByTypeAsHashmap(\"tiddlerfield\");\n\t$tw.modules.applyMethods(\"tiddlermethod\",$tw.Tiddler.prototype);\n\t$tw.modules.applyMethods(\"wikimethod\",$tw.Wiki.prototype);\n\t$tw.modules.applyMethods(\"tiddlerdeserializer\",$tw.Wiki.tiddlerDeserializerModules);\n\t$tw.macros = $tw.modules.getModulesByTypeAsHashmap(\"macro\");\n\t$tw.wiki.initParsers();\n\t$tw.Commander.initCommands();\n};\n\n})();\n",
"title": "$:/core/modules/startup/load-modules.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/password.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/password.js\ntype: application/javascript\nmodule-type: startup\n\nPassword handling\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"password\";\nexports.platforms = [\"browser\"];\nexports.after = [\"startup\"];\nexports.synchronous = true;\n\nexports.startup = function() {\n\t$tw.rootWidget.addEventListener(\"tm-set-password\",function(event) {\n\t\t$tw.passwordPrompt.createPrompt({\n\t\t\tserviceName: $tw.language.getString(\"Encryption/PromptSetPassword\"),\n\t\t\tnoUserName: true,\n\t\t\tsubmitText: $tw.language.getString(\"Encryption/SetPassword\"),\n\t\t\tcanCancel: true,\n\t\t\trepeatPassword: true,\n\t\t\tcallback: function(data) {\n\t\t\t\tif(data) {\n\t\t\t\t\t$tw.crypto.setPassword(data.password);\n\t\t\t\t}\n\t\t\t\treturn true; // Get rid of the password prompt\n\t\t\t}\n\t\t});\n\t});\n\t$tw.rootWidget.addEventListener(\"tm-clear-password\",function(event) {\n\t\tif($tw.browser) {\n\t\t\tif(!confirm($tw.language.getString(\"Encryption/ConfirmClearPassword\"))) {\n\t\t\t\treturn;\n\t\t\t}\n\t\t}\n\t\t$tw.crypto.setPassword(null);\n\t});\n\t// Ensure that $:/isEncrypted is maintained properly\n\t$tw.wiki.addEventListener(\"change\",function(changes) {\n\t\tif($tw.utils.hop(changes,\"$:/isEncrypted\")) {\n\t\t\t$tw.crypto.updateCryptoStateTiddler();\n\t\t}\n\t});\n};\n\n})();\n",
"title": "$:/core/modules/startup/password.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/render.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/render.js\ntype: application/javascript\nmodule-type: startup\n\nTitle, stylesheet and page rendering\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"render\";\nexports.platforms = [\"browser\"];\nexports.after = [\"story\"];\nexports.synchronous = true;\n\n// Default story and history lists\nvar PAGE_TITLE_TITLE = \"$:/core/wiki/title\";\nvar PAGE_STYLESHEET_TITLE = \"$:/core/ui/PageStylesheet\";\nvar PAGE_TEMPLATE_TITLE = \"$:/core/ui/PageTemplate\";\n\n// Time (in ms) that we defer refreshing changes to draft tiddlers\nvar DRAFT_TIDDLER_TIMEOUT_TITLE = \"$:/config/Drafts/TypingTimeout\";\nvar DRAFT_TIDDLER_TIMEOUT = 400;\n\nexports.startup = function() {\n\t// Set up the title\n\t$tw.titleWidgetNode = $tw.wiki.makeTranscludeWidget(PAGE_TITLE_TITLE,{document: $tw.fakeDocument, parseAsInline: true});\n\t$tw.titleContainer = $tw.fakeDocument.createElement(\"div\");\n\t$tw.titleWidgetNode.render($tw.titleContainer,null);\n\tdocument.title = $tw.titleContainer.textContent;\n\t$tw.wiki.addEventListener(\"change\",function(changes) {\n\t\tif($tw.titleWidgetNode.refresh(changes,$tw.titleContainer,null)) {\n\t\t\tdocument.title = $tw.titleContainer.textContent;\n\t\t}\n\t});\n\t// Set up the styles\n\t$tw.styleWidgetNode = $tw.wiki.makeTranscludeWidget(PAGE_STYLESHEET_TITLE,{document: $tw.fakeDocument});\n\t$tw.styleContainer = $tw.fakeDocument.createElement(\"style\");\n\t$tw.styleWidgetNode.render($tw.styleContainer,null);\n\t$tw.styleElement = document.createElement(\"style\");\n\t$tw.styleElement.innerHTML = $tw.styleContainer.textContent;\n\tdocument.head.insertBefore($tw.styleElement,document.head.firstChild);\n\t$tw.wiki.addEventListener(\"change\",$tw.perf.report(\"styleRefresh\",function(changes) {\n\t\tif($tw.styleWidgetNode.refresh(changes,$tw.styleContainer,null)) {\n\t\t\t$tw.styleElement.innerHTML = $tw.styleContainer.textContent;\n\t\t}\n\t}));\n\t// Display the $:/core/ui/PageTemplate tiddler to kick off the display\n\t$tw.perf.report(\"mainRender\",function() {\n\t\t$tw.pageWidgetNode = $tw.wiki.makeTranscludeWidget(PAGE_TEMPLATE_TITLE,{document: document, parentWidget: $tw.rootWidget});\n\t\t$tw.pageContainer = document.createElement(\"div\");\n\t\t$tw.utils.addClass($tw.pageContainer,\"tc-page-container-wrapper\");\n\t\tdocument.body.insertBefore($tw.pageContainer,document.body.firstChild);\n\t\t$tw.pageWidgetNode.render($tw.pageContainer,null);\n\t})();\n\t// Prepare refresh mechanism\n\tvar deferredChanges = Object.create(null),\n\t\ttimerId;\n\tfunction refresh() {\n\t\t// Process the refresh\n\t\t$tw.pageWidgetNode.refresh(deferredChanges);\n\t\tdeferredChanges = Object.create(null);\n\t}\n\t// Add the change event handler\n\t$tw.wiki.addEventListener(\"change\",$tw.perf.report(\"mainRefresh\",function(changes) {\n\t\t// Check if only drafts have changed\n\t\tvar onlyDraftsHaveChanged = true;\n\t\tfor(var title in changes) {\n\t\t\tvar tiddler = $tw.wiki.getTiddler(title);\n\t\t\tif(!tiddler || !tiddler.hasField(\"draft.of\")) {\n\t\t\t\tonlyDraftsHaveChanged = false;\n\t\t\t}\n\t\t}\n\t\t// Defer the change if only drafts have changed\n\t\tif(timerId) {\n\t\t\tclearTimeout(timerId);\n\t\t}\n\t\ttimerId = null;\n\t\tif(onlyDraftsHaveChanged) {\n\t\t\tvar timeout = parseInt($tw.wiki.getTiddlerText(DRAFT_TIDDLER_TIMEOUT_TITLE,\"\"),10);\n\t\t\tif(isNaN(timeout)) {\n\t\t\t\ttimeout = DRAFT_TIDDLER_TIMEOUT;\n\t\t\t}\n\t\t\ttimerId = setTimeout(refresh,timeout);\n\t\t\t$tw.utils.extend(deferredChanges,changes);\n\t\t} else {\n\t\t\t$tw.utils.extend(deferredChanges,changes);\n\t\t\trefresh();\n\t\t}\n\t}));\n\t// Fix up the link between the root widget and the page container\n\t$tw.rootWidget.domNodes = [$tw.pageContainer];\n\t$tw.rootWidget.children = [$tw.pageWidgetNode];\n};\n\n})();\n",
"title": "$:/core/modules/startup/render.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/rootwidget.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/rootwidget.js\ntype: application/javascript\nmodule-type: startup\n\nSetup the root widget and the core root widget handlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"rootwidget\";\nexports.platforms = [\"browser\"];\nexports.after = [\"startup\"];\nexports.before = [\"story\"];\nexports.synchronous = true;\n\nexports.startup = function() {\n\t// Install the modal message mechanism\n\t$tw.modal = new $tw.utils.Modal($tw.wiki);\n\t$tw.rootWidget.addEventListener(\"tm-modal\",function(event) {\n\t\t$tw.modal.display(event.param,{variables: event.paramObject});\n\t});\n\t// Install the notification mechanism\n\t$tw.notifier = new $tw.utils.Notifier($tw.wiki);\n\t$tw.rootWidget.addEventListener(\"tm-notify\",function(event) {\n\t\t$tw.notifier.display(event.param,{variables: event.paramObject});\n\t});\n\t// Install the scroller\n\t$tw.pageScroller = new $tw.utils.PageScroller();\n\t$tw.rootWidget.addEventListener(\"tm-scroll\",function(event) {\n\t\t$tw.pageScroller.handleEvent(event);\n\t});\n\tvar fullscreen = $tw.utils.getFullScreenApis();\n\tif(fullscreen) {\n\t\t$tw.rootWidget.addEventListener(\"tm-full-screen\",function(event) {\n\t\t\tif(document[fullscreen._fullscreenElement]) {\n\t\t\t\tdocument[fullscreen._exitFullscreen]();\n\t\t\t} else {\n\t\t\t\tdocument.documentElement[fullscreen._requestFullscreen](Element.ALLOW_KEYBOARD_INPUT);\n\t\t\t}\n\t\t});\n\t}\n\t// If we're being viewed on a data: URI then give instructions for how to save\n\tif(document.location.protocol === \"data:\") {\n\t\t$tw.rootWidget.dispatchEvent({\n\t\t\ttype: \"tm-modal\",\n\t\t\tparam: \"$:/language/Modals/SaveInstructions\"\n\t\t});\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/startup/rootwidget.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup.js": {
"text": "/*\\\ntitle: $:/core/modules/startup.js\ntype: application/javascript\nmodule-type: startup\n\nMiscellaneous startup logic for both the client and server.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"startup\";\nexports.after = [\"load-modules\"];\nexports.synchronous = true;\n\n// Set to `true` to enable performance instrumentation\nvar PERFORMANCE_INSTRUMENTATION_CONFIG_TITLE = \"$:/config/Performance/Instrumentation\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nexports.startup = function() {\n\tvar modules,n,m,f;\n\t// Minimal browser detection\n\tif($tw.browser) {\n\t\t$tw.browser.isIE = (/msie|trident/i.test(navigator.userAgent));\n\t\t$tw.browser.isFirefox = !!document.mozFullScreenEnabled;\n\t}\n\t// Platform detection\n\t$tw.platform = {};\n\tif($tw.browser) {\n\t\t$tw.platform.isMac = /Mac/.test(navigator.platform);\n\t\t$tw.platform.isWindows = /win/i.test(navigator.platform);\n\t\t$tw.platform.isLinux = /Linux/i.test(navigator.appVersion);\n\t} else {\n\t\tswitch(require(\"os\").platform()) {\n\t\t\tcase \"darwin\":\n\t\t\t\t$tw.platform.isMac = true;\n\t\t\t\tbreak;\n\t\t\tcase \"win32\":\n\t\t\t\t$tw.platform.isWindows = true;\n\t\t\t\tbreak;\n\t\t\tcase \"freebsd\":\n\t\t\t\t$tw.platform.isLinux = true;\n\t\t\t\tbreak;\n\t\t\tcase \"linux\":\n\t\t\t\t$tw.platform.isLinux = true;\n\t\t\t\tbreak;\n\t\t}\n\t}\n\t// Initialise version\n\t$tw.version = $tw.utils.extractVersionInfo();\n\t// Set up the performance framework\n\t$tw.perf = new $tw.Performance($tw.wiki.getTiddlerText(PERFORMANCE_INSTRUMENTATION_CONFIG_TITLE,\"no\") === \"yes\");\n\t// Kick off the language manager and switcher\n\t$tw.language = new $tw.Language();\n\t$tw.languageSwitcher = new $tw.PluginSwitcher({\n\t\twiki: $tw.wiki,\n\t\tpluginType: \"language\",\n\t\tcontrollerTitle: \"$:/language\",\n\t\tdefaultPlugins: [\n\t\t\t\"$:/languages/en-US\"\n\t\t]\n\t});\n\t// Kick off the theme manager\n\t$tw.themeManager = new $tw.PluginSwitcher({\n\t\twiki: $tw.wiki,\n\t\tpluginType: \"theme\",\n\t\tcontrollerTitle: \"$:/theme\",\n\t\tdefaultPlugins: [\n\t\t\t\"$:/themes/tiddlywiki/snowwhite\",\n\t\t\t\"$:/themes/tiddlywiki/vanilla\"\n\t\t]\n\t});\n\t// Kick off the keyboard manager\n\t$tw.keyboardManager = new $tw.KeyboardManager();\n\t// Clear outstanding tiddler store change events to avoid an unnecessary refresh cycle at startup\n\t$tw.wiki.clearTiddlerEventQueue();\n\t// Create a root widget for attaching event handlers. By using it as the parentWidget for another widget tree, one can reuse the event handlers\n\tif($tw.browser) {\n\t\t$tw.rootWidget = new widget.widget({\n\t\t\ttype: \"widget\",\n\t\t\tchildren: []\n\t\t},{\n\t\t\twiki: $tw.wiki,\n\t\t\tdocument: document\n\t\t});\n\t}\n\t// Find a working syncadaptor\n\t$tw.syncadaptor = undefined;\n\t$tw.modules.forEachModuleOfType(\"syncadaptor\",function(title,module) {\n\t\tif(!$tw.syncadaptor && module.adaptorClass) {\n\t\t\t$tw.syncadaptor = new module.adaptorClass({wiki: $tw.wiki});\n\t\t}\n\t});\n\t// Set up the syncer object if we've got a syncadaptor\n\tif($tw.syncadaptor) {\n\t\t$tw.syncer = new $tw.Syncer({wiki: $tw.wiki, syncadaptor: $tw.syncadaptor});\n\t} \n\t// Setup the saver handler\n\t$tw.saverHandler = new $tw.SaverHandler({wiki: $tw.wiki, dirtyTracking: !$tw.syncadaptor});\n\t// Host-specific startup\n\tif($tw.browser) {\n\t\t// Install the popup manager\n\t\t$tw.popup = new $tw.utils.Popup();\n\t\t// Install the animator\n\t\t$tw.anim = new $tw.utils.Animator();\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/startup.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/story.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/story.js\ntype: application/javascript\nmodule-type: startup\n\nLoad core modules\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"story\";\nexports.after = [\"startup\"];\nexports.synchronous = true;\n\n// Default story and history lists\nvar DEFAULT_STORY_TITLE = \"$:/StoryList\";\nvar DEFAULT_HISTORY_TITLE = \"$:/HistoryList\";\n\n// Default tiddlers\nvar DEFAULT_TIDDLERS_TITLE = \"$:/DefaultTiddlers\";\n\n// Config\nvar CONFIG_UPDATE_ADDRESS_BAR = \"$:/config/Navigation/UpdateAddressBar\"; // Can be \"no\", \"permalink\", \"permaview\"\nvar CONFIG_UPDATE_HISTORY = \"$:/config/Navigation/UpdateHistory\"; // Can be \"yes\" or \"no\"\n\nexports.startup = function() {\n\t// Open startup tiddlers\n\topenStartupTiddlers();\n\tif($tw.browser) {\n\t\t// Set up location hash update\n\t\t$tw.wiki.addEventListener(\"change\",function(changes) {\n\t\t\tif($tw.utils.hop(changes,DEFAULT_STORY_TITLE) || $tw.utils.hop(changes,DEFAULT_HISTORY_TITLE)) {\n\t\t\t\tupdateLocationHash({\n\t\t\t\t\tupdateAddressBar: $tw.wiki.getTiddlerText(CONFIG_UPDATE_ADDRESS_BAR,\"permaview\").trim(),\n\t\t\t\t\tupdateHistory: $tw.wiki.getTiddlerText(CONFIG_UPDATE_HISTORY,\"no\").trim()\n\t\t\t\t});\n\t\t\t}\n\t\t});\n\t\t// Listen for changes to the browser location hash\n\t\twindow.addEventListener(\"hashchange\",function() {\n\t\t\tvar hash = $tw.utils.getLocationHash();\n\t\t\tif(hash !== $tw.locationHash) {\n\t\t\t\t$tw.locationHash = hash;\n\t\t\t\topenStartupTiddlers({defaultToCurrentStory: true});\n\t\t\t}\n\t\t},false);\n\t\t// Listen for the tm-browser-refresh message\n\t\t$tw.rootWidget.addEventListener(\"tm-browser-refresh\",function(event) {\n\t\t\twindow.location.reload(true);\n\t\t});\n\t\t// Listen for the tm-home message\n\t\t$tw.rootWidget.addEventListener(\"tm-home\",function(event) {\n\t\t\twindow.location.hash = \"\";\n\t\t\tvar storyFilter = $tw.wiki.getTiddlerText(DEFAULT_TIDDLERS_TITLE),\n\t\t\t\tstoryList = $tw.wiki.filterTiddlers(storyFilter);\n\t\t\t//invoke any hooks that might change the default story list\n\t\t\tstoryList = $tw.hooks.invokeHook(\"th-opening-default-tiddlers-list\",storyList);\n\t\t\t$tw.wiki.addTiddler({title: DEFAULT_STORY_TITLE, text: \"\", list: storyList},$tw.wiki.getModificationFields());\n\t\t\tif(storyList[0]) {\n\t\t\t\t$tw.wiki.addToHistory(storyList[0]);\t\t\t\t\n\t\t\t}\n\t\t});\n\t\t// Listen for the tm-permalink message\n\t\t$tw.rootWidget.addEventListener(\"tm-permalink\",function(event) {\n\t\t\tupdateLocationHash({\n\t\t\t\tupdateAddressBar: \"permalink\",\n\t\t\t\tupdateHistory: $tw.wiki.getTiddlerText(CONFIG_UPDATE_HISTORY,\"no\").trim(),\n\t\t\t\ttargetTiddler: event.param || event.tiddlerTitle\n\t\t\t});\n\t\t});\n\t\t// Listen for the tm-permaview message\n\t\t$tw.rootWidget.addEventListener(\"tm-permaview\",function(event) {\n\t\t\tupdateLocationHash({\n\t\t\t\tupdateAddressBar: \"permaview\",\n\t\t\t\tupdateHistory: $tw.wiki.getTiddlerText(CONFIG_UPDATE_HISTORY,\"no\").trim(),\n\t\t\t\ttargetTiddler: event.param || event.tiddlerTitle\n\t\t\t});\n\t\t});\n\t}\n};\n\n/*\nProcess the location hash to open the specified tiddlers. Options:\ndefaultToCurrentStory: If true, the current story is retained as the default, instead of opening the default tiddlers\n*/\nfunction openStartupTiddlers(options) {\n\toptions = options || {};\n\t// Work out the target tiddler and the story filter. \"null\" means \"unspecified\"\n\tvar target = null,\n\t\tstoryFilter = null;\n\tif($tw.locationHash.length > 1) {\n\t\tvar hash = $tw.locationHash.substr(1),\n\t\t\tsplit = hash.indexOf(\":\");\n\t\tif(split === -1) {\n\t\t\ttarget = decodeURIComponent(hash.trim());\n\t\t} else {\n\t\t\ttarget = decodeURIComponent(hash.substr(0,split).trim());\n\t\t\tstoryFilter = decodeURIComponent(hash.substr(split + 1).trim());\n\t\t}\n\t}\n\t// If the story wasn't specified use the current tiddlers or a blank story\n\tif(storyFilter === null) {\n\t\tif(options.defaultToCurrentStory) {\n\t\t\tvar currStoryList = $tw.wiki.getTiddlerList(DEFAULT_STORY_TITLE);\n\t\t\tstoryFilter = $tw.utils.stringifyList(currStoryList);\n\t\t} else {\n\t\t\tif(target && target !== \"\") {\n\t\t\t\tstoryFilter = \"\";\n\t\t\t} else {\n\t\t\t\tstoryFilter = $tw.wiki.getTiddlerText(DEFAULT_TIDDLERS_TITLE);\n\t\t\t}\n\t\t}\n\t}\n\t// Process the story filter to get the story list\n\tvar storyList = $tw.wiki.filterTiddlers(storyFilter);\n\t// Invoke any hooks that want to change the default story list\n\tstoryList = $tw.hooks.invokeHook(\"th-opening-default-tiddlers-list\",storyList);\n\t// If the target tiddler isn't included then splice it in at the top\n\tif(target && storyList.indexOf(target) === -1) {\n\t\tstoryList.unshift(target);\n\t}\n\t// Save the story list\n\t$tw.wiki.addTiddler({title: DEFAULT_STORY_TITLE, text: \"\", list: storyList},$tw.wiki.getModificationFields());\n\t// If a target tiddler was specified add it to the history stack\n\tif(target && target !== \"\") {\n\t\t// The target tiddler doesn't need double square brackets, but we'll silently remove them if they're present\n\t\tif(target.indexOf(\"[[\") === 0 && target.substr(-2) === \"]]\") {\n\t\t\ttarget = target.substr(2,target.length - 4);\n\t\t}\n\t\t$tw.wiki.addToHistory(target);\n\t} else if(storyList.length > 0) {\n\t\t$tw.wiki.addToHistory(storyList[0]);\n\t}\n}\n\n/*\noptions: See below\noptions.updateAddressBar: \"permalink\", \"permaview\" or \"no\" (defaults to \"permaview\")\noptions.updateHistory: \"yes\" or \"no\" (defaults to \"no\")\noptions.targetTiddler: optional title of target tiddler for permalink\n*/\nfunction updateLocationHash(options) {\n\tif(options.updateAddressBar !== \"no\") {\n\t\t// Get the story and the history stack\n\t\tvar storyList = $tw.wiki.getTiddlerList(DEFAULT_STORY_TITLE),\n\t\t\thistoryList = $tw.wiki.getTiddlerData(DEFAULT_HISTORY_TITLE,[]),\n\t\t\ttargetTiddler = \"\";\n\t\tif(options.targetTiddler) {\n\t\t\ttargetTiddler = options.targetTiddler;\n\t\t} else {\n\t\t\t// The target tiddler is the one at the top of the stack\n\t\t\tif(historyList.length > 0) {\n\t\t\t\ttargetTiddler = historyList[historyList.length-1].title;\n\t\t\t}\n\t\t\t// Blank the target tiddler if it isn't present in the story\n\t\t\tif(storyList.indexOf(targetTiddler) === -1) {\n\t\t\t\ttargetTiddler = \"\";\n\t\t\t}\n\t\t}\n\t\t// Assemble the location hash\n\t\tif(options.updateAddressBar === \"permalink\") {\n\t\t\t$tw.locationHash = \"#\" + encodeURIComponent(targetTiddler);\n\t\t} else {\n\t\t\t$tw.locationHash = \"#\" + encodeURIComponent(targetTiddler) + \":\" + encodeURIComponent($tw.utils.stringifyList(storyList));\n\t\t}\n\t\t// Only change the location hash if we must, thus avoiding unnecessary onhashchange events\n\t\tif($tw.utils.getLocationHash() !== $tw.locationHash) {\n\t\t\tif(options.updateHistory === \"yes\") {\n\t\t\t\t// Assign the location hash so that history is updated\n\t\t\t\twindow.location.hash = $tw.locationHash;\n\t\t\t} else {\n\t\t\t\t// We use replace so that browser history isn't affected\n\t\t\t\twindow.location.replace(window.location.toString().split(\"#\")[0] + $tw.locationHash);\n\t\t\t}\n\t\t}\n\t}\n}\n\n})();\n",
"title": "$:/core/modules/startup/story.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/startup/windows.js": {
"text": "/*\\\ntitle: $:/core/modules/startup/windows.js\ntype: application/javascript\nmodule-type: startup\n\nSetup root widget handlers for the messages concerned with opening external browser windows\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"windows\";\nexports.platforms = [\"browser\"];\nexports.after = [\"startup\"];\nexports.synchronous = true;\n\n// Global to keep track of open windows (hashmap by title)\nvar windows = {};\n\nexports.startup = function() {\n\t// Handle open window message\n\t$tw.rootWidget.addEventListener(\"tm-open-window\",function(event) {\n\t\t// Get the parameters\n\t\tvar refreshHandler,\n\t\t\ttitle = event.param || event.tiddlerTitle,\n\t\t\tparamObject = event.paramObject || {},\n\t\t\ttemplate = paramObject.template || \"$:/core/templates/single.tiddler.window\",\n\t\t\twidth = paramObject.width || \"700\",\n\t\t\theight = paramObject.height || \"600\",\n\t\t\tvariables = $tw.utils.extend({},paramObject,{currentTiddler: title});\n\t\t// Open the window\n\t\tvar srcWindow = window.open(\"\",\"external-\" + title,\"scrollbars,width=\" + width + \",height=\" + height),\n\t\t\tsrcDocument = srcWindow.document;\n\t\twindows[title] = srcWindow;\n\t\t// Check for reopening the same window\n\t\tif(srcWindow.haveInitialisedWindow) {\n\t\t\treturn;\n\t\t}\n\t\t// Initialise the document\n\t\tsrcDocument.write(\"<html><head></head><body class='tc-body tc-single-tiddler-window'></body></html>\");\n\t\tsrcDocument.close();\n\t\tsrcDocument.title = title;\n\t\tsrcWindow.addEventListener(\"beforeunload\",function(event) {\n\t\t\tdelete windows[title];\n\t\t\t$tw.wiki.removeEventListener(\"change\",refreshHandler);\n\t\t},false);\n\t\t// Set up the styles\n\t\tvar styleWidgetNode = $tw.wiki.makeTranscludeWidget(\"$:/core/ui/PageStylesheet\",{document: $tw.fakeDocument, variables: variables}),\n\t\t\tstyleContainer = $tw.fakeDocument.createElement(\"style\");\n\t\tstyleWidgetNode.render(styleContainer,null);\n\t\tvar styleElement = srcDocument.createElement(\"style\");\n\t\tstyleElement.innerHTML = styleContainer.textContent;\n\t\tsrcDocument.head.insertBefore(styleElement,srcDocument.head.firstChild);\n\t\t// Render the text of the tiddler\n\t\tvar parser = $tw.wiki.parseTiddler(template),\n\t\t\twidgetNode = $tw.wiki.makeWidget(parser,{document: srcDocument, parentWidget: $tw.rootWidget, variables: variables});\n\t\twidgetNode.render(srcDocument.body,srcDocument.body.firstChild);\n\t\t// Function to handle refreshes\n\t\trefreshHandler = function(changes) {\n\t\t\tif(styleWidgetNode.refresh(changes,styleContainer,null)) {\n\t\t\t\tstyleElement.innerHTML = styleContainer.textContent;\n\t\t\t}\n\t\t\twidgetNode.refresh(changes);\n\t\t};\n\t\t$tw.wiki.addEventListener(\"change\",refreshHandler);\n\t\tsrcWindow.haveInitialisedWindow = true;\n\t});\n\t// Close open windows when unloading main window\n\t$tw.addUnloadTask(function() {\n\t\t$tw.utils.each(windows,function(win) {\n\t\t\twin.close();\n\t\t});\n\t});\n\n};\n\n})();\n",
"title": "$:/core/modules/startup/windows.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/core/modules/story.js": {
"text": "/*\\\ntitle: $:/core/modules/story.js\ntype: application/javascript\nmodule-type: global\n\nLightweight object for managing interactions with the story and history lists.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nConstruct Story object with options:\nwiki: reference to wiki object to use to resolve tiddler titles\nstoryTitle: title of story list tiddler\nhistoryTitle: title of history list tiddler\n*/\nfunction Story(options) {\n\toptions = options || {};\n\tthis.wiki = options.wiki || $tw.wiki;\n\tthis.storyTitle = options.storyTitle || \"$:/StoryList\";\n\tthis.historyTitle = options.historyTitle || \"$:/HistoryList\";\n};\n\nStory.prototype.navigateTiddler = function(navigateTo,navigateFromTitle,navigateFromClientRect) {\n\tthis.addToStory(navigateTo,navigateFromTitle);\n\tthis.addToHistory(navigateTo,navigateFromClientRect);\n};\n\nStory.prototype.getStoryList = function() {\n\treturn this.wiki.getTiddlerList(this.storyTitle) || [];\n};\n\nStory.prototype.addToStory = function(navigateTo,navigateFromTitle,options) {\n\toptions = options || {};\n\tvar storyList = this.getStoryList();\n\t// See if the tiddler is already there\n\tvar slot = storyList.indexOf(navigateTo);\n\t// Quit if it already exists in the story river\n\tif(slot >= 0) {\n\t\treturn;\n\t}\n\t// First we try to find the position of the story element we navigated from\n\tvar fromIndex = storyList.indexOf(navigateFromTitle);\n\tif(fromIndex >= 0) {\n\t\t// The tiddler is added from inside the river\n\t\t// Determine where to insert the tiddler; Fallback is \"below\"\n\t\tswitch(options.openLinkFromInsideRiver) {\n\t\t\tcase \"top\":\n\t\t\t\tslot = 0;\n\t\t\t\tbreak;\n\t\t\tcase \"bottom\":\n\t\t\t\tslot = storyList.length;\n\t\t\t\tbreak;\n\t\t\tcase \"above\":\n\t\t\t\tslot = fromIndex;\n\t\t\t\tbreak;\n\t\t\tcase \"below\": // Intentional fall-through\n\t\t\tdefault:\n\t\t\t\tslot = fromIndex + 1;\n\t\t\t\tbreak;\n\t\t}\n\t} else {\n\t\t// The tiddler is opened from outside the river. Determine where to insert the tiddler; default is \"top\"\n\t\tif(options.openLinkFromOutsideRiver === \"bottom\") {\n\t\t\t// Insert at bottom\n\t\t\tslot = storyList.length;\n\t\t} else {\n\t\t\t// Insert at top\n\t\t\tslot = 0;\n\t\t}\n\t}\n\t// Add the tiddler\n\tstoryList.splice(slot,0,navigateTo);\n\t// Save the story\n\tthis.saveStoryList(storyList);\n};\n\nStory.prototype.saveStoryList = function(storyList) {\n\tvar storyTiddler = this.wiki.getTiddler(this.storyTitle);\n\tthis.wiki.addTiddler(new $tw.Tiddler(\n\t\tthis.wiki.getCreationFields(),\n\t\t{title: this.storyTitle},\n\t\tstoryTiddler,\n\t\t{list: storyList},\n\t\tthis.wiki.getModificationFields()\n\t));\n};\n\nStory.prototype.addToHistory = function(navigateTo,navigateFromClientRect) {\n\tvar titles = $tw.utils.isArray(navigateTo) ? navigateTo : [navigateTo];\n\t// Add a new record to the top of the history stack\n\tvar historyList = this.wiki.getTiddlerData(this.historyTitle,[]);\n\t$tw.utils.each(titles,function(title) {\n\t\thistoryList.push({title: title, fromPageRect: navigateFromClientRect});\n\t});\n\tthis.wiki.setTiddlerData(this.historyTitle,historyList,{\"current-tiddler\": titles[titles.length-1]});\n};\n\nStory.prototype.storyCloseTiddler = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storyCloseAllTiddlers = function() {\n// TBD\n};\n\nStory.prototype.storyCloseOtherTiddlers = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storyEditTiddler = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storyDeleteTiddler = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storySaveTiddler = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storyCancelTiddler = function(targetTitle) {\n// TBD\n};\n\nStory.prototype.storyNewTiddler = function(targetTitle) {\n// TBD\n};\n\nexports.Story = Story;\n\n\n})();\n",
"title": "$:/core/modules/story.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/storyviews/classic.js": {
"text": "/*\\\ntitle: $:/core/modules/storyviews/classic.js\ntype: application/javascript\nmodule-type: storyview\n\nViews the story as a linear sequence\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar easing = \"cubic-bezier(0.645, 0.045, 0.355, 1)\"; // From http://easings.net/#easeInOutCubic\n\nvar ClassicStoryView = function(listWidget) {\n\tthis.listWidget = listWidget;\n};\n\nClassicStoryView.prototype.navigateTo = function(historyInfo) {\n\tvar listElementIndex = this.listWidget.findListItem(0,historyInfo.title);\n\tif(listElementIndex === undefined) {\n\t\treturn;\n\t}\n\tvar listItemWidget = this.listWidget.children[listElementIndex],\n\t\ttargetElement = listItemWidget.findFirstDomNode();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Scroll the node into view\n\tthis.listWidget.dispatchEvent({type: \"tm-scroll\", target: targetElement});\n};\n\nClassicStoryView.prototype.insert = function(widget) {\n\tvar targetElement = widget.findFirstDomNode(),\n\t\tduration = $tw.utils.getAnimationDuration();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Get the current height of the tiddler\n\tvar computedStyle = window.getComputedStyle(targetElement),\n\t\tcurrMarginBottom = parseInt(computedStyle.marginBottom,10),\n\t\tcurrMarginTop = parseInt(computedStyle.marginTop,10),\n\t\tcurrHeight = targetElement.offsetHeight + currMarginTop;\n\t// Reset the margin once the transition is over\n\tsetTimeout(function() {\n\t\t$tw.utils.setStyle(targetElement,[\n\t\t\t{transition: \"none\"},\n\t\t\t{marginBottom: \"\"}\n\t\t]);\n\t},duration);\n\t// Set up the initial position of the element\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: \"none\"},\n\t\t{marginBottom: (-currHeight) + \"px\"},\n\t\t{opacity: \"0.0\"}\n\t]);\n\t$tw.utils.forceLayout(targetElement);\n\t// Transition to the final position\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: \"opacity \" + duration + \"ms \" + easing + \", \" +\n\t\t\t\t\t\"margin-bottom \" + duration + \"ms \" + easing},\n\t\t{marginBottom: currMarginBottom + \"px\"},\n\t\t{opacity: \"1.0\"}\n\t]);\n};\n\nClassicStoryView.prototype.remove = function(widget) {\n\tvar targetElement = widget.findFirstDomNode(),\n\t\tduration = $tw.utils.getAnimationDuration(),\n\t\tremoveElement = function() {\n\t\t\twidget.removeChildDomNodes();\n\t\t};\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\tremoveElement();\n\t\treturn;\n\t}\n\t// Get the current height of the tiddler\n\tvar currWidth = targetElement.offsetWidth,\n\t\tcomputedStyle = window.getComputedStyle(targetElement),\n\t\tcurrMarginBottom = parseInt(computedStyle.marginBottom,10),\n\t\tcurrMarginTop = parseInt(computedStyle.marginTop,10),\n\t\tcurrHeight = targetElement.offsetHeight + currMarginTop;\n\t// Remove the dom nodes of the widget at the end of the transition\n\tsetTimeout(removeElement,duration);\n\t// Animate the closure\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: \"none\"},\n\t\t{transform: \"translateX(0px)\"},\n\t\t{marginBottom: currMarginBottom + \"px\"},\n\t\t{opacity: \"1.0\"}\n\t]);\n\t$tw.utils.forceLayout(targetElement);\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms \" + easing + \", \" +\n\t\t\t\t\t\"opacity \" + duration + \"ms \" + easing + \", \" +\n\t\t\t\t\t\"margin-bottom \" + duration + \"ms \" + easing},\n\t\t{transform: \"translateX(-\" + currWidth + \"px)\"},\n\t\t{marginBottom: (-currHeight) + \"px\"},\n\t\t{opacity: \"0.0\"}\n\t]);\n};\n\nexports.classic = ClassicStoryView;\n\n})();",
"title": "$:/core/modules/storyviews/classic.js",
"type": "application/javascript",
"module-type": "storyview"
},
"$:/core/modules/storyviews/pop.js": {
"text": "/*\\\ntitle: $:/core/modules/storyviews/pop.js\ntype: application/javascript\nmodule-type: storyview\n\nAnimates list insertions and removals\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar PopStoryView = function(listWidget) {\n\tthis.listWidget = listWidget;\n};\n\nPopStoryView.prototype.navigateTo = function(historyInfo) {\n\tvar listElementIndex = this.listWidget.findListItem(0,historyInfo.title);\n\tif(listElementIndex === undefined) {\n\t\treturn;\n\t}\n\tvar listItemWidget = this.listWidget.children[listElementIndex],\n\t\ttargetElement = listItemWidget.findFirstDomNode();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Scroll the node into view\n\tthis.listWidget.dispatchEvent({type: \"tm-scroll\", target: targetElement});\n};\n\nPopStoryView.prototype.insert = function(widget) {\n\tvar targetElement = widget.findFirstDomNode(),\n\t\tduration = $tw.utils.getAnimationDuration();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Reset once the transition is over\n\tsetTimeout(function() {\n\t\t$tw.utils.setStyle(targetElement,[\n\t\t\t{transition: \"none\"},\n\t\t\t{transform: \"none\"}\n\t\t]);\n\t},duration);\n\t// Set up the initial position of the element\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: \"none\"},\n\t\t{transform: \"scale(2)\"},\n\t\t{opacity: \"0.0\"}\n\t]);\n\t$tw.utils.forceLayout(targetElement);\n\t// Transition to the final position\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"opacity \" + duration + \"ms ease-in-out\"},\n\t\t{transform: \"scale(1)\"},\n\t\t{opacity: \"1.0\"}\n\t]);\n};\n\nPopStoryView.prototype.remove = function(widget) {\n\tvar targetElement = widget.findFirstDomNode(),\n\t\tduration = $tw.utils.getAnimationDuration(),\n\t\tremoveElement = function() {\n\t\t\tif(targetElement.parentNode) {\n\t\t\t\twidget.removeChildDomNodes();\n\t\t\t}\n\t\t};\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\tremoveElement();\n\t\treturn;\n\t}\n\t// Remove the element at the end of the transition\n\tsetTimeout(removeElement,duration);\n\t// Animate the closure\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: \"none\"},\n\t\t{transform: \"scale(1)\"},\n\t\t{opacity: \"1.0\"}\n\t]);\n\t$tw.utils.forceLayout(targetElement);\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"opacity \" + duration + \"ms ease-in-out\"},\n\t\t{transform: \"scale(0.1)\"},\n\t\t{opacity: \"0.0\"}\n\t]);\n};\n\nexports.pop = PopStoryView;\n\n})();\n",
"title": "$:/core/modules/storyviews/pop.js",
"type": "application/javascript",
"module-type": "storyview"
},
"$:/core/modules/storyviews/zoomin.js": {
"text": "/*\\\ntitle: $:/core/modules/storyviews/zoomin.js\ntype: application/javascript\nmodule-type: storyview\n\nZooms between individual tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar easing = \"cubic-bezier(0.645, 0.045, 0.355, 1)\"; // From http://easings.net/#easeInOutCubic\n\nvar ZoominListView = function(listWidget) {\n\tvar self = this;\n\tthis.listWidget = listWidget;\n\t// Get the index of the tiddler that is at the top of the history\n\tvar history = this.listWidget.wiki.getTiddlerDataCached(this.listWidget.historyTitle,[]),\n\t\ttargetTiddler;\n\tif(history.length > 0) {\n\t\ttargetTiddler = history[history.length-1].title;\n\t}\n\t// Make all the tiddlers position absolute, and hide all but the top (or first) one\n\t$tw.utils.each(this.listWidget.children,function(itemWidget,index) {\n\t\tvar domNode = itemWidget.findFirstDomNode();\n\t\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\t\tif(!(domNode instanceof Element)) {\n\t\t\treturn;\n\t\t}\n\t\tif((targetTiddler && targetTiddler !== itemWidget.parseTreeNode.itemTitle) || (!targetTiddler && index)) {\n\t\t\tdomNode.style.display = \"none\";\n\t\t} else {\n\t\t\tself.currentTiddlerDomNode = domNode;\n\t\t}\n\t\t$tw.utils.addClass(domNode,\"tc-storyview-zoomin-tiddler\");\n\t});\n};\n\nZoominListView.prototype.navigateTo = function(historyInfo) {\n\tvar duration = $tw.utils.getAnimationDuration(),\n\t\tlistElementIndex = this.listWidget.findListItem(0,historyInfo.title);\n\tif(listElementIndex === undefined) {\n\t\treturn;\n\t}\n\tvar listItemWidget = this.listWidget.children[listElementIndex],\n\t\ttargetElement = listItemWidget.findFirstDomNode();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Make the new tiddler be position absolute and visible so that we can measure it\n\t$tw.utils.addClass(targetElement,\"tc-storyview-zoomin-tiddler\");\n\t$tw.utils.setStyle(targetElement,[\n\t\t{display: \"block\"},\n\t\t{transformOrigin: \"0 0\"},\n\t\t{transform: \"translateX(0px) translateY(0px) scale(1)\"},\n\t\t{transition: \"none\"},\n\t\t{opacity: \"0.0\"}\n\t]);\n\t// Get the position of the source node, or use the centre of the window as the source position\n\tvar sourceBounds = historyInfo.fromPageRect || {\n\t\t\tleft: window.innerWidth/2 - 2,\n\t\t\ttop: window.innerHeight/2 - 2,\n\t\t\twidth: window.innerWidth/8,\n\t\t\theight: window.innerHeight/8\n\t\t};\n\t// Try to find the title node in the target tiddler\n\tvar titleDomNode = findTitleDomNode(listItemWidget) || listItemWidget.findFirstDomNode(),\n\t\tzoomBounds = titleDomNode.getBoundingClientRect();\n\t// Compute the transform for the target tiddler to make the title lie over the source rectange\n\tvar targetBounds = targetElement.getBoundingClientRect(),\n\t\tscale = sourceBounds.width / zoomBounds.width,\n\t\tx = sourceBounds.left - targetBounds.left - (zoomBounds.left - targetBounds.left) * scale,\n\t\ty = sourceBounds.top - targetBounds.top - (zoomBounds.top - targetBounds.top) * scale;\n\t// Transform the target tiddler to its starting position\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transform: \"translateX(\" + x + \"px) translateY(\" + y + \"px) scale(\" + scale + \")\"}\n\t]);\n\t// Force layout\n\t$tw.utils.forceLayout(targetElement);\n\t// Apply the ending transitions with a timeout to ensure that the previously applied transformations are applied first\n\tvar self = this,\n\t\tprevCurrentTiddler = this.currentTiddlerDomNode;\n\tthis.currentTiddlerDomNode = targetElement;\n\t// Transform the target tiddler to its natural size\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms \" + easing + \", opacity \" + duration + \"ms \" + easing},\n\t\t{opacity: \"1.0\"},\n\t\t{transform: \"translateX(0px) translateY(0px) scale(1)\"},\n\t\t{zIndex: \"500\"},\n\t]);\n\t// Transform the previous tiddler out of the way and then hide it\n\tif(prevCurrentTiddler && prevCurrentTiddler !== targetElement) {\n\t\tscale = zoomBounds.width / sourceBounds.width;\n\t\tx = zoomBounds.left - targetBounds.left - (sourceBounds.left - targetBounds.left) * scale;\n\t\ty = zoomBounds.top - targetBounds.top - (sourceBounds.top - targetBounds.top) * scale;\n\t\t$tw.utils.setStyle(prevCurrentTiddler,[\n\t\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms \" + easing + \", opacity \" + duration + \"ms \" + easing},\n\t\t\t{opacity: \"0.0\"},\n\t\t\t{transformOrigin: \"0 0\"},\n\t\t\t{transform: \"translateX(\" + x + \"px) translateY(\" + y + \"px) scale(\" + scale + \")\"},\n\t\t\t{zIndex: \"0\"}\n\t\t]);\n\t\t// Hide the tiddler when the transition has finished\n\t\tsetTimeout(function() {\n\t\t\tif(self.currentTiddlerDomNode !== prevCurrentTiddler) {\n\t\t\t\tprevCurrentTiddler.style.display = \"none\";\n\t\t\t}\n\t\t},duration);\n\t}\n\t// Scroll the target into view\n//\t$tw.pageScroller.scrollIntoView(targetElement);\n};\n\n/*\nFind the first child DOM node of a widget that has the class \"tc-title\"\n*/\nfunction findTitleDomNode(widget,targetClass) {\n\ttargetClass = targetClass || \"tc-title\";\n\tvar domNode = widget.findFirstDomNode();\n\tif(domNode && domNode.querySelector) {\n\t\treturn domNode.querySelector(\".\" + targetClass);\n\t}\n\treturn null;\n}\n\nZoominListView.prototype.insert = function(widget) {\n\tvar targetElement = widget.findFirstDomNode();\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\treturn;\n\t}\n\t// Make the newly inserted node position absolute and hidden\n\t$tw.utils.addClass(targetElement,\"tc-storyview-zoomin-tiddler\");\n\t$tw.utils.setStyle(targetElement,[\n\t\t{display: \"none\"}\n\t]);\n};\n\nZoominListView.prototype.remove = function(widget) {\n\tvar targetElement = widget.findFirstDomNode(),\n\t\tduration = $tw.utils.getAnimationDuration(),\n\t\tremoveElement = function() {\n\t\t\twidget.removeChildDomNodes();\n\t\t};\n\t// Abandon if the list entry isn't a DOM element (it might be a text node)\n\tif(!(targetElement instanceof Element)) {\n\t\tremoveElement();\n\t\treturn;\n\t}\n\t// Abandon if hidden\n\tif(targetElement.style.display != \"block\" ) {\n\t\tremoveElement();\n\t\treturn;\n\t}\n\t// Set up the tiddler that is being closed\n\t$tw.utils.addClass(targetElement,\"tc-storyview-zoomin-tiddler\");\n\t$tw.utils.setStyle(targetElement,[\n\t\t{display: \"block\"},\n\t\t{transformOrigin: \"50% 50%\"},\n\t\t{transform: \"translateX(0px) translateY(0px) scale(1)\"},\n\t\t{transition: \"none\"},\n\t\t{zIndex: \"0\"}\n\t]);\n\t// We'll move back to the previous or next element in the story\n\tvar toWidget = widget.previousSibling();\n\tif(!toWidget) {\n\t\ttoWidget = widget.nextSibling();\n\t}\n\tvar toWidgetDomNode = toWidget && toWidget.findFirstDomNode();\n\t// Set up the tiddler we're moving back in\n\tif(toWidgetDomNode) {\n\t\t$tw.utils.addClass(toWidgetDomNode,\"tc-storyview-zoomin-tiddler\");\n\t\t$tw.utils.setStyle(toWidgetDomNode,[\n\t\t\t{display: \"block\"},\n\t\t\t{transformOrigin: \"50% 50%\"},\n\t\t\t{transform: \"translateX(0px) translateY(0px) scale(10)\"},\n\t\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms \" + easing + \", opacity \" + duration + \"ms \" + easing},\n\t\t\t{opacity: \"0\"},\n\t\t\t{zIndex: \"500\"}\n\t\t]);\n\t\tthis.currentTiddlerDomNode = toWidgetDomNode;\n\t}\n\t// Animate them both\n\t// Force layout\n\t$tw.utils.forceLayout(this.listWidget.parentDomNode);\n\t// First, the tiddler we're closing\n\t$tw.utils.setStyle(targetElement,[\n\t\t{transformOrigin: \"50% 50%\"},\n\t\t{transform: \"translateX(0px) translateY(0px) scale(0.1)\"},\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms \" + easing + \", opacity \" + duration + \"ms \" + easing},\n\t\t{opacity: \"0\"},\n\t\t{zIndex: \"0\"}\n\t]);\n\tsetTimeout(removeElement,duration);\n\t// Now the tiddler we're going back to\n\tif(toWidgetDomNode) {\n\t\t$tw.utils.setStyle(toWidgetDomNode,[\n\t\t\t{transform: \"translateX(0px) translateY(0px) scale(1)\"},\n\t\t\t{opacity: \"1\"}\n\t\t]);\n\t}\n\treturn true; // Indicate that we'll delete the DOM node\n};\n\nexports.zoomin = ZoominListView;\n\n})();\n",
"title": "$:/core/modules/storyviews/zoomin.js",
"type": "application/javascript",
"module-type": "storyview"
},
"$:/core/modules/syncer.js": {
"text": "/*\\\ntitle: $:/core/modules/syncer.js\ntype: application/javascript\nmodule-type: global\n\nThe syncer tracks changes to the store. If a syncadaptor is used then individual tiddlers are synchronised through it. If there is no syncadaptor then the entire wiki is saved via saver modules.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nInstantiate the syncer with the following options:\nsyncadaptor: reference to syncadaptor to be used\nwiki: wiki to be synced\n*/\nfunction Syncer(options) {\n\tvar self = this;\n\tthis.wiki = options.wiki;\n\tthis.syncadaptor = options.syncadaptor;\n\t// Make a logger\n\tthis.logger = new $tw.utils.Logger(\"syncer\" + ($tw.browser ? \"-browser\" : \"\") + ($tw.node ? \"-server\" : \"\"));\n\t// Compile the dirty tiddler filter\n\tthis.filterFn = this.wiki.compileFilter(this.wiki.getTiddlerText(this.titleSyncFilter));\n\t// Record information for known tiddlers\n\tthis.readTiddlerInfo();\n\t// Tasks are {type: \"load\"/\"save\"/\"delete\", title:, queueTime:, lastModificationTime:}\n\tthis.taskQueue = {}; // Hashmap of tasks yet to be performed\n\tthis.taskInProgress = {}; // Hash of tasks in progress\n\tthis.taskTimerId = null; // Timer for task dispatch\n\tthis.pollTimerId = null; // Timer for polling server\n\t// Listen out for changes to tiddlers\n\tthis.wiki.addEventListener(\"change\",function(changes) {\n\t\tself.syncToServer(changes);\n\t});\n\t// Browser event handlers\n\tif($tw.browser) {\n\t\t// Set up our beforeunload handler\n\t\t$tw.addUnloadTask(function(event) {\n\t\t\tvar confirmationMessage;\n\t\t\tif(self.isDirty()) {\n\t\t\t\tconfirmationMessage = $tw.language.getString(\"UnsavedChangesWarning\");\n\t\t\t\tevent.returnValue = confirmationMessage; // Gecko\n\t\t\t}\n\t\t\treturn confirmationMessage;\n\t\t});\n\t\t// Listen out for login/logout/refresh events in the browser\n\t\t$tw.rootWidget.addEventListener(\"tm-login\",function() {\n\t\t\tself.handleLoginEvent();\n\t\t});\n\t\t$tw.rootWidget.addEventListener(\"tm-logout\",function() {\n\t\t\tself.handleLogoutEvent();\n\t\t});\n\t\t$tw.rootWidget.addEventListener(\"tm-server-refresh\",function() {\n\t\t\tself.handleRefreshEvent();\n\t\t});\n\t}\n\t// Listen out for lazyLoad events\n\tthis.wiki.addEventListener(\"lazyLoad\",function(title) {\n\t\tself.handleLazyLoadEvent(title);\n\t});\n\t// Get the login status\n\tthis.getStatus(function(err,isLoggedIn) {\n\t\t// Do a sync from the server\n\t\tself.syncFromServer();\n\t});\n}\n\n/*\nConstants\n*/\nSyncer.prototype.titleIsLoggedIn = \"$:/status/IsLoggedIn\";\nSyncer.prototype.titleUserName = \"$:/status/UserName\";\nSyncer.prototype.titleSyncFilter = \"$:/config/SyncFilter\";\nSyncer.prototype.titleSavedNotification = \"$:/language/Notifications/Save/Done\";\nSyncer.prototype.taskTimerInterval = 1 * 1000; // Interval for sync timer\nSyncer.prototype.throttleInterval = 1 * 1000; // Defer saving tiddlers if they've changed in the last 1s...\nSyncer.prototype.fallbackInterval = 10 * 1000; // Unless the task is older than 10s\nSyncer.prototype.pollTimerInterval = 60 * 1000; // Interval for polling for changes from the adaptor\n\n\n/*\nRead (or re-read) the latest tiddler info from the store\n*/\nSyncer.prototype.readTiddlerInfo = function() {\n\t// Hashmap by title of {revision:,changeCount:,adaptorInfo:}\n\tthis.tiddlerInfo = {};\n\t// Record information for known tiddlers\n\tvar self = this,\n\t\ttiddlers = this.filterFn.call(this.wiki);\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar tiddler = self.wiki.getTiddler(title);\n\t\tself.tiddlerInfo[title] = {\n\t\t\trevision: tiddler.fields.revision,\n\t\t\tadaptorInfo: self.syncadaptor && self.syncadaptor.getTiddlerInfo(tiddler),\n\t\t\tchangeCount: self.wiki.getChangeCount(title),\n\t\t\thasBeenLazyLoaded: false\n\t\t};\n\t});\n};\n\n/*\nCreate an tiddlerInfo structure if it doesn't already exist\n*/\nSyncer.prototype.createTiddlerInfo = function(title) {\n\tif(!$tw.utils.hop(this.tiddlerInfo,title)) {\n\t\tthis.tiddlerInfo[title] = {\n\t\t\trevision: null,\n\t\t\tadaptorInfo: {},\n\t\t\tchangeCount: -1,\n\t\t\thasBeenLazyLoaded: false\n\t\t};\n\t}\n};\n\n/*\nChecks whether the wiki is dirty (ie the window shouldn't be closed)\n*/\nSyncer.prototype.isDirty = function() {\n\treturn (this.numTasksInQueue() > 0) || (this.numTasksInProgress() > 0);\n};\n\n/*\nUpdate the document body with the class \"tc-dirty\" if the wiki has unsaved/unsynced changes\n*/\nSyncer.prototype.updateDirtyStatus = function() {\n\tif($tw.browser) {\n\t\t$tw.utils.toggleClass(document.body,\"tc-dirty\",this.isDirty());\n\t}\n};\n\n/*\nSave an incoming tiddler in the store, and updates the associated tiddlerInfo\n*/\nSyncer.prototype.storeTiddler = function(tiddlerFields) {\n\t// Save the tiddler\n\tvar tiddler = new $tw.Tiddler(this.wiki.getTiddler(tiddlerFields.title),tiddlerFields);\n\tthis.wiki.addTiddler(tiddler);\n\t// Save the tiddler revision and changeCount details\n\tthis.tiddlerInfo[tiddlerFields.title] = {\n\t\trevision: tiddlerFields.revision,\n\t\tadaptorInfo: this.syncadaptor.getTiddlerInfo(tiddler),\n\t\tchangeCount: this.wiki.getChangeCount(tiddlerFields.title),\n\t\thasBeenLazyLoaded: true\n\t};\n};\n\nSyncer.prototype.getStatus = function(callback) {\n\tvar self = this;\n\t// Check if the adaptor supports getStatus()\n\tif(this.syncadaptor && this.syncadaptor.getStatus) {\n\t\t// Mark us as not logged in\n\t\tthis.wiki.addTiddler({title: this.titleIsLoggedIn,text: \"no\"});\n\t\t// Get login status\n\t\tthis.syncadaptor.getStatus(function(err,isLoggedIn,username) {\n\t\t\tif(err) {\n\t\t\t\tself.logger.alert(err);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t// Set the various status tiddlers\n\t\t\tself.wiki.addTiddler({title: self.titleIsLoggedIn,text: isLoggedIn ? \"yes\" : \"no\"});\n\t\t\tif(isLoggedIn) {\n\t\t\t\tself.wiki.addTiddler({title: self.titleUserName,text: username || \"\"});\n\t\t\t} else {\n\t\t\t\tself.wiki.deleteTiddler(self.titleUserName);\n\t\t\t}\n\t\t\t// Invoke the callback\n\t\t\tif(callback) {\n\t\t\t\tcallback(err,isLoggedIn,username);\n\t\t\t}\n\t\t});\n\t} else {\n\t\tcallback(null,true,\"UNAUTHENTICATED\");\n\t}\n};\n\n/*\nSynchronise from the server by reading the skinny tiddler list and queuing up loads for any tiddlers that we don't already have up to date\n*/\nSyncer.prototype.syncFromServer = function() {\n\tif(this.syncadaptor && this.syncadaptor.getSkinnyTiddlers) {\n\t\tthis.logger.log(\"Retrieving skinny tiddler list\");\n\t\tvar self = this;\n\t\tif(this.pollTimerId) {\n\t\t\tclearTimeout(this.pollTimerId);\n\t\t\tthis.pollTimerId = null;\n\t\t}\n\t\tthis.syncadaptor.getSkinnyTiddlers(function(err,tiddlers) {\n\t\t\t// Trigger the next sync\n\t\t\tself.pollTimerId = setTimeout(function() {\n\t\t\t\tself.pollTimerId = null;\n\t\t\t\tself.syncFromServer.call(self);\n\t\t\t},self.pollTimerInterval);\n\t\t\t// Check for errors\n\t\t\tif(err) {\n\t\t\t\tself.logger.alert($tw.language.getString(\"Error/RetrievingSkinny\") + \":\",err);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t// Process each incoming tiddler\n\t\t\tfor(var t=0; t<tiddlers.length; t++) {\n\t\t\t\t// Get the incoming tiddler fields, and the existing tiddler\n\t\t\t\tvar tiddlerFields = tiddlers[t],\n\t\t\t\t\tincomingRevision = tiddlerFields.revision + \"\",\n\t\t\t\t\ttiddler = self.wiki.getTiddler(tiddlerFields.title),\n\t\t\t\t\ttiddlerInfo = self.tiddlerInfo[tiddlerFields.title],\n\t\t\t\t\tcurrRevision = tiddlerInfo ? tiddlerInfo.revision : null;\n\t\t\t\t// Ignore the incoming tiddler if it's the same as the revision we've already got\n\t\t\t\tif(currRevision !== incomingRevision) {\n\t\t\t\t\t// Do a full load if we've already got a fat version of the tiddler\n\t\t\t\t\tif(tiddler && tiddler.fields.text !== undefined) {\n\t\t\t\t\t\t// Do a full load of this tiddler\n\t\t\t\t\t\tself.enqueueSyncTask({\n\t\t\t\t\t\t\ttype: \"load\",\n\t\t\t\t\t\t\ttitle: tiddlerFields.title\n\t\t\t\t\t\t});\n\t\t\t\t\t} else {\n\t\t\t\t\t\t// Load the skinny version of the tiddler\n\t\t\t\t\t\tself.storeTiddler(tiddlerFields);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t}\n};\n\n/*\nSynchronise a set of changes to the server\n*/\nSyncer.prototype.syncToServer = function(changes) {\n\tvar self = this,\n\t\tnow = Date.now(),\n\t\tfilteredChanges = this.filterFn.call(this.wiki,function(callback) {\n\t\t\t$tw.utils.each(changes,function(change,title) {\n\t\t\t\tvar tiddler = self.wiki.getTiddler(title);\n\t\t\t\tcallback(tiddler,title);\n\t\t\t});\n\t\t});\n\t$tw.utils.each(changes,function(change,title,object) {\n\t\t// Process the change if it is a deletion of a tiddler we're already syncing, or is on the filtered change list\n\t\tif((change.deleted && $tw.utils.hop(self.tiddlerInfo,title)) || filteredChanges.indexOf(title) !== -1) {\n\t\t\t// Queue a task to sync this tiddler\n\t\t\tself.enqueueSyncTask({\n\t\t\t\ttype: change.deleted ? \"delete\" : \"save\",\n\t\t\t\ttitle: title\n\t\t\t});\n\t\t}\n\t});\n};\n\n/*\nLazily load a skinny tiddler if we can\n*/\nSyncer.prototype.handleLazyLoadEvent = function(title) {\n\t// Don't lazy load the same tiddler twice\n\tvar info = this.tiddlerInfo[title];\n\tif(!info || !info.hasBeenLazyLoaded) {\n\t\tthis.createTiddlerInfo(title);\n\t\tthis.tiddlerInfo[title].hasBeenLazyLoaded = true;\n\t\t// Queue up a sync task to load this tiddler\n\t\tthis.enqueueSyncTask({\n\t\t\ttype: \"load\",\n\t\t\ttitle: title\n\t\t});\t\t\n\t}\n};\n\n/*\nDispay a password prompt and allow the user to login\n*/\nSyncer.prototype.handleLoginEvent = function() {\n\tvar self = this;\n\tthis.getStatus(function(err,isLoggedIn,username) {\n\t\tif(!isLoggedIn) {\n\t\t\t$tw.passwordPrompt.createPrompt({\n\t\t\t\tserviceName: $tw.language.getString(\"LoginToTiddlySpace\"),\n\t\t\t\tcallback: function(data) {\n\t\t\t\t\tself.login(data.username,data.password,function(err,isLoggedIn) {\n\t\t\t\t\t\tself.syncFromServer();\n\t\t\t\t\t});\n\t\t\t\t\treturn true; // Get rid of the password prompt\n\t\t\t\t}\n\t\t\t});\n\t\t}\n\t});\n};\n\n/*\nAttempt to login to TiddlyWeb.\n\tusername: username\n\tpassword: password\n\tcallback: invoked with arguments (err,isLoggedIn)\n*/\nSyncer.prototype.login = function(username,password,callback) {\n\tthis.logger.log(\"Attempting to login as\",username);\n\tvar self = this;\n\tif(this.syncadaptor.login) {\n\t\tthis.syncadaptor.login(username,password,function(err) {\n\t\t\tif(err) {\n\t\t\t\treturn callback(err);\n\t\t\t}\n\t\t\tself.getStatus(function(err,isLoggedIn,username) {\n\t\t\t\tif(callback) {\n\t\t\t\t\tcallback(null,isLoggedIn);\n\t\t\t\t}\n\t\t\t});\n\t\t});\n\t} else {\n\t\tcallback(null,true);\n\t}\n};\n\n/*\nAttempt to log out of TiddlyWeb\n*/\nSyncer.prototype.handleLogoutEvent = function() {\n\tthis.logger.log(\"Attempting to logout\");\n\tvar self = this;\n\tif(this.syncadaptor.logout) {\n\t\tthis.syncadaptor.logout(function(err) {\n\t\t\tif(err) {\n\t\t\t\tself.logger.alert(err);\n\t\t\t} else {\n\t\t\t\tself.getStatus();\n\t\t\t}\n\t\t});\n\t}\n};\n\n/*\nImmediately refresh from the server\n*/\nSyncer.prototype.handleRefreshEvent = function() {\n\tthis.syncFromServer();\n};\n\n/*\nQueue up a sync task. If there is already a pending task for the tiddler, just update the last modification time\n*/\nSyncer.prototype.enqueueSyncTask = function(task) {\n\tvar self = this,\n\t\tnow = Date.now();\n\t// Set the timestamps on this task\n\ttask.queueTime = now;\n\ttask.lastModificationTime = now;\n\t// Fill in some tiddlerInfo if the tiddler is one we haven't seen before\n\tthis.createTiddlerInfo(task.title);\n\t// Bail if this is a save and the tiddler is already at the changeCount that the server has\n\tif(task.type === \"save\" && this.wiki.getChangeCount(task.title) <= this.tiddlerInfo[task.title].changeCount) {\n\t\treturn;\n\t}\n\t// Check if this tiddler is already in the queue\n\tif($tw.utils.hop(this.taskQueue,task.title)) {\n\t\t// this.logger.log(\"Re-queueing up sync task with type:\",task.type,\"title:\",task.title);\n\t\tvar existingTask = this.taskQueue[task.title];\n\t\t// If so, just update the last modification time\n\t\texistingTask.lastModificationTime = task.lastModificationTime;\n\t\t// If the new task is a save then we upgrade the existing task to a save. Thus a pending load is turned into a save if the tiddler changes locally in the meantime. But a pending save is not modified to become a load\n\t\tif(task.type === \"save\" || task.type === \"delete\") {\n\t\t\texistingTask.type = task.type;\n\t\t}\n\t} else {\n\t\t// this.logger.log(\"Queuing up sync task with type:\",task.type,\"title:\",task.title);\n\t\t// If it is not in the queue, insert it\n\t\tthis.taskQueue[task.title] = task;\n\t\tthis.updateDirtyStatus();\n\t}\n\t// Process the queue\n\t$tw.utils.nextTick(function() {self.processTaskQueue.call(self);});\n};\n\n/*\nReturn the number of tasks in progress\n*/\nSyncer.prototype.numTasksInProgress = function() {\n\treturn $tw.utils.count(this.taskInProgress);\n};\n\n/*\nReturn the number of tasks in the queue\n*/\nSyncer.prototype.numTasksInQueue = function() {\n\treturn $tw.utils.count(this.taskQueue);\n};\n\n/*\nTrigger a timeout if one isn't already outstanding\n*/\nSyncer.prototype.triggerTimeout = function() {\n\tvar self = this;\n\tif(!this.taskTimerId) {\n\t\tthis.taskTimerId = setTimeout(function() {\n\t\t\tself.taskTimerId = null;\n\t\t\tself.processTaskQueue.call(self);\n\t\t},self.taskTimerInterval);\n\t}\n};\n\n/*\nProcess the task queue, performing the next task if appropriate\n*/\nSyncer.prototype.processTaskQueue = function() {\n\tvar self = this;\n\t// Only process a task if the sync adaptor is fully initialised and we're not already performing a task. If we are already performing a task then we'll dispatch the next one when it completes\n\tif(this.syncadaptor.isReady() && this.numTasksInProgress() === 0) {\n\t\t// Choose the next task to perform\n\t\tvar task = this.chooseNextTask();\n\t\t// Perform the task if we had one\n\t\tif(task) {\n\t\t\t// Remove the task from the queue and add it to the in progress list\n\t\t\tdelete this.taskQueue[task.title];\n\t\t\tthis.taskInProgress[task.title] = task;\n\t\t\tthis.updateDirtyStatus();\n\t\t\t// Dispatch the task\n\t\t\tthis.dispatchTask(task,function(err) {\n\t\t\t\tif(err) {\n\t\t\t\t\tself.logger.alert(\"Sync error while processing '\" + task.title + \"':\\n\" + err);\n\t\t\t\t}\n\t\t\t\t// Mark that this task is no longer in progress\n\t\t\t\tdelete self.taskInProgress[task.title];\n\t\t\t\tself.updateDirtyStatus();\n\t\t\t\t// Process the next task\n\t\t\t\tself.processTaskQueue.call(self);\n\t\t\t});\n\t\t} else {\n\t\t\t// Make sure we've set a time if there wasn't a task to perform, but we've still got tasks in the queue\n\t\t\tif(this.numTasksInQueue() > 0) {\n\t\t\t\tthis.triggerTimeout();\n\t\t\t}\n\t\t}\n\t}\n};\n\n/*\nChoose the next applicable task\n*/\nSyncer.prototype.chooseNextTask = function() {\n\tvar self = this,\n\t\tcandidateTask = null,\n\t\tnow = Date.now();\n\t// Select the best candidate task\n\t$tw.utils.each(this.taskQueue,function(task,title) {\n\t\t// Exclude the task if there's one of the same name in progress\n\t\tif($tw.utils.hop(self.taskInProgress,title)) {\n\t\t\treturn;\n\t\t}\n\t\t// Exclude the task if it is a save and the tiddler has been modified recently, but not hit the fallback time\n\t\tif(task.type === \"save\" && (now - task.lastModificationTime) < self.throttleInterval &&\n\t\t\t(now - task.queueTime) < self.fallbackInterval) {\n\t\t\treturn;\n\t\t}\n\t\t// Exclude the task if it is newer than the current best candidate\n\t\tif(candidateTask && candidateTask.queueTime < task.queueTime) {\n\t\t\treturn;\n\t\t}\n\t\t// Now this is our best candidate\n\t\tcandidateTask = task;\n\t});\n\treturn candidateTask;\n};\n\n/*\nDispatch a task and invoke the callback\n*/\nSyncer.prototype.dispatchTask = function(task,callback) {\n\tvar self = this;\n\tif(task.type === \"save\") {\n\t\tvar changeCount = this.wiki.getChangeCount(task.title),\n\t\t\ttiddler = this.wiki.getTiddler(task.title);\n\t\tthis.logger.log(\"Dispatching 'save' task:\",task.title);\n\t\tif(tiddler) {\n\t\t\tthis.syncadaptor.saveTiddler(tiddler,function(err,adaptorInfo,revision) {\n\t\t\t\tif(err) {\n\t\t\t\t\treturn callback(err);\n\t\t\t\t}\n\t\t\t\t// Adjust the info stored about this tiddler\n\t\t\t\tself.tiddlerInfo[task.title] = {\n\t\t\t\t\tchangeCount: changeCount,\n\t\t\t\t\tadaptorInfo: adaptorInfo,\n\t\t\t\t\trevision: revision\n\t\t\t\t};\n\t\t\t\t// Invoke the callback\n\t\t\t\tcallback(null);\n\t\t\t},{\n\t\t\t\ttiddlerInfo: self.tiddlerInfo[task.title]\n\t\t\t});\n\t\t} else {\n\t\t\tthis.logger.log(\" Not Dispatching 'save' task:\",task.title,\"tiddler does not exist\");\n\t\t\treturn callback(null);\n\t\t}\n\t} else if(task.type === \"load\") {\n\t\t// Load the tiddler\n\t\tthis.logger.log(\"Dispatching 'load' task:\",task.title);\n\t\tthis.syncadaptor.loadTiddler(task.title,function(err,tiddlerFields) {\n\t\t\tif(err) {\n\t\t\t\treturn callback(err);\n\t\t\t}\n\t\t\t// Store the tiddler\n\t\t\tif(tiddlerFields) {\n\t\t\t\tself.storeTiddler(tiddlerFields);\n\t\t\t}\n\t\t\t// Invoke the callback\n\t\t\tcallback(null);\n\t\t});\n\t} else if(task.type === \"delete\") {\n\t\t// Delete the tiddler\n\t\tthis.logger.log(\"Dispatching 'delete' task:\",task.title);\n\t\tthis.syncadaptor.deleteTiddler(task.title,function(err) {\n\t\t\tif(err) {\n\t\t\t\treturn callback(err);\n\t\t\t}\n\t\t\tdelete self.tiddlerInfo[task.title];\n\t\t\t// Invoke the callback\n\t\t\tcallback(null);\n\t\t},{\n\t\t\ttiddlerInfo: self.tiddlerInfo[task.title]\n\t\t});\n\t}\n};\n\nexports.Syncer = Syncer;\n\n})();\n",
"title": "$:/core/modules/syncer.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/tiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/tiddler.js\ntype: application/javascript\nmodule-type: tiddlermethod\n\nExtension methods for the $tw.Tiddler object (constructor and methods required at boot time are in boot/boot.js)\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.hasTag = function(tag) {\n\treturn this.fields.tags && this.fields.tags.indexOf(tag) !== -1;\n};\n\nexports.isPlugin = function() {\n\treturn this.fields.type === \"application/json\" && this.hasField(\"plugin-type\");\n};\n\nexports.isDraft = function() {\n\treturn this.hasField(\"draft.of\");\n};\n\nexports.getFieldString = function(field) {\n\tvar value = this.fields[field];\n\t// Check for a missing field\n\tif(value === undefined || value === null) {\n\t\treturn \"\";\n\t}\n\t// Parse the field with the associated module (if any)\n\tvar fieldModule = $tw.Tiddler.fieldModules[field];\n\tif(fieldModule && fieldModule.stringify) {\n\t\treturn fieldModule.stringify.call(this,value);\n\t} else {\n\t\treturn value.toString();\n\t}\n};\n\n/*\nGet all the fields as a name:value block. Options:\n\texclude: an array of field names to exclude\n*/\nexports.getFieldStringBlock = function(options) {\n\toptions = options || {};\n\tvar exclude = options.exclude || [];\n\tvar fields = [];\n\tfor(var field in this.fields) {\n\t\tif($tw.utils.hop(this.fields,field)) {\n\t\t\tif(exclude.indexOf(field) === -1) {\n\t\t\t\tfields.push(field + \": \" + this.getFieldString(field));\n\t\t\t}\n\t\t}\n\t}\n\treturn fields.join(\"\\n\");\n};\n\n/*\nCompare two tiddlers for equality\ntiddler: the tiddler to compare\nexcludeFields: array of field names to exclude from the comparison\n*/\nexports.isEqual = function(tiddler,excludeFields) {\n\tif(!(tiddler instanceof $tw.Tiddler)) {\n\t\treturn false;\n\t}\n\texcludeFields = excludeFields || [];\n\tvar self = this,\n\t\tdifferences = []; // Fields that have differences\n\t// Add to the differences array\n\tfunction addDifference(fieldName) {\n\t\t// Check for this field being excluded\n\t\tif(excludeFields.indexOf(fieldName) === -1) {\n\t\t\t// Save the field as a difference\n\t\t\t$tw.utils.pushTop(differences,fieldName);\n\t\t}\n\t}\n\t// Returns true if the two values of this field are equal\n\tfunction isFieldValueEqual(fieldName) {\n\t\tvar valueA = self.fields[fieldName],\n\t\t\tvalueB = tiddler.fields[fieldName];\n\t\t// Check for identical string values\n\t\tif(typeof(valueA) === \"string\" && typeof(valueB) === \"string\" && valueA === valueB) {\n\t\t\treturn true;\n\t\t}\n\t\t// Check for identical array values\n\t\tif($tw.utils.isArray(valueA) && $tw.utils.isArray(valueB) && $tw.utils.isArrayEqual(valueA,valueB)) {\n\t\t\treturn true;\n\t\t}\n\t\t// Otherwise the fields must be different\n\t\treturn false;\n\t}\n\t// Compare our fields\n\tfor(var fieldName in this.fields) {\n\t\tif(!isFieldValueEqual(fieldName)) {\n\t\t\taddDifference(fieldName);\n\t\t}\n\t}\n\t// There's a difference for every field in the other tiddler that we don't have\n\tfor(fieldName in tiddler.fields) {\n\t\tif(!(fieldName in this.fields)) {\n\t\t\taddDifference(fieldName);\n\t\t}\n\t}\n\t// Return whether there were any differences\n\treturn differences.length === 0;\n};\n\n})();\n",
"title": "$:/core/modules/tiddler.js",
"type": "application/javascript",
"module-type": "tiddlermethod"
},
"$:/core/modules/upgraders/plugins.js": {
"text": "/*\\\ntitle: $:/core/modules/upgraders/plugins.js\ntype: application/javascript\nmodule-type: upgrader\n\nUpgrader module that checks that plugins are newer than any already installed version\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar UPGRADE_LIBRARY_TITLE = \"$:/UpgradeLibrary\";\n\nvar BLOCKED_PLUGINS = {\n\t\"$:/themes/tiddlywiki/stickytitles\": {\n\t\tversions: [\"*\"]\n\t},\n\t\"$:/plugins/tiddlywiki/fullscreen\": {\n\t\tversions: [\"*\"]\n\t}\n};\n\nexports.upgrade = function(wiki,titles,tiddlers) {\n\tvar self = this,\n\t\tmessages = {},\n\t\tupgradeLibrary,\n\t\tgetLibraryTiddler = function(title) {\n\t\t\tif(!upgradeLibrary) {\n\t\t\t\tupgradeLibrary = wiki.getTiddlerData(UPGRADE_LIBRARY_TITLE,{});\n\t\t\t\tupgradeLibrary.tiddlers = upgradeLibrary.tiddlers || {};\n\t\t\t}\n\t\t\treturn upgradeLibrary.tiddlers[title];\n\t\t};\n\n\t// Go through all the incoming tiddlers\n\t$tw.utils.each(titles,function(title) {\n\t\tvar incomingTiddler = tiddlers[title];\n\t\t// Check if we're dealing with a plugin\n\t\tif(incomingTiddler && incomingTiddler[\"plugin-type\"] && incomingTiddler.version) {\n\t\t\t// Upgrade the incoming plugin if it is in the upgrade library\n\t\t\tvar libraryTiddler = getLibraryTiddler(title);\n\t\t\tif(libraryTiddler && libraryTiddler[\"plugin-type\"] && libraryTiddler.version) {\n\t\t\t\ttiddlers[title] = libraryTiddler;\n\t\t\t\tmessages[title] = $tw.language.getString(\"Import/Upgrader/Plugins/Upgraded\",{variables: {incoming: incomingTiddler.version, upgraded: libraryTiddler.version}});\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t// Suppress the incoming plugin if it is older than the currently installed one\n\t\t\tvar existingTiddler = wiki.getTiddler(title);\n\t\t\tif(existingTiddler && existingTiddler.hasField(\"plugin-type\") && existingTiddler.hasField(\"version\")) {\n\t\t\t\t// Reject the incoming plugin by blanking all its fields\n\t\t\t\tif($tw.utils.checkVersions(existingTiddler.fields.version,incomingTiddler.version)) {\n\t\t\t\t\ttiddlers[title] = Object.create(null);\n\t\t\t\t\tmessages[title] = $tw.language.getString(\"Import/Upgrader/Plugins/Suppressed/Version\",{variables: {incoming: incomingTiddler.version, existing: existingTiddler.fields.version}});\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tif(incomingTiddler && incomingTiddler[\"plugin-type\"]) {\n\t\t\t// Check whether the plugin is on the blocked list\n\t\t\tvar blockInfo = BLOCKED_PLUGINS[title];\n\t\t\tif(blockInfo) {\n\t\t\t\tif(blockInfo.versions.indexOf(\"*\") !== -1 || (incomingTiddler.version && blockInfo.versions.indexOf(incomingTiddler.version) !== -1)) {\n\t\t\t\t\ttiddlers[title] = Object.create(null);\n\t\t\t\t\tmessages[title] = $tw.language.getString(\"Import/Upgrader/Plugins/Suppressed/Incompatible\");\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t});\n\treturn messages;\n};\n\n})();\n",
"title": "$:/core/modules/upgraders/plugins.js",
"type": "application/javascript",
"module-type": "upgrader"
},
"$:/core/modules/upgraders/system.js": {
"text": "/*\\\ntitle: $:/core/modules/upgraders/system.js\ntype: application/javascript\nmodule-type: upgrader\n\nUpgrader module that suppresses certain system tiddlers that shouldn't be imported\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar DONT_IMPORT_LIST = [\"$:/StoryList\",\"$:/HistoryList\"],\n\tDONT_IMPORT_PREFIX_LIST = [\"$:/temp/\",\"$:/state/\"];\n\nexports.upgrade = function(wiki,titles,tiddlers) {\n\tvar self = this,\n\t\tmessages = {};\n\t// Check for tiddlers on our list\n\t$tw.utils.each(titles,function(title) {\n\t\tif(DONT_IMPORT_LIST.indexOf(title) !== -1) {\n\t\t\ttiddlers[title] = Object.create(null);\n\t\t\tmessages[title] = $tw.language.getString(\"Import/Upgrader/System/Suppressed\");\n\t\t} else {\n\t\t\tfor(var t=0; t<DONT_IMPORT_PREFIX_LIST.length; t++) {\n\t\t\t\tvar prefix = DONT_IMPORT_PREFIX_LIST[t];\n\t\t\t\tif(title.substr(0,prefix.length) === prefix) {\n\t\t\t\t\ttiddlers[title] = Object.create(null);\n\t\t\t\t\tmessages[title] = $tw.language.getString(\"Import/Upgrader/State/Suppressed\");\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t});\n\treturn messages;\n};\n\n})();\n",
"title": "$:/core/modules/upgraders/system.js",
"type": "application/javascript",
"module-type": "upgrader"
},
"$:/core/modules/upgraders/themetweaks.js": {
"text": "/*\\\ntitle: $:/core/modules/upgraders/themetweaks.js\ntype: application/javascript\nmodule-type: upgrader\n\nUpgrader module that handles the change in theme tweak storage introduced in 5.0.14-beta.\n\nPreviously, theme tweaks were stored in two data tiddlers:\n\n* $:/themes/tiddlywiki/vanilla/metrics\n* $:/themes/tiddlywiki/vanilla/settings\n\nNow, each tweak is stored in its own separate tiddler.\n\nThis upgrader copies any values from the old format to the new. The old data tiddlers are not deleted in case they have been used to store additional indexes.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar MAPPINGS = {\n\t\"$:/themes/tiddlywiki/vanilla/metrics\": {\n\t\t\"fontsize\": \"$:/themes/tiddlywiki/vanilla/metrics/fontsize\",\n\t\t\"lineheight\": \"$:/themes/tiddlywiki/vanilla/metrics/lineheight\",\n\t\t\"storyleft\": \"$:/themes/tiddlywiki/vanilla/metrics/storyleft\",\n\t\t\"storytop\": \"$:/themes/tiddlywiki/vanilla/metrics/storytop\",\n\t\t\"storyright\": \"$:/themes/tiddlywiki/vanilla/metrics/storyright\",\n\t\t\"storywidth\": \"$:/themes/tiddlywiki/vanilla/metrics/storywidth\",\n\t\t\"tiddlerwidth\": \"$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth\"\n\t},\n\t\"$:/themes/tiddlywiki/vanilla/settings\": {\n\t\t\"fontfamily\": \"$:/themes/tiddlywiki/vanilla/settings/fontfamily\"\n\t}\n};\n\nexports.upgrade = function(wiki,titles,tiddlers) {\n\tvar self = this,\n\t\tmessages = {};\n\t// Check for tiddlers on our list\n\t$tw.utils.each(titles,function(title) {\n\t\tvar mapping = MAPPINGS[title];\n\t\tif(mapping) {\n\t\t\tvar tiddler = new $tw.Tiddler(tiddlers[title]),\n\t\t\t\ttiddlerData = wiki.getTiddlerDataCached(tiddler,{});\n\t\t\tfor(var index in mapping) {\n\t\t\t\tvar mappedTitle = mapping[index];\n\t\t\t\tif(!tiddlers[mappedTitle] || tiddlers[mappedTitle].title !== mappedTitle) {\n\t\t\t\t\ttiddlers[mappedTitle] = {\n\t\t\t\t\t\ttitle: mappedTitle,\n\t\t\t\t\t\ttext: tiddlerData[index]\n\t\t\t\t\t};\n\t\t\t\t\tmessages[mappedTitle] = $tw.language.getString(\"Import/Upgrader/ThemeTweaks/Created\",{variables: {\n\t\t\t\t\t\tfrom: title + \"##\" + index\n\t\t\t\t\t}});\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t});\n\treturn messages;\n};\n\n})();\n",
"title": "$:/core/modules/upgraders/themetweaks.js",
"type": "application/javascript",
"module-type": "upgrader"
},
"$:/core/modules/utils/crypto.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/crypto.js\ntype: application/javascript\nmodule-type: utils\n\nUtility functions related to crypto.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nLook for an encrypted store area in the text of a TiddlyWiki file\n*/\nexports.extractEncryptedStoreArea = function(text) {\n\tvar encryptedStoreAreaStartMarker = \"<pre id=\\\"encryptedStoreArea\\\" type=\\\"text/plain\\\" style=\\\"display:none;\\\">\",\n\t\tencryptedStoreAreaStart = text.indexOf(encryptedStoreAreaStartMarker);\n\tif(encryptedStoreAreaStart !== -1) {\n\t\tvar encryptedStoreAreaEnd = text.indexOf(\"</pre>\",encryptedStoreAreaStart);\n\t\tif(encryptedStoreAreaEnd !== -1) {\n\t\t\treturn $tw.utils.htmlDecode(text.substring(encryptedStoreAreaStart + encryptedStoreAreaStartMarker.length,encryptedStoreAreaEnd-1));\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nAttempt to extract the tiddlers from an encrypted store area using the current password. If the password is not provided then the password in the password store will be used\n*/\nexports.decryptStoreArea = function(encryptedStoreArea,password) {\n\tvar decryptedText = $tw.crypto.decrypt(encryptedStoreArea,password);\n\tif(decryptedText) {\n\t\tvar json = JSON.parse(decryptedText),\n\t\t\ttiddlers = [];\n\t\tfor(var title in json) {\n\t\t\tif(title !== \"$:/isEncrypted\") {\n\t\t\t\ttiddlers.push(json[title]);\n\t\t\t}\n\t\t}\n\t\treturn tiddlers;\n\t} else {\n\t\treturn null;\n\t}\n};\n\n\n/*\nAttempt to extract the tiddlers from an encrypted store area using the current password. If that fails, the user is prompted for a password.\nencryptedStoreArea: text of the TiddlyWiki encrypted store area\ncallback: function(tiddlers) called with the array of decrypted tiddlers\n\nThe following configuration settings are supported:\n\n$tw.config.usePasswordVault: causes any password entered by the user to also be put into the system password vault\n*/\nexports.decryptStoreAreaInteractive = function(encryptedStoreArea,callback,options) {\n\t// Try to decrypt with the current password\n\tvar tiddlers = $tw.utils.decryptStoreArea(encryptedStoreArea);\n\tif(tiddlers) {\n\t\tcallback(tiddlers);\n\t} else {\n\t\t// Prompt for a new password and keep trying\n\t\t$tw.passwordPrompt.createPrompt({\n\t\t\tserviceName: \"Enter a password to decrypt the imported TiddlyWiki\",\n\t\t\tnoUserName: true,\n\t\t\tcanCancel: true,\n\t\t\tsubmitText: \"Decrypt\",\n\t\t\tcallback: function(data) {\n\t\t\t\t// Exit if the user cancelled\n\t\t\t\tif(!data) {\n\t\t\t\t\treturn false;\n\t\t\t\t}\n\t\t\t\t// Attempt to decrypt the tiddlers\n\t\t\t\tvar tiddlers = $tw.utils.decryptStoreArea(encryptedStoreArea,data.password);\n\t\t\t\tif(tiddlers) {\n\t\t\t\t\tif($tw.config.usePasswordVault) {\n\t\t\t\t\t\t$tw.crypto.setPassword(data.password);\n\t\t\t\t\t}\n\t\t\t\t\tcallback(tiddlers);\n\t\t\t\t\t// Exit and remove the password prompt\n\t\t\t\t\treturn true;\n\t\t\t\t} else {\n\t\t\t\t\t// We didn't decrypt everything, so continue to prompt for password\n\t\t\t\t\treturn false;\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/utils/crypto.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/animations/slide.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/animations/slide.js\ntype: application/javascript\nmodule-type: animation\n\nA simple slide animation that varies the height of the element\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nfunction slideOpen(domNode,options) {\n\toptions = options || {};\n\tvar duration = options.duration || $tw.utils.getAnimationDuration();\n\t// Get the current height of the domNode\n\tvar computedStyle = window.getComputedStyle(domNode),\n\t\tcurrMarginBottom = parseInt(computedStyle.marginBottom,10),\n\t\tcurrMarginTop = parseInt(computedStyle.marginTop,10),\n\t\tcurrPaddingBottom = parseInt(computedStyle.paddingBottom,10),\n\t\tcurrPaddingTop = parseInt(computedStyle.paddingTop,10),\n\t\tcurrHeight = domNode.offsetHeight;\n\t// Reset the margin once the transition is over\n\tsetTimeout(function() {\n\t\t$tw.utils.setStyle(domNode,[\n\t\t\t{transition: \"none\"},\n\t\t\t{marginBottom: \"\"},\n\t\t\t{marginTop: \"\"},\n\t\t\t{paddingBottom: \"\"},\n\t\t\t{paddingTop: \"\"},\n\t\t\t{height: \"auto\"},\n\t\t\t{opacity: \"\"}\n\t\t]);\n\t\tif(options.callback) {\n\t\t\toptions.callback();\n\t\t}\n\t},duration);\n\t// Set up the initial position of the element\n\t$tw.utils.setStyle(domNode,[\n\t\t{transition: \"none\"},\n\t\t{marginTop: \"0px\"},\n\t\t{marginBottom: \"0px\"},\n\t\t{paddingTop: \"0px\"},\n\t\t{paddingBottom: \"0px\"},\n\t\t{height: \"0px\"},\n\t\t{opacity: \"0\"}\n\t]);\n\t$tw.utils.forceLayout(domNode);\n\t// Transition to the final position\n\t$tw.utils.setStyle(domNode,[\n\t\t{transition: \"margin-top \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"margin-bottom \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"padding-top \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"padding-bottom \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"height \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"opacity \" + duration + \"ms ease-in-out\"},\n\t\t{marginBottom: currMarginBottom + \"px\"},\n\t\t{marginTop: currMarginTop + \"px\"},\n\t\t{paddingBottom: currPaddingBottom + \"px\"},\n\t\t{paddingTop: currPaddingTop + \"px\"},\n\t\t{height: currHeight + \"px\"},\n\t\t{opacity: \"1\"}\n\t]);\n}\n\nfunction slideClosed(domNode,options) {\n\toptions = options || {};\n\tvar duration = options.duration || $tw.utils.getAnimationDuration(),\n\t\tcurrHeight = domNode.offsetHeight;\n\t// Clear the properties we've set when the animation is over\n\tsetTimeout(function() {\n\t\t$tw.utils.setStyle(domNode,[\n\t\t\t{transition: \"none\"},\n\t\t\t{marginBottom: \"\"},\n\t\t\t{marginTop: \"\"},\n\t\t\t{paddingBottom: \"\"},\n\t\t\t{paddingTop: \"\"},\n\t\t\t{height: \"auto\"},\n\t\t\t{opacity: \"\"}\n\t\t]);\n\t\tif(options.callback) {\n\t\t\toptions.callback();\n\t\t}\n\t},duration);\n\t// Set up the initial position of the element\n\t$tw.utils.setStyle(domNode,[\n\t\t{height: currHeight + \"px\"},\n\t\t{opacity: \"1\"}\n\t]);\n\t$tw.utils.forceLayout(domNode);\n\t// Transition to the final position\n\t$tw.utils.setStyle(domNode,[\n\t\t{transition: \"margin-top \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"margin-bottom \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"padding-top \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"padding-bottom \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"height \" + duration + \"ms ease-in-out, \" +\n\t\t\t\t\t\"opacity \" + duration + \"ms ease-in-out\"},\n\t\t{marginTop: \"0px\"},\n\t\t{marginBottom: \"0px\"},\n\t\t{paddingTop: \"0px\"},\n\t\t{paddingBottom: \"0px\"},\n\t\t{height: \"0px\"},\n\t\t{opacity: \"0\"}\n\t]);\n}\n\nexports.slide = {\n\topen: slideOpen,\n\tclose: slideClosed\n};\n\n})();\n",
"title": "$:/core/modules/utils/dom/animations/slide.js",
"type": "application/javascript",
"module-type": "animation"
},
"$:/core/modules/utils/dom/animator.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/animator.js\ntype: application/javascript\nmodule-type: utils\n\nOrchestrates animations and transitions\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nfunction Animator() {\n\t// Get the registered animation modules\n\tthis.animations = {};\n\t$tw.modules.applyMethods(\"animation\",this.animations);\n}\n\nAnimator.prototype.perform = function(type,domNode,options) {\n\toptions = options || {};\n\t// Find an animation that can handle this type\n\tvar chosenAnimation;\n\t$tw.utils.each(this.animations,function(animation,name) {\n\t\tif($tw.utils.hop(animation,type)) {\n\t\t\tchosenAnimation = animation[type];\n\t\t}\n\t});\n\tif(!chosenAnimation) {\n\t\tchosenAnimation = function(domNode,options) {\n\t\t\tif(options.callback) {\n\t\t\t\toptions.callback();\n\t\t\t}\n\t\t};\n\t}\n\t// Call the animation\n\tchosenAnimation(domNode,options);\n};\n\nexports.Animator = Animator;\n\n})();\n",
"title": "$:/core/modules/utils/dom/animator.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/browser.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/browser.js\ntype: application/javascript\nmodule-type: utils\n\nBrowser feature detection\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nSet style properties of an element\n\telement: dom node\n\tstyles: ordered array of {name: value} pairs\n*/\nexports.setStyle = function(element,styles) {\n\tif(element.nodeType === 1) { // Element.ELEMENT_NODE\n\t\tfor(var t=0; t<styles.length; t++) {\n\t\t\tfor(var styleName in styles[t]) {\n\t\t\t\telement.style[$tw.utils.convertStyleNameToPropertyName(styleName)] = styles[t][styleName];\n\t\t\t}\n\t\t}\n\t}\n};\n\n/*\nConverts a standard CSS property name into the local browser-specific equivalent. For example:\n\t\"background-color\" --> \"backgroundColor\"\n\t\"transition\" --> \"webkitTransition\"\n*/\n\nvar styleNameCache = {}; // We'll cache the style name conversions\n\nexports.convertStyleNameToPropertyName = function(styleName) {\n\t// Return from the cache if we can\n\tif(styleNameCache[styleName]) {\n\t\treturn styleNameCache[styleName];\n\t}\n\t// Convert it by first removing any hyphens\n\tvar propertyName = $tw.utils.unHyphenateCss(styleName);\n\t// Then check if it needs a prefix\n\tif($tw.browser && document.body.style[propertyName] === undefined) {\n\t\tvar prefixes = [\"O\",\"MS\",\"Moz\",\"webkit\"];\n\t\tfor(var t=0; t<prefixes.length; t++) {\n\t\t\tvar prefixedName = prefixes[t] + propertyName.substr(0,1).toUpperCase() + propertyName.substr(1);\n\t\t\tif(document.body.style[prefixedName] !== undefined) {\n\t\t\t\tpropertyName = prefixedName;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t}\n\t// Put it in the cache too\n\tstyleNameCache[styleName] = propertyName;\n\treturn propertyName;\n};\n\n/*\nConverts a JS format CSS property name back into the dashed form used in CSS declarations. For example:\n\t\"backgroundColor\" --> \"background-color\"\n\t\"webkitTransform\" --> \"-webkit-transform\"\n*/\nexports.convertPropertyNameToStyleName = function(propertyName) {\n\t// Rehyphenate the name\n\tvar styleName = $tw.utils.hyphenateCss(propertyName);\n\t// If there's a webkit prefix, add a dash (other browsers have uppercase prefixes, and so get the dash automatically)\n\tif(styleName.indexOf(\"webkit\") === 0) {\n\t\tstyleName = \"-\" + styleName;\n\t} else if(styleName.indexOf(\"-m-s\") === 0) {\n\t\tstyleName = \"-ms\" + styleName.substr(4);\n\t}\n\treturn styleName;\n};\n\n/*\nRound trip a stylename to a property name and back again. For example:\n\t\"transform\" --> \"webkitTransform\" --> \"-webkit-transform\"\n*/\nexports.roundTripPropertyName = function(propertyName) {\n\treturn $tw.utils.convertPropertyNameToStyleName($tw.utils.convertStyleNameToPropertyName(propertyName));\n};\n\n/*\nConverts a standard event name into the local browser specific equivalent. For example:\n\t\"animationEnd\" --> \"webkitAnimationEnd\"\n*/\n\nvar eventNameCache = {}; // We'll cache the conversions\n\nvar eventNameMappings = {\n\t\"transitionEnd\": {\n\t\tcorrespondingCssProperty: \"transition\",\n\t\tmappings: {\n\t\t\ttransition: \"transitionend\",\n\t\t\tOTransition: \"oTransitionEnd\",\n\t\t\tMSTransition: \"msTransitionEnd\",\n\t\t\tMozTransition: \"transitionend\",\n\t\t\twebkitTransition: \"webkitTransitionEnd\"\n\t\t}\n\t},\n\t\"animationEnd\": {\n\t\tcorrespondingCssProperty: \"animation\",\n\t\tmappings: {\n\t\t\tanimation: \"animationend\",\n\t\t\tOAnimation: \"oAnimationEnd\",\n\t\t\tMSAnimation: \"msAnimationEnd\",\n\t\t\tMozAnimation: \"animationend\",\n\t\t\twebkitAnimation: \"webkitAnimationEnd\"\n\t\t}\n\t}\n};\n\nexports.convertEventName = function(eventName) {\n\tif(eventNameCache[eventName]) {\n\t\treturn eventNameCache[eventName];\n\t}\n\tvar newEventName = eventName,\n\t\tmappings = eventNameMappings[eventName];\n\tif(mappings) {\n\t\tvar convertedProperty = $tw.utils.convertStyleNameToPropertyName(mappings.correspondingCssProperty);\n\t\tif(mappings.mappings[convertedProperty]) {\n\t\t\tnewEventName = mappings.mappings[convertedProperty];\n\t\t}\n\t}\n\t// Put it in the cache too\n\teventNameCache[eventName] = newEventName;\n\treturn newEventName;\n};\n\n/*\nReturn the names of the fullscreen APIs\n*/\nexports.getFullScreenApis = function() {\n\tvar d = document,\n\t\tdb = d.body,\n\t\tresult = {\n\t\t\"_requestFullscreen\": db.webkitRequestFullscreen !== undefined ? \"webkitRequestFullscreen\" :\n\t\t\t\t\t\t\tdb.mozRequestFullScreen !== undefined ? \"mozRequestFullScreen\" :\n\t\t\t\t\t\t\tdb.msRequestFullscreen !== undefined ? \"msRequestFullscreen\" :\n\t\t\t\t\t\t\tdb.requestFullscreen !== undefined ? \"requestFullscreen\" : \"\",\n\t\t\"_exitFullscreen\": d.webkitExitFullscreen !== undefined ? \"webkitExitFullscreen\" :\n\t\t\t\t\t\t\td.mozCancelFullScreen !== undefined ? \"mozCancelFullScreen\" :\n\t\t\t\t\t\t\td.msExitFullscreen !== undefined ? \"msExitFullscreen\" :\n\t\t\t\t\t\t\td.exitFullscreen !== undefined ? \"exitFullscreen\" : \"\",\n\t\t\"_fullscreenElement\": d.webkitFullscreenElement !== undefined ? \"webkitFullscreenElement\" :\n\t\t\t\t\t\t\td.mozFullScreenElement !== undefined ? \"mozFullScreenElement\" :\n\t\t\t\t\t\t\td.msFullscreenElement !== undefined ? \"msFullscreenElement\" :\n\t\t\t\t\t\t\td.fullscreenElement !== undefined ? \"fullscreenElement\" : \"\",\n\t\t\"_fullscreenChange\": d.webkitFullscreenElement !== undefined ? \"webkitfullscreenchange\" :\n\t\t\t\t\t\t\td.mozFullScreenElement !== undefined ? \"mozfullscreenchange\" :\n\t\t\t\t\t\t\td.msFullscreenElement !== undefined ? \"MSFullscreenChange\" :\n\t\t\t\t\t\t\td.fullscreenElement !== undefined ? \"fullscreenchange\" : \"\"\n\t};\n\tif(!result._requestFullscreen || !result._exitFullscreen || !result._fullscreenElement || !result._fullscreenChange) {\n\t\treturn null;\n\t} else {\n\t\treturn result;\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/utils/dom/browser.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/csscolorparser.js": {
"text": "// (c) Dean McNamee <dean@gmail.com>, 2012.\n//\n// https://github.com/deanm/css-color-parser-js\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to\n// deal in the Software without restriction, including without limitation the\n// rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n// sell copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n// IN THE SOFTWARE.\n\n// http://www.w3.org/TR/css3-color/\nvar kCSSColorTable = {\n \"transparent\": [0,0,0,0], \"aliceblue\": [240,248,255,1],\n \"antiquewhite\": [250,235,215,1], \"aqua\": [0,255,255,1],\n \"aquamarine\": [127,255,212,1], \"azure\": [240,255,255,1],\n \"beige\": [245,245,220,1], \"bisque\": [255,228,196,1],\n \"black\": [0,0,0,1], \"blanchedalmond\": [255,235,205,1],\n \"blue\": [0,0,255,1], \"blueviolet\": [138,43,226,1],\n \"brown\": [165,42,42,1], \"burlywood\": [222,184,135,1],\n \"cadetblue\": [95,158,160,1], \"chartreuse\": [127,255,0,1],\n \"chocolate\": [210,105,30,1], \"coral\": [255,127,80,1],\n \"cornflowerblue\": [100,149,237,1], \"cornsilk\": [255,248,220,1],\n \"crimson\": [220,20,60,1], \"cyan\": [0,255,255,1],\n \"darkblue\": [0,0,139,1], \"darkcyan\": [0,139,139,1],\n \"darkgoldenrod\": [184,134,11,1], \"darkgray\": [169,169,169,1],\n \"darkgreen\": [0,100,0,1], \"darkgrey\": [169,169,169,1],\n \"darkkhaki\": [189,183,107,1], \"darkmagenta\": [139,0,139,1],\n \"darkolivegreen\": [85,107,47,1], \"darkorange\": [255,140,0,1],\n \"darkorchid\": [153,50,204,1], \"darkred\": [139,0,0,1],\n \"darksalmon\": [233,150,122,1], \"darkseagreen\": [143,188,143,1],\n \"darkslateblue\": [72,61,139,1], \"darkslategray\": [47,79,79,1],\n \"darkslategrey\": [47,79,79,1], \"darkturquoise\": [0,206,209,1],\n \"darkviolet\": [148,0,211,1], \"deeppink\": [255,20,147,1],\n \"deepskyblue\": [0,191,255,1], \"dimgray\": [105,105,105,1],\n \"dimgrey\": [105,105,105,1], \"dodgerblue\": [30,144,255,1],\n \"firebrick\": [178,34,34,1], \"floralwhite\": [255,250,240,1],\n \"forestgreen\": [34,139,34,1], \"fuchsia\": [255,0,255,1],\n \"gainsboro\": [220,220,220,1], \"ghostwhite\": [248,248,255,1],\n \"gold\": [255,215,0,1], \"goldenrod\": [218,165,32,1],\n \"gray\": [128,128,128,1], \"green\": [0,128,0,1],\n \"greenyellow\": [173,255,47,1], \"grey\": [128,128,128,1],\n \"honeydew\": [240,255,240,1], \"hotpink\": [255,105,180,1],\n \"indianred\": [205,92,92,1], \"indigo\": [75,0,130,1],\n \"ivory\": [255,255,240,1], \"khaki\": [240,230,140,1],\n \"lavender\": [230,230,250,1], \"lavenderblush\": [255,240,245,1],\n \"lawngreen\": [124,252,0,1], \"lemonchiffon\": [255,250,205,1],\n \"lightblue\": [173,216,230,1], \"lightcoral\": [240,128,128,1],\n \"lightcyan\": [224,255,255,1], \"lightgoldenrodyellow\": [250,250,210,1],\n \"lightgray\": [211,211,211,1], \"lightgreen\": [144,238,144,1],\n \"lightgrey\": [211,211,211,1], \"lightpink\": [255,182,193,1],\n \"lightsalmon\": [255,160,122,1], \"lightseagreen\": [32,178,170,1],\n \"lightskyblue\": [135,206,250,1], \"lightslategray\": [119,136,153,1],\n \"lightslategrey\": [119,136,153,1], \"lightsteelblue\": [176,196,222,1],\n \"lightyellow\": [255,255,224,1], \"lime\": [0,255,0,1],\n \"limegreen\": [50,205,50,1], \"linen\": [250,240,230,1],\n \"magenta\": [255,0,255,1], \"maroon\": [128,0,0,1],\n \"mediumaquamarine\": [102,205,170,1], \"mediumblue\": [0,0,205,1],\n \"mediumorchid\": [186,85,211,1], \"mediumpurple\": [147,112,219,1],\n \"mediumseagreen\": [60,179,113,1], \"mediumslateblue\": [123,104,238,1],\n \"mediumspringgreen\": [0,250,154,1], \"mediumturquoise\": [72,209,204,1],\n \"mediumvioletred\": [199,21,133,1], \"midnightblue\": [25,25,112,1],\n \"mintcream\": [245,255,250,1], \"mistyrose\": [255,228,225,1],\n \"moccasin\": [255,228,181,1], \"navajowhite\": [255,222,173,1],\n \"navy\": [0,0,128,1], \"oldlace\": [253,245,230,1],\n \"olive\": [128,128,0,1], \"olivedrab\": [107,142,35,1],\n \"orange\": [255,165,0,1], \"orangered\": [255,69,0,1],\n \"orchid\": [218,112,214,1], \"palegoldenrod\": [238,232,170,1],\n \"palegreen\": [152,251,152,1], \"paleturquoise\": [175,238,238,1],\n \"palevioletred\": [219,112,147,1], \"papayawhip\": [255,239,213,1],\n \"peachpuff\": [255,218,185,1], \"peru\": [205,133,63,1],\n \"pink\": [255,192,203,1], \"plum\": [221,160,221,1],\n \"powderblue\": [176,224,230,1], \"purple\": [128,0,128,1],\n \"red\": [255,0,0,1], \"rosybrown\": [188,143,143,1],\n \"royalblue\": [65,105,225,1], \"saddlebrown\": [139,69,19,1],\n \"salmon\": [250,128,114,1], \"sandybrown\": [244,164,96,1],\n \"seagreen\": [46,139,87,1], \"seashell\": [255,245,238,1],\n \"sienna\": [160,82,45,1], \"silver\": [192,192,192,1],\n \"skyblue\": [135,206,235,1], \"slateblue\": [106,90,205,1],\n \"slategray\": [112,128,144,1], \"slategrey\": [112,128,144,1],\n \"snow\": [255,250,250,1], \"springgreen\": [0,255,127,1],\n \"steelblue\": [70,130,180,1], \"tan\": [210,180,140,1],\n \"teal\": [0,128,128,1], \"thistle\": [216,191,216,1],\n \"tomato\": [255,99,71,1], \"turquoise\": [64,224,208,1],\n \"violet\": [238,130,238,1], \"wheat\": [245,222,179,1],\n \"white\": [255,255,255,1], \"whitesmoke\": [245,245,245,1],\n \"yellow\": [255,255,0,1], \"yellowgreen\": [154,205,50,1]}\n\nfunction clamp_css_byte(i) { // Clamp to integer 0 .. 255.\n i = Math.round(i); // Seems to be what Chrome does (vs truncation).\n return i < 0 ? 0 : i > 255 ? 255 : i;\n}\n\nfunction clamp_css_float(f) { // Clamp to float 0.0 .. 1.0.\n return f < 0 ? 0 : f > 1 ? 1 : f;\n}\n\nfunction parse_css_int(str) { // int or percentage.\n if (str[str.length - 1] === '%')\n return clamp_css_byte(parseFloat(str) / 100 * 255);\n return clamp_css_byte(parseInt(str));\n}\n\nfunction parse_css_float(str) { // float or percentage.\n if (str[str.length - 1] === '%')\n return clamp_css_float(parseFloat(str) / 100);\n return clamp_css_float(parseFloat(str));\n}\n\nfunction css_hue_to_rgb(m1, m2, h) {\n if (h < 0) h += 1;\n else if (h > 1) h -= 1;\n\n if (h * 6 < 1) return m1 + (m2 - m1) * h * 6;\n if (h * 2 < 1) return m2;\n if (h * 3 < 2) return m1 + (m2 - m1) * (2/3 - h) * 6;\n return m1;\n}\n\nfunction parseCSSColor(css_str) {\n // Remove all whitespace, not compliant, but should just be more accepting.\n var str = css_str.replace(/ /g, '').toLowerCase();\n\n // Color keywords (and transparent) lookup.\n if (str in kCSSColorTable) return kCSSColorTable[str].slice(); // dup.\n\n // #abc and #abc123 syntax.\n if (str[0] === '#') {\n if (str.length === 4) {\n var iv = parseInt(str.substr(1), 16); // TODO(deanm): Stricter parsing.\n if (!(iv >= 0 && iv <= 0xfff)) return null; // Covers NaN.\n return [((iv & 0xf00) >> 4) | ((iv & 0xf00) >> 8),\n (iv & 0xf0) | ((iv & 0xf0) >> 4),\n (iv & 0xf) | ((iv & 0xf) << 4),\n 1];\n } else if (str.length === 7) {\n var iv = parseInt(str.substr(1), 16); // TODO(deanm): Stricter parsing.\n if (!(iv >= 0 && iv <= 0xffffff)) return null; // Covers NaN.\n return [(iv & 0xff0000) >> 16,\n (iv & 0xff00) >> 8,\n iv & 0xff,\n 1];\n }\n\n return null;\n }\n\n var op = str.indexOf('('), ep = str.indexOf(')');\n if (op !== -1 && ep + 1 === str.length) {\n var fname = str.substr(0, op);\n var params = str.substr(op+1, ep-(op+1)).split(',');\n var alpha = 1; // To allow case fallthrough.\n switch (fname) {\n case 'rgba':\n if (params.length !== 4) return null;\n alpha = parse_css_float(params.pop());\n // Fall through.\n case 'rgb':\n if (params.length !== 3) return null;\n return [parse_css_int(params[0]),\n parse_css_int(params[1]),\n parse_css_int(params[2]),\n alpha];\n case 'hsla':\n if (params.length !== 4) return null;\n alpha = parse_css_float(params.pop());\n // Fall through.\n case 'hsl':\n if (params.length !== 3) return null;\n var h = (((parseFloat(params[0]) % 360) + 360) % 360) / 360; // 0 .. 1\n // NOTE(deanm): According to the CSS spec s/l should only be\n // percentages, but we don't bother and let float or percentage.\n var s = parse_css_float(params[1]);\n var l = parse_css_float(params[2]);\n var m2 = l <= 0.5 ? l * (s + 1) : l + s - l * s;\n var m1 = l * 2 - m2;\n return [clamp_css_byte(css_hue_to_rgb(m1, m2, h+1/3) * 255),\n clamp_css_byte(css_hue_to_rgb(m1, m2, h) * 255),\n clamp_css_byte(css_hue_to_rgb(m1, m2, h-1/3) * 255),\n alpha];\n default:\n return null;\n }\n }\n\n return null;\n}\n\ntry { exports.parseCSSColor = parseCSSColor } catch(e) { }\n",
"title": "$:/core/modules/utils/dom/csscolorparser.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom.js\ntype: application/javascript\nmodule-type: utils\n\nVarious static DOM-related utility functions.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nDetermines whether element 'a' contains element 'b'\nCode thanks to John Resig, http://ejohn.org/blog/comparing-document-position/\n*/\nexports.domContains = function(a,b) {\n\treturn a.contains ?\n\t\ta !== b && a.contains(b) :\n\t\t!!(a.compareDocumentPosition(b) & 16);\n};\n\nexports.removeChildren = function(node) {\n\twhile(node.hasChildNodes()) {\n\t\tnode.removeChild(node.firstChild);\n\t}\n};\n\nexports.hasClass = function(el,className) {\n\treturn el && el.className && el.className.toString().split(\" \").indexOf(className) !== -1;\n};\n\nexports.addClass = function(el,className) {\n\tvar c = el.className.split(\" \");\n\tif(c.indexOf(className) === -1) {\n\t\tc.push(className);\n\t}\n\tel.className = c.join(\" \");\n};\n\nexports.removeClass = function(el,className) {\n\tvar c = el.className.split(\" \"),\n\t\tp = c.indexOf(className);\n\tif(p !== -1) {\n\t\tc.splice(p,1);\n\t\tel.className = c.join(\" \");\n\t}\n};\n\nexports.toggleClass = function(el,className,status) {\n\tif(status === undefined) {\n\t\tstatus = !exports.hasClass(el,className);\n\t}\n\tif(status) {\n\t\texports.addClass(el,className);\n\t} else {\n\t\texports.removeClass(el,className);\n\t}\n};\n\n/*\nGet the first parent element that has scrollbars or use the body as fallback.\n*/\nexports.getScrollContainer = function(el) {\n\tvar doc = el.ownerDocument;\n\twhile(el.parentNode) {\t\n\t\tel = el.parentNode;\n\t\tif(el.scrollTop) {\n\t\t\treturn el;\n\t\t}\n\t}\n\treturn doc.body;\n};\n\n/*\nGet the scroll position of the viewport\nReturns:\n\t{\n\t\tx: horizontal scroll position in pixels,\n\t\ty: vertical scroll position in pixels\n\t}\n*/\nexports.getScrollPosition = function() {\n\tif(\"scrollX\" in window) {\n\t\treturn {x: window.scrollX, y: window.scrollY};\n\t} else {\n\t\treturn {x: document.documentElement.scrollLeft, y: document.documentElement.scrollTop};\n\t}\n};\n\n/*\nAdjust the height of a textarea to fit its content, preserving scroll position, and return the height\n*/\nexports.resizeTextAreaToFit = function(domNode,minHeight) {\n\t// Get the scroll container and register the current scroll position\n\tvar container = $tw.utils.getScrollContainer(domNode),\n\t\tscrollTop = container.scrollTop;\n // Measure the specified minimum height\n\tdomNode.style.height = minHeight;\n\tvar measuredHeight = domNode.offsetHeight;\n\t// Set its height to auto so that it snaps to the correct height\n\tdomNode.style.height = \"auto\";\n\t// Calculate the revised height\n\tvar newHeight = Math.max(domNode.scrollHeight + domNode.offsetHeight - domNode.clientHeight,measuredHeight);\n\t// Only try to change the height if it has changed\n\tif(newHeight !== domNode.offsetHeight) {\n\t\tdomNode.style.height = newHeight + \"px\";\n\t\t// Make sure that the dimensions of the textarea are recalculated\n\t\t$tw.utils.forceLayout(domNode);\n\t\t// Set the container to the position we registered at the beginning\n\t\tcontainer.scrollTop = scrollTop;\n\t}\n\treturn newHeight;\n};\n\n/*\nGets the bounding rectangle of an element in absolute page coordinates\n*/\nexports.getBoundingPageRect = function(element) {\n\tvar scrollPos = $tw.utils.getScrollPosition(),\n\t\tclientRect = element.getBoundingClientRect();\n\treturn {\n\t\tleft: clientRect.left + scrollPos.x,\n\t\twidth: clientRect.width,\n\t\tright: clientRect.right + scrollPos.x,\n\t\ttop: clientRect.top + scrollPos.y,\n\t\theight: clientRect.height,\n\t\tbottom: clientRect.bottom + scrollPos.y\n\t};\n};\n\n/*\nSaves a named password in the browser\n*/\nexports.savePassword = function(name,password) {\n\ttry {\n\t\tif(window.localStorage) {\n\t\t\tlocalStorage.setItem(\"tw5-password-\" + name,password);\n\t\t}\n\t} catch(e) {\n\t}\n};\n\n/*\nRetrieve a named password from the browser\n*/\nexports.getPassword = function(name) {\n\ttry {\n\t\treturn window.localStorage ? localStorage.getItem(\"tw5-password-\" + name) : \"\";\n\t} catch(e) {\n\t\treturn \"\";\n\t}\n};\n\n/*\nForce layout of a dom node and its descendents\n*/\nexports.forceLayout = function(element) {\n\tvar dummy = element.offsetWidth;\n};\n\n/*\nPulse an element for debugging purposes\n*/\nexports.pulseElement = function(element) {\n\t// Event handler to remove the class at the end\n\telement.addEventListener($tw.browser.animationEnd,function handler(event) {\n\t\telement.removeEventListener($tw.browser.animationEnd,handler,false);\n\t\t$tw.utils.removeClass(element,\"pulse\");\n\t},false);\n\t// Apply the pulse class\n\t$tw.utils.removeClass(element,\"pulse\");\n\t$tw.utils.forceLayout(element);\n\t$tw.utils.addClass(element,\"pulse\");\n};\n\n/*\nAttach specified event handlers to a DOM node\ndomNode: where to attach the event handlers\nevents: array of event handlers to be added (see below)\nEach entry in the events array is an object with these properties:\nhandlerFunction: optional event handler function\nhandlerObject: optional event handler object\nhandlerMethod: optionally specifies object handler method name (defaults to `handleEvent`)\n*/\nexports.addEventListeners = function(domNode,events) {\n\t$tw.utils.each(events,function(eventInfo) {\n\t\tvar handler;\n\t\tif(eventInfo.handlerFunction) {\n\t\t\thandler = eventInfo.handlerFunction;\n\t\t} else if(eventInfo.handlerObject) {\n\t\t\tif(eventInfo.handlerMethod) {\n\t\t\t\thandler = function(event) {\n\t\t\t\t\teventInfo.handlerObject[eventInfo.handlerMethod].call(eventInfo.handlerObject,event);\n\t\t\t\t};\t\n\t\t\t} else {\n\t\t\t\thandler = eventInfo.handlerObject;\n\t\t\t}\n\t\t}\n\t\tdomNode.addEventListener(eventInfo.name,handler,false);\n\t});\n};\n\n/*\nGet the computed styles applied to an element as an array of strings of individual CSS properties\n*/\nexports.getComputedStyles = function(domNode) {\n\tvar textAreaStyles = window.getComputedStyle(domNode,null),\n\t\tstyleDefs = [],\n\t\tname;\n\tfor(var t=0; t<textAreaStyles.length; t++) {\n\t\tname = textAreaStyles[t];\n\t\tstyleDefs.push(name + \": \" + textAreaStyles.getPropertyValue(name) + \";\");\n\t}\n\treturn styleDefs;\n};\n\n/*\nApply a set of styles passed as an array of strings of individual CSS properties\n*/\nexports.setStyles = function(domNode,styleDefs) {\n\tdomNode.style.cssText = styleDefs.join(\"\");\n};\n\n/*\nCopy the computed styles from a source element to a destination element\n*/\nexports.copyStyles = function(srcDomNode,dstDomNode) {\n\t$tw.utils.setStyles(dstDomNode,$tw.utils.getComputedStyles(srcDomNode));\n};\n\n})();\n",
"title": "$:/core/modules/utils/dom.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/http.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/http.js\ntype: application/javascript\nmodule-type: utils\n\nBrowser HTTP support\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nA quick and dirty HTTP function; to be refactored later. Options are:\n\turl: URL to retrieve\n\ttype: GET, PUT, POST etc\n\tcallback: function invoked with (err,data)\n*/\nexports.httpRequest = function(options) {\n\tvar type = options.type || \"GET\",\n\t\theaders = options.headers || {accept: \"application/json\"},\n\t\trequest = new XMLHttpRequest(),\n\t\tdata = \"\",\n\t\tf,results;\n\t// Massage the data hashmap into a string\n\tif(options.data) {\n\t\tif(typeof options.data === \"string\") { // Already a string\n\t\t\tdata = options.data;\n\t\t} else { // A hashmap of strings\n\t\t\tresults = [];\n\t\t\t$tw.utils.each(options.data,function(dataItem,dataItemTitle) {\n\t\t\t\tresults.push(dataItemTitle + \"=\" + encodeURIComponent(dataItem));\n\t\t\t});\n\t\t\tdata = results.join(\"&\");\n\t\t}\n\t}\n\t// Set up the state change handler\n\trequest.onreadystatechange = function() {\n\t\tif(this.readyState === 4) {\n\t\t\tif(this.status === 200 || this.status === 201 || this.status === 204) {\n\t\t\t\t// Success!\n\t\t\t\toptions.callback(null,this.responseText,this);\n\t\t\t\treturn;\n\t\t\t}\n\t\t// Something went wrong\n\t\toptions.callback($tw.language.getString(\"Error/XMLHttpRequest\") + \": \" + this.status);\n\t\t}\n\t};\n\t// Make the request\n\trequest.open(type,options.url,true);\n\tif(headers) {\n\t\t$tw.utils.each(headers,function(header,headerTitle,object) {\n\t\t\trequest.setRequestHeader(headerTitle,header);\n\t\t});\n\t}\n\tif(data && !$tw.utils.hop(headers,\"Content-type\")) {\n\t\trequest.setRequestHeader(\"Content-type\",\"application/x-www-form-urlencoded; charset=UTF-8\");\n\t}\n\ttry {\n\t\trequest.send(data);\n\t} catch(e) {\n\t\toptions.callback(e);\n\t}\n\treturn request;\n};\n\n})();\n",
"title": "$:/core/modules/utils/dom/http.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/keyboard.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/keyboard.js\ntype: application/javascript\nmodule-type: utils\n\nKeyboard utilities; now deprecated. Instead, use $tw.keyboardManager\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n[\"parseKeyDescriptor\",\"checkKeyDescriptor\"].forEach(function(method) {\n\texports[method] = function() {\n\t\tif($tw.keyboardManager) {\n\t\t\treturn $tw.keyboardManager[method].apply($tw.keyboardManager,Array.prototype.slice.call(arguments,0));\n\t\t} else {\n\t\t\treturn null\n\t\t}\n\t};\n});\n\n})();\n",
"title": "$:/core/modules/utils/dom/keyboard.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/modal.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/modal.js\ntype: application/javascript\nmodule-type: utils\n\nModal message mechanism\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nvar Modal = function(wiki) {\n\tthis.wiki = wiki;\n\tthis.modalCount = 0;\n};\n\n/*\nDisplay a modal dialogue\n\ttitle: Title of tiddler to display\n\toptions: see below\nOptions include:\n\tdownloadLink: Text of a big download link to include\n*/\nModal.prototype.display = function(title,options) {\n\toptions = options || {};\n\tvar self = this,\n\t\trefreshHandler,\n\t\tduration = $tw.utils.getAnimationDuration(),\n\t\ttiddler = this.wiki.getTiddler(title);\n\t// Don't do anything if the tiddler doesn't exist\n\tif(!tiddler) {\n\t\treturn;\n\t}\n\t// Create the variables\n\tvar variables = $tw.utils.extend({currentTiddler: title},options.variables);\n\t// Create the wrapper divs\n\tvar wrapper = document.createElement(\"div\"),\n\t\tmodalBackdrop = document.createElement(\"div\"),\n\t\tmodalWrapper = document.createElement(\"div\"),\n\t\tmodalHeader = document.createElement(\"div\"),\n\t\theaderTitle = document.createElement(\"h3\"),\n\t\tmodalBody = document.createElement(\"div\"),\n\t\tmodalLink = document.createElement(\"a\"),\n\t\tmodalFooter = document.createElement(\"div\"),\n\t\tmodalFooterHelp = document.createElement(\"span\"),\n\t\tmodalFooterButtons = document.createElement(\"span\");\n\t// Up the modal count and adjust the body class\n\tthis.modalCount++;\n\tthis.adjustPageClass();\n\t// Add classes\n\t$tw.utils.addClass(wrapper,\"tc-modal-wrapper\");\n\t$tw.utils.addClass(modalBackdrop,\"tc-modal-backdrop\");\n\t$tw.utils.addClass(modalWrapper,\"tc-modal\");\n\t$tw.utils.addClass(modalHeader,\"tc-modal-header\");\n\t$tw.utils.addClass(modalBody,\"tc-modal-body\");\n\t$tw.utils.addClass(modalFooter,\"tc-modal-footer\");\n\t// Join them together\n\twrapper.appendChild(modalBackdrop);\n\twrapper.appendChild(modalWrapper);\n\tmodalHeader.appendChild(headerTitle);\n\tmodalWrapper.appendChild(modalHeader);\n\tmodalWrapper.appendChild(modalBody);\n\tmodalFooter.appendChild(modalFooterHelp);\n\tmodalFooter.appendChild(modalFooterButtons);\n\tmodalWrapper.appendChild(modalFooter);\n\t// Render the title of the message\n\tvar headerWidgetNode = this.wiki.makeTranscludeWidget(title,{\n\t\tfield: \"subtitle\",\n\t\tmode: \"inline\",\n\t\tchildren: [{\n\t\t\ttype: \"text\",\n\t\t\tattributes: {\n\t\t\t\ttext: {\n\t\t\t\t\ttype: \"string\",\n\t\t\t\t\tvalue: title\n\t\t}}}],\n\t\tparentWidget: $tw.rootWidget,\n\t\tdocument: document,\n\t\tvariables: variables\n\t});\n\theaderWidgetNode.render(headerTitle,null);\n\t// Render the body of the message\n\tvar bodyWidgetNode = this.wiki.makeTranscludeWidget(title,{\n\t\tparentWidget: $tw.rootWidget,\n\t\tdocument: document,\n\t\tvariables: variables\n\t});\n\tbodyWidgetNode.render(modalBody,null);\n\t// Setup the link if present\n\tif(options.downloadLink) {\n\t\tmodalLink.href = options.downloadLink;\n\t\tmodalLink.appendChild(document.createTextNode(\"Right-click to save changes\"));\n\t\tmodalBody.appendChild(modalLink);\n\t}\n\t// Render the footer of the message\n\tif(tiddler && tiddler.fields && tiddler.fields.help) {\n\t\tvar link = document.createElement(\"a\");\n\t\tlink.setAttribute(\"href\",tiddler.fields.help);\n\t\tlink.setAttribute(\"target\",\"_blank\");\n\t\tlink.setAttribute(\"rel\",\"noopener noreferrer\");\n\t\tlink.appendChild(document.createTextNode(\"Help\"));\n\t\tmodalFooterHelp.appendChild(link);\n\t\tmodalFooterHelp.style.float = \"left\";\n\t}\n\tvar footerWidgetNode = this.wiki.makeTranscludeWidget(title,{\n\t\tfield: \"footer\",\n\t\tmode: \"inline\",\n\t\tchildren: [{\n\t\t\ttype: \"button\",\n\t\t\tattributes: {\n\t\t\t\tmessage: {\n\t\t\t\t\ttype: \"string\",\n\t\t\t\t\tvalue: \"tm-close-tiddler\"\n\t\t\t\t}\n\t\t\t},\n\t\t\tchildren: [{\n\t\t\t\ttype: \"text\",\n\t\t\t\tattributes: {\n\t\t\t\t\ttext: {\n\t\t\t\t\t\ttype: \"string\",\n\t\t\t\t\t\tvalue: $tw.language.getString(\"Buttons/Close/Caption\")\n\t\t\t}}}\n\t\t]}],\n\t\tparentWidget: $tw.rootWidget,\n\t\tdocument: document,\n\t\tvariables: variables\n\t});\n\tfooterWidgetNode.render(modalFooterButtons,null);\n\t// Set up the refresh handler\n\trefreshHandler = function(changes) {\n\t\theaderWidgetNode.refresh(changes,modalHeader,null);\n\t\tbodyWidgetNode.refresh(changes,modalBody,null);\n\t\tfooterWidgetNode.refresh(changes,modalFooterButtons,null);\n\t};\n\tthis.wiki.addEventListener(\"change\",refreshHandler);\n\t// Add the close event handler\n\tvar closeHandler = function(event) {\n\t\t// Remove our refresh handler\n\t\tself.wiki.removeEventListener(\"change\",refreshHandler);\n\t\t// Decrease the modal count and adjust the body class\n\t\tself.modalCount--;\n\t\tself.adjustPageClass();\n\t\t// Force layout and animate the modal message away\n\t\t$tw.utils.forceLayout(modalBackdrop);\n\t\t$tw.utils.forceLayout(modalWrapper);\n\t\t$tw.utils.setStyle(modalBackdrop,[\n\t\t\t{opacity: \"0\"}\n\t\t]);\n\t\t$tw.utils.setStyle(modalWrapper,[\n\t\t\t{transform: \"translateY(\" + window.innerHeight + \"px)\"}\n\t\t]);\n\t\t// Set up an event for the transition end\n\t\twindow.setTimeout(function() {\n\t\t\tif(wrapper.parentNode) {\n\t\t\t\t// Remove the modal message from the DOM\n\t\t\t\tdocument.body.removeChild(wrapper);\n\t\t\t}\n\t\t},duration);\n\t\t// Don't let anyone else handle the tm-close-tiddler message\n\t\treturn false;\n\t};\n\theaderWidgetNode.addEventListener(\"tm-close-tiddler\",closeHandler,false);\n\tbodyWidgetNode.addEventListener(\"tm-close-tiddler\",closeHandler,false);\n\tfooterWidgetNode.addEventListener(\"tm-close-tiddler\",closeHandler,false);\n\t// Set the initial styles for the message\n\t$tw.utils.setStyle(modalBackdrop,[\n\t\t{opacity: \"0\"}\n\t]);\n\t$tw.utils.setStyle(modalWrapper,[\n\t\t{transformOrigin: \"0% 0%\"},\n\t\t{transform: \"translateY(\" + (-window.innerHeight) + \"px)\"}\n\t]);\n\t// Put the message into the document\n\tdocument.body.appendChild(wrapper);\n\t// Set up animation for the styles\n\t$tw.utils.setStyle(modalBackdrop,[\n\t\t{transition: \"opacity \" + duration + \"ms ease-out\"}\n\t]);\n\t$tw.utils.setStyle(modalWrapper,[\n\t\t{transition: $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms ease-in-out\"}\n\t]);\n\t// Force layout\n\t$tw.utils.forceLayout(modalBackdrop);\n\t$tw.utils.forceLayout(modalWrapper);\n\t// Set final animated styles\n\t$tw.utils.setStyle(modalBackdrop,[\n\t\t{opacity: \"0.7\"}\n\t]);\n\t$tw.utils.setStyle(modalWrapper,[\n\t\t{transform: \"translateY(0px)\"}\n\t]);\n};\n\nModal.prototype.adjustPageClass = function() {\n\tif($tw.pageContainer) {\n\t\t$tw.utils.toggleClass($tw.pageContainer,\"tc-modal-displayed\",this.modalCount > 0);\n\t}\n};\n\nexports.Modal = Modal;\n\n})();\n",
"title": "$:/core/modules/utils/dom/modal.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/notifier.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/notifier.js\ntype: application/javascript\nmodule-type: utils\n\nNotifier mechanism\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nvar Notifier = function(wiki) {\n\tthis.wiki = wiki;\n};\n\n/*\nDisplay a notification\n\ttitle: Title of tiddler containing the notification text\n\toptions: see below\nOptions include:\n*/\nNotifier.prototype.display = function(title,options) {\n\toptions = options || {};\n\t// Create the wrapper divs\n\tvar self = this,\n\t\tnotification = document.createElement(\"div\"),\n\t\ttiddler = this.wiki.getTiddler(title),\n\t\tduration = $tw.utils.getAnimationDuration(),\n\t\trefreshHandler;\n\t// Don't do anything if the tiddler doesn't exist\n\tif(!tiddler) {\n\t\treturn;\n\t}\n\t// Add classes\n\t$tw.utils.addClass(notification,\"tc-notification\");\n\t// Create the variables\n\tvar variables = $tw.utils.extend({currentTiddler: title},options.variables);\n\t// Render the body of the notification\n\tvar widgetNode = this.wiki.makeTranscludeWidget(title,{parentWidget: $tw.rootWidget, document: document, variables: variables});\n\twidgetNode.render(notification,null);\n\trefreshHandler = function(changes) {\n\t\twidgetNode.refresh(changes,notification,null);\n\t};\n\tthis.wiki.addEventListener(\"change\",refreshHandler);\n\t// Set the initial styles for the notification\n\t$tw.utils.setStyle(notification,[\n\t\t{opacity: \"0\"},\n\t\t{transformOrigin: \"0% 0%\"},\n\t\t{transform: \"translateY(\" + (-window.innerHeight) + \"px)\"},\n\t\t{transition: \"opacity \" + duration + \"ms ease-out, \" + $tw.utils.roundTripPropertyName(\"transform\") + \" \" + duration + \"ms ease-in-out\"}\n\t]);\n\t// Add the notification to the DOM\n\tdocument.body.appendChild(notification);\n\t// Force layout\n\t$tw.utils.forceLayout(notification);\n\t// Set final animated styles\n\t$tw.utils.setStyle(notification,[\n\t\t{opacity: \"1.0\"},\n\t\t{transform: \"translateY(0px)\"}\n\t]);\n\t// Set a timer to remove the notification\n\twindow.setTimeout(function() {\n\t\t// Remove our change event handler\n\t\tself.wiki.removeEventListener(\"change\",refreshHandler);\n\t\t// Force layout and animate the notification away\n\t\t$tw.utils.forceLayout(notification);\n\t\t$tw.utils.setStyle(notification,[\n\t\t\t{opacity: \"0.0\"},\n\t\t\t{transform: \"translateX(\" + (notification.offsetWidth) + \"px)\"}\n\t\t]);\n\t\t// Remove the modal message from the DOM once the transition ends\n\t\tsetTimeout(function() {\n\t\t\tif(notification.parentNode) {\n\t\t\t\tdocument.body.removeChild(notification);\n\t\t\t}\n\t\t},duration);\n\t},$tw.config.preferences.notificationDuration);\n};\n\nexports.Notifier = Notifier;\n\n})();\n",
"title": "$:/core/modules/utils/dom/notifier.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/popup.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/popup.js\ntype: application/javascript\nmodule-type: utils\n\nModule that creates a $tw.utils.Popup object prototype that manages popups in the browser\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nCreates a Popup object with these options:\n\trootElement: the DOM element to which the popup zapper should be attached\n*/\nvar Popup = function(options) {\n\toptions = options || {};\n\tthis.rootElement = options.rootElement || document.documentElement;\n\tthis.popups = []; // Array of {title:,wiki:,domNode:} objects\n};\n\n/*\nTrigger a popup open or closed. Parameters are in a hashmap:\n\ttitle: title of the tiddler where the popup details are stored\n\tdomNode: dom node to which the popup will be positioned\n\twiki: wiki\n\tforce: if specified, forces the popup state to true or false (instead of toggling it)\n*/\nPopup.prototype.triggerPopup = function(options) {\n\t// Check if this popup is already active\n\tvar index = this.findPopup(options.title);\n\t// Compute the new state\n\tvar state = index === -1;\n\tif(options.force !== undefined) {\n\t\tstate = options.force;\n\t}\n\t// Show or cancel the popup according to the new state\n\tif(state) {\n\t\tthis.show(options);\n\t} else {\n\t\tthis.cancel(index);\n\t}\n};\n\nPopup.prototype.findPopup = function(title) {\n\tvar index = -1;\n\tfor(var t=0; t<this.popups.length; t++) {\n\t\tif(this.popups[t].title === title) {\n\t\t\tindex = t;\n\t\t}\n\t}\n\treturn index;\n};\n\nPopup.prototype.handleEvent = function(event) {\n\tif(event.type === \"click\") {\n\t\t// Find out what was clicked on\n\t\tvar info = this.popupInfo(event.target),\n\t\t\tcancelLevel = info.popupLevel - 1;\n\t\t// Don't remove the level that was clicked on if we clicked on a handle\n\t\tif(info.isHandle) {\n\t\t\tcancelLevel++;\n\t\t}\n\t\t// Cancel\n\t\tthis.cancel(cancelLevel);\n\t}\n};\n\n/*\nFind the popup level containing a DOM node. Returns:\npopupLevel: count of the number of nested popups containing the specified element\nisHandle: true if the specified element is within a popup handle\n*/\nPopup.prototype.popupInfo = function(domNode) {\n\tvar isHandle = false,\n\t\tpopupCount = 0,\n\t\tnode = domNode;\n\t// First check ancestors to see if we're within a popup handle\n\twhile(node) {\n\t\tif($tw.utils.hasClass(node,\"tc-popup-handle\")) {\n\t\t\tisHandle = true;\n\t\t\tpopupCount++;\n\t\t}\n\t\tif($tw.utils.hasClass(node,\"tc-popup-keep\")) {\n\t\t\tisHandle = true;\n\t\t}\n\t\tnode = node.parentNode;\n\t}\n\t// Then count the number of ancestor popups\n\tnode = domNode;\n\twhile(node) {\n\t\tif($tw.utils.hasClass(node,\"tc-popup\")) {\n\t\t\tpopupCount++;\n\t\t}\n\t\tnode = node.parentNode;\n\t}\n\tvar info = {\n\t\tpopupLevel: popupCount,\n\t\tisHandle: isHandle\n\t};\n\treturn info;\n};\n\n/*\nDisplay a popup by adding it to the stack\n*/\nPopup.prototype.show = function(options) {\n\t// Find out what was clicked on\n\tvar info = this.popupInfo(options.domNode);\n\t// Cancel any higher level popups\n\tthis.cancel(info.popupLevel);\n\t// Store the popup details if not already there\n\tif(this.findPopup(options.title) === -1) {\n\t\tthis.popups.push({\n\t\t\ttitle: options.title,\n\t\t\twiki: options.wiki,\n\t\t\tdomNode: options.domNode\n\t\t});\n\t}\n\t// Set the state tiddler\n\toptions.wiki.setTextReference(options.title,\n\t\t\t\"(\" + options.domNode.offsetLeft + \",\" + options.domNode.offsetTop + \",\" + \n\t\t\t\toptions.domNode.offsetWidth + \",\" + options.domNode.offsetHeight + \")\");\n\t// Add the click handler if we have any popups\n\tif(this.popups.length > 0) {\n\t\tthis.rootElement.addEventListener(\"click\",this,true);\t\t\n\t}\n};\n\n/*\nCancel all popups at or above a specified level or DOM node\nlevel: popup level to cancel (0 cancels all popups)\n*/\nPopup.prototype.cancel = function(level) {\n\tvar numPopups = this.popups.length;\n\tlevel = Math.max(0,Math.min(level,numPopups));\n\tfor(var t=level; t<numPopups; t++) {\n\t\tvar popup = this.popups.pop();\n\t\tif(popup.title) {\n\t\t\tpopup.wiki.deleteTiddler(popup.title);\n\t\t}\n\t}\n\tif(this.popups.length === 0) {\n\t\tthis.rootElement.removeEventListener(\"click\",this,false);\n\t}\n};\n\n/*\nReturns true if the specified title and text identifies an active popup\n*/\nPopup.prototype.readPopupState = function(text) {\n\tvar popupLocationRegExp = /^\\((-?[0-9\\.E]+),(-?[0-9\\.E]+),(-?[0-9\\.E]+),(-?[0-9\\.E]+)\\)$/;\n\treturn popupLocationRegExp.test(text);\n};\n\nexports.Popup = Popup;\n\n})();\n",
"title": "$:/core/modules/utils/dom/popup.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/dom/scroller.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/dom/scroller.js\ntype: application/javascript\nmodule-type: utils\n\nModule that creates a $tw.utils.Scroller object prototype that manages scrolling in the browser\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nEvent handler for when the `tm-scroll` event hits the document body\n*/\nvar PageScroller = function() {\n\tthis.idRequestFrame = null;\n\tthis.requestAnimationFrame = window.requestAnimationFrame ||\n\t\twindow.webkitRequestAnimationFrame ||\n\t\twindow.mozRequestAnimationFrame ||\n\t\tfunction(callback) {\n\t\t\treturn window.setTimeout(callback, 1000/60);\n\t\t};\n\tthis.cancelAnimationFrame = window.cancelAnimationFrame ||\n\t\twindow.webkitCancelAnimationFrame ||\n\t\twindow.webkitCancelRequestAnimationFrame ||\n\t\twindow.mozCancelAnimationFrame ||\n\t\twindow.mozCancelRequestAnimationFrame ||\n\t\tfunction(id) {\n\t\t\twindow.clearTimeout(id);\n\t\t};\n};\n\nPageScroller.prototype.cancelScroll = function() {\n\tif(this.idRequestFrame) {\n\t\tthis.cancelAnimationFrame.call(window,this.idRequestFrame);\n\t\tthis.idRequestFrame = null;\n\t}\n};\n\n/*\nHandle an event\n*/\nPageScroller.prototype.handleEvent = function(event) {\n\tif(event.type === \"tm-scroll\") {\n\t\treturn this.scrollIntoView(event.target);\n\t}\n\treturn true;\n};\n\n/*\nHandle a scroll event hitting the page document\n*/\nPageScroller.prototype.scrollIntoView = function(element) {\n\tvar duration = $tw.utils.getAnimationDuration();\n\t// Now get ready to scroll the body\n\tthis.cancelScroll();\n\tthis.startTime = Date.now();\n\tvar scrollPosition = $tw.utils.getScrollPosition();\n\t// Get the client bounds of the element and adjust by the scroll position\n\tvar clientBounds = element.getBoundingClientRect(),\n\t\tbounds = {\n\t\t\tleft: clientBounds.left + scrollPosition.x,\n\t\t\ttop: clientBounds.top + scrollPosition.y,\n\t\t\twidth: clientBounds.width,\n\t\t\theight: clientBounds.height\n\t\t};\n\t// We'll consider the horizontal and vertical scroll directions separately via this function\n\t// targetPos/targetSize - position and size of the target element\n\t// currentPos/currentSize - position and size of the current scroll viewport\n\t// returns: new position of the scroll viewport\n\tvar getEndPos = function(targetPos,targetSize,currentPos,currentSize) {\n\t\t\tvar newPos = currentPos;\n\t\t\t// If the target is above/left of the current view, then scroll to it's top/left\n\t\t\tif(targetPos <= currentPos) {\n\t\t\t\tnewPos = targetPos;\n\t\t\t// If the target is smaller than the window and the scroll position is too far up, then scroll till the target is at the bottom of the window\n\t\t\t} else if(targetSize < currentSize && currentPos < (targetPos + targetSize - currentSize)) {\n\t\t\t\tnewPos = targetPos + targetSize - currentSize;\n\t\t\t// If the target is big, then just scroll to the top\n\t\t\t} else if(currentPos < targetPos) {\n\t\t\t\tnewPos = targetPos;\n\t\t\t// Otherwise, stay where we are\n\t\t\t} else {\n\t\t\t\tnewPos = currentPos;\n\t\t\t}\n\t\t\t// If we are scrolling within 50 pixels of the top/left then snap to zero\n\t\t\tif(newPos < 50) {\n\t\t\t\tnewPos = 0;\n\t\t\t}\n\t\t\treturn newPos;\n\t\t},\n\t\tendX = getEndPos(bounds.left,bounds.width,scrollPosition.x,window.innerWidth),\n\t\tendY = getEndPos(bounds.top,bounds.height,scrollPosition.y,window.innerHeight);\n\t// Only scroll if the position has changed\n\tif(endX !== scrollPosition.x || endY !== scrollPosition.y) {\n\t\tvar self = this,\n\t\t\tdrawFrame;\n\t\tdrawFrame = function () {\n\t\t\tvar t;\n\t\t\tif(duration <= 0) {\n\t\t\t\tt = 1;\n\t\t\t} else {\n\t\t\t\tt = ((Date.now()) - self.startTime) / duration;\t\n\t\t\t}\n\t\t\tif(t >= 1) {\n\t\t\t\tself.cancelScroll();\n\t\t\t\tt = 1;\n\t\t\t}\n\t\t\tt = $tw.utils.slowInSlowOut(t);\n\t\t\twindow.scrollTo(scrollPosition.x + (endX - scrollPosition.x) * t,scrollPosition.y + (endY - scrollPosition.y) * t);\n\t\t\tif(t < 1) {\n\t\t\t\tself.idRequestFrame = self.requestAnimationFrame.call(window,drawFrame);\n\t\t\t}\n\t\t};\n\t\tdrawFrame();\n\t}\n};\n\nexports.PageScroller = PageScroller;\n\n})();\n",
"title": "$:/core/modules/utils/dom/scroller.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/edition-info.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/edition-info.js\ntype: application/javascript\nmodule-type: utils-node\n\nInformation about the available editions\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar fs = require(\"fs\"),\n\tpath = require(\"path\");\n\nvar editionInfo;\n\nexports.getEditionInfo = function() {\n\tif(!editionInfo) {\n\t\t// Enumerate the edition paths\n\t\tvar editionPaths = $tw.getLibraryItemSearchPaths($tw.config.editionsPath,$tw.config.editionsEnvVar);\n\t\teditionInfo = {};\n\t\tfor(var editionIndex=0; editionIndex<editionPaths.length; editionIndex++) {\n\t\t\tvar editionPath = editionPaths[editionIndex];\n\t\t\t// Enumerate the folders\n\t\t\tvar entries = fs.readdirSync(editionPath);\n\t\t\tfor(var entryIndex=0; entryIndex<entries.length; entryIndex++) {\n\t\t\t\tvar entry = entries[entryIndex];\n\t\t\t\t// Check if directories have a valid tiddlywiki.info\n\t\t\t\tif(!editionInfo[entry] && $tw.utils.isDirectory(path.resolve(editionPath,entry))) {\n\t\t\t\t\tvar info;\n\t\t\t\t\ttry {\n\t\t\t\t\t\tinfo = JSON.parse(fs.readFileSync(path.resolve(editionPath,entry,\"tiddlywiki.info\"),\"utf8\"));\n\t\t\t\t\t} catch(ex) {\n\t\t\t\t\t}\n\t\t\t\t\tif(info) {\n\t\t\t\t\t\teditionInfo[entry] = info;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\treturn editionInfo;\n};\n\n})();\n",
"title": "$:/core/modules/utils/edition-info.js",
"type": "application/javascript",
"module-type": "utils-node"
},
"$:/core/modules/utils/fakedom.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/fakedom.js\ntype: application/javascript\nmodule-type: global\n\nA barebones implementation of DOM interfaces needed by the rendering mechanism.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Sequence number used to enable us to track objects for testing\nvar sequenceNumber = null;\n\nvar bumpSequenceNumber = function(object) {\n\tif(sequenceNumber !== null) {\n\t\tobject.sequenceNumber = sequenceNumber++;\n\t}\n};\n\nvar TW_TextNode = function(text) {\n\tbumpSequenceNumber(this);\n\tthis.textContent = text;\n};\n\nObject.defineProperty(TW_TextNode.prototype, \"nodeType\", {\n\tget: function() {\n\t\treturn 3;\n\t}\n});\n\nObject.defineProperty(TW_TextNode.prototype, \"formattedTextContent\", {\n\tget: function() {\n\t\treturn this.textContent.replace(/(\\r?\\n)/g,\"\");\n\t}\n});\n\nvar TW_Element = function(tag,namespace) {\n\tbumpSequenceNumber(this);\n\tthis.isTiddlyWikiFakeDom = true;\n\tthis.tag = tag;\n\tthis.attributes = {};\n\tthis.isRaw = false;\n\tthis.children = [];\n\tthis.style = {};\n\tthis.namespaceURI = namespace || \"http://www.w3.org/1999/xhtml\";\n};\n\nObject.defineProperty(TW_Element.prototype, \"nodeType\", {\n\tget: function() {\n\t\treturn 1;\n\t}\n});\n\nTW_Element.prototype.getAttribute = function(name) {\n\tif(this.isRaw) {\n\t\tthrow \"Cannot getAttribute on a raw TW_Element\";\n\t}\n\treturn this.attributes[name];\n};\n\nTW_Element.prototype.setAttribute = function(name,value) {\n\tif(this.isRaw) {\n\t\tthrow \"Cannot setAttribute on a raw TW_Element\";\n\t}\n\tthis.attributes[name] = value;\n};\n\nTW_Element.prototype.setAttributeNS = function(namespace,name,value) {\n\tthis.setAttribute(name,value);\n};\n\nTW_Element.prototype.removeAttribute = function(name) {\n\tif(this.isRaw) {\n\t\tthrow \"Cannot removeAttribute on a raw TW_Element\";\n\t}\n\tif($tw.utils.hop(this.attributes,name)) {\n\t\tdelete this.attributes[name];\n\t}\n};\n\nTW_Element.prototype.appendChild = function(node) {\n\tthis.children.push(node);\n\tnode.parentNode = this;\n};\n\nTW_Element.prototype.insertBefore = function(node,nextSibling) {\n\tif(nextSibling) {\n\t\tvar p = this.children.indexOf(nextSibling);\n\t\tif(p !== -1) {\n\t\t\tthis.children.splice(p,0,node);\n\t\t\tnode.parentNode = this;\n\t\t} else {\n\t\t\tthis.appendChild(node);\n\t\t}\n\t} else {\n\t\tthis.appendChild(node);\n\t}\n};\n\nTW_Element.prototype.removeChild = function(node) {\n\tvar p = this.children.indexOf(node);\n\tif(p !== -1) {\n\t\tthis.children.splice(p,1);\n\t}\n};\n\nTW_Element.prototype.hasChildNodes = function() {\n\treturn !!this.children.length;\n};\n\nObject.defineProperty(TW_Element.prototype, \"childNodes\", {\n\tget: function() {\n\t\treturn this.children;\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"firstChild\", {\n\tget: function() {\n\t\treturn this.children[0];\n\t}\n});\n\nTW_Element.prototype.addEventListener = function(type,listener,useCapture) {\n\t// Do nothing\n};\n\nObject.defineProperty(TW_Element.prototype, \"tagName\", {\n\tget: function() {\n\t\treturn this.tag || \"\";\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"className\", {\n\tget: function() {\n\t\treturn this.attributes[\"class\"] || \"\";\n\t},\n\tset: function(value) {\n\t\tthis.attributes[\"class\"] = value;\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"value\", {\n\tget: function() {\n\t\treturn this.attributes.value || \"\";\n\t},\n\tset: function(value) {\n\t\tthis.attributes.value = value;\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"outerHTML\", {\n\tget: function() {\n\t\tvar output = [],attr,a,v;\n\t\toutput.push(\"<\",this.tag);\n\t\tif(this.attributes) {\n\t\t\tattr = [];\n\t\t\tfor(a in this.attributes) {\n\t\t\t\tattr.push(a);\n\t\t\t}\n\t\t\tattr.sort();\n\t\t\tfor(a=0; a<attr.length; a++) {\n\t\t\t\tv = this.attributes[attr[a]];\n\t\t\t\tif(v !== undefined) {\n\t\t\t\t\toutput.push(\" \",attr[a],\"=\\\"\",$tw.utils.htmlEncode(v),\"\\\"\");\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tif(this.style) {\n\t\t\tvar style = [];\n\t\t\tfor(var s in this.style) {\n\t\t\t\tstyle.push(s + \":\" + this.style[s] + \";\");\n\t\t\t}\n\t\t\tif(style.length > 0) {\n\t\t\t\toutput.push(\" style=\\\"\",style.join(\"\"),\"\\\"\")\n\t\t\t}\n\t\t}\n\t\toutput.push(\">\");\n\t\tif($tw.config.htmlVoidElements.indexOf(this.tag) === -1) {\n\t\t\toutput.push(this.innerHTML);\n\t\t\toutput.push(\"</\",this.tag,\">\");\n\t\t}\n\t\treturn output.join(\"\");\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"innerHTML\", {\n\tget: function() {\n\t\tif(this.isRaw) {\n\t\t\treturn this.rawHTML;\n\t\t} else {\n\t\t\tvar b = [];\n\t\t\t$tw.utils.each(this.children,function(node) {\n\t\t\t\tif(node instanceof TW_Element) {\n\t\t\t\t\tb.push(node.outerHTML);\n\t\t\t\t} else if(node instanceof TW_TextNode) {\n\t\t\t\t\tb.push($tw.utils.htmlEncode(node.textContent));\n\t\t\t\t}\n\t\t\t});\n\t\t\treturn b.join(\"\");\n\t\t}\n\t},\n\tset: function(value) {\n\t\tthis.isRaw = true;\n\t\tthis.rawHTML = value;\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"textContent\", {\n\tget: function() {\n\t\tif(this.isRaw) {\n\t\t\tthrow \"Cannot get textContent on a raw TW_Element\";\n\t\t} else {\n\t\t\tvar b = [];\n\t\t\t$tw.utils.each(this.children,function(node) {\n\t\t\t\tb.push(node.textContent);\n\t\t\t});\n\t\t\treturn b.join(\"\");\n\t\t}\n\t},\n\tset: function(value) {\n\t\tthis.children = [new TW_TextNode(value)];\n\t}\n});\n\nObject.defineProperty(TW_Element.prototype, \"formattedTextContent\", {\n\tget: function() {\n\t\tif(this.isRaw) {\n\t\t\tthrow \"Cannot get formattedTextContent on a raw TW_Element\";\n\t\t} else {\n\t\t\tvar b = [],\n\t\t\t\tisBlock = $tw.config.htmlBlockElements.indexOf(this.tag) !== -1;\n\t\t\tif(isBlock) {\n\t\t\t\tb.push(\"\\n\");\n\t\t\t}\n\t\t\tif(this.tag === \"li\") {\n\t\t\t\tb.push(\"* \");\n\t\t\t}\n\t\t\t$tw.utils.each(this.children,function(node) {\n\t\t\t\tb.push(node.formattedTextContent);\n\t\t\t});\n\t\t\tif(isBlock) {\n\t\t\t\tb.push(\"\\n\");\n\t\t\t}\n\t\t\treturn b.join(\"\");\n\t\t}\n\t}\n});\n\nvar document = {\n\tsetSequenceNumber: function(value) {\n\t\tsequenceNumber = value;\n\t},\n\tcreateElementNS: function(namespace,tag) {\n\t\treturn new TW_Element(tag,namespace);\n\t},\n\tcreateElement: function(tag) {\n\t\treturn new TW_Element(tag);\n\t},\n\tcreateTextNode: function(text) {\n\t\treturn new TW_TextNode(text);\n\t},\n\tcompatMode: \"CSS1Compat\", // For KaTeX to know that we're not a browser in quirks mode\n\tisTiddlyWikiFakeDom: true\n};\n\nexports.fakeDocument = document;\n\n})();\n",
"title": "$:/core/modules/utils/fakedom.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/utils/filesystem.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/filesystem.js\ntype: application/javascript\nmodule-type: utils-node\n\nFile system utilities\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar fs = require(\"fs\"),\n\tpath = require(\"path\");\n\n/*\nRecursively (and synchronously) copy a directory and all its content\n*/\nexports.copyDirectory = function(srcPath,dstPath) {\n\t// Remove any trailing path separators\n\tsrcPath = $tw.utils.removeTrailingSeparator(srcPath);\n\tdstPath = $tw.utils.removeTrailingSeparator(dstPath);\n\t// Create the destination directory\n\tvar err = $tw.utils.createDirectory(dstPath);\n\tif(err) {\n\t\treturn err;\n\t}\n\t// Function to copy a folder full of files\n\tvar copy = function(srcPath,dstPath) {\n\t\tvar srcStats = fs.lstatSync(srcPath),\n\t\t\tdstExists = fs.existsSync(dstPath);\n\t\tif(srcStats.isFile()) {\n\t\t\t$tw.utils.copyFile(srcPath,dstPath);\n\t\t} else if(srcStats.isDirectory()) {\n\t\t\tvar items = fs.readdirSync(srcPath);\n\t\t\tfor(var t=0; t<items.length; t++) {\n\t\t\t\tvar item = items[t],\n\t\t\t\t\terr = copy(srcPath + path.sep + item,dstPath + path.sep + item);\n\t\t\t\tif(err) {\n\t\t\t\t\treturn err;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t};\n\tcopy(srcPath,dstPath);\n\treturn null;\n};\n\n/*\nCopy a file\n*/\nvar FILE_BUFFER_LENGTH = 64 * 1024,\n\tfileBuffer;\n\nexports.copyFile = function(srcPath,dstPath) {\n\t// Create buffer if required\n\tif(!fileBuffer) {\n\t\tfileBuffer = new Buffer(FILE_BUFFER_LENGTH);\n\t}\n\t// Create any directories in the destination\n\t$tw.utils.createDirectory(path.dirname(dstPath));\n\t// Copy the file\n\tvar srcFile = fs.openSync(srcPath,\"r\"),\n\t\tdstFile = fs.openSync(dstPath,\"w\"),\n\t\tbytesRead = 1,\n\t\tpos = 0;\n\twhile (bytesRead > 0) {\n\t\tbytesRead = fs.readSync(srcFile,fileBuffer,0,FILE_BUFFER_LENGTH,pos);\n\t\tfs.writeSync(dstFile,fileBuffer,0,bytesRead);\n\t\tpos += bytesRead;\n\t}\n\tfs.closeSync(srcFile);\n\tfs.closeSync(dstFile);\n\treturn null;\n};\n\n/*\nRemove trailing path separator\n*/\nexports.removeTrailingSeparator = function(dirPath) {\n\tvar len = dirPath.length;\n\tif(dirPath.charAt(len-1) === path.sep) {\n\t\tdirPath = dirPath.substr(0,len-1);\n\t}\n\treturn dirPath;\n};\n\n/*\nRecursively create a directory\n*/\nexports.createDirectory = function(dirPath) {\n\tif(dirPath.substr(dirPath.length-1,1) !== path.sep) {\n\t\tdirPath = dirPath + path.sep;\n\t}\n\tvar pos = 1;\n\tpos = dirPath.indexOf(path.sep,pos);\n\twhile(pos !== -1) {\n\t\tvar subDirPath = dirPath.substr(0,pos);\n\t\tif(!$tw.utils.isDirectory(subDirPath)) {\n\t\t\ttry {\n\t\t\t\tfs.mkdirSync(subDirPath);\n\t\t\t} catch(e) {\n\t\t\t\treturn \"Error creating directory '\" + subDirPath + \"'\";\n\t\t\t}\n\t\t}\n\t\tpos = dirPath.indexOf(path.sep,pos + 1);\n\t}\n\treturn null;\n};\n\n/*\nRecursively create directories needed to contain a specified file\n*/\nexports.createFileDirectories = function(filePath) {\n\treturn $tw.utils.createDirectory(path.dirname(filePath));\n};\n\n/*\nRecursively delete a directory\n*/\nexports.deleteDirectory = function(dirPath) {\n\tif(fs.existsSync(dirPath)) {\n\t\tvar entries = fs.readdirSync(dirPath);\n\t\tfor(var entryIndex=0; entryIndex<entries.length; entryIndex++) {\n\t\t\tvar currPath = dirPath + path.sep + entries[entryIndex];\n\t\t\tif(fs.lstatSync(currPath).isDirectory()) {\n\t\t\t\t$tw.utils.deleteDirectory(currPath);\n\t\t\t} else {\n\t\t\t\tfs.unlinkSync(currPath);\n\t\t\t}\n\t\t}\n\tfs.rmdirSync(dirPath);\n\t}\n\treturn null;\n};\n\n/*\nCheck if a path identifies a directory\n*/\nexports.isDirectory = function(dirPath) {\n\treturn fs.existsSync(dirPath) && fs.statSync(dirPath).isDirectory();\n};\n\n/*\nCheck if a path identifies a directory that is empty\n*/\nexports.isDirectoryEmpty = function(dirPath) {\n\tif(!$tw.utils.isDirectory(dirPath)) {\n\t\treturn false;\n\t}\n\tvar files = fs.readdirSync(dirPath),\n\t\tempty = true;\n\t$tw.utils.each(files,function(file,index) {\n\t\tif(file.charAt(0) !== \".\") {\n\t\t\tempty = false;\n\t\t}\n\t});\n\treturn empty;\n};\n\n/*\nRecursively delete a tree of empty directories\n*/\nexports.deleteEmptyDirs = function(dirpath,callback) {\n\tvar self = this;\n\tfs.readdir(dirpath,function(err,files) {\n\t\tif(err) {\n\t\t\treturn callback(err);\n\t\t}\n\t\tif(files.length > 0) {\n\t\t\treturn callback(null);\n\t\t}\n\t\tfs.rmdir(dirpath,function(err) {\n\t\t\tif(err) {\n\t\t\t\treturn callback(err);\n\t\t\t}\n\t\t\tself.deleteEmptyDirs(path.dirname(dirpath),callback);\n\t\t});\n\t});\n};\n\n})();\n",
"title": "$:/core/modules/utils/filesystem.js",
"type": "application/javascript",
"module-type": "utils-node"
},
"$:/core/modules/utils/logger.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/logger.js\ntype: application/javascript\nmodule-type: utils\n\nA basic logging implementation\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar ALERT_TAG = \"$:/tags/Alert\";\n\n/*\nMake a new logger\n*/\nfunction Logger(componentName) {\n\tthis.componentName = componentName || \"\";\n}\n\n/*\nLog a message\n*/\nLogger.prototype.log = function(/* args */) {\n\tif(console !== undefined && console.log !== undefined) {\n\t\treturn Function.apply.call(console.log, console, [this.componentName + \":\"].concat(Array.prototype.slice.call(arguments,0)));\n\t}\n};\n\n/*\nAlert a message\n*/\nLogger.prototype.alert = function(/* args */) {\n\t// Prepare the text of the alert\n\tvar text = Array.prototype.join.call(arguments,\" \");\n\t// Create alert tiddlers in the browser\n\tif($tw.browser) {\n\t\t// Check if there is an existing alert with the same text and the same component\n\t\tvar existingAlerts = $tw.wiki.getTiddlersWithTag(ALERT_TAG),\n\t\t\talertFields,\n\t\t\texistingCount,\n\t\t\tself = this;\n\t\t$tw.utils.each(existingAlerts,function(title) {\n\t\t\tvar tiddler = $tw.wiki.getTiddler(title);\n\t\t\tif(tiddler.fields.text === text && tiddler.fields.component === self.componentName && tiddler.fields.modified && (!alertFields || tiddler.fields.modified < alertFields.modified)) {\n\t\t\t\t\talertFields = $tw.utils.extend({},tiddler.fields);\n\t\t\t}\n\t\t});\n\t\tif(alertFields) {\n\t\t\texistingCount = alertFields.count || 1;\n\t\t} else {\n\t\t\talertFields = {\n\t\t\t\ttitle: $tw.wiki.generateNewTitle(\"$:/temp/alerts/alert\",{prefix: \"\"}),\n\t\t\t\ttext: text,\n\t\t\t\ttags: [ALERT_TAG],\n\t\t\t\tcomponent: this.componentName\n\t\t\t};\n\t\t\texistingCount = 0;\n\t\t}\n\t\talertFields.modified = new Date();\n\t\tif(++existingCount > 1) {\n\t\t\talertFields.count = existingCount;\n\t\t} else {\n\t\t\talertFields.count = undefined;\n\t\t}\n\t\t$tw.wiki.addTiddler(new $tw.Tiddler(alertFields));\n\t\t// Log the alert as well\n\t\tthis.log.apply(this,Array.prototype.slice.call(arguments,0));\n\t} else {\n\t\t// Print an orange message to the console if not in the browser\n\t\tconsole.error(\"\\x1b[1;33m\" + text + \"\\x1b[0m\");\n\t}\n};\n\nexports.Logger = Logger;\n\n})();\n",
"title": "$:/core/modules/utils/logger.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/parsetree.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/parsetree.js\ntype: application/javascript\nmodule-type: utils\n\nParse tree utility functions.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.addAttributeToParseTreeNode = function(node,name,value) {\n\tnode.attributes = node.attributes || {};\n\tnode.attributes[name] = {type: \"string\", value: value};\n};\n\nexports.getAttributeValueFromParseTreeNode = function(node,name,defaultValue) {\n\tif(node.attributes && node.attributes[name] && node.attributes[name].value !== undefined) {\n\t\treturn node.attributes[name].value;\n\t}\n\treturn defaultValue;\n};\n\nexports.addClassToParseTreeNode = function(node,classString) {\n\tvar classes = [];\n\tnode.attributes = node.attributes || {};\n\tnode.attributes[\"class\"] = node.attributes[\"class\"] || {type: \"string\", value: \"\"};\n\tif(node.attributes[\"class\"].type === \"string\") {\n\t\tif(node.attributes[\"class\"].value !== \"\") {\n\t\t\tclasses = node.attributes[\"class\"].value.split(\" \");\n\t\t}\n\t\tif(classString !== \"\") {\n\t\t\t$tw.utils.pushTop(classes,classString.split(\" \"));\n\t\t}\n\t\tnode.attributes[\"class\"].value = classes.join(\" \");\n\t}\n};\n\nexports.addStyleToParseTreeNode = function(node,name,value) {\n\t\tnode.attributes = node.attributes || {};\n\t\tnode.attributes.style = node.attributes.style || {type: \"string\", value: \"\"};\n\t\tif(node.attributes.style.type === \"string\") {\n\t\t\tnode.attributes.style.value += name + \":\" + value + \";\";\n\t\t}\n};\n\nexports.findParseTreeNode = function(nodeArray,search) {\n\tfor(var t=0; t<nodeArray.length; t++) {\n\t\tif(nodeArray[t].type === search.type && nodeArray[t].tag === search.tag) {\n\t\t\treturn nodeArray[t];\n\t\t}\n\t}\n\treturn undefined;\n};\n\n/*\nHelper to get the text of a parse tree node or array of nodes\n*/\nexports.getParseTreeText = function getParseTreeText(tree) {\n\tvar output = [];\n\tif($tw.utils.isArray(tree)) {\n\t\t$tw.utils.each(tree,function(node) {\n\t\t\toutput.push(getParseTreeText(node));\n\t\t});\n\t} else {\n\t\tif(tree.type === \"text\") {\n\t\t\toutput.push(tree.text);\n\t\t}\n\t\tif(tree.children) {\n\t\t\treturn getParseTreeText(tree.children);\n\t\t}\n\t}\n\treturn output.join(\"\");\n};\n\n})();\n",
"title": "$:/core/modules/utils/parsetree.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/performance.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/performance.js\ntype: application/javascript\nmodule-type: global\n\nPerformance measurement.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nfunction Performance(enabled) {\n\tthis.enabled = !!enabled;\n\tthis.measures = {}; // Hashmap of current values of measurements\n\tthis.logger = new $tw.utils.Logger(\"performance\");\n}\n\n/*\nWrap performance reporting around a top level function\n*/\nPerformance.prototype.report = function(name,fn) {\n\tvar self = this;\n\tif(this.enabled) {\n\t\treturn function() {\n\t\t\tself.measures = {};\n\t\t\tvar startTime = $tw.utils.timer(),\n\t\t\t\tresult = fn.apply(this,arguments);\n\t\t\tself.logger.log(name + \": \" + $tw.utils.timer(startTime).toFixed(2) + \"ms\");\n\t\t\tfor(var m in self.measures) {\n\t\t\t\tself.logger.log(\"+\" + m + \": \" + self.measures[m].toFixed(2) + \"ms\");\n\t\t\t}\n\t\t\treturn result;\n\t\t};\n\t} else {\n\t\treturn fn;\n\t}\n};\n\n/*\nWrap performance measurements around a subfunction\n*/\nPerformance.prototype.measure = function(name,fn) {\n\tvar self = this;\n\tif(this.enabled) {\n\t\treturn function() {\n\t\t\tvar startTime = $tw.utils.timer(),\n\t\t\t\tresult = fn.apply(this,arguments),\n\t\t\t\tvalue = self.measures[name] || 0;\n\t\t\tself.measures[name] = value + $tw.utils.timer(startTime);\n\t\t\treturn result;\n\t\t};\n\t} else {\n\t\treturn fn;\n\t}\n};\n\nexports.Performance = Performance;\n\n})();\n",
"title": "$:/core/modules/utils/performance.js",
"type": "application/javascript",
"module-type": "global"
},
"$:/core/modules/utils/pluginmaker.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/pluginmaker.js\ntype: application/javascript\nmodule-type: utils\n\nA quick and dirty way to pack up plugins within the browser.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nRepack a plugin, and then delete any non-shadow payload tiddlers\n*/\nexports.repackPlugin = function(title,additionalTiddlers,excludeTiddlers) {\n\tadditionalTiddlers = additionalTiddlers || [];\n\texcludeTiddlers = excludeTiddlers || [];\n\t// Get the plugin tiddler\n\tvar pluginTiddler = $tw.wiki.getTiddler(title);\n\tif(!pluginTiddler) {\n\t\tthrow \"No such tiddler as \" + title;\n\t}\n\t// Extract the JSON\n\tvar jsonPluginTiddler;\n\ttry {\n\t\tjsonPluginTiddler = JSON.parse(pluginTiddler.fields.text);\n\t} catch(e) {\n\t\tthrow \"Cannot parse plugin tiddler \" + title + \"\\n\" + $tw.language.getString(\"Error/Caption\") + \": \" + e;\n\t}\n\t// Get the list of tiddlers\n\tvar tiddlers = Object.keys(jsonPluginTiddler.tiddlers);\n\t// Add the additional tiddlers\n\t$tw.utils.pushTop(tiddlers,additionalTiddlers);\n\t// Remove any excluded tiddlers\n\tfor(var t=tiddlers.length-1; t>=0; t--) {\n\t\tif(excludeTiddlers.indexOf(tiddlers[t]) !== -1) {\n\t\t\ttiddlers.splice(t,1);\n\t\t}\n\t}\n\t// Pack up the tiddlers into a block of JSON\n\tvar plugins = {};\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar tiddler = $tw.wiki.getTiddler(title),\n\t\t\tfields = {};\n\t\t$tw.utils.each(tiddler.fields,function (value,name) {\n\t\t\tfields[name] = tiddler.getFieldString(name);\n\t\t});\n\t\tplugins[title] = fields;\n\t});\n\t// Retrieve and bump the version number\n\tvar pluginVersion = $tw.utils.parseVersion(pluginTiddler.getFieldString(\"version\") || \"0.0.0\") || {\n\t\t\tmajor: \"0\",\n\t\t\tminor: \"0\",\n\t\t\tpatch: \"0\"\n\t\t};\n\tpluginVersion.patch++;\n\tvar version = pluginVersion.major + \".\" + pluginVersion.minor + \".\" + pluginVersion.patch;\n\tif(pluginVersion.prerelease) {\n\t\tversion += \"-\" + pluginVersion.prerelease;\n\t}\n\tif(pluginVersion.build) {\n\t\tversion += \"+\" + pluginVersion.build;\n\t}\n\t// Save the tiddler\n\t$tw.wiki.addTiddler(new $tw.Tiddler(pluginTiddler,{text: JSON.stringify({tiddlers: plugins},null,4), version: version}));\n\t// Delete any non-shadow constituent tiddlers\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tif($tw.wiki.tiddlerExists(title)) {\n\t\t\t$tw.wiki.deleteTiddler(title);\n\t\t}\n\t});\n\t// Trigger an autosave\n\t$tw.rootWidget.dispatchEvent({type: \"tm-auto-save-wiki\"});\n\t// Return a heartwarming confirmation\n\treturn \"Plugin \" + title + \" successfully saved\";\n};\n\n})();\n",
"title": "$:/core/modules/utils/pluginmaker.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/utils/utils.js": {
"text": "/*\\\ntitle: $:/core/modules/utils/utils.js\ntype: application/javascript\nmodule-type: utils\n\nVarious static utility functions.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nDisplay a warning, in colour if we're on a terminal\n*/\nexports.warning = function(text) {\n\tconsole.log($tw.node ? \"\\x1b[1;33m\" + text + \"\\x1b[0m\" : text);\n};\n\n/*\nRepeats a string\n*/\nexports.repeat = function(str,count) {\n\tvar result = \"\";\n\tfor(var t=0;t<count;t++) {\n\t\tresult += str;\n\t}\n\treturn result;\n};\n\n/*\nTrim whitespace from the start and end of a string\nThanks to Steven Levithan, http://blog.stevenlevithan.com/archives/faster-trim-javascript\n*/\nexports.trim = function(str) {\n\tif(typeof str === \"string\") {\n\t\treturn str.replace(/^\\s\\s*/, '').replace(/\\s\\s*$/, '');\n\t} else {\n\t\treturn str;\n\t}\n};\n\n/*\nFind the line break preceding a given position in a string\nReturns position immediately after that line break, or the start of the string\n*/\nexports.findPrecedingLineBreak = function(text,pos) {\n\tvar result = text.lastIndexOf(\"\\n\",pos - 1);\n\tif(result === -1) {\n\t\tresult = 0;\n\t} else {\n\t\tresult++;\n\t\tif(text.charAt(result) === \"\\r\") {\n\t\t\tresult++;\n\t\t}\n\t}\n\treturn result;\n};\n\n/*\nFind the line break following a given position in a string\n*/\nexports.findFollowingLineBreak = function(text,pos) {\n\t// Cut to just past the following line break, or to the end of the text\n\tvar result = text.indexOf(\"\\n\",pos);\n\tif(result === -1) {\n\t\tresult = text.length;\n\t} else {\n\t\tif(text.charAt(result) === \"\\r\") {\n\t\t\tresult++;\n\t\t}\n\t}\n\treturn result;\n};\n\n/*\nReturn the number of keys in an object\n*/\nexports.count = function(object) {\n\treturn Object.keys(object || {}).length;\n};\n\n/*\nCheck if an array is equal by value and by reference.\n*/\nexports.isArrayEqual = function(array1,array2) {\n\tif(array1 === array2) {\n\t\treturn true;\n\t}\n\tarray1 = array1 || [];\n\tarray2 = array2 || [];\n\tif(array1.length !== array2.length) {\n\t\treturn false;\n\t}\n\treturn array1.every(function(value,index) {\n\t\treturn value === array2[index];\n\t});\n};\n\n/*\nPush entries onto an array, removing them first if they already exist in the array\n\tarray: array to modify (assumed to be free of duplicates)\n\tvalue: a single value to push or an array of values to push\n*/\nexports.pushTop = function(array,value) {\n\tvar t,p;\n\tif($tw.utils.isArray(value)) {\n\t\t// Remove any array entries that are duplicated in the new values\n\t\tif(value.length !== 0) {\n\t\t\tif(array.length !== 0) {\n\t\t\t\tif(value.length < array.length) {\n\t\t\t\t\tfor(t=0; t<value.length; t++) {\n\t\t\t\t\t\tp = array.indexOf(value[t]);\n\t\t\t\t\t\tif(p !== -1) {\n\t\t\t\t\t\t\tarray.splice(p,1);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\tfor(t=array.length-1; t>=0; t--) {\n\t\t\t\t\t\tp = value.indexOf(array[t]);\n\t\t\t\t\t\tif(p !== -1) {\n\t\t\t\t\t\t\tarray.splice(t,1);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\t// Push the values on top of the main array\n\t\t\tarray.push.apply(array,value);\n\t\t}\n\t} else {\n\t\tp = array.indexOf(value);\n\t\tif(p !== -1) {\n\t\t\tarray.splice(p,1);\n\t\t}\n\t\tarray.push(value);\n\t}\n\treturn array;\n};\n\n/*\nRemove entries from an array\n\tarray: array to modify\n\tvalue: a single value to remove, or an array of values to remove\n*/\nexports.removeArrayEntries = function(array,value) {\n\tvar t,p;\n\tif($tw.utils.isArray(value)) {\n\t\tfor(t=0; t<value.length; t++) {\n\t\t\tp = array.indexOf(value[t]);\n\t\t\tif(p !== -1) {\n\t\t\t\tarray.splice(p,1);\n\t\t\t}\n\t\t}\n\t} else {\n\t\tp = array.indexOf(value);\n\t\tif(p !== -1) {\n\t\t\tarray.splice(p,1);\n\t\t}\n\t}\n};\n\n/*\nCheck whether any members of a hashmap are present in another hashmap\n*/\nexports.checkDependencies = function(dependencies,changes) {\n\tvar hit = false;\n\t$tw.utils.each(changes,function(change,title) {\n\t\tif($tw.utils.hop(dependencies,title)) {\n\t\t\thit = true;\n\t\t}\n\t});\n\treturn hit;\n};\n\nexports.extend = function(object /* [, src] */) {\n\t$tw.utils.each(Array.prototype.slice.call(arguments, 1), function(source) {\n\t\tif(source) {\n\t\t\tfor(var property in source) {\n\t\t\t\tobject[property] = source[property];\n\t\t\t}\n\t\t}\n\t});\n\treturn object;\n};\n\nexports.deepCopy = function(object) {\n\tvar result,t;\n\tif($tw.utils.isArray(object)) {\n\t\t// Copy arrays\n\t\tresult = object.slice(0);\n\t} else if(typeof object === \"object\") {\n\t\tresult = {};\n\t\tfor(t in object) {\n\t\t\tif(object[t] !== undefined) {\n\t\t\t\tresult[t] = $tw.utils.deepCopy(object[t]);\n\t\t\t}\n\t\t}\n\t} else {\n\t\tresult = object;\n\t}\n\treturn result;\n};\n\nexports.extendDeepCopy = function(object,extendedProperties) {\n\tvar result = $tw.utils.deepCopy(object),t;\n\tfor(t in extendedProperties) {\n\t\tif(extendedProperties[t] !== undefined) {\n\t\t\tresult[t] = $tw.utils.deepCopy(extendedProperties[t]);\n\t\t}\n\t}\n\treturn result;\n};\n\nexports.deepFreeze = function deepFreeze(object) {\n\tvar property, key;\n\tObject.freeze(object);\n\tfor(key in object) {\n\t\tproperty = object[key];\n\t\tif($tw.utils.hop(object,key) && (typeof property === \"object\") && !Object.isFrozen(property)) {\n\t\t\tdeepFreeze(property);\n\t\t}\n\t}\n};\n\nexports.slowInSlowOut = function(t) {\n\treturn (1 - ((Math.cos(t * Math.PI) + 1) / 2));\n};\n\nexports.formatDateString = function(date,template) {\n\tvar result = \"\",\n\t\tt = template,\n\t\tmatches = [\n\t\t\t[/^0hh12/, function() {\n\t\t\t\treturn $tw.utils.pad($tw.utils.getHours12(date));\n\t\t\t}],\n\t\t\t[/^wYYYY/, function() {\n\t\t\t\treturn $tw.utils.getYearForWeekNo(date);\n\t\t\t}],\n\t\t\t[/^hh12/, function() {\n\t\t\t\treturn $tw.utils.getHours12(date);\n\t\t\t}],\n\t\t\t[/^DDth/, function() {\n\t\t\t\treturn date.getDate() + $tw.utils.getDaySuffix(date);\n\t\t\t}],\n\t\t\t[/^YYYY/, function() {\n\t\t\t\treturn date.getFullYear();\n\t\t\t}],\n\t\t\t[/^0hh/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getHours());\n\t\t\t}],\n\t\t\t[/^0mm/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getMinutes());\n\t\t\t}],\n\t\t\t[/^0ss/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getSeconds());\n\t\t\t}],\n\t\t\t[/^0DD/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getDate());\n\t\t\t}],\n\t\t\t[/^0MM/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getMonth()+1);\n\t\t\t}],\n\t\t\t[/^0WW/, function() {\n\t\t\t\treturn $tw.utils.pad($tw.utils.getWeek(date));\n\t\t\t}],\n\t\t\t[/^ddd/, function() {\n\t\t\t\treturn $tw.language.getString(\"Date/Short/Day/\" + date.getDay());\n\t\t\t}],\n\t\t\t[/^mmm/, function() {\n\t\t\t\treturn $tw.language.getString(\"Date/Short/Month/\" + (date.getMonth() + 1));\n\t\t\t}],\n\t\t\t[/^DDD/, function() {\n\t\t\t\treturn $tw.language.getString(\"Date/Long/Day/\" + date.getDay());\n\t\t\t}],\n\t\t\t[/^MMM/, function() {\n\t\t\t\treturn $tw.language.getString(\"Date/Long/Month/\" + (date.getMonth() + 1));\n\t\t\t}],\n\t\t\t[/^TZD/, function() {\n\t\t\t\tvar tz = date.getTimezoneOffset(),\n\t\t\t\tatz = Math.abs(tz);\n\t\t\t\treturn (tz < 0 ? '+' : '-') + $tw.utils.pad(Math.floor(atz / 60)) + ':' + $tw.utils.pad(atz % 60);\n\t\t\t}],\n\t\t\t[/^wYY/, function() {\n\t\t\t\treturn $tw.utils.pad($tw.utils.getYearForWeekNo(date) - 2000);\n\t\t\t}],\n\t\t\t[/^[ap]m/, function() {\n\t\t\t\treturn $tw.utils.getAmPm(date).toLowerCase();\n\t\t\t}],\n\t\t\t[/^hh/, function() {\n\t\t\t\treturn date.getHours();\n\t\t\t}],\n\t\t\t[/^mm/, function() {\n\t\t\t\treturn date.getMinutes();\n\t\t\t}],\n\t\t\t[/^ss/, function() {\n\t\t\t\treturn date.getSeconds();\n\t\t\t}],\n\t\t\t[/^[AP]M/, function() {\n\t\t\t\treturn $tw.utils.getAmPm(date).toUpperCase();\n\t\t\t}],\n\t\t\t[/^DD/, function() {\n\t\t\t\treturn date.getDate();\n\t\t\t}],\n\t\t\t[/^MM/, function() {\n\t\t\t\treturn date.getMonth() + 1;\n\t\t\t}],\n\t\t\t[/^WW/, function() {\n\t\t\t\treturn $tw.utils.getWeek(date);\n\t\t\t}],\n\t\t\t[/^YY/, function() {\n\t\t\t\treturn $tw.utils.pad(date.getFullYear() - 2000);\n\t\t\t}]\n\t\t];\n\twhile(t.length){\n\t\tvar matchString = \"\";\n\t\t$tw.utils.each(matches, function(m) {\n\t\t\tvar match = m[0].exec(t);\n\t\t\tif(match) {\n\t\t\t\tmatchString = m[1].call();\n\t\t\t\tt = t.substr(match[0].length);\n\t\t\t\treturn false;\n\t\t\t}\n\t\t});\n\t\tif(matchString) {\n\t\t\tresult += matchString;\n\t\t} else {\n\t\t\tresult += t.charAt(0);\n\t\t\tt = t.substr(1);\n\t\t}\n\t}\n\tresult = result.replace(/\\\\(.)/g,\"$1\");\n\treturn result;\n};\n\nexports.getAmPm = function(date) {\n\treturn $tw.language.getString(\"Date/Period/\" + (date.getHours() >= 12 ? \"pm\" : \"am\"));\n};\n\nexports.getDaySuffix = function(date) {\n\treturn $tw.language.getString(\"Date/DaySuffix/\" + date.getDate());\n};\n\nexports.getWeek = function(date) {\n\tvar dt = new Date(date.getTime());\n\tvar d = dt.getDay();\n\tif(d === 0) {\n\t\td = 7; // JavaScript Sun=0, ISO Sun=7\n\t}\n\tdt.setTime(dt.getTime() + (4 - d) * 86400000);// shift day to Thurs of same week to calculate weekNo\n\tvar n = Math.floor((dt.getTime()-new Date(dt.getFullYear(),0,1) + 3600000) / 86400000);\n\treturn Math.floor(n / 7) + 1;\n};\n\nexports.getYearForWeekNo = function(date) {\n\tvar dt = new Date(date.getTime());\n\tvar d = dt.getDay();\n\tif(d === 0) {\n\t\td = 7; // JavaScript Sun=0, ISO Sun=7\n\t}\n\tdt.setTime(dt.getTime() + (4 - d) * 86400000);// shift day to Thurs of same week\n\treturn dt.getFullYear();\n};\n\nexports.getHours12 = function(date) {\n\tvar h = date.getHours();\n\treturn h > 12 ? h-12 : ( h > 0 ? h : 12 );\n};\n\n/*\nConvert a date delta in milliseconds into a string representation of \"23 seconds ago\", \"27 minutes ago\" etc.\n\tdelta: delta in milliseconds\nReturns an object with these members:\n\tdescription: string describing the delta period\n\tupdatePeriod: time in millisecond until the string will be inaccurate\n*/\nexports.getRelativeDate = function(delta) {\n\tvar futurep = false;\n\tif(delta < 0) {\n\t\tdelta = -1 * delta;\n\t\tfuturep = true;\n\t}\n\tvar units = [\n\t\t{name: \"Years\", duration: 365 * 24 * 60 * 60 * 1000},\n\t\t{name: \"Months\", duration: (365/12) * 24 * 60 * 60 * 1000},\n\t\t{name: \"Days\", duration: 24 * 60 * 60 * 1000},\n\t\t{name: \"Hours\", duration: 60 * 60 * 1000},\n\t\t{name: \"Minutes\", duration: 60 * 1000},\n\t\t{name: \"Seconds\", duration: 1000}\n\t];\n\tfor(var t=0; t<units.length; t++) {\n\t\tvar result = Math.floor(delta / units[t].duration);\n\t\tif(result >= 2) {\n\t\t\treturn {\n\t\t\t\tdelta: delta,\n\t\t\t\tdescription: $tw.language.getString(\n\t\t\t\t\t\"RelativeDate/\" + (futurep ? \"Future\" : \"Past\") + \"/\" + units[t].name,\n\t\t\t\t\t{variables:\n\t\t\t\t\t\t{period: result.toString()}\n\t\t\t\t\t}\n\t\t\t\t),\n\t\t\t\tupdatePeriod: units[t].duration\n\t\t\t};\n\t\t}\n\t}\n\treturn {\n\t\tdelta: delta,\n\t\tdescription: $tw.language.getString(\n\t\t\t\"RelativeDate/\" + (futurep ? \"Future\" : \"Past\") + \"/Second\",\n\t\t\t{variables:\n\t\t\t\t{period: \"1\"}\n\t\t\t}\n\t\t),\n\t\tupdatePeriod: 1000\n\t};\n};\n\n// Convert & to \"&\", < to \"<\", > to \">\", \" to \""\"\nexports.htmlEncode = function(s) {\n\tif(s) {\n\t\treturn s.toString().replace(/&/mg,\"&\").replace(/</mg,\"<\").replace(/>/mg,\">\").replace(/\\\"/mg,\""\");\n\t} else {\n\t\treturn \"\";\n\t}\n};\n\n// Converts all HTML entities to their character equivalents\nexports.entityDecode = function(s) {\n\tvar converter = String.fromCodePoint || String.fromCharCode,\n\t\te = s.substr(1,s.length-2); // Strip the & and the ;\n\tif(e.charAt(0) === \"#\") {\n\t\tif(e.charAt(1) === \"x\" || e.charAt(1) === \"X\") {\n\t\t\treturn converter(parseInt(e.substr(2),16));\t\n\t\t} else {\n\t\t\treturn converter(parseInt(e.substr(1),10));\n\t\t}\n\t} else {\n\t\tvar c = $tw.config.htmlEntities[e];\n\t\tif(c) {\n\t\t\treturn converter(c);\n\t\t} else {\n\t\t\treturn s; // Couldn't convert it as an entity, just return it raw\n\t\t}\n\t}\n};\n\nexports.unescapeLineBreaks = function(s) {\n\treturn s.replace(/\\\\n/mg,\"\\n\").replace(/\\\\b/mg,\" \").replace(/\\\\s/mg,\"\\\\\").replace(/\\r/mg,\"\");\n};\n\n/*\n * Returns an escape sequence for given character. Uses \\x for characters <=\n * 0xFF to save space, \\u for the rest.\n *\n * The code needs to be in sync with th code template in the compilation\n * function for \"action\" nodes.\n */\n// Copied from peg.js, thanks to David Majda\nexports.escape = function(ch) {\n\tvar charCode = ch.charCodeAt(0);\n\tif(charCode <= 0xFF) {\n\t\treturn '\\\\x' + $tw.utils.pad(charCode.toString(16).toUpperCase());\n\t} else {\n\t\treturn '\\\\u' + $tw.utils.pad(charCode.toString(16).toUpperCase(),4);\n\t}\n};\n\n// Turns a string into a legal JavaScript string\n// Copied from peg.js, thanks to David Majda\nexports.stringify = function(s) {\n\t/*\n\t* ECMA-262, 5th ed., 7.8.4: All characters may appear literally in a string\n\t* literal except for the closing quote character, backslash, carriage return,\n\t* line separator, paragraph separator, and line feed. Any character may\n\t* appear in the form of an escape sequence.\n\t*\n\t* For portability, we also escape all non-ASCII characters.\n\t*/\n\treturn (s || \"\")\n\t\t.replace(/\\\\/g, '\\\\\\\\') // backslash\n\t\t.replace(/\"/g, '\\\\\"') // double quote character\n\t\t.replace(/'/g, \"\\\\'\") // single quote character\n\t\t.replace(/\\r/g, '\\\\r') // carriage return\n\t\t.replace(/\\n/g, '\\\\n') // line feed\n\t\t.replace(/[\\x80-\\uFFFF]/g, exports.escape); // non-ASCII characters\n};\n\n/*\nEscape the RegExp special characters with a preceding backslash\n*/\nexports.escapeRegExp = function(s) {\n return s.replace(/[\\-\\/\\\\\\^\\$\\*\\+\\?\\.\\(\\)\\|\\[\\]\\{\\}]/g, '\\\\$&');\n};\n\n// Checks whether a link target is external, i.e. not a tiddler title\nexports.isLinkExternal = function(to) {\n\tvar externalRegExp = /^(?:file|http|https|mailto|ftp|irc|news|data|skype):[^\\s<>{}\\[\\]`|\"\\\\^]+(?:\\/|\\b)/i;\n\treturn externalRegExp.test(to);\n};\n\nexports.nextTick = function(fn) {\n/*global window: false */\n\tif(typeof process === \"undefined\") {\n\t\t// Apparently it would be faster to use postMessage - http://dbaron.org/log/20100309-faster-timeouts\n\t\twindow.setTimeout(fn,4);\n\t} else {\n\t\tprocess.nextTick(fn);\n\t}\n};\n\n/*\nConvert a hyphenated CSS property name into a camel case one\n*/\nexports.unHyphenateCss = function(propName) {\n\treturn propName.replace(/-([a-z])/gi, function(match0,match1) {\n\t\treturn match1.toUpperCase();\n\t});\n};\n\n/*\nConvert a camelcase CSS property name into a dashed one (\"backgroundColor\" --> \"background-color\")\n*/\nexports.hyphenateCss = function(propName) {\n\treturn propName.replace(/([A-Z])/g, function(match0,match1) {\n\t\treturn \"-\" + match1.toLowerCase();\n\t});\n};\n\n/*\nParse a text reference of one of these forms:\n* title\n* !!field\n* title!!field\n* title##index\n* etc\nReturns an object with the following fields, all optional:\n* title: tiddler title\n* field: tiddler field name\n* index: JSON property index\n*/\nexports.parseTextReference = function(textRef) {\n\t// Separate out the title, field name and/or JSON indices\n\tvar reTextRef = /(?:(.*?)!!(.+))|(?:(.*?)##(.+))|(.*)/mg,\n\t\tmatch = reTextRef.exec(textRef),\n\t\tresult = {};\n\tif(match && reTextRef.lastIndex === textRef.length) {\n\t\t// Return the parts\n\t\tif(match[1]) {\n\t\t\tresult.title = match[1];\n\t\t}\n\t\tif(match[2]) {\n\t\t\tresult.field = match[2];\n\t\t}\n\t\tif(match[3]) {\n\t\t\tresult.title = match[3];\n\t\t}\n\t\tif(match[4]) {\n\t\t\tresult.index = match[4];\n\t\t}\n\t\tif(match[5]) {\n\t\t\tresult.title = match[5];\n\t\t}\n\t} else {\n\t\t// If we couldn't parse it\n\t\tresult.title = textRef\n\t}\n\treturn result;\n};\n\n/*\nChecks whether a string is a valid fieldname\n*/\nexports.isValidFieldName = function(name) {\n\tif(!name || typeof name !== \"string\") {\n\t\treturn false;\n\t}\n\tname = name.toLowerCase().trim();\n\tvar fieldValidatorRegEx = /^[a-z0-9\\-\\._]+$/mg;\n\treturn fieldValidatorRegEx.test(name);\n};\n\n/*\nExtract the version number from the meta tag or from the boot file\n*/\n\n// Browser version\nexports.extractVersionInfo = function() {\n\tif($tw.packageInfo) {\n\t\treturn $tw.packageInfo.version;\n\t} else {\n\t\tvar metatags = document.getElementsByTagName(\"meta\");\n\t\tfor(var t=0; t<metatags.length; t++) {\n\t\t\tvar m = metatags[t];\n\t\t\tif(m.name === \"tiddlywiki-version\") {\n\t\t\t\treturn m.content;\n\t\t\t}\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nGet the animation duration in ms\n*/\nexports.getAnimationDuration = function() {\n\treturn parseInt($tw.wiki.getTiddlerText(\"$:/config/AnimationDuration\",\"400\"),10);\n};\n\n/*\nHash a string to a number\nDerived from http://stackoverflow.com/a/15710692\n*/\nexports.hashString = function(str) {\n\treturn str.split(\"\").reduce(function(a,b) {\n\t\ta = ((a << 5) - a) + b.charCodeAt(0);\n\t\treturn a & a;\n\t},0);\n};\n\n/*\nDecode a base64 string\n*/\nexports.base64Decode = function(string64) {\n\tif($tw.browser) {\n\t\t// TODO\n\t\tthrow \"$tw.utils.base64Decode() doesn't work in the browser\";\n\t} else {\n\t\treturn (new Buffer(string64,\"base64\")).toString();\n\t}\n};\n\n/*\nConvert a hashmap into a tiddler dictionary format sequence of name:value pairs\n*/\nexports.makeTiddlerDictionary = function(data) {\n\tvar output = [];\n\tfor(var name in data) {\n\t\toutput.push(name + \": \" + data[name]);\n\t}\n\treturn output.join(\"\\n\");\n};\n\n/*\nHigh resolution microsecond timer for profiling\n*/\nexports.timer = function(base) {\n\tvar m;\n\tif($tw.node) {\n\t\tvar r = process.hrtime();\t\t\n\t\tm = r[0] * 1e3 + (r[1] / 1e6);\n\t} else if(window.performance) {\n\t\tm = performance.now();\n\t} else {\n\t\tm = Date.now();\n\t}\n\tif(typeof base !== \"undefined\") {\n\t\tm = m - base;\n\t}\n\treturn m;\n};\n\n/*\nConvert text and content type to a data URI\n*/\nexports.makeDataUri = function(text,type) {\n\ttype = type || \"text/vnd.tiddlywiki\";\n\tvar typeInfo = $tw.config.contentTypeInfo[type] || $tw.config.contentTypeInfo[\"text/plain\"],\n\t\tisBase64 = typeInfo.encoding === \"base64\",\n\t\tparts = [];\n\tparts.push(\"data:\");\n\tparts.push(type);\n\tparts.push(isBase64 ? \";base64\" : \"\");\n\tparts.push(\",\");\n\tparts.push(isBase64 ? text : encodeURIComponent(text));\n\treturn parts.join(\"\");\n};\n\n/*\nUseful for finding out the fully escaped CSS selector equivalent to a given tag. For example:\n\n$tw.utils.tagToCssSelector(\"$:/tags/Stylesheet\") --> tc-tagged-\\%24\\%3A\\%2Ftags\\%2FStylesheet\n*/\nexports.tagToCssSelector = function(tagName) {\n\treturn \"tc-tagged-\" + encodeURIComponent(tagName).replace(/[!\"#$%&'()*+,\\-./:;<=>?@[\\\\\\]^`{\\|}~,]/mg,function(c) {\n\t\treturn \"\\\\\" + c;\n\t});\n};\n\n\n/*\nIE does not have sign function\n*/\nexports.sign = Math.sign || function(x) {\n\tx = +x; // convert to a number\n\tif (x === 0 || isNaN(x)) {\n\t\treturn x;\n\t}\n\treturn x > 0 ? 1 : -1;\n};\n\n/*\nIE does not have an endsWith function\n*/\nexports.strEndsWith = function(str,ending,position) {\n\tif(str.endsWith) {\n\t\treturn str.endsWith(ending,position);\n\t} else {\n\t\tif (typeof position !== 'number' || !isFinite(position) || Math.floor(position) !== position || position > str.length) {\n\t\t\tposition = str.length;\n\t\t}\n\t\tposition -= str.length;\n\t\tvar lastIndex = str.indexOf(ending, position);\n\t\treturn lastIndex !== -1 && lastIndex === position;\n\t}\n};\n\n})();\n",
"title": "$:/core/modules/utils/utils.js",
"type": "application/javascript",
"module-type": "utils"
},
"$:/core/modules/widgets/action-deletefield.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-deletefield.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to delete fields of a tiddler.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar DeleteFieldWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nDeleteFieldWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nDeleteFieldWidget.prototype.render = function(parent,nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n\n/*\nCompute the internal state of the widget\n*/\nDeleteFieldWidget.prototype.execute = function() {\n\tthis.actionTiddler = this.getAttribute(\"$tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.actionField = this.getAttribute(\"$field\");\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nDeleteFieldWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes[\"$tiddler\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nInvoke the action associated with this widget\n*/\nDeleteFieldWidget.prototype.invokeAction = function(triggeringWidget,event) {\n\tvar self = this,\n\t\ttiddler = this.wiki.getTiddler(self.actionTiddler),\n\t\tremoveFields = {};\n\tif(this.actionField) {\n\t\tremoveFields[this.actionField] = undefined;\n\t}\n\tif(tiddler) {\n\t\t$tw.utils.each(this.attributes,function(attribute,name) {\n\t\t\tif(name.charAt(0) !== \"$\" && name !== \"title\") {\n\t\t\t\tremoveFields[name] = undefined;\n\t\t\t}\n\t\t});\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(this.wiki.getModificationFields(),tiddler,removeFields,this.wiki.getCreationFields()));\n\t}\n\treturn true; // Action was invoked\n};\n\nexports[\"action-deletefield\"] = DeleteFieldWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-deletefield.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/action-deletetiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-deletetiddler.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to delete a tiddler.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar DeleteTiddlerWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nDeleteTiddlerWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nDeleteTiddlerWidget.prototype.render = function(parent,nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n\n/*\nCompute the internal state of the widget\n*/\nDeleteTiddlerWidget.prototype.execute = function() {\n\tthis.actionFilter = this.getAttribute(\"$filter\");\n\tthis.actionTiddler = this.getAttribute(\"$tiddler\");\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nDeleteTiddlerWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes[\"$filter\"] || changedAttributes[\"$tiddler\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nInvoke the action associated with this widget\n*/\nDeleteTiddlerWidget.prototype.invokeAction = function(triggeringWidget,event) {\n\tvar tiddlers = [];\n\tif(this.actionFilter) {\n\t\ttiddlers = this.wiki.filterTiddlers(this.actionFilter,this);\n\t}\n\tif(this.actionTiddler) {\n\t\ttiddlers.push(this.actionTiddler);\n\t}\n\tfor(var t=0; t<tiddlers.length; t++) {\n\t\tthis.wiki.deleteTiddler(tiddlers[t]);\n\t}\n\treturn true; // Action was invoked\n};\n\nexports[\"action-deletetiddler\"] = DeleteTiddlerWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-deletetiddler.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/action-listops.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-listops.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to apply list operations to any tiddler field (defaults to the 'list' field of the current tiddler)\n\n\\*/\n(function() {\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\nvar ActionListopsWidget = function(parseTreeNode, options) {\n\tthis.initialise(parseTreeNode, options);\n};\n/**\n * Inherit from the base widget class\n */\nActionListopsWidget.prototype = new Widget();\n/**\n * Render this widget into the DOM\n */\nActionListopsWidget.prototype.render = function(parent, nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n/**\n * Compute the internal state of the widget\n */\nActionListopsWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.target = this.getAttribute(\"$tiddler\", this.getVariable(\n\t\t\"currentTiddler\"));\n\tthis.filter = this.getAttribute(\"$filter\");\n\tthis.subfilter = this.getAttribute(\"$subfilter\");\n\tthis.listField = this.getAttribute(\"$field\", \"list\");\n\tthis.listIndex = this.getAttribute(\"$index\");\n\tthis.filtertags = this.getAttribute(\"$tags\");\n};\n/**\n * \tRefresh the widget by ensuring our attributes are up to date\n */\nActionListopsWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.$tiddler || changedAttributes.$filter ||\n\t\tchangedAttributes.$subfilter || changedAttributes.$field ||\n\t\tchangedAttributes.$index || changedAttributes.$tags) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n/**\n * \tInvoke the action associated with this widget\n */\nActionListopsWidget.prototype.invokeAction = function(triggeringWidget,\n\tevent) {\n\t//Apply the specified filters to the lists\n\tvar field = this.listField,\n\t\tindex,\n\t\ttype = \"!!\",\n\t\tlist = this.listField;\n\tif(this.listIndex) {\n\t\tfield = undefined;\n\t\tindex = this.listIndex;\n\t\ttype = \"##\";\n\t\tlist = this.listIndex;\n\t}\n\tif(this.filter) {\n\t\tthis.wiki.setText(this.target, field, index, $tw.utils.stringifyList(\n\t\t\tthis.wiki\n\t\t\t.filterTiddlers(this.filter, this)));\n\t}\n\tif(this.subfilter) {\n\t\tvar subfilter = \"[list[\" + this.target + type + list + \"]] \" + this.subfilter;\n\t\tthis.wiki.setText(this.target, field, index, $tw.utils.stringifyList(\n\t\t\tthis.wiki\n\t\t\t.filterTiddlers(subfilter, this)));\n\t}\n\tif(this.filtertags) {\n\t\tvar tagfilter = \"[list[\" + this.target + \"!!tags]] \" + this.filtertags;\n\t\tthis.wiki.setText(this.target, \"tags\", undefined, $tw.utils.stringifyList(\n\t\t\tthis.wiki.filterTiddlers(tagfilter, this)));\n\t}\n\treturn true; // Action was invoked\n};\n\nexports[\"action-listops\"] = ActionListopsWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-listops.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/action-navigate.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-navigate.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to navigate to a tiddler\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar NavigateWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nNavigateWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nNavigateWidget.prototype.render = function(parent,nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n\n/*\nCompute the internal state of the widget\n*/\nNavigateWidget.prototype.execute = function() {\n\tthis.actionTo = this.getAttribute(\"$to\");\n\tthis.actionScroll = this.getAttribute(\"$scroll\");\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nNavigateWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes[\"$to\"] || changedAttributes[\"$scroll\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nInvoke the action associated with this widget\n*/\nNavigateWidget.prototype.invokeAction = function(triggeringWidget,event) {\n\tvar bounds = triggeringWidget && triggeringWidget.getBoundingClientRect && triggeringWidget.getBoundingClientRect(),\n\t\tsuppressNavigation = event.metaKey || event.ctrlKey || (event.button === 1);\n\tif(this.actionScroll === \"yes\") {\n\t\tsuppressNavigation = false;\n\t} else if(this.actionScroll === \"no\") {\n\t\tsuppressNavigation = true;\n\t}\n\tthis.dispatchEvent({\n\t\ttype: \"tm-navigate\",\n\t\tnavigateTo: this.actionTo === undefined ? this.getVariable(\"currentTiddler\") : this.actionTo,\n\t\tnavigateFromTitle: this.getVariable(\"storyTiddler\"),\n\t\tnavigateFromNode: triggeringWidget,\n\t\tnavigateFromClientRect: bounds && { top: bounds.top, left: bounds.left, width: bounds.width, right: bounds.right, bottom: bounds.bottom, height: bounds.height\n\t\t},\n\t\tnavigateSuppressNavigation: suppressNavigation\n\t});\n\treturn true; // Action was invoked\n};\n\nexports[\"action-navigate\"] = NavigateWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-navigate.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/action-sendmessage.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-sendmessage.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to send a message\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar SendMessageWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nSendMessageWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nSendMessageWidget.prototype.render = function(parent,nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n\n/*\nCompute the internal state of the widget\n*/\nSendMessageWidget.prototype.execute = function() {\n\tthis.actionMessage = this.getAttribute(\"$message\");\n\tthis.actionParam = this.getAttribute(\"$param\");\n\tthis.actionName = this.getAttribute(\"$name\");\n\tthis.actionValue = this.getAttribute(\"$value\",\"\");\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nSendMessageWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(Object.keys(changedAttributes).length) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nInvoke the action associated with this widget\n*/\nSendMessageWidget.prototype.invokeAction = function(triggeringWidget,event) {\n\t// Get the string parameter\n\tvar param = this.actionParam;\n\t// Assemble the attributes as a hashmap\n\tvar paramObject = Object.create(null);\n\tvar count = 0;\n\t$tw.utils.each(this.attributes,function(attribute,name) {\n\t\tif(name.charAt(0) !== \"$\") {\n\t\t\tparamObject[name] = attribute;\n\t\t\tcount++;\n\t\t}\n\t});\n\t// Add name/value pair if present\n\tif(this.actionName) {\n\t\tparamObject[this.actionName] = this.actionValue;\n\t}\n\t// Dispatch the message\n\tthis.dispatchEvent({\n\t\ttype: this.actionMessage,\n\t\tparam: param,\n\t\tparamObject: paramObject,\n\t\ttiddlerTitle: this.getVariable(\"currentTiddler\"),\n\t\tnavigateFromTitle: this.getVariable(\"storyTiddler\")\n\t});\n\treturn true; // Action was invoked\n};\n\nexports[\"action-sendmessage\"] = SendMessageWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-sendmessage.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/action-setfield.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/action-setfield.js\ntype: application/javascript\nmodule-type: widget\n\nAction widget to set a single field or index on a tiddler.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar SetFieldWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nSetFieldWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nSetFieldWidget.prototype.render = function(parent,nextSibling) {\n\tthis.computeAttributes();\n\tthis.execute();\n};\n\n/*\nCompute the internal state of the widget\n*/\nSetFieldWidget.prototype.execute = function() {\n\tthis.actionTiddler = this.getAttribute(\"$tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.actionField = this.getAttribute(\"$field\");\n\tthis.actionIndex = this.getAttribute(\"$index\");\n\tthis.actionValue = this.getAttribute(\"$value\");\n\tthis.actionTimestamp = this.getAttribute(\"$timestamp\",\"yes\") === \"yes\";\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nSetFieldWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes[\"$tiddler\"] || changedAttributes[\"$field\"] || changedAttributes[\"$index\"] || changedAttributes[\"$value\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nInvoke the action associated with this widget\n*/\nSetFieldWidget.prototype.invokeAction = function(triggeringWidget,event) {\n\tvar self = this,\n\t\toptions = {};\n\toptions.suppressTimestamp = !this.actionTimestamp;\n\tif((typeof this.actionField == \"string\") || (typeof this.actionIndex == \"string\") || (typeof this.actionValue == \"string\")) {\n\t\tthis.wiki.setText(this.actionTiddler,this.actionField,this.actionIndex,this.actionValue,options);\n\t}\n\t$tw.utils.each(this.attributes,function(attribute,name) {\n\t\tif(name.charAt(0) !== \"$\") {\n\t\t\tself.wiki.setText(self.actionTiddler,name,undefined,attribute,options);\n\t\t}\n\t});\n\treturn true; // Action was invoked\n};\n\nexports[\"action-setfield\"] = SetFieldWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/action-setfield.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/browse.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/browse.js\ntype: application/javascript\nmodule-type: widget\n\nBrowse widget for browsing for files to import\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar BrowseWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nBrowseWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nBrowseWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Remember parent\n\tthis.parentDomNode = parent;\n\t// Compute attributes and execute state\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create element\n\tvar domNode = this.document.createElement(\"input\");\n\tdomNode.setAttribute(\"type\",\"file\");\n\tif(this.browseMultiple) {\n\t\tdomNode.setAttribute(\"multiple\",\"multiple\");\n\t}\n\tif(this.tooltip) {\n\t\tdomNode.setAttribute(\"title\",this.tooltip);\n\t}\n\t// Nw.js supports \"nwsaveas\" to force a \"save as\" dialogue that allows a new or existing file to be selected\n\tif(this.nwsaveas) {\n\t\tdomNode.setAttribute(\"nwsaveas\",this.nwsaveas);\n\t}\n\t// Nw.js supports \"webkitdirectory\" to allow a directory to be selected\n\tif(this.webkitdirectory) {\n\t\tdomNode.setAttribute(\"webkitdirectory\",this.webkitdirectory);\n\t}\n\t// Add a click event handler\n\tdomNode.addEventListener(\"change\",function (event) {\n\t\tif(self.message) {\n\t\t\tself.dispatchEvent({type: self.message, param: self.param, files: event.target.files});\n\t\t} else {\n\t\t\tself.wiki.readFiles(event.target.files,function(tiddlerFieldsArray) {\n\t\t\t\tself.dispatchEvent({type: \"tm-import-tiddlers\", param: JSON.stringify(tiddlerFieldsArray)});\n\t\t\t});\n\t\t}\n\t\treturn false;\n\t},false);\n\t// Insert element\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nBrowseWidget.prototype.execute = function() {\n\tthis.browseMultiple = this.getAttribute(\"multiple\");\n\tthis.message = this.getAttribute(\"message\");\n\tthis.param = this.getAttribute(\"param\");\n\tthis.tooltip = this.getAttribute(\"tooltip\");\n\tthis.nwsaveas = this.getAttribute(\"nwsaveas\");\n\tthis.webkitdirectory = this.getAttribute(\"webkitdirectory\");\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nBrowseWidget.prototype.refresh = function(changedTiddlers) {\n\treturn false;\n};\n\nexports.browse = BrowseWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/browse.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/button.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/button.js\ntype: application/javascript\nmodule-type: widget\n\nButton widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ButtonWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nButtonWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nButtonWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Remember parent\n\tthis.parentDomNode = parent;\n\t// Compute attributes and execute state\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create element\n\tvar tag = \"button\";\n\tif(this.buttonTag && $tw.config.htmlUnsafeElements.indexOf(this.buttonTag) === -1) {\n\t\ttag = this.buttonTag;\n\t}\n\tvar domNode = this.document.createElement(tag);\n\t// Assign classes\n\tvar classes = this[\"class\"].split(\" \") || [],\n\t\tisPoppedUp = this.popup && this.isPoppedUp();\n\tif(this.selectedClass) {\n\t\tif(this.set && this.setTo && this.isSelected()) {\n\t\t\t$tw.utils.pushTop(classes,this.selectedClass.split(\" \"));\n\t\t}\n\t\tif(isPoppedUp) {\n\t\t\t$tw.utils.pushTop(classes,this.selectedClass.split(\" \"));\n\t\t}\n\t}\n\tif(isPoppedUp) {\n\t\t$tw.utils.pushTop(classes,\"tc-popup-handle\");\n\t}\n\tdomNode.className = classes.join(\" \");\n\t// Assign other attributes\n\tif(this.style) {\n\t\tdomNode.setAttribute(\"style\",this.style);\n\t}\n\tif(this.tooltip) {\n\t\tdomNode.setAttribute(\"title\",this.tooltip);\n\t}\n\tif(this[\"aria-label\"]) {\n\t\tdomNode.setAttribute(\"aria-label\",this[\"aria-label\"]);\n\t}\n\t// Add a click event handler\n\tdomNode.addEventListener(\"click\",function (event) {\n\t\tvar handled = false;\n\t\tif(self.invokeActions(this,event)) {\n\t\t\thandled = true;\n\t\t}\n\t\tif(self.to) {\n\t\t\tself.navigateTo(event);\n\t\t\thandled = true;\n\t\t}\n\t\tif(self.message) {\n\t\t\tself.dispatchMessage(event);\n\t\t\thandled = true;\n\t\t}\n\t\tif(self.popup) {\n\t\t\tself.triggerPopup(event);\n\t\t\thandled = true;\n\t\t}\n\t\tif(self.set) {\n\t\t\tself.setTiddler();\n\t\t\thandled = true;\n\t\t}\n\t\tif(self.actions) {\n\t\t\tself.invokeActionString(self.actions,self,event);\n\t\t}\n\t\tif(handled) {\n\t\t\tevent.preventDefault();\n\t\t\tevent.stopPropagation();\n\t\t}\n\t\treturn handled;\n\t},false);\n\t// Insert element\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\n/*\nWe don't allow actions to propagate because we trigger actions ourselves\n*/\nButtonWidget.prototype.allowActionPropagation = function() {\n\treturn false;\n};\n\nButtonWidget.prototype.getBoundingClientRect = function() {\n\treturn this.domNodes[0].getBoundingClientRect();\n};\n\nButtonWidget.prototype.isSelected = function() {\n return this.wiki.getTextReference(this.set,this.defaultSetValue,this.getVariable(\"currentTiddler\")) === this.setTo;\n};\n\nButtonWidget.prototype.isPoppedUp = function() {\n\tvar tiddler = this.wiki.getTiddler(this.popup);\n\tvar result = tiddler && tiddler.fields.text ? $tw.popup.readPopupState(tiddler.fields.text) : false;\n\treturn result;\n};\n\nButtonWidget.prototype.navigateTo = function(event) {\n\tvar bounds = this.getBoundingClientRect();\n\tthis.dispatchEvent({\n\t\ttype: \"tm-navigate\",\n\t\tnavigateTo: this.to,\n\t\tnavigateFromTitle: this.getVariable(\"storyTiddler\"),\n\t\tnavigateFromNode: this,\n\t\tnavigateFromClientRect: { top: bounds.top, left: bounds.left, width: bounds.width, right: bounds.right, bottom: bounds.bottom, height: bounds.height\n\t\t},\n\t\tnavigateSuppressNavigation: event.metaKey || event.ctrlKey || (event.button === 1)\n\t});\n};\n\nButtonWidget.prototype.dispatchMessage = function(event) {\n\tthis.dispatchEvent({type: this.message, param: this.param, tiddlerTitle: this.getVariable(\"currentTiddler\")});\n};\n\nButtonWidget.prototype.triggerPopup = function(event) {\n\t$tw.popup.triggerPopup({\n\t\tdomNode: this.domNodes[0],\n\t\ttitle: this.popup,\n\t\twiki: this.wiki\n\t});\n};\n\nButtonWidget.prototype.setTiddler = function() {\n\tthis.wiki.setTextReference(this.set,this.setTo,this.getVariable(\"currentTiddler\"));\n};\n\n/*\nCompute the internal state of the widget\n*/\nButtonWidget.prototype.execute = function() {\n\t// Get attributes\n\tthis.actions = this.getAttribute(\"actions\");\n\tthis.to = this.getAttribute(\"to\");\n\tthis.message = this.getAttribute(\"message\");\n\tthis.param = this.getAttribute(\"param\");\n\tthis.set = this.getAttribute(\"set\");\n\tthis.setTo = this.getAttribute(\"setTo\");\n\tthis.popup = this.getAttribute(\"popup\");\n\tthis.hover = this.getAttribute(\"hover\");\n\tthis[\"class\"] = this.getAttribute(\"class\",\"\");\n\tthis[\"aria-label\"] = this.getAttribute(\"aria-label\");\n\tthis.tooltip = this.getAttribute(\"tooltip\");\n\tthis.style = this.getAttribute(\"style\");\n\tthis.selectedClass = this.getAttribute(\"selectedClass\");\n\tthis.defaultSetValue = this.getAttribute(\"default\",\"\");\n\tthis.buttonTag = this.getAttribute(\"tag\");\n\t// Make child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nButtonWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.to || changedAttributes.message || changedAttributes.param || changedAttributes.set || changedAttributes.setTo || changedAttributes.popup || changedAttributes.hover || changedAttributes[\"class\"] || changedAttributes.selectedClass || changedAttributes.style || (this.set && changedTiddlers[this.set]) || (this.popup && changedTiddlers[this.popup])) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.button = ButtonWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/button.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/checkbox.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/checkbox.js\ntype: application/javascript\nmodule-type: widget\n\nCheckbox widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar CheckboxWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nCheckboxWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nCheckboxWidget.prototype.render = function(parent,nextSibling) {\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\t// Create our elements\n\tthis.labelDomNode = this.document.createElement(\"label\");\n\tthis.labelDomNode.setAttribute(\"class\",this.checkboxClass);\n\tthis.inputDomNode = this.document.createElement(\"input\");\n\tthis.inputDomNode.setAttribute(\"type\",\"checkbox\");\n\tif(this.getValue()) {\n\t\tthis.inputDomNode.setAttribute(\"checked\",\"true\");\n\t}\n\tthis.labelDomNode.appendChild(this.inputDomNode);\n\tthis.spanDomNode = this.document.createElement(\"span\");\n\tthis.labelDomNode.appendChild(this.spanDomNode);\n\t// Add a click event handler\n\t$tw.utils.addEventListeners(this.inputDomNode,[\n\t\t{name: \"change\", handlerObject: this, handlerMethod: \"handleChangeEvent\"}\n\t]);\n\t// Insert the label into the DOM and render any children\n\tparent.insertBefore(this.labelDomNode,nextSibling);\n\tthis.renderChildren(this.spanDomNode,null);\n\tthis.domNodes.push(this.labelDomNode);\n};\n\nCheckboxWidget.prototype.getValue = function() {\n\tvar tiddler = this.wiki.getTiddler(this.checkboxTitle);\n\tif(tiddler) {\n\t\tif(this.checkboxTag) {\n\t\t\tif(this.checkboxInvertTag) {\n\t\t\t\treturn !tiddler.hasTag(this.checkboxTag);\n\t\t\t} else {\n\t\t\t\treturn tiddler.hasTag(this.checkboxTag);\n\t\t\t}\n\t\t}\n\t\tif(this.checkboxField) {\n\t\t\tvar value = tiddler.fields[this.checkboxField] || this.checkboxDefault || \"\";\n\t\t\tif(value === this.checkboxChecked) {\n\t\t\t\treturn true;\n\t\t\t}\n\t\t\tif(value === this.checkboxUnchecked) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t} else {\n\t\tif(this.checkboxTag) {\n\t\t\treturn false;\n\t\t}\n\t\tif(this.checkboxField) {\n\t\t\tif(this.checkboxDefault === this.checkboxChecked) {\n\t\t\t\treturn true;\n\t\t\t}\n\t\t\tif(this.checkboxDefault === this.checkboxUnchecked) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t}\n\treturn false;\n};\n\nCheckboxWidget.prototype.handleChangeEvent = function(event) {\n\tvar checked = this.inputDomNode.checked,\n\t\ttiddler = this.wiki.getTiddler(this.checkboxTitle),\n\t\tfallbackFields = {text: \"\"},\n\t\tnewFields = {title: this.checkboxTitle},\n\t\thasChanged = false,\n\t\ttagCheck = false,\n\t\thasTag = tiddler && tiddler.hasTag(this.checkboxTag);\n\tif(this.checkboxTag && this.checkboxInvertTag === \"yes\") {\n\t\ttagCheck = hasTag === checked;\n\t} else {\n\t\ttagCheck = hasTag !== checked;\n\t}\n\t// Set the tag if specified\n\tif(this.checkboxTag && (!tiddler || tagCheck)) {\n\t\tnewFields.tags = tiddler ? (tiddler.fields.tags || []).slice(0) : [];\n\t\tvar pos = newFields.tags.indexOf(this.checkboxTag);\n\t\tif(pos !== -1) {\n\t\t\tnewFields.tags.splice(pos,1);\n\t\t}\n\t\tif(this.checkboxInvertTag === \"yes\" && !checked) {\n\t\t\tnewFields.tags.push(this.checkboxTag);\n\t\t} else if(this.checkboxInvertTag !== \"yes\" && checked) {\n\t\t\tnewFields.tags.push(this.checkboxTag);\n\t\t}\n\t\thasChanged = true;\n\t}\n\t// Set the field if specified\n\tif(this.checkboxField) {\n\t\tvar value = checked ? this.checkboxChecked : this.checkboxUnchecked;\n\t\tif(!tiddler || tiddler.fields[this.checkboxField] !== value) {\n\t\t\tnewFields[this.checkboxField] = value;\n\t\t\thasChanged = true;\n\t\t}\n\t}\n\tif(hasChanged) {\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(this.wiki.getCreationFields(),fallbackFields,tiddler,newFields,this.wiki.getModificationFields()));\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nCheckboxWidget.prototype.execute = function() {\n\t// Get the parameters from the attributes\n\tthis.checkboxTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.checkboxTag = this.getAttribute(\"tag\");\n\tthis.checkboxField = this.getAttribute(\"field\");\n\tthis.checkboxChecked = this.getAttribute(\"checked\");\n\tthis.checkboxUnchecked = this.getAttribute(\"unchecked\");\n\tthis.checkboxDefault = this.getAttribute(\"default\");\n\tthis.checkboxClass = this.getAttribute(\"class\",\"\");\n\tthis.checkboxInvertTag = this.getAttribute(\"invertTag\",\"\");\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nCheckboxWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.tag || changedAttributes.invertTag || changedAttributes.field || changedAttributes.checked || changedAttributes.unchecked || changedAttributes[\"default\"] || changedAttributes[\"class\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\tvar refreshed = false;\n\t\tif(changedTiddlers[this.checkboxTitle]) {\n\t\t\tthis.inputDomNode.checked = this.getValue();\n\t\t\trefreshed = true;\n\t\t}\n\t\treturn this.refreshChildren(changedTiddlers) || refreshed;\n\t}\n};\n\nexports.checkbox = CheckboxWidget;\n\n})();",
"title": "$:/core/modules/widgets/checkbox.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/codeblock.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/codeblock.js\ntype: application/javascript\nmodule-type: widget\n\nCode block node widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar CodeBlockWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nCodeBlockWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nCodeBlockWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar codeNode = this.document.createElement(\"code\"),\n\t\tdomNode = this.document.createElement(\"pre\");\n\tcodeNode.appendChild(this.document.createTextNode(this.getAttribute(\"code\")));\n\tdomNode.appendChild(codeNode);\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.domNodes.push(domNode);\n\tif(this.postRender) {\n\t\tthis.postRender();\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nCodeBlockWidget.prototype.execute = function() {\n\tthis.language = this.getAttribute(\"language\");\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nCodeBlockWidget.prototype.refresh = function(changedTiddlers) {\n\treturn false;\n};\n\nexports.codeblock = CodeBlockWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/codeblock.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/count.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/count.js\ntype: application/javascript\nmodule-type: widget\n\nCount widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar CountWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nCountWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nCountWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar textNode = this.document.createTextNode(this.currentCount);\n\tparent.insertBefore(textNode,nextSibling);\n\tthis.domNodes.push(textNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nCountWidget.prototype.execute = function() {\n\t// Get parameters from our attributes\n\tthis.filter = this.getAttribute(\"filter\");\n\t// Execute the filter\n\tif(this.filter) {\n\t\tthis.currentCount = this.wiki.filterTiddlers(this.filter,this).length;\n\t} else {\n\t\tthis.currentCount = undefined;\n\t}\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nCountWidget.prototype.refresh = function(changedTiddlers) {\n\t// Re-execute the filter to get the count\n\tthis.computeAttributes();\n\tvar oldCount = this.currentCount;\n\tthis.execute();\n\tif(this.currentCount !== oldCount) {\n\t\t// Regenerate and rerender the widget and replace the existing DOM node\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\n\t}\n\n};\n\nexports.count = CountWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/count.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/dropzone.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/dropzone.js\ntype: application/javascript\nmodule-type: widget\n\nDropzone widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar DropZoneWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nDropZoneWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nDropZoneWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Remember parent\n\tthis.parentDomNode = parent;\n\t// Compute attributes and execute state\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create element\n\tvar domNode = this.document.createElement(\"div\");\n\tdomNode.className = \"tc-dropzone\";\n\t// Add event handlers\n\t$tw.utils.addEventListeners(domNode,[\n\t\t{name: \"dragenter\", handlerObject: this, handlerMethod: \"handleDragEnterEvent\"},\n\t\t{name: \"dragover\", handlerObject: this, handlerMethod: \"handleDragOverEvent\"},\n\t\t{name: \"dragleave\", handlerObject: this, handlerMethod: \"handleDragLeaveEvent\"},\n\t\t{name: \"drop\", handlerObject: this, handlerMethod: \"handleDropEvent\"},\n\t\t{name: \"paste\", handlerObject: this, handlerMethod: \"handlePasteEvent\"}\n\t]);\n\tdomNode.addEventListener(\"click\",function (event) {\n\t},false);\n\t// Insert element\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\nDropZoneWidget.prototype.enterDrag = function() {\n\t// Check for this window being the source of the drag\n\tif($tw.dragInProgress) {\n\t\treturn false;\n\t}\n\t// We count enter/leave events\n\tthis.dragEnterCount = (this.dragEnterCount || 0) + 1;\n\t// If we're entering for the first time we need to apply highlighting\n\tif(this.dragEnterCount === 1) {\n\t\t$tw.utils.addClass(this.domNodes[0],\"tc-dragover\");\n\t}\n};\n\nDropZoneWidget.prototype.leaveDrag = function() {\n\t// Reduce the enter count\n\tthis.dragEnterCount = (this.dragEnterCount || 0) - 1;\n\t// Remove highlighting if we're leaving externally\n\tif(this.dragEnterCount <= 0) {\n\t\t$tw.utils.removeClass(this.domNodes[0],\"tc-dragover\");\n\t}\n};\n\nDropZoneWidget.prototype.handleDragEnterEvent = function(event) {\n\tthis.enterDrag();\n\t// Tell the browser that we're ready to handle the drop\n\tevent.preventDefault();\n\t// Tell the browser not to ripple the drag up to any parent drop handlers\n\tevent.stopPropagation();\n};\n\nDropZoneWidget.prototype.handleDragOverEvent = function(event) {\n\t// Check for being over a TEXTAREA or INPUT\n\tif([\"TEXTAREA\",\"INPUT\"].indexOf(event.target.tagName) !== -1) {\n\t\treturn false;\n\t}\n\t// Check for this window being the source of the drag\n\tif($tw.dragInProgress) {\n\t\treturn false;\n\t}\n\t// Tell the browser that we're still interested in the drop\n\tevent.preventDefault();\n\tevent.dataTransfer.dropEffect = \"copy\"; // Explicitly show this is a copy\n};\n\nDropZoneWidget.prototype.handleDragLeaveEvent = function(event) {\n\tthis.leaveDrag();\n};\n\nDropZoneWidget.prototype.handleDropEvent = function(event) {\n\tthis.leaveDrag();\n\t// Check for being over a TEXTAREA or INPUT\n\tif([\"TEXTAREA\",\"INPUT\"].indexOf(event.target.tagName) !== -1) {\n\t\treturn false;\n\t}\n\t// Check for this window being the source of the drag\n\tif($tw.dragInProgress) {\n\t\treturn false;\n\t}\n\tvar self = this,\n\t\tdataTransfer = event.dataTransfer;\n\t// Reset the enter count\n\tthis.dragEnterCount = 0;\n\t// Remove highlighting\n\t$tw.utils.removeClass(this.domNodes[0],\"tc-dragover\");\n\t// Import any files in the drop\n\tvar numFiles = this.wiki.readFiles(dataTransfer.files,function(tiddlerFieldsArray) {\n\t\tself.dispatchEvent({type: \"tm-import-tiddlers\", param: JSON.stringify(tiddlerFieldsArray)});\n\t});\n\t// Try to import the various data types we understand\n\tif(numFiles === 0) {\n\t\tthis.importData(dataTransfer);\n\t}\n\t// Tell the browser that we handled the drop\n\tevent.preventDefault();\n\t// Stop the drop ripple up to any parent handlers\n\tevent.stopPropagation();\n};\n\nDropZoneWidget.prototype.importData = function(dataTransfer) {\n\t// Try each provided data type in turn\n\tfor(var t=0; t<this.importDataTypes.length; t++) {\n\t\tif(!$tw.browser.isIE || this.importDataTypes[t].IECompatible) {\n\t\t\t// Get the data\n\t\t\tvar dataType = this.importDataTypes[t];\n\t\t\t\tvar data = dataTransfer.getData(dataType.type);\n\t\t\t// Import the tiddlers in the data\n\t\t\tif(data !== \"\" && data !== null) {\n\t\t\t\tif($tw.log.IMPORT) {\n\t\t\t\t\tconsole.log(\"Importing data type '\" + dataType.type + \"', data: '\" + data + \"'\")\n\t\t\t\t}\n\t\t\t\tvar tiddlerFields = dataType.convertToFields(data);\n\t\t\t\tif(!tiddlerFields.title) {\n\t\t\t\t\ttiddlerFields.title = this.wiki.generateNewTitle(\"Untitled\");\n\t\t\t\t}\n\t\t\t\tthis.dispatchEvent({type: \"tm-import-tiddlers\", param: JSON.stringify([tiddlerFields])});\n\t\t\t\treturn;\n\t\t\t}\n\t\t}\n\t}\n};\n\nDropZoneWidget.prototype.importDataTypes = [\n\t{type: \"text/vnd.tiddler\", IECompatible: false, convertToFields: function(data) {\n\t\treturn JSON.parse(data);\n\t}},\n\t{type: \"URL\", IECompatible: true, convertToFields: function(data) {\n\t\t// Check for tiddler data URI\n\t\tvar match = decodeURIComponent(data).match(/^data\\:text\\/vnd\\.tiddler,(.*)/i);\n\t\tif(match) {\n\t\t\treturn JSON.parse(match[1]);\n\t\t} else {\n\t\t\treturn { // As URL string\n\t\t\t\ttext: data\n\t\t\t};\n\t\t}\n\t}},\n\t{type: \"text/x-moz-url\", IECompatible: false, convertToFields: function(data) {\n\t\t// Check for tiddler data URI\n\t\tvar match = decodeURIComponent(data).match(/^data\\:text\\/vnd\\.tiddler,(.*)/i);\n\t\tif(match) {\n\t\t\treturn JSON.parse(match[1]);\n\t\t} else {\n\t\t\treturn { // As URL string\n\t\t\t\ttext: data\n\t\t\t};\n\t\t}\n\t}},\n\t{type: \"text/html\", IECompatible: false, convertToFields: function(data) {\n\t\treturn {\n\t\t\ttext: data\n\t\t};\n\t}},\n\t{type: \"text/plain\", IECompatible: false, convertToFields: function(data) {\n\t\treturn {\n\t\t\ttext: data\n\t\t};\n\t}},\n\t{type: \"Text\", IECompatible: true, convertToFields: function(data) {\n\t\treturn {\n\t\t\ttext: data\n\t\t};\n\t}},\n\t{type: \"text/uri-list\", IECompatible: false, convertToFields: function(data) {\n\t\treturn {\n\t\t\ttext: data\n\t\t};\n\t}}\n];\n\nDropZoneWidget.prototype.handlePasteEvent = function(event) {\n\t// Let the browser handle it if we're in a textarea or input box\n\tif([\"TEXTAREA\",\"INPUT\"].indexOf(event.target.tagName) == -1) {\n\t\tvar self = this,\n\t\t\titems = event.clipboardData.items;\n\t\t// Enumerate the clipboard items\n\t\tfor(var t = 0; t<items.length; t++) {\n\t\t\tvar item = items[t];\n\t\t\tif(item.kind === \"file\") {\n\t\t\t\t// Import any files\n\t\t\t\tthis.wiki.readFile(item.getAsFile(),function(tiddlerFieldsArray) {\n\t\t\t\t\tself.dispatchEvent({type: \"tm-import-tiddlers\", param: JSON.stringify(tiddlerFieldsArray)});\n\t\t\t\t});\n\t\t\t} else if(item.kind === \"string\") {\n\t\t\t\t// Create tiddlers from string items\n\t\t\t\tvar type = item.type;\n\t\t\t\titem.getAsString(function(str) {\n\t\t\t\t\tvar tiddlerFields = {\n\t\t\t\t\t\ttitle: self.wiki.generateNewTitle(\"Untitled\"),\n\t\t\t\t\t\ttext: str,\n\t\t\t\t\t\ttype: type\n\t\t\t\t\t};\n\t\t\t\t\tif($tw.log.IMPORT) {\n\t\t\t\t\t\tconsole.log(\"Importing string '\" + str + \"', type: '\" + type + \"'\");\n\t\t\t\t\t}\n\t\t\t\t\tself.dispatchEvent({type: \"tm-import-tiddlers\", param: JSON.stringify([tiddlerFields])});\n\t\t\t\t});\n\t\t\t}\n\t\t}\n\t\t// Tell the browser that we've handled the paste\n\t\tevent.stopPropagation();\n\t\tevent.preventDefault();\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nDropZoneWidget.prototype.execute = function() {\n\t// Make child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nDropZoneWidget.prototype.refresh = function(changedTiddlers) {\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.dropzone = DropZoneWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/dropzone.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/edit-binary.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/edit-binary.js\ntype: application/javascript\nmodule-type: widget\n\nEdit-binary widget; placeholder for editing binary tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar BINARY_WARNING_MESSAGE = \"$:/core/ui/BinaryWarning\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EditBinaryWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEditBinaryWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEditBinaryWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nEditBinaryWidget.prototype.execute = function() {\n\t// Construct the child widgets\n\tthis.makeChildWidgets([{\n\t\ttype: \"transclude\",\n\t\tattributes: {\n\t\t\ttiddler: {type: \"string\", value: BINARY_WARNING_MESSAGE}\n\t\t}\n\t}]);\n};\n\n/*\nRefresh by refreshing our child widget\n*/\nEditBinaryWidget.prototype.refresh = function(changedTiddlers) {\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports[\"edit-binary\"] = EditBinaryWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/edit-binary.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/edit-bitmap.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/edit-bitmap.js\ntype: application/javascript\nmodule-type: widget\n\nEdit-bitmap widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Default image sizes\nvar DEFAULT_IMAGE_WIDTH = 600,\n\tDEFAULT_IMAGE_HEIGHT = 370;\n\n// Configuration tiddlers\nvar LINE_WIDTH_TITLE = \"$:/config/BitmapEditor/LineWidth\",\n\tLINE_COLOUR_TITLE = \"$:/config/BitmapEditor/Colour\",\n\tLINE_OPACITY_TITLE = \"$:/config/BitmapEditor/Opacity\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EditBitmapWidget = function(parseTreeNode,options) {\n\t// Initialise the editor operations if they've not been done already\n\tif(!this.editorOperations) {\n\t\tEditBitmapWidget.prototype.editorOperations = {};\n\t\t$tw.modules.applyMethods(\"bitmapeditoroperation\",this.editorOperations);\n\t}\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEditBitmapWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEditBitmapWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\t// Create the wrapper for the toolbar and render its content\n\tthis.toolbarNode = this.document.createElement(\"div\");\n\tthis.toolbarNode.className = \"tc-editor-toolbar\";\n\tparent.insertBefore(this.toolbarNode,nextSibling);\n\tthis.domNodes.push(this.toolbarNode);\n\t// Create the on-screen canvas\n\tthis.canvasDomNode = $tw.utils.domMaker(\"canvas\",{\n\t\tdocument: this.document,\n\t\t\"class\":\"tc-edit-bitmapeditor\",\n\t\teventListeners: [{\n\t\t\tname: \"touchstart\", handlerObject: this, handlerMethod: \"handleTouchStartEvent\"\n\t\t},{\n\t\t\tname: \"touchmove\", handlerObject: this, handlerMethod: \"handleTouchMoveEvent\"\n\t\t},{\n\t\t\tname: \"touchend\", handlerObject: this, handlerMethod: \"handleTouchEndEvent\"\n\t\t},{\n\t\t\tname: \"mousedown\", handlerObject: this, handlerMethod: \"handleMouseDownEvent\"\n\t\t},{\n\t\t\tname: \"mousemove\", handlerObject: this, handlerMethod: \"handleMouseMoveEvent\"\n\t\t},{\n\t\t\tname: \"mouseup\", handlerObject: this, handlerMethod: \"handleMouseUpEvent\"\n\t\t}]\n\t});\n\t// Set the width and height variables\n\tthis.setVariable(\"tv-bitmap-editor-width\",this.canvasDomNode.width + \"px\");\n\tthis.setVariable(\"tv-bitmap-editor-height\",this.canvasDomNode.height + \"px\");\n\t// Render toolbar child widgets\n\tthis.renderChildren(this.toolbarNode,null);\n\t// // Insert the elements into the DOM\n\tparent.insertBefore(this.canvasDomNode,nextSibling);\n\tthis.domNodes.push(this.canvasDomNode);\n\t// Load the image into the canvas\n\tif($tw.browser) {\n\t\tthis.loadCanvas();\n\t}\n\t// Add widget message listeners\n\tthis.addEventListeners([\n\t\t{type: \"tm-edit-bitmap-operation\", handler: \"handleEditBitmapOperationMessage\"}\n\t]);\n};\n\n/*\nHandle an edit bitmap operation message from the toolbar\n*/\nEditBitmapWidget.prototype.handleEditBitmapOperationMessage = function(event) {\n\t// Invoke the handler\n\tvar handler = this.editorOperations[event.param];\n\tif(handler) {\n\t\thandler.call(this,event);\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nEditBitmapWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.editTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nJust refresh the toolbar\n*/\nEditBitmapWidget.prototype.refresh = function(changedTiddlers) {\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nSet the bitmap size variables and refresh the toolbar\n*/\nEditBitmapWidget.prototype.refreshToolbar = function() {\n\t// Set the width and height variables\n\tthis.setVariable(\"tv-bitmap-editor-width\",this.canvasDomNode.width + \"px\");\n\tthis.setVariable(\"tv-bitmap-editor-height\",this.canvasDomNode.height + \"px\");\n\t// Refresh each of our child widgets\n\t$tw.utils.each(this.children,function(childWidget) {\n\t\tchildWidget.refreshSelf();\n\t});\n};\n\nEditBitmapWidget.prototype.loadCanvas = function() {\n\tvar tiddler = this.wiki.getTiddler(this.editTitle),\n\t\tcurrImage = new Image();\n\t// Set up event handlers for loading the image\n\tvar self = this;\n\tcurrImage.onload = function() {\n\t\t// Copy the image to the on-screen canvas\n\t\tself.initCanvas(self.canvasDomNode,currImage.width,currImage.height,currImage);\n\t\t// And also copy the current bitmap to the off-screen canvas\n\t\tself.currCanvas = self.document.createElement(\"canvas\");\n\t\tself.initCanvas(self.currCanvas,currImage.width,currImage.height,currImage);\n\t\t// Set the width and height input boxes\n\t\tself.refreshToolbar();\n\t};\n\tcurrImage.onerror = function() {\n\t\t// Set the on-screen canvas size and clear it\n\t\tself.initCanvas(self.canvasDomNode,DEFAULT_IMAGE_WIDTH,DEFAULT_IMAGE_HEIGHT);\n\t\t// Set the off-screen canvas size and clear it\n\t\tself.currCanvas = self.document.createElement(\"canvas\");\n\t\tself.initCanvas(self.currCanvas,DEFAULT_IMAGE_WIDTH,DEFAULT_IMAGE_HEIGHT);\n\t\t// Set the width and height input boxes\n\t\tself.refreshToolbar();\n\t};\n\t// Get the current bitmap into an image object\n\tcurrImage.src = \"data:\" + tiddler.fields.type + \";base64,\" + tiddler.fields.text;\n};\n\nEditBitmapWidget.prototype.initCanvas = function(canvas,width,height,image) {\n\tcanvas.width = width;\n\tcanvas.height = height;\n\tvar ctx = canvas.getContext(\"2d\");\n\tif(image) {\n\t\tctx.drawImage(image,0,0);\n\t} else {\n\t\tctx.fillStyle = \"#fff\";\n\t\tctx.fillRect(0,0,canvas.width,canvas.height);\n\t}\n};\n\n/*\n** Change the size of the canvas, preserving the current image\n*/\nEditBitmapWidget.prototype.changeCanvasSize = function(newWidth,newHeight) {\n\t// Create and size a new canvas\n\tvar newCanvas = this.document.createElement(\"canvas\");\n\tthis.initCanvas(newCanvas,newWidth,newHeight);\n\t// Copy the old image\n\tvar ctx = newCanvas.getContext(\"2d\");\n\tctx.drawImage(this.currCanvas,0,0);\n\t// Set the new canvas as the current one\n\tthis.currCanvas = newCanvas;\n\t// Set the size of the onscreen canvas\n\tthis.canvasDomNode.width = newWidth;\n\tthis.canvasDomNode.height = newHeight;\n\t// Paint the onscreen canvas with the offscreen canvas\n\tctx = this.canvasDomNode.getContext(\"2d\");\n\tctx.drawImage(this.currCanvas,0,0);\n};\n\nEditBitmapWidget.prototype.handleTouchStartEvent = function(event) {\n\tthis.brushDown = true;\n\tthis.strokeStart(event.touches[0].clientX,event.touches[0].clientY);\n\tevent.preventDefault();\n\tevent.stopPropagation();\n\treturn false;\n};\n\nEditBitmapWidget.prototype.handleTouchMoveEvent = function(event) {\n\tif(this.brushDown) {\n\t\tthis.strokeMove(event.touches[0].clientX,event.touches[0].clientY);\n\t}\n\tevent.preventDefault();\n\tevent.stopPropagation();\n\treturn false;\n};\n\nEditBitmapWidget.prototype.handleTouchEndEvent = function(event) {\n\tif(this.brushDown) {\n\t\tthis.brushDown = false;\n\t\tthis.strokeEnd();\n\t}\n\tevent.preventDefault();\n\tevent.stopPropagation();\n\treturn false;\n};\n\nEditBitmapWidget.prototype.handleMouseDownEvent = function(event) {\n\tthis.strokeStart(event.clientX,event.clientY);\n\tthis.brushDown = true;\n\tevent.preventDefault();\n\tevent.stopPropagation();\n\treturn false;\n};\n\nEditBitmapWidget.prototype.handleMouseMoveEvent = function(event) {\n\tif(this.brushDown) {\n\t\tthis.strokeMove(event.clientX,event.clientY);\n\t\tevent.preventDefault();\n\t\tevent.stopPropagation();\n\t\treturn false;\n\t}\n\treturn true;\n};\n\nEditBitmapWidget.prototype.handleMouseUpEvent = function(event) {\n\tif(this.brushDown) {\n\t\tthis.brushDown = false;\n\t\tthis.strokeEnd();\n\t\tevent.preventDefault();\n\t\tevent.stopPropagation();\n\t\treturn false;\n\t}\n\treturn true;\n};\n\nEditBitmapWidget.prototype.adjustCoordinates = function(x,y) {\n\tvar canvasRect = this.canvasDomNode.getBoundingClientRect(),\n\t\tscale = this.canvasDomNode.width/canvasRect.width;\n\treturn {x: (x - canvasRect.left) * scale, y: (y - canvasRect.top) * scale};\n};\n\nEditBitmapWidget.prototype.strokeStart = function(x,y) {\n\t// Start off a new stroke\n\tthis.stroke = [this.adjustCoordinates(x,y)];\n};\n\nEditBitmapWidget.prototype.strokeMove = function(x,y) {\n\tvar ctx = this.canvasDomNode.getContext(\"2d\"),\n\t\tt;\n\t// Add the new position to the end of the stroke\n\tthis.stroke.push(this.adjustCoordinates(x,y));\n\t// Redraw the previous image\n\tctx.drawImage(this.currCanvas,0,0);\n\t// Render the stroke\n\tctx.globalAlpha = parseFloat(this.wiki.getTiddlerText(LINE_OPACITY_TITLE,\"1.0\"));\n\tctx.strokeStyle = this.wiki.getTiddlerText(LINE_COLOUR_TITLE,\"#ff0\");\n\tctx.lineWidth = parseFloat(this.wiki.getTiddlerText(LINE_WIDTH_TITLE,\"3\"));\n\tctx.lineCap = \"round\";\n\tctx.lineJoin = \"round\";\n\tctx.beginPath();\n\tctx.moveTo(this.stroke[0].x,this.stroke[0].y);\n\tfor(t=1; t<this.stroke.length-1; t++) {\n\t\tvar s1 = this.stroke[t],\n\t\t\ts2 = this.stroke[t-1],\n\t\t\ttx = (s1.x + s2.x)/2,\n\t\t\tty = (s1.y + s2.y)/2;\n\t\tctx.quadraticCurveTo(s2.x,s2.y,tx,ty);\n\t}\n\tctx.stroke();\n};\n\nEditBitmapWidget.prototype.strokeEnd = function() {\n\t// Copy the bitmap to the off-screen canvas\n\tvar ctx = this.currCanvas.getContext(\"2d\");\n\tctx.drawImage(this.canvasDomNode,0,0);\n\t// Save the image into the tiddler\n\tthis.saveChanges();\n};\n\nEditBitmapWidget.prototype.saveChanges = function() {\n\tvar tiddler = this.wiki.getTiddler(this.editTitle);\n\tif(tiddler) {\n\t\t// data URIs look like \"data:<type>;base64,<text>\"\n\t\tvar dataURL = this.canvasDomNode.toDataURL(tiddler.fields.type),\n\t\t\tposColon = dataURL.indexOf(\":\"),\n\t\t\tposSemiColon = dataURL.indexOf(\";\"),\n\t\t\tposComma = dataURL.indexOf(\",\"),\n\t\t\ttype = dataURL.substring(posColon+1,posSemiColon),\n\t\t\ttext = dataURL.substring(posComma+1);\n\t\tvar update = {type: type, text: text};\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(this.wiki.getModificationFields(),tiddler,update,this.wiki.getCreationFields()));\n\t}\n};\n\nexports[\"edit-bitmap\"] = EditBitmapWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/edit-bitmap.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/edit-shortcut.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/edit-shortcut.js\ntype: application/javascript\nmodule-type: widget\n\nWidget to display an editable keyboard shortcut\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EditShortcutWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEditShortcutWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEditShortcutWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.inputNode = this.document.createElement(\"input\");\n\t// Assign classes\n\tif(this.shortcutClass) {\n\t\tthis.inputNode.className = this.shortcutClass;\t\t\n\t}\n\t// Assign other attributes\n\tif(this.shortcutStyle) {\n\t\tthis.inputNode.setAttribute(\"style\",this.shortcutStyle);\n\t}\n\tif(this.shortcutTooltip) {\n\t\tthis.inputNode.setAttribute(\"title\",this.shortcutTooltip);\n\t}\n\tif(this.shortcutPlaceholder) {\n\t\tthis.inputNode.setAttribute(\"placeholder\",this.shortcutPlaceholder);\n\t}\n\tif(this.shortcutAriaLabel) {\n\t\tthis.inputNode.setAttribute(\"aria-label\",this.shortcutAriaLabel);\n\t}\n\t// Assign the current shortcut\n\tthis.updateInputNode();\n\t// Add event handlers\n\t$tw.utils.addEventListeners(this.inputNode,[\n\t\t{name: \"keydown\", handlerObject: this, handlerMethod: \"handleKeydownEvent\"}\n\t]);\n\t// Link into the DOM\n\tparent.insertBefore(this.inputNode,nextSibling);\n\tthis.domNodes.push(this.inputNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nEditShortcutWidget.prototype.execute = function() {\n\tthis.shortcutTiddler = this.getAttribute(\"tiddler\");\n\tthis.shortcutField = this.getAttribute(\"field\");\n\tthis.shortcutIndex = this.getAttribute(\"index\");\n\tthis.shortcutPlaceholder = this.getAttribute(\"placeholder\");\n\tthis.shortcutDefault = this.getAttribute(\"default\",\"\");\n\tthis.shortcutClass = this.getAttribute(\"class\");\n\tthis.shortcutStyle = this.getAttribute(\"style\");\n\tthis.shortcutTooltip = this.getAttribute(\"tooltip\");\n\tthis.shortcutAriaLabel = this.getAttribute(\"aria-label\");\n};\n\n/*\nUpdate the value of the input node\n*/\nEditShortcutWidget.prototype.updateInputNode = function() {\n\tif(this.shortcutField) {\n\t\tvar tiddler = this.wiki.getTiddler(this.shortcutTiddler);\n\t\tif(tiddler && $tw.utils.hop(tiddler.fields,this.shortcutField)) {\n\t\t\tthis.inputNode.value = tiddler.getFieldString(this.shortcutField);\n\t\t} else {\n\t\t\tthis.inputNode.value = this.shortcutDefault;\n\t\t}\n\t} else if(this.shortcutIndex) {\n\t\tthis.inputNode.value = this.wiki.extractTiddlerDataItem(this.shortcutTiddler,this.shortcutIndex,this.shortcutDefault);\n\t} else {\n\t\tthis.inputNode.value = this.wiki.getTiddlerText(this.shortcutTiddler,this.shortcutDefault);\n\t}\n};\n\n/*\nHandle a dom \"keydown\" event\n*/\nEditShortcutWidget.prototype.handleKeydownEvent = function(event) {\n\t// Ignore shift, ctrl, meta, alt\n\tif(event.keyCode && $tw.keyboardManager.getModifierKeys().indexOf(event.keyCode) === -1) {\n\t\t// Get the shortcut text representation\n\t\tvar value = $tw.keyboardManager.getPrintableShortcuts([{\n\t\t\tctrlKey: event.ctrlKey,\n\t\t\tshiftKey: event.shiftKey,\n\t\t\taltKey: event.altKey,\n\t\t\tmetaKey: event.metaKey,\n\t\t\tkeyCode: event.keyCode\n\t\t}]);\n\t\tif(value.length > 0) {\n\t\t\tthis.wiki.setText(this.shortcutTiddler,this.shortcutField,this.shortcutIndex,value[0]);\n\t\t}\n\t\t// Ignore the keydown if it was already handled\n\t\tevent.preventDefault();\n\t\tevent.stopPropagation();\n\t\treturn true;\t\t\n\t} else {\n\t\treturn false;\n\t}\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget needed re-rendering\n*/\nEditShortcutWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.index || changedAttributes.placeholder || changedAttributes[\"default\"] || changedAttributes[\"class\"] || changedAttributes.style || changedAttributes.tooltip || changedAttributes[\"aria-label\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else if(changedTiddlers[this.shortcutTiddler]) {\n\t\tthis.updateInputNode();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports[\"edit-shortcut\"] = EditShortcutWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/edit-shortcut.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/edit-text.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/edit-text.js\ntype: application/javascript\nmodule-type: widget\n\nEdit-text widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar editTextWidgetFactory = require(\"$:/core/modules/editor/factory.js\").editTextWidgetFactory,\n\tFramedEngine = require(\"$:/core/modules/editor/engines/framed.js\").FramedEngine,\n\tSimpleEngine = require(\"$:/core/modules/editor/engines/simple.js\").SimpleEngine;\n\nexports[\"edit-text\"] = editTextWidgetFactory(FramedEngine,SimpleEngine);\n\n})();\n",
"title": "$:/core/modules/widgets/edit-text.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/edit.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/edit.js\ntype: application/javascript\nmodule-type: widget\n\nEdit widget is a meta-widget chooses the appropriate actual editting widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EditWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEditWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEditWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n// Mappings from content type to editor type are stored in tiddlers with this prefix\nvar EDITOR_MAPPING_PREFIX = \"$:/config/EditorTypeMappings/\";\n\n/*\nCompute the internal state of the widget\n*/\nEditWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.editTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.editField = this.getAttribute(\"field\",\"text\");\n\tthis.editIndex = this.getAttribute(\"index\");\n\tthis.editClass = this.getAttribute(\"class\");\n\tthis.editPlaceholder = this.getAttribute(\"placeholder\");\n\t// Choose the appropriate edit widget\n\tthis.editorType = this.getEditorType();\n\t// Make the child widgets\n\tthis.makeChildWidgets([{\n\t\ttype: \"edit-\" + this.editorType,\n\t\tattributes: {\n\t\t\ttiddler: {type: \"string\", value: this.editTitle},\n\t\t\tfield: {type: \"string\", value: this.editField},\n\t\t\tindex: {type: \"string\", value: this.editIndex},\n\t\t\t\"class\": {type: \"string\", value: this.editClass},\n\t\t\t\"placeholder\": {type: \"string\", value: this.editPlaceholder}\n\t\t},\n\t\tchildren: this.parseTreeNode.children\n\t}]);\n};\n\nEditWidget.prototype.getEditorType = function() {\n\t// Get the content type of the thing we're editing\n\tvar type;\n\tif(this.editField === \"text\") {\n\t\tvar tiddler = this.wiki.getTiddler(this.editTitle);\n\t\tif(tiddler) {\n\t\t\ttype = tiddler.fields.type;\n\t\t}\n\t}\n\ttype = type || \"text/vnd.tiddlywiki\";\n\tvar editorType = this.wiki.getTiddlerText(EDITOR_MAPPING_PREFIX + type);\n\tif(!editorType) {\n\t\tvar typeInfo = $tw.config.contentTypeInfo[type];\n\t\tif(typeInfo && typeInfo.encoding === \"base64\") {\n\t\t\teditorType = \"binary\";\n\t\t} else {\n\t\t\teditorType = \"text\";\n\t\t}\n\t}\n\treturn editorType;\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nEditWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\t// Refresh if an attribute has changed, or the type associated with the target tiddler has changed\n\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.index || (changedTiddlers[this.editTitle] && this.getEditorType() !== this.editorType)) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nexports.edit = EditWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/edit.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/element.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/element.js\ntype: application/javascript\nmodule-type: widget\n\nElement widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ElementWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nElementWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nElementWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Neuter blacklisted elements\n\tvar tag = this.parseTreeNode.tag;\n\tif($tw.config.htmlUnsafeElements.indexOf(tag) !== -1) {\n\t\ttag = \"safe-\" + tag;\n\t}\n\tvar domNode = this.document.createElementNS(this.namespace,tag);\n\tthis.assignAttributes(domNode,{excludeEventAttributes: true});\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nElementWidget.prototype.execute = function() {\n\t// Select the namespace for the tag\n\tvar tagNamespaces = {\n\t\t\tsvg: \"http://www.w3.org/2000/svg\",\n\t\t\tmath: \"http://www.w3.org/1998/Math/MathML\",\n\t\t\tbody: \"http://www.w3.org/1999/xhtml\"\n\t\t};\n\tthis.namespace = tagNamespaces[this.parseTreeNode.tag];\n\tif(this.namespace) {\n\t\tthis.setVariable(\"namespace\",this.namespace);\n\t} else {\n\t\tthis.namespace = this.getVariable(\"namespace\",{defaultValue: \"http://www.w3.org/1999/xhtml\"});\n\t}\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nElementWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes(),\n\t\thasChangedAttributes = $tw.utils.count(changedAttributes) > 0;\n\tif(hasChangedAttributes) {\n\t\t// Update our attributes\n\t\tthis.assignAttributes(this.domNodes[0],{excludeEventAttributes: true});\n\t}\n\treturn this.refreshChildren(changedTiddlers) || hasChangedAttributes;\n};\n\nexports.element = ElementWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/element.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/encrypt.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/encrypt.js\ntype: application/javascript\nmodule-type: widget\n\nEncrypt widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EncryptWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEncryptWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEncryptWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar textNode = this.document.createTextNode(this.encryptedText);\n\tparent.insertBefore(textNode,nextSibling);\n\tthis.domNodes.push(textNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nEncryptWidget.prototype.execute = function() {\n\t// Get parameters from our attributes\n\tthis.filter = this.getAttribute(\"filter\",\"[!is[system]]\");\n\t// Encrypt the filtered tiddlers\n\tvar tiddlers = this.wiki.filterTiddlers(this.filter),\n\t\tjson = {},\n\t\tself = this;\n\t$tw.utils.each(tiddlers,function(title) {\n\t\tvar tiddler = self.wiki.getTiddler(title),\n\t\t\tjsonTiddler = {};\n\t\tfor(var f in tiddler.fields) {\n\t\t\tjsonTiddler[f] = tiddler.getFieldString(f);\n\t\t}\n\t\tjson[title] = jsonTiddler;\n\t});\n\tthis.encryptedText = $tw.utils.htmlEncode($tw.crypto.encrypt(JSON.stringify(json)));\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nEncryptWidget.prototype.refresh = function(changedTiddlers) {\n\t// We don't need to worry about refreshing because the encrypt widget isn't for interactive use\n\treturn false;\n};\n\nexports.encrypt = EncryptWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/encrypt.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/entity.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/entity.js\ntype: application/javascript\nmodule-type: widget\n\nHTML entity widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar EntityWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nEntityWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nEntityWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.execute();\n\tvar entityString = this.getAttribute(\"entity\",this.parseTreeNode.entity || \"\"),\n\t\ttextNode = this.document.createTextNode($tw.utils.entityDecode(entityString));\n\tparent.insertBefore(textNode,nextSibling);\n\tthis.domNodes.push(textNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nEntityWidget.prototype.execute = function() {\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nEntityWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.entity) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports.entity = EntityWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/entity.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/fieldmangler.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/fieldmangler.js\ntype: application/javascript\nmodule-type: widget\n\nField mangler widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar FieldManglerWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.addEventListeners([\n\t\t{type: \"tm-remove-field\", handler: \"handleRemoveFieldEvent\"},\n\t\t{type: \"tm-add-field\", handler: \"handleAddFieldEvent\"},\n\t\t{type: \"tm-remove-tag\", handler: \"handleRemoveTagEvent\"},\n\t\t{type: \"tm-add-tag\", handler: \"handleAddTagEvent\"}\n\t]);\n};\n\n/*\nInherit from the base widget class\n*/\nFieldManglerWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nFieldManglerWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nFieldManglerWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.mangleTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nFieldManglerWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nFieldManglerWidget.prototype.handleRemoveFieldEvent = function(event) {\n\tvar tiddler = this.wiki.getTiddler(this.mangleTitle),\n\t\tdeletion = {};\n\tdeletion[event.param] = undefined;\n\tthis.wiki.addTiddler(new $tw.Tiddler(tiddler,deletion));\n\treturn true;\n};\n\nFieldManglerWidget.prototype.handleAddFieldEvent = function(event) {\n\tvar tiddler = this.wiki.getTiddler(this.mangleTitle),\n\t\taddition = this.wiki.getModificationFields(),\n\t\thadInvalidFieldName = false,\n\t\taddField = function(name,value) {\n\t\t\tvar trimmedName = name.toLowerCase().trim();\n\t\t\tif(!$tw.utils.isValidFieldName(trimmedName)) {\n\t\t\t\tif(!hadInvalidFieldName) {\n\t\t\t\t\talert($tw.language.getString(\n\t\t\t\t\t\t\"InvalidFieldName\",\n\t\t\t\t\t\t{variables:\n\t\t\t\t\t\t\t{fieldName: trimmedName}\n\t\t\t\t\t\t}\n\t\t\t\t\t));\n\t\t\t\t\thadInvalidFieldName = true;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\tif(!value && tiddler) {\n\t\t\t\t\tvalue = tiddler.fields[trimmedName];\n\t\t\t\t}\n\t\t\t\taddition[trimmedName] = value || \"\";\n\t\t\t}\n\t\t\treturn;\n\t\t};\n\taddition.title = this.mangleTitle;\n\tif(typeof event.param === \"string\") {\n\t\taddField(event.param,\"\");\n\t}\n\tif(typeof event.paramObject === \"object\") {\n\t\tfor(var name in event.paramObject) {\n\t\t\taddField(name,event.paramObject[name]);\n\t\t}\n\t}\n\tthis.wiki.addTiddler(new $tw.Tiddler(tiddler,addition));\n\treturn true;\n};\n\nFieldManglerWidget.prototype.handleRemoveTagEvent = function(event) {\n\tvar tiddler = this.wiki.getTiddler(this.mangleTitle);\n\tif(tiddler && tiddler.fields.tags) {\n\t\tvar p = tiddler.fields.tags.indexOf(event.param);\n\t\tif(p !== -1) {\n\t\t\tvar modification = this.wiki.getModificationFields();\n\t\t\tmodification.tags = (tiddler.fields.tags || []).slice(0);\n\t\t\tmodification.tags.splice(p,1);\n\t\t\tif(modification.tags.length === 0) {\n\t\t\t\tmodification.tags = undefined;\n\t\t\t}\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(tiddler,modification));\n\t\t}\n\t}\n\treturn true;\n};\n\nFieldManglerWidget.prototype.handleAddTagEvent = function(event) {\n\tvar tiddler = this.wiki.getTiddler(this.mangleTitle);\n\tif(tiddler && typeof event.param === \"string\") {\n\t\tvar tag = event.param.trim();\n\t\tif(tag !== \"\") {\n\t\t\tvar modification = this.wiki.getModificationFields();\n\t\t\tmodification.tags = (tiddler.fields.tags || []).slice(0);\n\t\t\t$tw.utils.pushTop(modification.tags,tag);\n\t\t\tthis.wiki.addTiddler(new $tw.Tiddler(tiddler,modification));\t\t\t\n\t\t}\n\t} else if(typeof event.param === \"string\" && event.param.trim() !== \"\" && this.mangleTitle.trim() !== \"\") {\n\t\tvar tag = [];\n\t\ttag.push(event.param.trim());\n\t\tthis.wiki.addTiddler({title: this.mangleTitle, tags: tag});\t\t\n\t}\n\treturn true;\n};\n\nexports.fieldmangler = FieldManglerWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/fieldmangler.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/fields.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/fields.js\ntype: application/javascript\nmodule-type: widget\n\nFields widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar FieldsWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nFieldsWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nFieldsWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar textNode = this.document.createTextNode(this.text);\n\tparent.insertBefore(textNode,nextSibling);\n\tthis.domNodes.push(textNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nFieldsWidget.prototype.execute = function() {\n\t// Get parameters from our attributes\n\tthis.tiddlerTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.template = this.getAttribute(\"template\");\n\tthis.exclude = this.getAttribute(\"exclude\");\n\tthis.stripTitlePrefix = this.getAttribute(\"stripTitlePrefix\",\"no\") === \"yes\";\n\t// Get the value to display\n\tvar tiddler = this.wiki.getTiddler(this.tiddlerTitle);\n\t// Get the exclusion list\n\tvar exclude;\n\tif(this.exclude) {\n\t\texclude = this.exclude.split(\" \");\n\t} else {\n\t\texclude = [\"text\"]; \n\t}\n\t// Compose the template\n\tvar text = [];\n\tif(this.template && tiddler) {\n\t\tvar fields = [];\n\t\tfor(var fieldName in tiddler.fields) {\n\t\t\tif(exclude.indexOf(fieldName) === -1) {\n\t\t\t\tfields.push(fieldName);\n\t\t\t}\n\t\t}\n\t\tfields.sort();\n\t\tfor(var f=0; f<fields.length; f++) {\n\t\t\tfieldName = fields[f];\n\t\t\tif(exclude.indexOf(fieldName) === -1) {\n\t\t\t\tvar row = this.template,\n\t\t\t\t\tvalue = tiddler.getFieldString(fieldName);\n\t\t\t\tif(this.stripTitlePrefix && fieldName === \"title\") {\n\t\t\t\t\tvar reStrip = /^\\{[^\\}]+\\}(.+)/mg,\n\t\t\t\t\t\treMatch = reStrip.exec(value);\n\t\t\t\t\tif(reMatch) {\n\t\t\t\t\t\tvalue = reMatch[1];\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\trow = row.replace(\"$name$\",fieldName);\n\t\t\t\trow = row.replace(\"$value$\",value);\n\t\t\t\trow = row.replace(\"$encoded_value$\",$tw.utils.htmlEncode(value));\n\t\t\t\ttext.push(row);\n\t\t\t}\n\t\t}\n\t}\n\tthis.text = text.join(\"\");\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nFieldsWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.template || changedAttributes.exclude || changedAttributes.stripTitlePrefix || changedTiddlers[this.tiddlerTitle]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports.fields = FieldsWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/fields.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/image.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/image.js\ntype: application/javascript\nmodule-type: widget\n\nThe image widget displays an image referenced with an external URI or with a local tiddler title.\n\n```\n<$image src=\"TiddlerTitle\" width=\"320\" height=\"400\" class=\"classnames\">\n```\n\nThe image source can be the title of an existing tiddler or the URL of an external image.\n\nExternal images always generate an HTML `<img>` tag.\n\nTiddlers that have a _canonical_uri field generate an HTML `<img>` tag with the src attribute containing the URI.\n\nTiddlers that contain image data generate an HTML `<img>` tag with the src attribute containing a base64 representation of the image.\n\nTiddlers that contain wikitext could be rendered to a DIV of the usual size of a tiddler, and then transformed to the size requested.\n\nThe width and height attributes are interpreted as a number of pixels, and do not need to include the \"px\" suffix.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ImageWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nImageWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nImageWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create element\n\t// Determine what type of image it is\n\tvar tag = \"img\", src = \"\",\n\t\ttiddler = this.wiki.getTiddler(this.imageSource);\n\tif(!tiddler) {\n\t\t// The source isn't the title of a tiddler, so we'll assume it's a URL\n\t\tsrc = this.getVariable(\"tv-get-export-image-link\",{params: [{name: \"src\",value: this.imageSource}],defaultValue: this.imageSource});\n\t} else {\n\t\t// Check if it is an image tiddler\n\t\tif(this.wiki.isImageTiddler(this.imageSource)) {\n\t\t\tvar type = tiddler.fields.type,\n\t\t\t\ttext = tiddler.fields.text,\n\t\t\t\t_canonical_uri = tiddler.fields._canonical_uri;\n\t\t\t// If the tiddler has body text then it doesn't need to be lazily loaded\n\t\t\tif(text) {\n\t\t\t\t// Render the appropriate element for the image type\n\t\t\t\tswitch(type) {\n\t\t\t\t\tcase \"application/pdf\":\n\t\t\t\t\t\ttag = \"embed\";\n\t\t\t\t\t\tsrc = \"data:application/pdf;base64,\" + text;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase \"image/svg+xml\":\n\t\t\t\t\t\tsrc = \"data:image/svg+xml,\" + encodeURIComponent(text);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tdefault:\n\t\t\t\t\t\tsrc = \"data:\" + type + \";base64,\" + text;\n\t\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t} else if(_canonical_uri) {\n\t\t\t\tswitch(type) {\n\t\t\t\t\tcase \"application/pdf\":\n\t\t\t\t\t\ttag = \"embed\";\n\t\t\t\t\t\tsrc = _canonical_uri;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase \"image/svg+xml\":\n\t\t\t\t\t\tsrc = _canonical_uri;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tdefault:\n\t\t\t\t\t\tsrc = _canonical_uri;\n\t\t\t\t\t\tbreak;\n\t\t\t\t}\t\n\t\t\t} else {\n\t\t\t\t// Just trigger loading of the tiddler\n\t\t\t\tthis.wiki.getTiddlerText(this.imageSource);\n\t\t\t}\n\t\t}\n\t}\n\t// Create the element and assign the attributes\n\tvar domNode = this.document.createElement(tag);\n\tdomNode.setAttribute(\"src\",src);\n\tif(this.imageClass) {\n\t\tdomNode.setAttribute(\"class\",this.imageClass);\t\t\n\t}\n\tif(this.imageWidth) {\n\t\tdomNode.setAttribute(\"width\",this.imageWidth);\n\t}\n\tif(this.imageHeight) {\n\t\tdomNode.setAttribute(\"height\",this.imageHeight);\n\t}\n\tif(this.imageTooltip) {\n\t\tdomNode.setAttribute(\"title\",this.imageTooltip);\t\t\n\t}\n\tif(this.imageAlt) {\n\t\tdomNode.setAttribute(\"alt\",this.imageAlt);\t\t\n\t}\n\t// Insert element\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.domNodes.push(domNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nImageWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.imageSource = this.getAttribute(\"source\");\n\tthis.imageWidth = this.getAttribute(\"width\");\n\tthis.imageHeight = this.getAttribute(\"height\");\n\tthis.imageClass = this.getAttribute(\"class\");\n\tthis.imageTooltip = this.getAttribute(\"tooltip\");\n\tthis.imageAlt = this.getAttribute(\"alt\");\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nImageWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.source || changedAttributes.width || changedAttributes.height || changedAttributes[\"class\"] || changedAttributes.tooltip || changedTiddlers[this.imageSource]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\t\n\t}\n};\n\nexports.image = ImageWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/image.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/importvariables.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/importvariables.js\ntype: application/javascript\nmodule-type: widget\n\nImport variable definitions from other tiddlers\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ImportVariablesWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nImportVariablesWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nImportVariablesWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nImportVariablesWidget.prototype.execute = function(tiddlerList) {\n\tvar self = this;\n\t// Get our parameters\n\tthis.filter = this.getAttribute(\"filter\");\n\t// Compute the filter\n\tthis.tiddlerList = tiddlerList || this.wiki.filterTiddlers(this.filter,this);\n\t// Accumulate the <$set> widgets from each tiddler\n\tvar widgetStackStart,widgetStackEnd;\n\tfunction addWidgetNode(widgetNode) {\n\t\tif(widgetNode) {\n\t\t\tif(!widgetStackStart && !widgetStackEnd) {\n\t\t\t\twidgetStackStart = widgetNode;\n\t\t\t\twidgetStackEnd = widgetNode;\n\t\t\t} else {\n\t\t\t\twidgetStackEnd.children = [widgetNode];\n\t\t\t\twidgetStackEnd = widgetNode;\n\t\t\t}\n\t\t}\n\t}\n\t$tw.utils.each(this.tiddlerList,function(title) {\n\t\tvar parser = self.wiki.parseTiddler(title);\n\t\tif(parser) {\n\t\t\tvar parseTreeNode = parser.tree[0];\n\t\t\twhile(parseTreeNode && parseTreeNode.type === \"set\") {\n\t\t\t\taddWidgetNode({\n\t\t\t\t\ttype: \"set\",\n\t\t\t\t\tattributes: parseTreeNode.attributes,\n\t\t\t\t\tparams: parseTreeNode.params\n\t\t\t\t});\n\t\t\t\tparseTreeNode = parseTreeNode.children[0];\n\t\t\t}\n\t\t} \n\t});\n\t// Add our own children to the end of the pile\n\tvar parseTreeNodes;\n\tif(widgetStackStart && widgetStackEnd) {\n\t\tparseTreeNodes = [widgetStackStart];\n\t\twidgetStackEnd.children = this.parseTreeNode.children;\n\t} else {\n\t\tparseTreeNodes = this.parseTreeNode.children;\n\t}\n\t// Construct the child widgets\n\tthis.makeChildWidgets(parseTreeNodes);\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nImportVariablesWidget.prototype.refresh = function(changedTiddlers) {\n\t// Recompute our attributes and the filter list\n\tvar changedAttributes = this.computeAttributes(),\n\t\ttiddlerList = this.wiki.filterTiddlers(this.getAttribute(\"filter\"),this);\n\t// Refresh if the filter has changed, or the list of tiddlers has changed, or any of the tiddlers in the list has changed\n\tfunction haveListedTiddlersChanged() {\n\t\tvar changed = false;\n\t\ttiddlerList.forEach(function(title) {\n\t\t\tif(changedTiddlers[title]) {\n\t\t\t\tchanged = true;\n\t\t\t}\n\t\t});\n\t\treturn changed;\n\t}\n\tif(changedAttributes.filter || !$tw.utils.isArrayEqual(this.tiddlerList,tiddlerList) || haveListedTiddlersChanged()) {\n\t\t// Compute the filter\n\t\tthis.removeChildDomNodes();\n\t\tthis.execute(tiddlerList);\n\t\tthis.renderChildren(this.parentDomNode,this.findNextSiblingDomNode());\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nexports.importvariables = ImportVariablesWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/importvariables.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/keyboard.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/keyboard.js\ntype: application/javascript\nmodule-type: widget\n\nKeyboard shortcut widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar KeyboardWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nKeyboardWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nKeyboardWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Remember parent\n\tthis.parentDomNode = parent;\n\t// Compute attributes and execute state\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create element\n\tvar domNode = this.document.createElement(\"div\");\n\t// Assign classes\n\tvar classes = (this[\"class\"] || \"\").split(\" \");\n\tclasses.push(\"tc-keyboard\");\n\tdomNode.className = classes.join(\" \");\n\t// Add a keyboard event handler\n\tdomNode.addEventListener(\"keydown\",function (event) {\n\t\tif($tw.keyboardManager.checkKeyDescriptors(event,self.keyInfoArray)) {\n\t\t\tself.invokeActions(self,event);\n\t\t\tif(self.actions) {\n\t\t\t\tself.invokeActionString(self.actions,self,event);\n\t\t\t}\n\t\t\tself.dispatchMessage(event);\n\t\t\tevent.preventDefault();\n\t\t\tevent.stopPropagation();\n\t\t\treturn true;\n\t\t}\n\t\treturn false;\n\t},false);\n\t// Insert element\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\nKeyboardWidget.prototype.dispatchMessage = function(event) {\n\tthis.dispatchEvent({type: this.message, param: this.param, tiddlerTitle: this.getVariable(\"currentTiddler\")});\n};\n\n/*\nCompute the internal state of the widget\n*/\nKeyboardWidget.prototype.execute = function() {\n\t// Get attributes\n\tthis.actions = this.getAttribute(\"actions\");\n\tthis.message = this.getAttribute(\"message\");\n\tthis.param = this.getAttribute(\"param\");\n\tthis.key = this.getAttribute(\"key\");\n\tthis.keyInfoArray = $tw.keyboardManager.parseKeyDescriptors(this.key);\n\tthis[\"class\"] = this.getAttribute(\"class\");\n\t// Make child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nKeyboardWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.message || changedAttributes.param || changedAttributes.key || changedAttributes[\"class\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.keyboard = KeyboardWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/keyboard.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/link.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/link.js\ntype: application/javascript\nmodule-type: widget\n\nLink widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\nvar MISSING_LINK_CONFIG_TITLE = \"$:/config/MissingLinks\";\n\nvar LinkWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nLinkWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nLinkWidget.prototype.render = function(parent,nextSibling) {\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\t// Get the value of the tv-wikilinks configuration macro\n\tvar wikiLinksMacro = this.getVariable(\"tv-wikilinks\"),\n\t\tuseWikiLinks = wikiLinksMacro ? (wikiLinksMacro.trim() !== \"no\") : true,\n\t\tmissingLinksEnabled = !(this.hideMissingLinks && this.isMissing && !this.isShadow);\n\t// Render the link if required\n\tif(useWikiLinks && missingLinksEnabled) {\n\t\tthis.renderLink(parent,nextSibling);\n\t} else {\n\t\t// Just insert the link text\n\t\tvar domNode = this.document.createElement(\"span\");\n\t\tparent.insertBefore(domNode,nextSibling);\n\t\tthis.renderChildren(domNode,null);\n\t\tthis.domNodes.push(domNode);\n\t}\n};\n\n/*\nRender this widget into the DOM\n*/\nLinkWidget.prototype.renderLink = function(parent,nextSibling) {\n\tvar self = this;\n\t// Sanitise the specified tag\n\tvar tag = this.linkTag;\n\tif($tw.config.htmlUnsafeElements.indexOf(tag) !== -1) {\n\t\ttag = \"a\";\n\t}\n\t// Create our element\n\tvar domNode = this.document.createElement(tag);\n\t// Assign classes\n\tvar classes = [];\n\tif(this.linkClasses) {\n\t\tclasses.push(this.linkClasses);\n\t}\n\tclasses.push(\"tc-tiddlylink\");\n\tif(this.isShadow) {\n\t\tclasses.push(\"tc-tiddlylink-shadow\");\n\t}\n\tif(this.isMissing && !this.isShadow) {\n\t\tclasses.push(\"tc-tiddlylink-missing\");\n\t} else {\n\t\tif(!this.isMissing) {\n\t\t\tclasses.push(\"tc-tiddlylink-resolves\");\n\t\t}\n\t}\n\tdomNode.setAttribute(\"class\",classes.join(\" \"));\n\t// Set an href\n\tvar wikiLinkTemplateMacro = this.getVariable(\"tv-wikilink-template\"),\n\t\twikiLinkTemplate = wikiLinkTemplateMacro ? wikiLinkTemplateMacro.trim() : \"#$uri_encoded$\",\n\t\twikiLinkText = wikiLinkTemplate.replace(\"$uri_encoded$\",encodeURIComponent(this.to));\n\twikiLinkText = wikiLinkText.replace(\"$uri_doubleencoded$\",encodeURIComponent(encodeURIComponent(this.to)));\n\twikiLinkText = this.getVariable(\"tv-get-export-link\",{params: [{name: \"to\",value: this.to}],defaultValue: wikiLinkText});\n\tif(tag === \"a\") {\n\t\tdomNode.setAttribute(\"href\",wikiLinkText);\n\t}\n\tif(this.tabIndex) {\n\t\tdomNode.setAttribute(\"tabindex\",this.tabIndex);\n\t}\n\t// Set the tooltip\n\t// HACK: Performance issues with re-parsing the tooltip prevent us defaulting the tooltip to \"<$transclude field='tooltip'><$transclude field='title'/></$transclude>\"\n\tvar tooltipWikiText = this.tooltip || this.getVariable(\"tv-wikilink-tooltip\");\n\tif(tooltipWikiText) {\n\t\tvar tooltipText = this.wiki.renderText(\"text/plain\",\"text/vnd.tiddlywiki\",tooltipWikiText,{\n\t\t\t\tparseAsInline: true,\n\t\t\t\tvariables: {\n\t\t\t\t\tcurrentTiddler: this.to\n\t\t\t\t},\n\t\t\t\tparentWidget: this\n\t\t\t});\n\t\tdomNode.setAttribute(\"title\",tooltipText);\n\t}\n\tif(this[\"aria-label\"]) {\n\t\tdomNode.setAttribute(\"aria-label\",this[\"aria-label\"]);\n\t}\n\t// Add a click event handler\n\t$tw.utils.addEventListeners(domNode,[\n\t\t{name: \"click\", handlerObject: this, handlerMethod: \"handleClickEvent\"},\n\t]);\n\tif(this.draggable === \"yes\") {\n\t\t$tw.utils.addEventListeners(domNode,[\n\t\t\t{name: \"dragstart\", handlerObject: this, handlerMethod: \"handleDragStartEvent\"},\n\t\t\t{name: \"dragend\", handlerObject: this, handlerMethod: \"handleDragEndEvent\"}\n\t\t]);\n\t}\n\t// Insert the link into the DOM and render any children\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\nLinkWidget.prototype.handleClickEvent = function(event) {\n\t// Send the click on its way as a navigate event\n\tvar bounds = this.domNodes[0].getBoundingClientRect();\n\tthis.dispatchEvent({\n\t\ttype: \"tm-navigate\",\n\t\tnavigateTo: this.to,\n\t\tnavigateFromTitle: this.getVariable(\"storyTiddler\"),\n\t\tnavigateFromNode: this,\n\t\tnavigateFromClientRect: { top: bounds.top, left: bounds.left, width: bounds.width, right: bounds.right, bottom: bounds.bottom, height: bounds.height\n\t\t},\n\t\tnavigateSuppressNavigation: event.metaKey || event.ctrlKey || (event.button === 1)\n\t});\n\tif(this.domNodes[0].hasAttribute(\"href\")) {\n\t\tevent.preventDefault();\n\t}\n\tevent.stopPropagation();\n\treturn false;\n};\n\nLinkWidget.prototype.handleDragStartEvent = function(event) {\n\tif(event.target === this.domNodes[0]) {\n\t\tif(this.to) {\n\t\t\t$tw.dragInProgress = true;\n\t\t\t// Set the dragging class on the element being dragged\n\t\t\t$tw.utils.addClass(event.target,\"tc-tiddlylink-dragging\");\n\t\t\t// Create the drag image elements\n\t\t\tthis.dragImage = this.document.createElement(\"div\");\n\t\t\tthis.dragImage.className = \"tc-tiddler-dragger\";\n\t\t\tvar inner = this.document.createElement(\"div\");\n\t\t\tinner.className = \"tc-tiddler-dragger-inner\";\n\t\t\tinner.appendChild(this.document.createTextNode(this.to));\n\t\t\tthis.dragImage.appendChild(inner);\n\t\t\tthis.document.body.appendChild(this.dragImage);\n\t\t\t// Astoundingly, we need to cover the dragger up: http://www.kryogenix.org/code/browser/custom-drag-image.html\n\t\t\tvar cover = this.document.createElement(\"div\");\n\t\t\tcover.className = \"tc-tiddler-dragger-cover\";\n\t\t\tcover.style.left = (inner.offsetLeft - 16) + \"px\";\n\t\t\tcover.style.top = (inner.offsetTop - 16) + \"px\";\n\t\t\tcover.style.width = (inner.offsetWidth + 32) + \"px\";\n\t\t\tcover.style.height = (inner.offsetHeight + 32) + \"px\";\n\t\t\tthis.dragImage.appendChild(cover);\n\t\t\t// Set the data transfer properties\n\t\t\tvar dataTransfer = event.dataTransfer;\n\t\t\t// First the image\n\t\t\tdataTransfer.effectAllowed = \"copy\";\n\t\t\tif(dataTransfer.setDragImage) {\n\t\t\t\tdataTransfer.setDragImage(this.dragImage.firstChild,-16,-16);\n\t\t\t}\n\t\t\t// Then the data\n\t\t\tdataTransfer.clearData();\n\t\t\tvar jsonData = this.wiki.getTiddlerAsJson(this.to),\n\t\t\t\ttextData = this.wiki.getTiddlerText(this.to,\"\"),\n\t\t\t\ttitle = (new RegExp(\"^\" + $tw.config.textPrimitives.wikiLink + \"$\",\"mg\")).exec(this.to) ? this.to : \"[[\" + this.to + \"]]\";\n\t\t\t// IE doesn't like these content types\n\t\t\tif(!$tw.browser.isIE) {\n\t\t\t\tdataTransfer.setData(\"text/vnd.tiddler\",jsonData);\n\t\t\t\tdataTransfer.setData(\"text/plain\",title);\n\t\t\t\tdataTransfer.setData(\"text/x-moz-url\",\"data:text/vnd.tiddler,\" + encodeURIComponent(jsonData));\n\t\t\t}\n\t\t\tdataTransfer.setData(\"URL\",\"data:text/vnd.tiddler,\" + encodeURIComponent(jsonData));\n\t\t\tdataTransfer.setData(\"Text\",title);\n\t\t\tevent.stopPropagation();\n\t\t} else {\n\t\t\tevent.preventDefault();\n\t\t}\n\t}\n};\n\nLinkWidget.prototype.handleDragEndEvent = function(event) {\n\tif(event.target === this.domNodes[0]) {\n\t\t$tw.dragInProgress = false;\n\t\t// Remove the dragging class on the element being dragged\n\t\t$tw.utils.removeClass(event.target,\"tc-tiddlylink-dragging\");\n\t\t// Delete the drag image element\n\t\tif(this.dragImage) {\n\t\t\tthis.dragImage.parentNode.removeChild(this.dragImage);\n\t\t}\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nLinkWidget.prototype.execute = function() {\n\t// Pick up our attributes\n\tthis.to = this.getAttribute(\"to\",this.getVariable(\"currentTiddler\"));\n\tthis.tooltip = this.getAttribute(\"tooltip\");\n\tthis[\"aria-label\"] = this.getAttribute(\"aria-label\");\n\tthis.linkClasses = this.getAttribute(\"class\");\n\tthis.tabIndex = this.getAttribute(\"tabindex\");\n\tthis.draggable = this.getAttribute(\"draggable\",\"yes\");\n\tthis.linkTag = this.getAttribute(\"tag\",\"a\");\n\t// Determine the link characteristics\n\tthis.isMissing = !this.wiki.tiddlerExists(this.to);\n\tthis.isShadow = this.wiki.isShadowTiddler(this.to);\n\tthis.hideMissingLinks = ($tw.wiki.getTiddlerText(MISSING_LINK_CONFIG_TITLE,\"yes\") === \"no\");\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nLinkWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.to || changedTiddlers[this.to] || changedAttributes[\"aria-label\"] || changedAttributes.tooltip || changedTiddlers[MISSING_LINK_CONFIG_TITLE]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.link = LinkWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/link.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/linkcatcher.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/linkcatcher.js\ntype: application/javascript\nmodule-type: widget\n\nLinkcatcher widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar LinkCatcherWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.addEventListeners([\n\t\t{type: \"tm-navigate\", handler: \"handleNavigateEvent\"}\n\t]);\n};\n\n/*\nInherit from the base widget class\n*/\nLinkCatcherWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nLinkCatcherWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nLinkCatcherWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.catchTo = this.getAttribute(\"to\");\n\tthis.catchMessage = this.getAttribute(\"message\");\n\tthis.catchSet = this.getAttribute(\"set\");\n\tthis.catchSetTo = this.getAttribute(\"setTo\");\n\tthis.catchActions = this.getAttribute(\"actions\");\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nLinkCatcherWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.to || changedAttributes.message || changedAttributes.set || changedAttributes.setTo) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\n/*\nHandle a tm-navigate event\n*/\nLinkCatcherWidget.prototype.handleNavigateEvent = function(event) {\n\tif(this.catchTo) {\n\t\tthis.wiki.setTextReference(this.catchTo,event.navigateTo,this.getVariable(\"currentTiddler\"));\n\t}\n\tif(this.catchMessage && this.parentWidget) {\n\t\tthis.parentWidget.dispatchEvent({\n\t\t\ttype: this.catchMessage,\n\t\t\tparam: event.navigateTo,\n\t\t\tnavigateTo: event.navigateTo\n\t\t});\n\t}\n\tif(this.catchSet) {\n\t\tvar tiddler = this.wiki.getTiddler(this.catchSet);\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(tiddler,{title: this.catchSet, text: this.catchSetTo}));\n\t}\n\tif(this.catchActions) {\n\t\tthis.invokeActionString(this.catchActions,this);\n\t}\n\treturn false;\n};\n\nexports.linkcatcher = LinkCatcherWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/linkcatcher.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/list.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/list.js\ntype: application/javascript\nmodule-type: widget\n\nList and list item widgets\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\n/*\nThe list widget creates list element sub-widgets that reach back into the list widget for their configuration\n*/\n\nvar ListWidget = function(parseTreeNode,options) {\n\t// Initialise the storyviews if they've not been done already\n\tif(!this.storyViews) {\n\t\tListWidget.prototype.storyViews = {};\n\t\t$tw.modules.applyMethods(\"storyview\",this.storyViews);\n\t}\n\t// Main initialisation inherited from widget.js\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nListWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nListWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n\t// Construct the storyview\n\tvar StoryView = this.storyViews[this.storyViewName];\n\tif(StoryView && !this.document.isTiddlyWikiFakeDom) {\n\t\tthis.storyview = new StoryView(this);\n\t} else {\n\t\tthis.storyview = null;\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nListWidget.prototype.execute = function() {\n\t// Get our attributes\n\tthis.template = this.getAttribute(\"template\");\n\tthis.editTemplate = this.getAttribute(\"editTemplate\");\n\tthis.variableName = this.getAttribute(\"variable\",\"currentTiddler\");\n\tthis.storyViewName = this.getAttribute(\"storyview\");\n\tthis.historyTitle = this.getAttribute(\"history\");\n\t// Compose the list elements\n\tthis.list = this.getTiddlerList();\n\tvar members = [],\n\t\tself = this;\n\t// Check for an empty list\n\tif(this.list.length === 0) {\n\t\tmembers = this.getEmptyMessage();\n\t} else {\n\t\t$tw.utils.each(this.list,function(title,index) {\n\t\t\tmembers.push(self.makeItemTemplate(title));\n\t\t});\n\t}\n\t// Construct the child widgets\n\tthis.makeChildWidgets(members);\n\t// Clear the last history\n\tthis.history = [];\n};\n\nListWidget.prototype.getTiddlerList = function() {\n\tvar defaultFilter = \"[!is[system]sort[title]]\";\n\treturn this.wiki.filterTiddlers(this.getAttribute(\"filter\",defaultFilter),this);\n};\n\nListWidget.prototype.getEmptyMessage = function() {\n\tvar emptyMessage = this.getAttribute(\"emptyMessage\",\"\"),\n\t\tparser = this.wiki.parseText(\"text/vnd.tiddlywiki\",emptyMessage,{parseAsInline: true});\n\tif(parser) {\n\t\treturn parser.tree;\n\t} else {\n\t\treturn [];\n\t}\n};\n\n/*\nCompose the template for a list item\n*/\nListWidget.prototype.makeItemTemplate = function(title) {\n\t// Check if the tiddler is a draft\n\tvar tiddler = this.wiki.getTiddler(title),\n\t\tisDraft = tiddler && tiddler.hasField(\"draft.of\"),\n\t\ttemplate = this.template,\n\t\ttemplateTree;\n\tif(isDraft && this.editTemplate) {\n\t\ttemplate = this.editTemplate;\n\t}\n\t// Compose the transclusion of the template\n\tif(template) {\n\t\ttemplateTree = [{type: \"transclude\", attributes: {tiddler: {type: \"string\", value: template}}}];\n\t} else {\n\t\tif(this.parseTreeNode.children && this.parseTreeNode.children.length > 0) {\n\t\t\ttemplateTree = this.parseTreeNode.children;\n\t\t} else {\n\t\t\t// Default template is a link to the title\n\t\t\ttemplateTree = [{type: \"element\", tag: this.parseTreeNode.isBlock ? \"div\" : \"span\", children: [{type: \"link\", attributes: {to: {type: \"string\", value: title}}, children: [\n\t\t\t\t\t{type: \"text\", text: title}\n\t\t\t]}]}];\n\t\t}\n\t}\n\t// Return the list item\n\treturn {type: \"listitem\", itemTitle: title, variableName: this.variableName, children: templateTree};\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nListWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes(),\n\t\tresult;\n\t// Call the storyview\n\tif(this.storyview && this.storyview.refreshStart) {\n\t\tthis.storyview.refreshStart(changedTiddlers,changedAttributes);\n\t}\n\t// Completely refresh if any of our attributes have changed\n\tif(changedAttributes.filter || changedAttributes.template || changedAttributes.editTemplate || changedAttributes.emptyMessage || changedAttributes.storyview || changedAttributes.history) {\n\t\tthis.refreshSelf();\n\t\tresult = true;\n\t} else {\n\t\t// Handle any changes to the list\n\t\tresult = this.handleListChanges(changedTiddlers);\n\t\t// Handle any changes to the history stack\n\t\tif(this.historyTitle && changedTiddlers[this.historyTitle]) {\n\t\t\tthis.handleHistoryChanges();\n\t\t}\n\t}\n\t// Call the storyview\n\tif(this.storyview && this.storyview.refreshEnd) {\n\t\tthis.storyview.refreshEnd(changedTiddlers,changedAttributes);\n\t}\n\treturn result;\n};\n\n/*\nHandle any changes to the history list\n*/\nListWidget.prototype.handleHistoryChanges = function() {\n\t// Get the history data\n\tvar newHistory = this.wiki.getTiddlerDataCached(this.historyTitle,[]);\n\t// Ignore any entries of the history that match the previous history\n\tvar entry = 0;\n\twhile(entry < newHistory.length && entry < this.history.length && newHistory[entry].title === this.history[entry].title) {\n\t\tentry++;\n\t}\n\t// Navigate forwards to each of the new tiddlers\n\twhile(entry < newHistory.length) {\n\t\tif(this.storyview && this.storyview.navigateTo) {\n\t\t\tthis.storyview.navigateTo(newHistory[entry]);\n\t\t}\n\t\tentry++;\n\t}\n\t// Update the history\n\tthis.history = newHistory;\n};\n\n/*\nProcess any changes to the list\n*/\nListWidget.prototype.handleListChanges = function(changedTiddlers) {\n\t// Get the new list\n\tvar prevList = this.list;\n\tthis.list = this.getTiddlerList();\n\t// Check for an empty list\n\tif(this.list.length === 0) {\n\t\t// Check if it was empty before\n\t\tif(prevList.length === 0) {\n\t\t\t// If so, just refresh the empty message\n\t\t\treturn this.refreshChildren(changedTiddlers);\n\t\t} else {\n\t\t\t// Replace the previous content with the empty message\n\t\t\tfor(t=this.children.length-1; t>=0; t--) {\n\t\t\t\tthis.removeListItem(t);\n\t\t\t}\n\t\t\tvar nextSibling = this.findNextSiblingDomNode();\n\t\t\tthis.makeChildWidgets(this.getEmptyMessage());\n\t\t\tthis.renderChildren(this.parentDomNode,nextSibling);\n\t\t\treturn true;\n\t\t}\n\t} else {\n\t\t// If the list was empty then we need to remove the empty message\n\t\tif(prevList.length === 0) {\n\t\t\tthis.removeChildDomNodes();\n\t\t\tthis.children = [];\n\t\t}\n\t\t// Cycle through the list, inserting and removing list items as needed\n\t\tvar hasRefreshed = false;\n\t\tfor(var t=0; t<this.list.length; t++) {\n\t\t\tvar index = this.findListItem(t,this.list[t]);\n\t\t\tif(index === undefined) {\n\t\t\t\t// The list item must be inserted\n\t\t\t\tthis.insertListItem(t,this.list[t]);\n\t\t\t\thasRefreshed = true;\n\t\t\t} else {\n\t\t\t\t// There are intervening list items that must be removed\n\t\t\t\tfor(var n=index-1; n>=t; n--) {\n\t\t\t\t\tthis.removeListItem(n);\n\t\t\t\t\thasRefreshed = true;\n\t\t\t\t}\n\t\t\t\t// Refresh the item we're reusing\n\t\t\t\tvar refreshed = this.children[t].refresh(changedTiddlers);\n\t\t\t\thasRefreshed = hasRefreshed || refreshed;\n\t\t\t}\n\t\t}\n\t\t// Remove any left over items\n\t\tfor(t=this.children.length-1; t>=this.list.length; t--) {\n\t\t\tthis.removeListItem(t);\n\t\t\thasRefreshed = true;\n\t\t}\n\t\treturn hasRefreshed;\n\t}\n};\n\n/*\nFind the list item with a given title, starting from a specified position\n*/\nListWidget.prototype.findListItem = function(startIndex,title) {\n\twhile(startIndex < this.children.length) {\n\t\tif(this.children[startIndex].parseTreeNode.itemTitle === title) {\n\t\t\treturn startIndex;\n\t\t}\n\t\tstartIndex++;\n\t}\n\treturn undefined;\n};\n\n/*\nInsert a new list item at the specified index\n*/\nListWidget.prototype.insertListItem = function(index,title) {\n\t// Create, insert and render the new child widgets\n\tvar widget = this.makeChildWidget(this.makeItemTemplate(title));\n\twidget.parentDomNode = this.parentDomNode; // Hack to enable findNextSiblingDomNode() to work\n\tthis.children.splice(index,0,widget);\n\tvar nextSibling = widget.findNextSiblingDomNode();\n\twidget.render(this.parentDomNode,nextSibling);\n\t// Animate the insertion if required\n\tif(this.storyview && this.storyview.insert) {\n\t\tthis.storyview.insert(widget);\n\t}\n\treturn true;\n};\n\n/*\nRemove the specified list item\n*/\nListWidget.prototype.removeListItem = function(index) {\n\tvar widget = this.children[index];\n\t// Animate the removal if required\n\tif(this.storyview && this.storyview.remove) {\n\t\tthis.storyview.remove(widget);\n\t} else {\n\t\twidget.removeChildDomNodes();\n\t}\n\t// Remove the child widget\n\tthis.children.splice(index,1);\n};\n\nexports.list = ListWidget;\n\nvar ListItemWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nListItemWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nListItemWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nListItemWidget.prototype.execute = function() {\n\t// Set the current list item title\n\tthis.setVariable(this.parseTreeNode.variableName,this.parseTreeNode.itemTitle);\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nListItemWidget.prototype.refresh = function(changedTiddlers) {\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.listitem = ListItemWidget;\n\n})();",
"title": "$:/core/modules/widgets/list.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/macrocall.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/macrocall.js\ntype: application/javascript\nmodule-type: widget\n\nMacrocall widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar MacroCallWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nMacroCallWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nMacroCallWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nMacroCallWidget.prototype.execute = function() {\n\t// Get the parse type if specified\n\tthis.parseType = this.getAttribute(\"$type\",\"text/vnd.tiddlywiki\");\n\tthis.renderOutput = this.getAttribute(\"$output\",\"text/html\");\n\t// Merge together the parameters specified in the parse tree with the specified attributes\n\tvar params = this.parseTreeNode.params ? this.parseTreeNode.params.slice(0) : [];\n\t$tw.utils.each(this.attributes,function(attribute,name) {\n\t\tif(name.charAt(0) !== \"$\") {\n\t\t\tparams.push({name: name, value: attribute});\t\t\t\n\t\t}\n\t});\n\t// Get the macro value\n\tvar text = this.getVariable(this.parseTreeNode.name || this.getAttribute(\"$name\"),{params: params}),\n\t\tparseTreeNodes;\n\t// Are we rendering to HTML?\n\tif(this.renderOutput === \"text/html\") {\n\t\t// If so we'll return the parsed macro\n\t\tvar parser = this.wiki.parseText(this.parseType,text,\n\t\t\t\t\t\t\t{parseAsInline: !this.parseTreeNode.isBlock});\n\t\tparseTreeNodes = parser ? parser.tree : [];\n\t} else {\n\t\t// Otherwise, we'll render the text\n\t\tvar plainText = this.wiki.renderText(\"text/plain\",this.parseType,text,{parentWidget: this});\n\t\tparseTreeNodes = [{type: \"text\", text: plainText}];\n\t}\n\t// Construct the child widgets\n\tthis.makeChildWidgets(parseTreeNodes);\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nMacroCallWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif($tw.utils.count(changedAttributes) > 0) {\n\t\t// Rerender ourselves\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\n\t}\n};\n\nexports.macrocall = MacroCallWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/macrocall.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/navigator.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/navigator.js\ntype: application/javascript\nmodule-type: widget\n\nNavigator widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar IMPORT_TITLE = \"$:/Import\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar NavigatorWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.addEventListeners([\n\t\t{type: \"tm-navigate\", handler: \"handleNavigateEvent\"},\n\t\t{type: \"tm-edit-tiddler\", handler: \"handleEditTiddlerEvent\"},\n\t\t{type: \"tm-delete-tiddler\", handler: \"handleDeleteTiddlerEvent\"},\n\t\t{type: \"tm-save-tiddler\", handler: \"handleSaveTiddlerEvent\"},\n\t\t{type: \"tm-cancel-tiddler\", handler: \"handleCancelTiddlerEvent\"},\n\t\t{type: \"tm-close-tiddler\", handler: \"handleCloseTiddlerEvent\"},\n\t\t{type: \"tm-close-all-tiddlers\", handler: \"handleCloseAllTiddlersEvent\"},\n\t\t{type: \"tm-close-other-tiddlers\", handler: \"handleCloseOtherTiddlersEvent\"},\n\t\t{type: \"tm-new-tiddler\", handler: \"handleNewTiddlerEvent\"},\n\t\t{type: \"tm-import-tiddlers\", handler: \"handleImportTiddlersEvent\"},\n\t\t{type: \"tm-perform-import\", handler: \"handlePerformImportEvent\"},\n\t\t{type: \"tm-fold-tiddler\", handler: \"handleFoldTiddlerEvent\"},\n\t\t{type: \"tm-fold-other-tiddlers\", handler: \"handleFoldOtherTiddlersEvent\"},\n\t\t{type: \"tm-fold-all-tiddlers\", handler: \"handleFoldAllTiddlersEvent\"},\n\t\t{type: \"tm-unfold-all-tiddlers\", handler: \"handleUnfoldAllTiddlersEvent\"},\n\t\t{type: \"tm-rename-tiddler\", handler: \"handleRenameTiddlerEvent\"}\n\t]);\n};\n\n/*\nInherit from the base widget class\n*/\nNavigatorWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nNavigatorWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nNavigatorWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.storyTitle = this.getAttribute(\"story\");\n\tthis.historyTitle = this.getAttribute(\"history\");\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nNavigatorWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.story || changedAttributes.history) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nNavigatorWidget.prototype.getStoryList = function() {\n\treturn this.storyTitle ? this.wiki.getTiddlerList(this.storyTitle) : null;\n};\n\nNavigatorWidget.prototype.saveStoryList = function(storyList) {\n\tvar storyTiddler = this.wiki.getTiddler(this.storyTitle);\n\tthis.wiki.addTiddler(new $tw.Tiddler(\n\t\t{title: this.storyTitle},\n\t\tstoryTiddler,\n\t\t{list: storyList}\n\t));\n};\n\nNavigatorWidget.prototype.removeTitleFromStory = function(storyList,title) {\n\tvar p = storyList.indexOf(title);\n\twhile(p !== -1) {\n\t\tstoryList.splice(p,1);\n\t\tp = storyList.indexOf(title);\n\t}\n};\n\nNavigatorWidget.prototype.replaceFirstTitleInStory = function(storyList,oldTitle,newTitle) {\n\tvar pos = storyList.indexOf(oldTitle);\n\tif(pos !== -1) {\n\t\tstoryList[pos] = newTitle;\n\t\tdo {\n\t\t\tpos = storyList.indexOf(oldTitle,pos + 1);\n\t\t\tif(pos !== -1) {\n\t\t\t\tstoryList.splice(pos,1);\n\t\t\t}\n\t\t} while(pos !== -1);\n\t} else {\n\t\tstoryList.splice(0,0,newTitle);\n\t}\n};\n\nNavigatorWidget.prototype.addToStory = function(title,fromTitle) {\n\tvar storyList = this.getStoryList();\n\t// Quit if we cannot get hold of the story list\n\tif(!storyList) {\n\t\treturn;\n\t}\n\t// See if the tiddler is already there\n\tvar slot = storyList.indexOf(title);\n\t// Quit if it already exists in the story river\n\tif(slot >= 0) {\n\t\treturn;\n\t}\n\t// First we try to find the position of the story element we navigated from\n\tvar fromIndex = storyList.indexOf(fromTitle);\n\tif(fromIndex >= 0) {\n\t\t// The tiddler is added from inside the river\n\t\t// Determine where to insert the tiddler; Fallback is \"below\"\n\t\tswitch(this.getAttribute(\"openLinkFromInsideRiver\",\"below\")) {\n\t\t\tcase \"top\":\n\t\t\t\tslot = 0;\n\t\t\t\tbreak;\n\t\t\tcase \"bottom\":\n\t\t\t\tslot = storyList.length;\n\t\t\t\tbreak;\n\t\t\tcase \"above\":\n\t\t\t\tslot = fromIndex;\n\t\t\t\tbreak;\n\t\t\tcase \"below\": // Intentional fall-through\n\t\t\tdefault:\n\t\t\t\tslot = fromIndex + 1;\n\t\t\t\tbreak;\n\t\t}\n\t} else {\n\t\t// The tiddler is opened from outside the river. Determine where to insert the tiddler; default is \"top\"\n\t\tif(this.getAttribute(\"openLinkFromOutsideRiver\",\"top\") === \"bottom\") {\n\t\t\t// Insert at bottom\n\t\t\tslot = storyList.length;\n\t\t} else {\n\t\t\t// Insert at top\n\t\t\tslot = 0;\n\t\t}\n\t}\n\t// Add the tiddler\n\tstoryList.splice(slot,0,title);\n\t// Save the story\n\tthis.saveStoryList(storyList);\n};\n\n/*\nAdd a new record to the top of the history stack\ntitle: a title string or an array of title strings\nfromPageRect: page coordinates of the origin of the navigation\n*/\nNavigatorWidget.prototype.addToHistory = function(title,fromPageRect) {\n\tthis.wiki.addToHistory(title,fromPageRect,this.historyTitle);\n};\n\n/*\nHandle a tm-navigate event\n*/\nNavigatorWidget.prototype.handleNavigateEvent = function(event) {\n\tif(event.navigateTo) {\n\t\tthis.addToStory(event.navigateTo,event.navigateFromTitle);\n\t\tif(!event.navigateSuppressNavigation) {\n\t\t\tthis.addToHistory(event.navigateTo,event.navigateFromClientRect);\n\t\t}\n\t}\n\treturn false;\n};\n\n// Close a specified tiddler\nNavigatorWidget.prototype.handleCloseTiddlerEvent = function(event) {\n\tvar title = event.param || event.tiddlerTitle,\n\t\tstoryList = this.getStoryList();\n\t// Look for tiddlers with this title to close\n\tthis.removeTitleFromStory(storyList,title);\n\tthis.saveStoryList(storyList);\n\treturn false;\n};\n\n// Close all tiddlers\nNavigatorWidget.prototype.handleCloseAllTiddlersEvent = function(event) {\n\tthis.saveStoryList([]);\n\treturn false;\n};\n\n// Close other tiddlers\nNavigatorWidget.prototype.handleCloseOtherTiddlersEvent = function(event) {\n\tvar title = event.param || event.tiddlerTitle;\n\tthis.saveStoryList([title]);\n\treturn false;\n};\n\n// Place a tiddler in edit mode\nNavigatorWidget.prototype.handleEditTiddlerEvent = function(event) {\n\tvar self = this;\n\tfunction isUnmodifiedShadow(title) {\n\t\treturn self.wiki.isShadowTiddler(title) && !self.wiki.tiddlerExists(title);\n\t}\n\tfunction confirmEditShadow(title) {\n\t\treturn confirm($tw.language.getString(\n\t\t\t\"ConfirmEditShadowTiddler\",\n\t\t\t{variables:\n\t\t\t\t{title: title}\n\t\t\t}\n\t\t));\n\t}\n\tvar title = event.param || event.tiddlerTitle;\n\tif(isUnmodifiedShadow(title) && !confirmEditShadow(title)) {\n\t\treturn false;\n\t}\n\t// Replace the specified tiddler with a draft in edit mode\n\tvar draftTiddler = this.makeDraftTiddler(title);\n\t// Update the story and history if required\n\tif(!event.paramObject || event.paramObject.suppressNavigation !== \"yes\") {\n\t\tvar draftTitle = draftTiddler.fields.title,\n\t\t\tstoryList = this.getStoryList();\n\t\tthis.removeTitleFromStory(storyList,draftTitle);\n\t\tthis.replaceFirstTitleInStory(storyList,title,draftTitle);\n\t\tthis.addToHistory(draftTitle,event.navigateFromClientRect);\n\t\tthis.saveStoryList(storyList);\n\t\treturn false;\n\t}\n};\n\n// Delete a tiddler\nNavigatorWidget.prototype.handleDeleteTiddlerEvent = function(event) {\n\t// Get the tiddler we're deleting\n\tvar title = event.param || event.tiddlerTitle,\n\t\ttiddler = this.wiki.getTiddler(title),\n\t\tstoryList = this.getStoryList(),\n\t\toriginalTitle = tiddler ? tiddler.fields[\"draft.of\"] : \"\",\n\t\tconfirmationTitle;\n\tif(!tiddler) {\n\t\treturn false;\n\t}\n\t// Check if the tiddler we're deleting is in draft mode\n\tif(originalTitle) {\n\t\t// If so, we'll prompt for confirmation referencing the original tiddler\n\t\tconfirmationTitle = originalTitle;\n\t} else {\n\t\t// If not a draft, then prompt for confirmation referencing the specified tiddler\n\t\tconfirmationTitle = title;\n\t}\n\t// Seek confirmation\n\tif((this.wiki.getTiddler(originalTitle) || (tiddler.fields.text || \"\") !== \"\") && !confirm($tw.language.getString(\n\t\t\t\t\"ConfirmDeleteTiddler\",\n\t\t\t\t{variables:\n\t\t\t\t\t{title: confirmationTitle}\n\t\t\t\t}\n\t\t\t))) {\n\t\treturn false;\n\t}\n\t// Delete the original tiddler\n\tif(originalTitle) {\n\t\tthis.wiki.deleteTiddler(originalTitle);\n\t\tthis.removeTitleFromStory(storyList,originalTitle);\n\t}\n\t// Delete this tiddler\n\tthis.wiki.deleteTiddler(title);\n\t// Remove the closed tiddler from the story\n\tthis.removeTitleFromStory(storyList,title);\n\tthis.saveStoryList(storyList);\n\t// Trigger an autosave\n\t$tw.rootWidget.dispatchEvent({type: \"tm-auto-save-wiki\"});\n\treturn false;\n};\n\n/*\nCreate/reuse the draft tiddler for a given title\n*/\nNavigatorWidget.prototype.makeDraftTiddler = function(targetTitle) {\n\t// See if there is already a draft tiddler for this tiddler\n\tvar draftTitle = this.wiki.findDraft(targetTitle);\n\tif(draftTitle) {\n\t\treturn this.wiki.getTiddler(draftTitle);\n\t}\n\t// Get the current value of the tiddler we're editing\n\tvar tiddler = this.wiki.getTiddler(targetTitle);\n\t// Save the initial value of the draft tiddler\n\tdraftTitle = this.generateDraftTitle(targetTitle);\n\tvar draftTiddler = new $tw.Tiddler(\n\t\t\ttiddler,\n\t\t\t{\n\t\t\t\ttitle: draftTitle,\n\t\t\t\t\"draft.title\": targetTitle,\n\t\t\t\t\"draft.of\": targetTitle\n\t\t\t},\n\t\t\tthis.wiki.getModificationFields()\n\t\t);\n\tthis.wiki.addTiddler(draftTiddler);\n\treturn draftTiddler;\n};\n\n/*\nGenerate a title for the draft of a given tiddler\n*/\nNavigatorWidget.prototype.generateDraftTitle = function(title) {\n\tvar c = 0,\n\t\tdraftTitle;\n\tdo {\n\t\tdraftTitle = \"Draft \" + (c ? (c + 1) + \" \" : \"\") + \"of '\" + title + \"'\";\n\t\tc++;\n\t} while(this.wiki.tiddlerExists(draftTitle));\n\treturn draftTitle;\n};\n\n// Take a tiddler out of edit mode, saving the changes\nNavigatorWidget.prototype.handleSaveTiddlerEvent = function(event) {\n\tvar title = event.param || event.tiddlerTitle,\n\t\ttiddler = this.wiki.getTiddler(title),\n\t\tstoryList = this.getStoryList();\n\t// Replace the original tiddler with the draft\n\tif(tiddler) {\n\t\tvar draftTitle = (tiddler.fields[\"draft.title\"] || \"\").trim(),\n\t\t\tdraftOf = (tiddler.fields[\"draft.of\"] || \"\").trim();\n\t\tif(draftTitle) {\n\t\t\tvar isRename = draftOf !== draftTitle,\n\t\t\t\tisConfirmed = true;\n\t\t\tif(isRename && this.wiki.tiddlerExists(draftTitle)) {\n\t\t\t\tisConfirmed = confirm($tw.language.getString(\n\t\t\t\t\t\"ConfirmOverwriteTiddler\",\n\t\t\t\t\t{variables:\n\t\t\t\t\t\t{title: draftTitle}\n\t\t\t\t\t}\n\t\t\t\t));\n\t\t\t}\n\t\t\tif(isConfirmed) {\n\t\t\t\t// Create the new tiddler and pass it through the th-saving-tiddler hook\n\t\t\t\tvar newTiddler = new $tw.Tiddler(this.wiki.getCreationFields(),tiddler,{\n\t\t\t\t\ttitle: draftTitle,\n\t\t\t\t\t\"draft.title\": undefined,\n\t\t\t\t\t\"draft.of\": undefined\n\t\t\t\t},this.wiki.getModificationFields());\n\t\t\t\tnewTiddler = $tw.hooks.invokeHook(\"th-saving-tiddler\",newTiddler);\n\t\t\t\tthis.wiki.addTiddler(newTiddler);\n\t\t\t\t// Remove the draft tiddler\n\t\t\t\tthis.wiki.deleteTiddler(title);\n\t\t\t\t// Remove the original tiddler if we're renaming it\n\t\t\t\tif(isRename) {\n\t\t\t\t\tthis.wiki.deleteTiddler(draftOf);\n\t\t\t\t}\n\t\t\t\tif(!event.paramObject || event.paramObject.suppressNavigation !== \"yes\") {\n\t\t\t\t\t// Replace the draft in the story with the original\n\t\t\t\t\tthis.replaceFirstTitleInStory(storyList,title,draftTitle);\n\t\t\t\t\tthis.addToHistory(draftTitle,event.navigateFromClientRect);\n\t\t\t\t\tif(draftTitle !== this.storyTitle) {\n\t\t\t\t\t\tthis.saveStoryList(storyList);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t// Trigger an autosave\n\t\t\t\t$tw.rootWidget.dispatchEvent({type: \"tm-auto-save-wiki\"});\n\t\t\t}\n\t\t}\n\t}\n\treturn false;\n};\n\n// Take a tiddler out of edit mode without saving the changes\nNavigatorWidget.prototype.handleCancelTiddlerEvent = function(event) {\n\t// Flip the specified tiddler from draft back to the original\n\tvar draftTitle = event.param || event.tiddlerTitle,\n\t\tdraftTiddler = this.wiki.getTiddler(draftTitle),\n\t\toriginalTitle = draftTiddler && draftTiddler.fields[\"draft.of\"];\n\tif(draftTiddler && originalTitle) {\n\t\t// Ask for confirmation if the tiddler text has changed\n\t\tvar isConfirmed = true,\n\t\t\toriginalTiddler = this.wiki.getTiddler(originalTitle),\n\t\t\tstoryList = this.getStoryList();\n\t\tif(this.wiki.isDraftModified(draftTitle)) {\n\t\t\tisConfirmed = confirm($tw.language.getString(\n\t\t\t\t\"ConfirmCancelTiddler\",\n\t\t\t\t{variables:\n\t\t\t\t\t{title: draftTitle}\n\t\t\t\t}\n\t\t\t));\n\t\t}\n\t\t// Remove the draft tiddler\n\t\tif(isConfirmed) {\n\t\t\tthis.wiki.deleteTiddler(draftTitle);\n\t\t\tif(!event.paramObject || event.paramObject.suppressNavigation !== \"yes\") {\n\t\t\t\tif(originalTiddler) {\n\t\t\t\t\tthis.replaceFirstTitleInStory(storyList,draftTitle,originalTitle);\n\t\t\t\t\tthis.addToHistory(originalTitle,event.navigateFromClientRect);\n\t\t\t\t} else {\n\t\t\t\t\tthis.removeTitleFromStory(storyList,draftTitle);\n\t\t\t\t}\n\t\t\t\tthis.saveStoryList(storyList);\n\t\t\t}\n\t\t}\n\t}\n\treturn false;\n};\n\n// Create a new draft tiddler\n// event.param can either be the title of a template tiddler, or a hashmap of fields.\n//\n// The title of the newly created tiddler follows these rules:\n// * If a hashmap was used and a title field was specified, use that title\n// * If a hashmap was used without a title field, use a default title, if necessary making it unique with a numeric suffix\n// * If a template tiddler was used, use the title of the template, if necessary making it unique with a numeric suffix\n//\n// If a draft of the target tiddler already exists then it is reused\nNavigatorWidget.prototype.handleNewTiddlerEvent = function(event) {\n\t// Get the story details\n\tvar storyList = this.getStoryList(),\n\t\ttemplateTiddler, additionalFields, title, draftTitle, existingTiddler;\n\t// Get the template tiddler (if any)\n\tif(typeof event.param === \"string\") {\n\t\t// Get the template tiddler\n\t\ttemplateTiddler = this.wiki.getTiddler(event.param);\n\t\t// Generate a new title\n\t\ttitle = this.wiki.generateNewTitle(event.param || $tw.language.getString(\"DefaultNewTiddlerTitle\"));\n\t}\n\t// Get the specified additional fields\n\tif(typeof event.paramObject === \"object\") {\n\t\tadditionalFields = event.paramObject;\n\t}\n\tif(typeof event.param === \"object\") { // Backwards compatibility with 5.1.3\n\t\tadditionalFields = event.param;\n\t}\n\tif(additionalFields && additionalFields.title) {\n\t\ttitle = additionalFields.title;\n\t}\n\t// Generate a title if we don't have one\n\ttitle = title || this.wiki.generateNewTitle($tw.language.getString(\"DefaultNewTiddlerTitle\"));\n\t// Find any existing draft for this tiddler\n\tdraftTitle = this.wiki.findDraft(title);\n\t// Pull in any existing tiddler\n\tif(draftTitle) {\n\t\texistingTiddler = this.wiki.getTiddler(draftTitle);\n\t} else {\n\t\tdraftTitle = this.generateDraftTitle(title);\n\t\texistingTiddler = this.wiki.getTiddler(title);\n\t}\n\t// Merge the tags\n\tvar mergedTags = [];\n\tif(existingTiddler && existingTiddler.fields.tags) {\n\t\t$tw.utils.pushTop(mergedTags,existingTiddler.fields.tags)\n\t}\n\tif(additionalFields && additionalFields.tags) {\n\t\t// Merge tags\n\t\tmergedTags = $tw.utils.pushTop(mergedTags,$tw.utils.parseStringArray(additionalFields.tags));\n\t}\n\tif(templateTiddler && templateTiddler.fields.tags) {\n\t\t// Merge tags\n\t\tmergedTags = $tw.utils.pushTop(mergedTags,templateTiddler.fields.tags);\n\t}\n\t// Save the draft tiddler\n\tvar draftTiddler = new $tw.Tiddler({\n\t\t\ttext: \"\",\n\t\t\t\"draft.title\": title\n\t\t},\n\t\ttemplateTiddler,\n\t\texistingTiddler,\n\t\tadditionalFields,\n\t\tthis.wiki.getCreationFields(),\n\t\t{\n\t\t\ttitle: draftTitle,\n\t\t\t\"draft.of\": title,\n\t\t\ttags: mergedTags\n\t\t},this.wiki.getModificationFields());\n\tthis.wiki.addTiddler(draftTiddler);\n\t// Update the story to insert the new draft at the top and remove any existing tiddler\n\tif(storyList.indexOf(draftTitle) === -1) {\n\t\tvar slot = storyList.indexOf(event.navigateFromTitle);\n\t\tstoryList.splice(slot + 1,0,draftTitle);\n\t}\n\tif(storyList.indexOf(title) !== -1) {\n\t\tstoryList.splice(storyList.indexOf(title),1);\t\t\n\t}\n\tthis.saveStoryList(storyList);\n\t// Add a new record to the top of the history stack\n\tthis.addToHistory(draftTitle);\n\treturn false;\n};\n\n// Import JSON tiddlers into a pending import tiddler\nNavigatorWidget.prototype.handleImportTiddlersEvent = function(event) {\n\tvar self = this;\n\t// Get the tiddlers\n\tvar tiddlers = [];\n\ttry {\n\t\ttiddlers = JSON.parse(event.param);\t\n\t} catch(e) {\n\t}\n\t// Get the current $:/Import tiddler\n\tvar importTiddler = this.wiki.getTiddler(IMPORT_TITLE),\n\t\timportData = this.wiki.getTiddlerData(IMPORT_TITLE,{}),\n\t\tnewFields = new Object({\n\t\t\ttitle: IMPORT_TITLE,\n\t\t\ttype: \"application/json\",\n\t\t\t\"plugin-type\": \"import\",\n\t\t\t\"status\": \"pending\"\n\t\t}),\n\t\tincomingTiddlers = [];\n\t// Process each tiddler\n\timportData.tiddlers = importData.tiddlers || {};\n\t$tw.utils.each(tiddlers,function(tiddlerFields) {\n\t\tvar title = tiddlerFields.title;\n\t\tif(title) {\n\t\t\tincomingTiddlers.push(title);\n\t\t\timportData.tiddlers[title] = tiddlerFields;\n\t\t}\n\t});\n\t// Give the active upgrader modules a chance to process the incoming tiddlers\n\tvar messages = this.wiki.invokeUpgraders(incomingTiddlers,importData.tiddlers);\n\t$tw.utils.each(messages,function(message,title) {\n\t\tnewFields[\"message-\" + title] = message;\n\t});\n\t// Deselect any suppressed tiddlers\n\t$tw.utils.each(importData.tiddlers,function(tiddler,title) {\n\t\tif($tw.utils.count(tiddler) === 0) {\n\t\t\tnewFields[\"selection-\" + title] = \"unchecked\";\n\t\t}\n\t});\n\t// Save the $:/Import tiddler\n\tnewFields.text = JSON.stringify(importData,null,$tw.config.preferences.jsonSpaces);\n\tthis.wiki.addTiddler(new $tw.Tiddler(importTiddler,newFields));\n\t// Update the story and history details\n\tif(this.getVariable(\"tv-auto-open-on-import\") !== \"no\") {\n\t\tvar storyList = this.getStoryList(),\n\t\t\thistory = [];\n\t\t// Add it to the story\n\t\tif(storyList.indexOf(IMPORT_TITLE) === -1) {\n\t\t\tstoryList.unshift(IMPORT_TITLE);\n\t\t}\n\t\t// And to history\n\t\thistory.push(IMPORT_TITLE);\n\t\t// Save the updated story and history\n\t\tthis.saveStoryList(storyList);\n\t\tthis.addToHistory(history);\t\t\n\t}\n\treturn false;\n};\n\n// \nNavigatorWidget.prototype.handlePerformImportEvent = function(event) {\n\tvar self = this,\n\t\timportTiddler = this.wiki.getTiddler(event.param),\n\t\timportData = this.wiki.getTiddlerDataCached(event.param,{tiddlers: {}}),\n\t\timportReport = [];\n\t// Add the tiddlers to the store\n\timportReport.push($tw.language.getString(\"Import/Imported/Hint\") + \"\\n\");\n\t$tw.utils.each(importData.tiddlers,function(tiddlerFields) {\n\t\tvar title = tiddlerFields.title;\n\t\tif(title && importTiddler && importTiddler.fields[\"selection-\" + title] !== \"unchecked\") {\n\t\t\tself.wiki.addTiddler(new $tw.Tiddler(tiddlerFields));\n\t\t\timportReport.push(\"# [[\" + tiddlerFields.title + \"]]\");\n\t\t}\n\t});\n\t// Replace the $:/Import tiddler with an import report\n\tthis.wiki.addTiddler(new $tw.Tiddler({\n\t\ttitle: event.param,\n\t\ttext: importReport.join(\"\\n\"),\n\t\t\"status\": \"complete\"\n\t}));\n\t// Navigate to the $:/Import tiddler\n\tthis.addToHistory([event.param]);\n\t// Trigger an autosave\n\t$tw.rootWidget.dispatchEvent({type: \"tm-auto-save-wiki\"});\n};\n\nNavigatorWidget.prototype.handleFoldTiddlerEvent = function(event) {\n\tvar self = this,\n\t\tparamObject = event.paramObject || {};\n\tif(paramObject.foldedState) {\n\t\tvar foldedState = this.wiki.getTiddlerText(paramObject.foldedState,\"show\") === \"show\" ? \"hide\" : \"show\";\n\t\tthis.wiki.setText(paramObject.foldedState,\"text\",null,foldedState);\n\t}\n};\n\nNavigatorWidget.prototype.handleFoldOtherTiddlersEvent = function(event) {\n\tvar self = this,\n\t\tparamObject = event.paramObject || {},\n\t\tprefix = paramObject.foldedStatePrefix;\n\t$tw.utils.each(this.getStoryList(),function(title) {\n\t\tself.wiki.setText(prefix + title,\"text\",null,event.param === title ? \"show\" : \"hide\");\n\t});\n};\n\nNavigatorWidget.prototype.handleFoldAllTiddlersEvent = function(event) {\n\tvar self = this,\n\t\tparamObject = event.paramObject || {},\n\t\tprefix = paramObject.foldedStatePrefix;\n\t$tw.utils.each(this.getStoryList(),function(title) {\n\t\tself.wiki.setText(prefix + title,\"text\",null,\"hide\");\n\t});\n};\n\nNavigatorWidget.prototype.handleUnfoldAllTiddlersEvent = function(event) {\n\tvar self = this,\n\t\tparamObject = event.paramObject || {},\n\t\tprefix = paramObject.foldedStatePrefix;\n\t$tw.utils.each(this.getStoryList(),function(title) {\n\t\tself.wiki.setText(prefix + title,\"text\",null,\"show\");\n\t});\n};\n\nNavigatorWidget.prototype.handleRenameTiddlerEvent = function(event) {\n\tvar self = this,\n\t\tparamObject = event.paramObject || {},\n\t\tfrom = paramObject.from || event.tiddlerTitle,\n\t\tto = paramObject.to;\n\t$tw.wiki.renameTiddler(from,to);\n};\n\nexports.navigator = NavigatorWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/navigator.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/password.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/password.js\ntype: application/javascript\nmodule-type: widget\n\nPassword widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar PasswordWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nPasswordWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nPasswordWidget.prototype.render = function(parent,nextSibling) {\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\t// Get the current password\n\tvar password = $tw.browser ? $tw.utils.getPassword(this.passwordName) || \"\" : \"\";\n\t// Create our element\n\tvar domNode = this.document.createElement(\"input\");\n\tdomNode.setAttribute(\"type\",\"password\");\n\tdomNode.setAttribute(\"value\",password);\n\t// Add a click event handler\n\t$tw.utils.addEventListeners(domNode,[\n\t\t{name: \"change\", handlerObject: this, handlerMethod: \"handleChangeEvent\"}\n\t]);\n\t// Insert the label into the DOM and render any children\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tthis.domNodes.push(domNode);\n};\n\nPasswordWidget.prototype.handleChangeEvent = function(event) {\n\tvar password = this.domNodes[0].value;\n\treturn $tw.utils.savePassword(this.passwordName,password);\n};\n\n/*\nCompute the internal state of the widget\n*/\nPasswordWidget.prototype.execute = function() {\n\t// Get the parameters from the attributes\n\tthis.passwordName = this.getAttribute(\"name\",\"\");\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nPasswordWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.name) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\n\t}\n};\n\nexports.password = PasswordWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/password.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/radio.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/radio.js\ntype: application/javascript\nmodule-type: widget\n\nRadio widget\n\nWill set a field to the selected value:\n\n```\n\t<$radio field=\"myfield\" value=\"check 1\">one</$radio>\n\t<$radio field=\"myfield\" value=\"check 2\">two</$radio>\n\t<$radio field=\"myfield\" value=\"check 3\">three</$radio>\n```\n\n|Parameter |Description |h\n|tiddler |Name of the tiddler in which the field should be set. Defaults to current tiddler |\n|field |The name of the field to be set |\n|value |The value to set |\n|class |Optional class name(s) |\n\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar RadioWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nRadioWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nRadioWidget.prototype.render = function(parent,nextSibling) {\n\t// Save the parent dom node\n\tthis.parentDomNode = parent;\n\t// Compute our attributes\n\tthis.computeAttributes();\n\t// Execute our logic\n\tthis.execute();\n\t// Create our elements\n\tthis.labelDomNode = this.document.createElement(\"label\");\n\tthis.labelDomNode.setAttribute(\"class\",this.radioClass);\n\tthis.inputDomNode = this.document.createElement(\"input\");\n\tthis.inputDomNode.setAttribute(\"type\",\"radio\");\n\tif(this.getValue() == this.radioValue) {\n\t\tthis.inputDomNode.setAttribute(\"checked\",\"true\");\n\t}\n\tthis.labelDomNode.appendChild(this.inputDomNode);\n\tthis.spanDomNode = this.document.createElement(\"span\");\n\tthis.labelDomNode.appendChild(this.spanDomNode);\n\t// Add a click event handler\n\t$tw.utils.addEventListeners(this.inputDomNode,[\n\t\t{name: \"change\", handlerObject: this, handlerMethod: \"handleChangeEvent\"}\n\t]);\n\t// Insert the label into the DOM and render any children\n\tparent.insertBefore(this.labelDomNode,nextSibling);\n\tthis.renderChildren(this.spanDomNode,null);\n\tthis.domNodes.push(this.labelDomNode);\n};\n\nRadioWidget.prototype.getValue = function() {\n\tvar tiddler = this.wiki.getTiddler(this.radioTitle);\n\treturn tiddler && tiddler.getFieldString(this.radioField);\n};\n\nRadioWidget.prototype.setValue = function() {\n\tif(this.radioField) {\n\t\tvar tiddler = this.wiki.getTiddler(this.radioTitle),\n\t\t\taddition = {};\n\t\taddition[this.radioField] = this.radioValue;\n\t\tthis.wiki.addTiddler(new $tw.Tiddler(this.wiki.getCreationFields(),{title: this.radioTitle},tiddler,addition,this.wiki.getModificationFields()));\n\t}\n};\n\nRadioWidget.prototype.handleChangeEvent = function(event) {\n\tif(this.inputDomNode.checked) {\n\t\tthis.setValue();\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nRadioWidget.prototype.execute = function() {\n\t// Get the parameters from the attributes\n\tthis.radioTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.radioField = this.getAttribute(\"field\",\"text\");\n\tthis.radioValue = this.getAttribute(\"value\");\n\tthis.radioClass = this.getAttribute(\"class\",\"\");\n\tif(this.radioClass !== \"\") {\n\t\tthis.radioClass += \" \";\n\t}\n\tthis.radioClass += \"tc-radio\";\n\t// Make the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nRadioWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.value || changedAttributes[\"class\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\tvar refreshed = false;\n\t\tif(changedTiddlers[this.radioTitle]) {\n\t\t\tthis.inputDomNode.checked = this.getValue() === this.radioValue;\n\t\t\trefreshed = true;\n\t\t}\n\t\treturn this.refreshChildren(changedTiddlers) || refreshed;\n\t}\n};\n\nexports.radio = RadioWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/radio.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/raw.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/raw.js\ntype: application/javascript\nmodule-type: widget\n\nRaw widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar RawWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nRawWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nRawWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.execute();\n\tvar div = this.document.createElement(\"div\");\n\tdiv.innerHTML=this.parseTreeNode.html;\n\tparent.insertBefore(div,nextSibling);\n\tthis.domNodes.push(div);\t\n};\n\n/*\nCompute the internal state of the widget\n*/\nRawWidget.prototype.execute = function() {\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nRawWidget.prototype.refresh = function(changedTiddlers) {\n\treturn false;\n};\n\nexports.raw = RawWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/raw.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/reveal.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/reveal.js\ntype: application/javascript\nmodule-type: widget\n\nReveal widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar RevealWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nRevealWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nRevealWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar tag = this.parseTreeNode.isBlock ? \"div\" : \"span\";\n\tif(this.revealTag && $tw.config.htmlUnsafeElements.indexOf(this.revealTag) === -1) {\n\t\ttag = this.revealTag;\n\t}\n\tvar domNode = this.document.createElement(tag);\n\tvar classes = this[\"class\"].split(\" \") || [];\n\tclasses.push(\"tc-reveal\");\n\tdomNode.className = classes.join(\" \");\n\tif(this.style) {\n\t\tdomNode.setAttribute(\"style\",this.style);\n\t}\n\tparent.insertBefore(domNode,nextSibling);\n\tthis.renderChildren(domNode,null);\n\tif(!domNode.isTiddlyWikiFakeDom && this.type === \"popup\" && this.isOpen) {\n\t\tthis.positionPopup(domNode);\n\t\t$tw.utils.addClass(domNode,\"tc-popup\"); // Make sure that clicks don't dismiss popups within the revealed content\n\t}\n\tif(!this.isOpen) {\n\t\tdomNode.setAttribute(\"hidden\",\"true\");\n\t}\n\tthis.domNodes.push(domNode);\n};\n\nRevealWidget.prototype.positionPopup = function(domNode) {\n\tdomNode.style.position = \"absolute\";\n\tdomNode.style.zIndex = \"1000\";\n\tswitch(this.position) {\n\t\tcase \"left\":\n\t\t\tdomNode.style.left = (this.popup.left - domNode.offsetWidth) + \"px\";\n\t\t\tdomNode.style.top = this.popup.top + \"px\";\n\t\t\tbreak;\n\t\tcase \"above\":\n\t\t\tdomNode.style.left = this.popup.left + \"px\";\n\t\t\tdomNode.style.top = (this.popup.top - domNode.offsetHeight) + \"px\";\n\t\t\tbreak;\n\t\tcase \"aboveright\":\n\t\t\tdomNode.style.left = (this.popup.left + this.popup.width) + \"px\";\n\t\t\tdomNode.style.top = (this.popup.top + this.popup.height - domNode.offsetHeight) + \"px\";\n\t\t\tbreak;\n\t\tcase \"right\":\n\t\t\tdomNode.style.left = (this.popup.left + this.popup.width) + \"px\";\n\t\t\tdomNode.style.top = this.popup.top + \"px\";\n\t\t\tbreak;\n\t\tcase \"belowleft\":\n\t\t\tdomNode.style.left = (this.popup.left + this.popup.width - domNode.offsetWidth) + \"px\";\n\t\t\tdomNode.style.top = (this.popup.top + this.popup.height) + \"px\";\n\t\t\tbreak;\n\t\tdefault: // Below\n\t\t\tdomNode.style.left = this.popup.left + \"px\";\n\t\t\tdomNode.style.top = (this.popup.top + this.popup.height) + \"px\";\n\t\t\tbreak;\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nRevealWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.state = this.getAttribute(\"state\");\n\tthis.revealTag = this.getAttribute(\"tag\");\n\tthis.type = this.getAttribute(\"type\");\n\tthis.text = this.getAttribute(\"text\");\n\tthis.position = this.getAttribute(\"position\");\n\tthis[\"class\"] = this.getAttribute(\"class\",\"\");\n\tthis.style = this.getAttribute(\"style\",\"\");\n\tthis[\"default\"] = this.getAttribute(\"default\",\"\");\n\tthis.animate = this.getAttribute(\"animate\",\"no\");\n\tthis.retain = this.getAttribute(\"retain\",\"no\");\n\tthis.openAnimation = this.animate === \"no\" ? undefined : \"open\";\n\tthis.closeAnimation = this.animate === \"no\" ? undefined : \"close\";\n\t// Compute the title of the state tiddler and read it\n\tthis.stateTitle = this.state;\n\tthis.readState();\n\t// Construct the child widgets\n\tvar childNodes = this.isOpen ? this.parseTreeNode.children : [];\n\tthis.hasChildNodes = this.isOpen;\n\tthis.makeChildWidgets(childNodes);\n};\n\n/*\nRead the state tiddler\n*/\nRevealWidget.prototype.readState = function() {\n\t// Read the information from the state tiddler\n\tvar state = this.stateTitle ? this.wiki.getTextReference(this.stateTitle,this[\"default\"],this.getVariable(\"currentTiddler\")) : this[\"default\"];\n\tswitch(this.type) {\n\t\tcase \"popup\":\n\t\t\tthis.readPopupState(state);\n\t\t\tbreak;\n\t\tcase \"match\":\n\t\t\tthis.readMatchState(state);\n\t\t\tbreak;\n\t\tcase \"nomatch\":\n\t\t\tthis.readMatchState(state);\n\t\t\tthis.isOpen = !this.isOpen;\n\t\t\tbreak;\n\t}\n};\n\nRevealWidget.prototype.readMatchState = function(state) {\n\tthis.isOpen = state === this.text;\n};\n\nRevealWidget.prototype.readPopupState = function(state) {\n\tvar popupLocationRegExp = /^\\((-?[0-9\\.E]+),(-?[0-9\\.E]+),(-?[0-9\\.E]+),(-?[0-9\\.E]+)\\)$/,\n\t\tmatch = popupLocationRegExp.exec(state);\n\t// Check if the state matches the location regexp\n\tif(match) {\n\t\t// If so, we're open\n\t\tthis.isOpen = true;\n\t\t// Get the location\n\t\tthis.popup = {\n\t\t\tleft: parseFloat(match[1]),\n\t\t\ttop: parseFloat(match[2]),\n\t\t\twidth: parseFloat(match[3]),\n\t\t\theight: parseFloat(match[4])\n\t\t};\n\t} else {\n\t\t// If not, we're closed\n\t\tthis.isOpen = false;\n\t}\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nRevealWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.state || changedAttributes.type || changedAttributes.text || changedAttributes.position || changedAttributes[\"default\"] || changedAttributes.animate) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\tvar refreshed = false,\n\t\t\tcurrentlyOpen = this.isOpen;\n\t\tthis.readState();\n\t\tif(this.isOpen !== currentlyOpen) {\n\t\t\tif(this.retain === \"yes\") {\n\t\t\t\tthis.updateState();\n\t\t\t} else {\n\t\t\t\tthis.refreshSelf();\n\t\t\t\trefreshed = true;\n\t\t\t}\n\t\t}\n\t\treturn this.refreshChildren(changedTiddlers) || refreshed;\n\t}\n};\n\n/*\nCalled by refresh() to dynamically show or hide the content\n*/\nRevealWidget.prototype.updateState = function() {\n\t// Read the current state\n\tthis.readState();\n\t// Construct the child nodes if needed\n\tvar domNode = this.domNodes[0];\n\tif(this.isOpen && !this.hasChildNodes) {\n\t\tthis.hasChildNodes = true;\n\t\tthis.makeChildWidgets(this.parseTreeNode.children);\n\t\tthis.renderChildren(domNode,null);\n\t}\n\t// Animate our DOM node\n\tif(!domNode.isTiddlyWikiFakeDom && this.type === \"popup\" && this.isOpen) {\n\t\tthis.positionPopup(domNode);\n\t\t$tw.utils.addClass(domNode,\"tc-popup\"); // Make sure that clicks don't dismiss popups within the revealed content\n\n\t}\n\tif(this.isOpen) {\n\t\tdomNode.removeAttribute(\"hidden\");\n $tw.anim.perform(this.openAnimation,domNode);\n\t} else {\n\t\t$tw.anim.perform(this.closeAnimation,domNode,{callback: function() {\n\t\t\tdomNode.setAttribute(\"hidden\",\"true\");\n }});\n\t}\n};\n\nexports.reveal = RevealWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/reveal.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/scrollable.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/scrollable.js\ntype: application/javascript\nmodule-type: widget\n\nScrollable widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ScrollableWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.scaleFactor = 1;\n\tthis.addEventListeners([\n\t\t{type: \"tm-scroll\", handler: \"handleScrollEvent\"}\n\t]);\n\tif($tw.browser) {\n\t\tthis.requestAnimationFrame = window.requestAnimationFrame ||\n\t\t\twindow.webkitRequestAnimationFrame ||\n\t\t\twindow.mozRequestAnimationFrame ||\n\t\t\tfunction(callback) {\n\t\t\t\treturn window.setTimeout(callback, 1000/60);\n\t\t\t};\n\t\tthis.cancelAnimationFrame = window.cancelAnimationFrame ||\n\t\t\twindow.webkitCancelAnimationFrame ||\n\t\t\twindow.webkitCancelRequestAnimationFrame ||\n\t\t\twindow.mozCancelAnimationFrame ||\n\t\t\twindow.mozCancelRequestAnimationFrame ||\n\t\t\tfunction(id) {\n\t\t\t\twindow.clearTimeout(id);\n\t\t\t};\n\t}\n};\n\n/*\nInherit from the base widget class\n*/\nScrollableWidget.prototype = new Widget();\n\nScrollableWidget.prototype.cancelScroll = function() {\n\tif(this.idRequestFrame) {\n\t\tthis.cancelAnimationFrame.call(window,this.idRequestFrame);\n\t\tthis.idRequestFrame = null;\n\t}\n};\n\n/*\nHandle a scroll event\n*/\nScrollableWidget.prototype.handleScrollEvent = function(event) {\n\t// Pass the scroll event through if our offsetsize is larger than our scrollsize\n\tif(this.outerDomNode.scrollWidth <= this.outerDomNode.offsetWidth && this.outerDomNode.scrollHeight <= this.outerDomNode.offsetHeight && this.fallthrough === \"yes\") {\n\t\treturn true;\n\t}\n\tthis.scrollIntoView(event.target);\n\treturn false; // Handled event\n};\n\n/*\nScroll an element into view\n*/\nScrollableWidget.prototype.scrollIntoView = function(element) {\n\tvar duration = $tw.utils.getAnimationDuration();\n\tthis.cancelScroll();\n\tthis.startTime = Date.now();\n\tvar scrollPosition = {\n\t\tx: this.outerDomNode.scrollLeft,\n\t\ty: this.outerDomNode.scrollTop\n\t};\n\t// Get the client bounds of the element and adjust by the scroll position\n\tvar scrollableBounds = this.outerDomNode.getBoundingClientRect(),\n\t\tclientTargetBounds = element.getBoundingClientRect(),\n\t\tbounds = {\n\t\t\tleft: clientTargetBounds.left + scrollPosition.x - scrollableBounds.left,\n\t\t\ttop: clientTargetBounds.top + scrollPosition.y - scrollableBounds.top,\n\t\t\twidth: clientTargetBounds.width,\n\t\t\theight: clientTargetBounds.height\n\t\t};\n\t// We'll consider the horizontal and vertical scroll directions separately via this function\n\tvar getEndPos = function(targetPos,targetSize,currentPos,currentSize) {\n\t\t\t// If the target is already visible then stay where we are\n\t\t\tif(targetPos >= currentPos && (targetPos + targetSize) <= (currentPos + currentSize)) {\n\t\t\t\treturn currentPos;\n\t\t\t// If the target is above/left of the current view, then scroll to its top/left\n\t\t\t} else if(targetPos <= currentPos) {\n\t\t\t\treturn targetPos;\n\t\t\t// If the target is smaller than the window and the scroll position is too far up, then scroll till the target is at the bottom of the window\n\t\t\t} else if(targetSize < currentSize && currentPos < (targetPos + targetSize - currentSize)) {\n\t\t\t\treturn targetPos + targetSize - currentSize;\n\t\t\t// If the target is big, then just scroll to the top\n\t\t\t} else if(currentPos < targetPos) {\n\t\t\t\treturn targetPos;\n\t\t\t// Otherwise, stay where we are\n\t\t\t} else {\n\t\t\t\treturn currentPos;\n\t\t\t}\n\t\t},\n\t\tendX = getEndPos(bounds.left,bounds.width,scrollPosition.x,this.outerDomNode.offsetWidth),\n\t\tendY = getEndPos(bounds.top,bounds.height,scrollPosition.y,this.outerDomNode.offsetHeight);\n\t// Only scroll if necessary\n\tif(endX !== scrollPosition.x || endY !== scrollPosition.y) {\n\t\tvar self = this,\n\t\t\tdrawFrame;\n\t\tdrawFrame = function () {\n\t\t\tvar t;\n\t\t\tif(duration <= 0) {\n\t\t\t\tt = 1;\n\t\t\t} else {\n\t\t\t\tt = ((Date.now()) - self.startTime) / duration;\t\n\t\t\t}\n\t\t\tif(t >= 1) {\n\t\t\t\tself.cancelScroll();\n\t\t\t\tt = 1;\n\t\t\t}\n\t\t\tt = $tw.utils.slowInSlowOut(t);\n\t\t\tself.outerDomNode.scrollLeft = scrollPosition.x + (endX - scrollPosition.x) * t;\n\t\t\tself.outerDomNode.scrollTop = scrollPosition.y + (endY - scrollPosition.y) * t;\n\t\t\tif(t < 1) {\n\t\t\t\tself.idRequestFrame = self.requestAnimationFrame.call(window,drawFrame);\n\t\t\t}\n\t\t};\n\t\tdrawFrame();\n\t}\n};\n\n/*\nRender this widget into the DOM\n*/\nScrollableWidget.prototype.render = function(parent,nextSibling) {\n\tvar self = this;\n\t// Remember parent\n\tthis.parentDomNode = parent;\n\t// Compute attributes and execute state\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Create elements\n\tthis.outerDomNode = this.document.createElement(\"div\");\n\t$tw.utils.setStyle(this.outerDomNode,[\n\t\t{overflowY: \"auto\"},\n\t\t{overflowX: \"auto\"},\n\t\t{webkitOverflowScrolling: \"touch\"}\n\t]);\n\tthis.innerDomNode = this.document.createElement(\"div\");\n\tthis.outerDomNode.appendChild(this.innerDomNode);\n\t// Assign classes\n\tthis.outerDomNode.className = this[\"class\"] || \"\";\n\t// Insert element\n\tparent.insertBefore(this.outerDomNode,nextSibling);\n\tthis.renderChildren(this.innerDomNode,null);\n\tthis.domNodes.push(this.outerDomNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nScrollableWidget.prototype.execute = function() {\n\t// Get attributes\n\tthis.fallthrough = this.getAttribute(\"fallthrough\",\"yes\");\n\tthis[\"class\"] = this.getAttribute(\"class\");\n\t// Make child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nScrollableWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes[\"class\"]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports.scrollable = ScrollableWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/scrollable.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/select.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/select.js\ntype: application/javascript\nmodule-type: widget\n\nSelect widget:\n\n```\n<$select tiddler=\"MyTiddler\" field=\"text\">\n<$list filter=\"[tag[chapter]]\">\n<option value=<<currentTiddler>>>\n<$view field=\"description\"/>\n</option>\n</$list>\n</$select>\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar SelectWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nSelectWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nSelectWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n\tthis.setSelectValue();\n\t$tw.utils.addEventListeners(this.getSelectDomNode(),[\n\t\t{name: \"change\", handlerObject: this, handlerMethod: \"handleChangeEvent\"}\n\t]);\n};\n\n/*\nHandle a change event\n*/\nSelectWidget.prototype.handleChangeEvent = function(event) {\n\t// Get the new value and assign it to the tiddler\n\tif(this.selectMultiple == false) {\n\t\tvar value = this.getSelectDomNode().value;\n\t} else {\n\t\tvar value = this.getSelectValues()\n\t\t\t\tvalue = $tw.utils.stringifyList(value);\n\t}\n\tthis.wiki.setText(this.selectTitle,this.selectField,this.selectIndex,value);\n\t// Trigger actions\n\tif(this.selectActions) {\n\t\tthis.invokeActionString(this.selectActions,this,event);\n\t}\n};\n\n/*\nIf necessary, set the value of the select element to the current value\n*/\nSelectWidget.prototype.setSelectValue = function() {\n\tvar value = this.selectDefault;\n\t// Get the value\n\tif(this.selectIndex) {\n\t\tvalue = this.wiki.extractTiddlerDataItem(this.selectTitle,this.selectIndex);\n\t} else {\n\t\tvar tiddler = this.wiki.getTiddler(this.selectTitle);\n\t\tif(tiddler) {\n\t\t\tif(this.selectField === \"text\") {\n\t\t\t\t// Calling getTiddlerText() triggers lazy loading of skinny tiddlers\n\t\t\t\tvalue = this.wiki.getTiddlerText(this.selectTitle);\n\t\t\t} else {\n\t\t\t\tif($tw.utils.hop(tiddler.fields,this.selectField)) {\n\t\t\t\t\tvalue = tiddler.getFieldString(this.selectField);\n\t\t\t\t}\n\t\t\t}\n\t\t} else {\n\t\t\tif(this.selectField === \"title\") {\n\t\t\t\tvalue = this.selectTitle;\n\t\t\t}\n\t\t}\n\t}\n\t// Assign it to the select element if it's different than the current value\n\tif (this.selectMultiple) {\n\t\tvalue = value === undefined ? \"\" : value;\n\t\tvar select = this.getSelectDomNode();\n\t\tvar values = Array.isArray(value) ? value : $tw.utils.parseStringArray(value);\n\t\tfor(var i=0; i < select.children.length; i++){\n\t\t\tif(values.indexOf(select.children[i].value) != -1) {\n\t\t\t\tselect.children[i].selected = true;\n\t\t\t}\n\t\t}\n\t\t\n\t} else {\n\t\tvar domNode = this.getSelectDomNode();\n\t\tif(domNode.value !== value) {\n\t\t\tdomNode.value = value;\n\t\t}\n\t}\n};\n\n/*\nGet the DOM node of the select element\n*/\nSelectWidget.prototype.getSelectDomNode = function() {\n\treturn this.children[0].domNodes[0];\n};\n\n// Return an array of the selected opion values\n// select is an HTML select element\nSelectWidget.prototype.getSelectValues = function() {\n\tvar select, result, options, opt;\n\tselect = this.getSelectDomNode();\n\tresult = [];\n\toptions = select && select.options;\n\tfor (var i=0; i<options.length; i++) {\n\t\topt = options[i];\n\t\tif (opt.selected) {\n\t\t\tresult.push(opt.value || opt.text);\n\t\t}\n\t}\n\treturn result;\n}\n\n/*\nCompute the internal state of the widget\n*/\nSelectWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.selectActions = this.getAttribute(\"actions\");\n\tthis.selectTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.selectField = this.getAttribute(\"field\",\"text\");\n\tthis.selectIndex = this.getAttribute(\"index\");\n\tthis.selectClass = this.getAttribute(\"class\");\n\tthis.selectDefault = this.getAttribute(\"default\");\n\tthis.selectMultiple = this.getAttribute(\"multiple\", false);\n\tthis.selectSize = this.getAttribute(\"size\");\n\t// Make the child widgets\n\tvar selectNode = {\n\t\ttype: \"element\",\n\t\ttag: \"select\",\n\t\tchildren: this.parseTreeNode.children\n\t};\n\tif(this.selectClass) {\n\t\t$tw.utils.addAttributeToParseTreeNode(selectNode,\"class\",this.selectClass);\n\t}\n\tif(this.selectMultiple) {\n\t\t$tw.utils.addAttributeToParseTreeNode(selectNode,\"multiple\",\"multiple\");\n\t}\n\tif(this.selectSize) {\n\t\t$tw.utils.addAttributeToParseTreeNode(selectNode,\"size\",this.selectSize);\n\t}\n\tthis.makeChildWidgets([selectNode]);\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nSelectWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\t// If we're using a different tiddler/field/index then completely refresh ourselves\n\tif(changedAttributes.selectTitle || changedAttributes.selectField || changedAttributes.selectIndex) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t// If the target tiddler value has changed, just update setting and refresh the children\n\t} else {\n\t\tvar childrenRefreshed = this.refreshChildren(changedTiddlers);\n\t\tif(changedTiddlers[this.selectTitle] || childrenRefreshed) {\n\t\t\tthis.setSelectValue();\n\t\t} \n\t\treturn childrenRefreshed;\n\t}\n};\n\nexports.select = SelectWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/select.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/set.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/set.js\ntype: application/javascript\nmodule-type: widget\n\nSet variable widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar SetWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nSetWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nSetWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nSetWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.setName = this.getAttribute(\"name\",\"currentTiddler\");\n\tthis.setFilter = this.getAttribute(\"filter\");\n\tthis.setValue = this.getAttribute(\"value\");\n\tthis.setEmptyValue = this.getAttribute(\"emptyValue\");\n\t// Set context variable\n\tthis.setVariable(this.setName,this.getValue(),this.parseTreeNode.params);\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nGet the value to be assigned\n*/\nSetWidget.prototype.getValue = function() {\n\tvar value = this.setValue;\n\tif(this.setFilter) {\n\t\tvar results = this.wiki.filterTiddlers(this.setFilter,this);\n\t\tif(!this.setValue) {\n\t\t\tvalue = $tw.utils.stringifyList(results);\n\t\t}\n\t\tif(results.length === 0 && this.setEmptyValue !== undefined) {\n\t\t\tvalue = this.setEmptyValue;\n\t\t}\n\t} else if(!value && this.setEmptyValue) {\n\t\tvalue = this.setEmptyValue;\n\t}\n\treturn value;\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nSetWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.name || changedAttributes.filter || changedAttributes.value || changedAttributes.emptyValue ||\n\t (this.setFilter && this.getValue() != this.variables[this.setName].value)) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\n\t}\n};\n\nexports.setvariable = SetWidget;\nexports.set = SetWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/set.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/text.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/text.js\ntype: application/javascript\nmodule-type: widget\n\nText node widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar TextNodeWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nTextNodeWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nTextNodeWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tvar text = this.getAttribute(\"text\",this.parseTreeNode.text || \"\");\n\ttext = text.replace(/\\r/mg,\"\");\n\tvar textNode = this.document.createTextNode(text);\n\tparent.insertBefore(textNode,nextSibling);\n\tthis.domNodes.push(textNode);\n};\n\n/*\nCompute the internal state of the widget\n*/\nTextNodeWidget.prototype.execute = function() {\n\t// Nothing to do for a text node\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nTextNodeWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.text) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports.text = TextNodeWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/text.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/tiddler.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/tiddler.js\ntype: application/javascript\nmodule-type: widget\n\nTiddler widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar TiddlerWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nTiddlerWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nTiddlerWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nTiddlerWidget.prototype.execute = function() {\n\tthis.tiddlerState = this.computeTiddlerState();\n\tthis.setVariable(\"currentTiddler\",this.tiddlerState.currentTiddler);\n\tthis.setVariable(\"missingTiddlerClass\",this.tiddlerState.missingTiddlerClass);\n\tthis.setVariable(\"shadowTiddlerClass\",this.tiddlerState.shadowTiddlerClass);\n\tthis.setVariable(\"systemTiddlerClass\",this.tiddlerState.systemTiddlerClass);\n\tthis.setVariable(\"tiddlerTagClasses\",this.tiddlerState.tiddlerTagClasses);\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nCompute the tiddler state flags\n*/\nTiddlerWidget.prototype.computeTiddlerState = function() {\n\t// Get our parameters\n\tthis.tiddlerTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\t// Compute the state\n\tvar state = {\n\t\tcurrentTiddler: this.tiddlerTitle || \"\",\n\t\tmissingTiddlerClass: (this.wiki.tiddlerExists(this.tiddlerTitle) || this.wiki.isShadowTiddler(this.tiddlerTitle)) ? \"tc-tiddler-exists\" : \"tc-tiddler-missing\",\n\t\tshadowTiddlerClass: this.wiki.isShadowTiddler(this.tiddlerTitle) ? \"tc-tiddler-shadow\" : \"\",\n\t\tsystemTiddlerClass: this.wiki.isSystemTiddler(this.tiddlerTitle) ? \"tc-tiddler-system\" : \"\",\n\t\ttiddlerTagClasses: this.getTagClasses()\n\t};\n\t// Compute a simple hash to make it easier to detect changes\n\tstate.hash = state.currentTiddler + state.missingTiddlerClass + state.shadowTiddlerClass + state.systemTiddlerClass + state.tiddlerTagClasses;\n\treturn state;\n};\n\n/*\nCreate a string of CSS classes derived from the tags of the current tiddler\n*/\nTiddlerWidget.prototype.getTagClasses = function() {\n\tvar tiddler = this.wiki.getTiddler(this.tiddlerTitle);\n\tif(tiddler) {\n\t\tvar tags = [];\n\t\t$tw.utils.each(tiddler.fields.tags,function(tag) {\n\t\t\ttags.push(\"tc-tagged-\" + encodeURIComponent(tag));\n\t\t});\n\t\treturn tags.join(\" \");\n\t} else {\n\t\treturn \"\";\n\t}\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nTiddlerWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes(),\n\t\tnewTiddlerState = this.computeTiddlerState();\n\tif(changedAttributes.tiddler || newTiddlerState.hash !== this.tiddlerState.hash) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nexports.tiddler = TiddlerWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/tiddler.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/transclude.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/transclude.js\ntype: application/javascript\nmodule-type: widget\n\nTransclude widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar TranscludeWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nTranscludeWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nTranscludeWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nTranscludeWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.transcludeTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.transcludeSubTiddler = this.getAttribute(\"subtiddler\");\n\tthis.transcludeField = this.getAttribute(\"field\");\n\tthis.transcludeIndex = this.getAttribute(\"index\");\n\tthis.transcludeMode = this.getAttribute(\"mode\");\n\t// Parse the text reference\n\tvar parseAsInline = !this.parseTreeNode.isBlock;\n\tif(this.transcludeMode === \"inline\") {\n\t\tparseAsInline = true;\n\t} else if(this.transcludeMode === \"block\") {\n\t\tparseAsInline = false;\n\t}\n\tvar parser = this.wiki.parseTextReference(\n\t\t\t\t\t\tthis.transcludeTitle,\n\t\t\t\t\t\tthis.transcludeField,\n\t\t\t\t\t\tthis.transcludeIndex,\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tparseAsInline: parseAsInline,\n\t\t\t\t\t\t\tsubTiddler: this.transcludeSubTiddler\n\t\t\t\t\t\t}),\n\t\tparseTreeNodes = parser ? parser.tree : this.parseTreeNode.children;\n\t// Set context variables for recursion detection\n\tvar recursionMarker = this.makeRecursionMarker();\n\tthis.setVariable(\"transclusion\",recursionMarker);\n\t// Check for recursion\n\tif(parser) {\n\t\tif(this.parentWidget && this.parentWidget.hasVariable(\"transclusion\",recursionMarker)) {\n\t\t\tparseTreeNodes = [{type: \"element\", tag: \"span\", attributes: {\n\t\t\t\t\"class\": {type: \"string\", value: \"tc-error\"}\n\t\t\t}, children: [\n\t\t\t\t{type: \"text\", text: $tw.language.getString(\"Error/RecursiveTransclusion\")}\n\t\t\t]}];\n\t\t}\n\t}\n\t// Construct the child widgets\n\tthis.makeChildWidgets(parseTreeNodes);\n};\n\n/*\nCompose a string comprising the title, field and/or index to identify this transclusion for recursion detection\n*/\nTranscludeWidget.prototype.makeRecursionMarker = function() {\n\tvar output = [];\n\toutput.push(\"{\");\n\toutput.push(this.getVariable(\"currentTiddler\",{defaultValue: \"\"}));\n\toutput.push(\"|\");\n\toutput.push(this.transcludeTitle || \"\");\n\toutput.push(\"|\");\n\toutput.push(this.transcludeField || \"\");\n\toutput.push(\"|\");\n\toutput.push(this.transcludeIndex || \"\");\n\toutput.push(\"|\");\n\toutput.push(this.transcludeSubTiddler || \"\");\n\toutput.push(\"}\");\n\treturn output.join(\"\");\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nTranscludeWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.index || changedTiddlers[this.transcludeTitle]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\t\t\n\t}\n};\n\nexports.transclude = TranscludeWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/transclude.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/vars.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/vars.js\ntype: application/javascript\nmodule-type: widget\n\nThis widget allows multiple variables to be set in one go:\n\n```\n\\define helloworld() Hello world!\n<$vars greeting=\"Hi\" me={{!!title}} sentence=<<helloworld>>>\n <<greeting>>! I am <<me>> and I say: <<sentence>>\n</$vars>\n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar VarsWidget = function(parseTreeNode,options) {\n\t// Call the constructor\n\tWidget.call(this);\n\t// Initialise\t\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nVarsWidget.prototype = Object.create(Widget.prototype);\n\n/*\nRender this widget into the DOM\n*/\nVarsWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nVarsWidget.prototype.execute = function() {\n\t// Parse variables\n\tvar self = this;\n\t$tw.utils.each(this.attributes,function(val,key) {\n\t\tif(key.charAt(0) !== \"$\") {\n\t\t\tself.setVariable(key,val);\n\t\t}\n\t});\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nVarsWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(Object.keys(changedAttributes).length) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn this.refreshChildren(changedTiddlers);\n};\n\nexports[\"vars\"] = VarsWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/vars.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/view.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/view.js\ntype: application/javascript\nmodule-type: widget\n\nView widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ViewWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nViewWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nViewWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tif(this.text) {\n\t\tvar textNode = this.document.createTextNode(this.text);\n\t\tparent.insertBefore(textNode,nextSibling);\n\t\tthis.domNodes.push(textNode);\n\t} else {\n\t\tthis.makeChildWidgets();\n\t\tthis.renderChildren(parent,nextSibling);\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nViewWidget.prototype.execute = function() {\n\t// Get parameters from our attributes\n\tthis.viewTitle = this.getAttribute(\"tiddler\",this.getVariable(\"currentTiddler\"));\n\tthis.viewSubtiddler = this.getAttribute(\"subtiddler\");\n\tthis.viewField = this.getAttribute(\"field\",\"text\");\n\tthis.viewIndex = this.getAttribute(\"index\");\n\tthis.viewFormat = this.getAttribute(\"format\",\"text\");\n\tthis.viewTemplate = this.getAttribute(\"template\",\"\");\n\tswitch(this.viewFormat) {\n\t\tcase \"htmlwikified\":\n\t\t\tthis.text = this.getValueAsHtmlWikified();\n\t\t\tbreak;\n\t\tcase \"plainwikified\":\n\t\t\tthis.text = this.getValueAsPlainWikified();\n\t\t\tbreak;\n\t\tcase \"htmlencodedplainwikified\":\n\t\t\tthis.text = this.getValueAsHtmlEncodedPlainWikified();\n\t\t\tbreak;\n\t\tcase \"htmlencoded\":\n\t\t\tthis.text = this.getValueAsHtmlEncoded();\n\t\t\tbreak;\n\t\tcase \"urlencoded\":\n\t\t\tthis.text = this.getValueAsUrlEncoded();\n\t\t\tbreak;\n\t\tcase \"doubleurlencoded\":\n\t\t\tthis.text = this.getValueAsDoubleUrlEncoded();\n\t\t\tbreak;\n\t\tcase \"date\":\n\t\t\tthis.text = this.getValueAsDate(this.viewTemplate);\n\t\t\tbreak;\n\t\tcase \"relativedate\":\n\t\t\tthis.text = this.getValueAsRelativeDate();\n\t\t\tbreak;\n\t\tcase \"stripcomments\":\n\t\t\tthis.text = this.getValueAsStrippedComments();\n\t\t\tbreak;\n\t\tcase \"jsencoded\":\n\t\t\tthis.text = this.getValueAsJsEncoded();\n\t\t\tbreak;\n\t\tdefault: // \"text\"\n\t\t\tthis.text = this.getValueAsText();\n\t\t\tbreak;\n\t}\n};\n\n/*\nThe various formatter functions are baked into this widget for the moment. Eventually they will be replaced by macro functions\n*/\n\n/*\nRetrieve the value of the widget. Options are:\nasString: Optionally return the value as a string\n*/\nViewWidget.prototype.getValue = function(options) {\n\toptions = options || {};\n\tvar value = options.asString ? \"\" : undefined;\n\tif(this.viewIndex) {\n\t\tvalue = this.wiki.extractTiddlerDataItem(this.viewTitle,this.viewIndex);\n\t} else {\n\t\tvar tiddler;\n\t\tif(this.viewSubtiddler) {\n\t\t\ttiddler = this.wiki.getSubTiddler(this.viewTitle,this.viewSubtiddler);\t\n\t\t} else {\n\t\t\ttiddler = this.wiki.getTiddler(this.viewTitle);\n\t\t}\n\t\tif(tiddler) {\n\t\t\tif(this.viewField === \"text\" && !this.viewSubtiddler) {\n\t\t\t\t// Calling getTiddlerText() triggers lazy loading of skinny tiddlers\n\t\t\t\tvalue = this.wiki.getTiddlerText(this.viewTitle);\n\t\t\t} else {\n\t\t\t\tif($tw.utils.hop(tiddler.fields,this.viewField)) {\n\t\t\t\t\tif(options.asString) {\n\t\t\t\t\t\tvalue = tiddler.getFieldString(this.viewField);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tvalue = tiddler.fields[this.viewField];\t\t\t\t\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t} else {\n\t\t\tif(this.viewField === \"title\") {\n\t\t\t\tvalue = this.viewTitle;\n\t\t\t}\n\t\t}\n\t}\n\treturn value;\n};\n\nViewWidget.prototype.getValueAsText = function() {\n\treturn this.getValue({asString: true});\n};\n\nViewWidget.prototype.getValueAsHtmlWikified = function() {\n\treturn this.wiki.renderText(\"text/html\",\"text/vnd.tiddlywiki\",this.getValueAsText(),{parentWidget: this});\n};\n\nViewWidget.prototype.getValueAsPlainWikified = function() {\n\treturn this.wiki.renderText(\"text/plain\",\"text/vnd.tiddlywiki\",this.getValueAsText(),{parentWidget: this});\n};\n\nViewWidget.prototype.getValueAsHtmlEncodedPlainWikified = function() {\n\treturn $tw.utils.htmlEncode(this.wiki.renderText(\"text/plain\",\"text/vnd.tiddlywiki\",this.getValueAsText(),{parentWidget: this}));\n};\n\nViewWidget.prototype.getValueAsHtmlEncoded = function() {\n\treturn $tw.utils.htmlEncode(this.getValueAsText());\n};\n\nViewWidget.prototype.getValueAsUrlEncoded = function() {\n\treturn encodeURIComponent(this.getValueAsText());\n};\n\nViewWidget.prototype.getValueAsDoubleUrlEncoded = function() {\n\treturn encodeURIComponent(encodeURIComponent(this.getValueAsText()));\n};\n\nViewWidget.prototype.getValueAsDate = function(format) {\n\tformat = format || \"YYYY MM DD 0hh:0mm\";\n\tvar value = $tw.utils.parseDate(this.getValue());\n\tif(value && $tw.utils.isDate(value) && value.toString() !== \"Invalid Date\") {\n\t\treturn $tw.utils.formatDateString(value,format);\n\t} else {\n\t\treturn \"\";\n\t}\n};\n\nViewWidget.prototype.getValueAsRelativeDate = function(format) {\n\tvar value = $tw.utils.parseDate(this.getValue());\n\tif(value && $tw.utils.isDate(value) && value.toString() !== \"Invalid Date\") {\n\t\treturn $tw.utils.getRelativeDate((new Date()) - (new Date(value))).description;\n\t} else {\n\t\treturn \"\";\n\t}\n};\n\nViewWidget.prototype.getValueAsStrippedComments = function() {\n\tvar lines = this.getValueAsText().split(\"\\n\"),\n\t\tout = [];\n\tfor(var line=0; line<lines.length; line++) {\n\t\tvar text = lines[line];\n\t\tif(!/^\\s*\\/\\/#/.test(text)) {\n\t\t\tout.push(text);\n\t\t}\n\t}\n\treturn out.join(\"\\n\");\n};\n\nViewWidget.prototype.getValueAsJsEncoded = function() {\n\treturn $tw.utils.stringify(this.getValueAsText());\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nViewWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.tiddler || changedAttributes.field || changedAttributes.index || changedAttributes.template || changedAttributes.format || changedTiddlers[this.viewTitle]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports.view = ViewWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/view.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/widget.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/widget.js\ntype: application/javascript\nmodule-type: widget\n\nWidget base class\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nCreate a widget object for a parse tree node\n\tparseTreeNode: reference to the parse tree node to be rendered\n\toptions: see below\nOptions include:\n\twiki: mandatory reference to wiki associated with this render tree\n\tparentWidget: optional reference to a parent renderer node for the context chain\n\tdocument: optional document object to use instead of global document\n*/\nvar Widget = function(parseTreeNode,options) {\n\tif(arguments.length > 0) {\n\t\tthis.initialise(parseTreeNode,options);\n\t}\n};\n\n/*\nInitialise widget properties. These steps are pulled out of the constructor so that we can reuse them in subclasses\n*/\nWidget.prototype.initialise = function(parseTreeNode,options) {\n\toptions = options || {};\n\t// Save widget info\n\tthis.parseTreeNode = parseTreeNode;\n\tthis.wiki = options.wiki;\n\tthis.parentWidget = options.parentWidget;\n\tthis.variablesConstructor = function() {};\n\tthis.variablesConstructor.prototype = this.parentWidget ? this.parentWidget.variables : {};\n\tthis.variables = new this.variablesConstructor();\n\tthis.document = options.document;\n\tthis.attributes = {};\n\tthis.children = [];\n\tthis.domNodes = [];\n\tthis.eventListeners = {};\n\t// Hashmap of the widget classes\n\tif(!this.widgetClasses) {\n\t\tWidget.prototype.widgetClasses = $tw.modules.applyMethods(\"widget\");\n\t}\n};\n\n/*\nRender this widget into the DOM\n*/\nWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nWidget.prototype.execute = function() {\n\tthis.makeChildWidgets();\n};\n\n/*\nSet the value of a context variable\nname: name of the variable\nvalue: value of the variable\nparams: array of {name:, default:} for each parameter\n*/\nWidget.prototype.setVariable = function(name,value,params) {\n\tthis.variables[name] = {value: value, params: params};\n};\n\n/*\nGet the prevailing value of a context variable\nname: name of variable\noptions: see below\nOptions include\nparams: array of {name:, value:} for each parameter\ndefaultValue: default value if the variable is not defined\n*/\nWidget.prototype.getVariable = function(name,options) {\n\toptions = options || {};\n\tvar actualParams = options.params || [],\n\t\tparentWidget = this.parentWidget;\n\t// Check for the variable defined in the parent widget (or an ancestor in the prototype chain)\n\tif(parentWidget && name in parentWidget.variables) {\n\t\tvar variable = parentWidget.variables[name],\n\t\t\tvalue = variable.value;\n\t\t// Substitute any parameters specified in the definition\n\t\tvalue = this.substituteVariableParameters(value,variable.params,actualParams);\n\t\tvalue = this.substituteVariableReferences(value);\n\t\treturn value;\n\t}\n\t// If the variable doesn't exist in the parent widget then look for a macro module\n\treturn this.evaluateMacroModule(name,actualParams,options.defaultValue);\n};\n\nWidget.prototype.substituteVariableParameters = function(text,formalParams,actualParams) {\n\tif(formalParams) {\n\t\tvar nextAnonParameter = 0, // Next candidate anonymous parameter in macro call\n\t\t\tparamInfo, paramValue;\n\t\t// Step through each of the parameters in the macro definition\n\t\tfor(var p=0; p<formalParams.length; p++) {\n\t\t\t// Check if we've got a macro call parameter with the same name\n\t\t\tparamInfo = formalParams[p];\n\t\t\tparamValue = undefined;\n\t\t\tfor(var m=0; m<actualParams.length; m++) {\n\t\t\t\tif(actualParams[m].name === paramInfo.name) {\n\t\t\t\t\tparamValue = actualParams[m].value;\n\t\t\t\t}\n\t\t\t}\n\t\t\t// If not, use the next available anonymous macro call parameter\n\t\t\twhile(nextAnonParameter < actualParams.length && actualParams[nextAnonParameter].name) {\n\t\t\t\tnextAnonParameter++;\n\t\t\t}\n\t\t\tif(paramValue === undefined && nextAnonParameter < actualParams.length) {\n\t\t\t\tparamValue = actualParams[nextAnonParameter++].value;\n\t\t\t}\n\t\t\t// If we've still not got a value, use the default, if any\n\t\t\tparamValue = paramValue || paramInfo[\"default\"] || \"\";\n\t\t\t// Replace any instances of this parameter\n\t\t\ttext = text.replace(new RegExp(\"\\\\$\" + $tw.utils.escapeRegExp(paramInfo.name) + \"\\\\$\",\"mg\"),paramValue);\n\t\t}\n\t}\n\treturn text;\n};\n\nWidget.prototype.substituteVariableReferences = function(text) {\n\tvar self = this;\n\treturn (text || \"\").replace(/\\$\\(([^\\)\\$]+)\\)\\$/g,function(match,p1,offset,string) {\n\t\treturn self.getVariable(p1,{defaultValue: \"\"});\n\t});\n};\n\nWidget.prototype.evaluateMacroModule = function(name,actualParams,defaultValue) {\n\tif($tw.utils.hop($tw.macros,name)) {\n\t\tvar macro = $tw.macros[name],\n\t\t\targs = [];\n\t\tif(macro.params.length > 0) {\n\t\t\tvar nextAnonParameter = 0, // Next candidate anonymous parameter in macro call\n\t\t\t\tparamInfo, paramValue;\n\t\t\t// Step through each of the parameters in the macro definition\n\t\t\tfor(var p=0; p<macro.params.length; p++) {\n\t\t\t\t// Check if we've got a macro call parameter with the same name\n\t\t\t\tparamInfo = macro.params[p];\n\t\t\t\tparamValue = undefined;\n\t\t\t\tfor(var m=0; m<actualParams.length; m++) {\n\t\t\t\t\tif(actualParams[m].name === paramInfo.name) {\n\t\t\t\t\t\tparamValue = actualParams[m].value;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t// If not, use the next available anonymous macro call parameter\n\t\t\t\twhile(nextAnonParameter < actualParams.length && actualParams[nextAnonParameter].name) {\n\t\t\t\t\tnextAnonParameter++;\n\t\t\t\t}\n\t\t\t\tif(paramValue === undefined && nextAnonParameter < actualParams.length) {\n\t\t\t\t\tparamValue = actualParams[nextAnonParameter++].value;\n\t\t\t\t}\n\t\t\t\t// If we've still not got a value, use the default, if any\n\t\t\t\tparamValue = paramValue || paramInfo[\"default\"] || \"\";\n\t\t\t\t// Save the parameter\n\t\t\t\targs.push(paramValue);\n\t\t\t}\n\t\t}\n\t\telse for(var i=0; i<actualParams.length; ++i) {\n\t\t\targs.push(actualParams[i].value);\n\t\t}\n\t\treturn (macro.run.apply(this,args) || \"\").toString();\n\t} else {\n\t\treturn defaultValue;\n\t}\n};\n\n/*\nCheck whether a given context variable value exists in the parent chain\n*/\nWidget.prototype.hasVariable = function(name,value) {\n\tvar node = this;\n\twhile(node) {\n\t\tif($tw.utils.hop(node.variables,name) && node.variables[name].value === value) {\n\t\t\treturn true;\n\t\t}\n\t\tnode = node.parentWidget;\n\t}\n\treturn false;\n};\n\n/*\nConstruct a qualifying string based on a hash of concatenating the values of a given variable in the parent chain\n*/\nWidget.prototype.getStateQualifier = function(name) {\n\tthis.qualifiers = this.qualifiers || Object.create(null);\n\tname = name || \"transclusion\";\n\tif(this.qualifiers[name]) {\n\t\treturn this.qualifiers[name];\n\t} else {\n\t\tvar output = [],\n\t\t\tnode = this;\n\t\twhile(node && node.parentWidget) {\n\t\t\tif($tw.utils.hop(node.parentWidget.variables,name)) {\n\t\t\t\toutput.push(node.getVariable(name));\n\t\t\t}\n\t\t\tnode = node.parentWidget;\n\t\t}\n\t\tvar value = $tw.utils.hashString(output.join(\"\"));\n\t\tthis.qualifiers[name] = value;\n\t\treturn value;\n\t}\n};\n\n/*\nCompute the current values of the attributes of the widget. Returns a hashmap of the names of the attributes that have changed\n*/\nWidget.prototype.computeAttributes = function() {\n\tvar changedAttributes = {},\n\t\tself = this,\n\t\tvalue;\n\t$tw.utils.each(this.parseTreeNode.attributes,function(attribute,name) {\n\t\tif(attribute.type === \"indirect\") {\n\t\t\tvalue = self.wiki.getTextReference(attribute.textReference,\"\",self.getVariable(\"currentTiddler\"));\n\t\t} else if(attribute.type === \"macro\") {\n\t\t\tvalue = self.getVariable(attribute.value.name,{params: attribute.value.params});\n\t\t} else { // String attribute\n\t\t\tvalue = attribute.value;\n\t\t}\n\t\t// Check whether the attribute has changed\n\t\tif(self.attributes[name] !== value) {\n\t\t\tself.attributes[name] = value;\n\t\t\tchangedAttributes[name] = true;\n\t\t}\n\t});\n\treturn changedAttributes;\n};\n\n/*\nCheck for the presence of an attribute\n*/\nWidget.prototype.hasAttribute = function(name) {\n\treturn $tw.utils.hop(this.attributes,name);\n};\n\n/*\nGet the value of an attribute\n*/\nWidget.prototype.getAttribute = function(name,defaultText) {\n\tif($tw.utils.hop(this.attributes,name)) {\n\t\treturn this.attributes[name];\n\t} else {\n\t\treturn defaultText;\n\t}\n};\n\n/*\nAssign the computed attributes of the widget to a domNode\noptions include:\nexcludeEventAttributes: ignores attributes whose name begins with \"on\"\n*/\nWidget.prototype.assignAttributes = function(domNode,options) {\n\toptions = options || {};\n\tvar self = this;\n\t$tw.utils.each(this.attributes,function(v,a) {\n\t\t// Check exclusions\n\t\tif(options.excludeEventAttributes && a.substr(0,2) === \"on\") {\n\t\t\tv = undefined;\n\t\t}\n\t\tif(v !== undefined) {\n\t\t\tvar b = a.split(\":\");\n\t\t\t// Setting certain attributes can cause a DOM error (eg xmlns on the svg element)\n\t\t\ttry {\n\t\t\t\tif (b.length == 2 && b[0] == \"xlink\"){\n\t\t\t\t\tdomNode.setAttributeNS(\"http://www.w3.org/1999/xlink\",b[1],v);\n\t\t\t\t} else {\n\t\t\t\t\tdomNode.setAttributeNS(null,a,v);\n\t\t\t\t}\n\t\t\t} catch(e) {\n\t\t\t}\n\t\t}\n\t});\n};\n\n/*\nMake child widgets correspondng to specified parseTreeNodes\n*/\nWidget.prototype.makeChildWidgets = function(parseTreeNodes) {\n\tthis.children = [];\n\tvar self = this;\n\t$tw.utils.each(parseTreeNodes || (this.parseTreeNode && this.parseTreeNode.children),function(childNode) {\n\t\tself.children.push(self.makeChildWidget(childNode));\n\t});\n};\n\n/*\nConstruct the widget object for a parse tree node\n*/\nWidget.prototype.makeChildWidget = function(parseTreeNode) {\n\tvar WidgetClass = this.widgetClasses[parseTreeNode.type];\n\tif(!WidgetClass) {\n\t\tWidgetClass = this.widgetClasses.text;\n\t\tparseTreeNode = {type: \"text\", text: \"Undefined widget '\" + parseTreeNode.type + \"'\"};\n\t}\n\treturn new WidgetClass(parseTreeNode,{\n\t\twiki: this.wiki,\n\t\tvariables: {},\n\t\tparentWidget: this,\n\t\tdocument: this.document\n\t});\n};\n\n/*\nGet the next sibling of this widget\n*/\nWidget.prototype.nextSibling = function() {\n\tif(this.parentWidget) {\n\t\tvar index = this.parentWidget.children.indexOf(this);\n\t\tif(index !== -1 && index < this.parentWidget.children.length-1) {\n\t\t\treturn this.parentWidget.children[index+1];\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nGet the previous sibling of this widget\n*/\nWidget.prototype.previousSibling = function() {\n\tif(this.parentWidget) {\n\t\tvar index = this.parentWidget.children.indexOf(this);\n\t\tif(index !== -1 && index > 0) {\n\t\t\treturn this.parentWidget.children[index-1];\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nRender the children of this widget into the DOM\n*/\nWidget.prototype.renderChildren = function(parent,nextSibling) {\n\t$tw.utils.each(this.children,function(childWidget) {\n\t\tchildWidget.render(parent,nextSibling);\n\t});\n};\n\n/*\nAdd a list of event listeners from an array [{type:,handler:},...]\n*/\nWidget.prototype.addEventListeners = function(listeners) {\n\tvar self = this;\n\t$tw.utils.each(listeners,function(listenerInfo) {\n\t\tself.addEventListener(listenerInfo.type,listenerInfo.handler);\n\t});\n};\n\n/*\nAdd an event listener\n*/\nWidget.prototype.addEventListener = function(type,handler) {\n\tvar self = this;\n\tif(typeof handler === \"string\") { // The handler is a method name on this widget\n\t\tthis.eventListeners[type] = function(event) {\n\t\t\treturn self[handler].call(self,event);\n\t\t};\n\t} else { // The handler is a function\n\t\tthis.eventListeners[type] = function(event) {\n\t\t\treturn handler.call(self,event);\n\t\t};\n\t}\n};\n\n/*\nDispatch an event to a widget. If the widget doesn't handle the event then it is also dispatched to the parent widget\n*/\nWidget.prototype.dispatchEvent = function(event) {\n\t// Dispatch the event if this widget handles it\n\tvar listener = this.eventListeners[event.type];\n\tif(listener) {\n\t\t// Don't propagate the event if the listener returned false\n\t\tif(!listener(event)) {\n\t\t\treturn false;\n\t\t}\n\t}\n\t// Dispatch the event to the parent widget\n\tif(this.parentWidget) {\n\t\treturn this.parentWidget.dispatchEvent(event);\n\t}\n\treturn true;\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nWidget.prototype.refresh = function(changedTiddlers) {\n\treturn this.refreshChildren(changedTiddlers);\n};\n\n/*\nRebuild a previously rendered widget\n*/\nWidget.prototype.refreshSelf = function() {\n\tvar nextSibling = this.findNextSiblingDomNode();\n\tthis.removeChildDomNodes();\n\tthis.render(this.parentDomNode,nextSibling);\n};\n\n/*\nRefresh all the children of a widget\n*/\nWidget.prototype.refreshChildren = function(changedTiddlers) {\n\tvar self = this,\n\t\trefreshed = false;\n\t$tw.utils.each(this.children,function(childWidget) {\n\t\trefreshed = childWidget.refresh(changedTiddlers) || refreshed;\n\t});\n\treturn refreshed;\n};\n\n/*\nFind the next sibling in the DOM to this widget. This is done by scanning the widget tree through all next siblings and their descendents that share the same parent DOM node\n*/\nWidget.prototype.findNextSiblingDomNode = function(startIndex) {\n\t// Refer to this widget by its index within its parents children\n\tvar parent = this.parentWidget,\n\t\tindex = startIndex !== undefined ? startIndex : parent.children.indexOf(this);\nif(index === -1) {\n\tthrow \"node not found in parents children\";\n}\n\t// Look for a DOM node in the later siblings\n\twhile(++index < parent.children.length) {\n\t\tvar domNode = parent.children[index].findFirstDomNode();\n\t\tif(domNode) {\n\t\t\treturn domNode;\n\t\t}\n\t}\n\t// Go back and look for later siblings of our parent if it has the same parent dom node\n\tvar grandParent = parent.parentWidget;\n\tif(grandParent && parent.parentDomNode === this.parentDomNode) {\n\t\tindex = grandParent.children.indexOf(parent);\n\t\tif(index !== -1) {\n\t\t\treturn parent.findNextSiblingDomNode(index);\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nFind the first DOM node generated by a widget or its children\n*/\nWidget.prototype.findFirstDomNode = function() {\n\t// Return the first dom node of this widget, if we've got one\n\tif(this.domNodes.length > 0) {\n\t\treturn this.domNodes[0];\n\t}\n\t// Otherwise, recursively call our children\n\tfor(var t=0; t<this.children.length; t++) {\n\t\tvar domNode = this.children[t].findFirstDomNode();\n\t\tif(domNode) {\n\t\t\treturn domNode;\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nRemove any DOM nodes created by this widget or its children\n*/\nWidget.prototype.removeChildDomNodes = function() {\n\t// If this widget has directly created DOM nodes, delete them and exit. This assumes that any child widgets are contained within the created DOM nodes, which would normally be the case\n\tif(this.domNodes.length > 0) {\n\t\t$tw.utils.each(this.domNodes,function(domNode) {\n\t\t\tdomNode.parentNode.removeChild(domNode);\n\t\t});\n\t\tthis.domNodes = [];\n\t} else {\n\t\t// Otherwise, ask the child widgets to delete their DOM nodes\n\t\t$tw.utils.each(this.children,function(childWidget) {\n\t\t\tchildWidget.removeChildDomNodes();\n\t\t});\n\t}\n};\n\n/*\nInvoke the action widgets that are descendents of the current widget.\n*/\nWidget.prototype.invokeActions = function(triggeringWidget,event) {\n\tvar handled = false;\n\t// For each child widget\n\tfor(var t=0; t<this.children.length; t++) {\n\t\tvar child = this.children[t];\n\t\t// Invoke the child if it is an action widget\n\t\tif(child.invokeAction && child.invokeAction(triggeringWidget,event)) {\n\t\t\thandled = true;\n\t\t}\n\t\t// Propagate through through the child if it permits it\n\t\tif(child.allowActionPropagation() && child.invokeActions(triggeringWidget,event)) {\n\t\t\thandled = true;\n\t\t}\n\t}\n\treturn handled;\n};\n\n/*\nInvoke the action widgets defined in a string\n*/\nWidget.prototype.invokeActionString = function(actions,triggeringWidget,event) {\n\tactions = actions || \"\";\n\tvar parser = this.wiki.parseText(\"text/vnd.tiddlywiki\",actions,{\n\t\t\tparentWidget: this,\n\t\t\tdocument: this.document\n\t\t}),\n\t\twidgetNode = this.wiki.makeWidget(parser,{\n\t\t\tparentWidget: this,\n\t\t\tdocument: this.document\n\t\t});\n\tvar container = this.document.createElement(\"div\");\n\twidgetNode.render(container,null);\n\treturn widgetNode.invokeActions(this,event);\n};\n\nWidget.prototype.allowActionPropagation = function() {\n\treturn true;\n};\n\nexports.widget = Widget;\n\n})();\n",
"title": "$:/core/modules/widgets/widget.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/widgets/wikify.js": {
"text": "/*\\\ntitle: $:/core/modules/widgets/wikify.js\ntype: application/javascript\nmodule-type: widget\n\nWidget to wikify text into a variable\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar WikifyWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nWikifyWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nWikifyWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nWikifyWidget.prototype.execute = function() {\n\t// Get our parameters\n\tthis.wikifyName = this.getAttribute(\"name\");\n\tthis.wikifyText = this.getAttribute(\"text\");\n\tthis.wikifyType = this.getAttribute(\"type\");\n\tthis.wikifyMode = this.getAttribute(\"mode\",\"block\");\n\tthis.wikifyOutput = this.getAttribute(\"output\",\"text\");\n\t// Create the parse tree\n\tthis.wikifyParser = this.wiki.parseText(this.wikifyType,this.wikifyText,{\n\t\t\tparseAsInline: this.wikifyMode === \"inline\"\n\t\t});\n\t// Create the widget tree \n\tthis.wikifyWidgetNode = this.wiki.makeWidget(this.wikifyParser,{\n\t\t\tdocument: $tw.fakeDocument,\n\t\t\tparentWidget: this\n\t\t});\n\t// Render the widget tree to the container\n\tthis.wikifyContainer = $tw.fakeDocument.createElement(\"div\");\n\tthis.wikifyWidgetNode.render(this.wikifyContainer,null);\n\tthis.wikifyResult = this.getResult();\n\t// Set context variable\n\tthis.setVariable(this.wikifyName,this.wikifyResult);\n\t// Construct the child widgets\n\tthis.makeChildWidgets();\n};\n\n/*\nReturn the result string\n*/\nWikifyWidget.prototype.getResult = function() {\n\tvar result;\n\tswitch(this.wikifyOutput) {\n\t\tcase \"text\":\n\t\t\tresult = this.wikifyContainer.textContent;\n\t\t\tbreak;\n\t\tcase \"html\":\n\t\t\tresult = this.wikifyContainer.innerHTML;\n\t\t\tbreak;\n\t\tcase \"parsetree\":\n\t\t\tresult = JSON.stringify(this.wikifyParser.tree,0,$tw.config.preferences.jsonSpaces);\n\t\t\tbreak;\n\t\tcase \"widgettree\":\n\t\t\tresult = JSON.stringify(this.getWidgetTree(),0,$tw.config.preferences.jsonSpaces);\n\t\t\tbreak;\n\t}\n\treturn result;\n};\n\n/*\nReturn a string of the widget tree\n*/\nWikifyWidget.prototype.getWidgetTree = function() {\n\tvar copyNode = function(widgetNode,resultNode) {\n\t\t\tvar type = widgetNode.parseTreeNode.type;\n\t\t\tresultNode.type = type;\n\t\t\tswitch(type) {\n\t\t\t\tcase \"element\":\n\t\t\t\t\tresultNode.tag = widgetNode.parseTreeNode.tag;\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"text\":\n\t\t\t\t\tresultNode.text = widgetNode.parseTreeNode.text;\n\t\t\t\t\tbreak;\t\n\t\t\t}\n\t\t\tif(Object.keys(widgetNode.attributes || {}).length > 0) {\n\t\t\t\tresultNode.attributes = {};\n\t\t\t\t$tw.utils.each(widgetNode.attributes,function(attr,attrName) {\n\t\t\t\t\tresultNode.attributes[attrName] = widgetNode.getAttribute(attrName);\n\t\t\t\t});\n\t\t\t}\n\t\t\tif(Object.keys(widgetNode.children || {}).length > 0) {\n\t\t\t\tresultNode.children = [];\n\t\t\t\t$tw.utils.each(widgetNode.children,function(widgetChildNode) {\n\t\t\t\t\tvar node = {};\n\t\t\t\t\tresultNode.children.push(node);\n\t\t\t\t\tcopyNode(widgetChildNode,node);\n\t\t\t\t});\n\t\t\t}\n\t\t},\n\t\tresults = {};\n\tcopyNode(this.wikifyWidgetNode,results);\n\treturn results;\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nWikifyWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\t// Refresh ourselves entirely if any of our attributes have changed\n\tif(changedAttributes.name || changedAttributes.text || changedAttributes.type || changedAttributes.mode || changedAttributes.output) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\t// Refresh the widget tree\n\t\tif(this.wikifyWidgetNode.refresh(changedTiddlers)) {\n\t\t\t// Check if there was any change\n\t\t\tvar result = this.getResult();\n\t\t\tif(result !== this.wikifyResult) {\n\t\t\t\t// If so, save the change\n\t\t\t\tthis.wikifyResult = result;\n\t\t\t\tthis.setVariable(this.wikifyName,this.wikifyResult);\n\t\t\t\t// Refresh each of our child widgets\n\t\t\t\t$tw.utils.each(this.children,function(childWidget) {\n\t\t\t\t\tchildWidget.refreshSelf();\n\t\t\t\t});\n\t\t\t\treturn true;\n\t\t\t}\n\t\t}\n\t\t// Just refresh the children\n\t\treturn this.refreshChildren(changedTiddlers);\n\t}\n};\n\nexports.wikify = WikifyWidget;\n\n})();\n",
"title": "$:/core/modules/widgets/wikify.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/core/modules/wiki-bulkops.js": {
"text": "/*\\\ntitle: $:/core/modules/wiki-bulkops.js\ntype: application/javascript\nmodule-type: wikimethod\n\nBulk tiddler operations such as rename.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nRename a tiddler, and relink any tags or lists that reference it.\n*/\nexports.renameTiddler = function(fromTitle,toTitle) {\n\tvar self = this;\n\tfromTitle = (fromTitle || \"\").trim();\n\ttoTitle = (toTitle || \"\").trim();\n\tif(fromTitle && toTitle && fromTitle !== toTitle) {\n\t\t// Rename the tiddler itself\n\t\tvar tiddler = this.getTiddler(fromTitle);\n\t\tthis.addTiddler(new $tw.Tiddler(tiddler,{title: toTitle},this.getModificationFields()));\n\t\tthis.deleteTiddler(fromTitle);\n\t\t// Rename any tags or lists that reference it\n\t\tthis.each(function(tiddler,title) {\n\t\t\tvar tags = (tiddler.fields.tags || []).slice(0),\n\t\t\t\tlist = (tiddler.fields.list || []).slice(0),\n\t\t\t\tisModified = false;\n\t\t\t// Rename tags\n\t\t\t$tw.utils.each(tags,function (title,index) {\n\t\t\t\tif(title === fromTitle) {\n\t\t\t\t\ttags[index] = toTitle;\n\t\t\t\t\tisModified = true;\n\t\t\t\t}\n\t\t\t});\n\t\t\t// Rename lists\n\t\t\t$tw.utils.each(list,function (title,index) {\n\t\t\t\tif(title === fromTitle) {\n\t\t\t\t\tlist[index] = toTitle;\n\t\t\t\t\tisModified = true;\n\t\t\t\t}\n\t\t\t});\n\t\t\tif(isModified) {\n\t\t\t\tself.addTiddler(new $tw.Tiddler(tiddler,{tags: tags, list: list},self.getModificationFields()));\n\t\t\t}\n\t\t});\n\t}\n}\n\n})();\n",
"title": "$:/core/modules/wiki-bulkops.js",
"type": "application/javascript",
"module-type": "wikimethod"
},
"$:/core/modules/wiki.js": {
"text": "/*\\\ntitle: $:/core/modules/wiki.js\ntype: application/javascript\nmodule-type: wikimethod\n\nExtension methods for the $tw.Wiki object\n\nAdds the following properties to the wiki object:\n\n* `eventListeners` is a hashmap by type of arrays of listener functions\n* `changedTiddlers` is a hashmap describing changes to named tiddlers since wiki change events were last dispatched. Each entry is a hashmap containing two fields:\n\tmodified: true/false\n\tdeleted: true/false\n* `changeCount` is a hashmap by tiddler title containing a numerical index that starts at zero and is incremented each time a tiddler is created changed or deleted\n* `caches` is a hashmap by tiddler title containing a further hashmap of named cache objects. Caches are automatically cleared when a tiddler is modified or deleted\n* `globalCache` is a hashmap by cache name of cache objects that are cleared whenever any tiddler change occurs\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar widget = require(\"$:/core/modules/widgets/widget.js\");\n\nvar USER_NAME_TITLE = \"$:/status/UserName\";\n\n/*\nGet the value of a text reference. Text references can have any of these forms:\n\t<tiddlertitle>\n\t<tiddlertitle>!!<fieldname>\n\t!!<fieldname> - specifies a field of the current tiddlers\n\t<tiddlertitle>##<index>\n*/\nexports.getTextReference = function(textRef,defaultText,currTiddlerTitle) {\n\tvar tr = $tw.utils.parseTextReference(textRef),\n\t\ttitle = tr.title || currTiddlerTitle;\n\tif(tr.field) {\n\t\tvar tiddler = this.getTiddler(title);\n\t\tif(tr.field === \"title\") { // Special case so we can return the title of a non-existent tiddler\n\t\t\treturn title;\n\t\t} else if(tiddler && $tw.utils.hop(tiddler.fields,tr.field)) {\n\t\t\treturn tiddler.getFieldString(tr.field);\n\t\t} else {\n\t\t\treturn defaultText;\n\t\t}\n\t} else if(tr.index) {\n\t\treturn this.extractTiddlerDataItem(title,tr.index,defaultText);\n\t} else {\n\t\treturn this.getTiddlerText(title,defaultText);\n\t}\n};\n\nexports.setTextReference = function(textRef,value,currTiddlerTitle) {\n\tvar tr = $tw.utils.parseTextReference(textRef),\n\t\ttitle = tr.title || currTiddlerTitle;\n\tthis.setText(title,tr.field,tr.index,value);\n};\n\nexports.setText = function(title,field,index,value,options) {\n\toptions = options || {};\n\tvar creationFields = options.suppressTimestamp ? {} : this.getCreationFields(),\n\t\tmodificationFields = options.suppressTimestamp ? {} : this.getModificationFields();\n\t// Check if it is a reference to a tiddler field\n\tif(index) {\n\t\tvar data = this.getTiddlerData(title,Object.create(null));\n\t\tif(value !== undefined) {\n\t\t\tdata[index] = value;\n\t\t} else {\n\t\t\tdelete data[index];\n\t\t}\n\t\tthis.setTiddlerData(title,data,modificationFields);\n\t} else {\n\t\tvar tiddler = this.getTiddler(title),\n\t\t\tfields = {title: title};\n\t\tfields[field || \"text\"] = value;\n\t\tthis.addTiddler(new $tw.Tiddler(creationFields,tiddler,fields,modificationFields));\n\t}\n};\n\nexports.deleteTextReference = function(textRef,currTiddlerTitle) {\n\tvar tr = $tw.utils.parseTextReference(textRef),\n\t\ttitle,tiddler,fields;\n\t// Check if it is a reference to a tiddler\n\tif(tr.title && !tr.field) {\n\t\tthis.deleteTiddler(tr.title);\n\t// Else check for a field reference\n\t} else if(tr.field) {\n\t\ttitle = tr.title || currTiddlerTitle;\n\t\ttiddler = this.getTiddler(title);\n\t\tif(tiddler && $tw.utils.hop(tiddler.fields,tr.field)) {\n\t\t\tfields = Object.create(null);\n\t\t\tfields[tr.field] = undefined;\n\t\t\tthis.addTiddler(new $tw.Tiddler(tiddler,fields,this.getModificationFields()));\n\t\t}\n\t}\n};\n\nexports.addEventListener = function(type,listener) {\n\tthis.eventListeners = this.eventListeners || {};\n\tthis.eventListeners[type] = this.eventListeners[type] || [];\n\tthis.eventListeners[type].push(listener);\t\n};\n\nexports.removeEventListener = function(type,listener) {\n\tvar listeners = this.eventListeners[type];\n\tif(listeners) {\n\t\tvar p = listeners.indexOf(listener);\n\t\tif(p !== -1) {\n\t\t\tlisteners.splice(p,1);\n\t\t}\n\t}\n};\n\nexports.dispatchEvent = function(type /*, args */) {\n\tvar args = Array.prototype.slice.call(arguments,1),\n\t\tlisteners = this.eventListeners[type];\n\tif(listeners) {\n\t\tfor(var p=0; p<listeners.length; p++) {\n\t\t\tvar listener = listeners[p];\n\t\t\tlistener.apply(listener,args);\n\t\t}\n\t}\n};\n\n/*\nCauses a tiddler to be marked as changed, incrementing the change count, and triggers event handlers.\nThis method should be called after the changes it describes have been made to the wiki.tiddlers[] array.\n\ttitle: Title of tiddler\n\tisDeleted: defaults to false (meaning the tiddler has been created or modified),\n\t\ttrue if the tiddler has been deleted\n*/\nexports.enqueueTiddlerEvent = function(title,isDeleted) {\n\t// Record the touch in the list of changed tiddlers\n\tthis.changedTiddlers = this.changedTiddlers || Object.create(null);\n\tthis.changedTiddlers[title] = this.changedTiddlers[title] || Object.create(null);\n\tthis.changedTiddlers[title][isDeleted ? \"deleted\" : \"modified\"] = true;\n\t// Increment the change count\n\tthis.changeCount = this.changeCount || Object.create(null);\n\tif($tw.utils.hop(this.changeCount,title)) {\n\t\tthis.changeCount[title]++;\n\t} else {\n\t\tthis.changeCount[title] = 1;\n\t}\n\t// Trigger events\n\tthis.eventListeners = this.eventListeners || {};\n\tif(!this.eventsTriggered) {\n\t\tvar self = this;\n\t\t$tw.utils.nextTick(function() {\n\t\t\tvar changes = self.changedTiddlers;\n\t\t\tself.changedTiddlers = Object.create(null);\n\t\t\tself.eventsTriggered = false;\n\t\t\tif($tw.utils.count(changes) > 0) {\n\t\t\t\tself.dispatchEvent(\"change\",changes);\n\t\t\t}\n\t\t});\n\t\tthis.eventsTriggered = true;\n\t}\n};\n\nexports.getSizeOfTiddlerEventQueue = function() {\n\treturn $tw.utils.count(this.changedTiddlers);\n};\n\nexports.clearTiddlerEventQueue = function() {\n\tthis.changedTiddlers = Object.create(null);\n\tthis.changeCount = Object.create(null);\n};\n\nexports.getChangeCount = function(title) {\n\tthis.changeCount = this.changeCount || Object.create(null);\n\tif($tw.utils.hop(this.changeCount,title)) {\n\t\treturn this.changeCount[title];\n\t} else {\n\t\treturn 0;\n\t}\n};\n\n/*\nGenerate an unused title from the specified base\n*/\nexports.generateNewTitle = function(baseTitle,options) {\n\toptions = options || {};\n\tvar c = 0,\n\t\ttitle = baseTitle;\n\twhile(this.tiddlerExists(title) || this.isShadowTiddler(title) || this.findDraft(title)) {\n\t\ttitle = baseTitle + \n\t\t\t(options.prefix || \" \") + \n\t\t\t(++c);\n\t}\n\treturn title;\n};\n\nexports.isSystemTiddler = function(title) {\n\treturn title && title.indexOf(\"$:/\") === 0;\n};\n\nexports.isTemporaryTiddler = function(title) {\n\treturn title && title.indexOf(\"$:/temp/\") === 0;\n};\n\nexports.isImageTiddler = function(title) {\n\tvar tiddler = this.getTiddler(title);\n\tif(tiddler) {\t\t\n\t\tvar contentTypeInfo = $tw.config.contentTypeInfo[tiddler.fields.type || \"text/vnd.tiddlywiki\"];\n\t\treturn !!contentTypeInfo && contentTypeInfo.flags.indexOf(\"image\") !== -1;\n\t} else {\n\t\treturn null;\n\t}\n};\n\n/*\nLike addTiddler() except it will silently reject any plugin tiddlers that are older than the currently loaded version. Returns true if the tiddler was imported\n*/\nexports.importTiddler = function(tiddler) {\n\tvar existingTiddler = this.getTiddler(tiddler.fields.title);\n\t// Check if we're dealing with a plugin\n\tif(tiddler && tiddler.hasField(\"plugin-type\") && tiddler.hasField(\"version\") && existingTiddler && existingTiddler.hasField(\"plugin-type\") && existingTiddler.hasField(\"version\")) {\n\t\t// Reject the incoming plugin if it is older\n\t\tif(!$tw.utils.checkVersions(tiddler.fields.version,existingTiddler.fields.version)) {\n\t\t\treturn false;\n\t\t}\n\t}\n\t// Fall through to adding the tiddler\n\tthis.addTiddler(tiddler);\n\treturn true;\n};\n\n/*\nReturn a hashmap of the fields that should be set when a tiddler is created\n*/\nexports.getCreationFields = function() {\n\tvar fields = {\n\t\t\tcreated: new Date()\n\t\t},\n\t\tcreator = this.getTiddlerText(USER_NAME_TITLE);\n\tif(creator) {\n\t\tfields.creator = creator;\n\t}\n\treturn fields;\n};\n\n/*\nReturn a hashmap of the fields that should be set when a tiddler is modified\n*/\nexports.getModificationFields = function() {\n\tvar fields = Object.create(null),\n\t\tmodifier = this.getTiddlerText(USER_NAME_TITLE);\n\tfields.modified = new Date();\n\tif(modifier) {\n\t\tfields.modifier = modifier;\n\t}\n\treturn fields;\n};\n\n/*\nReturn a sorted array of tiddler titles. Options include:\nsortField: field to sort by\nexcludeTag: tag to exclude\nincludeSystem: whether to include system tiddlers (defaults to false)\n*/\nexports.getTiddlers = function(options) {\n\toptions = options || Object.create(null);\n\tvar self = this,\n\t\tsortField = options.sortField || \"title\",\n\t\ttiddlers = [], t, titles = [];\n\tthis.each(function(tiddler,title) {\n\t\tif(options.includeSystem || !self.isSystemTiddler(title)) {\n\t\t\tif(!options.excludeTag || !tiddler.hasTag(options.excludeTag)) {\n\t\t\t\ttiddlers.push(tiddler);\n\t\t\t}\n\t\t}\n\t});\n\ttiddlers.sort(function(a,b) {\n\t\tvar aa = a.fields[sortField].toLowerCase() || \"\",\n\t\t\tbb = b.fields[sortField].toLowerCase() || \"\";\n\t\tif(aa < bb) {\n\t\t\treturn -1;\n\t\t} else {\n\t\t\tif(aa > bb) {\n\t\t\t\treturn 1;\n\t\t\t} else {\n\t\t\t\treturn 0;\n\t\t\t}\n\t\t}\n\t});\n\tfor(t=0; t<tiddlers.length; t++) {\n\t\ttitles.push(tiddlers[t].fields.title);\n\t}\n\treturn titles;\n};\n\nexports.countTiddlers = function(excludeTag) {\n\tvar tiddlers = this.getTiddlers({excludeTag: excludeTag});\n\treturn $tw.utils.count(tiddlers);\n};\n\n/*\nReturns a function iterator(callback) that iterates through the specified titles, and invokes the callback with callback(tiddler,title)\n*/\nexports.makeTiddlerIterator = function(titles) {\n\tvar self = this;\n\tif(!$tw.utils.isArray(titles)) {\n\t\ttitles = Object.keys(titles);\n\t} else {\n\t\ttitles = titles.slice(0);\n\t}\n\treturn function(callback) {\n\t\ttitles.forEach(function(title) {\n\t\t\tcallback(self.getTiddler(title),title);\n\t\t});\n\t};\n};\n\n/*\nSort an array of tiddler titles by a specified field\n\ttitles: array of titles (sorted in place)\n\tsortField: name of field to sort by\n\tisDescending: true if the sort should be descending\n\tisCaseSensitive: true if the sort should consider upper and lower case letters to be different\n*/\nexports.sortTiddlers = function(titles,sortField,isDescending,isCaseSensitive,isNumeric) {\n\tvar self = this;\n\ttitles.sort(function(a,b) {\n\t\tvar x,y,\n\t\t\tcompareNumbers = function(x,y) {\n\t\t\t\tvar result = \n\t\t\t\t\tisNaN(x) && !isNaN(y) ? (isDescending ? -1 : 1) :\n\t\t\t\t\t!isNaN(x) && isNaN(y) ? (isDescending ? 1 : -1) :\n\t\t\t\t\t (isDescending ? y - x : x - y);\n\t\t\t\treturn result;\n\t\t\t};\n\t\tif(sortField !== \"title\") {\n\t\t\tvar tiddlerA = self.getTiddler(a),\n\t\t\t\ttiddlerB = self.getTiddler(b);\n\t\t\tif(tiddlerA) {\n\t\t\t\ta = tiddlerA.fields[sortField] || \"\";\n\t\t\t} else {\n\t\t\t\ta = \"\";\n\t\t\t}\n\t\t\tif(tiddlerB) {\n\t\t\t\tb = tiddlerB.fields[sortField] || \"\";\n\t\t\t} else {\n\t\t\t\tb = \"\";\n\t\t\t}\n\t\t}\n\t\tx = Number(a);\n\t\ty = Number(b);\n\t\tif(isNumeric && (!isNaN(x) || !isNaN(y))) {\n\t\t\treturn compareNumbers(x,y);\n\t\t} else if($tw.utils.isDate(a) && $tw.utils.isDate(b)) {\n\t\t\treturn isDescending ? b - a : a - b;\n\t\t} else {\n\t\t\ta = String(a);\n\t\t\tb = String(b);\n\t\t\tif(!isCaseSensitive) {\n\t\t\t\ta = a.toLowerCase();\n\t\t\t\tb = b.toLowerCase();\n\t\t\t}\n\t\t\treturn isDescending ? b.localeCompare(a) : a.localeCompare(b);\n\t\t}\n\t});\n};\n\n/*\nFor every tiddler invoke a callback(title,tiddler) with `this` set to the wiki object. Options include:\nsortField: field to sort by\nexcludeTag: tag to exclude\nincludeSystem: whether to include system tiddlers (defaults to false)\n*/\nexports.forEachTiddler = function(/* [options,]callback */) {\n\tvar arg = 0,\n\t\toptions = arguments.length >= 2 ? arguments[arg++] : {},\n\t\tcallback = arguments[arg++],\n\t\ttitles = this.getTiddlers(options),\n\t\tt, tiddler;\n\tfor(t=0; t<titles.length; t++) {\n\t\ttiddler = this.getTiddler(titles[t]);\n\t\tif(tiddler) {\n\t\t\tcallback.call(this,tiddler.fields.title,tiddler);\n\t\t}\n\t}\n};\n\n/*\nReturn an array of tiddler titles that are directly linked from the specified tiddler\n*/\nexports.getTiddlerLinks = function(title) {\n\tvar self = this;\n\t// We'll cache the links so they only get computed if the tiddler changes\n\treturn this.getCacheForTiddler(title,\"links\",function() {\n\t\t// Parse the tiddler\n\t\tvar parser = self.parseTiddler(title);\n\t\t// Count up the links\n\t\tvar links = [],\n\t\t\tcheckParseTree = function(parseTree) {\n\t\t\t\tfor(var t=0; t<parseTree.length; t++) {\n\t\t\t\t\tvar parseTreeNode = parseTree[t];\n\t\t\t\t\tif(parseTreeNode.type === \"link\" && parseTreeNode.attributes.to && parseTreeNode.attributes.to.type === \"string\") {\n\t\t\t\t\t\tvar value = parseTreeNode.attributes.to.value;\n\t\t\t\t\t\tif(links.indexOf(value) === -1) {\n\t\t\t\t\t\t\tlinks.push(value);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t\tif(parseTreeNode.children) {\n\t\t\t\t\t\tcheckParseTree(parseTreeNode.children);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t};\n\t\tif(parser) {\n\t\t\tcheckParseTree(parser.tree);\n\t\t}\n\t\treturn links;\n\t});\n};\n\n/*\nReturn an array of tiddler titles that link to the specified tiddler\n*/\nexports.getTiddlerBacklinks = function(targetTitle) {\n\tvar self = this,\n\t\tbacklinks = [];\n\tthis.forEachTiddler(function(title,tiddler) {\n\t\tvar links = self.getTiddlerLinks(title);\n\t\tif(links.indexOf(targetTitle) !== -1) {\n\t\t\tbacklinks.push(title);\n\t\t}\n\t});\n\treturn backlinks;\n};\n\n/*\nReturn a hashmap of tiddler titles that are referenced but not defined. Each value is the number of times the missing tiddler is referenced\n*/\nexports.getMissingTitles = function() {\n\tvar self = this,\n\t\tmissing = [];\n// We should cache the missing tiddler list, even if we recreate it every time any tiddler is modified\n\tthis.forEachTiddler(function(title,tiddler) {\n\t\tvar links = self.getTiddlerLinks(title);\n\t\t$tw.utils.each(links,function(link) {\n\t\t\tif((!self.tiddlerExists(link) && !self.isShadowTiddler(link)) && missing.indexOf(link) === -1) {\n\t\t\t\tmissing.push(link);\n\t\t\t}\n\t\t});\n\t});\n\treturn missing;\n};\n\nexports.getOrphanTitles = function() {\n\tvar self = this,\n\t\torphans = this.getTiddlers();\n\tthis.forEachTiddler(function(title,tiddler) {\n\t\tvar links = self.getTiddlerLinks(title);\n\t\t$tw.utils.each(links,function(link) {\n\t\t\tvar p = orphans.indexOf(link);\n\t\t\tif(p !== -1) {\n\t\t\t\torphans.splice(p,1);\n\t\t\t}\n\t\t});\n\t});\n\treturn orphans; // Todo\n};\n\n/*\nRetrieves a list of the tiddler titles that are tagged with a given tag\n*/\nexports.getTiddlersWithTag = function(tag) {\n\tvar self = this;\n\treturn this.getGlobalCache(\"taglist-\" + tag,function() {\n\t\tvar tagmap = self.getTagMap();\n\t\treturn self.sortByList(tagmap[tag],tag);\n\t});\n};\n\n/*\nGet a hashmap by tag of arrays of tiddler titles\n*/\nexports.getTagMap = function() {\n\tvar self = this;\n\treturn this.getGlobalCache(\"tagmap\",function() {\n\t\tvar tags = Object.create(null),\n\t\t\tstoreTags = function(tagArray,title) {\n\t\t\t\tif(tagArray) {\n\t\t\t\t\tfor(var index=0; index<tagArray.length; index++) {\n\t\t\t\t\t\tvar tag = tagArray[index];\n\t\t\t\t\t\tif($tw.utils.hop(tags,tag)) {\n\t\t\t\t\t\t\ttags[tag].push(title);\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ttags[tag] = [title];\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t},\n\t\t\ttitle, tiddler;\n\t\t// Collect up all the tags\n\t\tself.eachShadow(function(tiddler,title) {\n\t\t\tif(!self.tiddlerExists(title)) {\n\t\t\t\ttiddler = self.getTiddler(title);\n\t\t\t\tstoreTags(tiddler.fields.tags,title);\n\t\t\t}\n\t\t});\n\t\tself.each(function(tiddler,title) {\n\t\t\tstoreTags(tiddler.fields.tags,title);\n\t\t});\n\t\treturn tags;\n\t});\n};\n\n/*\nLookup a given tiddler and return a list of all the tiddlers that include it in the specified list field\n*/\nexports.findListingsOfTiddler = function(targetTitle,fieldName) {\n\tfieldName = fieldName || \"list\";\n\tvar titles = [];\n\tthis.each(function(tiddler,title) {\n\t\tvar list = $tw.utils.parseStringArray(tiddler.fields[fieldName]);\n\t\tif(list && list.indexOf(targetTitle) !== -1) {\n\t\t\ttitles.push(title);\n\t\t}\n\t});\n\treturn titles;\n};\n\n/*\nSorts an array of tiddler titles according to an ordered list\n*/\nexports.sortByList = function(array,listTitle) {\n\tvar list = this.getTiddlerList(listTitle);\n\tif(!array || array.length === 0) {\n\t\treturn [];\n\t} else {\n\t\tvar titles = [], t, title;\n\t\t// First place any entries that are present in the list\n\t\tfor(t=0; t<list.length; t++) {\n\t\t\ttitle = list[t];\n\t\t\tif(array.indexOf(title) !== -1) {\n\t\t\t\ttitles.push(title);\n\t\t\t}\n\t\t}\n\t\t// Then place any remaining entries\n\t\tfor(t=0; t<array.length; t++) {\n\t\t\ttitle = array[t];\n\t\t\tif(list.indexOf(title) === -1) {\n\t\t\t\ttitles.push(title);\n\t\t\t}\n\t\t}\n\t\t// Finally obey the list-before and list-after fields of each tiddler in turn\n\t\tvar sortedTitles = titles.slice(0);\n\t\tfor(t=0; t<sortedTitles.length; t++) {\n\t\t\ttitle = sortedTitles[t];\n\t\t\tvar currPos = titles.indexOf(title),\n\t\t\t\tnewPos = -1,\n\t\t\t\ttiddler = this.getTiddler(title);\n\t\t\tif(tiddler) {\n\t\t\t\tvar beforeTitle = tiddler.fields[\"list-before\"],\n\t\t\t\t\tafterTitle = tiddler.fields[\"list-after\"];\n\t\t\t\tif(beforeTitle === \"\") {\n\t\t\t\t\tnewPos = 0;\n\t\t\t\t} else if(beforeTitle) {\n\t\t\t\t\tnewPos = titles.indexOf(beforeTitle);\n\t\t\t\t} else if(afterTitle) {\n\t\t\t\t\tnewPos = titles.indexOf(afterTitle);\n\t\t\t\t\tif(newPos >= 0) {\n\t\t\t\t\t\t++newPos;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tif(newPos === -1) {\n\t\t\t\t\tnewPos = currPos;\n\t\t\t\t}\n\t\t\t\tif(newPos !== currPos) {\n\t\t\t\t\ttitles.splice(currPos,1);\n\t\t\t\t\tif(newPos >= currPos) {\n\t\t\t\t\t\tnewPos--;\n\t\t\t\t\t}\n\t\t\t\t\ttitles.splice(newPos,0,title);\n\t\t\t\t}\n\t\t\t}\n\n\t\t}\n\t\treturn titles;\n\t}\n};\n\nexports.getSubTiddler = function(title,subTiddlerTitle) {\n\tvar bundleInfo = this.getPluginInfo(title) || this.getTiddlerDataCached(title);\n\tif(bundleInfo && bundleInfo.tiddlers) {\n\t\tvar subTiddler = bundleInfo.tiddlers[subTiddlerTitle];\n\t\tif(subTiddler) {\n\t\t\treturn new $tw.Tiddler(subTiddler);\n\t\t}\n\t}\n\treturn null;\n};\n\n/*\nRetrieve a tiddler as a JSON string of the fields\n*/\nexports.getTiddlerAsJson = function(title) {\n\tvar tiddler = this.getTiddler(title);\n\tif(tiddler) {\n\t\tvar fields = Object.create(null);\n\t\t$tw.utils.each(tiddler.fields,function(value,name) {\n\t\t\tfields[name] = tiddler.getFieldString(name);\n\t\t});\n\t\treturn JSON.stringify(fields);\n\t} else {\n\t\treturn JSON.stringify({title: title});\n\t}\n};\n\n/*\nGet the content of a tiddler as a JavaScript object. How this is done depends on the type of the tiddler:\n\napplication/json: the tiddler JSON is parsed into an object\napplication/x-tiddler-dictionary: the tiddler is parsed as sequence of name:value pairs\n\nOther types currently just return null.\n\ntitleOrTiddler: string tiddler title or a tiddler object\ndefaultData: default data to be returned if the tiddler is missing or doesn't contain data\n\nNote that the same value is returned for repeated calls for the same tiddler data. The value is frozen to prevent modification; otherwise modifications would be visible to all callers\n*/\nexports.getTiddlerDataCached = function(titleOrTiddler,defaultData) {\n\tvar self = this,\n\t\ttiddler = titleOrTiddler;\n\tif(!(tiddler instanceof $tw.Tiddler)) {\n\t\ttiddler = this.getTiddler(tiddler);\t\n\t}\n\tif(tiddler) {\n\t\treturn this.getCacheForTiddler(tiddler.fields.title,\"data\",function() {\n\t\t\t// Return the frozen value\n\t\t\tvar value = self.getTiddlerData(tiddler.fields.title,defaultData);\n\t\t\t$tw.utils.deepFreeze(value);\n\t\t\treturn value;\n\t\t});\n\t} else {\n\t\treturn defaultData;\n\t}\n};\n\n/*\nAlternative, uncached version of getTiddlerDataCached(). The return value can be mutated freely and reused\n*/\nexports.getTiddlerData = function(titleOrTiddler,defaultData) {\n\tvar tiddler = titleOrTiddler,\n\t\tdata;\n\tif(!(tiddler instanceof $tw.Tiddler)) {\n\t\ttiddler = this.getTiddler(tiddler);\t\n\t}\n\tif(tiddler && tiddler.fields.text) {\n\t\tswitch(tiddler.fields.type) {\n\t\t\tcase \"application/json\":\n\t\t\t\t// JSON tiddler\n\t\t\t\ttry {\n\t\t\t\t\tdata = JSON.parse(tiddler.fields.text);\n\t\t\t\t} catch(ex) {\n\t\t\t\t\treturn defaultData;\n\t\t\t\t}\n\t\t\t\treturn data;\n\t\t\tcase \"application/x-tiddler-dictionary\":\n\t\t\t\treturn $tw.utils.parseFields(tiddler.fields.text);\n\t\t}\n\t}\n\treturn defaultData;\n};\n\n/*\nExtract an indexed field from within a data tiddler\n*/\nexports.extractTiddlerDataItem = function(titleOrTiddler,index,defaultText) {\n\tvar data = this.getTiddlerData(titleOrTiddler,Object.create(null)),\n\t\ttext;\n\tif(data && $tw.utils.hop(data,index)) {\n\t\ttext = data[index];\n\t}\n\tif(typeof text === \"string\" || typeof text === \"number\") {\n\t\treturn text.toString();\n\t} else {\n\t\treturn defaultText;\n\t}\n};\n\n/*\nSet a tiddlers content to a JavaScript object. Currently this is done by setting the tiddler's type to \"application/json\" and setting the text to the JSON text of the data.\ntitle: title of tiddler\ndata: object that can be serialised to JSON\nfields: optional hashmap of additional tiddler fields to be set\n*/\nexports.setTiddlerData = function(title,data,fields) {\n\tvar existingTiddler = this.getTiddler(title),\n\t\tnewFields = {\n\t\t\ttitle: title\n\t};\n\tif(existingTiddler && existingTiddler.fields.type === \"application/x-tiddler-dictionary\") {\n\t\tnewFields.text = $tw.utils.makeTiddlerDictionary(data);\n\t} else {\n\t\tnewFields.type = \"application/json\";\n\t\tnewFields.text = JSON.stringify(data,null,$tw.config.preferences.jsonSpaces);\n\t}\n\tthis.addTiddler(new $tw.Tiddler(this.getCreationFields(),existingTiddler,fields,newFields,this.getModificationFields()));\n};\n\n/*\nReturn the content of a tiddler as an array containing each line\n*/\nexports.getTiddlerList = function(title,field,index) {\n\tif(index) {\n\t\treturn $tw.utils.parseStringArray(this.extractTiddlerDataItem(title,index,\"\"));\n\t}\n\tfield = field || \"list\";\n\tvar tiddler = this.getTiddler(title);\n\tif(tiddler) {\n\t\treturn ($tw.utils.parseStringArray(tiddler.fields[field]) || []).slice(0);\n\t}\n\treturn [];\n};\n\n// Return a named global cache object. Global cache objects are cleared whenever a tiddler change occurs\nexports.getGlobalCache = function(cacheName,initializer) {\n\tthis.globalCache = this.globalCache || Object.create(null);\n\tif($tw.utils.hop(this.globalCache,cacheName)) {\n\t\treturn this.globalCache[cacheName];\n\t} else {\n\t\tthis.globalCache[cacheName] = initializer();\n\t\treturn this.globalCache[cacheName];\n\t}\n};\n\nexports.clearGlobalCache = function() {\n\tthis.globalCache = Object.create(null);\n};\n\n// Return the named cache object for a tiddler. If the cache doesn't exist then the initializer function is invoked to create it\nexports.getCacheForTiddler = function(title,cacheName,initializer) {\n\tthis.caches = this.caches || Object.create(null);\n\tvar caches = this.caches[title];\n\tif(caches && caches[cacheName]) {\n\t\treturn caches[cacheName];\n\t} else {\n\t\tif(!caches) {\n\t\t\tcaches = Object.create(null);\n\t\t\tthis.caches[title] = caches;\n\t\t}\n\t\tcaches[cacheName] = initializer();\n\t\treturn caches[cacheName];\n\t}\n};\n\n// Clear all caches associated with a particular tiddler, or, if the title is null, clear all the caches for all the tiddlers\nexports.clearCache = function(title) {\n\tif(title) {\n\t\tthis.caches = this.caches || Object.create(null);\n\t\tif($tw.utils.hop(this.caches,title)) {\n\t\t\tdelete this.caches[title];\n\t\t}\n\t} else {\n\t\tthis.caches = Object.create(null);\n\t}\n};\n\nexports.initParsers = function(moduleType) {\n\t// Install the parser modules\n\t$tw.Wiki.parsers = {};\n\tvar self = this;\n\t$tw.modules.forEachModuleOfType(\"parser\",function(title,module) {\n\t\tfor(var f in module) {\n\t\t\tif($tw.utils.hop(module,f)) {\n\t\t\t\t$tw.Wiki.parsers[f] = module[f]; // Store the parser class\n\t\t\t}\n\t\t}\n\t});\n};\n\n/*\nParse a block of text of a specified MIME type\n\ttype: content type of text to be parsed\n\ttext: text\n\toptions: see below\nOptions include:\n\tparseAsInline: if true, the text of the tiddler will be parsed as an inline run\n\t_canonical_uri: optional string of the canonical URI of this content\n*/\nexports.parseText = function(type,text,options) {\n\ttext = text || \"\";\n\toptions = options || {};\n\t// Select a parser\n\tvar Parser = $tw.Wiki.parsers[type];\n\tif(!Parser && $tw.utils.getFileExtensionInfo(type)) {\n\t\tParser = $tw.Wiki.parsers[$tw.utils.getFileExtensionInfo(type).type];\n\t}\n\tif(!Parser) {\n\t\tParser = $tw.Wiki.parsers[options.defaultType || \"text/vnd.tiddlywiki\"];\n\t}\n\tif(!Parser) {\n\t\treturn null;\n\t}\n\t// Return the parser instance\n\treturn new Parser(type,text,{\n\t\tparseAsInline: options.parseAsInline,\n\t\twiki: this,\n\t\t_canonical_uri: options._canonical_uri\n\t});\n};\n\n/*\nParse a tiddler according to its MIME type\n*/\nexports.parseTiddler = function(title,options) {\n\toptions = $tw.utils.extend({},options);\n\tvar cacheType = options.parseAsInline ? \"inlineParseTree\" : \"blockParseTree\",\n\t\ttiddler = this.getTiddler(title),\n\t\tself = this;\n\treturn tiddler ? this.getCacheForTiddler(title,cacheType,function() {\n\t\t\tif(tiddler.hasField(\"_canonical_uri\")) {\n\t\t\t\toptions._canonical_uri = tiddler.fields._canonical_uri;\n\t\t\t}\n\t\t\treturn self.parseText(tiddler.fields.type,tiddler.fields.text,options);\n\t\t}) : null;\n};\n\nexports.parseTextReference = function(title,field,index,options) {\n\tvar tiddler,text;\n\tif(options.subTiddler) {\n\t\ttiddler = this.getSubTiddler(title,options.subTiddler);\n\t} else {\n\t\ttiddler = this.getTiddler(title);\n\t\tif(field === \"text\" || (!field && !index)) {\n\t\t\tthis.getTiddlerText(title); // Force the tiddler to be lazily loaded\n\t\t\treturn this.parseTiddler(title,options);\n\t\t}\n\t}\n\tif(field === \"text\" || (!field && !index)) {\n\t\tif(tiddler && tiddler.fields) {\n\t\t\treturn this.parseText(tiddler.fields.type || \"text/vnd.tiddlywiki\",tiddler.fields.text,options);\t\t\t\n\t\t} else {\n\t\t\treturn null;\n\t\t}\n\t} else if(field) {\n\t\tif(field === \"title\") {\n\t\t\ttext = title;\n\t\t} else {\n\t\t\tif(!tiddler || !tiddler.hasField(field)) {\n\t\t\t\treturn null;\n\t\t\t}\n\t\t\ttext = tiddler.fields[field];\n\t\t}\n\t\treturn this.parseText(\"text/vnd.tiddlywiki\",text.toString(),options);\n\t} else if(index) {\n\t\tthis.getTiddlerText(title); // Force the tiddler to be lazily loaded\n\t\ttext = this.extractTiddlerDataItem(tiddler,index,undefined);\n\t\tif(text === undefined) {\n\t\t\treturn null;\n\t\t}\n\t\treturn this.parseText(\"text/vnd.tiddlywiki\",text,options);\n\t}\n};\n\n/*\nMake a widget tree for a parse tree\nparser: parser object\noptions: see below\nOptions include:\ndocument: optional document to use\nvariables: hashmap of variables to set\nparentWidget: optional parent widget for the root node\n*/\nexports.makeWidget = function(parser,options) {\n\toptions = options || {};\n\tvar widgetNode = {\n\t\t\ttype: \"widget\",\n\t\t\tchildren: []\n\t\t},\n\t\tcurrWidgetNode = widgetNode;\n\t// Create set variable widgets for each variable\n\t$tw.utils.each(options.variables,function(value,name) {\n\t\tvar setVariableWidget = {\n\t\t\ttype: \"set\",\n\t\t\tattributes: {\n\t\t\t\tname: {type: \"string\", value: name},\n\t\t\t\tvalue: {type: \"string\", value: value}\n\t\t\t},\n\t\t\tchildren: []\n\t\t};\n\t\tcurrWidgetNode.children = [setVariableWidget];\n\t\tcurrWidgetNode = setVariableWidget;\n\t});\n\t// Add in the supplied parse tree nodes\n\tcurrWidgetNode.children = parser ? parser.tree : [];\n\t// Create the widget\n\treturn new widget.widget(widgetNode,{\n\t\twiki: this,\n\t\tdocument: options.document || $tw.fakeDocument,\n\t\tparentWidget: options.parentWidget\n\t});\n};\n\n/*\nMake a widget tree for transclusion\ntitle: target tiddler title\noptions: as for wiki.makeWidget() plus:\noptions.field: optional field to transclude (defaults to \"text\")\noptions.mode: transclusion mode \"inline\" or \"block\"\noptions.children: optional array of children for the transclude widget\n*/\nexports.makeTranscludeWidget = function(title,options) {\n\toptions = options || {};\n\tvar parseTree = {tree: [{\n\t\t\ttype: \"element\",\n\t\t\ttag: \"div\",\n\t\t\tchildren: [{\n\t\t\t\ttype: \"transclude\",\n\t\t\t\tattributes: {\n\t\t\t\t\ttiddler: {\n\t\t\t\t\t\tname: \"tiddler\",\n\t\t\t\t\t\ttype: \"string\",\n\t\t\t\t\t\tvalue: title}},\n\t\t\t\tisBlock: !options.parseAsInline}]}\n\t]};\n\tif(options.field) {\n\t\tparseTree.tree[0].children[0].attributes.field = {type: \"string\", value: options.field};\n\t}\n\tif(options.mode) {\n\t\tparseTree.tree[0].children[0].attributes.mode = {type: \"string\", value: options.mode};\n\t}\n\tif(options.children) {\n\t\tparseTree.tree[0].children[0].children = options.children;\n\t}\n\treturn $tw.wiki.makeWidget(parseTree,options);\n};\n\n/*\nParse text in a specified format and render it into another format\n\toutputType: content type for the output\n\ttextType: content type of the input text\n\ttext: input text\n\toptions: see below\nOptions include:\nvariables: hashmap of variables to set\nparentWidget: optional parent widget for the root node\n*/\nexports.renderText = function(outputType,textType,text,options) {\n\toptions = options || {};\n\tvar parser = this.parseText(textType,text,options),\n\t\twidgetNode = this.makeWidget(parser,options);\n\tvar container = $tw.fakeDocument.createElement(\"div\");\n\twidgetNode.render(container,null);\n\treturn outputType === \"text/html\" ? container.innerHTML : container.textContent;\n};\n\n/*\nParse text from a tiddler and render it into another format\n\toutputType: content type for the output\n\ttitle: title of the tiddler to be rendered\n\toptions: see below\nOptions include:\nvariables: hashmap of variables to set\nparentWidget: optional parent widget for the root node\n*/\nexports.renderTiddler = function(outputType,title,options) {\n\toptions = options || {};\n\tvar parser = this.parseTiddler(title,options),\n\t\twidgetNode = this.makeWidget(parser,options);\n\tvar container = $tw.fakeDocument.createElement(\"div\");\n\twidgetNode.render(container,null);\n\treturn outputType === \"text/html\" ? container.innerHTML : (outputType === \"text/plain-formatted\" ? container.formattedTextContent : container.textContent);\n};\n\n/*\nReturn an array of tiddler titles that match a search string\n\ttext: The text string to search for\n\toptions: see below\nOptions available:\n\tsource: an iterator function for the source tiddlers, called source(iterator), where iterator is called as iterator(tiddler,title)\n\texclude: An array of tiddler titles to exclude from the search\n\tinvert: If true returns tiddlers that do not contain the specified string\n\tcaseSensitive: If true forces a case sensitive search\n\tliteral: If true, searches for literal string, rather than separate search terms\n\tfield: If specified, restricts the search to the specified field\n*/\nexports.search = function(text,options) {\n\toptions = options || {};\n\tvar self = this,\n\t\tt,\n\t\tinvert = !!options.invert;\n\t// Convert the search string into a regexp for each term\n\tvar terms, searchTermsRegExps,\n\t\tflags = options.caseSensitive ? \"\" : \"i\";\n\tif(options.literal) {\n\t\tif(text.length === 0) {\n\t\t\tsearchTermsRegExps = null;\n\t\t} else {\n\t\t\tsearchTermsRegExps = [new RegExp(\"(\" + $tw.utils.escapeRegExp(text) + \")\",flags)];\n\t\t}\n\t} else {\n\t\tterms = text.split(/ +/);\n\t\tif(terms.length === 1 && terms[0] === \"\") {\n\t\t\tsearchTermsRegExps = null;\n\t\t} else {\n\t\t\tsearchTermsRegExps = [];\n\t\t\tfor(t=0; t<terms.length; t++) {\n\t\t\t\tsearchTermsRegExps.push(new RegExp(\"(\" + $tw.utils.escapeRegExp(terms[t]) + \")\",flags));\n\t\t\t}\n\t\t}\n\t}\n\t// Function to check a given tiddler for the search term\n\tvar searchTiddler = function(title) {\n\t\tif(!searchTermsRegExps) {\n\t\t\treturn true;\n\t\t}\n\t\tvar tiddler = self.getTiddler(title);\n\t\tif(!tiddler) {\n\t\t\ttiddler = new $tw.Tiddler({title: title, text: \"\", type: \"text/vnd.tiddlywiki\"});\n\t\t}\n\t\tvar contentTypeInfo = $tw.config.contentTypeInfo[tiddler.fields.type] || $tw.config.contentTypeInfo[\"text/vnd.tiddlywiki\"],\n\t\t\tmatch;\n\t\tfor(var t=0; t<searchTermsRegExps.length; t++) {\n\t\t\tmatch = false;\n\t\t\tif(options.field) {\n\t\t\t\tmatch = searchTermsRegExps[t].test(tiddler.getFieldString(options.field));\n\t\t\t} else {\n\t\t\t\t// Search title, tags and body\n\t\t\t\tif(contentTypeInfo.encoding === \"utf8\") {\n\t\t\t\t\tmatch = match || searchTermsRegExps[t].test(tiddler.fields.text);\n\t\t\t\t}\n\t\t\t\tvar tags = tiddler.fields.tags ? tiddler.fields.tags.join(\"\\0\") : \"\";\n\t\t\t\tmatch = match || searchTermsRegExps[t].test(tags) || searchTermsRegExps[t].test(tiddler.fields.title);\n\t\t\t}\n\t\t\tif(!match) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t};\n\t// Loop through all the tiddlers doing the search\n\tvar results = [],\n\t\tsource = options.source || this.each;\n\tsource(function(tiddler,title) {\n\t\tif(searchTiddler(title) !== options.invert) {\n\t\t\tresults.push(title);\n\t\t}\n\t});\n\t// Remove any of the results we have to exclude\n\tif(options.exclude) {\n\t\tfor(t=0; t<options.exclude.length; t++) {\n\t\t\tvar p = results.indexOf(options.exclude[t]);\n\t\t\tif(p !== -1) {\n\t\t\t\tresults.splice(p,1);\n\t\t\t}\n\t\t}\n\t}\n\treturn results;\n};\n\n/*\nTrigger a load for a tiddler if it is skinny. Returns the text, or undefined if the tiddler is missing, null if the tiddler is being lazily loaded.\n*/\nexports.getTiddlerText = function(title,defaultText) {\n\tvar tiddler = this.getTiddler(title);\n\t// Return undefined if the tiddler isn't found\n\tif(!tiddler) {\n\t\treturn defaultText;\n\t}\n\tif(tiddler.fields.text !== undefined) {\n\t\t// Just return the text if we've got it\n\t\treturn tiddler.fields.text;\n\t} else {\n\t\t// Tell any listeners about the need to lazily load this tiddler\n\t\tthis.dispatchEvent(\"lazyLoad\",title);\n\t\t// Indicate that the text is being loaded\n\t\treturn null;\n\t}\n};\n\n/*\nRead an array of browser File objects, invoking callback(tiddlerFieldsArray) once they're all read\n*/\nexports.readFiles = function(files,callback) {\n\tvar result = [],\n\t\toutstanding = files.length;\n\tfor(var f=0; f<files.length; f++) {\n\t\tthis.readFile(files[f],function(tiddlerFieldsArray) {\n\t\t\tresult.push.apply(result,tiddlerFieldsArray);\n\t\t\tif(--outstanding === 0) {\n\t\t\t\tcallback(result);\n\t\t\t}\n\t\t});\n\t}\n\treturn files.length;\n};\n\n/*\nRead a browser File object, invoking callback(tiddlerFieldsArray) with an array of tiddler fields objects\n*/\nexports.readFile = function(file,callback) {\n\t// Get the type, falling back to the filename extension\n\tvar self = this,\n\t\ttype = file.type;\n\tif(type === \"\" || !type) {\n\t\tvar dotPos = file.name.lastIndexOf(\".\");\n\t\tif(dotPos !== -1) {\n\t\t\tvar fileExtensionInfo = $tw.utils.getFileExtensionInfo(file.name.substr(dotPos));\n\t\t\tif(fileExtensionInfo) {\n\t\t\t\ttype = fileExtensionInfo.type;\n\t\t\t}\n\t\t}\n\t}\n\t// Figure out if we're reading a binary file\n\tvar contentTypeInfo = $tw.config.contentTypeInfo[type],\n\t\tisBinary = contentTypeInfo ? contentTypeInfo.encoding === \"base64\" : false;\n\t// Log some debugging information\n\tif($tw.log.IMPORT) {\n\t\tconsole.log(\"Importing file '\" + file.name + \"', type: '\" + type + \"', isBinary: \" + isBinary);\n\t}\n\t// Create the FileReader\n\tvar reader = new FileReader();\n\t// Onload\n\treader.onload = function(event) {\n\t\t// Deserialise the file contents\n\t\tvar text = event.target.result,\n\t\t\ttiddlerFields = {title: file.name || \"Untitled\", type: type};\n\t\t// Are we binary?\n\t\tif(isBinary) {\n\t\t\t// The base64 section starts after the first comma in the data URI\n\t\t\tvar commaPos = text.indexOf(\",\");\n\t\t\tif(commaPos !== -1) {\n\t\t\t\ttiddlerFields.text = text.substr(commaPos+1);\n\t\t\t\tcallback([tiddlerFields]);\n\t\t\t}\n\t\t} else {\n\t\t\t// Check whether this is an encrypted TiddlyWiki file\n\t\t\tvar encryptedJson = $tw.utils.extractEncryptedStoreArea(text);\n\t\t\tif(encryptedJson) {\n\t\t\t\t// If so, attempt to decrypt it with the current password\n\t\t\t\t$tw.utils.decryptStoreAreaInteractive(encryptedJson,function(tiddlers) {\n\t\t\t\t\tcallback(tiddlers);\n\t\t\t\t});\n\t\t\t} else {\n\t\t\t\t// Otherwise, just try to deserialise any tiddlers in the file\n\t\t\t\tcallback(self.deserializeTiddlers(type,text,tiddlerFields));\n\t\t\t}\n\t\t}\n\t};\n\t// Kick off the read\n\tif(isBinary) {\n\t\treader.readAsDataURL(file);\n\t} else {\n\t\treader.readAsText(file);\n\t}\n};\n\n/*\nFind any existing draft of a specified tiddler\n*/\nexports.findDraft = function(targetTitle) {\n\tvar draftTitle = undefined;\n\tthis.forEachTiddler({includeSystem: true},function(title,tiddler) {\n\t\tif(tiddler.fields[\"draft.title\"] && tiddler.fields[\"draft.of\"] === targetTitle) {\n\t\t\tdraftTitle = title;\n\t\t}\n\t});\n\treturn draftTitle;\n}\n\n/*\nCheck whether the specified draft tiddler has been modified.\nIf the original tiddler doesn't exist, create a vanilla tiddler variable,\nto check if additional fields have been added.\n*/\nexports.isDraftModified = function(title) {\n\tvar tiddler = this.getTiddler(title);\n\tif(!tiddler.isDraft()) {\n\t\treturn false;\n\t}\n\tvar ignoredFields = [\"created\", \"modified\", \"title\", \"draft.title\", \"draft.of\"],\n\t\torigTiddler = this.getTiddler(tiddler.fields[\"draft.of\"]) || new $tw.Tiddler({text:\"\", tags:[]}),\n\t\ttitleModified = tiddler.fields[\"draft.title\"] !== tiddler.fields[\"draft.of\"];\n\treturn titleModified || !tiddler.isEqual(origTiddler,ignoredFields);\n};\n\n/*\nAdd a new record to the top of the history stack\ntitle: a title string or an array of title strings\nfromPageRect: page coordinates of the origin of the navigation\nhistoryTitle: title of history tiddler (defaults to $:/HistoryList)\n*/\nexports.addToHistory = function(title,fromPageRect,historyTitle) {\n\tvar story = new $tw.Story({wiki: this, historyTitle: historyTitle});\n\tstory.addToHistory(title,fromPageRect);\n};\n\n/*\nInvoke the available upgrader modules\ntitles: array of tiddler titles to be processed\ntiddlers: hashmap by title of tiddler fields of pending import tiddlers. These can be modified by the upgraders. An entry with no fields indicates a tiddler that was pending import has been suppressed. When entries are added to the pending import the tiddlers hashmap may have entries that are not present in the titles array\nReturns a hashmap of messages keyed by tiddler title.\n*/\nexports.invokeUpgraders = function(titles,tiddlers) {\n\t// Collect up the available upgrader modules\n\tvar self = this;\n\tif(!this.upgraderModules) {\n\t\tthis.upgraderModules = [];\n\t\t$tw.modules.forEachModuleOfType(\"upgrader\",function(title,module) {\n\t\t\tif(module.upgrade) {\n\t\t\t\tself.upgraderModules.push(module);\n\t\t\t}\n\t\t});\n\t}\n\t// Invoke each upgrader in turn\n\tvar messages = {};\n\tfor(var t=0; t<this.upgraderModules.length; t++) {\n\t\tvar upgrader = this.upgraderModules[t],\n\t\t\tupgraderMessages = upgrader.upgrade(this,titles,tiddlers);\n\t\t$tw.utils.extend(messages,upgraderMessages);\n\t}\n\treturn messages;\n};\n\n})();\n",
"title": "$:/core/modules/wiki.js",
"type": "application/javascript",
"module-type": "wikimethod"
},
"$:/palettes/Blanca": {
"title": "$:/palettes/Blanca",
"name": "Blanca",
"description": "A clean white palette to let you focus",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #ffffff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background:\nbutton-foreground:\nbutton-border:\ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #66cccc\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333333\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #999999\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #ffffff\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #7897f3\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #000000\nsidebar-controls-foreground: #ccc\nsidebar-foreground-shadow: rgba(255,255,255, 0.8)\nsidebar-foreground: #acacac\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #c0c0c0\nsidebar-tab-background-selected: #ffffff\nsidebar-tab-background: <<colour tab-background>>\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: <<colour tab-divider>>\nsidebar-tab-foreground-selected: \nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: #444444\nsidebar-tiddler-link-foreground: #7897f3\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: #ffffff\ntab-background: #eeeeee\ntab-border-selected: #cccccc\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #ffeedd\ntag-foreground: #000\ntiddler-background: <<colour background>>\ntiddler-border: #eee\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #f8f8f8\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #f8f8f8\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #ff9900\ntoolbar-new-button:\ntoolbar-options-button:\ntoolbar-save-button:\ntoolbar-info-button:\ntoolbar-edit-button:\ntoolbar-close-button:\ntoolbar-delete-button:\ntoolbar-cancel-button:\ntoolbar-done-button:\nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/Blue": {
"title": "$:/palettes/Blue",
"name": "Blue",
"description": "A blue theme",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #fff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background:\nbutton-foreground:\nbutton-border:\ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #34c734\ndownload-foreground: <<colour foreground>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333353\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #999999\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #ddddff\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #5778d8\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #000000\nsidebar-controls-foreground: #ffffff\nsidebar-foreground-shadow: rgba(255,255,255, 0.8)\nsidebar-foreground: #acacac\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #c0c0c0\nsidebar-tab-background-selected: <<colour page-background>>\nsidebar-tab-background: <<colour tab-background>>\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: <<colour tab-divider>>\nsidebar-tab-foreground-selected: \nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: #444444\nsidebar-tiddler-link-foreground: #5959c0\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: <<colour background>>\ntab-background: #ccccdd\ntab-border-selected: #ccccdd\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #eeeeff\ntag-foreground: #000\ntiddler-background: <<colour background>>\ntiddler-border: <<colour background>>\ntiddler-controls-foreground-hover: #666666\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #ffffff\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #ffffff\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #5959c0\ntoolbar-new-button: #5eb95e\ntoolbar-options-button: rgb(128, 88, 165)\ntoolbar-save-button: #0e90d2\ntoolbar-info-button: #0e90d2\ntoolbar-edit-button: rgb(243, 123, 29)\ntoolbar-close-button: #dd514c\ntoolbar-delete-button: #dd514c\ntoolbar-cancel-button: rgb(243, 123, 29)\ntoolbar-done-button: #5eb95e\nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/Muted": {
"title": "$:/palettes/Muted",
"name": "Muted",
"description": "Bright tiddlers on a muted background",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #ffffff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background:\nbutton-foreground:\nbutton-border:\ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #34c734\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333333\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #bbb\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #6f6f70\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #29a6ee\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #000000\nsidebar-controls-foreground: #c2c1c2\nsidebar-foreground-shadow: rgba(255,255,255,0)\nsidebar-foreground: #d3d2d4\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #c0c0c0\nsidebar-tab-background-selected: #6f6f70\nsidebar-tab-background: #666667\nsidebar-tab-border-selected: #999\nsidebar-tab-border: #515151\nsidebar-tab-divider: #999\nsidebar-tab-foreground-selected: \nsidebar-tab-foreground: #999\nsidebar-tiddler-link-foreground-hover: #444444\nsidebar-tiddler-link-foreground: #d1d0d2\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: #ffffff\ntab-background: #d8d8d8\ntab-border-selected: #d8d8d8\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #d5ad34\ntag-foreground: #ffffff\ntiddler-background: <<colour background>>\ntiddler-border: <<colour background>>\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #f8f8f8\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #f8f8f8\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #182955\ntoolbar-new-button: \ntoolbar-options-button: \ntoolbar-save-button: \ntoolbar-info-button: \ntoolbar-edit-button: \ntoolbar-close-button: \ntoolbar-delete-button: \ntoolbar-cancel-button: \ntoolbar-done-button: \nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/ContrastLight": {
"title": "$:/palettes/ContrastLight",
"name": "Contrast (Light)",
"description": "High contrast and unambiguous (light version)",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #f00\nalert-border: <<colour background>>\nalert-highlight: <<colour foreground>>\nalert-muted-foreground: #800\nbackground: #fff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background: <<colour background>>\nbutton-foreground: <<colour foreground>>\nbutton-border: <<colour foreground>>\ncode-background: <<colour background>>\ncode-border: <<colour foreground>>\ncode-foreground: <<colour foreground>>\ndirty-indicator: #f00\ndownload-background: #080\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: <<colour foreground>>\ndropdown-tab-background: <<colour foreground>>\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #00a\nexternal-link-foreground: #00e\nforeground: #000\nmessage-background: <<colour foreground>>\nmessage-border: <<colour background>>\nmessage-foreground: <<colour background>>\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: <<colour foreground>>\nmodal-footer-background: <<colour background>>\nmodal-footer-border: <<colour foreground>>\nmodal-header-border: <<colour foreground>>\nmuted-foreground: <<colour foreground>>\nnotification-background: <<colour background>>\nnotification-border: <<colour foreground>>\npage-background: <<colour background>>\npre-background: <<colour background>>\npre-border: <<colour foreground>>\nprimary: #00f\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: <<colour background>>\nsidebar-controls-foreground: <<colour foreground>>\nsidebar-foreground-shadow: rgba(0,0,0, 0)\nsidebar-foreground: <<colour foreground>>\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: <<colour foreground>>\nsidebar-tab-background-selected: <<colour background>>\nsidebar-tab-background: <<colour tab-background>>\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: <<colour tab-divider>>\nsidebar-tab-foreground-selected: <<colour foreground>>\nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: <<colour foreground>>\nsidebar-tiddler-link-foreground: <<colour primary>>\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: <<colour background>>\ntab-background: <<colour foreground>>\ntab-border-selected: <<colour foreground>>\ntab-border: <<colour foreground>>\ntab-divider: <<colour foreground>>\ntab-foreground-selected: <<colour foreground>>\ntab-foreground: <<colour background>>\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #000\ntag-foreground: #fff\ntiddler-background: <<colour background>>\ntiddler-border: <<colour foreground>>\ntiddler-controls-foreground-hover: #ddd\ntiddler-controls-foreground-selected: #fdd\ntiddler-controls-foreground: <<colour foreground>>\ntiddler-editor-background: <<colour background>>\ntiddler-editor-border-image: <<colour foreground>>\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: <<colour background>>\ntiddler-editor-fields-odd: <<colour background>>\ntiddler-info-background: <<colour background>>\ntiddler-info-border: <<colour foreground>>\ntiddler-info-tab-background: <<colour background>>\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: <<colour foreground>>\ntiddler-title-foreground: <<colour foreground>>\ntoolbar-new-button: \ntoolbar-options-button: \ntoolbar-save-button: \ntoolbar-info-button: \ntoolbar-edit-button: \ntoolbar-close-button: \ntoolbar-delete-button: \ntoolbar-cancel-button: \ntoolbar-done-button: \nuntagged-background: <<colour foreground>>\nvery-muted-foreground: #888888\n"
},
"$:/palettes/ContrastDark": {
"title": "$:/palettes/ContrastDark",
"name": "Contrast (Dark)",
"description": "High contrast and unambiguous (dark version)",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #f00\nalert-border: <<colour background>>\nalert-highlight: <<colour foreground>>\nalert-muted-foreground: #800\nbackground: #000\nblockquote-bar: <<colour muted-foreground>>\nbutton-background: <<colour background>>\nbutton-foreground: <<colour foreground>>\nbutton-border: <<colour foreground>>\ncode-background: <<colour background>>\ncode-border: <<colour foreground>>\ncode-foreground: <<colour foreground>>\ndirty-indicator: #f00\ndownload-background: #080\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: <<colour foreground>>\ndropdown-tab-background: <<colour foreground>>\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #00a\nexternal-link-foreground: #00e\nforeground: #fff\nmessage-background: <<colour foreground>>\nmessage-border: <<colour background>>\nmessage-foreground: <<colour background>>\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: <<colour foreground>>\nmodal-footer-background: <<colour background>>\nmodal-footer-border: <<colour foreground>>\nmodal-header-border: <<colour foreground>>\nmuted-foreground: <<colour foreground>>\nnotification-background: <<colour background>>\nnotification-border: <<colour foreground>>\npage-background: <<colour background>>\npre-background: <<colour background>>\npre-border: <<colour foreground>>\nprimary: #00f\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: <<colour background>>\nsidebar-controls-foreground: <<colour foreground>>\nsidebar-foreground-shadow: rgba(0,0,0, 0)\nsidebar-foreground: <<colour foreground>>\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: <<colour foreground>>\nsidebar-tab-background-selected: <<colour background>>\nsidebar-tab-background: <<colour tab-background>>\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: <<colour tab-divider>>\nsidebar-tab-foreground-selected: <<colour foreground>>\nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: <<colour foreground>>\nsidebar-tiddler-link-foreground: <<colour primary>>\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: <<colour background>>\ntab-background: <<colour foreground>>\ntab-border-selected: <<colour foreground>>\ntab-border: <<colour foreground>>\ntab-divider: <<colour foreground>>\ntab-foreground-selected: <<colour foreground>>\ntab-foreground: <<colour background>>\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #fff\ntag-foreground: #000\ntiddler-background: <<colour background>>\ntiddler-border: <<colour foreground>>\ntiddler-controls-foreground-hover: #ddd\ntiddler-controls-foreground-selected: #fdd\ntiddler-controls-foreground: <<colour foreground>>\ntiddler-editor-background: <<colour background>>\ntiddler-editor-border-image: <<colour foreground>>\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: <<colour background>>\ntiddler-editor-fields-odd: <<colour background>>\ntiddler-info-background: <<colour background>>\ntiddler-info-border: <<colour foreground>>\ntiddler-info-tab-background: <<colour background>>\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: <<colour foreground>>\ntiddler-title-foreground: <<colour foreground>>\ntoolbar-new-button: \ntoolbar-options-button: \ntoolbar-save-button: \ntoolbar-info-button: \ntoolbar-edit-button: \ntoolbar-close-button: \ntoolbar-delete-button: \ntoolbar-cancel-button: \ntoolbar-done-button: \nuntagged-background: <<colour foreground>>\nvery-muted-foreground: #888888\n"
},
"$:/palettes/DarkPhotos": {
"created": "20150402111612188",
"description": "Good with dark photo backgrounds",
"modified": "20150402112344080",
"name": "DarkPhotos",
"tags": "$:/tags/Palette",
"title": "$:/palettes/DarkPhotos",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #ffffff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background: \nbutton-foreground: \nbutton-border: \ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #34c734\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333333\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #ddd\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #336438\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #5778d8\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #ccf\nsidebar-controls-foreground: #fff\nsidebar-foreground-shadow: rgba(0,0,0, 0.5)\nsidebar-foreground: #fff\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #eee\nsidebar-tab-background-selected: rgba(255,255,255, 0.8)\nsidebar-tab-background: rgba(255,255,255, 0.4)\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: rgba(255,255,255, 0.2)\nsidebar-tab-foreground-selected: \nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: #aaf\nsidebar-tiddler-link-foreground: #ddf\nsite-title-foreground: #fff\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: #ffffff\ntab-background: #d8d8d8\ntab-border-selected: #d8d8d8\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #ec6\ntag-foreground: #ffffff\ntiddler-background: <<colour background>>\ntiddler-border: <<colour background>>\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #f8f8f8\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #f8f8f8\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #182955\ntoolbar-new-button: \ntoolbar-options-button: \ntoolbar-save-button: \ntoolbar-info-button: \ntoolbar-edit-button: \ntoolbar-close-button: \ntoolbar-delete-button: \ntoolbar-cancel-button: \ntoolbar-done-button: \nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/Rocker": {
"title": "$:/palettes/Rocker",
"name": "Rocker",
"description": "A dark theme",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #ffffff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background:\nbutton-foreground:\nbutton-border:\ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #34c734\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333333\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #999999\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #000\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #cc0000\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #000000\nsidebar-controls-foreground: #ffffff\nsidebar-foreground-shadow: rgba(255,255,255, 0.0)\nsidebar-foreground: #acacac\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #c0c0c0\nsidebar-tab-background-selected: #000\nsidebar-tab-background: <<colour tab-background>>\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: <<colour tab-divider>>\nsidebar-tab-foreground-selected: \nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: #ffbb99\nsidebar-tiddler-link-foreground: #cc0000\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: #ffffff\ntab-background: #d8d8d8\ntab-border-selected: #d8d8d8\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #ffbb99\ntag-foreground: #000\ntiddler-background: <<colour background>>\ntiddler-border: <<colour background>>\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #f8f8f8\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #f8f8f8\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #cc0000\ntoolbar-new-button:\ntoolbar-options-button:\ntoolbar-save-button:\ntoolbar-info-button:\ntoolbar-edit-button:\ntoolbar-close-button:\ntoolbar-delete-button:\ntoolbar-cancel-button:\ntoolbar-done-button:\nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/SolarFlare": {
"title": "$:/palettes/SolarFlare",
"name": "Solar Flare",
"description": "Warm, relaxing earth colours",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": ": Background Tones\n\nbase03: #002b36\nbase02: #073642\n\n: Content Tones\n\nbase01: #586e75\nbase00: #657b83\nbase0: #839496\nbase1: #93a1a1\n\n: Background Tones\n\nbase2: #eee8d5\nbase3: #fdf6e3\n\n: Accent Colors\n\nyellow: #b58900\norange: #cb4b16\nred: #dc322f\nmagenta: #d33682\nviolet: #6c71c4\nblue: #268bd2\ncyan: #2aa198\ngreen: #859900\n\n: Additional Tones (RA)\n\nbase10: #c0c4bb\nviolet-muted: #7c81b0\nblue-muted: #4e7baa\n\nyellow-hot: #ffcc44\norange-hot: #eb6d20\nred-hot: #ff2222\nblue-hot: #2298ee\ngreen-hot: #98ee22\n\n: Palette\n\n: Do not use colour macro for background and foreground\nbackground: #fdf6e3\n download-foreground: <<colour background>>\n dragger-foreground: <<colour background>>\n dropdown-background: <<colour background>>\n modal-background: <<colour background>>\n sidebar-foreground-shadow: <<colour background>>\n tiddler-background: <<colour background>>\n tiddler-border: <<colour background>>\n tiddler-link-background: <<colour background>>\n tab-background-selected: <<colour background>>\n dropdown-tab-background-selected: <<colour tab-background-selected>>\nforeground: #657b83\n dragger-background: <<colour foreground>>\n tab-foreground: <<colour foreground>>\n tab-foreground-selected: <<colour tab-foreground>>\n sidebar-tab-foreground-selected: <<colour tab-foreground-selected>>\n sidebar-tab-foreground: <<colour tab-foreground>>\n sidebar-button-foreground: <<colour foreground>>\n sidebar-controls-foreground: <<colour foreground>>\n sidebar-foreground: <<colour foreground>>\n: base03\n: base02\n: base01\n alert-muted-foreground: <<colour base01>>\n: base00\n code-foreground: <<colour base00>>\n message-foreground: <<colour base00>>\n tag-foreground: <<colour base00>>\n: base0\n sidebar-tiddler-link-foreground: <<colour base0>>\n: base1\n muted-foreground: <<colour base1>>\n blockquote-bar: <<colour muted-foreground>>\n dropdown-border: <<colour muted-foreground>>\n sidebar-muted-foreground: <<colour muted-foreground>>\n tiddler-title-foreground: <<colour muted-foreground>>\n site-title-foreground: <<colour tiddler-title-foreground>>\n: base2\n modal-footer-background: <<colour base2>>\n page-background: <<colour base2>>\n modal-backdrop: <<colour page-background>>\n notification-background: <<colour page-background>>\n code-background: <<colour page-background>>\n code-border: <<colour code-background>>\n pre-background: <<colour page-background>>\n pre-border: <<colour pre-background>>\n sidebar-tab-background-selected: <<colour page-background>>\n table-header-background: <<colour base2>>\n tag-background: <<colour base2>>\n tiddler-editor-background: <<colour base2>>\n tiddler-info-background: <<colour base2>>\n tiddler-info-tab-background: <<colour base2>>\n tab-background: <<colour base2>>\n dropdown-tab-background: <<colour tab-background>>\n: base3\n alert-background: <<colour base3>>\n message-background: <<colour base3>>\n: yellow\n: orange\n: red\n: magenta\n alert-highlight: <<colour magenta>>\n: violet\n external-link-foreground: <<colour violet>>\n: blue\n: cyan\n: green\n: base10\n tiddler-controls-foreground: <<colour base10>>\n: violet-muted\n external-link-foreground-visited: <<colour violet-muted>>\n: blue-muted\n primary: <<colour blue-muted>>\n download-background: <<colour primary>>\n tiddler-link-foreground: <<colour primary>>\n\nalert-border: #b99e2f\ndirty-indicator: #ff0000\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nmessage-border: #cfd6e6\nmodal-border: #999999\nsidebar-controls-foreground-hover:\nsidebar-muted-foreground-hover:\nsidebar-tab-background: #ded8c5\nsidebar-tiddler-link-foreground-hover:\nstatic-alert-foreground: #aaaaaa\ntab-border: #cccccc\n modal-footer-border: <<colour tab-border>>\n modal-header-border: <<colour tab-border>>\n notification-border: <<colour tab-border>>\n sidebar-tab-border: <<colour tab-border>>\n tab-border-selected: <<colour tab-border>>\n sidebar-tab-border-selected: <<colour tab-border-selected>>\ntab-divider: #d8d8d8\n sidebar-tab-divider: <<colour tab-divider>>\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-border: #dddddd\ntiddler-subtitle-foreground: #c0c0c0\ntoolbar-new-button:\ntoolbar-options-button:\ntoolbar-save-button:\ntoolbar-info-button:\ntoolbar-edit-button:\ntoolbar-close-button:\ntoolbar-delete-button:\ntoolbar-cancel-button:\ntoolbar-done-button:\nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/palettes/Vanilla": {
"title": "$:/palettes/Vanilla",
"name": "Vanilla",
"description": "Pale and unobtrusive",
"tags": "$:/tags/Palette",
"type": "application/x-tiddler-dictionary",
"text": "alert-background: #ffe476\nalert-border: #b99e2f\nalert-highlight: #881122\nalert-muted-foreground: #b99e2f\nbackground: #ffffff\nblockquote-bar: <<colour muted-foreground>>\nbutton-background:\nbutton-foreground:\nbutton-border:\ncode-background: #f7f7f9\ncode-border: #e1e1e8\ncode-foreground: #dd1144\ndirty-indicator: #ff0000\ndownload-background: #34c734\ndownload-foreground: <<colour background>>\ndragger-background: <<colour foreground>>\ndragger-foreground: <<colour background>>\ndropdown-background: <<colour background>>\ndropdown-border: <<colour muted-foreground>>\ndropdown-tab-background-selected: #fff\ndropdown-tab-background: #ececec\ndropzone-background: rgba(0,200,0,0.7)\nexternal-link-background-hover: inherit\nexternal-link-background-visited: inherit\nexternal-link-background: inherit\nexternal-link-foreground-hover: inherit\nexternal-link-foreground-visited: #0000aa\nexternal-link-foreground: #0000ee\nforeground: #333333\nmessage-background: #ecf2ff\nmessage-border: #cfd6e6\nmessage-foreground: #547599\nmodal-backdrop: <<colour foreground>>\nmodal-background: <<colour background>>\nmodal-border: #999999\nmodal-footer-background: #f5f5f5\nmodal-footer-border: #dddddd\nmodal-header-border: #eeeeee\nmuted-foreground: #bbb\nnotification-background: #ffffdd\nnotification-border: #999999\npage-background: #f4f4f4\npre-background: #f5f5f5\npre-border: #cccccc\nprimary: #5778d8\nsidebar-button-foreground: <<colour foreground>>\nsidebar-controls-foreground-hover: #000000\nsidebar-controls-foreground: #aaaaaa\nsidebar-foreground-shadow: rgba(255,255,255, 0.8)\nsidebar-foreground: #acacac\nsidebar-muted-foreground-hover: #444444\nsidebar-muted-foreground: #c0c0c0\nsidebar-tab-background-selected: #f4f4f4\nsidebar-tab-background: #e0e0e0\nsidebar-tab-border-selected: <<colour tab-border-selected>>\nsidebar-tab-border: <<colour tab-border>>\nsidebar-tab-divider: #e4e4e4\nsidebar-tab-foreground-selected:\nsidebar-tab-foreground: <<colour tab-foreground>>\nsidebar-tiddler-link-foreground-hover: #444444\nsidebar-tiddler-link-foreground: #999999\nsite-title-foreground: <<colour tiddler-title-foreground>>\nstatic-alert-foreground: #aaaaaa\ntab-background-selected: #ffffff\ntab-background: #d8d8d8\ntab-border-selected: #d8d8d8\ntab-border: #cccccc\ntab-divider: #d8d8d8\ntab-foreground-selected: <<colour tab-foreground>>\ntab-foreground: #666666\ntable-border: #dddddd\ntable-footer-background: #a8a8a8\ntable-header-background: #f0f0f0\ntag-background: #ec6\ntag-foreground: #ffffff\ntiddler-background: <<colour background>>\ntiddler-border: <<colour background>>\ntiddler-controls-foreground-hover: #888888\ntiddler-controls-foreground-selected: #444444\ntiddler-controls-foreground: #cccccc\ntiddler-editor-background: #f8f8f8\ntiddler-editor-border-image: #ffffff\ntiddler-editor-border: #cccccc\ntiddler-editor-fields-even: #e0e8e0\ntiddler-editor-fields-odd: #f0f4f0\ntiddler-info-background: #f8f8f8\ntiddler-info-border: #dddddd\ntiddler-info-tab-background: #f8f8f8\ntiddler-link-background: <<colour background>>\ntiddler-link-foreground: <<colour primary>>\ntiddler-subtitle-foreground: #c0c0c0\ntiddler-title-foreground: #182955\ntoolbar-new-button:\ntoolbar-options-button:\ntoolbar-save-button:\ntoolbar-info-button:\ntoolbar-edit-button:\ntoolbar-close-button:\ntoolbar-delete-button:\ntoolbar-cancel-button:\ntoolbar-done-button:\nuntagged-background: #999999\nvery-muted-foreground: #888888\n"
},
"$:/core/readme": {
"title": "$:/core/readme",
"text": "This plugin contains TiddlyWiki's core components, comprising:\n\n* JavaScript code modules\n* Icons\n* Templates needed to create TiddlyWiki's user interface\n* British English (''en-GB'') translations of the localisable strings used by the core\n"
},
"$:/core/templates/MOTW.html": {
"title": "$:/core/templates/MOTW.html",
"text": "\\rules only filteredtranscludeinline transcludeinline entity\n<!-- The following comment is called a MOTW comment and is necessary for the TiddlyIE Internet Explorer extension -->\n<!-- saved from url=(0021)http://tiddlywiki.com --> "
},
"$:/core/templates/alltiddlers.template.html": {
"title": "$:/core/templates/alltiddlers.template.html",
"type": "text/vnd.tiddlywiki-html",
"text": "<!-- This template is provided for backwards compatibility with older versions of TiddlyWiki -->\n\n<$set name=\"exportFilter\" value=\"[!is[system]sort[title]]\">\n\n{{$:/core/templates/exporters/StaticRiver}}\n\n</$set>\n"
},
"$:/core/templates/canonical-uri-external-image": {
"title": "$:/core/templates/canonical-uri-external-image",
"text": "<!--\n\nThis template is used to assign the ''_canonical_uri'' field to external images.\n\nChange the `./images/` part to a different base URI. The URI can be relative or absolute.\n\n-->\n./images/<$view field=\"title\" format=\"doubleurlencoded\"/>"
},
"$:/core/templates/canonical-uri-external-text": {
"title": "$:/core/templates/canonical-uri-external-text",
"text": "<!--\n\nThis template is used to assign the ''_canonical_uri'' field to external text files.\n\nChange the `./text/` part to a different base URI. The URI can be relative or absolute.\n\n-->\n./text/<$view field=\"title\" format=\"doubleurlencoded\"/>.tid"
},
"$:/core/templates/css-tiddler": {
"title": "$:/core/templates/css-tiddler",
"text": "<!--\n\nThis template is used for saving CSS tiddlers as a style tag with data attributes representing the tiddler fields.\n\n-->`<style`<$fields template=' data-tiddler-$name$=\"$encoded_value$\"'></$fields>` type=\"text/css\">`<$view field=\"text\" format=\"text\" />`</style>`"
},
"$:/core/templates/exporters/CsvFile": {
"title": "$:/core/templates/exporters/CsvFile",
"tags": "$:/tags/Exporter",
"description": "{{$:/language/Exporters/CsvFile}}",
"extension": ".csv",
"text": "\\define renderContent()\n<$text text=<<csvtiddlers filter:\"\"\"$(exportFilter)$\"\"\" format:\"quoted-comma-sep\">>/>\n\\end\n<<renderContent>>\n"
},
"$:/core/templates/exporters/JsonFile": {
"title": "$:/core/templates/exporters/JsonFile",
"tags": "$:/tags/Exporter",
"description": "{{$:/language/Exporters/JsonFile}}",
"extension": ".json",
"text": "\\define renderContent()\n<$text text=<<jsontiddlers filter:\"\"\"$(exportFilter)$\"\"\">>/>\n\\end\n<<renderContent>>\n"
},
"$:/core/templates/exporters/StaticRiver": {
"title": "$:/core/templates/exporters/StaticRiver",
"tags": "$:/tags/Exporter",
"description": "{{$:/language/Exporters/StaticRiver}}",
"extension": ".html",
"text": "\\define tv-wikilink-template() #$uri_encoded$\n\\define tv-config-toolbar-icons() no\n\\define tv-config-toolbar-text() no\n\\define tv-config-toolbar-class() tc-btn-invisible\n\\rules only filteredtranscludeinline transcludeinline\n<!doctype html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html;charset=utf-8\" />\n<meta name=\"generator\" content=\"TiddlyWiki\" />\n<meta name=\"tiddlywiki-version\" content=\"{{$:/core/templates/version}}\" />\n<meta name=\"format-detection\" content=\"telephone=no\">\n<link id=\"faviconLink\" rel=\"shortcut icon\" href=\"favicon.ico\">\n<title>{{$:/core/wiki/title}}</title>\n<div id=\"styleArea\">\n{{$:/boot/boot.css||$:/core/templates/css-tiddler}}\n</div>\n<style type=\"text/css\">\n{{$:/core/ui/PageStylesheet||$:/core/templates/wikified-tiddler}}\n</style>\n</head>\n<body class=\"tc-body\">\n{{$:/StaticBanner||$:/core/templates/html-tiddler}}\n<section class=\"tc-story-river\">\n{{$:/core/templates/exporters/StaticRiver/Content||$:/core/templates/html-tiddler}}\n</section>\n</body>\n</html>\n"
},
"$:/core/templates/exporters/StaticRiver/Content": {
"title": "$:/core/templates/exporters/StaticRiver/Content",
"text": "\\define renderContent()\n{{{ $(exportFilter)$ ||$:/core/templates/static-tiddler}}}\n\\end\n<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n<<renderContent>>\n</$importvariables>\n"
},
"$:/core/templates/exporters/TidFile": {
"title": "$:/core/templates/exporters/TidFile",
"tags": "$:/tags/Exporter",
"description": "{{$:/language/Exporters/TidFile}}",
"extension": ".tid",
"text": "\\define renderContent()\n{{{ $(exportFilter)$ +[limit[1]] ||$:/core/templates/tid-tiddler}}}\n\\end\n<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\"><<renderContent>></$importvariables>"
},
"$:/core/templates/html-div-tiddler": {
"title": "$:/core/templates/html-div-tiddler",
"text": "<!--\n\nThis template is used for saving tiddlers as an HTML DIV tag with attributes representing the tiddler fields.\n\n-->`<div`<$fields template=' $name$=\"$encoded_value$\"'></$fields>`>\n<pre>`<$view field=\"text\" format=\"htmlencoded\" />`</pre>\n</div>`\n"
},
"$:/core/templates/html-tiddler": {
"title": "$:/core/templates/html-tiddler",
"text": "<!--\n\nThis template is used for saving tiddlers as raw HTML\n\n--><$view field=\"text\" format=\"htmlwikified\" />"
},
"$:/core/templates/javascript-tiddler": {
"title": "$:/core/templates/javascript-tiddler",
"text": "<!--\n\nThis template is used for saving JavaScript tiddlers as a script tag with data attributes representing the tiddler fields.\n\n-->`<script`<$fields template=' data-tiddler-$name$=\"$encoded_value$\"'></$fields>` type=\"text/javascript\">`<$view field=\"text\" format=\"text\" />`</script>`"
},
"$:/core/templates/module-tiddler": {
"title": "$:/core/templates/module-tiddler",
"text": "<!--\n\nThis template is used for saving JavaScript tiddlers as a script tag with data attributes representing the tiddler fields. The body of the tiddler is wrapped in a call to the `$tw.modules.define` function in order to define the body of the tiddler as a module\n\n-->`<script`<$fields template=' data-tiddler-$name$=\"$encoded_value$\"'></$fields>` type=\"text/javascript\" data-module=\"yes\">$tw.modules.define(\"`<$view field=\"title\" format=\"jsencoded\" />`\",\"`<$view field=\"module-type\" format=\"jsencoded\" />`\",function(module,exports,require) {`<$view field=\"text\" format=\"text\" />`});\n</script>`"
},
"$:/core/templates/plain-text-tiddler": {
"title": "$:/core/templates/plain-text-tiddler",
"text": "<$view field=\"text\" format=\"text\" />"
},
"$:/core/templates/raw-static-tiddler": {
"title": "$:/core/templates/raw-static-tiddler",
"text": "<!--\n\nThis template is used for saving tiddlers as static HTML\n\n--><$view field=\"text\" format=\"plainwikified\" />"
},
"$:/core/save/all": {
"title": "$:/core/save/all",
"text": "\\define saveTiddlerFilter()\n[is[tiddler]] -[prefix[$:/state/popup/]] -[[$:/HistoryList]] -[[$:/boot/boot.css]] -[type[application/javascript]library[yes]] -[[$:/boot/boot.js]] -[[$:/boot/bootprefix.js]] +[sort[title]] $(publishFilter)$\n\\end\n{{$:/core/templates/tiddlywiki5.html}}\n"
},
"$:/core/save/empty": {
"title": "$:/core/save/empty",
"text": "\\define saveTiddlerFilter()\n[is[system]] -[prefix[$:/state/popup/]] -[[$:/boot/boot.css]] -[type[application/javascript]library[yes]] -[[$:/boot/boot.js]] -[[$:/boot/bootprefix.js]] +[sort[title]]\n\\end\n{{$:/core/templates/tiddlywiki5.html}}\n"
},
"$:/core/save/lazy-all": {
"title": "$:/core/save/lazy-all",
"text": "\\define saveTiddlerFilter()\n[is[system]] -[prefix[$:/state/popup/]] -[[$:/HistoryList]] -[[$:/boot/boot.css]] -[type[application/javascript]library[yes]] -[[$:/boot/boot.js]] -[[$:/boot/bootprefix.js]] +[sort[title]] \n\\end\n{{$:/core/templates/tiddlywiki5.html}}\n"
},
"$:/core/save/lazy-images": {
"title": "$:/core/save/lazy-images",
"text": "\\define saveTiddlerFilter()\n[is[tiddler]] -[prefix[$:/state/popup/]] -[[$:/HistoryList]] -[[$:/boot/boot.css]] -[type[application/javascript]library[yes]] -[[$:/boot/boot.js]] -[[$:/boot/bootprefix.js]] -[!is[system]is[image]] +[sort[title]] \n\\end\n{{$:/core/templates/tiddlywiki5.html}}\n"
},
"$:/core/templates/single.tiddler.window": {
"title": "$:/core/templates/single.tiddler.window",
"text": "<$set name=\"themeTitle\" value={{$:/view}}>\n\n<$set name=\"tempCurrentTiddler\" value=<<currentTiddler>>>\n\n<$set name=\"currentTiddler\" value={{$:/language}}>\n\n<$set name=\"languageTitle\" value={{!!name}}>\n\n<$set name=\"currentTiddler\" value=<<tempCurrentTiddler>>>\n\n<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n\n<$navigator story=\"$:/StoryList\" history=\"$:/HistoryList\">\n\n<$transclude mode=\"block\"/>\n\n</$navigator>\n\n</$importvariables>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n"
},
"$:/core/templates/split-recipe": {
"title": "$:/core/templates/split-recipe",
"text": "<$list filter=\"[!is[system]]\">\ntiddler: <$view field=\"title\" format=\"urlencoded\"/>.tid\n</$list>\n"
},
"$:/core/templates/static-tiddler": {
"title": "$:/core/templates/static-tiddler",
"text": "<a name=<<currentTiddler>>>\n<$transclude tiddler=\"$:/core/ui/ViewTemplate\"/>\n</a>"
},
"$:/core/templates/static.area": {
"title": "$:/core/templates/static.area",
"text": "<$reveal type=\"nomatch\" state=\"$:/isEncrypted\" text=\"yes\">\n{{{ [all[shadows+tiddlers]tag[$:/tags/RawStaticContent]!has[draft.of]] ||$:/core/templates/raw-static-tiddler}}}\n{{$:/core/templates/static.content||$:/core/templates/html-tiddler}}\n</$reveal>\n<$reveal type=\"match\" state=\"$:/isEncrypted\" text=\"yes\">\nThis file contains an encrypted ~TiddlyWiki. Enable ~JavaScript and enter the decryption password when prompted.\n</$reveal>\n"
},
"$:/core/templates/static.content": {
"title": "$:/core/templates/static.content",
"type": "text/vnd.tiddlywiki",
"text": "<!-- For Google, and people without JavaScript-->\nThis [[TiddlyWiki|http://tiddlywiki.com]] contains the following tiddlers:\n\n<ul>\n<$list filter=<<saveTiddlerFilter>>>\n<li><$view field=\"title\" format=\"text\"></$view></li>\n</$list>\n</ul>\n"
},
"$:/core/templates/static.template.css": {
"title": "$:/core/templates/static.template.css",
"text": "{{$:/boot/boot.css||$:/core/templates/plain-text-tiddler}}\n\n{{$:/core/ui/PageStylesheet||$:/core/templates/wikified-tiddler}}\n"
},
"$:/core/templates/static.template.html": {
"title": "$:/core/templates/static.template.html",
"type": "text/vnd.tiddlywiki-html",
"text": "\\define tv-wikilink-template() static/$uri_doubleencoded$.html\n\\define tv-config-toolbar-icons() no\n\\define tv-config-toolbar-text() no\n\\define tv-config-toolbar-class() tc-btn-invisible\n\\rules only filteredtranscludeinline transcludeinline\n<!doctype html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html;charset=utf-8\" />\n<meta name=\"generator\" content=\"TiddlyWiki\" />\n<meta name=\"tiddlywiki-version\" content=\"{{$:/core/templates/version}}\" />\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n<meta name=\"apple-mobile-web-app-capable\" content=\"yes\" />\n<meta name=\"apple-mobile-web-app-status-bar-style\" content=\"black-translucent\" />\n<meta name=\"mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"format-detection\" content=\"telephone=no\">\n<link id=\"faviconLink\" rel=\"shortcut icon\" href=\"favicon.ico\">\n<title>{{$:/core/wiki/title}}</title>\n<div id=\"styleArea\">\n{{$:/boot/boot.css||$:/core/templates/css-tiddler}}\n</div>\n<style type=\"text/css\">\n{{$:/core/ui/PageStylesheet||$:/core/templates/wikified-tiddler}}\n</style>\n</head>\n<body class=\"tc-body\">\n{{$:/StaticBanner||$:/core/templates/html-tiddler}}\n{{$:/core/ui/PageTemplate||$:/core/templates/html-tiddler}}\n</body>\n</html>\n"
},
"$:/core/templates/static.tiddler.html": {
"title": "$:/core/templates/static.tiddler.html",
"text": "\\define tv-wikilink-template() $uri_doubleencoded$.html\n\\define tv-config-toolbar-icons() no\n\\define tv-config-toolbar-text() no\n\\define tv-config-toolbar-class() tc-btn-invisible\n`<!doctype html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html;charset=utf-8\" />\n<meta name=\"generator\" content=\"TiddlyWiki\" />\n<meta name=\"tiddlywiki-version\" content=\"`{{$:/core/templates/version}}`\" />\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n<meta name=\"apple-mobile-web-app-capable\" content=\"yes\" />\n<meta name=\"apple-mobile-web-app-status-bar-style\" content=\"black-translucent\" />\n<meta name=\"mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"format-detection\" content=\"telephone=no\">\n<link id=\"faviconLink\" rel=\"shortcut icon\" href=\"favicon.ico\">\n<link rel=\"stylesheet\" href=\"static.css\">\n<title>`<$view field=\"caption\"><$view field=\"title\"/></$view>: {{$:/core/wiki/title}}`</title>\n</head>\n<body class=\"tc-body\">\n`{{$:/StaticBanner||$:/core/templates/html-tiddler}}`\n<section class=\"tc-story-river\">\n`<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n<$view tiddler=\"$:/core/ui/ViewTemplate\" format=\"htmlwikified\"/>\n</$importvariables>`\n</section>\n</body>\n</html>\n`"
},
"$:/core/templates/store.area.template.html": {
"title": "$:/core/templates/store.area.template.html",
"text": "<$reveal type=\"nomatch\" state=\"$:/isEncrypted\" text=\"yes\">\n`<div id=\"storeArea\" style=\"display:none;\">`\n<$list filter=<<saveTiddlerFilter>> template=\"$:/core/templates/html-div-tiddler\"/>\n`</div>`\n</$reveal>\n<$reveal type=\"match\" state=\"$:/isEncrypted\" text=\"yes\">\n`<!--~~ Encrypted tiddlers ~~-->`\n`<pre id=\"encryptedStoreArea\" type=\"text/plain\" style=\"display:none;\">`\n<$encrypt filter=<<saveTiddlerFilter>>/>\n`</pre>`\n</$reveal>"
},
"$:/core/templates/tid-tiddler": {
"title": "$:/core/templates/tid-tiddler",
"text": "<!--\n\nThis template is used for saving tiddlers in TiddlyWeb *.tid format\n\n--><$fields exclude='text bag' template='$name$: $value$\n'></$fields>`\n`<$view field=\"text\" format=\"text\" />"
},
"$:/core/templates/tiddler-metadata": {
"title": "$:/core/templates/tiddler-metadata",
"text": "<!--\n\nThis template is used for saving tiddler metadata *.meta files\n\n--><$fields exclude='text bag' template='$name$: $value$\n'></$fields>"
},
"$:/core/templates/tiddlywiki5.html": {
"title": "$:/core/templates/tiddlywiki5.html",
"text": "\\rules only filteredtranscludeinline transcludeinline\n<!doctype html>\n{{$:/core/templates/MOTW.html}}<html>\n<head>\n<meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\" />\t\t<!-- Force IE standards mode for Intranet and HTA - should be the first meta -->\n<meta http-equiv=\"Content-Type\" content=\"text/html;charset=utf-8\" />\n<meta name=\"application-name\" content=\"TiddlyWiki\" />\n<meta name=\"generator\" content=\"TiddlyWiki\" />\n<meta name=\"tiddlywiki-version\" content=\"{{$:/core/templates/version}}\" />\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n<meta name=\"apple-mobile-web-app-capable\" content=\"yes\" />\n<meta name=\"apple-mobile-web-app-status-bar-style\" content=\"black-translucent\" />\n<meta name=\"mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"format-detection\" content=\"telephone=no\" />\n<meta name=\"copyright\" content=\"{{$:/core/copyright.txt}}\" />\n<link id=\"faviconLink\" rel=\"shortcut icon\" href=\"favicon.ico\">\n<title>{{$:/core/wiki/title}}</title>\n<!--~~ This is a Tiddlywiki file. The points of interest in the file are marked with this pattern ~~-->\n\n<!--~~ Raw markup ~~-->\n{{{ [all[shadows+tiddlers]tag[$:/core/wiki/rawmarkup]] [all[shadows+tiddlers]tag[$:/tags/RawMarkup]] ||$:/core/templates/plain-text-tiddler}}}\n</head>\n<body class=\"tc-body\">\n<!--~~ Static styles ~~-->\n<div id=\"styleArea\">\n{{$:/boot/boot.css||$:/core/templates/css-tiddler}}\n</div>\n<!--~~ Static content for Google and browsers without JavaScript ~~-->\n<noscript>\n<div id=\"splashArea\">\n{{$:/core/templates/static.area}}\n</div>\n</noscript>\n<!--~~ Ordinary tiddlers ~~-->\n{{$:/core/templates/store.area.template.html}}\n<!--~~ Library modules ~~-->\n<div id=\"libraryModules\" style=\"display:none;\">\n{{{ [is[system]type[application/javascript]library[yes]] ||$:/core/templates/javascript-tiddler}}}\n</div>\n<!--~~ Boot kernel prologue ~~-->\n<div id=\"bootKernelPrefix\" style=\"display:none;\">\n{{ $:/boot/bootprefix.js ||$:/core/templates/javascript-tiddler}}\n</div>\n<!--~~ Boot kernel ~~-->\n<div id=\"bootKernel\" style=\"display:none;\">\n{{ $:/boot/boot.js ||$:/core/templates/javascript-tiddler}}\n</div>\n</body>\n</html>\n"
},
"$:/core/templates/version": {
"title": "$:/core/templates/version",
"text": "<<version>>"
},
"$:/core/templates/wikified-tiddler": {
"title": "$:/core/templates/wikified-tiddler",
"text": "<$transclude />"
},
"$:/core/ui/AboveStory/tw2-plugin-check": {
"title": "$:/core/ui/AboveStory/tw2-plugin-check",
"tags": "$:/tags/AboveStory",
"text": "\\define lingo-base() $:/language/AboveStory/ClassicPlugin/\n<$list filter=\"[all[system+tiddlers]tag[systemConfig]limit[1]]\">\n\n<div class=\"tc-message-box\">\n\n<<lingo Warning>>\n\n<ul>\n\n<$list filter=\"[all[system+tiddlers]tag[systemConfig]limit[1]]\">\n\n<li>\n\n<$link><$view field=\"title\"/></$link>\n\n</li>\n\n</$list>\n\n</ul>\n\n</div>\n\n</$list>\n"
},
"$:/core/ui/AdvancedSearch/Filter": {
"title": "$:/core/ui/AdvancedSearch/Filter",
"tags": "$:/tags/AdvancedSearch",
"caption": "{{$:/language/Search/Filter/Caption}}",
"text": "\\define lingo-base() $:/language/Search/\n<<lingo Filter/Hint>>\n\n<div class=\"tc-search tc-advanced-search\">\n<$edit-text tiddler=\"$:/temp/advancedsearch\" type=\"search\" tag=\"input\"/>\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/AdvancedSearch/FilterButton]!has[draft.of]]\"><$transclude/></$list>\n</div>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$set name=\"resultCount\" value=\"\"\"<$count filter={{$:/temp/advancedsearch}}/>\"\"\">\n<div class=\"tc-search-results\">\n<<lingo Filter/Matches>>\n<$list filter={{$:/temp/advancedsearch}} template=\"$:/core/ui/ListItemTemplate\"/>\n</div>\n</$set>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Filter/FilterButtons/clear": {
"title": "$:/core/ui/AdvancedSearch/Filter/FilterButtons/clear",
"tags": "$:/tags/AdvancedSearch/FilterButton",
"text": "<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" $field=\"text\" $value=\"\"/>\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Filter/FilterButtons/delete": {
"title": "$:/core/ui/AdvancedSearch/Filter/FilterButtons/delete",
"tags": "$:/tags/AdvancedSearch/FilterButton",
"text": "<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$button popup=<<qualify \"$:/state/filterDeleteDropdown\">> class=\"tc-btn-invisible\">\n{{$:/core/images/delete-button}}\n</$button>\n</$reveal>\n\n<$reveal state=<<qualify \"$:/state/filterDeleteDropdown\">> type=\"popup\" position=\"belowleft\" animate=\"yes\">\n<div class=\"tc-block-dropdown-wrapper\">\n<div class=\"tc-block-dropdown tc-edit-type-dropdown\">\n<div class=\"tc-dropdown-item-plain\">\n<$set name=\"resultCount\" value=\"\"\"<$count filter={{$:/temp/advancedsearch}}/>\"\"\">\nAre you sure you wish to delete <<resultCount>> tiddler(s)?\n</$set>\n</div>\n<div class=\"tc-dropdown-item-plain\">\n<$button class=\"tc-btn\">\n<$action-deletetiddler $filter={{$:/temp/advancedsearch}}/>\nDelete these tiddlers\n</$button>\n</div>\n</div>\n</div>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Filter/FilterButtons/dropdown": {
"title": "$:/core/ui/AdvancedSearch/Filter/FilterButtons/dropdown",
"tags": "$:/tags/AdvancedSearch/FilterButton",
"text": "<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/filterDropdown\">> class=\"tc-btn-invisible\">\n{{$:/core/images/down-arrow}}\n</$button>\n</span>\n\n<$reveal state=<<qualify \"$:/state/filterDropdown\">> type=\"popup\" position=\"belowleft\" animate=\"yes\">\n<$linkcatcher to=\"$:/temp/advancedsearch\">\n<div class=\"tc-block-dropdown-wrapper\">\n<div class=\"tc-block-dropdown tc-edit-type-dropdown\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Filter]]\"><$link to={{!!filter}}><$transclude field=\"description\"/></$link>\n</$list>\n</div>\n</div>\n</$linkcatcher>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Filter/FilterButtons/export": {
"title": "$:/core/ui/AdvancedSearch/Filter/FilterButtons/export",
"tags": "$:/tags/AdvancedSearch/FilterButton",
"text": "<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$macrocall $name=\"exportButton\" exportFilter={{$:/temp/advancedsearch}} lingoBase=\"$:/language/Buttons/ExportTiddlers/\"/>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Shadows": {
"title": "$:/core/ui/AdvancedSearch/Shadows",
"tags": "$:/tags/AdvancedSearch",
"caption": "{{$:/language/Search/Shadows/Caption}}",
"text": "\\define lingo-base() $:/language/Search/\n<$linkcatcher to=\"$:/temp/advancedsearch\">\n\n<<lingo Shadows/Hint>>\n\n<div class=\"tc-search\">\n<$edit-text tiddler=\"$:/temp/advancedsearch\" type=\"search\" tag=\"input\"/>\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" $field=\"text\" $value=\"\"/>\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n</div>\n\n</$linkcatcher>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n\n<$set name=\"resultCount\" value=\"\"\"<$count filter=\"[all[shadows]search{$:/temp/advancedsearch}] -[[$:/temp/advancedsearch]]\"/>\"\"\">\n\n<div class=\"tc-search-results\">\n\n<<lingo Shadows/Matches>>\n\n<$list filter=\"[all[shadows]search{$:/temp/advancedsearch}sort[title]limit[250]] -[[$:/temp/advancedsearch]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n\n</div>\n\n</$set>\n\n</$reveal>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"match\" text=\"\">\n\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/Standard": {
"title": "$:/core/ui/AdvancedSearch/Standard",
"tags": "$:/tags/AdvancedSearch",
"caption": "{{$:/language/Search/Standard/Caption}}",
"text": "\\define lingo-base() $:/language/Search/\n<$linkcatcher to=\"$:/temp/advancedsearch\">\n\n<<lingo Standard/Hint>>\n\n<div class=\"tc-search\">\n<$edit-text tiddler=\"$:/temp/advancedsearch\" type=\"search\" tag=\"input\"/>\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" $field=\"text\" $value=\"\"/>\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n</div>\n\n</$linkcatcher>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$set name=\"searchTiddler\" value=\"$:/temp/advancedsearch\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]butfirst[]limit[1]]\" emptyMessage=\"\"\"\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]]\">\n<$transclude/>\n</$list>\n\"\"\">\n<$macrocall $name=\"tabs\" tabsList=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]]\" default={{$:/config/SearchResults/Default}}/>\n</$list>\n</$set>\n</$reveal>\n"
},
"$:/core/ui/AdvancedSearch/System": {
"title": "$:/core/ui/AdvancedSearch/System",
"tags": "$:/tags/AdvancedSearch",
"caption": "{{$:/language/Search/System/Caption}}",
"text": "\\define lingo-base() $:/language/Search/\n<$linkcatcher to=\"$:/temp/advancedsearch\">\n\n<<lingo System/Hint>>\n\n<div class=\"tc-search\">\n<$edit-text tiddler=\"$:/temp/advancedsearch\" type=\"search\" tag=\"input\"/>\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" $field=\"text\" $value=\"\"/>\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n</div>\n\n</$linkcatcher>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"nomatch\" text=\"\">\n\n<$set name=\"resultCount\" value=\"\"\"<$count filter=\"[is[system]search{$:/temp/advancedsearch}] -[[$:/temp/advancedsearch]]\"/>\"\"\">\n\n<div class=\"tc-search-results\">\n\n<<lingo System/Matches>>\n\n<$list filter=\"[is[system]search{$:/temp/advancedsearch}sort[title]limit[250]] -[[$:/temp/advancedsearch]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n\n</div>\n\n</$set>\n\n</$reveal>\n\n<$reveal state=\"$:/temp/advancedsearch\" type=\"match\" text=\"\">\n\n</$reveal>\n"
},
"$:/AdvancedSearch": {
"title": "$:/AdvancedSearch",
"icon": "$:/core/images/advanced-search-button",
"color": "#bbb",
"text": "<div class=\"tc-advanced-search\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/AdvancedSearch]!has[draft.of]]\" \"$:/core/ui/AdvancedSearch/System\">>\n</div>\n"
},
"$:/core/ui/AlertTemplate": {
"title": "$:/core/ui/AlertTemplate",
"text": "<div class=\"tc-alert\">\n<div class=\"tc-alert-toolbar\">\n<$button class=\"tc-btn-invisible\"><$action-deletetiddler $tiddler=<<currentTiddler>>/>{{$:/core/images/delete-button}}</$button>\n</div>\n<div class=\"tc-alert-subtitle\">\n<$view field=\"component\"/> - <$view field=\"modified\" format=\"date\" template=\"0hh:0mm:0ss DD MM YYYY\"/> <$reveal type=\"nomatch\" state=\"!!count\" text=\"\"><span class=\"tc-alert-highlight\">({{$:/language/Count}}: <$view field=\"count\"/>)</span></$reveal>\n</div>\n<div class=\"tc-alert-body\">\n\n<$transclude/>\n\n</div>\n</div>\n"
},
"$:/core/ui/BinaryWarning": {
"title": "$:/core/ui/BinaryWarning",
"text": "\\define lingo-base() $:/language/BinaryWarning/\n<div class=\"tc-binary-warning\">\n\n<<lingo Prompt>>\n\n</div>\n"
},
"$:/core/ui/Components/tag-link": {
"title": "$:/core/ui/Components/tag-link",
"text": "<$link>\n<$set name=\"backgroundColor\" value={{!!color}}>\n<span style=<<tag-styles>> class=\"tc-tag-label\">\n<$view field=\"title\" format=\"text\"/>\n</span>\n</$set>\n</$link>"
},
"$:/core/ui/ControlPanel/Advanced": {
"title": "$:/core/ui/ControlPanel/Advanced",
"tags": "$:/tags/ControlPanel/Info",
"caption": "{{$:/language/ControlPanel/Advanced/Caption}}",
"text": "{{$:/language/ControlPanel/Advanced/Hint}}\n\n<div class=\"tc-control-panel\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/ControlPanel/Advanced]!has[draft.of]]\" \"$:/core/ui/ControlPanel/TiddlerFields\">>\n</div>\n"
},
"$:/core/ui/ControlPanel/Appearance": {
"title": "$:/core/ui/ControlPanel/Appearance",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/Appearance/Caption}}",
"text": "{{$:/language/ControlPanel/Appearance/Hint}}\n\n<div class=\"tc-control-panel\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/ControlPanel/Appearance]!has[draft.of]]\" \"$:/core/ui/ControlPanel/Theme\">>\n</div>\n"
},
"$:/core/ui/ControlPanel/Basics": {
"title": "$:/core/ui/ControlPanel/Basics",
"tags": "$:/tags/ControlPanel/Info",
"caption": "{{$:/language/ControlPanel/Basics/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Basics/\n\n\\define show-filter-count(filter)\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" $value=\"\"\"$filter$\"\"\"/>\n<$action-setfield $tiddler=\"$:/state/tab--1498284803\" $value=\"$:/core/ui/AdvancedSearch/Filter\"/>\n<$action-navigate $to=\"$:/AdvancedSearch\"/>\n''<$count filter=\"\"\"$filter$\"\"\"/>''\n{{$:/core/images/advanced-search-button}}\n</$button>\n\\end\n\n|<<lingo Version/Prompt>> |''<<version>>'' |\n|<$link to=\"$:/SiteTitle\"><<lingo Title/Prompt>></$link> |<$edit-text tiddler=\"$:/SiteTitle\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/SiteSubtitle\"><<lingo Subtitle/Prompt>></$link> |<$edit-text tiddler=\"$:/SiteSubtitle\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/status/UserName\"><<lingo Username/Prompt>></$link> |<$edit-text tiddler=\"$:/status/UserName\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/config/AnimationDuration\"><<lingo AnimDuration/Prompt>></$link> |<$edit-text tiddler=\"$:/config/AnimationDuration\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/DefaultTiddlers\"><<lingo DefaultTiddlers/Prompt>></$link> |<<lingo DefaultTiddlers/TopHint>><br> <$edit tag=\"textarea\" tiddler=\"$:/DefaultTiddlers\" class=\"tc-edit-texteditor\"/><br>//<<lingo DefaultTiddlers/BottomHint>>// |\n|<$link to=\"$:/config/NewJournal/Title\"><<lingo NewJournal/Title/Prompt>></$link> |<$edit-text tiddler=\"$:/config/NewJournal/Title\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/config/NewJournal/Tags\"><<lingo NewJournal/Tags/Prompt>></$link> |<$edit-text tiddler=\"$:/config/NewJournal/Tags\" default=\"\" tag=\"input\"/> |\n|<<lingo Language/Prompt>> |{{$:/snippets/minilanguageswitcher}} |\n|<<lingo Tiddlers/Prompt>> |<<show-filter-count \"[!is[system]sort[title]]\">> |\n|<<lingo Tags/Prompt>> |<<show-filter-count \"[tags[]sort[title]]\">> |\n|<<lingo SystemTiddlers/Prompt>> |<<show-filter-count \"[is[system]sort[title]]\">> |\n|<<lingo ShadowTiddlers/Prompt>> |<<show-filter-count \"[all[shadows]sort[title]]\">> |\n|<<lingo OverriddenShadowTiddlers/Prompt>> |<<show-filter-count \"[is[tiddler]is[shadow]sort[title]]\">> |\n"
},
"$:/core/ui/ControlPanel/EditorTypes": {
"title": "$:/core/ui/ControlPanel/EditorTypes",
"tags": "$:/tags/ControlPanel/Advanced",
"caption": "{{$:/language/ControlPanel/EditorTypes/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/EditorTypes/\n\n<<lingo Hint>>\n\n<table>\n<tbody>\n<tr>\n<th><<lingo Type/Caption>></th>\n<th><<lingo Editor/Caption>></th>\n</tr>\n<$list filter=\"[all[shadows+tiddlers]prefix[$:/config/EditorTypeMappings/]sort[title]]\">\n<tr>\n<td>\n<$link>\n<$list filter=\"[all[current]removeprefix[$:/config/EditorTypeMappings/]]\">\n<$text text={{!!title}}/>\n</$list>\n</$link>\n</td>\n<td>\n<$view field=\"text\"/>\n</td>\n</tr>\n</$list>\n</tbody>\n</table>\n"
},
"$:/core/ui/ControlPanel/Info": {
"title": "$:/core/ui/ControlPanel/Info",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/Info/Caption}}",
"text": "{{$:/language/ControlPanel/Info/Hint}}\n\n<div class=\"tc-control-panel\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/ControlPanel/Info]!has[draft.of]]\" \"$:/core/ui/ControlPanel/Basics\">>\n</div>\n"
},
"$:/core/ui/ControlPanel/KeyboardShortcuts": {
"title": "$:/core/ui/ControlPanel/KeyboardShortcuts",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/KeyboardShortcuts/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/KeyboardShortcuts/\n\n\\define new-shortcut(title)\n<div class=\"tc-dropdown-item-plain\">\n<$edit-shortcut tiddler=\"$title$\" placeholder={{$:/language/ControlPanel/KeyboardShortcuts/Add/Prompt}} style=\"width:auto;\"/> <$button>\n<<lingo Add/Caption>>\n<$action-listops\n\t$tiddler=\"$(shortcutTitle)$\"\n\t$field=\"text\"\n\t$subfilter=\"[{$title$}]\"\n/>\n<$action-deletetiddler\n\t$tiddler=\"$title$\"\n/>\n</$button>\n</div>\n\\end\n\n\\define shortcut-list-item(caption)\n<td>\n</td>\n<td style=\"text-align:right;font-size:0.7em;\">\n<<lingo Platform/$caption$>>\n</td>\n<td>\n<div style=\"position:relative;\">\n<$button popup=<<qualify \"$:/state/dropdown/$(shortcutTitle)$\">> class=\"tc-btn-invisible\">\n{{$:/core/images/edit-button}}\n</$button>\n<$macrocall $name=\"displayshortcuts\" $output=\"text/html\" shortcuts={{$(shortcutTitle)$}} prefix=\"<kbd>\" separator=\"</kbd> <kbd>\" suffix=\"</kbd>\"/>\n\n<$reveal state=<<qualify \"$:/state/dropdown/$(shortcutTitle)$\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-block-dropdown-wrapper\">\n<div class=\"tc-block-dropdown tc-edit-type-dropdown tc-popup-keep\">\n<$list filter=\"[list[$(shortcutTitle)$!!text]sort[title]]\" variable=\"shortcut\" emptyMessage=\"\"\"\n<div class=\"tc-dropdown-item-plain\">\n//<<lingo NoShortcuts/Caption>>//\n</div>\n\"\"\">\n<div class=\"tc-dropdown-item-plain\">\n<$button class=\"tc-btn-invisible\" tooltip=<<lingo Remove/Hint>>>\n<$action-listops\n\t$tiddler=\"$(shortcutTitle)$\"\n\t$field=\"text\"\n\t$subfilter=\"+[remove<shortcut>]\"\n/>\n×\n</$button>\n<kbd>\n<$macrocall $name=\"displayshortcuts\" $output=\"text/html\" shortcuts=<<shortcut>>/>\n</kbd>\n</div>\n</$list>\n<hr/>\n<$macrocall $name=\"new-shortcut\" title=<<qualify \"$:/state/new-shortcut/$(shortcutTitle)$\">>/>\n</div>\n</div>\n</$reveal>\n</div>\n</td>\n\\end\n\n\\define shortcut-list(caption,prefix)\n<tr>\n<$list filter=\"[all[tiddlers+shadows][$prefix$$(shortcutName)$]]\" variable=\"shortcutTitle\">\n<<shortcut-list-item \"$caption$\">>\n</$list>\n</tr>\n\\end\n\n\\define shortcut-editor()\n<<shortcut-list \"All\" \"$:/config/shortcuts/\">>\n<<shortcut-list \"Mac\" \"$:/config/shortcuts-mac/\">>\n<<shortcut-list \"NonMac\" \"$:/config/shortcuts-not-mac/\">>\n<<shortcut-list \"Linux\" \"$:/config/shortcuts-linux/\">>\n<<shortcut-list \"NonLinux\" \"$:/config/shortcuts-not-linux/\">>\n<<shortcut-list \"Windows\" \"$:/config/shortcuts-windows/\">>\n<<shortcut-list \"NonWindows\" \"$:/config/shortcuts-not-windows/\">>\n\\end\n\n\\define shortcut-preview()\n<$macrocall $name=\"displayshortcuts\" $output=\"text/html\" shortcuts={{$(shortcutPrefix)$$(shortcutName)$}} prefix=\"<kbd>\" separator=\"</kbd> <kbd>\" suffix=\"</kbd>\"/>\n\\end\n\n\\define shortcut-item-inner()\n<tr>\n<td>\n<$reveal type=\"nomatch\" state=<<dropdownStateTitle>> text=\"open\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield\n\t$tiddler=<<dropdownStateTitle>>\n\t$value=\"open\"\n/>\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<dropdownStateTitle>> text=\"open\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield\n\t$tiddler=<<dropdownStateTitle>>\n\t$value=\"close\"\n/>\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n''<$text text=<<shortcutName>>/>''\n</td>\n<td>\n<$transclude tiddler=\"$:/config/ShortcutInfo/$(shortcutName)$\"/>\n</td>\n<td>\n<$list filter=\"$:/config/shortcuts/ $:/config/shortcuts-mac/ $:/config/shortcuts-not-mac/ $:/config/shortcuts-linux/ $:/config/shortcuts-not-linux/ $:/config/shortcuts-windows/ $:/config/shortcuts-not-windows/\" variable=\"shortcutPrefix\">\n<<shortcut-preview>>\n</$list>\n</td>\n</tr>\n<$set name=\"dropdownState\" value={{$(dropdownStateTitle)$}}>\n<$list filter=\"[<dropdownState>prefix[open]]\" variable=\"listItem\">\n<<shortcut-editor>>\n</$list>\n</$set>\n\\end\n\n\\define shortcut-item()\n<$set name=\"dropdownStateTitle\" value=<<qualify \"$:/state/dropdown/keyboardshortcut/$(shortcutName)$\">>>\n<<shortcut-item-inner>>\n</$set>\n\\end\n\n<table>\n<tbody>\n<$list filter=\"[all[shadows+tiddlers]removeprefix[$:/config/ShortcutInfo/]]\" variable=\"shortcutName\">\n<<shortcut-item>>\n</$list>\n</tbody>\n</table>\n"
},
"$:/core/ui/ControlPanel/LoadedModules": {
"title": "$:/core/ui/ControlPanel/LoadedModules",
"tags": "$:/tags/ControlPanel/Advanced",
"caption": "{{$:/language/ControlPanel/LoadedModules/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/\n<<lingo LoadedModules/Hint>>\n\n{{$:/snippets/modules}}\n"
},
"$:/core/ui/ControlPanel/Modals/AddPlugins": {
"title": "$:/core/ui/ControlPanel/Modals/AddPlugins",
"subtitle": "{{$:/core/images/download-button}} {{$:/language/ControlPanel/Plugins/Add/Caption}}",
"text": "\\define install-plugin-button()\n<$button>\n<$action-sendmessage $message=\"tm-load-plugin-from-library\" url={{!!url}} title={{$(assetInfo)$!!original-title}}/>\n<$list filter=\"[<assetInfo>get[original-title]get[version]]\" variable=\"installedVersion\" emptyMessage=\"\"\"{{$:/language/ControlPanel/Plugins/Install/Caption}}\"\"\">\n{{$:/language/ControlPanel/Plugins/Reinstall/Caption}}\n</$list>\n</$button>\n\\end\n\n\\define popup-state-macro()\n$:/state/add-plugin-info/$(connectionTiddler)$/$(assetInfo)$\n\\end\n\n\\define display-plugin-info(type)\n<$set name=\"popup-state\" value=<<popup-state-macro>>>\n<div class=\"tc-plugin-info\">\n<div class=\"tc-plugin-info-chunk tc-small-icon\">\n<$reveal type=\"nomatch\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"yes\">\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"no\">\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<$list filter=\"[<assetInfo>has[icon]]\" emptyMessage=\"\"\"<$transclude tiddler=\"$:/core/images/plugin-generic-$type$\"/>\"\"\">\n<img src={{$(assetInfo)$!!icon}}/>\n</$list>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<h1><$view tiddler=<<assetInfo>> field=\"description\"/></h1>\n<h2><$view tiddler=<<assetInfo>> field=\"original-title\"/></h2>\n<div><em><$view tiddler=<<assetInfo>> field=\"version\"/></em></div>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<<install-plugin-button>>\n</div>\n</div>\n<$reveal type=\"match\" text=\"yes\" state=<<popup-state>>>\n<div class=\"tc-plugin-info-dropdown\">\n<div class=\"tc-plugin-info-dropdown-message\">\n<$list filter=\"[<assetInfo>get[original-title]get[version]]\" variable=\"installedVersion\" emptyMessage=\"\"\"{{$:/language/ControlPanel/Plugins/NotInstalled/Hint}}\"\"\">\n<em>\n{{$:/language/ControlPanel/Plugins/AlreadyInstalled/Hint}}\n</em>\n</$list>\n</div>\n<div class=\"tc-plugin-info-dropdown-body\">\n<$transclude tiddler=<<assetInfo>> field=\"readme\" mode=\"block\"/>\n</div>\n</div>\n</$reveal>\n</$set>\n\\end\n\n\\define load-plugin-library-button()\n<$button class=\"tc-btn-big-green\">\n<$action-sendmessage $message=\"tm-load-plugin-library\" url={{!!url}} infoTitlePrefix=\"$:/temp/RemoteAssetInfo/\"/>\n{{$:/core/images/chevron-right}} {{$:/language/ControlPanel/Plugins/OpenPluginLibrary}}\n</$button>\n\\end\n\n\\define display-server-assets(type)\n{{$:/language/Search/Search}}: <$edit-text tiddler=\"\"\"$:/temp/RemoteAssetSearch/$(currentTiddler)$\"\"\" default=\"\" type=\"search\" tag=\"input\"/>\n<$reveal state=\"\"\"$:/temp/RemoteAssetSearch/$(currentTiddler)$\"\"\" type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"\"\"$:/temp/RemoteAssetSearch/$(currentTiddler)$\"\"\" $field=\"text\" $value=\"\"/>\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n<div class=\"tc-plugin-library-listing\">\n<$list filter=\"[all[tiddlers+shadows]tag[$:/tags/RemoteAssetInfo]server-url{!!url}original-plugin-type[$type$]search{$:/temp/RemoteAssetSearch/$(currentTiddler)$}sort[description]]\" variable=\"assetInfo\">\n<<display-plugin-info \"$type$\">>\n</$list>\n</div>\n\\end\n\n\\define display-server-connection()\n<$list filter=\"[all[tiddlers+shadows]tag[$:/tags/ServerConnection]suffix{!!url}]\" variable=\"connectionTiddler\" emptyMessage=<<load-plugin-library-button>>>\n\n<<tabs \"[[$:/core/ui/ControlPanel/Plugins/Add/Plugins]] [[$:/core/ui/ControlPanel/Plugins/Add/Themes]] [[$:/core/ui/ControlPanel/Plugins/Add/Languages]]\" \"$:/core/ui/ControlPanel/Plugins/Add/Plugins\">>\n\n</$list>\n\\end\n\n\\define plugin-library-listing()\n<$list filter=\"[all[tiddlers+shadows]tag[$:/tags/PluginLibrary]]\">\n<div class=\"tc-plugin-library\">\n\n!! <$link><$transclude field=\"caption\"><$view field=\"title\"/></$transclude></$link>\n\n//<$view field=\"url\"/>//\n\n<$transclude/>\n\n<<display-server-connection>>\n</div>\n</$list>\n\\end\n\n<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n\n<div>\n<<plugin-library-listing>>\n</div>\n\n</$importvariables>\n"
},
"$:/core/ui/ControlPanel/Palette": {
"title": "$:/core/ui/ControlPanel/Palette",
"tags": "$:/tags/ControlPanel/Appearance",
"caption": "{{$:/language/ControlPanel/Palette/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Palette/\n\n{{$:/snippets/paletteswitcher}}\n\n<$reveal type=\"nomatch\" state=\"$:/state/ShowPaletteEditor\" text=\"yes\">\n\n<$button set=\"$:/state/ShowPaletteEditor\" setTo=\"yes\"><<lingo ShowEditor/Caption>></$button>\n\n</$reveal>\n\n<$reveal type=\"match\" state=\"$:/state/ShowPaletteEditor\" text=\"yes\">\n\n<$button set=\"$:/state/ShowPaletteEditor\" setTo=\"no\"><<lingo HideEditor/Caption>></$button>\n{{$:/snippets/paletteeditor}}\n\n</$reveal>\n\n"
},
"$:/core/ui/ControlPanel/Parsing": {
"title": "$:/core/ui/ControlPanel/Parsing",
"tags": "$:/tags/ControlPanel/Advanced",
"caption": "{{$:/language/ControlPanel/Parsing/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Parsing/\n\n\\define parsing-inner(typeCap)\n<li>\n<$checkbox tiddler=\"\"\"$:/config/WikiParserRules/$typeCap$/$(currentTiddler)$\"\"\" field=\"text\" checked=\"enable\" unchecked=\"disable\" default=\"enable\"> ''<$text text=<<currentTiddler>>/>'': </$checkbox>\n</li>\n\\end\n\n\\define parsing-outer(typeLower,typeCap)\n<ul>\n<$list filter=\"[wikiparserrules[$typeLower$]]\">\n<<parsing-inner typeCap:\"$typeCap$\">>\n</$list>\n</ul>\n\\end\n\n<<lingo Hint>>\n\n! <<lingo Pragma/Caption>>\n\n<<parsing-outer typeLower:\"pragma\" typeCap:\"Pragma\">>\n\n! <<lingo Inline/Caption>>\n\n<<parsing-outer typeLower:\"inline\" typeCap:\"Inline\">>\n\n! <<lingo Block/Caption>>\n\n<<parsing-outer typeLower:\"block\" typeCap:\"Block\">>\n"
},
"$:/core/ui/ControlPanel/Plugins/Add/Languages": {
"title": "$:/core/ui/ControlPanel/Plugins/Add/Languages",
"caption": "{{$:/language/ControlPanel/Plugins/Languages/Caption}} (<$count filter=\"[all[tiddlers+shadows]tag[$:/tags/RemoteAssetInfo]server-url{!!url}original-plugin-type[language]]\"/>)",
"text": "<<display-server-assets language>>\n"
},
"$:/core/ui/ControlPanel/Plugins/Add/Plugins": {
"title": "$:/core/ui/ControlPanel/Plugins/Add/Plugins",
"caption": "{{$:/language/ControlPanel/Plugins/Plugins/Caption}} (<$count filter=\"[all[tiddlers+shadows]tag[$:/tags/RemoteAssetInfo]server-url{!!url}original-plugin-type[plugin]]\"/>)",
"text": "<<display-server-assets plugin>>\n"
},
"$:/core/ui/ControlPanel/Plugins/Add/Themes": {
"title": "$:/core/ui/ControlPanel/Plugins/Add/Themes",
"caption": "{{$:/language/ControlPanel/Plugins/Themes/Caption}} (<$count filter=\"[all[tiddlers+shadows]tag[$:/tags/RemoteAssetInfo]server-url{!!url}original-plugin-type[theme]]\"/>)",
"text": "<<display-server-assets theme>>\n"
},
"$:/core/ui/ControlPanel/Plugins/AddPlugins": {
"title": "$:/core/ui/ControlPanel/Plugins/AddPlugins",
"text": "\\define lingo-base() $:/language/ControlPanel/Plugins/\n\n<$button message=\"tm-modal\" param=\"$:/core/ui/ControlPanel/Modals/AddPlugins\" tooltip={{$:/language/ControlPanel/Plugins/Add/Hint}} class=\"tc-btn-big-green\" style=\"background:blue;\">\n{{$:/core/images/download-button}} <<lingo Add/Caption>>\n</$button>\n"
},
"$:/core/ui/ControlPanel/Plugins/Installed/Languages": {
"title": "$:/core/ui/ControlPanel/Plugins/Installed/Languages",
"caption": "{{$:/language/ControlPanel/Plugins/Languages/Caption}} (<$count filter=\"[!has[draft.of]plugin-type[language]]\"/>)",
"text": "<<plugin-table language>>\n"
},
"$:/core/ui/ControlPanel/Plugins/Installed/Plugins": {
"title": "$:/core/ui/ControlPanel/Plugins/Installed/Plugins",
"caption": "{{$:/language/ControlPanel/Plugins/Plugins/Caption}} (<$count filter=\"[!has[draft.of]plugin-type[plugin]]\"/>)",
"text": "<<plugin-table plugin>>\n"
},
"$:/core/ui/ControlPanel/Plugins/Installed/Themes": {
"title": "$:/core/ui/ControlPanel/Plugins/Installed/Themes",
"caption": "{{$:/language/ControlPanel/Plugins/Themes/Caption}} (<$count filter=\"[!has[draft.of]plugin-type[theme]]\"/>)",
"text": "<<plugin-table theme>>\n"
},
"$:/core/ui/ControlPanel/Plugins": {
"title": "$:/core/ui/ControlPanel/Plugins",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/Plugins/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Plugins/\n\n\\define popup-state-macro()\n$(qualified-state)$-$(currentTiddler)$\n\\end\n\n\\define tabs-state-macro()\n$(popup-state)$-$(pluginInfoType)$\n\\end\n\n\\define plugin-icon-title()\n$(currentTiddler)$/icon\n\\end\n\n\\define plugin-disable-title()\n$:/config/Plugins/Disabled/$(currentTiddler)$\n\\end\n\n\\define plugin-table-body(type,disabledMessage)\n<div class=\"tc-plugin-info-chunk tc-small-icon\">\n<$reveal type=\"nomatch\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"yes\">\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"no\">\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<$transclude tiddler=<<currentTiddler>> subtiddler=<<plugin-icon-title>>>\n<$transclude tiddler=\"$:/core/images/plugin-generic-$type$\"/>\n</$transclude>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<h1>\n''<$view field=\"description\"><$view field=\"title\"/></$view>'' $disabledMessage$\n</h1>\n<h2>\n<$view field=\"title\"/>\n</h2>\n<h2>\n<div><em><$view field=\"version\"/></em></div>\n</h2>\n</div>\n\\end\n\n\\define plugin-table(type)\n<$set name=\"qualified-state\" value=<<qualify \"$:/state/plugin-info\">>>\n<$list filter=\"[!has[draft.of]plugin-type[$type$]sort[description]]\" emptyMessage=<<lingo \"Empty/Hint\">>>\n<$set name=\"popup-state\" value=<<popup-state-macro>>>\n<$reveal type=\"nomatch\" state=<<plugin-disable-title>> text=\"yes\">\n<$link to={{!!title}} class=\"tc-plugin-info\">\n<<plugin-table-body type:\"$type$\">>\n</$link>\n</$reveal>\n<$reveal type=\"match\" state=<<plugin-disable-title>> text=\"yes\">\n<$link to={{!!title}} class=\"tc-plugin-info tc-plugin-info-disabled\">\n<<plugin-table-body type:\"$type$\" disabledMessage:\"<$macrocall $name='lingo' title='Disabled/Status'/>\">>\n</$link>\n</$reveal>\n<$reveal type=\"match\" text=\"yes\" state=<<popup-state>>>\n<div class=\"tc-plugin-info-dropdown\">\n<div class=\"tc-plugin-info-dropdown-body\">\n<$list filter=\"[all[current]] -[[$:/core]]\">\n<div style=\"float:right;\">\n<$reveal type=\"nomatch\" state=<<plugin-disable-title>> text=\"yes\">\n<$button set=<<plugin-disable-title>> setTo=\"yes\" tooltip={{$:/language/ControlPanel/Plugins/Disable/Hint}} aria-label={{$:/language/ControlPanel/Plugins/Disable/Caption}}>\n<<lingo Disable/Caption>>\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<plugin-disable-title>> text=\"yes\">\n<$button set=<<plugin-disable-title>> setTo=\"no\" tooltip={{$:/language/ControlPanel/Plugins/Enable/Hint}} aria-label={{$:/language/ControlPanel/Plugins/Enable/Caption}}>\n<<lingo Enable/Caption>>\n</$button>\n</$reveal>\n</div>\n</$list>\n<$reveal type=\"nomatch\" text=\"\" state=\"!!list\">\n<$macrocall $name=\"tabs\" state=<<tabs-state-macro>> tabsList={{!!list}} default=\"readme\" template=\"$:/core/ui/PluginInfo\"/>\n</$reveal>\n<$reveal type=\"match\" text=\"\" state=\"!!list\">\n<<lingo NoInformation/Hint>>\n</$reveal>\n</div>\n</div>\n</$reveal>\n</$set>\n</$list>\n</$set>\n\\end\n\n{{$:/core/ui/ControlPanel/Plugins/AddPlugins}}\n\n<<lingo Installed/Hint>>\n\n<<tabs \"[[$:/core/ui/ControlPanel/Plugins/Installed/Plugins]] [[$:/core/ui/ControlPanel/Plugins/Installed/Themes]] [[$:/core/ui/ControlPanel/Plugins/Installed/Languages]]\" \"$:/core/ui/ControlPanel/Plugins/Installed/Plugins\">>\n"
},
"$:/core/ui/ControlPanel/Saving": {
"title": "$:/core/ui/ControlPanel/Saving",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/Saving/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Saving/\n\\define backupURL()\nhttp://$(userName)$.tiddlyspot.com/backup/\n\\end\n\\define backupLink()\n<$reveal type=\"nomatch\" state=\"$:/UploadName\" text=\"\">\n<$set name=\"userName\" value={{$:/UploadName}}>\n<$reveal type=\"match\" state=\"$:/UploadURL\" text=\"\">\n<<backupURL>>\n</$reveal>\n<$reveal type=\"nomatch\" state=\"$:/UploadURL\" text=\"\">\n<$macrocall $name=resolvePath source={{$:/UploadBackupDir}} root={{$:/UploadURL}}>>\n</$reveal>\n</$set>\n</$reveal>\n\\end\n! <<lingo TiddlySpot/Heading>>\n\n<<lingo TiddlySpot/Description>>\n\n|<<lingo TiddlySpot/UserName>> |<$edit-text tiddler=\"$:/UploadName\" default=\"\" tag=\"input\"/> |\n|<<lingo TiddlySpot/Password>> |<$password name=\"upload\"/> |\n|<<lingo TiddlySpot/Backups>> |<<backupLink>> |\n\n''<<lingo TiddlySpot/Advanced/Heading>>''\n\n|<<lingo TiddlySpot/ServerURL>> |<$edit-text tiddler=\"$:/UploadURL\" default=\"\" tag=\"input\"/> |\n|<<lingo TiddlySpot/Filename>> |<$edit-text tiddler=\"$:/UploadFilename\" default=\"index.html\" tag=\"input\"/> |\n|<<lingo TiddlySpot/UploadDir>> |<$edit-text tiddler=\"$:/UploadDir\" default=\".\" tag=\"input\"/> |\n|<<lingo TiddlySpot/BackupDir>> |<$edit-text tiddler=\"$:/UploadBackupDir\" default=\".\" tag=\"input\"/> |\n\n<<lingo TiddlySpot/Hint>>"
},
"$:/core/ui/ControlPanel/Settings/AutoSave": {
"title": "$:/core/ui/ControlPanel/Settings/AutoSave",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/AutoSave/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/AutoSave/\n\n<$link to=\"$:/config/AutoSave\"><<lingo Hint>></$link>\n\n<$radio tiddler=\"$:/config/AutoSave\" value=\"yes\"> <<lingo Enabled/Description>> </$radio>\n\n<$radio tiddler=\"$:/config/AutoSave\" value=\"no\"> <<lingo Disabled/Description>> </$radio>\n"
},
"$:/core/buttonstyles/Borderless": {
"title": "$:/core/buttonstyles/Borderless",
"tags": "$:/tags/ToolbarButtonStyle",
"caption": "{{$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Borderless}}",
"text": "tc-btn-invisible"
},
"$:/core/buttonstyles/Boxed": {
"title": "$:/core/buttonstyles/Boxed",
"tags": "$:/tags/ToolbarButtonStyle",
"caption": "{{$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Boxed}}",
"text": "tc-btn-boxed"
},
"$:/core/buttonstyles/Rounded": {
"title": "$:/core/buttonstyles/Rounded",
"tags": "$:/tags/ToolbarButtonStyle",
"caption": "{{$:/language/ControlPanel/Settings/ToolbarButtonStyle/Styles/Rounded}}",
"text": "tc-btn-rounded"
},
"$:/core/ui/ControlPanel/Settings/CamelCase": {
"title": "$:/core/ui/ControlPanel/Settings/CamelCase",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/CamelCase/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/CamelCase/\n<<lingo Hint>>\n\n<$checkbox tiddler=\"$:/config/WikiParserRules/Inline/wikilink\" field=\"text\" checked=\"enable\" unchecked=\"disable\" default=\"enable\"> <$link to=\"$:/config/WikiParserRules/Inline/wikilink\"><<lingo Description>></$link> </$checkbox>\n"
},
"$:/core/ui/ControlPanel/Settings/DefaultSidebarTab": {
"caption": "{{$:/language/ControlPanel/Settings/DefaultSidebarTab/Caption}}",
"tags": "$:/tags/ControlPanel/Settings",
"title": "$:/core/ui/ControlPanel/Settings/DefaultSidebarTab",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/DefaultSidebarTab/\n\n<$link to=\"$:/config/DefaultSidebarTab\"><<lingo Hint>></$link>\n\n<$select tiddler=\"$:/config/DefaultSidebarTab\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/SideBar]!has[draft.of]]\">\n<option value=<<currentTiddler>>><$transclude field=\"caption\"><$text text=<<currentTiddler>>/></$transclude></option>\n</$list>\n</$select>\n"
},
"$:/core/ui/ControlPanel/Settings/EditorToolbar": {
"title": "$:/core/ui/ControlPanel/Settings/EditorToolbar",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/EditorToolbar/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/EditorToolbar/\n<<lingo Hint>>\n\n<$checkbox tiddler=\"$:/config/TextEditor/EnableToolbar\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"yes\"> <$link to=\"$:/config/TextEditor/EnableToolbar\"><<lingo Description>></$link> </$checkbox>\n\n"
},
"$:/core/ui/ControlPanel/Settings/LinkToBehaviour": {
"title": "$:/core/ui/ControlPanel/Settings/LinkToBehaviour",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/LinkToBehaviour/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/LinkToBehaviour/\n\n<$link to=\"$:/config/Navigation/openLinkFromInsideRiver\"><<lingo \"InsideRiver/Hint\">></$link>\n\n<$select tiddler=\"$:/config/Navigation/openLinkFromInsideRiver\">\n <option value=\"above\"><<lingo \"OpenAbove\">></option>\n <option value=\"below\"><<lingo \"OpenBelow\">></option>\n <option value=\"top\"><<lingo \"OpenAtTop\">></option>\n <option value=\"bottom\"><<lingo \"OpenAtBottom\">></option>\n</$select>\n\n<$link to=\"$:/config/Navigation/openLinkFromOutsideRiver\"><<lingo \"OutsideRiver/Hint\">></$link>\n\n<$select tiddler=\"$:/config/Navigation/openLinkFromOutsideRiver\">\n <option value=\"top\"><<lingo \"OpenAtTop\">></option>\n <option value=\"bottom\"><<lingo \"OpenAtBottom\">></option>\n</$select>\n"
},
"$:/core/ui/ControlPanel/Settings/MissingLinks": {
"title": "$:/core/ui/ControlPanel/Settings/MissingLinks",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/MissingLinks/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/MissingLinks/\n<<lingo Hint>>\n\n<$checkbox tiddler=\"$:/config/MissingLinks\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"yes\"> <$link to=\"$:/config/MissingLinks\"><<lingo Description>></$link> </$checkbox>\n\n"
},
"$:/core/ui/ControlPanel/Settings/NavigationAddressBar": {
"title": "$:/core/ui/ControlPanel/Settings/NavigationAddressBar",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/NavigationAddressBar/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/NavigationAddressBar/\n\n<$link to=\"$:/config/Navigation/UpdateAddressBar\"><<lingo Hint>></$link>\n\n<$radio tiddler=\"$:/config/Navigation/UpdateAddressBar\" value=\"permaview\"> <<lingo Permaview/Description>> </$radio>\n\n<$radio tiddler=\"$:/config/Navigation/UpdateAddressBar\" value=\"permalink\"> <<lingo Permalink/Description>> </$radio>\n\n<$radio tiddler=\"$:/config/Navigation/UpdateAddressBar\" value=\"no\"> <<lingo No/Description>> </$radio>\n"
},
"$:/core/ui/ControlPanel/Settings/NavigationHistory": {
"title": "$:/core/ui/ControlPanel/Settings/NavigationHistory",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/NavigationHistory/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/NavigationHistory/\n<$link to=\"$:/config/Navigation/UpdateHistory\"><<lingo Hint>></$link>\n\n<$radio tiddler=\"$:/config/Navigation/UpdateHistory\" value=\"yes\"> <<lingo Yes/Description>> </$radio>\n\n<$radio tiddler=\"$:/config/Navigation/UpdateHistory\" value=\"no\"> <<lingo No/Description>> </$radio>\n"
},
"$:/core/ui/ControlPanel/Settings/PerformanceInstrumentation": {
"title": "$:/core/ui/ControlPanel/Settings/PerformanceInstrumentation",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/PerformanceInstrumentation/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/PerformanceInstrumentation/\n<<lingo Hint>>\n\n<$checkbox tiddler=\"$:/config/Performance/Instrumentation\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"no\"> <$link to=\"$:/config/Performance/Instrumentation\"><<lingo Description>></$link> </$checkbox>\n"
},
"$:/core/ui/ControlPanel/Settings/TitleLinks": {
"title": "$:/core/ui/ControlPanel/Settings/TitleLinks",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/TitleLinks/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/TitleLinks/\n<$link to=\"$:/config/Tiddlers/TitleLinks\"><<lingo Hint>></$link>\n\n<$radio tiddler=\"$:/config/Tiddlers/TitleLinks\" value=\"yes\"> <<lingo Yes/Description>> </$radio>\n\n<$radio tiddler=\"$:/config/Tiddlers/TitleLinks\" value=\"no\"> <<lingo No/Description>> </$radio>\n"
},
"$:/core/ui/ControlPanel/Settings/ToolbarButtonStyle": {
"title": "$:/core/ui/ControlPanel/Settings/ToolbarButtonStyle",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/ToolbarButtonStyle/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/ToolbarButtonStyle/\n<$link to=\"$:/config/Toolbar/ButtonClass\"><<lingo \"Hint\">></$link>\n\n<$select tiddler=\"$:/config/Toolbar/ButtonClass\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ToolbarButtonStyle]]\">\n<option value={{!!text}}>{{!!caption}}</option>\n</$list>\n</$select>\n"
},
"$:/core/ui/ControlPanel/Settings/ToolbarButtons": {
"title": "$:/core/ui/ControlPanel/Settings/ToolbarButtons",
"tags": "$:/tags/ControlPanel/Settings",
"caption": "{{$:/language/ControlPanel/Settings/ToolbarButtons/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/ToolbarButtons/\n<<lingo Hint>>\n\n<$checkbox tiddler=\"$:/config/Toolbar/Icons\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"yes\"> <$link to=\"$:/config/Toolbar/Icons\"><<lingo Icons/Description>></$link> </$checkbox>\n\n<$checkbox tiddler=\"$:/config/Toolbar/Text\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"no\"> <$link to=\"$:/config/Toolbar/Text\"><<lingo Text/Description>></$link> </$checkbox>\n"
},
"$:/core/ui/ControlPanel/Settings": {
"title": "$:/core/ui/ControlPanel/Settings",
"tags": "$:/tags/ControlPanel",
"caption": "{{$:/language/ControlPanel/Settings/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/Settings/\n\n<<lingo Hint>>\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ControlPanel/Settings]]\">\n\n<div style=\"border-top:1px solid #eee;\">\n\n!! <$link><$transclude field=\"caption\"/></$link>\n\n<$transclude/>\n\n</div>\n\n</$list>\n"
},
"$:/core/ui/ControlPanel/StoryView": {
"title": "$:/core/ui/ControlPanel/StoryView",
"tags": "$:/tags/ControlPanel/Appearance",
"caption": "{{$:/language/ControlPanel/StoryView/Caption}}",
"text": "{{$:/snippets/viewswitcher}}\n"
},
"$:/core/ui/ControlPanel/Theme": {
"title": "$:/core/ui/ControlPanel/Theme",
"tags": "$:/tags/ControlPanel/Appearance",
"caption": "{{$:/language/ControlPanel/Theme/Caption}}",
"text": "{{$:/snippets/themeswitcher}}\n"
},
"$:/core/ui/ControlPanel/TiddlerFields": {
"title": "$:/core/ui/ControlPanel/TiddlerFields",
"tags": "$:/tags/ControlPanel/Advanced",
"caption": "{{$:/language/ControlPanel/TiddlerFields/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/\n\n<<lingo TiddlerFields/Hint>>\n\n{{$:/snippets/allfields}}"
},
"$:/core/ui/ControlPanel/Toolbars/EditToolbar": {
"title": "$:/core/ui/ControlPanel/Toolbars/EditToolbar",
"tags": "$:/tags/ControlPanel/Toolbars",
"caption": "{{$:/language/ControlPanel/Toolbars/EditToolbar/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n\\define config-title()\n$:/config/EditToolbarButtons/Visibility/$(listItem)$\n\\end\n\n{{$:/language/ControlPanel/Toolbars/EditToolbar/Hint}}\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditToolbar]!has[draft.of]]\" variable=\"listItem\">\n\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"/> <$transclude tiddler=<<listItem>> field=\"caption\"/> <i class=\"tc-muted\">-- <$transclude tiddler=<<listItem>> field=\"description\"/></i>\n\n</$list>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/ControlPanel/Toolbars/EditorToolbar": {
"title": "$:/core/ui/ControlPanel/Toolbars/EditorToolbar",
"tags": "$:/tags/ControlPanel/Toolbars",
"caption": "{{$:/language/ControlPanel/Toolbars/EditorToolbar/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n\n\\define config-title()\n$:/config/EditorToolbarButtons/Visibility/$(listItem)$\n\\end\n\n\\define toolbar-button()\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"> <$transclude tiddler={{$(listItem)$!!icon}}/> <$transclude tiddler=<<listItem>> field=\"caption\"/> -- <i class=\"tc-muted\"><$transclude tiddler=<<listItem>> field=\"description\"/></i></$checkbox>\n\\end\n\n{{$:/language/ControlPanel/Toolbars/EditorToolbar/Hint}}\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditorToolbar]!has[draft.of]]\" variable=\"listItem\">\n\n<<toolbar-button>>\n\n</$list>\n"
},
"$:/core/ui/ControlPanel/Toolbars/PageControls": {
"title": "$:/core/ui/ControlPanel/Toolbars/PageControls",
"tags": "$:/tags/ControlPanel/Toolbars",
"caption": "{{$:/language/ControlPanel/Toolbars/PageControls/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n\\define config-title()\n$:/config/PageControlButtons/Visibility/$(listItem)$\n\\end\n\n{{$:/language/ControlPanel/Toolbars/PageControls/Hint}}\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/PageControls]!has[draft.of]]\" variable=\"listItem\">\n\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"/> <$transclude tiddler=<<listItem>> field=\"caption\"/> <i class=\"tc-muted\">-- <$transclude tiddler=<<listItem>> field=\"description\"/></i>\n\n</$list>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/ControlPanel/Toolbars/ViewToolbar": {
"title": "$:/core/ui/ControlPanel/Toolbars/ViewToolbar",
"tags": "$:/tags/ControlPanel/Toolbars",
"caption": "{{$:/language/ControlPanel/Toolbars/ViewToolbar/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n\\define config-title()\n$:/config/ViewToolbarButtons/Visibility/$(listItem)$\n\\end\n\n{{$:/language/ControlPanel/Toolbars/ViewToolbar/Hint}}\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ViewToolbar]!has[draft.of]]\" variable=\"listItem\">\n\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"/> <$transclude tiddler=<<listItem>> field=\"caption\"/> <i class=\"tc-muted\">-- <$transclude tiddler=<<listItem>> field=\"description\"/></i>\n\n</$list>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/ControlPanel/Toolbars": {
"title": "$:/core/ui/ControlPanel/Toolbars",
"tags": "$:/tags/ControlPanel/Appearance",
"caption": "{{$:/language/ControlPanel/Toolbars/Caption}}",
"text": "{{$:/language/ControlPanel/Toolbars/Hint}}\n\n<div class=\"tc-control-panel\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/ControlPanel/Toolbars]!has[draft.of]]\" \"$:/core/ui/ControlPanel/Toolbars/ViewToolbar\" \"$:/state/tabs/controlpanel/toolbars\" \"tc-vertical\">>\n</div>\n"
},
"$:/ControlPanel": {
"title": "$:/ControlPanel",
"icon": "$:/core/images/options-button",
"color": "#bbb",
"text": "<div class=\"tc-control-panel\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/ControlPanel]!has[draft.of]]\" \"$:/core/ui/ControlPanel/Info\">>\n</div>\n"
},
"$:/core/ui/DefaultSearchResultList": {
"title": "$:/core/ui/DefaultSearchResultList",
"tags": "$:/tags/SearchResults",
"caption": "{{$:/language/Search/DefaultResults/Caption}}",
"text": "\\define searchResultList()\n//<small>{{$:/language/Search/Matches/Title}}</small>//\n\n<$list filter=\"[!is[system]search:title{$(searchTiddler)$}sort[title]limit[250]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n\n//<small>{{$:/language/Search/Matches/All}}</small>//\n\n<$list filter=\"[!is[system]search{$(searchTiddler)$}sort[title]limit[250]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n\n\\end\n<<searchResultList>>\n"
},
"$:/core/ui/EditTemplate/body/preview/output": {
"title": "$:/core/ui/EditTemplate/body/preview/output",
"tags": "$:/tags/EditPreview",
"caption": "{{$:/language/EditTemplate/Body/Preview/Type/Output}}",
"text": "<$set name=\"tv-tiddler-preview\" value=\"yes\">\n\n<$transclude />\n\n</$set>\n"
},
"$:/core/ui/EditTemplate/body/editor": {
"title": "$:/core/ui/EditTemplate/body/editor",
"text": "<$edit\n\n field=\"text\"\n class=\"tc-edit-texteditor\"\n placeholder={{$:/language/EditTemplate/Body/Placeholder}}\n\n><$set\n\n name=\"targetTiddler\"\n value=<<currentTiddler>>\n\n><$list\n\n filter=\"[all[shadows+tiddlers]tag[$:/tags/EditorToolbar]!has[draft.of]]\"\n\n><$reveal\n\n type=\"nomatch\"\n state=<<config-visibility-title>>\n text=\"hide\"\n class=\"tc-text-editor-toolbar-item-wrapper\"\n\n><$transclude\n\n tiddler=\"$:/core/ui/EditTemplate/body/toolbar/button\"\n mode=\"inline\"\n\n/></$reveal></$list></$set></$edit>\n"
},
"$:/core/ui/EditTemplate/body/toolbar/button": {
"title": "$:/core/ui/EditTemplate/body/toolbar/button",
"text": "\\define toolbar-button-icon()\n<$list\n\n filter=\"[all[current]!has[custom-icon]]\"\n variable=\"no-custom-icon\"\n\n><$transclude\n\n tiddler={{!!icon}}\n\n/></$list>\n\\end\n\n\\define toolbar-button-tooltip()\n{{!!description}}<$macrocall $name=\"displayshortcuts\" $output=\"text/plain\" shortcuts={{!!shortcuts}} prefix=\"` - [\" separator=\"] [\" suffix=\"]`\"/>\n\\end\n\n\\define toolbar-button()\n<$list\n\n filter={{!!condition}}\n variable=\"list-condition\"\n\n><$wikify\n\n name=\"tooltip-text\"\n text=<<toolbar-button-tooltip>>\n mode=\"inline\"\n output=\"text\"\n\n><$list\n\n filter=\"[all[current]!has[dropdown]]\"\n variable=\"no-dropdown\"\n\n><$button\n\n class=\"tc-btn-invisible $(buttonClasses)$\"\n tooltip=<<tooltip-text>>\n\n><span\n\n data-tw-keyboard-shortcut={{!!shortcuts}}\n\n/><<toolbar-button-icon>><$transclude\n\n tiddler=<<currentTiddler>>\n field=\"text\"\n\n/></$button></$list><$list\n\n filter=\"[all[current]has[dropdown]]\"\n variable=\"dropdown\"\n\n><$set\n\n name=\"dropdown-state\"\n value=<<qualify \"$:/state/EditorToolbarDropdown\">>\n\n><$button\n\n popup=<<dropdown-state>>\n class=\"tc-popup-keep tc-btn-invisible $(buttonClasses)$\"\n selectedClass=\"tc-selected\"\n tooltip=<<tooltip-text>>\n\n><span\n\n data-tw-keyboard-shortcut={{!!shortcuts}}\n\n/><<toolbar-button-icon>><$transclude\n\n tiddler=<<currentTiddler>>\n field=\"text\"\n\n/></$button><$reveal\n\n state=<<dropdown-state>>\n type=\"popup\"\n position=\"below\"\n animate=\"yes\"\n tag=\"span\"\n\n><div\n\n class=\"tc-drop-down tc-popup-keep\"\n\n><$transclude\n\n tiddler={{!!dropdown}}\n mode=\"block\"\n\n/></div></$reveal></$set></$list></$wikify></$list>\n\\end\n\n\\define toolbar-button-outer()\n<$set\n\n name=\"buttonClasses\"\n value={{!!button-classes}}\n\n><<toolbar-button>></$set>\n\\end\n\n<<toolbar-button-outer>>"
},
"$:/core/ui/EditTemplate/body": {
"title": "$:/core/ui/EditTemplate/body",
"tags": "$:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/EditTemplate/Body/\n\\define config-visibility-title()\n$:/config/EditorToolbarButtons/Visibility/$(currentTiddler)$\n\\end\n<$list filter=\"[is[current]has[_canonical_uri]]\">\n\n<div class=\"tc-message-box\">\n\n<<lingo External/Hint>>\n\n<a href={{!!_canonical_uri}}><$text text={{!!_canonical_uri}}/></a>\n\n<$edit-text field=\"_canonical_uri\" class=\"tc-edit-fields\"></$edit-text>\n\n</div>\n\n</$list>\n\n<$list filter=\"[is[current]!has[_canonical_uri]]\">\n\n<$reveal state=\"$:/state/showeditpreview\" type=\"match\" text=\"yes\">\n\n<div class=\"tc-tiddler-preview\">\n\n<$transclude tiddler=\"$:/core/ui/EditTemplate/body/editor\" mode=\"inline\"/>\n\n<div class=\"tc-tiddler-preview-preview\">\n\n<$transclude tiddler={{$:/state/editpreviewtype}} mode=\"inline\">\n\n<$transclude tiddler=\"$:/core/ui/EditTemplate/body/preview/output\" mode=\"inline\"/>\n\n</$transclude>\n\n</div>\n\n</div>\n\n</$reveal>\n\n<$reveal state=\"$:/state/showeditpreview\" type=\"nomatch\" text=\"yes\">\n\n<$transclude tiddler=\"$:/core/ui/EditTemplate/body/editor\" mode=\"inline\"/>\n\n</$reveal>\n\n</$list>\n"
},
"$:/core/ui/EditTemplate/controls": {
"title": "$:/core/ui/EditTemplate/controls",
"tags": "$:/tags/EditTemplate",
"text": "\\define config-title()\n$:/config/EditToolbarButtons/Visibility/$(listItem)$\n\\end\n<div class=\"tc-tiddler-title tc-tiddler-edit-title\">\n<$view field=\"title\"/>\n<span class=\"tc-tiddler-controls tc-titlebar\"><$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditToolbar]!has[draft.of]]\" variable=\"listItem\"><$reveal type=\"nomatch\" state=<<config-title>> text=\"hide\"><$transclude tiddler=<<listItem>>/></$reveal></$list></span>\n<div style=\"clear: both;\"></div>\n</div>\n"
},
"$:/core/ui/EditTemplate/fields": {
"title": "$:/core/ui/EditTemplate/fields",
"tags": "$:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/EditTemplate/\n\\define config-title()\n$:/config/EditTemplateFields/Visibility/$(currentField)$\n\\end\n\n\\define config-filter()\n[[hide]] -[title{$(config-title)$}]\n\\end\n\n\\define new-field-inner()\n<$reveal type=\"nomatch\" text=\"\" default=<<name>>>\n<$button>\n<$action-sendmessage $message=\"tm-add-field\" $name=<<name>> $value=<<value>>/>\n<$action-deletetiddler $tiddler=\"$:/temp/newfieldname\"/>\n<$action-deletetiddler $tiddler=\"$:/temp/newfieldvalue\"/>\n<<lingo Fields/Add/Button>>\n</$button>\n</$reveal>\n<$reveal type=\"match\" text=\"\" default=<<name>>>\n<$button>\n<<lingo Fields/Add/Button>>\n</$button>\n</$reveal>\n\\end\n\n\\define new-field()\n<$set name=\"name\" value={{$:/temp/newfieldname}}>\n<$set name=\"value\" value={{$:/temp/newfieldvalue}}>\n<<new-field-inner>>\n</$set>\n</$set>\n\\end\n\n<div class=\"tc-edit-fields\">\n<table class=\"tc-edit-fields\">\n<tbody>\n<$list filter=\"[all[current]fields[]] +[sort[title]]\" variable=\"currentField\">\n<$list filter=<<config-filter>> variable=\"temp\">\n<tr class=\"tc-edit-field\">\n<td class=\"tc-edit-field-name\">\n<$text text=<<currentField>>/>:</td>\n<td class=\"tc-edit-field-value\">\n<$edit-text tiddler=<<currentTiddler>> field=<<currentField>> placeholder={{$:/language/EditTemplate/Fields/Add/Value/Placeholder}}/>\n</td>\n<td class=\"tc-edit-field-remove\">\n<$button class=\"tc-btn-invisible\" tooltip={{$:/language/EditTemplate/Field/Remove/Hint}} aria-label={{$:/language/EditTemplate/Field/Remove/Caption}}>\n<$action-deletefield $field=<<currentField>>/>\n{{$:/core/images/delete-button}}\n</$button>\n</td>\n</tr>\n</$list>\n</$list>\n</tbody>\n</table>\n</div>\n\n<$fieldmangler>\n<div class=\"tc-edit-field-add\">\n<em class=\"tc-edit\">\n<<lingo Fields/Add/Prompt>>\n</em>\n<span class=\"tc-edit-field-add-name\">\n<$edit-text tiddler=\"$:/temp/newfieldname\" tag=\"input\" default=\"\" placeholder={{$:/language/EditTemplate/Fields/Add/Name/Placeholder}} focusPopup=<<qualify \"$:/state/popup/field-dropdown\">> class=\"tc-edit-texteditor tc-popup-handle\"/>\n</span>\n<$button popup=<<qualify \"$:/state/popup/field-dropdown\">> class=\"tc-btn-invisible tc-btn-dropdown\" tooltip={{$:/language/EditTemplate/Field/Dropdown/Hint}} aria-label={{$:/language/EditTemplate/Field/Dropdown/Caption}}>{{$:/core/images/down-arrow}}</$button>\n<$reveal state=<<qualify \"$:/state/popup/field-dropdown\">> type=\"nomatch\" text=\"\" default=\"\">\n<div class=\"tc-block-dropdown tc-edit-type-dropdown\">\n<$linkcatcher to=\"$:/temp/newfieldname\">\n<div class=\"tc-dropdown-item\">\n<<lingo Fields/Add/Dropdown/User>>\n</div>\n<$list filter=\"[!is[shadow]!is[system]fields[]sort[]] -created -creator -draft.of -draft.title -modified -modifier -tags -text -title -type\" variable=\"currentField\">\n<$link to=<<currentField>>>\n<<currentField>>\n</$link>\n</$list>\n<div class=\"tc-dropdown-item\">\n<<lingo Fields/Add/Dropdown/System>>\n</div>\n<$list filter=\"[fields[]sort[]] -[!is[shadow]!is[system]fields[]]\" variable=\"currentField\">\n<$link to=<<currentField>>>\n<<currentField>>\n</$link>\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>\n<span class=\"tc-edit-field-add-value\">\n<$edit-text tiddler=\"$:/temp/newfieldvalue\" tag=\"input\" default=\"\" placeholder={{$:/language/EditTemplate/Fields/Add/Value/Placeholder}} class=\"tc-edit-texteditor\"/>\n</span>\n<span class=\"tc-edit-field-add-button\">\n<$macrocall $name=\"new-field\"/>\n</span>\n</div>\n</$fieldmangler>\n\n"
},
"$:/core/ui/EditTemplate/shadow": {
"title": "$:/core/ui/EditTemplate/shadow",
"tags": "$:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/EditTemplate/Shadow/\n\\define pluginLinkBody()\n<$link to=\"\"\"$(pluginTitle)$\"\"\">\n<$text text=\"\"\"$(pluginTitle)$\"\"\"/>\n</$link>\n\\end\n<$list filter=\"[all[current]get[draft.of]is[shadow]!is[tiddler]]\">\n\n<$list filter=\"[all[current]shadowsource[]]\" variable=\"pluginTitle\">\n\n<$set name=\"pluginLink\" value=<<pluginLinkBody>>>\n<div class=\"tc-message-box\">\n\n<<lingo Warning>>\n\n</div>\n</$set>\n</$list>\n\n</$list>\n\n<$list filter=\"[all[current]get[draft.of]is[shadow]is[tiddler]]\">\n\n<$list filter=\"[all[current]shadowsource[]]\" variable=\"pluginTitle\">\n\n<$set name=\"pluginLink\" value=<<pluginLinkBody>>>\n<div class=\"tc-message-box\">\n\n<<lingo OverriddenWarning>>\n\n</div>\n</$set>\n</$list>\n\n</$list>"
},
"$:/core/ui/EditTemplate/tags": {
"title": "$:/core/ui/EditTemplate/tags",
"tags": "$:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/EditTemplate/\n\\define tag-styles()\nbackground-color:$(backgroundColor)$;\nfill:$(foregroundColor)$;\ncolor:$(foregroundColor)$;\n\\end\n\\define tag-body-inner(colour,fallbackTarget,colourA,colourB)\n<$vars foregroundColor=<<contrastcolour target:\"\"\"$colour$\"\"\" fallbackTarget:\"\"\"$fallbackTarget$\"\"\" colourA:\"\"\"$colourA$\"\"\" colourB:\"\"\"$colourB$\"\"\">> backgroundColor=\"\"\"$colour$\"\"\">\n<span style=<<tag-styles>> class=\"tc-tag-label\">\n<$view field=\"title\" format=\"text\" />\n<$button message=\"tm-remove-tag\" param={{!!title}} class=\"tc-btn-invisible tc-remove-tag-button\">×</$button>\n</span>\n</$vars>\n\\end\n\\define tag-body(colour,palette)\n<$macrocall $name=\"tag-body-inner\" colour=\"\"\"$colour$\"\"\" fallbackTarget={{$palette$##tag-background}} colourA={{$palette$##foreground}} colourB={{$palette$##background}}/>\n\\end\n<div class=\"tc-edit-tags\">\n<$fieldmangler>\n<$list filter=\"[all[current]tags[]sort[title]]\" storyview=\"pop\">\n<$macrocall $name=\"tag-body\" colour={{!!color}} palette={{$:/palette}}/>\n</$list>\n\n<div class=\"tc-edit-add-tag\">\n<span class=\"tc-add-tag-name\">\n<$edit-text tiddler=\"$:/temp/NewTagName\" tag=\"input\" default=\"\" placeholder={{$:/language/EditTemplate/Tags/Add/Placeholder}} focusPopup=<<qualify \"$:/state/popup/tags-auto-complete\">> class=\"tc-edit-texteditor tc-popup-handle\"/>\n</span> <$button popup=<<qualify \"$:/state/popup/tags-auto-complete\">> class=\"tc-btn-invisible tc-btn-dropdown\" tooltip={{$:/language/EditTemplate/Tags/Dropdown/Hint}} aria-label={{$:/language/EditTemplate/Tags/Dropdown/Caption}}>{{$:/core/images/down-arrow}}</$button> <span class=\"tc-add-tag-button\">\n<$button message=\"tm-add-tag\" param={{$:/temp/NewTagName}} set=\"$:/temp/NewTagName\" setTo=\"\" class=\"\">\n<<lingo Tags/Add/Button>>\n</$button>\n</span>\n</div>\n\n<div class=\"tc-block-dropdown-wrapper\">\n<$reveal state=<<qualify \"$:/state/popup/tags-auto-complete\">> type=\"nomatch\" text=\"\" default=\"\">\n<div class=\"tc-block-dropdown\">\n<$linkcatcher set=\"$:/temp/NewTagName\" setTo=\"\" message=\"tm-add-tag\">\n<$list filter=\"[tags[]!is[system]search:title{$:/temp/NewTagName}sort[]]\">\n{{||$:/core/ui/Components/tag-link}}\n</$list>\n<hr>\n<$list filter=\"[tags[]is[system]search:title{$:/temp/NewTagName}sort[]]\">\n{{||$:/core/ui/Components/tag-link}}\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>\n</div>\n</$fieldmangler>\n</div>"
},
"$:/core/ui/EditTemplate/title": {
"title": "$:/core/ui/EditTemplate/title",
"tags": "$:/tags/EditTemplate",
"text": "<$vars pattern=\"\"\"[\\|\\[\\]{}]\"\"\" bad-chars=\"\"\"`| [ ] { }`\"\"\">\n\n<$list filter=\"[is[current]regexp:draft.title<pattern>]\" variable=\"listItem\">\n\n<div class=\"tc-message-box\">\n\n{{$:/language/EditTemplate/Title/BadCharacterWarning}}\n\n</div>\n\n</$list>\n\n</$vars>\n\n<$edit-text field=\"draft.title\" class=\"tc-titlebar tc-edit-texteditor\" focus=\"true\"/>\n"
},
"$:/core/ui/EditTemplate/type": {
"title": "$:/core/ui/EditTemplate/type",
"tags": "$:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/EditTemplate/\n<div class=\"tc-type-selector\"><$fieldmangler>\n<em class=\"tc-edit\"><<lingo Type/Prompt>></em> <$edit-text field=\"type\" tag=\"input\" default=\"\" placeholder={{$:/language/EditTemplate/Type/Placeholder}} focusPopup=<<qualify \"$:/state/popup/type-dropdown\">> class=\"tc-edit-typeeditor tc-popup-handle\"/> <$button popup=<<qualify \"$:/state/popup/type-dropdown\">> class=\"tc-btn-invisible tc-btn-dropdown\" tooltip={{$:/language/EditTemplate/Type/Dropdown/Hint}} aria-label={{$:/language/EditTemplate/Type/Dropdown/Caption}}>{{$:/core/images/down-arrow}}</$button> <$button message=\"tm-remove-field\" param=\"type\" class=\"tc-btn-invisible tc-btn-icon\" tooltip={{$:/language/EditTemplate/Type/Delete/Hint}} aria-label={{$:/language/EditTemplate/Type/Delete/Caption}}>{{$:/core/images/delete-button}}</$button>\n</$fieldmangler></div>\n\n<div class=\"tc-block-dropdown-wrapper\">\n<$reveal state=<<qualify \"$:/state/popup/type-dropdown\">> type=\"nomatch\" text=\"\" default=\"\">\n<div class=\"tc-block-dropdown tc-edit-type-dropdown\">\n<$linkcatcher to=\"!!type\">\n<$list filter='[all[shadows+tiddlers]prefix[$:/language/Docs/Types/]each[group]sort[group]]'>\n<div class=\"tc-dropdown-item\">\n<$text text={{!!group}}/>\n</div>\n<$list filter=\"[all[shadows+tiddlers]prefix[$:/language/Docs/Types/]group{!!group}] +[sort[description]]\"><$link to={{!!name}}><$view field=\"description\"/> (<$view field=\"name\"/>)</$link>\n</$list>\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>\n</div>"
},
"$:/core/ui/EditTemplate": {
"title": "$:/core/ui/EditTemplate",
"text": "\\define frame-classes()\ntc-tiddler-frame tc-tiddler-edit-frame $(missingTiddlerClass)$ $(shadowTiddlerClass)$ $(systemTiddlerClass)$\n\\end\n<div class=<<frame-classes>>>\n<$set name=\"storyTiddler\" value=<<currentTiddler>>>\n<$keyboard key=\"((cancel-edit-tiddler))\" message=\"tm-cancel-tiddler\">\n<$keyboard key=\"((save-tiddler))\" message=\"tm-save-tiddler\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditTemplate]!has[draft.of]]\" variable=\"listItem\">\n<$transclude tiddler=<<listItem>>/>\n</$list>\n</$keyboard>\n</$keyboard>\n</$set>\n</div>\n"
},
"$:/core/ui/Buttons/cancel": {
"title": "$:/core/ui/Buttons/cancel",
"tags": "$:/tags/EditToolbar",
"caption": "{{$:/core/images/cancel-button}} {{$:/language/Buttons/Cancel/Caption}}",
"description": "{{$:/language/Buttons/Cancel/Hint}}",
"text": "<$button message=\"tm-cancel-tiddler\" tooltip={{$:/language/Buttons/Cancel/Hint}} aria-label={{$:/language/Buttons/Cancel/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/cancel-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Cancel/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/delete": {
"title": "$:/core/ui/Buttons/delete",
"tags": "$:/tags/EditToolbar $:/tags/ViewToolbar",
"caption": "{{$:/core/images/delete-button}} {{$:/language/Buttons/Delete/Caption}}",
"description": "{{$:/language/Buttons/Delete/Hint}}",
"text": "<$button message=\"tm-delete-tiddler\" tooltip={{$:/language/Buttons/Delete/Hint}} aria-label={{$:/language/Buttons/Delete/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/delete-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Delete/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/save": {
"title": "$:/core/ui/Buttons/save",
"tags": "$:/tags/EditToolbar",
"caption": "{{$:/core/images/done-button}} {{$:/language/Buttons/Save/Caption}}",
"description": "{{$:/language/Buttons/Save/Hint}}",
"text": "<$fieldmangler><$button tooltip={{$:/language/Buttons/Save/Hint}} aria-label={{$:/language/Buttons/Save/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-add-tag\" $param={{$:/temp/NewTagName}}/>\n<$action-deletetiddler $tiddler=\"$:/temp/NewTagName\"/>\n<$action-sendmessage $message=\"tm-add-field\" $name={{$:/temp/newfieldname}} $value={{$:/temp/newfieldvalue}}/>\n<$action-deletetiddler $tiddler=\"$:/temp/newfieldname\"/>\n<$action-deletetiddler $tiddler=\"$:/temp/newfieldvalue\"/>\n<$action-sendmessage $message=\"tm-save-tiddler\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/done-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Save/Caption}}/></span>\n</$list>\n</$button>\n</$fieldmangler>\n"
},
"$:/core/ui/EditorToolbar/bold": {
"title": "$:/core/ui/EditorToolbar/bold",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/bold",
"caption": "{{$:/language/Buttons/Bold/Caption}}",
"description": "{{$:/language/Buttons/Bold/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((bold))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"''\"\n\tsuffix=\"''\"\n/>\n"
},
"$:/core/ui/EditorToolbar/clear-dropdown": {
"title": "$:/core/ui/EditorToolbar/clear-dropdown",
"text": "''{{$:/language/Buttons/Clear/Hint}}''\n\n<div class=\"tc-colour-chooser\">\n\n<$macrocall $name=\"colour-picker\" actions=\"\"\"\n\n<$action-sendmessage\n\t$message=\"tm-edit-bitmap-operation\"\n\t$param=\"clear\"\n\tcolour=<<colour-picker-value>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n\"\"\"/>\n\n</div>\n"
},
"$:/core/ui/EditorToolbar/clear": {
"title": "$:/core/ui/EditorToolbar/clear",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/erase",
"caption": "{{$:/language/Buttons/Clear/Caption}}",
"description": "{{$:/language/Buttons/Clear/Hint}}",
"condition": "[<targetTiddler>is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/clear-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/editor-height-dropdown": {
"title": "$:/core/ui/EditorToolbar/editor-height-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/EditorHeight/\n''<<lingo Hint>>''\n\n<$radio tiddler=\"$:/config/TextEditor/EditorHeight/Mode\" value=\"auto\"> {{$:/core/images/auto-height}} <<lingo Caption/Auto>></$radio>\n\n<$radio tiddler=\"$:/config/TextEditor/EditorHeight/Mode\" value=\"fixed\"> {{$:/core/images/fixed-height}} <<lingo Caption/Fixed>> <$edit-text tag=\"input\" tiddler=\"$:/config/TextEditor/EditorHeight/Height\" default=\"100px\"/></$radio>\n"
},
"$:/core/ui/EditorToolbar/editor-height": {
"title": "$:/core/ui/EditorToolbar/editor-height",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/fixed-height",
"custom-icon": "yes",
"caption": "{{$:/language/Buttons/EditorHeight/Caption}}",
"description": "{{$:/language/Buttons/EditorHeight/Hint}}",
"condition": "[<targetTiddler>!is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/editor-height-dropdown",
"text": "<$reveal tag=\"span\" state=\"$:/config/TextEditor/EditorHeight/Mode\" type=\"match\" text=\"fixed\">\n{{$:/core/images/fixed-height}}\n</$reveal>\n<$reveal tag=\"span\" state=\"$:/config/TextEditor/EditorHeight/Mode\" type=\"match\" text=\"auto\">\n{{$:/core/images/auto-height}}\n</$reveal>\n"
},
"$:/core/ui/EditorToolbar/excise-dropdown": {
"title": "$:/core/ui/EditorToolbar/excise-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/Excise/\n\n\\define body(config-title)\n''<<lingo Hint>>''\n\n<<lingo Caption/NewTitle>> <$edit-text tag=\"input\" tiddler=\"$config-title$/new-title\" default=\"\" focus=\"true\"/>\n\n<$set name=\"new-title\" value={{$config-title$/new-title}}>\n<$list filter=\"\"\"[<new-title>is[tiddler]]\"\"\">\n<div class=\"tc-error\">\n<<lingo Caption/TiddlerExists>>\n</div>\n</$list>\n</$set>\n\n<$checkbox tiddler=\"\"\"$config-title$/tagnew\"\"\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"false\"> <<lingo Caption/Tag>></$checkbox>\n\n<<lingo Caption/Replace>> <$select tiddler=\"\"\"$config-title$/type\"\"\" default=\"transclude\">\n<option value=\"link\"><<lingo Caption/Replace/Link>></option>\n<option value=\"transclude\"><<lingo Caption/Replace/Transclusion>></option>\n<option value=\"macro\"><<lingo Caption/Replace/Macro>></option>\n</$select>\n\n<$reveal state=\"\"\"$config-title$/type\"\"\" type=\"match\" text=\"macro\">\n<<lingo Caption/MacroName>> <$edit-text tag=\"input\" tiddler=\"\"\"$config-title$/macro-title\"\"\" default=\"translink\"/>\n</$reveal>\n\n<$button>\n<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"excise\"\n\ttitle={{$config-title$/new-title}}\n\ttype={{$config-title$/type}}\n\tmacro={{$config-title$/macro-title}}\n\ttagnew={{$config-title$/tagnew}}\n/>\n<$action-deletetiddler\n\t$tiddler=<<qualify \"$:/state/Excise/NewTitle\">>\n/>\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n<<lingo Caption/Excise>>\n</$button>\n\\end\n\n<$macrocall $name=\"body\" config-title=<<qualify \"$:/state/Excise/\">>/>\n"
},
"$:/core/ui/EditorToolbar/excise": {
"title": "$:/core/ui/EditorToolbar/excise",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/excise",
"caption": "{{$:/language/Buttons/Excise/Caption}}",
"description": "{{$:/language/Buttons/Excise/Hint}}",
"condition": "[<targetTiddler>!is[image]]",
"shortcuts": "((excise))",
"dropdown": "$:/core/ui/EditorToolbar/excise-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/heading-1": {
"title": "$:/core/ui/EditorToolbar/heading-1",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-1",
"caption": "{{$:/language/Buttons/Heading1/Caption}}",
"description": "{{$:/language/Buttons/Heading1/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"button-classes": "tc-text-editor-toolbar-item-start-group",
"shortcuts": "((heading-1))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"1\"\n/>\n"
},
"$:/core/ui/EditorToolbar/heading-2": {
"title": "$:/core/ui/EditorToolbar/heading-2",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-2",
"caption": "{{$:/language/Buttons/Heading2/Caption}}",
"description": "{{$:/language/Buttons/Heading2/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((heading-2))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"2\"\n/>\n"
},
"$:/core/ui/EditorToolbar/heading-3": {
"title": "$:/core/ui/EditorToolbar/heading-3",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-3",
"caption": "{{$:/language/Buttons/Heading3/Caption}}",
"description": "{{$:/language/Buttons/Heading3/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((heading-3))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"3\"\n/>\n"
},
"$:/core/ui/EditorToolbar/heading-4": {
"title": "$:/core/ui/EditorToolbar/heading-4",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-4",
"caption": "{{$:/language/Buttons/Heading4/Caption}}",
"description": "{{$:/language/Buttons/Heading4/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((heading-4))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"4\"\n/>\n"
},
"$:/core/ui/EditorToolbar/heading-5": {
"title": "$:/core/ui/EditorToolbar/heading-5",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-5",
"caption": "{{$:/language/Buttons/Heading5/Caption}}",
"description": "{{$:/language/Buttons/Heading5/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((heading-5))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"5\"\n/>\n"
},
"$:/core/ui/EditorToolbar/heading-6": {
"title": "$:/core/ui/EditorToolbar/heading-6",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/heading-6",
"caption": "{{$:/language/Buttons/Heading6/Caption}}",
"description": "{{$:/language/Buttons/Heading6/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((heading-6))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"!\"\n\tcount=\"6\"\n/>\n"
},
"$:/core/ui/EditorToolbar/italic": {
"title": "$:/core/ui/EditorToolbar/italic",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/italic",
"caption": "{{$:/language/Buttons/Italic/Caption}}",
"description": "{{$:/language/Buttons/Italic/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((italic))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"//\"\n\tsuffix=\"//\"\n/>\n"
},
"$:/core/ui/EditorToolbar/line-width-dropdown": {
"title": "$:/core/ui/EditorToolbar/line-width-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/LineWidth/\n\n\\define toolbar-line-width-inner()\n<$button tag=\"a\" tooltip=\"\"\"$(line-width)$\"\"\">\n\n<$action-setfield\n\t$tiddler=\"$:/config/BitmapEditor/LineWidth\"\n\t$value=\"$(line-width)$\"\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<div style=\"display: inline-block; margin: 4px calc(80px - $(line-width)$); background-color: #000; width: calc(100px + $(line-width)$ * 2); height: $(line-width)$; border-radius: 120px; vertical-align: middle;\"/>\n\n<span style=\"margin-left: 8px;\">\n\n<$text text=\"\"\"$(line-width)$\"\"\"/>\n\n<$reveal state=\"$:/config/BitmapEditor/LineWidth\" type=\"match\" text=\"\"\"$(line-width)$\"\"\" tag=\"span\">\n\n<$entity entity=\" \"/>\n\n<$entity entity=\"✓\"/>\n\n</$reveal>\n\n</span>\n\n</$button>\n\\end\n\n''<<lingo Hint>>''\n\n<$list filter={{$:/config/BitmapEditor/LineWidths}} variable=\"line-width\">\n\n<<toolbar-line-width-inner>>\n\n</$list>\n"
},
"$:/core/ui/EditorToolbar/line-width": {
"title": "$:/core/ui/EditorToolbar/line-width",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/line-width",
"caption": "{{$:/language/Buttons/LineWidth/Caption}}",
"description": "{{$:/language/Buttons/LineWidth/Hint}}",
"condition": "[<targetTiddler>is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/line-width-dropdown",
"text": "<$text text={{$:/config/BitmapEditor/LineWidth}}/>"
},
"$:/core/ui/EditorToolbar/link-dropdown": {
"title": "$:/core/ui/EditorToolbar/link-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/Link/\n\n\\define link-actions()\n<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"make-link\"\n\ttext={{$(linkTiddler)$}}\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<searchTiddler>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<linkTiddler>>\n/>\n\\end\n\n\\define body(config-title)\n''<<lingo Hint>>''\n\n<$vars searchTiddler=\"\"\"$config-title$/search\"\"\" linkTiddler=\"\"\"$config-title$/link\"\"\">\n\n<$edit-text tiddler=<<searchTiddler>> type=\"search\" tag=\"input\" focus=\"true\" placeholder={{$:/language/Search/Search}} default=\"\"/>\n<$reveal tag=\"span\" state=<<searchTiddler>> type=\"nomatch\" text=\"\">\n<$button class=\"tc-btn-invisible\" style=\"width: auto; display: inline-block; background-colour: inherit;\">\n<$action-setfield $tiddler=<<searchTiddler>> text=\"\" />\n{{$:/core/images/close-button}}\n</$button>\n</$reveal>\n\n<$reveal tag=\"div\" state=<<searchTiddler>> type=\"nomatch\" text=\"\">\n\n<$linkcatcher actions=<<link-actions>> to=<<linkTiddler>>>\n\n{{$:/core/ui/SearchResults}}\n\n</$linkcatcher>\n\n</$reveal>\n\n</$vars>\n\n\\end\n\n<$macrocall $name=\"body\" config-title=<<qualify \"$:/state/Link/\">>/>\n"
},
"$:/core/ui/EditorToolbar/link": {
"title": "$:/core/ui/EditorToolbar/link",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/link",
"caption": "{{$:/language/Buttons/Link/Caption}}",
"description": "{{$:/language/Buttons/Link/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"button-classes": "tc-text-editor-toolbar-item-start-group",
"shortcuts": "((link))",
"dropdown": "$:/core/ui/EditorToolbar/link-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/list-bullet": {
"title": "$:/core/ui/EditorToolbar/list-bullet",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/list-bullet",
"caption": "{{$:/language/Buttons/ListBullet/Caption}}",
"description": "{{$:/language/Buttons/ListBullet/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((list-bullet))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"*\"\n\tcount=\"1\"\n/>\n"
},
"$:/core/ui/EditorToolbar/list-number": {
"title": "$:/core/ui/EditorToolbar/list-number",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/list-number",
"caption": "{{$:/language/Buttons/ListNumber/Caption}}",
"description": "{{$:/language/Buttons/ListNumber/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((list-number))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"prefix-lines\"\n\tcharacter=\"#\"\n\tcount=\"1\"\n/>\n"
},
"$:/core/ui/EditorToolbar/mono-block": {
"title": "$:/core/ui/EditorToolbar/mono-block",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/mono-block",
"caption": "{{$:/language/Buttons/MonoBlock/Caption}}",
"description": "{{$:/language/Buttons/MonoBlock/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"button-classes": "tc-text-editor-toolbar-item-start-group",
"shortcuts": "((mono-block))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-lines\"\n\tprefix=\"\n```\"\n\tsuffix=\"```\"\n/>\n"
},
"$:/core/ui/EditorToolbar/mono-line": {
"title": "$:/core/ui/EditorToolbar/mono-line",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/mono-line",
"caption": "{{$:/language/Buttons/MonoLine/Caption}}",
"description": "{{$:/language/Buttons/MonoLine/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((mono-line))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"`\"\n\tsuffix=\"`\"\n/>\n"
},
"$:/core/ui/EditorToolbar/more-dropdown": {
"title": "$:/core/ui/EditorToolbar/more-dropdown",
"text": "\\define config-title()\n$:/config/EditorToolbarButtons/Visibility/$(toolbarItem)$\n\\end\n\n\\define conditional-button()\n<$list filter={{$(toolbarItem)$!!condition}} variable=\"condition\">\n<$transclude tiddler=\"$:/core/ui/EditTemplate/body/toolbar/button\" mode=\"inline\"/> <$transclude tiddler=<<toolbarItem>> field=\"description\"/>\n</$list>\n\\end\n\n<div class=\"tc-text-editor-toolbar-more\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditorToolbar]!has[draft.of]] -[[$:/core/ui/EditorToolbar/more]]\">\n<$reveal type=\"match\" state=<<config-visibility-title>> text=\"hide\" tag=\"div\">\n<<conditional-button>>\n</$reveal>\n</$list>\n</div>\n"
},
"$:/core/ui/EditorToolbar/more": {
"title": "$:/core/ui/EditorToolbar/more",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/down-arrow",
"caption": "{{$:/language/Buttons/More/Caption}}",
"description": "{{$:/language/Buttons/More/Hint}}",
"condition": "[<targetTiddler>]",
"dropdown": "$:/core/ui/EditorToolbar/more-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/opacity-dropdown": {
"title": "$:/core/ui/EditorToolbar/opacity-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/Opacity/\n\n\\define toolbar-opacity-inner()\n<$button tag=\"a\" tooltip=\"\"\"$(opacity)$\"\"\">\n\n<$action-setfield\n\t$tiddler=\"$:/config/BitmapEditor/Opacity\"\n\t$value=\"$(opacity)$\"\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<div style=\"display: inline-block; vertical-align: middle; background-color: $(current-paint-colour)$; opacity: $(opacity)$; width: 1em; height: 1em; border-radius: 50%;\"/>\n\n<span style=\"margin-left: 8px;\">\n\n<$text text=\"\"\"$(opacity)$\"\"\"/>\n\n<$reveal state=\"$:/config/BitmapEditor/Opacity\" type=\"match\" text=\"\"\"$(opacity)$\"\"\" tag=\"span\">\n\n<$entity entity=\" \"/>\n\n<$entity entity=\"✓\"/>\n\n</$reveal>\n\n</span>\n\n</$button>\n\\end\n\n\\define toolbar-opacity()\n''<<lingo Hint>>''\n\n<$list filter={{$:/config/BitmapEditor/Opacities}} variable=\"opacity\">\n\n<<toolbar-opacity-inner>>\n\n</$list>\n\\end\n\n<$set name=\"current-paint-colour\" value={{$:/config/BitmapEditor/Colour}}>\n\n<$set name=\"current-opacity\" value={{$:/config/BitmapEditor/Opacity}}>\n\n<<toolbar-opacity>>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/EditorToolbar/opacity": {
"title": "$:/core/ui/EditorToolbar/opacity",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/opacity",
"caption": "{{$:/language/Buttons/Opacity/Caption}}",
"description": "{{$:/language/Buttons/Opacity/Hint}}",
"condition": "[<targetTiddler>is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/opacity-dropdown",
"text": "<$text text={{$:/config/BitmapEditor/Opacity}}/>\n"
},
"$:/core/ui/EditorToolbar/paint-dropdown": {
"title": "$:/core/ui/EditorToolbar/paint-dropdown",
"text": "''{{$:/language/Buttons/Paint/Hint}}''\n\n<$macrocall $name=\"colour-picker\" actions=\"\"\"\n\n<$action-setfield\n\t$tiddler=\"$:/config/BitmapEditor/Colour\"\n\t$value=<<colour-picker-value>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n\"\"\"/>\n"
},
"$:/core/ui/EditorToolbar/paint": {
"title": "$:/core/ui/EditorToolbar/paint",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/paint",
"caption": "{{$:/language/Buttons/Paint/Caption}}",
"description": "{{$:/language/Buttons/Paint/Hint}}",
"condition": "[<targetTiddler>is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/paint-dropdown",
"text": "\\define toolbar-paint()\n<div style=\"display: inline-block; vertical-align: middle; background-color: $(colour-picker-value)$; width: 1em; height: 1em; border-radius: 50%;\"/>\n\\end\n<$set name=\"colour-picker-value\" value={{$:/config/BitmapEditor/Colour}}>\n<<toolbar-paint>>\n</$set>\n"
},
"$:/core/ui/EditorToolbar/picture-dropdown": {
"title": "$:/core/ui/EditorToolbar/picture-dropdown",
"text": "\\define replacement-text()\n[img[$(imageTitle)$]]\n\\end\n\n''{{$:/language/Buttons/Picture/Hint}}''\n\n<$macrocall $name=\"image-picker\" actions=\"\"\"\n\n<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"replace-selection\"\n\ttext=<<replacement-text>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n\"\"\"/>\n"
},
"$:/core/ui/EditorToolbar/picture": {
"title": "$:/core/ui/EditorToolbar/picture",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/picture",
"caption": "{{$:/language/Buttons/Picture/Caption}}",
"description": "{{$:/language/Buttons/Picture/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((picture))",
"dropdown": "$:/core/ui/EditorToolbar/picture-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/preview-type-dropdown": {
"title": "$:/core/ui/EditorToolbar/preview-type-dropdown",
"text": "\\define preview-type-button()\n<$button tag=\"a\">\n\n<$action-setfield $tiddler=\"$:/state/editpreviewtype\" $value=\"$(previewType)$\"/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<$transclude tiddler=<<previewType>> field=\"caption\" mode=\"inline\">\n\n<$view tiddler=<<previewType>> field=\"title\" mode=\"inline\"/>\n\n</$transclude> \n\n<$reveal tag=\"span\" state=\"$:/state/editpreviewtype\" type=\"match\" text=<<previewType>> default=\"$:/core/ui/EditTemplate/body/preview/output\">\n\n<$entity entity=\" \"/>\n\n<$entity entity=\"✓\"/>\n\n</$reveal>\n\n</$button>\n\\end\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/EditPreview]!has[draft.of]]\" variable=\"previewType\">\n\n<<preview-type-button>>\n\n</$list>\n"
},
"$:/core/ui/EditorToolbar/preview-type": {
"title": "$:/core/ui/EditorToolbar/preview-type",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/chevron-down",
"caption": "{{$:/language/Buttons/PreviewType/Caption}}",
"description": "{{$:/language/Buttons/PreviewType/Hint}}",
"condition": "[all[shadows+tiddlers]tag[$:/tags/EditPreview]!has[draft.of]butfirst[]limit[1]]",
"button-classes": "tc-text-editor-toolbar-item-adjunct",
"dropdown": "$:/core/ui/EditorToolbar/preview-type-dropdown"
},
"$:/core/ui/EditorToolbar/preview": {
"title": "$:/core/ui/EditorToolbar/preview",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/preview-open",
"custom-icon": "yes",
"caption": "{{$:/language/Buttons/Preview/Caption}}",
"description": "{{$:/language/Buttons/Preview/Hint}}",
"condition": "[<targetTiddler>]",
"button-classes": "tc-text-editor-toolbar-item-start-group",
"shortcuts": "((preview))",
"text": "<$reveal state=\"$:/state/showeditpreview\" type=\"match\" text=\"yes\" tag=\"span\">\n{{$:/core/images/preview-open}}\n<$action-setfield $tiddler=\"$:/state/showeditpreview\" $value=\"no\"/>\n</$reveal>\n<$reveal state=\"$:/state/showeditpreview\" type=\"nomatch\" text=\"yes\" tag=\"span\">\n{{$:/core/images/preview-closed}}\n<$action-setfield $tiddler=\"$:/state/showeditpreview\" $value=\"yes\"/>\n</$reveal>\n"
},
"$:/core/ui/EditorToolbar/quote": {
"title": "$:/core/ui/EditorToolbar/quote",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/quote",
"caption": "{{$:/language/Buttons/Quote/Caption}}",
"description": "{{$:/language/Buttons/Quote/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((quote))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-lines\"\n\tprefix=\"\n<<<\"\n\tsuffix=\"<<<\"\n/>\n"
},
"$:/core/ui/EditorToolbar/size-dropdown": {
"title": "$:/core/ui/EditorToolbar/size-dropdown",
"text": "\\define lingo-base() $:/language/Buttons/Size/\n\n\\define toolbar-button-size-preset(config-title)\n<$set name=\"width\" filter=\"$(sizePair)$ +[first[]]\">\n\n<$set name=\"height\" filter=\"$(sizePair)$ +[last[]]\">\n\n<$button tag=\"a\">\n\n<$action-setfield\n\t$tiddler=\"\"\"$config-title$/new-width\"\"\"\n\t$value=<<width>>\n/>\n\n<$action-setfield\n\t$tiddler=\"\"\"$config-title$/new-height\"\"\"\n\t$value=<<height>>\n/>\n\n<$action-deletetiddler\n\t$tiddler=\"\"\"$config-title$/presets-popup\"\"\"\n/>\n\n<$text text=<<width>>/> × <$text text=<<height>>/>\n\n</$button>\n\n</$set>\n\n</$set>\n\\end\n\n\\define toolbar-button-size(config-title)\n''{{$:/language/Buttons/Size/Hint}}''\n\n<<lingo Caption/Width>> <$edit-text tag=\"input\" tiddler=\"\"\"$config-title$/new-width\"\"\" default=<<tv-bitmap-editor-width>> focus=\"true\" size=\"8\"/> <<lingo Caption/Height>> <$edit-text tag=\"input\" tiddler=\"\"\"$config-title$/new-height\"\"\" default=<<tv-bitmap-editor-height>> size=\"8\"/> <$button popup=\"\"\"$config-title$/presets-popup\"\"\" class=\"tc-btn-invisible tc-popup-keep\" style=\"width: auto; display: inline-block; background-colour: inherit;\" selectedClass=\"tc-selected\">\n{{$:/core/images/down-arrow}}\n</$button>\n\n<$reveal tag=\"span\" state=\"\"\"$config-title$/presets-popup\"\"\" type=\"popup\" position=\"belowleft\" animate=\"yes\">\n\n<div class=\"tc-drop-down tc-popup-keep\">\n\n<$list filter={{$:/config/BitmapEditor/ImageSizes}} variable=\"sizePair\">\n\n<$macrocall $name=\"toolbar-button-size-preset\" config-title=\"$config-title$\"/>\n\n</$list>\n\n</div>\n\n</$reveal>\n\n<$button>\n<$action-sendmessage\n\t$message=\"tm-edit-bitmap-operation\"\n\t$param=\"resize\"\n\twidth={{$config-title$/new-width}}\n\theight={{$config-title$/new-height}}\n/>\n<$action-deletetiddler\n\t$tiddler=\"\"\"$config-title$/new-width\"\"\"\n/>\n<$action-deletetiddler\n\t$tiddler=\"\"\"$config-title$/new-height\"\"\"\n/>\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n<<lingo Caption/Resize>>\n</$button>\n\\end\n\n<$macrocall $name=\"toolbar-button-size\" config-title=<<qualify \"$:/state/Size/\">>/>\n"
},
"$:/core/ui/EditorToolbar/size": {
"title": "$:/core/ui/EditorToolbar/size",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/size",
"caption": "{{$:/language/Buttons/Size/Caption}}",
"description": "{{$:/language/Buttons/Size/Hint}}",
"condition": "[<targetTiddler>is[image]]",
"dropdown": "$:/core/ui/EditorToolbar/size-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/stamp-dropdown": {
"title": "$:/core/ui/EditorToolbar/stamp-dropdown",
"text": "\\define toolbar-button-stamp-inner()\n<$button tag=\"a\">\n\n<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"replace-selection\"\n\ttext={{$(snippetTitle)$}}\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<$view tiddler=<<snippetTitle>> field=\"caption\" mode=\"inline\">\n\n<$view tiddler=<<snippetTitle>> field=\"title\" mode=\"inline\"/>\n\n</$view>\n\n</$button>\n\\end\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/TextEditor/Snippet]!has[draft.of]sort[caption]]\" variable=\"snippetTitle\">\n\n<<toolbar-button-stamp-inner>>\n\n</$list>\n\n----\n\n<$button tag=\"a\">\n\n<$action-sendmessage\n\t$message=\"tm-new-tiddler\"\n\ttags=\"$:/tags/TextEditor/Snippet\"\n\tcaption={{$:/language/Buttons/Stamp/New/Title}}\n\ttext={{$:/language/Buttons/Stamp/New/Text}}\n/>\n\n<$action-deletetiddler\n\t$tiddler=<<dropdown-state>>\n/>\n\n<em>\n\n<$text text={{$:/language/Buttons/Stamp/Caption/New}}/>\n\n</em>\n\n</$button>\n"
},
"$:/core/ui/EditorToolbar/stamp": {
"title": "$:/core/ui/EditorToolbar/stamp",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/stamp",
"caption": "{{$:/language/Buttons/Stamp/Caption}}",
"description": "{{$:/language/Buttons/Stamp/Hint}}",
"condition": "[<targetTiddler>!is[image]]",
"shortcuts": "((stamp))",
"dropdown": "$:/core/ui/EditorToolbar/stamp-dropdown",
"text": ""
},
"$:/core/ui/EditorToolbar/strikethrough": {
"title": "$:/core/ui/EditorToolbar/strikethrough",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/strikethrough",
"caption": "{{$:/language/Buttons/Strikethrough/Caption}}",
"description": "{{$:/language/Buttons/Strikethrough/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((strikethrough))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"~~\"\n\tsuffix=\"~~\"\n/>\n"
},
"$:/core/ui/EditorToolbar/subscript": {
"title": "$:/core/ui/EditorToolbar/subscript",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/subscript",
"caption": "{{$:/language/Buttons/Subscript/Caption}}",
"description": "{{$:/language/Buttons/Subscript/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((subscript))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\",,\"\n\tsuffix=\",,\"\n/>\n"
},
"$:/core/ui/EditorToolbar/superscript": {
"title": "$:/core/ui/EditorToolbar/superscript",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/superscript",
"caption": "{{$:/language/Buttons/Superscript/Caption}}",
"description": "{{$:/language/Buttons/Superscript/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((superscript))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"^^\"\n\tsuffix=\"^^\"\n/>\n"
},
"$:/core/ui/EditorToolbar/underline": {
"title": "$:/core/ui/EditorToolbar/underline",
"tags": "$:/tags/EditorToolbar",
"icon": "$:/core/images/underline",
"caption": "{{$:/language/Buttons/Underline/Caption}}",
"description": "{{$:/language/Buttons/Underline/Hint}}",
"condition": "[<targetTiddler>!has[type]] [<targetTiddler>type[text/vnd.tiddlywiki]]",
"shortcuts": "((underline))",
"text": "<$action-sendmessage\n\t$message=\"tm-edit-text-operation\"\n\t$param=\"wrap-selection\"\n\tprefix=\"__\"\n\tsuffix=\"__\"\n/>\n"
},
"$:/core/Filters/AllTags": {
"title": "$:/core/Filters/AllTags",
"tags": "$:/tags/Filter",
"filter": "[tags[]!is[system]sort[title]]",
"description": "{{$:/language/Filters/AllTags}}",
"text": ""
},
"$:/core/Filters/AllTiddlers": {
"title": "$:/core/Filters/AllTiddlers",
"tags": "$:/tags/Filter",
"filter": "[!is[system]sort[title]]",
"description": "{{$:/language/Filters/AllTiddlers}}",
"text": ""
},
"$:/core/Filters/Drafts": {
"title": "$:/core/Filters/Drafts",
"tags": "$:/tags/Filter",
"filter": "[has[draft.of]sort[title]]",
"description": "{{$:/language/Filters/Drafts}}",
"text": ""
},
"$:/core/Filters/Missing": {
"title": "$:/core/Filters/Missing",
"tags": "$:/tags/Filter",
"filter": "[all[missing]sort[title]]",
"description": "{{$:/language/Filters/Missing}}",
"text": ""
},
"$:/core/Filters/Orphans": {
"title": "$:/core/Filters/Orphans",
"tags": "$:/tags/Filter",
"filter": "[all[orphans]sort[title]]",
"description": "{{$:/language/Filters/Orphans}}",
"text": ""
},
"$:/core/Filters/OverriddenShadowTiddlers": {
"title": "$:/core/Filters/OverriddenShadowTiddlers",
"tags": "$:/tags/Filter",
"filter": "[is[shadow]]",
"description": "{{$:/language/Filters/OverriddenShadowTiddlers}}",
"text": ""
},
"$:/core/Filters/RecentSystemTiddlers": {
"title": "$:/core/Filters/RecentSystemTiddlers",
"tags": "$:/tags/Filter",
"filter": "[has[modified]!sort[modified]limit[50]]",
"description": "{{$:/language/Filters/RecentSystemTiddlers}}",
"text": ""
},
"$:/core/Filters/RecentTiddlers": {
"title": "$:/core/Filters/RecentTiddlers",
"tags": "$:/tags/Filter",
"filter": "[!is[system]has[modified]!sort[modified]limit[50]]",
"description": "{{$:/language/Filters/RecentTiddlers}}",
"text": ""
},
"$:/core/Filters/ShadowTiddlers": {
"title": "$:/core/Filters/ShadowTiddlers",
"tags": "$:/tags/Filter",
"filter": "[all[shadows]sort[title]]",
"description": "{{$:/language/Filters/ShadowTiddlers}}",
"text": ""
},
"$:/core/Filters/SystemTags": {
"title": "$:/core/Filters/SystemTags",
"tags": "$:/tags/Filter",
"filter": "[all[shadows+tiddlers]tags[]is[system]sort[title]]",
"description": "{{$:/language/Filters/SystemTags}}",
"text": ""
},
"$:/core/Filters/SystemTiddlers": {
"title": "$:/core/Filters/SystemTiddlers",
"tags": "$:/tags/Filter",
"filter": "[is[system]sort[title]]",
"description": "{{$:/language/Filters/SystemTiddlers}}",
"text": ""
},
"$:/core/Filters/TypedTiddlers": {
"title": "$:/core/Filters/TypedTiddlers",
"tags": "$:/tags/Filter",
"filter": "[!is[system]has[type]each[type]sort[type]] -[type[text/vnd.tiddlywiki]]",
"description": "{{$:/language/Filters/TypedTiddlers}}",
"text": ""
},
"$:/core/ui/ImportListing": {
"title": "$:/core/ui/ImportListing",
"text": "\\define lingo-base() $:/language/Import/\n\\define messageField()\nmessage-$(payloadTiddler)$\n\\end\n\\define selectionField()\nselection-$(payloadTiddler)$\n\\end\n\\define previewPopupState()\n$(currentTiddler)$!!popup-$(payloadTiddler)$\n\\end\n<table>\n<tbody>\n<tr>\n<th>\n<<lingo Listing/Select/Caption>>\n</th>\n<th>\n<<lingo Listing/Title/Caption>>\n</th>\n<th>\n<<lingo Listing/Status/Caption>>\n</th>\n</tr>\n<$list filter=\"[all[current]plugintiddlers[]sort[title]]\" variable=\"payloadTiddler\">\n<tr>\n<td>\n<$checkbox field=<<selectionField>> checked=\"checked\" unchecked=\"unchecked\" default=\"checked\"/>\n</td>\n<td>\n<$reveal type=\"nomatch\" state=<<previewPopupState>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<previewPopupState>> setTo=\"yes\">\n{{$:/core/images/right-arrow}} <$text text=<<payloadTiddler>>/>\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<previewPopupState>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<previewPopupState>> setTo=\"no\">\n{{$:/core/images/down-arrow}} <$text text=<<payloadTiddler>>/>\n</$button>\n</$reveal>\n</td>\n<td>\n<$view field=<<messageField>>/>\n</td>\n</tr>\n<tr>\n<td colspan=\"3\">\n<$reveal type=\"match\" text=\"yes\" state=<<previewPopupState>>>\n<$transclude subtiddler=<<payloadTiddler>> mode=\"block\"/>\n</$reveal>\n</td>\n</tr>\n</$list>\n</tbody>\n</table>\n"
},
"$:/core/ui/ListItemTemplate": {
"title": "$:/core/ui/ListItemTemplate",
"text": "<div class=\"tc-menu-list-item\">\n<$link to={{!!title}}>\n<$view field=\"title\"/>\n</$link>\n</div>"
},
"$:/core/ui/MissingTemplate": {
"title": "$:/core/ui/MissingTemplate",
"text": "<div class=\"tc-tiddler-missing\">\n<$button popup=<<qualify \"$:/state/popup/missing\">> class=\"tc-btn-invisible tc-missing-tiddler-label\">\n<$view field=\"title\" format=\"text\" />\n</$button>\n<$reveal state=<<qualify \"$:/state/popup/missing\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\">\n<$transclude tiddler=\"$:/core/ui/ListItemTemplate\"/>\n<hr>\n<$list filter=\"[all[current]backlinks[]sort[title]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n</div>\n</$reveal>\n</div>\n"
},
"$:/core/ui/MoreSideBar/All": {
"title": "$:/core/ui/MoreSideBar/All",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/All/Caption}}",
"text": "<$list filter={{$:/core/Filters/AllTiddlers!!filter}} template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/Drafts": {
"title": "$:/core/ui/MoreSideBar/Drafts",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Drafts/Caption}}",
"text": "<$list filter={{$:/core/Filters/Drafts!!filter}} template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/Missing": {
"title": "$:/core/ui/MoreSideBar/Missing",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Missing/Caption}}",
"text": "<$list filter={{$:/core/Filters/Missing!!filter}} template=\"$:/core/ui/MissingTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/Orphans": {
"title": "$:/core/ui/MoreSideBar/Orphans",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Orphans/Caption}}",
"text": "<$list filter={{$:/core/Filters/Orphans!!filter}} template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/Recent": {
"title": "$:/core/ui/MoreSideBar/Recent",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Recent/Caption}}",
"text": "<$macrocall $name=\"timeline\" format={{$:/language/RecentChanges/DateFormat}}/>\n"
},
"$:/core/ui/MoreSideBar/Shadows": {
"title": "$:/core/ui/MoreSideBar/Shadows",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Shadows/Caption}}",
"text": "<$list filter={{$:/core/Filters/ShadowTiddlers!!filter}} template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/System": {
"title": "$:/core/ui/MoreSideBar/System",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/System/Caption}}",
"text": "<$list filter={{$:/core/Filters/SystemTiddlers!!filter}} template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/MoreSideBar/Tags": {
"title": "$:/core/ui/MoreSideBar/Tags",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Tags/Caption}}",
"text": "<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"\">\n\n{{$:/core/ui/Buttons/tag-manager}}\n\n</$set>\n\n</$set>\n\n</$set>\n\n<$list filter={{$:/core/Filters/AllTags!!filter}}>\n\n<$transclude tiddler=\"$:/core/ui/TagTemplate\"/>\n\n</$list>\n\n<hr class=\"tc-untagged-separator\">\n\n{{$:/core/ui/UntaggedTemplate}}\n"
},
"$:/core/ui/MoreSideBar/Types": {
"title": "$:/core/ui/MoreSideBar/Types",
"tags": "$:/tags/MoreSideBar",
"caption": "{{$:/language/SideBar/Types/Caption}}",
"text": "<$list filter={{$:/core/Filters/TypedTiddlers!!filter}}>\n<div class=\"tc-menu-list-item\">\n<$view field=\"type\"/>\n<$list filter=\"[type{!!type}!is[system]sort[title]]\">\n<div class=\"tc-menu-list-subitem\">\n<$link to={{!!title}}><$view field=\"title\"/></$link>\n</div>\n</$list>\n</div>\n</$list>\n"
},
"$:/core/ui/Buttons/advanced-search": {
"title": "$:/core/ui/Buttons/advanced-search",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/advanced-search-button}} {{$:/language/Buttons/AdvancedSearch/Caption}}",
"description": "{{$:/language/Buttons/AdvancedSearch/Hint}}",
"text": "\\define control-panel-button(class)\n<$button to=\"$:/AdvancedSearch\" tooltip={{$:/language/Buttons/AdvancedSearch/Hint}} aria-label={{$:/language/Buttons/AdvancedSearch/Caption}} class=\"\"\"$(tv-config-toolbar-class)$ $class$\"\"\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/advanced-search-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/AdvancedSearch/Caption}}/></span>\n</$list>\n</$button>\n\\end\n\n<$list filter=\"[list[$:/StoryList]] +[field:title[$:/AdvancedSearch]]\" emptyMessage=<<control-panel-button>>>\n<<control-panel-button \"tc-selected\">>\n</$list>\n"
},
"$:/core/ui/Buttons/close-all": {
"title": "$:/core/ui/Buttons/close-all",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/close-all-button}} {{$:/language/Buttons/CloseAll/Caption}}",
"description": "{{$:/language/Buttons/CloseAll/Hint}}",
"text": "<$button message=\"tm-close-all-tiddlers\" tooltip={{$:/language/Buttons/CloseAll/Hint}} aria-label={{$:/language/Buttons/CloseAll/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/close-all-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/CloseAll/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/control-panel": {
"title": "$:/core/ui/Buttons/control-panel",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/options-button}} {{$:/language/Buttons/ControlPanel/Caption}}",
"description": "{{$:/language/Buttons/ControlPanel/Hint}}",
"text": "\\define control-panel-button(class)\n<$button to=\"$:/ControlPanel\" tooltip={{$:/language/Buttons/ControlPanel/Hint}} aria-label={{$:/language/Buttons/ControlPanel/Caption}} class=\"\"\"$(tv-config-toolbar-class)$ $class$\"\"\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/options-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/ControlPanel/Caption}}/></span>\n</$list>\n</$button>\n\\end\n\n<$list filter=\"[list[$:/StoryList]] +[field:title[$:/ControlPanel]]\" emptyMessage=<<control-panel-button>>>\n<<control-panel-button \"tc-selected\">>\n</$list>\n"
},
"$:/core/ui/Buttons/encryption": {
"title": "$:/core/ui/Buttons/encryption",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/locked-padlock}} {{$:/language/Buttons/Encryption/Caption}}",
"description": "{{$:/language/Buttons/Encryption/Hint}}",
"text": "<$reveal type=\"match\" state=\"$:/isEncrypted\" text=\"yes\">\n<$button message=\"tm-clear-password\" tooltip={{$:/language/Buttons/Encryption/ClearPassword/Hint}} aria-label={{$:/language/Buttons/Encryption/ClearPassword/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/locked-padlock}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Encryption/ClearPassword/Caption}}/></span>\n</$list>\n</$button>\n</$reveal>\n<$reveal type=\"nomatch\" state=\"$:/isEncrypted\" text=\"yes\">\n<$button message=\"tm-set-password\" tooltip={{$:/language/Buttons/Encryption/SetPassword/Hint}} aria-label={{$:/language/Buttons/Encryption/SetPassword/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/unlocked-padlock}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Encryption/SetPassword/Caption}}/></span>\n</$list>\n</$button>\n</$reveal>"
},
"$:/core/ui/Buttons/export-page": {
"title": "$:/core/ui/Buttons/export-page",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/export-button}} {{$:/language/Buttons/ExportPage/Caption}}",
"description": "{{$:/language/Buttons/ExportPage/Hint}}",
"text": "<$macrocall $name=\"exportButton\" exportFilter=\"[!is[system]sort[title]]\" lingoBase=\"$:/language/Buttons/ExportPage/\"/>"
},
"$:/core/ui/Buttons/fold-all": {
"title": "$:/core/ui/Buttons/fold-all",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/fold-all-button}} {{$:/language/Buttons/FoldAll/Caption}}",
"description": "{{$:/language/Buttons/FoldAll/Hint}}",
"text": "<$button tooltip={{$:/language/Buttons/FoldAll/Hint}} aria-label={{$:/language/Buttons/FoldAll/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-fold-all-tiddlers\" $param=<<currentTiddler>> foldedStatePrefix=\"$:/state/folded/\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\" variable=\"listItem\">\n{{$:/core/images/fold-all-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/FoldAll/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/full-screen": {
"title": "$:/core/ui/Buttons/full-screen",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/full-screen-button}} {{$:/language/Buttons/FullScreen/Caption}}",
"description": "{{$:/language/Buttons/FullScreen/Hint}}",
"text": "<$button message=\"tm-full-screen\" tooltip={{$:/language/Buttons/FullScreen/Hint}} aria-label={{$:/language/Buttons/FullScreen/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/full-screen-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/FullScreen/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/home": {
"title": "$:/core/ui/Buttons/home",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/home-button}} {{$:/language/Buttons/Home/Caption}}",
"description": "{{$:/language/Buttons/Home/Hint}}",
"text": "<$button message=\"tm-home\" tooltip={{$:/language/Buttons/Home/Hint}} aria-label={{$:/language/Buttons/Home/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/home-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Home/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/import": {
"title": "$:/core/ui/Buttons/import",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/import-button}} {{$:/language/Buttons/Import/Caption}}",
"description": "{{$:/language/Buttons/Import/Hint}}",
"text": "<div class=\"tc-file-input-wrapper\">\n<$button tooltip={{$:/language/Buttons/Import/Hint}} aria-label={{$:/language/Buttons/Import/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/import-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Import/Caption}}/></span>\n</$list>\n</$button>\n<$browse tooltip={{$:/language/Buttons/Import/Hint}}/>\n</div>"
},
"$:/core/ui/Buttons/language": {
"title": "$:/core/ui/Buttons/language",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/globe}} {{$:/language/Buttons/Language/Caption}}",
"description": "{{$:/language/Buttons/Language/Hint}}",
"text": "\\define flag-title()\n$(languagePluginTitle)$/icon\n\\end\n<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/popup/language\">> tooltip={{$:/language/Buttons/Language/Hint}} aria-label={{$:/language/Buttons/Language/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n<span class=\"tc-image-button\">\n<$set name=\"languagePluginTitle\" value={{$:/language}}>\n<$image source=<<flag-title>>/>\n</$set>\n</span>\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Language/Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<qualify \"$:/state/popup/language\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down tc-drop-down-language-chooser\">\n<$linkcatcher to=\"$:/language\">\n<$list filter=\"[[$:/languages/en-GB]] [plugin-type[language]sort[description]]\">\n<$link>\n<span class=\"tc-drop-down-bullet\">\n<$reveal type=\"match\" state=\"$:/language\" text=<<currentTiddler>>>\n•\n</$reveal>\n<$reveal type=\"nomatch\" state=\"$:/language\" text=<<currentTiddler>>>\n \n</$reveal>\n</span>\n<span class=\"tc-image-button\">\n<$set name=\"languagePluginTitle\" value=<<currentTiddler>>>\n<$transclude subtiddler=<<flag-title>>>\n<$list filter=\"[all[current]field:title[$:/languages/en-GB]]\">\n<$transclude tiddler=\"$:/languages/en-GB/icon\"/>\n</$list>\n</$transclude>\n</$set>\n</span>\n<$view field=\"description\">\n<$view field=\"name\">\n<$view field=\"title\"/>\n</$view>\n</$view>\n</$link>\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>"
},
"$:/core/ui/Buttons/more-page-actions": {
"title": "$:/core/ui/Buttons/more-page-actions",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/down-arrow}} {{$:/language/Buttons/More/Caption}}",
"description": "{{$:/language/Buttons/More/Hint}}",
"text": "\\define config-title()\n$:/config/PageControlButtons/Visibility/$(listItem)$\n\\end\n<$button popup=<<qualify \"$:/state/popup/more\">> tooltip={{$:/language/Buttons/More/Hint}} aria-label={{$:/language/Buttons/More/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/down-arrow}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/More/Caption}}/></span>\n</$list>\n</$button><$reveal state=<<qualify \"$:/state/popup/more\">> type=\"popup\" position=\"below\" animate=\"yes\">\n\n<div class=\"tc-drop-down\">\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"tc-btn-invisible\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/PageControls]!has[draft.of]] -[[$:/core/ui/Buttons/more-page-actions]]\" variable=\"listItem\">\n\n<$reveal type=\"match\" state=<<config-title>> text=\"hide\">\n\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n\n</$reveal>\n\n</$list>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</div>\n\n</$reveal>"
},
"$:/core/ui/Buttons/new-image": {
"title": "$:/core/ui/Buttons/new-image",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/new-image-button}} {{$:/language/Buttons/NewImage/Caption}}",
"description": "{{$:/language/Buttons/NewImage/Hint}}",
"text": "<$button tooltip={{$:/language/Buttons/NewImage/Hint}} aria-label={{$:/language/Buttons/NewImage/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-new-tiddler\" type=\"image/jpeg\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/new-image-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/NewImage/Caption}}/></span>\n</$list>\n</$button>\n"
},
"$:/core/ui/Buttons/new-journal": {
"title": "$:/core/ui/Buttons/new-journal",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/new-journal-button}} {{$:/language/Buttons/NewJournal/Caption}}",
"description": "{{$:/language/Buttons/NewJournal/Hint}}",
"text": "\\define journalButton()\n<$button tooltip={{$:/language/Buttons/NewJournal/Hint}} aria-label={{$:/language/Buttons/NewJournal/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-new-tiddler\" title=<<now \"$(journalTitleTemplate)$\">> tags=\"$(journalTags)$\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/new-journal-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/NewJournal/Caption}}/></span>\n</$list>\n</$button>\n\\end\n<$set name=\"journalTitleTemplate\" value={{$:/config/NewJournal/Title}}>\n<$set name=\"journalTags\" value={{$:/config/NewJournal/Tags}}>\n<<journalButton>>\n</$set></$set>"
},
"$:/core/ui/Buttons/new-tiddler": {
"title": "$:/core/ui/Buttons/new-tiddler",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/new-button}} {{$:/language/Buttons/NewTiddler/Caption}}",
"description": "{{$:/language/Buttons/NewTiddler/Hint}}",
"text": "<$button message=\"tm-new-tiddler\" tooltip={{$:/language/Buttons/NewTiddler/Hint}} aria-label={{$:/language/Buttons/NewTiddler/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/new-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/NewTiddler/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/palette": {
"title": "$:/core/ui/Buttons/palette",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/palette}} {{$:/language/Buttons/Palette/Caption}}",
"description": "{{$:/language/Buttons/Palette/Hint}}",
"text": "<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/popup/palette\">> tooltip={{$:/language/Buttons/Palette/Hint}} aria-label={{$:/language/Buttons/Palette/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/palette}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Palette/Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<qualify \"$:/state/popup/palette\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\" style=\"font-size:0.7em;\">\n{{$:/snippets/paletteswitcher}}\n</div>\n</$reveal>"
},
"$:/core/ui/Buttons/refresh": {
"title": "$:/core/ui/Buttons/refresh",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/refresh-button}} {{$:/language/Buttons/Refresh/Caption}}",
"description": "{{$:/language/Buttons/Refresh/Hint}}",
"text": "<$button message=\"tm-browser-refresh\" tooltip={{$:/language/Buttons/Refresh/Hint}} aria-label={{$:/language/Buttons/Refresh/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/refresh-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Refresh/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/save-wiki": {
"title": "$:/core/ui/Buttons/save-wiki",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/save-button}} {{$:/language/Buttons/SaveWiki/Caption}}",
"description": "{{$:/language/Buttons/SaveWiki/Hint}}",
"text": "<$button message=\"tm-save-wiki\" param={{$:/config/SaveWikiButton/Template}} tooltip={{$:/language/Buttons/SaveWiki/Hint}} aria-label={{$:/language/Buttons/SaveWiki/Caption}} class=<<tv-config-toolbar-class>>>\n<span class=\"tc-dirty-indicator\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/save-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/SaveWiki/Caption}}/></span>\n</$list>\n</span>\n</$button>"
},
"$:/core/ui/Buttons/storyview": {
"title": "$:/core/ui/Buttons/storyview",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/storyview-classic}} {{$:/language/Buttons/StoryView/Caption}}",
"description": "{{$:/language/Buttons/StoryView/Hint}}",
"text": "\\define icon()\n$:/core/images/storyview-$(storyview)$\n\\end\n<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/popup/storyview\">> tooltip={{$:/language/Buttons/StoryView/Hint}} aria-label={{$:/language/Buttons/StoryView/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n<$set name=\"storyview\" value={{$:/view}}>\n<$transclude tiddler=<<icon>>/>\n</$set>\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/StoryView/Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<qualify \"$:/state/popup/storyview\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\">\n<$linkcatcher to=\"$:/view\">\n<$list filter=\"[storyviews[]]\" variable=\"storyview\">\n<$link to=<<storyview>>>\n<span class=\"tc-drop-down-bullet\">\n<$reveal type=\"match\" state=\"$:/view\" text=<<storyview>>>\n•\n</$reveal>\n<$reveal type=\"nomatch\" state=\"$:/view\" text=<<storyview>>>\n \n</$reveal>\n</span>\n<$transclude tiddler=<<icon>>/>\n<$text text=<<storyview>>/></$link>\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>"
},
"$:/core/ui/Buttons/tag-manager": {
"title": "$:/core/ui/Buttons/tag-manager",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/tag-button}} {{$:/language/Buttons/TagManager/Caption}}",
"description": "{{$:/language/Buttons/TagManager/Hint}}",
"text": "\\define control-panel-button(class)\n<$button to=\"$:/TagManager\" tooltip={{$:/language/Buttons/TagManager/Hint}} aria-label={{$:/language/Buttons/TagManager/Caption}} class=\"\"\"$(tv-config-toolbar-class)$ $class$\"\"\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/tag-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/TagManager/Caption}}/></span>\n</$list>\n</$button>\n\\end\n\n<$list filter=\"[list[$:/StoryList]] +[field:title[$:/TagManager]]\" emptyMessage=<<control-panel-button>>>\n<<control-panel-button \"tc-selected\">>\n</$list>\n"
},
"$:/core/ui/Buttons/theme": {
"title": "$:/core/ui/Buttons/theme",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/theme-button}} {{$:/language/Buttons/Theme/Caption}}",
"description": "{{$:/language/Buttons/Theme/Hint}}",
"text": "<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/popup/theme\">> tooltip={{$:/language/Buttons/Theme/Hint}} aria-label={{$:/language/Buttons/Theme/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/theme-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Theme/Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<qualify \"$:/state/popup/theme\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\">\n<$linkcatcher to=\"$:/theme\">\n<$list filter=\"[plugin-type[theme]sort[title]]\" variable=\"themeTitle\">\n<$link to=<<themeTitle>>>\n<span class=\"tc-drop-down-bullet\">\n<$reveal type=\"match\" state=\"$:/theme\" text=<<themeTitle>>>\n•\n</$reveal>\n<$reveal type=\"nomatch\" state=\"$:/theme\" text=<<themeTitle>>>\n \n</$reveal>\n</span>\n<$view tiddler=<<themeTitle>> field=\"name\"/>\n</$link>\n</$list>\n</$linkcatcher>\n</div>\n</$reveal>"
},
"$:/core/ui/Buttons/unfold-all": {
"title": "$:/core/ui/Buttons/unfold-all",
"tags": "$:/tags/PageControls",
"caption": "{{$:/core/images/unfold-all-button}} {{$:/language/Buttons/UnfoldAll/Caption}}",
"description": "{{$:/language/Buttons/UnfoldAll/Hint}}",
"text": "<$button tooltip={{$:/language/Buttons/UnfoldAll/Hint}} aria-label={{$:/language/Buttons/UnfoldAll/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-unfold-all-tiddlers\" $param=<<currentTiddler>> foldedStatePrefix=\"$:/state/folded/\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\" variable=\"listItem\">\n{{$:/core/images/unfold-all-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/UnfoldAll/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/PageTemplate/pagecontrols": {
"title": "$:/core/ui/PageTemplate/pagecontrols",
"text": "\\define config-title()\n$:/config/PageControlButtons/Visibility/$(listItem)$\n\\end\n<div class=\"tc-page-controls\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/PageControls]!has[draft.of]]\" variable=\"listItem\">\n<$reveal type=\"nomatch\" state=<<config-title>> text=\"hide\">\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n</$reveal>\n</$list>\n</div>\n\n"
},
"$:/core/ui/PageStylesheet": {
"title": "$:/core/ui/PageStylesheet",
"text": "<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n\n<$set name=\"currentTiddler\" value={{$:/language}}>\n\n<$set name=\"languageTitle\" value={{!!name}}>\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Stylesheet]!has[draft.of]]\">\n<$transclude mode=\"block\"/>\n</$list>\n\n</$set>\n\n</$set>\n\n</$importvariables>\n"
},
"$:/core/ui/PageTemplate/alerts": {
"title": "$:/core/ui/PageTemplate/alerts",
"tags": "$:/tags/PageTemplate",
"text": "<div class=\"tc-alerts\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Alert]!has[draft.of]]\" template=\"$:/core/ui/AlertTemplate\" storyview=\"pop\"/>\n\n</div>\n"
},
"$:/core/ui/PageTemplate/pluginreloadwarning": {
"title": "$:/core/ui/PageTemplate/pluginreloadwarning",
"tags": "$:/tags/PageTemplate",
"text": "\\define lingo-base() $:/language/\n\n<$list filter=\"[has[plugin-type]haschanged[]!plugin-type[import]limit[1]]\">\n\n<$reveal type=\"nomatch\" state=\"$:/temp/HidePluginWarning\" text=\"yes\">\n\n<div class=\"tc-plugin-reload-warning\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"\">\n\n<<lingo PluginReloadWarning>> <$button set=\"$:/temp/HidePluginWarning\" setTo=\"yes\" class=\"tc-btn-invisible\">{{$:/core/images/close-button}}</$button>\n\n</$set>\n\n</div>\n\n</$reveal>\n\n</$list>\n"
},
"$:/core/ui/PageTemplate/sidebar": {
"title": "$:/core/ui/PageTemplate/sidebar",
"tags": "$:/tags/PageTemplate",
"text": "<$scrollable fallthrough=\"no\" class=\"tc-sidebar-scrollable\">\n\n<div class=\"tc-sidebar-header\">\n\n<$reveal state=\"$:/state/sidebar\" type=\"match\" text=\"yes\" default=\"yes\" retain=\"yes\" animate=\"yes\">\n\n<h1 class=\"tc-site-title\">\n\n<$transclude tiddler=\"$:/SiteTitle\" mode=\"inline\"/>\n\n</h1>\n\n<div class=\"tc-site-subtitle\">\n\n<$transclude tiddler=\"$:/SiteSubtitle\" mode=\"inline\"/>\n\n</div>\n\n{{||$:/core/ui/PageTemplate/pagecontrols}}\n\n<$transclude tiddler=\"$:/core/ui/SideBarLists\" mode=\"inline\"/>\n\n</$reveal>\n\n</div>\n\n</$scrollable>"
},
"$:/core/ui/PageTemplate/story": {
"title": "$:/core/ui/PageTemplate/story",
"tags": "$:/tags/PageTemplate",
"text": "<section class=\"tc-story-river\">\n\n<section class=\"story-backdrop\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/AboveStory]!has[draft.of]]\">\n\n<$transclude/>\n\n</$list>\n\n</section>\n\n<$list filter=\"[list[$:/StoryList]]\" history=\"$:/HistoryList\" template=\"$:/core/ui/ViewTemplate\" editTemplate=\"$:/core/ui/EditTemplate\" storyview={{$:/view}} emptyMessage={{$:/config/EmptyStoryMessage}}/>\n\n<section class=\"story-frontdrop\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/BelowStory]!has[draft.of]]\">\n\n<$transclude/>\n\n</$list>\n\n</section>\n\n</section>\n"
},
"$:/core/ui/PageTemplate/topleftbar": {
"title": "$:/core/ui/PageTemplate/topleftbar",
"tags": "$:/tags/PageTemplate",
"text": "<span class=\"tc-topbar tc-topbar-left\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/TopLeftBar]!has[draft.of]]\" variable=\"listItem\">\n\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n\n</$list>\n\n</span>\n"
},
"$:/core/ui/PageTemplate/toprightbar": {
"title": "$:/core/ui/PageTemplate/toprightbar",
"tags": "$:/tags/PageTemplate",
"text": "<span class=\"tc-topbar tc-topbar-right\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/TopRightBar]!has[draft.of]]\" variable=\"listItem\">\n\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n\n</$list>\n\n</span>\n"
},
"$:/core/ui/PageTemplate": {
"title": "$:/core/ui/PageTemplate",
"text": "\\define containerClasses()\ntc-page-container tc-page-view-$(themeTitle)$ tc-language-$(languageTitle)$\n\\end\n\n<$importvariables filter=\"[[$:/core/ui/PageMacros]] [all[shadows+tiddlers]tag[$:/tags/Macro]!has[draft.of]]\">\n\n<$set name=\"tv-config-toolbar-icons\" value={{$:/config/Toolbar/Icons}}>\n\n<$set name=\"tv-config-toolbar-text\" value={{$:/config/Toolbar/Text}}>\n\n<$set name=\"tv-config-toolbar-class\" value={{$:/config/Toolbar/ButtonClass}}>\n\n<$set name=\"themeTitle\" value={{$:/view}}>\n\n<$set name=\"currentTiddler\" value={{$:/language}}>\n\n<$set name=\"languageTitle\" value={{!!name}}>\n\n<$set name=\"currentTiddler\" value=\"\">\n\n<div class=<<containerClasses>>>\n\n<$navigator story=\"$:/StoryList\" history=\"$:/HistoryList\" openLinkFromInsideRiver={{$:/config/Navigation/openLinkFromInsideRiver}} openLinkFromOutsideRiver={{$:/config/Navigation/openLinkFromOutsideRiver}}>\n\n<$dropzone>\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/PageTemplate]!has[draft.of]]\" variable=\"listItem\">\n\n<$transclude tiddler=<<listItem>>/>\n\n</$list>\n\n</$dropzone>\n\n</$navigator>\n\n</div>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</$importvariables>\n"
},
"$:/core/ui/PluginInfo": {
"title": "$:/core/ui/PluginInfo",
"text": "\\define localised-info-tiddler-title()\n$(currentTiddler)$/$(languageTitle)$/$(currentTab)$\n\\end\n\\define info-tiddler-title()\n$(currentTiddler)$/$(currentTab)$\n\\end\n<$transclude tiddler=<<localised-info-tiddler-title>> mode=\"block\">\n<$transclude tiddler=<<currentTiddler>> subtiddler=<<localised-info-tiddler-title>> mode=\"block\">\n<$transclude tiddler=<<currentTiddler>> subtiddler=<<info-tiddler-title>> mode=\"block\">\n{{$:/language/ControlPanel/Plugin/NoInfoFound/Hint}}\n</$transclude>\n</$transclude>\n</$transclude>\n"
},
"$:/core/ui/SearchResults": {
"title": "$:/core/ui/SearchResults",
"text": "<div class=\"tc-search-results\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]butfirst[]limit[1]]\" emptyMessage=\"\"\"\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]]\">\n<$transclude mode=\"block\"/>\n</$list>\n\"\"\">\n\n<$macrocall $name=\"tabs\" tabsList=\"[all[shadows+tiddlers]tag[$:/tags/SearchResults]!has[draft.of]]\" default={{$:/config/SearchResults/Default}}/>\n\n</$list>\n\n</div>\n"
},
"$:/core/ui/SideBar/More": {
"title": "$:/core/ui/SideBar/More",
"tags": "$:/tags/SideBar",
"caption": "{{$:/language/SideBar/More/Caption}}",
"text": "<div class=\"tc-more-sidebar\">\n<<tabs \"[all[shadows+tiddlers]tag[$:/tags/MoreSideBar]!has[draft.of]]\" \"$:/core/ui/MoreSideBar/Tags\" \"$:/state/tab/moresidebar\" \"tc-vertical\">>\n</div>\n"
},
"$:/core/ui/SideBar/Open": {
"title": "$:/core/ui/SideBar/Open",
"tags": "$:/tags/SideBar",
"caption": "{{$:/language/SideBar/Open/Caption}}",
"text": "\\define lingo-base() $:/language/CloseAll/\n<$list filter=\"[list[$:/StoryList]]\" history=\"$:/HistoryList\" storyview=\"pop\">\n\n<$button message=\"tm-close-tiddler\" tooltip={{$:/language/Buttons/Close/Hint}} aria-label={{$:/language/Buttons/Close/Caption}} class=\"tc-btn-invisible tc-btn-mini\">×</$button> <$link to={{!!title}}><$view field=\"title\"/></$link>\n\n</$list>\n\n<$button message=\"tm-close-all-tiddlers\" class=\"tc-btn-invisible tc-btn-mini\"><<lingo Button>></$button>\n"
},
"$:/core/ui/SideBar/Recent": {
"title": "$:/core/ui/SideBar/Recent",
"tags": "$:/tags/SideBar",
"caption": "{{$:/language/SideBar/Recent/Caption}}",
"text": "<$macrocall $name=\"timeline\" format={{$:/language/RecentChanges/DateFormat}}/>\n"
},
"$:/core/ui/SideBar/Tools": {
"title": "$:/core/ui/SideBar/Tools",
"tags": "$:/tags/SideBar",
"caption": "{{$:/language/SideBar/Tools/Caption}}",
"text": "\\define lingo-base() $:/language/ControlPanel/\n\\define config-title()\n$:/config/PageControlButtons/Visibility/$(listItem)$\n\\end\n\n<<lingo Basics/Version/Prompt>> <<version>>\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/PageControls]!has[draft.of]]\" variable=\"listItem\">\n\n<div style=\"position:relative;\">\n\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"/> <$transclude tiddler=<<listItem>>/> <i class=\"tc-muted\"><$transclude tiddler=<<listItem>> field=\"description\"/></i>\n\n</div>\n\n</$list>\n\n</$set>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/SideBarLists": {
"title": "$:/core/ui/SideBarLists",
"text": "<div class=\"tc-sidebar-lists\">\n\n<$set name=\"searchTiddler\" value=\"$:/temp/search\">\n<div class=\"tc-search\">\n<$edit-text tiddler=\"$:/temp/search\" type=\"search\" tag=\"input\" focus={{$:/config/Search/AutoFocus}} focusPopup=<<qualify \"$:/state/popup/search-dropdown\">> class=\"tc-popup-handle\"/>\n<$reveal state=\"$:/temp/search\" type=\"nomatch\" text=\"\">\n<$button tooltip={{$:/language/Buttons/AdvancedSearch/Hint}} aria-label={{$:/language/Buttons/AdvancedSearch/Caption}} class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/advancedsearch\" text={{$:/temp/search}}/>\n<$action-setfield $tiddler=\"$:/temp/search\" text=\"\"/>\n<$action-navigate $to=\"$:/AdvancedSearch\"/>\n{{$:/core/images/advanced-search-button}}\n</$button>\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"$:/temp/search\" text=\"\" />\n{{$:/core/images/close-button}}\n</$button>\n<$button popup=<<qualify \"$:/state/popup/search-dropdown\">> class=\"tc-btn-invisible\">\n<$set name=\"resultCount\" value=\"\"\"<$count filter=\"[!is[system]search{$(searchTiddler)$}]\"/>\"\"\">\n{{$:/core/images/down-arrow}} {{$:/language/Search/Matches}}\n</$set>\n</$button>\n</$reveal>\n<$reveal state=\"$:/temp/search\" type=\"match\" text=\"\">\n<$button to=\"$:/AdvancedSearch\" tooltip={{$:/language/Buttons/AdvancedSearch/Hint}} aria-label={{$:/language/Buttons/AdvancedSearch/Caption}} class=\"tc-btn-invisible\">\n{{$:/core/images/advanced-search-button}}\n</$button>\n</$reveal>\n</div>\n\n<$reveal tag=\"div\" class=\"tc-block-dropdown-wrapper\" state=\"$:/temp/search\" type=\"nomatch\" text=\"\">\n\n<$reveal tag=\"div\" class=\"tc-block-dropdown tc-search-drop-down tc-popup-handle\" state=<<qualify \"$:/state/popup/search-dropdown\">> type=\"nomatch\" text=\"\" default=\"\">\n\n{{$:/core/ui/SearchResults}}\n\n</$reveal>\n\n</$reveal>\n\n</$set>\n\n<$macrocall $name=\"tabs\" tabsList=\"[all[shadows+tiddlers]tag[$:/tags/SideBar]!has[draft.of]]\" default={{$:/config/DefaultSidebarTab}} state=\"$:/state/tab/sidebar\" />\n\n</div>\n"
},
"$:/TagManager": {
"title": "$:/TagManager",
"icon": "$:/core/images/tag-button",
"color": "#bbb",
"text": "\\define lingo-base() $:/language/TagManager/\n\\define iconEditorTab(type)\n<$list filter=\"[all[shadows+tiddlers]is[image]] [all[shadows+tiddlers]tag[$:/tags/Image]] -[type[application/pdf]] +[sort[title]] +[$type$is[system]]\">\n<$link to={{!!title}}>\n<$transclude/> <$view field=\"title\"/>\n</$link>\n</$list>\n\\end\n\\define iconEditor(title)\n<div class=\"tc-drop-down-wrapper\">\n<$button popup=<<qualify \"$:/state/popup/icon/$title$\">> class=\"tc-btn-invisible tc-btn-dropdown\">{{$:/core/images/down-arrow}}</$button>\n<$reveal state=<<qualify \"$:/state/popup/icon/$title$\">> type=\"popup\" position=\"belowleft\" text=\"\" default=\"\">\n<div class=\"tc-drop-down\">\n<$linkcatcher to=\"$title$!!icon\">\n<<iconEditorTab type:\"!\">>\n<hr/>\n<<iconEditorTab type:\"\">>\n</$linkcatcher>\n</div>\n</$reveal>\n</div>\n\\end\n\\define qualifyTitle(title)\n$title$$(currentTiddler)$\n\\end\n\\define toggleButton(state)\n<$reveal state=\"$state$\" type=\"match\" text=\"closed\" default=\"closed\">\n<$button set=\"$state$\" setTo=\"open\" class=\"tc-btn-invisible tc-btn-dropdown\" selectedClass=\"tc-selected\">\n{{$:/core/images/info-button}}\n</$button>\n</$reveal>\n<$reveal state=\"$state$\" type=\"match\" text=\"open\" default=\"closed\">\n<$button set=\"$state$\" setTo=\"closed\" class=\"tc-btn-invisible tc-btn-dropdown\" selectedClass=\"tc-selected\">\n{{$:/core/images/info-button}}\n</$button>\n</$reveal>\n\\end\n<table class=\"tc-tag-manager-table\">\n<tbody>\n<tr>\n<th><<lingo Colour/Heading>></th>\n<th class=\"tc-tag-manager-tag\"><<lingo Tag/Heading>></th>\n<th><<lingo Count/Heading>></th>\n<th><<lingo Icon/Heading>></th>\n<th><<lingo Info/Heading>></th>\n</tr>\n<$list filter=\"[tags[]!is[system]sort[title]]\">\n<tr>\n<td><$edit-text field=\"color\" tag=\"input\" type=\"color\"/></td>\n<td><$transclude tiddler=\"$:/core/ui/TagTemplate\"/></td>\n<td><$count filter=\"[all[current]tagging[]]\"/></td>\n<td>\n<$macrocall $name=\"iconEditor\" title={{!!title}}/>\n</td>\n<td>\n<$macrocall $name=\"toggleButton\" state=<<qualifyTitle \"$:/state/tag-manager/\">> /> \n</td>\n</tr>\n<tr>\n<td></td>\n<td colspan=\"4\">\n<$reveal state=<<qualifyTitle \"$:/state/tag-manager/\">> type=\"match\" text=\"open\" default=\"\">\n<table>\n<tbody>\n<tr><td><<lingo Colour/Heading>></td><td><$edit-text field=\"color\" tag=\"input\" type=\"text\" size=\"9\"/></td></tr>\n<tr><td><<lingo Icon/Heading>></td><td><$edit-text field=\"icon\" tag=\"input\" size=\"45\"/></td></tr>\n</tbody>\n</table>\n</$reveal>\n</td>\n</tr>\n</$list>\n<tr>\n<td></td>\n<td>\n{{$:/core/ui/UntaggedTemplate}}\n</td>\n<td>\n<small class=\"tc-menu-list-count\"><$count filter=\"[untagged[]!is[system]] -[tags[]]\"/></small>\n</td>\n<td></td>\n<td></td>\n</tr>\n</tbody>\n</table>\n"
},
"$:/core/ui/TagTemplate": {
"title": "$:/core/ui/TagTemplate",
"text": "\\define tag-styles()\nbackground-color:$(backgroundColor)$;\nfill:$(foregroundColor)$;\ncolor:$(foregroundColor)$;\n\\end\n\n\\define tag-body-inner(colour,fallbackTarget,colourA,colourB)\n<$vars foregroundColor=<<contrastcolour target:\"\"\"$colour$\"\"\" fallbackTarget:\"\"\"$fallbackTarget$\"\"\" colourA:\"\"\"$colourA$\"\"\" colourB:\"\"\"$colourB$\"\"\">> backgroundColor=\"\"\"$colour$\"\"\">\n<$button popup=<<qualify \"$:/state/popup/tag\">> class=\"tc-btn-invisible tc-tag-label\" style=<<tag-styles>>>\n<$transclude tiddler={{!!icon}}/> <$view field=\"title\" format=\"text\" />\n</$button>\n<$reveal state=<<qualify \"$:/state/popup/tag\">> type=\"popup\" position=\"below\" animate=\"yes\" class=\"tc-drop-down\"><$transclude tiddler=\"$:/core/ui/ListItemTemplate\"/>\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/TagDropdown]!has[draft.of]]\" variable=\"listItem\"> \n<$transclude tiddler=<<listItem>>/> \n</$list> \n<hr>\n<$list filter=\"[all[current]tagging[]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n</$reveal>\n</$vars>\n\\end\n\n\\define tag-body(colour,palette)\n<span class=\"tc-tag-list-item\">\n<$macrocall $name=\"tag-body-inner\" colour=\"\"\"$colour$\"\"\" fallbackTarget={{$palette$##tag-background}} colourA={{$palette$##foreground}} colourB={{$palette$##background}}/>\n</span>\n\\end\n\n<$macrocall $name=\"tag-body\" colour={{!!color}} palette={{$:/palette}}/>\n"
},
"$:/core/ui/TiddlerFieldTemplate": {
"title": "$:/core/ui/TiddlerFieldTemplate",
"text": "<tr class=\"tc-view-field\">\n<td class=\"tc-view-field-name\">\n<$text text=<<listItem>>/>\n</td>\n<td class=\"tc-view-field-value\">\n<$view field=<<listItem>>/>\n</td>\n</tr>"
},
"$:/core/ui/TiddlerFields": {
"title": "$:/core/ui/TiddlerFields",
"text": "<table class=\"tc-view-field-table\">\n<tbody>\n<$list filter=\"[all[current]fields[]sort[title]] -text\" template=\"$:/core/ui/TiddlerFieldTemplate\" variable=\"listItem\"/>\n</tbody>\n</table>\n"
},
"$:/core/ui/TiddlerInfo/Advanced/PluginInfo": {
"title": "$:/core/ui/TiddlerInfo/Advanced/PluginInfo",
"tags": "$:/tags/TiddlerInfo/Advanced",
"text": "\\define lingo-base() $:/language/TiddlerInfo/Advanced/PluginInfo/\n<$list filter=\"[all[current]has[plugin-type]]\">\n\n! <<lingo Heading>>\n\n<<lingo Hint>>\n<ul>\n<$list filter=\"[all[current]plugintiddlers[]sort[title]]\" emptyMessage=<<lingo Empty/Hint>>>\n<li>\n<$link to={{!!title}}>\n<$view field=\"title\"/>\n</$link>\n</li>\n</$list>\n</ul>\n\n</$list>\n"
},
"$:/core/ui/TiddlerInfo/Advanced/ShadowInfo": {
"title": "$:/core/ui/TiddlerInfo/Advanced/ShadowInfo",
"tags": "$:/tags/TiddlerInfo/Advanced",
"text": "\\define lingo-base() $:/language/TiddlerInfo/Advanced/ShadowInfo/\n<$set name=\"infoTiddler\" value=<<currentTiddler>>>\n\n''<<lingo Heading>>''\n\n<$list filter=\"[all[current]!is[shadow]]\">\n\n<<lingo NotShadow/Hint>>\n\n</$list>\n\n<$list filter=\"[all[current]is[shadow]]\">\n\n<<lingo Shadow/Hint>>\n\n<$list filter=\"[all[current]shadowsource[]]\">\n\n<$set name=\"pluginTiddler\" value=<<currentTiddler>>>\n<<lingo Shadow/Source>>\n</$set>\n\n</$list>\n\n<$list filter=\"[all[current]is[shadow]is[tiddler]]\">\n\n<<lingo OverriddenShadow/Hint>>\n\n</$list>\n\n\n</$list>\n</$set>\n"
},
"$:/core/ui/TiddlerInfo/Advanced": {
"title": "$:/core/ui/TiddlerInfo/Advanced",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/Advanced/Caption}}",
"text": "<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/TiddlerInfo/Advanced]!has[draft.of]]\" variable=\"listItem\">\n<$transclude tiddler=<<listItem>>/>\n\n</$list>\n"
},
"$:/core/ui/TiddlerInfo/Fields": {
"title": "$:/core/ui/TiddlerInfo/Fields",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/Fields/Caption}}",
"text": "<$transclude tiddler=\"$:/core/ui/TiddlerFields\"/>\n"
},
"$:/core/ui/TiddlerInfo/List": {
"title": "$:/core/ui/TiddlerInfo/List",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/List/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n<$list filter=\"[list{!!title}]\" emptyMessage=<<lingo List/Empty>> template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/TiddlerInfo/Listed": {
"title": "$:/core/ui/TiddlerInfo/Listed",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/Listed/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n<$list filter=\"[all[current]listed[]!is[system]]\" emptyMessage=<<lingo Listed/Empty>> template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/TiddlerInfo/References": {
"title": "$:/core/ui/TiddlerInfo/References",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/References/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n<$list filter=\"[all[current]backlinks[]sort[title]]\" emptyMessage=<<lingo References/Empty>> template=\"$:/core/ui/ListItemTemplate\">\n</$list>\n"
},
"$:/core/ui/TiddlerInfo/Tagging": {
"title": "$:/core/ui/TiddlerInfo/Tagging",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/Tagging/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n<$list filter=\"[all[current]tagging[]]\" emptyMessage=<<lingo Tagging/Empty>> template=\"$:/core/ui/ListItemTemplate\"/>\n"
},
"$:/core/ui/TiddlerInfo/Tools": {
"title": "$:/core/ui/TiddlerInfo/Tools",
"tags": "$:/tags/TiddlerInfo",
"caption": "{{$:/language/TiddlerInfo/Tools/Caption}}",
"text": "\\define lingo-base() $:/language/TiddlerInfo/\n\\define config-title()\n$:/config/ViewToolbarButtons/Visibility/$(listItem)$\n\\end\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ViewToolbar]!has[draft.of]]\" variable=\"listItem\">\n\n<$checkbox tiddler=<<config-title>> field=\"text\" checked=\"show\" unchecked=\"hide\" default=\"show\"/> <$transclude tiddler=<<listItem>>/> <i class=\"tc-muted\"><$transclude tiddler=<<listItem>> field=\"description\"/></i>\n\n</$list>\n\n</$set>\n\n</$set>\n\n</$set>\n"
},
"$:/core/ui/TiddlerInfo": {
"title": "$:/core/ui/TiddlerInfo",
"text": "<$macrocall $name=\"tabs\" tabsList=\"[all[shadows+tiddlers]tag[$:/tags/TiddlerInfo]!has[draft.of]]\" default={{$:/config/TiddlerInfo/Default}}/>"
},
"$:/core/ui/TopBar/menu": {
"title": "$:/core/ui/TopBar/menu",
"tags": "$:/tags/TopRightBar",
"text": "<$reveal state=\"$:/state/sidebar\" type=\"nomatch\" text=\"no\">\n<$button set=\"$:/state/sidebar\" setTo=\"no\" tooltip={{$:/language/Buttons/HideSideBar/Hint}} aria-label={{$:/language/Buttons/HideSideBar/Caption}} class=\"tc-btn-invisible\">{{$:/core/images/chevron-right}}</$button>\n</$reveal>\n<$reveal state=\"$:/state/sidebar\" type=\"match\" text=\"no\">\n<$button set=\"$:/state/sidebar\" setTo=\"yes\" tooltip={{$:/language/Buttons/ShowSideBar/Hint}} aria-label={{$:/language/Buttons/ShowSideBar/Caption}} class=\"tc-btn-invisible\">{{$:/core/images/chevron-left}}</$button>\n</$reveal>\n"
},
"$:/core/ui/UntaggedTemplate": {
"title": "$:/core/ui/UntaggedTemplate",
"text": "\\define lingo-base() $:/language/SideBar/\n<$button popup=<<qualify \"$:/state/popup/tag\">> class=\"tc-btn-invisible tc-untagged-label tc-tag-label\">\n<<lingo Tags/Untagged/Caption>>\n</$button>\n<$reveal state=<<qualify \"$:/state/popup/tag\">> type=\"popup\" position=\"below\">\n<div class=\"tc-drop-down\">\n<$list filter=\"[untagged[]!is[system]] -[tags[]] +[sort[title]]\" template=\"$:/core/ui/ListItemTemplate\"/>\n</div>\n</$reveal>\n"
},
"$:/core/ui/ViewTemplate/body": {
"title": "$:/core/ui/ViewTemplate/body",
"tags": "$:/tags/ViewTemplate",
"text": "<$reveal tag=\"div\" class=\"tc-tiddler-body\" type=\"nomatch\" state=<<folded-state>> text=\"hide\" retain=\"yes\" animate=\"yes\">\n\n<$list filter=\"[all[current]!has[plugin-type]!field:hide-body[yes]]\">\n\n<$transclude>\n\n<$transclude tiddler=\"$:/language/MissingTiddler/Hint\"/>\n\n</$transclude>\n\n</$list>\n\n</$reveal>\n"
},
"$:/core/ui/ViewTemplate/classic": {
"title": "$:/core/ui/ViewTemplate/classic",
"tags": "$:/tags/ViewTemplate $:/tags/EditTemplate",
"text": "\\define lingo-base() $:/language/ClassicWarning/\n<$list filter=\"[all[current]type[text/x-tiddlywiki]]\">\n<div class=\"tc-message-box\">\n\n<<lingo Hint>>\n\n<$button set=\"!!type\" setTo=\"text/vnd.tiddlywiki\"><<lingo Upgrade/Caption>></$button>\n\n</div>\n</$list>\n"
},
"$:/core/ui/ViewTemplate/import": {
"title": "$:/core/ui/ViewTemplate/import",
"tags": "$:/tags/ViewTemplate",
"text": "\\define lingo-base() $:/language/Import/\n\n<$list filter=\"[all[current]field:plugin-type[import]]\">\n\n<div class=\"tc-import\">\n\n<<lingo Listing/Hint>>\n\n<$button message=\"tm-delete-tiddler\" param=<<currentTiddler>>><<lingo Listing/Cancel/Caption>></$button>\n<$button message=\"tm-perform-import\" param=<<currentTiddler>>><<lingo Listing/Import/Caption>></$button>\n\n{{||$:/core/ui/ImportListing}}\n\n<$button message=\"tm-delete-tiddler\" param=<<currentTiddler>>><<lingo Listing/Cancel/Caption>></$button>\n<$button message=\"tm-perform-import\" param=<<currentTiddler>>><<lingo Listing/Import/Caption>></$button>\n\n</div>\n\n</$list>\n"
},
"$:/core/ui/ViewTemplate/plugin": {
"title": "$:/core/ui/ViewTemplate/plugin",
"tags": "$:/tags/ViewTemplate",
"text": "<$list filter=\"[all[current]has[plugin-type]] -[all[current]field:plugin-type[import]]\">\n\n{{||$:/core/ui/TiddlerInfo/Advanced/PluginInfo}}\n\n</$list>\n"
},
"$:/core/ui/ViewTemplate/subtitle": {
"title": "$:/core/ui/ViewTemplate/subtitle",
"tags": "$:/tags/ViewTemplate",
"text": "<$reveal type=\"nomatch\" state=<<folded-state>> text=\"hide\" tag=\"div\" retain=\"yes\" animate=\"yes\">\n<div class=\"tc-subtitle\">\n<$link to={{!!modifier}}>\n<$view field=\"modifier\"/>\n</$link> <$view field=\"modified\" format=\"date\" template={{$:/language/Tiddler/DateFormat}}/>\n</div>\n</$reveal>\n"
},
"$:/core/ui/ViewTemplate/tags": {
"title": "$:/core/ui/ViewTemplate/tags",
"tags": "$:/tags/ViewTemplate",
"text": "<$reveal type=\"nomatch\" state=<<folded-state>> text=\"hide\" tag=\"div\" retain=\"yes\" animate=\"yes\">\n<div class=\"tc-tags-wrapper\"><$list filter=\"[all[current]tags[]sort[title]]\" template=\"$:/core/ui/TagTemplate\" storyview=\"pop\"/></div>\n</$reveal>"
},
"$:/core/ui/ViewTemplate/title": {
"title": "$:/core/ui/ViewTemplate/title",
"tags": "$:/tags/ViewTemplate",
"text": "\\define title-styles()\nfill:$(foregroundColor)$;\n\\end\n\\define config-title()\n$:/config/ViewToolbarButtons/Visibility/$(listItem)$\n\\end\n<div class=\"tc-tiddler-title\">\n<div class=\"tc-titlebar\">\n<span class=\"tc-tiddler-controls\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ViewToolbar]!has[draft.of]]\" variable=\"listItem\"><$reveal type=\"nomatch\" state=<<config-title>> text=\"hide\"><$transclude tiddler=<<listItem>>/></$reveal></$list>\n</span>\n<$set name=\"tv-wikilinks\" value={{$:/config/Tiddlers/TitleLinks}}>\n<$link>\n<$set name=\"foregroundColor\" value={{!!color}}>\n<span class=\"tc-tiddler-title-icon\" style=<<title-styles>>>\n<$transclude tiddler={{!!icon}}/>\n</span>\n</$set>\n<$list filter=\"[all[current]removeprefix[$:/]]\">\n<h2 class=\"tc-title\" title={{$:/language/SystemTiddler/Tooltip}}>\n<span class=\"tc-system-title-prefix\">$:/</span><$text text=<<currentTiddler>>/>\n</h2>\n</$list>\n<$list filter=\"[all[current]!prefix[$:/]]\">\n<h2 class=\"tc-title\">\n<$view field=\"title\"/>\n</h2>\n</$list>\n</$link>\n</$set>\n</div>\n\n<$reveal type=\"nomatch\" text=\"\" default=\"\" state=<<tiddlerInfoState>> class=\"tc-tiddler-info tc-popup-handle\" animate=\"yes\" retain=\"yes\">\n\n<$transclude tiddler=\"$:/core/ui/TiddlerInfo\"/>\n\n</$reveal>\n</div>"
},
"$:/core/ui/ViewTemplate/unfold": {
"title": "$:/core/ui/ViewTemplate/unfold",
"tags": "$:/tags/ViewTemplate",
"text": "<$reveal tag=\"div\" type=\"nomatch\" state=\"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold-bar\" text=\"hide\">\n<$reveal tag=\"div\" type=\"nomatch\" state=<<folded-state>> text=\"hide\" default=\"show\" retain=\"yes\" animate=\"yes\">\n<$button tooltip={{$:/language/Buttons/Fold/Hint}} aria-label={{$:/language/Buttons/Fold/Caption}} class=\"tc-fold-banner\">\n<$action-sendmessage $message=\"tm-fold-tiddler\" $param=<<currentTiddler>> foldedState=<<folded-state>>/>\n{{$:/core/images/chevron-up}}\n</$button>\n</$reveal>\n<$reveal tag=\"div\" type=\"nomatch\" state=<<folded-state>> text=\"show\" default=\"show\" retain=\"yes\" animate=\"yes\">\n<$button tooltip={{$:/language/Buttons/Unfold/Hint}} aria-label={{$:/language/Buttons/Unfold/Caption}} class=\"tc-unfold-banner\">\n<$action-sendmessage $message=\"tm-fold-tiddler\" $param=<<currentTiddler>> foldedState=<<folded-state>>/>\n{{$:/core/images/chevron-down}}\n</$button>\n</$reveal>\n</$reveal>\n"
},
"$:/core/ui/ViewTemplate": {
"title": "$:/core/ui/ViewTemplate",
"text": "\\define frame-classes()\ntc-tiddler-frame tc-tiddler-view-frame $(missingTiddlerClass)$ $(shadowTiddlerClass)$ $(systemTiddlerClass)$ $(tiddlerTagClasses)$\n\\end\n\\define folded-state()\n$:/state/folded/$(currentTiddler)$\n\\end\n<$set name=\"storyTiddler\" value=<<currentTiddler>>><$set name=\"tiddlerInfoState\" value=<<qualify \"$:/state/popup/tiddler-info\">>><$tiddler tiddler=<<currentTiddler>>><div class=<<frame-classes>>><$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ViewTemplate]!has[draft.of]]\" variable=\"listItem\"><$transclude tiddler=<<listItem>>/></$list>\n</div>\n</$tiddler></$set></$set>\n"
},
"$:/core/ui/Buttons/clone": {
"title": "$:/core/ui/Buttons/clone",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/clone-button}} {{$:/language/Buttons/Clone/Caption}}",
"description": "{{$:/language/Buttons/Clone/Hint}}",
"text": "<$button message=\"tm-new-tiddler\" param=<<currentTiddler>> tooltip={{$:/language/Buttons/Clone/Hint}} aria-label={{$:/language/Buttons/Clone/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/clone-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Clone/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/close-others": {
"title": "$:/core/ui/Buttons/close-others",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/close-others-button}} {{$:/language/Buttons/CloseOthers/Caption}}",
"description": "{{$:/language/Buttons/CloseOthers/Hint}}",
"text": "<$button message=\"tm-close-other-tiddlers\" param=<<currentTiddler>> tooltip={{$:/language/Buttons/CloseOthers/Hint}} aria-label={{$:/language/Buttons/CloseOthers/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/close-others-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/CloseOthers/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/close": {
"title": "$:/core/ui/Buttons/close",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/close-button}} {{$:/language/Buttons/Close/Caption}}",
"description": "{{$:/language/Buttons/Close/Hint}}",
"text": "<$button message=\"tm-close-tiddler\" tooltip={{$:/language/Buttons/Close/Hint}} aria-label={{$:/language/Buttons/Close/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/close-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Close/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/edit": {
"title": "$:/core/ui/Buttons/edit",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/edit-button}} {{$:/language/Buttons/Edit/Caption}}",
"description": "{{$:/language/Buttons/Edit/Hint}}",
"text": "<$button message=\"tm-edit-tiddler\" tooltip={{$:/language/Buttons/Edit/Hint}} aria-label={{$:/language/Buttons/Edit/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/edit-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Edit/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/export-tiddler": {
"title": "$:/core/ui/Buttons/export-tiddler",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/export-button}} {{$:/language/Buttons/ExportTiddler/Caption}}",
"description": "{{$:/language/Buttons/ExportTiddler/Hint}}",
"text": "\\define makeExportFilter()\n[[$(currentTiddler)$]]\n\\end\n<$macrocall $name=\"exportButton\" exportFilter=<<makeExportFilter>> lingoBase=\"$:/language/Buttons/ExportTiddler/\" baseFilename=<<currentTiddler>>/>"
},
"$:/core/ui/Buttons/fold-bar": {
"title": "$:/core/ui/Buttons/fold-bar",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/language/Buttons/Fold/FoldBar/Caption}}",
"description": "{{$:/language/Buttons/Fold/FoldBar/Hint}}",
"text": "<!-- This dummy toolbar button is here to allow visibility of the fold-bar to be controlled as if it were a toolbar button -->"
},
"$:/core/ui/Buttons/fold-others": {
"title": "$:/core/ui/Buttons/fold-others",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/fold-others-button}} {{$:/language/Buttons/FoldOthers/Caption}}",
"description": "{{$:/language/Buttons/FoldOthers/Hint}}",
"text": "<$button tooltip={{$:/language/Buttons/FoldOthers/Hint}} aria-label={{$:/language/Buttons/FoldOthers/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-fold-other-tiddlers\" $param=<<currentTiddler>> foldedStatePrefix=\"$:/state/folded/\"/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\" variable=\"listItem\">\n{{$:/core/images/fold-others-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/FoldOthers/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/fold": {
"title": "$:/core/ui/Buttons/fold",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/fold-button}} {{$:/language/Buttons/Fold/Caption}}",
"description": "{{$:/language/Buttons/Fold/Hint}}",
"text": "<$reveal type=\"nomatch\" state=<<folded-state>> text=\"hide\" default=\"show\"><$button tooltip={{$:/language/Buttons/Fold/Hint}} aria-label={{$:/language/Buttons/Fold/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-fold-tiddler\" $param=<<currentTiddler>> foldedState=<<folded-state>>/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\" variable=\"listItem\">\n{{$:/core/images/fold-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\">\n<$text text={{$:/language/Buttons/Fold/Caption}}/>\n</span>\n</$list>\n</$button></$reveal><$reveal type=\"match\" state=<<folded-state>> text=\"hide\" default=\"show\"><$button tooltip={{$:/language/Buttons/Unfold/Hint}} aria-label={{$:/language/Buttons/Unfold/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-fold-tiddler\" $param=<<currentTiddler>> foldedState=<<folded-state>>/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\" variable=\"listItem\">\n{{$:/core/images/unfold-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\">\n<$text text={{$:/language/Buttons/Unfold/Caption}}/>\n</span>\n</$list>\n</$button></$reveal>"
},
"$:/core/ui/Buttons/info": {
"title": "$:/core/ui/Buttons/info",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/info-button}} {{$:/language/Buttons/Info/Caption}}",
"description": "{{$:/language/Buttons/Info/Hint}}",
"text": "<$button popup=<<tiddlerInfoState>> tooltip={{$:/language/Buttons/Info/Hint}} aria-label={{$:/language/Buttons/Info/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/info-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Info/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/more-tiddler-actions": {
"title": "$:/core/ui/Buttons/more-tiddler-actions",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/down-arrow}} {{$:/language/Buttons/More/Caption}}",
"description": "{{$:/language/Buttons/More/Hint}}",
"text": "\\define config-title()\n$:/config/ViewToolbarButtons/Visibility/$(listItem)$\n\\end\n<$button popup=<<qualify \"$:/state/popup/more\">> tooltip={{$:/language/Buttons/More/Hint}} aria-label={{$:/language/Buttons/More/Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/down-arrow}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/More/Caption}}/></span>\n</$list>\n</$button><$reveal state=<<qualify \"$:/state/popup/more\">> type=\"popup\" position=\"below\" animate=\"yes\">\n\n<div class=\"tc-drop-down\">\n\n<$set name=\"tv-config-toolbar-icons\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-text\" value=\"yes\">\n\n<$set name=\"tv-config-toolbar-class\" value=\"tc-btn-invisible\">\n\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/ViewToolbar]!has[draft.of]] -[[$:/core/ui/Buttons/more-tiddler-actions]]\" variable=\"listItem\">\n\n<$reveal type=\"match\" state=<<config-title>> text=\"hide\">\n\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n\n</$reveal>\n\n</$list>\n\n</$set>\n\n</$set>\n\n</$set>\n\n</div>\n\n</$reveal>"
},
"$:/core/ui/Buttons/new-here": {
"title": "$:/core/ui/Buttons/new-here",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/new-here-button}} {{$:/language/Buttons/NewHere/Caption}}",
"description": "{{$:/language/Buttons/NewHere/Hint}}",
"text": "\\define newHereButtonTags()\n[[$(currentTiddler)$]]\n\\end\n\\define newHereButton()\n<$button tooltip={{$:/language/Buttons/NewHere/Hint}} aria-label={{$:/language/Buttons/NewHere/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-new-tiddler\" tags=<<newHereButtonTags>>/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/new-here-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/NewHere/Caption}}/></span>\n</$list>\n</$button>\n\\end\n<<newHereButton>>"
},
"$:/core/ui/Buttons/new-journal-here": {
"title": "$:/core/ui/Buttons/new-journal-here",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/new-journal-button}} {{$:/language/Buttons/NewJournalHere/Caption}}",
"description": "{{$:/language/Buttons/NewJournalHere/Hint}}",
"text": "\\define journalButtonTags()\n[[$(currentTiddlerTag)$]] $(journalTags)$\n\\end\n\\define journalButton()\n<$button tooltip={{$:/language/Buttons/NewJournalHere/Hint}} aria-label={{$:/language/Buttons/NewJournalHere/Caption}} class=<<tv-config-toolbar-class>>>\n<$action-sendmessage $message=\"tm-new-tiddler\" title=<<now \"$(journalTitleTemplate)$\">> tags=<<journalButtonTags>>/>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/new-journal-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/NewJournalHere/Caption}}/></span>\n</$list>\n</$button>\n\\end\n<$set name=\"journalTitleTemplate\" value={{$:/config/NewJournal/Title}}>\n<$set name=\"journalTags\" value={{$:/config/NewJournal/Tags}}>\n<$set name=\"currentTiddlerTag\" value=<<currentTiddler>>>\n<<journalButton>>\n</$set></$set></$set>"
},
"$:/core/ui/Buttons/open-window": {
"title": "$:/core/ui/Buttons/open-window",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/open-window}} {{$:/language/Buttons/OpenWindow/Caption}}",
"description": "{{$:/language/Buttons/OpenWindow/Hint}}",
"text": "<$button message=\"tm-open-window\" tooltip={{$:/language/Buttons/OpenWindow/Hint}} aria-label={{$:/language/Buttons/OpenWindow/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/open-window}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/OpenWindow/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/permalink": {
"title": "$:/core/ui/Buttons/permalink",
"tags": "$:/tags/ViewToolbar",
"caption": "{{$:/core/images/permalink-button}} {{$:/language/Buttons/Permalink/Caption}}",
"description": "{{$:/language/Buttons/Permalink/Hint}}",
"text": "<$button message=\"tm-permalink\" tooltip={{$:/language/Buttons/Permalink/Hint}} aria-label={{$:/language/Buttons/Permalink/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/permalink-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Permalink/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/core/ui/Buttons/permaview": {
"title": "$:/core/ui/Buttons/permaview",
"tags": "$:/tags/ViewToolbar $:/tags/PageControls",
"caption": "{{$:/core/images/permaview-button}} {{$:/language/Buttons/Permaview/Caption}}",
"description": "{{$:/language/Buttons/Permaview/Hint}}",
"text": "<$button message=\"tm-permaview\" tooltip={{$:/language/Buttons/Permaview/Hint}} aria-label={{$:/language/Buttons/Permaview/Caption}} class=<<tv-config-toolbar-class>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/permaview-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/Permaview/Caption}}/></span>\n</$list>\n</$button>"
},
"$:/DefaultTiddlers": {
"title": "$:/DefaultTiddlers",
"text": "GettingStarted\n"
},
"$:/temp/advancedsearch": {
"title": "$:/temp/advancedsearch",
"text": ""
},
"$:/snippets/allfields": {
"title": "$:/snippets/allfields",
"text": "\\define renderfield(title)\n<tr class=\"tc-view-field\"><td class=\"tc-view-field-name\">''$title$'':</td><td class=\"tc-view-field-value\">//{{$:/language/Docs/Fields/$title$}}//</td></tr>\n\\end\n<table class=\"tc-view-field-table\"><tbody><$list filter=\"[fields[]sort[title]]\" variable=\"listItem\"><$macrocall $name=\"renderfield\" title=<<listItem>>/></$list>\n</tbody></table>\n"
},
"$:/config/AnimationDuration": {
"title": "$:/config/AnimationDuration",
"text": "400"
},
"$:/config/AutoSave": {
"title": "$:/config/AutoSave",
"text": "yes"
},
"$:/config/BitmapEditor/Colour": {
"title": "$:/config/BitmapEditor/Colour",
"text": "#444"
},
"$:/config/BitmapEditor/ImageSizes": {
"title": "$:/config/BitmapEditor/ImageSizes",
"text": "[[62px 100px]] [[100px 62px]] [[124px 200px]] [[200px 124px]] [[248px 400px]] [[371px 600px]] [[400px 248px]] [[556px 900px]] [[600px 371px]] [[742px 1200px]] [[900px 556px]] [[1200px 742px]]"
},
"$:/config/BitmapEditor/LineWidth": {
"title": "$:/config/BitmapEditor/LineWidth",
"text": "3px"
},
"$:/config/BitmapEditor/LineWidths": {
"title": "$:/config/BitmapEditor/LineWidths",
"text": "0.25px 0.5px 1px 2px 3px 4px 6px 8px 10px 16px 20px 28px 40px 56px 80px"
},
"$:/config/BitmapEditor/Opacities": {
"title": "$:/config/BitmapEditor/Opacities",
"text": "0.01 0.025 0.05 0.075 0.1 0.15 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0"
},
"$:/config/BitmapEditor/Opacity": {
"title": "$:/config/BitmapEditor/Opacity",
"text": "1.0"
},
"$:/config/DefaultSidebarTab": {
"title": "$:/config/DefaultSidebarTab",
"text": "$:/core/ui/SideBar/Open"
},
"$:/config/Drafts/TypingTimeout": {
"title": "$:/config/Drafts/TypingTimeout",
"text": "400"
},
"$:/config/EditTemplateFields/Visibility/title": {
"title": "$:/config/EditTemplateFields/Visibility/title",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/tags": {
"title": "$:/config/EditTemplateFields/Visibility/tags",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/text": {
"title": "$:/config/EditTemplateFields/Visibility/text",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/creator": {
"title": "$:/config/EditTemplateFields/Visibility/creator",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/created": {
"title": "$:/config/EditTemplateFields/Visibility/created",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/modified": {
"title": "$:/config/EditTemplateFields/Visibility/modified",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/modifier": {
"title": "$:/config/EditTemplateFields/Visibility/modifier",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/type": {
"title": "$:/config/EditTemplateFields/Visibility/type",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/draft.title": {
"title": "$:/config/EditTemplateFields/Visibility/draft.title",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/draft.of": {
"title": "$:/config/EditTemplateFields/Visibility/draft.of",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/revision": {
"title": "$:/config/EditTemplateFields/Visibility/revision",
"text": "hide"
},
"$:/config/EditTemplateFields/Visibility/bag": {
"title": "$:/config/EditTemplateFields/Visibility/bag",
"text": "hide"
},
"$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-4": {
"title": "$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-4",
"text": "hide"
},
"$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-5": {
"title": "$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-5",
"text": "hide"
},
"$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-6": {
"title": "$:/config/EditorToolbarButtons/Visibility/$:/core/ui/EditorToolbar/heading-6",
"text": "hide"
},
"$:/config/EditorTypeMappings/image/gif": {
"title": "$:/config/EditorTypeMappings/image/gif",
"text": "bitmap"
},
"$:/config/EditorTypeMappings/image/jpeg": {
"title": "$:/config/EditorTypeMappings/image/jpeg",
"text": "bitmap"
},
"$:/config/EditorTypeMappings/image/jpg": {
"title": "$:/config/EditorTypeMappings/image/jpg",
"text": "bitmap"
},
"$:/config/EditorTypeMappings/image/png": {
"title": "$:/config/EditorTypeMappings/image/png",
"text": "bitmap"
},
"$:/config/EditorTypeMappings/image/x-icon": {
"title": "$:/config/EditorTypeMappings/image/x-icon",
"text": "bitmap"
},
"$:/config/EditorTypeMappings/text/vnd.tiddlywiki": {
"title": "$:/config/EditorTypeMappings/text/vnd.tiddlywiki",
"text": "text"
},
"$:/config/MissingLinks": {
"title": "$:/config/MissingLinks",
"text": "yes"
},
"$:/config/Navigation/UpdateAddressBar": {
"title": "$:/config/Navigation/UpdateAddressBar",
"text": "no"
},
"$:/config/Navigation/UpdateHistory": {
"title": "$:/config/Navigation/UpdateHistory",
"text": "no"
},
"$:/config/OfficialPluginLibrary": {
"title": "$:/config/OfficialPluginLibrary",
"tags": "$:/tags/PluginLibrary",
"url": "http://tiddlywiki.com/library/v5.1.13/index.html",
"caption": "{{$:/language/OfficialPluginLibrary}}",
"text": "{{$:/language/OfficialPluginLibrary/Hint}}\n"
},
"$:/config/Navigation/openLinkFromInsideRiver": {
"title": "$:/config/Navigation/openLinkFromInsideRiver",
"text": "below"
},
"$:/config/Navigation/openLinkFromOutsideRiver": {
"title": "$:/config/Navigation/openLinkFromOutsideRiver",
"text": "top"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/advanced-search": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/advanced-search",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/close-all": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/close-all",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/encryption": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/encryption",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/export-page": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/export-page",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/fold-all": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/fold-all",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/full-screen": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/full-screen",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/home": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/home",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/refresh": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/refresh",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/import": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/import",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/language": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/language",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/tag-manager": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/tag-manager",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/more-page-actions": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/more-page-actions",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/new-journal": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/new-journal",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/new-image": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/new-image",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/palette": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/palette",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/permaview": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/permaview",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/storyview": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/storyview",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/theme": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/theme",
"text": "hide"
},
"$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/unfold-all": {
"title": "$:/config/PageControlButtons/Visibility/$:/core/ui/Buttons/unfold-all",
"text": "hide"
},
"$:/config/Performance/Instrumentation": {
"title": "$:/config/Performance/Instrumentation",
"text": "no"
},
"$:/config/SaveWikiButton/Template": {
"title": "$:/config/SaveWikiButton/Template",
"text": "$:/core/save/all"
},
"$:/config/SaverFilter": {
"title": "$:/config/SaverFilter",
"text": "[all[]] -[[$:/HistoryList]] -[[$:/StoryList]] -[[$:/Import]] -[[$:/isEncrypted]] -[[$:/UploadName]] -[prefix[$:/state/]] -[prefix[$:/temp/]]"
},
"$:/config/Search/AutoFocus": {
"title": "$:/config/Search/AutoFocus",
"text": "true"
},
"$:/config/SearchResults/Default": {
"title": "$:/config/SearchResults/Default",
"text": "$:/core/ui/DefaultSearchResultList"
},
"$:/config/ShortcutInfo/bold": {
"title": "$:/config/ShortcutInfo/bold",
"text": "{{$:/language/Buttons/Bold/Hint}}"
},
"$:/config/ShortcutInfo/cancel-edit-tiddler": {
"title": "$:/config/ShortcutInfo/cancel-edit-tiddler",
"text": "{{$:/language/Buttons/Cancel/Hint}}"
},
"$:/config/ShortcutInfo/excise": {
"title": "$:/config/ShortcutInfo/excise",
"text": "{{$:/language/Buttons/Excise/Hint}}"
},
"$:/config/ShortcutInfo/heading-1": {
"title": "$:/config/ShortcutInfo/heading-1",
"text": "{{$:/language/Buttons/Heading1/Hint}}"
},
"$:/config/ShortcutInfo/heading-2": {
"title": "$:/config/ShortcutInfo/heading-2",
"text": "{{$:/language/Buttons/Heading2/Hint}}"
},
"$:/config/ShortcutInfo/heading-3": {
"title": "$:/config/ShortcutInfo/heading-3",
"text": "{{$:/language/Buttons/Heading3/Hint}}"
},
"$:/config/ShortcutInfo/heading-4": {
"title": "$:/config/ShortcutInfo/heading-4",
"text": "{{$:/language/Buttons/Heading4/Hint}}"
},
"$:/config/ShortcutInfo/heading-5": {
"title": "$:/config/ShortcutInfo/heading-5",
"text": "{{$:/language/Buttons/Heading5/Hint}}"
},
"$:/config/ShortcutInfo/heading-6": {
"title": "$:/config/ShortcutInfo/heading-6",
"text": "{{$:/language/Buttons/Heading6/Hint}}"
},
"$:/config/ShortcutInfo/italic": {
"title": "$:/config/ShortcutInfo/italic",
"text": "{{$:/language/Buttons/Italic/Hint}}"
},
"$:/config/ShortcutInfo/link": {
"title": "$:/config/ShortcutInfo/link",
"text": "{{$:/language/Buttons/Link/Hint}}"
},
"$:/config/ShortcutInfo/list-bullet": {
"title": "$:/config/ShortcutInfo/list-bullet",
"text": "{{$:/language/Buttons/ListBullet/Hint}}"
},
"$:/config/ShortcutInfo/list-number": {
"title": "$:/config/ShortcutInfo/list-number",
"text": "{{$:/language/Buttons/ListNumber/Hint}}"
},
"$:/config/ShortcutInfo/mono-block": {
"title": "$:/config/ShortcutInfo/mono-block",
"text": "{{$:/language/Buttons/MonoBlock/Hint}}"
},
"$:/config/ShortcutInfo/mono-line": {
"title": "$:/config/ShortcutInfo/mono-line",
"text": "{{$:/language/Buttons/MonoLine/Hint}}"
},
"$:/config/ShortcutInfo/picture": {
"title": "$:/config/ShortcutInfo/picture",
"text": "{{$:/language/Buttons/Picture/Hint}}"
},
"$:/config/ShortcutInfo/preview": {
"title": "$:/config/ShortcutInfo/preview",
"text": "{{$:/language/Buttons/Preview/Hint}}"
},
"$:/config/ShortcutInfo/quote": {
"title": "$:/config/ShortcutInfo/quote",
"text": "{{$:/language/Buttons/Quote/Hint}}"
},
"$:/config/ShortcutInfo/save-tiddler": {
"title": "$:/config/ShortcutInfo/save-tiddler",
"text": "{{$:/language/Buttons/Save/Hint}}"
},
"$:/config/ShortcutInfo/stamp": {
"title": "$:/config/ShortcutInfo/stamp",
"text": "{{$:/language/Buttons/Stamp/Hint}}"
},
"$:/config/ShortcutInfo/strikethrough": {
"title": "$:/config/ShortcutInfo/strikethrough",
"text": "{{$:/language/Buttons/Strikethrough/Hint}}"
},
"$:/config/ShortcutInfo/subscript": {
"title": "$:/config/ShortcutInfo/subscript",
"text": "{{$:/language/Buttons/Subscript/Hint}}"
},
"$:/config/ShortcutInfo/superscript": {
"title": "$:/config/ShortcutInfo/superscript",
"text": "{{$:/language/Buttons/Superscript/Hint}}"
},
"$:/config/ShortcutInfo/underline": {
"title": "$:/config/ShortcutInfo/underline",
"text": "{{$:/language/Buttons/Underline/Hint}}"
},
"$:/config/SyncFilter": {
"title": "$:/config/SyncFilter",
"text": "[is[tiddler]] -[[$:/HistoryList]] -[[$:/Import]] -[[$:/isEncrypted]] -[prefix[$:/status/]] -[prefix[$:/state/]] -[prefix[$:/temp/]]"
},
"$:/config/TextEditor/EditorHeight/Height": {
"title": "$:/config/TextEditor/EditorHeight/Height",
"text": "400px"
},
"$:/config/TextEditor/EditorHeight/Mode": {
"title": "$:/config/TextEditor/EditorHeight/Mode",
"text": "auto"
},
"$:/config/TiddlerInfo/Default": {
"title": "$:/config/TiddlerInfo/Default",
"text": "$:/core/ui/TiddlerInfo/Fields"
},
"$:/config/Tiddlers/TitleLinks": {
"title": "$:/config/Tiddlers/TitleLinks",
"text": "no"
},
"$:/config/Toolbar/ButtonClass": {
"title": "$:/config/Toolbar/ButtonClass",
"text": "tc-btn-invisible"
},
"$:/config/Toolbar/Icons": {
"title": "$:/config/Toolbar/Icons",
"text": "yes"
},
"$:/config/Toolbar/Text": {
"title": "$:/config/Toolbar/Text",
"text": "no"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/clone": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/clone",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/close-others": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/close-others",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/export-tiddler": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/export-tiddler",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/info": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/info",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/more-tiddler-actions": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/more-tiddler-actions",
"text": "show"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/new-here": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/new-here",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/new-journal-here": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/new-journal-here",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/open-window": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/open-window",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/permalink": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/permalink",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/permaview": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/permaview",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/delete": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/delete",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold-bar": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold-bar",
"text": "hide"
},
"$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold-others": {
"title": "$:/config/ViewToolbarButtons/Visibility/$:/core/ui/Buttons/fold-others",
"text": "hide"
},
"$:/config/shortcuts-mac/bold": {
"title": "$:/config/shortcuts-mac/bold",
"text": "meta-B"
},
"$:/config/shortcuts-mac/italic": {
"title": "$:/config/shortcuts-mac/italic",
"text": "meta-I"
},
"$:/config/shortcuts-mac/underline": {
"title": "$:/config/shortcuts-mac/underline",
"text": "meta-U"
},
"$:/config/shortcuts-not-mac/bold": {
"title": "$:/config/shortcuts-not-mac/bold",
"text": "ctrl-B"
},
"$:/config/shortcuts-not-mac/italic": {
"title": "$:/config/shortcuts-not-mac/italic",
"text": "ctrl-I"
},
"$:/config/shortcuts-not-mac/underline": {
"title": "$:/config/shortcuts-not-mac/underline",
"text": "ctrl-U"
},
"$:/config/shortcuts/cancel-edit-tiddler": {
"title": "$:/config/shortcuts/cancel-edit-tiddler",
"text": "escape"
},
"$:/config/shortcuts/excise": {
"title": "$:/config/shortcuts/excise",
"text": "ctrl-E"
},
"$:/config/shortcuts/heading-1": {
"title": "$:/config/shortcuts/heading-1",
"text": "ctrl-1"
},
"$:/config/shortcuts/heading-2": {
"title": "$:/config/shortcuts/heading-2",
"text": "ctrl-2"
},
"$:/config/shortcuts/heading-3": {
"title": "$:/config/shortcuts/heading-3",
"text": "ctrl-3"
},
"$:/config/shortcuts/heading-4": {
"title": "$:/config/shortcuts/heading-4",
"text": "ctrl-4"
},
"$:/config/shortcuts/heading-5": {
"title": "$:/config/shortcuts/heading-5",
"text": "ctrl-5"
},
"$:/config/shortcuts/heading-6": {
"title": "$:/config/shortcuts/heading-6",
"text": "ctrl-6"
},
"$:/config/shortcuts/link": {
"title": "$:/config/shortcuts/link",
"text": "ctrl-L"
},
"$:/config/shortcuts/list-bullet": {
"title": "$:/config/shortcuts/list-bullet",
"text": "ctrl-shift-L"
},
"$:/config/shortcuts/list-number": {
"title": "$:/config/shortcuts/list-number",
"text": "ctrl-shift-N"
},
"$:/config/shortcuts/mono-block": {
"title": "$:/config/shortcuts/mono-block",
"text": "ctrl-shift-M"
},
"$:/config/shortcuts/mono-line": {
"title": "$:/config/shortcuts/mono-line",
"text": "ctrl-M"
},
"$:/config/shortcuts/picture": {
"title": "$:/config/shortcuts/picture",
"text": "ctrl-shift-I"
},
"$:/config/shortcuts/preview": {
"title": "$:/config/shortcuts/preview",
"text": "alt-P"
},
"$:/config/shortcuts/quote": {
"title": "$:/config/shortcuts/quote",
"text": "ctrl-Q"
},
"$:/config/shortcuts/save-tiddler": {
"title": "$:/config/shortcuts/save-tiddler",
"text": "ctrl+enter"
},
"$:/config/shortcuts/stamp": {
"title": "$:/config/shortcuts/stamp",
"text": "ctrl-S"
},
"$:/config/shortcuts/strikethrough": {
"title": "$:/config/shortcuts/strikethrough",
"text": "ctrl-T"
},
"$:/config/shortcuts/subscript": {
"title": "$:/config/shortcuts/subscript",
"text": "ctrl-shift-B"
},
"$:/config/shortcuts/superscript": {
"title": "$:/config/shortcuts/superscript",
"text": "ctrl-shift-P"
},
"$:/config/WikiParserRules/Inline/wikilink": {
"title": "$:/config/WikiParserRules/Inline/wikilink",
"text": "enable"
},
"$:/snippets/currpalettepreview": {
"title": "$:/snippets/currpalettepreview",
"text": "\\define swatchStyle()\nbackground-color: $(swatchColour)$;\n\\end\n\\define swatch(colour)\n<$set name=\"swatchColour\" value={{##$colour$}}>\n<div class=\"tc-swatch\" style=<<swatchStyle>>/>\n</$set>\n\\end\n<div class=\"tc-swatches-horiz\">\n<<swatch foreground>>\n<<swatch background>>\n<<swatch muted-foreground>>\n<<swatch primary>>\n<<swatch page-background>>\n<<swatch tab-background>>\n<<swatch tiddler-info-background>>\n</div>\n"
},
"$:/snippets/download-wiki-button": {
"title": "$:/snippets/download-wiki-button",
"text": "\\define lingo-base() $:/language/ControlPanel/Tools/Download/\n<$button class=\"tc-btn-big-green\">\n<$action-sendmessage $message=\"tm-download-file\" $param=\"$:/core/save/all\" filename=\"index.html\"/>\n<<lingo Full/Caption>> {{$:/core/images/save-button}}\n</$button>"
},
"$:/language": {
"title": "$:/language",
"text": "$:/languages/en-GB"
},
"$:/snippets/languageswitcher": {
"title": "$:/snippets/languageswitcher",
"text": "{{$:/language/ControlPanel/Basics/Language/Prompt}} <$select tiddler=\"$:/language\">\n<$list filter=\"[[$:/languages/en-GB]] [plugin-type[language]sort[description]]\">\n<option value=<<currentTiddler>>><$view field=\"description\"><$view field=\"name\"><$view field=\"title\"/></$view></$view></option>\n</$list>\n</$select>"
},
"$:/core/macros/CSS": {
"title": "$:/core/macros/CSS",
"tags": "$:/tags/Macro",
"text": "\\define colour(name)\n<$transclude tiddler={{$:/palette}} index=\"$name$\"><$transclude tiddler=\"$:/palettes/Vanilla\" index=\"$name$\"/></$transclude>\n\\end\n\n\\define color(name)\n<<colour $name$>>\n\\end\n\n\\define box-shadow(shadow)\n``\n -webkit-box-shadow: $shadow$;\n -moz-box-shadow: $shadow$;\n box-shadow: $shadow$;\n``\n\\end\n\n\\define filter(filter)\n``\n -webkit-filter: $filter$;\n -moz-filter: $filter$;\n filter: $filter$;\n``\n\\end\n\n\\define transition(transition)\n``\n -webkit-transition: $transition$;\n -moz-transition: $transition$;\n transition: $transition$;\n``\n\\end\n\n\\define transform-origin(origin)\n``\n -webkit-transform-origin: $origin$;\n -moz-transform-origin: $origin$;\n transform-origin: $origin$;\n``\n\\end\n\n\\define background-linear-gradient(gradient)\n``\nbackground-image: linear-gradient($gradient$);\nbackground-image: -o-linear-gradient($gradient$);\nbackground-image: -moz-linear-gradient($gradient$);\nbackground-image: -webkit-linear-gradient($gradient$);\nbackground-image: -ms-linear-gradient($gradient$);\n``\n\\end\n\n\\define datauri(title)\n<$macrocall $name=\"makedatauri\" type={{$title$!!type}} text={{$title$}}/>\n\\end\n\n\\define if-sidebar(text)\n<$reveal state=\"$:/state/sidebar\" type=\"match\" text=\"yes\" default=\"yes\">$text$</$reveal>\n\\end\n\n\\define if-no-sidebar(text)\n<$reveal state=\"$:/state/sidebar\" type=\"nomatch\" text=\"yes\" default=\"yes\">$text$</$reveal>\n\\end\n"
},
"$:/core/macros/colour-picker": {
"title": "$:/core/macros/colour-picker",
"tags": "$:/tags/Macro",
"text": "\\define colour-picker-update-recent()\n<$action-listops\n\t$tiddler=\"$:/config/ColourPicker/Recent\"\n\t$subfilter=\"$(colour-picker-value)$ [list[$:/config/ColourPicker/Recent]remove[$(colour-picker-value)$]] +[limit[8]]\"\n/>\n\\end\n\n\\define colour-picker-inner(actions)\n<$button tag=\"a\" tooltip=\"\"\"$(colour-picker-value)$\"\"\">\n\n$(colour-picker-update-recent)$\n\n$actions$\n\n<div style=\"background-color: $(colour-picker-value)$; width: 100%; height: 100%; border-radius: 50%;\"/>\n\n</$button>\n\\end\n\n\\define colour-picker-recent-inner(actions)\n<$set name=\"colour-picker-value\" value=\"$(recentColour)$\">\n<$macrocall $name=\"colour-picker-inner\" actions=\"\"\"$actions$\"\"\"/>\n</$set>\n\\end\n\n\\define colour-picker-recent(actions)\n{{$:/language/ColourPicker/Recent}} <$list filter=\"[list[$:/config/ColourPicker/Recent]]\" variable=\"recentColour\">\n<$macrocall $name=\"colour-picker-recent-inner\" actions=\"\"\"$actions$\"\"\"/></$list>\n\\end\n\n\\define colour-picker(actions)\n<div class=\"tc-colour-chooser\">\n\n<$macrocall $name=\"colour-picker-recent\" actions=\"\"\"$actions$\"\"\"/>\n\n---\n\n<$list filter=\"LightPink Pink Crimson LavenderBlush PaleVioletRed HotPink DeepPink MediumVioletRed Orchid Thistle Plum Violet Magenta Fuchsia DarkMagenta Purple MediumOrchid DarkViolet DarkOrchid Indigo BlueViolet MediumPurple MediumSlateBlue SlateBlue DarkSlateBlue Lavender GhostWhite Blue MediumBlue MidnightBlue DarkBlue Navy RoyalBlue CornflowerBlue LightSteelBlue LightSlateGrey SlateGrey DodgerBlue AliceBlue SteelBlue LightSkyBlue SkyBlue DeepSkyBlue LightBlue PowderBlue CadetBlue Azure LightCyan PaleTurquoise Cyan Aqua DarkTurquoise DarkSlateGrey DarkCyan Teal MediumTurquoise LightSeaGreen Turquoise Aquamarine MediumAquamarine MediumSpringGreen MintCream SpringGreen MediumSeaGreen SeaGreen Honeydew LightGreen PaleGreen DarkSeaGreen LimeGreen Lime ForestGreen Green DarkGreen Chartreuse LawnGreen GreenYellow DarkOliveGreen YellowGreen OliveDrab Beige LightGoldenrodYellow Ivory LightYellow Yellow Olive DarkKhaki LemonChiffon PaleGoldenrod Khaki Gold Cornsilk Goldenrod DarkGoldenrod FloralWhite OldLace Wheat Moccasin Orange PapayaWhip BlanchedAlmond NavajoWhite AntiqueWhite Tan BurlyWood Bisque DarkOrange Linen Peru PeachPuff SandyBrown Chocolate SaddleBrown Seashell Sienna LightSalmon Coral OrangeRed DarkSalmon Tomato MistyRose Salmon Snow LightCoral RosyBrown IndianRed Red Brown FireBrick DarkRed Maroon White WhiteSmoke Gainsboro LightGrey Silver DarkGrey Grey DimGrey Black\" variable=\"colour-picker-value\">\n<$macrocall $name=\"colour-picker-inner\" actions=\"\"\"$actions$\"\"\"/>\n</$list>\n\n---\n\n<$edit-text tiddler=\"$:/config/ColourPicker/New\" tag=\"input\" default=\"\" placeholder=\"\"/> \n<$edit-text tiddler=\"$:/config/ColourPicker/New\" type=\"color\" tag=\"input\"/>\n<$set name=\"colour-picker-value\" value={{$:/config/ColourPicker/New}}>\n<$macrocall $name=\"colour-picker-inner\" actions=\"\"\"$actions$\"\"\"/>\n</$set>\n\n</div>\n\n\\end\n"
},
"$:/core/macros/export": {
"title": "$:/core/macros/export",
"tags": "$:/tags/Macro",
"text": "\\define exportButtonFilename(baseFilename)\n$baseFilename$$(extension)$\n\\end\n\n\\define exportButton(exportFilter:\"[!is[system]sort[title]]\",lingoBase,baseFilename:\"tiddlers\")\n<span class=\"tc-popup-keep\">\n<$button popup=<<qualify \"$:/state/popup/export\">> tooltip={{$lingoBase$Hint}} aria-label={{$lingoBase$Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/export-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$lingoBase$Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<qualify \"$:/state/popup/export\">> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Exporter]]\">\n<$set name=\"extension\" value={{!!extension}}>\n<$button class=\"tc-btn-invisible\">\n<$action-sendmessage $message=\"tm-download-file\" $param=<<currentTiddler>> exportFilter=\"\"\"$exportFilter$\"\"\" filename=<<exportButtonFilename \"\"\"$baseFilename$\"\"\">>/>\n<$action-deletetiddler $tiddler=<<qualify \"$:/state/popup/export\">>/>\n<$transclude field=\"description\"/>\n</$button>\n</$set>\n</$list>\n</div>\n</$reveal>\n\\end\n"
},
"$:/core/macros/image-picker": {
"title": "$:/core/macros/image-picker",
"tags": "$:/tags/Macro",
"text": "\\define image-picker-inner(actions)\n<$button tag=\"a\" tooltip=\"\"\"$(imageTitle)$\"\"\">\n\n$actions$\n\n<$transclude tiddler=<<imageTitle>>/>\n\n</$button>\n\\end\n\n\\define image-picker(actions,subfilter:\"\")\n<div class=\"tc-image-chooser\">\n\n<$list filter=\"[all[shadows+tiddlers]is[image]$subfilter$!has[draft.of]] -[type[application/pdf]] +[sort[title]]\" variable=\"imageTitle\">\n\n<$macrocall $name=\"image-picker-inner\" actions=\"\"\"$actions$\"\"\"/>\n\n</$list>\n\n</div>\n\n\\end\n\n"
},
"$:/core/macros/lingo": {
"title": "$:/core/macros/lingo",
"tags": "$:/tags/Macro",
"text": "\\define lingo-base()\n$:/language/\n\\end\n\n\\define lingo(title)\n{{$(lingo-base)$$title$}}\n\\end\n"
},
"$:/core/macros/list": {
"title": "$:/core/macros/list",
"tags": "$:/tags/Macro",
"text": "\\define list-links(filter,type:\"ul\",subtype:\"li\",class:\"\")\n<$type$ class=\"$class$\">\n<$list filter=\"$filter$\">\n<$subtype$>\n<$link to={{!!title}}>\n<$transclude field=\"caption\">\n<$view field=\"title\"/>\n</$transclude>\n</$link>\n</$subtype$>\n</$list>\n</$type$>\n\\end\n"
},
"$:/core/macros/tabs": {
"title": "$:/core/macros/tabs",
"tags": "$:/tags/Macro",
"text": "\\define tabs(tabsList,default,state:\"$:/state/tab\",class,template)\n<div class=\"tc-tab-set $class$\">\n<div class=\"tc-tab-buttons $class$\">\n<$list filter=\"$tabsList$\" variable=\"currentTab\"><$set name=\"save-currentTiddler\" value=<<currentTiddler>>><$tiddler tiddler=<<currentTab>>><$button set=<<qualify \"$state$\">> setTo=<<currentTab>> default=\"$default$\" selectedClass=\"tc-tab-selected\" tooltip={{!!tooltip}}>\n<$tiddler tiddler=<<save-currentTiddler>>>\n<$set name=\"tv-wikilinks\" value=\"no\">\n<$transclude tiddler=<<currentTab>> field=\"caption\">\n<$macrocall $name=\"currentTab\" $type=\"text/plain\" $output=\"text/plain\"/>\n</$transclude>\n</$set></$tiddler></$button></$tiddler></$set></$list>\n</div>\n<div class=\"tc-tab-divider $class$\"/>\n<div class=\"tc-tab-content $class$\">\n<$list filter=\"$tabsList$\" variable=\"currentTab\">\n\n<$reveal type=\"match\" state=<<qualify \"$state$\">> text=<<currentTab>> default=\"$default$\">\n\n<$transclude tiddler=\"$template$\" mode=\"block\">\n\n<$transclude tiddler=<<currentTab>> mode=\"block\"/>\n\n</$transclude>\n\n</$reveal>\n\n</$list>\n</div>\n</div>\n\\end\n"
},
"$:/core/macros/tag": {
"title": "$:/core/macros/tag",
"tags": "$:/tags/Macro",
"text": "\\define tag(tag)\n{{$tag$||$:/core/ui/TagTemplate}}\n\\end\n"
},
"$:/core/macros/thumbnails": {
"title": "$:/core/macros/thumbnails",
"tags": "$:/tags/Macro",
"text": "\\define thumbnail(link,icon,color,background-color,image,caption,width:\"280\",height:\"157\")\n<$link to=\"\"\"$link$\"\"\"><div class=\"tc-thumbnail-wrapper\">\n<div class=\"tc-thumbnail-image\" style=\"width:$width$px;height:$height$px;\"><$reveal type=\"nomatch\" text=\"\" default=\"\"\"$image$\"\"\" tag=\"div\" style=\"width:$width$px;height:$height$px;\">\n[img[$image$]]\n</$reveal><$reveal type=\"match\" text=\"\" default=\"\"\"$image$\"\"\" tag=\"div\" class=\"tc-thumbnail-background\" style=\"width:$width$px;height:$height$px;background-color:$background-color$;\"></$reveal></div><div class=\"tc-thumbnail-icon\" style=\"fill:$color$;color:$color$;\">\n$icon$\n</div><div class=\"tc-thumbnail-caption\">\n$caption$\n</div>\n</div></$link>\n\\end\n\n\\define thumbnail-right(link,icon,color,background-color,image,caption,width:\"280\",height:\"157\")\n<div class=\"tc-thumbnail-right-wrapper\"><<thumbnail \"\"\"$link$\"\"\" \"\"\"$icon$\"\"\" \"\"\"$color$\"\"\" \"\"\"$background-color$\"\"\" \"\"\"$image$\"\"\" \"\"\"$caption$\"\"\" \"\"\"$width$\"\"\" \"\"\"$height$\"\"\">></div>\n\\end\n\n\\define list-thumbnails(filter,width:\"280\",height:\"157\")\n<$list filter=\"\"\"$filter$\"\"\"><$macrocall $name=\"thumbnail\" link={{!!link}} icon={{!!icon}} color={{!!color}} background-color={{!!background-color}} image={{!!image}} caption={{!!caption}} width=\"\"\"$width$\"\"\" height=\"\"\"$height$\"\"\"/></$list>\n\\end\n"
},
"$:/core/macros/timeline": {
"created": "20141212105914482",
"modified": "20141212110330815",
"tags": "$:/tags/Macro",
"title": "$:/core/macros/timeline",
"type": "text/vnd.tiddlywiki",
"text": "\\define timeline-title()\n<!-- Override this macro with a global macro \n of the same name if you need to change \n how titles are displayed on the timeline \n -->\n<$view field=\"title\"/>\n\\end\n\\define timeline(limit:\"100\",format:\"DDth MMM YYYY\",subfilter:\"\",dateField:\"modified\")\n<div class=\"tc-timeline\">\n<$list filter=\"[!is[system]$subfilter$has[$dateField$]!sort[$dateField$]limit[$limit$]eachday[$dateField$]]\">\n<div class=\"tc-menu-list-item\">\n<$view field=\"$dateField$\" format=\"date\" template=\"$format$\"/>\n<$list filter=\"[sameday:$dateField${!!$dateField$}!is[system]$subfilter$!sort[$dateField$]]\">\n<div class=\"tc-menu-list-subitem\">\n<$link to={{!!title}}>\n<<timeline-title>>\n</$link>\n</div>\n</$list>\n</div>\n</$list>\n</div>\n\\end\n"
},
"$:/core/macros/toc": {
"title": "$:/core/macros/toc",
"tags": "$:/tags/Macro",
"text": "\\define toc-caption()\n<$set name=\"tv-wikilinks\" value=\"no\">\n<$transclude field=\"caption\">\n<$view field=\"title\"/>\n</$transclude>\n</$set>\n\\end\n\n\\define toc-body(rootTag,tag,sort:\"\",itemClassFilter)\n<ol class=\"tc-toc\">\n<$list filter=\"\"\"[all[shadows+tiddlers]tag[$tag$]!has[draft.of]$sort$]\"\"\">\n<$set name=\"toc-item-class\" filter=\"\"\"$itemClassFilter$\"\"\" value=\"toc-item-selected\" emptyValue=\"toc-item\">\n<li class=<<toc-item-class>>>\n<$list filter=\"[all[current]toc-link[no]]\" emptyMessage=\"<$link><$view field='caption'><$view field='title'/></$view></$link>\">\n<<toc-caption>>\n</$list>\n<$list filter=\"\"\"[all[current]] -[[$rootTag$]]\"\"\">\n<$macrocall $name=\"toc-body\" rootTag=\"\"\"$rootTag$\"\"\" tag=<<currentTiddler>> sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\"/>\n</$list>\n</li>\n</$set>\n</$list>\n</ol>\n\\end\n\n\\define toc(tag,sort:\"\",itemClassFilter)\n<<toc-body rootTag:\"\"\"$tag$\"\"\" tag:\"\"\"$tag$\"\"\" sort:\"\"\"$sort$\"\"\" itemClassFilter:\"\"\"itemClassFilter\"\"\">>\n\\end\n\n\\define toc-linked-expandable-body(tag,sort:\"\",itemClassFilter)\n<$set name=\"toc-state\" value=<<qualify \"\"\"$:/state/toc/$tag$-$(currentTiddler)$\"\"\">>>\n<$set name=\"toc-item-class\" filter=\"\"\"$itemClassFilter$\"\"\" value=\"toc-item-selected\" emptyValue=\"toc-item\">\n<li class=<<toc-item-class>>>\n<$link>\n<$reveal type=\"nomatch\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"open\" class=\"tc-btn-invisible\">\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"close\" class=\"tc-btn-invisible\">\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n<<toc-caption>>\n</$link>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$macrocall $name=\"toc-expandable\" tag=<<currentTiddler>> sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\"/>\n</$reveal>\n</li>\n</$set>\n</$set>\n\\end\n\n\\define toc-unlinked-expandable-body(tag,sort:\"\",itemClassFilter)\n<$set name=\"toc-state\" value=<<qualify \"\"\"$:/state/toc/$tag$-$(currentTiddler)$\"\"\">>>\n<$set name=\"toc-item-class\" filter=\"\"\"$itemClassFilter$\"\"\" value=\"toc-item-selected\" emptyValue=\"toc-item\">\n<li class=<<toc-item-class>>>\n<$reveal type=\"nomatch\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"open\" class=\"tc-btn-invisible\">\n{{$:/core/images/right-arrow}}\n<<toc-caption>>\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"close\" class=\"tc-btn-invisible\">\n{{$:/core/images/down-arrow}}\n<<toc-caption>>\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$macrocall $name=\"toc-expandable\" tag=<<currentTiddler>> sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\"/>\n</$reveal>\n</li>\n</$set>\n</$set>\n\\end\n\n\\define toc-expandable-empty-message()\n<<toc-linked-expandable-body tag:\"\"\"$(tag)$\"\"\" sort:\"\"\"$(sort)$\"\"\" itemClassFilter:\"\"\"$(itemClassFilter)$\"\"\">>\n\\end\n\n\\define toc-expandable(tag,sort:\"\",itemClassFilter)\n<$vars tag=\"\"\"$tag$\"\"\" sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\">\n<ol class=\"tc-toc toc-expandable\">\n<$list filter=\"[all[shadows+tiddlers]tag[$tag$]!has[draft.of]$sort$]\">\n<$list filter=\"[all[current]toc-link[no]]\" emptyMessage=<<toc-expandable-empty-message>>>\n<<toc-unlinked-expandable-body tag:\"\"\"$tag$\"\"\" sort:\"\"\"$sort$\"\"\" itemClassFilter:\"\"\"itemClassFilter\"\"\">>\n</$list>\n</$list>\n</ol>\n</$vars>\n\\end\n\n\\define toc-linked-selective-expandable-body(tag,sort:\"\",itemClassFilter)\n<$set name=\"toc-state\" value=<<qualify \"\"\"$:/state/toc/$tag$-$(currentTiddler)$\"\"\">>>\n<$set name=\"toc-item-class\" filter=\"\"\"$itemClassFilter$\"\"\" value=\"toc-item-selected\" emptyValue=\"toc-item\">\n<li class=<<toc-item-class>>>\n<$link>\n<$list filter=\"[all[current]tagging[]limit[1]]\" variable=\"ignore\" emptyMessage=\"<$button class='tc-btn-invisible'>{{$:/core/images/blank}}</$button>\">\n<$reveal type=\"nomatch\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"open\" class=\"tc-btn-invisible\">\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"close\" class=\"tc-btn-invisible\">\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n</$list>\n<<toc-caption>>\n</$link>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$macrocall $name=\"toc-selective-expandable\" tag=<<currentTiddler>> sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\"/>\n</$reveal>\n</li>\n</$set>\n</$set>\n\\end\n\n\\define toc-unlinked-selective-expandable-body(tag,sort:\"\",itemClassFilter)\n<$set name=\"toc-state\" value=<<qualify \"\"\"$:/state/toc/$tag$-$(currentTiddler)$\"\"\">>>\n<$set name=\"toc-item-class\" filter=\"\"\"$itemClassFilter$\"\"\" value=\"toc-item-selected\" emptyValue=\"toc-item\">\n<li class=<<toc-item-class>>>\n<$list filter=\"[all[current]tagging[]limit[1]]\" variable=\"ignore\" emptyMessage=\"<$button class='tc-btn-invisible'>{{$:/core/images/blank}}</$button> <$view field='caption'><$view field='title'/></$view>\">\n<$reveal type=\"nomatch\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"open\" class=\"tc-btn-invisible\">\n{{$:/core/images/right-arrow}}\n<<toc-caption>>\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$button set=<<toc-state>> setTo=\"close\" class=\"tc-btn-invisible\">\n{{$:/core/images/down-arrow}}\n<<toc-caption>>\n</$button>\n</$reveal>\n</$list>\n<$reveal type=\"match\" state=<<toc-state>> text=\"open\">\n<$macrocall $name=\"\"\"toc-selective-expandable\"\"\" tag=<<currentTiddler>> sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\"/>\n</$reveal>\n</li>\n</$set>\n</$set>\n\\end\n\n\\define toc-selective-expandable-empty-message()\n<<toc-linked-selective-expandable-body tag:\"\"\"$(tag)$\"\"\" sort:\"\"\"$(sort)$\"\"\" itemClassFilter:\"\"\"$(itemClassFilter)$\"\"\">>\n\\end\n\n\\define toc-selective-expandable(tag,sort:\"\",itemClassFilter)\n<$vars tag=\"\"\"$tag$\"\"\" sort=\"\"\"$sort$\"\"\" itemClassFilter=\"\"\"$itemClassFilter$\"\"\">\n<ol class=\"tc-toc toc-selective-expandable\">\n<$list filter=\"[all[shadows+tiddlers]tag[$tag$]!has[draft.of]$sort$]\">\n<$list filter=\"[all[current]toc-link[no]]\" variable=\"ignore\" emptyMessage=<<toc-selective-expandable-empty-message>>>\n<<toc-unlinked-selective-expandable-body tag:\"\"\"$tag$\"\"\" sort:\"\"\"$sort$\"\"\" itemClassFilter:\"\"\"$itemClassFilter$\"\"\">>\n</$list>\n</$list>\n</ol>\n</$vars>\n\\end\n\n\\define toc-tabbed-selected-item-filter(selectedTiddler)\n[all[current]field:title{$selectedTiddler$}]\n\\end\n\n\\define toc-tabbed-external-nav(tag,sort:\"\",selectedTiddler:\"$:/temp/toc/selectedTiddler\",unselectedText,missingText,template:\"\")\n<$tiddler tiddler={{$selectedTiddler$}}>\n<div class=\"tc-tabbed-table-of-contents\">\n<$linkcatcher to=\"$selectedTiddler$\">\n<div class=\"tc-table-of-contents\">\n<$macrocall $name=\"toc-selective-expandable\" tag=\"\"\"$tag$\"\"\" sort=\"\"\"$sort$\"\"\" itemClassFilter=<<toc-tabbed-selected-item-filter selectedTiddler:\"\"\"$selectedTiddler$\"\"\">>/>\n</div>\n</$linkcatcher>\n<div class=\"tc-tabbed-table-of-contents-content\">\n<$reveal state=\"\"\"$selectedTiddler$\"\"\" type=\"nomatch\" text=\"\">\n<$transclude mode=\"block\" tiddler=\"$template$\">\n<h1><<toc-caption>></h1>\n<$transclude mode=\"block\">$missingText$</$transclude>\n</$transclude>\n</$reveal>\n<$reveal state=\"\"\"$selectedTiddler$\"\"\" type=\"match\" text=\"\">\n$unselectedText$\n</$reveal>\n</div>\n</div>\n</$tiddler>\n\\end\n\n\\define toc-tabbed-internal-nav(tag,sort:\"\",selectedTiddler:\"$:/temp/toc/selectedTiddler\",unselectedText,missingText,template:\"\")\n<$linkcatcher to=\"\"\"$selectedTiddler$\"\"\">\n<$macrocall $name=\"toc-tabbed-external-nav\" tag=\"\"\"$tag$\"\"\" sort=\"\"\"$sort$\"\"\" selectedTiddler=\"\"\"$selectedTiddler$\"\"\" unselectedText=\"\"\"$unselectedText$\"\"\" missingText=\"\"\"$missingText$\"\"\" template=\"\"\"$template$\"\"\"/>\n</$linkcatcher>\n\\end\n\n"
},
"$:/core/macros/translink": {
"title": "$:/core/macros/translink",
"tags": "$:/tags/Macro",
"text": "\\define translink(title,mode:\"block\")\n<div style=\"border:1px solid #ccc; padding: 0.5em; background: black; foreground; white;\">\n<$link to=\"\"\"$title$\"\"\">\n<$text text=\"\"\"$title$\"\"\"/>\n</$link>\n<div style=\"border:1px solid #ccc; padding: 0.5em; background: white; foreground; black;\">\n<$transclude tiddler=\"\"\"$title$\"\"\" mode=\"$mode$\">\n\"<$text text=\"\"\"$title$\"\"\"/>\" is missing\n</$transclude>\n</div>\n</div>\n\\end\n"
},
"$:/snippets/minilanguageswitcher": {
"title": "$:/snippets/minilanguageswitcher",
"text": "<$select tiddler=\"$:/language\">\n<$list filter=\"[[$:/languages/en-GB]] [plugin-type[language]sort[title]]\">\n<option value=<<currentTiddler>>><$view field=\"description\"><$view field=\"name\"><$view field=\"title\"/></$view></$view></option>\n</$list>\n</$select>"
},
"$:/snippets/minithemeswitcher": {
"title": "$:/snippets/minithemeswitcher",
"text": "\\define lingo-base() $:/language/ControlPanel/Theme/\n<<lingo Prompt>> <$select tiddler=\"$:/theme\">\n<$list filter=\"[plugin-type[theme]sort[title]]\">\n<option value=<<currentTiddler>>><$view field=\"name\"><$view field=\"title\"/></$view></option>\n</$list>\n</$select>"
},
"$:/snippets/modules": {
"title": "$:/snippets/modules",
"text": "\\define describeModuleType(type)\n{{$:/language/Docs/ModuleTypes/$type$}}\n\\end\n<$list filter=\"[moduletypes[]]\">\n\n!! <$macrocall $name=\"currentTiddler\" $type=\"text/plain\" $output=\"text/plain\"/>\n\n<$macrocall $name=\"describeModuleType\" type=<<currentTiddler>>/>\n\n<ul><$list filter=\"[all[current]modules[]]\"><li><$link><<currentTiddler>></$link>\n</li>\n</$list>\n</ul>\n</$list>\n"
},
"$:/palette": {
"title": "$:/palette",
"text": "$:/palettes/Vanilla"
},
"$:/snippets/paletteeditor": {
"title": "$:/snippets/paletteeditor",
"text": "\\define lingo-base() $:/language/ControlPanel/Palette/Editor/\n\\define describePaletteColour(colour)\n<$transclude tiddler=\"$:/language/Docs/PaletteColours/$colour$\"><$text text=\"$colour$\"/></$transclude>\n\\end\n<$set name=\"currentTiddler\" value={{$:/palette}}>\n\n<<lingo Prompt>> <$link to={{$:/palette}}><$macrocall $name=\"currentTiddler\" $output=\"text/plain\"/></$link>\n\n<$list filter=\"[all[current]is[shadow]is[tiddler]]\" variable=\"listItem\">\n<<lingo Prompt/Modified>>\n<$button message=\"tm-delete-tiddler\" param={{$:/palette}}><<lingo Reset/Caption>></$button>\n</$list>\n\n<$list filter=\"[all[current]is[shadow]!is[tiddler]]\" variable=\"listItem\">\n<<lingo Clone/Prompt>>\n</$list>\n\n<$button message=\"tm-new-tiddler\" param={{$:/palette}}><<lingo Clone/Caption>></$button>\n\n<table>\n<tbody>\n<$list filter=\"[all[current]indexes[]]\" variable=\"colourName\">\n<tr>\n<td>\n''<$macrocall $name=\"describePaletteColour\" colour=<<colourName>>/>''<br/>\n<$macrocall $name=\"colourName\" $output=\"text/plain\"/>\n</td>\n<td>\n<$edit-text index=<<colourName>> tag=\"input\"/>\n<br>\n<$edit-text index=<<colourName>> type=\"color\" tag=\"input\"/>\n</td>\n</tr>\n</$list>\n</tbody>\n</table>\n</$set>\n"
},
"$:/snippets/palettepreview": {
"title": "$:/snippets/palettepreview",
"text": "<$set name=\"currentTiddler\" value={{$:/palette}}>\n<$transclude tiddler=\"$:/snippets/currpalettepreview\"/>\n</$set>\n"
},
"$:/snippets/paletteswitcher": {
"title": "$:/snippets/paletteswitcher",
"text": "\\define lingo-base() $:/language/ControlPanel/Palette/\n<div class=\"tc-prompt\">\n<<lingo Prompt>> <$view tiddler={{$:/palette}} field=\"name\"/>\n</div>\n\n<$linkcatcher to=\"$:/palette\">\n<div class=\"tc-chooser\"><$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Palette]sort[description]]\"><div class=\"tc-chooser-item\"><$link to={{!!title}}><div><$reveal state=\"$:/palette\" type=\"match\" text={{!!title}}>•</$reveal><$reveal state=\"$:/palette\" type=\"nomatch\" text={{!!title}}> </$reveal> ''<$view field=\"name\" format=\"text\"/>'' - <$view field=\"description\" format=\"text\"/></div><$transclude tiddler=\"$:/snippets/currpalettepreview\"/></$link></div>\n</$list>\n</div>\n</$linkcatcher>"
},
"$:/temp/search": {
"title": "$:/temp/search",
"text": ""
},
"$:/tags/AdvancedSearch": {
"title": "$:/tags/AdvancedSearch",
"list": "[[$:/core/ui/AdvancedSearch/Standard]] [[$:/core/ui/AdvancedSearch/System]] [[$:/core/ui/AdvancedSearch/Shadows]] [[$:/core/ui/AdvancedSearch/Filter]]"
},
"$:/tags/AdvancedSearch/FilterButton": {
"title": "$:/tags/AdvancedSearch/FilterButton",
"list": "$:/core/ui/AdvancedSearch/Filter/FilterButtons/dropdown $:/core/ui/AdvancedSearch/Filter/FilterButtons/clear $:/core/ui/AdvancedSearch/Filter/FilterButtons/export $:/core/ui/AdvancedSearch/Filter/FilterButtons/delete"
},
"$:/tags/ControlPanel": {
"title": "$:/tags/ControlPanel",
"list": "$:/core/ui/ControlPanel/Info $:/core/ui/ControlPanel/Appearance $:/core/ui/ControlPanel/Settings $:/core/ui/ControlPanel/Saving $:/core/ui/ControlPanel/Plugins $:/core/ui/ControlPanel/Tools $:/core/ui/ControlPanel/Internals"
},
"$:/tags/ControlPanel/Info": {
"title": "$:/tags/ControlPanel/Info",
"list": "$:/core/ui/ControlPanel/Basics $:/core/ui/ControlPanel/Advanced"
},
"$:/tags/ControlPanel/Plugins": {
"title": "$:/tags/ControlPanel/Plugins",
"list": "[[$:/core/ui/ControlPanel/Plugins/Installed]] [[$:/core/ui/ControlPanel/Plugins/Add]]"
},
"$:/tags/EditTemplate": {
"title": "$:/tags/EditTemplate",
"list": "[[$:/core/ui/EditTemplate/controls]] [[$:/core/ui/EditTemplate/title]] [[$:/core/ui/EditTemplate/tags]] [[$:/core/ui/EditTemplate/shadow]] [[$:/core/ui/ViewTemplate/classic]] [[$:/core/ui/EditTemplate/body]] [[$:/core/ui/EditTemplate/type]] [[$:/core/ui/EditTemplate/fields]]"
},
"$:/tags/EditToolbar": {
"title": "$:/tags/EditToolbar",
"list": "[[$:/core/ui/Buttons/delete]] [[$:/core/ui/Buttons/cancel]] [[$:/core/ui/Buttons/save]]"
},
"$:/tags/EditorToolbar": {
"title": "$:/tags/EditorToolbar",
"list": "$:/core/ui/EditorToolbar/paint $:/core/ui/EditorToolbar/opacity $:/core/ui/EditorToolbar/line-width $:/core/ui/EditorToolbar/clear $:/core/ui/EditorToolbar/bold $:/core/ui/EditorToolbar/italic $:/core/ui/EditorToolbar/strikethrough $:/core/ui/EditorToolbar/underline $:/core/ui/EditorToolbar/superscript $:/core/ui/EditorToolbar/subscript $:/core/ui/EditorToolbar/mono-line $:/core/ui/EditorToolbar/mono-block $:/core/ui/EditorToolbar/quote $:/core/ui/EditorToolbar/list-bullet $:/core/ui/EditorToolbar/list-number $:/core/ui/EditorToolbar/heading-1 $:/core/ui/EditorToolbar/heading-2 $:/core/ui/EditorToolbar/heading-3 $:/core/ui/EditorToolbar/heading-4 $:/core/ui/EditorToolbar/heading-5 $:/core/ui/EditorToolbar/heading-6 $:/core/ui/EditorToolbar/link $:/core/ui/EditorToolbar/excise $:/core/ui/EditorToolbar/picture $:/core/ui/EditorToolbar/stamp $:/core/ui/EditorToolbar/size $:/core/ui/EditorToolbar/editor-height $:/core/ui/EditorToolbar/more $:/core/ui/EditorToolbar/preview $:/core/ui/EditorToolbar/preview-type"
},
"$:/tags/MoreSideBar": {
"title": "$:/tags/MoreSideBar",
"list": "[[$:/core/ui/MoreSideBar/All]] [[$:/core/ui/MoreSideBar/Recent]] [[$:/core/ui/MoreSideBar/Tags]] [[$:/core/ui/MoreSideBar/Missing]] [[$:/core/ui/MoreSideBar/Drafts]] [[$:/core/ui/MoreSideBar/Orphans]] [[$:/core/ui/MoreSideBar/Types]] [[$:/core/ui/MoreSideBar/System]] [[$:/core/ui/MoreSideBar/Shadows]]",
"text": ""
},
"$:/tags/PageControls": {
"title": "$:/tags/PageControls",
"list": "[[$:/core/ui/Buttons/home]] [[$:/core/ui/Buttons/close-all]] [[$:/core/ui/Buttons/fold-all]] [[$:/core/ui/Buttons/unfold-all]] [[$:/core/ui/Buttons/permaview]] [[$:/core/ui/Buttons/new-tiddler]] [[$:/core/ui/Buttons/new-journal]] [[$:/core/ui/Buttons/new-image]] [[$:/core/ui/Buttons/import]] [[$:/core/ui/Buttons/export-page]] [[$:/core/ui/Buttons/control-panel]] [[$:/core/ui/Buttons/advanced-search]] [[$:/core/ui/Buttons/tag-manager]] [[$:/core/ui/Buttons/language]] [[$:/core/ui/Buttons/palette]] [[$:/core/ui/Buttons/theme]] [[$:/core/ui/Buttons/storyview]] [[$:/core/ui/Buttons/encryption]] [[$:/core/ui/Buttons/full-screen]] [[$:/core/ui/Buttons/save-wiki]] [[$:/core/ui/Buttons/refresh]] [[$:/core/ui/Buttons/more-page-actions]]"
},
"$:/tags/PageTemplate": {
"title": "$:/tags/PageTemplate",
"list": "[[$:/core/ui/PageTemplate/topleftbar]] [[$:/core/ui/PageTemplate/toprightbar]] [[$:/core/ui/PageTemplate/sidebar]] [[$:/core/ui/PageTemplate/story]] [[$:/core/ui/PageTemplate/alerts]]",
"text": ""
},
"$:/tags/SideBar": {
"title": "$:/tags/SideBar",
"list": "[[$:/core/ui/SideBar/Open]] [[$:/core/ui/SideBar/Recent]] [[$:/core/ui/SideBar/Tools]] [[$:/core/ui/SideBar/More]]",
"text": ""
},
"$:/tags/TiddlerInfo": {
"title": "$:/tags/TiddlerInfo",
"list": "[[$:/core/ui/TiddlerInfo/Tools]] [[$:/core/ui/TiddlerInfo/References]] [[$:/core/ui/TiddlerInfo/Tagging]] [[$:/core/ui/TiddlerInfo/List]] [[$:/core/ui/TiddlerInfo/Listed]] [[$:/core/ui/TiddlerInfo/Fields]]",
"text": ""
},
"$:/tags/TiddlerInfo/Advanced": {
"title": "$:/tags/TiddlerInfo/Advanced",
"list": "[[$:/core/ui/TiddlerInfo/Advanced/ShadowInfo]] [[$:/core/ui/TiddlerInfo/Advanced/PluginInfo]]"
},
"$:/tags/ViewTemplate": {
"title": "$:/tags/ViewTemplate",
"list": "[[$:/core/ui/ViewTemplate/title]] [[$:/core/ui/ViewTemplate/unfold]] [[$:/core/ui/ViewTemplate/subtitle]] [[$:/core/ui/ViewTemplate/tags]] [[$:/core/ui/ViewTemplate/classic]] [[$:/core/ui/ViewTemplate/body]]"
},
"$:/tags/ViewToolbar": {
"title": "$:/tags/ViewToolbar",
"list": "[[$:/core/ui/Buttons/more-tiddler-actions]] [[$:/core/ui/Buttons/info]] [[$:/core/ui/Buttons/new-here]] [[$:/core/ui/Buttons/new-journal-here]] [[$:/core/ui/Buttons/clone]] [[$:/core/ui/Buttons/export-tiddler]] [[$:/core/ui/Buttons/edit]] [[$:/core/ui/Buttons/delete]] [[$:/core/ui/Buttons/permalink]] [[$:/core/ui/Buttons/permaview]] [[$:/core/ui/Buttons/open-window]] [[$:/core/ui/Buttons/close-others]] [[$:/core/ui/Buttons/close]] [[$:/core/ui/Buttons/fold-others]] [[$:/core/ui/Buttons/fold]]"
},
"$:/snippets/themeswitcher": {
"title": "$:/snippets/themeswitcher",
"text": "\\define lingo-base() $:/language/ControlPanel/Theme/\n<<lingo Prompt>> <$view tiddler={{$:/theme}} field=\"name\"/>\n\n<$linkcatcher to=\"$:/theme\">\n<$list filter=\"[plugin-type[theme]sort[title]]\"><div><$reveal state=\"$:/theme\" type=\"match\" text={{!!title}}>•</$reveal><$reveal state=\"$:/theme\" type=\"nomatch\" text={{!!title}}> </$reveal> <$link to={{!!title}}>''<$view field=\"name\" format=\"text\"/>'' <$view field=\"description\" format=\"text\"/></$link></div>\n</$list>\n</$linkcatcher>"
},
"$:/core/wiki/title": {
"title": "$:/core/wiki/title",
"type": "text/vnd.tiddlywiki",
"text": "{{$:/SiteTitle}} --- {{$:/SiteSubtitle}}"
},
"$:/view": {
"title": "$:/view",
"text": "classic"
},
"$:/snippets/viewswitcher": {
"title": "$:/snippets/viewswitcher",
"text": "\\define lingo-base() $:/language/ControlPanel/StoryView/\n<<lingo Prompt>> <$select tiddler=\"$:/view\">\n<$list filter=\"[storyviews[]]\">\n<option><$view field=\"title\"/></option>\n</$list>\n</$select>"
}
}
}
/*\
title: $:/core/modules/macros/3Dmol
type: application/javascript
module-type: macro
Macro to return a formatted version of the current time
\*/
(function(){
/*jslint node: true, browser: true */
/*global $tw: false */
"use strict";
/*
Information about this macro
*/
exports.name = "3Dmol";
exports.params = [
{name: "src"},
{name: "mol"},
{name: "id"},
{name: "style"}
];
/*
Run the macro
*/
exports.run = function(src, mol, id, style) {
// Assume there exists an HTML div with id "id"
var element = $("#"+id);
console.log(element)
// Viewer config - properties 'defaultcolors' and 'callback'
var config = {defaultcolors: $3Dmol.rasmolElementColors };
// Create GLViewer within 'gldiv'
var myviewer = $3Dmol.createViewer(element, config);
//'data' is a string containing molecule data in pdb format
//myviewer.addModel(data, "pdb");
//myviewer.zoomTo();
//myviewer.render();
myviewer.setBackgroundColor('white');
// GLModel 'm' created and loaded into glviewer for PDB id 2POR
// Note that m will not contain the atomic data until after the network request is completed
var m = $3Dmol.download(src+':'+mol, myviewer, {}, function() {
switch(style) {
case "sphere":
myviewer.setStyle({}, {sphere:{}});
break;
case "stick":
myviewer.setStyle({}, {stick:{}});
break;
case "cartoon":
myviewer.setStyle({}, {cartoon:{}});
break;
default:
myviewer.setStyle({}, {sphere:{}});
}
myviewer.render();
});
console.log(m)
return ""
//return mol
//$tw.utils.formatDateString(new Date(),format || "0hh:0mm, DDth MMM YYYY");
};
})();
/*\
title: $:/core/modules/macros/now.js
type: application/javascript
module-type: macro
Macro to return a formatted version of the current time
\*/
(function(){
/*jslint node: true, browser: true */
/*global $tw: false */
"use strict";
/*
Information about this macro
*/
exports.name = "testMacro";
exports.params = [
{name: "format"}
];
/*
Run the macro
*/
exports.run = function(format) {
return "test";
//$tw.utils.formatDateString(new Date(),format || "0hh:0mm, DDth MMM YYYY");
};
})();
alert-background: #a24f91
alert-border: #b99e2f
alert-highlight: #881122
alert-muted-foreground: #b99e2f
background: #3a484b
blockquote-bar: <<colour muted-foreground>>
button-background:
button-foreground:
button-border:
code-background: #494992
code-border: #e1e1e8
code-foreground: #dd1144
dirty-indicator: #ff0000
download-background: #34c734
download-foreground: <<colour background>>
dragger-background: <<colour foreground>>
dragger-foreground: <<colour background>>
dropdown-background: <<colour background>>
dropdown-border: <<colour muted-foreground>>
dropdown-tab-background-selected: #fff
dropdown-tab-background: #385caa
dropzone-background: rgba(0,200,0,0.7)
external-link-background-hover: inherit
external-link-background-visited: inherit
external-link-background: inherit
external-link-foreground-hover: inherit
external-link-foreground-visited: #00ee94
external-link-foreground: #00ee19
foreground: #cfd1f0
message-background: #365eb4
message-border: #2d55af
message-foreground: #547599
modal-backdrop: <<colour foreground>>
modal-background: <<colour background>>
modal-border: #999999
modal-footer-background: #f5f5f5
modal-footer-border: #dddddd
modal-header-border: #eeeeee
muted-foreground: #ddd
notification-background: #383b7a
notification-border: #76b276
page-background: #336438
pre-background: #393f5f
pre-border: #cccccc
primary: #63c769
sidebar-button-foreground: <<colour foreground>>
sidebar-controls-foreground-hover: #ccf
sidebar-controls-foreground: #fff
sidebar-foreground-shadow: rgba(0,0,0, 0.5)
sidebar-foreground: #fff
sidebar-muted-foreground-hover: #444444
sidebar-muted-foreground: #eee
sidebar-tab-background-selected: rgba(255,255,255, 0.8)
sidebar-tab-background: rgba(255,255,255, 0.4)
sidebar-tab-border-selected: <<colour tab-border-selected>>
sidebar-tab-border: <<colour tab-border>>
sidebar-tab-divider: rgba(255,255,255, 0.2)
sidebar-tab-foreground-selected:
sidebar-tab-foreground: <<colour tab-foreground>>
sidebar-tiddler-link-foreground-hover: #aaf
sidebar-tiddler-link-foreground: #ddf
site-title-foreground: #fff
static-alert-foreground: #aaaaaa
tab-background-selected: #ffffff
tab-background: #d8d8d8
tab-border-selected: #d8d8d8
tab-border: #cccccc
tab-divider: #d8d8d8
tab-foreground-selected: <<colour tab-foreground>>
tab-foreground: #2f2e52
table-border: #dddddd
table-footer-background: #a8a8a8
table-header-background: #1eae37
tag-background: #ec6
tag-foreground: #ffffff
tiddler-background: <<colour background>>
tiddler-border: <<colour background>>
tiddler-controls-foreground-hover: #888888
tiddler-controls-foreground-selected: #444444
tiddler-controls-foreground: #cccccc
tiddler-editor-background: #255b52
tiddler-editor-border-image: #ffffff
tiddler-editor-border: #cccccc
tiddler-editor-fields-even: #784d7b
tiddler-editor-fields-odd: #4b1b7f
tiddler-info-background: #f8f8f8
tiddler-info-border: #dddddd
tiddler-info-tab-background: #f8f8f8
tiddler-link-background: <<colour background>>
tiddler-link-foreground: <<colour primary>>
tiddler-subtitle-foreground: #c0c0c0
tiddler-title-foreground: #73dcde
toolbar-new-button:
toolbar-options-button:
toolbar-save-button:
toolbar-info-button:
toolbar-edit-button:
toolbar-close-button:
toolbar-delete-button:
toolbar-cancel-button:
toolbar-done-button:
untagged-background: #999999
very-muted-foreground: #888888
alert-background: #ffe476
alert-border: #b99e2f
alert-highlight: #881122
alert-muted-foreground: #b99e2f
background: #c5d3cd
blockquote-bar: <<colour muted-foreground>>
button-background:
button-foreground:
button-border:
code-background: #f7f7f9
code-border: #e1e1e8
code-foreground: #dd1144
dirty-indicator: #ff0000
download-background: #34c734
download-foreground: <<colour background>>
dragger-background: <<colour foreground>>
dragger-foreground: <<colour background>>
dropdown-background: <<colour background>>
dropdown-border: <<colour muted-foreground>>
dropdown-tab-background-selected: #fff
dropdown-tab-background: #ececec
dropzone-background: rgba(0,200,0,0.7)
external-link-background-hover: inherit
external-link-background-visited: inherit
external-link-background: inherit
external-link-foreground-hover: inherit
external-link-foreground-visited: #0000aa
external-link-foreground: #0000ee
foreground: #333333
message-background: #ecf2ff
message-border: #cfd6e6
message-foreground: #547599
modal-backdrop: <<colour foreground>>
modal-background: <<colour background>>
modal-border: #999999
modal-footer-background: #f5f5f5
modal-footer-border: #dddddd
modal-header-border: #eeeeee
muted-foreground: #ddd
notification-background: #ffffdd
notification-border: #999999
page-background: #336438
pre-background: #f5f5f5
pre-border: #cccccc
primary: #5778d8
sidebar-button-foreground: <<colour foreground>>
sidebar-controls-foreground-hover: #ccf
sidebar-controls-foreground: #fff
sidebar-foreground-shadow: rgba(0,0,0, 0.5)
sidebar-foreground: #fff
sidebar-muted-foreground-hover: #444444
sidebar-muted-foreground: #eee
sidebar-tab-background-selected: rgba(255,255,255, 0.8)
sidebar-tab-background: rgba(255,255,255, 0.4)
sidebar-tab-border-selected: <<colour tab-border-selected>>
sidebar-tab-border: <<colour tab-border>>
sidebar-tab-divider: rgba(255,255,255, 0.2)
sidebar-tab-foreground-selected:
sidebar-tab-foreground: <<colour tab-foreground>>
sidebar-tiddler-link-foreground-hover: #aaf
sidebar-tiddler-link-foreground: #ddf
site-title-foreground: #fff
static-alert-foreground: #aaaaaa
tab-background-selected: #ffffff
tab-background: #d8d8d8
tab-border-selected: #d8d8d8
tab-border: #cccccc
tab-divider: #d8d8d8
tab-foreground-selected: <<colour tab-foreground>>
tab-foreground: #666666
table-border: #7b8a9e
table-footer-background: #a8a8a8
table-header-background: #f0f0f0
tag-background: #ec6
tag-foreground: #ffffff
tiddler-background: <<colour background>>
tiddler-border: <<colour background>>
tiddler-controls-foreground-hover: #888888
tiddler-controls-foreground-selected: #444444
tiddler-controls-foreground: #cccccc
tiddler-editor-background: #f8f8f8
tiddler-editor-border-image: #ffffff
tiddler-editor-border: #cccccc
tiddler-editor-fields-even: #e0e8e0
tiddler-editor-fields-odd: #f0f4f0
tiddler-info-background: #f8f8f8
tiddler-info-border: #dddddd
tiddler-info-tab-background: #f8f8f8
tiddler-link-background: <<colour background>>
tiddler-link-foreground: <<colour primary>>
tiddler-subtitle-foreground: #c0c0c0
tiddler-title-foreground: #182955
toolbar-new-button:
toolbar-options-button:
toolbar-save-button:
toolbar-info-button:
toolbar-edit-button:
toolbar-close-button:
toolbar-delete-button:
toolbar-cancel-button:
toolbar-done-button:
untagged-background: #999999
very-muted-foreground: #888888
alert-background: #ffe476
alert-border: #b99e2f
alert-highlight: #881122
alert-muted-foreground: #b99e2f
background: #c4d9d4
blockquote-bar: <<colour muted-foreground>>
button-background:
button-foreground:
button-border:
code-background: #f7f7f9
code-border: #e1e1e8
code-foreground: #dd1144
dirty-indicator: #ff0000
download-background: #34c734
download-foreground: <<colour background>>
dragger-background: <<colour foreground>>
dragger-foreground: <<colour background>>
dropdown-background: <<colour background>>
dropdown-border: <<colour muted-foreground>>
dropdown-tab-background-selected: #fff
dropdown-tab-background: #ececec
dropzone-background: rgba(0,200,0,0.7)
external-link-background-hover: inherit
external-link-background-visited: inherit
external-link-background: inherit
external-link-foreground-hover: inherit
external-link-foreground-visited: #0000aa
external-link-foreground: #0000ee
foreground: #333333
message-background: #ecf2ff
message-border: #cfd6e6
message-foreground: #547599
modal-backdrop: <<colour foreground>>
modal-background: <<colour background>>
modal-border: #999999
modal-footer-background: #f5f5f5
modal-footer-border: #dddddd
modal-header-border: #eeeeee
muted-foreground: #ddd
notification-background: #ffffdd
notification-border: #999999
page-background: #336438
pre-background: #f5f5f5
pre-border: #cccccc
primary: #5778d8
sidebar-button-foreground: <<colour foreground>>
sidebar-controls-foreground-hover: #ccf
sidebar-controls-foreground: #fff
sidebar-foreground-shadow: rgba(0,0,0, 0.5)
sidebar-foreground: #fff
sidebar-muted-foreground-hover: #444444
sidebar-muted-foreground: #eee
sidebar-tab-background-selected: rgba(255,255,255, 0.8)
sidebar-tab-background: rgba(255,255,255, 0.4)
sidebar-tab-border-selected: <<colour tab-border-selected>>
sidebar-tab-border: <<colour tab-border>>
sidebar-tab-divider: rgba(255,255,255, 0.2)
sidebar-tab-foreground-selected:
sidebar-tab-foreground: <<colour tab-foreground>>
sidebar-tiddler-link-foreground-hover: #aaf
sidebar-tiddler-link-foreground: #ddf
site-title-foreground: #fff
static-alert-foreground: #aaaaaa
tab-background-selected: #ffffff
tab-background: #d8d8d8
tab-border-selected: #d8d8d8
tab-border: #cccccc
tab-divider: #d8d8d8
tab-foreground-selected: <<colour tab-foreground>>
tab-foreground: #666666
table-border: #7b8a9e
table-footer-background: #a8a8a8
table-header-background: #f0f0f0
tag-background: #ec6
tag-foreground: #ffffff
tiddler-background: <<colour background>>
tiddler-border: <<colour background>>
tiddler-controls-foreground-hover: #888888
tiddler-controls-foreground-selected: #444444
tiddler-controls-foreground: #9b876b
tiddler-editor-background: #f8f8f8
tiddler-editor-border-image: #ffffff
tiddler-editor-border: #cccccc
tiddler-editor-fields-even: #e0e8e0
tiddler-editor-fields-odd: #f0f4f0
tiddler-info-background: #f8f8f8
tiddler-info-border: #c8c8c8
tiddler-info-tab-background: #f8f8f8
tiddler-link-background: <<colour background>>
tiddler-link-foreground: <<colour primary>>
tiddler-subtitle-foreground: #7b6a53
tiddler-title-foreground: #182955
toolbar-new-button:
toolbar-options-button:
toolbar-save-button:
toolbar-info-button:
toolbar-edit-button:
toolbar-close-button:
toolbar-delete-button:
toolbar-cancel-button:
toolbar-done-button:
untagged-background: #999999
very-muted-foreground: #888888
alert-background: #ffe476
alert-border: #b99e2f
alert-highlight: #881122
alert-muted-foreground: #b99e2f
background: #3a484b
blockquote-bar: <<colour muted-foreground>>
button-background:
button-foreground:
button-border:
code-background: #f7f7f9
code-border: #e1e1e8
code-foreground: #dd1144
dirty-indicator: #ff0000
download-background: #34c734
download-foreground: <<colour background>>
dragger-background: <<colour foreground>>
dragger-foreground: <<colour background>>
dropdown-background: <<colour background>>
dropdown-border: <<colour muted-foreground>>
dropdown-tab-background-selected: #fff
dropdown-tab-background: #ececec
dropzone-background: rgba(0,200,0,0.7)
external-link-background-hover: inherit
external-link-background-visited: inherit
external-link-background: inherit
external-link-foreground-hover: inherit
external-link-foreground-visited: #0000aa
external-link-foreground: #0000ee
foreground: #cfd1f0
message-background: #ecf2ff
message-border: #cfd6e6
message-foreground: #547599
modal-backdrop: <<colour foreground>>
modal-background: <<colour background>>
modal-border: #999999
modal-footer-background: #f5f5f5
modal-footer-border: #dddddd
modal-header-border: #eeeeee
muted-foreground: #ddd
notification-background: #ffffdd
notification-border: #999999
page-background: #336438
pre-background: #f5f5f5
pre-border: #cccccc
primary: #63c769
sidebar-button-foreground: <<colour foreground>>
sidebar-controls-foreground-hover: #ccf
sidebar-controls-foreground: #fff
sidebar-foreground-shadow: rgba(0,0,0, 0.5)
sidebar-foreground: #fff
sidebar-muted-foreground-hover: #444444
sidebar-muted-foreground: #eee
sidebar-tab-background-selected: rgba(255,255,255, 0.8)
sidebar-tab-background: rgba(255,255,255, 0.4)
sidebar-tab-border-selected: <<colour tab-border-selected>>
sidebar-tab-border: <<colour tab-border>>
sidebar-tab-divider: rgba(255,255,255, 0.2)
sidebar-tab-foreground-selected:
sidebar-tab-foreground: <<colour tab-foreground>>
sidebar-tiddler-link-foreground-hover: #aaf
sidebar-tiddler-link-foreground: #ddf
site-title-foreground: #fff
static-alert-foreground: #aaaaaa
tab-background-selected: #ffffff
tab-background: #d8d8d8
tab-border-selected: #d8d8d8
tab-border: #cccccc
tab-divider: #d8d8d8
tab-foreground-selected: <<colour tab-foreground>>
tab-foreground: #666666
table-border: #dddddd
table-footer-background: #a8a8a8
table-header-background: #f0f0f0
tag-background: #ec6
tag-foreground: #ffffff
tiddler-background: <<colour background>>
tiddler-border: <<colour background>>
tiddler-controls-foreground-hover: #888888
tiddler-controls-foreground-selected: #444444
tiddler-controls-foreground: #cccccc
tiddler-editor-background: #f8f8f8
tiddler-editor-border-image: #ffffff
tiddler-editor-border: #cccccc
tiddler-editor-fields-even: #e0e8e0
tiddler-editor-fields-odd: #f0f4f0
tiddler-info-background: #f8f8f8
tiddler-info-border: #dddddd
tiddler-info-tab-background: #f8f8f8
tiddler-link-background: <<colour background>>
tiddler-link-foreground: <<colour primary>>
tiddler-subtitle-foreground: #c0c0c0
tiddler-title-foreground: #73dcde
toolbar-new-button:
toolbar-options-button:
toolbar-save-button:
toolbar-info-button:
toolbar-edit-button:
toolbar-close-button:
toolbar-delete-button:
toolbar-cancel-button:
toolbar-done-button:
untagged-background: #999999
very-muted-foreground: #888888
{
"tiddlers": {
"$:/plugins/danielo515/2click2edit/ClickListener.js": {
"text": "/*\\\ntitle: $:/plugins/danielo515/2click2edit/ClickListener.js\ntype: application/javascript\nmodule-type: widget\n\nThis widgets adds an double click event listener to its parent\n\n\\*/\n\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar ClickListener = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nClickListener.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nClickListener.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.execute();\n\tvar self = this;\n /*Since the event listener have been added to the parent, the \"this\" property is pointing to the\n wrong object, we should call our edit function with our widget object set as the this property.*/\n parent.addEventListener(\"dblclick\",function(event){self.editTiddler.call(self,event)});\n};\n\nClickListener.prototype.editTiddler = function(event) {\n this.dispatchEvent({type: \"tm-edit-tiddler\", param: this.getVariable(\"currentTiddler\")}); \n};\n\n/*\nCompute the internal state of the widget\n*/\nClickListener.prototype.execute = function() {\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nClickListener.prototype.refresh = function(changedTiddlers) {\n\treturn false;\n};\n\nexports.click = ClickListener;\n\n})();",
"title": "$:/plugins/danielo515/2click2edit/ClickListener.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/plugins/danielo515/2click2edit/readme": {
"title": "$:/plugins/danielo515/2click2edit/readme",
"text": "This plugin adds the ability to edit tiddlers by double clicking on its body.\nJust try to edit any tiddler shown here by double clicking on it.\n\nThis can be considered a fast solution. It is only to fill the gap until TiddlyWiki adds support \nfor it officially.\n"
},
"$:/plugins/danielo515/2click2edit/ui/ViewTemplate": {
"tags": "$:/tags/ViewTemplate",
"title": "$:/plugins/danielo515/2click2edit/ui/ViewTemplate",
"type": "text/vnd.tiddlywiki",
"text": "<$click>"
}
}
}
{
"tiddlers": {
"$:/plugins/felixhayashi/hotzone/config.js": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/hotzone/config.js\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n(function(){\"use strict\";exports.config={classNames:{storyRiver:\"tc-story-river\",tiddlerFrame:\"tc-tiddler-frame\",tiddlerTitle:\"tc-title\"},references:{userConfig:\"$:/config/hotzone/focusOffset\",focussedTiddlerStore:\"$:/temp/focussedTiddler\"},checkbackTime:$tw.utils.getAnimationDuration()}})();",
"title": "$:/plugins/felixhayashi/hotzone/config.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/hotzone/hotzone.js": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/hotzone/hotzone.js\ntype: application/javascript\nmodule-type: startup\n\n@preserve\n\n\\*/\n(function(){\"use strict\";exports.name=\"hotzone\";exports.platforms=[\"browser\"];exports.after=[\"story\"];exports.synchronous=true;exports.startup=function(){var t=require(\"$:/plugins/felixhayashi/hotzone/config.js\").config;var e=null;var i=false;var r=document.getElementsByClassName(t.classNames.storyRiver)[0];var s=$tw.wiki.getTiddlerData(t.references.userConfig,{});var a=isNaN(parseInt(s.focusOffset))?150:parseInt(s.focusOffset);var n=function(e,i,r){if(!(e instanceof Element))return;if(!$tw.utils.hasClass(e,t.classNames.tiddlerFrame))return;var s=e.getElementsByClassName(t.classNames.tiddlerTitle)[0];if(s){var a=s.innerText||s.textContent;return a.trim()}};var o=function(t){if(!i){i=true;window.setTimeout(f,t||0)}};var l=function(e,i){$tw.wiki.addTiddler(new $tw.Tiddler({title:t.references.focussedTiddlerStore,text:e},$tw.wiki.getModificationFields()));if(i){var r=document.getElementsByClassName(\"hzone-focus\")[0];if(r){$tw.utils.removeClass(r,\"hzone-focus\")}$tw.utils.addClass(i,\"hzone-focus\")}};var f=function(){i=false;var s=$tw.wiki.getTiddler(\"$:/StoryList\");if(s&&s.fields.list.length){var o=null;var f=Number.MAX_VALUE;var d=r.children;var u=t.classNames.tiddlerFrame;for(var c=d.length;c--;){if($tw.utils.hasClass(d[c],u)){var v=d[c].getBoundingClientRect();var w=Math.min(Math.abs(a-v.top),Math.abs(a-v.bottom));if(w<f){o=d[c];f=w}}}var m=n(o);if(m!==e&&$tw.wiki.getTiddler(m)){e=m;l(e,o);return}}else if(e){e=\"\";l(e)}};var d=function(t){if(t[\"$:/HistoryList\"]){if(!$tw.wiki.tiddlerExists(\"$:/HistoryList\"))return;var e=$tw.wiki.getTiddler(\"$:/HistoryList\").fields[\"current-tiddler\"];var i=$tw.wiki.getTiddlerList(\"$:/StoryList\");var r=i.indexOf(e)>=0;if(!r)return;o($tw.utils.getAnimationDuration()+100)}else if(t[\"$:/StoryList\"]){o($tw.utils.getAnimationDuration()+100)}};var u=function(t){o(250)};$tw.wiki.addEventListener(\"change\",d);window.addEventListener(\"scroll\",u,false);u()}})();",
"title": "$:/plugins/felixhayashi/hotzone/hotzone.js",
"type": "application/javascript",
"module-type": "startup"
},
"$:/plugins/felixhayashi/hotzone/Configuration": {
"title": "$:/plugins/felixhayashi/hotzone/Configuration",
"text": "Please see the [[GitHub page|https://github.com/felixhayashi/TW5-HotZone]] for more information on the options.\n\nSave and reload the wiki to activate changes.\n\n<table>\n <tr>\n <th align=\"left\">Focus offset:</th>\n <td><$edit-text tiddler=\"$:/config/hotzone/focusOffset\" tag=\"input\" default=\"71px\" /></td>\n </tr>\n</table>"
},
"$:/temp/focussedTiddler": {
"title": "$:/temp/focussedTiddler"
},
"$:/plugins/felixhayashi/hotzone/License": {
"title": "$:/plugins/felixhayashi/hotzone/License",
"text": "This code is released under the BSD license. For the exact terms visit:\n\nhttps://github.com/felixhayashi/TW5-HotZone/blob/master/LICENSE"
},
"$:/plugins/felixhayashi/hotzone/Readme": {
"title": "$:/plugins/felixhayashi/hotzone/Readme",
"text": "Please visit the [[GitHub page|https://github.com/felixhayashi/TW5-HotZone]] for more information."
}
}
}
{
"tiddlers": {
"$:/plugins/felixhayashi/tiddlymap/layout": {
"title": "$:/plugins/felixhayashi/tiddlymap/layout",
"type": "text/vnd.tiddlywiki",
"tags": [
"$:/tags/Stylesheet"
],
"text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline \n\nbody .tc-page-container-wrapper.tc-modal-displayed{-webkit-filter:inherit;-moz-filter:inherit;filter:inherit}body .tc-modal-wrapper{z-index:1010}body .tc-modal-wrapper .tc-modal-header svg{vertical-align:sub}body .tc-modal-wrapper .tc-modal-header h3{line-height:10px}body .tc-modal-wrapper .tc-modal-body{min-height:250px;max-height:70vh;padding-top:0px;padding-bottom:0px;overflow:auto}body .tc-modal-wrapper .tc-modal-footer{padding:8px}body .tc-modal-wrapper .tc-modal-footer .tmap-dialog-button{font-weight:bold}body .tc-modal-wrapper .tc-modal-footer .tmap-hidden-close-button{display:none}table.tmap-table tr:nth-child(odd),.tc-modal-body table.tmap-config-table tr:nth-child(odd){background-color:#F0F0F0}table.tmap-table tr:nth-child(even),.tc-modal-body table.tmap-config-table tr:nth-child(even){background-color:#FFFFFF}.tmap-save-canvas-preview{text-align:center}.tmap-save-canvas-preview img{background-color:white;border:1px solid lightgray;max-width:100%;max-height:100px}.tmap-list-separator{display:block;background-color:#efefef;margin:10px 0 5px 0;cursor:default;border-bottom:1px dotted gray;font-weight:bold;font-size:0.8em}.tmap-unicode-icon{width:1em;display:inline-block;text-align:center;color:black}html .tmap-link{color:#5778D8}html .tmap-link:hover{color:white;background:#5778D8}html .tmap-small-list,html .tmap-smaller-list,html .tmap-very-small-list{overflow:auto;min-height:2em;max-height:9em;display:block}html .tmap-smaller-list{max-height:7em}html .tmap-very-small-list{max-height:5empx}html .tc-tiddler-controls button.tmap-active-button svg{fill:#888888}html #tmap-node-filter-dialog #tmap-filter-tips{font-size:0.8em}html #tmap-node-filter-dialog textarea{height:100px;max-height:300px;overflow:auto;width:100%;font-size:11px;font-family:\"Courier New\", Courier, monospace}@media (max-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}){.tc-sidebar-scrollable .tmap-desktop-editor .tmap-widget:not(.tmap-fullscreen){display:none}}@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}){.tc-sidebar-scrollable .tmap-mobile-editor{display:none}.tc-modal-wrapper{z-index:1010}.tc-modal-wrapper .tc-modal{boder:1px solid #999999;left:calc(50% - 400px);width:802px}.tc-modal-wrapper .tc-modal-body{left:calc(50% - 400px);width:800px}}@-o-keyframes fadein-keyframes{0%{opacity:0}100%{opacity:1}}@-moz-keyframes fadein-keyframes{0%{opacity:0}100%{opacity:1}}@-webkit-keyframes fadein-keyframes{0%{opacity:0}100%{opacity:1}}@keyframes flash fadein-keyframes{0%{opacity:0}100%{opacity:1}}@-o-keyframes fadeout-keyframes{0%{opacity:1}100%{opacity:0}}@-moz-keyframes fadeout-keyframes{0%{opacity:1}100%{opacity:0}}@-webkit-keyframes fadeout-keyframes{0%{opacity:1}100%{opacity:0}}@keyframes flash fadeout-keyframes{0%{opacity:1}100%{opacity:0}}.tmap-config-widget{background:#F0F0F0;padding:5px;margin:5px 0;box-sizing:border-box;display:block}.tmap-config-widget .vis-network{display:none}.tmap-config-widget .vis-configuration-wrapper{width:100%}.tmap-config-widget .vis-configuration-wrapper .vis-config-rangeinput{height:inherit;margin-left:4px}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item{width:100%;height:inherit;background:none;padding-left:0px;left:0}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item.tmap-vis-config-item-active .vis-config-label::after{content:\"(inherited)\";position:absolute;display:inline-block;margin-left:10px;-o-animation:fadein-keyframes 1s;-moz-animation:fadein-keyframes 1s;-webkit-animation:fadein-keyframes 1s;animation:fadein-keyframes 1s;content:\"✔\";color:green;font-weight:bold;font-size:15px}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item button.tmap-config-item-reset{vertical-align:top;margin-left:5px}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item .vis-config-range{width:150px}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item .vis-config-range::-moz-range-track{width:150px !important}.tmap-config-widget .vis-configuration-wrapper .vis-configuration.vis-config-item .vis-config-label{width:150px}.tmap-config-widget::after{clear:both;content:\"\";display:block}.tmap-flash-message{border:1px solid lightgray;padding:5px;margin:6px 0;display:block;color:#333333}.tmap-flash-message.tmap-info,.tmap-flash-message.tmap-plain,.tmap-flash-message.tmap-neutral{background:#F0F0F0}.tmap-flash-message.tmap-info::before,.tmap-flash-message.tmap-plain::before,.tmap-flash-message.tmap-neutral::before{content:\"i\";display:inline-block;border-radius:50%;width:0.8em;border:2px solid;font-family:serif;text-align:center;height:0.8em;font-weight:bold;line-height:0.8em;vertical-align:text-top;margin-right:2px}.tmap-flash-message.tmap-valid,.tmap-flash-message.tmap-success{background:#D1EED4}.tmap-flash-message.tmap-valid::before,.tmap-flash-message.tmap-success::before{content:\"i\";display:inline-block;border-radius:50%;width:0.8em;border:2px solid;font-family:serif;text-align:center;height:0.8em;font-weight:bold;line-height:0.8em;vertical-align:text-top;margin-right:2px}.tmap-flash-message.tmap-warning{background:#FFF6D1}.tmap-flash-message.tmap-warning::before{content:\"\";display:inline-block;background:url(<<tmap \"datauri\" \"$:/core/images/warning\" \"\">>);display:inline-block;width:1em;height:1em;background-size:100% 100%;vertical-align:text-top;margin-right:2px}.tmap-flash-message.tmap-malformed,.tmap-flash-message.tmap-invalid,.tmap-flash-message.tmap-danger{background:#EED5D1}.tmap-flash-message.tmap-malformed::before,.tmap-flash-message.tmap-invalid::before,.tmap-flash-message.tmap-danger::before{content:\"\";display:inline-block;background:url(<<tmap \"datauri\" \"$:/core/images/warning\" \"\">>);display:inline-block;width:1em;height:1em;background-size:100% 100%;vertical-align:text-top;margin-right:2px}.tmap-widget{background:#FFFFFF;width:auto;position:relative;border:1px dotted lightgray;padding:2px;color:#666;display:block}.tmap-widget.tmap-click-to-use:not(.tmap-fullscreen) .vis-network:not(.vis-active){cursor:pointer}.tmap-widget.tmap-click-to-use:not(.tmap-fullscreen) .vis-network:not(.vis-active) .vis-navigation{display:none}.tmap-widget.tmap-click-to-use:not(.tmap-fullscreen) .vis-network:not(.vis-active):hover:before{color:gray;background:white;content:\"Click to use\";font-size:14px;font-weight:bold;right:calc(50% - 65px - 5px);position:absolute;text-align:center;top:calc(50% - 14px - 5px);width:130px;z-index:2000;padding:5px;pointer-events:none;background-color:rgba(255,255,255,0.3)}.tmap-widget .tmap-loading-bar{display:none;position:absolute;text-align:center;font-size:2em;padding:10px;top:50%;background:rgba(245,245,245,0.5);z-index:1;width:250px;margin:auto;left:0px;right:0px}.tmap-widget .tmap-vis-graph{height:calc(100% - 35px)}.tmap-widget.tmap-no-buttons .vis-navigation{display:none}.tmap-widget.tmap-advanced-editor .tmap-topbar{background:#d6d9d8}.tmap-widget.tmap-advanced-editor .tmap-topbar .tmap-active-button{color:#488DCD}.tmap-widget.tmap-advanced-editor .tmap-topbar .tmap-active-button svg{fill:#488DCD}.tmap-widget.tmap-advanced-editor .tmap-topbar .tmap-neigh-scope-button{font-size:1.5em;vertical-align:bottom}.tmap-widget .tmap-menu-bar{width:100%}.tmap-widget .tmap-topbar{background:#F5F5F5;border-bottom:1px solid lightgray;padding:3px 5px;height:35px;position:relative}.tmap-widget .tmap-topbar .tmap-view-label{width:100%;text-align:center;font-weight:bold;padding-top:3px}.tmap-widget .tmap-topbar .tmap-focus-button{position:absolute;right:10px}.tmap-widget .tmap-topbar .tmap-focus-button input{width:140px}.tmap-widget .tmap-topbar .tmap-search-dropdown{position:relative}.tmap-widget .tmap-topbar .tmap-search-dropdown .tc-drop-down{position:absolute;z-index:999;right:0px}.tmap-widget .tmap-topbar [hidden]{display:none}.tmap-widget .tmap-topbar select{width:30%;max-width:200px;word-wrap:initial;padding:0px}.tmap-widget .tmap-topbar button{line-height:inherit;color:#666}.tmap-widget .tmap-topbar>*{display:inline-block}.tmap-widget .tmap-topbar .tmap-separator:after{color:#bdbdbd;margin:3px;content:\" | \"}.tmap-widget .tmap-topbar .tc-edit-add-tag .tc-add-tag-name input{width:70%}.tmap-widget .tmap-topbar .tc-sidebar-header{text-shadow:none}.tmap-widget .tmap-topbar .tc-edit-tags{border:none;padding:inherit;box-shadow:none}.tmap-widget.tmap-static-mode .tmap-topbar{height:initial}.tmap-widget.tmap-static-mode .tmap-vis-graph{text-align:center;cursor:not-allowed}.tmap-widget.tmap-static-mode .tmap-vis-graph:not(.tmap-graph-placeholder):hover::before{box-shadow:10px 10px 5px lightgray;color:gray;background:white;content:\"Static\";font-size:18px;font-weight:bold;left:50%;margin-left:-100px;position:absolute;text-align:center;top:50px;width:200px;z-index:2000;padding:5px;pointer-events:none}.tmap-widget.tmap-static-mode .tmap-vis-graph.tmap-graph-placeholder::before{content:\"No Preview\";display:block;text-align:center;padding:20px}.tmap-widget .tc-drop-down{min-width:170px;max-width:210px;padding:5px;margin:5px 0}.tmap-widget .tc-drop-down button,.tmap-widget .tc-drop-down a{padding:0 2px;text-decoration:none}.tmap-widget .tc-drop-down button:hover,.tmap-widget .tc-drop-down a:hover{color:#ffffff}.tmap-widget .tc-drop-down button svg,.tmap-widget .tc-drop-down a svg{vertical-align:middle}.tmap-widget .tc-block-dropdown{width:370px;min-width:370px;padding:5px;margin:15px 0 0 -370px}.tmap-widget .tc-block-dropdown a{display:inline;padding:0px}.tmap-widget.tmap-plain-design{border:none;padding:0px}.tmap-widget.tmap-plain-design .tmap-topbar{display:none}.tc-sidebar-scrollable .tmap-widget{position:absolute;min-height:350px}.tmap-widget div.vis-network .vis-edit-mode{height:26px}.tmap-widget div.vis-network .vis-manipulation{height:34px;border-top:1px solid #d6d9d8;background:rgba(245,245,245,0.7)}.tmap-widget div.vis-network .vis-navigation .vis-button.tmap-button-enabled{right:15px}.tmap-widget div.vis-network .vis-navigation .vis-button.tmap-button-enabled.tmap-fullscreen-button{bottom:90px;background-image:url(<<tmap \"datauri\" \"$:/plugins/felixhayashi/tiddlymap/media/fullscreen.png\" \"\">>)}.tmap-widget div.vis-network .vis-navigation .vis-button.tmap-button-enabled.tmap-halfscreen-button{bottom:130px;background-image:url(<<tmap \"datauri\" \"$:/plugins/felixhayashi/tiddlymap/media/halfscreen.png\" \"\">>)}.tmap-widget div.vis-network .vis-navigation .vis-button:hover{box-shadow:0 0 3px 3px rgba(75,75,75,0.3)}.tmap-widget div.vis-network .vis-navigation .vis-button:hover:before{background:beige;display:block;color:black;padding:3px;position:relative;border:1px solid lightgray;width:80px;left:-100px;top:-50px;z-index:1000;text-align:center}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-up:before{left:30px;content:\"Scroll up\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-down:before{left:30px;content:\"Scroll down\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-right:before{left:30px;content:\"Scroll right\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-left:before{left:30px;content:\"Scroll left\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-zoomOut:before{content:\"Zoom out\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-zoomIn:before{content:\"Zoom in\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.vis-zoomExtends:before{content:\"Fit whole graph\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.tmap-fullscreen-button:before{content:\"Toggle Fullscreen\"}.tmap-widget div.vis-network .vis-navigation .vis-button:hover.tmap-halfscreen-button:before{content:\"Toggle Halfscreen\"}.tc-dropzone>.tc-story-river .tmap-widget .vis-navigation .tmap-halfscreen-button{display:none}.tc-dropzone>.tc-story-river .tmap-widget:not(.tmap-fullscreen) .vis-navigation .vis-button{display:none}.tc-dropzone>.tc-story-river .tmap-widget:hover .vis-navigation .vis-button.tmap-fullscreen-button{display:block}.tc-dropzone>.tc-story-river .tmap-widget:hover .vis-navigation .vis-button.vis-zoomExtends{display:block}body.tmap-has-fullscreen-widget{overflow:hidden}body.tmap-has-fullscreen-widget .tmap-widget.tmap-fullscreen{background:white !important;height:100% !important;width:100% !important;position:fixed !important;top:0 !important;right:0 !important;bottom:0 !important;left:0 !important;z-index:999 !important;border:none !important;margin:0 !important}body.tmap-has-fullscreen-widget .tc-dropzone>*.tmap-has-fullscreen-widget{background:white !important;height:100% !important;width:100% !important;position:fixed !important;top:0 !important;right:0 !important;bottom:0 !important;left:0 !important;z-index:999 !important;border:none !important;margin:0 !important}body.tmap-has-fullscreen-widget .tc-dropzone>*:not(.tmap-has-fullscreen-widget){display:none}body.tmap-has-halfscreen-widget .tmap-widget.tmap-halfscreen{background:white !important;height:100% !important;width:100% !important;position:fixed !important;top:0 !important;right:0 !important;bottom:0 !important;left:0 !important;z-index:999 !important;border:none !important;margin:0 !important;position:absolute !important;border-left:1px solid lightgray !important}.tc-modal-footer .tmap-hidden-close-button{display:none}.tmap-modal-content{position:relative;padding:1em 0;padding-top:0}.tmap-modal-content table tr td{vertical-align:top}.tmap-modal-content :not(pre)>code{padding:1px;font-size:0.9em;position:relative;top:-1px}.tmap-modal-content :not(pre)>code{color:#666}.tmap-modal-content .tc-tab-set .tc-tab-content{margin-top:0.5em}.tmap-modal-content .tc-image-button{font-size:14px}.tmap-modal-content fieldset{margin:0px}.tmap-modal-content fieldset legend{font-weight:bold}.tc-modal-body .tmap-modal-editor>p{margin:0px}.tc-modal-body .tmap-modal-editor .tmap-template-select select{width:50%}.tc-modal-body .tmap-modal-editor .tc-tiddler-frame{margin:auto;width:auto}.tc-modal-body .tmap-modal-editor .tc-tiddler-frame .tc-tiddler-controls{display:none}.tc-modal-body .tmap-modal-editor .tc-tiddler-frame .tc-tiddler-title{display:none}.tc-modal-body table{margin:6px 0;border:none;width:100%}.tc-modal-body table td,.tc-modal-body table th{border:1px solid lightgray}.tc-modal-body table.tmap-key-value-table th{width:30%;background-color:#F0F0F0}.tc-modal-body table.tmap-config-table.tmap-large-input tr td:last-child{width:20%}.tc-modal-body table.tmap-config-table.tmap-small-input tr td:last-child{width:60%}.tc-modal-body table.tmap-config-table tr td{border:none;vertical-align:top;padding:5px}.tc-modal-body table.tmap-config-table tr td:first-child{width:15%}.tc-modal-body table.tmap-config-table tr td:last-child{width:40%}.tc-modal-body table.tmap-config-table tr td input:not([type=radio]),.tc-modal-body table.tmap-config-table tr td textarea,.tc-modal-body table.tmap-config-table tr td select{width:100%;word-wrap:normal}.tc-modal-body table.tmap-config-table tr td textarea{height:100%}.tc-modal-body table.tmap-config-table tr td .tmap-no-stretch input,.tc-modal-body table.tmap-config-table tr td .tmap-no-stretch textarea,.tc-modal-body table.tmap-config-table tr td .tmap-no-stretch select{width:auto}.tc-modal-body table.tmap-config-table tr td div.tmap-button-wrapper{text-align:center}.tc-modal-body table.tmap-config-table tr td .tmap-note{margin-top:0.5em}.tc-modal-body table.tmap-config-table tr td .tmap-description{font-style:italic}#tmap-element-type-manager>div:first-child{height:50vh;float:left;width:21%;background:linear-gradient(90deg, #f5f5f5 0%, #fff 50%)}#tmap-element-type-manager>div:first-child .tmap-searchbar{padding:1em 0 0 0}#tmap-element-type-manager>div:first-child .tmap-searchbar input{width:calc(100% - 36px)}#tmap-element-type-manager>div:first-child .tmap-searchbar button{width:30px;float:right}#tmap-element-type-manager>div:first-child ul{height:calc(100% - 65px);overflow:auto;margin-top:1em;padding:0}#tmap-element-type-manager>div:first-child ul.no-bullets li{list-style:none}#tmap-element-type-manager>div:first-child ul li{white-space:nowrap}#tmap-element-type-manager>div:first-child ul li .tmap-ranking{width:30px;display:inline-block}#tmap-element-type-manager>div:last-child{height:100%;width:calc(79% - 15px);float:right}#tmap-element-type-manager>div:last-child .tc-tab-set .tc-tab-content{overflow:auto;height:50vh}.tmap-manage-node-types .tmap-edge-type-specific{display:none !important}.tmap-manage-edge-types .tmap-node-type-specific{display:none !important}.tmap-modal-fullscreen-editor .tc-tab-content p{margin:1em 0}.tmap-has-pending-template{background-color:#C1EDC4}#tmap-search-table td{border:none;padding-left:0px}#tmap-search-table td:first-child{width:30px}#tmap-search-table b{display:inline-block;width:40px;text-align:right}#tmap-search-table ul{padding-left:20px;margin:1em 0 0 0}#tmap-search-table ul li{list-style:inherit}#tmap-search-table ul button{text-align:left}button.tmap-go-back{margin-bottom:1em;font-weight:bold}.tmap-badges>span,.tmap-badge{background:gray;font-size:11px;color:white;padding:3px 4px;display:inline-block;font-weight:bold;border-radius:2px;line-height:1em;cursor:help}.tmap-badges>span.tmap-red-flag,.tmap-badge.tmap-red-flag{background:red}.tmap-popup{display:none;position:absolute;opacity:0;transition:opacity 0.3s ease}.tmap-popup.tmap-popup-active{opacity:1}.tmap-tooltip{box-shadow:3px 3px 10px rgba(0,0,0,0.2);min-width:100px;min-height:50px;max-width:<<tmap option config.sys.popups.width>>;max-height:<<tmap option config.sys.popups.height>>;padding:5px;resize:both;overflow:auto;cursor:auto;font-family:verdana;font-size:14px;background-color:#f5f4ed;border:1px solid #808074;-moz-border-radius:3px;-webkit-border-radius:3px;border-radius:3px}.tmap-tooltip[style*=\"height\"]{max-height:none !important}.tmap-tooltip[style*=\"width\"]{max-width:none !important}.tmap-quick-connect{font-size:0.7em}.tmap-quick-connect p{padding-left:0;padding-right:0}.tmap-quick-connect .tc-drop-down{padding:5px;width:250px;white-space:normal;line-height:1em;position:absolute;z-index:1000;right:50px;background:linear-gradient(45deg, #f5f5f5 0%, #fff 50%, #f5f5f5 100%)}.tmap-quick-connect .tc-drop-down:first-child{padding-top:0;margin-top:0}.tmap-quick-connect .tc-drop-down .title{margin:1.5em 0 0.5em 0;font-weight:bold;color:gray}.tmap-quick-connect .tc-drop-down select{width:80px;word-wrap:initial}.tmap-quick-connect .tc-drop-down table{width:100%;border:none;margin:0.5em 0}.tmap-quick-connect .tc-drop-down table td,.tmap-quick-connect .tc-drop-down table th{padding:3px 3px 3px 0;vertical-align:middle;font-weight:normal;border:none}.tmap-quick-connect .tc-drop-down table td table,.tmap-quick-connect .tc-drop-down table th table{margin:0}.tmap-quick-connect .tc-drop-down .tmap-quick-connect-search-bar,.tmap-quick-connect .tc-drop-down .tmap-quick-connect-existing-bar{background:#F1F1F1;margin-top:0;border-bottom:1px solid #D5D5D5;border-top:1px solid #D5D5D5}.tmap-quick-connect .tc-drop-down table.tmap-quick-connect-search-bar td,.tmap-quick-connect .tc-drop-down th{padding:5px}.tmap-quick-connect .tc-drop-down .tmap-quick-connect-existing-bar{padding:5px}.tmap-quick-connect .tc-drop-down .tmap-connection-table th,.tmap-quick-connect .tc-drop-down .tmap-connection-table td{text-align:left;padding:1px 1px 1px 0}.tmap-quick-connect .tc-drop-down .tmap-connection-table button{width:20px;padding:0px}.tmap-quick-connect .tc-drop-down .tmap-scroll-table{height:120px;overflow:auto;display:block}.tmap-quick-connect .tc-drop-down hr{border:0;height:0;border-top:1px solid rgba(0,0,0,0.1);border-bottom:1px solid rgba(255,255,255,0.3)}.tmap-quick-connect .tc-drop-down a{display:inline;padding:0;color:#5778d8;background:transparent}.tmap-quick-connect .tc-drop-down a:hover{background:transparent;color:#5778d8;text-decoration:underline}.tmap-quick-connect .tc-drop-down button{display:inline-block;padding:0px 3px;text-align:center;color:#333333;line-height:1.0}.tmap-quick-connect .tc-drop-down button:hover{color:#ffffff}.tmap-quick-connect .tc-drop-down button svg{fill:inherit}.tmap-quick-connect .tc-drop-down button svg:hover{fill:#ffffff}\n"
},
"$:/plugins/felixhayashi/tiddlymap/js/Adapter": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/Adapter\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=Adapter;var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var NodeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/NodeType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var vis=require(\"$:/plugins/felixhayashi/vis/vis.js\");var getContrastColour=require(\"$:/core/modules/macros/contrastcolour.js\").run;function Adapter(){this.visShapesWithTextInside=utils.getLookupTable([\"ellipse\",\"circle\",\"database\",\"box\",\"text\"]);this.isTransTypeEnabled=typeof $tw.wiki.getTiddlerTranscludes===\"function\"}Adapter.prototype.deleteEdge=function(e){return this._processEdge(e,\"delete\")};Adapter.prototype.deleteEdges=function(e){e=utils.convert(e,\"array\");for(var t=e.length;t--;){this.deleteEdge(e[t])}};Adapter.prototype.insertEdge=function(e){return this._processEdge(e,\"insert\")};Adapter.prototype._processEdge=function(e,t){$tm.logger(\"debug\",\"Edge\",t,e);if(typeof e!==\"object\"||!t||!e.from)return;if(t===\"insert\"&&!e.to)return;var i=$tm.indeces.tById[e.from];if(!i||!utils.tiddlerExists(i))return;var r=new EdgeType(e.type);var s=utils.getTiddler(i);var a=r.namespace;if(a===\"tw-list\"){if(!e.to)return;return this._processListEdge(s,e,r,t)}else if(a===\"tw-field\"){if(!e.to)return;return this._processFieldEdge(s,e,r,t)}else if(a===\"tw-body\"){return null}else{return this._processTmapEdge(s,e,r,t)}return e};Adapter.prototype._processTmapEdge=function(e,t,i,r){if(r===\"delete\"&&!t.id)return;var s=utils.parseFieldData(e,\"tmap.edges\",{});if(r===\"insert\"){t.id=t.id||utils.genUUID();s[t.id]={to:t.to,type:i.id};if(!i.exists()){i.save()}}else{delete s[t.id]}utils.writeFieldData(e,\"tmap.edges\",s,$tm.config.sys.jsonIndentation);return t};Adapter.prototype._processListEdge=function(e,t,i,r){var s=i.name;var a=utils.getTiddler(e);var o=$tw.utils.parseStringArray(e.fields[s]);o=(o||[]).slice();var d=$tm.indeces.tById[t.to];if(r===\"insert\"){o.push(d);if(!i.exists()){i.save()}}else{var n=o.indexOf(d);if(n>-1){o.splice(n,1)}}utils.setField(a,s,$tw.utils.stringifyList(o));return t};Adapter.prototype._processFieldEdge=function(e,t,i,r){var s=$tm.indeces.tById[t.to];if(s==null)return;var a=r===\"insert\"?s:\"\";utils.setField(e,i.name,a);if(!i.exists()){i.save()}return t};Adapter.prototype.getAdjacencyList=function(e,t){$tm.start(\"Creating adjacency list\");t=t||{};if(!t.edges){var i=utils.getMatches($tm.selector.allPotentialNodes);t.edges=this.getEdgesForSet(i,t.toWL,t.typeWL)}var r=utils.groupByProperty(t.edges,e||\"to\");$tm.stop(\"Creating adjacency list\");return r};Adapter.prototype.getNeighbours=function(e,t){$tm.start(\"Get neighbours\");t=t||{};var i=utils.getArrayValuesAsHashmapKeys(e);var r=new ViewAbstraction(t.view);var s=t.addProperties;var a=utils.makeHashMap();var o=$tm.indeces.allETy;var d=utils.makeHashMap();var n=t.toWL;var l=t.typeWL;var p=$tm.indeces.tById;var u=$tm.indeces.idByT;var f=parseInt(t.steps)>0?t.steps:1;var g=t.direction||r.exists()&&r.getConfig(\"neighbourhood_directions\");var c=!g||g===\"both\";var v=c||g===\"in\";var y=c||g===\"out\";var h=this.getAdjacencyList(\"to\",t);var m=function(e,t){a[e.id]=e;var r=p[e[t]];if(!i[r]){i[r]=true;var o=this.makeNode(r,s);if(o){d[o.id]=o;A.push(r)}}}.bind(this);for(var w=0;w<f&&e.length;w++){var A=[];for(var b=e.length;b--;){if(utils.isSystemOrDraft(e[b])){continue}var T=this.getEdges(e[b],n,l);for(var $ in T){var E=o[T[$].type];if(c||y&&E.toArrow||v&&E.invertedArrow){m(T[$],\"to\")}}var N=h[u[e[b]]];if(!N)continue;for(var x=N.length;x--;){var E=o[N[x].type];if(c||v&&E.toArrow||y&&E.invertedArrow){m(N[x],\"from\")}}}e=A}var k={nodes:d,edges:a};$tm.logger(\"debug\",\"Retrieved neighbourhood\",k,\"steps\",w);$tm.stop(\"Get neighbours\");return k};Adapter.prototype.getGraph=function(e){$tm.start(\"Assembling Graph\");e=e||{};var t=new ViewAbstraction(e.view);var i=utils.getMatches(e.filter||t.exists()&&t.getNodeFilter(\"compiled\"));var r=utils.getArrayValuesAsHashmapKeys(i);var s=e.edgeTypeWL||t.exists()&&t.getEdgeTypeFilter(\"whitelist\");var a=parseInt(e.neighbourhoodScope||t.exists()&&t.getConfig(\"neighbourhood_scope\"));var o={edges:this.getEdgesForSet(i,r,s),nodes:this.selectNodesByReferences(i,{view:t,outputType:\"hashmap\"})};if(a){var d=this.getNeighbours(i,{steps:a,view:t,typeWL:s,addProperties:{group:\"tmap:neighbour\"}});utils.merge(o,d);if(t.exists()&&t.isEnabled(\"show_inter_neighbour_edges\")){var n=this.getTiddlersById(d.nodes);var r=utils.getArrayValuesAsHashmapKeys(n);$tw.utils.extend(o.edges,this.getEdgesForSet(n,r))}}this._removeObsoleteViewData(o.nodes,t);this.attachStylesToNodes(o.nodes,t);$tm.stop(\"Assembling Graph\");$tm.logger(\"debug\",\"Assembled graph:\",o);return o};Adapter.prototype.getEdges=function(e,t,i){var r=utils.getTiddler(e);if(!r||utils.isSystemOrDraft(r))return;var s=utils.makeHashMap();this._addTmapEdges(s,r,t,i);this._addBodyAndFieldEdges(s,r,t,i);return s};Adapter.prototype._addBodyAndFieldEdges=function(e,t,i,r){var s=t.fields;var a=utils.getTiddlerRef(t);var o=$tm.indeces;var d=o.maETyFiNa;var n=utils.makeHashMap();if(!r||r[\"tw-body:link\"]){n[\"tw-body:link\"]=$tw.wiki.getTiddlerLinks(a)}if(this.isTransTypeEnabled&&(!r||r[\"tw-body:transclude\"])){n[\"tw-body:transclude\"]=$tw.wiki.getTiddlerTranscludes(a)}for(var l in s){var p=d[l];if(!p||r&&!r[p.id])continue;if(p.namespace===\"tw-field\"){n[p.id]=[s[l]]}else if(p.namespace===\"tw-list\"){n[p.id]=$tw.utils.parseStringArray(s[l])}else if(p.namespace===\"tw-filter\"){var u=s[l];n[p.id]=utils.getMatches(u,i)}}if(!n)return;var f=t.fields[\"tmap.id\"];var g=o.idByT;var c=o.allETy;for(var v in n){var y=n[v];if(!y)continue;var p=c[v];for(var h=y.length;h--;){var m=y[h];if(!m||!$tw.wiki.tiddlerExists(m)||utils.isSystemOrDraft(m)||i&&!i[m])continue;var w=p.id+$tw.utils.hashString(a+m);var A=this.makeEdge(f,g[m],p,w);if(A){e[A.id]=A}}}};Adapter.prototype._addTmapEdges=function(e,t,i,r){var s=utils.parseFieldData(t,\"tmap.edges\");if(!s)return;var a=$tm.indeces.tById;var o=t.fields[\"tmap.id\"];for(var d in s){var n=s[d];var l=a[n.to];if(l&&(!i||i[l])&&(!r||r[n.type])){var p=this.makeEdge(o,n.to,n.type,d);if(p){e[d]=p}}}};Adapter.prototype.getEdgesForSet=function(e,t,i){var r=utils.makeHashMap();for(var s=e.length;s--;){$tw.utils.extend(r,this.getEdges(e[s],t,i))}return r};Adapter.prototype.selectEdgesByType=function(e){var t=utils.makeHashMap();t[new EdgeType(e).id]=true;return this.getEdgesForSet(this.getAllPotentialNodes(),null,t)};Adapter.prototype.getAllPotentialNodes=function(){return utils.getMatches($tm.selector.allPotentialNodes)};Adapter.prototype._processEdgesWithType=function(e,t){e=new EdgeType(e);$tm.logger(\"debug\",\"Processing edges\",e,t);var i=this.selectEdgesByType(e);if(t.action===\"rename\"){var r=new EdgeType(t.newName);r.load(e);r.save()}for(var s in i){this._processEdge(i[s],\"delete\");if(t.action===\"rename\"){i[s].type=t.newName;this._processEdge(i[s],\"insert\")}}$tw.wiki.deleteTiddler(e.fullPath)};Adapter.prototype.selectNodesByFilter=function(e,t){var i=utils.getMatches(e);return this.selectNodesByReferences(i,t)};Adapter.prototype.selectNodesByReferences=function(e,t){t=t||{};var i=t.addProperties;var r=utils.makeHashMap();var s=Object.keys(e);for(var a=s.length;a--;){var o=this.makeNode(e[s[a]],i);if(o){r[o.id]=o}}return utils.convert(r,t.outputType)};Adapter.prototype.selectNodesByIds=function(e,t){var i=this.getTiddlersById(e);return this.selectNodesByReferences(i,t)};Adapter.prototype.selectNodeById=function(e,t){t=utils.merge(t,{outputType:\"hashmap\"});var i=this.selectNodesByIds([e],t);return i[e]};Adapter.prototype.makeEdge=function(e,t,i,r){if(!e||!t)return;if(e instanceof $tw.Tiddler){e=e.fields[\"tmap.id\"]}else if(typeof e===\"object\"){e=e.id}i=$tm.indeces.allETy[i]||new EdgeType(i);var s=i.getLabel();var a={id:r||utils.genUUID(),from:e,to:t,type:i.id};if(utils.isTrue(i[\"show-label\"],true)){a.label=s}a=$tw.utils.extend(a,i.style);return a};Adapter.prototype.removeNodeType=function(e){var e=new NodeType(e);$tw.wiki.deleteTiddler(e.fullPath)};Adapter.prototype.makeNode=function(e,t){var i=utils.getTiddler(e);if(!i||utils.isSystemOrDraft(i))return;var r=utils.merge({},t);r.id=this.assignId(i);var s=i.fields[$tm.field.nodeLabel];r.label=s&&$tm.field.nodeLabel!==\"title\"?$tw.wiki.renderText(\"text/plain\",\"text/vnd-tiddlywiki\",s):i.fields.title;return r};Adapter.prototype.getInheritedNodeStyles=function(e){var t=this.getTiddlersById(e);var i={};var r=$tm.indeces.glNTy;for(var s=r.length;s--;){var a=r[s];if(a.id===\"tmap:neighbour\"){var o=$tm.indeces.tById;var d=[];for(var n in e){if(e[n].group===\"tmap:neighbour\"){d.push(o[n])}}}else{var d=a.getInheritors(t)}for(var l=d.length;l--;){var p=d[l];var u=i[p]=i[p]||{};u.style=utils.merge(u.style||{},a.style);if(a[\"fa-icon\"]){u[\"fa-icon\"]=a[\"fa-icon\"]}else if(a[\"tw-icon\"]){u[\"tw-icon\"]=a[\"tw-icon\"]}}}return i};Adapter.prototype.attachStylesToEdges=function(e,t){};Adapter.prototype._removeObsoleteViewData=function(e,t){t=new ViewAbstraction(t);if(!t.exists()||!e)return;var i=t.getNodeData();var r=0;for(var s in i){if(e[s]===undefined&&i[s]!=null){i[s]=undefined;r++}}if(r){$tm.logger(\"debug\",\"[Cleanup]\",\"Removed obsolete node data:\",t.getLabel(),r);t.saveNodeData(i)}};Adapter.prototype.attachStylesToNodes=function(e,t){t=new ViewAbstraction(t);var i=this.getInheritedNodeStyles(e);var r=t.exists()?t.getNodeData():utils.makeHashMap();var s=t.exists()&&!t.isEnabled(\"physics_mode\");var a=$tm.field.nodeIcon;var o=$tm.indeces.tById;for(var d in e){var n=o[d];var l=$tw.wiki.getTiddler(n);var p=l.fields;var u=e[d];var f=null;var g=null;if(i[n]){if(i[n].style){utils.merge(u,i[n].style)}f=i[n][\"fa-icon\"];g=i[n][\"tw-icon\"]}if(p.color){u.color=p.color}if(p[\"tmap.style\"]){utils.merge(u,utils.parseJSON(p[\"tmap.style\"]))}f=p[\"tmap.fa-icon\"]||f;g=p[\"icon\"]||g;if(r[d]){utils.merge(u,r[d]);if(s){u.fixed={x:u.x!=null,y:u.y!=null}}f=r[d][\"fa-icon\"]||f;g=r[d][\"tw-icon\"]||g}var c=u.color!==null&&typeof u.color===\"object\";var v=c?u.color.background:u.color;u.color={background:v,border:c?u.color.border:undefined};this._addNodeIcon(u,f,g);u.font=u.font||{};if(u.shape&&!this.visShapesWithTextInside[u.shape]){u.font.color=\"black\"}else if(!u.font.color&&v){u.font.color=getContrastColour(v,v,\"black\",\"white\")}if(u.shape===\"icon\"&&typeof u.icon===\"object\"){u.icon.color=v}}if(t.exists()){var u=e[t.getConfig(\"central-topic\")];if(u){utils.merge(u,$tm.indeces.glNTyById[\"tmap:central-topic\"].style)}}};Adapter.prototype.deleteNode=function(e){if(!e)return;var t=typeof e===\"object\"?e.id:e;var i=$tm.indeces.tById[t];if(i){utils.deleteTiddlers([i])}var r=utils.getMatches($tm.selector.allViews);for(var s=r.length;s--;){var a=new ViewAbstraction(r[s]);a.removeNode(t);if(a.getNodeData(t)){a.saveNodeData(t,null)}}var o=this.getNeighbours([i]);this.deleteEdges(o.edges)};Adapter.prototype.deleteNodes=function(e){e=utils.convert(e,\"array\");for(var t=e.length;t--;){this.deleteNode(e[t])}};Adapter.prototype.storePositions=function(e,t){t=new ViewAbstraction(t);if(!t.exists())return;t.saveNodeData(e)};Adapter.prototype.assignId=function(e,t){var i=utils.getTiddler(e,true);if(!i)return;var r=i.fields[\"tmap.id\"];if(!r||t){r=utils.genUUID();utils.setField(i,\"tmap.id\",r);$tm.logger(\"info\",\"Assigning new id to\",i.fields.title)}$tm.indeces.tById[r]=i.fields.title;$tm.indeces.idByT[i.fields.title]=r;return r};Adapter.prototype.insertNode=function(e,t,i){i=i||{};e=e||{};var r={\"tmap.id\":null};if(!i.fields||!i.fields.text){r.text=\"\"}var s=$tw.wiki.generateNewTitle(e.label||utils.getRandomLabel());e.label=r.title=s;var a=new $tw.Tiddler(i.fields,r,$tw.wiki.getModificationFields(),$tw.wiki.getCreationFields());$tw.wiki.addTiddler(a);e=this.makeNode(a,e);var t=new ViewAbstraction(t);if(t.exists()){t.addNode(e)}return e};Adapter.prototype._getFAdigits=function(e){return e.length===4?e:e.substr(3,4)};Adapter.prototype.getTiddlersById=function(e){if(Array.isArray(e)){e=utils.getArrayValuesAsHashmapKeys(e)}else if(e instanceof vis.DataSet){e=utils.getLookupTable(e,\"id\")}var t=[];var i=$tm.indeces.tById;for(var r in e){if(i[r])t.push(i[r])}return t};Adapter.prototype.getId=function(e){return $tm.indeces.idByT[utils.getTiddlerRef(e)]};Adapter.prototype._addNodeIcon=function(e,t,i){if(t){e.shape=\"icon\";e.icon={shape:\"icon\",face:\"FontAwesome\",color:e.color,code:String.fromCharCode(\"0x\"+this._getFAdigits(t))};return}if(!i)return;var r=utils.getTiddler(i);if(!r)return;if(r.fields[\"_canonical_uri\"]){e.image=r.fields[\"_canonical_uri\"];e.shape=\"image\";return}if(r.fields.text){e.image=utils.getDataUri(r);e.shape=\"image\";return}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/Adapter",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/CallbackManager": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/CallbackManager\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=CallbackManager;var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function CallbackManager(){this.callbacks=utils.makeHashMap()}CallbackManager.prototype.add=function(e,a,l){$tm.logger(\"debug\",'A callback was registered for changes of \"'+e+'\"');this.callbacks[e]={execute:a,isDeleteOnCall:typeof l===\"boolean\"?l:true}};CallbackManager.prototype.remove=function(e){if(!e)return;if(typeof e===\"string\"){e=[e]}for(var a=e.length;a--;){var l=e[a];if(this.callbacks[l]){$tm.logger(\"debug\",'A callback for \"'+l+'\" will be deleted');delete this.callbacks[l]}}};CallbackManager.prototype.handleChanges=function(e){if(this.callbacks.length==0)return;for(var a in e){if(!this.callbacks[a])continue;if($tw.wiki.getTiddler(a)){$tm.logger(\"debug\",\"Executing a callback for: \"+a);this.callbacks[a].execute(a);if(!this.callbacks.isDeleteOnCall)continue}this.remove(a)}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/CallbackManager",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/DialogManager": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/DialogManager\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=DialogManager;var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var CallbackManager=require(\"$:/plugins/felixhayashi/tiddlymap/js/CallbackManager\");function DialogManager(t,e){this.callbackManager=t;if(e){this.context=e}}DialogManager.prototype.open=function(t,e,i){if(utils.isTrue($tm.config.sys.suppressedDialogs[t],false)){$tm.logger(\"warning\",\"Suppressed dialog\",t);return}e=e||{};$tm.logger(\"debug\",\"Dialog param object\",e);if(typeof i===\"function\"&&this.context){i=i.bind(this.context)}var a=$tm.path.tempRoot+\"/dialog-\"+utils.genUUID();var l=utils.getTiddler($tm.path.dialogs+\"/\"+t);var r={title:a,buttons:l.fields[\"buttons\"]||\"ok_cancel\",classes:\"tmap-modal-content \"+l.fields[\"classes\"],output:a+\"/output\",result:a+\"/result\",temp:a+\"/temp\",template:l.fields.title,templateId:t,currentTiddler:a+\"/output\",text:utils.getText($tm.path.dialogs)};if(e.dialog){if(e.dialog.preselects){$tw.wiki.addTiddler(new $tw.Tiddler({title:r.output},utils.flatten(e.dialog.preselects)));delete e.dialog.preselects}utils.merge(r,e.dialog)}r.footer=utils.getText($tm.path.footers);r=utils.flatten(r);e=utils.flatten(e);var s=function(t){this.getElement(\"hidden-close-button\").click();var e=$tw.wiki.getTiddler(t);var l=e.fields.text;if(l){var s=$tw.wiki.getTiddler(r.output)}else{var s=null;$tm.notify(\"operation cancelled\")}if(typeof i===\"function\"){i(l,s)}utils.deleteByPrefix(a)}.bind(this);this.callbackManager.add(r.result,s,true);var n=new $tw.Tiddler(l,e,r);$tw.wiki.addTiddler(n);$tm.logger(\"debug\",\"Opening dialog\",n);$tw.rootWidget.dispatchEvent({type:\"tm-modal\",param:n.fields.title,paramObject:n.fields});this.addKeyBindings();return n};DialogManager.prototype.getElement=function(t){return utils.getFirstElementByClassName(\"tmap-\"+t)};DialogManager.prototype.addKeyBindings=function(){var t=$tm.keycharm({container:utils.getFirstElementByClassName(\"tc-modal\")});var e=/tmap-triggers-(.+?)-on-(.+?)(?:\\s|$)/;var i=document.getElementsByClassName(\"tmap-trigger-field\");for(var a=i.length;a--;){var l=i[a].className.split(\" \");for(var r=l.length;r--;){var s=l[r].match(e);if(!s){continue}var n=s[1];var o=s[2];var d=this.getElement(n);if(!d)continue;t.bind(o,function(){this.click()}.bind(d))}}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/DialogManager",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/exception": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/exception\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports={};var exception=module.exports;exception.EnvironmentError=function(e){this.name=\"EnvironmentError\";this.message=\"Critical parts of the underlying system changed: \"+e};exception.DependencyError=function(e){this.name=\"DependencyError\";this.message=\"TiddlyMap cannot run without: \"+e};for(var ex in exception){exception[ex].prototype=Object.create(Error.prototype);exception[ex].constructor=exception[ex]}",
"title": "$:/plugins/felixhayashi/tiddlymap/js/exception",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/fixer": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/fixer\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports={};var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var Adapter=require(\"$:/plugins/felixhayashi/tiddlymap/js/Adapter\");var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var moveEdges=function(e,t){var r=utils.getTiddlersByPrefix(e);for(var i=0;i<r.length;i++){var a=utils.getBasename(r[i]);if(a===\"__noname__\"){a=\"tmap:unknown\"}a=new EdgeType(a);if(!a.exists())a.save();var s=$tw.wiki.getTiddlerData(r[i]);for(var u=0;u<s.length;u++){s[u].type=(t?t+\":\":\"\")+a.id;$tm.adapter.insertEdge(s[u])}$tw.wiki.deleteTiddler(r[i])}};var executeUpgrade=function(e,t,r){if(!utils.isLeftVersionGreater(e,t))return;$tm.logger(\"debug\",\"Upgrading data structure to \"+e);var i=r();utils.setEntry($tm.ref.sysMeta,\"dataStructureState\",e);return i};var fixer=module.exports;fixer.fixId=function(){var e=$tw.wiki.getTiddlerData($tm.ref.sysMeta,{});var t={before:\"0.9.0\",after:\"0.9.2\"};executeUpgrade(\"0.9.2\",e.dataStructureState,function(){if(utils.isLeftVersionGreater(\"0.9.2\",e.originalVersion)){var t=\"$:/plugins/felixhayashi/tiddlymap/config/sys/user\";var r=utils.getEntry(t,\"field.nodeId\",\"tmap.id\");utils.moveFieldValues(r,\"tmap.id\",true,false)}})};fixer.fix=function(){var e=$tw.wiki.getTiddlerData($tm.ref.sysMeta,{});$tm.logger(\"debug\",\"Fixer is started\");$tm.logger(\"debug\",\"Data-structure currently in use: \",e.dataStructureState);executeUpgrade(\"0.7.0\",e.dataStructureState,function(){moveEdges(\"$:/plugins/felixhayashi/tiddlymap/graph/edges\",null);var e=$tm.selector.allViews;var t=utils.getMatches(e);for(var r=0;r<t.length;r++){var i=new ViewAbstraction(t[r]);moveEdges(i.getRoot()+\"/graph/edges\",i)}});executeUpgrade(\"0.7.32\",e.dataStructureState,function(){var e=new $tm.ViewAbstraction(\"Live View\");if(!e.exists())return;e.setNodeFilter(\"[field:title{$:/temp/tmap/currentTiddler}]\",true);e.setConfig({\"refresh-trigger\":null,\"refresh-triggers\":$tw.utils.stringifyList([\"$:/temp/tmap/currentTiddler\"])})});executeUpgrade(\"0.9.0\",e.dataStructureState,function(){var e=$tm.ref.visUserConf;var t=utils.unflatten($tw.wiki.getTiddlerData(e,{}));if(typeof t.groups===\"object\"){var r=new $tm.NodeType(\"tmap:neighbour\");r.setStyle(t.groups[\"neighbours\"]);r.save();delete t.groups;$tw.wiki.setTiddlerData(e,t)}});fixer.fixId();executeUpgrade(\"0.9.16\",e.dataStructureState,function(){var e=$tm.indeces.glNTy;for(var t=e.length;t--;){e[t].save(null,true)}});executeUpgrade(\"0.10.3\",e.dataStructureState,function(){var e=$tm.ref.liveTab;if(utils.getTiddler(e).hasTag(\"$:/tags/SideBar\")){$tw.wiki.deleteTiddler(e);utils.setField(e,\"tags\",\"$:/tags/SideBar\")}});executeUpgrade(\"0.11.0\",e.dataStructureState,function(){var e=utils.getMatches($tm.selector.allViews);for(var t=e.length;t--;){var r=new ViewAbstraction(e[t]);var i=r.getEdgeTypeFilter(\"raw\");var a=\"edge_type_namespace\";r.setConfig(a,r.getConfig(a));if(i){var s=$tm.path.edgeTypes;i=utils.replaceAll(i,\"\",[s,s+\"/\",\"[prefix[\"+s+\"]]\",\"[prefix[\"+s+\"/]]\",[\"[suffix[tw-body:link]]\",\"[[tw-body:link]]\"],[\"[suffix[tw-list:tags]]\",\"[[tw-list:tags]]\"],[\"[suffix[tw-list:list]]\",\"[[tw-body:list]]\"],[\"[suffix[tmap:unknown]]\",\"[[tmap:unknown]]\"],[\"[suffix[unknown]]\",\"[[tmap:unknown]]\"]]);var u=\"-[prefix[_]] \"+i}else{var u=$tm.filter.defaultEdgeTypeFilter}r.setEdgeTypeFilter(u)}})};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/fixer",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/EdgeType": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/EdgeType\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=EdgeType;var MapElementType=require(\"$:/plugins/felixhayashi/tiddlymap/js/MapElementType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function EdgeType(e,t,r){if(e instanceof EdgeType)return e;r=r||{};this.root=$tm.path.edgeTypes;var i=EdgeType._getIdParts(e,this.root);if(!i.name)return new EdgeType(\"tmap:unknown\");this.marker=i.marker;this.name=i.name;this.namespace=i.namespace;this.id=EdgeType._getId(this.marker,this.namespace,this.name);if(!this.namespace&&r.namespace){if(!new EdgeType(this.id).exists()){return new EdgeType(r.namespace+\":\"+this.name)}}MapElementType.call(this,this.id,this.root,EdgeType._fieldMeta,t);var s=this.style&&this.style.arrows;if(s){this.invertedArrow=this._isArrow(s,\"from\");this.toArrow=this._isArrow(s,\"to\")||this._isArrow(s,\"middle\");this.biArrow=this.invertedArrow===this.toArrow;if(this.biArrow)this.toArrow=this.invertedArrow=true}else{this.toArrow=true}}EdgeType.prototype=Object.create(MapElementType.prototype);EdgeType._fieldMeta=$tw.utils.extend({},MapElementType._fieldMeta,{label:{},\"show-label\":{}});EdgeType.edgeTypeRegexStr=\"^(_?)([^:_][^:]*):?([^:]*)\";EdgeType.edgeTypeRegex=new RegExp(EdgeType.edgeTypeRegexStr);EdgeType._getIdParts=function(e,t){e=utils.getWithoutPrefix(e||\"\",t+\"/\");var r=e.match(EdgeType.edgeTypeRegex)||[];return{marker:r[1]||\"\",namespace:r[3]&&r[2]||\"\",name:r[3]||r[2]||\"\"}};EdgeType._getId=function(e,t,r){return e+t+(t?\":\":\"\")+r};EdgeType.prototype.getLabel=function(){return this.label||this.name};EdgeType.prototype._isArrow=function(e,t){var r=e[t];return t===\"to\"&&r==null||r===true||typeof r===\"object\"&&r.enabled!==false};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/EdgeType",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/MapElementType": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/MapElementType\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=MapElementType;var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function MapElementType(t,i,e,s){this.id=t;this.root=i;this._fieldMeta=e;this.fullPath=this.root+\"/\"+this.id;this.isShipped=$tw.wiki.getSubTiddler($tm.path.pluginRoot,this.fullPath);this.load(s||this.fullPath)}MapElementType._fieldMeta={description:{},style:{parse:utils.parseJSON,stringify:JSON.stringify},modified:{},created:{}};MapElementType.prototype.load=function(t){if(!t)return;if(typeof t===\"string\"){var i=utils.startsWith(t,this.root);var e=i?t:this.root+\"/\"+t;this.loadFromTiddler(e)}else if(t instanceof $tw.Tiddler){this.loadFromTiddler(t)}else if(typeof t===\"object\"){for(var s in this._fieldMeta){this[s]=t[s]}}};MapElementType.prototype.loadFromTiddler=function(t){var i=utils.getTiddler(t);if(!i)return;var e=$tw.wiki.getSubTiddler($tm.path.pluginRoot,this.fullPath)||{};var s=$tw.utils.extend({},e.fields,i.fields);for(var l in this._fieldMeta){var r=this._fieldMeta[l].parse;var a=s[l];this[l]=r?r.call(this,a):a}};MapElementType.prototype.exists=function(){return utils.tiddlerExists(this.fullPath)};MapElementType.prototype.setStyle=function(t,i){if(typeof t===\"string\"){t=utils.parseJSON(t)}if(typeof t===\"object\"){if(i){utils.merge(this.style,t)}else{this.style=t}}};MapElementType.prototype.save=function(t,i){if(!t){t=this.fullPath}else if(typeof t!==\"string\"){return}var e={title:t,text:\"\"};if(!utils.startsWith(t,this.root)){e.id=this.id}if(i!==true){this.modified=new Date}if(!this.exists()){this.created=this.modified}for(var s in this._fieldMeta){var l=this._fieldMeta[s].stringify;e[s]=l?l.call(this,this[s]):this[s]}$tw.wiki.addTiddler(new $tw.Tiddler(e))};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/MapElementType",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/NodeType": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/NodeType\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=NodeType;var MapElementType=require(\"$:/plugins/felixhayashi/tiddlymap/js/MapElementType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function NodeType(e,t){if(e instanceof NodeType){return e}e=typeof e===\"string\"?utils.getWithoutPrefix(e,$tm.path.nodeTypes+\"/\"):\"tmap:unknown\";MapElementType.call(this,e,$tm.path.nodeTypes,NodeType._fieldMeta,t)}NodeType.prototype=Object.create(MapElementType.prototype);NodeType._fieldMeta=$tw.utils.extend({},MapElementType._fieldMeta,{view:{},priority:{parse:function(e){return isNaN(e)?1:parseInt(e)},stringify:function(e){return utils.isInteger(e)?e.toString():\"1\"}},scope:{stringify:utils.getWithoutNewLines},\"fa-icon\":{},\"tw-icon\":{}});NodeType.prototype.getInheritors=function(e){var t=this.scope;return t?utils.getMatches(t,e||$tw.wiki.allTitles()):[]};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/NodeType",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/Popup": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/Popup\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=Popup;var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function Popup(e,t){t=t||{};this._parentDomNode=e;this._domNode=document.createElement(\"div\");this._domNode.style.display=\"none\";this._domNode.className=\"tmap-popup\";this._parentDomNode.appendChild(this._domNode);$tw.utils.addClass(this._domNode,t.className);this._isEnabled=true;this._isPreventShowOrHide=false;this._isHideOnClick=!!t.hideOnClick;this._timeoutShow=null;this._timeoutHide=null;this._signature=null;this._isDisplayNoneAfterAnimation=true;var i=parseInt(t.leavingDelay);this._hideDelayLeavingPopup=utils.isInteger(i)?i:200;var i=parseInt(t.hideDelay);this._hideDelay=utils.isInteger(i)?i:200;var i=parseInt(t.showDelay);this._showDelay=utils.isInteger(i)?i:200;utils.bind(this,[\"_show\",\"_hide\",\"_handleEnter\",\"_handleLeave\",\"_handleAnimationEnd\",\"_handleClick\"]);this._listeners={mouseenter:this._handleEnter,mouseleave:this._handleLeave,click:[this._handleClick,true]};var s=this._handleAnimationEnd;this._listeners[$tw.utils.convertEventName(\"animationEnd\")]=s;this._listeners[$tw.utils.convertEventName(\"transitionEnd\")]=s;utils.setDomListeners(\"add\",this._domNode,this._listeners,false)}Popup.prototype._handleEnter=function(e){this._isPreventShowOrHide=true};Popup.prototype._handleLeave=function(e){this._isPreventShowOrHide=false;this.hide(this._hideDelayLeavingPopup)};Popup.prototype._handleClick=function(e){if(this._isHideOnClick){this._hide(true)}};Popup.prototype._handleAnimationEnd=function(){if(this._isDisplayNoneAfterAnimation){this._domNode.style.display=\"none\"}};Popup.prototype._hide=function(e){if(!e&&this._isPreventShowOrHide)return;this._signature=null;this._isDisplayNoneAfterAnimation=true;this._isPreventShowOrHide=false;$tw.utils.removeClass(this._domNode,\"tmap-popup-active\")};Popup.prototype._show=function(e,t){if(this._isPreventShowOrHide||$tm.mouse.ctrlKey||!this._isEnabled){return}this._domNode.style.display=\"none\";$tw.utils.removeClass(this._domNode,\"tmap-popup-active\");this._domNode.removeAttribute(\"style\");utils.removeDOMChildNodes(this._domNode);var i=this._domNode.appendChild(document.createElement(\"div\"));if(typeof t===\"function\"){t(e,i)}else{i.innerHTML=t}if(!i.childNodes.length)return;var s=this._parentDomNode.getBoundingClientRect();var o=$tm.mouse.clientX;var n=$tm.mouse.clientY;this._signature=e;this._domNode.style.display=\"block\";var h=this._domNode.getBoundingClientRect();var d=s.right-(o+h.width);var l=o-h.width-s.left;var a=d>l;var r=s.bottom-(n+h.height);var p=n-h.height-s.top;var u=r>p;var _=a?-15:h.width+15;var m=u?-15:h.height+15;this._domNode.style.left=o-s.left-_+\"px\";this._domNode.style.top=n-s.top-m+\"px\";this._isDisplayNoneAfterAnimation=false;$tw.utils.addClass(this._domNode,\"tmap-popup-active\")};Popup.prototype.show=function(e,t,i){this._clearTimeouts();i=utils.isInteger(i)?i:this._showDelay;this._timeoutShow=window.setTimeout(this._show,i,e,t)};Popup.prototype.hide=function(e,t){this._clearTimeouts();e=utils.isInteger(e)?e:this._hideDelay;if(t||e===0){this._hide(t)}else{this._timeoutHide=window.setTimeout(this._hide,e,t)}};Popup.prototype.setEnabled=function(e){this._isEnabled=e};Popup.prototype.isShown=function(){return this._domNode.style.display===\"block\"};Popup.prototype._clearTimeouts=function(){window.clearTimeout(this._timeoutShow);window.clearTimeout(this._timeoutHide);this._timeoutShow=undefined;this._timeoutHide=undefined};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/Popup",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/URL": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/URL\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=Url;/**\n * <<<\n * Lightweight URL manipulation with JavaScript. This library is \n * independent of any other libraries and has pretty simple interface\n * and lightweight code-base. Some ideas of query string parsing \n * had been taken from Jan Wolter.\"\n * \n * @see http://unixpapa.com/js/querystring.html\n * @license MIT\n * @author Mykhailo Stadnyk <mikhus@gmail.com>\n * <<< https://github.com/Mikhus/jsurl\n * \n * @class\n * @param {string} url\n */\nfunction Url(t){this.paths=function(t){var e=\"\",r=0,o;if(t&&t.length&&t+\"\"!==t){if(this.isAbsolute()){e=\"/\"}for(o=t.length;r<o;r++){t[r]=encode(t[r])}this.path=e+t.join(\"/\")}t=(this.path.charAt(0)===\"/\"?this.path.slice(1):this.path).split(\"/\");for(r=0,o=t.length;r<o;r++){t[r]=decode(t[r])}return t};this.encode=encode;this.decode=decode;this.isAbsolute=function(){return this.protocol||this.path.charAt(0)===\"/\"};this.toString=function(){return(this.protocol&&this.protocol+\"://\")+(this.user&&encode(this.user)+(this.pass&&\":\"+encode(this.pass))+\"@\")+(this.host&&this.host)+(this.port&&\":\"+this.port)+(this.path&&this.path)+(this.query.toString()&&\"?\"+this.query)+(this.hash&&\"#\"+encode(this.hash))};parse(this,t)}var map={protocol:\"protocol\",host:\"hostname\",port:\"port\",path:\"pathname\",query:\"search\",hash:\"hash\"},defaultPorts={ftp:21,gopher:70,http:80,https:443,ws:80,wss:443},parse=function(t,e){var r=document,o=r.createElement(\"a\"),e=e||r.location.href,s=e.match(/\\/\\/(.*?)(?::(.*?))?@/)||[],i;o.href=e;for(i in map){t[i]=o[map[i]]||\"\"}t.protocol=t.protocol.replace(/:$/,\"\");t.query=t.query.replace(/^\\?/,\"\");t.hash=decode(t.hash.replace(/^#/,\"\"));t.user=decode(s[1]||\"\");t.pass=decode(s[2]||\"\");t.port=defaultPorts[t.protocol]==t.port||t.port==0?\"\":t.port;if(!t.protocol&&!/^([a-z]+:)?\\/\\//.test(e)){var h=new Url(r.location.href.match(/(.*\\/)/)[0]),n=h.path.split(\"/\"),a=t.path.split(\"/\"),c=[\"protocol\",\"user\",\"pass\",\"host\",\"port\"],p=c.length;n.pop();for(i=0;i<p;i++){t[c[i]]=h[c[i]]}while(a[0]==\"..\"){n.pop();a.shift()}t.path=(e.charAt(0)!=\"/\"?n.join(\"/\"):\"\")+\"/\"+a.join(\"/\")}else{t.path=t.path.replace(/^\\/?/,\"/\")}t.paths((t.path.charAt(0)==\"/\"?t.path.slice(1):t.path).split(\"/\"));parseQs(t)},encode=function(t){return encodeURIComponent(t).replace(/'/g,\"%27\")},decode=function(t){t=t.replace(/\\+/g,\" \");t=t.replace(/%([ef][0-9a-f])%([89ab][0-9a-f])%([89ab][0-9a-f])/gi,function(t,e,r,o){var s=parseInt(e,16)-224,i=parseInt(r,16)-128;if(s==0&&i<32){return t}var h=parseInt(o,16)-128,n=(s<<12)+(i<<6)+h;if(n>65535){return t}return String.fromCharCode(n)});t=t.replace(/%([cd][0-9a-f])%([89ab][0-9a-f])/gi,function(t,e,r){var o=parseInt(e,16)-192;if(o<2){return t}var s=parseInt(r,16)-128;return String.fromCharCode((o<<6)+s)});t=t.replace(/%([0-7][0-9a-f])/gi,function(t,e){return String.fromCharCode(parseInt(e,16))});return t},parseQs=function(t){var e=t.query;t.query=new function(t){var e=/([^=&]+)(=([^&]*))?/g,r;while(r=e.exec(t)){var o=decodeURIComponent(r[1].replace(/\\+/g,\" \")),s=r[3]?decode(r[3]):\"\";if(this[o]!=null){if(!(this[o]instanceof Array)){this[o]=[this[o]]}this[o].push(s)}else{this[o]=s}}this.clear=function(){for(var t in this){if(!(this[t]instanceof Function)){delete this[t]}}};this.count=function(){var t=0,e;for(e in this){if(!(this[e]instanceof Function)){t++}}return t};this.isEmpty=function(){return this.count()===0};this.toString=function(){var t=\"\",e=encode,r,o;for(r in this){if(this[r]instanceof Function){continue}if(this[r]instanceof Array){var s=this[r].length;if(s){for(o=0;o<s;o++){t+=t?\"&\":\"\";t+=e(r)+\"=\"+e(this[r][o])}}else{t+=(t?\"&\":\"\")+e(r)+\"=\"}}else{t+=t?\"&\":\"\";t+=e(r)+\"=\"+e(this[r])}}return t}}(e)};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/URL",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/utils": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/utils\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports={};var vis=require(\"$:/plugins/felixhayashi/vis/vis.js\");var exception=require(\"$:/plugins/felixhayashi/tiddlymap/js/exception\");var URL=require(\"$:/plugins/felixhayashi/tiddlymap/js/URL\");var utils=module.exports;utils.deleteTiddlers=function(e){var t=Object.keys(e);var i=$tw.wiki.getTiddlerList(\"$:/StoryList\");for(var r=t.length;r--;){var n=utils.getTiddlerRef(e[t[r]]);if(!$tw.wiki.tiddlerExists(e[t[r]])){continue}var l=i.indexOf(n);if(l!==-1){i.splice(l,1);utils.setField(\"$:/StoryList\",\"list\",i)}$tw.wiki.deleteTiddler(n)}};utils.moveFieldValues=function(e,t,i,r,n){if(e===t)return;var l=n||$tw.wiki.allTitles();for(var u=l.length;u--;){var s=utils.getTiddler(l[u]);if(s.isDraft()||!s.fields[e]||!r&&$tw.wiki.isSystemTiddler(l[u])){continue}var a={};a[t]=s.fields[e];if(i){a[e]=undefined}$tw.wiki.addTiddler(new $tw.Tiddler(s,a))}};utils.getLabel=function(e,t){var i=utils.getTiddler(e);return i&&i.fields[t]?i.fields[t]:i.fields.title};utils.ucFirst=function(e){return e&&e[0].toUpperCase()+e.slice(1)};utils.convert=function(e,t){if(typeof e!==\"object\")return;switch(t){case\"array\":return utils.getValues(e);case\"hashmap\":case\"object\":if(e instanceof vis.DataSet){return e.get({returnType:\"Object\"})}else{return e}case\"dataset\":default:if(e instanceof vis.DataSet){return e}if(!Array.isArray(e)){e=utils.getValues(e)}return new vis.DataSet(e)}};utils.getValues=function(e){if(Array.isArray(e)){return e}else if(e instanceof vis.DataSet){return e.get({returnType:\"Array\"})}var t=[];var i=Object.keys(e);for(var r=i.length;r--;){t.push(e[i[r]])}return t};utils.getDataUri=function(e,t,i){var r=utils.getTiddler(e);var t=t||r.fields.type||\"image/svg+xml\";var n=r.fields.text;var l=$tw.config.contentTypeInfo[t].encoding;if(t===\"image/svg+xml\"){n=n.replace(/\\r?\\n|\\r/g,\" \");if(!utils.hasSubString(\"xmlns\",n)){n=n.replace(/<svg/,'<svg xmlns=\"http://www.w3.org/2000/svg\"')}}if(i&&l!==\"base64\"){l=\"base64\";n=window.btoa(n)}return\"data:\"+t+\";\"+l+\",\"+n};utils.hasOwnProp=function(e,t){return Object.prototype.hasOwnProperty.call(e,t)};utils.makeHashMap=function(){var e=Object.create(null);Object.defineProperty(e,\"hasOwnProperty\",{enumerable:false,configurable:false,writable:false,value:Object.prototype.hasOwnProperty.bind(e)});return e};utils.getMatches=function(e,t){var i=undefined;if(typeof e===\"string\"){e=$tw.wiki.compileFilter(e)}if(t!=null&&typeof t===\"object\"){var r=$tw.wiki;if(!Array.isArray(t)){t=Object.keys(t)}i=function(e){for(var i=t.length;i--;){var n=r.getTiddler(t[i]);e(n,t[i])}}}return e.call($tw.wiki,i)};var eTyFiltAutoPrefix=\"[all[]] \";utils.getEdgeTypeMatches=function(e,t){if(!t){var i=$tm.path.edgeTypes+\"/\";t=utils.getTiddlersByPrefix(i,{iterator:\"eachTiddlerPlusShadows\",removePrefix:true})}if(t!=null&&!Array.isArray(t)){t=Object.keys(t)}return utils.getMatches(eTyFiltAutoPrefix+(e||\"\"),t)};utils.isEdgeTypeMatch=function(e,t){return utils.isMatch(e,eTyFiltAutoPrefix+(t||\"\"))};utils.isMatch=function(e,t){var i=utils.getTiddlerRef(e);var r=utils.getMatches(t,[i]);return i===r[0]};utils.isInteger=Number.isInteger||function(e){return typeof e===\"number\"&&isFinite(e)&&Math.floor(e)===e};utils.escapeRegex=function(e){return e.replace(/[-$^?.+*[\\]\\\\(){}|]/g,\"\\\\$&\")};utils.replaceAll=function(e,t,i){t=t||\"\";for(var r=i.length;r--;){var n=i[r];var l=t;if(Array.isArray(n)){l=n[1];n=n[0]}e=e.replace(n,l)}return e};utils.isTrue=function(e,t){if(e==null){return!!t}else if(typeof e===\"string\"){var i=parseInt(e);return isNaN(i)?e===\"true\":i!==0}else if(typeof e===\"boolean\"){return e}else if(typeof e===\"number\"){return i!==0}return false};utils.getTiddlerRef=function(e){if(e instanceof $tw.Tiddler){return e.fields.title}else if(typeof e===\"string\"){return e}};utils.getTiddlerNode=function(e){var t=utils.getTiddlerRef(e);return{type:\"tiddler\",attributes:{tiddler:{type:\"string\",value:t}},children:[]}};utils.getTranscludeNode=function(e,t){var i=utils.getTiddlerRef(e);return{type:\"transclude\",attributes:{tiddler:{type:\"string\",value:i}},children:[],isBlock:!!t}};utils.getElementNode=function(e,t,i){var r={type:\"element\",tag:e,attributes:{\"class\":{type:\"string\",value:i}},children:[]};if(t){r.children.push({type:\"text\",text:t})}return r};utils.registerTransclude=function(e,t,i,r){utils.removeArrayElement(e.children,e[t]);var n=utils.getTiddlerNode(i);n.children.push(utils.getTranscludeNode(null,true));e[t]=e.makeChildWidget(n);e.children.push(e[t]);return e[t]};utils.getTiddler=function(e,t){if(e instanceof $tw.Tiddler){if(!t){return e}e=e.fields.title}return $tw.wiki.getTiddler(e)};utils.getBasename=function(e){return e.substring(e.lastIndexOf(\"/\")+1)};utils.notify=function(e){var t=\"$:/temp/tiddlymap/notify\";$tw.wiki.addTiddler(new $tw.Tiddler({title:t,text:e}));$tw.notifier.display(t)};utils.tiddlerExists=function(e){var t=utils.getTiddlerRef(e);return t&&($tw.wiki.tiddlerExists(t)||$tw.wiki.isShadowTiddler(t))};utils.isPreviewed=function(e){if(e){if(e.getVariable(\"tv-tiddler-preview\")){return true}else{var t=\"tc-tiddler-preview-preview\";return!!utils.getAncestorWithClass(e.parentDomNode,t)}}return false};utils.getAncestorWithClass=function(e,t){if(typeof e!==\"object\"||typeof t!==\"string\")return;while(e.parentNode){e=e.parentNode;if($tw.utils.hasClass(e,t)){return e}}};utils.getPropertiesByPrefix=function(e,t,i){var r=utils.makeHashMap();for(var n in e){if(utils.startsWith(n,t)){r[i?n.substr(t.length):n]=e[n]}}return r};utils.getWithoutPrefix=function(e,t){return utils.startsWith(e,t)?e.substr(t.length):e};utils.hasKeyWithPrefix=function(e,t){for(var i in e){if(utils.startsWith(i,t)){return true}}return false};utils.startsWith=function(e,t){return e.substring(0,t.length)===t};utils.hasElements=function(e){return Object.keys(e).length>0};utils.groupByProperty=function(e,t){e=utils.getIterableCollection(e);var i=utils.makeHashMap();var r=Object.keys(e);for(var n in r){var l=e[r[n]];var u=l[t];if(u==null){throw\"Cannot group by property \"+t}else{if(!Array.isArray(i[u])){i[u]=[]}i[u].push(l)}}return i};utils.findAndRemoveClassNames=function(e){for(var t=e.length;t--;){var i=document.getElementsByClassName(e[t]);for(var r=i.length;r--;){$tw.utils.removeClass(i[r],e[t])}}};utils.parseFieldData=function(e,t,i){var r=utils.getTiddler(e);if(!r)return i;if(!t)t=\"text\";return utils.parseJSON(r.fields[t],i)};utils.getImgFromWeb=function(e,t){if(!e||typeof t!==\"function\")return;var i=new XMLHttpRequest;i.open(\"GET\",e,true);i.responseType=\"blob\";i.onerror=function(e){console.log(e)};i.onload=function(e){if(this.readyState===4&&this.status===200){var i=this.response;t(window.URL.createObjectURL(i))}};try{i.send()}catch(r){console.log(r)}};utils.parseJSON=function(e,t){try{return JSON.parse(e)}catch(i){return t}};utils.writeFieldData=function(e,t,i,r){if(typeof i!==\"object\"){return}r=parseInt(r);r=r>0&&t===\"text\"?r:0;utils.setField(e,t,JSON.stringify(i,null,r))};utils.getPrettyFilter=function(e){e=e.trim().replace(\"][\",\"] [\");var t=/[\\+\\-]?\\[.+?[\\]\\}\\>]\\]/g;var i=e.match(t);e=e.replace(t,\" [] \").trim();var r=e.split(/\\s+/);var n=0;var l=[];for(var u=0;u<r.length;u++){l[u]=r[u]===\"[]\"?i[n++]:r[u]}return l.join(\"\\n\")};utils.setField=function(e,t,i){if(!e||!t)return;var r=utils.getTiddlerRef(e);var n={title:r};n[t]=i;var l=$tw.wiki.getTiddler(r,true);if(t!==\"text\"&&l&&!l.fields.text){n.text=\"\"}var l=new $tw.Tiddler(l,n);$tw.wiki.addTiddler(l);return l};utils.clone=function(e,t){utils.setField(e,\"title\",t)};utils.setEntry=function(e,t,i){$tw.wiki.setText(utils.getTiddlerRef(e),null,t,i)};utils.getEntry=function(e,t,i){var r=$tw.wiki.getTiddlerData(utils.getTiddlerRef(e),{});return r[t]==null?i:r[t]};utils.isLeftVersionGreater=function(e,t){return e!==t&&$tw.utils.checkVersions(e,t)};utils.getField=function(e,t,i){var r=utils.getTiddler(e);return!r?i||\"\":r.fields[t]||i||\"\"};utils.getText=function(e,t){return utils.getField(e,\"text\",t)};utils.setText=function(e,t){utils.setField(e,\"text\",t)};utils.getFirstElementByClassName=function(e,t,i){var r=(t||document).getElementsByClassName(e)[0];if(!r&&(typeof i===\"boolean\"?i:true)){var n=\"Missing element with class \"+e+\" inside \"+t;throw new utils.exception.EnvironmentError(n)}return r};utils.isDraft=function(e){var t=utils.getTiddler(e);return t&&t.isDraft()};utils.getRandomInt=function(e,t){return Math.floor(Math.random()*(t-e)+e)};utils.pickRandom=function(e){return e[utils.getRandomInt(0,e.length-1)]};utils.getRandomLabel=function(e){e=e||{};var t=[\"exciting\",\"notable\",\"epic\",\"new\",\"fancy\",\"great\",\"cool\",\"fresh\",\"funky\",\"clever\"];var i=[\"concept\",\"idea\",\"thought\",\"topic\",\"subject\"];return\"My\"+\" \"+utils.pickRandom(t)+\" \"+(e.object||utils.pickRandom(i))+(e.plural?\"s\":\"\")};utils.merge=function(){var e=function(t,i){if(typeof t!==\"object\"){t={}}for(var r in i){if(i.hasOwnProperty(r)){if(i[r]!=null){t[r]=typeof i[r]===\"object\"?e(t[r],i[r]):i[r]}}}return t};return function(t){for(var i=1,r=arguments.length;i<r;i++){var n=arguments[i];if(n!=null&&typeof n===\"object\"){t=e(t,n)}}return t}}();utils.drawRaster=function(e,t,i,r,n){var r=parseInt(r)||10;var l=e.canvas;var u=l.width/t;var s=l.width/t;var a=i.x-u/2;var f=i.y-s/2;for(var o=a;o<u;o+=r){e.moveTo(o,f);e.lineTo(o,s)}for(var d=f;d<s;d+=r){e.moveTo(a,d);e.lineTo(u,d)}e.strokeStyle=n||\"#D9D9D9\";e.stroke()};utils.isSystemOrDraft=function(e){if($tw.wiki.isSystemTiddler(utils.getTiddlerRef(e))){return true}var t=utils.getTiddler(e);return t&&t.isDraft()};utils.getMergedTiddlers=function(e,t){if(!Array.isArray(e))return;for(var i=e.length;i--;){e[i]=utils.getTiddler(e[i])}if(!e.length)return;e.push({title:t||e[0].fields.title},$tw.wiki.getModificationFields(),$tw.wiki.getCreationFields());e.unshift(null);return new(Function.prototype.bind.apply($tw.Tiddler,e))};utils.getChildWidgetByProperty=function(e,t,i){var r=e.children;for(var n=r.length;n--;){var l=r[n];if(l[t]===i){return l}else{l=utils.getChildWidgetByProperty(l,t,i);if(l){return l}}}};utils.setDomListeners=function(e,t,i,r){r=typeof r===\"boolean\"?r:false;e=e+\"EventListener\";for(var n in i){var l=i[n];if(typeof l===\"function\"){t[e](n,l,r)}else{t[e](n,l[0],typeof l[1]===\"boolean\"?l[1]:r)}}};utils.removeArrayElement=function(e,t){var i=e.indexOf(t);if(i>-1){return e.splice(i,1)[0]}};utils.removeDOMChildNodes=function(e){for(var t=e.childNodes.length;t--;){e.removeChild(e.childNodes[t])}};utils.addTWlisteners=function(e,t,i){for(var r in e){t.addEventListener(r,e[r].bind(i))}};utils.bind=function(e,t){if(typeof t===\"string\"){t=[t]}else{for(var i=t.length;i--;){var r=e[t[i]];if(typeof r===\"function\"){e[t[i]]=r.bind(e)}}}};utils.mv=function(e,t,i,r){if(e===t||!e||!t)return;i=typeof i===\"boolean\"?i:false;r=typeof r===\"boolean\"?r:true;var n=utils.getTiddlersByPrefix(e);var l=utils.makeHashMap();for(var u=n.length;u--;){var s=n[u];var a=s.replace(e,t);if($tw.wiki.tiddlerExists(a)&&!i){return}l[s]=a}for(var s in l){utils.setField(s,\"title\",l[s]);if(r)$tw.wiki.deleteTiddler(s)}return l};utils.cp=function(e,t,i){return utils.mv(e,t,i,false)};utils.inArray=function(e,t){return t.indexOf(e)!==-1};utils.hasSubString=function(e,t){return e.indexOf(t)!==-1};utils.joinAndWrap=function(e,t,i,r){if(!r)r=\" \";return t+e.join(i+r+t)+i};utils.keysOfItemsWithProperty=function(e,t,i,r){e=utils.getIterableCollection(e);var n=Object.keys(e);var l=[];var r=typeof r===\"number\"?r:n.length;for(var u=0,s=n.length;u<s;u++){var a=n[u];if(typeof e[a]===\"object\"&&e[a][t]){if(!i||e[a][t]===i){l.push(a);if(l.length===r){break}}}}return l};utils.keyOfItemWithProperty=function(e,t,i){var r=utils.keysOfItemsWithProperty(e,t,i,1);return r.length?r[0]:undefined};utils.deleteByPrefix=function(e,t){if(!e)return;t=t||$tw.wiki.allTitles();var i=[];for(var r=t.length;r--;){if(utils.startsWith(t[r],e)){$tw.wiki.deleteTiddler(t[r]);i.push(i[r])}}return i};utils.getIterableCollection=function(e){return e instanceof vis.DataSet?e.get():e};utils.getLookupTable=function(e,t){e=utils.getIterableCollection(e);var i=utils.makeHashMap();var r=Object.keys(e);for(var n=0,l=r.length;n<l;n++){var u=r[n];var s=t?e[u][t]:e[u];var a=typeof s;if(a===\"string\"&&s!==\"\"||a===\"number\"){if(!i[s]){i[s]=t?e[u]:true;continue}}throw'TiddlyMap: Cannot use \"'+ltIndex+'\" as lookup table index'}return i};utils.getWithoutNewLines=function(e){if(typeof e===\"string\"){return e.replace(/[\\n\\r]/g,\" \")}};utils.getArrayValuesAsHashmapKeys=function(e){return utils.getLookupTable(e)};utils.getTiddlersWithField=function(e,t,i){if(!i||typeof i!==\"object\")i={};var r=i.tiddlers||$tw.wiki.allTitles();var n=i.limit||0;var l=i.isIncludeDrafts===true;var u=utils.makeHashMap();var s=Object.keys(r);var a=$tw.utils.hop;for(var f=s.length;f--;){var o=utils.getTiddler(r[s[f]]);var d=o.fields;if(a(d,e)&&(!a(d,\"draft.of\")||l)){if(!t||d[e]===t){u[d.title]=o;if(--n===0)break}}}return u};utils.getTiddlerWithField=function(e,t){var i=utils.getTiddlersWithField(e,t,{limit:1});return Object.keys(i)[0]};utils.getTiddlersByPrefix=function(e,t){t=t||{};var i=t.removePrefix===true;var r=[];$tw.wiki[t.iterator||\"each\"](function(t,n){if(utils.startsWith(n,e)){r.push(i?utils.getWithoutPrefix(n,e):n)}});return r};utils.addTiddler=function(e,t){var i=utils.getTiddler(e);if(!t&&i)return i;i=new $tw.Tiddler({title:e,text:\"\"},$tw.wiki.getModificationFields(),$tw.wiki.getCreationFields());$tw.wiki.addTiddler(i);return i};utils.getSnapshotTitle=function(e,t){return\"Snapshot – \"+e+\" (\"+(new Date).toDateString()+\")\"+\".\"+(t||\"png\")};utils.exception=exception;utils.URL=URL;utils.makeDraftTiddler=function(e){var t=$tw.wiki.findDraft(e);if(t){return $tw.wiki.getTiddler(t)}var i=$tw.wiki.getTiddler(e);t=utils.generateDraftTitle(e);var r=new $tw.Tiddler(i,{title:t,\"draft.title\":e,\"draft.of\":e},$tw.wiki.getModificationFields());$tw.wiki.addTiddler(r);return r};utils.generateDraftTitle=function(e){var t=0,i;do{i=\"Draft \"+(t?t+1+\" \":\"\")+\"of '\"+e+\"'\";t++}while($tw.wiki.tiddlerExists(i));return i};utils.touch=function(e){utils.setField(e,\"modified\",new Date)};utils.getFullScreenApis=function(){var e=document,t=e.body,i={_requestFullscreen:t.webkitRequestFullscreen!==undefined?\"webkitRequestFullscreen\":t.mozRequestFullScreen!==undefined?\"mozRequestFullScreen\":t.msRequestFullscreen!==undefined?\"msRequestFullscreen\":t.requestFullscreen!==undefined?\"requestFullscreen\":\"\",_exitFullscreen:e.webkitExitFullscreen!==undefined?\"webkitExitFullscreen\":e.mozCancelFullScreen!==undefined?\"mozCancelFullScreen\":e.msExitFullscreen!==undefined?\"msExitFullscreen\":e.exitFullscreen!==undefined?\"exitFullscreen\":\"\",_fullscreenElement:e.webkitFullscreenElement!==undefined?\"webkitFullscreenElement\":e.mozFullScreenElement!==undefined?\"mozFullScreenElement\":e.msFullscreenElement!==undefined?\"msFullscreenElement\":e.fullscreenElement!==undefined?\"fullscreenElement\":\"\",_fullscreenChange:e.webkitFullscreenElement!==undefined?\"webkitfullscreenchange\":e.mozFullScreenElement!==undefined?\"mozfullscreenchange\":e.msFullscreenElement!==undefined?\"MSFullscreenChange\":e.fullscreenElement!==undefined?\"fullscreenchange\":\"\"};if(!i._requestFullscreen||!i._exitFullscreen||!i._fullscreenElement){return null}else{return i}};utils.flatten=function(e,t){t=t||{};var i=t.delimiter||\".\";var r=t.prefix||\"\";var n={};function l(e,u){Object.keys(e).forEach(function(s){var a=e[s];var f=t.safe&&Array.isArray(a);var o=Object.prototype.toString.call(a);var d=o===\"[object Object]\"||o===\"[object Array]\";var c=u?u+i+s:r+s;if(!f&&d){return l(a,c)}n[c]=a})}l(e);return n};utils.unflatten=function(e,t){t=t||{};var i=t.delimiter||\".\";var r={};if(Object.prototype.toString.call(e)!==\"[object Object]\"){return e}function n(e){var t=Number(e);return isNaN(t)||e.indexOf(\".\")!==-1?e:t}Object.keys(e).forEach(function(l){var u=l.split(i);var s=n(u.shift());var a=n(u[0]);var f=r;while(a!==undefined){if(f[s]===undefined){f[s]=typeof a===\"number\"&&!t.object?[]:{}}f=f[s];if(u.length>0){s=n(u.shift());a=n(u[0])}}f[s]=utils.unflatten(e[l],t)});return r};utils.genUUID=function(){var e=\"0123456789abcdefghijklmnopqrstuvwxyz\".split(\"\");return function(){var t=e,i=new Array(36);var r=0,n;for(var l=0;l<36;l++){if(l==8||l==13||l==18||l==23){i[l]=\"-\"}else if(l==14){i[l]=\"4\"}else{if(r<=2)r=33554432+Math.random()*16777216|0;n=r&15;r=r>>4;i[l]=t[l==19?n&3|8:n]}}return i.join(\"\")}}();",
"title": "$:/plugins/felixhayashi/tiddlymap/js/utils",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports=ViewAbstraction;var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function ViewAbstraction(t,e){e=e||{};this._edgeTypePath=$tm.path.edgeTypes;if(t instanceof ViewAbstraction){return t}this._registerPaths(t,e.isCreate);if(e.isCreate){this._createView(e)}else if(!this.exists()){return{exists:function(){return false}}}this.rebuildCache()}ViewAbstraction.prototype._noNeedToRebuildCache=false;ViewAbstraction.prototype._registerPaths=function(t,e){this.comp=this.comp||utils.makeHashMap();this.comp.config=this._getConfigPath(t,e);this.comp.map=this.comp.config+\"/map\";this.comp.nodeFilter=this.comp.config+\"/filter/nodes\";this.comp.edgeTypeFilter=this.comp.config+\"/filter/edges\"};ViewAbstraction.prototype._getConfigPath=function(t,e){if(t instanceof $tw.Tiddler){return t.fields.title}if(typeof t===\"string\"){t=utils.getWithoutPrefix(t,$tm.path.views+\"/\");if(t&&!utils.hasSubString(t,\"/\")){return $tm.path.views+\"/\"+t}}if(e){var i=$tm.path.views+\"/\"+utils.getRandomLabel({plural:true});return $tw.wiki.generateNewTitle(i)}};ViewAbstraction.prototype.getPaths=function(){return this.comp};ViewAbstraction.prototype._createView=function(t){if(this.exists()){if(!t.isForce)return;this.destroy()}var e=new ViewAbstraction(t.protoView);if(e.exists()){var i=utils.cp(e.getRoot(),this.comp.config,true)}var r={};r.title=this.comp.config;if(!t.isHidden){r[$tm.field.viewMarker]=true}r.id=utils.genUUID();$tw.wiki.addTiddler(new $tw.Tiddler(utils.getTiddler(this.comp.config),r));this.setEdgeTypeFilter($tm.filter.defaultEdgeTypeFilter)};ViewAbstraction.prototype.isLocked=function(){return $tw.wiki.isShadowTiddler(this.comp.config)};ViewAbstraction.prototype.update=function(t){var e=t.changedTiddlers;if(t[$tm.path.edgeTypes]||utils.hasKeyWithPrefix(e,this.comp.config)){this.rebuildCache();return true}};ViewAbstraction.prototype.rebuildCache=function(t){if(!t&&this._noNeedToRebuildCache){this._noNeedToRebuildCache=false;return}this.config=this.getConfig(null,true);this.nodeData=this.getNodeData(null,true);this.nodeFilter=this.getNodeFilter(null,true);this.edgeTypeFilter=this.getEdgeTypeFilter(null,true)};ViewAbstraction.prototype.addPlaceholder=function(t){utils.cp(t,this.getRoot()+\"/snapshot\",true)};ViewAbstraction.prototype.exists=function(){return utils.tiddlerExists(this.comp.config)};ViewAbstraction.prototype.getRoot=function(){return this.comp.config};ViewAbstraction.prototype.getCreationDate=function(t){var e=$tw.wiki.getTiddler(this.comp.config).fields[\"created\"];if(t){return e instanceof Date?$tw.utils.formatDateString(e,\"DDth MMM YYYY\"):\"\"}return e};ViewAbstraction.prototype.getLabel=function(){return utils.getBasename(this.comp.config)};ViewAbstraction.prototype.destroy=function(){var t=\"[prefix[\"+this.getRoot()+\"]]\";utils.deleteTiddlers(utils.getMatches(t))};ViewAbstraction.prototype.getOccurrences=function(){var t=\"[regexp:text[<\\\\$(tiddlymap|tmap).*?view=.\"+this.getLabel()+\"..*?>]]\";return utils.getMatches(t)};ViewAbstraction.prototype.rename=function(t){if(typeof t!==\"string\")return false;if(utils.inArray(\"/\",t)){$tm.notify('A view name must not contain any \"/\"');return false}var e=this.getLabel();var i=$tm.path.views+\"/\"+t;var r=this.getRoot();var o=utils.mv(r,i,true);if($tm.config.sys.defaultView===e){utils.setEntry($tm.ref.sysUserConf,\"defaultView\",t)}if($tm.config.sys.liveTab.fallbackView===e){utils.setEntry($tm.ref.sysUserConf,\"liveTab.fallbackView\",t)}$tw.wiki.each(function(i,r){if(i.fields[\"tmap.open-view\"]===e){utils.setField(r,\"tmap.open-view\",t)}else if(utils.startsWith(r,$tm.path.views)){var o=new ViewAbstraction(r);if(!o.exists())return;var s=o.getNodeData();for(var n in s){if(s[n][\"open-view\"]===e){s[n][\"open-view\"]=t}}o.saveNodeData(s)}});this._registerPaths(t);this.rebuildCache()};ViewAbstraction.prototype.isEnabled=function(t){return utils.isTrue(this.getConfig(t),false)};ViewAbstraction.prototype.getConfig=function(t,e,i){if(!e&&this.config){var r=this.config}else{var o=$tw.wiki.getTiddler(this.comp.config).fields;var r=utils.getPropertiesByPrefix(o,\"config.\")}return t?r[utils.startsWith(t,\"config.\")?t:\"config.\"+t]:r};ViewAbstraction.prototype.getHierarchyEdgeTypes=function(){if(this.getConfig(\"layout.active\")!==\"hierarchical\")return[];var t=utils.getPropertiesByPrefix(this.getConfig(),\"config.layout.hierarchical.order-by-\",true);var e=utils.makeHashMap();for(var i in t){if(t[i]===\"true\"){var r=utils.getTiddler($tm.indeces.tById[i]);if(r){e[utils.getBasename(r.fields.title)]=true}}}return e};ViewAbstraction.prototype.setConfig=function(){var t=arguments;if(t[0]==null)return;if(t.length===1&&typeof t[0]===\"object\"){for(var e in t[0]){this.setConfig(e,t[0][e])}}else if(t.length===2&&typeof t[0]===\"string\"){var e=utils.getWithoutPrefix(t[0],\"config.\");var i=t[1];if(i===undefined)return;if(i===null){$tm.logger(\"debug\",\"Removing config\",e);delete this.config[\"config.\"+e]}else{if(e===\"edge_type_namespace\"){var r=i.match(/[^:]+/);i=r?r[0]:\"\"}}$tm.logger(\"log\",\"Setting config\",e,i);this.config[\"config.\"+e]=i}else{return}$tw.wiki.addTiddler(new $tw.Tiddler($tw.wiki.getTiddler(this.comp.config),this.config));this._noNeedToRebuildCache=true};ViewAbstraction.prototype.isExplicitNode=function(t){var e=$tw.utils.escapeRegExp(this._getAddNodeFilterPart(t));return this.getNodeFilter(\"raw\").match(e)};ViewAbstraction.prototype.isLiveView=function(){return this.getLabel()===$tm.misc.liveViewLabel};ViewAbstraction.prototype._getAddNodeFilterPart=function(t){if(!t){throw\"Supplied param is not a node!\"}var e=typeof t===\"object\"?t.id:t;return\"[field:tmap.id[\"+e+\"]]\"};ViewAbstraction.prototype.setNodeFilter=function(t,e){t=t.replace(/[\\n\\r]/g,\" \");if(this.getNodeFilter(\"raw\")===t){return}if(this.isLiveView()&&!e){var i=\"You must not change the live view's node filter!\";$tm.notify(i);return}utils.setField(this.comp.nodeFilter,\"filter\",t);$tm.logger(\"debug\",\"Node filter set to\",t);this.nodeFilter=this.getNodeFilter(null,true);this._noNeedToRebuildCache=true};ViewAbstraction.prototype.setEdgeTypeFilter=function(t){t=t.replace(/[\\n\\r]/g,\" \");if(this.getEdgeTypeFilter(\"raw\")===t){return}utils.setField(this.comp.edgeTypeFilter,\"filter\",t);$tm.logger(\"debug\",\"Edge filter set to\",t);this.edgeTypeFilter=this.getEdgeTypeFilter(null,true);this._noNeedToRebuildCache=true};ViewAbstraction.prototype.addNode=function(t){if(this.isExplicitNode(t))return false;var e=this._getAddNodeFilterPart(t);this.setNodeFilter(this.getNodeFilter(\"raw\")+\" \"+e);this.saveNodePosition(t)};ViewAbstraction.prototype.removeNode=function(t){if(!this.isExplicitNode(t))return false;var e=this._getAddNodeFilterPart(t);var i=this.getNodeFilter(\"raw\").replace(e,\"\");this.setNodeFilter(i);return true};ViewAbstraction.prototype.getEdgeTypeFilter=function(t,e){if(!e&&this.edgeTypeFilter){var i=this.edgeTypeFilter}else{var i=utils.makeHashMap();var r=$tm.indeces.allETy;var o=Object.keys(r);var s=$tw.wiki.getTiddler(this.comp.edgeTypeFilter);i.raw=s&&s.fields.filter||\"\";i.pretty=utils.getPrettyFilter(i.raw);i.matches=utils.getEdgeTypeMatches(i.raw,r);i.whitelist=utils.getLookupTable(i.matches)}return t?i[t]:i};ViewAbstraction.prototype.isEdgeTypeVisible=function(t){var e={namespace:this.getConfig(\"edge_type_namespace\")};var t=new EdgeType(t,null,e);return utils.isEdgeTypeMatch(t.id,this.edgeTypeFilter.raw)};ViewAbstraction.prototype.getNodeFilter=function(t,e){if(!e&&this.nodeFilter){var i=this.nodeFilter}else{var i=utils.makeHashMap();var r=$tw.wiki.getTiddler(this.comp.nodeFilter);i.raw=r&&r.fields.filter||\"\";i.pretty=utils.getPrettyFilter(i.raw);i.compiled=$tw.wiki.compileFilter(i.raw)}return t?i[t]:i};ViewAbstraction.prototype.getNodeData=function(t,e){var i=!e&&this.nodeData?this.nodeData:utils.parseFieldData(this.comp.map,\"text\",{});return t?i[t]:i};ViewAbstraction.prototype.equals=function(t){if(t===this)return true;var t=new ViewAbstraction(t);return t.exists()&&this.getRoot()===t.getRoot()};ViewAbstraction.prototype.saveNodeData=function(){var t=arguments;var e=this.getNodeData();if(t.length===2){if(typeof t[1]===\"object\"){if(t[1]===null){e[t[0]]=undefined}else{e[t[0]]=$tw.utils.extend(e[t[0]]||{},t[1])}}}else if(t.length===1&&typeof t[0]===\"object\"){$tm.logger(\"log\",\"Storing data in\",this.comp.map);$tw.utils.extend(e,t[0])}else{return}utils.writeFieldData(this.comp.map,\"text\",e,$tm.config.sys.jsonIndentation);this.nodeData=e;this._noNeedToRebuildCache=true};ViewAbstraction.prototype.saveNodePosition=function(t){if(t.id&&t.x&&t.y){this.saveNodeData(t.id,{x:t.x,y:t.y})}};ViewAbstraction.prototype.setCentralTopic=function(t){this.setConfig(\"central-topic\",t)};ViewAbstraction.prototype.saveNodeStyle=function(t,e){var i=this.getNodeData()[t];if(i){for(var r in i){if(r!==\"x\"&&r!==\"y\")i[r]=undefined}}this.saveNodeData(t,e)};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/config/vis": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/config/vis\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n\"use strict\";module.exports={locale:\"en_EN\",clickToUse:false,autoResize:false,height:\"100%\",width:\"100%\",configure:{enabled:false},interaction:{dragNodes:true,dragView:true,hideEdgesOnDrag:false,hideNodesOnDrag:false,hover:true,navigationButtons:true,multiselect:true,selectable:true,selectConnectedEdges:true,tooltipDelay:600,zoomView:false,keyboard:{enabled:false,speed:{x:10,y:10,zoom:.02},bindToWindow:false}},manipulation:{initiallyActive:true},nodes:{shape:\"box\",shadow:{enabled:false},color:{border:\"#2B7CE9\",background:\"#97C2FC\"}},edges:{smooth:{enabled:true},color:{color:\"#848484\",inherit:false},arrows:{to:{enabled:true}}},physics:{forceAtlas2Based:{gravitationalConstant:-300,springLength:0,springConstant:.2,centralGravity:.015,damping:.4},solver:\"forceAtlas2Based\",stabilization:{enabled:true,iterations:1e3,updateInterval:10,onlyDynamicEdges:false,fit:false}}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/config/vis",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/tiddlymap/js/macro/tmap": {
"text": "/*\\\ntitle: $:/plugins/felixhayashi/tiddlymap/js/macro/tmap\ntype: application/javascript\nmodule-type: macro\n\n@preserve\n\n\\*/\n\"use strict\";exports.name=\"tmap\";exports.params=getParamSlots(5);exports.run=run;var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");function run(){this.substVarRefs=this.substituteVariableReferences;var r=command[arguments[0]];var t=null;if(typeof r===\"function\"){var e=Array.prototype.slice.call(arguments,1);var t=r.apply(this,e)}return typeof t===\"string\"?t:\"\"}function getParamSlots(r){var t=[];for(var e=0;e<r;e++){t.push({name:\"arg\"+e})}return t}var command=utils.makeHashMap();command.basename=function(r){var t=r||this.getVariable(\"currentTiddler\");return utils.getBasename(t)};command.datauri=function(r,t){return utils.getDataUri(r,t,true)};command.testJSON=function(r){var t=$tw.wiki.getTiddler(this.getVariable(\"currentTiddler\"));try{JSON.parse(t.fields[r]);return\"valid\"}catch(e){return\"malformed\"}};command.splitAndSelect=function(r,t){var e=this.getVariable(\"currentTiddler\");var a=e.split(r)[t];return a!=null?a:e};command.concat=function(){var r=\"\";for(var t=1,e=arguments.length;t<e;t++){r+=arguments[t]}return r};command.uuid=function(){return utils.genUUID()};command.regRepl=function(){var r=this.substVarRefs(arguments[0]);var t=arguments[1];var e=this.substVarRefs(arguments[2]);var a=this.substVarRefs(arguments[4]);return r.replace(new RegExp(t,a),e)};command.halfOfString=function(){var r=this.substVarRefs(arguments[0]);if(!r)return\"\";return r.substr(0,Math.ceil(r.length/2))};command.isETyVisible=function(r,t,e){e=command.getETyId.call(this,r,e);return\"\"+utils.isEdgeTypeMatch(e,t)};command.getETyId=function(r,t){t=t||this.getVariable(\"currentTiddler\");return new EdgeType(t,null,{namespace:r}).id};command.scale=function(){var r=\"\";for(var t=1,e=parseInt(arguments[0]);t<e;t++){r+=\"[[\"+t+\"]]\"}return r};command.mergeFields=function(){var r=utils.getTiddler(arguments[0]);var t=arguments[1];var e=arguments[2]||\" \";if(!r)return;var a=utils.getPropertiesByPrefix(r.fields,t);var n=\"\";for(var i in a){if(typeof a[i]===\"string\"){n+=a[i]+e}}return n};command.option=function(r,t){var e=$tm;var a=r.split(\".\");for(var n=0;n<a.length;n++){if(typeof e==\"object\"&&e[a[n]]){e=e[a[n]]}}if(t&&typeof e===\"string\"&&utils.hasSubString(t)&&e.lastIndexOf(t)+t.length===e.length){e=e+t}return e};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/macro/tmap",
"type": "application/javascript",
"module-type": "macro"
},
"$:/plugins/felixhayashi/tiddlymap/js/startup/caretaker": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/startup/caretaker\ntype: application/javascript\nmodule-type: startup\n\n@preserve\n\n\\*/\n\"use strict\";exports.name=\"tmap.caretaker\";exports.platforms=[\"browser\"];exports.after=[\"startup\",\"tmap.environment\"];exports.before=[\"rootwidget\"];exports.synchronous=true;exports.startup=startup;var visConfig=require(\"$:/plugins/felixhayashi/tiddlymap/js/config/vis\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var fixer=require(\"$:/plugins/felixhayashi/tiddlymap/js/fixer\");var Adapter=require(\"$:/plugins/felixhayashi/tiddlymap/js/Adapter\");var DialogManager=require(\"$:/plugins/felixhayashi/tiddlymap/js/DialogManager\");var CallbackManager=require(\"$:/plugins/felixhayashi/tiddlymap/js/CallbackManager\");var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var NodeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/NodeType\");var vis=require(\"$:/plugins/felixhayashi/vis/vis.js\");function startup(){$tm.utils=utils;$tm.keycharm=vis.keycharm;$tm.NodeType=NodeType;$tm.EdgeType=EdgeType;$tm.ViewAbstraction=ViewAbstraction;$tm.url=new $tm.utils.URL(window.location.href);updateGlobals();createMetaFile();cleanup();attachIndeces($tm);$tm.updateTree=updateTree;setDefaults();$tm.adapter=new Adapter;fixer.fix();$tm.callbackManager=new CallbackManager;$tm.dialogManager=new DialogManager($tm.callbackManager);$tm.registry=[];window.setInterval(routineCheck,5e3);registerChangeListener($tm.callbackManager);registerMousemoveListener();registerClickListener();maybePrepareForFullscreenStart($tm.url);$tm.logger(\"warn\",\"TiddlyMap's caretaker successfully started\")}var attachOptions=function(e){var t=e;if(!t.config)t.config=utils.makeHashMap();t.config.sys=utils.merge(t.config.sys,utils.unflatten($tw.wiki.getTiddlerData(t.ref.sysUserConf)));t.config.vis=utils.merge({},visConfig,utils.parseFieldData(t.ref.visUserConf));if(!t.field)t.field=utils.makeHashMap();$tw.utils.extend(t.field,t.config.sys.field)};var attachIndeces=function(e){$tm.start(\"Attaching Indeces\");if(!e.indeces){e.indeces={};var t=$tm.path.pluginRoot;e.indeces.tmapTiddlers=$tw.wiki.getPluginInfo(t).tiddlers}var i=$tw.wiki.allTitles();updateTiddlerVsIdIndeces(e.indeces,i);updateNodeTypesIndeces(e.indeces);updateEdgeTypesIndeces(e.indeces);$tm.stop(\"Attaching Indeces\")};var updateTiddlerVsIdIndeces=function(e,t){e=e||$tm.indeces;t=t||$tw.wiki.allTitles();fixer.fixId();var i=e.tById={};var a=e.idByT={};$tw.wiki.each(function(e,t){if(utils.isSystemOrDraft(e))return;var r=e.fields[\"tmap.id\"];if(!r){r=utils.genUUID();utils.setField(e,\"tmap.id\",r)}i[r]=t;a[t]=r})};var updateNodeTypesIndeces=function(e){e=e||$tm.indeces;var t=$tm.path.nodeTypes;var i=e.glNTy=[];var a=e.glNTyById=utils.makeHashMap();$tw.wiki.eachTiddlerPlusShadows(function(e,r){if(utils.startsWith(r,t)){var s=new NodeType(r);a[s.id]=s;i.push(s)}});i.sort(function(e,t){return e.priority-t.priority})};var updateEdgeTypesIndeces=function(e){e=e||$tm.indeces;var t=$tm.path.edgeTypes;var i=e.allETy=utils.makeHashMap();var a=e.maETyFiNa=utils.makeHashMap();var r=utils.getLookupTable($tm.misc.magicETyNamespaces);$tw.wiki.eachTiddlerPlusShadows(function(e,s){if(utils.startsWith(s,t)){var n=new EdgeType(s);i[n.id]=n;if(r[n.namespace]){a[n.name]=n}}})};var updateAdjacencyList=function(e){};var attachFunctions=function(e){var t=e;var i=function(){};if(utils.isTrue($tm.config.sys.debug,false)&&console){t.logger=function(){if(arguments.length<2)return;var e=Array.prototype.slice.call(arguments);var t=e.shift(e);var i=console.hasOwnProperty(t)?t:\"debug\";console[i].apply(console,e)};t.start=function(e){console.time(\"[timer] \"+e)};t.stop=function(e){console.timeEnd(\"[timer] \"+e)}}else{t.logger=t.start=t.stop=i}t.notify=utils.isTrue($tm.config.sys.notifications)?utils.notify:i};var routineCheck=function(){for(var e=$tm.registry.length;e--;){var t=$tm.registry[e];if(!t.destruct||!t.isZombieWidget)return;if(t.isZombieWidget()){$tm.logger(\"warn\",\"a widget will be removed\");$tm.registry.splice(e,1);t.destruct()}}};var dispatchUpdates=function(e){var t=$tm.registry;for(var i=t.length;i--;){var a=t[i];if(!a.destruct||!a.isZombieWidget)return;if(a.update&&!a.isZombieWidget()){a.update(e)}}};var checkForDublicates=function(e){var t=e.fields[\"tmap.id\"];if(!t)return;var i=$tm;var a=utils.getTiddlersWithField(\"tmap.id\",t,{limit:2});delete a[e.fields.title];var r=Object.keys(a)[0];if(r){var s={param:{changedTiddler:e.fields.title,existingTiddler:r,id:t}};$tm.dialogManager.open(\"dublicateIdInfo\",s)}if(r){utils.setField(e,\"tmap.edges\",undefined);$tm.adapter.assignId(e,true)}};var updateGlobals=function(e){attachOptions($tm);attachFunctions($tm);$tm.logger(\"warn\",\"Rebuilt globals\")};var lastCurrentTiddler=null;var updateLiveViewTrigger=function(e){if(e[\"$:/HistoryList\"]){var t=utils.getField(\"$:/HistoryList\",\"current-tiddler\")}else if(e[\"$:/temp/focussedTiddler\"]){var t=utils.getField(\"$:/temp/focussedTiddler\",\"text\")}if(t!=null&&lastCurrentTiddler!==t){lastCurrentTiddler=t;utils.setField(\"$:/temp/tmap/currentTiddler\",\"text\",t)}};var printChanges=function(e,t){if(!utils.isTrue($tm.config.sys.debug,false))return;$tm.logger(\"warn\",\"=== Refresh \"+t+\" ===\");for(var i in e){var a=e[i].deleted?\"[Deleted]\":\"[Modified]\";$tm.logger(\"warn\",a,i,$tw.wiki.getTiddler(i))}};var registerMousemoveListener=function(){$tm.mouse={};var e=function(e){$tm.mouse=e};window.addEventListener(\"mousemove\",e,false)};var registerClickListener=function(){var e=$tm.path.tempPopups;window.addEventListener(\"click\",function(t){var i=utils.getTiddlersByPrefix(e);for(var a=i.length;a--;){if(utils.getText(i[a]))break}if(a===-1)return;if(!$tw.utils.hasClass(t.target,\"tc-drop-down\")&&!utils.getAncestorWithClass(t.target,\"tc-drop-down\")){for(var a=i.length;a--;){utils.setText(i[a],\"\")}}},false)};var updateTree=function(){updateGlobals();updateNodeTypesIndeces();updateEdgeTypesIndeces()};var registerChangeListener=function(e){var t=0;var i={};i[$tm.path.options]=updateGlobals;i[$tm.path.nodeTypes]=updateNodeTypesIndeces;i[$tm.path.edgeTypes]=updateEdgeTypesIndeces;$tw.wiki.addEventListener(\"change\",function(a){$tm.start(\"Caretaker handling changes\");printChanges(a,t++);e.handleChanges(a);var r={changedTiddlers:a};for(var s in a){var n=utils.getTiddler(s);if(n&&n.isDraft())continue;if($tw.wiki.isSystemTiddler(s)){handleSysTidChanges(s,n,r,i)}else{handleTidChanges(s,n,r)}}dispatchUpdates(r);updateLiveViewTrigger(a);$tm.stop(\"Caretaker handling changes\")})};var handleSysTidChanges=function(e,t,i,a){var r=$tm.path;for(var s in a){if(utils.startsWith(e,s)&&!i[s]){$tm.logger(\"warn\",\"[System change]\",s);a[s]();i[s]=true;return}}};var handleTidChanges=function(e,t,i){if(t){checkForDublicates(t);$tm.adapter.assignId(t)}else{var a=$tm.indeces.idByT[e];if(!a)return;var r=utils.getTiddlerWithField(\"tmap.id\",a);if(r){$tm.logger(\"warn\",\"[Renamed]\",e,\"into\",r)}else{$tm.adapter.deleteNode(a)}}};var cleanup=function(){utils.deleteByPrefix(\"$:/temp/felixhayashi\");utils.deleteByPrefix(\"$:/temp/tiddlymap\");utils.deleteByPrefix(\"$:/temp/tmap\")};var setDefaults=function(){var e=$tm.config.sys.defaultView;if(!e)return;utils.setField($tm.ref.defaultViewHolder,\"text\",e)};var maybePrepareForFullscreenStart=function(e){if(!e.query[\"tmap-enlarged\"])return;var t=$tm.ref;var i=utils.getTiddlersByPrefix(\"$:/state/tab/sidebar-\")[0];utils.setText(i,t.mainEditor);var a=new ViewAbstraction(e.query[\"tmap-view\"]);if(a.exists()){utils.setField(t.defaultViewHolder,\"text\",a.getLabel())}};var createMetaFile=function(){if(utils.tiddlerExists($tm.ref.sysMeta))return;$tm.logger(\"warn\",\"Creating meta file\");var e=$tw.wiki.getTiddler($tm.path.pluginRoot);$tw.wiki.setTiddlerData($tm.ref.sysMeta,{originalVersion:e.fields.version,dataStructureState:\"0.6.9\",showWelcomeMessage:true})};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/startup/caretaker",
"type": "application/javascript",
"module-type": "startup"
},
"$:/plugins/felixhayashi/tiddlymap/js/startup/environment": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/startup/environment\ntype: application/javascript\nmodule-type: startup\n\n@preserve\n\n\\*/\n\"use strict\";exports.name=\"tmap.environment\";exports.platforms=[\"browser\"];exports.after=[\"startup\"];exports.before=[\"tmap.caretaker\"];exports.synchronous=true;exports.startup=run;function run(e){window.$tm={};$tm.path={pluginRoot:\"$:/plugins/felixhayashi/tiddlymap\",edgeTypes:\"$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes\",nodeTypes:\"$:/plugins/felixhayashi/tiddlymap/graph/nodeTypes\",views:\"$:/plugins/felixhayashi/tiddlymap/graph/views\",options:\"$:/plugins/felixhayashi/tiddlymap/config\",dialogs:\"$:/plugins/felixhayashi/tiddlymap/dialog\",footers:\"$:/plugins/felixhayashi/tiddlymap/dialogFooter\",tempRoot:\"$:/temp/tmap\",tempStates:\"$:/temp/tmap/state\",tempPopups:\"$:/temp/tmap/state/popup\",localHolders:\"$:/temp/tmap/holders\"};$tm.ref={defaultViewHolder:\"$:/plugins/felixhayashi/tiddlymap/misc/defaultViewHolder\",graphBar:\"$:/plugins/felixhayashi/tiddlymap/misc/advancedEditorBar\",sysUserConf:\"$:/plugins/felixhayashi/tiddlymap/config/sys/user\",visUserConf:\"$:/plugins/felixhayashi/tiddlymap/config/vis/user\",welcomeFlag:\"$:/plugins/felixhayashi/tiddlymap/flag/welcome\",focusButton:\"$:/plugins/felixhayashi/tiddlymap/misc/focusButton\",sysMeta:\"$:/plugins/felixhayashi/tiddlymap/misc/meta\",liveTab:\"$:/plugins/felixhayashi/tiddlymap/hook/liveTab\",mainEditor:\"$:/plugins/felixhayashi/tiddlymap/hook/editor\",sidebarBreakpoint:\"$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint\"};$tm.misc={unknownEdgeLabel:\"tmap:undefined\",liveViewLabel:\"Live View\",defaultViewLabel:\"Default\",mainEditorId:\"main_editor\",arrows:{\"in\":\"⇦\",out:\"➡\",bi:\"⇄\"},magicETyNamespaces:[\"tw-list\",\"tw-field\",\"tw-filter\"]};$tm.config={sys:{field:{nodeLabel:\"caption\",nodeIcon:\"icon\",nodeInfo:\"description\",viewMarker:\"isview\"},liveTab:{fallbackView:$tm.misc.liveViewLabel},suppressedDialogs:{},edgeClickBehaviour:\"manager\",debug:\"false\",notifications:\"true\",popups:{enabled:\"true\",delay:\"600\",width:\"240px\",height:\"140px\"},jsonIndentation:\"1\",editNodeOnCreate:\"false\",singleClickMode:\"false\",editorMenuBar:{showNeighScopeButton:\"true\",showScreenshotButton:\"true\"}}};$tm.filter={nodeTypes:\"[prefix[\"+$tm.path.nodeTypes+\"]]\",edgeTypes:\"[prefix[\"+$tm.path.edgeTypes+\"]]\",views:\"[\"+$tm.config.sys.field.viewMarker+\"[true]]\"};$tm.filter.defaultEdgeTypeFilter=\" -[prefix[_]]\"+\" -[[tw-body:link]]\"+\" -[[tw-list:tags]]\"+\" -[[tw-list:list]]\";var i=$tm.selector={};var a=\"[all[tiddlers+shadows]!has[draft.of]]\";i.allEdgeTypes=a+\" +\"+$tm.filter.edgeTypes;i.allEdgeTypesById=i.allEdgeTypes+\" +[removeprefix[\"+$tm.path.edgeTypes+\"/]]\";i.allNodeTypes=a+\" +\"+$tm.filter.nodeTypes;i.allNodeTypesById=i.allNodeTypes+\" +[removeprefix[\"+$tm.path.nodeTypes+\"/]]\";i.allViews=a+\" +\"+$tm.filter.views;i.allViewsByLabel=i.allViews+\"+[removeprefix[\"+$tm.path.views+\"/]]\";i.allPotentialNodes=\"[all[tiddlers]!is[system]!has[draft.of]]\"}",
"title": "$:/plugins/felixhayashi/tiddlymap/js/startup/environment",
"type": "application/javascript",
"module-type": "startup"
},
"$:/plugins/felixhayashi/tiddlymap/js/startup/listener": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/startup/listener\ntype: application/javascript\nmodule-type: startup\n\n@preserve\n\n\\*/\n\"use strict\";exports.name=\"tmap.listener\";exports.platforms=[\"browser\"];exports.after=[\"rootwidget\",\"tmap.caretaker\"];exports.before=[\"story\"];exports.synchronous=true;exports.startup=function(){new GlobalListener};var NodeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/NodeType\");var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var visDefConf=require(\"$:/plugins/felixhayashi/tiddlymap/js/config/vis\");function GlobalListener(){this.wiki=$tw.wiki;utils.addTWlisteners({\"tmap:tm-remove-edge\":this.handleRemoveEdge,\"tmap:tm-load-type-form\":this.handleLoadTypeForm,\"tmap:tm-save-type-form\":this.handleSaveTypeForm,\"tmap:tm-create-type\":this.handleCreateType,\"tmap:tm-create-edge\":this.handleCreateEdge,\"tmap:tm-suppress-dialog\":this.handleSuppressDialog,\"tmap:tm-generate-widget\":this.handleGenerateWidget,\"tmap:tm-download-graph\":this.handleDownloadGraph,\"tmap:tm-configure-system\":this.handleConfigureSystem,\"tmap:tm-manage-edge-types\":this.handleOpenTypeManager,\"tmap:tm-manage-node-types\":this.handleOpenTypeManager,\"tmap:tm-cancel-dialog\":this.handleCancelDialog,\"tmap:tm-clear-tiddler\":this.handleClearTiddler,\"tmap:tm-merge-tiddlers\":this.handleMixTiddlers,\"tmap:tm-confirm-dialog\":this.handleConfirmDialog},$tw.rootWidget,this)}GlobalListener.prototype.handleCancelDialog=function(e){utils.setField(e.param,\"text\",\"\")};GlobalListener.prototype.handleClearTiddler=function(e){var t=e.paramObject;if(!t||!t.title)return;var a=utils.getTiddler(t.title);var i=a?a.fields:{};var r=t.keep?t.keep.split():[];var d={title:t.title,text:\"\"};for(var l=r.length;l--;){var s=r[l];d[s]=i[s]}$tw.wiki.deleteTiddler(t.title);$tw.wiki.addTiddler(new $tw.Tiddler(d))};GlobalListener.prototype.handleMixTiddlers=function(e){var t=e.paramObject;if(!t||!t.tiddlers)return;var a=$tw.utils.parseStringArray(t.tiddlers);var i=utils.getMergedTiddlers(a,t.output);$tw.wiki.addTiddler(i)};GlobalListener.prototype.handleConfirmDialog=function(e){utils.setField(e.param,\"text\",\"1\")};GlobalListener.prototype.handleSuppressDialog=function(e){if(utils.isTrue(e.paramObject.suppress,false)){utils.setEntry($tm.ref.sysUserConf,\"suppressedDialogs.\"+e.paramObject.dialog,true)}};GlobalListener.prototype.handleDownloadGraph=function(e){var t=$tm.adapter.getGraph({view:e.paramObject.view});t.nodes=utils.convert(t.nodes,\"array\");t.edges=utils.convert(t.edges,\"array\");var a=\"$:/temp/tmap/export\";utils.setField(a,\"text\",JSON.stringify(t,null,2));$tw.rootWidget.dispatchEvent({type:\"tm-download-file\",param:a,paramObject:{filename:e.paramObject.view+\".json\"}})};GlobalListener.prototype.handleConfigureSystem=function(){var e=$tm.adapter.getAllPotentialNodes();var t=$tm.adapter.getEdgesForSet(e);var a=$tw.wiki.getTiddler($tm.path.pluginRoot).fields;var i=$tw.wiki.getTiddlerData($tm.ref.sysMeta);var r=utils.getTiddler($tm.ref.liveTab).hasTag(\"$:/tags/SideBar\");var d={numberOfNodes:\"\"+e.length,numberOfEdges:\"\"+Object.keys(t).length,pluginVersion:\"v\"+a.version,dataStructureVersion:\"v\"+i.dataStructureState,dialog:{preselects:{liveTab:\"\"+r,\"vis-inherited\":JSON.stringify(visDefConf),\"config.vis\":utils.getText($tm.ref.visUserConf),\"config.sys\":$tm.config.sys}}};var l=\"globalConfig\";$tm.dialogManager.open(l,d,function(e,t){if(!e)return;var a=utils.getPropertiesByPrefix(t.fields,\"config.sys.\",true);$tw.wiki.setTiddlerData($tm.ref.sysUserConf,a);if(utils.isTrue(t.fields.liveTab,false)){utils.setField($tm.ref.liveTab,\"tags\",\"$:/tags/SideBar\")}else{$tw.wiki.deleteTiddler($tm.ref.liveTab)}utils.setField($tm.ref.visUserConf,\"text\",t.fields[\"config.vis\"])}.bind(this))};GlobalListener.prototype.handleGenerateWidget=function(e){if(!e.paramObject)e.paramObject={};var t={dialog:{preselects:{view:e.paramObject.view||$tm.misc.defaultViewLabel}}};$tm.dialogManager.open(\"widgetCodeGenerator\",t)};GlobalListener.prototype.handleRemoveEdge=function(e){$tm.adapter.deleteEdge(e.paramObject)};GlobalListener.prototype.handleCreateEdge=function(e){var t=e.paramObject.from;var a=e.paramObject.to;var i=e.paramObject.force;if(!t||!a)return;if(utils.tiddlerExists(t)&&utils.tiddlerExists(a)||i){utils.addTiddler(a);utils.addTiddler(t);var r={from:$tm.adapter.makeNode(t).id,to:$tm.adapter.makeNode(a).id,type:e.paramObject.label,id:e.paramObject.id};$tm.adapter.insertEdge(r);$tm.notify(\"Edge inserted\")}};GlobalListener.prototype.handleOpenTypeManager=function(e){if(!e.paramObject)e.paramObject={};var t=e.type.match(/tmap:tm-(.*)/)[1];if(t===\"manage-edge-types\"){var a=\"Edge-Type Manager\";var i=$tm.selector.allEdgeTypes;var r=$tm.path.edgeTypes}else{var a=\"Node-Type Manager\";var i=$tm.selector.allNodeTypes;var r=$tm.path.nodeTypes}var d={mode:t,topic:a,searchSelector:i,typeRootPath:r};var l=$tm.dialogManager.open(\"MapElementTypeManager\",d);if(e.paramObject.type){this.handleLoadTypeForm({paramObject:{mode:t,id:e.paramObject.type,output:l.fields[\"output\"]}})}};GlobalListener.prototype.handleLoadTypeForm=function(e){var t=e.paramObject.output;var a=e.paramObject.mode===\"manage-edge-types\"?new EdgeType(e.paramObject.id):new NodeType(e.paramObject.id);a.save(t);if(e.paramObject.mode===\"manage-edge-types\"){var i=$tm.adapter.selectEdgesByType(a);var r=Object.keys(i).length;utils.setField(t,\"temp.usageCount\",r)}$tw.wiki.addTiddler(new $tw.Tiddler(utils.getTiddler(t),{typeTRef:a.fullPath,\"temp.idImmutable\":a.isShipped?\"true\":\"\",\"temp.newId\":a.id,\"vis-inherited\":JSON.stringify($tm.config.vis)}));utils.deleteByPrefix(\"$:/state/tabs/MapElementTypeManager\")};GlobalListener.prototype.handleSaveTypeForm=function(e){var t=utils.getTiddler(e.paramObject.output);if(!t)return;var a=e.paramObject.mode;var i=a===\"manage-edge-types\"?new EdgeType(t.fields.id):new NodeType(t.fields.id);if(utils.isTrue(t.fields[\"temp.deleteType\"],false)){this.deleteType(a,i,t)}else{this.saveType(a,i,t)}};GlobalListener.prototype.deleteType=function(e,t,a){$tm.logger(\"debug\",\"Deleting type\",t);if(e===\"manage-edge-types\"){$tm.adapter._processEdgesWithType(t,{action:\"delete\"})}else{$tm.adapter.removeNodeType(t)}this.wiki.addTiddler(new $tw.Tiddler({title:utils.getTiddlerRef(a)}));$tm.notify(\"Deleted type\")};GlobalListener.prototype.saveType=function(e,t,a){var i=utils.getTiddler(a);t.loadFromTiddler(i);t.save();var r=i.fields[\"temp.newId\"];if(r&&r!==i.fields[\"id\"]){if(e===\"manage-edge-types\"){$tm.adapter._processEdgesWithType(t,{action:\"rename\",newName:r})}else{var d=new NodeType(r);d.load(t);d.save();$tw.wiki.deleteTiddler(t.fullPath)}utils.setField(i,\"id\",r)}$tm.notify(\"Saved type data\")};GlobalListener.prototype.handleCreateType=function(e){var t=e.paramObject.id||\"New type\";var a=e.paramObject.mode===\"manage-edge-types\"?new EdgeType(t):new NodeType(t);a.save();this.handleLoadTypeForm({paramObject:{id:a.id,mode:e.paramObject.mode,output:e.paramObject.output}})};GlobalListener.prototype.getTypeFromEvent=function(e){return e.paramObject.mode===\"manage-edge-types\"?new EdgeType(e.paramObject.id):new NodeType(e.paramObject.id)};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/startup/listener",
"type": "application/javascript",
"module-type": "startup"
},
"$:/plugins/felixhayashi/tiddlymap/js/widget/MapConfigWidget": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/widget/MapConfigWidget\ntype: application/javascript\nmodule-type: widget\n\n@preserve\n\n\\*/\n\"use strict\";exports[\"tmap-config\"]=MapConfigWidget;var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var vis=require(\"$:/plugins/felixhayashi/vis/vis.js\");var Widget=require(\"$:/core/modules/widgets/widget.js\").widget;function MapConfigWidget(e,t){Widget.call(this);this.initialise(e,t);this.computeAttributes()}MapConfigWidget.prototype=Object.create(Widget.prototype);MapConfigWidget.prototype.render=function(e,t){this.parentDomNode=e;if(!this.domNode){this.domNode=this.document.createElement(\"div\");$tw.utils.addClass(this.domNode,\"tmap-config-widget\");e.insertBefore(this.domNode,t)}if(this.network){this.network.destroy()}this.networkContainer=document.createElement(\"div\");this.domNode.appendChild(this.networkContainer);this.refreshTrigger=this.getAttribute(\"refresh-trigger\");this.pipeTRef=this.getVariable(\"currentTiddler\");this.inheritedFields=$tw.utils.parseStringArray(this.getAttribute(\"inherited\"));this.extensionTField=this.getAttribute(\"extension\");this.mode=this.getAttribute(\"mode\");for(var i=0;i<this.inheritedFields.length;i++){var s=this.inheritedFields[i];var n=utils.parseFieldData(this.pipeTRef,s,{});if(this.mode===\"manage-edge-types\"){if(!n.edges){n={edges:n}}}else if(this.mode===\"manage-node-types\"){if(!n.nodes){n={nodes:n}}}this.inherited=utils.merge(this.inherited,n)}this.extension=utils.parseFieldData(this.pipeTRef,this.extensionTField,{});if(this.mode===\"manage-edge-types\"){if(!this.extension.edges){this.extension={edges:this.extension}}}else if(this.mode===\"manage-node-types\"){if(!this.extension.nodes){this.extension={nodes:this.extension}}}var r=utils.isTrue(this.getAttribute(\"save-only-changes\"));this.changes=r?{}:this.extension;var a={nodes:[],edges:[]};var o=utils.merge({},this.inherited,this.extension);$tw.utils.extend(o,{configure:{enabled:true,showButton:false,filter:this.getOptionFilter(this.mode)}});this.network=new vis.Network(this.networkContainer,a,o);this.network.on(\"configChange\",this.handleConfigChange.bind(this));var h=this.parentDomNode.getBoundingClientRect().height;this.parentDomNode.style[\"height\"]=h+\"px\";var l=this.handleResetEvent.bind(this);this.networkContainer.addEventListener(\"reset\",l,false);$tm.registry.push(this);this.enhanceConfigurator()};MapConfigWidget.prototype.handleResetEvent=function(e){var t={};t[e.detail.trigger.path]=null;this.handleConfigChange(t)};MapConfigWidget.prototype.handleConfigChange=function(e){var t=utils.flatten(this.changes);var i=utils.flatten(e);var s=Object.keys(utils.flatten(e))[0];var n=i[s]===null;if(n){t[s]=undefined;this.changes=utils.unflatten(t)}else{this.changes=utils.merge(this.changes,e)}var r=utils.merge({},this.changes);if(this.mode===\"manage-node-types\"){r=r[\"nodes\"]}if(this.mode===\"manage-edge-types\"){r=r[\"edges\"]}utils.writeFieldData(this.pipeTRef,this.extensionTField,r,$tm.config.sys.jsonIndentation);var a=\"vis-configuration-wrapper\";var o=this.networkContainer.getElementsByClassName(a)[0];o.style.height=o.getBoundingClientRect().height+\"px\";if(n){window.setTimeout(this.refresh.bind(this),0)}else{window.setTimeout(this.enhanceConfigurator.bind(this),50)}};MapConfigWidget.prototype.enhanceConfigurator=function(){var e=\"vis-configuration-wrapper\";var t=this.networkContainer.getElementsByClassName(e)[0].children;var i=[];var s=utils.flatten(this.changes);for(var n=0;n<t.length;n++){if(!t[n].classList.contains(\"vis-config-item\"))continue;var r=new VisConfElement(t[n],i,n);i.push(r);if(r.level===0)continue;r.setActive(!!s[r.path])}};function VisConfElement(e,t,i){var s=\"getElementsByClassName\";var n=\"getElementsByTagName\";this.isActive=false;this.pos=i;this.el=e;this.inputEl=e[s](\"vis-config-colorBlock\")[0]||e[n](\"input\")[0];this.labelEl=e[s](\"vis-config-label\")[0]||e[s](\"vis-config-header\")[0]||e;var r=this.labelEl.innerText||this.labelEl.textContent;this.label=r&&r.match(/([a-zA-Z0-9]+)/)[1];this.level=parseInt(e.className.match(/.*vis-config-s(.).*/)[1])||0;this.path=this.label;if(this.level>0){for(var a=i;a--;){var o=t[a];if(o.level<this.level){this.path=o.path+\".\"+this.path;break}}}}VisConfElement.prototype.setActive=function(e){if(!e)return;var t=\"tmap-vis-config-item-\"+(e?\"active\":\"inactive\");$tw.utils.addClass(this.el,t);if(e){var i=document.createElement(\"button\");i.innerHTML=\"reset\";i.className=\"tmap-config-item-reset\";var s=this;i.addEventListener(\"click\",function(e){e.currentTarget.dispatchEvent(new CustomEvent(\"reset\",{detail:{trigger:s},bubbles:true,cancelable:true}))},false);this.el.appendChild(i)}};MapConfigWidget.prototype.getOptionFilter=function(e){var t={nodes:{borderWidth:true,borderWidthSelected:true,color:{background:true,border:true},font:{color:true,size:true},icon:true,labelHighlightBold:false,shadow:true,shape:true,shapeProperties:{borderDashes:true},size:true},edges:{arrows:true,color:true,dashes:true,font:true,labelHighlightBold:false,length:true,selfReferenceSize:false,shadow:true,smooth:true,width:true},interaction:{hideEdgesOnDrag:true,hideNodesOnDrag:true,tooltipDelay:true},layout:{hierarchical:false},manipulation:{initiallyActive:true},physics:{forceAtlas2Based:{gravitationalConstant:true,springLength:true,springConstant:true,damping:true,centralGravity:true}}};if(e===\"manage-edge-types\"){t={edges:t.edges}}else if(e===\"manage-node-types\"){t={nodes:t.nodes}}else{t.edges.arrows=false}return function(e,i){i=i.concat([e]);var s=t;for(var n=0,r=i.length;n<r;n++){if(s[i[n]]===true){return true}else if(s[i[n]]==null){return false}s=s[i[n]]}return false}};MapConfigWidget.prototype.isZombieWidget=function(){return!document.body.contains(this.parentDomNode)};MapConfigWidget.prototype.destruct=function(){if(this.network){this.network.destroy()}};MapConfigWidget.prototype.refresh=function(e){if(this.isZombieWidget()||!this.network)return;if(!e||e[this.refreshTrigger]){this.refreshSelf();return true}};MapConfigWidget.prototype.setNull=function(e){for(var t in e){if(typeof e[t]==\"object\"){this.setNull(e[t])}else{e[t]=undefined}}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/widget/MapConfigWidget",
"type": "application/javascript",
"module-type": "widget"
},
"$:/plugins/felixhayashi/tiddlymap/js/widget/connections": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/widget/connections\ntype: application/javascript\nmodule-type: widget\n\n@preserve\n\n\\*/\n\"use strict\";exports[\"tmap-edgelistitem\"]=EdgeListItemWidget;exports[\"tmap-connections\"]=EdgeListWidget;var Widget=require(\"$:/core/modules/widgets/widget.js\").widget;var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");function EdgeListWidget(e,t){Widget.call(this,e,t)}EdgeListWidget.prototype=Object.create(Widget.prototype);EdgeListWidget.prototype.render=function(e,t){this.parentDomNode=e;this.computeAttributes();this.execute();this.renderChildren(e,t)};EdgeListWidget.prototype.execute=function(){var e=[this.getVariable(\"currentTiddler\")];var t=this.getAttribute(\"filter\",\"\");var i=this.getAttribute(\"direction\",\"both\");var r=$tm.indeces.allETy;var s=utils.getEdgeTypeMatches(t,r);var d={typeWL:utils.getLookupTable(s),direction:i};var o=$tm.adapter.getNeighbours(e,d);var a=o.nodes;var g=o.edges;var n=[];for(var h in g){var p=g[h];var l=a[p.to]||a[p.from];if(!l)continue;n.push({type:\"tmap-edgelistitem\",edge:p,typeWL:d.typeWL,neighbour:l,children:this.parseTreeNode.children})}if(!n.length){this.wasEmpty=true;n=this.getEmptyMessage()}else if(this.wasEmpty){this.removeChildDomNodes()}this.makeChildWidgets(n)};EdgeListWidget.prototype.getEmptyMessage=function(){var e=this.wiki.parseText(\"text/vnd.tiddlywiki\",this.getAttribute(\"emptyMessage\",\"\"),{parseAsInline:true});return e?e.tree:[]};EdgeListWidget.prototype.refresh=function(e){var t=this.computeAttributes();var i=Object.keys(t).length;if(i){this.refreshSelf();return true}for(var r in e){if(!utils.isSystemOrDraft(r)){this.refreshSelf();return true}}return this.refreshChildren(e)};function EdgeListItemWidget(e,t){Widget.call(this,e,t);this.arrows=$tm.misc.arrows}EdgeListItemWidget.prototype=Object.create(Widget.prototype);EdgeListItemWidget.prototype.execute=function(){var e=this.parseTreeNode;var t=$tm.indeces.tById[e.neighbour.id];var i=utils.flatten(e.edge);for(var r in i){if(typeof i[r]===\"string\"){this.setVariable(\"edge.\"+r,i[r])}}this.setVariable(\"currentTiddler\",t);this.setVariable(\"neighbour\",t);var s=$tm.indeces.allETy[i.type];var d=i.to===e.neighbour.id?\"to\":\"from\";var o=d;if(s.biArrow){o=\"bi\"}else{if(d===\"to\"&&s.invertedArrow){o=\"from\"}else if(d===\"from\"&&s.invertedArrow){o=\"to\"}}this.setVariable(\"direction\",o);this.setVariable(\"directionSymbol\",o===\"bi\"?this.arrows.bi:o===\"from\"?this.arrows.in:this.arrows.out);this.makeChildWidgets()};EdgeListItemWidget.prototype.refresh=function(e){return this.refreshChildren(e)};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/widget/connections",
"type": "application/javascript",
"module-type": "widget"
},
"$:/plugins/felixhayashi/tiddlymap/js/widget/MapWidget": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/tiddlymap/js/widget/MapWidget\ntype: application/javascript\nmodule-type: widget\n\n@preserve\n\n\\*/\n\"use strict\";exports.tiddlymap=MapWidget;exports.tmap=MapWidget;var utils=require(\"$:/plugins/felixhayashi/tiddlymap/js/utils\");var DialogManager=require(\"$:/plugins/felixhayashi/tiddlymap/js/DialogManager\");var CallbackManager=require(\"$:/plugins/felixhayashi/tiddlymap/js/CallbackManager\");var ViewAbstraction=require(\"$:/plugins/felixhayashi/tiddlymap/js/ViewAbstraction\");var EdgeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/EdgeType\");var NodeType=require(\"$:/plugins/felixhayashi/tiddlymap/js/NodeType\");var Popup=require(\"$:/plugins/felixhayashi/tiddlymap/js/Popup\");var vis=require(\"$:/plugins/felixhayashi/vis/vis.js\");var Widget=require(\"$:/core/modules/widgets/widget.js\").widget;function MapWidget(e,t){Widget.call(this,e,t);this.getAttr=this.getAttribute;this.isDebug=utils.isTrue($tm.config.sys.debug,false);utils.bind(this,[\"constructTooltip\",\"handleResizeEvent\",\"handleClickEvent\",\"handleCanvasKeyup\",\"handleCanvasKeydown\",\"handleCanvasScroll\",\"handleWidgetKeyup\",\"handleWidgetKeydown\",\"handleTriggeredRefresh\",\"handleContextMenu\"]);this.callbackManager=new CallbackManager;this.dialogManager=new DialogManager(this.callbackManager,this);this.computeAttributes();this.editorMode=this.getAttr(\"editor\");this.clickToUse=utils.isTrue(this.getAttr(\"click-to-use\"),false);this.id=this.getAttr(\"object-id\")||this.getStateQualifier();this.widgetTempStatePath=$tm.path.tempStates+\"/\"+this.id;this.widgetPopupsPath=$tm.path.tempPopups+\"/\"+this.id;if(this.editorMode){utils.addTWlisteners({\"tmap:tm-create-view\":this.handleCreateView,\"tmap:tm-rename-view\":this.handleRenameView,\"tmap:tm-delete-view\":this.handleDeleteView,\"tmap:tm-delete-element\":this.handleDeleteElement,\"tmap:tm-edit-view\":this.handleEditView,\"tmap:tm-store-position\":this.handleStorePositions,\"tmap:tm-generate-widget\":this.handleGenerateWidget,\"tmap:tm-toggle-central-topic\":this.handleSetCentralTopic,\"tmap:tm-save-canvas\":this.handleSaveCanvas},this,this)}utils.addTWlisteners({\"tmap:tm-focus-node\":this.handleFocusNode,\"tmap:tm-reset-focus\":this.repaintGraph},this,this);this.visListeners={click:this.handleVisSingleClickEvent,doubleClick:this.handleVisDoubleClickEvent,stabilized:this.handleVisStabilizedEvent,selectNode:this.handleVisSelectNode,deselectNode:this.handleVisDeselectNode,dragStart:this.handleVisDragStart,dragEnd:this.handleVisDragEnd,hoverNode:this.handleVisHoverElement,hoverEdge:this.handleVisHoverElement,blurNode:this.handleVisBlurElement,blurEdge:this.handleVisBlurElement,beforeDrawing:this.handleVisBeforeDrawing,stabilizationProgress:this.handleVisLoading,stabilizationIterationsDone:this.handleVisLoadingDone};this.windowDomListeners={resize:[this.handleResizeEvent,false],click:[this.handleClickEvent,false]};this.canvasDomListeners={keyup:[this.handleCanvasKeyup,true],keydown:[this.handleCanvasKeydown,true],mousewheel:[this.handleCanvasScroll,true],contextmenu:[this.handleContextMenu,true]};this.widgetDomListeners={keyup:[this.handleWidgetKeyup,true],keydown:[this.handleWidgetKeydown,true]}}MapWidget.prototype=Object.create(Widget.prototype);MapWidget.prototype.handleConnectionEvent=function(e,t){var i=this.view.getEdgeTypeFilter();var s={fromLabel:$tm.adapter.selectNodeById(e.from).label,toLabel:$tm.adapter.selectNodeById(e.to).label,viewNS:this.view.getConfig(\"edge_type_namespace\"),eTyFilter:i.raw};var a=\"getEdgeType\";this.dialogManager.open(a,s,function(s,a){if(s){var r=utils.getText(a);var o={namespace:this.view.getConfig(\"edge_type_namespace\")};var r=new EdgeType(r,null,o);if(!r.exists())r.save();e.type=r.id;$tm.adapter.insertEdge(e);if(!this.view.isEdgeTypeVisible(r.id)){var n={type:r.id,view:this.view.getLabel(),eTyFilter:i.pretty};this.dialogManager.open(\"edgeNotVisible\",n)}this.preventFitAfterRebuild=true}if(typeof t===\"function\"){t(s)}})};MapWidget.prototype.checkForFreshInstall=function(){var e=$tm.ref.sysMeta;if(!utils.getEntry(e,\"showWelcomeMessage\",true))return;utils.setEntry(e,\"showWelcomeMessage\",false);var t={};var i=\"welcome\";this.dialogManager.open(i,t,function(e,t){if(utils.tiddlerExists(\"$:/plugins/felixhayashi/topstoryview\")){utils.setText(\"$:/view\",\"top\");utils.setText(\"$:/config/Navigation/openLinkFromInsideRiver\",\"above\");utils.setText(\"$:/config/Navigation/openLinkFromOutsideRiver\",\"top\");utils.setText(\"$:/themes/tiddlywiki/vanilla/options/sidebarlayout\",\"fixed-fluid\");utils.touch(\"$:/plugins/felixhayashi/topstoryview\")}var i=$tm.misc.defaultViewLabel;var s={label:\"Have fun with\",x:0,y:0};var a=$tm.adapter.insertNode(s,i);var s={label:\"TiddlyMap!!\",x:100,y:100};var r=$tm.adapter.insertNode(s,i);$tm.adapter.insertEdge({from:a.id,to:r.id})})};MapWidget.prototype.openStandardConfirmDialog=function(e,t){var i={message:t};this.dialogManager.open(\"getConfirmation\",i,e)};MapWidget.prototype.logger=function(e,t){if(this.isDebug){var i=Array.prototype.slice.call(arguments,1);i.unshift(\"@\"+this.id);i.unshift(e);$tm.logger.apply(this,i)}};MapWidget.prototype.render=function(e,t){this.parentDomNode=e;this.domNode=this.document.createElement(\"div\");e.insertBefore(this.domNode,t);this.registerClassNames(this.domNode);this.viewHolderRef=this.getViewHolderRef();this.view=this.getView();this.graphBarDomNode=this.document.createElement(\"div\");$tw.utils.addClass(this.graphBarDomNode,\"tmap-topbar\");this.domNode.appendChild(this.graphBarDomNode);this.graphDomNode=this.document.createElement(\"div\");this.domNode.appendChild(this.graphDomNode);$tw.utils.addClass(this.graphDomNode,\"tmap-vis-graph\");if(utils.isPreviewed(this)||this.domNode.isTiddlyWikiFakeDom){$tw.utils.addClass(this.domNode,\"tmap-static-mode\");this.renderPreview(this.graphBarDomNode,this.graphDomNode)}else{this.renderFullWidget(this.domNode,this.graphBarDomNode,this.graphDomNode)}};MapWidget.prototype.renderPreview=function(e,t){var i=this.view.getRoot()+\"/snapshot\";var s=utils.getTiddler(i);var a=this.document.createElement(\"span\");a.innerHTML=this.view.getLabel();a.className=\"tmap-view-label\";e.appendChild(a);if(s){var r=this.makeChildWidget(utils.getTranscludeNode(i),true);r.renderChildren(t,null)}else{$tw.utils.addClass(t,\"tmap-graph-placeholder\")}};MapWidget.prototype.renderFullWidget=function(e,t,i){utils.setDomListeners(\"add\",window,this.windowDomListeners);utils.setDomListeners(\"add\",e,this.widgetDomListeners);this.addLoadingBar(this.domNode);this.tooltip=new Popup(this.domNode,{className:\"tmap-tooltip\",showDelay:$tm.config.sys.popups.delay});this.contextMenu=new Popup(this.domNode,{className:\"tmap-context-menu\",showDelay:0,hideOnClick:true,leavingDelay:999999});this.sidebar=utils.getFirstElementByClassName(\"tc-sidebar-scrollable\");this.isInSidebar=this.sidebar&&!this.domNode.isTiddlyWikiFakeDom&&this.sidebar.contains(this.domNode);this.doFitAfterStabilize=true;this.preventFitAfterRebuild=false;this.initAndRenderEditorBar(t);this.initAndRenderGraph(i);$tm.registry.push(this);this.reloadRefreshTriggers();this.checkForFreshInstall();if(this.id===$tm.misc.mainEditorId){var s=$tm.url;if(s&&s.query[\"tmap-enlarged\"]){this.toggleEnlargedMode(s.query[\"tmap-enlarged\"])}}};MapWidget.prototype.registerClassNames=function(e){var t=$tw.utils.addClass;t(e,\"tmap-widget\");if(this.clickToUse){t(e,\"tmap-click-to-use\")}if(this.getAttr(\"editor\")===\"advanced\"){t(e,\"tmap-advanced-editor\")}if(this.getAttr(\"design\")===\"plain\"){t(e,\"tmap-plain-design\")}if(!utils.isTrue(this.getAttr(\"show-buttons\"),true)){t(e,\"tmap-no-buttons\")}if(this.getAttr(\"class\")){t(e,this.getAttr(\"class\"))}};MapWidget.prototype.addLoadingBar=function(e){this.graphLoadingBarDomNode=this.document.createElement(\"progress\");$tw.utils.addClass(this.graphLoadingBarDomNode,\"tmap-loading-bar\");e.appendChild(this.graphLoadingBarDomNode)};MapWidget.prototype.initAndRenderEditorBar=function(e){this.rebuildEditorBar()};MapWidget.prototype.rebuildEditorBar=function(){var e=this.view;var t={widgetQualifier:this.getStateQualifier(),widgetTempPath:this.widgetTempPath,widgetPopupsPath:this.widgetPopupsPath,isViewBound:String(this.isViewBound()),viewRoot:e.getRoot(),viewLabel:e.getLabel(),viewHolder:this.getViewHolderRef(),edgeTypeFilter:e.getPaths().edgeTypeFilter,allEdgesFilter:$tm.selector.allEdgeTypes,neighScopeBtnClass:\"tmap-neigh-scope-button\"+(e.isEnabled(\"neighbourhood_scope\")?\" \"+\"tmap-active-button\":\"\")};for(var i in t){this.setVariable(i,t[i])}var s=utils.getTiddlerNode(e.getRoot());if(this.editorMode===\"advanced\"){s.children.push(utils.getTranscludeNode($tm.ref.graphBar))}else{var a=utils.getElementNode(\"span\",e.getLabel(),\"tmap-view-label\");s.children.push(a)}s.children.push(utils.getTranscludeNode($tm.ref.focusButton));this.makeChildWidgets([s]);this.renderChildren(this.graphBarDomNode,this.graphBarDomNode.firstChild)};MapWidget.prototype.refresh=function(e){return false};MapWidget.prototype.update=function(e){if(!this.network||this.isZombieWidget()||utils.isPreviewed(this)){return}var t=e.changedTiddlers;var i=false;var s=false;var a=false;var r={};this.callbackManager.handleChanges(t);if(this.isViewSwitched(t)||this.hasChangedAttributes()||e[$tm.path.options]||e[$tm.path.nodeTypes]||t[this.view.getRoot()]){this.logger(\"warn\",\"View switched (or main config change)\");this.view=this.getView(true);this.reloadRefreshTriggers();i=true;a=true}else{var o=this.view.update(e);if(o&&!this.ignoreNextViewModification){this.logger(\"warn\",\"View components modified\");this.reloadBackgroundImage();i=true;s=true;r.resetEdgeTypeWL=true;if(!this.preventFitAfterRebuild){r.resetFocus={delay:0,duration:0}}}else{if(e[$tm.path.nodeTypes]){s=true}else if(this.hasChangedElements(t)){s=true}}}if(a){this.initAndRenderGraph(this.graphDomNode);this.hidePopups(0,true)}else if(s){this.rebuildGraph(r);this.hidePopups(0,true)}if(i){this.removeChildDomNodes();this.rebuildEditorBar()}else{this.refreshChildren(t)}this.ignoreNextViewModification=false};MapWidget.prototype.hidePopups=function(e,t){this.tooltip.hide(e,t);this.contextMenu.hide(0,true)};MapWidget.prototype.reloadRefreshTriggers=function(){this.callbackManager.remove(this.refreshTriggers);var e=this.getAttr(\"refresh-triggers\")||this.view.getConfig(\"refresh-triggers\");this.refreshTriggers=$tw.utils.parseStringArray(e)||[];this.logger(\"debug\",\"Registering refresh trigger\",this.refreshTriggers);for(var t=this.refreshTriggers.length;t--;){this.callbackManager.add(this.refreshTriggers[t],this.handleTriggeredRefresh,false)}};MapWidget.prototype.rebuildGraph=function(e){if(utils.isPreviewed(this))return;this.logger(\"debug\",\"Rebuilding graph\");e=e||{};this.hasNetworkStabilized=false;if(e.resetData){this.graphData.edges.clear();this.graphData.nodes.clear();this.graphData.edgesById=null;this.graphData.nodesById=null}if(!this.view.isEnabled(\"physics_mode\")){var t=this.visOptions.physics;t[t.solver].centralGravity=.015}if(!e.resetFocus){this.doFitAfterStabilize=false}this.rebuildGraphData();if(!utils.hasElements(this.graphData.nodesById)){return}this.network.stabilize();if(e.resetFocus&&!this.preventFitAfterRebuild){this.doFitAfterStabilize=true;this.fitGraph(e.resetFocus.delay,e.resetFocus.duration)}this.preventFitAfterRebuild=false};MapWidget.prototype.getContainer=function(){return this.domNode};MapWidget.prototype.rebuildGraphData=function(e){$tm.start(\"Reloading Network\");e=e||{};var t=$tm.adapter.getGraph({view:this.view});var i=t.nodes;var s=t.edges;this.graphData.nodes=this.getRefreshedDataSet(i,this.graphData.nodesById,this.graphData.nodes);this.graphData.edges=this.getRefreshedDataSet(s,this.graphData.edgesById,this.graphData.edges);this.graphData.nodesById=i;this.graphData.edgesById=s;utils.setField(\"$:/temp/tmap/nodes/\"+this.view.getLabel(),\"list\",$tm.adapter.getTiddlersById(i));$tm.stop(\"Reloading Network\");return this.graphData};MapWidget.prototype.isViewBound=function(){return utils.startsWith(this.getViewHolderRef(),$tm.path.localHolders)};MapWidget.prototype.isViewSwitched=function(e){return e[this.getViewHolderRef()]};MapWidget.prototype.hasChangedAttributes=function(){return Object.keys(this.computeAttributes()).length};MapWidget.prototype.hasChangedElements=function(e){var t=[];var i=this.graphData.nodesById;var s=this.view.isEnabled(\"neighbourhood_scope\");var a=this.view.getEdgeTypeFilter(\"whitelist\");for(var r in e){if(utils.isSystemOrDraft(r))continue;if(i[$tm.adapter.getId(r)]||s){return true}if(e[r].modified){t.push(r)}}if(t.length){var o=this.view.getNodeFilter(\"compiled\");var n=utils.getMatches(o,t);return!!n.length}};MapWidget.prototype.initAndRenderGraph=function(e){if(this.network)this._destructVis();this.logger(\"info\",\"Initializing and rendering the graph\");if(!this.isInSidebar){this.callbackManager.add(\"$:/state/sidebar\",this.handleResizeEvent)}this.visOptions=this.getVisOptions();this.graphData={nodes:new vis.DataSet,edges:new vis.DataSet,nodesById:utils.makeHashMap(),edgesById:utils.makeHashMap()};this.tooltip.setEnabled(utils.isTrue($tm.config.sys.popups.enabled,true));this.network=new vis.Network(e,this.graphData,this.visOptions);this.canvas=e.getElementsByTagName(\"canvas\")[0];this.canvas.tabIndex=0;for(var t in this.visListeners){this.network.on(t,this.visListeners[t].bind(this))}this.addGraphButtons({\"fullscreen-button\":function(){this.toggleEnlargedMode(\"fullscreen\")},\"halfscreen-button\":function(){this.toggleEnlargedMode(\"halfscreen\")}});utils.setDomListeners(\"add\",this.canvas,this.canvasDomListeners);this.reloadBackgroundImage();this.rebuildGraph({resetFocus:{delay:0,duration:0}});this.handleResizeEvent();this.canvas.focus()};MapWidget.prototype.handleCanvasKeyup=function(){var e={from:null,to:null};return function(t){var i=this.network.getSelectedNodes();if(t.ctrlKey){t.preventDefault();if(t.keyCode===88){if(this.editorMode){this.handleAddNodesToClipboard(\"move\")}else{$tm.notify(\"Map is read only!\")}}else if(t.keyCode===67){this.handleAddNodesToClipboard(\"copy\")}else if(t.keyCode===86){this.handlePasteNodesFromClipboard()}else if(t.keyCode===65){var s=Object.keys(this.graphData.nodesById);this.network.selectNodes(s)}else if(t.keyCode===49||t.keyCode===50){if(i.length!==1)return;var a=t.keyCode===49?\"from\":\"to\";$tm.notify(utils.ucFirst(a)+\"-part selected\");e[a]=i[0];if(e.from&&e.to){this.handleConnectionEvent(e,function(){e={from:null,to:null}})}}}else if(t.keyCode===13){if(i.length!==1)return;this.openTiddlerWithId(i[0])}}}();MapWidget.prototype.handleDeleteElement=function(e){var t=e.paramObject.id;var i=t?[t]:this.network.getSelectedNodes();this.handleRemoveElements({nodes:i})};MapWidget.prototype.handleConfigureElement=function(e){};MapWidget.prototype.handleCanvasKeydown=function(e){if(e.keyCode===46){e.preventDefault();this.handleRemoveElements(this.network.getSelection())}};MapWidget.prototype.handleCanvasScroll=function(e){var t=!!(e.ctrlKey||this.isInSidebar||this.enlargedMode);if(t){e.preventDefault()}if(t!==this.visOptions.interaction.zoomView){e.preventDefault();e.stopPropagation();this.visOptions.interaction.zoomView=t;this.network.setOptions({interaction:{zoomView:t}});return false}};MapWidget.prototype.handleContextMenu=function(e){e.preventDefault();this.tooltip.hide(0,true);var t=this.network.getNodeAt({x:e.offsetX,y:e.offsetY});if(!t)return;var i=this.network.getSelectedNodes();if(!utils.inArray(t,i)){i=[t];this.network.selectNodes(i)}this.contextMenu.show(i,function(e,t){var i=e.length>1?\"multi\":\"single\";var s=\"$:/plugins/felixhayashi/tiddlymap/editor/contextMenu/node\";utils.registerTransclude(this,\"contextMenuWidget\",s);this.contextMenuWidget.setVariable(\"mode\",i);this.contextMenuWidget.render(t)}.bind(this))};MapWidget.prototype.handleWidgetKeyup=function(e){};MapWidget.prototype.handleWidgetKeydown=function(e){if(e.ctrlKey){e.preventDefault();if(e.keyCode===70){e.preventDefault();var t=this.widgetPopupsPath+\"/focus\";utils.setText(t,utils.getText(t)?\"\":\"1\")}else{return}}else if(e.keyCode===120){e.preventDefault();this.toggleEnlargedMode(\"halfscreen\")}else if(e.keyCode===121){e.preventDefault();this.toggleEnlargedMode(\"fullscreen\")}else if(e.keyCode===27){e.preventDefault();utils.deleteByPrefix(this.widgetPopupsPath)}else{return}this.canvas.focus()};MapWidget.prototype.handlePasteNodesFromClipboard=function(){if(!this.editorMode||this.view.isLiveView()){$tm.notify(\"Map is read only!\");return}if($tm.clipBoard){if($tm.clipBoard.type===\"nodes\"){var e=$tm.clipBoard.nodes;var t=Object.keys(e);if(t.length){for(var i in e){if(this.graphData.nodesById[i])continue;this.view.addNode(e[i]);this.graphData.nodes.update({id:i})}this.network.selectNodes(t);$tm.notify(\"pasted \"+t.length+\" nodes into map.\")}return}}$tm.notify(\"TiddlyMap clipboad is empty!\")};MapWidget.prototype.handleAddNodesToClipboard=function(e){var t=this.network.getSelectedNodes();if(!t.length)return;$tm.clipBoard={type:\"nodes\",nodes:this.graphData.nodes.get(t,{returnType:\"Object\"})};$tm.notify(\"Copied \"+t.length+\" nodes to clipboard\");if(e===\"move\"){for(var i=t.length;i--;){this.view.removeNode(t[i])}}};MapWidget.prototype.isMobileMode=function(){var e=utils.getText($tm.ref.sidebarBreakpoint,960);return window.innerWidth<=parseInt(e)};MapWidget.prototype.getVisOptions=function(){var e=$tm.config.vis;var t=utils.parseJSON(this.view.getConfig(\"vis\"));var i=utils.merge({},e,t);i.clickToUse=this.clickToUse;i.manipulation.enabled=!!this.editorMode;i.manipulation.deleteNode=function(e,t){this.handleRemoveElements(e);this.resetVisManipulationBar(t)}.bind(this);i.manipulation.deleteEdge=function(e,t){this.handleRemoveElements(e);this.resetVisManipulationBar(t)}.bind(this);i.manipulation.addEdge=function(e,t){this.handleConnectionEvent(e);this.resetVisManipulationBar(t)}.bind(this);i.manipulation.addNode=function(e,t){this.handleInsertNode(e);this.resetVisManipulationBar(t)}.bind(this);i.manipulation.editNode=function(e,t){this.handleEditNode(e);this.resetVisManipulationBar(t)}.bind(this);i.interaction.zoomView=!!(this.isInSidebar||this.enlargedMode);i.manipulation.editEdge=false;var s=i.physics;s[s.solver]=s[s.solver]||{};s.stabilization.iterations=1e3;this.logger(\"debug\",\"Loaded graph options\",i);return i};MapWidget.prototype.resetVisManipulationBar=function(e){if(e)e(null);this.network.disableEditMode();this.network.enableEditMode()};MapWidget.prototype.isVisInEditMode=function(){var e=\"vis-button vis-back\";return this.graphDomNode.getElementsByClassName(e).length>0};MapWidget.prototype.handleCreateView=function(){var e={view:this.view.getLabel()};var t=\"createView\";this.dialogManager.open(t,e,function(e,t){if(!e)return;var i=utils.getField(t,\"name\");var s=utils.getField(t,\"clone\",false);var a=new ViewAbstraction(i);if(a.exists()){$tm.notify(\"Forbidden! View already exists!\");return}if(s&&this.view.isLiveView()){$tm.notify(\"Forbidden to clone the live view!\");return}a=new ViewAbstraction(i,{isCreate:true,protoView:s?this.view:null});this.setView(a)})};MapWidget.prototype.handleRenameView=function(){if(this.view.isLocked()){$tm.notify(\"Forbidden!\");return}var e=this.view.getOccurrences();var t={count:e.length.toString(),filter:utils.joinAndWrap(e,\"[[\",\"]]\")};var i=\"renameView\";this.dialogManager.open(i,t,function(e,t){if(e){var i=utils.getText(t);var s=new ViewAbstraction(i);if(!i){$tm.notify(\"Invalid name!\")}else if(s.exists()){$tm.notify(\"Forbidden! View already exists!\")}else{this.view.rename(i);this.setView(this.view)}}})};MapWidget.prototype.handleEditView=function(){var e=JSON.stringify($tm.config.vis);var t=this.graphData;var i=this.view.getConfig();var s={\"filter.prettyNodeFltr\":this.view.getNodeFilter(\"pretty\"),\"filter.prettyEdgeFltr\":this.view.getEdgeTypeFilter(\"pretty\"),\"vis-inherited\":e};var a={view:this.view.getLabel(),createdOn:this.view.getCreationDate(true),numberOfNodes:Object.keys(t.nodesById).length.toString(),numberOfEdges:Object.keys(t.edgesById).length.toString(),dialog:{preselects:$tw.utils.extend({},i,s)}};var r=\"configureView\";this.dialogManager.open(r,a,function(e,t){if(!e)return;var i=utils.getPropertiesByPrefix(t.fields,\"config.\",true);var s=this.view.getConfig(\"background_image\");this.view.setConfig(i);if(i[\"physics_mode\"]&&!this.view.isEnabled(\"physics_mode\")){this.handleStorePositions()}var a=this.view.getConfig(\"background_image\");if(a&&a!==s){$tm.notify(\"Background changed! You may need to zoom out a bit.\")}var r=utils.getField(t,\"filter.prettyNodeFltr\",\"\");var o=utils.getField(t,\"filter.prettyEdgeFltr\",\"\");this.view.setNodeFilter(r);this.view.setEdgeTypeFilter(o)})};MapWidget.prototype.handleSaveCanvas=function(){var e=\"$:/temp/tmap/snapshot\";var t=this.createAndSaveSnapshot(e);var i=utils.getSnapshotTitle(this.view.getLabel(),\"png\");var s={dialog:{snapshot:e,width:this.canvas.width.toString(),height:this.canvas.height.toString(),preselects:{name:i,action:\"download\"}}};var a=\"saveCanvas\";this.dialogManager.open(a,s,function(t,s){if(!t)return;i=s.fields.name||i;var a=s.fields.action;if(a===\"download\"){this.handleDownloadSnapshot(i)}else if(a===\"wiki\"){utils.cp(e,i,true);this.dispatchEvent({type:\"tm-navigate\",navigateTo:i})}else if(a===\"placeholder\"){this.view.addPlaceholder(e)}$tw.wiki.deleteTiddler(\"$:/temp/tmap/snapshot\")})};MapWidget.prototype.handleDownloadSnapshot=function(e){var t=this.document.createElement(\"a\");var i=this.view.getLabel();t.download=e||utils.getSnapshotTitle(i,\"png\");t.href=this.getSnapshot();var s=new MouseEvent(\"click\");t.dispatchEvent(s)};MapWidget.prototype.createAndSaveSnapshot=function(e){var t=this.view.getLabel();var i=e||this.view.getRoot()+\"/snapshot\";$tw.wiki.addTiddler(new $tw.Tiddler({title:i,type:\"image/png\",text:this.getSnapshot(true),modified:new Date}));return i};MapWidget.prototype.getSnapshot=function(e){var t=this.canvas.toDataURL(\"image/png\");return e?utils.getWithoutPrefix(t,\"data:image/png;base64,\"):t};MapWidget.prototype.handleDeleteView=function(){var e=this.view.getLabel();if(this.view.isLocked()){$tm.notify(\"Forbidden!\");return}var t=this.view.getOccurrences();if(t.length){var i={count:t.length.toString(),filter:utils.joinAndWrap(t,\"[[\",\"]]\")};this.dialogManager.open(\"cannotDeleteViewDialog\",i);return}var s=\"You are about to delete the view \"+\"''\"+e+\"'' (no tiddler currently references this view).\";this.openStandardConfirmDialog(function(t){if(t){this.view.destroy();this.setView($tm.misc.defaultViewLabel);this.logger(\"debug\",'view \"'+e+'\" deleted ');$tm.notify('view \"'+e+'\" deleted ')}},s)};MapWidget.prototype.handleTriggeredRefresh=function(e){this.logger(\"log\",e,\"Triggered a refresh\");if(this.id===\"live_tab\"){var t=utils.getTiddler(utils.getText(e));if(t){var i=t.fields[\"tmap.open-view\"]||$tm.config.sys.liveTab.fallbackView;if(i&&i!==this.view.getLabel()){this.setView(i);return}}}this.rebuildGraph({resetFocus:{delay:1e3,duration:1e3}})};MapWidget.prototype.handleRemoveElements=function(e){if(e.nodes.length){this.handleRemoveNodes(e.nodes)}else if(e.edges.length){this.handleRemoveEdges(e.edges)}this.resetVisManipulationBar()};MapWidget.prototype.handleRemoveEdges=function(e){$tm.adapter.deleteEdges(this.graphData.edges.get(e));$tm.notify(\"edge\"+(e.length>1?\"s\":\"\")+\" removed\");this.preventFitAfterRebuild=true};MapWidget.prototype.handleRemoveNodes=function(e){var t=$tm.adapter.getTiddlersById(e);var i={count:e.length.toString(),tiddlers:$tw.utils.stringifyList(t),dialog:{preselects:{\"delete-from\":\"filter\"}}};var s=\"deleteNodeDialog\";this.dialogManager.open(s,i,function(t,i){if(!t)return;if(i.fields[\"delete-from\"]===\"system\"){$tm.adapter.deleteNodes(e);var s=e.length}else{var s=0;for(var a=e.length;a--;){var r=this.view.removeNode(e[a]);if(r)s++}}this.preventFitAfterRebuild=true;$tm.notify(\"Removed \"+s+\" of \"+e.length+\" from \"+i.fields[\"delete-from\"])})};MapWidget.prototype.toggleEnlargedMode=function(e){if(!this.isInSidebar&&e===\"halfscreen\")return;this.logger(\"log\",\"Toggled graph enlargement\");var t=this.enlargedMode;if(t){this.network.setOptions({clickToUse:this.clickToUse});utils.findAndRemoveClassNames([\"tmap-has-\"+t+\"-widget\",\"tmap-\"+t]);this.enlargedMode=null;document.body.scrollTop=this.scrollTop}if(!t||t!==e&&(e===\"fullscreen\"||e===\"halfscreen\"&&!this.isInSidebar)){var i=document.documentElement;this.scrollTop=document.body.scrollTop;this.enlargedMode=e;var s=this.isInSidebar?this.sidebar:utils.getFirstElementByClassName(\"tc-story-river\");$tw.utils.addClass(this.document.body,\"tmap-has-\"+e+\"-widget\");$tw.utils.addClass(s,\"tmap-has-\"+e+\"-widget\");$tw.utils.addClass(this.domNode,\"tmap-\"+e);this.network.setOptions({clickToUse:false});$tm.notify(\"Toggled \"+e+\" mode\")}this.handleResizeEvent()};MapWidget.prototype.handleGenerateWidget=function(e){$tw.rootWidget.dispatchEvent({type:\"tmap:tm-generate-widget\",paramObject:{view:this.view.getLabel()}})};MapWidget.prototype.handleSetCentralTopic=function(e){var t=e.paramObject.id||this.network.getSelectedNodes()[0];if(t===this.view.getConfig(\"central-topic\")){t=\"\"}this.view.setCentralTopic(t)};MapWidget.prototype.handleStorePositions=function(e){var t=this.view.getNodeData();var i=this.network.getPositions();for(var s in i){t[s]=t[s]||{};t[s].x=i[s].x;t[s].y=i[s].y}this.view.saveNodeData(t);this.ignoreNextViewModification=true;if(e){$tm.notify(\"positions stored\")}};MapWidget.prototype.handleVisStabilizedEvent=function(e){if(this.hasNetworkStabilized)return;this.hasNetworkStabilized=true;this.logger(\"log\",\"Network stabilized after\",e.iterations,\"iterations\");if(!this.view.isEnabled(\"physics_mode\")){var t=this.graphData.nodesById;var i=[];for(var s in t){if(!t[s].x){i.push(s)}}if(i.length){this.setNodesMoveable(i,false);$tm.notify(i.length+\" nodes were added to the graph\");this.doFitAfterStabilize=true}var a=this.visOptions.physics;a[a.solver].centralGravity=0;this.network.setOptions(this.visOptions)}if(this.doFitAfterStabilize){this.doFitAfterStabilize=false;this.fitGraph(1e3,1e3)}};MapWidget.prototype.handleFocusNode=function(e){this.network.focus($tm.adapter.getId(e.param),{scale:1.5,animation:true})};MapWidget.prototype.isZombieWidget=function(){if(this.domNode.isTiddlyWikiFakeDom===true){return true}else{return!this.document.body.contains(this.getContainer())}};MapWidget.prototype.fitGraph=function(e,t){window.clearTimeout(this.activeFitTimeout);t=t||0;e=e||0;var i=function(){if(this.isZombieWidget())return;this.network.redraw();this.network.fit({animation:{duration:t,easingFunction:\"easeOutQuart\"}})};this.activeFitTimeout=window.setTimeout(i.bind(this),e)};MapWidget.prototype.handleInsertNode=function(e){var t=\"addNodeToMap\";this.dialogManager.open(t,null,function(t,i){if(!t)return;var s=utils.getField(i,\"draft.title\");if(utils.tiddlerExists(s)){if(utils.isMatch(s,this.view.getNodeFilter(\"compiled\"))){$tm.notify(\"Node already exists\");return}else{e=$tm.adapter.makeNode(s,e);this.view.addNode(e)}}else{var a=new $tw.Tiddler(i,{\"draft.title\":null});e.label=s;$tm.adapter.insertNode(e,this.view,a)}this.preventFitAfterRebuild=true})};MapWidget.prototype.handleEditNode=function(e){var t=$tm.indeces.tById[e.id];var i=utils.getTiddler(t);var s=JSON.stringify($tm.config.vis);var a=this.view.getConfig(\"vis\");var r={};r[e.id]=e;var o=$tm.adapter.getInheritedNodeStyles(r);var n=JSON.stringify(o[t]);var d=JSON.stringify(utils.merge({},{color:i.fields[\"color\"]},utils.parseJSON(i.fields[\"tmap.style\"])));var l=this.view.getLabel();var h={id:e.id};var g=this.view.getNodeData(e.id,true)||{};delete g.x;delete g.y;var p={view:l,tiddler:i.fields.title,tidColor:i.fields[\"color\"],tidIcon:i.fields[$tm.field.nodeIcon]||i.fields[\"tmap.fa-icon\"],tidLabelField:\"global.\"+$tm.field.nodeLabel,tidIconField:\"global.\"+$tm.field.nodeIcon,dialog:{preselects:{\"inherited-global-default-style\":s,\"inherited-local-default-style\":a,\"inherited-group-styles\":n,\"global.tmap.style\":d,\"local-node-style\":JSON.stringify(g)}}};var u=function(e,t,i){for(var s=i.length;s--;){p.dialog.preselects[e+\".\"+i[s]]=t[i[s]]||\"\"}};u(\"local\",g,[\"label\",\"tw-icon\",\"fa-icon\",\"open-view\"]);u(\"global\",i.fields,[$tm.field.nodeLabel,$tm.field.nodeIcon,\"tmap.fa-icon\",\"tmap.open-view\"]);this.dialogManager.open(\"editNode\",p,function(i,s){if(!i)return;var a=s.fields;var r=utils.getPropertiesByPrefix(a,\"global.\",true);for(var o in r){utils.setField(t,o,r[o]||undefined)}var n=utils.getPropertiesByPrefix(a,\"local.\",true);var d=utils.parseJSON(a[\"local-node-style\"],{});for(var o in n){d[o]=n[o]||undefined}this.view.saveNodeStyle(e.id,d);this.preventFitAfterRebuild=true})};MapWidget.prototype.handleVisSingleClickEvent=function(e){var t=utils.isTrue($tm.config.sys.singleClickMode);if(t&&!this.editorMode){this.handleOpenMapElementEvent(e)}};MapWidget.prototype.handleVisDoubleClickEvent=function(e){if(e.nodes.length||e.edges.length){if(this.editorMode||!utils.isTrue($tm.config.sys.singleClickMode)){this.handleOpenMapElementEvent(e)}}else{if(this.editorMode){this.handleInsertNode(e.pointer.canvas)}}};MapWidget.prototype.handleOpenMapElementEvent=function(e){if(e.nodes.length){var t=this.graphData.nodesById[e.nodes[0]];if(t[\"open-view\"]){$tm.notify(\"Switching view\");this.setView(t[\"open-view\"])}else{this.openTiddlerWithId(e.nodes[0])}}else if(e.edges.length){this.logger(\"debug\",\"Clicked on an Edge\");var i=this.graphData.edgesById[e.edges[0]].type;this.handleEditEdgeType(i)}else{return}this.hidePopups(0,true)};MapWidget.prototype.handleEditEdgeType=function(e){if(!this.editorMode)return;var t=$tm.config.sys.edgeClickBehaviour;if(t!==\"manager\")return;$tw.rootWidget.dispatchEvent({type:\"tmap:tm-manage-edge-types\",paramObject:{type:e}})};MapWidget.prototype.handleResizeEvent=function(e){if(this.isZombieWidget())return;var t=this.getAttr(\"height\");var i=this.getAttr(\"width\");if(this.isInSidebar){var s=this.domNode.getBoundingClientRect();var a=15;i=document.body.clientWidth-s.left-a+\"px\";var r=parseInt(this.getAttr(\"bottom-spacing\"))||15;var o=window.innerHeight-s.top;t=o-r+\"px\"}this.domNode.style.height=t||\"300px\";this.domNode.style.width=i;this.repaintGraph()};MapWidget.prototype.handleClickEvent=function(e){if(this.isZombieWidget()||!this.network)return;if(!this.graphDomNode.contains(e.target)){var t=this.network.getSelection();if(t.nodes.length||t.edges.length){this.logger(\"debug\",\"Clicked outside; deselecting nodes/edges\");this.network.selectNodes([]);this.resetVisManipulationBar()}}else{this.canvas.focus()}this.contextMenu.hide(0,true)};MapWidget.prototype.handleVisSelectNode=function(e){this.assignActiveStyle(e.nodes)};MapWidget.prototype.assignActiveStyle=function(e){if(!Array.isArray(e))e=[e];var t=this.visOptions.nodes.color;for(var i=e.length;i--;){var s=e[i];var a=this.graphData.nodesById[s];var r=utils.merge({},t,a.color);this.graphData.nodes.update({id:s,color:{highlight:r,hover:r}})}};MapWidget.prototype.handleVisDeselectNode=function(e){};MapWidget.prototype.handleVisDragEnd=function(e){if(!e.nodes.length)return;this.setNodesMoveable(e.nodes,false)};MapWidget.prototype.handleVisBeforeDrawing=function(e){if(this.backgroundImage){e.drawImage(this.backgroundImage,0,0)}};MapWidget.prototype.constructTooltip=function(e,t){var i=utils.parseJSON(e);var s=i.node||i.edge;var a=null;var r=\"text/html\";var o=\"text/vnd-tiddlywiki\";if(i.node){var n=$tm.indeces.tById[s];var d=utils.getTiddler(n);var l=d.fields[$tm.field.nodeInfo];if(l){t.innerHTML=$tw.wiki.renderText(r,o,l)}else if(d.fields.text){utils.registerTransclude(this,\"tooltipWidget\",n);this.tooltipWidget.setVariable(\"tv-tiddler-preview\",\"yes\");this.tooltipWidget.render(t)}else{t.innerHTML=n}}else{var h=this.graphData.edgesById[s];var g=$tm.indeces.allETy[h.type];if(g.description){a=$tw.wiki.renderText(r,o,g.description)}t.innerHTML=a||g.label||g.id}};MapWidget.prototype.handleVisHoverElement=function(e){if($tm.mouse.buttons)return;var t=e.node||e.edge;var i=JSON.stringify(e);if(e.node){this.assignActiveStyle(t)}if(!this.isVisInEditMode()&&!this.contextMenu.isShown()){var s=this.constructTooltip;var i=JSON.stringify(e);this.tooltip.show(i,s)}};MapWidget.prototype.handleVisBlurElement=function(e){this.tooltip.hide()};MapWidget.prototype.handleVisLoading=function(e){this.graphLoadingBarDomNode.style.display=\"block\";this.graphLoadingBarDomNode.setAttribute(\"max\",e.total);this.graphLoadingBarDomNode.setAttribute(\"value\",e.iterations)};MapWidget.prototype.handleVisLoadingDone=function(e){\nthis.graphLoadingBarDomNode.style.display=\"none\"};MapWidget.prototype.handleVisDragStart=function(e){if(e.nodes.length){this.hidePopups(0,true);this.assignActiveStyle(e.nodes);this.setNodesMoveable(e.nodes,true)}};MapWidget.prototype.destruct=function(){utils.setDomListeners(\"remove\",window,this.windowDomListeners);utils.setDomListeners(\"remove\",this.domNode,this.widgetDomListeners);this._destructVis()};MapWidget.prototype._destructVis=function(){if(!this.network)return;utils.setDomListeners(\"remove\",this.canvas,this.canvasDomListeners);this.network.destroy();this.network=null};MapWidget.prototype.openTiddlerWithId=function(e){var t=$tm.indeces.tById[e];this.logger(\"debug\",\"Opening tiddler\",t,\"with id\",e);if(this.enlargedMode===\"fullscreen\"){var i=this.wiki.findDraft(t);var s=!!i;if(!s){var a=\"tm-edit-tiddler\";this.dispatchEvent({type:a,tiddlerTitle:t});i=this.wiki.findDraft(t)}var r={draftTRef:i,originalTRef:t};var o=\"fullscreenTiddlerEditor\";this.dialogManager.open(o,r,function(e,a){if(e){var r=\"tm-save-tiddler\";this.dispatchEvent({type:r,tiddlerTitle:i})}else if(!s){utils.deleteTiddlers([i])}var r=\"tm-close-tiddler\";this.dispatchEvent({type:r,tiddlerTitle:t})})}else{var n=this.domNode.getBoundingClientRect();this.dispatchEvent({type:\"tm-navigate\",navigateTo:t,navigateFromTitle:this.getVariable(\"storyTiddler\"),navigateFromNode:this,navigateFromClientRect:{top:n.top,left:n.left,width:n.width,right:n.right,bottom:n.bottom,height:n.height}})}};MapWidget.prototype.getViewHolderRef=function(){if(this.viewHolderRef){return this.viewHolderRef}this.logger(\"info\",\"Retrieving or generating the view holder reference\");var e=this.getAttr(\"view\");if(e){this.logger(\"log\",'User wants to bind view \"'+e+'\" to graph');var t=$tm.path.views+\"/\"+e;if(this.wiki.getTiddler(t)){var i=$tm.path.localHolders+\"/\"+utils.genUUID();this.logger(\"log\",'Created an independent temporary view holder \"'+i+'\"');utils.setText(i,t);this.logger(\"log\",'View \"'+t+'\" inserted into independend holder')}else{this.logger(\"log\",'View \"'+e+'\" does not exist')}}if(typeof i===\"undefined\"){this.logger(\"log\",\"Using default (global) view holder\");var i=$tm.ref.defaultViewHolder}return i};MapWidget.prototype.setView=function(e,t){e=new ViewAbstraction(e);if(!e.exists())return;var i=e.getLabel();t=t||this.viewHolderRef;this.logger(\"info\",\"Inserting view '\"+i+\"' into holder '\"+t+\"'\");this.wiki.addTiddler(new $tw.Tiddler({title:t,text:i}))};MapWidget.prototype.getView=function(e){if(!e&&this.view){return this.view}var t=this.getViewHolderRef();var i=utils.getText(t);var s=new ViewAbstraction(i);this.logger(\"debug\",\"Retrieved view from holder\");if(!s.exists()){this.logger(\"debug\",'Warning: View \"'+i+\"\\\" doesn't exist. Default is used instead.\");s=new ViewAbstraction(\"Default\")}return s};MapWidget.prototype.reloadBackgroundImage=function(e){this.backgroundImage=null;var t=this.view.getConfig(\"background_image\");var i=utils.getTiddler(t);if(!i&&!t)return;var s=new Image;var a=function(e){s.src=e};s.onload=function(){this.backgroundImage=s;this.repaintGraph();if(e){$tm.notify(e)}}.bind(this);if(i){var r=i.fields[\"_canonical_uri\"];if(r){utils.getImgFromWeb(r,a)}else if(i.fields.text){var o=$tw.utils.makeDataUri(i.fields.text,i.fields.type);s.src=o}}else if(t){utils.getImgFromWeb(t,a)}};MapWidget.prototype.getRefreshedDataSet=function(e,t,i){if(!i){return new vis.DataSet(utils.getValues(e))}if(t)i.remove(Object.keys(t));i.update(utils.getValues(e));return i};MapWidget.prototype.repaintGraph=function(){var e=$tw.utils.hasClass(this.document.body,\"tmap-has-fullscreen-widget\");if(this.network&&(!e||e&&this.enlargedMode)){this.logger(\"info\",\"Repainting the whole graph\");this.network.redraw();this.fitGraph(0,1e3)}};MapWidget.prototype.setGraphButtonEnabled=function(e,t){var i=\"vis-button\"+\" \"+\"tmap-\"+e;var s=utils.getFirstElementByClassName(i,this.domNode);$tw.utils.toggleClass(s,\"tmap-button-enabled\",t)};MapWidget.prototype.dialogPostProcessor=function(){this.network.selectNodes([]);this.resetVisManipulationBar()};MapWidget.prototype.setNodesMoveable=function(e,t){if(!e||!e.length||this.view.isEnabled(\"physics_mode\")){return}var i=[];var s=!t;for(var a=e.length;a--;){i.push({id:e[a],fixed:{x:s,y:s}})}this.graphData.nodes.update(i);if(s){this.logger(\"debug\",\"Fixing\",i.length,\"nodes\");this.handleStorePositions()}};MapWidget.prototype.addGraphButtons=function(e){var t=utils.getFirstElementByClassName(\"vis-navigation\",this.domNode);for(var i in e){var s=this.document.createElement(\"div\");s.className=\"vis-button \"+\" \"+\"tmap-\"+i;s.addEventListener(\"click\",e[i].bind(this),false);t.appendChild(s);this.setGraphButtonEnabled(i,true)}};",
"title": "$:/plugins/felixhayashi/tiddlymap/js/widget/MapWidget",
"type": "application/javascript",
"module-type": "widget"
},
"$:/plugins/felixhayashi/tiddlymap/license": {
"title": "$:/plugins/felixhayashi/tiddlymap/license",
"subtitle": "License",
"caption": "License",
"text": "\\rules except wikilink\n\n!! TiddlyMap\n\nCopyright (c) 2014, Felix Küppers\nAll rights reserved.\n\nTiddlyMap is licensed under the [[BSD 2-Clause License|http://opensource.org/licenses/BSD-2-Clause]]. For the exact license terms, please visit [[https://github.com/felixhayashi/TW5-TiddlyMap/blob/master/LICENSE]]. \n\n!! TiddlyWiki\n\nCreated by Jeremy Ruston, (jeremy [at] jermolene [dot] com)\n\nCopyright © Jeremy Ruston 2004-2007 Copyright © UnaMesa Association 2007-2014\n\nPublished under the following [licenses](https://github.com/Jermolene/TiddlyWiki5/tree/master/licenses):\n\n# BSD 3-clause \"New\" or \"Revised\" License (including any right to adopt any future version of a license if permitted)\n# Creative Commons Attribution 3.0 (including any right to adopt any future version of a license if permitted)\n\n!! Vis.js\n\nCopyright (c) 2014 [Almende B.V.](https://github.com/almende/vis)\n\nPublished under the following licenses:\n\n# Apache License Version 2.0, January 2004 http://www.apache.org/licenses/\n# MIT License (MIT)\n"
},
"$:/plugins/felixhayashi/tiddlymap/readme": {
"title": "$:/plugins/felixhayashi/tiddlymap/readme",
"text": "* Please refer to the project-readme hosted at [[https://github.com/felixhayashi/TW5-TiddlyMap]].\n* A demo with several examples and explanations can be found at [[http://tiddlymap.org]]."
},
"$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tmap:unknown": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tmap:unknown",
"description": "Automatically assigned to an edge that does not have a type assigned",
"style": "{\"color\":\"gray\"}",
"show-label": "false"
},
"$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-body:link": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-body:link",
"description": "A link that is contained in the tiddler's body pointing to another resource.",
"style": "{\"color\":\"orange\", \"dashes\":true}",
"label": "links to",
"text": ""
},
"$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-list:list": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-list:list",
"description": "Contained in a list of this tiddler",
"style": "{ \"color\": \"red\", \"dashes\":true}",
"label": "listed in",
"text": ""
},
"$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-list:tags": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes/tw-list:tags",
"description": "A tag that refers to a tiddler of the same name.",
"style": "{ \"color\": \"DarkSlateGray\", \"dashes\":true}",
"label": "tagged with"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/default": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/default",
"caption": "Overview",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-plain\">\n Please visit the [[online docs|http://tiddlymap.org/Documentation]]\n for more information about the available global options.\n</div>\n<table class=\"tmap-key-value-table\">\n <tr>\n <th align=\"left\">Plugin version</th>\n <td><<pluginVersion>></td>\n </tr>\n<!--\n <tr>\n <th align=\"left\">Datastructure version</th>\n <td><<dataStructureVersion>></td>\n </tr>\n-->\n <tr>\n <th align=\"left\">Nodes in system</th>\n <td><<numberOfNodes>></td>\n </tr>\n <tr>\n <th align=\"left\">Edges in system</th>\n <td><<numberOfEdges>></td>\n </tr>\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/editor": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/editor",
"caption": "Editor",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-checkbox\"\n title:\"Show Neighbour­hood button\"\n field:\"config.sys.editorMenuBar.showNeighScopeButton\" \n descr:\"Show or hide the neighbourhood scope button from the menu.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Show Screen­shot button\"\n field:\"config.sys.editorMenuBar.showScreenshotButton\" \n descr:\"Show or hide the screenshot button.\">>\n</table> \n"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/fields": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/fields",
"caption": "Field settings",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-text\"\n title:\"Node-icon field\"\n field:\"config.sys.field.nodeIcon\" \n descr:\"Local image used as node image in the graphs.\">>\n <<tmap-row type:\"input-text\"\n title:\"Node-label field\"\n field:\"config.sys.field.nodeLabel\" \n descr:\"Alternative node label to use instead of the title.\">>\n <<tmap-row type:\"input-text\"\n title:\"Node-info field\"\n field:\"config.sys.field.nodeInfo\" \n descr:\"Field used as tooltip when hovering over a node in a graph.\"\n note:\"It is prohibited to use the text field here.\">>\n</table> \n\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/interaction": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/interaction",
"caption": "Interaction & behaviour",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n<!--\n <<tmap-row type:\"input-select\"\n title:\"Default node tooltip\"\n field:\"config.sys.defaultNodeTooltip\" \n descr:\"What to show when hovering over a node.\"\n nochoice:\"No\"\n selectFilter:\"[[nothing|Nothing]]\n [[manager|Open edge-type manager]]\">>\n-->\n <$macrocall type=\"input-select\"\n $name=\"tmap-row\"\n title=\"Default startup view\"\n field=\"config.sys.defaultView\"\n nochoice=\"Last view used at startup\"\n selectFilter=<<tmap \"option\" \"selector.allViewsByLabel\">>\n descr=\"The view to display at startup\" />\n <<tmap-row type:\"input-checkbox\"\n title:\"Show popups\"\n field:\"config.sys.popups.enabled\" \n descr:\"Set this to true if you want to see automatic\n popups in the map.\">>\n <$list filter=\"[config.sys.popups.enabled[true]]\">\n <<tmap-row type:\"input-text\"\n title:\"Popup delay\"\n field:\"config.sys.popups.delay\"\n descr:\"The time in miliseconds that needs to pass after\n a tooltip is triggered.\">>\n <<tmap-row type:\"input-text\"\n title:\"Popup width\"\n field:\"config.sys.popups.width\"\n descr:\"The default max-width of the popup.\"\n note:\"Make sure you added the desired unit (e.g. `px`).\n Requires a wiki refresh.\">>\n <<tmap-row type:\"input-text\"\n title:\"Popup height\"\n field:\"config.sys.popups.height\"\n descr:\"The default max-height of the popup.\"\n note:\"Make sure you added desired the unit (e.g. `px`).\n Requires a wiki refresh.\">>\n </$list>\n <<tmap-row type:\"input-checkbox\"\n title:\"Allow single click mode\"\n field:\"config.sys.singleClickMode\" \n descr:\"A single click on a node is sufficient to open the\n corresponding tiddler.\"\n note:\"Drag and drop will still work and does not cause a\n tiddler to be opened. Single click is never active in\n the map editor.\">>\n <<tmap-row type:\"input-select\"\n title:\"Edge click behaviour\"\n field:\"config.sys.edgeClickBehaviour\" \n selectFilter:\"[[nothing|Nothing]]\n [[manager|Open edge-type manager]]\"\n descr:\"What should happen when you click on an edge?\">>\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/liveTab": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/liveTab",
"caption": "Live tab",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-checkbox\"\n title:\"Show Live tab\"\n field:\"liveTab\" \n descr:\"Show or hide the live tab in the sidebar.\">>\n <$macrocall type=\"input-select\"\n $name=\"tmap-row\"\n title=\"Fallback view\"\n field=\"config.sys.liveTab.fallbackView\" \n selectFilter=<<tmap \"option\" \"selector.allViewsByLabel\">>\n descr=\"The view to display in the sidebar's live tab in\n case the current tiddler did not specify a view\n to open.\" />\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig",
"subtitle": "{{$:/core/images/options-button}} Global configuration of TiddlyMap",
"classes": "tmap-remove-top-space",
"text": "\\rules except wikilink\n\n<$macrocall $name=\"tabs\"\n default=<<concat \"$(template)$/default\">>\n tabsList=\"[all[shadows]prefix<template>] -[<template>]\"\n/>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/verbosity": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/verbosity",
"caption": "Verbosity",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-plain\">\n Here you can restrict the system's talkativeness.\n</div>\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-checkbox\"\n title:\"Debug output\"\n field:\"config.sys.debug\" \n descr:\"Set this to true if you want debug information to be\n displayed in the browser console.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Show notifications\"\n field:\"config.sys.notifications\" \n descr:\"Set this to true if you want to receive fade-out\n notifications for important events.\">>\n</table> "
},
"$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/vis": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/globalConfig/vis",
"classes": "tmap-remove-top-space",
"caption": "Graph",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n The global vis configurations will affect all views and their\n elements (nodes and edges) unless they are overridden on a lower\n level. All options below are documented at\n [[vis.js.org|http://visjs.org/docs/network]].\n</div>\n<div class=\"tmap-flash-message tmap-info\">\n Only config items that you actually changed have an effect on\n the graph. Other options are visible, yet, inactive.\n</div>\n<$tmap-config\n mode=\"manage-config\"\n inherited=\"vis-inherited\"\n extension=\"config.vis\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView/default": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView/default",
"caption": "Overview",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n All configurations __only__ affect this view.\n</div>\n\n<table class=\"tmap-key-value-table\">\n <tr>\n <th align=\"left\">Created on</th>\n <td><<createdOn>></td>\n </tr>\n <tr>\n <th align=\"left\">Nodes contained in graph</th>\n <td><<numberOfNodes>></td>\n </tr>\n <tr>\n <th align=\"left\">Edges contained in graph</th>\n <td><<numberOfEdges>></td>\n </tr>\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView/editFilters": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView/editFilters",
"caption": "Edit filters",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n Completely new to filters? Please read\n [[Introduction to filter notation|http://tiddlywiki.com/#Introduction%20to%20filter%20notation]]\n first.\n</div>\n\n<fieldset>\n <legend>Filters <sup>[1]</sup></legend>\n <table class=\"tmap-config-table tmap-large-input\">\n <<tmap-row type:\"input-textarea\"\n title:\"Node filter\"\n field:\"filter.prettyNodeFltr\"\n descr:\"In the map, only those tiddlers that match this filter\n are shown. Drafts and system tiddlers are automatically\n excluded.\">>\n <<tmap-row type:\"input-textarea\"\n title:\"Edge-type filter\"\n field:\"filter.prettyEdgeFltr\" \n descr:\"Only edges with a type that matches the filter are shown.\">>\n </table> \n</fieldset>\n\n---\n\n<sup>[1]</sup> In the editors above, a new line is equivalent to a space symbol.<br />\n<sup>[2]</sup> It is suggested to read\n[[Node and edge-type filters|http://tiddlymap.org#Node%20and%20edge-type%20filters]]\nand [[Edge-type namespaces|http://tiddlymap.org#Node%20and%20edge-type%20filters]]\nbefore using Tiddlymap's filter editor."
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView/layout": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView/layout",
"caption": "Layout",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-checkbox\"\n title:\"Floating nodes\"\n field:\"config.physics_mode\" \n descr:\"Set this to true if you want your nodes to freely\n swirl around.\">>\n <<tmap-row type:\"input-text\"\n title:\"Background image\"\n field:\"config.background_image\" \n descr:\"The title of an image tiddler to be used as background\n in the view.\"\n note:\"You can also use an image url directly, however, the\n image needs be stored under the same domain as your wiki.\n Otherwise, it won't be displayed!\">>\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView/namespace": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView/namespace",
"caption": "Namespace",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table tmap-small-input\">\n <<tmap-row type:\"input-text\"\n title:\"Edge-type namespace\"\n field:\"config.edge_type_namespace\" \n descr:\"A namespace (like `foaf` in `foaf:knows`) that will be\n automatically added to all edge types you create in\n this view. The namespace is only added if the types\n do not exist yet and do not have a namespace assigned yet.\n Namespaces are always hidden in the graph.\"\n note:\"Most likely, you don't want the edges created with this\n namespace to leak into other views, moreover, you don't\n want edges that do not possess the namespace ever to be\n shown here. In this case, use a private marker (`_`)\n in front of your namespace, e.g. `_mynamespace` and use\n an appropriate edge type filter, i.e. `+[prefix[_mynamespace]]`\n For further information see:\n \n * [[Edge-type namespaces|http://tiddlymap.org/#Edge-type%20namespaces]]\n * [[Private edge types|http://tiddlymap.org/#Private%20edge%20types]]\n \">>\n</table>\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView",
"subtitle": "{{$:/core/images/options-button}} View configuration -- <<view>>",
"text": "\\rules except wikilink\n\n\\define privateEdgeTypes() [[private edge-types|http://tiddlymap.org/#Private%20edge%20types]]\n\n<$macrocall $name=\"tabs\"\n default=<<concat \"$(template)$/default\">>\n tabsList=\"[all[shadows]prefix<template>] -[<template>]\"\n/>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/configureView/vis": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/configureView/vis",
"caption": "Graph",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n The local vis configurations will affect all\n elements (nodes and edges) of this view, unless they are\n overridden on a lower level. All options below are documented at\n [[vis.js.org|http://visjs.org/docs/network]].\n</div>\n<div class=\"tmap-flash-message tmap-info\">\n Only config items that you actually changed have an effect on the\n graph. Other options are visible, yet, inactive.\n</div>\n<$tmap-config\n mode=\"manage-config\"\n inherited=\"vis-inherited\"\n extension=\"config.vis\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/cannotDeleteViewDialog": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/cannotDeleteViewDialog",
"subtitle": "{{$:/core/images/locked-padlock}} You cannot delete this view!",
"buttons": "ok",
"text": "\\rules except wikilink\n\nIt is not possible to delete the current view as ''<<count>>'' tiddlers\nare referencing it. To delete the view you must first remove the tiddlymap\nwidgets in the tiddlers listed below or change their view attributes.\n\n''References''\n\n<ul>\n<$list filter=<<filter>> variable=\"item\">\n <li><$link><<item>></$link></li>\n</$list>\n</ul>\n\nAfter the references are removed, you may delete the view."
},
"$:/plugins/felixhayashi/tiddlymap/dialog/getConfirmation": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/getConfirmation",
"subtitle": "{{$:/core/images/import-button}} You must confirm in order to proceed!",
"text": "\\rules except wikilink\n\n<<message>>\n\n''Are you really sure you want to do this?''"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/createView": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/createView",
"subtitle": "{{$:/core/images/new-button}} Creating a new view",
"text": "\\rules except wikilink\n\n<table class=\"tmap-config-table\">\n <<tmap-row type:\"input-text\"\n title:\"View name\"\n field:\"name\" \n descr:\"The name for the new view. If no name is entered,\n the program will invent one for you.\"\n note:\"You cannot override an existing view. In this case,\n you need to delete the old view first! You must no use\n slashes (`/`) in the name.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Clone view\"\n field:\"clone\" \n descr:\"Use the view that is currently displayed in the\n editor as blueprint. The view will be an __exact__\n clone of the current one, only with a different \n name.\">>\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/deleteNodeDialog": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/deleteNodeDialog",
"subtitle": "{{$:/core/images/delete-button}} You are about to delete <<count>> nodes",
"text": "\\rules except wikilink\n\n''Please choose an option or abort:''\n\n<$radio tiddler=<<output>> field=\"delete-from\" value=\"system\">\n Delete nodes from system <sup>[1]</sup>\n</$radio><br />\n<$radio tiddler=<<output>> field=\"delete-from\" value=\"filter\">\n Delete nodes from graph's filter <sup>[2]</sup>\n</$radio>\n\nThe following nodes will be deleted:\n\n<ul>\n<$list filter=<<tiddlers>>>\n <li><$view tiddler={{!!title}} field=\"title\" /></li>\n</$list>\n</ul>\n\n---\n\n<sup>[1]</sup>\n<small>This will delete all nodes, their corresponding tiddlers and all connected edges.</small><br/>\n<sup>[2]</sup>\n<small>''Important:'' Removing a node from the graph's filter only works, if the node has been added in the map editor per double click or via \"Add Node\". If the node hasn't been added as mentioned above, you need to change the underlying tiddler in a way that it doesn't match your filter anymore, if you don't want it to be displayed in the graph.</small>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/dublicateIdInfo": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/dublicateIdInfo",
"subtitle": "{{$:/core/images/info-button}} Dublicate id detected",
"buttons": "ok_suppress",
"text": "\\rules except wikilink\n\nTiddlyMap requires the value of the id field (\"tmap.id\") to be\nunique in order to correctly identify nodes and tiddlers.\n\nThe tiddler \"<<param.changedTiddler>>\" had the same id as the\ntiddler \"<<param.existingTiddler>>\".\n\nTherefore TiddlyMap\n\n* assigned a new id to tiddler \"<<param.changedTiddler>>\"\n* removed all edges from \"<<param.changedTiddler>>\""
},
"$:/plugins/felixhayashi/tiddlymap/dialog/edgeNotVisible": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/edgeNotVisible",
"subtitle": "{{$:/core/images/info-button}} Edge will not be visible in view \"<<view>>\"",
"buttons": "ok_suppress",
"text": "\\rules except wikilink\n\nYou just created an edge of type\n<code><$text text=<<type>> /></code> that will not be\nvisible in this view because it doesn't match your\nedge-type filter settings.\n\nThe current edge-type filter of view \"<<view>>\" looks like this:\n\n<pre><code><$text text=<<eTyFilter>> /></code></pre>\n\nTo have the newly added type displayed in your view, adjust your\nedge-type filter accordingly. \n\nSome suggestions:\n\n<ul>\n <li>\n Explicitly add the type to the filter:\n <code><$text text=\"[[\" /><$text text=<<type>> /><$text text=\"]]\" /></code>\n </li>\n <li>\n <$set\n filter=\"[<type>regexp[:]splitbefore[:]]\"\n name=\"prefix\"\n emptyValue=<<tmap halfOfString \"$(type)$\">>>\n Add a filter rule (e.g. a prefix filter) that will match\n your type: <code>[prefix[<<prefix>>]]</code>\n </$set>\n </li>\n <li>Make your current view-filter less restrictive.</li>\n</ul>\n\nFor further information, please see:\n[[Node and edge-type filters|http://tiddlymap.org#Node%20and%20edge-type%20filters]]."
},
"$:/plugins/felixhayashi/tiddlymap/dialog/editNode/default": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/editNode/default",
"caption": "Global node style",
"classes": "tmap-remove-top-space",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n A node's ''global configuration''\n (also referred to as //global individual config//) defines its\n individual appearance and behaviour in all views.\n</div>\n<<maybeShowTidColorWarning>>\n \n<$macrocall $name=\"sharedSettings\"\n twIconField=<<tidIconField>>\n faIconField=\"global.tmap.fa-icon\"\n labelField=<<tidLabelField>> />\n\n<$macrocall $name=\"visConfiguration\"\n mode=\"manage-node-types\"\n extensionField=\"global.tmap.style\"\n styleName=\"node's global style\"\n inheritedList=\"[[inherited-global-default-style]]\n [[inherited-local-default-style]]\n [[inherited-group-styles]]\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/editNode/local": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/editNode/local",
"caption": "Local node style",
"classes": "tmap-remove-top-space",
"text": "\\rules except wikilink\n \n<div class=\"tmap-flash-message tmap-info\">\n The ''local node configuration'' \n (also referred to as //view-specific node configuration//)\n overrides the //global individual configuration// and only affects\n the node's appearance and behaviour in the current view.\n</div>\n<<maybeShowTidColorWarning>>\n\n<fieldset>\n <legend>Behaviour</legend>\n <table class=\"tmap-config-table\">\n <$macrocall type=\"input-select\"\n $name=\"tmap-row\"\n title=\"Open view\"\n field=\"local.open-view\"\n nochoice=\"Disabled\"\n selectFilter=<<tmap \"option\" \"selector.allViewsByLabel\">>\n descr=\"Clicking on this node will open the specified\n view instead of the tiddler represented by this node.\" />\n </table>\n</fieldset>\n\n<$macrocall $name=\"sharedSettings\"\n twIconField=\"local.tw-icon\"\n faIconField=\"local.fa-icon\"\n labelField=\"local.label\" />\n \n<$macrocall $name=\"visConfiguration\"\n mode=\"manage-node-types\"\n extensionField=\"local-node-style\"\n styleName=\"node's local style\"\n inheritedList=\"[[inherited-global-default-style]]\n [[inherited-local-default-style]]\n [[inherited-group-styles]]\n [[global.tmap.style]]\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/editNode": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/editNode",
"subtitle": "{{$:/core/images/edit-button}} Editing style of node \"<<tiddler>>\"",
"classes": "tmap-remove-top-space",
"text": "\\rules except wikilink\n\n\\define maybeShowTidColorWarning()\n <$list filter=\"[<tidColor>regexp[.+]]\">\n <div class=\"tmap-flash-message tmap-warning\">\n You have set the tiddler's color\n field to \"<<tidColor>>\". This value will be completely ignored\n when you change node's color properties in the vis editor below.\n </div>\n </$list>\n\\end\n\n\\define iconSettings(twIconField, faIconField)\n <fieldset>\n <legend>Icon Settings</legend>\n <table class=\"tmap-config-table\">\n <<tmap-row type:\"input-text\"\n title:\"TW-icon\"\n field:\"$twIconField$\"\n descr:\"A tiddlywiki image reference.\n For example '$:/core/icon' for Movotun Jack.\">>\n <<tmap-row type:\"input-text\"\n title:\"FA-icon\"\n field:\"$faIconField$\"\n descr:\"A Font Awesome icon code.\n For example 'f206' for the bicycle symbol.\">>\n </table>\n </fieldset>\n\\end\n\n\\define sharedSettings(twIconField, faIconField, labelField)\n <fieldset>\n <legend>General Settings</legend>\n <table class=\"tmap-config-table\">\n <<tmap-row type:\"input-text\"\n title:\"Label\"\n field:\"$labelField$\"\n descr:\"Use this value as node label.\">>\n </table>\n </fieldset>\n <!-- display icon fieldset -->\n <<iconSettings \"$twIconField$\" \"$faIconField$\">> \n\\end\n\n<$macrocall\n $name=\"tabs\"\n default=<<concat \"$(template)$/default\">>\n tabsList=\"[all[shadows]prefix<template>] -[<template>]\"\n/>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/draft": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/draft",
"caption": "Draft",
"text": "\\rules except wikilink\n\n<div class=\"tmap-modal-editor\">\n <$importvariables filter=\"[all[tiddlers+shadows]prefix[$:/core/macros/]]\">\n <$set name=\"currentTiddler\" value=<<draftTRef>> >\n <$transclude tiddler=\"$:/core/ui/EditTemplate\" field=\"text\" mode=\"block\" />\n </$set>\n </$importvariables>\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/original": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/original",
"caption": "Preview",
"text": "\\rules except wikilink\n\n<div class=\"tmap-modal-editor\">\n <$importvariables filter=\"[all[tiddlers+shadows]prefix[$:/core/macros/]]\">\n <$set name=\"currentTiddler\" value=<<draftTRef>> >\n <$transclude tiddler=\"$:/core/ui/ViewTemplate\" field=\"text\" mode=\"block\" />\n </$set>\n </$importvariables>\n</div>\n\n<!--\n<$set name=\"currentTiddler\" value=<<draftTRef>> >\n <$transclude tiddler=\"$:/core/ui/ViewTemplate\" field=\"text\" mode=\"block\" />\n</$set>-->\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor",
"subtitle": "{{$:/core/images/edit-button}} <<originalTRef>>",
"classes": "tmap-modal-fullscreen-editor tmap-remove-top-space",
"text": "\\rules except wikilink\n\n\\define defaultTab() $:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/original\n\n<$macrocall $name=\"tabs\"\n default=<<defaultTab>>\n tabsList=\"[all[shadows]prefix[$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenTiddlerEditor/]]\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/fieldChanged": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/fieldChanged",
"subtitle": "{{$:/core/images/info-button}} The field \"<<name>>\" changed",
"text": "\\rules except wikilink\n\nYou changed the field \"<<name>>\" from \"<<oldValue>>\" to \"<<newValue>>\".\n\nIt is recommended to let TiddlyMap copy all values from the former field \"<<oldValue>>\" to the new field \"<<newValue>>\" so the data stored in \"<<oldValue>>\" is not lost. This operation has to be done now or never.\n\nDo you want to move each tiddler's existing \"<<oldValue>>\" value to \"<<newValue>>\"? Please note that any value currently stored in \"<<newValue>>\" would consequently be overridden and the old field \"<<oldValue>>\" would be eventually removed!"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenNotSupported": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/fullscreenNotSupported",
"subtitle": "{{$:/core/images/info-button}} Your machine does not support fullscreen",
"buttons": "ok_suppress",
"text": "\\rules except wikilink\n\nPlease have a look [[here|http://caniuse.com/#feat=fullscreen]] to see a list of supported devices/browsers.\n\nSorry for this :("
},
"$:/plugins/felixhayashi/tiddlymap/dialog/addNodeToMap": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/addNodeToMap",
"subtitle": "{{$:/core/images/tag-button}} Add node",
"classes": "tmap-modal-add-node",
"text": "\\rules except wikilink\n\n\\define backButtonText() back to list\n\\define outputAndTemplate() [[$(output)$]] [[$(template)$]]\n\n\\define editor()\n <$button class=\"tmap-go-back tc-btn-invisible\">\n {{$:/core/images/chevron-left}} <<backButtonText>>\n <$action-deletefield $tiddler=<<temp>> more template />\n <$action-sendmessage\n $message=\"tmap:tm-clear-tiddler\"\n keep=\"draft.title\"\n title=<<output>> />\n </$button>\n \n <$list filter=\"[<output>get[draft.title]is[tiddler]]\">\n <div class=\"tmap-flash-message tmap-warning\">\n Tiddler already exists! Use another title or click\n \"<<backButtonText>>\" to cancel your edit.\n </div>\n </$list>\n \n <div class=\"tmap-modal-editor\">\n <table class=\"tmap-config-table\">\n <tr class=\"tmap-template-select\">\n <td>Template</td>\n <td>\n <$select\n tiddler=<<temp>>\n field=\"template\">\n <option value=\"\"></option>\n <$list filter=<<tmap \"option\" \"selector.allPotentialNodes\">>>\n <option><$view field=\"title\" /></option>\n </$list> \n </$select>\n <$button>Load\n <$action-sendmessage\n $message=\"tmap:tm-clear-tiddler\"\n keep=\"draft.title\"\n title=<<output>> />\n <$list filter=\"[<temp>get[template]]\" variable=\"template\">\n <$action-sendmessage\n $message=\"tmap:tm-merge-tiddlers\"\n tiddlers=<<outputAndTemplate>>\n output=<<output>> />\n <$action-deletefield $tiddler=<<output>> tmap.id tmap.edges />\n </$list>\n </$button>\n </td>\n <td></td>\n </tr>\n </table>\n <$importvariables filter=\"[all[tiddlers+shadows]prefix[$:/core/macros/]]\">\n <$set name=\"currentTiddler\" value=<<output>>>\n <$transclude tiddler=\"$:/core/ui/EditTemplate\" mode=\"block\" />\n </$set>\n </$importvariables>\n </div>\n\\end\n\n\\define search()\n<p>Add an existing tiddler to the map or create a new one.</p>\n<table id=\"tmap-search-table\">\n <tr>\n <td><b>Title:</b></td>\n <td>\n <$edit-text\n tiddler=<<output>>\n field=\"draft.title\"\n focus=\"true\"\n type=\"text\"\n tag=\"input\"\n default=\"\" />\n <$list filter=\"[<output>get[draft.title]!is[tiddler]]\">\n <$button\n tooltip=\"The tiddler does not exist yet and you may edit it\n before it is added to the map\">\n {{$:/core/images/edit-button}}\n <$action-setfield $tiddler=<<temp>> more=\"true\" />\n </$button> <sup>[1]</sup>\n </$list>\n </td>\n </tr>\n <tr>\n <td></td>\n <td>\n <$set name=\"term\" value={{!!draft.title}}>\n <ul class=\"tmap-small-list\">\n <$list filter=\"[search:title<term>!is[system]!has[draft.of]]\">\n <li>\n <$button class=\"tc-btn-invisible tmap-link\">\n <$view field=\"title\" />\n <$action-setfield $tiddler=<<output>> draft.title={{!!title}} />\n </$button>\n </li>\n </$list>\n </ul>\n </$set>\n </td>\n </tr>\n</table>\n\n<$list filter=\"[<output>get[draft.title]!is[tiddler]]\">\n<hr />\n<sup>[1]</sup>\n<small>\n The tiddler does not exist yet and you may edit it\n before it is added to the map\n</small>\n</$list>\n\\end\n\n<$list filter=\"[<temp>!has[more]]\" variable=\"item\"><<search>></$list>\n<$list filter=\"[<temp>has[more]]\" variable=\"item\"><<editor>></$list>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/renameView": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/renameView",
"subtitle": "{{$:/core/images/tag-button}} Please specify a view name",
"text": "\\rules except wikilink\n\n''Name:''\n<$edit-text focus=\"true\" tiddler=<<output>> field=\"text\" type=\"text\" tag=\"input\" default=\"\"\n class=\"tmap-trigger-field tmap-triggers-ok-button-on-enter\" />\n\nNote that ''<<count>>'' tiddlers are referencing this view.\n\n<$reveal type=\"nomatch\" text=\"0\" default=<<count>>>\n \nRenaming the view will cause the reference to be invalid.\nIt is recommended to first remove the tiddlymap widgets in\nthe tiddlers listed below or change their view attributes\naccordingly.\n\n''References''\n\n<ul>\n<$list filter=<<filter>> variable=\"item\">\n <li><$text text=<<item>> /></li>\n</$list>\n</ul>\n \n</$reveal>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/saveCanvas": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/saveCanvas",
"subtitle": "{{$:/core/images/options-button}} Save a snapshot image of view \"<<view>>\"",
"text": "\\rules except wikilink\n\n\\define preview()\n<div class=\"tmap-save-canvas-preview\">\n <$transclude tiddler=<<snapshot>> /><br />\n Measures: <<width>> × <<height>>\n</div>\n\\end\n\n<table class=\"tmap-config-table\">\n<!--\n <<tmap-row type:\"input-text\"\n title:\"Name\"\n field:\"name\">\n-->\n<$macrocall $name=\"tmap-row\"\n type=\"input-text\"\n title=\"Name\"\n field=\"name\"\n descr=<<preview>> />\n</table>\n\n<fieldset><legend>Options</legend>\n <table class=\"tmap-config-table\">\n <<tmap-row type:\"input-radio\"\n title:\"Action\"\n field:\"action\" \n selectFilter:\"[[download|Download]]\n [[wiki|Save in wiki]]\n [[placeholder|Use as placeholder for this view]]\"\n descr:\"Save the image by downloading it to your computer or\n save it as a tiddler in your wiki.<br /><br />\n A third option is to make TiddlyMap use this image as\n placeholder for the current view. Placeholders are used\n when tiddlers are exported in form of static html\n or when editing a tiddler while having the preview\n shown. In this case the title input is ignored.\">>\n </table>\n</fieldset>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/getEdgeType": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/getEdgeType",
"subtitle": "{{$:/plugins/felixhayashi/tiddlymap/icon}} Edge type specification",
"text": "\\rules except wikilink\n\\rules except underscore\n\n\\define filter() $(allEdgeTypes)$ +[search:title[$(term)$]]\n\n\\define badge(color, label, tooltip)\n<span style=\"background: $color$\" title=\"$tooltip$\">$label$</span>\n\\end\n\n\\define badges()\n<$tiddler tiddler={{!!text}}>\n<$set name=\"id\" value=<<tmap \"getETyId\" \"$(viewNS)$\">>>\n<$set name=\"isVisible\" value=<<tmap \"isETyVisible\" \"$(viewNS)$\" \"$(eTyFilter)$\">>>\n<div class=\"tmap-badges\">\n <span\n style=\"background: darkslategray\"\n title=\"Your input translates into this id.\">\n <<id>>\n </span>\n <$list filter=\"[<isVisible>regexp[true]]\">\n <<badge \"green\" \"visible\" \"Matches your view's filter\">>\n </$list>\n <$list filter=\"[<isVisible>regexp[false]]\">\n <<badge \"red\" \"not visible\" \"Doesn't match your view's filter\">>\n </$list>\n <$list filter=\"[<id>!regexp[^tmap:unknown$]]\" variable=\"item\">\n <$list filter=\"[<id>regexp[^_]]\">\n <<badge \"purple\" \"private\" \"Not shown in other views per default\">>\n </$list>\n <$list filter=\"[<id>regexp[.+:.+]]\">\n <<badge \"orange\" \"namespace\" \"This type is prefixed with a proper namespace\">>\n </$list>\n </$list> \n</div>\n</$set>\n</$set>\n</$tiddler>\n\\end\n\n\\define search()\n<p>\n You are about to connect \"<$text text=\"$(fromLabel)$\" />\"\n with \"<$text text=\"$(toLabel)$\" />\". Please specify a type.\n</p>\n<table id=\"tmap-search-table\">\n <tr>\n <td><b>Type:</b></td>\n <td>\n <$edit-text\n focus=\"true\"\n field=\"text\"\n type=\"text\"\n tag=\"input\"\n default=\"\"\n class=\"tmap-trigger-field tmap-triggers-ok-button-on-enter\" />\n <<badges>>\n </td>\n </tr>\n <tr>\n <td></td>\n <td>\n <$set name=\"term\" value={{!!text}}>\n <$set name=\"allEdgeTypes\" value=<<tmap \"option\" \"selector.allEdgeTypesById\">>>\n <ul class=\"tmap-small-list\">\n <$list filter=<<filter>>>\n <li>\n <$button class=\"tc-btn-invisible tmap-link\">\n <$view field=\"title\" />\n <$action-setfield $tiddler=<<output>> text={{!!title}} />\n </$button>\n </li>\n </$list>\n </ul>\n </$set>\n </$set>\n </td>\n </tr>\n</table>\n\\end\n\n<$list filter=\"[<temp>!has[more]]\" variable=\"item\"><<search>></$list>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog",
"text": "\\rules except wikilink\n\n<div class=<<classes>>>\n<$importvariables\n filter=\"[[$:/plugins/felixhayashi/tiddlymap/misc/macros]]\n [[$:/core/macros/tabs]]\">\n<$transclude tiddler=<<template>> mode=\"block\" />\n</$importvariables>\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/welcome": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/welcome",
"subtitle": "{{$:/core/images/info-button }} Welcome",
"buttons": "ok",
"text": "\\rules except wikilink\n\n<$list filter=\"[[$:/plugins/felixhayashi/topstoryview]]\">\n<div class=\"tmap-flash-message tmap-success\">\n TiddlyMap configured your wiki for optimal use. Please save &\n restart after closing this dialog.\n</div>\n</$list>\n\nIt seems that you freshly installed TiddlyMap.\n\n* In case you need any help, please consult the [[online docs|http://tiddlymap.org#Documentation]] first.\n* You are welcome to create an [[issue|https://github.com/felixhayashi/TW5-TiddlyMap/issues]] at GitHub for any bug you discover.\n* Make sure to revisit the [[demo site|http://tiddlymap.org]] to see whether your version is up-to-date.\n* If you like TiddlyMap, please give it a star at [[GitHub|https://github.com/felixhayashi/TW5-TiddlyMap]] or tell your friends about it :)\n\nHave a great time.\n\n---\n\n''Please note:'' TiddlyMap is distributed under the [[BSD 2-Clause License|http://opensource.org/licenses/BSD-2-Clause]], which belongs to the same license family, as the license used by TiddlyWiki. By using this plugin you agree to the product's [[License Terms|https://github.com/felixhayashi/TW5-TiddlyMap/blob/master/LICENSE]]."
},
"$:/plugins/felixhayashi/tiddlymap/dialog/widgetCodeGenerator": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/widgetCodeGenerator",
"subtitle": "{{$:/core/images/permalink-button}} Widget Code Generator",
"buttons": "close",
"text": "\\rules except wikilink\n\n<div class=\"tmap-flash-message tmap-info\">\n Use the code below to embed a view in a tiddler.\n</div>\n\n<pre style=\"white-space: normal;\">\n<$tmap\n\n<$list filter=\"[<output>has[var.view]]\">\n view=\"<$view field='var.view' />\"</$list>\n<$list filter=\"[<output>field:var.click-to-use[true]]\">\n click-to-use=\"true\"</$list>\n<$list filter=\"[<output>has[var.editor]]\">\n editor=\"<$view field='var.editor' />\"</$list>\n<$list filter=\"[<output>has[var.width]]\">\n width=\"<$view field='var.width' />\"</$list>\n<$list filter=\"[<output>has[var.height]]\">\n height=\"<$view field='var.height' />\"</$list>\n<$list filter=\"[<output>has[var.class]]\">\n class=\"<$view field='var.class' />\"</$list>\n<$list filter=\"[<output>field:var.show-buttons[false]]\">\n show-buttons=\"false\"</$list>\n<$list filter=\"[<output>has[var.design]]\">\n design=\"<$view field='var.design' />\"</$list>></$tmap>\n</pre>\n\n<fieldset>\n <legend>Parameters</legend> \n <table class=\"tmap-config-table\">\n <$macrocall type=\"input-select\"\n $name=\"tmap-row\"\n title=\"View\"\n field=\"var.view\"\n nochoice=\" \"\n selectFilter=<<tmap \"option\" \"selector.allViewsByLabel\">>\n descr=\"The view to bind the wiedget to\" />\n <<tmap-row type:\"input-select\"\n title:\"Editor bar\"\n field:\"var.editor\"\n selectFilter:\"[[|Hidden]]\n [[vis|Simple]]\n [[advanced|Advanced]]\"\n descr:\"Whether the widget should act as an editor or not.\">>\n <<tmap-row type:\"input-select\"\n title:\"Design\"\n field:\"var.design\"\n selectFilter:\"[[|Normal]]\n [[plain|Plain]]\"\n descr:\"Usually a header is displayed and borders. Plain\n design will only show the mere graph.\">>\n <<tmap-row type:\"input-text\"\n title:\"Height\"\n field:\"var.height\"\n descr:\"Graph's height in css units. Defaults to '300px'.\">>\n <<tmap-row type:\"input-text\"\n title:\"Width\"\n field:\"var.width\"\n descr:\"Graph's width in css units. Defaults to '100%'.\">>\n <<tmap-row type:\"input-text\"\n title:\"Class\"\n field:\"var.class\"\n descr:\"A custom class to apply your own css.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Click to use\"\n field:\"var.click-to-use\"\n default:\"false\"\n descr:\"A click is needed to enable the graph.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Show buttons\"\n field:\"var.show-buttons\"\n default:\"true\"\n descr:\"Show or hide the graph's navigation buttons.\">>\n </table>\n</fieldset>"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter/close": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter/close",
"text": "\\rules except wikilink\n\n<$button class=\"tmap-dialog-button tmap-close-button\" tooltip=\"Close this dialog\">Close\n\n <!-- trigger dialog callback -->\n <$action-setfield $tiddler=<<result>> text=\"1\" />\n \n</$button>\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok",
"text": "\\rules except wikilink\n\n<$button class=\"tmap-dialog-button tmap-ok-button\" tooltip=\"Confirm dialog\">OK\n\n <!-- trigger dialog callback -->\n <$action-setfield $tiddler=<<result>> text=\"1\" />\n \n</$button>\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok_cancel": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok_cancel",
"text": "\\rules except wikilink\n\n<$transclude tiddler=\"$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok\" mode=\"inline\" />\n<$button class=\"tmap-dialog-button tmap-cancel-button\" tooltip=\"Close dialog without saving\">Cancel\n <!-- trigger dialog callback -->\n <$action-setfield $tiddler=<<result>> text=\"\" />\n</$button>\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok_suppress": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter/ok_suppress",
"text": "\\rules except wikilink\n\n<$set name=\"currentTiddler\" value=<<title>> >\n\n<$checkbox field=\"suppress\" checked=\"1\" unchecked=\"0\" default=\"0\"> Do not show this dialog again</$checkbox>\n<$button class=\"tmap-dialog-button tmap-ok-button\" tooltip=\"Confirm this dialog\">OK\n\n <!-- trigger dialog callback -->\n <$action-setfield $tiddler=<<result>> text=\"1\" />\n \n <!-- suppress dialog in the future -->\n <$action-sendmessage $message=\"tmap:tm-suppress-dialog\"\n dialog=<<templateId>>\n suppress={{!!suppress}} />\n \n</$button>\n\n</$set>"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter",
"text": "\\rules except wikilink\n\n\\define footer() $:/plugins/felixhayashi/tiddlymap/dialogFooter/$(buttons)$\n\n<$transclude tiddler=<<footer>> />\n\n<!-- we need this button to be able to close a tiddler from outside programmatically -->\n<$button class=\"tmap-hidden-close-button\" message=\"tm-close-tiddler\" />"
},
"$:/plugins/felixhayashi/tiddlymap/dialogFooter/element_type_manager": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialogFooter/element_type_manager",
"text": "\\rules except wikilink\n\n<$button\n class=\"tmap-dialog-button tmap-save-button\"\n tooltip=\"Save the current changes\">Save\n <$action-sendmessage\n $message=\"tmap:tm-save-type-form\"\n mode=<<mode>>\n output=<<output>> />\n</$button>\n<$button\n class=\"tmap-dialog-button tmap-cancel-button\"\n tooltip=\"Cancel the most resent changes and exit\">Quit\n <$action-setfield $tiddler=<<result>> text=\"1\" />\n</$button>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/deleteType": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/deleteType",
"caption": "Removal",
"text": "\\rules except wikilink\n\n\\define manage-edge-types()\n <$macrocall $name=\"tmap-row\"\n type=\"input-checkbox\"\n title=\"Delete type\"\n field=\"temp.deleteType\"\n default={{!id}}\n readonly={{!!temp.idImmutable}}\n descr=\"If you want to delete this type, set this to true\n and click the save button afterwards. Predefined system\n types cannot be deleted.\" note=\"Consequently, all edges\n of this type will be deleted.\" />\n\\end\n\n\\define manage-node-types()\n <$macrocall $name=\"tmap-row\"\n type=\"input-checkbox\"\n title=\"Delete type\"\n field=\"temp.deleteType\"\n default={{!id}}\n readonly={{!!temp.idImmutable}}\n descr=\"If you want to delete this type, set this to true and\n click the save button afterwards. Predefined system\n types cannot be deleted.\" />\n\\end\n\n<table class=\"tmap-config-table\"><$macrocall $name=<<mode>> /></table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/description": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/description",
"caption": "Description",
"text": "\\rules except wikilink\n\n\\define manage-edge-types()\n <<tmap-row type:\"input-textarea\"\n title:\"Description\"\n field:\"description\"\n descr:\"An optional description for this type. The\n description will be displayed as tooltip when\n moving the mouse over an edge of this type.\">>\n\\end\n\n\\define manage-node-types()\n <<tmap-row type:\"input-textarea\"\n title:\"Description\"\n field:\"description\" \n descr:\"An optional description for this type.\">>\n\\end\n\n<table class=\"tmap-config-table\">\n <$macrocall $name=<<mode>> />\n</table>\n\n"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/generalSettings": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/generalSettings",
"caption": "General",
"text": "\\rules except wikilink\n\n\\define manage-edge-types()\n <<tmap-row type:\"input-text\"\n title:\"Label\"\n field:\"label\" \n descr:\"An optional alias used as edge-label.\">>\n <<tmap-row type:\"input-checkbox\"\n title:\"Show label\"\n field:\"show-label\"\n default:\"true\"\n descr:\"If unchecked, no edge label will be displayed.\">>\n\\end\n\\define manage-node-types()\n <$list filter=\"[<currentTiddler>!regexp:id[tmap:]]\">\n <<tmap-row type:\"input-textarea\"\n title:\"Scope\"\n field:\"scope\" \n descr:\"A filter expression that defines, which nodes inherit\n this node-type and its style.\">>\n </$list>\n <$macrocall type=\"input-select\"\n $name=\"tmap-row\" \n title=\"Priority\"\n field=\"priority\"\n selectFilter=<<tmap \"scale\" \"100\">>\n descr=\"When a type has a a higher priority than another type,\n its style will override the other style\" />\n\\end\n\n<table class=\"tmap-config-table\">\n <$macrocall\n $name=\"tmap-row\"\n title=\"Identifier\"\n field=\"temp.newId\"\n type=\"input-text\"\n default={{!!id}}\n readonly={{!!temp.idImmutable}}\n descr=\"A unique identifier\"\n />\n <$macrocall $name=<<mode>> />\n</table>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/overview": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/overview",
"caption": "Overview",
"text": "\\rules except wikilink\n\n\\define date(f) <$view field=$f$ format=\"date\" template=\"DDth mmm hh:mm:ss\"/>\n\n! <$link to={{!!typeTRef}}><$view field=\"id\" /></$link>\n\n<table class=\"tmap-key-value-table\">\n <tr>\n <th align=\"left\">Created on</th>\n <td>\n <<date \"created\">>\n </td>\n </tr>\n <tr>\n <th align=\"left\">Modified on</th>\n <td><<date \"modified\">></td>\n </tr>\n <tr>\n <th align=\"left\">Usage count</th>\n <td>\n <span class=\"tmap-edge-type-specific\">\n <$view field=\"temp.usageCount\" />\n </span>\n <span class=\"tmap-node-type-specific\">\n <$count filter={{!!scope}}>0</$count>\n </span>\n </td>\n </tr>\n</table>\n\n<$view field=\"description\">//No description available//</$view>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/styling": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/styling",
"caption": "Styling",
"text": "\\rules except wikilink\n\n\\define url()\n <$set\n filter=\"[<mode>prefix[manage-edge-types]]\"\n name=\"module\"\n value=\"edges\"\n emptyValue=\"nodes\">\n [[visjs.org|http://visjs.org/docs/network/$(module)$]]\n </$set>\n\\end\n\n<fieldset class=\"tmap-node-type-specific\">\n <legend>Icon Settings</legend>\n <table class=\"tmap-config-table\">\n <<tmap-row type:\"input-text\"\n title:\"TW-icon\"\n field:\"tw-icon\"\n descr:\"A tiddlywiki image reference.\n For example '$:/core/icon' for Movotun Jack.\">>\n <<tmap-row type:\"input-text\"\n title:\"FA-icon\"\n field:\"fa-icon\"\n descr:\"A Font Awesome icon code.\n For example 'f206' for the bicycle symbol.\">>\n </table>\n</fieldset>\n\n<fieldset><legend>Visjs styles</legend>\n <div class=\"tmap-flash-message tmap-info\">\n All visjs options below are documented at <<url>>.\n </div>\n <div class=\"tmap-flash-message tmap-info\">\n Only config items that you actually changed have an effect on\n the graph. Other options are visible, yet, inactive.\n </div>\n <$tmap-config\n mode=<<mode>>\n inherited=\"vis-inherited\"\n extension=\"style\" />\n</fieldset>"
},
"$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager": {
"title": "$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager",
"subtitle": "{{$:/core/images/tag-button}} <<topic>>",
"buttons": "element_type_manager",
"classes": "tmap-remove-top-space",
"text": "\\rules except wikilink\n\n\\define defaultTab() \n$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/overview\n\\end\n\n\\define settingsTab()\n$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/generalSettings\n\\end\n\n\\define tabsFilter()\n[all[shadows]prefix[$:/plugins/felixhayashi/tiddlymap/dialog/MapElementTypeManager/]]\n\\end\n\n\\define searchFilter()\n$(searchSelector)$\n+[sort[title]nsort[priority]]\n+[removeprefix<typeRootPath>removeprefix[/]]\n+[search:title{$:/temp/tmap/MapElementTypeSearch}]\n\\end\n\n\\define managerClass() tmap-$(mode)$\n\n\\define typePath() $(typeRootPath)$/$(id)$\n\n<div id=\"tmap-element-type-manager\" class=<<managerClass>>>\n <div>\n <div class=\"tmap-searchbar\">\n <$edit-text\n focus=\"true\"\n tiddler=\"$:/temp/tmap/MapElementTypeSearch\"\n type=\"text\"\n tag=\"input\"\n default=\"\" />\n <$list filter=\"[{$:/temp/tmap/MapElementTypeSearch}regexp[.+]]\n +[addprefix[/]]\n +[addprefix<typeRootPath>]\n +[!is[tiddler]!is[shadow]]\">\n <$button tooltip=\"Create a new type of this name\">\n {{$:/core/images/new-button}}\n <$action-setfield $tiddler=\"$:/temp/tmap/MapElementTypeSearch\" text=\"\" />\n <$action-sendmessage\n $message=\"tmap:tm-create-type\"\n mode=<<mode>> id={{$:/temp/tmap/MapElementTypeSearch}}\n output=<<output>> />\n </$button>\n </$list>\n \n </div>\n <ul>\n <$list\n filter=<<searchFilter>>\n emptyMessage=<<noTypeFound>>\n variable=\"id\">\n <li>\n <span class=\"tmap-ranking tmap-node-type-specific\">\n # <$view tiddler=<<typePath>> field=\"priority\">1</$view>\n </span>\n <$button class=\"tc-btn-invisible tmap-link\"><<id>>\n <$action-setfield\n $tiddler=<<qualify \"$:/state/tabs/MapElementTypeManager\">>\n text=<<defaultTab>> />\n <$action-sendmessage\n $message=\"tmap:tm-load-type-form\"\n id=<<id>>\n mode=<<mode>>\n output=<<output>> />\n </$button>\n </li>\n </$list>\n </ul>\n </div>\n <div>\n <$reveal type=\"nomatch\" text=\"\" default={{!!id}} >\n <$macrocall\n $name=\"tabs\"\n default=<<defaultTab>>\n state=\"$:/state/tabs/MapElementTypeManager\"\n tabsList=<<tabsFilter>> />\n </$reveal>\n <$reveal type=\"match\" text=\"\" default={{!!id}} >\n <div class=\"tmap-flash-message tmap-info\">\n Please select a type from the list or create a new one by\n entering the type name in the search field on the left.\n </div>\n <div class=\"tmap-flash-message tmap-info tmap-node-type-specific\">\n The number next to the node-type label represents it's priority.\n </div>\n </$reveal>\n </div>\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/editor/contextMenu/node": {
"title": "$:/plugins/felixhayashi/tiddlymap/editor/contextMenu/node",
"text": "\\define single()\n <$list filter=\"\n [[tmap:tm-toggle-central-topic, $:/core/images/star-filled, Toggle central topic]]\n [[tmap:tm-delete-element, $:/core/images/delete-button, Delete node]]\">\n <$button class=\"tc-btn-invisible\">\n <$action-sendmessage $message=<<tmap \"splitAndSelect\" \", \" \"0\">> />\n <$transclude tiddler=<<tmap \"splitAndSelect\" \", \" \"1\">> />\n <<tmap \"splitAndSelect\" \", \" \"2\">>\n </$button>\n </$list>\n\\end\n\n\\define multi()\n <$list filter=\"\n [[tmap:tm-delete-element, $:/core/images/delete-button, Delete selected nodes]]\">\n <$button class=\"tc-btn-invisible\">\n <$action-sendmessage $message=<<tmap \"splitAndSelect\" \", \" \"0\">> />\n <$transclude tiddler=<<tmap \"splitAndSelect\" \", \" \"1\">> />\n <<tmap \"splitAndSelect\" \", \" \"2\">>\n </$button>\n </$list>\n\\end\n\n<div class=\"tc-drop-down\">\n <$macrocall $name=<<mode>> />\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/misc/advancedEditorBar": {
"title": "$:/plugins/felixhayashi/tiddlymap/misc/advancedEditorBar",
"text": "\\rules except wikilink\n\\define showEdgeField() show-$(curEdgeId)$\n\n<!-- === View Switcher ========================================== -->\n\n<div class=\"tmap-menu-bar\">\n View:\n <$reveal type=\"match\" text=\"false\" default=<<isViewBound>> >\n <$select\n tiddler=<<viewHolder>>\n field=\"text\"\n default=<<viewLabel>> >\n <$list filter=<<tmap \"option\" \"selector.allViewsByLabel\">> >\n <option value={{!!title}}>\n <$view tiddler={{!!title}} field=\"title\" />\n </option>\n </$list>\n </$select>\n </$reveal>\n <$reveal type=\"match\" text=\"true\" default=<<isViewBound>> >\n <b><<viewLabel>></b>\n </$reveal>\n\n<!-- === Menu =================================================== -->\n\n <$button\n popup=<<qualify \"$:/temp/menu\">>\n tooltip=\"Open the Menu\">{{$:/core/images/menu-button}}\n </$button>\n \n <$reveal type=\"popup\" position=\"below\" state=<<qualify \"$:/temp/menu\">> >\n <div class=\"tc-drop-down\">\n <a href=\"http://tiddlymap.org#Documentation\" target=\"_blank\">\n {{$:/core/images/info-button}} Open online help\n </a>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-create-view\">\n {{$:/core/images/new-button}} Create new view\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-generate-widget\">\n {{$:/core/images/permalink-button}} Grab widget code\n </$button>\n <div class=\"tmap-list-separator\">Global configurations:</div>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-configure-system\">\n {{$:/core/images/options-button}} Configure TiddlyMap\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-manage-edge-types\">\n <span class=\"tmap-unicode-icon\">◭</span> Manage edge-types\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-manage-node-types\">\n <span class=\"tmap-unicode-icon\">▢</span> Manage node-types\n </$button>\n <div class=\"tmap-view-actions\">\n <div class=\"tmap-list-separator\">Actions for this view:</div>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-edit-view\">\n {{$:/core/images/options-button}} Configure view\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-store-position\">\n {{$:/core/images/globe}} Save positions\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-rename-view\">\n {{$:/core/images/tag-button}} Rename view\n </$button>\n <$button class=\"tc-btn-invisible\" message=\"tmap:tm-delete-view\">\n {{$:/core/images/delete-button}} Delete view\n </$button>\n </div>\n </div>\n </$reveal>\n \n<!-- === Neighbourhood menu ===================================== -->\n\n <$reveal\n type=\"match\"\n text=\"true\"\n default=<<tmap \"option\"\n \"config.sys.editorMenuBar.showNeighScopeButton\">>>\n <$button\n class=<<neighScopeBtnClass>>\n tooltip=\"Change the neighbourhood scope\"\n popup=<<qualify \"$:/temp/neighScope\">>>☀\n </$button>\n </$reveal>\n \n <$reveal type=\"popup\" position=\"below\" state=<<qualify \"$:/temp/neighScope\">> >\n <div class=\"tc-drop-down\">\n <div class=\"tmap-list-separator\">Neighbourhood scope</div>\n <$button class=\"tc-btn-invisible\">None\n <$action-setfield\n $tiddler=<<viewRoot>>\n config.neighbourhood_scope=\"\" />\n </$button>\n <$list filter=\"[[1|1 step distance]]\n [[2|2 step distance]]\n [[3|3 step distance]]\n [[4|4 step distance]]\n [[5|5 step distance]]\">\n <$button class=\"tc-btn-invisible\">\n <<tmap \"splitAndSelect\" \"|\" \"1\">>\n <$action-setfield\n $tiddler=<<viewRoot>>\n config.neighbourhood_scope=<<tmap \"splitAndSelect\" \"|\" \"0\">> />\n </$button>\n </$list>\n <$button class=\"tc-btn-invisible\">No limit\n <$action-setfield\n $tiddler=<<viewRoot>>\n config.neighbourhood_scope=\"100\" />\n </$button>\n <div class=\"tmap-list-separator\">Neighbourhood traversal</div>\n <$radio field=\"config.neighbourhood_directions\" value=\"in\"> Incoming</$radio><br />\n <$radio field=\"config.neighbourhood_directions\" value=\"out\"> Outgoing</$radio><br />\n <$radio field=\"config.neighbourhood_directions\" value=\"\"> Both</$radio>\n <div class=\"tmap-list-separator\">Other</div>\n <$checkbox field=\"config.show_inter_neighbour_edges\"\n checked=\"true\" unchecked=\"false\"> Inter-neighbour edges</$checkbox>\n \n </div>\n </$reveal>\n \n<!-- === Export menu ============================================ -->\n \n <$reveal\n type=\"match\"\n text=\"true\"\n default=<<tmap \"option\"\n \"config.sys.editorMenuBar.showScreenshotButton\">>>\n <$button\n tooltip=\"Open the map-export menu\"\n popup=<<qualify \"$:/temp/mapExport\">>>\n {{$:/core/images/download-button}}\n </$button>\n </$reveal>\n \n <$reveal\n type=\"popup\"\n position=\"below\"\n state=<<qualify \"$:/temp/mapExport\">>>\n <div class=\"tc-drop-down\">\n <$button\n class=\"tc-btn-invisible\"\n tooltip=\"Export the graph and all its elements\n in form of a JSON file\">\n {{$:/core/images/permalink-button}} Save as JSON file\n <$action-sendmessage\n $message=\"tmap:tm-download-graph\"\n view=<<viewLabel>> />\n </$button>\n <$button\n class=\"tc-btn-invisible\"\n tooltip=\"Create a png image to download or save it\n as image or view-placeholder in your wiki\">\n {{$:/core/images/palette}} Save as png image\n <$action-sendmessage $message=\"tmap:tm-save-canvas\" />\n </$button>\n </div>\n </$reveal>\n \n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/misc/focusButton": {
"title": "$:/plugins/felixhayashi/tiddlymap/misc/focusButton",
"text": "\\define filter() [list[$:/temp/tmap/nodes/$(viewLabel)$]search:title{$:/temp/tmap/bar/search}]\n\\define concat(str) $str$\n\n\\define state() $(widgetPopupsPath)$/focus\n\n<div class=\"tmap-focus-button\">\n <$reveal type=\"match\" state=<<state>> text=\"\">\n <$button\n tooltip=\"Zoom on a specific node\"\n class=<<tv-config-toolbar-class>>>{{$:/core/images/advanced-search-button}}\n <$action-setfield $tiddler=\"$:/temp/tmap/bar/search\" text=\"\" />\n <$action-setfield $tiddler=<<state>> text=\"1\" />\n </$button>\n </$reveal>\n <$reveal type=\"nomatch\" state=<<state>> text=\"\">\n <$button\n tooltip=\"Close zoom popup\"\n class=<<tv-config-toolbar-class>>>{{$:/core/images/advanced-search-button}}\n <$action-setfield $tiddler=<<state>> text=\"\" />\n </$button>\n <div class=\"tmap-search-dropdown\">\n <div class=\"tc-drop-down\">\n <$edit-text\n focus=\"true\"\n tiddler=\"$:/temp/tmap/bar/search\"\n field=\"text\"\n type=\"text\"\n tag=\"input\"\n default=\"\" />\n <small><$count filter=<<filter>> /> results</small>\n <hr />\n <div class=\"tmap-very-small-list\">\n <$list filter=<<filter>>\n variable=\"item\"\n emptyMessage=\"//No results//\">\n <$button\n class=\"tc-btn-invisible\"\n message=\"tmap:tm-focus-node\"\n param=<<item>>>\n <$view tiddler=<<item>> field=\"title\" />\n </$button>\n </$list>\n </div>\n </div>\n </div>\n </$reveal>\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/hook/editor": {
"caption": "Map",
"tags": "$:/tags/SideBar",
"title": "$:/plugins/felixhayashi/tiddlymap/hook/editor",
"text": "\\define width() calc(100% - 15px)\n\n<div class=\"tmap-mobile-editor\">\n <div class=\"tmap-flash-message tmap-warning\">\n The editor is not displayed in mobile mode.\n </div>\n</div>\n<div class=\"tmap-desktop-editor\">\n <$tiddlymap\n class=\"tmap-sidebar-map-editor\"\n editor=\"advanced\"\n object-id=\"main_editor\"\n click-to-use=\"false\">\n </$tiddlymap>\n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/hook/liveTab": {
"title": "$:/plugins/felixhayashi/tiddlymap/hook/liveTab",
"caption": "Live",
"text": "\\define width() calc(100% - 15px)\n\n<div class=\"tmap-mobile-editor\">\n <div class=\"tmap-flash-message tmap-warning\">\n The live tab is not displayed in mobile mode.\n </div>\n</div>\n<div class=\"tmap-desktop-editor\">\n <$set name=\"view\"\n filter=\"[{$:/temp/tmap/currentTiddler}get[tmap.open-view]]\"\n emptyValue=<<tmap \"option\" \"config.sys.liveTab.fallbackView\">>>\n <div>\n <$tiddlymap\n view=<<view>>\n click-to-use=\"false\"\n refresh-triggers=\"$:/temp/tmap/currentTiddler\"\n object-id=\"live_tab\">\n </$tiddlymap>\n </div>\n </$set> \n</div>"
},
"$:/plugins/felixhayashi/tiddlymap/misc/quickConnectButton": {
"tags": "$:/tags/ViewToolbar",
"title": "$:/plugins/felixhayashi/tiddlymap/misc/quickConnectButton",
"description": "{{$:/language/Buttons/TiddlyMap/Hint}}",
"caption": "{{$:/plugins/felixhayashi/tiddlymap/icon}} {{$:/language/Buttons/TiddlyMap/Caption}}",
"text": "\\define buttonClass() $(tv-config-toolbar-class)$ $(additional-classes)$\n\n\\define nonExistentItem()\n<<item>> <span style=\"color: #9E9E9E\">(will be created)</span>\n\\end\n\n\\define noConnectionsMsg()\n<tr><td colspan=\"4\">//No connections found!//</td></tr>\n\\end\n\n\\define normalSearchFilter()\n[!is[system]!has[draft.of]search:title{$:/temp/quickConnectSearch}sortcs[title]limit[50]]\n\\end\n\n\\define regexSearchFilter()\n[!is[system]!has[draft.of]regexp{$:/temp/quickConnectSearch}sortcs[title]limit[50]]\n\\end\n\n\\define showButton(state)\n<$button set=\"$:/temp/tmap/state/popup/quickConnect\"\n setTo=\"$state$\" tooltip={{$:/language/Buttons/TiddlyMap/Hint}} \n aria-label={{$:/language/Buttons/TiddlyMap/Caption}}\n class=<<buttonClass>>>\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">{{$:/plugins/felixhayashi/tiddlymap/icon}}</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$:/language/Buttons/TiddlyMap/Caption}}/></span>\n</$list>\n</$button>\n\\end\n\n\\define searchResults()\n<td>\n <$button tooltip=\"Create incoming edge\">\n <<tmap \"option\" \"misc.arrows.in\">>\n <$action-sendmessage $message=\"tmap:tm-create-edge\"\n from=<<item>>\n to=<<currentTiddler>>\n force=\"true\"\n label={{$:/temp/quickConnectSearch/type}}\n view={{$:/temp/quickConnectSearch/view}} />\n </$button>\n</td>\n<td>\n <$button tooltip=\"Create outgoing edge\">\n <<tmap \"option\" \"misc.arrows.out\">>\n <$action-sendmessage $message=\"tmap:tm-create-edge\"\n from=<<currentTiddler>>\n to=<<item>>\n force=\"true\"\n label={{$:/temp/quickConnectSearch/type}}\n view={{$:/temp/quickConnectSearch/view}} />\n </$button>\n</td>\n<td>\n <$list\n filter=\"[<item>is[tiddler]]\"\n emptyMessage=<<nonExistentItem>>>\n <$view tiddler=<<item>> field=\"title\" />\n </$list>\n</td>\n\\end\n\n\\define hidePopup()\n<$macrocall $name=\"showButton\" state=<<qualify>> />\n\\end\n\n\\define showPopup()\n<$set name=\"additional-classes\" value=\"tmap-active-button\">\n <$macrocall $name=\"showButton\" state=\"\" />\n</$set>\n<$set\n name=\"searchFilter\"\n filter=\"[field:title[$:/state/tmap/tid-toolbar]has[re-filter]]\"\n value=<<regexSearchFilter>>\n emptyValue=<<normalSearchFilter>>>\n<div class=\"tmap-quick-connect tc-reveal tc-popup\">\n <div class=\"tc-drop-down\">\n <div class=\"title\">Create connection</div>\n <table class=\"tmap-quick-connect-search-bar\">\n <tr>\n <td>Type:</td>\n <td>\n <$edit-text\n tiddler=\"$:/temp/quickConnectSearch/type\"\n field=\"text\"\n type=\"text\"\n tag=\"input\"\n default=\"\" />\n <$select tiddler=\"$:/temp/quickConnectSearch/type\" default=\"\">\n <option></option>\n <$list filter=<<tmap \"option\" \"selector.allEdgeTypesById\">>>\n <option>{{!!title}}</option>\n </$list>\n </$select>\n </td>\n </tr>\n <tr>\n <td>Search:</td>\n <td>\n <$edit-text tiddler=\"$:/temp/quickConnectSearch\" type=\"text\" tag=\"input\" default=\"\"></$edit-text>\n <$checkbox\n tiddler=\"$:/state/tmap/tid-toolbar\"\n field=\"re-filter\"\n checked=\"1\"\n unchecked=\"\"\n default=\"\"> regexp\n </$checkbox>\n<!--\n <small>(<$count filter=<<searchFilter>> /> results)</small>\n-->\n </td>\n </tr>\n </table>\n <table class=\"tmap-create-connection-table\">\n <tr>\n <td colspan=\"2\">\n <table class=\"tmap-very-small-list\">\n <$list\n filter=<<searchFilter>>\n variable=\"item\">\n <tr><<searchResults>></tr>\n </$list>\n <tr>\n <$list filter=\"[{$:/temp/quickConnectSearch}regexp[.+]] -[is[tiddler]]\" variable=\"item\">\n <<searchResults>>\n </$list>\n </tr>\n </table>\n </td>\n </tr>\n </table>\n <div class=\"title\">Existing Connections</div>\n <div class=\"tmap-quick-connect-existing-bar\">\n <$select\n tiddler=\"$:/state/tmap/tid-toolbar\"\n field=\"direction\"\n default=\"both\">\n <option value=\"both\">both</option>\n <option value=\"in\">incoming</option>\n <option value=\"out\">outgoing</option>\n </$select>\n <$checkbox\n tiddler=\"$:/state/tmap/tid-toolbar\"\n field=\"filter.links\"\n checked=\"-[[tw-body:link]]\"\n unchecked=\"\"\n default=\"\"> hide links\n </$checkbox>\n </div>\n <table class=\"tmap-connection-table\">\n<!--\n <tr>\n <th></th>\n <th>Tiddler</th>\n <th>Type</th>\n <th></th>\n </tr>\n-->\n \n <$tmap-connections\n filter=<<tmap mergeFields \"$:/state/tmap/tid-toolbar\" \"filter.\">>\n direction={{$:/state/tmap/tid-toolbar!!direction}}\n emptyMessage=<<noConnectionsMsg>>>\n <tr>\n <td title=<<direction>>><<directionSymbol>></td>\n <td><$link to=<<neighbour>>><$view field=\"title\" /></$link></td>\n <td><<edge.type>></td>\n <td>\n <$button\n tooltip=\"Delete this connection\"\n class=\"tc-btn-invisible\">{{$:/core/images/close-button}}\n <$action-sendmessage $message=\"tmap:tm-remove-edge\"\n id=<<edge.id>>\n from=<<edge.from>>\n to=<<edge.to>>\n type=<<edge.type>> />\n </$button>\n </td>\n </tr>\n </$tmap-connections>\n </table> \n </div>\n</div>\n</$set>\n\\end\n\n<$list filter=\"[all[current]is[tiddler]]\"><$list filter=\"[{$:/temp/tmap/state/popup/quickConnect}prefix<qualify>]\" variable=\"item\" emptyMessage=<<hidePopup>>><<showPopup>></$list></$list>"
},
"$:/plugins/felixhayashi/tiddlymap/media/fullscreen.png": {
"title": "$:/plugins/felixhayashi/tiddlymap/media/fullscreen.png",
"type": "image/png",
"text": 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8Pl/BDX13d/enAL4zLA4WiyWlaVpi8+bNaVVVF8rKyjJ5G5yZmXknkUhYdF1/b25uTs2fOkge6uzsPL/iI4zf75fHjx93KoryjclkgtGfgSQMI0B+YovvSXbV19efdrvdKz/CvDyBbDbbTPITkjtFRBOR54ZPclJEbgL4weFw/LYcMK9/AFcdm7xTEIntAAAAAElFTkSuQmCC"
},
"$:/plugins/felixhayashi/tiddlymap/media/halfscreen.png": {
"title": "$:/plugins/felixhayashi/tiddlymap/media/halfscreen.png",
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"title": "$:/plugins/felixhayashi/tiddlymap/icon",
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},
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"title": "$:/plugins/felixhayashi/tiddlymap/media/surface.png",
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"
},
"$:/language/Buttons/TiddlyMap/Caption": {
"title": "$:/language/Buttons/TiddlyMap/Caption",
"text": "tiddlymap"
},
"$:/language/Buttons/TiddlyMap/Hint": {
"title": "$:/language/Buttons/TiddlyMap/Hint",
"text": "Toggle TiddlyMap actions"
},
"$:/plugins/felixhayashi/tiddlymap/misc/macros": {
"title": "$:/plugins/felixhayashi/tiddlymap/misc/macros",
"text": "\\define concat(str) $str$\n\n\\define input-text(field, index, default, readonly)\n <$reveal type=\"match\" text=\"\" default=\"$readonly$\">\n <$edit-text tiddler=<<output>> field=\"$field$\" index=\"$index$\" type=\"text\" tag=\"input\" default=\"$default$\" />\n </$reveal>\n <$reveal type=\"nomatch\" text=\"\" default=\"$readonly$\">\n <input type=\"text\" value=\"$default$\" readonly=\"true\" disabled=\"true\" />\n </$reveal>\n\\end\n\n\\define input-button(field, index, default, default, label:\"Proceed\")\n <div class=\"tmap-button-wrapper\">\n <$button>$label$\n <$action-setfield $tiddler=<<output>> $field=\"$field$\" index=\"$index$\" $value=\"$default$\" />\n </$button>\n </div>\n\\end\n\n\\define input-textarea(field, index, default, default)\n <$edit-text tiddler=<<output>> field=\"$field$\" index=\"$index$\" autoHeight=\"no\" type=\"text\" tag=\"textarea\" default=\"$default$\" />\n\\end\n\n\\define input-checkbox(field, index, readonly, default)\n <$reveal type=\"match\" text=\"\" default=\"$readonly$\">\n <$checkbox\n tiddler=<<output>>\n field=\"$field$\"\n index=\"$index$\"\n checked=\"true\"\n unchecked=\"false\"\n default=\"$default$\" />\n </$reveal>\n <$reveal type=\"nomatch\" text=\"\" default=\"$readonly$\">\n <input type=\"checkbox\" value=\"$default$\" readonly=\"true\" disabled=\"true\" />\n </$reveal>\n\\end\n\n\\define input-multi-checkbox(selectFilter, invert:\"no\", default)\n <div class=\"tmap-no-stretch\">\n <$list\n filter=\"$selectFilter$\"\n emptyMessage=\"– This list contains no items –\">\n <$checkbox\n tiddler=<<output>>\n tag=<<tmap \"splitAndSelect\" \"|\" \"0\">>>\n <$view\n tiddler=<<tmap \"splitAndSelect\" \"|\" \"1\">>\n field=\"title\" />\n </$checkbox><br />\n </$list>\n </div>\n\\end\n\n\\define input-select(field, index, selectFilter, default, nochoice)\n <$select\n tiddler=<<output>>\n field=\"$field$\"\n index=\"$index$\"\n default=\"$default$\">\n <$set name=\"nochoice\" value=\"$nochoice$\">\n <$list filter=\"[<nochoice>regexp[.+]]\">\n <option value=\"\"><b><<nochoice>></b></option>\n </$list>\n </$set>\n <$list filter=\"$selectFilter$\">\n <option value=<<tmap \"splitAndSelect\" \"|\" \"0\">> >\n <$view tiddler=<<tmap \"splitAndSelect\" \"|\" \"1\">> field=\"title\" /> \n </option>\n </$list> \n </$select>\n\\end\n\n\\define input-radio(field, index, selectFilter, default)\n <$list filter=\"$selectFilter$\">\n <$radio\n tiddler=<<output>>\n field=\"$field$\"\n index=\"$index$\"\n value=<<tmap \"splitAndSelect\" \"|\" \"0\">>>\n <<tmap \"splitAndSelect\" \"|\" \"1\">>\n </$radio><br />\n </$list>\n\\end\n\n\\define tmap-row(title, field, index, type, descr, note, label, default, readonly, reset, selectFilter, nochoice, invert)\n <tr>\n <td class=\"tmap-title\">$title$:</td>\n <td>\n <<$type$\n field:\"$field$\"\n index:\"$index$\"\n readonly:\"$readonly$\"\n default:\"$default$\"\n label:\"$label$\"\n invert:\"$invert$\"\n selectFilter:\"$selectFilter$\"\n nochoice:\"$nochoice$\" >>\n <$reveal type=\"match\" text=\"true\" default=\"$reset$\">\n <$button>reset\n <$action-setfield $tiddler=<<output>> $field=\"$field$\" $index=\"$index$\" $value=\"$default$\" />\n </$button>\n </$reveal>\n </td>\n <td>\n <span class=\"tmap-description\">$descr$</span>\n <$reveal type=\"nomatch\" text=\"\" default=\"$note$\">\n <div class=\"tmap-note\">''Note:'' $note$</div>\n </$reveal>\n </td>\n </tr>\n\\end\n\n\\define visConfiguration(inheritedList,\n extensionField,\n styleName:\"style\")\n \n <fieldset><legend>Visjs configurations ($styleName$)</legend>\n <div class=\"tmap-flash-message tmap-info\">\n Only config items that you actually changed have an effect on\n the graph. Other options are visible, yet, inactive.\n </div>\n <$tmap-config\n mode=\"manage-node-types\"\n inherited=\"$inheritedList$\"\n extension=\"$extensionField$\"\n />\n </fieldset>\n\\end"
},
"$:/plugins/felixhayashi/tiddlymap/misc/defaultViewHolder": {
"title": "$:/plugins/felixhayashi/tiddlymap/misc/defaultViewHolder",
"text": "Default"
},
"$:/plugins/felixhayashi/tiddlymap/graph/nodeTypes/tmap:central-topic": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/nodeTypes/tmap:central-topic",
"description": "The style is applied to the node that you marked as central topic in a map.",
"style": "{\"font\":{\"size\":22,\"color\":\"rgba(0,0,0,1)\"},\"shape\":\"star\"}"
},
"$:/plugins/felixhayashi/tiddlymap/graph/nodeTypes/tmap:neighbour": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/nodeTypes/tmap:neighbour",
"description": "Neighbours are all nodes that are not part of the original set of nodes (\"matches\") but are connected (either outgoing or incoming) to a node of the original set.",
"style": "{\"color\":\"#565656\"}"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Default/filter/edges": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Default/filter/edges"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Default/filter/nodes": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Default/filter/nodes"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Default": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Default",
"config.physics_mode": "false",
"isview": "true"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Live View/filter/edges": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Live View/filter/edges",
"filter": "[prefix[$:/plugins/felixhayashi/tiddlymap/graph/edgeTypes]]",
"text": "\n\n"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Live View/filter/nodes": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Live View/filter/nodes",
"filter": "[field:title{$:/temp/tmap/currentTiddler}]"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Live View": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Live View",
"config.neighbourhood_scope": "1",
"config.refresh-triggers": "$:/temp/tmap/currentTiddler",
"config.physics_mode": "true",
"config.vis": "{\"physics\":{\"forceAtlas2Based\":{\"springLength\":0,\"springConstant\":0.09}}}",
"isview": "true"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Graph search/filter/nodes": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Graph search/filter/nodes",
"filter": "[!is[system]search{$:/temp/search}] [!is[system]search:tags{$:/temp/search}] [!is[system]search:text{$:/temp/search}limit[10]]"
},
"$:/plugins/felixhayashi/tiddlymap/graph/views/Graph search": {
"title": "$:/plugins/felixhayashi/tiddlymap/graph/views/Graph search",
"config.refresh-triggers": "$:/temp/search",
"config.neighbourhood_scope": "1",
"config.physics_mode": "true"
}
}
}
{
"c63b14d3-e247-4bb2-adfe-f4bec0eca7c7": {
"x": 78,
"y": -33
}
}
{
"originalVersion": "0.11.8+9075",
"dataStructureState": "0.11.0",
"showWelcomeMessage": false
}
{
"tiddlers": {
"$:/plugins/felixhayashi/topstoryview/config.js": {
"text": "/*\\\n\ntitle: $:/plugins/felixhayashi/topstoryview/config.js\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\n\\*/\n(function(){\"use strict\";exports.config={classNames:{storyRiver:\"tc-story-river\",backDrop:\"story-backdrop\",tiddlerFrame:\"tc-tiddler-frame\",tiddlerTitle:\"tc-title\"},references:{userConfig:\"$:/config/topStoryView\",focussedTiddlerStore:\"$:/temp/focussedTiddler\",refreshTrigger:\"$:/temp/focussedTiddler/refresh\"},checkbackTime:$tw.utils.getAnimationDuration()}})();",
"title": "$:/plugins/felixhayashi/topstoryview/config.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/felixhayashi/topstoryview/layout": {
"title": "$:/plugins/felixhayashi/topstoryview/layout",
"type": "text/vnd.tiddlywiki",
"tags": [
"$:/tags/Stylesheet"
],
"text": "html .tc-story-river:after {\n content: \"\";\n display: block; }\n"
},
"$:/plugins/felixhayashi/topstoryview/Configuration": {
"title": "$:/plugins/felixhayashi/topstoryview/Configuration",
"text": "Please see the [[GitHub page|https://github.com/felixhayashi/TW5-TopStoryView]] for more information on the options.\n\nSave and reload the wiki to activate changes.\n\n<table>\n <tr>\n <th align=\"left\">Scroll offset:</th>\n <td><$edit-text tiddler=\"$:/config/topStoryView\" field=\"scroll-offset\" tag=\"input\" default=\"150px\" /></td>\n </tr>\n</table>"
},
"$:/plugins/felixhayashi/topstoryview/License": {
"title": "$:/plugins/felixhayashi/topstoryview/License",
"text": "This code is released under the BSD license. For the exact terms visit:\n\nhttps://github.com/felixhayashi/TW5-TopStoryView/blob/master/LICENSE"
},
"$:/plugins/felixhayashi/topstoryview/Readme": {
"title": "$:/plugins/felixhayashi/topstoryview/Readme",
"text": "Please visit the [[GitHub page|https://github.com/felixhayashi/TW5-TopStoryView]] for more information."
},
"$:/plugins/felixhayashi/topstoryview/top.js": {
"text": "/*\\\ntitle: $:/plugins/felixhayashi/topstoryview/top.js\ntype: application/javascript\nmodule-type: storyview\n\nViews the story as a linear sequence\n\n@preserve\n\n\\*/\n(function(){\"use strict\";var t=require(\"$:/plugins/felixhayashi/topstoryview/config.js\").config;var e=\"cubic-bezier(0.645, 0.045, 0.355, 1)\";var i=function(e){this.listWidget=e;this.pageScroller=new $tw.utils.PageScroller;this.pageScroller.scrollIntoView=this.scrollIntoView;this.pageScroller.storyRiverDomNode=document.getElementsByClassName(t.classNames.storyRiver)[0];var i=$tw.wiki.getTiddler(t.references.userConfig);var o=i?i.fields:{};$tw.hooks.addHook(\"th-opening-default-tiddlers-list\",this.hookOpenDefaultTiddlers);var r=parseInt(o[\"scroll-offset\"]);this.pageScroller.scrollOffset=isNaN(r)?71:r;this.recalculateBottomSpace()};i.prototype.refreshStart=function(t,e){};i.prototype.refreshEnd=function(t,e){};i.prototype.hookOpenDefaultTiddlers=function(t){return t};i.prototype.navigateTo=function(t){var e=this.listWidget.findListItem(0,t.title);if(e===undefined)return;var i=this.listWidget.children[e];var o=i.findFirstDomNode();if(!(o instanceof Element))return;this.pageScroller.scrollIntoView(o)};i.prototype.insert=function(t){if(!t)return;var e=t.findFirstDomNode();if(!(e instanceof Element))return;this.startInsertAnimation(e,function(){this.recalculateBottomSpace()}.bind(this))};i.prototype.remove=function(t){if(!t)return;var e=t.findFirstDomNode();if(!(e instanceof Element)){t.removeChildDomNodes();return}var i=this.getLastFrame()===e;this.startRemoveAnimation(t,e,function(){t.removeChildDomNodes();this.recalculateBottomSpace();if(i){this.pageScroller.scrollIntoView(this.getLastFrame())}}.bind(this))};i.prototype.getLastFrame=function(){var t=this.listWidget.children[this.listWidget.children.length-1];return t?t.findFirstDomNode():null};i.prototype.recalculateBottomSpace=function(){var t=this.pageScroller.storyRiverDomNode;if(this.getLastFrame()){var e=this.getLastFrame().getBoundingClientRect();var i=window.innerHeight;if(e.height<i){t.style[\"paddingBottom\"]=i-e.height+\"px\";return}}t.style[\"paddingBottom\"]=\"\"};i.prototype.scrollIntoView=function(t){if(this.preventNextScrollAttempt){this.preventNextScrollAttempt=false}if(!t)return;var e=$tw.utils.getAnimationDuration();this.cancelScroll();this.startTime=Date.now();var i=$tw.utils.getScrollPosition();var o=t.getBoundingClientRect(),r={left:o.left+i.x,top:o.top+i.y,width:o.width,height:o.height};var n=function(t,e,i,o){if(t<=i){return t}else if(e<o&&i<t+e-o){return t+e-o}else if(i<t){return t}else{return i}},s=n(r.left,r.width,i.x,window.innerWidth),a=r.top-this.scrollOffset;if(s!==i.x||a!==i.y){var l=this,c;c=function(){var t;if(e<=0){t=1}else{t=(Date.now()-l.startTime)/e}if(t>=1){l.cancelScroll();t=1}t=$tw.utils.slowInSlowOut(t);window.scrollTo(i.x+(s-i.x)*t,i.y+(a-i.y)*t);if(t<1){l.idRequestFrame=l.requestAnimationFrame.call(window,c)}};c()}};i.prototype.startInsertAnimation=function(t,i){var o=$tw.utils.getAnimationDuration();var r=window.getComputedStyle(t),n=parseInt(r.marginBottom,10),s=parseInt(r.marginTop,10),a=t.offsetHeight+s;setTimeout(function(){$tw.utils.setStyle(t,[{transition:\"none\"},{marginBottom:\"\"}]);i()},o);$tw.utils.setStyle(t,[{transition:\"none\"},{marginBottom:-a+\"px\"},{opacity:\"0.0\"}]);$tw.utils.forceLayout(t);$tw.utils.setStyle(t,[{transition:\"opacity \"+o+\"ms \"+e+\", \"+\"margin-bottom \"+o+\"ms \"+e},{marginBottom:n+\"px\"},{opacity:\"1.0\"}])};i.prototype.startRemoveAnimation=function(t,i,o){var r=$tw.utils.getAnimationDuration();var n=i.offsetWidth,s=window.getComputedStyle(i),a=parseInt(s.marginBottom,10),l=parseInt(s.marginTop,10),c=i.offsetHeight+l;setTimeout(o,r);$tw.utils.setStyle(i,[{transition:\"none\"},{transform:\"translateX(0px)\"},{marginBottom:a+\"px\"},{opacity:\"1.0\"}]);$tw.utils.forceLayout(i);$tw.utils.setStyle(i,[{transition:$tw.utils.roundTripPropertyName(\"transform\")+\" \"+r+\"ms \"+e+\", \"+\"opacity \"+r+\"ms \"+e+\", \"+\"margin-bottom \"+r+\"ms \"+e},{transform:\"translateX(-\"+n+\"px)\"},{marginBottom:-c+\"px\"},{opacity:\"0.0\"}])};exports.top=i})();",
"title": "$:/plugins/felixhayashi/topstoryview/top.js",
"type": "application/javascript",
"module-type": "storyview"
}
}
}
{
"tiddlers": {
"$:/plugins/felixhayashi/vis/img/network/acceptDeleteIcon.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/acceptDeleteIcon.png",
"type": "image/png",
"text": 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},
"$:/plugins/felixhayashi/vis/img/network/addNodeIcon.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/addNodeIcon.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/network/backIcon.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/backIcon.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/network/connectIcon.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/connectIcon.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/network/cross.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/cross.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/network/cross2.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/cross2.png",
"type": "image/png",
"text": 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},
"$:/plugins/felixhayashi/vis/img/network/deleteIcon.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/deleteIcon.png",
"type": "image/png",
"text": 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"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/network/leftArrow.png": {
"title": "$:/plugins/felixhayashi/vis/img/network/leftArrow.png",
"type": "image/png",
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"title": "$:/plugins/felixhayashi/vis/img/network/rightArrow.png",
"type": "image/png",
"text": 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},
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"title": "$:/plugins/felixhayashi/vis/img/network/upArrow.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/img/timeline/delete.png": {
"title": "$:/plugins/felixhayashi/vis/img/timeline/delete.png",
"type": "image/png",
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},
"$:/plugins/felixhayashi/vis/readme": {
"title": "$:/plugins/felixhayashi/vis/readme",
"text": "! TW5-Vis.js\n\nA tiddlywiki plugin for the vis.js library.\n\n---\n\n! Notes on Copyright\n\n!! TiddlyWiki\n\nCreated by Jeremy Ruston, (jeremy [at] jermolene [dot] com)\n\nCopyright © Jeremy Ruston 2004-2007 Copyright © UnaMesa Association 2007-2014\n\nPublished under the following [licenses](https://github.com/Jermolene/TiddlyWiki5/tree/master/licenses):\n\n1. BSD 3-clause \"New\" or \"Revised\" License (including any right to adopt any future version of a license if permitted)\n2. Creative Commons Attribution 3.0 (including any right to adopt any future version of a license if permitted)\n\n!! The **vis.js** library\n\nCopyright (c) 2014 [Almende B.V.](https://github.com/almende/vis)\n\nPublished under the following licenses:\n\n1. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/\n2. MIT License (MIT)\n"
},
"$:/plugins/felixhayashi/vis/vis.css": {
"title": "$:/plugins/felixhayashi/vis/vis.css",
"type": "text/vnd.tiddlywiki",
"tags": "$:/tags/Stylesheet",
"text": "\\rules except list\n\n\\define datauri(title)\n<$macrocall $name=\"makedatauri\" type={{$title$!!type}} text={{$title$}}/>\n\\end\n\n.vis .overlay {\n position: absolute;\n top: 0;\n left: 0;\n width: 100%;\n height: 100%;\n\n /* Must be displayed above for example selected Timeline items */\n z-index: 10;\n}\n\n.vis-active {\n box-shadow: 0 0 10px #86d5f8;\n}\n\n/* override some bootstrap styles screwing up the timelines css */\n\n.vis [class*=\"span\"] {\n min-height: 0;\n width: auto;\n}\n\ndiv.vis-configuration {\n position:relative;\n display:block;\n float:left;\n font-size:12px;\n}\n\ndiv.vis-configuration-wrapper {\n display:block;\n width:700px;\n}\n\ndiv.vis-configuration-wrapper::after {\n clear: both;\n content: \"\";\n display: block;\n}\n\ndiv.vis-configuration.vis-config-option-container{\n display:block;\n width:495px;\n background-color: #ffffff;\n border:2px solid #f7f8fa;\n border-radius:4px;\n margin-top:20px;\n left:10px;\n padding-left:5px;\n}\n\ndiv.vis-configuration.vis-config-button{\n display:block;\n width:495px;\n height:25px;\n vertical-align: middle;\n line-height:25px;\n background-color: #f7f8fa;\n border:2px solid #ceced0;\n border-radius:4px;\n margin-top:20px;\n left:10px;\n padding-left:5px;\n cursor: pointer;\n margin-bottom:30px;\n}\n\ndiv.vis-configuration.vis-config-button.hover{\n background-color: #4588e6;\n border:2px solid #214373;\n color:#ffffff;\n}\n\ndiv.vis-configuration.vis-config-item{\n display:block;\n float:left;\n width:495px;\n height:25px;\n vertical-align: middle;\n line-height:25px;\n}\n\n\ndiv.vis-configuration.vis-config-item.vis-config-s2{\n left:10px;\n background-color: #f7f8fa;\n padding-left:5px;\n border-radius:3px;\n}\ndiv.vis-configuration.vis-config-item.vis-config-s3{\n left:20px;\n background-color: #e4e9f0;\n padding-left:5px;\n border-radius:3px;\n}\ndiv.vis-configuration.vis-config-item.vis-config-s4{\n left:30px;\n background-color: #cfd8e6;\n padding-left:5px;\n border-radius:3px;\n}\n\ndiv.vis-configuration.vis-config-header{\n font-size:18px;\n font-weight: bold;\n}\n\ndiv.vis-configuration.vis-config-label{\n width:120px;\n height:25px;\n line-height: 25px;\n}\n\ndiv.vis-configuration.vis-config-label.vis-config-s3{\n width:110px;\n}\ndiv.vis-configuration.vis-config-label.vis-config-s4{\n width:100px;\n}\n\ndiv.vis-configuration.vis-config-colorBlock{\n top:1px;\n width:30px;\n height:19px;\n border:1px solid #444444;\n border-radius:2px;\n padding:0px;\n margin:0px;\n cursor:pointer;\n}\n\ninput.vis-configuration.vis-config-checkbox {\n left:-5px;\n}\n\n\ninput.vis-configuration.vis-config-rangeinput{\n position:relative;\n top:-5px;\n width:60px;\n /*height:13px;*/\n padding:1px;\n margin:0;\n pointer-events:none;\n}\n\ninput.vis-configuration.vis-config-range{\n /*removes default webkit styles*/\n -webkit-appearance: none;\n\n /*fix for FF unable to apply focus style bug */\n border: 0px solid white;\n background-color:rgba(0,0,0,0);\n\n /*required for proper track sizing in FF*/\n width: 300px;\n height:20px;\n}\ninput.vis-configuration.vis-config-range::-webkit-slider-runnable-track {\n width: 300px;\n height: 5px;\n background: #dedede; /* Old browsers */\n background: -moz-linear-gradient(top, #dedede 0%, #c8c8c8 99%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#dedede), color-stop(99%,#c8c8c8)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #dedede 0%,#c8c8c8 99%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #dedede 0%, #c8c8c8 99%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #dedede 0%,#c8c8c8 99%); /* IE10+ */\n background: linear-gradient(to bottom, #dedede 0%,#c8c8c8 99%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#dedede', endColorstr='#c8c8c8',GradientType=0 ); /* IE6-9 */\n\n border: 1px solid #999999;\n box-shadow: #aaaaaa 0px 0px 3px 0px;\n border-radius: 3px;\n}\ninput.vis-configuration.vis-config-range::-webkit-slider-thumb {\n -webkit-appearance: none;\n border: 1px solid #14334b;\n height: 17px;\n width: 17px;\n border-radius: 50%;\n background: #3876c2; /* Old browsers */\n background: -moz-linear-gradient(top, #3876c2 0%, #385380 100%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#3876c2), color-stop(100%,#385380)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #3876c2 0%,#385380 100%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #3876c2 0%,#385380 100%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #3876c2 0%,#385380 100%); /* IE10+ */\n background: linear-gradient(to bottom, #3876c2 0%,#385380 100%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#3876c2', endColorstr='#385380',GradientType=0 ); /* IE6-9 */\n box-shadow: #111927 0px 0px 1px 0px;\n margin-top: -7px;\n}\ninput.vis-configuration.vis-config-range:focus {\n outline: none;\n}\ninput.vis-configuration.vis-config-range:focus::-webkit-slider-runnable-track {\n background: #9d9d9d; /* Old browsers */\n background: -moz-linear-gradient(top, #9d9d9d 0%, #c8c8c8 99%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#9d9d9d), color-stop(99%,#c8c8c8)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #9d9d9d 0%,#c8c8c8 99%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #9d9d9d 0%,#c8c8c8 99%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #9d9d9d 0%,#c8c8c8 99%); /* IE10+ */\n background: linear-gradient(to bottom, #9d9d9d 0%,#c8c8c8 99%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#9d9d9d', endColorstr='#c8c8c8',GradientType=0 ); /* IE6-9 */\n}\n\ninput.vis-configuration.vis-config-range::-moz-range-track {\n width: 300px;\n height: 10px;\n background: #dedede; /* Old browsers */\n background: -moz-linear-gradient(top, #dedede 0%, #c8c8c8 99%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#dedede), color-stop(99%,#c8c8c8)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #dedede 0%,#c8c8c8 99%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #dedede 0%, #c8c8c8 99%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #dedede 0%,#c8c8c8 99%); /* IE10+ */\n background: linear-gradient(to bottom, #dedede 0%,#c8c8c8 99%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#dedede', endColorstr='#c8c8c8',GradientType=0 ); /* IE6-9 */\n\n border: 1px solid #999999;\n box-shadow: #aaaaaa 0px 0px 3px 0px;\n border-radius: 3px;\n}\ninput.vis-configuration.vis-config-range::-moz-range-thumb {\n border: none;\n height: 16px;\n width: 16px;\n\n border-radius: 50%;\n background: #385380;\n}\n\n/*hide the outline behind the border*/\ninput.vis-configuration.vis-config-range:-moz-focusring{\n outline: 1px solid white;\n outline-offset: -1px;\n}\n\ninput.vis-configuration.vis-config-range::-ms-track {\n width: 300px;\n height: 5px;\n\n /*remove bg colour from the track, we'll use ms-fill-lower and ms-fill-upper instead */\n background: transparent;\n\n /*leave room for the larger thumb to overflow with a transparent border */\n border-color: transparent;\n border-width: 6px 0;\n\n /*remove default tick marks*/\n color: transparent;\n}\ninput.vis-configuration.vis-config-range::-ms-fill-lower {\n background: #777;\n border-radius: 10px;\n}\ninput.vis-configuration.vis-config-range::-ms-fill-upper {\n background: #ddd;\n border-radius: 10px;\n}\ninput.vis-configuration.vis-config-range::-ms-thumb {\n border: none;\n height: 16px;\n width: 16px;\n border-radius: 50%;\n background: #385380;\n}\ninput.vis-configuration.vis-config-range:focus::-ms-fill-lower {\n background: #888;\n}\ninput.vis-configuration.vis-config-range:focus::-ms-fill-upper {\n background: #ccc;\n}\n\n.vis-configuration-popup {\n position: absolute;\n background: rgba(57, 76, 89, 0.85);\n border: 2px solid #f2faff;\n line-height:30px;\n height:30px;\n width:150px;\n text-align:center;\n color: #ffffff;\n font-size:14px;\n border-radius:4px;\n -webkit-transition: opacity 0.3s ease-in-out;\n -moz-transition: opacity 0.3s ease-in-out;\n transition: opacity 0.3s ease-in-out;\n}\n.vis-configuration-popup:after, .vis-configuration-popup:before {\n left: 100%;\n top: 50%;\n border: solid transparent;\n content: \" \";\n height: 0;\n width: 0;\n position: absolute;\n pointer-events: none;\n}\n\n.vis-configuration-popup:after {\n border-color: rgba(136, 183, 213, 0);\n border-left-color: rgba(57, 76, 89, 0.85);\n border-width: 8px;\n margin-top: -8px;\n}\n.vis-configuration-popup:before {\n border-color: rgba(194, 225, 245, 0);\n border-left-color: #f2faff;\n border-width: 12px;\n margin-top: -12px;\n}\n\n.vis-timeline {\n position: relative;\n border: 1px solid #bfbfbf;\n\n overflow: hidden;\n padding: 0;\n margin: 0;\n\n box-sizing: border-box;\n}\n\n\n.vis-panel {\n position: absolute;\n\n padding: 0;\n margin: 0;\n\n box-sizing: border-box;\n}\n\n.vis-panel.vis-center,\n.vis-panel.vis-left,\n.vis-panel.vis-right,\n.vis-panel.vis-top,\n.vis-panel.vis-bottom {\n border: 1px #bfbfbf;\n}\n\n.vis-panel.vis-center,\n.vis-panel.vis-left,\n.vis-panel.vis-right {\n border-top-style: solid;\n border-bottom-style: solid;\n overflow: hidden;\n}\n\n.vis-panel.vis-center,\n.vis-panel.vis-top,\n.vis-panel.vis-bottom {\n border-left-style: solid;\n border-right-style: solid;\n}\n\n.vis-background {\n overflow: hidden;\n}\n\n.vis-panel > .vis-content {\n position: relative;\n}\n\n.vis-panel .vis-shadow {\n position: absolute;\n width: 100%;\n height: 1px;\n box-shadow: 0 0 10px rgba(0,0,0,0.8);\n /* TODO: find a nice way to ensure vis-shadows are drawn on top of items\n z-index: 1;\n */\n}\n\n.vis-panel .vis-shadow.vis-top {\n top: -1px;\n left: 0;\n}\n\n.vis-panel .vis-shadow.vis-bottom {\n bottom: -1px;\n left: 0;\n}\n\n.vis-labelset {\n position: relative;\n\n overflow: hidden;\n\n box-sizing: border-box;\n}\n\n.vis-labelset .vis-label {\n position: relative;\n left: 0;\n top: 0;\n width: 100%;\n color: #4d4d4d;\n\n box-sizing: border-box;\n}\n\n.vis-labelset .vis-label {\n border-bottom: 1px solid #bfbfbf;\n}\n\n.vis-labelset .vis-label.draggable {\n cursor: pointer;\n}\n\n.vis-labelset .vis-label:last-child {\n border-bottom: none;\n}\n\n.vis-labelset .vis-label .vis-inner {\n display: inline-block;\n padding: 5px;\n}\n\n.vis-labelset .vis-label .vis-inner.vis-hidden {\n padding: 0;\n}\n\n\n.vis-itemset {\n position: relative;\n padding: 0;\n margin: 0;\n\n box-sizing: border-box;\n}\n\n.vis-itemset .vis-background,\n.vis-itemset .vis-foreground {\n position: absolute;\n width: 100%;\n height: 100%;\n overflow: visible;\n}\n\n.vis-axis {\n position: absolute;\n width: 100%;\n height: 0;\n left: 0;\n z-index: 1;\n}\n\n.vis-foreground .vis-group {\n position: relative;\n box-sizing: border-box;\n border-bottom: 1px solid #bfbfbf;\n}\n\n.vis-foreground .vis-group:last-child {\n border-bottom: none;\n}\n\n.vis-overlay {\n position: absolute;\n top: 0;\n left: 0;\n width: 100%;\n height: 100%;\n z-index: 10;\n}\n\n.vis-item {\n position: absolute;\n color: #1A1A1A;\n border-color: #97B0F8;\n border-width: 1px;\n background-color: #D5DDF6;\n display: inline-block;\n /*overflow: hidden;*/\n}\n\n.vis-item.vis-selected {\n border-color: #FFC200;\n background-color: #FFF785;\n\n /* z-index must be higher than the z-index of custom time bar and current time bar */\n z-index: 2;\n}\n\n.vis-editable.vis-selected {\n cursor: move;\n}\n\n.vis-item.vis-point.vis-selected {\n background-color: #FFF785;\n}\n\n.vis-item.vis-box {\n text-align: center;\n border-style: solid;\n border-radius: 2px;\n}\n\n.vis-item.vis-point {\n background: none;\n}\n\n.vis-item.vis-dot {\n position: absolute;\n padding: 0;\n border-width: 4px;\n border-style: solid;\n border-radius: 4px;\n}\n\n.vis-item.vis-range {\n border-style: solid;\n border-radius: 2px;\n box-sizing: border-box;\n}\n\n.vis-item.vis-background {\n border: none;\n background-color: rgba(213, 221, 246, 0.4);\n box-sizing: border-box;\n padding: 0;\n margin: 0;\n}\n\n.vis-item .vis-item-overflow {\n position: relative;\n width: 100%;\n height: 100%;\n padding: 0;\n margin: 0;\n overflow: hidden;\n}\n\n.vis-item.vis-range .vis-item-content {\n position: relative;\n display: inline-block;\n}\n\n.vis-item.vis-background .vis-item-content {\n position: absolute;\n display: inline-block;\n}\n\n.vis-item.vis-line {\n padding: 0;\n position: absolute;\n width: 0;\n border-left-width: 1px;\n border-left-style: solid;\n}\n\n.vis-item .vis-item-content {\n white-space: nowrap;\n box-sizing: border-box;\n padding: 5px;\n}\n\n.vis-item .vis-delete {\n background: url( <<datauri \"$:/plugins/felixhayashi/vis/img/timeline/delete.png\">> ) no-repeat center;\n position: absolute;\n width: 24px;\n height: 24px;\n top: -4px;\n right: -24px;\n cursor: pointer;\n}\n\n.vis-item.vis-range .vis-drag-left {\n position: absolute;\n width: 24px;\n max-width: 20%;\n min-width: 2px;\n height: 100%;\n top: 0;\n left: -4px;\n\n cursor: w-resize;\n}\n\n.vis-item.vis-range .vis-drag-right {\n position: absolute;\n width: 24px;\n max-width: 20%;\n min-width: 2px;\n height: 100%;\n top: 0;\n right: -4px;\n\n cursor: e-resize;\n}\n\n.vis-range.vis-item.vis-readonly .vis-drag-left,\n.vis-range.vis-item.vis-readonly .vis-drag-right {\n cursor: auto;\n}\n\n.vis-time-axis {\n position: relative;\n overflow: hidden;\n}\n\n.vis-time-axis.vis-foreground {\n top: 0;\n left: 0;\n width: 100%;\n}\n\n.vis-time-axis.vis-background {\n position: absolute;\n top: 0;\n left: 0;\n width: 100%;\n height: 100%;\n}\n\n.vis-time-axis .vis-text {\n position: absolute;\n color: #4d4d4d;\n padding: 3px;\n overflow: hidden;\n box-sizing: border-box;\n\n white-space: nowrap;\n}\n\n.vis-time-axis .vis-text.vis-measure {\n position: absolute;\n padding-left: 0;\n padding-right: 0;\n margin-left: 0;\n margin-right: 0;\n visibility: hidden;\n}\n\n.vis-time-axis .vis-grid.vis-vertical {\n position: absolute;\n border-left: 1px solid;\n}\n\n.vis-time-axis .vis-grid.vis-minor {\n border-color: #e5e5e5;\n}\n\n.vis-time-axis .vis-grid.vis-major {\n border-color: #bfbfbf;\n}\n\n.vis-current-time {\n background-color: #FF7F6E;\n width: 2px;\n z-index: 1;\n}\n.vis-custom-time {\n background-color: #6E94FF;\n width: 2px;\n cursor: move;\n z-index: 1;\n}\n.vis-timeline {\n /*\n -webkit-transition: height .4s ease-in-out;\n transition: height .4s ease-in-out;\n */\n}\n\n.vis-panel {\n /*\n -webkit-transition: height .4s ease-in-out, top .4s ease-in-out;\n transition: height .4s ease-in-out, top .4s ease-in-out;\n */\n}\n\n.vis-axis {\n /*\n -webkit-transition: top .4s ease-in-out;\n transition: top .4s ease-in-out;\n */\n}\n\n/* TODO: get animation working nicely\n\n.vis-item {\n -webkit-transition: top .4s ease-in-out;\n transition: top .4s ease-in-out;\n}\n\n.vis-item.line {\n -webkit-transition: height .4s ease-in-out, top .4s ease-in-out;\n transition: height .4s ease-in-out, top .4s ease-in-out;\n}\n/**/\n\n.vis-panel.vis-background.vis-horizontal .vis-grid.vis-horizontal {\n position: absolute;\n width: 100%;\n height: 0;\n border-bottom: 1px solid;\n}\n\n.vis-panel.vis-background.vis-horizontal .vis-grid.vis-minor {\n border-color: #e5e5e5;\n}\n\n.vis-panel.vis-background.vis-horizontal .vis-grid.vis-major {\n border-color: #bfbfbf;\n}\n\n\n.vis-data-axis .vis-y-axis.vis-major {\n width: 100%;\n position: absolute;\n color: #4d4d4d;\n white-space: nowrap;\n}\n\n.vis-data-axis .vis-y-axis.vis-major.vis-measure {\n padding: 0;\n margin: 0;\n border: 0;\n visibility: hidden;\n width: auto;\n}\n\n\n.vis-data-axis .vis-y-axis.vis-minor {\n position: absolute;\n width: 100%;\n color: #bebebe;\n white-space: nowrap;\n}\n\n.vis-data-axis .vis-y-axis.vis-minor.vis-measure {\n padding: 0;\n margin: 0;\n border: 0;\n visibility: hidden;\n width: auto;\n}\n\n.vis-data-axis .vis-y-axis.vis-title {\n position: absolute;\n color: #4d4d4d;\n white-space: nowrap;\n bottom: 20px;\n text-align: center;\n}\n\n.vis-data-axis .vis-y-axis.vis-title.vis-measure {\n padding: 0;\n margin: 0;\n visibility: hidden;\n width: auto;\n}\n\n.vis-data-axis .vis-y-axis.vis-title.vis-left {\n bottom: 0;\n -webkit-transform-origin: left top;\n -moz-transform-origin: left top;\n -ms-transform-origin: left top;\n -o-transform-origin: left top;\n transform-origin: left bottom;\n -webkit-transform: rotate(-90deg);\n -moz-transform: rotate(-90deg);\n -ms-transform: rotate(-90deg);\n -o-transform: rotate(-90deg);\n transform: rotate(-90deg);\n}\n\n.vis-data-axis .vis-y-axis.vis-title.vis-right {\n bottom: 0;\n -webkit-transform-origin: right bottom;\n -moz-transform-origin: right bottom;\n -ms-transform-origin: right bottom;\n -o-transform-origin: right bottom;\n transform-origin: right bottom;\n -webkit-transform: rotate(90deg);\n -moz-transform: rotate(90deg);\n -ms-transform: rotate(90deg);\n -o-transform: rotate(90deg);\n transform: rotate(90deg);\n}\n\n.vis-legend {\n background-color: rgba(247, 252, 255, 0.65);\n padding: 5px;\n border: 1px solid #b3b3b3;\n box-shadow: 2px 2px 10px rgba(154, 154, 154, 0.55);\n}\n\n.vis-legend-text {\n /*font-size: 10px;*/\n white-space: nowrap;\n display: inline-block\n}\n.vis-graph-group0 {\n fill:#4f81bd;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #4f81bd;\n}\n\n.vis-graph-group1 {\n fill:#f79646;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #f79646;\n}\n\n.vis-graph-group2 {\n fill: #8c51cf;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #8c51cf;\n}\n\n.vis-graph-group3 {\n fill: #75c841;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #75c841;\n}\n\n.vis-graph-group4 {\n fill: #ff0100;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #ff0100;\n}\n\n.vis-graph-group5 {\n fill: #37d8e6;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #37d8e6;\n}\n\n.vis-graph-group6 {\n fill: #042662;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #042662;\n}\n\n.vis-graph-group7 {\n fill:#00ff26;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #00ff26;\n}\n\n.vis-graph-group8 {\n fill:#ff00ff;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #ff00ff;\n}\n\n.vis-graph-group9 {\n fill: #8f3938;\n fill-opacity:0;\n stroke-width:2px;\n stroke: #8f3938;\n}\n\n.vis-timeline .vis-fill {\n fill-opacity:0.1;\n stroke: none;\n}\n\n\n.vis-timeline .vis-bar {\n fill-opacity:0.5;\n stroke-width:1px;\n}\n\n.vis-timeline .vis-point {\n stroke-width:2px;\n fill-opacity:1.0;\n}\n\n\n.vis-timeline .vis-legend-background {\n stroke-width:1px;\n fill-opacity:0.9;\n fill: #ffffff;\n stroke: #c2c2c2;\n}\n\n\n.vis-timeline .vis-outline {\n stroke-width:1px;\n fill-opacity:1;\n fill: #ffffff;\n stroke: #e5e5e5;\n}\n\n.vis-timeline .vis-icon-fill {\n fill-opacity:0.3;\n stroke: none;\n}\n\ndiv.vis-network div.vis-manipulation {\n border-width: 0;\n border-bottom: 1px;\n border-style:solid;\n border-color: #d6d9d8;\n background: #ffffff; /* Old browsers */\n background: -moz-linear-gradient(top, #ffffff 0%, #fcfcfc 48%, #fafafa 50%, #fcfcfc 100%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#ffffff), color-stop(48%,#fcfcfc), color-stop(50%,#fafafa), color-stop(100%,#fcfcfc)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #ffffff 0%,#fcfcfc 48%,#fafafa 50%,#fcfcfc 100%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #ffffff 0%,#fcfcfc 48%,#fafafa 50%,#fcfcfc 100%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #ffffff 0%,#fcfcfc 48%,#fafafa 50%,#fcfcfc 100%); /* IE10+ */\n background: linear-gradient(to bottom, #ffffff 0%,#fcfcfc 48%,#fafafa 50%,#fcfcfc 100%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#ffffff', endColorstr='#fcfcfc',GradientType=0 ); /* IE6-9 */\n\n padding-top:4px;\n position: absolute;\n left: 0;\n top: 0;\n width: 100%;\n height: 28px;\n}\n\ndiv.vis-network div.vis-edit-mode {\n position:absolute;\n left: 0;\n top: 5px;\n height: 30px;\n}\n\n/* FIXME: shouldn't the vis-close button be a child of the vis-manipulation div? */\n\ndiv.vis-network div.vis-close {\n position:absolute;\n right: 0;\n top: 0;\n width: 30px;\n height: 30px;\n\n background-position: 20px 3px;\n background-repeat: no-repeat;\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/cross.png\">> );\n cursor: pointer;\n -webkit-touch-callout: none;\n -webkit-user-select: none;\n -khtml-user-select: none;\n -moz-user-select: none;\n -ms-user-select: none;\n user-select: none;\n}\n\ndiv.vis-network div.vis-close:hover {\n opacity: 0.6;\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button,\ndiv.vis-network div.vis-edit-mode div.vis-button {\n float:left;\n font-family: verdana;\n font-size: 12px;\n -moz-border-radius: 15px;\n border-radius: 15px;\n display:inline-block;\n background-position: 0px 0px;\n background-repeat:no-repeat;\n height:24px;\n margin-left: 10px;\n /*vertical-align:middle;*/\n cursor: pointer;\n padding: 0px 8px 0px 8px;\n -webkit-touch-callout: none;\n -webkit-user-select: none;\n -khtml-user-select: none;\n -moz-user-select: none;\n -ms-user-select: none;\n user-select: none;\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button:hover {\n box-shadow: 1px 1px 8px rgba(0, 0, 0, 0.20);\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button:active {\n box-shadow: 1px 1px 8px rgba(0, 0, 0, 0.50);\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-back {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/backIcon.png\">> );\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-none:hover {\n box-shadow: 1px 1px 8px rgba(0, 0, 0, 0.0);\n cursor: default;\n}\ndiv.vis-network div.vis-manipulation div.vis-button.vis-none:active {\n box-shadow: 1px 1px 8px rgba(0, 0, 0, 0.0);\n}\ndiv.vis-network div.vis-manipulation div.vis-button.vis-none {\n padding: 0;\n}\ndiv.vis-network div.vis-manipulation div.notification {\n margin: 2px;\n font-weight: bold;\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-add {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/addNodeIcon.png\">> );\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-edit,\ndiv.vis-network div.vis-edit-mode div.vis-button.vis-edit {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/editIcon.png\">> );\n}\n\ndiv.vis-network div.vis-edit-mode div.vis-button.vis-edit.vis-edit-mode {\n background-color: #fcfcfc;\n border: 1px solid #cccccc;\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-connect {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/connectIcon.png\">> );\n}\n\ndiv.vis-network div.vis-manipulation div.vis-button.vis-delete {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/deleteIcon.png\">> );\n}\n/* top right bottom left */\ndiv.vis-network div.vis-manipulation div.vis-label,\ndiv.vis-network div.vis-edit-mode div.vis-label {\n margin: 0 0 0 23px;\n line-height: 25px;\n}\ndiv.vis-network div.vis-manipulation div.vis-separator-line {\n float:left;\n display:inline-block;\n width:1px;\n height:21px;\n background-color: #bdbdbd;\n margin: 0px 7px 0 15px; /*top right bottom left*/\n}\n\n/* TODO: is this redundant?\ndiv.network-navigation_wrapper {\n position: absolute;\n left: 0;\n top: 0;\n width: 100%;\n height: 100%;\n}\n*/\ndiv.vis-network-tooltip {\n position: absolute;\n visibility: hidden;\n padding: 5px;\n white-space: nowrap;\n\n font-family: verdana;\n font-size:14px;\n font-color:#000000;\n background-color: #f5f4ed;\n\n -moz-border-radius: 3px;\n -webkit-border-radius: 3px;\n border-radius: 3px;\n border: 1px solid #808074;\n\n box-shadow: 3px 3px 10px rgba(0, 0, 0, 0.2);\n pointer-events: none;\n}\ndiv.vis-network div.vis-navigation div.vis-button {\n width:34px;\n height:34px;\n -moz-border-radius: 17px;\n border-radius: 17px;\n position:absolute;\n display:inline-block;\n background-position: 2px 2px;\n background-repeat:no-repeat;\n cursor: pointer;\n -webkit-touch-callout: none;\n -webkit-user-select: none;\n -khtml-user-select: none;\n -moz-user-select: none;\n -ms-user-select: none;\n user-select: none;\n}\n\ndiv.vis-network div.vis-navigation div.vis-button:hover {\n box-shadow: 0 0 3px 3px rgba(56, 207, 21, 0.30);\n}\n\ndiv.vis-network div.vis-navigation div.vis-button:active {\n box-shadow: 0 0 1px 3px rgba(56, 207, 21, 0.95);\n}\n\ndiv.vis-network div.vis-navigation div.vis-button.vis-up {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/upArrow.png\">> );\n bottom:50px;\n left:55px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-down {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/downArrow.png\">> );\n bottom:10px;\n left:55px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-left {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/leftArrow.png\">> );\n bottom:10px;\n left:15px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-right {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/rightArrow.png\">> );\n bottom:10px;\n left:95px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-zoomIn {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/plus.png\">> );\n bottom:10px;\n right:15px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-zoomOut {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/minus.png\">> );\n bottom:10px;\n right:55px;\n}\ndiv.vis-network div.vis-navigation div.vis-button.vis-zoomExtends {\n background-image: url( <<datauri \"$:/plugins/felixhayashi/vis/img/network/zoomExtends.png\">> );\n bottom:50px;\n right:15px;\n}\n\ndiv.vis-color-picker {\n position:absolute;\n top: 0px;\n left: 30px;\n margin-top:-140px;\n margin-left:30px;\n width:310px;\n height:444px;\n z-index: 1;\n padding: 10px;\n border-radius:15px;\n background-color:#ffffff;\n display: none;\n box-shadow: rgba(0,0,0,0.5) 0px 0px 10px 0px;\n}\n\ndiv.vis-color-picker div.vis-arrow {\n position: absolute;\n top:147px;\n left:5px;\n}\n\ndiv.vis-color-picker div.vis-arrow::after,\ndiv.vis-color-picker div.vis-arrow::before {\n right: 100%;\n top: 50%;\n border: solid transparent;\n content: \" \";\n height: 0;\n width: 0;\n position: absolute;\n pointer-events: none;\n}\n\ndiv.vis-color-picker div.vis-arrow:after {\n border-color: rgba(255, 255, 255, 0);\n border-right-color: #ffffff;\n border-width: 30px;\n margin-top: -30px;\n}\n\ndiv.vis-color-picker div.vis-color {\n position:absolute;\n width: 289px;\n height: 289px;\n cursor: pointer;\n}\n\n\n\ndiv.vis-color-picker div.vis-brightness {\n position: absolute;\n top:313px;\n}\n\ndiv.vis-color-picker div.vis-opacity {\n position:absolute;\n top:350px;\n}\n\ndiv.vis-color-picker div.vis-selector {\n position:absolute;\n top:137px;\n left:137px;\n width:15px;\n height:15px;\n border-radius:15px;\n border:1px solid #ffffff;\n background: #4c4c4c; /* Old browsers */\n background: -moz-linear-gradient(top, #4c4c4c 0%, #595959 12%, #666666 25%, #474747 39%, #2c2c2c 50%, #000000 51%, #111111 60%, #2b2b2b 76%, #1c1c1c 91%, #131313 100%); /* FF3.6+ */\n background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#4c4c4c), color-stop(12%,#595959), color-stop(25%,#666666), color-stop(39%,#474747), color-stop(50%,#2c2c2c), color-stop(51%,#000000), color-stop(60%,#111111), color-stop(76%,#2b2b2b), color-stop(91%,#1c1c1c), color-stop(100%,#131313)); /* Chrome,Safari4+ */\n background: -webkit-linear-gradient(top, #4c4c4c 0%,#595959 12%,#666666 25%,#474747 39%,#2c2c2c 50%,#000000 51%,#111111 60%,#2b2b2b 76%,#1c1c1c 91%,#131313 100%); /* Chrome10+,Safari5.1+ */\n background: -o-linear-gradient(top, #4c4c4c 0%,#595959 12%,#666666 25%,#474747 39%,#2c2c2c 50%,#000000 51%,#111111 60%,#2b2b2b 76%,#1c1c1c 91%,#131313 100%); /* Opera 11.10+ */\n background: -ms-linear-gradient(top, #4c4c4c 0%,#595959 12%,#666666 25%,#474747 39%,#2c2c2c 50%,#000000 51%,#111111 60%,#2b2b2b 76%,#1c1c1c 91%,#131313 100%); /* IE10+ */\n background: linear-gradient(to bottom, #4c4c4c 0%,#595959 12%,#666666 25%,#474747 39%,#2c2c2c 50%,#000000 51%,#111111 60%,#2b2b2b 76%,#1c1c1c 91%,#131313 100%); /* W3C */\n filter: progid:DXImageTransform.Microsoft.gradient( startColorstr='#4c4c4c', endColorstr='#131313',GradientType=0 ); /* IE6-9 */\n}\n\n\n\ndiv.vis-color-picker div.vis-new-color {\n position:absolute;\n width:140px;\n height:20px;\n border:1px solid rgba(0,0,0,0.1);\n border-radius:5px;\n top:380px;\n left:159px;\n text-align:right;\n padding-right:2px;\n font-size:10px;\n color:rgba(0,0,0,0.4);\n vertical-align:middle;\n line-height:20px;\n\n}\n\ndiv.vis-color-picker div.vis-initial-color {\n position:absolute;\n width:140px;\n height:20px;\n border:1px solid rgba(0,0,0,0.1);\n border-radius:5px;\n top:380px;\n left:10px;\n text-align:left;\n padding-left:2px;\n font-size:10px;\n color:rgba(0,0,0,0.4);\n vertical-align:middle;\n line-height:20px;\n}\n\ndiv.vis-color-picker div.vis-label {\n position:absolute;\n width:300px;\n left:10px;\n}\n\ndiv.vis-color-picker div.vis-label.vis-brightness {\n top:300px;\n}\n\ndiv.vis-color-picker div.vis-label.vis-opacity {\n top:338px;\n}\n\ndiv.vis-color-picker div.vis-button {\n position:absolute;\n width:68px;\n height:25px;\n border-radius:10px;\n vertical-align: middle;\n text-align:center;\n line-height: 25px;\n top:410px;\n border:2px solid #d9d9d9;\n background-color: #f7f7f7;\n cursor:pointer;\n}\n\ndiv.vis-color-picker div.vis-button.vis-cancel {\n /*border:2px solid #ff4e33;*/\n /*background-color: #ff7761;*/\n left:5px;\n}\ndiv.vis-color-picker div.vis-button.vis-load {\n /*border:2px solid #a153e6;*/\n /*background-color: #cb8dff;*/\n left:82px;\n}\ndiv.vis-color-picker div.vis-button.vis-apply {\n /*border:2px solid #4588e6;*/\n /*background-color: #82b6ff;*/\n left:159px;\n}\ndiv.vis-color-picker div.vis-button.vis-save {\n /*border:2px solid #45e655;*/\n /*background-color: #6dff7c;*/\n left:236px;\n}\n\n\ndiv.vis-color-picker input.vis-range {\n width: 290px;\n height:20px;\n}\n\n/* TODO: is this redundant?\ndiv.vis-color-picker input.vis-range-brightness {\n width: 289px !important;\n}\n\n\ndiv.vis-color-picker input.vis-saturation-range {\n width: 289px !important;\n}*/"
},
"$:/plugins/felixhayashi/vis/vis.js": {
"text": "/*\\\ntitle: $:/plugins/felixhayashi/vis/vis.js\ntype: application/javascript\nmodule-type: library\n\n@preserve\n\\*/\n\n/*** TO AVOID STRANGE LIB ERRORS FROM BUBBLING UP *****************/\n\nif($tw.boot.tasks.trapErrors) {\n\n var defaultHandler = window.onerror;\n window.onerror = function(errorMsg, url, lineNumber) {\n \n if(errorMsg.indexOf(\"NS_ERROR_NOT_AVAILABLE\") !== -1\n && url == \"$:/plugins/felixhayashi/vis/vis.js\") {\n \n var text = \"Strange firefox related vis.js error (see #125)\";\n console.error(text, arguments);\n \n } else if(errorMsg.indexOf(\"Permission denied to access property\") !== -1) {\n \n var text = \"Strange firefox related vis.js error (see #163)\";\n console.error(text, arguments);\n \n } else if(defaultHandler) {\n \n defaultHandler.apply(this, arguments);\n \n }\n \n }\n \n}\n\n/******************************************************************/\n\n/**\n * vis.js\n * https://github.com/almende/vis\n *\n * A dynamic, browser-based visualization library.\n *\n * @version 4.14.0\n * @date 2016-02-04\n *\n * @license\n * Copyright (C) 2011-2016 Almende B.V, http://almende.com\n *\n * Vis.js is dual licensed under both\n *\n * * The Apache 2.0 License\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * and\n *\n * * The MIT License\n * http://opensource.org/licenses/MIT\n *\n * Vis.js may be distributed under either license.\n */\n\n\"use strict\";\n\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"vis\"] = factory();\n\telse\n\t\troot[\"vis\"] = factory();\n})(this, function() {\nreturn /******/ (function(modules) { // webpackBootstrap\n/******/ \t// The module cache\n/******/ \tvar installedModules = {};\n\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(installedModules[moduleId])\n/******/ \t\t\treturn installedModules[moduleId].exports;\n\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = installedModules[moduleId] = {\n/******/ \t\t\texports: {},\n/******/ \t\t\tid: moduleId,\n/******/ \t\t\tloaded: false\n/******/ \t\t};\n\n/******/ \t\t// Execute the module function\n/******/ \t\tmodules[moduleId].call(module.exports, module, module.exports, __webpack_require__);\n\n/******/ \t\t// Flag the module as loaded\n/******/ \t\tmodule.loaded = true;\n\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n\n\n/******/ \t// expose the modules object (__webpack_modules__)\n/******/ \t__webpack_require__.m = modules;\n\n/******/ \t// expose the module cache\n/******/ \t__webpack_require__.c = installedModules;\n\n/******/ \t// __webpack_public_path__\n/******/ \t__webpack_require__.p = \"\";\n\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(0);\n/******/ })\n/************************************************************************/\n/******/ ([\n/* 0 */\n/***/ function(module, exports, __webpack_require__) {\n\n // utils\n 'use strict';\n\n exports.util = __webpack_require__(1);\n exports.DOMutil = __webpack_require__(7);\n\n // data\n exports.DataSet = __webpack_require__(8);\n exports.DataView = __webpack_require__(10);\n exports.Queue = __webpack_require__(9);\n\n // Graph3d\n exports.Graph3d = __webpack_require__(11);\n exports.graph3d = {\n Camera: __webpack_require__(15),\n Filter: __webpack_require__(16),\n Point2d: __webpack_require__(14),\n Point3d: __webpack_require__(13),\n Slider: __webpack_require__(17),\n StepNumber: __webpack_require__(18)\n };\n\n // Timeline\n exports.Timeline = __webpack_require__(19);\n exports.Graph2d = __webpack_require__(48);\n exports.timeline = {\n Core: __webpack_require__(27),\n DateUtil: __webpack_require__(26),\n Range: __webpack_require__(23),\n stack: __webpack_require__(31),\n TimeStep: __webpack_require__(29),\n\n components: {\n items: {\n Item: __webpack_require__(33),\n BackgroundItem: __webpack_require__(37),\n BoxItem: __webpack_require__(35),\n PointItem: __webpack_require__(36),\n RangeItem: __webpack_require__(32)\n },\n\n BackgroundGroup: __webpack_require__(34),\n Component: __webpack_require__(25),\n CurrentTime: __webpack_require__(43),\n CustomTime: __webpack_require__(41),\n DataAxis: __webpack_require__(50),\n DataScale: __webpack_require__(51),\n GraphGroup: __webpack_require__(52),\n Group: __webpack_require__(30),\n ItemSet: __webpack_require__(28),\n Legend: __webpack_require__(56),\n LineGraph: __webpack_require__(49),\n TimeAxis: __webpack_require__(38)\n }\n };\n\n // Network\n exports.Network = __webpack_require__(58);\n exports.network = {\n Images: __webpack_require__(116),\n dotparser: __webpack_require__(114),\n gephiParser: __webpack_require__(115),\n allOptions: __webpack_require__(110)\n };\n exports.network.convertDot = function (input) {\n return exports.network.dotparser.DOTToGraph(input);\n };\n exports.network.convertGephi = function (input, options) {\n return exports.network.gephiParser.parseGephi(input, options);\n };\n\n // bundled external libraries\n exports.moment = __webpack_require__(2);\n exports.Hammer = __webpack_require__(20);\n exports.keycharm = __webpack_require__(40);\n\n/***/ },\n/* 1 */\n/***/ function(module, exports, __webpack_require__) {\n\n // utility functions\n\n // first check if moment.js is already loaded in the browser window, if so,\n // use this instance. Else, load via commonjs.\n\n 'use strict';\n\n var moment = __webpack_require__(2);\n var uuid = __webpack_require__(6);\n\n /**\n * Test whether given object is a number\n * @param {*} object\n * @return {Boolean} isNumber\n */\n exports.isNumber = function (object) {\n return object instanceof Number || typeof object == 'number';\n };\n\n /**\n * Remove everything in the DOM object\n * @param DOMobject\n */\n exports.recursiveDOMDelete = function (DOMobject) {\n if (DOMobject) {\n while (DOMobject.hasChildNodes() === true) {\n exports.recursiveDOMDelete(DOMobject.firstChild);\n DOMobject.removeChild(DOMobject.firstChild);\n }\n }\n };\n\n /**\n * this function gives you a range between 0 and 1 based on the min and max values in the set, the total sum of all values and the current value.\n *\n * @param min\n * @param max\n * @param total\n * @param value\n * @returns {number}\n */\n exports.giveRange = function (min, max, total, value) {\n if (max == min) {\n return 0.5;\n } else {\n var scale = 1 / (max - min);\n return Math.max(0, (value - min) * scale);\n }\n };\n\n /**\n * Test whether given object is a string\n * @param {*} object\n * @return {Boolean} isString\n */\n exports.isString = function (object) {\n return object instanceof String || typeof object == 'string';\n };\n\n /**\n * Test whether given object is a Date, or a String containing a Date\n * @param {Date | String} object\n * @return {Boolean} isDate\n */\n exports.isDate = function (object) {\n if (object instanceof Date) {\n return true;\n } else if (exports.isString(object)) {\n // test whether this string contains a date\n var match = ASPDateRegex.exec(object);\n if (match) {\n return true;\n } else if (!isNaN(Date.parse(object))) {\n return true;\n }\n }\n\n return false;\n };\n\n /**\n * Create a semi UUID\n * source: http://stackoverflow.com/a/105074/1262753\n * @return {String} uuid\n */\n exports.randomUUID = function () {\n return uuid.v4();\n };\n\n /**\n * assign all keys of an object that are not nested objects to a certain value (used for color objects).\n * @param obj\n * @param value\n */\n exports.assignAllKeys = function (obj, value) {\n for (var prop in obj) {\n if (obj.hasOwnProperty(prop)) {\n if (typeof obj[prop] !== 'object') {\n obj[prop] = value;\n }\n }\n }\n };\n\n /**\n * Fill an object with a possibly partially defined other object. Only copies values if the a object has an object requiring values.\n * That means an object is not created on a property if only the b object has it.\n * @param obj\n * @param value\n */\n exports.fillIfDefined = function (a, b) {\n var allowDeletion = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n for (var prop in a) {\n if (b[prop] !== undefined) {\n if (typeof b[prop] !== 'object') {\n if ((b[prop] === undefined || b[prop] === null) && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n } else {\n if (typeof a[prop] === 'object') {\n exports.fillIfDefined(a[prop], b[prop], allowDeletion);\n }\n }\n }\n }\n };\n\n /**\n * Extend object a with the properties of object b or a series of objects\n * Only properties with defined values are copied\n * @param {Object} a\n * @param {... Object} b\n * @return {Object} a\n */\n exports.protoExtend = function (a, b) {\n for (var i = 1; i < arguments.length; i++) {\n var other = arguments[i];\n for (var prop in other) {\n a[prop] = other[prop];\n }\n }\n return a;\n };\n\n /**\n * Extend object a with the properties of object b or a series of objects\n * Only properties with defined values are copied\n * @param {Object} a\n * @param {... Object} b\n * @return {Object} a\n */\n exports.extend = function (a, b) {\n for (var i = 1; i < arguments.length; i++) {\n var other = arguments[i];\n for (var prop in other) {\n if (other.hasOwnProperty(prop)) {\n a[prop] = other[prop];\n }\n }\n }\n return a;\n };\n\n /**\n * Extend object a with selected properties of object b or a series of objects\n * Only properties with defined values are copied\n * @param {Array.<String>} props\n * @param {Object} a\n * @param {Object} b\n * @return {Object} a\n */\n exports.selectiveExtend = function (props, a, b) {\n if (!Array.isArray(props)) {\n throw new Error('Array with property names expected as first argument');\n }\n\n for (var i = 2; i < arguments.length; i++) {\n var other = arguments[i];\n\n for (var p = 0; p < props.length; p++) {\n var prop = props[p];\n if (other.hasOwnProperty(prop)) {\n a[prop] = other[prop];\n }\n }\n }\n return a;\n };\n\n /**\n * Extend object a with selected properties of object b or a series of objects\n * Only properties with defined values are copied\n * @param {Array.<String>} props\n * @param {Object} a\n * @param {Object} b\n * @return {Object} a\n */\n exports.selectiveDeepExtend = function (props, a, b) {\n var allowDeletion = arguments.length <= 3 || arguments[3] === undefined ? false : arguments[3];\n\n // TODO: add support for Arrays to deepExtend\n if (Array.isArray(b)) {\n throw new TypeError('Arrays are not supported by deepExtend');\n }\n for (var i = 2; i < arguments.length; i++) {\n var other = arguments[i];\n for (var p = 0; p < props.length; p++) {\n var prop = props[p];\n if (other.hasOwnProperty(prop)) {\n if (b[prop] && b[prop].constructor === Object) {\n if (a[prop] === undefined) {\n a[prop] = {};\n }\n if (a[prop].constructor === Object) {\n exports.deepExtend(a[prop], b[prop], false, allowDeletion);\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n } else if (Array.isArray(b[prop])) {\n throw new TypeError('Arrays are not supported by deepExtend');\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n }\n }\n }\n return a;\n };\n\n /**\n * Extend object a with selected properties of object b or a series of objects\n * Only properties with defined values are copied\n * @param {Array.<String>} props\n * @param {Object} a\n * @param {Object} b\n * @return {Object} a\n */\n exports.selectiveNotDeepExtend = function (props, a, b) {\n var allowDeletion = arguments.length <= 3 || arguments[3] === undefined ? false : arguments[3];\n\n // TODO: add support for Arrays to deepExtend\n if (Array.isArray(b)) {\n throw new TypeError('Arrays are not supported by deepExtend');\n }\n for (var prop in b) {\n if (b.hasOwnProperty(prop)) {\n if (props.indexOf(prop) == -1) {\n if (b[prop] && b[prop].constructor === Object) {\n if (a[prop] === undefined) {\n a[prop] = {};\n }\n if (a[prop].constructor === Object) {\n exports.deepExtend(a[prop], b[prop]);\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n } else if (Array.isArray(b[prop])) {\n a[prop] = [];\n for (var i = 0; i < b[prop].length; i++) {\n a[prop].push(b[prop][i]);\n }\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n }\n }\n }\n return a;\n };\n\n /**\n * Deep extend an object a with the properties of object b\n * @param {Object} a\n * @param {Object} b\n * @param [Boolean] protoExtend --> optional parameter. If true, the prototype values will also be extended.\n * (ie. the options objects that inherit from others will also get the inherited options)\n * @param [Boolean] global --> optional parameter. If true, the values of fields that are null will not deleted\n * @returns {Object}\n */\n exports.deepExtend = function (a, b, protoExtend, allowDeletion) {\n for (var prop in b) {\n if (b.hasOwnProperty(prop) || protoExtend === true) {\n if (b[prop] && b[prop].constructor === Object) {\n if (a[prop] === undefined) {\n a[prop] = {};\n }\n if (a[prop].constructor === Object) {\n exports.deepExtend(a[prop], b[prop], protoExtend);\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n } else if (Array.isArray(b[prop])) {\n a[prop] = [];\n for (var i = 0; i < b[prop].length; i++) {\n a[prop].push(b[prop][i]);\n }\n } else {\n if (b[prop] === null && a[prop] !== undefined && allowDeletion === true) {\n delete a[prop];\n } else {\n a[prop] = b[prop];\n }\n }\n }\n }\n return a;\n };\n\n /**\n * Test whether all elements in two arrays are equal.\n * @param {Array} a\n * @param {Array} b\n * @return {boolean} Returns true if both arrays have the same length and same\n * elements.\n */\n exports.equalArray = function (a, b) {\n if (a.length != b.length) return false;\n\n for (var i = 0, len = a.length; i < len; i++) {\n if (a[i] != b[i]) return false;\n }\n\n return true;\n };\n\n /**\n * Convert an object to another type\n * @param {Boolean | Number | String | Date | Moment | Null | undefined} object\n * @param {String | undefined} type Name of the type. Available types:\n * 'Boolean', 'Number', 'String',\n * 'Date', 'Moment', ISODate', 'ASPDate'.\n * @return {*} object\n * @throws Error\n */\n exports.convert = function (object, type) {\n var match;\n\n if (object === undefined) {\n return undefined;\n }\n if (object === null) {\n return null;\n }\n\n if (!type) {\n return object;\n }\n if (!(typeof type === 'string') && !(type instanceof String)) {\n throw new Error('Type must be a string');\n }\n\n //noinspection FallthroughInSwitchStatementJS\n switch (type) {\n case 'boolean':\n case 'Boolean':\n return Boolean(object);\n\n case 'number':\n case 'Number':\n return Number(object.valueOf());\n\n case 'string':\n case 'String':\n return String(object);\n\n case 'Date':\n if (exports.isNumber(object)) {\n return new Date(object);\n }\n if (object instanceof Date) {\n return new Date(object.valueOf());\n } else if (moment.isMoment(object)) {\n return new Date(object.valueOf());\n }\n if (exports.isString(object)) {\n match = ASPDateRegex.exec(object);\n if (match) {\n // object is an ASP date\n return new Date(Number(match[1])); // parse number\n } else {\n return moment(object).toDate(); // parse string\n }\n } else {\n throw new Error('Cannot convert object of type ' + exports.getType(object) + ' to type Date');\n }\n\n case 'Moment':\n if (exports.isNumber(object)) {\n return moment(object);\n }\n if (object instanceof Date) {\n return moment(object.valueOf());\n } else if (moment.isMoment(object)) {\n return moment(object);\n }\n if (exports.isString(object)) {\n match = ASPDateRegex.exec(object);\n if (match) {\n // object is an ASP date\n return moment(Number(match[1])); // parse number\n } else {\n return moment(object); // parse string\n }\n } else {\n throw new Error('Cannot convert object of type ' + exports.getType(object) + ' to type Date');\n }\n\n case 'ISODate':\n if (exports.isNumber(object)) {\n return new Date(object);\n } else if (object instanceof Date) {\n return object.toISOString();\n } else if (moment.isMoment(object)) {\n return object.toDate().toISOString();\n } else if (exports.isString(object)) {\n match = ASPDateRegex.exec(object);\n if (match) {\n // object is an ASP date\n return new Date(Number(match[1])).toISOString(); // parse number\n } else {\n return new Date(object).toISOString(); // parse string\n }\n } else {\n throw new Error('Cannot convert object of type ' + exports.getType(object) + ' to type ISODate');\n }\n\n case 'ASPDate':\n if (exports.isNumber(object)) {\n return '/Date(' + object + ')/';\n } else if (object instanceof Date) {\n return '/Date(' + object.valueOf() + ')/';\n } else if (exports.isString(object)) {\n match = ASPDateRegex.exec(object);\n var value;\n if (match) {\n // object is an ASP date\n value = new Date(Number(match[1])).valueOf(); // parse number\n } else {\n value = new Date(object).valueOf(); // parse string\n }\n return '/Date(' + value + ')/';\n } else {\n throw new Error('Cannot convert object of type ' + exports.getType(object) + ' to type ASPDate');\n }\n\n default:\n throw new Error('Unknown type \"' + type + '\"');\n }\n };\n\n // parse ASP.Net Date pattern,\n // for example '/Date(1198908717056)/' or '/Date(1198908717056-0700)/'\n // code from http://momentjs.com/\n var ASPDateRegex = /^\\/?Date\\((\\-?\\d+)/i;\n\n /**\n * Get the type of an object, for example exports.getType([]) returns 'Array'\n * @param {*} object\n * @return {String} type\n */\n exports.getType = function (object) {\n var type = typeof object;\n\n if (type == 'object') {\n if (object === null) {\n return 'null';\n }\n if (object instanceof Boolean) {\n return 'Boolean';\n }\n if (object instanceof Number) {\n return 'Number';\n }\n if (object instanceof String) {\n return 'String';\n }\n if (Array.isArray(object)) {\n return 'Array';\n }\n if (object instanceof Date) {\n return 'Date';\n }\n return 'Object';\n } else if (type == 'number') {\n return 'Number';\n } else if (type == 'boolean') {\n return 'Boolean';\n } else if (type == 'string') {\n return 'String';\n } else if (type === undefined) {\n return 'undefined';\n }\n\n return type;\n };\n\n /**\n * Used to extend an array and copy it. This is used to propagate paths recursively.\n *\n * @param arr\n * @param newValue\n * @returns {Array}\n */\n exports.copyAndExtendArray = function (arr, newValue) {\n var newArr = [];\n for (var i = 0; i < arr.length; i++) {\n newArr.push(arr[i]);\n }\n newArr.push(newValue);\n return newArr;\n };\n\n /**\n * Used to extend an array and copy it. This is used to propagate paths recursively.\n *\n * @param arr\n * @param newValue\n * @returns {Array}\n */\n exports.copyArray = function (arr) {\n var newArr = [];\n for (var i = 0; i < arr.length; i++) {\n newArr.push(arr[i]);\n }\n return newArr;\n };\n\n /**\n * Retrieve the absolute left value of a DOM element\n * @param {Element} elem A dom element, for example a div\n * @return {number} left The absolute left position of this element\n * in the browser page.\n */\n exports.getAbsoluteLeft = function (elem) {\n return elem.getBoundingClientRect().left;\n };\n\n /**\n * Retrieve the absolute top value of a DOM element\n * @param {Element} elem A dom element, for example a div\n * @return {number} top The absolute top position of this element\n * in the browser page.\n */\n exports.getAbsoluteTop = function (elem) {\n return elem.getBoundingClientRect().top;\n };\n\n /**\n * add a className to the given elements style\n * @param {Element} elem\n * @param {String} className\n */\n exports.addClassName = function (elem, className) {\n var classes = elem.className.split(' ');\n if (classes.indexOf(className) == -1) {\n classes.push(className); // add the class to the array\n elem.className = classes.join(' ');\n }\n };\n\n /**\n * add a className to the given elements style\n * @param {Element} elem\n * @param {String} className\n */\n exports.removeClassName = function (elem, className) {\n var classes = elem.className.split(' ');\n var index = classes.indexOf(className);\n if (index != -1) {\n classes.splice(index, 1); // remove the class from the array\n elem.className = classes.join(' ');\n }\n };\n\n /**\n * For each method for both arrays and objects.\n * In case of an array, the built-in Array.forEach() is applied.\n * In case of an Object, the method loops over all properties of the object.\n * @param {Object | Array} object An Object or Array\n * @param {function} callback Callback method, called for each item in\n * the object or array with three parameters:\n * callback(value, index, object)\n */\n exports.forEach = function (object, callback) {\n var i, len;\n if (Array.isArray(object)) {\n // array\n for (i = 0, len = object.length; i < len; i++) {\n callback(object[i], i, object);\n }\n } else {\n // object\n for (i in object) {\n if (object.hasOwnProperty(i)) {\n callback(object[i], i, object);\n }\n }\n }\n };\n\n /**\n * Convert an object into an array: all objects properties are put into the\n * array. The resulting array is unordered.\n * @param {Object} object\n * @param {Array} array\n */\n exports.toArray = function (object) {\n var array = [];\n\n for (var prop in object) {\n if (object.hasOwnProperty(prop)) array.push(object[prop]);\n }\n\n return array;\n };\n\n /**\n * Update a property in an object\n * @param {Object} object\n * @param {String} key\n * @param {*} value\n * @return {Boolean} changed\n */\n exports.updateProperty = function (object, key, value) {\n if (object[key] !== value) {\n object[key] = value;\n return true;\n } else {\n return false;\n }\n };\n\n /**\n * Throttle the given function to be only executed once every `wait` milliseconds\n * @param {function} fn\n * @param {number} wait Time in milliseconds\n * @returns {function} Returns the throttled function\n */\n exports.throttle = function (fn, wait) {\n var timeout = null;\n var needExecution = false;\n\n return function throttled() {\n if (!timeout) {\n needExecution = false;\n fn();\n\n timeout = setTimeout(function () {\n timeout = null;\n if (needExecution) {\n throttled();\n }\n }, wait);\n } else {\n needExecution = true;\n }\n };\n };\n\n /**\n * Add and event listener. Works for all browsers\n * @param {Element} element An html element\n * @param {string} action The action, for example \"click\",\n * without the prefix \"on\"\n * @param {function} listener The callback function to be executed\n * @param {boolean} [useCapture]\n */\n exports.addEventListener = function (element, action, listener, useCapture) {\n if (element.addEventListener) {\n if (useCapture === undefined) useCapture = false;\n\n if (action === \"mousewheel\" && navigator.userAgent.indexOf(\"Firefox\") >= 0) {\n action = \"DOMMouseScroll\"; // For Firefox\n }\n\n element.addEventListener(action, listener, useCapture);\n } else {\n element.attachEvent(\"on\" + action, listener); // IE browsers\n }\n };\n\n /**\n * Remove an event listener from an element\n * @param {Element} element An html dom element\n * @param {string} action The name of the event, for example \"mousedown\"\n * @param {function} listener The listener function\n * @param {boolean} [useCapture]\n */\n exports.removeEventListener = function (element, action, listener, useCapture) {\n if (element.removeEventListener) {\n // non-IE browsers\n if (useCapture === undefined) useCapture = false;\n\n if (action === \"mousewheel\" && navigator.userAgent.indexOf(\"Firefox\") >= 0) {\n action = \"DOMMouseScroll\"; // For Firefox\n }\n\n element.removeEventListener(action, listener, useCapture);\n } else {\n // IE browsers\n element.detachEvent(\"on\" + action, listener);\n }\n };\n\n /**\n * Cancels the event if it is cancelable, without stopping further propagation of the event.\n */\n exports.preventDefault = function (event) {\n if (!event) event = window.event;\n\n if (event.preventDefault) {\n event.preventDefault(); // non-IE browsers\n } else {\n event.returnValue = false; // IE browsers\n }\n };\n\n /**\n * Get HTML element which is the target of the event\n * @param {Event} event\n * @return {Element} target element\n */\n exports.getTarget = function (event) {\n // code from http://www.quirksmode.org/js/events_properties.html\n if (!event) {\n event = window.event;\n }\n\n var target;\n\n if (event.target) {\n target = event.target;\n } else if (event.srcElement) {\n target = event.srcElement;\n }\n\n if (target.nodeType != undefined && target.nodeType == 3) {\n // defeat Safari bug\n target = target.parentNode;\n }\n\n return target;\n };\n\n /**\n * Check if given element contains given parent somewhere in the DOM tree\n * @param {Element} element\n * @param {Element} parent\n */\n exports.hasParent = function (element, parent) {\n var e = element;\n\n while (e) {\n if (e === parent) {\n return true;\n }\n e = e.parentNode;\n }\n\n return false;\n };\n\n exports.option = {};\n\n /**\n * Convert a value into a boolean\n * @param {Boolean | function | undefined} value\n * @param {Boolean} [defaultValue]\n * @returns {Boolean} bool\n */\n exports.option.asBoolean = function (value, defaultValue) {\n if (typeof value == 'function') {\n value = value();\n }\n\n if (value != null) {\n return value != false;\n }\n\n return defaultValue || null;\n };\n\n /**\n * Convert a value into a number\n * @param {Boolean | function | undefined} value\n * @param {Number} [defaultValue]\n * @returns {Number} number\n */\n exports.option.asNumber = function (value, defaultValue) {\n if (typeof value == 'function') {\n value = value();\n }\n\n if (value != null) {\n return Number(value) || defaultValue || null;\n }\n\n return defaultValue || null;\n };\n\n /**\n * Convert a value into a string\n * @param {String | function | undefined} value\n * @param {String} [defaultValue]\n * @returns {String} str\n */\n exports.option.asString = function (value, defaultValue) {\n if (typeof value == 'function') {\n value = value();\n }\n\n if (value != null) {\n return String(value);\n }\n\n return defaultValue || null;\n };\n\n /**\n * Convert a size or location into a string with pixels or a percentage\n * @param {String | Number | function | undefined} value\n * @param {String} [defaultValue]\n * @returns {String} size\n */\n exports.option.asSize = function (value, defaultValue) {\n if (typeof value == 'function') {\n value = value();\n }\n\n if (exports.isString(value)) {\n return value;\n } else if (exports.isNumber(value)) {\n return value + 'px';\n } else {\n return defaultValue || null;\n }\n };\n\n /**\n * Convert a value into a DOM element\n * @param {HTMLElement | function | undefined} value\n * @param {HTMLElement} [defaultValue]\n * @returns {HTMLElement | null} dom\n */\n exports.option.asElement = function (value, defaultValue) {\n if (typeof value == 'function') {\n value = value();\n }\n\n return value || defaultValue || null;\n };\n\n /**\n * http://stackoverflow.com/questions/5623838/rgb-to-hex-and-hex-to-rgb\n *\n * @param {String} hex\n * @returns {{r: *, g: *, b: *}} | 255 range\n */\n exports.hexToRGB = function (hex) {\n // Expand shorthand form (e.g. \"03F\") to full form (e.g. \"0033FF\")\n var shorthandRegex = /^#?([a-f\\d])([a-f\\d])([a-f\\d])$/i;\n hex = hex.replace(shorthandRegex, function (m, r, g, b) {\n return r + r + g + g + b + b;\n });\n var result = /^#?([a-f\\d]{2})([a-f\\d]{2})([a-f\\d]{2})$/i.exec(hex);\n return result ? {\n r: parseInt(result[1], 16),\n g: parseInt(result[2], 16),\n b: parseInt(result[3], 16)\n } : null;\n };\n\n /**\n * This function takes color in hex format or rgb() or rgba() format and overrides the opacity. Returns rgba() string.\n * @param color\n * @param opacity\n * @returns {*}\n */\n exports.overrideOpacity = function (color, opacity) {\n if (color.indexOf(\"rgba\") != -1) {\n return color;\n } else if (color.indexOf(\"rgb\") != -1) {\n var rgb = color.substr(color.indexOf(\"(\") + 1).replace(\")\", \"\").split(\",\");\n return \"rgba(\" + rgb[0] + \",\" + rgb[1] + \",\" + rgb[2] + \",\" + opacity + \")\";\n } else {\n var rgb = exports.hexToRGB(color);\n if (rgb == null) {\n return color;\n } else {\n return \"rgba(\" + rgb.r + \",\" + rgb.g + \",\" + rgb.b + \",\" + opacity + \")\";\n }\n }\n };\n\n /**\n *\n * @param red 0 -- 255\n * @param green 0 -- 255\n * @param blue 0 -- 255\n * @returns {string}\n * @constructor\n */\n exports.RGBToHex = function (red, green, blue) {\n return \"#\" + ((1 << 24) + (red << 16) + (green << 8) + blue).toString(16).slice(1);\n };\n\n /**\n * Parse a color property into an object with border, background, and\n * highlight colors\n * @param {Object | String} color\n * @return {Object} colorObject\n */\n exports.parseColor = function (color) {\n var c;\n if (exports.isString(color) === true) {\n if (exports.isValidRGB(color) === true) {\n var rgb = color.substr(4).substr(0, color.length - 5).split(',').map(function (value) {\n return parseInt(value);\n });\n color = exports.RGBToHex(rgb[0], rgb[1], rgb[2]);\n }\n if (exports.isValidHex(color) === true) {\n var hsv = exports.hexToHSV(color);\n var lighterColorHSV = { h: hsv.h, s: hsv.s * 0.8, v: Math.min(1, hsv.v * 1.02) };\n var darkerColorHSV = { h: hsv.h, s: Math.min(1, hsv.s * 1.25), v: hsv.v * 0.8 };\n var darkerColorHex = exports.HSVToHex(darkerColorHSV.h, darkerColorHSV.s, darkerColorHSV.v);\n var lighterColorHex = exports.HSVToHex(lighterColorHSV.h, lighterColorHSV.s, lighterColorHSV.v);\n c = {\n background: color,\n border: darkerColorHex,\n highlight: {\n background: lighterColorHex,\n border: darkerColorHex\n },\n hover: {\n background: lighterColorHex,\n border: darkerColorHex\n }\n };\n } else {\n c = {\n background: color,\n border: color,\n highlight: {\n background: color,\n border: color\n },\n hover: {\n background: color,\n border: color\n }\n };\n }\n } else {\n c = {};\n c.background = color.background || undefined;\n c.border = color.border || undefined;\n\n if (exports.isString(color.highlight)) {\n c.highlight = {\n border: color.highlight,\n background: color.highlight\n };\n } else {\n c.highlight = {};\n c.highlight.background = color.highlight && color.highlight.background || undefined;\n c.highlight.border = color.highlight && color.highlight.border || undefined;\n }\n\n if (exports.isString(color.hover)) {\n c.hover = {\n border: color.hover,\n background: color.hover\n };\n } else {\n c.hover = {};\n c.hover.background = color.hover && color.hover.background || undefined;\n c.hover.border = color.hover && color.hover.border || undefined;\n }\n }\n\n return c;\n };\n\n /**\n * http://www.javascripter.net/faq/rgb2hsv.htm\n *\n * @param red\n * @param green\n * @param blue\n * @returns {*}\n * @constructor\n */\n exports.RGBToHSV = function (red, green, blue) {\n red = red / 255;green = green / 255;blue = blue / 255;\n var minRGB = Math.min(red, Math.min(green, blue));\n var maxRGB = Math.max(red, Math.max(green, blue));\n\n // Black-gray-white\n if (minRGB == maxRGB) {\n return { h: 0, s: 0, v: minRGB };\n }\n\n // Colors other than black-gray-white:\n var d = red == minRGB ? green - blue : blue == minRGB ? red - green : blue - red;\n var h = red == minRGB ? 3 : blue == minRGB ? 1 : 5;\n var hue = 60 * (h - d / (maxRGB - minRGB)) / 360;\n var saturation = (maxRGB - minRGB) / maxRGB;\n var value = maxRGB;\n return { h: hue, s: saturation, v: value };\n };\n\n var cssUtil = {\n // split a string with css styles into an object with key/values\n split: function split(cssText) {\n var styles = {};\n\n cssText.split(';').forEach(function (style) {\n if (style.trim() != '') {\n var parts = style.split(':');\n var key = parts[0].trim();\n var value = parts[1].trim();\n styles[key] = value;\n }\n });\n\n return styles;\n },\n\n // build a css text string from an object with key/values\n join: function join(styles) {\n return Object.keys(styles).map(function (key) {\n return key + ': ' + styles[key];\n }).join('; ');\n }\n };\n\n /**\n * Append a string with css styles to an element\n * @param {Element} element\n * @param {String} cssText\n */\n exports.addCssText = function (element, cssText) {\n var currentStyles = cssUtil.split(element.style.cssText);\n var newStyles = cssUtil.split(cssText);\n var styles = exports.extend(currentStyles, newStyles);\n\n element.style.cssText = cssUtil.join(styles);\n };\n\n /**\n * Remove a string with css styles from an element\n * @param {Element} element\n * @param {String} cssText\n */\n exports.removeCssText = function (element, cssText) {\n var styles = cssUtil.split(element.style.cssText);\n var removeStyles = cssUtil.split(cssText);\n\n for (var key in removeStyles) {\n if (removeStyles.hasOwnProperty(key)) {\n delete styles[key];\n }\n }\n\n element.style.cssText = cssUtil.join(styles);\n };\n\n /**\n * https://gist.github.com/mjijackson/5311256\n * @param h\n * @param s\n * @param v\n * @returns {{r: number, g: number, b: number}}\n * @constructor\n */\n exports.HSVToRGB = function (h, s, v) {\n var r, g, b;\n\n var i = Math.floor(h * 6);\n var f = h * 6 - i;\n var p = v * (1 - s);\n var q = v * (1 - f * s);\n var t = v * (1 - (1 - f) * s);\n\n switch (i % 6) {\n case 0:\n r = v, g = t, b = p;break;\n case 1:\n r = q, g = v, b = p;break;\n case 2:\n r = p, g = v, b = t;break;\n case 3:\n r = p, g = q, b = v;break;\n case 4:\n r = t, g = p, b = v;break;\n case 5:\n r = v, g = p, b = q;break;\n }\n\n return { r: Math.floor(r * 255), g: Math.floor(g * 255), b: Math.floor(b * 255) };\n };\n\n exports.HSVToHex = function (h, s, v) {\n var rgb = exports.HSVToRGB(h, s, v);\n return exports.RGBToHex(rgb.r, rgb.g, rgb.b);\n };\n\n exports.hexToHSV = function (hex) {\n var rgb = exports.hexToRGB(hex);\n return exports.RGBToHSV(rgb.r, rgb.g, rgb.b);\n };\n\n exports.isValidHex = function (hex) {\n var isOk = /(^#[0-9A-F]{6}$)|(^#[0-9A-F]{3}$)/i.test(hex);\n return isOk;\n };\n\n exports.isValidRGB = function (rgb) {\n rgb = rgb.replace(\" \", \"\");\n var isOk = /rgb\\((\\d{1,3}),(\\d{1,3}),(\\d{1,3})\\)/i.test(rgb);\n return isOk;\n };\n exports.isValidRGBA = function (rgba) {\n rgba = rgba.replace(\" \", \"\");\n var isOk = /rgba\\((\\d{1,3}),(\\d{1,3}),(\\d{1,3}),(.{1,3})\\)/i.test(rgba);\n return isOk;\n };\n\n /**\n * This recursively redirects the prototype of JSON objects to the referenceObject\n * This is used for default options.\n *\n * @param referenceObject\n * @returns {*}\n */\n exports.selectiveBridgeObject = function (fields, referenceObject) {\n if (typeof referenceObject == \"object\") {\n var objectTo = Object.create(referenceObject);\n for (var i = 0; i < fields.length; i++) {\n if (referenceObject.hasOwnProperty(fields[i])) {\n if (typeof referenceObject[fields[i]] == \"object\") {\n objectTo[fields[i]] = exports.bridgeObject(referenceObject[fields[i]]);\n }\n }\n }\n return objectTo;\n } else {\n return null;\n }\n };\n\n /**\n * This recursively redirects the prototype of JSON objects to the referenceObject\n * This is used for default options.\n *\n * @param referenceObject\n * @returns {*}\n */\n exports.bridgeObject = function (referenceObject) {\n if (typeof referenceObject == \"object\") {\n var objectTo = Object.create(referenceObject);\n for (var i in referenceObject) {\n if (referenceObject.hasOwnProperty(i)) {\n if (typeof referenceObject[i] == \"object\") {\n objectTo[i] = exports.bridgeObject(referenceObject[i]);\n }\n }\n }\n return objectTo;\n } else {\n return null;\n }\n };\n\n /**\n * This method provides a stable sort implementation, very fast for presorted data\n *\n * @param a the array\n * @param a order comparator\n * @returns {the array}\n */\n exports.insertSort = function (a, compare) {\n for (var i = 0; i < a.length; i++) {\n var k = a[i];\n for (var j = i; j > 0 && compare(k, a[j - 1]) < 0; j--) {\n a[j] = a[j - 1];\n }\n a[j] = k;\n }\n return a;\n };\n\n /**\n * this is used to set the options of subobjects in the options object. A requirement of these subobjects\n * is that they have an 'enabled' element which is optional for the user but mandatory for the program.\n *\n * @param [object] mergeTarget | this is either this.options or the options used for the groups.\n * @param [object] options | options\n * @param [String] option | this is the option key in the options argument\n */\n exports.mergeOptions = function (mergeTarget, options, option) {\n var allowDeletion = arguments.length <= 3 || arguments[3] === undefined ? false : arguments[3];\n var globalOptions = arguments.length <= 4 || arguments[4] === undefined ? {} : arguments[4];\n\n if (options[option] === null) {\n mergeTarget[option] = Object.create(globalOptions[option]);\n } else {\n if (options[option] !== undefined) {\n if (typeof options[option] === 'boolean') {\n mergeTarget[option].enabled = options[option];\n } else {\n if (options[option].enabled === undefined) {\n mergeTarget[option].enabled = true;\n }\n for (var prop in options[option]) {\n if (options[option].hasOwnProperty(prop)) {\n mergeTarget[option][prop] = options[option][prop];\n }\n }\n }\n }\n }\n };\n\n /**\n * This function does a binary search for a visible item in a sorted list. If we find a visible item, the code that uses\n * this function will then iterate in both directions over this sorted list to find all visible items.\n *\n * @param {Item[]} orderedItems | Items ordered by start\n * @param {function} comparator | -1 is lower, 0 is equal, 1 is higher\n * @param {String} field\n * @param {String} field2\n * @returns {number}\n * @private\n */\n exports.binarySearchCustom = function (orderedItems, comparator, field, field2) {\n var maxIterations = 10000;\n var iteration = 0;\n var low = 0;\n var high = orderedItems.length - 1;\n\n while (low <= high && iteration < maxIterations) {\n var middle = Math.floor((low + high) / 2);\n\n var item = orderedItems[middle];\n var value = field2 === undefined ? item[field] : item[field][field2];\n\n var searchResult = comparator(value);\n if (searchResult == 0) {\n // jihaa, found a visible item!\n return middle;\n } else if (searchResult == -1) {\n // it is too small --> increase low\n low = middle + 1;\n } else {\n // it is too big --> decrease high\n high = middle - 1;\n }\n\n iteration++;\n }\n\n return -1;\n };\n\n /**\n * This function does a binary search for a specific value in a sorted array. If it does not exist but is in between of\n * two values, we return either the one before or the one after, depending on user input\n * If it is found, we return the index, else -1.\n *\n * @param {Array} orderedItems\n * @param {{start: number, end: number}} target\n * @param {String} field\n * @param {String} sidePreference 'before' or 'after'\n * @param {function} comparator an optional comparator, returning -1,0,1 for <,==,>.\n * @returns {number}\n * @private\n */\n exports.binarySearchValue = function (orderedItems, target, field, sidePreference, comparator) {\n var maxIterations = 10000;\n var iteration = 0;\n var low = 0;\n var high = orderedItems.length - 1;\n var prevValue, value, nextValue, middle;\n\n var comparator = comparator != undefined ? comparator : function (a, b) {\n return a == b ? 0 : a < b ? -1 : 1;\n };\n\n while (low <= high && iteration < maxIterations) {\n // get a new guess\n middle = Math.floor(0.5 * (high + low));\n prevValue = orderedItems[Math.max(0, middle - 1)][field];\n value = orderedItems[middle][field];\n nextValue = orderedItems[Math.min(orderedItems.length - 1, middle + 1)][field];\n\n if (comparator(value, target) == 0) {\n // we found the target\n return middle;\n } else if (comparator(prevValue, target) < 0 && comparator(value, target) > 0) {\n // target is in between of the previous and the current\n return sidePreference == 'before' ? Math.max(0, middle - 1) : middle;\n } else if (comparator(value, target) < 0 && comparator(nextValue, target) > 0) {\n // target is in between of the current and the next\n return sidePreference == 'before' ? middle : Math.min(orderedItems.length - 1, middle + 1);\n } else {\n // didnt find the target, we need to change our boundaries.\n if (comparator(value, target) < 0) {\n // it is too small --> increase low\n low = middle + 1;\n } else {\n // it is too big --> decrease high\n high = middle - 1;\n }\n }\n iteration++;\n }\n\n // didnt find anything. Return -1.\n return -1;\n };\n\n /*\n * Easing Functions - inspired from http://gizma.com/easing/\n * only considering the t value for the range [0, 1] => [0, 1]\n * https://gist.github.com/gre/1650294\n */\n exports.easingFunctions = {\n // no easing, no acceleration\n linear: function linear(t) {\n return t;\n },\n // accelerating from zero velocity\n easeInQuad: function easeInQuad(t) {\n return t * t;\n },\n // decelerating to zero velocity\n easeOutQuad: function easeOutQuad(t) {\n return t * (2 - t);\n },\n // acceleration until halfway, then deceleration\n easeInOutQuad: function easeInOutQuad(t) {\n return t < .5 ? 2 * t * t : -1 + (4 - 2 * t) * t;\n },\n // accelerating from zero velocity\n easeInCubic: function easeInCubic(t) {\n return t * t * t;\n },\n // decelerating to zero velocity\n easeOutCubic: function easeOutCubic(t) {\n return --t * t * t + 1;\n },\n // acceleration until halfway, then deceleration\n easeInOutCubic: function easeInOutCubic(t) {\n return t < .5 ? 4 * t * t * t : (t - 1) * (2 * t - 2) * (2 * t - 2) + 1;\n },\n // accelerating from zero velocity\n easeInQuart: function easeInQuart(t) {\n return t * t * t * t;\n },\n // decelerating to zero velocity\n easeOutQuart: function easeOutQuart(t) {\n return 1 - --t * t * t * t;\n },\n // acceleration until halfway, then deceleration\n easeInOutQuart: function easeInOutQuart(t) {\n return t < .5 ? 8 * t * t * t * t : 1 - 8 * --t * t * t * t;\n },\n // accelerating from zero velocity\n easeInQuint: function easeInQuint(t) {\n return t * t * t * t * t;\n },\n // decelerating to zero velocity\n easeOutQuint: function easeOutQuint(t) {\n return 1 + --t * t * t * t * t;\n },\n // acceleration until halfway, then deceleration\n easeInOutQuint: function easeInOutQuint(t) {\n return t < .5 ? 16 * t * t * t * t * t : 1 + 16 * --t * t * t * t * t;\n }\n };\n\n/***/ },\n/* 2 */\n/***/ function(module, exports, __webpack_require__) {\n\n // first check if moment.js is already loaded in the browser window, if so,\n // use this instance. Else, load via commonjs.\n 'use strict';\n\n module.exports = typeof window !== 'undefined' && window['moment'] || __webpack_require__(3);\n\n/***/ },\n/* 3 */\n/***/ function(module, exports, __webpack_require__) {\n\n /* WEBPACK VAR INJECTION */(function(module) {//! moment.js\n //! version : 2.11.2\n //! authors : Tim Wood, Iskren Chernev, Moment.js contributors\n //! license : MIT\n //! momentjs.com\n\n ;(function (global, factory) {\n true ? module.exports = factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n global.moment = factory()\n }(this, function () { 'use strict';\n\n var hookCallback;\n\n function utils_hooks__hooks () {\n return hookCallback.apply(null, arguments);\n }\n\n // This is done to register the method called with moment()\n // without creating circular dependencies.\n function setHookCallback (callback) {\n hookCallback = callback;\n }\n\n function isArray(input) {\n return Object.prototype.toString.call(input) === '[object Array]';\n }\n\n function isDate(input) {\n return input instanceof Date || Object.prototype.toString.call(input) === '[object Date]';\n }\n\n function map(arr, fn) {\n var res = [], i;\n for (i = 0; i < arr.length; ++i) {\n res.push(fn(arr[i], i));\n }\n return res;\n }\n\n function hasOwnProp(a, b) {\n return Object.prototype.hasOwnProperty.call(a, b);\n }\n\n function extend(a, b) {\n for (var i in b) {\n if (hasOwnProp(b, i)) {\n a[i] = b[i];\n }\n }\n\n if (hasOwnProp(b, 'toString')) {\n a.toString = b.toString;\n }\n\n if (hasOwnProp(b, 'valueOf')) {\n a.valueOf = b.valueOf;\n }\n\n return a;\n }\n\n function create_utc__createUTC (input, format, locale, strict) {\n return createLocalOrUTC(input, format, locale, strict, true).utc();\n }\n\n function defaultParsingFlags() {\n // We need to deep clone this object.\n return {\n empty : false,\n unusedTokens : [],\n unusedInput : [],\n overflow : -2,\n charsLeftOver : 0,\n nullInput : false,\n invalidMonth : null,\n invalidFormat : false,\n userInvalidated : false,\n iso : false\n };\n }\n\n function getParsingFlags(m) {\n if (m._pf == null) {\n m._pf = defaultParsingFlags();\n }\n return m._pf;\n }\n\n function valid__isValid(m) {\n if (m._isValid == null) {\n var flags = getParsingFlags(m);\n m._isValid = !isNaN(m._d.getTime()) &&\n flags.overflow < 0 &&\n !flags.empty &&\n !flags.invalidMonth &&\n !flags.invalidWeekday &&\n !flags.nullInput &&\n !flags.invalidFormat &&\n !flags.userInvalidated;\n\n if (m._strict) {\n m._isValid = m._isValid &&\n flags.charsLeftOver === 0 &&\n flags.unusedTokens.length === 0 &&\n flags.bigHour === undefined;\n }\n }\n return m._isValid;\n }\n\n function valid__createInvalid (flags) {\n var m = create_utc__createUTC(NaN);\n if (flags != null) {\n extend(getParsingFlags(m), flags);\n }\n else {\n getParsingFlags(m).userInvalidated = true;\n }\n\n return m;\n }\n\n function isUndefined(input) {\n return input === void 0;\n }\n\n // Plugins that add properties should also add the key here (null value),\n // so we can properly clone ourselves.\n var momentProperties = utils_hooks__hooks.momentProperties = [];\n\n function copyConfig(to, from) {\n var i, prop, val;\n\n if (!isUndefined(from._isAMomentObject)) {\n to._isAMomentObject = from._isAMomentObject;\n }\n if (!isUndefined(from._i)) {\n to._i = from._i;\n }\n if (!isUndefined(from._f)) {\n to._f = from._f;\n }\n if (!isUndefined(from._l)) {\n to._l = from._l;\n }\n if (!isUndefined(from._strict)) {\n to._strict = from._strict;\n }\n if (!isUndefined(from._tzm)) {\n to._tzm = from._tzm;\n }\n if (!isUndefined(from._isUTC)) {\n to._isUTC = from._isUTC;\n }\n if (!isUndefined(from._offset)) {\n to._offset = from._offset;\n }\n if (!isUndefined(from._pf)) {\n to._pf = getParsingFlags(from);\n }\n if (!isUndefined(from._locale)) {\n to._locale = from._locale;\n }\n\n if (momentProperties.length > 0) {\n for (i in momentProperties) {\n prop = momentProperties[i];\n val = from[prop];\n if (!isUndefined(val)) {\n to[prop] = val;\n }\n }\n }\n\n return to;\n }\n\n var updateInProgress = false;\n\n // Moment prototype object\n function Moment(config) {\n copyConfig(this, config);\n this._d = new Date(config._d != null ? config._d.getTime() : NaN);\n // Prevent infinite loop in case updateOffset creates new moment\n // objects.\n if (updateInProgress === false) {\n updateInProgress = true;\n utils_hooks__hooks.updateOffset(this);\n updateInProgress = false;\n }\n }\n\n function isMoment (obj) {\n return obj instanceof Moment || (obj != null && obj._isAMomentObject != null);\n }\n\n function absFloor (number) {\n if (number < 0) {\n return Math.ceil(number);\n } else {\n return Math.floor(number);\n }\n }\n\n function toInt(argumentForCoercion) {\n var coercedNumber = +argumentForCoercion,\n value = 0;\n\n if (coercedNumber !== 0 && isFinite(coercedNumber)) {\n value = absFloor(coercedNumber);\n }\n\n return value;\n }\n\n // compare two arrays, return the number of differences\n function compareArrays(array1, array2, dontConvert) {\n var len = Math.min(array1.length, array2.length),\n lengthDiff = Math.abs(array1.length - array2.length),\n diffs = 0,\n i;\n for (i = 0; i < len; i++) {\n if ((dontConvert && array1[i] !== array2[i]) ||\n (!dontConvert && toInt(array1[i]) !== toInt(array2[i]))) {\n diffs++;\n }\n }\n return diffs + lengthDiff;\n }\n\n function Locale() {\n }\n\n // internal storage for locale config files\n var locales = {};\n var globalLocale;\n\n function normalizeLocale(key) {\n return key ? key.toLowerCase().replace('_', '-') : key;\n }\n\n // pick the locale from the array\n // try ['en-au', 'en-gb'] as 'en-au', 'en-gb', 'en', as in move through the list trying each\n // substring from most specific to least, but move to the next array item if it's a more specific variant than the current root\n function chooseLocale(names) {\n var i = 0, j, next, locale, split;\n\n while (i < names.length) {\n split = normalizeLocale(names[i]).split('-');\n j = split.length;\n next = normalizeLocale(names[i + 1]);\n next = next ? next.split('-') : null;\n while (j > 0) {\n locale = loadLocale(split.slice(0, j).join('-'));\n if (locale) {\n return locale;\n }\n if (next && next.length >= j && compareArrays(split, next, true) >= j - 1) {\n //the next array item is better than a shallower substring of this one\n break;\n }\n j--;\n }\n i++;\n }\n return null;\n }\n\n function loadLocale(name) {\n var oldLocale = null;\n // TODO: Find a better way to register and load all the locales in Node\n if (!locales[name] && (typeof module !== 'undefined') &&\n module && module.exports) {\n try {\n oldLocale = globalLocale._abbr;\n !(function webpackMissingModule() { var e = new Error(\"Cannot find module \\\"./locale\\\"\"); e.code = 'MODULE_NOT_FOUND'; throw e; }());\n // because defineLocale currently also sets the global locale, we\n // want to undo that for lazy loaded locales\n locale_locales__getSetGlobalLocale(oldLocale);\n } catch (e) { }\n }\n return locales[name];\n }\n\n // This function will load locale and then set the global locale. If\n // no arguments are passed in, it will simply return the current global\n // locale key.\n function locale_locales__getSetGlobalLocale (key, values) {\n var data;\n if (key) {\n if (isUndefined(values)) {\n data = locale_locales__getLocale(key);\n }\n else {\n data = defineLocale(key, values);\n }\n\n if (data) {\n // moment.duration._locale = moment._locale = data;\n globalLocale = data;\n }\n }\n\n return globalLocale._abbr;\n }\n\n function defineLocale (name, values) {\n if (values !== null) {\n values.abbr = name;\n locales[name] = locales[name] || new Locale();\n locales[name].set(values);\n\n // backwards compat for now: also set the locale\n locale_locales__getSetGlobalLocale(name);\n\n return locales[name];\n } else {\n // useful for testing\n delete locales[name];\n return null;\n }\n }\n\n // returns locale data\n function locale_locales__getLocale (key) {\n var locale;\n\n if (key && key._locale && key._locale._abbr) {\n key = key._locale._abbr;\n }\n\n if (!key) {\n return globalLocale;\n }\n\n if (!isArray(key)) {\n //short-circuit everything else\n locale = loadLocale(key);\n if (locale) {\n return locale;\n }\n key = [key];\n }\n\n return chooseLocale(key);\n }\n\n var aliases = {};\n\n function addUnitAlias (unit, shorthand) {\n var lowerCase = unit.toLowerCase();\n aliases[lowerCase] = aliases[lowerCase + 's'] = aliases[shorthand] = unit;\n }\n\n function normalizeUnits(units) {\n return typeof units === 'string' ? aliases[units] || aliases[units.toLowerCase()] : undefined;\n }\n\n function normalizeObjectUnits(inputObject) {\n var normalizedInput = {},\n normalizedProp,\n prop;\n\n for (prop in inputObject) {\n if (hasOwnProp(inputObject, prop)) {\n normalizedProp = normalizeUnits(prop);\n if (normalizedProp) {\n normalizedInput[normalizedProp] = inputObject[prop];\n }\n }\n }\n\n return normalizedInput;\n }\n\n function isFunction(input) {\n return input instanceof Function || Object.prototype.toString.call(input) === '[object Function]';\n }\n\n function makeGetSet (unit, keepTime) {\n return function (value) {\n if (value != null) {\n get_set__set(this, unit, value);\n utils_hooks__hooks.updateOffset(this, keepTime);\n return this;\n } else {\n return get_set__get(this, unit);\n }\n };\n }\n\n function get_set__get (mom, unit) {\n return mom.isValid() ?\n mom._d['get' + (mom._isUTC ? 'UTC' : '') + unit]() : NaN;\n }\n\n function get_set__set (mom, unit, value) {\n if (mom.isValid()) {\n mom._d['set' + (mom._isUTC ? 'UTC' : '') + unit](value);\n }\n }\n\n // MOMENTS\n\n function getSet (units, value) {\n var unit;\n if (typeof units === 'object') {\n for (unit in units) {\n this.set(unit, units[unit]);\n }\n } else {\n units = normalizeUnits(units);\n if (isFunction(this[units])) {\n return this[units](value);\n }\n }\n return this;\n }\n\n function zeroFill(number, targetLength, forceSign) {\n var absNumber = '' + Math.abs(number),\n zerosToFill = targetLength - absNumber.length,\n sign = number >= 0;\n return (sign ? (forceSign ? '+' : '') : '-') +\n Math.pow(10, Math.max(0, zerosToFill)).toString().substr(1) + absNumber;\n }\n\n var formattingTokens = /(\\[[^\\[]*\\])|(\\\\)?([Hh]mm(ss)?|Mo|MM?M?M?|Do|DDDo|DD?D?D?|ddd?d?|do?|w[o|w]?|W[o|W]?|Qo?|YYYYYY|YYYYY|YYYY|YY|gg(ggg?)?|GG(GGG?)?|e|E|a|A|hh?|HH?|mm?|ss?|S{1,9}|x|X|zz?|ZZ?|.)/g;\n\n var localFormattingTokens = /(\\[[^\\[]*\\])|(\\\\)?(LTS|LT|LL?L?L?|l{1,4})/g;\n\n var formatFunctions = {};\n\n var formatTokenFunctions = {};\n\n // token: 'M'\n // padded: ['MM', 2]\n // ordinal: 'Mo'\n // callback: function () { this.month() + 1 }\n function addFormatToken (token, padded, ordinal, callback) {\n var func = callback;\n if (typeof callback === 'string') {\n func = function () {\n return this[callback]();\n };\n }\n if (token) {\n formatTokenFunctions[token] = func;\n }\n if (padded) {\n formatTokenFunctions[padded[0]] = function () {\n return zeroFill(func.apply(this, arguments), padded[1], padded[2]);\n };\n }\n if (ordinal) {\n formatTokenFunctions[ordinal] = function () {\n return this.localeData().ordinal(func.apply(this, arguments), token);\n };\n }\n }\n\n function removeFormattingTokens(input) {\n if (input.match(/\\[[\\s\\S]/)) {\n return input.replace(/^\\[|\\]$/g, '');\n }\n return input.replace(/\\\\/g, '');\n }\n\n function makeFormatFunction(format) {\n var array = format.match(formattingTokens), i, length;\n\n for (i = 0, length = array.length; i < length; i++) {\n if (formatTokenFunctions[array[i]]) {\n array[i] = formatTokenFunctions[array[i]];\n } else {\n array[i] = removeFormattingTokens(array[i]);\n }\n }\n\n return function (mom) {\n var output = '';\n for (i = 0; i < length; i++) {\n output += array[i] instanceof Function ? array[i].call(mom, format) : array[i];\n }\n return output;\n };\n }\n\n // format date using native date object\n function formatMoment(m, format) {\n if (!m.isValid()) {\n return m.localeData().invalidDate();\n }\n\n format = expandFormat(format, m.localeData());\n formatFunctions[format] = formatFunctions[format] || makeFormatFunction(format);\n\n return formatFunctions[format](m);\n }\n\n function expandFormat(format, locale) {\n var i = 5;\n\n function replaceLongDateFormatTokens(input) {\n return locale.longDateFormat(input) || input;\n }\n\n localFormattingTokens.lastIndex = 0;\n while (i >= 0 && localFormattingTokens.test(format)) {\n format = format.replace(localFormattingTokens, replaceLongDateFormatTokens);\n localFormattingTokens.lastIndex = 0;\n i -= 1;\n }\n\n return format;\n }\n\n var match1 = /\\d/; // 0 - 9\n var match2 = /\\d\\d/; // 00 - 99\n var match3 = /\\d{3}/; // 000 - 999\n var match4 = /\\d{4}/; // 0000 - 9999\n var match6 = /[+-]?\\d{6}/; // -999999 - 999999\n var match1to2 = /\\d\\d?/; // 0 - 99\n var match3to4 = /\\d\\d\\d\\d?/; // 999 - 9999\n var match5to6 = /\\d\\d\\d\\d\\d\\d?/; // 99999 - 999999\n var match1to3 = /\\d{1,3}/; // 0 - 999\n var match1to4 = /\\d{1,4}/; // 0 - 9999\n var match1to6 = /[+-]?\\d{1,6}/; // -999999 - 999999\n\n var matchUnsigned = /\\d+/; // 0 - inf\n var matchSigned = /[+-]?\\d+/; // -inf - inf\n\n var matchOffset = /Z|[+-]\\d\\d:?\\d\\d/gi; // +00:00 -00:00 +0000 -0000 or Z\n var matchShortOffset = /Z|[+-]\\d\\d(?::?\\d\\d)?/gi; // +00 -00 +00:00 -00:00 +0000 -0000 or Z\n\n var matchTimestamp = /[+-]?\\d+(\\.\\d{1,3})?/; // 123456789 123456789.123\n\n // any word (or two) characters or numbers including two/three word month in arabic.\n // includes scottish gaelic two word and hyphenated months\n var matchWord = /[0-9]*['a-z\\u00A0-\\u05FF\\u0700-\\uD7FF\\uF900-\\uFDCF\\uFDF0-\\uFFEF]+|[\\u0600-\\u06FF\\/]+(\\s*?[\\u0600-\\u06FF]+){1,2}/i;\n\n\n var regexes = {};\n\n function addRegexToken (token, regex, strictRegex) {\n regexes[token] = isFunction(regex) ? regex : function (isStrict, localeData) {\n return (isStrict && strictRegex) ? strictRegex : regex;\n };\n }\n\n function getParseRegexForToken (token, config) {\n if (!hasOwnProp(regexes, token)) {\n return new RegExp(unescapeFormat(token));\n }\n\n return regexes[token](config._strict, config._locale);\n }\n\n // Code from http://stackoverflow.com/questions/3561493/is-there-a-regexp-escape-function-in-javascript\n function unescapeFormat(s) {\n return regexEscape(s.replace('\\\\', '').replace(/\\\\(\\[)|\\\\(\\])|\\[([^\\]\\[]*)\\]|\\\\(.)/g, function (matched, p1, p2, p3, p4) {\n return p1 || p2 || p3 || p4;\n }));\n }\n\n function regexEscape(s) {\n return s.replace(/[-\\/\\\\^$*+?.()|[\\]{}]/g, '\\\\$&');\n }\n\n var tokens = {};\n\n function addParseToken (token, callback) {\n var i, func = callback;\n if (typeof token === 'string') {\n token = [token];\n }\n if (typeof callback === 'number') {\n func = function (input, array) {\n array[callback] = toInt(input);\n };\n }\n for (i = 0; i < token.length; i++) {\n tokens[token[i]] = func;\n }\n }\n\n function addWeekParseToken (token, callback) {\n addParseToken(token, function (input, array, config, token) {\n config._w = config._w || {};\n callback(input, config._w, config, token);\n });\n }\n\n function addTimeToArrayFromToken(token, input, config) {\n if (input != null && hasOwnProp(tokens, token)) {\n tokens[token](input, config._a, config, token);\n }\n }\n\n var YEAR = 0;\n var MONTH = 1;\n var DATE = 2;\n var HOUR = 3;\n var MINUTE = 4;\n var SECOND = 5;\n var MILLISECOND = 6;\n var WEEK = 7;\n var WEEKDAY = 8;\n\n function daysInMonth(year, month) {\n return new Date(Date.UTC(year, month + 1, 0)).getUTCDate();\n }\n\n // FORMATTING\n\n addFormatToken('M', ['MM', 2], 'Mo', function () {\n return this.month() + 1;\n });\n\n addFormatToken('MMM', 0, 0, function (format) {\n return this.localeData().monthsShort(this, format);\n });\n\n addFormatToken('MMMM', 0, 0, function (format) {\n return this.localeData().months(this, format);\n });\n\n // ALIASES\n\n addUnitAlias('month', 'M');\n\n // PARSING\n\n addRegexToken('M', match1to2);\n addRegexToken('MM', match1to2, match2);\n addRegexToken('MMM', function (isStrict, locale) {\n return locale.monthsShortRegex(isStrict);\n });\n addRegexToken('MMMM', function (isStrict, locale) {\n return locale.monthsRegex(isStrict);\n });\n\n addParseToken(['M', 'MM'], function (input, array) {\n array[MONTH] = toInt(input) - 1;\n });\n\n addParseToken(['MMM', 'MMMM'], function (input, array, config, token) {\n var month = config._locale.monthsParse(input, token, config._strict);\n // if we didn't find a month name, mark the date as invalid.\n if (month != null) {\n array[MONTH] = month;\n } else {\n getParsingFlags(config).invalidMonth = input;\n }\n });\n\n // LOCALES\n\n var MONTHS_IN_FORMAT = /D[oD]?(\\[[^\\[\\]]*\\]|\\s+)+MMMM?/;\n var defaultLocaleMonths = 'January_February_March_April_May_June_July_August_September_October_November_December'.split('_');\n function localeMonths (m, format) {\n return isArray(this._months) ? this._months[m.month()] :\n this._months[MONTHS_IN_FORMAT.test(format) ? 'format' : 'standalone'][m.month()];\n }\n\n var defaultLocaleMonthsShort = 'Jan_Feb_Mar_Apr_May_Jun_Jul_Aug_Sep_Oct_Nov_Dec'.split('_');\n function localeMonthsShort (m, format) {\n return isArray(this._monthsShort) ? this._monthsShort[m.month()] :\n this._monthsShort[MONTHS_IN_FORMAT.test(format) ? 'format' : 'standalone'][m.month()];\n }\n\n function localeMonthsParse (monthName, format, strict) {\n var i, mom, regex;\n\n if (!this._monthsParse) {\n this._monthsParse = [];\n this._longMonthsParse = [];\n this._shortMonthsParse = [];\n }\n\n for (i = 0; i < 12; i++) {\n // make the regex if we don't have it already\n mom = create_utc__createUTC([2000, i]);\n if (strict && !this._longMonthsParse[i]) {\n this._longMonthsParse[i] = new RegExp('^' + this.months(mom, '').replace('.', '') + '$', 'i');\n this._shortMonthsParse[i] = new RegExp('^' + this.monthsShort(mom, '').replace('.', '') + '$', 'i');\n }\n if (!strict && !this._monthsParse[i]) {\n regex = '^' + this.months(mom, '') + '|^' + this.monthsShort(mom, '');\n this._monthsParse[i] = new RegExp(regex.replace('.', ''), 'i');\n }\n // test the regex\n if (strict && format === 'MMMM' && this._longMonthsParse[i].test(monthName)) {\n return i;\n } else if (strict && format === 'MMM' && this._shortMonthsParse[i].test(monthName)) {\n return i;\n } else if (!strict && this._monthsParse[i].test(monthName)) {\n return i;\n }\n }\n }\n\n // MOMENTS\n\n function setMonth (mom, value) {\n var dayOfMonth;\n\n if (!mom.isValid()) {\n // No op\n return mom;\n }\n\n // TODO: Move this out of here!\n if (typeof value === 'string') {\n value = mom.localeData().monthsParse(value);\n // TODO: Another silent failure?\n if (typeof value !== 'number') {\n return mom;\n }\n }\n\n dayOfMonth = Math.min(mom.date(), daysInMonth(mom.year(), value));\n mom._d['set' + (mom._isUTC ? 'UTC' : '') + 'Month'](value, dayOfMonth);\n return mom;\n }\n\n function getSetMonth (value) {\n if (value != null) {\n setMonth(this, value);\n utils_hooks__hooks.updateOffset(this, true);\n return this;\n } else {\n return get_set__get(this, 'Month');\n }\n }\n\n function getDaysInMonth () {\n return daysInMonth(this.year(), this.month());\n }\n\n var defaultMonthsShortRegex = matchWord;\n function monthsShortRegex (isStrict) {\n if (this._monthsParseExact) {\n if (!hasOwnProp(this, '_monthsRegex')) {\n computeMonthsParse.call(this);\n }\n if (isStrict) {\n return this._monthsShortStrictRegex;\n } else {\n return this._monthsShortRegex;\n }\n } else {\n return this._monthsShortStrictRegex && isStrict ?\n this._monthsShortStrictRegex : this._monthsShortRegex;\n }\n }\n\n var defaultMonthsRegex = matchWord;\n function monthsRegex (isStrict) {\n if (this._monthsParseExact) {\n if (!hasOwnProp(this, '_monthsRegex')) {\n computeMonthsParse.call(this);\n }\n if (isStrict) {\n return this._monthsStrictRegex;\n } else {\n return this._monthsRegex;\n }\n } else {\n return this._monthsStrictRegex && isStrict ?\n this._monthsStrictRegex : this._monthsRegex;\n }\n }\n\n function computeMonthsParse () {\n function cmpLenRev(a, b) {\n return b.length - a.length;\n }\n\n var shortPieces = [], longPieces = [], mixedPieces = [],\n i, mom;\n for (i = 0; i < 12; i++) {\n // make the regex if we don't have it already\n mom = create_utc__createUTC([2000, i]);\n shortPieces.push(this.monthsShort(mom, ''));\n longPieces.push(this.months(mom, ''));\n mixedPieces.push(this.months(mom, ''));\n mixedPieces.push(this.monthsShort(mom, ''));\n }\n // Sorting makes sure if one month (or abbr) is a prefix of another it\n // will match the longer piece.\n shortPieces.sort(cmpLenRev);\n longPieces.sort(cmpLenRev);\n mixedPieces.sort(cmpLenRev);\n for (i = 0; i < 12; i++) {\n shortPieces[i] = regexEscape(shortPieces[i]);\n longPieces[i] = regexEscape(longPieces[i]);\n mixedPieces[i] = regexEscape(mixedPieces[i]);\n }\n\n this._monthsRegex = new RegExp('^(' + mixedPieces.join('|') + ')', 'i');\n this._monthsShortRegex = this._monthsRegex;\n this._monthsStrictRegex = new RegExp('^(' + longPieces.join('|') + ')$', 'i');\n this._monthsShortStrictRegex = new RegExp('^(' + shortPieces.join('|') + ')$', 'i');\n }\n\n function checkOverflow (m) {\n var overflow;\n var a = m._a;\n\n if (a && getParsingFlags(m).overflow === -2) {\n overflow =\n a[MONTH] < 0 || a[MONTH] > 11 ? MONTH :\n a[DATE] < 1 || a[DATE] > daysInMonth(a[YEAR], a[MONTH]) ? DATE :\n a[HOUR] < 0 || a[HOUR] > 24 || (a[HOUR] === 24 && (a[MINUTE] !== 0 || a[SECOND] !== 0 || a[MILLISECOND] !== 0)) ? HOUR :\n a[MINUTE] < 0 || a[MINUTE] > 59 ? MINUTE :\n a[SECOND] < 0 || a[SECOND] > 59 ? SECOND :\n a[MILLISECOND] < 0 || a[MILLISECOND] > 999 ? MILLISECOND :\n -1;\n\n if (getParsingFlags(m)._overflowDayOfYear && (overflow < YEAR || overflow > DATE)) {\n overflow = DATE;\n }\n if (getParsingFlags(m)._overflowWeeks && overflow === -1) {\n overflow = WEEK;\n }\n if (getParsingFlags(m)._overflowWeekday && overflow === -1) {\n overflow = WEEKDAY;\n }\n\n getParsingFlags(m).overflow = overflow;\n }\n\n return m;\n }\n\n function warn(msg) {\n if (utils_hooks__hooks.suppressDeprecationWarnings === false &&\n (typeof console !== 'undefined') && console.warn) {\n console.warn('Deprecation warning: ' + msg);\n }\n }\n\n function deprecate(msg, fn) {\n var firstTime = true;\n\n return extend(function () {\n if (firstTime) {\n warn(msg + '\\nArguments: ' + Array.prototype.slice.call(arguments).join(', ') + '\\n' + (new Error()).stack);\n firstTime = false;\n }\n return fn.apply(this, arguments);\n }, fn);\n }\n\n var deprecations = {};\n\n function deprecateSimple(name, msg) {\n if (!deprecations[name]) {\n warn(msg);\n deprecations[name] = true;\n }\n }\n\n utils_hooks__hooks.suppressDeprecationWarnings = false;\n\n // iso 8601 regex\n // 0000-00-00 0000-W00 or 0000-W00-0 + T + 00 or 00:00 or 00:00:00 or 00:00:00.000 + +00:00 or +0000 or +00)\n var extendedIsoRegex = /^\\s*((?:[+-]\\d{6}|\\d{4})-(?:\\d\\d-\\d\\d|W\\d\\d-\\d|W\\d\\d|\\d\\d\\d|\\d\\d))(?:(T| )(\\d\\d(?::\\d\\d(?::\\d\\d(?:[.,]\\d+)?)?)?)([\\+\\-]\\d\\d(?::?\\d\\d)?|\\s*Z)?)?/;\n var basicIsoRegex = /^\\s*((?:[+-]\\d{6}|\\d{4})(?:\\d\\d\\d\\d|W\\d\\d\\d|W\\d\\d|\\d\\d\\d|\\d\\d))(?:(T| )(\\d\\d(?:\\d\\d(?:\\d\\d(?:[.,]\\d+)?)?)?)([\\+\\-]\\d\\d(?::?\\d\\d)?|\\s*Z)?)?/;\n\n var tzRegex = /Z|[+-]\\d\\d(?::?\\d\\d)?/;\n\n var isoDates = [\n ['YYYYYY-MM-DD', /[+-]\\d{6}-\\d\\d-\\d\\d/],\n ['YYYY-MM-DD', /\\d{4}-\\d\\d-\\d\\d/],\n ['GGGG-[W]WW-E', /\\d{4}-W\\d\\d-\\d/],\n ['GGGG-[W]WW', /\\d{4}-W\\d\\d/, false],\n ['YYYY-DDD', /\\d{4}-\\d{3}/],\n ['YYYY-MM', /\\d{4}-\\d\\d/, false],\n ['YYYYYYMMDD', /[+-]\\d{10}/],\n ['YYYYMMDD', /\\d{8}/],\n // YYYYMM is NOT allowed by the standard\n ['GGGG[W]WWE', /\\d{4}W\\d{3}/],\n ['GGGG[W]WW', /\\d{4}W\\d{2}/, false],\n ['YYYYDDD', /\\d{7}/]\n ];\n\n // iso time formats and regexes\n var isoTimes = [\n ['HH:mm:ss.SSSS', /\\d\\d:\\d\\d:\\d\\d\\.\\d+/],\n ['HH:mm:ss,SSSS', /\\d\\d:\\d\\d:\\d\\d,\\d+/],\n ['HH:mm:ss', /\\d\\d:\\d\\d:\\d\\d/],\n ['HH:mm', /\\d\\d:\\d\\d/],\n ['HHmmss.SSSS', /\\d\\d\\d\\d\\d\\d\\.\\d+/],\n ['HHmmss,SSSS', /\\d\\d\\d\\d\\d\\d,\\d+/],\n ['HHmmss', /\\d\\d\\d\\d\\d\\d/],\n ['HHmm', /\\d\\d\\d\\d/],\n ['HH', /\\d\\d/]\n ];\n\n var aspNetJsonRegex = /^\\/?Date\\((\\-?\\d+)/i;\n\n // date from iso format\n function configFromISO(config) {\n var i, l,\n string = config._i,\n match = extendedIsoRegex.exec(string) || basicIsoRegex.exec(string),\n allowTime, dateFormat, timeFormat, tzFormat;\n\n if (match) {\n getParsingFlags(config).iso = true;\n\n for (i = 0, l = isoDates.length; i < l; i++) {\n if (isoDates[i][1].exec(match[1])) {\n dateFormat = isoDates[i][0];\n allowTime = isoDates[i][2] !== false;\n break;\n }\n }\n if (dateFormat == null) {\n config._isValid = false;\n return;\n }\n if (match[3]) {\n for (i = 0, l = isoTimes.length; i < l; i++) {\n if (isoTimes[i][1].exec(match[3])) {\n // match[2] should be 'T' or space\n timeFormat = (match[2] || ' ') + isoTimes[i][0];\n break;\n }\n }\n if (timeFormat == null) {\n config._isValid = false;\n return;\n }\n }\n if (!allowTime && timeFormat != null) {\n config._isValid = false;\n return;\n }\n if (match[4]) {\n if (tzRegex.exec(match[4])) {\n tzFormat = 'Z';\n } else {\n config._isValid = false;\n return;\n }\n }\n config._f = dateFormat + (timeFormat || '') + (tzFormat || '');\n configFromStringAndFormat(config);\n } else {\n config._isValid = false;\n }\n }\n\n // date from iso format or fallback\n function configFromString(config) {\n var matched = aspNetJsonRegex.exec(config._i);\n\n if (matched !== null) {\n config._d = new Date(+matched[1]);\n return;\n }\n\n configFromISO(config);\n if (config._isValid === false) {\n delete config._isValid;\n utils_hooks__hooks.createFromInputFallback(config);\n }\n }\n\n utils_hooks__hooks.createFromInputFallback = deprecate(\n 'moment construction falls back to js Date. This is ' +\n 'discouraged and will be removed in upcoming major ' +\n 'release. Please refer to ' +\n 'https://github.com/moment/moment/issues/1407 for more info.',\n function (config) {\n config._d = new Date(config._i + (config._useUTC ? ' UTC' : ''));\n }\n );\n\n function createDate (y, m, d, h, M, s, ms) {\n //can't just apply() to create a date:\n //http://stackoverflow.com/questions/181348/instantiating-a-javascript-object-by-calling-prototype-constructor-apply\n var date = new Date(y, m, d, h, M, s, ms);\n\n //the date constructor remaps years 0-99 to 1900-1999\n if (y < 100 && y >= 0 && isFinite(date.getFullYear())) {\n date.setFullYear(y);\n }\n return date;\n }\n\n function createUTCDate (y) {\n var date = new Date(Date.UTC.apply(null, arguments));\n\n //the Date.UTC function remaps years 0-99 to 1900-1999\n if (y < 100 && y >= 0 && isFinite(date.getUTCFullYear())) {\n date.setUTCFullYear(y);\n }\n return date;\n }\n\n // FORMATTING\n\n addFormatToken('Y', 0, 0, function () {\n var y = this.year();\n return y <= 9999 ? '' + y : '+' + y;\n });\n\n addFormatToken(0, ['YY', 2], 0, function () {\n return this.year() % 100;\n });\n\n addFormatToken(0, ['YYYY', 4], 0, 'year');\n addFormatToken(0, ['YYYYY', 5], 0, 'year');\n addFormatToken(0, ['YYYYYY', 6, true], 0, 'year');\n\n // ALIASES\n\n addUnitAlias('year', 'y');\n\n // PARSING\n\n addRegexToken('Y', matchSigned);\n addRegexToken('YY', match1to2, match2);\n addRegexToken('YYYY', match1to4, match4);\n addRegexToken('YYYYY', match1to6, match6);\n addRegexToken('YYYYYY', match1to6, match6);\n\n addParseToken(['YYYYY', 'YYYYYY'], YEAR);\n addParseToken('YYYY', function (input, array) {\n array[YEAR] = input.length === 2 ? utils_hooks__hooks.parseTwoDigitYear(input) : toInt(input);\n });\n addParseToken('YY', function (input, array) {\n array[YEAR] = utils_hooks__hooks.parseTwoDigitYear(input);\n });\n addParseToken('Y', function (input, array) {\n array[YEAR] = parseInt(input, 10);\n });\n\n // HELPERS\n\n function daysInYear(year) {\n return isLeapYear(year) ? 366 : 365;\n }\n\n function isLeapYear(year) {\n return (year % 4 === 0 && year % 100 !== 0) || year % 400 === 0;\n }\n\n // HOOKS\n\n utils_hooks__hooks.parseTwoDigitYear = function (input) {\n return toInt(input) + (toInt(input) > 68 ? 1900 : 2000);\n };\n\n // MOMENTS\n\n var getSetYear = makeGetSet('FullYear', false);\n\n function getIsLeapYear () {\n return isLeapYear(this.year());\n }\n\n // start-of-first-week - start-of-year\n function firstWeekOffset(year, dow, doy) {\n var // first-week day -- which january is always in the first week (4 for iso, 1 for other)\n fwd = 7 + dow - doy,\n // first-week day local weekday -- which local weekday is fwd\n fwdlw = (7 + createUTCDate(year, 0, fwd).getUTCDay() - dow) % 7;\n\n return -fwdlw + fwd - 1;\n }\n\n //http://en.wikipedia.org/wiki/ISO_week_date#Calculating_a_date_given_the_year.2C_week_number_and_weekday\n function dayOfYearFromWeeks(year, week, weekday, dow, doy) {\n var localWeekday = (7 + weekday - dow) % 7,\n weekOffset = firstWeekOffset(year, dow, doy),\n dayOfYear = 1 + 7 * (week - 1) + localWeekday + weekOffset,\n resYear, resDayOfYear;\n\n if (dayOfYear <= 0) {\n resYear = year - 1;\n resDayOfYear = daysInYear(resYear) + dayOfYear;\n } else if (dayOfYear > daysInYear(year)) {\n resYear = year + 1;\n resDayOfYear = dayOfYear - daysInYear(year);\n } else {\n resYear = year;\n resDayOfYear = dayOfYear;\n }\n\n return {\n year: resYear,\n dayOfYear: resDayOfYear\n };\n }\n\n function weekOfYear(mom, dow, doy) {\n var weekOffset = firstWeekOffset(mom.year(), dow, doy),\n week = Math.floor((mom.dayOfYear() - weekOffset - 1) / 7) + 1,\n resWeek, resYear;\n\n if (week < 1) {\n resYear = mom.year() - 1;\n resWeek = week + weeksInYear(resYear, dow, doy);\n } else if (week > weeksInYear(mom.year(), dow, doy)) {\n resWeek = week - weeksInYear(mom.year(), dow, doy);\n resYear = mom.year() + 1;\n } else {\n resYear = mom.year();\n resWeek = week;\n }\n\n return {\n week: resWeek,\n year: resYear\n };\n }\n\n function weeksInYear(year, dow, doy) {\n var weekOffset = firstWeekOffset(year, dow, doy),\n weekOffsetNext = firstWeekOffset(year + 1, dow, doy);\n return (daysInYear(year) - weekOffset + weekOffsetNext) / 7;\n }\n\n // Pick the first defined of two or three arguments.\n function defaults(a, b, c) {\n if (a != null) {\n return a;\n }\n if (b != null) {\n return b;\n }\n return c;\n }\n\n function currentDateArray(config) {\n // hooks is actually the exported moment object\n var nowValue = new Date(utils_hooks__hooks.now());\n if (config._useUTC) {\n return [nowValue.getUTCFullYear(), nowValue.getUTCMonth(), nowValue.getUTCDate()];\n }\n return [nowValue.getFullYear(), nowValue.getMonth(), nowValue.getDate()];\n }\n\n // convert an array to a date.\n // the array should mirror the parameters below\n // note: all values past the year are optional and will default to the lowest possible value.\n // [year, month, day , hour, minute, second, millisecond]\n function configFromArray (config) {\n var i, date, input = [], currentDate, yearToUse;\n\n if (config._d) {\n return;\n }\n\n currentDate = currentDateArray(config);\n\n //compute day of the year from weeks and weekdays\n if (config._w && config._a[DATE] == null && config._a[MONTH] == null) {\n dayOfYearFromWeekInfo(config);\n }\n\n //if the day of the year is set, figure out what it is\n if (config._dayOfYear) {\n yearToUse = defaults(config._a[YEAR], currentDate[YEAR]);\n\n if (config._dayOfYear > daysInYear(yearToUse)) {\n getParsingFlags(config)._overflowDayOfYear = true;\n }\n\n date = createUTCDate(yearToUse, 0, config._dayOfYear);\n config._a[MONTH] = date.getUTCMonth();\n config._a[DATE] = date.getUTCDate();\n }\n\n // Default to current date.\n // * if no year, month, day of month are given, default to today\n // * if day of month is given, default month and year\n // * if month is given, default only year\n // * if year is given, don't default anything\n for (i = 0; i < 3 && config._a[i] == null; ++i) {\n config._a[i] = input[i] = currentDate[i];\n }\n\n // Zero out whatever was not defaulted, including time\n for (; i < 7; i++) {\n config._a[i] = input[i] = (config._a[i] == null) ? (i === 2 ? 1 : 0) : config._a[i];\n }\n\n // Check for 24:00:00.000\n if (config._a[HOUR] === 24 &&\n config._a[MINUTE] === 0 &&\n config._a[SECOND] === 0 &&\n config._a[MILLISECOND] === 0) {\n config._nextDay = true;\n config._a[HOUR] = 0;\n }\n\n config._d = (config._useUTC ? createUTCDate : createDate).apply(null, input);\n // Apply timezone offset from input. The actual utcOffset can be changed\n // with parseZone.\n if (config._tzm != null) {\n config._d.setUTCMinutes(config._d.getUTCMinutes() - config._tzm);\n }\n\n if (config._nextDay) {\n config._a[HOUR] = 24;\n }\n }\n\n function dayOfYearFromWeekInfo(config) {\n var w, weekYear, week, weekday, dow, doy, temp, weekdayOverflow;\n\n w = config._w;\n if (w.GG != null || w.W != null || w.E != null) {\n dow = 1;\n doy = 4;\n\n // TODO: We need to take the current isoWeekYear, but that depends on\n // how we interpret now (local, utc, fixed offset). So create\n // a now version of current config (take local/utc/offset flags, and\n // create now).\n weekYear = defaults(w.GG, config._a[YEAR], weekOfYear(local__createLocal(), 1, 4).year);\n week = defaults(w.W, 1);\n weekday = defaults(w.E, 1);\n if (weekday < 1 || weekday > 7) {\n weekdayOverflow = true;\n }\n } else {\n dow = config._locale._week.dow;\n doy = config._locale._week.doy;\n\n weekYear = defaults(w.gg, config._a[YEAR], weekOfYear(local__createLocal(), dow, doy).year);\n week = defaults(w.w, 1);\n\n if (w.d != null) {\n // weekday -- low day numbers are considered next week\n weekday = w.d;\n if (weekday < 0 || weekday > 6) {\n weekdayOverflow = true;\n }\n } else if (w.e != null) {\n // local weekday -- counting starts from begining of week\n weekday = w.e + dow;\n if (w.e < 0 || w.e > 6) {\n weekdayOverflow = true;\n }\n } else {\n // default to begining of week\n weekday = dow;\n }\n }\n if (week < 1 || week > weeksInYear(weekYear, dow, doy)) {\n getParsingFlags(config)._overflowWeeks = true;\n } else if (weekdayOverflow != null) {\n getParsingFlags(config)._overflowWeekday = true;\n } else {\n temp = dayOfYearFromWeeks(weekYear, week, weekday, dow, doy);\n config._a[YEAR] = temp.year;\n config._dayOfYear = temp.dayOfYear;\n }\n }\n\n // constant that refers to the ISO standard\n utils_hooks__hooks.ISO_8601 = function () {};\n\n // date from string and format string\n function configFromStringAndFormat(config) {\n // TODO: Move this to another part of the creation flow to prevent circular deps\n if (config._f === utils_hooks__hooks.ISO_8601) {\n configFromISO(config);\n return;\n }\n\n config._a = [];\n getParsingFlags(config).empty = true;\n\n // This array is used to make a Date, either with `new Date` or `Date.UTC`\n var string = '' + config._i,\n i, parsedInput, tokens, token, skipped,\n stringLength = string.length,\n totalParsedInputLength = 0;\n\n tokens = expandFormat(config._f, config._locale).match(formattingTokens) || [];\n\n for (i = 0; i < tokens.length; i++) {\n token = tokens[i];\n parsedInput = (string.match(getParseRegexForToken(token, config)) || [])[0];\n // console.log('token', token, 'parsedInput', parsedInput,\n // 'regex', getParseRegexForToken(token, config));\n if (parsedInput) {\n skipped = string.substr(0, string.indexOf(parsedInput));\n if (skipped.length > 0) {\n getParsingFlags(config).unusedInput.push(skipped);\n }\n string = string.slice(string.indexOf(parsedInput) + parsedInput.length);\n totalParsedInputLength += parsedInput.length;\n }\n // don't parse if it's not a known token\n if (formatTokenFunctions[token]) {\n if (parsedInput) {\n getParsingFlags(config).empty = false;\n }\n else {\n getParsingFlags(config).unusedTokens.push(token);\n }\n addTimeToArrayFromToken(token, parsedInput, config);\n }\n else if (config._strict && !parsedInput) {\n getParsingFlags(config).unusedTokens.push(token);\n }\n }\n\n // add remaining unparsed input length to the string\n getParsingFlags(config).charsLeftOver = stringLength - totalParsedInputLength;\n if (string.length > 0) {\n getParsingFlags(config).unusedInput.push(string);\n }\n\n // clear _12h flag if hour is <= 12\n if (getParsingFlags(config).bigHour === true &&\n config._a[HOUR] <= 12 &&\n config._a[HOUR] > 0) {\n getParsingFlags(config).bigHour = undefined;\n }\n // handle meridiem\n config._a[HOUR] = meridiemFixWrap(config._locale, config._a[HOUR], config._meridiem);\n\n configFromArray(config);\n checkOverflow(config);\n }\n\n\n function meridiemFixWrap (locale, hour, meridiem) {\n var isPm;\n\n if (meridiem == null) {\n // nothing to do\n return hour;\n }\n if (locale.meridiemHour != null) {\n return locale.meridiemHour(hour, meridiem);\n } else if (locale.isPM != null) {\n // Fallback\n isPm = locale.isPM(meridiem);\n if (isPm && hour < 12) {\n hour += 12;\n }\n if (!isPm && hour === 12) {\n hour = 0;\n }\n return hour;\n } else {\n // this is not supposed to happen\n return hour;\n }\n }\n\n // date from string and array of format strings\n function configFromStringAndArray(config) {\n var tempConfig,\n bestMoment,\n\n scoreToBeat,\n i,\n currentScore;\n\n if (config._f.length === 0) {\n getParsingFlags(config).invalidFormat = true;\n config._d = new Date(NaN);\n return;\n }\n\n for (i = 0; i < config._f.length; i++) {\n currentScore = 0;\n tempConfig = copyConfig({}, config);\n if (config._useUTC != null) {\n tempConfig._useUTC = config._useUTC;\n }\n tempConfig._f = config._f[i];\n configFromStringAndFormat(tempConfig);\n\n if (!valid__isValid(tempConfig)) {\n continue;\n }\n\n // if there is any input that was not parsed add a penalty for that format\n currentScore += getParsingFlags(tempConfig).charsLeftOver;\n\n //or tokens\n currentScore += getParsingFlags(tempConfig).unusedTokens.length * 10;\n\n getParsingFlags(tempConfig).score = currentScore;\n\n if (scoreToBeat == null || currentScore < scoreToBeat) {\n scoreToBeat = currentScore;\n bestMoment = tempConfig;\n }\n }\n\n extend(config, bestMoment || tempConfig);\n }\n\n function configFromObject(config) {\n if (config._d) {\n return;\n }\n\n var i = normalizeObjectUnits(config._i);\n config._a = map([i.year, i.month, i.day || i.date, i.hour, i.minute, i.second, i.millisecond], function (obj) {\n return obj && parseInt(obj, 10);\n });\n\n configFromArray(config);\n }\n\n function createFromConfig (config) {\n var res = new Moment(checkOverflow(prepareConfig(config)));\n if (res._nextDay) {\n // Adding is smart enough around DST\n res.add(1, 'd');\n res._nextDay = undefined;\n }\n\n return res;\n }\n\n function prepareConfig (config) {\n var input = config._i,\n format = config._f;\n\n config._locale = config._locale || locale_locales__getLocale(config._l);\n\n if (input === null || (format === undefined && input === '')) {\n return valid__createInvalid({nullInput: true});\n }\n\n if (typeof input === 'string') {\n config._i = input = config._locale.preparse(input);\n }\n\n if (isMoment(input)) {\n return new Moment(checkOverflow(input));\n } else if (isArray(format)) {\n configFromStringAndArray(config);\n } else if (format) {\n configFromStringAndFormat(config);\n } else if (isDate(input)) {\n config._d = input;\n } else {\n configFromInput(config);\n }\n\n if (!valid__isValid(config)) {\n config._d = null;\n }\n\n return config;\n }\n\n function configFromInput(config) {\n var input = config._i;\n if (input === undefined) {\n config._d = new Date(utils_hooks__hooks.now());\n } else if (isDate(input)) {\n config._d = new Date(+input);\n } else if (typeof input === 'string') {\n configFromString(config);\n } else if (isArray(input)) {\n config._a = map(input.slice(0), function (obj) {\n return parseInt(obj, 10);\n });\n configFromArray(config);\n } else if (typeof(input) === 'object') {\n configFromObject(config);\n } else if (typeof(input) === 'number') {\n // from milliseconds\n config._d = new Date(input);\n } else {\n utils_hooks__hooks.createFromInputFallback(config);\n }\n }\n\n function createLocalOrUTC (input, format, locale, strict, isUTC) {\n var c = {};\n\n if (typeof(locale) === 'boolean') {\n strict = locale;\n locale = undefined;\n }\n // object construction must be done this way.\n // https://github.com/moment/moment/issues/1423\n c._isAMomentObject = true;\n c._useUTC = c._isUTC = isUTC;\n c._l = locale;\n c._i = input;\n c._f = format;\n c._strict = strict;\n\n return createFromConfig(c);\n }\n\n function local__createLocal (input, format, locale, strict) {\n return createLocalOrUTC(input, format, locale, strict, false);\n }\n\n var prototypeMin = deprecate(\n 'moment().min is deprecated, use moment.min instead. https://github.com/moment/moment/issues/1548',\n function () {\n var other = local__createLocal.apply(null, arguments);\n if (this.isValid() && other.isValid()) {\n return other < this ? this : other;\n } else {\n return valid__createInvalid();\n }\n }\n );\n\n var prototypeMax = deprecate(\n 'moment().max is deprecated, use moment.max instead. https://github.com/moment/moment/issues/1548',\n function () {\n var other = local__createLocal.apply(null, arguments);\n if (this.isValid() && other.isValid()) {\n return other > this ? this : other;\n } else {\n return valid__createInvalid();\n }\n }\n );\n\n // Pick a moment m from moments so that m[fn](other) is true for all\n // other. This relies on the function fn to be transitive.\n //\n // moments should either be an array of moment objects or an array, whose\n // first element is an array of moment objects.\n function pickBy(fn, moments) {\n var res, i;\n if (moments.length === 1 && isArray(moments[0])) {\n moments = moments[0];\n }\n if (!moments.length) {\n return local__createLocal();\n }\n res = moments[0];\n for (i = 1; i < moments.length; ++i) {\n if (!moments[i].isValid() || moments[i][fn](res)) {\n res = moments[i];\n }\n }\n return res;\n }\n\n // TODO: Use [].sort instead?\n function min () {\n var args = [].slice.call(arguments, 0);\n\n return pickBy('isBefore', args);\n }\n\n function max () {\n var args = [].slice.call(arguments, 0);\n\n return pickBy('isAfter', args);\n }\n\n var now = function () {\n return Date.now ? Date.now() : +(new Date());\n };\n\n function Duration (duration) {\n var normalizedInput = normalizeObjectUnits(duration),\n years = normalizedInput.year || 0,\n quarters = normalizedInput.quarter || 0,\n months = normalizedInput.month || 0,\n weeks = normalizedInput.week || 0,\n days = normalizedInput.day || 0,\n hours = normalizedInput.hour || 0,\n minutes = normalizedInput.minute || 0,\n seconds = normalizedInput.second || 0,\n milliseconds = normalizedInput.millisecond || 0;\n\n // representation for dateAddRemove\n this._milliseconds = +milliseconds +\n seconds * 1e3 + // 1000\n minutes * 6e4 + // 1000 * 60\n hours * 36e5; // 1000 * 60 * 60\n // Because of dateAddRemove treats 24 hours as different from a\n // day when working around DST, we need to store them separately\n this._days = +days +\n weeks * 7;\n // It is impossible translate months into days without knowing\n // which months you are are talking about, so we have to store\n // it separately.\n this._months = +months +\n quarters * 3 +\n years * 12;\n\n this._data = {};\n\n this._locale = locale_locales__getLocale();\n\n this._bubble();\n }\n\n function isDuration (obj) {\n return obj instanceof Duration;\n }\n\n // FORMATTING\n\n function offset (token, separator) {\n addFormatToken(token, 0, 0, function () {\n var offset = this.utcOffset();\n var sign = '+';\n if (offset < 0) {\n offset = -offset;\n sign = '-';\n }\n return sign + zeroFill(~~(offset / 60), 2) + separator + zeroFill(~~(offset) % 60, 2);\n });\n }\n\n offset('Z', ':');\n offset('ZZ', '');\n\n // PARSING\n\n addRegexToken('Z', matchShortOffset);\n addRegexToken('ZZ', matchShortOffset);\n addParseToken(['Z', 'ZZ'], function (input, array, config) {\n config._useUTC = true;\n config._tzm = offsetFromString(matchShortOffset, input);\n });\n\n // HELPERS\n\n // timezone chunker\n // '+10:00' > ['10', '00']\n // '-1530' > ['-15', '30']\n var chunkOffset = /([\\+\\-]|\\d\\d)/gi;\n\n function offsetFromString(matcher, string) {\n var matches = ((string || '').match(matcher) || []);\n var chunk = matches[matches.length - 1] || [];\n var parts = (chunk + '').match(chunkOffset) || ['-', 0, 0];\n var minutes = +(parts[1] * 60) + toInt(parts[2]);\n\n return parts[0] === '+' ? minutes : -minutes;\n }\n\n // Return a moment from input, that is local/utc/zone equivalent to model.\n function cloneWithOffset(input, model) {\n var res, diff;\n if (model._isUTC) {\n res = model.clone();\n diff = (isMoment(input) || isDate(input) ? +input : +local__createLocal(input)) - (+res);\n // Use low-level api, because this fn is low-level api.\n res._d.setTime(+res._d + diff);\n utils_hooks__hooks.updateOffset(res, false);\n return res;\n } else {\n return local__createLocal(input).local();\n }\n }\n\n function getDateOffset (m) {\n // On Firefox.24 Date#getTimezoneOffset returns a floating point.\n // https://github.com/moment/moment/pull/1871\n return -Math.round(m._d.getTimezoneOffset() / 15) * 15;\n }\n\n // HOOKS\n\n // This function will be called whenever a moment is mutated.\n // It is intended to keep the offset in sync with the timezone.\n utils_hooks__hooks.updateOffset = function () {};\n\n // MOMENTS\n\n // keepLocalTime = true means only change the timezone, without\n // affecting the local hour. So 5:31:26 +0300 --[utcOffset(2, true)]-->\n // 5:31:26 +0200 It is possible that 5:31:26 doesn't exist with offset\n // +0200, so we adjust the time as needed, to be valid.\n //\n // Keeping the time actually adds/subtracts (one hour)\n // from the actual represented time. That is why we call updateOffset\n // a second time. In case it wants us to change the offset again\n // _changeInProgress == true case, then we have to adjust, because\n // there is no such time in the given timezone.\n function getSetOffset (input, keepLocalTime) {\n var offset = this._offset || 0,\n localAdjust;\n if (!this.isValid()) {\n return input != null ? this : NaN;\n }\n if (input != null) {\n if (typeof input === 'string') {\n input = offsetFromString(matchShortOffset, input);\n } else if (Math.abs(input) < 16) {\n input = input * 60;\n }\n if (!this._isUTC && keepLocalTime) {\n localAdjust = getDateOffset(this);\n }\n this._offset = input;\n this._isUTC = true;\n if (localAdjust != null) {\n this.add(localAdjust, 'm');\n }\n if (offset !== input) {\n if (!keepLocalTime || this._changeInProgress) {\n add_subtract__addSubtract(this, create__createDuration(input - offset, 'm'), 1, false);\n } else if (!this._changeInProgress) {\n this._changeInProgress = true;\n utils_hooks__hooks.updateOffset(this, true);\n this._changeInProgress = null;\n }\n }\n return this;\n } else {\n return this._isUTC ? offset : getDateOffset(this);\n }\n }\n\n function getSetZone (input, keepLocalTime) {\n if (input != null) {\n if (typeof input !== 'string') {\n input = -input;\n }\n\n this.utcOffset(input, keepLocalTime);\n\n return this;\n } else {\n return -this.utcOffset();\n }\n }\n\n function setOffsetToUTC (keepLocalTime) {\n return this.utcOffset(0, keepLocalTime);\n }\n\n function setOffsetToLocal (keepLocalTime) {\n if (this._isUTC) {\n this.utcOffset(0, keepLocalTime);\n this._isUTC = false;\n\n if (keepLocalTime) {\n this.subtract(getDateOffset(this), 'm');\n }\n }\n return this;\n }\n\n function setOffsetToParsedOffset () {\n if (this._tzm) {\n this.utcOffset(this._tzm);\n } else if (typeof this._i === 'string') {\n this.utcOffset(offsetFromString(matchOffset, this._i));\n }\n return this;\n }\n\n function hasAlignedHourOffset (input) {\n if (!this.isValid()) {\n return false;\n }\n input = input ? local__createLocal(input).utcOffset() : 0;\n\n return (this.utcOffset() - input) % 60 === 0;\n }\n\n function isDaylightSavingTime () {\n return (\n this.utcOffset() > this.clone().month(0).utcOffset() ||\n this.utcOffset() > this.clone().month(5).utcOffset()\n );\n }\n\n function isDaylightSavingTimeShifted () {\n if (!isUndefined(this._isDSTShifted)) {\n return this._isDSTShifted;\n }\n\n var c = {};\n\n copyConfig(c, this);\n c = prepareConfig(c);\n\n if (c._a) {\n var other = c._isUTC ? create_utc__createUTC(c._a) : local__createLocal(c._a);\n this._isDSTShifted = this.isValid() &&\n compareArrays(c._a, other.toArray()) > 0;\n } else {\n this._isDSTShifted = false;\n }\n\n return this._isDSTShifted;\n }\n\n function isLocal () {\n return this.isValid() ? !this._isUTC : false;\n }\n\n function isUtcOffset () {\n return this.isValid() ? this._isUTC : false;\n }\n\n function isUtc () {\n return this.isValid() ? this._isUTC && this._offset === 0 : false;\n }\n\n // ASP.NET json date format regex\n var aspNetRegex = /^(\\-)?(?:(\\d*)[. ])?(\\d+)\\:(\\d+)(?:\\:(\\d+)\\.?(\\d{3})?\\d*)?$/;\n\n // from http://docs.closure-library.googlecode.com/git/closure_goog_date_date.js.source.html\n // somewhat more in line with 4.4.3.2 2004 spec, but allows decimal anywhere\n var isoRegex = /^(-)?P(?:(?:([0-9,.]*)Y)?(?:([0-9,.]*)M)?(?:([0-9,.]*)D)?(?:T(?:([0-9,.]*)H)?(?:([0-9,.]*)M)?(?:([0-9,.]*)S)?)?|([0-9,.]*)W)$/;\n\n function create__createDuration (input, key) {\n var duration = input,\n // matching against regexp is expensive, do it on demand\n match = null,\n sign,\n ret,\n diffRes;\n\n if (isDuration(input)) {\n duration = {\n ms : input._milliseconds,\n d : input._days,\n M : input._months\n };\n } else if (typeof input === 'number') {\n duration = {};\n if (key) {\n duration[key] = input;\n } else {\n duration.milliseconds = input;\n }\n } else if (!!(match = aspNetRegex.exec(input))) {\n sign = (match[1] === '-') ? -1 : 1;\n duration = {\n y : 0,\n d : toInt(match[DATE]) * sign,\n h : toInt(match[HOUR]) * sign,\n m : toInt(match[MINUTE]) * sign,\n s : toInt(match[SECOND]) * sign,\n ms : toInt(match[MILLISECOND]) * sign\n };\n } else if (!!(match = isoRegex.exec(input))) {\n sign = (match[1] === '-') ? -1 : 1;\n duration = {\n y : parseIso(match[2], sign),\n M : parseIso(match[3], sign),\n d : parseIso(match[4], sign),\n h : parseIso(match[5], sign),\n m : parseIso(match[6], sign),\n s : parseIso(match[7], sign),\n w : parseIso(match[8], sign)\n };\n } else if (duration == null) {// checks for null or undefined\n duration = {};\n } else if (typeof duration === 'object' && ('from' in duration || 'to' in duration)) {\n diffRes = momentsDifference(local__createLocal(duration.from), local__createLocal(duration.to));\n\n duration = {};\n duration.ms = diffRes.milliseconds;\n duration.M = diffRes.months;\n }\n\n ret = new Duration(duration);\n\n if (isDuration(input) && hasOwnProp(input, '_locale')) {\n ret._locale = input._locale;\n }\n\n return ret;\n }\n\n create__createDuration.fn = Duration.prototype;\n\n function parseIso (inp, sign) {\n // We'd normally use ~~inp for this, but unfortunately it also\n // converts floats to ints.\n // inp may be undefined, so careful calling replace on it.\n var res = inp && parseFloat(inp.replace(',', '.'));\n // apply sign while we're at it\n return (isNaN(res) ? 0 : res) * sign;\n }\n\n function positiveMomentsDifference(base, other) {\n var res = {milliseconds: 0, months: 0};\n\n res.months = other.month() - base.month() +\n (other.year() - base.year()) * 12;\n if (base.clone().add(res.months, 'M').isAfter(other)) {\n --res.months;\n }\n\n res.milliseconds = +other - +(base.clone().add(res.months, 'M'));\n\n return res;\n }\n\n function momentsDifference(base, other) {\n var res;\n if (!(base.isValid() && other.isValid())) {\n return {milliseconds: 0, months: 0};\n }\n\n other = cloneWithOffset(other, base);\n if (base.isBefore(other)) {\n res = positiveMomentsDifference(base, other);\n } else {\n res = positiveMomentsDifference(other, base);\n res.milliseconds = -res.milliseconds;\n res.months = -res.months;\n }\n\n return res;\n }\n\n // TODO: remove 'name' arg after deprecation is removed\n function createAdder(direction, name) {\n return function (val, period) {\n var dur, tmp;\n //invert the arguments, but complain about it\n if (period !== null && !isNaN(+period)) {\n deprecateSimple(name, 'moment().' + name + '(period, number) is deprecated. Please use moment().' + name + '(number, period).');\n tmp = val; val = period; period = tmp;\n }\n\n val = typeof val === 'string' ? +val : val;\n dur = create__createDuration(val, period);\n add_subtract__addSubtract(this, dur, direction);\n return this;\n };\n }\n\n function add_subtract__addSubtract (mom, duration, isAdding, updateOffset) {\n var milliseconds = duration._milliseconds,\n days = duration._days,\n months = duration._months;\n\n if (!mom.isValid()) {\n // No op\n return;\n }\n\n updateOffset = updateOffset == null ? true : updateOffset;\n\n if (milliseconds) {\n mom._d.setTime(+mom._d + milliseconds * isAdding);\n }\n if (days) {\n get_set__set(mom, 'Date', get_set__get(mom, 'Date') + days * isAdding);\n }\n if (months) {\n setMonth(mom, get_set__get(mom, 'Month') + months * isAdding);\n }\n if (updateOffset) {\n utils_hooks__hooks.updateOffset(mom, days || months);\n }\n }\n\n var add_subtract__add = createAdder(1, 'add');\n var add_subtract__subtract = createAdder(-1, 'subtract');\n\n function moment_calendar__calendar (time, formats) {\n // We want to compare the start of today, vs this.\n // Getting start-of-today depends on whether we're local/utc/offset or not.\n var now = time || local__createLocal(),\n sod = cloneWithOffset(now, this).startOf('day'),\n diff = this.diff(sod, 'days', true),\n format = diff < -6 ? 'sameElse' :\n diff < -1 ? 'lastWeek' :\n diff < 0 ? 'lastDay' :\n diff < 1 ? 'sameDay' :\n diff < 2 ? 'nextDay' :\n diff < 7 ? 'nextWeek' : 'sameElse';\n\n var output = formats && (isFunction(formats[format]) ? formats[format]() : formats[format]);\n\n return this.format(output || this.localeData().calendar(format, this, local__createLocal(now)));\n }\n\n function clone () {\n return new Moment(this);\n }\n\n function isAfter (input, units) {\n var localInput = isMoment(input) ? input : local__createLocal(input);\n if (!(this.isValid() && localInput.isValid())) {\n return false;\n }\n units = normalizeUnits(!isUndefined(units) ? units : 'millisecond');\n if (units === 'millisecond') {\n return +this > +localInput;\n } else {\n return +localInput < +this.clone().startOf(units);\n }\n }\n\n function isBefore (input, units) {\n var localInput = isMoment(input) ? input : local__createLocal(input);\n if (!(this.isValid() && localInput.isValid())) {\n return false;\n }\n units = normalizeUnits(!isUndefined(units) ? units : 'millisecond');\n if (units === 'millisecond') {\n return +this < +localInput;\n } else {\n return +this.clone().endOf(units) < +localInput;\n }\n }\n\n function isBetween (from, to, units) {\n return this.isAfter(from, units) && this.isBefore(to, units);\n }\n\n function isSame (input, units) {\n var localInput = isMoment(input) ? input : local__createLocal(input),\n inputMs;\n if (!(this.isValid() && localInput.isValid())) {\n return false;\n }\n units = normalizeUnits(units || 'millisecond');\n if (units === 'millisecond') {\n return +this === +localInput;\n } else {\n inputMs = +localInput;\n return +(this.clone().startOf(units)) <= inputMs && inputMs <= +(this.clone().endOf(units));\n }\n }\n\n function isSameOrAfter (input, units) {\n return this.isSame(input, units) || this.isAfter(input,units);\n }\n\n function isSameOrBefore (input, units) {\n return this.isSame(input, units) || this.isBefore(input,units);\n }\n\n function diff (input, units, asFloat) {\n var that,\n zoneDelta,\n delta, output;\n\n if (!this.isValid()) {\n return NaN;\n }\n\n that = cloneWithOffset(input, this);\n\n if (!that.isValid()) {\n return NaN;\n }\n\n zoneDelta = (that.utcOffset() - this.utcOffset()) * 6e4;\n\n units = normalizeUnits(units);\n\n if (units === 'year' || units === 'month' || units === 'quarter') {\n output = monthDiff(this, that);\n if (units === 'quarter') {\n output = output / 3;\n } else if (units === 'year') {\n output = output / 12;\n }\n } else {\n delta = this - that;\n output = units === 'second' ? delta / 1e3 : // 1000\n units === 'minute' ? delta / 6e4 : // 1000 * 60\n units === 'hour' ? delta / 36e5 : // 1000 * 60 * 60\n units === 'day' ? (delta - zoneDelta) / 864e5 : // 1000 * 60 * 60 * 24, negate dst\n units === 'week' ? (delta - zoneDelta) / 6048e5 : // 1000 * 60 * 60 * 24 * 7, negate dst\n delta;\n }\n return asFloat ? output : absFloor(output);\n }\n\n function monthDiff (a, b) {\n // difference in months\n var wholeMonthDiff = ((b.year() - a.year()) * 12) + (b.month() - a.month()),\n // b is in (anchor - 1 month, anchor + 1 month)\n anchor = a.clone().add(wholeMonthDiff, 'months'),\n anchor2, adjust;\n\n if (b - anchor < 0) {\n anchor2 = a.clone().add(wholeMonthDiff - 1, 'months');\n // linear across the month\n adjust = (b - anchor) / (anchor - anchor2);\n } else {\n anchor2 = a.clone().add(wholeMonthDiff + 1, 'months');\n // linear across the month\n adjust = (b - anchor) / (anchor2 - anchor);\n }\n\n return -(wholeMonthDiff + adjust);\n }\n\n utils_hooks__hooks.defaultFormat = 'YYYY-MM-DDTHH:mm:ssZ';\n\n function toString () {\n return this.clone().locale('en').format('ddd MMM DD YYYY HH:mm:ss [GMT]ZZ');\n }\n\n function moment_format__toISOString () {\n var m = this.clone().utc();\n if (0 < m.year() && m.year() <= 9999) {\n if (isFunction(Date.prototype.toISOString)) {\n // native implementation is ~50x faster, use it when we can\n return this.toDate().toISOString();\n } else {\n return formatMoment(m, 'YYYY-MM-DD[T]HH:mm:ss.SSS[Z]');\n }\n } else {\n return formatMoment(m, 'YYYYYY-MM-DD[T]HH:mm:ss.SSS[Z]');\n }\n }\n\n function format (inputString) {\n var output = formatMoment(this, inputString || utils_hooks__hooks.defaultFormat);\n return this.localeData().postformat(output);\n }\n\n function from (time, withoutSuffix) {\n if (this.isValid() &&\n ((isMoment(time) && time.isValid()) ||\n local__createLocal(time).isValid())) {\n return create__createDuration({to: this, from: time}).locale(this.locale()).humanize(!withoutSuffix);\n } else {\n return this.localeData().invalidDate();\n }\n }\n\n function fromNow (withoutSuffix) {\n return this.from(local__createLocal(), withoutSuffix);\n }\n\n function to (time, withoutSuffix) {\n if (this.isValid() &&\n ((isMoment(time) && time.isValid()) ||\n local__createLocal(time).isValid())) {\n return create__createDuration({from: this, to: time}).locale(this.locale()).humanize(!withoutSuffix);\n } else {\n return this.localeData().invalidDate();\n }\n }\n\n function toNow (withoutSuffix) {\n return this.to(local__createLocal(), withoutSuffix);\n }\n\n // If passed a locale key, it will set the locale for this\n // instance. Otherwise, it will return the locale configuration\n // variables for this instance.\n function locale (key) {\n var newLocaleData;\n\n if (key === undefined) {\n return this._locale._abbr;\n } else {\n newLocaleData = locale_locales__getLocale(key);\n if (newLocaleData != null) {\n this._locale = newLocaleData;\n }\n return this;\n }\n }\n\n var lang = deprecate(\n 'moment().lang() is deprecated. Instead, use moment().localeData() to get the language configuration. Use moment().locale() to change languages.',\n function (key) {\n if (key === undefined) {\n return this.localeData();\n } else {\n return this.locale(key);\n }\n }\n );\n\n function localeData () {\n return this._locale;\n }\n\n function startOf (units) {\n units = normalizeUnits(units);\n // the following switch intentionally omits break keywords\n // to utilize falling through the cases.\n switch (units) {\n case 'year':\n this.month(0);\n /* falls through */\n case 'quarter':\n case 'month':\n this.date(1);\n /* falls through */\n case 'week':\n case 'isoWeek':\n case 'day':\n this.hours(0);\n /* falls through */\n case 'hour':\n this.minutes(0);\n /* falls through */\n case 'minute':\n this.seconds(0);\n /* falls through */\n case 'second':\n this.milliseconds(0);\n }\n\n // weeks are a special case\n if (units === 'week') {\n this.weekday(0);\n }\n if (units === 'isoWeek') {\n this.isoWeekday(1);\n }\n\n // quarters are also special\n if (units === 'quarter') {\n this.month(Math.floor(this.month() / 3) * 3);\n }\n\n return this;\n }\n\n function endOf (units) {\n units = normalizeUnits(units);\n if (units === undefined || units === 'millisecond') {\n return this;\n }\n return this.startOf(units).add(1, (units === 'isoWeek' ? 'week' : units)).subtract(1, 'ms');\n }\n\n function to_type__valueOf () {\n return +this._d - ((this._offset || 0) * 60000);\n }\n\n function unix () {\n return Math.floor(+this / 1000);\n }\n\n function toDate () {\n return this._offset ? new Date(+this) : this._d;\n }\n\n function toArray () {\n var m = this;\n return [m.year(), m.month(), m.date(), m.hour(), m.minute(), m.second(), m.millisecond()];\n }\n\n function toObject () {\n var m = this;\n return {\n years: m.year(),\n months: m.month(),\n date: m.date(),\n hours: m.hours(),\n minutes: m.minutes(),\n seconds: m.seconds(),\n milliseconds: m.milliseconds()\n };\n }\n\n function toJSON () {\n // JSON.stringify(new Date(NaN)) === 'null'\n return this.isValid() ? this.toISOString() : 'null';\n }\n\n function moment_valid__isValid () {\n return valid__isValid(this);\n }\n\n function parsingFlags () {\n return extend({}, getParsingFlags(this));\n }\n\n function invalidAt () {\n return getParsingFlags(this).overflow;\n }\n\n function creationData() {\n return {\n input: this._i,\n format: this._f,\n locale: this._locale,\n isUTC: this._isUTC,\n strict: this._strict\n };\n }\n\n // FORMATTING\n\n addFormatToken(0, ['gg', 2], 0, function () {\n return this.weekYear() % 100;\n });\n\n addFormatToken(0, ['GG', 2], 0, function () {\n return this.isoWeekYear() % 100;\n });\n\n function addWeekYearFormatToken (token, getter) {\n addFormatToken(0, [token, token.length], 0, getter);\n }\n\n addWeekYearFormatToken('gggg', 'weekYear');\n addWeekYearFormatToken('ggggg', 'weekYear');\n addWeekYearFormatToken('GGGG', 'isoWeekYear');\n addWeekYearFormatToken('GGGGG', 'isoWeekYear');\n\n // ALIASES\n\n addUnitAlias('weekYear', 'gg');\n addUnitAlias('isoWeekYear', 'GG');\n\n // PARSING\n\n addRegexToken('G', matchSigned);\n addRegexToken('g', matchSigned);\n addRegexToken('GG', match1to2, match2);\n addRegexToken('gg', match1to2, match2);\n addRegexToken('GGGG', match1to4, match4);\n addRegexToken('gggg', match1to4, match4);\n addRegexToken('GGGGG', match1to6, match6);\n addRegexToken('ggggg', match1to6, match6);\n\n addWeekParseToken(['gggg', 'ggggg', 'GGGG', 'GGGGG'], function (input, week, config, token) {\n week[token.substr(0, 2)] = toInt(input);\n });\n\n addWeekParseToken(['gg', 'GG'], function (input, week, config, token) {\n week[token] = utils_hooks__hooks.parseTwoDigitYear(input);\n });\n\n // MOMENTS\n\n function getSetWeekYear (input) {\n return getSetWeekYearHelper.call(this,\n input,\n this.week(),\n this.weekday(),\n this.localeData()._week.dow,\n this.localeData()._week.doy);\n }\n\n function getSetISOWeekYear (input) {\n return getSetWeekYearHelper.call(this,\n input, this.isoWeek(), this.isoWeekday(), 1, 4);\n }\n\n function getISOWeeksInYear () {\n return weeksInYear(this.year(), 1, 4);\n }\n\n function getWeeksInYear () {\n var weekInfo = this.localeData()._week;\n return weeksInYear(this.year(), weekInfo.dow, weekInfo.doy);\n }\n\n function getSetWeekYearHelper(input, week, weekday, dow, doy) {\n var weeksTarget;\n if (input == null) {\n return weekOfYear(this, dow, doy).year;\n } else {\n weeksTarget = weeksInYear(input, dow, doy);\n if (week > weeksTarget) {\n week = weeksTarget;\n }\n return setWeekAll.call(this, input, week, weekday, dow, doy);\n }\n }\n\n function setWeekAll(weekYear, week, weekday, dow, doy) {\n var dayOfYearData = dayOfYearFromWeeks(weekYear, week, weekday, dow, doy),\n date = createUTCDate(dayOfYearData.year, 0, dayOfYearData.dayOfYear);\n\n // console.log(\"got\", weekYear, week, weekday, \"set\", date.toISOString());\n this.year(date.getUTCFullYear());\n this.month(date.getUTCMonth());\n this.date(date.getUTCDate());\n return this;\n }\n\n // FORMATTING\n\n addFormatToken('Q', 0, 'Qo', 'quarter');\n\n // ALIASES\n\n addUnitAlias('quarter', 'Q');\n\n // PARSING\n\n addRegexToken('Q', match1);\n addParseToken('Q', function (input, array) {\n array[MONTH] = (toInt(input) - 1) * 3;\n });\n\n // MOMENTS\n\n function getSetQuarter (input) {\n return input == null ? Math.ceil((this.month() + 1) / 3) : this.month((input - 1) * 3 + this.month() % 3);\n }\n\n // FORMATTING\n\n addFormatToken('w', ['ww', 2], 'wo', 'week');\n addFormatToken('W', ['WW', 2], 'Wo', 'isoWeek');\n\n // ALIASES\n\n addUnitAlias('week', 'w');\n addUnitAlias('isoWeek', 'W');\n\n // PARSING\n\n addRegexToken('w', match1to2);\n addRegexToken('ww', match1to2, match2);\n addRegexToken('W', match1to2);\n addRegexToken('WW', match1to2, match2);\n\n addWeekParseToken(['w', 'ww', 'W', 'WW'], function (input, week, config, token) {\n week[token.substr(0, 1)] = toInt(input);\n });\n\n // HELPERS\n\n // LOCALES\n\n function localeWeek (mom) {\n return weekOfYear(mom, this._week.dow, this._week.doy).week;\n }\n\n var defaultLocaleWeek = {\n dow : 0, // Sunday is the first day of the week.\n doy : 6 // The week that contains Jan 1st is the first week of the year.\n };\n\n function localeFirstDayOfWeek () {\n return this._week.dow;\n }\n\n function localeFirstDayOfYear () {\n return this._week.doy;\n }\n\n // MOMENTS\n\n function getSetWeek (input) {\n var week = this.localeData().week(this);\n return input == null ? week : this.add((input - week) * 7, 'd');\n }\n\n function getSetISOWeek (input) {\n var week = weekOfYear(this, 1, 4).week;\n return input == null ? week : this.add((input - week) * 7, 'd');\n }\n\n // FORMATTING\n\n addFormatToken('D', ['DD', 2], 'Do', 'date');\n\n // ALIASES\n\n addUnitAlias('date', 'D');\n\n // PARSING\n\n addRegexToken('D', match1to2);\n addRegexToken('DD', match1to2, match2);\n addRegexToken('Do', function (isStrict, locale) {\n return isStrict ? locale._ordinalParse : locale._ordinalParseLenient;\n });\n\n addParseToken(['D', 'DD'], DATE);\n addParseToken('Do', function (input, array) {\n array[DATE] = toInt(input.match(match1to2)[0], 10);\n });\n\n // MOMENTS\n\n var getSetDayOfMonth = makeGetSet('Date', true);\n\n // FORMATTING\n\n addFormatToken('d', 0, 'do', 'day');\n\n addFormatToken('dd', 0, 0, function (format) {\n return this.localeData().weekdaysMin(this, format);\n });\n\n addFormatToken('ddd', 0, 0, function (format) {\n return this.localeData().weekdaysShort(this, format);\n });\n\n addFormatToken('dddd', 0, 0, function (format) {\n return this.localeData().weekdays(this, format);\n });\n\n addFormatToken('e', 0, 0, 'weekday');\n addFormatToken('E', 0, 0, 'isoWeekday');\n\n // ALIASES\n\n addUnitAlias('day', 'd');\n addUnitAlias('weekday', 'e');\n addUnitAlias('isoWeekday', 'E');\n\n // PARSING\n\n addRegexToken('d', match1to2);\n addRegexToken('e', match1to2);\n addRegexToken('E', match1to2);\n addRegexToken('dd', matchWord);\n addRegexToken('ddd', matchWord);\n addRegexToken('dddd', matchWord);\n\n addWeekParseToken(['dd', 'ddd', 'dddd'], function (input, week, config, token) {\n var weekday = config._locale.weekdaysParse(input, token, config._strict);\n // if we didn't get a weekday name, mark the date as invalid\n if (weekday != null) {\n week.d = weekday;\n } else {\n getParsingFlags(config).invalidWeekday = input;\n }\n });\n\n addWeekParseToken(['d', 'e', 'E'], function (input, week, config, token) {\n week[token] = toInt(input);\n });\n\n // HELPERS\n\n function parseWeekday(input, locale) {\n if (typeof input !== 'string') {\n return input;\n }\n\n if (!isNaN(input)) {\n return parseInt(input, 10);\n }\n\n input = locale.weekdaysParse(input);\n if (typeof input === 'number') {\n return input;\n }\n\n return null;\n }\n\n // LOCALES\n\n var defaultLocaleWeekdays = 'Sunday_Monday_Tuesday_Wednesday_Thursday_Friday_Saturday'.split('_');\n function localeWeekdays (m, format) {\n return isArray(this._weekdays) ? this._weekdays[m.day()] :\n this._weekdays[this._weekdays.isFormat.test(format) ? 'format' : 'standalone'][m.day()];\n }\n\n var defaultLocaleWeekdaysShort = 'Sun_Mon_Tue_Wed_Thu_Fri_Sat'.split('_');\n function localeWeekdaysShort (m) {\n return this._weekdaysShort[m.day()];\n }\n\n var defaultLocaleWeekdaysMin = 'Su_Mo_Tu_We_Th_Fr_Sa'.split('_');\n function localeWeekdaysMin (m) {\n return this._weekdaysMin[m.day()];\n }\n\n function localeWeekdaysParse (weekdayName, format, strict) {\n var i, mom, regex;\n\n if (!this._weekdaysParse) {\n this._weekdaysParse = [];\n this._minWeekdaysParse = [];\n this._shortWeekdaysParse = [];\n this._fullWeekdaysParse = [];\n }\n\n for (i = 0; i < 7; i++) {\n // make the regex if we don't have it already\n\n mom = local__createLocal([2000, 1]).day(i);\n if (strict && !this._fullWeekdaysParse[i]) {\n this._fullWeekdaysParse[i] = new RegExp('^' + this.weekdays(mom, '').replace('.', '\\.?') + '$', 'i');\n this._shortWeekdaysParse[i] = new RegExp('^' + this.weekdaysShort(mom, '').replace('.', '\\.?') + '$', 'i');\n this._minWeekdaysParse[i] = new RegExp('^' + this.weekdaysMin(mom, '').replace('.', '\\.?') + '$', 'i');\n }\n if (!this._weekdaysParse[i]) {\n regex = '^' + this.weekdays(mom, '') + '|^' + this.weekdaysShort(mom, '') + '|^' + this.weekdaysMin(mom, '');\n this._weekdaysParse[i] = new RegExp(regex.replace('.', ''), 'i');\n }\n // test the regex\n if (strict && format === 'dddd' && this._fullWeekdaysParse[i].test(weekdayName)) {\n return i;\n } else if (strict && format === 'ddd' && this._shortWeekdaysParse[i].test(weekdayName)) {\n return i;\n } else if (strict && format === 'dd' && this._minWeekdaysParse[i].test(weekdayName)) {\n return i;\n } else if (!strict && this._weekdaysParse[i].test(weekdayName)) {\n return i;\n }\n }\n }\n\n // MOMENTS\n\n function getSetDayOfWeek (input) {\n if (!this.isValid()) {\n return input != null ? this : NaN;\n }\n var day = this._isUTC ? this._d.getUTCDay() : this._d.getDay();\n if (input != null) {\n input = parseWeekday(input, this.localeData());\n return this.add(input - day, 'd');\n } else {\n return day;\n }\n }\n\n function getSetLocaleDayOfWeek (input) {\n if (!this.isValid()) {\n return input != null ? this : NaN;\n }\n var weekday = (this.day() + 7 - this.localeData()._week.dow) % 7;\n return input == null ? weekday : this.add(input - weekday, 'd');\n }\n\n function getSetISODayOfWeek (input) {\n if (!this.isValid()) {\n return input != null ? this : NaN;\n }\n // behaves the same as moment#day except\n // as a getter, returns 7 instead of 0 (1-7 range instead of 0-6)\n // as a setter, sunday should belong to the previous week.\n return input == null ? this.day() || 7 : this.day(this.day() % 7 ? input : input - 7);\n }\n\n // FORMATTING\n\n addFormatToken('DDD', ['DDDD', 3], 'DDDo', 'dayOfYear');\n\n // ALIASES\n\n addUnitAlias('dayOfYear', 'DDD');\n\n // PARSING\n\n addRegexToken('DDD', match1to3);\n addRegexToken('DDDD', match3);\n addParseToken(['DDD', 'DDDD'], function (input, array, config) {\n config._dayOfYear = toInt(input);\n });\n\n // HELPERS\n\n // MOMENTS\n\n function getSetDayOfYear (input) {\n var dayOfYear = Math.round((this.clone().startOf('day') - this.clone().startOf('year')) / 864e5) + 1;\n return input == null ? dayOfYear : this.add((input - dayOfYear), 'd');\n }\n\n // FORMATTING\n\n function hFormat() {\n return this.hours() % 12 || 12;\n }\n\n addFormatToken('H', ['HH', 2], 0, 'hour');\n addFormatToken('h', ['hh', 2], 0, hFormat);\n\n addFormatToken('hmm', 0, 0, function () {\n return '' + hFormat.apply(this) + zeroFill(this.minutes(), 2);\n });\n\n addFormatToken('hmmss', 0, 0, function () {\n return '' + hFormat.apply(this) + zeroFill(this.minutes(), 2) +\n zeroFill(this.seconds(), 2);\n });\n\n addFormatToken('Hmm', 0, 0, function () {\n return '' + this.hours() + zeroFill(this.minutes(), 2);\n });\n\n addFormatToken('Hmmss', 0, 0, function () {\n return '' + this.hours() + zeroFill(this.minutes(), 2) +\n zeroFill(this.seconds(), 2);\n });\n\n function meridiem (token, lowercase) {\n addFormatToken(token, 0, 0, function () {\n return this.localeData().meridiem(this.hours(), this.minutes(), lowercase);\n });\n }\n\n meridiem('a', true);\n meridiem('A', false);\n\n // ALIASES\n\n addUnitAlias('hour', 'h');\n\n // PARSING\n\n function matchMeridiem (isStrict, locale) {\n return locale._meridiemParse;\n }\n\n addRegexToken('a', matchMeridiem);\n addRegexToken('A', matchMeridiem);\n addRegexToken('H', match1to2);\n addRegexToken('h', match1to2);\n addRegexToken('HH', match1to2, match2);\n addRegexToken('hh', match1to2, match2);\n\n addRegexToken('hmm', match3to4);\n addRegexToken('hmmss', match5to6);\n addRegexToken('Hmm', match3to4);\n addRegexToken('Hmmss', match5to6);\n\n addParseToken(['H', 'HH'], HOUR);\n addParseToken(['a', 'A'], function (input, array, config) {\n config._isPm = config._locale.isPM(input);\n config._meridiem = input;\n });\n addParseToken(['h', 'hh'], function (input, array, config) {\n array[HOUR] = toInt(input);\n getParsingFlags(config).bigHour = true;\n });\n addParseToken('hmm', function (input, array, config) {\n var pos = input.length - 2;\n array[HOUR] = toInt(input.substr(0, pos));\n array[MINUTE] = toInt(input.substr(pos));\n getParsingFlags(config).bigHour = true;\n });\n addParseToken('hmmss', function (input, array, config) {\n var pos1 = input.length - 4;\n var pos2 = input.length - 2;\n array[HOUR] = toInt(input.substr(0, pos1));\n array[MINUTE] = toInt(input.substr(pos1, 2));\n array[SECOND] = toInt(input.substr(pos2));\n getParsingFlags(config).bigHour = true;\n });\n addParseToken('Hmm', function (input, array, config) {\n var pos = input.length - 2;\n array[HOUR] = toInt(input.substr(0, pos));\n array[MINUTE] = toInt(input.substr(pos));\n });\n addParseToken('Hmmss', function (input, array, config) {\n var pos1 = input.length - 4;\n var pos2 = input.length - 2;\n array[HOUR] = toInt(input.substr(0, pos1));\n array[MINUTE] = toInt(input.substr(pos1, 2));\n array[SECOND] = toInt(input.substr(pos2));\n });\n\n // LOCALES\n\n function localeIsPM (input) {\n // IE8 Quirks Mode & IE7 Standards Mode do not allow accessing strings like arrays\n // Using charAt should be more compatible.\n return ((input + '').toLowerCase().charAt(0) === 'p');\n }\n\n var defaultLocaleMeridiemParse = /[ap]\\.?m?\\.?/i;\n function localeMeridiem (hours, minutes, isLower) {\n if (hours > 11) {\n return isLower ? 'pm' : 'PM';\n } else {\n return isLower ? 'am' : 'AM';\n }\n }\n\n\n // MOMENTS\n\n // Setting the hour should keep the time, because the user explicitly\n // specified which hour he wants. So trying to maintain the same hour (in\n // a new timezone) makes sense. Adding/subtracting hours does not follow\n // this rule.\n var getSetHour = makeGetSet('Hours', true);\n\n // FORMATTING\n\n addFormatToken('m', ['mm', 2], 0, 'minute');\n\n // ALIASES\n\n addUnitAlias('minute', 'm');\n\n // PARSING\n\n addRegexToken('m', match1to2);\n addRegexToken('mm', match1to2, match2);\n addParseToken(['m', 'mm'], MINUTE);\n\n // MOMENTS\n\n var getSetMinute = makeGetSet('Minutes', false);\n\n // FORMATTING\n\n addFormatToken('s', ['ss', 2], 0, 'second');\n\n // ALIASES\n\n addUnitAlias('second', 's');\n\n // PARSING\n\n addRegexToken('s', match1to2);\n addRegexToken('ss', match1to2, match2);\n addParseToken(['s', 'ss'], SECOND);\n\n // MOMENTS\n\n var getSetSecond = makeGetSet('Seconds', false);\n\n // FORMATTING\n\n addFormatToken('S', 0, 0, function () {\n return ~~(this.millisecond() / 100);\n });\n\n addFormatToken(0, ['SS', 2], 0, function () {\n return ~~(this.millisecond() / 10);\n });\n\n addFormatToken(0, ['SSS', 3], 0, 'millisecond');\n addFormatToken(0, ['SSSS', 4], 0, function () {\n return this.millisecond() * 10;\n });\n addFormatToken(0, ['SSSSS', 5], 0, function () {\n return this.millisecond() * 100;\n });\n addFormatToken(0, ['SSSSSS', 6], 0, function () {\n return this.millisecond() * 1000;\n });\n addFormatToken(0, ['SSSSSSS', 7], 0, function () {\n return this.millisecond() * 10000;\n });\n addFormatToken(0, ['SSSSSSSS', 8], 0, function () {\n return this.millisecond() * 100000;\n });\n addFormatToken(0, ['SSSSSSSSS', 9], 0, function () {\n return this.millisecond() * 1000000;\n });\n\n\n // ALIASES\n\n addUnitAlias('millisecond', 'ms');\n\n // PARSING\n\n addRegexToken('S', match1to3, match1);\n addRegexToken('SS', match1to3, match2);\n addRegexToken('SSS', match1to3, match3);\n\n var token;\n for (token = 'SSSS'; token.length <= 9; token += 'S') {\n addRegexToken(token, matchUnsigned);\n }\n\n function parseMs(input, array) {\n array[MILLISECOND] = toInt(('0.' + input) * 1000);\n }\n\n for (token = 'S'; token.length <= 9; token += 'S') {\n addParseToken(token, parseMs);\n }\n // MOMENTS\n\n var getSetMillisecond = makeGetSet('Milliseconds', false);\n\n // FORMATTING\n\n addFormatToken('z', 0, 0, 'zoneAbbr');\n addFormatToken('zz', 0, 0, 'zoneName');\n\n // MOMENTS\n\n function getZoneAbbr () {\n return this._isUTC ? 'UTC' : '';\n }\n\n function getZoneName () {\n return this._isUTC ? 'Coordinated Universal Time' : '';\n }\n\n var momentPrototype__proto = Moment.prototype;\n\n momentPrototype__proto.add = add_subtract__add;\n momentPrototype__proto.calendar = moment_calendar__calendar;\n momentPrototype__proto.clone = clone;\n momentPrototype__proto.diff = diff;\n momentPrototype__proto.endOf = endOf;\n momentPrototype__proto.format = format;\n momentPrototype__proto.from = from;\n momentPrototype__proto.fromNow = fromNow;\n momentPrototype__proto.to = to;\n momentPrototype__proto.toNow = toNow;\n momentPrototype__proto.get = getSet;\n momentPrototype__proto.invalidAt = invalidAt;\n momentPrototype__proto.isAfter = isAfter;\n momentPrototype__proto.isBefore = isBefore;\n momentPrototype__proto.isBetween = isBetween;\n momentPrototype__proto.isSame = isSame;\n momentPrototype__proto.isSameOrAfter = isSameOrAfter;\n momentPrototype__proto.isSameOrBefore = isSameOrBefore;\n momentPrototype__proto.isValid = moment_valid__isValid;\n momentPrototype__proto.lang = lang;\n momentPrototype__proto.locale = locale;\n momentPrototype__proto.localeData = localeData;\n momentPrototype__proto.max = prototypeMax;\n momentPrototype__proto.min = prototypeMin;\n momentPrototype__proto.parsingFlags = parsingFlags;\n momentPrototype__proto.set = getSet;\n momentPrototype__proto.startOf = startOf;\n momentPrototype__proto.subtract = add_subtract__subtract;\n momentPrototype__proto.toArray = toArray;\n momentPrototype__proto.toObject = toObject;\n momentPrototype__proto.toDate = toDate;\n momentPrototype__proto.toISOString = moment_format__toISOString;\n momentPrototype__proto.toJSON = toJSON;\n momentPrototype__proto.toString = toString;\n momentPrototype__proto.unix = unix;\n momentPrototype__proto.valueOf = to_type__valueOf;\n momentPrototype__proto.creationData = creationData;\n\n // Year\n momentPrototype__proto.year = getSetYear;\n momentPrototype__proto.isLeapYear = getIsLeapYear;\n\n // Week Year\n momentPrototype__proto.weekYear = getSetWeekYear;\n momentPrototype__proto.isoWeekYear = getSetISOWeekYear;\n\n // Quarter\n momentPrototype__proto.quarter = momentPrototype__proto.quarters = getSetQuarter;\n\n // Month\n momentPrototype__proto.month = getSetMonth;\n momentPrototype__proto.daysInMonth = getDaysInMonth;\n\n // Week\n momentPrototype__proto.week = momentPrototype__proto.weeks = getSetWeek;\n momentPrototype__proto.isoWeek = momentPrototype__proto.isoWeeks = getSetISOWeek;\n momentPrototype__proto.weeksInYear = getWeeksInYear;\n momentPrototype__proto.isoWeeksInYear = getISOWeeksInYear;\n\n // Day\n momentPrototype__proto.date = getSetDayOfMonth;\n momentPrototype__proto.day = momentPrototype__proto.days = getSetDayOfWeek;\n momentPrototype__proto.weekday = getSetLocaleDayOfWeek;\n momentPrototype__proto.isoWeekday = getSetISODayOfWeek;\n momentPrototype__proto.dayOfYear = getSetDayOfYear;\n\n // Hour\n momentPrototype__proto.hour = momentPrototype__proto.hours = getSetHour;\n\n // Minute\n momentPrototype__proto.minute = momentPrototype__proto.minutes = getSetMinute;\n\n // Second\n momentPrototype__proto.second = momentPrototype__proto.seconds = getSetSecond;\n\n // Millisecond\n momentPrototype__proto.millisecond = momentPrototype__proto.milliseconds = getSetMillisecond;\n\n // Offset\n momentPrototype__proto.utcOffset = getSetOffset;\n momentPrototype__proto.utc = setOffsetToUTC;\n momentPrototype__proto.local = setOffsetToLocal;\n momentPrototype__proto.parseZone = setOffsetToParsedOffset;\n momentPrototype__proto.hasAlignedHourOffset = hasAlignedHourOffset;\n momentPrototype__proto.isDST = isDaylightSavingTime;\n momentPrototype__proto.isDSTShifted = isDaylightSavingTimeShifted;\n momentPrototype__proto.isLocal = isLocal;\n momentPrototype__proto.isUtcOffset = isUtcOffset;\n momentPrototype__proto.isUtc = isUtc;\n momentPrototype__proto.isUTC = isUtc;\n\n // Timezone\n momentPrototype__proto.zoneAbbr = getZoneAbbr;\n momentPrototype__proto.zoneName = getZoneName;\n\n // Deprecations\n momentPrototype__proto.dates = deprecate('dates accessor is deprecated. Use date instead.', getSetDayOfMonth);\n momentPrototype__proto.months = deprecate('months accessor is deprecated. Use month instead', getSetMonth);\n momentPrototype__proto.years = deprecate('years accessor is deprecated. Use year instead', getSetYear);\n momentPrototype__proto.zone = deprecate('moment().zone is deprecated, use moment().utcOffset instead. https://github.com/moment/moment/issues/1779', getSetZone);\n\n var momentPrototype = momentPrototype__proto;\n\n function moment__createUnix (input) {\n return local__createLocal(input * 1000);\n }\n\n function moment__createInZone () {\n return local__createLocal.apply(null, arguments).parseZone();\n }\n\n var defaultCalendar = {\n sameDay : '[Today at] LT',\n nextDay : '[Tomorrow at] LT',\n nextWeek : 'dddd [at] LT',\n lastDay : '[Yesterday at] LT',\n lastWeek : '[Last] dddd [at] LT',\n sameElse : 'L'\n };\n\n function locale_calendar__calendar (key, mom, now) {\n var output = this._calendar[key];\n return isFunction(output) ? output.call(mom, now) : output;\n }\n\n var defaultLongDateFormat = {\n LTS : 'h:mm:ss A',\n LT : 'h:mm A',\n L : 'MM/DD/YYYY',\n LL : 'MMMM D, YYYY',\n LLL : 'MMMM D, YYYY h:mm A',\n LLLL : 'dddd, MMMM D, YYYY h:mm A'\n };\n\n function longDateFormat (key) {\n var format = this._longDateFormat[key],\n formatUpper = this._longDateFormat[key.toUpperCase()];\n\n if (format || !formatUpper) {\n return format;\n }\n\n this._longDateFormat[key] = formatUpper.replace(/MMMM|MM|DD|dddd/g, function (val) {\n return val.slice(1);\n });\n\n return this._longDateFormat[key];\n }\n\n var defaultInvalidDate = 'Invalid date';\n\n function invalidDate () {\n return this._invalidDate;\n }\n\n var defaultOrdinal = '%d';\n var defaultOrdinalParse = /\\d{1,2}/;\n\n function ordinal (number) {\n return this._ordinal.replace('%d', number);\n }\n\n function preParsePostFormat (string) {\n return string;\n }\n\n var defaultRelativeTime = {\n future : 'in %s',\n past : '%s ago',\n s : 'a few seconds',\n m : 'a minute',\n mm : '%d minutes',\n h : 'an hour',\n hh : '%d hours',\n d : 'a day',\n dd : '%d days',\n M : 'a month',\n MM : '%d months',\n y : 'a year',\n yy : '%d years'\n };\n\n function relative__relativeTime (number, withoutSuffix, string, isFuture) {\n var output = this._relativeTime[string];\n return (isFunction(output)) ?\n output(number, withoutSuffix, string, isFuture) :\n output.replace(/%d/i, number);\n }\n\n function pastFuture (diff, output) {\n var format = this._relativeTime[diff > 0 ? 'future' : 'past'];\n return isFunction(format) ? format(output) : format.replace(/%s/i, output);\n }\n\n function locale_set__set (config) {\n var prop, i;\n for (i in config) {\n prop = config[i];\n if (isFunction(prop)) {\n this[i] = prop;\n } else {\n this['_' + i] = prop;\n }\n }\n // Lenient ordinal parsing accepts just a number in addition to\n // number + (possibly) stuff coming from _ordinalParseLenient.\n this._ordinalParseLenient = new RegExp(this._ordinalParse.source + '|' + (/\\d{1,2}/).source);\n }\n\n var prototype__proto = Locale.prototype;\n\n prototype__proto._calendar = defaultCalendar;\n prototype__proto.calendar = locale_calendar__calendar;\n prototype__proto._longDateFormat = defaultLongDateFormat;\n prototype__proto.longDateFormat = longDateFormat;\n prototype__proto._invalidDate = defaultInvalidDate;\n prototype__proto.invalidDate = invalidDate;\n prototype__proto._ordinal = defaultOrdinal;\n prototype__proto.ordinal = ordinal;\n prototype__proto._ordinalParse = defaultOrdinalParse;\n prototype__proto.preparse = preParsePostFormat;\n prototype__proto.postformat = preParsePostFormat;\n prototype__proto._relativeTime = defaultRelativeTime;\n prototype__proto.relativeTime = relative__relativeTime;\n prototype__proto.pastFuture = pastFuture;\n prototype__proto.set = locale_set__set;\n\n // Month\n prototype__proto.months = localeMonths;\n prototype__proto._months = defaultLocaleMonths;\n prototype__proto.monthsShort = localeMonthsShort;\n prototype__proto._monthsShort = defaultLocaleMonthsShort;\n prototype__proto.monthsParse = localeMonthsParse;\n prototype__proto._monthsRegex = defaultMonthsRegex;\n prototype__proto.monthsRegex = monthsRegex;\n prototype__proto._monthsShortRegex = defaultMonthsShortRegex;\n prototype__proto.monthsShortRegex = monthsShortRegex;\n\n // Week\n prototype__proto.week = localeWeek;\n prototype__proto._week = defaultLocaleWeek;\n prototype__proto.firstDayOfYear = localeFirstDayOfYear;\n prototype__proto.firstDayOfWeek = localeFirstDayOfWeek;\n\n // Day of Week\n prototype__proto.weekdays = localeWeekdays;\n prototype__proto._weekdays = defaultLocaleWeekdays;\n prototype__proto.weekdaysMin = localeWeekdaysMin;\n prototype__proto._weekdaysMin = defaultLocaleWeekdaysMin;\n prototype__proto.weekdaysShort = localeWeekdaysShort;\n prototype__proto._weekdaysShort = defaultLocaleWeekdaysShort;\n prototype__proto.weekdaysParse = localeWeekdaysParse;\n\n // Hours\n prototype__proto.isPM = localeIsPM;\n prototype__proto._meridiemParse = defaultLocaleMeridiemParse;\n prototype__proto.meridiem = localeMeridiem;\n\n function lists__get (format, index, field, setter) {\n var locale = locale_locales__getLocale();\n var utc = create_utc__createUTC().set(setter, index);\n return locale[field](utc, format);\n }\n\n function list (format, index, field, count, setter) {\n if (typeof format === 'number') {\n index = format;\n format = undefined;\n }\n\n format = format || '';\n\n if (index != null) {\n return lists__get(format, index, field, setter);\n }\n\n var i;\n var out = [];\n for (i = 0; i < count; i++) {\n out[i] = lists__get(format, i, field, setter);\n }\n return out;\n }\n\n function lists__listMonths (format, index) {\n return list(format, index, 'months', 12, 'month');\n }\n\n function lists__listMonthsShort (format, index) {\n return list(format, index, 'monthsShort', 12, 'month');\n }\n\n function lists__listWeekdays (format, index) {\n return list(format, index, 'weekdays', 7, 'day');\n }\n\n function lists__listWeekdaysShort (format, index) {\n return list(format, index, 'weekdaysShort', 7, 'day');\n }\n\n function lists__listWeekdaysMin (format, index) {\n return list(format, index, 'weekdaysMin', 7, 'day');\n }\n\n locale_locales__getSetGlobalLocale('en', {\n ordinalParse: /\\d{1,2}(th|st|nd|rd)/,\n ordinal : function (number) {\n var b = number % 10,\n output = (toInt(number % 100 / 10) === 1) ? 'th' :\n (b === 1) ? 'st' :\n (b === 2) ? 'nd' :\n (b === 3) ? 'rd' : 'th';\n return number + output;\n }\n });\n\n // Side effect imports\n utils_hooks__hooks.lang = deprecate('moment.lang is deprecated. Use moment.locale instead.', locale_locales__getSetGlobalLocale);\n utils_hooks__hooks.langData = deprecate('moment.langData is deprecated. Use moment.localeData instead.', locale_locales__getLocale);\n\n var mathAbs = Math.abs;\n\n function duration_abs__abs () {\n var data = this._data;\n\n this._milliseconds = mathAbs(this._milliseconds);\n this._days = mathAbs(this._days);\n this._months = mathAbs(this._months);\n\n data.milliseconds = mathAbs(data.milliseconds);\n data.seconds = mathAbs(data.seconds);\n data.minutes = mathAbs(data.minutes);\n data.hours = mathAbs(data.hours);\n data.months = mathAbs(data.months);\n data.years = mathAbs(data.years);\n\n return this;\n }\n\n function duration_add_subtract__addSubtract (duration, input, value, direction) {\n var other = create__createDuration(input, value);\n\n duration._milliseconds += direction * other._milliseconds;\n duration._days += direction * other._days;\n duration._months += direction * other._months;\n\n return duration._bubble();\n }\n\n // supports only 2.0-style add(1, 's') or add(duration)\n function duration_add_subtract__add (input, value) {\n return duration_add_subtract__addSubtract(this, input, value, 1);\n }\n\n // supports only 2.0-style subtract(1, 's') or subtract(duration)\n function duration_add_subtract__subtract (input, value) {\n return duration_add_subtract__addSubtract(this, input, value, -1);\n }\n\n function absCeil (number) {\n if (number < 0) {\n return Math.floor(number);\n } else {\n return Math.ceil(number);\n }\n }\n\n function bubble () {\n var milliseconds = this._milliseconds;\n var days = this._days;\n var months = this._months;\n var data = this._data;\n var seconds, minutes, hours, years, monthsFromDays;\n\n // if we have a mix of positive and negative values, bubble down first\n // check: https://github.com/moment/moment/issues/2166\n if (!((milliseconds >= 0 && days >= 0 && months >= 0) ||\n (milliseconds <= 0 && days <= 0 && months <= 0))) {\n milliseconds += absCeil(monthsToDays(months) + days) * 864e5;\n days = 0;\n months = 0;\n }\n\n // The following code bubbles up values, see the tests for\n // examples of what that means.\n data.milliseconds = milliseconds % 1000;\n\n seconds = absFloor(milliseconds / 1000);\n data.seconds = seconds % 60;\n\n minutes = absFloor(seconds / 60);\n data.minutes = minutes % 60;\n\n hours = absFloor(minutes / 60);\n data.hours = hours % 24;\n\n days += absFloor(hours / 24);\n\n // convert days to months\n monthsFromDays = absFloor(daysToMonths(days));\n months += monthsFromDays;\n days -= absCeil(monthsToDays(monthsFromDays));\n\n // 12 months -> 1 year\n years = absFloor(months / 12);\n months %= 12;\n\n data.days = days;\n data.months = months;\n data.years = years;\n\n return this;\n }\n\n function daysToMonths (days) {\n // 400 years have 146097 days (taking into account leap year rules)\n // 400 years have 12 months === 4800\n return days * 4800 / 146097;\n }\n\n function monthsToDays (months) {\n // the reverse of daysToMonths\n return months * 146097 / 4800;\n }\n\n function as (units) {\n var days;\n var months;\n var milliseconds = this._milliseconds;\n\n units = normalizeUnits(units);\n\n if (units === 'month' || units === 'year') {\n days = this._days + milliseconds / 864e5;\n months = this._months + daysToMonths(days);\n return units === 'month' ? months : months / 12;\n } else {\n // handle milliseconds separately because of floating point math errors (issue #1867)\n days = this._days + Math.round(monthsToDays(this._months));\n switch (units) {\n case 'week' : return days / 7 + milliseconds / 6048e5;\n case 'day' : return days + milliseconds / 864e5;\n case 'hour' : return days * 24 + milliseconds / 36e5;\n case 'minute' : return days * 1440 + milliseconds / 6e4;\n case 'second' : return days * 86400 + milliseconds / 1000;\n // Math.floor prevents floating point math errors here\n case 'millisecond': return Math.floor(days * 864e5) + milliseconds;\n default: throw new Error('Unknown unit ' + units);\n }\n }\n }\n\n // TODO: Use this.as('ms')?\n function duration_as__valueOf () {\n return (\n this._milliseconds +\n this._days * 864e5 +\n (this._months % 12) * 2592e6 +\n toInt(this._months / 12) * 31536e6\n );\n }\n\n function makeAs (alias) {\n return function () {\n return this.as(alias);\n };\n }\n\n var asMilliseconds = makeAs('ms');\n var asSeconds = makeAs('s');\n var asMinutes = makeAs('m');\n var asHours = makeAs('h');\n var asDays = makeAs('d');\n var asWeeks = makeAs('w');\n var asMonths = makeAs('M');\n var asYears = makeAs('y');\n\n function duration_get__get (units) {\n units = normalizeUnits(units);\n return this[units + 's']();\n }\n\n function makeGetter(name) {\n return function () {\n return this._data[name];\n };\n }\n\n var milliseconds = makeGetter('milliseconds');\n var seconds = makeGetter('seconds');\n var minutes = makeGetter('minutes');\n var hours = makeGetter('hours');\n var days = makeGetter('days');\n var months = makeGetter('months');\n var years = makeGetter('years');\n\n function weeks () {\n return absFloor(this.days() / 7);\n }\n\n var round = Math.round;\n var thresholds = {\n s: 45, // seconds to minute\n m: 45, // minutes to hour\n h: 22, // hours to day\n d: 26, // days to month\n M: 11 // months to year\n };\n\n // helper function for moment.fn.from, moment.fn.fromNow, and moment.duration.fn.humanize\n function substituteTimeAgo(string, number, withoutSuffix, isFuture, locale) {\n return locale.relativeTime(number || 1, !!withoutSuffix, string, isFuture);\n }\n\n function duration_humanize__relativeTime (posNegDuration, withoutSuffix, locale) {\n var duration = create__createDuration(posNegDuration).abs();\n var seconds = round(duration.as('s'));\n var minutes = round(duration.as('m'));\n var hours = round(duration.as('h'));\n var days = round(duration.as('d'));\n var months = round(duration.as('M'));\n var years = round(duration.as('y'));\n\n var a = seconds < thresholds.s && ['s', seconds] ||\n minutes <= 1 && ['m'] ||\n minutes < thresholds.m && ['mm', minutes] ||\n hours <= 1 && ['h'] ||\n hours < thresholds.h && ['hh', hours] ||\n days <= 1 && ['d'] ||\n days < thresholds.d && ['dd', days] ||\n months <= 1 && ['M'] ||\n months < thresholds.M && ['MM', months] ||\n years <= 1 && ['y'] || ['yy', years];\n\n a[2] = withoutSuffix;\n a[3] = +posNegDuration > 0;\n a[4] = locale;\n return substituteTimeAgo.apply(null, a);\n }\n\n // This function allows you to set a threshold for relative time strings\n function duration_humanize__getSetRelativeTimeThreshold (threshold, limit) {\n if (thresholds[threshold] === undefined) {\n return false;\n }\n if (limit === undefined) {\n return thresholds[threshold];\n }\n thresholds[threshold] = limit;\n return true;\n }\n\n function humanize (withSuffix) {\n var locale = this.localeData();\n var output = duration_humanize__relativeTime(this, !withSuffix, locale);\n\n if (withSuffix) {\n output = locale.pastFuture(+this, output);\n }\n\n return locale.postformat(output);\n }\n\n var iso_string__abs = Math.abs;\n\n function iso_string__toISOString() {\n // for ISO strings we do not use the normal bubbling rules:\n // * milliseconds bubble up until they become hours\n // * days do not bubble at all\n // * months bubble up until they become years\n // This is because there is no context-free conversion between hours and days\n // (think of clock changes)\n // and also not between days and months (28-31 days per month)\n var seconds = iso_string__abs(this._milliseconds) / 1000;\n var days = iso_string__abs(this._days);\n var months = iso_string__abs(this._months);\n var minutes, hours, years;\n\n // 3600 seconds -> 60 minutes -> 1 hour\n minutes = absFloor(seconds / 60);\n hours = absFloor(minutes / 60);\n seconds %= 60;\n minutes %= 60;\n\n // 12 months -> 1 year\n years = absFloor(months / 12);\n months %= 12;\n\n\n // inspired by https://github.com/dordille/moment-isoduration/blob/master/moment.isoduration.js\n var Y = years;\n var M = months;\n var D = days;\n var h = hours;\n var m = minutes;\n var s = seconds;\n var total = this.asSeconds();\n\n if (!total) {\n // this is the same as C#'s (Noda) and python (isodate)...\n // but not other JS (goog.date)\n return 'P0D';\n }\n\n return (total < 0 ? '-' : '') +\n 'P' +\n (Y ? Y + 'Y' : '') +\n (M ? M + 'M' : '') +\n (D ? D + 'D' : '') +\n ((h || m || s) ? 'T' : '') +\n (h ? h + 'H' : '') +\n (m ? m + 'M' : '') +\n (s ? s + 'S' : '');\n }\n\n var duration_prototype__proto = Duration.prototype;\n\n duration_prototype__proto.abs = duration_abs__abs;\n duration_prototype__proto.add = duration_add_subtract__add;\n duration_prototype__proto.subtract = duration_add_subtract__subtract;\n duration_prototype__proto.as = as;\n duration_prototype__proto.asMilliseconds = asMilliseconds;\n duration_prototype__proto.asSeconds = asSeconds;\n duration_prototype__proto.asMinutes = asMinutes;\n duration_prototype__proto.asHours = asHours;\n duration_prototype__proto.asDays = asDays;\n duration_prototype__proto.asWeeks = asWeeks;\n duration_prototype__proto.asMonths = asMonths;\n duration_prototype__proto.asYears = asYears;\n duration_prototype__proto.valueOf = duration_as__valueOf;\n duration_prototype__proto._bubble = bubble;\n duration_prototype__proto.get = duration_get__get;\n duration_prototype__proto.milliseconds = milliseconds;\n duration_prototype__proto.seconds = seconds;\n duration_prototype__proto.minutes = minutes;\n duration_prototype__proto.hours = hours;\n duration_prototype__proto.days = days;\n duration_prototype__proto.weeks = weeks;\n duration_prototype__proto.months = months;\n duration_prototype__proto.years = years;\n duration_prototype__proto.humanize = humanize;\n duration_prototype__proto.toISOString = iso_string__toISOString;\n duration_prototype__proto.toString = iso_string__toISOString;\n duration_prototype__proto.toJSON = iso_string__toISOString;\n duration_prototype__proto.locale = locale;\n duration_prototype__proto.localeData = localeData;\n\n // Deprecations\n duration_prototype__proto.toIsoString = deprecate('toIsoString() is deprecated. Please use toISOString() instead (notice the capitals)', iso_string__toISOString);\n duration_prototype__proto.lang = lang;\n\n // Side effect imports\n\n // FORMATTING\n\n addFormatToken('X', 0, 0, 'unix');\n addFormatToken('x', 0, 0, 'valueOf');\n\n // PARSING\n\n addRegexToken('x', matchSigned);\n addRegexToken('X', matchTimestamp);\n addParseToken('X', function (input, array, config) {\n config._d = new Date(parseFloat(input, 10) * 1000);\n });\n addParseToken('x', function (input, array, config) {\n config._d = new Date(toInt(input));\n });\n\n // Side effect imports\n\n\n utils_hooks__hooks.version = '2.11.2';\n\n setHookCallback(local__createLocal);\n\n utils_hooks__hooks.fn = momentPrototype;\n utils_hooks__hooks.min = min;\n utils_hooks__hooks.max = max;\n utils_hooks__hooks.now = now;\n utils_hooks__hooks.utc = create_utc__createUTC;\n utils_hooks__hooks.unix = moment__createUnix;\n utils_hooks__hooks.months = lists__listMonths;\n utils_hooks__hooks.isDate = isDate;\n utils_hooks__hooks.locale = locale_locales__getSetGlobalLocale;\n utils_hooks__hooks.invalid = valid__createInvalid;\n utils_hooks__hooks.duration = create__createDuration;\n utils_hooks__hooks.isMoment = isMoment;\n utils_hooks__hooks.weekdays = lists__listWeekdays;\n utils_hooks__hooks.parseZone = moment__createInZone;\n utils_hooks__hooks.localeData = locale_locales__getLocale;\n utils_hooks__hooks.isDuration = isDuration;\n utils_hooks__hooks.monthsShort = lists__listMonthsShort;\n utils_hooks__hooks.weekdaysMin = lists__listWeekdaysMin;\n utils_hooks__hooks.defineLocale = defineLocale;\n utils_hooks__hooks.weekdaysShort = lists__listWeekdaysShort;\n utils_hooks__hooks.normalizeUnits = normalizeUnits;\n utils_hooks__hooks.relativeTimeThreshold = duration_humanize__getSetRelativeTimeThreshold;\n utils_hooks__hooks.prototype = momentPrototype;\n\n var _moment = utils_hooks__hooks;\n\n return _moment;\n\n }));\n /* WEBPACK VAR INJECTION */}.call(exports, __webpack_require__(4)(module)))\n\n/***/ },\n/* 4 */\n/***/ function(module, exports) {\n\n module.exports = function(module) {\n \tif(!module.webpackPolyfill) {\n \t\tmodule.deprecate = function() {};\n \t\tmodule.paths = [];\n \t\t// module.parent = undefined by default\n \t\tmodule.children = [];\n \t\tmodule.webpackPolyfill = 1;\n \t}\n \treturn module;\n }\n\n\n/***/ },\n/* 5 */\n/***/ function(module, exports) {\n\n function webpackContext(req) {\n \tthrow new Error(\"Cannot find module '\" + req + \"'.\");\n }\n webpackContext.keys = function() { return []; };\n webpackContext.resolve = webpackContext;\n module.exports = webpackContext;\n webpackContext.id = 5;\n\n\n/***/ },\n/* 6 */\n/***/ function(module, exports) {\n\n /* WEBPACK VAR INJECTION */(function(global) {'use strict';\n\n var _rng;\n\n var globalVar = typeof window !== 'undefined' ? window : typeof global !== 'undefined' ? global : null;\n\n if (globalVar && globalVar.crypto && crypto.getRandomValues) {\n // WHATWG crypto-based RNG - http://wiki.whatwg.org/wiki/Crypto\n // Moderately fast, high quality\n var _rnds8 = new Uint8Array(16);\n _rng = function whatwgRNG() {\n crypto.getRandomValues(_rnds8);\n return _rnds8;\n };\n }\n\n if (!_rng) {\n // Math.random()-based (RNG)\n //\n // If all else fails, use Math.random(). It's fast, but is of unspecified\n // quality.\n var _rnds = new Array(16);\n _rng = function () {\n for (var i = 0, r; i < 16; i++) {\n if ((i & 0x03) === 0) r = Math.random() * 0x100000000;\n _rnds[i] = r >>> ((i & 0x03) << 3) & 0xff;\n }\n\n return _rnds;\n };\n }\n\n // uuid.js\n //\n // Copyright (c) 2010-2012 Robert Kieffer\n // MIT License - http://opensource.org/licenses/mit-license.php\n\n // Unique ID creation requires a high quality random # generator. We feature\n // detect to determine the best RNG source, normalizing to a function that\n // returns 128-bits of randomness, since that's what's usually required\n\n //var _rng = require('./rng');\n\n // Maps for number <-> hex string conversion\n var _byteToHex = [];\n var _hexToByte = {};\n for (var i = 0; i < 256; i++) {\n _byteToHex[i] = (i + 0x100).toString(16).substr(1);\n _hexToByte[_byteToHex[i]] = i;\n }\n\n // **`parse()` - Parse a UUID into it's component bytes**\n function parse(s, buf, offset) {\n var i = buf && offset || 0,\n ii = 0;\n\n buf = buf || [];\n s.toLowerCase().replace(/[0-9a-f]{2}/g, function (oct) {\n if (ii < 16) {\n // Don't overflow!\n buf[i + ii++] = _hexToByte[oct];\n }\n });\n\n // Zero out remaining bytes if string was short\n while (ii < 16) {\n buf[i + ii++] = 0;\n }\n\n return buf;\n }\n\n // **`unparse()` - Convert UUID byte array (ala parse()) into a string**\n function unparse(buf, offset) {\n var i = offset || 0,\n bth = _byteToHex;\n return bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]] + '-' + bth[buf[i++]] + bth[buf[i++]] + '-' + bth[buf[i++]] + bth[buf[i++]] + '-' + bth[buf[i++]] + bth[buf[i++]] + '-' + bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]] + bth[buf[i++]];\n }\n\n // **`v1()` - Generate time-based UUID**\n //\n // Inspired by https://github.com/LiosK/UUID.js\n // and http://docs.python.org/library/uuid.html\n\n // random #'s we need to init node and clockseq\n var _seedBytes = _rng();\n\n // Per 4.5, create and 48-bit node id, (47 random bits + multicast bit = 1)\n var _nodeId = [_seedBytes[0] | 0x01, _seedBytes[1], _seedBytes[2], _seedBytes[3], _seedBytes[4], _seedBytes[5]];\n\n // Per 4.2.2, randomize (14 bit) clockseq\n var _clockseq = (_seedBytes[6] << 8 | _seedBytes[7]) & 0x3fff;\n\n // Previous uuid creation time\n var _lastMSecs = 0,\n _lastNSecs = 0;\n\n // See https://github.com/broofa/node-uuid for API details\n function v1(options, buf, offset) {\n var i = buf && offset || 0;\n var b = buf || [];\n\n options = options || {};\n\n var clockseq = options.clockseq !== undefined ? options.clockseq : _clockseq;\n\n // UUID timestamps are 100 nano-second units since the Gregorian epoch,\n // (1582-10-15 00:00). JSNumbers aren't precise enough for this, so\n // time is handled internally as 'msecs' (integer milliseconds) and 'nsecs'\n // (100-nanoseconds offset from msecs) since unix epoch, 1970-01-01 00:00.\n var msecs = options.msecs !== undefined ? options.msecs : new Date().getTime();\n\n // Per 4.2.1.2, use count of uuid's generated during the current clock\n // cycle to simulate higher resolution clock\n var nsecs = options.nsecs !== undefined ? options.nsecs : _lastNSecs + 1;\n\n // Time since last uuid creation (in msecs)\n var dt = msecs - _lastMSecs + (nsecs - _lastNSecs) / 10000;\n\n // Per 4.2.1.2, Bump clockseq on clock regression\n if (dt < 0 && options.clockseq === undefined) {\n clockseq = clockseq + 1 & 0x3fff;\n }\n\n // Reset nsecs if clock regresses (new clockseq) or we've moved onto a new\n // time interval\n if ((dt < 0 || msecs > _lastMSecs) && options.nsecs === undefined) {\n nsecs = 0;\n }\n\n // Per 4.2.1.2 Throw error if too many uuids are requested\n if (nsecs >= 10000) {\n throw new Error('uuid.v1(): Can\\'t create more than 10M uuids/sec');\n }\n\n _lastMSecs = msecs;\n _lastNSecs = nsecs;\n _clockseq = clockseq;\n\n // Per 4.1.4 - Convert from unix epoch to Gregorian epoch\n msecs += 12219292800000;\n\n // `time_low`\n var tl = ((msecs & 0xfffffff) * 10000 + nsecs) % 0x100000000;\n b[i++] = tl >>> 24 & 0xff;\n b[i++] = tl >>> 16 & 0xff;\n b[i++] = tl >>> 8 & 0xff;\n b[i++] = tl & 0xff;\n\n // `time_mid`\n var tmh = msecs / 0x100000000 * 10000 & 0xfffffff;\n b[i++] = tmh >>> 8 & 0xff;\n b[i++] = tmh & 0xff;\n\n // `time_high_and_version`\n b[i++] = tmh >>> 24 & 0xf | 0x10; // include version\n b[i++] = tmh >>> 16 & 0xff;\n\n // `clock_seq_hi_and_reserved` (Per 4.2.2 - include variant)\n b[i++] = clockseq >>> 8 | 0x80;\n\n // `clock_seq_low`\n b[i++] = clockseq & 0xff;\n\n // `node`\n var node = options.node || _nodeId;\n for (var n = 0; n < 6; n++) {\n b[i + n] = node[n];\n }\n\n return buf ? buf : unparse(b);\n }\n\n // **`v4()` - Generate random UUID**\n\n // See https://github.com/broofa/node-uuid for API details\n function v4(options, buf, offset) {\n // Deprecated - 'format' argument, as supported in v1.2\n var i = buf && offset || 0;\n\n if (typeof options == 'string') {\n buf = options == 'binary' ? new Array(16) : null;\n options = null;\n }\n options = options || {};\n\n var rnds = options.random || (options.rng || _rng)();\n\n // Per 4.4, set bits for version and `clock_seq_hi_and_reserved`\n rnds[6] = rnds[6] & 0x0f | 0x40;\n rnds[8] = rnds[8] & 0x3f | 0x80;\n\n // Copy bytes to buffer, if provided\n if (buf) {\n for (var ii = 0; ii < 16; ii++) {\n buf[i + ii] = rnds[ii];\n }\n }\n\n return buf || unparse(rnds);\n }\n\n // Export public API\n var uuid = v4;\n uuid.v1 = v1;\n uuid.v4 = v4;\n uuid.parse = parse;\n uuid.unparse = unparse;\n\n module.exports = uuid;\n /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }())))\n\n/***/ },\n/* 7 */\n/***/ function(module, exports) {\n\n // DOM utility methods\n\n /**\n * this prepares the JSON container for allocating SVG elements\n * @param JSONcontainer\n * @private\n */\n 'use strict';\n\n exports.prepareElements = function (JSONcontainer) {\n // cleanup the redundant svgElements;\n for (var elementType in JSONcontainer) {\n if (JSONcontainer.hasOwnProperty(elementType)) {\n JSONcontainer[elementType].redundant = JSONcontainer[elementType].used;\n JSONcontainer[elementType].used = [];\n }\n }\n };\n\n /**\n * this cleans up all the unused SVG elements. By asking for the parentNode, we only need to supply the JSON container from\n * which to remove the redundant elements.\n *\n * @param JSONcontainer\n * @private\n */\n exports.cleanupElements = function (JSONcontainer) {\n // cleanup the redundant svgElements;\n for (var elementType in JSONcontainer) {\n if (JSONcontainer.hasOwnProperty(elementType)) {\n if (JSONcontainer[elementType].redundant) {\n for (var i = 0; i < JSONcontainer[elementType].redundant.length; i++) {\n JSONcontainer[elementType].redundant[i].parentNode.removeChild(JSONcontainer[elementType].redundant[i]);\n }\n JSONcontainer[elementType].redundant = [];\n }\n }\n }\n };\n\n /**\n * Ensures that all elements are removed first up so they can be recreated cleanly\n * @param JSONcontainer\n */\n exports.resetElements = function (JSONcontainer) {\n exports.prepareElements(JSONcontainer);\n exports.cleanupElements(JSONcontainer);\n exports.prepareElements(JSONcontainer);\n };\n\n /**\n * Allocate or generate an SVG element if needed. Store a reference to it in the JSON container and draw it in the svgContainer\n * the JSON container and the SVG container have to be supplied so other svg containers (like the legend) can use this.\n *\n * @param elementType\n * @param JSONcontainer\n * @param svgContainer\n * @returns {*}\n * @private\n */\n exports.getSVGElement = function (elementType, JSONcontainer, svgContainer) {\n var element;\n // allocate SVG element, if it doesnt yet exist, create one.\n if (JSONcontainer.hasOwnProperty(elementType)) {\n // this element has been created before\n // check if there is an redundant element\n if (JSONcontainer[elementType].redundant.length > 0) {\n element = JSONcontainer[elementType].redundant[0];\n JSONcontainer[elementType].redundant.shift();\n } else {\n // create a new element and add it to the SVG\n element = document.createElementNS('http://www.w3.org/2000/svg', elementType);\n svgContainer.appendChild(element);\n }\n } else {\n // create a new element and add it to the SVG, also create a new object in the svgElements to keep track of it.\n element = document.createElementNS('http://www.w3.org/2000/svg', elementType);\n JSONcontainer[elementType] = { used: [], redundant: [] };\n svgContainer.appendChild(element);\n }\n JSONcontainer[elementType].used.push(element);\n return element;\n };\n\n /**\n * Allocate or generate an SVG element if needed. Store a reference to it in the JSON container and draw it in the svgContainer\n * the JSON container and the SVG container have to be supplied so other svg containers (like the legend) can use this.\n *\n * @param elementType\n * @param JSONcontainer\n * @param DOMContainer\n * @returns {*}\n * @private\n */\n exports.getDOMElement = function (elementType, JSONcontainer, DOMContainer, insertBefore) {\n var element;\n // allocate DOM element, if it doesnt yet exist, create one.\n if (JSONcontainer.hasOwnProperty(elementType)) {\n // this element has been created before\n // check if there is an redundant element\n if (JSONcontainer[elementType].redundant.length > 0) {\n element = JSONcontainer[elementType].redundant[0];\n JSONcontainer[elementType].redundant.shift();\n } else {\n // create a new element and add it to the SVG\n element = document.createElement(elementType);\n if (insertBefore !== undefined) {\n DOMContainer.insertBefore(element, insertBefore);\n } else {\n DOMContainer.appendChild(element);\n }\n }\n } else {\n // create a new element and add it to the SVG, also create a new object in the svgElements to keep track of it.\n element = document.createElement(elementType);\n JSONcontainer[elementType] = { used: [], redundant: [] };\n if (insertBefore !== undefined) {\n DOMContainer.insertBefore(element, insertBefore);\n } else {\n DOMContainer.appendChild(element);\n }\n }\n JSONcontainer[elementType].used.push(element);\n return element;\n };\n\n /**\n * Draw a point object. This is a separate function because it can also be called by the legend.\n * The reason the JSONcontainer and the target SVG svgContainer have to be supplied is so the legend can use these functions\n * as well.\n *\n * @param x\n * @param y\n * @param groupTemplate: A template containing the necessary information to draw the datapoint e.g., {style: 'circle', size: 5, className: 'className' }\n * @param JSONcontainer\n * @param svgContainer\n * @param labelObj\n * @returns {*}\n */\n exports.drawPoint = function (x, y, groupTemplate, JSONcontainer, svgContainer, labelObj) {\n var point;\n if (groupTemplate.style == 'circle') {\n point = exports.getSVGElement('circle', JSONcontainer, svgContainer);\n point.setAttributeNS(null, \"cx\", x);\n point.setAttributeNS(null, \"cy\", y);\n point.setAttributeNS(null, \"r\", 0.5 * groupTemplate.size);\n } else {\n point = exports.getSVGElement('rect', JSONcontainer, svgContainer);\n point.setAttributeNS(null, \"x\", x - 0.5 * groupTemplate.size);\n point.setAttributeNS(null, \"y\", y - 0.5 * groupTemplate.size);\n point.setAttributeNS(null, \"width\", groupTemplate.size);\n point.setAttributeNS(null, \"height\", groupTemplate.size);\n }\n\n if (groupTemplate.styles !== undefined) {\n point.setAttributeNS(null, \"style\", groupTemplate.styles);\n }\n point.setAttributeNS(null, \"class\", groupTemplate.className + \" vis-point\");\n //handle label\n\n if (labelObj) {\n var label = exports.getSVGElement('text', JSONcontainer, svgContainer);\n if (labelObj.xOffset) {\n x = x + labelObj.xOffset;\n }\n\n if (labelObj.yOffset) {\n y = y + labelObj.yOffset;\n }\n if (labelObj.content) {\n label.textContent = labelObj.content;\n }\n\n if (labelObj.className) {\n label.setAttributeNS(null, \"class\", labelObj.className + \" vis-label\");\n }\n label.setAttributeNS(null, \"x\", x);\n label.setAttributeNS(null, \"y\", y);\n }\n\n return point;\n };\n\n /**\n * draw a bar SVG element centered on the X coordinate\n *\n * @param x\n * @param y\n * @param className\n */\n exports.drawBar = function (x, y, width, height, className, JSONcontainer, svgContainer, style) {\n if (height != 0) {\n if (height < 0) {\n height *= -1;\n y -= height;\n }\n var rect = exports.getSVGElement('rect', JSONcontainer, svgContainer);\n rect.setAttributeNS(null, \"x\", x - 0.5 * width);\n rect.setAttributeNS(null, \"y\", y);\n rect.setAttributeNS(null, \"width\", width);\n rect.setAttributeNS(null, \"height\", height);\n rect.setAttributeNS(null, \"class\", className);\n if (style) {\n rect.setAttributeNS(null, \"style\", style);\n }\n }\n };\n\n/***/ },\n/* 8 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var Queue = __webpack_require__(9);\n\n /**\n * DataSet\n *\n * Usage:\n * var dataSet = new DataSet({\n * fieldId: '_id',\n * type: {\n * // ...\n * }\n * });\n *\n * dataSet.add(item);\n * dataSet.add(data);\n * dataSet.update(item);\n * dataSet.update(data);\n * dataSet.remove(id);\n * dataSet.remove(ids);\n * var data = dataSet.get();\n * var data = dataSet.get(id);\n * var data = dataSet.get(ids);\n * var data = dataSet.get(ids, options, data);\n * dataSet.clear();\n *\n * A data set can:\n * - add/remove/update data\n * - gives triggers upon changes in the data\n * - can import/export data in various data formats\n *\n * @param {Array} [data] Optional array with initial data\n * @param {Object} [options] Available options:\n * {String} fieldId Field name of the id in the\n * items, 'id' by default.\n * {Object.<String, String} type\n * A map with field names as key,\n * and the field type as value.\n * {Object} queue Queue changes to the DataSet,\n * flush them all at once.\n * Queue options:\n * - {number} delay Delay in ms, null by default\n * - {number} max Maximum number of entries in the queue, Infinity by default\n * @constructor DataSet\n */\n // TODO: add a DataSet constructor DataSet(data, options)\n function DataSet(data, options) {\n // correctly read optional arguments\n if (data && !Array.isArray(data)) {\n options = data;\n data = null;\n }\n\n this._options = options || {};\n this._data = {}; // map with data indexed by id\n this.length = 0; // number of items in the DataSet\n this._fieldId = this._options.fieldId || 'id'; // name of the field containing id\n this._type = {}; // internal field types (NOTE: this can differ from this._options.type)\n\n // all variants of a Date are internally stored as Date, so we can convert\n // from everything to everything (also from ISODate to Number for example)\n if (this._options.type) {\n var fields = Object.keys(this._options.type);\n for (var i = 0, len = fields.length; i < len; i++) {\n var field = fields[i];\n var value = this._options.type[field];\n if (value == 'Date' || value == 'ISODate' || value == 'ASPDate') {\n this._type[field] = 'Date';\n } else {\n this._type[field] = value;\n }\n }\n }\n\n // TODO: deprecated since version 1.1.1 (or 2.0.0?)\n if (this._options.convert) {\n throw new Error('Option \"convert\" is deprecated. Use \"type\" instead.');\n }\n\n this._subscribers = {}; // event subscribers\n\n // add initial data when provided\n if (data) {\n this.add(data);\n }\n\n this.setOptions(options);\n }\n\n /**\n * @param {Object} [options] Available options:\n * {Object} queue Queue changes to the DataSet,\n * flush them all at once.\n * Queue options:\n * - {number} delay Delay in ms, null by default\n * - {number} max Maximum number of entries in the queue, Infinity by default\n * @param options\n */\n DataSet.prototype.setOptions = function (options) {\n if (options && options.queue !== undefined) {\n if (options.queue === false) {\n // delete queue if loaded\n if (this._queue) {\n this._queue.destroy();\n delete this._queue;\n }\n } else {\n // create queue and update its options\n if (!this._queue) {\n this._queue = Queue.extend(this, {\n replace: ['add', 'update', 'remove']\n });\n }\n\n if (typeof options.queue === 'object') {\n this._queue.setOptions(options.queue);\n }\n }\n }\n };\n\n /**\n * Subscribe to an event, add an event listener\n * @param {String} event Event name. Available events: 'put', 'update',\n * 'remove'\n * @param {function} callback Callback method. Called with three parameters:\n * {String} event\n * {Object | null} params\n * {String | Number} senderId\n */\n DataSet.prototype.on = function (event, callback) {\n var subscribers = this._subscribers[event];\n if (!subscribers) {\n subscribers = [];\n this._subscribers[event] = subscribers;\n }\n\n subscribers.push({\n callback: callback\n });\n };\n\n // TODO: remove this deprecated function some day (replaced with `on` since version 0.5, deprecated since v4.0)\n DataSet.prototype.subscribe = function () {\n throw new Error('DataSet.subscribe is deprecated. Use DataSet.on instead.');\n };\n\n /**\n * Unsubscribe from an event, remove an event listener\n * @param {String} event\n * @param {function} callback\n */\n DataSet.prototype.off = function (event, callback) {\n var subscribers = this._subscribers[event];\n if (subscribers) {\n this._subscribers[event] = subscribers.filter(function (listener) {\n return listener.callback != callback;\n });\n }\n };\n\n // TODO: remove this deprecated function some day (replaced with `on` since version 0.5, deprecated since v4.0)\n DataSet.prototype.unsubscribe = function () {\n throw new Error('DataSet.unsubscribe is deprecated. Use DataSet.off instead.');\n };\n\n /**\n * Trigger an event\n * @param {String} event\n * @param {Object | null} params\n * @param {String} [senderId] Optional id of the sender.\n * @private\n */\n DataSet.prototype._trigger = function (event, params, senderId) {\n if (event == '*') {\n throw new Error('Cannot trigger event *');\n }\n\n var subscribers = [];\n if (event in this._subscribers) {\n subscribers = subscribers.concat(this._subscribers[event]);\n }\n if ('*' in this._subscribers) {\n subscribers = subscribers.concat(this._subscribers['*']);\n }\n\n for (var i = 0, len = subscribers.length; i < len; i++) {\n var subscriber = subscribers[i];\n if (subscriber.callback) {\n subscriber.callback(event, params, senderId || null);\n }\n }\n };\n\n /**\n * Add data.\n * Adding an item will fail when there already is an item with the same id.\n * @param {Object | Array} data\n * @param {String} [senderId] Optional sender id\n * @return {Array} addedIds Array with the ids of the added items\n */\n DataSet.prototype.add = function (data, senderId) {\n var addedIds = [],\n id,\n me = this;\n\n if (Array.isArray(data)) {\n // Array\n for (var i = 0, len = data.length; i < len; i++) {\n id = me._addItem(data[i]);\n addedIds.push(id);\n }\n } else if (data instanceof Object) {\n // Single item\n id = me._addItem(data);\n addedIds.push(id);\n } else {\n throw new Error('Unknown dataType');\n }\n\n if (addedIds.length) {\n this._trigger('add', { items: addedIds }, senderId);\n }\n\n return addedIds;\n };\n\n /**\n * Update existing items. When an item does not exist, it will be created\n * @param {Object | Array} data\n * @param {String} [senderId] Optional sender id\n * @return {Array} updatedIds The ids of the added or updated items\n */\n DataSet.prototype.update = function (data, senderId) {\n var addedIds = [];\n var updatedIds = [];\n var oldData = [];\n var updatedData = [];\n var me = this;\n var fieldId = me._fieldId;\n\n var addOrUpdate = function addOrUpdate(item) {\n var id = item[fieldId];\n if (me._data[id]) {\n var oldItem = util.extend({}, me._data[id]);\n // update item\n id = me._updateItem(item);\n updatedIds.push(id);\n updatedData.push(item);\n oldData.push(oldItem);\n } else {\n // add new item\n id = me._addItem(item);\n addedIds.push(id);\n }\n };\n\n if (Array.isArray(data)) {\n // Array\n for (var i = 0, len = data.length; i < len; i++) {\n if (data[i] instanceof Object) {\n addOrUpdate(data[i]);\n } else {\n console.warn('Ignoring input item, which is not an object at index ' + i);\n }\n }\n } else if (data instanceof Object) {\n // Single item\n addOrUpdate(data);\n } else {\n throw new Error('Unknown dataType');\n }\n\n if (addedIds.length) {\n this._trigger('add', { items: addedIds }, senderId);\n }\n if (updatedIds.length) {\n var props = { items: updatedIds, oldData: oldData, data: updatedData };\n // TODO: remove deprecated property 'data' some day\n //Object.defineProperty(props, 'data', {\n // 'get': (function() {\n // console.warn('Property data is deprecated. Use DataSet.get(ids) to retrieve the new data, use the oldData property on this object to get the old data');\n // return updatedData;\n // }).bind(this)\n //});\n this._trigger('update', props, senderId);\n }\n\n return addedIds.concat(updatedIds);\n };\n\n /**\n * Get a data item or multiple items.\n *\n * Usage:\n *\n * get()\n * get(options: Object)\n *\n * get(id: Number | String)\n * get(id: Number | String, options: Object)\n *\n * get(ids: Number[] | String[])\n * get(ids: Number[] | String[], options: Object)\n *\n * Where:\n *\n * {Number | String} id The id of an item\n * {Number[] | String{}} ids An array with ids of items\n * {Object} options An Object with options. Available options:\n * {String} [returnType] Type of data to be returned.\n * Can be 'Array' (default) or 'Object'.\n * {Object.<String, String>} [type]\n * {String[]} [fields] field names to be returned\n * {function} [filter] filter items\n * {String | function} [order] Order the items by a field name or custom sort function.\n * @throws Error\n */\n DataSet.prototype.get = function (args) {\n var me = this;\n\n // parse the arguments\n var id, ids, options;\n var firstType = util.getType(arguments[0]);\n if (firstType == 'String' || firstType == 'Number') {\n // get(id [, options])\n id = arguments[0];\n options = arguments[1];\n } else if (firstType == 'Array') {\n // get(ids [, options])\n ids = arguments[0];\n options = arguments[1];\n } else {\n // get([, options])\n options = arguments[0];\n }\n\n // determine the return type\n var returnType;\n if (options && options.returnType) {\n var allowedValues = ['Array', 'Object'];\n returnType = allowedValues.indexOf(options.returnType) == -1 ? 'Array' : options.returnType;\n } else {\n returnType = 'Array';\n }\n\n // build options\n var type = options && options.type || this._options.type;\n var filter = options && options.filter;\n var items = [],\n item,\n itemIds,\n itemId,\n i,\n len;\n\n // convert items\n if (id != undefined) {\n // return a single item\n item = me._getItem(id, type);\n if (item && filter && !filter(item)) {\n item = null;\n }\n } else if (ids != undefined) {\n // return a subset of items\n for (i = 0, len = ids.length; i < len; i++) {\n item = me._getItem(ids[i], type);\n if (!filter || filter(item)) {\n items.push(item);\n }\n }\n } else {\n // return all items\n itemIds = Object.keys(this._data);\n for (i = 0, len = itemIds.length; i < len; i++) {\n itemId = itemIds[i];\n item = me._getItem(itemId, type);\n if (!filter || filter(item)) {\n items.push(item);\n }\n }\n }\n\n // order the results\n if (options && options.order && id == undefined) {\n this._sort(items, options.order);\n }\n\n // filter fields of the items\n if (options && options.fields) {\n var fields = options.fields;\n if (id != undefined) {\n item = this._filterFields(item, fields);\n } else {\n for (i = 0, len = items.length; i < len; i++) {\n items[i] = this._filterFields(items[i], fields);\n }\n }\n }\n\n // return the results\n if (returnType == 'Object') {\n var result = {},\n resultant;\n for (i = 0, len = items.length; i < len; i++) {\n resultant = items[i];\n result[resultant.id] = resultant;\n }\n return result;\n } else {\n if (id != undefined) {\n // a single item\n return item;\n } else {\n // just return our array\n return items;\n }\n }\n };\n\n /**\n * Get ids of all items or from a filtered set of items.\n * @param {Object} [options] An Object with options. Available options:\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n * @return {Array} ids\n */\n DataSet.prototype.getIds = function (options) {\n var data = this._data,\n filter = options && options.filter,\n order = options && options.order,\n type = options && options.type || this._options.type,\n itemIds = Object.keys(data),\n i,\n len,\n id,\n item,\n items,\n ids = [];\n\n if (filter) {\n // get filtered items\n if (order) {\n // create ordered list\n items = [];\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n item = this._getItem(id, type);\n if (filter(item)) {\n items.push(item);\n }\n }\n\n this._sort(items, order);\n\n for (i = 0, len = items.length; i < len; i++) {\n ids.push(items[i][this._fieldId]);\n }\n } else {\n // create unordered list\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n item = this._getItem(id, type);\n if (filter(item)) {\n ids.push(item[this._fieldId]);\n }\n }\n }\n } else {\n // get all items\n if (order) {\n // create an ordered list\n items = [];\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n items.push(data[id]);\n }\n\n this._sort(items, order);\n\n for (i = 0, len = items.length; i < len; i++) {\n ids.push(items[i][this._fieldId]);\n }\n } else {\n // create unordered list\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n item = data[id];\n ids.push(item[this._fieldId]);\n }\n }\n }\n\n return ids;\n };\n\n /**\n * Returns the DataSet itself. Is overwritten for example by the DataView,\n * which returns the DataSet it is connected to instead.\n */\n DataSet.prototype.getDataSet = function () {\n return this;\n };\n\n /**\n * Execute a callback function for every item in the dataset.\n * @param {function} callback\n * @param {Object} [options] Available options:\n * {Object.<String, String>} [type]\n * {String[]} [fields] filter fields\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n */\n DataSet.prototype.forEach = function (callback, options) {\n var filter = options && options.filter,\n type = options && options.type || this._options.type,\n data = this._data,\n itemIds = Object.keys(data),\n i,\n len,\n item,\n id;\n\n if (options && options.order) {\n // execute forEach on ordered list\n var items = this.get(options);\n\n for (i = 0, len = items.length; i < len; i++) {\n item = items[i];\n id = item[this._fieldId];\n callback(item, id);\n }\n } else {\n // unordered\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n item = this._getItem(id, type);\n if (!filter || filter(item)) {\n callback(item, id);\n }\n }\n }\n };\n\n /**\n * Map every item in the dataset.\n * @param {function} callback\n * @param {Object} [options] Available options:\n * {Object.<String, String>} [type]\n * {String[]} [fields] filter fields\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n * @return {Object[]} mappedItems\n */\n DataSet.prototype.map = function (callback, options) {\n var filter = options && options.filter,\n type = options && options.type || this._options.type,\n mappedItems = [],\n data = this._data,\n itemIds = Object.keys(data),\n i,\n len,\n id,\n item;\n\n // convert and filter items\n for (i = 0, len = itemIds.length; i < len; i++) {\n id = itemIds[i];\n item = this._getItem(id, type);\n if (!filter || filter(item)) {\n mappedItems.push(callback(item, id));\n }\n }\n\n // order items\n if (options && options.order) {\n this._sort(mappedItems, options.order);\n }\n\n return mappedItems;\n };\n\n /**\n * Filter the fields of an item\n * @param {Object | null} item\n * @param {String[]} fields Field names\n * @return {Object | null} filteredItem or null if no item is provided\n * @private\n */\n DataSet.prototype._filterFields = function (item, fields) {\n if (!item) {\n // item is null\n return item;\n }\n\n var filteredItem = {},\n itemFields = Object.keys(item),\n len = itemFields.length,\n i,\n field;\n\n if (Array.isArray(fields)) {\n for (i = 0; i < len; i++) {\n field = itemFields[i];\n if (fields.indexOf(field) != -1) {\n filteredItem[field] = item[field];\n }\n }\n } else {\n for (i = 0; i < len; i++) {\n field = itemFields[i];\n if (fields.hasOwnProperty(field)) {\n filteredItem[fields[field]] = item[field];\n }\n }\n }\n\n return filteredItem;\n };\n\n /**\n * Sort the provided array with items\n * @param {Object[]} items\n * @param {String | function} order A field name or custom sort function.\n * @private\n */\n DataSet.prototype._sort = function (items, order) {\n if (util.isString(order)) {\n // order by provided field name\n var name = order; // field name\n items.sort(function (a, b) {\n var av = a[name];\n var bv = b[name];\n return av > bv ? 1 : av < bv ? -1 : 0;\n });\n } else if (typeof order === 'function') {\n // order by sort function\n items.sort(order);\n }\n // TODO: extend order by an Object {field:String, direction:String}\n // where direction can be 'asc' or 'desc'\n else {\n throw new TypeError('Order must be a function or a string');\n }\n };\n\n /**\n * Remove an object by pointer or by id\n * @param {String | Number | Object | Array} id Object or id, or an array with\n * objects or ids to be removed\n * @param {String} [senderId] Optional sender id\n * @return {Array} removedIds\n */\n DataSet.prototype.remove = function (id, senderId) {\n var removedIds = [],\n i,\n len,\n removedId;\n\n if (Array.isArray(id)) {\n for (i = 0, len = id.length; i < len; i++) {\n removedId = this._remove(id[i]);\n if (removedId != null) {\n removedIds.push(removedId);\n }\n }\n } else {\n removedId = this._remove(id);\n if (removedId != null) {\n removedIds.push(removedId);\n }\n }\n\n if (removedIds.length) {\n this._trigger('remove', { items: removedIds }, senderId);\n }\n\n return removedIds;\n };\n\n /**\n * Remove an item by its id\n * @param {Number | String | Object} id id or item\n * @returns {Number | String | null} id\n * @private\n */\n DataSet.prototype._remove = function (id) {\n if (util.isNumber(id) || util.isString(id)) {\n if (this._data[id]) {\n delete this._data[id];\n this.length--;\n return id;\n }\n } else if (id instanceof Object) {\n var itemId = id[this._fieldId];\n if (itemId !== undefined && this._data[itemId]) {\n delete this._data[itemId];\n this.length--;\n return itemId;\n }\n }\n return null;\n };\n\n /**\n * Clear the data\n * @param {String} [senderId] Optional sender id\n * @return {Array} removedIds The ids of all removed items\n */\n DataSet.prototype.clear = function (senderId) {\n var ids = Object.keys(this._data);\n\n this._data = {};\n this.length = 0;\n\n this._trigger('remove', { items: ids }, senderId);\n\n return ids;\n };\n\n /**\n * Find the item with maximum value of a specified field\n * @param {String} field\n * @return {Object | null} item Item containing max value, or null if no items\n */\n DataSet.prototype.max = function (field) {\n var data = this._data,\n itemIds = Object.keys(data),\n max = null,\n maxField = null,\n i,\n len;\n\n for (i = 0, len = itemIds.length; i < len; i++) {\n var id = itemIds[i];\n var item = data[id];\n var itemField = item[field];\n if (itemField != null && (!max || itemField > maxField)) {\n max = item;\n maxField = itemField;\n }\n }\n\n return max;\n };\n\n /**\n * Find the item with minimum value of a specified field\n * @param {String} field\n * @return {Object | null} item Item containing max value, or null if no items\n */\n DataSet.prototype.min = function (field) {\n var data = this._data,\n itemIds = Object.keys(data),\n min = null,\n minField = null,\n i,\n len;\n\n for (i = 0, len = itemIds.length; i < len; i++) {\n var id = itemIds[i];\n var item = data[id];\n var itemField = item[field];\n if (itemField != null && (!min || itemField < minField)) {\n min = item;\n minField = itemField;\n }\n }\n\n return min;\n };\n\n /**\n * Find all distinct values of a specified field\n * @param {String} field\n * @return {Array} values Array containing all distinct values. If data items\n * do not contain the specified field are ignored.\n * The returned array is unordered.\n */\n DataSet.prototype.distinct = function (field) {\n var data = this._data;\n var itemIds = Object.keys(data);\n var values = [];\n var fieldType = this._options.type && this._options.type[field] || null;\n var count = 0;\n var i, j, len;\n\n for (i = 0, len = itemIds.length; i < len; i++) {\n var id = itemIds[i];\n var item = data[id];\n var value = item[field];\n var exists = false;\n for (j = 0; j < count; j++) {\n if (values[j] == value) {\n exists = true;\n break;\n }\n }\n if (!exists && value !== undefined) {\n values[count] = value;\n count++;\n }\n }\n\n if (fieldType) {\n for (i = 0, len = values.length; i < len; i++) {\n values[i] = util.convert(values[i], fieldType);\n }\n }\n\n return values;\n };\n\n /**\n * Add a single item. Will fail when an item with the same id already exists.\n * @param {Object} item\n * @return {String} id\n * @private\n */\n DataSet.prototype._addItem = function (item) {\n var id = item[this._fieldId];\n\n if (id != undefined) {\n // check whether this id is already taken\n if (this._data[id]) {\n // item already exists\n throw new Error('Cannot add item: item with id ' + id + ' already exists');\n }\n } else {\n // generate an id\n id = util.randomUUID();\n item[this._fieldId] = id;\n }\n\n var d = {},\n fields = Object.keys(item),\n i,\n len;\n for (i = 0, len = fields.length; i < len; i++) {\n var field = fields[i];\n var fieldType = this._type[field]; // type may be undefined\n d[field] = util.convert(item[field], fieldType);\n }\n this._data[id] = d;\n this.length++;\n\n return id;\n };\n\n /**\n * Get an item. Fields can be converted to a specific type\n * @param {String} id\n * @param {Object.<String, String>} [types] field types to convert\n * @return {Object | null} item\n * @private\n */\n DataSet.prototype._getItem = function (id, types) {\n var field, value, i, len;\n\n // get the item from the dataset\n var raw = this._data[id];\n if (!raw) {\n return null;\n }\n\n // convert the items field types\n var converted = {},\n fields = Object.keys(raw);\n\n if (types) {\n for (i = 0, len = fields.length; i < len; i++) {\n field = fields[i];\n value = raw[field];\n converted[field] = util.convert(value, types[field]);\n }\n } else {\n // no field types specified, no converting needed\n for (i = 0, len = fields.length; i < len; i++) {\n field = fields[i];\n value = raw[field];\n converted[field] = value;\n }\n }\n return converted;\n };\n\n /**\n * Update a single item: merge with existing item.\n * Will fail when the item has no id, or when there does not exist an item\n * with the same id.\n * @param {Object} item\n * @return {String} id\n * @private\n */\n DataSet.prototype._updateItem = function (item) {\n var id = item[this._fieldId];\n if (id == undefined) {\n throw new Error('Cannot update item: item has no id (item: ' + JSON.stringify(item) + ')');\n }\n var d = this._data[id];\n if (!d) {\n // item doesn't exist\n throw new Error('Cannot update item: no item with id ' + id + ' found');\n }\n\n // merge with current item\n var fields = Object.keys(item);\n for (var i = 0, len = fields.length; i < len; i++) {\n var field = fields[i];\n var fieldType = this._type[field]; // type may be undefined\n d[field] = util.convert(item[field], fieldType);\n }\n\n return id;\n };\n\n module.exports = DataSet;\n\n/***/ },\n/* 9 */\n/***/ function(module, exports) {\n\n /**\n * A queue\n * @param {Object} options\n * Available options:\n * - delay: number When provided, the queue will be flushed\n * automatically after an inactivity of this delay\n * in milliseconds.\n * Default value is null.\n * - max: number When the queue exceeds the given maximum number\n * of entries, the queue is flushed automatically.\n * Default value of max is Infinity.\n * @constructor\n */\n 'use strict';\n\n function Queue(options) {\n // options\n this.delay = null;\n this.max = Infinity;\n\n // properties\n this._queue = [];\n this._timeout = null;\n this._extended = null;\n\n this.setOptions(options);\n }\n\n /**\n * Update the configuration of the queue\n * @param {Object} options\n * Available options:\n * - delay: number When provided, the queue will be flushed\n * automatically after an inactivity of this delay\n * in milliseconds.\n * Default value is null.\n * - max: number When the queue exceeds the given maximum number\n * of entries, the queue is flushed automatically.\n * Default value of max is Infinity.\n * @param options\n */\n Queue.prototype.setOptions = function (options) {\n if (options && typeof options.delay !== 'undefined') {\n this.delay = options.delay;\n }\n if (options && typeof options.max !== 'undefined') {\n this.max = options.max;\n }\n\n this._flushIfNeeded();\n };\n\n /**\n * Extend an object with queuing functionality.\n * The object will be extended with a function flush, and the methods provided\n * in options.replace will be replaced with queued ones.\n * @param {Object} object\n * @param {Object} options\n * Available options:\n * - replace: Array.<string>\n * A list with method names of the methods\n * on the object to be replaced with queued ones.\n * - delay: number When provided, the queue will be flushed\n * automatically after an inactivity of this delay\n * in milliseconds.\n * Default value is null.\n * - max: number When the queue exceeds the given maximum number\n * of entries, the queue is flushed automatically.\n * Default value of max is Infinity.\n * @return {Queue} Returns the created queue\n */\n Queue.extend = function (object, options) {\n var queue = new Queue(options);\n\n if (object.flush !== undefined) {\n throw new Error('Target object already has a property flush');\n }\n object.flush = function () {\n queue.flush();\n };\n\n var methods = [{\n name: 'flush',\n original: undefined\n }];\n\n if (options && options.replace) {\n for (var i = 0; i < options.replace.length; i++) {\n var name = options.replace[i];\n methods.push({\n name: name,\n original: object[name]\n });\n queue.replace(object, name);\n }\n }\n\n queue._extended = {\n object: object,\n methods: methods\n };\n\n return queue;\n };\n\n /**\n * Destroy the queue. The queue will first flush all queued actions, and in\n * case it has extended an object, will restore the original object.\n */\n Queue.prototype.destroy = function () {\n this.flush();\n\n if (this._extended) {\n var object = this._extended.object;\n var methods = this._extended.methods;\n for (var i = 0; i < methods.length; i++) {\n var method = methods[i];\n if (method.original) {\n object[method.name] = method.original;\n } else {\n delete object[method.name];\n }\n }\n this._extended = null;\n }\n };\n\n /**\n * Replace a method on an object with a queued version\n * @param {Object} object Object having the method\n * @param {string} method The method name\n */\n Queue.prototype.replace = function (object, method) {\n var me = this;\n var original = object[method];\n if (!original) {\n throw new Error('Method ' + method + ' undefined');\n }\n\n object[method] = function () {\n // create an Array with the arguments\n var args = [];\n for (var i = 0; i < arguments.length; i++) {\n args[i] = arguments[i];\n }\n\n // add this call to the queue\n me.queue({\n args: args,\n fn: original,\n context: this\n });\n };\n };\n\n /**\n * Queue a call\n * @param {function | {fn: function, args: Array} | {fn: function, args: Array, context: Object}} entry\n */\n Queue.prototype.queue = function (entry) {\n if (typeof entry === 'function') {\n this._queue.push({ fn: entry });\n } else {\n this._queue.push(entry);\n }\n\n this._flushIfNeeded();\n };\n\n /**\n * Check whether the queue needs to be flushed\n * @private\n */\n Queue.prototype._flushIfNeeded = function () {\n // flush when the maximum is exceeded.\n if (this._queue.length > this.max) {\n this.flush();\n }\n\n // flush after a period of inactivity when a delay is configured\n clearTimeout(this._timeout);\n if (this.queue.length > 0 && typeof this.delay === 'number') {\n var me = this;\n this._timeout = setTimeout(function () {\n me.flush();\n }, this.delay);\n }\n };\n\n /**\n * Flush all queued calls\n */\n Queue.prototype.flush = function () {\n while (this._queue.length > 0) {\n var entry = this._queue.shift();\n entry.fn.apply(entry.context || entry.fn, entry.args || []);\n }\n };\n\n module.exports = Queue;\n\n/***/ },\n/* 10 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n\n /**\n * DataView\n *\n * a dataview offers a filtered view on a dataset or an other dataview.\n *\n * @param {DataSet | DataView} data\n * @param {Object} [options] Available options: see method get\n *\n * @constructor DataView\n */\n function DataView(data, options) {\n this._data = null;\n this._ids = {}; // ids of the items currently in memory (just contains a boolean true)\n this.length = 0; // number of items in the DataView\n this._options = options || {};\n this._fieldId = 'id'; // name of the field containing id\n this._subscribers = {}; // event subscribers\n\n var me = this;\n this.listener = function () {\n me._onEvent.apply(me, arguments);\n };\n\n this.setData(data);\n }\n\n // TODO: implement a function .config() to dynamically update things like configured filter\n // and trigger changes accordingly\n\n /**\n * Set a data source for the view\n * @param {DataSet | DataView} data\n */\n DataView.prototype.setData = function (data) {\n var ids, id, i, len;\n\n if (this._data) {\n // unsubscribe from current dataset\n if (this._data.off) {\n this._data.off('*', this.listener);\n }\n\n // trigger a remove of all items in memory\n ids = Object.keys(this._ids);\n this._ids = {};\n this.length = 0;\n this._trigger('remove', { items: ids });\n }\n\n this._data = data;\n\n if (this._data) {\n // update fieldId\n this._fieldId = this._options.fieldId || this._data && this._data.options && this._data.options.fieldId || 'id';\n\n // trigger an add of all added items\n ids = this._data.getIds({ filter: this._options && this._options.filter });\n for (i = 0, len = ids.length; i < len; i++) {\n id = ids[i];\n this._ids[id] = true;\n }\n this.length = ids.length;\n this._trigger('add', { items: ids });\n\n // subscribe to new dataset\n if (this._data.on) {\n this._data.on('*', this.listener);\n }\n }\n };\n\n /**\n * Refresh the DataView. Useful when the DataView has a filter function\n * containing a variable parameter.\n */\n DataView.prototype.refresh = function () {\n var id, i, len;\n var ids = this._data.getIds({ filter: this._options && this._options.filter });\n var oldIds = Object.keys(this._ids);\n var newIds = {};\n var added = [];\n var removed = [];\n\n // check for additions\n for (i = 0, len = ids.length; i < len; i++) {\n id = ids[i];\n newIds[id] = true;\n if (!this._ids[id]) {\n added.push(id);\n this._ids[id] = true;\n }\n }\n\n // check for removals\n for (i = 0, len = oldIds.length; i < len; i++) {\n id = oldIds[i];\n if (!newIds[id]) {\n removed.push(id);\n delete this._ids[id];\n }\n }\n\n this.length += added.length - removed.length;\n\n // trigger events\n if (added.length) {\n this._trigger('add', { items: added });\n }\n if (removed.length) {\n this._trigger('remove', { items: removed });\n }\n };\n\n /**\n * Get data from the data view\n *\n * Usage:\n *\n * get()\n * get(options: Object)\n * get(options: Object, data: Array | DataTable)\n *\n * get(id: Number)\n * get(id: Number, options: Object)\n * get(id: Number, options: Object, data: Array | DataTable)\n *\n * get(ids: Number[])\n * get(ids: Number[], options: Object)\n * get(ids: Number[], options: Object, data: Array | DataTable)\n *\n * Where:\n *\n * {Number | String} id The id of an item\n * {Number[] | String{}} ids An array with ids of items\n * {Object} options An Object with options. Available options:\n * {String} [type] Type of data to be returned. Can\n * be 'DataTable' or 'Array' (default)\n * {Object.<String, String>} [convert]\n * {String[]} [fields] field names to be returned\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n * {Array | DataTable} [data] If provided, items will be appended to this\n * array or table. Required in case of Google\n * DataTable.\n * @param args\n */\n DataView.prototype.get = function (args) {\n var me = this;\n\n // parse the arguments\n var ids, options, data;\n var firstType = util.getType(arguments[0]);\n if (firstType == 'String' || firstType == 'Number' || firstType == 'Array') {\n // get(id(s) [, options] [, data])\n ids = arguments[0]; // can be a single id or an array with ids\n options = arguments[1];\n data = arguments[2];\n } else {\n // get([, options] [, data])\n options = arguments[0];\n data = arguments[1];\n }\n\n // extend the options with the default options and provided options\n var viewOptions = util.extend({}, this._options, options);\n\n // create a combined filter method when needed\n if (this._options.filter && options && options.filter) {\n viewOptions.filter = function (item) {\n return me._options.filter(item) && options.filter(item);\n };\n }\n\n // build up the call to the linked data set\n var getArguments = [];\n if (ids != undefined) {\n getArguments.push(ids);\n }\n getArguments.push(viewOptions);\n getArguments.push(data);\n\n return this._data && this._data.get.apply(this._data, getArguments);\n };\n\n /**\n * Get ids of all items or from a filtered set of items.\n * @param {Object} [options] An Object with options. Available options:\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n * @return {Array} ids\n */\n DataView.prototype.getIds = function (options) {\n var ids;\n\n if (this._data) {\n var defaultFilter = this._options.filter;\n var filter;\n\n if (options && options.filter) {\n if (defaultFilter) {\n filter = function (item) {\n return defaultFilter(item) && options.filter(item);\n };\n } else {\n filter = options.filter;\n }\n } else {\n filter = defaultFilter;\n }\n\n ids = this._data.getIds({\n filter: filter,\n order: options && options.order\n });\n } else {\n ids = [];\n }\n\n return ids;\n };\n\n /**\n * Map every item in the dataset.\n * @param {function} callback\n * @param {Object} [options] Available options:\n * {Object.<String, String>} [type]\n * {String[]} [fields] filter fields\n * {function} [filter] filter items\n * {String | function} [order] Order the items by\n * a field name or custom sort function.\n * @return {Object[]} mappedItems\n */\n DataView.prototype.map = function (callback, options) {\n var mappedItems = [];\n if (this._data) {\n var defaultFilter = this._options.filter;\n var filter;\n\n if (options && options.filter) {\n if (defaultFilter) {\n filter = function (item) {\n return defaultFilter(item) && options.filter(item);\n };\n } else {\n filter = options.filter;\n }\n } else {\n filter = defaultFilter;\n }\n\n mappedItems = this._data.map(callback, {\n filter: filter,\n order: options && options.order\n });\n } else {\n mappedItems = [];\n }\n\n return mappedItems;\n };\n\n /**\n * Get the DataSet to which this DataView is connected. In case there is a chain\n * of multiple DataViews, the root DataSet of this chain is returned.\n * @return {DataSet} dataSet\n */\n DataView.prototype.getDataSet = function () {\n var dataSet = this;\n while (dataSet instanceof DataView) {\n dataSet = dataSet._data;\n }\n return dataSet || null;\n };\n\n /**\n * Event listener. Will propagate all events from the connected data set to\n * the subscribers of the DataView, but will filter the items and only trigger\n * when there are changes in the filtered data set.\n * @param {String} event\n * @param {Object | null} params\n * @param {String} senderId\n * @private\n */\n DataView.prototype._onEvent = function (event, params, senderId) {\n var i, len, id, item;\n var ids = params && params.items;\n var data = this._data;\n var updatedData = [];\n var added = [];\n var updated = [];\n var removed = [];\n\n if (ids && data) {\n switch (event) {\n case 'add':\n // filter the ids of the added items\n for (i = 0, len = ids.length; i < len; i++) {\n id = ids[i];\n item = this.get(id);\n if (item) {\n this._ids[id] = true;\n added.push(id);\n }\n }\n\n break;\n\n case 'update':\n // determine the event from the views viewpoint: an updated\n // item can be added, updated, or removed from this view.\n for (i = 0, len = ids.length; i < len; i++) {\n id = ids[i];\n item = this.get(id);\n\n if (item) {\n if (this._ids[id]) {\n updated.push(id);\n updatedData.push(params.data[i]);\n } else {\n this._ids[id] = true;\n added.push(id);\n }\n } else {\n if (this._ids[id]) {\n delete this._ids[id];\n removed.push(id);\n } else {\n // nothing interesting for me :-(\n }\n }\n }\n\n break;\n\n case 'remove':\n // filter the ids of the removed items\n for (i = 0, len = ids.length; i < len; i++) {\n id = ids[i];\n if (this._ids[id]) {\n delete this._ids[id];\n removed.push(id);\n }\n }\n\n break;\n }\n\n this.length += added.length - removed.length;\n\n if (added.length) {\n this._trigger('add', { items: added }, senderId);\n }\n if (updated.length) {\n this._trigger('update', { items: updated, data: updatedData }, senderId);\n }\n if (removed.length) {\n this._trigger('remove', { items: removed }, senderId);\n }\n }\n };\n\n // copy subscription functionality from DataSet\n DataView.prototype.on = DataSet.prototype.on;\n DataView.prototype.off = DataSet.prototype.off;\n DataView.prototype._trigger = DataSet.prototype._trigger;\n\n // TODO: make these functions deprecated (replaced with `on` and `off` since version 0.5)\n DataView.prototype.subscribe = DataView.prototype.on;\n DataView.prototype.unsubscribe = DataView.prototype.off;\n\n module.exports = DataView;\n\n/***/ },\n/* 11 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Emitter = __webpack_require__(12);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var util = __webpack_require__(1);\n var Point3d = __webpack_require__(13);\n var Point2d = __webpack_require__(14);\n var Camera = __webpack_require__(15);\n var Filter = __webpack_require__(16);\n var Slider = __webpack_require__(17);\n var StepNumber = __webpack_require__(18);\n\n /**\n * @constructor Graph3d\n * Graph3d displays data in 3d.\n *\n * Graph3d is developed in javascript as a Google Visualization Chart.\n *\n * @param {Element} container The DOM element in which the Graph3d will\n * be created. Normally a div element.\n * @param {DataSet | DataView | Array} [data]\n * @param {Object} [options]\n */\n function Graph3d(container, data, options) {\n if (!(this instanceof Graph3d)) {\n throw new SyntaxError('Constructor must be called with the new operator');\n }\n\n // create variables and set default values\n this.containerElement = container;\n this.width = '400px';\n this.height = '400px';\n this.margin = 10; // px\n this.defaultXCenter = '55%';\n this.defaultYCenter = '50%';\n\n this.xLabel = 'x';\n this.yLabel = 'y';\n this.zLabel = 'z';\n\n var passValueFn = function passValueFn(v) {\n return v;\n };\n this.xValueLabel = passValueFn;\n this.yValueLabel = passValueFn;\n this.zValueLabel = passValueFn;\n\n this.filterLabel = 'time';\n this.legendLabel = 'value';\n\n this.style = Graph3d.STYLE.DOT;\n this.showPerspective = true;\n this.showGrid = true;\n this.keepAspectRatio = true;\n this.showShadow = false;\n this.showGrayBottom = false; // TODO: this does not work correctly\n this.showTooltip = false;\n this.verticalRatio = 0.5; // 0.1 to 1.0, where 1.0 results in a 'cube'\n\n this.animationInterval = 1000; // milliseconds\n this.animationPreload = false;\n\n this.camera = new Camera();\n this.camera.setArmRotation(1.0, 0.5);\n this.camera.setArmLength(1.7);\n this.eye = new Point3d(0, 0, -1); // TODO: set eye.z about 3/4 of the width of the window?\n\n this.dataTable = null; // The original data table\n this.dataPoints = null; // The table with point objects\n\n // the column indexes\n this.colX = undefined;\n this.colY = undefined;\n this.colZ = undefined;\n this.colValue = undefined;\n this.colFilter = undefined;\n\n this.xMin = 0;\n this.xStep = undefined; // auto by default\n this.xMax = 1;\n this.yMin = 0;\n this.yStep = undefined; // auto by default\n this.yMax = 1;\n this.zMin = 0;\n this.zStep = undefined; // auto by default\n this.zMax = 1;\n this.valueMin = 0;\n this.valueMax = 1;\n this.xBarWidth = 1;\n this.yBarWidth = 1;\n // TODO: customize axis range\n\n // colors\n this.axisColor = '#4D4D4D';\n this.gridColor = '#D3D3D3';\n this.dataColor = {\n fill: '#7DC1FF',\n stroke: '#3267D2',\n strokeWidth: 1 // px\n };\n\n this.dotSizeRatio = 0.02; // size of the dots as a fraction of the graph width\n\n // create a frame and canvas\n this.create();\n\n // apply options (also when undefined)\n this.setOptions(options);\n\n // apply data\n if (data) {\n this.setData(data);\n }\n }\n\n // Extend Graph3d with an Emitter mixin\n Emitter(Graph3d.prototype);\n\n /**\n * Calculate the scaling values, dependent on the range in x, y, and z direction\n */\n Graph3d.prototype._setScale = function () {\n this.scale = new Point3d(1 / (this.xMax - this.xMin), 1 / (this.yMax - this.yMin), 1 / (this.zMax - this.zMin));\n\n // keep aspect ration between x and y scale if desired\n if (this.keepAspectRatio) {\n if (this.scale.x < this.scale.y) {\n //noinspection JSSuspiciousNameCombination\n this.scale.y = this.scale.x;\n } else {\n //noinspection JSSuspiciousNameCombination\n this.scale.x = this.scale.y;\n }\n }\n\n // scale the vertical axis\n this.scale.z *= this.verticalRatio;\n // TODO: can this be automated? verticalRatio?\n\n // determine scale for (optional) value\n this.scale.value = 1 / (this.valueMax - this.valueMin);\n\n // position the camera arm\n var xCenter = (this.xMax + this.xMin) / 2 * this.scale.x;\n var yCenter = (this.yMax + this.yMin) / 2 * this.scale.y;\n var zCenter = (this.zMax + this.zMin) / 2 * this.scale.z;\n this.camera.setArmLocation(xCenter, yCenter, zCenter);\n };\n\n /**\n * Convert a 3D location to a 2D location on screen\n * http://en.wikipedia.org/wiki/3D_projection\n * @param {Point3d} point3d A 3D point with parameters x, y, z\n * @return {Point2d} point2d A 2D point with parameters x, y\n */\n Graph3d.prototype._convert3Dto2D = function (point3d) {\n var translation = this._convertPointToTranslation(point3d);\n return this._convertTranslationToScreen(translation);\n };\n\n /**\n * Convert a 3D location its translation seen from the camera\n * http://en.wikipedia.org/wiki/3D_projection\n * @param {Point3d} point3d A 3D point with parameters x, y, z\n * @return {Point3d} translation A 3D point with parameters x, y, z This is\n * the translation of the point, seen from the\n * camera\n */\n Graph3d.prototype._convertPointToTranslation = function (point3d) {\n var ax = point3d.x * this.scale.x,\n ay = point3d.y * this.scale.y,\n az = point3d.z * this.scale.z,\n cx = this.camera.getCameraLocation().x,\n cy = this.camera.getCameraLocation().y,\n cz = this.camera.getCameraLocation().z,\n\n // calculate angles\n sinTx = Math.sin(this.camera.getCameraRotation().x),\n cosTx = Math.cos(this.camera.getCameraRotation().x),\n sinTy = Math.sin(this.camera.getCameraRotation().y),\n cosTy = Math.cos(this.camera.getCameraRotation().y),\n sinTz = Math.sin(this.camera.getCameraRotation().z),\n cosTz = Math.cos(this.camera.getCameraRotation().z),\n\n // calculate translation\n dx = cosTy * (sinTz * (ay - cy) + cosTz * (ax - cx)) - sinTy * (az - cz),\n dy = sinTx * (cosTy * (az - cz) + sinTy * (sinTz * (ay - cy) + cosTz * (ax - cx))) + cosTx * (cosTz * (ay - cy) - sinTz * (ax - cx)),\n dz = cosTx * (cosTy * (az - cz) + sinTy * (sinTz * (ay - cy) + cosTz * (ax - cx))) - sinTx * (cosTz * (ay - cy) - sinTz * (ax - cx));\n\n return new Point3d(dx, dy, dz);\n };\n\n /**\n * Convert a translation point to a point on the screen\n * @param {Point3d} translation A 3D point with parameters x, y, z This is\n * the translation of the point, seen from the\n * camera\n * @return {Point2d} point2d A 2D point with parameters x, y\n */\n Graph3d.prototype._convertTranslationToScreen = function (translation) {\n var ex = this.eye.x,\n ey = this.eye.y,\n ez = this.eye.z,\n dx = translation.x,\n dy = translation.y,\n dz = translation.z;\n\n // calculate position on screen from translation\n var bx;\n var by;\n if (this.showPerspective) {\n bx = (dx - ex) * (ez / dz);\n by = (dy - ey) * (ez / dz);\n } else {\n bx = dx * -(ez / this.camera.getArmLength());\n by = dy * -(ez / this.camera.getArmLength());\n }\n\n // shift and scale the point to the center of the screen\n // use the width of the graph to scale both horizontally and vertically.\n return new Point2d(this.xcenter + bx * this.frame.canvas.clientWidth, this.ycenter - by * this.frame.canvas.clientWidth);\n };\n\n /**\n * Set the background styling for the graph\n * @param {string | {fill: string, stroke: string, strokeWidth: string}} backgroundColor\n */\n Graph3d.prototype._setBackgroundColor = function (backgroundColor) {\n var fill = 'white';\n var stroke = 'gray';\n var strokeWidth = 1;\n\n if (typeof backgroundColor === 'string') {\n fill = backgroundColor;\n stroke = 'none';\n strokeWidth = 0;\n } else if (typeof backgroundColor === 'object') {\n if (backgroundColor.fill !== undefined) fill = backgroundColor.fill;\n if (backgroundColor.stroke !== undefined) stroke = backgroundColor.stroke;\n if (backgroundColor.strokeWidth !== undefined) strokeWidth = backgroundColor.strokeWidth;\n } else if (backgroundColor === undefined) {\n // use use defaults\n } else {\n throw 'Unsupported type of backgroundColor';\n }\n\n this.frame.style.backgroundColor = fill;\n this.frame.style.borderColor = stroke;\n this.frame.style.borderWidth = strokeWidth + 'px';\n this.frame.style.borderStyle = 'solid';\n };\n\n /// enumerate the available styles\n Graph3d.STYLE = {\n BAR: 0,\n BARCOLOR: 1,\n BARSIZE: 2,\n DOT: 3,\n DOTLINE: 4,\n DOTCOLOR: 5,\n DOTSIZE: 6,\n GRID: 7,\n LINE: 8,\n SURFACE: 9\n };\n\n /**\n * Retrieve the style index from given styleName\n * @param {string} styleName Style name such as 'dot', 'grid', 'dot-line'\n * @return {Number} styleNumber Enumeration value representing the style, or -1\n * when not found\n */\n Graph3d.prototype._getStyleNumber = function (styleName) {\n switch (styleName) {\n case 'dot':\n return Graph3d.STYLE.DOT;\n case 'dot-line':\n return Graph3d.STYLE.DOTLINE;\n case 'dot-color':\n return Graph3d.STYLE.DOTCOLOR;\n case 'dot-size':\n return Graph3d.STYLE.DOTSIZE;\n case 'line':\n return Graph3d.STYLE.LINE;\n case 'grid':\n return Graph3d.STYLE.GRID;\n case 'surface':\n return Graph3d.STYLE.SURFACE;\n case 'bar':\n return Graph3d.STYLE.BAR;\n case 'bar-color':\n return Graph3d.STYLE.BARCOLOR;\n case 'bar-size':\n return Graph3d.STYLE.BARSIZE;\n }\n\n return -1;\n };\n\n /**\n * Determine the indexes of the data columns, based on the given style and data\n * @param {DataSet} data\n * @param {Number} style\n */\n Graph3d.prototype._determineColumnIndexes = function (data, style) {\n if (this.style === Graph3d.STYLE.DOT || this.style === Graph3d.STYLE.DOTLINE || this.style === Graph3d.STYLE.LINE || this.style === Graph3d.STYLE.GRID || this.style === Graph3d.STYLE.SURFACE || this.style === Graph3d.STYLE.BAR) {\n // 3 columns expected, and optionally a 4th with filter values\n this.colX = 0;\n this.colY = 1;\n this.colZ = 2;\n this.colValue = undefined;\n\n if (data.getNumberOfColumns() > 3) {\n this.colFilter = 3;\n }\n } else if (this.style === Graph3d.STYLE.DOTCOLOR || this.style === Graph3d.STYLE.DOTSIZE || this.style === Graph3d.STYLE.BARCOLOR || this.style === Graph3d.STYLE.BARSIZE) {\n // 4 columns expected, and optionally a 5th with filter values\n this.colX = 0;\n this.colY = 1;\n this.colZ = 2;\n this.colValue = 3;\n\n if (data.getNumberOfColumns() > 4) {\n this.colFilter = 4;\n }\n } else {\n throw 'Unknown style \"' + this.style + '\"';\n }\n };\n\n Graph3d.prototype.getNumberOfRows = function (data) {\n return data.length;\n };\n\n Graph3d.prototype.getNumberOfColumns = function (data) {\n var counter = 0;\n for (var column in data[0]) {\n if (data[0].hasOwnProperty(column)) {\n counter++;\n }\n }\n return counter;\n };\n\n Graph3d.prototype.getDistinctValues = function (data, column) {\n var distinctValues = [];\n for (var i = 0; i < data.length; i++) {\n if (distinctValues.indexOf(data[i][column]) == -1) {\n distinctValues.push(data[i][column]);\n }\n }\n return distinctValues;\n };\n\n Graph3d.prototype.getColumnRange = function (data, column) {\n var minMax = { min: data[0][column], max: data[0][column] };\n for (var i = 0; i < data.length; i++) {\n if (minMax.min > data[i][column]) {\n minMax.min = data[i][column];\n }\n if (minMax.max < data[i][column]) {\n minMax.max = data[i][column];\n }\n }\n return minMax;\n };\n\n /**\n * Initialize the data from the data table. Calculate minimum and maximum values\n * and column index values\n * @param {Array | DataSet | DataView} rawData The data containing the items for the Graph.\n * @param {Number} style Style Number\n */\n Graph3d.prototype._dataInitialize = function (rawData, style) {\n var me = this;\n\n // unsubscribe from the dataTable\n if (this.dataSet) {\n this.dataSet.off('*', this._onChange);\n }\n\n if (rawData === undefined) return;\n\n if (Array.isArray(rawData)) {\n rawData = new DataSet(rawData);\n }\n\n var data;\n if (rawData instanceof DataSet || rawData instanceof DataView) {\n data = rawData.get();\n } else {\n throw new Error('Array, DataSet, or DataView expected');\n }\n\n if (data.length == 0) return;\n\n this.dataSet = rawData;\n this.dataTable = data;\n\n // subscribe to changes in the dataset\n this._onChange = function () {\n me.setData(me.dataSet);\n };\n this.dataSet.on('*', this._onChange);\n\n // _determineColumnIndexes\n // getNumberOfRows (points)\n // getNumberOfColumns (x,y,z,v,t,t1,t2...)\n // getDistinctValues (unique values?)\n // getColumnRange\n\n // determine the location of x,y,z,value,filter columns\n this.colX = 'x';\n this.colY = 'y';\n this.colZ = 'z';\n this.colValue = 'style';\n this.colFilter = 'filter';\n\n // check if a filter column is provided\n if (data[0].hasOwnProperty('filter')) {\n if (this.dataFilter === undefined) {\n this.dataFilter = new Filter(rawData, this.colFilter, this);\n this.dataFilter.setOnLoadCallback(function () {\n me.redraw();\n });\n }\n }\n\n var withBars = this.style == Graph3d.STYLE.BAR || this.style == Graph3d.STYLE.BARCOLOR || this.style == Graph3d.STYLE.BARSIZE;\n\n // determine barWidth from data\n if (withBars) {\n if (this.defaultXBarWidth !== undefined) {\n this.xBarWidth = this.defaultXBarWidth;\n } else {\n var dataX = this.getDistinctValues(data, this.colX);\n this.xBarWidth = dataX[1] - dataX[0] || 1;\n }\n\n if (this.defaultYBarWidth !== undefined) {\n this.yBarWidth = this.defaultYBarWidth;\n } else {\n var dataY = this.getDistinctValues(data, this.colY);\n this.yBarWidth = dataY[1] - dataY[0] || 1;\n }\n }\n\n // calculate minimums and maximums\n var xRange = this.getColumnRange(data, this.colX);\n if (withBars) {\n xRange.min -= this.xBarWidth / 2;\n xRange.max += this.xBarWidth / 2;\n }\n this.xMin = this.defaultXMin !== undefined ? this.defaultXMin : xRange.min;\n this.xMax = this.defaultXMax !== undefined ? this.defaultXMax : xRange.max;\n if (this.xMax <= this.xMin) this.xMax = this.xMin + 1;\n this.xStep = this.defaultXStep !== undefined ? this.defaultXStep : (this.xMax - this.xMin) / 5;\n\n var yRange = this.getColumnRange(data, this.colY);\n if (withBars) {\n yRange.min -= this.yBarWidth / 2;\n yRange.max += this.yBarWidth / 2;\n }\n this.yMin = this.defaultYMin !== undefined ? this.defaultYMin : yRange.min;\n this.yMax = this.defaultYMax !== undefined ? this.defaultYMax : yRange.max;\n if (this.yMax <= this.yMin) this.yMax = this.yMin + 1;\n this.yStep = this.defaultYStep !== undefined ? this.defaultYStep : (this.yMax - this.yMin) / 5;\n\n var zRange = this.getColumnRange(data, this.colZ);\n this.zMin = this.defaultZMin !== undefined ? this.defaultZMin : zRange.min;\n this.zMax = this.defaultZMax !== undefined ? this.defaultZMax : zRange.max;\n if (this.zMax <= this.zMin) this.zMax = this.zMin + 1;\n this.zStep = this.defaultZStep !== undefined ? this.defaultZStep : (this.zMax - this.zMin) / 5;\n\n if (this.colValue !== undefined) {\n var valueRange = this.getColumnRange(data, this.colValue);\n this.valueMin = this.defaultValueMin !== undefined ? this.defaultValueMin : valueRange.min;\n this.valueMax = this.defaultValueMax !== undefined ? this.defaultValueMax : valueRange.max;\n if (this.valueMax <= this.valueMin) this.valueMax = this.valueMin + 1;\n }\n\n // set the scale dependent on the ranges.\n this._setScale();\n };\n\n /**\n * Filter the data based on the current filter\n * @param {Array} data\n * @return {Array} dataPoints Array with point objects which can be drawn on screen\n */\n Graph3d.prototype._getDataPoints = function (data) {\n // TODO: store the created matrix dataPoints in the filters instead of reloading each time\n var x, y, i, z, obj, point;\n\n var dataPoints = [];\n\n if (this.style === Graph3d.STYLE.GRID || this.style === Graph3d.STYLE.SURFACE) {\n // copy all values from the google data table to a matrix\n // the provided values are supposed to form a grid of (x,y) positions\n\n // create two lists with all present x and y values\n var dataX = [];\n var dataY = [];\n for (i = 0; i < this.getNumberOfRows(data); i++) {\n x = data[i][this.colX] || 0;\n y = data[i][this.colY] || 0;\n\n if (dataX.indexOf(x) === -1) {\n dataX.push(x);\n }\n if (dataY.indexOf(y) === -1) {\n dataY.push(y);\n }\n }\n\n var sortNumber = function sortNumber(a, b) {\n return a - b;\n };\n dataX.sort(sortNumber);\n dataY.sort(sortNumber);\n\n // create a grid, a 2d matrix, with all values.\n var dataMatrix = []; // temporary data matrix\n for (i = 0; i < data.length; i++) {\n x = data[i][this.colX] || 0;\n y = data[i][this.colY] || 0;\n z = data[i][this.colZ] || 0;\n\n var xIndex = dataX.indexOf(x); // TODO: implement Array().indexOf() for Internet Explorer\n var yIndex = dataY.indexOf(y);\n\n if (dataMatrix[xIndex] === undefined) {\n dataMatrix[xIndex] = [];\n }\n\n var point3d = new Point3d();\n point3d.x = x;\n point3d.y = y;\n point3d.z = z;\n\n obj = {};\n obj.point = point3d;\n obj.trans = undefined;\n obj.screen = undefined;\n obj.bottom = new Point3d(x, y, this.zMin);\n\n dataMatrix[xIndex][yIndex] = obj;\n\n dataPoints.push(obj);\n }\n\n // fill in the pointers to the neighbors.\n for (x = 0; x < dataMatrix.length; x++) {\n for (y = 0; y < dataMatrix[x].length; y++) {\n if (dataMatrix[x][y]) {\n dataMatrix[x][y].pointRight = x < dataMatrix.length - 1 ? dataMatrix[x + 1][y] : undefined;\n dataMatrix[x][y].pointTop = y < dataMatrix[x].length - 1 ? dataMatrix[x][y + 1] : undefined;\n dataMatrix[x][y].pointCross = x < dataMatrix.length - 1 && y < dataMatrix[x].length - 1 ? dataMatrix[x + 1][y + 1] : undefined;\n }\n }\n }\n } else {\n // 'dot', 'dot-line', etc.\n // copy all values from the google data table to a list with Point3d objects\n for (i = 0; i < data.length; i++) {\n point = new Point3d();\n point.x = data[i][this.colX] || 0;\n point.y = data[i][this.colY] || 0;\n point.z = data[i][this.colZ] || 0;\n\n if (this.colValue !== undefined) {\n point.value = data[i][this.colValue] || 0;\n }\n\n obj = {};\n obj.point = point;\n obj.bottom = new Point3d(point.x, point.y, this.zMin);\n obj.trans = undefined;\n obj.screen = undefined;\n\n dataPoints.push(obj);\n }\n }\n\n return dataPoints;\n };\n\n /**\n * Create the main frame for the Graph3d.\n * This function is executed once when a Graph3d object is created. The frame\n * contains a canvas, and this canvas contains all objects like the axis and\n * nodes.\n */\n Graph3d.prototype.create = function () {\n // remove all elements from the container element.\n while (this.containerElement.hasChildNodes()) {\n this.containerElement.removeChild(this.containerElement.firstChild);\n }\n\n this.frame = document.createElement('div');\n this.frame.style.position = 'relative';\n this.frame.style.overflow = 'hidden';\n\n // create the graph canvas (HTML canvas element)\n this.frame.canvas = document.createElement('canvas');\n this.frame.canvas.style.position = 'relative';\n this.frame.appendChild(this.frame.canvas);\n //if (!this.frame.canvas.getContext) {\n {\n var noCanvas = document.createElement('DIV');\n noCanvas.style.color = 'red';\n noCanvas.style.fontWeight = 'bold';\n noCanvas.style.padding = '10px';\n noCanvas.innerHTML = 'Error: your browser does not support HTML canvas';\n this.frame.canvas.appendChild(noCanvas);\n }\n\n this.frame.filter = document.createElement('div');\n this.frame.filter.style.position = 'absolute';\n this.frame.filter.style.bottom = '0px';\n this.frame.filter.style.left = '0px';\n this.frame.filter.style.width = '100%';\n this.frame.appendChild(this.frame.filter);\n\n // add event listeners to handle moving and zooming the contents\n var me = this;\n var onmousedown = function onmousedown(event) {\n me._onMouseDown(event);\n };\n var ontouchstart = function ontouchstart(event) {\n me._onTouchStart(event);\n };\n var onmousewheel = function onmousewheel(event) {\n me._onWheel(event);\n };\n var ontooltip = function ontooltip(event) {\n me._onTooltip(event);\n };\n // TODO: these events are never cleaned up... can give a 'memory leakage'\n\n util.addEventListener(this.frame.canvas, 'keydown', onkeydown);\n util.addEventListener(this.frame.canvas, 'mousedown', onmousedown);\n util.addEventListener(this.frame.canvas, 'touchstart', ontouchstart);\n util.addEventListener(this.frame.canvas, 'mousewheel', onmousewheel);\n util.addEventListener(this.frame.canvas, 'mousemove', ontooltip);\n\n // add the new graph to the container element\n this.containerElement.appendChild(this.frame);\n };\n\n /**\n * Set a new size for the graph\n * @param {string} width Width in pixels or percentage (for example '800px'\n * or '50%')\n * @param {string} height Height in pixels or percentage (for example '400px'\n * or '30%')\n */\n Graph3d.prototype.setSize = function (width, height) {\n this.frame.style.width = width;\n this.frame.style.height = height;\n\n this._resizeCanvas();\n };\n\n /**\n * Resize the canvas to the current size of the frame\n */\n Graph3d.prototype._resizeCanvas = function () {\n this.frame.canvas.style.width = '100%';\n this.frame.canvas.style.height = '100%';\n\n this.frame.canvas.width = this.frame.canvas.clientWidth;\n this.frame.canvas.height = this.frame.canvas.clientHeight;\n\n // adjust with for margin\n this.frame.filter.style.width = this.frame.canvas.clientWidth - 2 * 10 + 'px';\n };\n\n /**\n * Start animation\n */\n Graph3d.prototype.animationStart = function () {\n if (!this.frame.filter || !this.frame.filter.slider) throw 'No animation available';\n\n this.frame.filter.slider.play();\n };\n\n /**\n * Stop animation\n */\n Graph3d.prototype.animationStop = function () {\n if (!this.frame.filter || !this.frame.filter.slider) return;\n\n this.frame.filter.slider.stop();\n };\n\n /**\n * Resize the center position based on the current values in this.defaultXCenter\n * and this.defaultYCenter (which are strings with a percentage or a value\n * in pixels). The center positions are the variables this.xCenter\n * and this.yCenter\n */\n Graph3d.prototype._resizeCenter = function () {\n // calculate the horizontal center position\n if (this.defaultXCenter.charAt(this.defaultXCenter.length - 1) === '%') {\n this.xcenter = parseFloat(this.defaultXCenter) / 100 * this.frame.canvas.clientWidth;\n } else {\n this.xcenter = parseFloat(this.defaultXCenter); // supposed to be in px\n }\n\n // calculate the vertical center position\n if (this.defaultYCenter.charAt(this.defaultYCenter.length - 1) === '%') {\n this.ycenter = parseFloat(this.defaultYCenter) / 100 * (this.frame.canvas.clientHeight - this.frame.filter.clientHeight);\n } else {\n this.ycenter = parseFloat(this.defaultYCenter); // supposed to be in px\n }\n };\n\n /**\n * Set the rotation and distance of the camera\n * @param {Object} pos An object with the camera position. The object\n * contains three parameters:\n * - horizontal {Number}\n * The horizontal rotation, between 0 and 2*PI.\n * Optional, can be left undefined.\n * - vertical {Number}\n * The vertical rotation, between 0 and 0.5*PI\n * if vertical=0.5*PI, the graph is shown from the\n * top. Optional, can be left undefined.\n * - distance {Number}\n * The (normalized) distance of the camera to the\n * center of the graph, a value between 0.71 and 5.0.\n * Optional, can be left undefined.\n */\n Graph3d.prototype.setCameraPosition = function (pos) {\n if (pos === undefined) {\n return;\n }\n\n if (pos.horizontal !== undefined && pos.vertical !== undefined) {\n this.camera.setArmRotation(pos.horizontal, pos.vertical);\n }\n\n if (pos.distance !== undefined) {\n this.camera.setArmLength(pos.distance);\n }\n\n this.redraw();\n };\n\n /**\n * Retrieve the current camera rotation\n * @return {object} An object with parameters horizontal, vertical, and\n * distance\n */\n Graph3d.prototype.getCameraPosition = function () {\n var pos = this.camera.getArmRotation();\n pos.distance = this.camera.getArmLength();\n return pos;\n };\n\n /**\n * Load data into the 3D Graph\n */\n Graph3d.prototype._readData = function (data) {\n // read the data\n this._dataInitialize(data, this.style);\n\n if (this.dataFilter) {\n // apply filtering\n this.dataPoints = this.dataFilter._getDataPoints();\n } else {\n // no filtering. load all data\n this.dataPoints = this._getDataPoints(this.dataTable);\n }\n\n // draw the filter\n this._redrawFilter();\n };\n\n /**\n * Replace the dataset of the Graph3d\n * @param {Array | DataSet | DataView} data\n */\n Graph3d.prototype.setData = function (data) {\n this._readData(data);\n this.redraw();\n\n // start animation when option is true\n if (this.animationAutoStart && this.dataFilter) {\n this.animationStart();\n }\n };\n\n /**\n * Update the options. Options will be merged with current options\n * @param {Object} options\n */\n Graph3d.prototype.setOptions = function (options) {\n var cameraPosition = undefined;\n\n this.animationStop();\n\n if (options !== undefined) {\n // retrieve parameter values\n if (options.width !== undefined) this.width = options.width;\n if (options.height !== undefined) this.height = options.height;\n\n if (options.xCenter !== undefined) this.defaultXCenter = options.xCenter;\n if (options.yCenter !== undefined) this.defaultYCenter = options.yCenter;\n\n if (options.filterLabel !== undefined) this.filterLabel = options.filterLabel;\n if (options.legendLabel !== undefined) this.legendLabel = options.legendLabel;\n if (options.xLabel !== undefined) this.xLabel = options.xLabel;\n if (options.yLabel !== undefined) this.yLabel = options.yLabel;\n if (options.zLabel !== undefined) this.zLabel = options.zLabel;\n\n if (options.xValueLabel !== undefined) this.xValueLabel = options.xValueLabel;\n if (options.yValueLabel !== undefined) this.yValueLabel = options.yValueLabel;\n if (options.zValueLabel !== undefined) this.zValueLabel = options.zValueLabel;\n\n if (options.dotSizeRatio !== undefined) this.dotSizeRatio = options.dotSizeRatio;\n\n if (options.style !== undefined) {\n var styleNumber = this._getStyleNumber(options.style);\n if (styleNumber !== -1) {\n this.style = styleNumber;\n }\n }\n if (options.showGrid !== undefined) this.showGrid = options.showGrid;\n if (options.showPerspective !== undefined) this.showPerspective = options.showPerspective;\n if (options.showShadow !== undefined) this.showShadow = options.showShadow;\n if (options.tooltip !== undefined) this.showTooltip = options.tooltip;\n if (options.showAnimationControls !== undefined) this.showAnimationControls = options.showAnimationControls;\n if (options.keepAspectRatio !== undefined) this.keepAspectRatio = options.keepAspectRatio;\n if (options.verticalRatio !== undefined) this.verticalRatio = options.verticalRatio;\n\n if (options.animationInterval !== undefined) this.animationInterval = options.animationInterval;\n if (options.animationPreload !== undefined) this.animationPreload = options.animationPreload;\n if (options.animationAutoStart !== undefined) this.animationAutoStart = options.animationAutoStart;\n\n if (options.xBarWidth !== undefined) this.defaultXBarWidth = options.xBarWidth;\n if (options.yBarWidth !== undefined) this.defaultYBarWidth = options.yBarWidth;\n\n if (options.xMin !== undefined) this.defaultXMin = options.xMin;\n if (options.xStep !== undefined) this.defaultXStep = options.xStep;\n if (options.xMax !== undefined) this.defaultXMax = options.xMax;\n if (options.yMin !== undefined) this.defaultYMin = options.yMin;\n if (options.yStep !== undefined) this.defaultYStep = options.yStep;\n if (options.yMax !== undefined) this.defaultYMax = options.yMax;\n if (options.zMin !== undefined) this.defaultZMin = options.zMin;\n if (options.zStep !== undefined) this.defaultZStep = options.zStep;\n if (options.zMax !== undefined) this.defaultZMax = options.zMax;\n if (options.valueMin !== undefined) this.defaultValueMin = options.valueMin;\n if (options.valueMax !== undefined) this.defaultValueMax = options.valueMax;\n if (options.backgroundColor !== undefined) this._setBackgroundColor(options.backgroundColor);\n\n if (options.cameraPosition !== undefined) cameraPosition = options.cameraPosition;\n\n if (cameraPosition !== undefined) {\n this.camera.setArmRotation(cameraPosition.horizontal, cameraPosition.vertical);\n this.camera.setArmLength(cameraPosition.distance);\n }\n\n // colors\n if (options.axisColor !== undefined) this.axisColor = options.axisColor;\n if (options.gridColor !== undefined) this.gridColor = options.gridColor;\n if (options.dataColor) {\n if (typeof options.dataColor === 'string') {\n this.dataColor.fill = options.dataColor;\n this.dataColor.stroke = options.dataColor;\n } else {\n if (options.dataColor.fill) {\n this.dataColor.fill = options.dataColor.fill;\n }\n if (options.dataColor.stroke) {\n this.dataColor.stroke = options.dataColor.stroke;\n }\n if (options.dataColor.strokeWidth !== undefined) {\n this.dataColor.strokeWidth = options.dataColor.strokeWidth;\n }\n }\n }\n }\n\n this.setSize(this.width, this.height);\n\n // re-load the data\n if (this.dataTable) {\n this.setData(this.dataTable);\n }\n\n // start animation when option is true\n if (this.animationAutoStart && this.dataFilter) {\n this.animationStart();\n }\n };\n\n /**\n * Redraw the Graph.\n */\n Graph3d.prototype.redraw = function () {\n if (this.dataPoints === undefined) {\n throw 'Error: graph data not initialized';\n }\n\n this._resizeCanvas();\n this._resizeCenter();\n this._redrawSlider();\n this._redrawClear();\n this._redrawAxis();\n\n if (this.style === Graph3d.STYLE.GRID || this.style === Graph3d.STYLE.SURFACE) {\n this._redrawDataGrid();\n } else if (this.style === Graph3d.STYLE.LINE) {\n this._redrawDataLine();\n } else if (this.style === Graph3d.STYLE.BAR || this.style === Graph3d.STYLE.BARCOLOR || this.style === Graph3d.STYLE.BARSIZE) {\n this._redrawDataBar();\n } else {\n // style is DOT, DOTLINE, DOTCOLOR, DOTSIZE\n this._redrawDataDot();\n }\n\n this._redrawInfo();\n this._redrawLegend();\n };\n\n /**\n * Clear the canvas before redrawing\n */\n Graph3d.prototype._redrawClear = function () {\n var canvas = this.frame.canvas;\n var ctx = canvas.getContext('2d');\n\n ctx.clearRect(0, 0, canvas.width, canvas.height);\n };\n\n /**\n * Redraw the legend showing the colors\n */\n Graph3d.prototype._redrawLegend = function () {\n var y;\n\n if (this.style === Graph3d.STYLE.DOTCOLOR || this.style === Graph3d.STYLE.DOTSIZE) {\n\n var dotSize = this.frame.clientWidth * this.dotSizeRatio;\n\n var widthMin, widthMax;\n if (this.style === Graph3d.STYLE.DOTSIZE) {\n widthMin = dotSize / 2; // px\n widthMax = dotSize / 2 + dotSize * 2; // Todo: put this in one function\n } else {\n widthMin = 20; // px\n widthMax = 20; // px\n }\n\n var height = Math.max(this.frame.clientHeight * 0.25, 100);\n var top = this.margin;\n var right = this.frame.clientWidth - this.margin;\n var left = right - widthMax;\n var bottom = top + height;\n }\n\n var canvas = this.frame.canvas;\n var ctx = canvas.getContext('2d');\n ctx.lineWidth = 1;\n ctx.font = '14px arial'; // TODO: put in options\n\n if (this.style === Graph3d.STYLE.DOTCOLOR) {\n // draw the color bar\n var ymin = 0;\n var ymax = height; // Todo: make height customizable\n for (y = ymin; y < ymax; y++) {\n var f = (y - ymin) / (ymax - ymin);\n\n //var width = (dotSize / 2 + (1-f) * dotSize * 2); // Todo: put this in one function\n var hue = f * 240;\n var color = this._hsv2rgb(hue, 1, 1);\n\n ctx.strokeStyle = color;\n ctx.beginPath();\n ctx.moveTo(left, top + y);\n ctx.lineTo(right, top + y);\n ctx.stroke();\n }\n\n ctx.strokeStyle = this.axisColor;\n ctx.strokeRect(left, top, widthMax, height);\n }\n\n if (this.style === Graph3d.STYLE.DOTSIZE) {\n // draw border around color bar\n ctx.strokeStyle = this.axisColor;\n ctx.fillStyle = this.dataColor.fill;\n ctx.beginPath();\n ctx.moveTo(left, top);\n ctx.lineTo(right, top);\n ctx.lineTo(right - widthMax + widthMin, bottom);\n ctx.lineTo(left, bottom);\n ctx.closePath();\n ctx.fill();\n ctx.stroke();\n }\n\n if (this.style === Graph3d.STYLE.DOTCOLOR || this.style === Graph3d.STYLE.DOTSIZE) {\n // print values along the color bar\n var gridLineLen = 5; // px\n var step = new StepNumber(this.valueMin, this.valueMax, (this.valueMax - this.valueMin) / 5, true);\n step.start();\n if (step.getCurrent() < this.valueMin) {\n step.next();\n }\n while (!step.end()) {\n y = bottom - (step.getCurrent() - this.valueMin) / (this.valueMax - this.valueMin) * height;\n\n ctx.beginPath();\n ctx.moveTo(left - gridLineLen, y);\n ctx.lineTo(left, y);\n ctx.stroke();\n\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n ctx.fillStyle = this.axisColor;\n ctx.fillText(step.getCurrent(), left - 2 * gridLineLen, y);\n\n step.next();\n }\n\n ctx.textAlign = 'right';\n ctx.textBaseline = 'top';\n var label = this.legendLabel;\n ctx.fillText(label, right, bottom + this.margin);\n }\n };\n\n /**\n * Redraw the filter\n */\n Graph3d.prototype._redrawFilter = function () {\n this.frame.filter.innerHTML = '';\n\n if (this.dataFilter) {\n var options = {\n 'visible': this.showAnimationControls\n };\n var slider = new Slider(this.frame.filter, options);\n this.frame.filter.slider = slider;\n\n // TODO: css here is not nice here...\n this.frame.filter.style.padding = '10px';\n //this.frame.filter.style.backgroundColor = '#EFEFEF';\n\n slider.setValues(this.dataFilter.values);\n slider.setPlayInterval(this.animationInterval);\n\n // create an event handler\n var me = this;\n var onchange = function onchange() {\n var index = slider.getIndex();\n\n me.dataFilter.selectValue(index);\n me.dataPoints = me.dataFilter._getDataPoints();\n\n me.redraw();\n };\n slider.setOnChangeCallback(onchange);\n } else {\n this.frame.filter.slider = undefined;\n }\n };\n\n /**\n * Redraw the slider\n */\n Graph3d.prototype._redrawSlider = function () {\n if (this.frame.filter.slider !== undefined) {\n this.frame.filter.slider.redraw();\n }\n };\n\n /**\n * Redraw common information\n */\n Graph3d.prototype._redrawInfo = function () {\n if (this.dataFilter) {\n var canvas = this.frame.canvas;\n var ctx = canvas.getContext('2d');\n\n ctx.font = '14px arial'; // TODO: put in options\n ctx.lineStyle = 'gray';\n ctx.fillStyle = 'gray';\n ctx.textAlign = 'left';\n ctx.textBaseline = 'top';\n\n var x = this.margin;\n var y = this.margin;\n ctx.fillText(this.dataFilter.getLabel() + ': ' + this.dataFilter.getSelectedValue(), x, y);\n }\n };\n\n /**\n * Redraw the axis\n */\n Graph3d.prototype._redrawAxis = function () {\n var canvas = this.frame.canvas,\n ctx = canvas.getContext('2d'),\n from,\n to,\n step,\n prettyStep,\n text,\n xText,\n yText,\n zText,\n offset,\n xOffset,\n yOffset,\n xMin2d,\n xMax2d;\n\n // TODO: get the actual rendered style of the containerElement\n //ctx.font = this.containerElement.style.font;\n ctx.font = 24 / this.camera.getArmLength() + 'px arial';\n\n // calculate the length for the short grid lines\n var gridLenX = 0.025 / this.scale.x;\n var gridLenY = 0.025 / this.scale.y;\n var textMargin = 5 / this.camera.getArmLength(); // px\n var armAngle = this.camera.getArmRotation().horizontal;\n\n // draw x-grid lines\n ctx.lineWidth = 1;\n prettyStep = this.defaultXStep === undefined;\n step = new StepNumber(this.xMin, this.xMax, this.xStep, prettyStep);\n step.start();\n if (step.getCurrent() < this.xMin) {\n step.next();\n }\n while (!step.end()) {\n var x = step.getCurrent();\n\n if (this.showGrid) {\n from = this._convert3Dto2D(new Point3d(x, this.yMin, this.zMin));\n to = this._convert3Dto2D(new Point3d(x, this.yMax, this.zMin));\n ctx.strokeStyle = this.gridColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n } else {\n from = this._convert3Dto2D(new Point3d(x, this.yMin, this.zMin));\n to = this._convert3Dto2D(new Point3d(x, this.yMin + gridLenX, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n\n from = this._convert3Dto2D(new Point3d(x, this.yMax, this.zMin));\n to = this._convert3Dto2D(new Point3d(x, this.yMax - gridLenX, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n }\n\n yText = Math.cos(armAngle) > 0 ? this.yMin : this.yMax;\n text = this._convert3Dto2D(new Point3d(x, yText, this.zMin));\n if (Math.cos(armAngle * 2) > 0) {\n ctx.textAlign = 'center';\n ctx.textBaseline = 'top';\n text.y += textMargin;\n } else if (Math.sin(armAngle * 2) < 0) {\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n } else {\n ctx.textAlign = 'left';\n ctx.textBaseline = 'middle';\n }\n ctx.fillStyle = this.axisColor;\n ctx.fillText(' ' + this.xValueLabel(step.getCurrent()) + ' ', text.x, text.y);\n\n step.next();\n }\n\n // draw y-grid lines\n ctx.lineWidth = 1;\n prettyStep = this.defaultYStep === undefined;\n step = new StepNumber(this.yMin, this.yMax, this.yStep, prettyStep);\n step.start();\n if (step.getCurrent() < this.yMin) {\n step.next();\n }\n while (!step.end()) {\n if (this.showGrid) {\n from = this._convert3Dto2D(new Point3d(this.xMin, step.getCurrent(), this.zMin));\n to = this._convert3Dto2D(new Point3d(this.xMax, step.getCurrent(), this.zMin));\n ctx.strokeStyle = this.gridColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n } else {\n from = this._convert3Dto2D(new Point3d(this.xMin, step.getCurrent(), this.zMin));\n to = this._convert3Dto2D(new Point3d(this.xMin + gridLenY, step.getCurrent(), this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n\n from = this._convert3Dto2D(new Point3d(this.xMax, step.getCurrent(), this.zMin));\n to = this._convert3Dto2D(new Point3d(this.xMax - gridLenY, step.getCurrent(), this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n }\n\n xText = Math.sin(armAngle) > 0 ? this.xMin : this.xMax;\n text = this._convert3Dto2D(new Point3d(xText, step.getCurrent(), this.zMin));\n if (Math.cos(armAngle * 2) < 0) {\n ctx.textAlign = 'center';\n ctx.textBaseline = 'top';\n text.y += textMargin;\n } else if (Math.sin(armAngle * 2) > 0) {\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n } else {\n ctx.textAlign = 'left';\n ctx.textBaseline = 'middle';\n }\n ctx.fillStyle = this.axisColor;\n ctx.fillText(' ' + this.yValueLabel(step.getCurrent()) + ' ', text.x, text.y);\n\n step.next();\n }\n\n // draw z-grid lines and axis\n ctx.lineWidth = 1;\n prettyStep = this.defaultZStep === undefined;\n step = new StepNumber(this.zMin, this.zMax, this.zStep, prettyStep);\n step.start();\n if (step.getCurrent() < this.zMin) {\n step.next();\n }\n xText = Math.cos(armAngle) > 0 ? this.xMin : this.xMax;\n yText = Math.sin(armAngle) < 0 ? this.yMin : this.yMax;\n while (!step.end()) {\n // TODO: make z-grid lines really 3d?\n from = this._convert3Dto2D(new Point3d(xText, yText, step.getCurrent()));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(from.x - textMargin, from.y);\n ctx.stroke();\n\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n ctx.fillStyle = this.axisColor;\n ctx.fillText(this.zValueLabel(step.getCurrent()) + ' ', from.x - 5, from.y);\n\n step.next();\n }\n ctx.lineWidth = 1;\n from = this._convert3Dto2D(new Point3d(xText, yText, this.zMin));\n to = this._convert3Dto2D(new Point3d(xText, yText, this.zMax));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n\n // draw x-axis\n ctx.lineWidth = 1;\n // line at yMin\n xMin2d = this._convert3Dto2D(new Point3d(this.xMin, this.yMin, this.zMin));\n xMax2d = this._convert3Dto2D(new Point3d(this.xMax, this.yMin, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(xMin2d.x, xMin2d.y);\n ctx.lineTo(xMax2d.x, xMax2d.y);\n ctx.stroke();\n // line at ymax\n xMin2d = this._convert3Dto2D(new Point3d(this.xMin, this.yMax, this.zMin));\n xMax2d = this._convert3Dto2D(new Point3d(this.xMax, this.yMax, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(xMin2d.x, xMin2d.y);\n ctx.lineTo(xMax2d.x, xMax2d.y);\n ctx.stroke();\n\n // draw y-axis\n ctx.lineWidth = 1;\n // line at xMin\n from = this._convert3Dto2D(new Point3d(this.xMin, this.yMin, this.zMin));\n to = this._convert3Dto2D(new Point3d(this.xMin, this.yMax, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n // line at xMax\n from = this._convert3Dto2D(new Point3d(this.xMax, this.yMin, this.zMin));\n to = this._convert3Dto2D(new Point3d(this.xMax, this.yMax, this.zMin));\n ctx.strokeStyle = this.axisColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(to.x, to.y);\n ctx.stroke();\n\n // draw x-label\n var xLabel = this.xLabel;\n if (xLabel.length > 0) {\n yOffset = 0.1 / this.scale.y;\n xText = (this.xMin + this.xMax) / 2;\n yText = Math.cos(armAngle) > 0 ? this.yMin - yOffset : this.yMax + yOffset;\n text = this._convert3Dto2D(new Point3d(xText, yText, this.zMin));\n if (Math.cos(armAngle * 2) > 0) {\n ctx.textAlign = 'center';\n ctx.textBaseline = 'top';\n } else if (Math.sin(armAngle * 2) < 0) {\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n } else {\n ctx.textAlign = 'left';\n ctx.textBaseline = 'middle';\n }\n ctx.fillStyle = this.axisColor;\n ctx.fillText(xLabel, text.x, text.y);\n }\n\n // draw y-label\n var yLabel = this.yLabel;\n if (yLabel.length > 0) {\n xOffset = 0.1 / this.scale.x;\n xText = Math.sin(armAngle) > 0 ? this.xMin - xOffset : this.xMax + xOffset;\n yText = (this.yMin + this.yMax) / 2;\n text = this._convert3Dto2D(new Point3d(xText, yText, this.zMin));\n if (Math.cos(armAngle * 2) < 0) {\n ctx.textAlign = 'center';\n ctx.textBaseline = 'top';\n } else if (Math.sin(armAngle * 2) > 0) {\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n } else {\n ctx.textAlign = 'left';\n ctx.textBaseline = 'middle';\n }\n ctx.fillStyle = this.axisColor;\n ctx.fillText(yLabel, text.x, text.y);\n }\n\n // draw z-label\n var zLabel = this.zLabel;\n if (zLabel.length > 0) {\n offset = 30; // pixels. // TODO: relate to the max width of the values on the z axis?\n xText = Math.cos(armAngle) > 0 ? this.xMin : this.xMax;\n yText = Math.sin(armAngle) < 0 ? this.yMin : this.yMax;\n zText = (this.zMin + this.zMax) / 2;\n text = this._convert3Dto2D(new Point3d(xText, yText, zText));\n ctx.textAlign = 'right';\n ctx.textBaseline = 'middle';\n ctx.fillStyle = this.axisColor;\n ctx.fillText(zLabel, text.x - offset, text.y);\n }\n };\n\n /**\n * Calculate the color based on the given value.\n * @param {Number} H Hue, a value be between 0 and 360\n * @param {Number} S Saturation, a value between 0 and 1\n * @param {Number} V Value, a value between 0 and 1\n */\n Graph3d.prototype._hsv2rgb = function (H, S, V) {\n var R, G, B, C, Hi, X;\n\n C = V * S;\n Hi = Math.floor(H / 60); // hi = 0,1,2,3,4,5\n X = C * (1 - Math.abs(H / 60 % 2 - 1));\n\n switch (Hi) {\n case 0:\n R = C;G = X;B = 0;break;\n case 1:\n R = X;G = C;B = 0;break;\n case 2:\n R = 0;G = C;B = X;break;\n case 3:\n R = 0;G = X;B = C;break;\n case 4:\n R = X;G = 0;B = C;break;\n case 5:\n R = C;G = 0;B = X;break;\n\n default:\n R = 0;G = 0;B = 0;break;\n }\n\n return 'RGB(' + parseInt(R * 255) + ',' + parseInt(G * 255) + ',' + parseInt(B * 255) + ')';\n };\n\n /**\n * Draw all datapoints as a grid\n * This function can be used when the style is 'grid'\n */\n Graph3d.prototype._redrawDataGrid = function () {\n var canvas = this.frame.canvas,\n ctx = canvas.getContext('2d'),\n point,\n right,\n top,\n cross,\n i,\n topSideVisible,\n fillStyle,\n strokeStyle,\n lineWidth,\n h,\n s,\n v,\n zAvg;\n\n ctx.lineJoin = 'round';\n ctx.lineCap = 'round';\n\n if (this.dataPoints === undefined || this.dataPoints.length <= 0) return; // TODO: throw exception?\n\n // calculate the translations and screen position of all points\n for (i = 0; i < this.dataPoints.length; i++) {\n var trans = this._convertPointToTranslation(this.dataPoints[i].point);\n var screen = this._convertTranslationToScreen(trans);\n\n this.dataPoints[i].trans = trans;\n this.dataPoints[i].screen = screen;\n\n // calculate the translation of the point at the bottom (needed for sorting)\n var transBottom = this._convertPointToTranslation(this.dataPoints[i].bottom);\n this.dataPoints[i].dist = this.showPerspective ? transBottom.length() : -transBottom.z;\n }\n\n // sort the points on depth of their (x,y) position (not on z)\n var sortDepth = function sortDepth(a, b) {\n return b.dist - a.dist;\n };\n this.dataPoints.sort(sortDepth);\n\n if (this.style === Graph3d.STYLE.SURFACE) {\n for (i = 0; i < this.dataPoints.length; i++) {\n point = this.dataPoints[i];\n right = this.dataPoints[i].pointRight;\n top = this.dataPoints[i].pointTop;\n cross = this.dataPoints[i].pointCross;\n\n if (point !== undefined && right !== undefined && top !== undefined && cross !== undefined) {\n\n if (this.showGrayBottom || this.showShadow) {\n // calculate the cross product of the two vectors from center\n // to left and right, in order to know whether we are looking at the\n // bottom or at the top side. We can also use the cross product\n // for calculating light intensity\n var aDiff = Point3d.subtract(cross.trans, point.trans);\n var bDiff = Point3d.subtract(top.trans, right.trans);\n var crossproduct = Point3d.crossProduct(aDiff, bDiff);\n var len = crossproduct.length();\n // FIXME: there is a bug with determining the surface side (shadow or colored)\n\n topSideVisible = crossproduct.z > 0;\n } else {\n topSideVisible = true;\n }\n\n if (topSideVisible) {\n // calculate Hue from the current value. At zMin the hue is 240, at zMax the hue is 0\n zAvg = (point.point.z + right.point.z + top.point.z + cross.point.z) / 4;\n h = (1 - (zAvg - this.zMin) * this.scale.z / this.verticalRatio) * 240;\n s = 1; // saturation\n\n if (this.showShadow) {\n v = Math.min(1 + crossproduct.x / len / 2, 1); // value. TODO: scale\n fillStyle = this._hsv2rgb(h, s, v);\n strokeStyle = fillStyle;\n } else {\n v = 1;\n fillStyle = this._hsv2rgb(h, s, v);\n strokeStyle = this.axisColor; // TODO: should be customizable\n }\n } else {\n fillStyle = 'gray';\n strokeStyle = this.axisColor;\n }\n\n ctx.lineWidth = this._getStrokeWidth(point);\n ctx.fillStyle = fillStyle;\n ctx.strokeStyle = strokeStyle;\n ctx.beginPath();\n ctx.moveTo(point.screen.x, point.screen.y);\n ctx.lineTo(right.screen.x, right.screen.y);\n ctx.lineTo(cross.screen.x, cross.screen.y);\n ctx.lineTo(top.screen.x, top.screen.y);\n ctx.closePath();\n ctx.fill();\n ctx.stroke(); // TODO: only draw stroke when strokeWidth > 0\n }\n }\n } else {\n // grid style\n for (i = 0; i < this.dataPoints.length; i++) {\n point = this.dataPoints[i];\n right = this.dataPoints[i].pointRight;\n top = this.dataPoints[i].pointTop;\n\n if (point !== undefined && right !== undefined) {\n // calculate Hue from the current value. At zMin the hue is 240, at zMax the hue is 0\n zAvg = (point.point.z + right.point.z) / 2;\n h = (1 - (zAvg - this.zMin) * this.scale.z / this.verticalRatio) * 240;\n\n ctx.lineWidth = this._getStrokeWidth(point) * 2;\n ctx.strokeStyle = this._hsv2rgb(h, 1, 1);\n ctx.beginPath();\n ctx.moveTo(point.screen.x, point.screen.y);\n ctx.lineTo(right.screen.x, right.screen.y);\n ctx.stroke();\n }\n\n if (point !== undefined && top !== undefined) {\n // calculate Hue from the current value. At zMin the hue is 240, at zMax the hue is 0\n zAvg = (point.point.z + top.point.z) / 2;\n h = (1 - (zAvg - this.zMin) * this.scale.z / this.verticalRatio) * 240;\n\n ctx.lineWidth = this._getStrokeWidth(point) * 2;\n ctx.strokeStyle = this._hsv2rgb(h, 1, 1);\n ctx.beginPath();\n ctx.moveTo(point.screen.x, point.screen.y);\n ctx.lineTo(top.screen.x, top.screen.y);\n ctx.stroke();\n }\n }\n }\n };\n\n Graph3d.prototype._getStrokeWidth = function (point) {\n if (point !== undefined) {\n if (this.showPerspective) {\n return 1 / -point.trans.z * this.dataColor.strokeWidth;\n } else {\n return -(this.eye.z / this.camera.getArmLength()) * this.dataColor.strokeWidth;\n }\n }\n\n return this.dataColor.strokeWidth;\n };\n\n /**\n * Draw all datapoints as dots.\n * This function can be used when the style is 'dot' or 'dot-line'\n */\n Graph3d.prototype._redrawDataDot = function () {\n var canvas = this.frame.canvas;\n var ctx = canvas.getContext('2d');\n var i;\n\n if (this.dataPoints === undefined || this.dataPoints.length <= 0) return; // TODO: throw exception?\n\n // calculate the translations of all points\n for (i = 0; i < this.dataPoints.length; i++) {\n var trans = this._convertPointToTranslation(this.dataPoints[i].point);\n var screen = this._convertTranslationToScreen(trans);\n this.dataPoints[i].trans = trans;\n this.dataPoints[i].screen = screen;\n\n // calculate the distance from the point at the bottom to the camera\n var transBottom = this._convertPointToTranslation(this.dataPoints[i].bottom);\n this.dataPoints[i].dist = this.showPerspective ? transBottom.length() : -transBottom.z;\n }\n\n // order the translated points by depth\n var sortDepth = function sortDepth(a, b) {\n return b.dist - a.dist;\n };\n this.dataPoints.sort(sortDepth);\n\n // draw the datapoints as colored circles\n var dotSize = this.frame.clientWidth * this.dotSizeRatio; // px\n for (i = 0; i < this.dataPoints.length; i++) {\n var point = this.dataPoints[i];\n\n if (this.style === Graph3d.STYLE.DOTLINE) {\n // draw a vertical line from the bottom to the graph value\n //var from = this._convert3Dto2D(new Point3d(point.point.x, point.point.y, this.zMin));\n var from = this._convert3Dto2D(point.bottom);\n ctx.lineWidth = 1;\n ctx.strokeStyle = this.gridColor;\n ctx.beginPath();\n ctx.moveTo(from.x, from.y);\n ctx.lineTo(point.screen.x, point.screen.y);\n ctx.stroke();\n }\n\n // calculate radius for the circle\n var size;\n if (this.style === Graph3d.STYLE.DOTSIZE) {\n size = dotSize / 2 + 2 * dotSize * (point.point.value - this.valueMin) / (this.valueMax - this.valueMin);\n } else {\n size = dotSize;\n }\n\n var radius;\n if (this.showPerspective) {\n radius = size / -point.trans.z;\n } else {\n radius = size * -(this.eye.z / this.camera.getArmLength());\n }\n if (radius < 0) {\n radius = 0;\n }\n\n var hue, color, borderColor;\n if (this.style === Graph3d.STYLE.DOTCOLOR) {\n // calculate the color based on the value\n hue = (1 - (point.point.value - this.valueMin) * this.scale.value) * 240;\n color = this._hsv2rgb(hue, 1, 1);\n borderColor = this._hsv2rgb(hue, 1, 0.8);\n } else if (this.style === Graph3d.STYLE.DOTSIZE) {\n color = this.dataColor.fill;\n borderColor = this.dataColor.stroke;\n } else {\n // calculate Hue from the current value. At zMin the hue is 240, at zMax the hue is 0\n hue = (1 - (point.point.z - this.zMin) * this.scale.z / this.verticalRatio) * 240;\n color = this._hsv2rgb(hue, 1, 1);\n borderColor = this._hsv2rgb(hue, 1, 0.8);\n }\n\n // draw the circle\n ctx.lineWidth = this._getStrokeWidth(point);\n ctx.strokeStyle = borderColor;\n ctx.fillStyle = color;\n ctx.beginPath();\n ctx.arc(point.screen.x, point.screen.y, radius, 0, Math.PI * 2, true);\n ctx.fill();\n ctx.stroke();\n }\n };\n\n /**\n * Draw all datapoints as bars.\n * This function can be used when the style is 'bar', 'bar-color', or 'bar-size'\n */\n Graph3d.prototype._redrawDataBar = function () {\n var canvas = this.frame.canvas;\n var ctx = canvas.getContext('2d');\n var i, j, surface, corners;\n\n if (this.dataPoints === undefined || this.dataPoints.length <= 0) return; // TODO: throw exception?\n\n // calculate the translations of all points\n for (i = 0; i < this.dataPoints.length; i++) {\n var trans = this._convertPointToTranslation(this.dataPoints[i].point);\n var screen = this._convertTranslationToScreen(trans);\n this.dataPoints[i].trans = trans;\n this.dataPoints[i].screen = screen;\n\n // calculate the distance from the point at the bottom to the camera\n var transBottom = this._convertPointToTranslation(this.dataPoints[i].bottom);\n this.dataPoints[i].dist = this.showPerspective ? transBottom.length() : -transBottom.z;\n }\n\n // order the translated points by depth\n var sortDepth = function sortDepth(a, b) {\n return b.dist - a.dist;\n };\n this.dataPoints.sort(sortDepth);\n\n ctx.lineJoin = 'round';\n ctx.lineCap = 'round';\n\n // draw the datapoints as bars\n var xWidth = this.xBarWidth / 2;\n var yWidth = this.yBarWidth / 2;\n for (i = 0; i < this.dataPoints.length; i++) {\n var point = this.dataPoints[i];\n\n // determine color\n var hue, color, borderColor;\n if (this.style === Graph3d.STYLE.BARCOLOR) {\n // calculate the color based on the value\n hue = (1 - (point.point.value - this.valueMin) * this.scale.value) * 240;\n color = this._hsv2rgb(hue, 1, 1);\n borderColor = this._hsv2rgb(hue, 1, 0.8);\n } else if (this.style === Graph3d.STYLE.BARSIZE) {\n color = this.dataColor.fill;\n borderColor = this.dataColor.stroke;\n } else {\n // calculate Hue from the current value. At zMin the hue is 240, at zMax the hue is 0\n hue = (1 - (point.point.z - this.zMin) * this.scale.z / this.verticalRatio) * 240;\n color = this._hsv2rgb(hue, 1, 1);\n borderColor = this._hsv2rgb(hue, 1, 0.8);\n }\n\n // calculate size for the bar\n if (this.style === Graph3d.STYLE.BARSIZE) {\n xWidth = this.xBarWidth / 2 * ((point.point.value - this.valueMin) / (this.valueMax - this.valueMin) * 0.8 + 0.2);\n yWidth = this.yBarWidth / 2 * ((point.point.value - this.valueMin) / (this.valueMax - this.valueMin) * 0.8 + 0.2);\n }\n\n // calculate all corner points\n var me = this;\n var point3d = point.point;\n var top = [{ point: new Point3d(point3d.x - xWidth, point3d.y - yWidth, point3d.z) }, { point: new Point3d(point3d.x + xWidth, point3d.y - yWidth, point3d.z) }, { point: new Point3d(point3d.x + xWidth, point3d.y + yWidth, point3d.z) }, { point: new Point3d(point3d.x - xWidth, point3d.y + yWidth, point3d.z) }];\n var bottom = [{ point: new Point3d(point3d.x - xWidth, point3d.y - yWidth, this.zMin) }, { point: new Point3d(point3d.x + xWidth, point3d.y - yWidth, this.zMin) }, { point: new Point3d(point3d.x + xWidth, point3d.y + yWidth, this.zMin) }, { point: new Point3d(point3d.x - xWidth, point3d.y + yWidth, this.zMin) }];\n\n // calculate screen location of the points\n top.forEach(function (obj) {\n obj.screen = me._convert3Dto2D(obj.point);\n });\n bottom.forEach(function (obj) {\n obj.screen = me._convert3Dto2D(obj.point);\n });\n\n // create five sides, calculate both corner points and center points\n var surfaces = [{ corners: top, center: Point3d.avg(bottom[0].point, bottom[2].point) }, { corners: [top[0], top[1], bottom[1], bottom[0]], center: Point3d.avg(bottom[1].point, bottom[0].point) }, { corners: [top[1], top[2], bottom[2], bottom[1]], center: Point3d.avg(bottom[2].point, bottom[1].point) }, { corners: [top[2], top[3], bottom[3], bottom[2]], center: Point3d.avg(bottom[3].point, bottom[2].point) }, { corners: [top[3], top[0], bottom[0], bottom[3]], center: Point3d.avg(bottom[0].point, bottom[3].point) }];\n point.surfaces = surfaces;\n\n // calculate the distance of each of the surface centers to the camera\n for (j = 0; j < surfaces.length; j++) {\n surface = surfaces[j];\n var transCenter = this._convertPointToTranslation(surface.center);\n surface.dist = this.showPerspective ? transCenter.length() : -transCenter.z;\n // TODO: this dept calculation doesn't work 100% of the cases due to perspective,\n // but the current solution is fast/simple and works in 99.9% of all cases\n // the issue is visible in example 14, with graph.setCameraPosition({horizontal: 2.97, vertical: 0.5, distance: 0.9})\n }\n\n // order the surfaces by their (translated) depth\n surfaces.sort(function (a, b) {\n var diff = b.dist - a.dist;\n if (diff) return diff;\n\n // if equal depth, sort the top surface last\n if (a.corners === top) return 1;\n if (b.corners === top) return -1;\n\n // both are equal\n return 0;\n });\n\n // draw the ordered surfaces\n ctx.lineWidth = this._getStrokeWidth(point);\n ctx.strokeStyle = borderColor;\n ctx.fillStyle = color;\n // NOTE: we start at j=2 instead of j=0 as we don't need to draw the two surfaces at the backside\n for (j = 2; j < surfaces.length; j++) {\n surface = surfaces[j];\n corners = surface.corners;\n ctx.beginPath();\n ctx.moveTo(corners[3].screen.x, corners[3].screen.y);\n ctx.lineTo(corners[0].screen.x, corners[0].screen.y);\n ctx.lineTo(corners[1].screen.x, corners[1].screen.y);\n ctx.lineTo(corners[2].screen.x, corners[2].screen.y);\n ctx.lineTo(corners[3].screen.x, corners[3].screen.y);\n ctx.fill();\n ctx.stroke();\n }\n }\n };\n\n /**\n * Draw a line through all datapoints.\n * This function can be used when the style is 'line'\n */\n Graph3d.prototype._redrawDataLine = function () {\n var canvas = this.frame.canvas,\n ctx = canvas.getContext('2d'),\n point,\n i;\n\n if (this.dataPoints === undefined || this.dataPoints.length <= 0) return; // TODO: throw exception?\n\n // calculate the translations of all points\n for (i = 0; i < this.dataPoints.length; i++) {\n var trans = this._convertPointToTranslation(this.dataPoints[i].point);\n var screen = this._convertTranslationToScreen(trans);\n\n this.dataPoints[i].trans = trans;\n this.dataPoints[i].screen = screen;\n }\n\n // start the line\n if (this.dataPoints.length > 0) {\n point = this.dataPoints[0];\n\n ctx.lineWidth = this._getStrokeWidth(point);\n ctx.lineJoin = 'round';\n ctx.lineCap = 'round';\n ctx.strokeStyle = this.dataColor.stroke;\n ctx.beginPath();\n ctx.moveTo(point.screen.x, point.screen.y);\n\n // draw the datapoints as colored circles\n for (i = 1; i < this.dataPoints.length; i++) {\n point = this.dataPoints[i];\n ctx.lineTo(point.screen.x, point.screen.y);\n }\n\n // finish the line\n ctx.stroke();\n }\n };\n\n /**\n * Start a moving operation inside the provided parent element\n * @param {Event} event The event that occurred (required for\n * retrieving the mouse position)\n */\n Graph3d.prototype._onMouseDown = function (event) {\n event = event || window.event;\n\n // check if mouse is still down (may be up when focus is lost for example\n // in an iframe)\n if (this.leftButtonDown) {\n this._onMouseUp(event);\n }\n\n // only react on left mouse button down\n this.leftButtonDown = event.which ? event.which === 1 : event.button === 1;\n if (!this.leftButtonDown && !this.touchDown) return;\n\n // get mouse position (different code for IE and all other browsers)\n this.startMouseX = getMouseX(event);\n this.startMouseY = getMouseY(event);\n\n this.startStart = new Date(this.start);\n this.startEnd = new Date(this.end);\n this.startArmRotation = this.camera.getArmRotation();\n\n this.frame.style.cursor = 'move';\n\n // add event listeners to handle moving the contents\n // we store the function onmousemove and onmouseup in the graph, so we can\n // remove the eventlisteners lateron in the function mouseUp()\n var me = this;\n this.onmousemove = function (event) {\n me._onMouseMove(event);\n };\n this.onmouseup = function (event) {\n me._onMouseUp(event);\n };\n util.addEventListener(document, 'mousemove', me.onmousemove);\n util.addEventListener(document, 'mouseup', me.onmouseup);\n util.preventDefault(event);\n };\n\n /**\n * Perform moving operating.\n * This function activated from within the funcion Graph.mouseDown().\n * @param {Event} event Well, eehh, the event\n */\n Graph3d.prototype._onMouseMove = function (event) {\n event = event || window.event;\n\n // calculate change in mouse position\n var diffX = parseFloat(getMouseX(event)) - this.startMouseX;\n var diffY = parseFloat(getMouseY(event)) - this.startMouseY;\n\n var horizontalNew = this.startArmRotation.horizontal + diffX / 200;\n var verticalNew = this.startArmRotation.vertical + diffY / 200;\n\n var snapAngle = 4; // degrees\n var snapValue = Math.sin(snapAngle / 360 * 2 * Math.PI);\n\n // snap horizontally to nice angles at 0pi, 0.5pi, 1pi, 1.5pi, etc...\n // the -0.001 is to take care that the vertical axis is always drawn at the left front corner\n if (Math.abs(Math.sin(horizontalNew)) < snapValue) {\n horizontalNew = Math.round(horizontalNew / Math.PI) * Math.PI - 0.001;\n }\n if (Math.abs(Math.cos(horizontalNew)) < snapValue) {\n horizontalNew = (Math.round(horizontalNew / Math.PI - 0.5) + 0.5) * Math.PI - 0.001;\n }\n\n // snap vertically to nice angles\n if (Math.abs(Math.sin(verticalNew)) < snapValue) {\n verticalNew = Math.round(verticalNew / Math.PI) * Math.PI;\n }\n if (Math.abs(Math.cos(verticalNew)) < snapValue) {\n verticalNew = (Math.round(verticalNew / Math.PI - 0.5) + 0.5) * Math.PI;\n }\n\n this.camera.setArmRotation(horizontalNew, verticalNew);\n this.redraw();\n\n // fire a cameraPositionChange event\n var parameters = this.getCameraPosition();\n this.emit('cameraPositionChange', parameters);\n\n util.preventDefault(event);\n };\n\n /**\n * Stop moving operating.\n * This function activated from within the funcion Graph.mouseDown().\n * @param {event} event The event\n */\n Graph3d.prototype._onMouseUp = function (event) {\n this.frame.style.cursor = 'auto';\n this.leftButtonDown = false;\n\n // remove event listeners here\n util.removeEventListener(document, 'mousemove', this.onmousemove);\n util.removeEventListener(document, 'mouseup', this.onmouseup);\n util.preventDefault(event);\n };\n\n /**\n * After having moved the mouse, a tooltip should pop up when the mouse is resting on a data point\n * @param {Event} event A mouse move event\n */\n Graph3d.prototype._onTooltip = function (event) {\n var delay = 300; // ms\n var boundingRect = this.frame.getBoundingClientRect();\n var mouseX = getMouseX(event) - boundingRect.left;\n var mouseY = getMouseY(event) - boundingRect.top;\n\n if (!this.showTooltip) {\n return;\n }\n\n if (this.tooltipTimeout) {\n clearTimeout(this.tooltipTimeout);\n }\n\n // (delayed) display of a tooltip only if no mouse button is down\n if (this.leftButtonDown) {\n this._hideTooltip();\n return;\n }\n\n if (this.tooltip && this.tooltip.dataPoint) {\n // tooltip is currently visible\n var dataPoint = this._dataPointFromXY(mouseX, mouseY);\n if (dataPoint !== this.tooltip.dataPoint) {\n // datapoint changed\n if (dataPoint) {\n this._showTooltip(dataPoint);\n } else {\n this._hideTooltip();\n }\n }\n } else {\n // tooltip is currently not visible\n var me = this;\n this.tooltipTimeout = setTimeout(function () {\n me.tooltipTimeout = null;\n\n // show a tooltip if we have a data point\n var dataPoint = me._dataPointFromXY(mouseX, mouseY);\n if (dataPoint) {\n me._showTooltip(dataPoint);\n }\n }, delay);\n }\n };\n\n /**\n * Event handler for touchstart event on mobile devices\n */\n Graph3d.prototype._onTouchStart = function (event) {\n this.touchDown = true;\n\n var me = this;\n this.ontouchmove = function (event) {\n me._onTouchMove(event);\n };\n this.ontouchend = function (event) {\n me._onTouchEnd(event);\n };\n util.addEventListener(document, 'touchmove', me.ontouchmove);\n util.addEventListener(document, 'touchend', me.ontouchend);\n\n this._onMouseDown(event);\n };\n\n /**\n * Event handler for touchmove event on mobile devices\n */\n Graph3d.prototype._onTouchMove = function (event) {\n this._onMouseMove(event);\n };\n\n /**\n * Event handler for touchend event on mobile devices\n */\n Graph3d.prototype._onTouchEnd = function (event) {\n this.touchDown = false;\n\n util.removeEventListener(document, 'touchmove', this.ontouchmove);\n util.removeEventListener(document, 'touchend', this.ontouchend);\n\n this._onMouseUp(event);\n };\n\n /**\n * Event handler for mouse wheel event, used to zoom the graph\n * Code from http://adomas.org/javascript-mouse-wheel/\n * @param {event} event The event\n */\n Graph3d.prototype._onWheel = function (event) {\n if (!event) /* For IE. */\n event = window.event;\n\n // retrieve delta\n var delta = 0;\n if (event.wheelDelta) {\n /* IE/Opera. */\n delta = event.wheelDelta / 120;\n } else if (event.detail) {\n /* Mozilla case. */\n // In Mozilla, sign of delta is different than in IE.\n // Also, delta is multiple of 3.\n delta = -event.detail / 3;\n }\n\n // If delta is nonzero, handle it.\n // Basically, delta is now positive if wheel was scrolled up,\n // and negative, if wheel was scrolled down.\n if (delta) {\n var oldLength = this.camera.getArmLength();\n var newLength = oldLength * (1 - delta / 10);\n\n this.camera.setArmLength(newLength);\n this.redraw();\n\n this._hideTooltip();\n }\n\n // fire a cameraPositionChange event\n var parameters = this.getCameraPosition();\n this.emit('cameraPositionChange', parameters);\n\n // Prevent default actions caused by mouse wheel.\n // That might be ugly, but we handle scrolls somehow\n // anyway, so don't bother here..\n util.preventDefault(event);\n };\n\n /**\n * Test whether a point lies inside given 2D triangle\n * @param {Point2d} point\n * @param {Point2d[]} triangle\n * @return {boolean} Returns true if given point lies inside or on the edge of the triangle\n * @private\n */\n Graph3d.prototype._insideTriangle = function (point, triangle) {\n var a = triangle[0],\n b = triangle[1],\n c = triangle[2];\n\n function sign(x) {\n return x > 0 ? 1 : x < 0 ? -1 : 0;\n }\n\n var as = sign((b.x - a.x) * (point.y - a.y) - (b.y - a.y) * (point.x - a.x));\n var bs = sign((c.x - b.x) * (point.y - b.y) - (c.y - b.y) * (point.x - b.x));\n var cs = sign((a.x - c.x) * (point.y - c.y) - (a.y - c.y) * (point.x - c.x));\n\n // each of the three signs must be either equal to each other or zero\n return (as == 0 || bs == 0 || as == bs) && (bs == 0 || cs == 0 || bs == cs) && (as == 0 || cs == 0 || as == cs);\n };\n\n /**\n * Find a data point close to given screen position (x, y)\n * @param {Number} x\n * @param {Number} y\n * @return {Object | null} The closest data point or null if not close to any data point\n * @private\n */\n Graph3d.prototype._dataPointFromXY = function (x, y) {\n var i,\n distMax = 100,\n // px\n dataPoint = null,\n closestDataPoint = null,\n closestDist = null,\n center = new Point2d(x, y);\n\n if (this.style === Graph3d.STYLE.BAR || this.style === Graph3d.STYLE.BARCOLOR || this.style === Graph3d.STYLE.BARSIZE) {\n // the data points are ordered from far away to closest\n for (i = this.dataPoints.length - 1; i >= 0; i--) {\n dataPoint = this.dataPoints[i];\n var surfaces = dataPoint.surfaces;\n if (surfaces) {\n for (var s = surfaces.length - 1; s >= 0; s--) {\n // split each surface in two triangles, and see if the center point is inside one of these\n var surface = surfaces[s];\n var corners = surface.corners;\n var triangle1 = [corners[0].screen, corners[1].screen, corners[2].screen];\n var triangle2 = [corners[2].screen, corners[3].screen, corners[0].screen];\n if (this._insideTriangle(center, triangle1) || this._insideTriangle(center, triangle2)) {\n // return immediately at the first hit\n return dataPoint;\n }\n }\n }\n }\n } else {\n // find the closest data point, using distance to the center of the point on 2d screen\n for (i = 0; i < this.dataPoints.length; i++) {\n dataPoint = this.dataPoints[i];\n var point = dataPoint.screen;\n if (point) {\n var distX = Math.abs(x - point.x);\n var distY = Math.abs(y - point.y);\n var dist = Math.sqrt(distX * distX + distY * distY);\n\n if ((closestDist === null || dist < closestDist) && dist < distMax) {\n closestDist = dist;\n closestDataPoint = dataPoint;\n }\n }\n }\n }\n\n return closestDataPoint;\n };\n\n /**\n * Display a tooltip for given data point\n * @param {Object} dataPoint\n * @private\n */\n Graph3d.prototype._showTooltip = function (dataPoint) {\n var content, line, dot;\n\n if (!this.tooltip) {\n content = document.createElement('div');\n content.style.position = 'absolute';\n content.style.padding = '10px';\n content.style.border = '1px solid #4d4d4d';\n content.style.color = '#1a1a1a';\n content.style.background = 'rgba(255,255,255,0.7)';\n content.style.borderRadius = '2px';\n content.style.boxShadow = '5px 5px 10px rgba(128,128,128,0.5)';\n\n line = document.createElement('div');\n line.style.position = 'absolute';\n line.style.height = '40px';\n line.style.width = '0';\n line.style.borderLeft = '1px solid #4d4d4d';\n\n dot = document.createElement('div');\n dot.style.position = 'absolute';\n dot.style.height = '0';\n dot.style.width = '0';\n dot.style.border = '5px solid #4d4d4d';\n dot.style.borderRadius = '5px';\n\n this.tooltip = {\n dataPoint: null,\n dom: {\n content: content,\n line: line,\n dot: dot\n }\n };\n } else {\n content = this.tooltip.dom.content;\n line = this.tooltip.dom.line;\n dot = this.tooltip.dom.dot;\n }\n\n this._hideTooltip();\n\n this.tooltip.dataPoint = dataPoint;\n if (typeof this.showTooltip === 'function') {\n content.innerHTML = this.showTooltip(dataPoint.point);\n } else {\n content.innerHTML = '<table>' + '<tr><td>x:</td><td>' + dataPoint.point.x + '</td></tr>' + '<tr><td>y:</td><td>' + dataPoint.point.y + '</td></tr>' + '<tr><td>z:</td><td>' + dataPoint.point.z + '</td></tr>' + '</table>';\n }\n\n content.style.left = '0';\n content.style.top = '0';\n this.frame.appendChild(content);\n this.frame.appendChild(line);\n this.frame.appendChild(dot);\n\n // calculate sizes\n var contentWidth = content.offsetWidth;\n var contentHeight = content.offsetHeight;\n var lineHeight = line.offsetHeight;\n var dotWidth = dot.offsetWidth;\n var dotHeight = dot.offsetHeight;\n\n var left = dataPoint.screen.x - contentWidth / 2;\n left = Math.min(Math.max(left, 10), this.frame.clientWidth - 10 - contentWidth);\n\n line.style.left = dataPoint.screen.x + 'px';\n line.style.top = dataPoint.screen.y - lineHeight + 'px';\n content.style.left = left + 'px';\n content.style.top = dataPoint.screen.y - lineHeight - contentHeight + 'px';\n dot.style.left = dataPoint.screen.x - dotWidth / 2 + 'px';\n dot.style.top = dataPoint.screen.y - dotHeight / 2 + 'px';\n };\n\n /**\n * Hide the tooltip when displayed\n * @private\n */\n Graph3d.prototype._hideTooltip = function () {\n if (this.tooltip) {\n this.tooltip.dataPoint = null;\n\n for (var prop in this.tooltip.dom) {\n if (this.tooltip.dom.hasOwnProperty(prop)) {\n var elem = this.tooltip.dom[prop];\n if (elem && elem.parentNode) {\n elem.parentNode.removeChild(elem);\n }\n }\n }\n }\n };\n\n /**--------------------------------------------------------------------------**/\n\n /**\n * Get the horizontal mouse position from a mouse event\n * @param {Event} event\n * @return {Number} mouse x\n */\n function getMouseX(event) {\n if ('clientX' in event) return event.clientX;\n return event.targetTouches[0] && event.targetTouches[0].clientX || 0;\n }\n\n /**\n * Get the vertical mouse position from a mouse event\n * @param {Event} event\n * @return {Number} mouse y\n */\n function getMouseY(event) {\n if ('clientY' in event) return event.clientY;\n return event.targetTouches[0] && event.targetTouches[0].clientY || 0;\n }\n\n module.exports = Graph3d;\n\n/***/ },\n/* 12 */\n/***/ function(module, exports) {\n\n \n /**\n * Expose `Emitter`.\n */\n\n module.exports = Emitter;\n\n /**\n * Initialize a new `Emitter`.\n *\n * @api public\n */\n\n function Emitter(obj) {\n if (obj) return mixin(obj);\n };\n\n /**\n * Mixin the emitter properties.\n *\n * @param {Object} obj\n * @return {Object}\n * @api private\n */\n\n function mixin(obj) {\n for (var key in Emitter.prototype) {\n obj[key] = Emitter.prototype[key];\n }\n return obj;\n }\n\n /**\n * Listen on the given `event` with `fn`.\n *\n * @param {String} event\n * @param {Function} fn\n * @return {Emitter}\n * @api public\n */\n\n Emitter.prototype.on =\n Emitter.prototype.addEventListener = function(event, fn){\n this._callbacks = this._callbacks || {};\n (this._callbacks[event] = this._callbacks[event] || [])\n .push(fn);\n return this;\n };\n\n /**\n * Adds an `event` listener that will be invoked a single\n * time then automatically removed.\n *\n * @param {String} event\n * @param {Function} fn\n * @return {Emitter}\n * @api public\n */\n\n Emitter.prototype.once = function(event, fn){\n var self = this;\n this._callbacks = this._callbacks || {};\n\n function on() {\n self.off(event, on);\n fn.apply(this, arguments);\n }\n\n on.fn = fn;\n this.on(event, on);\n return this;\n };\n\n /**\n * Remove the given callback for `event` or all\n * registered callbacks.\n *\n * @param {String} event\n * @param {Function} fn\n * @return {Emitter}\n * @api public\n */\n\n Emitter.prototype.off =\n Emitter.prototype.removeListener =\n Emitter.prototype.removeAllListeners =\n Emitter.prototype.removeEventListener = function(event, fn){\n this._callbacks = this._callbacks || {};\n\n // all\n if (0 == arguments.length) {\n this._callbacks = {};\n return this;\n }\n\n // specific event\n var callbacks = this._callbacks[event];\n if (!callbacks) return this;\n\n // remove all handlers\n if (1 == arguments.length) {\n delete this._callbacks[event];\n return this;\n }\n\n // remove specific handler\n var cb;\n for (var i = 0; i < callbacks.length; i++) {\n cb = callbacks[i];\n if (cb === fn || cb.fn === fn) {\n callbacks.splice(i, 1);\n break;\n }\n }\n return this;\n };\n\n /**\n * Emit `event` with the given args.\n *\n * @param {String} event\n * @param {Mixed} ...\n * @return {Emitter}\n */\n\n Emitter.prototype.emit = function(event){\n this._callbacks = this._callbacks || {};\n var args = [].slice.call(arguments, 1)\n , callbacks = this._callbacks[event];\n\n if (callbacks) {\n callbacks = callbacks.slice(0);\n for (var i = 0, len = callbacks.length; i < len; ++i) {\n callbacks[i].apply(this, args);\n }\n }\n\n return this;\n };\n\n /**\n * Return array of callbacks for `event`.\n *\n * @param {String} event\n * @return {Array}\n * @api public\n */\n\n Emitter.prototype.listeners = function(event){\n this._callbacks = this._callbacks || {};\n return this._callbacks[event] || [];\n };\n\n /**\n * Check if this emitter has `event` handlers.\n *\n * @param {String} event\n * @return {Boolean}\n * @api public\n */\n\n Emitter.prototype.hasListeners = function(event){\n return !! this.listeners(event).length;\n };\n\n\n/***/ },\n/* 13 */\n/***/ function(module, exports) {\n\n /**\n * @prototype Point3d\n * @param {Number} [x]\n * @param {Number} [y]\n * @param {Number} [z]\n */\n \"use strict\";\n\n function Point3d(x, y, z) {\n this.x = x !== undefined ? x : 0;\n this.y = y !== undefined ? y : 0;\n this.z = z !== undefined ? z : 0;\n };\n\n /**\n * Subtract the two provided points, returns a-b\n * @param {Point3d} a\n * @param {Point3d} b\n * @return {Point3d} a-b\n */\n Point3d.subtract = function (a, b) {\n var sub = new Point3d();\n sub.x = a.x - b.x;\n sub.y = a.y - b.y;\n sub.z = a.z - b.z;\n return sub;\n };\n\n /**\n * Add the two provided points, returns a+b\n * @param {Point3d} a\n * @param {Point3d} b\n * @return {Point3d} a+b\n */\n Point3d.add = function (a, b) {\n var sum = new Point3d();\n sum.x = a.x + b.x;\n sum.y = a.y + b.y;\n sum.z = a.z + b.z;\n return sum;\n };\n\n /**\n * Calculate the average of two 3d points\n * @param {Point3d} a\n * @param {Point3d} b\n * @return {Point3d} The average, (a+b)/2\n */\n Point3d.avg = function (a, b) {\n return new Point3d((a.x + b.x) / 2, (a.y + b.y) / 2, (a.z + b.z) / 2);\n };\n\n /**\n * Calculate the cross product of the two provided points, returns axb\n * Documentation: http://en.wikipedia.org/wiki/Cross_product\n * @param {Point3d} a\n * @param {Point3d} b\n * @return {Point3d} cross product axb\n */\n Point3d.crossProduct = function (a, b) {\n var crossproduct = new Point3d();\n\n crossproduct.x = a.y * b.z - a.z * b.y;\n crossproduct.y = a.z * b.x - a.x * b.z;\n crossproduct.z = a.x * b.y - a.y * b.x;\n\n return crossproduct;\n };\n\n /**\n * Rtrieve the length of the vector (or the distance from this point to the origin\n * @return {Number} length\n */\n Point3d.prototype.length = function () {\n return Math.sqrt(this.x * this.x + this.y * this.y + this.z * this.z);\n };\n\n module.exports = Point3d;\n\n/***/ },\n/* 14 */\n/***/ function(module, exports) {\n\n /**\n * @prototype Point2d\n * @param {Number} [x]\n * @param {Number} [y]\n */\n \"use strict\";\n\n function Point2d(x, y) {\n this.x = x !== undefined ? x : 0;\n this.y = y !== undefined ? y : 0;\n }\n\n module.exports = Point2d;\n\n/***/ },\n/* 15 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Point3d = __webpack_require__(13);\n\n /**\n * @class Camera\n * The camera is mounted on a (virtual) camera arm. The camera arm can rotate\n * The camera is always looking in the direction of the origin of the arm.\n * This way, the camera always rotates around one fixed point, the location\n * of the camera arm.\n *\n * Documentation:\n * http://en.wikipedia.org/wiki/3D_projection\n */\n function Camera() {\n this.armLocation = new Point3d();\n this.armRotation = {};\n this.armRotation.horizontal = 0;\n this.armRotation.vertical = 0;\n this.armLength = 1.7;\n\n this.cameraLocation = new Point3d();\n this.cameraRotation = new Point3d(0.5 * Math.PI, 0, 0);\n\n this.calculateCameraOrientation();\n }\n\n /**\n * Set the location (origin) of the arm\n * @param {Number} x Normalized value of x\n * @param {Number} y Normalized value of y\n * @param {Number} z Normalized value of z\n */\n Camera.prototype.setArmLocation = function (x, y, z) {\n this.armLocation.x = x;\n this.armLocation.y = y;\n this.armLocation.z = z;\n\n this.calculateCameraOrientation();\n };\n\n /**\n * Set the rotation of the camera arm\n * @param {Number} horizontal The horizontal rotation, between 0 and 2*PI.\n * Optional, can be left undefined.\n * @param {Number} vertical The vertical rotation, between 0 and 0.5*PI\n * if vertical=0.5*PI, the graph is shown from the\n * top. Optional, can be left undefined.\n */\n Camera.prototype.setArmRotation = function (horizontal, vertical) {\n if (horizontal !== undefined) {\n this.armRotation.horizontal = horizontal;\n }\n\n if (vertical !== undefined) {\n this.armRotation.vertical = vertical;\n if (this.armRotation.vertical < 0) this.armRotation.vertical = 0;\n if (this.armRotation.vertical > 0.5 * Math.PI) this.armRotation.vertical = 0.5 * Math.PI;\n }\n\n if (horizontal !== undefined || vertical !== undefined) {\n this.calculateCameraOrientation();\n }\n };\n\n /**\n * Retrieve the current arm rotation\n * @return {object} An object with parameters horizontal and vertical\n */\n Camera.prototype.getArmRotation = function () {\n var rot = {};\n rot.horizontal = this.armRotation.horizontal;\n rot.vertical = this.armRotation.vertical;\n\n return rot;\n };\n\n /**\n * Set the (normalized) length of the camera arm.\n * @param {Number} length A length between 0.71 and 5.0\n */\n Camera.prototype.setArmLength = function (length) {\n if (length === undefined) return;\n\n this.armLength = length;\n\n // Radius must be larger than the corner of the graph,\n // which has a distance of sqrt(0.5^2+0.5^2) = 0.71 from the center of the\n // graph\n if (this.armLength < 0.71) this.armLength = 0.71;\n if (this.armLength > 5.0) this.armLength = 5.0;\n\n this.calculateCameraOrientation();\n };\n\n /**\n * Retrieve the arm length\n * @return {Number} length\n */\n Camera.prototype.getArmLength = function () {\n return this.armLength;\n };\n\n /**\n * Retrieve the camera location\n * @return {Point3d} cameraLocation\n */\n Camera.prototype.getCameraLocation = function () {\n return this.cameraLocation;\n };\n\n /**\n * Retrieve the camera rotation\n * @return {Point3d} cameraRotation\n */\n Camera.prototype.getCameraRotation = function () {\n return this.cameraRotation;\n };\n\n /**\n * Calculate the location and rotation of the camera based on the\n * position and orientation of the camera arm\n */\n Camera.prototype.calculateCameraOrientation = function () {\n // calculate location of the camera\n this.cameraLocation.x = this.armLocation.x - this.armLength * Math.sin(this.armRotation.horizontal) * Math.cos(this.armRotation.vertical);\n this.cameraLocation.y = this.armLocation.y - this.armLength * Math.cos(this.armRotation.horizontal) * Math.cos(this.armRotation.vertical);\n this.cameraLocation.z = this.armLocation.z + this.armLength * Math.sin(this.armRotation.vertical);\n\n // calculate rotation of the camera\n this.cameraRotation.x = Math.PI / 2 - this.armRotation.vertical;\n this.cameraRotation.y = 0;\n this.cameraRotation.z = -this.armRotation.horizontal;\n };\n\n module.exports = Camera;\n\n/***/ },\n/* 16 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var DataView = __webpack_require__(10);\n\n /**\n * @class Filter\n *\n * @param {DataSet} data The google data table\n * @param {Number} column The index of the column to be filtered\n * @param {Graph} graph The graph\n */\n function Filter(data, column, graph) {\n this.data = data;\n this.column = column;\n this.graph = graph; // the parent graph\n\n this.index = undefined;\n this.value = undefined;\n\n // read all distinct values and select the first one\n this.values = graph.getDistinctValues(data.get(), this.column);\n\n // sort both numeric and string values correctly\n this.values.sort(function (a, b) {\n return a > b ? 1 : a < b ? -1 : 0;\n });\n\n if (this.values.length > 0) {\n this.selectValue(0);\n }\n\n // create an array with the filtered datapoints. this will be loaded afterwards\n this.dataPoints = [];\n\n this.loaded = false;\n this.onLoadCallback = undefined;\n\n if (graph.animationPreload) {\n this.loaded = false;\n this.loadInBackground();\n } else {\n this.loaded = true;\n }\n };\n\n /**\n * Return the label\n * @return {string} label\n */\n Filter.prototype.isLoaded = function () {\n return this.loaded;\n };\n\n /**\n * Return the loaded progress\n * @return {Number} percentage between 0 and 100\n */\n Filter.prototype.getLoadedProgress = function () {\n var len = this.values.length;\n\n var i = 0;\n while (this.dataPoints[i]) {\n i++;\n }\n\n return Math.round(i / len * 100);\n };\n\n /**\n * Return the label\n * @return {string} label\n */\n Filter.prototype.getLabel = function () {\n return this.graph.filterLabel;\n };\n\n /**\n * Return the columnIndex of the filter\n * @return {Number} columnIndex\n */\n Filter.prototype.getColumn = function () {\n return this.column;\n };\n\n /**\n * Return the currently selected value. Returns undefined if there is no selection\n * @return {*} value\n */\n Filter.prototype.getSelectedValue = function () {\n if (this.index === undefined) return undefined;\n\n return this.values[this.index];\n };\n\n /**\n * Retrieve all values of the filter\n * @return {Array} values\n */\n Filter.prototype.getValues = function () {\n return this.values;\n };\n\n /**\n * Retrieve one value of the filter\n * @param {Number} index\n * @return {*} value\n */\n Filter.prototype.getValue = function (index) {\n if (index >= this.values.length) throw 'Error: index out of range';\n\n return this.values[index];\n };\n\n /**\n * Retrieve the (filtered) dataPoints for the currently selected filter index\n * @param {Number} [index] (optional)\n * @return {Array} dataPoints\n */\n Filter.prototype._getDataPoints = function (index) {\n if (index === undefined) index = this.index;\n\n if (index === undefined) return [];\n\n var dataPoints;\n if (this.dataPoints[index]) {\n dataPoints = this.dataPoints[index];\n } else {\n var f = {};\n f.column = this.column;\n f.value = this.values[index];\n\n var dataView = new DataView(this.data, { filter: function filter(item) {\n return item[f.column] == f.value;\n } }).get();\n dataPoints = this.graph._getDataPoints(dataView);\n\n this.dataPoints[index] = dataPoints;\n }\n\n return dataPoints;\n };\n\n /**\n * Set a callback function when the filter is fully loaded.\n */\n Filter.prototype.setOnLoadCallback = function (callback) {\n this.onLoadCallback = callback;\n };\n\n /**\n * Add a value to the list with available values for this filter\n * No double entries will be created.\n * @param {Number} index\n */\n Filter.prototype.selectValue = function (index) {\n if (index >= this.values.length) throw 'Error: index out of range';\n\n this.index = index;\n this.value = this.values[index];\n };\n\n /**\n * Load all filtered rows in the background one by one\n * Start this method without providing an index!\n */\n Filter.prototype.loadInBackground = function (index) {\n if (index === undefined) index = 0;\n\n var frame = this.graph.frame;\n\n if (index < this.values.length) {\n var dataPointsTemp = this._getDataPoints(index);\n //this.graph.redrawInfo(); // TODO: not neat\n\n // create a progress box\n if (frame.progress === undefined) {\n frame.progress = document.createElement('DIV');\n frame.progress.style.position = 'absolute';\n frame.progress.style.color = 'gray';\n frame.appendChild(frame.progress);\n }\n var progress = this.getLoadedProgress();\n frame.progress.innerHTML = 'Loading animation... ' + progress + '%';\n // TODO: this is no nice solution...\n frame.progress.style.bottom = 60 + 'px'; // TODO: use height of slider\n frame.progress.style.left = 10 + 'px';\n\n var me = this;\n setTimeout(function () {\n me.loadInBackground(index + 1);\n }, 10);\n this.loaded = false;\n } else {\n this.loaded = true;\n\n // remove the progress box\n if (frame.progress !== undefined) {\n frame.removeChild(frame.progress);\n frame.progress = undefined;\n }\n\n if (this.onLoadCallback) this.onLoadCallback();\n }\n };\n\n module.exports = Filter;\n\n/***/ },\n/* 17 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n\n /**\n * @constructor Slider\n *\n * An html slider control with start/stop/prev/next buttons\n * @param {Element} container The element where the slider will be created\n * @param {Object} options Available options:\n * {boolean} visible If true (default) the\n * slider is visible.\n */\n function Slider(container, options) {\n if (container === undefined) {\n throw 'Error: No container element defined';\n }\n this.container = container;\n this.visible = options && options.visible != undefined ? options.visible : true;\n\n if (this.visible) {\n this.frame = document.createElement('DIV');\n //this.frame.style.backgroundColor = '#E5E5E5';\n this.frame.style.width = '100%';\n this.frame.style.position = 'relative';\n this.container.appendChild(this.frame);\n\n this.frame.prev = document.createElement('INPUT');\n this.frame.prev.type = 'BUTTON';\n this.frame.prev.value = 'Prev';\n this.frame.appendChild(this.frame.prev);\n\n this.frame.play = document.createElement('INPUT');\n this.frame.play.type = 'BUTTON';\n this.frame.play.value = 'Play';\n this.frame.appendChild(this.frame.play);\n\n this.frame.next = document.createElement('INPUT');\n this.frame.next.type = 'BUTTON';\n this.frame.next.value = 'Next';\n this.frame.appendChild(this.frame.next);\n\n this.frame.bar = document.createElement('INPUT');\n this.frame.bar.type = 'BUTTON';\n this.frame.bar.style.position = 'absolute';\n this.frame.bar.style.border = '1px solid red';\n this.frame.bar.style.width = '100px';\n this.frame.bar.style.height = '6px';\n this.frame.bar.style.borderRadius = '2px';\n this.frame.bar.style.MozBorderRadius = '2px';\n this.frame.bar.style.border = '1px solid #7F7F7F';\n this.frame.bar.style.backgroundColor = '#E5E5E5';\n this.frame.appendChild(this.frame.bar);\n\n this.frame.slide = document.createElement('INPUT');\n this.frame.slide.type = 'BUTTON';\n this.frame.slide.style.margin = '0px';\n this.frame.slide.value = ' ';\n this.frame.slide.style.position = 'relative';\n this.frame.slide.style.left = '-100px';\n this.frame.appendChild(this.frame.slide);\n\n // create events\n var me = this;\n this.frame.slide.onmousedown = function (event) {\n me._onMouseDown(event);\n };\n this.frame.prev.onclick = function (event) {\n me.prev(event);\n };\n this.frame.play.onclick = function (event) {\n me.togglePlay(event);\n };\n this.frame.next.onclick = function (event) {\n me.next(event);\n };\n }\n\n this.onChangeCallback = undefined;\n\n this.values = [];\n this.index = undefined;\n\n this.playTimeout = undefined;\n this.playInterval = 1000; // milliseconds\n this.playLoop = true;\n }\n\n /**\n * Select the previous index\n */\n Slider.prototype.prev = function () {\n var index = this.getIndex();\n if (index > 0) {\n index--;\n this.setIndex(index);\n }\n };\n\n /**\n * Select the next index\n */\n Slider.prototype.next = function () {\n var index = this.getIndex();\n if (index < this.values.length - 1) {\n index++;\n this.setIndex(index);\n }\n };\n\n /**\n * Select the next index\n */\n Slider.prototype.playNext = function () {\n var start = new Date();\n\n var index = this.getIndex();\n if (index < this.values.length - 1) {\n index++;\n this.setIndex(index);\n } else if (this.playLoop) {\n // jump to the start\n index = 0;\n this.setIndex(index);\n }\n\n var end = new Date();\n var diff = end - start;\n\n // calculate how much time it to to set the index and to execute the callback\n // function.\n var interval = Math.max(this.playInterval - diff, 0);\n // document.title = diff // TODO: cleanup\n\n var me = this;\n this.playTimeout = setTimeout(function () {\n me.playNext();\n }, interval);\n };\n\n /**\n * Toggle start or stop playing\n */\n Slider.prototype.togglePlay = function () {\n if (this.playTimeout === undefined) {\n this.play();\n } else {\n this.stop();\n }\n };\n\n /**\n * Start playing\n */\n Slider.prototype.play = function () {\n // Test whether already playing\n if (this.playTimeout) return;\n\n this.playNext();\n\n if (this.frame) {\n this.frame.play.value = 'Stop';\n }\n };\n\n /**\n * Stop playing\n */\n Slider.prototype.stop = function () {\n clearInterval(this.playTimeout);\n this.playTimeout = undefined;\n\n if (this.frame) {\n this.frame.play.value = 'Play';\n }\n };\n\n /**\n * Set a callback function which will be triggered when the value of the\n * slider bar has changed.\n */\n Slider.prototype.setOnChangeCallback = function (callback) {\n this.onChangeCallback = callback;\n };\n\n /**\n * Set the interval for playing the list\n * @param {Number} interval The interval in milliseconds\n */\n Slider.prototype.setPlayInterval = function (interval) {\n this.playInterval = interval;\n };\n\n /**\n * Retrieve the current play interval\n * @return {Number} interval The interval in milliseconds\n */\n Slider.prototype.getPlayInterval = function (interval) {\n return this.playInterval;\n };\n\n /**\n * Set looping on or off\n * @pararm {boolean} doLoop If true, the slider will jump to the start when\n * the end is passed, and will jump to the end\n * when the start is passed.\n */\n Slider.prototype.setPlayLoop = function (doLoop) {\n this.playLoop = doLoop;\n };\n\n /**\n * Execute the onchange callback function\n */\n Slider.prototype.onChange = function () {\n if (this.onChangeCallback !== undefined) {\n this.onChangeCallback();\n }\n };\n\n /**\n * redraw the slider on the correct place\n */\n Slider.prototype.redraw = function () {\n if (this.frame) {\n // resize the bar\n this.frame.bar.style.top = this.frame.clientHeight / 2 - this.frame.bar.offsetHeight / 2 + 'px';\n this.frame.bar.style.width = this.frame.clientWidth - this.frame.prev.clientWidth - this.frame.play.clientWidth - this.frame.next.clientWidth - 30 + 'px';\n\n // position the slider button\n var left = this.indexToLeft(this.index);\n this.frame.slide.style.left = left + 'px';\n }\n };\n\n /**\n * Set the list with values for the slider\n * @param {Array} values A javascript array with values (any type)\n */\n Slider.prototype.setValues = function (values) {\n this.values = values;\n\n if (this.values.length > 0) this.setIndex(0);else this.index = undefined;\n };\n\n /**\n * Select a value by its index\n * @param {Number} index\n */\n Slider.prototype.setIndex = function (index) {\n if (index < this.values.length) {\n this.index = index;\n\n this.redraw();\n this.onChange();\n } else {\n throw 'Error: index out of range';\n }\n };\n\n /**\n * retrieve the index of the currently selected vaue\n * @return {Number} index\n */\n Slider.prototype.getIndex = function () {\n return this.index;\n };\n\n /**\n * retrieve the currently selected value\n * @return {*} value\n */\n Slider.prototype.get = function () {\n return this.values[this.index];\n };\n\n Slider.prototype._onMouseDown = function (event) {\n // only react on left mouse button down\n var leftButtonDown = event.which ? event.which === 1 : event.button === 1;\n if (!leftButtonDown) return;\n\n this.startClientX = event.clientX;\n this.startSlideX = parseFloat(this.frame.slide.style.left);\n\n this.frame.style.cursor = 'move';\n\n // add event listeners to handle moving the contents\n // we store the function onmousemove and onmouseup in the graph, so we can\n // remove the eventlisteners lateron in the function mouseUp()\n var me = this;\n this.onmousemove = function (event) {\n me._onMouseMove(event);\n };\n this.onmouseup = function (event) {\n me._onMouseUp(event);\n };\n util.addEventListener(document, 'mousemove', this.onmousemove);\n util.addEventListener(document, 'mouseup', this.onmouseup);\n util.preventDefault(event);\n };\n\n Slider.prototype.leftToIndex = function (left) {\n var width = parseFloat(this.frame.bar.style.width) - this.frame.slide.clientWidth - 10;\n var x = left - 3;\n\n var index = Math.round(x / width * (this.values.length - 1));\n if (index < 0) index = 0;\n if (index > this.values.length - 1) index = this.values.length - 1;\n\n return index;\n };\n\n Slider.prototype.indexToLeft = function (index) {\n var width = parseFloat(this.frame.bar.style.width) - this.frame.slide.clientWidth - 10;\n\n var x = index / (this.values.length - 1) * width;\n var left = x + 3;\n\n return left;\n };\n\n Slider.prototype._onMouseMove = function (event) {\n var diff = event.clientX - this.startClientX;\n var x = this.startSlideX + diff;\n\n var index = this.leftToIndex(x);\n\n this.setIndex(index);\n\n util.preventDefault();\n };\n\n Slider.prototype._onMouseUp = function (event) {\n this.frame.style.cursor = 'auto';\n\n // remove event listeners\n util.removeEventListener(document, 'mousemove', this.onmousemove);\n util.removeEventListener(document, 'mouseup', this.onmouseup);\n\n util.preventDefault();\n };\n\n module.exports = Slider;\n\n/***/ },\n/* 18 */\n/***/ function(module, exports) {\n\n /**\n * @prototype StepNumber\n * The class StepNumber is an iterator for Numbers. You provide a start and end\n * value, and a best step size. StepNumber itself rounds to fixed values and\n * a finds the step that best fits the provided step.\n *\n * If prettyStep is true, the step size is chosen as close as possible to the\n * provided step, but being a round value like 1, 2, 5, 10, 20, 50, ....\n *\n * Example usage:\n * var step = new StepNumber(0, 10, 2.5, true);\n * step.start();\n * while (!step.end()) {\n * alert(step.getCurrent());\n * step.next();\n * }\n *\n * Version: 1.0\n *\n * @param {Number} start The start value\n * @param {Number} end The end value\n * @param {Number} step Optional. Step size. Must be a positive value.\n * @param {boolean} prettyStep Optional. If true, the step size is rounded\n * To a pretty step size (like 1, 2, 5, 10, 20, 50, ...)\n */\n \"use strict\";\n\n function StepNumber(start, end, step, prettyStep) {\n // set default values\n this._start = 0;\n this._end = 0;\n this._step = 1;\n this.prettyStep = true;\n this.precision = 5;\n\n this._current = 0;\n this.setRange(start, end, step, prettyStep);\n };\n\n /**\n * Set a new range: start, end and step.\n *\n * @param {Number} start The start value\n * @param {Number} end The end value\n * @param {Number} step Optional. Step size. Must be a positive value.\n * @param {boolean} prettyStep Optional. If true, the step size is rounded\n * To a pretty step size (like 1, 2, 5, 10, 20, 50, ...)\n */\n StepNumber.prototype.setRange = function (start, end, step, prettyStep) {\n this._start = start ? start : 0;\n this._end = end ? end : 0;\n\n this.setStep(step, prettyStep);\n };\n\n /**\n * Set a new step size\n * @param {Number} step New step size. Must be a positive value\n * @param {boolean} prettyStep Optional. If true, the provided step is rounded\n * to a pretty step size (like 1, 2, 5, 10, 20, 50, ...)\n */\n StepNumber.prototype.setStep = function (step, prettyStep) {\n if (step === undefined || step <= 0) return;\n\n if (prettyStep !== undefined) this.prettyStep = prettyStep;\n\n if (this.prettyStep === true) this._step = StepNumber.calculatePrettyStep(step);else this._step = step;\n };\n\n /**\n * Calculate a nice step size, closest to the desired step size.\n * Returns a value in one of the ranges 1*10^n, 2*10^n, or 5*10^n, where n is an\n * integer Number. For example 1, 2, 5, 10, 20, 50, etc...\n * @param {Number} step Desired step size\n * @return {Number} Nice step size\n */\n StepNumber.calculatePrettyStep = function (step) {\n var log10 = function log10(x) {\n return Math.log(x) / Math.LN10;\n };\n\n // try three steps (multiple of 1, 2, or 5\n var step1 = Math.pow(10, Math.round(log10(step))),\n step2 = 2 * Math.pow(10, Math.round(log10(step / 2))),\n step5 = 5 * Math.pow(10, Math.round(log10(step / 5)));\n\n // choose the best step (closest to minimum step)\n var prettyStep = step1;\n if (Math.abs(step2 - step) <= Math.abs(prettyStep - step)) prettyStep = step2;\n if (Math.abs(step5 - step) <= Math.abs(prettyStep - step)) prettyStep = step5;\n\n // for safety\n if (prettyStep <= 0) {\n prettyStep = 1;\n }\n\n return prettyStep;\n };\n\n /**\n * returns the current value of the step\n * @return {Number} current value\n */\n StepNumber.prototype.getCurrent = function () {\n return parseFloat(this._current.toPrecision(this.precision));\n };\n\n /**\n * returns the current step size\n * @return {Number} current step size\n */\n StepNumber.prototype.getStep = function () {\n return this._step;\n };\n\n /**\n * Set the current value to the largest value smaller than start, which\n * is a multiple of the step size\n */\n StepNumber.prototype.start = function () {\n this._current = this._start - this._start % this._step;\n };\n\n /**\n * Do a step, add the step size to the current value\n */\n StepNumber.prototype.next = function () {\n this._current += this._step;\n };\n\n /**\n * Returns true whether the end is reached\n * @return {boolean} True if the current value has passed the end value.\n */\n StepNumber.prototype.end = function () {\n return this._current > this._end;\n };\n\n module.exports = StepNumber;\n\n/***/ },\n/* 19 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Emitter = __webpack_require__(12);\n var Hammer = __webpack_require__(20);\n var moment = __webpack_require__(2);\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var Range = __webpack_require__(23);\n var Core = __webpack_require__(27);\n var TimeAxis = __webpack_require__(38);\n var CurrentTime = __webpack_require__(43);\n var CustomTime = __webpack_require__(41);\n var ItemSet = __webpack_require__(28);\n\n var Configurator = __webpack_require__(44);\n var Validator = __webpack_require__(46)['default'];\n var printStyle = __webpack_require__(46).printStyle;\n var allOptions = __webpack_require__(47).allOptions;\n var configureOptions = __webpack_require__(47).configureOptions;\n\n /**\n * Create a timeline visualization\n * @param {HTMLElement} container\n * @param {vis.DataSet | vis.DataView | Array} [items]\n * @param {vis.DataSet | vis.DataView | Array} [groups]\n * @param {Object} [options] See Timeline.setOptions for the available options.\n * @constructor\n * @extends Core\n */\n function Timeline(container, items, groups, options) {\n if (!(this instanceof Timeline)) {\n throw new SyntaxError('Constructor must be called with the new operator');\n }\n\n // if the third element is options, the forth is groups (optionally);\n if (!(Array.isArray(groups) || groups instanceof DataSet || groups instanceof DataView) && groups instanceof Object) {\n var forthArgument = options;\n options = groups;\n groups = forthArgument;\n }\n\n var me = this;\n this.defaultOptions = {\n start: null,\n end: null,\n\n autoResize: true,\n throttleRedraw: 0, // ms\n\n orientation: {\n axis: 'bottom', // axis orientation: 'bottom', 'top', or 'both'\n item: 'bottom' // not relevant\n },\n\n moment: moment,\n\n width: null,\n height: null,\n maxHeight: null,\n minHeight: null\n };\n this.options = util.deepExtend({}, this.defaultOptions);\n\n // Create the DOM, props, and emitter\n this._create(container);\n\n // all components listed here will be repainted automatically\n this.components = [];\n\n this.body = {\n dom: this.dom,\n domProps: this.props,\n emitter: {\n on: this.on.bind(this),\n off: this.off.bind(this),\n emit: this.emit.bind(this)\n },\n hiddenDates: [],\n util: {\n getScale: function getScale() {\n return me.timeAxis.step.scale;\n },\n getStep: function getStep() {\n return me.timeAxis.step.step;\n },\n\n toScreen: me._toScreen.bind(me),\n toGlobalScreen: me._toGlobalScreen.bind(me), // this refers to the root.width\n toTime: me._toTime.bind(me),\n toGlobalTime: me._toGlobalTime.bind(me)\n }\n };\n\n // range\n this.range = new Range(this.body);\n this.components.push(this.range);\n this.body.range = this.range;\n\n // time axis\n this.timeAxis = new TimeAxis(this.body);\n this.timeAxis2 = null; // used in case of orientation option 'both'\n this.components.push(this.timeAxis);\n\n // current time bar\n this.currentTime = new CurrentTime(this.body);\n this.components.push(this.currentTime);\n\n // item set\n this.itemSet = new ItemSet(this.body);\n this.components.push(this.itemSet);\n\n this.itemsData = null; // DataSet\n this.groupsData = null; // DataSet\n\n this.on('tap', function (event) {\n me.emit('click', me.getEventProperties(event));\n });\n this.on('doubletap', function (event) {\n me.emit('doubleClick', me.getEventProperties(event));\n });\n this.dom.root.oncontextmenu = function (event) {\n me.emit('contextmenu', me.getEventProperties(event));\n };\n\n //Single time autoscale/fit\n this.fitDone = false;\n this.on('changed', function () {\n if (this.itemsData == null) return;\n if (!me.fitDone) {\n me.fitDone = true;\n if (me.options.start != undefined || me.options.end != undefined) {\n if (me.options.start == undefined || me.options.end == undefined) {\n var range = me.getItemRange();\n }\n\n var start = me.options.start != undefined ? me.options.start : range.min;\n var end = me.options.end != undefined ? me.options.end : range.max;\n\n me.setWindow(start, end, { animation: false });\n } else {\n me.fit({ animation: false });\n }\n }\n });\n\n // apply options\n if (options) {\n this.setOptions(options);\n }\n\n // IMPORTANT: THIS HAPPENS BEFORE SET ITEMS!\n if (groups) {\n this.setGroups(groups);\n }\n\n // create itemset\n if (items) {\n this.setItems(items);\n }\n\n // draw for the first time\n this._redraw();\n }\n\n // Extend the functionality from Core\n Timeline.prototype = new Core();\n\n /**\n * Load a configurator\n * @return {Object}\n * @private\n */\n Timeline.prototype._createConfigurator = function () {\n return new Configurator(this, this.dom.container, configureOptions);\n };\n\n /**\n * Force a redraw. The size of all items will be recalculated.\n * Can be useful to manually redraw when option autoResize=false and the window\n * has been resized, or when the items CSS has been changed.\n *\n * Note: this function will be overridden on construction with a trottled version\n */\n Timeline.prototype.redraw = function () {\n this.itemSet && this.itemSet.markDirty({ refreshItems: true });\n this._redraw();\n };\n\n Timeline.prototype.setOptions = function (options) {\n // validate options\n var errorFound = Validator.validate(options, allOptions);\n if (errorFound === true) {\n console.log('%cErrors have been found in the supplied options object.', printStyle);\n }\n\n Core.prototype.setOptions.call(this, options);\n\n if ('type' in options) {\n if (options.type !== this.options.type) {\n this.options.type = options.type;\n\n // force recreation of all items\n var itemsData = this.itemsData;\n if (itemsData) {\n var selection = this.getSelection();\n this.setItems(null); // remove all\n this.setItems(itemsData); // add all\n this.setSelection(selection); // restore selection\n }\n }\n }\n };\n\n /**\n * Set items\n * @param {vis.DataSet | Array | null} items\n */\n Timeline.prototype.setItems = function (items) {\n // convert to type DataSet when needed\n var newDataSet;\n if (!items) {\n newDataSet = null;\n } else if (items instanceof DataSet || items instanceof DataView) {\n newDataSet = items;\n } else {\n // turn an array into a dataset\n newDataSet = new DataSet(items, {\n type: {\n start: 'Date',\n end: 'Date'\n }\n });\n }\n\n // set items\n this.itemsData = newDataSet;\n this.itemSet && this.itemSet.setItems(newDataSet);\n };\n\n /**\n * Set groups\n * @param {vis.DataSet | Array} groups\n */\n Timeline.prototype.setGroups = function (groups) {\n // convert to type DataSet when needed\n var newDataSet;\n if (!groups) {\n newDataSet = null;\n } else if (groups instanceof DataSet || groups instanceof DataView) {\n newDataSet = groups;\n } else {\n // turn an array into a dataset\n newDataSet = new DataSet(groups);\n }\n\n this.groupsData = newDataSet;\n this.itemSet.setGroups(newDataSet);\n };\n\n /**\n * Set both items and groups in one go\n * @param {{items: Array | vis.DataSet, groups: Array | vis.DataSet}} data\n */\n Timeline.prototype.setData = function (data) {\n if (data && data.groups) {\n this.setGroups(data.groups);\n }\n\n if (data && data.items) {\n this.setItems(data.items);\n }\n };\n\n /**\n * Set selected items by their id. Replaces the current selection\n * Unknown id's are silently ignored.\n * @param {string[] | string} [ids] An array with zero or more id's of the items to be\n * selected. If ids is an empty array, all items will be\n * unselected.\n * @param {Object} [options] Available options:\n * `focus: boolean`\n * If true, focus will be set to the selected item(s)\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n * Only applicable when option focus is true.\n */\n Timeline.prototype.setSelection = function (ids, options) {\n this.itemSet && this.itemSet.setSelection(ids);\n\n if (options && options.focus) {\n this.focus(ids, options);\n }\n };\n\n /**\n * Get the selected items by their id\n * @return {Array} ids The ids of the selected items\n */\n Timeline.prototype.getSelection = function () {\n return this.itemSet && this.itemSet.getSelection() || [];\n };\n\n /**\n * Adjust the visible window such that the selected item (or multiple items)\n * are centered on screen.\n * @param {String | String[]} id An item id or array with item ids\n * @param {Object} [options] Available options:\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n */\n Timeline.prototype.focus = function (id, options) {\n if (!this.itemsData || id == undefined) return;\n\n var ids = Array.isArray(id) ? id : [id];\n\n // get the specified item(s)\n var itemsData = this.itemsData.getDataSet().get(ids, {\n type: {\n start: 'Date',\n end: 'Date'\n }\n });\n\n // calculate minimum start and maximum end of specified items\n var start = null;\n var end = null;\n itemsData.forEach(function (itemData) {\n var s = itemData.start.valueOf();\n var e = 'end' in itemData ? itemData.end.valueOf() : itemData.start.valueOf();\n\n if (start === null || s < start) {\n start = s;\n }\n\n if (end === null || e > end) {\n end = e;\n }\n });\n\n if (start !== null && end !== null) {\n // calculate the new middle and interval for the window\n var middle = (start + end) / 2;\n var interval = Math.max(this.range.end - this.range.start, (end - start) * 1.1);\n\n var animation = options && options.animation !== undefined ? options.animation : true;\n this.range.setRange(middle - interval / 2, middle + interval / 2, animation);\n }\n };\n\n /**\n * Set Timeline window such that it fits all items\n * @param {Object} [options] Available options:\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n */\n Timeline.prototype.fit = function (options) {\n var animation = options && options.animation !== undefined ? options.animation : true;\n var range = this.getItemRange();\n this.range.setRange(range.min, range.max, animation);\n };\n\n /**\n * Determine the range of the items, taking into account their actual width\n * and a margin of 10 pixels on both sides.\n * @return {{min: Date | null, max: Date | null}}\n */\n Timeline.prototype.getItemRange = function () {\n var _this = this;\n\n // get a rough approximation for the range based on the items start and end dates\n var range = this.getDataRange();\n var min = range.min !== null ? range.min.valueOf() : null;\n var max = range.max !== null ? range.max.valueOf() : null;\n var minItem = null;\n var maxItem = null;\n\n if (min != null && max != null) {\n var interval;\n var factor;\n var lhs;\n var rhs;\n var delta;\n\n (function () {\n var getStart = function getStart(item) {\n return util.convert(item.data.start, 'Date').valueOf();\n };\n\n var getEnd = function getEnd(item) {\n var end = item.data.end != undefined ? item.data.end : item.data.start;\n return util.convert(end, 'Date').valueOf();\n }\n\n // calculate the date of the left side and right side of the items given\n ;\n\n interval = max - min;\n // ms\n if (interval <= 0) {\n interval = 10;\n }\n factor = interval / _this.props.center.width;\n util.forEach(_this.itemSet.items, (function (item) {\n item.show();\n item.repositionX();\n\n var start = getStart(item);\n var end = getEnd(item);\n\n var left = start - (item.getWidthLeft() + 10) * factor;\n var right = end + (item.getWidthRight() + 10) * factor;\n\n if (left < min) {\n min = left;\n minItem = item;\n }\n if (right > max) {\n max = right;\n maxItem = item;\n }\n }).bind(_this));\n\n if (minItem && maxItem) {\n lhs = minItem.getWidthLeft() + 10;\n rhs = maxItem.getWidthRight() + 10;\n delta = _this.props.center.width - lhs - rhs;\n // px\n\n if (delta > 0) {\n min = getStart(minItem) - lhs * interval / delta; // ms\n max = getEnd(maxItem) + rhs * interval / delta; // ms\n }\n }\n })();\n }\n\n return {\n min: min != null ? new Date(min) : null,\n max: max != null ? new Date(max) : null\n };\n };\n\n /**\n * Calculate the data range of the items start and end dates\n * @returns {{min: Date | null, max: Date | null}}\n */\n Timeline.prototype.getDataRange = function () {\n var min = null;\n var max = null;\n\n var dataset = this.itemsData && this.itemsData.getDataSet();\n if (dataset) {\n dataset.forEach(function (item) {\n var start = util.convert(item.start, 'Date').valueOf();\n var end = util.convert(item.end != undefined ? item.end : item.start, 'Date').valueOf();\n if (min === null || start < min) {\n min = start;\n }\n if (max === null || end > max) {\n max = end;\n }\n });\n }\n\n return {\n min: min != null ? new Date(min) : null,\n max: max != null ? new Date(max) : null\n };\n };\n\n /**\n * Generate Timeline related information from an event\n * @param {Event} event\n * @return {Object} An object with related information, like on which area\n * The event happened, whether clicked on an item, etc.\n */\n Timeline.prototype.getEventProperties = function (event) {\n var clientX = event.center ? event.center.x : event.clientX;\n var clientY = event.center ? event.center.y : event.clientY;\n var x = clientX - util.getAbsoluteLeft(this.dom.centerContainer);\n var y = clientY - util.getAbsoluteTop(this.dom.centerContainer);\n\n var item = this.itemSet.itemFromTarget(event);\n var group = this.itemSet.groupFromTarget(event);\n var customTime = CustomTime.customTimeFromTarget(event);\n\n var snap = this.itemSet.options.snap || null;\n var scale = this.body.util.getScale();\n var step = this.body.util.getStep();\n var time = this._toTime(x);\n var snappedTime = snap ? snap(time, scale, step) : time;\n\n var element = util.getTarget(event);\n var what = null;\n if (item != null) {\n what = 'item';\n } else if (customTime != null) {\n what = 'custom-time';\n } else if (util.hasParent(element, this.timeAxis.dom.foreground)) {\n what = 'axis';\n } else if (this.timeAxis2 && util.hasParent(element, this.timeAxis2.dom.foreground)) {\n what = 'axis';\n } else if (util.hasParent(element, this.itemSet.dom.labelSet)) {\n what = 'group-label';\n } else if (util.hasParent(element, this.currentTime.bar)) {\n what = 'current-time';\n } else if (util.hasParent(element, this.dom.center)) {\n what = 'background';\n }\n\n return {\n event: event,\n item: item ? item.id : null,\n group: group ? group.groupId : null,\n what: what,\n pageX: event.srcEvent ? event.srcEvent.pageX : event.pageX,\n pageY: event.srcEvent ? event.srcEvent.pageY : event.pageY,\n x: x,\n y: y,\n time: time,\n snappedTime: snappedTime\n };\n };\n\n module.exports = Timeline;\n\n/***/ },\n/* 20 */\n/***/ function(module, exports, __webpack_require__) {\n\n // Only load hammer.js when in a browser environment\n // (loading hammer.js in a node.js environment gives errors)\n 'use strict';\n\n if (typeof window !== 'undefined') {\n var propagating = __webpack_require__(21);\n var Hammer = window['Hammer'] || __webpack_require__(22);\n module.exports = propagating(Hammer, {\n preventDefault: 'mouse'\n });\n } else {\n module.exports = function () {\n throw Error('hammer.js is only available in a browser, not in node.js.');\n };\n }\n\n/***/ },\n/* 21 */\n/***/ function(module, exports, __webpack_require__) {\n\n var __WEBPACK_AMD_DEFINE_FACTORY__, __WEBPACK_AMD_DEFINE_ARRAY__, __WEBPACK_AMD_DEFINE_RESULT__;'use strict';\n\n (function (factory) {\n if (true) {\n // AMD. Register as an anonymous module.\n !(__WEBPACK_AMD_DEFINE_ARRAY__ = [], __WEBPACK_AMD_DEFINE_FACTORY__ = (factory), __WEBPACK_AMD_DEFINE_RESULT__ = (typeof __WEBPACK_AMD_DEFINE_FACTORY__ === 'function' ? (__WEBPACK_AMD_DEFINE_FACTORY__.apply(exports, __WEBPACK_AMD_DEFINE_ARRAY__)) : __WEBPACK_AMD_DEFINE_FACTORY__), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));\n } else if (typeof exports === 'object') {\n // Node. Does not work with strict CommonJS, but\n // only CommonJS-like environments that support module.exports,\n // like Node.\n module.exports = factory();\n } else {\n // Browser globals (root is window)\n window.propagating = factory();\n }\n }(function () {\n var _firstTarget = null; // singleton, will contain the target element where the touch event started\n var _processing = false; // singleton, true when a touch event is being handled\n\n /**\n * Extend an Hammer.js instance with event propagation.\n *\n * Features:\n * - Events emitted by hammer will propagate in order from child to parent\n * elements.\n * - Events are extended with a function `event.stopPropagation()` to stop\n * propagation to parent elements.\n * - An option `preventDefault` to stop all default browser behavior.\n *\n * Usage:\n * var hammer = propagatingHammer(new Hammer(element));\n * var hammer = propagatingHammer(new Hammer(element), {preventDefault: true});\n *\n * @param {Hammer.Manager} hammer An hammer instance.\n * @param {Object} [options] Available options:\n * - `preventDefault: true | 'mouse' | 'touch' | 'pen'`.\n * Enforce preventing the default browser behavior.\n * Cannot be set to `false`.\n * @return {Hammer.Manager} Returns the same hammer instance with extended\n * functionality\n */\n return function propagating(hammer, options) {\n var _options = options || {\n preventDefault: false\n };\n\n if (hammer.Manager) {\n // This looks like the Hammer constructor.\n // Overload the constructors with our own.\n var Hammer = hammer;\n\n var PropagatingHammer = function(element, options) {\n var o = Object.create(_options);\n if (options) Hammer.assign(o, options);\n return propagating(new Hammer(element, o), o);\n };\n Hammer.assign(PropagatingHammer, Hammer);\n\n PropagatingHammer.Manager = function (element, options) {\n var o = Object.create(_options);\n if (options) Hammer.assign(o, options);\n return propagating(new Hammer.Manager(element, o), o);\n };\n\n return PropagatingHammer;\n }\n\n // create a wrapper object which will override the functions\n // `on`, `off`, `destroy`, and `emit` of the hammer instance\n var wrapper = Object.create(hammer);\n\n // attach to DOM element\n var element = hammer.element;\n\n if(!element.hammer) element.hammer = [];\n element.hammer.push(wrapper);\n\n // register an event to catch the start of a gesture and store the\n // target in a singleton\n hammer.on('hammer.input', function (event) {\n if (_options.preventDefault === true || (_options.preventDefault === event.pointerType)) {\n event.preventDefault();\n }\n if (event.isFirst) {\n _firstTarget = event.target;\n }\n });\n\n /** @type {Object.<String, Array.<function>>} */\n wrapper._handlers = {};\n\n /**\n * Register a handler for one or multiple events\n * @param {String} events A space separated string with events\n * @param {function} handler A callback function, called as handler(event)\n * @returns {Hammer.Manager} Returns the hammer instance\n */\n wrapper.on = function (events, handler) {\n // register the handler\n split(events).forEach(function (event) {\n var _handlers = wrapper._handlers[event];\n if (!_handlers) {\n wrapper._handlers[event] = _handlers = [];\n\n // register the static, propagated handler\n hammer.on(event, propagatedHandler);\n }\n _handlers.push(handler);\n });\n\n return wrapper;\n };\n\n /**\n * Unregister a handler for one or multiple events\n * @param {String} events A space separated string with events\n * @param {function} [handler] Optional. The registered handler. If not\n * provided, all handlers for given events\n * are removed.\n * @returns {Hammer.Manager} Returns the hammer instance\n */\n wrapper.off = function (events, handler) {\n // unregister the handler\n split(events).forEach(function (event) {\n var _handlers = wrapper._handlers[event];\n if (_handlers) {\n _handlers = handler ? _handlers.filter(function (h) {\n return h !== handler;\n }) : [];\n\n if (_handlers.length > 0) {\n wrapper._handlers[event] = _handlers;\n }\n else {\n // remove static, propagated handler\n hammer.off(event, propagatedHandler);\n delete wrapper._handlers[event];\n }\n }\n });\n\n return wrapper;\n };\n\n /**\n * Emit to the event listeners\n * @param {string} eventType\n * @param {Event} event\n */\n wrapper.emit = function(eventType, event) {\n _firstTarget = event.target;\n hammer.emit(eventType, event);\n };\n\n wrapper.destroy = function () {\n // Detach from DOM element\n var hammers = hammer.element.hammer;\n var idx = hammers.indexOf(wrapper);\n if(idx !== -1) hammers.splice(idx,1);\n if(!hammers.length) delete hammer.element.hammer;\n\n // clear all handlers\n wrapper._handlers = {};\n\n // call original hammer destroy\n hammer.destroy();\n };\n\n // split a string with space separated words\n function split(events) {\n return events.match(/[^ ]+/g);\n }\n\n /**\n * A static event handler, applying event propagation.\n * @param {Object} event\n */\n function propagatedHandler(event) {\n // let only a single hammer instance handle this event\n if (event.type !== 'hammer.input') {\n // it is possible that the same srcEvent is used with multiple hammer events,\n // we keep track on which events are handled in an object _handled\n if (!event.srcEvent._handled) {\n event.srcEvent._handled = {};\n }\n\n if (event.srcEvent._handled[event.type]) {\n return;\n }\n else {\n event.srcEvent._handled[event.type] = true;\n }\n }\n\n // attach a stopPropagation function to the event\n var stopped = false;\n event.stopPropagation = function () {\n stopped = true;\n };\n\n //wrap the srcEvent's stopPropagation to also stop hammer propagation:\n var srcStop = event.srcEvent.stopPropagation;\n if(typeof srcStop == \"function\") {\n event.srcEvent.stopPropagation = function(){\n srcStop();\n event.stopPropagation();\n }\n }\n\n // attach firstTarget property to the event\n event.firstTarget = _firstTarget;\n\n // propagate over all elements (until stopped)\n var elem = _firstTarget;\n while (elem && !stopped) {\n var elemHammer = elem.hammer;\n if(elemHammer){\n var _handlers;\n for(var k = 0; k < elemHammer.length; k++){\n _handlers = elemHammer[k]._handlers[event.type];\n if(_handlers) for (var i = 0; i < _handlers.length && !stopped; i++) {\n _handlers[i](event);\n }\n }\n }\n elem = elem.parentNode;\n }\n }\n\n return wrapper;\n };\n }));\n\n\n/***/ },\n/* 22 */\n/***/ function(module, exports, __webpack_require__) {\n\n var __WEBPACK_AMD_DEFINE_RESULT__;/*! Hammer.JS - v2.0.6 - 2015-12-23\n * http://hammerjs.github.io/\n *\n * Copyright (c) 2015 Jorik Tangelder;\n * Licensed under the license */\n (function(window, document, exportName, undefined) {\n 'use strict';\n\n var VENDOR_PREFIXES = ['', 'webkit', 'Moz', 'MS', 'ms', 'o'];\n var TEST_ELEMENT = document.createElement('div');\n\n var TYPE_FUNCTION = 'function';\n\n var round = Math.round;\n var abs = Math.abs;\n var now = Date.now;\n\n /**\n * set a timeout with a given scope\n * @param {Function} fn\n * @param {Number} timeout\n * @param {Object} context\n * @returns {number}\n */\n function setTimeoutContext(fn, timeout, context) {\n return setTimeout(bindFn(fn, context), timeout);\n }\n\n /**\n * if the argument is an array, we want to execute the fn on each entry\n * if it aint an array we don't want to do a thing.\n * this is used by all the methods that accept a single and array argument.\n * @param {*|Array} arg\n * @param {String} fn\n * @param {Object} [context]\n * @returns {Boolean}\n */\n function invokeArrayArg(arg, fn, context) {\n if (Array.isArray(arg)) {\n each(arg, context[fn], context);\n return true;\n }\n return false;\n }\n\n /**\n * walk objects and arrays\n * @param {Object} obj\n * @param {Function} iterator\n * @param {Object} context\n */\n function each(obj, iterator, context) {\n var i;\n\n if (!obj) {\n return;\n }\n\n if (obj.forEach) {\n obj.forEach(iterator, context);\n } else if (obj.length !== undefined) {\n i = 0;\n while (i < obj.length) {\n iterator.call(context, obj[i], i, obj);\n i++;\n }\n } else {\n for (i in obj) {\n obj.hasOwnProperty(i) && iterator.call(context, obj[i], i, obj);\n }\n }\n }\n\n /**\n * wrap a method with a deprecation warning and stack trace\n * @param {Function} method\n * @param {String} name\n * @param {String} message\n * @returns {Function} A new function wrapping the supplied method.\n */\n function deprecate(method, name, message) {\n var deprecationMessage = 'DEPRECATED METHOD: ' + name + '\\n' + message + ' AT \\n';\n return function() {\n var e = new Error('get-stack-trace');\n var stack = e && e.stack ? e.stack.replace(/^[^\\(]+?[\\n$]/gm, '')\n .replace(/^\\s+at\\s+/gm, '')\n .replace(/^Object.<anonymous>\\s*\\(/gm, '{anonymous}()@') : 'Unknown Stack Trace';\n\n var log = window.console && (window.console.warn || window.console.log);\n if (log) {\n log.call(window.console, deprecationMessage, stack);\n }\n return method.apply(this, arguments);\n };\n }\n\n /**\n * extend object.\n * means that properties in dest will be overwritten by the ones in src.\n * @param {Object} target\n * @param {...Object} objects_to_assign\n * @returns {Object} target\n */\n var assign;\n if (typeof Object.assign !== 'function') {\n assign = function assign(target) {\n if (target === undefined || target === null) {\n throw new TypeError('Cannot convert undefined or null to object');\n }\n\n var output = Object(target);\n for (var index = 1; index < arguments.length; index++) {\n var source = arguments[index];\n if (source !== undefined && source !== null) {\n for (var nextKey in source) {\n if (source.hasOwnProperty(nextKey)) {\n output[nextKey] = source[nextKey];\n }\n }\n }\n }\n return output;\n };\n } else {\n assign = Object.assign;\n }\n\n /**\n * extend object.\n * means that properties in dest will be overwritten by the ones in src.\n * @param {Object} dest\n * @param {Object} src\n * @param {Boolean=false} [merge]\n * @returns {Object} dest\n */\n var extend = deprecate(function extend(dest, src, merge) {\n var keys = Object.keys(src);\n var i = 0;\n while (i < keys.length) {\n if (!merge || (merge && dest[keys[i]] === undefined)) {\n dest[keys[i]] = src[keys[i]];\n }\n i++;\n }\n return dest;\n }, 'extend', 'Use `assign`.');\n\n /**\n * merge the values from src in the dest.\n * means that properties that exist in dest will not be overwritten by src\n * @param {Object} dest\n * @param {Object} src\n * @returns {Object} dest\n */\n var merge = deprecate(function merge(dest, src) {\n return extend(dest, src, true);\n }, 'merge', 'Use `assign`.');\n\n /**\n * simple class inheritance\n * @param {Function} child\n * @param {Function} base\n * @param {Object} [properties]\n */\n function inherit(child, base, properties) {\n var baseP = base.prototype,\n childP;\n\n childP = child.prototype = Object.create(baseP);\n childP.constructor = child;\n childP._super = baseP;\n\n if (properties) {\n assign(childP, properties);\n }\n }\n\n /**\n * simple function bind\n * @param {Function} fn\n * @param {Object} context\n * @returns {Function}\n */\n function bindFn(fn, context) {\n return function boundFn() {\n return fn.apply(context, arguments);\n };\n }\n\n /**\n * let a boolean value also be a function that must return a boolean\n * this first item in args will be used as the context\n * @param {Boolean|Function} val\n * @param {Array} [args]\n * @returns {Boolean}\n */\n function boolOrFn(val, args) {\n if (typeof val == TYPE_FUNCTION) {\n return val.apply(args ? args[0] || undefined : undefined, args);\n }\n return val;\n }\n\n /**\n * use the val2 when val1 is undefined\n * @param {*} val1\n * @param {*} val2\n * @returns {*}\n */\n function ifUndefined(val1, val2) {\n return (val1 === undefined) ? val2 : val1;\n }\n\n /**\n * addEventListener with multiple events at once\n * @param {EventTarget} target\n * @param {String} types\n * @param {Function} handler\n */\n function addEventListeners(target, types, handler) {\n each(splitStr(types), function(type) {\n target.addEventListener(type, handler, false);\n });\n }\n\n /**\n * removeEventListener with multiple events at once\n * @param {EventTarget} target\n * @param {String} types\n * @param {Function} handler\n */\n function removeEventListeners(target, types, handler) {\n each(splitStr(types), function(type) {\n target.removeEventListener(type, handler, false);\n });\n }\n\n /**\n * find if a node is in the given parent\n * @method hasParent\n * @param {HTMLElement} node\n * @param {HTMLElement} parent\n * @return {Boolean} found\n */\n function hasParent(node, parent) {\n while (node) {\n if (node == parent) {\n return true;\n }\n node = node.parentNode;\n }\n return false;\n }\n\n /**\n * small indexOf wrapper\n * @param {String} str\n * @param {String} find\n * @returns {Boolean} found\n */\n function inStr(str, find) {\n return str.indexOf(find) > -1;\n }\n\n /**\n * split string on whitespace\n * @param {String} str\n * @returns {Array} words\n */\n function splitStr(str) {\n return str.trim().split(/\\s+/g);\n }\n\n /**\n * find if a array contains the object using indexOf or a simple polyFill\n * @param {Array} src\n * @param {String} find\n * @param {String} [findByKey]\n * @return {Boolean|Number} false when not found, or the index\n */\n function inArray(src, find, findByKey) {\n if (src.indexOf && !findByKey) {\n return src.indexOf(find);\n } else {\n var i = 0;\n while (i < src.length) {\n if ((findByKey && src[i][findByKey] == find) || (!findByKey && src[i] === find)) {\n return i;\n }\n i++;\n }\n return -1;\n }\n }\n\n /**\n * convert array-like objects to real arrays\n * @param {Object} obj\n * @returns {Array}\n */\n function toArray(obj) {\n return Array.prototype.slice.call(obj, 0);\n }\n\n /**\n * unique array with objects based on a key (like 'id') or just by the array's value\n * @param {Array} src [{id:1},{id:2},{id:1}]\n * @param {String} [key]\n * @param {Boolean} [sort=False]\n * @returns {Array} [{id:1},{id:2}]\n */\n function uniqueArray(src, key, sort) {\n var results = [];\n var values = [];\n var i = 0;\n\n while (i < src.length) {\n var val = key ? src[i][key] : src[i];\n if (inArray(values, val) < 0) {\n results.push(src[i]);\n }\n values[i] = val;\n i++;\n }\n\n if (sort) {\n if (!key) {\n results = results.sort();\n } else {\n results = results.sort(function sortUniqueArray(a, b) {\n return a[key] > b[key];\n });\n }\n }\n\n return results;\n }\n\n /**\n * get the prefixed property\n * @param {Object} obj\n * @param {String} property\n * @returns {String|Undefined} prefixed\n */\n function prefixed(obj, property) {\n var prefix, prop;\n var camelProp = property[0].toUpperCase() + property.slice(1);\n\n var i = 0;\n while (i < VENDOR_PREFIXES.length) {\n prefix = VENDOR_PREFIXES[i];\n prop = (prefix) ? prefix + camelProp : property;\n\n if (prop in obj) {\n return prop;\n }\n i++;\n }\n return undefined;\n }\n\n /**\n * get a unique id\n * @returns {number} uniqueId\n */\n var _uniqueId = 1;\n function uniqueId() {\n return _uniqueId++;\n }\n\n /**\n * get the window object of an element\n * @param {HTMLElement} element\n * @returns {DocumentView|Window}\n */\n function getWindowForElement(element) {\n var doc = element.ownerDocument || element;\n return (doc.defaultView || doc.parentWindow || window);\n }\n\n var MOBILE_REGEX = /mobile|tablet|ip(ad|hone|od)|android/i;\n\n var SUPPORT_TOUCH = ('ontouchstart' in window);\n var SUPPORT_POINTER_EVENTS = prefixed(window, 'PointerEvent') !== undefined;\n var SUPPORT_ONLY_TOUCH = SUPPORT_TOUCH && MOBILE_REGEX.test(navigator.userAgent);\n\n var INPUT_TYPE_TOUCH = 'touch';\n var INPUT_TYPE_PEN = 'pen';\n var INPUT_TYPE_MOUSE = 'mouse';\n var INPUT_TYPE_KINECT = 'kinect';\n\n var COMPUTE_INTERVAL = 25;\n\n var INPUT_START = 1;\n var INPUT_MOVE = 2;\n var INPUT_END = 4;\n var INPUT_CANCEL = 8;\n\n var DIRECTION_NONE = 1;\n var DIRECTION_LEFT = 2;\n var DIRECTION_RIGHT = 4;\n var DIRECTION_UP = 8;\n var DIRECTION_DOWN = 16;\n\n var DIRECTION_HORIZONTAL = DIRECTION_LEFT | DIRECTION_RIGHT;\n var DIRECTION_VERTICAL = DIRECTION_UP | DIRECTION_DOWN;\n var DIRECTION_ALL = DIRECTION_HORIZONTAL | DIRECTION_VERTICAL;\n\n var PROPS_XY = ['x', 'y'];\n var PROPS_CLIENT_XY = ['clientX', 'clientY'];\n\n /**\n * create new input type manager\n * @param {Manager} manager\n * @param {Function} callback\n * @returns {Input}\n * @constructor\n */\n function Input(manager, callback) {\n var self = this;\n this.manager = manager;\n this.callback = callback;\n this.element = manager.element;\n this.target = manager.options.inputTarget;\n\n // smaller wrapper around the handler, for the scope and the enabled state of the manager,\n // so when disabled the input events are completely bypassed.\n this.domHandler = function(ev) {\n if (boolOrFn(manager.options.enable, [manager])) {\n self.handler(ev);\n }\n };\n\n this.init();\n\n }\n\n Input.prototype = {\n /**\n * should handle the inputEvent data and trigger the callback\n * @virtual\n */\n handler: function() { },\n\n /**\n * bind the events\n */\n init: function() {\n this.evEl && addEventListeners(this.element, this.evEl, this.domHandler);\n this.evTarget && addEventListeners(this.target, this.evTarget, this.domHandler);\n this.evWin && addEventListeners(getWindowForElement(this.element), this.evWin, this.domHandler);\n },\n\n /**\n * unbind the events\n */\n destroy: function() {\n this.evEl && removeEventListeners(this.element, this.evEl, this.domHandler);\n this.evTarget && removeEventListeners(this.target, this.evTarget, this.domHandler);\n this.evWin && removeEventListeners(getWindowForElement(this.element), this.evWin, this.domHandler);\n }\n };\n\n /**\n * create new input type manager\n * called by the Manager constructor\n * @param {Hammer} manager\n * @returns {Input}\n */\n function createInputInstance(manager) {\n var Type;\n var inputClass = manager.options.inputClass;\n\n if (inputClass) {\n Type = inputClass;\n } else if (SUPPORT_POINTER_EVENTS) {\n Type = PointerEventInput;\n } else if (SUPPORT_ONLY_TOUCH) {\n Type = TouchInput;\n } else if (!SUPPORT_TOUCH) {\n Type = MouseInput;\n } else {\n Type = TouchMouseInput;\n }\n return new (Type)(manager, inputHandler);\n }\n\n /**\n * handle input events\n * @param {Manager} manager\n * @param {String} eventType\n * @param {Object} input\n */\n function inputHandler(manager, eventType, input) {\n var pointersLen = input.pointers.length;\n var changedPointersLen = input.changedPointers.length;\n var isFirst = (eventType & INPUT_START && (pointersLen - changedPointersLen === 0));\n var isFinal = (eventType & (INPUT_END | INPUT_CANCEL) && (pointersLen - changedPointersLen === 0));\n\n input.isFirst = !!isFirst;\n input.isFinal = !!isFinal;\n\n if (isFirst) {\n manager.session = {};\n }\n\n // source event is the normalized value of the domEvents\n // like 'touchstart, mouseup, pointerdown'\n input.eventType = eventType;\n\n // compute scale, rotation etc\n computeInputData(manager, input);\n\n // emit secret event\n manager.emit('hammer.input', input);\n\n manager.recognize(input);\n manager.session.prevInput = input;\n }\n\n /**\n * extend the data with some usable properties like scale, rotate, velocity etc\n * @param {Object} manager\n * @param {Object} input\n */\n function computeInputData(manager, input) {\n var session = manager.session;\n var pointers = input.pointers;\n var pointersLength = pointers.length;\n\n // store the first input to calculate the distance and direction\n if (!session.firstInput) {\n session.firstInput = simpleCloneInputData(input);\n }\n\n // to compute scale and rotation we need to store the multiple touches\n if (pointersLength > 1 && !session.firstMultiple) {\n session.firstMultiple = simpleCloneInputData(input);\n } else if (pointersLength === 1) {\n session.firstMultiple = false;\n }\n\n var firstInput = session.firstInput;\n var firstMultiple = session.firstMultiple;\n var offsetCenter = firstMultiple ? firstMultiple.center : firstInput.center;\n\n var center = input.center = getCenter(pointers);\n input.timeStamp = now();\n input.deltaTime = input.timeStamp - firstInput.timeStamp;\n\n input.angle = getAngle(offsetCenter, center);\n input.distance = getDistance(offsetCenter, center);\n\n computeDeltaXY(session, input);\n input.offsetDirection = getDirection(input.deltaX, input.deltaY);\n\n var overallVelocity = getVelocity(input.deltaTime, input.deltaX, input.deltaY);\n input.overallVelocityX = overallVelocity.x;\n input.overallVelocityY = overallVelocity.y;\n input.overallVelocity = (abs(overallVelocity.x) > abs(overallVelocity.y)) ? overallVelocity.x : overallVelocity.y;\n\n input.scale = firstMultiple ? getScale(firstMultiple.pointers, pointers) : 1;\n input.rotation = firstMultiple ? getRotation(firstMultiple.pointers, pointers) : 0;\n\n input.maxPointers = !session.prevInput ? input.pointers.length : ((input.pointers.length >\n session.prevInput.maxPointers) ? input.pointers.length : session.prevInput.maxPointers);\n\n computeIntervalInputData(session, input);\n\n // find the correct target\n var target = manager.element;\n if (hasParent(input.srcEvent.target, target)) {\n target = input.srcEvent.target;\n }\n input.target = target;\n }\n\n function computeDeltaXY(session, input) {\n var center = input.center;\n var offset = session.offsetDelta || {};\n var prevDelta = session.prevDelta || {};\n var prevInput = session.prevInput || {};\n\n if (input.eventType === INPUT_START || prevInput.eventType === INPUT_END) {\n prevDelta = session.prevDelta = {\n x: prevInput.deltaX || 0,\n y: prevInput.deltaY || 0\n };\n\n offset = session.offsetDelta = {\n x: center.x,\n y: center.y\n };\n }\n\n input.deltaX = prevDelta.x + (center.x - offset.x);\n input.deltaY = prevDelta.y + (center.y - offset.y);\n }\n\n /**\n * velocity is calculated every x ms\n * @param {Object} session\n * @param {Object} input\n */\n function computeIntervalInputData(session, input) {\n var last = session.lastInterval || input,\n deltaTime = input.timeStamp - last.timeStamp,\n velocity, velocityX, velocityY, direction;\n\n if (input.eventType != INPUT_CANCEL && (deltaTime > COMPUTE_INTERVAL || last.velocity === undefined)) {\n var deltaX = input.deltaX - last.deltaX;\n var deltaY = input.deltaY - last.deltaY;\n\n var v = getVelocity(deltaTime, deltaX, deltaY);\n velocityX = v.x;\n velocityY = v.y;\n velocity = (abs(v.x) > abs(v.y)) ? v.x : v.y;\n direction = getDirection(deltaX, deltaY);\n\n session.lastInterval = input;\n } else {\n // use latest velocity info if it doesn't overtake a minimum period\n velocity = last.velocity;\n velocityX = last.velocityX;\n velocityY = last.velocityY;\n direction = last.direction;\n }\n\n input.velocity = velocity;\n input.velocityX = velocityX;\n input.velocityY = velocityY;\n input.direction = direction;\n }\n\n /**\n * create a simple clone from the input used for storage of firstInput and firstMultiple\n * @param {Object} input\n * @returns {Object} clonedInputData\n */\n function simpleCloneInputData(input) {\n // make a simple copy of the pointers because we will get a reference if we don't\n // we only need clientXY for the calculations\n var pointers = [];\n var i = 0;\n while (i < input.pointers.length) {\n pointers[i] = {\n clientX: round(input.pointers[i].clientX),\n clientY: round(input.pointers[i].clientY)\n };\n i++;\n }\n\n return {\n timeStamp: now(),\n pointers: pointers,\n center: getCenter(pointers),\n deltaX: input.deltaX,\n deltaY: input.deltaY\n };\n }\n\n /**\n * get the center of all the pointers\n * @param {Array} pointers\n * @return {Object} center contains `x` and `y` properties\n */\n function getCenter(pointers) {\n var pointersLength = pointers.length;\n\n // no need to loop when only one touch\n if (pointersLength === 1) {\n return {\n x: round(pointers[0].clientX),\n y: round(pointers[0].clientY)\n };\n }\n\n var x = 0, y = 0, i = 0;\n while (i < pointersLength) {\n x += pointers[i].clientX;\n y += pointers[i].clientY;\n i++;\n }\n\n return {\n x: round(x / pointersLength),\n y: round(y / pointersLength)\n };\n }\n\n /**\n * calculate the velocity between two points. unit is in px per ms.\n * @param {Number} deltaTime\n * @param {Number} x\n * @param {Number} y\n * @return {Object} velocity `x` and `y`\n */\n function getVelocity(deltaTime, x, y) {\n return {\n x: x / deltaTime || 0,\n y: y / deltaTime || 0\n };\n }\n\n /**\n * get the direction between two points\n * @param {Number} x\n * @param {Number} y\n * @return {Number} direction\n */\n function getDirection(x, y) {\n if (x === y) {\n return DIRECTION_NONE;\n }\n\n if (abs(x) >= abs(y)) {\n return x < 0 ? DIRECTION_LEFT : DIRECTION_RIGHT;\n }\n return y < 0 ? DIRECTION_UP : DIRECTION_DOWN;\n }\n\n /**\n * calculate the absolute distance between two points\n * @param {Object} p1 {x, y}\n * @param {Object} p2 {x, y}\n * @param {Array} [props] containing x and y keys\n * @return {Number} distance\n */\n function getDistance(p1, p2, props) {\n if (!props) {\n props = PROPS_XY;\n }\n var x = p2[props[0]] - p1[props[0]],\n y = p2[props[1]] - p1[props[1]];\n\n return Math.sqrt((x * x) + (y * y));\n }\n\n /**\n * calculate the angle between two coordinates\n * @param {Object} p1\n * @param {Object} p2\n * @param {Array} [props] containing x and y keys\n * @return {Number} angle\n */\n function getAngle(p1, p2, props) {\n if (!props) {\n props = PROPS_XY;\n }\n var x = p2[props[0]] - p1[props[0]],\n y = p2[props[1]] - p1[props[1]];\n return Math.atan2(y, x) * 180 / Math.PI;\n }\n\n /**\n * calculate the rotation degrees between two pointersets\n * @param {Array} start array of pointers\n * @param {Array} end array of pointers\n * @return {Number} rotation\n */\n function getRotation(start, end) {\n return getAngle(end[1], end[0], PROPS_CLIENT_XY) + getAngle(start[1], start[0], PROPS_CLIENT_XY);\n }\n\n /**\n * calculate the scale factor between two pointersets\n * no scale is 1, and goes down to 0 when pinched together, and bigger when pinched out\n * @param {Array} start array of pointers\n * @param {Array} end array of pointers\n * @return {Number} scale\n */\n function getScale(start, end) {\n return getDistance(end[0], end[1], PROPS_CLIENT_XY) / getDistance(start[0], start[1], PROPS_CLIENT_XY);\n }\n\n var MOUSE_INPUT_MAP = {\n mousedown: INPUT_START,\n mousemove: INPUT_MOVE,\n mouseup: INPUT_END\n };\n\n var MOUSE_ELEMENT_EVENTS = 'mousedown';\n var MOUSE_WINDOW_EVENTS = 'mousemove mouseup';\n\n /**\n * Mouse events input\n * @constructor\n * @extends Input\n */\n function MouseInput() {\n this.evEl = MOUSE_ELEMENT_EVENTS;\n this.evWin = MOUSE_WINDOW_EVENTS;\n\n this.allow = true; // used by Input.TouchMouse to disable mouse events\n this.pressed = false; // mousedown state\n\n Input.apply(this, arguments);\n }\n\n inherit(MouseInput, Input, {\n /**\n * handle mouse events\n * @param {Object} ev\n */\n handler: function MEhandler(ev) {\n var eventType = MOUSE_INPUT_MAP[ev.type];\n\n // on start we want to have the left mouse button down\n if (eventType & INPUT_START && ev.button === 0) {\n this.pressed = true;\n }\n\n if (eventType & INPUT_MOVE && ev.which !== 1) {\n eventType = INPUT_END;\n }\n\n // mouse must be down, and mouse events are allowed (see the TouchMouse input)\n if (!this.pressed || !this.allow) {\n return;\n }\n\n if (eventType & INPUT_END) {\n this.pressed = false;\n }\n\n this.callback(this.manager, eventType, {\n pointers: [ev],\n changedPointers: [ev],\n pointerType: INPUT_TYPE_MOUSE,\n srcEvent: ev\n });\n }\n });\n\n var POINTER_INPUT_MAP = {\n pointerdown: INPUT_START,\n pointermove: INPUT_MOVE,\n pointerup: INPUT_END,\n pointercancel: INPUT_CANCEL,\n pointerout: INPUT_CANCEL\n };\n\n // in IE10 the pointer types is defined as an enum\n var IE10_POINTER_TYPE_ENUM = {\n 2: INPUT_TYPE_TOUCH,\n 3: INPUT_TYPE_PEN,\n 4: INPUT_TYPE_MOUSE,\n 5: INPUT_TYPE_KINECT // see https://twitter.com/jacobrossi/status/480596438489890816\n };\n\n var POINTER_ELEMENT_EVENTS = 'pointerdown';\n var POINTER_WINDOW_EVENTS = 'pointermove pointerup pointercancel';\n\n // IE10 has prefixed support, and case-sensitive\n if (window.MSPointerEvent && !window.PointerEvent) {\n POINTER_ELEMENT_EVENTS = 'MSPointerDown';\n POINTER_WINDOW_EVENTS = 'MSPointerMove MSPointerUp MSPointerCancel';\n }\n\n /**\n * Pointer events input\n * @constructor\n * @extends Input\n */\n function PointerEventInput() {\n this.evEl = POINTER_ELEMENT_EVENTS;\n this.evWin = POINTER_WINDOW_EVENTS;\n\n Input.apply(this, arguments);\n\n this.store = (this.manager.session.pointerEvents = []);\n }\n\n inherit(PointerEventInput, Input, {\n /**\n * handle mouse events\n * @param {Object} ev\n */\n handler: function PEhandler(ev) {\n var store = this.store;\n var removePointer = false;\n\n var eventTypeNormalized = ev.type.toLowerCase().replace('ms', '');\n var eventType = POINTER_INPUT_MAP[eventTypeNormalized];\n var pointerType = IE10_POINTER_TYPE_ENUM[ev.pointerType] || ev.pointerType;\n\n var isTouch = (pointerType == INPUT_TYPE_TOUCH);\n\n // get index of the event in the store\n var storeIndex = inArray(store, ev.pointerId, 'pointerId');\n\n // start and mouse must be down\n if (eventType & INPUT_START && (ev.button === 0 || isTouch)) {\n if (storeIndex < 0) {\n store.push(ev);\n storeIndex = store.length - 1;\n }\n } else if (eventType & (INPUT_END | INPUT_CANCEL)) {\n removePointer = true;\n }\n\n // it not found, so the pointer hasn't been down (so it's probably a hover)\n if (storeIndex < 0) {\n return;\n }\n\n // update the event in the store\n store[storeIndex] = ev;\n\n this.callback(this.manager, eventType, {\n pointers: store,\n changedPointers: [ev],\n pointerType: pointerType,\n srcEvent: ev\n });\n\n if (removePointer) {\n // remove from the store\n store.splice(storeIndex, 1);\n }\n }\n });\n\n var SINGLE_TOUCH_INPUT_MAP = {\n touchstart: INPUT_START,\n touchmove: INPUT_MOVE,\n touchend: INPUT_END,\n touchcancel: INPUT_CANCEL\n };\n\n var SINGLE_TOUCH_TARGET_EVENTS = 'touchstart';\n var SINGLE_TOUCH_WINDOW_EVENTS = 'touchstart touchmove touchend touchcancel';\n\n /**\n * Touch events input\n * @constructor\n * @extends Input\n */\n function SingleTouchInput() {\n this.evTarget = SINGLE_TOUCH_TARGET_EVENTS;\n this.evWin = SINGLE_TOUCH_WINDOW_EVENTS;\n this.started = false;\n\n Input.apply(this, arguments);\n }\n\n inherit(SingleTouchInput, Input, {\n handler: function TEhandler(ev) {\n var type = SINGLE_TOUCH_INPUT_MAP[ev.type];\n\n // should we handle the touch events?\n if (type === INPUT_START) {\n this.started = true;\n }\n\n if (!this.started) {\n return;\n }\n\n var touches = normalizeSingleTouches.call(this, ev, type);\n\n // when done, reset the started state\n if (type & (INPUT_END | INPUT_CANCEL) && touches[0].length - touches[1].length === 0) {\n this.started = false;\n }\n\n this.callback(this.manager, type, {\n pointers: touches[0],\n changedPointers: touches[1],\n pointerType: INPUT_TYPE_TOUCH,\n srcEvent: ev\n });\n }\n });\n\n /**\n * @this {TouchInput}\n * @param {Object} ev\n * @param {Number} type flag\n * @returns {undefined|Array} [all, changed]\n */\n function normalizeSingleTouches(ev, type) {\n var all = toArray(ev.touches);\n var changed = toArray(ev.changedTouches);\n\n if (type & (INPUT_END | INPUT_CANCEL)) {\n all = uniqueArray(all.concat(changed), 'identifier', true);\n }\n\n return [all, changed];\n }\n\n var TOUCH_INPUT_MAP = {\n touchstart: INPUT_START,\n touchmove: INPUT_MOVE,\n touchend: INPUT_END,\n touchcancel: INPUT_CANCEL\n };\n\n var TOUCH_TARGET_EVENTS = 'touchstart touchmove touchend touchcancel';\n\n /**\n * Multi-user touch events input\n * @constructor\n * @extends Input\n */\n function TouchInput() {\n this.evTarget = TOUCH_TARGET_EVENTS;\n this.targetIds = {};\n\n Input.apply(this, arguments);\n }\n\n inherit(TouchInput, Input, {\n handler: function MTEhandler(ev) {\n var type = TOUCH_INPUT_MAP[ev.type];\n var touches = getTouches.call(this, ev, type);\n if (!touches) {\n return;\n }\n\n this.callback(this.manager, type, {\n pointers: touches[0],\n changedPointers: touches[1],\n pointerType: INPUT_TYPE_TOUCH,\n srcEvent: ev\n });\n }\n });\n\n /**\n * @this {TouchInput}\n * @param {Object} ev\n * @param {Number} type flag\n * @returns {undefined|Array} [all, changed]\n */\n function getTouches(ev, type) {\n var allTouches = toArray(ev.touches);\n var targetIds = this.targetIds;\n\n // when there is only one touch, the process can be simplified\n if (type & (INPUT_START | INPUT_MOVE) && allTouches.length === 1) {\n targetIds[allTouches[0].identifier] = true;\n return [allTouches, allTouches];\n }\n\n var i,\n targetTouches,\n changedTouches = toArray(ev.changedTouches),\n changedTargetTouches = [],\n target = this.target;\n\n // get target touches from touches\n targetTouches = allTouches.filter(function(touch) {\n return hasParent(touch.target, target);\n });\n\n // collect touches\n if (type === INPUT_START) {\n i = 0;\n while (i < targetTouches.length) {\n targetIds[targetTouches[i].identifier] = true;\n i++;\n }\n }\n\n // filter changed touches to only contain touches that exist in the collected target ids\n i = 0;\n while (i < changedTouches.length) {\n if (targetIds[changedTouches[i].identifier]) {\n changedTargetTouches.push(changedTouches[i]);\n }\n\n // cleanup removed touches\n if (type & (INPUT_END | INPUT_CANCEL)) {\n delete targetIds[changedTouches[i].identifier];\n }\n i++;\n }\n\n if (!changedTargetTouches.length) {\n return;\n }\n\n return [\n // merge targetTouches with changedTargetTouches so it contains ALL touches, including 'end' and 'cancel'\n uniqueArray(targetTouches.concat(changedTargetTouches), 'identifier', true),\n changedTargetTouches\n ];\n }\n\n /**\n * Combined touch and mouse input\n *\n * Touch has a higher priority then mouse, and while touching no mouse events are allowed.\n * This because touch devices also emit mouse events while doing a touch.\n *\n * @constructor\n * @extends Input\n */\n function TouchMouseInput() {\n Input.apply(this, arguments);\n\n var handler = bindFn(this.handler, this);\n this.touch = new TouchInput(this.manager, handler);\n this.mouse = new MouseInput(this.manager, handler);\n }\n\n inherit(TouchMouseInput, Input, {\n /**\n * handle mouse and touch events\n * @param {Hammer} manager\n * @param {String} inputEvent\n * @param {Object} inputData\n */\n handler: function TMEhandler(manager, inputEvent, inputData) {\n var isTouch = (inputData.pointerType == INPUT_TYPE_TOUCH),\n isMouse = (inputData.pointerType == INPUT_TYPE_MOUSE);\n\n // when we're in a touch event, so block all upcoming mouse events\n // most mobile browser also emit mouseevents, right after touchstart\n if (isTouch) {\n this.mouse.allow = false;\n } else if (isMouse && !this.mouse.allow) {\n return;\n }\n\n // reset the allowMouse when we're done\n if (inputEvent & (INPUT_END | INPUT_CANCEL)) {\n this.mouse.allow = true;\n }\n\n this.callback(manager, inputEvent, inputData);\n },\n\n /**\n * remove the event listeners\n */\n destroy: function destroy() {\n this.touch.destroy();\n this.mouse.destroy();\n }\n });\n\n var PREFIXED_TOUCH_ACTION = prefixed(TEST_ELEMENT.style, 'touchAction');\n var NATIVE_TOUCH_ACTION = PREFIXED_TOUCH_ACTION !== undefined;\n\n // magical touchAction value\n var TOUCH_ACTION_COMPUTE = 'compute';\n var TOUCH_ACTION_AUTO = 'auto';\n var TOUCH_ACTION_MANIPULATION = 'manipulation'; // not implemented\n var TOUCH_ACTION_NONE = 'none';\n var TOUCH_ACTION_PAN_X = 'pan-x';\n var TOUCH_ACTION_PAN_Y = 'pan-y';\n\n /**\n * Touch Action\n * sets the touchAction property or uses the js alternative\n * @param {Manager} manager\n * @param {String} value\n * @constructor\n */\n function TouchAction(manager, value) {\n this.manager = manager;\n this.set(value);\n }\n\n TouchAction.prototype = {\n /**\n * set the touchAction value on the element or enable the polyfill\n * @param {String} value\n */\n set: function(value) {\n // find out the touch-action by the event handlers\n if (value == TOUCH_ACTION_COMPUTE) {\n value = this.compute();\n }\n\n if (NATIVE_TOUCH_ACTION && this.manager.element.style) {\n this.manager.element.style[PREFIXED_TOUCH_ACTION] = value;\n }\n this.actions = value.toLowerCase().trim();\n },\n\n /**\n * just re-set the touchAction value\n */\n update: function() {\n this.set(this.manager.options.touchAction);\n },\n\n /**\n * compute the value for the touchAction property based on the recognizer's settings\n * @returns {String} value\n */\n compute: function() {\n var actions = [];\n each(this.manager.recognizers, function(recognizer) {\n if (boolOrFn(recognizer.options.enable, [recognizer])) {\n actions = actions.concat(recognizer.getTouchAction());\n }\n });\n return cleanTouchActions(actions.join(' '));\n },\n\n /**\n * this method is called on each input cycle and provides the preventing of the browser behavior\n * @param {Object} input\n */\n preventDefaults: function(input) {\n // not needed with native support for the touchAction property\n if (NATIVE_TOUCH_ACTION) {\n return;\n }\n\n var srcEvent = input.srcEvent;\n var direction = input.offsetDirection;\n\n // if the touch action did prevented once this session\n if (this.manager.session.prevented) {\n srcEvent.preventDefault();\n return;\n }\n\n var actions = this.actions;\n var hasNone = inStr(actions, TOUCH_ACTION_NONE);\n var hasPanY = inStr(actions, TOUCH_ACTION_PAN_Y);\n var hasPanX = inStr(actions, TOUCH_ACTION_PAN_X);\n\n if (hasNone) {\n //do not prevent defaults if this is a tap gesture\n\n var isTapPointer = input.pointers.length === 1;\n var isTapMovement = input.distance < 2;\n var isTapTouchTime = input.deltaTime < 250;\n\n if (isTapPointer && isTapMovement && isTapTouchTime) {\n return;\n }\n }\n\n if (hasPanX && hasPanY) {\n // `pan-x pan-y` means browser handles all scrolling/panning, do not prevent\n return;\n }\n\n if (hasNone ||\n (hasPanY && direction & DIRECTION_HORIZONTAL) ||\n (hasPanX && direction & DIRECTION_VERTICAL)) {\n return this.preventSrc(srcEvent);\n }\n },\n\n /**\n * call preventDefault to prevent the browser's default behavior (scrolling in most cases)\n * @param {Object} srcEvent\n */\n preventSrc: function(srcEvent) {\n this.manager.session.prevented = true;\n srcEvent.preventDefault();\n }\n };\n\n /**\n * when the touchActions are collected they are not a valid value, so we need to clean things up. *\n * @param {String} actions\n * @returns {*}\n */\n function cleanTouchActions(actions) {\n // none\n if (inStr(actions, TOUCH_ACTION_NONE)) {\n return TOUCH_ACTION_NONE;\n }\n\n var hasPanX = inStr(actions, TOUCH_ACTION_PAN_X);\n var hasPanY = inStr(actions, TOUCH_ACTION_PAN_Y);\n\n // if both pan-x and pan-y are set (different recognizers\n // for different directions, e.g. horizontal pan but vertical swipe?)\n // we need none (as otherwise with pan-x pan-y combined none of these\n // recognizers will work, since the browser would handle all panning\n if (hasPanX && hasPanY) {\n return TOUCH_ACTION_NONE;\n }\n\n // pan-x OR pan-y\n if (hasPanX || hasPanY) {\n return hasPanX ? TOUCH_ACTION_PAN_X : TOUCH_ACTION_PAN_Y;\n }\n\n // manipulation\n if (inStr(actions, TOUCH_ACTION_MANIPULATION)) {\n return TOUCH_ACTION_MANIPULATION;\n }\n\n return TOUCH_ACTION_AUTO;\n }\n\n /**\n * Recognizer flow explained; *\n * All recognizers have the initial state of POSSIBLE when a input session starts.\n * The definition of a input session is from the first input until the last input, with all it's movement in it. *\n * Example session for mouse-input: mousedown -> mousemove -> mouseup\n *\n * On each recognizing cycle (see Manager.recognize) the .recognize() method is executed\n * which determines with state it should be.\n *\n * If the recognizer has the state FAILED, CANCELLED or RECOGNIZED (equals ENDED), it is reset to\n * POSSIBLE to give it another change on the next cycle.\n *\n * Possible\n * |\n * +-----+---------------+\n * | |\n * +-----+-----+ |\n * | | |\n * Failed Cancelled |\n * +-------+------+\n * | |\n * Recognized Began\n * |\n * Changed\n * |\n * Ended/Recognized\n */\n var STATE_POSSIBLE = 1;\n var STATE_BEGAN = 2;\n var STATE_CHANGED = 4;\n var STATE_ENDED = 8;\n var STATE_RECOGNIZED = STATE_ENDED;\n var STATE_CANCELLED = 16;\n var STATE_FAILED = 32;\n\n /**\n * Recognizer\n * Every recognizer needs to extend from this class.\n * @constructor\n * @param {Object} options\n */\n function Recognizer(options) {\n this.options = assign({}, this.defaults, options || {});\n\n this.id = uniqueId();\n\n this.manager = null;\n\n // default is enable true\n this.options.enable = ifUndefined(this.options.enable, true);\n\n this.state = STATE_POSSIBLE;\n\n this.simultaneous = {};\n this.requireFail = [];\n }\n\n Recognizer.prototype = {\n /**\n * @virtual\n * @type {Object}\n */\n defaults: {},\n\n /**\n * set options\n * @param {Object} options\n * @return {Recognizer}\n */\n set: function(options) {\n assign(this.options, options);\n\n // also update the touchAction, in case something changed about the directions/enabled state\n this.manager && this.manager.touchAction.update();\n return this;\n },\n\n /**\n * recognize simultaneous with an other recognizer.\n * @param {Recognizer} otherRecognizer\n * @returns {Recognizer} this\n */\n recognizeWith: function(otherRecognizer) {\n if (invokeArrayArg(otherRecognizer, 'recognizeWith', this)) {\n return this;\n }\n\n var simultaneous = this.simultaneous;\n otherRecognizer = getRecognizerByNameIfManager(otherRecognizer, this);\n if (!simultaneous[otherRecognizer.id]) {\n simultaneous[otherRecognizer.id] = otherRecognizer;\n otherRecognizer.recognizeWith(this);\n }\n return this;\n },\n\n /**\n * drop the simultaneous link. it doesnt remove the link on the other recognizer.\n * @param {Recognizer} otherRecognizer\n * @returns {Recognizer} this\n */\n dropRecognizeWith: function(otherRecognizer) {\n if (invokeArrayArg(otherRecognizer, 'dropRecognizeWith', this)) {\n return this;\n }\n\n otherRecognizer = getRecognizerByNameIfManager(otherRecognizer, this);\n delete this.simultaneous[otherRecognizer.id];\n return this;\n },\n\n /**\n * recognizer can only run when an other is failing\n * @param {Recognizer} otherRecognizer\n * @returns {Recognizer} this\n */\n requireFailure: function(otherRecognizer) {\n if (invokeArrayArg(otherRecognizer, 'requireFailure', this)) {\n return this;\n }\n\n var requireFail = this.requireFail;\n otherRecognizer = getRecognizerByNameIfManager(otherRecognizer, this);\n if (inArray(requireFail, otherRecognizer) === -1) {\n requireFail.push(otherRecognizer);\n otherRecognizer.requireFailure(this);\n }\n return this;\n },\n\n /**\n * drop the requireFailure link. it does not remove the link on the other recognizer.\n * @param {Recognizer} otherRecognizer\n * @returns {Recognizer} this\n */\n dropRequireFailure: function(otherRecognizer) {\n if (invokeArrayArg(otherRecognizer, 'dropRequireFailure', this)) {\n return this;\n }\n\n otherRecognizer = getRecognizerByNameIfManager(otherRecognizer, this);\n var index = inArray(this.requireFail, otherRecognizer);\n if (index > -1) {\n this.requireFail.splice(index, 1);\n }\n return this;\n },\n\n /**\n * has require failures boolean\n * @returns {boolean}\n */\n hasRequireFailures: function() {\n return this.requireFail.length > 0;\n },\n\n /**\n * if the recognizer can recognize simultaneous with an other recognizer\n * @param {Recognizer} otherRecognizer\n * @returns {Boolean}\n */\n canRecognizeWith: function(otherRecognizer) {\n return !!this.simultaneous[otherRecognizer.id];\n },\n\n /**\n * You should use `tryEmit` instead of `emit` directly to check\n * that all the needed recognizers has failed before emitting.\n * @param {Object} input\n */\n emit: function(input) {\n var self = this;\n var state = this.state;\n\n function emit(event) {\n self.manager.emit(event, input);\n }\n\n // 'panstart' and 'panmove'\n if (state < STATE_ENDED) {\n emit(self.options.event + stateStr(state));\n }\n\n emit(self.options.event); // simple 'eventName' events\n\n if (input.additionalEvent) { // additional event(panleft, panright, pinchin, pinchout...)\n emit(input.additionalEvent);\n }\n\n // panend and pancancel\n if (state >= STATE_ENDED) {\n emit(self.options.event + stateStr(state));\n }\n },\n\n /**\n * Check that all the require failure recognizers has failed,\n * if true, it emits a gesture event,\n * otherwise, setup the state to FAILED.\n * @param {Object} input\n */\n tryEmit: function(input) {\n if (this.canEmit()) {\n return this.emit(input);\n }\n // it's failing anyway\n this.state = STATE_FAILED;\n },\n\n /**\n * can we emit?\n * @returns {boolean}\n */\n canEmit: function() {\n var i = 0;\n while (i < this.requireFail.length) {\n if (!(this.requireFail[i].state & (STATE_FAILED | STATE_POSSIBLE))) {\n return false;\n }\n i++;\n }\n return true;\n },\n\n /**\n * update the recognizer\n * @param {Object} inputData\n */\n recognize: function(inputData) {\n // make a new copy of the inputData\n // so we can change the inputData without messing up the other recognizers\n var inputDataClone = assign({}, inputData);\n\n // is is enabled and allow recognizing?\n if (!boolOrFn(this.options.enable, [this, inputDataClone])) {\n this.reset();\n this.state = STATE_FAILED;\n return;\n }\n\n // reset when we've reached the end\n if (this.state & (STATE_RECOGNIZED | STATE_CANCELLED | STATE_FAILED)) {\n this.state = STATE_POSSIBLE;\n }\n\n this.state = this.process(inputDataClone);\n\n // the recognizer has recognized a gesture\n // so trigger an event\n if (this.state & (STATE_BEGAN | STATE_CHANGED | STATE_ENDED | STATE_CANCELLED)) {\n this.tryEmit(inputDataClone);\n }\n },\n\n /**\n * return the state of the recognizer\n * the actual recognizing happens in this method\n * @virtual\n * @param {Object} inputData\n * @returns {Const} STATE\n */\n process: function(inputData) { }, // jshint ignore:line\n\n /**\n * return the preferred touch-action\n * @virtual\n * @returns {Array}\n */\n getTouchAction: function() { },\n\n /**\n * called when the gesture isn't allowed to recognize\n * like when another is being recognized or it is disabled\n * @virtual\n */\n reset: function() { }\n };\n\n /**\n * get a usable string, used as event postfix\n * @param {Const} state\n * @returns {String} state\n */\n function stateStr(state) {\n if (state & STATE_CANCELLED) {\n return 'cancel';\n } else if (state & STATE_ENDED) {\n return 'end';\n } else if (state & STATE_CHANGED) {\n return 'move';\n } else if (state & STATE_BEGAN) {\n return 'start';\n }\n return '';\n }\n\n /**\n * direction cons to string\n * @param {Const} direction\n * @returns {String}\n */\n function directionStr(direction) {\n if (direction == DIRECTION_DOWN) {\n return 'down';\n } else if (direction == DIRECTION_UP) {\n return 'up';\n } else if (direction == DIRECTION_LEFT) {\n return 'left';\n } else if (direction == DIRECTION_RIGHT) {\n return 'right';\n }\n return '';\n }\n\n /**\n * get a recognizer by name if it is bound to a manager\n * @param {Recognizer|String} otherRecognizer\n * @param {Recognizer} recognizer\n * @returns {Recognizer}\n */\n function getRecognizerByNameIfManager(otherRecognizer, recognizer) {\n var manager = recognizer.manager;\n if (manager) {\n return manager.get(otherRecognizer);\n }\n return otherRecognizer;\n }\n\n /**\n * This recognizer is just used as a base for the simple attribute recognizers.\n * @constructor\n * @extends Recognizer\n */\n function AttrRecognizer() {\n Recognizer.apply(this, arguments);\n }\n\n inherit(AttrRecognizer, Recognizer, {\n /**\n * @namespace\n * @memberof AttrRecognizer\n */\n defaults: {\n /**\n * @type {Number}\n * @default 1\n */\n pointers: 1\n },\n\n /**\n * Used to check if it the recognizer receives valid input, like input.distance > 10.\n * @memberof AttrRecognizer\n * @param {Object} input\n * @returns {Boolean} recognized\n */\n attrTest: function(input) {\n var optionPointers = this.options.pointers;\n return optionPointers === 0 || input.pointers.length === optionPointers;\n },\n\n /**\n * Process the input and return the state for the recognizer\n * @memberof AttrRecognizer\n * @param {Object} input\n * @returns {*} State\n */\n process: function(input) {\n var state = this.state;\n var eventType = input.eventType;\n\n var isRecognized = state & (STATE_BEGAN | STATE_CHANGED);\n var isValid = this.attrTest(input);\n\n // on cancel input and we've recognized before, return STATE_CANCELLED\n if (isRecognized && (eventType & INPUT_CANCEL || !isValid)) {\n return state | STATE_CANCELLED;\n } else if (isRecognized || isValid) {\n if (eventType & INPUT_END) {\n return state | STATE_ENDED;\n } else if (!(state & STATE_BEGAN)) {\n return STATE_BEGAN;\n }\n return state | STATE_CHANGED;\n }\n return STATE_FAILED;\n }\n });\n\n /**\n * Pan\n * Recognized when the pointer is down and moved in the allowed direction.\n * @constructor\n * @extends AttrRecognizer\n */\n function PanRecognizer() {\n AttrRecognizer.apply(this, arguments);\n\n this.pX = null;\n this.pY = null;\n }\n\n inherit(PanRecognizer, AttrRecognizer, {\n /**\n * @namespace\n * @memberof PanRecognizer\n */\n defaults: {\n event: 'pan',\n threshold: 10,\n pointers: 1,\n direction: DIRECTION_ALL\n },\n\n getTouchAction: function() {\n var direction = this.options.direction;\n var actions = [];\n if (direction & DIRECTION_HORIZONTAL) {\n actions.push(TOUCH_ACTION_PAN_Y);\n }\n if (direction & DIRECTION_VERTICAL) {\n actions.push(TOUCH_ACTION_PAN_X);\n }\n return actions;\n },\n\n directionTest: function(input) {\n var options = this.options;\n var hasMoved = true;\n var distance = input.distance;\n var direction = input.direction;\n var x = input.deltaX;\n var y = input.deltaY;\n\n // lock to axis?\n if (!(direction & options.direction)) {\n if (options.direction & DIRECTION_HORIZONTAL) {\n direction = (x === 0) ? DIRECTION_NONE : (x < 0) ? DIRECTION_LEFT : DIRECTION_RIGHT;\n hasMoved = x != this.pX;\n distance = Math.abs(input.deltaX);\n } else {\n direction = (y === 0) ? DIRECTION_NONE : (y < 0) ? DIRECTION_UP : DIRECTION_DOWN;\n hasMoved = y != this.pY;\n distance = Math.abs(input.deltaY);\n }\n }\n input.direction = direction;\n return hasMoved && distance > options.threshold && direction & options.direction;\n },\n\n attrTest: function(input) {\n return AttrRecognizer.prototype.attrTest.call(this, input) &&\n (this.state & STATE_BEGAN || (!(this.state & STATE_BEGAN) && this.directionTest(input)));\n },\n\n emit: function(input) {\n\n this.pX = input.deltaX;\n this.pY = input.deltaY;\n\n var direction = directionStr(input.direction);\n\n if (direction) {\n input.additionalEvent = this.options.event + direction;\n }\n this._super.emit.call(this, input);\n }\n });\n\n /**\n * Pinch\n * Recognized when two or more pointers are moving toward (zoom-in) or away from each other (zoom-out).\n * @constructor\n * @extends AttrRecognizer\n */\n function PinchRecognizer() {\n AttrRecognizer.apply(this, arguments);\n }\n\n inherit(PinchRecognizer, AttrRecognizer, {\n /**\n * @namespace\n * @memberof PinchRecognizer\n */\n defaults: {\n event: 'pinch',\n threshold: 0,\n pointers: 2\n },\n\n getTouchAction: function() {\n return [TOUCH_ACTION_NONE];\n },\n\n attrTest: function(input) {\n return this._super.attrTest.call(this, input) &&\n (Math.abs(input.scale - 1) > this.options.threshold || this.state & STATE_BEGAN);\n },\n\n emit: function(input) {\n if (input.scale !== 1) {\n var inOut = input.scale < 1 ? 'in' : 'out';\n input.additionalEvent = this.options.event + inOut;\n }\n this._super.emit.call(this, input);\n }\n });\n\n /**\n * Press\n * Recognized when the pointer is down for x ms without any movement.\n * @constructor\n * @extends Recognizer\n */\n function PressRecognizer() {\n Recognizer.apply(this, arguments);\n\n this._timer = null;\n this._input = null;\n }\n\n inherit(PressRecognizer, Recognizer, {\n /**\n * @namespace\n * @memberof PressRecognizer\n */\n defaults: {\n event: 'press',\n pointers: 1,\n time: 251, // minimal time of the pointer to be pressed\n threshold: 9 // a minimal movement is ok, but keep it low\n },\n\n getTouchAction: function() {\n return [TOUCH_ACTION_AUTO];\n },\n\n process: function(input) {\n var options = this.options;\n var validPointers = input.pointers.length === options.pointers;\n var validMovement = input.distance < options.threshold;\n var validTime = input.deltaTime > options.time;\n\n this._input = input;\n\n // we only allow little movement\n // and we've reached an end event, so a tap is possible\n if (!validMovement || !validPointers || (input.eventType & (INPUT_END | INPUT_CANCEL) && !validTime)) {\n this.reset();\n } else if (input.eventType & INPUT_START) {\n this.reset();\n this._timer = setTimeoutContext(function() {\n this.state = STATE_RECOGNIZED;\n this.tryEmit();\n }, options.time, this);\n } else if (input.eventType & INPUT_END) {\n return STATE_RECOGNIZED;\n }\n return STATE_FAILED;\n },\n\n reset: function() {\n clearTimeout(this._timer);\n },\n\n emit: function(input) {\n if (this.state !== STATE_RECOGNIZED) {\n return;\n }\n\n if (input && (input.eventType & INPUT_END)) {\n this.manager.emit(this.options.event + 'up', input);\n } else {\n this._input.timeStamp = now();\n this.manager.emit(this.options.event, this._input);\n }\n }\n });\n\n /**\n * Rotate\n * Recognized when two or more pointer are moving in a circular motion.\n * @constructor\n * @extends AttrRecognizer\n */\n function RotateRecognizer() {\n AttrRecognizer.apply(this, arguments);\n }\n\n inherit(RotateRecognizer, AttrRecognizer, {\n /**\n * @namespace\n * @memberof RotateRecognizer\n */\n defaults: {\n event: 'rotate',\n threshold: 0,\n pointers: 2\n },\n\n getTouchAction: function() {\n return [TOUCH_ACTION_NONE];\n },\n\n attrTest: function(input) {\n return this._super.attrTest.call(this, input) &&\n (Math.abs(input.rotation) > this.options.threshold || this.state & STATE_BEGAN);\n }\n });\n\n /**\n * Swipe\n * Recognized when the pointer is moving fast (velocity), with enough distance in the allowed direction.\n * @constructor\n * @extends AttrRecognizer\n */\n function SwipeRecognizer() {\n AttrRecognizer.apply(this, arguments);\n }\n\n inherit(SwipeRecognizer, AttrRecognizer, {\n /**\n * @namespace\n * @memberof SwipeRecognizer\n */\n defaults: {\n event: 'swipe',\n threshold: 10,\n velocity: 0.3,\n direction: DIRECTION_HORIZONTAL | DIRECTION_VERTICAL,\n pointers: 1\n },\n\n getTouchAction: function() {\n return PanRecognizer.prototype.getTouchAction.call(this);\n },\n\n attrTest: function(input) {\n var direction = this.options.direction;\n var velocity;\n\n if (direction & (DIRECTION_HORIZONTAL | DIRECTION_VERTICAL)) {\n velocity = input.overallVelocity;\n } else if (direction & DIRECTION_HORIZONTAL) {\n velocity = input.overallVelocityX;\n } else if (direction & DIRECTION_VERTICAL) {\n velocity = input.overallVelocityY;\n }\n\n return this._super.attrTest.call(this, input) &&\n direction & input.offsetDirection &&\n input.distance > this.options.threshold &&\n input.maxPointers == this.options.pointers &&\n abs(velocity) > this.options.velocity && input.eventType & INPUT_END;\n },\n\n emit: function(input) {\n var direction = directionStr(input.offsetDirection);\n if (direction) {\n this.manager.emit(this.options.event + direction, input);\n }\n\n this.manager.emit(this.options.event, input);\n }\n });\n\n /**\n * A tap is ecognized when the pointer is doing a small tap/click. Multiple taps are recognized if they occur\n * between the given interval and position. The delay option can be used to recognize multi-taps without firing\n * a single tap.\n *\n * The eventData from the emitted event contains the property `tapCount`, which contains the amount of\n * multi-taps being recognized.\n * @constructor\n * @extends Recognizer\n */\n function TapRecognizer() {\n Recognizer.apply(this, arguments);\n\n // previous time and center,\n // used for tap counting\n this.pTime = false;\n this.pCenter = false;\n\n this._timer = null;\n this._input = null;\n this.count = 0;\n }\n\n inherit(TapRecognizer, Recognizer, {\n /**\n * @namespace\n * @memberof PinchRecognizer\n */\n defaults: {\n event: 'tap',\n pointers: 1,\n taps: 1,\n interval: 300, // max time between the multi-tap taps\n time: 250, // max time of the pointer to be down (like finger on the screen)\n threshold: 9, // a minimal movement is ok, but keep it low\n posThreshold: 10 // a multi-tap can be a bit off the initial position\n },\n\n getTouchAction: function() {\n return [TOUCH_ACTION_MANIPULATION];\n },\n\n process: function(input) {\n var options = this.options;\n\n var validPointers = input.pointers.length === options.pointers;\n var validMovement = input.distance < options.threshold;\n var validTouchTime = input.deltaTime < options.time;\n\n this.reset();\n\n if ((input.eventType & INPUT_START) && (this.count === 0)) {\n return this.failTimeout();\n }\n\n // we only allow little movement\n // and we've reached an end event, so a tap is possible\n if (validMovement && validTouchTime && validPointers) {\n if (input.eventType != INPUT_END) {\n return this.failTimeout();\n }\n\n var validInterval = this.pTime ? (input.timeStamp - this.pTime < options.interval) : true;\n var validMultiTap = !this.pCenter || getDistance(this.pCenter, input.center) < options.posThreshold;\n\n this.pTime = input.timeStamp;\n this.pCenter = input.center;\n\n if (!validMultiTap || !validInterval) {\n this.count = 1;\n } else {\n this.count += 1;\n }\n\n this._input = input;\n\n // if tap count matches we have recognized it,\n // else it has began recognizing...\n var tapCount = this.count % options.taps;\n if (tapCount === 0) {\n // no failing requirements, immediately trigger the tap event\n // or wait as long as the multitap interval to trigger\n if (!this.hasRequireFailures()) {\n return STATE_RECOGNIZED;\n } else {\n this._timer = setTimeoutContext(function() {\n this.state = STATE_RECOGNIZED;\n this.tryEmit();\n }, options.interval, this);\n return STATE_BEGAN;\n }\n }\n }\n return STATE_FAILED;\n },\n\n failTimeout: function() {\n this._timer = setTimeoutContext(function() {\n this.state = STATE_FAILED;\n }, this.options.interval, this);\n return STATE_FAILED;\n },\n\n reset: function() {\n clearTimeout(this._timer);\n },\n\n emit: function() {\n if (this.state == STATE_RECOGNIZED) {\n this._input.tapCount = this.count;\n this.manager.emit(this.options.event, this._input);\n }\n }\n });\n\n /**\n * Simple way to create a manager with a default set of recognizers.\n * @param {HTMLElement} element\n * @param {Object} [options]\n * @constructor\n */\n function Hammer(element, options) {\n options = options || {};\n options.recognizers = ifUndefined(options.recognizers, Hammer.defaults.preset);\n return new Manager(element, options);\n }\n\n /**\n * @const {string}\n */\n Hammer.VERSION = '2.0.6';\n\n /**\n * default settings\n * @namespace\n */\n Hammer.defaults = {\n /**\n * set if DOM events are being triggered.\n * But this is slower and unused by simple implementations, so disabled by default.\n * @type {Boolean}\n * @default false\n */\n domEvents: false,\n\n /**\n * The value for the touchAction property/fallback.\n * When set to `compute` it will magically set the correct value based on the added recognizers.\n * @type {String}\n * @default compute\n */\n touchAction: TOUCH_ACTION_COMPUTE,\n\n /**\n * @type {Boolean}\n * @default true\n */\n enable: true,\n\n /**\n * EXPERIMENTAL FEATURE -- can be removed/changed\n * Change the parent input target element.\n * If Null, then it is being set the to main element.\n * @type {Null|EventTarget}\n * @default null\n */\n inputTarget: null,\n\n /**\n * force an input class\n * @type {Null|Function}\n * @default null\n */\n inputClass: null,\n\n /**\n * Default recognizer setup when calling `Hammer()`\n * When creating a new Manager these will be skipped.\n * @type {Array}\n */\n preset: [\n // RecognizerClass, options, [recognizeWith, ...], [requireFailure, ...]\n [RotateRecognizer, {enable: false}],\n [PinchRecognizer, {enable: false}, ['rotate']],\n [SwipeRecognizer, {direction: DIRECTION_HORIZONTAL}],\n [PanRecognizer, {direction: DIRECTION_HORIZONTAL}, ['swipe']],\n [TapRecognizer],\n [TapRecognizer, {event: 'doubletap', taps: 2}, ['tap']],\n [PressRecognizer]\n ],\n\n /**\n * Some CSS properties can be used to improve the working of Hammer.\n * Add them to this method and they will be set when creating a new Manager.\n * @namespace\n */\n cssProps: {\n /**\n * Disables text selection to improve the dragging gesture. Mainly for desktop browsers.\n * @type {String}\n * @default 'none'\n */\n userSelect: 'none',\n\n /**\n * Disable the Windows Phone grippers when pressing an element.\n * @type {String}\n * @default 'none'\n */\n touchSelect: 'none',\n\n /**\n * Disables the default callout shown when you touch and hold a touch target.\n * On iOS, when you touch and hold a touch target such as a link, Safari displays\n * a callout containing information about the link. This property allows you to disable that callout.\n * @type {String}\n * @default 'none'\n */\n touchCallout: 'none',\n\n /**\n * Specifies whether zooming is enabled. Used by IE10>\n * @type {String}\n * @default 'none'\n */\n contentZooming: 'none',\n\n /**\n * Specifies that an entire element should be draggable instead of its contents. Mainly for desktop browsers.\n * @type {String}\n * @default 'none'\n */\n userDrag: 'none',\n\n /**\n * Overrides the highlight color shown when the user taps a link or a JavaScript\n * clickable element in iOS. This property obeys the alpha value, if specified.\n * @type {String}\n * @default 'rgba(0,0,0,0)'\n */\n tapHighlightColor: 'rgba(0,0,0,0)'\n }\n };\n\n var STOP = 1;\n var FORCED_STOP = 2;\n\n /**\n * Manager\n * @param {HTMLElement} element\n * @param {Object} [options]\n * @constructor\n */\n function Manager(element, options) {\n this.options = assign({}, Hammer.defaults, options || {});\n\n this.options.inputTarget = this.options.inputTarget || element;\n\n this.handlers = {};\n this.session = {};\n this.recognizers = [];\n\n this.element = element;\n this.input = createInputInstance(this);\n this.touchAction = new TouchAction(this, this.options.touchAction);\n\n toggleCssProps(this, true);\n\n each(this.options.recognizers, function(item) {\n var recognizer = this.add(new (item[0])(item[1]));\n item[2] && recognizer.recognizeWith(item[2]);\n item[3] && recognizer.requireFailure(item[3]);\n }, this);\n }\n\n Manager.prototype = {\n /**\n * set options\n * @param {Object} options\n * @returns {Manager}\n */\n set: function(options) {\n assign(this.options, options);\n\n // Options that need a little more setup\n if (options.touchAction) {\n this.touchAction.update();\n }\n if (options.inputTarget) {\n // Clean up existing event listeners and reinitialize\n this.input.destroy();\n this.input.target = options.inputTarget;\n this.input.init();\n }\n return this;\n },\n\n /**\n * stop recognizing for this session.\n * This session will be discarded, when a new [input]start event is fired.\n * When forced, the recognizer cycle is stopped immediately.\n * @param {Boolean} [force]\n */\n stop: function(force) {\n this.session.stopped = force ? FORCED_STOP : STOP;\n },\n\n /**\n * run the recognizers!\n * called by the inputHandler function on every movement of the pointers (touches)\n * it walks through all the recognizers and tries to detect the gesture that is being made\n * @param {Object} inputData\n */\n recognize: function(inputData) {\n var session = this.session;\n if (session.stopped) {\n return;\n }\n\n // run the touch-action polyfill\n this.touchAction.preventDefaults(inputData);\n\n var recognizer;\n var recognizers = this.recognizers;\n\n // this holds the recognizer that is being recognized.\n // so the recognizer's state needs to be BEGAN, CHANGED, ENDED or RECOGNIZED\n // if no recognizer is detecting a thing, it is set to `null`\n var curRecognizer = session.curRecognizer;\n\n // reset when the last recognizer is recognized\n // or when we're in a new session\n if (!curRecognizer || (curRecognizer && curRecognizer.state & STATE_RECOGNIZED)) {\n curRecognizer = session.curRecognizer = null;\n }\n\n var i = 0;\n while (i < recognizers.length) {\n recognizer = recognizers[i];\n\n // find out if we are allowed try to recognize the input for this one.\n // 1. allow if the session is NOT forced stopped (see the .stop() method)\n // 2. allow if we still haven't recognized a gesture in this session, or the this recognizer is the one\n // that is being recognized.\n // 3. allow if the recognizer is allowed to run simultaneous with the current recognized recognizer.\n // this can be setup with the `recognizeWith()` method on the recognizer.\n if (session.stopped !== FORCED_STOP && ( // 1\n !curRecognizer || recognizer == curRecognizer || // 2\n recognizer.canRecognizeWith(curRecognizer))) { // 3\n recognizer.recognize(inputData);\n } else {\n recognizer.reset();\n }\n\n // if the recognizer has been recognizing the input as a valid gesture, we want to store this one as the\n // current active recognizer. but only if we don't already have an active recognizer\n if (!curRecognizer && recognizer.state & (STATE_BEGAN | STATE_CHANGED | STATE_ENDED)) {\n curRecognizer = session.curRecognizer = recognizer;\n }\n i++;\n }\n },\n\n /**\n * get a recognizer by its event name.\n * @param {Recognizer|String} recognizer\n * @returns {Recognizer|Null}\n */\n get: function(recognizer) {\n if (recognizer instanceof Recognizer) {\n return recognizer;\n }\n\n var recognizers = this.recognizers;\n for (var i = 0; i < recognizers.length; i++) {\n if (recognizers[i].options.event == recognizer) {\n return recognizers[i];\n }\n }\n return null;\n },\n\n /**\n * add a recognizer to the manager\n * existing recognizers with the same event name will be removed\n * @param {Recognizer} recognizer\n * @returns {Recognizer|Manager}\n */\n add: function(recognizer) {\n if (invokeArrayArg(recognizer, 'add', this)) {\n return this;\n }\n\n // remove existing\n var existing = this.get(recognizer.options.event);\n if (existing) {\n this.remove(existing);\n }\n\n this.recognizers.push(recognizer);\n recognizer.manager = this;\n\n this.touchAction.update();\n return recognizer;\n },\n\n /**\n * remove a recognizer by name or instance\n * @param {Recognizer|String} recognizer\n * @returns {Manager}\n */\n remove: function(recognizer) {\n if (invokeArrayArg(recognizer, 'remove', this)) {\n return this;\n }\n\n recognizer = this.get(recognizer);\n\n // let's make sure this recognizer exists\n if (recognizer) {\n var recognizers = this.recognizers;\n var index = inArray(recognizers, recognizer);\n\n if (index !== -1) {\n recognizers.splice(index, 1);\n this.touchAction.update();\n }\n }\n\n return this;\n },\n\n /**\n * bind event\n * @param {String} events\n * @param {Function} handler\n * @returns {EventEmitter} this\n */\n on: function(events, handler) {\n var handlers = this.handlers;\n each(splitStr(events), function(event) {\n handlers[event] = handlers[event] || [];\n handlers[event].push(handler);\n });\n return this;\n },\n\n /**\n * unbind event, leave emit blank to remove all handlers\n * @param {String} events\n * @param {Function} [handler]\n * @returns {EventEmitter} this\n */\n off: function(events, handler) {\n var handlers = this.handlers;\n each(splitStr(events), function(event) {\n if (!handler) {\n delete handlers[event];\n } else {\n handlers[event] && handlers[event].splice(inArray(handlers[event], handler), 1);\n }\n });\n return this;\n },\n\n /**\n * emit event to the listeners\n * @param {String} event\n * @param {Object} data\n */\n emit: function(event, data) {\n // we also want to trigger dom events\n if (this.options.domEvents) {\n triggerDomEvent(event, data);\n }\n\n // no handlers, so skip it all\n var handlers = this.handlers[event] && this.handlers[event].slice();\n if (!handlers || !handlers.length) {\n return;\n }\n\n data.type = event;\n data.preventDefault = function() {\n data.srcEvent.preventDefault();\n };\n\n var i = 0;\n while (i < handlers.length) {\n handlers[i](data);\n i++;\n }\n },\n\n /**\n * destroy the manager and unbinds all events\n * it doesn't unbind dom events, that is the user own responsibility\n */\n destroy: function() {\n this.element && toggleCssProps(this, false);\n\n this.handlers = {};\n this.session = {};\n this.input.destroy();\n this.element = null;\n }\n };\n\n /**\n * add/remove the css properties as defined in manager.options.cssProps\n * @param {Manager} manager\n * @param {Boolean} add\n */\n function toggleCssProps(manager, add) {\n var element = manager.element;\n if (!element.style) {\n return;\n }\n each(manager.options.cssProps, function(value, name) {\n element.style[prefixed(element.style, name)] = add ? value : '';\n });\n }\n\n /**\n * trigger dom event\n * @param {String} event\n * @param {Object} data\n */\n function triggerDomEvent(event, data) {\n var gestureEvent = document.createEvent('Event');\n gestureEvent.initEvent(event, true, true);\n gestureEvent.gesture = data;\n data.target.dispatchEvent(gestureEvent);\n }\n\n assign(Hammer, {\n INPUT_START: INPUT_START,\n INPUT_MOVE: INPUT_MOVE,\n INPUT_END: INPUT_END,\n INPUT_CANCEL: INPUT_CANCEL,\n\n STATE_POSSIBLE: STATE_POSSIBLE,\n STATE_BEGAN: STATE_BEGAN,\n STATE_CHANGED: STATE_CHANGED,\n STATE_ENDED: STATE_ENDED,\n STATE_RECOGNIZED: STATE_RECOGNIZED,\n STATE_CANCELLED: STATE_CANCELLED,\n STATE_FAILED: STATE_FAILED,\n\n DIRECTION_NONE: DIRECTION_NONE,\n DIRECTION_LEFT: DIRECTION_LEFT,\n DIRECTION_RIGHT: DIRECTION_RIGHT,\n DIRECTION_UP: DIRECTION_UP,\n DIRECTION_DOWN: DIRECTION_DOWN,\n DIRECTION_HORIZONTAL: DIRECTION_HORIZONTAL,\n DIRECTION_VERTICAL: DIRECTION_VERTICAL,\n DIRECTION_ALL: DIRECTION_ALL,\n\n Manager: Manager,\n Input: Input,\n TouchAction: TouchAction,\n\n TouchInput: TouchInput,\n MouseInput: MouseInput,\n PointerEventInput: PointerEventInput,\n TouchMouseInput: TouchMouseInput,\n SingleTouchInput: SingleTouchInput,\n\n Recognizer: Recognizer,\n AttrRecognizer: AttrRecognizer,\n Tap: TapRecognizer,\n Pan: PanRecognizer,\n Swipe: SwipeRecognizer,\n Pinch: PinchRecognizer,\n Rotate: RotateRecognizer,\n Press: PressRecognizer,\n\n on: addEventListeners,\n off: removeEventListeners,\n each: each,\n merge: merge,\n extend: extend,\n assign: assign,\n inherit: inherit,\n bindFn: bindFn,\n prefixed: prefixed\n });\n\n // this prevents errors when Hammer is loaded in the presence of an AMD\n // style loader but by script tag, not by the loader.\n var freeGlobal = (typeof window !== 'undefined' ? window : (typeof self !== 'undefined' ? self : {})); // jshint ignore:line\n freeGlobal.Hammer = Hammer;\n\n if (true) {\n !(__WEBPACK_AMD_DEFINE_RESULT__ = function() {\n return Hammer;\n }.call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));\n } else if (typeof module != 'undefined' && module.exports) {\n module.exports = Hammer;\n } else {\n window[exportName] = Hammer;\n }\n\n })(window, document, 'Hammer');\n\n\n/***/ },\n/* 23 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var hammerUtil = __webpack_require__(24);\n var moment = __webpack_require__(2);\n var Component = __webpack_require__(25);\n var DateUtil = __webpack_require__(26);\n\n /**\n * @constructor Range\n * A Range controls a numeric range with a start and end value.\n * The Range adjusts the range based on mouse events or programmatic changes,\n * and triggers events when the range is changing or has been changed.\n * @param {{dom: Object, domProps: Object, emitter: Emitter}} body\n * @param {Object} [options] See description at Range.setOptions\n */\n function Range(body, options) {\n var now = moment().hours(0).minutes(0).seconds(0).milliseconds(0);\n this.start = now.clone().add(-3, 'days').valueOf(); // Number\n this.end = now.clone().add(4, 'days').valueOf(); // Number\n\n this.body = body;\n this.deltaDifference = 0;\n this.scaleOffset = 0;\n this.startToFront = false;\n this.endToFront = true;\n\n // default options\n this.defaultOptions = {\n start: null,\n end: null,\n moment: moment,\n direction: 'horizontal', // 'horizontal' or 'vertical'\n moveable: true,\n zoomable: true,\n min: null,\n max: null,\n zoomMin: 10, // milliseconds\n zoomMax: 1000 * 60 * 60 * 24 * 365 * 10000 // milliseconds\n };\n this.options = util.extend({}, this.defaultOptions);\n\n this.props = {\n touch: {}\n };\n this.animationTimer = null;\n\n // drag listeners for dragging\n this.body.emitter.on('panstart', this._onDragStart.bind(this));\n this.body.emitter.on('panmove', this._onDrag.bind(this));\n this.body.emitter.on('panend', this._onDragEnd.bind(this));\n\n // mouse wheel for zooming\n this.body.emitter.on('mousewheel', this._onMouseWheel.bind(this));\n\n // pinch to zoom\n this.body.emitter.on('touch', this._onTouch.bind(this));\n this.body.emitter.on('pinch', this._onPinch.bind(this));\n\n this.setOptions(options);\n }\n\n Range.prototype = new Component();\n\n /**\n * Set options for the range controller\n * @param {Object} options Available options:\n * {Number | Date | String} start Start date for the range\n * {Number | Date | String} end End date for the range\n * {Number} min Minimum value for start\n * {Number} max Maximum value for end\n * {Number} zoomMin Set a minimum value for\n * (end - start).\n * {Number} zoomMax Set a maximum value for\n * (end - start).\n * {Boolean} moveable Enable moving of the range\n * by dragging. True by default\n * {Boolean} zoomable Enable zooming of the range\n * by pinching/scrolling. True by default\n */\n Range.prototype.setOptions = function (options) {\n if (options) {\n // copy the options that we know\n var fields = ['direction', 'min', 'max', 'zoomMin', 'zoomMax', 'moveable', 'zoomable', 'moment', 'activate', 'hiddenDates', 'zoomKey'];\n util.selectiveExtend(fields, this.options, options);\n\n if ('start' in options || 'end' in options) {\n // apply a new range. both start and end are optional\n this.setRange(options.start, options.end);\n }\n }\n };\n\n /**\n * Test whether direction has a valid value\n * @param {String} direction 'horizontal' or 'vertical'\n */\n function validateDirection(direction) {\n if (direction != 'horizontal' && direction != 'vertical') {\n throw new TypeError('Unknown direction \"' + direction + '\". ' + 'Choose \"horizontal\" or \"vertical\".');\n }\n }\n\n /**\n * Set a new start and end range\n * @param {Date | Number | String} [start]\n * @param {Date | Number | String} [end]\n * @param {boolean | {duration: number, easingFunction: string}} [animation=false]\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n * @param {Boolean} [byUser=false]\n *\n */\n Range.prototype.setRange = function (start, end, animation, byUser) {\n if (byUser !== true) {\n byUser = false;\n }\n var finalStart = start != undefined ? util.convert(start, 'Date').valueOf() : null;\n var finalEnd = end != undefined ? util.convert(end, 'Date').valueOf() : null;\n this._cancelAnimation();\n\n if (animation) {\n // true or an Object\n var me = this;\n var initStart = this.start;\n var initEnd = this.end;\n var duration = typeof animation === 'object' && 'duration' in animation ? animation.duration : 500;\n var easingName = typeof animation === 'object' && 'easingFunction' in animation ? animation.easingFunction : 'easeInOutQuad';\n var easingFunction = util.easingFunctions[easingName];\n if (!easingFunction) {\n throw new Error('Unknown easing function ' + JSON.stringify(easingName) + '. ' + 'Choose from: ' + Object.keys(util.easingFunctions).join(', '));\n }\n\n var initTime = new Date().valueOf();\n var anyChanged = false;\n\n var next = function next() {\n if (!me.props.touch.dragging) {\n var now = new Date().valueOf();\n var time = now - initTime;\n var ease = easingFunction(time / duration);\n var done = time > duration;\n var s = done || finalStart === null ? finalStart : initStart + (finalStart - initStart) * ease;\n var e = done || finalEnd === null ? finalEnd : initEnd + (finalEnd - initEnd) * ease;\n\n changed = me._applyRange(s, e);\n DateUtil.updateHiddenDates(me.options.moment, me.body, me.options.hiddenDates);\n anyChanged = anyChanged || changed;\n if (changed) {\n me.body.emitter.emit('rangechange', { start: new Date(me.start), end: new Date(me.end), byUser: byUser });\n }\n\n if (done) {\n if (anyChanged) {\n me.body.emitter.emit('rangechanged', { start: new Date(me.start), end: new Date(me.end), byUser: byUser });\n }\n } else {\n // animate with as high as possible frame rate, leave 20 ms in between\n // each to prevent the browser from blocking\n me.animationTimer = setTimeout(next, 20);\n }\n }\n };\n\n return next();\n } else {\n var changed = this._applyRange(finalStart, finalEnd);\n DateUtil.updateHiddenDates(this.options.moment, this.body, this.options.hiddenDates);\n if (changed) {\n var params = { start: new Date(this.start), end: new Date(this.end), byUser: byUser };\n this.body.emitter.emit('rangechange', params);\n this.body.emitter.emit('rangechanged', params);\n }\n }\n };\n\n /**\n * Stop an animation\n * @private\n */\n Range.prototype._cancelAnimation = function () {\n if (this.animationTimer) {\n clearTimeout(this.animationTimer);\n this.animationTimer = null;\n }\n };\n\n /**\n * Set a new start and end range. This method is the same as setRange, but\n * does not trigger a range change and range changed event, and it returns\n * true when the range is changed\n * @param {Number} [start]\n * @param {Number} [end]\n * @return {Boolean} changed\n * @private\n */\n Range.prototype._applyRange = function (start, end) {\n var newStart = start != null ? util.convert(start, 'Date').valueOf() : this.start,\n newEnd = end != null ? util.convert(end, 'Date').valueOf() : this.end,\n max = this.options.max != null ? util.convert(this.options.max, 'Date').valueOf() : null,\n min = this.options.min != null ? util.convert(this.options.min, 'Date').valueOf() : null,\n diff;\n\n // check for valid number\n if (isNaN(newStart) || newStart === null) {\n throw new Error('Invalid start \"' + start + '\"');\n }\n if (isNaN(newEnd) || newEnd === null) {\n throw new Error('Invalid end \"' + end + '\"');\n }\n\n // prevent start < end\n if (newEnd < newStart) {\n newEnd = newStart;\n }\n\n // prevent start < min\n if (min !== null) {\n if (newStart < min) {\n diff = min - newStart;\n newStart += diff;\n newEnd += diff;\n\n // prevent end > max\n if (max != null) {\n if (newEnd > max) {\n newEnd = max;\n }\n }\n }\n }\n\n // prevent end > max\n if (max !== null) {\n if (newEnd > max) {\n diff = newEnd - max;\n newStart -= diff;\n newEnd -= diff;\n\n // prevent start < min\n if (min != null) {\n if (newStart < min) {\n newStart = min;\n }\n }\n }\n }\n\n // prevent (end-start) < zoomMin\n if (this.options.zoomMin !== null) {\n var zoomMin = parseFloat(this.options.zoomMin);\n if (zoomMin < 0) {\n zoomMin = 0;\n }\n if (newEnd - newStart < zoomMin) {\n if (this.end - this.start === zoomMin && newStart > this.start && newEnd < this.end) {\n // ignore this action, we are already zoomed to the minimum\n newStart = this.start;\n newEnd = this.end;\n } else {\n // zoom to the minimum\n diff = zoomMin - (newEnd - newStart);\n newStart -= diff / 2;\n newEnd += diff / 2;\n }\n }\n }\n\n // prevent (end-start) > zoomMax\n if (this.options.zoomMax !== null) {\n var zoomMax = parseFloat(this.options.zoomMax);\n if (zoomMax < 0) {\n zoomMax = 0;\n }\n\n if (newEnd - newStart > zoomMax) {\n if (this.end - this.start === zoomMax && newStart < this.start && newEnd > this.end) {\n // ignore this action, we are already zoomed to the maximum\n newStart = this.start;\n newEnd = this.end;\n } else {\n // zoom to the maximum\n diff = newEnd - newStart - zoomMax;\n newStart += diff / 2;\n newEnd -= diff / 2;\n }\n }\n }\n\n var changed = this.start != newStart || this.end != newEnd;\n\n // if the new range does NOT overlap with the old range, emit checkRangedItems to avoid not showing ranged items (ranged meaning has end time, not necessarily of type Range)\n if (!(newStart >= this.start && newStart <= this.end || newEnd >= this.start && newEnd <= this.end) && !(this.start >= newStart && this.start <= newEnd || this.end >= newStart && this.end <= newEnd)) {\n this.body.emitter.emit('checkRangedItems');\n }\n\n this.start = newStart;\n this.end = newEnd;\n return changed;\n };\n\n /**\n * Retrieve the current range.\n * @return {Object} An object with start and end properties\n */\n Range.prototype.getRange = function () {\n return {\n start: this.start,\n end: this.end\n };\n };\n\n /**\n * Calculate the conversion offset and scale for current range, based on\n * the provided width\n * @param {Number} width\n * @returns {{offset: number, scale: number}} conversion\n */\n Range.prototype.conversion = function (width, totalHidden) {\n return Range.conversion(this.start, this.end, width, totalHidden);\n };\n\n /**\n * Static method to calculate the conversion offset and scale for a range,\n * based on the provided start, end, and width\n * @param {Number} start\n * @param {Number} end\n * @param {Number} width\n * @returns {{offset: number, scale: number}} conversion\n */\n Range.conversion = function (start, end, width, totalHidden) {\n if (totalHidden === undefined) {\n totalHidden = 0;\n }\n if (width != 0 && end - start != 0) {\n return {\n offset: start,\n scale: width / (end - start - totalHidden)\n };\n } else {\n return {\n offset: 0,\n scale: 1\n };\n }\n };\n\n /**\n * Start dragging horizontally or vertically\n * @param {Event} event\n * @private\n */\n Range.prototype._onDragStart = function (event) {\n this.deltaDifference = 0;\n this.previousDelta = 0;\n\n // only allow dragging when configured as movable\n if (!this.options.moveable) return;\n\n // only start dragging when the mouse is inside the current range\n if (!this._isInsideRange(event)) return;\n\n // refuse to drag when we where pinching to prevent the timeline make a jump\n // when releasing the fingers in opposite order from the touch screen\n if (!this.props.touch.allowDragging) return;\n\n this.props.touch.start = this.start;\n this.props.touch.end = this.end;\n this.props.touch.dragging = true;\n\n if (this.body.dom.root) {\n this.body.dom.root.style.cursor = 'move';\n }\n };\n\n /**\n * Perform dragging operation\n * @param {Event} event\n * @private\n */\n Range.prototype._onDrag = function (event) {\n if (!this.props.touch.dragging) return;\n\n // only allow dragging when configured as movable\n if (!this.options.moveable) return;\n\n // TODO: this may be redundant in hammerjs2\n // refuse to drag when we where pinching to prevent the timeline make a jump\n // when releasing the fingers in opposite order from the touch screen\n if (!this.props.touch.allowDragging) return;\n\n var direction = this.options.direction;\n validateDirection(direction);\n var delta = direction == 'horizontal' ? event.deltaX : event.deltaY;\n delta -= this.deltaDifference;\n var interval = this.props.touch.end - this.props.touch.start;\n\n // normalize dragging speed if cutout is in between.\n var duration = DateUtil.getHiddenDurationBetween(this.body.hiddenDates, this.start, this.end);\n interval -= duration;\n\n var width = direction == 'horizontal' ? this.body.domProps.center.width : this.body.domProps.center.height;\n var diffRange = -delta / width * interval;\n var newStart = this.props.touch.start + diffRange;\n var newEnd = this.props.touch.end + diffRange;\n\n // snapping times away from hidden zones\n var safeStart = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newStart, this.previousDelta - delta, true);\n var safeEnd = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newEnd, this.previousDelta - delta, true);\n if (safeStart != newStart || safeEnd != newEnd) {\n this.deltaDifference += delta;\n this.props.touch.start = safeStart;\n this.props.touch.end = safeEnd;\n this._onDrag(event);\n return;\n }\n\n this.previousDelta = delta;\n this._applyRange(newStart, newEnd);\n\n var startDate = new Date(this.start);\n var endDate = new Date(this.end);\n\n // fire a rangechange event\n this.body.emitter.emit('rangechange', {\n start: startDate,\n end: endDate,\n byUser: true\n });\n };\n\n /**\n * Stop dragging operation\n * @param {event} event\n * @private\n */\n Range.prototype._onDragEnd = function (event) {\n if (!this.props.touch.dragging) return;\n\n // only allow dragging when configured as movable\n if (!this.options.moveable) return;\n\n // TODO: this may be redundant in hammerjs2\n // refuse to drag when we where pinching to prevent the timeline make a jump\n // when releasing the fingers in opposite order from the touch screen\n if (!this.props.touch.allowDragging) return;\n\n this.props.touch.dragging = false;\n if (this.body.dom.root) {\n this.body.dom.root.style.cursor = 'auto';\n }\n\n // fire a rangechanged event\n this.body.emitter.emit('rangechanged', {\n start: new Date(this.start),\n end: new Date(this.end),\n byUser: true\n });\n };\n\n /**\n * Event handler for mouse wheel event, used to zoom\n * Code from http://adomas.org/javascript-mouse-wheel/\n * @param {Event} event\n * @private\n */\n Range.prototype._onMouseWheel = function (event) {\n // only allow zooming when configured as zoomable and moveable\n if (!(this.options.zoomable && this.options.moveable)) return;\n\n // only zoom when the mouse is inside the current range\n if (!this._isInsideRange(event)) return;\n\n // only zoom when the according key is pressed and the zoomKey option is set\n if (this.options.zoomKey && !event[this.options.zoomKey]) return;\n\n // retrieve delta\n var delta = 0;\n if (event.wheelDelta) {\n /* IE/Opera. */\n delta = event.wheelDelta / 120;\n } else if (event.detail) {\n /* Mozilla case. */\n // In Mozilla, sign of delta is different than in IE.\n // Also, delta is multiple of 3.\n delta = -event.detail / 3;\n }\n\n // If delta is nonzero, handle it.\n // Basically, delta is now positive if wheel was scrolled up,\n // and negative, if wheel was scrolled down.\n if (delta) {\n // perform the zoom action. Delta is normally 1 or -1\n\n // adjust a negative delta such that zooming in with delta 0.1\n // equals zooming out with a delta -0.1\n var scale;\n if (delta < 0) {\n scale = 1 - delta / 5;\n } else {\n scale = 1 / (1 + delta / 5);\n }\n\n // calculate center, the date to zoom around\n var pointer = getPointer({ x: event.clientX, y: event.clientY }, this.body.dom.center);\n var pointerDate = this._pointerToDate(pointer);\n\n this.zoom(scale, pointerDate, delta);\n }\n\n // Prevent default actions caused by mouse wheel\n // (else the page and timeline both zoom and scroll)\n event.preventDefault();\n };\n\n /**\n * Start of a touch gesture\n * @private\n */\n Range.prototype._onTouch = function (event) {\n this.props.touch.start = this.start;\n this.props.touch.end = this.end;\n this.props.touch.allowDragging = true;\n this.props.touch.center = null;\n this.scaleOffset = 0;\n this.deltaDifference = 0;\n };\n\n /**\n * Handle pinch event\n * @param {Event} event\n * @private\n */\n Range.prototype._onPinch = function (event) {\n // only allow zooming when configured as zoomable and moveable\n if (!(this.options.zoomable && this.options.moveable)) return;\n\n this.props.touch.allowDragging = false;\n\n if (!this.props.touch.center) {\n this.props.touch.center = getPointer(event.center, this.body.dom.center);\n }\n\n var scale = 1 / (event.scale + this.scaleOffset);\n var centerDate = this._pointerToDate(this.props.touch.center);\n\n var hiddenDuration = DateUtil.getHiddenDurationBetween(this.body.hiddenDates, this.start, this.end);\n var hiddenDurationBefore = DateUtil.getHiddenDurationBefore(this.options.moment, this.body.hiddenDates, this, centerDate);\n var hiddenDurationAfter = hiddenDuration - hiddenDurationBefore;\n\n // calculate new start and end\n var newStart = centerDate - hiddenDurationBefore + (this.props.touch.start - (centerDate - hiddenDurationBefore)) * scale;\n var newEnd = centerDate + hiddenDurationAfter + (this.props.touch.end - (centerDate + hiddenDurationAfter)) * scale;\n\n // snapping times away from hidden zones\n this.startToFront = 1 - scale <= 0; // used to do the right auto correction with periodic hidden times\n this.endToFront = scale - 1 <= 0; // used to do the right auto correction with periodic hidden times\n\n var safeStart = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newStart, 1 - scale, true);\n var safeEnd = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newEnd, scale - 1, true);\n if (safeStart != newStart || safeEnd != newEnd) {\n this.props.touch.start = safeStart;\n this.props.touch.end = safeEnd;\n this.scaleOffset = 1 - event.scale;\n newStart = safeStart;\n newEnd = safeEnd;\n }\n\n this.setRange(newStart, newEnd, false, true);\n\n this.startToFront = false; // revert to default\n this.endToFront = true; // revert to default\n };\n\n /**\n * Test whether the mouse from a mouse event is inside the visible window,\n * between the current start and end date\n * @param {Object} event\n * @return {boolean} Returns true when inside the visible window\n * @private\n */\n Range.prototype._isInsideRange = function (event) {\n // calculate the time where the mouse is, check whether inside\n // and no scroll action should happen.\n var clientX = event.center ? event.center.x : event.clientX;\n var x = clientX - util.getAbsoluteLeft(this.body.dom.centerContainer);\n var time = this.body.util.toTime(x);\n\n return time >= this.start && time <= this.end;\n };\n\n /**\n * Helper function to calculate the center date for zooming\n * @param {{x: Number, y: Number}} pointer\n * @return {number} date\n * @private\n */\n Range.prototype._pointerToDate = function (pointer) {\n var conversion;\n var direction = this.options.direction;\n\n validateDirection(direction);\n\n if (direction == 'horizontal') {\n return this.body.util.toTime(pointer.x).valueOf();\n } else {\n var height = this.body.domProps.center.height;\n conversion = this.conversion(height);\n return pointer.y / conversion.scale + conversion.offset;\n }\n };\n\n /**\n * Get the pointer location relative to the location of the dom element\n * @param {{x: Number, y: Number}} touch\n * @param {Element} element HTML DOM element\n * @return {{x: Number, y: Number}} pointer\n * @private\n */\n function getPointer(touch, element) {\n return {\n x: touch.x - util.getAbsoluteLeft(element),\n y: touch.y - util.getAbsoluteTop(element)\n };\n }\n\n /**\n * Zoom the range the given scale in or out. Start and end date will\n * be adjusted, and the timeline will be redrawn. You can optionally give a\n * date around which to zoom.\n * For example, try scale = 0.9 or 1.1\n * @param {Number} scale Scaling factor. Values above 1 will zoom out,\n * values below 1 will zoom in.\n * @param {Number} [center] Value representing a date around which will\n * be zoomed.\n */\n Range.prototype.zoom = function (scale, center, delta) {\n // if centerDate is not provided, take it half between start Date and end Date\n if (center == null) {\n center = (this.start + this.end) / 2;\n }\n\n var hiddenDuration = DateUtil.getHiddenDurationBetween(this.body.hiddenDates, this.start, this.end);\n var hiddenDurationBefore = DateUtil.getHiddenDurationBefore(this.options.moment, this.body.hiddenDates, this, center);\n var hiddenDurationAfter = hiddenDuration - hiddenDurationBefore;\n\n // calculate new start and end\n var newStart = center - hiddenDurationBefore + (this.start - (center - hiddenDurationBefore)) * scale;\n var newEnd = center + hiddenDurationAfter + (this.end - (center + hiddenDurationAfter)) * scale;\n\n // snapping times away from hidden zones\n this.startToFront = delta > 0 ? false : true; // used to do the right autocorrection with periodic hidden times\n this.endToFront = -delta > 0 ? false : true; // used to do the right autocorrection with periodic hidden times\n var safeStart = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newStart, delta, true);\n var safeEnd = DateUtil.snapAwayFromHidden(this.body.hiddenDates, newEnd, -delta, true);\n if (safeStart != newStart || safeEnd != newEnd) {\n newStart = safeStart;\n newEnd = safeEnd;\n }\n\n this.setRange(newStart, newEnd, false, true);\n\n this.startToFront = false; // revert to default\n this.endToFront = true; // revert to default\n };\n\n /**\n * Move the range with a given delta to the left or right. Start and end\n * value will be adjusted. For example, try delta = 0.1 or -0.1\n * @param {Number} delta Moving amount. Positive value will move right,\n * negative value will move left\n */\n Range.prototype.move = function (delta) {\n // zoom start Date and end Date relative to the centerDate\n var diff = this.end - this.start;\n\n // apply new values\n var newStart = this.start + diff * delta;\n var newEnd = this.end + diff * delta;\n\n // TODO: reckon with min and max range\n\n this.start = newStart;\n this.end = newEnd;\n };\n\n /**\n * Move the range to a new center point\n * @param {Number} moveTo New center point of the range\n */\n Range.prototype.moveTo = function (moveTo) {\n var center = (this.start + this.end) / 2;\n\n var diff = center - moveTo;\n\n // calculate new start and end\n var newStart = this.start - diff;\n var newEnd = this.end - diff;\n\n this.setRange(newStart, newEnd);\n };\n\n module.exports = Range;\n\n/***/ },\n/* 24 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n\n /**\n * Register a touch event, taking place before a gesture\n * @param {Hammer} hammer A hammer instance\n * @param {function} callback Callback, called as callback(event)\n */\n exports.onTouch = function (hammer, callback) {\n callback.inputHandler = function (event) {\n if (event.isFirst) {\n callback(event);\n }\n };\n\n hammer.on('hammer.input', callback.inputHandler);\n };\n\n /**\n * Register a release event, taking place after a gesture\n * @param {Hammer} hammer A hammer instance\n * @param {function} callback Callback, called as callback(event)\n */\n exports.onRelease = function (hammer, callback) {\n callback.inputHandler = function (event) {\n if (event.isFinal) {\n callback(event);\n }\n };\n\n return hammer.on('hammer.input', callback.inputHandler);\n };\n\n /**\n * Unregister a touch event, taking place before a gesture\n * @param {Hammer} hammer A hammer instance\n * @param {function} callback Callback, called as callback(event)\n */\n exports.offTouch = function (hammer, callback) {\n hammer.off('hammer.input', callback.inputHandler);\n };\n\n /**\n * Unregister a release event, taking place before a gesture\n * @param {Hammer} hammer A hammer instance\n * @param {function} callback Callback, called as callback(event)\n */\n exports.offRelease = exports.offTouch;\n\n/***/ },\n/* 25 */\n/***/ function(module, exports) {\n\n /**\n * Prototype for visual components\n * @param {{dom: Object, domProps: Object, emitter: Emitter, range: Range}} [body]\n * @param {Object} [options]\n */\n \"use strict\";\n\n function Component(body, options) {\n this.options = null;\n this.props = null;\n }\n\n /**\n * Set options for the component. The new options will be merged into the\n * current options.\n * @param {Object} options\n */\n Component.prototype.setOptions = function (options) {\n if (options) {\n util.extend(this.options, options);\n }\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n Component.prototype.redraw = function () {\n // should be implemented by the component\n return false;\n };\n\n /**\n * Destroy the component. Cleanup DOM and event listeners\n */\n Component.prototype.destroy = function () {\n // should be implemented by the component\n };\n\n /**\n * Test whether the component is resized since the last time _isResized() was\n * called.\n * @return {Boolean} Returns true if the component is resized\n * @protected\n */\n Component.prototype._isResized = function () {\n var resized = this.props._previousWidth !== this.props.width || this.props._previousHeight !== this.props.height;\n\n this.props._previousWidth = this.props.width;\n this.props._previousHeight = this.props.height;\n\n return resized;\n };\n\n module.exports = Component;\n\n/***/ },\n/* 26 */\n/***/ function(module, exports) {\n\n \n /**\n * used in Core to convert the options into a volatile variable\n * \n * @param {function} moment\n * @param {Object} body\n * @param {Array | Object} hiddenDates\n */\n \"use strict\";\n\n exports.convertHiddenOptions = function (moment, body, hiddenDates) {\n if (hiddenDates && !Array.isArray(hiddenDates)) {\n return exports.convertHiddenOptions(moment, body, [hiddenDates]);\n }\n\n body.hiddenDates = [];\n if (hiddenDates) {\n if (Array.isArray(hiddenDates) == true) {\n for (var i = 0; i < hiddenDates.length; i++) {\n if (hiddenDates[i].repeat === undefined) {\n var dateItem = {};\n dateItem.start = moment(hiddenDates[i].start).toDate().valueOf();\n dateItem.end = moment(hiddenDates[i].end).toDate().valueOf();\n body.hiddenDates.push(dateItem);\n }\n }\n body.hiddenDates.sort(function (a, b) {\n return a.start - b.start;\n }); // sort by start time\n }\n }\n };\n\n /**\n * create new entrees for the repeating hidden dates\n * @param {function} moment\n * @param {Object} body\n * @param {Array | Object} hiddenDates\n */\n exports.updateHiddenDates = function (moment, body, hiddenDates) {\n if (hiddenDates && !Array.isArray(hiddenDates)) {\n return exports.updateHiddenDates(moment, body, [hiddenDates]);\n }\n\n if (hiddenDates && body.domProps.centerContainer.width !== undefined) {\n exports.convertHiddenOptions(moment, body, hiddenDates);\n\n var start = moment(body.range.start);\n var end = moment(body.range.end);\n\n var totalRange = body.range.end - body.range.start;\n var pixelTime = totalRange / body.domProps.centerContainer.width;\n\n for (var i = 0; i < hiddenDates.length; i++) {\n if (hiddenDates[i].repeat !== undefined) {\n var startDate = moment(hiddenDates[i].start);\n var endDate = moment(hiddenDates[i].end);\n\n if (startDate._d == \"Invalid Date\") {\n throw new Error(\"Supplied start date is not valid: \" + hiddenDates[i].start);\n }\n if (endDate._d == \"Invalid Date\") {\n throw new Error(\"Supplied end date is not valid: \" + hiddenDates[i].end);\n }\n\n var duration = endDate - startDate;\n if (duration >= 4 * pixelTime) {\n\n var offset = 0;\n var runUntil = end.clone();\n switch (hiddenDates[i].repeat) {\n case \"daily\":\n // case of time\n if (startDate.day() != endDate.day()) {\n offset = 1;\n }\n startDate.dayOfYear(start.dayOfYear());\n startDate.year(start.year());\n startDate.subtract(7, 'days');\n\n endDate.dayOfYear(start.dayOfYear());\n endDate.year(start.year());\n endDate.subtract(7 - offset, 'days');\n\n runUntil.add(1, 'weeks');\n break;\n case \"weekly\":\n var dayOffset = endDate.diff(startDate, 'days');\n var day = startDate.day();\n\n // set the start date to the range.start\n startDate.date(start.date());\n startDate.month(start.month());\n startDate.year(start.year());\n endDate = startDate.clone();\n\n // force\n startDate.day(day);\n endDate.day(day);\n endDate.add(dayOffset, 'days');\n\n startDate.subtract(1, 'weeks');\n endDate.subtract(1, 'weeks');\n\n runUntil.add(1, 'weeks');\n break;\n case \"monthly\":\n if (startDate.month() != endDate.month()) {\n offset = 1;\n }\n startDate.month(start.month());\n startDate.year(start.year());\n startDate.subtract(1, 'months');\n\n endDate.month(start.month());\n endDate.year(start.year());\n endDate.subtract(1, 'months');\n endDate.add(offset, 'months');\n\n runUntil.add(1, 'months');\n break;\n case \"yearly\":\n if (startDate.year() != endDate.year()) {\n offset = 1;\n }\n startDate.year(start.year());\n startDate.subtract(1, 'years');\n endDate.year(start.year());\n endDate.subtract(1, 'years');\n endDate.add(offset, 'years');\n\n runUntil.add(1, 'years');\n break;\n default:\n console.log(\"Wrong repeat format, allowed are: daily, weekly, monthly, yearly. Given:\", hiddenDates[i].repeat);\n return;\n }\n while (startDate < runUntil) {\n body.hiddenDates.push({ start: startDate.valueOf(), end: endDate.valueOf() });\n switch (hiddenDates[i].repeat) {\n case \"daily\":\n startDate.add(1, 'days');\n endDate.add(1, 'days');\n break;\n case \"weekly\":\n startDate.add(1, 'weeks');\n endDate.add(1, 'weeks');\n break;\n case \"monthly\":\n startDate.add(1, 'months');\n endDate.add(1, 'months');\n break;\n case \"yearly\":\n startDate.add(1, 'y');\n endDate.add(1, 'y');\n break;\n default:\n console.log(\"Wrong repeat format, allowed are: daily, weekly, monthly, yearly. Given:\", hiddenDates[i].repeat);\n return;\n }\n }\n body.hiddenDates.push({ start: startDate.valueOf(), end: endDate.valueOf() });\n }\n }\n }\n // remove duplicates, merge where possible\n exports.removeDuplicates(body);\n // ensure the new positions are not on hidden dates\n var startHidden = exports.isHidden(body.range.start, body.hiddenDates);\n var endHidden = exports.isHidden(body.range.end, body.hiddenDates);\n var rangeStart = body.range.start;\n var rangeEnd = body.range.end;\n if (startHidden.hidden == true) {\n rangeStart = body.range.startToFront == true ? startHidden.startDate - 1 : startHidden.endDate + 1;\n }\n if (endHidden.hidden == true) {\n rangeEnd = body.range.endToFront == true ? endHidden.startDate - 1 : endHidden.endDate + 1;\n }\n if (startHidden.hidden == true || endHidden.hidden == true) {\n body.range._applyRange(rangeStart, rangeEnd);\n }\n }\n };\n\n /**\n * remove duplicates from the hidden dates list. Duplicates are evil. They mess everything up.\n * Scales with N^2\n * @param body\n */\n exports.removeDuplicates = function (body) {\n var hiddenDates = body.hiddenDates;\n var safeDates = [];\n for (var i = 0; i < hiddenDates.length; i++) {\n for (var j = 0; j < hiddenDates.length; j++) {\n if (i != j && hiddenDates[j].remove != true && hiddenDates[i].remove != true) {\n // j inside i\n if (hiddenDates[j].start >= hiddenDates[i].start && hiddenDates[j].end <= hiddenDates[i].end) {\n hiddenDates[j].remove = true;\n }\n // j start inside i\n else if (hiddenDates[j].start >= hiddenDates[i].start && hiddenDates[j].start <= hiddenDates[i].end) {\n hiddenDates[i].end = hiddenDates[j].end;\n hiddenDates[j].remove = true;\n }\n // j end inside i\n else if (hiddenDates[j].end >= hiddenDates[i].start && hiddenDates[j].end <= hiddenDates[i].end) {\n hiddenDates[i].start = hiddenDates[j].start;\n hiddenDates[j].remove = true;\n }\n }\n }\n }\n\n for (var i = 0; i < hiddenDates.length; i++) {\n if (hiddenDates[i].remove !== true) {\n safeDates.push(hiddenDates[i]);\n }\n }\n\n body.hiddenDates = safeDates;\n body.hiddenDates.sort(function (a, b) {\n return a.start - b.start;\n }); // sort by start time\n };\n\n exports.printDates = function (dates) {\n for (var i = 0; i < dates.length; i++) {\n console.log(i, new Date(dates[i].start), new Date(dates[i].end), dates[i].start, dates[i].end, dates[i].remove);\n }\n };\n\n /**\n * Used in TimeStep to avoid the hidden times.\n * @param {function} moment\n * @param {TimeStep} timeStep\n * @param previousTime\n */\n exports.stepOverHiddenDates = function (moment, timeStep, previousTime) {\n var stepInHidden = false;\n var currentValue = timeStep.current.valueOf();\n for (var i = 0; i < timeStep.hiddenDates.length; i++) {\n var startDate = timeStep.hiddenDates[i].start;\n var endDate = timeStep.hiddenDates[i].end;\n if (currentValue >= startDate && currentValue < endDate) {\n stepInHidden = true;\n break;\n }\n }\n\n if (stepInHidden == true && currentValue < timeStep._end.valueOf() && currentValue != previousTime) {\n var prevValue = moment(previousTime);\n var newValue = moment(endDate);\n //check if the next step should be major\n if (prevValue.year() != newValue.year()) {\n timeStep.switchedYear = true;\n } else if (prevValue.month() != newValue.month()) {\n timeStep.switchedMonth = true;\n } else if (prevValue.dayOfYear() != newValue.dayOfYear()) {\n timeStep.switchedDay = true;\n }\n\n timeStep.current = newValue;\n }\n };\n\n ///**\n // * Used in TimeStep to avoid the hidden times.\n // * @param timeStep\n // * @param previousTime\n // */\n //exports.checkFirstStep = function(timeStep) {\n // var stepInHidden = false;\n // var currentValue = timeStep.current.valueOf();\n // for (var i = 0; i < timeStep.hiddenDates.length; i++) {\n // var startDate = timeStep.hiddenDates[i].start;\n // var endDate = timeStep.hiddenDates[i].end;\n // if (currentValue >= startDate && currentValue < endDate) {\n // stepInHidden = true;\n // break;\n // }\n // }\n //\n // if (stepInHidden == true && currentValue <= timeStep._end.valueOf()) {\n // var newValue = moment(endDate);\n // timeStep.current = newValue.toDate();\n // }\n //};\n\n /**\n * replaces the Core toScreen methods\n * @param Core\n * @param time\n * @param width\n * @returns {number}\n */\n exports.toScreen = function (Core, time, width) {\n if (Core.body.hiddenDates.length == 0) {\n var conversion = Core.range.conversion(width);\n return (time.valueOf() - conversion.offset) * conversion.scale;\n } else {\n var hidden = exports.isHidden(time, Core.body.hiddenDates);\n if (hidden.hidden == true) {\n time = hidden.startDate;\n }\n\n var duration = exports.getHiddenDurationBetween(Core.body.hiddenDates, Core.range.start, Core.range.end);\n time = exports.correctTimeForHidden(Core.options.moment, Core.body.hiddenDates, Core.range, time);\n\n var conversion = Core.range.conversion(width, duration);\n return (time.valueOf() - conversion.offset) * conversion.scale;\n }\n };\n\n /**\n * Replaces the core toTime methods\n * @param body\n * @param range\n * @param x\n * @param width\n * @returns {Date}\n */\n exports.toTime = function (Core, x, width) {\n if (Core.body.hiddenDates.length == 0) {\n var conversion = Core.range.conversion(width);\n return new Date(x / conversion.scale + conversion.offset);\n } else {\n var hiddenDuration = exports.getHiddenDurationBetween(Core.body.hiddenDates, Core.range.start, Core.range.end);\n var totalDuration = Core.range.end - Core.range.start - hiddenDuration;\n var partialDuration = totalDuration * x / width;\n var accumulatedHiddenDuration = exports.getAccumulatedHiddenDuration(Core.body.hiddenDates, Core.range, partialDuration);\n\n var newTime = new Date(accumulatedHiddenDuration + partialDuration + Core.range.start);\n return newTime;\n }\n };\n\n /**\n * Support function\n *\n * @param hiddenDates\n * @param range\n * @returns {number}\n */\n exports.getHiddenDurationBetween = function (hiddenDates, start, end) {\n var duration = 0;\n for (var i = 0; i < hiddenDates.length; i++) {\n var startDate = hiddenDates[i].start;\n var endDate = hiddenDates[i].end;\n // if time after the cutout, and the\n if (startDate >= start && endDate < end) {\n duration += endDate - startDate;\n }\n }\n return duration;\n };\n\n /**\n * Support function\n * @param moment\n * @param hiddenDates\n * @param range\n * @param time\n * @returns {{duration: number, time: *, offset: number}}\n */\n exports.correctTimeForHidden = function (moment, hiddenDates, range, time) {\n time = moment(time).toDate().valueOf();\n time -= exports.getHiddenDurationBefore(moment, hiddenDates, range, time);\n return time;\n };\n\n exports.getHiddenDurationBefore = function (moment, hiddenDates, range, time) {\n var timeOffset = 0;\n time = moment(time).toDate().valueOf();\n\n for (var i = 0; i < hiddenDates.length; i++) {\n var startDate = hiddenDates[i].start;\n var endDate = hiddenDates[i].end;\n // if time after the cutout, and the\n if (startDate >= range.start && endDate < range.end) {\n if (time >= endDate) {\n timeOffset += endDate - startDate;\n }\n }\n }\n return timeOffset;\n };\n\n /**\n * sum the duration from start to finish, including the hidden duration,\n * until the required amount has been reached, return the accumulated hidden duration\n * @param hiddenDates\n * @param range\n * @param time\n * @returns {{duration: number, time: *, offset: number}}\n */\n exports.getAccumulatedHiddenDuration = function (hiddenDates, range, requiredDuration) {\n var hiddenDuration = 0;\n var duration = 0;\n var previousPoint = range.start;\n //exports.printDates(hiddenDates)\n for (var i = 0; i < hiddenDates.length; i++) {\n var startDate = hiddenDates[i].start;\n var endDate = hiddenDates[i].end;\n // if time after the cutout, and the\n if (startDate >= range.start && endDate < range.end) {\n duration += startDate - previousPoint;\n previousPoint = endDate;\n if (duration >= requiredDuration) {\n break;\n } else {\n hiddenDuration += endDate - startDate;\n }\n }\n }\n\n return hiddenDuration;\n };\n\n /**\n * used to step over to either side of a hidden block. Correction is disabled on tablets, might be set to true\n * @param hiddenDates\n * @param time\n * @param direction\n * @param correctionEnabled\n * @returns {*}\n */\n exports.snapAwayFromHidden = function (hiddenDates, time, direction, correctionEnabled) {\n var isHidden = exports.isHidden(time, hiddenDates);\n if (isHidden.hidden == true) {\n if (direction < 0) {\n if (correctionEnabled == true) {\n return isHidden.startDate - (isHidden.endDate - time) - 1;\n } else {\n return isHidden.startDate - 1;\n }\n } else {\n if (correctionEnabled == true) {\n return isHidden.endDate + (time - isHidden.startDate) + 1;\n } else {\n return isHidden.endDate + 1;\n }\n }\n } else {\n return time;\n }\n };\n\n /**\n * Check if a time is hidden\n *\n * @param time\n * @param hiddenDates\n * @returns {{hidden: boolean, startDate: Window.start, endDate: *}}\n */\n exports.isHidden = function (time, hiddenDates) {\n for (var i = 0; i < hiddenDates.length; i++) {\n var startDate = hiddenDates[i].start;\n var endDate = hiddenDates[i].end;\n\n if (time >= startDate && time < endDate) {\n // if the start is entering a hidden zone\n return { hidden: true, startDate: startDate, endDate: endDate };\n break;\n }\n }\n return { hidden: false, startDate: startDate, endDate: endDate };\n };\n\n/***/ },\n/* 27 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Emitter = __webpack_require__(12);\n var Hammer = __webpack_require__(20);\n var hammerUtil = __webpack_require__(24);\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var Range = __webpack_require__(23);\n var ItemSet = __webpack_require__(28);\n var TimeAxis = __webpack_require__(38);\n var Activator = __webpack_require__(39);\n var DateUtil = __webpack_require__(26);\n var CustomTime = __webpack_require__(41);\n\n /**\n * Create a timeline visualization\n * @constructor\n */\n function Core() {}\n\n // turn Core into an event emitter\n Emitter(Core.prototype);\n\n /**\n * Create the main DOM for the Core: a root panel containing left, right,\n * top, bottom, content, and background panel.\n * @param {Element} container The container element where the Core will\n * be attached.\n * @protected\n */\n Core.prototype._create = function (container) {\n this.dom = {};\n\n this.dom.container = container;\n\n this.dom.root = document.createElement('div');\n this.dom.background = document.createElement('div');\n this.dom.backgroundVertical = document.createElement('div');\n this.dom.backgroundHorizontal = document.createElement('div');\n this.dom.centerContainer = document.createElement('div');\n this.dom.leftContainer = document.createElement('div');\n this.dom.rightContainer = document.createElement('div');\n this.dom.center = document.createElement('div');\n this.dom.left = document.createElement('div');\n this.dom.right = document.createElement('div');\n this.dom.top = document.createElement('div');\n this.dom.bottom = document.createElement('div');\n this.dom.shadowTop = document.createElement('div');\n this.dom.shadowBottom = document.createElement('div');\n this.dom.shadowTopLeft = document.createElement('div');\n this.dom.shadowBottomLeft = document.createElement('div');\n this.dom.shadowTopRight = document.createElement('div');\n this.dom.shadowBottomRight = document.createElement('div');\n\n this.dom.root.className = 'vis-timeline';\n this.dom.background.className = 'vis-panel vis-background';\n this.dom.backgroundVertical.className = 'vis-panel vis-background vis-vertical';\n this.dom.backgroundHorizontal.className = 'vis-panel vis-background vis-horizontal';\n this.dom.centerContainer.className = 'vis-panel vis-center';\n this.dom.leftContainer.className = 'vis-panel vis-left';\n this.dom.rightContainer.className = 'vis-panel vis-right';\n this.dom.top.className = 'vis-panel vis-top';\n this.dom.bottom.className = 'vis-panel vis-bottom';\n this.dom.left.className = 'vis-content';\n this.dom.center.className = 'vis-content';\n this.dom.right.className = 'vis-content';\n this.dom.shadowTop.className = 'vis-shadow vis-top';\n this.dom.shadowBottom.className = 'vis-shadow vis-bottom';\n this.dom.shadowTopLeft.className = 'vis-shadow vis-top';\n this.dom.shadowBottomLeft.className = 'vis-shadow vis-bottom';\n this.dom.shadowTopRight.className = 'vis-shadow vis-top';\n this.dom.shadowBottomRight.className = 'vis-shadow vis-bottom';\n\n this.dom.root.appendChild(this.dom.background);\n this.dom.root.appendChild(this.dom.backgroundVertical);\n this.dom.root.appendChild(this.dom.backgroundHorizontal);\n this.dom.root.appendChild(this.dom.centerContainer);\n this.dom.root.appendChild(this.dom.leftContainer);\n this.dom.root.appendChild(this.dom.rightContainer);\n this.dom.root.appendChild(this.dom.top);\n this.dom.root.appendChild(this.dom.bottom);\n\n this.dom.centerContainer.appendChild(this.dom.center);\n this.dom.leftContainer.appendChild(this.dom.left);\n this.dom.rightContainer.appendChild(this.dom.right);\n\n this.dom.centerContainer.appendChild(this.dom.shadowTop);\n this.dom.centerContainer.appendChild(this.dom.shadowBottom);\n this.dom.leftContainer.appendChild(this.dom.shadowTopLeft);\n this.dom.leftContainer.appendChild(this.dom.shadowBottomLeft);\n this.dom.rightContainer.appendChild(this.dom.shadowTopRight);\n this.dom.rightContainer.appendChild(this.dom.shadowBottomRight);\n\n this.on('rangechange', (function () {\n if (this.initialDrawDone === true) {\n this._redraw(); // this allows overriding the _redraw method\n }\n }).bind(this));\n this.on('touch', this._onTouch.bind(this));\n this.on('pan', this._onDrag.bind(this));\n\n var me = this;\n this.on('_change', function (properties) {\n if (properties && properties.queue == true) {\n // redraw once on next tick\n if (!me._redrawTimer) {\n me._redrawTimer = setTimeout(function () {\n me._redrawTimer = null;\n me._redraw();\n }, 0);\n }\n } else {\n // redraw immediately\n me._redraw();\n }\n });\n\n // create event listeners for all interesting events, these events will be\n // emitted via emitter\n this.hammer = new Hammer(this.dom.root);\n this.hammer.get('pinch').set({ enable: true });\n this.hammer.get('pan').set({ threshold: 5, direction: 30 }); // 30 is ALL_DIRECTIONS in hammer.\n this.listeners = {};\n\n var events = ['tap', 'doubletap', 'press', 'pinch', 'pan', 'panstart', 'panmove', 'panend'\n // TODO: cleanup\n //'touch', 'pinch',\n //'tap', 'doubletap', 'hold',\n //'dragstart', 'drag', 'dragend',\n //'mousewheel', 'DOMMouseScroll' // DOMMouseScroll is needed for Firefox\n ];\n events.forEach(function (type) {\n var listener = function listener(event) {\n if (me.isActive()) {\n me.emit(type, event);\n }\n };\n me.hammer.on(type, listener);\n me.listeners[type] = listener;\n });\n\n // emulate a touch event (emitted before the start of a pan, pinch, tap, or press)\n hammerUtil.onTouch(this.hammer, (function (event) {\n me.emit('touch', event);\n }).bind(this));\n\n // emulate a release event (emitted after a pan, pinch, tap, or press)\n hammerUtil.onRelease(this.hammer, (function (event) {\n me.emit('release', event);\n }).bind(this));\n\n function onMouseWheel(event) {\n if (me.isActive()) {\n me.emit('mousewheel', event);\n }\n }\n this.dom.root.addEventListener('mousewheel', onMouseWheel);\n this.dom.root.addEventListener('DOMMouseScroll', onMouseWheel);\n\n // size properties of each of the panels\n this.props = {\n root: {},\n background: {},\n centerContainer: {},\n leftContainer: {},\n rightContainer: {},\n center: {},\n left: {},\n right: {},\n top: {},\n bottom: {},\n border: {},\n scrollTop: 0,\n scrollTopMin: 0\n };\n\n this.customTimes = [];\n\n // store state information needed for touch events\n this.touch = {};\n\n this.redrawCount = 0;\n this.initialDrawDone = false;\n\n // attach the root panel to the provided container\n if (!container) throw new Error('No container provided');\n container.appendChild(this.dom.root);\n };\n\n /**\n * Set options. Options will be passed to all components loaded in the Timeline.\n * @param {Object} [options]\n * {String} orientation\n * Vertical orientation for the Timeline,\n * can be 'bottom' (default) or 'top'.\n * {String | Number} width\n * Width for the timeline, a number in pixels or\n * a css string like '1000px' or '75%'. '100%' by default.\n * {String | Number} height\n * Fixed height for the Timeline, a number in pixels or\n * a css string like '400px' or '75%'. If undefined,\n * The Timeline will automatically size such that\n * its contents fit.\n * {String | Number} minHeight\n * Minimum height for the Timeline, a number in pixels or\n * a css string like '400px' or '75%'.\n * {String | Number} maxHeight\n * Maximum height for the Timeline, a number in pixels or\n * a css string like '400px' or '75%'.\n * {Number | Date | String} start\n * Start date for the visible window\n * {Number | Date | String} end\n * End date for the visible window\n */\n Core.prototype.setOptions = function (options) {\n if (options) {\n // copy the known options\n var fields = ['width', 'height', 'minHeight', 'maxHeight', 'autoResize', 'start', 'end', 'clickToUse', 'dataAttributes', 'hiddenDates', 'locale', 'locales', 'moment', 'throttleRedraw'];\n util.selectiveExtend(fields, this.options, options);\n\n this.options.orientation = { item: undefined, axis: undefined };\n if ('orientation' in options) {\n if (typeof options.orientation === 'string') {\n this.options.orientation = {\n item: options.orientation,\n axis: options.orientation\n };\n } else if (typeof options.orientation === 'object') {\n if ('item' in options.orientation) {\n this.options.orientation.item = options.orientation.item;\n }\n if ('axis' in options.orientation) {\n this.options.orientation.axis = options.orientation.axis;\n }\n }\n }\n\n if (this.options.orientation.axis === 'both') {\n if (!this.timeAxis2) {\n var timeAxis2 = this.timeAxis2 = new TimeAxis(this.body);\n timeAxis2.setOptions = function (options) {\n var _options = options ? util.extend({}, options) : {};\n _options.orientation = 'top'; // override the orientation option, always top\n TimeAxis.prototype.setOptions.call(timeAxis2, _options);\n };\n this.components.push(timeAxis2);\n }\n } else {\n if (this.timeAxis2) {\n var index = this.components.indexOf(this.timeAxis2);\n if (index !== -1) {\n this.components.splice(index, 1);\n }\n this.timeAxis2.destroy();\n this.timeAxis2 = null;\n }\n }\n\n // if the graph2d's drawPoints is a function delegate the callback to the onRender property\n if (typeof options.drawPoints == 'function') {\n options.drawPoints = {\n onRender: options.drawPoints\n };\n }\n\n if ('hiddenDates' in this.options) {\n DateUtil.convertHiddenOptions(this.options.moment, this.body, this.options.hiddenDates);\n }\n\n if ('clickToUse' in options) {\n if (options.clickToUse) {\n if (!this.activator) {\n this.activator = new Activator(this.dom.root);\n }\n } else {\n if (this.activator) {\n this.activator.destroy();\n delete this.activator;\n }\n }\n }\n\n if ('showCustomTime' in options) {\n throw new Error('Option `showCustomTime` is deprecated. Create a custom time bar via timeline.addCustomTime(time [, id])');\n }\n\n // enable/disable autoResize\n this._initAutoResize();\n }\n\n // propagate options to all components\n this.components.forEach(function (component) {\n return component.setOptions(options);\n });\n\n // enable/disable configure\n if ('configure' in options) {\n if (!this.configurator) {\n this.configurator = this._createConfigurator();\n }\n\n this.configurator.setOptions(options.configure);\n\n // collect the settings of all components, and pass them to the configuration system\n var appliedOptions = util.deepExtend({}, this.options);\n this.components.forEach(function (component) {\n util.deepExtend(appliedOptions, component.options);\n });\n this.configurator.setModuleOptions({ global: appliedOptions });\n }\n\n // override redraw with a throttled version\n if (!this._origRedraw) {\n this._origRedraw = this._redraw.bind(this);\n this._redraw = util.throttle(this._origRedraw, this.options.throttleRedraw);\n } else {\n // Not the initial run: redraw everything\n this._redraw();\n }\n };\n\n /**\n * Returns true when the Timeline is active.\n * @returns {boolean}\n */\n Core.prototype.isActive = function () {\n return !this.activator || this.activator.active;\n };\n\n /**\n * Destroy the Core, clean up all DOM elements and event listeners.\n */\n Core.prototype.destroy = function () {\n // unbind datasets\n this.setItems(null);\n this.setGroups(null);\n\n // remove all event listeners\n this.off();\n\n // stop checking for changed size\n this._stopAutoResize();\n\n // remove from DOM\n if (this.dom.root.parentNode) {\n this.dom.root.parentNode.removeChild(this.dom.root);\n }\n this.dom = null;\n\n // remove Activator\n if (this.activator) {\n this.activator.destroy();\n delete this.activator;\n }\n\n // cleanup hammer touch events\n for (var event in this.listeners) {\n if (this.listeners.hasOwnProperty(event)) {\n delete this.listeners[event];\n }\n }\n this.listeners = null;\n this.hammer = null;\n\n // give all components the opportunity to cleanup\n this.components.forEach(function (component) {\n return component.destroy();\n });\n\n this.body = null;\n };\n\n /**\n * Set a custom time bar\n * @param {Date} time\n * @param {number} [id=undefined] Optional id of the custom time bar to be adjusted.\n */\n Core.prototype.setCustomTime = function (time, id) {\n var customTimes = this.customTimes.filter(function (component) {\n return id === component.options.id;\n });\n\n if (customTimes.length === 0) {\n throw new Error('No custom time bar found with id ' + JSON.stringify(id));\n }\n\n if (customTimes.length > 0) {\n customTimes[0].setCustomTime(time);\n }\n };\n\n /**\n * Retrieve the current custom time.\n * @param {number} [id=undefined] Id of the custom time bar.\n * @return {Date | undefined} customTime\n */\n Core.prototype.getCustomTime = function (id) {\n var customTimes = this.customTimes.filter(function (component) {\n return component.options.id === id;\n });\n\n if (customTimes.length === 0) {\n throw new Error('No custom time bar found with id ' + JSON.stringify(id));\n }\n return customTimes[0].getCustomTime();\n };\n\n /**\n * Set a custom title for the custom time bar.\n * @param {String} [title] Custom title\n * @param {number} [id=undefined] Id of the custom time bar.\n */\n Core.prototype.setCustomTimeTitle = function (title, id) {\n var customTimes = this.customTimes.filter(function (component) {\n return component.options.id === id;\n });\n\n if (customTimes.length === 0) {\n throw new Error('No custom time bar found with id ' + JSON.stringify(id));\n }\n if (customTimes.length > 0) {\n return customTimes[0].setCustomTitle(title);\n }\n };\n\n /**\n * Retrieve meta information from an event.\n * Should be overridden by classes extending Core\n * @param {Event} event\n * @return {Object} An object with related information.\n */\n Core.prototype.getEventProperties = function (event) {\n return { event: event };\n };\n\n /**\n * Add custom vertical bar\n * @param {Date | String | Number} [time] A Date, unix timestamp, or\n * ISO date string. Time point where\n * the new bar should be placed.\n * If not provided, `new Date()` will\n * be used.\n * @param {Number | String} [id=undefined] Id of the new bar. Optional\n * @return {Number | String} Returns the id of the new bar\n */\n Core.prototype.addCustomTime = function (time, id) {\n var timestamp = time !== undefined ? util.convert(time, 'Date').valueOf() : new Date();\n\n var exists = this.customTimes.some(function (customTime) {\n return customTime.options.id === id;\n });\n if (exists) {\n throw new Error('A custom time with id ' + JSON.stringify(id) + ' already exists');\n }\n\n var customTime = new CustomTime(this.body, util.extend({}, this.options, {\n time: timestamp,\n id: id\n }));\n\n this.customTimes.push(customTime);\n this.components.push(customTime);\n this._redraw();\n\n return id;\n };\n\n /**\n * Remove previously added custom bar\n * @param {int} id ID of the custom bar to be removed\n * @return {boolean} True if the bar exists and is removed, false otherwise\n */\n Core.prototype.removeCustomTime = function (id) {\n var customTimes = this.customTimes.filter(function (bar) {\n return bar.options.id === id;\n });\n\n if (customTimes.length === 0) {\n throw new Error('No custom time bar found with id ' + JSON.stringify(id));\n }\n\n customTimes.forEach((function (customTime) {\n this.customTimes.splice(this.customTimes.indexOf(customTime), 1);\n this.components.splice(this.components.indexOf(customTime), 1);\n customTime.destroy();\n }).bind(this));\n };\n\n /**\n * Get the id's of the currently visible items.\n * @returns {Array} The ids of the visible items\n */\n Core.prototype.getVisibleItems = function () {\n return this.itemSet && this.itemSet.getVisibleItems() || [];\n };\n\n /**\n * Set Core window such that it fits all items\n * @param {Object} [options] Available options:\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n */\n Core.prototype.fit = function (options) {\n var range = this.getDataRange();\n\n // skip range set if there is no min and max date\n if (range.min === null && range.max === null) {\n return;\n }\n\n // apply a margin of 1% left and right of the data\n var interval = range.max - range.min;\n var min = new Date(range.min.valueOf() - interval * 0.01);\n var max = new Date(range.max.valueOf() + interval * 0.01);\n\n var animation = options && options.animation !== undefined ? options.animation : true;\n this.range.setRange(min, max, animation);\n };\n\n /**\n * Calculate the data range of the items start and end dates\n * @returns {{min: Date | null, max: Date | null}}\n * @protected\n */\n Core.prototype.getDataRange = function () {\n // must be implemented by Timeline and Graph2d\n throw new Error('Cannot invoke abstract method getDataRange');\n };\n\n /**\n * Set the visible window. Both parameters are optional, you can change only\n * start or only end. Syntax:\n *\n * TimeLine.setWindow(start, end)\n * TimeLine.setWindow(start, end, options)\n * TimeLine.setWindow(range)\n *\n * Where start and end can be a Date, number, or string, and range is an\n * object with properties start and end.\n *\n * @param {Date | Number | String | Object} [start] Start date of visible window\n * @param {Date | Number | String} [end] End date of visible window\n * @param {Object} [options] Available options:\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n */\n Core.prototype.setWindow = function (start, end, options) {\n var animation;\n if (arguments.length == 1) {\n var range = arguments[0];\n animation = range.animation !== undefined ? range.animation : true;\n this.range.setRange(range.start, range.end, animation);\n } else {\n animation = options && options.animation !== undefined ? options.animation : true;\n this.range.setRange(start, end, animation);\n }\n };\n\n /**\n * Move the window such that given time is centered on screen.\n * @param {Date | Number | String} time\n * @param {Object} [options] Available options:\n * `animation: boolean | {duration: number, easingFunction: string}`\n * If true (default), the range is animated\n * smoothly to the new window. An object can be\n * provided to specify duration and easing function.\n * Default duration is 500 ms, and default easing\n * function is 'easeInOutQuad'.\n */\n Core.prototype.moveTo = function (time, options) {\n var interval = this.range.end - this.range.start;\n var t = util.convert(time, 'Date').valueOf();\n\n var start = t - interval / 2;\n var end = t + interval / 2;\n var animation = options && options.animation !== undefined ? options.animation : true;\n\n this.range.setRange(start, end, animation);\n };\n\n /**\n * Get the visible window\n * @return {{start: Date, end: Date}} Visible range\n */\n Core.prototype.getWindow = function () {\n var range = this.range.getRange();\n return {\n start: new Date(range.start),\n end: new Date(range.end)\n };\n };\n\n /**\n * Force a redraw. Can be overridden by implementations of Core\n *\n * Note: this function will be overridden on construction with a trottled version\n */\n Core.prototype.redraw = function () {\n this._redraw();\n };\n\n /**\n * Redraw for internal use. Redraws all components. See also the public\n * method redraw.\n * @protected\n */\n Core.prototype._redraw = function () {\n this.redrawCount++;\n var resized = false;\n var options = this.options;\n var props = this.props;\n var dom = this.dom;\n\n if (!dom || !dom.container || dom.container.clientWidth == 0) return; // when destroyed, or invisible\n\n DateUtil.updateHiddenDates(this.options.moment, this.body, this.options.hiddenDates);\n\n // update class names\n if (options.orientation == 'top') {\n util.addClassName(dom.root, 'vis-top');\n util.removeClassName(dom.root, 'vis-bottom');\n } else {\n util.removeClassName(dom.root, 'vis-top');\n util.addClassName(dom.root, 'vis-bottom');\n }\n\n // update root width and height options\n dom.root.style.maxHeight = util.option.asSize(options.maxHeight, '');\n dom.root.style.minHeight = util.option.asSize(options.minHeight, '');\n dom.root.style.width = util.option.asSize(options.width, '');\n\n // calculate border widths\n props.border.left = (dom.centerContainer.offsetWidth - dom.centerContainer.clientWidth) / 2;\n props.border.right = props.border.left;\n props.border.top = (dom.centerContainer.offsetHeight - dom.centerContainer.clientHeight) / 2;\n props.border.bottom = props.border.top;\n var borderRootHeight = dom.root.offsetHeight - dom.root.clientHeight;\n var borderRootWidth = dom.root.offsetWidth - dom.root.clientWidth;\n\n // workaround for a bug in IE: the clientWidth of an element with\n // a height:0px and overflow:hidden is not calculated and always has value 0\n if (dom.centerContainer.clientHeight === 0) {\n props.border.left = props.border.top;\n props.border.right = props.border.left;\n }\n if (dom.root.clientHeight === 0) {\n borderRootWidth = borderRootHeight;\n }\n\n // calculate the heights. If any of the side panels is empty, we set the height to\n // minus the border width, such that the border will be invisible\n props.center.height = dom.center.offsetHeight;\n props.left.height = dom.left.offsetHeight;\n props.right.height = dom.right.offsetHeight;\n props.top.height = dom.top.clientHeight || -props.border.top;\n props.bottom.height = dom.bottom.clientHeight || -props.border.bottom;\n\n // TODO: compensate borders when any of the panels is empty.\n\n // apply auto height\n // TODO: only calculate autoHeight when needed (else we cause an extra reflow/repaint of the DOM)\n var contentHeight = Math.max(props.left.height, props.center.height, props.right.height);\n var autoHeight = props.top.height + contentHeight + props.bottom.height + borderRootHeight + props.border.top + props.border.bottom;\n dom.root.style.height = util.option.asSize(options.height, autoHeight + 'px');\n\n // calculate heights of the content panels\n props.root.height = dom.root.offsetHeight;\n props.background.height = props.root.height - borderRootHeight;\n var containerHeight = props.root.height - props.top.height - props.bottom.height - borderRootHeight;\n props.centerContainer.height = containerHeight;\n props.leftContainer.height = containerHeight;\n props.rightContainer.height = props.leftContainer.height;\n\n // calculate the widths of the panels\n props.root.width = dom.root.offsetWidth;\n props.background.width = props.root.width - borderRootWidth;\n props.left.width = dom.leftContainer.clientWidth || -props.border.left;\n props.leftContainer.width = props.left.width;\n props.right.width = dom.rightContainer.clientWidth || -props.border.right;\n props.rightContainer.width = props.right.width;\n var centerWidth = props.root.width - props.left.width - props.right.width - borderRootWidth;\n props.center.width = centerWidth;\n props.centerContainer.width = centerWidth;\n props.top.width = centerWidth;\n props.bottom.width = centerWidth;\n\n // resize the panels\n dom.background.style.height = props.background.height + 'px';\n dom.backgroundVertical.style.height = props.background.height + 'px';\n dom.backgroundHorizontal.style.height = props.centerContainer.height + 'px';\n dom.centerContainer.style.height = props.centerContainer.height + 'px';\n dom.leftContainer.style.height = props.leftContainer.height + 'px';\n dom.rightContainer.style.height = props.rightContainer.height + 'px';\n\n dom.background.style.width = props.background.width + 'px';\n dom.backgroundVertical.style.width = props.centerContainer.width + 'px';\n dom.backgroundHorizontal.style.width = props.background.width + 'px';\n dom.centerContainer.style.width = props.center.width + 'px';\n dom.top.style.width = props.top.width + 'px';\n dom.bottom.style.width = props.bottom.width + 'px';\n\n // reposition the panels\n dom.background.style.left = '0';\n dom.background.style.top = '0';\n dom.backgroundVertical.style.left = props.left.width + props.border.left + 'px';\n dom.backgroundVertical.style.top = '0';\n dom.backgroundHorizontal.style.left = '0';\n dom.backgroundHorizontal.style.top = props.top.height + 'px';\n dom.centerContainer.style.left = props.left.width + 'px';\n dom.centerContainer.style.top = props.top.height + 'px';\n dom.leftContainer.style.left = '0';\n dom.leftContainer.style.top = props.top.height + 'px';\n dom.rightContainer.style.left = props.left.width + props.center.width + 'px';\n dom.rightContainer.style.top = props.top.height + 'px';\n dom.top.style.left = props.left.width + 'px';\n dom.top.style.top = '0';\n dom.bottom.style.left = props.left.width + 'px';\n dom.bottom.style.top = props.top.height + props.centerContainer.height + 'px';\n\n // update the scrollTop, feasible range for the offset can be changed\n // when the height of the Core or of the contents of the center changed\n this._updateScrollTop();\n\n // reposition the scrollable contents\n var offset = this.props.scrollTop;\n if (options.orientation.item != 'top') {\n offset += Math.max(this.props.centerContainer.height - this.props.center.height - this.props.border.top - this.props.border.bottom, 0);\n }\n dom.center.style.left = '0';\n dom.center.style.top = offset + 'px';\n dom.left.style.left = '0';\n dom.left.style.top = offset + 'px';\n dom.right.style.left = '0';\n dom.right.style.top = offset + 'px';\n\n // show shadows when vertical scrolling is available\n var visibilityTop = this.props.scrollTop == 0 ? 'hidden' : '';\n var visibilityBottom = this.props.scrollTop == this.props.scrollTopMin ? 'hidden' : '';\n dom.shadowTop.style.visibility = visibilityTop;\n dom.shadowBottom.style.visibility = visibilityBottom;\n dom.shadowTopLeft.style.visibility = visibilityTop;\n dom.shadowBottomLeft.style.visibility = visibilityBottom;\n dom.shadowTopRight.style.visibility = visibilityTop;\n dom.shadowBottomRight.style.visibility = visibilityBottom;\n\n // redraw all components\n this.components.forEach(function (component) {\n resized = component.redraw() || resized;\n });\n var MAX_REDRAW = 5;\n if (resized) {\n if (this.redrawCount < MAX_REDRAW) {\n this.body.emitter.emit('_change');\n return;\n } else {\n console.log('WARNING: infinite loop in redraw?');\n }\n } else {\n this.redrawCount = 0;\n }\n this.initialDrawDone = true;\n\n //Emit public 'changed' event for UI updates, see issue #1592\n this.body.emitter.emit(\"changed\");\n };\n\n // TODO: deprecated since version 1.1.0, remove some day\n Core.prototype.repaint = function () {\n throw new Error('Function repaint is deprecated. Use redraw instead.');\n };\n\n /**\n * Set a current time. This can be used for example to ensure that a client's\n * time is synchronized with a shared server time.\n * Only applicable when option `showCurrentTime` is true.\n * @param {Date | String | Number} time A Date, unix timestamp, or\n * ISO date string.\n */\n Core.prototype.setCurrentTime = function (time) {\n if (!this.currentTime) {\n throw new Error('Option showCurrentTime must be true');\n }\n\n this.currentTime.setCurrentTime(time);\n };\n\n /**\n * Get the current time.\n * Only applicable when option `showCurrentTime` is true.\n * @return {Date} Returns the current time.\n */\n Core.prototype.getCurrentTime = function () {\n if (!this.currentTime) {\n throw new Error('Option showCurrentTime must be true');\n }\n\n return this.currentTime.getCurrentTime();\n };\n\n /**\n * Convert a position on screen (pixels) to a datetime\n * @param {int} x Position on the screen in pixels\n * @return {Date} time The datetime the corresponds with given position x\n * @protected\n */\n // TODO: move this function to Range\n Core.prototype._toTime = function (x) {\n return DateUtil.toTime(this, x, this.props.center.width);\n };\n\n /**\n * Convert a position on the global screen (pixels) to a datetime\n * @param {int} x Position on the screen in pixels\n * @return {Date} time The datetime the corresponds with given position x\n * @protected\n */\n // TODO: move this function to Range\n Core.prototype._toGlobalTime = function (x) {\n return DateUtil.toTime(this, x, this.props.root.width);\n //var conversion = this.range.conversion(this.props.root.width);\n //return new Date(x / conversion.scale + conversion.offset);\n };\n\n /**\n * Convert a datetime (Date object) into a position on the screen\n * @param {Date} time A date\n * @return {int} x The position on the screen in pixels which corresponds\n * with the given date.\n * @protected\n */\n // TODO: move this function to Range\n Core.prototype._toScreen = function (time) {\n return DateUtil.toScreen(this, time, this.props.center.width);\n };\n\n /**\n * Convert a datetime (Date object) into a position on the root\n * This is used to get the pixel density estimate for the screen, not the center panel\n * @param {Date} time A date\n * @return {int} x The position on root in pixels which corresponds\n * with the given date.\n * @protected\n */\n // TODO: move this function to Range\n Core.prototype._toGlobalScreen = function (time) {\n return DateUtil.toScreen(this, time, this.props.root.width);\n //var conversion = this.range.conversion(this.props.root.width);\n //return (time.valueOf() - conversion.offset) * conversion.scale;\n };\n\n /**\n * Initialize watching when option autoResize is true\n * @private\n */\n Core.prototype._initAutoResize = function () {\n if (this.options.autoResize == true) {\n this._startAutoResize();\n } else {\n this._stopAutoResize();\n }\n };\n\n /**\n * Watch for changes in the size of the container. On resize, the Panel will\n * automatically redraw itself.\n * @private\n */\n Core.prototype._startAutoResize = function () {\n var me = this;\n\n this._stopAutoResize();\n\n this._onResize = function () {\n if (me.options.autoResize != true) {\n // stop watching when the option autoResize is changed to false\n me._stopAutoResize();\n return;\n }\n\n if (me.dom.root) {\n // check whether the frame is resized\n // Note: we compare offsetWidth here, not clientWidth. For some reason,\n // IE does not restore the clientWidth from 0 to the actual width after\n // changing the timeline's container display style from none to visible\n if (me.dom.root.offsetWidth != me.props.lastWidth || me.dom.root.offsetHeight != me.props.lastHeight) {\n me.props.lastWidth = me.dom.root.offsetWidth;\n me.props.lastHeight = me.dom.root.offsetHeight;\n\n me.body.emitter.emit('_change');\n }\n }\n };\n\n // add event listener to window resize\n util.addEventListener(window, 'resize', this._onResize);\n\n //Prevent initial unnecessary redraw\n if (me.dom.root) {\n me.props.lastWidth = me.dom.root.offsetWidth;\n me.props.lastHeight = me.dom.root.offsetHeight;\n }\n\n this.watchTimer = setInterval(this._onResize, 1000);\n };\n\n /**\n * Stop watching for a resize of the frame.\n * @private\n */\n Core.prototype._stopAutoResize = function () {\n if (this.watchTimer) {\n clearInterval(this.watchTimer);\n this.watchTimer = undefined;\n }\n\n // remove event listener on window.resize\n if (this._onResize) {\n util.removeEventListener(window, 'resize', this._onResize);\n this._onResize = null;\n }\n };\n\n /**\n * Start moving the timeline vertically\n * @param {Event} event\n * @private\n */\n Core.prototype._onTouch = function (event) {\n this.touch.allowDragging = true;\n this.touch.initialScrollTop = this.props.scrollTop;\n };\n\n /**\n * Start moving the timeline vertically\n * @param {Event} event\n * @private\n */\n Core.prototype._onPinch = function (event) {\n this.touch.allowDragging = false;\n };\n\n /**\n * Move the timeline vertically\n * @param {Event} event\n * @private\n */\n Core.prototype._onDrag = function (event) {\n // refuse to drag when we where pinching to prevent the timeline make a jump\n // when releasing the fingers in opposite order from the touch screen\n if (!this.touch.allowDragging) return;\n\n var delta = event.deltaY;\n\n var oldScrollTop = this._getScrollTop();\n var newScrollTop = this._setScrollTop(this.touch.initialScrollTop + delta);\n\n if (newScrollTop != oldScrollTop) {\n this.emit(\"verticalDrag\");\n }\n };\n\n /**\n * Apply a scrollTop\n * @param {Number} scrollTop\n * @returns {Number} scrollTop Returns the applied scrollTop\n * @private\n */\n Core.prototype._setScrollTop = function (scrollTop) {\n this.props.scrollTop = scrollTop;\n this._updateScrollTop();\n return this.props.scrollTop;\n };\n\n /**\n * Update the current scrollTop when the height of the containers has been changed\n * @returns {Number} scrollTop Returns the applied scrollTop\n * @private\n */\n Core.prototype._updateScrollTop = function () {\n // recalculate the scrollTopMin\n var scrollTopMin = Math.min(this.props.centerContainer.height - this.props.center.height, 0); // is negative or zero\n if (scrollTopMin != this.props.scrollTopMin) {\n // in case of bottom orientation, change the scrollTop such that the contents\n // do not move relative to the time axis at the bottom\n if (this.options.orientation.item != 'top') {\n this.props.scrollTop += scrollTopMin - this.props.scrollTopMin;\n }\n this.props.scrollTopMin = scrollTopMin;\n }\n\n // limit the scrollTop to the feasible scroll range\n if (this.props.scrollTop > 0) this.props.scrollTop = 0;\n if (this.props.scrollTop < scrollTopMin) this.props.scrollTop = scrollTopMin;\n\n return this.props.scrollTop;\n };\n\n /**\n * Get the current scrollTop\n * @returns {number} scrollTop\n * @private\n */\n Core.prototype._getScrollTop = function () {\n return this.props.scrollTop;\n };\n\n /**\n * Load a configurator\n * @return {Object}\n * @private\n */\n Core.prototype._createConfigurator = function () {\n throw new Error('Cannot invoke abstract method _createConfigurator');\n };\n\n module.exports = Core;\n\n/***/ },\n/* 28 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var TimeStep = __webpack_require__(29);\n var Component = __webpack_require__(25);\n var Group = __webpack_require__(30);\n var BackgroundGroup = __webpack_require__(34);\n var BoxItem = __webpack_require__(35);\n var PointItem = __webpack_require__(36);\n var RangeItem = __webpack_require__(32);\n var BackgroundItem = __webpack_require__(37);\n\n var UNGROUPED = '__ungrouped__'; // reserved group id for ungrouped items\n var BACKGROUND = '__background__'; // reserved group id for background items without group\n\n /**\n * An ItemSet holds a set of items and ranges which can be displayed in a\n * range. The width is determined by the parent of the ItemSet, and the height\n * is determined by the size of the items.\n * @param {{dom: Object, domProps: Object, emitter: Emitter, range: Range}} body\n * @param {Object} [options] See ItemSet.setOptions for the available options.\n * @constructor ItemSet\n * @extends Component\n */\n function ItemSet(body, options) {\n this.body = body;\n\n this.defaultOptions = {\n type: null, // 'box', 'point', 'range', 'background'\n orientation: {\n item: 'bottom' // item orientation: 'top' or 'bottom'\n },\n align: 'auto', // alignment of box items\n stack: true,\n groupOrderSwap: function groupOrderSwap(fromGroup, toGroup, groups) {\n var targetOrder = toGroup.order;\n toGroup.order = fromGroup.order;\n fromGroup.order = targetOrder;\n },\n groupOrder: 'order',\n\n selectable: true,\n multiselect: false,\n itemsAlwaysDraggable: false,\n\n editable: {\n updateTime: false,\n updateGroup: false,\n add: false,\n remove: false\n },\n\n groupEditable: {\n order: false,\n add: false,\n remove: false\n },\n\n snap: TimeStep.snap,\n\n onAdd: function onAdd(item, callback) {\n callback(item);\n },\n onUpdate: function onUpdate(item, callback) {\n callback(item);\n },\n onMove: function onMove(item, callback) {\n callback(item);\n },\n onRemove: function onRemove(item, callback) {\n callback(item);\n },\n onMoving: function onMoving(item, callback) {\n callback(item);\n },\n onAddGroup: function onAddGroup(item, callback) {\n callback(item);\n },\n onMoveGroup: function onMoveGroup(item, callback) {\n callback(item);\n },\n onRemoveGroup: function onRemoveGroup(item, callback) {\n callback(item);\n },\n\n margin: {\n item: {\n horizontal: 10,\n vertical: 10\n },\n axis: 20\n }\n };\n\n // options is shared by this ItemSet and all its items\n this.options = util.extend({}, this.defaultOptions);\n\n // options for getting items from the DataSet with the correct type\n this.itemOptions = {\n type: { start: 'Date', end: 'Date' }\n };\n\n this.conversion = {\n toScreen: body.util.toScreen,\n toTime: body.util.toTime\n };\n this.dom = {};\n this.props = {};\n this.hammer = null;\n\n var me = this;\n this.itemsData = null; // DataSet\n this.groupsData = null; // DataSet\n\n // listeners for the DataSet of the items\n this.itemListeners = {\n 'add': function add(event, params, senderId) {\n me._onAdd(params.items);\n },\n 'update': function update(event, params, senderId) {\n me._onUpdate(params.items);\n },\n 'remove': function remove(event, params, senderId) {\n me._onRemove(params.items);\n }\n };\n\n // listeners for the DataSet of the groups\n this.groupListeners = {\n 'add': function add(event, params, senderId) {\n me._onAddGroups(params.items);\n },\n 'update': function update(event, params, senderId) {\n me._onUpdateGroups(params.items);\n },\n 'remove': function remove(event, params, senderId) {\n me._onRemoveGroups(params.items);\n }\n };\n\n this.items = {}; // object with an Item for every data item\n this.groups = {}; // Group object for every group\n this.groupIds = [];\n\n this.selection = []; // list with the ids of all selected nodes\n this.stackDirty = true; // if true, all items will be restacked on next redraw\n\n this.touchParams = {}; // stores properties while dragging\n this.groupTouchParams = {};\n // create the HTML DOM\n\n this._create();\n\n this.setOptions(options);\n }\n\n ItemSet.prototype = new Component();\n\n // available item types will be registered here\n ItemSet.types = {\n background: BackgroundItem,\n box: BoxItem,\n range: RangeItem,\n point: PointItem\n };\n\n /**\n * Create the HTML DOM for the ItemSet\n */\n ItemSet.prototype._create = function () {\n var frame = document.createElement('div');\n frame.className = 'vis-itemset';\n frame['timeline-itemset'] = this;\n this.dom.frame = frame;\n\n // create background panel\n var background = document.createElement('div');\n background.className = 'vis-background';\n frame.appendChild(background);\n this.dom.background = background;\n\n // create foreground panel\n var foreground = document.createElement('div');\n foreground.className = 'vis-foreground';\n frame.appendChild(foreground);\n this.dom.foreground = foreground;\n\n // create axis panel\n var axis = document.createElement('div');\n axis.className = 'vis-axis';\n this.dom.axis = axis;\n\n // create labelset\n var labelSet = document.createElement('div');\n labelSet.className = 'vis-labelset';\n this.dom.labelSet = labelSet;\n\n // create ungrouped Group\n this._updateUngrouped();\n\n // create background Group\n var backgroundGroup = new BackgroundGroup(BACKGROUND, null, this);\n backgroundGroup.show();\n this.groups[BACKGROUND] = backgroundGroup;\n\n // attach event listeners\n // Note: we bind to the centerContainer for the case where the height\n // of the center container is larger than of the ItemSet, so we\n // can click in the empty area to create a new item or deselect an item.\n this.hammer = new Hammer(this.body.dom.centerContainer);\n\n // drag items when selected\n this.hammer.on('hammer.input', (function (event) {\n if (event.isFirst) {\n this._onTouch(event);\n }\n }).bind(this));\n this.hammer.on('panstart', this._onDragStart.bind(this));\n this.hammer.on('panmove', this._onDrag.bind(this));\n this.hammer.on('panend', this._onDragEnd.bind(this));\n this.hammer.get('pan').set({ threshold: 5, direction: 30 }); // 30 is ALL_DIRECTIONS in hammer.\n\n // single select (or unselect) when tapping an item\n this.hammer.on('tap', this._onSelectItem.bind(this));\n\n // multi select when holding mouse/touch, or on ctrl+click\n this.hammer.on('press', this._onMultiSelectItem.bind(this));\n\n // add item on doubletap\n this.hammer.on('doubletap', this._onAddItem.bind(this));\n\n this.groupHammer = new Hammer(this.body.dom.leftContainer);\n this.groupHammer.on('panstart', this._onGroupDragStart.bind(this));\n this.groupHammer.on('panmove', this._onGroupDrag.bind(this));\n this.groupHammer.on('panend', this._onGroupDragEnd.bind(this));\n this.groupHammer.get('pan').set({ threshold: 5, direction: 30 });\n\n // attach to the DOM\n this.show();\n };\n\n /**\n * Set options for the ItemSet. Existing options will be extended/overwritten.\n * @param {Object} [options] The following options are available:\n * {String} type\n * Default type for the items. Choose from 'box'\n * (default), 'point', 'range', or 'background'.\n * The default style can be overwritten by\n * individual items.\n * {String} align\n * Alignment for the items, only applicable for\n * BoxItem. Choose 'center' (default), 'left', or\n * 'right'.\n * {String} orientation.item\n * Orientation of the item set. Choose 'top' or\n * 'bottom' (default).\n * {Function} groupOrder\n * A sorting function for ordering groups\n * {Boolean} stack\n * If true (default), items will be stacked on\n * top of each other.\n * {Number} margin.axis\n * Margin between the axis and the items in pixels.\n * Default is 20.\n * {Number} margin.item.horizontal\n * Horizontal margin between items in pixels.\n * Default is 10.\n * {Number} margin.item.vertical\n * Vertical Margin between items in pixels.\n * Default is 10.\n * {Number} margin.item\n * Margin between items in pixels in both horizontal\n * and vertical direction. Default is 10.\n * {Number} margin\n * Set margin for both axis and items in pixels.\n * {Boolean} selectable\n * If true (default), items can be selected.\n * {Boolean} multiselect\n * If true, multiple items can be selected.\n * False by default.\n * {Boolean} editable\n * Set all editable options to true or false\n * {Boolean} editable.updateTime\n * Allow dragging an item to an other moment in time\n * {Boolean} editable.updateGroup\n * Allow dragging an item to an other group\n * {Boolean} editable.add\n * Allow creating new items on double tap\n * {Boolean} editable.remove\n * Allow removing items by clicking the delete button\n * top right of a selected item.\n * {Function(item: Item, callback: Function)} onAdd\n * Callback function triggered when an item is about to be added:\n * when the user double taps an empty space in the Timeline.\n * {Function(item: Item, callback: Function)} onUpdate\n * Callback function fired when an item is about to be updated.\n * This function typically has to show a dialog where the user\n * change the item. If not implemented, nothing happens.\n * {Function(item: Item, callback: Function)} onMove\n * Fired when an item has been moved. If not implemented,\n * the move action will be accepted.\n * {Function(item: Item, callback: Function)} onRemove\n * Fired when an item is about to be deleted.\n * If not implemented, the item will be always removed.\n */\n ItemSet.prototype.setOptions = function (options) {\n if (options) {\n // copy all options that we know\n var fields = ['type', 'align', 'order', 'stack', 'selectable', 'multiselect', 'itemsAlwaysDraggable', 'multiselectPerGroup', 'groupOrder', 'dataAttributes', 'template', 'groupTemplate', 'hide', 'snap', 'groupOrderSwap'];\n util.selectiveExtend(fields, this.options, options);\n\n if ('orientation' in options) {\n if (typeof options.orientation === 'string') {\n this.options.orientation.item = options.orientation === 'top' ? 'top' : 'bottom';\n } else if (typeof options.orientation === 'object' && 'item' in options.orientation) {\n this.options.orientation.item = options.orientation.item;\n }\n }\n\n if ('margin' in options) {\n if (typeof options.margin === 'number') {\n this.options.margin.axis = options.margin;\n this.options.margin.item.horizontal = options.margin;\n this.options.margin.item.vertical = options.margin;\n } else if (typeof options.margin === 'object') {\n util.selectiveExtend(['axis'], this.options.margin, options.margin);\n if ('item' in options.margin) {\n if (typeof options.margin.item === 'number') {\n this.options.margin.item.horizontal = options.margin.item;\n this.options.margin.item.vertical = options.margin.item;\n } else if (typeof options.margin.item === 'object') {\n util.selectiveExtend(['horizontal', 'vertical'], this.options.margin.item, options.margin.item);\n }\n }\n }\n }\n\n if ('editable' in options) {\n if (typeof options.editable === 'boolean') {\n this.options.editable.updateTime = options.editable;\n this.options.editable.updateGroup = options.editable;\n this.options.editable.add = options.editable;\n this.options.editable.remove = options.editable;\n } else if (typeof options.editable === 'object') {\n util.selectiveExtend(['updateTime', 'updateGroup', 'add', 'remove'], this.options.editable, options.editable);\n }\n }\n\n if ('groupEditable' in options) {\n if (typeof options.groupEditable === 'boolean') {\n this.options.groupEditable.order = options.groupEditable;\n this.options.groupEditable.add = options.groupEditable;\n this.options.groupEditable.remove = options.groupEditable;\n } else if (typeof options.groupEditable === 'object') {\n util.selectiveExtend(['order', 'add', 'remove'], this.options.groupEditable, options.groupEditable);\n }\n }\n\n // callback functions\n var addCallback = (function (name) {\n var fn = options[name];\n if (fn) {\n if (!(fn instanceof Function)) {\n throw new Error('option ' + name + ' must be a function ' + name + '(item, callback)');\n }\n this.options[name] = fn;\n }\n }).bind(this);\n ['onAdd', 'onUpdate', 'onRemove', 'onMove', 'onMoving', 'onAddGroup', 'onMoveGroup', 'onRemoveGroup'].forEach(addCallback);\n\n // force the itemSet to refresh: options like orientation and margins may be changed\n this.markDirty();\n }\n };\n\n /**\n * Mark the ItemSet dirty so it will refresh everything with next redraw.\n * Optionally, all items can be marked as dirty and be refreshed.\n * @param {{refreshItems: boolean}} [options]\n */\n ItemSet.prototype.markDirty = function (options) {\n this.groupIds = [];\n this.stackDirty = true;\n\n if (options && options.refreshItems) {\n util.forEach(this.items, function (item) {\n item.dirty = true;\n if (item.displayed) item.redraw();\n });\n }\n };\n\n /**\n * Destroy the ItemSet\n */\n ItemSet.prototype.destroy = function () {\n this.hide();\n this.setItems(null);\n this.setGroups(null);\n\n this.hammer = null;\n\n this.body = null;\n this.conversion = null;\n };\n\n /**\n * Hide the component from the DOM\n */\n ItemSet.prototype.hide = function () {\n // remove the frame containing the items\n if (this.dom.frame.parentNode) {\n this.dom.frame.parentNode.removeChild(this.dom.frame);\n }\n\n // remove the axis with dots\n if (this.dom.axis.parentNode) {\n this.dom.axis.parentNode.removeChild(this.dom.axis);\n }\n\n // remove the labelset containing all group labels\n if (this.dom.labelSet.parentNode) {\n this.dom.labelSet.parentNode.removeChild(this.dom.labelSet);\n }\n };\n\n /**\n * Show the component in the DOM (when not already visible).\n * @return {Boolean} changed\n */\n ItemSet.prototype.show = function () {\n // show frame containing the items\n if (!this.dom.frame.parentNode) {\n this.body.dom.center.appendChild(this.dom.frame);\n }\n\n // show axis with dots\n if (!this.dom.axis.parentNode) {\n this.body.dom.backgroundVertical.appendChild(this.dom.axis);\n }\n\n // show labelset containing labels\n if (!this.dom.labelSet.parentNode) {\n this.body.dom.left.appendChild(this.dom.labelSet);\n }\n };\n\n /**\n * Set selected items by their id. Replaces the current selection\n * Unknown id's are silently ignored.\n * @param {string[] | string} [ids] An array with zero or more id's of the items to be\n * selected, or a single item id. If ids is undefined\n * or an empty array, all items will be unselected.\n */\n ItemSet.prototype.setSelection = function (ids) {\n var i, ii, id, item;\n\n if (ids == undefined) ids = [];\n if (!Array.isArray(ids)) ids = [ids];\n\n // unselect currently selected items\n for (i = 0, ii = this.selection.length; i < ii; i++) {\n id = this.selection[i];\n item = this.items[id];\n if (item) item.unselect();\n }\n\n // select items\n this.selection = [];\n for (i = 0, ii = ids.length; i < ii; i++) {\n id = ids[i];\n item = this.items[id];\n if (item) {\n this.selection.push(id);\n item.select();\n }\n }\n };\n\n /**\n * Get the selected items by their id\n * @return {Array} ids The ids of the selected items\n */\n ItemSet.prototype.getSelection = function () {\n return this.selection.concat([]);\n };\n\n /**\n * Get the id's of the currently visible items.\n * @returns {Array} The ids of the visible items\n */\n ItemSet.prototype.getVisibleItems = function () {\n var range = this.body.range.getRange();\n var left = this.body.util.toScreen(range.start);\n var right = this.body.util.toScreen(range.end);\n\n var ids = [];\n for (var groupId in this.groups) {\n if (this.groups.hasOwnProperty(groupId)) {\n var group = this.groups[groupId];\n var rawVisibleItems = group.visibleItems;\n\n // filter the \"raw\" set with visibleItems into a set which is really\n // visible by pixels\n for (var i = 0; i < rawVisibleItems.length; i++) {\n var item = rawVisibleItems[i];\n // TODO: also check whether visible vertically\n if (item.left < right && item.left + item.width > left) {\n ids.push(item.id);\n }\n }\n }\n }\n\n return ids;\n };\n\n /**\n * Deselect a selected item\n * @param {String | Number} id\n * @private\n */\n ItemSet.prototype._deselect = function (id) {\n var selection = this.selection;\n for (var i = 0, ii = selection.length; i < ii; i++) {\n if (selection[i] == id) {\n // non-strict comparison!\n selection.splice(i, 1);\n break;\n }\n }\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n ItemSet.prototype.redraw = function () {\n var margin = this.options.margin,\n range = this.body.range,\n asSize = util.option.asSize,\n options = this.options,\n orientation = options.orientation.item,\n resized = false,\n frame = this.dom.frame;\n\n // recalculate absolute position (before redrawing groups)\n this.props.top = this.body.domProps.top.height + this.body.domProps.border.top;\n this.props.left = this.body.domProps.left.width + this.body.domProps.border.left;\n\n // update class name\n frame.className = 'vis-itemset';\n\n // reorder the groups (if needed)\n resized = this._orderGroups() || resized;\n\n // check whether zoomed (in that case we need to re-stack everything)\n // TODO: would be nicer to get this as a trigger from Range\n var visibleInterval = range.end - range.start;\n var zoomed = visibleInterval != this.lastVisibleInterval || this.props.width != this.props.lastWidth;\n if (zoomed) this.stackDirty = true;\n this.lastVisibleInterval = visibleInterval;\n this.props.lastWidth = this.props.width;\n\n var restack = this.stackDirty;\n var firstGroup = this._firstGroup();\n var firstMargin = {\n item: margin.item,\n axis: margin.axis\n };\n var nonFirstMargin = {\n item: margin.item,\n axis: margin.item.vertical / 2\n };\n var height = 0;\n var minHeight = margin.axis + margin.item.vertical;\n\n // redraw the background group\n this.groups[BACKGROUND].redraw(range, nonFirstMargin, restack);\n\n // redraw all regular groups\n util.forEach(this.groups, function (group) {\n var groupMargin = group == firstGroup ? firstMargin : nonFirstMargin;\n var groupResized = group.redraw(range, groupMargin, restack);\n resized = groupResized || resized;\n height += group.height;\n });\n height = Math.max(height, minHeight);\n this.stackDirty = false;\n\n // update frame height\n frame.style.height = asSize(height);\n\n // calculate actual size\n this.props.width = frame.offsetWidth;\n this.props.height = height;\n\n // reposition axis\n this.dom.axis.style.top = asSize(orientation == 'top' ? this.body.domProps.top.height + this.body.domProps.border.top : this.body.domProps.top.height + this.body.domProps.centerContainer.height);\n this.dom.axis.style.left = '0';\n\n // check if this component is resized\n resized = this._isResized() || resized;\n\n return resized;\n };\n\n /**\n * Get the first group, aligned with the axis\n * @return {Group | null} firstGroup\n * @private\n */\n ItemSet.prototype._firstGroup = function () {\n var firstGroupIndex = this.options.orientation.item == 'top' ? 0 : this.groupIds.length - 1;\n var firstGroupId = this.groupIds[firstGroupIndex];\n var firstGroup = this.groups[firstGroupId] || this.groups[UNGROUPED];\n\n return firstGroup || null;\n };\n\n /**\n * Create or delete the group holding all ungrouped items. This group is used when\n * there are no groups specified.\n * @protected\n */\n ItemSet.prototype._updateUngrouped = function () {\n var ungrouped = this.groups[UNGROUPED];\n var background = this.groups[BACKGROUND];\n var item, itemId;\n\n if (this.groupsData) {\n // remove the group holding all ungrouped items\n if (ungrouped) {\n ungrouped.hide();\n delete this.groups[UNGROUPED];\n\n for (itemId in this.items) {\n if (this.items.hasOwnProperty(itemId)) {\n item = this.items[itemId];\n item.parent && item.parent.remove(item);\n var groupId = this._getGroupId(item.data);\n var group = this.groups[groupId];\n group && group.add(item) || item.hide();\n }\n }\n }\n } else {\n // create a group holding all (unfiltered) items\n if (!ungrouped) {\n var id = null;\n var data = null;\n ungrouped = new Group(id, data, this);\n this.groups[UNGROUPED] = ungrouped;\n\n for (itemId in this.items) {\n if (this.items.hasOwnProperty(itemId)) {\n item = this.items[itemId];\n ungrouped.add(item);\n }\n }\n\n ungrouped.show();\n }\n }\n };\n\n /**\n * Get the element for the labelset\n * @return {HTMLElement} labelSet\n */\n ItemSet.prototype.getLabelSet = function () {\n return this.dom.labelSet;\n };\n\n /**\n * Set items\n * @param {vis.DataSet | null} items\n */\n ItemSet.prototype.setItems = function (items) {\n var me = this,\n ids,\n oldItemsData = this.itemsData;\n\n // replace the dataset\n if (!items) {\n this.itemsData = null;\n } else if (items instanceof DataSet || items instanceof DataView) {\n this.itemsData = items;\n } else {\n throw new TypeError('Data must be an instance of DataSet or DataView');\n }\n\n if (oldItemsData) {\n // unsubscribe from old dataset\n util.forEach(this.itemListeners, function (callback, event) {\n oldItemsData.off(event, callback);\n });\n\n // remove all drawn items\n ids = oldItemsData.getIds();\n this._onRemove(ids);\n }\n\n if (this.itemsData) {\n // subscribe to new dataset\n var id = this.id;\n util.forEach(this.itemListeners, function (callback, event) {\n me.itemsData.on(event, callback, id);\n });\n\n // add all new items\n ids = this.itemsData.getIds();\n this._onAdd(ids);\n\n // update the group holding all ungrouped items\n this._updateUngrouped();\n }\n\n this.body.emitter.emit('_change', { queue: true });\n };\n\n /**\n * Get the current items\n * @returns {vis.DataSet | null}\n */\n ItemSet.prototype.getItems = function () {\n return this.itemsData;\n };\n\n /**\n * Set groups\n * @param {vis.DataSet} groups\n */\n ItemSet.prototype.setGroups = function (groups) {\n var me = this,\n ids;\n\n // unsubscribe from current dataset\n if (this.groupsData) {\n util.forEach(this.groupListeners, function (callback, event) {\n me.groupsData.off(event, callback);\n });\n\n // remove all drawn groups\n ids = this.groupsData.getIds();\n this.groupsData = null;\n this._onRemoveGroups(ids); // note: this will cause a redraw\n }\n\n // replace the dataset\n if (!groups) {\n this.groupsData = null;\n } else if (groups instanceof DataSet || groups instanceof DataView) {\n this.groupsData = groups;\n } else {\n throw new TypeError('Data must be an instance of DataSet or DataView');\n }\n\n if (this.groupsData) {\n // subscribe to new dataset\n var id = this.id;\n util.forEach(this.groupListeners, function (callback, event) {\n me.groupsData.on(event, callback, id);\n });\n\n // draw all ms\n ids = this.groupsData.getIds();\n this._onAddGroups(ids);\n }\n\n // update the group holding all ungrouped items\n this._updateUngrouped();\n\n // update the order of all items in each group\n this._order();\n\n this.body.emitter.emit('_change', { queue: true });\n };\n\n /**\n * Get the current groups\n * @returns {vis.DataSet | null} groups\n */\n ItemSet.prototype.getGroups = function () {\n return this.groupsData;\n };\n\n /**\n * Remove an item by its id\n * @param {String | Number} id\n */\n ItemSet.prototype.removeItem = function (id) {\n var item = this.itemsData.get(id),\n dataset = this.itemsData.getDataSet();\n\n if (item) {\n // confirm deletion\n this.options.onRemove(item, function (item) {\n if (item) {\n // remove by id here, it is possible that an item has no id defined\n // itself, so better not delete by the item itself\n dataset.remove(id);\n }\n });\n }\n };\n\n /**\n * Get the time of an item based on it's data and options.type\n * @param {Object} itemData\n * @returns {string} Returns the type\n * @private\n */\n ItemSet.prototype._getType = function (itemData) {\n return itemData.type || this.options.type || (itemData.end ? 'range' : 'box');\n };\n\n /**\n * Get the group id for an item\n * @param {Object} itemData\n * @returns {string} Returns the groupId\n * @private\n */\n ItemSet.prototype._getGroupId = function (itemData) {\n var type = this._getType(itemData);\n if (type == 'background' && itemData.group == undefined) {\n return BACKGROUND;\n } else {\n return this.groupsData ? itemData.group : UNGROUPED;\n }\n };\n\n /**\n * Handle updated items\n * @param {Number[]} ids\n * @protected\n */\n ItemSet.prototype._onUpdate = function (ids) {\n var me = this;\n\n ids.forEach((function (id) {\n var itemData = me.itemsData.get(id, me.itemOptions);\n var item = me.items[id];\n var type = me._getType(itemData);\n\n var constructor = ItemSet.types[type];\n var selected;\n\n if (item) {\n // update item\n if (!constructor || !(item instanceof constructor)) {\n // item type has changed, delete the item and recreate it\n selected = item.selected; // preserve selection of this item\n me._removeItem(item);\n item = null;\n } else {\n me._updateItem(item, itemData);\n }\n }\n\n if (!item) {\n // create item\n if (constructor) {\n item = new constructor(itemData, me.conversion, me.options);\n item.id = id; // TODO: not so nice setting id afterwards\n me._addItem(item);\n if (selected) {\n this.selection.push(id);\n item.select();\n }\n } else if (type == 'rangeoverflow') {\n // TODO: deprecated since version 2.1.0 (or 3.0.0?). cleanup some day\n throw new TypeError('Item type \"rangeoverflow\" is deprecated. Use css styling instead: ' + '.vis-item.vis-range .vis-item-content {overflow: visible;}');\n } else {\n throw new TypeError('Unknown item type \"' + type + '\"');\n }\n }\n }).bind(this));\n\n this._order();\n this.stackDirty = true; // force re-stacking of all items next redraw\n this.body.emitter.emit('_change', { queue: true });\n };\n\n /**\n * Handle added items\n * @param {Number[]} ids\n * @protected\n */\n ItemSet.prototype._onAdd = ItemSet.prototype._onUpdate;\n\n /**\n * Handle removed items\n * @param {Number[]} ids\n * @protected\n */\n ItemSet.prototype._onRemove = function (ids) {\n var count = 0;\n var me = this;\n ids.forEach(function (id) {\n var item = me.items[id];\n if (item) {\n count++;\n me._removeItem(item);\n }\n });\n\n if (count) {\n // update order\n this._order();\n this.stackDirty = true; // force re-stacking of all items next redraw\n this.body.emitter.emit('_change', { queue: true });\n }\n };\n\n /**\n * Update the order of item in all groups\n * @private\n */\n ItemSet.prototype._order = function () {\n // reorder the items in all groups\n // TODO: optimization: only reorder groups affected by the changed items\n util.forEach(this.groups, function (group) {\n group.order();\n });\n };\n\n /**\n * Handle updated groups\n * @param {Number[]} ids\n * @private\n */\n ItemSet.prototype._onUpdateGroups = function (ids) {\n this._onAddGroups(ids);\n };\n\n /**\n * Handle changed groups (added or updated)\n * @param {Number[]} ids\n * @private\n */\n ItemSet.prototype._onAddGroups = function (ids) {\n var me = this;\n\n ids.forEach(function (id) {\n var groupData = me.groupsData.get(id);\n var group = me.groups[id];\n\n if (!group) {\n // check for reserved ids\n if (id == UNGROUPED || id == BACKGROUND) {\n throw new Error('Illegal group id. ' + id + ' is a reserved id.');\n }\n\n var groupOptions = Object.create(me.options);\n util.extend(groupOptions, {\n height: null\n });\n\n group = new Group(id, groupData, me);\n me.groups[id] = group;\n\n // add items with this groupId to the new group\n for (var itemId in me.items) {\n if (me.items.hasOwnProperty(itemId)) {\n var item = me.items[itemId];\n if (item.data.group == id) {\n group.add(item);\n }\n }\n }\n\n group.order();\n group.show();\n } else {\n // update group\n group.setData(groupData);\n }\n });\n\n this.body.emitter.emit('_change', { queue: true });\n };\n\n /**\n * Handle removed groups\n * @param {Number[]} ids\n * @private\n */\n ItemSet.prototype._onRemoveGroups = function (ids) {\n var groups = this.groups;\n ids.forEach(function (id) {\n var group = groups[id];\n\n if (group) {\n group.hide();\n delete groups[id];\n }\n });\n\n this.markDirty();\n\n this.body.emitter.emit('_change', { queue: true });\n };\n\n /**\n * Reorder the groups if needed\n * @return {boolean} changed\n * @private\n */\n ItemSet.prototype._orderGroups = function () {\n if (this.groupsData) {\n // reorder the groups\n var groupIds = this.groupsData.getIds({\n order: this.options.groupOrder\n });\n\n var changed = !util.equalArray(groupIds, this.groupIds);\n if (changed) {\n // hide all groups, removes them from the DOM\n var groups = this.groups;\n groupIds.forEach(function (groupId) {\n groups[groupId].hide();\n });\n\n // show the groups again, attach them to the DOM in correct order\n groupIds.forEach(function (groupId) {\n groups[groupId].show();\n });\n\n this.groupIds = groupIds;\n }\n\n return changed;\n } else {\n return false;\n }\n };\n\n /**\n * Add a new item\n * @param {Item} item\n * @private\n */\n ItemSet.prototype._addItem = function (item) {\n this.items[item.id] = item;\n\n // add to group\n var groupId = this._getGroupId(item.data);\n var group = this.groups[groupId];\n if (group) group.add(item);\n };\n\n /**\n * Update an existing item\n * @param {Item} item\n * @param {Object} itemData\n * @private\n */\n ItemSet.prototype._updateItem = function (item, itemData) {\n var oldGroupId = item.data.group;\n var oldSubGroupId = item.data.subgroup;\n\n // update the items data (will redraw the item when displayed)\n item.setData(itemData);\n\n // update group\n if (oldGroupId != item.data.group || oldSubGroupId != item.data.subgroup) {\n var oldGroup = this.groups[oldGroupId];\n if (oldGroup) oldGroup.remove(item);\n\n var groupId = this._getGroupId(item.data);\n var group = this.groups[groupId];\n if (group) group.add(item);\n }\n };\n\n /**\n * Delete an item from the ItemSet: remove it from the DOM, from the map\n * with items, and from the map with visible items, and from the selection\n * @param {Item} item\n * @private\n */\n ItemSet.prototype._removeItem = function (item) {\n // remove from DOM\n item.hide();\n\n // remove from items\n delete this.items[item.id];\n\n // remove from selection\n var index = this.selection.indexOf(item.id);\n if (index != -1) this.selection.splice(index, 1);\n\n // remove from group\n item.parent && item.parent.remove(item);\n };\n\n /**\n * Create an array containing all items being a range (having an end date)\n * @param array\n * @returns {Array}\n * @private\n */\n ItemSet.prototype._constructByEndArray = function (array) {\n var endArray = [];\n\n for (var i = 0; i < array.length; i++) {\n if (array[i] instanceof RangeItem) {\n endArray.push(array[i]);\n }\n }\n return endArray;\n };\n\n /**\n * Register the clicked item on touch, before dragStart is initiated.\n *\n * dragStart is initiated from a mousemove event, AFTER the mouse/touch is\n * already moving. Therefore, the mouse/touch can sometimes be above an other\n * DOM element than the item itself.\n *\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onTouch = function (event) {\n // store the touched item, used in _onDragStart\n this.touchParams.item = this.itemFromTarget(event);\n this.touchParams.dragLeftItem = event.target.dragLeftItem || false;\n this.touchParams.dragRightItem = event.target.dragRightItem || false;\n this.touchParams.itemProps = null;\n };\n\n /**\n * Given an group id, returns the index it has.\n *\n * @param {Number} groupID\n * @private\n */\n ItemSet.prototype._getGroupIndex = function (groupId) {\n for (var i = 0; i < this.groupIds.length; i++) {\n if (groupId == this.groupIds[i]) return i;\n }\n };\n\n /**\n * Start dragging the selected events\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onDragStart = function (event) {\n var item = this.touchParams.item || null;\n var me = this;\n var props;\n\n if (item && (item.selected || this.options.itemsAlwaysDraggable)) {\n\n if (!this.options.editable.updateTime && !this.options.editable.updateGroup && !item.editable) {\n return;\n }\n\n // override options.editable\n if (item.editable === false) {\n return;\n }\n\n var dragLeftItem = this.touchParams.dragLeftItem;\n var dragRightItem = this.touchParams.dragRightItem;\n\n if (dragLeftItem) {\n props = {\n item: dragLeftItem,\n initialX: event.center.x,\n dragLeft: true,\n data: this._cloneItemData(item.data)\n };\n\n this.touchParams.itemProps = [props];\n } else if (dragRightItem) {\n props = {\n item: dragRightItem,\n initialX: event.center.x,\n dragRight: true,\n data: this._cloneItemData(item.data)\n };\n\n this.touchParams.itemProps = [props];\n } else {\n this.touchParams.selectedItem = item;\n\n var baseGroupIndex = this._getGroupIndex(item.data.group);\n\n var itemsToDrag = this.options.itemsAlwaysDraggable && !item.selected ? [item.id] : this.getSelection();\n\n this.touchParams.itemProps = itemsToDrag.map((function (id) {\n var item = me.items[id];\n var groupIndex = me._getGroupIndex(item.data.group);\n return {\n item: item,\n initialX: event.center.x,\n groupOffset: baseGroupIndex - groupIndex,\n data: this._cloneItemData(item.data)\n };\n }).bind(this));\n }\n\n event.stopPropagation();\n } else if (this.options.editable.add && (event.srcEvent.ctrlKey || event.srcEvent.metaKey)) {\n // create a new range item when dragging with ctrl key down\n this._onDragStartAddItem(event);\n }\n };\n\n /**\n * Start creating a new range item by dragging.\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onDragStartAddItem = function (event) {\n var snap = this.options.snap || null;\n var xAbs = util.getAbsoluteLeft(this.dom.frame);\n var x = event.center.x - xAbs - 10; // minus 10 to compensate for the drag starting as soon as you've moved 10px\n var time = this.body.util.toTime(x);\n var scale = this.body.util.getScale();\n var step = this.body.util.getStep();\n var start = snap ? snap(time, scale, step) : time;\n var end = start;\n\n var itemData = {\n type: 'range',\n start: start,\n end: end,\n content: 'new item'\n };\n\n var id = util.randomUUID();\n itemData[this.itemsData._fieldId] = id;\n\n var group = this.groupFromTarget(event);\n if (group) {\n itemData.group = group.groupId;\n }\n\n var newItem = new RangeItem(itemData, this.conversion, this.options);\n newItem.id = id; // TODO: not so nice setting id afterwards\n newItem.data = this._cloneItemData(itemData);\n this._addItem(newItem);\n\n var props = {\n item: newItem,\n dragRight: true,\n initialX: event.center.x,\n data: newItem.data\n };\n this.touchParams.itemProps = [props];\n\n event.stopPropagation();\n };\n\n /**\n * Drag selected items\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onDrag = function (event) {\n if (this.touchParams.itemProps) {\n event.stopPropagation();\n\n var me = this;\n var snap = this.options.snap || null;\n var xOffset = this.body.dom.root.offsetLeft + this.body.domProps.left.width;\n var scale = this.body.util.getScale();\n var step = this.body.util.getStep();\n\n //only calculate the new group for the item that's actually dragged\n var selectedItem = this.touchParams.selectedItem;\n var updateGroupAllowed = me.options.editable.updateGroup;\n var newGroupBase = null;\n if (updateGroupAllowed && selectedItem) {\n if (selectedItem.data.group != undefined) {\n // drag from one group to another\n var group = me.groupFromTarget(event);\n if (group) {\n //we know the offset for all items, so the new group for all items\n //will be relative to this one.\n newGroupBase = this._getGroupIndex(group.groupId);\n }\n }\n }\n\n // move\n this.touchParams.itemProps.forEach((function (props) {\n var current = me.body.util.toTime(event.center.x - xOffset);\n var initial = me.body.util.toTime(props.initialX - xOffset);\n var offset = current - initial; // ms\n\n var itemData = this._cloneItemData(props.item.data); // clone the data\n if (props.item.editable === false) {\n return;\n }\n\n var updateTimeAllowed = me.options.editable.updateTime || props.item.editable === true;\n\n if (updateTimeAllowed) {\n if (props.dragLeft) {\n // drag left side of a range item\n if (itemData.start != undefined) {\n var initialStart = util.convert(props.data.start, 'Date');\n var start = new Date(initialStart.valueOf() + offset);\n // TODO: pass a Moment instead of a Date to snap(). (Breaking change)\n itemData.start = snap ? snap(start, scale, step) : start;\n }\n } else if (props.dragRight) {\n // drag right side of a range item\n if (itemData.end != undefined) {\n var initialEnd = util.convert(props.data.end, 'Date');\n var end = new Date(initialEnd.valueOf() + offset);\n // TODO: pass a Moment instead of a Date to snap(). (Breaking change)\n itemData.end = snap ? snap(end, scale, step) : end;\n }\n } else {\n // drag both start and end\n if (itemData.start != undefined) {\n var initialStart = util.convert(props.data.start, 'Date').valueOf();\n var start = new Date(initialStart + offset);\n\n if (itemData.end != undefined) {\n var initialEnd = util.convert(props.data.end, 'Date');\n var duration = initialEnd.valueOf() - initialStart.valueOf();\n\n // TODO: pass a Moment instead of a Date to snap(). (Breaking change)\n itemData.start = snap ? snap(start, scale, step) : start;\n itemData.end = new Date(itemData.start.valueOf() + duration);\n } else {\n // TODO: pass a Moment instead of a Date to snap(). (Breaking change)\n itemData.start = snap ? snap(start, scale, step) : start;\n }\n }\n }\n }\n\n var updateGroupAllowed = me.options.editable.updateGroup || props.item.editable === true;\n\n if (updateGroupAllowed && !props.dragLeft && !props.dragRight && newGroupBase != null) {\n if (itemData.group != undefined) {\n var newOffset = newGroupBase - props.groupOffset;\n\n //make sure we stay in bounds\n newOffset = Math.max(0, newOffset);\n newOffset = Math.min(me.groupIds.length - 1, newOffset);\n\n itemData.group = me.groupIds[newOffset];\n }\n }\n\n // confirm moving the item\n itemData = this._cloneItemData(itemData); // convert start and end to the correct type\n me.options.onMoving(itemData, (function (itemData) {\n if (itemData) {\n props.item.setData(this._cloneItemData(itemData, 'Date'));\n }\n }).bind(this));\n }).bind(this));\n\n this.stackDirty = true; // force re-stacking of all items next redraw\n this.body.emitter.emit('_change');\n }\n };\n\n /**\n * Move an item to another group\n * @param {Item} item\n * @param {String | Number} groupId\n * @private\n */\n ItemSet.prototype._moveToGroup = function (item, groupId) {\n var group = this.groups[groupId];\n if (group && group.groupId != item.data.group) {\n var oldGroup = item.parent;\n oldGroup.remove(item);\n oldGroup.order();\n group.add(item);\n group.order();\n\n item.data.group = group.groupId;\n }\n };\n\n /**\n * End of dragging selected items\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onDragEnd = function (event) {\n if (this.touchParams.itemProps) {\n event.stopPropagation();\n\n var me = this;\n var dataset = this.itemsData.getDataSet();\n var itemProps = this.touchParams.itemProps;\n this.touchParams.itemProps = null;\n\n itemProps.forEach((function (props) {\n var id = props.item.id;\n var exists = me.itemsData.get(id, me.itemOptions) != null;\n\n if (!exists) {\n // add a new item\n me.options.onAdd(props.item.data, function (itemData) {\n me._removeItem(props.item); // remove temporary item\n if (itemData) {\n me.itemsData.getDataSet().add(itemData);\n }\n\n // force re-stacking of all items next redraw\n me.stackDirty = true;\n me.body.emitter.emit('_change');\n });\n } else {\n // update existing item\n var itemData = this._cloneItemData(props.item.data); // convert start and end to the correct type\n me.options.onMove(itemData, function (itemData) {\n if (itemData) {\n // apply changes\n itemData[dataset._fieldId] = id; // ensure the item contains its id (can be undefined)\n dataset.update(itemData);\n } else {\n // restore original values\n props.item.setData(props.data);\n\n me.stackDirty = true; // force re-stacking of all items next redraw\n me.body.emitter.emit('_change');\n }\n });\n }\n }).bind(this));\n }\n };\n\n ItemSet.prototype._onGroupDragStart = function (event) {\n if (this.options.groupEditable.order) {\n this.groupTouchParams.group = this.groupFromTarget(event);\n\n if (this.groupTouchParams.group) {\n event.stopPropagation();\n\n this.groupTouchParams.originalOrder = this.groupsData.getIds({\n order: this.options.groupOrder\n });\n }\n }\n };\n\n ItemSet.prototype._onGroupDrag = function (event) {\n if (this.options.groupEditable.order && this.groupTouchParams.group) {\n event.stopPropagation();\n\n // drag from one group to another\n var group = this.groupFromTarget(event);\n\n // try to avoid toggling when groups differ in height\n if (group && group.height != this.groupTouchParams.group.height) {\n var movingUp = group.top < this.groupTouchParams.group.top;\n var clientY = event.center ? event.center.y : event.clientY;\n var targetGroupTop = util.getAbsoluteTop(group.dom.foreground);\n var draggedGroupHeight = this.groupTouchParams.group.height;\n if (movingUp) {\n // skip swapping the groups when the dragged group is not below clientY afterwards\n if (targetGroupTop + draggedGroupHeight < clientY) {\n return;\n }\n } else {\n var targetGroupHeight = group.height;\n // skip swapping the groups when the dragged group is not below clientY afterwards\n if (targetGroupTop + targetGroupHeight - draggedGroupHeight > clientY) {\n return;\n }\n }\n }\n\n if (group && group != this.groupTouchParams.group) {\n var groupsData = this.groupsData;\n var targetGroup = groupsData.get(group.groupId);\n var draggedGroup = groupsData.get(this.groupTouchParams.group.groupId);\n\n // switch groups\n if (draggedGroup && targetGroup) {\n this.options.groupOrderSwap(draggedGroup, targetGroup, this.groupsData);\n this.groupsData.update(draggedGroup);\n this.groupsData.update(targetGroup);\n }\n\n // fetch current order of groups\n var newOrder = this.groupsData.getIds({\n order: this.options.groupOrder\n });\n\n // in case of changes since _onGroupDragStart\n if (!util.equalArray(newOrder, this.groupTouchParams.originalOrder)) {\n var groupsData = this.groupsData;\n var origOrder = this.groupTouchParams.originalOrder;\n var draggedId = this.groupTouchParams.group.groupId;\n var numGroups = Math.min(origOrder.length, newOrder.length);\n var curPos = 0;\n var newOffset = 0;\n var orgOffset = 0;\n while (curPos < numGroups) {\n // as long as the groups are where they should be step down along the groups order\n while (curPos + newOffset < numGroups && curPos + orgOffset < numGroups && newOrder[curPos + newOffset] == origOrder[curPos + orgOffset]) {\n curPos++;\n }\n\n // all ok\n if (curPos + newOffset >= numGroups) {\n break;\n }\n\n // not all ok\n // if dragged group was move upwards everything below should have an offset\n if (newOrder[curPos + newOffset] == draggedId) {\n newOffset = 1;\n continue;\n }\n // if dragged group was move downwards everything above should have an offset\n else if (origOrder[curPos + orgOffset] == draggedId) {\n orgOffset = 1;\n continue;\n }\n // found a group (apart from dragged group) that has the wrong position -> switch with the\n // group at the position where other one should be, fix index arrays and continue\n else {\n var slippedPosition = newOrder.indexOf(origOrder[curPos + orgOffset]);\n var switchGroup = groupsData.get(newOrder[curPos + newOffset]);\n var shouldBeGroup = groupsData.get(origOrder[curPos + orgOffset]);\n this.options.groupOrderSwap(switchGroup, shouldBeGroup, groupsData);\n groupsData.update(switchGroup);\n groupsData.update(shouldBeGroup);\n\n var switchGroupId = newOrder[curPos + newOffset];\n newOrder[curPos + newOffset] = origOrder[curPos + orgOffset];\n newOrder[slippedPosition] = switchGroupId;\n\n curPos++;\n }\n }\n }\n }\n }\n };\n\n ItemSet.prototype._onGroupDragEnd = function (event) {\n if (this.options.groupEditable.order && this.groupTouchParams.group) {\n event.stopPropagation();\n\n // update existing group\n var me = this;\n var id = me.groupTouchParams.group.groupId;\n var dataset = me.groupsData.getDataSet();\n var groupData = util.extend({}, dataset.get(id)); // clone the data\n me.options.onMoveGroup(groupData, function (groupData) {\n if (groupData) {\n // apply changes\n groupData[dataset._fieldId] = id; // ensure the group contains its id (can be undefined)\n dataset.update(groupData);\n } else {\n\n // fetch current order of groups\n var newOrder = dataset.getIds({\n order: me.options.groupOrder\n });\n\n // restore original order\n if (!util.equalArray(newOrder, me.groupTouchParams.originalOrder)) {\n var origOrder = me.groupTouchParams.originalOrder;\n var numGroups = Math.min(origOrder.length, newOrder.length);\n var curPos = 0;\n while (curPos < numGroups) {\n // as long as the groups are where they should be step down along the groups order\n while (curPos < numGroups && newOrder[curPos] == origOrder[curPos]) {\n curPos++;\n }\n\n // all ok\n if (curPos >= numGroups) {\n break;\n }\n\n // found a group that has the wrong position -> switch with the\n // group at the position where other one should be, fix index arrays and continue\n var slippedPosition = newOrder.indexOf(origOrder[curPos]);\n var switchGroup = dataset.get(newOrder[curPos]);\n var shouldBeGroup = dataset.get(origOrder[curPos]);\n me.options.groupOrderSwap(switchGroup, shouldBeGroup, dataset);\n groupsData.update(switchGroup);\n groupsData.update(shouldBeGroup);\n\n var switchGroupId = newOrder[curPos];\n newOrder[curPos] = origOrder[curPos];\n newOrder[slippedPosition] = switchGroupId;\n\n curPos++;\n }\n }\n }\n });\n\n me.body.emitter.emit('groupDragged', { groupId: id });\n }\n };\n\n /**\n * Handle selecting/deselecting an item when tapping it\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onSelectItem = function (event) {\n if (!this.options.selectable) return;\n\n var ctrlKey = event.srcEvent && (event.srcEvent.ctrlKey || event.srcEvent.metaKey);\n var shiftKey = event.srcEvent && event.srcEvent.shiftKey;\n if (ctrlKey || shiftKey) {\n this._onMultiSelectItem(event);\n return;\n }\n\n var oldSelection = this.getSelection();\n\n var item = this.itemFromTarget(event);\n var selection = item ? [item.id] : [];\n this.setSelection(selection);\n\n var newSelection = this.getSelection();\n\n // emit a select event,\n // except when old selection is empty and new selection is still empty\n if (newSelection.length > 0 || oldSelection.length > 0) {\n this.body.emitter.emit('select', {\n items: newSelection,\n event: event\n });\n }\n };\n\n /**\n * Handle creation and updates of an item on double tap\n * @param event\n * @private\n */\n ItemSet.prototype._onAddItem = function (event) {\n if (!this.options.selectable) return;\n if (!this.options.editable.add) return;\n\n var me = this;\n var snap = this.options.snap || null;\n var item = this.itemFromTarget(event);\n\n if (item) {\n // update item\n\n // execute async handler to update the item (or cancel it)\n var itemData = me.itemsData.get(item.id); // get a clone of the data from the dataset\n this.options.onUpdate(itemData, function (itemData) {\n if (itemData) {\n me.itemsData.getDataSet().update(itemData);\n }\n });\n } else {\n // add item\n var xAbs = util.getAbsoluteLeft(this.dom.frame);\n var x = event.center.x - xAbs;\n var start = this.body.util.toTime(x);\n var scale = this.body.util.getScale();\n var step = this.body.util.getStep();\n\n var newItemData = {\n start: snap ? snap(start, scale, step) : start,\n content: 'new item'\n };\n\n // when default type is a range, add a default end date to the new item\n if (this.options.type === 'range') {\n var end = this.body.util.toTime(x + this.props.width / 5);\n newItemData.end = snap ? snap(end, scale, step) : end;\n }\n\n newItemData[this.itemsData._fieldId] = util.randomUUID();\n\n var group = this.groupFromTarget(event);\n if (group) {\n newItemData.group = group.groupId;\n }\n\n // execute async handler to customize (or cancel) adding an item\n newItemData = this._cloneItemData(newItemData); // convert start and end to the correct type\n this.options.onAdd(newItemData, function (item) {\n if (item) {\n me.itemsData.getDataSet().add(item);\n // TODO: need to trigger a redraw?\n }\n });\n }\n };\n\n /**\n * Handle selecting/deselecting multiple items when holding an item\n * @param {Event} event\n * @private\n */\n ItemSet.prototype._onMultiSelectItem = function (event) {\n if (!this.options.selectable) return;\n\n var item = this.itemFromTarget(event);\n\n if (item) {\n // multi select items (if allowed)\n\n var selection = this.options.multiselect ? this.getSelection() // take current selection\n : []; // deselect current selection\n\n var shiftKey = event.srcEvent && event.srcEvent.shiftKey || false;\n\n if (shiftKey && this.options.multiselect) {\n // select all items between the old selection and the tapped item\n var itemGroup = this.itemsData.get(item.id).group;\n\n // when filtering get the group of the last selected item\n var lastSelectedGroup = undefined;\n if (this.options.multiselectPerGroup) {\n if (selection.length > 0) {\n lastSelectedGroup = this.itemsData.get(selection[0]).group;\n }\n }\n\n // determine the selection range\n if (!this.options.multiselectPerGroup || lastSelectedGroup == undefined || lastSelectedGroup == itemGroup) {\n selection.push(item.id);\n }\n var range = ItemSet._getItemRange(this.itemsData.get(selection, this.itemOptions));\n\n if (!this.options.multiselectPerGroup || lastSelectedGroup == itemGroup) {\n // select all items within the selection range\n selection = [];\n for (var id in this.items) {\n if (this.items.hasOwnProperty(id)) {\n var _item = this.items[id];\n var start = _item.data.start;\n var end = _item.data.end !== undefined ? _item.data.end : start;\n\n if (start >= range.min && end <= range.max && (!this.options.multiselectPerGroup || lastSelectedGroup == this.itemsData.get(_item.id).group) && !(_item instanceof BackgroundItem)) {\n selection.push(_item.id); // do not use id but item.id, id itself is stringified\n }\n }\n }\n }\n } else {\n // add/remove this item from the current selection\n var index = selection.indexOf(item.id);\n if (index == -1) {\n // item is not yet selected -> select it\n selection.push(item.id);\n } else {\n // item is already selected -> deselect it\n selection.splice(index, 1);\n }\n }\n\n this.setSelection(selection);\n\n this.body.emitter.emit('select', {\n items: this.getSelection(),\n event: event\n });\n }\n };\n\n /**\n * Calculate the time range of a list of items\n * @param {Array.<Object>} itemsData\n * @return {{min: Date, max: Date}} Returns the range of the provided items\n * @private\n */\n ItemSet._getItemRange = function (itemsData) {\n var max = null;\n var min = null;\n\n itemsData.forEach(function (data) {\n if (min == null || data.start < min) {\n min = data.start;\n }\n\n if (data.end != undefined) {\n if (max == null || data.end > max) {\n max = data.end;\n }\n } else {\n if (max == null || data.start > max) {\n max = data.start;\n }\n }\n });\n\n return {\n min: min,\n max: max\n };\n };\n\n /**\n * Find an item from an event target:\n * searches for the attribute 'timeline-item' in the event target's element tree\n * @param {Event} event\n * @return {Item | null} item\n */\n ItemSet.prototype.itemFromTarget = function (event) {\n var target = event.target;\n while (target) {\n if (target.hasOwnProperty('timeline-item')) {\n return target['timeline-item'];\n }\n target = target.parentNode;\n }\n\n return null;\n };\n\n /**\n * Find the Group from an event target:\n * searches for the attribute 'timeline-group' in the event target's element tree\n * @param {Event} event\n * @return {Group | null} group\n */\n ItemSet.prototype.groupFromTarget = function (event) {\n var clientY = event.center ? event.center.y : event.clientY;\n for (var i = 0; i < this.groupIds.length; i++) {\n var groupId = this.groupIds[i];\n var group = this.groups[groupId];\n var foreground = group.dom.foreground;\n var top = util.getAbsoluteTop(foreground);\n if (clientY > top && clientY < top + foreground.offsetHeight) {\n return group;\n }\n\n if (this.options.orientation.item === 'top') {\n if (i === this.groupIds.length - 1 && clientY > top) {\n return group;\n }\n } else {\n if (i === 0 && clientY < top + foreground.offset) {\n return group;\n }\n }\n }\n\n return null;\n };\n\n /**\n * Find the ItemSet from an event target:\n * searches for the attribute 'timeline-itemset' in the event target's element tree\n * @param {Event} event\n * @return {ItemSet | null} item\n */\n ItemSet.itemSetFromTarget = function (event) {\n var target = event.target;\n while (target) {\n if (target.hasOwnProperty('timeline-itemset')) {\n return target['timeline-itemset'];\n }\n target = target.parentNode;\n }\n\n return null;\n };\n\n /**\n * Clone the data of an item, and \"normalize\" it: convert the start and end date\n * to the type (Date, Moment, ...) configured in the DataSet. If not configured,\n * start and end are converted to Date.\n * @param {Object} itemData, typically `item.data`\n * @param {string} [type] Optional Date type. If not provided, the type from the DataSet is taken\n * @return {Object} The cloned object\n * @private\n */\n ItemSet.prototype._cloneItemData = function (itemData, type) {\n var clone = util.extend({}, itemData);\n\n if (!type) {\n // convert start and end date to the type (Date, Moment, ...) configured in the DataSet\n type = this.itemsData.getDataSet()._options.type;\n }\n\n if (clone.start != undefined) {\n clone.start = util.convert(clone.start, type && type.start || 'Date');\n }\n if (clone.end != undefined) {\n clone.end = util.convert(clone.end, type && type.end || 'Date');\n }\n\n return clone;\n };\n\n module.exports = ItemSet;\n\n/***/ },\n/* 29 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var moment = __webpack_require__(2);\n var DateUtil = __webpack_require__(26);\n var util = __webpack_require__(1);\n\n /**\n * @constructor TimeStep\n * The class TimeStep is an iterator for dates. You provide a start date and an\n * end date. The class itself determines the best scale (step size) based on the\n * provided start Date, end Date, and minimumStep.\n *\n * If minimumStep is provided, the step size is chosen as close as possible\n * to the minimumStep but larger than minimumStep. If minimumStep is not\n * provided, the scale is set to 1 DAY.\n * The minimumStep should correspond with the onscreen size of about 6 characters\n *\n * Alternatively, you can set a scale by hand.\n * After creation, you can initialize the class by executing first(). Then you\n * can iterate from the start date to the end date via next(). You can check if\n * the end date is reached with the function hasNext(). After each step, you can\n * retrieve the current date via getCurrent().\n * The TimeStep has scales ranging from milliseconds, seconds, minutes, hours,\n * days, to years.\n *\n * Version: 1.2\n *\n * @param {Date} [start] The start date, for example new Date(2010, 9, 21)\n * or new Date(2010, 9, 21, 23, 45, 00)\n * @param {Date} [end] The end date\n * @param {Number} [minimumStep] Optional. Minimum step size in milliseconds\n */\n function TimeStep(start, end, minimumStep, hiddenDates) {\n this.moment = moment;\n\n // variables\n this.current = this.moment();\n this._start = this.moment();\n this._end = this.moment();\n\n this.autoScale = true;\n this.scale = 'day';\n this.step = 1;\n\n // initialize the range\n this.setRange(start, end, minimumStep);\n\n // hidden Dates options\n this.switchedDay = false;\n this.switchedMonth = false;\n this.switchedYear = false;\n if (Array.isArray(hiddenDates)) {\n this.hiddenDates = hiddenDates;\n } else if (hiddenDates != undefined) {\n this.hiddenDates = [hiddenDates];\n } else {\n this.hiddenDates = [];\n }\n\n this.format = TimeStep.FORMAT; // default formatting\n }\n\n // Time formatting\n TimeStep.FORMAT = {\n minorLabels: {\n millisecond: 'SSS',\n second: 's',\n minute: 'HH:mm',\n hour: 'HH:mm',\n weekday: 'ddd D',\n day: 'D',\n month: 'MMM',\n year: 'YYYY'\n },\n majorLabels: {\n millisecond: 'HH:mm:ss',\n second: 'D MMMM HH:mm',\n minute: 'ddd D MMMM',\n hour: 'ddd D MMMM',\n weekday: 'MMMM YYYY',\n day: 'MMMM YYYY',\n month: 'YYYY',\n year: ''\n }\n };\n\n /**\n * Set custom constructor function for moment. Can be used to set dates\n * to UTC or to set a utcOffset.\n * @param {function} moment\n */\n TimeStep.prototype.setMoment = function (moment) {\n this.moment = moment;\n\n // update the date properties, can have a new utcOffset\n this.current = this.moment(this.current);\n this._start = this.moment(this._start);\n this._end = this.moment(this._end);\n };\n\n /**\n * Set custom formatting for the minor an major labels of the TimeStep.\n * Both `minorLabels` and `majorLabels` are an Object with properties:\n * 'millisecond', 'second', 'minute', 'hour', 'weekday', 'day', 'month', 'year'.\n * @param {{minorLabels: Object, majorLabels: Object}} format\n */\n TimeStep.prototype.setFormat = function (format) {\n var defaultFormat = util.deepExtend({}, TimeStep.FORMAT);\n this.format = util.deepExtend(defaultFormat, format);\n };\n\n /**\n * Set a new range\n * If minimumStep is provided, the step size is chosen as close as possible\n * to the minimumStep but larger than minimumStep. If minimumStep is not\n * provided, the scale is set to 1 DAY.\n * The minimumStep should correspond with the onscreen size of about 6 characters\n * @param {Date} [start] The start date and time.\n * @param {Date} [end] The end date and time.\n * @param {int} [minimumStep] Optional. Minimum step size in milliseconds\n */\n TimeStep.prototype.setRange = function (start, end, minimumStep) {\n if (!(start instanceof Date) || !(end instanceof Date)) {\n throw \"No legal start or end date in method setRange\";\n }\n\n this._start = start != undefined ? this.moment(start.valueOf()) : new Date();\n this._end = end != undefined ? this.moment(end.valueOf()) : new Date();\n\n if (this.autoScale) {\n this.setMinimumStep(minimumStep);\n }\n };\n\n /**\n * Set the range iterator to the start date.\n */\n TimeStep.prototype.start = function () {\n this.current = this._start.clone();\n this.roundToMinor();\n };\n\n /**\n * Round the current date to the first minor date value\n * This must be executed once when the current date is set to start Date\n */\n TimeStep.prototype.roundToMinor = function () {\n // round to floor\n // IMPORTANT: we have no breaks in this switch! (this is no bug)\n // noinspection FallThroughInSwitchStatementJS\n switch (this.scale) {\n case 'year':\n this.current.year(this.step * Math.floor(this.current.year() / this.step));\n this.current.month(0);\n case 'month':\n this.current.date(1);\n case 'day': // intentional fall through\n case 'weekday':\n this.current.hours(0);\n case 'hour':\n this.current.minutes(0);\n case 'minute':\n this.current.seconds(0);\n case 'second':\n this.current.milliseconds(0);\n //case 'millisecond': // nothing to do for milliseconds\n }\n\n if (this.step != 1) {\n // round down to the first minor value that is a multiple of the current step size\n switch (this.scale) {\n case 'millisecond':\n this.current.subtract(this.current.milliseconds() % this.step, 'milliseconds');break;\n case 'second':\n this.current.subtract(this.current.seconds() % this.step, 'seconds');break;\n case 'minute':\n this.current.subtract(this.current.minutes() % this.step, 'minutes');break;\n case 'hour':\n this.current.subtract(this.current.hours() % this.step, 'hours');break;\n case 'weekday': // intentional fall through\n case 'day':\n this.current.subtract((this.current.date() - 1) % this.step, 'day');break;\n case 'month':\n this.current.subtract(this.current.month() % this.step, 'month');break;\n case 'year':\n this.current.subtract(this.current.year() % this.step, 'year');break;\n default:\n break;\n }\n }\n };\n\n /**\n * Check if the there is a next step\n * @return {boolean} true if the current date has not passed the end date\n */\n TimeStep.prototype.hasNext = function () {\n return this.current.valueOf() <= this._end.valueOf();\n };\n\n /**\n * Do the next step\n */\n TimeStep.prototype.next = function () {\n var prev = this.current.valueOf();\n\n // Two cases, needed to prevent issues with switching daylight savings\n // (end of March and end of October)\n if (this.current.month() < 6) {\n switch (this.scale) {\n case 'millisecond':\n this.current.add(this.step, 'millisecond');break;\n case 'second':\n this.current.add(this.step, 'second');break;\n case 'minute':\n this.current.add(this.step, 'minute');break;\n case 'hour':\n this.current.add(this.step, 'hour');\n // in case of skipping an hour for daylight savings, adjust the hour again (else you get: 0h 5h 9h ... instead of 0h 4h 8h ...)\n // TODO: is this still needed now we use the function of moment.js?\n this.current.subtract(this.current.hours() % this.step, 'hour');\n break;\n case 'weekday': // intentional fall through\n case 'day':\n this.current.add(this.step, 'day');break;\n case 'month':\n this.current.add(this.step, 'month');break;\n case 'year':\n this.current.add(this.step, 'year');break;\n default:\n break;\n }\n } else {\n switch (this.scale) {\n case 'millisecond':\n this.current.add(this.step, 'millisecond');break;\n case 'second':\n this.current.add(this.step, 'second');break;\n case 'minute':\n this.current.add(this.step, 'minute');break;\n case 'hour':\n this.current.add(this.step, 'hour');break;\n case 'weekday': // intentional fall through\n case 'day':\n this.current.add(this.step, 'day');break;\n case 'month':\n this.current.add(this.step, 'month');break;\n case 'year':\n this.current.add(this.step, 'year');break;\n default:\n break;\n }\n }\n\n if (this.step != 1) {\n // round down to the correct major value\n switch (this.scale) {\n case 'millisecond':\n if (this.current.milliseconds() < this.step) this.current.milliseconds(0);break;\n case 'second':\n if (this.current.seconds() < this.step) this.current.seconds(0);break;\n case 'minute':\n if (this.current.minutes() < this.step) this.current.minutes(0);break;\n case 'hour':\n if (this.current.hours() < this.step) this.current.hours(0);break;\n case 'weekday': // intentional fall through\n case 'day':\n if (this.current.date() < this.step + 1) this.current.date(1);break;\n case 'month':\n if (this.current.month() < this.step) this.current.month(0);break;\n case 'year':\n break; // nothing to do for year\n default:\n break;\n }\n }\n\n // safety mechanism: if current time is still unchanged, move to the end\n if (this.current.valueOf() == prev) {\n this.current = this._end.clone();\n }\n\n DateUtil.stepOverHiddenDates(this.moment, this, prev);\n };\n\n /**\n * Get the current datetime\n * @return {Moment} current The current date\n */\n TimeStep.prototype.getCurrent = function () {\n return this.current;\n };\n\n /**\n * Set a custom scale. Autoscaling will be disabled.\n * For example setScale('minute', 5) will result\n * in minor steps of 5 minutes, and major steps of an hour.\n *\n * @param {{scale: string, step: number}} params\n * An object containing two properties:\n * - A string 'scale'. Choose from 'millisecond', 'second',\n * 'minute', 'hour', 'weekday', 'day', 'month', 'year'.\n * - A number 'step'. A step size, by default 1.\n * Choose for example 1, 2, 5, or 10.\n */\n TimeStep.prototype.setScale = function (params) {\n if (params && typeof params.scale == 'string') {\n this.scale = params.scale;\n this.step = params.step > 0 ? params.step : 1;\n this.autoScale = false;\n }\n };\n\n /**\n * Enable or disable autoscaling\n * @param {boolean} enable If true, autoascaling is set true\n */\n TimeStep.prototype.setAutoScale = function (enable) {\n this.autoScale = enable;\n };\n\n /**\n * Automatically determine the scale that bests fits the provided minimum step\n * @param {Number} [minimumStep] The minimum step size in milliseconds\n */\n TimeStep.prototype.setMinimumStep = function (minimumStep) {\n if (minimumStep == undefined) {\n return;\n }\n\n //var b = asc + ds;\n\n var stepYear = 1000 * 60 * 60 * 24 * 30 * 12;\n var stepMonth = 1000 * 60 * 60 * 24 * 30;\n var stepDay = 1000 * 60 * 60 * 24;\n var stepHour = 1000 * 60 * 60;\n var stepMinute = 1000 * 60;\n var stepSecond = 1000;\n var stepMillisecond = 1;\n\n // find the smallest step that is larger than the provided minimumStep\n if (stepYear * 1000 > minimumStep) {\n this.scale = 'year';this.step = 1000;\n }\n if (stepYear * 500 > minimumStep) {\n this.scale = 'year';this.step = 500;\n }\n if (stepYear * 100 > minimumStep) {\n this.scale = 'year';this.step = 100;\n }\n if (stepYear * 50 > minimumStep) {\n this.scale = 'year';this.step = 50;\n }\n if (stepYear * 10 > minimumStep) {\n this.scale = 'year';this.step = 10;\n }\n if (stepYear * 5 > minimumStep) {\n this.scale = 'year';this.step = 5;\n }\n if (stepYear > minimumStep) {\n this.scale = 'year';this.step = 1;\n }\n if (stepMonth * 3 > minimumStep) {\n this.scale = 'month';this.step = 3;\n }\n if (stepMonth > minimumStep) {\n this.scale = 'month';this.step = 1;\n }\n if (stepDay * 5 > minimumStep) {\n this.scale = 'day';this.step = 5;\n }\n if (stepDay * 2 > minimumStep) {\n this.scale = 'day';this.step = 2;\n }\n if (stepDay > minimumStep) {\n this.scale = 'day';this.step = 1;\n }\n if (stepDay / 2 > minimumStep) {\n this.scale = 'weekday';this.step = 1;\n }\n if (stepHour * 4 > minimumStep) {\n this.scale = 'hour';this.step = 4;\n }\n if (stepHour > minimumStep) {\n this.scale = 'hour';this.step = 1;\n }\n if (stepMinute * 15 > minimumStep) {\n this.scale = 'minute';this.step = 15;\n }\n if (stepMinute * 10 > minimumStep) {\n this.scale = 'minute';this.step = 10;\n }\n if (stepMinute * 5 > minimumStep) {\n this.scale = 'minute';this.step = 5;\n }\n if (stepMinute > minimumStep) {\n this.scale = 'minute';this.step = 1;\n }\n if (stepSecond * 15 > minimumStep) {\n this.scale = 'second';this.step = 15;\n }\n if (stepSecond * 10 > minimumStep) {\n this.scale = 'second';this.step = 10;\n }\n if (stepSecond * 5 > minimumStep) {\n this.scale = 'second';this.step = 5;\n }\n if (stepSecond > minimumStep) {\n this.scale = 'second';this.step = 1;\n }\n if (stepMillisecond * 200 > minimumStep) {\n this.scale = 'millisecond';this.step = 200;\n }\n if (stepMillisecond * 100 > minimumStep) {\n this.scale = 'millisecond';this.step = 100;\n }\n if (stepMillisecond * 50 > minimumStep) {\n this.scale = 'millisecond';this.step = 50;\n }\n if (stepMillisecond * 10 > minimumStep) {\n this.scale = 'millisecond';this.step = 10;\n }\n if (stepMillisecond * 5 > minimumStep) {\n this.scale = 'millisecond';this.step = 5;\n }\n if (stepMillisecond > minimumStep) {\n this.scale = 'millisecond';this.step = 1;\n }\n };\n\n /**\n * Snap a date to a rounded value.\n * The snap intervals are dependent on the current scale and step.\n * Static function\n * @param {Date} date the date to be snapped.\n * @param {string} scale Current scale, can be 'millisecond', 'second',\n * 'minute', 'hour', 'weekday, 'day', 'month', 'year'.\n * @param {number} step Current step (1, 2, 4, 5, ...\n * @return {Date} snappedDate\n */\n TimeStep.snap = function (date, scale, step) {\n var clone = moment(date);\n\n if (scale == 'year') {\n var year = clone.year() + Math.round(clone.month() / 12);\n clone.year(Math.round(year / step) * step);\n clone.month(0);\n clone.date(0);\n clone.hours(0);\n clone.minutes(0);\n clone.seconds(0);\n clone.milliseconds(0);\n } else if (scale == 'month') {\n if (clone.date() > 15) {\n clone.date(1);\n clone.add(1, 'month');\n // important: first set Date to 1, after that change the month.\n } else {\n clone.date(1);\n }\n\n clone.hours(0);\n clone.minutes(0);\n clone.seconds(0);\n clone.milliseconds(0);\n } else if (scale == 'day') {\n //noinspection FallthroughInSwitchStatementJS\n switch (step) {\n case 5:\n case 2:\n clone.hours(Math.round(clone.hours() / 24) * 24);break;\n default:\n clone.hours(Math.round(clone.hours() / 12) * 12);break;\n }\n clone.minutes(0);\n clone.seconds(0);\n clone.milliseconds(0);\n } else if (scale == 'weekday') {\n //noinspection FallthroughInSwitchStatementJS\n switch (step) {\n case 5:\n case 2:\n clone.hours(Math.round(clone.hours() / 12) * 12);break;\n default:\n clone.hours(Math.round(clone.hours() / 6) * 6);break;\n }\n clone.minutes(0);\n clone.seconds(0);\n clone.milliseconds(0);\n } else if (scale == 'hour') {\n switch (step) {\n case 4:\n clone.minutes(Math.round(clone.minutes() / 60) * 60);break;\n default:\n clone.minutes(Math.round(clone.minutes() / 30) * 30);break;\n }\n clone.seconds(0);\n clone.milliseconds(0);\n } else if (scale == 'minute') {\n //noinspection FallthroughInSwitchStatementJS\n switch (step) {\n case 15:\n case 10:\n clone.minutes(Math.round(clone.minutes() / 5) * 5);\n clone.seconds(0);\n break;\n case 5:\n clone.seconds(Math.round(clone.seconds() / 60) * 60);break;\n default:\n clone.seconds(Math.round(clone.seconds() / 30) * 30);break;\n }\n clone.milliseconds(0);\n } else if (scale == 'second') {\n //noinspection FallthroughInSwitchStatementJS\n switch (step) {\n case 15:\n case 10:\n clone.seconds(Math.round(clone.seconds() / 5) * 5);\n clone.milliseconds(0);\n break;\n case 5:\n clone.milliseconds(Math.round(clone.milliseconds() / 1000) * 1000);break;\n default:\n clone.milliseconds(Math.round(clone.milliseconds() / 500) * 500);break;\n }\n } else if (scale == 'millisecond') {\n var _step = step > 5 ? step / 2 : 1;\n clone.milliseconds(Math.round(clone.milliseconds() / _step) * _step);\n }\n\n return clone;\n };\n\n /**\n * Check if the current value is a major value (for example when the step\n * is DAY, a major value is each first day of the MONTH)\n * @return {boolean} true if current date is major, else false.\n */\n TimeStep.prototype.isMajor = function () {\n if (this.switchedYear == true) {\n this.switchedYear = false;\n switch (this.scale) {\n case 'year':\n case 'month':\n case 'weekday':\n case 'day':\n case 'hour':\n case 'minute':\n case 'second':\n case 'millisecond':\n return true;\n default:\n return false;\n }\n } else if (this.switchedMonth == true) {\n this.switchedMonth = false;\n switch (this.scale) {\n case 'weekday':\n case 'day':\n case 'hour':\n case 'minute':\n case 'second':\n case 'millisecond':\n return true;\n default:\n return false;\n }\n } else if (this.switchedDay == true) {\n this.switchedDay = false;\n switch (this.scale) {\n case 'millisecond':\n case 'second':\n case 'minute':\n case 'hour':\n return true;\n default:\n return false;\n }\n }\n\n var date = this.moment(this.current);\n switch (this.scale) {\n case 'millisecond':\n return date.milliseconds() == 0;\n case 'second':\n return date.seconds() == 0;\n case 'minute':\n return date.hours() == 0 && date.minutes() == 0;\n case 'hour':\n return date.hours() == 0;\n case 'weekday': // intentional fall through\n case 'day':\n return date.date() == 1;\n case 'month':\n return date.month() == 0;\n case 'year':\n return false;\n default:\n return false;\n }\n };\n\n /**\n * Returns formatted text for the minor axislabel, depending on the current\n * date and the scale. For example when scale is MINUTE, the current time is\n * formatted as \"hh:mm\".\n * @param {Date} [date] custom date. if not provided, current date is taken\n */\n TimeStep.prototype.getLabelMinor = function (date) {\n if (date == undefined) {\n date = this.current;\n }\n\n var format = this.format.minorLabels[this.scale];\n return format && format.length > 0 ? this.moment(date).format(format) : '';\n };\n\n /**\n * Returns formatted text for the major axis label, depending on the current\n * date and the scale. For example when scale is MINUTE, the major scale is\n * hours, and the hour will be formatted as \"hh\".\n * @param {Date} [date] custom date. if not provided, current date is taken\n */\n TimeStep.prototype.getLabelMajor = function (date) {\n if (date == undefined) {\n date = this.current;\n }\n\n var format = this.format.majorLabels[this.scale];\n return format && format.length > 0 ? this.moment(date).format(format) : '';\n };\n\n TimeStep.prototype.getClassName = function () {\n var _moment = this.moment;\n var m = this.moment(this.current);\n var current = m.locale ? m.locale('en') : m.lang('en'); // old versions of moment have .lang() function\n var step = this.step;\n\n function even(value) {\n return value / step % 2 == 0 ? ' vis-even' : ' vis-odd';\n }\n\n function today(date) {\n if (date.isSame(new Date(), 'day')) {\n return ' vis-today';\n }\n if (date.isSame(_moment().add(1, 'day'), 'day')) {\n return ' vis-tomorrow';\n }\n if (date.isSame(_moment().add(-1, 'day'), 'day')) {\n return ' vis-yesterday';\n }\n return '';\n }\n\n function currentWeek(date) {\n return date.isSame(new Date(), 'week') ? ' vis-current-week' : '';\n }\n\n function currentMonth(date) {\n return date.isSame(new Date(), 'month') ? ' vis-current-month' : '';\n }\n\n function currentYear(date) {\n return date.isSame(new Date(), 'year') ? ' vis-current-year' : '';\n }\n\n switch (this.scale) {\n case 'millisecond':\n return even(current.milliseconds()).trim();\n\n case 'second':\n return even(current.seconds()).trim();\n\n case 'minute':\n return even(current.minutes()).trim();\n\n case 'hour':\n var hours = current.hours();\n if (this.step == 4) {\n hours = hours + '-h' + (hours + 4);\n }\n return 'vis-h' + hours + today(current) + even(current.hours());\n\n case 'weekday':\n return 'vis-' + current.format('dddd').toLowerCase() + today(current) + currentWeek(current) + even(current.date());\n\n case 'day':\n var day = current.date();\n var month = current.format('MMMM').toLowerCase();\n return 'vis-day' + day + ' vis-' + month + currentMonth(current) + even(day - 1);\n\n case 'month':\n return 'vis-' + current.format('MMMM').toLowerCase() + currentMonth(current) + even(current.month());\n\n case 'year':\n var year = current.year();\n return 'vis-year' + year + currentYear(current) + even(year);\n\n default:\n return '';\n }\n };\n\n module.exports = TimeStep;\n\n/***/ },\n/* 30 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var stack = __webpack_require__(31);\n var RangeItem = __webpack_require__(32);\n\n /**\n * @constructor Group\n * @param {Number | String} groupId\n * @param {Object} data\n * @param {ItemSet} itemSet\n */\n function Group(groupId, data, itemSet) {\n this.groupId = groupId;\n this.subgroups = {};\n this.subgroupIndex = 0;\n this.subgroupOrderer = data && data.subgroupOrder;\n this.itemSet = itemSet;\n\n this.dom = {};\n this.props = {\n label: {\n width: 0,\n height: 0\n }\n };\n this.className = null;\n\n this.items = {}; // items filtered by groupId of this group\n this.visibleItems = []; // items currently visible in window\n this.orderedItems = {\n byStart: [],\n byEnd: []\n };\n this.checkRangedItems = false; // needed to refresh the ranged items if the window is programatically changed with NO overlap.\n var me = this;\n this.itemSet.body.emitter.on(\"checkRangedItems\", function () {\n me.checkRangedItems = true;\n });\n\n this._create();\n\n this.setData(data);\n }\n\n /**\n * Create DOM elements for the group\n * @private\n */\n Group.prototype._create = function () {\n var label = document.createElement('div');\n if (this.itemSet.options.groupEditable.order) {\n label.className = 'vis-label draggable';\n } else {\n label.className = 'vis-label';\n }\n this.dom.label = label;\n\n var inner = document.createElement('div');\n inner.className = 'vis-inner';\n label.appendChild(inner);\n this.dom.inner = inner;\n\n var foreground = document.createElement('div');\n foreground.className = 'vis-group';\n foreground['timeline-group'] = this;\n this.dom.foreground = foreground;\n\n this.dom.background = document.createElement('div');\n this.dom.background.className = 'vis-group';\n\n this.dom.axis = document.createElement('div');\n this.dom.axis.className = 'vis-group';\n\n // create a hidden marker to detect when the Timelines container is attached\n // to the DOM, or the style of a parent of the Timeline is changed from\n // display:none is changed to visible.\n this.dom.marker = document.createElement('div');\n this.dom.marker.style.visibility = 'hidden';\n this.dom.marker.innerHTML = '?';\n this.dom.background.appendChild(this.dom.marker);\n };\n\n /**\n * Set the group data for this group\n * @param {Object} data Group data, can contain properties content and className\n */\n Group.prototype.setData = function (data) {\n // update contents\n var content;\n if (this.itemSet.options && this.itemSet.options.groupTemplate) {\n content = this.itemSet.options.groupTemplate(data);\n } else {\n content = data && data.content;\n }\n\n if (content instanceof Element) {\n this.dom.inner.appendChild(content);\n while (this.dom.inner.firstChild) {\n this.dom.inner.removeChild(this.dom.inner.firstChild);\n }\n this.dom.inner.appendChild(content);\n } else if (content !== undefined && content !== null) {\n this.dom.inner.innerHTML = content;\n } else {\n this.dom.inner.innerHTML = this.groupId || ''; // groupId can be null\n }\n\n // update title\n this.dom.label.title = data && data.title || '';\n\n if (!this.dom.inner.firstChild) {\n util.addClassName(this.dom.inner, 'vis-hidden');\n } else {\n util.removeClassName(this.dom.inner, 'vis-hidden');\n }\n\n // update className\n var className = data && data.className || null;\n if (className != this.className) {\n if (this.className) {\n util.removeClassName(this.dom.label, this.className);\n util.removeClassName(this.dom.foreground, this.className);\n util.removeClassName(this.dom.background, this.className);\n util.removeClassName(this.dom.axis, this.className);\n }\n util.addClassName(this.dom.label, className);\n util.addClassName(this.dom.foreground, className);\n util.addClassName(this.dom.background, className);\n util.addClassName(this.dom.axis, className);\n this.className = className;\n }\n\n // update style\n if (this.style) {\n util.removeCssText(this.dom.label, this.style);\n this.style = null;\n }\n if (data && data.style) {\n util.addCssText(this.dom.label, data.style);\n this.style = data.style;\n }\n };\n\n /**\n * Get the width of the group label\n * @return {number} width\n */\n Group.prototype.getLabelWidth = function () {\n return this.props.label.width;\n };\n\n /**\n * Repaint this group\n * @param {{start: number, end: number}} range\n * @param {{item: {horizontal: number, vertical: number}, axis: number}} margin\n * @param {boolean} [restack=false] Force restacking of all items\n * @return {boolean} Returns true if the group is resized\n */\n Group.prototype.redraw = function (range, margin, restack) {\n var resized = false;\n\n // force recalculation of the height of the items when the marker height changed\n // (due to the Timeline being attached to the DOM or changed from display:none to visible)\n var markerHeight = this.dom.marker.clientHeight;\n if (markerHeight != this.lastMarkerHeight) {\n this.lastMarkerHeight = markerHeight;\n\n util.forEach(this.items, function (item) {\n item.dirty = true;\n if (item.displayed) item.redraw();\n });\n\n restack = true;\n }\n\n // recalculate the height of the subgroups\n this._calculateSubGroupHeights();\n\n // reposition visible items vertically\n if (typeof this.itemSet.options.order === 'function') {\n // a custom order function\n\n if (restack) {\n // brute force restack of all items\n\n // show all items\n var me = this;\n var limitSize = false;\n util.forEach(this.items, function (item) {\n if (!item.displayed) {\n item.redraw();\n me.visibleItems.push(item);\n }\n item.repositionX(limitSize);\n });\n\n // order all items and force a restacking\n var customOrderedItems = this.orderedItems.byStart.slice().sort(function (a, b) {\n return me.itemSet.options.order(a.data, b.data);\n });\n stack.stack(customOrderedItems, margin, true /* restack=true */);\n }\n\n this.visibleItems = this._updateVisibleItems(this.orderedItems, this.visibleItems, range);\n } else {\n // no custom order function, lazy stacking\n this.visibleItems = this._updateVisibleItems(this.orderedItems, this.visibleItems, range);\n\n if (this.itemSet.options.stack) {\n // TODO: ugly way to access options...\n stack.stack(this.visibleItems, margin, restack);\n } else {\n // no stacking\n stack.nostack(this.visibleItems, margin, this.subgroups);\n }\n }\n\n // recalculate the height of the group\n var height = this._calculateHeight(margin);\n\n // calculate actual size and position\n var foreground = this.dom.foreground;\n this.top = foreground.offsetTop;\n this.left = foreground.offsetLeft;\n this.width = foreground.offsetWidth;\n resized = util.updateProperty(this, 'height', height) || resized;\n\n // recalculate size of label\n resized = util.updateProperty(this.props.label, 'width', this.dom.inner.clientWidth) || resized;\n resized = util.updateProperty(this.props.label, 'height', this.dom.inner.clientHeight) || resized;\n\n // apply new height\n this.dom.background.style.height = height + 'px';\n this.dom.foreground.style.height = height + 'px';\n this.dom.label.style.height = height + 'px';\n\n // update vertical position of items after they are re-stacked and the height of the group is calculated\n for (var i = 0, ii = this.visibleItems.length; i < ii; i++) {\n var item = this.visibleItems[i];\n item.repositionY(margin);\n }\n\n return resized;\n };\n\n /**\n * recalculate the height of the subgroups\n * @private\n */\n Group.prototype._calculateSubGroupHeights = function () {\n if (Object.keys(this.subgroups).length > 0) {\n var me = this;\n\n this.resetSubgroups();\n\n util.forEach(this.visibleItems, function (item) {\n if (item.data.subgroup !== undefined) {\n me.subgroups[item.data.subgroup].height = Math.max(me.subgroups[item.data.subgroup].height, item.height);\n me.subgroups[item.data.subgroup].visible = true;\n }\n });\n }\n };\n\n /**\n * recalculate the height of the group\n * @param {{item: {horizontal: number, vertical: number}, axis: number}} margin\n * @returns {number} Returns the height\n * @private\n */\n Group.prototype._calculateHeight = function (margin) {\n // recalculate the height of the group\n var height;\n var visibleItems = this.visibleItems;\n if (visibleItems.length > 0) {\n var min = visibleItems[0].top;\n var max = visibleItems[0].top + visibleItems[0].height;\n util.forEach(visibleItems, function (item) {\n min = Math.min(min, item.top);\n max = Math.max(max, item.top + item.height);\n });\n if (min > margin.axis) {\n // there is an empty gap between the lowest item and the axis\n var offset = min - margin.axis;\n max -= offset;\n util.forEach(visibleItems, function (item) {\n item.top -= offset;\n });\n }\n height = max + margin.item.vertical / 2;\n } else {\n height = 0;\n }\n height = Math.max(height, this.props.label.height);\n\n return height;\n };\n\n /**\n * Show this group: attach to the DOM\n */\n Group.prototype.show = function () {\n if (!this.dom.label.parentNode) {\n this.itemSet.dom.labelSet.appendChild(this.dom.label);\n }\n\n if (!this.dom.foreground.parentNode) {\n this.itemSet.dom.foreground.appendChild(this.dom.foreground);\n }\n\n if (!this.dom.background.parentNode) {\n this.itemSet.dom.background.appendChild(this.dom.background);\n }\n\n if (!this.dom.axis.parentNode) {\n this.itemSet.dom.axis.appendChild(this.dom.axis);\n }\n };\n\n /**\n * Hide this group: remove from the DOM\n */\n Group.prototype.hide = function () {\n var label = this.dom.label;\n if (label.parentNode) {\n label.parentNode.removeChild(label);\n }\n\n var foreground = this.dom.foreground;\n if (foreground.parentNode) {\n foreground.parentNode.removeChild(foreground);\n }\n\n var background = this.dom.background;\n if (background.parentNode) {\n background.parentNode.removeChild(background);\n }\n\n var axis = this.dom.axis;\n if (axis.parentNode) {\n axis.parentNode.removeChild(axis);\n }\n };\n\n /**\n * Add an item to the group\n * @param {Item} item\n */\n Group.prototype.add = function (item) {\n this.items[item.id] = item;\n item.setParent(this);\n\n // add to\n if (item.data.subgroup !== undefined) {\n if (this.subgroups[item.data.subgroup] === undefined) {\n this.subgroups[item.data.subgroup] = { height: 0, visible: false, index: this.subgroupIndex, items: [] };\n this.subgroupIndex++;\n }\n this.subgroups[item.data.subgroup].items.push(item);\n }\n this.orderSubgroups();\n\n if (this.visibleItems.indexOf(item) == -1) {\n var range = this.itemSet.body.range; // TODO: not nice accessing the range like this\n this._checkIfVisible(item, this.visibleItems, range);\n }\n };\n\n Group.prototype.orderSubgroups = function () {\n if (this.subgroupOrderer !== undefined) {\n var sortArray = [];\n if (typeof this.subgroupOrderer == 'string') {\n for (var subgroup in this.subgroups) {\n sortArray.push({ subgroup: subgroup, sortField: this.subgroups[subgroup].items[0].data[this.subgroupOrderer] });\n }\n sortArray.sort(function (a, b) {\n return a.sortField - b.sortField;\n });\n } else if (typeof this.subgroupOrderer == 'function') {\n for (var subgroup in this.subgroups) {\n sortArray.push(this.subgroups[subgroup].items[0].data);\n }\n sortArray.sort(this.subgroupOrderer);\n }\n\n if (sortArray.length > 0) {\n for (var i = 0; i < sortArray.length; i++) {\n this.subgroups[sortArray[i].subgroup].index = i;\n }\n }\n }\n };\n\n Group.prototype.resetSubgroups = function () {\n for (var subgroup in this.subgroups) {\n if (this.subgroups.hasOwnProperty(subgroup)) {\n this.subgroups[subgroup].visible = false;\n }\n }\n };\n\n /**\n * Remove an item from the group\n * @param {Item} item\n */\n Group.prototype.remove = function (item) {\n delete this.items[item.id];\n item.setParent(null);\n\n // remove from visible items\n var index = this.visibleItems.indexOf(item);\n if (index != -1) this.visibleItems.splice(index, 1);\n\n if (item.data.subgroup !== undefined) {\n var subgroup = this.subgroups[item.data.subgroup];\n if (subgroup) {\n var itemIndex = subgroup.items.indexOf(item);\n subgroup.items.splice(itemIndex, 1);\n if (!subgroup.items.length) {\n delete this.subgroups[item.data.subgroup];\n this.subgroupIndex--;\n }\n this.orderSubgroups();\n }\n }\n };\n\n /**\n * Remove an item from the corresponding DataSet\n * @param {Item} item\n */\n Group.prototype.removeFromDataSet = function (item) {\n this.itemSet.removeItem(item.id);\n };\n\n /**\n * Reorder the items\n */\n Group.prototype.order = function () {\n var array = util.toArray(this.items);\n var startArray = [];\n var endArray = [];\n\n for (var i = 0; i < array.length; i++) {\n if (array[i].data.end !== undefined) {\n endArray.push(array[i]);\n }\n startArray.push(array[i]);\n }\n this.orderedItems = {\n byStart: startArray,\n byEnd: endArray\n };\n\n stack.orderByStart(this.orderedItems.byStart);\n stack.orderByEnd(this.orderedItems.byEnd);\n };\n\n /**\n * Update the visible items\n * @param {{byStart: Item[], byEnd: Item[]}} orderedItems All items ordered by start date and by end date\n * @param {Item[]} visibleItems The previously visible items.\n * @param {{start: number, end: number}} range Visible range\n * @return {Item[]} visibleItems The new visible items.\n * @private\n */\n Group.prototype._updateVisibleItems = function (orderedItems, oldVisibleItems, range) {\n var visibleItems = [];\n var visibleItemsLookup = {}; // we keep this to quickly look up if an item already exists in the list without using indexOf on visibleItems\n var interval = (range.end - range.start) / 4;\n var lowerBound = range.start - interval;\n var upperBound = range.end + interval;\n var item, i;\n\n // this function is used to do the binary search.\n var searchFunction = function searchFunction(value) {\n if (value < lowerBound) {\n return -1;\n } else if (value <= upperBound) {\n return 0;\n } else {\n return 1;\n }\n };\n\n // first check if the items that were in view previously are still in view.\n // IMPORTANT: this handles the case for the items with startdate before the window and enddate after the window!\n // also cleans up invisible items.\n if (oldVisibleItems.length > 0) {\n for (i = 0; i < oldVisibleItems.length; i++) {\n this._checkIfVisibleWithReference(oldVisibleItems[i], visibleItems, visibleItemsLookup, range);\n }\n }\n\n // we do a binary search for the items that have only start values.\n var initialPosByStart = util.binarySearchCustom(orderedItems.byStart, searchFunction, 'data', 'start');\n\n // trace the visible items from the inital start pos both ways until an invisible item is found, we only look at the start values.\n this._traceVisible(initialPosByStart, orderedItems.byStart, visibleItems, visibleItemsLookup, function (item) {\n return item.data.start < lowerBound || item.data.start > upperBound;\n });\n\n // if the window has changed programmatically without overlapping the old window, the ranged items with start < lowerBound and end > upperbound are not shown.\n // We therefore have to brute force check all items in the byEnd list\n if (this.checkRangedItems == true) {\n this.checkRangedItems = false;\n for (i = 0; i < orderedItems.byEnd.length; i++) {\n this._checkIfVisibleWithReference(orderedItems.byEnd[i], visibleItems, visibleItemsLookup, range);\n }\n } else {\n // we do a binary search for the items that have defined end times.\n var initialPosByEnd = util.binarySearchCustom(orderedItems.byEnd, searchFunction, 'data', 'end');\n\n // trace the visible items from the inital start pos both ways until an invisible item is found, we only look at the end values.\n this._traceVisible(initialPosByEnd, orderedItems.byEnd, visibleItems, visibleItemsLookup, function (item) {\n return item.data.end < lowerBound || item.data.end > upperBound;\n });\n }\n\n // finally, we reposition all the visible items.\n for (i = 0; i < visibleItems.length; i++) {\n item = visibleItems[i];\n if (!item.displayed) item.show();\n // reposition item horizontally\n item.repositionX();\n }\n\n // debug\n //console.log(\"new line\")\n //if (this.groupId == null) {\n // for (i = 0; i < orderedItems.byStart.length; i++) {\n // item = orderedItems.byStart[i].data;\n // console.log('start',i,initialPosByStart, item.start.valueOf(), item.content, item.start >= lowerBound && item.start <= upperBound,i == initialPosByStart ? \"<------------------- HEREEEE\" : \"\")\n // }\n // for (i = 0; i < orderedItems.byEnd.length; i++) {\n // item = orderedItems.byEnd[i].data;\n // console.log('rangeEnd',i,initialPosByEnd, item.end.valueOf(), item.content, item.end >= range.start && item.end <= range.end,i == initialPosByEnd ? \"<------------------- HEREEEE\" : \"\")\n // }\n //}\n\n return visibleItems;\n };\n\n Group.prototype._traceVisible = function (initialPos, items, visibleItems, visibleItemsLookup, breakCondition) {\n var item;\n var i;\n\n if (initialPos != -1) {\n for (i = initialPos; i >= 0; i--) {\n item = items[i];\n if (breakCondition(item)) {\n break;\n } else {\n if (visibleItemsLookup[item.id] === undefined) {\n visibleItemsLookup[item.id] = true;\n visibleItems.push(item);\n }\n }\n }\n\n for (i = initialPos + 1; i < items.length; i++) {\n item = items[i];\n if (breakCondition(item)) {\n break;\n } else {\n if (visibleItemsLookup[item.id] === undefined) {\n visibleItemsLookup[item.id] = true;\n visibleItems.push(item);\n }\n }\n }\n }\n };\n\n /**\n * this function is very similar to the _checkIfInvisible() but it does not\n * return booleans, hides the item if it should not be seen and always adds to\n * the visibleItems.\n * this one is for brute forcing and hiding.\n *\n * @param {Item} item\n * @param {Array} visibleItems\n * @param {{start:number, end:number}} range\n * @private\n */\n Group.prototype._checkIfVisible = function (item, visibleItems, range) {\n if (item.isVisible(range)) {\n if (!item.displayed) item.show();\n // reposition item horizontally\n item.repositionX();\n visibleItems.push(item);\n } else {\n if (item.displayed) item.hide();\n }\n };\n\n /**\n * this function is very similar to the _checkIfInvisible() but it does not\n * return booleans, hides the item if it should not be seen and always adds to\n * the visibleItems.\n * this one is for brute forcing and hiding.\n *\n * @param {Item} item\n * @param {Array} visibleItems\n * @param {{start:number, end:number}} range\n * @private\n */\n Group.prototype._checkIfVisibleWithReference = function (item, visibleItems, visibleItemsLookup, range) {\n if (item.isVisible(range)) {\n if (visibleItemsLookup[item.id] === undefined) {\n visibleItemsLookup[item.id] = true;\n visibleItems.push(item);\n }\n } else {\n if (item.displayed) item.hide();\n }\n };\n\n module.exports = Group;\n\n/***/ },\n/* 31 */\n/***/ function(module, exports) {\n\n // Utility functions for ordering and stacking of items\n 'use strict';\n\n var EPSILON = 0.001; // used when checking collisions, to prevent round-off errors\n\n /**\n * Order items by their start data\n * @param {Item[]} items\n */\n exports.orderByStart = function (items) {\n items.sort(function (a, b) {\n return a.data.start - b.data.start;\n });\n };\n\n /**\n * Order items by their end date. If they have no end date, their start date\n * is used.\n * @param {Item[]} items\n */\n exports.orderByEnd = function (items) {\n items.sort(function (a, b) {\n var aTime = 'end' in a.data ? a.data.end : a.data.start,\n bTime = 'end' in b.data ? b.data.end : b.data.start;\n\n return aTime - bTime;\n });\n };\n\n /**\n * Adjust vertical positions of the items such that they don't overlap each\n * other.\n * @param {Item[]} items\n * All visible items\n * @param {{item: {horizontal: number, vertical: number}, axis: number}} margin\n * Margins between items and between items and the axis.\n * @param {boolean} [force=false]\n * If true, all items will be repositioned. If false (default), only\n * items having a top===null will be re-stacked\n */\n exports.stack = function (items, margin, force) {\n var i, iMax;\n\n if (force) {\n // reset top position of all items\n for (i = 0, iMax = items.length; i < iMax; i++) {\n items[i].top = null;\n }\n }\n\n // calculate new, non-overlapping positions\n for (i = 0, iMax = items.length; i < iMax; i++) {\n var item = items[i];\n if (item.stack && item.top === null) {\n // initialize top position\n item.top = margin.axis;\n\n do {\n // TODO: optimize checking for overlap. when there is a gap without items,\n // you only need to check for items from the next item on, not from zero\n var collidingItem = null;\n for (var j = 0, jj = items.length; j < jj; j++) {\n var other = items[j];\n if (other.top !== null && other !== item && other.stack && exports.collision(item, other, margin.item)) {\n collidingItem = other;\n break;\n }\n }\n\n if (collidingItem != null) {\n // There is a collision. Reposition the items above the colliding element\n item.top = collidingItem.top + collidingItem.height + margin.item.vertical;\n }\n } while (collidingItem);\n }\n }\n };\n\n /**\n * Adjust vertical positions of the items without stacking them\n * @param {Item[]} items\n * All visible items\n * @param {{item: {horizontal: number, vertical: number}, axis: number}} margin\n * Margins between items and between items and the axis.\n */\n exports.nostack = function (items, margin, subgroups) {\n var i, iMax, newTop;\n\n // reset top position of all items\n for (i = 0, iMax = items.length; i < iMax; i++) {\n if (items[i].data.subgroup !== undefined) {\n newTop = margin.axis;\n for (var subgroup in subgroups) {\n if (subgroups.hasOwnProperty(subgroup)) {\n if (subgroups[subgroup].visible == true && subgroups[subgroup].index < subgroups[items[i].data.subgroup].index) {\n newTop += subgroups[subgroup].height + margin.item.vertical;\n }\n }\n }\n items[i].top = newTop;\n } else {\n items[i].top = margin.axis;\n }\n }\n };\n\n /**\n * Test if the two provided items collide\n * The items must have parameters left, width, top, and height.\n * @param {Item} a The first item\n * @param {Item} b The second item\n * @param {{horizontal: number, vertical: number}} margin\n * An object containing a horizontal and vertical\n * minimum required margin.\n * @return {boolean} true if a and b collide, else false\n */\n exports.collision = function (a, b, margin) {\n return a.left - margin.horizontal + EPSILON < b.left + b.width && a.left + a.width + margin.horizontal - EPSILON > b.left && a.top - margin.vertical + EPSILON < b.top + b.height && a.top + a.height + margin.vertical - EPSILON > b.top;\n };\n\n/***/ },\n/* 32 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n var Item = __webpack_require__(33);\n\n /**\n * @constructor RangeItem\n * @extends Item\n * @param {Object} data Object containing parameters start, end\n * content, className.\n * @param {{toScreen: function, toTime: function}} conversion\n * Conversion functions from time to screen and vice versa\n * @param {Object} [options] Configuration options\n * // TODO: describe options\n */\n function RangeItem(data, conversion, options) {\n this.props = {\n content: {\n width: 0\n }\n };\n this.overflow = false; // if contents can overflow (css styling), this flag is set to true\n\n // validate data\n if (data) {\n if (data.start == undefined) {\n throw new Error('Property \"start\" missing in item ' + data.id);\n }\n if (data.end == undefined) {\n throw new Error('Property \"end\" missing in item ' + data.id);\n }\n }\n\n Item.call(this, data, conversion, options);\n }\n\n RangeItem.prototype = new Item(null, null, null);\n\n RangeItem.prototype.baseClassName = 'vis-item vis-range';\n\n /**\n * Check whether this item is visible inside given range\n * @returns {{start: Number, end: Number}} range with a timestamp for start and end\n * @returns {boolean} True if visible\n */\n RangeItem.prototype.isVisible = function (range) {\n // determine visibility\n return this.data.start < range.end && this.data.end > range.start;\n };\n\n /**\n * Repaint the item\n */\n RangeItem.prototype.redraw = function () {\n var dom = this.dom;\n if (!dom) {\n // create DOM\n this.dom = {};\n dom = this.dom;\n\n // background box\n dom.box = document.createElement('div');\n // className is updated in redraw()\n\n // frame box (to prevent the item contents from overflowing\n dom.frame = document.createElement('div');\n dom.frame.className = 'vis-item-overflow';\n dom.box.appendChild(dom.frame);\n\n // contents box\n dom.content = document.createElement('div');\n dom.content.className = 'vis-item-content';\n dom.frame.appendChild(dom.content);\n\n // attach this item as attribute\n dom.box['timeline-item'] = this;\n\n this.dirty = true;\n }\n\n // append DOM to parent DOM\n if (!this.parent) {\n throw new Error('Cannot redraw item: no parent attached');\n }\n if (!dom.box.parentNode) {\n var foreground = this.parent.dom.foreground;\n if (!foreground) {\n throw new Error('Cannot redraw item: parent has no foreground container element');\n }\n foreground.appendChild(dom.box);\n }\n this.displayed = true;\n\n // Update DOM when item is marked dirty. An item is marked dirty when:\n // - the item is not yet rendered\n // - the item's data is changed\n // - the item is selected/deselected\n if (this.dirty) {\n this._updateContents(this.dom.content);\n this._updateTitle(this.dom.box);\n this._updateDataAttributes(this.dom.box);\n this._updateStyle(this.dom.box);\n\n var editable = (this.options.editable.updateTime || this.options.editable.updateGroup || this.editable === true) && this.editable !== false;\n\n // update class\n var className = (this.data.className ? ' ' + this.data.className : '') + (this.selected ? ' vis-selected' : '') + (editable ? ' vis-editable' : ' vis-readonly');\n dom.box.className = this.baseClassName + className;\n\n // determine from css whether this box has overflow\n this.overflow = window.getComputedStyle(dom.frame).overflow !== 'hidden';\n\n // recalculate size\n // turn off max-width to be able to calculate the real width\n // this causes an extra browser repaint/reflow, but so be it\n this.dom.content.style.maxWidth = 'none';\n this.props.content.width = this.dom.content.offsetWidth;\n this.height = this.dom.box.offsetHeight;\n this.dom.content.style.maxWidth = '';\n\n this.dirty = false;\n }\n\n this._repaintDeleteButton(dom.box);\n this._repaintDragLeft();\n this._repaintDragRight();\n };\n\n /**\n * Show the item in the DOM (when not already visible). The items DOM will\n * be created when needed.\n */\n RangeItem.prototype.show = function () {\n if (!this.displayed) {\n this.redraw();\n }\n };\n\n /**\n * Hide the item from the DOM (when visible)\n * @return {Boolean} changed\n */\n RangeItem.prototype.hide = function () {\n if (this.displayed) {\n var box = this.dom.box;\n\n if (box.parentNode) {\n box.parentNode.removeChild(box);\n }\n\n this.displayed = false;\n }\n };\n\n /**\n * Reposition the item horizontally\n * @param {boolean} [limitSize=true] If true (default), the width of the range\n * item will be limited, as the browser cannot\n * display very wide divs. This means though\n * that the applied left and width may\n * not correspond to the ranges start and end\n * @Override\n */\n RangeItem.prototype.repositionX = function (limitSize) {\n var parentWidth = this.parent.width;\n var start = this.conversion.toScreen(this.data.start);\n var end = this.conversion.toScreen(this.data.end);\n var contentLeft;\n var contentWidth;\n\n // limit the width of the range, as browsers cannot draw very wide divs\n if (limitSize === undefined || limitSize === true) {\n if (start < -parentWidth) {\n start = -parentWidth;\n }\n if (end > 2 * parentWidth) {\n end = 2 * parentWidth;\n }\n }\n var boxWidth = Math.max(end - start, 1);\n\n if (this.overflow) {\n this.left = start;\n this.width = boxWidth + this.props.content.width;\n contentWidth = this.props.content.width;\n\n // Note: The calculation of width is an optimistic calculation, giving\n // a width which will not change when moving the Timeline\n // So no re-stacking needed, which is nicer for the eye;\n } else {\n this.left = start;\n this.width = boxWidth;\n contentWidth = Math.min(end - start, this.props.content.width);\n }\n\n this.dom.box.style.left = this.left + 'px';\n this.dom.box.style.width = boxWidth + 'px';\n\n switch (this.options.align) {\n case 'left':\n this.dom.content.style.left = '0';\n break;\n\n case 'right':\n this.dom.content.style.left = Math.max(boxWidth - contentWidth, 0) + 'px';\n break;\n\n case 'center':\n this.dom.content.style.left = Math.max((boxWidth - contentWidth) / 2, 0) + 'px';\n break;\n\n default:\n // 'auto'\n // when range exceeds left of the window, position the contents at the left of the visible area\n if (this.overflow) {\n if (end > 0) {\n contentLeft = Math.max(-start, 0);\n } else {\n contentLeft = -contentWidth; // ensure it's not visible anymore\n }\n } else {\n if (start < 0) {\n contentLeft = -start;\n } else {\n contentLeft = 0;\n }\n }\n this.dom.content.style.left = contentLeft + 'px';\n }\n };\n\n /**\n * Reposition the item vertically\n * @Override\n */\n RangeItem.prototype.repositionY = function () {\n var orientation = this.options.orientation.item;\n var box = this.dom.box;\n\n if (orientation == 'top') {\n box.style.top = this.top + 'px';\n } else {\n box.style.top = this.parent.height - this.top - this.height + 'px';\n }\n };\n\n /**\n * Repaint a drag area on the left side of the range when the range is selected\n * @protected\n */\n RangeItem.prototype._repaintDragLeft = function () {\n if (this.selected && this.options.editable.updateTime && !this.dom.dragLeft) {\n // create and show drag area\n var dragLeft = document.createElement('div');\n dragLeft.className = 'vis-drag-left';\n dragLeft.dragLeftItem = this;\n\n this.dom.box.appendChild(dragLeft);\n this.dom.dragLeft = dragLeft;\n } else if (!this.selected && this.dom.dragLeft) {\n // delete drag area\n if (this.dom.dragLeft.parentNode) {\n this.dom.dragLeft.parentNode.removeChild(this.dom.dragLeft);\n }\n this.dom.dragLeft = null;\n }\n };\n\n /**\n * Repaint a drag area on the right side of the range when the range is selected\n * @protected\n */\n RangeItem.prototype._repaintDragRight = function () {\n if (this.selected && this.options.editable.updateTime && !this.dom.dragRight) {\n // create and show drag area\n var dragRight = document.createElement('div');\n dragRight.className = 'vis-drag-right';\n dragRight.dragRightItem = this;\n\n this.dom.box.appendChild(dragRight);\n this.dom.dragRight = dragRight;\n } else if (!this.selected && this.dom.dragRight) {\n // delete drag area\n if (this.dom.dragRight.parentNode) {\n this.dom.dragRight.parentNode.removeChild(this.dom.dragRight);\n }\n this.dom.dragRight = null;\n }\n };\n\n module.exports = RangeItem;\n\n/***/ },\n/* 33 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n var util = __webpack_require__(1);\n\n /**\n * @constructor Item\n * @param {Object} data Object containing (optional) parameters type,\n * start, end, content, group, className.\n * @param {{toScreen: function, toTime: function}} conversion\n * Conversion functions from time to screen and vice versa\n * @param {Object} options Configuration options\n * // TODO: describe available options\n */\n function Item(data, conversion, options) {\n this.id = null;\n this.parent = null;\n this.data = data;\n this.dom = null;\n this.conversion = conversion || {};\n this.options = options || {};\n\n this.selected = false;\n this.displayed = false;\n this.dirty = true;\n\n this.top = null;\n this.left = null;\n this.width = null;\n this.height = null;\n\n this.editable = null;\n if (this.data && this.data.hasOwnProperty('editable') && typeof this.data.editable === 'boolean') {\n this.editable = data.editable;\n }\n }\n\n Item.prototype.stack = true;\n\n /**\n * Select current item\n */\n Item.prototype.select = function () {\n this.selected = true;\n this.dirty = true;\n if (this.displayed) this.redraw();\n };\n\n /**\n * Unselect current item\n */\n Item.prototype.unselect = function () {\n this.selected = false;\n this.dirty = true;\n if (this.displayed) this.redraw();\n };\n\n /**\n * Set data for the item. Existing data will be updated. The id should not\n * be changed. When the item is displayed, it will be redrawn immediately.\n * @param {Object} data\n */\n Item.prototype.setData = function (data) {\n var groupChanged = data.group != undefined && this.data.group != data.group;\n if (groupChanged) {\n this.parent.itemSet._moveToGroup(this, data.group);\n }\n\n if (data.hasOwnProperty('editable') && typeof data.editable === 'boolean') {\n this.editable = data.editable;\n }\n\n this.data = data;\n this.dirty = true;\n if (this.displayed) this.redraw();\n };\n\n /**\n * Set a parent for the item\n * @param {ItemSet | Group} parent\n */\n Item.prototype.setParent = function (parent) {\n if (this.displayed) {\n this.hide();\n this.parent = parent;\n if (this.parent) {\n this.show();\n }\n } else {\n this.parent = parent;\n }\n };\n\n /**\n * Check whether this item is visible inside given range\n * @returns {{start: Number, end: Number}} range with a timestamp for start and end\n * @returns {boolean} True if visible\n */\n Item.prototype.isVisible = function (range) {\n // Should be implemented by Item implementations\n return false;\n };\n\n /**\n * Show the Item in the DOM (when not already visible)\n * @return {Boolean} changed\n */\n Item.prototype.show = function () {\n return false;\n };\n\n /**\n * Hide the Item from the DOM (when visible)\n * @return {Boolean} changed\n */\n Item.prototype.hide = function () {\n return false;\n };\n\n /**\n * Repaint the item\n */\n Item.prototype.redraw = function () {\n // should be implemented by the item\n };\n\n /**\n * Reposition the Item horizontally\n */\n Item.prototype.repositionX = function () {\n // should be implemented by the item\n };\n\n /**\n * Reposition the Item vertically\n */\n Item.prototype.repositionY = function () {\n // should be implemented by the item\n };\n\n /**\n * Repaint a delete button on the top right of the item when the item is selected\n * @param {HTMLElement} anchor\n * @protected\n */\n Item.prototype._repaintDeleteButton = function (anchor) {\n var editable = (this.options.editable.remove || this.data.editable === true) && this.data.editable !== false;\n\n if (this.selected && editable && !this.dom.deleteButton) {\n // create and show button\n var me = this;\n\n var deleteButton = document.createElement('div');\n deleteButton.className = 'vis-delete';\n deleteButton.title = 'Delete this item';\n\n // TODO: be able to destroy the delete button\n new Hammer(deleteButton).on('tap', function (event) {\n event.stopPropagation();\n me.parent.removeFromDataSet(me);\n });\n\n anchor.appendChild(deleteButton);\n this.dom.deleteButton = deleteButton;\n } else if (!this.selected && this.dom.deleteButton) {\n // remove button\n if (this.dom.deleteButton.parentNode) {\n this.dom.deleteButton.parentNode.removeChild(this.dom.deleteButton);\n }\n this.dom.deleteButton = null;\n }\n };\n\n /**\n * Set HTML contents for the item\n * @param {Element} element HTML element to fill with the contents\n * @private\n */\n Item.prototype._updateContents = function (element) {\n var content;\n if (this.options.template) {\n var itemData = this.parent.itemSet.itemsData.get(this.id); // get a clone of the data from the dataset\n content = this.options.template(itemData);\n } else {\n content = this.data.content;\n }\n\n var changed = this._contentToString(this.content) !== this._contentToString(content);\n if (changed) {\n // only replace the content when changed\n if (content instanceof Element) {\n element.innerHTML = '';\n element.appendChild(content);\n } else if (content != undefined) {\n element.innerHTML = content;\n } else {\n if (!(this.data.type == 'background' && this.data.content === undefined)) {\n throw new Error('Property \"content\" missing in item ' + this.id);\n }\n }\n\n this.content = content;\n }\n };\n\n /**\n * Set HTML contents for the item\n * @param {Element} element HTML element to fill with the contents\n * @private\n */\n Item.prototype._updateTitle = function (element) {\n if (this.data.title != null) {\n element.title = this.data.title || '';\n } else {\n element.removeAttribute('vis-title');\n }\n };\n\n /**\n * Process dataAttributes timeline option and set as data- attributes on dom.content\n * @param {Element} element HTML element to which the attributes will be attached\n * @private\n */\n Item.prototype._updateDataAttributes = function (element) {\n if (this.options.dataAttributes && this.options.dataAttributes.length > 0) {\n var attributes = [];\n\n if (Array.isArray(this.options.dataAttributes)) {\n attributes = this.options.dataAttributes;\n } else if (this.options.dataAttributes == 'all') {\n attributes = Object.keys(this.data);\n } else {\n return;\n }\n\n for (var i = 0; i < attributes.length; i++) {\n var name = attributes[i];\n var value = this.data[name];\n\n if (value != null) {\n element.setAttribute('data-' + name, value);\n } else {\n element.removeAttribute('data-' + name);\n }\n }\n }\n };\n\n /**\n * Update custom styles of the element\n * @param element\n * @private\n */\n Item.prototype._updateStyle = function (element) {\n // remove old styles\n if (this.style) {\n util.removeCssText(element, this.style);\n this.style = null;\n }\n\n // append new styles\n if (this.data.style) {\n util.addCssText(element, this.data.style);\n this.style = this.data.style;\n }\n };\n\n /**\n * Stringify the items contents\n * @param {string | Element | undefined} content\n * @returns {string | undefined}\n * @private\n */\n Item.prototype._contentToString = function (content) {\n if (typeof content === 'string') return content;\n if (content && 'outerHTML' in content) return content.outerHTML;\n return content;\n };\n\n /**\n * Return the width of the item left from its start date\n * @return {number}\n */\n Item.prototype.getWidthLeft = function () {\n return 0;\n };\n\n /**\n * Return the width of the item right from the max of its start and end date\n * @return {number}\n */\n Item.prototype.getWidthRight = function () {\n return 0;\n };\n\n module.exports = Item;\n\n/***/ },\n/* 34 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var Group = __webpack_require__(30);\n\n /**\n * @constructor BackgroundGroup\n * @param {Number | String} groupId\n * @param {Object} data\n * @param {ItemSet} itemSet\n */\n function BackgroundGroup(groupId, data, itemSet) {\n Group.call(this, groupId, data, itemSet);\n\n this.width = 0;\n this.height = 0;\n this.top = 0;\n this.left = 0;\n }\n\n BackgroundGroup.prototype = Object.create(Group.prototype);\n\n /**\n * Repaint this group\n * @param {{start: number, end: number}} range\n * @param {{item: {horizontal: number, vertical: number}, axis: number}} margin\n * @param {boolean} [restack=false] Force restacking of all items\n * @return {boolean} Returns true if the group is resized\n */\n BackgroundGroup.prototype.redraw = function (range, margin, restack) {\n var resized = false;\n\n this.visibleItems = this._updateVisibleItems(this.orderedItems, this.visibleItems, range);\n\n // calculate actual size\n this.width = this.dom.background.offsetWidth;\n\n // apply new height (just always zero for BackgroundGroup\n this.dom.background.style.height = '0';\n\n // update vertical position of items after they are re-stacked and the height of the group is calculated\n for (var i = 0, ii = this.visibleItems.length; i < ii; i++) {\n var item = this.visibleItems[i];\n item.repositionY(margin);\n }\n\n return resized;\n };\n\n /**\n * Show this group: attach to the DOM\n */\n BackgroundGroup.prototype.show = function () {\n if (!this.dom.background.parentNode) {\n this.itemSet.dom.background.appendChild(this.dom.background);\n }\n };\n\n module.exports = BackgroundGroup;\n\n/***/ },\n/* 35 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Item = __webpack_require__(33);\n var util = __webpack_require__(1);\n\n /**\n * @constructor BoxItem\n * @extends Item\n * @param {Object} data Object containing parameters start\n * content, className.\n * @param {{toScreen: function, toTime: function}} conversion\n * Conversion functions from time to screen and vice versa\n * @param {Object} [options] Configuration options\n * // TODO: describe available options\n */\n function BoxItem(data, conversion, options) {\n this.props = {\n dot: {\n width: 0,\n height: 0\n },\n line: {\n width: 0,\n height: 0\n }\n };\n\n // validate data\n if (data) {\n if (data.start == undefined) {\n throw new Error('Property \"start\" missing in item ' + data);\n }\n }\n\n Item.call(this, data, conversion, options);\n }\n\n BoxItem.prototype = new Item(null, null, null);\n\n /**\n * Check whether this item is visible inside given range\n * @returns {{start: Number, end: Number}} range with a timestamp for start and end\n * @returns {boolean} True if visible\n */\n BoxItem.prototype.isVisible = function (range) {\n // determine visibility\n // TODO: account for the real width of the item. Right now we just add 1/4 to the window\n var interval = (range.end - range.start) / 4;\n return this.data.start > range.start - interval && this.data.start < range.end + interval;\n };\n\n /**\n * Repaint the item\n */\n BoxItem.prototype.redraw = function () {\n var dom = this.dom;\n if (!dom) {\n // create DOM\n this.dom = {};\n dom = this.dom;\n\n // create main box\n dom.box = document.createElement('DIV');\n\n // contents box (inside the background box). used for making margins\n dom.content = document.createElement('DIV');\n dom.content.className = 'vis-item-content';\n dom.box.appendChild(dom.content);\n\n // line to axis\n dom.line = document.createElement('DIV');\n dom.line.className = 'vis-line';\n\n // dot on axis\n dom.dot = document.createElement('DIV');\n dom.dot.className = 'vis-dot';\n\n // attach this item as attribute\n dom.box['timeline-item'] = this;\n\n this.dirty = true;\n }\n\n // append DOM to parent DOM\n if (!this.parent) {\n throw new Error('Cannot redraw item: no parent attached');\n }\n if (!dom.box.parentNode) {\n var foreground = this.parent.dom.foreground;\n if (!foreground) throw new Error('Cannot redraw item: parent has no foreground container element');\n foreground.appendChild(dom.box);\n }\n if (!dom.line.parentNode) {\n var background = this.parent.dom.background;\n if (!background) throw new Error('Cannot redraw item: parent has no background container element');\n background.appendChild(dom.line);\n }\n if (!dom.dot.parentNode) {\n var axis = this.parent.dom.axis;\n if (!background) throw new Error('Cannot redraw item: parent has no axis container element');\n axis.appendChild(dom.dot);\n }\n this.displayed = true;\n\n // Update DOM when item is marked dirty. An item is marked dirty when:\n // - the item is not yet rendered\n // - the item's data is changed\n // - the item is selected/deselected\n if (this.dirty) {\n this._updateContents(this.dom.content);\n this._updateTitle(this.dom.box);\n this._updateDataAttributes(this.dom.box);\n this._updateStyle(this.dom.box);\n\n var editable = (this.options.editable.updateTime || this.options.editable.updateGroup || this.editable === true) && this.editable !== false;\n\n // update class\n var className = (this.data.className ? ' ' + this.data.className : '') + (this.selected ? ' vis-selected' : '') + (editable ? ' vis-editable' : ' vis-readonly');\n dom.box.className = 'vis-item vis-box' + className;\n dom.line.className = 'vis-item vis-line' + className;\n dom.dot.className = 'vis-item vis-dot' + className;\n\n // recalculate size\n this.props.dot.height = dom.dot.offsetHeight;\n this.props.dot.width = dom.dot.offsetWidth;\n this.props.line.width = dom.line.offsetWidth;\n this.width = dom.box.offsetWidth;\n this.height = dom.box.offsetHeight;\n\n this.dirty = false;\n }\n\n this._repaintDeleteButton(dom.box);\n };\n\n /**\n * Show the item in the DOM (when not already displayed). The items DOM will\n * be created when needed.\n */\n BoxItem.prototype.show = function () {\n if (!this.displayed) {\n this.redraw();\n }\n };\n\n /**\n * Hide the item from the DOM (when visible)\n */\n BoxItem.prototype.hide = function () {\n if (this.displayed) {\n var dom = this.dom;\n\n if (dom.box.parentNode) dom.box.parentNode.removeChild(dom.box);\n if (dom.line.parentNode) dom.line.parentNode.removeChild(dom.line);\n if (dom.dot.parentNode) dom.dot.parentNode.removeChild(dom.dot);\n\n this.displayed = false;\n }\n };\n\n /**\n * Reposition the item horizontally\n * @Override\n */\n BoxItem.prototype.repositionX = function () {\n var start = this.conversion.toScreen(this.data.start);\n var align = this.options.align;\n var left;\n\n // calculate left position of the box\n if (align == 'right') {\n this.left = start - this.width;\n } else if (align == 'left') {\n this.left = start;\n } else {\n // default or 'center'\n this.left = start - this.width / 2;\n }\n\n // reposition box\n this.dom.box.style.left = this.left + 'px';\n\n // reposition line\n this.dom.line.style.left = start - this.props.line.width / 2 + 'px';\n\n // reposition dot\n this.dom.dot.style.left = start - this.props.dot.width / 2 + 'px';\n };\n\n /**\n * Reposition the item vertically\n * @Override\n */\n BoxItem.prototype.repositionY = function () {\n var orientation = this.options.orientation.item;\n var box = this.dom.box;\n var line = this.dom.line;\n var dot = this.dom.dot;\n\n if (orientation == 'top') {\n box.style.top = (this.top || 0) + 'px';\n\n line.style.top = '0';\n line.style.height = this.parent.top + this.top + 1 + 'px';\n line.style.bottom = '';\n } else {\n // orientation 'bottom'\n var itemSetHeight = this.parent.itemSet.props.height; // TODO: this is nasty\n var lineHeight = itemSetHeight - this.parent.top - this.parent.height + this.top;\n\n box.style.top = (this.parent.height - this.top - this.height || 0) + 'px';\n line.style.top = itemSetHeight - lineHeight + 'px';\n line.style.bottom = '0';\n }\n\n dot.style.top = -this.props.dot.height / 2 + 'px';\n };\n\n /**\n * Return the width of the item left from its start date\n * @return {number}\n */\n BoxItem.prototype.getWidthLeft = function () {\n return this.width / 2;\n };\n\n /**\n * Return the width of the item right from its start date\n * @return {number}\n */\n BoxItem.prototype.getWidthRight = function () {\n return this.width / 2;\n };\n\n module.exports = BoxItem;\n\n/***/ },\n/* 36 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Item = __webpack_require__(33);\n\n /**\n * @constructor PointItem\n * @extends Item\n * @param {Object} data Object containing parameters start\n * content, className.\n * @param {{toScreen: function, toTime: function}} conversion\n * Conversion functions from time to screen and vice versa\n * @param {Object} [options] Configuration options\n * // TODO: describe available options\n */\n function PointItem(data, conversion, options) {\n this.props = {\n dot: {\n top: 0,\n width: 0,\n height: 0\n },\n content: {\n height: 0,\n marginLeft: 0\n }\n };\n\n // validate data\n if (data) {\n if (data.start == undefined) {\n throw new Error('Property \"start\" missing in item ' + data);\n }\n }\n\n Item.call(this, data, conversion, options);\n }\n\n PointItem.prototype = new Item(null, null, null);\n\n /**\n * Check whether this item is visible inside given range\n * @returns {{start: Number, end: Number}} range with a timestamp for start and end\n * @returns {boolean} True if visible\n */\n PointItem.prototype.isVisible = function (range) {\n // determine visibility\n // TODO: account for the real width of the item. Right now we just add 1/4 to the window\n var interval = (range.end - range.start) / 4;\n return this.data.start > range.start - interval && this.data.start < range.end + interval;\n };\n\n /**\n * Repaint the item\n */\n PointItem.prototype.redraw = function () {\n var dom = this.dom;\n if (!dom) {\n // create DOM\n this.dom = {};\n dom = this.dom;\n\n // background box\n dom.point = document.createElement('div');\n // className is updated in redraw()\n\n // contents box, right from the dot\n dom.content = document.createElement('div');\n dom.content.className = 'vis-item-content';\n dom.point.appendChild(dom.content);\n\n // dot at start\n dom.dot = document.createElement('div');\n dom.point.appendChild(dom.dot);\n\n // attach this item as attribute\n dom.point['timeline-item'] = this;\n\n this.dirty = true;\n }\n\n // append DOM to parent DOM\n if (!this.parent) {\n throw new Error('Cannot redraw item: no parent attached');\n }\n if (!dom.point.parentNode) {\n var foreground = this.parent.dom.foreground;\n if (!foreground) {\n throw new Error('Cannot redraw item: parent has no foreground container element');\n }\n foreground.appendChild(dom.point);\n }\n this.displayed = true;\n\n // Update DOM when item is marked dirty. An item is marked dirty when:\n // - the item is not yet rendered\n // - the item's data is changed\n // - the item is selected/deselected\n if (this.dirty) {\n this._updateContents(this.dom.content);\n this._updateTitle(this.dom.point);\n this._updateDataAttributes(this.dom.point);\n this._updateStyle(this.dom.point);\n\n var editable = (this.options.editable.updateTime || this.options.editable.updateGroup || this.editable === true) && this.editable !== false;\n\n // update class\n var className = (this.data.className ? ' ' + this.data.className : '') + (this.selected ? ' vis-selected' : '') + (editable ? ' vis-editable' : ' vis-readonly');\n dom.point.className = 'vis-item vis-point' + className;\n dom.dot.className = 'vis-item vis-dot' + className;\n\n // recalculate size of dot and contents\n this.props.dot.width = dom.dot.offsetWidth;\n this.props.dot.height = dom.dot.offsetHeight;\n this.props.content.height = dom.content.offsetHeight;\n\n // resize contents\n dom.content.style.marginLeft = 2 * this.props.dot.width + 'px';\n //dom.content.style.marginRight = ... + 'px'; // TODO: margin right\n\n // recalculate size\n this.width = dom.point.offsetWidth;\n this.height = dom.point.offsetHeight;\n\n // reposition the dot\n dom.dot.style.top = (this.height - this.props.dot.height) / 2 + 'px';\n dom.dot.style.left = this.props.dot.width / 2 + 'px';\n\n this.dirty = false;\n }\n\n this._repaintDeleteButton(dom.point);\n };\n\n /**\n * Show the item in the DOM (when not already visible). The items DOM will\n * be created when needed.\n */\n PointItem.prototype.show = function () {\n if (!this.displayed) {\n this.redraw();\n }\n };\n\n /**\n * Hide the item from the DOM (when visible)\n */\n PointItem.prototype.hide = function () {\n if (this.displayed) {\n if (this.dom.point.parentNode) {\n this.dom.point.parentNode.removeChild(this.dom.point);\n }\n\n this.displayed = false;\n }\n };\n\n /**\n * Reposition the item horizontally\n * @Override\n */\n PointItem.prototype.repositionX = function () {\n var start = this.conversion.toScreen(this.data.start);\n\n this.left = start - this.props.dot.width;\n\n // reposition point\n this.dom.point.style.left = this.left + 'px';\n };\n\n /**\n * Reposition the item vertically\n * @Override\n */\n PointItem.prototype.repositionY = function () {\n var orientation = this.options.orientation.item;\n var point = this.dom.point;\n\n if (orientation == 'top') {\n point.style.top = this.top + 'px';\n } else {\n point.style.top = this.parent.height - this.top - this.height + 'px';\n }\n };\n\n /**\n * Return the width of the item left from its start date\n * @return {number}\n */\n PointItem.prototype.getWidthLeft = function () {\n return this.props.dot.width;\n };\n\n /**\n * Return the width of the item right from its start date\n * @return {number}\n */\n PointItem.prototype.getWidthRight = function () {\n return this.width - this.props.dot.width;\n };\n\n module.exports = PointItem;\n\n/***/ },\n/* 37 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n var Item = __webpack_require__(33);\n var BackgroundGroup = __webpack_require__(34);\n var RangeItem = __webpack_require__(32);\n\n /**\n * @constructor BackgroundItem\n * @extends Item\n * @param {Object} data Object containing parameters start, end\n * content, className.\n * @param {{toScreen: function, toTime: function}} conversion\n * Conversion functions from time to screen and vice versa\n * @param {Object} [options] Configuration options\n * // TODO: describe options\n */\n // TODO: implement support for the BackgroundItem just having a start, then being displayed as a sort of an annotation\n function BackgroundItem(data, conversion, options) {\n this.props = {\n content: {\n width: 0\n }\n };\n this.overflow = false; // if contents can overflow (css styling), this flag is set to true\n\n // validate data\n if (data) {\n if (data.start == undefined) {\n throw new Error('Property \"start\" missing in item ' + data.id);\n }\n if (data.end == undefined) {\n throw new Error('Property \"end\" missing in item ' + data.id);\n }\n }\n\n Item.call(this, data, conversion, options);\n }\n\n BackgroundItem.prototype = new Item(null, null, null);\n\n BackgroundItem.prototype.baseClassName = 'vis-item vis-background';\n BackgroundItem.prototype.stack = false;\n\n /**\n * Check whether this item is visible inside given range\n * @returns {{start: Number, end: Number}} range with a timestamp for start and end\n * @returns {boolean} True if visible\n */\n BackgroundItem.prototype.isVisible = function (range) {\n // determine visibility\n return this.data.start < range.end && this.data.end > range.start;\n };\n\n /**\n * Repaint the item\n */\n BackgroundItem.prototype.redraw = function () {\n var dom = this.dom;\n if (!dom) {\n // create DOM\n this.dom = {};\n dom = this.dom;\n\n // background box\n dom.box = document.createElement('div');\n // className is updated in redraw()\n\n // frame box (to prevent the item contents from overflowing\n dom.frame = document.createElement('div');\n dom.frame.className = 'vis-item-overflow';\n dom.box.appendChild(dom.frame);\n\n // contents box\n dom.content = document.createElement('div');\n dom.content.className = 'vis-item-content';\n dom.frame.appendChild(dom.content);\n\n // Note: we do NOT attach this item as attribute to the DOM,\n // such that background items cannot be selected\n //dom.box['timeline-item'] = this;\n\n this.dirty = true;\n }\n\n // append DOM to parent DOM\n if (!this.parent) {\n throw new Error('Cannot redraw item: no parent attached');\n }\n if (!dom.box.parentNode) {\n var background = this.parent.dom.background;\n if (!background) {\n throw new Error('Cannot redraw item: parent has no background container element');\n }\n background.appendChild(dom.box);\n }\n this.displayed = true;\n\n // Update DOM when item is marked dirty. An item is marked dirty when:\n // - the item is not yet rendered\n // - the item's data is changed\n // - the item is selected/deselected\n if (this.dirty) {\n this._updateContents(this.dom.content);\n this._updateTitle(this.dom.content);\n this._updateDataAttributes(this.dom.content);\n this._updateStyle(this.dom.box);\n\n // update class\n var className = (this.data.className ? ' ' + this.data.className : '') + (this.selected ? ' vis-selected' : '');\n dom.box.className = this.baseClassName + className;\n\n // determine from css whether this box has overflow\n this.overflow = window.getComputedStyle(dom.content).overflow !== 'hidden';\n\n // recalculate size\n this.props.content.width = this.dom.content.offsetWidth;\n this.height = 0; // set height zero, so this item will be ignored when stacking items\n\n this.dirty = false;\n }\n };\n\n /**\n * Show the item in the DOM (when not already visible). The items DOM will\n * be created when needed.\n */\n BackgroundItem.prototype.show = RangeItem.prototype.show;\n\n /**\n * Hide the item from the DOM (when visible)\n * @return {Boolean} changed\n */\n BackgroundItem.prototype.hide = RangeItem.prototype.hide;\n\n /**\n * Reposition the item horizontally\n * @Override\n */\n BackgroundItem.prototype.repositionX = RangeItem.prototype.repositionX;\n\n /**\n * Reposition the item vertically\n * @Override\n */\n BackgroundItem.prototype.repositionY = function (margin) {\n var onTop = this.options.orientation.item === 'top';\n this.dom.content.style.top = onTop ? '' : '0';\n this.dom.content.style.bottom = onTop ? '0' : '';\n var height;\n\n // special positioning for subgroups\n if (this.data.subgroup !== undefined) {\n // TODO: instead of calculating the top position of the subgroups here for every BackgroundItem, calculate the top of the subgroup once in Itemset\n\n var itemSubgroup = this.data.subgroup;\n var subgroups = this.parent.subgroups;\n var subgroupIndex = subgroups[itemSubgroup].index;\n // if the orientation is top, we need to take the difference in height into account.\n if (onTop == true) {\n // the first subgroup will have to account for the distance from the top to the first item.\n height = this.parent.subgroups[itemSubgroup].height + margin.item.vertical;\n height += subgroupIndex == 0 ? margin.axis - 0.5 * margin.item.vertical : 0;\n var newTop = this.parent.top;\n for (var subgroup in subgroups) {\n if (subgroups.hasOwnProperty(subgroup)) {\n if (subgroups[subgroup].visible == true && subgroups[subgroup].index < subgroupIndex) {\n newTop += subgroups[subgroup].height + margin.item.vertical;\n }\n }\n }\n\n // the others will have to be offset downwards with this same distance.\n newTop += subgroupIndex != 0 ? margin.axis - 0.5 * margin.item.vertical : 0;\n this.dom.box.style.top = newTop + 'px';\n this.dom.box.style.bottom = '';\n }\n // and when the orientation is bottom:\n else {\n var newTop = this.parent.top;\n var totalHeight = 0;\n for (var subgroup in subgroups) {\n if (subgroups.hasOwnProperty(subgroup)) {\n if (subgroups[subgroup].visible == true) {\n var newHeight = subgroups[subgroup].height + margin.item.vertical;\n totalHeight += newHeight;\n if (subgroups[subgroup].index > subgroupIndex) {\n newTop += newHeight;\n }\n }\n }\n }\n height = this.parent.subgroups[itemSubgroup].height + margin.item.vertical;\n this.dom.box.style.top = this.parent.height - totalHeight + newTop + 'px';\n this.dom.box.style.bottom = '';\n }\n }\n // and in the case of no subgroups:\n else {\n // we want backgrounds with groups to only show in groups.\n if (this.parent instanceof BackgroundGroup) {\n // if the item is not in a group:\n height = Math.max(this.parent.height, this.parent.itemSet.body.domProps.center.height, this.parent.itemSet.body.domProps.centerContainer.height);\n this.dom.box.style.top = onTop ? '0' : '';\n this.dom.box.style.bottom = onTop ? '' : '0';\n } else {\n height = this.parent.height;\n // same alignment for items when orientation is top or bottom\n this.dom.box.style.top = this.parent.top + 'px';\n this.dom.box.style.bottom = '';\n }\n }\n this.dom.box.style.height = height + 'px';\n };\n\n module.exports = BackgroundItem;\n\n/***/ },\n/* 38 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var Component = __webpack_require__(25);\n var TimeStep = __webpack_require__(29);\n var DateUtil = __webpack_require__(26);\n var moment = __webpack_require__(2);\n\n /**\n * A horizontal time axis\n * @param {{dom: Object, domProps: Object, emitter: Emitter, range: Range}} body\n * @param {Object} [options] See TimeAxis.setOptions for the available\n * options.\n * @constructor TimeAxis\n * @extends Component\n */\n function TimeAxis(body, options) {\n this.dom = {\n foreground: null,\n lines: [],\n majorTexts: [],\n minorTexts: [],\n redundant: {\n lines: [],\n majorTexts: [],\n minorTexts: []\n }\n };\n this.props = {\n range: {\n start: 0,\n end: 0,\n minimumStep: 0\n },\n lineTop: 0\n };\n\n this.defaultOptions = {\n orientation: {\n axis: 'bottom'\n }, // axis orientation: 'top' or 'bottom'\n showMinorLabels: true,\n showMajorLabels: true,\n maxMinorChars: 7,\n format: TimeStep.FORMAT,\n moment: moment,\n timeAxis: null\n };\n this.options = util.extend({}, this.defaultOptions);\n\n this.body = body;\n\n // create the HTML DOM\n this._create();\n\n this.setOptions(options);\n }\n\n TimeAxis.prototype = new Component();\n\n /**\n * Set options for the TimeAxis.\n * Parameters will be merged in current options.\n * @param {Object} options Available options:\n * {string} [orientation.axis]\n * {boolean} [showMinorLabels]\n * {boolean} [showMajorLabels]\n */\n TimeAxis.prototype.setOptions = function (options) {\n if (options) {\n // copy all options that we know\n util.selectiveExtend(['showMinorLabels', 'showMajorLabels', 'maxMinorChars', 'hiddenDates', 'timeAxis', 'moment'], this.options, options);\n\n // deep copy the format options\n util.selectiveDeepExtend(['format'], this.options, options);\n\n if ('orientation' in options) {\n if (typeof options.orientation === 'string') {\n this.options.orientation.axis = options.orientation;\n } else if (typeof options.orientation === 'object' && 'axis' in options.orientation) {\n this.options.orientation.axis = options.orientation.axis;\n }\n }\n\n // apply locale to moment.js\n // TODO: not so nice, this is applied globally to moment.js\n if ('locale' in options) {\n if (typeof moment.locale === 'function') {\n // moment.js 2.8.1+\n moment.locale(options.locale);\n } else {\n moment.lang(options.locale);\n }\n }\n }\n };\n\n /**\n * Create the HTML DOM for the TimeAxis\n */\n TimeAxis.prototype._create = function () {\n this.dom.foreground = document.createElement('div');\n this.dom.background = document.createElement('div');\n\n this.dom.foreground.className = 'vis-time-axis vis-foreground';\n this.dom.background.className = 'vis-time-axis vis-background';\n };\n\n /**\n * Destroy the TimeAxis\n */\n TimeAxis.prototype.destroy = function () {\n // remove from DOM\n if (this.dom.foreground.parentNode) {\n this.dom.foreground.parentNode.removeChild(this.dom.foreground);\n }\n if (this.dom.background.parentNode) {\n this.dom.background.parentNode.removeChild(this.dom.background);\n }\n\n this.body = null;\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n TimeAxis.prototype.redraw = function () {\n var props = this.props;\n var foreground = this.dom.foreground;\n var background = this.dom.background;\n\n // determine the correct parent DOM element (depending on option orientation)\n var parent = this.options.orientation.axis == 'top' ? this.body.dom.top : this.body.dom.bottom;\n var parentChanged = foreground.parentNode !== parent;\n\n // calculate character width and height\n this._calculateCharSize();\n\n // TODO: recalculate sizes only needed when parent is resized or options is changed\n var showMinorLabels = this.options.showMinorLabels && this.options.orientation.axis !== 'none';\n var showMajorLabels = this.options.showMajorLabels && this.options.orientation.axis !== 'none';\n\n // determine the width and height of the elemens for the axis\n props.minorLabelHeight = showMinorLabels ? props.minorCharHeight : 0;\n props.majorLabelHeight = showMajorLabels ? props.majorCharHeight : 0;\n props.height = props.minorLabelHeight + props.majorLabelHeight;\n props.width = foreground.offsetWidth;\n\n props.minorLineHeight = this.body.domProps.root.height - props.majorLabelHeight - (this.options.orientation.axis == 'top' ? this.body.domProps.bottom.height : this.body.domProps.top.height);\n props.minorLineWidth = 1; // TODO: really calculate width\n props.majorLineHeight = props.minorLineHeight + props.majorLabelHeight;\n props.majorLineWidth = 1; // TODO: really calculate width\n\n // take foreground and background offline while updating (is almost twice as fast)\n var foregroundNextSibling = foreground.nextSibling;\n var backgroundNextSibling = background.nextSibling;\n foreground.parentNode && foreground.parentNode.removeChild(foreground);\n background.parentNode && background.parentNode.removeChild(background);\n\n foreground.style.height = this.props.height + 'px';\n\n this._repaintLabels();\n\n // put DOM online again (at the same place)\n if (foregroundNextSibling) {\n parent.insertBefore(foreground, foregroundNextSibling);\n } else {\n parent.appendChild(foreground);\n }\n if (backgroundNextSibling) {\n this.body.dom.backgroundVertical.insertBefore(background, backgroundNextSibling);\n } else {\n this.body.dom.backgroundVertical.appendChild(background);\n }\n\n return this._isResized() || parentChanged;\n };\n\n /**\n * Repaint major and minor text labels and vertical grid lines\n * @private\n */\n TimeAxis.prototype._repaintLabels = function () {\n var orientation = this.options.orientation.axis;\n\n // calculate range and step (step such that we have space for 7 characters per label)\n var start = util.convert(this.body.range.start, 'Number');\n var end = util.convert(this.body.range.end, 'Number');\n var timeLabelsize = this.body.util.toTime((this.props.minorCharWidth || 10) * this.options.maxMinorChars).valueOf();\n var minimumStep = timeLabelsize - DateUtil.getHiddenDurationBefore(this.options.moment, this.body.hiddenDates, this.body.range, timeLabelsize);\n minimumStep -= this.body.util.toTime(0).valueOf();\n\n var step = new TimeStep(new Date(start), new Date(end), minimumStep, this.body.hiddenDates);\n step.setMoment(this.options.moment);\n if (this.options.format) {\n step.setFormat(this.options.format);\n }\n if (this.options.timeAxis) {\n step.setScale(this.options.timeAxis);\n }\n this.step = step;\n\n // Move all DOM elements to a \"redundant\" list, where they\n // can be picked for re-use, and clear the lists with lines and texts.\n // At the end of the function _repaintLabels, left over elements will be cleaned up\n var dom = this.dom;\n dom.redundant.lines = dom.lines;\n dom.redundant.majorTexts = dom.majorTexts;\n dom.redundant.minorTexts = dom.minorTexts;\n dom.lines = [];\n dom.majorTexts = [];\n dom.minorTexts = [];\n\n var current;\n var next;\n var x;\n var xNext;\n var isMajor, nextIsMajor;\n var width = 0,\n prevWidth;\n var line;\n var labelMinor;\n var xFirstMajorLabel = undefined;\n var count = 0;\n var MAX = 1000;\n var className;\n\n step.start();\n next = step.getCurrent();\n xNext = this.body.util.toScreen(next);\n while (step.hasNext() && count < MAX) {\n count++;\n\n isMajor = step.isMajor();\n className = step.getClassName();\n labelMinor = step.getLabelMinor();\n\n current = next;\n x = xNext;\n\n step.next();\n next = step.getCurrent();\n nextIsMajor = step.isMajor();\n xNext = this.body.util.toScreen(next);\n\n prevWidth = width;\n width = xNext - x;\n var showMinorGrid = width >= prevWidth * 0.4; // prevent displaying of the 31th of the month on a scale of 5 days\n\n if (this.options.showMinorLabels && showMinorGrid) {\n var label = this._repaintMinorText(x, labelMinor, orientation, className);\n label.style.width = width + 'px'; // set width to prevent overflow\n }\n\n if (isMajor && this.options.showMajorLabels) {\n if (x > 0) {\n if (xFirstMajorLabel == undefined) {\n xFirstMajorLabel = x;\n }\n label = this._repaintMajorText(x, step.getLabelMajor(), orientation, className);\n }\n line = this._repaintMajorLine(x, width, orientation, className);\n } else {\n // minor line\n if (showMinorGrid) {\n line = this._repaintMinorLine(x, width, orientation, className);\n } else {\n if (line) {\n // adjust the width of the previous grid\n line.style.width = parseInt(line.style.width) + width + 'px';\n }\n }\n }\n }\n\n if (count === MAX && !warnedForOverflow) {\n console.warn('Something is wrong with the Timeline scale. Limited drawing of grid lines to ' + MAX + ' lines.');\n warnedForOverflow = true;\n }\n\n // create a major label on the left when needed\n if (this.options.showMajorLabels) {\n var leftTime = this.body.util.toTime(0),\n leftText = step.getLabelMajor(leftTime),\n widthText = leftText.length * (this.props.majorCharWidth || 10) + 10; // upper bound estimation\n\n if (xFirstMajorLabel == undefined || widthText < xFirstMajorLabel) {\n this._repaintMajorText(0, leftText, orientation, className);\n }\n }\n\n // Cleanup leftover DOM elements from the redundant list\n util.forEach(this.dom.redundant, function (arr) {\n while (arr.length) {\n var elem = arr.pop();\n if (elem && elem.parentNode) {\n elem.parentNode.removeChild(elem);\n }\n }\n });\n };\n\n /**\n * Create a minor label for the axis at position x\n * @param {Number} x\n * @param {String} text\n * @param {String} orientation \"top\" or \"bottom\" (default)\n * @param {String} className\n * @return {Element} Returns the HTML element of the created label\n * @private\n */\n TimeAxis.prototype._repaintMinorText = function (x, text, orientation, className) {\n // reuse redundant label\n var label = this.dom.redundant.minorTexts.shift();\n\n if (!label) {\n // create new label\n var content = document.createTextNode('');\n label = document.createElement('div');\n label.appendChild(content);\n this.dom.foreground.appendChild(label);\n }\n this.dom.minorTexts.push(label);\n\n label.childNodes[0].nodeValue = text;\n\n label.style.top = orientation == 'top' ? this.props.majorLabelHeight + 'px' : '0';\n label.style.left = x + 'px';\n label.className = 'vis-text vis-minor ' + className;\n //label.title = title; // TODO: this is a heavy operation\n\n return label;\n };\n\n /**\n * Create a Major label for the axis at position x\n * @param {Number} x\n * @param {String} text\n * @param {String} orientation \"top\" or \"bottom\" (default)\n * @param {String} className\n * @return {Element} Returns the HTML element of the created label\n * @private\n */\n TimeAxis.prototype._repaintMajorText = function (x, text, orientation, className) {\n // reuse redundant label\n var label = this.dom.redundant.majorTexts.shift();\n\n if (!label) {\n // create label\n var content = document.createTextNode(text);\n label = document.createElement('div');\n label.appendChild(content);\n this.dom.foreground.appendChild(label);\n }\n this.dom.majorTexts.push(label);\n\n label.childNodes[0].nodeValue = text;\n label.className = 'vis-text vis-major ' + className;\n //label.title = title; // TODO: this is a heavy operation\n\n label.style.top = orientation == 'top' ? '0' : this.props.minorLabelHeight + 'px';\n label.style.left = x + 'px';\n\n return label;\n };\n\n /**\n * Create a minor line for the axis at position x\n * @param {Number} x\n * @param {Number} width\n * @param {String} orientation \"top\" or \"bottom\" (default)\n * @param {String} className\n * @return {Element} Returns the created line\n * @private\n */\n TimeAxis.prototype._repaintMinorLine = function (x, width, orientation, className) {\n // reuse redundant line\n var line = this.dom.redundant.lines.shift();\n if (!line) {\n // create vertical line\n line = document.createElement('div');\n this.dom.background.appendChild(line);\n }\n this.dom.lines.push(line);\n\n var props = this.props;\n if (orientation == 'top') {\n line.style.top = props.majorLabelHeight + 'px';\n } else {\n line.style.top = this.body.domProps.top.height + 'px';\n }\n line.style.height = props.minorLineHeight + 'px';\n line.style.left = x - props.minorLineWidth / 2 + 'px';\n line.style.width = width + 'px';\n\n line.className = 'vis-grid vis-vertical vis-minor ' + className;\n\n return line;\n };\n\n /**\n * Create a Major line for the axis at position x\n * @param {Number} x\n * @param {Number} width\n * @param {String} orientation \"top\" or \"bottom\" (default)\n * @param {String} className\n * @return {Element} Returns the created line\n * @private\n */\n TimeAxis.prototype._repaintMajorLine = function (x, width, orientation, className) {\n // reuse redundant line\n var line = this.dom.redundant.lines.shift();\n if (!line) {\n // create vertical line\n line = document.createElement('div');\n this.dom.background.appendChild(line);\n }\n this.dom.lines.push(line);\n\n var props = this.props;\n if (orientation == 'top') {\n line.style.top = '0';\n } else {\n line.style.top = this.body.domProps.top.height + 'px';\n }\n line.style.left = x - props.majorLineWidth / 2 + 'px';\n line.style.height = props.majorLineHeight + 'px';\n line.style.width = width + 'px';\n\n line.className = 'vis-grid vis-vertical vis-major ' + className;\n\n return line;\n };\n\n /**\n * Determine the size of text on the axis (both major and minor axis).\n * The size is calculated only once and then cached in this.props.\n * @private\n */\n TimeAxis.prototype._calculateCharSize = function () {\n // Note: We calculate char size with every redraw. Size may change, for\n // example when any of the timelines parents had display:none for example.\n\n // determine the char width and height on the minor axis\n if (!this.dom.measureCharMinor) {\n this.dom.measureCharMinor = document.createElement('DIV');\n this.dom.measureCharMinor.className = 'vis-text vis-minor vis-measure';\n this.dom.measureCharMinor.style.position = 'absolute';\n\n this.dom.measureCharMinor.appendChild(document.createTextNode('0'));\n this.dom.foreground.appendChild(this.dom.measureCharMinor);\n }\n this.props.minorCharHeight = this.dom.measureCharMinor.clientHeight;\n this.props.minorCharWidth = this.dom.measureCharMinor.clientWidth;\n\n // determine the char width and height on the major axis\n if (!this.dom.measureCharMajor) {\n this.dom.measureCharMajor = document.createElement('DIV');\n this.dom.measureCharMajor.className = 'vis-text vis-major vis-measure';\n this.dom.measureCharMajor.style.position = 'absolute';\n\n this.dom.measureCharMajor.appendChild(document.createTextNode('0'));\n this.dom.foreground.appendChild(this.dom.measureCharMajor);\n }\n this.props.majorCharHeight = this.dom.measureCharMajor.clientHeight;\n this.props.majorCharWidth = this.dom.measureCharMajor.clientWidth;\n };\n\n var warnedForOverflow = false;\n\n module.exports = TimeAxis;\n\n/***/ },\n/* 39 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var keycharm = __webpack_require__(40);\n var Emitter = __webpack_require__(12);\n var Hammer = __webpack_require__(20);\n var util = __webpack_require__(1);\n\n /**\n * Turn an element into an clickToUse element.\n * When not active, the element has a transparent overlay. When the overlay is\n * clicked, the mode is changed to active.\n * When active, the element is displayed with a blue border around it, and\n * the interactive contents of the element can be used. When clicked outside\n * the element, the elements mode is changed to inactive.\n * @param {Element} container\n * @constructor\n */\n function Activator(container) {\n this.active = false;\n\n this.dom = {\n container: container\n };\n\n this.dom.overlay = document.createElement('div');\n this.dom.overlay.className = 'vis-overlay';\n\n this.dom.container.appendChild(this.dom.overlay);\n\n this.hammer = Hammer(this.dom.overlay);\n this.hammer.on('tap', this._onTapOverlay.bind(this));\n\n // block all touch events (except tap)\n var me = this;\n var events = ['tap', 'doubletap', 'press', 'pinch', 'pan', 'panstart', 'panmove', 'panend'];\n events.forEach(function (event) {\n me.hammer.on(event, function (event) {\n event.stopPropagation();\n });\n });\n\n // attach a click event to the window, in order to deactivate when clicking outside the timeline\n if (document && document.body) {\n this.onClick = function (event) {\n if (!_hasParent(event.target, container)) {\n me.deactivate();\n }\n };\n document.body.addEventListener('click', this.onClick);\n }\n\n if (this.keycharm !== undefined) {\n this.keycharm.destroy();\n }\n this.keycharm = keycharm();\n\n // keycharm listener only bounded when active)\n this.escListener = this.deactivate.bind(this);\n }\n\n // turn into an event emitter\n Emitter(Activator.prototype);\n\n // The currently active activator\n Activator.current = null;\n\n /**\n * Destroy the activator. Cleans up all created DOM and event listeners\n */\n Activator.prototype.destroy = function () {\n this.deactivate();\n\n // remove dom\n this.dom.overlay.parentNode.removeChild(this.dom.overlay);\n\n // remove global event listener\n if (this.onClick) {\n document.body.removeEventListener('click', this.onClick);\n }\n\n // cleanup hammer instances\n this.hammer.destroy();\n this.hammer = null;\n // FIXME: cleaning up hammer instances doesn't work (Timeline not removed from memory)\n };\n\n /**\n * Activate the element\n * Overlay is hidden, element is decorated with a blue shadow border\n */\n Activator.prototype.activate = function () {\n // we allow only one active activator at a time\n if (Activator.current) {\n Activator.current.deactivate();\n }\n Activator.current = this;\n\n this.active = true;\n this.dom.overlay.style.display = 'none';\n util.addClassName(this.dom.container, 'vis-active');\n\n this.emit('change');\n this.emit('activate');\n\n // ugly hack: bind ESC after emitting the events, as the Network rebinds all\n // keyboard events on a 'change' event\n this.keycharm.bind('esc', this.escListener);\n };\n\n /**\n * Deactivate the element\n * Overlay is displayed on top of the element\n */\n Activator.prototype.deactivate = function () {\n this.active = false;\n this.dom.overlay.style.display = '';\n util.removeClassName(this.dom.container, 'vis-active');\n this.keycharm.unbind('esc', this.escListener);\n\n this.emit('change');\n this.emit('deactivate');\n };\n\n /**\n * Handle a tap event: activate the container\n * @param event\n * @private\n */\n Activator.prototype._onTapOverlay = function (event) {\n // activate the container\n this.activate();\n event.stopPropagation();\n };\n\n /**\n * Test whether the element has the requested parent element somewhere in\n * its chain of parent nodes.\n * @param {HTMLElement} element\n * @param {HTMLElement} parent\n * @returns {boolean} Returns true when the parent is found somewhere in the\n * chain of parent nodes.\n * @private\n */\n function _hasParent(element, parent) {\n while (element) {\n if (element === parent) {\n return true;\n }\n element = element.parentNode;\n }\n return false;\n }\n\n module.exports = Activator;\n\n/***/ },\n/* 40 */\n/***/ function(module, exports, __webpack_require__) {\n\n var __WEBPACK_AMD_DEFINE_FACTORY__, __WEBPACK_AMD_DEFINE_ARRAY__, __WEBPACK_AMD_DEFINE_RESULT__;\"use strict\";\n /**\n * Created by Alex on 11/6/2014.\n */\n\n // https://github.com/umdjs/umd/blob/master/returnExports.js#L40-L60\n // if the module has no dependencies, the above pattern can be simplified to\n (function (root, factory) {\n if (true) {\n // AMD. Register as an anonymous module.\n !(__WEBPACK_AMD_DEFINE_ARRAY__ = [], __WEBPACK_AMD_DEFINE_FACTORY__ = (factory), __WEBPACK_AMD_DEFINE_RESULT__ = (typeof __WEBPACK_AMD_DEFINE_FACTORY__ === 'function' ? (__WEBPACK_AMD_DEFINE_FACTORY__.apply(exports, __WEBPACK_AMD_DEFINE_ARRAY__)) : __WEBPACK_AMD_DEFINE_FACTORY__), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));\n } else if (typeof exports === 'object') {\n // Node. Does not work with strict CommonJS, but\n // only CommonJS-like environments that support module.exports,\n // like Node.\n module.exports = factory();\n } else {\n // Browser globals (root is window)\n root.keycharm = factory();\n }\n }(this, function () {\n\n function keycharm(options) {\n var preventDefault = options && options.preventDefault || false;\n\n var container = options && options.container || window;\n\n var _exportFunctions = {};\n var _bound = {keydown:{}, keyup:{}};\n var _keys = {};\n var i;\n\n // a - z\n for (i = 97; i <= 122; i++) {_keys[String.fromCharCode(i)] = {code:65 + (i - 97), shift: false};}\n // A - Z\n for (i = 65; i <= 90; i++) {_keys[String.fromCharCode(i)] = {code:i, shift: true};}\n // 0 - 9\n for (i = 0; i <= 9; i++) {_keys['' + i] = {code:48 + i, shift: false};}\n // F1 - F12\n for (i = 1; i <= 12; i++) {_keys['F' + i] = {code:111 + i, shift: false};}\n // num0 - num9\n for (i = 0; i <= 9; i++) {_keys['num' + i] = {code:96 + i, shift: false};}\n\n // numpad misc\n _keys['num*'] = {code:106, shift: false};\n _keys['num+'] = {code:107, shift: false};\n _keys['num-'] = {code:109, shift: false};\n _keys['num/'] = {code:111, shift: false};\n _keys['num.'] = {code:110, shift: false};\n // arrows\n _keys['left'] = {code:37, shift: false};\n _keys['up'] = {code:38, shift: false};\n _keys['right'] = {code:39, shift: false};\n _keys['down'] = {code:40, shift: false};\n // extra keys\n _keys['space'] = {code:32, shift: false};\n _keys['enter'] = {code:13, shift: false};\n _keys['shift'] = {code:16, shift: undefined};\n _keys['esc'] = {code:27, shift: false};\n _keys['backspace'] = {code:8, shift: false};\n _keys['tab'] = {code:9, shift: false};\n _keys['ctrl'] = {code:17, shift: false};\n _keys['alt'] = {code:18, shift: false};\n _keys['delete'] = {code:46, shift: false};\n _keys['pageup'] = {code:33, shift: false};\n _keys['pagedown'] = {code:34, shift: false};\n // symbols\n _keys['='] = {code:187, shift: false};\n _keys['-'] = {code:189, shift: false};\n _keys[']'] = {code:221, shift: false};\n _keys['['] = {code:219, shift: false};\n\n\n\n var down = function(event) {handleEvent(event,'keydown');};\n var up = function(event) {handleEvent(event,'keyup');};\n\n // handle the actualy bound key with the event\n var handleEvent = function(event,type) {\n if (_bound[type][event.keyCode] !== undefined) {\n var bound = _bound[type][event.keyCode];\n for (var i = 0; i < bound.length; i++) {\n if (bound[i].shift === undefined) {\n bound[i].fn(event);\n }\n else if (bound[i].shift == true && event.shiftKey == true) {\n bound[i].fn(event);\n }\n else if (bound[i].shift == false && event.shiftKey == false) {\n bound[i].fn(event);\n }\n }\n\n if (preventDefault == true) {\n event.preventDefault();\n }\n }\n };\n\n // bind a key to a callback\n _exportFunctions.bind = function(key, callback, type) {\n if (type === undefined) {\n type = 'keydown';\n }\n if (_keys[key] === undefined) {\n throw new Error(\"unsupported key: \" + key);\n }\n if (_bound[type][_keys[key].code] === undefined) {\n _bound[type][_keys[key].code] = [];\n }\n _bound[type][_keys[key].code].push({fn:callback, shift:_keys[key].shift});\n };\n\n\n // bind all keys to a call back (demo purposes)\n _exportFunctions.bindAll = function(callback, type) {\n if (type === undefined) {\n type = 'keydown';\n }\n for (var key in _keys) {\n if (_keys.hasOwnProperty(key)) {\n _exportFunctions.bind(key,callback,type);\n }\n }\n };\n\n // get the key label from an event\n _exportFunctions.getKey = function(event) {\n for (var key in _keys) {\n if (_keys.hasOwnProperty(key)) {\n if (event.shiftKey == true && _keys[key].shift == true && event.keyCode == _keys[key].code) {\n return key;\n }\n else if (event.shiftKey == false && _keys[key].shift == false && event.keyCode == _keys[key].code) {\n return key;\n }\n else if (event.keyCode == _keys[key].code && key == 'shift') {\n return key;\n }\n }\n }\n return \"unknown key, currently not supported\";\n };\n\n // unbind either a specific callback from a key or all of them (by leaving callback undefined)\n _exportFunctions.unbind = function(key, callback, type) {\n if (type === undefined) {\n type = 'keydown';\n }\n if (_keys[key] === undefined) {\n throw new Error(\"unsupported key: \" + key);\n }\n if (callback !== undefined) {\n var newBindings = [];\n var bound = _bound[type][_keys[key].code];\n if (bound !== undefined) {\n for (var i = 0; i < bound.length; i++) {\n if (!(bound[i].fn == callback && bound[i].shift == _keys[key].shift)) {\n newBindings.push(_bound[type][_keys[key].code][i]);\n }\n }\n }\n _bound[type][_keys[key].code] = newBindings;\n }\n else {\n _bound[type][_keys[key].code] = [];\n }\n };\n\n // reset all bound variables.\n _exportFunctions.reset = function() {\n _bound = {keydown:{}, keyup:{}};\n };\n\n // unbind all listeners and reset all variables.\n _exportFunctions.destroy = function() {\n _bound = {keydown:{}, keyup:{}};\n container.removeEventListener('keydown', down, true);\n container.removeEventListener('keyup', up, true);\n };\n\n // create listeners.\n container.addEventListener('keydown',down,true);\n container.addEventListener('keyup',up,true);\n\n // return the public functions.\n return _exportFunctions;\n }\n\n return keycharm;\n }));\n\n\n\n\n/***/ },\n/* 41 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Hammer = __webpack_require__(20);\n var util = __webpack_require__(1);\n var Component = __webpack_require__(25);\n var moment = __webpack_require__(2);\n var locales = __webpack_require__(42);\n\n /**\n * A custom time bar\n * @param {{range: Range, dom: Object}} body\n * @param {Object} [options] Available parameters:\n * {number | string} id\n * {string} locales\n * {string} locale\n * @constructor CustomTime\n * @extends Component\n */\n\n function CustomTime(body, options) {\n this.body = body;\n\n // default options\n this.defaultOptions = {\n moment: moment,\n locales: locales,\n locale: 'en',\n id: undefined,\n title: undefined\n };\n this.options = util.extend({}, this.defaultOptions);\n\n if (options && options.time) {\n this.customTime = options.time;\n } else {\n this.customTime = new Date();\n }\n\n this.eventParams = {}; // stores state parameters while dragging the bar\n\n this.setOptions(options);\n\n // create the DOM\n this._create();\n }\n\n CustomTime.prototype = new Component();\n\n /**\n * Set options for the component. Options will be merged in current options.\n * @param {Object} options Available parameters:\n * {number | string} id\n * {string} locales\n * {string} locale\n */\n CustomTime.prototype.setOptions = function (options) {\n if (options) {\n // copy all options that we know\n util.selectiveExtend(['moment', 'locale', 'locales', 'id'], this.options, options);\n }\n };\n\n /**\n * Create the DOM for the custom time\n * @private\n */\n CustomTime.prototype._create = function () {\n var bar = document.createElement('div');\n bar['custom-time'] = this;\n bar.className = 'vis-custom-time ' + (this.options.id || '');\n bar.style.position = 'absolute';\n bar.style.top = '0px';\n bar.style.height = '100%';\n this.bar = bar;\n\n var drag = document.createElement('div');\n drag.style.position = 'relative';\n drag.style.top = '0px';\n drag.style.left = '-10px';\n drag.style.height = '100%';\n drag.style.width = '20px';\n bar.appendChild(drag);\n\n // attach event listeners\n this.hammer = new Hammer(drag);\n this.hammer.on('panstart', this._onDragStart.bind(this));\n this.hammer.on('panmove', this._onDrag.bind(this));\n this.hammer.on('panend', this._onDragEnd.bind(this));\n this.hammer.get('pan').set({ threshold: 5, direction: 30 }); // 30 is ALL_DIRECTIONS in hammer.\n };\n\n /**\n * Destroy the CustomTime bar\n */\n CustomTime.prototype.destroy = function () {\n this.hide();\n\n this.hammer.destroy();\n this.hammer = null;\n\n this.body = null;\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n CustomTime.prototype.redraw = function () {\n var parent = this.body.dom.backgroundVertical;\n if (this.bar.parentNode != parent) {\n // attach to the dom\n if (this.bar.parentNode) {\n this.bar.parentNode.removeChild(this.bar);\n }\n parent.appendChild(this.bar);\n }\n\n var x = this.body.util.toScreen(this.customTime);\n\n var locale = this.options.locales[this.options.locale];\n if (!locale) {\n if (!this.warned) {\n console.log('WARNING: options.locales[\\'' + this.options.locale + '\\'] not found. See http://visjs.org/docs/timeline.html#Localization');\n this.warned = true;\n }\n locale = this.options.locales['en']; // fall back on english when not available\n }\n\n var title = this.options.title;\n // To hide the title completely use empty string ''.\n if (title === undefined) {\n title = locale.time + ': ' + this.options.moment(this.customTime).format('dddd, MMMM Do YYYY, H:mm:ss');\n title = title.charAt(0).toUpperCase() + title.substring(1);\n }\n\n this.bar.style.left = x + 'px';\n this.bar.title = title;\n\n return false;\n };\n\n /**\n * Remove the CustomTime from the DOM\n */\n CustomTime.prototype.hide = function () {\n // remove the line from the DOM\n if (this.bar.parentNode) {\n this.bar.parentNode.removeChild(this.bar);\n }\n };\n\n /**\n * Set custom time.\n * @param {Date | number | string} time\n */\n CustomTime.prototype.setCustomTime = function (time) {\n this.customTime = util.convert(time, 'Date');\n this.redraw();\n };\n\n /**\n * Retrieve the current custom time.\n * @return {Date} customTime\n */\n CustomTime.prototype.getCustomTime = function () {\n return new Date(this.customTime.valueOf());\n };\n\n /**\n * Set custom title.\n * @param {Date | number | string} title\n */\n CustomTime.prototype.setCustomTitle = function (title) {\n this.options.title = title;\n };\n\n /**\n * Start moving horizontally\n * @param {Event} event\n * @private\n */\n CustomTime.prototype._onDragStart = function (event) {\n this.eventParams.dragging = true;\n this.eventParams.customTime = this.customTime;\n\n event.stopPropagation();\n };\n\n /**\n * Perform moving operating.\n * @param {Event} event\n * @private\n */\n CustomTime.prototype._onDrag = function (event) {\n if (!this.eventParams.dragging) return;\n\n var x = this.body.util.toScreen(this.eventParams.customTime) + event.deltaX;\n var time = this.body.util.toTime(x);\n\n this.setCustomTime(time);\n\n // fire a timechange event\n this.body.emitter.emit('timechange', {\n id: this.options.id,\n time: new Date(this.customTime.valueOf())\n });\n\n event.stopPropagation();\n };\n\n /**\n * Stop moving operating.\n * @param {Event} event\n * @private\n */\n CustomTime.prototype._onDragEnd = function (event) {\n if (!this.eventParams.dragging) return;\n\n // fire a timechanged event\n this.body.emitter.emit('timechanged', {\n id: this.options.id,\n time: new Date(this.customTime.valueOf())\n });\n\n event.stopPropagation();\n };\n\n /**\n * Find a custom time from an event target:\n * searches for the attribute 'custom-time' in the event target's element tree\n * @param {Event} event\n * @return {CustomTime | null} customTime\n */\n CustomTime.customTimeFromTarget = function (event) {\n var target = event.target;\n while (target) {\n if (target.hasOwnProperty('custom-time')) {\n return target['custom-time'];\n }\n target = target.parentNode;\n }\n\n return null;\n };\n\n module.exports = CustomTime;\n\n/***/ },\n/* 42 */\n/***/ function(module, exports) {\n\n // English\n 'use strict';\n\n exports['en'] = {\n current: 'current',\n time: 'time'\n };\n exports['en_EN'] = exports['en'];\n exports['en_US'] = exports['en'];\n\n // Dutch\n exports['nl'] = {\n current: 'huidige',\n time: 'tijd'\n };\n exports['nl_NL'] = exports['nl'];\n exports['nl_BE'] = exports['nl'];\n\n/***/ },\n/* 43 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var Component = __webpack_require__(25);\n var moment = __webpack_require__(2);\n var locales = __webpack_require__(42);\n\n /**\n * A current time bar\n * @param {{range: Range, dom: Object, domProps: Object}} body\n * @param {Object} [options] Available parameters:\n * {Boolean} [showCurrentTime]\n * @constructor CurrentTime\n * @extends Component\n */\n function CurrentTime(body, options) {\n this.body = body;\n\n // default options\n this.defaultOptions = {\n showCurrentTime: true,\n\n moment: moment,\n locales: locales,\n locale: 'en'\n };\n this.options = util.extend({}, this.defaultOptions);\n this.offset = 0;\n\n this._create();\n\n this.setOptions(options);\n }\n\n CurrentTime.prototype = new Component();\n\n /**\n * Create the HTML DOM for the current time bar\n * @private\n */\n CurrentTime.prototype._create = function () {\n var bar = document.createElement('div');\n bar.className = 'vis-current-time';\n bar.style.position = 'absolute';\n bar.style.top = '0px';\n bar.style.height = '100%';\n\n this.bar = bar;\n };\n\n /**\n * Destroy the CurrentTime bar\n */\n CurrentTime.prototype.destroy = function () {\n this.options.showCurrentTime = false;\n this.redraw(); // will remove the bar from the DOM and stop refreshing\n\n this.body = null;\n };\n\n /**\n * Set options for the component. Options will be merged in current options.\n * @param {Object} options Available parameters:\n * {boolean} [showCurrentTime]\n */\n CurrentTime.prototype.setOptions = function (options) {\n if (options) {\n // copy all options that we know\n util.selectiveExtend(['showCurrentTime', 'moment', 'locale', 'locales'], this.options, options);\n }\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n CurrentTime.prototype.redraw = function () {\n if (this.options.showCurrentTime) {\n var parent = this.body.dom.backgroundVertical;\n if (this.bar.parentNode != parent) {\n // attach to the dom\n if (this.bar.parentNode) {\n this.bar.parentNode.removeChild(this.bar);\n }\n parent.appendChild(this.bar);\n\n this.start();\n }\n\n var now = this.options.moment(new Date().valueOf() + this.offset);\n var x = this.body.util.toScreen(now);\n\n var locale = this.options.locales[this.options.locale];\n if (!locale) {\n if (!this.warned) {\n console.log('WARNING: options.locales[\\'' + this.options.locale + '\\'] not found. See http://visjs.org/docs/timeline/#Localization');\n this.warned = true;\n }\n locale = this.options.locales['en']; // fall back on english when not available\n }\n var title = locale.current + ' ' + locale.time + ': ' + now.format('dddd, MMMM Do YYYY, H:mm:ss');\n title = title.charAt(0).toUpperCase() + title.substring(1);\n\n this.bar.style.left = x + 'px';\n this.bar.title = title;\n } else {\n // remove the line from the DOM\n if (this.bar.parentNode) {\n this.bar.parentNode.removeChild(this.bar);\n }\n this.stop();\n }\n\n return false;\n };\n\n /**\n * Start auto refreshing the current time bar\n */\n CurrentTime.prototype.start = function () {\n var me = this;\n\n function update() {\n me.stop();\n\n // determine interval to refresh\n var scale = me.body.range.conversion(me.body.domProps.center.width).scale;\n var interval = 1 / scale / 10;\n if (interval < 30) interval = 30;\n if (interval > 1000) interval = 1000;\n\n me.redraw();\n\n // start a renderTimer to adjust for the new time\n me.currentTimeTimer = setTimeout(update, interval);\n }\n\n update();\n };\n\n /**\n * Stop auto refreshing the current time bar\n */\n CurrentTime.prototype.stop = function () {\n if (this.currentTimeTimer !== undefined) {\n clearTimeout(this.currentTimeTimer);\n delete this.currentTimeTimer;\n }\n };\n\n /**\n * Set a current time. This can be used for example to ensure that a client's\n * time is synchronized with a shared server time.\n * @param {Date | String | Number} time A Date, unix timestamp, or\n * ISO date string.\n */\n CurrentTime.prototype.setCurrentTime = function (time) {\n var t = util.convert(time, 'Date').valueOf();\n var now = new Date().valueOf();\n this.offset = t - now;\n this.redraw();\n };\n\n /**\n * Get the current time.\n * @return {Date} Returns the current time.\n */\n CurrentTime.prototype.getCurrentTime = function () {\n return new Date(new Date().valueOf() + this.offset);\n };\n\n module.exports = CurrentTime;\n\n/***/ },\n/* 44 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _ColorPicker = __webpack_require__(45);\n\n var _ColorPicker2 = _interopRequireDefault(_ColorPicker);\n\n /**\n * The way this works is for all properties of this.possible options, you can supply the property name in any form to list the options.\n * Boolean options are recognised as Boolean\n * Number options should be written as array: [default value, min value, max value, stepsize]\n * Colors should be written as array: ['color', '#ffffff']\n * Strings with should be written as array: [option1, option2, option3, ..]\n *\n * The options are matched with their counterparts in each of the modules and the values used in the configuration are\n *\n * @param parentModule | the location where parentModule.setOptions() can be called\n * @param defaultContainer | the default container of the module\n * @param configureOptions | the fully configured and predefined options set found in allOptions.js\n * @param pixelRatio | canvas pixel ratio\n */\n var util = __webpack_require__(1);\n\n var Configurator = (function () {\n function Configurator(parentModule, defaultContainer, configureOptions) {\n var pixelRatio = arguments.length <= 3 || arguments[3] === undefined ? 1 : arguments[3];\n\n _classCallCheck(this, Configurator);\n\n this.parent = parentModule;\n this.changedOptions = [];\n this.container = defaultContainer;\n this.allowCreation = false;\n\n this.options = {};\n this.initialized = false;\n this.popupCounter = 0;\n this.defaultOptions = {\n enabled: false,\n filter: true,\n container: undefined,\n showButton: true\n };\n util.extend(this.options, this.defaultOptions);\n\n this.configureOptions = configureOptions;\n this.moduleOptions = {};\n this.domElements = [];\n this.popupDiv = {};\n this.popupLimit = 5;\n this.popupHistory = {};\n this.colorPicker = new _ColorPicker2['default'](pixelRatio);\n this.wrapper = undefined;\n }\n\n /**\n * refresh all options.\n * Because all modules parse their options by themselves, we just use their options. We copy them here.\n *\n * @param options\n */\n\n _createClass(Configurator, [{\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n // reset the popup history because the indices may have been changed.\n this.popupHistory = {};\n this._removePopup();\n\n var enabled = true;\n if (typeof options === 'string') {\n this.options.filter = options;\n } else if (options instanceof Array) {\n this.options.filter = options.join();\n } else if (typeof options === 'object') {\n if (options.container !== undefined) {\n this.options.container = options.container;\n }\n if (options.filter !== undefined) {\n this.options.filter = options.filter;\n }\n if (options.showButton !== undefined) {\n this.options.showButton = options.showButton;\n }\n if (options.enabled !== undefined) {\n enabled = options.enabled;\n }\n } else if (typeof options === 'boolean') {\n this.options.filter = true;\n enabled = options;\n } else if (typeof options === 'function') {\n this.options.filter = options;\n enabled = true;\n }\n if (this.options.filter === false) {\n enabled = false;\n }\n\n this.options.enabled = enabled;\n }\n this._clean();\n }\n }, {\n key: 'setModuleOptions',\n value: function setModuleOptions(moduleOptions) {\n this.moduleOptions = moduleOptions;\n if (this.options.enabled === true) {\n this._clean();\n if (this.options.container !== undefined) {\n this.container = this.options.container;\n }\n this._create();\n }\n }\n\n /**\n * Create all DOM elements\n * @private\n */\n }, {\n key: '_create',\n value: function _create() {\n var _this = this;\n\n this._clean();\n this.changedOptions = [];\n\n var filter = this.options.filter;\n var counter = 0;\n var show = false;\n for (var option in this.configureOptions) {\n if (this.configureOptions.hasOwnProperty(option)) {\n this.allowCreation = false;\n show = false;\n if (typeof filter === 'function') {\n show = filter(option, []);\n show = show || this._handleObject(this.configureOptions[option], [option], true);\n } else if (filter === true || filter.indexOf(option) !== -1) {\n show = true;\n }\n\n if (show !== false) {\n this.allowCreation = true;\n\n // linebreak between categories\n if (counter > 0) {\n this._makeItem([]);\n }\n // a header for the category\n this._makeHeader(option);\n\n // get the sub options\n this._handleObject(this.configureOptions[option], [option]);\n }\n counter++;\n }\n }\n\n if (this.options.showButton === true) {\n (function () {\n var generateButton = document.createElement('div');\n generateButton.className = 'vis-configuration vis-config-button';\n generateButton.innerHTML = 'generate options';\n generateButton.onclick = function () {\n _this._printOptions();\n };\n generateButton.onmouseover = function () {\n generateButton.className = 'vis-configuration vis-config-button hover';\n };\n generateButton.onmouseout = function () {\n generateButton.className = 'vis-configuration vis-config-button';\n };\n\n _this.optionsContainer = document.createElement('div');\n _this.optionsContainer.className = 'vis-configuration vis-config-option-container';\n\n _this.domElements.push(_this.optionsContainer);\n _this.domElements.push(generateButton);\n })();\n }\n\n this._push();\n //~ this.colorPicker.insertTo(this.container);\n }\n\n /**\n * draw all DOM elements on the screen\n * @private\n */\n }, {\n key: '_push',\n value: function _push() {\n this.wrapper = document.createElement('div');\n this.wrapper.className = 'vis-configuration-wrapper';\n this.container.appendChild(this.wrapper);\n for (var i = 0; i < this.domElements.length; i++) {\n this.wrapper.appendChild(this.domElements[i]);\n }\n\n this._showPopupIfNeeded();\n }\n\n /**\n * delete all DOM elements\n * @private\n */\n }, {\n key: '_clean',\n value: function _clean() {\n for (var i = 0; i < this.domElements.length; i++) {\n this.wrapper.removeChild(this.domElements[i]);\n }\n\n if (this.wrapper !== undefined) {\n this.container.removeChild(this.wrapper);\n this.wrapper = undefined;\n }\n this.domElements = [];\n\n this._removePopup();\n }\n\n /**\n * get the value from the actualOptions if it exists\n * @param {array} path | where to look for the actual option\n * @returns {*}\n * @private\n */\n }, {\n key: '_getValue',\n value: function _getValue(path) {\n var base = this.moduleOptions;\n for (var i = 0; i < path.length; i++) {\n if (base[path[i]] !== undefined) {\n base = base[path[i]];\n } else {\n base = undefined;\n break;\n }\n }\n return base;\n }\n\n /**\n * all option elements are wrapped in an item\n * @param path\n * @param domElements\n * @private\n */\n }, {\n key: '_makeItem',\n value: function _makeItem(path) {\n var _arguments = arguments,\n _this2 = this;\n\n if (this.allowCreation === true) {\n var _len, domElements, _key;\n\n var _ret2 = (function () {\n var item = document.createElement('div');\n item.className = 'vis-configuration vis-config-item vis-config-s' + path.length;\n\n for (_len = _arguments.length, domElements = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) {\n domElements[_key - 1] = _arguments[_key];\n }\n\n domElements.forEach(function (element) {\n item.appendChild(element);\n });\n _this2.domElements.push(item);\n return {\n v: _this2.domElements.length\n };\n })();\n\n if (typeof _ret2 === 'object') return _ret2.v;\n }\n return 0;\n }\n\n /**\n * header for major subjects\n * @param name\n * @private\n */\n }, {\n key: '_makeHeader',\n value: function _makeHeader(name) {\n var div = document.createElement('div');\n div.className = 'vis-configuration vis-config-header';\n div.innerHTML = name;\n this._makeItem([], div);\n }\n\n /**\n * make a label, if it is an object label, it gets different styling.\n * @param name\n * @param path\n * @param objectLabel\n * @returns {HTMLElement}\n * @private\n */\n }, {\n key: '_makeLabel',\n value: function _makeLabel(name, path) {\n var objectLabel = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n var div = document.createElement('div');\n div.className = 'vis-configuration vis-config-label vis-config-s' + path.length;\n if (objectLabel === true) {\n div.innerHTML = '<i><b>' + name + ':</b></i>';\n } else {\n div.innerHTML = name + ':';\n }\n return div;\n }\n\n /**\n * make a dropdown list for multiple possible string optoins\n * @param arr\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_makeDropdown',\n value: function _makeDropdown(arr, value, path) {\n var select = document.createElement('select');\n select.className = 'vis-configuration vis-config-select';\n var selectedValue = 0;\n if (value !== undefined) {\n if (arr.indexOf(value) !== -1) {\n selectedValue = arr.indexOf(value);\n }\n }\n\n for (var i = 0; i < arr.length; i++) {\n var option = document.createElement('option');\n option.value = arr[i];\n if (i === selectedValue) {\n option.selected = 'selected';\n }\n option.innerHTML = arr[i];\n select.appendChild(option);\n }\n\n var me = this;\n select.onchange = function () {\n me._update(this.value, path);\n };\n\n var label = this._makeLabel(path[path.length - 1], path);\n this._makeItem(path, label, select);\n }\n\n /**\n * make a range object for numeric options\n * @param arr\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_makeRange',\n value: function _makeRange(arr, value, path) {\n var defaultValue = arr[0];\n var min = arr[1];\n var max = arr[2];\n var step = arr[3];\n var range = document.createElement('input');\n range.className = 'vis-configuration vis-config-range';\n try {\n range.type = 'range'; // not supported on IE9\n range.min = min;\n range.max = max;\n } catch (err) {}\n range.step = step;\n\n // set up the popup settings in case they are needed.\n var popupString = '';\n var popupValue = 0;\n\n if (value !== undefined) {\n var factor = 1.20;\n if (value < 0 && value * factor < min) {\n range.min = Math.ceil(value * factor);\n popupValue = range.min;\n popupString = 'range increased';\n } else if (value / factor < min) {\n range.min = Math.ceil(value / factor);\n popupValue = range.min;\n popupString = 'range increased';\n }\n if (value * factor > max && max !== 1) {\n range.max = Math.ceil(value * factor);\n popupValue = range.max;\n popupString = 'range increased';\n }\n range.value = value;\n } else {\n range.value = defaultValue;\n }\n\n var input = document.createElement('input');\n input.className = 'vis-configuration vis-config-rangeinput';\n input.value = range.value;\n\n var me = this;\n range.onchange = function () {\n input.value = this.value;me._update(Number(this.value), path);\n };\n range.oninput = function () {\n input.value = this.value;\n };\n\n var label = this._makeLabel(path[path.length - 1], path);\n var itemIndex = this._makeItem(path, label, range, input);\n\n // if a popup is needed AND it has not been shown for this value, show it.\n if (popupString !== '' && this.popupHistory[itemIndex] !== popupValue) {\n this.popupHistory[itemIndex] = popupValue;\n this._setupPopup(popupString, itemIndex);\n }\n }\n\n /**\n * prepare the popup\n * @param string\n * @param index\n * @private\n */\n }, {\n key: '_setupPopup',\n value: function _setupPopup(string, index) {\n var _this3 = this;\n\n if (this.initialized === true && this.allowCreation === true && this.popupCounter < this.popupLimit) {\n var div = document.createElement(\"div\");\n div.id = \"vis-configuration-popup\";\n div.className = \"vis-configuration-popup\";\n div.innerHTML = string;\n div.onclick = function () {\n _this3._removePopup();\n };\n this.popupCounter += 1;\n this.popupDiv = { html: div, index: index };\n }\n }\n\n /**\n * remove the popup from the dom\n * @private\n */\n }, {\n key: '_removePopup',\n value: function _removePopup() {\n if (this.popupDiv.html !== undefined) {\n this.popupDiv.html.parentNode.removeChild(this.popupDiv.html);\n clearTimeout(this.popupDiv.hideTimeout);\n clearTimeout(this.popupDiv.deleteTimeout);\n this.popupDiv = {};\n }\n }\n\n /**\n * Show the popup if it is needed.\n * @private\n */\n }, {\n key: '_showPopupIfNeeded',\n value: function _showPopupIfNeeded() {\n var _this4 = this;\n\n if (this.popupDiv.html !== undefined) {\n var correspondingElement = this.domElements[this.popupDiv.index];\n var rect = correspondingElement.getBoundingClientRect();\n this.popupDiv.html.style.left = rect.left + \"px\";\n this.popupDiv.html.style.top = rect.top - 30 + \"px\"; // 30 is the height;\n document.body.appendChild(this.popupDiv.html);\n this.popupDiv.hideTimeout = setTimeout(function () {\n _this4.popupDiv.html.style.opacity = 0;\n }, 1500);\n this.popupDiv.deleteTimeout = setTimeout(function () {\n _this4._removePopup();\n }, 1800);\n }\n }\n\n /**\n * make a checkbox for boolean options.\n * @param defaultValue\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_makeCheckbox',\n value: function _makeCheckbox(defaultValue, value, path) {\n var checkbox = document.createElement('input');\n checkbox.type = 'checkbox';\n checkbox.className = 'vis-configuration vis-config-checkbox';\n checkbox.checked = defaultValue;\n if (value !== undefined) {\n checkbox.checked = value;\n if (value !== defaultValue) {\n if (typeof defaultValue === 'object') {\n if (value !== defaultValue.enabled) {\n this.changedOptions.push({ path: path, value: value });\n }\n } else {\n this.changedOptions.push({ path: path, value: value });\n }\n }\n }\n\n var me = this;\n checkbox.onchange = function () {\n me._update(this.checked, path);\n };\n\n var label = this._makeLabel(path[path.length - 1], path);\n this._makeItem(path, label, checkbox);\n }\n\n /**\n * make a text input field for string options.\n * @param defaultValue\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_makeTextInput',\n value: function _makeTextInput(defaultValue, value, path) {\n var checkbox = document.createElement('input');\n checkbox.type = 'text';\n checkbox.className = 'vis-configuration vis-config-text';\n checkbox.value = value;\n if (value !== defaultValue) {\n this.changedOptions.push({ path: path, value: value });\n }\n\n var me = this;\n checkbox.onchange = function () {\n me._update(this.value, path);\n };\n\n var label = this._makeLabel(path[path.length - 1], path);\n this._makeItem(path, label, checkbox);\n }\n\n /**\n * make a color field with a color picker for color fields\n * @param arr\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_makeColorField',\n value: function _makeColorField(arr, value, path) {\n var _this5 = this;\n\n var defaultColor = arr[1];\n var div = document.createElement('div');\n value = value === undefined ? defaultColor : value;\n\n if (value !== 'none') {\n div.className = 'vis-configuration vis-config-colorBlock';\n div.style.backgroundColor = value;\n } else {\n div.className = 'vis-configuration vis-config-colorBlock none';\n }\n\n value = value === undefined ? defaultColor : value;\n div.onclick = function () {\n _this5._showColorPicker(value, div, path);\n };\n\n var label = this._makeLabel(path[path.length - 1], path);\n this._makeItem(path, label, div);\n }\n\n /**\n * used by the color buttons to call the color picker.\n * @param event\n * @param value\n * @param div\n * @param path\n * @private\n */\n }, {\n key: '_showColorPicker',\n value: function _showColorPicker(value, div, path) {\n var _this6 = this;\n\n // clear the callback from this div\n div.onclick = function () {};\n\n this.colorPicker.insertTo(div);\n this.colorPicker.show();\n\n this.colorPicker.setColor(value);\n this.colorPicker.setUpdateCallback(function (color) {\n var colorString = 'rgba(' + color.r + ',' + color.g + ',' + color.b + ',' + color.a + ')';\n div.style.backgroundColor = colorString;\n _this6._update(colorString, path);\n });\n\n // on close of the colorpicker, restore the callback.\n this.colorPicker.setCloseCallback(function () {\n div.onclick = function () {\n _this6._showColorPicker(value, div, path);\n };\n });\n }\n\n /**\n * parse an object and draw the correct items\n * @param obj\n * @param path\n * @private\n */\n }, {\n key: '_handleObject',\n value: function _handleObject(obj) {\n var path = arguments.length <= 1 || arguments[1] === undefined ? [] : arguments[1];\n var checkOnly = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n var show = false;\n var filter = this.options.filter;\n var visibleInSet = false;\n for (var subObj in obj) {\n if (obj.hasOwnProperty(subObj)) {\n show = true;\n var item = obj[subObj];\n var newPath = util.copyAndExtendArray(path, subObj);\n if (typeof filter === 'function') {\n show = filter(subObj, path);\n\n // if needed we must go deeper into the object.\n if (show === false) {\n if (!(item instanceof Array) && typeof item !== 'string' && typeof item !== 'boolean' && item instanceof Object) {\n this.allowCreation = false;\n show = this._handleObject(item, newPath, true);\n this.allowCreation = checkOnly === false;\n }\n }\n }\n\n if (show !== false) {\n visibleInSet = true;\n var value = this._getValue(newPath);\n\n if (item instanceof Array) {\n this._handleArray(item, value, newPath);\n } else if (typeof item === 'string') {\n this._makeTextInput(item, value, newPath);\n } else if (typeof item === 'boolean') {\n this._makeCheckbox(item, value, newPath);\n } else if (item instanceof Object) {\n // collapse the physics options that are not enabled\n var draw = true;\n if (path.indexOf('physics') !== -1) {\n if (this.moduleOptions.physics.solver !== subObj) {\n draw = false;\n }\n }\n\n if (draw === true) {\n // initially collapse options with an disabled enabled option.\n if (item.enabled !== undefined) {\n var enabledPath = util.copyAndExtendArray(newPath, 'enabled');\n var enabledValue = this._getValue(enabledPath);\n if (enabledValue === true) {\n var label = this._makeLabel(subObj, newPath, true);\n this._makeItem(newPath, label);\n visibleInSet = this._handleObject(item, newPath) || visibleInSet;\n } else {\n this._makeCheckbox(item, enabledValue, newPath);\n }\n } else {\n var label = this._makeLabel(subObj, newPath, true);\n this._makeItem(newPath, label);\n visibleInSet = this._handleObject(item, newPath) || visibleInSet;\n }\n }\n } else {\n console.error('dont know how to handle', item, subObj, newPath);\n }\n }\n }\n }\n return visibleInSet;\n }\n\n /**\n * handle the array type of option\n * @param optionName\n * @param arr\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_handleArray',\n value: function _handleArray(arr, value, path) {\n if (typeof arr[0] === 'string' && arr[0] === 'color') {\n this._makeColorField(arr, value, path);\n if (arr[1] !== value) {\n this.changedOptions.push({ path: path, value: value });\n }\n } else if (typeof arr[0] === 'string') {\n this._makeDropdown(arr, value, path);\n if (arr[0] !== value) {\n this.changedOptions.push({ path: path, value: value });\n }\n } else if (typeof arr[0] === 'number') {\n this._makeRange(arr, value, path);\n if (arr[0] !== value) {\n this.changedOptions.push({ path: path, value: Number(value) });\n }\n }\n }\n\n /**\n * called to update the network with the new settings.\n * @param value\n * @param path\n * @private\n */\n }, {\n key: '_update',\n value: function _update(value, path) {\n var options = this._constructOptions(value, path);\n\n if (this.parent.body && this.parent.body.emitter && this.parent.body.emitter.emit) {\n this.parent.body.emitter.emit(\"configChange\", options);\n }\n this.initialized = true;\n this.parent.setOptions(options);\n }\n }, {\n key: '_constructOptions',\n value: function _constructOptions(value, path) {\n var optionsObj = arguments.length <= 2 || arguments[2] === undefined ? {} : arguments[2];\n\n var pointer = optionsObj;\n\n // when dropdown boxes can be string or boolean, we typecast it into correct types\n value = value === 'true' ? true : value;\n value = value === 'false' ? false : value;\n\n for (var i = 0; i < path.length; i++) {\n if (path[i] !== 'global') {\n if (pointer[path[i]] === undefined) {\n pointer[path[i]] = {};\n }\n if (i !== path.length - 1) {\n pointer = pointer[path[i]];\n } else {\n pointer[path[i]] = value;\n }\n }\n }\n return optionsObj;\n }\n }, {\n key: '_printOptions',\n value: function _printOptions() {\n var options = this.getOptions();\n this.optionsContainer.innerHTML = '<pre>var options = ' + JSON.stringify(options, null, 2) + '</pre>';\n }\n }, {\n key: 'getOptions',\n value: function getOptions() {\n var options = {};\n for (var i = 0; i < this.changedOptions.length; i++) {\n this._constructOptions(this.changedOptions[i].value, this.changedOptions[i].path, options);\n }\n return options;\n }\n }]);\n\n return Configurator;\n })();\n\n exports['default'] = Configurator;\n module.exports = exports['default'];\n\n/***/ },\n/* 45 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var Hammer = __webpack_require__(20);\n var hammerUtil = __webpack_require__(24);\n var util = __webpack_require__(1);\n\n var ColorPicker = (function () {\n function ColorPicker() {\n var pixelRatio = arguments.length <= 0 || arguments[0] === undefined ? 1 : arguments[0];\n\n _classCallCheck(this, ColorPicker);\n\n this.pixelRatio = pixelRatio;\n this.generated = false;\n this.centerCoordinates = { x: 289 / 2, y: 289 / 2 };\n this.r = 289 * 0.49;\n this.color = { r: 255, g: 255, b: 255, a: 1.0 };\n this.hueCircle = undefined;\n this.initialColor = { r: 255, g: 255, b: 255, a: 1.0 };\n this.previousColor = undefined;\n this.applied = false;\n\n // bound by\n this.updateCallback = function () {};\n this.closeCallback = function () {};\n\n // create all DOM elements\n this._create();\n }\n\n /**\n * this inserts the colorPicker into a div from the DOM\n * @param container\n */\n\n _createClass(ColorPicker, [{\n key: 'insertTo',\n value: function insertTo(container) {\n if (this.hammer !== undefined) {\n this.hammer.destroy();\n this.hammer = undefined;\n }\n this.container = container;\n this.container.appendChild(this.frame);\n this._bindHammer();\n\n this._setSize();\n }\n\n /**\n * the callback is executed on apply and save. Bind it to the application\n * @param callback\n */\n }, {\n key: 'setUpdateCallback',\n value: function setUpdateCallback(callback) {\n if (typeof callback === 'function') {\n this.updateCallback = callback;\n } else {\n throw new Error(\"Function attempted to set as colorPicker update callback is not a function.\");\n }\n }\n\n /**\n * the callback is executed on apply and save. Bind it to the application\n * @param callback\n */\n }, {\n key: 'setCloseCallback',\n value: function setCloseCallback(callback) {\n if (typeof callback === 'function') {\n this.closeCallback = callback;\n } else {\n throw new Error(\"Function attempted to set as colorPicker closing callback is not a function.\");\n }\n }\n }, {\n key: '_isColorString',\n value: function _isColorString(color) {\n var htmlColors = { black: '#000000', navy: '#000080', darkblue: '#00008B', mediumblue: '#0000CD', blue: '#0000FF', darkgreen: '#006400', green: '#008000', teal: '#008080', darkcyan: '#008B8B', deepskyblue: '#00BFFF', darkturquoise: '#00CED1', mediumspringgreen: '#00FA9A', lime: '#00FF00', springgreen: '#00FF7F', aqua: '#00FFFF', cyan: '#00FFFF', midnightblue: '#191970', dodgerblue: '#1E90FF', lightseagreen: '#20B2AA', forestgreen: '#228B22', seagreen: '#2E8B57', darkslategray: '#2F4F4F', limegreen: '#32CD32', mediumseagreen: '#3CB371', turquoise: '#40E0D0', royalblue: '#4169E1', steelblue: '#4682B4', darkslateblue: '#483D8B', mediumturquoise: '#48D1CC', indigo: '#4B0082', darkolivegreen: '#556B2F', cadetblue: '#5F9EA0', cornflowerblue: '#6495ED', mediumaquamarine: '#66CDAA', dimgray: '#696969', slateblue: '#6A5ACD', olivedrab: '#6B8E23', slategray: '#708090', lightslategray: '#778899', mediumslateblue: '#7B68EE', lawngreen: '#7CFC00', chartreuse: '#7FFF00', aquamarine: '#7FFFD4', maroon: '#800000', purple: '#800080', olive: '#808000', gray: '#808080', skyblue: '#87CEEB', lightskyblue: '#87CEFA', blueviolet: '#8A2BE2', darkred: '#8B0000', darkmagenta: '#8B008B', saddlebrown: '#8B4513', darkseagreen: '#8FBC8F', lightgreen: '#90EE90', mediumpurple: '#9370D8', darkviolet: '#9400D3', palegreen: '#98FB98', darkorchid: '#9932CC', yellowgreen: '#9ACD32', sienna: '#A0522D', brown: '#A52A2A', darkgray: '#A9A9A9', lightblue: '#ADD8E6', greenyellow: '#ADFF2F', paleturquoise: '#AFEEEE', lightsteelblue: '#B0C4DE', powderblue: '#B0E0E6', firebrick: '#B22222', darkgoldenrod: '#B8860B', mediumorchid: '#BA55D3', rosybrown: '#BC8F8F', darkkhaki: '#BDB76B', silver: '#C0C0C0', mediumvioletred: '#C71585', indianred: '#CD5C5C', peru: '#CD853F', chocolate: '#D2691E', tan: '#D2B48C', lightgrey: '#D3D3D3', palevioletred: '#D87093', thistle: '#D8BFD8', orchid: '#DA70D6', goldenrod: '#DAA520', crimson: '#DC143C', gainsboro: '#DCDCDC', plum: '#DDA0DD', burlywood: '#DEB887', lightcyan: '#E0FFFF', lavender: '#E6E6FA', darksalmon: '#E9967A', violet: '#EE82EE', palegoldenrod: '#EEE8AA', lightcoral: '#F08080', khaki: '#F0E68C', aliceblue: '#F0F8FF', honeydew: '#F0FFF0', azure: '#F0FFFF', sandybrown: '#F4A460', wheat: '#F5DEB3', beige: '#F5F5DC', whitesmoke: '#F5F5F5', mintcream: '#F5FFFA', ghostwhite: '#F8F8FF', salmon: '#FA8072', antiquewhite: '#FAEBD7', linen: '#FAF0E6', lightgoldenrodyellow: '#FAFAD2', oldlace: '#FDF5E6', red: '#FF0000', fuchsia: '#FF00FF', magenta: '#FF00FF', deeppink: '#FF1493', orangered: '#FF4500', tomato: '#FF6347', hotpink: '#FF69B4', coral: '#FF7F50', darkorange: '#FF8C00', lightsalmon: '#FFA07A', orange: '#FFA500', lightpink: '#FFB6C1', pink: '#FFC0CB', gold: '#FFD700', peachpuff: '#FFDAB9', navajowhite: '#FFDEAD', moccasin: '#FFE4B5', bisque: '#FFE4C4', mistyrose: '#FFE4E1', blanchedalmond: '#FFEBCD', papayawhip: '#FFEFD5', lavenderblush: '#FFF0F5', seashell: '#FFF5EE', cornsilk: '#FFF8DC', lemonchiffon: '#FFFACD', floralwhite: '#FFFAF0', snow: '#FFFAFA', yellow: '#FFFF00', lightyellow: '#FFFFE0', ivory: '#FFFFF0', white: '#FFFFFF' };\n if (typeof color === 'string') {\n return htmlColors[color];\n }\n }\n\n /**\n * Set the color of the colorPicker\n * Supported formats:\n * 'red' --> HTML color string\n * '#ffffff' --> hex string\n * 'rbg(255,255,255)' --> rgb string\n * 'rgba(255,255,255,1.0)' --> rgba string\n * {r:255,g:255,b:255} --> rgb object\n * {r:255,g:255,b:255,a:1.0} --> rgba object\n * @param color\n * @param setInitial\n */\n }, {\n key: 'setColor',\n value: function setColor(color) {\n var setInitial = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n if (color === 'none') {\n return;\n }\n\n var rgba = undefined;\n\n // if a html color shorthand is used, convert to hex\n var htmlColor = this._isColorString(color);\n if (htmlColor !== undefined) {\n color = htmlColor;\n }\n\n // check format\n if (util.isString(color) === true) {\n if (util.isValidRGB(color) === true) {\n var rgbaArray = color.substr(4).substr(0, color.length - 5).split(',');\n rgba = { r: rgbaArray[0], g: rgbaArray[1], b: rgbaArray[2], a: 1.0 };\n } else if (util.isValidRGBA(color) === true) {\n var rgbaArray = color.substr(5).substr(0, color.length - 6).split(',');\n rgba = { r: rgbaArray[0], g: rgbaArray[1], b: rgbaArray[2], a: rgbaArray[3] };\n } else if (util.isValidHex(color) === true) {\n var rgbObj = util.hexToRGB(color);\n rgba = { r: rgbObj.r, g: rgbObj.g, b: rgbObj.b, a: 1.0 };\n }\n } else {\n if (color instanceof Object) {\n if (color.r !== undefined && color.g !== undefined && color.b !== undefined) {\n var alpha = color.a !== undefined ? color.a : '1.0';\n rgba = { r: color.r, g: color.g, b: color.b, a: alpha };\n }\n }\n }\n\n // set color\n if (rgba === undefined) {\n throw new Error(\"Unknown color passed to the colorPicker. Supported are strings: rgb, hex, rgba. Object: rgb ({r:r,g:g,b:b,[a:a]}). Supplied: \" + JSON.stringify(color));\n } else {\n this._setColor(rgba, setInitial);\n }\n }\n\n /**\n * this shows the color picker.\n * The hue circle is constructed once and stored.\n */\n }, {\n key: 'show',\n value: function show() {\n if (this.closeCallback !== undefined) {\n this.closeCallback();\n this.closeCallback = undefined;\n }\n\n this.applied = false;\n this.frame.style.display = 'block';\n this._generateHueCircle();\n }\n\n // ------------------------------------------ PRIVATE ----------------------------- //\n\n /**\n * Hide the picker. Is called by the cancel button.\n * Optional boolean to store the previous color for easy access later on.\n * @param storePrevious\n * @private\n */\n }, {\n key: '_hide',\n value: function _hide() {\n var _this = this;\n\n var storePrevious = arguments.length <= 0 || arguments[0] === undefined ? true : arguments[0];\n\n // store the previous color for next time;\n if (storePrevious === true) {\n this.previousColor = util.extend({}, this.color);\n }\n\n if (this.applied === true) {\n this.updateCallback(this.initialColor);\n }\n\n this.frame.style.display = 'none';\n\n // call the closing callback, restoring the onclick method.\n // this is in a setTimeout because it will trigger the show again before the click is done.\n setTimeout(function () {\n if (_this.closeCallback !== undefined) {\n _this.closeCallback();\n _this.closeCallback = undefined;\n }\n }, 0);\n }\n\n /**\n * bound to the save button. Saves and hides.\n * @private\n */\n }, {\n key: '_save',\n value: function _save() {\n this.updateCallback(this.color);\n this.applied = false;\n this._hide();\n }\n\n /**\n * Bound to apply button. Saves but does not close. Is undone by the cancel button.\n * @private\n */\n }, {\n key: '_apply',\n value: function _apply() {\n this.applied = true;\n this.updateCallback(this.color);\n this._updatePicker(this.color);\n }\n\n /**\n * load the color from the previous session.\n * @private\n */\n }, {\n key: '_loadLast',\n value: function _loadLast() {\n if (this.previousColor !== undefined) {\n this.setColor(this.previousColor, false);\n } else {\n alert(\"There is no last color to load...\");\n }\n }\n\n /**\n * set the color, place the picker\n * @param rgba\n * @param setInitial\n * @private\n */\n }, {\n key: '_setColor',\n value: function _setColor(rgba) {\n var setInitial = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n // store the initial color\n if (setInitial === true) {\n this.initialColor = util.extend({}, rgba);\n }\n\n this.color = rgba;\n var hsv = util.RGBToHSV(rgba.r, rgba.g, rgba.b);\n\n var angleConvert = 2 * Math.PI;\n var radius = this.r * hsv.s;\n var x = this.centerCoordinates.x + radius * Math.sin(angleConvert * hsv.h);\n var y = this.centerCoordinates.y + radius * Math.cos(angleConvert * hsv.h);\n\n this.colorPickerSelector.style.left = x - 0.5 * this.colorPickerSelector.clientWidth + 'px';\n this.colorPickerSelector.style.top = y - 0.5 * this.colorPickerSelector.clientHeight + 'px';\n\n this._updatePicker(rgba);\n }\n\n /**\n * bound to opacity control\n * @param value\n * @private\n */\n }, {\n key: '_setOpacity',\n value: function _setOpacity(value) {\n this.color.a = value / 100;\n this._updatePicker(this.color);\n }\n\n /**\n * bound to brightness control\n * @param value\n * @private\n */\n }, {\n key: '_setBrightness',\n value: function _setBrightness(value) {\n var hsv = util.RGBToHSV(this.color.r, this.color.g, this.color.b);\n hsv.v = value / 100;\n var rgba = util.HSVToRGB(hsv.h, hsv.s, hsv.v);\n rgba['a'] = this.color.a;\n this.color = rgba;\n this._updatePicker();\n }\n\n /**\n * update the color picker. A black circle overlays the hue circle to mimic the brightness decreasing.\n * @param rgba\n * @private\n */\n }, {\n key: '_updatePicker',\n value: function _updatePicker() {\n var rgba = arguments.length <= 0 || arguments[0] === undefined ? this.color : arguments[0];\n\n var hsv = util.RGBToHSV(rgba.r, rgba.g, rgba.b);\n var ctx = this.colorPickerCanvas.getContext('2d');\n if (this.pixelRation === undefined) {\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n }\n ctx.setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n\n // clear the canvas\n var w = this.colorPickerCanvas.clientWidth;\n var h = this.colorPickerCanvas.clientHeight;\n ctx.clearRect(0, 0, w, h);\n\n ctx.putImageData(this.hueCircle, 0, 0);\n ctx.fillStyle = 'rgba(0,0,0,' + (1 - hsv.v) + ')';\n ctx.circle(this.centerCoordinates.x, this.centerCoordinates.y, this.r);\n ctx.fill();\n\n this.brightnessRange.value = 100 * hsv.v;\n this.opacityRange.value = 100 * rgba.a;\n\n this.initialColorDiv.style.backgroundColor = 'rgba(' + this.initialColor.r + ',' + this.initialColor.g + ',' + this.initialColor.b + ',' + this.initialColor.a + ')';\n this.newColorDiv.style.backgroundColor = 'rgba(' + this.color.r + ',' + this.color.g + ',' + this.color.b + ',' + this.color.a + ')';\n }\n\n /**\n * used by create to set the size of the canvas.\n * @private\n */\n }, {\n key: '_setSize',\n value: function _setSize() {\n this.colorPickerCanvas.style.width = '100%';\n this.colorPickerCanvas.style.height = '100%';\n\n this.colorPickerCanvas.width = 289 * this.pixelRatio;\n this.colorPickerCanvas.height = 289 * this.pixelRatio;\n }\n\n /**\n * create all dom elements\n * TODO: cleanup, lots of similar dom elements\n * @private\n */\n }, {\n key: '_create',\n value: function _create() {\n this.frame = document.createElement('div');\n this.frame.className = 'vis-color-picker';\n\n this.colorPickerDiv = document.createElement('div');\n this.colorPickerSelector = document.createElement('div');\n this.colorPickerSelector.className = 'vis-selector';\n this.colorPickerDiv.appendChild(this.colorPickerSelector);\n\n this.colorPickerCanvas = document.createElement('canvas');\n this.colorPickerDiv.appendChild(this.colorPickerCanvas);\n\n if (!this.colorPickerCanvas.getContext) {\n var noCanvas = document.createElement('DIV');\n noCanvas.style.color = 'red';\n noCanvas.style.fontWeight = 'bold';\n noCanvas.style.padding = '10px';\n noCanvas.innerHTML = 'Error: your browser does not support HTML canvas';\n this.colorPickerCanvas.appendChild(noCanvas);\n } else {\n var ctx = this.colorPickerCanvas.getContext(\"2d\");\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n\n this.colorPickerCanvas.getContext(\"2d\").setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n }\n\n this.colorPickerDiv.className = 'vis-color';\n\n this.opacityDiv = document.createElement('div');\n this.opacityDiv.className = 'vis-opacity';\n\n this.brightnessDiv = document.createElement('div');\n this.brightnessDiv.className = 'vis-brightness';\n\n this.arrowDiv = document.createElement('div');\n this.arrowDiv.className = 'vis-arrow';\n\n this.opacityRange = document.createElement('input');\n try {\n this.opacityRange.type = 'range'; // Not supported on IE9\n this.opacityRange.min = '0';\n this.opacityRange.max = '100';\n } catch (err) {}\n this.opacityRange.value = '100';\n this.opacityRange.className = 'vis-range';\n\n this.brightnessRange = document.createElement('input');\n try {\n this.brightnessRange.type = 'range'; // Not supported on IE9\n this.brightnessRange.min = '0';\n this.brightnessRange.max = '100';\n } catch (err) {}\n this.brightnessRange.value = '100';\n this.brightnessRange.className = 'vis-range';\n\n this.opacityDiv.appendChild(this.opacityRange);\n this.brightnessDiv.appendChild(this.brightnessRange);\n\n var me = this;\n this.opacityRange.onchange = function () {\n me._setOpacity(this.value);\n };\n this.opacityRange.oninput = function () {\n me._setOpacity(this.value);\n };\n this.brightnessRange.onchange = function () {\n me._setBrightness(this.value);\n };\n this.brightnessRange.oninput = function () {\n me._setBrightness(this.value);\n };\n\n this.brightnessLabel = document.createElement(\"div\");\n this.brightnessLabel.className = \"vis-label vis-brightness\";\n this.brightnessLabel.innerHTML = 'brightness:';\n\n this.opacityLabel = document.createElement(\"div\");\n this.opacityLabel.className = \"vis-label vis-opacity\";\n this.opacityLabel.innerHTML = 'opacity:';\n\n this.newColorDiv = document.createElement(\"div\");\n this.newColorDiv.className = \"vis-new-color\";\n this.newColorDiv.innerHTML = 'new';\n\n this.initialColorDiv = document.createElement(\"div\");\n this.initialColorDiv.className = \"vis-initial-color\";\n this.initialColorDiv.innerHTML = 'initial';\n\n this.cancelButton = document.createElement(\"div\");\n this.cancelButton.className = \"vis-button vis-cancel\";\n this.cancelButton.innerHTML = 'cancel';\n this.cancelButton.onclick = this._hide.bind(this, false);\n\n this.applyButton = document.createElement(\"div\");\n this.applyButton.className = \"vis-button vis-apply\";\n this.applyButton.innerHTML = 'apply';\n this.applyButton.onclick = this._apply.bind(this);\n\n this.saveButton = document.createElement(\"div\");\n this.saveButton.className = \"vis-button vis-save\";\n this.saveButton.innerHTML = 'save';\n this.saveButton.onclick = this._save.bind(this);\n\n this.loadButton = document.createElement(\"div\");\n this.loadButton.className = \"vis-button vis-load\";\n this.loadButton.innerHTML = 'load last';\n this.loadButton.onclick = this._loadLast.bind(this);\n\n this.frame.appendChild(this.colorPickerDiv);\n this.frame.appendChild(this.arrowDiv);\n this.frame.appendChild(this.brightnessLabel);\n this.frame.appendChild(this.brightnessDiv);\n this.frame.appendChild(this.opacityLabel);\n this.frame.appendChild(this.opacityDiv);\n this.frame.appendChild(this.newColorDiv);\n this.frame.appendChild(this.initialColorDiv);\n\n this.frame.appendChild(this.cancelButton);\n this.frame.appendChild(this.applyButton);\n this.frame.appendChild(this.saveButton);\n this.frame.appendChild(this.loadButton);\n }\n\n /**\n * bind hammer to the color picker\n * @private\n */\n }, {\n key: '_bindHammer',\n value: function _bindHammer() {\n var _this2 = this;\n\n this.drag = {};\n this.pinch = {};\n this.hammer = new Hammer(this.colorPickerCanvas);\n this.hammer.get('pinch').set({ enable: true });\n\n hammerUtil.onTouch(this.hammer, function (event) {\n _this2._moveSelector(event);\n });\n this.hammer.on('tap', function (event) {\n _this2._moveSelector(event);\n });\n this.hammer.on('panstart', function (event) {\n _this2._moveSelector(event);\n });\n this.hammer.on('panmove', function (event) {\n _this2._moveSelector(event);\n });\n this.hammer.on('panend', function (event) {\n _this2._moveSelector(event);\n });\n }\n\n /**\n * generate the hue circle. This is relatively heavy (200ms) and is done only once on the first time it is shown.\n * @private\n */\n }, {\n key: '_generateHueCircle',\n value: function _generateHueCircle() {\n if (this.generated === false) {\n var ctx = this.colorPickerCanvas.getContext('2d');\n if (this.pixelRation === undefined) {\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n }\n ctx.setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n\n // clear the canvas\n var w = this.colorPickerCanvas.clientWidth;\n var h = this.colorPickerCanvas.clientHeight;\n ctx.clearRect(0, 0, w, h);\n\n // draw hue circle\n var x = undefined,\n y = undefined,\n hue = undefined,\n sat = undefined;\n this.centerCoordinates = { x: w * 0.5, y: h * 0.5 };\n this.r = 0.49 * w;\n var angleConvert = 2 * Math.PI / 360;\n var hfac = 1 / 360;\n var sfac = 1 / this.r;\n var rgb = undefined;\n for (hue = 0; hue < 360; hue++) {\n for (sat = 0; sat < this.r; sat++) {\n x = this.centerCoordinates.x + sat * Math.sin(angleConvert * hue);\n y = this.centerCoordinates.y + sat * Math.cos(angleConvert * hue);\n rgb = util.HSVToRGB(hue * hfac, sat * sfac, 1);\n ctx.fillStyle = 'rgb(' + rgb.r + ',' + rgb.g + ',' + rgb.b + ')';\n ctx.fillRect(x - 0.5, y - 0.5, 2, 2);\n }\n }\n ctx.strokeStyle = 'rgba(0,0,0,1)';\n ctx.circle(this.centerCoordinates.x, this.centerCoordinates.y, this.r);\n ctx.stroke();\n\n this.hueCircle = ctx.getImageData(0, 0, w, h);\n }\n this.generated = true;\n }\n\n /**\n * move the selector. This is called by hammer functions.\n *\n * @param event\n * @private\n */\n }, {\n key: '_moveSelector',\n value: function _moveSelector(event) {\n var rect = this.colorPickerDiv.getBoundingClientRect();\n var left = event.center.x - rect.left;\n var top = event.center.y - rect.top;\n\n var centerY = 0.5 * this.colorPickerDiv.clientHeight;\n var centerX = 0.5 * this.colorPickerDiv.clientWidth;\n\n var x = left - centerX;\n var y = top - centerY;\n\n var angle = Math.atan2(x, y);\n var radius = 0.98 * Math.min(Math.sqrt(x * x + y * y), centerX);\n\n var newTop = Math.cos(angle) * radius + centerY;\n var newLeft = Math.sin(angle) * radius + centerX;\n\n this.colorPickerSelector.style.top = newTop - 0.5 * this.colorPickerSelector.clientHeight + 'px';\n this.colorPickerSelector.style.left = newLeft - 0.5 * this.colorPickerSelector.clientWidth + 'px';\n\n // set color\n var h = angle / (2 * Math.PI);\n h = h < 0 ? h + 1 : h;\n var s = radius / this.r;\n var hsv = util.RGBToHSV(this.color.r, this.color.g, this.color.b);\n hsv.h = h;\n hsv.s = s;\n var rgba = util.HSVToRGB(hsv.h, hsv.s, hsv.v);\n rgba['a'] = this.color.a;\n this.color = rgba;\n\n // update previews\n this.initialColorDiv.style.backgroundColor = 'rgba(' + this.initialColor.r + ',' + this.initialColor.g + ',' + this.initialColor.b + ',' + this.initialColor.a + ')';\n this.newColorDiv.style.backgroundColor = 'rgba(' + this.color.r + ',' + this.color.g + ',' + this.color.b + ',' + this.color.a + ')';\n }\n }]);\n\n return ColorPicker;\n })();\n\n exports['default'] = ColorPicker;\n module.exports = exports['default'];\n\n/***/ },\n/* 46 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var util = __webpack_require__(1);\n\n var errorFound = false;\n var allOptions = undefined;\n var printStyle = 'background: #FFeeee; color: #dd0000';\n /**\n * Used to validate options.\n */\n\n var Validator = (function () {\n function Validator() {\n _classCallCheck(this, Validator);\n }\n\n /**\n * Main function to be called\n * @param options\n * @param subObject\n * @returns {boolean}\n */\n\n _createClass(Validator, null, [{\n key: 'validate',\n value: function validate(options, referenceOptions, subObject) {\n errorFound = false;\n allOptions = referenceOptions;\n var usedOptions = referenceOptions;\n if (subObject !== undefined) {\n usedOptions = referenceOptions[subObject];\n }\n Validator.parse(options, usedOptions, []);\n return errorFound;\n }\n\n /**\n * Will traverse an object recursively and check every value\n * @param options\n * @param referenceOptions\n * @param path\n */\n }, {\n key: 'parse',\n value: function parse(options, referenceOptions, path) {\n for (var option in options) {\n if (options.hasOwnProperty(option)) {\n Validator.check(option, options, referenceOptions, path);\n }\n }\n }\n\n /**\n * Check every value. If the value is an object, call the parse function on that object.\n * @param option\n * @param options\n * @param referenceOptions\n * @param path\n */\n }, {\n key: 'check',\n value: function check(option, options, referenceOptions, path) {\n if (referenceOptions[option] === undefined && referenceOptions.__any__ === undefined) {\n Validator.getSuggestion(option, referenceOptions, path);\n } else if (referenceOptions[option] === undefined && referenceOptions.__any__ !== undefined) {\n // __any__ is a wildcard. Any value is accepted and will be further analysed by reference.\n if (Validator.getType(options[option]) === 'object' && referenceOptions['__any__'].__type__ !== undefined) {\n // if the any subgroup is not a predefined object int he configurator we do not look deeper into the object.\n Validator.checkFields(option, options, referenceOptions, '__any__', referenceOptions['__any__'].__type__, path);\n } else {\n Validator.checkFields(option, options, referenceOptions, '__any__', referenceOptions['__any__'], path);\n }\n } else {\n // Since all options in the reference are objects, we can check whether they are supposed to be object to look for the __type__ field.\n if (referenceOptions[option].__type__ !== undefined) {\n // if this should be an object, we check if the correct type has been supplied to account for shorthand options.\n Validator.checkFields(option, options, referenceOptions, option, referenceOptions[option].__type__, path);\n } else {\n Validator.checkFields(option, options, referenceOptions, option, referenceOptions[option], path);\n }\n }\n }\n\n /**\n *\n * @param {String} option | the option property\n * @param {Object} options | The supplied options object\n * @param {Object} referenceOptions | The reference options containing all options and their allowed formats\n * @param {String} referenceOption | Usually this is the same as option, except when handling an __any__ tag.\n * @param {String} refOptionType | This is the type object from the reference options\n * @param {Array} path | where in the object is the option\n */\n }, {\n key: 'checkFields',\n value: function checkFields(option, options, referenceOptions, referenceOption, refOptionObj, path) {\n var optionType = Validator.getType(options[option]);\n var refOptionType = refOptionObj[optionType];\n if (refOptionType !== undefined) {\n // if the type is correct, we check if it is supposed to be one of a few select values\n if (Validator.getType(refOptionType) === 'array') {\n if (refOptionType.indexOf(options[option]) === -1) {\n console.log('%cInvalid option detected in \"' + option + '\".' + ' Allowed values are:' + Validator.print(refOptionType) + ' not \"' + options[option] + '\". ' + Validator.printLocation(path, option), printStyle);\n errorFound = true;\n } else if (optionType === 'object' && referenceOption !== \"__any__\") {\n path = util.copyAndExtendArray(path, option);\n Validator.parse(options[option], referenceOptions[referenceOption], path);\n }\n } else if (optionType === 'object' && referenceOption !== \"__any__\") {\n path = util.copyAndExtendArray(path, option);\n Validator.parse(options[option], referenceOptions[referenceOption], path);\n }\n } else if (refOptionObj['any'] === undefined) {\n // type of the field is incorrect and the field cannot be any\n console.log('%cInvalid type received for \"' + option + '\". Expected: ' + Validator.print(Object.keys(refOptionObj)) + '. Received [' + optionType + '] \"' + options[option] + '\"' + Validator.printLocation(path, option), printStyle);\n errorFound = true;\n }\n }\n }, {\n key: 'getType',\n value: function getType(object) {\n var type = typeof object;\n\n if (type === 'object') {\n if (object === null) {\n return 'null';\n }\n if (object instanceof Boolean) {\n return 'boolean';\n }\n if (object instanceof Number) {\n return 'number';\n }\n if (object instanceof String) {\n return 'string';\n }\n if (Array.isArray(object)) {\n return 'array';\n }\n if (object instanceof Date) {\n return 'date';\n }\n if (object.nodeType !== undefined) {\n return 'dom';\n }\n if (object._isAMomentObject === true) {\n return 'moment';\n }\n return 'object';\n } else if (type === 'number') {\n return 'number';\n } else if (type === 'boolean') {\n return 'boolean';\n } else if (type === 'string') {\n return 'string';\n } else if (type === undefined) {\n return 'undefined';\n }\n return type;\n }\n }, {\n key: 'getSuggestion',\n value: function getSuggestion(option, options, path) {\n var localSearch = Validator.findInOptions(option, options, path, false);\n var globalSearch = Validator.findInOptions(option, allOptions, [], true);\n\n var localSearchThreshold = 8;\n var globalSearchThreshold = 4;\n\n if (localSearch.indexMatch !== undefined) {\n console.log('%cUnknown option detected: \"' + option + '\" in ' + Validator.printLocation(localSearch.path, option, '') + 'Perhaps it was incomplete? Did you mean: \"' + localSearch.indexMatch + '\"?\\n\\n', printStyle);\n } else if (globalSearch.distance <= globalSearchThreshold && localSearch.distance > globalSearch.distance) {\n console.log('%cUnknown option detected: \"' + option + '\" in ' + Validator.printLocation(localSearch.path, option, '') + 'Perhaps it was misplaced? Matching option found at: ' + Validator.printLocation(globalSearch.path, globalSearch.closestMatch, ''), printStyle);\n } else if (localSearch.distance <= localSearchThreshold) {\n console.log('%cUnknown option detected: \"' + option + '\". Did you mean \"' + localSearch.closestMatch + '\"?' + Validator.printLocation(localSearch.path, option), printStyle);\n } else {\n console.log('%cUnknown option detected: \"' + option + '\". Did you mean one of these: ' + Validator.print(Object.keys(options)) + Validator.printLocation(path, option), printStyle);\n }\n\n errorFound = true;\n }\n\n /**\n * traverse the options in search for a match.\n * @param option\n * @param options\n * @param path\n * @param recursive\n * @returns {{closestMatch: string, path: Array, distance: number}}\n */\n }, {\n key: 'findInOptions',\n value: function findInOptions(option, options, path) {\n var recursive = arguments.length <= 3 || arguments[3] === undefined ? false : arguments[3];\n\n var min = 1e9;\n var closestMatch = '';\n var closestMatchPath = [];\n var lowerCaseOption = option.toLowerCase();\n var indexMatch = undefined;\n for (var op in options) {\n var distance = undefined;\n if (options[op].__type__ !== undefined && recursive === true) {\n var result = Validator.findInOptions(option, options[op], util.copyAndExtendArray(path, op));\n if (min > result.distance) {\n closestMatch = result.closestMatch;\n closestMatchPath = result.path;\n min = result.distance;\n indexMatch = result.indexMatch;\n }\n } else {\n if (op.toLowerCase().indexOf(lowerCaseOption) !== -1) {\n indexMatch = op;\n }\n distance = Validator.levenshteinDistance(option, op);\n if (min > distance) {\n closestMatch = op;\n closestMatchPath = util.copyArray(path);\n min = distance;\n }\n }\n }\n return { closestMatch: closestMatch, path: closestMatchPath, distance: min, indexMatch: indexMatch };\n }\n }, {\n key: 'printLocation',\n value: function printLocation(path, option) {\n var prefix = arguments.length <= 2 || arguments[2] === undefined ? 'Problem value found at: \\n' : arguments[2];\n\n var str = '\\n\\n' + prefix + 'options = {\\n';\n for (var i = 0; i < path.length; i++) {\n for (var j = 0; j < i + 1; j++) {\n str += ' ';\n }\n str += path[i] + ': {\\n';\n }\n for (var j = 0; j < path.length + 1; j++) {\n str += ' ';\n }\n str += option + '\\n';\n for (var i = 0; i < path.length + 1; i++) {\n for (var j = 0; j < path.length - i; j++) {\n str += ' ';\n }\n str += '}\\n';\n }\n return str + '\\n\\n';\n }\n }, {\n key: 'print',\n value: function print(options) {\n return JSON.stringify(options).replace(/(\\\")|(\\[)|(\\])|(,\"__type__\")/g, \"\").replace(/(\\,)/g, ', ');\n }\n\n // Compute the edit distance between the two given strings\n // http://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance#JavaScript\n /*\n Copyright (c) 2011 Andrei Mackenzie\n Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n */\n }, {\n key: 'levenshteinDistance',\n value: function levenshteinDistance(a, b) {\n if (a.length === 0) return b.length;\n if (b.length === 0) return a.length;\n\n var matrix = [];\n\n // increment along the first column of each row\n var i;\n for (i = 0; i <= b.length; i++) {\n matrix[i] = [i];\n }\n\n // increment each column in the first row\n var j;\n for (j = 0; j <= a.length; j++) {\n matrix[0][j] = j;\n }\n\n // Fill in the rest of the matrix\n for (i = 1; i <= b.length; i++) {\n for (j = 1; j <= a.length; j++) {\n if (b.charAt(i - 1) == a.charAt(j - 1)) {\n matrix[i][j] = matrix[i - 1][j - 1];\n } else {\n matrix[i][j] = Math.min(matrix[i - 1][j - 1] + 1, // substitution\n Math.min(matrix[i][j - 1] + 1, // insertion\n matrix[i - 1][j] + 1)); // deletion\n }\n }\n }\n\n return matrix[b.length][a.length];\n }\n }]);\n\n return Validator;\n })();\n\n exports['default'] = Validator;\n exports.printStyle = printStyle;\n\n/***/ },\n/* 47 */\n/***/ function(module, exports) {\n\n /**\n * This object contains all possible options. It will check if the types are correct, if required if the option is one\n * of the allowed values.\n *\n * __any__ means that the name of the property does not matter.\n * __type__ is a required field for all objects and contains the allowed types of all objects\n */\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n var string = 'string';\n var boolean = 'boolean';\n var number = 'number';\n var array = 'array';\n var date = 'date';\n var object = 'object'; // should only be in a __type__ property\n var dom = 'dom';\n var moment = 'moment';\n var any = 'any';\n\n var allOptions = {\n configure: {\n enabled: { boolean: boolean },\n filter: { boolean: boolean, 'function': 'function' },\n container: { dom: dom },\n __type__: { object: object, boolean: boolean, 'function': 'function' }\n },\n\n //globals :\n align: { string: string },\n autoResize: { boolean: boolean },\n throttleRedraw: { number: number },\n clickToUse: { boolean: boolean },\n dataAttributes: { string: string, array: array },\n editable: {\n add: { boolean: boolean, 'undefined': 'undefined' },\n remove: { boolean: boolean, 'undefined': 'undefined' },\n updateGroup: { boolean: boolean, 'undefined': 'undefined' },\n updateTime: { boolean: boolean, 'undefined': 'undefined' },\n __type__: { boolean: boolean, object: object }\n },\n end: { number: number, date: date, string: string, moment: moment },\n format: {\n minorLabels: {\n millisecond: { string: string, 'undefined': 'undefined' },\n second: { string: string, 'undefined': 'undefined' },\n minute: { string: string, 'undefined': 'undefined' },\n hour: { string: string, 'undefined': 'undefined' },\n weekday: { string: string, 'undefined': 'undefined' },\n day: { string: string, 'undefined': 'undefined' },\n month: { string: string, 'undefined': 'undefined' },\n year: { string: string, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n majorLabels: {\n millisecond: { string: string, 'undefined': 'undefined' },\n second: { string: string, 'undefined': 'undefined' },\n minute: { string: string, 'undefined': 'undefined' },\n hour: { string: string, 'undefined': 'undefined' },\n weekday: { string: string, 'undefined': 'undefined' },\n day: { string: string, 'undefined': 'undefined' },\n month: { string: string, 'undefined': 'undefined' },\n year: { string: string, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n __type__: { object: object }\n },\n moment: { 'function': 'function' },\n groupOrder: { string: string, 'function': 'function' },\n groupEditable: {\n add: { boolean: boolean, 'undefined': 'undefined' },\n remove: { boolean: boolean, 'undefined': 'undefined' },\n order: { boolean: boolean, 'undefined': 'undefined' },\n __type__: { boolean: boolean, object: object }\n },\n groupOrderSwap: { 'function': 'function' },\n height: { string: string, number: number },\n hiddenDates: {\n start: { date: date, number: number, string: string, moment: moment },\n end: { date: date, number: number, string: string, moment: moment },\n repeat: { string: string },\n __type__: { object: object, array: array }\n },\n itemsAlwaysDraggable: { boolean: boolean },\n locale: { string: string },\n locales: {\n __any__: { any: any },\n __type__: { object: object }\n },\n margin: {\n axis: { number: number },\n item: {\n horizontal: { number: number, 'undefined': 'undefined' },\n vertical: { number: number, 'undefined': 'undefined' },\n __type__: { object: object, number: number }\n },\n __type__: { object: object, number: number }\n },\n max: { date: date, number: number, string: string, moment: moment },\n maxHeight: { number: number, string: string },\n maxMinorChars: { number: number },\n min: { date: date, number: number, string: string, moment: moment },\n minHeight: { number: number, string: string },\n moveable: { boolean: boolean },\n multiselect: { boolean: boolean },\n multiselectPerGroup: { boolean: boolean },\n onAdd: { 'function': 'function' },\n onUpdate: { 'function': 'function' },\n onMove: { 'function': 'function' },\n onMoving: { 'function': 'function' },\n onRemove: { 'function': 'function' },\n onAddGroup: { 'function': 'function' },\n onMoveGroup: { 'function': 'function' },\n onRemoveGroup: { 'function': 'function' },\n order: { 'function': 'function' },\n orientation: {\n axis: { string: string, 'undefined': 'undefined' },\n item: { string: string, 'undefined': 'undefined' },\n __type__: { string: string, object: object }\n },\n selectable: { boolean: boolean },\n showCurrentTime: { boolean: boolean },\n showMajorLabels: { boolean: boolean },\n showMinorLabels: { boolean: boolean },\n stack: { boolean: boolean },\n snap: { 'function': 'function', 'null': 'null' },\n start: { date: date, number: number, string: string, moment: moment },\n template: { 'function': 'function' },\n groupTemplate: { 'function': 'function' },\n timeAxis: {\n scale: { string: string, 'undefined': 'undefined' },\n step: { number: number, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n type: { string: string },\n width: { string: string, number: number },\n zoomable: { boolean: boolean },\n zoomKey: { string: ['ctrlKey', 'altKey', 'metaKey', ''] },\n zoomMax: { number: number },\n zoomMin: { number: number },\n\n __type__: { object: object }\n };\n\n var configureOptions = {\n global: {\n align: ['center', 'left', 'right'],\n autoResize: true,\n throttleRedraw: [10, 0, 1000, 10],\n clickToUse: false,\n // dataAttributes: ['all'], // FIXME: can be 'all' or string[]\n editable: {\n add: false,\n remove: false,\n updateGroup: false,\n updateTime: false\n },\n end: '',\n format: {\n minorLabels: {\n millisecond: 'SSS',\n second: 's',\n minute: 'HH:mm',\n hour: 'HH:mm',\n weekday: 'ddd D',\n day: 'D',\n month: 'MMM',\n year: 'YYYY'\n },\n majorLabels: {\n millisecond: 'HH:mm:ss',\n second: 'D MMMM HH:mm',\n minute: 'ddd D MMMM',\n hour: 'ddd D MMMM',\n weekday: 'MMMM YYYY',\n day: 'MMMM YYYY',\n month: 'YYYY',\n year: ''\n }\n },\n\n //groupOrder: {string, 'function': 'function'},\n groupsDraggable: false,\n height: '',\n //hiddenDates: {object, array},\n locale: '',\n margin: {\n axis: [20, 0, 100, 1],\n item: {\n horizontal: [10, 0, 100, 1],\n vertical: [10, 0, 100, 1]\n }\n },\n max: '',\n maxHeight: '',\n maxMinorChars: [7, 0, 20, 1],\n min: '',\n minHeight: '',\n moveable: false,\n multiselect: false,\n multiselectPerGroup: false,\n //onAdd: {'function': 'function'},\n //onUpdate: {'function': 'function'},\n //onMove: {'function': 'function'},\n //onMoving: {'function': 'function'},\n //onRename: {'function': 'function'},\n //order: {'function': 'function'},\n orientation: {\n axis: ['both', 'bottom', 'top'],\n item: ['bottom', 'top']\n },\n selectable: true,\n showCurrentTime: false,\n showMajorLabels: true,\n showMinorLabels: true,\n stack: true,\n //snap: {'function': 'function', nada},\n start: '',\n //template: {'function': 'function'},\n //timeAxis: {\n // scale: ['millisecond', 'second', 'minute', 'hour', 'weekday', 'day', 'month', 'year'],\n // step: [1, 1, 10, 1]\n //},\n type: ['box', 'point', 'range', 'background'],\n width: '100%',\n zoomable: true,\n zoomKey: ['ctrlKey', 'altKey', 'metaKey', ''],\n zoomMax: [315360000000000, 10, 315360000000000, 1],\n zoomMin: [10, 10, 315360000000000, 1]\n }\n };\n\n exports.allOptions = allOptions;\n exports.configureOptions = configureOptions;\n\n/***/ },\n/* 48 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var Emitter = __webpack_require__(12);\n var Hammer = __webpack_require__(20);\n var moment = __webpack_require__(2);\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var Range = __webpack_require__(23);\n var Core = __webpack_require__(27);\n var TimeAxis = __webpack_require__(38);\n var CurrentTime = __webpack_require__(43);\n var CustomTime = __webpack_require__(41);\n var LineGraph = __webpack_require__(49);\n\n var Configurator = __webpack_require__(44);\n var Validator = __webpack_require__(46)['default'];\n var printStyle = __webpack_require__(46).printStyle;\n var allOptions = __webpack_require__(57).allOptions;\n var configureOptions = __webpack_require__(57).configureOptions;\n\n /**\n * Create a timeline visualization\n * @param {HTMLElement} container\n * @param {vis.DataSet | Array} [items]\n * @param {Object} [options] See Graph2d.setOptions for the available options.\n * @constructor\n * @extends Core\n */\n function Graph2d(container, items, groups, options) {\n // if the third element is options, the forth is groups (optionally);\n if (!(Array.isArray(groups) || groups instanceof DataSet || groups instanceof DataView) && groups instanceof Object) {\n var forthArgument = options;\n options = groups;\n groups = forthArgument;\n }\n\n var me = this;\n this.defaultOptions = {\n start: null,\n end: null,\n\n autoResize: true,\n\n orientation: {\n axis: 'bottom', // axis orientation: 'bottom', 'top', or 'both'\n item: 'bottom' // not relevant for Graph2d\n },\n\n moment: moment,\n\n width: null,\n height: null,\n maxHeight: null,\n minHeight: null\n };\n this.options = util.deepExtend({}, this.defaultOptions);\n\n // Create the DOM, props, and emitter\n this._create(container);\n\n // all components listed here will be repainted automatically\n this.components = [];\n\n this.body = {\n dom: this.dom,\n domProps: this.props,\n emitter: {\n on: this.on.bind(this),\n off: this.off.bind(this),\n emit: this.emit.bind(this)\n },\n hiddenDates: [],\n util: {\n toScreen: me._toScreen.bind(me),\n toGlobalScreen: me._toGlobalScreen.bind(me), // this refers to the root.width\n toTime: me._toTime.bind(me),\n toGlobalTime: me._toGlobalTime.bind(me)\n }\n };\n\n // range\n this.range = new Range(this.body);\n this.components.push(this.range);\n this.body.range = this.range;\n\n // time axis\n this.timeAxis = new TimeAxis(this.body);\n this.components.push(this.timeAxis);\n //this.body.util.snap = this.timeAxis.snap.bind(this.timeAxis);\n\n // current time bar\n this.currentTime = new CurrentTime(this.body);\n this.components.push(this.currentTime);\n\n // item set\n this.linegraph = new LineGraph(this.body);\n\n this.components.push(this.linegraph);\n\n this.itemsData = null; // DataSet\n this.groupsData = null; // DataSet\n\n this.on('tap', function (event) {\n me.emit('click', me.getEventProperties(event));\n });\n this.on('doubletap', function (event) {\n me.emit('doubleClick', me.getEventProperties(event));\n });\n this.dom.root.oncontextmenu = function (event) {\n me.emit('contextmenu', me.getEventProperties(event));\n };\n\n // apply options\n if (options) {\n this.setOptions(options);\n }\n\n // IMPORTANT: THIS HAPPENS BEFORE SET ITEMS!\n if (groups) {\n this.setGroups(groups);\n }\n\n // create itemset\n if (items) {\n this.setItems(items);\n }\n\n // draw for the first time\n this._redraw();\n }\n\n // Extend the functionality from Core\n Graph2d.prototype = new Core();\n\n Graph2d.prototype.setOptions = function (options) {\n // validate options\n var errorFound = Validator.validate(options, allOptions);\n if (errorFound === true) {\n console.log('%cErrors have been found in the supplied options object.', printStyle);\n }\n\n Core.prototype.setOptions.call(this, options);\n };\n\n /**\n * Set items\n * @param {vis.DataSet | Array | null} items\n */\n Graph2d.prototype.setItems = function (items) {\n var initialLoad = this.itemsData == null;\n\n // convert to type DataSet when needed\n var newDataSet;\n if (!items) {\n newDataSet = null;\n } else if (items instanceof DataSet || items instanceof DataView) {\n newDataSet = items;\n } else {\n // turn an array into a dataset\n newDataSet = new DataSet(items, {\n type: {\n start: 'Date',\n end: 'Date'\n }\n });\n }\n\n // set items\n this.itemsData = newDataSet;\n this.linegraph && this.linegraph.setItems(newDataSet);\n\n if (initialLoad) {\n if (this.options.start != undefined || this.options.end != undefined) {\n var start = this.options.start != undefined ? this.options.start : null;\n var end = this.options.end != undefined ? this.options.end : null;\n this.setWindow(start, end, { animation: false });\n } else {\n this.fit({ animation: false });\n }\n }\n };\n\n /**\n * Set groups\n * @param {vis.DataSet | Array} groups\n */\n Graph2d.prototype.setGroups = function (groups) {\n // convert to type DataSet when needed\n var newDataSet;\n if (!groups) {\n newDataSet = null;\n } else if (groups instanceof DataSet || groups instanceof DataView) {\n newDataSet = groups;\n } else {\n // turn an array into a dataset\n newDataSet = new DataSet(groups);\n }\n\n this.groupsData = newDataSet;\n this.linegraph.setGroups(newDataSet);\n };\n\n /**\n * Returns an object containing an SVG element with the icon of the group (size determined by iconWidth and iconHeight), the label of the group (content) and the yAxisOrientation of the group (left or right).\n * @param groupId\n * @param width\n * @param height\n */\n Graph2d.prototype.getLegend = function (groupId, width, height) {\n if (width === undefined) {\n width = 15;\n }\n if (height === undefined) {\n height = 15;\n }\n if (this.linegraph.groups[groupId] !== undefined) {\n return this.linegraph.groups[groupId].getLegend(width, height);\n } else {\n return \"cannot find group:'\" + groupId + \"'\";\n }\n };\n\n /**\n * This checks if the visible option of the supplied group (by ID) is true or false.\n * @param groupId\n * @returns {*}\n */\n Graph2d.prototype.isGroupVisible = function (groupId) {\n if (this.linegraph.groups[groupId] !== undefined) {\n return this.linegraph.groups[groupId].visible && (this.linegraph.options.groups.visibility[groupId] === undefined || this.linegraph.options.groups.visibility[groupId] == true);\n } else {\n return false;\n }\n };\n\n /**\n * Get the data range of the item set.\n * @returns {{min: Date, max: Date}} range A range with a start and end Date.\n * When no minimum is found, min==null\n * When no maximum is found, max==null\n */\n Graph2d.prototype.getDataRange = function () {\n var min = null;\n var max = null;\n\n // calculate min from start filed\n for (var groupId in this.linegraph.groups) {\n if (this.linegraph.groups.hasOwnProperty(groupId)) {\n if (this.linegraph.groups[groupId].visible == true) {\n for (var i = 0; i < this.linegraph.groups[groupId].itemsData.length; i++) {\n var item = this.linegraph.groups[groupId].itemsData[i];\n var value = util.convert(item.x, 'Date').valueOf();\n min = min == null ? value : min > value ? value : min;\n max = max == null ? value : max < value ? value : max;\n }\n }\n }\n }\n\n return {\n min: min != null ? new Date(min) : null,\n max: max != null ? new Date(max) : null\n };\n };\n\n /**\n * Generate Timeline related information from an event\n * @param {Event} event\n * @return {Object} An object with related information, like on which area\n * The event happened, whether clicked on an item, etc.\n */\n Graph2d.prototype.getEventProperties = function (event) {\n var clientX = event.center ? event.center.x : event.clientX;\n var clientY = event.center ? event.center.y : event.clientY;\n var x = clientX - util.getAbsoluteLeft(this.dom.centerContainer);\n var y = clientY - util.getAbsoluteTop(this.dom.centerContainer);\n var time = this._toTime(x);\n\n var customTime = CustomTime.customTimeFromTarget(event);\n\n var element = util.getTarget(event);\n var what = null;\n if (util.hasParent(element, this.timeAxis.dom.foreground)) {\n what = 'axis';\n } else if (this.timeAxis2 && util.hasParent(element, this.timeAxis2.dom.foreground)) {\n what = 'axis';\n } else if (util.hasParent(element, this.linegraph.yAxisLeft.dom.frame)) {\n what = 'data-axis';\n } else if (util.hasParent(element, this.linegraph.yAxisRight.dom.frame)) {\n what = 'data-axis';\n } else if (util.hasParent(element, this.linegraph.legendLeft.dom.frame)) {\n what = 'legend';\n } else if (util.hasParent(element, this.linegraph.legendRight.dom.frame)) {\n what = 'legend';\n } else if (customTime != null) {\n what = 'custom-time';\n } else if (util.hasParent(element, this.currentTime.bar)) {\n what = 'current-time';\n } else if (util.hasParent(element, this.dom.center)) {\n what = 'background';\n }\n\n var value = [];\n var yAxisLeft = this.linegraph.yAxisLeft;\n var yAxisRight = this.linegraph.yAxisRight;\n if (!yAxisLeft.hidden) {\n value.push(yAxisLeft.screenToValue(y));\n }\n if (!yAxisRight.hidden) {\n value.push(yAxisRight.screenToValue(y));\n }\n\n return {\n event: event,\n what: what,\n pageX: event.srcEvent ? event.srcEvent.pageX : event.pageX,\n pageY: event.srcEvent ? event.srcEvent.pageY : event.pageY,\n x: x,\n y: y,\n time: time,\n value: value\n };\n };\n\n /**\n * Load a configurator\n * @return {Object}\n * @private\n */\n Graph2d.prototype._createConfigurator = function () {\n return new Configurator(this, this.dom.container, configureOptions);\n };\n\n module.exports = Graph2d;\n\n/***/ },\n/* 49 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var DOMutil = __webpack_require__(7);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var Component = __webpack_require__(25);\n var DataAxis = __webpack_require__(50);\n var GraphGroup = __webpack_require__(52);\n var Legend = __webpack_require__(56);\n var Bars = __webpack_require__(53);\n var Lines = __webpack_require__(55);\n var Points = __webpack_require__(54);\n\n var UNGROUPED = '__ungrouped__'; // reserved group id for ungrouped items\n\n /**\n * This is the constructor of the LineGraph. It requires a Timeline body and options.\n *\n * @param body\n * @param options\n * @constructor\n */\n function LineGraph(body, options) {\n this.id = util.randomUUID();\n this.body = body;\n\n this.defaultOptions = {\n yAxisOrientation: 'left',\n defaultGroup: 'default',\n sort: true,\n sampling: true,\n stack: false,\n graphHeight: '400px',\n shaded: {\n enabled: false,\n orientation: 'bottom' // top, bottom, zero\n },\n style: 'line', // line, bar\n barChart: {\n width: 50,\n sideBySide: false,\n align: 'center' // left, center, right\n },\n interpolation: {\n enabled: true,\n parametrization: 'centripetal', // uniform (alpha = 0.0), chordal (alpha = 1.0), centripetal (alpha = 0.5)\n alpha: 0.5\n },\n drawPoints: {\n enabled: true,\n size: 6,\n style: 'square' // square, circle\n },\n dataAxis: {}, //Defaults are done on DataAxis level\n legend: {}, //Defaults are done on Legend level\n groups: {\n visibility: {}\n }\n };\n\n // options is shared by this lineGraph and all its items\n this.options = util.extend({}, this.defaultOptions);\n this.dom = {};\n this.props = {};\n this.hammer = null;\n this.groups = {};\n this.abortedGraphUpdate = false;\n this.updateSVGheight = false;\n this.updateSVGheightOnResize = false;\n this.forceGraphUpdate = true;\n\n var me = this;\n this.itemsData = null; // DataSet\n this.groupsData = null; // DataSet\n\n // listeners for the DataSet of the items\n this.itemListeners = {\n 'add': function add(event, params, senderId) {\n me._onAdd(params.items);\n },\n 'update': function update(event, params, senderId) {\n me._onUpdate(params.items);\n },\n 'remove': function remove(event, params, senderId) {\n me._onRemove(params.items);\n }\n };\n\n // listeners for the DataSet of the groups\n this.groupListeners = {\n 'add': function add(event, params, senderId) {\n me._onAddGroups(params.items);\n },\n 'update': function update(event, params, senderId) {\n me._onUpdateGroups(params.items);\n },\n 'remove': function remove(event, params, senderId) {\n me._onRemoveGroups(params.items);\n }\n };\n\n this.items = {}; // object with an Item for every data item\n this.selection = []; // list with the ids of all selected nodes\n this.lastStart = this.body.range.start;\n this.touchParams = {}; // stores properties while dragging\n\n this.svgElements = {};\n this.setOptions(options);\n this.groupsUsingDefaultStyles = [0];\n this.body.emitter.on('rangechanged', function () {\n me.lastStart = me.body.range.start;\n me.svg.style.left = util.option.asSize(-me.props.width);\n\n me.forceGraphUpdate = true;\n //Is this local redraw necessary? (Core also does a change event!)\n me.redraw.call(me);\n });\n\n // create the HTML DOM\n this._create();\n this.framework = { svg: this.svg, svgElements: this.svgElements, options: this.options, groups: this.groups };\n }\n\n LineGraph.prototype = new Component();\n\n /**\n * Create the HTML DOM for the ItemSet\n */\n LineGraph.prototype._create = function () {\n var frame = document.createElement('div');\n frame.className = 'vis-line-graph';\n this.dom.frame = frame;\n\n // create svg element for graph drawing.\n this.svg = document.createElementNS('http://www.w3.org/2000/svg', 'svg');\n this.svg.style.position = 'relative';\n this.svg.style.height = ('' + this.options.graphHeight).replace('px', '') + 'px';\n this.svg.style.display = 'block';\n frame.appendChild(this.svg);\n\n // data axis\n this.options.dataAxis.orientation = 'left';\n this.yAxisLeft = new DataAxis(this.body, this.options.dataAxis, this.svg, this.options.groups);\n\n this.options.dataAxis.orientation = 'right';\n this.yAxisRight = new DataAxis(this.body, this.options.dataAxis, this.svg, this.options.groups);\n delete this.options.dataAxis.orientation;\n\n // legends\n this.legendLeft = new Legend(this.body, this.options.legend, 'left', this.options.groups);\n this.legendRight = new Legend(this.body, this.options.legend, 'right', this.options.groups);\n\n this.show();\n };\n\n /**\n * set the options of the LineGraph. the mergeOptions is used for subObjects that have an enabled element.\n * @param {object} options\n */\n LineGraph.prototype.setOptions = function (options) {\n if (options) {\n var fields = ['sampling', 'defaultGroup', 'stack', 'height', 'graphHeight', 'yAxisOrientation', 'style', 'barChart', 'dataAxis', 'sort', 'groups'];\n if (options.graphHeight === undefined && options.height !== undefined) {\n this.updateSVGheight = true;\n this.updateSVGheightOnResize = true;\n } else if (this.body.domProps.centerContainer.height !== undefined && options.graphHeight !== undefined) {\n if (parseInt((options.graphHeight + '').replace(\"px\", '')) < this.body.domProps.centerContainer.height) {\n this.updateSVGheight = true;\n }\n }\n util.selectiveDeepExtend(fields, this.options, options);\n util.mergeOptions(this.options, options, 'interpolation');\n util.mergeOptions(this.options, options, 'drawPoints');\n util.mergeOptions(this.options, options, 'shaded');\n util.mergeOptions(this.options, options, 'legend');\n\n if (options.interpolation) {\n if (typeof options.interpolation == 'object') {\n if (options.interpolation.parametrization) {\n if (options.interpolation.parametrization == 'uniform') {\n this.options.interpolation.alpha = 0;\n } else if (options.interpolation.parametrization == 'chordal') {\n this.options.interpolation.alpha = 1.0;\n } else {\n this.options.interpolation.parametrization = 'centripetal';\n this.options.interpolation.alpha = 0.5;\n }\n }\n }\n }\n\n if (this.yAxisLeft) {\n if (options.dataAxis !== undefined) {\n this.yAxisLeft.setOptions(this.options.dataAxis);\n this.yAxisRight.setOptions(this.options.dataAxis);\n }\n }\n\n if (this.legendLeft) {\n if (options.legend !== undefined) {\n this.legendLeft.setOptions(this.options.legend);\n this.legendRight.setOptions(this.options.legend);\n }\n }\n\n if (this.groups.hasOwnProperty(UNGROUPED)) {\n this.groups[UNGROUPED].setOptions(options);\n }\n }\n\n // this is used to redraw the graph if the visibility of the groups is changed.\n if (this.dom.frame) {\n //not on initial run?\n this.forceGraphUpdate = true;\n this.body.emitter.emit(\"_change\", { queue: true });\n }\n };\n\n /**\n * Hide the component from the DOM\n */\n LineGraph.prototype.hide = function () {\n // remove the frame containing the items\n if (this.dom.frame.parentNode) {\n this.dom.frame.parentNode.removeChild(this.dom.frame);\n }\n };\n\n /**\n * Show the component in the DOM (when not already visible).\n * @return {Boolean} changed\n */\n LineGraph.prototype.show = function () {\n // show frame containing the items\n if (!this.dom.frame.parentNode) {\n this.body.dom.center.appendChild(this.dom.frame);\n }\n };\n\n /**\n * Set items\n * @param {vis.DataSet | null} items\n */\n LineGraph.prototype.setItems = function (items) {\n var me = this,\n ids,\n oldItemsData = this.itemsData;\n\n // replace the dataset\n if (!items) {\n this.itemsData = null;\n } else if (items instanceof DataSet || items instanceof DataView) {\n this.itemsData = items;\n } else {\n throw new TypeError('Data must be an instance of DataSet or DataView');\n }\n\n if (oldItemsData) {\n // unsubscribe from old dataset\n util.forEach(this.itemListeners, function (callback, event) {\n oldItemsData.off(event, callback);\n });\n\n // remove all drawn items\n ids = oldItemsData.getIds();\n this._onRemove(ids);\n }\n\n if (this.itemsData) {\n // subscribe to new dataset\n var id = this.id;\n util.forEach(this.itemListeners, function (callback, event) {\n me.itemsData.on(event, callback, id);\n });\n\n // add all new items\n ids = this.itemsData.getIds();\n this._onAdd(ids);\n }\n };\n\n /**\n * Set groups\n * @param {vis.DataSet} groups\n */\n LineGraph.prototype.setGroups = function (groups) {\n var me = this;\n var ids;\n\n // unsubscribe from current dataset\n if (this.groupsData) {\n util.forEach(this.groupListeners, function (callback, event) {\n me.groupsData.off(event, callback);\n });\n\n // remove all drawn groups\n ids = this.groupsData.getIds();\n this.groupsData = null;\n for (var i = 0; i < ids.length; i++) {\n this._removeGroup(ids[i]);\n }\n }\n\n // replace the dataset\n if (!groups) {\n this.groupsData = null;\n } else if (groups instanceof DataSet || groups instanceof DataView) {\n this.groupsData = groups;\n } else {\n throw new TypeError('Data must be an instance of DataSet or DataView');\n }\n\n if (this.groupsData) {\n // subscribe to new dataset\n var id = this.id;\n util.forEach(this.groupListeners, function (callback, event) {\n me.groupsData.on(event, callback, id);\n });\n\n // draw all ms\n ids = this.groupsData.getIds();\n this._onAddGroups(ids);\n }\n };\n\n LineGraph.prototype._onUpdate = function (ids) {\n this._updateAllGroupData();\n };\n LineGraph.prototype._onAdd = function (ids) {\n this._onUpdate(ids);\n };\n LineGraph.prototype._onRemove = function (ids) {\n this._onUpdate(ids);\n };\n LineGraph.prototype._onUpdateGroups = function (groupIds) {\n this._updateAllGroupData();\n };\n LineGraph.prototype._onAddGroups = function (groupIds) {\n this._onUpdateGroups(groupIds);\n };\n\n /**\n * this cleans the group out off the legends and the dataaxis, updates the ungrouped and updates the graph\n * @param {Array} groupIds\n * @private\n */\n LineGraph.prototype._onRemoveGroups = function (groupIds) {\n for (var i = 0; i < groupIds.length; i++) {\n this._removeGroup(groupIds[i]);\n }\n this.forceGraphUpdate = true;\n this.body.emitter.emit(\"_change\", { queue: true });\n };\n\n /**\n * this cleans the group out off the legends and the dataaxis\n * @param groupId\n * @private\n */\n LineGraph.prototype._removeGroup = function (groupId) {\n if (this.groups.hasOwnProperty(groupId)) {\n if (this.groups[groupId].options.yAxisOrientation == 'right') {\n this.yAxisRight.removeGroup(groupId);\n this.legendRight.removeGroup(groupId);\n this.legendRight.redraw();\n } else {\n this.yAxisLeft.removeGroup(groupId);\n this.legendLeft.removeGroup(groupId);\n this.legendLeft.redraw();\n }\n delete this.groups[groupId];\n }\n };\n\n /**\n * update a group object with the group dataset entree\n *\n * @param group\n * @param groupId\n * @private\n */\n LineGraph.prototype._updateGroup = function (group, groupId) {\n if (!this.groups.hasOwnProperty(groupId)) {\n this.groups[groupId] = new GraphGroup(group, groupId, this.options, this.groupsUsingDefaultStyles);\n if (this.groups[groupId].options.yAxisOrientation == 'right') {\n this.yAxisRight.addGroup(groupId, this.groups[groupId]);\n this.legendRight.addGroup(groupId, this.groups[groupId]);\n } else {\n this.yAxisLeft.addGroup(groupId, this.groups[groupId]);\n this.legendLeft.addGroup(groupId, this.groups[groupId]);\n }\n } else {\n this.groups[groupId].update(group);\n if (this.groups[groupId].options.yAxisOrientation == 'right') {\n this.yAxisRight.updateGroup(groupId, this.groups[groupId]);\n this.legendRight.updateGroup(groupId, this.groups[groupId]);\n //If yAxisOrientation changed, clean out the group from the other axis.\n this.yAxisLeft.removeGroup(groupId);\n this.legendLeft.removeGroup(groupId);\n } else {\n this.yAxisLeft.updateGroup(groupId, this.groups[groupId]);\n this.legendLeft.updateGroup(groupId, this.groups[groupId]);\n //If yAxisOrientation changed, clean out the group from the other axis.\n this.yAxisRight.removeGroup(groupId);\n this.legendRight.removeGroup(groupId);\n }\n }\n this.legendLeft.redraw();\n this.legendRight.redraw();\n };\n\n /**\n * this updates all groups, it is used when there is an update the the itemset.\n *\n * @private\n */\n LineGraph.prototype._updateAllGroupData = function () {\n if (this.itemsData != null) {\n var groupsContent = {};\n var items = this.itemsData.get();\n //pre-Determine array sizes, for more efficient memory claim\n var groupCounts = {};\n for (var i = 0; i < items.length; i++) {\n var item = items[i];\n var groupId = item.group;\n if (groupId === null || groupId === undefined) {\n groupId = UNGROUPED;\n }\n groupCounts.hasOwnProperty(groupId) ? groupCounts[groupId]++ : groupCounts[groupId] = 1;\n }\n //Now insert data into the arrays.\n for (var i = 0; i < items.length; i++) {\n var item = items[i];\n var groupId = item.group;\n if (groupId === null || groupId === undefined) {\n groupId = UNGROUPED;\n }\n if (!groupsContent.hasOwnProperty(groupId)) {\n groupsContent[groupId] = new Array(groupCounts[groupId]);\n }\n //Copy data (because of unmodifiable DataView input.\n var extended = util.bridgeObject(item);\n extended.x = util.convert(item.x, 'Date');\n extended.orginalY = item.y; //real Y\n extended.y = Number(item.y);\n\n var index = groupsContent[groupId].length - groupCounts[groupId]--;\n groupsContent[groupId][index] = extended;\n }\n\n //Make sure all groups are present, to allow removal of old groups\n for (var groupId in this.groups) {\n if (this.groups.hasOwnProperty(groupId)) {\n if (!groupsContent.hasOwnProperty(groupId)) {\n groupsContent[groupId] = new Array(0);\n }\n }\n }\n\n //Update legendas, style and axis\n for (var groupId in groupsContent) {\n if (groupsContent.hasOwnProperty(groupId)) {\n if (groupsContent[groupId].length == 0) {\n if (this.groups.hasOwnProperty(groupId)) {\n this._removeGroup(groupId);\n }\n } else {\n var group = undefined;\n if (this.groupsData != undefined) {\n group = this.groupsData.get(groupId);\n }\n if (group == undefined) {\n group = { id: groupId, content: this.options.defaultGroup + groupId };\n }\n this._updateGroup(group, groupId);\n this.groups[groupId].setItems(groupsContent[groupId]);\n }\n }\n }\n this.forceGraphUpdate = true;\n this.body.emitter.emit(\"_change\", { queue: true });\n }\n };\n\n /**\n * Redraw the component, mandatory function\n * @return {boolean} Returns true if the component is resized\n */\n LineGraph.prototype.redraw = function () {\n var resized = false;\n\n // calculate actual size and position\n this.props.width = this.dom.frame.offsetWidth;\n this.props.height = this.body.domProps.centerContainer.height - this.body.domProps.border.top - this.body.domProps.border.bottom;\n\n // check if this component is resized\n resized = this._isResized() || resized;\n\n // check whether zoomed (in that case we need to re-stack everything)\n var visibleInterval = this.body.range.end - this.body.range.start;\n var zoomed = visibleInterval != this.lastVisibleInterval;\n this.lastVisibleInterval = visibleInterval;\n\n // the svg element is three times as big as the width, this allows for fully dragging left and right\n // without reloading the graph. the controls for this are bound to events in the constructor\n if (resized == true) {\n this.svg.style.width = util.option.asSize(3 * this.props.width);\n this.svg.style.left = util.option.asSize(-this.props.width);\n\n // if the height of the graph is set as proportional, change the height of the svg\n if ((this.options.height + '').indexOf(\"%\") != -1 || this.updateSVGheightOnResize == true) {\n this.updateSVGheight = true;\n }\n }\n\n // update the height of the graph on each redraw of the graph.\n if (this.updateSVGheight == true) {\n if (this.options.graphHeight != this.props.height + 'px') {\n this.options.graphHeight = this.props.height + 'px';\n this.svg.style.height = this.props.height + 'px';\n }\n this.updateSVGheight = false;\n } else {\n this.svg.style.height = ('' + this.options.graphHeight).replace('px', '') + 'px';\n }\n\n // zoomed is here to ensure that animations are shown correctly.\n if (resized == true || zoomed == true || this.abortedGraphUpdate == true || this.forceGraphUpdate == true) {\n resized = this._updateGraph() || resized;\n this.forceGraphUpdate = false;\n } else {\n // move the whole svg while dragging\n if (this.lastStart != 0) {\n var offset = this.body.range.start - this.lastStart;\n var range = this.body.range.end - this.body.range.start;\n if (this.props.width != 0) {\n var rangePerPixelInv = this.props.width / range;\n var xOffset = offset * rangePerPixelInv;\n this.svg.style.left = -this.props.width - xOffset + 'px';\n }\n }\n }\n this.legendLeft.redraw();\n this.legendRight.redraw();\n return resized;\n };\n\n LineGraph.prototype._getSortedGroupIds = function () {\n // getting group Ids\n var grouplist = [];\n for (var groupId in this.groups) {\n if (this.groups.hasOwnProperty(groupId)) {\n var group = this.groups[groupId];\n if (group.visible == true && (this.options.groups.visibility[groupId] === undefined || this.options.groups.visibility[groupId] == true)) {\n grouplist.push({ id: groupId, zIndex: group.options.zIndex });\n }\n }\n }\n util.insertSort(grouplist, function (a, b) {\n var az = a.zIndex;\n var bz = b.zIndex;\n if (az === undefined) az = 0;\n if (bz === undefined) bz = 0;\n return az == bz ? 0 : az < bz ? -1 : 1;\n });\n var groupIds = new Array(grouplist.length);\n for (var i = 0; i < grouplist.length; i++) {\n groupIds[i] = grouplist[i].id;\n }\n return groupIds;\n };\n\n /**\n * Update and redraw the graph.\n *\n */\n LineGraph.prototype._updateGraph = function () {\n // reset the svg elements\n DOMutil.prepareElements(this.svgElements);\n if (this.props.width != 0 && this.itemsData != null) {\n var group, i;\n var groupRanges = {};\n var changeCalled = false;\n // this is the range of the SVG canvas\n var minDate = this.body.util.toGlobalTime(-this.body.domProps.root.width);\n var maxDate = this.body.util.toGlobalTime(2 * this.body.domProps.root.width);\n\n // getting group Ids\n var groupIds = this._getSortedGroupIds();\n if (groupIds.length > 0) {\n var groupsData = {};\n\n // fill groups data, this only loads the data we require based on the timewindow\n this._getRelevantData(groupIds, groupsData, minDate, maxDate);\n\n // apply sampling, if disabled, it will pass through this function.\n this._applySampling(groupIds, groupsData);\n\n // we transform the X coordinates to detect collisions\n for (i = 0; i < groupIds.length; i++) {\n this._convertXcoordinates(groupsData[groupIds[i]]);\n }\n\n // now all needed data has been collected we start the processing.\n this._getYRanges(groupIds, groupsData, groupRanges);\n\n // update the Y axis first, we use this data to draw at the correct Y points\n changeCalled = this._updateYAxis(groupIds, groupRanges);\n\n // at changeCalled, abort this update cycle as the graph needs another update with new Width input from the Redraw container.\n // Cleanup SVG elements on abort.\n if (changeCalled == true) {\n DOMutil.cleanupElements(this.svgElements);\n this.abortedGraphUpdate = true;\n return true;\n }\n this.abortedGraphUpdate = false;\n\n // With the yAxis scaled correctly, use this to get the Y values of the points.\n var below = undefined;\n for (i = 0; i < groupIds.length; i++) {\n group = this.groups[groupIds[i]];\n if (this.options.stack === true && this.options.style === 'line') {\n if (group.options.excludeFromStacking == undefined || !group.options.excludeFromStacking) {\n if (below != undefined) {\n this._stack(groupsData[group.id], groupsData[below.id]);\n if (group.options.shaded.enabled == true && group.options.shaded.orientation !== \"group\") {\n if (group.options.shaded.orientation == \"top\" && below.options.shaded.orientation !== \"group\") {\n below.options.shaded.orientation = \"group\";\n below.options.shaded.groupId = group.id;\n } else {\n group.options.shaded.orientation = \"group\";\n group.options.shaded.groupId = below.id;\n }\n }\n }\n below = group;\n }\n }\n this._convertYcoordinates(groupsData[groupIds[i]], group);\n }\n\n //Precalculate paths and draw shading if appropriate. This will make sure the shading is always behind any lines.\n var paths = {};\n for (i = 0; i < groupIds.length; i++) {\n group = this.groups[groupIds[i]];\n if (group.options.style === 'line' && group.options.shaded.enabled == true) {\n var dataset = groupsData[groupIds[i]];\n if (dataset == null || dataset.length == 0) {\n continue;\n }\n if (!paths.hasOwnProperty(groupIds[i])) {\n paths[groupIds[i]] = Lines.calcPath(dataset, group);\n }\n if (group.options.shaded.orientation === \"group\") {\n var subGroupId = group.options.shaded.groupId;\n if (groupIds.indexOf(subGroupId) === -1) {\n console.log(group.id + \": Unknown shading group target given:\" + subGroupId);\n continue;\n }\n if (!paths.hasOwnProperty(subGroupId)) {\n paths[subGroupId] = Lines.calcPath(groupsData[subGroupId], this.groups[subGroupId]);\n }\n Lines.drawShading(paths[groupIds[i]], group, paths[subGroupId], this.framework);\n } else {\n Lines.drawShading(paths[groupIds[i]], group, undefined, this.framework);\n }\n }\n }\n\n // draw the groups, calculating paths if still necessary.\n Bars.draw(groupIds, groupsData, this.framework);\n for (i = 0; i < groupIds.length; i++) {\n group = this.groups[groupIds[i]];\n if (groupsData[groupIds[i]].length > 0) {\n switch (group.options.style) {\n case \"line\":\n if (!paths.hasOwnProperty(groupIds[i])) {\n paths[groupIds[i]] = Lines.calcPath(groupsData[groupIds[i]], group);\n }\n Lines.draw(paths[groupIds[i]], group, this.framework);\n //explicit no break;\n case \"point\":\n //explicit no break;\n case \"points\":\n if (group.options.style == \"point\" || group.options.style == \"points\" || group.options.drawPoints.enabled == true) {\n Points.draw(groupsData[groupIds[i]], group, this.framework);\n }\n break;\n case \"bar\":\n // bar needs to be drawn enmasse\n //explicit no break\n default:\n //do nothing...\n }\n }\n }\n }\n }\n\n // cleanup unused svg elements\n DOMutil.cleanupElements(this.svgElements);\n return false;\n };\n\n LineGraph.prototype._stack = function (data, subData) {\n var index, dx, dy, subPrevPoint, subNextPoint;\n index = 0;\n // for each data point we look for a matching on in the set below\n for (var j = 0; j < data.length; j++) {\n subPrevPoint = undefined;\n subNextPoint = undefined;\n // we look for time matches or a before-after point\n for (var k = index; k < subData.length; k++) {\n // if times match exactly\n if (subData[k].x === data[j].x) {\n subPrevPoint = subData[k];\n subNextPoint = subData[k];\n index = k;\n break;\n } else if (subData[k].x > data[j].x) {\n // overshoot\n subNextPoint = subData[k];\n if (k == 0) {\n subPrevPoint = subNextPoint;\n } else {\n subPrevPoint = subData[k - 1];\n }\n index = k;\n break;\n }\n }\n // in case the last data point has been used, we assume it stays like this.\n if (subNextPoint === undefined) {\n subPrevPoint = subData[subData.length - 1];\n subNextPoint = subData[subData.length - 1];\n }\n // linear interpolation\n dx = subNextPoint.x - subPrevPoint.x;\n dy = subNextPoint.y - subPrevPoint.y;\n if (dx == 0) {\n data[j].y = data[j].orginalY + subNextPoint.y;\n } else {\n data[j].y = data[j].orginalY + dy / dx * (data[j].x - subPrevPoint.x) + subPrevPoint.y; // ax + b where b is data[j].y\n }\n }\n };\n\n /**\n * first select and preprocess the data from the datasets.\n * the groups have their preselection of data, we now loop over this data to see\n * what data we need to draw. Sorted data is much faster.\n * more optimization is possible by doing the sampling before and using the binary search\n * to find the end date to determine the increment.\n *\n * @param {array} groupIds\n * @param {object} groupsData\n * @param {date} minDate\n * @param {date} maxDate\n * @private\n */\n LineGraph.prototype._getRelevantData = function (groupIds, groupsData, minDate, maxDate) {\n var group, i, j, item;\n if (groupIds.length > 0) {\n for (i = 0; i < groupIds.length; i++) {\n group = this.groups[groupIds[i]];\n var itemsData = group.getItems();\n // optimization for sorted data\n if (group.options.sort == true) {\n var dateComparator = function dateComparator(a, b) {\n return a.getTime() == b.getTime() ? 0 : a < b ? -1 : 1;\n };\n var first = Math.max(0, util.binarySearchValue(itemsData, minDate, 'x', 'before', dateComparator));\n var last = Math.min(itemsData.length, util.binarySearchValue(itemsData, maxDate, 'x', 'after', dateComparator) + 1);\n if (last <= 0) {\n last = itemsData.length;\n }\n var dataContainer = new Array(last - first);\n for (j = first; j < last; j++) {\n item = group.itemsData[j];\n dataContainer[j - first] = item;\n }\n groupsData[groupIds[i]] = dataContainer;\n } else {\n // If unsorted data, all data is relevant, just returning entire structure\n groupsData[groupIds[i]] = group.itemsData;\n }\n }\n }\n };\n\n /**\n *\n * @param groupIds\n * @param groupsData\n * @private\n */\n LineGraph.prototype._applySampling = function (groupIds, groupsData) {\n var group;\n if (groupIds.length > 0) {\n for (var i = 0; i < groupIds.length; i++) {\n group = this.groups[groupIds[i]];\n if (group.options.sampling == true) {\n var dataContainer = groupsData[groupIds[i]];\n if (dataContainer.length > 0) {\n var increment = 1;\n var amountOfPoints = dataContainer.length;\n\n // the global screen is used because changing the width of the yAxis may affect the increment, resulting in an endless loop\n // of width changing of the yAxis.\n var xDistance = this.body.util.toGlobalScreen(dataContainer[dataContainer.length - 1].x) - this.body.util.toGlobalScreen(dataContainer[0].x);\n var pointsPerPixel = amountOfPoints / xDistance;\n increment = Math.min(Math.ceil(0.2 * amountOfPoints), Math.max(1, Math.round(pointsPerPixel)));\n\n var sampledData = new Array(amountOfPoints);\n for (var j = 0; j < amountOfPoints; j += increment) {\n var idx = Math.round(j / increment);\n sampledData[idx] = dataContainer[j];\n }\n groupsData[groupIds[i]] = sampledData.splice(0, Math.round(amountOfPoints / increment));\n }\n }\n }\n }\n };\n\n /**\n *\n *\n * @param {array} groupIds\n * @param {object} groupsData\n * @param {object} groupRanges | this is being filled here\n * @private\n */\n LineGraph.prototype._getYRanges = function (groupIds, groupsData, groupRanges) {\n var groupData, group, i;\n var combinedDataLeft = [];\n var combinedDataRight = [];\n var options;\n if (groupIds.length > 0) {\n for (i = 0; i < groupIds.length; i++) {\n groupData = groupsData[groupIds[i]];\n options = this.groups[groupIds[i]].options;\n if (groupData.length > 0) {\n group = this.groups[groupIds[i]];\n // if bar graphs are stacked, their range need to be handled differently and accumulated over all groups.\n if (options.stack === true && options.style === 'bar') {\n if (options.yAxisOrientation === 'left') {\n combinedDataLeft = combinedDataLeft.concat(group.getItems());\n } else {\n combinedDataRight = combinedDataRight.concat(group.getItems());\n }\n } else {\n groupRanges[groupIds[i]] = group.getYRange(groupData, groupIds[i]);\n }\n }\n }\n\n // if bar graphs are stacked, their range need to be handled differently and accumulated over all groups.\n Bars.getStackedYRange(combinedDataLeft, groupRanges, groupIds, '__barStackLeft', 'left');\n Bars.getStackedYRange(combinedDataRight, groupRanges, groupIds, '__barStackRight', 'right');\n }\n };\n\n /**\n * this sets the Y ranges for the Y axis. It also determines which of the axis should be shown or hidden.\n * @param {Array} groupIds\n * @param {Object} groupRanges\n * @private\n */\n LineGraph.prototype._updateYAxis = function (groupIds, groupRanges) {\n var resized = false;\n var yAxisLeftUsed = false;\n var yAxisRightUsed = false;\n var minLeft = 1e9,\n minRight = 1e9,\n maxLeft = -1e9,\n maxRight = -1e9,\n minVal,\n maxVal;\n // if groups are present\n if (groupIds.length > 0) {\n // this is here to make sure that if there are no items in the axis but there are groups, that there is no infinite draw/redraw loop.\n for (var i = 0; i < groupIds.length; i++) {\n var group = this.groups[groupIds[i]];\n if (group && group.options.yAxisOrientation != 'right') {\n yAxisLeftUsed = true;\n minLeft = 1e9;\n maxLeft = -1e9;\n } else if (group && group.options.yAxisOrientation) {\n yAxisRightUsed = true;\n minRight = 1e9;\n maxRight = -1e9;\n }\n }\n\n // if there are items:\n for (var i = 0; i < groupIds.length; i++) {\n if (groupRanges.hasOwnProperty(groupIds[i])) {\n if (groupRanges[groupIds[i]].ignore !== true) {\n minVal = groupRanges[groupIds[i]].min;\n maxVal = groupRanges[groupIds[i]].max;\n\n if (groupRanges[groupIds[i]].yAxisOrientation != 'right') {\n yAxisLeftUsed = true;\n minLeft = minLeft > minVal ? minVal : minLeft;\n maxLeft = maxLeft < maxVal ? maxVal : maxLeft;\n } else {\n yAxisRightUsed = true;\n minRight = minRight > minVal ? minVal : minRight;\n maxRight = maxRight < maxVal ? maxVal : maxRight;\n }\n }\n }\n }\n\n if (yAxisLeftUsed == true) {\n this.yAxisLeft.setRange(minLeft, maxLeft);\n }\n if (yAxisRightUsed == true) {\n this.yAxisRight.setRange(minRight, maxRight);\n }\n }\n resized = this._toggleAxisVisiblity(yAxisLeftUsed, this.yAxisLeft) || resized;\n resized = this._toggleAxisVisiblity(yAxisRightUsed, this.yAxisRight) || resized;\n\n if (yAxisRightUsed == true && yAxisLeftUsed == true) {\n this.yAxisLeft.drawIcons = true;\n this.yAxisRight.drawIcons = true;\n } else {\n this.yAxisLeft.drawIcons = false;\n this.yAxisRight.drawIcons = false;\n }\n this.yAxisRight.master = !yAxisLeftUsed;\n this.yAxisRight.masterAxis = this.yAxisLeft;\n\n if (this.yAxisRight.master == false) {\n if (yAxisRightUsed == true) {\n this.yAxisLeft.lineOffset = this.yAxisRight.width;\n } else {\n this.yAxisLeft.lineOffset = 0;\n }\n\n resized = this.yAxisLeft.redraw() || resized;\n resized = this.yAxisRight.redraw() || resized;\n } else {\n resized = this.yAxisRight.redraw() || resized;\n }\n\n // clean the accumulated lists\n var tempGroups = ['__barStackLeft', '__barStackRight', '__lineStackLeft', '__lineStackRight'];\n for (var i = 0; i < tempGroups.length; i++) {\n if (groupIds.indexOf(tempGroups[i]) != -1) {\n groupIds.splice(groupIds.indexOf(tempGroups[i]), 1);\n }\n }\n\n return resized;\n };\n\n /**\n * This shows or hides the Y axis if needed. If there is a change, the changed event is emitted by the updateYAxis function\n *\n * @param {boolean} axisUsed\n * @returns {boolean}\n * @private\n * @param axis\n */\n LineGraph.prototype._toggleAxisVisiblity = function (axisUsed, axis) {\n var changed = false;\n if (axisUsed == false) {\n if (axis.dom.frame.parentNode && axis.hidden == false) {\n axis.hide();\n changed = true;\n }\n } else {\n if (!axis.dom.frame.parentNode && axis.hidden == true) {\n axis.show();\n changed = true;\n }\n }\n return changed;\n };\n\n /**\n * This uses the DataAxis object to generate the correct X coordinate on the SVG window. It uses the\n * util function toScreen to get the x coordinate from the timestamp. It also pre-filters the data and get the minMax ranges for\n * the yAxis.\n *\n * @param datapoints\n * @returns {Array}\n * @private\n */\n LineGraph.prototype._convertXcoordinates = function (datapoints) {\n var toScreen = this.body.util.toScreen;\n for (var i = 0; i < datapoints.length; i++) {\n datapoints[i].screen_x = toScreen(datapoints[i].x) + this.props.width;\n datapoints[i].screen_y = datapoints[i].y; //starting point for range calculations\n }\n };\n\n /**\n * This uses the DataAxis object to generate the correct X coordinate on the SVG window. It uses the\n * util function toScreen to get the x coordinate from the timestamp. It also pre-filters the data and get the minMax ranges for\n * the yAxis.\n *\n * @param datapoints\n * @param group\n * @returns {Array}\n * @private\n */\n LineGraph.prototype._convertYcoordinates = function (datapoints, group) {\n var axis = this.yAxisLeft;\n var svgHeight = Number(this.svg.style.height.replace('px', ''));\n if (group.options.yAxisOrientation == 'right') {\n axis = this.yAxisRight;\n }\n for (var i = 0; i < datapoints.length; i++) {\n datapoints[i].screen_y = Math.round(axis.convertValue(datapoints[i].y));\n }\n group.setZeroPosition(Math.min(svgHeight, axis.convertValue(0)));\n };\n\n module.exports = LineGraph;\n\n/***/ },\n/* 50 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var DOMutil = __webpack_require__(7);\n var Component = __webpack_require__(25);\n var DataScale = __webpack_require__(51);\n /**\n * A horizontal time axis\n * @param {Object} [options] See DataAxis.setOptions for the available\n * options.\n * @constructor DataAxis\n * @extends Component\n * @param body\n */\n function DataAxis(body, options, svg, linegraphOptions) {\n this.id = util.randomUUID();\n this.body = body;\n\n this.defaultOptions = {\n orientation: 'left', // supported: 'left', 'right'\n showMinorLabels: true,\n showMajorLabels: true,\n icons: false,\n majorLinesOffset: 7,\n minorLinesOffset: 4,\n labelOffsetX: 10,\n labelOffsetY: 2,\n iconWidth: 20,\n width: '40px',\n visible: true,\n alignZeros: true,\n left: {\n range: { min: undefined, max: undefined },\n format: function format(value) {\n return '' + Number.parseFloat(value.toPrecision(3));\n },\n title: { text: undefined, style: undefined }\n },\n right: {\n range: { min: undefined, max: undefined },\n format: function format(value) {\n return '' + Number.parseFloat(value.toPrecision(3));\n },\n title: { text: undefined, style: undefined }\n }\n };\n\n this.linegraphOptions = linegraphOptions;\n this.linegraphSVG = svg;\n this.props = {};\n this.DOMelements = { // dynamic elements\n lines: {},\n labels: {},\n title: {}\n };\n\n this.dom = {};\n this.scale = undefined;\n this.range = { start: 0, end: 0 };\n\n this.options = util.extend({}, this.defaultOptions);\n this.conversionFactor = 1;\n\n this.setOptions(options);\n this.width = Number(('' + this.options.width).replace(\"px\", \"\"));\n this.minWidth = this.width;\n this.height = this.linegraphSVG.getBoundingClientRect().height;\n this.hidden = false;\n\n this.stepPixels = 25;\n this.zeroCrossing = -1;\n this.amountOfSteps = -1;\n\n this.lineOffset = 0;\n this.master = true;\n this.masterAxis = null;\n this.svgElements = {};\n this.iconsRemoved = false;\n\n this.groups = {};\n this.amountOfGroups = 0;\n\n // create the HTML DOM\n this._create();\n this.framework = { svg: this.svg, svgElements: this.svgElements, options: this.options, groups: this.groups };\n\n var me = this;\n this.body.emitter.on(\"verticalDrag\", function () {\n me.dom.lineContainer.style.top = me.body.domProps.scrollTop + 'px';\n });\n }\n\n DataAxis.prototype = new Component();\n\n DataAxis.prototype.addGroup = function (label, graphOptions) {\n if (!this.groups.hasOwnProperty(label)) {\n this.groups[label] = graphOptions;\n }\n this.amountOfGroups += 1;\n };\n\n DataAxis.prototype.updateGroup = function (label, graphOptions) {\n if (!this.groups.hasOwnProperty(label)) {\n this.amountOfGroups += 1;\n }\n this.groups[label] = graphOptions;\n };\n\n DataAxis.prototype.removeGroup = function (label) {\n if (this.groups.hasOwnProperty(label)) {\n delete this.groups[label];\n this.amountOfGroups -= 1;\n }\n };\n\n DataAxis.prototype.setOptions = function (options) {\n if (options) {\n var redraw = false;\n if (this.options.orientation != options.orientation && options.orientation !== undefined) {\n redraw = true;\n }\n var fields = ['orientation', 'showMinorLabels', 'showMajorLabels', 'icons', 'majorLinesOffset', 'minorLinesOffset', 'labelOffsetX', 'labelOffsetY', 'iconWidth', 'width', 'visible', 'left', 'right', 'alignZeros'];\n util.selectiveDeepExtend(fields, this.options, options);\n\n this.minWidth = Number(('' + this.options.width).replace(\"px\", \"\"));\n if (redraw === true && this.dom.frame) {\n this.hide();\n this.show();\n }\n }\n };\n\n /**\n * Create the HTML DOM for the DataAxis\n */\n DataAxis.prototype._create = function () {\n this.dom.frame = document.createElement('div');\n this.dom.frame.style.width = this.options.width;\n this.dom.frame.style.height = this.height;\n\n this.dom.lineContainer = document.createElement('div');\n this.dom.lineContainer.style.width = '100%';\n this.dom.lineContainer.style.height = this.height;\n this.dom.lineContainer.style.position = 'relative';\n\n // create svg element for graph drawing.\n this.svg = document.createElementNS('http://www.w3.org/2000/svg', \"svg\");\n this.svg.style.position = \"absolute\";\n this.svg.style.top = '0px';\n this.svg.style.height = '100%';\n this.svg.style.width = '100%';\n this.svg.style.display = \"block\";\n this.dom.frame.appendChild(this.svg);\n };\n\n DataAxis.prototype._redrawGroupIcons = function () {\n DOMutil.prepareElements(this.svgElements);\n\n var x;\n var iconWidth = this.options.iconWidth;\n var iconHeight = 15;\n var iconOffset = 4;\n var y = iconOffset + 0.5 * iconHeight;\n\n if (this.options.orientation === 'left') {\n x = iconOffset;\n } else {\n x = this.width - iconWidth - iconOffset;\n }\n\n var groupArray = Object.keys(this.groups);\n groupArray.sort(function (a, b) {\n return a < b ? -1 : 1;\n });\n\n for (var i = 0; i < groupArray.length; i++) {\n var groupId = groupArray[i];\n if (this.groups[groupId].visible === true && (this.linegraphOptions.visibility[groupId] === undefined || this.linegraphOptions.visibility[groupId] === true)) {\n this.groups[groupId].getLegend(iconWidth, iconHeight, this.framework, x, y);\n y += iconHeight + iconOffset;\n }\n }\n\n DOMutil.cleanupElements(this.svgElements);\n this.iconsRemoved = false;\n };\n\n DataAxis.prototype._cleanupIcons = function () {\n if (this.iconsRemoved === false) {\n DOMutil.prepareElements(this.svgElements);\n DOMutil.cleanupElements(this.svgElements);\n this.iconsRemoved = true;\n }\n };\n\n /**\n * Create the HTML DOM for the DataAxis\n */\n DataAxis.prototype.show = function () {\n this.hidden = false;\n if (!this.dom.frame.parentNode) {\n if (this.options.orientation === 'left') {\n this.body.dom.left.appendChild(this.dom.frame);\n } else {\n this.body.dom.right.appendChild(this.dom.frame);\n }\n }\n\n if (!this.dom.lineContainer.parentNode) {\n this.body.dom.backgroundHorizontal.appendChild(this.dom.lineContainer);\n }\n };\n\n /**\n * Create the HTML DOM for the DataAxis\n */\n DataAxis.prototype.hide = function () {\n this.hidden = true;\n if (this.dom.frame.parentNode) {\n this.dom.frame.parentNode.removeChild(this.dom.frame);\n }\n\n if (this.dom.lineContainer.parentNode) {\n this.dom.lineContainer.parentNode.removeChild(this.dom.lineContainer);\n }\n };\n\n /**\n * Set a range (start and end)\n * @param end\n * @param start\n * @param end\n */\n DataAxis.prototype.setRange = function (start, end) {\n this.range.start = start;\n this.range.end = end;\n };\n\n /**\n * Repaint the component\n * @return {boolean} Returns true if the component is resized\n */\n DataAxis.prototype.redraw = function () {\n var resized = false;\n var activeGroups = 0;\n\n // Make sure the line container adheres to the vertical scrolling.\n this.dom.lineContainer.style.top = this.body.domProps.scrollTop + 'px';\n\n for (var groupId in this.groups) {\n if (this.groups.hasOwnProperty(groupId)) {\n if (this.groups[groupId].visible === true && (this.linegraphOptions.visibility[groupId] === undefined || this.linegraphOptions.visibility[groupId] === true)) {\n activeGroups++;\n }\n }\n }\n if (this.amountOfGroups === 0 || activeGroups === 0) {\n this.hide();\n } else {\n this.show();\n this.height = Number(this.linegraphSVG.style.height.replace(\"px\", \"\"));\n\n // svg offsetheight did not work in firefox and explorer...\n this.dom.lineContainer.style.height = this.height + 'px';\n this.width = this.options.visible === true ? Number(('' + this.options.width).replace(\"px\", \"\")) : 0;\n\n var props = this.props;\n var frame = this.dom.frame;\n\n // update classname\n frame.className = 'vis-data-axis';\n\n // calculate character width and height\n this._calculateCharSize();\n\n var orientation = this.options.orientation;\n var showMinorLabels = this.options.showMinorLabels;\n var showMajorLabels = this.options.showMajorLabels;\n\n // determine the width and height of the elements for the axis\n props.minorLabelHeight = showMinorLabels ? props.minorCharHeight : 0;\n props.majorLabelHeight = showMajorLabels ? props.majorCharHeight : 0;\n\n props.minorLineWidth = this.body.dom.backgroundHorizontal.offsetWidth - this.lineOffset - this.width + 2 * this.options.minorLinesOffset;\n props.minorLineHeight = 1;\n props.majorLineWidth = this.body.dom.backgroundHorizontal.offsetWidth - this.lineOffset - this.width + 2 * this.options.majorLinesOffset;\n props.majorLineHeight = 1;\n\n // take frame offline while updating (is almost twice as fast)\n if (orientation === 'left') {\n frame.style.top = '0';\n frame.style.left = '0';\n frame.style.bottom = '';\n frame.style.width = this.width + 'px';\n frame.style.height = this.height + \"px\";\n this.props.width = this.body.domProps.left.width;\n this.props.height = this.body.domProps.left.height;\n } else {\n // right\n frame.style.top = '';\n frame.style.bottom = '0';\n frame.style.left = '0';\n frame.style.width = this.width + 'px';\n frame.style.height = this.height + \"px\";\n this.props.width = this.body.domProps.right.width;\n this.props.height = this.body.domProps.right.height;\n }\n\n resized = this._redrawLabels();\n resized = this._isResized() || resized;\n\n if (this.options.icons === true) {\n this._redrawGroupIcons();\n } else {\n this._cleanupIcons();\n }\n\n this._redrawTitle(orientation);\n }\n return resized;\n };\n\n /**\n * Repaint major and minor text labels and vertical grid lines\n * @private\n */\n DataAxis.prototype._redrawLabels = function () {\n var _this = this;\n\n var resized = false;\n DOMutil.prepareElements(this.DOMelements.lines);\n DOMutil.prepareElements(this.DOMelements.labels);\n var orientation = this.options['orientation'];\n var customRange = this.options[orientation].range != undefined ? this.options[orientation].range : {};\n\n //Override range with manual options:\n var autoScaleEnd = true;\n if (customRange.max != undefined) {\n this.range.end = customRange.max;\n autoScaleEnd = false;\n }\n var autoScaleStart = true;\n if (customRange.min != undefined) {\n this.range.start = customRange.min;\n autoScaleStart = false;\n }\n\n this.scale = new DataScale(this.range.start, this.range.end, autoScaleStart, autoScaleEnd, this.dom.frame.offsetHeight, this.props.majorCharHeight, this.options.alignZeros, this.options[orientation].format);\n\n if (this.master === false && this.masterAxis != undefined) {\n this.scale.followScale(this.masterAxis.scale);\n }\n\n //Is updated in side-effect of _redrawLabel():\n this.maxLabelSize = 0;\n\n var lines = this.scale.getLines();\n lines.forEach(function (line) {\n var y = line.y;\n var isMajor = line.major;\n if (_this.options['showMinorLabels'] && isMajor === false) {\n _this._redrawLabel(y - 2, line.val, orientation, 'vis-y-axis vis-minor', _this.props.minorCharHeight);\n }\n if (isMajor) {\n if (y >= 0) {\n _this._redrawLabel(y - 2, line.val, orientation, 'vis-y-axis vis-major', _this.props.majorCharHeight);\n }\n }\n if (_this.master === true) {\n if (isMajor) {\n _this._redrawLine(y, orientation, 'vis-grid vis-horizontal vis-major', _this.options.majorLinesOffset, _this.props.majorLineWidth);\n } else {\n _this._redrawLine(y, orientation, 'vis-grid vis-horizontal vis-minor', _this.options.minorLinesOffset, _this.props.minorLineWidth);\n }\n }\n });\n\n // Note that title is rotated, so we're using the height, not width!\n var titleWidth = 0;\n if (this.options[orientation].title !== undefined && this.options[orientation].title.text !== undefined) {\n titleWidth = this.props.titleCharHeight;\n }\n var offset = this.options.icons === true ? Math.max(this.options.iconWidth, titleWidth) + this.options.labelOffsetX + 15 : titleWidth + this.options.labelOffsetX + 15;\n\n // this will resize the yAxis to accommodate the labels.\n if (this.maxLabelSize > this.width - offset && this.options.visible === true) {\n this.width = this.maxLabelSize + offset;\n this.options.width = this.width + \"px\";\n DOMutil.cleanupElements(this.DOMelements.lines);\n DOMutil.cleanupElements(this.DOMelements.labels);\n this.redraw();\n resized = true;\n }\n // this will resize the yAxis if it is too big for the labels.\n else if (this.maxLabelSize < this.width - offset && this.options.visible === true && this.width > this.minWidth) {\n this.width = Math.max(this.minWidth, this.maxLabelSize + offset);\n this.options.width = this.width + \"px\";\n DOMutil.cleanupElements(this.DOMelements.lines);\n DOMutil.cleanupElements(this.DOMelements.labels);\n this.redraw();\n resized = true;\n } else {\n DOMutil.cleanupElements(this.DOMelements.lines);\n DOMutil.cleanupElements(this.DOMelements.labels);\n resized = false;\n }\n\n return resized;\n };\n\n DataAxis.prototype.convertValue = function (value) {\n return this.scale.convertValue(value);\n };\n\n DataAxis.prototype.screenToValue = function (x) {\n return this.scale.screenToValue(x);\n };\n\n /**\n * Create a label for the axis at position x\n * @private\n * @param y\n * @param text\n * @param orientation\n * @param className\n * @param characterHeight\n */\n DataAxis.prototype._redrawLabel = function (y, text, orientation, className, characterHeight) {\n // reuse redundant label\n var label = DOMutil.getDOMElement('div', this.DOMelements.labels, this.dom.frame); //this.dom.redundant.labels.shift();\n label.className = className;\n label.innerHTML = text;\n if (orientation === 'left') {\n label.style.left = '-' + this.options.labelOffsetX + 'px';\n label.style.textAlign = \"right\";\n } else {\n label.style.right = '-' + this.options.labelOffsetX + 'px';\n label.style.textAlign = \"left\";\n }\n\n label.style.top = y - 0.5 * characterHeight + this.options.labelOffsetY + 'px';\n\n text += '';\n\n var largestWidth = Math.max(this.props.majorCharWidth, this.props.minorCharWidth);\n if (this.maxLabelSize < text.length * largestWidth) {\n this.maxLabelSize = text.length * largestWidth;\n }\n };\n\n /**\n * Create a minor line for the axis at position y\n * @param y\n * @param orientation\n * @param className\n * @param offset\n * @param width\n */\n DataAxis.prototype._redrawLine = function (y, orientation, className, offset, width) {\n if (this.master === true) {\n var line = DOMutil.getDOMElement('div', this.DOMelements.lines, this.dom.lineContainer); //this.dom.redundant.lines.shift();\n line.className = className;\n line.innerHTML = '';\n\n if (orientation === 'left') {\n line.style.left = this.width - offset + 'px';\n } else {\n line.style.right = this.width - offset + 'px';\n }\n\n line.style.width = width + 'px';\n line.style.top = y + 'px';\n }\n };\n\n /**\n * Create a title for the axis\n * @private\n * @param orientation\n */\n DataAxis.prototype._redrawTitle = function (orientation) {\n DOMutil.prepareElements(this.DOMelements.title);\n\n // Check if the title is defined for this axes\n if (this.options[orientation].title !== undefined && this.options[orientation].title.text !== undefined) {\n var title = DOMutil.getDOMElement('div', this.DOMelements.title, this.dom.frame);\n title.className = 'vis-y-axis vis-title vis-' + orientation;\n title.innerHTML = this.options[orientation].title.text;\n\n // Add style - if provided\n if (this.options[orientation].title.style !== undefined) {\n util.addCssText(title, this.options[orientation].title.style);\n }\n\n if (orientation === 'left') {\n title.style.left = this.props.titleCharHeight + 'px';\n } else {\n title.style.right = this.props.titleCharHeight + 'px';\n }\n\n title.style.width = this.height + 'px';\n }\n\n // we need to clean up in case we did not use all elements.\n DOMutil.cleanupElements(this.DOMelements.title);\n };\n\n /**\n * Determine the size of text on the axis (both major and minor axis).\n * The size is calculated only once and then cached in this.props.\n * @private\n */\n DataAxis.prototype._calculateCharSize = function () {\n // determine the char width and height on the minor axis\n if (!('minorCharHeight' in this.props)) {\n var textMinor = document.createTextNode('0');\n var measureCharMinor = document.createElement('div');\n measureCharMinor.className = 'vis-y-axis vis-minor vis-measure';\n measureCharMinor.appendChild(textMinor);\n this.dom.frame.appendChild(measureCharMinor);\n\n this.props.minorCharHeight = measureCharMinor.clientHeight;\n this.props.minorCharWidth = measureCharMinor.clientWidth;\n\n this.dom.frame.removeChild(measureCharMinor);\n }\n\n if (!('majorCharHeight' in this.props)) {\n var textMajor = document.createTextNode('0');\n var measureCharMajor = document.createElement('div');\n measureCharMajor.className = 'vis-y-axis vis-major vis-measure';\n measureCharMajor.appendChild(textMajor);\n this.dom.frame.appendChild(measureCharMajor);\n\n this.props.majorCharHeight = measureCharMajor.clientHeight;\n this.props.majorCharWidth = measureCharMajor.clientWidth;\n\n this.dom.frame.removeChild(measureCharMajor);\n }\n\n if (!('titleCharHeight' in this.props)) {\n var textTitle = document.createTextNode('0');\n var measureCharTitle = document.createElement('div');\n measureCharTitle.className = 'vis-y-axis vis-title vis-measure';\n measureCharTitle.appendChild(textTitle);\n this.dom.frame.appendChild(measureCharTitle);\n\n this.props.titleCharHeight = measureCharTitle.clientHeight;\n this.props.titleCharWidth = measureCharTitle.clientWidth;\n\n this.dom.frame.removeChild(measureCharTitle);\n }\n };\n\n module.exports = DataAxis;\n\n/***/ },\n/* 51 */\n/***/ function(module, exports) {\n\n /**\n * Created by ludo on 25-1-16.\n */\n\n 'use strict';\n\n function DataScale(start, end, autoScaleStart, autoScaleEnd, containerHeight, majorCharHeight) {\n var zeroAlign = arguments.length <= 6 || arguments[6] === undefined ? false : arguments[6];\n var formattingFunction = arguments.length <= 7 || arguments[7] === undefined ? false : arguments[7];\n\n this.majorSteps = [1, 2, 5, 10];\n this.minorSteps = [0.25, 0.5, 1, 2];\n this.customLines = null;\n\n this.containerHeight = containerHeight;\n this.majorCharHeight = majorCharHeight;\n this._start = start;\n this._end = end;\n\n this.scale = 1;\n this.minorStepIdx = -1;\n this.magnitudefactor = 1;\n this.determineScale();\n\n this.zeroAlign = zeroAlign;\n this.autoScaleStart = autoScaleStart;\n this.autoScaleEnd = autoScaleEnd;\n\n this.formattingFunction = formattingFunction;\n\n if (autoScaleStart || autoScaleEnd) {\n var me = this;\n var roundToMinor = function roundToMinor(value) {\n var rounded = value - value % (me.magnitudefactor * me.minorSteps[me.minorStepIdx]);\n if (value % (me.magnitudefactor * me.minorSteps[me.minorStepIdx]) > 0.5 * (me.magnitudefactor * me.minorSteps[me.minorStepIdx])) {\n return rounded + me.magnitudefactor * me.minorSteps[me.minorStepIdx];\n } else {\n return rounded;\n }\n };\n if (autoScaleStart) {\n this._start -= this.magnitudefactor * 2 * this.minorSteps[this.minorStepIdx];\n this._start = roundToMinor(this._start);\n }\n\n if (autoScaleEnd) {\n this._end += this.magnitudefactor * this.minorSteps[this.minorStepIdx];\n this._end = roundToMinor(this._end);\n }\n this.determineScale();\n }\n }\n\n DataScale.prototype.setCharHeight = function (majorCharHeight) {\n this.majorCharHeight = majorCharHeight;\n };\n\n DataScale.prototype.setHeight = function (containerHeight) {\n this.containerHeight = containerHeight;\n };\n\n DataScale.prototype.determineScale = function () {\n var range = this._end - this._start;\n this.scale = this.containerHeight / range;\n var minimumStepValue = this.majorCharHeight / this.scale;\n var orderOfMagnitude = Math.round(Math.log(range) / Math.LN10);\n\n this.minorStepIdx = -1;\n this.magnitudefactor = Math.pow(10, orderOfMagnitude);\n\n var start = 0;\n if (orderOfMagnitude < 0) {\n start = orderOfMagnitude;\n }\n\n var solutionFound = false;\n for (var l = start; Math.abs(l) <= Math.abs(orderOfMagnitude); l++) {\n this.magnitudefactor = Math.pow(10, l);\n for (var j = 0; j < this.minorSteps.length; j++) {\n var stepSize = this.magnitudefactor * this.minorSteps[j];\n if (stepSize >= minimumStepValue) {\n solutionFound = true;\n this.minorStepIdx = j;\n break;\n }\n }\n if (solutionFound === true) {\n break;\n }\n }\n };\n\n DataScale.prototype.is_major = function (value) {\n return value % (this.magnitudefactor * this.majorSteps[this.minorStepIdx]) === 0;\n };\n\n DataScale.prototype.getStep = function () {\n return this.magnitudefactor * this.minorSteps[this.minorStepIdx];\n };\n\n DataScale.prototype.getFirstMajor = function () {\n var majorStep = this.magnitudefactor * this.majorSteps[this.minorStepIdx];\n return this.convertValue(this._start + (majorStep - this._start % majorStep) % majorStep);\n };\n\n DataScale.prototype.formatValue = function (current) {\n var returnValue = current.toPrecision(5);\n if (typeof this.formattingFunction === 'function') {\n returnValue = this.formattingFunction(current);\n }\n\n if (typeof returnValue === 'number') {\n return '' + returnValue;\n } else if (typeof returnValue === 'string') {\n return returnValue;\n } else {\n return current.toPrecision(5);\n }\n };\n\n DataScale.prototype.getLines = function () {\n var lines = [];\n var step = this.getStep();\n var bottomOffset = (step - this._start % step) % step;\n for (var i = this._start + bottomOffset; this._end - i > 0.00001; i += step) {\n if (i != this._start) {\n //Skip the bottom line\n lines.push({ major: this.is_major(i), y: this.convertValue(i), val: this.formatValue(i) });\n }\n }\n return lines;\n };\n\n DataScale.prototype.followScale = function (other) {\n var oldStepIdx = this.minorStepIdx;\n var oldStart = this._start;\n var oldEnd = this._end;\n\n var me = this;\n var increaseMagnitude = function increaseMagnitude() {\n me.magnitudefactor *= 2;\n };\n var decreaseMagnitude = function decreaseMagnitude() {\n me.magnitudefactor /= 2;\n };\n\n if (other.minorStepIdx <= 1 && this.minorStepIdx <= 1 || other.minorStepIdx > 1 && this.minorStepIdx > 1) {\n //easy, no need to change stepIdx nor multiplication factor\n } else if (other.minorStepIdx < this.minorStepIdx) {\n //I'm 5, they are 4 per major.\n this.minorStepIdx = 1;\n if (oldStepIdx == 2) {\n increaseMagnitude();\n } else {\n increaseMagnitude();\n increaseMagnitude();\n }\n } else {\n //I'm 4, they are 5 per major\n this.minorStepIdx = 2;\n if (oldStepIdx == 1) {\n decreaseMagnitude();\n } else {\n decreaseMagnitude();\n decreaseMagnitude();\n }\n }\n\n //Get masters stats:\n var lines = other.getLines();\n var otherZero = other.convertValue(0);\n var otherStep = other.getStep() * other.scale;\n\n var done = false;\n var count = 0;\n //Loop until magnitude is correct for given constrains.\n while (!done && count++ < 5) {\n\n //Get my stats:\n this.scale = otherStep / (this.minorSteps[this.minorStepIdx] * this.magnitudefactor);\n var newRange = this.containerHeight / this.scale;\n\n //For the case the magnitudefactor has changed:\n this._start = oldStart;\n this._end = this._start + newRange;\n\n var myOriginalZero = this._end * this.scale;\n var majorStep = this.magnitudefactor * this.majorSteps[this.minorStepIdx];\n var majorOffset = this.getFirstMajor() - other.getFirstMajor();\n\n if (this.zeroAlign) {\n var zeroOffset = otherZero - myOriginalZero;\n this._end += zeroOffset / this.scale;\n this._start = this._end - newRange;\n } else {\n if (!this.autoScaleStart) {\n this._start += majorStep - majorOffset / this.scale;\n this._end = this._start + newRange;\n } else {\n this._start -= majorOffset / this.scale;\n this._end = this._start + newRange;\n }\n }\n if (!this.autoScaleEnd && this._end > oldEnd + 0.00001) {\n //Need to decrease magnitude to prevent scale overshoot! (end)\n decreaseMagnitude();\n done = false;\n continue;\n }\n if (!this.autoScaleStart && this._start < oldStart - 0.00001) {\n if (this.zeroAlign && oldStart >= 0) {\n console.warn(\"Can't adhere to given 'min' range, due to zeroalign\");\n } else {\n //Need to decrease magnitude to prevent scale overshoot! (start)\n decreaseMagnitude();\n done = false;\n continue;\n }\n }\n if (this.autoScaleStart && this.autoScaleEnd && newRange < oldEnd - oldStart) {\n increaseMagnitude();\n done = false;\n continue;\n }\n done = true;\n }\n };\n\n DataScale.prototype.convertValue = function (value) {\n return this.containerHeight - (value - this._start) * this.scale;\n };\n\n DataScale.prototype.screenToValue = function (pixels) {\n return (this.containerHeight - pixels) / this.scale + this._start;\n };\n\n module.exports = DataScale;\n\n/***/ },\n/* 52 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var DOMutil = __webpack_require__(7);\n var Bars = __webpack_require__(53);\n var Lines = __webpack_require__(55);\n var Points = __webpack_require__(54);\n\n /**\n * /**\n * @param {object} group | the object of the group from the dataset\n * @param {string} groupId | ID of the group\n * @param {object} options | the default options\n * @param {array} groupsUsingDefaultStyles | this array has one entree.\n * It is passed as an array so it is passed by reference.\n * It enumerates through the default styles\n * @constructor\n */\n function GraphGroup(group, groupId, options, groupsUsingDefaultStyles) {\n this.id = groupId;\n var fields = ['sampling', 'style', 'sort', 'yAxisOrientation', 'barChart', 'drawPoints', 'shaded', 'interpolation', 'zIndex', 'excludeFromStacking', 'excludeFromLegend'];\n this.options = util.selectiveBridgeObject(fields, options);\n this.usingDefaultStyle = group.className === undefined;\n this.groupsUsingDefaultStyles = groupsUsingDefaultStyles;\n this.zeroPosition = 0;\n this.update(group);\n if (this.usingDefaultStyle == true) {\n this.groupsUsingDefaultStyles[0] += 1;\n }\n this.itemsData = [];\n this.visible = group.visible === undefined ? true : group.visible;\n }\n\n /**\n * this loads a reference to all items in this group into this group.\n * @param {array} items\n */\n GraphGroup.prototype.setItems = function (items) {\n if (items != null) {\n this.itemsData = items;\n if (this.options.sort == true) {\n util.insertSort(this.itemsData, function (a, b) {\n return a.x > b.x ? 1 : -1;\n });\n }\n } else {\n this.itemsData = [];\n }\n };\n\n GraphGroup.prototype.getItems = function () {\n return this.itemsData;\n };\n\n /**\n * this is used for barcharts and shading, this way, we only have to calculate it once.\n * @param pos\n */\n GraphGroup.prototype.setZeroPosition = function (pos) {\n this.zeroPosition = pos;\n };\n\n /**\n * set the options of the graph group over the default options.\n * @param options\n */\n GraphGroup.prototype.setOptions = function (options) {\n if (options !== undefined) {\n var fields = ['sampling', 'style', 'sort', 'yAxisOrientation', 'barChart', 'zIndex', 'excludeFromStacking', 'excludeFromLegend'];\n util.selectiveDeepExtend(fields, this.options, options);\n\n // if the group's drawPoints is a function delegate the callback to the onRender property\n if (typeof options.drawPoints == 'function') {\n options.drawPoints = {\n onRender: options.drawPoints\n };\n }\n\n util.mergeOptions(this.options, options, 'interpolation');\n util.mergeOptions(this.options, options, 'drawPoints');\n util.mergeOptions(this.options, options, 'shaded');\n\n if (options.interpolation) {\n if (typeof options.interpolation == 'object') {\n if (options.interpolation.parametrization) {\n if (options.interpolation.parametrization == 'uniform') {\n this.options.interpolation.alpha = 0;\n } else if (options.interpolation.parametrization == 'chordal') {\n this.options.interpolation.alpha = 1.0;\n } else {\n this.options.interpolation.parametrization = 'centripetal';\n this.options.interpolation.alpha = 0.5;\n }\n }\n }\n }\n }\n };\n\n /**\n * this updates the current group class with the latest group dataset entree, used in _updateGroup in linegraph\n * @param group\n */\n GraphGroup.prototype.update = function (group) {\n this.group = group;\n this.content = group.content || 'graph';\n this.className = group.className || this.className || 'vis-graph-group' + this.groupsUsingDefaultStyles[0] % 10;\n this.visible = group.visible === undefined ? true : group.visible;\n this.style = group.style;\n this.setOptions(group.options);\n };\n\n /**\n * return the legend entree for this group.\n *\n * @param iconWidth\n * @param iconHeight\n * @returns {{icon: HTMLElement, label: (group.content|*|string), orientation: (.options.yAxisOrientation|*)}}\n */\n GraphGroup.prototype.getLegend = function (iconWidth, iconHeight, framework, x, y) {\n if (framework == undefined || framework == null) {\n var svg = document.createElementNS('http://www.w3.org/2000/svg', \"svg\");\n framework = { svg: svg, svgElements: {}, options: this.options, groups: [this] };\n }\n if (x == undefined || x == null) {\n x = 0;\n }\n if (y == undefined || y == null) {\n y = 0.5 * iconHeight;\n }\n switch (this.options.style) {\n case \"line\":\n Lines.drawIcon(this, x, y, iconWidth, iconHeight, framework);\n break;\n case \"points\": //explicit no break\n case \"point\":\n Points.drawIcon(this, x, y, iconWidth, iconHeight, framework);\n break;\n case \"bar\":\n Bars.drawIcon(this, x, y, iconWidth, iconHeight, framework);\n break;\n }\n return { icon: framework.svg, label: this.content, orientation: this.options.yAxisOrientation };\n };\n\n GraphGroup.prototype.getYRange = function (groupData) {\n var yMin = groupData[0].y;\n var yMax = groupData[0].y;\n for (var j = 0; j < groupData.length; j++) {\n yMin = yMin > groupData[j].y ? groupData[j].y : yMin;\n yMax = yMax < groupData[j].y ? groupData[j].y : yMax;\n }\n return { min: yMin, max: yMax, yAxisOrientation: this.options.yAxisOrientation };\n };\n\n module.exports = GraphGroup;\n\n/***/ },\n/* 53 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var DOMutil = __webpack_require__(7);\n var Points = __webpack_require__(54);\n\n function Bargraph(groupId, options) {}\n\n Bargraph.drawIcon = function (group, x, y, iconWidth, iconHeight, framework) {\n var fillHeight = iconHeight * 0.5;\n var path, fillPath;\n\n var outline = DOMutil.getSVGElement(\"rect\", framework.svgElements, framework.svg);\n outline.setAttributeNS(null, \"x\", x);\n outline.setAttributeNS(null, \"y\", y - fillHeight);\n outline.setAttributeNS(null, \"width\", iconWidth);\n outline.setAttributeNS(null, \"height\", 2 * fillHeight);\n outline.setAttributeNS(null, \"class\", \"vis-outline\");\n\n var barWidth = Math.round(0.3 * iconWidth);\n var originalWidth = group.options.barChart.width;\n var scale = originalWidth / barWidth;\n var bar1Height = Math.round(0.4 * iconHeight);\n var bar2Height = Math.round(0.75 * iconHeight);\n\n var offset = Math.round((iconWidth - 2 * barWidth) / 3);\n\n DOMutil.drawBar(x + 0.5 * barWidth + offset, y + fillHeight - bar1Height - 1, barWidth, bar1Height, group.className + ' vis-bar', framework.svgElements, framework.svg, group.style);\n DOMutil.drawBar(x + 1.5 * barWidth + offset + 2, y + fillHeight - bar2Height - 1, barWidth, bar2Height, group.className + ' vis-bar', framework.svgElements, framework.svg, group.style);\n\n if (group.options.drawPoints.enabled == true) {\n var groupTemplate = {\n style: group.options.drawPoints.style,\n styles: group.options.drawPoints.styles,\n size: group.options.drawPoints.size / scale,\n className: group.className\n };\n DOMutil.drawPoint(x + 0.5 * barWidth + offset, y + fillHeight - bar1Height - 1, groupTemplate, framework.svgElements, framework.svg);\n DOMutil.drawPoint(x + 1.5 * barWidth + offset + 2, y + fillHeight - bar2Height - 1, groupTemplate, framework.svgElements, framework.svg);\n }\n };\n\n /**\n * draw a bar graph\n *\n * @param groupIds\n * @param processedGroupData\n */\n Bargraph.draw = function (groupIds, processedGroupData, framework) {\n var combinedData = [];\n var intersections = {};\n var coreDistance;\n var key, drawData;\n var group;\n var i, j;\n var barPoints = 0;\n\n // combine all barchart data\n for (i = 0; i < groupIds.length; i++) {\n group = framework.groups[groupIds[i]];\n if (group.options.style === 'bar') {\n if (group.visible === true && (framework.options.groups.visibility[groupIds[i]] === undefined || framework.options.groups.visibility[groupIds[i]] === true)) {\n for (j = 0; j < processedGroupData[groupIds[i]].length; j++) {\n combinedData.push({\n screen_x: processedGroupData[groupIds[i]][j].screen_x,\n screen_y: processedGroupData[groupIds[i]][j].screen_y,\n x: processedGroupData[groupIds[i]][j].x,\n y: processedGroupData[groupIds[i]][j].y,\n groupId: groupIds[i],\n label: processedGroupData[groupIds[i]][j].label\n });\n barPoints += 1;\n }\n }\n }\n }\n\n if (barPoints === 0) {\n return;\n }\n\n // sort by time and by group\n combinedData.sort(function (a, b) {\n if (a.screen_x === b.screen_x) {\n return a.groupId < b.groupId ? -1 : 1;\n } else {\n return a.screen_x - b.screen_x;\n }\n });\n\n // get intersections\n Bargraph._getDataIntersections(intersections, combinedData);\n\n // plot barchart\n for (i = 0; i < combinedData.length; i++) {\n group = framework.groups[combinedData[i].groupId];\n var minWidth = group.options.barChart.minWidth != undefined ? group.options.barChart.minWidth : 0.1 * group.options.barChart.width;\n\n key = combinedData[i].screen_x;\n var heightOffset = 0;\n if (intersections[key] === undefined) {\n if (i + 1 < combinedData.length) {\n coreDistance = Math.abs(combinedData[i + 1].screen_x - key);\n }\n drawData = Bargraph._getSafeDrawData(coreDistance, group, minWidth);\n } else {\n var nextKey = i + (intersections[key].amount - intersections[key].resolved);\n var prevKey = i - (intersections[key].resolved + 1);\n if (nextKey < combinedData.length) {\n coreDistance = Math.abs(combinedData[nextKey].screen_x - key);\n }\n drawData = Bargraph._getSafeDrawData(coreDistance, group, minWidth);\n intersections[key].resolved += 1;\n\n if (group.options.stack === true && group.options.excludeFromStacking !== true) {\n if (combinedData[i].screen_y < group.zeroPosition) {\n heightOffset = intersections[key].accumulatedNegative;\n intersections[key].accumulatedNegative += group.zeroPosition - combinedData[i].screen_y;\n } else {\n heightOffset = intersections[key].accumulatedPositive;\n intersections[key].accumulatedPositive += group.zeroPosition - combinedData[i].screen_y;\n }\n } else if (group.options.barChart.sideBySide === true) {\n drawData.width = drawData.width / intersections[key].amount;\n drawData.offset += intersections[key].resolved * drawData.width - 0.5 * drawData.width * (intersections[key].amount + 1);\n }\n }\n DOMutil.drawBar(combinedData[i].screen_x + drawData.offset, combinedData[i].screen_y - heightOffset, drawData.width, group.zeroPosition - combinedData[i].screen_y, group.className + ' vis-bar', framework.svgElements, framework.svg, group.style);\n // draw points\n if (group.options.drawPoints.enabled === true) {\n var pointData = {\n screen_x: combinedData[i].screen_x,\n screen_y: combinedData[i].screen_y - heightOffset,\n x: combinedData[i].x,\n y: combinedData[i].y,\n groupId: combinedData[i].groupId,\n label: combinedData[i].label\n };\n Points.draw([pointData], group, framework, drawData.offset);\n //DOMutil.drawPoint(combinedData[i].x + drawData.offset, combinedData[i].y, group, framework.svgElements, framework.svg);\n }\n }\n };\n\n /**\n * Fill the intersections object with counters of how many datapoints share the same x coordinates\n * @param intersections\n * @param combinedData\n * @private\n */\n Bargraph._getDataIntersections = function (intersections, combinedData) {\n // get intersections\n var coreDistance;\n for (var i = 0; i < combinedData.length; i++) {\n if (i + 1 < combinedData.length) {\n coreDistance = Math.abs(combinedData[i + 1].screen_x - combinedData[i].screen_x);\n }\n if (i > 0) {\n coreDistance = Math.min(coreDistance, Math.abs(combinedData[i - 1].screen_x - combinedData[i].screen_x));\n }\n if (coreDistance === 0) {\n if (intersections[combinedData[i].screen_x] === undefined) {\n intersections[combinedData[i].screen_x] = {\n amount: 0,\n resolved: 0,\n accumulatedPositive: 0,\n accumulatedNegative: 0\n };\n }\n intersections[combinedData[i].screen_x].amount += 1;\n }\n }\n };\n\n /**\n * Get the width and offset for bargraphs based on the coredistance between datapoints\n *\n * @param coreDistance\n * @param group\n * @param minWidth\n * @returns {{width: Number, offset: Number}}\n * @private\n */\n Bargraph._getSafeDrawData = function (coreDistance, group, minWidth) {\n var width, offset;\n if (coreDistance < group.options.barChart.width && coreDistance > 0) {\n width = coreDistance < minWidth ? minWidth : coreDistance;\n\n offset = 0; // recalculate offset with the new width;\n if (group.options.barChart.align === 'left') {\n offset -= 0.5 * coreDistance;\n } else if (group.options.barChart.align === 'right') {\n offset += 0.5 * coreDistance;\n }\n } else {\n // default settings\n width = group.options.barChart.width;\n offset = 0;\n if (group.options.barChart.align === 'left') {\n offset -= 0.5 * group.options.barChart.width;\n } else if (group.options.barChart.align === 'right') {\n offset += 0.5 * group.options.barChart.width;\n }\n }\n\n return { width: width, offset: offset };\n };\n\n Bargraph.getStackedYRange = function (combinedData, groupRanges, groupIds, groupLabel, orientation) {\n if (combinedData.length > 0) {\n // sort by time and by group\n combinedData.sort(function (a, b) {\n if (a.screen_x === b.screen_x) {\n return a.groupId < b.groupId ? -1 : 1;\n } else {\n return a.screen_x - b.screen_x;\n }\n });\n var intersections = {};\n\n Bargraph._getDataIntersections(intersections, combinedData);\n groupRanges[groupLabel] = Bargraph._getStackedYRange(intersections, combinedData);\n groupRanges[groupLabel].yAxisOrientation = orientation;\n groupIds.push(groupLabel);\n }\n };\n\n Bargraph._getStackedYRange = function (intersections, combinedData) {\n var key;\n var yMin = combinedData[0].screen_y;\n var yMax = combinedData[0].screen_y;\n for (var i = 0; i < combinedData.length; i++) {\n key = combinedData[i].screen_x;\n if (intersections[key] === undefined) {\n yMin = yMin > combinedData[i].screen_y ? combinedData[i].screen_y : yMin;\n yMax = yMax < combinedData[i].screen_y ? combinedData[i].screen_y : yMax;\n } else {\n if (combinedData[i].screen_y < 0) {\n intersections[key].accumulatedNegative += combinedData[i].screen_y;\n } else {\n intersections[key].accumulatedPositive += combinedData[i].screen_y;\n }\n }\n }\n for (var xpos in intersections) {\n if (intersections.hasOwnProperty(xpos)) {\n yMin = yMin > intersections[xpos].accumulatedNegative ? intersections[xpos].accumulatedNegative : yMin;\n yMin = yMin > intersections[xpos].accumulatedPositive ? intersections[xpos].accumulatedPositive : yMin;\n yMax = yMax < intersections[xpos].accumulatedNegative ? intersections[xpos].accumulatedNegative : yMax;\n yMax = yMax < intersections[xpos].accumulatedPositive ? intersections[xpos].accumulatedPositive : yMax;\n }\n }\n\n return { min: yMin, max: yMax };\n };\n\n module.exports = Bargraph;\n\n/***/ },\n/* 54 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var DOMutil = __webpack_require__(7);\n\n function Points(groupId, options) {}\n\n /**\n * draw the data points\n *\n * @param {Array} dataset\n * @param {Object} JSONcontainer\n * @param {Object} svg | SVG DOM element\n * @param {GraphGroup} group\n * @param {Number} [offset]\n */\n Points.draw = function (dataset, group, framework, offset) {\n offset = offset || 0;\n var callback = getCallback(framework, group);\n\n for (var i = 0; i < dataset.length; i++) {\n if (!callback) {\n // draw the point the simple way.\n DOMutil.drawPoint(dataset[i].screen_x + offset, dataset[i].screen_y, getGroupTemplate(group), framework.svgElements, framework.svg, dataset[i].label);\n } else {\n var callbackResult = callback(dataset[i], group); // result might be true, false or an object\n if (callbackResult === true || typeof callbackResult === 'object') {\n DOMutil.drawPoint(dataset[i].screen_x + offset, dataset[i].screen_y, getGroupTemplate(group, callbackResult), framework.svgElements, framework.svg, dataset[i].label);\n }\n }\n }\n };\n\n Points.drawIcon = function (group, x, y, iconWidth, iconHeight, framework) {\n var fillHeight = iconHeight * 0.5;\n var path, fillPath;\n\n var outline = DOMutil.getSVGElement(\"rect\", framework.svgElements, framework.svg);\n outline.setAttributeNS(null, \"x\", x);\n outline.setAttributeNS(null, \"y\", y - fillHeight);\n outline.setAttributeNS(null, \"width\", iconWidth);\n outline.setAttributeNS(null, \"height\", 2 * fillHeight);\n outline.setAttributeNS(null, \"class\", \"vis-outline\");\n\n //Don't call callback on icon\n DOMutil.drawPoint(x + 0.5 * iconWidth, y, getGroupTemplate(group), framework.svgElements, framework.svg);\n };\n\n function getGroupTemplate(group, callbackResult) {\n callbackResult = typeof callbackResult === 'undefined' ? {} : callbackResult;\n return {\n style: callbackResult.style || group.options.drawPoints.style,\n styles: callbackResult.styles || group.options.drawPoints.styles,\n size: callbackResult.size || group.options.drawPoints.size,\n className: callbackResult.className || group.className\n };\n }\n\n function getCallback(framework, group) {\n var callback = undefined;\n // check for the graph2d onRender\n if (framework.options && framework.options.drawPoints && framework.options.drawPoints.onRender && typeof framework.options.drawPoints.onRender == 'function') {\n callback = framework.options.drawPoints.onRender;\n }\n\n // override it with the group onRender if defined\n if (group.group.options && group.group.options.drawPoints && group.group.options.drawPoints.onRender && typeof group.group.options.drawPoints.onRender == 'function') {\n callback = group.group.options.drawPoints.onRender;\n }\n return callback;\n }\n\n module.exports = Points;\n\n/***/ },\n/* 55 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n var DOMutil = __webpack_require__(7);\n\n function Line(groupId, options) {}\n\n Line.calcPath = function (dataset, group) {\n if (dataset != null) {\n if (dataset.length > 0) {\n var d = [];\n\n // construct path from dataset\n if (group.options.interpolation.enabled == true) {\n d = Line._catmullRom(dataset, group);\n } else {\n d = Line._linear(dataset);\n }\n return d;\n }\n }\n };\n\n Line.drawIcon = function (group, x, y, iconWidth, iconHeight, framework) {\n var fillHeight = iconHeight * 0.5;\n var path, fillPath;\n\n var outline = DOMutil.getSVGElement(\"rect\", framework.svgElements, framework.svg);\n outline.setAttributeNS(null, \"x\", x);\n outline.setAttributeNS(null, \"y\", y - fillHeight);\n outline.setAttributeNS(null, \"width\", iconWidth);\n outline.setAttributeNS(null, \"height\", 2 * fillHeight);\n outline.setAttributeNS(null, \"class\", \"vis-outline\");\n\n path = DOMutil.getSVGElement(\"path\", framework.svgElements, framework.svg);\n path.setAttributeNS(null, \"class\", group.className);\n if (group.style !== undefined) {\n path.setAttributeNS(null, \"style\", group.style);\n }\n\n path.setAttributeNS(null, \"d\", \"M\" + x + \",\" + y + \" L\" + (x + iconWidth) + \",\" + y + \"\");\n if (group.options.shaded.enabled == true) {\n fillPath = DOMutil.getSVGElement(\"path\", framework.svgElements, framework.svg);\n if (group.options.shaded.orientation == 'top') {\n fillPath.setAttributeNS(null, \"d\", \"M\" + x + \", \" + (y - fillHeight) + \"L\" + x + \",\" + y + \" L\" + (x + iconWidth) + \",\" + y + \" L\" + (x + iconWidth) + \",\" + (y - fillHeight));\n } else {\n fillPath.setAttributeNS(null, \"d\", \"M\" + x + \",\" + y + \" \" + \"L\" + x + \",\" + (y + fillHeight) + \" \" + \"L\" + (x + iconWidth) + \",\" + (y + fillHeight) + \"L\" + (x + iconWidth) + \",\" + y);\n }\n fillPath.setAttributeNS(null, \"class\", group.className + \" vis-icon-fill\");\n if (group.options.shaded.style !== undefined && group.options.shaded.style !== \"\") {\n fillPath.setAttributeNS(null, \"style\", group.options.shaded.style);\n }\n }\n\n if (group.options.drawPoints.enabled == true) {\n var groupTemplate = {\n style: group.options.drawPoints.style,\n styles: group.options.drawPoints.styles,\n size: group.options.drawPoints.size,\n className: group.className\n };\n DOMutil.drawPoint(x + 0.5 * iconWidth, y, groupTemplate, framework.svgElements, framework.svg);\n }\n };\n\n Line.drawShading = function (pathArray, group, subPathArray, framework) {\n // append shading to the path\n if (group.options.shaded.enabled == true) {\n var svgHeight = Number(framework.svg.style.height.replace('px', ''));\n var fillPath = DOMutil.getSVGElement('path', framework.svgElements, framework.svg);\n var type = \"L\";\n if (group.options.interpolation.enabled == true) {\n type = \"C\";\n }\n var dFill;\n var zero = 0;\n if (group.options.shaded.orientation == 'top') {\n zero = 0;\n } else if (group.options.shaded.orientation == 'bottom') {\n zero = svgHeight;\n } else {\n zero = Math.min(Math.max(0, group.zeroPosition), svgHeight);\n }\n if (group.options.shaded.orientation == 'group' && subPathArray != null && subPathArray != undefined) {\n dFill = 'M' + pathArray[0][0] + \",\" + pathArray[0][1] + \" \" + this.serializePath(pathArray, type, false) + ' L' + subPathArray[subPathArray.length - 1][0] + \",\" + subPathArray[subPathArray.length - 1][1] + \" \" + this.serializePath(subPathArray, type, true) + subPathArray[0][0] + \",\" + subPathArray[0][1] + \" Z\";\n } else {\n dFill = 'M' + pathArray[0][0] + \",\" + pathArray[0][1] + \" \" + this.serializePath(pathArray, type, false) + ' V' + zero + ' H' + pathArray[0][0] + \" Z\";\n }\n\n fillPath.setAttributeNS(null, 'class', group.className + ' vis-fill');\n if (group.options.shaded.style !== undefined) {\n fillPath.setAttributeNS(null, 'style', group.options.shaded.style);\n }\n fillPath.setAttributeNS(null, 'd', dFill);\n }\n };\n\n /**\n * draw a line graph\n *\n * @param dataset\n * @param group\n */\n Line.draw = function (pathArray, group, framework) {\n if (pathArray != null && pathArray != undefined) {\n var path = DOMutil.getSVGElement('path', framework.svgElements, framework.svg);\n path.setAttributeNS(null, \"class\", group.className);\n if (group.style !== undefined) {\n path.setAttributeNS(null, \"style\", group.style);\n }\n\n var type = \"L\";\n if (group.options.interpolation.enabled == true) {\n type = \"C\";\n }\n // copy properties to path for drawing.\n path.setAttributeNS(null, 'd', 'M' + pathArray[0][0] + \",\" + pathArray[0][1] + \" \" + this.serializePath(pathArray, type, false));\n }\n };\n\n Line.serializePath = function (pathArray, type, inverse) {\n if (pathArray.length < 2) {\n //Too little data to create a path.\n return \"\";\n }\n var d = type;\n if (inverse) {\n for (var i = pathArray.length - 2; i > 0; i--) {\n d += pathArray[i][0] + \",\" + pathArray[i][1] + \" \";\n }\n } else {\n for (var i = 1; i < pathArray.length; i++) {\n d += pathArray[i][0] + \",\" + pathArray[i][1] + \" \";\n }\n }\n return d;\n };\n\n /**\n * This uses an uniform parametrization of the interpolation algorithm:\n * 'On the Parameterization of Catmull-Rom Curves' by Cem Yuksel et al.\n * @param data\n * @returns {string}\n * @private\n */\n Line._catmullRomUniform = function (data) {\n // catmull rom\n var p0, p1, p2, p3, bp1, bp2;\n var d = [];\n d.push([Math.round(data[0].screen_x), Math.round(data[0].screen_y)]);\n var normalization = 1 / 6;\n var length = data.length;\n for (var i = 0; i < length - 1; i++) {\n\n p0 = i == 0 ? data[0] : data[i - 1];\n p1 = data[i];\n p2 = data[i + 1];\n p3 = i + 2 < length ? data[i + 2] : p2;\n\n // Catmull-Rom to Cubic Bezier conversion matrix\n // 0 1 0 0\n // -1/6 1 1/6 0\n // 0 1/6 1 -1/6\n // 0 0 1 0\n\n // bp0 = { x: p1.x, y: p1.y };\n bp1 = {\n screen_x: (-p0.screen_x + 6 * p1.screen_x + p2.screen_x) * normalization,\n screen_y: (-p0.screen_y + 6 * p1.screen_y + p2.screen_y) * normalization\n };\n bp2 = {\n screen_x: (p1.screen_x + 6 * p2.screen_x - p3.screen_x) * normalization,\n screen_y: (p1.screen_y + 6 * p2.screen_y - p3.screen_y) * normalization\n };\n // bp0 = { x: p2.x, y: p2.y };\n\n d.push([bp1.screen_x, bp1.screen_y]);\n d.push([bp2.screen_x, bp2.screen_y]);\n d.push([p2.screen_x, p2.screen_y]);\n }\n\n return d;\n };\n\n /**\n * This uses either the chordal or centripetal parameterization of the catmull-rom algorithm.\n * By default, the centripetal parameterization is used because this gives the nicest results.\n * These parameterizations are relatively heavy because the distance between 4 points have to be calculated.\n *\n * One optimization can be used to reuse distances since this is a sliding window approach.\n * @param data\n * @param group\n * @returns {string}\n * @private\n */\n Line._catmullRom = function (data, group) {\n var alpha = group.options.interpolation.alpha;\n if (alpha == 0 || alpha === undefined) {\n return this._catmullRomUniform(data);\n } else {\n var p0, p1, p2, p3, bp1, bp2, d1, d2, d3, A, B, N, M;\n var d3powA, d2powA, d3pow2A, d2pow2A, d1pow2A, d1powA;\n var d = [];\n d.push([Math.round(data[0].screen_x), Math.round(data[0].screen_y)]);\n var length = data.length;\n for (var i = 0; i < length - 1; i++) {\n\n p0 = i == 0 ? data[0] : data[i - 1];\n p1 = data[i];\n p2 = data[i + 1];\n p3 = i + 2 < length ? data[i + 2] : p2;\n\n d1 = Math.sqrt(Math.pow(p0.screen_x - p1.screen_x, 2) + Math.pow(p0.screen_y - p1.screen_y, 2));\n d2 = Math.sqrt(Math.pow(p1.screen_x - p2.screen_x, 2) + Math.pow(p1.screen_y - p2.screen_y, 2));\n d3 = Math.sqrt(Math.pow(p2.screen_x - p3.screen_x, 2) + Math.pow(p2.screen_y - p3.screen_y, 2));\n\n // Catmull-Rom to Cubic Bezier conversion matrix\n\n // A = 2d1^2a + 3d1^a * d2^a + d3^2a\n // B = 2d3^2a + 3d3^a * d2^a + d2^2a\n\n // [ 0 1 0 0 ]\n // [ -d2^2a /N A/N d1^2a /N 0 ]\n // [ 0 d3^2a /M B/M -d2^2a /M ]\n // [ 0 0 1 0 ]\n\n d3powA = Math.pow(d3, alpha);\n d3pow2A = Math.pow(d3, 2 * alpha);\n d2powA = Math.pow(d2, alpha);\n d2pow2A = Math.pow(d2, 2 * alpha);\n d1powA = Math.pow(d1, alpha);\n d1pow2A = Math.pow(d1, 2 * alpha);\n\n A = 2 * d1pow2A + 3 * d1powA * d2powA + d2pow2A;\n B = 2 * d3pow2A + 3 * d3powA * d2powA + d2pow2A;\n N = 3 * d1powA * (d1powA + d2powA);\n if (N > 0) {\n N = 1 / N;\n }\n M = 3 * d3powA * (d3powA + d2powA);\n if (M > 0) {\n M = 1 / M;\n }\n\n bp1 = {\n screen_x: (-d2pow2A * p0.screen_x + A * p1.screen_x + d1pow2A * p2.screen_x) * N,\n screen_y: (-d2pow2A * p0.screen_y + A * p1.screen_y + d1pow2A * p2.screen_y) * N\n };\n\n bp2 = {\n screen_x: (d3pow2A * p1.screen_x + B * p2.screen_x - d2pow2A * p3.screen_x) * M,\n screen_y: (d3pow2A * p1.screen_y + B * p2.screen_y - d2pow2A * p3.screen_y) * M\n };\n\n if (bp1.screen_x == 0 && bp1.screen_y == 0) {\n bp1 = p1;\n }\n if (bp2.screen_x == 0 && bp2.screen_y == 0) {\n bp2 = p2;\n }\n d.push([bp1.screen_x, bp1.screen_y]);\n d.push([bp2.screen_x, bp2.screen_y]);\n d.push([p2.screen_x, p2.screen_y]);\n }\n\n return d;\n }\n };\n\n /**\n * this generates the SVG path for a linear drawing between datapoints.\n * @param data\n * @returns {string}\n * @private\n */\n Line._linear = function (data) {\n // linear\n var d = [];\n for (var i = 0; i < data.length; i++) {\n d.push([data[i].screen_x, data[i].screen_y]);\n }\n return d;\n };\n\n module.exports = Line;\n\n/***/ },\n/* 56 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n var util = __webpack_require__(1);\n var DOMutil = __webpack_require__(7);\n var Component = __webpack_require__(25);\n\n /**\n * Legend for Graph2d\n */\n function Legend(body, options, side, linegraphOptions) {\n this.body = body;\n this.defaultOptions = {\n enabled: false,\n icons: true,\n iconSize: 20,\n iconSpacing: 6,\n left: {\n visible: true,\n position: 'top-left' // top/bottom - left,center,right\n },\n right: {\n visible: true,\n position: 'top-right' // top/bottom - left,center,right\n }\n };\n\n this.side = side;\n this.options = util.extend({}, this.defaultOptions);\n this.linegraphOptions = linegraphOptions;\n\n this.svgElements = {};\n this.dom = {};\n this.groups = {};\n this.amountOfGroups = 0;\n this._create();\n this.framework = { svg: this.svg, svgElements: this.svgElements, options: this.options, groups: this.groups };\n\n this.setOptions(options);\n }\n\n Legend.prototype = new Component();\n\n Legend.prototype.clear = function () {\n this.groups = {};\n this.amountOfGroups = 0;\n };\n\n Legend.prototype.addGroup = function (label, graphOptions) {\n\n // Include a group only if the group option 'excludeFromLegend: false' is not set.\n if (graphOptions.options.excludeFromLegend != true) {\n if (!this.groups.hasOwnProperty(label)) {\n this.groups[label] = graphOptions;\n }\n this.amountOfGroups += 1;\n }\n };\n\n Legend.prototype.updateGroup = function (label, graphOptions) {\n this.groups[label] = graphOptions;\n };\n\n Legend.prototype.removeGroup = function (label) {\n if (this.groups.hasOwnProperty(label)) {\n delete this.groups[label];\n this.amountOfGroups -= 1;\n }\n };\n\n Legend.prototype._create = function () {\n this.dom.frame = document.createElement('div');\n this.dom.frame.className = 'vis-legend';\n this.dom.frame.style.position = \"absolute\";\n this.dom.frame.style.top = \"10px\";\n this.dom.frame.style.display = \"block\";\n\n this.dom.textArea = document.createElement('div');\n this.dom.textArea.className = 'vis-legend-text';\n this.dom.textArea.style.position = \"relative\";\n this.dom.textArea.style.top = \"0px\";\n\n this.svg = document.createElementNS('http://www.w3.org/2000/svg', \"svg\");\n this.svg.style.position = 'absolute';\n this.svg.style.top = 0 + 'px';\n this.svg.style.width = this.options.iconSize + 5 + 'px';\n this.svg.style.height = '100%';\n\n this.dom.frame.appendChild(this.svg);\n this.dom.frame.appendChild(this.dom.textArea);\n };\n\n /**\n * Hide the component from the DOM\n */\n Legend.prototype.hide = function () {\n // remove the frame containing the items\n if (this.dom.frame.parentNode) {\n this.dom.frame.parentNode.removeChild(this.dom.frame);\n }\n };\n\n /**\n * Show the component in the DOM (when not already visible).\n * @return {Boolean} changed\n */\n Legend.prototype.show = function () {\n // show frame containing the items\n if (!this.dom.frame.parentNode) {\n this.body.dom.center.appendChild(this.dom.frame);\n }\n };\n\n Legend.prototype.setOptions = function (options) {\n var fields = ['enabled', 'orientation', 'icons', 'left', 'right'];\n util.selectiveDeepExtend(fields, this.options, options);\n };\n\n Legend.prototype.redraw = function () {\n var activeGroups = 0;\n var groupArray = Object.keys(this.groups);\n groupArray.sort(function (a, b) {\n return a < b ? -1 : 1;\n });\n\n for (var i = 0; i < groupArray.length; i++) {\n var groupId = groupArray[i];\n if (this.groups[groupId].visible == true && (this.linegraphOptions.visibility[groupId] === undefined || this.linegraphOptions.visibility[groupId] == true)) {\n activeGroups++;\n }\n }\n\n if (this.options[this.side].visible == false || this.amountOfGroups == 0 || this.options.enabled == false || activeGroups == 0) {\n this.hide();\n } else {\n this.show();\n if (this.options[this.side].position == 'top-left' || this.options[this.side].position == 'bottom-left') {\n this.dom.frame.style.left = '4px';\n this.dom.frame.style.textAlign = \"left\";\n this.dom.textArea.style.textAlign = \"left\";\n this.dom.textArea.style.left = this.options.iconSize + 15 + 'px';\n this.dom.textArea.style.right = '';\n this.svg.style.left = 0 + 'px';\n this.svg.style.right = '';\n } else {\n this.dom.frame.style.right = '4px';\n this.dom.frame.style.textAlign = \"right\";\n this.dom.textArea.style.textAlign = \"right\";\n this.dom.textArea.style.right = this.options.iconSize + 15 + 'px';\n this.dom.textArea.style.left = '';\n this.svg.style.right = 0 + 'px';\n this.svg.style.left = '';\n }\n\n if (this.options[this.side].position == 'top-left' || this.options[this.side].position == 'top-right') {\n this.dom.frame.style.top = 4 - Number(this.body.dom.center.style.top.replace(\"px\", \"\")) + 'px';\n this.dom.frame.style.bottom = '';\n } else {\n var scrollableHeight = this.body.domProps.center.height - this.body.domProps.centerContainer.height;\n this.dom.frame.style.bottom = 4 + scrollableHeight + Number(this.body.dom.center.style.top.replace(\"px\", \"\")) + 'px';\n this.dom.frame.style.top = '';\n }\n\n if (this.options.icons == false) {\n this.dom.frame.style.width = this.dom.textArea.offsetWidth + 10 + 'px';\n this.dom.textArea.style.right = '';\n this.dom.textArea.style.left = '';\n this.svg.style.width = '0px';\n } else {\n this.dom.frame.style.width = this.options.iconSize + 15 + this.dom.textArea.offsetWidth + 10 + 'px';\n this.drawLegendIcons();\n }\n\n var content = '';\n for (var i = 0; i < groupArray.length; i++) {\n var groupId = groupArray[i];\n if (this.groups[groupId].visible == true && (this.linegraphOptions.visibility[groupId] === undefined || this.linegraphOptions.visibility[groupId] == true)) {\n content += this.groups[groupId].content + '<br />';\n }\n }\n this.dom.textArea.innerHTML = content;\n this.dom.textArea.style.lineHeight = 0.75 * this.options.iconSize + this.options.iconSpacing + 'px';\n }\n };\n\n Legend.prototype.drawLegendIcons = function () {\n if (this.dom.frame.parentNode) {\n var groupArray = Object.keys(this.groups);\n groupArray.sort(function (a, b) {\n return a < b ? -1 : 1;\n });\n\n // this resets the elements so the order is maintained\n DOMutil.resetElements(this.svgElements);\n\n var padding = window.getComputedStyle(this.dom.frame).paddingTop;\n var iconOffset = Number(padding.replace('px', ''));\n var x = iconOffset;\n var iconWidth = this.options.iconSize;\n var iconHeight = 0.75 * this.options.iconSize;\n var y = iconOffset + 0.5 * iconHeight + 3;\n\n this.svg.style.width = iconWidth + 5 + iconOffset + 'px';\n\n for (var i = 0; i < groupArray.length; i++) {\n var groupId = groupArray[i];\n if (this.groups[groupId].visible == true && (this.linegraphOptions.visibility[groupId] === undefined || this.linegraphOptions.visibility[groupId] == true)) {\n this.groups[groupId].getLegend(iconWidth, iconHeight, this.framework, x, y);\n y += iconHeight + this.options.iconSpacing;\n }\n }\n }\n };\n\n module.exports = Legend;\n\n/***/ },\n/* 57 */\n/***/ function(module, exports) {\n\n /**\n * This object contains all possible options. It will check if the types are correct, if required if the option is one\n * of the allowed values.\n *\n * __any__ means that the name of the property does not matter.\n * __type__ is a required field for all objects and contains the allowed types of all objects\n */\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n var string = 'string';\n var boolean = 'boolean';\n var number = 'number';\n var array = 'array';\n var date = 'date';\n var object = 'object'; // should only be in a __type__ property\n var dom = 'dom';\n var moment = 'moment';\n var any = 'any';\n\n var allOptions = {\n configure: {\n enabled: { boolean: boolean },\n filter: { boolean: boolean, 'function': 'function' },\n container: { dom: dom },\n __type__: { object: object, boolean: boolean, 'function': 'function' }\n },\n\n //globals :\n yAxisOrientation: { string: ['left', 'right'] },\n defaultGroup: { string: string },\n sort: { boolean: boolean },\n sampling: { boolean: boolean },\n stack: { boolean: boolean },\n graphHeight: { string: string, number: number },\n shaded: {\n enabled: { boolean: boolean },\n orientation: { string: ['bottom', 'top', 'zero', 'group'] }, // top, bottom, zero, group\n groupId: { object: object },\n __type__: { boolean: boolean, object: object }\n },\n style: { string: ['line', 'bar', 'points'] }, // line, bar\n barChart: {\n width: { number: number },\n minWidth: { number: number },\n sideBySide: { boolean: boolean },\n align: { string: ['left', 'center', 'right'] },\n __type__: { object: object }\n },\n interpolation: {\n enabled: { boolean: boolean },\n parametrization: { string: ['centripetal', 'chordal', 'uniform'] }, // uniform (alpha = 0.0), chordal (alpha = 1.0), centripetal (alpha = 0.5)\n alpha: { number: number },\n __type__: { object: object, boolean: boolean }\n },\n drawPoints: {\n enabled: { boolean: boolean },\n onRender: { 'function': 'function' },\n size: { number: number },\n style: { string: ['square', 'circle'] }, // square, circle\n __type__: { object: object, boolean: boolean, 'function': 'function' }\n },\n dataAxis: {\n showMinorLabels: { boolean: boolean },\n showMajorLabels: { boolean: boolean },\n icons: { boolean: boolean },\n width: { string: string, number: number },\n visible: { boolean: boolean },\n alignZeros: { boolean: boolean },\n left: {\n range: { min: { number: number }, max: { number: number }, __type__: { object: object } },\n format: { 'function': 'function' },\n title: { text: { string: string, number: number }, style: { string: string }, __type__: { object: object } },\n __type__: { object: object }\n },\n right: {\n range: { min: { number: number }, max: { number: number }, __type__: { object: object } },\n format: { 'function': 'function' },\n title: { text: { string: string, number: number }, style: { string: string }, __type__: { object: object } },\n __type__: { object: object }\n },\n __type__: { object: object }\n },\n legend: {\n enabled: { boolean: boolean },\n icons: { boolean: boolean },\n left: {\n visible: { boolean: boolean },\n position: { string: ['top-right', 'bottom-right', 'top-left', 'bottom-left'] },\n __type__: { object: object }\n },\n right: {\n visible: { boolean: boolean },\n position: { string: ['top-right', 'bottom-right', 'top-left', 'bottom-left'] },\n __type__: { object: object }\n },\n __type__: { object: object, boolean: boolean }\n },\n groups: {\n visibility: { any: any },\n __type__: { object: object }\n },\n\n autoResize: { boolean: boolean },\n throttleRedraw: { number: number },\n clickToUse: { boolean: boolean },\n end: { number: number, date: date, string: string, moment: moment },\n format: {\n minorLabels: {\n millisecond: { string: string, 'undefined': 'undefined' },\n second: { string: string, 'undefined': 'undefined' },\n minute: { string: string, 'undefined': 'undefined' },\n hour: { string: string, 'undefined': 'undefined' },\n weekday: { string: string, 'undefined': 'undefined' },\n day: { string: string, 'undefined': 'undefined' },\n month: { string: string, 'undefined': 'undefined' },\n year: { string: string, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n majorLabels: {\n millisecond: { string: string, 'undefined': 'undefined' },\n second: { string: string, 'undefined': 'undefined' },\n minute: { string: string, 'undefined': 'undefined' },\n hour: { string: string, 'undefined': 'undefined' },\n weekday: { string: string, 'undefined': 'undefined' },\n day: { string: string, 'undefined': 'undefined' },\n month: { string: string, 'undefined': 'undefined' },\n year: { string: string, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n __type__: { object: object }\n },\n moment: { 'function': 'function' },\n height: { string: string, number: number },\n hiddenDates: {\n start: { date: date, number: number, string: string, moment: moment },\n end: { date: date, number: number, string: string, moment: moment },\n repeat: { string: string },\n __type__: { object: object, array: array }\n },\n locale: { string: string },\n locales: {\n __any__: { any: any },\n __type__: { object: object }\n },\n max: { date: date, number: number, string: string, moment: moment },\n maxHeight: { number: number, string: string },\n maxMinorChars: { number: number },\n min: { date: date, number: number, string: string, moment: moment },\n minHeight: { number: number, string: string },\n moveable: { boolean: boolean },\n multiselect: { boolean: boolean },\n orientation: { string: string },\n showCurrentTime: { boolean: boolean },\n showMajorLabels: { boolean: boolean },\n showMinorLabels: { boolean: boolean },\n start: { date: date, number: number, string: string, moment: moment },\n timeAxis: {\n scale: { string: string, 'undefined': 'undefined' },\n step: { number: number, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n width: { string: string, number: number },\n zoomable: { boolean: boolean },\n zoomKey: { string: ['ctrlKey', 'altKey', 'metaKey', ''] },\n zoomMax: { number: number },\n zoomMin: { number: number },\n zIndex: { number: number },\n __type__: { object: object }\n };\n\n var configureOptions = {\n global: {\n //yAxisOrientation: ['left','right'], // TDOO: enable as soon as Grahp2d doesn't crash when changing this on the fly\n sort: true,\n sampling: true,\n stack: false,\n shaded: {\n enabled: false,\n orientation: ['zero', 'top', 'bottom', 'group'] // zero, top, bottom\n },\n style: ['line', 'bar', 'points'], // line, bar\n barChart: {\n width: [50, 5, 100, 5],\n minWidth: [50, 5, 100, 5],\n sideBySide: false,\n align: ['left', 'center', 'right'] // left, center, right\n },\n interpolation: {\n enabled: true,\n parametrization: ['centripetal', 'chordal', 'uniform'] // uniform (alpha = 0.0), chordal (alpha = 1.0), centripetal (alpha = 0.5)\n },\n drawPoints: {\n enabled: true,\n size: [6, 2, 30, 1],\n style: ['square', 'circle'] // square, circle\n },\n dataAxis: {\n showMinorLabels: true,\n showMajorLabels: true,\n icons: false,\n width: [40, 0, 200, 1],\n visible: true,\n alignZeros: true,\n left: {\n //range: {min:'undefined': 'undefined'ined,max:'undefined': 'undefined'ined},\n //format: function (value) {return value;},\n title: { text: '', style: '' }\n },\n right: {\n //range: {min:'undefined': 'undefined'ined,max:'undefined': 'undefined'ined},\n //format: function (value) {return value;},\n title: { text: '', style: '' }\n }\n },\n legend: {\n enabled: false,\n icons: true,\n left: {\n visible: true,\n position: ['top-right', 'bottom-right', 'top-left', 'bottom-left'] // top/bottom - left,right\n },\n right: {\n visible: true,\n position: ['top-right', 'bottom-right', 'top-left', 'bottom-left'] // top/bottom - left,right\n }\n },\n\n autoResize: true,\n throttleRedraw: [10, 0, 1000, 10],\n clickToUse: false,\n end: '',\n format: {\n minorLabels: {\n millisecond: 'SSS',\n second: 's',\n minute: 'HH:mm',\n hour: 'HH:mm',\n weekday: 'ddd D',\n day: 'D',\n month: 'MMM',\n year: 'YYYY'\n },\n majorLabels: {\n millisecond: 'HH:mm:ss',\n second: 'D MMMM HH:mm',\n minute: 'ddd D MMMM',\n hour: 'ddd D MMMM',\n weekday: 'MMMM YYYY',\n day: 'MMMM YYYY',\n month: 'YYYY',\n year: ''\n }\n },\n\n height: '',\n locale: '',\n max: '',\n maxHeight: '',\n maxMinorChars: [7, 0, 20, 1],\n min: '',\n minHeight: '',\n moveable: true,\n orientation: ['both', 'bottom', 'top'],\n showCurrentTime: false,\n showMajorLabels: true,\n showMinorLabels: true,\n start: '',\n width: '100%',\n zoomable: true,\n zoomKey: ['ctrlKey', 'altKey', 'metaKey', ''],\n zoomMax: [315360000000000, 10, 315360000000000, 1],\n zoomMin: [10, 10, 315360000000000, 1],\n zIndex: 0\n }\n };\n\n exports.allOptions = allOptions;\n exports.configureOptions = configureOptions;\n\n/***/ },\n/* 58 */\n/***/ function(module, exports, __webpack_require__) {\n\n // Load custom shapes into CanvasRenderingContext2D\n 'use strict';\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n var _modulesGroups = __webpack_require__(59);\n\n var _modulesGroups2 = _interopRequireDefault(_modulesGroups);\n\n var _modulesNodesHandler = __webpack_require__(60);\n\n var _modulesNodesHandler2 = _interopRequireDefault(_modulesNodesHandler);\n\n var _modulesEdgesHandler = __webpack_require__(80);\n\n var _modulesEdgesHandler2 = _interopRequireDefault(_modulesEdgesHandler);\n\n var _modulesPhysicsEngine = __webpack_require__(89);\n\n var _modulesPhysicsEngine2 = _interopRequireDefault(_modulesPhysicsEngine);\n\n var _modulesClustering = __webpack_require__(98);\n\n var _modulesClustering2 = _interopRequireDefault(_modulesClustering);\n\n var _modulesCanvasRenderer = __webpack_require__(101);\n\n var _modulesCanvasRenderer2 = _interopRequireDefault(_modulesCanvasRenderer);\n\n var _modulesCanvas = __webpack_require__(102);\n\n var _modulesCanvas2 = _interopRequireDefault(_modulesCanvas);\n\n var _modulesView = __webpack_require__(103);\n\n var _modulesView2 = _interopRequireDefault(_modulesView);\n\n var _modulesInteractionHandler = __webpack_require__(104);\n\n var _modulesInteractionHandler2 = _interopRequireDefault(_modulesInteractionHandler);\n\n var _modulesSelectionHandler = __webpack_require__(107);\n\n var _modulesSelectionHandler2 = _interopRequireDefault(_modulesSelectionHandler);\n\n var _modulesLayoutEngine = __webpack_require__(108);\n\n var _modulesLayoutEngine2 = _interopRequireDefault(_modulesLayoutEngine);\n\n var _modulesManipulationSystem = __webpack_require__(109);\n\n var _modulesManipulationSystem2 = _interopRequireDefault(_modulesManipulationSystem);\n\n var _sharedConfigurator = __webpack_require__(44);\n\n var _sharedConfigurator2 = _interopRequireDefault(_sharedConfigurator);\n\n var _sharedValidator = __webpack_require__(46);\n\n var _sharedValidator2 = _interopRequireDefault(_sharedValidator);\n\n var _optionsJs = __webpack_require__(110);\n\n var _modulesKamadaKawaiJs = __webpack_require__(111);\n\n var _modulesKamadaKawaiJs2 = _interopRequireDefault(_modulesKamadaKawaiJs);\n\n /**\n * @constructor Network\n * Create a network visualization, displaying nodes and edges.\n *\n * @param {Element} container The DOM element in which the Network will\n * be created. Normally a div element.\n * @param {Object} data An object containing parameters\n * {Array} nodes\n * {Array} edges\n * @param {Object} options Options\n */\n __webpack_require__(113);\n\n var Emitter = __webpack_require__(12);\n var Hammer = __webpack_require__(20);\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n var dotparser = __webpack_require__(114);\n var gephiParser = __webpack_require__(115);\n var Images = __webpack_require__(116);\n var Activator = __webpack_require__(39);\n var locales = __webpack_require__(117);\n\n function Network(container, data, options) {\n var _this = this;\n\n if (!(this instanceof Network)) {\n throw new SyntaxError('Constructor must be called with the new operator');\n }\n\n // set constant values\n this.options = {};\n this.defaultOptions = {\n locale: 'en',\n locales: locales,\n clickToUse: false\n };\n util.extend(this.options, this.defaultOptions);\n\n // containers for nodes and edges\n this.body = {\n container: container,\n nodes: {},\n nodeIndices: [],\n edges: {},\n edgeIndices: [],\n emitter: {\n on: this.on.bind(this),\n off: this.off.bind(this),\n emit: this.emit.bind(this),\n once: this.once.bind(this)\n },\n eventListeners: {\n onTap: function onTap() {},\n onTouch: function onTouch() {},\n onDoubleTap: function onDoubleTap() {},\n onHold: function onHold() {},\n onDragStart: function onDragStart() {},\n onDrag: function onDrag() {},\n onDragEnd: function onDragEnd() {},\n onMouseWheel: function onMouseWheel() {},\n onPinch: function onPinch() {},\n onMouseMove: function onMouseMove() {},\n onRelease: function onRelease() {},\n onContext: function onContext() {}\n },\n data: {\n nodes: null, // A DataSet or DataView\n edges: null // A DataSet or DataView\n },\n functions: {\n createNode: function createNode() {},\n createEdge: function createEdge() {},\n getPointer: function getPointer() {}\n },\n modules: {},\n view: {\n scale: 1,\n translation: { x: 0, y: 0 }\n }\n };\n\n // bind the event listeners\n this.bindEventListeners();\n\n // setting up all modules\n this.images = new Images(function () {\n return _this.body.emitter.emit(\"_requestRedraw\");\n }); // object with images\n this.groups = new _modulesGroups2['default'](); // object with groups\n this.canvas = new _modulesCanvas2['default'](this.body); // DOM handler\n this.selectionHandler = new _modulesSelectionHandler2['default'](this.body, this.canvas); // Selection handler\n this.interactionHandler = new _modulesInteractionHandler2['default'](this.body, this.canvas, this.selectionHandler); // Interaction handler handles all the hammer bindings (that are bound by canvas), key\n this.view = new _modulesView2['default'](this.body, this.canvas); // camera handler, does animations and zooms\n this.renderer = new _modulesCanvasRenderer2['default'](this.body, this.canvas); // renderer, starts renderloop, has events that modules can hook into\n this.physics = new _modulesPhysicsEngine2['default'](this.body); // physics engine, does all the simulations\n this.layoutEngine = new _modulesLayoutEngine2['default'](this.body); // layout engine for inital layout and hierarchical layout\n this.clustering = new _modulesClustering2['default'](this.body); // clustering api\n this.manipulation = new _modulesManipulationSystem2['default'](this.body, this.canvas, this.selectionHandler); // data manipulation system\n\n this.nodesHandler = new _modulesNodesHandler2['default'](this.body, this.images, this.groups, this.layoutEngine); // Handle adding, deleting and updating of nodes as well as global options\n this.edgesHandler = new _modulesEdgesHandler2['default'](this.body, this.images, this.groups); // Handle adding, deleting and updating of edges as well as global options\n\n this.body.modules[\"kamadaKawai\"] = new _modulesKamadaKawaiJs2['default'](this.body, 150, 0.05); // Layouting algorithm.\n this.body.modules[\"clustering\"] = this.clustering;\n\n // create the DOM elements\n this.canvas._create();\n\n // apply options\n this.setOptions(options);\n\n // load data (the disable start variable will be the same as the enabled clustering)\n this.setData(data);\n }\n\n // Extend Network with an Emitter mixin\n Emitter(Network.prototype);\n\n /**\n * Set options\n * @param {Object} options\n */\n Network.prototype.setOptions = function (options) {\n var _this2 = this;\n\n if (options !== undefined) {\n var errorFound = _sharedValidator2['default'].validate(options, _optionsJs.allOptions);\n if (errorFound === true) {\n console.log('%cErrors have been found in the supplied options object.', _sharedValidator.printStyle);\n }\n\n // copy the global fields over\n var fields = ['locale', 'locales', 'clickToUse'];\n util.selectiveDeepExtend(fields, this.options, options);\n\n // the hierarchical system can adapt the edges and the physics to it's own options because not all combinations work with the hierarichical system.\n options = this.layoutEngine.setOptions(options.layout, options);\n\n this.canvas.setOptions(options); // options for canvas are in globals\n\n // pass the options to the modules\n this.groups.setOptions(options.groups);\n this.nodesHandler.setOptions(options.nodes);\n this.edgesHandler.setOptions(options.edges);\n this.physics.setOptions(options.physics);\n this.manipulation.setOptions(options.manipulation, options, this.options); // manipulation uses the locales in the globals\n\n this.interactionHandler.setOptions(options.interaction);\n this.renderer.setOptions(options.interaction); // options for rendering are in interaction\n this.selectionHandler.setOptions(options.interaction); // options for selection are in interaction\n\n // reload the settings of the nodes to apply changes in groups that are not referenced by pointer.\n if (options.groups !== undefined) {\n this.body.emitter.emit(\"refreshNodes\");\n }\n // these two do not have options at the moment, here for completeness\n //this.view.setOptions(options.view);\n //this.clustering.setOptions(options.clustering);\n\n if ('configure' in options) {\n if (!this.configurator) {\n this.configurator = new _sharedConfigurator2['default'](this, this.body.container, _optionsJs.configureOptions, this.canvas.pixelRatio);\n }\n\n this.configurator.setOptions(options.configure);\n }\n\n // if the configuration system is enabled, copy all options and put them into the config system\n if (this.configurator && this.configurator.options.enabled === true) {\n var networkOptions = { nodes: {}, edges: {}, layout: {}, interaction: {}, manipulation: {}, physics: {}, global: {} };\n util.deepExtend(networkOptions.nodes, this.nodesHandler.options);\n util.deepExtend(networkOptions.edges, this.edgesHandler.options);\n util.deepExtend(networkOptions.layout, this.layoutEngine.options);\n // load the selectionHandler and render default options in to the interaction group\n util.deepExtend(networkOptions.interaction, this.selectionHandler.options);\n util.deepExtend(networkOptions.interaction, this.renderer.options);\n\n util.deepExtend(networkOptions.interaction, this.interactionHandler.options);\n util.deepExtend(networkOptions.manipulation, this.manipulation.options);\n util.deepExtend(networkOptions.physics, this.physics.options);\n\n // load globals into the global object\n util.deepExtend(networkOptions.global, this.canvas.options);\n util.deepExtend(networkOptions.global, this.options);\n\n this.configurator.setModuleOptions(networkOptions);\n }\n\n // handle network global options\n if (options.clickToUse !== undefined) {\n if (options.clickToUse === true) {\n if (this.activator === undefined) {\n this.activator = new Activator(this.canvas.frame);\n this.activator.on('change', function () {\n _this2.body.emitter.emit(\"activate\");\n });\n }\n } else {\n if (this.activator !== undefined) {\n this.activator.destroy();\n delete this.activator;\n }\n this.body.emitter.emit(\"activate\");\n }\n } else {\n this.body.emitter.emit(\"activate\");\n }\n\n this.canvas.setSize();\n // start the physics simulation. Can be safely called multiple times.\n this.body.emitter.emit(\"startSimulation\");\n }\n };\n\n /**\n * Update the this.body.nodeIndices with the most recent node index list\n * @private\n */\n Network.prototype._updateVisibleIndices = function () {\n var nodes = this.body.nodes;\n var edges = this.body.edges;\n this.body.nodeIndices = [];\n this.body.edgeIndices = [];\n\n for (var nodeId in nodes) {\n if (nodes.hasOwnProperty(nodeId)) {\n if (nodes[nodeId].options.hidden === false) {\n this.body.nodeIndices.push(nodes[nodeId].id);\n }\n }\n }\n\n for (var edgeId in edges) {\n if (edges.hasOwnProperty(edgeId)) {\n if (edges[edgeId].options.hidden === false) {\n this.body.edgeIndices.push(edges[edgeId].id);\n }\n }\n }\n };\n\n /**\n * Bind all events\n */\n Network.prototype.bindEventListeners = function () {\n var _this3 = this;\n\n // this event will trigger a rebuilding of the cache everything. Used when nodes or edges have been added or removed.\n this.body.emitter.on(\"_dataChanged\", function () {\n // update shortcut lists\n _this3._updateVisibleIndices();\n _this3.body.emitter.emit(\"_requestRedraw\");\n // call the dataUpdated event because the only difference between the two is the updating of the indices\n _this3.body.emitter.emit(\"_dataUpdated\");\n });\n\n // this is called when options of EXISTING nodes or edges have changed.\n this.body.emitter.on(\"_dataUpdated\", function () {\n // update values\n _this3._updateValueRange(_this3.body.nodes);\n _this3._updateValueRange(_this3.body.edges);\n // start simulation (can be called safely, even if already running)\n _this3.body.emitter.emit(\"startSimulation\");\n _this3.body.emitter.emit(\"_requestRedraw\");\n });\n };\n\n /**\n * Set nodes and edges, and optionally options as well.\n *\n * @param {Object} data Object containing parameters:\n * {Array | DataSet | DataView} [nodes] Array with nodes\n * {Array | DataSet | DataView} [edges] Array with edges\n * {String} [dot] String containing data in DOT format\n * {String} [gephi] String containing data in gephi JSON format\n * {Options} [options] Object with options\n */\n Network.prototype.setData = function (data) {\n // reset the physics engine.\n this.body.emitter.emit(\"resetPhysics\");\n this.body.emitter.emit(\"_resetData\");\n\n // unselect all to ensure no selections from old data are carried over.\n this.selectionHandler.unselectAll();\n\n if (data && data.dot && (data.nodes || data.edges)) {\n throw new SyntaxError('Data must contain either parameter \"dot\" or ' + ' parameter pair \"nodes\" and \"edges\", but not both.');\n }\n\n // set options\n this.setOptions(data && data.options);\n // set all data\n if (data && data.dot) {\n console.log('The dot property has been depricated. Please use the static convertDot method to convert DOT into vis.network format and use the normal data format with nodes and edges. This converter is used like this: var data = vis.network.convertDot(dotString);');\n // parse DOT file\n var dotData = dotparser.DOTToGraph(data.dot);\n this.setData(dotData);\n return;\n } else if (data && data.gephi) {\n // parse DOT file\n console.log('The gephi property has been depricated. Please use the static convertGephi method to convert gephi into vis.network format and use the normal data format with nodes and edges. This converter is used like this: var data = vis.network.convertGephi(gephiJson);');\n var gephiData = gephiParser.parseGephi(data.gephi);\n this.setData(gephiData);\n return;\n } else {\n this.nodesHandler.setData(data && data.nodes, true);\n this.edgesHandler.setData(data && data.edges, true);\n }\n\n // emit change in data\n this.body.emitter.emit(\"_dataChanged\");\n\n // emit data loaded\n this.body.emitter.emit(\"_dataLoaded\");\n\n // find a stable position or start animating to a stable position\n this.body.emitter.emit(\"initPhysics\");\n };\n\n /**\n * Cleans up all bindings of the network, removing it fully from the memory IF the variable is set to null after calling this function.\n * var network = new vis.Network(..);\n * network.destroy();\n * network = null;\n */\n Network.prototype.destroy = function () {\n this.body.emitter.emit(\"destroy\");\n // clear events\n this.body.emitter.off();\n this.off();\n\n // delete modules\n delete this.groups;\n delete this.canvas;\n delete this.selectionHandler;\n delete this.interactionHandler;\n delete this.view;\n delete this.renderer;\n delete this.physics;\n delete this.layoutEngine;\n delete this.clustering;\n delete this.manipulation;\n delete this.nodesHandler;\n delete this.edgesHandler;\n delete this.configurator;\n delete this.images;\n\n for (var nodeId in this.body.nodes) {\n delete this.body.nodes[nodeId];\n }\n for (var edgeId in this.body.edges) {\n delete this.body.edges[edgeId];\n }\n\n // remove the container and everything inside it recursively\n util.recursiveDOMDelete(this.body.container);\n };\n\n /**\n * Update the values of all object in the given array according to the current\n * value range of the objects in the array.\n * @param {Object} obj An object containing a set of Edges or Nodes\n * The objects must have a method getValue() and\n * setValueRange(min, max).\n * @private\n */\n Network.prototype._updateValueRange = function (obj) {\n var id;\n\n // determine the range of the objects\n var valueMin = undefined;\n var valueMax = undefined;\n var valueTotal = 0;\n for (id in obj) {\n if (obj.hasOwnProperty(id)) {\n var value = obj[id].getValue();\n if (value !== undefined) {\n valueMin = valueMin === undefined ? value : Math.min(value, valueMin);\n valueMax = valueMax === undefined ? value : Math.max(value, valueMax);\n valueTotal += value;\n }\n }\n }\n\n // adjust the range of all objects\n if (valueMin !== undefined && valueMax !== undefined) {\n for (id in obj) {\n if (obj.hasOwnProperty(id)) {\n obj[id].setValueRange(valueMin, valueMax, valueTotal);\n }\n }\n }\n };\n\n /**\n * Returns true when the Network is active.\n * @returns {boolean}\n */\n Network.prototype.isActive = function () {\n return !this.activator || this.activator.active;\n };\n\n Network.prototype.setSize = function () {\n return this.canvas.setSize.apply(this.canvas, arguments);\n };\n Network.prototype.canvasToDOM = function () {\n return this.canvas.canvasToDOM.apply(this.canvas, arguments);\n };\n Network.prototype.DOMtoCanvas = function () {\n return this.canvas.DOMtoCanvas.apply(this.canvas, arguments);\n };\n Network.prototype.findNode = function () {\n return this.clustering.findNode.apply(this.clustering, arguments);\n };\n Network.prototype.isCluster = function () {\n return this.clustering.isCluster.apply(this.clustering, arguments);\n };\n Network.prototype.openCluster = function () {\n return this.clustering.openCluster.apply(this.clustering, arguments);\n };\n Network.prototype.cluster = function () {\n return this.clustering.cluster.apply(this.clustering, arguments);\n };\n Network.prototype.getNodesInCluster = function () {\n return this.clustering.getNodesInCluster.apply(this.clustering, arguments);\n };\n Network.prototype.clusterByConnection = function () {\n return this.clustering.clusterByConnection.apply(this.clustering, arguments);\n };\n Network.prototype.clusterByHubsize = function () {\n return this.clustering.clusterByHubsize.apply(this.clustering, arguments);\n };\n Network.prototype.clusterOutliers = function () {\n return this.clustering.clusterOutliers.apply(this.clustering, arguments);\n };\n Network.prototype.getSeed = function () {\n return this.layoutEngine.getSeed.apply(this.layoutEngine, arguments);\n };\n Network.prototype.enableEditMode = function () {\n return this.manipulation.enableEditMode.apply(this.manipulation, arguments);\n };\n Network.prototype.disableEditMode = function () {\n return this.manipulation.disableEditMode.apply(this.manipulation, arguments);\n };\n Network.prototype.addNodeMode = function () {\n return this.manipulation.addNodeMode.apply(this.manipulation, arguments);\n };\n Network.prototype.editNode = function () {\n return this.manipulation.editNode.apply(this.manipulation, arguments);\n };\n Network.prototype.editNodeMode = function () {\n console.log(\"Deprecated: Please use editNode instead of editNodeMode.\");return this.manipulation.editNode.apply(this.manipulation, arguments);\n };\n Network.prototype.addEdgeMode = function () {\n return this.manipulation.addEdgeMode.apply(this.manipulation, arguments);\n };\n Network.prototype.editEdgeMode = function () {\n return this.manipulation.editEdgeMode.apply(this.manipulation, arguments);\n };\n Network.prototype.deleteSelected = function () {\n return this.manipulation.deleteSelected.apply(this.manipulation, arguments);\n };\n Network.prototype.getPositions = function () {\n return this.nodesHandler.getPositions.apply(this.nodesHandler, arguments);\n };\n Network.prototype.storePositions = function () {\n return this.nodesHandler.storePositions.apply(this.nodesHandler, arguments);\n };\n Network.prototype.moveNode = function () {\n return this.nodesHandler.moveNode.apply(this.nodesHandler, arguments);\n };\n Network.prototype.getBoundingBox = function () {\n return this.nodesHandler.getBoundingBox.apply(this.nodesHandler, arguments);\n };\n Network.prototype.getConnectedNodes = function (objectId) {\n if (this.body.nodes[objectId] !== undefined) {\n return this.nodesHandler.getConnectedNodes.apply(this.nodesHandler, arguments);\n } else {\n return this.edgesHandler.getConnectedNodes.apply(this.edgesHandler, arguments);\n }\n };\n Network.prototype.getConnectedEdges = function () {\n return this.nodesHandler.getConnectedEdges.apply(this.nodesHandler, arguments);\n };\n Network.prototype.startSimulation = function () {\n return this.physics.startSimulation.apply(this.physics, arguments);\n };\n Network.prototype.stopSimulation = function () {\n return this.physics.stopSimulation.apply(this.physics, arguments);\n };\n Network.prototype.stabilize = function () {\n return this.physics.stabilize.apply(this.physics, arguments);\n };\n Network.prototype.getSelection = function () {\n return this.selectionHandler.getSelection.apply(this.selectionHandler, arguments);\n };\n Network.prototype.setSelection = function () {\n return this.selectionHandler.setSelection.apply(this.selectionHandler, arguments);\n };\n Network.prototype.getSelectedNodes = function () {\n return this.selectionHandler.getSelectedNodes.apply(this.selectionHandler, arguments);\n };\n Network.prototype.getSelectedEdges = function () {\n return this.selectionHandler.getSelectedEdges.apply(this.selectionHandler, arguments);\n };\n Network.prototype.getNodeAt = function () {\n var node = this.selectionHandler.getNodeAt.apply(this.selectionHandler, arguments);\n if (node !== undefined && node.id !== undefined) {\n return node.id;\n }\n return node;\n };\n Network.prototype.getEdgeAt = function () {\n var edge = this.selectionHandler.getEdgeAt.apply(this.selectionHandler, arguments);\n if (edge !== undefined && edge.id !== undefined) {\n return edge.id;\n }\n return edge;\n };\n Network.prototype.selectNodes = function () {\n return this.selectionHandler.selectNodes.apply(this.selectionHandler, arguments);\n };\n Network.prototype.selectEdges = function () {\n return this.selectionHandler.selectEdges.apply(this.selectionHandler, arguments);\n };\n Network.prototype.unselectAll = function () {\n this.selectionHandler.unselectAll.apply(this.selectionHandler, arguments);\n this.redraw();\n };\n Network.prototype.redraw = function () {\n return this.renderer.redraw.apply(this.renderer, arguments);\n };\n Network.prototype.getScale = function () {\n return this.view.getScale.apply(this.view, arguments);\n };\n Network.prototype.getViewPosition = function () {\n return this.view.getViewPosition.apply(this.view, arguments);\n };\n Network.prototype.fit = function () {\n return this.view.fit.apply(this.view, arguments);\n };\n Network.prototype.moveTo = function () {\n return this.view.moveTo.apply(this.view, arguments);\n };\n Network.prototype.focus = function () {\n return this.view.focus.apply(this.view, arguments);\n };\n Network.prototype.releaseNode = function () {\n return this.view.releaseNode.apply(this.view, arguments);\n };\n Network.prototype.getOptionsFromConfigurator = function () {\n var options = {};\n if (this.configurator) {\n options = this.configurator.getOptions.apply(this.configurator);\n }\n return options;\n };\n\n module.exports = Network;\n\n/***/ },\n/* 59 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var util = __webpack_require__(1);\n\n /**\n * @class Groups\n * This class can store groups and options specific for groups.\n */\n\n var Groups = (function () {\n function Groups() {\n _classCallCheck(this, Groups);\n\n this.clear();\n this.defaultIndex = 0;\n this.groupsArray = [];\n this.groupIndex = 0;\n\n this.defaultGroups = [{ border: \"#2B7CE9\", background: \"#97C2FC\", highlight: { border: \"#2B7CE9\", background: \"#D2E5FF\" }, hover: { border: \"#2B7CE9\", background: \"#D2E5FF\" } }, // 0: blue\n { border: \"#FFA500\", background: \"#FFFF00\", highlight: { border: \"#FFA500\", background: \"#FFFFA3\" }, hover: { border: \"#FFA500\", background: \"#FFFFA3\" } }, // 1: yellow\n { border: \"#FA0A10\", background: \"#FB7E81\", highlight: { border: \"#FA0A10\", background: \"#FFAFB1\" }, hover: { border: \"#FA0A10\", background: \"#FFAFB1\" } }, // 2: red\n { border: \"#41A906\", background: \"#7BE141\", highlight: { border: \"#41A906\", background: \"#A1EC76\" }, hover: { border: \"#41A906\", background: \"#A1EC76\" } }, // 3: green\n { border: \"#E129F0\", background: \"#EB7DF4\", highlight: { border: \"#E129F0\", background: \"#F0B3F5\" }, hover: { border: \"#E129F0\", background: \"#F0B3F5\" } }, // 4: magenta\n { border: \"#7C29F0\", background: \"#AD85E4\", highlight: { border: \"#7C29F0\", background: \"#D3BDF0\" }, hover: { border: \"#7C29F0\", background: \"#D3BDF0\" } }, // 5: purple\n { border: \"#C37F00\", background: \"#FFA807\", highlight: { border: \"#C37F00\", background: \"#FFCA66\" }, hover: { border: \"#C37F00\", background: \"#FFCA66\" } }, // 6: orange\n { border: \"#4220FB\", background: \"#6E6EFD\", highlight: { border: \"#4220FB\", background: \"#9B9BFD\" }, hover: { border: \"#4220FB\", background: \"#9B9BFD\" } }, // 7: darkblue\n { border: \"#FD5A77\", background: \"#FFC0CB\", highlight: { border: \"#FD5A77\", background: \"#FFD1D9\" }, hover: { border: \"#FD5A77\", background: \"#FFD1D9\" } }, // 8: pink\n { border: \"#4AD63A\", background: \"#C2FABC\", highlight: { border: \"#4AD63A\", background: \"#E6FFE3\" }, hover: { border: \"#4AD63A\", background: \"#E6FFE3\" } }, // 9: mint\n\n { border: \"#990000\", background: \"#EE0000\", highlight: { border: \"#BB0000\", background: \"#FF3333\" }, hover: { border: \"#BB0000\", background: \"#FF3333\" } }, // 10:bright red\n\n { border: \"#FF6000\", background: \"#FF6000\", highlight: { border: \"#FF6000\", background: \"#FF6000\" }, hover: { border: \"#FF6000\", background: \"#FF6000\" } }, // 12: real orange\n { border: \"#97C2FC\", background: \"#2B7CE9\", highlight: { border: \"#D2E5FF\", background: \"#2B7CE9\" }, hover: { border: \"#D2E5FF\", background: \"#2B7CE9\" } }, // 13: blue\n { border: \"#399605\", background: \"#255C03\", highlight: { border: \"#399605\", background: \"#255C03\" }, hover: { border: \"#399605\", background: \"#255C03\" } }, // 14: green\n { border: \"#B70054\", background: \"#FF007E\", highlight: { border: \"#B70054\", background: \"#FF007E\" }, hover: { border: \"#B70054\", background: \"#FF007E\" } }, // 15: magenta\n { border: \"#AD85E4\", background: \"#7C29F0\", highlight: { border: \"#D3BDF0\", background: \"#7C29F0\" }, hover: { border: \"#D3BDF0\", background: \"#7C29F0\" } }, // 16: purple\n { border: \"#4557FA\", background: \"#000EA1\", highlight: { border: \"#6E6EFD\", background: \"#000EA1\" }, hover: { border: \"#6E6EFD\", background: \"#000EA1\" } }, // 17: darkblue\n { border: \"#FFC0CB\", background: \"#FD5A77\", highlight: { border: \"#FFD1D9\", background: \"#FD5A77\" }, hover: { border: \"#FFD1D9\", background: \"#FD5A77\" } }, // 18: pink\n { border: \"#C2FABC\", background: \"#74D66A\", highlight: { border: \"#E6FFE3\", background: \"#74D66A\" }, hover: { border: \"#E6FFE3\", background: \"#74D66A\" } }, // 19: mint\n\n { border: \"#EE0000\", background: \"#990000\", highlight: { border: \"#FF3333\", background: \"#BB0000\" }, hover: { border: \"#FF3333\", background: \"#BB0000\" } } // 20:bright red\n ];\n\n this.options = {};\n this.defaultOptions = {\n useDefaultGroups: true\n };\n util.extend(this.options, this.defaultOptions);\n }\n\n _createClass(Groups, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n var optionFields = ['useDefaultGroups'];\n\n if (options !== undefined) {\n for (var groupName in options) {\n if (options.hasOwnProperty(groupName)) {\n if (optionFields.indexOf(groupName) === -1) {\n var group = options[groupName];\n this.add(groupName, group);\n }\n }\n }\n }\n }\n\n /**\n * Clear all groups\n */\n }, {\n key: \"clear\",\n value: function clear() {\n this.groups = {};\n this.groupsArray = [];\n }\n\n /**\n * get group options of a groupname. If groupname is not found, a new group\n * is added.\n * @param {*} groupname Can be a number, string, Date, etc.\n * @return {Object} group The created group, containing all group options\n */\n }, {\n key: \"get\",\n value: function get(groupname) {\n var group = this.groups[groupname];\n if (group === undefined) {\n if (this.options.useDefaultGroups === false && this.groupsArray.length > 0) {\n // create new group\n var index = this.groupIndex % this.groupsArray.length;\n this.groupIndex++;\n group = {};\n group.color = this.groups[this.groupsArray[index]];\n this.groups[groupname] = group;\n } else {\n // create new group\n var index = this.defaultIndex % this.defaultGroups.length;\n this.defaultIndex++;\n group = {};\n group.color = this.defaultGroups[index];\n this.groups[groupname] = group;\n }\n }\n\n return group;\n }\n\n /**\n * Add a custom group style\n * @param {String} groupName\n * @param {Object} style An object containing borderColor,\n * backgroundColor, etc.\n * @return {Object} group The created group object\n */\n }, {\n key: \"add\",\n value: function add(groupName, style) {\n this.groups[groupName] = style;\n this.groupsArray.push(groupName);\n return style;\n }\n }]);\n\n return Groups;\n })();\n\n exports[\"default\"] = Groups;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 60 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _componentsNode = __webpack_require__(61);\n\n var _componentsNode2 = _interopRequireDefault(_componentsNode);\n\n var _componentsSharedLabel = __webpack_require__(62);\n\n var _componentsSharedLabel2 = _interopRequireDefault(_componentsSharedLabel);\n\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n\n var NodesHandler = (function () {\n function NodesHandler(body, images, groups, layoutEngine) {\n var _this = this;\n\n _classCallCheck(this, NodesHandler);\n\n this.body = body;\n this.images = images;\n this.groups = groups;\n this.layoutEngine = layoutEngine;\n\n // create the node API in the body container\n this.body.functions.createNode = this.create.bind(this);\n\n this.nodesListeners = {\n add: function add(event, params) {\n _this.add(params.items);\n },\n update: function update(event, params) {\n _this.update(params.items, params.data);\n },\n remove: function remove(event, params) {\n _this.remove(params.items);\n }\n };\n\n this.options = {};\n this.defaultOptions = {\n borderWidth: 1,\n borderWidthSelected: 2,\n brokenImage: undefined,\n color: {\n border: '#2B7CE9',\n background: '#97C2FC',\n highlight: {\n border: '#2B7CE9',\n background: '#D2E5FF'\n },\n hover: {\n border: '#2B7CE9',\n background: '#D2E5FF'\n }\n },\n fixed: {\n x: false,\n y: false\n },\n font: {\n color: '#343434',\n size: 14, // px\n face: 'arial',\n background: 'none',\n strokeWidth: 0, // px\n strokeColor: '#ffffff',\n align: 'horizontal'\n },\n group: undefined,\n hidden: false,\n icon: {\n face: 'FontAwesome', //'FontAwesome',\n code: undefined, //'\\uf007',\n size: 50, //50,\n color: '#2B7CE9' //'#aa00ff'\n },\n image: undefined, // --> URL\n label: undefined,\n labelHighlightBold: true,\n level: undefined,\n mass: 1,\n physics: true,\n scaling: {\n min: 10,\n max: 30,\n label: {\n enabled: false,\n min: 14,\n max: 30,\n maxVisible: 30,\n drawThreshold: 5\n },\n customScalingFunction: function customScalingFunction(min, max, total, value) {\n if (max === min) {\n return 0.5;\n } else {\n var scale = 1 / (max - min);\n return Math.max(0, (value - min) * scale);\n }\n }\n },\n shadow: {\n enabled: false,\n color: 'rgba(0,0,0,0.5)',\n size: 10,\n x: 5,\n y: 5\n },\n shape: 'ellipse',\n shapeProperties: {\n borderDashes: false, // only for borders\n borderRadius: 6, // only for box shape\n useImageSize: false, // only for image and circularImage shapes\n useBorderWithImage: false // only for image shape\n },\n size: 25,\n title: undefined,\n value: undefined,\n x: undefined,\n y: undefined\n };\n util.extend(this.options, this.defaultOptions);\n\n this.bindEventListeners();\n }\n\n _createClass(NodesHandler, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this2 = this;\n\n // refresh the nodes. Used when reverting from hierarchical layout\n this.body.emitter.on('refreshNodes', this.refresh.bind(this));\n this.body.emitter.on('refresh', this.refresh.bind(this));\n this.body.emitter.on('destroy', function () {\n util.forEach(_this2.nodesListeners, function (callback, event) {\n if (_this2.body.data.nodes) _this2.body.data.nodes.off(event, callback);\n });\n delete _this2.body.functions.createNode;\n delete _this2.nodesListeners.add;\n delete _this2.nodesListeners.update;\n delete _this2.nodesListeners.remove;\n delete _this2.nodesListeners;\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n _componentsNode2['default'].parseOptions(this.options, options);\n\n // update the shape in all nodes\n if (options.shape !== undefined) {\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n this.body.nodes[nodeId].updateShape();\n }\n }\n }\n\n // update the font in all nodes\n if (options.font !== undefined) {\n _componentsSharedLabel2['default'].parseOptions(this.options.font, options);\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n this.body.nodes[nodeId].updateLabelModule();\n this.body.nodes[nodeId]._reset();\n }\n }\n }\n\n // update the shape size in all nodes\n if (options.size !== undefined) {\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n this.body.nodes[nodeId]._reset();\n }\n }\n }\n\n // update the state of the letiables if needed\n if (options.hidden !== undefined || options.physics !== undefined) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n }\n\n /**\n * Set a data set with nodes for the network\n * @param {Array | DataSet | DataView} nodes The data containing the nodes.\n * @private\n */\n }, {\n key: 'setData',\n value: function setData(nodes) {\n var _this3 = this;\n\n var doNotEmit = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var oldNodesData = this.body.data.nodes;\n\n if (nodes instanceof DataSet || nodes instanceof DataView) {\n this.body.data.nodes = nodes;\n } else if (Array.isArray(nodes)) {\n this.body.data.nodes = new DataSet();\n this.body.data.nodes.add(nodes);\n } else if (!nodes) {\n this.body.data.nodes = new DataSet();\n } else {\n throw new TypeError('Array or DataSet expected');\n }\n\n if (oldNodesData) {\n // unsubscribe from old dataset\n util.forEach(this.nodesListeners, function (callback, event) {\n oldNodesData.off(event, callback);\n });\n }\n\n // remove drawn nodes\n this.body.nodes = {};\n\n if (this.body.data.nodes) {\n (function () {\n // subscribe to new dataset\n var me = _this3;\n util.forEach(_this3.nodesListeners, function (callback, event) {\n me.body.data.nodes.on(event, callback);\n });\n\n // draw all new nodes\n var ids = _this3.body.data.nodes.getIds();\n _this3.add(ids, true);\n })();\n }\n\n if (doNotEmit === false) {\n this.body.emitter.emit(\"_dataChanged\");\n }\n }\n\n /**\n * Add nodes\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'add',\n value: function add(ids) {\n var doNotEmit = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var id = undefined;\n var newNodes = [];\n for (var i = 0; i < ids.length; i++) {\n id = ids[i];\n var properties = this.body.data.nodes.get(id);\n var node = this.create(properties);\n newNodes.push(node);\n this.body.nodes[id] = node; // note: this may replace an existing node\n }\n\n this.layoutEngine.positionInitially(newNodes);\n\n if (doNotEmit === false) {\n this.body.emitter.emit(\"_dataChanged\");\n }\n }\n\n /**\n * Update existing nodes, or create them when not yet existing\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'update',\n value: function update(ids, changedData) {\n var nodes = this.body.nodes;\n var dataChanged = false;\n for (var i = 0; i < ids.length; i++) {\n var id = ids[i];\n var node = nodes[id];\n var data = changedData[i];\n if (node !== undefined) {\n // update node\n dataChanged = node.setOptions(data);\n } else {\n dataChanged = true;\n // create node\n node = this.create(data);\n nodes[id] = node;\n }\n }\n if (dataChanged === true) {\n this.body.emitter.emit(\"_dataChanged\");\n } else {\n this.body.emitter.emit(\"_dataUpdated\");\n }\n }\n\n /**\n * Remove existing nodes. If nodes do not exist, the method will just ignore it.\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'remove',\n value: function remove(ids) {\n var nodes = this.body.nodes;\n\n for (var i = 0; i < ids.length; i++) {\n var id = ids[i];\n delete nodes[id];\n }\n\n this.body.emitter.emit(\"_dataChanged\");\n }\n\n /**\n * create a node\n * @param properties\n * @param constructorClass\n */\n }, {\n key: 'create',\n value: function create(properties) {\n var constructorClass = arguments.length <= 1 || arguments[1] === undefined ? _componentsNode2['default'] : arguments[1];\n\n return new constructorClass(properties, this.body, this.images, this.groups, this.options);\n }\n }, {\n key: 'refresh',\n value: function refresh() {\n var clearPositions = arguments.length <= 0 || arguments[0] === undefined ? false : arguments[0];\n\n var nodes = this.body.nodes;\n for (var nodeId in nodes) {\n var node = undefined;\n if (nodes.hasOwnProperty(nodeId)) {\n node = nodes[nodeId];\n }\n var data = this.body.data.nodes._data[nodeId];\n if (node !== undefined && data !== undefined) {\n if (clearPositions === true) {\n node.setOptions({ x: null, y: null });\n }\n node.setOptions({ fixed: false });\n node.setOptions(data);\n }\n }\n }\n\n /**\n * Returns the positions of the nodes.\n * @param ids --> optional, can be array of nodeIds, can be string\n * @returns {{}}\n */\n }, {\n key: 'getPositions',\n value: function getPositions(ids) {\n var dataArray = {};\n if (ids !== undefined) {\n if (Array.isArray(ids) === true) {\n for (var i = 0; i < ids.length; i++) {\n if (this.body.nodes[ids[i]] !== undefined) {\n var node = this.body.nodes[ids[i]];\n dataArray[ids[i]] = { x: Math.round(node.x), y: Math.round(node.y) };\n }\n }\n } else {\n if (this.body.nodes[ids] !== undefined) {\n var node = this.body.nodes[ids];\n dataArray[ids] = { x: Math.round(node.x), y: Math.round(node.y) };\n }\n }\n } else {\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var node = this.body.nodes[this.body.nodeIndices[i]];\n dataArray[this.body.nodeIndices[i]] = { x: Math.round(node.x), y: Math.round(node.y) };\n }\n }\n return dataArray;\n }\n\n /**\n * Load the XY positions of the nodes into the dataset.\n */\n }, {\n key: 'storePositions',\n value: function storePositions() {\n // todo: add support for clusters and hierarchical.\n var dataArray = [];\n var dataset = this.body.data.nodes.getDataSet();\n\n for (var nodeId in dataset._data) {\n if (dataset._data.hasOwnProperty(nodeId)) {\n var node = this.body.nodes[nodeId];\n if (dataset._data[nodeId].x != Math.round(node.x) || dataset._data[nodeId].y != Math.round(node.y)) {\n dataArray.push({ id: node.id, x: Math.round(node.x), y: Math.round(node.y) });\n }\n }\n }\n dataset.update(dataArray);\n }\n\n /**\n * get the bounding box of a node.\n * @param nodeId\n * @returns {j|*}\n */\n }, {\n key: 'getBoundingBox',\n value: function getBoundingBox(nodeId) {\n if (this.body.nodes[nodeId] !== undefined) {\n return this.body.nodes[nodeId].shape.boundingBox;\n }\n }\n\n /**\n * Get the Ids of nodes connected to this node.\n * @param nodeId\n * @returns {Array}\n */\n }, {\n key: 'getConnectedNodes',\n value: function getConnectedNodes(nodeId) {\n var nodeList = [];\n if (this.body.nodes[nodeId] !== undefined) {\n var node = this.body.nodes[nodeId];\n var nodeObj = {}; // used to quickly check if node already exists\n for (var i = 0; i < node.edges.length; i++) {\n var edge = node.edges[i];\n if (edge.toId == node.id) {\n // these are double equals since ids can be numeric or string\n if (nodeObj[edge.fromId] === undefined) {\n nodeList.push(edge.fromId);\n nodeObj[edge.fromId] = true;\n }\n } else if (edge.fromId == node.id) {\n // these are double equals since ids can be numeric or string\n if (nodeObj[edge.toId] === undefined) {\n nodeList.push(edge.toId);\n nodeObj[edge.toId] = true;\n }\n }\n }\n }\n return nodeList;\n }\n\n /**\n * Get the ids of the edges connected to this node.\n * @param nodeId\n * @returns {*}\n */\n }, {\n key: 'getConnectedEdges',\n value: function getConnectedEdges(nodeId) {\n var edgeList = [];\n if (this.body.nodes[nodeId] !== undefined) {\n var node = this.body.nodes[nodeId];\n for (var i = 0; i < node.edges.length; i++) {\n edgeList.push(node.edges[i].id);\n }\n } else {\n console.log(\"NodeId provided for getConnectedEdges does not exist. Provided: \", nodeId);\n }\n return edgeList;\n }\n\n /**\n * Move a node.\n * @param String nodeId\n * @param Number x\n * @param Number y\n */\n }, {\n key: 'moveNode',\n value: function moveNode(nodeId, x, y) {\n var _this4 = this;\n\n if (this.body.nodes[nodeId] !== undefined) {\n this.body.nodes[nodeId].x = Number(x);\n this.body.nodes[nodeId].y = Number(y);\n setTimeout(function () {\n _this4.body.emitter.emit(\"startSimulation\");\n }, 0);\n } else {\n console.log(\"Node id supplied to moveNode does not exist. Provided: \", nodeId);\n }\n }\n }]);\n\n return NodesHandler;\n })();\n\n exports['default'] = NodesHandler;\n module.exports = exports['default'];\n\n/***/ },\n/* 61 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _sharedLabel = __webpack_require__(62);\n\n var _sharedLabel2 = _interopRequireDefault(_sharedLabel);\n\n var _nodesShapesBox = __webpack_require__(63);\n\n var _nodesShapesBox2 = _interopRequireDefault(_nodesShapesBox);\n\n var _nodesShapesCircle = __webpack_require__(65);\n\n var _nodesShapesCircle2 = _interopRequireDefault(_nodesShapesCircle);\n\n var _nodesShapesCircularImage = __webpack_require__(67);\n\n var _nodesShapesCircularImage2 = _interopRequireDefault(_nodesShapesCircularImage);\n\n var _nodesShapesDatabase = __webpack_require__(68);\n\n var _nodesShapesDatabase2 = _interopRequireDefault(_nodesShapesDatabase);\n\n var _nodesShapesDiamond = __webpack_require__(69);\n\n var _nodesShapesDiamond2 = _interopRequireDefault(_nodesShapesDiamond);\n\n var _nodesShapesDot = __webpack_require__(71);\n\n var _nodesShapesDot2 = _interopRequireDefault(_nodesShapesDot);\n\n var _nodesShapesEllipse = __webpack_require__(72);\n\n var _nodesShapesEllipse2 = _interopRequireDefault(_nodesShapesEllipse);\n\n var _nodesShapesIcon = __webpack_require__(73);\n\n var _nodesShapesIcon2 = _interopRequireDefault(_nodesShapesIcon);\n\n var _nodesShapesImage = __webpack_require__(74);\n\n var _nodesShapesImage2 = _interopRequireDefault(_nodesShapesImage);\n\n var _nodesShapesSquare = __webpack_require__(75);\n\n var _nodesShapesSquare2 = _interopRequireDefault(_nodesShapesSquare);\n\n var _nodesShapesStar = __webpack_require__(76);\n\n var _nodesShapesStar2 = _interopRequireDefault(_nodesShapesStar);\n\n var _nodesShapesText = __webpack_require__(77);\n\n var _nodesShapesText2 = _interopRequireDefault(_nodesShapesText);\n\n var _nodesShapesTriangle = __webpack_require__(78);\n\n var _nodesShapesTriangle2 = _interopRequireDefault(_nodesShapesTriangle);\n\n var _nodesShapesTriangleDown = __webpack_require__(79);\n\n var _nodesShapesTriangleDown2 = _interopRequireDefault(_nodesShapesTriangleDown);\n\n var _sharedValidator = __webpack_require__(46);\n\n var _sharedValidator2 = _interopRequireDefault(_sharedValidator);\n\n var util = __webpack_require__(1);\n\n /**\n * @class Node\n * A node. A node can be connected to other nodes via one or multiple edges.\n * @param {object} options An object containing options for the node. All\n * options are optional, except for the id.\n * {number} id Id of the node. Required\n * {string} label Text label for the node\n * {number} x Horizontal position of the node\n * {number} y Vertical position of the node\n * {string} shape Node shape, available:\n * \"database\", \"circle\", \"ellipse\",\n * \"box\", \"image\", \"text\", \"dot\",\n * \"star\", \"triangle\", \"triangleDown\",\n * \"square\", \"icon\"\n * {string} image An image url\n * {string} title An title text, can be HTML\n * {anytype} group A group name or number\n * @param {Network.Images} imagelist A list with images. Only needed\n * when the node has an image\n * @param {Network.Groups} grouplist A list with groups. Needed for\n * retrieving group options\n * @param {Object} constants An object with default values for\n * example for the color\n *\n */\n\n var Node = (function () {\n function Node(options, body, imagelist, grouplist, globalOptions) {\n _classCallCheck(this, Node);\n\n this.options = util.bridgeObject(globalOptions);\n this.globalOptions = globalOptions;\n this.body = body;\n\n this.edges = []; // all edges connected to this node\n\n // set defaults for the options\n this.id = undefined;\n this.imagelist = imagelist;\n this.grouplist = grouplist;\n\n // state options\n this.x = undefined;\n this.y = undefined;\n this.baseSize = this.options.size;\n this.baseFontSize = this.options.font.size;\n this.predefinedPosition = false; // used to check if initial fit should just take the range or approximate\n this.selected = false;\n this.hover = false;\n\n this.labelModule = new _sharedLabel2['default'](this.body, this.options);\n this.setOptions(options);\n }\n\n /**\n * Attach a edge to the node\n * @param {Edge} edge\n */\n\n _createClass(Node, [{\n key: 'attachEdge',\n value: function attachEdge(edge) {\n if (this.edges.indexOf(edge) === -1) {\n this.edges.push(edge);\n }\n }\n\n /**\n * Detach a edge from the node\n * @param {Edge} edge\n */\n }, {\n key: 'detachEdge',\n value: function detachEdge(edge) {\n var index = this.edges.indexOf(edge);\n if (index != -1) {\n this.edges.splice(index, 1);\n }\n }\n\n /**\n * Set or overwrite options for the node\n * @param {Object} options an object with options\n * @param {Object} constants and object with default, global options\n */\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n var currentShape = this.options.shape;\n if (!options) {\n return;\n }\n // basic options\n if (options.id !== undefined) {\n this.id = options.id;\n }\n\n if (this.id === undefined) {\n throw \"Node must have an id\";\n }\n\n // set these options locally\n // clear x and y positions\n if (options.x !== undefined) {\n if (options.x === null) {\n this.x = undefined;this.predefinedPosition = false;\n } else {\n this.x = parseInt(options.x);this.predefinedPosition = true;\n }\n }\n if (options.y !== undefined) {\n if (options.y === null) {\n this.y = undefined;this.predefinedPosition = false;\n } else {\n this.y = parseInt(options.y);this.predefinedPosition = true;\n }\n }\n if (options.size !== undefined) {\n this.baseSize = options.size;\n }\n if (options.value !== undefined) {\n options.value = parseFloat(options.value);\n }\n\n // copy group options\n if (typeof options.group === 'number' || typeof options.group === 'string' && options.group != '') {\n var groupObj = this.grouplist.get(options.group);\n util.deepExtend(this.options, groupObj);\n // the color object needs to be completely defined. Since groups can partially overwrite the colors, we parse it again, just in case.\n this.options.color = util.parseColor(this.options.color);\n }\n\n // this transforms all shorthands into fully defined options\n Node.parseOptions(this.options, options, true, this.globalOptions);\n\n // load the images\n if (this.options.image !== undefined) {\n if (this.imagelist) {\n this.imageObj = this.imagelist.load(this.options.image, this.options.brokenImage, this.id);\n } else {\n throw \"No imagelist provided\";\n }\n }\n\n this.updateLabelModule();\n this.updateShape(currentShape);\n\n if (options.hidden !== undefined || options.physics !== undefined) {\n return true;\n }\n return false;\n }\n\n /**\n * This process all possible shorthands in the new options and makes sure that the parentOptions are fully defined.\n * Static so it can also be used by the handler.\n * @param parentOptions\n * @param newOptions\n * @param allowDeletion\n * @param globalOptions\n */\n }, {\n key: 'updateLabelModule',\n value: function updateLabelModule() {\n if (this.options.label === undefined || this.options.label === null) {\n this.options.label = '';\n }\n this.labelModule.setOptions(this.options, true);\n if (this.labelModule.baseSize !== undefined) {\n this.baseFontSize = this.labelModule.baseSize;\n }\n }\n }, {\n key: 'updateShape',\n value: function updateShape(currentShape) {\n if (currentShape === this.options.shape && this.shape) {\n this.shape.setOptions(this.options, this.imageObj);\n } else {\n // choose draw method depending on the shape\n switch (this.options.shape) {\n case 'box':\n this.shape = new _nodesShapesBox2['default'](this.options, this.body, this.labelModule);\n break;\n case 'circle':\n this.shape = new _nodesShapesCircle2['default'](this.options, this.body, this.labelModule);\n break;\n case 'circularImage':\n this.shape = new _nodesShapesCircularImage2['default'](this.options, this.body, this.labelModule, this.imageObj);\n break;\n case 'database':\n this.shape = new _nodesShapesDatabase2['default'](this.options, this.body, this.labelModule);\n break;\n case 'diamond':\n this.shape = new _nodesShapesDiamond2['default'](this.options, this.body, this.labelModule);\n break;\n case 'dot':\n this.shape = new _nodesShapesDot2['default'](this.options, this.body, this.labelModule);\n break;\n case 'ellipse':\n this.shape = new _nodesShapesEllipse2['default'](this.options, this.body, this.labelModule);\n break;\n case 'icon':\n this.shape = new _nodesShapesIcon2['default'](this.options, this.body, this.labelModule);\n break;\n case 'image':\n this.shape = new _nodesShapesImage2['default'](this.options, this.body, this.labelModule, this.imageObj);\n break;\n case 'square':\n this.shape = new _nodesShapesSquare2['default'](this.options, this.body, this.labelModule);\n break;\n case 'star':\n this.shape = new _nodesShapesStar2['default'](this.options, this.body, this.labelModule);\n break;\n case 'text':\n this.shape = new _nodesShapesText2['default'](this.options, this.body, this.labelModule);\n break;\n case 'triangle':\n this.shape = new _nodesShapesTriangle2['default'](this.options, this.body, this.labelModule);\n break;\n case 'triangleDown':\n this.shape = new _nodesShapesTriangleDown2['default'](this.options, this.body, this.labelModule);\n break;\n default:\n this.shape = new _nodesShapesEllipse2['default'](this.options, this.body, this.labelModule);\n break;\n }\n }\n this._reset();\n }\n\n /**\n * select this node\n */\n }, {\n key: 'select',\n value: function select() {\n this.selected = true;\n this._reset();\n }\n\n /**\n * unselect this node\n */\n }, {\n key: 'unselect',\n value: function unselect() {\n this.selected = false;\n this._reset();\n }\n\n /**\n * Reset the calculated size of the node, forces it to recalculate its size\n * @private\n */\n }, {\n key: '_reset',\n value: function _reset() {\n this.shape.width = undefined;\n this.shape.height = undefined;\n }\n\n /**\n * get the title of this node.\n * @return {string} title The title of the node, or undefined when no title\n * has been set.\n */\n }, {\n key: 'getTitle',\n value: function getTitle() {\n return this.options.title;\n }\n\n /**\n * Calculate the distance to the border of the Node\n * @param {CanvasRenderingContext2D} ctx\n * @param {Number} angle Angle in radians\n * @returns {number} distance Distance to the border in pixels\n */\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this.shape.distanceToBorder(ctx, angle);\n }\n\n /**\n * Check if this node has a fixed x and y position\n * @return {boolean} true if fixed, false if not\n */\n }, {\n key: 'isFixed',\n value: function isFixed() {\n return this.options.fixed.x && this.options.fixed.y;\n }\n\n /**\n * check if this node is selecte\n * @return {boolean} selected True if node is selected, else false\n */\n }, {\n key: 'isSelected',\n value: function isSelected() {\n return this.selected;\n }\n\n /**\n * Retrieve the value of the node. Can be undefined\n * @return {Number} value\n */\n }, {\n key: 'getValue',\n value: function getValue() {\n return this.options.value;\n }\n\n /**\n * Adjust the value range of the node. The node will adjust it's size\n * based on its value.\n * @param {Number} min\n * @param {Number} max\n */\n }, {\n key: 'setValueRange',\n value: function setValueRange(min, max, total) {\n if (this.options.value !== undefined) {\n var scale = this.options.scaling.customScalingFunction(min, max, total, this.options.value);\n var sizeDiff = this.options.scaling.max - this.options.scaling.min;\n if (this.options.scaling.label.enabled === true) {\n var fontDiff = this.options.scaling.label.max - this.options.scaling.label.min;\n this.options.font.size = this.options.scaling.label.min + scale * fontDiff;\n }\n this.options.size = this.options.scaling.min + scale * sizeDiff;\n } else {\n this.options.size = this.baseSize;\n this.options.font.size = this.baseFontSize;\n }\n\n this.updateLabelModule();\n }\n\n /**\n * Draw this node in the given canvas\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext(\"2d\");\n * @param {CanvasRenderingContext2D} ctx\n */\n }, {\n key: 'draw',\n value: function draw(ctx) {\n this.shape.draw(ctx, this.x, this.y, this.selected, this.hover);\n }\n\n /**\n * Update the bounding box of the shape\n */\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(ctx) {\n this.shape.updateBoundingBox(this.x, this.y, ctx);\n }\n\n /**\n * Recalculate the size of this node in the given canvas\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext(\"2d\");\n * @param {CanvasRenderingContext2D} ctx\n */\n }, {\n key: 'resize',\n value: function resize(ctx) {\n this.shape.resize(ctx, this.selected);\n }\n\n /**\n * Check if this object is overlapping with the provided object\n * @param {Object} obj an object with parameters left, top, right, bottom\n * @return {boolean} True if location is located on node\n */\n }, {\n key: 'isOverlappingWith',\n value: function isOverlappingWith(obj) {\n return this.shape.left < obj.right && this.shape.left + this.shape.width > obj.left && this.shape.top < obj.bottom && this.shape.top + this.shape.height > obj.top;\n }\n\n /**\n * Check if this object is overlapping with the provided object\n * @param {Object} obj an object with parameters left, top, right, bottom\n * @return {boolean} True if location is located on node\n */\n }, {\n key: 'isBoundingBoxOverlappingWith',\n value: function isBoundingBoxOverlappingWith(obj) {\n return this.shape.boundingBox.left < obj.right && this.shape.boundingBox.right > obj.left && this.shape.boundingBox.top < obj.bottom && this.shape.boundingBox.bottom > obj.top;\n }\n }], [{\n key: 'parseOptions',\n value: function parseOptions(parentOptions, newOptions) {\n var allowDeletion = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n var globalOptions = arguments.length <= 3 || arguments[3] === undefined ? {} : arguments[3];\n\n var fields = ['color', 'font', 'fixed', 'shadow'];\n util.selectiveNotDeepExtend(fields, parentOptions, newOptions, allowDeletion);\n\n // merge the shadow options into the parent.\n util.mergeOptions(parentOptions, newOptions, 'shadow', allowDeletion, globalOptions);\n\n // individual shape newOptions\n if (newOptions.color !== undefined && newOptions.color !== null) {\n var parsedColor = util.parseColor(newOptions.color);\n util.fillIfDefined(parentOptions.color, parsedColor);\n } else if (allowDeletion === true && newOptions.color === null) {\n parentOptions.color = util.bridgeObject(globalOptions.color); // set the object back to the global options\n }\n\n // handle the fixed options\n if (newOptions.fixed !== undefined && newOptions.fixed !== null) {\n if (typeof newOptions.fixed === 'boolean') {\n parentOptions.fixed.x = newOptions.fixed;\n parentOptions.fixed.y = newOptions.fixed;\n } else {\n if (newOptions.fixed.x !== undefined && typeof newOptions.fixed.x === 'boolean') {\n parentOptions.fixed.x = newOptions.fixed.x;\n }\n if (newOptions.fixed.y !== undefined && typeof newOptions.fixed.y === 'boolean') {\n parentOptions.fixed.y = newOptions.fixed.y;\n }\n }\n }\n\n // handle the font options\n if (newOptions.font !== undefined && newOptions.font !== null) {\n _sharedLabel2['default'].parseOptions(parentOptions.font, newOptions);\n } else if (allowDeletion === true && newOptions.font === null) {\n parentOptions.font = util.bridgeObject(globalOptions.font); // set the object back to the global options\n }\n\n // handle the scaling options, specifically the label part\n if (newOptions.scaling !== undefined) {\n util.mergeOptions(parentOptions.scaling, newOptions.scaling, 'label', allowDeletion, globalOptions.scaling);\n }\n }\n }]);\n\n return Node;\n })();\n\n exports['default'] = Node;\n module.exports = exports['default'];\n\n/***/ },\n/* 62 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _slicedToArray = (function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i['return']) _i['return'](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError('Invalid attempt to destructure non-iterable instance'); } }; })();\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var util = __webpack_require__(1);\n\n var Label = (function () {\n function Label(body, options) {\n _classCallCheck(this, Label);\n\n this.body = body;\n\n this.pointToSelf = false;\n this.baseSize = undefined;\n this.fontOptions = {};\n this.setOptions(options);\n this.size = { top: 0, left: 0, width: 0, height: 0, yLine: 0 }; // could be cached\n }\n\n _createClass(Label, [{\n key: 'setOptions',\n value: function setOptions(options) {\n var allowDeletion = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n this.nodeOptions = options;\n\n // We want to keep the font options seperated from the node options.\n // The node options have to mirror the globals when they are not overruled.\n this.fontOptions = util.deepExtend({}, options.font, true);\n\n if (options.label !== undefined) {\n this.labelDirty = true;\n }\n\n if (options.font !== undefined) {\n Label.parseOptions(this.fontOptions, options, allowDeletion);\n if (typeof options.font === 'string') {\n this.baseSize = this.fontOptions.size;\n } else if (typeof options.font === 'object') {\n if (options.font.size !== undefined) {\n this.baseSize = options.font.size;\n }\n }\n }\n }\n }, {\n key: 'draw',\n\n /**\n * Main function. This is called from anything that wants to draw a label.\n * @param ctx\n * @param x\n * @param y\n * @param selected\n * @param baseline\n */\n value: function draw(ctx, x, y, selected) {\n var baseline = arguments.length <= 4 || arguments[4] === undefined ? 'middle' : arguments[4];\n\n // if no label, return\n if (this.nodeOptions.label === undefined) return;\n\n // check if we have to render the label\n var viewFontSize = this.fontOptions.size * this.body.view.scale;\n if (this.nodeOptions.label && viewFontSize < this.nodeOptions.scaling.label.drawThreshold - 1) return;\n\n // update the size cache if required\n this.calculateLabelSize(ctx, selected, x, y, baseline);\n\n // create the fontfill background\n this._drawBackground(ctx);\n // draw text\n this._drawText(ctx, selected, x, y, baseline);\n }\n\n /**\n * Draws the label background\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n }, {\n key: '_drawBackground',\n value: function _drawBackground(ctx) {\n if (this.fontOptions.background !== undefined && this.fontOptions.background !== \"none\") {\n ctx.fillStyle = this.fontOptions.background;\n\n var lineMargin = 2;\n\n switch (this.fontOptions.align) {\n case 'middle':\n ctx.fillRect(-this.size.width * 0.5, -this.size.height * 0.5, this.size.width, this.size.height);\n break;\n case 'top':\n ctx.fillRect(-this.size.width * 0.5, -(this.size.height + lineMargin), this.size.width, this.size.height);\n break;\n case 'bottom':\n ctx.fillRect(-this.size.width * 0.5, lineMargin, this.size.width, this.size.height);\n break;\n default:\n ctx.fillRect(this.size.left, this.size.top - 0.5 * lineMargin, this.size.width, this.size.height);\n break;\n }\n }\n }\n\n /**\n *\n * @param ctx\n * @param x\n * @param baseline\n * @private\n */\n }, {\n key: '_drawText',\n value: function _drawText(ctx, selected, x, y) {\n var baseline = arguments.length <= 4 || arguments[4] === undefined ? 'middle' : arguments[4];\n\n var fontSize = this.fontOptions.size;\n var viewFontSize = fontSize * this.body.view.scale;\n // this ensures that there will not be HUGE letters on screen by setting an upper limit on the visible text size (regardless of zoomLevel)\n if (viewFontSize >= this.nodeOptions.scaling.label.maxVisible) {\n fontSize = Number(this.nodeOptions.scaling.label.maxVisible) / this.body.view.scale;\n }\n\n var yLine = this.size.yLine;\n\n var _getColor2 = this._getColor(viewFontSize);\n\n var _getColor22 = _slicedToArray(_getColor2, 2);\n\n var fontColor = _getColor22[0];\n var strokeColor = _getColor22[1];\n\n // configure context for drawing the text\n\n var _setAlignment2 = this._setAlignment(ctx, x, yLine, baseline);\n\n var _setAlignment22 = _slicedToArray(_setAlignment2, 2);\n\n x = _setAlignment22[0];\n yLine = _setAlignment22[1];\n ctx.font = (selected && this.nodeOptions.labelHighlightBold ? 'bold ' : '') + fontSize + \"px \" + this.fontOptions.face;\n ctx.fillStyle = fontColor;\n ctx.textAlign = 'center';\n\n // set the strokeWidth\n if (this.fontOptions.strokeWidth > 0) {\n ctx.lineWidth = this.fontOptions.strokeWidth;\n ctx.strokeStyle = strokeColor;\n ctx.lineJoin = 'round';\n }\n\n // draw the text\n for (var i = 0; i < this.lineCount; i++) {\n if (this.fontOptions.strokeWidth > 0) {\n ctx.strokeText(this.lines[i], x, yLine);\n }\n ctx.fillText(this.lines[i], x, yLine);\n yLine += fontSize;\n }\n }\n }, {\n key: '_setAlignment',\n value: function _setAlignment(ctx, x, yLine, baseline) {\n // check for label alignment (for edges)\n // TODO: make alignment for nodes\n if (this.fontOptions.align !== 'horizontal' && this.pointToSelf === false) {\n x = 0;\n yLine = 0;\n\n var lineMargin = 2;\n if (this.fontOptions.align === 'top') {\n ctx.textBaseline = 'alphabetic';\n yLine -= 2 * lineMargin; // distance from edge, required because we use alphabetic. Alphabetic has less difference between browsers\n } else if (this.fontOptions.align === 'bottom') {\n ctx.textBaseline = 'hanging';\n yLine += 2 * lineMargin; // distance from edge, required because we use hanging. Hanging has less difference between browsers\n } else {\n ctx.textBaseline = 'middle';\n }\n } else {\n ctx.textBaseline = baseline;\n }\n\n return [x, yLine];\n }\n\n /**\n * fade in when relative scale is between threshold and threshold - 1.\n * If the relative scale would be smaller than threshold -1 the draw function would have returned before coming here.\n *\n * @param viewFontSize\n * @returns {*[]}\n * @private\n */\n }, {\n key: '_getColor',\n value: function _getColor(viewFontSize) {\n var fontColor = this.fontOptions.color || '#000000';\n var strokeColor = this.fontOptions.strokeColor || '#ffffff';\n if (viewFontSize <= this.nodeOptions.scaling.label.drawThreshold) {\n var opacity = Math.max(0, Math.min(1, 1 - (this.nodeOptions.scaling.label.drawThreshold - viewFontSize)));\n fontColor = util.overrideOpacity(fontColor, opacity);\n strokeColor = util.overrideOpacity(strokeColor, opacity);\n }\n return [fontColor, strokeColor];\n }\n\n /**\n *\n * @param ctx\n * @param selected\n * @returns {{width: number, height: number}}\n */\n }, {\n key: 'getTextSize',\n value: function getTextSize(ctx) {\n var selected = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var size = {\n width: this._processLabel(ctx, selected),\n height: this.fontOptions.size * this.lineCount,\n lineCount: this.lineCount\n };\n return size;\n }\n\n /**\n *\n * @param ctx\n * @param selected\n * @param x\n * @param y\n * @param baseline\n */\n }, {\n key: 'calculateLabelSize',\n value: function calculateLabelSize(ctx, selected) {\n var x = arguments.length <= 2 || arguments[2] === undefined ? 0 : arguments[2];\n var y = arguments.length <= 3 || arguments[3] === undefined ? 0 : arguments[3];\n var baseline = arguments.length <= 4 || arguments[4] === undefined ? 'middle' : arguments[4];\n\n if (this.labelDirty === true) {\n this.size.width = this._processLabel(ctx, selected);\n }\n this.size.height = this.fontOptions.size * this.lineCount;\n this.size.left = x - this.size.width * 0.5;\n this.size.top = y - this.size.height * 0.5;\n this.size.yLine = y + (1 - this.lineCount) * 0.5 * this.fontOptions.size;\n if (baseline === \"hanging\") {\n this.size.top += 0.5 * this.fontOptions.size;\n this.size.top += 4; // distance from node, required because we use hanging. Hanging has less difference between browsers\n this.size.yLine += 4; // distance from node\n }\n\n this.labelDirty = false;\n }\n\n /**\n * This calculates the width as well as explodes the label string and calculates the amount of lines.\n * @param ctx\n * @param selected\n * @returns {number}\n * @private\n */\n }, {\n key: '_processLabel',\n value: function _processLabel(ctx, selected) {\n var width = 0;\n var lines = [''];\n var lineCount = 0;\n if (this.nodeOptions.label !== undefined) {\n lines = String(this.nodeOptions.label).split('\\n');\n lineCount = lines.length;\n ctx.font = (selected && this.nodeOptions.labelHighlightBold ? 'bold ' : '') + this.fontOptions.size + \"px \" + this.fontOptions.face;\n width = ctx.measureText(lines[0]).width;\n for (var i = 1; i < lineCount; i++) {\n var lineWidth = ctx.measureText(lines[i]).width;\n width = lineWidth > width ? lineWidth : width;\n }\n }\n this.lines = lines;\n this.lineCount = lineCount;\n\n return width;\n }\n }], [{\n key: 'parseOptions',\n value: function parseOptions(parentOptions, newOptions) {\n var allowDeletion = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n if (typeof newOptions.font === 'string') {\n var newOptionsArray = newOptions.font.split(\" \");\n parentOptions.size = newOptionsArray[0].replace(\"px\", '');\n parentOptions.face = newOptionsArray[1];\n parentOptions.color = newOptionsArray[2];\n } else if (typeof newOptions.font === 'object') {\n util.fillIfDefined(parentOptions, newOptions.font, allowDeletion);\n }\n parentOptions.size = Number(parentOptions.size);\n }\n }]);\n\n return Label;\n })();\n\n exports['default'] = Label;\n module.exports = exports['default'];\n\n/***/ },\n/* 63 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var Box = (function (_NodeBase) {\n _inherits(Box, _NodeBase);\n\n function Box(options, body, labelModule) {\n _classCallCheck(this, Box);\n\n _get(Object.getPrototypeOf(Box.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Box, [{\n key: 'resize',\n value: function resize(ctx, selected) {\n if (this.width === undefined) {\n var margin = 5;\n var textSize = this.labelModule.getTextSize(ctx, selected);\n this.width = textSize.width + 2 * margin;\n this.height = textSize.height + 2 * margin;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx, selected);\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n var borderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n ctx.lineWidth = selected ? selectionLineWidth : borderWidth;\n ctx.lineWidth /= this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, ctx.lineWidth);\n\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n\n var borderRadius = this.options.shapeProperties.borderRadius; // only effective for box\n ctx.roundRect(this.left, this.top, this.width, this.height, borderRadius);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n // draw the background\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n ctx.restore();\n\n this.updateBoundingBox(x, y, ctx, selected);\n this.labelModule.draw(ctx, x, y, selected);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y, ctx, selected) {\n this.resize(ctx, selected);\n this.left = x - this.width * 0.5;\n this.top = y - this.height * 0.5;\n\n var borderRadius = this.options.shapeProperties.borderRadius; // only effective for box\n this.boundingBox.left = this.left - borderRadius;\n this.boundingBox.top = this.top - borderRadius;\n this.boundingBox.bottom = this.top + this.height + borderRadius;\n this.boundingBox.right = this.left + this.width + borderRadius;\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n this.resize(ctx);\n var borderWidth = this.options.borderWidth;\n\n return Math.min(Math.abs(this.width / 2 / Math.cos(angle)), Math.abs(this.height / 2 / Math.sin(angle))) + borderWidth;\n }\n }]);\n\n return Box;\n })(_utilNodeBase2['default']);\n\n exports['default'] = Box;\n module.exports = exports['default'];\n\n/***/ },\n/* 64 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var NodeBase = (function () {\n function NodeBase(options, body, labelModule) {\n _classCallCheck(this, NodeBase);\n\n this.body = body;\n this.labelModule = labelModule;\n this.setOptions(options);\n this.top = undefined;\n this.left = undefined;\n this.height = undefined;\n this.width = undefined;\n this.radius = undefined;\n this.boundingBox = { top: 0, left: 0, right: 0, bottom: 0 };\n }\n\n _createClass(NodeBase, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n }, {\n key: \"_distanceToBorder\",\n value: function _distanceToBorder(ctx, angle) {\n var borderWidth = this.options.borderWidth;\n this.resize(ctx);\n return Math.min(Math.abs(this.width / 2 / Math.cos(angle)), Math.abs(this.height / 2 / Math.sin(angle))) + borderWidth;\n }\n }, {\n key: \"enableShadow\",\n value: function enableShadow(ctx) {\n if (this.options.shadow.enabled === true) {\n ctx.shadowColor = this.options.shadow.color;\n ctx.shadowBlur = this.options.shadow.size;\n ctx.shadowOffsetX = this.options.shadow.x;\n ctx.shadowOffsetY = this.options.shadow.y;\n }\n }\n }, {\n key: \"disableShadow\",\n value: function disableShadow(ctx) {\n if (this.options.shadow.enabled === true) {\n ctx.shadowColor = 'rgba(0,0,0,0)';\n ctx.shadowBlur = 0;\n ctx.shadowOffsetX = 0;\n ctx.shadowOffsetY = 0;\n }\n }\n }, {\n key: \"enableBorderDashes\",\n value: function enableBorderDashes(ctx) {\n if (this.options.shapeProperties.borderDashes !== false) {\n if (ctx.setLineDash !== undefined) {\n var dashes = this.options.shapeProperties.borderDashes;\n if (dashes === true) {\n dashes = [5, 15];\n }\n ctx.setLineDash(dashes);\n } else {\n console.warn(\"setLineDash is not supported in this browser. The dashed borders cannot be used.\");\n this.options.shapeProperties.borderDashes = false;\n }\n }\n }\n }, {\n key: \"disableBorderDashes\",\n value: function disableBorderDashes(ctx) {\n if (this.options.shapeProperties.borderDashes !== false) {\n if (ctx.setLineDash !== undefined) {\n ctx.setLineDash([0]);\n } else {\n console.warn(\"setLineDash is not supported in this browser. The dashed borders cannot be used.\");\n this.options.shapeProperties.borderDashes = false;\n }\n }\n }\n }]);\n\n return NodeBase;\n })();\n\n exports[\"default\"] = NodeBase;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 65 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilCircleImageBase = __webpack_require__(66);\n\n var _utilCircleImageBase2 = _interopRequireDefault(_utilCircleImageBase);\n\n var Circle = (function (_CircleImageBase) {\n _inherits(Circle, _CircleImageBase);\n\n function Circle(options, body, labelModule) {\n _classCallCheck(this, Circle);\n\n _get(Object.getPrototypeOf(Circle.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Circle, [{\n key: 'resize',\n value: function resize(ctx, selected) {\n if (this.width === undefined) {\n var margin = 5;\n var textSize = this.labelModule.getTextSize(ctx, selected);\n var diameter = Math.max(textSize.width, textSize.height) + 2 * margin;\n this.options.size = diameter / 2;\n\n this.width = diameter;\n this.height = diameter;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx, selected);\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n this._drawRawCircle(ctx, x, y, selected, hover, this.options.size);\n\n this.boundingBox.top = y - this.options.size;\n this.boundingBox.left = x - this.options.size;\n this.boundingBox.right = x + this.options.size;\n this.boundingBox.bottom = y + this.options.size;\n\n this.updateBoundingBox(x, y);\n this.labelModule.draw(ctx, x, y, selected);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y) {\n this.boundingBox.top = y - this.options.size;\n this.boundingBox.left = x - this.options.size;\n this.boundingBox.right = x + this.options.size;\n this.boundingBox.bottom = y + this.options.size;\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n this.resize(ctx);\n return this.width * 0.5;\n }\n }]);\n\n return Circle;\n })(_utilCircleImageBase2['default']);\n\n exports['default'] = Circle;\n module.exports = exports['default'];\n\n/***/ },\n/* 66 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var CircleImageBase = (function (_NodeBase) {\n _inherits(CircleImageBase, _NodeBase);\n\n function CircleImageBase(options, body, labelModule) {\n _classCallCheck(this, CircleImageBase);\n\n _get(Object.getPrototypeOf(CircleImageBase.prototype), 'constructor', this).call(this, options, body, labelModule);\n this.labelOffset = 0;\n this.imageLoaded = false;\n }\n\n _createClass(CircleImageBase, [{\n key: 'setOptions',\n value: function setOptions(options, imageObj) {\n this.options = options;\n if (imageObj) {\n this.imageObj = imageObj;\n }\n }\n\n /**\n * This function resizes the image by the options size when the image has not yet loaded. If the image has loaded, we\n * force the update of the size again.\n *\n * @private\n */\n }, {\n key: '_resizeImage',\n value: function _resizeImage() {\n var force = false;\n if (!this.imageObj.width || !this.imageObj.height) {\n // undefined or 0\n this.imageLoaded = false;\n } else if (this.imageLoaded === false) {\n this.imageLoaded = true;\n force = true;\n }\n\n if (!this.width || !this.height || force === true) {\n // undefined or 0\n var width, height, ratio;\n if (this.imageObj.width && this.imageObj.height) {\n // not undefined or 0\n width = 0;\n height = 0;\n }\n if (this.options.shapeProperties.useImageSize === false) {\n if (this.imageObj.width > this.imageObj.height) {\n ratio = this.imageObj.width / this.imageObj.height;\n width = this.options.size * 2 * ratio || this.imageObj.width;\n height = this.options.size * 2 || this.imageObj.height;\n } else {\n if (this.imageObj.width && this.imageObj.height) {\n // not undefined or 0\n ratio = this.imageObj.height / this.imageObj.width;\n } else {\n ratio = 1;\n }\n width = this.options.size * 2;\n height = this.options.size * 2 * ratio;\n }\n } else {\n // when not using the size property, we use the image size\n width = this.imageObj.width;\n height = this.imageObj.height;\n }\n this.width = width;\n this.height = height;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: '_drawRawCircle',\n value: function _drawRawCircle(ctx, x, y, selected, hover, size) {\n var neutralborderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n var borderWidth = (selected ? selectionLineWidth : neutralborderWidth) / this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, borderWidth);\n\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n ctx.circle(x, y, size);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n // draw the background\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n ctx.restore();\n }\n }, {\n key: '_drawImageAtPosition',\n value: function _drawImageAtPosition(ctx) {\n if (this.imageObj.width != 0) {\n // draw the image\n ctx.globalAlpha = 1.0;\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n\n // draw image\n ctx.drawImage(this.imageObj, this.left, this.top, this.width, this.height);\n\n // disable shadows for other elements.\n this.disableShadow(ctx);\n }\n }\n }, {\n key: '_drawImageLabel',\n value: function _drawImageLabel(ctx, x, y, selected) {\n var yLabel;\n var offset = 0;\n\n if (this.height !== undefined) {\n offset = this.height * 0.5;\n var labelDimensions = this.labelModule.getTextSize(ctx);\n if (labelDimensions.lineCount >= 1) {\n offset += labelDimensions.height / 2;\n }\n }\n\n yLabel = y + offset;\n\n if (this.options.label) {\n this.labelOffset = offset;\n }\n this.labelModule.draw(ctx, x, yLabel, selected, 'hanging');\n }\n }]);\n\n return CircleImageBase;\n })(_utilNodeBase2['default']);\n\n exports['default'] = CircleImageBase;\n module.exports = exports['default'];\n\n/***/ },\n/* 67 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilCircleImageBase = __webpack_require__(66);\n\n var _utilCircleImageBase2 = _interopRequireDefault(_utilCircleImageBase);\n\n var CircularImage = (function (_CircleImageBase) {\n _inherits(CircularImage, _CircleImageBase);\n\n function CircularImage(options, body, labelModule, imageObj) {\n _classCallCheck(this, CircularImage);\n\n _get(Object.getPrototypeOf(CircularImage.prototype), 'constructor', this).call(this, options, body, labelModule);\n this.imageObj = imageObj;\n this._swapToImageResizeWhenImageLoaded = true;\n }\n\n _createClass(CircularImage, [{\n key: 'resize',\n value: function resize() {\n if (this.imageObj.src === undefined || this.imageObj.width === undefined || this.imageObj.height === undefined) {\n if (!this.width) {\n var diameter = this.options.size * 2;\n this.width = diameter;\n this.height = diameter;\n this._swapToImageResizeWhenImageLoaded = true;\n this.radius = 0.5 * this.width;\n }\n } else {\n if (this._swapToImageResizeWhenImageLoaded) {\n this.width = undefined;\n this.height = undefined;\n this._swapToImageResizeWhenImageLoaded = false;\n }\n this._resizeImage();\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize();\n\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n var size = Math.min(0.5 * this.height, 0.5 * this.width);\n\n // draw the background circle. IMPORTANT: the stroke in this method is used by the clip method below.\n this._drawRawCircle(ctx, x, y, selected, hover, size);\n\n // now we draw in the circle, we save so we can revert the clip operation after drawing.\n ctx.save();\n // clip is used to use the stroke in drawRawCircle as an area that we can draw in.\n ctx.clip();\n // draw the image\n this._drawImageAtPosition(ctx);\n // restore so we can again draw on the full canvas\n ctx.restore();\n\n this._drawImageLabel(ctx, x, y, selected);\n\n this.updateBoundingBox(x, y);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y) {\n this.boundingBox.top = y - this.options.size;\n this.boundingBox.left = x - this.options.size;\n this.boundingBox.right = x + this.options.size;\n this.boundingBox.bottom = y + this.options.size;\n this.boundingBox.left = Math.min(this.boundingBox.left, this.labelModule.size.left);\n this.boundingBox.right = Math.max(this.boundingBox.right, this.labelModule.size.left + this.labelModule.size.width);\n this.boundingBox.bottom = Math.max(this.boundingBox.bottom, this.boundingBox.bottom + this.labelOffset);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n this.resize(ctx);\n return this.width * 0.5;\n }\n }]);\n\n return CircularImage;\n })(_utilCircleImageBase2['default']);\n\n exports['default'] = CircularImage;\n module.exports = exports['default'];\n\n/***/ },\n/* 68 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var Database = (function (_NodeBase) {\n _inherits(Database, _NodeBase);\n\n function Database(options, body, labelModule) {\n _classCallCheck(this, Database);\n\n _get(Object.getPrototypeOf(Database.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Database, [{\n key: 'resize',\n value: function resize(ctx, selected) {\n if (this.width === undefined) {\n var margin = 5;\n var textSize = this.labelModule.getTextSize(ctx, selected);\n var size = textSize.width + 2 * margin;\n this.width = size;\n this.height = size;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx, selected);\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n var neutralborderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n var borderWidth = (selected ? selectionLineWidth : neutralborderWidth) / this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, borderWidth);\n\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n ctx.database(x - this.width / 2, y - this.height * 0.5, this.width, this.height);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n // draw the background\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n ctx.restore();\n\n this.updateBoundingBox(x, y, ctx, selected);\n this.labelModule.draw(ctx, x, y, selected);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y, ctx, selected) {\n this.resize(ctx, selected);\n\n this.left = x - this.width * 0.5;\n this.top = y - this.height * 0.5;\n\n this.boundingBox.left = this.left;\n this.boundingBox.top = this.top;\n this.boundingBox.bottom = this.top + this.height;\n this.boundingBox.right = this.left + this.width;\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Database;\n })(_utilNodeBase2['default']);\n\n exports['default'] = Database;\n module.exports = exports['default'];\n\n/***/ },\n/* 69 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var Diamond = (function (_ShapeBase) {\n _inherits(Diamond, _ShapeBase);\n\n function Diamond(options, body, labelModule) {\n _classCallCheck(this, Diamond);\n\n _get(Object.getPrototypeOf(Diamond.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Diamond, [{\n key: 'resize',\n value: function resize(ctx) {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'diamond', 4, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Diamond;\n })(_utilShapeBase2['default']);\n\n exports['default'] = Diamond;\n module.exports = exports['default'];\n\n/***/ },\n/* 70 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var ShapeBase = (function (_NodeBase) {\n _inherits(ShapeBase, _NodeBase);\n\n function ShapeBase(options, body, labelModule) {\n _classCallCheck(this, ShapeBase);\n\n _get(Object.getPrototypeOf(ShapeBase.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(ShapeBase, [{\n key: '_resizeShape',\n value: function _resizeShape() {\n if (this.width === undefined) {\n var size = 2 * this.options.size;\n this.width = size;\n this.height = size;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: '_drawShape',\n value: function _drawShape(ctx, shape, sizeMultiplier, x, y, selected, hover) {\n this._resizeShape();\n\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n var neutralborderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n var borderWidth = (selected ? selectionLineWidth : neutralborderWidth) / this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, borderWidth);\n\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n ctx[shape](x, y, this.options.size);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n // draw the background\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n ctx.restore();\n\n if (this.options.label !== undefined) {\n var yLabel = y + 0.5 * this.height + 3; // the + 3 is to offset it a bit below the node.\n this.labelModule.draw(ctx, x, yLabel, selected, 'hanging');\n }\n\n this.updateBoundingBox(x, y);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y) {\n this.boundingBox.top = y - this.options.size;\n this.boundingBox.left = x - this.options.size;\n this.boundingBox.right = x + this.options.size;\n this.boundingBox.bottom = y + this.options.size;\n\n if (this.options.label !== undefined && this.labelModule.size.width > 0) {\n this.boundingBox.left = Math.min(this.boundingBox.left, this.labelModule.size.left);\n this.boundingBox.right = Math.max(this.boundingBox.right, this.labelModule.size.left + this.labelModule.size.width);\n this.boundingBox.bottom = Math.max(this.boundingBox.bottom, this.boundingBox.bottom + this.labelModule.size.height + 3);\n }\n }\n }]);\n\n return ShapeBase;\n })(_utilNodeBase2['default']);\n\n exports['default'] = ShapeBase;\n module.exports = exports['default'];\n\n/***/ },\n/* 71 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var Dot = (function (_ShapeBase) {\n _inherits(Dot, _ShapeBase);\n\n function Dot(options, body, labelModule) {\n _classCallCheck(this, Dot);\n\n _get(Object.getPrototypeOf(Dot.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Dot, [{\n key: 'resize',\n value: function resize(ctx) {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'circle', 2, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n this.resize(ctx);\n return this.options.size;\n }\n }]);\n\n return Dot;\n })(_utilShapeBase2['default']);\n\n exports['default'] = Dot;\n module.exports = exports['default'];\n\n/***/ },\n/* 72 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var Ellipse = (function (_NodeBase) {\n _inherits(Ellipse, _NodeBase);\n\n function Ellipse(options, body, labelModule) {\n _classCallCheck(this, Ellipse);\n\n _get(Object.getPrototypeOf(Ellipse.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Ellipse, [{\n key: 'resize',\n value: function resize(ctx, selected) {\n if (this.width === undefined) {\n var textSize = this.labelModule.getTextSize(ctx, selected);\n\n this.width = textSize.width * 1.5;\n this.height = textSize.height * 2;\n if (this.width < this.height) {\n this.width = this.height;\n }\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx, selected);\n this.left = x - this.width * 0.5;\n this.top = y - this.height * 0.5;\n\n var neutralborderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n var borderWidth = (selected ? selectionLineWidth : neutralborderWidth) / this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, borderWidth);\n\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n ctx.ellipse(this.left, this.top, this.width, this.height);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n // draw the background\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n\n ctx.restore();\n\n this.updateBoundingBox(x, y, ctx, selected);\n this.labelModule.draw(ctx, x, y, selected);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y, ctx, selected) {\n this.resize(ctx, selected); // just in case\n\n this.left = x - this.width * 0.5;\n this.top = y - this.height * 0.5;\n\n this.boundingBox.left = this.left;\n this.boundingBox.top = this.top;\n this.boundingBox.bottom = this.top + this.height;\n this.boundingBox.right = this.left + this.width;\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n this.resize(ctx);\n var a = this.width * 0.5;\n var b = this.height * 0.5;\n var w = Math.sin(angle) * a;\n var h = Math.cos(angle) * b;\n return a * b / Math.sqrt(w * w + h * h);\n }\n }]);\n\n return Ellipse;\n })(_utilNodeBase2['default']);\n\n exports['default'] = Ellipse;\n module.exports = exports['default'];\n\n/***/ },\n/* 73 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var Icon = (function (_NodeBase) {\n _inherits(Icon, _NodeBase);\n\n function Icon(options, body, labelModule) {\n _classCallCheck(this, Icon);\n\n _get(Object.getPrototypeOf(Icon.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Icon, [{\n key: 'resize',\n value: function resize(ctx) {\n if (this.width === undefined) {\n var margin = 5;\n var iconSize = {\n width: Number(this.options.icon.size),\n height: Number(this.options.icon.size)\n };\n this.width = iconSize.width + 2 * margin;\n this.height = iconSize.height + 2 * margin;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx);\n this.options.icon.size = this.options.icon.size || 50;\n\n this.left = x - this.width * 0.5;\n this.top = y - this.height * 0.5;\n this._icon(ctx, x, y, selected);\n\n if (this.options.label !== undefined) {\n var iconTextSpacing = 5;\n this.labelModule.draw(ctx, x, y + this.height * 0.5 + iconTextSpacing, selected);\n }\n\n this.updateBoundingBox(x, y);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y) {\n this.boundingBox.top = y - this.options.icon.size * 0.5;\n this.boundingBox.left = x - this.options.icon.size * 0.5;\n this.boundingBox.right = x + this.options.icon.size * 0.5;\n this.boundingBox.bottom = y + this.options.icon.size * 0.5;\n\n if (this.options.label !== undefined && this.labelModule.size.width > 0) {\n var iconTextSpacing = 5;\n this.boundingBox.left = Math.min(this.boundingBox.left, this.labelModule.size.left);\n this.boundingBox.right = Math.max(this.boundingBox.right, this.labelModule.size.left + this.labelModule.size.width);\n this.boundingBox.bottom = Math.max(this.boundingBox.bottom, this.boundingBox.bottom + this.labelModule.size.height + iconTextSpacing);\n }\n }\n }, {\n key: '_icon',\n value: function _icon(ctx, x, y, selected) {\n var iconSize = Number(this.options.icon.size);\n\n if (this.options.icon.code !== undefined) {\n ctx.font = (selected ? \"bold \" : \"\") + iconSize + \"px \" + this.options.icon.face;\n\n // draw icon\n ctx.fillStyle = this.options.icon.color || \"black\";\n ctx.textAlign = \"center\";\n ctx.textBaseline = \"middle\";\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.fillText(this.options.icon.code, x, y);\n\n // disable shadows for other elements.\n this.disableShadow(ctx);\n } else {\n console.error('When using the icon shape, you need to define the code in the icon options object. This can be done per node or globally.');\n }\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Icon;\n })(_utilNodeBase2['default']);\n\n exports['default'] = Icon;\n module.exports = exports['default'];\n\n/***/ },\n/* 74 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilCircleImageBase = __webpack_require__(66);\n\n var _utilCircleImageBase2 = _interopRequireDefault(_utilCircleImageBase);\n\n var Image = (function (_CircleImageBase) {\n _inherits(Image, _CircleImageBase);\n\n function Image(options, body, labelModule, imageObj) {\n _classCallCheck(this, Image);\n\n _get(Object.getPrototypeOf(Image.prototype), 'constructor', this).call(this, options, body, labelModule);\n this.imageObj = imageObj;\n }\n\n _createClass(Image, [{\n key: 'resize',\n value: function resize() {\n this._resizeImage();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize();\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n if (this.options.shapeProperties.useBorderWithImage === true) {\n var neutralborderWidth = this.options.borderWidth;\n var selectionLineWidth = this.options.borderWidthSelected || 2 * this.options.borderWidth;\n var borderWidth = (selected ? selectionLineWidth : neutralborderWidth) / this.body.view.scale;\n ctx.lineWidth = Math.min(this.width, borderWidth);\n\n ctx.beginPath();\n\n // setup the line properties.\n ctx.strokeStyle = selected ? this.options.color.highlight.border : hover ? this.options.color.hover.border : this.options.color.border;\n\n // set a fillstyle\n ctx.fillStyle = selected ? this.options.color.highlight.background : hover ? this.options.color.hover.background : this.options.color.background;\n\n // draw a rectangle to form the border around. This rectangle is filled so the opacity of a picture (in future vis releases?) can be used to tint the image\n ctx.rect(this.left - 0.5 * ctx.lineWidth, this.top - 0.5 * ctx.lineWidth, this.width + ctx.lineWidth, this.height + ctx.lineWidth);\n ctx.fill();\n\n //draw dashed border if enabled, save and restore is required for firefox not to crash on unix.\n ctx.save();\n // if borders are zero width, they will be drawn with width 1 by default. This prevents that\n if (borderWidth > 0) {\n this.enableBorderDashes(ctx);\n //draw the border\n ctx.stroke();\n //disable dashed border for other elements\n this.disableBorderDashes(ctx);\n }\n ctx.restore();\n\n ctx.closePath();\n }\n\n this._drawImageAtPosition(ctx);\n\n this._drawImageLabel(ctx, x, y, selected || hover);\n\n this.updateBoundingBox(x, y);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y) {\n this.resize();\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n this.boundingBox.top = this.top;\n this.boundingBox.left = this.left;\n this.boundingBox.right = this.left + this.width;\n this.boundingBox.bottom = this.top + this.height;\n\n if (this.options.label !== undefined && this.labelModule.size.width > 0) {\n this.boundingBox.left = Math.min(this.boundingBox.left, this.labelModule.size.left);\n this.boundingBox.right = Math.max(this.boundingBox.right, this.labelModule.size.left + this.labelModule.size.width);\n this.boundingBox.bottom = Math.max(this.boundingBox.bottom, this.boundingBox.bottom + this.labelOffset);\n }\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Image;\n })(_utilCircleImageBase2['default']);\n\n exports['default'] = Image;\n module.exports = exports['default'];\n\n/***/ },\n/* 75 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var Square = (function (_ShapeBase) {\n _inherits(Square, _ShapeBase);\n\n function Square(options, body, labelModule) {\n _classCallCheck(this, Square);\n\n _get(Object.getPrototypeOf(Square.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Square, [{\n key: 'resize',\n value: function resize() {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'square', 2, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Square;\n })(_utilShapeBase2['default']);\n\n exports['default'] = Square;\n module.exports = exports['default'];\n\n/***/ },\n/* 76 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var Star = (function (_ShapeBase) {\n _inherits(Star, _ShapeBase);\n\n function Star(options, body, labelModule) {\n _classCallCheck(this, Star);\n\n _get(Object.getPrototypeOf(Star.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Star, [{\n key: 'resize',\n value: function resize(ctx) {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'star', 4, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Star;\n })(_utilShapeBase2['default']);\n\n exports['default'] = Star;\n module.exports = exports['default'];\n\n/***/ },\n/* 77 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilNodeBase = __webpack_require__(64);\n\n var _utilNodeBase2 = _interopRequireDefault(_utilNodeBase);\n\n var Text = (function (_NodeBase) {\n _inherits(Text, _NodeBase);\n\n function Text(options, body, labelModule) {\n _classCallCheck(this, Text);\n\n _get(Object.getPrototypeOf(Text.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Text, [{\n key: 'resize',\n value: function resize(ctx, selected) {\n if (this.width === undefined) {\n var margin = 5;\n var textSize = this.labelModule.getTextSize(ctx, selected);\n this.width = textSize.width + 2 * margin;\n this.height = textSize.height + 2 * margin;\n this.radius = 0.5 * this.width;\n }\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this.resize(ctx, selected || hover);\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n this.labelModule.draw(ctx, x, y, selected || hover);\n\n // disable shadows for other elements.\n this.disableShadow(ctx);\n\n this.updateBoundingBox(x, y, ctx, selected);\n }\n }, {\n key: 'updateBoundingBox',\n value: function updateBoundingBox(x, y, ctx, selected) {\n this.resize(ctx, selected);\n\n this.left = x - this.width / 2;\n this.top = y - this.height / 2;\n\n this.boundingBox.top = this.top;\n this.boundingBox.left = this.left;\n this.boundingBox.right = this.left + this.width;\n this.boundingBox.bottom = this.top + this.height;\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Text;\n })(_utilNodeBase2['default']);\n\n exports['default'] = Text;\n module.exports = exports['default'];\n\n/***/ },\n/* 78 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var Triangle = (function (_ShapeBase) {\n _inherits(Triangle, _ShapeBase);\n\n function Triangle(options, body, labelModule) {\n _classCallCheck(this, Triangle);\n\n _get(Object.getPrototypeOf(Triangle.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(Triangle, [{\n key: 'resize',\n value: function resize(ctx) {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'triangle', 3, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return Triangle;\n })(_utilShapeBase2['default']);\n\n exports['default'] = Triangle;\n module.exports = exports['default'];\n\n/***/ },\n/* 79 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilShapeBase = __webpack_require__(70);\n\n var _utilShapeBase2 = _interopRequireDefault(_utilShapeBase);\n\n var TriangleDown = (function (_ShapeBase) {\n _inherits(TriangleDown, _ShapeBase);\n\n function TriangleDown(options, body, labelModule) {\n _classCallCheck(this, TriangleDown);\n\n _get(Object.getPrototypeOf(TriangleDown.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n _createClass(TriangleDown, [{\n key: 'resize',\n value: function resize(ctx) {\n this._resizeShape();\n }\n }, {\n key: 'draw',\n value: function draw(ctx, x, y, selected, hover) {\n this._drawShape(ctx, 'triangleDown', 3, x, y, selected, hover);\n }\n }, {\n key: 'distanceToBorder',\n value: function distanceToBorder(ctx, angle) {\n return this._distanceToBorder(ctx, angle);\n }\n }]);\n\n return TriangleDown;\n })(_utilShapeBase2['default']);\n\n exports['default'] = TriangleDown;\n module.exports = exports['default'];\n\n/***/ },\n/* 80 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _componentsEdge = __webpack_require__(81);\n\n var _componentsEdge2 = _interopRequireDefault(_componentsEdge);\n\n var _componentsSharedLabel = __webpack_require__(62);\n\n var _componentsSharedLabel2 = _interopRequireDefault(_componentsSharedLabel);\n\n var util = __webpack_require__(1);\n var DataSet = __webpack_require__(8);\n var DataView = __webpack_require__(10);\n\n var EdgesHandler = (function () {\n function EdgesHandler(body, images, groups) {\n var _this = this;\n\n _classCallCheck(this, EdgesHandler);\n\n this.body = body;\n this.images = images;\n this.groups = groups;\n\n // create the edge API in the body container\n this.body.functions.createEdge = this.create.bind(this);\n\n this.edgesListeners = {\n add: function add(event, params) {\n _this.add(params.items);\n },\n update: function update(event, params) {\n _this.update(params.items);\n },\n remove: function remove(event, params) {\n _this.remove(params.items);\n }\n };\n\n this.options = {};\n this.defaultOptions = {\n arrows: {\n to: { enabled: false, scaleFactor: 1 }, // boolean / {arrowScaleFactor:1} / {enabled: false, arrowScaleFactor:1}\n middle: { enabled: false, scaleFactor: 1 },\n from: { enabled: false, scaleFactor: 1 }\n },\n arrowStrikethrough: true,\n color: {\n color: '#848484',\n highlight: '#848484',\n hover: '#848484',\n inherit: 'from',\n opacity: 1.0\n },\n dashes: false,\n font: {\n color: '#343434',\n size: 14, // px\n face: 'arial',\n background: 'none',\n strokeWidth: 2, // px\n strokeColor: '#ffffff',\n align: 'horizontal'\n },\n hidden: false,\n hoverWidth: 1.5,\n label: undefined,\n labelHighlightBold: true,\n length: undefined,\n physics: true,\n scaling: {\n min: 1,\n max: 15,\n label: {\n enabled: true,\n min: 14,\n max: 30,\n maxVisible: 30,\n drawThreshold: 5\n },\n customScalingFunction: function customScalingFunction(min, max, total, value) {\n if (max === min) {\n return 0.5;\n } else {\n var scale = 1 / (max - min);\n return Math.max(0, (value - min) * scale);\n }\n }\n },\n selectionWidth: 1.5,\n selfReferenceSize: 20,\n shadow: {\n enabled: false,\n color: 'rgba(0,0,0,0.5)',\n size: 10,\n x: 5,\n y: 5\n },\n smooth: {\n enabled: true,\n type: \"dynamic\",\n forceDirection: 'none',\n roundness: 0.5\n },\n title: undefined,\n width: 1,\n value: undefined\n };\n\n util.extend(this.options, this.defaultOptions);\n\n this.bindEventListeners();\n }\n\n _createClass(EdgesHandler, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this2 = this;\n\n // this allows external modules to force all dynamic curves to turn static.\n this.body.emitter.on(\"_forceDisableDynamicCurves\", function (type) {\n if (type === 'dynamic') {\n type = 'continuous';\n }\n var emitChange = false;\n for (var edgeId in _this2.body.edges) {\n if (_this2.body.edges.hasOwnProperty(edgeId)) {\n var edge = _this2.body.edges[edgeId];\n var edgeData = _this2.body.data.edges._data[edgeId];\n\n // only forcibly remove the smooth curve if the data has been set of the edge has the smooth curves defined.\n // this is because a change in the global would not affect these curves.\n if (edgeData !== undefined) {\n var edgeOptions = edgeData.smooth;\n if (edgeOptions !== undefined) {\n if (edgeOptions.enabled === true && edgeOptions.type === 'dynamic') {\n if (type === undefined) {\n edge.setOptions({ smooth: false });\n } else {\n edge.setOptions({ smooth: { type: type } });\n }\n emitChange = true;\n }\n }\n }\n }\n }\n if (emitChange === true) {\n _this2.body.emitter.emit(\"_dataChanged\");\n }\n });\n\n // this is called when options of EXISTING nodes or edges have changed.\n this.body.emitter.on(\"_dataUpdated\", function () {\n _this2.reconnectEdges();\n _this2.markAllEdgesAsDirty();\n });\n\n // refresh the edges. Used when reverting from hierarchical layout\n this.body.emitter.on(\"refreshEdges\", this.refresh.bind(this));\n this.body.emitter.on(\"refresh\", this.refresh.bind(this));\n this.body.emitter.on(\"destroy\", function () {\n util.forEach(_this2.edgesListeners, function (callback, event) {\n if (_this2.body.data.edges) _this2.body.data.edges.off(event, callback);\n });\n delete _this2.body.functions.createEdge;\n delete _this2.edgesListeners.add;\n delete _this2.edgesListeners.update;\n delete _this2.edgesListeners.remove;\n delete _this2.edgesListeners;\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n // use the parser from the Edge class to fill in all shorthand notations\n _componentsEdge2['default'].parseOptions(this.options, options);\n\n // handle multiple input cases for color\n if (options.color !== undefined) {\n this.markAllEdgesAsDirty();\n }\n\n // update smooth settings in all edges\n var dataChanged = false;\n if (options.smooth !== undefined) {\n for (var edgeId in this.body.edges) {\n if (this.body.edges.hasOwnProperty(edgeId)) {\n dataChanged = this.body.edges[edgeId].updateEdgeType() || dataChanged;\n }\n }\n }\n\n // update fonts in all edges\n if (options.font !== undefined) {\n // use the parser from the Label class to fill in all shorthand notations\n _componentsSharedLabel2['default'].parseOptions(this.options.font, options);\n for (var edgeId in this.body.edges) {\n if (this.body.edges.hasOwnProperty(edgeId)) {\n this.body.edges[edgeId].updateLabelModule();\n }\n }\n }\n\n // update the state of the variables if needed\n if (options.hidden !== undefined || options.physics !== undefined || dataChanged === true) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n }\n\n /**\n * Load edges by reading the data table\n * @param {Array | DataSet | DataView} edges The data containing the edges.\n * @private\n * @private\n */\n }, {\n key: 'setData',\n value: function setData(edges) {\n var _this3 = this;\n\n var doNotEmit = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var oldEdgesData = this.body.data.edges;\n\n if (edges instanceof DataSet || edges instanceof DataView) {\n this.body.data.edges = edges;\n } else if (Array.isArray(edges)) {\n this.body.data.edges = new DataSet();\n this.body.data.edges.add(edges);\n } else if (!edges) {\n this.body.data.edges = new DataSet();\n } else {\n throw new TypeError('Array or DataSet expected');\n }\n\n // TODO: is this null or undefined or false?\n if (oldEdgesData) {\n // unsubscribe from old dataset\n util.forEach(this.edgesListeners, function (callback, event) {\n oldEdgesData.off(event, callback);\n });\n }\n\n // remove drawn edges\n this.body.edges = {};\n\n // TODO: is this null or undefined or false?\n if (this.body.data.edges) {\n // subscribe to new dataset\n util.forEach(this.edgesListeners, function (callback, event) {\n _this3.body.data.edges.on(event, callback);\n });\n\n // draw all new nodes\n var ids = this.body.data.edges.getIds();\n this.add(ids, true);\n }\n\n if (doNotEmit === false) {\n this.body.emitter.emit(\"_dataChanged\");\n }\n }\n\n /**\n * Add edges\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'add',\n value: function add(ids) {\n var doNotEmit = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var edges = this.body.edges;\n var edgesData = this.body.data.edges;\n\n for (var i = 0; i < ids.length; i++) {\n var id = ids[i];\n\n var oldEdge = edges[id];\n if (oldEdge) {\n oldEdge.disconnect();\n }\n\n var data = edgesData.get(id, { \"showInternalIds\": true });\n edges[id] = this.create(data);\n }\n\n if (doNotEmit === false) {\n this.body.emitter.emit(\"_dataChanged\");\n }\n }\n\n /**\n * Update existing edges, or create them when not yet existing\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'update',\n value: function update(ids) {\n var edges = this.body.edges;\n var edgesData = this.body.data.edges;\n var dataChanged = false;\n for (var i = 0; i < ids.length; i++) {\n var id = ids[i];\n var data = edgesData.get(id);\n var edge = edges[id];\n if (edge !== undefined) {\n // update edge\n edge.disconnect();\n dataChanged = edge.setOptions(data) || dataChanged; // if a support node is added, data can be changed.\n edge.connect();\n } else {\n // create edge\n this.body.edges[id] = this.create(data);\n dataChanged = true;\n }\n }\n\n if (dataChanged === true) {\n this.body.emitter.emit(\"_dataChanged\");\n } else {\n this.body.emitter.emit(\"_dataUpdated\");\n }\n }\n\n /**\n * Remove existing edges. Non existing ids will be ignored\n * @param {Number[] | String[]} ids\n * @private\n */\n }, {\n key: 'remove',\n value: function remove(ids) {\n var edges = this.body.edges;\n for (var i = 0; i < ids.length; i++) {\n var id = ids[i];\n var edge = edges[id];\n if (edge !== undefined) {\n edge.cleanup();\n edge.disconnect();\n delete edges[id];\n }\n }\n\n this.body.emitter.emit(\"_dataChanged\");\n }\n }, {\n key: 'refresh',\n value: function refresh() {\n var edges = this.body.edges;\n for (var edgeId in edges) {\n var edge = undefined;\n if (edges.hasOwnProperty(edgeId)) {\n edge = edges[edgeId];\n }\n var data = this.body.data.edges._data[edgeId];\n if (edge !== undefined && data !== undefined) {\n edge.setOptions(data);\n }\n }\n }\n }, {\n key: 'create',\n value: function create(properties) {\n return new _componentsEdge2['default'](properties, this.body, this.options);\n }\n }, {\n key: 'markAllEdgesAsDirty',\n value: function markAllEdgesAsDirty() {\n for (var edgeId in this.body.edges) {\n this.body.edges[edgeId].edgeType.colorDirty = true;\n }\n }\n\n /**\n * Reconnect all edges\n * @private\n */\n }, {\n key: 'reconnectEdges',\n value: function reconnectEdges() {\n var id;\n var nodes = this.body.nodes;\n var edges = this.body.edges;\n\n for (id in nodes) {\n if (nodes.hasOwnProperty(id)) {\n nodes[id].edges = [];\n }\n }\n\n for (id in edges) {\n if (edges.hasOwnProperty(id)) {\n var edge = edges[id];\n edge.from = null;\n edge.to = null;\n edge.connect();\n }\n }\n }\n }, {\n key: 'getConnectedNodes',\n value: function getConnectedNodes(edgeId) {\n var nodeList = [];\n if (this.body.edges[edgeId] !== undefined) {\n var edge = this.body.edges[edgeId];\n if (edge.fromId) {\n nodeList.push(edge.fromId);\n }\n if (edge.toId) {\n nodeList.push(edge.toId);\n }\n }\n return nodeList;\n }\n }]);\n\n return EdgesHandler;\n })();\n\n exports['default'] = EdgesHandler;\n module.exports = exports['default'];\n\n/***/ },\n/* 81 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _sharedLabel = __webpack_require__(62);\n\n var _sharedLabel2 = _interopRequireDefault(_sharedLabel);\n\n var _edgesCubicBezierEdge = __webpack_require__(82);\n\n var _edgesCubicBezierEdge2 = _interopRequireDefault(_edgesCubicBezierEdge);\n\n var _edgesBezierEdgeDynamic = __webpack_require__(86);\n\n var _edgesBezierEdgeDynamic2 = _interopRequireDefault(_edgesBezierEdgeDynamic);\n\n var _edgesBezierEdgeStatic = __webpack_require__(87);\n\n var _edgesBezierEdgeStatic2 = _interopRequireDefault(_edgesBezierEdgeStatic);\n\n var _edgesStraightEdge = __webpack_require__(88);\n\n var _edgesStraightEdge2 = _interopRequireDefault(_edgesStraightEdge);\n\n /**\n * @class Edge\n *\n * A edge connects two nodes\n * @param {Object} properties Object with options. Must contain\n * At least options from and to.\n * Available options: from (number),\n * to (number), label (string, color (string),\n * width (number), style (string),\n * length (number), title (string)\n * @param {Network} network A Network object, used to find and edge to\n * nodes.\n * @param {Object} constants An object with default values for\n * example for the color\n */\n var util = __webpack_require__(1);\n\n var Edge = (function () {\n function Edge(options, body, globalOptions) {\n _classCallCheck(this, Edge);\n\n if (body === undefined) {\n throw \"No body provided\";\n }\n this.options = util.bridgeObject(globalOptions);\n this.globalOptions = globalOptions;\n this.body = body;\n\n // initialize variables\n this.id = undefined;\n this.fromId = undefined;\n this.toId = undefined;\n this.selected = false;\n this.hover = false;\n this.labelDirty = true;\n this.colorDirty = true;\n\n this.baseWidth = this.options.width;\n this.baseFontSize = this.options.font.size;\n\n this.from = undefined; // a node\n this.to = undefined; // a node\n\n this.edgeType = undefined;\n\n this.connected = false;\n\n this.labelModule = new _sharedLabel2['default'](this.body, this.options);\n\n this.setOptions(options);\n }\n\n /**\n * Set or overwrite options for the edge\n * @param {Object} options an object with options\n * @param doNotEmit\n */\n\n _createClass(Edge, [{\n key: 'setOptions',\n value: function setOptions(options) {\n if (!options) {\n return;\n }\n this.colorDirty = true;\n\n Edge.parseOptions(this.options, options, true, this.globalOptions);\n\n if (options.id !== undefined) {\n this.id = options.id;\n }\n if (options.from !== undefined) {\n this.fromId = options.from;\n }\n if (options.to !== undefined) {\n this.toId = options.to;\n }\n if (options.title !== undefined) {\n this.title = options.title;\n }\n if (options.value !== undefined) {\n options.value = parseFloat(options.value);\n }\n\n // update label Module\n this.updateLabelModule();\n\n var dataChanged = this.updateEdgeType();\n\n // if anything has been updates, reset the selection width and the hover width\n this._setInteractionWidths();\n\n // A node is connected when it has a from and to node that both exist in the network.body.nodes.\n this.connect();\n\n if (options.hidden !== undefined || options.physics !== undefined) {\n dataChanged = true;\n }\n\n return dataChanged;\n }\n }, {\n key: 'updateLabelModule',\n // set the object back to the global options\n\n /**\n * update the options in the label module\n */\n value: function updateLabelModule() {\n this.labelModule.setOptions(this.options, true);\n if (this.labelModule.baseSize !== undefined) {\n this.baseFontSize = this.labelModule.baseSize;\n }\n }\n\n /**\n * update the edge type, set the options\n * @returns {boolean}\n */\n }, {\n key: 'updateEdgeType',\n value: function updateEdgeType() {\n var dataChanged = false;\n var changeInType = true;\n var smooth = this.options.smooth;\n if (this.edgeType !== undefined) {\n if (this.edgeType instanceof _edgesBezierEdgeDynamic2['default'] && smooth.enabled === true && smooth.type === 'dynamic') {\n changeInType = false;\n }\n if (this.edgeType instanceof _edgesCubicBezierEdge2['default'] && smooth.enabled === true && smooth.type === 'cubicBezier') {\n changeInType = false;\n }\n if (this.edgeType instanceof _edgesBezierEdgeStatic2['default'] && smooth.enabled === true && smooth.type !== 'dynamic' && smooth.type !== 'cubicBezier') {\n changeInType = false;\n }\n if (this.edgeType instanceof _edgesStraightEdge2['default'] && smooth.enabled === false) {\n changeInType = false;\n }\n\n if (changeInType === true) {\n dataChanged = this.cleanup();\n }\n }\n\n if (changeInType === true) {\n if (this.options.smooth.enabled === true) {\n if (this.options.smooth.type === 'dynamic') {\n dataChanged = true;\n this.edgeType = new _edgesBezierEdgeDynamic2['default'](this.options, this.body, this.labelModule);\n } else if (this.options.smooth.type === 'cubicBezier') {\n this.edgeType = new _edgesCubicBezierEdge2['default'](this.options, this.body, this.labelModule);\n } else {\n this.edgeType = new _edgesBezierEdgeStatic2['default'](this.options, this.body, this.labelModule);\n }\n } else {\n this.edgeType = new _edgesStraightEdge2['default'](this.options, this.body, this.labelModule);\n }\n } else {\n // if nothing changes, we just set the options.\n this.edgeType.setOptions(this.options);\n }\n\n return dataChanged;\n }\n\n /**\n * Connect an edge to its nodes\n */\n }, {\n key: 'connect',\n value: function connect() {\n this.disconnect();\n\n this.from = this.body.nodes[this.fromId] || undefined;\n this.to = this.body.nodes[this.toId] || undefined;\n this.connected = this.from !== undefined && this.to !== undefined;\n\n if (this.connected === true) {\n this.from.attachEdge(this);\n this.to.attachEdge(this);\n } else {\n if (this.from) {\n this.from.detachEdge(this);\n }\n if (this.to) {\n this.to.detachEdge(this);\n }\n }\n\n this.edgeType.connect();\n }\n\n /**\n * Disconnect an edge from its nodes\n */\n }, {\n key: 'disconnect',\n value: function disconnect() {\n if (this.from) {\n this.from.detachEdge(this);\n this.from = undefined;\n }\n if (this.to) {\n this.to.detachEdge(this);\n this.to = undefined;\n }\n\n this.connected = false;\n }\n\n /**\n * get the title of this edge.\n * @return {string} title The title of the edge, or undefined when no title\n * has been set.\n */\n }, {\n key: 'getTitle',\n value: function getTitle() {\n return this.title;\n }\n\n /**\n * check if this node is selecte\n * @return {boolean} selected True if node is selected, else false\n */\n }, {\n key: 'isSelected',\n value: function isSelected() {\n return this.selected;\n }\n\n /**\n * Retrieve the value of the edge. Can be undefined\n * @return {Number} value\n */\n }, {\n key: 'getValue',\n value: function getValue() {\n return this.options.value;\n }\n\n /**\n * Adjust the value range of the edge. The edge will adjust it's width\n * based on its value.\n * @param {Number} min\n * @param {Number} max\n * @param total\n */\n }, {\n key: 'setValueRange',\n value: function setValueRange(min, max, total) {\n if (this.options.value !== undefined) {\n var scale = this.options.scaling.customScalingFunction(min, max, total, this.options.value);\n var widthDiff = this.options.scaling.max - this.options.scaling.min;\n if (this.options.scaling.label.enabled === true) {\n var fontDiff = this.options.scaling.label.max - this.options.scaling.label.min;\n this.options.font.size = this.options.scaling.label.min + scale * fontDiff;\n }\n this.options.width = this.options.scaling.min + scale * widthDiff;\n } else {\n this.options.width = this.baseWidth;\n this.options.font.size = this.baseFontSize;\n }\n\n this._setInteractionWidths();\n this.updateLabelModule();\n }\n }, {\n key: '_setInteractionWidths',\n value: function _setInteractionWidths() {\n if (typeof this.options.hoverWidth === 'function') {\n this.edgeType.hoverWidth = this.options.hoverWidth(this.options.width);\n } else {\n this.edgeType.hoverWidth = this.options.hoverWidth + this.options.width;\n }\n\n if (typeof this.options.selectionWidth === 'function') {\n this.edgeType.selectionWidth = this.options.selectionWidth(this.options.width);\n } else {\n this.edgeType.selectionWidth = this.options.selectionWidth + this.options.width;\n }\n }\n\n /**\n * Redraw a edge\n * Draw this edge in the given canvas\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext(\"2d\");\n * @param {CanvasRenderingContext2D} ctx\n */\n }, {\n key: 'draw',\n value: function draw(ctx) {\n // get the via node from the edge type\n var viaNode = this.edgeType.getViaNode();\n var arrowData = {};\n\n // restore edge targets to defaults\n this.edgeType.fromPoint = this.from;\n this.edgeType.toPoint = this.to;\n\n // from and to arrows give a different end point for edges. we set them here\n if (this.options.arrows.from.enabled === true) {\n arrowData.from = this.edgeType.getArrowData(ctx, 'from', viaNode, this.selected, this.hover);\n if (this.options.arrowStrikethrough === false) this.edgeType.fromPoint = arrowData.from.core;\n }\n if (this.options.arrows.to.enabled === true) {\n arrowData.to = this.edgeType.getArrowData(ctx, 'to', viaNode, this.selected, this.hover);\n if (this.options.arrowStrikethrough === false) this.edgeType.toPoint = arrowData.to.core;\n }\n\n // the middle arrow depends on the line, which can depend on the to and from arrows so we do this one lastly.\n if (this.options.arrows.middle.enabled === true) {\n arrowData.middle = this.edgeType.getArrowData(ctx, 'middle', viaNode, this.selected, this.hover);\n }\n\n // draw everything\n this.edgeType.drawLine(ctx, this.selected, this.hover, viaNode);\n this.drawArrows(ctx, arrowData);\n this.drawLabel(ctx, viaNode);\n }\n }, {\n key: 'drawArrows',\n value: function drawArrows(ctx, arrowData) {\n if (this.options.arrows.from.enabled === true) {\n this.edgeType.drawArrowHead(ctx, this.selected, this.hover, arrowData.from);\n }\n if (this.options.arrows.middle.enabled === true) {\n this.edgeType.drawArrowHead(ctx, this.selected, this.hover, arrowData.middle);\n }\n if (this.options.arrows.to.enabled === true) {\n this.edgeType.drawArrowHead(ctx, this.selected, this.hover, arrowData.to);\n }\n }\n }, {\n key: 'drawLabel',\n value: function drawLabel(ctx, viaNode) {\n if (this.options.label !== undefined) {\n // set style\n var node1 = this.from;\n var node2 = this.to;\n var selected = this.from.selected || this.to.selected || this.selected;\n if (node1.id != node2.id) {\n this.labelModule.pointToSelf = false;\n var point = this.edgeType.getPoint(0.5, viaNode);\n ctx.save();\n\n // if the label has to be rotated:\n if (this.options.font.align !== \"horizontal\") {\n this.labelModule.calculateLabelSize(ctx, selected, point.x, point.y);\n ctx.translate(point.x, this.labelModule.size.yLine);\n this._rotateForLabelAlignment(ctx);\n }\n\n // draw the label\n this.labelModule.draw(ctx, point.x, point.y, selected);\n ctx.restore();\n } else {\n // Ignore the orientations.\n this.labelModule.pointToSelf = true;\n var x, y;\n var radius = this.options.selfReferenceSize;\n if (node1.shape.width > node1.shape.height) {\n x = node1.x + node1.shape.width * 0.5;\n y = node1.y - radius;\n } else {\n x = node1.x + radius;\n y = node1.y - node1.shape.height * 0.5;\n }\n point = this._pointOnCircle(x, y, radius, 0.125);\n this.labelModule.draw(ctx, point.x, point.y, selected);\n }\n }\n }\n\n /**\n * Check if this object is overlapping with the provided object\n * @param {Object} obj an object with parameters left, top\n * @return {boolean} True if location is located on the edge\n */\n }, {\n key: 'isOverlappingWith',\n value: function isOverlappingWith(obj) {\n if (this.connected) {\n var distMax = 10;\n var xFrom = this.from.x;\n var yFrom = this.from.y;\n var xTo = this.to.x;\n var yTo = this.to.y;\n var xObj = obj.left;\n var yObj = obj.top;\n\n var dist = this.edgeType.getDistanceToEdge(xFrom, yFrom, xTo, yTo, xObj, yObj);\n\n return dist < distMax;\n } else {\n return false;\n }\n }\n\n /**\n * Rotates the canvas so the text is most readable\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n }, {\n key: '_rotateForLabelAlignment',\n value: function _rotateForLabelAlignment(ctx) {\n var dy = this.from.y - this.to.y;\n var dx = this.from.x - this.to.x;\n var angleInDegrees = Math.atan2(dy, dx);\n\n // rotate so label it is readable\n if (angleInDegrees < -1 && dx < 0 || angleInDegrees > 0 && dx < 0) {\n angleInDegrees = angleInDegrees + Math.PI;\n }\n\n ctx.rotate(angleInDegrees);\n }\n\n /**\n * Get a point on a circle\n * @param {Number} x\n * @param {Number} y\n * @param {Number} radius\n * @param {Number} percentage. Value between 0 (line start) and 1 (line end)\n * @return {Object} point\n * @private\n */\n }, {\n key: '_pointOnCircle',\n value: function _pointOnCircle(x, y, radius, percentage) {\n var angle = percentage * 2 * Math.PI;\n return {\n x: x + radius * Math.cos(angle),\n y: y - radius * Math.sin(angle)\n };\n }\n }, {\n key: 'select',\n value: function select() {\n this.selected = true;\n }\n }, {\n key: 'unselect',\n value: function unselect() {\n this.selected = false;\n }\n\n /**\n * cleans all required things on delete\n * @returns {*}\n */\n }, {\n key: 'cleanup',\n value: function cleanup() {\n return this.edgeType.cleanup();\n }\n }], [{\n key: 'parseOptions',\n value: function parseOptions(parentOptions, newOptions) {\n var allowDeletion = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n var globalOptions = arguments.length <= 3 || arguments[3] === undefined ? {} : arguments[3];\n\n var fields = ['arrowStrikethrough', 'id', 'from', 'hidden', 'hoverWidth', 'label', 'labelHighlightBold', 'length', 'line', 'opacity', 'physics', 'scaling', 'selectionWidth', 'selfReferenceSize', 'to', 'title', 'value', 'width'];\n\n // only deep extend the items in the field array. These do not have shorthand.\n util.selectiveDeepExtend(fields, parentOptions, newOptions, allowDeletion);\n\n util.mergeOptions(parentOptions, newOptions, 'smooth', allowDeletion, globalOptions);\n util.mergeOptions(parentOptions, newOptions, 'shadow', allowDeletion, globalOptions);\n\n if (newOptions.dashes !== undefined && newOptions.dashes !== null) {\n parentOptions.dashes = newOptions.dashes;\n } else if (allowDeletion === true && newOptions.dashes === null) {\n parentOptions.dashes = Object.create(globalOptions.dashes); // this sets the pointer of the option back to the global option.\n }\n\n // set the scaling newOptions\n if (newOptions.scaling !== undefined && newOptions.scaling !== null) {\n if (newOptions.scaling.min !== undefined) {\n parentOptions.scaling.min = newOptions.scaling.min;\n }\n if (newOptions.scaling.max !== undefined) {\n parentOptions.scaling.max = newOptions.scaling.max;\n }\n util.mergeOptions(parentOptions.scaling, newOptions.scaling, 'label', allowDeletion, globalOptions.scaling);\n } else if (allowDeletion === true && newOptions.scaling === null) {\n parentOptions.scaling = Object.create(globalOptions.scaling); // this sets the pointer of the option back to the global option.\n }\n\n // handle multiple input cases for arrows\n if (newOptions.arrows !== undefined && newOptions.arrows !== null) {\n if (typeof newOptions.arrows === 'string') {\n var arrows = newOptions.arrows.toLowerCase();\n if (arrows.indexOf(\"to\") != -1) {\n parentOptions.arrows.to.enabled = true;\n }\n if (arrows.indexOf(\"middle\") != -1) {\n parentOptions.arrows.middle.enabled = true;\n }\n if (arrows.indexOf(\"from\") != -1) {\n parentOptions.arrows.from.enabled = true;\n }\n } else if (typeof newOptions.arrows === 'object') {\n util.mergeOptions(parentOptions.arrows, newOptions.arrows, 'to', allowDeletion, globalOptions.arrows);\n util.mergeOptions(parentOptions.arrows, newOptions.arrows, 'middle', allowDeletion, globalOptions.arrows);\n util.mergeOptions(parentOptions.arrows, newOptions.arrows, 'from', allowDeletion, globalOptions.arrows);\n } else {\n throw new Error(\"The arrow newOptions can only be an object or a string. Refer to the documentation. You used:\" + JSON.stringify(newOptions.arrows));\n }\n } else if (allowDeletion === true && newOptions.arrows === null) {\n parentOptions.arrows = Object.create(globalOptions.arrows); // this sets the pointer of the option back to the global option.\n }\n\n // handle multiple input cases for color\n if (newOptions.color !== undefined && newOptions.color !== null) {\n // make a copy of the parent object in case this is referring to the global one (due to object create once, then update)\n parentOptions.color = util.deepExtend({}, parentOptions.color, true);\n if (util.isString(newOptions.color)) {\n parentOptions.color.color = newOptions.color;\n parentOptions.color.highlight = newOptions.color;\n parentOptions.color.hover = newOptions.color;\n parentOptions.color.inherit = false;\n } else {\n var colorsDefined = false;\n if (newOptions.color.color !== undefined) {\n parentOptions.color.color = newOptions.color.color;colorsDefined = true;\n }\n if (newOptions.color.highlight !== undefined) {\n parentOptions.color.highlight = newOptions.color.highlight;colorsDefined = true;\n }\n if (newOptions.color.hover !== undefined) {\n parentOptions.color.hover = newOptions.color.hover;colorsDefined = true;\n }\n if (newOptions.color.inherit !== undefined) {\n parentOptions.color.inherit = newOptions.color.inherit;\n }\n if (newOptions.color.opacity !== undefined) {\n parentOptions.color.opacity = Math.min(1, Math.max(0, newOptions.color.opacity));\n }\n\n if (newOptions.color.inherit === undefined && colorsDefined === true) {\n parentOptions.color.inherit = false;\n }\n }\n } else if (allowDeletion === true && newOptions.color === null) {\n parentOptions.color = util.bridgeObject(globalOptions.color); // set the object back to the global options\n }\n\n // handle the font settings\n if (newOptions.font !== undefined && newOptions.font !== null) {\n _sharedLabel2['default'].parseOptions(parentOptions.font, newOptions);\n } else if (allowDeletion === true && newOptions.font === null) {\n parentOptions.font = util.bridgeObject(globalOptions.font);\n }\n }\n }]);\n\n return Edge;\n })();\n\n exports['default'] = Edge;\n module.exports = exports['default'];\n\n/***/ },\n/* 82 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _slicedToArray = (function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i['return']) _i['return'](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError('Invalid attempt to destructure non-iterable instance'); } }; })();\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x3, _x4, _x5) { var _again = true; _function: while (_again) { var object = _x3, property = _x4, receiver = _x5; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x3 = parent; _x4 = property; _x5 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilCubicBezierEdgeBase = __webpack_require__(83);\n\n var _utilCubicBezierEdgeBase2 = _interopRequireDefault(_utilCubicBezierEdgeBase);\n\n var CubicBezierEdge = (function (_CubicBezierEdgeBase) {\n _inherits(CubicBezierEdge, _CubicBezierEdgeBase);\n\n function CubicBezierEdge(options, body, labelModule) {\n _classCallCheck(this, CubicBezierEdge);\n\n _get(Object.getPrototypeOf(CubicBezierEdge.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n /**\n * Draw a line between two nodes\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n\n _createClass(CubicBezierEdge, [{\n key: '_line',\n value: function _line(ctx, viaNodes) {\n // get the coordinates of the support points.\n var via1 = viaNodes[0];\n var via2 = viaNodes[1];\n\n // start drawing the line.\n ctx.beginPath();\n ctx.moveTo(this.fromPoint.x, this.fromPoint.y);\n\n // fallback to normal straight edges\n if (viaNodes === undefined || via1.x === undefined) {\n ctx.lineTo(this.toPoint.x, this.toPoint.y);\n } else {\n ctx.bezierCurveTo(via1.x, via1.y, via2.x, via2.y, this.toPoint.x, this.toPoint.y);\n }\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.stroke();\n this.disableShadow(ctx);\n }\n }, {\n key: '_getViaCoordinates',\n value: function _getViaCoordinates() {\n var dx = this.from.x - this.to.x;\n var dy = this.from.y - this.to.y;\n\n var x1 = undefined,\n y1 = undefined,\n x2 = undefined,\n y2 = undefined;\n var roundness = this.options.smooth.roundness;\n\n // horizontal if x > y or if direction is forced or if direction is horizontal\n if ((Math.abs(dx) > Math.abs(dy) || this.options.smooth.forceDirection === true || this.options.smooth.forceDirection === 'horizontal') && this.options.smooth.forceDirection !== 'vertical') {\n y1 = this.from.y;\n y2 = this.to.y;\n x1 = this.from.x - roundness * dx;\n x2 = this.to.x + roundness * dx;\n } else {\n y1 = this.from.y - roundness * dy;\n y2 = this.to.y + roundness * dy;\n x1 = this.from.x;\n x2 = this.to.x;\n }\n\n return [{ x: x1, y: y1 }, { x: x2, y: y2 }];\n }\n }, {\n key: 'getViaNode',\n value: function getViaNode() {\n return this._getViaCoordinates();\n }\n }, {\n key: '_findBorderPosition',\n value: function _findBorderPosition(nearNode, ctx) {\n return this._findBorderPositionBezier(nearNode, ctx);\n }\n }, {\n key: '_getDistanceToEdge',\n value: function _getDistanceToEdge(x1, y1, x2, y2, x3, y3) {\n var _ref = arguments.length <= 6 || arguments[6] === undefined ? this._getViaCoordinates() : arguments[6];\n\n var _ref2 = _slicedToArray(_ref, 2);\n\n var via1 = _ref2[0];\n var via2 = _ref2[1];\n // x3,y3 is the point\n return this._getDistanceToBezierEdge(x1, y1, x2, y2, x3, y3, via1, via2);\n }\n\n /**\n * Combined function of pointOnLine and pointOnBezier. This gives the coordinates of a point on the line at a certain percentage of the way\n * @param percentage\n * @param via\n * @returns {{x: number, y: number}}\n * @private\n */\n }, {\n key: 'getPoint',\n value: function getPoint(percentage) {\n var _ref3 = arguments.length <= 1 || arguments[1] === undefined ? this._getViaCoordinates() : arguments[1];\n\n var _ref32 = _slicedToArray(_ref3, 2);\n\n var via1 = _ref32[0];\n var via2 = _ref32[1];\n\n var t = percentage;\n var vec = [];\n vec[0] = Math.pow(1 - t, 3);\n vec[1] = 3 * t * Math.pow(1 - t, 2);\n vec[2] = 3 * Math.pow(t, 2) * (1 - t);\n vec[3] = Math.pow(t, 3);\n var x = vec[0] * this.fromPoint.x + vec[1] * via1.x + vec[2] * via2.x + vec[3] * this.toPoint.x;\n var y = vec[0] * this.fromPoint.y + vec[1] * via1.y + vec[2] * via2.y + vec[3] * this.toPoint.y;\n\n return { x: x, y: y };\n }\n }]);\n\n return CubicBezierEdge;\n })(_utilCubicBezierEdgeBase2['default']);\n\n exports['default'] = CubicBezierEdge;\n module.exports = exports['default'];\n\n/***/ },\n/* 83 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _BezierEdgeBase2 = __webpack_require__(84);\n\n var _BezierEdgeBase3 = _interopRequireDefault(_BezierEdgeBase2);\n\n var CubicBezierEdgeBase = (function (_BezierEdgeBase) {\n _inherits(CubicBezierEdgeBase, _BezierEdgeBase);\n\n function CubicBezierEdgeBase(options, body, labelModule) {\n _classCallCheck(this, CubicBezierEdgeBase);\n\n _get(Object.getPrototypeOf(CubicBezierEdgeBase.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n /**\n * Calculate the distance between a point (x3,y3) and a line segment from\n * (x1,y1) to (x2,y2).\n * http://stackoverflow.com/questions/849211/shortest-distancae-between-a-point-and-a-line-segment\n * https://en.wikipedia.org/wiki/B%C3%A9zier_curve\n * @param {number} x1 from x\n * @param {number} y1 from y\n * @param {number} x2 to x\n * @param {number} y2 to y\n * @param {number} x3 point to check x\n * @param {number} y3 point to check y\n * @private\n */\n\n _createClass(CubicBezierEdgeBase, [{\n key: '_getDistanceToBezierEdge',\n value: function _getDistanceToBezierEdge(x1, y1, x2, y2, x3, y3, via1, via2) {\n // x3,y3 is the point\n var minDistance = 1e9;\n var distance = undefined;\n var i = undefined,\n t = undefined,\n x = undefined,\n y = undefined;\n var lastX = x1;\n var lastY = y1;\n var vec = [0, 0, 0, 0];\n for (i = 1; i < 10; i++) {\n t = 0.1 * i;\n vec[0] = Math.pow(1 - t, 3);\n vec[1] = 3 * t * Math.pow(1 - t, 2);\n vec[2] = 3 * Math.pow(t, 2) * (1 - t);\n vec[3] = Math.pow(t, 3);\n x = vec[0] * x1 + vec[1] * via1.x + vec[2] * via2.x + vec[3] * x2;\n y = vec[0] * y1 + vec[1] * via1.y + vec[2] * via2.y + vec[3] * y2;\n if (i > 0) {\n distance = this._getDistanceToLine(lastX, lastY, x, y, x3, y3);\n minDistance = distance < minDistance ? distance : minDistance;\n }\n lastX = x;\n lastY = y;\n }\n\n return minDistance;\n }\n }]);\n\n return CubicBezierEdgeBase;\n })(_BezierEdgeBase3['default']);\n\n exports['default'] = CubicBezierEdgeBase;\n module.exports = exports['default'];\n\n/***/ },\n/* 84 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x2, _x3, _x4) { var _again = true; _function: while (_again) { var object = _x2, property = _x3, receiver = _x4; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x2 = parent; _x3 = property; _x4 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _EdgeBase2 = __webpack_require__(85);\n\n var _EdgeBase3 = _interopRequireDefault(_EdgeBase2);\n\n var BezierEdgeBase = (function (_EdgeBase) {\n _inherits(BezierEdgeBase, _EdgeBase);\n\n function BezierEdgeBase(options, body, labelModule) {\n _classCallCheck(this, BezierEdgeBase);\n\n _get(Object.getPrototypeOf(BezierEdgeBase.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n /**\n * This function uses binary search to look for the point where the bezier curve crosses the border of the node.\n *\n * @param nearNode\n * @param ctx\n * @param viaNode\n * @param nearNode\n * @param ctx\n * @param viaNode\n * @param nearNode\n * @param ctx\n * @param viaNode\n */\n\n _createClass(BezierEdgeBase, [{\n key: '_findBorderPositionBezier',\n value: function _findBorderPositionBezier(nearNode, ctx) {\n var viaNode = arguments.length <= 2 || arguments[2] === undefined ? this._getViaCoordinates() : arguments[2];\n\n var maxIterations = 10;\n var iteration = 0;\n var low = 0;\n var high = 1;\n var pos, angle, distanceToBorder, distanceToPoint, difference;\n var threshold = 0.2;\n var node = this.to;\n var from = false;\n if (nearNode.id === this.from.id) {\n node = this.from;\n from = true;\n }\n\n while (low <= high && iteration < maxIterations) {\n var middle = (low + high) * 0.5;\n\n pos = this.getPoint(middle, viaNode);\n angle = Math.atan2(node.y - pos.y, node.x - pos.x);\n distanceToBorder = node.distanceToBorder(ctx, angle);\n distanceToPoint = Math.sqrt(Math.pow(pos.x - node.x, 2) + Math.pow(pos.y - node.y, 2));\n difference = distanceToBorder - distanceToPoint;\n if (Math.abs(difference) < threshold) {\n break; // found\n } else if (difference < 0) {\n // distance to nodes is larger than distance to border --> t needs to be bigger if we're looking at the to node.\n if (from === false) {\n low = middle;\n } else {\n high = middle;\n }\n } else {\n if (from === false) {\n high = middle;\n } else {\n low = middle;\n }\n }\n\n iteration++;\n }\n pos.t = middle;\n\n return pos;\n }\n\n /**\n * Calculate the distance between a point (x3,y3) and a line segment from\n * (x1,y1) to (x2,y2).\n * http://stackoverflow.com/questions/849211/shortest-distancae-between-a-point-and-a-line-segment\n * @param {number} x1 from x\n * @param {number} y1 from y\n * @param {number} x2 to x\n * @param {number} y2 to y\n * @param {number} x3 point to check x\n * @param {number} y3 point to check y\n * @private\n */\n }, {\n key: '_getDistanceToBezierEdge',\n value: function _getDistanceToBezierEdge(x1, y1, x2, y2, x3, y3, via) {\n // x3,y3 is the point\n var minDistance = 1e9;\n var distance = undefined;\n var i = undefined,\n t = undefined,\n x = undefined,\n y = undefined;\n var lastX = x1;\n var lastY = y1;\n for (i = 1; i < 10; i++) {\n t = 0.1 * i;\n x = Math.pow(1 - t, 2) * x1 + 2 * t * (1 - t) * via.x + Math.pow(t, 2) * x2;\n y = Math.pow(1 - t, 2) * y1 + 2 * t * (1 - t) * via.y + Math.pow(t, 2) * y2;\n if (i > 0) {\n distance = this._getDistanceToLine(lastX, lastY, x, y, x3, y3);\n minDistance = distance < minDistance ? distance : minDistance;\n }\n lastX = x;\n lastY = y;\n }\n\n return minDistance;\n }\n }]);\n\n return BezierEdgeBase;\n })(_EdgeBase3['default']);\n\n exports['default'] = BezierEdgeBase;\n module.exports = exports['default'];\n\n/***/ },\n/* 85 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _slicedToArray = (function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i['return']) _i['return'](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError('Invalid attempt to destructure non-iterable instance'); } }; })();\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var util = __webpack_require__(1);\n\n var EdgeBase = (function () {\n function EdgeBase(options, body, labelModule) {\n _classCallCheck(this, EdgeBase);\n\n this.body = body;\n this.labelModule = labelModule;\n this.options = {};\n this.setOptions(options);\n this.colorDirty = true;\n this.color = {};\n this.selectionWidth = 2;\n this.hoverWidth = 1.5;\n this.fromPoint = this.from;\n this.toPoint = this.to;\n }\n\n _createClass(EdgeBase, [{\n key: 'connect',\n value: function connect() {\n this.from = this.body.nodes[this.options.from];\n this.to = this.body.nodes[this.options.to];\n }\n }, {\n key: 'cleanup',\n value: function cleanup() {\n return false;\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n this.options = options;\n this.from = this.body.nodes[this.options.from];\n this.to = this.body.nodes[this.options.to];\n this.id = this.options.id;\n }\n\n /**\n * Redraw a edge as a line\n * Draw this edge in the given canvas\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext(\"2d\");\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n }, {\n key: 'drawLine',\n value: function drawLine(ctx, selected, hover, viaNode) {\n // set style\n ctx.strokeStyle = this.getColor(ctx, selected, hover);\n ctx.lineWidth = this.getLineWidth(selected, hover);\n\n if (this.options.dashes !== false) {\n this._drawDashedLine(ctx, viaNode);\n } else {\n this._drawLine(ctx, viaNode);\n }\n }\n }, {\n key: '_drawLine',\n value: function _drawLine(ctx, viaNode, fromPoint, toPoint) {\n if (this.from != this.to) {\n // draw line\n this._line(ctx, viaNode, fromPoint, toPoint);\n } else {\n var _getCircleData2 = this._getCircleData(ctx);\n\n var _getCircleData22 = _slicedToArray(_getCircleData2, 3);\n\n var x = _getCircleData22[0];\n var y = _getCircleData22[1];\n var radius = _getCircleData22[2];\n\n this._circle(ctx, x, y, radius);\n }\n }\n }, {\n key: '_drawDashedLine',\n value: function _drawDashedLine(ctx, viaNode, fromPoint, toPoint) {\n ctx.lineCap = 'round';\n var pattern = [5, 5];\n if (Array.isArray(this.options.dashes) === true) {\n pattern = this.options.dashes;\n }\n\n // only firefox and chrome support this method, else we use the legacy one.\n if (ctx.setLineDash !== undefined) {\n ctx.save();\n\n // set dash settings for chrome or firefox\n ctx.setLineDash(pattern);\n ctx.lineDashOffset = 0;\n\n // draw the line\n if (this.from != this.to) {\n // draw line\n this._line(ctx, viaNode);\n } else {\n var _getCircleData3 = this._getCircleData(ctx);\n\n var _getCircleData32 = _slicedToArray(_getCircleData3, 3);\n\n var x = _getCircleData32[0];\n var y = _getCircleData32[1];\n var radius = _getCircleData32[2];\n\n this._circle(ctx, x, y, radius);\n }\n\n // restore the dash settings.\n ctx.setLineDash([0]);\n ctx.lineDashOffset = 0;\n ctx.restore();\n } else {\n // unsupporting smooth lines\n if (this.from != this.to) {\n // draw line\n ctx.dashedLine(this.from.x, this.from.y, this.to.x, this.to.y, pattern);\n } else {\n var _getCircleData4 = this._getCircleData(ctx);\n\n var _getCircleData42 = _slicedToArray(_getCircleData4, 3);\n\n var x = _getCircleData42[0];\n var y = _getCircleData42[1];\n var radius = _getCircleData42[2];\n\n this._circle(ctx, x, y, radius);\n }\n // draw shadow if enabled\n this.enableShadow(ctx);\n\n ctx.stroke();\n\n // disable shadows for other elements.\n this.disableShadow(ctx);\n }\n }\n }, {\n key: 'findBorderPosition',\n value: function findBorderPosition(nearNode, ctx, options) {\n if (this.from != this.to) {\n return this._findBorderPosition(nearNode, ctx, options);\n } else {\n return this._findBorderPositionCircle(nearNode, ctx, options);\n }\n }\n }, {\n key: 'findBorderPositions',\n value: function findBorderPositions(ctx) {\n var from = {};\n var to = {};\n if (this.from != this.to) {\n from = this._findBorderPosition(this.from, ctx);\n to = this._findBorderPosition(this.to, ctx);\n } else {\n var _getCircleData5 = this._getCircleData(ctx);\n\n var _getCircleData52 = _slicedToArray(_getCircleData5, 3);\n\n var x = _getCircleData52[0];\n var y = _getCircleData52[1];\n var radius = _getCircleData52[2];\n\n from = this._findBorderPositionCircle(this.from, ctx, { x: x, y: y, low: 0.25, high: 0.6, direction: -1 });\n to = this._findBorderPositionCircle(this.from, ctx, { x: x, y: y, low: 0.6, high: 0.8, direction: 1 });\n }\n return { from: from, to: to };\n }\n }, {\n key: '_getCircleData',\n value: function _getCircleData(ctx) {\n var x = undefined,\n y = undefined;\n var node = this.from;\n var radius = this.options.selfReferenceSize;\n\n if (ctx !== undefined) {\n if (node.shape.width === undefined) {\n node.shape.resize(ctx);\n }\n }\n\n // get circle coordinates\n if (node.shape.width > node.shape.height) {\n x = node.x + node.shape.width * 0.5;\n y = node.y - radius;\n } else {\n x = node.x + radius;\n y = node.y - node.shape.height * 0.5;\n }\n return [x, y, radius];\n }\n\n /**\n * Get a point on a circle\n * @param {Number} x\n * @param {Number} y\n * @param {Number} radius\n * @param {Number} percentage. Value between 0 (line start) and 1 (line end)\n * @return {Object} point\n * @private\n */\n }, {\n key: '_pointOnCircle',\n value: function _pointOnCircle(x, y, radius, percentage) {\n var angle = percentage * 2 * Math.PI;\n return {\n x: x + radius * Math.cos(angle),\n y: y - radius * Math.sin(angle)\n };\n }\n\n /**\n * This function uses binary search to look for the point where the circle crosses the border of the node.\n * @param node\n * @param ctx\n * @param options\n * @returns {*}\n * @private\n */\n }, {\n key: '_findBorderPositionCircle',\n value: function _findBorderPositionCircle(node, ctx, options) {\n var x = options.x;\n var y = options.y;\n var low = options.low;\n var high = options.high;\n var direction = options.direction;\n\n var maxIterations = 10;\n var iteration = 0;\n var radius = this.options.selfReferenceSize;\n var pos = undefined,\n angle = undefined,\n distanceToBorder = undefined,\n distanceToPoint = undefined,\n difference = undefined;\n var threshold = 0.05;\n var middle = (low + high) * 0.5;\n\n while (low <= high && iteration < maxIterations) {\n middle = (low + high) * 0.5;\n\n pos = this._pointOnCircle(x, y, radius, middle);\n angle = Math.atan2(node.y - pos.y, node.x - pos.x);\n distanceToBorder = node.distanceToBorder(ctx, angle);\n distanceToPoint = Math.sqrt(Math.pow(pos.x - node.x, 2) + Math.pow(pos.y - node.y, 2));\n difference = distanceToBorder - distanceToPoint;\n if (Math.abs(difference) < threshold) {\n break; // found\n } else if (difference > 0) {\n // distance to nodes is larger than distance to border --> t needs to be bigger if we're looking at the to node.\n if (direction > 0) {\n low = middle;\n } else {\n high = middle;\n }\n } else {\n if (direction > 0) {\n high = middle;\n } else {\n low = middle;\n }\n }\n iteration++;\n }\n pos.t = middle;\n\n return pos;\n }\n\n /**\n * Get the line width of the edge. Depends on width and whether one of the\n * connected nodes is selected.\n * @return {Number} width\n * @private\n */\n }, {\n key: 'getLineWidth',\n value: function getLineWidth(selected, hover) {\n if (selected === true) {\n return Math.max(this.selectionWidth, 0.3 / this.body.view.scale);\n } else {\n if (hover === true) {\n return Math.max(this.hoverWidth, 0.3 / this.body.view.scale);\n } else {\n return Math.max(this.options.width, 0.3 / this.body.view.scale);\n }\n }\n }\n }, {\n key: 'getColor',\n value: function getColor(ctx, selected, hover) {\n var colorOptions = this.options.color;\n if (colorOptions.inherit !== false) {\n // when this is a loop edge, just use the 'from' method\n if (colorOptions.inherit === 'both' && this.from.id !== this.to.id) {\n var grd = ctx.createLinearGradient(this.from.x, this.from.y, this.to.x, this.to.y);\n var fromColor = undefined,\n toColor = undefined;\n fromColor = this.from.options.color.highlight.border;\n toColor = this.to.options.color.highlight.border;\n\n if (this.from.selected === false && this.to.selected === false) {\n fromColor = util.overrideOpacity(this.from.options.color.border, this.options.color.opacity);\n toColor = util.overrideOpacity(this.to.options.color.border, this.options.color.opacity);\n } else if (this.from.selected === true && this.to.selected === false) {\n toColor = this.to.options.color.border;\n } else if (this.from.selected === false && this.to.selected === true) {\n fromColor = this.from.options.color.border;\n }\n grd.addColorStop(0, fromColor);\n grd.addColorStop(1, toColor);\n\n // -------------------- this returns -------------------- //\n return grd;\n }\n\n if (this.colorDirty === true) {\n if (colorOptions.inherit === \"to\") {\n this.color.highlight = this.to.options.color.highlight.border;\n this.color.hover = this.to.options.color.hover.border;\n this.color.color = util.overrideOpacity(this.to.options.color.border, colorOptions.opacity);\n } else {\n // (this.options.color.inherit.source === \"from\") {\n this.color.highlight = this.from.options.color.highlight.border;\n this.color.hover = this.from.options.color.hover.border;\n this.color.color = util.overrideOpacity(this.from.options.color.border, colorOptions.opacity);\n }\n }\n } else if (this.colorDirty === true) {\n this.color.highlight = colorOptions.highlight;\n this.color.hover = colorOptions.hover;\n this.color.color = util.overrideOpacity(colorOptions.color, colorOptions.opacity);\n }\n\n // if color inherit is on and gradients are used, the function has already returned by now.\n this.colorDirty = false;\n\n if (selected === true) {\n return this.color.highlight;\n } else if (hover === true) {\n return this.color.hover;\n } else {\n return this.color.color;\n }\n }\n\n /**\n * Draw a line from a node to itself, a circle\n * @param {CanvasRenderingContext2D} ctx\n * @param {Number} x\n * @param {Number} y\n * @param {Number} radius\n * @private\n */\n }, {\n key: '_circle',\n value: function _circle(ctx, x, y, radius) {\n // draw shadow if enabled\n this.enableShadow(ctx);\n\n // draw a circle\n ctx.beginPath();\n ctx.arc(x, y, radius, 0, 2 * Math.PI, false);\n ctx.stroke();\n\n // disable shadows for other elements.\n this.disableShadow(ctx);\n }\n\n /**\n * Calculate the distance between a point (x3,y3) and a line segment from\n * (x1,y1) to (x2,y2).\n * http://stackoverflow.com/questions/849211/shortest-distancae-between-a-point-and-a-line-segment\n * @param {number} x1\n * @param {number} y1\n * @param {number} x2\n * @param {number} y2\n * @param {number} x3\n * @param {number} y3\n * @private\n */\n }, {\n key: 'getDistanceToEdge',\n value: function getDistanceToEdge(x1, y1, x2, y2, x3, y3, via) {\n // x3,y3 is the point\n var returnValue = 0;\n if (this.from != this.to) {\n returnValue = this._getDistanceToEdge(x1, y1, x2, y2, x3, y3, via);\n } else {\n var _getCircleData6 = this._getCircleData();\n\n var _getCircleData62 = _slicedToArray(_getCircleData6, 3);\n\n var x = _getCircleData62[0];\n var y = _getCircleData62[1];\n var radius = _getCircleData62[2];\n\n var dx = x - x3;\n var dy = y - y3;\n returnValue = Math.abs(Math.sqrt(dx * dx + dy * dy) - radius);\n }\n\n if (this.labelModule.size.left < x3 && this.labelModule.size.left + this.labelModule.size.width > x3 && this.labelModule.size.top < y3 && this.labelModule.size.top + this.labelModule.size.height > y3) {\n return 0;\n } else {\n return returnValue;\n }\n }\n }, {\n key: '_getDistanceToLine',\n value: function _getDistanceToLine(x1, y1, x2, y2, x3, y3) {\n var px = x2 - x1;\n var py = y2 - y1;\n var something = px * px + py * py;\n var u = ((x3 - x1) * px + (y3 - y1) * py) / something;\n\n if (u > 1) {\n u = 1;\n } else if (u < 0) {\n u = 0;\n }\n\n var x = x1 + u * px;\n var y = y1 + u * py;\n var dx = x - x3;\n var dy = y - y3;\n\n //# Note: If the actual distance does not matter,\n //# if you only want to compare what this function\n //# returns to other results of this function, you\n //# can just return the squared distance instead\n //# (i.e. remove the sqrt) to gain a little performance\n\n return Math.sqrt(dx * dx + dy * dy);\n }\n\n /**\n *\n * @param ctx\n * @param position\n * @param viaNode\n */\n }, {\n key: 'getArrowData',\n value: function getArrowData(ctx, position, viaNode, selected, hover) {\n // set lets\n var angle = undefined;\n var arrowPoint = undefined;\n var node1 = undefined;\n var node2 = undefined;\n var guideOffset = undefined;\n var scaleFactor = undefined;\n var lineWidth = this.getLineWidth(selected, hover);\n\n if (position === 'from') {\n node1 = this.from;\n node2 = this.to;\n guideOffset = 0.1;\n scaleFactor = this.options.arrows.from.scaleFactor;\n } else if (position === 'to') {\n node1 = this.to;\n node2 = this.from;\n guideOffset = -0.1;\n scaleFactor = this.options.arrows.to.scaleFactor;\n } else {\n node1 = this.to;\n node2 = this.from;\n scaleFactor = this.options.arrows.middle.scaleFactor;\n }\n\n // if not connected to itself\n if (node1 != node2) {\n if (position !== 'middle') {\n // draw arrow head\n if (this.options.smooth.enabled === true) {\n arrowPoint = this.findBorderPosition(node1, ctx, { via: viaNode });\n var guidePos = this.getPoint(Math.max(0.0, Math.min(1.0, arrowPoint.t + guideOffset)), viaNode);\n angle = Math.atan2(arrowPoint.y - guidePos.y, arrowPoint.x - guidePos.x);\n } else {\n angle = Math.atan2(node1.y - node2.y, node1.x - node2.x);\n arrowPoint = this.findBorderPosition(node1, ctx);\n }\n } else {\n angle = Math.atan2(node1.y - node2.y, node1.x - node2.x);\n arrowPoint = this.getPoint(0.5, viaNode); // this is 0.6 to account for the size of the arrow.\n }\n } else {\n var _getCircleData7 = this._getCircleData(ctx);\n\n var _getCircleData72 = _slicedToArray(_getCircleData7, 3);\n\n var x = _getCircleData72[0];\n var y = _getCircleData72[1];\n var radius = _getCircleData72[2];\n\n if (position === 'from') {\n arrowPoint = this.findBorderPosition(this.from, ctx, { x: x, y: y, low: 0.25, high: 0.6, direction: -1 });\n angle = arrowPoint.t * -2 * Math.PI + 1.5 * Math.PI + 0.1 * Math.PI;\n } else if (position === 'to') {\n arrowPoint = this.findBorderPosition(this.from, ctx, { x: x, y: y, low: 0.6, high: 1.0, direction: 1 });\n angle = arrowPoint.t * -2 * Math.PI + 1.5 * Math.PI - 1.1 * Math.PI;\n } else {\n arrowPoint = this._pointOnCircle(x, y, radius, 0.175);\n angle = 3.9269908169872414; // === 0.175 * -2 * Math.PI + 1.5 * Math.PI + 0.1 * Math.PI;\n }\n }\n\n var length = 15 * scaleFactor + 3 * lineWidth; // 3* lineWidth is the width of the edge.\n\n var xi = arrowPoint.x - length * 0.9 * Math.cos(angle);\n var yi = arrowPoint.y - length * 0.9 * Math.sin(angle);\n var arrowCore = { x: xi, y: yi };\n\n return { point: arrowPoint, core: arrowCore, angle: angle, length: length };\n }\n\n /**\n *\n * @param ctx\n * @param selected\n * @param hover\n * @param arrowData\n */\n }, {\n key: 'drawArrowHead',\n value: function drawArrowHead(ctx, selected, hover, arrowData) {\n // set style\n ctx.strokeStyle = this.getColor(ctx, selected, hover);\n ctx.fillStyle = ctx.strokeStyle;\n ctx.lineWidth = this.getLineWidth(selected, hover);\n\n // draw arrow at the end of the line\n ctx.arrow(arrowData.point.x, arrowData.point.y, arrowData.angle, arrowData.length);\n\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.fill();\n // disable shadows for other elements.\n this.disableShadow(ctx);\n }\n }, {\n key: 'enableShadow',\n value: function enableShadow(ctx) {\n if (this.options.shadow.enabled === true) {\n ctx.shadowColor = this.options.shadow.color;\n ctx.shadowBlur = this.options.shadow.size;\n ctx.shadowOffsetX = this.options.shadow.x;\n ctx.shadowOffsetY = this.options.shadow.y;\n }\n }\n }, {\n key: 'disableShadow',\n value: function disableShadow(ctx) {\n if (this.options.shadow.enabled === true) {\n ctx.shadowColor = 'rgba(0,0,0,0)';\n ctx.shadowBlur = 0;\n ctx.shadowOffsetX = 0;\n ctx.shadowOffsetY = 0;\n }\n }\n }]);\n\n return EdgeBase;\n })();\n\n exports['default'] = EdgeBase;\n module.exports = exports['default'];\n\n // draw circle\n\n/***/ },\n/* 86 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x2, _x3, _x4) { var _again = true; _function: while (_again) { var object = _x2, property = _x3, receiver = _x4; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x2 = parent; _x3 = property; _x4 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if (\"value\" in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { \"default\": obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function, not \" + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilBezierEdgeBase = __webpack_require__(84);\n\n var _utilBezierEdgeBase2 = _interopRequireDefault(_utilBezierEdgeBase);\n\n var BezierEdgeDynamic = (function (_BezierEdgeBase) {\n _inherits(BezierEdgeDynamic, _BezierEdgeBase);\n\n function BezierEdgeDynamic(options, body, labelModule) {\n var _this = this;\n\n _classCallCheck(this, BezierEdgeDynamic);\n\n //this.via = undefined; // Here for completeness but not allowed to defined before super() is invoked.\n _get(Object.getPrototypeOf(BezierEdgeDynamic.prototype), \"constructor\", this).call(this, options, body, labelModule); // --> this calls the setOptions below\n this._boundFunction = function () {\n _this.positionBezierNode();\n };\n this.body.emitter.on(\"_repositionBezierNodes\", this._boundFunction);\n }\n\n _createClass(BezierEdgeDynamic, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n // check if the physics has changed.\n var physicsChange = false;\n if (this.options.physics !== options.physics) {\n physicsChange = true;\n }\n\n // set the options and the to and from nodes\n this.options = options;\n this.id = this.options.id;\n this.from = this.body.nodes[this.options.from];\n this.to = this.body.nodes[this.options.to];\n\n // setup the support node and connect\n this.setupSupportNode();\n this.connect();\n\n // when we change the physics state of the edge, we reposition the support node.\n if (physicsChange === true) {\n this.via.setOptions({ physics: this.options.physics });\n this.positionBezierNode();\n }\n }\n }, {\n key: \"connect\",\n value: function connect() {\n this.from = this.body.nodes[this.options.from];\n this.to = this.body.nodes[this.options.to];\n if (this.from === undefined || this.to === undefined || this.options.physics === false) {\n this.via.setOptions({ physics: false });\n } else {\n // fix weird behaviour where a self referencing node has physics enabled\n if (this.from.id === this.to.id) {\n this.via.setOptions({ physics: false });\n } else {\n this.via.setOptions({ physics: true });\n }\n }\n }\n\n /**\n * remove the support nodes\n * @returns {boolean}\n */\n }, {\n key: \"cleanup\",\n value: function cleanup() {\n this.body.emitter.off(\"_repositionBezierNodes\", this._boundFunction);\n if (this.via !== undefined) {\n delete this.body.nodes[this.via.id];\n this.via = undefined;\n return true;\n }\n return false;\n }\n\n /**\n * Bezier curves require an anchor point to calculate the smooth flow. These points are nodes. These nodes are invisible but\n * are used for the force calculation.\n *\n * The changed data is not called, if needed, it is returned by the main edge constructor.\n * @private\n */\n }, {\n key: \"setupSupportNode\",\n value: function setupSupportNode() {\n if (this.via === undefined) {\n var nodeId = \"edgeId:\" + this.id;\n var node = this.body.functions.createNode({\n id: nodeId,\n shape: 'circle',\n physics: true,\n hidden: true\n });\n this.body.nodes[nodeId] = node;\n this.via = node;\n this.via.parentEdgeId = this.id;\n this.positionBezierNode();\n }\n }\n }, {\n key: \"positionBezierNode\",\n value: function positionBezierNode() {\n if (this.via !== undefined && this.from !== undefined && this.to !== undefined) {\n this.via.x = 0.5 * (this.from.x + this.to.x);\n this.via.y = 0.5 * (this.from.y + this.to.y);\n } else if (this.via !== undefined) {\n this.via.x = 0;\n this.via.y = 0;\n }\n }\n\n /**\n * Draw a line between two nodes\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n }, {\n key: \"_line\",\n value: function _line(ctx, viaNode) {\n // draw a straight line\n ctx.beginPath();\n ctx.moveTo(this.fromPoint.x, this.fromPoint.y);\n // fallback to normal straight edges\n if (viaNode.x === undefined) {\n ctx.lineTo(this.toPoint.x, this.toPoint.y);\n } else {\n ctx.quadraticCurveTo(viaNode.x, viaNode.y, this.toPoint.x, this.toPoint.y);\n }\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.stroke();\n this.disableShadow(ctx);\n }\n }, {\n key: \"getViaNode\",\n value: function getViaNode() {\n return this.via;\n }\n\n /**\n * Combined function of pointOnLine and pointOnBezier. This gives the coordinates of a point on the line at a certain percentage of the way\n * @param percentage\n * @param viaNode\n * @returns {{x: number, y: number}}\n * @private\n */\n }, {\n key: \"getPoint\",\n value: function getPoint(percentage) {\n var viaNode = arguments.length <= 1 || arguments[1] === undefined ? this.via : arguments[1];\n\n var t = percentage;\n var x = Math.pow(1 - t, 2) * this.fromPoint.x + 2 * t * (1 - t) * viaNode.x + Math.pow(t, 2) * this.toPoint.x;\n var y = Math.pow(1 - t, 2) * this.fromPoint.y + 2 * t * (1 - t) * viaNode.y + Math.pow(t, 2) * this.toPoint.y;\n\n return { x: x, y: y };\n }\n }, {\n key: \"_findBorderPosition\",\n value: function _findBorderPosition(nearNode, ctx) {\n return this._findBorderPositionBezier(nearNode, ctx, this.via);\n }\n }, {\n key: \"_getDistanceToEdge\",\n value: function _getDistanceToEdge(x1, y1, x2, y2, x3, y3) {\n // x3,y3 is the point\n return this._getDistanceToBezierEdge(x1, y1, x2, y2, x3, y3, this.via);\n }\n }]);\n\n return BezierEdgeDynamic;\n })(_utilBezierEdgeBase2[\"default\"]);\n\n exports[\"default\"] = BezierEdgeDynamic;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 87 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x4, _x5, _x6) { var _again = true; _function: while (_again) { var object = _x4, property = _x5, receiver = _x6; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x4 = parent; _x5 = property; _x6 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilBezierEdgeBase = __webpack_require__(84);\n\n var _utilBezierEdgeBase2 = _interopRequireDefault(_utilBezierEdgeBase);\n\n var BezierEdgeStatic = (function (_BezierEdgeBase) {\n _inherits(BezierEdgeStatic, _BezierEdgeBase);\n\n function BezierEdgeStatic(options, body, labelModule) {\n _classCallCheck(this, BezierEdgeStatic);\n\n _get(Object.getPrototypeOf(BezierEdgeStatic.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n /**\n * Draw a line between two nodes\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n\n _createClass(BezierEdgeStatic, [{\n key: '_line',\n value: function _line(ctx, viaNode) {\n // draw a straight line\n ctx.beginPath();\n ctx.moveTo(this.fromPoint.x, this.fromPoint.y);\n\n // fallback to normal straight edges\n if (viaNode.x === undefined) {\n ctx.lineTo(this.toPoint.x, this.toPoint.y);\n } else {\n ctx.quadraticCurveTo(viaNode.x, viaNode.y, this.toPoint.x, this.toPoint.y);\n }\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.stroke();\n this.disableShadow(ctx);\n }\n }, {\n key: 'getViaNode',\n value: function getViaNode() {\n return this._getViaCoordinates();\n }\n\n /**\n * We do not use the to and fromPoints here to make the via nodes the same as edges without arrows.\n * @returns {{x: undefined, y: undefined}}\n * @private\n */\n }, {\n key: '_getViaCoordinates',\n value: function _getViaCoordinates() {\n var xVia = undefined;\n var yVia = undefined;\n var factor = this.options.smooth.roundness;\n var type = this.options.smooth.type;\n var dx = Math.abs(this.from.x - this.to.x);\n var dy = Math.abs(this.from.y - this.to.y);\n if (type === 'discrete' || type === 'diagonalCross') {\n if (Math.abs(this.from.x - this.to.x) <= Math.abs(this.from.y - this.to.y)) {\n if (this.from.y >= this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dy;\n yVia = this.from.y - factor * dy;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dy;\n yVia = this.from.y - factor * dy;\n }\n } else if (this.from.y < this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dy;\n yVia = this.from.y + factor * dy;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dy;\n yVia = this.from.y + factor * dy;\n }\n }\n if (type === \"discrete\") {\n xVia = dx < factor * dy ? this.from.x : xVia;\n }\n } else if (Math.abs(this.from.x - this.to.x) > Math.abs(this.from.y - this.to.y)) {\n if (this.from.y >= this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dx;\n yVia = this.from.y - factor * dx;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dx;\n yVia = this.from.y - factor * dx;\n }\n } else if (this.from.y < this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dx;\n yVia = this.from.y + factor * dx;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dx;\n yVia = this.from.y + factor * dx;\n }\n }\n if (type === \"discrete\") {\n yVia = dy < factor * dx ? this.from.y : yVia;\n }\n }\n } else if (type === \"straightCross\") {\n if (Math.abs(this.from.x - this.to.x) <= Math.abs(this.from.y - this.to.y)) {\n // up - down\n xVia = this.from.x;\n if (this.from.y < this.to.y) {\n yVia = this.to.y - (1 - factor) * dy;\n } else {\n yVia = this.to.y + (1 - factor) * dy;\n }\n } else if (Math.abs(this.from.x - this.to.x) > Math.abs(this.from.y - this.to.y)) {\n // left - right\n if (this.from.x < this.to.x) {\n xVia = this.to.x - (1 - factor) * dx;\n } else {\n xVia = this.to.x + (1 - factor) * dx;\n }\n yVia = this.from.y;\n }\n } else if (type === 'horizontal') {\n if (this.from.x < this.to.x) {\n xVia = this.to.x - (1 - factor) * dx;\n } else {\n xVia = this.to.x + (1 - factor) * dx;\n }\n yVia = this.from.y;\n } else if (type === 'vertical') {\n xVia = this.from.x;\n if (this.from.y < this.to.y) {\n yVia = this.to.y - (1 - factor) * dy;\n } else {\n yVia = this.to.y + (1 - factor) * dy;\n }\n } else if (type === 'curvedCW') {\n dx = this.to.x - this.from.x;\n dy = this.from.y - this.to.y;\n var radius = Math.sqrt(dx * dx + dy * dy);\n var pi = Math.PI;\n\n var originalAngle = Math.atan2(dy, dx);\n var myAngle = (originalAngle + (factor * 0.5 + 0.5) * pi) % (2 * pi);\n\n xVia = this.from.x + (factor * 0.5 + 0.5) * radius * Math.sin(myAngle);\n yVia = this.from.y + (factor * 0.5 + 0.5) * radius * Math.cos(myAngle);\n } else if (type === 'curvedCCW') {\n dx = this.to.x - this.from.x;\n dy = this.from.y - this.to.y;\n var radius = Math.sqrt(dx * dx + dy * dy);\n var pi = Math.PI;\n\n var originalAngle = Math.atan2(dy, dx);\n var myAngle = (originalAngle + (-factor * 0.5 + 0.5) * pi) % (2 * pi);\n\n xVia = this.from.x + (factor * 0.5 + 0.5) * radius * Math.sin(myAngle);\n yVia = this.from.y + (factor * 0.5 + 0.5) * radius * Math.cos(myAngle);\n } else {\n // continuous\n if (Math.abs(this.from.x - this.to.x) <= Math.abs(this.from.y - this.to.y)) {\n if (this.from.y >= this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dy;\n yVia = this.from.y - factor * dy;\n xVia = this.to.x < xVia ? this.to.x : xVia;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dy;\n yVia = this.from.y - factor * dy;\n xVia = this.to.x > xVia ? this.to.x : xVia;\n }\n } else if (this.from.y < this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dy;\n yVia = this.from.y + factor * dy;\n xVia = this.to.x < xVia ? this.to.x : xVia;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dy;\n yVia = this.from.y + factor * dy;\n xVia = this.to.x > xVia ? this.to.x : xVia;\n }\n }\n } else if (Math.abs(this.from.x - this.to.x) > Math.abs(this.from.y - this.to.y)) {\n if (this.from.y >= this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dx;\n yVia = this.from.y - factor * dx;\n yVia = this.to.y > yVia ? this.to.y : yVia;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dx;\n yVia = this.from.y - factor * dx;\n yVia = this.to.y > yVia ? this.to.y : yVia;\n }\n } else if (this.from.y < this.to.y) {\n if (this.from.x <= this.to.x) {\n xVia = this.from.x + factor * dx;\n yVia = this.from.y + factor * dx;\n yVia = this.to.y < yVia ? this.to.y : yVia;\n } else if (this.from.x > this.to.x) {\n xVia = this.from.x - factor * dx;\n yVia = this.from.y + factor * dx;\n yVia = this.to.y < yVia ? this.to.y : yVia;\n }\n }\n }\n }\n return { x: xVia, y: yVia };\n }\n }, {\n key: '_findBorderPosition',\n value: function _findBorderPosition(nearNode, ctx) {\n var options = arguments.length <= 2 || arguments[2] === undefined ? {} : arguments[2];\n\n return this._findBorderPositionBezier(nearNode, ctx, options.via);\n }\n }, {\n key: '_getDistanceToEdge',\n value: function _getDistanceToEdge(x1, y1, x2, y2, x3, y3) {\n var viaNode = arguments.length <= 6 || arguments[6] === undefined ? this._getViaCoordinates() : arguments[6];\n // x3,y3 is the point\n return this._getDistanceToBezierEdge(x1, y1, x2, y2, x3, y3, viaNode);\n }\n\n /**\n * Combined function of pointOnLine and pointOnBezier. This gives the coordinates of a point on the line at a certain percentage of the way\n * @param percentage\n * @param viaNode\n * @returns {{x: number, y: number}}\n * @private\n */\n }, {\n key: 'getPoint',\n value: function getPoint(percentage) {\n var viaNode = arguments.length <= 1 || arguments[1] === undefined ? this._getViaCoordinates() : arguments[1];\n\n var t = percentage;\n var x = Math.pow(1 - t, 2) * this.fromPoint.x + 2 * t * (1 - t) * viaNode.x + Math.pow(t, 2) * this.toPoint.x;\n var y = Math.pow(1 - t, 2) * this.fromPoint.y + 2 * t * (1 - t) * viaNode.y + Math.pow(t, 2) * this.toPoint.y;\n\n return { x: x, y: y };\n }\n }]);\n\n return BezierEdgeStatic;\n })(_utilBezierEdgeBase2['default']);\n\n exports['default'] = BezierEdgeStatic;\n module.exports = exports['default'];\n\n/***/ },\n/* 88 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _utilEdgeBase = __webpack_require__(85);\n\n var _utilEdgeBase2 = _interopRequireDefault(_utilEdgeBase);\n\n var StraightEdge = (function (_EdgeBase) {\n _inherits(StraightEdge, _EdgeBase);\n\n function StraightEdge(options, body, labelModule) {\n _classCallCheck(this, StraightEdge);\n\n _get(Object.getPrototypeOf(StraightEdge.prototype), 'constructor', this).call(this, options, body, labelModule);\n }\n\n /**\n * Draw a line between two nodes\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n\n _createClass(StraightEdge, [{\n key: '_line',\n value: function _line(ctx) {\n // draw a straight line\n ctx.beginPath();\n ctx.moveTo(this.fromPoint.x, this.fromPoint.y);\n ctx.lineTo(this.toPoint.x, this.toPoint.y);\n // draw shadow if enabled\n this.enableShadow(ctx);\n ctx.stroke();\n this.disableShadow(ctx);\n }\n }, {\n key: 'getViaNode',\n value: function getViaNode() {\n return undefined;\n }\n\n /**\n * Combined function of pointOnLine and pointOnBezier. This gives the coordinates of a point on the line at a certain percentage of the way\n * @param percentage\n * @param via\n * @returns {{x: number, y: number}}\n * @private\n */\n }, {\n key: 'getPoint',\n value: function getPoint(percentage) {\n return {\n x: (1 - percentage) * this.fromPoint.x + percentage * this.toPoint.x,\n y: (1 - percentage) * this.fromPoint.y + percentage * this.toPoint.y\n };\n }\n }, {\n key: '_findBorderPosition',\n value: function _findBorderPosition(nearNode, ctx) {\n var node1 = this.to;\n var node2 = this.from;\n if (nearNode.id === this.from.id) {\n node1 = this.from;\n node2 = this.to;\n }\n\n var angle = Math.atan2(node1.y - node2.y, node1.x - node2.x);\n var dx = node1.x - node2.x;\n var dy = node1.y - node2.y;\n var edgeSegmentLength = Math.sqrt(dx * dx + dy * dy);\n var toBorderDist = nearNode.distanceToBorder(ctx, angle);\n var toBorderPoint = (edgeSegmentLength - toBorderDist) / edgeSegmentLength;\n\n var borderPos = {};\n borderPos.x = (1 - toBorderPoint) * node2.x + toBorderPoint * node1.x;\n borderPos.y = (1 - toBorderPoint) * node2.y + toBorderPoint * node1.y;\n\n return borderPos;\n }\n }, {\n key: '_getDistanceToEdge',\n value: function _getDistanceToEdge(x1, y1, x2, y2, x3, y3) {\n // x3,y3 is the point\n return this._getDistanceToLine(x1, y1, x2, y2, x3, y3);\n }\n }]);\n\n return StraightEdge;\n })(_utilEdgeBase2['default']);\n\n exports['default'] = StraightEdge;\n module.exports = exports['default'];\n\n/***/ },\n/* 89 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _componentsPhysicsBarnesHutSolver = __webpack_require__(90);\n\n var _componentsPhysicsBarnesHutSolver2 = _interopRequireDefault(_componentsPhysicsBarnesHutSolver);\n\n var _componentsPhysicsRepulsionSolver = __webpack_require__(91);\n\n var _componentsPhysicsRepulsionSolver2 = _interopRequireDefault(_componentsPhysicsRepulsionSolver);\n\n var _componentsPhysicsHierarchicalRepulsionSolver = __webpack_require__(92);\n\n var _componentsPhysicsHierarchicalRepulsionSolver2 = _interopRequireDefault(_componentsPhysicsHierarchicalRepulsionSolver);\n\n var _componentsPhysicsSpringSolver = __webpack_require__(93);\n\n var _componentsPhysicsSpringSolver2 = _interopRequireDefault(_componentsPhysicsSpringSolver);\n\n var _componentsPhysicsHierarchicalSpringSolver = __webpack_require__(94);\n\n var _componentsPhysicsHierarchicalSpringSolver2 = _interopRequireDefault(_componentsPhysicsHierarchicalSpringSolver);\n\n var _componentsPhysicsCentralGravitySolver = __webpack_require__(95);\n\n var _componentsPhysicsCentralGravitySolver2 = _interopRequireDefault(_componentsPhysicsCentralGravitySolver);\n\n var _componentsPhysicsFA2BasedRepulsionSolver = __webpack_require__(96);\n\n var _componentsPhysicsFA2BasedRepulsionSolver2 = _interopRequireDefault(_componentsPhysicsFA2BasedRepulsionSolver);\n\n var _componentsPhysicsFA2BasedCentralGravitySolver = __webpack_require__(97);\n\n var _componentsPhysicsFA2BasedCentralGravitySolver2 = _interopRequireDefault(_componentsPhysicsFA2BasedCentralGravitySolver);\n\n var util = __webpack_require__(1);\n\n var PhysicsEngine = (function () {\n function PhysicsEngine(body) {\n _classCallCheck(this, PhysicsEngine);\n\n this.body = body;\n this.physicsBody = { physicsNodeIndices: [], physicsEdgeIndices: [], forces: {}, velocities: {} };\n\n this.physicsEnabled = true;\n this.simulationInterval = 1000 / 60;\n this.requiresTimeout = true;\n this.previousStates = {};\n this.referenceState = {};\n this.freezeCache = {};\n this.renderTimer = undefined;\n\n // parameters for the adaptive timestep\n this.adaptiveTimestep = false;\n this.adaptiveTimestepEnabled = false;\n this.adaptiveCounter = 0;\n this.adaptiveInterval = 3;\n\n this.stabilized = false;\n this.startedStabilization = false;\n this.stabilizationIterations = 0;\n this.ready = false; // will be set to true if the stabilize\n\n // default options\n this.options = {};\n this.defaultOptions = {\n enabled: true,\n barnesHut: {\n theta: 0.5,\n gravitationalConstant: -2000,\n centralGravity: 0.3,\n springLength: 95,\n springConstant: 0.04,\n damping: 0.09,\n avoidOverlap: 0\n },\n forceAtlas2Based: {\n theta: 0.5,\n gravitationalConstant: -50,\n centralGravity: 0.01,\n springConstant: 0.08,\n springLength: 100,\n damping: 0.4,\n avoidOverlap: 0\n },\n repulsion: {\n centralGravity: 0.2,\n springLength: 200,\n springConstant: 0.05,\n nodeDistance: 100,\n damping: 0.09,\n avoidOverlap: 0\n },\n hierarchicalRepulsion: {\n centralGravity: 0.0,\n springLength: 100,\n springConstant: 0.01,\n nodeDistance: 120,\n damping: 0.09\n },\n maxVelocity: 50,\n minVelocity: 0.75, // px/s\n solver: 'barnesHut',\n stabilization: {\n enabled: true,\n iterations: 1000, // maximum number of iteration to stabilize\n updateInterval: 50,\n onlyDynamicEdges: false,\n fit: true\n },\n timestep: 0.5,\n adaptiveTimestep: true\n };\n util.extend(this.options, this.defaultOptions);\n this.timestep = 0.5;\n this.layoutFailed = false;\n\n this.bindEventListeners();\n }\n\n _createClass(PhysicsEngine, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this = this;\n\n this.body.emitter.on('initPhysics', function () {\n _this.initPhysics();\n });\n this.body.emitter.on('_layoutFailed', function () {\n _this.layoutFailed = true;\n });\n this.body.emitter.on('resetPhysics', function () {\n _this.stopSimulation();_this.ready = false;\n });\n this.body.emitter.on('disablePhysics', function () {\n _this.physicsEnabled = false;_this.stopSimulation();\n });\n this.body.emitter.on('restorePhysics', function () {\n _this.setOptions(_this.options);\n if (_this.ready === true) {\n _this.startSimulation();\n }\n });\n this.body.emitter.on('startSimulation', function () {\n if (_this.ready === true) {\n _this.startSimulation();\n }\n });\n this.body.emitter.on('stopSimulation', function () {\n _this.stopSimulation();\n });\n this.body.emitter.on('destroy', function () {\n _this.stopSimulation(false);\n _this.body.emitter.off();\n });\n // this event will trigger a rebuilding of the cache everything. Used when nodes or edges have been added or removed.\n this.body.emitter.on(\"_dataChanged\", function () {\n // update shortcut lists\n _this.updatePhysicsData();\n });\n\n // debug: show forces\n // this.body.emitter.on(\"afterDrawing\", (ctx) => {this._drawForces(ctx);});\n }\n\n /**\n * set the physics options\n * @param options\n */\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n if (options === false) {\n this.options.enabled = false;\n this.physicsEnabled = false;\n this.stopSimulation();\n } else {\n this.physicsEnabled = true;\n util.selectiveNotDeepExtend(['stabilization'], this.options, options);\n util.mergeOptions(this.options, options, 'stabilization');\n\n if (options.enabled === undefined) {\n this.options.enabled = true;\n }\n\n if (this.options.enabled === false) {\n this.physicsEnabled = false;\n this.stopSimulation();\n }\n\n // set the timestep\n this.timestep = this.options.timestep;\n }\n }\n this.init();\n }\n\n /**\n * configure the engine.\n */\n }, {\n key: 'init',\n value: function init() {\n var options;\n if (this.options.solver === 'forceAtlas2Based') {\n options = this.options.forceAtlas2Based;\n this.nodesSolver = new _componentsPhysicsFA2BasedRepulsionSolver2['default'](this.body, this.physicsBody, options);\n this.edgesSolver = new _componentsPhysicsSpringSolver2['default'](this.body, this.physicsBody, options);\n this.gravitySolver = new _componentsPhysicsFA2BasedCentralGravitySolver2['default'](this.body, this.physicsBody, options);\n } else if (this.options.solver === 'repulsion') {\n options = this.options.repulsion;\n this.nodesSolver = new _componentsPhysicsRepulsionSolver2['default'](this.body, this.physicsBody, options);\n this.edgesSolver = new _componentsPhysicsSpringSolver2['default'](this.body, this.physicsBody, options);\n this.gravitySolver = new _componentsPhysicsCentralGravitySolver2['default'](this.body, this.physicsBody, options);\n } else if (this.options.solver === 'hierarchicalRepulsion') {\n options = this.options.hierarchicalRepulsion;\n this.nodesSolver = new _componentsPhysicsHierarchicalRepulsionSolver2['default'](this.body, this.physicsBody, options);\n this.edgesSolver = new _componentsPhysicsHierarchicalSpringSolver2['default'](this.body, this.physicsBody, options);\n this.gravitySolver = new _componentsPhysicsCentralGravitySolver2['default'](this.body, this.physicsBody, options);\n } else {\n // barnesHut\n options = this.options.barnesHut;\n this.nodesSolver = new _componentsPhysicsBarnesHutSolver2['default'](this.body, this.physicsBody, options);\n this.edgesSolver = new _componentsPhysicsSpringSolver2['default'](this.body, this.physicsBody, options);\n this.gravitySolver = new _componentsPhysicsCentralGravitySolver2['default'](this.body, this.physicsBody, options);\n }\n\n this.modelOptions = options;\n }\n\n /**\n * initialize the engine\n */\n }, {\n key: 'initPhysics',\n value: function initPhysics() {\n if (this.physicsEnabled === true && this.options.enabled === true) {\n if (this.options.stabilization.enabled === true) {\n this.stabilize();\n } else {\n this.stabilized = false;\n this.ready = true;\n this.body.emitter.emit('fit', {}, this.layoutFailed); // if the layout failed, we use the approximation for the zoom\n this.startSimulation();\n }\n } else {\n this.ready = true;\n this.body.emitter.emit('fit');\n }\n }\n\n /**\n * Start the simulation\n */\n }, {\n key: 'startSimulation',\n value: function startSimulation() {\n if (this.physicsEnabled === true && this.options.enabled === true) {\n this.stabilized = false;\n\n // when visible, adaptivity is disabled.\n this.adaptiveTimestep = false;\n\n // this sets the width of all nodes initially which could be required for the avoidOverlap\n this.body.emitter.emit(\"_resizeNodes\");\n if (this.viewFunction === undefined) {\n this.viewFunction = this.simulationStep.bind(this);\n this.body.emitter.on('initRedraw', this.viewFunction);\n this.body.emitter.emit('_startRendering');\n }\n } else {\n this.body.emitter.emit('_redraw');\n }\n }\n\n /**\n * Stop the simulation, force stabilization.\n */\n }, {\n key: 'stopSimulation',\n value: function stopSimulation() {\n var emit = arguments.length <= 0 || arguments[0] === undefined ? true : arguments[0];\n\n this.stabilized = true;\n if (emit === true) {\n this._emitStabilized();\n }\n if (this.viewFunction !== undefined) {\n this.body.emitter.off('initRedraw', this.viewFunction);\n this.viewFunction = undefined;\n if (emit === true) {\n this.body.emitter.emit('_stopRendering');\n }\n }\n }\n\n /**\n * The viewFunction inserts this step into each render loop. It calls the physics tick and handles the cleanup at stabilized.\n *\n */\n }, {\n key: 'simulationStep',\n value: function simulationStep() {\n // check if the physics have settled\n var startTime = Date.now();\n this.physicsTick();\n var physicsTime = Date.now() - startTime;\n\n // run double speed if it is a little graph\n if ((physicsTime < 0.4 * this.simulationInterval || this.runDoubleSpeed === true) && this.stabilized === false) {\n this.physicsTick();\n\n // this makes sure there is no jitter. The decision is taken once to run it at double speed.\n this.runDoubleSpeed = true;\n }\n\n if (this.stabilized === true) {\n this.stopSimulation();\n }\n }\n\n /**\n * trigger the stabilized event.\n * @private\n */\n }, {\n key: '_emitStabilized',\n value: function _emitStabilized() {\n var _this2 = this;\n\n var amountOfIterations = arguments.length <= 0 || arguments[0] === undefined ? this.stabilizationIterations : arguments[0];\n\n if (this.stabilizationIterations > 1 || this.startedStabilization === true) {\n setTimeout(function () {\n _this2.body.emitter.emit('stabilized', { iterations: amountOfIterations });\n _this2.startedStabilization = false;\n _this2.stabilizationIterations = 0;\n }, 0);\n }\n }\n\n /**\n * A single simulation step (or 'tick') in the physics simulation\n *\n * @private\n */\n }, {\n key: 'physicsTick',\n value: function physicsTick() {\n // this is here to ensure that there is no start event when the network is already stable.\n if (this.startedStabilization === false) {\n this.body.emitter.emit('startStabilizing');\n this.startedStabilization = true;\n }\n\n if (this.stabilized === false) {\n // adaptivity means the timestep adapts to the situation, only applicable for stabilization\n if (this.adaptiveTimestep === true && this.adaptiveTimestepEnabled === true) {\n // this is the factor for increasing the timestep on success.\n var factor = 1.2;\n\n // we assume the adaptive interval is\n if (this.adaptiveCounter % this.adaptiveInterval === 0) {\n // we leave the timestep stable for \"interval\" iterations.\n // first the big step and revert. Revert saves the reference state.\n this.timestep = 2 * this.timestep;\n this.calculateForces();\n this.moveNodes();\n this.revert();\n\n // now the normal step. Since this is the last step, it is the more stable one and we will take this.\n this.timestep = 0.5 * this.timestep;\n\n // since it's half the step, we do it twice.\n this.calculateForces();\n this.moveNodes();\n this.calculateForces();\n this.moveNodes();\n\n // we compare the two steps. if it is acceptable we double the step.\n if (this._evaluateStepQuality() === true) {\n this.timestep = factor * this.timestep;\n } else {\n // if not, we decrease the step to a minimum of the options timestep.\n // if the decreased timestep is smaller than the options step, we do not reset the counter\n // we assume that the options timestep is stable enough.\n if (this.timestep / factor < this.options.timestep) {\n this.timestep = this.options.timestep;\n } else {\n // if the timestep was larger than 2 times the option one we check the adaptivity again to ensure\n // that large instabilities do not form.\n this.adaptiveCounter = -1; // check again next iteration\n this.timestep = Math.max(this.options.timestep, this.timestep / factor);\n }\n }\n } else {\n // normal step, keeping timestep constant\n this.calculateForces();\n this.moveNodes();\n }\n\n // increment the counter\n this.adaptiveCounter += 1;\n } else {\n // case for the static timestep, we reset it to the one in options and take a normal step.\n this.timestep = this.options.timestep;\n this.calculateForces();\n this.moveNodes();\n }\n\n // determine if the network has stabilzied\n if (this.stabilized === true) {\n this.revert();\n }\n\n this.stabilizationIterations++;\n }\n }\n\n /**\n * Nodes and edges can have the physics toggles on or off. A collection of indices is created here so we can skip the check all the time.\n *\n * @private\n */\n }, {\n key: 'updatePhysicsData',\n value: function updatePhysicsData() {\n this.physicsBody.forces = {};\n this.physicsBody.physicsNodeIndices = [];\n this.physicsBody.physicsEdgeIndices = [];\n var nodes = this.body.nodes;\n var edges = this.body.edges;\n\n // get node indices for physics\n for (var nodeId in nodes) {\n if (nodes.hasOwnProperty(nodeId)) {\n if (nodes[nodeId].options.physics === true) {\n this.physicsBody.physicsNodeIndices.push(nodes[nodeId].id);\n }\n }\n }\n\n // get edge indices for physics\n for (var edgeId in edges) {\n if (edges.hasOwnProperty(edgeId)) {\n if (edges[edgeId].options.physics === true) {\n this.physicsBody.physicsEdgeIndices.push(edges[edgeId].id);\n }\n }\n }\n\n // get the velocity and the forces vector\n for (var i = 0; i < this.physicsBody.physicsNodeIndices.length; i++) {\n var nodeId = this.physicsBody.physicsNodeIndices[i];\n this.physicsBody.forces[nodeId] = { x: 0, y: 0 };\n\n // forces can be reset because they are recalculated. Velocities have to persist.\n if (this.physicsBody.velocities[nodeId] === undefined) {\n this.physicsBody.velocities[nodeId] = { x: 0, y: 0 };\n }\n }\n\n // clean deleted nodes from the velocity vector\n for (var nodeId in this.physicsBody.velocities) {\n if (nodes[nodeId] === undefined) {\n delete this.physicsBody.velocities[nodeId];\n }\n }\n }\n\n /**\n * Revert the simulation one step. This is done so after stabilization, every new start of the simulation will also say stabilized.\n */\n }, {\n key: 'revert',\n value: function revert() {\n var nodeIds = Object.keys(this.previousStates);\n var nodes = this.body.nodes;\n var velocities = this.physicsBody.velocities;\n this.referenceState = {};\n\n for (var i = 0; i < nodeIds.length; i++) {\n var nodeId = nodeIds[i];\n if (nodes[nodeId] !== undefined) {\n if (nodes[nodeId].options.physics === true) {\n this.referenceState[nodeId] = {\n positions: { x: nodes[nodeId].x, y: nodes[nodeId].y }\n };\n velocities[nodeId].x = this.previousStates[nodeId].vx;\n velocities[nodeId].y = this.previousStates[nodeId].vy;\n nodes[nodeId].x = this.previousStates[nodeId].x;\n nodes[nodeId].y = this.previousStates[nodeId].y;\n }\n } else {\n delete this.previousStates[nodeId];\n }\n }\n }\n\n /**\n * This compares the reference state to the current state\n */\n }, {\n key: '_evaluateStepQuality',\n value: function _evaluateStepQuality() {\n var dx = undefined,\n dy = undefined,\n dpos = undefined;\n var nodes = this.body.nodes;\n var reference = this.referenceState;\n var posThreshold = 0.3;\n\n for (var nodeId in this.referenceState) {\n if (this.referenceState.hasOwnProperty(nodeId) && nodes[nodeId] !== undefined) {\n dx = nodes[nodeId].x - reference[nodeId].positions.x;\n dy = nodes[nodeId].y - reference[nodeId].positions.y;\n\n dpos = Math.sqrt(Math.pow(dx, 2) + Math.pow(dy, 2));\n\n if (dpos > posThreshold) {\n return false;\n }\n }\n }\n return true;\n }\n\n /**\n * move the nodes one timestep and check if they are stabilized\n * @returns {boolean}\n */\n }, {\n key: 'moveNodes',\n value: function moveNodes() {\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var maxVelocity = this.options.maxVelocity ? this.options.maxVelocity : 1e9;\n var maxNodeVelocity = 0;\n var averageNodeVelocity = 0;\n\n // the velocity threshold (energy in the system) for the adaptivity toggle\n var velocityAdaptiveThreshold = 5;\n\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n var nodeVelocity = this._performStep(nodeId, maxVelocity);\n // stabilized is true if stabilized is true and velocity is smaller than vmin --> all nodes must be stabilized\n maxNodeVelocity = Math.max(maxNodeVelocity, nodeVelocity);\n averageNodeVelocity += nodeVelocity;\n }\n\n // evaluating the stabilized and adaptiveTimestepEnabled conditions\n this.adaptiveTimestepEnabled = averageNodeVelocity / nodeIndices.length < velocityAdaptiveThreshold;\n this.stabilized = maxNodeVelocity < this.options.minVelocity;\n }\n\n /**\n * Perform the actual step\n *\n * @param nodeId\n * @param maxVelocity\n * @returns {number}\n * @private\n */\n }, {\n key: '_performStep',\n value: function _performStep(nodeId, maxVelocity) {\n var node = this.body.nodes[nodeId];\n var timestep = this.timestep;\n var forces = this.physicsBody.forces;\n var velocities = this.physicsBody.velocities;\n\n // store the state so we can revert\n this.previousStates[nodeId] = { x: node.x, y: node.y, vx: velocities[nodeId].x, vy: velocities[nodeId].y };\n\n if (node.options.fixed.x === false) {\n var dx = this.modelOptions.damping * velocities[nodeId].x; // damping force\n var ax = (forces[nodeId].x - dx) / node.options.mass; // acceleration\n velocities[nodeId].x += ax * timestep; // velocity\n velocities[nodeId].x = Math.abs(velocities[nodeId].x) > maxVelocity ? velocities[nodeId].x > 0 ? maxVelocity : -maxVelocity : velocities[nodeId].x;\n node.x += velocities[nodeId].x * timestep; // position\n } else {\n forces[nodeId].x = 0;\n velocities[nodeId].x = 0;\n }\n\n if (node.options.fixed.y === false) {\n var dy = this.modelOptions.damping * velocities[nodeId].y; // damping force\n var ay = (forces[nodeId].y - dy) / node.options.mass; // acceleration\n velocities[nodeId].y += ay * timestep; // velocity\n velocities[nodeId].y = Math.abs(velocities[nodeId].y) > maxVelocity ? velocities[nodeId].y > 0 ? maxVelocity : -maxVelocity : velocities[nodeId].y;\n node.y += velocities[nodeId].y * timestep; // position\n } else {\n forces[nodeId].y = 0;\n velocities[nodeId].y = 0;\n }\n\n var totalVelocity = Math.sqrt(Math.pow(velocities[nodeId].x, 2) + Math.pow(velocities[nodeId].y, 2));\n return totalVelocity;\n }\n\n /**\n * calculate the forces for one physics iteration.\n */\n }, {\n key: 'calculateForces',\n value: function calculateForces() {\n this.gravitySolver.solve();\n this.nodesSolver.solve();\n this.edgesSolver.solve();\n }\n\n /**\n * When initializing and stabilizing, we can freeze nodes with a predefined position. This greatly speeds up stabilization\n * because only the supportnodes for the smoothCurves have to settle.\n *\n * @private\n */\n }, {\n key: '_freezeNodes',\n value: function _freezeNodes() {\n var nodes = this.body.nodes;\n for (var id in nodes) {\n if (nodes.hasOwnProperty(id)) {\n if (nodes[id].x && nodes[id].y) {\n this.freezeCache[id] = { x: nodes[id].options.fixed.x, y: nodes[id].options.fixed.y };\n nodes[id].options.fixed.x = true;\n nodes[id].options.fixed.y = true;\n }\n }\n }\n }\n\n /**\n * Unfreezes the nodes that have been frozen by _freezeDefinedNodes.\n *\n * @private\n */\n }, {\n key: '_restoreFrozenNodes',\n value: function _restoreFrozenNodes() {\n var nodes = this.body.nodes;\n for (var id in nodes) {\n if (nodes.hasOwnProperty(id)) {\n if (this.freezeCache[id] !== undefined) {\n nodes[id].options.fixed.x = this.freezeCache[id].x;\n nodes[id].options.fixed.y = this.freezeCache[id].y;\n }\n }\n }\n this.freezeCache = {};\n }\n\n /**\n * Find a stable position for all nodes\n */\n }, {\n key: 'stabilize',\n value: function stabilize() {\n var _this3 = this;\n\n var iterations = arguments.length <= 0 || arguments[0] === undefined ? this.options.stabilization.iterations : arguments[0];\n\n if (typeof iterations !== 'number') {\n console.log('The stabilize method needs a numeric amount of iterations. Switching to default: ', this.options.stabilization.iterations);\n iterations = this.options.stabilization.iterations;\n }\n\n if (this.physicsBody.physicsNodeIndices.length === 0) {\n this.ready = true;\n return;\n }\n\n // enable adaptive timesteps\n this.adaptiveTimestep = true && this.options.adaptiveTimestep;\n\n // this sets the width of all nodes initially which could be required for the avoidOverlap\n this.body.emitter.emit(\"_resizeNodes\");\n\n // stop the render loop\n this.stopSimulation();\n\n // set stabilze to false\n this.stabilized = false;\n\n // block redraw requests\n this.body.emitter.emit('_blockRedraw');\n this.targetIterations = iterations;\n\n // start the stabilization\n if (this.options.stabilization.onlyDynamicEdges === true) {\n this._freezeNodes();\n }\n this.stabilizationIterations = 0;\n\n setTimeout(function () {\n return _this3._stabilizationBatch();\n }, 0);\n }\n\n /**\n * One batch of stabilization\n * @private\n */\n }, {\n key: '_stabilizationBatch',\n value: function _stabilizationBatch() {\n // this is here to ensure that there is at least one start event.\n if (this.startedStabilization === false) {\n this.body.emitter.emit('startStabilizing');\n this.startedStabilization = true;\n }\n\n var count = 0;\n while (this.stabilized === false && count < this.options.stabilization.updateInterval && this.stabilizationIterations < this.targetIterations) {\n this.physicsTick();\n count++;\n }\n\n if (this.stabilized === false && this.stabilizationIterations < this.targetIterations) {\n this.body.emitter.emit('stabilizationProgress', { iterations: this.stabilizationIterations, total: this.targetIterations });\n setTimeout(this._stabilizationBatch.bind(this), 0);\n } else {\n this._finalizeStabilization();\n }\n }\n\n /**\n * Wrap up the stabilization, fit and emit the events.\n * @private\n */\n }, {\n key: '_finalizeStabilization',\n value: function _finalizeStabilization() {\n this.body.emitter.emit('_allowRedraw');\n if (this.options.stabilization.fit === true) {\n this.body.emitter.emit('fit');\n }\n\n if (this.options.stabilization.onlyDynamicEdges === true) {\n this._restoreFrozenNodes();\n }\n\n this.body.emitter.emit('stabilizationIterationsDone');\n this.body.emitter.emit('_requestRedraw');\n\n if (this.stabilized === true) {\n this._emitStabilized();\n } else {\n this.startSimulation();\n }\n\n this.ready = true;\n }\n }, {\n key: '_drawForces',\n value: function _drawForces(ctx) {\n for (var i = 0; i < this.physicsBody.physicsNodeIndices.length; i++) {\n var node = this.body.nodes[this.physicsBody.physicsNodeIndices[i]];\n var force = this.physicsBody.forces[this.physicsBody.physicsNodeIndices[i]];\n var factor = 20;\n var colorFactor = 0.03;\n var forceSize = Math.sqrt(Math.pow(force.x, 2) + Math.pow(force.x, 2));\n\n var size = Math.min(Math.max(5, forceSize), 15);\n var arrowSize = 3 * size;\n\n var color = util.HSVToHex((180 - Math.min(1, Math.max(0, colorFactor * forceSize)) * 180) / 360, 1, 1);\n\n ctx.lineWidth = size;\n ctx.strokeStyle = color;\n ctx.beginPath();\n ctx.moveTo(node.x, node.y);\n ctx.lineTo(node.x + factor * force.x, node.y + factor * force.y);\n ctx.stroke();\n\n var angle = Math.atan2(force.y, force.x);\n ctx.fillStyle = color;\n ctx.arrow(node.x + factor * force.x + Math.cos(angle) * arrowSize, node.y + factor * force.y + Math.sin(angle) * arrowSize, angle, arrowSize);\n ctx.fill();\n }\n }\n }]);\n\n return PhysicsEngine;\n })();\n\n exports['default'] = PhysicsEngine;\n module.exports = exports['default'];\n\n/***/ },\n/* 90 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var BarnesHutSolver = (function () {\n function BarnesHutSolver(body, physicsBody, options) {\n _classCallCheck(this, BarnesHutSolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.barnesHutTree;\n this.setOptions(options);\n this.randomSeed = 5;\n\n // debug: show grid\n //this.body.emitter.on(\"afterDrawing\", (ctx) => {this._debug(ctx,'#ff0000')})\n }\n\n _createClass(BarnesHutSolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n this.thetaInversed = 1 / this.options.theta;\n this.overlapAvoidanceFactor = 1 - Math.max(0, Math.min(1, this.options.avoidOverlap)); // if 1 then min distance = 0.5, if 0.5 then min distance = 0.5 + 0.5*node.shape.radius\n }\n }, {\n key: \"seededRandom\",\n value: function seededRandom() {\n var x = Math.sin(this.randomSeed++) * 10000;\n return x - Math.floor(x);\n }\n\n /**\n * This function calculates the forces the nodes apply on each other based on a gravitational model.\n * The Barnes Hut method is used to speed up this N-body simulation.\n *\n * @private\n */\n }, {\n key: \"solve\",\n value: function solve() {\n if (this.options.gravitationalConstant !== 0 && this.physicsBody.physicsNodeIndices.length > 0) {\n var node = undefined;\n var nodes = this.body.nodes;\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var nodeCount = nodeIndices.length;\n\n // create the tree\n var barnesHutTree = this._formBarnesHutTree(nodes, nodeIndices);\n\n // for debugging\n this.barnesHutTree = barnesHutTree;\n\n // place the nodes one by one recursively\n for (var i = 0; i < nodeCount; i++) {\n node = nodes[nodeIndices[i]];\n if (node.options.mass > 0) {\n // starting with root is irrelevant, it never passes the BarnesHutSolver condition\n this._getForceContribution(barnesHutTree.root.children.NW, node);\n this._getForceContribution(barnesHutTree.root.children.NE, node);\n this._getForceContribution(barnesHutTree.root.children.SW, node);\n this._getForceContribution(barnesHutTree.root.children.SE, node);\n }\n }\n }\n }\n\n /**\n * This function traverses the barnesHutTree. It checks when it can approximate distant nodes with their center of mass.\n * If a region contains a single node, we check if it is not itself, then we apply the force.\n *\n * @param parentBranch\n * @param node\n * @private\n */\n }, {\n key: \"_getForceContribution\",\n value: function _getForceContribution(parentBranch, node) {\n // we get no force contribution from an empty region\n if (parentBranch.childrenCount > 0) {\n var dx = undefined,\n dy = undefined,\n distance = undefined;\n\n // get the distance from the center of mass to the node.\n dx = parentBranch.centerOfMass.x - node.x;\n dy = parentBranch.centerOfMass.y - node.y;\n distance = Math.sqrt(dx * dx + dy * dy);\n\n // BarnesHutSolver condition\n // original condition : s/d < theta = passed === d/s > 1/theta = passed\n // calcSize = 1/s --> d * 1/s > 1/theta = passed\n if (distance * parentBranch.calcSize > this.thetaInversed) {\n this._calculateForces(distance, dx, dy, node, parentBranch);\n } else {\n // Did not pass the condition, go into children if available\n if (parentBranch.childrenCount === 4) {\n this._getForceContribution(parentBranch.children.NW, node);\n this._getForceContribution(parentBranch.children.NE, node);\n this._getForceContribution(parentBranch.children.SW, node);\n this._getForceContribution(parentBranch.children.SE, node);\n } else {\n // parentBranch must have only one node, if it was empty we wouldnt be here\n if (parentBranch.children.data.id != node.id) {\n // if it is not self\n this._calculateForces(distance, dx, dy, node, parentBranch);\n }\n }\n }\n }\n }\n\n /**\n * Calculate the forces based on the distance.\n *\n * @param distance\n * @param dx\n * @param dy\n * @param node\n * @param parentBranch\n * @private\n */\n }, {\n key: \"_calculateForces\",\n value: function _calculateForces(distance, dx, dy, node, parentBranch) {\n if (distance === 0) {\n distance = 0.1;\n dx = distance;\n }\n\n if (this.overlapAvoidanceFactor < 1) {\n distance = Math.max(0.1 + this.overlapAvoidanceFactor * node.shape.radius, distance - node.shape.radius);\n }\n\n // the dividing by the distance cubed instead of squared allows us to get the fx and fy components without sines and cosines\n // it is shorthand for gravityforce with distance squared and fx = dx/distance * gravityForce\n var gravityForce = this.options.gravitationalConstant * parentBranch.mass * node.options.mass / Math.pow(distance, 3);\n var fx = dx * gravityForce;\n var fy = dy * gravityForce;\n\n this.physicsBody.forces[node.id].x += fx;\n this.physicsBody.forces[node.id].y += fy;\n }\n\n /**\n * This function constructs the barnesHut tree recursively. It creates the root, splits it and starts placing the nodes.\n *\n * @param nodes\n * @param nodeIndices\n * @private\n */\n }, {\n key: \"_formBarnesHutTree\",\n value: function _formBarnesHutTree(nodes, nodeIndices) {\n var node = undefined;\n var nodeCount = nodeIndices.length;\n\n var minX = nodes[nodeIndices[0]].x;\n var minY = nodes[nodeIndices[0]].y;\n var maxX = nodes[nodeIndices[0]].x;\n var maxY = nodes[nodeIndices[0]].y;\n\n // get the range of the nodes\n for (var i = 1; i < nodeCount; i++) {\n var x = nodes[nodeIndices[i]].x;\n var y = nodes[nodeIndices[i]].y;\n if (nodes[nodeIndices[i]].options.mass > 0) {\n if (x < minX) {\n minX = x;\n }\n if (x > maxX) {\n maxX = x;\n }\n if (y < minY) {\n minY = y;\n }\n if (y > maxY) {\n maxY = y;\n }\n }\n }\n // make the range a square\n var sizeDiff = Math.abs(maxX - minX) - Math.abs(maxY - minY); // difference between X and Y\n if (sizeDiff > 0) {\n minY -= 0.5 * sizeDiff;\n maxY += 0.5 * sizeDiff;\n } // xSize > ySize\n else {\n minX += 0.5 * sizeDiff;\n maxX -= 0.5 * sizeDiff;\n } // xSize < ySize\n\n var minimumTreeSize = 1e-5;\n var rootSize = Math.max(minimumTreeSize, Math.abs(maxX - minX));\n var halfRootSize = 0.5 * rootSize;\n var centerX = 0.5 * (minX + maxX),\n centerY = 0.5 * (minY + maxY);\n\n // construct the barnesHutTree\n var barnesHutTree = {\n root: {\n centerOfMass: { x: 0, y: 0 },\n mass: 0,\n range: {\n minX: centerX - halfRootSize, maxX: centerX + halfRootSize,\n minY: centerY - halfRootSize, maxY: centerY + halfRootSize\n },\n size: rootSize,\n calcSize: 1 / rootSize,\n children: { data: null },\n maxWidth: 0,\n level: 0,\n childrenCount: 4\n }\n };\n this._splitBranch(barnesHutTree.root);\n\n // place the nodes one by one recursively\n for (var i = 0; i < nodeCount; i++) {\n node = nodes[nodeIndices[i]];\n if (node.options.mass > 0) {\n this._placeInTree(barnesHutTree.root, node);\n }\n }\n\n // make global\n return barnesHutTree;\n }\n\n /**\n * this updates the mass of a branch. this is increased by adding a node.\n *\n * @param parentBranch\n * @param node\n * @private\n */\n }, {\n key: \"_updateBranchMass\",\n value: function _updateBranchMass(parentBranch, node) {\n var totalMass = parentBranch.mass + node.options.mass;\n var totalMassInv = 1 / totalMass;\n\n parentBranch.centerOfMass.x = parentBranch.centerOfMass.x * parentBranch.mass + node.x * node.options.mass;\n parentBranch.centerOfMass.x *= totalMassInv;\n\n parentBranch.centerOfMass.y = parentBranch.centerOfMass.y * parentBranch.mass + node.y * node.options.mass;\n parentBranch.centerOfMass.y *= totalMassInv;\n\n parentBranch.mass = totalMass;\n var biggestSize = Math.max(Math.max(node.height, node.radius), node.width);\n parentBranch.maxWidth = parentBranch.maxWidth < biggestSize ? biggestSize : parentBranch.maxWidth;\n }\n\n /**\n * determine in which branch the node will be placed.\n *\n * @param parentBranch\n * @param node\n * @param skipMassUpdate\n * @private\n */\n }, {\n key: \"_placeInTree\",\n value: function _placeInTree(parentBranch, node, skipMassUpdate) {\n if (skipMassUpdate != true || skipMassUpdate === undefined) {\n // update the mass of the branch.\n this._updateBranchMass(parentBranch, node);\n }\n\n if (parentBranch.children.NW.range.maxX > node.x) {\n // in NW or SW\n if (parentBranch.children.NW.range.maxY > node.y) {\n // in NW\n this._placeInRegion(parentBranch, node, \"NW\");\n } else {\n // in SW\n this._placeInRegion(parentBranch, node, \"SW\");\n }\n } else {\n // in NE or SE\n if (parentBranch.children.NW.range.maxY > node.y) {\n // in NE\n this._placeInRegion(parentBranch, node, \"NE\");\n } else {\n // in SE\n this._placeInRegion(parentBranch, node, \"SE\");\n }\n }\n }\n\n /**\n * actually place the node in a region (or branch)\n *\n * @param parentBranch\n * @param node\n * @param region\n * @private\n */\n }, {\n key: \"_placeInRegion\",\n value: function _placeInRegion(parentBranch, node, region) {\n switch (parentBranch.children[region].childrenCount) {\n case 0:\n // place node here\n parentBranch.children[region].children.data = node;\n parentBranch.children[region].childrenCount = 1;\n this._updateBranchMass(parentBranch.children[region], node);\n break;\n case 1:\n // convert into children\n // if there are two nodes exactly overlapping (on init, on opening of cluster etc.)\n // we move one node a little bit and we do not put it in the tree.\n if (parentBranch.children[region].children.data.x === node.x && parentBranch.children[region].children.data.y === node.y) {\n node.x += this.seededRandom();\n node.y += this.seededRandom();\n } else {\n this._splitBranch(parentBranch.children[region]);\n this._placeInTree(parentBranch.children[region], node);\n }\n break;\n case 4:\n // place in branch\n this._placeInTree(parentBranch.children[region], node);\n break;\n }\n }\n\n /**\n * this function splits a branch into 4 sub branches. If the branch contained a node, we place it in the subbranch\n * after the split is complete.\n *\n * @param parentBranch\n * @private\n */\n }, {\n key: \"_splitBranch\",\n value: function _splitBranch(parentBranch) {\n // if the branch is shaded with a node, replace the node in the new subset.\n var containedNode = null;\n if (parentBranch.childrenCount === 1) {\n containedNode = parentBranch.children.data;\n parentBranch.mass = 0;\n parentBranch.centerOfMass.x = 0;\n parentBranch.centerOfMass.y = 0;\n }\n parentBranch.childrenCount = 4;\n parentBranch.children.data = null;\n this._insertRegion(parentBranch, \"NW\");\n this._insertRegion(parentBranch, \"NE\");\n this._insertRegion(parentBranch, \"SW\");\n this._insertRegion(parentBranch, \"SE\");\n\n if (containedNode != null) {\n this._placeInTree(parentBranch, containedNode);\n }\n }\n\n /**\n * This function subdivides the region into four new segments.\n * Specifically, this inserts a single new segment.\n * It fills the children section of the parentBranch\n *\n * @param parentBranch\n * @param region\n * @param parentRange\n * @private\n */\n }, {\n key: \"_insertRegion\",\n value: function _insertRegion(parentBranch, region) {\n var minX = undefined,\n maxX = undefined,\n minY = undefined,\n maxY = undefined;\n var childSize = 0.5 * parentBranch.size;\n switch (region) {\n case \"NW\":\n minX = parentBranch.range.minX;\n maxX = parentBranch.range.minX + childSize;\n minY = parentBranch.range.minY;\n maxY = parentBranch.range.minY + childSize;\n break;\n case \"NE\":\n minX = parentBranch.range.minX + childSize;\n maxX = parentBranch.range.maxX;\n minY = parentBranch.range.minY;\n maxY = parentBranch.range.minY + childSize;\n break;\n case \"SW\":\n minX = parentBranch.range.minX;\n maxX = parentBranch.range.minX + childSize;\n minY = parentBranch.range.minY + childSize;\n maxY = parentBranch.range.maxY;\n break;\n case \"SE\":\n minX = parentBranch.range.minX + childSize;\n maxX = parentBranch.range.maxX;\n minY = parentBranch.range.minY + childSize;\n maxY = parentBranch.range.maxY;\n break;\n }\n\n parentBranch.children[region] = {\n centerOfMass: { x: 0, y: 0 },\n mass: 0,\n range: { minX: minX, maxX: maxX, minY: minY, maxY: maxY },\n size: 0.5 * parentBranch.size,\n calcSize: 2 * parentBranch.calcSize,\n children: { data: null },\n maxWidth: 0,\n level: parentBranch.level + 1,\n childrenCount: 0\n };\n }\n\n //--------------------------- DEBUGGING BELOW ---------------------------//\n\n /**\n * This function is for debugging purposed, it draws the tree.\n *\n * @param ctx\n * @param color\n * @private\n */\n }, {\n key: \"_debug\",\n value: function _debug(ctx, color) {\n if (this.barnesHutTree !== undefined) {\n\n ctx.lineWidth = 1;\n\n this._drawBranch(this.barnesHutTree.root, ctx, color);\n }\n }\n\n /**\n * This function is for debugging purposes. It draws the branches recursively.\n *\n * @param branch\n * @param ctx\n * @param color\n * @private\n */\n }, {\n key: \"_drawBranch\",\n value: function _drawBranch(branch, ctx, color) {\n if (color === undefined) {\n color = \"#FF0000\";\n }\n\n if (branch.childrenCount === 4) {\n this._drawBranch(branch.children.NW, ctx);\n this._drawBranch(branch.children.NE, ctx);\n this._drawBranch(branch.children.SE, ctx);\n this._drawBranch(branch.children.SW, ctx);\n }\n ctx.strokeStyle = color;\n ctx.beginPath();\n ctx.moveTo(branch.range.minX, branch.range.minY);\n ctx.lineTo(branch.range.maxX, branch.range.minY);\n ctx.stroke();\n\n ctx.beginPath();\n ctx.moveTo(branch.range.maxX, branch.range.minY);\n ctx.lineTo(branch.range.maxX, branch.range.maxY);\n ctx.stroke();\n\n ctx.beginPath();\n ctx.moveTo(branch.range.maxX, branch.range.maxY);\n ctx.lineTo(branch.range.minX, branch.range.maxY);\n ctx.stroke();\n\n ctx.beginPath();\n ctx.moveTo(branch.range.minX, branch.range.maxY);\n ctx.lineTo(branch.range.minX, branch.range.minY);\n ctx.stroke();\n\n /*\n if (branch.mass > 0) {\n ctx.circle(branch.centerOfMass.x, branch.centerOfMass.y, 3*branch.mass);\n ctx.stroke();\n }\n */\n }\n }]);\n\n return BarnesHutSolver;\n })();\n\n exports[\"default\"] = BarnesHutSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 91 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var RepulsionSolver = (function () {\n function RepulsionSolver(body, physicsBody, options) {\n _classCallCheck(this, RepulsionSolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.setOptions(options);\n }\n\n _createClass(RepulsionSolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n\n /**\n * Calculate the forces the nodes apply on each other based on a repulsion field.\n * This field is linearly approximated.\n *\n * @private\n */\n }, {\n key: \"solve\",\n value: function solve() {\n var dx, dy, distance, fx, fy, repulsingForce, node1, node2;\n\n var nodes = this.body.nodes;\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var forces = this.physicsBody.forces;\n\n // repulsing forces between nodes\n var nodeDistance = this.options.nodeDistance;\n\n // approximation constants\n var a = -2 / 3 / nodeDistance;\n var b = 4 / 3;\n\n // we loop from i over all but the last entree in the array\n // j loops from i+1 to the last. This way we do not double count any of the indices, nor i === j\n for (var i = 0; i < nodeIndices.length - 1; i++) {\n node1 = nodes[nodeIndices[i]];\n for (var j = i + 1; j < nodeIndices.length; j++) {\n node2 = nodes[nodeIndices[j]];\n\n dx = node2.x - node1.x;\n dy = node2.y - node1.y;\n distance = Math.sqrt(dx * dx + dy * dy);\n\n // same condition as BarnesHutSolver, making sure nodes are never 100% overlapping.\n if (distance === 0) {\n distance = 0.1 * Math.random();\n dx = distance;\n }\n\n if (distance < 2 * nodeDistance) {\n if (distance < 0.5 * nodeDistance) {\n repulsingForce = 1.0;\n } else {\n repulsingForce = a * distance + b; // linear approx of 1 / (1 + Math.exp((distance / nodeDistance - 1) * steepness))\n }\n repulsingForce = repulsingForce / distance;\n\n fx = dx * repulsingForce;\n fy = dy * repulsingForce;\n\n forces[node1.id].x -= fx;\n forces[node1.id].y -= fy;\n forces[node2.id].x += fx;\n forces[node2.id].y += fy;\n }\n }\n }\n }\n }]);\n\n return RepulsionSolver;\n })();\n\n exports[\"default\"] = RepulsionSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 92 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var HierarchicalRepulsionSolver = (function () {\n function HierarchicalRepulsionSolver(body, physicsBody, options) {\n _classCallCheck(this, HierarchicalRepulsionSolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.setOptions(options);\n }\n\n _createClass(HierarchicalRepulsionSolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n\n /**\n * Calculate the forces the nodes apply on each other based on a repulsion field.\n * This field is linearly approximated.\n *\n * @private\n */\n }, {\n key: \"solve\",\n value: function solve() {\n var dx, dy, distance, fx, fy, repulsingForce, node1, node2, i, j;\n\n var nodes = this.body.nodes;\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var forces = this.physicsBody.forces;\n\n // repulsing forces between nodes\n var nodeDistance = this.options.nodeDistance;\n\n // we loop from i over all but the last entree in the array\n // j loops from i+1 to the last. This way we do not double count any of the indices, nor i === j\n for (i = 0; i < nodeIndices.length - 1; i++) {\n node1 = nodes[nodeIndices[i]];\n for (j = i + 1; j < nodeIndices.length; j++) {\n node2 = nodes[nodeIndices[j]];\n\n // nodes only affect nodes on their level\n if (node1.level === node2.level) {\n dx = node2.x - node1.x;\n dy = node2.y - node1.y;\n distance = Math.sqrt(dx * dx + dy * dy);\n\n var steepness = 0.05;\n if (distance < nodeDistance) {\n repulsingForce = -Math.pow(steepness * distance, 2) + Math.pow(steepness * nodeDistance, 2);\n } else {\n repulsingForce = 0;\n }\n // normalize force with\n if (distance === 0) {\n distance = 0.01;\n } else {\n repulsingForce = repulsingForce / distance;\n }\n fx = dx * repulsingForce;\n fy = dy * repulsingForce;\n\n forces[node1.id].x -= fx;\n forces[node1.id].y -= fy;\n forces[node2.id].x += fx;\n forces[node2.id].y += fy;\n }\n }\n }\n }\n }]);\n\n return HierarchicalRepulsionSolver;\n })();\n\n exports[\"default\"] = HierarchicalRepulsionSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 93 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var SpringSolver = (function () {\n function SpringSolver(body, physicsBody, options) {\n _classCallCheck(this, SpringSolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.setOptions(options);\n }\n\n _createClass(SpringSolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n\n /**\n * This function calculates the springforces on the nodes, accounting for the support nodes.\n *\n * @private\n */\n }, {\n key: \"solve\",\n value: function solve() {\n var edgeLength = undefined,\n edge = undefined;\n var edgeIndices = this.physicsBody.physicsEdgeIndices;\n var edges = this.body.edges;\n var node1 = undefined,\n node2 = undefined,\n node3 = undefined;\n\n // forces caused by the edges, modelled as springs\n for (var i = 0; i < edgeIndices.length; i++) {\n edge = edges[edgeIndices[i]];\n if (edge.connected === true && edge.toId !== edge.fromId) {\n // only calculate forces if nodes are in the same sector\n if (this.body.nodes[edge.toId] !== undefined && this.body.nodes[edge.fromId] !== undefined) {\n if (edge.edgeType.via !== undefined) {\n edgeLength = edge.options.length === undefined ? this.options.springLength : edge.options.length;\n node1 = edge.to;\n node2 = edge.edgeType.via;\n node3 = edge.from;\n\n this._calculateSpringForce(node1, node2, 0.5 * edgeLength);\n this._calculateSpringForce(node2, node3, 0.5 * edgeLength);\n } else {\n // the * 1.5 is here so the edge looks as large as a smooth edge. It does not initially because the smooth edges use\n // the support nodes which exert a repulsive force on the to and from nodes, making the edge appear larger.\n edgeLength = edge.options.length === undefined ? this.options.springLength * 1.5 : edge.options.length;\n this._calculateSpringForce(edge.from, edge.to, edgeLength);\n }\n }\n }\n }\n }\n\n /**\n * This is the code actually performing the calculation for the function above.\n *\n * @param node1\n * @param node2\n * @param edgeLength\n * @private\n */\n }, {\n key: \"_calculateSpringForce\",\n value: function _calculateSpringForce(node1, node2, edgeLength) {\n var dx = node1.x - node2.x;\n var dy = node1.y - node2.y;\n var distance = Math.max(Math.sqrt(dx * dx + dy * dy), 0.01);\n\n // the 1/distance is so the fx and fy can be calculated without sine or cosine.\n var springForce = this.options.springConstant * (edgeLength - distance) / distance;\n\n var fx = dx * springForce;\n var fy = dy * springForce;\n\n // handle the case where one node is not part of the physcis\n if (this.physicsBody.forces[node1.id] !== undefined) {\n this.physicsBody.forces[node1.id].x += fx;\n this.physicsBody.forces[node1.id].y += fy;\n }\n\n if (this.physicsBody.forces[node2.id] !== undefined) {\n this.physicsBody.forces[node2.id].x -= fx;\n this.physicsBody.forces[node2.id].y -= fy;\n }\n }\n }]);\n\n return SpringSolver;\n })();\n\n exports[\"default\"] = SpringSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 94 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var HierarchicalSpringSolver = (function () {\n function HierarchicalSpringSolver(body, physicsBody, options) {\n _classCallCheck(this, HierarchicalSpringSolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.setOptions(options);\n }\n\n _createClass(HierarchicalSpringSolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n\n /**\n * This function calculates the springforces on the nodes, accounting for the support nodes.\n *\n * @private\n */\n }, {\n key: \"solve\",\n value: function solve() {\n var edgeLength, edge;\n var dx, dy, fx, fy, springForce, distance;\n var edges = this.body.edges;\n var factor = 0.5;\n\n var edgeIndices = this.physicsBody.physicsEdgeIndices;\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var forces = this.physicsBody.forces;\n\n // initialize the spring force counters\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n forces[nodeId].springFx = 0;\n forces[nodeId].springFy = 0;\n }\n\n // forces caused by the edges, modelled as springs\n for (var i = 0; i < edgeIndices.length; i++) {\n edge = edges[edgeIndices[i]];\n if (edge.connected === true) {\n edgeLength = edge.options.length === undefined ? this.options.springLength : edge.options.length;\n\n dx = edge.from.x - edge.to.x;\n dy = edge.from.y - edge.to.y;\n distance = Math.sqrt(dx * dx + dy * dy);\n distance = distance === 0 ? 0.01 : distance;\n\n // the 1/distance is so the fx and fy can be calculated without sine or cosine.\n springForce = this.options.springConstant * (edgeLength - distance) / distance;\n\n fx = dx * springForce;\n fy = dy * springForce;\n\n if (edge.to.level != edge.from.level) {\n if (forces[edge.toId] !== undefined) {\n forces[edge.toId].springFx -= fx;\n forces[edge.toId].springFy -= fy;\n }\n if (forces[edge.fromId] !== undefined) {\n forces[edge.fromId].springFx += fx;\n forces[edge.fromId].springFy += fy;\n }\n } else {\n if (forces[edge.toId] !== undefined) {\n forces[edge.toId].x -= factor * fx;\n forces[edge.toId].y -= factor * fy;\n }\n if (forces[edge.fromId] !== undefined) {\n forces[edge.fromId].x += factor * fx;\n forces[edge.fromId].y += factor * fy;\n }\n }\n }\n }\n\n // normalize spring forces\n var springForce = 1;\n var springFx, springFy;\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n springFx = Math.min(springForce, Math.max(-springForce, forces[nodeId].springFx));\n springFy = Math.min(springForce, Math.max(-springForce, forces[nodeId].springFy));\n\n forces[nodeId].x += springFx;\n forces[nodeId].y += springFy;\n }\n\n // retain energy balance\n var totalFx = 0;\n var totalFy = 0;\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n totalFx += forces[nodeId].x;\n totalFy += forces[nodeId].y;\n }\n var correctionFx = totalFx / nodeIndices.length;\n var correctionFy = totalFy / nodeIndices.length;\n\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n forces[nodeId].x -= correctionFx;\n forces[nodeId].y -= correctionFy;\n }\n }\n }]);\n\n return HierarchicalSpringSolver;\n })();\n\n exports[\"default\"] = HierarchicalSpringSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 95 */\n/***/ function(module, exports) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var CentralGravitySolver = (function () {\n function CentralGravitySolver(body, physicsBody, options) {\n _classCallCheck(this, CentralGravitySolver);\n\n this.body = body;\n this.physicsBody = physicsBody;\n this.setOptions(options);\n }\n\n _createClass(CentralGravitySolver, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n this.options = options;\n }\n }, {\n key: \"solve\",\n value: function solve() {\n var dx = undefined,\n dy = undefined,\n distance = undefined,\n node = undefined;\n var nodes = this.body.nodes;\n var nodeIndices = this.physicsBody.physicsNodeIndices;\n var forces = this.physicsBody.forces;\n\n for (var i = 0; i < nodeIndices.length; i++) {\n var nodeId = nodeIndices[i];\n node = nodes[nodeId];\n dx = -node.x;\n dy = -node.y;\n distance = Math.sqrt(dx * dx + dy * dy);\n\n this._calculateForces(distance, dx, dy, forces, node);\n }\n }\n\n /**\n * Calculate the forces based on the distance.\n * @private\n */\n }, {\n key: \"_calculateForces\",\n value: function _calculateForces(distance, dx, dy, forces, node) {\n var gravityForce = distance === 0 ? 0 : this.options.centralGravity / distance;\n forces[node.id].x = dx * gravityForce;\n forces[node.id].y = dy * gravityForce;\n }\n }]);\n\n return CentralGravitySolver;\n })();\n\n exports[\"default\"] = CentralGravitySolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 96 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if (\"value\" in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { \"default\": obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function, not \" + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _BarnesHutSolver2 = __webpack_require__(90);\n\n var _BarnesHutSolver3 = _interopRequireDefault(_BarnesHutSolver2);\n\n var ForceAtlas2BasedRepulsionSolver = (function (_BarnesHutSolver) {\n _inherits(ForceAtlas2BasedRepulsionSolver, _BarnesHutSolver);\n\n function ForceAtlas2BasedRepulsionSolver(body, physicsBody, options) {\n _classCallCheck(this, ForceAtlas2BasedRepulsionSolver);\n\n _get(Object.getPrototypeOf(ForceAtlas2BasedRepulsionSolver.prototype), \"constructor\", this).call(this, body, physicsBody, options);\n }\n\n /**\n * Calculate the forces based on the distance.\n *\n * @param distance\n * @param dx\n * @param dy\n * @param node\n * @param parentBranch\n * @private\n */\n\n _createClass(ForceAtlas2BasedRepulsionSolver, [{\n key: \"_calculateForces\",\n value: function _calculateForces(distance, dx, dy, node, parentBranch) {\n if (distance === 0) {\n distance = 0.1 * Math.random();\n dx = distance;\n }\n\n if (this.overlapAvoidanceFactor < 1) {\n distance = Math.max(0.1 + this.overlapAvoidanceFactor * node.shape.radius, distance - node.shape.radius);\n }\n\n var degree = node.edges.length + 1;\n // the dividing by the distance cubed instead of squared allows us to get the fx and fy components without sines and cosines\n // it is shorthand for gravityforce with distance squared and fx = dx/distance * gravityForce\n var gravityForce = this.options.gravitationalConstant * parentBranch.mass * node.options.mass * degree / Math.pow(distance, 2);\n var fx = dx * gravityForce;\n var fy = dy * gravityForce;\n\n this.physicsBody.forces[node.id].x += fx;\n this.physicsBody.forces[node.id].y += fy;\n }\n }]);\n\n return ForceAtlas2BasedRepulsionSolver;\n })(_BarnesHutSolver3[\"default\"]);\n\n exports[\"default\"] = ForceAtlas2BasedRepulsionSolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 97 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if (\"value\" in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { \"default\": obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function, not \" + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _CentralGravitySolver2 = __webpack_require__(95);\n\n var _CentralGravitySolver3 = _interopRequireDefault(_CentralGravitySolver2);\n\n var ForceAtlas2BasedCentralGravitySolver = (function (_CentralGravitySolver) {\n _inherits(ForceAtlas2BasedCentralGravitySolver, _CentralGravitySolver);\n\n function ForceAtlas2BasedCentralGravitySolver(body, physicsBody, options) {\n _classCallCheck(this, ForceAtlas2BasedCentralGravitySolver);\n\n _get(Object.getPrototypeOf(ForceAtlas2BasedCentralGravitySolver.prototype), \"constructor\", this).call(this, body, physicsBody, options);\n }\n\n /**\n * Calculate the forces based on the distance.\n * @private\n */\n\n _createClass(ForceAtlas2BasedCentralGravitySolver, [{\n key: \"_calculateForces\",\n value: function _calculateForces(distance, dx, dy, forces, node) {\n if (distance > 0) {\n var degree = node.edges.length + 1;\n var gravityForce = this.options.centralGravity * degree * node.options.mass;\n forces[node.id].x = dx * gravityForce;\n forces[node.id].y = dy * gravityForce;\n }\n }\n }]);\n\n return ForceAtlas2BasedCentralGravitySolver;\n })(_CentralGravitySolver3[\"default\"]);\n\n exports[\"default\"] = ForceAtlas2BasedCentralGravitySolver;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 98 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _NetworkUtil = __webpack_require__(99);\n\n var _NetworkUtil2 = _interopRequireDefault(_NetworkUtil);\n\n var _componentsNodesCluster = __webpack_require__(100);\n\n var _componentsNodesCluster2 = _interopRequireDefault(_componentsNodesCluster);\n\n var util = __webpack_require__(1);\n\n var ClusterEngine = (function () {\n function ClusterEngine(body) {\n var _this = this;\n\n _classCallCheck(this, ClusterEngine);\n\n this.body = body;\n this.clusteredNodes = {};\n this.clusteredEdges = {};\n\n this.options = {};\n this.defaultOptions = {};\n util.extend(this.options, this.defaultOptions);\n\n this.body.emitter.on('_resetData', function () {\n _this.clusteredNodes = {};_this.clusteredEdges = {};\n });\n }\n\n _createClass(ClusterEngine, [{\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {}\n }\n\n /**\n *\n * @param hubsize\n * @param options\n */\n }, {\n key: 'clusterByHubsize',\n value: function clusterByHubsize(hubsize, options) {\n if (hubsize === undefined) {\n hubsize = this._getHubSize();\n } else if (typeof hubsize === \"object\") {\n options = this._checkOptions(hubsize);\n hubsize = this._getHubSize();\n }\n\n var nodesToCluster = [];\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var node = this.body.nodes[this.body.nodeIndices[i]];\n if (node.edges.length >= hubsize) {\n nodesToCluster.push(node.id);\n }\n }\n\n for (var i = 0; i < nodesToCluster.length; i++) {\n this.clusterByConnection(nodesToCluster[i], options, true);\n }\n\n this.body.emitter.emit('_dataChanged');\n }\n\n /**\n * loop over all nodes, check if they adhere to the condition and cluster if needed.\n * @param options\n * @param refreshData\n */\n }, {\n key: 'cluster',\n value: function cluster() {\n var options = arguments.length <= 0 || arguments[0] === undefined ? {} : arguments[0];\n var refreshData = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n if (options.joinCondition === undefined) {\n throw new Error(\"Cannot call clusterByNodeData without a joinCondition function in the options.\");\n }\n\n // check if the options object is fine, append if needed\n options = this._checkOptions(options);\n\n var childNodesObj = {};\n var childEdgesObj = {};\n\n // collect the nodes that will be in the cluster\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var nodeId = this.body.nodeIndices[i];\n var node = this.body.nodes[nodeId];\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(node);\n if (options.joinCondition(clonedOptions) === true) {\n childNodesObj[nodeId] = this.body.nodes[nodeId];\n\n // collect the nodes that will be in the cluster\n for (var _i = 0; _i < node.edges.length; _i++) {\n var edge = node.edges[_i];\n if (this.clusteredEdges[edge.id] === undefined) {\n childEdgesObj[edge.id] = edge;\n }\n }\n }\n }\n\n this._cluster(childNodesObj, childEdgesObj, options, refreshData);\n }\n\n /**\n * Cluster all nodes in the network that have only X edges\n * @param edgeCount\n * @param options\n * @param refreshData\n */\n }, {\n key: 'clusterByEdgeCount',\n value: function clusterByEdgeCount(edgeCount, options) {\n var refreshData = arguments.length <= 2 || arguments[2] === undefined ? true : arguments[2];\n\n options = this._checkOptions(options);\n var clusters = [];\n var usedNodes = {};\n var edge = undefined,\n edges = undefined,\n node = undefined,\n nodeId = undefined,\n relevantEdgeCount = undefined;\n // collect the nodes that will be in the cluster\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var childNodesObj = {};\n var childEdgesObj = {};\n nodeId = this.body.nodeIndices[i];\n\n // if this node is already used in another cluster this session, we do not have to re-evaluate it.\n if (usedNodes[nodeId] === undefined) {\n relevantEdgeCount = 0;\n node = this.body.nodes[nodeId];\n edges = [];\n for (var j = 0; j < node.edges.length; j++) {\n edge = node.edges[j];\n if (this.clusteredEdges[edge.id] === undefined) {\n if (edge.toId !== edge.fromId) {\n relevantEdgeCount++;\n }\n edges.push(edge);\n }\n }\n\n // this node qualifies, we collect its neighbours to start the clustering process.\n if (relevantEdgeCount === edgeCount) {\n var gatheringSuccessful = true;\n for (var j = 0; j < edges.length; j++) {\n edge = edges[j];\n var childNodeId = this._getConnectedId(edge, nodeId);\n // add the nodes to the list by the join condition.\n if (options.joinCondition === undefined) {\n childEdgesObj[edge.id] = edge;\n childNodesObj[nodeId] = this.body.nodes[nodeId];\n childNodesObj[childNodeId] = this.body.nodes[childNodeId];\n usedNodes[nodeId] = true;\n } else {\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(this.body.nodes[nodeId]);\n if (options.joinCondition(clonedOptions) === true) {\n childEdgesObj[edge.id] = edge;\n childNodesObj[nodeId] = this.body.nodes[nodeId];\n usedNodes[nodeId] = true;\n } else {\n // this node does not qualify after all.\n gatheringSuccessful = false;\n break;\n }\n }\n }\n\n // add to the cluster queue\n if (Object.keys(childNodesObj).length > 0 && Object.keys(childEdgesObj).length > 0 && gatheringSuccessful === true) {\n clusters.push({ nodes: childNodesObj, edges: childEdgesObj });\n }\n }\n }\n }\n\n for (var i = 0; i < clusters.length; i++) {\n this._cluster(clusters[i].nodes, clusters[i].edges, options, false);\n }\n\n if (refreshData === true) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n\n /**\n * Cluster all nodes in the network that have only 1 edge\n * @param options\n * @param refreshData\n */\n }, {\n key: 'clusterOutliers',\n value: function clusterOutliers(options) {\n var refreshData = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n this.clusterByEdgeCount(1, options, refreshData);\n }\n\n /**\n * Cluster all nodes in the network that have only 2 edge\n * @param options\n * @param refreshData\n */\n }, {\n key: 'clusterBridges',\n value: function clusterBridges(options) {\n var refreshData = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n this.clusterByEdgeCount(2, options, refreshData);\n }\n\n /**\n * suck all connected nodes of a node into the node.\n * @param nodeId\n * @param options\n * @param refreshData\n */\n }, {\n key: 'clusterByConnection',\n value: function clusterByConnection(nodeId, options) {\n var refreshData = arguments.length <= 2 || arguments[2] === undefined ? true : arguments[2];\n\n // kill conditions\n if (nodeId === undefined) {\n throw new Error(\"No nodeId supplied to clusterByConnection!\");\n }\n if (this.body.nodes[nodeId] === undefined) {\n throw new Error(\"The nodeId given to clusterByConnection does not exist!\");\n }\n\n var node = this.body.nodes[nodeId];\n options = this._checkOptions(options, node);\n if (options.clusterNodeProperties.x === undefined) {\n options.clusterNodeProperties.x = node.x;\n }\n if (options.clusterNodeProperties.y === undefined) {\n options.clusterNodeProperties.y = node.y;\n }\n if (options.clusterNodeProperties.fixed === undefined) {\n options.clusterNodeProperties.fixed = {};\n options.clusterNodeProperties.fixed.x = node.options.fixed.x;\n options.clusterNodeProperties.fixed.y = node.options.fixed.y;\n }\n\n var childNodesObj = {};\n var childEdgesObj = {};\n var parentNodeId = node.id;\n var parentClonedOptions = _NetworkUtil2['default'].cloneOptions(node);\n childNodesObj[parentNodeId] = node;\n\n // collect the nodes that will be in the cluster\n for (var i = 0; i < node.edges.length; i++) {\n var edge = node.edges[i];\n if (this.clusteredEdges[edge.id] === undefined) {\n var childNodeId = this._getConnectedId(edge, parentNodeId);\n\n // if the child node is not in a cluster\n if (this.clusteredNodes[childNodeId] === undefined) {\n if (childNodeId !== parentNodeId) {\n if (options.joinCondition === undefined) {\n childEdgesObj[edge.id] = edge;\n childNodesObj[childNodeId] = this.body.nodes[childNodeId];\n } else {\n // clone the options and insert some additional parameters that could be interesting.\n var childClonedOptions = _NetworkUtil2['default'].cloneOptions(this.body.nodes[childNodeId]);\n if (options.joinCondition(parentClonedOptions, childClonedOptions) === true) {\n childEdgesObj[edge.id] = edge;\n childNodesObj[childNodeId] = this.body.nodes[childNodeId];\n }\n }\n } else {\n // swallow the edge if it is self-referencing.\n childEdgesObj[edge.id] = edge;\n }\n }\n }\n }\n\n this._cluster(childNodesObj, childEdgesObj, options, refreshData);\n }\n\n /**\n * This function creates the edges that will be attached to the cluster\n * It looks for edges that are connected to the nodes from the \"outside' of the cluster.\n *\n * @param childNodesObj\n * @param childEdgesObj\n * @param clusterNodeProperties\n * @param clusterEdgeProperties\n * @private\n */\n }, {\n key: '_createClusterEdges',\n value: function _createClusterEdges(childNodesObj, childEdgesObj, clusterNodeProperties, clusterEdgeProperties) {\n var edge = undefined,\n childNodeId = undefined,\n childNode = undefined,\n toId = undefined,\n fromId = undefined,\n otherNodeId = undefined;\n\n // loop over all child nodes and their edges to find edges going out of the cluster\n // these edges will be replaced by clusterEdges.\n var childKeys = Object.keys(childNodesObj);\n var createEdges = [];\n for (var i = 0; i < childKeys.length; i++) {\n childNodeId = childKeys[i];\n childNode = childNodesObj[childNodeId];\n\n // construct new edges from the cluster to others\n for (var j = 0; j < childNode.edges.length; j++) {\n edge = childNode.edges[j];\n // we only handle edges that are visible to the system, not the disabled ones from the clustering process.\n if (this.clusteredEdges[edge.id] === undefined) {\n // self-referencing edges will be added to the \"hidden\" list\n if (edge.toId == edge.fromId) {\n childEdgesObj[edge.id] = edge;\n } else {\n // set up the from and to.\n if (edge.toId == childNodeId) {\n // this is a double equals because ints and strings can be interchanged here.\n toId = clusterNodeProperties.id;\n fromId = edge.fromId;\n otherNodeId = fromId;\n } else {\n toId = edge.toId;\n fromId = clusterNodeProperties.id;\n otherNodeId = toId;\n }\n }\n\n // Only edges from the cluster outwards are being replaced.\n if (childNodesObj[otherNodeId] === undefined) {\n createEdges.push({ edge: edge, fromId: fromId, toId: toId });\n }\n }\n }\n }\n\n // here we actually create the replacement edges. We could not do this in the loop above as the creation process\n // would add an edge to the edges array we are iterating over.\n for (var j = 0; j < createEdges.length; j++) {\n var _edge = createEdges[j].edge;\n // copy the options of the edge we will replace\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(_edge, 'edge');\n // make sure the properties of clusterEdges are superimposed on it\n util.deepExtend(clonedOptions, clusterEdgeProperties);\n\n // set up the edge\n clonedOptions.from = createEdges[j].fromId;\n clonedOptions.to = createEdges[j].toId;\n clonedOptions.id = 'clusterEdge:' + util.randomUUID();\n //clonedOptions.id = '(cf: ' + createEdges[j].fromId + \" to: \" + createEdges[j].toId + \")\" + Math.random();\n\n // create the edge and give a reference to the one it replaced.\n var newEdge = this.body.functions.createEdge(clonedOptions);\n newEdge.clusteringEdgeReplacingId = _edge.id;\n\n // connect the edge.\n this.body.edges[newEdge.id] = newEdge;\n newEdge.connect();\n\n // hide the replaced edge\n this._backupEdgeOptions(_edge);\n _edge.setOptions({ physics: false, hidden: true });\n }\n }\n\n /**\n * This function checks the options that can be supplied to the different cluster functions\n * for certain fields and inserts defaults if needed\n * @param options\n * @returns {*}\n * @private\n */\n }, {\n key: '_checkOptions',\n value: function _checkOptions() {\n var options = arguments.length <= 0 || arguments[0] === undefined ? {} : arguments[0];\n\n if (options.clusterEdgeProperties === undefined) {\n options.clusterEdgeProperties = {};\n }\n if (options.clusterNodeProperties === undefined) {\n options.clusterNodeProperties = {};\n }\n\n return options;\n }\n\n /**\n *\n * @param {Object} childNodesObj | object with node objects, id as keys, same as childNodes except it also contains a source node\n * @param {Object} childEdgesObj | object with edge objects, id as keys\n * @param {Array} options | object with {clusterNodeProperties, clusterEdgeProperties, processProperties}\n * @param {Boolean} refreshData | when true, do not wrap up\n * @private\n */\n }, {\n key: '_cluster',\n value: function _cluster(childNodesObj, childEdgesObj, options) {\n var refreshData = arguments.length <= 3 || arguments[3] === undefined ? true : arguments[3];\n\n // kill condition: no children so can't cluster or only one node in the cluster, don't bother\n if (Object.keys(childNodesObj).length < 2) {\n return;\n }\n\n // check if this cluster call is not trying to cluster anything that is in another cluster.\n for (var nodeId in childNodesObj) {\n if (childNodesObj.hasOwnProperty(nodeId)) {\n if (this.clusteredNodes[nodeId] !== undefined) {\n return;\n }\n }\n }\n\n var clusterNodeProperties = util.deepExtend({}, options.clusterNodeProperties);\n\n // construct the clusterNodeProperties\n if (options.processProperties !== undefined) {\n // get the childNode options\n var childNodesOptions = [];\n for (var nodeId in childNodesObj) {\n if (childNodesObj.hasOwnProperty(nodeId)) {\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(childNodesObj[nodeId]);\n childNodesOptions.push(clonedOptions);\n }\n }\n\n // get cluster properties based on childNodes\n var childEdgesOptions = [];\n for (var edgeId in childEdgesObj) {\n if (childEdgesObj.hasOwnProperty(edgeId)) {\n // these cluster edges will be removed on creation of the cluster.\n if (edgeId.substr(0, 12) !== \"clusterEdge:\") {\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(childEdgesObj[edgeId], 'edge');\n childEdgesOptions.push(clonedOptions);\n }\n }\n }\n\n clusterNodeProperties = options.processProperties(clusterNodeProperties, childNodesOptions, childEdgesOptions);\n if (!clusterNodeProperties) {\n throw new Error(\"The processProperties function does not return properties!\");\n }\n }\n\n // check if we have an unique id;\n if (clusterNodeProperties.id === undefined) {\n clusterNodeProperties.id = 'cluster:' + util.randomUUID();\n }\n var clusterId = clusterNodeProperties.id;\n\n if (clusterNodeProperties.label === undefined) {\n clusterNodeProperties.label = 'cluster';\n }\n\n // give the clusterNode a position if it does not have one.\n var pos = undefined;\n if (clusterNodeProperties.x === undefined) {\n pos = this._getClusterPosition(childNodesObj);\n clusterNodeProperties.x = pos.x;\n }\n if (clusterNodeProperties.y === undefined) {\n if (pos === undefined) {\n pos = this._getClusterPosition(childNodesObj);\n }\n clusterNodeProperties.y = pos.y;\n }\n\n // force the ID to remain the same\n clusterNodeProperties.id = clusterId;\n\n // create the clusterNode\n var clusterNode = this.body.functions.createNode(clusterNodeProperties, _componentsNodesCluster2['default']);\n clusterNode.isCluster = true;\n clusterNode.containedNodes = childNodesObj;\n clusterNode.containedEdges = childEdgesObj;\n // cache a copy from the cluster edge properties if we have to reconnect others later on\n clusterNode.clusterEdgeProperties = options.clusterEdgeProperties;\n\n // finally put the cluster node into global\n this.body.nodes[clusterNodeProperties.id] = clusterNode;\n\n // create the new edges that will connect to the cluster, all self-referencing edges will be added to childEdgesObject here.\n this._createClusterEdges(childNodesObj, childEdgesObj, clusterNodeProperties, options.clusterEdgeProperties);\n\n // disable the childEdges\n for (var edgeId in childEdgesObj) {\n if (childEdgesObj.hasOwnProperty(edgeId)) {\n if (this.body.edges[edgeId] !== undefined) {\n var edge = this.body.edges[edgeId];\n // cache the options before changing\n this._backupEdgeOptions(edge);\n // disable physics and hide the edge\n edge.setOptions({ physics: false, hidden: true });\n }\n }\n }\n\n // disable the childNodes\n for (var nodeId in childNodesObj) {\n if (childNodesObj.hasOwnProperty(nodeId)) {\n this.clusteredNodes[nodeId] = { clusterId: clusterNodeProperties.id, node: this.body.nodes[nodeId] };\n this.body.nodes[nodeId].setOptions({ hidden: true, physics: false });\n }\n }\n\n // set ID to undefined so no duplicates arise\n clusterNodeProperties.id = undefined;\n\n // wrap up\n if (refreshData === true) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n }, {\n key: '_backupEdgeOptions',\n value: function _backupEdgeOptions(edge) {\n if (this.clusteredEdges[edge.id] === undefined) {\n this.clusteredEdges[edge.id] = { physics: edge.options.physics, hidden: edge.options.hidden };\n }\n }\n }, {\n key: '_restoreEdge',\n value: function _restoreEdge(edge) {\n var originalOptions = this.clusteredEdges[edge.id];\n if (originalOptions !== undefined) {\n edge.setOptions({ physics: originalOptions.physics, hidden: originalOptions.hidden });\n delete this.clusteredEdges[edge.id];\n }\n }\n\n /**\n * Check if a node is a cluster.\n * @param nodeId\n * @returns {*}\n */\n }, {\n key: 'isCluster',\n value: function isCluster(nodeId) {\n if (this.body.nodes[nodeId] !== undefined) {\n return this.body.nodes[nodeId].isCluster === true;\n } else {\n console.log(\"Node does not exist.\");\n return false;\n }\n }\n\n /**\n * get the position of the cluster node based on what's inside\n * @param {object} childNodesObj | object with node objects, id as keys\n * @returns {{x: number, y: number}}\n * @private\n */\n }, {\n key: '_getClusterPosition',\n value: function _getClusterPosition(childNodesObj) {\n var childKeys = Object.keys(childNodesObj);\n var minX = childNodesObj[childKeys[0]].x;\n var maxX = childNodesObj[childKeys[0]].x;\n var minY = childNodesObj[childKeys[0]].y;\n var maxY = childNodesObj[childKeys[0]].y;\n var node = undefined;\n for (var i = 1; i < childKeys.length; i++) {\n node = childNodesObj[childKeys[i]];\n minX = node.x < minX ? node.x : minX;\n maxX = node.x > maxX ? node.x : maxX;\n minY = node.y < minY ? node.y : minY;\n maxY = node.y > maxY ? node.y : maxY;\n }\n\n return { x: 0.5 * (minX + maxX), y: 0.5 * (minY + maxY) };\n }\n\n /**\n * Open a cluster by calling this function.\n * @param {String} clusterNodeId | the ID of the cluster node\n * @param {Boolean} refreshData | wrap up afterwards if not true\n */\n }, {\n key: 'openCluster',\n value: function openCluster(clusterNodeId, options) {\n var refreshData = arguments.length <= 2 || arguments[2] === undefined ? true : arguments[2];\n\n // kill conditions\n if (clusterNodeId === undefined) {\n throw new Error(\"No clusterNodeId supplied to openCluster.\");\n }\n if (this.body.nodes[clusterNodeId] === undefined) {\n throw new Error(\"The clusterNodeId supplied to openCluster does not exist.\");\n }\n if (this.body.nodes[clusterNodeId].containedNodes === undefined) {\n console.log(\"The node:\" + clusterNodeId + \" is not a cluster.\");\n return;\n }\n var clusterNode = this.body.nodes[clusterNodeId];\n var containedNodes = clusterNode.containedNodes;\n var containedEdges = clusterNode.containedEdges;\n\n // allow the user to position the nodes after release.\n if (options !== undefined && options.releaseFunction !== undefined && typeof options.releaseFunction === 'function') {\n var positions = {};\n var clusterPosition = { x: clusterNode.x, y: clusterNode.y };\n for (var nodeId in containedNodes) {\n if (containedNodes.hasOwnProperty(nodeId)) {\n var containedNode = this.body.nodes[nodeId];\n positions[nodeId] = { x: containedNode.x, y: containedNode.y };\n }\n }\n var newPositions = options.releaseFunction(clusterPosition, positions);\n\n for (var nodeId in containedNodes) {\n if (containedNodes.hasOwnProperty(nodeId)) {\n var containedNode = this.body.nodes[nodeId];\n if (newPositions[nodeId] !== undefined) {\n containedNode.x = newPositions[nodeId].x === undefined ? clusterNode.x : newPositions[nodeId].x;\n containedNode.y = newPositions[nodeId].y === undefined ? clusterNode.y : newPositions[nodeId].y;\n }\n }\n }\n } else {\n // copy the position from the cluster\n for (var nodeId in containedNodes) {\n if (containedNodes.hasOwnProperty(nodeId)) {\n var containedNode = this.body.nodes[nodeId];\n containedNode = containedNodes[nodeId];\n // inherit position\n if (containedNode.options.fixed.x === false) {\n containedNode.x = clusterNode.x;\n }\n if (containedNode.options.fixed.y === false) {\n containedNode.y = clusterNode.y;\n }\n }\n }\n }\n\n // release nodes\n for (var nodeId in containedNodes) {\n if (containedNodes.hasOwnProperty(nodeId)) {\n var containedNode = this.body.nodes[nodeId];\n\n // inherit speed\n containedNode.vx = clusterNode.vx;\n containedNode.vy = clusterNode.vy;\n\n // we use these methods to avoid re-instantiating the shape, which happens with setOptions.\n containedNode.setOptions({ hidden: false, physics: true });\n\n delete this.clusteredNodes[nodeId];\n }\n }\n\n // copy the clusterNode edges because we cannot iterate over an object that we add or remove from.\n var edgesToBeDeleted = [];\n for (var i = 0; i < clusterNode.edges.length; i++) {\n edgesToBeDeleted.push(clusterNode.edges[i]);\n }\n\n // actually handling the deleting.\n for (var i = 0; i < edgesToBeDeleted.length; i++) {\n var edge = edgesToBeDeleted[i];\n\n var otherNodeId = this._getConnectedId(edge, clusterNodeId);\n // if the other node is in another cluster, we transfer ownership of this edge to the other cluster\n if (this.clusteredNodes[otherNodeId] !== undefined) {\n // transfer ownership:\n var otherCluster = this.body.nodes[this.clusteredNodes[otherNodeId].clusterId];\n var transferEdge = this.body.edges[edge.clusteringEdgeReplacingId];\n if (transferEdge !== undefined) {\n otherCluster.containedEdges[transferEdge.id] = transferEdge;\n\n // delete local reference\n delete containedEdges[transferEdge.id];\n\n // create new cluster edge from the otherCluster:\n // get to and from\n var fromId = transferEdge.fromId;\n var toId = transferEdge.toId;\n if (transferEdge.toId == otherNodeId) {\n toId = this.clusteredNodes[otherNodeId].clusterId;\n } else {\n fromId = this.clusteredNodes[otherNodeId].clusterId;\n }\n\n // clone the options and apply the cluster options to them\n var clonedOptions = _NetworkUtil2['default'].cloneOptions(transferEdge, 'edge');\n util.deepExtend(clonedOptions, otherCluster.clusterEdgeProperties);\n\n // apply the edge specific options to it.\n var id = 'clusterEdge:' + util.randomUUID();\n util.deepExtend(clonedOptions, { from: fromId, to: toId, hidden: false, physics: true, id: id });\n\n // create it\n var newEdge = this.body.functions.createEdge(clonedOptions);\n newEdge.clusteringEdgeReplacingId = transferEdge.id;\n this.body.edges[id] = newEdge;\n this.body.edges[id].connect();\n }\n } else {\n var replacedEdge = this.body.edges[edge.clusteringEdgeReplacingId];\n if (replacedEdge !== undefined) {\n this._restoreEdge(replacedEdge);\n }\n }\n edge.cleanup();\n // this removes the edge from node.edges, which is why edgeIds is formed\n edge.disconnect();\n delete this.body.edges[edge.id];\n }\n\n // handle the releasing of the edges\n for (var edgeId in containedEdges) {\n if (containedEdges.hasOwnProperty(edgeId)) {\n this._restoreEdge(containedEdges[edgeId]);\n }\n }\n\n // remove clusterNode\n delete this.body.nodes[clusterNodeId];\n\n if (refreshData === true) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n }, {\n key: 'getNodesInCluster',\n value: function getNodesInCluster(clusterId) {\n var nodesArray = [];\n if (this.isCluster(clusterId) === true) {\n var containedNodes = this.body.nodes[clusterId].containedNodes;\n for (var nodeId in containedNodes) {\n if (containedNodes.hasOwnProperty(nodeId)) {\n nodesArray.push(this.body.nodes[nodeId].id);\n }\n }\n }\n\n return nodesArray;\n }\n\n /**\n * Get the stack clusterId's that a certain node resides in. cluster A -> cluster B -> cluster C -> node\n * @param nodeId\n * @returns {Array}\n */\n }, {\n key: 'findNode',\n value: function findNode(nodeId) {\n var stack = [];\n var max = 100;\n var counter = 0;\n\n while (this.clusteredNodes[nodeId] !== undefined && counter < max) {\n stack.push(this.body.nodes[nodeId].id);\n nodeId = this.clusteredNodes[nodeId].clusterId;\n counter++;\n }\n stack.push(this.body.nodes[nodeId].id);\n stack.reverse();\n\n return stack;\n }\n\n /**\n * Get the Id the node is connected to\n * @param edge\n * @param nodeId\n * @returns {*}\n * @private\n */\n }, {\n key: '_getConnectedId',\n value: function _getConnectedId(edge, nodeId) {\n if (edge.toId != nodeId) {\n return edge.toId;\n } else if (edge.fromId != nodeId) {\n return edge.fromId;\n } else {\n return edge.fromId;\n }\n }\n\n /**\n * We determine how many connections denote an important hub.\n * We take the mean + 2*std as the important hub size. (Assuming a normal distribution of data, ~2.2%)\n *\n * @private\n */\n }, {\n key: '_getHubSize',\n value: function _getHubSize() {\n var average = 0;\n var averageSquared = 0;\n var hubCounter = 0;\n var largestHub = 0;\n\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var node = this.body.nodes[this.body.nodeIndices[i]];\n if (node.edges.length > largestHub) {\n largestHub = node.edges.length;\n }\n average += node.edges.length;\n averageSquared += Math.pow(node.edges.length, 2);\n hubCounter += 1;\n }\n average = average / hubCounter;\n averageSquared = averageSquared / hubCounter;\n\n var variance = averageSquared - Math.pow(average, 2);\n var standardDeviation = Math.sqrt(variance);\n\n var hubThreshold = Math.floor(average + 2 * standardDeviation);\n\n // always have at least one to cluster\n if (hubThreshold > largestHub) {\n hubThreshold = largestHub;\n }\n\n return hubThreshold;\n }\n }]);\n\n return ClusterEngine;\n })();\n\n exports['default'] = ClusterEngine;\n module.exports = exports['default'];\n\n/***/ },\n/* 99 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var util = __webpack_require__(1);\n\n var NetworkUtil = (function () {\n function NetworkUtil() {\n _classCallCheck(this, NetworkUtil);\n }\n\n /**\n * Find the center position of the network considering the bounding boxes\n */\n\n _createClass(NetworkUtil, null, [{\n key: \"getRange\",\n value: function getRange(allNodes) {\n var specificNodes = arguments.length <= 1 || arguments[1] === undefined ? [] : arguments[1];\n\n var minY = 1e9,\n maxY = -1e9,\n minX = 1e9,\n maxX = -1e9,\n node;\n if (specificNodes.length > 0) {\n for (var i = 0; i < specificNodes.length; i++) {\n node = allNodes[specificNodes[i]];\n if (minX > node.shape.boundingBox.left) {\n minX = node.shape.boundingBox.left;\n }\n if (maxX < node.shape.boundingBox.right) {\n maxX = node.shape.boundingBox.right;\n }\n if (minY > node.shape.boundingBox.top) {\n minY = node.shape.boundingBox.top;\n } // top is negative, bottom is positive\n if (maxY < node.shape.boundingBox.bottom) {\n maxY = node.shape.boundingBox.bottom;\n } // top is negative, bottom is positive\n }\n }\n\n if (minX === 1e9 && maxX === -1e9 && minY === 1e9 && maxY === -1e9) {\n minY = 0, maxY = 0, minX = 0, maxX = 0;\n }\n return { minX: minX, maxX: maxX, minY: minY, maxY: maxY };\n }\n\n /**\n * Find the center position of the network\n */\n }, {\n key: \"getRangeCore\",\n value: function getRangeCore(allNodes) {\n var specificNodes = arguments.length <= 1 || arguments[1] === undefined ? [] : arguments[1];\n\n var minY = 1e9,\n maxY = -1e9,\n minX = 1e9,\n maxX = -1e9,\n node;\n if (specificNodes.length > 0) {\n for (var i = 0; i < specificNodes.length; i++) {\n node = allNodes[specificNodes[i]];\n if (minX > node.x) {\n minX = node.x;\n }\n if (maxX < node.x) {\n maxX = node.x;\n }\n if (minY > node.y) {\n minY = node.y;\n } // top is negative, bottom is positive\n if (maxY < node.y) {\n maxY = node.y;\n } // top is negative, bottom is positive\n }\n }\n\n if (minX === 1e9 && maxX === -1e9 && minY === 1e9 && maxY === -1e9) {\n minY = 0, maxY = 0, minX = 0, maxX = 0;\n }\n return { minX: minX, maxX: maxX, minY: minY, maxY: maxY };\n }\n\n /**\n * @param {object} range = {minX: minX, maxX: maxX, minY: minY, maxY: maxY};\n * @returns {{x: number, y: number}}\n */\n }, {\n key: \"findCenter\",\n value: function findCenter(range) {\n return { x: 0.5 * (range.maxX + range.minX),\n y: 0.5 * (range.maxY + range.minY) };\n }\n\n /**\n * This returns a clone of the options or options of the edge or node to be used for construction of new edges or check functions for new nodes.\n * @param item\n * @param type\n * @returns {{}}\n */\n }, {\n key: \"cloneOptions\",\n value: function cloneOptions(item, type) {\n var clonedOptions = {};\n if (type === undefined || type === 'node') {\n util.deepExtend(clonedOptions, item.options, true);\n clonedOptions.x = item.x;\n clonedOptions.y = item.y;\n clonedOptions.amountOfConnections = item.edges.length;\n } else {\n util.deepExtend(clonedOptions, item.options, true);\n }\n return clonedOptions;\n }\n }]);\n\n return NetworkUtil;\n })();\n\n exports[\"default\"] = NetworkUtil;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 100 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _get = function get(_x, _x2, _x3) { var _again = true; _function: while (_again) { var object = _x, property = _x2, receiver = _x3; _again = false; if (object === null) object = Function.prototype; var desc = Object.getOwnPropertyDescriptor(object, property); if (desc === undefined) { var parent = Object.getPrototypeOf(object); if (parent === null) { return undefined; } else { _x = parent; _x2 = property; _x3 = receiver; _again = true; desc = parent = undefined; continue _function; } } else if ('value' in desc) { return desc.value; } else { var getter = desc.get; if (getter === undefined) { return undefined; } return getter.call(receiver); } } };\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n function _inherits(subClass, superClass) { if (typeof superClass !== 'function' && superClass !== null) { throw new TypeError('Super expression must either be null or a function, not ' + typeof superClass); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, enumerable: false, writable: true, configurable: true } }); if (superClass) Object.setPrototypeOf ? Object.setPrototypeOf(subClass, superClass) : subClass.__proto__ = superClass; }\n\n var _Node2 = __webpack_require__(61);\n\n var _Node3 = _interopRequireDefault(_Node2);\n\n /**\n *\n */\n\n var Cluster = (function (_Node) {\n _inherits(Cluster, _Node);\n\n function Cluster(options, body, imagelist, grouplist, globalOptions) {\n _classCallCheck(this, Cluster);\n\n _get(Object.getPrototypeOf(Cluster.prototype), 'constructor', this).call(this, options, body, imagelist, grouplist, globalOptions);\n\n this.isCluster = true;\n this.containedNodes = {};\n this.containedEdges = {};\n }\n\n return Cluster;\n })(_Node3['default']);\n\n exports['default'] = Cluster;\n module.exports = exports['default'];\n\n/***/ },\n/* 101 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n if (typeof window !== 'undefined') {\n window.requestAnimationFrame = window.requestAnimationFrame || window.mozRequestAnimationFrame || window.webkitRequestAnimationFrame || window.msRequestAnimationFrame;\n }\n\n var util = __webpack_require__(1);\n\n var CanvasRenderer = (function () {\n function CanvasRenderer(body, canvas) {\n _classCallCheck(this, CanvasRenderer);\n\n this.body = body;\n this.canvas = canvas;\n\n this.redrawRequested = false;\n this.renderTimer = undefined;\n this.requiresTimeout = true;\n this.renderingActive = false;\n this.renderRequests = 0;\n this.pixelRatio = undefined;\n this.allowRedraw = true;\n\n this.dragging = false;\n this.options = {};\n this.defaultOptions = {\n hideEdgesOnDrag: false,\n hideNodesOnDrag: false\n };\n util.extend(this.options, this.defaultOptions);\n\n this._determineBrowserMethod();\n this.bindEventListeners();\n }\n\n _createClass(CanvasRenderer, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this = this;\n\n this.body.emitter.on(\"dragStart\", function () {\n _this.dragging = true;\n });\n this.body.emitter.on(\"dragEnd\", function () {\n return _this.dragging = false;\n });\n this.body.emitter.on(\"_resizeNodes\", function () {\n return _this._resizeNodes();\n });\n this.body.emitter.on(\"_redraw\", function () {\n if (_this.renderingActive === false) {\n _this._redraw();\n }\n });\n this.body.emitter.on(\"_blockRedraw\", function () {\n _this.allowRedraw = false;\n });\n this.body.emitter.on(\"_allowRedraw\", function () {\n _this.allowRedraw = true;_this.redrawRequested = false;\n });\n this.body.emitter.on(\"_requestRedraw\", this._requestRedraw.bind(this));\n this.body.emitter.on(\"_startRendering\", function () {\n _this.renderRequests += 1;\n _this.renderingActive = true;\n _this._startRendering();\n });\n this.body.emitter.on(\"_stopRendering\", function () {\n _this.renderRequests -= 1;\n _this.renderingActive = _this.renderRequests > 0;\n _this.renderTimer = undefined;\n });\n this.body.emitter.on('destroy', function () {\n _this.renderRequests = 0;\n _this.allowRedraw = false;\n _this.renderingActive = false;\n if (_this.requiresTimeout === true) {\n clearTimeout(_this.renderTimer);\n } else {\n cancelAnimationFrame(_this.renderTimer);\n }\n _this.body.emitter.off();\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n var fields = ['hideEdgesOnDrag', 'hideNodesOnDrag'];\n util.selectiveDeepExtend(fields, this.options, options);\n }\n }\n }, {\n key: '_startRendering',\n value: function _startRendering() {\n if (this.renderingActive === true) {\n if (this.renderTimer === undefined) {\n if (this.requiresTimeout === true) {\n this.renderTimer = window.setTimeout(this._renderStep.bind(this), this.simulationInterval); // wait this.renderTimeStep milliseconds and perform the animation step function\n } else {\n this.renderTimer = window.requestAnimationFrame(this._renderStep.bind(this)); // wait this.renderTimeStep milliseconds and perform the animation step function\n }\n }\n }\n }\n }, {\n key: '_renderStep',\n value: function _renderStep() {\n if (this.renderingActive === true) {\n // reset the renderTimer so a new scheduled animation step can be set\n this.renderTimer = undefined;\n\n if (this.requiresTimeout === true) {\n // this schedules a new simulation step\n this._startRendering();\n }\n\n this._redraw();\n\n if (this.requiresTimeout === false) {\n // this schedules a new simulation step\n this._startRendering();\n }\n }\n }\n\n /**\n * Redraw the network with the current data\n * chart will be resized too.\n */\n }, {\n key: 'redraw',\n value: function redraw() {\n this.body.emitter.emit('setSize');\n this._redraw();\n }\n\n /**\n * Redraw the network with the current data\n * @param hidden | used to get the first estimate of the node sizes. only the nodes are drawn after which they are quickly drawn over.\n * @private\n */\n }, {\n key: '_requestRedraw',\n value: function _requestRedraw() {\n var _this2 = this;\n\n if (this.redrawRequested !== true && this.renderingActive === false && this.allowRedraw === true) {\n this.redrawRequested = true;\n if (this.requiresTimeout === true) {\n window.setTimeout(function () {\n _this2._redraw(false);\n }, 0);\n } else {\n window.requestAnimationFrame(function () {\n _this2._redraw(false);\n });\n }\n }\n }\n }, {\n key: '_redraw',\n value: function _redraw() {\n var hidden = arguments.length <= 0 || arguments[0] === undefined ? false : arguments[0];\n\n if (this.allowRedraw === true) {\n this.body.emitter.emit(\"initRedraw\");\n\n this.redrawRequested = false;\n var ctx = this.canvas.frame.canvas.getContext('2d');\n\n // when the container div was hidden, this fixes it back up!\n if (this.canvas.frame.canvas.width === 0 || this.canvas.frame.canvas.height === 0) {\n this.canvas.setSize();\n }\n\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n\n ctx.setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n\n // clear the canvas\n var w = this.canvas.frame.canvas.clientWidth;\n var h = this.canvas.frame.canvas.clientHeight;\n ctx.clearRect(0, 0, w, h);\n\n // if the div is hidden, we stop the redraw here for performance.\n if (this.canvas.frame.clientWidth === 0) {\n return;\n }\n\n // set scaling and translation\n ctx.save();\n ctx.translate(this.body.view.translation.x, this.body.view.translation.y);\n ctx.scale(this.body.view.scale, this.body.view.scale);\n\n ctx.beginPath();\n this.body.emitter.emit(\"beforeDrawing\", ctx);\n ctx.closePath();\n\n if (hidden === false) {\n if (this.dragging === false || this.dragging === true && this.options.hideEdgesOnDrag === false) {\n this._drawEdges(ctx);\n }\n }\n\n if (this.dragging === false || this.dragging === true && this.options.hideNodesOnDrag === false) {\n this._drawNodes(ctx, hidden);\n }\n\n ctx.beginPath();\n this.body.emitter.emit(\"afterDrawing\", ctx);\n ctx.closePath();\n\n // restore original scaling and translation\n ctx.restore();\n if (hidden === true) {\n ctx.clearRect(0, 0, w, h);\n }\n }\n }\n\n /**\n * Redraw all nodes\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext('2d');\n * @param {CanvasRenderingContext2D} ctx\n * @param {Boolean} [alwaysShow]\n * @private\n */\n }, {\n key: '_resizeNodes',\n value: function _resizeNodes() {\n var ctx = this.canvas.frame.canvas.getContext('2d');\n if (this.pixelRatio === undefined) {\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n }\n ctx.setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n ctx.save();\n ctx.translate(this.body.view.translation.x, this.body.view.translation.y);\n ctx.scale(this.body.view.scale, this.body.view.scale);\n\n var nodes = this.body.nodes;\n var node = undefined;\n\n // resize all nodes\n for (var nodeId in nodes) {\n if (nodes.hasOwnProperty(nodeId)) {\n node = nodes[nodeId];\n node.resize(ctx);\n node.updateBoundingBox(ctx, node.selected);\n }\n }\n\n // restore original scaling and translation\n ctx.restore();\n }\n\n /**\n * Redraw all nodes\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext('2d');\n * @param {CanvasRenderingContext2D} ctx\n * @param {Boolean} [alwaysShow]\n * @private\n */\n }, {\n key: '_drawNodes',\n value: function _drawNodes(ctx) {\n var alwaysShow = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var nodes = this.body.nodes;\n var nodeIndices = this.body.nodeIndices;\n var node = undefined;\n var selected = [];\n var margin = 20;\n var topLeft = this.canvas.DOMtoCanvas({ x: -margin, y: -margin });\n var bottomRight = this.canvas.DOMtoCanvas({\n x: this.canvas.frame.canvas.clientWidth + margin,\n y: this.canvas.frame.canvas.clientHeight + margin\n });\n var viewableArea = { top: topLeft.y, left: topLeft.x, bottom: bottomRight.y, right: bottomRight.x };\n\n // draw unselected nodes;\n for (var i = 0; i < nodeIndices.length; i++) {\n node = nodes[nodeIndices[i]];\n // set selected nodes aside\n if (node.isSelected()) {\n selected.push(nodeIndices[i]);\n } else {\n if (alwaysShow === true) {\n node.draw(ctx);\n } else if (node.isBoundingBoxOverlappingWith(viewableArea) === true) {\n node.draw(ctx);\n } else {\n node.updateBoundingBox(ctx, node.selected);\n }\n }\n }\n\n // draw the selected nodes on top\n for (var i = 0; i < selected.length; i++) {\n node = nodes[selected[i]];\n node.draw(ctx);\n }\n }\n\n /**\n * Redraw all edges\n * The 2d context of a HTML canvas can be retrieved by canvas.getContext('2d');\n * @param {CanvasRenderingContext2D} ctx\n * @private\n */\n }, {\n key: '_drawEdges',\n value: function _drawEdges(ctx) {\n var edges = this.body.edges;\n var edgeIndices = this.body.edgeIndices;\n var edge = undefined;\n\n for (var i = 0; i < edgeIndices.length; i++) {\n edge = edges[edgeIndices[i]];\n if (edge.connected === true) {\n edge.draw(ctx);\n }\n }\n }\n\n /**\n * Determine if the browser requires a setTimeout or a requestAnimationFrame. This was required because\n * some implementations (safari and IE9) did not support requestAnimationFrame\n * @private\n */\n }, {\n key: '_determineBrowserMethod',\n value: function _determineBrowserMethod() {\n if (typeof window !== 'undefined') {\n var browserType = navigator.userAgent.toLowerCase();\n this.requiresTimeout = false;\n if (browserType.indexOf('msie 9.0') != -1) {\n // IE 9\n this.requiresTimeout = true;\n } else if (browserType.indexOf('safari') != -1) {\n // safari\n if (browserType.indexOf('chrome') <= -1) {\n this.requiresTimeout = true;\n }\n }\n } else {\n this.requiresTimeout = true;\n }\n }\n }]);\n\n return CanvasRenderer;\n })();\n\n exports['default'] = CanvasRenderer;\n module.exports = exports['default'];\n\n/***/ },\n/* 102 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var Hammer = __webpack_require__(20);\n var hammerUtil = __webpack_require__(24);\n\n var util = __webpack_require__(1);\n\n /**\n * Create the main frame for the Network.\n * This function is executed once when a Network object is created. The frame\n * contains a canvas, and this canvas contains all objects like the axis and\n * nodes.\n * @private\n */\n\n var Canvas = (function () {\n function Canvas(body) {\n _classCallCheck(this, Canvas);\n\n this.body = body;\n this.pixelRatio = 1;\n this.resizeTimer = undefined;\n this.resizeFunction = this._onResize.bind(this);\n this.cameraState = {};\n\n this.options = {};\n this.defaultOptions = {\n autoResize: true,\n height: '100%',\n width: '100%'\n };\n util.extend(this.options, this.defaultOptions);\n\n this.bindEventListeners();\n }\n\n _createClass(Canvas, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this = this;\n\n // bind the events\n this.body.emitter.once(\"resize\", function (obj) {\n if (obj.width !== 0) {\n _this.body.view.translation.x = obj.width * 0.5;\n }\n if (obj.height !== 0) {\n _this.body.view.translation.y = obj.height * 0.5;\n }\n });\n this.body.emitter.on(\"setSize\", this.setSize.bind(this));\n this.body.emitter.on(\"destroy\", function () {\n _this.hammerFrame.destroy();\n _this.hammer.destroy();\n _this._cleanUp();\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n var _this2 = this;\n\n if (options !== undefined) {\n var fields = ['width', 'height', 'autoResize'];\n util.selectiveDeepExtend(fields, this.options, options);\n }\n\n if (this.options.autoResize === true) {\n // automatically adapt to a changing size of the browser.\n this._cleanUp();\n this.resizeTimer = setInterval(function () {\n var changed = _this2.setSize();\n if (changed === true) {\n _this2.body.emitter.emit(\"_requestRedraw\");\n }\n }, 1000);\n this.resizeFunction = this._onResize.bind(this);\n util.addEventListener(window, 'resize', this.resizeFunction);\n }\n }\n }, {\n key: '_cleanUp',\n value: function _cleanUp() {\n // automatically adapt to a changing size of the browser.\n if (this.resizeTimer !== undefined) {\n clearInterval(this.resizeTimer);\n }\n util.removeEventListener(window, 'resize', this.resizeFunction);\n this.resizeFunction = undefined;\n }\n }, {\n key: '_onResize',\n value: function _onResize() {\n this.setSize();\n this.body.emitter.emit(\"_redraw\");\n }\n\n /**\n * Get and store the cameraState\n * @private\n */\n }, {\n key: '_getCameraState',\n value: function _getCameraState() {\n var pixelRatio = arguments.length <= 0 || arguments[0] === undefined ? this.pixelRatio : arguments[0];\n\n this.cameraState.previousWidth = this.frame.canvas.width / pixelRatio;\n this.cameraState.previousHeight = this.frame.canvas.height / pixelRatio;\n this.cameraState.scale = this.body.view.scale;\n this.cameraState.position = this.DOMtoCanvas({ x: 0.5 * this.frame.canvas.width / pixelRatio, y: 0.5 * this.frame.canvas.height / pixelRatio });\n }\n\n /**\n * Set the cameraState\n * @private\n */\n }, {\n key: '_setCameraState',\n value: function _setCameraState() {\n if (this.cameraState.scale !== undefined && this.frame.canvas.clientWidth !== 0 && this.frame.canvas.clientHeight !== 0 && this.pixelRatio !== 0 && this.cameraState.previousWidth > 0) {\n\n var widthRatio = this.frame.canvas.width / this.pixelRatio / this.cameraState.previousWidth;\n var heightRatio = this.frame.canvas.height / this.pixelRatio / this.cameraState.previousHeight;\n var newScale = this.cameraState.scale;\n\n if (widthRatio != 1 && heightRatio != 1) {\n newScale = this.cameraState.scale * 0.5 * (widthRatio + heightRatio);\n } else if (widthRatio != 1) {\n newScale = this.cameraState.scale * widthRatio;\n } else if (heightRatio != 1) {\n newScale = this.cameraState.scale * heightRatio;\n }\n\n this.body.view.scale = newScale;\n // this comes from the view module.\n var currentViewCenter = this.DOMtoCanvas({\n x: 0.5 * this.frame.canvas.clientWidth,\n y: 0.5 * this.frame.canvas.clientHeight\n });\n\n var distanceFromCenter = { // offset from view, distance view has to change by these x and y to center the node\n x: currentViewCenter.x - this.cameraState.position.x,\n y: currentViewCenter.y - this.cameraState.position.y\n };\n this.body.view.translation.x += distanceFromCenter.x * this.body.view.scale;\n this.body.view.translation.y += distanceFromCenter.y * this.body.view.scale;\n }\n }\n }, {\n key: '_prepareValue',\n value: function _prepareValue(value) {\n if (typeof value === 'number') {\n return value + 'px';\n } else if (typeof value === 'string') {\n if (value.indexOf('%') !== -1 || value.indexOf('px') !== -1) {\n return value;\n } else if (value.indexOf('%') === -1) {\n return value + 'px';\n }\n }\n throw new Error('Could not use the value supplied for width or height:' + value);\n }\n\n /**\n * Create the HTML\n */\n }, {\n key: '_create',\n value: function _create() {\n // remove all elements from the container element.\n while (this.body.container.hasChildNodes()) {\n this.body.container.removeChild(this.body.container.firstChild);\n }\n\n this.frame = document.createElement('div');\n this.frame.className = 'vis-network';\n this.frame.style.position = 'relative';\n this.frame.style.overflow = 'hidden';\n this.frame.tabIndex = 900; // tab index is required for keycharm to bind keystrokes to the div instead of the window\n\n //////////////////////////////////////////////////////////////////\n\n this.frame.canvas = document.createElement(\"canvas\");\n this.frame.canvas.style.position = 'relative';\n this.frame.appendChild(this.frame.canvas);\n\n if (!this.frame.canvas.getContext) {\n var noCanvas = document.createElement('DIV');\n noCanvas.style.color = 'red';\n noCanvas.style.fontWeight = 'bold';\n noCanvas.style.padding = '10px';\n noCanvas.innerHTML = 'Error: your browser does not support HTML canvas';\n this.frame.canvas.appendChild(noCanvas);\n } else {\n var ctx = this.frame.canvas.getContext(\"2d\");\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n\n this.frame.canvas.getContext(\"2d\").setTransform(this.pixelRatio, 0, 0, this.pixelRatio, 0, 0);\n }\n\n // add the frame to the container element\n this.body.container.appendChild(this.frame);\n\n this.body.view.scale = 1;\n this.body.view.translation = { x: 0.5 * this.frame.canvas.clientWidth, y: 0.5 * this.frame.canvas.clientHeight };\n\n this._bindHammer();\n }\n\n /**\n * This function binds hammer, it can be repeated over and over due to the uniqueness check.\n * @private\n */\n }, {\n key: '_bindHammer',\n value: function _bindHammer() {\n var _this3 = this;\n\n if (this.hammer !== undefined) {\n this.hammer.destroy();\n }\n this.drag = {};\n this.pinch = {};\n\n // init hammer\n this.hammer = new Hammer(this.frame.canvas);\n this.hammer.get('pinch').set({ enable: true });\n // enable to get better response, todo: test on mobile.\n this.hammer.get('pan').set({ threshold: 5, direction: 30 }); // 30 is ALL_DIRECTIONS in hammer.\n\n hammerUtil.onTouch(this.hammer, function (event) {\n _this3.body.eventListeners.onTouch(event);\n });\n this.hammer.on('tap', function (event) {\n _this3.body.eventListeners.onTap(event);\n });\n this.hammer.on('doubletap', function (event) {\n _this3.body.eventListeners.onDoubleTap(event);\n });\n this.hammer.on('press', function (event) {\n _this3.body.eventListeners.onHold(event);\n });\n this.hammer.on('panstart', function (event) {\n _this3.body.eventListeners.onDragStart(event);\n });\n this.hammer.on('panmove', function (event) {\n _this3.body.eventListeners.onDrag(event);\n });\n this.hammer.on('panend', function (event) {\n _this3.body.eventListeners.onDragEnd(event);\n });\n this.hammer.on('pinch', function (event) {\n _this3.body.eventListeners.onPinch(event);\n });\n\n // TODO: neatly cleanup these handlers when re-creating the Canvas, IF these are done with hammer, event.stopPropagation will not work?\n this.frame.canvas.addEventListener('mousewheel', function (event) {\n _this3.body.eventListeners.onMouseWheel(event);\n });\n this.frame.canvas.addEventListener('DOMMouseScroll', function (event) {\n _this3.body.eventListeners.onMouseWheel(event);\n });\n\n this.frame.canvas.addEventListener('mousemove', function (event) {\n _this3.body.eventListeners.onMouseMove(event);\n });\n this.frame.canvas.addEventListener('contextmenu', function (event) {\n _this3.body.eventListeners.onContext(event);\n });\n\n this.hammerFrame = new Hammer(this.frame);\n hammerUtil.onRelease(this.hammerFrame, function (event) {\n _this3.body.eventListeners.onRelease(event);\n });\n }\n\n /**\n * Set a new size for the network\n * @param {string} width Width in pixels or percentage (for example '800px'\n * or '50%')\n * @param {string} height Height in pixels or percentage (for example '400px'\n * or '30%')\n */\n }, {\n key: 'setSize',\n value: function setSize() {\n var width = arguments.length <= 0 || arguments[0] === undefined ? this.options.width : arguments[0];\n var height = arguments.length <= 1 || arguments[1] === undefined ? this.options.height : arguments[1];\n\n width = this._prepareValue(width);\n height = this._prepareValue(height);\n\n var emitEvent = false;\n var oldWidth = this.frame.canvas.width;\n var oldHeight = this.frame.canvas.height;\n\n // update the pixel ratio\n var ctx = this.frame.canvas.getContext(\"2d\");\n var previousRatio = this.pixelRatio; // we cache this because the camera state storage needs the old value\n this.pixelRatio = (window.devicePixelRatio || 1) / (ctx.webkitBackingStorePixelRatio || ctx.mozBackingStorePixelRatio || ctx.msBackingStorePixelRatio || ctx.oBackingStorePixelRatio || ctx.backingStorePixelRatio || 1);\n\n if (width != this.options.width || height != this.options.height || this.frame.style.width != width || this.frame.style.height != height) {\n this._getCameraState(previousRatio);\n\n this.frame.style.width = width;\n this.frame.style.height = height;\n\n this.frame.canvas.style.width = '100%';\n this.frame.canvas.style.height = '100%';\n\n this.frame.canvas.width = Math.round(this.frame.canvas.clientWidth * this.pixelRatio);\n this.frame.canvas.height = Math.round(this.frame.canvas.clientHeight * this.pixelRatio);\n\n this.options.width = width;\n this.options.height = height;\n\n emitEvent = true;\n } else {\n // this would adapt the width of the canvas to the width from 100% if and only if\n // there is a change.\n\n // store the camera if there is a change in size.\n if (this.frame.canvas.width != Math.round(this.frame.canvas.clientWidth * this.pixelRatio) || this.frame.canvas.height != Math.round(this.frame.canvas.clientHeight * this.pixelRatio)) {\n this._getCameraState(previousRatio);\n }\n\n if (this.frame.canvas.width != Math.round(this.frame.canvas.clientWidth * this.pixelRatio)) {\n this.frame.canvas.width = Math.round(this.frame.canvas.clientWidth * this.pixelRatio);\n emitEvent = true;\n }\n if (this.frame.canvas.height != Math.round(this.frame.canvas.clientHeight * this.pixelRatio)) {\n this.frame.canvas.height = Math.round(this.frame.canvas.clientHeight * this.pixelRatio);\n emitEvent = true;\n }\n }\n\n if (emitEvent === true) {\n this.body.emitter.emit('resize', {\n width: Math.round(this.frame.canvas.width / this.pixelRatio),\n height: Math.round(this.frame.canvas.height / this.pixelRatio),\n oldWidth: Math.round(oldWidth / this.pixelRatio),\n oldHeight: Math.round(oldHeight / this.pixelRatio)\n });\n\n // restore the camera on change.\n this._setCameraState();\n }\n\n return emitEvent;\n }\n }, {\n key: '_XconvertDOMtoCanvas',\n\n /**\n * Convert the X coordinate in DOM-space (coordinate point in browser relative to the container div) to\n * the X coordinate in canvas-space (the simulation sandbox, which the camera looks upon)\n * @param {number} x\n * @returns {number}\n * @private\n */\n value: function _XconvertDOMtoCanvas(x) {\n return (x - this.body.view.translation.x) / this.body.view.scale;\n }\n\n /**\n * Convert the X coordinate in canvas-space (the simulation sandbox, which the camera looks upon) to\n * the X coordinate in DOM-space (coordinate point in browser relative to the container div)\n * @param {number} x\n * @returns {number}\n * @private\n */\n }, {\n key: '_XconvertCanvasToDOM',\n value: function _XconvertCanvasToDOM(x) {\n return x * this.body.view.scale + this.body.view.translation.x;\n }\n\n /**\n * Convert the Y coordinate in DOM-space (coordinate point in browser relative to the container div) to\n * the Y coordinate in canvas-space (the simulation sandbox, which the camera looks upon)\n * @param {number} y\n * @returns {number}\n * @private\n */\n }, {\n key: '_YconvertDOMtoCanvas',\n value: function _YconvertDOMtoCanvas(y) {\n return (y - this.body.view.translation.y) / this.body.view.scale;\n }\n\n /**\n * Convert the Y coordinate in canvas-space (the simulation sandbox, which the camera looks upon) to\n * the Y coordinate in DOM-space (coordinate point in browser relative to the container div)\n * @param {number} y\n * @returns {number}\n * @private\n */\n }, {\n key: '_YconvertCanvasToDOM',\n value: function _YconvertCanvasToDOM(y) {\n return y * this.body.view.scale + this.body.view.translation.y;\n }\n\n /**\n *\n * @param {object} pos = {x: number, y: number}\n * @returns {{x: number, y: number}}\n * @constructor\n */\n }, {\n key: 'canvasToDOM',\n value: function canvasToDOM(pos) {\n return { x: this._XconvertCanvasToDOM(pos.x), y: this._YconvertCanvasToDOM(pos.y) };\n }\n\n /**\n *\n * @param {object} pos = {x: number, y: number}\n * @returns {{x: number, y: number}}\n * @constructor\n */\n }, {\n key: 'DOMtoCanvas',\n value: function DOMtoCanvas(pos) {\n return { x: this._XconvertDOMtoCanvas(pos.x), y: this._YconvertDOMtoCanvas(pos.y) };\n }\n }]);\n\n return Canvas;\n })();\n\n exports['default'] = Canvas;\n module.exports = exports['default'];\n\n/***/ },\n/* 103 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _NetworkUtil = __webpack_require__(99);\n\n var _NetworkUtil2 = _interopRequireDefault(_NetworkUtil);\n\n var util = __webpack_require__(1);\n\n var View = (function () {\n function View(body, canvas) {\n var _this = this;\n\n _classCallCheck(this, View);\n\n this.body = body;\n this.canvas = canvas;\n\n this.animationSpeed = 1 / this.renderRefreshRate;\n this.animationEasingFunction = \"easeInOutQuint\";\n this.easingTime = 0;\n this.sourceScale = 0;\n this.targetScale = 0;\n this.sourceTranslation = 0;\n this.targetTranslation = 0;\n this.lockedOnNodeId = undefined;\n this.lockedOnNodeOffset = undefined;\n this.touchTime = 0;\n\n this.viewFunction = undefined;\n\n this.body.emitter.on(\"fit\", this.fit.bind(this));\n this.body.emitter.on(\"animationFinished\", function () {\n _this.body.emitter.emit(\"_stopRendering\");\n });\n this.body.emitter.on(\"unlockNode\", this.releaseNode.bind(this));\n }\n\n _createClass(View, [{\n key: 'setOptions',\n value: function setOptions() {\n var options = arguments.length <= 0 || arguments[0] === undefined ? {} : arguments[0];\n\n this.options = options;\n }\n\n /**\n * This function zooms out to fit all data on screen based on amount of nodes\n * @param {Object} Options\n * @param {Boolean} [initialZoom] | zoom based on fitted formula or range, true = fitted, default = false;\n */\n }, {\n key: 'fit',\n value: function fit() {\n var options = arguments.length <= 0 || arguments[0] === undefined ? { nodes: [] } : arguments[0];\n var initialZoom = arguments.length <= 1 || arguments[1] === undefined ? false : arguments[1];\n\n var range = undefined;\n var zoomLevel = undefined;\n if (options.nodes === undefined || options.nodes.length === 0) {\n options.nodes = this.body.nodeIndices;\n }\n\n if (initialZoom === true) {\n // check if more than half of the nodes have a predefined position. If so, we use the range, not the approximation.\n var positionDefined = 0;\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n var node = this.body.nodes[nodeId];\n if (node.predefinedPosition === true) {\n positionDefined += 1;\n }\n }\n }\n if (positionDefined > 0.5 * this.body.nodeIndices.length) {\n this.fit(options, false);\n return;\n }\n\n range = _NetworkUtil2['default'].getRange(this.body.nodes, options.nodes);\n\n var numberOfNodes = this.body.nodeIndices.length;\n zoomLevel = 12.662 / (numberOfNodes + 7.4147) + 0.0964822; // this is obtained from fitting a dataset from 5 points with scale levels that looked good.\n\n // correct for larger canvasses.\n var factor = Math.min(this.canvas.frame.canvas.clientWidth / 600, this.canvas.frame.canvas.clientHeight / 600);\n zoomLevel *= factor;\n } else {\n this.body.emitter.emit(\"_resizeNodes\");\n range = _NetworkUtil2['default'].getRange(this.body.nodes, options.nodes);\n\n var xDistance = Math.abs(range.maxX - range.minX) * 1.1;\n var yDistance = Math.abs(range.maxY - range.minY) * 1.1;\n\n var xZoomLevel = this.canvas.frame.canvas.clientWidth / xDistance;\n var yZoomLevel = this.canvas.frame.canvas.clientHeight / yDistance;\n\n zoomLevel = xZoomLevel <= yZoomLevel ? xZoomLevel : yZoomLevel;\n }\n\n if (zoomLevel > 1.0) {\n zoomLevel = 1.0;\n } else if (zoomLevel === 0) {\n zoomLevel = 1.0;\n }\n\n var center = _NetworkUtil2['default'].findCenter(range);\n var animationOptions = { position: center, scale: zoomLevel, animation: options.animation };\n this.moveTo(animationOptions);\n }\n\n // animation\n\n /**\n * Center a node in view.\n *\n * @param {Number} nodeId\n * @param {Number} [options]\n */\n }, {\n key: 'focus',\n value: function focus(nodeId) {\n var options = arguments.length <= 1 || arguments[1] === undefined ? {} : arguments[1];\n\n if (this.body.nodes[nodeId] !== undefined) {\n var nodePosition = { x: this.body.nodes[nodeId].x, y: this.body.nodes[nodeId].y };\n options.position = nodePosition;\n options.lockedOnNode = nodeId;\n\n this.moveTo(options);\n } else {\n console.log(\"Node: \" + nodeId + \" cannot be found.\");\n }\n }\n\n /**\n *\n * @param {Object} options | options.offset = {x:Number, y:Number} // offset from the center in DOM pixels\n * | options.scale = Number // scale to move to\n * | options.position = {x:Number, y:Number} // position to move to\n * | options.animation = {duration:Number, easingFunction:String} || Boolean // position to move to\n */\n }, {\n key: 'moveTo',\n value: function moveTo(options) {\n if (options === undefined) {\n options = {};\n return;\n }\n if (options.offset === undefined) {\n options.offset = { x: 0, y: 0 };\n }\n if (options.offset.x === undefined) {\n options.offset.x = 0;\n }\n if (options.offset.y === undefined) {\n options.offset.y = 0;\n }\n if (options.scale === undefined) {\n options.scale = this.body.view.scale;\n }\n if (options.position === undefined) {\n options.position = this.getViewPosition();\n }\n if (options.animation === undefined) {\n options.animation = { duration: 0 };\n }\n if (options.animation === false) {\n options.animation = { duration: 0 };\n }\n if (options.animation === true) {\n options.animation = {};\n }\n if (options.animation.duration === undefined) {\n options.animation.duration = 1000;\n } // default duration\n if (options.animation.easingFunction === undefined) {\n options.animation.easingFunction = \"easeInOutQuad\";\n } // default easing function\n\n this.animateView(options);\n }\n\n /**\n *\n * @param {Object} options | options.offset = {x:Number, y:Number} // offset from the center in DOM pixels\n * | options.time = Number // animation time in milliseconds\n * | options.scale = Number // scale to animate to\n * | options.position = {x:Number, y:Number} // position to animate to\n * | options.easingFunction = String // linear, easeInQuad, easeOutQuad, easeInOutQuad,\n * // easeInCubic, easeOutCubic, easeInOutCubic,\n * // easeInQuart, easeOutQuart, easeInOutQuart,\n * // easeInQuint, easeOutQuint, easeInOutQuint\n */\n }, {\n key: 'animateView',\n value: function animateView(options) {\n if (options === undefined) {\n return;\n }\n this.animationEasingFunction = options.animation.easingFunction;\n // release if something focussed on the node\n this.releaseNode();\n if (options.locked === true) {\n this.lockedOnNodeId = options.lockedOnNode;\n this.lockedOnNodeOffset = options.offset;\n }\n\n // forcefully complete the old animation if it was still running\n if (this.easingTime != 0) {\n this._transitionRedraw(true); // by setting easingtime to 1, we finish the animation.\n }\n\n this.sourceScale = this.body.view.scale;\n this.sourceTranslation = this.body.view.translation;\n this.targetScale = options.scale;\n\n // set the scale so the viewCenter is based on the correct zoom level. This is overridden in the transitionRedraw\n // but at least then we'll have the target transition\n this.body.view.scale = this.targetScale;\n var viewCenter = this.canvas.DOMtoCanvas({ x: 0.5 * this.canvas.frame.canvas.clientWidth, y: 0.5 * this.canvas.frame.canvas.clientHeight });\n\n var distanceFromCenter = { // offset from view, distance view has to change by these x and y to center the node\n x: viewCenter.x - options.position.x,\n y: viewCenter.y - options.position.y\n };\n this.targetTranslation = {\n x: this.sourceTranslation.x + distanceFromCenter.x * this.targetScale + options.offset.x,\n y: this.sourceTranslation.y + distanceFromCenter.y * this.targetScale + options.offset.y\n };\n\n // if the time is set to 0, don't do an animation\n if (options.animation.duration === 0) {\n if (this.lockedOnNodeId != undefined) {\n this.viewFunction = this._lockedRedraw.bind(this);\n this.body.emitter.on(\"initRedraw\", this.viewFunction);\n } else {\n this.body.view.scale = this.targetScale;\n this.body.view.translation = this.targetTranslation;\n this.body.emitter.emit(\"_requestRedraw\");\n }\n } else {\n this.animationSpeed = 1 / (60 * options.animation.duration * 0.001) || 1 / 60; // 60 for 60 seconds, 0.001 for milli's\n this.animationEasingFunction = options.animation.easingFunction;\n\n this.viewFunction = this._transitionRedraw.bind(this);\n this.body.emitter.on(\"initRedraw\", this.viewFunction);\n this.body.emitter.emit(\"_startRendering\");\n }\n }\n\n /**\n * used to animate smoothly by hijacking the redraw function.\n * @private\n */\n }, {\n key: '_lockedRedraw',\n value: function _lockedRedraw() {\n var nodePosition = { x: this.body.nodes[this.lockedOnNodeId].x, y: this.body.nodes[this.lockedOnNodeId].y };\n var viewCenter = this.canvas.DOMtoCanvas({ x: 0.5 * this.canvas.frame.canvas.clientWidth, y: 0.5 * this.canvas.frame.canvas.clientHeight });\n var distanceFromCenter = { // offset from view, distance view has to change by these x and y to center the node\n x: viewCenter.x - nodePosition.x,\n y: viewCenter.y - nodePosition.y\n };\n var sourceTranslation = this.body.view.translation;\n var targetTranslation = {\n x: sourceTranslation.x + distanceFromCenter.x * this.body.view.scale + this.lockedOnNodeOffset.x,\n y: sourceTranslation.y + distanceFromCenter.y * this.body.view.scale + this.lockedOnNodeOffset.y\n };\n\n this.body.view.translation = targetTranslation;\n }\n }, {\n key: 'releaseNode',\n value: function releaseNode() {\n if (this.lockedOnNodeId !== undefined && this.viewFunction !== undefined) {\n this.body.emitter.off(\"initRedraw\", this.viewFunction);\n this.lockedOnNodeId = undefined;\n this.lockedOnNodeOffset = undefined;\n }\n }\n\n /**\n *\n * @param easingTime\n * @private\n */\n }, {\n key: '_transitionRedraw',\n value: function _transitionRedraw() {\n var finished = arguments.length <= 0 || arguments[0] === undefined ? false : arguments[0];\n\n this.easingTime += this.animationSpeed;\n this.easingTime = finished === true ? 1.0 : this.easingTime;\n\n var progress = util.easingFunctions[this.animationEasingFunction](this.easingTime);\n\n this.body.view.scale = this.sourceScale + (this.targetScale - this.sourceScale) * progress;\n this.body.view.translation = {\n x: this.sourceTranslation.x + (this.targetTranslation.x - this.sourceTranslation.x) * progress,\n y: this.sourceTranslation.y + (this.targetTranslation.y - this.sourceTranslation.y) * progress\n };\n\n // cleanup\n if (this.easingTime >= 1.0) {\n this.body.emitter.off(\"initRedraw\", this.viewFunction);\n this.easingTime = 0;\n if (this.lockedOnNodeId != undefined) {\n this.viewFunction = this._lockedRedraw.bind(this);\n this.body.emitter.on(\"initRedraw\", this.viewFunction);\n }\n this.body.emitter.emit(\"animationFinished\");\n }\n }\n }, {\n key: 'getScale',\n value: function getScale() {\n return this.body.view.scale;\n }\n }, {\n key: 'getViewPosition',\n value: function getViewPosition() {\n return this.canvas.DOMtoCanvas({ x: 0.5 * this.canvas.frame.canvas.clientWidth, y: 0.5 * this.canvas.frame.canvas.clientHeight });\n }\n }]);\n\n return View;\n })();\n\n exports['default'] = View;\n module.exports = exports['default'];\n\n/***/ },\n/* 104 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _componentsNavigationHandler = __webpack_require__(105);\n\n var _componentsNavigationHandler2 = _interopRequireDefault(_componentsNavigationHandler);\n\n var _componentsPopup = __webpack_require__(106);\n\n var _componentsPopup2 = _interopRequireDefault(_componentsPopup);\n\n var util = __webpack_require__(1);\n\n var InteractionHandler = (function () {\n function InteractionHandler(body, canvas, selectionHandler) {\n _classCallCheck(this, InteractionHandler);\n\n this.body = body;\n this.canvas = canvas;\n this.selectionHandler = selectionHandler;\n this.navigationHandler = new _componentsNavigationHandler2['default'](body, canvas);\n\n // bind the events from hammer to functions in this object\n this.body.eventListeners.onTap = this.onTap.bind(this);\n this.body.eventListeners.onTouch = this.onTouch.bind(this);\n this.body.eventListeners.onDoubleTap = this.onDoubleTap.bind(this);\n this.body.eventListeners.onHold = this.onHold.bind(this);\n this.body.eventListeners.onDragStart = this.onDragStart.bind(this);\n this.body.eventListeners.onDrag = this.onDrag.bind(this);\n this.body.eventListeners.onDragEnd = this.onDragEnd.bind(this);\n this.body.eventListeners.onMouseWheel = this.onMouseWheel.bind(this);\n this.body.eventListeners.onPinch = this.onPinch.bind(this);\n this.body.eventListeners.onMouseMove = this.onMouseMove.bind(this);\n this.body.eventListeners.onRelease = this.onRelease.bind(this);\n this.body.eventListeners.onContext = this.onContext.bind(this);\n\n this.touchTime = 0;\n this.drag = {};\n this.pinch = {};\n this.popup = undefined;\n this.popupObj = undefined;\n this.popupTimer = undefined;\n\n this.body.functions.getPointer = this.getPointer.bind(this);\n\n this.options = {};\n this.defaultOptions = {\n dragNodes: true,\n dragView: true,\n hover: false,\n keyboard: {\n enabled: false,\n speed: { x: 10, y: 10, zoom: 0.02 },\n bindToWindow: true\n },\n navigationButtons: false,\n tooltipDelay: 300,\n zoomView: true\n };\n util.extend(this.options, this.defaultOptions);\n\n this.bindEventListeners();\n }\n\n _createClass(InteractionHandler, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this = this;\n\n this.body.emitter.on('destroy', function () {\n clearTimeout(_this.popupTimer);\n delete _this.body.functions.getPointer;\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n // extend all but the values in fields\n var fields = ['hideEdgesOnDrag', 'hideNodesOnDrag', 'keyboard', 'multiselect', 'selectable', 'selectConnectedEdges'];\n util.selectiveNotDeepExtend(fields, this.options, options);\n\n // merge the keyboard options in.\n util.mergeOptions(this.options, options, 'keyboard');\n\n if (options.tooltip) {\n util.extend(this.options.tooltip, options.tooltip);\n if (options.tooltip.color) {\n this.options.tooltip.color = util.parseColor(options.tooltip.color);\n }\n }\n }\n\n this.navigationHandler.setOptions(this.options);\n }\n\n /**\n * Get the pointer location from a touch location\n * @param {{x: Number, y: Number}} touch\n * @return {{x: Number, y: Number}} pointer\n * @private\n */\n }, {\n key: 'getPointer',\n value: function getPointer(touch) {\n return {\n x: touch.x - util.getAbsoluteLeft(this.canvas.frame.canvas),\n y: touch.y - util.getAbsoluteTop(this.canvas.frame.canvas)\n };\n }\n\n /**\n * On start of a touch gesture, store the pointer\n * @param event\n * @private\n */\n }, {\n key: 'onTouch',\n value: function onTouch(event) {\n if (new Date().valueOf() - this.touchTime > 50) {\n this.drag.pointer = this.getPointer(event.center);\n this.drag.pinched = false;\n this.pinch.scale = this.body.view.scale;\n // to avoid double fireing of this event because we have two hammer instances. (on canvas and on frame)\n this.touchTime = new Date().valueOf();\n }\n }\n\n /**\n * handle tap/click event: select/unselect a node\n * @private\n */\n }, {\n key: 'onTap',\n value: function onTap(event) {\n var pointer = this.getPointer(event.center);\n var multiselect = this.selectionHandler.options.multiselect && (event.changedPointers[0].ctrlKey || event.changedPointers[0].metaKey);\n\n this.checkSelectionChanges(pointer, event, multiselect);\n this.selectionHandler._generateClickEvent('click', event, pointer);\n }\n\n /**\n * handle doubletap event\n * @private\n */\n }, {\n key: 'onDoubleTap',\n value: function onDoubleTap(event) {\n var pointer = this.getPointer(event.center);\n this.selectionHandler._generateClickEvent('doubleClick', event, pointer);\n }\n\n /**\n * handle long tap event: multi select nodes\n * @private\n */\n }, {\n key: 'onHold',\n value: function onHold(event) {\n var pointer = this.getPointer(event.center);\n var multiselect = this.selectionHandler.options.multiselect;\n\n this.checkSelectionChanges(pointer, event, multiselect);\n\n this.selectionHandler._generateClickEvent('click', event, pointer);\n this.selectionHandler._generateClickEvent('hold', event, pointer);\n }\n\n /**\n * handle the release of the screen\n *\n * @private\n */\n }, {\n key: 'onRelease',\n value: function onRelease(event) {\n if (new Date().valueOf() - this.touchTime > 10) {\n var pointer = this.getPointer(event.center);\n this.selectionHandler._generateClickEvent('release', event, pointer);\n // to avoid double fireing of this event because we have two hammer instances. (on canvas and on frame)\n this.touchTime = new Date().valueOf();\n }\n }\n }, {\n key: 'onContext',\n value: function onContext(event) {\n var pointer = this.getPointer({ x: event.clientX, y: event.clientY });\n this.selectionHandler._generateClickEvent('oncontext', event, pointer);\n }\n\n /**\n *\n * @param pointer\n * @param add\n */\n }, {\n key: 'checkSelectionChanges',\n value: function checkSelectionChanges(pointer, event) {\n var add = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n var previouslySelectedEdgeCount = this.selectionHandler._getSelectedEdgeCount();\n var previouslySelectedNodeCount = this.selectionHandler._getSelectedNodeCount();\n var previousSelection = this.selectionHandler.getSelection();\n var selected = undefined;\n if (add === true) {\n selected = this.selectionHandler.selectAdditionalOnPoint(pointer);\n } else {\n selected = this.selectionHandler.selectOnPoint(pointer);\n }\n var selectedEdgesCount = this.selectionHandler._getSelectedEdgeCount();\n var selectedNodesCount = this.selectionHandler._getSelectedNodeCount();\n var currentSelection = this.selectionHandler.getSelection();\n\n var _determineIfDifferent2 = this._determineIfDifferent(previousSelection, currentSelection);\n\n var nodesChanges = _determineIfDifferent2.nodesChanges;\n var edgesChanges = _determineIfDifferent2.edgesChanges;\n\n var nodeSelected = false;\n\n if (selectedNodesCount - previouslySelectedNodeCount > 0) {\n // node was selected\n this.selectionHandler._generateClickEvent('selectNode', event, pointer);\n selected = true;\n nodeSelected = true;\n } else if (selectedNodesCount - previouslySelectedNodeCount < 0) {\n // node was deselected\n this.selectionHandler._generateClickEvent('deselectNode', event, pointer, previousSelection);\n selected = true;\n } else if (selectedNodesCount === previouslySelectedNodeCount && nodesChanges === true) {\n this.selectionHandler._generateClickEvent('deselectNode', event, pointer, previousSelection);\n this.selectionHandler._generateClickEvent('selectNode', event, pointer);\n nodeSelected = true;\n selected = true;\n }\n\n // handle the selected edges\n if (selectedEdgesCount - previouslySelectedEdgeCount > 0 && nodeSelected === false) {\n // edge was selected\n this.selectionHandler._generateClickEvent('selectEdge', event, pointer);\n selected = true;\n } else if (selectedEdgesCount - previouslySelectedEdgeCount < 0) {\n // edge was deselected\n this.selectionHandler._generateClickEvent('deselectEdge', event, pointer, previousSelection);\n selected = true;\n } else if (selectedEdgesCount === previouslySelectedEdgeCount && edgesChanges === true) {\n this.selectionHandler._generateClickEvent('deselectEdge', event, pointer, previousSelection);\n this.selectionHandler._generateClickEvent('selectEdge', event, pointer);\n selected = true;\n }\n\n // fire the select event if anything has been selected or deselected\n if (selected === true) {\n // select or unselect\n this.selectionHandler._generateClickEvent('select', event, pointer);\n }\n }\n\n /**\n * This function checks if the nodes and edges previously selected have changed.\n * @param previousSelection\n * @param currentSelection\n * @returns {{nodesChanges: boolean, edgesChanges: boolean}}\n * @private\n */\n }, {\n key: '_determineIfDifferent',\n value: function _determineIfDifferent(previousSelection, currentSelection) {\n var nodesChanges = false;\n var edgesChanges = false;\n\n for (var i = 0; i < previousSelection.nodes.length; i++) {\n if (currentSelection.nodes.indexOf(previousSelection.nodes[i]) === -1) {\n nodesChanges = true;\n }\n }\n for (var i = 0; i < currentSelection.nodes.length; i++) {\n if (previousSelection.nodes.indexOf(previousSelection.nodes[i]) === -1) {\n nodesChanges = true;\n }\n }\n for (var i = 0; i < previousSelection.edges.length; i++) {\n if (currentSelection.edges.indexOf(previousSelection.edges[i]) === -1) {\n edgesChanges = true;\n }\n }\n for (var i = 0; i < currentSelection.edges.length; i++) {\n if (previousSelection.edges.indexOf(previousSelection.edges[i]) === -1) {\n edgesChanges = true;\n }\n }\n\n return { nodesChanges: nodesChanges, edgesChanges: edgesChanges };\n }\n\n /**\n * This function is called by onDragStart.\n * It is separated out because we can then overload it for the datamanipulation system.\n *\n * @private\n */\n }, {\n key: 'onDragStart',\n value: function onDragStart(event) {\n //in case the touch event was triggered on an external div, do the initial touch now.\n if (this.drag.pointer === undefined) {\n this.onTouch(event);\n }\n\n // note: drag.pointer is set in onTouch to get the initial touch location\n var node = this.selectionHandler.getNodeAt(this.drag.pointer);\n\n this.drag.dragging = true;\n this.drag.selection = [];\n this.drag.translation = util.extend({}, this.body.view.translation); // copy the object\n this.drag.nodeId = undefined;\n\n if (node !== undefined && this.options.dragNodes === true) {\n this.drag.nodeId = node.id;\n // select the clicked node if not yet selected\n if (node.isSelected() === false) {\n this.selectionHandler.unselectAll();\n this.selectionHandler.selectObject(node);\n }\n\n // after select to contain the node\n this.selectionHandler._generateClickEvent('dragStart', event, this.drag.pointer);\n\n var selection = this.selectionHandler.selectionObj.nodes;\n // create an array with the selected nodes and their original location and status\n for (var nodeId in selection) {\n if (selection.hasOwnProperty(nodeId)) {\n var object = selection[nodeId];\n var s = {\n id: object.id,\n node: object,\n\n // store original x, y, xFixed and yFixed, make the node temporarily Fixed\n x: object.x,\n y: object.y,\n xFixed: object.options.fixed.x,\n yFixed: object.options.fixed.y\n };\n\n object.options.fixed.x = true;\n object.options.fixed.y = true;\n\n this.drag.selection.push(s);\n }\n }\n } else {\n // fallback if no node is selected and thus the view is dragged.\n this.selectionHandler._generateClickEvent('dragStart', event, this.drag.pointer, undefined, true);\n }\n }\n\n /**\n * handle drag event\n * @private\n */\n }, {\n key: 'onDrag',\n value: function onDrag(event) {\n var _this2 = this;\n\n if (this.drag.pinched === true) {\n return;\n }\n\n // remove the focus on node if it is focussed on by the focusOnNode\n this.body.emitter.emit('unlockNode');\n\n var pointer = this.getPointer(event.center);\n\n var selection = this.drag.selection;\n if (selection && selection.length && this.options.dragNodes === true) {\n (function () {\n _this2.selectionHandler._generateClickEvent('dragging', event, pointer);\n\n // calculate delta's and new location\n var deltaX = pointer.x - _this2.drag.pointer.x;\n var deltaY = pointer.y - _this2.drag.pointer.y;\n\n // update position of all selected nodes\n selection.forEach(function (selection) {\n var node = selection.node;\n // only move the node if it was not fixed initially\n if (selection.xFixed === false) {\n node.x = _this2.canvas._XconvertDOMtoCanvas(_this2.canvas._XconvertCanvasToDOM(selection.x) + deltaX);\n }\n // only move the node if it was not fixed initially\n if (selection.yFixed === false) {\n node.y = _this2.canvas._YconvertDOMtoCanvas(_this2.canvas._YconvertCanvasToDOM(selection.y) + deltaY);\n }\n });\n\n // start the simulation of the physics\n _this2.body.emitter.emit('startSimulation');\n })();\n } else {\n // move the network\n if (this.options.dragView === true) {\n this.selectionHandler._generateClickEvent('dragging', event, pointer, undefined, true);\n\n // if the drag was not started properly because the click started outside the network div, start it now.\n if (this.drag.pointer === undefined) {\n this.onDragStart(event);\n return;\n }\n var diffX = pointer.x - this.drag.pointer.x;\n var diffY = pointer.y - this.drag.pointer.y;\n\n this.body.view.translation = { x: this.drag.translation.x + diffX, y: this.drag.translation.y + diffY };\n this.body.emitter.emit('_redraw');\n }\n }\n }\n\n /**\n * handle drag start event\n * @private\n */\n }, {\n key: 'onDragEnd',\n value: function onDragEnd(event) {\n this.drag.dragging = false;\n var selection = this.drag.selection;\n if (selection && selection.length) {\n selection.forEach(function (s) {\n // restore original xFixed and yFixed\n s.node.options.fixed.x = s.xFixed;\n s.node.options.fixed.y = s.yFixed;\n });\n this.selectionHandler._generateClickEvent('dragEnd', event, this.getPointer(event.center));\n this.body.emitter.emit('startSimulation');\n } else {\n this.selectionHandler._generateClickEvent('dragEnd', event, this.getPointer(event.center), undefined, true);\n this.body.emitter.emit('_requestRedraw');\n }\n }\n\n /**\n * Handle pinch event\n * @param event\n * @private\n */\n }, {\n key: 'onPinch',\n value: function onPinch(event) {\n var pointer = this.getPointer(event.center);\n\n this.drag.pinched = true;\n if (this.pinch['scale'] === undefined) {\n this.pinch.scale = 1;\n }\n\n // TODO: enabled moving while pinching?\n var scale = this.pinch.scale * event.scale;\n this.zoom(scale, pointer);\n }\n\n /**\n * Zoom the network in or out\n * @param {Number} scale a number around 1, and between 0.01 and 10\n * @param {{x: Number, y: Number}} pointer Position on screen\n * @return {Number} appliedScale scale is limited within the boundaries\n * @private\n */\n }, {\n key: 'zoom',\n value: function zoom(scale, pointer) {\n if (this.options.zoomView === true) {\n var scaleOld = this.body.view.scale;\n if (scale < 0.00001) {\n scale = 0.00001;\n }\n if (scale > 10) {\n scale = 10;\n }\n\n var preScaleDragPointer = undefined;\n if (this.drag !== undefined) {\n if (this.drag.dragging === true) {\n preScaleDragPointer = this.canvas.DOMtoCanvas(this.drag.pointer);\n }\n }\n // + this.canvas.frame.canvas.clientHeight / 2\n var translation = this.body.view.translation;\n\n var scaleFrac = scale / scaleOld;\n var tx = (1 - scaleFrac) * pointer.x + translation.x * scaleFrac;\n var ty = (1 - scaleFrac) * pointer.y + translation.y * scaleFrac;\n\n this.body.view.scale = scale;\n this.body.view.translation = { x: tx, y: ty };\n\n if (preScaleDragPointer != undefined) {\n var postScaleDragPointer = this.canvas.canvasToDOM(preScaleDragPointer);\n this.drag.pointer.x = postScaleDragPointer.x;\n this.drag.pointer.y = postScaleDragPointer.y;\n }\n\n this.body.emitter.emit('_requestRedraw');\n\n if (scaleOld < scale) {\n this.body.emitter.emit('zoom', { direction: '+', scale: this.body.view.scale });\n } else {\n this.body.emitter.emit('zoom', { direction: '-', scale: this.body.view.scale });\n }\n }\n }\n\n /**\n * Event handler for mouse wheel event, used to zoom the timeline\n * See http://adomas.org/javascript-mouse-wheel/\n * https://github.com/EightMedia/hammer.js/issues/256\n * @param {MouseEvent} event\n * @private\n */\n }, {\n key: 'onMouseWheel',\n value: function onMouseWheel(event) {\n if (this.options.zoomView === true) {\n // retrieve delta\n var delta = 0;\n if (event.wheelDelta) {\n /* IE/Opera. */\n delta = event.wheelDelta / 120;\n } else if (event.detail) {\n /* Mozilla case. */\n // In Mozilla, sign of delta is different than in IE.\n // Also, delta is multiple of 3.\n delta = -event.detail / 3;\n }\n\n // If delta is nonzero, handle it.\n // Basically, delta is now positive if wheel was scrolled up,\n // and negative, if wheel was scrolled down.\n if (delta !== 0) {\n\n // calculate the new scale\n var scale = this.body.view.scale;\n var zoom = delta / 10;\n if (delta < 0) {\n zoom = zoom / (1 - zoom);\n }\n scale *= 1 + zoom;\n\n // calculate the pointer location\n var pointer = this.getPointer({ x: event.clientX, y: event.clientY });\n\n // apply the new scale\n this.zoom(scale, pointer);\n }\n\n // Prevent default actions caused by mouse wheel.\n event.preventDefault();\n }\n }\n\n /**\n * Mouse move handler for checking whether the title moves over a node with a title.\n * @param {Event} event\n * @private\n */\n }, {\n key: 'onMouseMove',\n value: function onMouseMove(event) {\n var _this3 = this;\n\n var pointer = this.getPointer({ x: event.clientX, y: event.clientY });\n var popupVisible = false;\n\n // check if the previously selected node is still selected\n if (this.popup !== undefined) {\n if (this.popup.hidden === false) {\n this._checkHidePopup(pointer);\n }\n\n // if the popup was not hidden above\n if (this.popup.hidden === false) {\n popupVisible = true;\n this.popup.setPosition(pointer.x + 3, pointer.y - 5);\n this.popup.show();\n }\n }\n\n // if we bind the keyboard to the div, we have to highlight it to use it. This highlights it on mouse over.\n if (this.options.keyboard.bindToWindow === false && this.options.keyboard.enabled === true) {\n this.canvas.frame.focus();\n }\n\n // start a timeout that will check if the mouse is positioned above an element\n if (popupVisible === false) {\n if (this.popupTimer !== undefined) {\n clearInterval(this.popupTimer); // stop any running calculationTimer\n this.popupTimer = undefined;\n }\n if (!this.drag.dragging) {\n this.popupTimer = setTimeout(function () {\n return _this3._checkShowPopup(pointer);\n }, this.options.tooltipDelay);\n }\n }\n\n /**\n * Adding hover highlights\n */\n if (this.options.hover === true) {\n // adding hover highlights\n var obj = this.selectionHandler.getNodeAt(pointer);\n if (obj === undefined) {\n obj = this.selectionHandler.getEdgeAt(pointer);\n }\n this.selectionHandler.hoverObject(obj);\n }\n }\n\n /**\n * Check if there is an element on the given position in the network\n * (a node or edge). If so, and if this element has a title,\n * show a popup window with its title.\n *\n * @param {{x:Number, y:Number}} pointer\n * @private\n */\n }, {\n key: '_checkShowPopup',\n value: function _checkShowPopup(pointer) {\n var x = this.canvas._XconvertDOMtoCanvas(pointer.x);\n var y = this.canvas._YconvertDOMtoCanvas(pointer.y);\n var pointerObj = {\n left: x,\n top: y,\n right: x,\n bottom: y\n };\n\n var previousPopupObjId = this.popupObj === undefined ? undefined : this.popupObj.id;\n var nodeUnderCursor = false;\n var popupType = 'node';\n\n // check if a node is under the cursor.\n if (this.popupObj === undefined) {\n // search the nodes for overlap, select the top one in case of multiple nodes\n var nodeIndices = this.body.nodeIndices;\n var nodes = this.body.nodes;\n var node = undefined;\n var overlappingNodes = [];\n for (var i = 0; i < nodeIndices.length; i++) {\n node = nodes[nodeIndices[i]];\n if (node.isOverlappingWith(pointerObj) === true) {\n if (node.getTitle() !== undefined) {\n overlappingNodes.push(nodeIndices[i]);\n }\n }\n }\n\n if (overlappingNodes.length > 0) {\n // if there are overlapping nodes, select the last one, this is the one which is drawn on top of the others\n this.popupObj = nodes[overlappingNodes[overlappingNodes.length - 1]];\n // if you hover over a node, the title of the edge is not supposed to be shown.\n nodeUnderCursor = true;\n }\n }\n\n if (this.popupObj === undefined && nodeUnderCursor === false) {\n // search the edges for overlap\n var edgeIndices = this.body.edgeIndices;\n var edges = this.body.edges;\n var edge = undefined;\n var overlappingEdges = [];\n for (var i = 0; i < edgeIndices.length; i++) {\n edge = edges[edgeIndices[i]];\n if (edge.isOverlappingWith(pointerObj) === true) {\n if (edge.connected === true && edge.getTitle() !== undefined) {\n overlappingEdges.push(edgeIndices[i]);\n }\n }\n }\n\n if (overlappingEdges.length > 0) {\n this.popupObj = edges[overlappingEdges[overlappingEdges.length - 1]];\n popupType = 'edge';\n }\n }\n\n if (this.popupObj !== undefined) {\n // show popup message window\n if (this.popupObj.id !== previousPopupObjId) {\n if (this.popup === undefined) {\n this.popup = new _componentsPopup2['default'](this.canvas.frame);\n }\n\n this.popup.popupTargetType = popupType;\n this.popup.popupTargetId = this.popupObj.id;\n\n // adjust a small offset such that the mouse cursor is located in the\n // bottom left location of the popup, and you can easily move over the\n // popup area\n this.popup.setPosition(pointer.x + 3, pointer.y - 5);\n this.popup.setText(this.popupObj.getTitle());\n this.popup.show();\n this.body.emitter.emit('showPopup', this.popupObj.id);\n }\n } else {\n if (this.popup !== undefined) {\n this.popup.hide();\n this.body.emitter.emit('hidePopup');\n }\n }\n }\n\n /**\n * Check if the popup must be hidden, which is the case when the mouse is no\n * longer hovering on the object\n * @param {{x:Number, y:Number}} pointer\n * @private\n */\n }, {\n key: '_checkHidePopup',\n value: function _checkHidePopup(pointer) {\n var pointerObj = this.selectionHandler._pointerToPositionObject(pointer);\n\n var stillOnObj = false;\n if (this.popup.popupTargetType === 'node') {\n if (this.body.nodes[this.popup.popupTargetId] !== undefined) {\n stillOnObj = this.body.nodes[this.popup.popupTargetId].isOverlappingWith(pointerObj);\n\n // if the mouse is still one the node, we have to check if it is not also on one that is drawn on top of it.\n // we initially only check stillOnObj because this is much faster.\n if (stillOnObj === true) {\n var overNode = this.selectionHandler.getNodeAt(pointer);\n stillOnObj = overNode.id === this.popup.popupTargetId;\n }\n }\n } else {\n if (this.selectionHandler.getNodeAt(pointer) === undefined) {\n if (this.body.edges[this.popup.popupTargetId] !== undefined) {\n stillOnObj = this.body.edges[this.popup.popupTargetId].isOverlappingWith(pointerObj);\n }\n }\n }\n\n if (stillOnObj === false) {\n this.popupObj = undefined;\n this.popup.hide();\n this.body.emitter.emit('hidePopup');\n }\n }\n }]);\n\n return InteractionHandler;\n })();\n\n exports['default'] = InteractionHandler;\n module.exports = exports['default'];\n\n/***/ },\n/* 105 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var util = __webpack_require__(1);\n var Hammer = __webpack_require__(20);\n var hammerUtil = __webpack_require__(24);\n var keycharm = __webpack_require__(40);\n\n var NavigationHandler = (function () {\n function NavigationHandler(body, canvas) {\n var _this = this;\n\n _classCallCheck(this, NavigationHandler);\n\n this.body = body;\n this.canvas = canvas;\n\n this.iconsCreated = false;\n this.navigationHammers = [];\n this.boundFunctions = {};\n this.touchTime = 0;\n this.activated = false;\n\n this.body.emitter.on(\"activate\", function () {\n _this.activated = true;_this.configureKeyboardBindings();\n });\n this.body.emitter.on(\"deactivate\", function () {\n _this.activated = false;_this.configureKeyboardBindings();\n });\n this.body.emitter.on(\"destroy\", function () {\n if (_this.keycharm !== undefined) {\n _this.keycharm.destroy();\n }\n });\n\n this.options = {};\n }\n\n _createClass(NavigationHandler, [{\n key: 'setOptions',\n value: function setOptions(options) {\n if (options !== undefined) {\n this.options = options;\n this.create();\n }\n }\n }, {\n key: 'create',\n value: function create() {\n if (this.options.navigationButtons === true) {\n if (this.iconsCreated === false) {\n this.loadNavigationElements();\n }\n } else if (this.iconsCreated === true) {\n this.cleanNavigation();\n }\n\n this.configureKeyboardBindings();\n }\n }, {\n key: 'cleanNavigation',\n value: function cleanNavigation() {\n // clean hammer bindings\n if (this.navigationHammers.length != 0) {\n for (var i = 0; i < this.navigationHammers.length; i++) {\n this.navigationHammers[i].destroy();\n }\n this.navigationHammers = [];\n }\n\n // clean up previous navigation items\n if (this.navigationDOM && this.navigationDOM['wrapper'] && this.navigationDOM['wrapper'].parentNode) {\n this.navigationDOM['wrapper'].parentNode.removeChild(this.navigationDOM['wrapper']);\n }\n\n this.iconsCreated = false;\n }\n\n /**\n * Creation of the navigation controls nodes. They are drawn over the rest of the nodes and are not affected by scale and translation\n * they have a triggerFunction which is called on click. If the position of the navigation controls is dependent\n * on this.frame.canvas.clientWidth or this.frame.canvas.clientHeight, we flag horizontalAlignLeft and verticalAlignTop false.\n * This means that the location will be corrected by the _relocateNavigation function on a size change of the canvas.\n *\n * @private\n */\n }, {\n key: 'loadNavigationElements',\n value: function loadNavigationElements() {\n var _this2 = this;\n\n this.cleanNavigation();\n\n this.navigationDOM = {};\n var navigationDivs = ['up', 'down', 'left', 'right', 'zoomIn', 'zoomOut', 'zoomExtends'];\n var navigationDivActions = ['_moveUp', '_moveDown', '_moveLeft', '_moveRight', '_zoomIn', '_zoomOut', '_fit'];\n\n this.navigationDOM['wrapper'] = document.createElement('div');\n this.navigationDOM['wrapper'].className = 'vis-navigation';\n this.canvas.frame.appendChild(this.navigationDOM['wrapper']);\n\n for (var i = 0; i < navigationDivs.length; i++) {\n this.navigationDOM[navigationDivs[i]] = document.createElement('div');\n this.navigationDOM[navigationDivs[i]].className = 'vis-button vis-' + navigationDivs[i];\n this.navigationDOM['wrapper'].appendChild(this.navigationDOM[navigationDivs[i]]);\n\n var hammer = new Hammer(this.navigationDOM[navigationDivs[i]]);\n if (navigationDivActions[i] === \"_fit\") {\n hammerUtil.onTouch(hammer, this._fit.bind(this));\n } else {\n hammerUtil.onTouch(hammer, this.bindToRedraw.bind(this, navigationDivActions[i]));\n }\n\n this.navigationHammers.push(hammer);\n }\n\n // use a hammer for the release so we do not require the one used in the rest of the network\n // the one the rest uses can be overloaded by the manipulation system.\n var hammerFrame = new Hammer(this.canvas.frame);\n hammerUtil.onRelease(hammerFrame, function () {\n _this2._stopMovement();\n });\n this.navigationHammers.push(hammerFrame);\n\n this.iconsCreated = true;\n }\n }, {\n key: 'bindToRedraw',\n value: function bindToRedraw(action) {\n if (this.boundFunctions[action] === undefined) {\n this.boundFunctions[action] = this[action].bind(this);\n this.body.emitter.on(\"initRedraw\", this.boundFunctions[action]);\n this.body.emitter.emit(\"_startRendering\");\n }\n }\n }, {\n key: 'unbindFromRedraw',\n value: function unbindFromRedraw(action) {\n if (this.boundFunctions[action] !== undefined) {\n this.body.emitter.off(\"initRedraw\", this.boundFunctions[action]);\n this.body.emitter.emit(\"_stopRendering\");\n delete this.boundFunctions[action];\n }\n }\n\n /**\n * this stops all movement induced by the navigation buttons\n *\n * @private\n */\n }, {\n key: '_fit',\n value: function _fit() {\n if (new Date().valueOf() - this.touchTime > 700) {\n // TODO: fix ugly hack to avoid hammer's double fireing of event (because we use release?)\n this.body.emitter.emit(\"fit\", { duration: 700 });\n this.touchTime = new Date().valueOf();\n }\n }\n\n /**\n * this stops all movement induced by the navigation buttons\n *\n * @private\n */\n }, {\n key: '_stopMovement',\n value: function _stopMovement() {\n for (var boundAction in this.boundFunctions) {\n if (this.boundFunctions.hasOwnProperty(boundAction)) {\n this.body.emitter.off(\"initRedraw\", this.boundFunctions[boundAction]);\n this.body.emitter.emit(\"_stopRendering\");\n }\n }\n this.boundFunctions = {};\n }\n }, {\n key: '_moveUp',\n value: function _moveUp() {\n this.body.view.translation.y += this.options.keyboard.speed.y;\n }\n }, {\n key: '_moveDown',\n value: function _moveDown() {\n this.body.view.translation.y -= this.options.keyboard.speed.y;\n }\n }, {\n key: '_moveLeft',\n value: function _moveLeft() {\n this.body.view.translation.x += this.options.keyboard.speed.x;\n }\n }, {\n key: '_moveRight',\n value: function _moveRight() {\n this.body.view.translation.x -= this.options.keyboard.speed.x;\n }\n }, {\n key: '_zoomIn',\n value: function _zoomIn() {\n this.body.view.scale *= 1 + this.options.keyboard.speed.zoom;\n this.body.emitter.emit('zoom', { direction: '+', scale: this.body.view.scale });\n }\n }, {\n key: '_zoomOut',\n value: function _zoomOut() {\n this.body.view.scale /= 1 + this.options.keyboard.speed.zoom;\n this.body.emitter.emit('zoom', { direction: '-', scale: this.body.view.scale });\n }\n\n /**\n * bind all keys using keycharm.\n */\n }, {\n key: 'configureKeyboardBindings',\n value: function configureKeyboardBindings() {\n var _this3 = this;\n\n if (this.keycharm !== undefined) {\n this.keycharm.destroy();\n }\n\n if (this.options.keyboard.enabled === true) {\n if (this.options.keyboard.bindToWindow === true) {\n this.keycharm = keycharm({ container: window, preventDefault: true });\n } else {\n this.keycharm = keycharm({ container: this.canvas.frame, preventDefault: true });\n }\n\n this.keycharm.reset();\n\n if (this.activated === true) {\n this.keycharm.bind(\"up\", function () {\n _this3.bindToRedraw(\"_moveUp\");\n }, \"keydown\");\n this.keycharm.bind(\"down\", function () {\n _this3.bindToRedraw(\"_moveDown\");\n }, \"keydown\");\n this.keycharm.bind(\"left\", function () {\n _this3.bindToRedraw(\"_moveLeft\");\n }, \"keydown\");\n this.keycharm.bind(\"right\", function () {\n _this3.bindToRedraw(\"_moveRight\");\n }, \"keydown\");\n this.keycharm.bind(\"=\", function () {\n _this3.bindToRedraw(\"_zoomIn\");\n }, \"keydown\");\n this.keycharm.bind(\"num+\", function () {\n _this3.bindToRedraw(\"_zoomIn\");\n }, \"keydown\");\n this.keycharm.bind(\"num-\", function () {\n _this3.bindToRedraw(\"_zoomOut\");\n }, \"keydown\");\n this.keycharm.bind(\"-\", function () {\n _this3.bindToRedraw(\"_zoomOut\");\n }, \"keydown\");\n this.keycharm.bind(\"[\", function () {\n _this3.bindToRedraw(\"_zoomOut\");\n }, \"keydown\");\n this.keycharm.bind(\"]\", function () {\n _this3.bindToRedraw(\"_zoomIn\");\n }, \"keydown\");\n this.keycharm.bind(\"pageup\", function () {\n _this3.bindToRedraw(\"_zoomIn\");\n }, \"keydown\");\n this.keycharm.bind(\"pagedown\", function () {\n _this3.bindToRedraw(\"_zoomOut\");\n }, \"keydown\");\n\n this.keycharm.bind(\"up\", function () {\n _this3.unbindFromRedraw(\"_moveUp\");\n }, \"keyup\");\n this.keycharm.bind(\"down\", function () {\n _this3.unbindFromRedraw(\"_moveDown\");\n }, \"keyup\");\n this.keycharm.bind(\"left\", function () {\n _this3.unbindFromRedraw(\"_moveLeft\");\n }, \"keyup\");\n this.keycharm.bind(\"right\", function () {\n _this3.unbindFromRedraw(\"_moveRight\");\n }, \"keyup\");\n this.keycharm.bind(\"=\", function () {\n _this3.unbindFromRedraw(\"_zoomIn\");\n }, \"keyup\");\n this.keycharm.bind(\"num+\", function () {\n _this3.unbindFromRedraw(\"_zoomIn\");\n }, \"keyup\");\n this.keycharm.bind(\"num-\", function () {\n _this3.unbindFromRedraw(\"_zoomOut\");\n }, \"keyup\");\n this.keycharm.bind(\"-\", function () {\n _this3.unbindFromRedraw(\"_zoomOut\");\n }, \"keyup\");\n this.keycharm.bind(\"[\", function () {\n _this3.unbindFromRedraw(\"_zoomOut\");\n }, \"keyup\");\n this.keycharm.bind(\"]\", function () {\n _this3.unbindFromRedraw(\"_zoomIn\");\n }, \"keyup\");\n this.keycharm.bind(\"pageup\", function () {\n _this3.unbindFromRedraw(\"_zoomIn\");\n }, \"keyup\");\n this.keycharm.bind(\"pagedown\", function () {\n _this3.unbindFromRedraw(\"_zoomOut\");\n }, \"keyup\");\n }\n }\n }\n }]);\n\n return NavigationHandler;\n })();\n\n exports['default'] = NavigationHandler;\n module.exports = exports['default'];\n\n/***/ },\n/* 106 */\n/***/ function(module, exports) {\n\n /**\n * Popup is a class to create a popup window with some text\n * @param {Element} container The container object.\n * @param {Number} [x]\n * @param {Number} [y]\n * @param {String} [text]\n * @param {Object} [style] An object containing borderColor,\n * backgroundColor, etc.\n */\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var Popup = (function () {\n function Popup(container) {\n _classCallCheck(this, Popup);\n\n this.container = container;\n\n this.x = 0;\n this.y = 0;\n this.padding = 5;\n this.hidden = false;\n\n // create the frame\n this.frame = document.createElement('div');\n this.frame.className = 'vis-network-tooltip';\n this.container.appendChild(this.frame);\n }\n\n /**\n * @param {number} x Horizontal position of the popup window\n * @param {number} y Vertical position of the popup window\n */\n\n _createClass(Popup, [{\n key: 'setPosition',\n value: function setPosition(x, y) {\n this.x = parseInt(x);\n this.y = parseInt(y);\n }\n\n /**\n * Set the content for the popup window. This can be HTML code or text.\n * @param {string | Element} content\n */\n }, {\n key: 'setText',\n value: function setText(content) {\n if (content instanceof Element) {\n this.frame.innerHTML = '';\n this.frame.appendChild(content);\n } else {\n this.frame.innerHTML = content; // string containing text or HTML\n }\n }\n\n /**\n * Show the popup window\n * @param {boolean} [doShow] Show or hide the window\n */\n }, {\n key: 'show',\n value: function show(doShow) {\n if (doShow === undefined) {\n doShow = true;\n }\n\n if (doShow === true) {\n var height = this.frame.clientHeight;\n var width = this.frame.clientWidth;\n var maxHeight = this.frame.parentNode.clientHeight;\n var maxWidth = this.frame.parentNode.clientWidth;\n\n var top = this.y - height;\n if (top + height + this.padding > maxHeight) {\n top = maxHeight - height - this.padding;\n }\n if (top < this.padding) {\n top = this.padding;\n }\n\n var left = this.x;\n if (left + width + this.padding > maxWidth) {\n left = maxWidth - width - this.padding;\n }\n if (left < this.padding) {\n left = this.padding;\n }\n\n this.frame.style.left = left + \"px\";\n this.frame.style.top = top + \"px\";\n this.frame.style.visibility = \"visible\";\n this.hidden = false;\n } else {\n this.hide();\n }\n }\n\n /**\n * Hide the popup window\n */\n }, {\n key: 'hide',\n value: function hide() {\n this.hidden = true;\n this.frame.style.visibility = \"hidden\";\n }\n }]);\n\n return Popup;\n })();\n\n exports['default'] = Popup;\n module.exports = exports['default'];\n\n/***/ },\n/* 107 */\n/***/ function(module, exports, __webpack_require__) {\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var Node = __webpack_require__(61);\n var Edge = __webpack_require__(81);\n var util = __webpack_require__(1);\n\n var SelectionHandler = (function () {\n function SelectionHandler(body, canvas) {\n var _this = this;\n\n _classCallCheck(this, SelectionHandler);\n\n this.body = body;\n this.canvas = canvas;\n this.selectionObj = { nodes: [], edges: [] };\n this.hoverObj = { nodes: {}, edges: {} };\n\n this.options = {};\n this.defaultOptions = {\n multiselect: false,\n selectable: true,\n selectConnectedEdges: true,\n hoverConnectedEdges: true\n };\n util.extend(this.options, this.defaultOptions);\n\n this.body.emitter.on(\"_dataChanged\", function () {\n _this.updateSelection();\n });\n }\n\n _createClass(SelectionHandler, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n if (options !== undefined) {\n var fields = ['multiselect', 'hoverConnectedEdges', 'selectable', 'selectConnectedEdges'];\n util.selectiveDeepExtend(fields, this.options, options);\n }\n }\n\n /**\n * handles the selection part of the tap;\n *\n * @param {Object} pointer\n * @private\n */\n }, {\n key: \"selectOnPoint\",\n value: function selectOnPoint(pointer) {\n var selected = false;\n if (this.options.selectable === true) {\n var obj = this.getNodeAt(pointer) || this.getEdgeAt(pointer);\n\n // unselect after getting the objects in order to restore width and height.\n this.unselectAll();\n\n if (obj !== undefined) {\n selected = this.selectObject(obj);\n }\n this.body.emitter.emit(\"_requestRedraw\");\n }\n return selected;\n }\n }, {\n key: \"selectAdditionalOnPoint\",\n value: function selectAdditionalOnPoint(pointer) {\n var selectionChanged = false;\n if (this.options.selectable === true) {\n var obj = this.getNodeAt(pointer) || this.getEdgeAt(pointer);\n\n if (obj !== undefined) {\n selectionChanged = true;\n if (obj.isSelected() === true) {\n this.deselectObject(obj);\n } else {\n this.selectObject(obj);\n }\n\n this.body.emitter.emit(\"_requestRedraw\");\n }\n }\n return selectionChanged;\n }\n }, {\n key: \"_generateClickEvent\",\n value: function _generateClickEvent(eventType, event, pointer, oldSelection) {\n var emptySelection = arguments.length <= 4 || arguments[4] === undefined ? false : arguments[4];\n\n var properties = undefined;\n if (emptySelection === true) {\n properties = { nodes: [], edges: [] };\n } else {\n properties = this.getSelection();\n }\n properties['pointer'] = {\n DOM: { x: pointer.x, y: pointer.y },\n canvas: this.canvas.DOMtoCanvas(pointer)\n };\n properties['event'] = event;\n\n if (oldSelection !== undefined) {\n properties['previousSelection'] = oldSelection;\n }\n this.body.emitter.emit(eventType, properties);\n }\n }, {\n key: \"selectObject\",\n value: function selectObject(obj) {\n var highlightEdges = arguments.length <= 1 || arguments[1] === undefined ? this.options.selectConnectedEdges : arguments[1];\n\n if (obj !== undefined) {\n if (obj instanceof Node) {\n if (highlightEdges === true) {\n this._selectConnectedEdges(obj);\n }\n }\n obj.select();\n this._addToSelection(obj);\n return true;\n }\n return false;\n }\n }, {\n key: \"deselectObject\",\n value: function deselectObject(obj) {\n if (obj.isSelected() === true) {\n obj.selected = false;\n this._removeFromSelection(obj);\n }\n }\n\n /**\n * retrieve all nodes overlapping with given object\n * @param {Object} object An object with parameters left, top, right, bottom\n * @return {Number[]} An array with id's of the overlapping nodes\n * @private\n */\n }, {\n key: \"_getAllNodesOverlappingWith\",\n value: function _getAllNodesOverlappingWith(object) {\n var overlappingNodes = [];\n var nodes = this.body.nodes;\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var nodeId = this.body.nodeIndices[i];\n if (nodes[nodeId].isOverlappingWith(object)) {\n overlappingNodes.push(nodeId);\n }\n }\n return overlappingNodes;\n }\n\n /**\n * Return a position object in canvasspace from a single point in screenspace\n *\n * @param pointer\n * @returns {{left: number, top: number, right: number, bottom: number}}\n * @private\n */\n }, {\n key: \"_pointerToPositionObject\",\n value: function _pointerToPositionObject(pointer) {\n var canvasPos = this.canvas.DOMtoCanvas(pointer);\n return {\n left: canvasPos.x - 1,\n top: canvasPos.y + 1,\n right: canvasPos.x + 1,\n bottom: canvasPos.y - 1\n };\n }\n\n /**\n * Get the top node at the a specific point (like a click)\n *\n * @param {{x: Number, y: Number}} pointer\n * @return {Node | undefined} node\n */\n }, {\n key: \"getNodeAt\",\n value: function getNodeAt(pointer) {\n var returnNode = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n // we first check if this is an navigation controls element\n var positionObject = this._pointerToPositionObject(pointer);\n var overlappingNodes = this._getAllNodesOverlappingWith(positionObject);\n // if there are overlapping nodes, select the last one, this is the\n // one which is drawn on top of the others\n if (overlappingNodes.length > 0) {\n if (returnNode === true) {\n return this.body.nodes[overlappingNodes[overlappingNodes.length - 1]];\n } else {\n return overlappingNodes[overlappingNodes.length - 1];\n }\n } else {\n return undefined;\n }\n }\n\n /**\n * retrieve all edges overlapping with given object, selector is around center\n * @param {Object} object An object with parameters left, top, right, bottom\n * @return {Number[]} An array with id's of the overlapping nodes\n * @private\n */\n }, {\n key: \"_getEdgesOverlappingWith\",\n value: function _getEdgesOverlappingWith(object, overlappingEdges) {\n var edges = this.body.edges;\n for (var i = 0; i < this.body.edgeIndices.length; i++) {\n var edgeId = this.body.edgeIndices[i];\n if (edges[edgeId].isOverlappingWith(object)) {\n overlappingEdges.push(edgeId);\n }\n }\n }\n\n /**\n * retrieve all nodes overlapping with given object\n * @param {Object} object An object with parameters left, top, right, bottom\n * @return {Number[]} An array with id's of the overlapping nodes\n * @private\n */\n }, {\n key: \"_getAllEdgesOverlappingWith\",\n value: function _getAllEdgesOverlappingWith(object) {\n var overlappingEdges = [];\n this._getEdgesOverlappingWith(object, overlappingEdges);\n return overlappingEdges;\n }\n\n /**\n * Place holder. To implement change the getNodeAt to a _getObjectAt. Have the _getObjectAt call\n * getNodeAt and _getEdgesAt, then priortize the selection to user preferences.\n *\n * @param pointer\n * @returns {undefined}\n */\n }, {\n key: \"getEdgeAt\",\n value: function getEdgeAt(pointer) {\n var returnEdge = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n var positionObject = this._pointerToPositionObject(pointer);\n var overlappingEdges = this._getAllEdgesOverlappingWith(positionObject);\n\n if (overlappingEdges.length > 0) {\n if (returnEdge === true) {\n return this.body.edges[overlappingEdges[overlappingEdges.length - 1]];\n } else {\n return overlappingEdges[overlappingEdges.length - 1];\n }\n } else {\n return undefined;\n }\n }\n\n /**\n * Add object to the selection array.\n *\n * @param obj\n * @private\n */\n }, {\n key: \"_addToSelection\",\n value: function _addToSelection(obj) {\n if (obj instanceof Node) {\n this.selectionObj.nodes[obj.id] = obj;\n } else {\n this.selectionObj.edges[obj.id] = obj;\n }\n }\n\n /**\n * Add object to the selection array.\n *\n * @param obj\n * @private\n */\n }, {\n key: \"_addToHover\",\n value: function _addToHover(obj) {\n if (obj instanceof Node) {\n this.hoverObj.nodes[obj.id] = obj;\n } else {\n this.hoverObj.edges[obj.id] = obj;\n }\n }\n\n /**\n * Remove a single option from selection.\n *\n * @param {Object} obj\n * @private\n */\n }, {\n key: \"_removeFromSelection\",\n value: function _removeFromSelection(obj) {\n if (obj instanceof Node) {\n delete this.selectionObj.nodes[obj.id];\n this._unselectConnectedEdges(obj);\n } else {\n delete this.selectionObj.edges[obj.id];\n }\n }\n\n /**\n * Unselect all. The selectionObj is useful for this.\n */\n }, {\n key: \"unselectAll\",\n value: function unselectAll() {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n this.selectionObj.nodes[nodeId].unselect();\n }\n }\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n this.selectionObj.edges[edgeId].unselect();\n }\n }\n\n this.selectionObj = { nodes: {}, edges: {} };\n }\n\n /**\n * return the number of selected nodes\n *\n * @returns {number}\n * @private\n */\n }, {\n key: \"_getSelectedNodeCount\",\n value: function _getSelectedNodeCount() {\n var count = 0;\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n count += 1;\n }\n }\n return count;\n }\n\n /**\n * return the selected node\n *\n * @returns {number}\n * @private\n */\n }, {\n key: \"_getSelectedNode\",\n value: function _getSelectedNode() {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n return this.selectionObj.nodes[nodeId];\n }\n }\n return undefined;\n }\n\n /**\n * return the selected edge\n *\n * @returns {number}\n * @private\n */\n }, {\n key: \"_getSelectedEdge\",\n value: function _getSelectedEdge() {\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n return this.selectionObj.edges[edgeId];\n }\n }\n return undefined;\n }\n\n /**\n * return the number of selected edges\n *\n * @returns {number}\n * @private\n */\n }, {\n key: \"_getSelectedEdgeCount\",\n value: function _getSelectedEdgeCount() {\n var count = 0;\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n count += 1;\n }\n }\n return count;\n }\n\n /**\n * return the number of selected objects.\n *\n * @returns {number}\n * @private\n */\n }, {\n key: \"_getSelectedObjectCount\",\n value: function _getSelectedObjectCount() {\n var count = 0;\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n count += 1;\n }\n }\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n count += 1;\n }\n }\n return count;\n }\n\n /**\n * Check if anything is selected\n *\n * @returns {boolean}\n * @private\n */\n }, {\n key: \"_selectionIsEmpty\",\n value: function _selectionIsEmpty() {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n return false;\n }\n }\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n return false;\n }\n }\n return true;\n }\n\n /**\n * check if one of the selected nodes is a cluster.\n *\n * @returns {boolean}\n * @private\n */\n }, {\n key: \"_clusterInSelection\",\n value: function _clusterInSelection() {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n if (this.selectionObj.nodes[nodeId].clusterSize > 1) {\n return true;\n }\n }\n }\n return false;\n }\n\n /**\n * select the edges connected to the node that is being selected\n *\n * @param {Node} node\n * @private\n */\n }, {\n key: \"_selectConnectedEdges\",\n value: function _selectConnectedEdges(node) {\n for (var i = 0; i < node.edges.length; i++) {\n var edge = node.edges[i];\n edge.select();\n this._addToSelection(edge);\n }\n }\n\n /**\n * select the edges connected to the node that is being selected\n *\n * @param {Node} node\n * @private\n */\n }, {\n key: \"_hoverConnectedEdges\",\n value: function _hoverConnectedEdges(node) {\n for (var i = 0; i < node.edges.length; i++) {\n var edge = node.edges[i];\n edge.hover = true;\n this._addToHover(edge);\n }\n }\n\n /**\n * unselect the edges connected to the node that is being selected\n *\n * @param {Node} node\n * @private\n */\n }, {\n key: \"_unselectConnectedEdges\",\n value: function _unselectConnectedEdges(node) {\n for (var i = 0; i < node.edges.length; i++) {\n var edge = node.edges[i];\n edge.unselect();\n this._removeFromSelection(edge);\n }\n }\n\n /**\n * This is called when someone clicks on a node. either select or deselect it.\n * If there is an existing selection and we don't want to append to it, clear the existing selection\n *\n * @param {Node || Edge} object\n * @private\n */\n }, {\n key: \"blurObject\",\n value: function blurObject(object) {\n if (object.hover === true) {\n object.hover = false;\n if (object instanceof Node) {\n this.body.emitter.emit(\"blurNode\", { node: object.id });\n } else {\n this.body.emitter.emit(\"blurEdge\", { edge: object.id });\n }\n }\n }\n\n /**\n * This is called when someone clicks on a node. either select or deselect it.\n * If there is an existing selection and we don't want to append to it, clear the existing selection\n *\n * @param {Node || Edge} object\n * @private\n */\n }, {\n key: \"hoverObject\",\n value: function hoverObject(object) {\n var hoverChanged = false;\n // remove all node hover highlights\n for (var nodeId in this.hoverObj.nodes) {\n if (this.hoverObj.nodes.hasOwnProperty(nodeId)) {\n if (object === undefined || object instanceof Node && object.id != nodeId || object instanceof Edge) {\n this.blurObject(this.hoverObj.nodes[nodeId]);\n delete this.hoverObj.nodes[nodeId];\n hoverChanged = true;\n }\n }\n }\n\n // removing all edge hover highlights\n for (var edgeId in this.hoverObj.edges) {\n if (this.hoverObj.edges.hasOwnProperty(edgeId)) {\n // if the hover has been changed here it means that the node has been hovered over or off\n // we then do not use the blurObject method here.\n if (hoverChanged === true) {\n this.hoverObj.edges[edgeId].hover = false;\n delete this.hoverObj.edges[edgeId];\n }\n // if the blur remains the same and the object is undefined (mouse off), we blur the edge\n else if (object === undefined) {\n this.blurObject(this.hoverObj.edges[edgeId]);\n delete this.hoverObj.edges[edgeId];\n hoverChanged = true;\n }\n }\n }\n\n if (object !== undefined) {\n if (object.hover === false) {\n object.hover = true;\n this._addToHover(object);\n hoverChanged = true;\n if (object instanceof Node) {\n this.body.emitter.emit(\"hoverNode\", { node: object.id });\n } else {\n this.body.emitter.emit(\"hoverEdge\", { edge: object.id });\n }\n }\n if (object instanceof Node && this.options.hoverConnectedEdges === true) {\n this._hoverConnectedEdges(object);\n }\n }\n\n if (hoverChanged === true) {\n this.body.emitter.emit('_requestRedraw');\n }\n }\n\n /**\n *\n * retrieve the currently selected objects\n * @return {{nodes: Array.<String>, edges: Array.<String>}} selection\n */\n }, {\n key: \"getSelection\",\n value: function getSelection() {\n var nodeIds = this.getSelectedNodes();\n var edgeIds = this.getSelectedEdges();\n return { nodes: nodeIds, edges: edgeIds };\n }\n\n /**\n *\n * retrieve the currently selected nodes\n * @return {String[]} selection An array with the ids of the\n * selected nodes.\n */\n }, {\n key: \"getSelectedNodes\",\n value: function getSelectedNodes() {\n var idArray = [];\n if (this.options.selectable === true) {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n idArray.push(this.selectionObj.nodes[nodeId].id);\n }\n }\n }\n return idArray;\n }\n\n /**\n *\n * retrieve the currently selected edges\n * @return {Array} selection An array with the ids of the\n * selected nodes.\n */\n }, {\n key: \"getSelectedEdges\",\n value: function getSelectedEdges() {\n var idArray = [];\n if (this.options.selectable === true) {\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n idArray.push(this.selectionObj.edges[edgeId].id);\n }\n }\n }\n return idArray;\n }\n\n /**\n * Updates the current selection\n * @param {{nodes: Array.<String>, edges: Array.<String>}} Selection\n * @param {Object} options Options\n */\n }, {\n key: \"setSelection\",\n value: function setSelection(selection) {\n var options = arguments.length <= 1 || arguments[1] === undefined ? {} : arguments[1];\n\n var i = undefined,\n id = undefined;\n\n if (!selection || !selection.nodes && !selection.edges) throw 'Selection must be an object with nodes and/or edges properties';\n // first unselect any selected node, if option is true or undefined\n if (options.unselectAll || options.unselectAll === undefined) {\n this.unselectAll();\n }\n if (selection.nodes) {\n for (i = 0; i < selection.nodes.length; i++) {\n id = selection.nodes[i];\n\n var node = this.body.nodes[id];\n if (!node) {\n throw new RangeError('Node with id \"' + id + '\" not found');\n }\n // don't select edges with it\n this.selectObject(node, options.highlightEdges);\n }\n }\n\n if (selection.edges) {\n for (i = 0; i < selection.edges.length; i++) {\n id = selection.edges[i];\n\n var edge = this.body.edges[id];\n if (!edge) {\n throw new RangeError('Edge with id \"' + id + '\" not found');\n }\n this.selectObject(edge);\n }\n }\n this.body.emitter.emit('_requestRedraw');\n }\n\n /**\n * select zero or more nodes with the option to highlight edges\n * @param {Number[] | String[]} selection An array with the ids of the\n * selected nodes.\n * @param {boolean} [highlightEdges]\n */\n }, {\n key: \"selectNodes\",\n value: function selectNodes(selection) {\n var highlightEdges = arguments.length <= 1 || arguments[1] === undefined ? true : arguments[1];\n\n if (!selection || selection.length === undefined) throw 'Selection must be an array with ids';\n\n this.setSelection({ nodes: selection }, { highlightEdges: highlightEdges });\n }\n\n /**\n * select zero or more edges\n * @param {Number[] | String[]} selection An array with the ids of the\n * selected nodes.\n */\n }, {\n key: \"selectEdges\",\n value: function selectEdges(selection) {\n if (!selection || selection.length === undefined) throw 'Selection must be an array with ids';\n\n this.setSelection({ edges: selection });\n }\n\n /**\n * Validate the selection: remove ids of nodes which no longer exist\n * @private\n */\n }, {\n key: \"updateSelection\",\n value: function updateSelection() {\n for (var nodeId in this.selectionObj.nodes) {\n if (this.selectionObj.nodes.hasOwnProperty(nodeId)) {\n if (!this.body.nodes.hasOwnProperty(nodeId)) {\n delete this.selectionObj.nodes[nodeId];\n }\n }\n }\n for (var edgeId in this.selectionObj.edges) {\n if (this.selectionObj.edges.hasOwnProperty(edgeId)) {\n if (!this.body.edges.hasOwnProperty(edgeId)) {\n delete this.selectionObj.edges[edgeId];\n }\n }\n }\n }\n }]);\n\n return SelectionHandler;\n })();\n\n exports[\"default\"] = SelectionHandler;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 108 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _slicedToArray = (function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i['return']) _i['return'](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError('Invalid attempt to destructure non-iterable instance'); } }; })();\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { 'default': obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var _NetworkUtil = __webpack_require__(99);\n\n var _NetworkUtil2 = _interopRequireDefault(_NetworkUtil);\n\n var util = __webpack_require__(1);\n\n var LayoutEngine = (function () {\n function LayoutEngine(body) {\n _classCallCheck(this, LayoutEngine);\n\n this.body = body;\n\n this.initialRandomSeed = Math.round(Math.random() * 1000000);\n this.randomSeed = this.initialRandomSeed;\n this.setPhysics = false;\n this.options = {};\n this.optionsBackup = { physics: {} };\n\n this.defaultOptions = {\n randomSeed: undefined,\n improvedLayout: true,\n hierarchical: {\n enabled: false,\n levelSeparation: 150,\n nodeSpacing: 100,\n treeSpacing: 200,\n blockShifting: true,\n edgeMinimization: true,\n direction: 'UD', // UD, DU, LR, RL\n sortMethod: 'hubsize' // hubsize, directed\n }\n };\n util.extend(this.options, this.defaultOptions);\n this.bindEventListeners();\n }\n\n _createClass(LayoutEngine, [{\n key: 'bindEventListeners',\n value: function bindEventListeners() {\n var _this = this;\n\n this.body.emitter.on('_dataChanged', function () {\n _this.setupHierarchicalLayout();\n });\n this.body.emitter.on('_dataLoaded', function () {\n _this.layoutNetwork();\n });\n this.body.emitter.on('_resetHierarchicalLayout', function () {\n _this.setupHierarchicalLayout();\n });\n }\n }, {\n key: 'setOptions',\n value: function setOptions(options, allOptions) {\n if (options !== undefined) {\n var prevHierarchicalState = this.options.hierarchical.enabled;\n util.selectiveDeepExtend([\"randomSeed\", \"improvedLayout\"], this.options, options);\n util.mergeOptions(this.options, options, 'hierarchical');\n if (options.randomSeed !== undefined) {\n this.initialRandomSeed = options.randomSeed;\n }\n\n if (this.options.hierarchical.enabled === true) {\n if (prevHierarchicalState === true) {\n // refresh the overridden options for nodes and edges.\n this.body.emitter.emit('refresh', true);\n }\n\n // make sure the level separation is the right way up\n if (this.options.hierarchical.direction === 'RL' || this.options.hierarchical.direction === 'DU') {\n if (this.options.hierarchical.levelSeparation > 0) {\n this.options.hierarchical.levelSeparation *= -1;\n }\n } else {\n if (this.options.hierarchical.levelSeparation < 0) {\n this.options.hierarchical.levelSeparation *= -1;\n }\n }\n\n this.body.emitter.emit('_resetHierarchicalLayout');\n // because the hierarchical system needs it's own physics and smooth curve settings, we adapt the other options if needed.\n return this.adaptAllOptionsForHierarchicalLayout(allOptions);\n } else {\n if (prevHierarchicalState === true) {\n // refresh the overridden options for nodes and edges.\n this.body.emitter.emit('refresh');\n return util.deepExtend(allOptions, this.optionsBackup);\n }\n }\n }\n return allOptions;\n }\n }, {\n key: 'adaptAllOptionsForHierarchicalLayout',\n value: function adaptAllOptionsForHierarchicalLayout(allOptions) {\n if (this.options.hierarchical.enabled === true) {\n // set the physics\n if (allOptions.physics === undefined || allOptions.physics === true) {\n allOptions.physics = {\n enabled: this.optionsBackup.physics.enabled === undefined ? true : this.optionsBackup.physics.enabled,\n solver: 'hierarchicalRepulsion'\n };\n this.optionsBackup.physics.enabled = this.optionsBackup.physics.enabled === undefined ? true : this.optionsBackup.physics.enabled;\n this.optionsBackup.physics.solver = this.optionsBackup.physics.solver || 'barnesHut';\n } else if (typeof allOptions.physics === 'object') {\n this.optionsBackup.physics.enabled = allOptions.physics.enabled === undefined ? true : allOptions.physics.enabled;\n this.optionsBackup.physics.solver = allOptions.physics.solver || 'barnesHut';\n allOptions.physics.solver = 'hierarchicalRepulsion';\n } else if (allOptions.physics !== false) {\n this.optionsBackup.physics.solver = 'barnesHut';\n allOptions.physics = { solver: 'hierarchicalRepulsion' };\n }\n\n // get the type of static smooth curve in case it is required\n var type = 'horizontal';\n if (this.options.hierarchical.direction === 'RL' || this.options.hierarchical.direction === 'LR') {\n type = 'vertical';\n }\n\n // disable smooth curves if nothing is defined. If smooth curves have been turned on, turn them into static smooth curves.\n if (allOptions.edges === undefined) {\n this.optionsBackup.edges = { smooth: { enabled: true, type: 'dynamic' } };\n allOptions.edges = { smooth: false };\n } else if (allOptions.edges.smooth === undefined) {\n this.optionsBackup.edges = { smooth: { enabled: true, type: 'dynamic' } };\n allOptions.edges.smooth = false;\n } else {\n if (typeof allOptions.edges.smooth === 'boolean') {\n this.optionsBackup.edges = { smooth: allOptions.edges.smooth };\n allOptions.edges.smooth = { enabled: allOptions.edges.smooth, type: type };\n } else {\n // allow custom types except for dynamic\n if (allOptions.edges.smooth.type !== undefined && allOptions.edges.smooth.type !== 'dynamic') {\n type = allOptions.edges.smooth.type;\n }\n\n this.optionsBackup.edges = {\n smooth: allOptions.edges.smooth.enabled === undefined ? true : allOptions.edges.smooth.enabled,\n type: allOptions.edges.smooth.type === undefined ? 'dynamic' : allOptions.edges.smooth.type,\n roundness: allOptions.edges.smooth.roundness === undefined ? 0.5 : allOptions.edges.smooth.roundness,\n forceDirection: allOptions.edges.smooth.forceDirection === undefined ? false : allOptions.edges.smooth.forceDirection\n };\n allOptions.edges.smooth = {\n enabled: allOptions.edges.smooth.enabled === undefined ? true : allOptions.edges.smooth.enabled,\n type: type,\n roundness: allOptions.edges.smooth.roundness === undefined ? 0.5 : allOptions.edges.smooth.roundness,\n forceDirection: allOptions.edges.smooth.forceDirection === undefined ? false : allOptions.edges.smooth.forceDirection\n };\n }\n }\n\n // force all edges into static smooth curves. Only applies to edges that do not use the global options for smooth.\n this.body.emitter.emit('_forceDisableDynamicCurves', type);\n }\n\n return allOptions;\n }\n }, {\n key: 'seededRandom',\n value: function seededRandom() {\n var x = Math.sin(this.randomSeed++) * 10000;\n return x - Math.floor(x);\n }\n }, {\n key: 'positionInitially',\n value: function positionInitially(nodesArray) {\n if (this.options.hierarchical.enabled !== true) {\n this.randomSeed = this.initialRandomSeed;\n for (var i = 0; i < nodesArray.length; i++) {\n var node = nodesArray[i];\n var radius = 10 * 0.1 * nodesArray.length + 10;\n var angle = 2 * Math.PI * this.seededRandom();\n if (node.x === undefined) {\n node.x = radius * Math.cos(angle);\n }\n if (node.y === undefined) {\n node.y = radius * Math.sin(angle);\n }\n }\n }\n }\n\n /**\n * Use Kamada Kawai to position nodes. This is quite a heavy algorithm so if there are a lot of nodes we\n * cluster them first to reduce the amount.\n */\n }, {\n key: 'layoutNetwork',\n value: function layoutNetwork() {\n if (this.options.hierarchical.enabled !== true && this.options.improvedLayout === true) {\n // first check if we should Kamada Kawai to layout. The threshold is if less than half of the visible\n // nodes have predefined positions we use this.\n var positionDefined = 0;\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var node = this.body.nodes[this.body.nodeIndices[i]];\n if (node.predefinedPosition === true) {\n positionDefined += 1;\n }\n }\n\n // if less than half of the nodes have a predefined position we continue\n if (positionDefined < 0.5 * this.body.nodeIndices.length) {\n var MAX_LEVELS = 10;\n var level = 0;\n var clusterThreshold = 100;\n // if there are a lot of nodes, we cluster before we run the algorithm.\n if (this.body.nodeIndices.length > clusterThreshold) {\n var startLength = this.body.nodeIndices.length;\n while (this.body.nodeIndices.length > clusterThreshold) {\n //console.time(\"clustering\")\n level += 1;\n var before = this.body.nodeIndices.length;\n // if there are many nodes we do a hubsize cluster\n if (level % 3 === 0) {\n this.body.modules.clustering.clusterBridges();\n } else {\n this.body.modules.clustering.clusterOutliers();\n }\n var after = this.body.nodeIndices.length;\n if (before == after && level % 3 !== 0 || level > MAX_LEVELS) {\n this._declusterAll();\n this.body.emitter.emit(\"_layoutFailed\");\n console.info(\"This network could not be positioned by this version of the improved layout algorithm. Please disable improvedLayout for better performance.\");\n return;\n }\n //console.timeEnd(\"clustering\")\n //console.log(level,after)\n }\n // increase the size of the edges\n this.body.modules.kamadaKawai.setOptions({ springLength: Math.max(150, 2 * startLength) });\n }\n\n // position the system for these nodes and edges\n this.body.modules.kamadaKawai.solve(this.body.nodeIndices, this.body.edgeIndices, true);\n\n // shift to center point\n this._shiftToCenter();\n\n // perturb the nodes a little bit to force the physics to kick in\n var offset = 70;\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n this.body.nodes[this.body.nodeIndices[i]].x += (0.5 - this.seededRandom()) * offset;\n this.body.nodes[this.body.nodeIndices[i]].y += (0.5 - this.seededRandom()) * offset;\n }\n\n // uncluster all clusters\n this._declusterAll();\n\n // reposition all bezier nodes.\n this.body.emitter.emit(\"_repositionBezierNodes\");\n }\n }\n }\n\n /**\n * Move all the nodes towards to the center so gravitational pull wil not move the nodes away from view\n * @private\n */\n }, {\n key: '_shiftToCenter',\n value: function _shiftToCenter() {\n var range = _NetworkUtil2['default'].getRangeCore(this.body.nodes, this.body.nodeIndices);\n var center = _NetworkUtil2['default'].findCenter(range);\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n this.body.nodes[this.body.nodeIndices[i]].x -= center.x;\n this.body.nodes[this.body.nodeIndices[i]].y -= center.y;\n }\n }\n }, {\n key: '_declusterAll',\n value: function _declusterAll() {\n var clustersPresent = true;\n while (clustersPresent === true) {\n clustersPresent = false;\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n if (this.body.nodes[this.body.nodeIndices[i]].isCluster === true) {\n clustersPresent = true;\n this.body.modules.clustering.openCluster(this.body.nodeIndices[i], {}, false);\n }\n }\n if (clustersPresent === true) {\n this.body.emitter.emit('_dataChanged');\n }\n }\n }\n }, {\n key: 'getSeed',\n value: function getSeed() {\n return this.initialRandomSeed;\n }\n\n /**\n * This is the main function to layout the nodes in a hierarchical way.\n * It checks if the node details are supplied correctly\n *\n * @private\n */\n }, {\n key: 'setupHierarchicalLayout',\n value: function setupHierarchicalLayout() {\n if (this.options.hierarchical.enabled === true && this.body.nodeIndices.length > 0) {\n // get the size of the largest hubs and check if the user has defined a level for a node.\n var node = undefined,\n nodeId = undefined;\n var definedLevel = false;\n var definedPositions = true;\n var undefinedLevel = false;\n this.hierarchicalLevels = {};\n this.lastNodeOnLevel = {};\n this.hierarchicalParents = {};\n this.hierarchicalChildren = {};\n this.hierarchicalTrees = {};\n this.treeIndex = -1;\n\n this.distributionOrdering = {};\n this.distributionIndex = {};\n this.distributionOrderingPresence = {};\n\n for (nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n node = this.body.nodes[nodeId];\n if (node.options.x === undefined && node.options.y === undefined) {\n definedPositions = false;\n }\n if (node.options.level !== undefined) {\n definedLevel = true;\n this.hierarchicalLevels[nodeId] = node.options.level;\n } else {\n undefinedLevel = true;\n }\n }\n }\n\n // if the user defined some levels but not all, alert and run without hierarchical layout\n if (undefinedLevel === true && definedLevel === true) {\n throw new Error('To use the hierarchical layout, nodes require either no predefined levels or levels have to be defined for all nodes.');\n return;\n } else {\n // define levels if undefined by the users. Based on hubsize.\n if (undefinedLevel === true) {\n if (this.options.hierarchical.sortMethod === 'hubsize') {\n this._determineLevelsByHubsize();\n } else if (this.options.hierarchical.sortMethod === 'directed') {\n this._determineLevelsDirected();\n } else if (this.options.hierarchical.sortMethod === 'custom') {\n this._determineLevelsCustomCallback();\n }\n }\n\n // fallback for cases where there are nodes but no edges\n for (var _nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(_nodeId)) {\n if (this.hierarchicalLevels[_nodeId] === undefined) {\n this.hierarchicalLevels[_nodeId] = 0;\n }\n }\n }\n // check the distribution of the nodes per level.\n var distribution = this._getDistribution();\n\n // get the parent children relations.\n this._generateMap();\n\n // place the nodes on the canvas.\n this._placeNodesByHierarchy(distribution);\n\n // condense the whitespace.\n this._condenseHierarchy();\n\n // shift to center so gravity does not have to do much\n this._shiftToCenter();\n }\n }\n }\n\n /**\n * @private\n */\n }, {\n key: '_condenseHierarchy',\n value: function _condenseHierarchy() {\n var _this2 = this;\n\n // Global var in this scope to define when the movement has stopped.\n var stillShifting = false;\n var branches = {};\n // first we have some methods to help shifting trees around.\n // the main method to shift the trees\n var shiftTrees = function shiftTrees() {\n var treeSizes = getTreeSizes();\n for (var i = 0; i < treeSizes.length - 1; i++) {\n var diff = treeSizes[i].max - treeSizes[i + 1].min;\n if (diff !== _this2.options.hierarchical.treeSpacing) {\n shiftTree(i + 1, diff - _this2.options.hierarchical.treeSpacing);\n }\n }\n };\n\n // shift a single tree by an offset\n var shiftTree = function shiftTree(index, offset) {\n for (var nodeId in _this2.hierarchicalTrees) {\n if (_this2.hierarchicalTrees.hasOwnProperty(nodeId)) {\n if (_this2.hierarchicalTrees[nodeId] === index) {\n _this2._setPositionForHierarchy(_this2.body.nodes[nodeId], offset, undefined, true);\n }\n }\n }\n };\n\n // get the width of a tree\n var getTreeSize = function getTreeSize(index) {\n var min = 1e9;\n var max = -1e9;\n for (var nodeId in _this2.hierarchicalTrees) {\n if (_this2.hierarchicalTrees.hasOwnProperty(nodeId)) {\n if (_this2.hierarchicalTrees[nodeId] === index) {\n var pos = _this2._getPositionForHierarchy(_this2.body.nodes[nodeId]);\n min = Math.min(pos, min);\n max = Math.max(pos, max);\n }\n }\n }\n return { min: min, max: max };\n };\n\n // get the width of all trees\n var getTreeSizes = function getTreeSizes() {\n var treeWidths = [];\n for (var i = 0; i < _this2.treeIndex; i++) {\n treeWidths.push(getTreeSize(i));\n }\n return treeWidths;\n };\n\n // get a map of all nodes in this branch\n var getBranchNodes = function getBranchNodes(source, map) {\n map[source.id] = true;\n if (_this2.hierarchicalParents[source.id]) {\n var children = _this2.hierarchicalParents[source.id].children;\n if (children.length > 0) {\n for (var i = 0; i < children.length; i++) {\n getBranchNodes(_this2.body.nodes[children[i]], map);\n }\n }\n }\n };\n\n // get a min max width as well as the maximum movement space it has on either sides\n // we use min max terminology because width and height can interchange depending on the direction of the layout\n var getBranchBoundary = function getBranchBoundary(branchMap) {\n var maxLevel = arguments.length <= 1 || arguments[1] === undefined ? 1e9 : arguments[1];\n\n var minSpace = 1e9;\n var maxSpace = 1e9;\n var min = 1e9;\n var max = -1e9;\n for (var branchNode in branchMap) {\n if (branchMap.hasOwnProperty(branchNode)) {\n var node = _this2.body.nodes[branchNode];\n var level = _this2.hierarchicalLevels[node.id];\n var position = _this2._getPositionForHierarchy(node);\n\n // get the space around the node.\n\n var _getSpaceAroundNode2 = _this2._getSpaceAroundNode(node, branchMap);\n\n var _getSpaceAroundNode22 = _slicedToArray(_getSpaceAroundNode2, 2);\n\n var minSpaceNode = _getSpaceAroundNode22[0];\n var maxSpaceNode = _getSpaceAroundNode22[1];\n\n minSpace = Math.min(minSpaceNode, minSpace);\n maxSpace = Math.min(maxSpaceNode, maxSpace);\n\n // the width is only relevant for the levels two nodes have in common. This is why we filter on this.\n if (level <= maxLevel) {\n min = Math.min(position, min);\n max = Math.max(position, max);\n }\n }\n }\n\n return [min, max, minSpace, maxSpace];\n };\n\n // get the maximum level of a branch.\n var getMaxLevel = function getMaxLevel(nodeId) {\n var level = _this2.hierarchicalLevels[nodeId];\n if (_this2.hierarchicalParents[nodeId]) {\n var children = _this2.hierarchicalParents[nodeId].children;\n if (children.length > 0) {\n for (var i = 0; i < children.length; i++) {\n level = Math.max(level, getMaxLevel(children[i]));\n }\n }\n }\n return level;\n };\n\n // check what the maximum level is these nodes have in common.\n var getCollisionLevel = function getCollisionLevel(node1, node2) {\n var maxLevel1 = getMaxLevel(node1.id);\n var maxLevel2 = getMaxLevel(node2.id);\n return Math.min(maxLevel1, maxLevel2);\n };\n\n // check if two nodes have the same parent(s)\n var hasSameParent = function hasSameParent(node1, node2) {\n var parents1 = _this2.hierarchicalChildren[node1.id];\n var parents2 = _this2.hierarchicalChildren[node2.id];\n if (parents1 === undefined || parents2 === undefined) {\n return false;\n }\n parents1 = parents1.parents;\n parents2 = parents2.parents;\n for (var i = 0; i < parents1.length; i++) {\n for (var j = 0; j < parents2.length; j++) {\n if (parents1[i] == parents2[j]) {\n return true;\n }\n }\n }\n return false;\n };\n\n // condense elements. These can be nodes or branches depending on the callback.\n var shiftElementsCloser = function shiftElementsCloser(callback, levels, centerParents) {\n for (var i = 0; i < levels.length; i++) {\n var level = levels[i];\n var levelNodes = _this2.distributionOrdering[level];\n if (levelNodes.length > 1) {\n for (var j = 0; j < levelNodes.length - 1; j++) {\n if (hasSameParent(levelNodes[j], levelNodes[j + 1]) === true) {\n if (_this2.hierarchicalTrees[levelNodes[j].id] === _this2.hierarchicalTrees[levelNodes[j + 1].id]) {\n callback(levelNodes[j], levelNodes[j + 1], centerParents);\n }\n }\n }\n }\n }\n };\n\n // callback for shifting branches\n var branchShiftCallback = function branchShiftCallback(node1, node2) {\n var centerParent = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n //window.CALLBACKS.push(() => {\n var pos1 = _this2._getPositionForHierarchy(node1);\n var pos2 = _this2._getPositionForHierarchy(node2);\n var diffAbs = Math.abs(pos2 - pos1);\n //console.log(\"NOW CHEcKING:\", node1.id, node2.id, diffAbs);\n if (diffAbs > _this2.options.hierarchical.nodeSpacing) {\n var branchNodes1 = {};branchNodes1[node1.id] = true;\n var branchNodes2 = {};branchNodes2[node2.id] = true;\n\n getBranchNodes(node1, branchNodes1);\n getBranchNodes(node2, branchNodes2);\n\n // check the largest distance between the branches\n var maxLevel = getCollisionLevel(node1, node2);\n\n var _getBranchBoundary = getBranchBoundary(branchNodes1, maxLevel);\n\n var _getBranchBoundary2 = _slicedToArray(_getBranchBoundary, 4);\n\n var min1 = _getBranchBoundary2[0];\n var max1 = _getBranchBoundary2[1];\n var minSpace1 = _getBranchBoundary2[2];\n var maxSpace1 = _getBranchBoundary2[3];\n\n var _getBranchBoundary3 = getBranchBoundary(branchNodes2, maxLevel);\n\n var _getBranchBoundary32 = _slicedToArray(_getBranchBoundary3, 4);\n\n var min2 = _getBranchBoundary32[0];\n var max2 = _getBranchBoundary32[1];\n var minSpace2 = _getBranchBoundary32[2];\n var maxSpace2 = _getBranchBoundary32[3];\n\n //console.log(node1.id, getBranchBoundary(branchNodes1, maxLevel), node2.id, getBranchBoundary(branchNodes2, maxLevel), maxLevel);\n var diffBranch = Math.abs(max1 - min2);\n if (diffBranch > _this2.options.hierarchical.nodeSpacing) {\n var offset = max1 - min2 + _this2.options.hierarchical.nodeSpacing;\n if (offset < -minSpace2 + _this2.options.hierarchical.nodeSpacing) {\n offset = -minSpace2 + _this2.options.hierarchical.nodeSpacing;\n //console.log(\"RESETTING OFFSET\", max1 - min2 + this.options.hierarchical.nodeSpacing, -minSpace2, offset);\n }\n if (offset < 0) {\n //console.log(\"SHIFTING\", node2.id, offset);\n _this2._shiftBlock(node2.id, offset);\n stillShifting = true;\n\n if (centerParent === true) _this2._centerParent(node2);\n }\n }\n }\n //this.body.emitter.emit(\"_redraw\");})\n };\n\n var minimizeEdgeLength = function minimizeEdgeLength(iterations, node) {\n //window.CALLBACKS.push(() => {\n // console.log(\"ts\",node.id);\n var nodeId = node.id;\n var allEdges = node.edges;\n var nodeLevel = _this2.hierarchicalLevels[node.id];\n\n // gather constants\n var C2 = _this2.options.hierarchical.levelSeparation * _this2.options.hierarchical.levelSeparation;\n var referenceNodes = {};\n var aboveEdges = [];\n for (var i = 0; i < allEdges.length; i++) {\n var edge = allEdges[i];\n if (edge.toId != edge.fromId) {\n var otherNode = edge.toId == nodeId ? edge.from : edge.to;\n referenceNodes[allEdges[i].id] = otherNode;\n if (_this2.hierarchicalLevels[otherNode.id] < nodeLevel) {\n aboveEdges.push(edge);\n }\n }\n }\n\n // differentiated sum of lengths based on only moving one node over one axis\n var getFx = function getFx(point, edges) {\n var sum = 0;\n for (var i = 0; i < edges.length; i++) {\n if (referenceNodes[edges[i].id] !== undefined) {\n var a = _this2._getPositionForHierarchy(referenceNodes[edges[i].id]) - point;\n sum += a / Math.sqrt(a * a + C2);\n }\n }\n return sum;\n };\n\n // doubly differentiated sum of lengths based on only moving one node over one axis\n var getDFx = function getDFx(point, edges) {\n var sum = 0;\n for (var i = 0; i < edges.length; i++) {\n if (referenceNodes[edges[i].id] !== undefined) {\n var a = _this2._getPositionForHierarchy(referenceNodes[edges[i].id]) - point;\n sum -= C2 * Math.pow(a * a + C2, -1.5);\n }\n }\n return sum;\n };\n\n var getGuess = function getGuess(iterations, edges) {\n var guess = _this2._getPositionForHierarchy(node);\n // Newton's method for optimization\n var guessMap = {};\n for (var i = 0; i < iterations; i++) {\n var fx = getFx(guess, edges);\n var dfx = getDFx(guess, edges);\n\n // we limit the movement to avoid instability.\n var limit = 40;\n var ratio = Math.max(-limit, Math.min(limit, Math.round(fx / dfx)));\n guess = guess - ratio;\n // reduce duplicates\n if (guessMap[guess] !== undefined) {\n break;\n }\n guessMap[guess] = i;\n }\n return guess;\n };\n\n var moveBranch = function moveBranch(guess) {\n // position node if there is space\n var nodePosition = _this2._getPositionForHierarchy(node);\n\n // check movable area of the branch\n if (branches[node.id] === undefined) {\n var branchNodes = {};\n branchNodes[node.id] = true;\n getBranchNodes(node, branchNodes);\n branches[node.id] = branchNodes;\n }\n\n var _getBranchBoundary4 = getBranchBoundary(branches[node.id]);\n\n var _getBranchBoundary42 = _slicedToArray(_getBranchBoundary4, 4);\n\n var minBranch = _getBranchBoundary42[0];\n var maxBranch = _getBranchBoundary42[1];\n var minSpaceBranch = _getBranchBoundary42[2];\n var maxSpaceBranch = _getBranchBoundary42[3];\n\n var diff = guess - nodePosition;\n\n // check if we are allowed to move the node:\n var branchOffset = 0;\n if (diff > 0) {\n branchOffset = Math.min(diff, maxSpaceBranch - _this2.options.hierarchical.nodeSpacing);\n } else if (diff < 0) {\n branchOffset = -Math.min(-diff, minSpaceBranch - _this2.options.hierarchical.nodeSpacing);\n }\n\n if (branchOffset != 0) {\n //console.log(\"moving branch:\",branchOffset, maxSpaceBranch, minSpaceBranch)\n _this2._shiftBlock(node.id, branchOffset);\n //this.body.emitter.emit(\"_redraw\");\n stillShifting = true;\n }\n };\n\n var moveNode = function moveNode(guess) {\n var nodePosition = _this2._getPositionForHierarchy(node);\n\n // position node if there is space\n\n var _getSpaceAroundNode3 = _this2._getSpaceAroundNode(node);\n\n var _getSpaceAroundNode32 = _slicedToArray(_getSpaceAroundNode3, 2);\n\n var minSpace = _getSpaceAroundNode32[0];\n var maxSpace = _getSpaceAroundNode32[1];\n\n var diff = guess - nodePosition;\n // check if we are allowed to move the node:\n var newPosition = nodePosition;\n if (diff > 0) {\n newPosition = Math.min(nodePosition + (maxSpace - _this2.options.hierarchical.nodeSpacing), guess);\n } else if (diff < 0) {\n newPosition = Math.max(nodePosition - (minSpace - _this2.options.hierarchical.nodeSpacing), guess);\n }\n\n if (newPosition !== nodePosition) {\n //console.log(\"moving Node:\",diff, minSpace, maxSpace)\n _this2._setPositionForHierarchy(node, newPosition, undefined, true);\n //this.body.emitter.emit(\"_redraw\");\n stillShifting = true;\n }\n };\n\n var guess = getGuess(iterations, aboveEdges);\n moveBranch(guess);\n guess = getGuess(iterations, allEdges);\n moveNode(guess);\n //})\n };\n\n // method to remove whitespace between branches. Because we do bottom up, we can center the parents.\n var minimizeEdgeLengthBottomUp = function minimizeEdgeLengthBottomUp(iterations) {\n var levels = Object.keys(_this2.distributionOrdering);\n levels = levels.reverse();\n for (var i = 0; i < iterations; i++) {\n stillShifting = false;\n for (var j = 0; j < levels.length; j++) {\n var level = levels[j];\n var levelNodes = _this2.distributionOrdering[level];\n for (var k = 0; k < levelNodes.length; k++) {\n minimizeEdgeLength(1000, levelNodes[k]);\n }\n }\n if (stillShifting !== true) {\n //console.log(\"FINISHED minimizeEdgeLengthBottomUp IN \" + i);\n break;\n }\n }\n };\n\n //// method to remove whitespace between branches. Because we do bottom up, we can center the parents.\n var shiftBranchesCloserBottomUp = function shiftBranchesCloserBottomUp(iterations) {\n var levels = Object.keys(_this2.distributionOrdering);\n levels = levels.reverse();\n for (var i = 0; i < iterations; i++) {\n stillShifting = false;\n shiftElementsCloser(branchShiftCallback, levels, true);\n if (stillShifting !== true) {\n //console.log(\"FINISHED shiftBranchesCloserBottomUp IN \" + (i+1));\n break;\n }\n }\n };\n\n // center all parents\n var centerAllParents = function centerAllParents() {\n for (var nodeId in _this2.body.nodes) {\n if (_this2.body.nodes.hasOwnProperty(nodeId)) _this2._centerParent(_this2.body.nodes[nodeId]);\n }\n };\n\n // the actual work is done here.\n if (this.options.hierarchical.blockShifting === true) {\n shiftBranchesCloserBottomUp(5);\n centerAllParents();\n }\n\n // minimize edge length\n if (this.options.hierarchical.edgeMinimization === true) {\n minimizeEdgeLengthBottomUp(20);\n }\n\n shiftTrees();\n }\n\n /**\n * This gives the space around the node. IF a map is supplied, it will only check against nodes NOT in the map.\n * This is used to only get the distances to nodes outside of a branch.\n * @param node\n * @param map\n * @returns {*[]}\n * @private\n */\n }, {\n key: '_getSpaceAroundNode',\n value: function _getSpaceAroundNode(node, map) {\n var useMap = true;\n if (map === undefined) {\n useMap = false;\n }\n var level = this.hierarchicalLevels[node.id];\n if (level !== undefined) {\n var index = this.distributionIndex[node.id];\n var position = this._getPositionForHierarchy(node);\n var minSpace = 1e9;\n var maxSpace = 1e9;\n if (index !== 0) {\n var prevNode = this.distributionOrdering[level][index - 1];\n if (useMap === true && map[prevNode.id] === undefined || useMap === false) {\n var prevPos = this._getPositionForHierarchy(prevNode);\n minSpace = position - prevPos;\n }\n }\n\n if (index != this.distributionOrdering[level].length - 1) {\n var nextNode = this.distributionOrdering[level][index + 1];\n if (useMap === true && map[nextNode.id] === undefined || useMap === false) {\n var nextPos = this._getPositionForHierarchy(nextNode);\n maxSpace = Math.min(maxSpace, nextPos - position);\n }\n }\n\n return [minSpace, maxSpace];\n } else {\n return [0, 0];\n }\n }\n\n /**\n * We use this method to center a parent node and check if it does not cross other nodes when it does.\n * @param node\n * @private\n */\n }, {\n key: '_centerParent',\n value: function _centerParent(node) {\n if (this.hierarchicalChildren[node.id]) {\n var parents = this.hierarchicalChildren[node.id].parents;\n for (var i = 0; i < parents.length; i++) {\n var parentId = parents[i];\n var parentNode = this.body.nodes[parentId];\n if (this.hierarchicalParents[parentId]) {\n // get the range of the children\n var minPos = 1e9;\n var maxPos = -1e9;\n var children = this.hierarchicalParents[parentId].children;\n if (children.length > 0) {\n for (var _i = 0; _i < children.length; _i++) {\n var childNode = this.body.nodes[children[_i]];\n minPos = Math.min(minPos, this._getPositionForHierarchy(childNode));\n maxPos = Math.max(maxPos, this._getPositionForHierarchy(childNode));\n }\n }\n\n var position = this._getPositionForHierarchy(parentNode);\n\n var _getSpaceAroundNode4 = this._getSpaceAroundNode(parentNode);\n\n var _getSpaceAroundNode42 = _slicedToArray(_getSpaceAroundNode4, 2);\n\n var minSpace = _getSpaceAroundNode42[0];\n var maxSpace = _getSpaceAroundNode42[1];\n\n var newPosition = 0.5 * (minPos + maxPos);\n var diff = position - newPosition;\n if (diff < 0 && Math.abs(diff) < maxSpace - this.options.hierarchical.nodeSpacing || diff > 0 && Math.abs(diff) < minSpace - this.options.hierarchical.nodeSpacing) {\n this._setPositionForHierarchy(parentNode, newPosition, undefined, true);\n }\n }\n }\n }\n }\n\n /**\n * This function places the nodes on the canvas based on the hierarchial distribution.\n *\n * @param {Object} distribution | obtained by the function this._getDistribution()\n * @private\n */\n }, {\n key: '_placeNodesByHierarchy',\n value: function _placeNodesByHierarchy(distribution) {\n this.positionedNodes = {};\n // start placing all the level 0 nodes first. Then recursively position their branches.\n for (var level in distribution) {\n if (distribution.hasOwnProperty(level)) {\n // sort nodes in level by position:\n var nodeArray = Object.keys(distribution[level]);\n nodeArray = this._indexArrayToNodes(nodeArray);\n this._sortNodeArray(nodeArray);\n\n for (var i = 0; i < nodeArray.length; i++) {\n var node = nodeArray[i];\n if (this.positionedNodes[node.id] === undefined) {\n this._setPositionForHierarchy(node, this.options.hierarchical.nodeSpacing * i, level);\n this.positionedNodes[node.id] = true;\n this._placeBranchNodes(node.id, level);\n }\n }\n }\n }\n }\n\n /**\n * Receives an array with node indices and returns an array with the actual node references. Used for sorting based on\n * node properties.\n * @param idArray\n */\n }, {\n key: '_indexArrayToNodes',\n value: function _indexArrayToNodes(idArray) {\n var array = [];\n for (var i = 0; i < idArray.length; i++) {\n array.push(this.body.nodes[idArray[i]]);\n }\n return array;\n }\n\n /**\n * This function get the distribution of levels based on hubsize\n *\n * @returns {Object}\n * @private\n */\n }, {\n key: '_getDistribution',\n value: function _getDistribution() {\n var distribution = {};\n var nodeId = undefined,\n node = undefined;\n\n // we fix Y because the hierarchy is vertical, we fix X so we do not give a node an x position for a second time.\n // the fix of X is removed after the x value has been set.\n for (nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n node = this.body.nodes[nodeId];\n var level = this.hierarchicalLevels[nodeId] === undefined ? 0 : this.hierarchicalLevels[nodeId];\n if (this.options.hierarchical.direction === 'UD' || this.options.hierarchical.direction === 'DU') {\n node.y = this.options.hierarchical.levelSeparation * level;\n node.options.fixed.y = true;\n } else {\n node.x = this.options.hierarchical.levelSeparation * level;\n node.options.fixed.x = true;\n }\n if (distribution[level] === undefined) {\n distribution[level] = {};\n }\n distribution[level][nodeId] = node;\n }\n }\n return distribution;\n }\n\n /**\n * Get the hubsize from all remaining unlevelled nodes.\n *\n * @returns {number}\n * @private\n */\n }, {\n key: '_getHubSize',\n value: function _getHubSize() {\n var hubSize = 0;\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n var node = this.body.nodes[nodeId];\n if (this.hierarchicalLevels[nodeId] === undefined) {\n hubSize = node.edges.length < hubSize ? hubSize : node.edges.length;\n }\n }\n }\n return hubSize;\n }\n\n /**\n * this function allocates nodes in levels based on the recursive branching from the largest hubs.\n *\n * @param hubsize\n * @private\n */\n }, {\n key: '_determineLevelsByHubsize',\n value: function _determineLevelsByHubsize() {\n var _this3 = this;\n\n var hubSize = 1;\n\n var levelDownstream = function levelDownstream(nodeA, nodeB) {\n if (_this3.hierarchicalLevels[nodeB.id] === undefined) {\n // set initial level\n if (_this3.hierarchicalLevels[nodeA.id] === undefined) {\n _this3.hierarchicalLevels[nodeA.id] = 0;\n }\n // set level\n _this3.hierarchicalLevels[nodeB.id] = _this3.hierarchicalLevels[nodeA.id] + 1;\n }\n };\n\n while (hubSize > 0) {\n // determine hubs\n hubSize = this._getHubSize();\n if (hubSize === 0) break;\n\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n var node = this.body.nodes[nodeId];\n if (node.edges.length === hubSize) {\n this._crawlNetwork(levelDownstream, nodeId);\n }\n }\n }\n }\n }\n\n /**\n * TODO: release feature\n * @private\n */\n }, {\n key: '_determineLevelsCustomCallback',\n value: function _determineLevelsCustomCallback() {\n var _this4 = this;\n\n var minLevel = 100000;\n\n // TODO: this should come from options.\n var customCallback = function customCallback(nodeA, nodeB, edge) {};\n\n var levelByDirection = function levelByDirection(nodeA, nodeB, edge) {\n var levelA = _this4.hierarchicalLevels[nodeA.id];\n // set initial level\n if (levelA === undefined) {\n _this4.hierarchicalLevels[nodeA.id] = minLevel;\n }\n\n var diff = customCallback(_NetworkUtil2['default'].cloneOptions(nodeA, 'node'), _NetworkUtil2['default'].cloneOptions(nodeB, 'node'), _NetworkUtil2['default'].cloneOptions(edge, 'edge'));\n\n _this4.hierarchicalLevels[nodeB.id] = _this4.hierarchicalLevels[nodeA.id] + diff;\n };\n\n this._crawlNetwork(levelByDirection);\n this._setMinLevelToZero();\n }\n\n /**\n * this function allocates nodes in levels based on the direction of the edges\n *\n * @param hubsize\n * @private\n */\n }, {\n key: '_determineLevelsDirected',\n value: function _determineLevelsDirected() {\n var _this5 = this;\n\n var minLevel = 10000;\n var levelByDirection = function levelByDirection(nodeA, nodeB, edge) {\n var levelA = _this5.hierarchicalLevels[nodeA.id];\n // set initial level\n if (levelA === undefined) {\n _this5.hierarchicalLevels[nodeA.id] = minLevel;\n }\n if (edge.toId == nodeB.id) {\n _this5.hierarchicalLevels[nodeB.id] = _this5.hierarchicalLevels[nodeA.id] + 1;\n } else {\n _this5.hierarchicalLevels[nodeB.id] = _this5.hierarchicalLevels[nodeA.id] - 1;\n }\n };\n this._crawlNetwork(levelByDirection);\n this._setMinLevelToZero();\n }\n\n /**\n * Small util method to set the minimum levels of the nodes to zero.\n * @private\n */\n }, {\n key: '_setMinLevelToZero',\n value: function _setMinLevelToZero() {\n var minLevel = 1e9;\n // get the minimum level\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n if (this.hierarchicalLevels[nodeId] !== undefined) {\n minLevel = Math.min(this.hierarchicalLevels[nodeId], minLevel);\n }\n }\n }\n\n // subtract the minimum from the set so we have a range starting from 0\n for (var nodeId in this.body.nodes) {\n if (this.body.nodes.hasOwnProperty(nodeId)) {\n if (this.hierarchicalLevels[nodeId] !== undefined) {\n this.hierarchicalLevels[nodeId] -= minLevel;\n }\n }\n }\n }\n\n /**\n * Update the bookkeeping of parent and child.\n * @private\n */\n }, {\n key: '_generateMap',\n value: function _generateMap() {\n var _this6 = this;\n\n var fillInRelations = function fillInRelations(parentNode, childNode) {\n if (_this6.hierarchicalLevels[childNode.id] > _this6.hierarchicalLevels[parentNode.id]) {\n var parentNodeId = parentNode.id;\n var childNodeId = childNode.id;\n if (_this6.hierarchicalParents[parentNodeId] === undefined) {\n _this6.hierarchicalParents[parentNodeId] = { children: [], amount: 0 };\n }\n _this6.hierarchicalParents[parentNodeId].children.push(childNodeId);\n if (_this6.hierarchicalChildren[childNodeId] === undefined) {\n _this6.hierarchicalChildren[childNodeId] = { parents: [], amount: 0 };\n }\n _this6.hierarchicalChildren[childNodeId].parents.push(parentNodeId);\n }\n };\n\n this._crawlNetwork(fillInRelations);\n }\n\n /**\n * Crawl over the entire network and use a callback on each node couple that is connected to each other.\n * @param callback | will receive nodeA nodeB and the connecting edge. A and B are unique.\n * @param startingNodeId\n * @private\n */\n }, {\n key: '_crawlNetwork',\n value: function _crawlNetwork(callback, startingNodeId) {\n if (callback === undefined) callback = function () {};\n\n var progress = {};\n var crawler = function crawler(node) {\n if (progress[node.id] === undefined) {\n progress[node.id] = true;\n var childNode = undefined;\n for (var i = 0; i < node.edges.length; i++) {\n if (node.edges[i].connected === true) {\n if (node.edges[i].toId === node.id) {\n childNode = node.edges[i].from;\n } else {\n childNode = node.edges[i].to;\n }\n\n if (node.id !== childNode.id) {\n callback(node, childNode, node.edges[i]);\n crawler(childNode);\n }\n }\n }\n }\n };\n\n // we can crawl from a specific node or over all nodes.\n if (startingNodeId === undefined) {\n for (var i = 0; i < this.body.nodeIndices.length; i++) {\n var node = this.body.nodes[this.body.nodeIndices[i]];\n crawler(node);\n }\n } else {\n var node = this.body.nodes[startingNodeId];\n if (node === undefined) {\n console.error(\"Node not found:\", startingNodeId);\n return;\n }\n crawler(node);\n }\n }\n\n /**\n * This is a recursively called function to enumerate the branches from the largest hubs and place the nodes\n * on a X position that ensures there will be no overlap.\n *\n * @param parentId\n * @param parentLevel\n * @private\n */\n }, {\n key: '_placeBranchNodes',\n value: function _placeBranchNodes(parentId, parentLevel) {\n // if this is not a parent, cancel the placing. This can happen with multiple parents to one child.\n if (this.hierarchicalParents[parentId] === undefined) {\n return;\n }\n\n // get a list of childNodes\n var childNodes = [];\n for (var i = 0; i < this.hierarchicalParents[parentId].children.length; i++) {\n childNodes.push(this.body.nodes[this.hierarchicalParents[parentId].children[i]]);\n }\n\n // use the positions to order the nodes.\n this._sortNodeArray(childNodes);\n\n // position the childNodes\n for (var i = 0; i < childNodes.length; i++) {\n var childNode = childNodes[i];\n var childNodeLevel = this.hierarchicalLevels[childNode.id];\n // check if the child node is below the parent node and if it has already been positioned.\n if (childNodeLevel > parentLevel && this.positionedNodes[childNode.id] === undefined) {\n // get the amount of space required for this node. If parent the width is based on the amount of children.\n var pos = undefined;\n\n // we get the X or Y values we need and store them in pos and previousPos. The get and set make sure we get X or Y\n if (i === 0) {\n pos = this._getPositionForHierarchy(this.body.nodes[parentId]);\n } else {\n pos = this._getPositionForHierarchy(childNodes[i - 1]) + this.options.hierarchical.nodeSpacing;\n }\n this._setPositionForHierarchy(childNode, pos, childNodeLevel);\n\n // if overlap has been detected, we shift the branch\n if (this.lastNodeOnLevel[childNodeLevel] !== undefined) {\n var previousPos = this._getPositionForHierarchy(this.body.nodes[this.lastNodeOnLevel[childNodeLevel]]);\n if (pos - previousPos < this.options.hierarchical.nodeSpacing) {\n var diff = previousPos + this.options.hierarchical.nodeSpacing - pos;\n var sharedParent = this._findCommonParent(this.lastNodeOnLevel[childNodeLevel], childNode.id);\n this._shiftBlock(sharedParent.withChild, diff);\n }\n }\n\n // store change in position.\n this.lastNodeOnLevel[childNodeLevel] = childNode.id;\n\n this.positionedNodes[childNode.id] = true;\n\n this._placeBranchNodes(childNode.id, childNodeLevel);\n } else {\n return;\n }\n }\n\n // center the parent nodes.\n var minPos = 1e9;\n var maxPos = -1e9;\n for (var i = 0; i < childNodes.length; i++) {\n var childNodeId = childNodes[i].id;\n minPos = Math.min(minPos, this._getPositionForHierarchy(this.body.nodes[childNodeId]));\n maxPos = Math.max(maxPos, this._getPositionForHierarchy(this.body.nodes[childNodeId]));\n }\n this._setPositionForHierarchy(this.body.nodes[parentId], 0.5 * (minPos + maxPos), parentLevel);\n }\n\n /**\n * Shift a branch a certain distance\n * @param parentId\n * @param diff\n * @private\n */\n }, {\n key: '_shiftBlock',\n value: function _shiftBlock(parentId, diff) {\n if (this.options.hierarchical.direction === 'UD' || this.options.hierarchical.direction === 'DU') {\n this.body.nodes[parentId].x += diff;\n } else {\n this.body.nodes[parentId].y += diff;\n }\n if (this.hierarchicalParents[parentId] !== undefined) {\n for (var i = 0; i < this.hierarchicalParents[parentId].children.length; i++) {\n this._shiftBlock(this.hierarchicalParents[parentId].children[i], diff);\n }\n }\n }\n\n /**\n * Find a common parent between branches.\n * @param childA\n * @param childB\n * @returns {{foundParent, withChild}}\n * @private\n */\n }, {\n key: '_findCommonParent',\n value: function _findCommonParent(childA, childB) {\n var _this7 = this;\n\n var parents = {};\n var iterateParents = function iterateParents(parents, child) {\n if (_this7.hierarchicalChildren[child] !== undefined) {\n for (var i = 0; i < _this7.hierarchicalChildren[child].parents.length; i++) {\n var _parent = _this7.hierarchicalChildren[child].parents[i];\n parents[_parent] = true;\n iterateParents(parents, _parent);\n }\n }\n };\n var findParent = function findParent(parents, child) {\n if (_this7.hierarchicalChildren[child] !== undefined) {\n for (var i = 0; i < _this7.hierarchicalChildren[child].parents.length; i++) {\n var _parent2 = _this7.hierarchicalChildren[child].parents[i];\n if (parents[_parent2] !== undefined) {\n return { foundParent: _parent2, withChild: child };\n }\n var branch = findParent(parents, _parent2);\n if (branch.foundParent !== null) {\n return branch;\n }\n }\n }\n return { foundParent: null, withChild: child };\n };\n\n iterateParents(parents, childA);\n return findParent(parents, childB);\n }\n\n /**\n * Abstract the getting of the position so we won't have to repeat the check for direction all the time\n * @param node\n * @param position\n * @param level\n * @private\n */\n }, {\n key: '_setPositionForHierarchy',\n value: function _setPositionForHierarchy(node, position, level) {\n var doNotUpdate = arguments.length <= 3 || arguments[3] === undefined ? false : arguments[3];\n\n if (doNotUpdate !== true) {\n if (this.distributionOrdering[level] === undefined) {\n this.distributionOrdering[level] = [];\n this.distributionOrderingPresence[level] = {};\n }\n\n if (this.distributionOrderingPresence[level][node.id] === undefined) {\n this.distributionOrdering[level].push(node);\n this.distributionIndex[node.id] = this.distributionOrdering[level].length - 1;\n }\n this.distributionOrderingPresence[level][node.id] = true;\n\n if (this.hierarchicalTrees[node.id] === undefined) {\n if (this.hierarchicalChildren[node.id] !== undefined) {\n var tree = 1;\n // get the lowest tree denominator.\n for (var i = 0; i < this.hierarchicalChildren[node.id].parents.length; i++) {\n var parentId = this.hierarchicalChildren[node.id].parents[i];\n if (this.hierarchicalTrees[parentId] !== undefined) {\n //tree = Math.min(tree,this.hierarchicalTrees[parentId]);\n tree = this.hierarchicalTrees[parentId];\n }\n }\n //for (let i = 0; i < this.hierarchicalChildren.parents.length; i++) {\n // let parentId = this.hierarchicalChildren.parents[i];\n // this.hierarchicalTrees[parentId] = tree;\n //}\n this.hierarchicalTrees[node.id] = tree;\n } else {\n this.hierarchicalTrees[node.id] = ++this.treeIndex;\n }\n }\n }\n\n if (this.options.hierarchical.direction === 'UD' || this.options.hierarchical.direction === 'DU') {\n node.x = position;\n } else {\n node.y = position;\n }\n }\n\n /**\n * Abstract the getting of the position of a node so we do not have to repeat the direction check all the time.\n * @param node\n * @returns {number|*}\n * @private\n */\n }, {\n key: '_getPositionForHierarchy',\n value: function _getPositionForHierarchy(node) {\n if (this.options.hierarchical.direction === 'UD' || this.options.hierarchical.direction === 'DU') {\n return node.x;\n } else {\n return node.y;\n }\n }\n\n /**\n * Use the x or y value to sort the array, allowing users to specify order.\n * @param nodeArray\n * @private\n */\n }, {\n key: '_sortNodeArray',\n value: function _sortNodeArray(nodeArray) {\n if (nodeArray.length > 1) {\n if (this.options.hierarchical.direction === 'UD' || this.options.hierarchical.direction === 'DU') {\n nodeArray.sort(function (a, b) {\n return a.x - b.x;\n });\n } else {\n nodeArray.sort(function (a, b) {\n return a.y - b.y;\n });\n }\n }\n }\n }]);\n\n return LayoutEngine;\n })();\n\n exports['default'] = LayoutEngine;\n module.exports = exports['default'];\n\n/***/ },\n/* 109 */\n/***/ function(module, exports, __webpack_require__) {\n\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ('value' in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError('Cannot call a class as a function'); } }\n\n var util = __webpack_require__(1);\n var Hammer = __webpack_require__(20);\n var hammerUtil = __webpack_require__(24);\n\n /**\n * clears the toolbar div element of children\n *\n * @private\n */\n\n var ManipulationSystem = (function () {\n function ManipulationSystem(body, canvas, selectionHandler) {\n var _this = this;\n\n _classCallCheck(this, ManipulationSystem);\n\n this.body = body;\n this.canvas = canvas;\n this.selectionHandler = selectionHandler;\n\n this.editMode = false;\n this.manipulationDiv = undefined;\n this.editModeDiv = undefined;\n this.closeDiv = undefined;\n\n this.manipulationHammers = [];\n this.temporaryUIFunctions = {};\n this.temporaryEventFunctions = [];\n\n this.touchTime = 0;\n this.temporaryIds = { nodes: [], edges: [] };\n this.guiEnabled = false;\n this.inMode = false;\n this.selectedControlNode = undefined;\n\n this.options = {};\n this.defaultOptions = {\n enabled: false,\n initiallyActive: false,\n addNode: true,\n addEdge: true,\n editNode: undefined,\n editEdge: true,\n deleteNode: true,\n deleteEdge: true,\n controlNodeStyle: {\n shape: 'dot',\n size: 6,\n color: { background: '#ff0000', border: '#3c3c3c', highlight: { background: '#07f968', border: '#3c3c3c' } },\n borderWidth: 2,\n borderWidthSelected: 2\n }\n };\n util.extend(this.options, this.defaultOptions);\n\n this.body.emitter.on('destroy', function () {\n _this._clean();\n });\n this.body.emitter.on('_dataChanged', this._restore.bind(this));\n this.body.emitter.on('_resetData', this._restore.bind(this));\n }\n\n /**\n * If something changes in the data during editing, switch back to the initial datamanipulation state and close all edit modes.\n * @private\n */\n\n _createClass(ManipulationSystem, [{\n key: '_restore',\n value: function _restore() {\n if (this.inMode !== false) {\n if (this.options.initiallyActive === true) {\n this.enableEditMode();\n } else {\n this.disableEditMode();\n }\n }\n }\n\n /**\n * Set the Options\n * @param options\n */\n }, {\n key: 'setOptions',\n value: function setOptions(options, allOptions, globalOptions) {\n if (allOptions !== undefined) {\n if (allOptions.locale !== undefined) {\n this.options.locale = allOptions.locale;\n } else {\n this.options.locale = globalOptions.locale;\n }\n if (allOptions.locales !== undefined) {\n this.options.locales = allOptions.locales;\n } else {\n this.options.locales = globalOptions.locales;\n }\n }\n\n if (options !== undefined) {\n if (typeof options === 'boolean') {\n this.options.enabled = options;\n } else {\n this.options.enabled = true;\n util.deepExtend(this.options, options);\n }\n if (this.options.initiallyActive === true) {\n this.editMode = true;\n }\n this._setup();\n }\n }\n\n /**\n * Enable or disable edit-mode. Draws the DOM required and cleans up after itself.\n *\n * @private\n */\n }, {\n key: 'toggleEditMode',\n value: function toggleEditMode() {\n if (this.editMode === true) {\n this.disableEditMode();\n } else {\n this.enableEditMode();\n }\n }\n }, {\n key: 'enableEditMode',\n value: function enableEditMode() {\n this.editMode = true;\n\n this._clean();\n if (this.guiEnabled === true) {\n this.manipulationDiv.style.display = 'block';\n this.closeDiv.style.display = 'block';\n this.editModeDiv.style.display = 'none';\n this.showManipulatorToolbar();\n }\n }\n }, {\n key: 'disableEditMode',\n value: function disableEditMode() {\n this.editMode = false;\n\n this._clean();\n if (this.guiEnabled === true) {\n this.manipulationDiv.style.display = 'none';\n this.closeDiv.style.display = 'none';\n this.editModeDiv.style.display = 'block';\n this._createEditButton();\n }\n }\n\n /**\n * Creates the main toolbar. Removes functions bound to the select event. Binds all the buttons of the toolbar.\n *\n * @private\n */\n }, {\n key: 'showManipulatorToolbar',\n value: function showManipulatorToolbar() {\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n\n // reset global variables\n this.manipulationDOM = {};\n\n // if the gui is enabled, draw all elements.\n if (this.guiEnabled === true) {\n // a _restore will hide these menus\n this.editMode = true;\n this.manipulationDiv.style.display = 'block';\n this.closeDiv.style.display = 'block';\n\n var selectedNodeCount = this.selectionHandler._getSelectedNodeCount();\n var selectedEdgeCount = this.selectionHandler._getSelectedEdgeCount();\n var selectedTotalCount = selectedNodeCount + selectedEdgeCount;\n var locale = this.options.locales[this.options.locale];\n var needSeperator = false;\n\n if (this.options.addNode !== false) {\n this._createAddNodeButton(locale);\n needSeperator = true;\n }\n if (this.options.addEdge !== false) {\n if (needSeperator === true) {\n this._createSeperator(1);\n } else {\n needSeperator = true;\n }\n this._createAddEdgeButton(locale);\n }\n\n if (selectedNodeCount === 1 && typeof this.options.editNode === 'function') {\n if (needSeperator === true) {\n this._createSeperator(2);\n } else {\n needSeperator = true;\n }\n this._createEditNodeButton(locale);\n } else if (selectedEdgeCount === 1 && selectedNodeCount === 0 && this.options.editEdge !== false) {\n if (needSeperator === true) {\n this._createSeperator(3);\n } else {\n needSeperator = true;\n }\n this._createEditEdgeButton(locale);\n }\n\n // remove buttons\n if (selectedTotalCount !== 0) {\n if (selectedNodeCount > 0 && this.options.deleteNode !== false) {\n if (needSeperator === true) {\n this._createSeperator(4);\n }\n this._createDeleteButton(locale);\n } else if (selectedNodeCount === 0 && this.options.deleteEdge !== false) {\n if (needSeperator === true) {\n this._createSeperator(4);\n }\n this._createDeleteButton(locale);\n }\n }\n\n // bind the close button\n this._bindHammerToDiv(this.closeDiv, this.toggleEditMode.bind(this));\n\n // refresh this bar based on what has been selected\n this._temporaryBindEvent('select', this.showManipulatorToolbar.bind(this));\n }\n\n // redraw to show any possible changes\n this.body.emitter.emit('_redraw');\n }\n\n /**\n * Create the toolbar for adding Nodes\n */\n }, {\n key: 'addNodeMode',\n value: function addNodeMode() {\n // when using the gui, enable edit mode if it wasnt already.\n if (this.editMode !== true) {\n this.enableEditMode();\n }\n\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n\n this.inMode = 'addNode';\n if (this.guiEnabled === true) {\n var locale = this.options.locales[this.options.locale];\n this.manipulationDOM = {};\n this._createBackButton(locale);\n this._createSeperator();\n this._createDescription(locale['addDescription'] || this.options.locales['en']['addDescription']);\n\n // bind the close button\n this._bindHammerToDiv(this.closeDiv, this.toggleEditMode.bind(this));\n }\n\n this._temporaryBindEvent('click', this._performAddNode.bind(this));\n }\n\n /**\n * call the bound function to handle the editing of the node. The node has to be selected.\n */\n }, {\n key: 'editNode',\n value: function editNode() {\n var _this2 = this;\n\n // when using the gui, enable edit mode if it wasnt already.\n if (this.editMode !== true) {\n this.enableEditMode();\n }\n\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n var node = this.selectionHandler._getSelectedNode();\n if (node !== undefined) {\n this.inMode = 'editNode';\n if (typeof this.options.editNode === 'function') {\n if (node.isCluster !== true) {\n var data = util.deepExtend({}, node.options, true);\n data.x = node.x;\n data.y = node.y;\n\n if (this.options.editNode.length === 2) {\n this.options.editNode(data, function (finalizedData) {\n if (finalizedData !== null && finalizedData !== undefined && _this2.inMode === 'editNode') {\n // if for whatever reason the mode has changes (due to dataset change) disregard the callback) {\n _this2.body.data.nodes.getDataSet().update(finalizedData);\n }\n _this2.showManipulatorToolbar();\n });\n } else {\n throw new Error('The function for edit does not support two arguments (data, callback)');\n }\n } else {\n alert(this.options.locales[this.options.locale]['editClusterError'] || this.options.locales['en']['editClusterError']);\n }\n } else {\n throw new Error('No function has been configured to handle the editing of nodes.');\n }\n } else {\n this.showManipulatorToolbar();\n }\n }\n\n /**\n * create the toolbar to connect nodes\n */\n }, {\n key: 'addEdgeMode',\n value: function addEdgeMode() {\n // when using the gui, enable edit mode if it wasnt already.\n if (this.editMode !== true) {\n this.enableEditMode();\n }\n\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n\n this.inMode = 'addEdge';\n if (this.guiEnabled === true) {\n var locale = this.options.locales[this.options.locale];\n this.manipulationDOM = {};\n this._createBackButton(locale);\n this._createSeperator();\n this._createDescription(locale['edgeDescription'] || this.options.locales['en']['edgeDescription']);\n\n // bind the close button\n this._bindHammerToDiv(this.closeDiv, this.toggleEditMode.bind(this));\n }\n\n // temporarily overload functions\n this._temporaryBindUI('onTouch', this._handleConnect.bind(this));\n this._temporaryBindUI('onDragEnd', this._finishConnect.bind(this));\n this._temporaryBindUI('onDrag', this._dragControlNode.bind(this));\n this._temporaryBindUI('onRelease', this._finishConnect.bind(this));\n\n this._temporaryBindUI('onDragStart', function () {});\n this._temporaryBindUI('onHold', function () {});\n }\n\n /**\n * create the toolbar to edit edges\n */\n }, {\n key: 'editEdgeMode',\n value: function editEdgeMode() {\n var _this3 = this;\n\n // when using the gui, enable edit mode if it wasn't already.\n if (this.editMode !== true) {\n this.enableEditMode();\n }\n\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n\n this.inMode = 'editEdge';\n if (this.guiEnabled === true) {\n var locale = this.options.locales[this.options.locale];\n this.manipulationDOM = {};\n this._createBackButton(locale);\n this._createSeperator();\n this._createDescription(locale['editEdgeDescription'] || this.options.locales['en']['editEdgeDescription']);\n\n // bind the close button\n this._bindHammerToDiv(this.closeDiv, this.toggleEditMode.bind(this));\n }\n\n this.edgeBeingEditedId = this.selectionHandler.getSelectedEdges()[0];\n if (this.edgeBeingEditedId !== undefined) {\n (function () {\n var edge = _this3.body.edges[_this3.edgeBeingEditedId];\n\n // create control nodes\n var controlNodeFrom = _this3._getNewTargetNode(edge.from.x, edge.from.y);\n var controlNodeTo = _this3._getNewTargetNode(edge.to.x, edge.to.y);\n\n _this3.temporaryIds.nodes.push(controlNodeFrom.id);\n _this3.temporaryIds.nodes.push(controlNodeTo.id);\n\n _this3.body.nodes[controlNodeFrom.id] = controlNodeFrom;\n _this3.body.nodeIndices.push(controlNodeFrom.id);\n _this3.body.nodes[controlNodeTo.id] = controlNodeTo;\n _this3.body.nodeIndices.push(controlNodeTo.id);\n\n // temporarily overload UI functions, cleaned up automatically because of _temporaryBindUI\n _this3._temporaryBindUI('onTouch', _this3._controlNodeTouch.bind(_this3)); // used to get the position\n _this3._temporaryBindUI('onTap', function () {}); // disabled\n _this3._temporaryBindUI('onHold', function () {}); // disabled\n _this3._temporaryBindUI('onDragStart', _this3._controlNodeDragStart.bind(_this3)); // used to select control node\n _this3._temporaryBindUI('onDrag', _this3._controlNodeDrag.bind(_this3)); // used to drag control node\n _this3._temporaryBindUI('onDragEnd', _this3._controlNodeDragEnd.bind(_this3)); // used to connect or revert control nodes\n _this3._temporaryBindUI('onMouseMove', function () {}); // disabled\n\n // create function to position control nodes correctly on movement\n // automatically cleaned up because we use the temporary bind\n _this3._temporaryBindEvent('beforeDrawing', function (ctx) {\n var positions = edge.edgeType.findBorderPositions(ctx);\n if (controlNodeFrom.selected === false) {\n controlNodeFrom.x = positions.from.x;\n controlNodeFrom.y = positions.from.y;\n }\n if (controlNodeTo.selected === false) {\n controlNodeTo.x = positions.to.x;\n controlNodeTo.y = positions.to.y;\n }\n });\n\n _this3.body.emitter.emit('_redraw');\n })();\n } else {\n this.showManipulatorToolbar();\n }\n }\n\n /**\n * delete everything in the selection\n */\n }, {\n key: 'deleteSelected',\n value: function deleteSelected() {\n var _this4 = this;\n\n // when using the gui, enable edit mode if it wasnt already.\n if (this.editMode !== true) {\n this.enableEditMode();\n }\n\n // restore the state of any bound functions or events, remove control nodes, restore physics\n this._clean();\n\n this.inMode = 'delete';\n var selectedNodes = this.selectionHandler.getSelectedNodes();\n var selectedEdges = this.selectionHandler.getSelectedEdges();\n var deleteFunction = undefined;\n if (selectedNodes.length > 0) {\n for (var i = 0; i < selectedNodes.length; i++) {\n if (this.body.nodes[selectedNodes[i]].isCluster === true) {\n alert(this.options.locales[this.options.locale]['deleteClusterError'] || this.options.locales['en']['deleteClusterError']);\n return;\n }\n }\n\n if (typeof this.options.deleteNode === 'function') {\n deleteFunction = this.options.deleteNode;\n }\n } else if (selectedEdges.length > 0) {\n if (typeof this.options.deleteEdge === 'function') {\n deleteFunction = this.options.deleteEdge;\n }\n }\n\n if (typeof deleteFunction === 'function') {\n var data = { nodes: selectedNodes, edges: selectedEdges };\n if (deleteFunction.length === 2) {\n deleteFunction(data, function (finalizedData) {\n if (finalizedData !== null && finalizedData !== undefined && _this4.inMode === 'delete') {\n // if for whatever reason the mode has changes (due to dataset change) disregard the callback) {\n _this4.body.data.edges.getDataSet().remove(finalizedData.edges);\n _this4.body.data.nodes.getDataSet().remove(finalizedData.nodes);\n _this4.body.emitter.emit('startSimulation');\n _this4.showManipulatorToolbar();\n } else {\n _this4.body.emitter.emit('startSimulation');\n _this4.showManipulatorToolbar();\n }\n });\n } else {\n throw new Error('The function for delete does not support two arguments (data, callback)');\n }\n } else {\n this.body.data.edges.getDataSet().remove(selectedEdges);\n this.body.data.nodes.getDataSet().remove(selectedNodes);\n this.body.emitter.emit('startSimulation');\n this.showManipulatorToolbar();\n }\n }\n\n //********************************************** PRIVATE ***************************************//\n\n /**\n * draw or remove the DOM\n * @private\n */\n }, {\n key: '_setup',\n value: function _setup() {\n if (this.options.enabled === true) {\n // Enable the GUI\n this.guiEnabled = true;\n\n this._createWrappers();\n if (this.editMode === false) {\n this._createEditButton();\n } else {\n this.showManipulatorToolbar();\n }\n } else {\n this._removeManipulationDOM();\n\n // disable the gui\n this.guiEnabled = false;\n }\n }\n\n /**\n * create the div overlays that contain the DOM\n * @private\n */\n }, {\n key: '_createWrappers',\n value: function _createWrappers() {\n // load the manipulator HTML elements. All styling done in css.\n if (this.manipulationDiv === undefined) {\n this.manipulationDiv = document.createElement('div');\n this.manipulationDiv.className = 'vis-manipulation';\n if (this.editMode === true) {\n this.manipulationDiv.style.display = 'block';\n } else {\n this.manipulationDiv.style.display = 'none';\n }\n this.canvas.frame.appendChild(this.manipulationDiv);\n }\n\n // container for the edit button.\n if (this.editModeDiv === undefined) {\n this.editModeDiv = document.createElement('div');\n this.editModeDiv.className = 'vis-edit-mode';\n if (this.editMode === true) {\n this.editModeDiv.style.display = 'none';\n } else {\n this.editModeDiv.style.display = 'block';\n }\n this.canvas.frame.appendChild(this.editModeDiv);\n }\n\n // container for the close div button\n if (this.closeDiv === undefined) {\n this.closeDiv = document.createElement('div');\n this.closeDiv.className = 'vis-close';\n this.closeDiv.style.display = this.manipulationDiv.style.display;\n this.canvas.frame.appendChild(this.closeDiv);\n }\n }\n\n /**\n * generate a new target node. Used for creating new edges and editing edges\n * @param x\n * @param y\n * @returns {*}\n * @private\n */\n }, {\n key: '_getNewTargetNode',\n value: function _getNewTargetNode(x, y) {\n var controlNodeStyle = util.deepExtend({}, this.options.controlNodeStyle);\n\n controlNodeStyle.id = 'targetNode' + util.randomUUID();\n controlNodeStyle.hidden = false;\n controlNodeStyle.physics = false;\n controlNodeStyle.x = x;\n controlNodeStyle.y = y;\n\n // we have to define the bounding box in order for the nodes to be drawn immediately\n var node = this.body.functions.createNode(controlNodeStyle);\n node.shape.boundingBox = { left: x, right: x, top: y, bottom: y };\n\n return node;\n }\n\n /**\n * Create the edit button\n */\n }, {\n key: '_createEditButton',\n value: function _createEditButton() {\n // restore everything to it's original state (if applicable)\n this._clean();\n\n // reset the manipulationDOM\n this.manipulationDOM = {};\n\n // empty the editModeDiv\n util.recursiveDOMDelete(this.editModeDiv);\n\n // create the contents for the editMode button\n var locale = this.options.locales[this.options.locale];\n var button = this._createButton('editMode', 'vis-button vis-edit vis-edit-mode', locale['edit'] || this.options.locales['en']['edit']);\n this.editModeDiv.appendChild(button);\n\n // bind a hammer listener to the button, calling the function toggleEditMode.\n this._bindHammerToDiv(button, this.toggleEditMode.bind(this));\n }\n\n /**\n * this function cleans up after everything this module does. Temporary elements, functions and events are removed, physics restored, hammers removed.\n * @private\n */\n }, {\n key: '_clean',\n value: function _clean() {\n // not in mode\n this.inMode = false;\n\n // _clean the divs\n if (this.guiEnabled === true) {\n util.recursiveDOMDelete(this.editModeDiv);\n util.recursiveDOMDelete(this.manipulationDiv);\n\n // removes all the bindings and overloads\n this._cleanManipulatorHammers();\n }\n\n // remove temporary nodes and edges\n this._cleanupTemporaryNodesAndEdges();\n\n // restore overloaded UI functions\n this._unbindTemporaryUIs();\n\n // remove the temporaryEventFunctions\n this._unbindTemporaryEvents();\n\n // restore the physics if required\n this.body.emitter.emit('restorePhysics');\n }\n\n /**\n * Each dom element has it's own hammer. They are stored in this.manipulationHammers. This cleans them up.\n * @private\n */\n }, {\n key: '_cleanManipulatorHammers',\n value: function _cleanManipulatorHammers() {\n // _clean hammer bindings\n if (this.manipulationHammers.length != 0) {\n for (var i = 0; i < this.manipulationHammers.length; i++) {\n this.manipulationHammers[i].destroy();\n }\n this.manipulationHammers = [];\n }\n }\n\n /**\n * Remove all DOM elements created by this module.\n * @private\n */\n }, {\n key: '_removeManipulationDOM',\n value: function _removeManipulationDOM() {\n // removes all the bindings and overloads\n this._clean();\n\n // empty the manipulation divs\n util.recursiveDOMDelete(this.manipulationDiv);\n util.recursiveDOMDelete(this.editModeDiv);\n util.recursiveDOMDelete(this.closeDiv);\n\n // remove the manipulation divs\n if (this.manipulationDiv) {\n this.canvas.frame.removeChild(this.manipulationDiv);\n }\n if (this.editModeDiv) {\n this.canvas.frame.removeChild(this.editModeDiv);\n }\n if (this.closeDiv) {\n this.canvas.frame.removeChild(this.closeDiv);\n }\n\n // set the references to undefined\n this.manipulationDiv = undefined;\n this.editModeDiv = undefined;\n this.closeDiv = undefined;\n }\n\n /**\n * create a seperator line. the index is to differentiate in the manipulation dom\n * @param index\n * @private\n */\n }, {\n key: '_createSeperator',\n value: function _createSeperator() {\n var index = arguments.length <= 0 || arguments[0] === undefined ? 1 : arguments[0];\n\n this.manipulationDOM['seperatorLineDiv' + index] = document.createElement('div');\n this.manipulationDOM['seperatorLineDiv' + index].className = 'vis-separator-line';\n this.manipulationDiv.appendChild(this.manipulationDOM['seperatorLineDiv' + index]);\n }\n\n // ---------------------- DOM functions for buttons --------------------------//\n\n }, {\n key: '_createAddNodeButton',\n value: function _createAddNodeButton(locale) {\n var button = this._createButton('addNode', 'vis-button vis-add', locale['addNode'] || this.options.locales['en']['addNode']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.addNodeMode.bind(this));\n }\n }, {\n key: '_createAddEdgeButton',\n value: function _createAddEdgeButton(locale) {\n var button = this._createButton('addEdge', 'vis-button vis-connect', locale['addEdge'] || this.options.locales['en']['addEdge']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.addEdgeMode.bind(this));\n }\n }, {\n key: '_createEditNodeButton',\n value: function _createEditNodeButton(locale) {\n var button = this._createButton('editNode', 'vis-button vis-edit', locale['editNode'] || this.options.locales['en']['editNode']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.editNode.bind(this));\n }\n }, {\n key: '_createEditEdgeButton',\n value: function _createEditEdgeButton(locale) {\n var button = this._createButton('editEdge', 'vis-button vis-edit', locale['editEdge'] || this.options.locales['en']['editEdge']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.editEdgeMode.bind(this));\n }\n }, {\n key: '_createDeleteButton',\n value: function _createDeleteButton(locale) {\n var button = this._createButton('delete', 'vis-button vis-delete', locale['del'] || this.options.locales['en']['del']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.deleteSelected.bind(this));\n }\n }, {\n key: '_createBackButton',\n value: function _createBackButton(locale) {\n var button = this._createButton('back', 'vis-button vis-back', locale['back'] || this.options.locales['en']['back']);\n this.manipulationDiv.appendChild(button);\n this._bindHammerToDiv(button, this.showManipulatorToolbar.bind(this));\n }\n }, {\n key: '_createButton',\n value: function _createButton(id, className, label) {\n var labelClassName = arguments.length <= 3 || arguments[3] === undefined ? 'vis-label' : arguments[3];\n\n this.manipulationDOM[id + 'Div'] = document.createElement('div');\n this.manipulationDOM[id + 'Div'].className = className;\n this.manipulationDOM[id + 'Label'] = document.createElement('div');\n this.manipulationDOM[id + 'Label'].className = labelClassName;\n this.manipulationDOM[id + 'Label'].innerHTML = label;\n this.manipulationDOM[id + 'Div'].appendChild(this.manipulationDOM[id + 'Label']);\n return this.manipulationDOM[id + 'Div'];\n }\n }, {\n key: '_createDescription',\n value: function _createDescription(label) {\n this.manipulationDiv.appendChild(this._createButton('description', 'vis-button vis-none', label));\n }\n\n // -------------------------- End of DOM functions for buttons ------------------------------//\n\n /**\n * this binds an event until cleanup by the clean functions.\n * @param event\n * @param newFunction\n * @private\n */\n }, {\n key: '_temporaryBindEvent',\n value: function _temporaryBindEvent(event, newFunction) {\n this.temporaryEventFunctions.push({ event: event, boundFunction: newFunction });\n this.body.emitter.on(event, newFunction);\n }\n\n /**\n * this overrides an UI function until cleanup by the clean function\n * @param UIfunctionName\n * @param newFunction\n * @private\n */\n }, {\n key: '_temporaryBindUI',\n value: function _temporaryBindUI(UIfunctionName, newFunction) {\n if (this.body.eventListeners[UIfunctionName] !== undefined) {\n this.temporaryUIFunctions[UIfunctionName] = this.body.eventListeners[UIfunctionName];\n this.body.eventListeners[UIfunctionName] = newFunction;\n } else {\n throw new Error('This UI function does not exist. Typo? You tried: ' + UIfunctionName + ' possible are: ' + JSON.stringify(Object.keys(this.body.eventListeners)));\n }\n }\n\n /**\n * Restore the overridden UI functions to their original state.\n *\n * @private\n */\n }, {\n key: '_unbindTemporaryUIs',\n value: function _unbindTemporaryUIs() {\n for (var functionName in this.temporaryUIFunctions) {\n if (this.temporaryUIFunctions.hasOwnProperty(functionName)) {\n this.body.eventListeners[functionName] = this.temporaryUIFunctions[functionName];\n delete this.temporaryUIFunctions[functionName];\n }\n }\n this.temporaryUIFunctions = {};\n }\n\n /**\n * Unbind the events created by _temporaryBindEvent\n * @private\n */\n }, {\n key: '_unbindTemporaryEvents',\n value: function _unbindTemporaryEvents() {\n for (var i = 0; i < this.temporaryEventFunctions.length; i++) {\n var eventName = this.temporaryEventFunctions[i].event;\n var boundFunction = this.temporaryEventFunctions[i].boundFunction;\n this.body.emitter.off(eventName, boundFunction);\n }\n this.temporaryEventFunctions = [];\n }\n\n /**\n * Bind an hammer instance to a DOM element.\n * @param domElement\n * @param funct\n */\n }, {\n key: '_bindHammerToDiv',\n value: function _bindHammerToDiv(domElement, boundFunction) {\n var hammer = new Hammer(domElement, {});\n hammerUtil.onTouch(hammer, boundFunction);\n this.manipulationHammers.push(hammer);\n }\n\n /**\n * Neatly clean up temporary edges and nodes\n * @private\n */\n }, {\n key: '_cleanupTemporaryNodesAndEdges',\n value: function _cleanupTemporaryNodesAndEdges() {\n // _clean temporary edges\n for (var i = 0; i < this.temporaryIds.edges.length; i++) {\n this.body.edges[this.temporaryIds.edges[i]].disconnect();\n delete this.body.edges[this.temporaryIds.edges[i]];\n var indexTempEdge = this.body.edgeIndices.indexOf(this.temporaryIds.edges[i]);\n if (indexTempEdge !== -1) {\n this.body.edgeIndices.splice(indexTempEdge, 1);\n }\n }\n\n // _clean temporary nodes\n for (var i = 0; i < this.temporaryIds.nodes.length; i++) {\n delete this.body.nodes[this.temporaryIds.nodes[i]];\n var indexTempNode = this.body.nodeIndices.indexOf(this.temporaryIds.nodes[i]);\n if (indexTempNode !== -1) {\n this.body.nodeIndices.splice(indexTempNode, 1);\n }\n }\n\n this.temporaryIds = { nodes: [], edges: [] };\n }\n\n // ------------------------------------------ EDIT EDGE FUNCTIONS -----------------------------------------//\n\n /**\n * the touch is used to get the position of the initial click\n * @param event\n * @private\n */\n }, {\n key: '_controlNodeTouch',\n value: function _controlNodeTouch(event) {\n this.selectionHandler.unselectAll();\n this.lastTouch = this.body.functions.getPointer(event.center);\n this.lastTouch.translation = util.extend({}, this.body.view.translation); // copy the object\n }\n\n /**\n * the drag start is used to mark one of the control nodes as selected.\n * @param event\n * @private\n */\n }, {\n key: '_controlNodeDragStart',\n value: function _controlNodeDragStart(event) {\n var pointer = this.lastTouch;\n var pointerObj = this.selectionHandler._pointerToPositionObject(pointer);\n var from = this.body.nodes[this.temporaryIds.nodes[0]];\n var to = this.body.nodes[this.temporaryIds.nodes[1]];\n var edge = this.body.edges[this.edgeBeingEditedId];\n this.selectedControlNode = undefined;\n\n var fromSelect = from.isOverlappingWith(pointerObj);\n var toSelect = to.isOverlappingWith(pointerObj);\n\n if (fromSelect === true) {\n this.selectedControlNode = from;\n edge.edgeType.from = from;\n } else if (toSelect === true) {\n this.selectedControlNode = to;\n edge.edgeType.to = to;\n }\n\n this.body.emitter.emit('_redraw');\n }\n\n /**\n * dragging the control nodes or the canvas\n * @param event\n * @private\n */\n }, {\n key: '_controlNodeDrag',\n value: function _controlNodeDrag(event) {\n this.body.emitter.emit('disablePhysics');\n var pointer = this.body.functions.getPointer(event.center);\n var pos = this.canvas.DOMtoCanvas(pointer);\n\n if (this.selectedControlNode !== undefined) {\n this.selectedControlNode.x = pos.x;\n this.selectedControlNode.y = pos.y;\n } else {\n // if the drag was not started properly because the click started outside the network div, start it now.\n var diffX = pointer.x - this.lastTouch.x;\n var diffY = pointer.y - this.lastTouch.y;\n this.body.view.translation = { x: this.lastTouch.translation.x + diffX, y: this.lastTouch.translation.y + diffY };\n }\n this.body.emitter.emit('_redraw');\n }\n\n /**\n * connecting or restoring the control nodes.\n * @param event\n * @private\n */\n }, {\n key: '_controlNodeDragEnd',\n value: function _controlNodeDragEnd(event) {\n var pointer = this.body.functions.getPointer(event.center);\n var pointerObj = this.selectionHandler._pointerToPositionObject(pointer);\n var edge = this.body.edges[this.edgeBeingEditedId];\n\n // if the node that was dragged is not a control node, return\n if (this.selectedControlNode === undefined) {\n return;\n }\n\n var overlappingNodeIds = this.selectionHandler._getAllNodesOverlappingWith(pointerObj);\n var node = undefined;\n for (var i = overlappingNodeIds.length - 1; i >= 0; i--) {\n if (overlappingNodeIds[i] !== this.selectedControlNode.id) {\n node = this.body.nodes[overlappingNodeIds[i]];\n break;\n }\n }\n\n // perform the connection\n if (node !== undefined && this.selectedControlNode !== undefined) {\n if (node.isCluster === true) {\n alert(this.options.locales[this.options.locale]['createEdgeError'] || this.options.locales['en']['createEdgeError']);\n } else {\n var from = this.body.nodes[this.temporaryIds.nodes[0]];\n if (this.selectedControlNode.id === from.id) {\n this._performEditEdge(node.id, edge.to.id);\n } else {\n this._performEditEdge(edge.from.id, node.id);\n }\n }\n } else {\n edge.updateEdgeType();\n this.body.emitter.emit('restorePhysics');\n }\n this.body.emitter.emit('_redraw');\n }\n\n // ------------------------------------ END OF EDIT EDGE FUNCTIONS -----------------------------------------//\n\n // ------------------------------------------- ADD EDGE FUNCTIONS -----------------------------------------//\n /**\n * the function bound to the selection event. It checks if you want to connect a cluster and changes the description\n * to walk the user through the process.\n *\n * @private\n */\n }, {\n key: '_handleConnect',\n value: function _handleConnect(event) {\n // check to avoid double fireing of this function.\n if (new Date().valueOf() - this.touchTime > 100) {\n this.lastTouch = this.body.functions.getPointer(event.center);\n this.lastTouch.translation = util.extend({}, this.body.view.translation); // copy the object\n\n var pointer = this.lastTouch;\n var node = this.selectionHandler.getNodeAt(pointer);\n\n if (node !== undefined) {\n if (node.isCluster === true) {\n alert(this.options.locales[this.options.locale]['createEdgeError'] || this.options.locales['en']['createEdgeError']);\n } else {\n // create a node the temporary line can look at\n var targetNode = this._getNewTargetNode(node.x, node.y);\n this.body.nodes[targetNode.id] = targetNode;\n this.body.nodeIndices.push(targetNode.id);\n\n // create a temporary edge\n var connectionEdge = this.body.functions.createEdge({\n id: 'connectionEdge' + util.randomUUID(),\n from: node.id,\n to: targetNode.id,\n physics: false,\n smooth: {\n enabled: true,\n type: 'continuous',\n roundness: 0.5\n }\n });\n this.body.edges[connectionEdge.id] = connectionEdge;\n this.body.edgeIndices.push(connectionEdge.id);\n\n this.temporaryIds.nodes.push(targetNode.id);\n this.temporaryIds.edges.push(connectionEdge.id);\n }\n }\n this.touchTime = new Date().valueOf();\n }\n }\n }, {\n key: '_dragControlNode',\n value: function _dragControlNode(event) {\n var pointer = this.body.functions.getPointer(event.center);\n if (this.temporaryIds.nodes[0] !== undefined) {\n var targetNode = this.body.nodes[this.temporaryIds.nodes[0]]; // there is only one temp node in the add edge mode.\n targetNode.x = this.canvas._XconvertDOMtoCanvas(pointer.x);\n targetNode.y = this.canvas._YconvertDOMtoCanvas(pointer.y);\n this.body.emitter.emit('_redraw');\n } else {\n var diffX = pointer.x - this.lastTouch.x;\n var diffY = pointer.y - this.lastTouch.y;\n this.body.view.translation = { x: this.lastTouch.translation.x + diffX, y: this.lastTouch.translation.y + diffY };\n }\n }\n\n /**\n * Connect the new edge to the target if one exists, otherwise remove temp line\n * @param event\n * @private\n */\n }, {\n key: '_finishConnect',\n value: function _finishConnect(event) {\n var pointer = this.body.functions.getPointer(event.center);\n var pointerObj = this.selectionHandler._pointerToPositionObject(pointer);\n\n // remember the edge id\n var connectFromId = undefined;\n if (this.temporaryIds.edges[0] !== undefined) {\n connectFromId = this.body.edges[this.temporaryIds.edges[0]].fromId;\n }\n\n // get the overlapping node but NOT the temporary node;\n var overlappingNodeIds = this.selectionHandler._getAllNodesOverlappingWith(pointerObj);\n var node = undefined;\n for (var i = overlappingNodeIds.length - 1; i >= 0; i--) {\n // if the node id is NOT a temporary node, accept the node.\n if (this.temporaryIds.nodes.indexOf(overlappingNodeIds[i]) === -1) {\n node = this.body.nodes[overlappingNodeIds[i]];\n break;\n }\n }\n\n // clean temporary nodes and edges.\n this._cleanupTemporaryNodesAndEdges();\n\n // perform the connection\n if (node !== undefined) {\n if (node.isCluster === true) {\n alert(this.options.locales[this.options.locale]['createEdgeError'] || this.options.locales['en']['createEdgeError']);\n } else {\n if (this.body.nodes[connectFromId] !== undefined && this.body.nodes[node.id] !== undefined) {\n this._performAddEdge(connectFromId, node.id);\n }\n }\n }\n this.body.emitter.emit('_redraw');\n }\n\n // --------------------------------------- END OF ADD EDGE FUNCTIONS -------------------------------------//\n\n // ------------------------------ Performing all the actual data manipulation ------------------------//\n\n /**\n * Adds a node on the specified location\n */\n }, {\n key: '_performAddNode',\n value: function _performAddNode(clickData) {\n var _this5 = this;\n\n var defaultData = {\n id: util.randomUUID(),\n x: clickData.pointer.canvas.x,\n y: clickData.pointer.canvas.y,\n label: 'new'\n };\n\n if (typeof this.options.addNode === 'function') {\n if (this.options.addNode.length === 2) {\n this.options.addNode(defaultData, function (finalizedData) {\n if (finalizedData !== null && finalizedData !== undefined && _this5.inMode === 'addNode') {\n // if for whatever reason the mode has changes (due to dataset change) disregard the callback\n _this5.body.data.nodes.getDataSet().add(finalizedData);\n _this5.showManipulatorToolbar();\n }\n });\n } else {\n throw new Error('The function for add does not support two arguments (data,callback)');\n this.showManipulatorToolbar();\n }\n } else {\n this.body.data.nodes.getDataSet().add(defaultData);\n this.showManipulatorToolbar();\n }\n }\n\n /**\n * connect two nodes with a new edge.\n *\n * @private\n */\n }, {\n key: '_performAddEdge',\n value: function _performAddEdge(sourceNodeId, targetNodeId) {\n var _this6 = this;\n\n var defaultData = { from: sourceNodeId, to: targetNodeId };\n if (typeof this.options.addEdge === 'function') {\n if (this.options.addEdge.length === 2) {\n this.options.addEdge(defaultData, function (finalizedData) {\n if (finalizedData !== null && finalizedData !== undefined && _this6.inMode === 'addEdge') {\n // if for whatever reason the mode has changes (due to dataset change) disregard the callback\n _this6.body.data.edges.getDataSet().add(finalizedData);\n _this6.selectionHandler.unselectAll();\n _this6.showManipulatorToolbar();\n }\n });\n } else {\n throw new Error('The function for connect does not support two arguments (data,callback)');\n }\n } else {\n this.body.data.edges.getDataSet().add(defaultData);\n this.selectionHandler.unselectAll();\n this.showManipulatorToolbar();\n }\n }\n\n /**\n * connect two nodes with a new edge.\n *\n * @private\n */\n }, {\n key: '_performEditEdge',\n value: function _performEditEdge(sourceNodeId, targetNodeId) {\n var _this7 = this;\n\n var defaultData = { id: this.edgeBeingEditedId, from: sourceNodeId, to: targetNodeId };\n if (typeof this.options.editEdge === 'function') {\n if (this.options.editEdge.length === 2) {\n this.options.editEdge(defaultData, function (finalizedData) {\n if (finalizedData === null || finalizedData === undefined || _this7.inMode !== 'editEdge') {\n // if for whatever reason the mode has changes (due to dataset change) disregard the callback) {\n _this7.body.edges[defaultData.id].updateEdgeType();\n _this7.body.emitter.emit('_redraw');\n } else {\n _this7.body.data.edges.getDataSet().update(finalizedData);\n _this7.selectionHandler.unselectAll();\n _this7.showManipulatorToolbar();\n }\n });\n } else {\n throw new Error('The function for edit does not support two arguments (data, callback)');\n }\n } else {\n this.body.data.edges.getDataSet().update(defaultData);\n this.selectionHandler.unselectAll();\n this.showManipulatorToolbar();\n }\n }\n }]);\n\n return ManipulationSystem;\n })();\n\n exports['default'] = ManipulationSystem;\n module.exports = exports['default'];\n\n/***/ },\n/* 110 */\n/***/ function(module, exports) {\n\n /**\n * This object contains all possible options. It will check if the types are correct, if required if the option is one\n * of the allowed values.\n *\n * __any__ means that the name of the property does not matter.\n * __type__ is a required field for all objects and contains the allowed types of all objects\n */\n 'use strict';\n\n Object.defineProperty(exports, '__esModule', {\n value: true\n });\n var string = 'string';\n var boolean = 'boolean';\n var number = 'number';\n var array = 'array';\n var object = 'object'; // should only be in a __type__ property\n var dom = 'dom';\n var any = 'any';\n\n var allOptions = {\n configure: {\n enabled: { boolean: boolean },\n filter: { boolean: boolean, string: string, array: array, 'function': 'function' },\n container: { dom: dom },\n showButton: { boolean: boolean },\n __type__: { object: object, boolean: boolean, string: string, array: array, 'function': 'function' }\n },\n edges: {\n arrows: {\n to: { enabled: { boolean: boolean }, scaleFactor: { number: number }, __type__: { object: object, boolean: boolean } },\n middle: { enabled: { boolean: boolean }, scaleFactor: { number: number }, __type__: { object: object, boolean: boolean } },\n from: { enabled: { boolean: boolean }, scaleFactor: { number: number }, __type__: { object: object, boolean: boolean } },\n __type__: { string: ['from', 'to', 'middle'], object: object }\n },\n arrowStrikethrough: { boolean: boolean },\n color: {\n color: { string: string },\n highlight: { string: string },\n hover: { string: string },\n inherit: { string: ['from', 'to', 'both'], boolean: boolean },\n opacity: { number: number },\n __type__: { object: object, string: string }\n },\n dashes: { boolean: boolean, array: array },\n font: {\n color: { string: string },\n size: { number: number }, // px\n face: { string: string },\n background: { string: string },\n strokeWidth: { number: number }, // px\n strokeColor: { string: string },\n align: { string: ['horizontal', 'top', 'middle', 'bottom'] },\n __type__: { object: object, string: string }\n },\n hidden: { boolean: boolean },\n hoverWidth: { 'function': 'function', number: number },\n label: { string: string, 'undefined': 'undefined' },\n labelHighlightBold: { boolean: boolean },\n length: { number: number, 'undefined': 'undefined' },\n physics: { boolean: boolean },\n scaling: {\n min: { number: number },\n max: { number: number },\n label: {\n enabled: { boolean: boolean },\n min: { number: number },\n max: { number: number },\n maxVisible: { number: number },\n drawThreshold: { number: number },\n __type__: { object: object, boolean: boolean }\n },\n customScalingFunction: { 'function': 'function' },\n __type__: { object: object }\n },\n selectionWidth: { 'function': 'function', number: number },\n selfReferenceSize: { number: number },\n shadow: {\n enabled: { boolean: boolean },\n color: { string: string },\n size: { number: number },\n x: { number: number },\n y: { number: number },\n __type__: { object: object, boolean: boolean }\n },\n smooth: {\n enabled: { boolean: boolean },\n type: { string: ['dynamic', 'continuous', 'discrete', 'diagonalCross', 'straightCross', 'horizontal', 'vertical', 'curvedCW', 'curvedCCW', 'cubicBezier'] },\n roundness: { number: number },\n forceDirection: { string: ['horizontal', 'vertical', 'none'], boolean: boolean },\n __type__: { object: object, boolean: boolean }\n },\n title: { string: string, 'undefined': 'undefined' },\n width: { number: number },\n value: { number: number, 'undefined': 'undefined' },\n __type__: { object: object }\n },\n groups: {\n useDefaultGroups: { boolean: boolean },\n __any__: 'get from nodes, will be overwritten below',\n __type__: { object: object }\n },\n interaction: {\n dragNodes: { boolean: boolean },\n dragView: { boolean: boolean },\n hideEdgesOnDrag: { boolean: boolean },\n hideNodesOnDrag: { boolean: boolean },\n hover: { boolean: boolean },\n keyboard: {\n enabled: { boolean: boolean },\n speed: { x: { number: number }, y: { number: number }, zoom: { number: number }, __type__: { object: object } },\n bindToWindow: { boolean: boolean },\n __type__: { object: object, boolean: boolean }\n },\n multiselect: { boolean: boolean },\n navigationButtons: { boolean: boolean },\n selectable: { boolean: boolean },\n selectConnectedEdges: { boolean: boolean },\n hoverConnectedEdges: { boolean: boolean },\n tooltipDelay: { number: number },\n zoomView: { boolean: boolean },\n __type__: { object: object }\n },\n layout: {\n randomSeed: { 'undefined': 'undefined', number: number },\n improvedLayout: { boolean: boolean },\n hierarchical: {\n enabled: { boolean: boolean },\n levelSeparation: { number: number },\n nodeSpacing: { number: number },\n treeSpacing: { number: number },\n blockShifting: { boolean: boolean },\n edgeMinimization: { boolean: boolean },\n direction: { string: ['UD', 'DU', 'LR', 'RL'] }, // UD, DU, LR, RL\n sortMethod: { string: ['hubsize', 'directed'] }, // hubsize, directed\n __type__: { object: object, boolean: boolean }\n },\n __type__: { object: object }\n },\n manipulation: {\n enabled: { boolean: boolean },\n initiallyActive: { boolean: boolean },\n addNode: { boolean: boolean, 'function': 'function' },\n addEdge: { boolean: boolean, 'function': 'function' },\n editNode: { 'function': 'function' },\n editEdge: { boolean: boolean, 'function': 'function' },\n deleteNode: { boolean: boolean, 'function': 'function' },\n deleteEdge: { boolean: boolean, 'function': 'function' },\n controlNodeStyle: 'get from nodes, will be overwritten below',\n __type__: { object: object, boolean: boolean }\n },\n nodes: {\n borderWidth: { number: number },\n borderWidthSelected: { number: number, 'undefined': 'undefined' },\n brokenImage: { string: string, 'undefined': 'undefined' },\n color: {\n border: { string: string },\n background: { string: string },\n highlight: {\n border: { string: string },\n background: { string: string },\n __type__: { object: object, string: string }\n },\n hover: {\n border: { string: string },\n background: { string: string },\n __type__: { object: object, string: string }\n },\n __type__: { object: object, string: string }\n },\n fixed: {\n x: { boolean: boolean },\n y: { boolean: boolean },\n __type__: { object: object, boolean: boolean }\n },\n font: {\n color: { string: string },\n size: { number: number }, // px\n face: { string: string },\n background: { string: string },\n strokeWidth: { number: number }, // px\n strokeColor: { string: string },\n __type__: { object: object, string: string }\n },\n group: { string: string, number: number, 'undefined': 'undefined' },\n hidden: { boolean: boolean },\n icon: {\n face: { string: string },\n code: { string: string }, //'\\uf007',\n size: { number: number }, //50,\n color: { string: string },\n __type__: { object: object }\n },\n id: { string: string, number: number },\n image: { string: string, 'undefined': 'undefined' }, // --> URL\n label: { string: string, 'undefined': 'undefined' },\n labelHighlightBold: { boolean: boolean },\n level: { number: number, 'undefined': 'undefined' },\n mass: { number: number },\n physics: { boolean: boolean },\n scaling: {\n min: { number: number },\n max: { number: number },\n label: {\n enabled: { boolean: boolean },\n min: { number: number },\n max: { number: number },\n maxVisible: { number: number },\n drawThreshold: { number: number },\n __type__: { object: object, boolean: boolean }\n },\n customScalingFunction: { 'function': 'function' },\n __type__: { object: object }\n },\n shadow: {\n enabled: { boolean: boolean },\n color: { string: string },\n size: { number: number },\n x: { number: number },\n y: { number: number },\n __type__: { object: object, boolean: boolean }\n },\n shape: { string: ['ellipse', 'circle', 'database', 'box', 'text', 'image', 'circularImage', 'diamond', 'dot', 'star', 'triangle', 'triangleDown', 'square', 'icon'] },\n shapeProperties: {\n borderDashes: { boolean: boolean, array: array },\n borderRadius: { number: number },\n useImageSize: { boolean: boolean },\n useBorderWithImage: { boolean: boolean },\n __type__: { object: object }\n },\n size: { number: number },\n title: { string: string, 'undefined': 'undefined' },\n value: { number: number, 'undefined': 'undefined' },\n x: { number: number },\n y: { number: number },\n __type__: { object: object }\n },\n physics: {\n enabled: { boolean: boolean },\n barnesHut: {\n gravitationalConstant: { number: number },\n centralGravity: { number: number },\n springLength: { number: number },\n springConstant: { number: number },\n damping: { number: number },\n avoidOverlap: { number: number },\n __type__: { object: object }\n },\n forceAtlas2Based: {\n gravitationalConstant: { number: number },\n centralGravity: { number: number },\n springLength: { number: number },\n springConstant: { number: number },\n damping: { number: number },\n avoidOverlap: { number: number },\n __type__: { object: object }\n },\n repulsion: {\n centralGravity: { number: number },\n springLength: { number: number },\n springConstant: { number: number },\n nodeDistance: { number: number },\n damping: { number: number },\n __type__: { object: object }\n },\n hierarchicalRepulsion: {\n centralGravity: { number: number },\n springLength: { number: number },\n springConstant: { number: number },\n nodeDistance: { number: number },\n damping: { number: number },\n __type__: { object: object }\n },\n maxVelocity: { number: number },\n minVelocity: { number: number }, // px/s\n solver: { string: ['barnesHut', 'repulsion', 'hierarchicalRepulsion', 'forceAtlas2Based'] },\n stabilization: {\n enabled: { boolean: boolean },\n iterations: { number: number }, // maximum number of iteration to stabilize\n updateInterval: { number: number },\n onlyDynamicEdges: { boolean: boolean },\n fit: { boolean: boolean },\n __type__: { object: object, boolean: boolean }\n },\n timestep: { number: number },\n adaptiveTimestep: { boolean: boolean },\n __type__: { object: object, boolean: boolean }\n },\n\n //globals :\n autoResize: { boolean: boolean },\n clickToUse: { boolean: boolean },\n locale: { string: string },\n locales: {\n __any__: { any: any },\n __type__: { object: object }\n },\n height: { string: string },\n width: { string: string },\n __type__: { object: object }\n };\n\n allOptions.groups.__any__ = allOptions.nodes;\n allOptions.manipulation.controlNodeStyle = allOptions.nodes;\n\n var configureOptions = {\n nodes: {\n borderWidth: [1, 0, 10, 1],\n borderWidthSelected: [2, 0, 10, 1],\n color: {\n border: ['color', '#2B7CE9'],\n background: ['color', '#97C2FC'],\n highlight: {\n border: ['color', '#2B7CE9'],\n background: ['color', '#D2E5FF']\n },\n hover: {\n border: ['color', '#2B7CE9'],\n background: ['color', '#D2E5FF']\n }\n },\n fixed: {\n x: false,\n y: false\n },\n font: {\n color: ['color', '#343434'],\n size: [14, 0, 100, 1], // px\n face: ['arial', 'verdana', 'tahoma'],\n background: ['color', 'none'],\n strokeWidth: [0, 0, 50, 1], // px\n strokeColor: ['color', '#ffffff']\n },\n //group: 'string',\n hidden: false,\n labelHighlightBold: true,\n //icon: {\n // face: 'string', //'FontAwesome',\n // code: 'string', //'\\uf007',\n // size: [50, 0, 200, 1], //50,\n // color: ['color','#2B7CE9'] //'#aa00ff'\n //},\n //image: 'string', // --> URL\n physics: true,\n scaling: {\n min: [10, 0, 200, 1],\n max: [30, 0, 200, 1],\n label: {\n enabled: false,\n min: [14, 0, 200, 1],\n max: [30, 0, 200, 1],\n maxVisible: [30, 0, 200, 1],\n drawThreshold: [5, 0, 20, 1]\n }\n },\n shadow: {\n enabled: false,\n color: 'rgba(0,0,0,0.5)',\n size: [10, 0, 20, 1],\n x: [5, -30, 30, 1],\n y: [5, -30, 30, 1]\n },\n shape: ['ellipse', 'box', 'circle', 'database', 'diamond', 'dot', 'square', 'star', 'text', 'triangle', 'triangleDown'],\n shapeProperties: {\n borderDashes: false,\n borderRadius: [6, 0, 20, 1],\n useImageSize: false\n },\n size: [25, 0, 200, 1]\n },\n edges: {\n arrows: {\n to: { enabled: false, scaleFactor: [1, 0, 3, 0.05] }, // boolean / {arrowScaleFactor:1} / {enabled: false, arrowScaleFactor:1}\n middle: { enabled: false, scaleFactor: [1, 0, 3, 0.05] },\n from: { enabled: false, scaleFactor: [1, 0, 3, 0.05] }\n },\n arrowStrikethrough: true,\n color: {\n color: ['color', '#848484'],\n highlight: ['color', '#848484'],\n hover: ['color', '#848484'],\n inherit: ['from', 'to', 'both', true, false],\n opacity: [1, 0, 1, 0.05]\n },\n dashes: false,\n font: {\n color: ['color', '#343434'],\n size: [14, 0, 100, 1], // px\n face: ['arial', 'verdana', 'tahoma'],\n background: ['color', 'none'],\n strokeWidth: [2, 0, 50, 1], // px\n strokeColor: ['color', '#ffffff'],\n align: ['horizontal', 'top', 'middle', 'bottom']\n },\n hidden: false,\n hoverWidth: [1.5, 0, 5, 0.1],\n labelHighlightBold: true,\n physics: true,\n scaling: {\n min: [1, 0, 100, 1],\n max: [15, 0, 100, 1],\n label: {\n enabled: true,\n min: [14, 0, 200, 1],\n max: [30, 0, 200, 1],\n maxVisible: [30, 0, 200, 1],\n drawThreshold: [5, 0, 20, 1]\n }\n },\n selectionWidth: [1.5, 0, 5, 0.1],\n selfReferenceSize: [20, 0, 200, 1],\n shadow: {\n enabled: false,\n color: 'rgba(0,0,0,0.5)',\n size: [10, 0, 20, 1],\n x: [5, -30, 30, 1],\n y: [5, -30, 30, 1]\n },\n smooth: {\n enabled: true,\n type: ['dynamic', 'continuous', 'discrete', 'diagonalCross', 'straightCross', 'horizontal', 'vertical', 'curvedCW', 'curvedCCW', 'cubicBezier'],\n forceDirection: ['horizontal', 'vertical', 'none'],\n roundness: [0.5, 0, 1, 0.05]\n },\n width: [1, 0, 30, 1]\n },\n layout: {\n //randomSeed: [0, 0, 500, 1],\n //improvedLayout: true,\n hierarchical: {\n enabled: false,\n levelSeparation: [150, 20, 500, 5],\n nodeSpacing: [100, 20, 500, 5],\n treeSpacing: [200, 20, 500, 5],\n blockShifting: true,\n edgeMinimization: true,\n direction: ['UD', 'DU', 'LR', 'RL'], // UD, DU, LR, RL\n sortMethod: ['hubsize', 'directed'] // hubsize, directed\n }\n },\n interaction: {\n dragNodes: true,\n dragView: true,\n hideEdgesOnDrag: false,\n hideNodesOnDrag: false,\n hover: false,\n keyboard: {\n enabled: false,\n speed: { x: [10, 0, 40, 1], y: [10, 0, 40, 1], zoom: [0.02, 0, 0.1, 0.005] },\n bindToWindow: true\n },\n multiselect: false,\n navigationButtons: false,\n selectable: true,\n selectConnectedEdges: true,\n hoverConnectedEdges: true,\n tooltipDelay: [300, 0, 1000, 25],\n zoomView: true\n },\n manipulation: {\n enabled: false,\n initiallyActive: false\n },\n physics: {\n enabled: true,\n barnesHut: {\n //theta: [0.5, 0.1, 1, 0.05],\n gravitationalConstant: [-2000, -30000, 0, 50],\n centralGravity: [0.3, 0, 10, 0.05],\n springLength: [95, 0, 500, 5],\n springConstant: [0.04, 0, 1.2, 0.005],\n damping: [0.09, 0, 1, 0.01],\n avoidOverlap: [0, 0, 1, 0.01]\n },\n forceAtlas2Based: {\n //theta: [0.5, 0.1, 1, 0.05],\n gravitationalConstant: [-50, -500, 0, 1],\n centralGravity: [0.01, 0, 1, 0.005],\n springLength: [95, 0, 500, 5],\n springConstant: [0.08, 0, 1.2, 0.005],\n damping: [0.4, 0, 1, 0.01],\n avoidOverlap: [0, 0, 1, 0.01]\n },\n repulsion: {\n centralGravity: [0.2, 0, 10, 0.05],\n springLength: [200, 0, 500, 5],\n springConstant: [0.05, 0, 1.2, 0.005],\n nodeDistance: [100, 0, 500, 5],\n damping: [0.09, 0, 1, 0.01]\n },\n hierarchicalRepulsion: {\n centralGravity: [0.2, 0, 10, 0.05],\n springLength: [100, 0, 500, 5],\n springConstant: [0.01, 0, 1.2, 0.005],\n nodeDistance: [120, 0, 500, 5],\n damping: [0.09, 0, 1, 0.01]\n },\n maxVelocity: [50, 0, 150, 1],\n minVelocity: [0.1, 0.01, 0.5, 0.01],\n solver: ['barnesHut', 'forceAtlas2Based', 'repulsion', 'hierarchicalRepulsion'],\n timestep: [0.5, 0.01, 1, 0.01]\n },\n //adaptiveTimestep: true\n global: {\n locale: ['en', 'nl']\n }\n };\n\n exports.allOptions = allOptions;\n exports.configureOptions = configureOptions;\n\n/***/ },\n/* 111 */\n/***/ function(module, exports, __webpack_require__) {\n\n // distance finding algorithm\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _slicedToArray = (function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i[\"return\"]) _i[\"return\"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError(\"Invalid attempt to destructure non-iterable instance\"); } }; })();\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { \"default\": obj }; }\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var _componentsAlgorithmsFloydWarshallJs = __webpack_require__(112);\n\n var _componentsAlgorithmsFloydWarshallJs2 = _interopRequireDefault(_componentsAlgorithmsFloydWarshallJs);\n\n /**\n * KamadaKawai positions the nodes initially based on\n *\n * \"AN ALGORITHM FOR DRAWING GENERAL UNDIRECTED GRAPHS\"\n * -- Tomihisa KAMADA and Satoru KAWAI in 1989\n *\n * Possible optimizations in the distance calculation can be implemented.\n */\n\n var KamadaKawai = (function () {\n function KamadaKawai(body, edgeLength, edgeStrength) {\n _classCallCheck(this, KamadaKawai);\n\n this.body = body;\n this.springLength = edgeLength;\n this.springConstant = edgeStrength;\n this.distanceSolver = new _componentsAlgorithmsFloydWarshallJs2[\"default\"]();\n }\n\n /**\n * Not sure if needed but can be used to update the spring length and spring constant\n * @param options\n */\n\n _createClass(KamadaKawai, [{\n key: \"setOptions\",\n value: function setOptions(options) {\n if (options) {\n if (options.springLength) {\n this.springLength = options.springLength;\n }\n if (options.springConstant) {\n this.springConstant = options.springConstant;\n }\n }\n }\n\n /**\n * Position the system\n * @param nodesArray\n * @param edgesArray\n */\n }, {\n key: \"solve\",\n value: function solve(nodesArray, edgesArray) {\n var ignoreClusters = arguments.length <= 2 || arguments[2] === undefined ? false : arguments[2];\n\n // get distance matrix\n var D_matrix = this.distanceSolver.getDistances(this.body, nodesArray, edgesArray); // distance matrix\n\n // get the L Matrix\n this._createL_matrix(D_matrix);\n\n // get the K Matrix\n this._createK_matrix(D_matrix);\n\n // calculate positions\n var threshold = 0.01;\n var innerThreshold = 1;\n var iterations = 0;\n var maxIterations = Math.max(1000, Math.min(10 * this.body.nodeIndices.length, 6000));\n var maxInnerIterations = 5;\n\n var maxEnergy = 1e9;\n var highE_nodeId = 0,\n dE_dx = 0,\n dE_dy = 0,\n delta_m = 0,\n subIterations = 0;\n\n while (maxEnergy > threshold && iterations < maxIterations) {\n iterations += 1;\n\n var _getHighestEnergyNode2 = this._getHighestEnergyNode(ignoreClusters);\n\n var _getHighestEnergyNode22 = _slicedToArray(_getHighestEnergyNode2, 4);\n\n highE_nodeId = _getHighestEnergyNode22[0];\n maxEnergy = _getHighestEnergyNode22[1];\n dE_dx = _getHighestEnergyNode22[2];\n dE_dy = _getHighestEnergyNode22[3];\n\n delta_m = maxEnergy;\n subIterations = 0;\n while (delta_m > innerThreshold && subIterations < maxInnerIterations) {\n subIterations += 1;\n this._moveNode(highE_nodeId, dE_dx, dE_dy);\n\n var _getEnergy2 = this._getEnergy(highE_nodeId);\n\n var _getEnergy22 = _slicedToArray(_getEnergy2, 3);\n\n delta_m = _getEnergy22[0];\n dE_dx = _getEnergy22[1];\n dE_dy = _getEnergy22[2];\n }\n }\n }\n\n /**\n * get the node with the highest energy\n * @returns {*[]}\n * @private\n */\n }, {\n key: \"_getHighestEnergyNode\",\n value: function _getHighestEnergyNode(ignoreClusters) {\n var nodesArray = this.body.nodeIndices;\n var nodes = this.body.nodes;\n var maxEnergy = 0;\n var maxEnergyNodeId = nodesArray[0];\n var dE_dx_max = 0,\n dE_dy_max = 0;\n\n for (var nodeIdx = 0; nodeIdx < nodesArray.length; nodeIdx++) {\n var m = nodesArray[nodeIdx];\n // by not evaluating nodes with predefined positions we should only move nodes that have no positions.\n if (nodes[m].predefinedPosition === false || nodes[m].isCluster === true && ignoreClusters === true || nodes[m].options.fixed.x === true || nodes[m].options.fixed.y === true) {\n var _getEnergy3 = this._getEnergy(m);\n\n var _getEnergy32 = _slicedToArray(_getEnergy3, 3);\n\n var delta_m = _getEnergy32[0];\n var dE_dx = _getEnergy32[1];\n var dE_dy = _getEnergy32[2];\n\n if (maxEnergy < delta_m) {\n maxEnergy = delta_m;\n maxEnergyNodeId = m;\n dE_dx_max = dE_dx;\n dE_dy_max = dE_dy;\n }\n }\n }\n\n return [maxEnergyNodeId, maxEnergy, dE_dx_max, dE_dy_max];\n }\n\n /**\n * calculate the energy of a single node\n * @param m\n * @returns {*[]}\n * @private\n */\n }, {\n key: \"_getEnergy\",\n value: function _getEnergy(m) {\n var nodesArray = this.body.nodeIndices;\n var nodes = this.body.nodes;\n\n var x_m = nodes[m].x;\n var y_m = nodes[m].y;\n var dE_dx = 0;\n var dE_dy = 0;\n for (var iIdx = 0; iIdx < nodesArray.length; iIdx++) {\n var i = nodesArray[iIdx];\n if (i !== m) {\n var x_i = nodes[i].x;\n var y_i = nodes[i].y;\n var denominator = 1.0 / Math.sqrt(Math.pow(x_m - x_i, 2) + Math.pow(y_m - y_i, 2));\n dE_dx += this.K_matrix[m][i] * (x_m - x_i - this.L_matrix[m][i] * (x_m - x_i) * denominator);\n dE_dy += this.K_matrix[m][i] * (y_m - y_i - this.L_matrix[m][i] * (y_m - y_i) * denominator);\n }\n }\n\n var delta_m = Math.sqrt(Math.pow(dE_dx, 2) + Math.pow(dE_dy, 2));\n return [delta_m, dE_dx, dE_dy];\n }\n\n /**\n * move the node based on it's energy\n * the dx and dy are calculated from the linear system proposed by Kamada and Kawai\n * @param m\n * @param dE_dx\n * @param dE_dy\n * @private\n */\n }, {\n key: \"_moveNode\",\n value: function _moveNode(m, dE_dx, dE_dy) {\n var nodesArray = this.body.nodeIndices;\n var nodes = this.body.nodes;\n var d2E_dx2 = 0;\n var d2E_dxdy = 0;\n var d2E_dy2 = 0;\n\n var x_m = nodes[m].x;\n var y_m = nodes[m].y;\n for (var iIdx = 0; iIdx < nodesArray.length; iIdx++) {\n var i = nodesArray[iIdx];\n if (i !== m) {\n var x_i = nodes[i].x;\n var y_i = nodes[i].y;\n var denominator = 1.0 / Math.pow(Math.pow(x_m - x_i, 2) + Math.pow(y_m - y_i, 2), 1.5);\n d2E_dx2 += this.K_matrix[m][i] * (1 - this.L_matrix[m][i] * Math.pow(y_m - y_i, 2) * denominator);\n d2E_dxdy += this.K_matrix[m][i] * (this.L_matrix[m][i] * (x_m - x_i) * (y_m - y_i) * denominator);\n d2E_dy2 += this.K_matrix[m][i] * (1 - this.L_matrix[m][i] * Math.pow(x_m - x_i, 2) * denominator);\n }\n }\n // make the variable names easier to make the solving of the linear system easier to read\n var A = d2E_dx2,\n B = d2E_dxdy,\n C = dE_dx,\n D = d2E_dy2,\n E = dE_dy;\n\n // solve the linear system for dx and dy\n var dy = (C / A + E / B) / (B / A - D / B);\n var dx = -(B * dy + C) / A;\n\n // move the node\n nodes[m].x += dx;\n nodes[m].y += dy;\n }\n\n /**\n * Create the L matrix: edge length times shortest path\n * @param D_matrix\n * @private\n */\n }, {\n key: \"_createL_matrix\",\n value: function _createL_matrix(D_matrix) {\n var nodesArray = this.body.nodeIndices;\n var edgeLength = this.springLength;\n\n this.L_matrix = [];\n for (var i = 0; i < nodesArray.length; i++) {\n this.L_matrix[nodesArray[i]] = {};\n for (var j = 0; j < nodesArray.length; j++) {\n this.L_matrix[nodesArray[i]][nodesArray[j]] = edgeLength * D_matrix[nodesArray[i]][nodesArray[j]];\n }\n }\n }\n\n /**\n * Create the K matrix: spring constants times shortest path\n * @param D_matrix\n * @private\n */\n }, {\n key: \"_createK_matrix\",\n value: function _createK_matrix(D_matrix) {\n var nodesArray = this.body.nodeIndices;\n var edgeStrength = this.springConstant;\n\n this.K_matrix = [];\n for (var i = 0; i < nodesArray.length; i++) {\n this.K_matrix[nodesArray[i]] = {};\n for (var j = 0; j < nodesArray.length; j++) {\n this.K_matrix[nodesArray[i]][nodesArray[j]] = edgeStrength * Math.pow(D_matrix[nodesArray[i]][nodesArray[j]], -2);\n }\n }\n }\n }]);\n\n return KamadaKawai;\n })();\n\n exports[\"default\"] = KamadaKawai;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 112 */\n/***/ function(module, exports) {\n\n /**\n * Created by Alex on 10-Aug-15.\n */\n\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var FloydWarshall = (function () {\n function FloydWarshall() {\n _classCallCheck(this, FloydWarshall);\n }\n\n _createClass(FloydWarshall, [{\n key: \"getDistances\",\n value: function getDistances(body, nodesArray, edgesArray) {\n var D_matrix = {};\n var edges = body.edges;\n\n // prepare matrix with large numbers\n for (var i = 0; i < nodesArray.length; i++) {\n D_matrix[nodesArray[i]] = {};\n D_matrix[nodesArray[i]] = {};\n for (var j = 0; j < nodesArray.length; j++) {\n D_matrix[nodesArray[i]][nodesArray[j]] = i == j ? 0 : 1e9;\n D_matrix[nodesArray[i]][nodesArray[j]] = i == j ? 0 : 1e9;\n }\n }\n\n // put the weights for the edges in. This assumes unidirectionality.\n for (var i = 0; i < edgesArray.length; i++) {\n var edge = edges[edgesArray[i]];\n // edge has to be connected if it counts to the distances. If it is connected to inner clusters it will crash so we also check if it is in the D_matrix\n if (edge.connected === true && D_matrix[edge.fromId] !== undefined && D_matrix[edge.toId] !== undefined) {\n D_matrix[edge.fromId][edge.toId] = 1;\n D_matrix[edge.toId][edge.fromId] = 1;\n }\n }\n\n var nodeCount = nodesArray.length;\n\n // Adapted FloydWarshall based on unidirectionality to greatly reduce complexity.\n for (var k = 0; k < nodeCount; k++) {\n for (var i = 0; i < nodeCount - 1; i++) {\n for (var j = i + 1; j < nodeCount; j++) {\n D_matrix[nodesArray[i]][nodesArray[j]] = Math.min(D_matrix[nodesArray[i]][nodesArray[j]], D_matrix[nodesArray[i]][nodesArray[k]] + D_matrix[nodesArray[k]][nodesArray[j]]);\n D_matrix[nodesArray[j]][nodesArray[i]] = D_matrix[nodesArray[i]][nodesArray[j]];\n }\n }\n }\n\n return D_matrix;\n }\n }]);\n\n return FloydWarshall;\n })();\n\n exports[\"default\"] = FloydWarshall;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 113 */\n/***/ function(module, exports) {\n\n /**\n * Canvas shapes used by Network\n */\n 'use strict';\n\n if (typeof CanvasRenderingContext2D !== 'undefined') {\n\n /**\n * Draw a circle shape\n */\n CanvasRenderingContext2D.prototype.circle = function (x, y, r) {\n this.beginPath();\n this.arc(x, y, r, 0, 2 * Math.PI, false);\n this.closePath();\n };\n\n /**\n * Draw a square shape\n * @param {Number} x horizontal center\n * @param {Number} y vertical center\n * @param {Number} r size, width and height of the square\n */\n CanvasRenderingContext2D.prototype.square = function (x, y, r) {\n this.beginPath();\n this.rect(x - r, y - r, r * 2, r * 2);\n this.closePath();\n };\n\n /**\n * Draw a triangle shape\n * @param {Number} x horizontal center\n * @param {Number} y vertical center\n * @param {Number} r radius, half the length of the sides of the triangle\n */\n CanvasRenderingContext2D.prototype.triangle = function (x, y, r) {\n // http://en.wikipedia.org/wiki/Equilateral_triangle\n this.beginPath();\n\n // the change in radius and the offset is here to center the shape\n r *= 1.15;\n y += 0.275 * r;\n\n var s = r * 2;\n var s2 = s / 2;\n var ir = Math.sqrt(3) / 6 * s; // radius of inner circle\n var h = Math.sqrt(s * s - s2 * s2); // height\n\n this.moveTo(x, y - (h - ir));\n this.lineTo(x + s2, y + ir);\n this.lineTo(x - s2, y + ir);\n this.lineTo(x, y - (h - ir));\n this.closePath();\n };\n\n /**\n * Draw a triangle shape in downward orientation\n * @param {Number} x horizontal center\n * @param {Number} y vertical center\n * @param {Number} r radius\n */\n CanvasRenderingContext2D.prototype.triangleDown = function (x, y, r) {\n // http://en.wikipedia.org/wiki/Equilateral_triangle\n this.beginPath();\n\n // the change in radius and the offset is here to center the shape\n r *= 1.15;\n y -= 0.275 * r;\n\n var s = r * 2;\n var s2 = s / 2;\n var ir = Math.sqrt(3) / 6 * s; // radius of inner circle\n var h = Math.sqrt(s * s - s2 * s2); // height\n\n this.moveTo(x, y + (h - ir));\n this.lineTo(x + s2, y - ir);\n this.lineTo(x - s2, y - ir);\n this.lineTo(x, y + (h - ir));\n this.closePath();\n };\n\n /**\n * Draw a star shape, a star with 5 points\n * @param {Number} x horizontal center\n * @param {Number} y vertical center\n * @param {Number} r radius, half the length of the sides of the triangle\n */\n CanvasRenderingContext2D.prototype.star = function (x, y, r) {\n // http://www.html5canvastutorials.com/labs/html5-canvas-star-spinner/\n this.beginPath();\n\n // the change in radius and the offset is here to center the shape\n r *= 0.82;\n y += 0.1 * r;\n\n for (var n = 0; n < 10; n++) {\n var radius = n % 2 === 0 ? r * 1.3 : r * 0.5;\n this.lineTo(x + radius * Math.sin(n * 2 * Math.PI / 10), y - radius * Math.cos(n * 2 * Math.PI / 10));\n }\n\n this.closePath();\n };\n\n /**\n * Draw a Diamond shape\n * @param {Number} x horizontal center\n * @param {Number} y vertical center\n * @param {Number} r radius, half the length of the sides of the triangle\n */\n CanvasRenderingContext2D.prototype.diamond = function (x, y, r) {\n // http://www.html5canvastutorials.com/labs/html5-canvas-star-spinner/\n this.beginPath();\n\n this.lineTo(x, y + r);\n this.lineTo(x + r, y);\n this.lineTo(x, y - r);\n this.lineTo(x - r, y);\n\n this.closePath();\n };\n\n /**\n * http://stackoverflow.com/questions/1255512/how-to-draw-a-rounded-rectangle-on-html-canvas\n */\n CanvasRenderingContext2D.prototype.roundRect = function (x, y, w, h, r) {\n var r2d = Math.PI / 180;\n if (w - 2 * r < 0) {\n r = w / 2;\n } //ensure that the radius isn't too large for x\n if (h - 2 * r < 0) {\n r = h / 2;\n } //ensure that the radius isn't too large for y\n this.beginPath();\n this.moveTo(x + r, y);\n this.lineTo(x + w - r, y);\n this.arc(x + w - r, y + r, r, r2d * 270, r2d * 360, false);\n this.lineTo(x + w, y + h - r);\n this.arc(x + w - r, y + h - r, r, 0, r2d * 90, false);\n this.lineTo(x + r, y + h);\n this.arc(x + r, y + h - r, r, r2d * 90, r2d * 180, false);\n this.lineTo(x, y + r);\n this.arc(x + r, y + r, r, r2d * 180, r2d * 270, false);\n this.closePath();\n };\n\n /**\n * http://stackoverflow.com/questions/2172798/how-to-draw-an-oval-in-html5-canvas\n */\n CanvasRenderingContext2D.prototype.ellipse = function (x, y, w, h) {\n var kappa = .5522848,\n ox = w / 2 * kappa,\n // control point offset horizontal\n oy = h / 2 * kappa,\n // control point offset vertical\n xe = x + w,\n // x-end\n ye = y + h,\n // y-end\n xm = x + w / 2,\n // x-middle\n ym = y + h / 2; // y-middle\n\n this.beginPath();\n this.moveTo(x, ym);\n this.bezierCurveTo(x, ym - oy, xm - ox, y, xm, y);\n this.bezierCurveTo(xm + ox, y, xe, ym - oy, xe, ym);\n this.bezierCurveTo(xe, ym + oy, xm + ox, ye, xm, ye);\n this.bezierCurveTo(xm - ox, ye, x, ym + oy, x, ym);\n this.closePath();\n };\n\n /**\n * http://stackoverflow.com/questions/2172798/how-to-draw-an-oval-in-html5-canvas\n */\n CanvasRenderingContext2D.prototype.database = function (x, y, w, h) {\n var f = 1 / 3;\n var wEllipse = w;\n var hEllipse = h * f;\n\n var kappa = .5522848,\n ox = wEllipse / 2 * kappa,\n // control point offset horizontal\n oy = hEllipse / 2 * kappa,\n // control point offset vertical\n xe = x + wEllipse,\n // x-end\n ye = y + hEllipse,\n // y-end\n xm = x + wEllipse / 2,\n // x-middle\n ym = y + hEllipse / 2,\n // y-middle\n ymb = y + (h - hEllipse / 2),\n // y-midlle, bottom ellipse\n yeb = y + h; // y-end, bottom ellipse\n\n this.beginPath();\n this.moveTo(xe, ym);\n\n this.bezierCurveTo(xe, ym + oy, xm + ox, ye, xm, ye);\n this.bezierCurveTo(xm - ox, ye, x, ym + oy, x, ym);\n\n this.bezierCurveTo(x, ym - oy, xm - ox, y, xm, y);\n this.bezierCurveTo(xm + ox, y, xe, ym - oy, xe, ym);\n\n this.lineTo(xe, ymb);\n\n this.bezierCurveTo(xe, ymb + oy, xm + ox, yeb, xm, yeb);\n this.bezierCurveTo(xm - ox, yeb, x, ymb + oy, x, ymb);\n\n this.lineTo(x, ym);\n };\n\n /**\n * Draw an arrow point (no line)\n */\n CanvasRenderingContext2D.prototype.arrow = function (x, y, angle, length) {\n // tail\n var xt = x - length * Math.cos(angle);\n var yt = y - length * Math.sin(angle);\n\n // inner tail\n var xi = x - length * 0.9 * Math.cos(angle);\n var yi = y - length * 0.9 * Math.sin(angle);\n\n // left\n var xl = xt + length / 3 * Math.cos(angle + 0.5 * Math.PI);\n var yl = yt + length / 3 * Math.sin(angle + 0.5 * Math.PI);\n\n // right\n var xr = xt + length / 3 * Math.cos(angle - 0.5 * Math.PI);\n var yr = yt + length / 3 * Math.sin(angle - 0.5 * Math.PI);\n\n this.beginPath();\n this.moveTo(x, y);\n this.lineTo(xl, yl);\n this.lineTo(xi, yi);\n this.lineTo(xr, yr);\n this.closePath();\n };\n\n /**\n * Sets up the dashedLine functionality for drawing\n * Original code came from http://stackoverflow.com/questions/4576724/dotted-stroke-in-canvas\n * @author David Jordan\n * @date 2012-08-08\n */\n CanvasRenderingContext2D.prototype.dashedLine = function (x, y, x2, y2, pattern) {\n this.beginPath();\n this.moveTo(x, y);\n\n var patternLength = pattern.length;\n var dx = x2 - x;\n var dy = y2 - y;\n var slope = dy / dx;\n var distRemaining = Math.sqrt(dx * dx + dy * dy);\n var patternIndex = 0;\n var draw = true;\n var xStep = 0;\n var dashLength = pattern[0];\n\n while (distRemaining >= 0.1) {\n dashLength = pattern[patternIndex++ % patternLength];\n if (dashLength > distRemaining) {\n dashLength = distRemaining;\n }\n\n xStep = Math.sqrt(dashLength * dashLength / (1 + slope * slope));\n xStep = dx < 0 ? -xStep : xStep;\n x += xStep;\n y += slope * xStep;\n\n if (draw === true) {\n this.lineTo(x, y);\n } else {\n this.moveTo(x, y);\n }\n\n distRemaining -= dashLength;\n draw = !draw;\n }\n };\n }\n\n/***/ },\n/* 114 */\n/***/ function(module, exports) {\n\n /**\n * Parse a text source containing data in DOT language into a JSON object.\n * The object contains two lists: one with nodes and one with edges.\n *\n * DOT language reference: http://www.graphviz.org/doc/info/lang.html\n *\n * DOT language attributes: http://graphviz.org/content/attrs\n *\n * @param {String} data Text containing a graph in DOT-notation\n * @return {Object} graph An object containing two parameters:\n * {Object[]} nodes\n * {Object[]} edges\n */\n 'use strict';\n\n function parseDOT(data) {\n dot = data;\n return parseGraph();\n }\n\n // mapping of attributes from DOT (the keys) to vis.js (the values)\n var NODE_ATTR_MAPPING = {\n 'fontsize': 'font.size',\n 'fontcolor': 'font.color',\n 'labelfontcolor': 'font.color',\n 'fontname': 'font.face',\n 'color': ['color.border', 'color.background'],\n 'fillcolor': 'color.background',\n 'tooltip': 'title',\n 'labeltooltip': 'title'\n };\n var EDGE_ATTR_MAPPING = Object.create(NODE_ATTR_MAPPING);\n EDGE_ATTR_MAPPING.color = 'color.color';\n\n // token types enumeration\n var TOKENTYPE = {\n NULL: 0,\n DELIMITER: 1,\n IDENTIFIER: 2,\n UNKNOWN: 3\n };\n\n // map with all delimiters\n var DELIMITERS = {\n '{': true,\n '}': true,\n '[': true,\n ']': true,\n ';': true,\n '=': true,\n ',': true,\n\n '->': true,\n '--': true\n };\n\n var dot = ''; // current dot file\n var index = 0; // current index in dot file\n var c = ''; // current token character in expr\n var token = ''; // current token\n var tokenType = TOKENTYPE.NULL; // type of the token\n\n /**\n * Get the first character from the dot file.\n * The character is stored into the char c. If the end of the dot file is\n * reached, the function puts an empty string in c.\n */\n function first() {\n index = 0;\n c = dot.charAt(0);\n }\n\n /**\n * Get the next character from the dot file.\n * The character is stored into the char c. If the end of the dot file is\n * reached, the function puts an empty string in c.\n */\n function next() {\n index++;\n c = dot.charAt(index);\n }\n\n /**\n * Preview the next character from the dot file.\n * @return {String} cNext\n */\n function nextPreview() {\n return dot.charAt(index + 1);\n }\n\n /**\n * Test whether given character is alphabetic or numeric\n * @param {String} c\n * @return {Boolean} isAlphaNumeric\n */\n var regexAlphaNumeric = /[a-zA-Z_0-9.:#]/;\n function isAlphaNumeric(c) {\n return regexAlphaNumeric.test(c);\n }\n\n /**\n * Merge all options of object b into object b\n * @param {Object} a\n * @param {Object} b\n * @return {Object} a\n */\n function merge(a, b) {\n if (!a) {\n a = {};\n }\n\n if (b) {\n for (var name in b) {\n if (b.hasOwnProperty(name)) {\n a[name] = b[name];\n }\n }\n }\n return a;\n }\n\n /**\n * Set a value in an object, where the provided parameter name can be a\n * path with nested parameters. For example:\n *\n * var obj = {a: 2};\n * setValue(obj, 'b.c', 3); // obj = {a: 2, b: {c: 3}}\n *\n * @param {Object} obj\n * @param {String} path A parameter name or dot-separated parameter path,\n * like \"color.highlight.border\".\n * @param {*} value\n */\n function setValue(obj, path, value) {\n var keys = path.split('.');\n var o = obj;\n while (keys.length) {\n var key = keys.shift();\n if (keys.length) {\n // this isn't the end point\n if (!o[key]) {\n o[key] = {};\n }\n o = o[key];\n } else {\n // this is the end point\n o[key] = value;\n }\n }\n }\n\n /**\n * Add a node to a graph object. If there is already a node with\n * the same id, their attributes will be merged.\n * @param {Object} graph\n * @param {Object} node\n */\n function addNode(graph, node) {\n var i, len;\n var current = null;\n\n // find root graph (in case of subgraph)\n var graphs = [graph]; // list with all graphs from current graph to root graph\n var root = graph;\n while (root.parent) {\n graphs.push(root.parent);\n root = root.parent;\n }\n\n // find existing node (at root level) by its id\n if (root.nodes) {\n for (i = 0, len = root.nodes.length; i < len; i++) {\n if (node.id === root.nodes[i].id) {\n current = root.nodes[i];\n break;\n }\n }\n }\n\n if (!current) {\n // this is a new node\n current = {\n id: node.id\n };\n if (graph.node) {\n // clone default attributes\n current.attr = merge(current.attr, graph.node);\n }\n }\n\n // add node to this (sub)graph and all its parent graphs\n for (i = graphs.length - 1; i >= 0; i--) {\n var g = graphs[i];\n\n if (!g.nodes) {\n g.nodes = [];\n }\n if (g.nodes.indexOf(current) === -1) {\n g.nodes.push(current);\n }\n }\n\n // merge attributes\n if (node.attr) {\n current.attr = merge(current.attr, node.attr);\n }\n }\n\n /**\n * Add an edge to a graph object\n * @param {Object} graph\n * @param {Object} edge\n */\n function addEdge(graph, edge) {\n if (!graph.edges) {\n graph.edges = [];\n }\n graph.edges.push(edge);\n if (graph.edge) {\n var attr = merge({}, graph.edge); // clone default attributes\n edge.attr = merge(attr, edge.attr); // merge attributes\n }\n }\n\n /**\n * Create an edge to a graph object\n * @param {Object} graph\n * @param {String | Number | Object} from\n * @param {String | Number | Object} to\n * @param {String} type\n * @param {Object | null} attr\n * @return {Object} edge\n */\n function createEdge(graph, from, to, type, attr) {\n var edge = {\n from: from,\n to: to,\n type: type\n };\n\n if (graph.edge) {\n edge.attr = merge({}, graph.edge); // clone default attributes\n }\n edge.attr = merge(edge.attr || {}, attr); // merge attributes\n\n return edge;\n }\n\n /**\n * Get next token in the current dot file.\n * The token and token type are available as token and tokenType\n */\n function getToken() {\n tokenType = TOKENTYPE.NULL;\n token = '';\n\n // skip over whitespaces\n while (c === ' ' || c === '\\t' || c === '\\n' || c === '\\r') {\n // space, tab, enter\n next();\n }\n\n do {\n var isComment = false;\n\n // skip comment\n if (c === '#') {\n // find the previous non-space character\n var i = index - 1;\n while (dot.charAt(i) === ' ' || dot.charAt(i) === '\\t') {\n i--;\n }\n if (dot.charAt(i) === '\\n' || dot.charAt(i) === '') {\n // the # is at the start of a line, this is indeed a line comment\n while (c != '' && c != '\\n') {\n next();\n }\n isComment = true;\n }\n }\n if (c === '/' && nextPreview() === '/') {\n // skip line comment\n while (c != '' && c != '\\n') {\n next();\n }\n isComment = true;\n }\n if (c === '/' && nextPreview() === '*') {\n // skip block comment\n while (c != '') {\n if (c === '*' && nextPreview() === '/') {\n // end of block comment found. skip these last two characters\n next();\n next();\n break;\n } else {\n next();\n }\n }\n isComment = true;\n }\n\n // skip over whitespaces\n while (c === ' ' || c === '\\t' || c === '\\n' || c === '\\r') {\n // space, tab, enter\n next();\n }\n } while (isComment);\n\n // check for end of dot file\n if (c === '') {\n // token is still empty\n tokenType = TOKENTYPE.DELIMITER;\n return;\n }\n\n // check for delimiters consisting of 2 characters\n var c2 = c + nextPreview();\n if (DELIMITERS[c2]) {\n tokenType = TOKENTYPE.DELIMITER;\n token = c2;\n next();\n next();\n return;\n }\n\n // check for delimiters consisting of 1 character\n if (DELIMITERS[c]) {\n tokenType = TOKENTYPE.DELIMITER;\n token = c;\n next();\n return;\n }\n\n // check for an identifier (number or string)\n // TODO: more precise parsing of numbers/strings (and the port separator ':')\n if (isAlphaNumeric(c) || c === '-') {\n token += c;\n next();\n\n while (isAlphaNumeric(c)) {\n token += c;\n next();\n }\n if (token === 'false') {\n token = false; // convert to boolean\n } else if (token === 'true') {\n token = true; // convert to boolean\n } else if (!isNaN(Number(token))) {\n token = Number(token); // convert to number\n }\n tokenType = TOKENTYPE.IDENTIFIER;\n return;\n }\n\n // check for a string enclosed by double quotes\n if (c === '\"') {\n next();\n while (c != '' && (c != '\"' || c === '\"' && nextPreview() === '\"')) {\n token += c;\n if (c === '\"') {\n // skip the escape character\n next();\n }\n next();\n }\n if (c != '\"') {\n throw newSyntaxError('End of string \" expected');\n }\n next();\n tokenType = TOKENTYPE.IDENTIFIER;\n return;\n }\n\n // something unknown is found, wrong characters, a syntax error\n tokenType = TOKENTYPE.UNKNOWN;\n while (c != '') {\n token += c;\n next();\n }\n throw new SyntaxError('Syntax error in part \"' + chop(token, 30) + '\"');\n }\n\n /**\n * Parse a graph.\n * @returns {Object} graph\n */\n function parseGraph() {\n var graph = {};\n\n first();\n getToken();\n\n // optional strict keyword\n if (token === 'strict') {\n graph.strict = true;\n getToken();\n }\n\n // graph or digraph keyword\n if (token === 'graph' || token === 'digraph') {\n graph.type = token;\n getToken();\n }\n\n // optional graph id\n if (tokenType === TOKENTYPE.IDENTIFIER) {\n graph.id = token;\n getToken();\n }\n\n // open angle bracket\n if (token != '{') {\n throw newSyntaxError('Angle bracket { expected');\n }\n getToken();\n\n // statements\n parseStatements(graph);\n\n // close angle bracket\n if (token != '}') {\n throw newSyntaxError('Angle bracket } expected');\n }\n getToken();\n\n // end of file\n if (token !== '') {\n throw newSyntaxError('End of file expected');\n }\n getToken();\n\n // remove temporary default options\n delete graph.node;\n delete graph.edge;\n delete graph.graph;\n\n return graph;\n }\n\n /**\n * Parse a list with statements.\n * @param {Object} graph\n */\n function parseStatements(graph) {\n while (token !== '' && token != '}') {\n parseStatement(graph);\n if (token === ';') {\n getToken();\n }\n }\n }\n\n /**\n * Parse a single statement. Can be a an attribute statement, node\n * statement, a series of node statements and edge statements, or a\n * parameter.\n * @param {Object} graph\n */\n function parseStatement(graph) {\n // parse subgraph\n var subgraph = parseSubgraph(graph);\n if (subgraph) {\n // edge statements\n parseEdge(graph, subgraph);\n\n return;\n }\n\n // parse an attribute statement\n var attr = parseAttributeStatement(graph);\n if (attr) {\n return;\n }\n\n // parse node\n if (tokenType != TOKENTYPE.IDENTIFIER) {\n throw newSyntaxError('Identifier expected');\n }\n var id = token; // id can be a string or a number\n getToken();\n\n if (token === '=') {\n // id statement\n getToken();\n if (tokenType != TOKENTYPE.IDENTIFIER) {\n throw newSyntaxError('Identifier expected');\n }\n graph[id] = token;\n getToken();\n // TODO: implement comma separated list with \"a_list: ID=ID [','] [a_list] \"\n } else {\n parseNodeStatement(graph, id);\n }\n }\n\n /**\n * Parse a subgraph\n * @param {Object} graph parent graph object\n * @return {Object | null} subgraph\n */\n function parseSubgraph(graph) {\n var subgraph = null;\n\n // optional subgraph keyword\n if (token === 'subgraph') {\n subgraph = {};\n subgraph.type = 'subgraph';\n getToken();\n\n // optional graph id\n if (tokenType === TOKENTYPE.IDENTIFIER) {\n subgraph.id = token;\n getToken();\n }\n }\n\n // open angle bracket\n if (token === '{') {\n getToken();\n\n if (!subgraph) {\n subgraph = {};\n }\n subgraph.parent = graph;\n subgraph.node = graph.node;\n subgraph.edge = graph.edge;\n subgraph.graph = graph.graph;\n\n // statements\n parseStatements(subgraph);\n\n // close angle bracket\n if (token != '}') {\n throw newSyntaxError('Angle bracket } expected');\n }\n getToken();\n\n // remove temporary default options\n delete subgraph.node;\n delete subgraph.edge;\n delete subgraph.graph;\n delete subgraph.parent;\n\n // register at the parent graph\n if (!graph.subgraphs) {\n graph.subgraphs = [];\n }\n graph.subgraphs.push(subgraph);\n }\n\n return subgraph;\n }\n\n /**\n * parse an attribute statement like \"node [shape=circle fontSize=16]\".\n * Available keywords are 'node', 'edge', 'graph'.\n * The previous list with default attributes will be replaced\n * @param {Object} graph\n * @returns {String | null} keyword Returns the name of the parsed attribute\n * (node, edge, graph), or null if nothing\n * is parsed.\n */\n function parseAttributeStatement(graph) {\n // attribute statements\n if (token === 'node') {\n getToken();\n\n // node attributes\n graph.node = parseAttributeList();\n return 'node';\n } else if (token === 'edge') {\n getToken();\n\n // edge attributes\n graph.edge = parseAttributeList();\n return 'edge';\n } else if (token === 'graph') {\n getToken();\n\n // graph attributes\n graph.graph = parseAttributeList();\n return 'graph';\n }\n\n return null;\n }\n\n /**\n * parse a node statement\n * @param {Object} graph\n * @param {String | Number} id\n */\n function parseNodeStatement(graph, id) {\n // node statement\n var node = {\n id: id\n };\n var attr = parseAttributeList();\n if (attr) {\n node.attr = attr;\n }\n addNode(graph, node);\n\n // edge statements\n parseEdge(graph, id);\n }\n\n /**\n * Parse an edge or a series of edges\n * @param {Object} graph\n * @param {String | Number} from Id of the from node\n */\n function parseEdge(graph, from) {\n while (token === '->' || token === '--') {\n var to;\n var type = token;\n getToken();\n\n var subgraph = parseSubgraph(graph);\n if (subgraph) {\n to = subgraph;\n } else {\n if (tokenType != TOKENTYPE.IDENTIFIER) {\n throw newSyntaxError('Identifier or subgraph expected');\n }\n to = token;\n addNode(graph, {\n id: to\n });\n getToken();\n }\n\n // parse edge attributes\n var attr = parseAttributeList();\n\n // create edge\n var edge = createEdge(graph, from, to, type, attr);\n addEdge(graph, edge);\n\n from = to;\n }\n }\n\n /**\n * Parse a set with attributes,\n * for example [label=\"1.000\", shape=solid]\n * @return {Object | null} attr\n */\n function parseAttributeList() {\n var attr = null;\n\n while (token === '[') {\n getToken();\n attr = {};\n while (token !== '' && token != ']') {\n if (tokenType != TOKENTYPE.IDENTIFIER) {\n throw newSyntaxError('Attribute name expected');\n }\n var name = token;\n\n getToken();\n if (token != '=') {\n throw newSyntaxError('Equal sign = expected');\n }\n getToken();\n\n if (tokenType != TOKENTYPE.IDENTIFIER) {\n throw newSyntaxError('Attribute value expected');\n }\n var value = token;\n setValue(attr, name, value); // name can be a path\n\n getToken();\n if (token == ',') {\n getToken();\n }\n }\n\n if (token != ']') {\n throw newSyntaxError('Bracket ] expected');\n }\n getToken();\n }\n\n return attr;\n }\n\n /**\n * Create a syntax error with extra information on current token and index.\n * @param {String} message\n * @returns {SyntaxError} err\n */\n function newSyntaxError(message) {\n return new SyntaxError(message + ', got \"' + chop(token, 30) + '\" (char ' + index + ')');\n }\n\n /**\n * Chop off text after a maximum length\n * @param {String} text\n * @param {Number} maxLength\n * @returns {String}\n */\n function chop(text, maxLength) {\n return text.length <= maxLength ? text : text.substr(0, 27) + '...';\n }\n\n /**\n * Execute a function fn for each pair of elements in two arrays\n * @param {Array | *} array1\n * @param {Array | *} array2\n * @param {function} fn\n */\n function forEach2(array1, array2, fn) {\n if (Array.isArray(array1)) {\n array1.forEach(function (elem1) {\n if (Array.isArray(array2)) {\n array2.forEach(function (elem2) {\n fn(elem1, elem2);\n });\n } else {\n fn(elem1, array2);\n }\n });\n } else {\n if (Array.isArray(array2)) {\n array2.forEach(function (elem2) {\n fn(array1, elem2);\n });\n } else {\n fn(array1, array2);\n }\n }\n }\n\n /**\n * Set a nested property on an object\n * When nested objects are missing, they will be created.\n * For example setProp({}, 'font.color', 'red') will return {font: {color: 'red'}}\n * @param {Object} object\n * @param {string} path A dot separated string like 'font.color'\n * @param {*} value Value for the property\n * @return {Object} Returns the original object, allows for chaining.\n */\n function setProp(object, path, value) {\n var names = path.split('.');\n var prop = names.pop();\n\n // traverse over the nested objects\n var obj = object;\n for (var i = 0; i < names.length; i++) {\n var name = names[i];\n if (!(name in obj)) {\n obj[name] = {};\n }\n obj = obj[name];\n }\n\n // set the property value\n obj[prop] = value;\n\n return object;\n }\n\n /**\n * Convert an object with DOT attributes to their vis.js equivalents.\n * @param {Object} attr Object with DOT attributes\n * @param {Object} mapping\n * @return {Object} Returns an object with vis.js attributes\n */\n function convertAttr(attr, mapping) {\n var converted = {};\n\n for (var prop in attr) {\n if (attr.hasOwnProperty(prop)) {\n var visProp = mapping[prop];\n if (Array.isArray(visProp)) {\n visProp.forEach(function (visPropI) {\n setProp(converted, visPropI, attr[prop]);\n });\n } else if (typeof visProp === 'string') {\n setProp(converted, visProp, attr[prop]);\n } else {\n setProp(converted, prop, attr[prop]);\n }\n }\n }\n\n return converted;\n }\n\n /**\n * Convert a string containing a graph in DOT language into a map containing\n * with nodes and edges in the format of graph.\n * @param {String} data Text containing a graph in DOT-notation\n * @return {Object} graphData\n */\n function DOTToGraph(data) {\n // parse the DOT file\n var dotData = parseDOT(data);\n var graphData = {\n nodes: [],\n edges: [],\n options: {}\n };\n\n // copy the nodes\n if (dotData.nodes) {\n dotData.nodes.forEach(function (dotNode) {\n var graphNode = {\n id: dotNode.id,\n label: String(dotNode.label || dotNode.id)\n };\n merge(graphNode, convertAttr(dotNode.attr, NODE_ATTR_MAPPING));\n if (graphNode.image) {\n graphNode.shape = 'image';\n }\n graphData.nodes.push(graphNode);\n });\n }\n\n // copy the edges\n if (dotData.edges) {\n /**\n * Convert an edge in DOT format to an edge with VisGraph format\n * @param {Object} dotEdge\n * @returns {Object} graphEdge\n */\n var convertEdge = function convertEdge(dotEdge) {\n var graphEdge = {\n from: dotEdge.from,\n to: dotEdge.to\n };\n merge(graphEdge, convertAttr(dotEdge.attr, EDGE_ATTR_MAPPING));\n graphEdge.arrows = dotEdge.type === '->' ? 'to' : undefined;\n\n return graphEdge;\n };\n\n dotData.edges.forEach(function (dotEdge) {\n var from, to;\n if (dotEdge.from instanceof Object) {\n from = dotEdge.from.nodes;\n } else {\n from = {\n id: dotEdge.from\n };\n }\n\n // TODO: support of solid/dotted/dashed edges (attr = 'style')\n // TODO: support for attributes 'dir' and 'arrowhead' (edge arrows)\n\n if (dotEdge.to instanceof Object) {\n to = dotEdge.to.nodes;\n } else {\n to = {\n id: dotEdge.to\n };\n }\n\n if (dotEdge.from instanceof Object && dotEdge.from.edges) {\n dotEdge.from.edges.forEach(function (subEdge) {\n var graphEdge = convertEdge(subEdge);\n graphData.edges.push(graphEdge);\n });\n }\n\n forEach2(from, to, function (from, to) {\n var subEdge = createEdge(graphData, from.id, to.id, dotEdge.type, dotEdge.attr);\n var graphEdge = convertEdge(subEdge);\n graphData.edges.push(graphEdge);\n });\n\n if (dotEdge.to instanceof Object && dotEdge.to.edges) {\n dotEdge.to.edges.forEach(function (subEdge) {\n var graphEdge = convertEdge(subEdge);\n graphData.edges.push(graphEdge);\n });\n }\n });\n }\n\n // copy the options\n if (dotData.attr) {\n graphData.options = dotData.attr;\n }\n\n return graphData;\n }\n\n // exports\n exports.parseDOT = parseDOT;\n exports.DOTToGraph = DOTToGraph;\n\n/***/ },\n/* 115 */\n/***/ function(module, exports) {\n\n 'use strict';\n\n function parseGephi(gephiJSON, optionsObj) {\n var edges = [];\n var nodes = [];\n var options = {\n edges: {\n inheritColor: false\n },\n nodes: {\n fixed: false,\n parseColor: false\n }\n };\n\n if (optionsObj !== undefined) {\n if (optionsObj.fixed !== undefined) {\n options.nodes.fixed = optionsObj.fixed;\n }\n if (optionsObj.parseColor !== undefined) {\n options.nodes.parseColor = optionsObj.parseColor;\n }\n if (optionsObj.inheritColor !== undefined) {\n options.edges.inheritColor = optionsObj.inheritColor;\n }\n }\n\n var gEdges = gephiJSON.edges;\n var gNodes = gephiJSON.nodes;\n for (var i = 0; i < gEdges.length; i++) {\n var edge = {};\n var gEdge = gEdges[i];\n edge['id'] = gEdge.id;\n edge['from'] = gEdge.source;\n edge['to'] = gEdge.target;\n edge['attributes'] = gEdge.attributes;\n edge['label'] = gEdge.label;\n edge['title'] = gEdge.attributes !== undefined ? gEdge.attributes.title : undefined;\n if (gEdge['type'] === 'Directed') {\n edge['arrows'] = 'to';\n }\n // edge['value'] = gEdge.attributes !== undefined ? gEdge.attributes.Weight : undefined;\n // edge['width'] = edge['value'] !== undefined ? undefined : edgegEdge.size;\n if (gEdge.color && options.inheritColor === false) {\n edge['color'] = gEdge.color;\n }\n edges.push(edge);\n }\n\n for (var i = 0; i < gNodes.length; i++) {\n var node = {};\n var gNode = gNodes[i];\n node['id'] = gNode.id;\n node['attributes'] = gNode.attributes;\n node['title'] = gNode.title;\n node['x'] = gNode.x;\n node['y'] = gNode.y;\n node['label'] = gNode.label;\n node['title'] = gNode.attributes !== undefined ? gNode.attributes.title : undefined;\n if (options.nodes.parseColor === true) {\n node['color'] = gNode.color;\n } else {\n node['color'] = gNode.color !== undefined ? { background: gNode.color, border: gNode.color, highlight: { background: gNode.color, border: gNode.color }, hover: { background: gNode.color, border: gNode.color } } : undefined;\n }\n node['size'] = gNode.size;\n node['fixed'] = options.nodes.fixed && gNode.x !== undefined && gNode.y !== undefined;\n nodes.push(node);\n }\n\n return { nodes: nodes, edges: edges };\n }\n\n exports.parseGephi = parseGephi;\n\n/***/ },\n/* 116 */\n/***/ function(module, exports) {\n\n /**\n * @class Images\n * This class loads images and keeps them stored.\n */\n \"use strict\";\n\n Object.defineProperty(exports, \"__esModule\", {\n value: true\n });\n\n var _createClass = (function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; })();\n\n function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\n var Images = (function () {\n function Images(callback) {\n _classCallCheck(this, Images);\n\n this.images = {};\n this.imageBroken = {};\n this.callback = callback;\n }\n\n /**\n * @param {string} url The Url to cache the image as \n * @return {Image} imageToLoadBrokenUrlOn The image object\n */\n\n _createClass(Images, [{\n key: \"_addImageToCache\",\n value: function _addImageToCache(url, imageToCache) {\n // IE11 fix -- thanks dponch!\n if (imageToCache.width === 0) {\n document.body.appendChild(imageToCache);\n imageToCache.width = imageToCache.offsetWidth;\n imageToCache.height = imageToCache.offsetHeight;\n document.body.removeChild(imageToCache);\n }\n\n this.images[url] = imageToCache;\n }\n\n /**\n * @param {string} url The original Url that failed to load, if the broken image is successfully loaded it will be added to the cache using this Url as the key so that subsequent requests for this Url will return the broken image\n * @param {string} brokenUrl Url the broken image to try and load\n * @return {Image} imageToLoadBrokenUrlOn The image object\n */\n }, {\n key: \"_tryloadBrokenUrl\",\n value: function _tryloadBrokenUrl(url, brokenUrl, imageToLoadBrokenUrlOn) {\n var _this = this;\n\n //If any of the parameters aren't specified then exit the function because nothing constructive can be done\n if (url === undefined || brokenUrl === undefined || imageToLoadBrokenUrlOn === undefined) return;\n\n //Clear the old subscription to the error event and put a new in place that only handle errors in loading the brokenImageUrl\n imageToLoadBrokenUrlOn.onerror = function () {\n console.error(\"Could not load brokenImage:\", brokenUrl);\n //Add an empty image to the cache so that when subsequent load calls are made for the url we don't try load the image and broken image again\n _this._addImageToCache(url, new Image());\n };\n\n //Set the source of the image to the brokenUrl, this is actually what kicks off the loading of the broken image\n imageToLoadBrokenUrlOn.src = brokenUrl;\n }\n\n /**\n * @return {Image} imageToRedrawWith The images that will be passed to the callback when it is invoked\n */\n }, {\n key: \"_redrawWithImage\",\n value: function _redrawWithImage(imageToRedrawWith) {\n if (this.callback) {\n this.callback(imageToRedrawWith);\n }\n }\n\n /**\n * @param {string} url Url of the image\n * @param {string} brokenUrl Url of an image to use if the url image is not found\n * @return {Image} img The image object\n */\n }, {\n key: \"load\",\n value: function load(url, brokenUrl, id) {\n var _this2 = this;\n\n //Try and get the image from the cache, if successful then return the cached image \n var cachedImage = this.images[url];\n if (cachedImage) return cachedImage;\n\n //Create a new image\n var img = new Image();\n\n //Subscribe to the event that is raised if the image loads successfully\n img.onload = function () {\n //Add the image to the cache and then request a redraw\n _this2._addImageToCache(url, img);\n _this2._redrawWithImage(img);\n };\n\n //Subscribe to the event that is raised if the image fails to load\n img.onerror = function () {\n console.error(\"Could not load image:\", url);\n //Try and load the image specified by the brokenUrl using\n _this2._tryloadBrokenUrl(url, brokenUrl, img);\n };\n\n //Set the source of the image to the url, this is actuall what kicks off the loading of the image\n img.src = url;\n\n //Return the new image\n return img;\n }\n }]);\n\n return Images;\n })();\n\n exports[\"default\"] = Images;\n module.exports = exports[\"default\"];\n\n/***/ },\n/* 117 */\n/***/ function(module, exports) {\n\n // English\n 'use strict';\n\n exports['en'] = {\n edit: 'Edit',\n del: 'Delete selected',\n back: 'Back',\n addNode: 'Add Node',\n addEdge: 'Add Edge',\n editNode: 'Edit Node',\n editEdge: 'Edit Edge',\n addDescription: 'Click in an empty space to place a new node.',\n edgeDescription: 'Click on a node and drag the edge to another node to connect them.',\n editEdgeDescription: 'Click on the control points and drag them to a node to connect to it.',\n createEdgeError: 'Cannot link edges to a cluster.',\n deleteClusterError: 'Clusters cannot be deleted.',\n editClusterError: 'Clusters cannot be edited.'\n };\n exports['en_EN'] = exports['en'];\n exports['en_US'] = exports['en'];\n\n // German\n exports['de'] = {\n edit: 'Editieren',\n del: 'Lösche Auswahl',\n back: 'Zurück',\n addNode: 'Knoten hinzufügen',\n addEdge: 'Kante hinzufügen',\n editNode: 'Knoten editieren',\n editEdge: 'Kante editieren',\n addDescription: 'Klicke auf eine freie Stelle, um einen neuen Knoten zu plazieren.',\n edgeDescription: 'Klicke auf einen Knoten und ziehe die Kante zu einem anderen Knoten, um diese zu verbinden.',\n editEdgeDescription: 'Klicke auf die Verbindungspunkte und ziehe diese auf einen Knoten, um sie zu verbinden.',\n createEdgeError: 'Es ist nicht möglich, Kanten mit Clustern zu verbinden.',\n deleteClusterError: 'Cluster können nicht gelöscht werden.',\n editClusterError: 'Cluster können nicht editiert werden.'\n };\n exports['de_DE'] = exports['de'];\n\n // Spanish\n exports['es'] = {\n edit: 'Editar',\n del: 'Eliminar selección',\n back: 'Átras',\n addNode: 'Añadir nodo',\n addEdge: 'Añadir arista',\n editNode: 'Editar nodo',\n editEdge: 'Editar arista',\n addDescription: 'Haga clic en un lugar vacío para colocar un nuevo nodo.',\n edgeDescription: 'Haga clic en un nodo y arrastre la arista hacia otro nodo para conectarlos.',\n editEdgeDescription: 'Haga clic en un punto de control y arrastrelo a un nodo para conectarlo.',\n createEdgeError: 'No se puede conectar una arista a un grupo.',\n deleteClusterError: 'No es posible eliminar grupos.',\n editClusterError: 'No es posible editar grupos.'\n };\n exports['es_ES'] = exports['es'];\n\n // Dutch\n exports['nl'] = {\n edit: 'Wijzigen',\n del: 'Selectie verwijderen',\n back: 'Terug',\n addNode: 'Node toevoegen',\n addEdge: 'Link toevoegen',\n editNode: 'Node wijzigen',\n editEdge: 'Link wijzigen',\n addDescription: 'Klik op een leeg gebied om een nieuwe node te maken.',\n edgeDescription: 'Klik op een node en sleep de link naar een andere node om ze te verbinden.',\n editEdgeDescription: 'Klik op de verbindingspunten en sleep ze naar een node om daarmee te verbinden.',\n createEdgeError: 'Kan geen link maken naar een cluster.',\n deleteClusterError: 'Clusters kunnen niet worden verwijderd.',\n editClusterError: 'Clusters kunnen niet worden aangepast.'\n };\n exports['nl_NL'] = exports['nl'];\n exports['nl_BE'] = exports['nl'];\n\n/***/ }\n/******/ ])\n});\n;\n",
"title": "$:/plugins/felixhayashi/vis/vis.js",
"type": "application/javascript",
"module-type": "library"
}
}
}
{
"tiddlers": {
"$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome/doc": {
"created": "20140307084843714",
"creator": "Harald Albrecht",
"modified": "20140901072320086",
"modifier": "TheDiveO",
"tags": "$:/TheDiveO/tags/TW5Custom $:/TheDiveO/tags/doc",
"title": "$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome/doc",
"type": "text/vnd.tiddlywiki",
"text": "<i class=\"fa fa-flag fa-3x pull-left fa-border\"></i>[[Font Awesome|http://fortawesome.github.io/Font-Awesome/]] is a set of 350+ scalable vector icons in form of a font. It has been created by Dave Gandy. According to its author, «//Font Awesome is a pictographic language of web-related actions//». The font is free as in free speech. This stylesheet tiddler provides the complete font together with a whooping bunch of CSS definitions to make working with Font Awesome a pleasure to do.\n\n! Version\n\nThe version of the embedded WOFF font and associated CSS stylesheet is 4.2.0.\n\n* Font Awesome font license: [[SIL OFL 1.1|http://scripts.sil.org/OFL]].\n* Font Awesome CSS and LESS files licenses: [[MIT License|http://opensource.org/licenses/mit-license.html]].\n\n! How to Update\n\n# First download the newest Font Awesome ZIP archive from the [[Font Awesome front page|http://fortawesome.github.io/Font-Awesome/]].\n# Unpack the archive contents into some temporary directory.\n# Replace the old contents of [[$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome]] with the contents of the CSS file ``css/font-awesome.css``.\n# Remove the existing ``src`` definitions from the ``@font-face`` rule at the top of the CSS.\n# Now add the new definition ``src: local(\"FontAwesome\"), url(data:application/font-woff;base64,``...``) format(\"woff\");`` to the ``@font-face`` rule. There is no need to paste the triple dots as these are just signalling where we need to insert the base64-encoded font data itself later.\n# Go to one of the base64 encoding web services, but take care: most of them break the result into multiple lines -- ''which won't work in CSS'' as the whole base64 result needs to be on a ''single'' line. [[http://webcodertools.com/imagetobase64converter]] is suitable. Drag the web font file from ``fonts/fontawesome-webfont.woff`` onto the file button in the web form and convert.\n# Press the ''Upload'' button in the web form.\n# Paste the Base64-encoded result from the top input box of the web form into the [[$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome]] and there into the ``src`` definition from the ``@font-face`` rule. The Base64-encoded contents need to be pasted after the ``base64,`` and before the terminating ``) format(\"woff\");``. Be careful to only copy and paste the portion ''after'' ``base64,`` ''up to but not including'' the final quote from the top example result field.\n# Save your ~TiddlyWiki.\n# Reload. Just to be sure -- you don't really need to reload as ~TiddlyWiki automatically brings any CSS changes from stylesheet tiddlers live as soon as you update them. So sweet!\n\n! Background\n\nFor background information on the font itself as well as on its integration into ~TiddlyWiki 5 please see:\n\n* [[Font Awesome web site|http://fortawesome.github.io/Font-Awesome/]] -- the source of this font, and comprehensive documentation on how to use the font Awesome.\n* [[How to incorporate Font Awesome Icons into TiddlyWiki 5|http://blog.jeffreykishner.com/2014/01/23/how-to-incorporate-font-awesome-icons-into-tiddlywiki-5.html]] -- a blog post detailing how to store and integrate the font into a ~TiddlyWiki 5."
},
"$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome": {
"created": "20140729121621919",
"creator": "Harald Albrecht",
"modified": "20140925072658739",
"modifier": "TheDiveO",
"tags": "$:/TheDiveO/tags/TW5Custom $:/TheDiveO/tags/font $:/tags/Stylesheet",
"title": "$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome",
"type": "text/css",
"text": "/*!\n * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome\n * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)\n */\n/* FONT PATH\n * -------------------------- */\n@font-face {\n font-family: 'FontAwesome';\nsrc: local(\"FontAwesome\"), 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) format(\"woff\");\n font-weight: normal;\n font-style: normal;\n}\n.fa {\n display: inline-block;\n font: normal normal normal 14px/1 FontAwesome;\n font-size: inherit;\n text-rendering: auto;\n -webkit-font-smoothing: antialiased;\n -moz-osx-font-smoothing: grayscale;\n}\n/* makes the font 33% larger relative to the icon container */\n.fa-lg {\n font-size: 1.33333333em;\n line-height: 0.75em;\n vertical-align: -15%;\n}\n.fa-2x {\n font-size: 2em;\n}\n.fa-3x {\n font-size: 3em;\n}\n.fa-4x {\n font-size: 4em;\n}\n.fa-5x {\n font-size: 5em;\n}\n.fa-fw {\n width: 1.28571429em;\n text-align: center;\n}\n.fa-ul {\n padding-left: 0;\n margin-left: 2.14285714em;\n list-style-type: none;\n}\n.fa-ul > li {\n position: relative;\n}\n.fa-li {\n position: absolute;\n left: -2.14285714em;\n width: 2.14285714em;\n top: 0.14285714em;\n text-align: center;\n}\n.fa-li.fa-lg {\n left: -1.85714286em;\n}\n.fa-border {\n padding: .2em .25em .15em;\n border: solid 0.08em #eeeeee;\n border-radius: .1em;\n}\n.pull-right {\n float: right;\n}\n.pull-left {\n float: left;\n}\n.fa.pull-left {\n margin-right: .3em;\n}\n.fa.pull-right {\n margin-left: .3em;\n}\n.fa-spin {\n -webkit-animation: fa-spin 2s infinite linear;\n animation: fa-spin 2s infinite linear;\n}\n@-webkit-keyframes fa-spin {\n 0% {\n -webkit-transform: rotate(0deg);\n transform: rotate(0deg);\n }\n 100% {\n -webkit-transform: rotate(359deg);\n transform: rotate(359deg);\n }\n}\n@keyframes fa-spin {\n 0% {\n -webkit-transform: rotate(0deg);\n transform: rotate(0deg);\n }\n 100% {\n -webkit-transform: rotate(359deg);\n transform: rotate(359deg);\n }\n}\n.fa-rotate-90 {\n filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);\n -webkit-transform: rotate(90deg);\n -ms-transform: rotate(90deg);\n transform: rotate(90deg);\n}\n.fa-rotate-180 {\n filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);\n -webkit-transform: rotate(180deg);\n -ms-transform: rotate(180deg);\n transform: rotate(180deg);\n}\n.fa-rotate-270 {\n filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);\n -webkit-transform: rotate(270deg);\n -ms-transform: rotate(270deg);\n transform: rotate(270deg);\n}\n.fa-flip-horizontal {\n filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);\n -webkit-transform: scale(-1, 1);\n -ms-transform: scale(-1, 1);\n transform: scale(-1, 1);\n}\n.fa-flip-vertical {\n filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);\n -webkit-transform: scale(1, -1);\n -ms-transform: scale(1, -1);\n transform: scale(1, -1);\n}\n:root .fa-rotate-90,\n:root .fa-rotate-180,\n:root .fa-rotate-270,\n:root .fa-flip-horizontal,\n:root .fa-flip-vertical {\n filter: none;\n}\n.fa-stack {\n position: relative;\n display: inline-block;\n width: 2em;\n height: 2em;\n line-height: 2em;\n vertical-align: middle;\n}\n.fa-stack-1x,\n.fa-stack-2x {\n position: absolute;\n left: 0;\n width: 100%;\n text-align: center;\n}\n.fa-stack-1x {\n line-height: inherit;\n}\n.fa-stack-2x {\n font-size: 2em;\n}\n.fa-inverse {\n color: #ffffff;\n}\n/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen\n readers do not read off random characters that represent icons */\n.fa-glass:before {\n content: \"\\f000\";\n}\n.fa-music:before {\n content: \"\\f001\";\n}\n.fa-search:before {\n content: \"\\f002\";\n}\n.fa-envelope-o:before {\n content: \"\\f003\";\n}\n.fa-heart:before {\n content: \"\\f004\";\n}\n.fa-star:before {\n content: \"\\f005\";\n}\n.fa-star-o:before {\n content: \"\\f006\";\n}\n.fa-user:before {\n content: \"\\f007\";\n}\n.fa-film:before {\n content: \"\\f008\";\n}\n.fa-th-large:before {\n content: \"\\f009\";\n}\n.fa-th:before {\n content: \"\\f00a\";\n}\n.fa-th-list:before {\n content: \"\\f00b\";\n}\n.fa-check:before {\n content: \"\\f00c\";\n}\n.fa-remove:before,\n.fa-close:before,\n.fa-times:before {\n content: \"\\f00d\";\n}\n.fa-search-plus:before {\n content: \"\\f00e\";\n}\n.fa-search-minus:before {\n content: \"\\f010\";\n}\n.fa-power-off:before {\n content: \"\\f011\";\n}\n.fa-signal:before {\n content: \"\\f012\";\n}\n.fa-gear:before,\n.fa-cog:before {\n content: \"\\f013\";\n}\n.fa-trash-o:before {\n content: \"\\f014\";\n}\n.fa-home:before {\n content: \"\\f015\";\n}\n.fa-file-o:before {\n content: \"\\f016\";\n}\n.fa-clock-o:before {\n content: \"\\f017\";\n}\n.fa-road:before {\n content: \"\\f018\";\n}\n.fa-download:before {\n content: \"\\f019\";\n}\n.fa-arrow-circle-o-down:before {\n content: \"\\f01a\";\n}\n.fa-arrow-circle-o-up:before {\n content: \"\\f01b\";\n}\n.fa-inbox:before {\n content: \"\\f01c\";\n}\n.fa-play-circle-o:before {\n content: \"\\f01d\";\n}\n.fa-rotate-right:before,\n.fa-repeat:before {\n content: \"\\f01e\";\n}\n.fa-refresh:before {\n content: \"\\f021\";\n}\n.fa-list-alt:before {\n content: \"\\f022\";\n}\n.fa-lock:before {\n content: \"\\f023\";\n}\n.fa-flag:before {\n content: \"\\f024\";\n}\n.fa-headphones:before {\n content: \"\\f025\";\n}\n.fa-volume-off:before {\n content: \"\\f026\";\n}\n.fa-volume-down:before {\n content: \"\\f027\";\n}\n.fa-volume-up:before {\n content: \"\\f028\";\n}\n.fa-qrcode:before {\n content: \"\\f029\";\n}\n.fa-barcode:before {\n content: \"\\f02a\";\n}\n.fa-tag:before {\n content: \"\\f02b\";\n}\n.fa-tags:before {\n content: \"\\f02c\";\n}\n.fa-book:before {\n content: \"\\f02d\";\n}\n.fa-bookmark:before {\n content: \"\\f02e\";\n}\n.fa-print:before {\n content: \"\\f02f\";\n}\n.fa-camera:before {\n content: \"\\f030\";\n}\n.fa-font:before {\n content: \"\\f031\";\n}\n.fa-bold:before {\n content: \"\\f032\";\n}\n.fa-italic:before {\n content: \"\\f033\";\n}\n.fa-text-height:before {\n content: \"\\f034\";\n}\n.fa-text-width:before {\n content: \"\\f035\";\n}\n.fa-align-left:before {\n content: \"\\f036\";\n}\n.fa-align-center:before {\n content: \"\\f037\";\n}\n.fa-align-right:before {\n content: \"\\f038\";\n}\n.fa-align-justify:before {\n content: \"\\f039\";\n}\n.fa-list:before {\n content: \"\\f03a\";\n}\n.fa-dedent:before,\n.fa-outdent:before {\n content: \"\\f03b\";\n}\n.fa-indent:before {\n content: \"\\f03c\";\n}\n.fa-video-camera:before {\n content: \"\\f03d\";\n}\n.fa-photo:before,\n.fa-image:before,\n.fa-picture-o:before {\n content: \"\\f03e\";\n}\n.fa-pencil:before {\n content: \"\\f040\";\n}\n.fa-map-marker:before {\n content: \"\\f041\";\n}\n.fa-adjust:before {\n content: \"\\f042\";\n}\n.fa-tint:before {\n content: \"\\f043\";\n}\n.fa-edit:before,\n.fa-pencil-square-o:before {\n content: \"\\f044\";\n}\n.fa-share-square-o:before {\n content: \"\\f045\";\n}\n.fa-check-square-o:before {\n content: \"\\f046\";\n}\n.fa-arrows:before {\n content: \"\\f047\";\n}\n.fa-step-backward:before {\n content: \"\\f048\";\n}\n.fa-fast-backward:before {\n content: \"\\f049\";\n}\n.fa-backward:before {\n content: \"\\f04a\";\n}\n.fa-play:before {\n content: \"\\f04b\";\n}\n.fa-pause:before {\n content: \"\\f04c\";\n}\n.fa-stop:before {\n content: \"\\f04d\";\n}\n.fa-forward:before {\n content: \"\\f04e\";\n}\n.fa-fast-forward:before {\n content: \"\\f050\";\n}\n.fa-step-forward:before {\n content: \"\\f051\";\n}\n.fa-eject:before {\n content: \"\\f052\";\n}\n.fa-chevron-left:before {\n content: \"\\f053\";\n}\n.fa-chevron-right:before {\n content: \"\\f054\";\n}\n.fa-plus-circle:before {\n content: \"\\f055\";\n}\n.fa-minus-circle:before {\n content: \"\\f056\";\n}\n.fa-times-circle:before {\n content: \"\\f057\";\n}\n.fa-check-circle:before {\n content: \"\\f058\";\n}\n.fa-question-circle:before {\n content: \"\\f059\";\n}\n.fa-info-circle:before {\n content: \"\\f05a\";\n}\n.fa-crosshairs:before {\n content: \"\\f05b\";\n}\n.fa-times-circle-o:before {\n content: \"\\f05c\";\n}\n.fa-check-circle-o:before {\n content: \"\\f05d\";\n}\n.fa-ban:before {\n content: \"\\f05e\";\n}\n.fa-arrow-left:before {\n content: \"\\f060\";\n}\n.fa-arrow-right:before {\n content: \"\\f061\";\n}\n.fa-arrow-up:before {\n content: \"\\f062\";\n}\n.fa-arrow-down:before {\n content: \"\\f063\";\n}\n.fa-mail-forward:before,\n.fa-share:before {\n content: \"\\f064\";\n}\n.fa-expand:before {\n content: \"\\f065\";\n}\n.fa-compress:before {\n content: \"\\f066\";\n}\n.fa-plus:before {\n content: \"\\f067\";\n}\n.fa-minus:before {\n content: \"\\f068\";\n}\n.fa-asterisk:before {\n content: \"\\f069\";\n}\n.fa-exclamation-circle:before {\n content: \"\\f06a\";\n}\n.fa-gift:before {\n content: \"\\f06b\";\n}\n.fa-leaf:before {\n content: \"\\f06c\";\n}\n.fa-fire:before {\n content: \"\\f06d\";\n}\n.fa-eye:before {\n content: \"\\f06e\";\n}\n.fa-eye-slash:before {\n content: \"\\f070\";\n}\n.fa-warning:before,\n.fa-exclamation-triangle:before {\n content: \"\\f071\";\n}\n.fa-plane:before {\n content: \"\\f072\";\n}\n.fa-calendar:before {\n content: \"\\f073\";\n}\n.fa-random:before {\n content: \"\\f074\";\n}\n.fa-comment:before {\n content: \"\\f075\";\n}\n.fa-magnet:before {\n content: \"\\f076\";\n}\n.fa-chevron-up:before {\n content: \"\\f077\";\n}\n.fa-chevron-down:before {\n content: \"\\f078\";\n}\n.fa-retweet:before {\n content: \"\\f079\";\n}\n.fa-shopping-cart:before {\n content: \"\\f07a\";\n}\n.fa-folder:before {\n content: \"\\f07b\";\n}\n.fa-folder-open:before {\n content: \"\\f07c\";\n}\n.fa-arrows-v:before {\n content: \"\\f07d\";\n}\n.fa-arrows-h:before {\n content: \"\\f07e\";\n}\n.fa-bar-chart-o:before,\n.fa-bar-chart:before {\n content: \"\\f080\";\n}\n.fa-twitter-square:before {\n content: \"\\f081\";\n}\n.fa-facebook-square:before {\n content: \"\\f082\";\n}\n.fa-camera-retro:before {\n content: \"\\f083\";\n}\n.fa-key:before {\n content: \"\\f084\";\n}\n.fa-gears:before,\n.fa-cogs:before {\n content: \"\\f085\";\n}\n.fa-comments:before {\n content: \"\\f086\";\n}\n.fa-thumbs-o-up:before {\n content: \"\\f087\";\n}\n.fa-thumbs-o-down:before {\n content: \"\\f088\";\n}\n.fa-star-half:before {\n content: \"\\f089\";\n}\n.fa-heart-o:before {\n content: \"\\f08a\";\n}\n.fa-sign-out:before {\n content: \"\\f08b\";\n}\n.fa-linkedin-square:before {\n content: \"\\f08c\";\n}\n.fa-thumb-tack:before {\n content: \"\\f08d\";\n}\n.fa-external-link:before {\n content: \"\\f08e\";\n}\n.fa-sign-in:before {\n content: \"\\f090\";\n}\n.fa-trophy:before {\n content: \"\\f091\";\n}\n.fa-github-square:before {\n content: \"\\f092\";\n}\n.fa-upload:before {\n content: \"\\f093\";\n}\n.fa-lemon-o:before {\n content: \"\\f094\";\n}\n.fa-phone:before {\n content: \"\\f095\";\n}\n.fa-square-o:before {\n content: \"\\f096\";\n}\n.fa-bookmark-o:before {\n content: \"\\f097\";\n}\n.fa-phone-square:before {\n content: \"\\f098\";\n}\n.fa-twitter:before {\n content: \"\\f099\";\n}\n.fa-facebook:before {\n content: \"\\f09a\";\n}\n.fa-github:before {\n content: \"\\f09b\";\n}\n.fa-unlock:before {\n content: \"\\f09c\";\n}\n.fa-credit-card:before {\n content: \"\\f09d\";\n}\n.fa-rss:before {\n content: \"\\f09e\";\n}\n.fa-hdd-o:before {\n content: \"\\f0a0\";\n}\n.fa-bullhorn:before {\n content: \"\\f0a1\";\n}\n.fa-bell:before {\n content: \"\\f0f3\";\n}\n.fa-certificate:before {\n content: \"\\f0a3\";\n}\n.fa-hand-o-right:before {\n content: \"\\f0a4\";\n}\n.fa-hand-o-left:before {\n content: \"\\f0a5\";\n}\n.fa-hand-o-up:before {\n content: \"\\f0a6\";\n}\n.fa-hand-o-down:before {\n content: \"\\f0a7\";\n}\n.fa-arrow-circle-left:before {\n content: \"\\f0a8\";\n}\n.fa-arrow-circle-right:before {\n content: \"\\f0a9\";\n}\n.fa-arrow-circle-up:before {\n content: \"\\f0aa\";\n}\n.fa-arrow-circle-down:before {\n content: \"\\f0ab\";\n}\n.fa-globe:before {\n content: \"\\f0ac\";\n}\n.fa-wrench:before {\n content: \"\\f0ad\";\n}\n.fa-tasks:before {\n content: \"\\f0ae\";\n}\n.fa-filter:before {\n content: \"\\f0b0\";\n}\n.fa-briefcase:before {\n content: \"\\f0b1\";\n}\n.fa-arrows-alt:before {\n content: \"\\f0b2\";\n}\n.fa-group:before,\n.fa-users:before {\n content: \"\\f0c0\";\n}\n.fa-chain:before,\n.fa-link:before {\n content: \"\\f0c1\";\n}\n.fa-cloud:before {\n content: \"\\f0c2\";\n}\n.fa-flask:before {\n content: \"\\f0c3\";\n}\n.fa-cut:before,\n.fa-scissors:before {\n content: \"\\f0c4\";\n}\n.fa-copy:before,\n.fa-files-o:before {\n content: \"\\f0c5\";\n}\n.fa-paperclip:before {\n content: \"\\f0c6\";\n}\n.fa-save:before,\n.fa-floppy-o:before {\n content: \"\\f0c7\";\n}\n.fa-square:before {\n content: \"\\f0c8\";\n}\n.fa-navicon:before,\n.fa-reorder:before,\n.fa-bars:before {\n content: \"\\f0c9\";\n}\n.fa-list-ul:before {\n content: \"\\f0ca\";\n}\n.fa-list-ol:before {\n content: \"\\f0cb\";\n}\n.fa-strikethrough:before {\n content: \"\\f0cc\";\n}\n.fa-underline:before {\n content: \"\\f0cd\";\n}\n.fa-table:before {\n content: \"\\f0ce\";\n}\n.fa-magic:before {\n content: \"\\f0d0\";\n}\n.fa-truck:before {\n content: \"\\f0d1\";\n}\n.fa-pinterest:before {\n content: \"\\f0d2\";\n}\n.fa-pinterest-square:before {\n content: \"\\f0d3\";\n}\n.fa-google-plus-square:before {\n content: \"\\f0d4\";\n}\n.fa-google-plus:before {\n content: \"\\f0d5\";\n}\n.fa-money:before {\n content: \"\\f0d6\";\n}\n.fa-caret-down:before {\n content: \"\\f0d7\";\n}\n.fa-caret-up:before {\n content: \"\\f0d8\";\n}\n.fa-caret-left:before {\n content: \"\\f0d9\";\n}\n.fa-caret-right:before {\n content: \"\\f0da\";\n}\n.fa-columns:before {\n content: \"\\f0db\";\n}\n.fa-unsorted:before,\n.fa-sort:before {\n content: \"\\f0dc\";\n}\n.fa-sort-down:before,\n.fa-sort-desc:before {\n content: \"\\f0dd\";\n}\n.fa-sort-up:before,\n.fa-sort-asc:before {\n content: \"\\f0de\";\n}\n.fa-envelope:before {\n content: \"\\f0e0\";\n}\n.fa-linkedin:before {\n content: \"\\f0e1\";\n}\n.fa-rotate-left:before,\n.fa-undo:before {\n content: \"\\f0e2\";\n}\n.fa-legal:before,\n.fa-gavel:before {\n content: \"\\f0e3\";\n}\n.fa-dashboard:before,\n.fa-tachometer:before {\n content: \"\\f0e4\";\n}\n.fa-comment-o:before {\n content: \"\\f0e5\";\n}\n.fa-comments-o:before {\n content: \"\\f0e6\";\n}\n.fa-flash:before,\n.fa-bolt:before {\n content: \"\\f0e7\";\n}\n.fa-sitemap:before {\n content: \"\\f0e8\";\n}\n.fa-umbrella:before {\n content: \"\\f0e9\";\n}\n.fa-paste:before,\n.fa-clipboard:before {\n content: \"\\f0ea\";\n}\n.fa-lightbulb-o:before {\n content: \"\\f0eb\";\n}\n.fa-exchange:before {\n content: \"\\f0ec\";\n}\n.fa-cloud-download:before {\n content: \"\\f0ed\";\n}\n.fa-cloud-upload:before {\n content: \"\\f0ee\";\n}\n.fa-user-md:before {\n content: \"\\f0f0\";\n}\n.fa-stethoscope:before {\n content: \"\\f0f1\";\n}\n.fa-suitcase:before {\n content: \"\\f0f2\";\n}\n.fa-bell-o:before {\n content: \"\\f0a2\";\n}\n.fa-coffee:before {\n content: \"\\f0f4\";\n}\n.fa-cutlery:before {\n content: \"\\f0f5\";\n}\n.fa-file-text-o:before {\n content: \"\\f0f6\";\n}\n.fa-building-o:before {\n content: \"\\f0f7\";\n}\n.fa-hospital-o:before {\n content: \"\\f0f8\";\n}\n.fa-ambulance:before {\n content: \"\\f0f9\";\n}\n.fa-medkit:before {\n content: \"\\f0fa\";\n}\n.fa-fighter-jet:before {\n content: \"\\f0fb\";\n}\n.fa-beer:before {\n content: \"\\f0fc\";\n}\n.fa-h-square:before {\n content: \"\\f0fd\";\n}\n.fa-plus-square:before {\n content: \"\\f0fe\";\n}\n.fa-angle-double-left:before {\n content: \"\\f100\";\n}\n.fa-angle-double-right:before {\n content: \"\\f101\";\n}\n.fa-angle-double-up:before {\n content: \"\\f102\";\n}\n.fa-angle-double-down:before {\n content: \"\\f103\";\n}\n.fa-angle-left:before {\n content: \"\\f104\";\n}\n.fa-angle-right:before {\n content: \"\\f105\";\n}\n.fa-angle-up:before {\n content: \"\\f106\";\n}\n.fa-angle-down:before {\n content: \"\\f107\";\n}\n.fa-desktop:before {\n content: \"\\f108\";\n}\n.fa-laptop:before {\n content: \"\\f109\";\n}\n.fa-tablet:before {\n content: \"\\f10a\";\n}\n.fa-mobile-phone:before,\n.fa-mobile:before {\n content: \"\\f10b\";\n}\n.fa-circle-o:before {\n content: \"\\f10c\";\n}\n.fa-quote-left:before {\n content: \"\\f10d\";\n}\n.fa-quote-right:before {\n content: \"\\f10e\";\n}\n.fa-spinner:before {\n content: \"\\f110\";\n}\n.fa-circle:before {\n content: \"\\f111\";\n}\n.fa-mail-reply:before,\n.fa-reply:before {\n content: \"\\f112\";\n}\n.fa-github-alt:before {\n content: \"\\f113\";\n}\n.fa-folder-o:before {\n content: \"\\f114\";\n}\n.fa-folder-open-o:before {\n content: \"\\f115\";\n}\n.fa-smile-o:before {\n content: \"\\f118\";\n}\n.fa-frown-o:before {\n content: \"\\f119\";\n}\n.fa-meh-o:before {\n content: \"\\f11a\";\n}\n.fa-gamepad:before {\n content: \"\\f11b\";\n}\n.fa-keyboard-o:before {\n content: \"\\f11c\";\n}\n.fa-flag-o:before {\n content: \"\\f11d\";\n}\n.fa-flag-checkered:before {\n content: \"\\f11e\";\n}\n.fa-terminal:before {\n content: \"\\f120\";\n}\n.fa-code:before {\n content: \"\\f121\";\n}\n.fa-mail-reply-all:before,\n.fa-reply-all:before {\n content: \"\\f122\";\n}\n.fa-star-half-empty:before,\n.fa-star-half-full:before,\n.fa-star-half-o:before {\n content: \"\\f123\";\n}\n.fa-location-arrow:before {\n content: \"\\f124\";\n}\n.fa-crop:before {\n content: \"\\f125\";\n}\n.fa-code-fork:before {\n content: \"\\f126\";\n}\n.fa-unlink:before,\n.fa-chain-broken:before {\n content: \"\\f127\";\n}\n.fa-question:before {\n content: \"\\f128\";\n}\n.fa-info:before {\n content: \"\\f129\";\n}\n.fa-exclamation:before {\n content: \"\\f12a\";\n}\n.fa-superscript:before {\n content: \"\\f12b\";\n}\n.fa-subscript:before {\n content: \"\\f12c\";\n}\n.fa-eraser:before {\n content: \"\\f12d\";\n}\n.fa-puzzle-piece:before {\n content: \"\\f12e\";\n}\n.fa-microphone:before {\n content: \"\\f130\";\n}\n.fa-microphone-slash:before {\n content: \"\\f131\";\n}\n.fa-shield:before {\n content: \"\\f132\";\n}\n.fa-calendar-o:before {\n content: \"\\f133\";\n}\n.fa-fire-extinguisher:before {\n content: \"\\f134\";\n}\n.fa-rocket:before {\n content: \"\\f135\";\n}\n.fa-maxcdn:before {\n content: \"\\f136\";\n}\n.fa-chevron-circle-left:before {\n content: \"\\f137\";\n}\n.fa-chevron-circle-right:before {\n content: \"\\f138\";\n}\n.fa-chevron-circle-up:before {\n content: \"\\f139\";\n}\n.fa-chevron-circle-down:before {\n content: \"\\f13a\";\n}\n.fa-html5:before {\n content: \"\\f13b\";\n}\n.fa-css3:before {\n content: \"\\f13c\";\n}\n.fa-anchor:before {\n content: \"\\f13d\";\n}\n.fa-unlock-alt:before {\n content: \"\\f13e\";\n}\n.fa-bullseye:before {\n content: \"\\f140\";\n}\n.fa-ellipsis-h:before {\n content: \"\\f141\";\n}\n.fa-ellipsis-v:before {\n content: \"\\f142\";\n}\n.fa-rss-square:before {\n content: \"\\f143\";\n}\n.fa-play-circle:before {\n content: \"\\f144\";\n}\n.fa-ticket:before {\n content: \"\\f145\";\n}\n.fa-minus-square:before {\n content: \"\\f146\";\n}\n.fa-minus-square-o:before {\n content: \"\\f147\";\n}\n.fa-level-up:before {\n content: \"\\f148\";\n}\n.fa-level-down:before {\n content: \"\\f149\";\n}\n.fa-check-square:before {\n content: \"\\f14a\";\n}\n.fa-pencil-square:before {\n content: \"\\f14b\";\n}\n.fa-external-link-square:before {\n content: \"\\f14c\";\n}\n.fa-share-square:before {\n content: \"\\f14d\";\n}\n.fa-compass:before {\n content: \"\\f14e\";\n}\n.fa-toggle-down:before,\n.fa-caret-square-o-down:before {\n content: \"\\f150\";\n}\n.fa-toggle-up:before,\n.fa-caret-square-o-up:before {\n content: \"\\f151\";\n}\n.fa-toggle-right:before,\n.fa-caret-square-o-right:before {\n content: \"\\f152\";\n}\n.fa-euro:before,\n.fa-eur:before {\n content: \"\\f153\";\n}\n.fa-gbp:before {\n content: \"\\f154\";\n}\n.fa-dollar:before,\n.fa-usd:before {\n content: \"\\f155\";\n}\n.fa-rupee:before,\n.fa-inr:before {\n content: \"\\f156\";\n}\n.fa-cny:before,\n.fa-rmb:before,\n.fa-yen:before,\n.fa-jpy:before {\n content: \"\\f157\";\n}\n.fa-ruble:before,\n.fa-rouble:before,\n.fa-rub:before {\n content: \"\\f158\";\n}\n.fa-won:before,\n.fa-krw:before {\n content: \"\\f159\";\n}\n.fa-bitcoin:before,\n.fa-btc:before {\n content: \"\\f15a\";\n}\n.fa-file:before {\n content: \"\\f15b\";\n}\n.fa-file-text:before {\n content: \"\\f15c\";\n}\n.fa-sort-alpha-asc:before {\n content: \"\\f15d\";\n}\n.fa-sort-alpha-desc:before {\n content: \"\\f15e\";\n}\n.fa-sort-amount-asc:before {\n content: \"\\f160\";\n}\n.fa-sort-amount-desc:before {\n content: \"\\f161\";\n}\n.fa-sort-numeric-asc:before {\n content: \"\\f162\";\n}\n.fa-sort-numeric-desc:before {\n content: \"\\f163\";\n}\n.fa-thumbs-up:before {\n content: \"\\f164\";\n}\n.fa-thumbs-down:before {\n content: \"\\f165\";\n}\n.fa-youtube-square:before {\n content: \"\\f166\";\n}\n.fa-youtube:before {\n content: \"\\f167\";\n}\n.fa-xing:before {\n content: \"\\f168\";\n}\n.fa-xing-square:before {\n content: \"\\f169\";\n}\n.fa-youtube-play:before {\n content: \"\\f16a\";\n}\n.fa-dropbox:before {\n content: \"\\f16b\";\n}\n.fa-stack-overflow:before {\n content: \"\\f16c\";\n}\n.fa-instagram:before {\n content: \"\\f16d\";\n}\n.fa-flickr:before {\n content: \"\\f16e\";\n}\n.fa-adn:before {\n content: \"\\f170\";\n}\n.fa-bitbucket:before {\n content: \"\\f171\";\n}\n.fa-bitbucket-square:before {\n content: \"\\f172\";\n}\n.fa-tumblr:before {\n content: \"\\f173\";\n}\n.fa-tumblr-square:before {\n content: \"\\f174\";\n}\n.fa-long-arrow-down:before {\n content: \"\\f175\";\n}\n.fa-long-arrow-up:before {\n content: \"\\f176\";\n}\n.fa-long-arrow-left:before {\n content: \"\\f177\";\n}\n.fa-long-arrow-right:before {\n content: \"\\f178\";\n}\n.fa-apple:before {\n content: \"\\f179\";\n}\n.fa-windows:before {\n content: \"\\f17a\";\n}\n.fa-android:before {\n content: \"\\f17b\";\n}\n.fa-linux:before {\n content: \"\\f17c\";\n}\n.fa-dribbble:before {\n content: \"\\f17d\";\n}\n.fa-skype:before {\n content: \"\\f17e\";\n}\n.fa-foursquare:before {\n content: \"\\f180\";\n}\n.fa-trello:before {\n content: \"\\f181\";\n}\n.fa-female:before {\n content: \"\\f182\";\n}\n.fa-male:before {\n 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"created": "20140901110931199",
"modified": "20140901123139044",
"title": "$:/plugins/TheDiveO/FontAwesome/history",
"type": "text/vnd.tiddlywiki",
"text": "* ''v0.0.1-beta1'': initial plugin release.\n"
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"created": "20140901105404058",
"modified": "20140901123028557",
"title": "$:/plugins/TheDiveO/FontAwesome/license",
"type": "text/vnd.tiddlywiki",
"text": "This plugin is licensed as follows:\n\n* The embedded Font Awesome web font ...\n* The embedded Font Awesome CSS ...\n* everything else in this plugin by ~TheDiveO:\n** code ...\n** text, declarations, ..."
},
"$:/plugins/TheDiveO/FontAwesome/macros/fa/doc": {
"created": "20140831145557569",
"modified": "20140901072402790",
"title": "$:/plugins/TheDiveO/FontAwesome/macros/fa/doc",
"type": "text/vnd.tiddlywiki",
"text": "Convenience macro to typeset symbols from Font Awesome."
},
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"created": "20140831145445334",
"modified": "20140901072357327",
"title": "$:/plugins/TheDiveO/FontAwesome/macros/fa",
"type": "text/vnd.tiddlywiki",
"text": ""
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"$:/plugins/TheDiveO/FontAwesome/readme": {
"created": "20140901105307611",
"modified": "20140901122952432",
"title": "$:/plugins/TheDiveO/FontAwesome/readme",
"type": "text/vnd.tiddlywiki",
"text": "This plugin adds support for Font Awesome to your ~TiddlyWiki 5. It embeds the Font Awesome so there is no need to install this font in your operating system."
},
"$:/plugins/TheDiveO/FontAwesome": {
"author": "TheDiveO",
"created": "20140901105647564",
"description": "FontAwesome embedded font support for TW5",
"list": "readme license history",
"modified": "20140925072522173",
"plugin-type": "plugin",
"source": "https://github.com/TheDiveO/TW5FontAwesome",
"title": "$:/plugins/TheDiveO/FontAwesome",
"type": "application/json",
"version": "0.9.2-beta",
"text": "{\"tiddlers\":{}}"
},
"$:/plugins/TheDiveO/ThirdFlow": {
"author": "TheDiveO",
"created": "20140902114846490",
"description": "Third Flow in-TW plugin development process support",
"list": "readme license history",
"modified": "20140925071806857",
"plugin-type": "plugin",
"source": "http://thediveo.github.io/ThirdFlow",
"title": "$:/plugins/TheDiveO/ThirdFlow",
"type": "application/json",
"version": "1.0.4",
"text": "{\"tiddlers\":{\"$:/plugins/TheDiveO/ThirdFlow/commands/packplugin.js\":{\"created\":\"20140903124549244\",\"modified\":\"20140904125703672\",\"module-type\":\"command\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/commands/packplugin.js\",\"type\":\"application/javascript\",\"text\":\"/*\\\\\\r\\ntitle: $:/plugins/TheDiveO/ThirdFlow/commands/packplugin.js\\r\\ntype: application/javascript\\r\\nmodule-type: command\\n\\nPack plugin command:\\r\\n--packplugin <plugin title>\\n\\n\\\\*/\\r\\n(function(){\\n\\n/*jslint node: true, browser: true */\\r\\n/*global $tw: false */\\r\\n\\\"use strict\\\";\\n\\nexports.info = {\\r\\n\\tname: \\\"packplugin\\\",\\r\\n\\tsynchronous: true\\r\\n};\\n\\nvar Command = function(params,commander) {\\r\\n\\tthis.params = params;\\r\\n\\tthis.commander = commander;\\r\\n\\tthis.logger = new $tw.utils.Logger(\\\"--\\\" + exports.info.name);\\r\\n};\\n\\nCommand.prototype.execute = function() {\\r\\n\\tif(this.params.length < 1) {\\r\\n\\t\\treturn \\\"Missing plugin title\\\";\\r\\n\\t}\\r\\n\\tvar wiki = this.commander.wiki,\\r\\n\\t\\tself = this,\\r\\n\\t\\tfs = require(\\\"fs\\\"),\\r\\n\\t\\tpath = require(\\\"path\\\"),\\r\\n\\t\\tpluginTitle = this.params[0],\\r\\n\\t\\tfilter = this.params[1] ||\\r\\n\\t\\t\\t\\\"[prefix[\\\"+this.params[0]+\\\"/]]\\\";\\r\\n//\\t\\t\\t\\\"[field:title/\\\"+this.params[0].replace(/\\\\$/g, \\\"\\\\\\\\$\\\").replace(/\\\\//g, \\\"\\\\\\\\/\\\")+\\\"\\\\\\\\//]\\\";\\r\\n\\t\\t\\r\\n\\t// Get the plug-in self-description tiddler. If it doesn't exist,\\r\\n\\t// bail out as the plugin developer needs to provide a plugin tiddler\\r\\n\\t// with the required self-description.\\r\\n\\tthis.logger.log(\\\"making plugin\\\", pluginTitle);\\r\\n\\tthis.logger.log(\\\"using filter for packing\\\", filter);\\r\\n\\tvar pluginTiddler = $tw.wiki.getTiddler(pluginTitle);\\r\\n\\tif (!pluginTiddler) {\\r\\n\\t\\treturn \\\"missing plugin tiddler: \\\" + pluginTitle;\\r\\n\\t}\\r\\n\\t// Sanity checks first...\\r\\n\\tif(pluginTiddler.fields.type !== \\\"application/json\\\" || !pluginTiddler.hasField(\\\"plugin-type\\\")) {\\r\\n\\t\\treturn \\\"not a plugin skeleton: \\\" + pluginTitle;\\r\\n\\t}\\r\\n\\t// Update the plugin content to contain all the tiddlers that match\\r\\n\\t// the filter expression.\\r\\n\\tvar tiddlers = $tw.wiki.filterTiddlers(filter),\\r\\n\\t pluginTiddlers = {};\\r\\n\\t$tw.utils.each(tiddlers, function(title) {\\r\\n\\t\\tvar tiddler = $tw.wiki.getTiddler(title),\\r\\n\\t\\t fields = {};\\r\\n\\t\\tself.logger.log(\\\"adding \\\" + title);\\r\\n\\t\\t$tw.utils.each(tiddler.fields, function(value, name) {\\r\\n\\t\\t\\tfields[name] = tiddler.getFieldString(name);\\r\\n\\t\\t});\\r\\n\\t\\tpluginTiddlers[title] = fields;\\r\\n\\t});\\r\\n\\tthis.logger.log(\\\"packed\\\", tiddlers.length, \\\"tiddlers\\\");\\r\\n\\tvar plugin = new $tw.Tiddler(pluginTiddler, { text: JSON.stringify({tiddlers: pluginTiddlers}) });\\r\\n\\t$tw.wiki.addTiddler(plugin);\\r\\n\\t// We need to update the plugin info that TW had built up during boot...\\r\\n\\t$tw.wiki.readPluginInfo();\\r\\n\\t// ...and we need to re-unpack the plugins into their shadow tiddlers in\\r\\n\\t// order to make [is[shadow]] work correctly.\\r\\n\\t$tw.wiki.unpackPluginTiddlers();\\r\\n\\t\\r\\n\\treturn null; // done & okay\\r\\n};\\n\\nexports.Command = Command;\\n\\n})();\\r\\n\"},\"$:/plugins/TheDiveO/ThirdFlow/commands/rendertemplatedtiddler.js\":{\"created\":\"20140903121310285\",\"modified\":\"20140903125924374\",\"module-type\":\"command\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/commands/rendertemplatedtiddler.js\",\"type\":\"application/javascript\",\"text\":\"/*\\\\\\ntitle: $:/plugins/TheDiveO/ThirdFlow/commands/rendertemplatedtiddler.js\\ntype: application/javascript\\nmodule-type: command\\n\\nRender single tiddler using template command.\\n--rendertemplatedtiddler <title> <template> <file>\\n\\nCommand to render a single tiddler using a template to a specific file.\\nIn comparism to --rendertiddler this command variant accepts a template\\nbut only works on a single tiddler. This allows us to avoid having specific\\ntemplate tiddlers including the filter set.\\n\\n\\\\*/\\n(function(){\\n\\n/*jslint node: true, browser: true */\\n/*global $tw: false */\\n\\\"use strict\\\";\\n\\nvar widget = require(\\\"$:/core/modules/widgets/widget.js\\\");\\n\\nexports.info = {\\n\\tname: \\\"rendertemplatedtiddler\\\",\\n\\tsynchronous: true\\n};\\n\\nvar Command = function(params,commander) {\\n\\tthis.params = params;\\n\\tthis.commander = commander;\\n this.logger = new $tw.utils.Logger(\\\"--\\\" + exports.info.name);\\n};\\n\\nCommand.prototype.execute = function() {\\n\\tif(this.params.length < 3) {\\n\\t\\treturn \\\"Missing template or filename\\\";\\n\\t}\\n\\tvar self = this,\\n\\t\\tfs = require(\\\"fs\\\"),\\n\\t\\tpath = require(\\\"path\\\"),\\n\\t\\twiki = this.commander.wiki,\\n\\t\\ttitle = this.params[0],\\n\\t\\ttemplate = this.params[1],\\n\\t\\tfilename = path.resolve(this.commander.outputPath,this.params[2]);\\n\\t$tw.utils.createFileDirectories(filename);\\n\\t// Save the tiddler as a self contained templated file\\n\\tvar content = wiki.renderTiddler(\\\"text/plain\\\",template,{variables: {currentTiddler: title}});\\n\\tfs.writeFileSync(filename,content,{encoding: \\\"utf8\\\"});\\n this.logger.log(\\\"rendered tiddler\\\", title, \\\"to\\\", filename);\\n\\n\\treturn null; // done fine\\n};\\n\\nexports.Command = Command;\\n\\n})();\"},\"$:/plugins/TheDiveO/ThirdFlow/filters/is/shadowinsync.js\":{\"created\":\"20140903162951165\",\"modified\":\"20140904093120486\",\"module-type\":\"isfilteroperator\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/filters/is/shadowinsync.js\",\"type\":\"application/javascript\",\"text\":\"/*\\\\\\ntitle: $:/plugins/TheDiveO/ThirdFlow/filters/is/shadowinsync.js\\ntype: application/javascript\\nmodule-type: isfilteroperator\\n\\nFilter function for [is[shadowinsync]]\\n a tiddler is shadowsynced when it has a shadow tiddler\\n *AND* the shadow tiddler is the same as the real tiddler.\\n\\n\\\\*/\\n(function(){\\n\\n/*jslint node: true, browser: true */\\n/*global $tw: false */\\n\\\"use strict\\\";\\n\\n/*\\nExport our filter function\\n*/\\nexports.shadowinsync = function(source,prefix,options) {\\n\\tvar results = [];\\n\\tvar invert = prefix === \\\"!\\\";\\n\\tsource(function(tiddler,title) {\\n\\t\\tvar match = invert;\\n\\t\\tvar pluginTitle = options.wiki.getShadowSource(title);\\n\\t\\tif(pluginTitle) {\\n\\t\\t\\tvar pluginInfo = options.wiki.getPluginInfo(pluginTitle),\\n\\t\\t\\t\\tshadow = pluginInfo.tiddlers[title];\\n\\t\\t\\tif ( (tiddler.fields.type == shadow.type)\\n\\t\\t\\t && (tiddler.getFieldString(\\\"created\\\") === shadow.created)\\n\\t\\t\\t\\t && (tiddler.getFieldString(\\\"modified\\\") === shadow.modified) ) {\\n\\t\\t\\t\\tmatch = !match;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif ( match ) {\\n\\t\\t\\tresults.push(title);\\n\\t\\t}\\n\\t});\\n\\treturn results;\\n};\\n\\n})();\\n\"},\"$:/plugins/TheDiveO/ThirdFlow/history\":{\"created\":\"20140902083720188\",\"modified\":\"20140926170600649\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/history\",\"type\":\"text/vnd.tiddlywiki\",\"text\":\"* ''1.0.4'' -- fix and more documentation.\\n** fixed a typo in the (empty) source plugin tiddler itself which caused hiccups in ~TiddlyWiki's control panel plugin tab.\\n** added more background information about plugins, modules, and the crazy stuff the //Third Flow// plugin is made of. \\n* ''1.0.3'' -- upgraded to work with the final ~TiddlyWiki 5.1.x releases.\\n** fixed using deprecated regular expression when packing plugin tiddlers.\\n* ''1.0.2'' -- fix and polishing release.\\n** fixes a problem in the hierarchical filesystem sync adaptor that previously caused server aborts when adding JPEG tiddlers. The sync adaptor now defaults to the \\\"~~binary~~base64\\\" encoding whenever a meta file is required.\\n** added two illustrations to the demo documentation showing the develop and release phases.\\n** further minor documentation fixes and improvements.\\n* ''1.0.1'' -- fix and polishing release.\\n** fixes an issue where the user plugin demonstration wikis contained still the plugin source in addition to the plugin itself.\\n** included polishing documentation from pmario (thanks!).\\n* ''1.0.0'' -- this marks the first public release of the //Third Flow// plugin. Of course, the //Third Flow// eats its own dog food: this plugin has been developed with itself. Sweet, isn't it?\\n** the ``--makeplugin`` command for creating plugins in headless TW5 instances running under Node.js.\\n** the ``hierarchicalfilesystemadaptor`` sync adapter that stores tiddlers according to their hierarchical names into folders and subfolders.\\n\"},\"$:/plugins/TheDiveO/ThirdFlow/icon\":{\"created\":\"20140902083115519\",\"modified\":\"20140902083155746\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/icon\",\"type\":\"text/vnd.tiddlywiki\",\"text\":\"<svg width=\\\"22pt\\\" height=\\\"22pt\\\" viewBox=\\\"0 0 128 128\\\">\\n <g fill-rule=\\\"evenodd\\\">\\n <path\\n d=\\\"M 13.6875,0.21875 1.96875,7 l 0,13.53125 11.71875,6.78125 11.75,-6.78125 0,-13.53125 -11.75,-6.78125 z m -0.21875,2.9375 -0.21875,0.3125 -0.1875,0.21875 0.1875,0.25 0.15625,0.25 C 8.2238491,4.3516565 4.0625,8.5897663 4.0625,13.8125 c 0,1.53048 0.3643003,2.966927 1,4.25 l -0.25,0.53125 -0.625,-0.0625 C 3.4739437,17.106473 3.0625,15.512243 3.0625,13.8125 3.0625,8.028588 7.716283,3.2895221 13.46875,3.15625 z M 14.4375,3.1875 c 5.534617,0.369785 9.90625,4.9983374 9.90625,10.625 0,1.833581 -0.463357,3.557017 -1.28125,5.0625 l -0.125,-0.25 -0.125,-0.28125 -0.28125,0.03125 -0.34375,0.03125 c 0.739688,-1.363949 1.15625,-2.929057 1.15625,-4.59375 0,-5.0803341 -3.922604,-9.2511654 -8.90625,-9.625 l -0.375,-0.5 0.375,-0.5 z M 10.25,7.5 c 1.425042,0 2.639576,0.7576324 3.8125,1.40625 1.172923,0.6486176 2.283798,1.21875 3.09375,1.21875 C 19.100721,10.125 20,9.09375 20,9.09375 L 21.25,10.25 c 0,0 -1.500142,1.5625 -4.09375,1.5625 -1.459089,0 -2.728987,-0.755233 -3.90625,-1.40625 -1.177263,-0.6510172 -2.253123,-1.1875 -3,-1.1875 -1.8328368,0 -2.875,1.03125 -2.875,1.03125 L 6.1875,9.0625 c 0,0 1.5514984,-1.5625 4.0625,-1.5625 z m 0.0625,4.6875 c 1.28542,0 2.513683,0.725888 3.6875,1.375 1.173817,0.649112 2.306403,1.21875 3.25,1.21875 2.078117,0 3.09375,-1.125 3.09375,-1.125 l 0.71875,0.65625 c 0,0 -1.352537,1.46875 -3.8125,1.46875 -1.325443,0 -2.573631,-0.724477 -3.75,-1.375 -1.176369,-0.650523 -2.301,-1.21875 -3.1875,-1.21875 -1.9724586,0 -3.09375,1.15625 -3.09375,1.15625 L 6.5,13.625 c 0,0 1.4411209,-1.4375 3.8125,-1.4375 z m 0,3.84375 c 1.28542,0 2.482432,0.694638 3.65625,1.34375 1.173817,0.649112 2.306403,1.25 3.25,1.25 2.078118,0 3.09375,-1.15625 3.09375,-1.15625 l 0.75,0.6875 c 0,0 -1.383787,1.46875 -3.84375,1.46875 -1.325443,0 -2.54238,-0.724477 -3.71875,-1.375 -1.176369,-0.650523 -2.301001,-1.21875 -3.1875,-1.21875 -1.9724586,0 -3.125,1.125 -3.125,1.125 L 6.5,17.46875 c 0,0 1.4411209,-1.4375 3.8125,-1.4375 z M 5.53125,18.875 c 1.7052086,2.730869 4.727356,4.5625 8.1875,4.5625 3.288587,0 6.171115,-1.649342 7.90625,-4.15625 l 0.6875,-0.09375 0.25,0.53125 c -1.906345,2.846287 -5.161209,4.71875 -8.84375,4.71875 -3.8226661,0 -7.1815039,-2.032459 -9.0625,-5.0625 L 5,19.40625 5.3125,19.4375 5.40625,19.15625 5.53125,18.875 z\\\"\\n transform=\\\"scale(4.6545455,4.6545455)\\\"\\n id=\\\"path4245\\\"\\n style=\\\"fill-opacity:1;fill-rule:nonzero;stroke:none;stroke-width:0.80000001;marker:none;visibility:visible;display:inline;overflow:visible;enable-background:accumulate\\\" />\\n </g>\\n</svg>\"},\"$:/plugins/TheDiveO/ThirdFlow/license\":{\"created\":\"20140902084022063\",\"modified\":\"20140902090843205\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/license\",\"type\":\"text/vnd.tiddlywiki\",\"text\":\"The //Third Flow// plugin is covered by the following licenses:\\n\\n* The ''Third Flow plugin'' is licensed under the [[MIT license|http://opensource.org/licenses/MIT]].\\n* The ''hierarchical file system adapter'' is licensed under the [[TiddlyWiki 5 license|https://raw.githubusercontent.com/Jermolene/TiddlyWiki5/master/licenses/copyright.md]] (links to ~GitHub TW5 repository). It bases on ``plugins/tiddlywiki/filesystem/filesystemadaptor.js`` and brings in storing tiddlers into hierarchical folder structures according to their titles.\\n* Other content of this ~TiddlyWiki which is not part of the plugin or ~TiddlyWiki 5 is covered by the [[CC BY 3.0|http://creativecommons.org/licenses/by/3.0/]] license.\"},\"$:/plugins/TheDiveO/ThirdFlow/readme\":{\"created\":\"20140902083641711\",\"modified\":\"20140902130540097\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/readme\",\"type\":\"text/vnd.tiddlywiki\",\"text\":\"Use the //Third Flow// plugin in your Node.js-based ~TiddlyWikis to develop your customization plugins inside ~TiddlyWiki but with support for well-structured source code repository layouts.\\n\\nThe //Third Flow// plugin supports your plugin development in that it organizes all your tiddler source files into a clear hierarchical folder structure based on tiddler titles. An additional plugin creation command module makes it easy to create the package plugin itself as well as a demonstration ~TiddlyWiki without the hassle of having to maintain separate and even multiple ``tiddlers/`` and ``plugin/`` folders. Also, the //Third Flow// relieves you from shuffling tiddler source code files around in your source code repository.\\n\\nThere's only a ''single'' tiddler source code tree and it is synchronized to your tiddler's title-based structure. Thus, no more need for external editing sessions and source file shuffling.\\n\\nSimply install this plugin into your ~TiddlyWiki in which you are developing your customizations. For more information, please go to the [[Third Flow project website|http://thediveo.github.io/ThirdFlow]].\\n\\nEnjoy the //Third Flow//!\"},\"$:/plugins/TheDiveO/ThirdFlow/syncadapters/hierarchicalfilesystemadaptor.js\":{\"created\":\"20140904130857052\",\"modified\":\"20140904130903925\",\"module-type\":\"syncadaptor\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/syncadapters/hierarchicalfilesystemadaptor.js\",\"type\":\"application/javascript\",\"text\":\"/*\\\\\\r\\ntitle: $:/plugins/TheDiveO/ThirdFlow/syncadapters/hierarchicalfilesystemadaptor.js\\r\\ntype: application/javascript\\r\\nmodule-type: syncadaptor\\n\\nA sync adaptor module for synchronising with the local filesystem via node.js APIs\\r\\n...in contrast to filesystemadaptor.js this variant understands forward slashes \\\"/\\\"\\r\\nin tiddler titles and stores tiddlers appropriately in the file system by mapping\\r\\nthe hierarchy in the title to a (sub) directory structure.\\n\\nIn addition, this sync adaptor understands the concept of system tiddlers (starting\\r\\ntheir titles with \\\"$:/\\\") and stores them inside a \\\"special\\\" system branch.\\n\\nMoreover, this sync adaptor also understands the concept of draft tiddlers (based\\r\\non the presence of the \\\"draft.of\\\" field) and stores all draft tiddlers in a flat\\r\\nsingle \\\".draft\\\" folder. The makes cleanup and (git) repository syncing easier to do.\\n\\nThe code for this sync adaptor comes from filesystemadaptor.js and has been enhanced\\r\\nto support hierarchical tiddler storage.\\r\\n\\\\*/\\r\\n(function(){\\n\\n/*jslint node: true, browser: true */\\r\\n/*global $tw: false */\\r\\n\\\"use strict\\\";\\n\\n// Get a reference to the file system\\r\\nvar fs = !$tw.browser ? require(\\\"fs\\\") : null,\\r\\n\\tpath = !$tw.browser ? require(\\\"path\\\") : null;\\n\\nfunction HierarchicalFileSystemAdaptor(options) {\\r\\n\\tvar self = this;\\r\\n\\tthis.wiki = options.wiki;\\r\\n\\tthis.watchers = {};\\r\\n\\tthis.pending = {};\\r\\n\\tthis.logger = new $tw.utils.Logger(\\\"HierarchicalFileSystem\\\");\\r\\n\\tthis.setwatcher = function(filename, title) {\\r\\n\\t\\treturn undefined;\\r\\n\\t\\treturn this.watchers[filename] = this.watchers[filename] ||\\r\\n\\t\\t\\tfs.watch(filename, {persistent: false}, function(e) {\\r\\n\\t\\t\\t\\tself.logger.log(\\\"Error:\\\",e,filename);\\r\\n\\t\\t\\t\\tif(e === \\\"change\\\") {\\r\\n\\t\\t\\t\\t\\tvar tiddlers = $tw.loadTiddlersFromFile(filename).tiddlers;\\r\\n\\t\\t\\t\\t\\tfor(var t in tiddlers) {\\r\\n\\t\\t\\t\\t\\t\\tif(tiddlers[t].title) {\\r\\n\\t\\t\\t\\t\\t\\t\\tself.wiki.addTiddler(tiddlers[t]);\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t}\\n\\n\\tfor(var f in $tw.boot.files) {\\r\\n\\t\\tvar fileInfo = $tw.boot.files[f];\\r\\n\\t\\tthis.setwatcher(fileInfo.filepath, f);\\r\\n\\t}\\r\\n\\t// Create the <wiki>/tiddlers folder if it doesn't exist\\r\\n\\t// TODO: we should create the path recursively\\r\\n\\tif(!fs.existsSync($tw.boot.wikiTiddlersPath)) {\\r\\n\\t\\tfs.mkdirSync($tw.boot.wikiTiddlersPath);\\r\\n\\t}\\r\\n\\t\\r\\n\\tthis.config = {\\r\\n\\t\\tdisabled: false\\r\\n\\t};\\r\\n\\t\\r\\n\\tif($tw.boot.wikiInfo.config[\\\"disable-hfs\\\"]) {\\r\\n\\t\\tthis.config.disabled = true;\\r\\n\\t\\tthis.logger.log(\\\"plugin disabled; no saving and deleting\\\");\\r\\n\\t}\\r\\n}\\n\\n// TODO: may we have modularized plugin config options in the boot kernel?\\r\\n// The file system folder immediately below the <wiki>/tiddlers root used\\r\\n// to store system tiddlers that have titles starting with \\\"$:/\\\". Default\\r\\n// is \\\"system\\\" (please note: no trailing separator slash!).\\r\\nHierarchicalFileSystemAdaptor.prototype.SYSTEM_FOLDER = \\\"system\\\";\\r\\n// The draft folder immediately below the <wiki>/tiddlers root used\\r\\n// to store system tiddlers that have their draft.of field set. Default\\r\\n// is \\\".drafts\\\" (please note: no trailing separator slash!).\\r\\nHierarchicalFileSystemAdaptor.prototype.DRAFT_FOLDER = \\\".drafts\\\";\\n\\nHierarchicalFileSystemAdaptor.prototype.getTiddlerInfo = function(tiddler) {\\r\\n\\treturn {};\\r\\n};\\n\\n// Nota Bene: this needs to mirror the file extension information as established\\r\\n// in function $tw.boot.startup (boot.js). Otherwise, the sync adaptor will use\\r\\n// another encoding than expected by the boot process.\\r\\n$tw.config.typeInfo = {\\r\\n\\t\\\"text/vnd.tiddlywiki\\\": {\\r\\n\\t\\tfileType: \\\"application/x-tiddler\\\",\\r\\n\\t\\textension: \\\".tid\\\"\\r\\n\\t},\\r\\n\\t\\\"image/jpeg\\\" : {\\r\\n\\t\\thasMetaFile: true,\\r\\n\\t\\tencoding: \\\"base64\\\"\\r\\n\\t},\\r\\n\\t\\\"image/png\\\" : {\\r\\n\\t\\thasMetaFile: true,\\r\\n\\t\\tencoding: \\\"base64\\\"\\r\\n\\t}\\r\\n};\\n\\n$tw.config.typeTemplates = {\\r\\n\\t\\\"application/x-tiddler\\\": \\\"$:/core/templates/tid-tiddler\\\"\\r\\n};\\n\\n// mkdirp as in \\\"mkdir -p\\\" ;)\\r\\n// Ensures that all subdirectories are created along the path, as necessary.\\r\\n// Fully asynchronous operation. \\r\\nHierarchicalFileSystemAdaptor.prototype.mkdirp = function(dir, callback) {\\r\\n\\tvar mkdirf = function(dir, callback) {\\r\\n\\t\\t// head recursion: try to create the directory specified and\\r\\n\\t\\t// see what happens. If it exists, then fine and we're done. If\\r\\n\\t\\t// it doesn't exist, then go up one directory level in the directory\\r\\n\\t\\t// path and recurse down in trying to create the parent directory.\\r\\n\\t\\tfs.mkdir(dir, function(err) {\\r\\n\\t\\t\\tif(!err || err.code === \\\"EEXIST\\\") {\\r\\n\\t\\t\\t\\t// either we succeeded or the directory already existed,\\r\\n\\t\\t\\t\\t// so we're done here. We don't see this as an error,\\r\\n\\t\\t\\t\\t// it's just fine.\\r\\n\\t\\t\\t\\treturn callback(null);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tif(err.code !== \\\"ENOENT\\\") {\\r\\n\\t\\t\\t\\t// signal all other errors when trying to create the\\r\\n\\t\\t\\t\\t// directory directly to the callback. Typically, we\\r\\n\\t\\t\\t\\t// will unwind here up to the original caller.\\r\\n\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t// So we're stuck with ENOENT ... that means that one or more\\r\\n\\t\\t\\t// parent directories are still missing. We now need to recurse\\r\\n\\t\\t\\t// by going up the directory path elements; but not beyond the\\r\\n\\t\\t\\t// beginning.\\r\\n\\t\\t\\tvar parent = path.dirname(dir);\\r\\n\\t\\t\\tif(parent === dir) {\\r\\n\\t\\t\\t\\t// when we've hit the root ENOENT then actually is\\r\\n\\t\\t\\t\\t// an error and we thus report it back.\\r\\n\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tmkdirf(parent, function(err) {\\r\\n\\t\\t\\t\\t// tail fixup: parent directories should now have been\\r\\n\\t\\t\\t\\t// created in case they didn't exist before. But beware\\r\\n\\t\\t\\t\\t// of other errors, as usual ... bail out if we couldn't\\r\\n\\t\\t\\t\\t// create the required parent directories.\\r\\n\\t\\t\\t\\tif(err && err.code !== \\\"EEXIST\\\") {\\r\\n\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t// Finally: we try to create this particular directory\\r\\n\\t\\t\\t\\t// and notify the caller that we're done one way or\\r\\n\\t\\t\\t\\t// the other...\\r\\n\\t\\t\\t\\tfs.mkdir(dir, function(err) {\\r\\n\\t\\t\\t\\t\\tif (err && err.code !== \\\"EEXIST\\\") {\\r\\n\\t\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\treturn callback(null);\\r\\n\\t\\t\\t\\t});\\r\\n\\t\\t\\t});\\r\\n\\t\\t});\\r\\n\\t};\\r\\n\\t// get the whole shebang rolling...\\r\\n\\tmkdirf(path.resolve(dir), callback);\\r\\n};\\n\\nHierarchicalFileSystemAdaptor.prototype.getTiddlerFileInfo = function(tiddler,callback) {\\r\\n\\t// See if we've already got information about this file\\r\\n\\tvar self = this,\\r\\n\\t\\ttitle = tiddler.fields.title,\\r\\n\\t\\tfileInfo = $tw.boot.files[title],\\r\\n\\t\\tdraftOf = tiddler.fields[\\\"draft.of\\\"];\\r\\n\\t// Get information about how to save tiddlers of this type\\r\\n\\tvar type = tiddler.fields.type || \\\"text/vnd.tiddlywiki\\\",\\r\\n\\t\\ttypeInfo = $tw.config.typeInfo[type];\\r\\n\\tif(!typeInfo) {\\r\\n\\t\\ttypeInfo = $tw.config.typeInfo[\\\"text/vnd.tiddlywiki\\\"];\\r\\n\\t}\\r\\n\\tvar extension = typeInfo.extension || \\\"\\\";\\r\\n\\tif(!fileInfo) {\\r\\n\\t\\t// If not, we'll need to generate it\\r\\n\\t\\t// Start by getting a list of the existing files in the directory\\r\\n\\t\\tfs.readdir($tw.boot.wikiTiddlersPath,function(err,files) {\\r\\n\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t// Assemble the new fileInfo\\r\\n\\t\\t\\tfileInfo = {};\\r\\n\\t\\t\\tfileInfo.filepath = $tw.boot.wikiTiddlersPath + path.sep + self.generateTiddlerFilename(title,draftOf,extension,files);\\r\\n\\t\\t\\tfileInfo.type = typeInfo.fileType || tiddler.fields.type;\\r\\n\\t\\t\\tfileInfo.hasMetaFile = typeInfo.hasMetaFile;\\r\\n\\t\\t\\t// Save the newly created fileInfo\\r\\n\\t\\t\\t$tw.boot.files[title] = fileInfo;\\r\\n\\t\\t\\tself.pending[fileInfo.filepath] = title;\\r\\n\\t\\t\\t// Pass it to the callback\\r\\n\\t\\t\\tcallback(null,fileInfo);\\r\\n\\t\\t});\\r\\n\\t} else {\\r\\n\\t\\t// Otherwise just invoke the callback\\r\\n\\t\\tcallback(null,fileInfo);\\r\\n\\t}\\r\\n};\\n\\n/*\\r\\nGiven a tiddler title and an array of existing filenames, generate a new legal filename for the title, case insensitively avoiding the array of existing filenames\\r\\n*/\\r\\nHierarchicalFileSystemAdaptor.prototype.generateTiddlerFilename = function(title,draftOf,extension,existingFilenames) {\\r\\n\\t// First remove any of the characters that are illegal in Windows filenames\\r\\n\\t//var baseFilename = title.replace(/\\\\<|\\\\>|\\\\:|\\\\\\\"|\\\\/|\\\\\\\\|\\\\||\\\\?|\\\\*|\\\\^/g,\\\"_\\\");\\r\\n\\t// Derive a hierarchical filename that is compatible with file system\\r\\n\\t// naming conventions.\\r\\n\\tvar baseFilename;\\r\\n\\tif(!draftOf) {\\r\\n\\t\\t// For non-draft tiddlers now use the hierarchical file system storage\\r\\n\\t\\tbaseFilename = title.replace(/^\\\\$:\\\\//, HierarchicalFileSystemAdaptor.prototype.SYSTEM_FOLDER + \\\"/\\\");\\r\\n\\t\\tbaseFilename = baseFilename.replace(/\\\\<|\\\\>|\\\\:|\\\\\\\"|\\\\\\\\|\\\\||\\\\?|\\\\*|\\\\^/g,\\\"_\\\");\\r\\n\\t} else {\\r\\n\\t\\t// Draft tiddlers go into their own flat drafts folder...\\t\\r\\n\\t\\tbaseFilename = HierarchicalFileSystemAdaptor.prototype.DRAFT_FOLDER + \\\"/\\\";\\r\\n\\t\\tbaseFilename += title.replace(/\\\\<|\\\\>|\\\\:|\\\\\\\"|\\\\/|\\\\\\\\|\\\\||\\\\?|\\\\*|\\\\^/g,\\\"_\\\");\\r\\n\\t}\\r\\n\\t// Finally ensure that all slashes get converted into the appropriate\\r\\n\\t// platform-specific path separator.\\r\\n\\tbaseFilename = baseFilename.replace(/\\\\//g, path.sep);\\r\\n\\t\\r\\n\\t// Truncate the filename if it is too long\\r\\n\\tif(baseFilename.length > 200) {\\r\\n\\t\\tbaseFilename = baseFilename.substr(0,200);\\r\\n\\t}\\r\\n\\t// Start with the base filename plus the extension\\r\\n\\tvar filename = baseFilename + extension,\\r\\n\\t\\tcount = 1;\\r\\n\\t// Add a discriminator if we're clashing with an existing filename\\r\\n\\twhile(existingFilenames.indexOf(filename) !== -1) {\\r\\n\\t\\tfilename = baseFilename + \\\" \\\" + (count++) + extension;\\r\\n\\t}\\r\\n\\treturn filename;\\r\\n};\\n\\n/*\\r\\nSave a tiddler and invoke the callback with (err,adaptorInfo,revision)\\r\\n*/\\r\\nHierarchicalFileSystemAdaptor.prototype.saveTiddler = function(tiddler,callback) {\\r\\n\\tif(this.config.disabled) {\\r\\n\\t\\tthis.logger.log(\\\"saving disabled\\\");\\r\\n\\t\\treturn callback(null, {}, 0);\\r\\n\\t}\\r\\n\\t\\r\\n\\tvar self = this;\\r\\n\\tthis.getTiddlerFileInfo(tiddler,function(err,fileInfo) {\\r\\n\\t\\tvar template, content, encoding;\\r\\n\\t\\tfunction _finish() {\\r\\n\\t\\t\\tif(self.pending[fileInfo.filepath]) {\\r\\n\\t\\t\\t\\tself.setwatcher(fileInfo.filepath, tiddler.fields.title);\\r\\n\\t\\t\\t\\tdelete self.pending[fileInfo.filepath];\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tcallback(null, {}, 0);\\r\\n\\t\\t}\\r\\n\\t\\tif(err) {\\r\\n\\t\\t\\treturn callback(err);\\r\\n\\t\\t}\\r\\n\\t\\tif(self.watchers[fileInfo.filepath]) {\\r\\n\\t\\t\\tself.watchers[fileInfo.filepath].close();\\r\\n\\t\\t\\tdelete self.watchers[fileInfo.filepath];\\r\\n\\t\\t\\tself.pending[fileInfo.filepath] = tiddler.fields.title;\\r\\n\\t\\t}\\r\\n\\t\\t// ensure that the required sub directory is present. Then try to\\r\\n\\t\\t// save the tiddler to its file or only its metadata to a separate\\r\\n\\t\\t// metadata file.\\r\\n\\t\\tself.mkdirp(path.dirname(fileInfo.filepath), function(err) {\\r\\n\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tif(fileInfo.hasMetaFile) {\\r\\n\\t\\t\\t\\t// Save the tiddler as a separate body and meta file\\r\\n\\t\\t\\t\\tvar typeInfo = $tw.config.typeInfo[fileInfo.type],\\r\\n\\t\\t\\t\\t encoding = typeInfo.encoding || \\\"base64\\\"; // makes sense for TW\\r\\n\\t\\t\\t\\tself.logger.log(\\\"saving type\\\", fileInfo.type, \\\"with meta file and encoding\\\", encoding);\\r\\n\\t\\t\\t\\tfs.writeFile(fileInfo.filepath,tiddler.fields.text,{encoding: encoding},function(err) {\\r\\n\\t\\t\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\tcontent = self.wiki.renderTiddler(\\\"text/plain\\\",\\\"$:/core/templates/tiddler-metadata\\\",{variables: {currentTiddler: tiddler.fields.title}});\\r\\n\\t\\t\\t\\t\\tfs.writeFile(fileInfo.filepath + \\\".meta\\\",content,{encoding: \\\"utf8\\\"},function (err) {\\r\\n\\t\\t\\t\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\tself.logger.log(\\\"Saved file\\\",fileInfo.filepath);\\r\\n\\t\\t\\t\\t\\t\\t_finish();\\r\\n\\t\\t\\t\\t\\t});\\r\\n\\t\\t\\t\\t});\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t// Save the tiddler as a self contained templated file\\r\\n\\t\\t\\t\\ttemplate = $tw.config.typeTemplates[fileInfo.type];\\r\\n\\t\\t\\t\\tcontent = self.wiki.renderTiddler(\\\"text/plain\\\",template,{variables: {currentTiddler: tiddler.fields.title}});\\r\\n\\t\\t\\t\\tfs.writeFile(fileInfo.filepath,content,{encoding: \\\"utf8\\\"},function (err) {\\r\\n\\t\\t\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\tself.logger.log(\\\"Saved file\\\",fileInfo.filepath);\\r\\n\\t\\t\\t\\t\\t_finish();\\r\\n\\t\\t\\t\\t});\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\t});\\r\\n};\\n\\n/*\\r\\nLoad a tiddler and invoke the callback with (err,tiddlerFields)\\n\\nWe don't need to implement loading for the file system adaptor, because all the tiddler files will have been loaded during the boot process.\\r\\n*/\\r\\nHierarchicalFileSystemAdaptor.prototype.loadTiddler = function(title,callback) {\\r\\n\\tcallback(null,null);\\r\\n};\\n\\n/*\\r\\nDelete a tiddler and invoke the callback with (err)\\r\\n*/\\r\\nHierarchicalFileSystemAdaptor.prototype.deleteTiddler = function(title,callback,options) {\\r\\n\\tif(this.config.disabled) {\\r\\n\\t\\tthis.logger.log(\\\"deleting disabled\\\");\\r\\n\\t\\treturn callback(null);\\r\\n\\t}\\n\\n\\tvar self = this,\\r\\n\\t\\tfileInfo = $tw.boot.files[title];\\r\\n\\t// Only delete the tiddler if we have writable information for the file\\r\\n\\tif(fileInfo) {\\r\\n\\t\\tif(this.watchers[fileInfo.filepath]) {\\r\\n\\t\\t\\tthis.watchers[fileInfo.filepath].close();\\r\\n\\t\\t\\tdelete this.watchers[fileInfo.filepath];\\r\\n\\t\\t}\\r\\n\\t\\tdelete this.pending[fileInfo.filepath];\\r\\n\\t\\t// Delete the file\\r\\n\\t\\tfs.unlink(fileInfo.filepath,function(err) {\\r\\n\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tself.logger.log(\\\"Deleted file\\\",fileInfo.filepath);\\r\\n\\t\\t\\t// Delete the metafile if present\\r\\n\\t\\t\\tif(fileInfo.hasMetaFile) {\\r\\n\\t\\t\\t\\tfs.unlink(fileInfo.filepath + \\\".meta\\\",function(err) {\\r\\n\\t\\t\\t\\t\\tif(err) {\\r\\n\\t\\t\\t\\t\\t\\treturn callback(err);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\tcallback(null);\\r\\n\\t\\t\\t\\t});\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tcallback(null);\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\t} else {\\r\\n\\t\\tcallback(null);\\r\\n\\t}\\r\\n};\\n\\nif(fs) {\\r\\n\\texports.adaptorClass = HierarchicalFileSystemAdaptor;\\r\\n}\\n\\n})();\\r\\n\"},\"$:/plugins/TheDiveO/ThirdFlow/templates/save-all-wo-plugin-sources\":{\"created\":\"20140902113827798\",\"modified\":\"20140904090211114\",\"title\":\"$:/plugins/TheDiveO/ThirdFlow/templates/save-all-wo-plugin-sources\",\"type\":\"text/vnd.tiddlywiki\",\"text\":\"\\\\define saveTiddlerFilter()\\r\\n[is[tiddler]] -[prefix[$:/state/popup/]] -[[$:/HistoryList]] -[[$:/boot/boot.css]] -[type[application/javascript]library[yes]] -[[$:/boot/boot.js]] -[[$:/boot/bootprefix.js]] -[prefix[$:/temp/]] -[is[shadowinsync]] -[[$:/plugins/TheDiveO/ThirdFlow/readme]is[shadow]!is[tiddler]removesuffix[/readme]] +[sort[title]]\\r\\n\\\\end\\r\\n{{$:/core/templates/tiddlywiki5.html}}\\r\\n\"}}}"
}
}
}
{
"tiddlers": {
"$:/config/EditorTypeMappings/application/javascript": {
"title": "$:/config/EditorTypeMappings/application/javascript",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/application/json": {
"title": "$:/config/EditorTypeMappings/application/json",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/application/x-tiddler-dictionary": {
"title": "$:/config/EditorTypeMappings/application/x-tiddler-dictionary",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/css": {
"title": "$:/config/EditorTypeMappings/text/css",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/html": {
"title": "$:/config/EditorTypeMappings/text/html",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/plain": {
"title": "$:/config/EditorTypeMappings/text/plain",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/vnd.tiddlywiki": {
"title": "$:/config/EditorTypeMappings/text/vnd.tiddlywiki",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/x-markdown": {
"title": "$:/config/EditorTypeMappings/text/x-markdown",
"text": "codemirror"
},
"$:/config/EditorTypeMappings/text/x-tiddlywiki": {
"title": "$:/config/EditorTypeMappings/text/x-tiddlywiki",
"text": "codemirror"
},
"$:/config/CodeMirror": {
"title": "$:/config/CodeMirror",
"type": "application/json",
"text": "{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/search/searchcursor.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/mode/multiplex.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/css/css.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/htmlembedded/htmlembedded.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/htmlmixed/htmlmixed.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/markdown/markdown.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/meta.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/tiddlywiki/tiddlywiki.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js\",\n \"$:/plugins/tiddlywiki/codemirror/keymap/vim.js\",\n \"$:/plugins/tiddlywiki/codemirror/keymap/emacs.js\"\n ],\n \"configuration\": {\n \"matchBrackets\": true,\n \"showCursorWhenSelecting\": true\n }\n}"
},
"$:/plugins/tiddlywiki/codemirror/edit-codemirror.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/codemirror/edit-codemirror.js\ntype: application/javascript\nmodule-type: widget\n\nEdit-codemirror widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar editTextWidgetFactory = require(\"$:/core/modules/editor/factory.js\").editTextWidgetFactory,\n\tCodeMirrorEngine = require(\"$:/plugins/tiddlywiki/codemirror/engine.js\").CodeMirrorEngine;\n\nexports[\"edit-codemirror\"] = editTextWidgetFactory(CodeMirrorEngine,CodeMirrorEngine);\n\n})();\n",
"title": "$:/plugins/tiddlywiki/codemirror/edit-codemirror.js",
"type": "application/javascript",
"module-type": "widget"
},
"$:/plugins/tiddlywiki/codemirror/engine.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/codemirror/engine.js\ntype: application/javascript\nmodule-type: library\n\nText editor engine based on a CodeMirror instance\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar CODEMIRROR_OPTIONS = \"$:/config/CodeMirror\",\n\tHEIGHT_VALUE_TITLE = \"$:/config/TextEditor/EditorHeight/Height\"\n\n// Install CodeMirror\nif($tw.browser && !window.CodeMirror) {\n\twindow.CodeMirror = require(\"$:/plugins/tiddlywiki/codemirror/lib/codemirror.js\");\n\t// Install required CodeMirror plugins\n\tvar configOptions = $tw.wiki.getTiddlerData(CODEMIRROR_OPTIONS,{}),\n\t\treq = configOptions.require;\n\tif(req) {\n\t\tif($tw.utils.isArray(req)) {\n\t\t\tfor(var index=0; index<req.length; index++) {\n\t\t\t\trequire(req[index]);\n\t\t\t}\n\t\t} else {\n\t\t\trequire(req);\n\t\t}\n\t}\n}\n\nfunction CodeMirrorEngine(options) {\n\t// Save our options\n\tvar self = this;\n\toptions = options || {};\n\tthis.widget = options.widget;\n\tthis.value = options.value;\n\tthis.parentNode = options.parentNode;\n\tthis.nextSibling = options.nextSibling;\n\t// Create the wrapper DIV\n\tthis.domNode = this.widget.document.createElement(\"div\");\n\tif(this.widget.editClass) {\n\t\tthis.domNode.className = this.widget.editClass;\n\t}\n\tthis.domNode.style.display = \"inline-block\";\n\tthis.parentNode.insertBefore(this.domNode,this.nextSibling);\n\tthis.widget.domNodes.push(this.domNode);\n\t// Get the configuration options for the CodeMirror object\n\tvar config = $tw.wiki.getTiddlerData(CODEMIRROR_OPTIONS,{}).configuration || {};\n\tif(!(\"lineWrapping\" in config)) {\n\t\tconfig.lineWrapping = true;\n\t}\n\tif(!(\"lineNumbers\" in config)) {\n\t\tconfig.lineNumbers = true;\n\t}\n\tconfig.mode = options.type;\n\tconfig.value = options.value;\n\t// Create the CodeMirror instance\n\tthis.cm = window.CodeMirror(function(cmDomNode) {\n\t\t// Note that this is a synchronous callback that is called before the constructor returns\n\t\tself.domNode.appendChild(cmDomNode);\n\t},config);\n\t// Set up a change event handler\n\tthis.cm.on(\"change\",function() {\n\t\tself.widget.saveChanges(self.getText());\n\t});\n\tthis.cm.on(\"drop\",function(cm,event) {\n\t\tevent.stopPropagation(); // Otherwise TW's dropzone widget sees the drop event\n\t\treturn false;\n\t});\n\tthis.cm.on(\"keydown\",function(cm,event) {\n\t\treturn self.widget.handleKeydownEvent.call(self.widget,event);\n\t});\n}\n\n/*\nSet the text of the engine if it doesn't currently have focus\n*/\nCodeMirrorEngine.prototype.setText = function(text,type) {\n\tthis.cm.setOption(\"mode\",type);\n\tif(!this.cm.hasFocus()) {\n\t\tthis.cm.setValue(text);\n\t}\n};\n\n/*\nGet the text of the engine\n*/\nCodeMirrorEngine.prototype.getText = function() {\n\treturn this.cm.getValue();\n};\n\n/*\nFix the height of textarea to fit content\n*/\nCodeMirrorEngine.prototype.fixHeight = function() {\n\tif(this.widget.editAutoHeight) {\n\t\t// Resize to fit\n\t\tthis.cm.setSize(null,null);\n\t} else {\n\t\tvar fixedHeight = parseInt(this.widget.wiki.getTiddlerText(HEIGHT_VALUE_TITLE,\"400px\"),10);\n\t\tfixedHeight = Math.max(fixedHeight,20);\n\t\tthis.cm.setSize(null,fixedHeight);\n\t}\n};\n\n/*\nFocus the engine node\n*/\nCodeMirrorEngine.prototype.focus = function() {\n\tthis.cm.focus();\n}\n\n/*\nCreate a blank structure representing a text operation\n*/\nCodeMirrorEngine.prototype.createTextOperation = function() {\n\tvar selections = this.cm.listSelections();\n\tif(selections.length > 0) {\n\t\tvar anchorPos = this.cm.indexFromPos(selections[0].anchor),\n\t\t\theadPos = this.cm.indexFromPos(selections[0].head);\n\t}\n\tvar operation = {\n\t\ttext: this.cm.getValue(),\n\t\tselStart: Math.min(anchorPos,headPos),\n\t\tselEnd: Math.max(anchorPos,headPos),\n\t\tcutStart: null,\n\t\tcutEnd: null,\n\t\treplacement: null,\n\t\tnewSelStart: null,\n\t\tnewSelEnd: null\n\t};\n\toperation.selection = operation.text.substring(operation.selStart,operation.selEnd);\n\treturn operation;\n};\n\n/*\nExecute a text operation\n*/\nCodeMirrorEngine.prototype.executeTextOperation = function(operation) {\n\t// Perform the required changes to the text area and the underlying tiddler\n\tvar newText = operation.text;\n\tif(operation.replacement !== null) {\n\t\tthis.cm.replaceRange(operation.replacement,this.cm.posFromIndex(operation.cutStart),this.cm.posFromIndex(operation.cutEnd));\n\t\tthis.cm.setSelection(this.cm.posFromIndex(operation.newSelStart),this.cm.posFromIndex(operation.newSelEnd));\n\t\tnewText = operation.text.substring(0,operation.cutStart) + operation.replacement + operation.text.substring(operation.cutEnd);\n\t}\n\tthis.cm.focus();\n\treturn newText;\n};\n\nexports.CodeMirrorEngine = CodeMirrorEngine;\n\n})();\n",
"title": "$:/plugins/tiddlywiki/codemirror/engine.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/tiddlywiki/codemirror/lib/codemirror.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/lib/codemirror.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n// This is CodeMirror (http://codemirror.net), a code editor\n// implemented in JavaScript on top of the browser's DOM.\n//\n// You can find some technical background for some of the code below\n// at http://marijnhaverbeke.nl/blog/#cm-internals .\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n module.exports = mod();\n else if (typeof define == \"function\" && define.amd) // AMD\n return define([], mod);\n else // Plain browser env\n (this || window).CodeMirror = mod();\n})(function() {\n \"use strict\";\n\n // BROWSER SNIFFING\n\n // Kludges for bugs and behavior differences that can't be feature\n // detected are enabled based on userAgent etc sniffing.\n var userAgent = navigator.userAgent;\n var platform = navigator.platform;\n\n var gecko = /gecko\\/\\d/i.test(userAgent);\n var ie_upto10 = /MSIE \\d/.test(userAgent);\n var ie_11up = /Trident\\/(?:[7-9]|\\d{2,})\\..*rv:(\\d+)/.exec(userAgent);\n var ie = ie_upto10 || ie_11up;\n var ie_version = ie && (ie_upto10 ? document.documentMode || 6 : ie_11up[1]);\n var webkit = /WebKit\\//.test(userAgent);\n var qtwebkit = webkit && /Qt\\/\\d+\\.\\d+/.test(userAgent);\n var chrome = /Chrome\\//.test(userAgent);\n var presto = /Opera\\//.test(userAgent);\n var safari = /Apple Computer/.test(navigator.vendor);\n var mac_geMountainLion = /Mac OS X 1\\d\\D([8-9]|\\d\\d)\\D/.test(userAgent);\n var phantom = /PhantomJS/.test(userAgent);\n\n var ios = /AppleWebKit/.test(userAgent) && /Mobile\\/\\w+/.test(userAgent);\n // This is woefully incomplete. Suggestions for alternative methods welcome.\n var mobile = ios || /Android|webOS|BlackBerry|Opera Mini|Opera Mobi|IEMobile/i.test(userAgent);\n var mac = ios || /Mac/.test(platform);\n var windows = /win/i.test(platform);\n\n var presto_version = presto && userAgent.match(/Version\\/(\\d*\\.\\d*)/);\n if (presto_version) presto_version = Number(presto_version[1]);\n if (presto_version && presto_version >= 15) { presto = false; webkit = true; }\n // Some browsers use the wrong event properties to signal cmd/ctrl on OS X\n var flipCtrlCmd = mac && (qtwebkit || presto && (presto_version == null || presto_version < 12.11));\n var captureRightClick = gecko || (ie && ie_version >= 9);\n\n // Optimize some code when these features are not used.\n var sawReadOnlySpans = false, sawCollapsedSpans = false;\n\n // EDITOR CONSTRUCTOR\n\n // A CodeMirror instance represents an editor. This is the object\n // that user code is usually dealing with.\n\n function CodeMirror(place, options) {\n if (!(this instanceof CodeMirror)) return new CodeMirror(place, options);\n\n this.options = options = options ? copyObj(options) : {};\n // Determine effective options based on given values and defaults.\n copyObj(defaults, options, false);\n setGuttersForLineNumbers(options);\n\n var doc = options.value;\n if (typeof doc == \"string\") doc = new Doc(doc, options.mode, null, options.lineSeparator);\n this.doc = doc;\n\n var input = new CodeMirror.inputStyles[options.inputStyle](this);\n var display = this.display = new Display(place, doc, input);\n display.wrapper.CodeMirror = this;\n updateGutters(this);\n themeChanged(this);\n if (options.lineWrapping)\n this.display.wrapper.className += \" CodeMirror-wrap\";\n if (options.autofocus && !mobile) display.input.focus();\n initScrollbars(this);\n\n this.state = {\n keyMaps: [], // stores maps added by addKeyMap\n overlays: [], // highlighting overlays, as added by addOverlay\n modeGen: 0, // bumped when mode/overlay changes, used to invalidate highlighting info\n overwrite: false,\n delayingBlurEvent: false,\n focused: false,\n suppressEdits: false, // used to disable editing during key handlers when in readOnly mode\n pasteIncoming: false, cutIncoming: false, // help recognize paste/cut edits in input.poll\n selectingText: false,\n draggingText: false,\n highlight: new Delayed(), // stores highlight worker timeout\n keySeq: null, // Unfinished key sequence\n specialChars: null\n };\n\n var cm = this;\n\n // Override magic textarea content restore that IE sometimes does\n // on our hidden textarea on reload\n if (ie && ie_version < 11) setTimeout(function() { cm.display.input.reset(true); }, 20);\n\n registerEventHandlers(this);\n ensureGlobalHandlers();\n\n startOperation(this);\n this.curOp.forceUpdate = true;\n attachDoc(this, doc);\n\n if ((options.autofocus && !mobile) || cm.hasFocus())\n setTimeout(bind(onFocus, this), 20);\n else\n onBlur(this);\n\n for (var opt in optionHandlers) if (optionHandlers.hasOwnProperty(opt))\n optionHandlers[opt](this, options[opt], Init);\n maybeUpdateLineNumberWidth(this);\n if (options.finishInit) options.finishInit(this);\n for (var i = 0; i < initHooks.length; ++i) initHooks[i](this);\n endOperation(this);\n // Suppress optimizelegibility in Webkit, since it breaks text\n // measuring on line wrapping boundaries.\n if (webkit && options.lineWrapping &&\n getComputedStyle(display.lineDiv).textRendering == \"optimizelegibility\")\n display.lineDiv.style.textRendering = \"auto\";\n }\n\n // DISPLAY CONSTRUCTOR\n\n // The display handles the DOM integration, both for input reading\n // and content drawing. It holds references to DOM nodes and\n // display-related state.\n\n function Display(place, doc, input) {\n var d = this;\n this.input = input;\n\n // Covers bottom-right square when both scrollbars are present.\n d.scrollbarFiller = elt(\"div\", null, \"CodeMirror-scrollbar-filler\");\n d.scrollbarFiller.setAttribute(\"cm-not-content\", \"true\");\n // Covers bottom of gutter when coverGutterNextToScrollbar is on\n // and h scrollbar is present.\n d.gutterFiller = elt(\"div\", null, \"CodeMirror-gutter-filler\");\n d.gutterFiller.setAttribute(\"cm-not-content\", \"true\");\n // Will contain the actual code, positioned to cover the viewport.\n d.lineDiv = elt(\"div\", null, \"CodeMirror-code\");\n // Elements are added to these to represent selection and cursors.\n d.selectionDiv = elt(\"div\", null, null, \"position: relative; z-index: 1\");\n d.cursorDiv = elt(\"div\", null, \"CodeMirror-cursors\");\n // A visibility: hidden element used to find the size of things.\n d.measure = elt(\"div\", null, \"CodeMirror-measure\");\n // When lines outside of the viewport are measured, they are drawn in this.\n d.lineMeasure = elt(\"div\", null, \"CodeMirror-measure\");\n // Wraps everything that needs to exist inside the vertically-padded coordinate system\n d.lineSpace = elt(\"div\", [d.measure, d.lineMeasure, d.selectionDiv, d.cursorDiv, d.lineDiv],\n null, \"position: relative; outline: none\");\n // Moved around its parent to cover visible view.\n d.mover = elt(\"div\", [elt(\"div\", [d.lineSpace], \"CodeMirror-lines\")], null, \"position: relative\");\n // Set to the height of the document, allowing scrolling.\n d.sizer = elt(\"div\", [d.mover], \"CodeMirror-sizer\");\n d.sizerWidth = null;\n // Behavior of elts with overflow: auto and padding is\n // inconsistent across browsers. This is used to ensure the\n // scrollable area is big enough.\n d.heightForcer = elt(\"div\", null, null, \"position: absolute; height: \" + scrollerGap + \"px; width: 1px;\");\n // Will contain the gutters, if any.\n d.gutters = elt(\"div\", null, \"CodeMirror-gutters\");\n d.lineGutter = null;\n // Actual scrollable element.\n d.scroller = elt(\"div\", [d.sizer, d.heightForcer, d.gutters], \"CodeMirror-scroll\");\n d.scroller.setAttribute(\"tabIndex\", \"-1\");\n // The element in which the editor lives.\n d.wrapper = elt(\"div\", [d.scrollbarFiller, d.gutterFiller, d.scroller], \"CodeMirror\");\n\n // Work around IE7 z-index bug (not perfect, hence IE7 not really being supported)\n if (ie && ie_version < 8) { d.gutters.style.zIndex = -1; d.scroller.style.paddingRight = 0; }\n if (!webkit && !(gecko && mobile)) d.scroller.draggable = true;\n\n if (place) {\n if (place.appendChild) place.appendChild(d.wrapper);\n else place(d.wrapper);\n }\n\n // Current rendered range (may be bigger than the view window).\n d.viewFrom = d.viewTo = doc.first;\n d.reportedViewFrom = d.reportedViewTo = doc.first;\n // Information about the rendered lines.\n d.view = [];\n d.renderedView = null;\n // Holds info about a single rendered line when it was rendered\n // for measurement, while not in view.\n d.externalMeasured = null;\n // Empty space (in pixels) above the view\n d.viewOffset = 0;\n d.lastWrapHeight = d.lastWrapWidth = 0;\n d.updateLineNumbers = null;\n\n d.nativeBarWidth = d.barHeight = d.barWidth = 0;\n d.scrollbarsClipped = false;\n\n // Used to only resize the line number gutter when necessary (when\n // the amount of lines crosses a boundary that makes its width change)\n d.lineNumWidth = d.lineNumInnerWidth = d.lineNumChars = null;\n // Set to true when a non-horizontal-scrolling line widget is\n // added. As an optimization, line widget aligning is skipped when\n // this is false.\n d.alignWidgets = false;\n\n d.cachedCharWidth = d.cachedTextHeight = d.cachedPaddingH = null;\n\n // Tracks the maximum line length so that the horizontal scrollbar\n // can be kept static when scrolling.\n d.maxLine = null;\n d.maxLineLength = 0;\n d.maxLineChanged = false;\n\n // Used for measuring wheel scrolling granularity\n d.wheelDX = d.wheelDY = d.wheelStartX = d.wheelStartY = null;\n\n // True when shift is held down.\n d.shift = false;\n\n // Used to track whether anything happened since the context menu\n // was opened.\n d.selForContextMenu = null;\n\n d.activeTouch = null;\n\n input.init(d);\n }\n\n // STATE UPDATES\n\n // Used to get the editor into a consistent state again when options change.\n\n function loadMode(cm) {\n cm.doc.mode = CodeMirror.getMode(cm.options, cm.doc.modeOption);\n resetModeState(cm);\n }\n\n function resetModeState(cm) {\n cm.doc.iter(function(line) {\n if (line.stateAfter) line.stateAfter = null;\n if (line.styles) line.styles = null;\n });\n cm.doc.frontier = cm.doc.first;\n startWorker(cm, 100);\n cm.state.modeGen++;\n if (cm.curOp) regChange(cm);\n }\n\n function wrappingChanged(cm) {\n if (cm.options.lineWrapping) {\n addClass(cm.display.wrapper, \"CodeMirror-wrap\");\n cm.display.sizer.style.minWidth = \"\";\n cm.display.sizerWidth = null;\n } else {\n rmClass(cm.display.wrapper, \"CodeMirror-wrap\");\n findMaxLine(cm);\n }\n estimateLineHeights(cm);\n regChange(cm);\n clearCaches(cm);\n setTimeout(function(){updateScrollbars(cm);}, 100);\n }\n\n // Returns a function that estimates the height of a line, to use as\n // first approximation until the line becomes visible (and is thus\n // properly measurable).\n function estimateHeight(cm) {\n var th = textHeight(cm.display), wrapping = cm.options.lineWrapping;\n var perLine = wrapping && Math.max(5, cm.display.scroller.clientWidth / charWidth(cm.display) - 3);\n return function(line) {\n if (lineIsHidden(cm.doc, line)) return 0;\n\n var widgetsHeight = 0;\n if (line.widgets) for (var i = 0; i < line.widgets.length; i++) {\n if (line.widgets[i].height) widgetsHeight += line.widgets[i].height;\n }\n\n if (wrapping)\n return widgetsHeight + (Math.ceil(line.text.length / perLine) || 1) * th;\n else\n return widgetsHeight + th;\n };\n }\n\n function estimateLineHeights(cm) {\n var doc = cm.doc, est = estimateHeight(cm);\n doc.iter(function(line) {\n var estHeight = est(line);\n if (estHeight != line.height) updateLineHeight(line, estHeight);\n });\n }\n\n function themeChanged(cm) {\n cm.display.wrapper.className = cm.display.wrapper.className.replace(/\\s*cm-s-\\S+/g, \"\") +\n cm.options.theme.replace(/(^|\\s)\\s*/g, \" cm-s-\");\n clearCaches(cm);\n }\n\n function guttersChanged(cm) {\n updateGutters(cm);\n regChange(cm);\n setTimeout(function(){alignHorizontally(cm);}, 20);\n }\n\n // Rebuild the gutter elements, ensure the margin to the left of the\n // code matches their width.\n function updateGutters(cm) {\n var gutters = cm.display.gutters, specs = cm.options.gutters;\n removeChildren(gutters);\n for (var i = 0; i < specs.length; ++i) {\n var gutterClass = specs[i];\n var gElt = gutters.appendChild(elt(\"div\", null, \"CodeMirror-gutter \" + gutterClass));\n if (gutterClass == \"CodeMirror-linenumbers\") {\n cm.display.lineGutter = gElt;\n gElt.style.width = (cm.display.lineNumWidth || 1) + \"px\";\n }\n }\n gutters.style.display = i ? \"\" : \"none\";\n updateGutterSpace(cm);\n }\n\n function updateGutterSpace(cm) {\n var width = cm.display.gutters.offsetWidth;\n cm.display.sizer.style.marginLeft = width + \"px\";\n }\n\n // Compute the character length of a line, taking into account\n // collapsed ranges (see markText) that might hide parts, and join\n // other lines onto it.\n function lineLength(line) {\n if (line.height == 0) return 0;\n var len = line.text.length, merged, cur = line;\n while (merged = collapsedSpanAtStart(cur)) {\n var found = merged.find(0, true);\n cur = found.from.line;\n len += found.from.ch - found.to.ch;\n }\n cur = line;\n while (merged = collapsedSpanAtEnd(cur)) {\n var found = merged.find(0, true);\n len -= cur.text.length - found.from.ch;\n cur = found.to.line;\n len += cur.text.length - found.to.ch;\n }\n return len;\n }\n\n // Find the longest line in the document.\n function findMaxLine(cm) {\n var d = cm.display, doc = cm.doc;\n d.maxLine = getLine(doc, doc.first);\n d.maxLineLength = lineLength(d.maxLine);\n d.maxLineChanged = true;\n doc.iter(function(line) {\n var len = lineLength(line);\n if (len > d.maxLineLength) {\n d.maxLineLength = len;\n d.maxLine = line;\n }\n });\n }\n\n // Make sure the gutters options contains the element\n // \"CodeMirror-linenumbers\" when the lineNumbers option is true.\n function setGuttersForLineNumbers(options) {\n var found = indexOf(options.gutters, \"CodeMirror-linenumbers\");\n if (found == -1 && options.lineNumbers) {\n options.gutters = options.gutters.concat([\"CodeMirror-linenumbers\"]);\n } else if (found > -1 && !options.lineNumbers) {\n options.gutters = options.gutters.slice(0);\n options.gutters.splice(found, 1);\n }\n }\n\n // SCROLLBARS\n\n // Prepare DOM reads needed to update the scrollbars. Done in one\n // shot to minimize update/measure roundtrips.\n function measureForScrollbars(cm) {\n var d = cm.display, gutterW = d.gutters.offsetWidth;\n var docH = Math.round(cm.doc.height + paddingVert(cm.display));\n return {\n clientHeight: d.scroller.clientHeight,\n viewHeight: d.wrapper.clientHeight,\n scrollWidth: d.scroller.scrollWidth, clientWidth: d.scroller.clientWidth,\n viewWidth: d.wrapper.clientWidth,\n barLeft: cm.options.fixedGutter ? gutterW : 0,\n docHeight: docH,\n scrollHeight: docH + scrollGap(cm) + d.barHeight,\n nativeBarWidth: d.nativeBarWidth,\n gutterWidth: gutterW\n };\n }\n\n function NativeScrollbars(place, scroll, cm) {\n this.cm = cm;\n var vert = this.vert = elt(\"div\", [elt(\"div\", null, null, \"min-width: 1px\")], \"CodeMirror-vscrollbar\");\n var horiz = this.horiz = elt(\"div\", [elt(\"div\", null, null, \"height: 100%; min-height: 1px\")], \"CodeMirror-hscrollbar\");\n place(vert); place(horiz);\n\n on(vert, \"scroll\", function() {\n if (vert.clientHeight) scroll(vert.scrollTop, \"vertical\");\n });\n on(horiz, \"scroll\", function() {\n if (horiz.clientWidth) scroll(horiz.scrollLeft, \"horizontal\");\n });\n\n this.checkedZeroWidth = false;\n // Need to set a minimum width to see the scrollbar on IE7 (but must not set it on IE8).\n if (ie && ie_version < 8) this.horiz.style.minHeight = this.vert.style.minWidth = \"18px\";\n }\n\n NativeScrollbars.prototype = copyObj({\n update: function(measure) {\n var needsH = measure.scrollWidth > measure.clientWidth + 1;\n var needsV = measure.scrollHeight > measure.clientHeight + 1;\n var sWidth = measure.nativeBarWidth;\n\n if (needsV) {\n this.vert.style.display = \"block\";\n this.vert.style.bottom = needsH ? sWidth + \"px\" : \"0\";\n var totalHeight = measure.viewHeight - (needsH ? sWidth : 0);\n // A bug in IE8 can cause this value to be negative, so guard it.\n this.vert.firstChild.style.height =\n Math.max(0, measure.scrollHeight - measure.clientHeight + totalHeight) + \"px\";\n } else {\n this.vert.style.display = \"\";\n this.vert.firstChild.style.height = \"0\";\n }\n\n if (needsH) {\n this.horiz.style.display = \"block\";\n this.horiz.style.right = needsV ? sWidth + \"px\" : \"0\";\n this.horiz.style.left = measure.barLeft + \"px\";\n var totalWidth = measure.viewWidth - measure.barLeft - (needsV ? sWidth : 0);\n this.horiz.firstChild.style.width =\n (measure.scrollWidth - measure.clientWidth + totalWidth) + \"px\";\n } else {\n this.horiz.style.display = \"\";\n this.horiz.firstChild.style.width = \"0\";\n }\n\n if (!this.checkedZeroWidth && measure.clientHeight > 0) {\n if (sWidth == 0) this.zeroWidthHack();\n this.checkedZeroWidth = true;\n }\n\n return {right: needsV ? sWidth : 0, bottom: needsH ? sWidth : 0};\n },\n setScrollLeft: function(pos) {\n if (this.horiz.scrollLeft != pos) this.horiz.scrollLeft = pos;\n if (this.disableHoriz) this.enableZeroWidthBar(this.horiz, this.disableHoriz);\n },\n setScrollTop: function(pos) {\n if (this.vert.scrollTop != pos) this.vert.scrollTop = pos;\n if (this.disableVert) this.enableZeroWidthBar(this.vert, this.disableVert);\n },\n zeroWidthHack: function() {\n var w = mac && !mac_geMountainLion ? \"12px\" : \"18px\";\n this.horiz.style.height = this.vert.style.width = w;\n this.horiz.style.pointerEvents = this.vert.style.pointerEvents = \"none\";\n this.disableHoriz = new Delayed;\n this.disableVert = new Delayed;\n },\n enableZeroWidthBar: function(bar, delay) {\n bar.style.pointerEvents = \"auto\";\n function maybeDisable() {\n // To find out whether the scrollbar is still visible, we\n // check whether the element under the pixel in the bottom\n // left corner of the scrollbar box is the scrollbar box\n // itself (when the bar is still visible) or its filler child\n // (when the bar is hidden). If it is still visible, we keep\n // it enabled, if it's hidden, we disable pointer events.\n var box = bar.getBoundingClientRect();\n var elt = document.elementFromPoint(box.left + 1, box.bottom - 1);\n if (elt != bar) bar.style.pointerEvents = \"none\";\n else delay.set(1000, maybeDisable);\n }\n delay.set(1000, maybeDisable);\n },\n clear: function() {\n var parent = this.horiz.parentNode;\n parent.removeChild(this.horiz);\n parent.removeChild(this.vert);\n }\n }, NativeScrollbars.prototype);\n\n function NullScrollbars() {}\n\n NullScrollbars.prototype = copyObj({\n update: function() { return {bottom: 0, right: 0}; },\n setScrollLeft: function() {},\n setScrollTop: function() {},\n clear: function() {}\n }, NullScrollbars.prototype);\n\n CodeMirror.scrollbarModel = {\"native\": NativeScrollbars, \"null\": NullScrollbars};\n\n function initScrollbars(cm) {\n if (cm.display.scrollbars) {\n cm.display.scrollbars.clear();\n if (cm.display.scrollbars.addClass)\n rmClass(cm.display.wrapper, cm.display.scrollbars.addClass);\n }\n\n cm.display.scrollbars = new CodeMirror.scrollbarModel[cm.options.scrollbarStyle](function(node) {\n cm.display.wrapper.insertBefore(node, cm.display.scrollbarFiller);\n // Prevent clicks in the scrollbars from killing focus\n on(node, \"mousedown\", function() {\n if (cm.state.focused) setTimeout(function() { cm.display.input.focus(); }, 0);\n });\n node.setAttribute(\"cm-not-content\", \"true\");\n }, function(pos, axis) {\n if (axis == \"horizontal\") setScrollLeft(cm, pos);\n else setScrollTop(cm, pos);\n }, cm);\n if (cm.display.scrollbars.addClass)\n addClass(cm.display.wrapper, cm.display.scrollbars.addClass);\n }\n\n function updateScrollbars(cm, measure) {\n if (!measure) measure = measureForScrollbars(cm);\n var startWidth = cm.display.barWidth, startHeight = cm.display.barHeight;\n updateScrollbarsInner(cm, measure);\n for (var i = 0; i < 4 && startWidth != cm.display.barWidth || startHeight != cm.display.barHeight; i++) {\n if (startWidth != cm.display.barWidth && cm.options.lineWrapping)\n updateHeightsInViewport(cm);\n updateScrollbarsInner(cm, measureForScrollbars(cm));\n startWidth = cm.display.barWidth; startHeight = cm.display.barHeight;\n }\n }\n\n // Re-synchronize the fake scrollbars with the actual size of the\n // content.\n function updateScrollbarsInner(cm, measure) {\n var d = cm.display;\n var sizes = d.scrollbars.update(measure);\n\n d.sizer.style.paddingRight = (d.barWidth = sizes.right) + \"px\";\n d.sizer.style.paddingBottom = (d.barHeight = sizes.bottom) + \"px\";\n d.heightForcer.style.borderBottom = sizes.bottom + \"px solid transparent\"\n\n if (sizes.right && sizes.bottom) {\n d.scrollbarFiller.style.display = \"block\";\n d.scrollbarFiller.style.height = sizes.bottom + \"px\";\n d.scrollbarFiller.style.width = sizes.right + \"px\";\n } else d.scrollbarFiller.style.display = \"\";\n if (sizes.bottom && cm.options.coverGutterNextToScrollbar && cm.options.fixedGutter) {\n d.gutterFiller.style.display = \"block\";\n d.gutterFiller.style.height = sizes.bottom + \"px\";\n d.gutterFiller.style.width = measure.gutterWidth + \"px\";\n } else d.gutterFiller.style.display = \"\";\n }\n\n // Compute the lines that are visible in a given viewport (defaults\n // the the current scroll position). viewport may contain top,\n // height, and ensure (see op.scrollToPos) properties.\n function visibleLines(display, doc, viewport) {\n var top = viewport && viewport.top != null ? Math.max(0, viewport.top) : display.scroller.scrollTop;\n top = Math.floor(top - paddingTop(display));\n var bottom = viewport && viewport.bottom != null ? viewport.bottom : top + display.wrapper.clientHeight;\n\n var from = lineAtHeight(doc, top), to = lineAtHeight(doc, bottom);\n // Ensure is a {from: {line, ch}, to: {line, ch}} object, and\n // forces those lines into the viewport (if possible).\n if (viewport && viewport.ensure) {\n var ensureFrom = viewport.ensure.from.line, ensureTo = viewport.ensure.to.line;\n if (ensureFrom < from) {\n from = ensureFrom;\n to = lineAtHeight(doc, heightAtLine(getLine(doc, ensureFrom)) + display.wrapper.clientHeight);\n } else if (Math.min(ensureTo, doc.lastLine()) >= to) {\n from = lineAtHeight(doc, heightAtLine(getLine(doc, ensureTo)) - display.wrapper.clientHeight);\n to = ensureTo;\n }\n }\n return {from: from, to: Math.max(to, from + 1)};\n }\n\n // LINE NUMBERS\n\n // Re-align line numbers and gutter marks to compensate for\n // horizontal scrolling.\n function alignHorizontally(cm) {\n var display = cm.display, view = display.view;\n if (!display.alignWidgets && (!display.gutters.firstChild || !cm.options.fixedGutter)) return;\n var comp = compensateForHScroll(display) - display.scroller.scrollLeft + cm.doc.scrollLeft;\n var gutterW = display.gutters.offsetWidth, left = comp + \"px\";\n for (var i = 0; i < view.length; i++) if (!view[i].hidden) {\n if (cm.options.fixedGutter && view[i].gutter)\n view[i].gutter.style.left = left;\n var align = view[i].alignable;\n if (align) for (var j = 0; j < align.length; j++)\n align[j].style.left = left;\n }\n if (cm.options.fixedGutter)\n display.gutters.style.left = (comp + gutterW) + \"px\";\n }\n\n // Used to ensure that the line number gutter is still the right\n // size for the current document size. Returns true when an update\n // is needed.\n function maybeUpdateLineNumberWidth(cm) {\n if (!cm.options.lineNumbers) return false;\n var doc = cm.doc, last = lineNumberFor(cm.options, doc.first + doc.size - 1), display = cm.display;\n if (last.length != display.lineNumChars) {\n var test = display.measure.appendChild(elt(\"div\", [elt(\"div\", last)],\n \"CodeMirror-linenumber CodeMirror-gutter-elt\"));\n var innerW = test.firstChild.offsetWidth, padding = test.offsetWidth - innerW;\n display.lineGutter.style.width = \"\";\n display.lineNumInnerWidth = Math.max(innerW, display.lineGutter.offsetWidth - padding) + 1;\n display.lineNumWidth = display.lineNumInnerWidth + padding;\n display.lineNumChars = display.lineNumInnerWidth ? last.length : -1;\n display.lineGutter.style.width = display.lineNumWidth + \"px\";\n updateGutterSpace(cm);\n return true;\n }\n return false;\n }\n\n function lineNumberFor(options, i) {\n return String(options.lineNumberFormatter(i + options.firstLineNumber));\n }\n\n // Computes display.scroller.scrollLeft + display.gutters.offsetWidth,\n // but using getBoundingClientRect to get a sub-pixel-accurate\n // result.\n function compensateForHScroll(display) {\n return display.scroller.getBoundingClientRect().left - display.sizer.getBoundingClientRect().left;\n }\n\n // DISPLAY DRAWING\n\n function DisplayUpdate(cm, viewport, force) {\n var display = cm.display;\n\n this.viewport = viewport;\n // Store some values that we'll need later (but don't want to force a relayout for)\n this.visible = visibleLines(display, cm.doc, viewport);\n this.editorIsHidden = !display.wrapper.offsetWidth;\n this.wrapperHeight = display.wrapper.clientHeight;\n this.wrapperWidth = display.wrapper.clientWidth;\n this.oldDisplayWidth = displayWidth(cm);\n this.force = force;\n this.dims = getDimensions(cm);\n this.events = [];\n }\n\n DisplayUpdate.prototype.signal = function(emitter, type) {\n if (hasHandler(emitter, type))\n this.events.push(arguments);\n };\n DisplayUpdate.prototype.finish = function() {\n for (var i = 0; i < this.events.length; i++)\n signal.apply(null, this.events[i]);\n };\n\n function maybeClipScrollbars(cm) {\n var display = cm.display;\n if (!display.scrollbarsClipped && display.scroller.offsetWidth) {\n display.nativeBarWidth = display.scroller.offsetWidth - display.scroller.clientWidth;\n display.heightForcer.style.height = scrollGap(cm) + \"px\";\n display.sizer.style.marginBottom = -display.nativeBarWidth + \"px\";\n display.sizer.style.borderRightWidth = scrollGap(cm) + \"px\";\n display.scrollbarsClipped = true;\n }\n }\n\n // Does the actual updating of the line display. Bails out\n // (returning false) when there is nothing to be done and forced is\n // false.\n function updateDisplayIfNeeded(cm, update) {\n var display = cm.display, doc = cm.doc;\n\n if (update.editorIsHidden) {\n resetView(cm);\n return false;\n }\n\n // Bail out if the visible area is already rendered and nothing changed.\n if (!update.force &&\n update.visible.from >= display.viewFrom && update.visible.to <= display.viewTo &&\n (display.updateLineNumbers == null || display.updateLineNumbers >= display.viewTo) &&\n display.renderedView == display.view && countDirtyView(cm) == 0)\n return false;\n\n if (maybeUpdateLineNumberWidth(cm)) {\n resetView(cm);\n update.dims = getDimensions(cm);\n }\n\n // Compute a suitable new viewport (from & to)\n var end = doc.first + doc.size;\n var from = Math.max(update.visible.from - cm.options.viewportMargin, doc.first);\n var to = Math.min(end, update.visible.to + cm.options.viewportMargin);\n if (display.viewFrom < from && from - display.viewFrom < 20) from = Math.max(doc.first, display.viewFrom);\n if (display.viewTo > to && display.viewTo - to < 20) to = Math.min(end, display.viewTo);\n if (sawCollapsedSpans) {\n from = visualLineNo(cm.doc, from);\n to = visualLineEndNo(cm.doc, to);\n }\n\n var different = from != display.viewFrom || to != display.viewTo ||\n display.lastWrapHeight != update.wrapperHeight || display.lastWrapWidth != update.wrapperWidth;\n adjustView(cm, from, to);\n\n display.viewOffset = heightAtLine(getLine(cm.doc, display.viewFrom));\n // Position the mover div to align with the current scroll position\n cm.display.mover.style.top = display.viewOffset + \"px\";\n\n var toUpdate = countDirtyView(cm);\n if (!different && toUpdate == 0 && !update.force && display.renderedView == display.view &&\n (display.updateLineNumbers == null || display.updateLineNumbers >= display.viewTo))\n return false;\n\n // For big changes, we hide the enclosing element during the\n // update, since that speeds up the operations on most browsers.\n var focused = activeElt();\n if (toUpdate > 4) display.lineDiv.style.display = \"none\";\n patchDisplay(cm, display.updateLineNumbers, update.dims);\n if (toUpdate > 4) display.lineDiv.style.display = \"\";\n display.renderedView = display.view;\n // There might have been a widget with a focused element that got\n // hidden or updated, if so re-focus it.\n if (focused && activeElt() != focused && focused.offsetHeight) focused.focus();\n\n // Prevent selection and cursors from interfering with the scroll\n // width and height.\n removeChildren(display.cursorDiv);\n removeChildren(display.selectionDiv);\n display.gutters.style.height = display.sizer.style.minHeight = 0;\n\n if (different) {\n display.lastWrapHeight = update.wrapperHeight;\n display.lastWrapWidth = update.wrapperWidth;\n startWorker(cm, 400);\n }\n\n display.updateLineNumbers = null;\n\n return true;\n }\n\n function postUpdateDisplay(cm, update) {\n var viewport = update.viewport;\n\n for (var first = true;; first = false) {\n if (!first || !cm.options.lineWrapping || update.oldDisplayWidth == displayWidth(cm)) {\n // Clip forced viewport to actual scrollable area.\n if (viewport && viewport.top != null)\n viewport = {top: Math.min(cm.doc.height + paddingVert(cm.display) - displayHeight(cm), viewport.top)};\n // Updated line heights might result in the drawn area not\n // actually covering the viewport. Keep looping until it does.\n update.visible = visibleLines(cm.display, cm.doc, viewport);\n if (update.visible.from >= cm.display.viewFrom && update.visible.to <= cm.display.viewTo)\n break;\n }\n if (!updateDisplayIfNeeded(cm, update)) break;\n updateHeightsInViewport(cm);\n var barMeasure = measureForScrollbars(cm);\n updateSelection(cm);\n updateScrollbars(cm, barMeasure);\n setDocumentHeight(cm, barMeasure);\n }\n\n update.signal(cm, \"update\", cm);\n if (cm.display.viewFrom != cm.display.reportedViewFrom || cm.display.viewTo != cm.display.reportedViewTo) {\n update.signal(cm, \"viewportChange\", cm, cm.display.viewFrom, cm.display.viewTo);\n cm.display.reportedViewFrom = cm.display.viewFrom; cm.display.reportedViewTo = cm.display.viewTo;\n }\n }\n\n function updateDisplaySimple(cm, viewport) {\n var update = new DisplayUpdate(cm, viewport);\n if (updateDisplayIfNeeded(cm, update)) {\n updateHeightsInViewport(cm);\n postUpdateDisplay(cm, update);\n var barMeasure = measureForScrollbars(cm);\n updateSelection(cm);\n updateScrollbars(cm, barMeasure);\n setDocumentHeight(cm, barMeasure);\n update.finish();\n }\n }\n\n function setDocumentHeight(cm, measure) {\n cm.display.sizer.style.minHeight = measure.docHeight + \"px\";\n cm.display.heightForcer.style.top = measure.docHeight + \"px\";\n cm.display.gutters.style.height = (measure.docHeight + cm.display.barHeight + scrollGap(cm)) + \"px\";\n }\n\n // Read the actual heights of the rendered lines, and update their\n // stored heights to match.\n function updateHeightsInViewport(cm) {\n var display = cm.display;\n var prevBottom = display.lineDiv.offsetTop;\n for (var i = 0; i < display.view.length; i++) {\n var cur = display.view[i], height;\n if (cur.hidden) continue;\n if (ie && ie_version < 8) {\n var bot = cur.node.offsetTop + cur.node.offsetHeight;\n height = bot - prevBottom;\n prevBottom = bot;\n } else {\n var box = cur.node.getBoundingClientRect();\n height = box.bottom - box.top;\n }\n var diff = cur.line.height - height;\n if (height < 2) height = textHeight(display);\n if (diff > .001 || diff < -.001) {\n updateLineHeight(cur.line, height);\n updateWidgetHeight(cur.line);\n if (cur.rest) for (var j = 0; j < cur.rest.length; j++)\n updateWidgetHeight(cur.rest[j]);\n }\n }\n }\n\n // Read and store the height of line widgets associated with the\n // given line.\n function updateWidgetHeight(line) {\n if (line.widgets) for (var i = 0; i < line.widgets.length; ++i)\n line.widgets[i].height = line.widgets[i].node.parentNode.offsetHeight;\n }\n\n // Do a bulk-read of the DOM positions and sizes needed to draw the\n // view, so that we don't interleave reading and writing to the DOM.\n function getDimensions(cm) {\n var d = cm.display, left = {}, width = {};\n var gutterLeft = d.gutters.clientLeft;\n for (var n = d.gutters.firstChild, i = 0; n; n = n.nextSibling, ++i) {\n left[cm.options.gutters[i]] = n.offsetLeft + n.clientLeft + gutterLeft;\n width[cm.options.gutters[i]] = n.clientWidth;\n }\n return {fixedPos: compensateForHScroll(d),\n gutterTotalWidth: d.gutters.offsetWidth,\n gutterLeft: left,\n gutterWidth: width,\n wrapperWidth: d.wrapper.clientWidth};\n }\n\n // Sync the actual display DOM structure with display.view, removing\n // nodes for lines that are no longer in view, and creating the ones\n // that are not there yet, and updating the ones that are out of\n // date.\n function patchDisplay(cm, updateNumbersFrom, dims) {\n var display = cm.display, lineNumbers = cm.options.lineNumbers;\n var container = display.lineDiv, cur = container.firstChild;\n\n function rm(node) {\n var next = node.nextSibling;\n // Works around a throw-scroll bug in OS X Webkit\n if (webkit && mac && cm.display.currentWheelTarget == node)\n node.style.display = \"none\";\n else\n node.parentNode.removeChild(node);\n return next;\n }\n\n var view = display.view, lineN = display.viewFrom;\n // Loop over the elements in the view, syncing cur (the DOM nodes\n // in display.lineDiv) with the view as we go.\n for (var i = 0; i < view.length; i++) {\n var lineView = view[i];\n if (lineView.hidden) {\n } else if (!lineView.node || lineView.node.parentNode != container) { // Not drawn yet\n var node = buildLineElement(cm, lineView, lineN, dims);\n container.insertBefore(node, cur);\n } else { // Already drawn\n while (cur != lineView.node) cur = rm(cur);\n var updateNumber = lineNumbers && updateNumbersFrom != null &&\n updateNumbersFrom <= lineN && lineView.lineNumber;\n if (lineView.changes) {\n if (indexOf(lineView.changes, \"gutter\") > -1) updateNumber = false;\n updateLineForChanges(cm, lineView, lineN, dims);\n }\n if (updateNumber) {\n removeChildren(lineView.lineNumber);\n lineView.lineNumber.appendChild(document.createTextNode(lineNumberFor(cm.options, lineN)));\n }\n cur = lineView.node.nextSibling;\n }\n lineN += lineView.size;\n }\n while (cur) cur = rm(cur);\n }\n\n // When an aspect of a line changes, a string is added to\n // lineView.changes. This updates the relevant part of the line's\n // DOM structure.\n function updateLineForChanges(cm, lineView, lineN, dims) {\n for (var j = 0; j < lineView.changes.length; j++) {\n var type = lineView.changes[j];\n if (type == \"text\") updateLineText(cm, lineView);\n else if (type == \"gutter\") updateLineGutter(cm, lineView, lineN, dims);\n else if (type == \"class\") updateLineClasses(lineView);\n else if (type == \"widget\") updateLineWidgets(cm, lineView, dims);\n }\n lineView.changes = null;\n }\n\n // Lines with gutter elements, widgets or a background class need to\n // be wrapped, and have the extra elements added to the wrapper div\n function ensureLineWrapped(lineView) {\n if (lineView.node == lineView.text) {\n lineView.node = elt(\"div\", null, null, \"position: relative\");\n if (lineView.text.parentNode)\n lineView.text.parentNode.replaceChild(lineView.node, lineView.text);\n lineView.node.appendChild(lineView.text);\n if (ie && ie_version < 8) lineView.node.style.zIndex = 2;\n }\n return lineView.node;\n }\n\n function updateLineBackground(lineView) {\n var cls = lineView.bgClass ? lineView.bgClass + \" \" + (lineView.line.bgClass || \"\") : lineView.line.bgClass;\n if (cls) cls += \" CodeMirror-linebackground\";\n if (lineView.background) {\n if (cls) lineView.background.className = cls;\n else { lineView.background.parentNode.removeChild(lineView.background); lineView.background = null; }\n } else if (cls) {\n var wrap = ensureLineWrapped(lineView);\n lineView.background = wrap.insertBefore(elt(\"div\", null, cls), wrap.firstChild);\n }\n }\n\n // Wrapper around buildLineContent which will reuse the structure\n // in display.externalMeasured when possible.\n function getLineContent(cm, lineView) {\n var ext = cm.display.externalMeasured;\n if (ext && ext.line == lineView.line) {\n cm.display.externalMeasured = null;\n lineView.measure = ext.measure;\n return ext.built;\n }\n return buildLineContent(cm, lineView);\n }\n\n // Redraw the line's text. Interacts with the background and text\n // classes because the mode may output tokens that influence these\n // classes.\n function updateLineText(cm, lineView) {\n var cls = lineView.text.className;\n var built = getLineContent(cm, lineView);\n if (lineView.text == lineView.node) lineView.node = built.pre;\n lineView.text.parentNode.replaceChild(built.pre, lineView.text);\n lineView.text = built.pre;\n if (built.bgClass != lineView.bgClass || built.textClass != lineView.textClass) {\n lineView.bgClass = built.bgClass;\n lineView.textClass = built.textClass;\n updateLineClasses(lineView);\n } else if (cls) {\n lineView.text.className = cls;\n }\n }\n\n function updateLineClasses(lineView) {\n updateLineBackground(lineView);\n if (lineView.line.wrapClass)\n ensureLineWrapped(lineView).className = lineView.line.wrapClass;\n else if (lineView.node != lineView.text)\n lineView.node.className = \"\";\n var textClass = lineView.textClass ? lineView.textClass + \" \" + (lineView.line.textClass || \"\") : lineView.line.textClass;\n lineView.text.className = textClass || \"\";\n }\n\n function updateLineGutter(cm, lineView, lineN, dims) {\n if (lineView.gutter) {\n lineView.node.removeChild(lineView.gutter);\n lineView.gutter = null;\n }\n if (lineView.gutterBackground) {\n lineView.node.removeChild(lineView.gutterBackground);\n lineView.gutterBackground = null;\n }\n if (lineView.line.gutterClass) {\n var wrap = ensureLineWrapped(lineView);\n lineView.gutterBackground = elt(\"div\", null, \"CodeMirror-gutter-background \" + lineView.line.gutterClass,\n \"left: \" + (cm.options.fixedGutter ? dims.fixedPos : -dims.gutterTotalWidth) +\n \"px; width: \" + dims.gutterTotalWidth + \"px\");\n wrap.insertBefore(lineView.gutterBackground, lineView.text);\n }\n var markers = lineView.line.gutterMarkers;\n if (cm.options.lineNumbers || markers) {\n var wrap = ensureLineWrapped(lineView);\n var gutterWrap = lineView.gutter = elt(\"div\", null, \"CodeMirror-gutter-wrapper\", \"left: \" +\n (cm.options.fixedGutter ? dims.fixedPos : -dims.gutterTotalWidth) + \"px\");\n cm.display.input.setUneditable(gutterWrap);\n wrap.insertBefore(gutterWrap, lineView.text);\n if (lineView.line.gutterClass)\n gutterWrap.className += \" \" + lineView.line.gutterClass;\n if (cm.options.lineNumbers && (!markers || !markers[\"CodeMirror-linenumbers\"]))\n lineView.lineNumber = gutterWrap.appendChild(\n elt(\"div\", lineNumberFor(cm.options, lineN),\n \"CodeMirror-linenumber CodeMirror-gutter-elt\",\n \"left: \" + dims.gutterLeft[\"CodeMirror-linenumbers\"] + \"px; width: \"\n + cm.display.lineNumInnerWidth + \"px\"));\n if (markers) for (var k = 0; k < cm.options.gutters.length; ++k) {\n var id = cm.options.gutters[k], found = markers.hasOwnProperty(id) && markers[id];\n if (found)\n gutterWrap.appendChild(elt(\"div\", [found], \"CodeMirror-gutter-elt\", \"left: \" +\n dims.gutterLeft[id] + \"px; width: \" + dims.gutterWidth[id] + \"px\"));\n }\n }\n }\n\n function updateLineWidgets(cm, lineView, dims) {\n if (lineView.alignable) lineView.alignable = null;\n for (var node = lineView.node.firstChild, next; node; node = next) {\n var next = node.nextSibling;\n if (node.className == \"CodeMirror-linewidget\")\n lineView.node.removeChild(node);\n }\n insertLineWidgets(cm, lineView, dims);\n }\n\n // Build a line's DOM representation from scratch\n function buildLineElement(cm, lineView, lineN, dims) {\n var built = getLineContent(cm, lineView);\n lineView.text = lineView.node = built.pre;\n if (built.bgClass) lineView.bgClass = built.bgClass;\n if (built.textClass) lineView.textClass = built.textClass;\n\n updateLineClasses(lineView);\n updateLineGutter(cm, lineView, lineN, dims);\n insertLineWidgets(cm, lineView, dims);\n return lineView.node;\n }\n\n // A lineView may contain multiple logical lines (when merged by\n // collapsed spans). The widgets for all of them need to be drawn.\n function insertLineWidgets(cm, lineView, dims) {\n insertLineWidgetsFor(cm, lineView.line, lineView, dims, true);\n if (lineView.rest) for (var i = 0; i < lineView.rest.length; i++)\n insertLineWidgetsFor(cm, lineView.rest[i], lineView, dims, false);\n }\n\n function insertLineWidgetsFor(cm, line, lineView, dims, allowAbove) {\n if (!line.widgets) return;\n var wrap = ensureLineWrapped(lineView);\n for (var i = 0, ws = line.widgets; i < ws.length; ++i) {\n var widget = ws[i], node = elt(\"div\", [widget.node], \"CodeMirror-linewidget\");\n if (!widget.handleMouseEvents) node.setAttribute(\"cm-ignore-events\", \"true\");\n positionLineWidget(widget, node, lineView, dims);\n cm.display.input.setUneditable(node);\n if (allowAbove && widget.above)\n wrap.insertBefore(node, lineView.gutter || lineView.text);\n else\n wrap.appendChild(node);\n signalLater(widget, \"redraw\");\n }\n }\n\n function positionLineWidget(widget, node, lineView, dims) {\n if (widget.noHScroll) {\n (lineView.alignable || (lineView.alignable = [])).push(node);\n var width = dims.wrapperWidth;\n node.style.left = dims.fixedPos + \"px\";\n if (!widget.coverGutter) {\n width -= dims.gutterTotalWidth;\n node.style.paddingLeft = dims.gutterTotalWidth + \"px\";\n }\n node.style.width = width + \"px\";\n }\n if (widget.coverGutter) {\n node.style.zIndex = 5;\n node.style.position = \"relative\";\n if (!widget.noHScroll) node.style.marginLeft = -dims.gutterTotalWidth + \"px\";\n }\n }\n\n // POSITION OBJECT\n\n // A Pos instance represents a position within the text.\n var Pos = CodeMirror.Pos = function(line, ch) {\n if (!(this instanceof Pos)) return new Pos(line, ch);\n this.line = line; this.ch = ch;\n };\n\n // Compare two positions, return 0 if they are the same, a negative\n // number when a is less, and a positive number otherwise.\n var cmp = CodeMirror.cmpPos = function(a, b) { return a.line - b.line || a.ch - b.ch; };\n\n function copyPos(x) {return Pos(x.line, x.ch);}\n function maxPos(a, b) { return cmp(a, b) < 0 ? b : a; }\n function minPos(a, b) { return cmp(a, b) < 0 ? a : b; }\n\n // INPUT HANDLING\n\n function ensureFocus(cm) {\n if (!cm.state.focused) { cm.display.input.focus(); onFocus(cm); }\n }\n\n // This will be set to an array of strings when copying, so that,\n // when pasting, we know what kind of selections the copied text\n // was made out of.\n var lastCopied = null;\n\n function applyTextInput(cm, inserted, deleted, sel, origin) {\n var doc = cm.doc;\n cm.display.shift = false;\n if (!sel) sel = doc.sel;\n\n var paste = cm.state.pasteIncoming || origin == \"paste\";\n var textLines = doc.splitLines(inserted), multiPaste = null;\n // When pasing N lines into N selections, insert one line per selection\n if (paste && sel.ranges.length > 1) {\n if (lastCopied && lastCopied.join(\"\\n\") == inserted) {\n if (sel.ranges.length % lastCopied.length == 0) {\n multiPaste = [];\n for (var i = 0; i < lastCopied.length; i++)\n multiPaste.push(doc.splitLines(lastCopied[i]));\n }\n } else if (textLines.length == sel.ranges.length) {\n multiPaste = map(textLines, function(l) { return [l]; });\n }\n }\n\n // Normal behavior is to insert the new text into every selection\n for (var i = sel.ranges.length - 1; i >= 0; i--) {\n var range = sel.ranges[i];\n var from = range.from(), to = range.to();\n if (range.empty()) {\n if (deleted && deleted > 0) // Handle deletion\n from = Pos(from.line, from.ch - deleted);\n else if (cm.state.overwrite && !paste) // Handle overwrite\n to = Pos(to.line, Math.min(getLine(doc, to.line).text.length, to.ch + lst(textLines).length));\n }\n var updateInput = cm.curOp.updateInput;\n var changeEvent = {from: from, to: to, text: multiPaste ? multiPaste[i % multiPaste.length] : textLines,\n origin: origin || (paste ? \"paste\" : cm.state.cutIncoming ? \"cut\" : \"+input\")};\n makeChange(cm.doc, changeEvent);\n signalLater(cm, \"inputRead\", cm, changeEvent);\n }\n if (inserted && !paste)\n triggerElectric(cm, inserted);\n\n ensureCursorVisible(cm);\n cm.curOp.updateInput = updateInput;\n cm.curOp.typing = true;\n cm.state.pasteIncoming = cm.state.cutIncoming = false;\n }\n\n function handlePaste(e, cm) {\n var pasted = e.clipboardData && e.clipboardData.getData(\"text/plain\");\n if (pasted) {\n e.preventDefault();\n if (!cm.isReadOnly() && !cm.options.disableInput)\n runInOp(cm, function() { applyTextInput(cm, pasted, 0, null, \"paste\"); });\n return true;\n }\n }\n\n function triggerElectric(cm, inserted) {\n // When an 'electric' character is inserted, immediately trigger a reindent\n if (!cm.options.electricChars || !cm.options.smartIndent) return;\n var sel = cm.doc.sel;\n\n for (var i = sel.ranges.length - 1; i >= 0; i--) {\n var range = sel.ranges[i];\n if (range.head.ch > 100 || (i && sel.ranges[i - 1].head.line == range.head.line)) continue;\n var mode = cm.getModeAt(range.head);\n var indented = false;\n if (mode.electricChars) {\n for (var j = 0; j < mode.electricChars.length; j++)\n if (inserted.indexOf(mode.electricChars.charAt(j)) > -1) {\n indented = indentLine(cm, range.head.line, \"smart\");\n break;\n }\n } else if (mode.electricInput) {\n if (mode.electricInput.test(getLine(cm.doc, range.head.line).text.slice(0, range.head.ch)))\n indented = indentLine(cm, range.head.line, \"smart\");\n }\n if (indented) signalLater(cm, \"electricInput\", cm, range.head.line);\n }\n }\n\n function copyableRanges(cm) {\n var text = [], ranges = [];\n for (var i = 0; i < cm.doc.sel.ranges.length; i++) {\n var line = cm.doc.sel.ranges[i].head.line;\n var lineRange = {anchor: Pos(line, 0), head: Pos(line + 1, 0)};\n ranges.push(lineRange);\n text.push(cm.getRange(lineRange.anchor, lineRange.head));\n }\n return {text: text, ranges: ranges};\n }\n\n function disableBrowserMagic(field) {\n field.setAttribute(\"autocorrect\", \"off\");\n field.setAttribute(\"autocapitalize\", \"off\");\n field.setAttribute(\"spellcheck\", \"false\");\n }\n\n // TEXTAREA INPUT STYLE\n\n function TextareaInput(cm) {\n this.cm = cm;\n // See input.poll and input.reset\n this.prevInput = \"\";\n\n // Flag that indicates whether we expect input to appear real soon\n // now (after some event like 'keypress' or 'input') and are\n // polling intensively.\n this.pollingFast = false;\n // Self-resetting timeout for the poller\n this.polling = new Delayed();\n // Tracks when input.reset has punted to just putting a short\n // string into the textarea instead of the full selection.\n this.inaccurateSelection = false;\n // Used to work around IE issue with selection being forgotten when focus moves away from textarea\n this.hasSelection = false;\n this.composing = null;\n };\n\n function hiddenTextarea() {\n var te = elt(\"textarea\", null, null, \"position: absolute; padding: 0; width: 1px; height: 1em; outline: none\");\n var div = elt(\"div\", [te], null, \"overflow: hidden; position: relative; width: 3px; height: 0px;\");\n // The textarea is kept positioned near the cursor to prevent the\n // fact that it'll be scrolled into view on input from scrolling\n // our fake cursor out of view. On webkit, when wrap=off, paste is\n // very slow. So make the area wide instead.\n if (webkit) te.style.width = \"1000px\";\n else te.setAttribute(\"wrap\", \"off\");\n // If border: 0; -- iOS fails to open keyboard (issue #1287)\n if (ios) te.style.border = \"1px solid black\";\n disableBrowserMagic(te);\n return div;\n }\n\n TextareaInput.prototype = copyObj({\n init: function(display) {\n var input = this, cm = this.cm;\n\n // Wraps and hides input textarea\n var div = this.wrapper = hiddenTextarea();\n // The semihidden textarea that is focused when the editor is\n // focused, and receives input.\n var te = this.textarea = div.firstChild;\n display.wrapper.insertBefore(div, display.wrapper.firstChild);\n\n // Needed to hide big blue blinking cursor on Mobile Safari (doesn't seem to work in iOS 8 anymore)\n if (ios) te.style.width = \"0px\";\n\n on(te, \"input\", function() {\n if (ie && ie_version >= 9 && input.hasSelection) input.hasSelection = null;\n input.poll();\n });\n\n on(te, \"paste\", function(e) {\n if (signalDOMEvent(cm, e) || handlePaste(e, cm)) return\n\n cm.state.pasteIncoming = true;\n input.fastPoll();\n });\n\n function prepareCopyCut(e) {\n if (signalDOMEvent(cm, e)) return\n if (cm.somethingSelected()) {\n lastCopied = cm.getSelections();\n if (input.inaccurateSelection) {\n input.prevInput = \"\";\n input.inaccurateSelection = false;\n te.value = lastCopied.join(\"\\n\");\n selectInput(te);\n }\n } else if (!cm.options.lineWiseCopyCut) {\n return;\n } else {\n var ranges = copyableRanges(cm);\n lastCopied = ranges.text;\n if (e.type == \"cut\") {\n cm.setSelections(ranges.ranges, null, sel_dontScroll);\n } else {\n input.prevInput = \"\";\n te.value = ranges.text.join(\"\\n\");\n selectInput(te);\n }\n }\n if (e.type == \"cut\") cm.state.cutIncoming = true;\n }\n on(te, \"cut\", prepareCopyCut);\n on(te, \"copy\", prepareCopyCut);\n\n on(display.scroller, \"paste\", function(e) {\n if (eventInWidget(display, e) || signalDOMEvent(cm, e)) return;\n cm.state.pasteIncoming = true;\n input.focus();\n });\n\n // Prevent normal selection in the editor (we handle our own)\n on(display.lineSpace, \"selectstart\", function(e) {\n if (!eventInWidget(display, e)) e_preventDefault(e);\n });\n\n on(te, \"compositionstart\", function() {\n var start = cm.getCursor(\"from\");\n if (input.composing) input.composing.range.clear()\n input.composing = {\n start: start,\n range: cm.markText(start, cm.getCursor(\"to\"), {className: \"CodeMirror-composing\"})\n };\n });\n on(te, \"compositionend\", function() {\n if (input.composing) {\n input.poll();\n input.composing.range.clear();\n input.composing = null;\n }\n });\n },\n\n prepareSelection: function() {\n // Redraw the selection and/or cursor\n var cm = this.cm, display = cm.display, doc = cm.doc;\n var result = prepareSelection(cm);\n\n // Move the hidden textarea near the cursor to prevent scrolling artifacts\n if (cm.options.moveInputWithCursor) {\n var headPos = cursorCoords(cm, doc.sel.primary().head, \"div\");\n var wrapOff = display.wrapper.getBoundingClientRect(), lineOff = display.lineDiv.getBoundingClientRect();\n result.teTop = Math.max(0, Math.min(display.wrapper.clientHeight - 10,\n headPos.top + lineOff.top - wrapOff.top));\n result.teLeft = Math.max(0, Math.min(display.wrapper.clientWidth - 10,\n headPos.left + lineOff.left - wrapOff.left));\n }\n\n return result;\n },\n\n showSelection: function(drawn) {\n var cm = this.cm, display = cm.display;\n removeChildrenAndAdd(display.cursorDiv, drawn.cursors);\n removeChildrenAndAdd(display.selectionDiv, drawn.selection);\n if (drawn.teTop != null) {\n this.wrapper.style.top = drawn.teTop + \"px\";\n this.wrapper.style.left = drawn.teLeft + \"px\";\n }\n },\n\n // Reset the input to correspond to the selection (or to be empty,\n // when not typing and nothing is selected)\n reset: function(typing) {\n if (this.contextMenuPending) return;\n var minimal, selected, cm = this.cm, doc = cm.doc;\n if (cm.somethingSelected()) {\n this.prevInput = \"\";\n var range = doc.sel.primary();\n minimal = hasCopyEvent &&\n (range.to().line - range.from().line > 100 || (selected = cm.getSelection()).length > 1000);\n var content = minimal ? \"-\" : selected || cm.getSelection();\n this.textarea.value = content;\n if (cm.state.focused) selectInput(this.textarea);\n if (ie && ie_version >= 9) this.hasSelection = content;\n } else if (!typing) {\n this.prevInput = this.textarea.value = \"\";\n if (ie && ie_version >= 9) this.hasSelection = null;\n }\n this.inaccurateSelection = minimal;\n },\n\n getField: function() { return this.textarea; },\n\n supportsTouch: function() { return false; },\n\n focus: function() {\n if (this.cm.options.readOnly != \"nocursor\" && (!mobile || activeElt() != this.textarea)) {\n try { this.textarea.focus(); }\n catch (e) {} // IE8 will throw if the textarea is display: none or not in DOM\n }\n },\n\n blur: function() { this.textarea.blur(); },\n\n resetPosition: function() {\n this.wrapper.style.top = this.wrapper.style.left = 0;\n },\n\n receivedFocus: function() { this.slowPoll(); },\n\n // Poll for input changes, using the normal rate of polling. This\n // runs as long as the editor is focused.\n slowPoll: function() {\n var input = this;\n if (input.pollingFast) return;\n input.polling.set(this.cm.options.pollInterval, function() {\n input.poll();\n if (input.cm.state.focused) input.slowPoll();\n });\n },\n\n // When an event has just come in that is likely to add or change\n // something in the input textarea, we poll faster, to ensure that\n // the change appears on the screen quickly.\n fastPoll: function() {\n var missed = false, input = this;\n input.pollingFast = true;\n function p() {\n var changed = input.poll();\n if (!changed && !missed) {missed = true; input.polling.set(60, p);}\n else {input.pollingFast = false; input.slowPoll();}\n }\n input.polling.set(20, p);\n },\n\n // Read input from the textarea, and update the document to match.\n // When something is selected, it is present in the textarea, and\n // selected (unless it is huge, in which case a placeholder is\n // used). When nothing is selected, the cursor sits after previously\n // seen text (can be empty), which is stored in prevInput (we must\n // not reset the textarea when typing, because that breaks IME).\n poll: function() {\n var cm = this.cm, input = this.textarea, prevInput = this.prevInput;\n // Since this is called a *lot*, try to bail out as cheaply as\n // possible when it is clear that nothing happened. hasSelection\n // will be the case when there is a lot of text in the textarea,\n // in which case reading its value would be expensive.\n if (this.contextMenuPending || !cm.state.focused ||\n (hasSelection(input) && !prevInput && !this.composing) ||\n cm.isReadOnly() || cm.options.disableInput || cm.state.keySeq)\n return false;\n\n var text = input.value;\n // If nothing changed, bail.\n if (text == prevInput && !cm.somethingSelected()) return false;\n // Work around nonsensical selection resetting in IE9/10, and\n // inexplicable appearance of private area unicode characters on\n // some key combos in Mac (#2689).\n if (ie && ie_version >= 9 && this.hasSelection === text ||\n mac && /[\\uf700-\\uf7ff]/.test(text)) {\n cm.display.input.reset();\n return false;\n }\n\n if (cm.doc.sel == cm.display.selForContextMenu) {\n var first = text.charCodeAt(0);\n if (first == 0x200b && !prevInput) prevInput = \"\\u200b\";\n if (first == 0x21da) { this.reset(); return this.cm.execCommand(\"undo\"); }\n }\n // Find the part of the input that is actually new\n var same = 0, l = Math.min(prevInput.length, text.length);\n while (same < l && prevInput.charCodeAt(same) == text.charCodeAt(same)) ++same;\n\n var self = this;\n runInOp(cm, function() {\n applyTextInput(cm, text.slice(same), prevInput.length - same,\n null, self.composing ? \"*compose\" : null);\n\n // Don't leave long text in the textarea, since it makes further polling slow\n if (text.length > 1000 || text.indexOf(\"\\n\") > -1) input.value = self.prevInput = \"\";\n else self.prevInput = text;\n\n if (self.composing) {\n self.composing.range.clear();\n self.composing.range = cm.markText(self.composing.start, cm.getCursor(\"to\"),\n {className: \"CodeMirror-composing\"});\n }\n });\n return true;\n },\n\n ensurePolled: function() {\n if (this.pollingFast && this.poll()) this.pollingFast = false;\n },\n\n onKeyPress: function() {\n if (ie && ie_version >= 9) this.hasSelection = null;\n this.fastPoll();\n },\n\n onContextMenu: function(e) {\n var input = this, cm = input.cm, display = cm.display, te = input.textarea;\n var pos = posFromMouse(cm, e), scrollPos = display.scroller.scrollTop;\n if (!pos || presto) return; // Opera is difficult.\n\n // Reset the current text selection only if the click is done outside of the selection\n // and 'resetSelectionOnContextMenu' option is true.\n var reset = cm.options.resetSelectionOnContextMenu;\n if (reset && cm.doc.sel.contains(pos) == -1)\n operation(cm, setSelection)(cm.doc, simpleSelection(pos), sel_dontScroll);\n\n var oldCSS = te.style.cssText, oldWrapperCSS = input.wrapper.style.cssText;\n input.wrapper.style.cssText = \"position: absolute\"\n var wrapperBox = input.wrapper.getBoundingClientRect()\n te.style.cssText = \"position: absolute; width: 30px; height: 30px; top: \" + (e.clientY - wrapperBox.top - 5) +\n \"px; left: \" + (e.clientX - wrapperBox.left - 5) + \"px; z-index: 1000; background: \" +\n (ie ? \"rgba(255, 255, 255, .05)\" : \"transparent\") +\n \"; outline: none; border-width: 0; outline: none; overflow: hidden; opacity: .05; filter: alpha(opacity=5);\";\n if (webkit) var oldScrollY = window.scrollY; // Work around Chrome issue (#2712)\n display.input.focus();\n if (webkit) window.scrollTo(null, oldScrollY);\n display.input.reset();\n // Adds \"Select all\" to context menu in FF\n if (!cm.somethingSelected()) te.value = input.prevInput = \" \";\n input.contextMenuPending = true;\n display.selForContextMenu = cm.doc.sel;\n clearTimeout(display.detectingSelectAll);\n\n // Select-all will be greyed out if there's nothing to select, so\n // this adds a zero-width space so that we can later check whether\n // it got selected.\n function prepareSelectAllHack() {\n if (te.selectionStart != null) {\n var selected = cm.somethingSelected();\n var extval = \"\\u200b\" + (selected ? te.value : \"\");\n te.value = \"\\u21da\"; // Used to catch context-menu undo\n te.value = extval;\n input.prevInput = selected ? \"\" : \"\\u200b\";\n te.selectionStart = 1; te.selectionEnd = extval.length;\n // Re-set this, in case some other handler touched the\n // selection in the meantime.\n display.selForContextMenu = cm.doc.sel;\n }\n }\n function rehide() {\n input.contextMenuPending = false;\n input.wrapper.style.cssText = oldWrapperCSS\n te.style.cssText = oldCSS;\n if (ie && ie_version < 9) display.scrollbars.setScrollTop(display.scroller.scrollTop = scrollPos);\n\n // Try to detect the user choosing select-all\n if (te.selectionStart != null) {\n if (!ie || (ie && ie_version < 9)) prepareSelectAllHack();\n var i = 0, poll = function() {\n if (display.selForContextMenu == cm.doc.sel && te.selectionStart == 0 &&\n te.selectionEnd > 0 && input.prevInput == \"\\u200b\")\n operation(cm, commands.selectAll)(cm);\n else if (i++ < 10) display.detectingSelectAll = setTimeout(poll, 500);\n else display.input.reset();\n };\n display.detectingSelectAll = setTimeout(poll, 200);\n }\n }\n\n if (ie && ie_version >= 9) prepareSelectAllHack();\n if (captureRightClick) {\n e_stop(e);\n var mouseup = function() {\n off(window, \"mouseup\", mouseup);\n setTimeout(rehide, 20);\n };\n on(window, \"mouseup\", mouseup);\n } else {\n setTimeout(rehide, 50);\n }\n },\n\n readOnlyChanged: function(val) {\n if (!val) this.reset();\n },\n\n setUneditable: nothing,\n\n needsContentAttribute: false\n }, TextareaInput.prototype);\n\n // CONTENTEDITABLE INPUT STYLE\n\n function ContentEditableInput(cm) {\n this.cm = cm;\n this.lastAnchorNode = this.lastAnchorOffset = this.lastFocusNode = this.lastFocusOffset = null;\n this.polling = new Delayed();\n this.gracePeriod = false;\n }\n\n ContentEditableInput.prototype = copyObj({\n init: function(display) {\n var input = this, cm = input.cm;\n var div = input.div = display.lineDiv;\n disableBrowserMagic(div);\n\n on(div, \"paste\", function(e) {\n if (!signalDOMEvent(cm, e)) handlePaste(e, cm);\n })\n\n on(div, \"compositionstart\", function(e) {\n var data = e.data;\n input.composing = {sel: cm.doc.sel, data: data, startData: data};\n if (!data) return;\n var prim = cm.doc.sel.primary();\n var line = cm.getLine(prim.head.line);\n var found = line.indexOf(data, Math.max(0, prim.head.ch - data.length));\n if (found > -1 && found <= prim.head.ch)\n input.composing.sel = simpleSelection(Pos(prim.head.line, found),\n Pos(prim.head.line, found + data.length));\n });\n on(div, \"compositionupdate\", function(e) {\n input.composing.data = e.data;\n });\n on(div, \"compositionend\", function(e) {\n var ours = input.composing;\n if (!ours) return;\n if (e.data != ours.startData && !/\\u200b/.test(e.data))\n ours.data = e.data;\n // Need a small delay to prevent other code (input event,\n // selection polling) from doing damage when fired right after\n // compositionend.\n setTimeout(function() {\n if (!ours.handled)\n input.applyComposition(ours);\n if (input.composing == ours)\n input.composing = null;\n }, 50);\n });\n\n on(div, \"touchstart\", function() {\n input.forceCompositionEnd();\n });\n\n on(div, \"input\", function() {\n if (input.composing) return;\n if (cm.isReadOnly() || !input.pollContent())\n runInOp(input.cm, function() {regChange(cm);});\n });\n\n function onCopyCut(e) {\n if (signalDOMEvent(cm, e)) return\n if (cm.somethingSelected()) {\n lastCopied = cm.getSelections();\n if (e.type == \"cut\") cm.replaceSelection(\"\", null, \"cut\");\n } else if (!cm.options.lineWiseCopyCut) {\n return;\n } else {\n var ranges = copyableRanges(cm);\n lastCopied = ranges.text;\n if (e.type == \"cut\") {\n cm.operation(function() {\n cm.setSelections(ranges.ranges, 0, sel_dontScroll);\n cm.replaceSelection(\"\", null, \"cut\");\n });\n }\n }\n // iOS exposes the clipboard API, but seems to discard content inserted into it\n if (e.clipboardData && !ios) {\n e.preventDefault();\n e.clipboardData.clearData();\n e.clipboardData.setData(\"text/plain\", lastCopied.join(\"\\n\"));\n } else {\n // Old-fashioned briefly-focus-a-textarea hack\n var kludge = hiddenTextarea(), te = kludge.firstChild;\n cm.display.lineSpace.insertBefore(kludge, cm.display.lineSpace.firstChild);\n te.value = lastCopied.join(\"\\n\");\n var hadFocus = document.activeElement;\n selectInput(te);\n setTimeout(function() {\n cm.display.lineSpace.removeChild(kludge);\n hadFocus.focus();\n }, 50);\n }\n }\n on(div, \"copy\", onCopyCut);\n on(div, \"cut\", onCopyCut);\n },\n\n prepareSelection: function() {\n var result = prepareSelection(this.cm, false);\n result.focus = this.cm.state.focused;\n return result;\n },\n\n showSelection: function(info) {\n if (!info || !this.cm.display.view.length) return;\n if (info.focus) this.showPrimarySelection();\n this.showMultipleSelections(info);\n },\n\n showPrimarySelection: function() {\n var sel = window.getSelection(), prim = this.cm.doc.sel.primary();\n var curAnchor = domToPos(this.cm, sel.anchorNode, sel.anchorOffset);\n var curFocus = domToPos(this.cm, sel.focusNode, sel.focusOffset);\n if (curAnchor && !curAnchor.bad && curFocus && !curFocus.bad &&\n cmp(minPos(curAnchor, curFocus), prim.from()) == 0 &&\n cmp(maxPos(curAnchor, curFocus), prim.to()) == 0)\n return;\n\n var start = posToDOM(this.cm, prim.from());\n var end = posToDOM(this.cm, prim.to());\n if (!start && !end) return;\n\n var view = this.cm.display.view;\n var old = sel.rangeCount && sel.getRangeAt(0);\n if (!start) {\n start = {node: view[0].measure.map[2], offset: 0};\n } else if (!end) { // FIXME dangerously hacky\n var measure = view[view.length - 1].measure;\n var map = measure.maps ? measure.maps[measure.maps.length - 1] : measure.map;\n end = {node: map[map.length - 1], offset: map[map.length - 2] - map[map.length - 3]};\n }\n\n try { var rng = range(start.node, start.offset, end.offset, end.node); }\n catch(e) {} // Our model of the DOM might be outdated, in which case the range we try to set can be impossible\n if (rng) {\n if (!gecko && this.cm.state.focused) {\n sel.collapse(start.node, start.offset);\n if (!rng.collapsed) sel.addRange(rng);\n } else {\n sel.removeAllRanges();\n sel.addRange(rng);\n }\n if (old && sel.anchorNode == null) sel.addRange(old);\n else if (gecko) this.startGracePeriod();\n }\n this.rememberSelection();\n },\n\n startGracePeriod: function() {\n var input = this;\n clearTimeout(this.gracePeriod);\n this.gracePeriod = setTimeout(function() {\n input.gracePeriod = false;\n if (input.selectionChanged())\n input.cm.operation(function() { input.cm.curOp.selectionChanged = true; });\n }, 20);\n },\n\n showMultipleSelections: function(info) {\n removeChildrenAndAdd(this.cm.display.cursorDiv, info.cursors);\n removeChildrenAndAdd(this.cm.display.selectionDiv, info.selection);\n },\n\n rememberSelection: function() {\n var sel = window.getSelection();\n this.lastAnchorNode = sel.anchorNode; this.lastAnchorOffset = sel.anchorOffset;\n this.lastFocusNode = sel.focusNode; this.lastFocusOffset = sel.focusOffset;\n },\n\n selectionInEditor: function() {\n var sel = window.getSelection();\n if (!sel.rangeCount) return false;\n var node = sel.getRangeAt(0).commonAncestorContainer;\n return contains(this.div, node);\n },\n\n focus: function() {\n if (this.cm.options.readOnly != \"nocursor\") this.div.focus();\n },\n blur: function() { this.div.blur(); },\n getField: function() { return this.div; },\n\n supportsTouch: function() { return true; },\n\n receivedFocus: function() {\n var input = this;\n if (this.selectionInEditor())\n this.pollSelection();\n else\n runInOp(this.cm, function() { input.cm.curOp.selectionChanged = true; });\n\n function poll() {\n if (input.cm.state.focused) {\n input.pollSelection();\n input.polling.set(input.cm.options.pollInterval, poll);\n }\n }\n this.polling.set(this.cm.options.pollInterval, poll);\n },\n\n selectionChanged: function() {\n var sel = window.getSelection();\n return sel.anchorNode != this.lastAnchorNode || sel.anchorOffset != this.lastAnchorOffset ||\n sel.focusNode != this.lastFocusNode || sel.focusOffset != this.lastFocusOffset;\n },\n\n pollSelection: function() {\n if (!this.composing && !this.gracePeriod && this.selectionChanged()) {\n var sel = window.getSelection(), cm = this.cm;\n this.rememberSelection();\n var anchor = domToPos(cm, sel.anchorNode, sel.anchorOffset);\n var head = domToPos(cm, sel.focusNode, sel.focusOffset);\n if (anchor && head) runInOp(cm, function() {\n setSelection(cm.doc, simpleSelection(anchor, head), sel_dontScroll);\n if (anchor.bad || head.bad) cm.curOp.selectionChanged = true;\n });\n }\n },\n\n pollContent: function() {\n var cm = this.cm, display = cm.display, sel = cm.doc.sel.primary();\n var from = sel.from(), to = sel.to();\n if (from.line < display.viewFrom || to.line > display.viewTo - 1) return false;\n\n var fromIndex;\n if (from.line == display.viewFrom || (fromIndex = findViewIndex(cm, from.line)) == 0) {\n var fromLine = lineNo(display.view[0].line);\n var fromNode = display.view[0].node;\n } else {\n var fromLine = lineNo(display.view[fromIndex].line);\n var fromNode = display.view[fromIndex - 1].node.nextSibling;\n }\n var toIndex = findViewIndex(cm, to.line);\n if (toIndex == display.view.length - 1) {\n var toLine = display.viewTo - 1;\n var toNode = display.lineDiv.lastChild;\n } else {\n var toLine = lineNo(display.view[toIndex + 1].line) - 1;\n var toNode = display.view[toIndex + 1].node.previousSibling;\n }\n\n var newText = cm.doc.splitLines(domTextBetween(cm, fromNode, toNode, fromLine, toLine));\n var oldText = getBetween(cm.doc, Pos(fromLine, 0), Pos(toLine, getLine(cm.doc, toLine).text.length));\n while (newText.length > 1 && oldText.length > 1) {\n if (lst(newText) == lst(oldText)) { newText.pop(); oldText.pop(); toLine--; }\n else if (newText[0] == oldText[0]) { newText.shift(); oldText.shift(); fromLine++; }\n else break;\n }\n\n var cutFront = 0, cutEnd = 0;\n var newTop = newText[0], oldTop = oldText[0], maxCutFront = Math.min(newTop.length, oldTop.length);\n while (cutFront < maxCutFront && newTop.charCodeAt(cutFront) == oldTop.charCodeAt(cutFront))\n ++cutFront;\n var newBot = lst(newText), oldBot = lst(oldText);\n var maxCutEnd = Math.min(newBot.length - (newText.length == 1 ? cutFront : 0),\n oldBot.length - (oldText.length == 1 ? cutFront : 0));\n while (cutEnd < maxCutEnd &&\n newBot.charCodeAt(newBot.length - cutEnd - 1) == oldBot.charCodeAt(oldBot.length - cutEnd - 1))\n ++cutEnd;\n\n newText[newText.length - 1] = newBot.slice(0, newBot.length - cutEnd);\n newText[0] = newText[0].slice(cutFront);\n\n var chFrom = Pos(fromLine, cutFront);\n var chTo = Pos(toLine, oldText.length ? lst(oldText).length - cutEnd : 0);\n if (newText.length > 1 || newText[0] || cmp(chFrom, chTo)) {\n replaceRange(cm.doc, newText, chFrom, chTo, \"+input\");\n return true;\n }\n },\n\n ensurePolled: function() {\n this.forceCompositionEnd();\n },\n reset: function() {\n this.forceCompositionEnd();\n },\n forceCompositionEnd: function() {\n if (!this.composing || this.composing.handled) return;\n this.applyComposition(this.composing);\n this.composing.handled = true;\n this.div.blur();\n this.div.focus();\n },\n applyComposition: function(composing) {\n if (this.cm.isReadOnly())\n operation(this.cm, regChange)(this.cm)\n else if (composing.data && composing.data != composing.startData)\n operation(this.cm, applyTextInput)(this.cm, composing.data, 0, composing.sel);\n },\n\n setUneditable: function(node) {\n node.contentEditable = \"false\"\n },\n\n onKeyPress: function(e) {\n e.preventDefault();\n if (!this.cm.isReadOnly())\n operation(this.cm, applyTextInput)(this.cm, String.fromCharCode(e.charCode == null ? e.keyCode : e.charCode), 0);\n },\n\n readOnlyChanged: function(val) {\n this.div.contentEditable = String(val != \"nocursor\")\n },\n\n onContextMenu: nothing,\n resetPosition: nothing,\n\n needsContentAttribute: true\n }, ContentEditableInput.prototype);\n\n function posToDOM(cm, pos) {\n var view = findViewForLine(cm, pos.line);\n if (!view || view.hidden) return null;\n var line = getLine(cm.doc, pos.line);\n var info = mapFromLineView(view, line, pos.line);\n\n var order = getOrder(line), side = \"left\";\n if (order) {\n var partPos = getBidiPartAt(order, pos.ch);\n side = partPos % 2 ? \"right\" : \"left\";\n }\n var result = nodeAndOffsetInLineMap(info.map, pos.ch, side);\n result.offset = result.collapse == \"right\" ? result.end : result.start;\n return result;\n }\n\n function badPos(pos, bad) { if (bad) pos.bad = true; return pos; }\n\n function domToPos(cm, node, offset) {\n var lineNode;\n if (node == cm.display.lineDiv) {\n lineNode = cm.display.lineDiv.childNodes[offset];\n if (!lineNode) return badPos(cm.clipPos(Pos(cm.display.viewTo - 1)), true);\n node = null; offset = 0;\n } else {\n for (lineNode = node;; lineNode = lineNode.parentNode) {\n if (!lineNode || lineNode == cm.display.lineDiv) return null;\n if (lineNode.parentNode && lineNode.parentNode == cm.display.lineDiv) break;\n }\n }\n for (var i = 0; i < cm.display.view.length; i++) {\n var lineView = cm.display.view[i];\n if (lineView.node == lineNode)\n return locateNodeInLineView(lineView, node, offset);\n }\n }\n\n function locateNodeInLineView(lineView, node, offset) {\n var wrapper = lineView.text.firstChild, bad = false;\n if (!node || !contains(wrapper, node)) return badPos(Pos(lineNo(lineView.line), 0), true);\n if (node == wrapper) {\n bad = true;\n node = wrapper.childNodes[offset];\n offset = 0;\n if (!node) {\n var line = lineView.rest ? lst(lineView.rest) : lineView.line;\n return badPos(Pos(lineNo(line), line.text.length), bad);\n }\n }\n\n var textNode = node.nodeType == 3 ? node : null, topNode = node;\n if (!textNode && node.childNodes.length == 1 && node.firstChild.nodeType == 3) {\n textNode = node.firstChild;\n if (offset) offset = textNode.nodeValue.length;\n }\n while (topNode.parentNode != wrapper) topNode = topNode.parentNode;\n var measure = lineView.measure, maps = measure.maps;\n\n function find(textNode, topNode, offset) {\n for (var i = -1; i < (maps ? maps.length : 0); i++) {\n var map = i < 0 ? measure.map : maps[i];\n for (var j = 0; j < map.length; j += 3) {\n var curNode = map[j + 2];\n if (curNode == textNode || curNode == topNode) {\n var line = lineNo(i < 0 ? lineView.line : lineView.rest[i]);\n var ch = map[j] + offset;\n if (offset < 0 || curNode != textNode) ch = map[j + (offset ? 1 : 0)];\n return Pos(line, ch);\n }\n }\n }\n }\n var found = find(textNode, topNode, offset);\n if (found) return badPos(found, bad);\n\n // FIXME this is all really shaky. might handle the few cases it needs to handle, but likely to cause problems\n for (var after = topNode.nextSibling, dist = textNode ? textNode.nodeValue.length - offset : 0; after; after = after.nextSibling) {\n found = find(after, after.firstChild, 0);\n if (found)\n return badPos(Pos(found.line, found.ch - dist), bad);\n else\n dist += after.textContent.length;\n }\n for (var before = topNode.previousSibling, dist = offset; before; before = before.previousSibling) {\n found = find(before, before.firstChild, -1);\n if (found)\n return badPos(Pos(found.line, found.ch + dist), bad);\n else\n dist += after.textContent.length;\n }\n }\n\n function domTextBetween(cm, from, to, fromLine, toLine) {\n var text = \"\", closing = false, lineSep = cm.doc.lineSeparator();\n function recognizeMarker(id) { return function(marker) { return marker.id == id; }; }\n function walk(node) {\n if (node.nodeType == 1) {\n var cmText = node.getAttribute(\"cm-text\");\n if (cmText != null) {\n if (cmText == \"\") cmText = node.textContent.replace(/\\u200b/g, \"\");\n text += cmText;\n return;\n }\n var markerID = node.getAttribute(\"cm-marker\"), range;\n if (markerID) {\n var found = cm.findMarks(Pos(fromLine, 0), Pos(toLine + 1, 0), recognizeMarker(+markerID));\n if (found.length && (range = found[0].find()))\n text += getBetween(cm.doc, range.from, range.to).join(lineSep);\n return;\n }\n if (node.getAttribute(\"contenteditable\") == \"false\") return;\n for (var i = 0; i < node.childNodes.length; i++)\n walk(node.childNodes[i]);\n if (/^(pre|div|p)$/i.test(node.nodeName))\n closing = true;\n } else if (node.nodeType == 3) {\n var val = node.nodeValue;\n if (!val) return;\n if (closing) {\n text += lineSep;\n closing = false;\n }\n text += val;\n }\n }\n for (;;) {\n walk(from);\n if (from == to) break;\n from = from.nextSibling;\n }\n return text;\n }\n\n CodeMirror.inputStyles = {\"textarea\": TextareaInput, \"contenteditable\": ContentEditableInput};\n\n // SELECTION / CURSOR\n\n // Selection objects are immutable. A new one is created every time\n // the selection changes. A selection is one or more non-overlapping\n // (and non-touching) ranges, sorted, and an integer that indicates\n // which one is the primary selection (the one that's scrolled into\n // view, that getCursor returns, etc).\n function Selection(ranges, primIndex) {\n this.ranges = ranges;\n this.primIndex = primIndex;\n }\n\n Selection.prototype = {\n primary: function() { return this.ranges[this.primIndex]; },\n equals: function(other) {\n if (other == this) return true;\n if (other.primIndex != this.primIndex || other.ranges.length != this.ranges.length) return false;\n for (var i = 0; i < this.ranges.length; i++) {\n var here = this.ranges[i], there = other.ranges[i];\n if (cmp(here.anchor, there.anchor) != 0 || cmp(here.head, there.head) != 0) return false;\n }\n return true;\n },\n deepCopy: function() {\n for (var out = [], i = 0; i < this.ranges.length; i++)\n out[i] = new Range(copyPos(this.ranges[i].anchor), copyPos(this.ranges[i].head));\n return new Selection(out, this.primIndex);\n },\n somethingSelected: function() {\n for (var i = 0; i < this.ranges.length; i++)\n if (!this.ranges[i].empty()) return true;\n return false;\n },\n contains: function(pos, end) {\n if (!end) end = pos;\n for (var i = 0; i < this.ranges.length; i++) {\n var range = this.ranges[i];\n if (cmp(end, range.from()) >= 0 && cmp(pos, range.to()) <= 0)\n return i;\n }\n return -1;\n }\n };\n\n function Range(anchor, head) {\n this.anchor = anchor; this.head = head;\n }\n\n Range.prototype = {\n from: function() { return minPos(this.anchor, this.head); },\n to: function() { return maxPos(this.anchor, this.head); },\n empty: function() {\n return this.head.line == this.anchor.line && this.head.ch == this.anchor.ch;\n }\n };\n\n // Take an unsorted, potentially overlapping set of ranges, and\n // build a selection out of it. 'Consumes' ranges array (modifying\n // it).\n function normalizeSelection(ranges, primIndex) {\n var prim = ranges[primIndex];\n ranges.sort(function(a, b) { return cmp(a.from(), b.from()); });\n primIndex = indexOf(ranges, prim);\n for (var i = 1; i < ranges.length; i++) {\n var cur = ranges[i], prev = ranges[i - 1];\n if (cmp(prev.to(), cur.from()) >= 0) {\n var from = minPos(prev.from(), cur.from()), to = maxPos(prev.to(), cur.to());\n var inv = prev.empty() ? cur.from() == cur.head : prev.from() == prev.head;\n if (i <= primIndex) --primIndex;\n ranges.splice(--i, 2, new Range(inv ? to : from, inv ? from : to));\n }\n }\n return new Selection(ranges, primIndex);\n }\n\n function simpleSelection(anchor, head) {\n return new Selection([new Range(anchor, head || anchor)], 0);\n }\n\n // Most of the external API clips given positions to make sure they\n // actually exist within the document.\n function clipLine(doc, n) {return Math.max(doc.first, Math.min(n, doc.first + doc.size - 1));}\n function clipPos(doc, pos) {\n if (pos.line < doc.first) return Pos(doc.first, 0);\n var last = doc.first + doc.size - 1;\n if (pos.line > last) return Pos(last, getLine(doc, last).text.length);\n return clipToLen(pos, getLine(doc, pos.line).text.length);\n }\n function clipToLen(pos, linelen) {\n var ch = pos.ch;\n if (ch == null || ch > linelen) return Pos(pos.line, linelen);\n else if (ch < 0) return Pos(pos.line, 0);\n else return pos;\n }\n function isLine(doc, l) {return l >= doc.first && l < doc.first + doc.size;}\n function clipPosArray(doc, array) {\n for (var out = [], i = 0; i < array.length; i++) out[i] = clipPos(doc, array[i]);\n return out;\n }\n\n // SELECTION UPDATES\n\n // The 'scroll' parameter given to many of these indicated whether\n // the new cursor position should be scrolled into view after\n // modifying the selection.\n\n // If shift is held or the extend flag is set, extends a range to\n // include a given position (and optionally a second position).\n // Otherwise, simply returns the range between the given positions.\n // Used for cursor motion and such.\n function extendRange(doc, range, head, other) {\n if (doc.cm && doc.cm.display.shift || doc.extend) {\n var anchor = range.anchor;\n if (other) {\n var posBefore = cmp(head, anchor) < 0;\n if (posBefore != (cmp(other, anchor) < 0)) {\n anchor = head;\n head = other;\n } else if (posBefore != (cmp(head, other) < 0)) {\n head = other;\n }\n }\n return new Range(anchor, head);\n } else {\n return new Range(other || head, head);\n }\n }\n\n // Extend the primary selection range, discard the rest.\n function extendSelection(doc, head, other, options) {\n setSelection(doc, new Selection([extendRange(doc, doc.sel.primary(), head, other)], 0), options);\n }\n\n // Extend all selections (pos is an array of selections with length\n // equal the number of selections)\n function extendSelections(doc, heads, options) {\n for (var out = [], i = 0; i < doc.sel.ranges.length; i++)\n out[i] = extendRange(doc, doc.sel.ranges[i], heads[i], null);\n var newSel = normalizeSelection(out, doc.sel.primIndex);\n setSelection(doc, newSel, options);\n }\n\n // Updates a single range in the selection.\n function replaceOneSelection(doc, i, range, options) {\n var ranges = doc.sel.ranges.slice(0);\n ranges[i] = range;\n setSelection(doc, normalizeSelection(ranges, doc.sel.primIndex), options);\n }\n\n // Reset the selection to a single range.\n function setSimpleSelection(doc, anchor, head, options) {\n setSelection(doc, simpleSelection(anchor, head), options);\n }\n\n // Give beforeSelectionChange handlers a change to influence a\n // selection update.\n function filterSelectionChange(doc, sel, options) {\n var obj = {\n ranges: sel.ranges,\n update: function(ranges) {\n this.ranges = [];\n for (var i = 0; i < ranges.length; i++)\n this.ranges[i] = new Range(clipPos(doc, ranges[i].anchor),\n clipPos(doc, ranges[i].head));\n },\n origin: options && options.origin\n };\n signal(doc, \"beforeSelectionChange\", doc, obj);\n if (doc.cm) signal(doc.cm, \"beforeSelectionChange\", doc.cm, obj);\n if (obj.ranges != sel.ranges) return normalizeSelection(obj.ranges, obj.ranges.length - 1);\n else return sel;\n }\n\n function setSelectionReplaceHistory(doc, sel, options) {\n var done = doc.history.done, last = lst(done);\n if (last && last.ranges) {\n done[done.length - 1] = sel;\n setSelectionNoUndo(doc, sel, options);\n } else {\n setSelection(doc, sel, options);\n }\n }\n\n // Set a new selection.\n function setSelection(doc, sel, options) {\n setSelectionNoUndo(doc, sel, options);\n addSelectionToHistory(doc, doc.sel, doc.cm ? doc.cm.curOp.id : NaN, options);\n }\n\n function setSelectionNoUndo(doc, sel, options) {\n if (hasHandler(doc, \"beforeSelectionChange\") || doc.cm && hasHandler(doc.cm, \"beforeSelectionChange\"))\n sel = filterSelectionChange(doc, sel, options);\n\n var bias = options && options.bias ||\n (cmp(sel.primary().head, doc.sel.primary().head) < 0 ? -1 : 1);\n setSelectionInner(doc, skipAtomicInSelection(doc, sel, bias, true));\n\n if (!(options && options.scroll === false) && doc.cm)\n ensureCursorVisible(doc.cm);\n }\n\n function setSelectionInner(doc, sel) {\n if (sel.equals(doc.sel)) return;\n\n doc.sel = sel;\n\n if (doc.cm) {\n doc.cm.curOp.updateInput = doc.cm.curOp.selectionChanged = true;\n signalCursorActivity(doc.cm);\n }\n signalLater(doc, \"cursorActivity\", doc);\n }\n\n // Verify that the selection does not partially select any atomic\n // marked ranges.\n function reCheckSelection(doc) {\n setSelectionInner(doc, skipAtomicInSelection(doc, doc.sel, null, false), sel_dontScroll);\n }\n\n // Return a selection that does not partially select any atomic\n // ranges.\n function skipAtomicInSelection(doc, sel, bias, mayClear) {\n var out;\n for (var i = 0; i < sel.ranges.length; i++) {\n var range = sel.ranges[i];\n var old = sel.ranges.length == doc.sel.ranges.length && doc.sel.ranges[i];\n var newAnchor = skipAtomic(doc, range.anchor, old && old.anchor, bias, mayClear);\n var newHead = skipAtomic(doc, range.head, old && old.head, bias, mayClear);\n if (out || newAnchor != range.anchor || newHead != range.head) {\n if (!out) out = sel.ranges.slice(0, i);\n out[i] = new Range(newAnchor, newHead);\n }\n }\n return out ? normalizeSelection(out, sel.primIndex) : sel;\n }\n\n function skipAtomicInner(doc, pos, oldPos, dir, mayClear) {\n var line = getLine(doc, pos.line);\n if (line.markedSpans) for (var i = 0; i < line.markedSpans.length; ++i) {\n var sp = line.markedSpans[i], m = sp.marker;\n if ((sp.from == null || (m.inclusiveLeft ? sp.from <= pos.ch : sp.from < pos.ch)) &&\n (sp.to == null || (m.inclusiveRight ? sp.to >= pos.ch : sp.to > pos.ch))) {\n if (mayClear) {\n signal(m, \"beforeCursorEnter\");\n if (m.explicitlyCleared) {\n if (!line.markedSpans) break;\n else {--i; continue;}\n }\n }\n if (!m.atomic) continue;\n\n if (oldPos) {\n var near = m.find(dir < 0 ? 1 : -1), diff;\n if (dir < 0 ? m.inclusiveRight : m.inclusiveLeft)\n near = movePos(doc, near, -dir, near && near.line == pos.line ? line : null);\n if (near && near.line == pos.line && (diff = cmp(near, oldPos)) && (dir < 0 ? diff < 0 : diff > 0))\n return skipAtomicInner(doc, near, pos, dir, mayClear);\n }\n\n var far = m.find(dir < 0 ? -1 : 1);\n if (dir < 0 ? m.inclusiveLeft : m.inclusiveRight)\n far = movePos(doc, far, dir, far.line == pos.line ? line : null);\n return far ? skipAtomicInner(doc, far, pos, dir, mayClear) : null;\n }\n }\n return pos;\n }\n\n // Ensure a given position is not inside an atomic range.\n function skipAtomic(doc, pos, oldPos, bias, mayClear) {\n var dir = bias || 1;\n var found = skipAtomicInner(doc, pos, oldPos, dir, mayClear) ||\n (!mayClear && skipAtomicInner(doc, pos, oldPos, dir, true)) ||\n skipAtomicInner(doc, pos, oldPos, -dir, mayClear) ||\n (!mayClear && skipAtomicInner(doc, pos, oldPos, -dir, true));\n if (!found) {\n doc.cantEdit = true;\n return Pos(doc.first, 0);\n }\n return found;\n }\n\n function movePos(doc, pos, dir, line) {\n if (dir < 0 && pos.ch == 0) {\n if (pos.line > doc.first) return clipPos(doc, Pos(pos.line - 1));\n else return null;\n } else if (dir > 0 && pos.ch == (line || getLine(doc, pos.line)).text.length) {\n if (pos.line < doc.first + doc.size - 1) return Pos(pos.line + 1, 0);\n else return null;\n } else {\n return new Pos(pos.line, pos.ch + dir);\n }\n }\n\n // SELECTION DRAWING\n\n function updateSelection(cm) {\n cm.display.input.showSelection(cm.display.input.prepareSelection());\n }\n\n function prepareSelection(cm, primary) {\n var doc = cm.doc, result = {};\n var curFragment = result.cursors = document.createDocumentFragment();\n var selFragment = result.selection = document.createDocumentFragment();\n\n for (var i = 0; i < doc.sel.ranges.length; i++) {\n if (primary === false && i == doc.sel.primIndex) continue;\n var range = doc.sel.ranges[i];\n if (range.from().line >= cm.display.viewTo || range.to().line < cm.display.viewFrom) continue;\n var collapsed = range.empty();\n if (collapsed || cm.options.showCursorWhenSelecting)\n drawSelectionCursor(cm, range.head, curFragment);\n if (!collapsed)\n drawSelectionRange(cm, range, selFragment);\n }\n return result;\n }\n\n // Draws a cursor for the given range\n function drawSelectionCursor(cm, head, output) {\n var pos = cursorCoords(cm, head, \"div\", null, null, !cm.options.singleCursorHeightPerLine);\n\n var cursor = output.appendChild(elt(\"div\", \"\\u00a0\", \"CodeMirror-cursor\"));\n cursor.style.left = pos.left + \"px\";\n cursor.style.top = pos.top + \"px\";\n cursor.style.height = Math.max(0, pos.bottom - pos.top) * cm.options.cursorHeight + \"px\";\n\n if (pos.other) {\n // Secondary cursor, shown when on a 'jump' in bi-directional text\n var otherCursor = output.appendChild(elt(\"div\", \"\\u00a0\", \"CodeMirror-cursor CodeMirror-secondarycursor\"));\n otherCursor.style.display = \"\";\n otherCursor.style.left = pos.other.left + \"px\";\n otherCursor.style.top = pos.other.top + \"px\";\n otherCursor.style.height = (pos.other.bottom - pos.other.top) * .85 + \"px\";\n }\n }\n\n // Draws the given range as a highlighted selection\n function drawSelectionRange(cm, range, output) {\n var display = cm.display, doc = cm.doc;\n var fragment = document.createDocumentFragment();\n var padding = paddingH(cm.display), leftSide = padding.left;\n var rightSide = Math.max(display.sizerWidth, displayWidth(cm) - display.sizer.offsetLeft) - padding.right;\n\n function add(left, top, width, bottom) {\n if (top < 0) top = 0;\n top = Math.round(top);\n bottom = Math.round(bottom);\n fragment.appendChild(elt(\"div\", null, \"CodeMirror-selected\", \"position: absolute; left: \" + left +\n \"px; top: \" + top + \"px; width: \" + (width == null ? rightSide - left : width) +\n \"px; height: \" + (bottom - top) + \"px\"));\n }\n\n function drawForLine(line, fromArg, toArg) {\n var lineObj = getLine(doc, line);\n var lineLen = lineObj.text.length;\n var start, end;\n function coords(ch, bias) {\n return charCoords(cm, Pos(line, ch), \"div\", lineObj, bias);\n }\n\n iterateBidiSections(getOrder(lineObj), fromArg || 0, toArg == null ? lineLen : toArg, function(from, to, dir) {\n var leftPos = coords(from, \"left\"), rightPos, left, right;\n if (from == to) {\n rightPos = leftPos;\n left = right = leftPos.left;\n } else {\n rightPos = coords(to - 1, \"right\");\n if (dir == \"rtl\") { var tmp = leftPos; leftPos = rightPos; rightPos = tmp; }\n left = leftPos.left;\n right = rightPos.right;\n }\n if (fromArg == null && from == 0) left = leftSide;\n if (rightPos.top - leftPos.top > 3) { // Different lines, draw top part\n add(left, leftPos.top, null, leftPos.bottom);\n left = leftSide;\n if (leftPos.bottom < rightPos.top) add(left, leftPos.bottom, null, rightPos.top);\n }\n if (toArg == null && to == lineLen) right = rightSide;\n if (!start || leftPos.top < start.top || leftPos.top == start.top && leftPos.left < start.left)\n start = leftPos;\n if (!end || rightPos.bottom > end.bottom || rightPos.bottom == end.bottom && rightPos.right > end.right)\n end = rightPos;\n if (left < leftSide + 1) left = leftSide;\n add(left, rightPos.top, right - left, rightPos.bottom);\n });\n return {start: start, end: end};\n }\n\n var sFrom = range.from(), sTo = range.to();\n if (sFrom.line == sTo.line) {\n drawForLine(sFrom.line, sFrom.ch, sTo.ch);\n } else {\n var fromLine = getLine(doc, sFrom.line), toLine = getLine(doc, sTo.line);\n var singleVLine = visualLine(fromLine) == visualLine(toLine);\n var leftEnd = drawForLine(sFrom.line, sFrom.ch, singleVLine ? fromLine.text.length + 1 : null).end;\n var rightStart = drawForLine(sTo.line, singleVLine ? 0 : null, sTo.ch).start;\n if (singleVLine) {\n if (leftEnd.top < rightStart.top - 2) {\n add(leftEnd.right, leftEnd.top, null, leftEnd.bottom);\n add(leftSide, rightStart.top, rightStart.left, rightStart.bottom);\n } else {\n add(leftEnd.right, leftEnd.top, rightStart.left - leftEnd.right, leftEnd.bottom);\n }\n }\n if (leftEnd.bottom < rightStart.top)\n add(leftSide, leftEnd.bottom, null, rightStart.top);\n }\n\n output.appendChild(fragment);\n }\n\n // Cursor-blinking\n function restartBlink(cm) {\n if (!cm.state.focused) return;\n var display = cm.display;\n clearInterval(display.blinker);\n var on = true;\n display.cursorDiv.style.visibility = \"\";\n if (cm.options.cursorBlinkRate > 0)\n display.blinker = setInterval(function() {\n display.cursorDiv.style.visibility = (on = !on) ? \"\" : \"hidden\";\n }, cm.options.cursorBlinkRate);\n else if (cm.options.cursorBlinkRate < 0)\n display.cursorDiv.style.visibility = \"hidden\";\n }\n\n // HIGHLIGHT WORKER\n\n function startWorker(cm, time) {\n if (cm.doc.mode.startState && cm.doc.frontier < cm.display.viewTo)\n cm.state.highlight.set(time, bind(highlightWorker, cm));\n }\n\n function highlightWorker(cm) {\n var doc = cm.doc;\n if (doc.frontier < doc.first) doc.frontier = doc.first;\n if (doc.frontier >= cm.display.viewTo) return;\n var end = +new Date + cm.options.workTime;\n var state = copyState(doc.mode, getStateBefore(cm, doc.frontier));\n var changedLines = [];\n\n doc.iter(doc.frontier, Math.min(doc.first + doc.size, cm.display.viewTo + 500), function(line) {\n if (doc.frontier >= cm.display.viewFrom) { // Visible\n var oldStyles = line.styles, tooLong = line.text.length > cm.options.maxHighlightLength;\n var highlighted = highlightLine(cm, line, tooLong ? copyState(doc.mode, state) : state, true);\n line.styles = highlighted.styles;\n var oldCls = line.styleClasses, newCls = highlighted.classes;\n if (newCls) line.styleClasses = newCls;\n else if (oldCls) line.styleClasses = null;\n var ischange = !oldStyles || oldStyles.length != line.styles.length ||\n oldCls != newCls && (!oldCls || !newCls || oldCls.bgClass != newCls.bgClass || oldCls.textClass != newCls.textClass);\n for (var i = 0; !ischange && i < oldStyles.length; ++i) ischange = oldStyles[i] != line.styles[i];\n if (ischange) changedLines.push(doc.frontier);\n line.stateAfter = tooLong ? state : copyState(doc.mode, state);\n } else {\n if (line.text.length <= cm.options.maxHighlightLength)\n processLine(cm, line.text, state);\n line.stateAfter = doc.frontier % 5 == 0 ? copyState(doc.mode, state) : null;\n }\n ++doc.frontier;\n if (+new Date > end) {\n startWorker(cm, cm.options.workDelay);\n return true;\n }\n });\n if (changedLines.length) runInOp(cm, function() {\n for (var i = 0; i < changedLines.length; i++)\n regLineChange(cm, changedLines[i], \"text\");\n });\n }\n\n // Finds the line to start with when starting a parse. Tries to\n // find a line with a stateAfter, so that it can start with a\n // valid state. If that fails, it returns the line with the\n // smallest indentation, which tends to need the least context to\n // parse correctly.\n function findStartLine(cm, n, precise) {\n var minindent, minline, doc = cm.doc;\n var lim = precise ? -1 : n - (cm.doc.mode.innerMode ? 1000 : 100);\n for (var search = n; search > lim; --search) {\n if (search <= doc.first) return doc.first;\n var line = getLine(doc, search - 1);\n if (line.stateAfter && (!precise || search <= doc.frontier)) return search;\n var indented = countColumn(line.text, null, cm.options.tabSize);\n if (minline == null || minindent > indented) {\n minline = search - 1;\n minindent = indented;\n }\n }\n return minline;\n }\n\n function getStateBefore(cm, n, precise) {\n var doc = cm.doc, display = cm.display;\n if (!doc.mode.startState) return true;\n var pos = findStartLine(cm, n, precise), state = pos > doc.first && getLine(doc, pos-1).stateAfter;\n if (!state) state = startState(doc.mode);\n else state = copyState(doc.mode, state);\n doc.iter(pos, n, function(line) {\n processLine(cm, line.text, state);\n var save = pos == n - 1 || pos % 5 == 0 || pos >= display.viewFrom && pos < display.viewTo;\n line.stateAfter = save ? copyState(doc.mode, state) : null;\n ++pos;\n });\n if (precise) doc.frontier = pos;\n return state;\n }\n\n // POSITION MEASUREMENT\n\n function paddingTop(display) {return display.lineSpace.offsetTop;}\n function paddingVert(display) {return display.mover.offsetHeight - display.lineSpace.offsetHeight;}\n function paddingH(display) {\n if (display.cachedPaddingH) return display.cachedPaddingH;\n var e = removeChildrenAndAdd(display.measure, elt(\"pre\", \"x\"));\n var style = window.getComputedStyle ? window.getComputedStyle(e) : e.currentStyle;\n var data = {left: parseInt(style.paddingLeft), right: parseInt(style.paddingRight)};\n if (!isNaN(data.left) && !isNaN(data.right)) display.cachedPaddingH = data;\n return data;\n }\n\n function scrollGap(cm) { return scrollerGap - cm.display.nativeBarWidth; }\n function displayWidth(cm) {\n return cm.display.scroller.clientWidth - scrollGap(cm) - cm.display.barWidth;\n }\n function displayHeight(cm) {\n return cm.display.scroller.clientHeight - scrollGap(cm) - cm.display.barHeight;\n }\n\n // Ensure the lineView.wrapping.heights array is populated. This is\n // an array of bottom offsets for the lines that make up a drawn\n // line. When lineWrapping is on, there might be more than one\n // height.\n function ensureLineHeights(cm, lineView, rect) {\n var wrapping = cm.options.lineWrapping;\n var curWidth = wrapping && displayWidth(cm);\n if (!lineView.measure.heights || wrapping && lineView.measure.width != curWidth) {\n var heights = lineView.measure.heights = [];\n if (wrapping) {\n lineView.measure.width = curWidth;\n var rects = lineView.text.firstChild.getClientRects();\n for (var i = 0; i < rects.length - 1; i++) {\n var cur = rects[i], next = rects[i + 1];\n if (Math.abs(cur.bottom - next.bottom) > 2)\n heights.push((cur.bottom + next.top) / 2 - rect.top);\n }\n }\n heights.push(rect.bottom - rect.top);\n }\n }\n\n // Find a line map (mapping character offsets to text nodes) and a\n // measurement cache for the given line number. (A line view might\n // contain multiple lines when collapsed ranges are present.)\n function mapFromLineView(lineView, line, lineN) {\n if (lineView.line == line)\n return {map: lineView.measure.map, cache: lineView.measure.cache};\n for (var i = 0; i < lineView.rest.length; i++)\n if (lineView.rest[i] == line)\n return {map: lineView.measure.maps[i], cache: lineView.measure.caches[i]};\n for (var i = 0; i < lineView.rest.length; i++)\n if (lineNo(lineView.rest[i]) > lineN)\n return {map: lineView.measure.maps[i], cache: lineView.measure.caches[i], before: true};\n }\n\n // Render a line into the hidden node display.externalMeasured. Used\n // when measurement is needed for a line that's not in the viewport.\n function updateExternalMeasurement(cm, line) {\n line = visualLine(line);\n var lineN = lineNo(line);\n var view = cm.display.externalMeasured = new LineView(cm.doc, line, lineN);\n view.lineN = lineN;\n var built = view.built = buildLineContent(cm, view);\n view.text = built.pre;\n removeChildrenAndAdd(cm.display.lineMeasure, built.pre);\n return view;\n }\n\n // Get a {top, bottom, left, right} box (in line-local coordinates)\n // for a given character.\n function measureChar(cm, line, ch, bias) {\n return measureCharPrepared(cm, prepareMeasureForLine(cm, line), ch, bias);\n }\n\n // Find a line view that corresponds to the given line number.\n function findViewForLine(cm, lineN) {\n if (lineN >= cm.display.viewFrom && lineN < cm.display.viewTo)\n return cm.display.view[findViewIndex(cm, lineN)];\n var ext = cm.display.externalMeasured;\n if (ext && lineN >= ext.lineN && lineN < ext.lineN + ext.size)\n return ext;\n }\n\n // Measurement can be split in two steps, the set-up work that\n // applies to the whole line, and the measurement of the actual\n // character. Functions like coordsChar, that need to do a lot of\n // measurements in a row, can thus ensure that the set-up work is\n // only done once.\n function prepareMeasureForLine(cm, line) {\n var lineN = lineNo(line);\n var view = findViewForLine(cm, lineN);\n if (view && !view.text) {\n view = null;\n } else if (view && view.changes) {\n updateLineForChanges(cm, view, lineN, getDimensions(cm));\n cm.curOp.forceUpdate = true;\n }\n if (!view)\n view = updateExternalMeasurement(cm, line);\n\n var info = mapFromLineView(view, line, lineN);\n return {\n line: line, view: view, rect: null,\n map: info.map, cache: info.cache, before: info.before,\n hasHeights: false\n };\n }\n\n // Given a prepared measurement object, measures the position of an\n // actual character (or fetches it from the cache).\n function measureCharPrepared(cm, prepared, ch, bias, varHeight) {\n if (prepared.before) ch = -1;\n var key = ch + (bias || \"\"), found;\n if (prepared.cache.hasOwnProperty(key)) {\n found = prepared.cache[key];\n } else {\n if (!prepared.rect)\n prepared.rect = prepared.view.text.getBoundingClientRect();\n if (!prepared.hasHeights) {\n ensureLineHeights(cm, prepared.view, prepared.rect);\n prepared.hasHeights = true;\n }\n found = measureCharInner(cm, prepared, ch, bias);\n if (!found.bogus) prepared.cache[key] = found;\n }\n return {left: found.left, right: found.right,\n top: varHeight ? found.rtop : found.top,\n bottom: varHeight ? found.rbottom : found.bottom};\n }\n\n var nullRect = {left: 0, right: 0, top: 0, bottom: 0};\n\n function nodeAndOffsetInLineMap(map, ch, bias) {\n var node, start, end, collapse;\n // First, search the line map for the text node corresponding to,\n // or closest to, the target character.\n for (var i = 0; i < map.length; i += 3) {\n var mStart = map[i], mEnd = map[i + 1];\n if (ch < mStart) {\n start = 0; end = 1;\n collapse = \"left\";\n } else if (ch < mEnd) {\n start = ch - mStart;\n end = start + 1;\n } else if (i == map.length - 3 || ch == mEnd && map[i + 3] > ch) {\n end = mEnd - mStart;\n start = end - 1;\n if (ch >= mEnd) collapse = \"right\";\n }\n if (start != null) {\n node = map[i + 2];\n if (mStart == mEnd && bias == (node.insertLeft ? \"left\" : \"right\"))\n collapse = bias;\n if (bias == \"left\" && start == 0)\n while (i && map[i - 2] == map[i - 3] && map[i - 1].insertLeft) {\n node = map[(i -= 3) + 2];\n collapse = \"left\";\n }\n if (bias == \"right\" && start == mEnd - mStart)\n while (i < map.length - 3 && map[i + 3] == map[i + 4] && !map[i + 5].insertLeft) {\n node = map[(i += 3) + 2];\n collapse = \"right\";\n }\n break;\n }\n }\n return {node: node, start: start, end: end, collapse: collapse, coverStart: mStart, coverEnd: mEnd};\n }\n\n function measureCharInner(cm, prepared, ch, bias) {\n var place = nodeAndOffsetInLineMap(prepared.map, ch, bias);\n var node = place.node, start = place.start, end = place.end, collapse = place.collapse;\n\n var rect;\n if (node.nodeType == 3) { // If it is a text node, use a range to retrieve the coordinates.\n for (var i = 0; i < 4; i++) { // Retry a maximum of 4 times when nonsense rectangles are returned\n while (start && isExtendingChar(prepared.line.text.charAt(place.coverStart + start))) --start;\n while (place.coverStart + end < place.coverEnd && isExtendingChar(prepared.line.text.charAt(place.coverStart + end))) ++end;\n if (ie && ie_version < 9 && start == 0 && end == place.coverEnd - place.coverStart) {\n rect = node.parentNode.getBoundingClientRect();\n } else if (ie && cm.options.lineWrapping) {\n var rects = range(node, start, end).getClientRects();\n if (rects.length)\n rect = rects[bias == \"right\" ? rects.length - 1 : 0];\n else\n rect = nullRect;\n } else {\n rect = range(node, start, end).getBoundingClientRect() || nullRect;\n }\n if (rect.left || rect.right || start == 0) break;\n end = start;\n start = start - 1;\n collapse = \"right\";\n }\n if (ie && ie_version < 11) rect = maybeUpdateRectForZooming(cm.display.measure, rect);\n } else { // If it is a widget, simply get the box for the whole widget.\n if (start > 0) collapse = bias = \"right\";\n var rects;\n if (cm.options.lineWrapping && (rects = node.getClientRects()).length > 1)\n rect = rects[bias == \"right\" ? rects.length - 1 : 0];\n else\n rect = node.getBoundingClientRect();\n }\n if (ie && ie_version < 9 && !start && (!rect || !rect.left && !rect.right)) {\n var rSpan = node.parentNode.getClientRects()[0];\n if (rSpan)\n rect = {left: rSpan.left, right: rSpan.left + charWidth(cm.display), top: rSpan.top, bottom: rSpan.bottom};\n else\n rect = nullRect;\n }\n\n var rtop = rect.top - prepared.rect.top, rbot = rect.bottom - prepared.rect.top;\n var mid = (rtop + rbot) / 2;\n var heights = prepared.view.measure.heights;\n for (var i = 0; i < heights.length - 1; i++)\n if (mid < heights[i]) break;\n var top = i ? heights[i - 1] : 0, bot = heights[i];\n var result = {left: (collapse == \"right\" ? rect.right : rect.left) - prepared.rect.left,\n right: (collapse == \"left\" ? rect.left : rect.right) - prepared.rect.left,\n top: top, bottom: bot};\n if (!rect.left && !rect.right) result.bogus = true;\n if (!cm.options.singleCursorHeightPerLine) { result.rtop = rtop; result.rbottom = rbot; }\n\n return result;\n }\n\n // Work around problem with bounding client rects on ranges being\n // returned incorrectly when zoomed on IE10 and below.\n function maybeUpdateRectForZooming(measure, rect) {\n if (!window.screen || screen.logicalXDPI == null ||\n screen.logicalXDPI == screen.deviceXDPI || !hasBadZoomedRects(measure))\n return rect;\n var scaleX = screen.logicalXDPI / screen.deviceXDPI;\n var scaleY = screen.logicalYDPI / screen.deviceYDPI;\n return {left: rect.left * scaleX, right: rect.right * scaleX,\n top: rect.top * scaleY, bottom: rect.bottom * scaleY};\n }\n\n function clearLineMeasurementCacheFor(lineView) {\n if (lineView.measure) {\n lineView.measure.cache = {};\n lineView.measure.heights = null;\n if (lineView.rest) for (var i = 0; i < lineView.rest.length; i++)\n lineView.measure.caches[i] = {};\n }\n }\n\n function clearLineMeasurementCache(cm) {\n cm.display.externalMeasure = null;\n removeChildren(cm.display.lineMeasure);\n for (var i = 0; i < cm.display.view.length; i++)\n clearLineMeasurementCacheFor(cm.display.view[i]);\n }\n\n function clearCaches(cm) {\n clearLineMeasurementCache(cm);\n cm.display.cachedCharWidth = cm.display.cachedTextHeight = cm.display.cachedPaddingH = null;\n if (!cm.options.lineWrapping) cm.display.maxLineChanged = true;\n cm.display.lineNumChars = null;\n }\n\n function pageScrollX() { return window.pageXOffset || (document.documentElement || document.body).scrollLeft; }\n function pageScrollY() { return window.pageYOffset || (document.documentElement || document.body).scrollTop; }\n\n // Converts a {top, bottom, left, right} box from line-local\n // coordinates into another coordinate system. Context may be one of\n // \"line\", \"div\" (display.lineDiv), \"local\"/null (editor), \"window\",\n // or \"page\".\n function intoCoordSystem(cm, lineObj, rect, context) {\n if (lineObj.widgets) for (var i = 0; i < lineObj.widgets.length; ++i) if (lineObj.widgets[i].above) {\n var size = widgetHeight(lineObj.widgets[i]);\n rect.top += size; rect.bottom += size;\n }\n if (context == \"line\") return rect;\n if (!context) context = \"local\";\n var yOff = heightAtLine(lineObj);\n if (context == \"local\") yOff += paddingTop(cm.display);\n else yOff -= cm.display.viewOffset;\n if (context == \"page\" || context == \"window\") {\n var lOff = cm.display.lineSpace.getBoundingClientRect();\n yOff += lOff.top + (context == \"window\" ? 0 : pageScrollY());\n var xOff = lOff.left + (context == \"window\" ? 0 : pageScrollX());\n rect.left += xOff; rect.right += xOff;\n }\n rect.top += yOff; rect.bottom += yOff;\n return rect;\n }\n\n // Coverts a box from \"div\" coords to another coordinate system.\n // Context may be \"window\", \"page\", \"div\", or \"local\"/null.\n function fromCoordSystem(cm, coords, context) {\n if (context == \"div\") return coords;\n var left = coords.left, top = coords.top;\n // First move into \"page\" coordinate system\n if (context == \"page\") {\n left -= pageScrollX();\n top -= pageScrollY();\n } else if (context == \"local\" || !context) {\n var localBox = cm.display.sizer.getBoundingClientRect();\n left += localBox.left;\n top += localBox.top;\n }\n\n var lineSpaceBox = cm.display.lineSpace.getBoundingClientRect();\n return {left: left - lineSpaceBox.left, top: top - lineSpaceBox.top};\n }\n\n function charCoords(cm, pos, context, lineObj, bias) {\n if (!lineObj) lineObj = getLine(cm.doc, pos.line);\n return intoCoordSystem(cm, lineObj, measureChar(cm, lineObj, pos.ch, bias), context);\n }\n\n // Returns a box for a given cursor position, which may have an\n // 'other' property containing the position of the secondary cursor\n // on a bidi boundary.\n function cursorCoords(cm, pos, context, lineObj, preparedMeasure, varHeight) {\n lineObj = lineObj || getLine(cm.doc, pos.line);\n if (!preparedMeasure) preparedMeasure = prepareMeasureForLine(cm, lineObj);\n function get(ch, right) {\n var m = measureCharPrepared(cm, preparedMeasure, ch, right ? \"right\" : \"left\", varHeight);\n if (right) m.left = m.right; else m.right = m.left;\n return intoCoordSystem(cm, lineObj, m, context);\n }\n function getBidi(ch, partPos) {\n var part = order[partPos], right = part.level % 2;\n if (ch == bidiLeft(part) && partPos && part.level < order[partPos - 1].level) {\n part = order[--partPos];\n ch = bidiRight(part) - (part.level % 2 ? 0 : 1);\n right = true;\n } else if (ch == bidiRight(part) && partPos < order.length - 1 && part.level < order[partPos + 1].level) {\n part = order[++partPos];\n ch = bidiLeft(part) - part.level % 2;\n right = false;\n }\n if (right && ch == part.to && ch > part.from) return get(ch - 1);\n return get(ch, right);\n }\n var order = getOrder(lineObj), ch = pos.ch;\n if (!order) return get(ch);\n var partPos = getBidiPartAt(order, ch);\n var val = getBidi(ch, partPos);\n if (bidiOther != null) val.other = getBidi(ch, bidiOther);\n return val;\n }\n\n // Used to cheaply estimate the coordinates for a position. Used for\n // intermediate scroll updates.\n function estimateCoords(cm, pos) {\n var left = 0, pos = clipPos(cm.doc, pos);\n if (!cm.options.lineWrapping) left = charWidth(cm.display) * pos.ch;\n var lineObj = getLine(cm.doc, pos.line);\n var top = heightAtLine(lineObj) + paddingTop(cm.display);\n return {left: left, right: left, top: top, bottom: top + lineObj.height};\n }\n\n // Positions returned by coordsChar contain some extra information.\n // xRel is the relative x position of the input coordinates compared\n // to the found position (so xRel > 0 means the coordinates are to\n // the right of the character position, for example). When outside\n // is true, that means the coordinates lie outside the line's\n // vertical range.\n function PosWithInfo(line, ch, outside, xRel) {\n var pos = Pos(line, ch);\n pos.xRel = xRel;\n if (outside) pos.outside = true;\n return pos;\n }\n\n // Compute the character position closest to the given coordinates.\n // Input must be lineSpace-local (\"div\" coordinate system).\n function coordsChar(cm, x, y) {\n var doc = cm.doc;\n y += cm.display.viewOffset;\n if (y < 0) return PosWithInfo(doc.first, 0, true, -1);\n var lineN = lineAtHeight(doc, y), last = doc.first + doc.size - 1;\n if (lineN > last)\n return PosWithInfo(doc.first + doc.size - 1, getLine(doc, last).text.length, true, 1);\n if (x < 0) x = 0;\n\n var lineObj = getLine(doc, lineN);\n for (;;) {\n var found = coordsCharInner(cm, lineObj, lineN, x, y);\n var merged = collapsedSpanAtEnd(lineObj);\n var mergedPos = merged && merged.find(0, true);\n if (merged && (found.ch > mergedPos.from.ch || found.ch == mergedPos.from.ch && found.xRel > 0))\n lineN = lineNo(lineObj = mergedPos.to.line);\n else\n return found;\n }\n }\n\n function coordsCharInner(cm, lineObj, lineNo, x, y) {\n var innerOff = y - heightAtLine(lineObj);\n var wrongLine = false, adjust = 2 * cm.display.wrapper.clientWidth;\n var preparedMeasure = prepareMeasureForLine(cm, lineObj);\n\n function getX(ch) {\n var sp = cursorCoords(cm, Pos(lineNo, ch), \"line\", lineObj, preparedMeasure);\n wrongLine = true;\n if (innerOff > sp.bottom) return sp.left - adjust;\n else if (innerOff < sp.top) return sp.left + adjust;\n else wrongLine = false;\n return sp.left;\n }\n\n var bidi = getOrder(lineObj), dist = lineObj.text.length;\n var from = lineLeft(lineObj), to = lineRight(lineObj);\n var fromX = getX(from), fromOutside = wrongLine, toX = getX(to), toOutside = wrongLine;\n\n if (x > toX) return PosWithInfo(lineNo, to, toOutside, 1);\n // Do a binary search between these bounds.\n for (;;) {\n if (bidi ? to == from || to == moveVisually(lineObj, from, 1) : to - from <= 1) {\n var ch = x < fromX || x - fromX <= toX - x ? from : to;\n var xDiff = x - (ch == from ? fromX : toX);\n while (isExtendingChar(lineObj.text.charAt(ch))) ++ch;\n var pos = PosWithInfo(lineNo, ch, ch == from ? fromOutside : toOutside,\n xDiff < -1 ? -1 : xDiff > 1 ? 1 : 0);\n return pos;\n }\n var step = Math.ceil(dist / 2), middle = from + step;\n if (bidi) {\n middle = from;\n for (var i = 0; i < step; ++i) middle = moveVisually(lineObj, middle, 1);\n }\n var middleX = getX(middle);\n if (middleX > x) {to = middle; toX = middleX; if (toOutside = wrongLine) toX += 1000; dist = step;}\n else {from = middle; fromX = middleX; fromOutside = wrongLine; dist -= step;}\n }\n }\n\n var measureText;\n // Compute the default text height.\n function textHeight(display) {\n if (display.cachedTextHeight != null) return display.cachedTextHeight;\n if (measureText == null) {\n measureText = elt(\"pre\");\n // Measure a bunch of lines, for browsers that compute\n // fractional heights.\n for (var i = 0; i < 49; ++i) {\n measureText.appendChild(document.createTextNode(\"x\"));\n measureText.appendChild(elt(\"br\"));\n }\n measureText.appendChild(document.createTextNode(\"x\"));\n }\n removeChildrenAndAdd(display.measure, measureText);\n var height = measureText.offsetHeight / 50;\n if (height > 3) display.cachedTextHeight = height;\n removeChildren(display.measure);\n return height || 1;\n }\n\n // Compute the default character width.\n function charWidth(display) {\n if (display.cachedCharWidth != null) return display.cachedCharWidth;\n var anchor = elt(\"span\", \"xxxxxxxxxx\");\n var pre = elt(\"pre\", [anchor]);\n removeChildrenAndAdd(display.measure, pre);\n var rect = anchor.getBoundingClientRect(), width = (rect.right - rect.left) / 10;\n if (width > 2) display.cachedCharWidth = width;\n return width || 10;\n }\n\n // OPERATIONS\n\n // Operations are used to wrap a series of changes to the editor\n // state in such a way that each change won't have to update the\n // cursor and display (which would be awkward, slow, and\n // error-prone). Instead, display updates are batched and then all\n // combined and executed at once.\n\n var operationGroup = null;\n\n var nextOpId = 0;\n // Start a new operation.\n function startOperation(cm) {\n cm.curOp = {\n cm: cm,\n viewChanged: false, // Flag that indicates that lines might need to be redrawn\n startHeight: cm.doc.height, // Used to detect need to update scrollbar\n forceUpdate: false, // Used to force a redraw\n updateInput: null, // Whether to reset the input textarea\n typing: false, // Whether this reset should be careful to leave existing text (for compositing)\n changeObjs: null, // Accumulated changes, for firing change events\n cursorActivityHandlers: null, // Set of handlers to fire cursorActivity on\n cursorActivityCalled: 0, // Tracks which cursorActivity handlers have been called already\n selectionChanged: false, // Whether the selection needs to be redrawn\n updateMaxLine: false, // Set when the widest line needs to be determined anew\n scrollLeft: null, scrollTop: null, // Intermediate scroll position, not pushed to DOM yet\n scrollToPos: null, // Used to scroll to a specific position\n focus: false,\n id: ++nextOpId // Unique ID\n };\n if (operationGroup) {\n operationGroup.ops.push(cm.curOp);\n } else {\n cm.curOp.ownsGroup = operationGroup = {\n ops: [cm.curOp],\n delayedCallbacks: []\n };\n }\n }\n\n function fireCallbacksForOps(group) {\n // Calls delayed callbacks and cursorActivity handlers until no\n // new ones appear\n var callbacks = group.delayedCallbacks, i = 0;\n do {\n for (; i < callbacks.length; i++)\n callbacks[i].call(null);\n for (var j = 0; j < group.ops.length; j++) {\n var op = group.ops[j];\n if (op.cursorActivityHandlers)\n while (op.cursorActivityCalled < op.cursorActivityHandlers.length)\n op.cursorActivityHandlers[op.cursorActivityCalled++].call(null, op.cm);\n }\n } while (i < callbacks.length);\n }\n\n // Finish an operation, updating the display and signalling delayed events\n function endOperation(cm) {\n var op = cm.curOp, group = op.ownsGroup;\n if (!group) return;\n\n try { fireCallbacksForOps(group); }\n finally {\n operationGroup = null;\n for (var i = 0; i < group.ops.length; i++)\n group.ops[i].cm.curOp = null;\n endOperations(group);\n }\n }\n\n // The DOM updates done when an operation finishes are batched so\n // that the minimum number of relayouts are required.\n function endOperations(group) {\n var ops = group.ops;\n for (var i = 0; i < ops.length; i++) // Read DOM\n endOperation_R1(ops[i]);\n for (var i = 0; i < ops.length; i++) // Write DOM (maybe)\n endOperation_W1(ops[i]);\n for (var i = 0; i < ops.length; i++) // Read DOM\n endOperation_R2(ops[i]);\n for (var i = 0; i < ops.length; i++) // Write DOM (maybe)\n endOperation_W2(ops[i]);\n for (var i = 0; i < ops.length; i++) // Read DOM\n endOperation_finish(ops[i]);\n }\n\n function endOperation_R1(op) {\n var cm = op.cm, display = cm.display;\n maybeClipScrollbars(cm);\n if (op.updateMaxLine) findMaxLine(cm);\n\n op.mustUpdate = op.viewChanged || op.forceUpdate || op.scrollTop != null ||\n op.scrollToPos && (op.scrollToPos.from.line < display.viewFrom ||\n op.scrollToPos.to.line >= display.viewTo) ||\n display.maxLineChanged && cm.options.lineWrapping;\n op.update = op.mustUpdate &&\n new DisplayUpdate(cm, op.mustUpdate && {top: op.scrollTop, ensure: op.scrollToPos}, op.forceUpdate);\n }\n\n function endOperation_W1(op) {\n op.updatedDisplay = op.mustUpdate && updateDisplayIfNeeded(op.cm, op.update);\n }\n\n function endOperation_R2(op) {\n var cm = op.cm, display = cm.display;\n if (op.updatedDisplay) updateHeightsInViewport(cm);\n\n op.barMeasure = measureForScrollbars(cm);\n\n // If the max line changed since it was last measured, measure it,\n // and ensure the document's width matches it.\n // updateDisplay_W2 will use these properties to do the actual resizing\n if (display.maxLineChanged && !cm.options.lineWrapping) {\n op.adjustWidthTo = measureChar(cm, display.maxLine, display.maxLine.text.length).left + 3;\n cm.display.sizerWidth = op.adjustWidthTo;\n op.barMeasure.scrollWidth =\n Math.max(display.scroller.clientWidth, display.sizer.offsetLeft + op.adjustWidthTo + scrollGap(cm) + cm.display.barWidth);\n op.maxScrollLeft = Math.max(0, display.sizer.offsetLeft + op.adjustWidthTo - displayWidth(cm));\n }\n\n if (op.updatedDisplay || op.selectionChanged)\n op.preparedSelection = display.input.prepareSelection();\n }\n\n function endOperation_W2(op) {\n var cm = op.cm;\n\n if (op.adjustWidthTo != null) {\n cm.display.sizer.style.minWidth = op.adjustWidthTo + \"px\";\n if (op.maxScrollLeft < cm.doc.scrollLeft)\n setScrollLeft(cm, Math.min(cm.display.scroller.scrollLeft, op.maxScrollLeft), true);\n cm.display.maxLineChanged = false;\n }\n\n if (op.preparedSelection)\n cm.display.input.showSelection(op.preparedSelection);\n if (op.updatedDisplay || op.startHeight != cm.doc.height)\n updateScrollbars(cm, op.barMeasure);\n if (op.updatedDisplay)\n setDocumentHeight(cm, op.barMeasure);\n\n if (op.selectionChanged) restartBlink(cm);\n\n if (cm.state.focused && op.updateInput)\n cm.display.input.reset(op.typing);\n if (op.focus && op.focus == activeElt() && (!document.hasFocus || document.hasFocus()))\n ensureFocus(op.cm);\n }\n\n function endOperation_finish(op) {\n var cm = op.cm, display = cm.display, doc = cm.doc;\n\n if (op.updatedDisplay) postUpdateDisplay(cm, op.update);\n\n // Abort mouse wheel delta measurement, when scrolling explicitly\n if (display.wheelStartX != null && (op.scrollTop != null || op.scrollLeft != null || op.scrollToPos))\n display.wheelStartX = display.wheelStartY = null;\n\n // Propagate the scroll position to the actual DOM scroller\n if (op.scrollTop != null && (display.scroller.scrollTop != op.scrollTop || op.forceScroll)) {\n doc.scrollTop = Math.max(0, Math.min(display.scroller.scrollHeight - display.scroller.clientHeight, op.scrollTop));\n display.scrollbars.setScrollTop(doc.scrollTop);\n display.scroller.scrollTop = doc.scrollTop;\n }\n if (op.scrollLeft != null && (display.scroller.scrollLeft != op.scrollLeft || op.forceScroll)) {\n doc.scrollLeft = Math.max(0, Math.min(display.scroller.scrollWidth - display.scroller.clientWidth, op.scrollLeft));\n display.scrollbars.setScrollLeft(doc.scrollLeft);\n display.scroller.scrollLeft = doc.scrollLeft;\n alignHorizontally(cm);\n }\n // If we need to scroll a specific position into view, do so.\n if (op.scrollToPos) {\n var coords = scrollPosIntoView(cm, clipPos(doc, op.scrollToPos.from),\n clipPos(doc, op.scrollToPos.to), op.scrollToPos.margin);\n if (op.scrollToPos.isCursor && cm.state.focused) maybeScrollWindow(cm, coords);\n }\n\n // Fire events for markers that are hidden/unidden by editing or\n // undoing\n var hidden = op.maybeHiddenMarkers, unhidden = op.maybeUnhiddenMarkers;\n if (hidden) for (var i = 0; i < hidden.length; ++i)\n if (!hidden[i].lines.length) signal(hidden[i], \"hide\");\n if (unhidden) for (var i = 0; i < unhidden.length; ++i)\n if (unhidden[i].lines.length) signal(unhidden[i], \"unhide\");\n\n if (display.wrapper.offsetHeight)\n doc.scrollTop = cm.display.scroller.scrollTop;\n\n // Fire change events, and delayed event handlers\n if (op.changeObjs)\n signal(cm, \"changes\", cm, op.changeObjs);\n if (op.update)\n op.update.finish();\n }\n\n // Run the given function in an operation\n function runInOp(cm, f) {\n if (cm.curOp) return f();\n startOperation(cm);\n try { return f(); }\n finally { endOperation(cm); }\n }\n // Wraps a function in an operation. Returns the wrapped function.\n function operation(cm, f) {\n return function() {\n if (cm.curOp) return f.apply(cm, arguments);\n startOperation(cm);\n try { return f.apply(cm, arguments); }\n finally { endOperation(cm); }\n };\n }\n // Used to add methods to editor and doc instances, wrapping them in\n // operations.\n function methodOp(f) {\n return function() {\n if (this.curOp) return f.apply(this, arguments);\n startOperation(this);\n try { return f.apply(this, arguments); }\n finally { endOperation(this); }\n };\n }\n function docMethodOp(f) {\n return function() {\n var cm = this.cm;\n if (!cm || cm.curOp) return f.apply(this, arguments);\n startOperation(cm);\n try { return f.apply(this, arguments); }\n finally { endOperation(cm); }\n };\n }\n\n // VIEW TRACKING\n\n // These objects are used to represent the visible (currently drawn)\n // part of the document. A LineView may correspond to multiple\n // logical lines, if those are connected by collapsed ranges.\n function LineView(doc, line, lineN) {\n // The starting line\n this.line = line;\n // Continuing lines, if any\n this.rest = visualLineContinued(line);\n // Number of logical lines in this visual line\n this.size = this.rest ? lineNo(lst(this.rest)) - lineN + 1 : 1;\n this.node = this.text = null;\n this.hidden = lineIsHidden(doc, line);\n }\n\n // Create a range of LineView objects for the given lines.\n function buildViewArray(cm, from, to) {\n var array = [], nextPos;\n for (var pos = from; pos < to; pos = nextPos) {\n var view = new LineView(cm.doc, getLine(cm.doc, pos), pos);\n nextPos = pos + view.size;\n array.push(view);\n }\n return array;\n }\n\n // Updates the display.view data structure for a given change to the\n // document. From and to are in pre-change coordinates. Lendiff is\n // the amount of lines added or subtracted by the change. This is\n // used for changes that span multiple lines, or change the way\n // lines are divided into visual lines. regLineChange (below)\n // registers single-line changes.\n function regChange(cm, from, to, lendiff) {\n if (from == null) from = cm.doc.first;\n if (to == null) to = cm.doc.first + cm.doc.size;\n if (!lendiff) lendiff = 0;\n\n var display = cm.display;\n if (lendiff && to < display.viewTo &&\n (display.updateLineNumbers == null || display.updateLineNumbers > from))\n display.updateLineNumbers = from;\n\n cm.curOp.viewChanged = true;\n\n if (from >= display.viewTo) { // Change after\n if (sawCollapsedSpans && visualLineNo(cm.doc, from) < display.viewTo)\n resetView(cm);\n } else if (to <= display.viewFrom) { // Change before\n if (sawCollapsedSpans && visualLineEndNo(cm.doc, to + lendiff) > display.viewFrom) {\n resetView(cm);\n } else {\n display.viewFrom += lendiff;\n display.viewTo += lendiff;\n }\n } else if (from <= display.viewFrom && to >= display.viewTo) { // Full overlap\n resetView(cm);\n } else if (from <= display.viewFrom) { // Top overlap\n var cut = viewCuttingPoint(cm, to, to + lendiff, 1);\n if (cut) {\n display.view = display.view.slice(cut.index);\n display.viewFrom = cut.lineN;\n display.viewTo += lendiff;\n } else {\n resetView(cm);\n }\n } else if (to >= display.viewTo) { // Bottom overlap\n var cut = viewCuttingPoint(cm, from, from, -1);\n if (cut) {\n display.view = display.view.slice(0, cut.index);\n display.viewTo = cut.lineN;\n } else {\n resetView(cm);\n }\n } else { // Gap in the middle\n var cutTop = viewCuttingPoint(cm, from, from, -1);\n var cutBot = viewCuttingPoint(cm, to, to + lendiff, 1);\n if (cutTop && cutBot) {\n display.view = display.view.slice(0, cutTop.index)\n .concat(buildViewArray(cm, cutTop.lineN, cutBot.lineN))\n .concat(display.view.slice(cutBot.index));\n display.viewTo += lendiff;\n } else {\n resetView(cm);\n }\n }\n\n var ext = display.externalMeasured;\n if (ext) {\n if (to < ext.lineN)\n ext.lineN += lendiff;\n else if (from < ext.lineN + ext.size)\n display.externalMeasured = null;\n }\n }\n\n // Register a change to a single line. Type must be one of \"text\",\n // \"gutter\", \"class\", \"widget\"\n function regLineChange(cm, line, type) {\n cm.curOp.viewChanged = true;\n var display = cm.display, ext = cm.display.externalMeasured;\n if (ext && line >= ext.lineN && line < ext.lineN + ext.size)\n display.externalMeasured = null;\n\n if (line < display.viewFrom || line >= display.viewTo) return;\n var lineView = display.view[findViewIndex(cm, line)];\n if (lineView.node == null) return;\n var arr = lineView.changes || (lineView.changes = []);\n if (indexOf(arr, type) == -1) arr.push(type);\n }\n\n // Clear the view.\n function resetView(cm) {\n cm.display.viewFrom = cm.display.viewTo = cm.doc.first;\n cm.display.view = [];\n cm.display.viewOffset = 0;\n }\n\n // Find the view element corresponding to a given line. Return null\n // when the line isn't visible.\n function findViewIndex(cm, n) {\n if (n >= cm.display.viewTo) return null;\n n -= cm.display.viewFrom;\n if (n < 0) return null;\n var view = cm.display.view;\n for (var i = 0; i < view.length; i++) {\n n -= view[i].size;\n if (n < 0) return i;\n }\n }\n\n function viewCuttingPoint(cm, oldN, newN, dir) {\n var index = findViewIndex(cm, oldN), diff, view = cm.display.view;\n if (!sawCollapsedSpans || newN == cm.doc.first + cm.doc.size)\n return {index: index, lineN: newN};\n for (var i = 0, n = cm.display.viewFrom; i < index; i++)\n n += view[i].size;\n if (n != oldN) {\n if (dir > 0) {\n if (index == view.length - 1) return null;\n diff = (n + view[index].size) - oldN;\n index++;\n } else {\n diff = n - oldN;\n }\n oldN += diff; newN += diff;\n }\n while (visualLineNo(cm.doc, newN) != newN) {\n if (index == (dir < 0 ? 0 : view.length - 1)) return null;\n newN += dir * view[index - (dir < 0 ? 1 : 0)].size;\n index += dir;\n }\n return {index: index, lineN: newN};\n }\n\n // Force the view to cover a given range, adding empty view element\n // or clipping off existing ones as needed.\n function adjustView(cm, from, to) {\n var display = cm.display, view = display.view;\n if (view.length == 0 || from >= display.viewTo || to <= display.viewFrom) {\n display.view = buildViewArray(cm, from, to);\n display.viewFrom = from;\n } else {\n if (display.viewFrom > from)\n display.view = buildViewArray(cm, from, display.viewFrom).concat(display.view);\n else if (display.viewFrom < from)\n display.view = display.view.slice(findViewIndex(cm, from));\n display.viewFrom = from;\n if (display.viewTo < to)\n display.view = display.view.concat(buildViewArray(cm, display.viewTo, to));\n else if (display.viewTo > to)\n display.view = display.view.slice(0, findViewIndex(cm, to));\n }\n display.viewTo = to;\n }\n\n // Count the number of lines in the view whose DOM representation is\n // out of date (or nonexistent).\n function countDirtyView(cm) {\n var view = cm.display.view, dirty = 0;\n for (var i = 0; i < view.length; i++) {\n var lineView = view[i];\n if (!lineView.hidden && (!lineView.node || lineView.changes)) ++dirty;\n }\n return dirty;\n }\n\n // EVENT HANDLERS\n\n // Attach the necessary event handlers when initializing the editor\n function registerEventHandlers(cm) {\n var d = cm.display;\n on(d.scroller, \"mousedown\", operation(cm, onMouseDown));\n // Older IE's will not fire a second mousedown for a double click\n if (ie && ie_version < 11)\n on(d.scroller, \"dblclick\", operation(cm, function(e) {\n if (signalDOMEvent(cm, e)) return;\n var pos = posFromMouse(cm, e);\n if (!pos || clickInGutter(cm, e) || eventInWidget(cm.display, e)) return;\n e_preventDefault(e);\n var word = cm.findWordAt(pos);\n extendSelection(cm.doc, word.anchor, word.head);\n }));\n else\n on(d.scroller, \"dblclick\", function(e) { signalDOMEvent(cm, e) || e_preventDefault(e); });\n // Some browsers fire contextmenu *after* opening the menu, at\n // which point we can't mess with it anymore. Context menu is\n // handled in onMouseDown for these browsers.\n if (!captureRightClick) on(d.scroller, \"contextmenu\", function(e) {onContextMenu(cm, e);});\n\n // Used to suppress mouse event handling when a touch happens\n var touchFinished, prevTouch = {end: 0};\n function finishTouch() {\n if (d.activeTouch) {\n touchFinished = setTimeout(function() {d.activeTouch = null;}, 1000);\n prevTouch = d.activeTouch;\n prevTouch.end = +new Date;\n }\n };\n function isMouseLikeTouchEvent(e) {\n if (e.touches.length != 1) return false;\n var touch = e.touches[0];\n return touch.radiusX <= 1 && touch.radiusY <= 1;\n }\n function farAway(touch, other) {\n if (other.left == null) return true;\n var dx = other.left - touch.left, dy = other.top - touch.top;\n return dx * dx + dy * dy > 20 * 20;\n }\n on(d.scroller, \"touchstart\", function(e) {\n if (!signalDOMEvent(cm, e) && !isMouseLikeTouchEvent(e)) {\n clearTimeout(touchFinished);\n var now = +new Date;\n d.activeTouch = {start: now, moved: false,\n prev: now - prevTouch.end <= 300 ? prevTouch : null};\n if (e.touches.length == 1) {\n d.activeTouch.left = e.touches[0].pageX;\n d.activeTouch.top = e.touches[0].pageY;\n }\n }\n });\n on(d.scroller, \"touchmove\", function() {\n if (d.activeTouch) d.activeTouch.moved = true;\n });\n on(d.scroller, \"touchend\", function(e) {\n var touch = d.activeTouch;\n if (touch && !eventInWidget(d, e) && touch.left != null &&\n !touch.moved && new Date - touch.start < 300) {\n var pos = cm.coordsChar(d.activeTouch, \"page\"), range;\n if (!touch.prev || farAway(touch, touch.prev)) // Single tap\n range = new Range(pos, pos);\n else if (!touch.prev.prev || farAway(touch, touch.prev.prev)) // Double tap\n range = cm.findWordAt(pos);\n else // Triple tap\n range = new Range(Pos(pos.line, 0), clipPos(cm.doc, Pos(pos.line + 1, 0)));\n cm.setSelection(range.anchor, range.head);\n cm.focus();\n e_preventDefault(e);\n }\n finishTouch();\n });\n on(d.scroller, \"touchcancel\", finishTouch);\n\n // Sync scrolling between fake scrollbars and real scrollable\n // area, ensure viewport is updated when scrolling.\n on(d.scroller, \"scroll\", function() {\n if (d.scroller.clientHeight) {\n setScrollTop(cm, d.scroller.scrollTop);\n setScrollLeft(cm, d.scroller.scrollLeft, true);\n signal(cm, \"scroll\", cm);\n }\n });\n\n // Listen to wheel events in order to try and update the viewport on time.\n on(d.scroller, \"mousewheel\", function(e){onScrollWheel(cm, e);});\n on(d.scroller, \"DOMMouseScroll\", function(e){onScrollWheel(cm, e);});\n\n // Prevent wrapper from ever scrolling\n on(d.wrapper, \"scroll\", function() { d.wrapper.scrollTop = d.wrapper.scrollLeft = 0; });\n\n d.dragFunctions = {\n enter: function(e) {if (!signalDOMEvent(cm, e)) e_stop(e);},\n over: function(e) {if (!signalDOMEvent(cm, e)) { onDragOver(cm, e); e_stop(e); }},\n start: function(e){onDragStart(cm, e);},\n drop: operation(cm, onDrop),\n leave: function(e) {if (!signalDOMEvent(cm, e)) { clearDragCursor(cm); }}\n };\n\n var inp = d.input.getField();\n on(inp, \"keyup\", function(e) { onKeyUp.call(cm, e); });\n on(inp, \"keydown\", operation(cm, onKeyDown));\n on(inp, \"keypress\", operation(cm, onKeyPress));\n on(inp, \"focus\", bind(onFocus, cm));\n on(inp, \"blur\", bind(onBlur, cm));\n }\n\n function dragDropChanged(cm, value, old) {\n var wasOn = old && old != CodeMirror.Init;\n if (!value != !wasOn) {\n var funcs = cm.display.dragFunctions;\n var toggle = value ? on : off;\n toggle(cm.display.scroller, \"dragstart\", funcs.start);\n toggle(cm.display.scroller, \"dragenter\", funcs.enter);\n toggle(cm.display.scroller, \"dragover\", funcs.over);\n toggle(cm.display.scroller, \"dragleave\", funcs.leave);\n toggle(cm.display.scroller, \"drop\", funcs.drop);\n }\n }\n\n // Called when the window resizes\n function onResize(cm) {\n var d = cm.display;\n if (d.lastWrapHeight == d.wrapper.clientHeight && d.lastWrapWidth == d.wrapper.clientWidth)\n return;\n // Might be a text scaling operation, clear size caches.\n d.cachedCharWidth = d.cachedTextHeight = d.cachedPaddingH = null;\n d.scrollbarsClipped = false;\n cm.setSize();\n }\n\n // MOUSE EVENTS\n\n // Return true when the given mouse event happened in a widget\n function eventInWidget(display, e) {\n for (var n = e_target(e); n != display.wrapper; n = n.parentNode) {\n if (!n || (n.nodeType == 1 && n.getAttribute(\"cm-ignore-events\") == \"true\") ||\n (n.parentNode == display.sizer && n != display.mover))\n return true;\n }\n }\n\n // Given a mouse event, find the corresponding position. If liberal\n // is false, it checks whether a gutter or scrollbar was clicked,\n // and returns null if it was. forRect is used by rectangular\n // selections, and tries to estimate a character position even for\n // coordinates beyond the right of the text.\n function posFromMouse(cm, e, liberal, forRect) {\n var display = cm.display;\n if (!liberal && e_target(e).getAttribute(\"cm-not-content\") == \"true\") return null;\n\n var x, y, space = display.lineSpace.getBoundingClientRect();\n // Fails unpredictably on IE[67] when mouse is dragged around quickly.\n try { x = e.clientX - space.left; y = e.clientY - space.top; }\n catch (e) { return null; }\n var coords = coordsChar(cm, x, y), line;\n if (forRect && coords.xRel == 1 && (line = getLine(cm.doc, coords.line).text).length == coords.ch) {\n var colDiff = countColumn(line, line.length, cm.options.tabSize) - line.length;\n coords = Pos(coords.line, Math.max(0, Math.round((x - paddingH(cm.display).left) / charWidth(cm.display)) - colDiff));\n }\n return coords;\n }\n\n // A mouse down can be a single click, double click, triple click,\n // start of selection drag, start of text drag, new cursor\n // (ctrl-click), rectangle drag (alt-drag), or xwin\n // middle-click-paste. Or it might be a click on something we should\n // not interfere with, such as a scrollbar or widget.\n function onMouseDown(e) {\n var cm = this, display = cm.display;\n if (signalDOMEvent(cm, e) || display.activeTouch && display.input.supportsTouch()) return;\n display.shift = e.shiftKey;\n\n if (eventInWidget(display, e)) {\n if (!webkit) {\n // Briefly turn off draggability, to allow widgets to do\n // normal dragging things.\n display.scroller.draggable = false;\n setTimeout(function(){display.scroller.draggable = true;}, 100);\n }\n return;\n }\n if (clickInGutter(cm, e)) return;\n var start = posFromMouse(cm, e);\n window.focus();\n\n switch (e_button(e)) {\n case 1:\n // #3261: make sure, that we're not starting a second selection\n if (cm.state.selectingText)\n cm.state.selectingText(e);\n else if (start)\n leftButtonDown(cm, e, start);\n else if (e_target(e) == display.scroller)\n e_preventDefault(e);\n break;\n case 2:\n if (webkit) cm.state.lastMiddleDown = +new Date;\n if (start) extendSelection(cm.doc, start);\n setTimeout(function() {display.input.focus();}, 20);\n e_preventDefault(e);\n break;\n case 3:\n if (captureRightClick) onContextMenu(cm, e);\n else delayBlurEvent(cm);\n break;\n }\n }\n\n var lastClick, lastDoubleClick;\n function leftButtonDown(cm, e, start) {\n if (ie) setTimeout(bind(ensureFocus, cm), 0);\n else cm.curOp.focus = activeElt();\n\n var now = +new Date, type;\n if (lastDoubleClick && lastDoubleClick.time > now - 400 && cmp(lastDoubleClick.pos, start) == 0) {\n type = \"triple\";\n } else if (lastClick && lastClick.time > now - 400 && cmp(lastClick.pos, start) == 0) {\n type = \"double\";\n lastDoubleClick = {time: now, pos: start};\n } else {\n type = \"single\";\n lastClick = {time: now, pos: start};\n }\n\n var sel = cm.doc.sel, modifier = mac ? e.metaKey : e.ctrlKey, contained;\n if (cm.options.dragDrop && dragAndDrop && !cm.isReadOnly() &&\n type == \"single\" && (contained = sel.contains(start)) > -1 &&\n (cmp((contained = sel.ranges[contained]).from(), start) < 0 || start.xRel > 0) &&\n (cmp(contained.to(), start) > 0 || start.xRel < 0))\n leftButtonStartDrag(cm, e, start, modifier);\n else\n leftButtonSelect(cm, e, start, type, modifier);\n }\n\n // Start a text drag. When it ends, see if any dragging actually\n // happen, and treat as a click if it didn't.\n function leftButtonStartDrag(cm, e, start, modifier) {\n var display = cm.display, startTime = +new Date;\n var dragEnd = operation(cm, function(e2) {\n if (webkit) display.scroller.draggable = false;\n cm.state.draggingText = false;\n off(document, \"mouseup\", dragEnd);\n off(display.scroller, \"drop\", dragEnd);\n if (Math.abs(e.clientX - e2.clientX) + Math.abs(e.clientY - e2.clientY) < 10) {\n e_preventDefault(e2);\n if (!modifier && +new Date - 200 < startTime)\n extendSelection(cm.doc, start);\n // Work around unexplainable focus problem in IE9 (#2127) and Chrome (#3081)\n if (webkit || ie && ie_version == 9)\n setTimeout(function() {document.body.focus(); display.input.focus();}, 20);\n else\n display.input.focus();\n }\n });\n // Let the drag handler handle this.\n if (webkit) display.scroller.draggable = true;\n cm.state.draggingText = dragEnd;\n // IE's approach to draggable\n if (display.scroller.dragDrop) display.scroller.dragDrop();\n on(document, \"mouseup\", dragEnd);\n on(display.scroller, \"drop\", dragEnd);\n }\n\n // Normal selection, as opposed to text dragging.\n function leftButtonSelect(cm, e, start, type, addNew) {\n var display = cm.display, doc = cm.doc;\n e_preventDefault(e);\n\n var ourRange, ourIndex, startSel = doc.sel, ranges = startSel.ranges;\n if (addNew && !e.shiftKey) {\n ourIndex = doc.sel.contains(start);\n if (ourIndex > -1)\n ourRange = ranges[ourIndex];\n else\n ourRange = new Range(start, start);\n } else {\n ourRange = doc.sel.primary();\n ourIndex = doc.sel.primIndex;\n }\n\n if (e.altKey) {\n type = \"rect\";\n if (!addNew) ourRange = new Range(start, start);\n start = posFromMouse(cm, e, true, true);\n ourIndex = -1;\n } else if (type == \"double\") {\n var word = cm.findWordAt(start);\n if (cm.display.shift || doc.extend)\n ourRange = extendRange(doc, ourRange, word.anchor, word.head);\n else\n ourRange = word;\n } else if (type == \"triple\") {\n var line = new Range(Pos(start.line, 0), clipPos(doc, Pos(start.line + 1, 0)));\n if (cm.display.shift || doc.extend)\n ourRange = extendRange(doc, ourRange, line.anchor, line.head);\n else\n ourRange = line;\n } else {\n ourRange = extendRange(doc, ourRange, start);\n }\n\n if (!addNew) {\n ourIndex = 0;\n setSelection(doc, new Selection([ourRange], 0), sel_mouse);\n startSel = doc.sel;\n } else if (ourIndex == -1) {\n ourIndex = ranges.length;\n setSelection(doc, normalizeSelection(ranges.concat([ourRange]), ourIndex),\n {scroll: false, origin: \"*mouse\"});\n } else if (ranges.length > 1 && ranges[ourIndex].empty() && type == \"single\" && !e.shiftKey) {\n setSelection(doc, normalizeSelection(ranges.slice(0, ourIndex).concat(ranges.slice(ourIndex + 1)), 0),\n {scroll: false, origin: \"*mouse\"});\n startSel = doc.sel;\n } else {\n replaceOneSelection(doc, ourIndex, ourRange, sel_mouse);\n }\n\n var lastPos = start;\n function extendTo(pos) {\n if (cmp(lastPos, pos) == 0) return;\n lastPos = pos;\n\n if (type == \"rect\") {\n var ranges = [], tabSize = cm.options.tabSize;\n var startCol = countColumn(getLine(doc, start.line).text, start.ch, tabSize);\n var posCol = countColumn(getLine(doc, pos.line).text, pos.ch, tabSize);\n var left = Math.min(startCol, posCol), right = Math.max(startCol, posCol);\n for (var line = Math.min(start.line, pos.line), end = Math.min(cm.lastLine(), Math.max(start.line, pos.line));\n line <= end; line++) {\n var text = getLine(doc, line).text, leftPos = findColumn(text, left, tabSize);\n if (left == right)\n ranges.push(new Range(Pos(line, leftPos), Pos(line, leftPos)));\n else if (text.length > leftPos)\n ranges.push(new Range(Pos(line, leftPos), Pos(line, findColumn(text, right, tabSize))));\n }\n if (!ranges.length) ranges.push(new Range(start, start));\n setSelection(doc, normalizeSelection(startSel.ranges.slice(0, ourIndex).concat(ranges), ourIndex),\n {origin: \"*mouse\", scroll: false});\n cm.scrollIntoView(pos);\n } else {\n var oldRange = ourRange;\n var anchor = oldRange.anchor, head = pos;\n if (type != \"single\") {\n if (type == \"double\")\n var range = cm.findWordAt(pos);\n else\n var range = new Range(Pos(pos.line, 0), clipPos(doc, Pos(pos.line + 1, 0)));\n if (cmp(range.anchor, anchor) > 0) {\n head = range.head;\n anchor = minPos(oldRange.from(), range.anchor);\n } else {\n head = range.anchor;\n anchor = maxPos(oldRange.to(), range.head);\n }\n }\n var ranges = startSel.ranges.slice(0);\n ranges[ourIndex] = new Range(clipPos(doc, anchor), head);\n setSelection(doc, normalizeSelection(ranges, ourIndex), sel_mouse);\n }\n }\n\n var editorSize = display.wrapper.getBoundingClientRect();\n // Used to ensure timeout re-tries don't fire when another extend\n // happened in the meantime (clearTimeout isn't reliable -- at\n // least on Chrome, the timeouts still happen even when cleared,\n // if the clear happens after their scheduled firing time).\n var counter = 0;\n\n function extend(e) {\n var curCount = ++counter;\n var cur = posFromMouse(cm, e, true, type == \"rect\");\n if (!cur) return;\n if (cmp(cur, lastPos) != 0) {\n cm.curOp.focus = activeElt();\n extendTo(cur);\n var visible = visibleLines(display, doc);\n if (cur.line >= visible.to || cur.line < visible.from)\n setTimeout(operation(cm, function(){if (counter == curCount) extend(e);}), 150);\n } else {\n var outside = e.clientY < editorSize.top ? -20 : e.clientY > editorSize.bottom ? 20 : 0;\n if (outside) setTimeout(operation(cm, function() {\n if (counter != curCount) return;\n display.scroller.scrollTop += outside;\n extend(e);\n }), 50);\n }\n }\n\n function done(e) {\n cm.state.selectingText = false;\n counter = Infinity;\n e_preventDefault(e);\n display.input.focus();\n off(document, \"mousemove\", move);\n off(document, \"mouseup\", up);\n doc.history.lastSelOrigin = null;\n }\n\n var move = operation(cm, function(e) {\n if (!e_button(e)) done(e);\n else extend(e);\n });\n var up = operation(cm, done);\n cm.state.selectingText = up;\n on(document, \"mousemove\", move);\n on(document, \"mouseup\", up);\n }\n\n // Determines whether an event happened in the gutter, and fires the\n // handlers for the corresponding event.\n function gutterEvent(cm, e, type, prevent) {\n try { var mX = e.clientX, mY = e.clientY; }\n catch(e) { return false; }\n if (mX >= Math.floor(cm.display.gutters.getBoundingClientRect().right)) return false;\n if (prevent) e_preventDefault(e);\n\n var display = cm.display;\n var lineBox = display.lineDiv.getBoundingClientRect();\n\n if (mY > lineBox.bottom || !hasHandler(cm, type)) return e_defaultPrevented(e);\n mY -= lineBox.top - display.viewOffset;\n\n for (var i = 0; i < cm.options.gutters.length; ++i) {\n var g = display.gutters.childNodes[i];\n if (g && g.getBoundingClientRect().right >= mX) {\n var line = lineAtHeight(cm.doc, mY);\n var gutter = cm.options.gutters[i];\n signal(cm, type, cm, line, gutter, e);\n return e_defaultPrevented(e);\n }\n }\n }\n\n function clickInGutter(cm, e) {\n return gutterEvent(cm, e, \"gutterClick\", true);\n }\n\n // Kludge to work around strange IE behavior where it'll sometimes\n // re-fire a series of drag-related events right after the drop (#1551)\n var lastDrop = 0;\n\n function onDrop(e) {\n var cm = this;\n clearDragCursor(cm);\n if (signalDOMEvent(cm, e) || eventInWidget(cm.display, e))\n return;\n e_preventDefault(e);\n if (ie) lastDrop = +new Date;\n var pos = posFromMouse(cm, e, true), files = e.dataTransfer.files;\n if (!pos || cm.isReadOnly()) return;\n // Might be a file drop, in which case we simply extract the text\n // and insert it.\n if (files && files.length && window.FileReader && window.File) {\n var n = files.length, text = Array(n), read = 0;\n var loadFile = function(file, i) {\n if (cm.options.allowDropFileTypes &&\n indexOf(cm.options.allowDropFileTypes, file.type) == -1)\n return;\n\n var reader = new FileReader;\n reader.onload = operation(cm, function() {\n var content = reader.result;\n if (/[\\x00-\\x08\\x0e-\\x1f]{2}/.test(content)) content = \"\";\n text[i] = content;\n if (++read == n) {\n pos = clipPos(cm.doc, pos);\n var change = {from: pos, to: pos,\n text: cm.doc.splitLines(text.join(cm.doc.lineSeparator())),\n origin: \"paste\"};\n makeChange(cm.doc, change);\n setSelectionReplaceHistory(cm.doc, simpleSelection(pos, changeEnd(change)));\n }\n });\n reader.readAsText(file);\n };\n for (var i = 0; i < n; ++i) loadFile(files[i], i);\n } else { // Normal drop\n // Don't do a replace if the drop happened inside of the selected text.\n if (cm.state.draggingText && cm.doc.sel.contains(pos) > -1) {\n cm.state.draggingText(e);\n // Ensure the editor is re-focused\n setTimeout(function() {cm.display.input.focus();}, 20);\n return;\n }\n try {\n var text = e.dataTransfer.getData(\"Text\");\n if (text) {\n if (cm.state.draggingText && !(mac ? e.altKey : e.ctrlKey))\n var selected = cm.listSelections();\n setSelectionNoUndo(cm.doc, simpleSelection(pos, pos));\n if (selected) for (var i = 0; i < selected.length; ++i)\n replaceRange(cm.doc, \"\", selected[i].anchor, selected[i].head, \"drag\");\n cm.replaceSelection(text, \"around\", \"paste\");\n cm.display.input.focus();\n }\n }\n catch(e){}\n }\n }\n\n function onDragStart(cm, e) {\n if (ie && (!cm.state.draggingText || +new Date - lastDrop < 100)) { e_stop(e); return; }\n if (signalDOMEvent(cm, e) || eventInWidget(cm.display, e)) return;\n\n e.dataTransfer.setData(\"Text\", cm.getSelection());\n\n // Use dummy image instead of default browsers image.\n // Recent Safari (~6.0.2) have a tendency to segfault when this happens, so we don't do it there.\n if (e.dataTransfer.setDragImage && !safari) {\n var img = elt(\"img\", null, null, \"position: fixed; left: 0; top: 0;\");\n img.src = \"data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\";\n if (presto) {\n img.width = img.height = 1;\n cm.display.wrapper.appendChild(img);\n // Force a relayout, or Opera won't use our image for some obscure reason\n img._top = img.offsetTop;\n }\n e.dataTransfer.setDragImage(img, 0, 0);\n if (presto) img.parentNode.removeChild(img);\n }\n }\n\n function onDragOver(cm, e) {\n var pos = posFromMouse(cm, e);\n if (!pos) return;\n var frag = document.createDocumentFragment();\n drawSelectionCursor(cm, pos, frag);\n if (!cm.display.dragCursor) {\n cm.display.dragCursor = elt(\"div\", null, \"CodeMirror-cursors CodeMirror-dragcursors\");\n cm.display.lineSpace.insertBefore(cm.display.dragCursor, cm.display.cursorDiv);\n }\n removeChildrenAndAdd(cm.display.dragCursor, frag);\n }\n\n function clearDragCursor(cm) {\n if (cm.display.dragCursor) {\n cm.display.lineSpace.removeChild(cm.display.dragCursor);\n cm.display.dragCursor = null;\n }\n }\n\n // SCROLL EVENTS\n\n // Sync the scrollable area and scrollbars, ensure the viewport\n // covers the visible area.\n function setScrollTop(cm, val) {\n if (Math.abs(cm.doc.scrollTop - val) < 2) return;\n cm.doc.scrollTop = val;\n if (!gecko) updateDisplaySimple(cm, {top: val});\n if (cm.display.scroller.scrollTop != val) cm.display.scroller.scrollTop = val;\n cm.display.scrollbars.setScrollTop(val);\n if (gecko) updateDisplaySimple(cm);\n startWorker(cm, 100);\n }\n // Sync scroller and scrollbar, ensure the gutter elements are\n // aligned.\n function setScrollLeft(cm, val, isScroller) {\n if (isScroller ? val == cm.doc.scrollLeft : Math.abs(cm.doc.scrollLeft - val) < 2) return;\n val = Math.min(val, cm.display.scroller.scrollWidth - cm.display.scroller.clientWidth);\n cm.doc.scrollLeft = val;\n alignHorizontally(cm);\n if (cm.display.scroller.scrollLeft != val) cm.display.scroller.scrollLeft = val;\n cm.display.scrollbars.setScrollLeft(val);\n }\n\n // Since the delta values reported on mouse wheel events are\n // unstandardized between browsers and even browser versions, and\n // generally horribly unpredictable, this code starts by measuring\n // the scroll effect that the first few mouse wheel events have,\n // and, from that, detects the way it can convert deltas to pixel\n // offsets afterwards.\n //\n // The reason we want to know the amount a wheel event will scroll\n // is that it gives us a chance to update the display before the\n // actual scrolling happens, reducing flickering.\n\n var wheelSamples = 0, wheelPixelsPerUnit = null;\n // Fill in a browser-detected starting value on browsers where we\n // know one. These don't have to be accurate -- the result of them\n // being wrong would just be a slight flicker on the first wheel\n // scroll (if it is large enough).\n if (ie) wheelPixelsPerUnit = -.53;\n else if (gecko) wheelPixelsPerUnit = 15;\n else if (chrome) wheelPixelsPerUnit = -.7;\n else if (safari) wheelPixelsPerUnit = -1/3;\n\n var wheelEventDelta = function(e) {\n var dx = e.wheelDeltaX, dy = e.wheelDeltaY;\n if (dx == null && e.detail && e.axis == e.HORIZONTAL_AXIS) dx = e.detail;\n if (dy == null && e.detail && e.axis == e.VERTICAL_AXIS) dy = e.detail;\n else if (dy == null) dy = e.wheelDelta;\n return {x: dx, y: dy};\n };\n CodeMirror.wheelEventPixels = function(e) {\n var delta = wheelEventDelta(e);\n delta.x *= wheelPixelsPerUnit;\n delta.y *= wheelPixelsPerUnit;\n return delta;\n };\n\n function onScrollWheel(cm, e) {\n var delta = wheelEventDelta(e), dx = delta.x, dy = delta.y;\n\n var display = cm.display, scroll = display.scroller;\n // Quit if there's nothing to scroll here\n var canScrollX = scroll.scrollWidth > scroll.clientWidth;\n var canScrollY = scroll.scrollHeight > scroll.clientHeight;\n if (!(dx && canScrollX || dy && canScrollY)) return;\n\n // Webkit browsers on OS X abort momentum scrolls when the target\n // of the scroll event is removed from the scrollable element.\n // This hack (see related code in patchDisplay) makes sure the\n // element is kept around.\n if (dy && mac && webkit) {\n outer: for (var cur = e.target, view = display.view; cur != scroll; cur = cur.parentNode) {\n for (var i = 0; i < view.length; i++) {\n if (view[i].node == cur) {\n cm.display.currentWheelTarget = cur;\n break outer;\n }\n }\n }\n }\n\n // On some browsers, horizontal scrolling will cause redraws to\n // happen before the gutter has been realigned, causing it to\n // wriggle around in a most unseemly way. When we have an\n // estimated pixels/delta value, we just handle horizontal\n // scrolling entirely here. It'll be slightly off from native, but\n // better than glitching out.\n if (dx && !gecko && !presto && wheelPixelsPerUnit != null) {\n if (dy && canScrollY)\n setScrollTop(cm, Math.max(0, Math.min(scroll.scrollTop + dy * wheelPixelsPerUnit, scroll.scrollHeight - scroll.clientHeight)));\n setScrollLeft(cm, Math.max(0, Math.min(scroll.scrollLeft + dx * wheelPixelsPerUnit, scroll.scrollWidth - scroll.clientWidth)));\n // Only prevent default scrolling if vertical scrolling is\n // actually possible. Otherwise, it causes vertical scroll\n // jitter on OSX trackpads when deltaX is small and deltaY\n // is large (issue #3579)\n if (!dy || (dy && canScrollY))\n e_preventDefault(e);\n display.wheelStartX = null; // Abort measurement, if in progress\n return;\n }\n\n // 'Project' the visible viewport to cover the area that is being\n // scrolled into view (if we know enough to estimate it).\n if (dy && wheelPixelsPerUnit != null) {\n var pixels = dy * wheelPixelsPerUnit;\n var top = cm.doc.scrollTop, bot = top + display.wrapper.clientHeight;\n if (pixels < 0) top = Math.max(0, top + pixels - 50);\n else bot = Math.min(cm.doc.height, bot + pixels + 50);\n updateDisplaySimple(cm, {top: top, bottom: bot});\n }\n\n if (wheelSamples < 20) {\n if (display.wheelStartX == null) {\n display.wheelStartX = scroll.scrollLeft; display.wheelStartY = scroll.scrollTop;\n display.wheelDX = dx; display.wheelDY = dy;\n setTimeout(function() {\n if (display.wheelStartX == null) return;\n var movedX = scroll.scrollLeft - display.wheelStartX;\n var movedY = scroll.scrollTop - display.wheelStartY;\n var sample = (movedY && display.wheelDY && movedY / display.wheelDY) ||\n (movedX && display.wheelDX && movedX / display.wheelDX);\n display.wheelStartX = display.wheelStartY = null;\n if (!sample) return;\n wheelPixelsPerUnit = (wheelPixelsPerUnit * wheelSamples + sample) / (wheelSamples + 1);\n ++wheelSamples;\n }, 200);\n } else {\n display.wheelDX += dx; display.wheelDY += dy;\n }\n }\n }\n\n // KEY EVENTS\n\n // Run a handler that was bound to a key.\n function doHandleBinding(cm, bound, dropShift) {\n if (typeof bound == \"string\") {\n bound = commands[bound];\n if (!bound) return false;\n }\n // Ensure previous input has been read, so that the handler sees a\n // consistent view of the document\n cm.display.input.ensurePolled();\n var prevShift = cm.display.shift, done = false;\n try {\n if (cm.isReadOnly()) cm.state.suppressEdits = true;\n if (dropShift) cm.display.shift = false;\n done = bound(cm) != Pass;\n } finally {\n cm.display.shift = prevShift;\n cm.state.suppressEdits = false;\n }\n return done;\n }\n\n function lookupKeyForEditor(cm, name, handle) {\n for (var i = 0; i < cm.state.keyMaps.length; i++) {\n var result = lookupKey(name, cm.state.keyMaps[i], handle, cm);\n if (result) return result;\n }\n return (cm.options.extraKeys && lookupKey(name, cm.options.extraKeys, handle, cm))\n || lookupKey(name, cm.options.keyMap, handle, cm);\n }\n\n var stopSeq = new Delayed;\n function dispatchKey(cm, name, e, handle) {\n var seq = cm.state.keySeq;\n if (seq) {\n if (isModifierKey(name)) return \"handled\";\n stopSeq.set(50, function() {\n if (cm.state.keySeq == seq) {\n cm.state.keySeq = null;\n cm.display.input.reset();\n }\n });\n name = seq + \" \" + name;\n }\n var result = lookupKeyForEditor(cm, name, handle);\n\n if (result == \"multi\")\n cm.state.keySeq = name;\n if (result == \"handled\")\n signalLater(cm, \"keyHandled\", cm, name, e);\n\n if (result == \"handled\" || result == \"multi\") {\n e_preventDefault(e);\n restartBlink(cm);\n }\n\n if (seq && !result && /\\'$/.test(name)) {\n e_preventDefault(e);\n return true;\n }\n return !!result;\n }\n\n // Handle a key from the keydown event.\n function handleKeyBinding(cm, e) {\n var name = keyName(e, true);\n if (!name) return false;\n\n if (e.shiftKey && !cm.state.keySeq) {\n // First try to resolve full name (including 'Shift-'). Failing\n // that, see if there is a cursor-motion command (starting with\n // 'go') bound to the keyname without 'Shift-'.\n return dispatchKey(cm, \"Shift-\" + name, e, function(b) {return doHandleBinding(cm, b, true);})\n || dispatchKey(cm, name, e, function(b) {\n if (typeof b == \"string\" ? /^go[A-Z]/.test(b) : b.motion)\n return doHandleBinding(cm, b);\n });\n } else {\n return dispatchKey(cm, name, e, function(b) { return doHandleBinding(cm, b); });\n }\n }\n\n // Handle a key from the keypress event\n function handleCharBinding(cm, e, ch) {\n return dispatchKey(cm, \"'\" + ch + \"'\", e,\n function(b) { return doHandleBinding(cm, b, true); });\n }\n\n var lastStoppedKey = null;\n function onKeyDown(e) {\n var cm = this;\n cm.curOp.focus = activeElt();\n if (signalDOMEvent(cm, e)) return;\n // IE does strange things with escape.\n if (ie && ie_version < 11 && e.keyCode == 27) e.returnValue = false;\n var code = e.keyCode;\n cm.display.shift = code == 16 || e.shiftKey;\n var handled = handleKeyBinding(cm, e);\n if (presto) {\n lastStoppedKey = handled ? code : null;\n // Opera has no cut event... we try to at least catch the key combo\n if (!handled && code == 88 && !hasCopyEvent && (mac ? e.metaKey : e.ctrlKey))\n cm.replaceSelection(\"\", null, \"cut\");\n }\n\n // Turn mouse into crosshair when Alt is held on Mac.\n if (code == 18 && !/\\bCodeMirror-crosshair\\b/.test(cm.display.lineDiv.className))\n showCrossHair(cm);\n }\n\n function showCrossHair(cm) {\n var lineDiv = cm.display.lineDiv;\n addClass(lineDiv, \"CodeMirror-crosshair\");\n\n function up(e) {\n if (e.keyCode == 18 || !e.altKey) {\n rmClass(lineDiv, \"CodeMirror-crosshair\");\n off(document, \"keyup\", up);\n off(document, \"mouseover\", up);\n }\n }\n on(document, \"keyup\", up);\n on(document, \"mouseover\", up);\n }\n\n function onKeyUp(e) {\n if (e.keyCode == 16) this.doc.sel.shift = false;\n signalDOMEvent(this, e);\n }\n\n function onKeyPress(e) {\n var cm = this;\n if (eventInWidget(cm.display, e) || signalDOMEvent(cm, e) || e.ctrlKey && !e.altKey || mac && e.metaKey) return;\n var keyCode = e.keyCode, charCode = e.charCode;\n if (presto && keyCode == lastStoppedKey) {lastStoppedKey = null; e_preventDefault(e); return;}\n if ((presto && (!e.which || e.which < 10)) && handleKeyBinding(cm, e)) return;\n var ch = String.fromCharCode(charCode == null ? keyCode : charCode);\n if (handleCharBinding(cm, e, ch)) return;\n cm.display.input.onKeyPress(e);\n }\n\n // FOCUS/BLUR EVENTS\n\n function delayBlurEvent(cm) {\n cm.state.delayingBlurEvent = true;\n setTimeout(function() {\n if (cm.state.delayingBlurEvent) {\n cm.state.delayingBlurEvent = false;\n onBlur(cm);\n }\n }, 100);\n }\n\n function onFocus(cm) {\n if (cm.state.delayingBlurEvent) cm.state.delayingBlurEvent = false;\n\n if (cm.options.readOnly == \"nocursor\") return;\n if (!cm.state.focused) {\n signal(cm, \"focus\", cm);\n cm.state.focused = true;\n addClass(cm.display.wrapper, \"CodeMirror-focused\");\n // This test prevents this from firing when a context\n // menu is closed (since the input reset would kill the\n // select-all detection hack)\n if (!cm.curOp && cm.display.selForContextMenu != cm.doc.sel) {\n cm.display.input.reset();\n if (webkit) setTimeout(function() { cm.display.input.reset(true); }, 20); // Issue #1730\n }\n cm.display.input.receivedFocus();\n }\n restartBlink(cm);\n }\n function onBlur(cm) {\n if (cm.state.delayingBlurEvent) return;\n\n if (cm.state.focused) {\n signal(cm, \"blur\", cm);\n cm.state.focused = false;\n rmClass(cm.display.wrapper, \"CodeMirror-focused\");\n }\n clearInterval(cm.display.blinker);\n setTimeout(function() {if (!cm.state.focused) cm.display.shift = false;}, 150);\n }\n\n // CONTEXT MENU HANDLING\n\n // To make the context menu work, we need to briefly unhide the\n // textarea (making it as unobtrusive as possible) to let the\n // right-click take effect on it.\n function onContextMenu(cm, e) {\n if (eventInWidget(cm.display, e) || contextMenuInGutter(cm, e)) return;\n if (signalDOMEvent(cm, e, \"contextmenu\")) return;\n cm.display.input.onContextMenu(e);\n }\n\n function contextMenuInGutter(cm, e) {\n if (!hasHandler(cm, \"gutterContextMenu\")) return false;\n return gutterEvent(cm, e, \"gutterContextMenu\", false);\n }\n\n // UPDATING\n\n // Compute the position of the end of a change (its 'to' property\n // refers to the pre-change end).\n var changeEnd = CodeMirror.changeEnd = function(change) {\n if (!change.text) return change.to;\n return Pos(change.from.line + change.text.length - 1,\n lst(change.text).length + (change.text.length == 1 ? change.from.ch : 0));\n };\n\n // Adjust a position to refer to the post-change position of the\n // same text, or the end of the change if the change covers it.\n function adjustForChange(pos, change) {\n if (cmp(pos, change.from) < 0) return pos;\n if (cmp(pos, change.to) <= 0) return changeEnd(change);\n\n var line = pos.line + change.text.length - (change.to.line - change.from.line) - 1, ch = pos.ch;\n if (pos.line == change.to.line) ch += changeEnd(change).ch - change.to.ch;\n return Pos(line, ch);\n }\n\n function computeSelAfterChange(doc, change) {\n var out = [];\n for (var i = 0; i < doc.sel.ranges.length; i++) {\n var range = doc.sel.ranges[i];\n out.push(new Range(adjustForChange(range.anchor, change),\n adjustForChange(range.head, change)));\n }\n return normalizeSelection(out, doc.sel.primIndex);\n }\n\n function offsetPos(pos, old, nw) {\n if (pos.line == old.line)\n return Pos(nw.line, pos.ch - old.ch + nw.ch);\n else\n return Pos(nw.line + (pos.line - old.line), pos.ch);\n }\n\n // Used by replaceSelections to allow moving the selection to the\n // start or around the replaced test. Hint may be \"start\" or \"around\".\n function computeReplacedSel(doc, changes, hint) {\n var out = [];\n var oldPrev = Pos(doc.first, 0), newPrev = oldPrev;\n for (var i = 0; i < changes.length; i++) {\n var change = changes[i];\n var from = offsetPos(change.from, oldPrev, newPrev);\n var to = offsetPos(changeEnd(change), oldPrev, newPrev);\n oldPrev = change.to;\n newPrev = to;\n if (hint == \"around\") {\n var range = doc.sel.ranges[i], inv = cmp(range.head, range.anchor) < 0;\n out[i] = new Range(inv ? to : from, inv ? from : to);\n } else {\n out[i] = new Range(from, from);\n }\n }\n return new Selection(out, doc.sel.primIndex);\n }\n\n // Allow \"beforeChange\" event handlers to influence a change\n function filterChange(doc, change, update) {\n var obj = {\n canceled: false,\n from: change.from,\n to: change.to,\n text: change.text,\n origin: change.origin,\n cancel: function() { this.canceled = true; }\n };\n if (update) obj.update = function(from, to, text, origin) {\n if (from) this.from = clipPos(doc, from);\n if (to) this.to = clipPos(doc, to);\n if (text) this.text = text;\n if (origin !== undefined) this.origin = origin;\n };\n signal(doc, \"beforeChange\", doc, obj);\n if (doc.cm) signal(doc.cm, \"beforeChange\", doc.cm, obj);\n\n if (obj.canceled) return null;\n return {from: obj.from, to: obj.to, text: obj.text, origin: obj.origin};\n }\n\n // Apply a change to a document, and add it to the document's\n // history, and propagating it to all linked documents.\n function makeChange(doc, change, ignoreReadOnly) {\n if (doc.cm) {\n if (!doc.cm.curOp) return operation(doc.cm, makeChange)(doc, change, ignoreReadOnly);\n if (doc.cm.state.suppressEdits) return;\n }\n\n if (hasHandler(doc, \"beforeChange\") || doc.cm && hasHandler(doc.cm, \"beforeChange\")) {\n change = filterChange(doc, change, true);\n if (!change) return;\n }\n\n // Possibly split or suppress the update based on the presence\n // of read-only spans in its range.\n var split = sawReadOnlySpans && !ignoreReadOnly && removeReadOnlyRanges(doc, change.from, change.to);\n if (split) {\n for (var i = split.length - 1; i >= 0; --i)\n makeChangeInner(doc, {from: split[i].from, to: split[i].to, text: i ? [\"\"] : change.text});\n } else {\n makeChangeInner(doc, change);\n }\n }\n\n function makeChangeInner(doc, change) {\n if (change.text.length == 1 && change.text[0] == \"\" && cmp(change.from, change.to) == 0) return;\n var selAfter = computeSelAfterChange(doc, change);\n addChangeToHistory(doc, change, selAfter, doc.cm ? doc.cm.curOp.id : NaN);\n\n makeChangeSingleDoc(doc, change, selAfter, stretchSpansOverChange(doc, change));\n var rebased = [];\n\n linkedDocs(doc, function(doc, sharedHist) {\n if (!sharedHist && indexOf(rebased, doc.history) == -1) {\n rebaseHist(doc.history, change);\n rebased.push(doc.history);\n }\n makeChangeSingleDoc(doc, change, null, stretchSpansOverChange(doc, change));\n });\n }\n\n // Revert a change stored in a document's history.\n function makeChangeFromHistory(doc, type, allowSelectionOnly) {\n if (doc.cm && doc.cm.state.suppressEdits) return;\n\n var hist = doc.history, event, selAfter = doc.sel;\n var source = type == \"undo\" ? hist.done : hist.undone, dest = type == \"undo\" ? hist.undone : hist.done;\n\n // Verify that there is a useable event (so that ctrl-z won't\n // needlessly clear selection events)\n for (var i = 0; i < source.length; i++) {\n event = source[i];\n if (allowSelectionOnly ? event.ranges && !event.equals(doc.sel) : !event.ranges)\n break;\n }\n if (i == source.length) return;\n hist.lastOrigin = hist.lastSelOrigin = null;\n\n for (;;) {\n event = source.pop();\n if (event.ranges) {\n pushSelectionToHistory(event, dest);\n if (allowSelectionOnly && !event.equals(doc.sel)) {\n setSelection(doc, event, {clearRedo: false});\n return;\n }\n selAfter = event;\n }\n else break;\n }\n\n // Build up a reverse change object to add to the opposite history\n // stack (redo when undoing, and vice versa).\n var antiChanges = [];\n pushSelectionToHistory(selAfter, dest);\n dest.push({changes: antiChanges, generation: hist.generation});\n hist.generation = event.generation || ++hist.maxGeneration;\n\n var filter = hasHandler(doc, \"beforeChange\") || doc.cm && hasHandler(doc.cm, \"beforeChange\");\n\n for (var i = event.changes.length - 1; i >= 0; --i) {\n var change = event.changes[i];\n change.origin = type;\n if (filter && !filterChange(doc, change, false)) {\n source.length = 0;\n return;\n }\n\n antiChanges.push(historyChangeFromChange(doc, change));\n\n var after = i ? computeSelAfterChange(doc, change) : lst(source);\n makeChangeSingleDoc(doc, change, after, mergeOldSpans(doc, change));\n if (!i && doc.cm) doc.cm.scrollIntoView({from: change.from, to: changeEnd(change)});\n var rebased = [];\n\n // Propagate to the linked documents\n linkedDocs(doc, function(doc, sharedHist) {\n if (!sharedHist && indexOf(rebased, doc.history) == -1) {\n rebaseHist(doc.history, change);\n rebased.push(doc.history);\n }\n makeChangeSingleDoc(doc, change, null, mergeOldSpans(doc, change));\n });\n }\n }\n\n // Sub-views need their line numbers shifted when text is added\n // above or below them in the parent document.\n function shiftDoc(doc, distance) {\n if (distance == 0) return;\n doc.first += distance;\n doc.sel = new Selection(map(doc.sel.ranges, function(range) {\n return new Range(Pos(range.anchor.line + distance, range.anchor.ch),\n Pos(range.head.line + distance, range.head.ch));\n }), doc.sel.primIndex);\n if (doc.cm) {\n regChange(doc.cm, doc.first, doc.first - distance, distance);\n for (var d = doc.cm.display, l = d.viewFrom; l < d.viewTo; l++)\n regLineChange(doc.cm, l, \"gutter\");\n }\n }\n\n // More lower-level change function, handling only a single document\n // (not linked ones).\n function makeChangeSingleDoc(doc, change, selAfter, spans) {\n if (doc.cm && !doc.cm.curOp)\n return operation(doc.cm, makeChangeSingleDoc)(doc, change, selAfter, spans);\n\n if (change.to.line < doc.first) {\n shiftDoc(doc, change.text.length - 1 - (change.to.line - change.from.line));\n return;\n }\n if (change.from.line > doc.lastLine()) return;\n\n // Clip the change to the size of this doc\n if (change.from.line < doc.first) {\n var shift = change.text.length - 1 - (doc.first - change.from.line);\n shiftDoc(doc, shift);\n change = {from: Pos(doc.first, 0), to: Pos(change.to.line + shift, change.to.ch),\n text: [lst(change.text)], origin: change.origin};\n }\n var last = doc.lastLine();\n if (change.to.line > last) {\n change = {from: change.from, to: Pos(last, getLine(doc, last).text.length),\n text: [change.text[0]], origin: change.origin};\n }\n\n change.removed = getBetween(doc, change.from, change.to);\n\n if (!selAfter) selAfter = computeSelAfterChange(doc, change);\n if (doc.cm) makeChangeSingleDocInEditor(doc.cm, change, spans);\n else updateDoc(doc, change, spans);\n setSelectionNoUndo(doc, selAfter, sel_dontScroll);\n }\n\n // Handle the interaction of a change to a document with the editor\n // that this document is part of.\n function makeChangeSingleDocInEditor(cm, change, spans) {\n var doc = cm.doc, display = cm.display, from = change.from, to = change.to;\n\n var recomputeMaxLength = false, checkWidthStart = from.line;\n if (!cm.options.lineWrapping) {\n checkWidthStart = lineNo(visualLine(getLine(doc, from.line)));\n doc.iter(checkWidthStart, to.line + 1, function(line) {\n if (line == display.maxLine) {\n recomputeMaxLength = true;\n return true;\n }\n });\n }\n\n if (doc.sel.contains(change.from, change.to) > -1)\n signalCursorActivity(cm);\n\n updateDoc(doc, change, spans, estimateHeight(cm));\n\n if (!cm.options.lineWrapping) {\n doc.iter(checkWidthStart, from.line + change.text.length, function(line) {\n var len = lineLength(line);\n if (len > display.maxLineLength) {\n display.maxLine = line;\n display.maxLineLength = len;\n display.maxLineChanged = true;\n recomputeMaxLength = false;\n }\n });\n if (recomputeMaxLength) cm.curOp.updateMaxLine = true;\n }\n\n // Adjust frontier, schedule worker\n doc.frontier = Math.min(doc.frontier, from.line);\n startWorker(cm, 400);\n\n var lendiff = change.text.length - (to.line - from.line) - 1;\n // Remember that these lines changed, for updating the display\n if (change.full)\n regChange(cm);\n else if (from.line == to.line && change.text.length == 1 && !isWholeLineUpdate(cm.doc, change))\n regLineChange(cm, from.line, \"text\");\n else\n regChange(cm, from.line, to.line + 1, lendiff);\n\n var changesHandler = hasHandler(cm, \"changes\"), changeHandler = hasHandler(cm, \"change\");\n if (changeHandler || changesHandler) {\n var obj = {\n from: from, to: to,\n text: change.text,\n removed: change.removed,\n origin: change.origin\n };\n if (changeHandler) signalLater(cm, \"change\", cm, obj);\n if (changesHandler) (cm.curOp.changeObjs || (cm.curOp.changeObjs = [])).push(obj);\n }\n cm.display.selForContextMenu = null;\n }\n\n function replaceRange(doc, code, from, to, origin) {\n if (!to) to = from;\n if (cmp(to, from) < 0) { var tmp = to; to = from; from = tmp; }\n if (typeof code == \"string\") code = doc.splitLines(code);\n makeChange(doc, {from: from, to: to, text: code, origin: origin});\n }\n\n // SCROLLING THINGS INTO VIEW\n\n // If an editor sits on the top or bottom of the window, partially\n // scrolled out of view, this ensures that the cursor is visible.\n function maybeScrollWindow(cm, coords) {\n if (signalDOMEvent(cm, \"scrollCursorIntoView\")) return;\n\n var display = cm.display, box = display.sizer.getBoundingClientRect(), doScroll = null;\n if (coords.top + box.top < 0) doScroll = true;\n else if (coords.bottom + box.top > (window.innerHeight || document.documentElement.clientHeight)) doScroll = false;\n if (doScroll != null && !phantom) {\n var scrollNode = elt(\"div\", \"\\u200b\", null, \"position: absolute; top: \" +\n (coords.top - display.viewOffset - paddingTop(cm.display)) + \"px; height: \" +\n (coords.bottom - coords.top + scrollGap(cm) + display.barHeight) + \"px; left: \" +\n coords.left + \"px; width: 2px;\");\n cm.display.lineSpace.appendChild(scrollNode);\n scrollNode.scrollIntoView(doScroll);\n cm.display.lineSpace.removeChild(scrollNode);\n }\n }\n\n // Scroll a given position into view (immediately), verifying that\n // it actually became visible (as line heights are accurately\n // measured, the position of something may 'drift' during drawing).\n function scrollPosIntoView(cm, pos, end, margin) {\n if (margin == null) margin = 0;\n for (var limit = 0; limit < 5; limit++) {\n var changed = false, coords = cursorCoords(cm, pos);\n var endCoords = !end || end == pos ? coords : cursorCoords(cm, end);\n var scrollPos = calculateScrollPos(cm, Math.min(coords.left, endCoords.left),\n Math.min(coords.top, endCoords.top) - margin,\n Math.max(coords.left, endCoords.left),\n Math.max(coords.bottom, endCoords.bottom) + margin);\n var startTop = cm.doc.scrollTop, startLeft = cm.doc.scrollLeft;\n if (scrollPos.scrollTop != null) {\n setScrollTop(cm, scrollPos.scrollTop);\n if (Math.abs(cm.doc.scrollTop - startTop) > 1) changed = true;\n }\n if (scrollPos.scrollLeft != null) {\n setScrollLeft(cm, scrollPos.scrollLeft);\n if (Math.abs(cm.doc.scrollLeft - startLeft) > 1) changed = true;\n }\n if (!changed) break;\n }\n return coords;\n }\n\n // Scroll a given set of coordinates into view (immediately).\n function scrollIntoView(cm, x1, y1, x2, y2) {\n var scrollPos = calculateScrollPos(cm, x1, y1, x2, y2);\n if (scrollPos.scrollTop != null) setScrollTop(cm, scrollPos.scrollTop);\n if (scrollPos.scrollLeft != null) setScrollLeft(cm, scrollPos.scrollLeft);\n }\n\n // Calculate a new scroll position needed to scroll the given\n // rectangle into view. Returns an object with scrollTop and\n // scrollLeft properties. When these are undefined, the\n // vertical/horizontal position does not need to be adjusted.\n function calculateScrollPos(cm, x1, y1, x2, y2) {\n var display = cm.display, snapMargin = textHeight(cm.display);\n if (y1 < 0) y1 = 0;\n var screentop = cm.curOp && cm.curOp.scrollTop != null ? cm.curOp.scrollTop : display.scroller.scrollTop;\n var screen = displayHeight(cm), result = {};\n if (y2 - y1 > screen) y2 = y1 + screen;\n var docBottom = cm.doc.height + paddingVert(display);\n var atTop = y1 < snapMargin, atBottom = y2 > docBottom - snapMargin;\n if (y1 < screentop) {\n result.scrollTop = atTop ? 0 : y1;\n } else if (y2 > screentop + screen) {\n var newTop = Math.min(y1, (atBottom ? docBottom : y2) - screen);\n if (newTop != screentop) result.scrollTop = newTop;\n }\n\n var screenleft = cm.curOp && cm.curOp.scrollLeft != null ? cm.curOp.scrollLeft : display.scroller.scrollLeft;\n var screenw = displayWidth(cm) - (cm.options.fixedGutter ? display.gutters.offsetWidth : 0);\n var tooWide = x2 - x1 > screenw;\n if (tooWide) x2 = x1 + screenw;\n if (x1 < 10)\n result.scrollLeft = 0;\n else if (x1 < screenleft)\n result.scrollLeft = Math.max(0, x1 - (tooWide ? 0 : 10));\n else if (x2 > screenw + screenleft - 3)\n result.scrollLeft = x2 + (tooWide ? 0 : 10) - screenw;\n return result;\n }\n\n // Store a relative adjustment to the scroll position in the current\n // operation (to be applied when the operation finishes).\n function addToScrollPos(cm, left, top) {\n if (left != null || top != null) resolveScrollToPos(cm);\n if (left != null)\n cm.curOp.scrollLeft = (cm.curOp.scrollLeft == null ? cm.doc.scrollLeft : cm.curOp.scrollLeft) + left;\n if (top != null)\n cm.curOp.scrollTop = (cm.curOp.scrollTop == null ? cm.doc.scrollTop : cm.curOp.scrollTop) + top;\n }\n\n // Make sure that at the end of the operation the current cursor is\n // shown.\n function ensureCursorVisible(cm) {\n resolveScrollToPos(cm);\n var cur = cm.getCursor(), from = cur, to = cur;\n if (!cm.options.lineWrapping) {\n from = cur.ch ? Pos(cur.line, cur.ch - 1) : cur;\n to = Pos(cur.line, cur.ch + 1);\n }\n cm.curOp.scrollToPos = {from: from, to: to, margin: cm.options.cursorScrollMargin, isCursor: true};\n }\n\n // When an operation has its scrollToPos property set, and another\n // scroll action is applied before the end of the operation, this\n // 'simulates' scrolling that position into view in a cheap way, so\n // that the effect of intermediate scroll commands is not ignored.\n function resolveScrollToPos(cm) {\n var range = cm.curOp.scrollToPos;\n if (range) {\n cm.curOp.scrollToPos = null;\n var from = estimateCoords(cm, range.from), to = estimateCoords(cm, range.to);\n var sPos = calculateScrollPos(cm, Math.min(from.left, to.left),\n Math.min(from.top, to.top) - range.margin,\n Math.max(from.right, to.right),\n Math.max(from.bottom, to.bottom) + range.margin);\n cm.scrollTo(sPos.scrollLeft, sPos.scrollTop);\n }\n }\n\n // API UTILITIES\n\n // Indent the given line. The how parameter can be \"smart\",\n // \"add\"/null, \"subtract\", or \"prev\". When aggressive is false\n // (typically set to true for forced single-line indents), empty\n // lines are not indented, and places where the mode returns Pass\n // are left alone.\n function indentLine(cm, n, how, aggressive) {\n var doc = cm.doc, state;\n if (how == null) how = \"add\";\n if (how == \"smart\") {\n // Fall back to \"prev\" when the mode doesn't have an indentation\n // method.\n if (!doc.mode.indent) how = \"prev\";\n else state = getStateBefore(cm, n);\n }\n\n var tabSize = cm.options.tabSize;\n var line = getLine(doc, n), curSpace = countColumn(line.text, null, tabSize);\n if (line.stateAfter) line.stateAfter = null;\n var curSpaceString = line.text.match(/^\\s*/)[0], indentation;\n if (!aggressive && !/\\S/.test(line.text)) {\n indentation = 0;\n how = \"not\";\n } else if (how == \"smart\") {\n indentation = doc.mode.indent(state, line.text.slice(curSpaceString.length), line.text);\n if (indentation == Pass || indentation > 150) {\n if (!aggressive) return;\n how = \"prev\";\n }\n }\n if (how == \"prev\") {\n if (n > doc.first) indentation = countColumn(getLine(doc, n-1).text, null, tabSize);\n else indentation = 0;\n } else if (how == \"add\") {\n indentation = curSpace + cm.options.indentUnit;\n } else if (how == \"subtract\") {\n indentation = curSpace - cm.options.indentUnit;\n } else if (typeof how == \"number\") {\n indentation = curSpace + how;\n }\n indentation = Math.max(0, indentation);\n\n var indentString = \"\", pos = 0;\n if (cm.options.indentWithTabs)\n for (var i = Math.floor(indentation / tabSize); i; --i) {pos += tabSize; indentString += \"\\t\";}\n if (pos < indentation) indentString += spaceStr(indentation - pos);\n\n if (indentString != curSpaceString) {\n replaceRange(doc, indentString, Pos(n, 0), Pos(n, curSpaceString.length), \"+input\");\n line.stateAfter = null;\n return true;\n } else {\n // Ensure that, if the cursor was in the whitespace at the start\n // of the line, it is moved to the end of that space.\n for (var i = 0; i < doc.sel.ranges.length; i++) {\n var range = doc.sel.ranges[i];\n if (range.head.line == n && range.head.ch < curSpaceString.length) {\n var pos = Pos(n, curSpaceString.length);\n replaceOneSelection(doc, i, new Range(pos, pos));\n break;\n }\n }\n }\n }\n\n // Utility for applying a change to a line by handle or number,\n // returning the number and optionally registering the line as\n // changed.\n function changeLine(doc, handle, changeType, op) {\n var no = handle, line = handle;\n if (typeof handle == \"number\") line = getLine(doc, clipLine(doc, handle));\n else no = lineNo(handle);\n if (no == null) return null;\n if (op(line, no) && doc.cm) regLineChange(doc.cm, no, changeType);\n return line;\n }\n\n // Helper for deleting text near the selection(s), used to implement\n // backspace, delete, and similar functionality.\n function deleteNearSelection(cm, compute) {\n var ranges = cm.doc.sel.ranges, kill = [];\n // Build up a set of ranges to kill first, merging overlapping\n // ranges.\n for (var i = 0; i < ranges.length; i++) {\n var toKill = compute(ranges[i]);\n while (kill.length && cmp(toKill.from, lst(kill).to) <= 0) {\n var replaced = kill.pop();\n if (cmp(replaced.from, toKill.from) < 0) {\n toKill.from = replaced.from;\n break;\n }\n }\n kill.push(toKill);\n }\n // Next, remove those actual ranges.\n runInOp(cm, function() {\n for (var i = kill.length - 1; i >= 0; i--)\n replaceRange(cm.doc, \"\", kill[i].from, kill[i].to, \"+delete\");\n ensureCursorVisible(cm);\n });\n }\n\n // Used for horizontal relative motion. Dir is -1 or 1 (left or\n // right), unit can be \"char\", \"column\" (like char, but doesn't\n // cross line boundaries), \"word\" (across next word), or \"group\" (to\n // the start of next group of word or non-word-non-whitespace\n // chars). The visually param controls whether, in right-to-left\n // text, direction 1 means to move towards the next index in the\n // string, or towards the character to the right of the current\n // position. The resulting position will have a hitSide=true\n // property if it reached the end of the document.\n function findPosH(doc, pos, dir, unit, visually) {\n var line = pos.line, ch = pos.ch, origDir = dir;\n var lineObj = getLine(doc, line);\n function findNextLine() {\n var l = line + dir;\n if (l < doc.first || l >= doc.first + doc.size) return false\n line = l;\n return lineObj = getLine(doc, l);\n }\n function moveOnce(boundToLine) {\n var next = (visually ? moveVisually : moveLogically)(lineObj, ch, dir, true);\n if (next == null) {\n if (!boundToLine && findNextLine()) {\n if (visually) ch = (dir < 0 ? lineRight : lineLeft)(lineObj);\n else ch = dir < 0 ? lineObj.text.length : 0;\n } else return false\n } else ch = next;\n return true;\n }\n\n if (unit == \"char\") {\n moveOnce()\n } else if (unit == \"column\") {\n moveOnce(true)\n } else if (unit == \"word\" || unit == \"group\") {\n var sawType = null, group = unit == \"group\";\n var helper = doc.cm && doc.cm.getHelper(pos, \"wordChars\");\n for (var first = true;; first = false) {\n if (dir < 0 && !moveOnce(!first)) break;\n var cur = lineObj.text.charAt(ch) || \"\\n\";\n var type = isWordChar(cur, helper) ? \"w\"\n : group && cur == \"\\n\" ? \"n\"\n : !group || /\\s/.test(cur) ? null\n : \"p\";\n if (group && !first && !type) type = \"s\";\n if (sawType && sawType != type) {\n if (dir < 0) {dir = 1; moveOnce();}\n break;\n }\n\n if (type) sawType = type;\n if (dir > 0 && !moveOnce(!first)) break;\n }\n }\n var result = skipAtomic(doc, Pos(line, ch), pos, origDir, true);\n if (!cmp(pos, result)) result.hitSide = true;\n return result;\n }\n\n // For relative vertical movement. Dir may be -1 or 1. Unit can be\n // \"page\" or \"line\". The resulting position will have a hitSide=true\n // property if it reached the end of the document.\n function findPosV(cm, pos, dir, unit) {\n var doc = cm.doc, x = pos.left, y;\n if (unit == \"page\") {\n var pageSize = Math.min(cm.display.wrapper.clientHeight, window.innerHeight || document.documentElement.clientHeight);\n y = pos.top + dir * (pageSize - (dir < 0 ? 1.5 : .5) * textHeight(cm.display));\n } else if (unit == \"line\") {\n y = dir > 0 ? pos.bottom + 3 : pos.top - 3;\n }\n for (;;) {\n var target = coordsChar(cm, x, y);\n if (!target.outside) break;\n if (dir < 0 ? y <= 0 : y >= doc.height) { target.hitSide = true; break; }\n y += dir * 5;\n }\n return target;\n }\n\n // EDITOR METHODS\n\n // The publicly visible API. Note that methodOp(f) means\n // 'wrap f in an operation, performed on its `this` parameter'.\n\n // This is not the complete set of editor methods. Most of the\n // methods defined on the Doc type are also injected into\n // CodeMirror.prototype, for backwards compatibility and\n // convenience.\n\n CodeMirror.prototype = {\n constructor: CodeMirror,\n focus: function(){window.focus(); this.display.input.focus();},\n\n setOption: function(option, value) {\n var options = this.options, old = options[option];\n if (options[option] == value && option != \"mode\") return;\n options[option] = value;\n if (optionHandlers.hasOwnProperty(option))\n operation(this, optionHandlers[option])(this, value, old);\n },\n\n getOption: function(option) {return this.options[option];},\n getDoc: function() {return this.doc;},\n\n addKeyMap: function(map, bottom) {\n this.state.keyMaps[bottom ? \"push\" : \"unshift\"](getKeyMap(map));\n },\n removeKeyMap: function(map) {\n var maps = this.state.keyMaps;\n for (var i = 0; i < maps.length; ++i)\n if (maps[i] == map || maps[i].name == map) {\n maps.splice(i, 1);\n return true;\n }\n },\n\n addOverlay: methodOp(function(spec, options) {\n var mode = spec.token ? spec : CodeMirror.getMode(this.options, spec);\n if (mode.startState) throw new Error(\"Overlays may not be stateful.\");\n this.state.overlays.push({mode: mode, modeSpec: spec, opaque: options && options.opaque});\n this.state.modeGen++;\n regChange(this);\n }),\n removeOverlay: methodOp(function(spec) {\n var overlays = this.state.overlays;\n for (var i = 0; i < overlays.length; ++i) {\n var cur = overlays[i].modeSpec;\n if (cur == spec || typeof spec == \"string\" && cur.name == spec) {\n overlays.splice(i, 1);\n this.state.modeGen++;\n regChange(this);\n return;\n }\n }\n }),\n\n indentLine: methodOp(function(n, dir, aggressive) {\n if (typeof dir != \"string\" && typeof dir != \"number\") {\n if (dir == null) dir = this.options.smartIndent ? \"smart\" : \"prev\";\n else dir = dir ? \"add\" : \"subtract\";\n }\n if (isLine(this.doc, n)) indentLine(this, n, dir, aggressive);\n }),\n indentSelection: methodOp(function(how) {\n var ranges = this.doc.sel.ranges, end = -1;\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n if (!range.empty()) {\n var from = range.from(), to = range.to();\n var start = Math.max(end, from.line);\n end = Math.min(this.lastLine(), to.line - (to.ch ? 0 : 1)) + 1;\n for (var j = start; j < end; ++j)\n indentLine(this, j, how);\n var newRanges = this.doc.sel.ranges;\n if (from.ch == 0 && ranges.length == newRanges.length && newRanges[i].from().ch > 0)\n replaceOneSelection(this.doc, i, new Range(from, newRanges[i].to()), sel_dontScroll);\n } else if (range.head.line > end) {\n indentLine(this, range.head.line, how, true);\n end = range.head.line;\n if (i == this.doc.sel.primIndex) ensureCursorVisible(this);\n }\n }\n }),\n\n // Fetch the parser token for a given character. Useful for hacks\n // that want to inspect the mode state (say, for completion).\n getTokenAt: function(pos, precise) {\n return takeToken(this, pos, precise);\n },\n\n getLineTokens: function(line, precise) {\n return takeToken(this, Pos(line), precise, true);\n },\n\n getTokenTypeAt: function(pos) {\n pos = clipPos(this.doc, pos);\n var styles = getLineStyles(this, getLine(this.doc, pos.line));\n var before = 0, after = (styles.length - 1) / 2, ch = pos.ch;\n var type;\n if (ch == 0) type = styles[2];\n else for (;;) {\n var mid = (before + after) >> 1;\n if ((mid ? styles[mid * 2 - 1] : 0) >= ch) after = mid;\n else if (styles[mid * 2 + 1] < ch) before = mid + 1;\n else { type = styles[mid * 2 + 2]; break; }\n }\n var cut = type ? type.indexOf(\"cm-overlay \") : -1;\n return cut < 0 ? type : cut == 0 ? null : type.slice(0, cut - 1);\n },\n\n getModeAt: function(pos) {\n var mode = this.doc.mode;\n if (!mode.innerMode) return mode;\n return CodeMirror.innerMode(mode, this.getTokenAt(pos).state).mode;\n },\n\n getHelper: function(pos, type) {\n return this.getHelpers(pos, type)[0];\n },\n\n getHelpers: function(pos, type) {\n var found = [];\n if (!helpers.hasOwnProperty(type)) return found;\n var help = helpers[type], mode = this.getModeAt(pos);\n if (typeof mode[type] == \"string\") {\n if (help[mode[type]]) found.push(help[mode[type]]);\n } else if (mode[type]) {\n for (var i = 0; i < mode[type].length; i++) {\n var val = help[mode[type][i]];\n if (val) found.push(val);\n }\n } else if (mode.helperType && help[mode.helperType]) {\n found.push(help[mode.helperType]);\n } else if (help[mode.name]) {\n found.push(help[mode.name]);\n }\n for (var i = 0; i < help._global.length; i++) {\n var cur = help._global[i];\n if (cur.pred(mode, this) && indexOf(found, cur.val) == -1)\n found.push(cur.val);\n }\n return found;\n },\n\n getStateAfter: function(line, precise) {\n var doc = this.doc;\n line = clipLine(doc, line == null ? doc.first + doc.size - 1: line);\n return getStateBefore(this, line + 1, precise);\n },\n\n cursorCoords: function(start, mode) {\n var pos, range = this.doc.sel.primary();\n if (start == null) pos = range.head;\n else if (typeof start == \"object\") pos = clipPos(this.doc, start);\n else pos = start ? range.from() : range.to();\n return cursorCoords(this, pos, mode || \"page\");\n },\n\n charCoords: function(pos, mode) {\n return charCoords(this, clipPos(this.doc, pos), mode || \"page\");\n },\n\n coordsChar: function(coords, mode) {\n coords = fromCoordSystem(this, coords, mode || \"page\");\n return coordsChar(this, coords.left, coords.top);\n },\n\n lineAtHeight: function(height, mode) {\n height = fromCoordSystem(this, {top: height, left: 0}, mode || \"page\").top;\n return lineAtHeight(this.doc, height + this.display.viewOffset);\n },\n heightAtLine: function(line, mode) {\n var end = false, lineObj;\n if (typeof line == \"number\") {\n var last = this.doc.first + this.doc.size - 1;\n if (line < this.doc.first) line = this.doc.first;\n else if (line > last) { line = last; end = true; }\n lineObj = getLine(this.doc, line);\n } else {\n lineObj = line;\n }\n return intoCoordSystem(this, lineObj, {top: 0, left: 0}, mode || \"page\").top +\n (end ? this.doc.height - heightAtLine(lineObj) : 0);\n },\n\n defaultTextHeight: function() { return textHeight(this.display); },\n defaultCharWidth: function() { return charWidth(this.display); },\n\n setGutterMarker: methodOp(function(line, gutterID, value) {\n return changeLine(this.doc, line, \"gutter\", function(line) {\n var markers = line.gutterMarkers || (line.gutterMarkers = {});\n markers[gutterID] = value;\n if (!value && isEmpty(markers)) line.gutterMarkers = null;\n return true;\n });\n }),\n\n clearGutter: methodOp(function(gutterID) {\n var cm = this, doc = cm.doc, i = doc.first;\n doc.iter(function(line) {\n if (line.gutterMarkers && line.gutterMarkers[gutterID]) {\n line.gutterMarkers[gutterID] = null;\n regLineChange(cm, i, \"gutter\");\n if (isEmpty(line.gutterMarkers)) line.gutterMarkers = null;\n }\n ++i;\n });\n }),\n\n lineInfo: function(line) {\n if (typeof line == \"number\") {\n if (!isLine(this.doc, line)) return null;\n var n = line;\n line = getLine(this.doc, line);\n if (!line) return null;\n } else {\n var n = lineNo(line);\n if (n == null) return null;\n }\n return {line: n, handle: line, text: line.text, gutterMarkers: line.gutterMarkers,\n textClass: line.textClass, bgClass: line.bgClass, wrapClass: line.wrapClass,\n widgets: line.widgets};\n },\n\n getViewport: function() { return {from: this.display.viewFrom, to: this.display.viewTo};},\n\n addWidget: function(pos, node, scroll, vert, horiz) {\n var display = this.display;\n pos = cursorCoords(this, clipPos(this.doc, pos));\n var top = pos.bottom, left = pos.left;\n node.style.position = \"absolute\";\n node.setAttribute(\"cm-ignore-events\", \"true\");\n this.display.input.setUneditable(node);\n display.sizer.appendChild(node);\n if (vert == \"over\") {\n top = pos.top;\n } else if (vert == \"above\" || vert == \"near\") {\n var vspace = Math.max(display.wrapper.clientHeight, this.doc.height),\n hspace = Math.max(display.sizer.clientWidth, display.lineSpace.clientWidth);\n // Default to positioning above (if specified and possible); otherwise default to positioning below\n if ((vert == 'above' || pos.bottom + node.offsetHeight > vspace) && pos.top > node.offsetHeight)\n top = pos.top - node.offsetHeight;\n else if (pos.bottom + node.offsetHeight <= vspace)\n top = pos.bottom;\n if (left + node.offsetWidth > hspace)\n left = hspace - node.offsetWidth;\n }\n node.style.top = top + \"px\";\n node.style.left = node.style.right = \"\";\n if (horiz == \"right\") {\n left = display.sizer.clientWidth - node.offsetWidth;\n node.style.right = \"0px\";\n } else {\n if (horiz == \"left\") left = 0;\n else if (horiz == \"middle\") left = (display.sizer.clientWidth - node.offsetWidth) / 2;\n node.style.left = left + \"px\";\n }\n if (scroll)\n scrollIntoView(this, left, top, left + node.offsetWidth, top + node.offsetHeight);\n },\n\n triggerOnKeyDown: methodOp(onKeyDown),\n triggerOnKeyPress: methodOp(onKeyPress),\n triggerOnKeyUp: onKeyUp,\n\n execCommand: function(cmd) {\n if (commands.hasOwnProperty(cmd))\n return commands[cmd].call(null, this);\n },\n\n triggerElectric: methodOp(function(text) { triggerElectric(this, text); }),\n\n findPosH: function(from, amount, unit, visually) {\n var dir = 1;\n if (amount < 0) { dir = -1; amount = -amount; }\n for (var i = 0, cur = clipPos(this.doc, from); i < amount; ++i) {\n cur = findPosH(this.doc, cur, dir, unit, visually);\n if (cur.hitSide) break;\n }\n return cur;\n },\n\n moveH: methodOp(function(dir, unit) {\n var cm = this;\n cm.extendSelectionsBy(function(range) {\n if (cm.display.shift || cm.doc.extend || range.empty())\n return findPosH(cm.doc, range.head, dir, unit, cm.options.rtlMoveVisually);\n else\n return dir < 0 ? range.from() : range.to();\n }, sel_move);\n }),\n\n deleteH: methodOp(function(dir, unit) {\n var sel = this.doc.sel, doc = this.doc;\n if (sel.somethingSelected())\n doc.replaceSelection(\"\", null, \"+delete\");\n else\n deleteNearSelection(this, function(range) {\n var other = findPosH(doc, range.head, dir, unit, false);\n return dir < 0 ? {from: other, to: range.head} : {from: range.head, to: other};\n });\n }),\n\n findPosV: function(from, amount, unit, goalColumn) {\n var dir = 1, x = goalColumn;\n if (amount < 0) { dir = -1; amount = -amount; }\n for (var i = 0, cur = clipPos(this.doc, from); i < amount; ++i) {\n var coords = cursorCoords(this, cur, \"div\");\n if (x == null) x = coords.left;\n else coords.left = x;\n cur = findPosV(this, coords, dir, unit);\n if (cur.hitSide) break;\n }\n return cur;\n },\n\n moveV: methodOp(function(dir, unit) {\n var cm = this, doc = this.doc, goals = [];\n var collapse = !cm.display.shift && !doc.extend && doc.sel.somethingSelected();\n doc.extendSelectionsBy(function(range) {\n if (collapse)\n return dir < 0 ? range.from() : range.to();\n var headPos = cursorCoords(cm, range.head, \"div\");\n if (range.goalColumn != null) headPos.left = range.goalColumn;\n goals.push(headPos.left);\n var pos = findPosV(cm, headPos, dir, unit);\n if (unit == \"page\" && range == doc.sel.primary())\n addToScrollPos(cm, null, charCoords(cm, pos, \"div\").top - headPos.top);\n return pos;\n }, sel_move);\n if (goals.length) for (var i = 0; i < doc.sel.ranges.length; i++)\n doc.sel.ranges[i].goalColumn = goals[i];\n }),\n\n // Find the word at the given position (as returned by coordsChar).\n findWordAt: function(pos) {\n var doc = this.doc, line = getLine(doc, pos.line).text;\n var start = pos.ch, end = pos.ch;\n if (line) {\n var helper = this.getHelper(pos, \"wordChars\");\n if ((pos.xRel < 0 || end == line.length) && start) --start; else ++end;\n var startChar = line.charAt(start);\n var check = isWordChar(startChar, helper)\n ? function(ch) { return isWordChar(ch, helper); }\n : /\\s/.test(startChar) ? function(ch) {return /\\s/.test(ch);}\n : function(ch) {return !/\\s/.test(ch) && !isWordChar(ch);};\n while (start > 0 && check(line.charAt(start - 1))) --start;\n while (end < line.length && check(line.charAt(end))) ++end;\n }\n return new Range(Pos(pos.line, start), Pos(pos.line, end));\n },\n\n toggleOverwrite: function(value) {\n if (value != null && value == this.state.overwrite) return;\n if (this.state.overwrite = !this.state.overwrite)\n addClass(this.display.cursorDiv, \"CodeMirror-overwrite\");\n else\n rmClass(this.display.cursorDiv, \"CodeMirror-overwrite\");\n\n signal(this, \"overwriteToggle\", this, this.state.overwrite);\n },\n hasFocus: function() { return this.display.input.getField() == activeElt(); },\n isReadOnly: function() { return !!(this.options.readOnly || this.doc.cantEdit); },\n\n scrollTo: methodOp(function(x, y) {\n if (x != null || y != null) resolveScrollToPos(this);\n if (x != null) this.curOp.scrollLeft = x;\n if (y != null) this.curOp.scrollTop = y;\n }),\n getScrollInfo: function() {\n var scroller = this.display.scroller;\n return {left: scroller.scrollLeft, top: scroller.scrollTop,\n height: scroller.scrollHeight - scrollGap(this) - this.display.barHeight,\n width: scroller.scrollWidth - scrollGap(this) - this.display.barWidth,\n clientHeight: displayHeight(this), clientWidth: displayWidth(this)};\n },\n\n scrollIntoView: methodOp(function(range, margin) {\n if (range == null) {\n range = {from: this.doc.sel.primary().head, to: null};\n if (margin == null) margin = this.options.cursorScrollMargin;\n } else if (typeof range == \"number\") {\n range = {from: Pos(range, 0), to: null};\n } else if (range.from == null) {\n range = {from: range, to: null};\n }\n if (!range.to) range.to = range.from;\n range.margin = margin || 0;\n\n if (range.from.line != null) {\n resolveScrollToPos(this);\n this.curOp.scrollToPos = range;\n } else {\n var sPos = calculateScrollPos(this, Math.min(range.from.left, range.to.left),\n Math.min(range.from.top, range.to.top) - range.margin,\n Math.max(range.from.right, range.to.right),\n Math.max(range.from.bottom, range.to.bottom) + range.margin);\n this.scrollTo(sPos.scrollLeft, sPos.scrollTop);\n }\n }),\n\n setSize: methodOp(function(width, height) {\n var cm = this;\n function interpret(val) {\n return typeof val == \"number\" || /^\\d+$/.test(String(val)) ? val + \"px\" : val;\n }\n if (width != null) cm.display.wrapper.style.width = interpret(width);\n if (height != null) cm.display.wrapper.style.height = interpret(height);\n if (cm.options.lineWrapping) clearLineMeasurementCache(this);\n var lineNo = cm.display.viewFrom;\n cm.doc.iter(lineNo, cm.display.viewTo, function(line) {\n if (line.widgets) for (var i = 0; i < line.widgets.length; i++)\n if (line.widgets[i].noHScroll) { regLineChange(cm, lineNo, \"widget\"); break; }\n ++lineNo;\n });\n cm.curOp.forceUpdate = true;\n signal(cm, \"refresh\", this);\n }),\n\n operation: function(f){return runInOp(this, f);},\n\n refresh: methodOp(function() {\n var oldHeight = this.display.cachedTextHeight;\n regChange(this);\n this.curOp.forceUpdate = true;\n clearCaches(this);\n this.scrollTo(this.doc.scrollLeft, this.doc.scrollTop);\n updateGutterSpace(this);\n if (oldHeight == null || Math.abs(oldHeight - textHeight(this.display)) > .5)\n estimateLineHeights(this);\n signal(this, \"refresh\", this);\n }),\n\n swapDoc: methodOp(function(doc) {\n var old = this.doc;\n old.cm = null;\n attachDoc(this, doc);\n clearCaches(this);\n this.display.input.reset();\n this.scrollTo(doc.scrollLeft, doc.scrollTop);\n this.curOp.forceScroll = true;\n signalLater(this, \"swapDoc\", this, old);\n return old;\n }),\n\n getInputField: function(){return this.display.input.getField();},\n getWrapperElement: function(){return this.display.wrapper;},\n getScrollerElement: function(){return this.display.scroller;},\n getGutterElement: function(){return this.display.gutters;}\n };\n eventMixin(CodeMirror);\n\n // OPTION DEFAULTS\n\n // The default configuration options.\n var defaults = CodeMirror.defaults = {};\n // Functions to run when options are changed.\n var optionHandlers = CodeMirror.optionHandlers = {};\n\n function option(name, deflt, handle, notOnInit) {\n CodeMirror.defaults[name] = deflt;\n if (handle) optionHandlers[name] =\n notOnInit ? function(cm, val, old) {if (old != Init) handle(cm, val, old);} : handle;\n }\n\n // Passed to option handlers when there is no old value.\n var Init = CodeMirror.Init = {toString: function(){return \"CodeMirror.Init\";}};\n\n // These two are, on init, called from the constructor because they\n // have to be initialized before the editor can start at all.\n option(\"value\", \"\", function(cm, val) {\n cm.setValue(val);\n }, true);\n option(\"mode\", null, function(cm, val) {\n cm.doc.modeOption = val;\n loadMode(cm);\n }, true);\n\n option(\"indentUnit\", 2, loadMode, true);\n option(\"indentWithTabs\", false);\n option(\"smartIndent\", true);\n option(\"tabSize\", 4, function(cm) {\n resetModeState(cm);\n clearCaches(cm);\n regChange(cm);\n }, true);\n option(\"lineSeparator\", null, function(cm, val) {\n cm.doc.lineSep = val;\n if (!val) return;\n var newBreaks = [], lineNo = cm.doc.first;\n cm.doc.iter(function(line) {\n for (var pos = 0;;) {\n var found = line.text.indexOf(val, pos);\n if (found == -1) break;\n pos = found + val.length;\n newBreaks.push(Pos(lineNo, found));\n }\n lineNo++;\n });\n for (var i = newBreaks.length - 1; i >= 0; i--)\n replaceRange(cm.doc, val, newBreaks[i], Pos(newBreaks[i].line, newBreaks[i].ch + val.length))\n });\n option(\"specialChars\", /[\\t\\u0000-\\u0019\\u00ad\\u200b-\\u200f\\u2028\\u2029\\ufeff]/g, function(cm, val, old) {\n cm.state.specialChars = new RegExp(val.source + (val.test(\"\\t\") ? \"\" : \"|\\t\"), \"g\");\n if (old != CodeMirror.Init) cm.refresh();\n });\n option(\"specialCharPlaceholder\", defaultSpecialCharPlaceholder, function(cm) {cm.refresh();}, true);\n option(\"electricChars\", true);\n option(\"inputStyle\", mobile ? \"contenteditable\" : \"textarea\", function() {\n throw new Error(\"inputStyle can not (yet) be changed in a running editor\"); // FIXME\n }, true);\n option(\"rtlMoveVisually\", !windows);\n option(\"wholeLineUpdateBefore\", true);\n\n option(\"theme\", \"default\", function(cm) {\n themeChanged(cm);\n guttersChanged(cm);\n }, true);\n option(\"keyMap\", \"default\", function(cm, val, old) {\n var next = getKeyMap(val);\n var prev = old != CodeMirror.Init && getKeyMap(old);\n if (prev && prev.detach) prev.detach(cm, next);\n if (next.attach) next.attach(cm, prev || null);\n });\n option(\"extraKeys\", null);\n\n option(\"lineWrapping\", false, wrappingChanged, true);\n option(\"gutters\", [], function(cm) {\n setGuttersForLineNumbers(cm.options);\n guttersChanged(cm);\n }, true);\n option(\"fixedGutter\", true, function(cm, val) {\n cm.display.gutters.style.left = val ? compensateForHScroll(cm.display) + \"px\" : \"0\";\n cm.refresh();\n }, true);\n option(\"coverGutterNextToScrollbar\", false, function(cm) {updateScrollbars(cm);}, true);\n option(\"scrollbarStyle\", \"native\", function(cm) {\n initScrollbars(cm);\n updateScrollbars(cm);\n cm.display.scrollbars.setScrollTop(cm.doc.scrollTop);\n cm.display.scrollbars.setScrollLeft(cm.doc.scrollLeft);\n }, true);\n option(\"lineNumbers\", false, function(cm) {\n setGuttersForLineNumbers(cm.options);\n guttersChanged(cm);\n }, true);\n option(\"firstLineNumber\", 1, guttersChanged, true);\n option(\"lineNumberFormatter\", function(integer) {return integer;}, guttersChanged, true);\n option(\"showCursorWhenSelecting\", false, updateSelection, true);\n\n option(\"resetSelectionOnContextMenu\", true);\n option(\"lineWiseCopyCut\", true);\n\n option(\"readOnly\", false, function(cm, val) {\n if (val == \"nocursor\") {\n onBlur(cm);\n cm.display.input.blur();\n cm.display.disabled = true;\n } else {\n cm.display.disabled = false;\n }\n cm.display.input.readOnlyChanged(val)\n });\n option(\"disableInput\", false, function(cm, val) {if (!val) cm.display.input.reset();}, true);\n option(\"dragDrop\", true, dragDropChanged);\n option(\"allowDropFileTypes\", null);\n\n option(\"cursorBlinkRate\", 530);\n option(\"cursorScrollMargin\", 0);\n option(\"cursorHeight\", 1, updateSelection, true);\n option(\"singleCursorHeightPerLine\", true, updateSelection, true);\n option(\"workTime\", 100);\n option(\"workDelay\", 100);\n option(\"flattenSpans\", true, resetModeState, true);\n option(\"addModeClass\", false, resetModeState, true);\n option(\"pollInterval\", 100);\n option(\"undoDepth\", 200, function(cm, val){cm.doc.history.undoDepth = val;});\n option(\"historyEventDelay\", 1250);\n option(\"viewportMargin\", 10, function(cm){cm.refresh();}, true);\n option(\"maxHighlightLength\", 10000, resetModeState, true);\n option(\"moveInputWithCursor\", true, function(cm, val) {\n if (!val) cm.display.input.resetPosition();\n });\n\n option(\"tabindex\", null, function(cm, val) {\n cm.display.input.getField().tabIndex = val || \"\";\n });\n option(\"autofocus\", null);\n\n // MODE DEFINITION AND QUERYING\n\n // Known modes, by name and by MIME\n var modes = CodeMirror.modes = {}, mimeModes = CodeMirror.mimeModes = {};\n\n // Extra arguments are stored as the mode's dependencies, which is\n // used by (legacy) mechanisms like loadmode.js to automatically\n // load a mode. (Preferred mechanism is the require/define calls.)\n CodeMirror.defineMode = function(name, mode) {\n if (!CodeMirror.defaults.mode && name != \"null\") CodeMirror.defaults.mode = name;\n if (arguments.length > 2)\n mode.dependencies = Array.prototype.slice.call(arguments, 2);\n modes[name] = mode;\n };\n\n CodeMirror.defineMIME = function(mime, spec) {\n mimeModes[mime] = spec;\n };\n\n // Given a MIME type, a {name, ...options} config object, or a name\n // string, return a mode config object.\n CodeMirror.resolveMode = function(spec) {\n if (typeof spec == \"string\" && mimeModes.hasOwnProperty(spec)) {\n spec = mimeModes[spec];\n } else if (spec && typeof spec.name == \"string\" && mimeModes.hasOwnProperty(spec.name)) {\n var found = mimeModes[spec.name];\n if (typeof found == \"string\") found = {name: found};\n spec = createObj(found, spec);\n spec.name = found.name;\n } else if (typeof spec == \"string\" && /^[\\w\\-]+\\/[\\w\\-]+\\+xml$/.test(spec)) {\n return CodeMirror.resolveMode(\"application/xml\");\n }\n if (typeof spec == \"string\") return {name: spec};\n else return spec || {name: \"null\"};\n };\n\n // Given a mode spec (anything that resolveMode accepts), find and\n // initialize an actual mode object.\n CodeMirror.getMode = function(options, spec) {\n var spec = CodeMirror.resolveMode(spec);\n var mfactory = modes[spec.name];\n if (!mfactory) return CodeMirror.getMode(options, \"text/plain\");\n var modeObj = mfactory(options, spec);\n if (modeExtensions.hasOwnProperty(spec.name)) {\n var exts = modeExtensions[spec.name];\n for (var prop in exts) {\n if (!exts.hasOwnProperty(prop)) continue;\n if (modeObj.hasOwnProperty(prop)) modeObj[\"_\" + prop] = modeObj[prop];\n modeObj[prop] = exts[prop];\n }\n }\n modeObj.name = spec.name;\n if (spec.helperType) modeObj.helperType = spec.helperType;\n if (spec.modeProps) for (var prop in spec.modeProps)\n modeObj[prop] = spec.modeProps[prop];\n\n return modeObj;\n };\n\n // Minimal default mode.\n CodeMirror.defineMode(\"null\", function() {\n return {token: function(stream) {stream.skipToEnd();}};\n });\n CodeMirror.defineMIME(\"text/plain\", \"null\");\n\n // This can be used to attach properties to mode objects from\n // outside the actual mode definition.\n var modeExtensions = CodeMirror.modeExtensions = {};\n CodeMirror.extendMode = function(mode, properties) {\n var exts = modeExtensions.hasOwnProperty(mode) ? modeExtensions[mode] : (modeExtensions[mode] = {});\n copyObj(properties, exts);\n };\n\n // EXTENSIONS\n\n CodeMirror.defineExtension = function(name, func) {\n CodeMirror.prototype[name] = func;\n };\n CodeMirror.defineDocExtension = function(name, func) {\n Doc.prototype[name] = func;\n };\n CodeMirror.defineOption = option;\n\n var initHooks = [];\n CodeMirror.defineInitHook = function(f) {initHooks.push(f);};\n\n var helpers = CodeMirror.helpers = {};\n CodeMirror.registerHelper = function(type, name, value) {\n if (!helpers.hasOwnProperty(type)) helpers[type] = CodeMirror[type] = {_global: []};\n helpers[type][name] = value;\n };\n CodeMirror.registerGlobalHelper = function(type, name, predicate, value) {\n CodeMirror.registerHelper(type, name, value);\n helpers[type]._global.push({pred: predicate, val: value});\n };\n\n // MODE STATE HANDLING\n\n // Utility functions for working with state. Exported because nested\n // modes need to do this for their inner modes.\n\n var copyState = CodeMirror.copyState = function(mode, state) {\n if (state === true) return state;\n if (mode.copyState) return mode.copyState(state);\n var nstate = {};\n for (var n in state) {\n var val = state[n];\n if (val instanceof Array) val = val.concat([]);\n nstate[n] = val;\n }\n return nstate;\n };\n\n var startState = CodeMirror.startState = function(mode, a1, a2) {\n return mode.startState ? mode.startState(a1, a2) : true;\n };\n\n // Given a mode and a state (for that mode), find the inner mode and\n // state at the position that the state refers to.\n CodeMirror.innerMode = function(mode, state) {\n while (mode.innerMode) {\n var info = mode.innerMode(state);\n if (!info || info.mode == mode) break;\n state = info.state;\n mode = info.mode;\n }\n return info || {mode: mode, state: state};\n };\n\n // STANDARD COMMANDS\n\n // Commands are parameter-less actions that can be performed on an\n // editor, mostly used for keybindings.\n var commands = CodeMirror.commands = {\n selectAll: function(cm) {cm.setSelection(Pos(cm.firstLine(), 0), Pos(cm.lastLine()), sel_dontScroll);},\n singleSelection: function(cm) {\n cm.setSelection(cm.getCursor(\"anchor\"), cm.getCursor(\"head\"), sel_dontScroll);\n },\n killLine: function(cm) {\n deleteNearSelection(cm, function(range) {\n if (range.empty()) {\n var len = getLine(cm.doc, range.head.line).text.length;\n if (range.head.ch == len && range.head.line < cm.lastLine())\n return {from: range.head, to: Pos(range.head.line + 1, 0)};\n else\n return {from: range.head, to: Pos(range.head.line, len)};\n } else {\n return {from: range.from(), to: range.to()};\n }\n });\n },\n deleteLine: function(cm) {\n deleteNearSelection(cm, function(range) {\n return {from: Pos(range.from().line, 0),\n to: clipPos(cm.doc, Pos(range.to().line + 1, 0))};\n });\n },\n delLineLeft: function(cm) {\n deleteNearSelection(cm, function(range) {\n return {from: Pos(range.from().line, 0), to: range.from()};\n });\n },\n delWrappedLineLeft: function(cm) {\n deleteNearSelection(cm, function(range) {\n var top = cm.charCoords(range.head, \"div\").top + 5;\n var leftPos = cm.coordsChar({left: 0, top: top}, \"div\");\n return {from: leftPos, to: range.from()};\n });\n },\n delWrappedLineRight: function(cm) {\n deleteNearSelection(cm, function(range) {\n var top = cm.charCoords(range.head, \"div\").top + 5;\n var rightPos = cm.coordsChar({left: cm.display.lineDiv.offsetWidth + 100, top: top}, \"div\");\n return {from: range.from(), to: rightPos };\n });\n },\n undo: function(cm) {cm.undo();},\n redo: function(cm) {cm.redo();},\n undoSelection: function(cm) {cm.undoSelection();},\n redoSelection: function(cm) {cm.redoSelection();},\n goDocStart: function(cm) {cm.extendSelection(Pos(cm.firstLine(), 0));},\n goDocEnd: function(cm) {cm.extendSelection(Pos(cm.lastLine()));},\n goLineStart: function(cm) {\n cm.extendSelectionsBy(function(range) { return lineStart(cm, range.head.line); },\n {origin: \"+move\", bias: 1});\n },\n goLineStartSmart: function(cm) {\n cm.extendSelectionsBy(function(range) {\n return lineStartSmart(cm, range.head);\n }, {origin: \"+move\", bias: 1});\n },\n goLineEnd: function(cm) {\n cm.extendSelectionsBy(function(range) { return lineEnd(cm, range.head.line); },\n {origin: \"+move\", bias: -1});\n },\n goLineRight: function(cm) {\n cm.extendSelectionsBy(function(range) {\n var top = cm.charCoords(range.head, \"div\").top + 5;\n return cm.coordsChar({left: cm.display.lineDiv.offsetWidth + 100, top: top}, \"div\");\n }, sel_move);\n },\n goLineLeft: function(cm) {\n cm.extendSelectionsBy(function(range) {\n var top = cm.charCoords(range.head, \"div\").top + 5;\n return cm.coordsChar({left: 0, top: top}, \"div\");\n }, sel_move);\n },\n goLineLeftSmart: function(cm) {\n cm.extendSelectionsBy(function(range) {\n var top = cm.charCoords(range.head, \"div\").top + 5;\n var pos = cm.coordsChar({left: 0, top: top}, \"div\");\n if (pos.ch < cm.getLine(pos.line).search(/\\S/)) return lineStartSmart(cm, range.head);\n return pos;\n }, sel_move);\n },\n goLineUp: function(cm) {cm.moveV(-1, \"line\");},\n goLineDown: function(cm) {cm.moveV(1, \"line\");},\n goPageUp: function(cm) {cm.moveV(-1, \"page\");},\n goPageDown: function(cm) {cm.moveV(1, \"page\");},\n goCharLeft: function(cm) {cm.moveH(-1, \"char\");},\n goCharRight: function(cm) {cm.moveH(1, \"char\");},\n goColumnLeft: function(cm) {cm.moveH(-1, \"column\");},\n goColumnRight: function(cm) {cm.moveH(1, \"column\");},\n goWordLeft: function(cm) {cm.moveH(-1, \"word\");},\n goGroupRight: function(cm) {cm.moveH(1, \"group\");},\n goGroupLeft: function(cm) {cm.moveH(-1, \"group\");},\n goWordRight: function(cm) {cm.moveH(1, \"word\");},\n delCharBefore: function(cm) {cm.deleteH(-1, \"char\");},\n delCharAfter: function(cm) {cm.deleteH(1, \"char\");},\n delWordBefore: function(cm) {cm.deleteH(-1, \"word\");},\n delWordAfter: function(cm) {cm.deleteH(1, \"word\");},\n delGroupBefore: function(cm) {cm.deleteH(-1, \"group\");},\n delGroupAfter: function(cm) {cm.deleteH(1, \"group\");},\n indentAuto: function(cm) {cm.indentSelection(\"smart\");},\n indentMore: function(cm) {cm.indentSelection(\"add\");},\n indentLess: function(cm) {cm.indentSelection(\"subtract\");},\n insertTab: function(cm) {cm.replaceSelection(\"\\t\");},\n insertSoftTab: function(cm) {\n var spaces = [], ranges = cm.listSelections(), tabSize = cm.options.tabSize;\n for (var i = 0; i < ranges.length; i++) {\n var pos = ranges[i].from();\n var col = countColumn(cm.getLine(pos.line), pos.ch, tabSize);\n spaces.push(new Array(tabSize - col % tabSize + 1).join(\" \"));\n }\n cm.replaceSelections(spaces);\n },\n defaultTab: function(cm) {\n if (cm.somethingSelected()) cm.indentSelection(\"add\");\n else cm.execCommand(\"insertTab\");\n },\n transposeChars: function(cm) {\n runInOp(cm, function() {\n var ranges = cm.listSelections(), newSel = [];\n for (var i = 0; i < ranges.length; i++) {\n var cur = ranges[i].head, line = getLine(cm.doc, cur.line).text;\n if (line) {\n if (cur.ch == line.length) cur = new Pos(cur.line, cur.ch - 1);\n if (cur.ch > 0) {\n cur = new Pos(cur.line, cur.ch + 1);\n cm.replaceRange(line.charAt(cur.ch - 1) + line.charAt(cur.ch - 2),\n Pos(cur.line, cur.ch - 2), cur, \"+transpose\");\n } else if (cur.line > cm.doc.first) {\n var prev = getLine(cm.doc, cur.line - 1).text;\n if (prev)\n cm.replaceRange(line.charAt(0) + cm.doc.lineSeparator() +\n prev.charAt(prev.length - 1),\n Pos(cur.line - 1, prev.length - 1), Pos(cur.line, 1), \"+transpose\");\n }\n }\n newSel.push(new Range(cur, cur));\n }\n cm.setSelections(newSel);\n });\n },\n newlineAndIndent: function(cm) {\n runInOp(cm, function() {\n var len = cm.listSelections().length;\n for (var i = 0; i < len; i++) {\n var range = cm.listSelections()[i];\n cm.replaceRange(cm.doc.lineSeparator(), range.anchor, range.head, \"+input\");\n cm.indentLine(range.from().line + 1, null, true);\n }\n ensureCursorVisible(cm);\n });\n },\n toggleOverwrite: function(cm) {cm.toggleOverwrite();}\n };\n\n\n // STANDARD KEYMAPS\n\n var keyMap = CodeMirror.keyMap = {};\n\n keyMap.basic = {\n \"Left\": \"goCharLeft\", \"Right\": \"goCharRight\", \"Up\": \"goLineUp\", \"Down\": \"goLineDown\",\n \"End\": \"goLineEnd\", \"Home\": \"goLineStartSmart\", \"PageUp\": \"goPageUp\", \"PageDown\": \"goPageDown\",\n \"Delete\": \"delCharAfter\", \"Backspace\": \"delCharBefore\", \"Shift-Backspace\": \"delCharBefore\",\n \"Tab\": \"defaultTab\", \"Shift-Tab\": \"indentAuto\",\n \"Enter\": \"newlineAndIndent\", \"Insert\": \"toggleOverwrite\",\n \"Esc\": \"singleSelection\"\n };\n // Note that the save and find-related commands aren't defined by\n // default. User code or addons can define them. Unknown commands\n // are simply ignored.\n keyMap.pcDefault = {\n \"Ctrl-A\": \"selectAll\", \"Ctrl-D\": \"deleteLine\", \"Ctrl-Z\": \"undo\", \"Shift-Ctrl-Z\": \"redo\", \"Ctrl-Y\": \"redo\",\n \"Ctrl-Home\": \"goDocStart\", \"Ctrl-End\": \"goDocEnd\", \"Ctrl-Up\": \"goLineUp\", \"Ctrl-Down\": \"goLineDown\",\n \"Ctrl-Left\": \"goGroupLeft\", \"Ctrl-Right\": \"goGroupRight\", \"Alt-Left\": \"goLineStart\", \"Alt-Right\": \"goLineEnd\",\n \"Ctrl-Backspace\": \"delGroupBefore\", \"Ctrl-Delete\": \"delGroupAfter\", \"Ctrl-S\": \"save\", \"Ctrl-F\": \"find\",\n \"Ctrl-G\": \"findNext\", \"Shift-Ctrl-G\": \"findPrev\", \"Shift-Ctrl-F\": \"replace\", \"Shift-Ctrl-R\": \"replaceAll\",\n \"Ctrl-[\": \"indentLess\", \"Ctrl-]\": \"indentMore\",\n \"Ctrl-U\": \"undoSelection\", \"Shift-Ctrl-U\": \"redoSelection\", \"Alt-U\": \"redoSelection\",\n fallthrough: \"basic\"\n };\n // Very basic readline/emacs-style bindings, which are standard on Mac.\n keyMap.emacsy = {\n \"Ctrl-F\": \"goCharRight\", \"Ctrl-B\": \"goCharLeft\", \"Ctrl-P\": \"goLineUp\", \"Ctrl-N\": \"goLineDown\",\n \"Alt-F\": \"goWordRight\", \"Alt-B\": \"goWordLeft\", \"Ctrl-A\": \"goLineStart\", \"Ctrl-E\": \"goLineEnd\",\n \"Ctrl-V\": \"goPageDown\", \"Shift-Ctrl-V\": \"goPageUp\", \"Ctrl-D\": \"delCharAfter\", \"Ctrl-H\": \"delCharBefore\",\n \"Alt-D\": \"delWordAfter\", \"Alt-Backspace\": \"delWordBefore\", \"Ctrl-K\": \"killLine\", \"Ctrl-T\": \"transposeChars\"\n };\n keyMap.macDefault = {\n \"Cmd-A\": \"selectAll\", \"Cmd-D\": \"deleteLine\", \"Cmd-Z\": \"undo\", \"Shift-Cmd-Z\": \"redo\", \"Cmd-Y\": \"redo\",\n \"Cmd-Home\": \"goDocStart\", \"Cmd-Up\": \"goDocStart\", \"Cmd-End\": \"goDocEnd\", \"Cmd-Down\": \"goDocEnd\", \"Alt-Left\": \"goGroupLeft\",\n \"Alt-Right\": \"goGroupRight\", \"Cmd-Left\": \"goLineLeft\", \"Cmd-Right\": \"goLineRight\", \"Alt-Backspace\": \"delGroupBefore\",\n \"Ctrl-Alt-Backspace\": \"delGroupAfter\", \"Alt-Delete\": \"delGroupAfter\", \"Cmd-S\": \"save\", \"Cmd-F\": \"find\",\n \"Cmd-G\": \"findNext\", \"Shift-Cmd-G\": \"findPrev\", \"Cmd-Alt-F\": \"replace\", \"Shift-Cmd-Alt-F\": \"replaceAll\",\n \"Cmd-[\": \"indentLess\", \"Cmd-]\": \"indentMore\", \"Cmd-Backspace\": \"delWrappedLineLeft\", \"Cmd-Delete\": \"delWrappedLineRight\",\n \"Cmd-U\": \"undoSelection\", \"Shift-Cmd-U\": \"redoSelection\", \"Ctrl-Up\": \"goDocStart\", \"Ctrl-Down\": \"goDocEnd\",\n fallthrough: [\"basic\", \"emacsy\"]\n };\n keyMap[\"default\"] = mac ? keyMap.macDefault : keyMap.pcDefault;\n\n // KEYMAP DISPATCH\n\n function normalizeKeyName(name) {\n var parts = name.split(/-(?!$)/), name = parts[parts.length - 1];\n var alt, ctrl, shift, cmd;\n for (var i = 0; i < parts.length - 1; i++) {\n var mod = parts[i];\n if (/^(cmd|meta|m)$/i.test(mod)) cmd = true;\n else if (/^a(lt)?$/i.test(mod)) alt = true;\n else if (/^(c|ctrl|control)$/i.test(mod)) ctrl = true;\n else if (/^s(hift)$/i.test(mod)) shift = true;\n else throw new Error(\"Unrecognized modifier name: \" + mod);\n }\n if (alt) name = \"Alt-\" + name;\n if (ctrl) name = \"Ctrl-\" + name;\n if (cmd) name = \"Cmd-\" + name;\n if (shift) name = \"Shift-\" + name;\n return name;\n }\n\n // This is a kludge to keep keymaps mostly working as raw objects\n // (backwards compatibility) while at the same time support features\n // like normalization and multi-stroke key bindings. It compiles a\n // new normalized keymap, and then updates the old object to reflect\n // this.\n CodeMirror.normalizeKeyMap = function(keymap) {\n var copy = {};\n for (var keyname in keymap) if (keymap.hasOwnProperty(keyname)) {\n var value = keymap[keyname];\n if (/^(name|fallthrough|(de|at)tach)$/.test(keyname)) continue;\n if (value == \"...\") { delete keymap[keyname]; continue; }\n\n var keys = map(keyname.split(\" \"), normalizeKeyName);\n for (var i = 0; i < keys.length; i++) {\n var val, name;\n if (i == keys.length - 1) {\n name = keys.join(\" \");\n val = value;\n } else {\n name = keys.slice(0, i + 1).join(\" \");\n val = \"...\";\n }\n var prev = copy[name];\n if (!prev) copy[name] = val;\n else if (prev != val) throw new Error(\"Inconsistent bindings for \" + name);\n }\n delete keymap[keyname];\n }\n for (var prop in copy) keymap[prop] = copy[prop];\n return keymap;\n };\n\n var lookupKey = CodeMirror.lookupKey = function(key, map, handle, context) {\n map = getKeyMap(map);\n var found = map.call ? map.call(key, context) : map[key];\n if (found === false) return \"nothing\";\n if (found === \"...\") return \"multi\";\n if (found != null && handle(found)) return \"handled\";\n\n if (map.fallthrough) {\n if (Object.prototype.toString.call(map.fallthrough) != \"[object Array]\")\n return lookupKey(key, map.fallthrough, handle, context);\n for (var i = 0; i < map.fallthrough.length; i++) {\n var result = lookupKey(key, map.fallthrough[i], handle, context);\n if (result) return result;\n }\n }\n };\n\n // Modifier key presses don't count as 'real' key presses for the\n // purpose of keymap fallthrough.\n var isModifierKey = CodeMirror.isModifierKey = function(value) {\n var name = typeof value == \"string\" ? value : keyNames[value.keyCode];\n return name == \"Ctrl\" || name == \"Alt\" || name == \"Shift\" || name == \"Mod\";\n };\n\n // Look up the name of a key as indicated by an event object.\n var keyName = CodeMirror.keyName = function(event, noShift) {\n if (presto && event.keyCode == 34 && event[\"char\"]) return false;\n var base = keyNames[event.keyCode], name = base;\n if (name == null || event.altGraphKey) return false;\n if (event.altKey && base != \"Alt\") name = \"Alt-\" + name;\n if ((flipCtrlCmd ? event.metaKey : event.ctrlKey) && base != \"Ctrl\") name = \"Ctrl-\" + name;\n if ((flipCtrlCmd ? event.ctrlKey : event.metaKey) && base != \"Cmd\") name = \"Cmd-\" + name;\n if (!noShift && event.shiftKey && base != \"Shift\") name = \"Shift-\" + name;\n return name;\n };\n\n function getKeyMap(val) {\n return typeof val == \"string\" ? keyMap[val] : val;\n }\n\n // FROMTEXTAREA\n\n CodeMirror.fromTextArea = function(textarea, options) {\n options = options ? copyObj(options) : {};\n options.value = textarea.value;\n if (!options.tabindex && textarea.tabIndex)\n options.tabindex = textarea.tabIndex;\n if (!options.placeholder && textarea.placeholder)\n options.placeholder = textarea.placeholder;\n // Set autofocus to true if this textarea is focused, or if it has\n // autofocus and no other element is focused.\n if (options.autofocus == null) {\n var hasFocus = activeElt();\n options.autofocus = hasFocus == textarea ||\n textarea.getAttribute(\"autofocus\") != null && hasFocus == document.body;\n }\n\n function save() {textarea.value = cm.getValue();}\n if (textarea.form) {\n on(textarea.form, \"submit\", save);\n // Deplorable hack to make the submit method do the right thing.\n if (!options.leaveSubmitMethodAlone) {\n var form = textarea.form, realSubmit = form.submit;\n try {\n var wrappedSubmit = form.submit = function() {\n save();\n form.submit = realSubmit;\n form.submit();\n form.submit = wrappedSubmit;\n };\n } catch(e) {}\n }\n }\n\n options.finishInit = function(cm) {\n cm.save = save;\n cm.getTextArea = function() { return textarea; };\n cm.toTextArea = function() {\n cm.toTextArea = isNaN; // Prevent this from being ran twice\n save();\n textarea.parentNode.removeChild(cm.getWrapperElement());\n textarea.style.display = \"\";\n if (textarea.form) {\n off(textarea.form, \"submit\", save);\n if (typeof textarea.form.submit == \"function\")\n textarea.form.submit = realSubmit;\n }\n };\n };\n\n textarea.style.display = \"none\";\n var cm = CodeMirror(function(node) {\n textarea.parentNode.insertBefore(node, textarea.nextSibling);\n }, options);\n return cm;\n };\n\n // STRING STREAM\n\n // Fed to the mode parsers, provides helper functions to make\n // parsers more succinct.\n\n var StringStream = CodeMirror.StringStream = function(string, tabSize) {\n this.pos = this.start = 0;\n this.string = string;\n this.tabSize = tabSize || 8;\n this.lastColumnPos = this.lastColumnValue = 0;\n this.lineStart = 0;\n };\n\n StringStream.prototype = {\n eol: function() {return this.pos >= this.string.length;},\n sol: function() {return this.pos == this.lineStart;},\n peek: function() {return this.string.charAt(this.pos) || undefined;},\n next: function() {\n if (this.pos < this.string.length)\n return this.string.charAt(this.pos++);\n },\n eat: function(match) {\n var ch = this.string.charAt(this.pos);\n if (typeof match == \"string\") var ok = ch == match;\n else var ok = ch && (match.test ? match.test(ch) : match(ch));\n if (ok) {++this.pos; return ch;}\n },\n eatWhile: function(match) {\n var start = this.pos;\n while (this.eat(match)){}\n return this.pos > start;\n },\n eatSpace: function() {\n var start = this.pos;\n while (/[\\s\\u00a0]/.test(this.string.charAt(this.pos))) ++this.pos;\n return this.pos > start;\n },\n skipToEnd: function() {this.pos = this.string.length;},\n skipTo: function(ch) {\n var found = this.string.indexOf(ch, this.pos);\n if (found > -1) {this.pos = found; return true;}\n },\n backUp: function(n) {this.pos -= n;},\n column: function() {\n if (this.lastColumnPos < this.start) {\n this.lastColumnValue = countColumn(this.string, this.start, this.tabSize, this.lastColumnPos, this.lastColumnValue);\n this.lastColumnPos = this.start;\n }\n return this.lastColumnValue - (this.lineStart ? countColumn(this.string, this.lineStart, this.tabSize) : 0);\n },\n indentation: function() {\n return countColumn(this.string, null, this.tabSize) -\n (this.lineStart ? countColumn(this.string, this.lineStart, this.tabSize) : 0);\n },\n match: function(pattern, consume, caseInsensitive) {\n if (typeof pattern == \"string\") {\n var cased = function(str) {return caseInsensitive ? str.toLowerCase() : str;};\n var substr = this.string.substr(this.pos, pattern.length);\n if (cased(substr) == cased(pattern)) {\n if (consume !== false) this.pos += pattern.length;\n return true;\n }\n } else {\n var match = this.string.slice(this.pos).match(pattern);\n if (match && match.index > 0) return null;\n if (match && consume !== false) this.pos += match[0].length;\n return match;\n }\n },\n current: function(){return this.string.slice(this.start, this.pos);},\n hideFirstChars: function(n, inner) {\n this.lineStart += n;\n try { return inner(); }\n finally { this.lineStart -= n; }\n }\n };\n\n // TEXTMARKERS\n\n // Created with markText and setBookmark methods. A TextMarker is a\n // handle that can be used to clear or find a marked position in the\n // document. Line objects hold arrays (markedSpans) containing\n // {from, to, marker} object pointing to such marker objects, and\n // indicating that such a marker is present on that line. Multiple\n // lines may point to the same marker when it spans across lines.\n // The spans will have null for their from/to properties when the\n // marker continues beyond the start/end of the line. Markers have\n // links back to the lines they currently touch.\n\n var nextMarkerId = 0;\n\n var TextMarker = CodeMirror.TextMarker = function(doc, type) {\n this.lines = [];\n this.type = type;\n this.doc = doc;\n this.id = ++nextMarkerId;\n };\n eventMixin(TextMarker);\n\n // Clear the marker.\n TextMarker.prototype.clear = function() {\n if (this.explicitlyCleared) return;\n var cm = this.doc.cm, withOp = cm && !cm.curOp;\n if (withOp) startOperation(cm);\n if (hasHandler(this, \"clear\")) {\n var found = this.find();\n if (found) signalLater(this, \"clear\", found.from, found.to);\n }\n var min = null, max = null;\n for (var i = 0; i < this.lines.length; ++i) {\n var line = this.lines[i];\n var span = getMarkedSpanFor(line.markedSpans, this);\n if (cm && !this.collapsed) regLineChange(cm, lineNo(line), \"text\");\n else if (cm) {\n if (span.to != null) max = lineNo(line);\n if (span.from != null) min = lineNo(line);\n }\n line.markedSpans = removeMarkedSpan(line.markedSpans, span);\n if (span.from == null && this.collapsed && !lineIsHidden(this.doc, line) && cm)\n updateLineHeight(line, textHeight(cm.display));\n }\n if (cm && this.collapsed && !cm.options.lineWrapping) for (var i = 0; i < this.lines.length; ++i) {\n var visual = visualLine(this.lines[i]), len = lineLength(visual);\n if (len > cm.display.maxLineLength) {\n cm.display.maxLine = visual;\n cm.display.maxLineLength = len;\n cm.display.maxLineChanged = true;\n }\n }\n\n if (min != null && cm && this.collapsed) regChange(cm, min, max + 1);\n this.lines.length = 0;\n this.explicitlyCleared = true;\n if (this.atomic && this.doc.cantEdit) {\n this.doc.cantEdit = false;\n if (cm) reCheckSelection(cm.doc);\n }\n if (cm) signalLater(cm, \"markerCleared\", cm, this);\n if (withOp) endOperation(cm);\n if (this.parent) this.parent.clear();\n };\n\n // Find the position of the marker in the document. Returns a {from,\n // to} object by default. Side can be passed to get a specific side\n // -- 0 (both), -1 (left), or 1 (right). When lineObj is true, the\n // Pos objects returned contain a line object, rather than a line\n // number (used to prevent looking up the same line twice).\n TextMarker.prototype.find = function(side, lineObj) {\n if (side == null && this.type == \"bookmark\") side = 1;\n var from, to;\n for (var i = 0; i < this.lines.length; ++i) {\n var line = this.lines[i];\n var span = getMarkedSpanFor(line.markedSpans, this);\n if (span.from != null) {\n from = Pos(lineObj ? line : lineNo(line), span.from);\n if (side == -1) return from;\n }\n if (span.to != null) {\n to = Pos(lineObj ? line : lineNo(line), span.to);\n if (side == 1) return to;\n }\n }\n return from && {from: from, to: to};\n };\n\n // Signals that the marker's widget changed, and surrounding layout\n // should be recomputed.\n TextMarker.prototype.changed = function() {\n var pos = this.find(-1, true), widget = this, cm = this.doc.cm;\n if (!pos || !cm) return;\n runInOp(cm, function() {\n var line = pos.line, lineN = lineNo(pos.line);\n var view = findViewForLine(cm, lineN);\n if (view) {\n clearLineMeasurementCacheFor(view);\n cm.curOp.selectionChanged = cm.curOp.forceUpdate = true;\n }\n cm.curOp.updateMaxLine = true;\n if (!lineIsHidden(widget.doc, line) && widget.height != null) {\n var oldHeight = widget.height;\n widget.height = null;\n var dHeight = widgetHeight(widget) - oldHeight;\n if (dHeight)\n updateLineHeight(line, line.height + dHeight);\n }\n });\n };\n\n TextMarker.prototype.attachLine = function(line) {\n if (!this.lines.length && this.doc.cm) {\n var op = this.doc.cm.curOp;\n if (!op.maybeHiddenMarkers || indexOf(op.maybeHiddenMarkers, this) == -1)\n (op.maybeUnhiddenMarkers || (op.maybeUnhiddenMarkers = [])).push(this);\n }\n this.lines.push(line);\n };\n TextMarker.prototype.detachLine = function(line) {\n this.lines.splice(indexOf(this.lines, line), 1);\n if (!this.lines.length && this.doc.cm) {\n var op = this.doc.cm.curOp;\n (op.maybeHiddenMarkers || (op.maybeHiddenMarkers = [])).push(this);\n }\n };\n\n // Collapsed markers have unique ids, in order to be able to order\n // them, which is needed for uniquely determining an outer marker\n // when they overlap (they may nest, but not partially overlap).\n var nextMarkerId = 0;\n\n // Create a marker, wire it up to the right lines, and\n function markText(doc, from, to, options, type) {\n // Shared markers (across linked documents) are handled separately\n // (markTextShared will call out to this again, once per\n // document).\n if (options && options.shared) return markTextShared(doc, from, to, options, type);\n // Ensure we are in an operation.\n if (doc.cm && !doc.cm.curOp) return operation(doc.cm, markText)(doc, from, to, options, type);\n\n var marker = new TextMarker(doc, type), diff = cmp(from, to);\n if (options) copyObj(options, marker, false);\n // Don't connect empty markers unless clearWhenEmpty is false\n if (diff > 0 || diff == 0 && marker.clearWhenEmpty !== false)\n return marker;\n if (marker.replacedWith) {\n // Showing up as a widget implies collapsed (widget replaces text)\n marker.collapsed = true;\n marker.widgetNode = elt(\"span\", [marker.replacedWith], \"CodeMirror-widget\");\n if (!options.handleMouseEvents) marker.widgetNode.setAttribute(\"cm-ignore-events\", \"true\");\n if (options.insertLeft) marker.widgetNode.insertLeft = true;\n }\n if (marker.collapsed) {\n if (conflictingCollapsedRange(doc, from.line, from, to, marker) ||\n from.line != to.line && conflictingCollapsedRange(doc, to.line, from, to, marker))\n throw new Error(\"Inserting collapsed marker partially overlapping an existing one\");\n sawCollapsedSpans = true;\n }\n\n if (marker.addToHistory)\n addChangeToHistory(doc, {from: from, to: to, origin: \"markText\"}, doc.sel, NaN);\n\n var curLine = from.line, cm = doc.cm, updateMaxLine;\n doc.iter(curLine, to.line + 1, function(line) {\n if (cm && marker.collapsed && !cm.options.lineWrapping && visualLine(line) == cm.display.maxLine)\n updateMaxLine = true;\n if (marker.collapsed && curLine != from.line) updateLineHeight(line, 0);\n addMarkedSpan(line, new MarkedSpan(marker,\n curLine == from.line ? from.ch : null,\n curLine == to.line ? to.ch : null));\n ++curLine;\n });\n // lineIsHidden depends on the presence of the spans, so needs a second pass\n if (marker.collapsed) doc.iter(from.line, to.line + 1, function(line) {\n if (lineIsHidden(doc, line)) updateLineHeight(line, 0);\n });\n\n if (marker.clearOnEnter) on(marker, \"beforeCursorEnter\", function() { marker.clear(); });\n\n if (marker.readOnly) {\n sawReadOnlySpans = true;\n if (doc.history.done.length || doc.history.undone.length)\n doc.clearHistory();\n }\n if (marker.collapsed) {\n marker.id = ++nextMarkerId;\n marker.atomic = true;\n }\n if (cm) {\n // Sync editor state\n if (updateMaxLine) cm.curOp.updateMaxLine = true;\n if (marker.collapsed)\n regChange(cm, from.line, to.line + 1);\n else if (marker.className || marker.title || marker.startStyle || marker.endStyle || marker.css)\n for (var i = from.line; i <= to.line; i++) regLineChange(cm, i, \"text\");\n if (marker.atomic) reCheckSelection(cm.doc);\n signalLater(cm, \"markerAdded\", cm, marker);\n }\n return marker;\n }\n\n // SHARED TEXTMARKERS\n\n // A shared marker spans multiple linked documents. It is\n // implemented as a meta-marker-object controlling multiple normal\n // markers.\n var SharedTextMarker = CodeMirror.SharedTextMarker = function(markers, primary) {\n this.markers = markers;\n this.primary = primary;\n for (var i = 0; i < markers.length; ++i)\n markers[i].parent = this;\n };\n eventMixin(SharedTextMarker);\n\n SharedTextMarker.prototype.clear = function() {\n if (this.explicitlyCleared) return;\n this.explicitlyCleared = true;\n for (var i = 0; i < this.markers.length; ++i)\n this.markers[i].clear();\n signalLater(this, \"clear\");\n };\n SharedTextMarker.prototype.find = function(side, lineObj) {\n return this.primary.find(side, lineObj);\n };\n\n function markTextShared(doc, from, to, options, type) {\n options = copyObj(options);\n options.shared = false;\n var markers = [markText(doc, from, to, options, type)], primary = markers[0];\n var widget = options.widgetNode;\n linkedDocs(doc, function(doc) {\n if (widget) options.widgetNode = widget.cloneNode(true);\n markers.push(markText(doc, clipPos(doc, from), clipPos(doc, to), options, type));\n for (var i = 0; i < doc.linked.length; ++i)\n if (doc.linked[i].isParent) return;\n primary = lst(markers);\n });\n return new SharedTextMarker(markers, primary);\n }\n\n function findSharedMarkers(doc) {\n return doc.findMarks(Pos(doc.first, 0), doc.clipPos(Pos(doc.lastLine())),\n function(m) { return m.parent; });\n }\n\n function copySharedMarkers(doc, markers) {\n for (var i = 0; i < markers.length; i++) {\n var marker = markers[i], pos = marker.find();\n var mFrom = doc.clipPos(pos.from), mTo = doc.clipPos(pos.to);\n if (cmp(mFrom, mTo)) {\n var subMark = markText(doc, mFrom, mTo, marker.primary, marker.primary.type);\n marker.markers.push(subMark);\n subMark.parent = marker;\n }\n }\n }\n\n function detachSharedMarkers(markers) {\n for (var i = 0; i < markers.length; i++) {\n var marker = markers[i], linked = [marker.primary.doc];;\n linkedDocs(marker.primary.doc, function(d) { linked.push(d); });\n for (var j = 0; j < marker.markers.length; j++) {\n var subMarker = marker.markers[j];\n if (indexOf(linked, subMarker.doc) == -1) {\n subMarker.parent = null;\n marker.markers.splice(j--, 1);\n }\n }\n }\n }\n\n // TEXTMARKER SPANS\n\n function MarkedSpan(marker, from, to) {\n this.marker = marker;\n this.from = from; this.to = to;\n }\n\n // Search an array of spans for a span matching the given marker.\n function getMarkedSpanFor(spans, marker) {\n if (spans) for (var i = 0; i < spans.length; ++i) {\n var span = spans[i];\n if (span.marker == marker) return span;\n }\n }\n // Remove a span from an array, returning undefined if no spans are\n // left (we don't store arrays for lines without spans).\n function removeMarkedSpan(spans, span) {\n for (var r, i = 0; i < spans.length; ++i)\n if (spans[i] != span) (r || (r = [])).push(spans[i]);\n return r;\n }\n // Add a span to a line.\n function addMarkedSpan(line, span) {\n line.markedSpans = line.markedSpans ? line.markedSpans.concat([span]) : [span];\n span.marker.attachLine(line);\n }\n\n // Used for the algorithm that adjusts markers for a change in the\n // document. These functions cut an array of spans at a given\n // character position, returning an array of remaining chunks (or\n // undefined if nothing remains).\n function markedSpansBefore(old, startCh, isInsert) {\n if (old) for (var i = 0, nw; i < old.length; ++i) {\n var span = old[i], marker = span.marker;\n var startsBefore = span.from == null || (marker.inclusiveLeft ? span.from <= startCh : span.from < startCh);\n if (startsBefore || span.from == startCh && marker.type == \"bookmark\" && (!isInsert || !span.marker.insertLeft)) {\n var endsAfter = span.to == null || (marker.inclusiveRight ? span.to >= startCh : span.to > startCh);\n (nw || (nw = [])).push(new MarkedSpan(marker, span.from, endsAfter ? null : span.to));\n }\n }\n return nw;\n }\n function markedSpansAfter(old, endCh, isInsert) {\n if (old) for (var i = 0, nw; i < old.length; ++i) {\n var span = old[i], marker = span.marker;\n var endsAfter = span.to == null || (marker.inclusiveRight ? span.to >= endCh : span.to > endCh);\n if (endsAfter || span.from == endCh && marker.type == \"bookmark\" && (!isInsert || span.marker.insertLeft)) {\n var startsBefore = span.from == null || (marker.inclusiveLeft ? span.from <= endCh : span.from < endCh);\n (nw || (nw = [])).push(new MarkedSpan(marker, startsBefore ? null : span.from - endCh,\n span.to == null ? null : span.to - endCh));\n }\n }\n return nw;\n }\n\n // Given a change object, compute the new set of marker spans that\n // cover the line in which the change took place. Removes spans\n // entirely within the change, reconnects spans belonging to the\n // same marker that appear on both sides of the change, and cuts off\n // spans partially within the change. Returns an array of span\n // arrays with one element for each line in (after) the change.\n function stretchSpansOverChange(doc, change) {\n if (change.full) return null;\n var oldFirst = isLine(doc, change.from.line) && getLine(doc, change.from.line).markedSpans;\n var oldLast = isLine(doc, change.to.line) && getLine(doc, change.to.line).markedSpans;\n if (!oldFirst && !oldLast) return null;\n\n var startCh = change.from.ch, endCh = change.to.ch, isInsert = cmp(change.from, change.to) == 0;\n // Get the spans that 'stick out' on both sides\n var first = markedSpansBefore(oldFirst, startCh, isInsert);\n var last = markedSpansAfter(oldLast, endCh, isInsert);\n\n // Next, merge those two ends\n var sameLine = change.text.length == 1, offset = lst(change.text).length + (sameLine ? startCh : 0);\n if (first) {\n // Fix up .to properties of first\n for (var i = 0; i < first.length; ++i) {\n var span = first[i];\n if (span.to == null) {\n var found = getMarkedSpanFor(last, span.marker);\n if (!found) span.to = startCh;\n else if (sameLine) span.to = found.to == null ? null : found.to + offset;\n }\n }\n }\n if (last) {\n // Fix up .from in last (or move them into first in case of sameLine)\n for (var i = 0; i < last.length; ++i) {\n var span = last[i];\n if (span.to != null) span.to += offset;\n if (span.from == null) {\n var found = getMarkedSpanFor(first, span.marker);\n if (!found) {\n span.from = offset;\n if (sameLine) (first || (first = [])).push(span);\n }\n } else {\n span.from += offset;\n if (sameLine) (first || (first = [])).push(span);\n }\n }\n }\n // Make sure we didn't create any zero-length spans\n if (first) first = clearEmptySpans(first);\n if (last && last != first) last = clearEmptySpans(last);\n\n var newMarkers = [first];\n if (!sameLine) {\n // Fill gap with whole-line-spans\n var gap = change.text.length - 2, gapMarkers;\n if (gap > 0 && first)\n for (var i = 0; i < first.length; ++i)\n if (first[i].to == null)\n (gapMarkers || (gapMarkers = [])).push(new MarkedSpan(first[i].marker, null, null));\n for (var i = 0; i < gap; ++i)\n newMarkers.push(gapMarkers);\n newMarkers.push(last);\n }\n return newMarkers;\n }\n\n // Remove spans that are empty and don't have a clearWhenEmpty\n // option of false.\n function clearEmptySpans(spans) {\n for (var i = 0; i < spans.length; ++i) {\n var span = spans[i];\n if (span.from != null && span.from == span.to && span.marker.clearWhenEmpty !== false)\n spans.splice(i--, 1);\n }\n if (!spans.length) return null;\n return spans;\n }\n\n // Used for un/re-doing changes from the history. Combines the\n // result of computing the existing spans with the set of spans that\n // existed in the history (so that deleting around a span and then\n // undoing brings back the span).\n function mergeOldSpans(doc, change) {\n var old = getOldSpans(doc, change);\n var stretched = stretchSpansOverChange(doc, change);\n if (!old) return stretched;\n if (!stretched) return old;\n\n for (var i = 0; i < old.length; ++i) {\n var oldCur = old[i], stretchCur = stretched[i];\n if (oldCur && stretchCur) {\n spans: for (var j = 0; j < stretchCur.length; ++j) {\n var span = stretchCur[j];\n for (var k = 0; k < oldCur.length; ++k)\n if (oldCur[k].marker == span.marker) continue spans;\n oldCur.push(span);\n }\n } else if (stretchCur) {\n old[i] = stretchCur;\n }\n }\n return old;\n }\n\n // Used to 'clip' out readOnly ranges when making a change.\n function removeReadOnlyRanges(doc, from, to) {\n var markers = null;\n doc.iter(from.line, to.line + 1, function(line) {\n if (line.markedSpans) for (var i = 0; i < line.markedSpans.length; ++i) {\n var mark = line.markedSpans[i].marker;\n if (mark.readOnly && (!markers || indexOf(markers, mark) == -1))\n (markers || (markers = [])).push(mark);\n }\n });\n if (!markers) return null;\n var parts = [{from: from, to: to}];\n for (var i = 0; i < markers.length; ++i) {\n var mk = markers[i], m = mk.find(0);\n for (var j = 0; j < parts.length; ++j) {\n var p = parts[j];\n if (cmp(p.to, m.from) < 0 || cmp(p.from, m.to) > 0) continue;\n var newParts = [j, 1], dfrom = cmp(p.from, m.from), dto = cmp(p.to, m.to);\n if (dfrom < 0 || !mk.inclusiveLeft && !dfrom)\n newParts.push({from: p.from, to: m.from});\n if (dto > 0 || !mk.inclusiveRight && !dto)\n newParts.push({from: m.to, to: p.to});\n parts.splice.apply(parts, newParts);\n j += newParts.length - 1;\n }\n }\n return parts;\n }\n\n // Connect or disconnect spans from a line.\n function detachMarkedSpans(line) {\n var spans = line.markedSpans;\n if (!spans) return;\n for (var i = 0; i < spans.length; ++i)\n spans[i].marker.detachLine(line);\n line.markedSpans = null;\n }\n function attachMarkedSpans(line, spans) {\n if (!spans) return;\n for (var i = 0; i < spans.length; ++i)\n spans[i].marker.attachLine(line);\n line.markedSpans = spans;\n }\n\n // Helpers used when computing which overlapping collapsed span\n // counts as the larger one.\n function extraLeft(marker) { return marker.inclusiveLeft ? -1 : 0; }\n function extraRight(marker) { return marker.inclusiveRight ? 1 : 0; }\n\n // Returns a number indicating which of two overlapping collapsed\n // spans is larger (and thus includes the other). Falls back to\n // comparing ids when the spans cover exactly the same range.\n function compareCollapsedMarkers(a, b) {\n var lenDiff = a.lines.length - b.lines.length;\n if (lenDiff != 0) return lenDiff;\n var aPos = a.find(), bPos = b.find();\n var fromCmp = cmp(aPos.from, bPos.from) || extraLeft(a) - extraLeft(b);\n if (fromCmp) return -fromCmp;\n var toCmp = cmp(aPos.to, bPos.to) || extraRight(a) - extraRight(b);\n if (toCmp) return toCmp;\n return b.id - a.id;\n }\n\n // Find out whether a line ends or starts in a collapsed span. If\n // so, return the marker for that span.\n function collapsedSpanAtSide(line, start) {\n var sps = sawCollapsedSpans && line.markedSpans, found;\n if (sps) for (var sp, i = 0; i < sps.length; ++i) {\n sp = sps[i];\n if (sp.marker.collapsed && (start ? sp.from : sp.to) == null &&\n (!found || compareCollapsedMarkers(found, sp.marker) < 0))\n found = sp.marker;\n }\n return found;\n }\n function collapsedSpanAtStart(line) { return collapsedSpanAtSide(line, true); }\n function collapsedSpanAtEnd(line) { return collapsedSpanAtSide(line, false); }\n\n // Test whether there exists a collapsed span that partially\n // overlaps (covers the start or end, but not both) of a new span.\n // Such overlap is not allowed.\n function conflictingCollapsedRange(doc, lineNo, from, to, marker) {\n var line = getLine(doc, lineNo);\n var sps = sawCollapsedSpans && line.markedSpans;\n if (sps) for (var i = 0; i < sps.length; ++i) {\n var sp = sps[i];\n if (!sp.marker.collapsed) continue;\n var found = sp.marker.find(0);\n var fromCmp = cmp(found.from, from) || extraLeft(sp.marker) - extraLeft(marker);\n var toCmp = cmp(found.to, to) || extraRight(sp.marker) - extraRight(marker);\n if (fromCmp >= 0 && toCmp <= 0 || fromCmp <= 0 && toCmp >= 0) continue;\n if (fromCmp <= 0 && (cmp(found.to, from) > 0 || (sp.marker.inclusiveRight && marker.inclusiveLeft)) ||\n fromCmp >= 0 && (cmp(found.from, to) < 0 || (sp.marker.inclusiveLeft && marker.inclusiveRight)))\n return true;\n }\n }\n\n // A visual line is a line as drawn on the screen. Folding, for\n // example, can cause multiple logical lines to appear on the same\n // visual line. This finds the start of the visual line that the\n // given line is part of (usually that is the line itself).\n function visualLine(line) {\n var merged;\n while (merged = collapsedSpanAtStart(line))\n line = merged.find(-1, true).line;\n return line;\n }\n\n // Returns an array of logical lines that continue the visual line\n // started by the argument, or undefined if there are no such lines.\n function visualLineContinued(line) {\n var merged, lines;\n while (merged = collapsedSpanAtEnd(line)) {\n line = merged.find(1, true).line;\n (lines || (lines = [])).push(line);\n }\n return lines;\n }\n\n // Get the line number of the start of the visual line that the\n // given line number is part of.\n function visualLineNo(doc, lineN) {\n var line = getLine(doc, lineN), vis = visualLine(line);\n if (line == vis) return lineN;\n return lineNo(vis);\n }\n // Get the line number of the start of the next visual line after\n // the given line.\n function visualLineEndNo(doc, lineN) {\n if (lineN > doc.lastLine()) return lineN;\n var line = getLine(doc, lineN), merged;\n if (!lineIsHidden(doc, line)) return lineN;\n while (merged = collapsedSpanAtEnd(line))\n line = merged.find(1, true).line;\n return lineNo(line) + 1;\n }\n\n // Compute whether a line is hidden. Lines count as hidden when they\n // are part of a visual line that starts with another line, or when\n // they are entirely covered by collapsed, non-widget span.\n function lineIsHidden(doc, line) {\n var sps = sawCollapsedSpans && line.markedSpans;\n if (sps) for (var sp, i = 0; i < sps.length; ++i) {\n sp = sps[i];\n if (!sp.marker.collapsed) continue;\n if (sp.from == null) return true;\n if (sp.marker.widgetNode) continue;\n if (sp.from == 0 && sp.marker.inclusiveLeft && lineIsHiddenInner(doc, line, sp))\n return true;\n }\n }\n function lineIsHiddenInner(doc, line, span) {\n if (span.to == null) {\n var end = span.marker.find(1, true);\n return lineIsHiddenInner(doc, end.line, getMarkedSpanFor(end.line.markedSpans, span.marker));\n }\n if (span.marker.inclusiveRight && span.to == line.text.length)\n return true;\n for (var sp, i = 0; i < line.markedSpans.length; ++i) {\n sp = line.markedSpans[i];\n if (sp.marker.collapsed && !sp.marker.widgetNode && sp.from == span.to &&\n (sp.to == null || sp.to != span.from) &&\n (sp.marker.inclusiveLeft || span.marker.inclusiveRight) &&\n lineIsHiddenInner(doc, line, sp)) return true;\n }\n }\n\n // LINE WIDGETS\n\n // Line widgets are block elements displayed above or below a line.\n\n var LineWidget = CodeMirror.LineWidget = function(doc, node, options) {\n if (options) for (var opt in options) if (options.hasOwnProperty(opt))\n this[opt] = options[opt];\n this.doc = doc;\n this.node = node;\n };\n eventMixin(LineWidget);\n\n function adjustScrollWhenAboveVisible(cm, line, diff) {\n if (heightAtLine(line) < ((cm.curOp && cm.curOp.scrollTop) || cm.doc.scrollTop))\n addToScrollPos(cm, null, diff);\n }\n\n LineWidget.prototype.clear = function() {\n var cm = this.doc.cm, ws = this.line.widgets, line = this.line, no = lineNo(line);\n if (no == null || !ws) return;\n for (var i = 0; i < ws.length; ++i) if (ws[i] == this) ws.splice(i--, 1);\n if (!ws.length) line.widgets = null;\n var height = widgetHeight(this);\n updateLineHeight(line, Math.max(0, line.height - height));\n if (cm) runInOp(cm, function() {\n adjustScrollWhenAboveVisible(cm, line, -height);\n regLineChange(cm, no, \"widget\");\n });\n };\n LineWidget.prototype.changed = function() {\n var oldH = this.height, cm = this.doc.cm, line = this.line;\n this.height = null;\n var diff = widgetHeight(this) - oldH;\n if (!diff) return;\n updateLineHeight(line, line.height + diff);\n if (cm) runInOp(cm, function() {\n cm.curOp.forceUpdate = true;\n adjustScrollWhenAboveVisible(cm, line, diff);\n });\n };\n\n function widgetHeight(widget) {\n if (widget.height != null) return widget.height;\n var cm = widget.doc.cm;\n if (!cm) return 0;\n if (!contains(document.body, widget.node)) {\n var parentStyle = \"position: relative;\";\n if (widget.coverGutter)\n parentStyle += \"margin-left: -\" + cm.display.gutters.offsetWidth + \"px;\";\n if (widget.noHScroll)\n parentStyle += \"width: \" + cm.display.wrapper.clientWidth + \"px;\";\n removeChildrenAndAdd(cm.display.measure, elt(\"div\", [widget.node], null, parentStyle));\n }\n return widget.height = widget.node.parentNode.offsetHeight;\n }\n\n function addLineWidget(doc, handle, node, options) {\n var widget = new LineWidget(doc, node, options);\n var cm = doc.cm;\n if (cm && widget.noHScroll) cm.display.alignWidgets = true;\n changeLine(doc, handle, \"widget\", function(line) {\n var widgets = line.widgets || (line.widgets = []);\n if (widget.insertAt == null) widgets.push(widget);\n else widgets.splice(Math.min(widgets.length - 1, Math.max(0, widget.insertAt)), 0, widget);\n widget.line = line;\n if (cm && !lineIsHidden(doc, line)) {\n var aboveVisible = heightAtLine(line) < doc.scrollTop;\n updateLineHeight(line, line.height + widgetHeight(widget));\n if (aboveVisible) addToScrollPos(cm, null, widget.height);\n cm.curOp.forceUpdate = true;\n }\n return true;\n });\n return widget;\n }\n\n // LINE DATA STRUCTURE\n\n // Line objects. These hold state related to a line, including\n // highlighting info (the styles array).\n var Line = CodeMirror.Line = function(text, markedSpans, estimateHeight) {\n this.text = text;\n attachMarkedSpans(this, markedSpans);\n this.height = estimateHeight ? estimateHeight(this) : 1;\n };\n eventMixin(Line);\n Line.prototype.lineNo = function() { return lineNo(this); };\n\n // Change the content (text, markers) of a line. Automatically\n // invalidates cached information and tries to re-estimate the\n // line's height.\n function updateLine(line, text, markedSpans, estimateHeight) {\n line.text = text;\n if (line.stateAfter) line.stateAfter = null;\n if (line.styles) line.styles = null;\n if (line.order != null) line.order = null;\n detachMarkedSpans(line);\n attachMarkedSpans(line, markedSpans);\n var estHeight = estimateHeight ? estimateHeight(line) : 1;\n if (estHeight != line.height) updateLineHeight(line, estHeight);\n }\n\n // Detach a line from the document tree and its markers.\n function cleanUpLine(line) {\n line.parent = null;\n detachMarkedSpans(line);\n }\n\n function extractLineClasses(type, output) {\n if (type) for (;;) {\n var lineClass = type.match(/(?:^|\\s+)line-(background-)?(\\S+)/);\n if (!lineClass) break;\n type = type.slice(0, lineClass.index) + type.slice(lineClass.index + lineClass[0].length);\n var prop = lineClass[1] ? \"bgClass\" : \"textClass\";\n if (output[prop] == null)\n output[prop] = lineClass[2];\n else if (!(new RegExp(\"(?:^|\\s)\" + lineClass[2] + \"(?:$|\\s)\")).test(output[prop]))\n output[prop] += \" \" + lineClass[2];\n }\n return type;\n }\n\n function callBlankLine(mode, state) {\n if (mode.blankLine) return mode.blankLine(state);\n if (!mode.innerMode) return;\n var inner = CodeMirror.innerMode(mode, state);\n if (inner.mode.blankLine) return inner.mode.blankLine(inner.state);\n }\n\n function readToken(mode, stream, state, inner) {\n for (var i = 0; i < 10; i++) {\n if (inner) inner[0] = CodeMirror.innerMode(mode, state).mode;\n var style = mode.token(stream, state);\n if (stream.pos > stream.start) return style;\n }\n throw new Error(\"Mode \" + mode.name + \" failed to advance stream.\");\n }\n\n // Utility for getTokenAt and getLineTokens\n function takeToken(cm, pos, precise, asArray) {\n function getObj(copy) {\n return {start: stream.start, end: stream.pos,\n string: stream.current(),\n type: style || null,\n state: copy ? copyState(doc.mode, state) : state};\n }\n\n var doc = cm.doc, mode = doc.mode, style;\n pos = clipPos(doc, pos);\n var line = getLine(doc, pos.line), state = getStateBefore(cm, pos.line, precise);\n var stream = new StringStream(line.text, cm.options.tabSize), tokens;\n if (asArray) tokens = [];\n while ((asArray || stream.pos < pos.ch) && !stream.eol()) {\n stream.start = stream.pos;\n style = readToken(mode, stream, state);\n if (asArray) tokens.push(getObj(true));\n }\n return asArray ? tokens : getObj();\n }\n\n // Run the given mode's parser over a line, calling f for each token.\n function runMode(cm, text, mode, state, f, lineClasses, forceToEnd) {\n var flattenSpans = mode.flattenSpans;\n if (flattenSpans == null) flattenSpans = cm.options.flattenSpans;\n var curStart = 0, curStyle = null;\n var stream = new StringStream(text, cm.options.tabSize), style;\n var inner = cm.options.addModeClass && [null];\n if (text == \"\") extractLineClasses(callBlankLine(mode, state), lineClasses);\n while (!stream.eol()) {\n if (stream.pos > cm.options.maxHighlightLength) {\n flattenSpans = false;\n if (forceToEnd) processLine(cm, text, state, stream.pos);\n stream.pos = text.length;\n style = null;\n } else {\n style = extractLineClasses(readToken(mode, stream, state, inner), lineClasses);\n }\n if (inner) {\n var mName = inner[0].name;\n if (mName) style = \"m-\" + (style ? mName + \" \" + style : mName);\n }\n if (!flattenSpans || curStyle != style) {\n while (curStart < stream.start) {\n curStart = Math.min(stream.start, curStart + 50000);\n f(curStart, curStyle);\n }\n curStyle = style;\n }\n stream.start = stream.pos;\n }\n while (curStart < stream.pos) {\n // Webkit seems to refuse to render text nodes longer than 57444 characters\n var pos = Math.min(stream.pos, curStart + 50000);\n f(pos, curStyle);\n curStart = pos;\n }\n }\n\n // Compute a style array (an array starting with a mode generation\n // -- for invalidation -- followed by pairs of end positions and\n // style strings), which is used to highlight the tokens on the\n // line.\n function highlightLine(cm, line, state, forceToEnd) {\n // A styles array always starts with a number identifying the\n // mode/overlays that it is based on (for easy invalidation).\n var st = [cm.state.modeGen], lineClasses = {};\n // Compute the base array of styles\n runMode(cm, line.text, cm.doc.mode, state, function(end, style) {\n st.push(end, style);\n }, lineClasses, forceToEnd);\n\n // Run overlays, adjust style array.\n for (var o = 0; o < cm.state.overlays.length; ++o) {\n var overlay = cm.state.overlays[o], i = 1, at = 0;\n runMode(cm, line.text, overlay.mode, true, function(end, style) {\n var start = i;\n // Ensure there's a token end at the current position, and that i points at it\n while (at < end) {\n var i_end = st[i];\n if (i_end > end)\n st.splice(i, 1, end, st[i+1], i_end);\n i += 2;\n at = Math.min(end, i_end);\n }\n if (!style) return;\n if (overlay.opaque) {\n st.splice(start, i - start, end, \"cm-overlay \" + style);\n i = start + 2;\n } else {\n for (; start < i; start += 2) {\n var cur = st[start+1];\n st[start+1] = (cur ? cur + \" \" : \"\") + \"cm-overlay \" + style;\n }\n }\n }, lineClasses);\n }\n\n return {styles: st, classes: lineClasses.bgClass || lineClasses.textClass ? lineClasses : null};\n }\n\n function getLineStyles(cm, line, updateFrontier) {\n if (!line.styles || line.styles[0] != cm.state.modeGen) {\n var state = getStateBefore(cm, lineNo(line));\n var result = highlightLine(cm, line, line.text.length > cm.options.maxHighlightLength ? copyState(cm.doc.mode, state) : state);\n line.stateAfter = state;\n line.styles = result.styles;\n if (result.classes) line.styleClasses = result.classes;\n else if (line.styleClasses) line.styleClasses = null;\n if (updateFrontier === cm.doc.frontier) cm.doc.frontier++;\n }\n return line.styles;\n }\n\n // Lightweight form of highlight -- proceed over this line and\n // update state, but don't save a style array. Used for lines that\n // aren't currently visible.\n function processLine(cm, text, state, startAt) {\n var mode = cm.doc.mode;\n var stream = new StringStream(text, cm.options.tabSize);\n stream.start = stream.pos = startAt || 0;\n if (text == \"\") callBlankLine(mode, state);\n while (!stream.eol()) {\n readToken(mode, stream, state);\n stream.start = stream.pos;\n }\n }\n\n // Convert a style as returned by a mode (either null, or a string\n // containing one or more styles) to a CSS style. This is cached,\n // and also looks for line-wide styles.\n var styleToClassCache = {}, styleToClassCacheWithMode = {};\n function interpretTokenStyle(style, options) {\n if (!style || /^\\s*$/.test(style)) return null;\n var cache = options.addModeClass ? styleToClassCacheWithMode : styleToClassCache;\n return cache[style] ||\n (cache[style] = style.replace(/\\S+/g, \"cm-$&\"));\n }\n\n // Render the DOM representation of the text of a line. Also builds\n // up a 'line map', which points at the DOM nodes that represent\n // specific stretches of text, and is used by the measuring code.\n // The returned object contains the DOM node, this map, and\n // information about line-wide styles that were set by the mode.\n function buildLineContent(cm, lineView) {\n // The padding-right forces the element to have a 'border', which\n // is needed on Webkit to be able to get line-level bounding\n // rectangles for it (in measureChar).\n var content = elt(\"span\", null, null, webkit ? \"padding-right: .1px\" : null);\n var builder = {pre: elt(\"pre\", [content], \"CodeMirror-line\"), content: content,\n col: 0, pos: 0, cm: cm,\n splitSpaces: (ie || webkit) && cm.getOption(\"lineWrapping\")};\n lineView.measure = {};\n\n // Iterate over the logical lines that make up this visual line.\n for (var i = 0; i <= (lineView.rest ? lineView.rest.length : 0); i++) {\n var line = i ? lineView.rest[i - 1] : lineView.line, order;\n builder.pos = 0;\n builder.addToken = buildToken;\n // Optionally wire in some hacks into the token-rendering\n // algorithm, to deal with browser quirks.\n if (hasBadBidiRects(cm.display.measure) && (order = getOrder(line)))\n builder.addToken = buildTokenBadBidi(builder.addToken, order);\n builder.map = [];\n var allowFrontierUpdate = lineView != cm.display.externalMeasured && lineNo(line);\n insertLineContent(line, builder, getLineStyles(cm, line, allowFrontierUpdate));\n if (line.styleClasses) {\n if (line.styleClasses.bgClass)\n builder.bgClass = joinClasses(line.styleClasses.bgClass, builder.bgClass || \"\");\n if (line.styleClasses.textClass)\n builder.textClass = joinClasses(line.styleClasses.textClass, builder.textClass || \"\");\n }\n\n // Ensure at least a single node is present, for measuring.\n if (builder.map.length == 0)\n builder.map.push(0, 0, builder.content.appendChild(zeroWidthElement(cm.display.measure)));\n\n // Store the map and a cache object for the current logical line\n if (i == 0) {\n lineView.measure.map = builder.map;\n lineView.measure.cache = {};\n } else {\n (lineView.measure.maps || (lineView.measure.maps = [])).push(builder.map);\n (lineView.measure.caches || (lineView.measure.caches = [])).push({});\n }\n }\n\n // See issue #2901\n if (webkit && /\\bcm-tab\\b/.test(builder.content.lastChild.className))\n builder.content.className = \"cm-tab-wrap-hack\";\n\n signal(cm, \"renderLine\", cm, lineView.line, builder.pre);\n if (builder.pre.className)\n builder.textClass = joinClasses(builder.pre.className, builder.textClass || \"\");\n\n return builder;\n }\n\n function defaultSpecialCharPlaceholder(ch) {\n var token = elt(\"span\", \"\\u2022\", \"cm-invalidchar\");\n token.title = \"\\\\u\" + ch.charCodeAt(0).toString(16);\n token.setAttribute(\"aria-label\", token.title);\n return token;\n }\n\n // Build up the DOM representation for a single token, and add it to\n // the line map. Takes care to render special characters separately.\n function buildToken(builder, text, style, startStyle, endStyle, title, css) {\n if (!text) return;\n var displayText = builder.splitSpaces ? text.replace(/ {3,}/g, splitSpaces) : text;\n var special = builder.cm.state.specialChars, mustWrap = false;\n if (!special.test(text)) {\n builder.col += text.length;\n var content = document.createTextNode(displayText);\n builder.map.push(builder.pos, builder.pos + text.length, content);\n if (ie && ie_version < 9) mustWrap = true;\n builder.pos += text.length;\n } else {\n var content = document.createDocumentFragment(), pos = 0;\n while (true) {\n special.lastIndex = pos;\n var m = special.exec(text);\n var skipped = m ? m.index - pos : text.length - pos;\n if (skipped) {\n var txt = document.createTextNode(displayText.slice(pos, pos + skipped));\n if (ie && ie_version < 9) content.appendChild(elt(\"span\", [txt]));\n else content.appendChild(txt);\n builder.map.push(builder.pos, builder.pos + skipped, txt);\n builder.col += skipped;\n builder.pos += skipped;\n }\n if (!m) break;\n pos += skipped + 1;\n if (m[0] == \"\\t\") {\n var tabSize = builder.cm.options.tabSize, tabWidth = tabSize - builder.col % tabSize;\n var txt = content.appendChild(elt(\"span\", spaceStr(tabWidth), \"cm-tab\"));\n txt.setAttribute(\"role\", \"presentation\");\n txt.setAttribute(\"cm-text\", \"\\t\");\n builder.col += tabWidth;\n } else if (m[0] == \"\\r\" || m[0] == \"\\n\") {\n var txt = content.appendChild(elt(\"span\", m[0] == \"\\r\" ? \"\\u240d\" : \"\\u2424\", \"cm-invalidchar\"));\n txt.setAttribute(\"cm-text\", m[0]);\n builder.col += 1;\n } else {\n var txt = builder.cm.options.specialCharPlaceholder(m[0]);\n txt.setAttribute(\"cm-text\", m[0]);\n if (ie && ie_version < 9) content.appendChild(elt(\"span\", [txt]));\n else content.appendChild(txt);\n builder.col += 1;\n }\n builder.map.push(builder.pos, builder.pos + 1, txt);\n builder.pos++;\n }\n }\n if (style || startStyle || endStyle || mustWrap || css) {\n var fullStyle = style || \"\";\n if (startStyle) fullStyle += startStyle;\n if (endStyle) fullStyle += endStyle;\n var token = elt(\"span\", [content], fullStyle, css);\n if (title) token.title = title;\n return builder.content.appendChild(token);\n }\n builder.content.appendChild(content);\n }\n\n function splitSpaces(old) {\n var out = \" \";\n for (var i = 0; i < old.length - 2; ++i) out += i % 2 ? \" \" : \"\\u00a0\";\n out += \" \";\n return out;\n }\n\n // Work around nonsense dimensions being reported for stretches of\n // right-to-left text.\n function buildTokenBadBidi(inner, order) {\n return function(builder, text, style, startStyle, endStyle, title, css) {\n style = style ? style + \" cm-force-border\" : \"cm-force-border\";\n var start = builder.pos, end = start + text.length;\n for (;;) {\n // Find the part that overlaps with the start of this text\n for (var i = 0; i < order.length; i++) {\n var part = order[i];\n if (part.to > start && part.from <= start) break;\n }\n if (part.to >= end) return inner(builder, text, style, startStyle, endStyle, title, css);\n inner(builder, text.slice(0, part.to - start), style, startStyle, null, title, css);\n startStyle = null;\n text = text.slice(part.to - start);\n start = part.to;\n }\n };\n }\n\n function buildCollapsedSpan(builder, size, marker, ignoreWidget) {\n var widget = !ignoreWidget && marker.widgetNode;\n if (widget) builder.map.push(builder.pos, builder.pos + size, widget);\n if (!ignoreWidget && builder.cm.display.input.needsContentAttribute) {\n if (!widget)\n widget = builder.content.appendChild(document.createElement(\"span\"));\n widget.setAttribute(\"cm-marker\", marker.id);\n }\n if (widget) {\n builder.cm.display.input.setUneditable(widget);\n builder.content.appendChild(widget);\n }\n builder.pos += size;\n }\n\n // Outputs a number of spans to make up a line, taking highlighting\n // and marked text into account.\n function insertLineContent(line, builder, styles) {\n var spans = line.markedSpans, allText = line.text, at = 0;\n if (!spans) {\n for (var i = 1; i < styles.length; i+=2)\n builder.addToken(builder, allText.slice(at, at = styles[i]), interpretTokenStyle(styles[i+1], builder.cm.options));\n return;\n }\n\n var len = allText.length, pos = 0, i = 1, text = \"\", style, css;\n var nextChange = 0, spanStyle, spanEndStyle, spanStartStyle, title, collapsed;\n for (;;) {\n if (nextChange == pos) { // Update current marker set\n spanStyle = spanEndStyle = spanStartStyle = title = css = \"\";\n collapsed = null; nextChange = Infinity;\n var foundBookmarks = [], endStyles\n for (var j = 0; j < spans.length; ++j) {\n var sp = spans[j], m = sp.marker;\n if (m.type == \"bookmark\" && sp.from == pos && m.widgetNode) {\n foundBookmarks.push(m);\n } else if (sp.from <= pos && (sp.to == null || sp.to > pos || m.collapsed && sp.to == pos && sp.from == pos)) {\n if (sp.to != null && sp.to != pos && nextChange > sp.to) {\n nextChange = sp.to;\n spanEndStyle = \"\";\n }\n if (m.className) spanStyle += \" \" + m.className;\n if (m.css) css = (css ? css + \";\" : \"\") + m.css;\n if (m.startStyle && sp.from == pos) spanStartStyle += \" \" + m.startStyle;\n if (m.endStyle && sp.to == nextChange) (endStyles || (endStyles = [])).push(m.endStyle, sp.to)\n if (m.title && !title) title = m.title;\n if (m.collapsed && (!collapsed || compareCollapsedMarkers(collapsed.marker, m) < 0))\n collapsed = sp;\n } else if (sp.from > pos && nextChange > sp.from) {\n nextChange = sp.from;\n }\n }\n if (endStyles) for (var j = 0; j < endStyles.length; j += 2)\n if (endStyles[j + 1] == nextChange) spanEndStyle += \" \" + endStyles[j]\n\n if (!collapsed || collapsed.from == pos) for (var j = 0; j < foundBookmarks.length; ++j)\n buildCollapsedSpan(builder, 0, foundBookmarks[j]);\n if (collapsed && (collapsed.from || 0) == pos) {\n buildCollapsedSpan(builder, (collapsed.to == null ? len + 1 : collapsed.to) - pos,\n collapsed.marker, collapsed.from == null);\n if (collapsed.to == null) return;\n if (collapsed.to == pos) collapsed = false;\n }\n }\n if (pos >= len) break;\n\n var upto = Math.min(len, nextChange);\n while (true) {\n if (text) {\n var end = pos + text.length;\n if (!collapsed) {\n var tokenText = end > upto ? text.slice(0, upto - pos) : text;\n builder.addToken(builder, tokenText, style ? style + spanStyle : spanStyle,\n spanStartStyle, pos + tokenText.length == nextChange ? spanEndStyle : \"\", title, css);\n }\n if (end >= upto) {text = text.slice(upto - pos); pos = upto; break;}\n pos = end;\n spanStartStyle = \"\";\n }\n text = allText.slice(at, at = styles[i++]);\n style = interpretTokenStyle(styles[i++], builder.cm.options);\n }\n }\n }\n\n // DOCUMENT DATA STRUCTURE\n\n // By default, updates that start and end at the beginning of a line\n // are treated specially, in order to make the association of line\n // widgets and marker elements with the text behave more intuitive.\n function isWholeLineUpdate(doc, change) {\n return change.from.ch == 0 && change.to.ch == 0 && lst(change.text) == \"\" &&\n (!doc.cm || doc.cm.options.wholeLineUpdateBefore);\n }\n\n // Perform a change on the document data structure.\n function updateDoc(doc, change, markedSpans, estimateHeight) {\n function spansFor(n) {return markedSpans ? markedSpans[n] : null;}\n function update(line, text, spans) {\n updateLine(line, text, spans, estimateHeight);\n signalLater(line, \"change\", line, change);\n }\n function linesFor(start, end) {\n for (var i = start, result = []; i < end; ++i)\n result.push(new Line(text[i], spansFor(i), estimateHeight));\n return result;\n }\n\n var from = change.from, to = change.to, text = change.text;\n var firstLine = getLine(doc, from.line), lastLine = getLine(doc, to.line);\n var lastText = lst(text), lastSpans = spansFor(text.length - 1), nlines = to.line - from.line;\n\n // Adjust the line structure\n if (change.full) {\n doc.insert(0, linesFor(0, text.length));\n doc.remove(text.length, doc.size - text.length);\n } else if (isWholeLineUpdate(doc, change)) {\n // This is a whole-line replace. Treated specially to make\n // sure line objects move the way they are supposed to.\n var added = linesFor(0, text.length - 1);\n update(lastLine, lastLine.text, lastSpans);\n if (nlines) doc.remove(from.line, nlines);\n if (added.length) doc.insert(from.line, added);\n } else if (firstLine == lastLine) {\n if (text.length == 1) {\n update(firstLine, firstLine.text.slice(0, from.ch) + lastText + firstLine.text.slice(to.ch), lastSpans);\n } else {\n var added = linesFor(1, text.length - 1);\n added.push(new Line(lastText + firstLine.text.slice(to.ch), lastSpans, estimateHeight));\n update(firstLine, firstLine.text.slice(0, from.ch) + text[0], spansFor(0));\n doc.insert(from.line + 1, added);\n }\n } else if (text.length == 1) {\n update(firstLine, firstLine.text.slice(0, from.ch) + text[0] + lastLine.text.slice(to.ch), spansFor(0));\n doc.remove(from.line + 1, nlines);\n } else {\n update(firstLine, firstLine.text.slice(0, from.ch) + text[0], spansFor(0));\n update(lastLine, lastText + lastLine.text.slice(to.ch), lastSpans);\n var added = linesFor(1, text.length - 1);\n if (nlines > 1) doc.remove(from.line + 1, nlines - 1);\n doc.insert(from.line + 1, added);\n }\n\n signalLater(doc, \"change\", doc, change);\n }\n\n // The document is represented as a BTree consisting of leaves, with\n // chunk of lines in them, and branches, with up to ten leaves or\n // other branch nodes below them. The top node is always a branch\n // node, and is the document object itself (meaning it has\n // additional methods and properties).\n //\n // All nodes have parent links. The tree is used both to go from\n // line numbers to line objects, and to go from objects to numbers.\n // It also indexes by height, and is used to convert between height\n // and line object, and to find the total height of the document.\n //\n // See also http://marijnhaverbeke.nl/blog/codemirror-line-tree.html\n\n function LeafChunk(lines) {\n this.lines = lines;\n this.parent = null;\n for (var i = 0, height = 0; i < lines.length; ++i) {\n lines[i].parent = this;\n height += lines[i].height;\n }\n this.height = height;\n }\n\n LeafChunk.prototype = {\n chunkSize: function() { return this.lines.length; },\n // Remove the n lines at offset 'at'.\n removeInner: function(at, n) {\n for (var i = at, e = at + n; i < e; ++i) {\n var line = this.lines[i];\n this.height -= line.height;\n cleanUpLine(line);\n signalLater(line, \"delete\");\n }\n this.lines.splice(at, n);\n },\n // Helper used to collapse a small branch into a single leaf.\n collapse: function(lines) {\n lines.push.apply(lines, this.lines);\n },\n // Insert the given array of lines at offset 'at', count them as\n // having the given height.\n insertInner: function(at, lines, height) {\n this.height += height;\n this.lines = this.lines.slice(0, at).concat(lines).concat(this.lines.slice(at));\n for (var i = 0; i < lines.length; ++i) lines[i].parent = this;\n },\n // Used to iterate over a part of the tree.\n iterN: function(at, n, op) {\n for (var e = at + n; at < e; ++at)\n if (op(this.lines[at])) return true;\n }\n };\n\n function BranchChunk(children) {\n this.children = children;\n var size = 0, height = 0;\n for (var i = 0; i < children.length; ++i) {\n var ch = children[i];\n size += ch.chunkSize(); height += ch.height;\n ch.parent = this;\n }\n this.size = size;\n this.height = height;\n this.parent = null;\n }\n\n BranchChunk.prototype = {\n chunkSize: function() { return this.size; },\n removeInner: function(at, n) {\n this.size -= n;\n for (var i = 0; i < this.children.length; ++i) {\n var child = this.children[i], sz = child.chunkSize();\n if (at < sz) {\n var rm = Math.min(n, sz - at), oldHeight = child.height;\n child.removeInner(at, rm);\n this.height -= oldHeight - child.height;\n if (sz == rm) { this.children.splice(i--, 1); child.parent = null; }\n if ((n -= rm) == 0) break;\n at = 0;\n } else at -= sz;\n }\n // If the result is smaller than 25 lines, ensure that it is a\n // single leaf node.\n if (this.size - n < 25 &&\n (this.children.length > 1 || !(this.children[0] instanceof LeafChunk))) {\n var lines = [];\n this.collapse(lines);\n this.children = [new LeafChunk(lines)];\n this.children[0].parent = this;\n }\n },\n collapse: function(lines) {\n for (var i = 0; i < this.children.length; ++i) this.children[i].collapse(lines);\n },\n insertInner: function(at, lines, height) {\n this.size += lines.length;\n this.height += height;\n for (var i = 0; i < this.children.length; ++i) {\n var child = this.children[i], sz = child.chunkSize();\n if (at <= sz) {\n child.insertInner(at, lines, height);\n if (child.lines && child.lines.length > 50) {\n while (child.lines.length > 50) {\n var spilled = child.lines.splice(child.lines.length - 25, 25);\n var newleaf = new LeafChunk(spilled);\n child.height -= newleaf.height;\n this.children.splice(i + 1, 0, newleaf);\n newleaf.parent = this;\n }\n this.maybeSpill();\n }\n break;\n }\n at -= sz;\n }\n },\n // When a node has grown, check whether it should be split.\n maybeSpill: function() {\n if (this.children.length <= 10) return;\n var me = this;\n do {\n var spilled = me.children.splice(me.children.length - 5, 5);\n var sibling = new BranchChunk(spilled);\n if (!me.parent) { // Become the parent node\n var copy = new BranchChunk(me.children);\n copy.parent = me;\n me.children = [copy, sibling];\n me = copy;\n } else {\n me.size -= sibling.size;\n me.height -= sibling.height;\n var myIndex = indexOf(me.parent.children, me);\n me.parent.children.splice(myIndex + 1, 0, sibling);\n }\n sibling.parent = me.parent;\n } while (me.children.length > 10);\n me.parent.maybeSpill();\n },\n iterN: function(at, n, op) {\n for (var i = 0; i < this.children.length; ++i) {\n var child = this.children[i], sz = child.chunkSize();\n if (at < sz) {\n var used = Math.min(n, sz - at);\n if (child.iterN(at, used, op)) return true;\n if ((n -= used) == 0) break;\n at = 0;\n } else at -= sz;\n }\n }\n };\n\n var nextDocId = 0;\n var Doc = CodeMirror.Doc = function(text, mode, firstLine, lineSep) {\n if (!(this instanceof Doc)) return new Doc(text, mode, firstLine, lineSep);\n if (firstLine == null) firstLine = 0;\n\n BranchChunk.call(this, [new LeafChunk([new Line(\"\", null)])]);\n this.first = firstLine;\n this.scrollTop = this.scrollLeft = 0;\n this.cantEdit = false;\n this.cleanGeneration = 1;\n this.frontier = firstLine;\n var start = Pos(firstLine, 0);\n this.sel = simpleSelection(start);\n this.history = new History(null);\n this.id = ++nextDocId;\n this.modeOption = mode;\n this.lineSep = lineSep;\n this.extend = false;\n\n if (typeof text == \"string\") text = this.splitLines(text);\n updateDoc(this, {from: start, to: start, text: text});\n setSelection(this, simpleSelection(start), sel_dontScroll);\n };\n\n Doc.prototype = createObj(BranchChunk.prototype, {\n constructor: Doc,\n // Iterate over the document. Supports two forms -- with only one\n // argument, it calls that for each line in the document. With\n // three, it iterates over the range given by the first two (with\n // the second being non-inclusive).\n iter: function(from, to, op) {\n if (op) this.iterN(from - this.first, to - from, op);\n else this.iterN(this.first, this.first + this.size, from);\n },\n\n // Non-public interface for adding and removing lines.\n insert: function(at, lines) {\n var height = 0;\n for (var i = 0; i < lines.length; ++i) height += lines[i].height;\n this.insertInner(at - this.first, lines, height);\n },\n remove: function(at, n) { this.removeInner(at - this.first, n); },\n\n // From here, the methods are part of the public interface. Most\n // are also available from CodeMirror (editor) instances.\n\n getValue: function(lineSep) {\n var lines = getLines(this, this.first, this.first + this.size);\n if (lineSep === false) return lines;\n return lines.join(lineSep || this.lineSeparator());\n },\n setValue: docMethodOp(function(code) {\n var top = Pos(this.first, 0), last = this.first + this.size - 1;\n makeChange(this, {from: top, to: Pos(last, getLine(this, last).text.length),\n text: this.splitLines(code), origin: \"setValue\", full: true}, true);\n setSelection(this, simpleSelection(top));\n }),\n replaceRange: function(code, from, to, origin) {\n from = clipPos(this, from);\n to = to ? clipPos(this, to) : from;\n replaceRange(this, code, from, to, origin);\n },\n getRange: function(from, to, lineSep) {\n var lines = getBetween(this, clipPos(this, from), clipPos(this, to));\n if (lineSep === false) return lines;\n return lines.join(lineSep || this.lineSeparator());\n },\n\n getLine: function(line) {var l = this.getLineHandle(line); return l && l.text;},\n\n getLineHandle: function(line) {if (isLine(this, line)) return getLine(this, line);},\n getLineNumber: function(line) {return lineNo(line);},\n\n getLineHandleVisualStart: function(line) {\n if (typeof line == \"number\") line = getLine(this, line);\n return visualLine(line);\n },\n\n lineCount: function() {return this.size;},\n firstLine: function() {return this.first;},\n lastLine: function() {return this.first + this.size - 1;},\n\n clipPos: function(pos) {return clipPos(this, pos);},\n\n getCursor: function(start) {\n var range = this.sel.primary(), pos;\n if (start == null || start == \"head\") pos = range.head;\n else if (start == \"anchor\") pos = range.anchor;\n else if (start == \"end\" || start == \"to\" || start === false) pos = range.to();\n else pos = range.from();\n return pos;\n },\n listSelections: function() { return this.sel.ranges; },\n somethingSelected: function() {return this.sel.somethingSelected();},\n\n setCursor: docMethodOp(function(line, ch, options) {\n setSimpleSelection(this, clipPos(this, typeof line == \"number\" ? Pos(line, ch || 0) : line), null, options);\n }),\n setSelection: docMethodOp(function(anchor, head, options) {\n setSimpleSelection(this, clipPos(this, anchor), clipPos(this, head || anchor), options);\n }),\n extendSelection: docMethodOp(function(head, other, options) {\n extendSelection(this, clipPos(this, head), other && clipPos(this, other), options);\n }),\n extendSelections: docMethodOp(function(heads, options) {\n extendSelections(this, clipPosArray(this, heads), options);\n }),\n extendSelectionsBy: docMethodOp(function(f, options) {\n var heads = map(this.sel.ranges, f);\n extendSelections(this, clipPosArray(this, heads), options);\n }),\n setSelections: docMethodOp(function(ranges, primary, options) {\n if (!ranges.length) return;\n for (var i = 0, out = []; i < ranges.length; i++)\n out[i] = new Range(clipPos(this, ranges[i].anchor),\n clipPos(this, ranges[i].head));\n if (primary == null) primary = Math.min(ranges.length - 1, this.sel.primIndex);\n setSelection(this, normalizeSelection(out, primary), options);\n }),\n addSelection: docMethodOp(function(anchor, head, options) {\n var ranges = this.sel.ranges.slice(0);\n ranges.push(new Range(clipPos(this, anchor), clipPos(this, head || anchor)));\n setSelection(this, normalizeSelection(ranges, ranges.length - 1), options);\n }),\n\n getSelection: function(lineSep) {\n var ranges = this.sel.ranges, lines;\n for (var i = 0; i < ranges.length; i++) {\n var sel = getBetween(this, ranges[i].from(), ranges[i].to());\n lines = lines ? lines.concat(sel) : sel;\n }\n if (lineSep === false) return lines;\n else return lines.join(lineSep || this.lineSeparator());\n },\n getSelections: function(lineSep) {\n var parts = [], ranges = this.sel.ranges;\n for (var i = 0; i < ranges.length; i++) {\n var sel = getBetween(this, ranges[i].from(), ranges[i].to());\n if (lineSep !== false) sel = sel.join(lineSep || this.lineSeparator());\n parts[i] = sel;\n }\n return parts;\n },\n replaceSelection: function(code, collapse, origin) {\n var dup = [];\n for (var i = 0; i < this.sel.ranges.length; i++)\n dup[i] = code;\n this.replaceSelections(dup, collapse, origin || \"+input\");\n },\n replaceSelections: docMethodOp(function(code, collapse, origin) {\n var changes = [], sel = this.sel;\n for (var i = 0; i < sel.ranges.length; i++) {\n var range = sel.ranges[i];\n changes[i] = {from: range.from(), to: range.to(), text: this.splitLines(code[i]), origin: origin};\n }\n var newSel = collapse && collapse != \"end\" && computeReplacedSel(this, changes, collapse);\n for (var i = changes.length - 1; i >= 0; i--)\n makeChange(this, changes[i]);\n if (newSel) setSelectionReplaceHistory(this, newSel);\n else if (this.cm) ensureCursorVisible(this.cm);\n }),\n undo: docMethodOp(function() {makeChangeFromHistory(this, \"undo\");}),\n redo: docMethodOp(function() {makeChangeFromHistory(this, \"redo\");}),\n undoSelection: docMethodOp(function() {makeChangeFromHistory(this, \"undo\", true);}),\n redoSelection: docMethodOp(function() {makeChangeFromHistory(this, \"redo\", true);}),\n\n setExtending: function(val) {this.extend = val;},\n getExtending: function() {return this.extend;},\n\n historySize: function() {\n var hist = this.history, done = 0, undone = 0;\n for (var i = 0; i < hist.done.length; i++) if (!hist.done[i].ranges) ++done;\n for (var i = 0; i < hist.undone.length; i++) if (!hist.undone[i].ranges) ++undone;\n return {undo: done, redo: undone};\n },\n clearHistory: function() {this.history = new History(this.history.maxGeneration);},\n\n markClean: function() {\n this.cleanGeneration = this.changeGeneration(true);\n },\n changeGeneration: function(forceSplit) {\n if (forceSplit)\n this.history.lastOp = this.history.lastSelOp = this.history.lastOrigin = null;\n return this.history.generation;\n },\n isClean: function (gen) {\n return this.history.generation == (gen || this.cleanGeneration);\n },\n\n getHistory: function() {\n return {done: copyHistoryArray(this.history.done),\n undone: copyHistoryArray(this.history.undone)};\n },\n setHistory: function(histData) {\n var hist = this.history = new History(this.history.maxGeneration);\n hist.done = copyHistoryArray(histData.done.slice(0), null, true);\n hist.undone = copyHistoryArray(histData.undone.slice(0), null, true);\n },\n\n addLineClass: docMethodOp(function(handle, where, cls) {\n return changeLine(this, handle, where == \"gutter\" ? \"gutter\" : \"class\", function(line) {\n var prop = where == \"text\" ? \"textClass\"\n : where == \"background\" ? \"bgClass\"\n : where == \"gutter\" ? \"gutterClass\" : \"wrapClass\";\n if (!line[prop]) line[prop] = cls;\n else if (classTest(cls).test(line[prop])) return false;\n else line[prop] += \" \" + cls;\n return true;\n });\n }),\n removeLineClass: docMethodOp(function(handle, where, cls) {\n return changeLine(this, handle, where == \"gutter\" ? \"gutter\" : \"class\", function(line) {\n var prop = where == \"text\" ? \"textClass\"\n : where == \"background\" ? \"bgClass\"\n : where == \"gutter\" ? \"gutterClass\" : \"wrapClass\";\n var cur = line[prop];\n if (!cur) return false;\n else if (cls == null) line[prop] = null;\n else {\n var found = cur.match(classTest(cls));\n if (!found) return false;\n var end = found.index + found[0].length;\n line[prop] = cur.slice(0, found.index) + (!found.index || end == cur.length ? \"\" : \" \") + cur.slice(end) || null;\n }\n return true;\n });\n }),\n\n addLineWidget: docMethodOp(function(handle, node, options) {\n return addLineWidget(this, handle, node, options);\n }),\n removeLineWidget: function(widget) { widget.clear(); },\n\n markText: function(from, to, options) {\n return markText(this, clipPos(this, from), clipPos(this, to), options, options && options.type || \"range\");\n },\n setBookmark: function(pos, options) {\n var realOpts = {replacedWith: options && (options.nodeType == null ? options.widget : options),\n insertLeft: options && options.insertLeft,\n clearWhenEmpty: false, shared: options && options.shared,\n handleMouseEvents: options && options.handleMouseEvents};\n pos = clipPos(this, pos);\n return markText(this, pos, pos, realOpts, \"bookmark\");\n },\n findMarksAt: function(pos) {\n pos = clipPos(this, pos);\n var markers = [], spans = getLine(this, pos.line).markedSpans;\n if (spans) for (var i = 0; i < spans.length; ++i) {\n var span = spans[i];\n if ((span.from == null || span.from <= pos.ch) &&\n (span.to == null || span.to >= pos.ch))\n markers.push(span.marker.parent || span.marker);\n }\n return markers;\n },\n findMarks: function(from, to, filter) {\n from = clipPos(this, from); to = clipPos(this, to);\n var found = [], lineNo = from.line;\n this.iter(from.line, to.line + 1, function(line) {\n var spans = line.markedSpans;\n if (spans) for (var i = 0; i < spans.length; i++) {\n var span = spans[i];\n if (!(span.to != null && lineNo == from.line && from.ch > span.to ||\n span.from == null && lineNo != from.line ||\n span.from != null && lineNo == to.line && span.from > to.ch) &&\n (!filter || filter(span.marker)))\n found.push(span.marker.parent || span.marker);\n }\n ++lineNo;\n });\n return found;\n },\n getAllMarks: function() {\n var markers = [];\n this.iter(function(line) {\n var sps = line.markedSpans;\n if (sps) for (var i = 0; i < sps.length; ++i)\n if (sps[i].from != null) markers.push(sps[i].marker);\n });\n return markers;\n },\n\n posFromIndex: function(off) {\n var ch, lineNo = this.first;\n this.iter(function(line) {\n var sz = line.text.length + 1;\n if (sz > off) { ch = off; return true; }\n off -= sz;\n ++lineNo;\n });\n return clipPos(this, Pos(lineNo, ch));\n },\n indexFromPos: function (coords) {\n coords = clipPos(this, coords);\n var index = coords.ch;\n if (coords.line < this.first || coords.ch < 0) return 0;\n this.iter(this.first, coords.line, function (line) {\n index += line.text.length + 1;\n });\n return index;\n },\n\n copy: function(copyHistory) {\n var doc = new Doc(getLines(this, this.first, this.first + this.size),\n this.modeOption, this.first, this.lineSep);\n doc.scrollTop = this.scrollTop; doc.scrollLeft = this.scrollLeft;\n doc.sel = this.sel;\n doc.extend = false;\n if (copyHistory) {\n doc.history.undoDepth = this.history.undoDepth;\n doc.setHistory(this.getHistory());\n }\n return doc;\n },\n\n linkedDoc: function(options) {\n if (!options) options = {};\n var from = this.first, to = this.first + this.size;\n if (options.from != null && options.from > from) from = options.from;\n if (options.to != null && options.to < to) to = options.to;\n var copy = new Doc(getLines(this, from, to), options.mode || this.modeOption, from, this.lineSep);\n if (options.sharedHist) copy.history = this.history;\n (this.linked || (this.linked = [])).push({doc: copy, sharedHist: options.sharedHist});\n copy.linked = [{doc: this, isParent: true, sharedHist: options.sharedHist}];\n copySharedMarkers(copy, findSharedMarkers(this));\n return copy;\n },\n unlinkDoc: function(other) {\n if (other instanceof CodeMirror) other = other.doc;\n if (this.linked) for (var i = 0; i < this.linked.length; ++i) {\n var link = this.linked[i];\n if (link.doc != other) continue;\n this.linked.splice(i, 1);\n other.unlinkDoc(this);\n detachSharedMarkers(findSharedMarkers(this));\n break;\n }\n // If the histories were shared, split them again\n if (other.history == this.history) {\n var splitIds = [other.id];\n linkedDocs(other, function(doc) {splitIds.push(doc.id);}, true);\n other.history = new History(null);\n other.history.done = copyHistoryArray(this.history.done, splitIds);\n other.history.undone = copyHistoryArray(this.history.undone, splitIds);\n }\n },\n iterLinkedDocs: function(f) {linkedDocs(this, f);},\n\n getMode: function() {return this.mode;},\n getEditor: function() {return this.cm;},\n\n splitLines: function(str) {\n if (this.lineSep) return str.split(this.lineSep);\n return splitLinesAuto(str);\n },\n lineSeparator: function() { return this.lineSep || \"\\n\"; }\n });\n\n // Public alias.\n Doc.prototype.eachLine = Doc.prototype.iter;\n\n // Set up methods on CodeMirror's prototype to redirect to the editor's document.\n var dontDelegate = \"iter insert remove copy getEditor constructor\".split(\" \");\n for (var prop in Doc.prototype) if (Doc.prototype.hasOwnProperty(prop) && indexOf(dontDelegate, prop) < 0)\n CodeMirror.prototype[prop] = (function(method) {\n return function() {return method.apply(this.doc, arguments);};\n })(Doc.prototype[prop]);\n\n eventMixin(Doc);\n\n // Call f for all linked documents.\n function linkedDocs(doc, f, sharedHistOnly) {\n function propagate(doc, skip, sharedHist) {\n if (doc.linked) for (var i = 0; i < doc.linked.length; ++i) {\n var rel = doc.linked[i];\n if (rel.doc == skip) continue;\n var shared = sharedHist && rel.sharedHist;\n if (sharedHistOnly && !shared) continue;\n f(rel.doc, shared);\n propagate(rel.doc, doc, shared);\n }\n }\n propagate(doc, null, true);\n }\n\n // Attach a document to an editor.\n function attachDoc(cm, doc) {\n if (doc.cm) throw new Error(\"This document is already in use.\");\n cm.doc = doc;\n doc.cm = cm;\n estimateLineHeights(cm);\n loadMode(cm);\n if (!cm.options.lineWrapping) findMaxLine(cm);\n cm.options.mode = doc.modeOption;\n regChange(cm);\n }\n\n // LINE UTILITIES\n\n // Find the line object corresponding to the given line number.\n function getLine(doc, n) {\n n -= doc.first;\n if (n < 0 || n >= doc.size) throw new Error(\"There is no line \" + (n + doc.first) + \" in the document.\");\n for (var chunk = doc; !chunk.lines;) {\n for (var i = 0;; ++i) {\n var child = chunk.children[i], sz = child.chunkSize();\n if (n < sz) { chunk = child; break; }\n n -= sz;\n }\n }\n return chunk.lines[n];\n }\n\n // Get the part of a document between two positions, as an array of\n // strings.\n function getBetween(doc, start, end) {\n var out = [], n = start.line;\n doc.iter(start.line, end.line + 1, function(line) {\n var text = line.text;\n if (n == end.line) text = text.slice(0, end.ch);\n if (n == start.line) text = text.slice(start.ch);\n out.push(text);\n ++n;\n });\n return out;\n }\n // Get the lines between from and to, as array of strings.\n function getLines(doc, from, to) {\n var out = [];\n doc.iter(from, to, function(line) { out.push(line.text); });\n return out;\n }\n\n // Update the height of a line, propagating the height change\n // upwards to parent nodes.\n function updateLineHeight(line, height) {\n var diff = height - line.height;\n if (diff) for (var n = line; n; n = n.parent) n.height += diff;\n }\n\n // Given a line object, find its line number by walking up through\n // its parent links.\n function lineNo(line) {\n if (line.parent == null) return null;\n var cur = line.parent, no = indexOf(cur.lines, line);\n for (var chunk = cur.parent; chunk; cur = chunk, chunk = chunk.parent) {\n for (var i = 0;; ++i) {\n if (chunk.children[i] == cur) break;\n no += chunk.children[i].chunkSize();\n }\n }\n return no + cur.first;\n }\n\n // Find the line at the given vertical position, using the height\n // information in the document tree.\n function lineAtHeight(chunk, h) {\n var n = chunk.first;\n outer: do {\n for (var i = 0; i < chunk.children.length; ++i) {\n var child = chunk.children[i], ch = child.height;\n if (h < ch) { chunk = child; continue outer; }\n h -= ch;\n n += child.chunkSize();\n }\n return n;\n } while (!chunk.lines);\n for (var i = 0; i < chunk.lines.length; ++i) {\n var line = chunk.lines[i], lh = line.height;\n if (h < lh) break;\n h -= lh;\n }\n return n + i;\n }\n\n\n // Find the height above the given line.\n function heightAtLine(lineObj) {\n lineObj = visualLine(lineObj);\n\n var h = 0, chunk = lineObj.parent;\n for (var i = 0; i < chunk.lines.length; ++i) {\n var line = chunk.lines[i];\n if (line == lineObj) break;\n else h += line.height;\n }\n for (var p = chunk.parent; p; chunk = p, p = chunk.parent) {\n for (var i = 0; i < p.children.length; ++i) {\n var cur = p.children[i];\n if (cur == chunk) break;\n else h += cur.height;\n }\n }\n return h;\n }\n\n // Get the bidi ordering for the given line (and cache it). Returns\n // false for lines that are fully left-to-right, and an array of\n // BidiSpan objects otherwise.\n function getOrder(line) {\n var order = line.order;\n if (order == null) order = line.order = bidiOrdering(line.text);\n return order;\n }\n\n // HISTORY\n\n function History(startGen) {\n // Arrays of change events and selections. Doing something adds an\n // event to done and clears undo. Undoing moves events from done\n // to undone, redoing moves them in the other direction.\n this.done = []; this.undone = [];\n this.undoDepth = Infinity;\n // Used to track when changes can be merged into a single undo\n // event\n this.lastModTime = this.lastSelTime = 0;\n this.lastOp = this.lastSelOp = null;\n this.lastOrigin = this.lastSelOrigin = null;\n // Used by the isClean() method\n this.generation = this.maxGeneration = startGen || 1;\n }\n\n // Create a history change event from an updateDoc-style change\n // object.\n function historyChangeFromChange(doc, change) {\n var histChange = {from: copyPos(change.from), to: changeEnd(change), text: getBetween(doc, change.from, change.to)};\n attachLocalSpans(doc, histChange, change.from.line, change.to.line + 1);\n linkedDocs(doc, function(doc) {attachLocalSpans(doc, histChange, change.from.line, change.to.line + 1);}, true);\n return histChange;\n }\n\n // Pop all selection events off the end of a history array. Stop at\n // a change event.\n function clearSelectionEvents(array) {\n while (array.length) {\n var last = lst(array);\n if (last.ranges) array.pop();\n else break;\n }\n }\n\n // Find the top change event in the history. Pop off selection\n // events that are in the way.\n function lastChangeEvent(hist, force) {\n if (force) {\n clearSelectionEvents(hist.done);\n return lst(hist.done);\n } else if (hist.done.length && !lst(hist.done).ranges) {\n return lst(hist.done);\n } else if (hist.done.length > 1 && !hist.done[hist.done.length - 2].ranges) {\n hist.done.pop();\n return lst(hist.done);\n }\n }\n\n // Register a change in the history. Merges changes that are within\n // a single operation, ore are close together with an origin that\n // allows merging (starting with \"+\") into a single event.\n function addChangeToHistory(doc, change, selAfter, opId) {\n var hist = doc.history;\n hist.undone.length = 0;\n var time = +new Date, cur;\n\n if ((hist.lastOp == opId ||\n hist.lastOrigin == change.origin && change.origin &&\n ((change.origin.charAt(0) == \"+\" && doc.cm && hist.lastModTime > time - doc.cm.options.historyEventDelay) ||\n change.origin.charAt(0) == \"*\")) &&\n (cur = lastChangeEvent(hist, hist.lastOp == opId))) {\n // Merge this change into the last event\n var last = lst(cur.changes);\n if (cmp(change.from, change.to) == 0 && cmp(change.from, last.to) == 0) {\n // Optimized case for simple insertion -- don't want to add\n // new changesets for every character typed\n last.to = changeEnd(change);\n } else {\n // Add new sub-event\n cur.changes.push(historyChangeFromChange(doc, change));\n }\n } else {\n // Can not be merged, start a new event.\n var before = lst(hist.done);\n if (!before || !before.ranges)\n pushSelectionToHistory(doc.sel, hist.done);\n cur = {changes: [historyChangeFromChange(doc, change)],\n generation: hist.generation};\n hist.done.push(cur);\n while (hist.done.length > hist.undoDepth) {\n hist.done.shift();\n if (!hist.done[0].ranges) hist.done.shift();\n }\n }\n hist.done.push(selAfter);\n hist.generation = ++hist.maxGeneration;\n hist.lastModTime = hist.lastSelTime = time;\n hist.lastOp = hist.lastSelOp = opId;\n hist.lastOrigin = hist.lastSelOrigin = change.origin;\n\n if (!last) signal(doc, \"historyAdded\");\n }\n\n function selectionEventCanBeMerged(doc, origin, prev, sel) {\n var ch = origin.charAt(0);\n return ch == \"*\" ||\n ch == \"+\" &&\n prev.ranges.length == sel.ranges.length &&\n prev.somethingSelected() == sel.somethingSelected() &&\n new Date - doc.history.lastSelTime <= (doc.cm ? doc.cm.options.historyEventDelay : 500);\n }\n\n // Called whenever the selection changes, sets the new selection as\n // the pending selection in the history, and pushes the old pending\n // selection into the 'done' array when it was significantly\n // different (in number of selected ranges, emptiness, or time).\n function addSelectionToHistory(doc, sel, opId, options) {\n var hist = doc.history, origin = options && options.origin;\n\n // A new event is started when the previous origin does not match\n // the current, or the origins don't allow matching. Origins\n // starting with * are always merged, those starting with + are\n // merged when similar and close together in time.\n if (opId == hist.lastSelOp ||\n (origin && hist.lastSelOrigin == origin &&\n (hist.lastModTime == hist.lastSelTime && hist.lastOrigin == origin ||\n selectionEventCanBeMerged(doc, origin, lst(hist.done), sel))))\n hist.done[hist.done.length - 1] = sel;\n else\n pushSelectionToHistory(sel, hist.done);\n\n hist.lastSelTime = +new Date;\n hist.lastSelOrigin = origin;\n hist.lastSelOp = opId;\n if (options && options.clearRedo !== false)\n clearSelectionEvents(hist.undone);\n }\n\n function pushSelectionToHistory(sel, dest) {\n var top = lst(dest);\n if (!(top && top.ranges && top.equals(sel)))\n dest.push(sel);\n }\n\n // Used to store marked span information in the history.\n function attachLocalSpans(doc, change, from, to) {\n var existing = change[\"spans_\" + doc.id], n = 0;\n doc.iter(Math.max(doc.first, from), Math.min(doc.first + doc.size, to), function(line) {\n if (line.markedSpans)\n (existing || (existing = change[\"spans_\" + doc.id] = {}))[n] = line.markedSpans;\n ++n;\n });\n }\n\n // When un/re-doing restores text containing marked spans, those\n // that have been explicitly cleared should not be restored.\n function removeClearedSpans(spans) {\n if (!spans) return null;\n for (var i = 0, out; i < spans.length; ++i) {\n if (spans[i].marker.explicitlyCleared) { if (!out) out = spans.slice(0, i); }\n else if (out) out.push(spans[i]);\n }\n return !out ? spans : out.length ? out : null;\n }\n\n // Retrieve and filter the old marked spans stored in a change event.\n function getOldSpans(doc, change) {\n var found = change[\"spans_\" + doc.id];\n if (!found) return null;\n for (var i = 0, nw = []; i < change.text.length; ++i)\n nw.push(removeClearedSpans(found[i]));\n return nw;\n }\n\n // Used both to provide a JSON-safe object in .getHistory, and, when\n // detaching a document, to split the history in two\n function copyHistoryArray(events, newGroup, instantiateSel) {\n for (var i = 0, copy = []; i < events.length; ++i) {\n var event = events[i];\n if (event.ranges) {\n copy.push(instantiateSel ? Selection.prototype.deepCopy.call(event) : event);\n continue;\n }\n var changes = event.changes, newChanges = [];\n copy.push({changes: newChanges});\n for (var j = 0; j < changes.length; ++j) {\n var change = changes[j], m;\n newChanges.push({from: change.from, to: change.to, text: change.text});\n if (newGroup) for (var prop in change) if (m = prop.match(/^spans_(\\d+)$/)) {\n if (indexOf(newGroup, Number(m[1])) > -1) {\n lst(newChanges)[prop] = change[prop];\n delete change[prop];\n }\n }\n }\n }\n return copy;\n }\n\n // Rebasing/resetting history to deal with externally-sourced changes\n\n function rebaseHistSelSingle(pos, from, to, diff) {\n if (to < pos.line) {\n pos.line += diff;\n } else if (from < pos.line) {\n pos.line = from;\n pos.ch = 0;\n }\n }\n\n // Tries to rebase an array of history events given a change in the\n // document. If the change touches the same lines as the event, the\n // event, and everything 'behind' it, is discarded. If the change is\n // before the event, the event's positions are updated. Uses a\n // copy-on-write scheme for the positions, to avoid having to\n // reallocate them all on every rebase, but also avoid problems with\n // shared position objects being unsafely updated.\n function rebaseHistArray(array, from, to, diff) {\n for (var i = 0; i < array.length; ++i) {\n var sub = array[i], ok = true;\n if (sub.ranges) {\n if (!sub.copied) { sub = array[i] = sub.deepCopy(); sub.copied = true; }\n for (var j = 0; j < sub.ranges.length; j++) {\n rebaseHistSelSingle(sub.ranges[j].anchor, from, to, diff);\n rebaseHistSelSingle(sub.ranges[j].head, from, to, diff);\n }\n continue;\n }\n for (var j = 0; j < sub.changes.length; ++j) {\n var cur = sub.changes[j];\n if (to < cur.from.line) {\n cur.from = Pos(cur.from.line + diff, cur.from.ch);\n cur.to = Pos(cur.to.line + diff, cur.to.ch);\n } else if (from <= cur.to.line) {\n ok = false;\n break;\n }\n }\n if (!ok) {\n array.splice(0, i + 1);\n i = 0;\n }\n }\n }\n\n function rebaseHist(hist, change) {\n var from = change.from.line, to = change.to.line, diff = change.text.length - (to - from) - 1;\n rebaseHistArray(hist.done, from, to, diff);\n rebaseHistArray(hist.undone, from, to, diff);\n }\n\n // EVENT UTILITIES\n\n // Due to the fact that we still support jurassic IE versions, some\n // compatibility wrappers are needed.\n\n var e_preventDefault = CodeMirror.e_preventDefault = function(e) {\n if (e.preventDefault) e.preventDefault();\n else e.returnValue = false;\n };\n var e_stopPropagation = CodeMirror.e_stopPropagation = function(e) {\n if (e.stopPropagation) e.stopPropagation();\n else e.cancelBubble = true;\n };\n function e_defaultPrevented(e) {\n return e.defaultPrevented != null ? e.defaultPrevented : e.returnValue == false;\n }\n var e_stop = CodeMirror.e_stop = function(e) {e_preventDefault(e); e_stopPropagation(e);};\n\n function e_target(e) {return e.target || e.srcElement;}\n function e_button(e) {\n var b = e.which;\n if (b == null) {\n if (e.button & 1) b = 1;\n else if (e.button & 2) b = 3;\n else if (e.button & 4) b = 2;\n }\n if (mac && e.ctrlKey && b == 1) b = 3;\n return b;\n }\n\n // EVENT HANDLING\n\n // Lightweight event framework. on/off also work on DOM nodes,\n // registering native DOM handlers.\n\n var on = CodeMirror.on = function(emitter, type, f) {\n if (emitter.addEventListener)\n emitter.addEventListener(type, f, false);\n else if (emitter.attachEvent)\n emitter.attachEvent(\"on\" + type, f);\n else {\n var map = emitter._handlers || (emitter._handlers = {});\n var arr = map[type] || (map[type] = []);\n arr.push(f);\n }\n };\n\n var noHandlers = []\n function getHandlers(emitter, type, copy) {\n var arr = emitter._handlers && emitter._handlers[type]\n if (copy) return arr && arr.length > 0 ? arr.slice() : noHandlers\n else return arr || noHandlers\n }\n\n var off = CodeMirror.off = function(emitter, type, f) {\n if (emitter.removeEventListener)\n emitter.removeEventListener(type, f, false);\n else if (emitter.detachEvent)\n emitter.detachEvent(\"on\" + type, f);\n else {\n var handlers = getHandlers(emitter, type, false)\n for (var i = 0; i < handlers.length; ++i)\n if (handlers[i] == f) { handlers.splice(i, 1); break; }\n }\n };\n\n var signal = CodeMirror.signal = function(emitter, type /*, values...*/) {\n var handlers = getHandlers(emitter, type, true)\n if (!handlers.length) return;\n var args = Array.prototype.slice.call(arguments, 2);\n for (var i = 0; i < handlers.length; ++i) handlers[i].apply(null, args);\n };\n\n var orphanDelayedCallbacks = null;\n\n // Often, we want to signal events at a point where we are in the\n // middle of some work, but don't want the handler to start calling\n // other methods on the editor, which might be in an inconsistent\n // state or simply not expect any other events to happen.\n // signalLater looks whether there are any handlers, and schedules\n // them to be executed when the last operation ends, or, if no\n // operation is active, when a timeout fires.\n function signalLater(emitter, type /*, values...*/) {\n var arr = getHandlers(emitter, type, false)\n if (!arr.length) return;\n var args = Array.prototype.slice.call(arguments, 2), list;\n if (operationGroup) {\n list = operationGroup.delayedCallbacks;\n } else if (orphanDelayedCallbacks) {\n list = orphanDelayedCallbacks;\n } else {\n list = orphanDelayedCallbacks = [];\n setTimeout(fireOrphanDelayed, 0);\n }\n function bnd(f) {return function(){f.apply(null, args);};};\n for (var i = 0; i < arr.length; ++i)\n list.push(bnd(arr[i]));\n }\n\n function fireOrphanDelayed() {\n var delayed = orphanDelayedCallbacks;\n orphanDelayedCallbacks = null;\n for (var i = 0; i < delayed.length; ++i) delayed[i]();\n }\n\n // The DOM events that CodeMirror handles can be overridden by\n // registering a (non-DOM) handler on the editor for the event name,\n // and preventDefault-ing the event in that handler.\n function signalDOMEvent(cm, e, override) {\n if (typeof e == \"string\")\n e = {type: e, preventDefault: function() { this.defaultPrevented = true; }};\n signal(cm, override || e.type, cm, e);\n return e_defaultPrevented(e) || e.codemirrorIgnore;\n }\n\n function signalCursorActivity(cm) {\n var arr = cm._handlers && cm._handlers.cursorActivity;\n if (!arr) return;\n var set = cm.curOp.cursorActivityHandlers || (cm.curOp.cursorActivityHandlers = []);\n for (var i = 0; i < arr.length; ++i) if (indexOf(set, arr[i]) == -1)\n set.push(arr[i]);\n }\n\n function hasHandler(emitter, type) {\n return getHandlers(emitter, type).length > 0\n }\n\n // Add on and off methods to a constructor's prototype, to make\n // registering events on such objects more convenient.\n function eventMixin(ctor) {\n ctor.prototype.on = function(type, f) {on(this, type, f);};\n ctor.prototype.off = function(type, f) {off(this, type, f);};\n }\n\n // MISC UTILITIES\n\n // Number of pixels added to scroller and sizer to hide scrollbar\n var scrollerGap = 30;\n\n // Returned or thrown by various protocols to signal 'I'm not\n // handling this'.\n var Pass = CodeMirror.Pass = {toString: function(){return \"CodeMirror.Pass\";}};\n\n // Reused option objects for setSelection & friends\n var sel_dontScroll = {scroll: false}, sel_mouse = {origin: \"*mouse\"}, sel_move = {origin: \"+move\"};\n\n function Delayed() {this.id = null;}\n Delayed.prototype.set = function(ms, f) {\n clearTimeout(this.id);\n this.id = setTimeout(f, ms);\n };\n\n // Counts the column offset in a string, taking tabs into account.\n // Used mostly to find indentation.\n var countColumn = CodeMirror.countColumn = function(string, end, tabSize, startIndex, startValue) {\n if (end == null) {\n end = string.search(/[^\\s\\u00a0]/);\n if (end == -1) end = string.length;\n }\n for (var i = startIndex || 0, n = startValue || 0;;) {\n var nextTab = string.indexOf(\"\\t\", i);\n if (nextTab < 0 || nextTab >= end)\n return n + (end - i);\n n += nextTab - i;\n n += tabSize - (n % tabSize);\n i = nextTab + 1;\n }\n };\n\n // The inverse of countColumn -- find the offset that corresponds to\n // a particular column.\n var findColumn = CodeMirror.findColumn = function(string, goal, tabSize) {\n for (var pos = 0, col = 0;;) {\n var nextTab = string.indexOf(\"\\t\", pos);\n if (nextTab == -1) nextTab = string.length;\n var skipped = nextTab - pos;\n if (nextTab == string.length || col + skipped >= goal)\n return pos + Math.min(skipped, goal - col);\n col += nextTab - pos;\n col += tabSize - (col % tabSize);\n pos = nextTab + 1;\n if (col >= goal) return pos;\n }\n }\n\n var spaceStrs = [\"\"];\n function spaceStr(n) {\n while (spaceStrs.length <= n)\n spaceStrs.push(lst(spaceStrs) + \" \");\n return spaceStrs[n];\n }\n\n function lst(arr) { return arr[arr.length-1]; }\n\n var selectInput = function(node) { node.select(); };\n if (ios) // Mobile Safari apparently has a bug where select() is broken.\n selectInput = function(node) { node.selectionStart = 0; node.selectionEnd = node.value.length; };\n else if (ie) // Suppress mysterious IE10 errors\n selectInput = function(node) { try { node.select(); } catch(_e) {} };\n\n function indexOf(array, elt) {\n for (var i = 0; i < array.length; ++i)\n if (array[i] == elt) return i;\n return -1;\n }\n function map(array, f) {\n var out = [];\n for (var i = 0; i < array.length; i++) out[i] = f(array[i], i);\n return out;\n }\n\n function nothing() {}\n\n function createObj(base, props) {\n var inst;\n if (Object.create) {\n inst = Object.create(base);\n } else {\n nothing.prototype = base;\n inst = new nothing();\n }\n if (props) copyObj(props, inst);\n return inst;\n };\n\n function copyObj(obj, target, overwrite) {\n if (!target) target = {};\n for (var prop in obj)\n if (obj.hasOwnProperty(prop) && (overwrite !== false || !target.hasOwnProperty(prop)))\n target[prop] = obj[prop];\n return target;\n }\n\n function bind(f) {\n var args = Array.prototype.slice.call(arguments, 1);\n return function(){return f.apply(null, args);};\n }\n\n var nonASCIISingleCaseWordChar = /[\\u00df\\u0587\\u0590-\\u05f4\\u0600-\\u06ff\\u3040-\\u309f\\u30a0-\\u30ff\\u3400-\\u4db5\\u4e00-\\u9fcc\\uac00-\\ud7af]/;\n var isWordCharBasic = CodeMirror.isWordChar = function(ch) {\n return /\\w/.test(ch) || ch > \"\\x80\" &&\n (ch.toUpperCase() != ch.toLowerCase() || nonASCIISingleCaseWordChar.test(ch));\n };\n function isWordChar(ch, helper) {\n if (!helper) return isWordCharBasic(ch);\n if (helper.source.indexOf(\"\\\\w\") > -1 && isWordCharBasic(ch)) return true;\n return helper.test(ch);\n }\n\n function isEmpty(obj) {\n for (var n in obj) if (obj.hasOwnProperty(n) && obj[n]) return false;\n return true;\n }\n\n // Extending unicode characters. A series of a non-extending char +\n // any number of extending chars is treated as a single unit as far\n // as editing and measuring is concerned. This is not fully correct,\n // since some scripts/fonts/browsers also treat other configurations\n // of code points as a group.\n var extendingChars = /[\\u0300-\\u036f\\u0483-\\u0489\\u0591-\\u05bd\\u05bf\\u05c1\\u05c2\\u05c4\\u05c5\\u05c7\\u0610-\\u061a\\u064b-\\u065e\\u0670\\u06d6-\\u06dc\\u06de-\\u06e4\\u06e7\\u06e8\\u06ea-\\u06ed\\u0711\\u0730-\\u074a\\u07a6-\\u07b0\\u07eb-\\u07f3\\u0816-\\u0819\\u081b-\\u0823\\u0825-\\u0827\\u0829-\\u082d\\u0900-\\u0902\\u093c\\u0941-\\u0948\\u094d\\u0951-\\u0955\\u0962\\u0963\\u0981\\u09bc\\u09be\\u09c1-\\u09c4\\u09cd\\u09d7\\u09e2\\u09e3\\u0a01\\u0a02\\u0a3c\\u0a41\\u0a42\\u0a47\\u0a48\\u0a4b-\\u0a4d\\u0a51\\u0a70\\u0a71\\u0a75\\u0a81\\u0a82\\u0abc\\u0ac1-\\u0ac5\\u0ac7\\u0ac8\\u0acd\\u0ae2\\u0ae3\\u0b01\\u0b3c\\u0b3e\\u0b3f\\u0b41-\\u0b44\\u0b4d\\u0b56\\u0b57\\u0b62\\u0b63\\u0b82\\u0bbe\\u0bc0\\u0bcd\\u0bd7\\u0c3e-\\u0c40\\u0c46-\\u0c48\\u0c4a-\\u0c4d\\u0c55\\u0c56\\u0c62\\u0c63\\u0cbc\\u0cbf\\u0cc2\\u0cc6\\u0ccc\\u0ccd\\u0cd5\\u0cd6\\u0ce2\\u0ce3\\u0d3e\\u0d41-\\u0d44\\u0d4d\\u0d57\\u0d62\\u0d63\\u0dca\\u0dcf\\u0dd2-\\u0dd4\\u0dd6\\u0ddf\\u0e31\\u0e34-\\u0e3a\\u0e47-\\u0e4e\\u0eb1\\u0eb4-\\u0eb9\\u0ebb\\u0ebc\\u0ec8-\\u0ecd\\u0f18\\u0f19\\u0f35\\u0f37\\u0f39\\u0f71-\\u0f7e\\u0f80-\\u0f84\\u0f86\\u0f87\\u0f90-\\u0f97\\u0f99-\\u0fbc\\u0fc6\\u102d-\\u1030\\u1032-\\u1037\\u1039\\u103a\\u103d\\u103e\\u1058\\u1059\\u105e-\\u1060\\u1071-\\u1074\\u1082\\u1085\\u1086\\u108d\\u109d\\u135f\\u1712-\\u1714\\u1732-\\u1734\\u1752\\u1753\\u1772\\u1773\\u17b7-\\u17bd\\u17c6\\u17c9-\\u17d3\\u17dd\\u180b-\\u180d\\u18a9\\u1920-\\u1922\\u1927\\u1928\\u1932\\u1939-\\u193b\\u1a17\\u1a18\\u1a56\\u1a58-\\u1a5e\\u1a60\\u1a62\\u1a65-\\u1a6c\\u1a73-\\u1a7c\\u1a7f\\u1b00-\\u1b03\\u1b34\\u1b36-\\u1b3a\\u1b3c\\u1b42\\u1b6b-\\u1b73\\u1b80\\u1b81\\u1ba2-\\u1ba5\\u1ba8\\u1ba9\\u1c2c-\\u1c33\\u1c36\\u1c37\\u1cd0-\\u1cd2\\u1cd4-\\u1ce0\\u1ce2-\\u1ce8\\u1ced\\u1dc0-\\u1de6\\u1dfd-\\u1dff\\u200c\\u200d\\u20d0-\\u20f0\\u2cef-\\u2cf1\\u2de0-\\u2dff\\u302a-\\u302f\\u3099\\u309a\\ua66f-\\ua672\\ua67c\\ua67d\\ua6f0\\ua6f1\\ua802\\ua806\\ua80b\\ua825\\ua826\\ua8c4\\ua8e0-\\ua8f1\\ua926-\\ua92d\\ua947-\\ua951\\ua980-\\ua982\\ua9b3\\ua9b6-\\ua9b9\\ua9bc\\uaa29-\\uaa2e\\uaa31\\uaa32\\uaa35\\uaa36\\uaa43\\uaa4c\\uaab0\\uaab2-\\uaab4\\uaab7\\uaab8\\uaabe\\uaabf\\uaac1\\uabe5\\uabe8\\uabed\\udc00-\\udfff\\ufb1e\\ufe00-\\ufe0f\\ufe20-\\ufe26\\uff9e\\uff9f]/;\n function isExtendingChar(ch) { return ch.charCodeAt(0) >= 768 && extendingChars.test(ch); }\n\n // DOM UTILITIES\n\n function elt(tag, content, className, style) {\n var e = document.createElement(tag);\n if (className) e.className = className;\n if (style) e.style.cssText = style;\n if (typeof content == \"string\") e.appendChild(document.createTextNode(content));\n else if (content) for (var i = 0; i < content.length; ++i) e.appendChild(content[i]);\n return e;\n }\n\n var range;\n if (document.createRange) range = function(node, start, end, endNode) {\n var r = document.createRange();\n r.setEnd(endNode || node, end);\n r.setStart(node, start);\n return r;\n };\n else range = function(node, start, end) {\n var r = document.body.createTextRange();\n try { r.moveToElementText(node.parentNode); }\n catch(e) { return r; }\n r.collapse(true);\n r.moveEnd(\"character\", end);\n r.moveStart(\"character\", start);\n return r;\n };\n\n function removeChildren(e) {\n for (var count = e.childNodes.length; count > 0; --count)\n e.removeChild(e.firstChild);\n return e;\n }\n\n function removeChildrenAndAdd(parent, e) {\n return removeChildren(parent).appendChild(e);\n }\n\n var contains = CodeMirror.contains = function(parent, child) {\n if (child.nodeType == 3) // Android browser always returns false when child is a textnode\n child = child.parentNode;\n if (parent.contains)\n return parent.contains(child);\n do {\n if (child.nodeType == 11) child = child.host;\n if (child == parent) return true;\n } while (child = child.parentNode);\n };\n\n function activeElt() {\n var activeElement = document.activeElement;\n while (activeElement && activeElement.root && activeElement.root.activeElement)\n activeElement = activeElement.root.activeElement;\n return activeElement;\n }\n // Older versions of IE throws unspecified error when touching\n // document.activeElement in some cases (during loading, in iframe)\n if (ie && ie_version < 11) activeElt = function() {\n try { return document.activeElement; }\n catch(e) { return document.body; }\n };\n\n function classTest(cls) { return new RegExp(\"(^|\\\\s)\" + cls + \"(?:$|\\\\s)\\\\s*\"); }\n var rmClass = CodeMirror.rmClass = function(node, cls) {\n var current = node.className;\n var match = classTest(cls).exec(current);\n if (match) {\n var after = current.slice(match.index + match[0].length);\n node.className = current.slice(0, match.index) + (after ? match[1] + after : \"\");\n }\n };\n var addClass = CodeMirror.addClass = function(node, cls) {\n var current = node.className;\n if (!classTest(cls).test(current)) node.className += (current ? \" \" : \"\") + cls;\n };\n function joinClasses(a, b) {\n var as = a.split(\" \");\n for (var i = 0; i < as.length; i++)\n if (as[i] && !classTest(as[i]).test(b)) b += \" \" + as[i];\n return b;\n }\n\n // WINDOW-WIDE EVENTS\n\n // These must be handled carefully, because naively registering a\n // handler for each editor will cause the editors to never be\n // garbage collected.\n\n function forEachCodeMirror(f) {\n if (!document.body.getElementsByClassName) return;\n var byClass = document.body.getElementsByClassName(\"CodeMirror\");\n for (var i = 0; i < byClass.length; i++) {\n var cm = byClass[i].CodeMirror;\n if (cm) f(cm);\n }\n }\n\n var globalsRegistered = false;\n function ensureGlobalHandlers() {\n if (globalsRegistered) return;\n registerGlobalHandlers();\n globalsRegistered = true;\n }\n function registerGlobalHandlers() {\n // When the window resizes, we need to refresh active editors.\n var resizeTimer;\n on(window, \"resize\", function() {\n if (resizeTimer == null) resizeTimer = setTimeout(function() {\n resizeTimer = null;\n forEachCodeMirror(onResize);\n }, 100);\n });\n // When the window loses focus, we want to show the editor as blurred\n on(window, \"blur\", function() {\n forEachCodeMirror(onBlur);\n });\n }\n\n // FEATURE DETECTION\n\n // Detect drag-and-drop\n var dragAndDrop = function() {\n // There is *some* kind of drag-and-drop support in IE6-8, but I\n // couldn't get it to work yet.\n if (ie && ie_version < 9) return false;\n var div = elt('div');\n return \"draggable\" in div || \"dragDrop\" in div;\n }();\n\n var zwspSupported;\n function zeroWidthElement(measure) {\n if (zwspSupported == null) {\n var test = elt(\"span\", \"\\u200b\");\n removeChildrenAndAdd(measure, elt(\"span\", [test, document.createTextNode(\"x\")]));\n if (measure.firstChild.offsetHeight != 0)\n zwspSupported = test.offsetWidth <= 1 && test.offsetHeight > 2 && !(ie && ie_version < 8);\n }\n var node = zwspSupported ? elt(\"span\", \"\\u200b\") :\n elt(\"span\", \"\\u00a0\", null, \"display: inline-block; width: 1px; margin-right: -1px\");\n node.setAttribute(\"cm-text\", \"\");\n return node;\n }\n\n // Feature-detect IE's crummy client rect reporting for bidi text\n var badBidiRects;\n function hasBadBidiRects(measure) {\n if (badBidiRects != null) return badBidiRects;\n var txt = removeChildrenAndAdd(measure, document.createTextNode(\"A\\u062eA\"));\n var r0 = range(txt, 0, 1).getBoundingClientRect();\n if (!r0 || r0.left == r0.right) return false; // Safari returns null in some cases (#2780)\n var r1 = range(txt, 1, 2).getBoundingClientRect();\n return badBidiRects = (r1.right - r0.right < 3);\n }\n\n // See if \"\".split is the broken IE version, if so, provide an\n // alternative way to split lines.\n var splitLinesAuto = CodeMirror.splitLines = \"\\n\\nb\".split(/\\n/).length != 3 ? function(string) {\n var pos = 0, result = [], l = string.length;\n while (pos <= l) {\n var nl = string.indexOf(\"\\n\", pos);\n if (nl == -1) nl = string.length;\n var line = string.slice(pos, string.charAt(nl - 1) == \"\\r\" ? nl - 1 : nl);\n var rt = line.indexOf(\"\\r\");\n if (rt != -1) {\n result.push(line.slice(0, rt));\n pos += rt + 1;\n } else {\n result.push(line);\n pos = nl + 1;\n }\n }\n return result;\n } : function(string){return string.split(/\\r\\n?|\\n/);};\n\n var hasSelection = window.getSelection ? function(te) {\n try { return te.selectionStart != te.selectionEnd; }\n catch(e) { return false; }\n } : function(te) {\n try {var range = te.ownerDocument.selection.createRange();}\n catch(e) {}\n if (!range || range.parentElement() != te) return false;\n return range.compareEndPoints(\"StartToEnd\", range) != 0;\n };\n\n var hasCopyEvent = (function() {\n var e = elt(\"div\");\n if (\"oncopy\" in e) return true;\n e.setAttribute(\"oncopy\", \"return;\");\n return typeof e.oncopy == \"function\";\n })();\n\n var badZoomedRects = null;\n function hasBadZoomedRects(measure) {\n if (badZoomedRects != null) return badZoomedRects;\n var node = removeChildrenAndAdd(measure, elt(\"span\", \"x\"));\n var normal = node.getBoundingClientRect();\n var fromRange = range(node, 0, 1).getBoundingClientRect();\n return badZoomedRects = Math.abs(normal.left - fromRange.left) > 1;\n }\n\n // KEY NAMES\n\n var keyNames = CodeMirror.keyNames = {\n 3: \"Enter\", 8: \"Backspace\", 9: \"Tab\", 13: \"Enter\", 16: \"Shift\", 17: \"Ctrl\", 18: \"Alt\",\n 19: \"Pause\", 20: \"CapsLock\", 27: \"Esc\", 32: \"Space\", 33: \"PageUp\", 34: \"PageDown\", 35: \"End\",\n 36: \"Home\", 37: \"Left\", 38: \"Up\", 39: \"Right\", 40: \"Down\", 44: \"PrintScrn\", 45: \"Insert\",\n 46: \"Delete\", 59: \";\", 61: \"=\", 91: \"Mod\", 92: \"Mod\", 93: \"Mod\",\n 106: \"*\", 107: \"=\", 109: \"-\", 110: \".\", 111: \"/\", 127: \"Delete\",\n 173: \"-\", 186: \";\", 187: \"=\", 188: \",\", 189: \"-\", 190: \".\", 191: \"/\", 192: \"`\", 219: \"[\", 220: \"\\\\\",\n 221: \"]\", 222: \"'\", 63232: \"Up\", 63233: \"Down\", 63234: \"Left\", 63235: \"Right\", 63272: \"Delete\",\n 63273: \"Home\", 63275: \"End\", 63276: \"PageUp\", 63277: \"PageDown\", 63302: \"Insert\"\n };\n (function() {\n // Number keys\n for (var i = 0; i < 10; i++) keyNames[i + 48] = keyNames[i + 96] = String(i);\n // Alphabetic keys\n for (var i = 65; i <= 90; i++) keyNames[i] = String.fromCharCode(i);\n // Function keys\n for (var i = 1; i <= 12; i++) keyNames[i + 111] = keyNames[i + 63235] = \"F\" + i;\n })();\n\n // BIDI HELPERS\n\n function iterateBidiSections(order, from, to, f) {\n if (!order) return f(from, to, \"ltr\");\n var found = false;\n for (var i = 0; i < order.length; ++i) {\n var part = order[i];\n if (part.from < to && part.to > from || from == to && part.to == from) {\n f(Math.max(part.from, from), Math.min(part.to, to), part.level == 1 ? \"rtl\" : \"ltr\");\n found = true;\n }\n }\n if (!found) f(from, to, \"ltr\");\n }\n\n function bidiLeft(part) { return part.level % 2 ? part.to : part.from; }\n function bidiRight(part) { return part.level % 2 ? part.from : part.to; }\n\n function lineLeft(line) { var order = getOrder(line); return order ? bidiLeft(order[0]) : 0; }\n function lineRight(line) {\n var order = getOrder(line);\n if (!order) return line.text.length;\n return bidiRight(lst(order));\n }\n\n function lineStart(cm, lineN) {\n var line = getLine(cm.doc, lineN);\n var visual = visualLine(line);\n if (visual != line) lineN = lineNo(visual);\n var order = getOrder(visual);\n var ch = !order ? 0 : order[0].level % 2 ? lineRight(visual) : lineLeft(visual);\n return Pos(lineN, ch);\n }\n function lineEnd(cm, lineN) {\n var merged, line = getLine(cm.doc, lineN);\n while (merged = collapsedSpanAtEnd(line)) {\n line = merged.find(1, true).line;\n lineN = null;\n }\n var order = getOrder(line);\n var ch = !order ? line.text.length : order[0].level % 2 ? lineLeft(line) : lineRight(line);\n return Pos(lineN == null ? lineNo(line) : lineN, ch);\n }\n function lineStartSmart(cm, pos) {\n var start = lineStart(cm, pos.line);\n var line = getLine(cm.doc, start.line);\n var order = getOrder(line);\n if (!order || order[0].level == 0) {\n var firstNonWS = Math.max(0, line.text.search(/\\S/));\n var inWS = pos.line == start.line && pos.ch <= firstNonWS && pos.ch;\n return Pos(start.line, inWS ? 0 : firstNonWS);\n }\n return start;\n }\n\n function compareBidiLevel(order, a, b) {\n var linedir = order[0].level;\n if (a == linedir) return true;\n if (b == linedir) return false;\n return a < b;\n }\n var bidiOther;\n function getBidiPartAt(order, pos) {\n bidiOther = null;\n for (var i = 0, found; i < order.length; ++i) {\n var cur = order[i];\n if (cur.from < pos && cur.to > pos) return i;\n if ((cur.from == pos || cur.to == pos)) {\n if (found == null) {\n found = i;\n } else if (compareBidiLevel(order, cur.level, order[found].level)) {\n if (cur.from != cur.to) bidiOther = found;\n return i;\n } else {\n if (cur.from != cur.to) bidiOther = i;\n return found;\n }\n }\n }\n return found;\n }\n\n function moveInLine(line, pos, dir, byUnit) {\n if (!byUnit) return pos + dir;\n do pos += dir;\n while (pos > 0 && isExtendingChar(line.text.charAt(pos)));\n return pos;\n }\n\n // This is needed in order to move 'visually' through bi-directional\n // text -- i.e., pressing left should make the cursor go left, even\n // when in RTL text. The tricky part is the 'jumps', where RTL and\n // LTR text touch each other. This often requires the cursor offset\n // to move more than one unit, in order to visually move one unit.\n function moveVisually(line, start, dir, byUnit) {\n var bidi = getOrder(line);\n if (!bidi) return moveLogically(line, start, dir, byUnit);\n var pos = getBidiPartAt(bidi, start), part = bidi[pos];\n var target = moveInLine(line, start, part.level % 2 ? -dir : dir, byUnit);\n\n for (;;) {\n if (target > part.from && target < part.to) return target;\n if (target == part.from || target == part.to) {\n if (getBidiPartAt(bidi, target) == pos) return target;\n part = bidi[pos += dir];\n return (dir > 0) == part.level % 2 ? part.to : part.from;\n } else {\n part = bidi[pos += dir];\n if (!part) return null;\n if ((dir > 0) == part.level % 2)\n target = moveInLine(line, part.to, -1, byUnit);\n else\n target = moveInLine(line, part.from, 1, byUnit);\n }\n }\n }\n\n function moveLogically(line, start, dir, byUnit) {\n var target = start + dir;\n if (byUnit) while (target > 0 && isExtendingChar(line.text.charAt(target))) target += dir;\n return target < 0 || target > line.text.length ? null : target;\n }\n\n // Bidirectional ordering algorithm\n // See http://unicode.org/reports/tr9/tr9-13.html for the algorithm\n // that this (partially) implements.\n\n // One-char codes used for character types:\n // L (L): Left-to-Right\n // R (R): Right-to-Left\n // r (AL): Right-to-Left Arabic\n // 1 (EN): European Number\n // + (ES): European Number Separator\n // % (ET): European Number Terminator\n // n (AN): Arabic Number\n // , (CS): Common Number Separator\n // m (NSM): Non-Spacing Mark\n // b (BN): Boundary Neutral\n // s (B): Paragraph Separator\n // t (S): Segment Separator\n // w (WS): Whitespace\n // N (ON): Other Neutrals\n\n // Returns null if characters are ordered as they appear\n // (left-to-right), or an array of sections ({from, to, level}\n // objects) in the order in which they occur visually.\n var bidiOrdering = (function() {\n // Character types for codepoints 0 to 0xff\n var lowTypes = \"bbbbbbbbbtstwsbbbbbbbbbbbbbbssstwNN%%%NNNNNN,N,N1111111111NNNNNNNLLLLLLLLLLLLLLLLLLLLLLLLLLNNNNNNLLLLLLLLLLLLLLLLLLLLLLLLLLNNNNbbbbbbsbbbbbbbbbbbbbbbbbbbbbbbbbb,N%%%%NNNNLNNNNN%%11NLNNN1LNNNNNLLLLLLLLLLLLLLLLLLLLLLLNLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLN\";\n // Character types for codepoints 0x600 to 0x6ff\n var arabicTypes = \"rrrrrrrrrrrr,rNNmmmmmmrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrmmmmmmmmmmmmmmrrrrrrrnnnnnnnnnn%nnrrrmrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrmmmmmmmmmmmmmmmmmmmNmmmm\";\n function charType(code) {\n if (code <= 0xf7) return lowTypes.charAt(code);\n else if (0x590 <= code && code <= 0x5f4) return \"R\";\n else if (0x600 <= code && code <= 0x6ed) return arabicTypes.charAt(code - 0x600);\n else if (0x6ee <= code && code <= 0x8ac) return \"r\";\n else if (0x2000 <= code && code <= 0x200b) return \"w\";\n else if (code == 0x200c) return \"b\";\n else return \"L\";\n }\n\n var bidiRE = /[\\u0590-\\u05f4\\u0600-\\u06ff\\u0700-\\u08ac]/;\n var isNeutral = /[stwN]/, isStrong = /[LRr]/, countsAsLeft = /[Lb1n]/, countsAsNum = /[1n]/;\n // Browsers seem to always treat the boundaries of block elements as being L.\n var outerType = \"L\";\n\n function BidiSpan(level, from, to) {\n this.level = level;\n this.from = from; this.to = to;\n }\n\n return function(str) {\n if (!bidiRE.test(str)) return false;\n var len = str.length, types = [];\n for (var i = 0, type; i < len; ++i)\n types.push(type = charType(str.charCodeAt(i)));\n\n // W1. Examine each non-spacing mark (NSM) in the level run, and\n // change the type of the NSM to the type of the previous\n // character. If the NSM is at the start of the level run, it will\n // get the type of sor.\n for (var i = 0, prev = outerType; i < len; ++i) {\n var type = types[i];\n if (type == \"m\") types[i] = prev;\n else prev = type;\n }\n\n // W2. Search backwards from each instance of a European number\n // until the first strong type (R, L, AL, or sor) is found. If an\n // AL is found, change the type of the European number to Arabic\n // number.\n // W3. Change all ALs to R.\n for (var i = 0, cur = outerType; i < len; ++i) {\n var type = types[i];\n if (type == \"1\" && cur == \"r\") types[i] = \"n\";\n else if (isStrong.test(type)) { cur = type; if (type == \"r\") types[i] = \"R\"; }\n }\n\n // W4. A single European separator between two European numbers\n // changes to a European number. A single common separator between\n // two numbers of the same type changes to that type.\n for (var i = 1, prev = types[0]; i < len - 1; ++i) {\n var type = types[i];\n if (type == \"+\" && prev == \"1\" && types[i+1] == \"1\") types[i] = \"1\";\n else if (type == \",\" && prev == types[i+1] &&\n (prev == \"1\" || prev == \"n\")) types[i] = prev;\n prev = type;\n }\n\n // W5. A sequence of European terminators adjacent to European\n // numbers changes to all European numbers.\n // W6. Otherwise, separators and terminators change to Other\n // Neutral.\n for (var i = 0; i < len; ++i) {\n var type = types[i];\n if (type == \",\") types[i] = \"N\";\n else if (type == \"%\") {\n for (var end = i + 1; end < len && types[end] == \"%\"; ++end) {}\n var replace = (i && types[i-1] == \"!\") || (end < len && types[end] == \"1\") ? \"1\" : \"N\";\n for (var j = i; j < end; ++j) types[j] = replace;\n i = end - 1;\n }\n }\n\n // W7. Search backwards from each instance of a European number\n // until the first strong type (R, L, or sor) is found. If an L is\n // found, then change the type of the European number to L.\n for (var i = 0, cur = outerType; i < len; ++i) {\n var type = types[i];\n if (cur == \"L\" && type == \"1\") types[i] = \"L\";\n else if (isStrong.test(type)) cur = type;\n }\n\n // N1. A sequence of neutrals takes the direction of the\n // surrounding strong text if the text on both sides has the same\n // direction. European and Arabic numbers act as if they were R in\n // terms of their influence on neutrals. Start-of-level-run (sor)\n // and end-of-level-run (eor) are used at level run boundaries.\n // N2. Any remaining neutrals take the embedding direction.\n for (var i = 0; i < len; ++i) {\n if (isNeutral.test(types[i])) {\n for (var end = i + 1; end < len && isNeutral.test(types[end]); ++end) {}\n var before = (i ? types[i-1] : outerType) == \"L\";\n var after = (end < len ? types[end] : outerType) == \"L\";\n var replace = before || after ? \"L\" : \"R\";\n for (var j = i; j < end; ++j) types[j] = replace;\n i = end - 1;\n }\n }\n\n // Here we depart from the documented algorithm, in order to avoid\n // building up an actual levels array. Since there are only three\n // levels (0, 1, 2) in an implementation that doesn't take\n // explicit embedding into account, we can build up the order on\n // the fly, without following the level-based algorithm.\n var order = [], m;\n for (var i = 0; i < len;) {\n if (countsAsLeft.test(types[i])) {\n var start = i;\n for (++i; i < len && countsAsLeft.test(types[i]); ++i) {}\n order.push(new BidiSpan(0, start, i));\n } else {\n var pos = i, at = order.length;\n for (++i; i < len && types[i] != \"L\"; ++i) {}\n for (var j = pos; j < i;) {\n if (countsAsNum.test(types[j])) {\n if (pos < j) order.splice(at, 0, new BidiSpan(1, pos, j));\n var nstart = j;\n for (++j; j < i && countsAsNum.test(types[j]); ++j) {}\n order.splice(at, 0, new BidiSpan(2, nstart, j));\n pos = j;\n } else ++j;\n }\n if (pos < i) order.splice(at, 0, new BidiSpan(1, pos, i));\n }\n }\n if (order[0].level == 1 && (m = str.match(/^\\s+/))) {\n order[0].from = m[0].length;\n order.unshift(new BidiSpan(0, 0, m[0].length));\n }\n if (lst(order).level == 1 && (m = str.match(/\\s+$/))) {\n lst(order).to -= m[0].length;\n order.push(new BidiSpan(0, len - m[0].length, len));\n }\n if (order[0].level == 2)\n order.unshift(new BidiSpan(1, order[0].to, order[0].to));\n if (order[0].level != lst(order).level)\n order.push(new BidiSpan(order[0].level, len, len));\n\n return order;\n };\n })();\n\n // THE END\n\n CodeMirror.version = \"5.13.2\";\n\n return CodeMirror;\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/lib/codemirror.css": {
"type": "text/css",
"title": "$:/plugins/tiddlywiki/codemirror/lib/codemirror.css",
"tags": "[[$:/tags/Stylesheet]]",
"text": "/* BASICS */\n\n.CodeMirror {\n /* Set height, width, borders, and global font properties here */\n font-family: monospace;\n height: 300px;\n color: black;\n}\n\n/* PADDING */\n\n.CodeMirror-lines {\n padding: 4px 0; /* Vertical padding around content */\n}\n.CodeMirror pre {\n padding: 0 4px; /* Horizontal padding of content */\n}\n\n.CodeMirror-scrollbar-filler, .CodeMirror-gutter-filler {\n background-color: white; /* The little square between H and V scrollbars */\n}\n\n/* GUTTER */\n\n.CodeMirror-gutters {\n border-right: 1px solid #ddd;\n background-color: #f7f7f7;\n white-space: nowrap;\n}\n.CodeMirror-linenumbers {}\n.CodeMirror-linenumber {\n padding: 0 3px 0 5px;\n min-width: 20px;\n text-align: right;\n color: #999;\n white-space: nowrap;\n}\n\n.CodeMirror-guttermarker { color: black; }\n.CodeMirror-guttermarker-subtle { color: #999; }\n\n/* CURSOR */\n\n.CodeMirror-cursor {\n border-left: 1px solid black;\n border-right: none;\n width: 0;\n}\n/* Shown when moving in bi-directional text */\n.CodeMirror div.CodeMirror-secondarycursor {\n border-left: 1px solid silver;\n}\n.cm-fat-cursor .CodeMirror-cursor {\n width: auto;\n border: 0;\n background: #7e7;\n}\n.cm-fat-cursor div.CodeMirror-cursors {\n z-index: 1;\n}\n\n.cm-animate-fat-cursor {\n width: auto;\n border: 0;\n -webkit-animation: blink 1.06s steps(1) infinite;\n -moz-animation: blink 1.06s steps(1) infinite;\n animation: blink 1.06s steps(1) infinite;\n background-color: #7e7;\n}\n@-moz-keyframes blink {\n 0% {}\n 50% { background-color: transparent; }\n 100% {}\n}\n@-webkit-keyframes blink {\n 0% {}\n 50% { background-color: transparent; }\n 100% {}\n}\n@keyframes blink {\n 0% {}\n 50% { background-color: transparent; }\n 100% {}\n}\n\n/* Can style cursor different in overwrite (non-insert) mode */\n.CodeMirror-overwrite .CodeMirror-cursor {}\n\n.cm-tab { display: inline-block; text-decoration: inherit; }\n\n.CodeMirror-ruler {\n border-left: 1px solid #ccc;\n position: absolute;\n}\n\n/* DEFAULT THEME */\n\n.cm-s-default .cm-header {color: blue;}\n.cm-s-default .cm-quote {color: #090;}\n.cm-negative {color: #d44;}\n.cm-positive {color: #292;}\n.cm-header, .cm-strong {font-weight: bold;}\n.cm-em {font-style: italic;}\n.cm-link {text-decoration: underline;}\n.cm-strikethrough {text-decoration: line-through;}\n\n.cm-s-default .cm-keyword {color: #708;}\n.cm-s-default .cm-atom {color: #219;}\n.cm-s-default .cm-number {color: #164;}\n.cm-s-default .cm-def {color: #00f;}\n.cm-s-default .cm-variable,\n.cm-s-default .cm-punctuation,\n.cm-s-default .cm-property,\n.cm-s-default .cm-operator {}\n.cm-s-default .cm-variable-2 {color: #05a;}\n.cm-s-default .cm-variable-3 {color: #085;}\n.cm-s-default .cm-comment {color: #a50;}\n.cm-s-default .cm-string {color: #a11;}\n.cm-s-default .cm-string-2 {color: #f50;}\n.cm-s-default .cm-meta {color: #555;}\n.cm-s-default .cm-qualifier {color: #555;}\n.cm-s-default .cm-builtin {color: #30a;}\n.cm-s-default .cm-bracket {color: #997;}\n.cm-s-default .cm-tag {color: #170;}\n.cm-s-default .cm-attribute {color: #00c;}\n.cm-s-default .cm-hr {color: #999;}\n.cm-s-default .cm-link {color: #00c;}\n\n.cm-s-default .cm-error {color: #f00;}\n.cm-invalidchar {color: #f00;}\n\n.CodeMirror-composing { border-bottom: 2px solid; }\n\n/* Default styles for common addons */\n\ndiv.CodeMirror span.CodeMirror-matchingbracket {color: #0f0;}\ndiv.CodeMirror span.CodeMirror-nonmatchingbracket {color: #f22;}\n.CodeMirror-matchingtag { background: rgba(255, 150, 0, .3); }\n.CodeMirror-activeline-background {background: #e8f2ff;}\n\n/* STOP */\n\n/* The rest of this file contains styles related to the mechanics of\n the editor. You probably shouldn't touch them. */\n\n.CodeMirror {\n position: relative;\n overflow: hidden;\n background: white;\n}\n\n.CodeMirror-scroll {\n overflow: scroll !important; /* Things will break if this is overridden */\n /* 30px is the magic margin used to hide the element's real scrollbars */\n /* See overflow: hidden in .CodeMirror */\n margin-bottom: -30px; margin-right: -30px;\n padding-bottom: 30px;\n height: 100%;\n outline: none; /* Prevent dragging from highlighting the element */\n position: relative;\n}\n.CodeMirror-sizer {\n position: relative;\n border-right: 30px solid transparent;\n}\n\n/* The fake, visible scrollbars. Used to force redraw during scrolling\n before actual scrolling happens, thus preventing shaking and\n flickering artifacts. */\n.CodeMirror-vscrollbar, .CodeMirror-hscrollbar, .CodeMirror-scrollbar-filler, .CodeMirror-gutter-filler {\n position: absolute;\n z-index: 6;\n display: none;\n}\n.CodeMirror-vscrollbar {\n right: 0; top: 0;\n overflow-x: hidden;\n overflow-y: scroll;\n}\n.CodeMirror-hscrollbar {\n bottom: 0; left: 0;\n overflow-y: hidden;\n overflow-x: scroll;\n}\n.CodeMirror-scrollbar-filler {\n right: 0; bottom: 0;\n}\n.CodeMirror-gutter-filler {\n left: 0; bottom: 0;\n}\n\n.CodeMirror-gutters {\n position: absolute; left: 0; top: 0;\n min-height: 100%;\n z-index: 3;\n}\n.CodeMirror-gutter {\n white-space: normal;\n height: 100%;\n display: inline-block;\n vertical-align: top;\n margin-bottom: -30px;\n /* Hack to make IE7 behave */\n *zoom:1;\n *display:inline;\n}\n.CodeMirror-gutter-wrapper {\n position: absolute;\n z-index: 4;\n background: none !important;\n border: none !important;\n}\n.CodeMirror-gutter-background {\n position: absolute;\n top: 0; bottom: 0;\n z-index: 4;\n}\n.CodeMirror-gutter-elt {\n position: absolute;\n cursor: default;\n z-index: 4;\n}\n.CodeMirror-gutter-wrapper {\n -webkit-user-select: none;\n -moz-user-select: none;\n user-select: none;\n}\n\n.CodeMirror-lines {\n cursor: text;\n min-height: 1px; /* prevents collapsing before first draw */\n}\n.CodeMirror pre {\n /* Reset some styles that the rest of the page might have set */\n -moz-border-radius: 0; -webkit-border-radius: 0; border-radius: 0;\n border-width: 0;\n background: transparent;\n font-family: inherit;\n font-size: inherit;\n margin: 0;\n white-space: pre;\n word-wrap: normal;\n line-height: inherit;\n color: inherit;\n z-index: 2;\n position: relative;\n overflow: visible;\n -webkit-tap-highlight-color: transparent;\n -webkit-font-variant-ligatures: none;\n font-variant-ligatures: none;\n}\n.CodeMirror-wrap pre {\n word-wrap: break-word;\n white-space: pre-wrap;\n word-break: normal;\n}\n\n.CodeMirror-linebackground {\n position: absolute;\n left: 0; right: 0; top: 0; bottom: 0;\n z-index: 0;\n}\n\n.CodeMirror-linewidget {\n position: relative;\n z-index: 2;\n overflow: auto;\n}\n\n.CodeMirror-widget {}\n\n.CodeMirror-code {\n outline: none;\n}\n\n/* Force content-box sizing for the elements where we expect it */\n.CodeMirror-scroll,\n.CodeMirror-sizer,\n.CodeMirror-gutter,\n.CodeMirror-gutters,\n.CodeMirror-linenumber {\n -moz-box-sizing: content-box;\n box-sizing: content-box;\n}\n\n.CodeMirror-measure {\n position: absolute;\n width: 100%;\n height: 0;\n overflow: hidden;\n visibility: hidden;\n}\n\n.CodeMirror-cursor { position: absolute; }\n.CodeMirror-measure pre { position: static; }\n\ndiv.CodeMirror-cursors {\n visibility: hidden;\n position: relative;\n z-index: 3;\n}\ndiv.CodeMirror-dragcursors {\n visibility: visible;\n}\n\n.CodeMirror-focused div.CodeMirror-cursors {\n visibility: visible;\n}\n\n.CodeMirror-selected { background: #d9d9d9; }\n.CodeMirror-focused .CodeMirror-selected { background: #d7d4f0; }\n.CodeMirror-crosshair { cursor: crosshair; }\n.CodeMirror-line::selection, .CodeMirror-line > span::selection, .CodeMirror-line > span > span::selection { background: #d7d4f0; }\n.CodeMirror-line::-moz-selection, .CodeMirror-line > span::-moz-selection, .CodeMirror-line > span > span::-moz-selection { background: #d7d4f0; }\n\n.cm-searching {\n background: #ffa;\n background: rgba(255, 255, 0, .4);\n}\n\n/* IE7 hack to prevent it from returning funny offsetTops on the spans */\n.CodeMirror span { *vertical-align: text-bottom; }\n\n/* Used to force a border model for a node */\n.cm-force-border { padding-right: .1px; }\n\n@media print {\n /* Hide the cursor when printing */\n .CodeMirror div.CodeMirror-cursors {\n visibility: hidden;\n }\n}\n\n/* See issue #2901 */\n.cm-tab-wrap-hack:after { content: ''; }\n\n/* Help users use markselection to safely style text background */\nspan.CodeMirror-selectedtext { background: none; }\n"
},
"$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.css": {
"type": "text/css",
"title": "$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.css",
"tags": "[[$:/tags/Stylesheet]]",
"text": ".CodeMirror-dialog {\n position: absolute;\n left: 0; right: 0;\n background: inherit;\n z-index: 15;\n padding: .1em .8em;\n overflow: hidden;\n color: inherit;\n}\n\n.CodeMirror-dialog-top {\n border-bottom: 1px solid #eee;\n top: 0;\n}\n\n.CodeMirror-dialog-bottom {\n border-top: 1px solid #eee;\n bottom: 0;\n}\n\n.CodeMirror-dialog input {\n border: none;\n outline: none;\n background: transparent;\n width: 20em;\n color: inherit;\n font-family: monospace;\n}\n\n.CodeMirror-dialog button {\n font-size: 70%;\n}\n"
},
"$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n// Open simple dialogs on top of an editor. Relies on dialog.css.\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n function dialogDiv(cm, template, bottom) {\n var wrap = cm.getWrapperElement();\n var dialog;\n dialog = wrap.appendChild(document.createElement(\"div\"));\n if (bottom)\n dialog.className = \"CodeMirror-dialog CodeMirror-dialog-bottom\";\n else\n dialog.className = \"CodeMirror-dialog CodeMirror-dialog-top\";\n\n if (typeof template == \"string\") {\n dialog.innerHTML = template;\n } else { // Assuming it's a detached DOM element.\n dialog.appendChild(template);\n }\n return dialog;\n }\n\n function closeNotification(cm, newVal) {\n if (cm.state.currentNotificationClose)\n cm.state.currentNotificationClose();\n cm.state.currentNotificationClose = newVal;\n }\n\n CodeMirror.defineExtension(\"openDialog\", function(template, callback, options) {\n if (!options) options = {};\n\n closeNotification(this, null);\n\n var dialog = dialogDiv(this, template, options.bottom);\n var closed = false, me = this;\n function close(newVal) {\n if (typeof newVal == 'string') {\n inp.value = newVal;\n } else {\n if (closed) return;\n closed = true;\n dialog.parentNode.removeChild(dialog);\n me.focus();\n\n if (options.onClose) options.onClose(dialog);\n }\n }\n\n var inp = dialog.getElementsByTagName(\"input\")[0], button;\n if (inp) {\n inp.focus();\n\n if (options.value) {\n inp.value = options.value;\n if (options.selectValueOnOpen !== false) {\n inp.select();\n }\n }\n\n if (options.onInput)\n CodeMirror.on(inp, \"input\", function(e) { options.onInput(e, inp.value, close);});\n if (options.onKeyUp)\n CodeMirror.on(inp, \"keyup\", function(e) {options.onKeyUp(e, inp.value, close);});\n\n CodeMirror.on(inp, \"keydown\", function(e) {\n if (options && options.onKeyDown && options.onKeyDown(e, inp.value, close)) { return; }\n if (e.keyCode == 27 || (options.closeOnEnter !== false && e.keyCode == 13)) {\n inp.blur();\n CodeMirror.e_stop(e);\n close();\n }\n if (e.keyCode == 13) callback(inp.value, e);\n });\n\n if (options.closeOnBlur !== false) CodeMirror.on(inp, \"blur\", close);\n } else if (button = dialog.getElementsByTagName(\"button\")[0]) {\n CodeMirror.on(button, \"click\", function() {\n close();\n me.focus();\n });\n\n if (options.closeOnBlur !== false) CodeMirror.on(button, \"blur\", close);\n\n button.focus();\n }\n return close;\n });\n\n CodeMirror.defineExtension(\"openConfirm\", function(template, callbacks, options) {\n closeNotification(this, null);\n var dialog = dialogDiv(this, template, options && options.bottom);\n var buttons = dialog.getElementsByTagName(\"button\");\n var closed = false, me = this, blurring = 1;\n function close() {\n if (closed) return;\n closed = true;\n dialog.parentNode.removeChild(dialog);\n me.focus();\n }\n buttons[0].focus();\n for (var i = 0; i < buttons.length; ++i) {\n var b = buttons[i];\n (function(callback) {\n CodeMirror.on(b, \"click\", function(e) {\n CodeMirror.e_preventDefault(e);\n close();\n if (callback) callback(me);\n });\n })(callbacks[i]);\n CodeMirror.on(b, \"blur\", function() {\n --blurring;\n setTimeout(function() { if (blurring <= 0) close(); }, 200);\n });\n CodeMirror.on(b, \"focus\", function() { ++blurring; });\n }\n });\n\n /*\n * openNotification\n * Opens a notification, that can be closed with an optional timer\n * (default 5000ms timer) and always closes on click.\n *\n * If a notification is opened while another is opened, it will close the\n * currently opened one and open the new one immediately.\n */\n CodeMirror.defineExtension(\"openNotification\", function(template, options) {\n closeNotification(this, close);\n var dialog = dialogDiv(this, template, options && options.bottom);\n var closed = false, doneTimer;\n var duration = options && typeof options.duration !== \"undefined\" ? options.duration : 5000;\n\n function close() {\n if (closed) return;\n closed = true;\n clearTimeout(doneTimer);\n dialog.parentNode.removeChild(dialog);\n }\n\n CodeMirror.on(dialog, 'click', function(e) {\n CodeMirror.e_preventDefault(e);\n close();\n });\n\n if (duration)\n doneTimer = setTimeout(close, duration);\n\n return close;\n });\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n var ie_lt8 = /MSIE \\d/.test(navigator.userAgent) &&\n (document.documentMode == null || document.documentMode < 8);\n\n var Pos = CodeMirror.Pos;\n\n var matching = {\"(\": \")>\", \")\": \"(<\", \"[\": \"]>\", \"]\": \"[<\", \"{\": \"}>\", \"}\": \"{<\"};\n\n function findMatchingBracket(cm, where, strict, config) {\n var line = cm.getLineHandle(where.line), pos = where.ch - 1;\n var match = (pos >= 0 && matching[line.text.charAt(pos)]) || matching[line.text.charAt(++pos)];\n if (!match) return null;\n var dir = match.charAt(1) == \">\" ? 1 : -1;\n if (strict && (dir > 0) != (pos == where.ch)) return null;\n var style = cm.getTokenTypeAt(Pos(where.line, pos + 1));\n\n var found = scanForBracket(cm, Pos(where.line, pos + (dir > 0 ? 1 : 0)), dir, style || null, config);\n if (found == null) return null;\n return {from: Pos(where.line, pos), to: found && found.pos,\n match: found && found.ch == match.charAt(0), forward: dir > 0};\n }\n\n // bracketRegex is used to specify which type of bracket to scan\n // should be a regexp, e.g. /[[\\]]/\n //\n // Note: If \"where\" is on an open bracket, then this bracket is ignored.\n //\n // Returns false when no bracket was found, null when it reached\n // maxScanLines and gave up\n function scanForBracket(cm, where, dir, style, config) {\n var maxScanLen = (config && config.maxScanLineLength) || 10000;\n var maxScanLines = (config && config.maxScanLines) || 1000;\n\n var stack = [];\n var re = config && config.bracketRegex ? config.bracketRegex : /[(){}[\\]]/;\n var lineEnd = dir > 0 ? Math.min(where.line + maxScanLines, cm.lastLine() + 1)\n : Math.max(cm.firstLine() - 1, where.line - maxScanLines);\n for (var lineNo = where.line; lineNo != lineEnd; lineNo += dir) {\n var line = cm.getLine(lineNo);\n if (!line) continue;\n var pos = dir > 0 ? 0 : line.length - 1, end = dir > 0 ? line.length : -1;\n if (line.length > maxScanLen) continue;\n if (lineNo == where.line) pos = where.ch - (dir < 0 ? 1 : 0);\n for (; pos != end; pos += dir) {\n var ch = line.charAt(pos);\n if (re.test(ch) && (style === undefined || cm.getTokenTypeAt(Pos(lineNo, pos + 1)) == style)) {\n var match = matching[ch];\n if ((match.charAt(1) == \">\") == (dir > 0)) stack.push(ch);\n else if (!stack.length) return {pos: Pos(lineNo, pos), ch: ch};\n else stack.pop();\n }\n }\n }\n return lineNo - dir == (dir > 0 ? cm.lastLine() : cm.firstLine()) ? false : null;\n }\n\n function matchBrackets(cm, autoclear, config) {\n // Disable brace matching in long lines, since it'll cause hugely slow updates\n var maxHighlightLen = cm.state.matchBrackets.maxHighlightLineLength || 1000;\n var marks = [], ranges = cm.listSelections();\n for (var i = 0; i < ranges.length; i++) {\n var match = ranges[i].empty() && findMatchingBracket(cm, ranges[i].head, false, config);\n if (match && cm.getLine(match.from.line).length <= maxHighlightLen) {\n var style = match.match ? \"CodeMirror-matchingbracket\" : \"CodeMirror-nonmatchingbracket\";\n marks.push(cm.markText(match.from, Pos(match.from.line, match.from.ch + 1), {className: style}));\n if (match.to && cm.getLine(match.to.line).length <= maxHighlightLen)\n marks.push(cm.markText(match.to, Pos(match.to.line, match.to.ch + 1), {className: style}));\n }\n }\n\n if (marks.length) {\n // Kludge to work around the IE bug from issue #1193, where text\n // input stops going to the textare whever this fires.\n if (ie_lt8 && cm.state.focused) cm.focus();\n\n var clear = function() {\n cm.operation(function() {\n for (var i = 0; i < marks.length; i++) marks[i].clear();\n });\n };\n if (autoclear) setTimeout(clear, 800);\n else return clear;\n }\n }\n\n var currentlyHighlighted = null;\n function doMatchBrackets(cm) {\n cm.operation(function() {\n if (currentlyHighlighted) {currentlyHighlighted(); currentlyHighlighted = null;}\n currentlyHighlighted = matchBrackets(cm, false, cm.state.matchBrackets);\n });\n }\n\n CodeMirror.defineOption(\"matchBrackets\", false, function(cm, val, old) {\n if (old && old != CodeMirror.Init)\n cm.off(\"cursorActivity\", doMatchBrackets);\n if (val) {\n cm.state.matchBrackets = typeof val == \"object\" ? val : {};\n cm.on(\"cursorActivity\", doMatchBrackets);\n }\n });\n\n CodeMirror.defineExtension(\"matchBrackets\", function() {matchBrackets(this, true);});\n CodeMirror.defineExtension(\"findMatchingBracket\", function(pos, strict, config){\n return findMatchingBracket(this, pos, strict, config);\n });\n CodeMirror.defineExtension(\"scanForBracket\", function(pos, dir, style, config){\n return scanForBracket(this, pos, dir, style, config);\n });\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/addon/mode/multiplex.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/addon/mode/multiplex.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nCodeMirror.multiplexingMode = function(outer /*, others */) {\n // Others should be {open, close, mode [, delimStyle] [, innerStyle]} objects\n var others = Array.prototype.slice.call(arguments, 1);\n\n function indexOf(string, pattern, from, returnEnd) {\n if (typeof pattern == \"string\") {\n var found = string.indexOf(pattern, from);\n return returnEnd && found > -1 ? found + pattern.length : found;\n }\n var m = pattern.exec(from ? string.slice(from) : string);\n return m ? m.index + from + (returnEnd ? m[0].length : 0) : -1;\n }\n\n return {\n startState: function() {\n return {\n outer: CodeMirror.startState(outer),\n innerActive: null,\n inner: null\n };\n },\n\n copyState: function(state) {\n return {\n outer: CodeMirror.copyState(outer, state.outer),\n innerActive: state.innerActive,\n inner: state.innerActive && CodeMirror.copyState(state.innerActive.mode, state.inner)\n };\n },\n\n token: function(stream, state) {\n if (!state.innerActive) {\n var cutOff = Infinity, oldContent = stream.string;\n for (var i = 0; i < others.length; ++i) {\n var other = others[i];\n var found = indexOf(oldContent, other.open, stream.pos);\n if (found == stream.pos) {\n if (!other.parseDelimiters) stream.match(other.open);\n state.innerActive = other;\n state.inner = CodeMirror.startState(other.mode, outer.indent ? outer.indent(state.outer, \"\") : 0);\n return other.delimStyle && (other.delimStyle + \" \" + other.delimStyle + \"-open\");\n } else if (found != -1 && found < cutOff) {\n cutOff = found;\n }\n }\n if (cutOff != Infinity) stream.string = oldContent.slice(0, cutOff);\n var outerToken = outer.token(stream, state.outer);\n if (cutOff != Infinity) stream.string = oldContent;\n return outerToken;\n } else {\n var curInner = state.innerActive, oldContent = stream.string;\n if (!curInner.close && stream.sol()) {\n state.innerActive = state.inner = null;\n return this.token(stream, state);\n }\n var found = curInner.close ? indexOf(oldContent, curInner.close, stream.pos, curInner.parseDelimiters) : -1;\n if (found == stream.pos && !curInner.parseDelimiters) {\n stream.match(curInner.close);\n state.innerActive = state.inner = null;\n return curInner.delimStyle && (curInner.delimStyle + \" \" + curInner.delimStyle + \"-close\");\n }\n if (found > -1) stream.string = oldContent.slice(0, found);\n var innerToken = curInner.mode.token(stream, state.inner);\n if (found > -1) stream.string = oldContent;\n\n if (found == stream.pos && curInner.parseDelimiters)\n state.innerActive = state.inner = null;\n\n if (curInner.innerStyle) {\n if (innerToken) innerToken = innerToken + \" \" + curInner.innerStyle;\n else innerToken = curInner.innerStyle;\n }\n\n return innerToken;\n }\n },\n\n indent: function(state, textAfter) {\n var mode = state.innerActive ? state.innerActive.mode : outer;\n if (!mode.indent) return CodeMirror.Pass;\n return mode.indent(state.innerActive ? state.inner : state.outer, textAfter);\n },\n\n blankLine: function(state) {\n var mode = state.innerActive ? state.innerActive.mode : outer;\n if (mode.blankLine) {\n mode.blankLine(state.innerActive ? state.inner : state.outer);\n }\n if (!state.innerActive) {\n for (var i = 0; i < others.length; ++i) {\n var other = others[i];\n if (other.open === \"\\n\") {\n state.innerActive = other;\n state.inner = CodeMirror.startState(other.mode, mode.indent ? mode.indent(state.outer, \"\") : 0);\n }\n }\n } else if (state.innerActive.close === \"\\n\") {\n state.innerActive = state.inner = null;\n }\n },\n\n electricChars: outer.electricChars,\n\n innerMode: function(state) {\n return state.inner ? {state: state.inner, mode: state.innerActive.mode} : {state: state.outer, mode: outer};\n }\n };\n};\n\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/addon/search/searchcursor.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/addon/search/searchcursor.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n var Pos = CodeMirror.Pos;\n\n function SearchCursor(doc, query, pos, caseFold) {\n this.atOccurrence = false; this.doc = doc;\n if (caseFold == null && typeof query == \"string\") caseFold = false;\n\n pos = pos ? doc.clipPos(pos) : Pos(0, 0);\n this.pos = {from: pos, to: pos};\n\n // The matches method is filled in based on the type of query.\n // It takes a position and a direction, and returns an object\n // describing the next occurrence of the query, or null if no\n // more matches were found.\n if (typeof query != \"string\") { // Regexp match\n if (!query.global) query = new RegExp(query.source, query.ignoreCase ? \"ig\" : \"g\");\n this.matches = function(reverse, pos) {\n if (reverse) {\n query.lastIndex = 0;\n var line = doc.getLine(pos.line).slice(0, pos.ch), cutOff = 0, match, start;\n for (;;) {\n query.lastIndex = cutOff;\n var newMatch = query.exec(line);\n if (!newMatch) break;\n match = newMatch;\n start = match.index;\n cutOff = match.index + (match[0].length || 1);\n if (cutOff == line.length) break;\n }\n var matchLen = (match && match[0].length) || 0;\n if (!matchLen) {\n if (start == 0 && line.length == 0) {match = undefined;}\n else if (start != doc.getLine(pos.line).length) {\n matchLen++;\n }\n }\n } else {\n query.lastIndex = pos.ch;\n var line = doc.getLine(pos.line), match = query.exec(line);\n var matchLen = (match && match[0].length) || 0;\n var start = match && match.index;\n if (start + matchLen != line.length && !matchLen) matchLen = 1;\n }\n if (match && matchLen)\n return {from: Pos(pos.line, start),\n to: Pos(pos.line, start + matchLen),\n match: match};\n };\n } else { // String query\n var origQuery = query;\n if (caseFold) query = query.toLowerCase();\n var fold = caseFold ? function(str){return str.toLowerCase();} : function(str){return str;};\n var target = query.split(\"\\n\");\n // Different methods for single-line and multi-line queries\n if (target.length == 1) {\n if (!query.length) {\n // Empty string would match anything and never progress, so\n // we define it to match nothing instead.\n this.matches = function() {};\n } else {\n this.matches = function(reverse, pos) {\n if (reverse) {\n var orig = doc.getLine(pos.line).slice(0, pos.ch), line = fold(orig);\n var match = line.lastIndexOf(query);\n if (match > -1) {\n match = adjustPos(orig, line, match);\n return {from: Pos(pos.line, match), to: Pos(pos.line, match + origQuery.length)};\n }\n } else {\n var orig = doc.getLine(pos.line).slice(pos.ch), line = fold(orig);\n var match = line.indexOf(query);\n if (match > -1) {\n match = adjustPos(orig, line, match) + pos.ch;\n return {from: Pos(pos.line, match), to: Pos(pos.line, match + origQuery.length)};\n }\n }\n };\n }\n } else {\n var origTarget = origQuery.split(\"\\n\");\n this.matches = function(reverse, pos) {\n var last = target.length - 1;\n if (reverse) {\n if (pos.line - (target.length - 1) < doc.firstLine()) return;\n if (fold(doc.getLine(pos.line).slice(0, origTarget[last].length)) != target[target.length - 1]) return;\n var to = Pos(pos.line, origTarget[last].length);\n for (var ln = pos.line - 1, i = last - 1; i >= 1; --i, --ln)\n if (target[i] != fold(doc.getLine(ln))) return;\n var line = doc.getLine(ln), cut = line.length - origTarget[0].length;\n if (fold(line.slice(cut)) != target[0]) return;\n return {from: Pos(ln, cut), to: to};\n } else {\n if (pos.line + (target.length - 1) > doc.lastLine()) return;\n var line = doc.getLine(pos.line), cut = line.length - origTarget[0].length;\n if (fold(line.slice(cut)) != target[0]) return;\n var from = Pos(pos.line, cut);\n for (var ln = pos.line + 1, i = 1; i < last; ++i, ++ln)\n if (target[i] != fold(doc.getLine(ln))) return;\n if (fold(doc.getLine(ln).slice(0, origTarget[last].length)) != target[last]) return;\n return {from: from, to: Pos(ln, origTarget[last].length)};\n }\n };\n }\n }\n }\n\n SearchCursor.prototype = {\n findNext: function() {return this.find(false);},\n findPrevious: function() {return this.find(true);},\n\n find: function(reverse) {\n var self = this, pos = this.doc.clipPos(reverse ? this.pos.from : this.pos.to);\n function savePosAndFail(line) {\n var pos = Pos(line, 0);\n self.pos = {from: pos, to: pos};\n self.atOccurrence = false;\n return false;\n }\n\n for (;;) {\n if (this.pos = this.matches(reverse, pos)) {\n this.atOccurrence = true;\n return this.pos.match || true;\n }\n if (reverse) {\n if (!pos.line) return savePosAndFail(0);\n pos = Pos(pos.line-1, this.doc.getLine(pos.line-1).length);\n }\n else {\n var maxLine = this.doc.lineCount();\n if (pos.line == maxLine - 1) return savePosAndFail(maxLine);\n pos = Pos(pos.line + 1, 0);\n }\n }\n },\n\n from: function() {if (this.atOccurrence) return this.pos.from;},\n to: function() {if (this.atOccurrence) return this.pos.to;},\n\n replace: function(newText, origin) {\n if (!this.atOccurrence) return;\n var lines = CodeMirror.splitLines(newText);\n this.doc.replaceRange(lines, this.pos.from, this.pos.to, origin);\n this.pos.to = Pos(this.pos.from.line + lines.length - 1,\n lines[lines.length - 1].length + (lines.length == 1 ? this.pos.from.ch : 0));\n }\n };\n\n // Maps a position in a case-folded line back to a position in the original line\n // (compensating for codepoints increasing in number during folding)\n function adjustPos(orig, folded, pos) {\n if (orig.length == folded.length) return pos;\n for (var pos1 = Math.min(pos, orig.length);;) {\n var len1 = orig.slice(0, pos1).toLowerCase().length;\n if (len1 < pos) ++pos1;\n else if (len1 > pos) --pos1;\n else return pos1;\n }\n }\n\n CodeMirror.defineExtension(\"getSearchCursor\", function(query, pos, caseFold) {\n return new SearchCursor(this.doc, query, pos, caseFold);\n });\n CodeMirror.defineDocExtension(\"getSearchCursor\", function(query, pos, caseFold) {\n return new SearchCursor(this, query, pos, caseFold);\n });\n\n CodeMirror.defineExtension(\"selectMatches\", function(query, caseFold) {\n var ranges = [];\n var cur = this.getSearchCursor(query, this.getCursor(\"from\"), caseFold);\n while (cur.findNext()) {\n if (CodeMirror.cmpPos(cur.to(), this.getCursor(\"to\")) > 0) break;\n ranges.push({anchor: cur.from(), head: cur.to()});\n }\n if (ranges.length)\n this.setSelections(ranges, 0);\n });\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/css/css.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/css/css.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nCodeMirror.defineMode(\"css\", function(config, parserConfig) {\n var inline = parserConfig.inline\n if (!parserConfig.propertyKeywords) parserConfig = CodeMirror.resolveMode(\"text/css\");\n\n var indentUnit = config.indentUnit,\n tokenHooks = parserConfig.tokenHooks,\n documentTypes = parserConfig.documentTypes || {},\n mediaTypes = parserConfig.mediaTypes || {},\n mediaFeatures = parserConfig.mediaFeatures || {},\n mediaValueKeywords = parserConfig.mediaValueKeywords || {},\n propertyKeywords = parserConfig.propertyKeywords || {},\n nonStandardPropertyKeywords = parserConfig.nonStandardPropertyKeywords || {},\n fontProperties = parserConfig.fontProperties || {},\n counterDescriptors = parserConfig.counterDescriptors || {},\n colorKeywords = parserConfig.colorKeywords || {},\n valueKeywords = parserConfig.valueKeywords || {},\n allowNested = parserConfig.allowNested,\n supportsAtComponent = parserConfig.supportsAtComponent === true;\n\n var type, override;\n function ret(style, tp) { type = tp; return style; }\n\n // Tokenizers\n\n function tokenBase(stream, state) {\n var ch = stream.next();\n if (tokenHooks[ch]) {\n var result = tokenHooks[ch](stream, state);\n if (result !== false) return result;\n }\n if (ch == \"@\") {\n stream.eatWhile(/[\\w\\\\\\-]/);\n return ret(\"def\", stream.current());\n } else if (ch == \"=\" || (ch == \"~\" || ch == \"|\") && stream.eat(\"=\")) {\n return ret(null, \"compare\");\n } else if (ch == \"\\\"\" || ch == \"'\") {\n state.tokenize = tokenString(ch);\n return state.tokenize(stream, state);\n } else if (ch == \"#\") {\n stream.eatWhile(/[\\w\\\\\\-]/);\n return ret(\"atom\", \"hash\");\n } else if (ch == \"!\") {\n stream.match(/^\\s*\\w*/);\n return ret(\"keyword\", \"important\");\n } else if (/\\d/.test(ch) || ch == \".\" && stream.eat(/\\d/)) {\n stream.eatWhile(/[\\w.%]/);\n return ret(\"number\", \"unit\");\n } else if (ch === \"-\") {\n if (/[\\d.]/.test(stream.peek())) {\n stream.eatWhile(/[\\w.%]/);\n return ret(\"number\", \"unit\");\n } else if (stream.match(/^-[\\w\\\\\\-]+/)) {\n stream.eatWhile(/[\\w\\\\\\-]/);\n if (stream.match(/^\\s*:/, false))\n return ret(\"variable-2\", \"variable-definition\");\n return ret(\"variable-2\", \"variable\");\n } else if (stream.match(/^\\w+-/)) {\n return ret(\"meta\", \"meta\");\n }\n } else if (/[,+>*\\/]/.test(ch)) {\n return ret(null, \"select-op\");\n } else if (ch == \".\" && stream.match(/^-?[_a-z][_a-z0-9-]*/i)) {\n return ret(\"qualifier\", \"qualifier\");\n } else if (/[:;{}\\[\\]\\(\\)]/.test(ch)) {\n return ret(null, ch);\n } else if ((ch == \"u\" && stream.match(/rl(-prefix)?\\(/)) ||\n (ch == \"d\" && stream.match(\"omain(\")) ||\n (ch == \"r\" && stream.match(\"egexp(\"))) {\n stream.backUp(1);\n state.tokenize = tokenParenthesized;\n return ret(\"property\", \"word\");\n } else if (/[\\w\\\\\\-]/.test(ch)) {\n stream.eatWhile(/[\\w\\\\\\-]/);\n return ret(\"property\", \"word\");\n } else {\n return ret(null, null);\n }\n }\n\n function tokenString(quote) {\n return function(stream, state) {\n var escaped = false, ch;\n while ((ch = stream.next()) != null) {\n if (ch == quote && !escaped) {\n if (quote == \")\") stream.backUp(1);\n break;\n }\n escaped = !escaped && ch == \"\\\\\";\n }\n if (ch == quote || !escaped && quote != \")\") state.tokenize = null;\n return ret(\"string\", \"string\");\n };\n }\n\n function tokenParenthesized(stream, state) {\n stream.next(); // Must be '('\n if (!stream.match(/\\s*[\\\"\\')]/, false))\n state.tokenize = tokenString(\")\");\n else\n state.tokenize = null;\n return ret(null, \"(\");\n }\n\n // Context management\n\n function Context(type, indent, prev) {\n this.type = type;\n this.indent = indent;\n this.prev = prev;\n }\n\n function pushContext(state, stream, type, indent) {\n state.context = new Context(type, stream.indentation() + (indent === false ? 0 : indentUnit), state.context);\n return type;\n }\n\n function popContext(state) {\n if (state.context.prev)\n state.context = state.context.prev;\n return state.context.type;\n }\n\n function pass(type, stream, state) {\n return states[state.context.type](type, stream, state);\n }\n function popAndPass(type, stream, state, n) {\n for (var i = n || 1; i > 0; i--)\n state.context = state.context.prev;\n return pass(type, stream, state);\n }\n\n // Parser\n\n function wordAsValue(stream) {\n var word = stream.current().toLowerCase();\n if (valueKeywords.hasOwnProperty(word))\n override = \"atom\";\n else if (colorKeywords.hasOwnProperty(word))\n override = \"keyword\";\n else\n override = \"variable\";\n }\n\n var states = {};\n\n states.top = function(type, stream, state) {\n if (type == \"{\") {\n return pushContext(state, stream, \"block\");\n } else if (type == \"}\" && state.context.prev) {\n return popContext(state);\n } else if (supportsAtComponent && /@component/.test(type)) {\n return pushContext(state, stream, \"atComponentBlock\");\n } else if (/^@(-moz-)?document$/.test(type)) {\n return pushContext(state, stream, \"documentTypes\");\n } else if (/^@(media|supports|(-moz-)?document|import)$/.test(type)) {\n return pushContext(state, stream, \"atBlock\");\n } else if (/^@(font-face|counter-style)/.test(type)) {\n state.stateArg = type;\n return \"restricted_atBlock_before\";\n } else if (/^@(-(moz|ms|o|webkit)-)?keyframes$/.test(type)) {\n return \"keyframes\";\n } else if (type && type.charAt(0) == \"@\") {\n return pushContext(state, stream, \"at\");\n } else if (type == \"hash\") {\n override = \"builtin\";\n } else if (type == \"word\") {\n override = \"tag\";\n } else if (type == \"variable-definition\") {\n return \"maybeprop\";\n } else if (type == \"interpolation\") {\n return pushContext(state, stream, \"interpolation\");\n } else if (type == \":\") {\n return \"pseudo\";\n } else if (allowNested && type == \"(\") {\n return pushContext(state, stream, \"parens\");\n }\n return state.context.type;\n };\n\n states.block = function(type, stream, state) {\n if (type == \"word\") {\n var word = stream.current().toLowerCase();\n if (propertyKeywords.hasOwnProperty(word)) {\n override = \"property\";\n return \"maybeprop\";\n } else if (nonStandardPropertyKeywords.hasOwnProperty(word)) {\n override = \"string-2\";\n return \"maybeprop\";\n } else if (allowNested) {\n override = stream.match(/^\\s*:(?:\\s|$)/, false) ? \"property\" : \"tag\";\n return \"block\";\n } else {\n override += \" error\";\n return \"maybeprop\";\n }\n } else if (type == \"meta\") {\n return \"block\";\n } else if (!allowNested && (type == \"hash\" || type == \"qualifier\")) {\n override = \"error\";\n return \"block\";\n } else {\n return states.top(type, stream, state);\n }\n };\n\n states.maybeprop = function(type, stream, state) {\n if (type == \":\") return pushContext(state, stream, \"prop\");\n return pass(type, stream, state);\n };\n\n states.prop = function(type, stream, state) {\n if (type == \";\") return popContext(state);\n if (type == \"{\" && allowNested) return pushContext(state, stream, \"propBlock\");\n if (type == \"}\" || type == \"{\") return popAndPass(type, stream, state);\n if (type == \"(\") return pushContext(state, stream, \"parens\");\n\n if (type == \"hash\" && !/^#([0-9a-fA-f]{3,4}|[0-9a-fA-f]{6}|[0-9a-fA-f]{8})$/.test(stream.current())) {\n override += \" error\";\n } else if (type == \"word\") {\n wordAsValue(stream);\n } else if (type == \"interpolation\") {\n return pushContext(state, stream, \"interpolation\");\n }\n return \"prop\";\n };\n\n states.propBlock = function(type, _stream, state) {\n if (type == \"}\") return popContext(state);\n if (type == \"word\") { override = \"property\"; return \"maybeprop\"; }\n return state.context.type;\n };\n\n states.parens = function(type, stream, state) {\n if (type == \"{\" || type == \"}\") return popAndPass(type, stream, state);\n if (type == \")\") return popContext(state);\n if (type == \"(\") return pushContext(state, stream, \"parens\");\n if (type == \"interpolation\") return pushContext(state, stream, \"interpolation\");\n if (type == \"word\") wordAsValue(stream);\n return \"parens\";\n };\n\n states.pseudo = function(type, stream, state) {\n if (type == \"word\") {\n override = \"variable-3\";\n return state.context.type;\n }\n return pass(type, stream, state);\n };\n\n states.documentTypes = function(type, stream, state) {\n if (type == \"word\" && documentTypes.hasOwnProperty(stream.current())) {\n override = \"tag\";\n return state.context.type;\n } else {\n return states.atBlock(type, stream, state);\n }\n };\n\n states.atBlock = function(type, stream, state) {\n if (type == \"(\") return pushContext(state, stream, \"atBlock_parens\");\n if (type == \"}\" || type == \";\") return popAndPass(type, stream, state);\n if (type == \"{\") return popContext(state) && pushContext(state, stream, allowNested ? \"block\" : \"top\");\n\n if (type == \"interpolation\") return pushContext(state, stream, \"interpolation\");\n\n if (type == \"word\") {\n var word = stream.current().toLowerCase();\n if (word == \"only\" || word == \"not\" || word == \"and\" || word == \"or\")\n override = \"keyword\";\n else if (mediaTypes.hasOwnProperty(word))\n override = \"attribute\";\n else if (mediaFeatures.hasOwnProperty(word))\n override = \"property\";\n else if (mediaValueKeywords.hasOwnProperty(word))\n override = \"keyword\";\n else if (propertyKeywords.hasOwnProperty(word))\n override = \"property\";\n else if (nonStandardPropertyKeywords.hasOwnProperty(word))\n override = \"string-2\";\n else if (valueKeywords.hasOwnProperty(word))\n override = \"atom\";\n else if (colorKeywords.hasOwnProperty(word))\n override = \"keyword\";\n else\n override = \"error\";\n }\n return state.context.type;\n };\n\n states.atComponentBlock = function(type, stream, state) {\n if (type == \"}\")\n return popAndPass(type, stream, state);\n if (type == \"{\")\n return popContext(state) && pushContext(state, stream, allowNested ? \"block\" : \"top\", false);\n if (type == \"word\")\n override = \"error\";\n return state.context.type;\n };\n\n states.atBlock_parens = function(type, stream, state) {\n if (type == \")\") return popContext(state);\n if (type == \"{\" || type == \"}\") return popAndPass(type, stream, state, 2);\n return states.atBlock(type, stream, state);\n };\n\n states.restricted_atBlock_before = function(type, stream, state) {\n if (type == \"{\")\n return pushContext(state, stream, \"restricted_atBlock\");\n if (type == \"word\" && state.stateArg == \"@counter-style\") {\n override = \"variable\";\n return \"restricted_atBlock_before\";\n }\n return pass(type, stream, state);\n };\n\n states.restricted_atBlock = function(type, stream, state) {\n if (type == \"}\") {\n state.stateArg = null;\n return popContext(state);\n }\n if (type == \"word\") {\n if ((state.stateArg == \"@font-face\" && !fontProperties.hasOwnProperty(stream.current().toLowerCase())) ||\n (state.stateArg == \"@counter-style\" && !counterDescriptors.hasOwnProperty(stream.current().toLowerCase())))\n override = \"error\";\n else\n override = \"property\";\n return \"maybeprop\";\n }\n return \"restricted_atBlock\";\n };\n\n states.keyframes = function(type, stream, state) {\n if (type == \"word\") { override = \"variable\"; return \"keyframes\"; }\n if (type == \"{\") return pushContext(state, stream, \"top\");\n return pass(type, stream, state);\n };\n\n states.at = function(type, stream, state) {\n if (type == \";\") return popContext(state);\n if (type == \"{\" || type == \"}\") return popAndPass(type, stream, state);\n if (type == \"word\") override = \"tag\";\n else if (type == \"hash\") override = \"builtin\";\n return \"at\";\n };\n\n states.interpolation = function(type, stream, state) {\n if (type == \"}\") return popContext(state);\n if (type == \"{\" || type == \";\") return popAndPass(type, stream, state);\n if (type == \"word\") override = \"variable\";\n else if (type != \"variable\" && type != \"(\" && type != \")\") override = \"error\";\n return \"interpolation\";\n };\n\n return {\n startState: function(base) {\n return {tokenize: null,\n state: inline ? \"block\" : \"top\",\n stateArg: null,\n context: new Context(inline ? \"block\" : \"top\", base || 0, null)};\n },\n\n token: function(stream, state) {\n if (!state.tokenize && stream.eatSpace()) return null;\n var style = (state.tokenize || tokenBase)(stream, state);\n if (style && typeof style == \"object\") {\n type = style[1];\n style = style[0];\n }\n override = style;\n state.state = states[state.state](type, stream, state);\n return override;\n },\n\n indent: function(state, textAfter) {\n var cx = state.context, ch = textAfter && textAfter.charAt(0);\n var indent = cx.indent;\n if (cx.type == \"prop\" && (ch == \"}\" || ch == \")\")) cx = cx.prev;\n if (cx.prev) {\n if (ch == \"}\" && (cx.type == \"block\" || cx.type == \"top\" ||\n cx.type == \"interpolation\" || cx.type == \"restricted_atBlock\")) {\n // Resume indentation from parent context.\n cx = cx.prev;\n indent = cx.indent;\n } else if (ch == \")\" && (cx.type == \"parens\" || cx.type == \"atBlock_parens\") ||\n ch == \"{\" && (cx.type == \"at\" || cx.type == \"atBlock\")) {\n // Dedent relative to current context.\n indent = Math.max(0, cx.indent - indentUnit);\n cx = cx.prev;\n }\n }\n return indent;\n },\n\n electricChars: \"}\",\n blockCommentStart: \"/*\",\n blockCommentEnd: \"*/\",\n fold: \"brace\"\n };\n});\n\n function keySet(array) {\n var keys = {};\n for (var i = 0; i < array.length; ++i) {\n keys[array[i]] = true;\n }\n return keys;\n }\n\n var documentTypes_ = [\n \"domain\", \"regexp\", \"url\", \"url-prefix\"\n ], documentTypes = keySet(documentTypes_);\n\n var mediaTypes_ = [\n \"all\", \"aural\", \"braille\", \"handheld\", \"print\", \"projection\", \"screen\",\n \"tty\", \"tv\", \"embossed\"\n ], mediaTypes = keySet(mediaTypes_);\n\n var mediaFeatures_ = [\n \"width\", \"min-width\", \"max-width\", \"height\", \"min-height\", \"max-height\",\n \"device-width\", \"min-device-width\", \"max-device-width\", \"device-height\",\n \"min-device-height\", \"max-device-height\", \"aspect-ratio\",\n \"min-aspect-ratio\", \"max-aspect-ratio\", \"device-aspect-ratio\",\n \"min-device-aspect-ratio\", \"max-device-aspect-ratio\", \"color\", \"min-color\",\n \"max-color\", \"color-index\", \"min-color-index\", \"max-color-index\",\n \"monochrome\", \"min-monochrome\", \"max-monochrome\", \"resolution\",\n \"min-resolution\", \"max-resolution\", \"scan\", \"grid\", \"orientation\",\n \"device-pixel-ratio\", \"min-device-pixel-ratio\", \"max-device-pixel-ratio\",\n \"pointer\", \"any-pointer\", \"hover\", \"any-hover\"\n ], mediaFeatures = keySet(mediaFeatures_);\n\n var mediaValueKeywords_ = [\n \"landscape\", \"portrait\", \"none\", \"coarse\", \"fine\", \"on-demand\", \"hover\",\n \"interlace\", \"progressive\"\n ], mediaValueKeywords = keySet(mediaValueKeywords_);\n\n var propertyKeywords_ = [\n \"align-content\", \"align-items\", \"align-self\", \"alignment-adjust\",\n \"alignment-baseline\", \"anchor-point\", \"animation\", \"animation-delay\",\n \"animation-direction\", \"animation-duration\", \"animation-fill-mode\",\n \"animation-iteration-count\", \"animation-name\", \"animation-play-state\",\n \"animation-timing-function\", \"appearance\", \"azimuth\", \"backface-visibility\",\n \"background\", \"background-attachment\", \"background-blend-mode\", \"background-clip\",\n \"background-color\", \"background-image\", \"background-origin\", \"background-position\",\n \"background-repeat\", \"background-size\", \"baseline-shift\", \"binding\",\n \"bleed\", \"bookmark-label\", \"bookmark-level\", \"bookmark-state\",\n \"bookmark-target\", \"border\", \"border-bottom\", \"border-bottom-color\",\n \"border-bottom-left-radius\", \"border-bottom-right-radius\",\n \"border-bottom-style\", \"border-bottom-width\", \"border-collapse\",\n \"border-color\", \"border-image\", \"border-image-outset\",\n \"border-image-repeat\", \"border-image-slice\", \"border-image-source\",\n \"border-image-width\", \"border-left\", \"border-left-color\",\n \"border-left-style\", \"border-left-width\", \"border-radius\", \"border-right\",\n \"border-right-color\", \"border-right-style\", \"border-right-width\",\n \"border-spacing\", \"border-style\", \"border-top\", \"border-top-color\",\n \"border-top-left-radius\", \"border-top-right-radius\", \"border-top-style\",\n \"border-top-width\", \"border-width\", \"bottom\", \"box-decoration-break\",\n \"box-shadow\", \"box-sizing\", \"break-after\", \"break-before\", \"break-inside\",\n \"caption-side\", \"clear\", \"clip\", \"color\", \"color-profile\", \"column-count\",\n \"column-fill\", \"column-gap\", \"column-rule\", \"column-rule-color\",\n \"column-rule-style\", \"column-rule-width\", \"column-span\", \"column-width\",\n \"columns\", \"content\", \"counter-increment\", \"counter-reset\", \"crop\", \"cue\",\n \"cue-after\", \"cue-before\", \"cursor\", \"direction\", \"display\",\n \"dominant-baseline\", \"drop-initial-after-adjust\",\n \"drop-initial-after-align\", \"drop-initial-before-adjust\",\n \"drop-initial-before-align\", \"drop-initial-size\", \"drop-initial-value\",\n \"elevation\", \"empty-cells\", \"fit\", \"fit-position\", \"flex\", \"flex-basis\",\n \"flex-direction\", \"flex-flow\", \"flex-grow\", \"flex-shrink\", \"flex-wrap\",\n \"float\", \"float-offset\", \"flow-from\", \"flow-into\", \"font\", \"font-feature-settings\",\n \"font-family\", \"font-kerning\", \"font-language-override\", \"font-size\", \"font-size-adjust\",\n \"font-stretch\", \"font-style\", \"font-synthesis\", \"font-variant\",\n \"font-variant-alternates\", \"font-variant-caps\", \"font-variant-east-asian\",\n \"font-variant-ligatures\", \"font-variant-numeric\", \"font-variant-position\",\n \"font-weight\", \"grid\", \"grid-area\", \"grid-auto-columns\", \"grid-auto-flow\",\n \"grid-auto-position\", \"grid-auto-rows\", \"grid-column\", \"grid-column-end\",\n \"grid-column-start\", \"grid-row\", \"grid-row-end\", \"grid-row-start\",\n \"grid-template\", \"grid-template-areas\", \"grid-template-columns\",\n \"grid-template-rows\", \"hanging-punctuation\", \"height\", \"hyphens\",\n \"icon\", \"image-orientation\", \"image-rendering\", \"image-resolution\",\n \"inline-box-align\", \"justify-content\", \"left\", \"letter-spacing\",\n \"line-break\", \"line-height\", \"line-stacking\", \"line-stacking-ruby\",\n \"line-stacking-shift\", \"line-stacking-strategy\", \"list-style\",\n \"list-style-image\", \"list-style-position\", \"list-style-type\", \"margin\",\n \"margin-bottom\", \"margin-left\", \"margin-right\", \"margin-top\",\n \"marker-offset\", \"marks\", \"marquee-direction\", \"marquee-loop\",\n \"marquee-play-count\", \"marquee-speed\", \"marquee-style\", \"max-height\",\n \"max-width\", \"min-height\", \"min-width\", \"move-to\", \"nav-down\", \"nav-index\",\n \"nav-left\", \"nav-right\", \"nav-up\", \"object-fit\", \"object-position\",\n \"opacity\", \"order\", \"orphans\", \"outline\",\n \"outline-color\", \"outline-offset\", \"outline-style\", \"outline-width\",\n \"overflow\", \"overflow-style\", \"overflow-wrap\", \"overflow-x\", \"overflow-y\",\n \"padding\", \"padding-bottom\", \"padding-left\", \"padding-right\", \"padding-top\",\n \"page\", \"page-break-after\", \"page-break-before\", \"page-break-inside\",\n \"page-policy\", \"pause\", \"pause-after\", \"pause-before\", \"perspective\",\n \"perspective-origin\", \"pitch\", \"pitch-range\", \"play-during\", \"position\",\n \"presentation-level\", \"punctuation-trim\", \"quotes\", \"region-break-after\",\n \"region-break-before\", \"region-break-inside\", \"region-fragment\",\n \"rendering-intent\", \"resize\", \"rest\", \"rest-after\", \"rest-before\", \"richness\",\n \"right\", \"rotation\", \"rotation-point\", \"ruby-align\", \"ruby-overhang\",\n \"ruby-position\", \"ruby-span\", \"shape-image-threshold\", \"shape-inside\", \"shape-margin\",\n \"shape-outside\", \"size\", \"speak\", \"speak-as\", \"speak-header\",\n \"speak-numeral\", \"speak-punctuation\", \"speech-rate\", \"stress\", \"string-set\",\n \"tab-size\", \"table-layout\", \"target\", \"target-name\", \"target-new\",\n \"target-position\", \"text-align\", \"text-align-last\", \"text-decoration\",\n \"text-decoration-color\", \"text-decoration-line\", \"text-decoration-skip\",\n \"text-decoration-style\", \"text-emphasis\", \"text-emphasis-color\",\n \"text-emphasis-position\", \"text-emphasis-style\", \"text-height\",\n \"text-indent\", \"text-justify\", \"text-outline\", \"text-overflow\", \"text-shadow\",\n \"text-size-adjust\", \"text-space-collapse\", \"text-transform\", \"text-underline-position\",\n \"text-wrap\", \"top\", \"transform\", \"transform-origin\", \"transform-style\",\n \"transition\", \"transition-delay\", \"transition-duration\",\n \"transition-property\", \"transition-timing-function\", \"unicode-bidi\",\n \"vertical-align\", \"visibility\", \"voice-balance\", \"voice-duration\",\n \"voice-family\", \"voice-pitch\", \"voice-range\", \"voice-rate\", \"voice-stress\",\n \"voice-volume\", \"volume\", \"white-space\", \"widows\", \"width\", \"word-break\",\n \"word-spacing\", \"word-wrap\", \"z-index\",\n // SVG-specific\n \"clip-path\", \"clip-rule\", \"mask\", \"enable-background\", \"filter\", \"flood-color\",\n \"flood-opacity\", \"lighting-color\", \"stop-color\", \"stop-opacity\", \"pointer-events\",\n \"color-interpolation\", \"color-interpolation-filters\",\n \"color-rendering\", \"fill\", \"fill-opacity\", \"fill-rule\", \"image-rendering\",\n \"marker\", \"marker-end\", \"marker-mid\", \"marker-start\", \"shape-rendering\", \"stroke\",\n \"stroke-dasharray\", \"stroke-dashoffset\", \"stroke-linecap\", \"stroke-linejoin\",\n \"stroke-miterlimit\", \"stroke-opacity\", \"stroke-width\", \"text-rendering\",\n \"baseline-shift\", \"dominant-baseline\", \"glyph-orientation-horizontal\",\n \"glyph-orientation-vertical\", \"text-anchor\", \"writing-mode\"\n ], propertyKeywords = keySet(propertyKeywords_);\n\n var nonStandardPropertyKeywords_ = [\n \"scrollbar-arrow-color\", \"scrollbar-base-color\", \"scrollbar-dark-shadow-color\",\n \"scrollbar-face-color\", \"scrollbar-highlight-color\", \"scrollbar-shadow-color\",\n \"scrollbar-3d-light-color\", \"scrollbar-track-color\", \"shape-inside\",\n \"searchfield-cancel-button\", \"searchfield-decoration\", \"searchfield-results-button\",\n \"searchfield-results-decoration\", \"zoom\"\n ], nonStandardPropertyKeywords = keySet(nonStandardPropertyKeywords_);\n\n var fontProperties_ = [\n \"font-family\", \"src\", \"unicode-range\", \"font-variant\", \"font-feature-settings\",\n \"font-stretch\", \"font-weight\", \"font-style\"\n ], fontProperties = keySet(fontProperties_);\n\n var counterDescriptors_ = [\n \"additive-symbols\", \"fallback\", \"negative\", \"pad\", \"prefix\", \"range\",\n \"speak-as\", \"suffix\", \"symbols\", \"system\"\n ], counterDescriptors = keySet(counterDescriptors_);\n\n var colorKeywords_ = [\n \"aliceblue\", \"antiquewhite\", \"aqua\", \"aquamarine\", \"azure\", \"beige\",\n \"bisque\", \"black\", \"blanchedalmond\", \"blue\", \"blueviolet\", \"brown\",\n \"burlywood\", \"cadetblue\", \"chartreuse\", \"chocolate\", \"coral\", \"cornflowerblue\",\n \"cornsilk\", \"crimson\", \"cyan\", \"darkblue\", \"darkcyan\", \"darkgoldenrod\",\n \"darkgray\", \"darkgreen\", \"darkkhaki\", \"darkmagenta\", \"darkolivegreen\",\n \"darkorange\", \"darkorchid\", \"darkred\", \"darksalmon\", \"darkseagreen\",\n \"darkslateblue\", \"darkslategray\", \"darkturquoise\", \"darkviolet\",\n \"deeppink\", \"deepskyblue\", \"dimgray\", \"dodgerblue\", \"firebrick\",\n \"floralwhite\", \"forestgreen\", \"fuchsia\", \"gainsboro\", \"ghostwhite\",\n \"gold\", \"goldenrod\", \"gray\", \"grey\", \"green\", \"greenyellow\", \"honeydew\",\n \"hotpink\", \"indianred\", \"indigo\", \"ivory\", \"khaki\", \"lavender\",\n \"lavenderblush\", \"lawngreen\", \"lemonchiffon\", \"lightblue\", \"lightcoral\",\n \"lightcyan\", \"lightgoldenrodyellow\", \"lightgray\", \"lightgreen\", \"lightpink\",\n \"lightsalmon\", \"lightseagreen\", \"lightskyblue\", \"lightslategray\",\n \"lightsteelblue\", \"lightyellow\", \"lime\", \"limegreen\", \"linen\", \"magenta\",\n \"maroon\", \"mediumaquamarine\", \"mediumblue\", \"mediumorchid\", \"mediumpurple\",\n \"mediumseagreen\", \"mediumslateblue\", \"mediumspringgreen\", \"mediumturquoise\",\n \"mediumvioletred\", \"midnightblue\", \"mintcream\", \"mistyrose\", \"moccasin\",\n \"navajowhite\", \"navy\", \"oldlace\", \"olive\", \"olivedrab\", \"orange\", \"orangered\",\n \"orchid\", \"palegoldenrod\", \"palegreen\", \"paleturquoise\", \"palevioletred\",\n \"papayawhip\", \"peachpuff\", \"peru\", \"pink\", \"plum\", \"powderblue\",\n \"purple\", \"rebeccapurple\", \"red\", \"rosybrown\", \"royalblue\", \"saddlebrown\",\n \"salmon\", \"sandybrown\", \"seagreen\", \"seashell\", \"sienna\", \"silver\", \"skyblue\",\n \"slateblue\", \"slategray\", \"snow\", \"springgreen\", \"steelblue\", \"tan\",\n \"teal\", \"thistle\", \"tomato\", \"turquoise\", \"violet\", \"wheat\", \"white\",\n \"whitesmoke\", \"yellow\", \"yellowgreen\"\n ], colorKeywords = keySet(colorKeywords_);\n\n var valueKeywords_ = [\n \"above\", \"absolute\", \"activeborder\", \"additive\", \"activecaption\", \"afar\",\n \"after-white-space\", \"ahead\", \"alias\", \"all\", \"all-scroll\", \"alphabetic\", \"alternate\",\n \"always\", \"amharic\", \"amharic-abegede\", \"antialiased\", \"appworkspace\",\n \"arabic-indic\", \"armenian\", \"asterisks\", \"attr\", \"auto\", \"avoid\", \"avoid-column\", \"avoid-page\",\n \"avoid-region\", \"background\", \"backwards\", \"baseline\", \"below\", \"bidi-override\", \"binary\",\n \"bengali\", \"blink\", \"block\", \"block-axis\", \"bold\", \"bolder\", \"border\", \"border-box\",\n \"both\", \"bottom\", \"break\", \"break-all\", \"break-word\", \"bullets\", \"button\", \"button-bevel\",\n \"buttonface\", \"buttonhighlight\", \"buttonshadow\", \"buttontext\", \"calc\", \"cambodian\",\n \"capitalize\", \"caps-lock-indicator\", \"caption\", \"captiontext\", \"caret\",\n \"cell\", \"center\", \"checkbox\", \"circle\", \"cjk-decimal\", \"cjk-earthly-branch\",\n \"cjk-heavenly-stem\", \"cjk-ideographic\", \"clear\", \"clip\", \"close-quote\",\n \"col-resize\", \"collapse\", \"color\", \"color-burn\", \"color-dodge\", \"column\", \"column-reverse\",\n \"compact\", \"condensed\", \"contain\", \"content\",\n \"content-box\", \"context-menu\", \"continuous\", \"copy\", \"counter\", \"counters\", \"cover\", \"crop\",\n \"cross\", \"crosshair\", \"currentcolor\", \"cursive\", \"cyclic\", \"darken\", \"dashed\", \"decimal\",\n \"decimal-leading-zero\", \"default\", \"default-button\", \"destination-atop\",\n \"destination-in\", \"destination-out\", \"destination-over\", \"devanagari\", \"difference\",\n \"disc\", \"discard\", \"disclosure-closed\", \"disclosure-open\", \"document\",\n \"dot-dash\", \"dot-dot-dash\",\n \"dotted\", \"double\", \"down\", \"e-resize\", \"ease\", \"ease-in\", \"ease-in-out\", \"ease-out\",\n \"element\", \"ellipse\", \"ellipsis\", \"embed\", \"end\", \"ethiopic\", \"ethiopic-abegede\",\n \"ethiopic-abegede-am-et\", \"ethiopic-abegede-gez\", \"ethiopic-abegede-ti-er\",\n \"ethiopic-abegede-ti-et\", \"ethiopic-halehame-aa-er\",\n \"ethiopic-halehame-aa-et\", \"ethiopic-halehame-am-et\",\n \"ethiopic-halehame-gez\", \"ethiopic-halehame-om-et\",\n \"ethiopic-halehame-sid-et\", \"ethiopic-halehame-so-et\",\n \"ethiopic-halehame-ti-er\", \"ethiopic-halehame-ti-et\", \"ethiopic-halehame-tig\",\n \"ethiopic-numeric\", \"ew-resize\", \"exclusion\", \"expanded\", \"extends\", \"extra-condensed\",\n \"extra-expanded\", \"fantasy\", \"fast\", \"fill\", \"fixed\", \"flat\", \"flex\", \"flex-end\", \"flex-start\", \"footnotes\",\n \"forwards\", \"from\", \"geometricPrecision\", \"georgian\", \"graytext\", \"groove\",\n \"gujarati\", \"gurmukhi\", \"hand\", \"hangul\", \"hangul-consonant\", \"hard-light\", \"hebrew\",\n \"help\", \"hidden\", \"hide\", \"higher\", \"highlight\", \"highlighttext\",\n \"hiragana\", \"hiragana-iroha\", \"horizontal\", \"hsl\", \"hsla\", \"hue\", \"icon\", \"ignore\",\n \"inactiveborder\", \"inactivecaption\", \"inactivecaptiontext\", \"infinite\",\n \"infobackground\", \"infotext\", \"inherit\", \"initial\", \"inline\", \"inline-axis\",\n \"inline-block\", \"inline-flex\", \"inline-table\", \"inset\", \"inside\", \"intrinsic\", \"invert\",\n \"italic\", \"japanese-formal\", \"japanese-informal\", \"justify\", \"kannada\",\n \"katakana\", \"katakana-iroha\", \"keep-all\", \"khmer\",\n \"korean-hangul-formal\", \"korean-hanja-formal\", \"korean-hanja-informal\",\n \"landscape\", \"lao\", \"large\", \"larger\", \"left\", \"level\", \"lighter\", \"lighten\",\n \"line-through\", \"linear\", \"linear-gradient\", \"lines\", \"list-item\", \"listbox\", \"listitem\",\n \"local\", \"logical\", \"loud\", \"lower\", \"lower-alpha\", \"lower-armenian\",\n \"lower-greek\", \"lower-hexadecimal\", \"lower-latin\", \"lower-norwegian\",\n \"lower-roman\", \"lowercase\", \"ltr\", \"luminosity\", \"malayalam\", \"match\", \"matrix\", \"matrix3d\",\n \"media-controls-background\", \"media-current-time-display\",\n \"media-fullscreen-button\", \"media-mute-button\", \"media-play-button\",\n \"media-return-to-realtime-button\", \"media-rewind-button\",\n \"media-seek-back-button\", \"media-seek-forward-button\", \"media-slider\",\n \"media-sliderthumb\", \"media-time-remaining-display\", \"media-volume-slider\",\n \"media-volume-slider-container\", \"media-volume-sliderthumb\", \"medium\",\n \"menu\", \"menulist\", \"menulist-button\", \"menulist-text\",\n \"menulist-textfield\", \"menutext\", \"message-box\", \"middle\", \"min-intrinsic\",\n \"mix\", \"mongolian\", \"monospace\", \"move\", \"multiple\", \"multiply\", \"myanmar\", \"n-resize\",\n \"narrower\", \"ne-resize\", \"nesw-resize\", \"no-close-quote\", \"no-drop\",\n \"no-open-quote\", \"no-repeat\", \"none\", \"normal\", \"not-allowed\", \"nowrap\",\n \"ns-resize\", \"numbers\", \"numeric\", \"nw-resize\", \"nwse-resize\", \"oblique\", \"octal\", \"open-quote\",\n \"optimizeLegibility\", \"optimizeSpeed\", \"oriya\", \"oromo\", \"outset\",\n \"outside\", \"outside-shape\", \"overlay\", \"overline\", \"padding\", \"padding-box\",\n \"painted\", \"page\", \"paused\", \"persian\", \"perspective\", \"plus-darker\", \"plus-lighter\",\n \"pointer\", \"polygon\", \"portrait\", \"pre\", \"pre-line\", \"pre-wrap\", \"preserve-3d\",\n \"progress\", \"push-button\", \"radial-gradient\", \"radio\", \"read-only\",\n \"read-write\", \"read-write-plaintext-only\", \"rectangle\", \"region\",\n \"relative\", \"repeat\", \"repeating-linear-gradient\",\n \"repeating-radial-gradient\", \"repeat-x\", \"repeat-y\", \"reset\", \"reverse\",\n \"rgb\", \"rgba\", \"ridge\", \"right\", \"rotate\", \"rotate3d\", \"rotateX\", \"rotateY\",\n \"rotateZ\", \"round\", \"row\", \"row-resize\", \"row-reverse\", \"rtl\", \"run-in\", \"running\",\n \"s-resize\", \"sans-serif\", \"saturation\", \"scale\", \"scale3d\", \"scaleX\", \"scaleY\", \"scaleZ\", \"screen\",\n \"scroll\", \"scrollbar\", \"se-resize\", \"searchfield\",\n \"searchfield-cancel-button\", \"searchfield-decoration\",\n \"searchfield-results-button\", \"searchfield-results-decoration\",\n \"semi-condensed\", \"semi-expanded\", \"separate\", \"serif\", \"show\", \"sidama\",\n \"simp-chinese-formal\", \"simp-chinese-informal\", \"single\",\n \"skew\", \"skewX\", \"skewY\", \"skip-white-space\", \"slide\", \"slider-horizontal\",\n \"slider-vertical\", \"sliderthumb-horizontal\", \"sliderthumb-vertical\", \"slow\",\n \"small\", \"small-caps\", \"small-caption\", \"smaller\", \"soft-light\", \"solid\", \"somali\",\n \"source-atop\", \"source-in\", \"source-out\", \"source-over\", \"space\", \"space-around\", \"space-between\", \"spell-out\", \"square\",\n \"square-button\", \"start\", \"static\", \"status-bar\", \"stretch\", \"stroke\", \"sub\",\n \"subpixel-antialiased\", \"super\", \"sw-resize\", \"symbolic\", \"symbols\", \"table\",\n \"table-caption\", \"table-cell\", \"table-column\", \"table-column-group\",\n \"table-footer-group\", \"table-header-group\", \"table-row\", \"table-row-group\",\n \"tamil\",\n \"telugu\", \"text\", \"text-bottom\", \"text-top\", \"textarea\", \"textfield\", \"thai\",\n \"thick\", \"thin\", \"threeddarkshadow\", \"threedface\", \"threedhighlight\",\n \"threedlightshadow\", \"threedshadow\", \"tibetan\", \"tigre\", \"tigrinya-er\",\n \"tigrinya-er-abegede\", \"tigrinya-et\", \"tigrinya-et-abegede\", \"to\", \"top\",\n \"trad-chinese-formal\", \"trad-chinese-informal\",\n \"translate\", \"translate3d\", \"translateX\", \"translateY\", \"translateZ\",\n \"transparent\", \"ultra-condensed\", \"ultra-expanded\", \"underline\", \"up\",\n \"upper-alpha\", \"upper-armenian\", \"upper-greek\", \"upper-hexadecimal\",\n \"upper-latin\", \"upper-norwegian\", \"upper-roman\", \"uppercase\", \"urdu\", \"url\",\n \"var\", \"vertical\", \"vertical-text\", \"visible\", \"visibleFill\", \"visiblePainted\",\n \"visibleStroke\", \"visual\", \"w-resize\", \"wait\", \"wave\", \"wider\",\n \"window\", \"windowframe\", \"windowtext\", \"words\", \"wrap\", \"wrap-reverse\", \"x-large\", \"x-small\", \"xor\",\n \"xx-large\", \"xx-small\"\n ], valueKeywords = keySet(valueKeywords_);\n\n var allWords = documentTypes_.concat(mediaTypes_).concat(mediaFeatures_).concat(mediaValueKeywords_)\n .concat(propertyKeywords_).concat(nonStandardPropertyKeywords_).concat(colorKeywords_)\n .concat(valueKeywords_);\n CodeMirror.registerHelper(\"hintWords\", \"css\", allWords);\n\n function tokenCComment(stream, state) {\n var maybeEnd = false, ch;\n while ((ch = stream.next()) != null) {\n if (maybeEnd && ch == \"/\") {\n state.tokenize = null;\n break;\n }\n maybeEnd = (ch == \"*\");\n }\n return [\"comment\", \"comment\"];\n }\n\n CodeMirror.defineMIME(\"text/css\", {\n documentTypes: documentTypes,\n mediaTypes: mediaTypes,\n mediaFeatures: mediaFeatures,\n mediaValueKeywords: mediaValueKeywords,\n propertyKeywords: propertyKeywords,\n nonStandardPropertyKeywords: nonStandardPropertyKeywords,\n fontProperties: fontProperties,\n counterDescriptors: counterDescriptors,\n colorKeywords: colorKeywords,\n valueKeywords: valueKeywords,\n tokenHooks: {\n \"/\": function(stream, state) {\n if (!stream.eat(\"*\")) return false;\n state.tokenize = tokenCComment;\n return tokenCComment(stream, state);\n }\n },\n name: \"css\"\n });\n\n CodeMirror.defineMIME(\"text/x-scss\", {\n mediaTypes: mediaTypes,\n mediaFeatures: mediaFeatures,\n mediaValueKeywords: mediaValueKeywords,\n propertyKeywords: propertyKeywords,\n nonStandardPropertyKeywords: nonStandardPropertyKeywords,\n colorKeywords: colorKeywords,\n valueKeywords: valueKeywords,\n fontProperties: fontProperties,\n allowNested: true,\n tokenHooks: {\n \"/\": function(stream, state) {\n if (stream.eat(\"/\")) {\n stream.skipToEnd();\n return [\"comment\", \"comment\"];\n } else if (stream.eat(\"*\")) {\n state.tokenize = tokenCComment;\n return tokenCComment(stream, state);\n } else {\n return [\"operator\", \"operator\"];\n }\n },\n \":\": function(stream) {\n if (stream.match(/\\s*\\{/))\n return [null, \"{\"];\n return false;\n },\n \"$\": function(stream) {\n stream.match(/^[\\w-]+/);\n if (stream.match(/^\\s*:/, false))\n return [\"variable-2\", \"variable-definition\"];\n return [\"variable-2\", \"variable\"];\n },\n \"#\": function(stream) {\n if (!stream.eat(\"{\")) return false;\n return [null, \"interpolation\"];\n }\n },\n name: \"css\",\n helperType: \"scss\"\n });\n\n CodeMirror.defineMIME(\"text/x-less\", {\n mediaTypes: mediaTypes,\n mediaFeatures: mediaFeatures,\n mediaValueKeywords: mediaValueKeywords,\n propertyKeywords: propertyKeywords,\n nonStandardPropertyKeywords: nonStandardPropertyKeywords,\n colorKeywords: colorKeywords,\n valueKeywords: valueKeywords,\n fontProperties: fontProperties,\n allowNested: true,\n tokenHooks: {\n \"/\": function(stream, state) {\n if (stream.eat(\"/\")) {\n stream.skipToEnd();\n return [\"comment\", \"comment\"];\n } else if (stream.eat(\"*\")) {\n state.tokenize = tokenCComment;\n return tokenCComment(stream, state);\n } else {\n return [\"operator\", \"operator\"];\n }\n },\n \"@\": function(stream) {\n if (stream.eat(\"{\")) return [null, \"interpolation\"];\n if (stream.match(/^(charset|document|font-face|import|(-(moz|ms|o|webkit)-)?keyframes|media|namespace|page|supports)\\b/, false)) return false;\n stream.eatWhile(/[\\w\\\\\\-]/);\n if (stream.match(/^\\s*:/, false))\n return [\"variable-2\", \"variable-definition\"];\n return [\"variable-2\", \"variable\"];\n },\n \"&\": function() {\n return [\"atom\", \"atom\"];\n }\n },\n name: \"css\",\n helperType: \"less\"\n });\n\n CodeMirror.defineMIME(\"text/x-gss\", {\n documentTypes: documentTypes,\n mediaTypes: mediaTypes,\n mediaFeatures: mediaFeatures,\n propertyKeywords: propertyKeywords,\n nonStandardPropertyKeywords: nonStandardPropertyKeywords,\n fontProperties: fontProperties,\n counterDescriptors: counterDescriptors,\n colorKeywords: colorKeywords,\n valueKeywords: valueKeywords,\n supportsAtComponent: true,\n tokenHooks: {\n \"/\": function(stream, state) {\n if (!stream.eat(\"*\")) return false;\n state.tokenize = tokenCComment;\n return tokenCComment(stream, state);\n }\n },\n name: \"css\",\n helperType: \"gss\"\n });\n\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/htmlembedded/htmlembedded.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/htmlembedded/htmlembedded.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"), require(\"../htmlmixed/htmlmixed\"),\n require(\"../../addon/mode/multiplex\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\", \"../htmlmixed/htmlmixed\",\n \"../../addon/mode/multiplex\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n\n CodeMirror.defineMode(\"htmlembedded\", function(config, parserConfig) {\n return CodeMirror.multiplexingMode(CodeMirror.getMode(config, \"htmlmixed\"), {\n open: parserConfig.open || parserConfig.scriptStartRegex || \"<%\",\n close: parserConfig.close || parserConfig.scriptEndRegex || \"%>\",\n mode: CodeMirror.getMode(config, parserConfig.scriptingModeSpec)\n });\n }, \"htmlmixed\");\n\n CodeMirror.defineMIME(\"application/x-ejs\", {name: \"htmlembedded\", scriptingModeSpec:\"javascript\"});\n CodeMirror.defineMIME(\"application/x-aspx\", {name: \"htmlembedded\", scriptingModeSpec:\"text/x-csharp\"});\n CodeMirror.defineMIME(\"application/x-jsp\", {name: \"htmlembedded\", scriptingModeSpec:\"text/x-java\"});\n CodeMirror.defineMIME(\"application/x-erb\", {name: \"htmlembedded\", scriptingModeSpec:\"ruby\"});\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/htmlmixed/htmlmixed.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/htmlmixed/htmlmixed.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"), require(\"../xml/xml\"), require(\"../javascript/javascript\"), require(\"../css/css\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\", \"../xml/xml\", \"../javascript/javascript\", \"../css/css\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n\n var defaultTags = {\n script: [\n [\"lang\", /(javascript|babel)/i, \"javascript\"],\n [\"type\", /^(?:text|application)\\/(?:x-)?(?:java|ecma)script$|^$/i, \"javascript\"],\n [\"type\", /./, \"text/plain\"],\n [null, null, \"javascript\"]\n ],\n style: [\n [\"lang\", /^css$/i, \"css\"],\n [\"type\", /^(text\\/)?(x-)?(stylesheet|css)$/i, \"css\"],\n [\"type\", /./, \"text/plain\"],\n [null, null, \"css\"]\n ]\n };\n\n function maybeBackup(stream, pat, style) {\n var cur = stream.current(), close = cur.search(pat);\n if (close > -1) {\n stream.backUp(cur.length - close);\n } else if (cur.match(/<\\/?$/)) {\n stream.backUp(cur.length);\n if (!stream.match(pat, false)) stream.match(cur);\n }\n return style;\n }\n\n var attrRegexpCache = {};\n function getAttrRegexp(attr) {\n var regexp = attrRegexpCache[attr];\n if (regexp) return regexp;\n return attrRegexpCache[attr] = new RegExp(\"\\\\s+\" + attr + \"\\\\s*=\\\\s*('|\\\")?([^'\\\"]+)('|\\\")?\\\\s*\");\n }\n\n function getAttrValue(text, attr) {\n var match = text.match(getAttrRegexp(attr))\n return match ? match[2] : \"\"\n }\n\n function getTagRegexp(tagName, anchored) {\n return new RegExp((anchored ? \"^\" : \"\") + \"<\\/\\s*\" + tagName + \"\\s*>\", \"i\");\n }\n\n function addTags(from, to) {\n for (var tag in from) {\n var dest = to[tag] || (to[tag] = []);\n var source = from[tag];\n for (var i = source.length - 1; i >= 0; i--)\n dest.unshift(source[i])\n }\n }\n\n function findMatchingMode(tagInfo, tagText) {\n for (var i = 0; i < tagInfo.length; i++) {\n var spec = tagInfo[i];\n if (!spec[0] || spec[1].test(getAttrValue(tagText, spec[0]))) return spec[2];\n }\n }\n\n CodeMirror.defineMode(\"htmlmixed\", function (config, parserConfig) {\n var htmlMode = CodeMirror.getMode(config, {\n name: \"xml\",\n htmlMode: true,\n multilineTagIndentFactor: parserConfig.multilineTagIndentFactor,\n multilineTagIndentPastTag: parserConfig.multilineTagIndentPastTag\n });\n\n var tags = {};\n var configTags = parserConfig && parserConfig.tags, configScript = parserConfig && parserConfig.scriptTypes;\n addTags(defaultTags, tags);\n if (configTags) addTags(configTags, tags);\n if (configScript) for (var i = configScript.length - 1; i >= 0; i--)\n tags.script.unshift([\"type\", configScript[i].matches, configScript[i].mode])\n\n function html(stream, state) {\n var style = htmlMode.token(stream, state.htmlState), tag = /\\btag\\b/.test(style), tagName\n if (tag && !/[<>\\s\\/]/.test(stream.current()) &&\n (tagName = state.htmlState.tagName && state.htmlState.tagName.toLowerCase()) &&\n tags.hasOwnProperty(tagName)) {\n state.inTag = tagName + \" \"\n } else if (state.inTag && tag && />$/.test(stream.current())) {\n var inTag = /^([\\S]+) (.*)/.exec(state.inTag)\n state.inTag = null\n var modeSpec = stream.current() == \">\" && findMatchingMode(tags[inTag[1]], inTag[2])\n var mode = CodeMirror.getMode(config, modeSpec)\n var endTagA = getTagRegexp(inTag[1], true), endTag = getTagRegexp(inTag[1], false);\n state.token = function (stream, state) {\n if (stream.match(endTagA, false)) {\n state.token = html;\n state.localState = state.localMode = null;\n return null;\n }\n return maybeBackup(stream, endTag, state.localMode.token(stream, state.localState));\n };\n state.localMode = mode;\n state.localState = CodeMirror.startState(mode, htmlMode.indent(state.htmlState, \"\"));\n } else if (state.inTag) {\n state.inTag += stream.current()\n if (stream.eol()) state.inTag += \" \"\n }\n return style;\n };\n\n return {\n startState: function () {\n var state = htmlMode.startState();\n return {token: html, inTag: null, localMode: null, localState: null, htmlState: state};\n },\n\n copyState: function (state) {\n var local;\n if (state.localState) {\n local = CodeMirror.copyState(state.localMode, state.localState);\n }\n return {token: state.token, inTag: state.inTag,\n localMode: state.localMode, localState: local,\n htmlState: CodeMirror.copyState(htmlMode, state.htmlState)};\n },\n\n token: function (stream, state) {\n return state.token(stream, state);\n },\n\n indent: function (state, textAfter) {\n if (!state.localMode || /^\\s*<\\//.test(textAfter))\n return htmlMode.indent(state.htmlState, textAfter);\n else if (state.localMode.indent)\n return state.localMode.indent(state.localState, textAfter);\n else\n return CodeMirror.Pass;\n },\n\n innerMode: function (state) {\n return {state: state.localState || state.htmlState, mode: state.localMode || htmlMode};\n }\n };\n }, \"xml\", \"javascript\", \"css\");\n\n CodeMirror.defineMIME(\"text/html\", \"htmlmixed\");\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n// TODO actually recognize syntax of TypeScript constructs\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nfunction expressionAllowed(stream, state, backUp) {\n return /^(?:operator|sof|keyword c|case|new|[\\[{}\\(,;:]|=>)$/.test(state.lastType) ||\n (state.lastType == \"quasi\" && /\\{\\s*$/.test(stream.string.slice(0, stream.pos - (backUp || 0))))\n}\n\nCodeMirror.defineMode(\"javascript\", function(config, parserConfig) {\n var indentUnit = config.indentUnit;\n var statementIndent = parserConfig.statementIndent;\n var jsonldMode = parserConfig.jsonld;\n var jsonMode = parserConfig.json || jsonldMode;\n var isTS = parserConfig.typescript;\n var wordRE = parserConfig.wordCharacters || /[\\w$\\xa1-\\uffff]/;\n\n // Tokenizer\n\n var keywords = function(){\n function kw(type) {return {type: type, style: \"keyword\"};}\n var A = kw(\"keyword a\"), B = kw(\"keyword b\"), C = kw(\"keyword c\");\n var operator = kw(\"operator\"), atom = {type: \"atom\", style: \"atom\"};\n\n var jsKeywords = {\n \"if\": kw(\"if\"), \"while\": A, \"with\": A, \"else\": B, \"do\": B, \"try\": B, \"finally\": B,\n \"return\": C, \"break\": C, \"continue\": C, \"new\": kw(\"new\"), \"delete\": C, \"throw\": C, \"debugger\": C,\n \"var\": kw(\"var\"), \"const\": kw(\"var\"), \"let\": kw(\"var\"),\n \"function\": kw(\"function\"), \"catch\": kw(\"catch\"),\n \"for\": kw(\"for\"), \"switch\": kw(\"switch\"), \"case\": kw(\"case\"), \"default\": kw(\"default\"),\n \"in\": operator, \"typeof\": operator, \"instanceof\": operator,\n \"true\": atom, \"false\": atom, \"null\": atom, \"undefined\": atom, \"NaN\": atom, \"Infinity\": atom,\n \"this\": kw(\"this\"), \"class\": kw(\"class\"), \"super\": kw(\"atom\"),\n \"yield\": C, \"export\": kw(\"export\"), \"import\": kw(\"import\"), \"extends\": C\n };\n\n // Extend the 'normal' keywords with the TypeScript language extensions\n if (isTS) {\n var type = {type: \"variable\", style: \"variable-3\"};\n var tsKeywords = {\n // object-like things\n \"interface\": kw(\"class\"),\n \"implements\": C,\n \"namespace\": C,\n \"module\": kw(\"module\"),\n \"enum\": kw(\"module\"),\n\n // scope modifiers\n \"public\": kw(\"modifier\"),\n \"private\": kw(\"modifier\"),\n \"protected\": kw(\"modifier\"),\n \"abstract\": kw(\"modifier\"),\n\n // operators\n \"as\": operator,\n\n // types\n \"string\": type, \"number\": type, \"boolean\": type, \"any\": type\n };\n\n for (var attr in tsKeywords) {\n jsKeywords[attr] = tsKeywords[attr];\n }\n }\n\n return jsKeywords;\n }();\n\n var isOperatorChar = /[+\\-*&%=<>!?|~^]/;\n var isJsonldKeyword = /^@(context|id|value|language|type|container|list|set|reverse|index|base|vocab|graph)\"/;\n\n function readRegexp(stream) {\n var escaped = false, next, inSet = false;\n while ((next = stream.next()) != null) {\n if (!escaped) {\n if (next == \"/\" && !inSet) return;\n if (next == \"[\") inSet = true;\n else if (inSet && next == \"]\") inSet = false;\n }\n escaped = !escaped && next == \"\\\\\";\n }\n }\n\n // Used as scratch variables to communicate multiple values without\n // consing up tons of objects.\n var type, content;\n function ret(tp, style, cont) {\n type = tp; content = cont;\n return style;\n }\n function tokenBase(stream, state) {\n var ch = stream.next();\n if (ch == '\"' || ch == \"'\") {\n state.tokenize = tokenString(ch);\n return state.tokenize(stream, state);\n } else if (ch == \".\" && stream.match(/^\\d+(?:[eE][+\\-]?\\d+)?/)) {\n return ret(\"number\", \"number\");\n } else if (ch == \".\" && stream.match(\"..\")) {\n return ret(\"spread\", \"meta\");\n } else if (/[\\[\\]{}\\(\\),;\\:\\.]/.test(ch)) {\n return ret(ch);\n } else if (ch == \"=\" && stream.eat(\">\")) {\n return ret(\"=>\", \"operator\");\n } else if (ch == \"0\" && stream.eat(/x/i)) {\n stream.eatWhile(/[\\da-f]/i);\n return ret(\"number\", \"number\");\n } else if (ch == \"0\" && stream.eat(/o/i)) {\n stream.eatWhile(/[0-7]/i);\n return ret(\"number\", \"number\");\n } else if (ch == \"0\" && stream.eat(/b/i)) {\n stream.eatWhile(/[01]/i);\n return ret(\"number\", \"number\");\n } else if (/\\d/.test(ch)) {\n stream.match(/^\\d*(?:\\.\\d*)?(?:[eE][+\\-]?\\d+)?/);\n return ret(\"number\", \"number\");\n } else if (ch == \"/\") {\n if (stream.eat(\"*\")) {\n state.tokenize = tokenComment;\n return tokenComment(stream, state);\n } else if (stream.eat(\"/\")) {\n stream.skipToEnd();\n return ret(\"comment\", \"comment\");\n } else if (expressionAllowed(stream, state, 1)) {\n readRegexp(stream);\n stream.match(/^\\b(([gimyu])(?![gimyu]*\\2))+\\b/);\n return ret(\"regexp\", \"string-2\");\n } else {\n stream.eatWhile(isOperatorChar);\n return ret(\"operator\", \"operator\", stream.current());\n }\n } else if (ch == \"`\") {\n state.tokenize = tokenQuasi;\n return tokenQuasi(stream, state);\n } else if (ch == \"#\") {\n stream.skipToEnd();\n return ret(\"error\", \"error\");\n } else if (isOperatorChar.test(ch)) {\n stream.eatWhile(isOperatorChar);\n return ret(\"operator\", \"operator\", stream.current());\n } else if (wordRE.test(ch)) {\n stream.eatWhile(wordRE);\n var word = stream.current(), known = keywords.propertyIsEnumerable(word) && keywords[word];\n return (known && state.lastType != \".\") ? ret(known.type, known.style, word) :\n ret(\"variable\", \"variable\", word);\n }\n }\n\n function tokenString(quote) {\n return function(stream, state) {\n var escaped = false, next;\n if (jsonldMode && stream.peek() == \"@\" && stream.match(isJsonldKeyword)){\n state.tokenize = tokenBase;\n return ret(\"jsonld-keyword\", \"meta\");\n }\n while ((next = stream.next()) != null) {\n if (next == quote && !escaped) break;\n escaped = !escaped && next == \"\\\\\";\n }\n if (!escaped) state.tokenize = tokenBase;\n return ret(\"string\", \"string\");\n };\n }\n\n function tokenComment(stream, state) {\n var maybeEnd = false, ch;\n while (ch = stream.next()) {\n if (ch == \"/\" && maybeEnd) {\n state.tokenize = tokenBase;\n break;\n }\n maybeEnd = (ch == \"*\");\n }\n return ret(\"comment\", \"comment\");\n }\n\n function tokenQuasi(stream, state) {\n var escaped = false, next;\n while ((next = stream.next()) != null) {\n if (!escaped && (next == \"`\" || next == \"$\" && stream.eat(\"{\"))) {\n state.tokenize = tokenBase;\n break;\n }\n escaped = !escaped && next == \"\\\\\";\n }\n return ret(\"quasi\", \"string-2\", stream.current());\n }\n\n var brackets = \"([{}])\";\n // This is a crude lookahead trick to try and notice that we're\n // parsing the argument patterns for a fat-arrow function before we\n // actually hit the arrow token. It only works if the arrow is on\n // the same line as the arguments and there's no strange noise\n // (comments) in between. Fallback is to only notice when we hit the\n // arrow, and not declare the arguments as locals for the arrow\n // body.\n function findFatArrow(stream, state) {\n if (state.fatArrowAt) state.fatArrowAt = null;\n var arrow = stream.string.indexOf(\"=>\", stream.start);\n if (arrow < 0) return;\n\n var depth = 0, sawSomething = false;\n for (var pos = arrow - 1; pos >= 0; --pos) {\n var ch = stream.string.charAt(pos);\n var bracket = brackets.indexOf(ch);\n if (bracket >= 0 && bracket < 3) {\n if (!depth) { ++pos; break; }\n if (--depth == 0) break;\n } else if (bracket >= 3 && bracket < 6) {\n ++depth;\n } else if (wordRE.test(ch)) {\n sawSomething = true;\n } else if (/[\"'\\/]/.test(ch)) {\n return;\n } else if (sawSomething && !depth) {\n ++pos;\n break;\n }\n }\n if (sawSomething && !depth) state.fatArrowAt = pos;\n }\n\n // Parser\n\n var atomicTypes = {\"atom\": true, \"number\": true, \"variable\": true, \"string\": true, \"regexp\": true, \"this\": true, \"jsonld-keyword\": true};\n\n function JSLexical(indented, column, type, align, prev, info) {\n this.indented = indented;\n this.column = column;\n this.type = type;\n this.prev = prev;\n this.info = info;\n if (align != null) this.align = align;\n }\n\n function inScope(state, varname) {\n for (var v = state.localVars; v; v = v.next)\n if (v.name == varname) return true;\n for (var cx = state.context; cx; cx = cx.prev) {\n for (var v = cx.vars; v; v = v.next)\n if (v.name == varname) return true;\n }\n }\n\n function parseJS(state, style, type, content, stream) {\n var cc = state.cc;\n // Communicate our context to the combinators.\n // (Less wasteful than consing up a hundred closures on every call.)\n cx.state = state; cx.stream = stream; cx.marked = null, cx.cc = cc; cx.style = style;\n\n if (!state.lexical.hasOwnProperty(\"align\"))\n state.lexical.align = true;\n\n while(true) {\n var combinator = cc.length ? cc.pop() : jsonMode ? expression : statement;\n if (combinator(type, content)) {\n while(cc.length && cc[cc.length - 1].lex)\n cc.pop()();\n if (cx.marked) return cx.marked;\n if (type == \"variable\" && inScope(state, content)) return \"variable-2\";\n return style;\n }\n }\n }\n\n // Combinator utils\n\n var cx = {state: null, column: null, marked: null, cc: null};\n function pass() {\n for (var i = arguments.length - 1; i >= 0; i--) cx.cc.push(arguments[i]);\n }\n function cont() {\n pass.apply(null, arguments);\n return true;\n }\n function register(varname) {\n function inList(list) {\n for (var v = list; v; v = v.next)\n if (v.name == varname) return true;\n return false;\n }\n var state = cx.state;\n cx.marked = \"def\";\n if (state.context) {\n if (inList(state.localVars)) return;\n state.localVars = {name: varname, next: state.localVars};\n } else {\n if (inList(state.globalVars)) return;\n if (parserConfig.globalVars)\n state.globalVars = {name: varname, next: state.globalVars};\n }\n }\n\n // Combinators\n\n var defaultVars = {name: \"this\", next: {name: \"arguments\"}};\n function pushcontext() {\n cx.state.context = {prev: cx.state.context, vars: cx.state.localVars};\n cx.state.localVars = defaultVars;\n }\n function popcontext() {\n cx.state.localVars = cx.state.context.vars;\n cx.state.context = cx.state.context.prev;\n }\n function pushlex(type, info) {\n var result = function() {\n var state = cx.state, indent = state.indented;\n if (state.lexical.type == \"stat\") indent = state.lexical.indented;\n else for (var outer = state.lexical; outer && outer.type == \")\" && outer.align; outer = outer.prev)\n indent = outer.indented;\n state.lexical = new JSLexical(indent, cx.stream.column(), type, null, state.lexical, info);\n };\n result.lex = true;\n return result;\n }\n function poplex() {\n var state = cx.state;\n if (state.lexical.prev) {\n if (state.lexical.type == \")\")\n state.indented = state.lexical.indented;\n state.lexical = state.lexical.prev;\n }\n }\n poplex.lex = true;\n\n function expect(wanted) {\n function exp(type) {\n if (type == wanted) return cont();\n else if (wanted == \";\") return pass();\n else return cont(exp);\n };\n return exp;\n }\n\n function statement(type, value) {\n if (type == \"var\") return cont(pushlex(\"vardef\", value.length), vardef, expect(\";\"), poplex);\n if (type == \"keyword a\") return cont(pushlex(\"form\"), expression, statement, poplex);\n if (type == \"keyword b\") return cont(pushlex(\"form\"), statement, poplex);\n if (type == \"{\") return cont(pushlex(\"}\"), block, poplex);\n if (type == \";\") return cont();\n if (type == \"if\") {\n if (cx.state.lexical.info == \"else\" && cx.state.cc[cx.state.cc.length - 1] == poplex)\n cx.state.cc.pop()();\n return cont(pushlex(\"form\"), expression, statement, poplex, maybeelse);\n }\n if (type == \"function\") return cont(functiondef);\n if (type == \"for\") return cont(pushlex(\"form\"), forspec, statement, poplex);\n if (type == \"variable\") return cont(pushlex(\"stat\"), maybelabel);\n if (type == \"switch\") return cont(pushlex(\"form\"), expression, pushlex(\"}\", \"switch\"), expect(\"{\"),\n block, poplex, poplex);\n if (type == \"case\") return cont(expression, expect(\":\"));\n if (type == \"default\") return cont(expect(\":\"));\n if (type == \"catch\") return cont(pushlex(\"form\"), pushcontext, expect(\"(\"), funarg, expect(\")\"),\n statement, poplex, popcontext);\n if (type == \"class\") return cont(pushlex(\"form\"), className, poplex);\n if (type == \"export\") return cont(pushlex(\"stat\"), afterExport, poplex);\n if (type == \"import\") return cont(pushlex(\"stat\"), afterImport, poplex);\n if (type == \"module\") return cont(pushlex(\"form\"), pattern, pushlex(\"}\"), expect(\"{\"), block, poplex, poplex)\n return pass(pushlex(\"stat\"), expression, expect(\";\"), poplex);\n }\n function expression(type) {\n return expressionInner(type, false);\n }\n function expressionNoComma(type) {\n return expressionInner(type, true);\n }\n function expressionInner(type, noComma) {\n if (cx.state.fatArrowAt == cx.stream.start) {\n var body = noComma ? arrowBodyNoComma : arrowBody;\n if (type == \"(\") return cont(pushcontext, pushlex(\")\"), commasep(pattern, \")\"), poplex, expect(\"=>\"), body, popcontext);\n else if (type == \"variable\") return pass(pushcontext, pattern, expect(\"=>\"), body, popcontext);\n }\n\n var maybeop = noComma ? maybeoperatorNoComma : maybeoperatorComma;\n if (atomicTypes.hasOwnProperty(type)) return cont(maybeop);\n if (type == \"function\") return cont(functiondef, maybeop);\n if (type == \"keyword c\") return cont(noComma ? maybeexpressionNoComma : maybeexpression);\n if (type == \"(\") return cont(pushlex(\")\"), maybeexpression, comprehension, expect(\")\"), poplex, maybeop);\n if (type == \"operator\" || type == \"spread\") return cont(noComma ? expressionNoComma : expression);\n if (type == \"[\") return cont(pushlex(\"]\"), arrayLiteral, poplex, maybeop);\n if (type == \"{\") return contCommasep(objprop, \"}\", null, maybeop);\n if (type == \"quasi\") return pass(quasi, maybeop);\n if (type == \"new\") return cont(maybeTarget(noComma));\n return cont();\n }\n function maybeexpression(type) {\n if (type.match(/[;\\}\\)\\],]/)) return pass();\n return pass(expression);\n }\n function maybeexpressionNoComma(type) {\n if (type.match(/[;\\}\\)\\],]/)) return pass();\n return pass(expressionNoComma);\n }\n\n function maybeoperatorComma(type, value) {\n if (type == \",\") return cont(expression);\n return maybeoperatorNoComma(type, value, false);\n }\n function maybeoperatorNoComma(type, value, noComma) {\n var me = noComma == false ? maybeoperatorComma : maybeoperatorNoComma;\n var expr = noComma == false ? expression : expressionNoComma;\n if (type == \"=>\") return cont(pushcontext, noComma ? arrowBodyNoComma : arrowBody, popcontext);\n if (type == \"operator\") {\n if (/\\+\\+|--/.test(value)) return cont(me);\n if (value == \"?\") return cont(expression, expect(\":\"), expr);\n return cont(expr);\n }\n if (type == \"quasi\") { return pass(quasi, me); }\n if (type == \";\") return;\n if (type == \"(\") return contCommasep(expressionNoComma, \")\", \"call\", me);\n if (type == \".\") return cont(property, me);\n if (type == \"[\") return cont(pushlex(\"]\"), maybeexpression, expect(\"]\"), poplex, me);\n }\n function quasi(type, value) {\n if (type != \"quasi\") return pass();\n if (value.slice(value.length - 2) != \"${\") return cont(quasi);\n return cont(expression, continueQuasi);\n }\n function continueQuasi(type) {\n if (type == \"}\") {\n cx.marked = \"string-2\";\n cx.state.tokenize = tokenQuasi;\n return cont(quasi);\n }\n }\n function arrowBody(type) {\n findFatArrow(cx.stream, cx.state);\n return pass(type == \"{\" ? statement : expression);\n }\n function arrowBodyNoComma(type) {\n findFatArrow(cx.stream, cx.state);\n return pass(type == \"{\" ? statement : expressionNoComma);\n }\n function maybeTarget(noComma) {\n return function(type) {\n if (type == \".\") return cont(noComma ? targetNoComma : target);\n else return pass(noComma ? expressionNoComma : expression);\n };\n }\n function target(_, value) {\n if (value == \"target\") { cx.marked = \"keyword\"; return cont(maybeoperatorComma); }\n }\n function targetNoComma(_, value) {\n if (value == \"target\") { cx.marked = \"keyword\"; return cont(maybeoperatorNoComma); }\n }\n function maybelabel(type) {\n if (type == \":\") return cont(poplex, statement);\n return pass(maybeoperatorComma, expect(\";\"), poplex);\n }\n function property(type) {\n if (type == \"variable\") {cx.marked = \"property\"; return cont();}\n }\n function objprop(type, value) {\n if (type == \"variable\" || cx.style == \"keyword\") {\n cx.marked = \"property\";\n if (value == \"get\" || value == \"set\") return cont(getterSetter);\n return cont(afterprop);\n } else if (type == \"number\" || type == \"string\") {\n cx.marked = jsonldMode ? \"property\" : (cx.style + \" property\");\n return cont(afterprop);\n } else if (type == \"jsonld-keyword\") {\n return cont(afterprop);\n } else if (type == \"modifier\") {\n return cont(objprop)\n } else if (type == \"[\") {\n return cont(expression, expect(\"]\"), afterprop);\n } else if (type == \"spread\") {\n return cont(expression);\n }\n }\n function getterSetter(type) {\n if (type != \"variable\") return pass(afterprop);\n cx.marked = \"property\";\n return cont(functiondef);\n }\n function afterprop(type) {\n if (type == \":\") return cont(expressionNoComma);\n if (type == \"(\") return pass(functiondef);\n }\n function commasep(what, end) {\n function proceed(type) {\n if (type == \",\") {\n var lex = cx.state.lexical;\n if (lex.info == \"call\") lex.pos = (lex.pos || 0) + 1;\n return cont(what, proceed);\n }\n if (type == end) return cont();\n return cont(expect(end));\n }\n return function(type) {\n if (type == end) return cont();\n return pass(what, proceed);\n };\n }\n function contCommasep(what, end, info) {\n for (var i = 3; i < arguments.length; i++)\n cx.cc.push(arguments[i]);\n return cont(pushlex(end, info), commasep(what, end), poplex);\n }\n function block(type) {\n if (type == \"}\") return cont();\n return pass(statement, block);\n }\n function maybetype(type) {\n if (isTS && type == \":\") return cont(typedef);\n }\n function maybedefault(_, value) {\n if (value == \"=\") return cont(expressionNoComma);\n }\n function typedef(type) {\n if (type == \"variable\") {cx.marked = \"variable-3\"; return cont();}\n }\n function vardef() {\n return pass(pattern, maybetype, maybeAssign, vardefCont);\n }\n function pattern(type, value) {\n if (type == \"modifier\") return cont(pattern)\n if (type == \"variable\") { register(value); return cont(); }\n if (type == \"spread\") return cont(pattern);\n if (type == \"[\") return contCommasep(pattern, \"]\");\n if (type == \"{\") return contCommasep(proppattern, \"}\");\n }\n function proppattern(type, value) {\n if (type == \"variable\" && !cx.stream.match(/^\\s*:/, false)) {\n register(value);\n return cont(maybeAssign);\n }\n if (type == \"variable\") cx.marked = \"property\";\n if (type == \"spread\") return cont(pattern);\n if (type == \"}\") return pass();\n return cont(expect(\":\"), pattern, maybeAssign);\n }\n function maybeAssign(_type, value) {\n if (value == \"=\") return cont(expressionNoComma);\n }\n function vardefCont(type) {\n if (type == \",\") return cont(vardef);\n }\n function maybeelse(type, value) {\n if (type == \"keyword b\" && value == \"else\") return cont(pushlex(\"form\", \"else\"), statement, poplex);\n }\n function forspec(type) {\n if (type == \"(\") return cont(pushlex(\")\"), forspec1, expect(\")\"), poplex);\n }\n function forspec1(type) {\n if (type == \"var\") return cont(vardef, expect(\";\"), forspec2);\n if (type == \";\") return cont(forspec2);\n if (type == \"variable\") return cont(formaybeinof);\n return pass(expression, expect(\";\"), forspec2);\n }\n function formaybeinof(_type, value) {\n if (value == \"in\" || value == \"of\") { cx.marked = \"keyword\"; return cont(expression); }\n return cont(maybeoperatorComma, forspec2);\n }\n function forspec2(type, value) {\n if (type == \";\") return cont(forspec3);\n if (value == \"in\" || value == \"of\") { cx.marked = \"keyword\"; return cont(expression); }\n return pass(expression, expect(\";\"), forspec3);\n }\n function forspec3(type) {\n if (type != \")\") cont(expression);\n }\n function functiondef(type, value) {\n if (value == \"*\") {cx.marked = \"keyword\"; return cont(functiondef);}\n if (type == \"variable\") {register(value); return cont(functiondef);}\n if (type == \"(\") return cont(pushcontext, pushlex(\")\"), commasep(funarg, \")\"), poplex, statement, popcontext);\n }\n function funarg(type) {\n if (type == \"spread\") return cont(funarg);\n return pass(pattern, maybetype, maybedefault);\n }\n function className(type, value) {\n if (type == \"variable\") {register(value); return cont(classNameAfter);}\n }\n function classNameAfter(type, value) {\n if (value == \"extends\") return cont(expression, classNameAfter);\n if (type == \"{\") return cont(pushlex(\"}\"), classBody, poplex);\n }\n function classBody(type, value) {\n if (type == \"variable\" || cx.style == \"keyword\") {\n if (value == \"static\") {\n cx.marked = \"keyword\";\n return cont(classBody);\n }\n cx.marked = \"property\";\n if (value == \"get\" || value == \"set\") return cont(classGetterSetter, functiondef, classBody);\n return cont(functiondef, classBody);\n }\n if (value == \"*\") {\n cx.marked = \"keyword\";\n return cont(classBody);\n }\n if (type == \";\") return cont(classBody);\n if (type == \"}\") return cont();\n }\n function classGetterSetter(type) {\n if (type != \"variable\") return pass();\n cx.marked = \"property\";\n return cont();\n }\n function afterExport(_type, value) {\n if (value == \"*\") { cx.marked = \"keyword\"; return cont(maybeFrom, expect(\";\")); }\n if (value == \"default\") { cx.marked = \"keyword\"; return cont(expression, expect(\";\")); }\n return pass(statement);\n }\n function afterImport(type) {\n if (type == \"string\") return cont();\n return pass(importSpec, maybeFrom);\n }\n function importSpec(type, value) {\n if (type == \"{\") return contCommasep(importSpec, \"}\");\n if (type == \"variable\") register(value);\n if (value == \"*\") cx.marked = \"keyword\";\n return cont(maybeAs);\n }\n function maybeAs(_type, value) {\n if (value == \"as\") { cx.marked = \"keyword\"; return cont(importSpec); }\n }\n function maybeFrom(_type, value) {\n if (value == \"from\") { cx.marked = \"keyword\"; return cont(expression); }\n }\n function arrayLiteral(type) {\n if (type == \"]\") return cont();\n return pass(expressionNoComma, maybeArrayComprehension);\n }\n function maybeArrayComprehension(type) {\n if (type == \"for\") return pass(comprehension, expect(\"]\"));\n if (type == \",\") return cont(commasep(maybeexpressionNoComma, \"]\"));\n return pass(commasep(expressionNoComma, \"]\"));\n }\n function comprehension(type) {\n if (type == \"for\") return cont(forspec, comprehension);\n if (type == \"if\") return cont(expression, comprehension);\n }\n\n function isContinuedStatement(state, textAfter) {\n return state.lastType == \"operator\" || state.lastType == \",\" ||\n isOperatorChar.test(textAfter.charAt(0)) ||\n /[,.]/.test(textAfter.charAt(0));\n }\n\n // Interface\n\n return {\n startState: function(basecolumn) {\n var state = {\n tokenize: tokenBase,\n lastType: \"sof\",\n cc: [],\n lexical: new JSLexical((basecolumn || 0) - indentUnit, 0, \"block\", false),\n localVars: parserConfig.localVars,\n context: parserConfig.localVars && {vars: parserConfig.localVars},\n indented: basecolumn || 0\n };\n if (parserConfig.globalVars && typeof parserConfig.globalVars == \"object\")\n state.globalVars = parserConfig.globalVars;\n return state;\n },\n\n token: function(stream, state) {\n if (stream.sol()) {\n if (!state.lexical.hasOwnProperty(\"align\"))\n state.lexical.align = false;\n state.indented = stream.indentation();\n findFatArrow(stream, state);\n }\n if (state.tokenize != tokenComment && stream.eatSpace()) return null;\n var style = state.tokenize(stream, state);\n if (type == \"comment\") return style;\n state.lastType = type == \"operator\" && (content == \"++\" || content == \"--\") ? \"incdec\" : type;\n return parseJS(state, style, type, content, stream);\n },\n\n indent: function(state, textAfter) {\n if (state.tokenize == tokenComment) return CodeMirror.Pass;\n if (state.tokenize != tokenBase) return 0;\n var firstChar = textAfter && textAfter.charAt(0), lexical = state.lexical;\n // Kludge to prevent 'maybelse' from blocking lexical scope pops\n if (!/^\\s*else\\b/.test(textAfter)) for (var i = state.cc.length - 1; i >= 0; --i) {\n var c = state.cc[i];\n if (c == poplex) lexical = lexical.prev;\n else if (c != maybeelse) break;\n }\n if (lexical.type == \"stat\" && firstChar == \"}\") lexical = lexical.prev;\n if (statementIndent && lexical.type == \")\" && lexical.prev.type == \"stat\")\n lexical = lexical.prev;\n var type = lexical.type, closing = firstChar == type;\n\n if (type == \"vardef\") return lexical.indented + (state.lastType == \"operator\" || state.lastType == \",\" ? lexical.info + 1 : 0);\n else if (type == \"form\" && firstChar == \"{\") return lexical.indented;\n else if (type == \"form\") return lexical.indented + indentUnit;\n else if (type == \"stat\")\n return lexical.indented + (isContinuedStatement(state, textAfter) ? statementIndent || indentUnit : 0);\n else if (lexical.info == \"switch\" && !closing && parserConfig.doubleIndentSwitch != false)\n return lexical.indented + (/^(?:case|default)\\b/.test(textAfter) ? indentUnit : 2 * indentUnit);\n else if (lexical.align) return lexical.column + (closing ? 0 : 1);\n else return lexical.indented + (closing ? 0 : indentUnit);\n },\n\n electricInput: /^\\s*(?:case .*?:|default:|\\{|\\})$/,\n blockCommentStart: jsonMode ? null : \"/*\",\n blockCommentEnd: jsonMode ? null : \"*/\",\n lineComment: jsonMode ? null : \"//\",\n fold: \"brace\",\n closeBrackets: \"()[]{}''\\\"\\\"``\",\n\n helperType: jsonMode ? \"json\" : \"javascript\",\n jsonldMode: jsonldMode,\n jsonMode: jsonMode,\n\n expressionAllowed: expressionAllowed,\n skipExpression: function(state) {\n var top = state.cc[state.cc.length - 1]\n if (top == expression || top == expressionNoComma) state.cc.pop()\n }\n };\n});\n\nCodeMirror.registerHelper(\"wordChars\", \"javascript\", /[\\w$]/);\n\nCodeMirror.defineMIME(\"text/javascript\", \"javascript\");\nCodeMirror.defineMIME(\"text/ecmascript\", \"javascript\");\nCodeMirror.defineMIME(\"application/javascript\", \"javascript\");\nCodeMirror.defineMIME(\"application/x-javascript\", \"javascript\");\nCodeMirror.defineMIME(\"application/ecmascript\", \"javascript\");\nCodeMirror.defineMIME(\"application/json\", {name: \"javascript\", json: true});\nCodeMirror.defineMIME(\"application/x-json\", {name: \"javascript\", json: true});\nCodeMirror.defineMIME(\"application/ld+json\", {name: \"javascript\", jsonld: true});\nCodeMirror.defineMIME(\"text/typescript\", { name: \"javascript\", typescript: true });\nCodeMirror.defineMIME(\"application/typescript\", { name: \"javascript\", typescript: true });\n\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/markdown/markdown.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/markdown/markdown.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"), require(\"../xml/xml\"), require(\"../meta\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\", \"../xml/xml\", \"../meta\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nCodeMirror.defineMode(\"markdown\", function(cmCfg, modeCfg) {\n\n var htmlMode = CodeMirror.getMode(cmCfg, \"text/html\");\n var htmlModeMissing = htmlMode.name == \"null\"\n\n function getMode(name) {\n if (CodeMirror.findModeByName) {\n var found = CodeMirror.findModeByName(name);\n if (found) name = found.mime || found.mimes[0];\n }\n var mode = CodeMirror.getMode(cmCfg, name);\n return mode.name == \"null\" ? null : mode;\n }\n\n // Should characters that affect highlighting be highlighted separate?\n // Does not include characters that will be output (such as `1.` and `-` for lists)\n if (modeCfg.highlightFormatting === undefined)\n modeCfg.highlightFormatting = false;\n\n // Maximum number of nested blockquotes. Set to 0 for infinite nesting.\n // Excess `>` will emit `error` token.\n if (modeCfg.maxBlockquoteDepth === undefined)\n modeCfg.maxBlockquoteDepth = 0;\n\n // Should underscores in words open/close em/strong?\n if (modeCfg.underscoresBreakWords === undefined)\n modeCfg.underscoresBreakWords = true;\n\n // Use `fencedCodeBlocks` to configure fenced code blocks. false to\n // disable, string to specify a precise regexp that the fence should\n // match, and true to allow three or more backticks or tildes (as\n // per CommonMark).\n\n // Turn on task lists? (\"- [ ] \" and \"- [x] \")\n if (modeCfg.taskLists === undefined) modeCfg.taskLists = false;\n\n // Turn on strikethrough syntax\n if (modeCfg.strikethrough === undefined)\n modeCfg.strikethrough = false;\n\n // Allow token types to be overridden by user-provided token types.\n if (modeCfg.tokenTypeOverrides === undefined)\n modeCfg.tokenTypeOverrides = {};\n\n var tokenTypes = {\n header: \"header\",\n code: \"comment\",\n quote: \"quote\",\n list1: \"variable-2\",\n list2: \"variable-3\",\n list3: \"keyword\",\n hr: \"hr\",\n image: \"tag\",\n formatting: \"formatting\",\n linkInline: \"link\",\n linkEmail: \"link\",\n linkText: \"link\",\n linkHref: \"string\",\n em: \"em\",\n strong: \"strong\",\n strikethrough: \"strikethrough\"\n };\n\n for (var tokenType in tokenTypes) {\n if (tokenTypes.hasOwnProperty(tokenType) && modeCfg.tokenTypeOverrides[tokenType]) {\n tokenTypes[tokenType] = modeCfg.tokenTypeOverrides[tokenType];\n }\n }\n\n var hrRE = /^([*\\-_])(?:\\s*\\1){2,}\\s*$/\n , ulRE = /^[*\\-+]\\s+/\n , olRE = /^[0-9]+([.)])\\s+/\n , taskListRE = /^\\[(x| )\\](?=\\s)/ // Must follow ulRE or olRE\n , atxHeaderRE = modeCfg.allowAtxHeaderWithoutSpace ? /^(#+)/ : /^(#+)(?: |$)/\n , setextHeaderRE = /^ *(?:\\={1,}|-{1,})\\s*$/\n , textRE = /^[^#!\\[\\]*_\\\\<>` \"'(~]+/\n , fencedCodeRE = new RegExp(\"^(\" + (modeCfg.fencedCodeBlocks === true ? \"~~~+|```+\" : modeCfg.fencedCodeBlocks) +\n \")[ \\\\t]*([\\\\w+#]*)\");\n\n function switchInline(stream, state, f) {\n state.f = state.inline = f;\n return f(stream, state);\n }\n\n function switchBlock(stream, state, f) {\n state.f = state.block = f;\n return f(stream, state);\n }\n\n function lineIsEmpty(line) {\n return !line || !/\\S/.test(line.string)\n }\n\n // Blocks\n\n function blankLine(state) {\n // Reset linkTitle state\n state.linkTitle = false;\n // Reset EM state\n state.em = false;\n // Reset STRONG state\n state.strong = false;\n // Reset strikethrough state\n state.strikethrough = false;\n // Reset state.quote\n state.quote = 0;\n // Reset state.indentedCode\n state.indentedCode = false;\n if (htmlModeMissing && state.f == htmlBlock) {\n state.f = inlineNormal;\n state.block = blockNormal;\n }\n // Reset state.trailingSpace\n state.trailingSpace = 0;\n state.trailingSpaceNewLine = false;\n // Mark this line as blank\n state.prevLine = state.thisLine\n state.thisLine = null\n return null;\n }\n\n function blockNormal(stream, state) {\n\n var sol = stream.sol();\n\n var prevLineIsList = state.list !== false,\n prevLineIsIndentedCode = state.indentedCode;\n\n state.indentedCode = false;\n\n if (prevLineIsList) {\n if (state.indentationDiff >= 0) { // Continued list\n if (state.indentationDiff < 4) { // Only adjust indentation if *not* a code block\n state.indentation -= state.indentationDiff;\n }\n state.list = null;\n } else if (state.indentation > 0) {\n state.list = null;\n } else { // No longer a list\n state.list = false;\n }\n }\n\n var match = null;\n if (state.indentationDiff >= 4) {\n stream.skipToEnd();\n if (prevLineIsIndentedCode || lineIsEmpty(state.prevLine)) {\n state.indentation -= 4;\n state.indentedCode = true;\n return tokenTypes.code;\n } else {\n return null;\n }\n } else if (stream.eatSpace()) {\n return null;\n } else if ((match = stream.match(atxHeaderRE)) && match[1].length <= 6) {\n state.header = match[1].length;\n if (modeCfg.highlightFormatting) state.formatting = \"header\";\n state.f = state.inline;\n return getType(state);\n } else if (!lineIsEmpty(state.prevLine) && !state.quote && !prevLineIsList &&\n !prevLineIsIndentedCode && (match = stream.match(setextHeaderRE))) {\n state.header = match[0].charAt(0) == '=' ? 1 : 2;\n if (modeCfg.highlightFormatting) state.formatting = \"header\";\n state.f = state.inline;\n return getType(state);\n } else if (stream.eat('>')) {\n state.quote = sol ? 1 : state.quote + 1;\n if (modeCfg.highlightFormatting) state.formatting = \"quote\";\n stream.eatSpace();\n return getType(state);\n } else if (stream.peek() === '[') {\n return switchInline(stream, state, footnoteLink);\n } else if (stream.match(hrRE, true)) {\n state.hr = true;\n return tokenTypes.hr;\n } else if ((lineIsEmpty(state.prevLine) || prevLineIsList) && (stream.match(ulRE, false) || stream.match(olRE, false))) {\n var listType = null;\n if (stream.match(ulRE, true)) {\n listType = 'ul';\n } else {\n stream.match(olRE, true);\n listType = 'ol';\n }\n state.indentation = stream.column() + stream.current().length;\n state.list = true;\n\n // While this list item's marker's indentation\n // is less than the deepest list item's content's indentation,\n // pop the deepest list item indentation off the stack.\n while (state.listStack && stream.column() < state.listStack[state.listStack.length - 1]) {\n state.listStack.pop();\n }\n\n // Add this list item's content's indentation to the stack\n state.listStack.push(state.indentation);\n\n if (modeCfg.taskLists && stream.match(taskListRE, false)) {\n state.taskList = true;\n }\n state.f = state.inline;\n if (modeCfg.highlightFormatting) state.formatting = [\"list\", \"list-\" + listType];\n return getType(state);\n } else if (modeCfg.fencedCodeBlocks && (match = stream.match(fencedCodeRE, true))) {\n state.fencedChars = match[1]\n // try switching mode\n state.localMode = getMode(match[2]);\n if (state.localMode) state.localState = state.localMode.startState();\n state.f = state.block = local;\n if (modeCfg.highlightFormatting) state.formatting = \"code-block\";\n state.code = -1\n return getType(state);\n }\n\n return switchInline(stream, state, state.inline);\n }\n\n function htmlBlock(stream, state) {\n var style = htmlMode.token(stream, state.htmlState);\n if (!htmlModeMissing) {\n var inner = CodeMirror.innerMode(htmlMode, state.htmlState)\n if ((inner.mode.name == \"xml\" && inner.state.tagStart === null &&\n (!inner.state.context && inner.state.tokenize.isInText)) ||\n (state.md_inside && stream.current().indexOf(\">\") > -1)) {\n state.f = inlineNormal;\n state.block = blockNormal;\n state.htmlState = null;\n }\n }\n return style;\n }\n\n function local(stream, state) {\n if (state.fencedChars && stream.match(state.fencedChars, false)) {\n state.localMode = state.localState = null;\n state.f = state.block = leavingLocal;\n return null;\n } else if (state.localMode) {\n return state.localMode.token(stream, state.localState);\n } else {\n stream.skipToEnd();\n return tokenTypes.code;\n }\n }\n\n function leavingLocal(stream, state) {\n stream.match(state.fencedChars);\n state.block = blockNormal;\n state.f = inlineNormal;\n state.fencedChars = null;\n if (modeCfg.highlightFormatting) state.formatting = \"code-block\";\n state.code = 1\n var returnType = getType(state);\n state.code = 0\n return returnType;\n }\n\n // Inline\n function getType(state) {\n var styles = [];\n\n if (state.formatting) {\n styles.push(tokenTypes.formatting);\n\n if (typeof state.formatting === \"string\") state.formatting = [state.formatting];\n\n for (var i = 0; i < state.formatting.length; i++) {\n styles.push(tokenTypes.formatting + \"-\" + state.formatting[i]);\n\n if (state.formatting[i] === \"header\") {\n styles.push(tokenTypes.formatting + \"-\" + state.formatting[i] + \"-\" + state.header);\n }\n\n // Add `formatting-quote` and `formatting-quote-#` for blockquotes\n // Add `error` instead if the maximum blockquote nesting depth is passed\n if (state.formatting[i] === \"quote\") {\n if (!modeCfg.maxBlockquoteDepth || modeCfg.maxBlockquoteDepth >= state.quote) {\n styles.push(tokenTypes.formatting + \"-\" + state.formatting[i] + \"-\" + state.quote);\n } else {\n styles.push(\"error\");\n }\n }\n }\n }\n\n if (state.taskOpen) {\n styles.push(\"meta\");\n return styles.length ? styles.join(' ') : null;\n }\n if (state.taskClosed) {\n styles.push(\"property\");\n return styles.length ? styles.join(' ') : null;\n }\n\n if (state.linkHref) {\n styles.push(tokenTypes.linkHref, \"url\");\n } else { // Only apply inline styles to non-url text\n if (state.strong) { styles.push(tokenTypes.strong); }\n if (state.em) { styles.push(tokenTypes.em); }\n if (state.strikethrough) { styles.push(tokenTypes.strikethrough); }\n if (state.linkText) { styles.push(tokenTypes.linkText); }\n if (state.code) { styles.push(tokenTypes.code); }\n }\n\n if (state.header) { styles.push(tokenTypes.header, tokenTypes.header + \"-\" + state.header); }\n\n if (state.quote) {\n styles.push(tokenTypes.quote);\n\n // Add `quote-#` where the maximum for `#` is modeCfg.maxBlockquoteDepth\n if (!modeCfg.maxBlockquoteDepth || modeCfg.maxBlockquoteDepth >= state.quote) {\n styles.push(tokenTypes.quote + \"-\" + state.quote);\n } else {\n styles.push(tokenTypes.quote + \"-\" + modeCfg.maxBlockquoteDepth);\n }\n }\n\n if (state.list !== false) {\n var listMod = (state.listStack.length - 1) % 3;\n if (!listMod) {\n styles.push(tokenTypes.list1);\n } else if (listMod === 1) {\n styles.push(tokenTypes.list2);\n } else {\n styles.push(tokenTypes.list3);\n }\n }\n\n if (state.trailingSpaceNewLine) {\n styles.push(\"trailing-space-new-line\");\n } else if (state.trailingSpace) {\n styles.push(\"trailing-space-\" + (state.trailingSpace % 2 ? \"a\" : \"b\"));\n }\n\n return styles.length ? styles.join(' ') : null;\n }\n\n function handleText(stream, state) {\n if (stream.match(textRE, true)) {\n return getType(state);\n }\n return undefined;\n }\n\n function inlineNormal(stream, state) {\n var style = state.text(stream, state);\n if (typeof style !== 'undefined')\n return style;\n\n if (state.list) { // List marker (*, +, -, 1., etc)\n state.list = null;\n return getType(state);\n }\n\n if (state.taskList) {\n var taskOpen = stream.match(taskListRE, true)[1] !== \"x\";\n if (taskOpen) state.taskOpen = true;\n else state.taskClosed = true;\n if (modeCfg.highlightFormatting) state.formatting = \"task\";\n state.taskList = false;\n return getType(state);\n }\n\n state.taskOpen = false;\n state.taskClosed = false;\n\n if (state.header && stream.match(/^#+$/, true)) {\n if (modeCfg.highlightFormatting) state.formatting = \"header\";\n return getType(state);\n }\n\n // Get sol() value now, before character is consumed\n var sol = stream.sol();\n\n var ch = stream.next();\n\n // Matches link titles present on next line\n if (state.linkTitle) {\n state.linkTitle = false;\n var matchCh = ch;\n if (ch === '(') {\n matchCh = ')';\n }\n matchCh = (matchCh+'').replace(/([.?*+^$[\\]\\\\(){}|-])/g, \"\\\\$1\");\n var regex = '^\\\\s*(?:[^' + matchCh + '\\\\\\\\]+|\\\\\\\\\\\\\\\\|\\\\\\\\.)' + matchCh;\n if (stream.match(new RegExp(regex), true)) {\n return tokenTypes.linkHref;\n }\n }\n\n // If this block is changed, it may need to be updated in GFM mode\n if (ch === '`') {\n var previousFormatting = state.formatting;\n if (modeCfg.highlightFormatting) state.formatting = \"code\";\n stream.eatWhile('`');\n var count = stream.current().length\n if (state.code == 0) {\n state.code = count\n return getType(state)\n } else if (count == state.code) { // Must be exact\n var t = getType(state)\n state.code = 0\n return t\n } else {\n state.formatting = previousFormatting\n return getType(state)\n }\n } else if (state.code) {\n return getType(state);\n }\n\n if (ch === '\\\\') {\n stream.next();\n if (modeCfg.highlightFormatting) {\n var type = getType(state);\n var formattingEscape = tokenTypes.formatting + \"-escape\";\n return type ? type + \" \" + formattingEscape : formattingEscape;\n }\n }\n\n if (ch === '!' && stream.match(/\\[[^\\]]*\\] ?(?:\\(|\\[)/, false)) {\n stream.match(/\\[[^\\]]*\\]/);\n state.inline = state.f = linkHref;\n return tokenTypes.image;\n }\n\n if (ch === '[' && stream.match(/.*\\](\\(.*\\)| ?\\[.*\\])/, false)) {\n state.linkText = true;\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n return getType(state);\n }\n\n if (ch === ']' && state.linkText && stream.match(/\\(.*\\)| ?\\[.*\\]/, false)) {\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n var type = getType(state);\n state.linkText = false;\n state.inline = state.f = linkHref;\n return type;\n }\n\n if (ch === '<' && stream.match(/^(https?|ftps?):\\/\\/(?:[^\\\\>]|\\\\.)+>/, false)) {\n state.f = state.inline = linkInline;\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n var type = getType(state);\n if (type){\n type += \" \";\n } else {\n type = \"\";\n }\n return type + tokenTypes.linkInline;\n }\n\n if (ch === '<' && stream.match(/^[^> \\\\]+@(?:[^\\\\>]|\\\\.)+>/, false)) {\n state.f = state.inline = linkInline;\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n var type = getType(state);\n if (type){\n type += \" \";\n } else {\n type = \"\";\n }\n return type + tokenTypes.linkEmail;\n }\n\n if (ch === '<' && stream.match(/^(!--|\\w)/, false)) {\n var end = stream.string.indexOf(\">\", stream.pos);\n if (end != -1) {\n var atts = stream.string.substring(stream.start, end);\n if (/markdown\\s*=\\s*('|\"){0,1}1('|\"){0,1}/.test(atts)) state.md_inside = true;\n }\n stream.backUp(1);\n state.htmlState = CodeMirror.startState(htmlMode);\n return switchBlock(stream, state, htmlBlock);\n }\n\n if (ch === '<' && stream.match(/^\\/\\w*?>/)) {\n state.md_inside = false;\n return \"tag\";\n }\n\n var ignoreUnderscore = false;\n if (!modeCfg.underscoresBreakWords) {\n if (ch === '_' && stream.peek() !== '_' && stream.match(/(\\w)/, false)) {\n var prevPos = stream.pos - 2;\n if (prevPos >= 0) {\n var prevCh = stream.string.charAt(prevPos);\n if (prevCh !== '_' && prevCh.match(/(\\w)/, false)) {\n ignoreUnderscore = true;\n }\n }\n }\n }\n if (ch === '*' || (ch === '_' && !ignoreUnderscore)) {\n if (sol && stream.peek() === ' ') {\n // Do nothing, surrounded by newline and space\n } else if (state.strong === ch && stream.eat(ch)) { // Remove STRONG\n if (modeCfg.highlightFormatting) state.formatting = \"strong\";\n var t = getType(state);\n state.strong = false;\n return t;\n } else if (!state.strong && stream.eat(ch)) { // Add STRONG\n state.strong = ch;\n if (modeCfg.highlightFormatting) state.formatting = \"strong\";\n return getType(state);\n } else if (state.em === ch) { // Remove EM\n if (modeCfg.highlightFormatting) state.formatting = \"em\";\n var t = getType(state);\n state.em = false;\n return t;\n } else if (!state.em) { // Add EM\n state.em = ch;\n if (modeCfg.highlightFormatting) state.formatting = \"em\";\n return getType(state);\n }\n } else if (ch === ' ') {\n if (stream.eat('*') || stream.eat('_')) { // Probably surrounded by spaces\n if (stream.peek() === ' ') { // Surrounded by spaces, ignore\n return getType(state);\n } else { // Not surrounded by spaces, back up pointer\n stream.backUp(1);\n }\n }\n }\n\n if (modeCfg.strikethrough) {\n if (ch === '~' && stream.eatWhile(ch)) {\n if (state.strikethrough) {// Remove strikethrough\n if (modeCfg.highlightFormatting) state.formatting = \"strikethrough\";\n var t = getType(state);\n state.strikethrough = false;\n return t;\n } else if (stream.match(/^[^\\s]/, false)) {// Add strikethrough\n state.strikethrough = true;\n if (modeCfg.highlightFormatting) state.formatting = \"strikethrough\";\n return getType(state);\n }\n } else if (ch === ' ') {\n if (stream.match(/^~~/, true)) { // Probably surrounded by space\n if (stream.peek() === ' ') { // Surrounded by spaces, ignore\n return getType(state);\n } else { // Not surrounded by spaces, back up pointer\n stream.backUp(2);\n }\n }\n }\n }\n\n if (ch === ' ') {\n if (stream.match(/ +$/, false)) {\n state.trailingSpace++;\n } else if (state.trailingSpace) {\n state.trailingSpaceNewLine = true;\n }\n }\n\n return getType(state);\n }\n\n function linkInline(stream, state) {\n var ch = stream.next();\n\n if (ch === \">\") {\n state.f = state.inline = inlineNormal;\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n var type = getType(state);\n if (type){\n type += \" \";\n } else {\n type = \"\";\n }\n return type + tokenTypes.linkInline;\n }\n\n stream.match(/^[^>]+/, true);\n\n return tokenTypes.linkInline;\n }\n\n function linkHref(stream, state) {\n // Check if space, and return NULL if so (to avoid marking the space)\n if(stream.eatSpace()){\n return null;\n }\n var ch = stream.next();\n if (ch === '(' || ch === '[') {\n state.f = state.inline = getLinkHrefInside(ch === \"(\" ? \")\" : \"]\");\n if (modeCfg.highlightFormatting) state.formatting = \"link-string\";\n state.linkHref = true;\n return getType(state);\n }\n return 'error';\n }\n\n function getLinkHrefInside(endChar) {\n return function(stream, state) {\n var ch = stream.next();\n\n if (ch === endChar) {\n state.f = state.inline = inlineNormal;\n if (modeCfg.highlightFormatting) state.formatting = \"link-string\";\n var returnState = getType(state);\n state.linkHref = false;\n return returnState;\n }\n\n if (stream.match(inlineRE(endChar), true)) {\n stream.backUp(1);\n }\n\n state.linkHref = true;\n return getType(state);\n };\n }\n\n function footnoteLink(stream, state) {\n if (stream.match(/^([^\\]\\\\]|\\\\.)*\\]:/, false)) {\n state.f = footnoteLinkInside;\n stream.next(); // Consume [\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n state.linkText = true;\n return getType(state);\n }\n return switchInline(stream, state, inlineNormal);\n }\n\n function footnoteLinkInside(stream, state) {\n if (stream.match(/^\\]:/, true)) {\n state.f = state.inline = footnoteUrl;\n if (modeCfg.highlightFormatting) state.formatting = \"link\";\n var returnType = getType(state);\n state.linkText = false;\n return returnType;\n }\n\n stream.match(/^([^\\]\\\\]|\\\\.)+/, true);\n\n return tokenTypes.linkText;\n }\n\n function footnoteUrl(stream, state) {\n // Check if space, and return NULL if so (to avoid marking the space)\n if(stream.eatSpace()){\n return null;\n }\n // Match URL\n stream.match(/^[^\\s]+/, true);\n // Check for link title\n if (stream.peek() === undefined) { // End of line, set flag to check next line\n state.linkTitle = true;\n } else { // More content on line, check if link title\n stream.match(/^(?:\\s+(?:\"(?:[^\"\\\\]|\\\\\\\\|\\\\.)+\"|'(?:[^'\\\\]|\\\\\\\\|\\\\.)+'|\\((?:[^)\\\\]|\\\\\\\\|\\\\.)+\\)))?/, true);\n }\n state.f = state.inline = inlineNormal;\n return tokenTypes.linkHref + \" url\";\n }\n\n var savedInlineRE = [];\n function inlineRE(endChar) {\n if (!savedInlineRE[endChar]) {\n // Escape endChar for RegExp (taken from http://stackoverflow.com/a/494122/526741)\n endChar = (endChar+'').replace(/([.?*+^$[\\]\\\\(){}|-])/g, \"\\\\$1\");\n // Match any non-endChar, escaped character, as well as the closing\n // endChar.\n savedInlineRE[endChar] = new RegExp('^(?:[^\\\\\\\\]|\\\\\\\\.)*?(' + endChar + ')');\n }\n return savedInlineRE[endChar];\n }\n\n var mode = {\n startState: function() {\n return {\n f: blockNormal,\n\n prevLine: null,\n thisLine: null,\n\n block: blockNormal,\n htmlState: null,\n indentation: 0,\n\n inline: inlineNormal,\n text: handleText,\n\n formatting: false,\n linkText: false,\n linkHref: false,\n linkTitle: false,\n code: 0,\n em: false,\n strong: false,\n header: 0,\n hr: false,\n taskList: false,\n list: false,\n listStack: [],\n quote: 0,\n trailingSpace: 0,\n trailingSpaceNewLine: false,\n strikethrough: false,\n fencedChars: null\n };\n },\n\n copyState: function(s) {\n return {\n f: s.f,\n\n prevLine: s.prevLine,\n thisLine: s.thisLine,\n\n block: s.block,\n htmlState: s.htmlState && CodeMirror.copyState(htmlMode, s.htmlState),\n indentation: s.indentation,\n\n localMode: s.localMode,\n localState: s.localMode ? CodeMirror.copyState(s.localMode, s.localState) : null,\n\n inline: s.inline,\n text: s.text,\n formatting: false,\n linkTitle: s.linkTitle,\n code: s.code,\n em: s.em,\n strong: s.strong,\n strikethrough: s.strikethrough,\n header: s.header,\n hr: s.hr,\n taskList: s.taskList,\n list: s.list,\n listStack: s.listStack.slice(0),\n quote: s.quote,\n indentedCode: s.indentedCode,\n trailingSpace: s.trailingSpace,\n trailingSpaceNewLine: s.trailingSpaceNewLine,\n md_inside: s.md_inside,\n fencedChars: s.fencedChars\n };\n },\n\n token: function(stream, state) {\n\n // Reset state.formatting\n state.formatting = false;\n\n if (stream != state.thisLine) {\n var forceBlankLine = state.header || state.hr;\n\n // Reset state.header and state.hr\n state.header = 0;\n state.hr = false;\n\n if (stream.match(/^\\s*$/, true) || forceBlankLine) {\n blankLine(state);\n if (!forceBlankLine) return null\n state.prevLine = null\n }\n\n state.prevLine = state.thisLine\n state.thisLine = stream\n\n // Reset state.taskList\n state.taskList = false;\n\n // Reset state.trailingSpace\n state.trailingSpace = 0;\n state.trailingSpaceNewLine = false;\n\n state.f = state.block;\n var indentation = stream.match(/^\\s*/, true)[0].replace(/\\t/g, ' ').length;\n state.indentationDiff = Math.min(indentation - state.indentation, 4);\n state.indentation = state.indentation + state.indentationDiff;\n if (indentation > 0) return null;\n }\n return state.f(stream, state);\n },\n\n innerMode: function(state) {\n if (state.block == htmlBlock) return {state: state.htmlState, mode: htmlMode};\n if (state.localState) return {state: state.localState, mode: state.localMode};\n return {state: state, mode: mode};\n },\n\n blankLine: blankLine,\n\n getType: getType,\n\n fold: \"markdown\"\n };\n return mode;\n}, \"xml\");\n\nCodeMirror.defineMIME(\"text/x-markdown\", \"markdown\");\n\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/meta.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/meta.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n\n CodeMirror.modeInfo = [\n {name: \"APL\", mime: \"text/apl\", mode: \"apl\", ext: [\"dyalog\", \"apl\"]},\n {name: \"PGP\", mimes: [\"application/pgp\", \"application/pgp-keys\", \"application/pgp-signature\"], mode: \"asciiarmor\", ext: [\"pgp\"]},\n {name: \"ASN.1\", mime: \"text/x-ttcn-asn\", mode: \"asn.1\", ext: [\"asn\", \"asn1\"]},\n {name: \"Asterisk\", mime: \"text/x-asterisk\", mode: \"asterisk\", file: /^extensions\\.conf$/i},\n {name: \"Brainfuck\", mime: \"text/x-brainfuck\", mode: \"brainfuck\", ext: [\"b\", \"bf\"]},\n {name: \"C\", mime: \"text/x-csrc\", mode: \"clike\", ext: [\"c\", \"h\"]},\n {name: \"C++\", mime: \"text/x-c++src\", mode: \"clike\", ext: [\"cpp\", \"c++\", \"cc\", \"cxx\", \"hpp\", \"h++\", \"hh\", \"hxx\"], alias: [\"cpp\"]},\n {name: \"Cobol\", mime: \"text/x-cobol\", mode: \"cobol\", ext: [\"cob\", \"cpy\"]},\n {name: \"C#\", mime: \"text/x-csharp\", mode: \"clike\", ext: [\"cs\"], alias: [\"csharp\"]},\n {name: \"Clojure\", mime: \"text/x-clojure\", mode: \"clojure\", ext: [\"clj\", \"cljc\", \"cljx\"]},\n {name: \"ClojureScript\", mime: \"text/x-clojurescript\", mode: \"clojure\", ext: [\"cljs\"]},\n {name: \"Closure Stylesheets (GSS)\", mime: \"text/x-gss\", mode: \"css\", ext: [\"gss\"]},\n {name: \"CMake\", mime: \"text/x-cmake\", mode: \"cmake\", ext: [\"cmake\", \"cmake.in\"], file: /^CMakeLists.txt$/},\n {name: \"CoffeeScript\", mime: \"text/x-coffeescript\", mode: \"coffeescript\", ext: [\"coffee\"], alias: [\"coffee\", \"coffee-script\"]},\n {name: \"Common Lisp\", mime: \"text/x-common-lisp\", mode: \"commonlisp\", ext: [\"cl\", \"lisp\", \"el\"], alias: [\"lisp\"]},\n {name: \"Cypher\", mime: \"application/x-cypher-query\", mode: \"cypher\", ext: [\"cyp\", \"cypher\"]},\n {name: \"Cython\", mime: \"text/x-cython\", mode: \"python\", ext: [\"pyx\", \"pxd\", \"pxi\"]},\n {name: \"Crystal\", mime: \"text/x-crystal\", mode: \"crystal\", ext: [\"cr\"]},\n {name: \"CSS\", mime: \"text/css\", mode: \"css\", ext: [\"css\"]},\n {name: \"CQL\", mime: \"text/x-cassandra\", mode: \"sql\", ext: [\"cql\"]},\n {name: \"D\", mime: \"text/x-d\", mode: \"d\", ext: [\"d\"]},\n {name: \"Dart\", mimes: [\"application/dart\", \"text/x-dart\"], mode: \"dart\", ext: [\"dart\"]},\n {name: \"diff\", mime: \"text/x-diff\", mode: \"diff\", ext: [\"diff\", \"patch\"]},\n {name: \"Django\", mime: \"text/x-django\", mode: \"django\"},\n {name: \"Dockerfile\", mime: \"text/x-dockerfile\", mode: \"dockerfile\", file: /^Dockerfile$/},\n {name: \"DTD\", mime: \"application/xml-dtd\", mode: \"dtd\", ext: [\"dtd\"]},\n {name: \"Dylan\", mime: \"text/x-dylan\", mode: \"dylan\", ext: [\"dylan\", \"dyl\", \"intr\"]},\n {name: \"EBNF\", mime: \"text/x-ebnf\", mode: \"ebnf\"},\n {name: \"ECL\", mime: \"text/x-ecl\", mode: \"ecl\", ext: [\"ecl\"]},\n {name: \"edn\", mime: \"application/edn\", mode: \"clojure\", ext: [\"edn\"]},\n {name: \"Eiffel\", mime: \"text/x-eiffel\", mode: \"eiffel\", ext: [\"e\"]},\n {name: \"Elm\", mime: \"text/x-elm\", mode: \"elm\", ext: [\"elm\"]},\n {name: \"Embedded Javascript\", mime: \"application/x-ejs\", mode: \"htmlembedded\", ext: [\"ejs\"]},\n {name: \"Embedded Ruby\", mime: \"application/x-erb\", mode: \"htmlembedded\", ext: [\"erb\"]},\n {name: \"Erlang\", mime: \"text/x-erlang\", mode: \"erlang\", ext: [\"erl\"]},\n {name: \"Factor\", mime: \"text/x-factor\", mode: \"factor\", ext: [\"factor\"]},\n {name: \"FCL\", mime: \"text/x-fcl\", mode: \"fcl\"},\n {name: \"Forth\", mime: \"text/x-forth\", mode: \"forth\", ext: [\"forth\", \"fth\", \"4th\"]},\n {name: \"Fortran\", mime: \"text/x-fortran\", mode: \"fortran\", ext: [\"f\", \"for\", \"f77\", \"f90\"]},\n {name: \"F#\", mime: \"text/x-fsharp\", mode: \"mllike\", ext: [\"fs\"], alias: [\"fsharp\"]},\n {name: \"Gas\", mime: \"text/x-gas\", mode: \"gas\", ext: [\"s\"]},\n {name: \"Gherkin\", mime: \"text/x-feature\", mode: \"gherkin\", ext: [\"feature\"]},\n {name: \"GitHub Flavored Markdown\", mime: \"text/x-gfm\", mode: \"gfm\", file: /^(readme|contributing|history).md$/i},\n {name: \"Go\", mime: \"text/x-go\", mode: \"go\", ext: [\"go\"]},\n {name: \"Groovy\", mime: \"text/x-groovy\", mode: \"groovy\", ext: [\"groovy\", \"gradle\"]},\n {name: \"HAML\", mime: \"text/x-haml\", mode: \"haml\", ext: [\"haml\"]},\n {name: \"Haskell\", mime: \"text/x-haskell\", mode: \"haskell\", ext: [\"hs\"]},\n {name: \"Haskell (Literate)\", mime: \"text/x-literate-haskell\", mode: \"haskell-literate\", ext: [\"lhs\"]},\n {name: \"Haxe\", mime: \"text/x-haxe\", mode: \"haxe\", ext: [\"hx\"]},\n {name: \"HXML\", mime: \"text/x-hxml\", mode: \"haxe\", ext: [\"hxml\"]},\n {name: \"ASP.NET\", mime: \"application/x-aspx\", mode: \"htmlembedded\", ext: [\"aspx\"], alias: [\"asp\", \"aspx\"]},\n {name: \"HTML\", mime: \"text/html\", mode: \"htmlmixed\", ext: [\"html\", \"htm\"], alias: [\"xhtml\"]},\n {name: \"HTTP\", mime: \"message/http\", mode: \"http\"},\n {name: \"IDL\", mime: \"text/x-idl\", mode: \"idl\", ext: [\"pro\"]},\n {name: \"Jade\", mime: \"text/x-jade\", mode: \"jade\", ext: [\"jade\"]},\n {name: \"Java\", mime: \"text/x-java\", mode: \"clike\", ext: [\"java\"]},\n {name: \"Java Server Pages\", mime: \"application/x-jsp\", mode: \"htmlembedded\", ext: [\"jsp\"], alias: [\"jsp\"]},\n {name: \"JavaScript\", mimes: [\"text/javascript\", \"text/ecmascript\", \"application/javascript\", \"application/x-javascript\", \"application/ecmascript\"],\n mode: \"javascript\", ext: [\"js\"], alias: [\"ecmascript\", \"js\", \"node\"]},\n {name: \"JSON\", mimes: [\"application/json\", \"application/x-json\"], mode: \"javascript\", ext: [\"json\", \"map\"], alias: [\"json5\"]},\n {name: \"JSON-LD\", mime: \"application/ld+json\", mode: \"javascript\", ext: [\"jsonld\"], alias: [\"jsonld\"]},\n {name: \"JSX\", mime: \"text/jsx\", mode: \"jsx\", ext: [\"jsx\"]},\n {name: \"Jinja2\", mime: \"null\", mode: \"jinja2\"},\n {name: \"Julia\", mime: \"text/x-julia\", mode: \"julia\", ext: [\"jl\"]},\n {name: \"Kotlin\", mime: \"text/x-kotlin\", mode: \"clike\", ext: [\"kt\"]},\n {name: \"LESS\", mime: \"text/x-less\", mode: \"css\", ext: [\"less\"]},\n {name: \"LiveScript\", mime: \"text/x-livescript\", mode: \"livescript\", ext: [\"ls\"], alias: [\"ls\"]},\n {name: \"Lua\", mime: \"text/x-lua\", mode: \"lua\", ext: [\"lua\"]},\n {name: \"Markdown\", mime: \"text/x-markdown\", mode: \"markdown\", ext: [\"markdown\", \"md\", \"mkd\"]},\n {name: \"mIRC\", mime: \"text/mirc\", mode: \"mirc\"},\n {name: \"MariaDB SQL\", mime: \"text/x-mariadb\", mode: \"sql\"},\n {name: \"Mathematica\", mime: \"text/x-mathematica\", mode: \"mathematica\", ext: [\"m\", \"nb\"]},\n {name: \"Modelica\", mime: \"text/x-modelica\", mode: \"modelica\", ext: [\"mo\"]},\n {name: \"MUMPS\", mime: \"text/x-mumps\", mode: \"mumps\", ext: [\"mps\"]},\n {name: \"MS SQL\", mime: \"text/x-mssql\", mode: \"sql\"},\n {name: \"MySQL\", mime: \"text/x-mysql\", mode: \"sql\"},\n {name: \"Nginx\", mime: \"text/x-nginx-conf\", mode: \"nginx\", file: /nginx.*\\.conf$/i},\n {name: \"NSIS\", mime: \"text/x-nsis\", mode: \"nsis\", ext: [\"nsh\", \"nsi\"]},\n {name: \"NTriples\", mime: \"text/n-triples\", mode: \"ntriples\", ext: [\"nt\"]},\n {name: \"Objective C\", mime: \"text/x-objectivec\", mode: \"clike\", ext: [\"m\", \"mm\"]},\n {name: \"OCaml\", mime: \"text/x-ocaml\", mode: \"mllike\", ext: [\"ml\", \"mli\", \"mll\", \"mly\"]},\n {name: \"Octave\", mime: \"text/x-octave\", mode: \"octave\", ext: [\"m\"]},\n {name: \"Oz\", mime: \"text/x-oz\", mode: \"oz\", ext: [\"oz\"]},\n {name: \"Pascal\", mime: \"text/x-pascal\", mode: \"pascal\", ext: [\"p\", \"pas\"]},\n {name: \"PEG.js\", mime: \"null\", mode: \"pegjs\", ext: [\"jsonld\"]},\n {name: \"Perl\", mime: \"text/x-perl\", mode: \"perl\", ext: [\"pl\", \"pm\"]},\n {name: \"PHP\", mime: \"application/x-httpd-php\", mode: \"php\", ext: [\"php\", \"php3\", \"php4\", \"php5\", \"phtml\"]},\n {name: \"Pig\", mime: \"text/x-pig\", mode: \"pig\", ext: [\"pig\"]},\n {name: \"Plain Text\", mime: \"text/plain\", mode: \"null\", ext: [\"txt\", \"text\", \"conf\", \"def\", \"list\", \"log\"]},\n {name: \"PLSQL\", mime: \"text/x-plsql\", mode: \"sql\", ext: [\"pls\"]},\n {name: \"Properties files\", mime: \"text/x-properties\", mode: \"properties\", ext: [\"properties\", \"ini\", \"in\"], alias: [\"ini\", \"properties\"]},\n {name: \"ProtoBuf\", mime: \"text/x-protobuf\", mode: \"protobuf\", ext: [\"proto\"]},\n {name: \"Python\", mime: \"text/x-python\", mode: \"python\", ext: [\"py\", \"pyw\"]},\n {name: \"Puppet\", mime: \"text/x-puppet\", mode: \"puppet\", ext: [\"pp\"]},\n {name: \"Q\", mime: \"text/x-q\", mode: \"q\", ext: [\"q\"]},\n {name: \"R\", mime: \"text/x-rsrc\", mode: \"r\", ext: [\"r\"], alias: [\"rscript\"]},\n {name: \"reStructuredText\", mime: \"text/x-rst\", mode: \"rst\", ext: [\"rst\"], alias: [\"rst\"]},\n {name: \"RPM Changes\", mime: \"text/x-rpm-changes\", mode: \"rpm\"},\n {name: \"RPM Spec\", mime: \"text/x-rpm-spec\", mode: \"rpm\", ext: [\"spec\"]},\n {name: \"Ruby\", mime: \"text/x-ruby\", mode: \"ruby\", ext: [\"rb\"], alias: [\"jruby\", \"macruby\", \"rake\", \"rb\", \"rbx\"]},\n {name: \"Rust\", mime: \"text/x-rustsrc\", mode: \"rust\", ext: [\"rs\"]},\n {name: \"Sass\", mime: \"text/x-sass\", mode: \"sass\", ext: [\"sass\"]},\n {name: \"Scala\", mime: \"text/x-scala\", mode: \"clike\", ext: [\"scala\"]},\n {name: \"Scheme\", mime: \"text/x-scheme\", mode: \"scheme\", ext: [\"scm\", \"ss\"]},\n {name: \"SCSS\", mime: \"text/x-scss\", mode: \"css\", ext: [\"scss\"]},\n {name: \"Shell\", mime: \"text/x-sh\", mode: \"shell\", ext: [\"sh\", \"ksh\", \"bash\"], alias: [\"bash\", \"sh\", \"zsh\"], file: /^PKGBUILD$/},\n {name: \"Sieve\", mime: \"application/sieve\", mode: \"sieve\", ext: [\"siv\", \"sieve\"]},\n {name: \"Slim\", mimes: [\"text/x-slim\", \"application/x-slim\"], mode: \"slim\", ext: [\"slim\"]},\n {name: \"Smalltalk\", mime: \"text/x-stsrc\", mode: \"smalltalk\", ext: [\"st\"]},\n {name: \"Smarty\", mime: \"text/x-smarty\", mode: \"smarty\", ext: [\"tpl\"]},\n {name: \"Solr\", mime: \"text/x-solr\", mode: \"solr\"},\n {name: \"Soy\", mime: \"text/x-soy\", mode: \"soy\", ext: [\"soy\"], alias: [\"closure template\"]},\n {name: \"SPARQL\", mime: \"application/sparql-query\", mode: \"sparql\", ext: [\"rq\", \"sparql\"], alias: [\"sparul\"]},\n {name: \"Spreadsheet\", mime: \"text/x-spreadsheet\", mode: \"spreadsheet\", alias: [\"excel\", \"formula\"]},\n {name: \"SQL\", mime: \"text/x-sql\", mode: \"sql\", ext: [\"sql\"]},\n {name: \"Squirrel\", mime: \"text/x-squirrel\", mode: \"clike\", ext: [\"nut\"]},\n {name: \"Swift\", mime: \"text/x-swift\", mode: \"swift\", ext: [\"swift\"]},\n {name: \"sTeX\", mime: \"text/x-stex\", mode: \"stex\"},\n {name: \"LaTeX\", mime: \"text/x-latex\", mode: \"stex\", ext: [\"text\", \"ltx\"], alias: [\"tex\"]},\n {name: \"SystemVerilog\", mime: \"text/x-systemverilog\", mode: \"verilog\", ext: [\"v\"]},\n {name: \"Tcl\", mime: \"text/x-tcl\", mode: \"tcl\", ext: [\"tcl\"]},\n {name: \"Textile\", mime: \"text/x-textile\", mode: \"textile\", ext: [\"textile\"]},\n {name: \"TiddlyWiki \", mime: \"text/x-tiddlywiki\", mode: \"tiddlywiki\"},\n {name: \"Tiki wiki\", mime: \"text/tiki\", mode: \"tiki\"},\n {name: \"TOML\", mime: \"text/x-toml\", mode: \"toml\", ext: [\"toml\"]},\n {name: \"Tornado\", mime: \"text/x-tornado\", mode: \"tornado\"},\n {name: \"troff\", mime: \"text/troff\", mode: \"troff\", ext: [\"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\"]},\n {name: \"TTCN\", mime: \"text/x-ttcn\", mode: \"ttcn\", ext: [\"ttcn\", \"ttcn3\", \"ttcnpp\"]},\n {name: \"TTCN_CFG\", mime: \"text/x-ttcn-cfg\", mode: \"ttcn-cfg\", ext: [\"cfg\"]},\n {name: \"Turtle\", mime: \"text/turtle\", mode: \"turtle\", ext: [\"ttl\"]},\n {name: \"TypeScript\", mime: \"application/typescript\", mode: \"javascript\", ext: [\"ts\"], alias: [\"ts\"]},\n {name: \"Twig\", mime: \"text/x-twig\", mode: \"twig\"},\n {name: \"VB.NET\", mime: \"text/x-vb\", mode: \"vb\", ext: [\"vb\"]},\n {name: \"VBScript\", mime: \"text/vbscript\", mode: \"vbscript\", ext: [\"vbs\"]},\n {name: \"Velocity\", mime: \"text/velocity\", mode: \"velocity\", ext: [\"vtl\"]},\n {name: \"Verilog\", mime: \"text/x-verilog\", mode: \"verilog\", ext: [\"v\"]},\n {name: \"VHDL\", mime: \"text/x-vhdl\", mode: \"vhdl\", ext: [\"vhd\", \"vhdl\"]},\n {name: \"XML\", mimes: [\"application/xml\", \"text/xml\"], mode: \"xml\", ext: [\"xml\", \"xsl\", \"xsd\"], alias: [\"rss\", \"wsdl\", \"xsd\"]},\n {name: \"XQuery\", mime: \"application/xquery\", mode: \"xquery\", ext: [\"xy\", \"xquery\"]},\n {name: \"YAML\", mime: \"text/x-yaml\", mode: \"yaml\", ext: [\"yaml\", \"yml\"], alias: [\"yml\"]},\n {name: \"Z80\", mime: \"text/x-z80\", mode: \"z80\", ext: [\"z80\"]},\n {name: \"mscgen\", mime: \"text/x-mscgen\", mode: \"mscgen\", ext: [\"mscgen\", \"mscin\", \"msc\"]},\n {name: \"xu\", mime: \"text/x-xu\", mode: \"mscgen\", ext: [\"xu\"]},\n {name: \"msgenny\", mime: \"text/x-msgenny\", mode: \"mscgen\", ext: [\"msgenny\"]}\n ];\n // Ensure all modes have a mime property for backwards compatibility\n for (var i = 0; i < CodeMirror.modeInfo.length; i++) {\n var info = CodeMirror.modeInfo[i];\n if (info.mimes) info.mime = info.mimes[0];\n }\n\n CodeMirror.findModeByMIME = function(mime) {\n mime = mime.toLowerCase();\n for (var i = 0; i < CodeMirror.modeInfo.length; i++) {\n var info = CodeMirror.modeInfo[i];\n if (info.mime == mime) return info;\n if (info.mimes) for (var j = 0; j < info.mimes.length; j++)\n if (info.mimes[j] == mime) return info;\n }\n };\n\n CodeMirror.findModeByExtension = function(ext) {\n for (var i = 0; i < CodeMirror.modeInfo.length; i++) {\n var info = CodeMirror.modeInfo[i];\n if (info.ext) for (var j = 0; j < info.ext.length; j++)\n if (info.ext[j] == ext) return info;\n }\n };\n\n CodeMirror.findModeByFileName = function(filename) {\n for (var i = 0; i < CodeMirror.modeInfo.length; i++) {\n var info = CodeMirror.modeInfo[i];\n if (info.file && info.file.test(filename)) return info;\n }\n var dot = filename.lastIndexOf(\".\");\n var ext = dot > -1 && filename.substring(dot + 1, filename.length);\n if (ext) return CodeMirror.findModeByExtension(ext);\n };\n\n CodeMirror.findModeByName = function(name) {\n name = name.toLowerCase();\n for (var i = 0; i < CodeMirror.modeInfo.length; i++) {\n var info = CodeMirror.modeInfo[i];\n if (info.name.toLowerCase() == name) return info;\n if (info.alias) for (var j = 0; j < info.alias.length; j++)\n if (info.alias[j].toLowerCase() == name) return info;\n }\n };\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/tiddlywiki/tiddlywiki.css": {
"type": "text/css",
"title": "$:/plugins/tiddlywiki/codemirror/mode/tiddlywiki/tiddlywiki.css",
"tags": "[[$:/tags/Stylesheet]]",
"text": "span.cm-underlined {\n text-decoration: underline;\n}\nspan.cm-strikethrough {\n text-decoration: line-through;\n}\nspan.cm-brace {\n color: #170;\n font-weight: bold;\n}\nspan.cm-table {\n color: blue;\n font-weight: bold;\n}\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/tiddlywiki/tiddlywiki.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/tiddlywiki/tiddlywiki.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n/***\n |''Name''|tiddlywiki.js|\n |''Description''|Enables TiddlyWikiy syntax highlighting using CodeMirror|\n |''Author''|PMario|\n |''Version''|0.1.7|\n |''Status''|''stable''|\n |''Source''|[[GitHub|https://github.com/pmario/CodeMirror2/blob/tw-syntax/mode/tiddlywiki]]|\n |''Documentation''|http://codemirror.tiddlyspace.com/|\n |''License''|[[MIT License|http://www.opensource.org/licenses/mit-license.php]]|\n |''CoreVersion''|2.5.0|\n |''Requires''|codemirror.js|\n |''Keywords''|syntax highlighting color code mirror codemirror|\n ! Info\n CoreVersion parameter is needed for TiddlyWiki only!\n***/\n//{{{\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nCodeMirror.defineMode(\"tiddlywiki\", function () {\n // Tokenizer\n var textwords = {};\n\n var keywords = function () {\n function kw(type) {\n return { type: type, style: \"macro\"};\n }\n return {\n \"allTags\": kw('allTags'), \"closeAll\": kw('closeAll'), \"list\": kw('list'),\n \"newJournal\": kw('newJournal'), \"newTiddler\": kw('newTiddler'),\n \"permaview\": kw('permaview'), \"saveChanges\": kw('saveChanges'),\n \"search\": kw('search'), \"slider\": kw('slider'), \"tabs\": kw('tabs'),\n \"tag\": kw('tag'), \"tagging\": kw('tagging'), \"tags\": kw('tags'),\n \"tiddler\": kw('tiddler'), \"timeline\": kw('timeline'),\n \"today\": kw('today'), \"version\": kw('version'), \"option\": kw('option'),\n\n \"with\": kw('with'),\n \"filter\": kw('filter')\n };\n }();\n\n var isSpaceName = /[\\w_\\-]/i,\n reHR = /^\\-\\-\\-\\-+$/, // <hr>\n reWikiCommentStart = /^\\/\\*\\*\\*$/, // /***\n reWikiCommentStop = /^\\*\\*\\*\\/$/, // ***/\n reBlockQuote = /^<<<$/,\n\n reJsCodeStart = /^\\/\\/\\{\\{\\{$/, // //{{{ js block start\n reJsCodeStop = /^\\/\\/\\}\\}\\}$/, // //}}} js stop\n reXmlCodeStart = /^<!--\\{\\{\\{-->$/, // xml block start\n reXmlCodeStop = /^<!--\\}\\}\\}-->$/, // xml stop\n\n reCodeBlockStart = /^\\{\\{\\{$/, // {{{ TW text div block start\n reCodeBlockStop = /^\\}\\}\\}$/, // }}} TW text stop\n\n reUntilCodeStop = /.*?\\}\\}\\}/;\n\n function chain(stream, state, f) {\n state.tokenize = f;\n return f(stream, state);\n }\n\n function jsTokenBase(stream, state) {\n var sol = stream.sol(), ch;\n\n state.block = false; // indicates the start of a code block.\n\n ch = stream.peek(); // don't eat, to make matching simpler\n\n // check start of blocks\n if (sol && /[<\\/\\*{}\\-]/.test(ch)) {\n if (stream.match(reCodeBlockStart)) {\n state.block = true;\n return chain(stream, state, twTokenCode);\n }\n if (stream.match(reBlockQuote)) {\n return 'quote';\n }\n if (stream.match(reWikiCommentStart) || stream.match(reWikiCommentStop)) {\n return 'comment';\n }\n if (stream.match(reJsCodeStart) || stream.match(reJsCodeStop) || stream.match(reXmlCodeStart) || stream.match(reXmlCodeStop)) {\n return 'comment';\n }\n if (stream.match(reHR)) {\n return 'hr';\n }\n } // sol\n ch = stream.next();\n\n if (sol && /[\\/\\*!#;:>|]/.test(ch)) {\n if (ch == \"!\") { // tw header\n stream.skipToEnd();\n return \"header\";\n }\n if (ch == \"*\") { // tw list\n stream.eatWhile('*');\n return \"comment\";\n }\n if (ch == \"#\") { // tw numbered list\n stream.eatWhile('#');\n return \"comment\";\n }\n if (ch == \";\") { // definition list, term\n stream.eatWhile(';');\n return \"comment\";\n }\n if (ch == \":\") { // definition list, description\n stream.eatWhile(':');\n return \"comment\";\n }\n if (ch == \">\") { // single line quote\n stream.eatWhile(\">\");\n return \"quote\";\n }\n if (ch == '|') {\n return 'header';\n }\n }\n\n if (ch == '{' && stream.match(/\\{\\{/)) {\n return chain(stream, state, twTokenCode);\n }\n\n // rudimentary html:// file:// link matching. TW knows much more ...\n if (/[hf]/i.test(ch)) {\n if (/[ti]/i.test(stream.peek()) && stream.match(/\\b(ttps?|tp|ile):\\/\\/[\\-A-Z0-9+&@#\\/%?=~_|$!:,.;]*[A-Z0-9+&@#\\/%=~_|$]/i)) {\n return \"link\";\n }\n }\n // just a little string indicator, don't want to have the whole string covered\n if (ch == '\"') {\n return 'string';\n }\n if (ch == '~') { // _no_ CamelCase indicator should be bold\n return 'brace';\n }\n if (/[\\[\\]]/.test(ch)) { // check for [[..]]\n if (stream.peek() == ch) {\n stream.next();\n return 'brace';\n }\n }\n if (ch == \"@\") { // check for space link. TODO fix @@...@@ highlighting\n stream.eatWhile(isSpaceName);\n return \"link\";\n }\n if (/\\d/.test(ch)) { // numbers\n stream.eatWhile(/\\d/);\n return \"number\";\n }\n if (ch == \"/\") { // tw invisible comment\n if (stream.eat(\"%\")) {\n return chain(stream, state, twTokenComment);\n }\n else if (stream.eat(\"/\")) { //\n return chain(stream, state, twTokenEm);\n }\n }\n if (ch == \"_\") { // tw underline\n if (stream.eat(\"_\")) {\n return chain(stream, state, twTokenUnderline);\n }\n }\n // strikethrough and mdash handling\n if (ch == \"-\") {\n if (stream.eat(\"-\")) {\n // if strikethrough looks ugly, change CSS.\n if (stream.peek() != ' ')\n return chain(stream, state, twTokenStrike);\n // mdash\n if (stream.peek() == ' ')\n return 'brace';\n }\n }\n if (ch == \"'\") { // tw bold\n if (stream.eat(\"'\")) {\n return chain(stream, state, twTokenStrong);\n }\n }\n if (ch == \"<\") { // tw macro\n if (stream.eat(\"<\")) {\n return chain(stream, state, twTokenMacro);\n }\n }\n else {\n return null;\n }\n\n // core macro handling\n stream.eatWhile(/[\\w\\$_]/);\n var word = stream.current(),\n known = textwords.propertyIsEnumerable(word) && textwords[word];\n\n return known ? known.style : null;\n } // jsTokenBase()\n\n // tw invisible comment\n function twTokenComment(stream, state) {\n var maybeEnd = false,\n ch;\n while (ch = stream.next()) {\n if (ch == \"/\" && maybeEnd) {\n state.tokenize = jsTokenBase;\n break;\n }\n maybeEnd = (ch == \"%\");\n }\n return \"comment\";\n }\n\n // tw strong / bold\n function twTokenStrong(stream, state) {\n var maybeEnd = false,\n ch;\n while (ch = stream.next()) {\n if (ch == \"'\" && maybeEnd) {\n state.tokenize = jsTokenBase;\n break;\n }\n maybeEnd = (ch == \"'\");\n }\n return \"strong\";\n }\n\n // tw code\n function twTokenCode(stream, state) {\n var sb = state.block;\n\n if (sb && stream.current()) {\n return \"comment\";\n }\n\n if (!sb && stream.match(reUntilCodeStop)) {\n state.tokenize = jsTokenBase;\n return \"comment\";\n }\n\n if (sb && stream.sol() && stream.match(reCodeBlockStop)) {\n state.tokenize = jsTokenBase;\n return \"comment\";\n }\n\n stream.next();\n return \"comment\";\n }\n\n // tw em / italic\n function twTokenEm(stream, state) {\n var maybeEnd = false,\n ch;\n while (ch = stream.next()) {\n if (ch == \"/\" && maybeEnd) {\n state.tokenize = jsTokenBase;\n break;\n }\n maybeEnd = (ch == \"/\");\n }\n return \"em\";\n }\n\n // tw underlined text\n function twTokenUnderline(stream, state) {\n var maybeEnd = false,\n ch;\n while (ch = stream.next()) {\n if (ch == \"_\" && maybeEnd) {\n state.tokenize = jsTokenBase;\n break;\n }\n maybeEnd = (ch == \"_\");\n }\n return \"underlined\";\n }\n\n // tw strike through text looks ugly\n // change CSS if needed\n function twTokenStrike(stream, state) {\n var maybeEnd = false, ch;\n\n while (ch = stream.next()) {\n if (ch == \"-\" && maybeEnd) {\n state.tokenize = jsTokenBase;\n break;\n }\n maybeEnd = (ch == \"-\");\n }\n return \"strikethrough\";\n }\n\n // macro\n function twTokenMacro(stream, state) {\n var ch, word, known;\n\n if (stream.current() == '<<') {\n return 'macro';\n }\n\n ch = stream.next();\n if (!ch) {\n state.tokenize = jsTokenBase;\n return null;\n }\n if (ch == \">\") {\n if (stream.peek() == '>') {\n stream.next();\n state.tokenize = jsTokenBase;\n return \"macro\";\n }\n }\n\n stream.eatWhile(/[\\w\\$_]/);\n word = stream.current();\n known = keywords.propertyIsEnumerable(word) && keywords[word];\n\n if (known) {\n return known.style, word;\n }\n else {\n return null, word;\n }\n }\n\n // Interface\n return {\n startState: function () {\n return {\n tokenize: jsTokenBase,\n indented: 0,\n level: 0\n };\n },\n\n token: function (stream, state) {\n if (stream.eatSpace()) return null;\n var style = state.tokenize(stream, state);\n return style;\n },\n\n electricChars: \"\"\n };\n});\n\nCodeMirror.defineMIME(\"text/x-tiddlywiki\", \"tiddlywiki\");\n});\n\n//}}}\n"
},
"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n\"use strict\";\n\nvar htmlConfig = {\n autoSelfClosers: {'area': true, 'base': true, 'br': true, 'col': true, 'command': true,\n 'embed': true, 'frame': true, 'hr': true, 'img': true, 'input': true,\n 'keygen': true, 'link': true, 'meta': true, 'param': true, 'source': true,\n 'track': true, 'wbr': true, 'menuitem': true},\n implicitlyClosed: {'dd': true, 'li': true, 'optgroup': true, 'option': true, 'p': true,\n 'rp': true, 'rt': true, 'tbody': true, 'td': true, 'tfoot': true,\n 'th': true, 'tr': true},\n contextGrabbers: {\n 'dd': {'dd': true, 'dt': true},\n 'dt': {'dd': true, 'dt': true},\n 'li': {'li': true},\n 'option': {'option': true, 'optgroup': true},\n 'optgroup': {'optgroup': true},\n 'p': {'address': true, 'article': true, 'aside': true, 'blockquote': true, 'dir': true,\n 'div': true, 'dl': true, 'fieldset': true, 'footer': true, 'form': true,\n 'h1': true, 'h2': true, 'h3': true, 'h4': true, 'h5': true, 'h6': true,\n 'header': true, 'hgroup': true, 'hr': true, 'menu': true, 'nav': true, 'ol': true,\n 'p': true, 'pre': true, 'section': true, 'table': true, 'ul': true},\n 'rp': {'rp': true, 'rt': true},\n 'rt': {'rp': true, 'rt': true},\n 'tbody': {'tbody': true, 'tfoot': true},\n 'td': {'td': true, 'th': true},\n 'tfoot': {'tbody': true},\n 'th': {'td': true, 'th': true},\n 'thead': {'tbody': true, 'tfoot': true},\n 'tr': {'tr': true}\n },\n doNotIndent: {\"pre\": true},\n allowUnquoted: true,\n allowMissing: true,\n caseFold: true\n}\n\nvar xmlConfig = {\n autoSelfClosers: {},\n implicitlyClosed: {},\n contextGrabbers: {},\n doNotIndent: {},\n allowUnquoted: false,\n allowMissing: false,\n caseFold: false\n}\n\nCodeMirror.defineMode(\"xml\", function(editorConf, config_) {\n var indentUnit = editorConf.indentUnit\n var config = {}\n var defaults = config_.htmlMode ? htmlConfig : xmlConfig\n for (var prop in defaults) config[prop] = defaults[prop]\n for (var prop in config_) config[prop] = config_[prop]\n\n // Return variables for tokenizers\n var type, setStyle;\n\n function inText(stream, state) {\n function chain(parser) {\n state.tokenize = parser;\n return parser(stream, state);\n }\n\n var ch = stream.next();\n if (ch == \"<\") {\n if (stream.eat(\"!\")) {\n if (stream.eat(\"[\")) {\n if (stream.match(\"CDATA[\")) return chain(inBlock(\"atom\", \"]]>\"));\n else return null;\n } else if (stream.match(\"--\")) {\n return chain(inBlock(\"comment\", \"-->\"));\n } else if (stream.match(\"DOCTYPE\", true, true)) {\n stream.eatWhile(/[\\w\\._\\-]/);\n return chain(doctype(1));\n } else {\n return null;\n }\n } else if (stream.eat(\"?\")) {\n stream.eatWhile(/[\\w\\._\\-]/);\n state.tokenize = inBlock(\"meta\", \"?>\");\n return \"meta\";\n } else {\n type = stream.eat(\"/\") ? \"closeTag\" : \"openTag\";\n state.tokenize = inTag;\n return \"tag bracket\";\n }\n } else if (ch == \"&\") {\n var ok;\n if (stream.eat(\"#\")) {\n if (stream.eat(\"x\")) {\n ok = stream.eatWhile(/[a-fA-F\\d]/) && stream.eat(\";\");\n } else {\n ok = stream.eatWhile(/[\\d]/) && stream.eat(\";\");\n }\n } else {\n ok = stream.eatWhile(/[\\w\\.\\-:]/) && stream.eat(\";\");\n }\n return ok ? \"atom\" : \"error\";\n } else {\n stream.eatWhile(/[^&<]/);\n return null;\n }\n }\n inText.isInText = true;\n\n function inTag(stream, state) {\n var ch = stream.next();\n if (ch == \">\" || (ch == \"/\" && stream.eat(\">\"))) {\n state.tokenize = inText;\n type = ch == \">\" ? \"endTag\" : \"selfcloseTag\";\n return \"tag bracket\";\n } else if (ch == \"=\") {\n type = \"equals\";\n return null;\n } else if (ch == \"<\") {\n state.tokenize = inText;\n state.state = baseState;\n state.tagName = state.tagStart = null;\n var next = state.tokenize(stream, state);\n return next ? next + \" tag error\" : \"tag error\";\n } else if (/[\\'\\\"]/.test(ch)) {\n state.tokenize = inAttribute(ch);\n state.stringStartCol = stream.column();\n return state.tokenize(stream, state);\n } else {\n stream.match(/^[^\\s\\u00a0=<>\\\"\\']*[^\\s\\u00a0=<>\\\"\\'\\/]/);\n return \"word\";\n }\n }\n\n function inAttribute(quote) {\n var closure = function(stream, state) {\n while (!stream.eol()) {\n if (stream.next() == quote) {\n state.tokenize = inTag;\n break;\n }\n }\n return \"string\";\n };\n closure.isInAttribute = true;\n return closure;\n }\n\n function inBlock(style, terminator) {\n return function(stream, state) {\n while (!stream.eol()) {\n if (stream.match(terminator)) {\n state.tokenize = inText;\n break;\n }\n stream.next();\n }\n return style;\n };\n }\n function doctype(depth) {\n return function(stream, state) {\n var ch;\n while ((ch = stream.next()) != null) {\n if (ch == \"<\") {\n state.tokenize = doctype(depth + 1);\n return state.tokenize(stream, state);\n } else if (ch == \">\") {\n if (depth == 1) {\n state.tokenize = inText;\n break;\n } else {\n state.tokenize = doctype(depth - 1);\n return state.tokenize(stream, state);\n }\n }\n }\n return \"meta\";\n };\n }\n\n function Context(state, tagName, startOfLine) {\n this.prev = state.context;\n this.tagName = tagName;\n this.indent = state.indented;\n this.startOfLine = startOfLine;\n if (config.doNotIndent.hasOwnProperty(tagName) || (state.context && state.context.noIndent))\n this.noIndent = true;\n }\n function popContext(state) {\n if (state.context) state.context = state.context.prev;\n }\n function maybePopContext(state, nextTagName) {\n var parentTagName;\n while (true) {\n if (!state.context) {\n return;\n }\n parentTagName = state.context.tagName;\n if (!config.contextGrabbers.hasOwnProperty(parentTagName) ||\n !config.contextGrabbers[parentTagName].hasOwnProperty(nextTagName)) {\n return;\n }\n popContext(state);\n }\n }\n\n function baseState(type, stream, state) {\n if (type == \"openTag\") {\n state.tagStart = stream.column();\n return tagNameState;\n } else if (type == \"closeTag\") {\n return closeTagNameState;\n } else {\n return baseState;\n }\n }\n function tagNameState(type, stream, state) {\n if (type == \"word\") {\n state.tagName = stream.current();\n setStyle = \"tag\";\n return attrState;\n } else {\n setStyle = \"error\";\n return tagNameState;\n }\n }\n function closeTagNameState(type, stream, state) {\n if (type == \"word\") {\n var tagName = stream.current();\n if (state.context && state.context.tagName != tagName &&\n config.implicitlyClosed.hasOwnProperty(state.context.tagName))\n popContext(state);\n if ((state.context && state.context.tagName == tagName) || config.matchClosing === false) {\n setStyle = \"tag\";\n return closeState;\n } else {\n setStyle = \"tag error\";\n return closeStateErr;\n }\n } else {\n setStyle = \"error\";\n return closeStateErr;\n }\n }\n\n function closeState(type, _stream, state) {\n if (type != \"endTag\") {\n setStyle = \"error\";\n return closeState;\n }\n popContext(state);\n return baseState;\n }\n function closeStateErr(type, stream, state) {\n setStyle = \"error\";\n return closeState(type, stream, state);\n }\n\n function attrState(type, _stream, state) {\n if (type == \"word\") {\n setStyle = \"attribute\";\n return attrEqState;\n } else if (type == \"endTag\" || type == \"selfcloseTag\") {\n var tagName = state.tagName, tagStart = state.tagStart;\n state.tagName = state.tagStart = null;\n if (type == \"selfcloseTag\" ||\n config.autoSelfClosers.hasOwnProperty(tagName)) {\n maybePopContext(state, tagName);\n } else {\n maybePopContext(state, tagName);\n state.context = new Context(state, tagName, tagStart == state.indented);\n }\n return baseState;\n }\n setStyle = \"error\";\n return attrState;\n }\n function attrEqState(type, stream, state) {\n if (type == \"equals\") return attrValueState;\n if (!config.allowMissing) setStyle = \"error\";\n return attrState(type, stream, state);\n }\n function attrValueState(type, stream, state) {\n if (type == \"string\") return attrContinuedState;\n if (type == \"word\" && config.allowUnquoted) {setStyle = \"string\"; return attrState;}\n setStyle = \"error\";\n return attrState(type, stream, state);\n }\n function attrContinuedState(type, stream, state) {\n if (type == \"string\") return attrContinuedState;\n return attrState(type, stream, state);\n }\n\n return {\n startState: function(baseIndent) {\n var state = {tokenize: inText,\n state: baseState,\n indented: baseIndent || 0,\n tagName: null, tagStart: null,\n context: null}\n if (baseIndent != null) state.baseIndent = baseIndent\n return state\n },\n\n token: function(stream, state) {\n if (!state.tagName && stream.sol())\n state.indented = stream.indentation();\n\n if (stream.eatSpace()) return null;\n type = null;\n var style = state.tokenize(stream, state);\n if ((style || type) && style != \"comment\") {\n setStyle = null;\n state.state = state.state(type || style, stream, state);\n if (setStyle)\n style = setStyle == \"error\" ? style + \" error\" : setStyle;\n }\n return style;\n },\n\n indent: function(state, textAfter, fullLine) {\n var context = state.context;\n // Indent multi-line strings (e.g. css).\n if (state.tokenize.isInAttribute) {\n if (state.tagStart == state.indented)\n return state.stringStartCol + 1;\n else\n return state.indented + indentUnit;\n }\n if (context && context.noIndent) return CodeMirror.Pass;\n if (state.tokenize != inTag && state.tokenize != inText)\n return fullLine ? fullLine.match(/^(\\s*)/)[0].length : 0;\n // Indent the starts of attribute names.\n if (state.tagName) {\n if (config.multilineTagIndentPastTag !== false)\n return state.tagStart + state.tagName.length + 2;\n else\n return state.tagStart + indentUnit * (config.multilineTagIndentFactor || 1);\n }\n if (config.alignCDATA && /<!\\[CDATA\\[/.test(textAfter)) return 0;\n var tagAfter = textAfter && /^<(\\/)?([\\w_:\\.-]*)/.exec(textAfter);\n if (tagAfter && tagAfter[1]) { // Closing tag spotted\n while (context) {\n if (context.tagName == tagAfter[2]) {\n context = context.prev;\n break;\n } else if (config.implicitlyClosed.hasOwnProperty(context.tagName)) {\n context = context.prev;\n } else {\n break;\n }\n }\n } else if (tagAfter) { // Opening tag spotted\n while (context) {\n var grabbers = config.contextGrabbers[context.tagName];\n if (grabbers && grabbers.hasOwnProperty(tagAfter[2]))\n context = context.prev;\n else\n break;\n }\n }\n while (context && context.prev && !context.startOfLine)\n context = context.prev;\n if (context) return context.indent + indentUnit;\n else return state.baseIndent || 0;\n },\n\n electricInput: /<\\/[\\s\\w:]+>$/,\n blockCommentStart: \"<!--\",\n blockCommentEnd: \"-->\",\n\n configuration: config.htmlMode ? \"html\" : \"xml\",\n helperType: config.htmlMode ? \"html\" : \"xml\",\n\n skipAttribute: function(state) {\n if (state.state == attrValueState)\n state.state = attrState\n }\n };\n});\n\nCodeMirror.defineMIME(\"text/xml\", \"xml\");\nCodeMirror.defineMIME(\"application/xml\", \"xml\");\nif (!CodeMirror.mimeModes.hasOwnProperty(\"text/html\"))\n CodeMirror.defineMIME(\"text/html\", {name: \"xml\", htmlMode: true});\n\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/keymap/vim.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/keymap/vim.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n/**\n * Supported keybindings:\n * Too many to list. Refer to defaultKeyMap below.\n *\n * Supported Ex commands:\n * Refer to defaultExCommandMap below.\n *\n * Registers: unnamed, -, a-z, A-Z, 0-9\n * (Does not respect the special case for number registers when delete\n * operator is made with these commands: %, (, ), , /, ?, n, N, {, } )\n * TODO: Implement the remaining registers.\n *\n * Marks: a-z, A-Z, and 0-9\n * TODO: Implement the remaining special marks. They have more complex\n * behavior.\n *\n * Events:\n * 'vim-mode-change' - raised on the editor anytime the current mode changes,\n * Event object: {mode: \"visual\", subMode: \"linewise\"}\n *\n * Code structure:\n * 1. Default keymap\n * 2. Variable declarations and short basic helpers\n * 3. Instance (External API) implementation\n * 4. Internal state tracking objects (input state, counter) implementation\n * and instanstiation\n * 5. Key handler (the main command dispatcher) implementation\n * 6. Motion, operator, and action implementations\n * 7. Helper functions for the key handler, motions, operators, and actions\n * 8. Set up Vim to work as a keymap for CodeMirror.\n * 9. Ex command implementations.\n */\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../lib/codemirror\"), require(\"../addon/search/searchcursor\"), require(\"../addon/dialog/dialog\"), require(\"../addon/edit/matchbrackets.js\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../lib/codemirror\", \"../addon/search/searchcursor\", \"../addon/dialog/dialog\", \"../addon/edit/matchbrackets\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n 'use strict';\n\n var defaultKeymap = [\n // Key to key mapping. This goes first to make it possible to override\n // existing mappings.\n { keys: '<Left>', type: 'keyToKey', toKeys: 'h' },\n { keys: '<Right>', type: 'keyToKey', toKeys: 'l' },\n { keys: '<Up>', type: 'keyToKey', toKeys: 'k' },\n { keys: '<Down>', type: 'keyToKey', toKeys: 'j' },\n { keys: '<Space>', type: 'keyToKey', toKeys: 'l' },\n { keys: '<BS>', type: 'keyToKey', toKeys: 'h', context: 'normal'},\n { keys: '<C-Space>', type: 'keyToKey', toKeys: 'W' },\n { keys: '<C-BS>', type: 'keyToKey', toKeys: 'B', context: 'normal' },\n { keys: '<S-Space>', type: 'keyToKey', toKeys: 'w' },\n { keys: '<S-BS>', type: 'keyToKey', toKeys: 'b', context: 'normal' },\n { keys: '<C-n>', type: 'keyToKey', toKeys: 'j' },\n { keys: '<C-p>', type: 'keyToKey', toKeys: 'k' },\n { keys: '<C-[>', type: 'keyToKey', toKeys: '<Esc>' },\n { keys: '<C-c>', type: 'keyToKey', toKeys: '<Esc>' },\n { keys: '<C-[>', type: 'keyToKey', toKeys: '<Esc>', context: 'insert' },\n { keys: '<C-c>', type: 'keyToKey', toKeys: '<Esc>', context: 'insert' },\n { keys: 's', type: 'keyToKey', toKeys: 'cl', context: 'normal' },\n { keys: 's', type: 'keyToKey', toKeys: 'c', context: 'visual'},\n { keys: 'S', type: 'keyToKey', toKeys: 'cc', context: 'normal' },\n { keys: 'S', type: 'keyToKey', toKeys: 'VdO', context: 'visual' },\n { keys: '<Home>', type: 'keyToKey', toKeys: '0' },\n { keys: '<End>', type: 'keyToKey', toKeys: '$' },\n { keys: '<PageUp>', type: 'keyToKey', toKeys: '<C-b>' },\n { keys: '<PageDown>', type: 'keyToKey', toKeys: '<C-f>' },\n { keys: '<CR>', type: 'keyToKey', toKeys: 'j^', context: 'normal' },\n // Motions\n { keys: 'H', type: 'motion', motion: 'moveToTopLine', motionArgs: { linewise: true, toJumplist: true }},\n { keys: 'M', type: 'motion', motion: 'moveToMiddleLine', motionArgs: { linewise: true, toJumplist: true }},\n { keys: 'L', type: 'motion', motion: 'moveToBottomLine', motionArgs: { linewise: true, toJumplist: true }},\n { keys: 'h', type: 'motion', motion: 'moveByCharacters', motionArgs: { forward: false }},\n { keys: 'l', type: 'motion', motion: 'moveByCharacters', motionArgs: { forward: true }},\n { keys: 'j', type: 'motion', motion: 'moveByLines', motionArgs: { forward: true, linewise: true }},\n { keys: 'k', type: 'motion', motion: 'moveByLines', motionArgs: { forward: false, linewise: true }},\n { keys: 'gj', type: 'motion', motion: 'moveByDisplayLines', motionArgs: { forward: true }},\n { keys: 'gk', type: 'motion', motion: 'moveByDisplayLines', motionArgs: { forward: false }},\n { keys: 'w', type: 'motion', motion: 'moveByWords', motionArgs: { forward: true, wordEnd: false }},\n { keys: 'W', type: 'motion', motion: 'moveByWords', motionArgs: { forward: true, wordEnd: false, bigWord: true }},\n { keys: 'e', type: 'motion', motion: 'moveByWords', motionArgs: { forward: true, wordEnd: true, inclusive: true }},\n { keys: 'E', type: 'motion', motion: 'moveByWords', motionArgs: { forward: true, wordEnd: true, bigWord: true, inclusive: true }},\n { keys: 'b', type: 'motion', motion: 'moveByWords', motionArgs: { forward: false, wordEnd: false }},\n { keys: 'B', type: 'motion', motion: 'moveByWords', motionArgs: { forward: false, wordEnd: false, bigWord: true }},\n { keys: 'ge', type: 'motion', motion: 'moveByWords', motionArgs: { forward: false, wordEnd: true, inclusive: true }},\n { keys: 'gE', type: 'motion', motion: 'moveByWords', motionArgs: { forward: false, wordEnd: true, bigWord: true, inclusive: true }},\n { keys: '{', type: 'motion', motion: 'moveByParagraph', motionArgs: { forward: false, toJumplist: true }},\n { keys: '}', type: 'motion', motion: 'moveByParagraph', motionArgs: { forward: true, toJumplist: true }},\n { keys: '<C-f>', type: 'motion', motion: 'moveByPage', motionArgs: { forward: true }},\n { keys: '<C-b>', type: 'motion', motion: 'moveByPage', motionArgs: { forward: false }},\n { keys: '<C-d>', type: 'motion', motion: 'moveByScroll', motionArgs: { forward: true, explicitRepeat: true }},\n { keys: '<C-u>', type: 'motion', motion: 'moveByScroll', motionArgs: { forward: false, explicitRepeat: true }},\n { keys: 'gg', type: 'motion', motion: 'moveToLineOrEdgeOfDocument', motionArgs: { forward: false, explicitRepeat: true, linewise: true, toJumplist: true }},\n { keys: 'G', type: 'motion', motion: 'moveToLineOrEdgeOfDocument', motionArgs: { forward: true, explicitRepeat: true, linewise: true, toJumplist: true }},\n { keys: '0', type: 'motion', motion: 'moveToStartOfLine' },\n { keys: '^', type: 'motion', motion: 'moveToFirstNonWhiteSpaceCharacter' },\n { keys: '+', type: 'motion', motion: 'moveByLines', motionArgs: { forward: true, toFirstChar:true }},\n { keys: '-', type: 'motion', motion: 'moveByLines', motionArgs: { forward: false, toFirstChar:true }},\n { keys: '_', type: 'motion', motion: 'moveByLines', motionArgs: { forward: true, toFirstChar:true, repeatOffset:-1 }},\n { keys: '$', type: 'motion', motion: 'moveToEol', motionArgs: { inclusive: true }},\n { keys: '%', type: 'motion', motion: 'moveToMatchedSymbol', motionArgs: { inclusive: true, toJumplist: true }},\n { keys: 'f<character>', type: 'motion', motion: 'moveToCharacter', motionArgs: { forward: true , inclusive: true }},\n { keys: 'F<character>', type: 'motion', motion: 'moveToCharacter', motionArgs: { forward: false }},\n { keys: 't<character>', type: 'motion', motion: 'moveTillCharacter', motionArgs: { forward: true, inclusive: true }},\n { keys: 'T<character>', type: 'motion', motion: 'moveTillCharacter', motionArgs: { forward: false }},\n { keys: ';', type: 'motion', motion: 'repeatLastCharacterSearch', motionArgs: { forward: true }},\n { keys: ',', type: 'motion', motion: 'repeatLastCharacterSearch', motionArgs: { forward: false }},\n { keys: '\\'<character>', type: 'motion', motion: 'goToMark', motionArgs: {toJumplist: true, linewise: true}},\n { keys: '`<character>', type: 'motion', motion: 'goToMark', motionArgs: {toJumplist: true}},\n { keys: ']`', type: 'motion', motion: 'jumpToMark', motionArgs: { forward: true } },\n { keys: '[`', type: 'motion', motion: 'jumpToMark', motionArgs: { forward: false } },\n { keys: ']\\'', type: 'motion', motion: 'jumpToMark', motionArgs: { forward: true, linewise: true } },\n { keys: '[\\'', type: 'motion', motion: 'jumpToMark', motionArgs: { forward: false, linewise: true } },\n // the next two aren't motions but must come before more general motion declarations\n { keys: ']p', type: 'action', action: 'paste', isEdit: true, actionArgs: { after: true, isEdit: true, matchIndent: true}},\n { keys: '[p', type: 'action', action: 'paste', isEdit: true, actionArgs: { after: false, isEdit: true, matchIndent: true}},\n { keys: ']<character>', type: 'motion', motion: 'moveToSymbol', motionArgs: { forward: true, toJumplist: true}},\n { keys: '[<character>', type: 'motion', motion: 'moveToSymbol', motionArgs: { forward: false, toJumplist: true}},\n { keys: '|', type: 'motion', motion: 'moveToColumn'},\n { keys: 'o', type: 'motion', motion: 'moveToOtherHighlightedEnd', context:'visual'},\n { keys: 'O', type: 'motion', motion: 'moveToOtherHighlightedEnd', motionArgs: {sameLine: true}, context:'visual'},\n // Operators\n { keys: 'd', type: 'operator', operator: 'delete' },\n { keys: 'y', type: 'operator', operator: 'yank' },\n { keys: 'c', type: 'operator', operator: 'change' },\n { keys: '>', type: 'operator', operator: 'indent', operatorArgs: { indentRight: true }},\n { keys: '<', type: 'operator', operator: 'indent', operatorArgs: { indentRight: false }},\n { keys: 'g~', type: 'operator', operator: 'changeCase' },\n { keys: 'gu', type: 'operator', operator: 'changeCase', operatorArgs: {toLower: true}, isEdit: true },\n { keys: 'gU', type: 'operator', operator: 'changeCase', operatorArgs: {toLower: false}, isEdit: true },\n { keys: 'n', type: 'motion', motion: 'findNext', motionArgs: { forward: true, toJumplist: true }},\n { keys: 'N', type: 'motion', motion: 'findNext', motionArgs: { forward: false, toJumplist: true }},\n // Operator-Motion dual commands\n { keys: 'x', type: 'operatorMotion', operator: 'delete', motion: 'moveByCharacters', motionArgs: { forward: true }, operatorMotionArgs: { visualLine: false }},\n { keys: 'X', type: 'operatorMotion', operator: 'delete', motion: 'moveByCharacters', motionArgs: { forward: false }, operatorMotionArgs: { visualLine: true }},\n { keys: 'D', type: 'operatorMotion', operator: 'delete', motion: 'moveToEol', motionArgs: { inclusive: true }, context: 'normal'},\n { keys: 'D', type: 'operator', operator: 'delete', operatorArgs: { linewise: true }, context: 'visual'},\n { keys: 'Y', type: 'operatorMotion', operator: 'yank', motion: 'moveToEol', motionArgs: { inclusive: true }, context: 'normal'},\n { keys: 'Y', type: 'operator', operator: 'yank', operatorArgs: { linewise: true }, context: 'visual'},\n { keys: 'C', type: 'operatorMotion', operator: 'change', motion: 'moveToEol', motionArgs: { inclusive: true }, context: 'normal'},\n { keys: 'C', type: 'operator', operator: 'change', operatorArgs: { linewise: true }, context: 'visual'},\n { keys: '~', type: 'operatorMotion', operator: 'changeCase', motion: 'moveByCharacters', motionArgs: { forward: true }, operatorArgs: { shouldMoveCursor: true }, context: 'normal'},\n { keys: '~', type: 'operator', operator: 'changeCase', context: 'visual'},\n { keys: '<C-w>', type: 'operatorMotion', operator: 'delete', motion: 'moveByWords', motionArgs: { forward: false, wordEnd: false }, context: 'insert' },\n // Actions\n { keys: '<C-i>', type: 'action', action: 'jumpListWalk', actionArgs: { forward: true }},\n { keys: '<C-o>', type: 'action', action: 'jumpListWalk', actionArgs: { forward: false }},\n { keys: '<C-e>', type: 'action', action: 'scroll', actionArgs: { forward: true, linewise: true }},\n { keys: '<C-y>', type: 'action', action: 'scroll', actionArgs: { forward: false, linewise: true }},\n { keys: 'a', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'charAfter' }, context: 'normal' },\n { keys: 'A', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'eol' }, context: 'normal' },\n { keys: 'A', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'endOfSelectedArea' }, context: 'visual' },\n { keys: 'i', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'inplace' }, context: 'normal' },\n { keys: 'I', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'firstNonBlank'}, context: 'normal' },\n { keys: 'I', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { insertAt: 'startOfSelectedArea' }, context: 'visual' },\n { keys: 'o', type: 'action', action: 'newLineAndEnterInsertMode', isEdit: true, interlaceInsertRepeat: true, actionArgs: { after: true }, context: 'normal' },\n { keys: 'O', type: 'action', action: 'newLineAndEnterInsertMode', isEdit: true, interlaceInsertRepeat: true, actionArgs: { after: false }, context: 'normal' },\n { keys: 'v', type: 'action', action: 'toggleVisualMode' },\n { keys: 'V', type: 'action', action: 'toggleVisualMode', actionArgs: { linewise: true }},\n { keys: '<C-v>', type: 'action', action: 'toggleVisualMode', actionArgs: { blockwise: true }},\n { keys: '<C-q>', type: 'action', action: 'toggleVisualMode', actionArgs: { blockwise: true }},\n { keys: 'gv', type: 'action', action: 'reselectLastSelection' },\n { keys: 'J', type: 'action', action: 'joinLines', isEdit: true },\n { keys: 'p', type: 'action', action: 'paste', isEdit: true, actionArgs: { after: true, isEdit: true }},\n { keys: 'P', type: 'action', action: 'paste', isEdit: true, actionArgs: { after: false, isEdit: true }},\n { keys: 'r<character>', type: 'action', action: 'replace', isEdit: true },\n { keys: '@<character>', type: 'action', action: 'replayMacro' },\n { keys: 'q<character>', type: 'action', action: 'enterMacroRecordMode' },\n // Handle Replace-mode as a special case of insert mode.\n { keys: 'R', type: 'action', action: 'enterInsertMode', isEdit: true, actionArgs: { replace: true }},\n { keys: 'u', type: 'action', action: 'undo', context: 'normal' },\n { keys: 'u', type: 'operator', operator: 'changeCase', operatorArgs: {toLower: true}, context: 'visual', isEdit: true },\n { keys: 'U', type: 'operator', operator: 'changeCase', operatorArgs: {toLower: false}, context: 'visual', isEdit: true },\n { keys: '<C-r>', type: 'action', action: 'redo' },\n { keys: 'm<character>', type: 'action', action: 'setMark' },\n { keys: '\"<character>', type: 'action', action: 'setRegister' },\n { keys: 'zz', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'center' }},\n { keys: 'z.', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'center' }, motion: 'moveToFirstNonWhiteSpaceCharacter' },\n { keys: 'zt', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'top' }},\n { keys: 'z<CR>', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'top' }, motion: 'moveToFirstNonWhiteSpaceCharacter' },\n { keys: 'z-', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'bottom' }},\n { keys: 'zb', type: 'action', action: 'scrollToCursor', actionArgs: { position: 'bottom' }, motion: 'moveToFirstNonWhiteSpaceCharacter' },\n { keys: '.', type: 'action', action: 'repeatLastEdit' },\n { keys: '<C-a>', type: 'action', action: 'incrementNumberToken', isEdit: true, actionArgs: {increase: true, backtrack: false}},\n { keys: '<C-x>', type: 'action', action: 'incrementNumberToken', isEdit: true, actionArgs: {increase: false, backtrack: false}},\n // Text object motions\n { keys: 'a<character>', type: 'motion', motion: 'textObjectManipulation' },\n { keys: 'i<character>', type: 'motion', motion: 'textObjectManipulation', motionArgs: { textObjectInner: true }},\n // Search\n { keys: '/', type: 'search', searchArgs: { forward: true, querySrc: 'prompt', toJumplist: true }},\n { keys: '?', type: 'search', searchArgs: { forward: false, querySrc: 'prompt', toJumplist: true }},\n { keys: '*', type: 'search', searchArgs: { forward: true, querySrc: 'wordUnderCursor', wholeWordOnly: true, toJumplist: true }},\n { keys: '#', type: 'search', searchArgs: { forward: false, querySrc: 'wordUnderCursor', wholeWordOnly: true, toJumplist: true }},\n { keys: 'g*', type: 'search', searchArgs: { forward: true, querySrc: 'wordUnderCursor', toJumplist: true }},\n { keys: 'g#', type: 'search', searchArgs: { forward: false, querySrc: 'wordUnderCursor', toJumplist: true }},\n // Ex command\n { keys: ':', type: 'ex' }\n ];\n\n /**\n * Ex commands\n * Care must be taken when adding to the default Ex command map. For any\n * pair of commands that have a shared prefix, at least one of their\n * shortNames must not match the prefix of the other command.\n */\n var defaultExCommandMap = [\n { name: 'colorscheme', shortName: 'colo' },\n { name: 'map' },\n { name: 'imap', shortName: 'im' },\n { name: 'nmap', shortName: 'nm' },\n { name: 'vmap', shortName: 'vm' },\n { name: 'unmap' },\n { name: 'write', shortName: 'w' },\n { name: 'undo', shortName: 'u' },\n { name: 'redo', shortName: 'red' },\n { name: 'set', shortName: 'se' },\n { name: 'set', shortName: 'se' },\n { name: 'setlocal', shortName: 'setl' },\n { name: 'setglobal', shortName: 'setg' },\n { name: 'sort', shortName: 'sor' },\n { name: 'substitute', shortName: 's', possiblyAsync: true },\n { name: 'nohlsearch', shortName: 'noh' },\n { name: 'delmarks', shortName: 'delm' },\n { name: 'registers', shortName: 'reg', excludeFromCommandHistory: true },\n { name: 'global', shortName: 'g' }\n ];\n\n var Pos = CodeMirror.Pos;\n\n var Vim = function() {\n function enterVimMode(cm) {\n cm.setOption('disableInput', true);\n cm.setOption('showCursorWhenSelecting', false);\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"normal\"});\n cm.on('cursorActivity', onCursorActivity);\n maybeInitVimState(cm);\n CodeMirror.on(cm.getInputField(), 'paste', getOnPasteFn(cm));\n }\n\n function leaveVimMode(cm) {\n cm.setOption('disableInput', false);\n cm.off('cursorActivity', onCursorActivity);\n CodeMirror.off(cm.getInputField(), 'paste', getOnPasteFn(cm));\n cm.state.vim = null;\n }\n\n function detachVimMap(cm, next) {\n if (this == CodeMirror.keyMap.vim)\n CodeMirror.rmClass(cm.getWrapperElement(), \"cm-fat-cursor\");\n\n if (!next || next.attach != attachVimMap)\n leaveVimMode(cm, false);\n }\n function attachVimMap(cm, prev) {\n if (this == CodeMirror.keyMap.vim)\n CodeMirror.addClass(cm.getWrapperElement(), \"cm-fat-cursor\");\n\n if (!prev || prev.attach != attachVimMap)\n enterVimMode(cm);\n }\n\n // Deprecated, simply setting the keymap works again.\n CodeMirror.defineOption('vimMode', false, function(cm, val, prev) {\n if (val && cm.getOption(\"keyMap\") != \"vim\")\n cm.setOption(\"keyMap\", \"vim\");\n else if (!val && prev != CodeMirror.Init && /^vim/.test(cm.getOption(\"keyMap\")))\n cm.setOption(\"keyMap\", \"default\");\n });\n\n function cmKey(key, cm) {\n if (!cm) { return undefined; }\n var vimKey = cmKeyToVimKey(key);\n if (!vimKey) {\n return false;\n }\n var cmd = CodeMirror.Vim.findKey(cm, vimKey);\n if (typeof cmd == 'function') {\n CodeMirror.signal(cm, 'vim-keypress', vimKey);\n }\n return cmd;\n }\n\n var modifiers = {'Shift': 'S', 'Ctrl': 'C', 'Alt': 'A', 'Cmd': 'D', 'Mod': 'A'};\n var specialKeys = {Enter:'CR',Backspace:'BS',Delete:'Del'};\n function cmKeyToVimKey(key) {\n if (key.charAt(0) == '\\'') {\n // Keypress character binding of format \"'a'\"\n return key.charAt(1);\n }\n var pieces = key.split(/-(?!$)/);\n var lastPiece = pieces[pieces.length - 1];\n if (pieces.length == 1 && pieces[0].length == 1) {\n // No-modifier bindings use literal character bindings above. Skip.\n return false;\n } else if (pieces.length == 2 && pieces[0] == 'Shift' && lastPiece.length == 1) {\n // Ignore Shift+char bindings as they should be handled by literal character.\n return false;\n }\n var hasCharacter = false;\n for (var i = 0; i < pieces.length; i++) {\n var piece = pieces[i];\n if (piece in modifiers) { pieces[i] = modifiers[piece]; }\n else { hasCharacter = true; }\n if (piece in specialKeys) { pieces[i] = specialKeys[piece]; }\n }\n if (!hasCharacter) {\n // Vim does not support modifier only keys.\n return false;\n }\n // TODO: Current bindings expect the character to be lower case, but\n // it looks like vim key notation uses upper case.\n if (isUpperCase(lastPiece)) {\n pieces[pieces.length - 1] = lastPiece.toLowerCase();\n }\n return '<' + pieces.join('-') + '>';\n }\n\n function getOnPasteFn(cm) {\n var vim = cm.state.vim;\n if (!vim.onPasteFn) {\n vim.onPasteFn = function() {\n if (!vim.insertMode) {\n cm.setCursor(offsetCursor(cm.getCursor(), 0, 1));\n actions.enterInsertMode(cm, {}, vim);\n }\n };\n }\n return vim.onPasteFn;\n }\n\n var numberRegex = /[\\d]/;\n var wordCharTest = [CodeMirror.isWordChar, function(ch) {\n return ch && !CodeMirror.isWordChar(ch) && !/\\s/.test(ch);\n }], bigWordCharTest = [function(ch) {\n return /\\S/.test(ch);\n }];\n function makeKeyRange(start, size) {\n var keys = [];\n for (var i = start; i < start + size; i++) {\n keys.push(String.fromCharCode(i));\n }\n return keys;\n }\n var upperCaseAlphabet = makeKeyRange(65, 26);\n var lowerCaseAlphabet = makeKeyRange(97, 26);\n var numbers = makeKeyRange(48, 10);\n var validMarks = [].concat(upperCaseAlphabet, lowerCaseAlphabet, numbers, ['<', '>']);\n var validRegisters = [].concat(upperCaseAlphabet, lowerCaseAlphabet, numbers, ['-', '\"', '.', ':', '/']);\n\n function isLine(cm, line) {\n return line >= cm.firstLine() && line <= cm.lastLine();\n }\n function isLowerCase(k) {\n return (/^[a-z]$/).test(k);\n }\n function isMatchableSymbol(k) {\n return '()[]{}'.indexOf(k) != -1;\n }\n function isNumber(k) {\n return numberRegex.test(k);\n }\n function isUpperCase(k) {\n return (/^[A-Z]$/).test(k);\n }\n function isWhiteSpaceString(k) {\n return (/^\\s*$/).test(k);\n }\n function inArray(val, arr) {\n for (var i = 0; i < arr.length; i++) {\n if (arr[i] == val) {\n return true;\n }\n }\n return false;\n }\n\n var options = {};\n function defineOption(name, defaultValue, type, aliases, callback) {\n if (defaultValue === undefined && !callback) {\n throw Error('defaultValue is required unless callback is provided');\n }\n if (!type) { type = 'string'; }\n options[name] = {\n type: type,\n defaultValue: defaultValue,\n callback: callback\n };\n if (aliases) {\n for (var i = 0; i < aliases.length; i++) {\n options[aliases[i]] = options[name];\n }\n }\n if (defaultValue) {\n setOption(name, defaultValue);\n }\n }\n\n function setOption(name, value, cm, cfg) {\n var option = options[name];\n cfg = cfg || {};\n var scope = cfg.scope;\n if (!option) {\n throw Error('Unknown option: ' + name);\n }\n if (option.type == 'boolean') {\n if (value && value !== true) {\n throw Error('Invalid argument: ' + name + '=' + value);\n } else if (value !== false) {\n // Boolean options are set to true if value is not defined.\n value = true;\n }\n }\n if (option.callback) {\n if (scope !== 'local') {\n option.callback(value, undefined);\n }\n if (scope !== 'global' && cm) {\n option.callback(value, cm);\n }\n } else {\n if (scope !== 'local') {\n option.value = option.type == 'boolean' ? !!value : value;\n }\n if (scope !== 'global' && cm) {\n cm.state.vim.options[name] = {value: value};\n }\n }\n }\n\n function getOption(name, cm, cfg) {\n var option = options[name];\n cfg = cfg || {};\n var scope = cfg.scope;\n if (!option) {\n throw Error('Unknown option: ' + name);\n }\n if (option.callback) {\n var local = cm && option.callback(undefined, cm);\n if (scope !== 'global' && local !== undefined) {\n return local;\n }\n if (scope !== 'local') {\n return option.callback();\n }\n return;\n } else {\n var local = (scope !== 'global') && (cm && cm.state.vim.options[name]);\n return (local || (scope !== 'local') && option || {}).value;\n }\n }\n\n defineOption('filetype', undefined, 'string', ['ft'], function(name, cm) {\n // Option is local. Do nothing for global.\n if (cm === undefined) {\n return;\n }\n // The 'filetype' option proxies to the CodeMirror 'mode' option.\n if (name === undefined) {\n var mode = cm.getOption('mode');\n return mode == 'null' ? '' : mode;\n } else {\n var mode = name == '' ? 'null' : name;\n cm.setOption('mode', mode);\n }\n });\n\n var createCircularJumpList = function() {\n var size = 100;\n var pointer = -1;\n var head = 0;\n var tail = 0;\n var buffer = new Array(size);\n function add(cm, oldCur, newCur) {\n var current = pointer % size;\n var curMark = buffer[current];\n function useNextSlot(cursor) {\n var next = ++pointer % size;\n var trashMark = buffer[next];\n if (trashMark) {\n trashMark.clear();\n }\n buffer[next] = cm.setBookmark(cursor);\n }\n if (curMark) {\n var markPos = curMark.find();\n // avoid recording redundant cursor position\n if (markPos && !cursorEqual(markPos, oldCur)) {\n useNextSlot(oldCur);\n }\n } else {\n useNextSlot(oldCur);\n }\n useNextSlot(newCur);\n head = pointer;\n tail = pointer - size + 1;\n if (tail < 0) {\n tail = 0;\n }\n }\n function move(cm, offset) {\n pointer += offset;\n if (pointer > head) {\n pointer = head;\n } else if (pointer < tail) {\n pointer = tail;\n }\n var mark = buffer[(size + pointer) % size];\n // skip marks that are temporarily removed from text buffer\n if (mark && !mark.find()) {\n var inc = offset > 0 ? 1 : -1;\n var newCur;\n var oldCur = cm.getCursor();\n do {\n pointer += inc;\n mark = buffer[(size + pointer) % size];\n // skip marks that are the same as current position\n if (mark &&\n (newCur = mark.find()) &&\n !cursorEqual(oldCur, newCur)) {\n break;\n }\n } while (pointer < head && pointer > tail);\n }\n return mark;\n }\n return {\n cachedCursor: undefined, //used for # and * jumps\n add: add,\n move: move\n };\n };\n\n // Returns an object to track the changes associated insert mode. It\n // clones the object that is passed in, or creates an empty object one if\n // none is provided.\n var createInsertModeChanges = function(c) {\n if (c) {\n // Copy construction\n return {\n changes: c.changes,\n expectCursorActivityForChange: c.expectCursorActivityForChange\n };\n }\n return {\n // Change list\n changes: [],\n // Set to true on change, false on cursorActivity.\n expectCursorActivityForChange: false\n };\n };\n\n function MacroModeState() {\n this.latestRegister = undefined;\n this.isPlaying = false;\n this.isRecording = false;\n this.replaySearchQueries = [];\n this.onRecordingDone = undefined;\n this.lastInsertModeChanges = createInsertModeChanges();\n }\n MacroModeState.prototype = {\n exitMacroRecordMode: function() {\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.onRecordingDone) {\n macroModeState.onRecordingDone(); // close dialog\n }\n macroModeState.onRecordingDone = undefined;\n macroModeState.isRecording = false;\n },\n enterMacroRecordMode: function(cm, registerName) {\n var register =\n vimGlobalState.registerController.getRegister(registerName);\n if (register) {\n register.clear();\n this.latestRegister = registerName;\n if (cm.openDialog) {\n this.onRecordingDone = cm.openDialog(\n '(recording)['+registerName+']', null, {bottom:true});\n }\n this.isRecording = true;\n }\n }\n };\n\n function maybeInitVimState(cm) {\n if (!cm.state.vim) {\n // Store instance state in the CodeMirror object.\n cm.state.vim = {\n inputState: new InputState(),\n // Vim's input state that triggered the last edit, used to repeat\n // motions and operators with '.'.\n lastEditInputState: undefined,\n // Vim's action command before the last edit, used to repeat actions\n // with '.' and insert mode repeat.\n lastEditActionCommand: undefined,\n // When using jk for navigation, if you move from a longer line to a\n // shorter line, the cursor may clip to the end of the shorter line.\n // If j is pressed again and cursor goes to the next line, the\n // cursor should go back to its horizontal position on the longer\n // line if it can. This is to keep track of the horizontal position.\n lastHPos: -1,\n // Doing the same with screen-position for gj/gk\n lastHSPos: -1,\n // The last motion command run. Cleared if a non-motion command gets\n // executed in between.\n lastMotion: null,\n marks: {},\n // Mark for rendering fake cursor for visual mode.\n fakeCursor: null,\n insertMode: false,\n // Repeat count for changes made in insert mode, triggered by key\n // sequences like 3,i. Only exists when insertMode is true.\n insertModeRepeat: undefined,\n visualMode: false,\n // If we are in visual line mode. No effect if visualMode is false.\n visualLine: false,\n visualBlock: false,\n lastSelection: null,\n lastPastedText: null,\n sel: {},\n // Buffer-local/window-local values of vim options.\n options: {}\n };\n }\n return cm.state.vim;\n }\n var vimGlobalState;\n function resetVimGlobalState() {\n vimGlobalState = {\n // The current search query.\n searchQuery: null,\n // Whether we are searching backwards.\n searchIsReversed: false,\n // Replace part of the last substituted pattern\n lastSubstituteReplacePart: undefined,\n jumpList: createCircularJumpList(),\n macroModeState: new MacroModeState,\n // Recording latest f, t, F or T motion command.\n lastChararacterSearch: {increment:0, forward:true, selectedCharacter:''},\n registerController: new RegisterController({}),\n // search history buffer\n searchHistoryController: new HistoryController({}),\n // ex Command history buffer\n exCommandHistoryController : new HistoryController({})\n };\n for (var optionName in options) {\n var option = options[optionName];\n option.value = option.defaultValue;\n }\n }\n\n var lastInsertModeKeyTimer;\n var vimApi= {\n buildKeyMap: function() {\n // TODO: Convert keymap into dictionary format for fast lookup.\n },\n // Testing hook, though it might be useful to expose the register\n // controller anyways.\n getRegisterController: function() {\n return vimGlobalState.registerController;\n },\n // Testing hook.\n resetVimGlobalState_: resetVimGlobalState,\n\n // Testing hook.\n getVimGlobalState_: function() {\n return vimGlobalState;\n },\n\n // Testing hook.\n maybeInitVimState_: maybeInitVimState,\n\n suppressErrorLogging: false,\n\n InsertModeKey: InsertModeKey,\n map: function(lhs, rhs, ctx) {\n // Add user defined key bindings.\n exCommandDispatcher.map(lhs, rhs, ctx);\n },\n unmap: function(lhs, ctx) {\n exCommandDispatcher.unmap(lhs, ctx);\n },\n // TODO: Expose setOption and getOption as instance methods. Need to decide how to namespace\n // them, or somehow make them work with the existing CodeMirror setOption/getOption API.\n setOption: setOption,\n getOption: getOption,\n defineOption: defineOption,\n defineEx: function(name, prefix, func){\n if (!prefix) {\n prefix = name;\n } else if (name.indexOf(prefix) !== 0) {\n throw new Error('(Vim.defineEx) \"'+prefix+'\" is not a prefix of \"'+name+'\", command not registered');\n }\n exCommands[name]=func;\n exCommandDispatcher.commandMap_[prefix]={name:name, shortName:prefix, type:'api'};\n },\n handleKey: function (cm, key, origin) {\n var command = this.findKey(cm, key, origin);\n if (typeof command === 'function') {\n return command();\n }\n },\n /**\n * This is the outermost function called by CodeMirror, after keys have\n * been mapped to their Vim equivalents.\n *\n * Finds a command based on the key (and cached keys if there is a\n * multi-key sequence). Returns `undefined` if no key is matched, a noop\n * function if a partial match is found (multi-key), and a function to\n * execute the bound command if a a key is matched. The function always\n * returns true.\n */\n findKey: function(cm, key, origin) {\n var vim = maybeInitVimState(cm);\n function handleMacroRecording() {\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.isRecording) {\n if (key == 'q') {\n macroModeState.exitMacroRecordMode();\n clearInputState(cm);\n return true;\n }\n if (origin != 'mapping') {\n logKey(macroModeState, key);\n }\n }\n }\n function handleEsc() {\n if (key == '<Esc>') {\n // Clear input state and get back to normal mode.\n clearInputState(cm);\n if (vim.visualMode) {\n exitVisualMode(cm);\n } else if (vim.insertMode) {\n exitInsertMode(cm);\n }\n return true;\n }\n }\n function doKeyToKey(keys) {\n // TODO: prevent infinite recursion.\n var match;\n while (keys) {\n // Pull off one command key, which is either a single character\n // or a special sequence wrapped in '<' and '>', e.g. '<Space>'.\n match = (/<\\w+-.+?>|<\\w+>|./).exec(keys);\n key = match[0];\n keys = keys.substring(match.index + key.length);\n CodeMirror.Vim.handleKey(cm, key, 'mapping');\n }\n }\n\n function handleKeyInsertMode() {\n if (handleEsc()) { return true; }\n var keys = vim.inputState.keyBuffer = vim.inputState.keyBuffer + key;\n var keysAreChars = key.length == 1;\n var match = commandDispatcher.matchCommand(keys, defaultKeymap, vim.inputState, 'insert');\n // Need to check all key substrings in insert mode.\n while (keys.length > 1 && match.type != 'full') {\n var keys = vim.inputState.keyBuffer = keys.slice(1);\n var thisMatch = commandDispatcher.matchCommand(keys, defaultKeymap, vim.inputState, 'insert');\n if (thisMatch.type != 'none') { match = thisMatch; }\n }\n if (match.type == 'none') { clearInputState(cm); return false; }\n else if (match.type == 'partial') {\n if (lastInsertModeKeyTimer) { window.clearTimeout(lastInsertModeKeyTimer); }\n lastInsertModeKeyTimer = window.setTimeout(\n function() { if (vim.insertMode && vim.inputState.keyBuffer) { clearInputState(cm); } },\n getOption('insertModeEscKeysTimeout'));\n return !keysAreChars;\n }\n\n if (lastInsertModeKeyTimer) { window.clearTimeout(lastInsertModeKeyTimer); }\n if (keysAreChars) {\n var here = cm.getCursor();\n cm.replaceRange('', offsetCursor(here, 0, -(keys.length - 1)), here, '+input');\n }\n clearInputState(cm);\n return match.command;\n }\n\n function handleKeyNonInsertMode() {\n if (handleMacroRecording() || handleEsc()) { return true; };\n\n var keys = vim.inputState.keyBuffer = vim.inputState.keyBuffer + key;\n if (/^[1-9]\\d*$/.test(keys)) { return true; }\n\n var keysMatcher = /^(\\d*)(.*)$/.exec(keys);\n if (!keysMatcher) { clearInputState(cm); return false; }\n var context = vim.visualMode ? 'visual' :\n 'normal';\n var match = commandDispatcher.matchCommand(keysMatcher[2] || keysMatcher[1], defaultKeymap, vim.inputState, context);\n if (match.type == 'none') { clearInputState(cm); return false; }\n else if (match.type == 'partial') { return true; }\n\n vim.inputState.keyBuffer = '';\n var keysMatcher = /^(\\d*)(.*)$/.exec(keys);\n if (keysMatcher[1] && keysMatcher[1] != '0') {\n vim.inputState.pushRepeatDigit(keysMatcher[1]);\n }\n return match.command;\n }\n\n var command;\n if (vim.insertMode) { command = handleKeyInsertMode(); }\n else { command = handleKeyNonInsertMode(); }\n if (command === false) {\n return undefined;\n } else if (command === true) {\n // TODO: Look into using CodeMirror's multi-key handling.\n // Return no-op since we are caching the key. Counts as handled, but\n // don't want act on it just yet.\n return function() {};\n } else {\n return function() {\n return cm.operation(function() {\n cm.curOp.isVimOp = true;\n try {\n if (command.type == 'keyToKey') {\n doKeyToKey(command.toKeys);\n } else {\n commandDispatcher.processCommand(cm, vim, command);\n }\n } catch (e) {\n // clear VIM state in case it's in a bad state.\n cm.state.vim = undefined;\n maybeInitVimState(cm);\n if (!CodeMirror.Vim.suppressErrorLogging) {\n console['log'](e);\n }\n throw e;\n }\n return true;\n });\n };\n }\n },\n handleEx: function(cm, input) {\n exCommandDispatcher.processCommand(cm, input);\n },\n\n defineMotion: defineMotion,\n defineAction: defineAction,\n defineOperator: defineOperator,\n mapCommand: mapCommand,\n _mapCommand: _mapCommand,\n\n defineRegister: defineRegister,\n\n exitVisualMode: exitVisualMode,\n exitInsertMode: exitInsertMode\n };\n\n // Represents the current input state.\n function InputState() {\n this.prefixRepeat = [];\n this.motionRepeat = [];\n\n this.operator = null;\n this.operatorArgs = null;\n this.motion = null;\n this.motionArgs = null;\n this.keyBuffer = []; // For matching multi-key commands.\n this.registerName = null; // Defaults to the unnamed register.\n }\n InputState.prototype.pushRepeatDigit = function(n) {\n if (!this.operator) {\n this.prefixRepeat = this.prefixRepeat.concat(n);\n } else {\n this.motionRepeat = this.motionRepeat.concat(n);\n }\n };\n InputState.prototype.getRepeat = function() {\n var repeat = 0;\n if (this.prefixRepeat.length > 0 || this.motionRepeat.length > 0) {\n repeat = 1;\n if (this.prefixRepeat.length > 0) {\n repeat *= parseInt(this.prefixRepeat.join(''), 10);\n }\n if (this.motionRepeat.length > 0) {\n repeat *= parseInt(this.motionRepeat.join(''), 10);\n }\n }\n return repeat;\n };\n\n function clearInputState(cm, reason) {\n cm.state.vim.inputState = new InputState();\n CodeMirror.signal(cm, 'vim-command-done', reason);\n }\n\n /*\n * Register stores information about copy and paste registers. Besides\n * text, a register must store whether it is linewise (i.e., when it is\n * pasted, should it insert itself into a new line, or should the text be\n * inserted at the cursor position.)\n */\n function Register(text, linewise, blockwise) {\n this.clear();\n this.keyBuffer = [text || ''];\n this.insertModeChanges = [];\n this.searchQueries = [];\n this.linewise = !!linewise;\n this.blockwise = !!blockwise;\n }\n Register.prototype = {\n setText: function(text, linewise, blockwise) {\n this.keyBuffer = [text || ''];\n this.linewise = !!linewise;\n this.blockwise = !!blockwise;\n },\n pushText: function(text, linewise) {\n // if this register has ever been set to linewise, use linewise.\n if (linewise) {\n if (!this.linewise) {\n this.keyBuffer.push('\\n');\n }\n this.linewise = true;\n }\n this.keyBuffer.push(text);\n },\n pushInsertModeChanges: function(changes) {\n this.insertModeChanges.push(createInsertModeChanges(changes));\n },\n pushSearchQuery: function(query) {\n this.searchQueries.push(query);\n },\n clear: function() {\n this.keyBuffer = [];\n this.insertModeChanges = [];\n this.searchQueries = [];\n this.linewise = false;\n },\n toString: function() {\n return this.keyBuffer.join('');\n }\n };\n\n /**\n * Defines an external register.\n *\n * The name should be a single character that will be used to reference the register.\n * The register should support setText, pushText, clear, and toString(). See Register\n * for a reference implementation.\n */\n function defineRegister(name, register) {\n var registers = vimGlobalState.registerController.registers[name];\n if (!name || name.length != 1) {\n throw Error('Register name must be 1 character');\n }\n if (registers[name]) {\n throw Error('Register already defined ' + name);\n }\n registers[name] = register;\n validRegisters.push(name);\n }\n\n /*\n * vim registers allow you to keep many independent copy and paste buffers.\n * See http://usevim.com/2012/04/13/registers/ for an introduction.\n *\n * RegisterController keeps the state of all the registers. An initial\n * state may be passed in. The unnamed register '\"' will always be\n * overridden.\n */\n function RegisterController(registers) {\n this.registers = registers;\n this.unnamedRegister = registers['\"'] = new Register();\n registers['.'] = new Register();\n registers[':'] = new Register();\n registers['/'] = new Register();\n }\n RegisterController.prototype = {\n pushText: function(registerName, operator, text, linewise, blockwise) {\n if (linewise && text.charAt(0) == '\\n') {\n text = text.slice(1) + '\\n';\n }\n if (linewise && text.charAt(text.length - 1) !== '\\n'){\n text += '\\n';\n }\n // Lowercase and uppercase registers refer to the same register.\n // Uppercase just means append.\n var register = this.isValidRegister(registerName) ?\n this.getRegister(registerName) : null;\n // if no register/an invalid register was specified, things go to the\n // default registers\n if (!register) {\n switch (operator) {\n case 'yank':\n // The 0 register contains the text from the most recent yank.\n this.registers['0'] = new Register(text, linewise, blockwise);\n break;\n case 'delete':\n case 'change':\n if (text.indexOf('\\n') == -1) {\n // Delete less than 1 line. Update the small delete register.\n this.registers['-'] = new Register(text, linewise);\n } else {\n // Shift down the contents of the numbered registers and put the\n // deleted text into register 1.\n this.shiftNumericRegisters_();\n this.registers['1'] = new Register(text, linewise);\n }\n break;\n }\n // Make sure the unnamed register is set to what just happened\n this.unnamedRegister.setText(text, linewise, blockwise);\n return;\n }\n\n // If we've gotten to this point, we've actually specified a register\n var append = isUpperCase(registerName);\n if (append) {\n register.pushText(text, linewise);\n } else {\n register.setText(text, linewise, blockwise);\n }\n // The unnamed register always has the same value as the last used\n // register.\n this.unnamedRegister.setText(register.toString(), linewise);\n },\n // Gets the register named @name. If one of @name doesn't already exist,\n // create it. If @name is invalid, return the unnamedRegister.\n getRegister: function(name) {\n if (!this.isValidRegister(name)) {\n return this.unnamedRegister;\n }\n name = name.toLowerCase();\n if (!this.registers[name]) {\n this.registers[name] = new Register();\n }\n return this.registers[name];\n },\n isValidRegister: function(name) {\n return name && inArray(name, validRegisters);\n },\n shiftNumericRegisters_: function() {\n for (var i = 9; i >= 2; i--) {\n this.registers[i] = this.getRegister('' + (i - 1));\n }\n }\n };\n function HistoryController() {\n this.historyBuffer = [];\n this.iterator;\n this.initialPrefix = null;\n }\n HistoryController.prototype = {\n // the input argument here acts a user entered prefix for a small time\n // until we start autocompletion in which case it is the autocompleted.\n nextMatch: function (input, up) {\n var historyBuffer = this.historyBuffer;\n var dir = up ? -1 : 1;\n if (this.initialPrefix === null) this.initialPrefix = input;\n for (var i = this.iterator + dir; up ? i >= 0 : i < historyBuffer.length; i+= dir) {\n var element = historyBuffer[i];\n for (var j = 0; j <= element.length; j++) {\n if (this.initialPrefix == element.substring(0, j)) {\n this.iterator = i;\n return element;\n }\n }\n }\n // should return the user input in case we reach the end of buffer.\n if (i >= historyBuffer.length) {\n this.iterator = historyBuffer.length;\n return this.initialPrefix;\n }\n // return the last autocompleted query or exCommand as it is.\n if (i < 0 ) return input;\n },\n pushInput: function(input) {\n var index = this.historyBuffer.indexOf(input);\n if (index > -1) this.historyBuffer.splice(index, 1);\n if (input.length) this.historyBuffer.push(input);\n },\n reset: function() {\n this.initialPrefix = null;\n this.iterator = this.historyBuffer.length;\n }\n };\n var commandDispatcher = {\n matchCommand: function(keys, keyMap, inputState, context) {\n var matches = commandMatches(keys, keyMap, context, inputState);\n if (!matches.full && !matches.partial) {\n return {type: 'none'};\n } else if (!matches.full && matches.partial) {\n return {type: 'partial'};\n }\n\n var bestMatch;\n for (var i = 0; i < matches.full.length; i++) {\n var match = matches.full[i];\n if (!bestMatch) {\n bestMatch = match;\n }\n }\n if (bestMatch.keys.slice(-11) == '<character>') {\n inputState.selectedCharacter = lastChar(keys);\n }\n return {type: 'full', command: bestMatch};\n },\n processCommand: function(cm, vim, command) {\n vim.inputState.repeatOverride = command.repeatOverride;\n switch (command.type) {\n case 'motion':\n this.processMotion(cm, vim, command);\n break;\n case 'operator':\n this.processOperator(cm, vim, command);\n break;\n case 'operatorMotion':\n this.processOperatorMotion(cm, vim, command);\n break;\n case 'action':\n this.processAction(cm, vim, command);\n break;\n case 'search':\n this.processSearch(cm, vim, command);\n break;\n case 'ex':\n case 'keyToEx':\n this.processEx(cm, vim, command);\n break;\n default:\n break;\n }\n },\n processMotion: function(cm, vim, command) {\n vim.inputState.motion = command.motion;\n vim.inputState.motionArgs = copyArgs(command.motionArgs);\n this.evalInput(cm, vim);\n },\n processOperator: function(cm, vim, command) {\n var inputState = vim.inputState;\n if (inputState.operator) {\n if (inputState.operator == command.operator) {\n // Typing an operator twice like 'dd' makes the operator operate\n // linewise\n inputState.motion = 'expandToLine';\n inputState.motionArgs = { linewise: true };\n this.evalInput(cm, vim);\n return;\n } else {\n // 2 different operators in a row doesn't make sense.\n clearInputState(cm);\n }\n }\n inputState.operator = command.operator;\n inputState.operatorArgs = copyArgs(command.operatorArgs);\n if (vim.visualMode) {\n // Operating on a selection in visual mode. We don't need a motion.\n this.evalInput(cm, vim);\n }\n },\n processOperatorMotion: function(cm, vim, command) {\n var visualMode = vim.visualMode;\n var operatorMotionArgs = copyArgs(command.operatorMotionArgs);\n if (operatorMotionArgs) {\n // Operator motions may have special behavior in visual mode.\n if (visualMode && operatorMotionArgs.visualLine) {\n vim.visualLine = true;\n }\n }\n this.processOperator(cm, vim, command);\n if (!visualMode) {\n this.processMotion(cm, vim, command);\n }\n },\n processAction: function(cm, vim, command) {\n var inputState = vim.inputState;\n var repeat = inputState.getRepeat();\n var repeatIsExplicit = !!repeat;\n var actionArgs = copyArgs(command.actionArgs) || {};\n if (inputState.selectedCharacter) {\n actionArgs.selectedCharacter = inputState.selectedCharacter;\n }\n // Actions may or may not have motions and operators. Do these first.\n if (command.operator) {\n this.processOperator(cm, vim, command);\n }\n if (command.motion) {\n this.processMotion(cm, vim, command);\n }\n if (command.motion || command.operator) {\n this.evalInput(cm, vim);\n }\n actionArgs.repeat = repeat || 1;\n actionArgs.repeatIsExplicit = repeatIsExplicit;\n actionArgs.registerName = inputState.registerName;\n clearInputState(cm);\n vim.lastMotion = null;\n if (command.isEdit) {\n this.recordLastEdit(vim, inputState, command);\n }\n actions[command.action](cm, actionArgs, vim);\n },\n processSearch: function(cm, vim, command) {\n if (!cm.getSearchCursor) {\n // Search depends on SearchCursor.\n return;\n }\n var forward = command.searchArgs.forward;\n var wholeWordOnly = command.searchArgs.wholeWordOnly;\n getSearchState(cm).setReversed(!forward);\n var promptPrefix = (forward) ? '/' : '?';\n var originalQuery = getSearchState(cm).getQuery();\n var originalScrollPos = cm.getScrollInfo();\n function handleQuery(query, ignoreCase, smartCase) {\n vimGlobalState.searchHistoryController.pushInput(query);\n vimGlobalState.searchHistoryController.reset();\n try {\n updateSearchQuery(cm, query, ignoreCase, smartCase);\n } catch (e) {\n showConfirm(cm, 'Invalid regex: ' + query);\n clearInputState(cm);\n return;\n }\n commandDispatcher.processMotion(cm, vim, {\n type: 'motion',\n motion: 'findNext',\n motionArgs: { forward: true, toJumplist: command.searchArgs.toJumplist }\n });\n }\n function onPromptClose(query) {\n cm.scrollTo(originalScrollPos.left, originalScrollPos.top);\n handleQuery(query, true /** ignoreCase */, true /** smartCase */);\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.isRecording) {\n logSearchQuery(macroModeState, query);\n }\n }\n function onPromptKeyUp(e, query, close) {\n var keyName = CodeMirror.keyName(e), up;\n if (keyName == 'Up' || keyName == 'Down') {\n up = keyName == 'Up' ? true : false;\n query = vimGlobalState.searchHistoryController.nextMatch(query, up) || '';\n close(query);\n } else {\n if ( keyName != 'Left' && keyName != 'Right' && keyName != 'Ctrl' && keyName != 'Alt' && keyName != 'Shift')\n vimGlobalState.searchHistoryController.reset();\n }\n var parsedQuery;\n try {\n parsedQuery = updateSearchQuery(cm, query,\n true /** ignoreCase */, true /** smartCase */);\n } catch (e) {\n // Swallow bad regexes for incremental search.\n }\n if (parsedQuery) {\n cm.scrollIntoView(findNext(cm, !forward, parsedQuery), 30);\n } else {\n clearSearchHighlight(cm);\n cm.scrollTo(originalScrollPos.left, originalScrollPos.top);\n }\n }\n function onPromptKeyDown(e, query, close) {\n var keyName = CodeMirror.keyName(e);\n if (keyName == 'Esc' || keyName == 'Ctrl-C' || keyName == 'Ctrl-[' ||\n (keyName == 'Backspace' && query == '')) {\n vimGlobalState.searchHistoryController.pushInput(query);\n vimGlobalState.searchHistoryController.reset();\n updateSearchQuery(cm, originalQuery);\n clearSearchHighlight(cm);\n cm.scrollTo(originalScrollPos.left, originalScrollPos.top);\n CodeMirror.e_stop(e);\n clearInputState(cm);\n close();\n cm.focus();\n } else if (keyName == 'Ctrl-U') {\n // Ctrl-U clears input.\n CodeMirror.e_stop(e);\n close('');\n }\n }\n switch (command.searchArgs.querySrc) {\n case 'prompt':\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.isPlaying) {\n var query = macroModeState.replaySearchQueries.shift();\n handleQuery(query, true /** ignoreCase */, false /** smartCase */);\n } else {\n showPrompt(cm, {\n onClose: onPromptClose,\n prefix: promptPrefix,\n desc: searchPromptDesc,\n onKeyUp: onPromptKeyUp,\n onKeyDown: onPromptKeyDown\n });\n }\n break;\n case 'wordUnderCursor':\n var word = expandWordUnderCursor(cm, false /** inclusive */,\n true /** forward */, false /** bigWord */,\n true /** noSymbol */);\n var isKeyword = true;\n if (!word) {\n word = expandWordUnderCursor(cm, false /** inclusive */,\n true /** forward */, false /** bigWord */,\n false /** noSymbol */);\n isKeyword = false;\n }\n if (!word) {\n return;\n }\n var query = cm.getLine(word.start.line).substring(word.start.ch,\n word.end.ch);\n if (isKeyword && wholeWordOnly) {\n query = '\\\\b' + query + '\\\\b';\n } else {\n query = escapeRegex(query);\n }\n\n // cachedCursor is used to save the old position of the cursor\n // when * or # causes vim to seek for the nearest word and shift\n // the cursor before entering the motion.\n vimGlobalState.jumpList.cachedCursor = cm.getCursor();\n cm.setCursor(word.start);\n\n handleQuery(query, true /** ignoreCase */, false /** smartCase */);\n break;\n }\n },\n processEx: function(cm, vim, command) {\n function onPromptClose(input) {\n // Give the prompt some time to close so that if processCommand shows\n // an error, the elements don't overlap.\n vimGlobalState.exCommandHistoryController.pushInput(input);\n vimGlobalState.exCommandHistoryController.reset();\n exCommandDispatcher.processCommand(cm, input);\n }\n function onPromptKeyDown(e, input, close) {\n var keyName = CodeMirror.keyName(e), up;\n if (keyName == 'Esc' || keyName == 'Ctrl-C' || keyName == 'Ctrl-[' ||\n (keyName == 'Backspace' && input == '')) {\n vimGlobalState.exCommandHistoryController.pushInput(input);\n vimGlobalState.exCommandHistoryController.reset();\n CodeMirror.e_stop(e);\n clearInputState(cm);\n close();\n cm.focus();\n }\n if (keyName == 'Up' || keyName == 'Down') {\n up = keyName == 'Up' ? true : false;\n input = vimGlobalState.exCommandHistoryController.nextMatch(input, up) || '';\n close(input);\n } else if (keyName == 'Ctrl-U') {\n // Ctrl-U clears input.\n CodeMirror.e_stop(e);\n close('');\n } else {\n if ( keyName != 'Left' && keyName != 'Right' && keyName != 'Ctrl' && keyName != 'Alt' && keyName != 'Shift')\n vimGlobalState.exCommandHistoryController.reset();\n }\n }\n if (command.type == 'keyToEx') {\n // Handle user defined Ex to Ex mappings\n exCommandDispatcher.processCommand(cm, command.exArgs.input);\n } else {\n if (vim.visualMode) {\n showPrompt(cm, { onClose: onPromptClose, prefix: ':', value: '\\'<,\\'>',\n onKeyDown: onPromptKeyDown});\n } else {\n showPrompt(cm, { onClose: onPromptClose, prefix: ':',\n onKeyDown: onPromptKeyDown});\n }\n }\n },\n evalInput: function(cm, vim) {\n // If the motion comand is set, execute both the operator and motion.\n // Otherwise return.\n var inputState = vim.inputState;\n var motion = inputState.motion;\n var motionArgs = inputState.motionArgs || {};\n var operator = inputState.operator;\n var operatorArgs = inputState.operatorArgs || {};\n var registerName = inputState.registerName;\n var sel = vim.sel;\n // TODO: Make sure cm and vim selections are identical outside visual mode.\n var origHead = copyCursor(vim.visualMode ? clipCursorToContent(cm, sel.head): cm.getCursor('head'));\n var origAnchor = copyCursor(vim.visualMode ? clipCursorToContent(cm, sel.anchor) : cm.getCursor('anchor'));\n var oldHead = copyCursor(origHead);\n var oldAnchor = copyCursor(origAnchor);\n var newHead, newAnchor;\n var repeat;\n if (operator) {\n this.recordLastEdit(vim, inputState);\n }\n if (inputState.repeatOverride !== undefined) {\n // If repeatOverride is specified, that takes precedence over the\n // input state's repeat. Used by Ex mode and can be user defined.\n repeat = inputState.repeatOverride;\n } else {\n repeat = inputState.getRepeat();\n }\n if (repeat > 0 && motionArgs.explicitRepeat) {\n motionArgs.repeatIsExplicit = true;\n } else if (motionArgs.noRepeat ||\n (!motionArgs.explicitRepeat && repeat === 0)) {\n repeat = 1;\n motionArgs.repeatIsExplicit = false;\n }\n if (inputState.selectedCharacter) {\n // If there is a character input, stick it in all of the arg arrays.\n motionArgs.selectedCharacter = operatorArgs.selectedCharacter =\n inputState.selectedCharacter;\n }\n motionArgs.repeat = repeat;\n clearInputState(cm);\n if (motion) {\n var motionResult = motions[motion](cm, origHead, motionArgs, vim);\n vim.lastMotion = motions[motion];\n if (!motionResult) {\n return;\n }\n if (motionArgs.toJumplist) {\n var jumpList = vimGlobalState.jumpList;\n // if the current motion is # or *, use cachedCursor\n var cachedCursor = jumpList.cachedCursor;\n if (cachedCursor) {\n recordJumpPosition(cm, cachedCursor, motionResult);\n delete jumpList.cachedCursor;\n } else {\n recordJumpPosition(cm, origHead, motionResult);\n }\n }\n if (motionResult instanceof Array) {\n newAnchor = motionResult[0];\n newHead = motionResult[1];\n } else {\n newHead = motionResult;\n }\n // TODO: Handle null returns from motion commands better.\n if (!newHead) {\n newHead = copyCursor(origHead);\n }\n if (vim.visualMode) {\n if (!(vim.visualBlock && newHead.ch === Infinity)) {\n newHead = clipCursorToContent(cm, newHead, vim.visualBlock);\n }\n if (newAnchor) {\n newAnchor = clipCursorToContent(cm, newAnchor, true);\n }\n newAnchor = newAnchor || oldAnchor;\n sel.anchor = newAnchor;\n sel.head = newHead;\n updateCmSelection(cm);\n updateMark(cm, vim, '<',\n cursorIsBefore(newAnchor, newHead) ? newAnchor\n : newHead);\n updateMark(cm, vim, '>',\n cursorIsBefore(newAnchor, newHead) ? newHead\n : newAnchor);\n } else if (!operator) {\n newHead = clipCursorToContent(cm, newHead);\n cm.setCursor(newHead.line, newHead.ch);\n }\n }\n if (operator) {\n if (operatorArgs.lastSel) {\n // Replaying a visual mode operation\n newAnchor = oldAnchor;\n var lastSel = operatorArgs.lastSel;\n var lineOffset = Math.abs(lastSel.head.line - lastSel.anchor.line);\n var chOffset = Math.abs(lastSel.head.ch - lastSel.anchor.ch);\n if (lastSel.visualLine) {\n // Linewise Visual mode: The same number of lines.\n newHead = Pos(oldAnchor.line + lineOffset, oldAnchor.ch);\n } else if (lastSel.visualBlock) {\n // Blockwise Visual mode: The same number of lines and columns.\n newHead = Pos(oldAnchor.line + lineOffset, oldAnchor.ch + chOffset);\n } else if (lastSel.head.line == lastSel.anchor.line) {\n // Normal Visual mode within one line: The same number of characters.\n newHead = Pos(oldAnchor.line, oldAnchor.ch + chOffset);\n } else {\n // Normal Visual mode with several lines: The same number of lines, in the\n // last line the same number of characters as in the last line the last time.\n newHead = Pos(oldAnchor.line + lineOffset, oldAnchor.ch);\n }\n vim.visualMode = true;\n vim.visualLine = lastSel.visualLine;\n vim.visualBlock = lastSel.visualBlock;\n sel = vim.sel = {\n anchor: newAnchor,\n head: newHead\n };\n updateCmSelection(cm);\n } else if (vim.visualMode) {\n operatorArgs.lastSel = {\n anchor: copyCursor(sel.anchor),\n head: copyCursor(sel.head),\n visualBlock: vim.visualBlock,\n visualLine: vim.visualLine\n };\n }\n var curStart, curEnd, linewise, mode;\n var cmSel;\n if (vim.visualMode) {\n // Init visual op\n curStart = cursorMin(sel.head, sel.anchor);\n curEnd = cursorMax(sel.head, sel.anchor);\n linewise = vim.visualLine || operatorArgs.linewise;\n mode = vim.visualBlock ? 'block' :\n linewise ? 'line' :\n 'char';\n cmSel = makeCmSelection(cm, {\n anchor: curStart,\n head: curEnd\n }, mode);\n if (linewise) {\n var ranges = cmSel.ranges;\n if (mode == 'block') {\n // Linewise operators in visual block mode extend to end of line\n for (var i = 0; i < ranges.length; i++) {\n ranges[i].head.ch = lineLength(cm, ranges[i].head.line);\n }\n } else if (mode == 'line') {\n ranges[0].head = Pos(ranges[0].head.line + 1, 0);\n }\n }\n } else {\n // Init motion op\n curStart = copyCursor(newAnchor || oldAnchor);\n curEnd = copyCursor(newHead || oldHead);\n if (cursorIsBefore(curEnd, curStart)) {\n var tmp = curStart;\n curStart = curEnd;\n curEnd = tmp;\n }\n linewise = motionArgs.linewise || operatorArgs.linewise;\n if (linewise) {\n // Expand selection to entire line.\n expandSelectionToLine(cm, curStart, curEnd);\n } else if (motionArgs.forward) {\n // Clip to trailing newlines only if the motion goes forward.\n clipToLine(cm, curStart, curEnd);\n }\n mode = 'char';\n var exclusive = !motionArgs.inclusive || linewise;\n cmSel = makeCmSelection(cm, {\n anchor: curStart,\n head: curEnd\n }, mode, exclusive);\n }\n cm.setSelections(cmSel.ranges, cmSel.primary);\n vim.lastMotion = null;\n operatorArgs.repeat = repeat; // For indent in visual mode.\n operatorArgs.registerName = registerName;\n // Keep track of linewise as it affects how paste and change behave.\n operatorArgs.linewise = linewise;\n var operatorMoveTo = operators[operator](\n cm, operatorArgs, cmSel.ranges, oldAnchor, newHead);\n if (vim.visualMode) {\n exitVisualMode(cm, operatorMoveTo != null);\n }\n if (operatorMoveTo) {\n cm.setCursor(operatorMoveTo);\n }\n }\n },\n recordLastEdit: function(vim, inputState, actionCommand) {\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.isPlaying) { return; }\n vim.lastEditInputState = inputState;\n vim.lastEditActionCommand = actionCommand;\n macroModeState.lastInsertModeChanges.changes = [];\n macroModeState.lastInsertModeChanges.expectCursorActivityForChange = false;\n }\n };\n\n /**\n * typedef {Object{line:number,ch:number}} Cursor An object containing the\n * position of the cursor.\n */\n // All of the functions below return Cursor objects.\n var motions = {\n moveToTopLine: function(cm, _head, motionArgs) {\n var line = getUserVisibleLines(cm).top + motionArgs.repeat -1;\n return Pos(line, findFirstNonWhiteSpaceCharacter(cm.getLine(line)));\n },\n moveToMiddleLine: function(cm) {\n var range = getUserVisibleLines(cm);\n var line = Math.floor((range.top + range.bottom) * 0.5);\n return Pos(line, findFirstNonWhiteSpaceCharacter(cm.getLine(line)));\n },\n moveToBottomLine: function(cm, _head, motionArgs) {\n var line = getUserVisibleLines(cm).bottom - motionArgs.repeat +1;\n return Pos(line, findFirstNonWhiteSpaceCharacter(cm.getLine(line)));\n },\n expandToLine: function(_cm, head, motionArgs) {\n // Expands forward to end of line, and then to next line if repeat is\n // >1. Does not handle backward motion!\n var cur = head;\n return Pos(cur.line + motionArgs.repeat - 1, Infinity);\n },\n findNext: function(cm, _head, motionArgs) {\n var state = getSearchState(cm);\n var query = state.getQuery();\n if (!query) {\n return;\n }\n var prev = !motionArgs.forward;\n // If search is initiated with ? instead of /, negate direction.\n prev = (state.isReversed()) ? !prev : prev;\n highlightSearchMatches(cm, query);\n return findNext(cm, prev/** prev */, query, motionArgs.repeat);\n },\n goToMark: function(cm, _head, motionArgs, vim) {\n var mark = vim.marks[motionArgs.selectedCharacter];\n if (mark) {\n var pos = mark.find();\n return motionArgs.linewise ? { line: pos.line, ch: findFirstNonWhiteSpaceCharacter(cm.getLine(pos.line)) } : pos;\n }\n return null;\n },\n moveToOtherHighlightedEnd: function(cm, _head, motionArgs, vim) {\n if (vim.visualBlock && motionArgs.sameLine) {\n var sel = vim.sel;\n return [\n clipCursorToContent(cm, Pos(sel.anchor.line, sel.head.ch)),\n clipCursorToContent(cm, Pos(sel.head.line, sel.anchor.ch))\n ];\n } else {\n return ([vim.sel.head, vim.sel.anchor]);\n }\n },\n jumpToMark: function(cm, head, motionArgs, vim) {\n var best = head;\n for (var i = 0; i < motionArgs.repeat; i++) {\n var cursor = best;\n for (var key in vim.marks) {\n if (!isLowerCase(key)) {\n continue;\n }\n var mark = vim.marks[key].find();\n var isWrongDirection = (motionArgs.forward) ?\n cursorIsBefore(mark, cursor) : cursorIsBefore(cursor, mark);\n\n if (isWrongDirection) {\n continue;\n }\n if (motionArgs.linewise && (mark.line == cursor.line)) {\n continue;\n }\n\n var equal = cursorEqual(cursor, best);\n var between = (motionArgs.forward) ?\n cursorIsBetween(cursor, mark, best) :\n cursorIsBetween(best, mark, cursor);\n\n if (equal || between) {\n best = mark;\n }\n }\n }\n\n if (motionArgs.linewise) {\n // Vim places the cursor on the first non-whitespace character of\n // the line if there is one, else it places the cursor at the end\n // of the line, regardless of whether a mark was found.\n best = Pos(best.line, findFirstNonWhiteSpaceCharacter(cm.getLine(best.line)));\n }\n return best;\n },\n moveByCharacters: function(_cm, head, motionArgs) {\n var cur = head;\n var repeat = motionArgs.repeat;\n var ch = motionArgs.forward ? cur.ch + repeat : cur.ch - repeat;\n return Pos(cur.line, ch);\n },\n moveByLines: function(cm, head, motionArgs, vim) {\n var cur = head;\n var endCh = cur.ch;\n // Depending what our last motion was, we may want to do different\n // things. If our last motion was moving vertically, we want to\n // preserve the HPos from our last horizontal move. If our last motion\n // was going to the end of a line, moving vertically we should go to\n // the end of the line, etc.\n switch (vim.lastMotion) {\n case this.moveByLines:\n case this.moveByDisplayLines:\n case this.moveByScroll:\n case this.moveToColumn:\n case this.moveToEol:\n endCh = vim.lastHPos;\n break;\n default:\n vim.lastHPos = endCh;\n }\n var repeat = motionArgs.repeat+(motionArgs.repeatOffset||0);\n var line = motionArgs.forward ? cur.line + repeat : cur.line - repeat;\n var first = cm.firstLine();\n var last = cm.lastLine();\n // Vim go to line begin or line end when cursor at first/last line and\n // move to previous/next line is triggered.\n if (line < first && cur.line == first){\n return this.moveToStartOfLine(cm, head, motionArgs, vim);\n }else if (line > last && cur.line == last){\n return this.moveToEol(cm, head, motionArgs, vim);\n }\n if (motionArgs.toFirstChar){\n endCh=findFirstNonWhiteSpaceCharacter(cm.getLine(line));\n vim.lastHPos = endCh;\n }\n vim.lastHSPos = cm.charCoords(Pos(line, endCh),'div').left;\n return Pos(line, endCh);\n },\n moveByDisplayLines: function(cm, head, motionArgs, vim) {\n var cur = head;\n switch (vim.lastMotion) {\n case this.moveByDisplayLines:\n case this.moveByScroll:\n case this.moveByLines:\n case this.moveToColumn:\n case this.moveToEol:\n break;\n default:\n vim.lastHSPos = cm.charCoords(cur,'div').left;\n }\n var repeat = motionArgs.repeat;\n var res=cm.findPosV(cur,(motionArgs.forward ? repeat : -repeat),'line',vim.lastHSPos);\n if (res.hitSide) {\n if (motionArgs.forward) {\n var lastCharCoords = cm.charCoords(res, 'div');\n var goalCoords = { top: lastCharCoords.top + 8, left: vim.lastHSPos };\n var res = cm.coordsChar(goalCoords, 'div');\n } else {\n var resCoords = cm.charCoords(Pos(cm.firstLine(), 0), 'div');\n resCoords.left = vim.lastHSPos;\n res = cm.coordsChar(resCoords, 'div');\n }\n }\n vim.lastHPos = res.ch;\n return res;\n },\n moveByPage: function(cm, head, motionArgs) {\n // CodeMirror only exposes functions that move the cursor page down, so\n // doing this bad hack to move the cursor and move it back. evalInput\n // will move the cursor to where it should be in the end.\n var curStart = head;\n var repeat = motionArgs.repeat;\n return cm.findPosV(curStart, (motionArgs.forward ? repeat : -repeat), 'page');\n },\n moveByParagraph: function(cm, head, motionArgs) {\n var dir = motionArgs.forward ? 1 : -1;\n return findParagraph(cm, head, motionArgs.repeat, dir);\n },\n moveByScroll: function(cm, head, motionArgs, vim) {\n var scrollbox = cm.getScrollInfo();\n var curEnd = null;\n var repeat = motionArgs.repeat;\n if (!repeat) {\n repeat = scrollbox.clientHeight / (2 * cm.defaultTextHeight());\n }\n var orig = cm.charCoords(head, 'local');\n motionArgs.repeat = repeat;\n var curEnd = motions.moveByDisplayLines(cm, head, motionArgs, vim);\n if (!curEnd) {\n return null;\n }\n var dest = cm.charCoords(curEnd, 'local');\n cm.scrollTo(null, scrollbox.top + dest.top - orig.top);\n return curEnd;\n },\n moveByWords: function(cm, head, motionArgs) {\n return moveToWord(cm, head, motionArgs.repeat, !!motionArgs.forward,\n !!motionArgs.wordEnd, !!motionArgs.bigWord);\n },\n moveTillCharacter: function(cm, _head, motionArgs) {\n var repeat = motionArgs.repeat;\n var curEnd = moveToCharacter(cm, repeat, motionArgs.forward,\n motionArgs.selectedCharacter);\n var increment = motionArgs.forward ? -1 : 1;\n recordLastCharacterSearch(increment, motionArgs);\n if (!curEnd) return null;\n curEnd.ch += increment;\n return curEnd;\n },\n moveToCharacter: function(cm, head, motionArgs) {\n var repeat = motionArgs.repeat;\n recordLastCharacterSearch(0, motionArgs);\n return moveToCharacter(cm, repeat, motionArgs.forward,\n motionArgs.selectedCharacter) || head;\n },\n moveToSymbol: function(cm, head, motionArgs) {\n var repeat = motionArgs.repeat;\n return findSymbol(cm, repeat, motionArgs.forward,\n motionArgs.selectedCharacter) || head;\n },\n moveToColumn: function(cm, head, motionArgs, vim) {\n var repeat = motionArgs.repeat;\n // repeat is equivalent to which column we want to move to!\n vim.lastHPos = repeat - 1;\n vim.lastHSPos = cm.charCoords(head,'div').left;\n return moveToColumn(cm, repeat);\n },\n moveToEol: function(cm, head, motionArgs, vim) {\n var cur = head;\n vim.lastHPos = Infinity;\n var retval= Pos(cur.line + motionArgs.repeat - 1, Infinity);\n var end=cm.clipPos(retval);\n end.ch--;\n vim.lastHSPos = cm.charCoords(end,'div').left;\n return retval;\n },\n moveToFirstNonWhiteSpaceCharacter: function(cm, head) {\n // Go to the start of the line where the text begins, or the end for\n // whitespace-only lines\n var cursor = head;\n return Pos(cursor.line,\n findFirstNonWhiteSpaceCharacter(cm.getLine(cursor.line)));\n },\n moveToMatchedSymbol: function(cm, head) {\n var cursor = head;\n var line = cursor.line;\n var ch = cursor.ch;\n var lineText = cm.getLine(line);\n var symbol;\n do {\n symbol = lineText.charAt(ch++);\n if (symbol && isMatchableSymbol(symbol)) {\n var style = cm.getTokenTypeAt(Pos(line, ch));\n if (style !== \"string\" && style !== \"comment\") {\n break;\n }\n }\n } while (symbol);\n if (symbol) {\n var matched = cm.findMatchingBracket(Pos(line, ch));\n return matched.to;\n } else {\n return cursor;\n }\n },\n moveToStartOfLine: function(_cm, head) {\n return Pos(head.line, 0);\n },\n moveToLineOrEdgeOfDocument: function(cm, _head, motionArgs) {\n var lineNum = motionArgs.forward ? cm.lastLine() : cm.firstLine();\n if (motionArgs.repeatIsExplicit) {\n lineNum = motionArgs.repeat - cm.getOption('firstLineNumber');\n }\n return Pos(lineNum,\n findFirstNonWhiteSpaceCharacter(cm.getLine(lineNum)));\n },\n textObjectManipulation: function(cm, head, motionArgs, vim) {\n // TODO: lots of possible exceptions that can be thrown here. Try da(\n // outside of a () block.\n\n // TODO: adding <> >< to this map doesn't work, presumably because\n // they're operators\n var mirroredPairs = {'(': ')', ')': '(',\n '{': '}', '}': '{',\n '[': ']', ']': '['};\n var selfPaired = {'\\'': true, '\"': true};\n\n var character = motionArgs.selectedCharacter;\n // 'b' refers to '()' block.\n // 'B' refers to '{}' block.\n if (character == 'b') {\n character = '(';\n } else if (character == 'B') {\n character = '{';\n }\n\n // Inclusive is the difference between a and i\n // TODO: Instead of using the additional text object map to perform text\n // object operations, merge the map into the defaultKeyMap and use\n // motionArgs to define behavior. Define separate entries for 'aw',\n // 'iw', 'a[', 'i[', etc.\n var inclusive = !motionArgs.textObjectInner;\n\n var tmp;\n if (mirroredPairs[character]) {\n tmp = selectCompanionObject(cm, head, character, inclusive);\n } else if (selfPaired[character]) {\n tmp = findBeginningAndEnd(cm, head, character, inclusive);\n } else if (character === 'W') {\n tmp = expandWordUnderCursor(cm, inclusive, true /** forward */,\n true /** bigWord */);\n } else if (character === 'w') {\n tmp = expandWordUnderCursor(cm, inclusive, true /** forward */,\n false /** bigWord */);\n } else if (character === 'p') {\n tmp = findParagraph(cm, head, motionArgs.repeat, 0, inclusive);\n motionArgs.linewise = true;\n if (vim.visualMode) {\n if (!vim.visualLine) { vim.visualLine = true; }\n } else {\n var operatorArgs = vim.inputState.operatorArgs;\n if (operatorArgs) { operatorArgs.linewise = true; }\n tmp.end.line--;\n }\n } else {\n // No text object defined for this, don't move.\n return null;\n }\n\n if (!cm.state.vim.visualMode) {\n return [tmp.start, tmp.end];\n } else {\n return expandSelection(cm, tmp.start, tmp.end);\n }\n },\n\n repeatLastCharacterSearch: function(cm, head, motionArgs) {\n var lastSearch = vimGlobalState.lastChararacterSearch;\n var repeat = motionArgs.repeat;\n var forward = motionArgs.forward === lastSearch.forward;\n var increment = (lastSearch.increment ? 1 : 0) * (forward ? -1 : 1);\n cm.moveH(-increment, 'char');\n motionArgs.inclusive = forward ? true : false;\n var curEnd = moveToCharacter(cm, repeat, forward, lastSearch.selectedCharacter);\n if (!curEnd) {\n cm.moveH(increment, 'char');\n return head;\n }\n curEnd.ch += increment;\n return curEnd;\n }\n };\n\n function defineMotion(name, fn) {\n motions[name] = fn;\n }\n\n function fillArray(val, times) {\n var arr = [];\n for (var i = 0; i < times; i++) {\n arr.push(val);\n }\n return arr;\n }\n /**\n * An operator acts on a text selection. It receives the list of selections\n * as input. The corresponding CodeMirror selection is guaranteed to\n * match the input selection.\n */\n var operators = {\n change: function(cm, args, ranges) {\n var finalHead, text;\n var vim = cm.state.vim;\n vimGlobalState.macroModeState.lastInsertModeChanges.inVisualBlock = vim.visualBlock;\n if (!vim.visualMode) {\n var anchor = ranges[0].anchor,\n head = ranges[0].head;\n text = cm.getRange(anchor, head);\n var lastState = vim.lastEditInputState || {};\n if (lastState.motion == \"moveByWords\" && !isWhiteSpaceString(text)) {\n // Exclude trailing whitespace if the range is not all whitespace.\n var match = (/\\s+$/).exec(text);\n if (match && lastState.motionArgs && lastState.motionArgs.forward) {\n head = offsetCursor(head, 0, - match[0].length);\n text = text.slice(0, - match[0].length);\n }\n }\n var prevLineEnd = new Pos(anchor.line - 1, Number.MAX_VALUE);\n var wasLastLine = cm.firstLine() == cm.lastLine();\n if (head.line > cm.lastLine() && args.linewise && !wasLastLine) {\n cm.replaceRange('', prevLineEnd, head);\n } else {\n cm.replaceRange('', anchor, head);\n }\n if (args.linewise) {\n // Push the next line back down, if there is a next line.\n if (!wasLastLine) {\n cm.setCursor(prevLineEnd);\n CodeMirror.commands.newlineAndIndent(cm);\n }\n // make sure cursor ends up at the end of the line.\n anchor.ch = Number.MAX_VALUE;\n }\n finalHead = anchor;\n } else {\n text = cm.getSelection();\n var replacement = fillArray('', ranges.length);\n cm.replaceSelections(replacement);\n finalHead = cursorMin(ranges[0].head, ranges[0].anchor);\n }\n vimGlobalState.registerController.pushText(\n args.registerName, 'change', text,\n args.linewise, ranges.length > 1);\n actions.enterInsertMode(cm, {head: finalHead}, cm.state.vim);\n },\n // delete is a javascript keyword.\n 'delete': function(cm, args, ranges) {\n var finalHead, text;\n var vim = cm.state.vim;\n if (!vim.visualBlock) {\n var anchor = ranges[0].anchor,\n head = ranges[0].head;\n if (args.linewise &&\n head.line != cm.firstLine() &&\n anchor.line == cm.lastLine() &&\n anchor.line == head.line - 1) {\n // Special case for dd on last line (and first line).\n if (anchor.line == cm.firstLine()) {\n anchor.ch = 0;\n } else {\n anchor = Pos(anchor.line - 1, lineLength(cm, anchor.line - 1));\n }\n }\n text = cm.getRange(anchor, head);\n cm.replaceRange('', anchor, head);\n finalHead = anchor;\n if (args.linewise) {\n finalHead = motions.moveToFirstNonWhiteSpaceCharacter(cm, anchor);\n }\n } else {\n text = cm.getSelection();\n var replacement = fillArray('', ranges.length);\n cm.replaceSelections(replacement);\n finalHead = ranges[0].anchor;\n }\n vimGlobalState.registerController.pushText(\n args.registerName, 'delete', text,\n args.linewise, vim.visualBlock);\n return clipCursorToContent(cm, finalHead);\n },\n indent: function(cm, args, ranges) {\n var vim = cm.state.vim;\n var startLine = ranges[0].anchor.line;\n var endLine = vim.visualBlock ?\n ranges[ranges.length - 1].anchor.line :\n ranges[0].head.line;\n // In visual mode, n> shifts the selection right n times, instead of\n // shifting n lines right once.\n var repeat = (vim.visualMode) ? args.repeat : 1;\n if (args.linewise) {\n // The only way to delete a newline is to delete until the start of\n // the next line, so in linewise mode evalInput will include the next\n // line. We don't want this in indent, so we go back a line.\n endLine--;\n }\n for (var i = startLine; i <= endLine; i++) {\n for (var j = 0; j < repeat; j++) {\n cm.indentLine(i, args.indentRight);\n }\n }\n return motions.moveToFirstNonWhiteSpaceCharacter(cm, ranges[0].anchor);\n },\n changeCase: function(cm, args, ranges, oldAnchor, newHead) {\n var selections = cm.getSelections();\n var swapped = [];\n var toLower = args.toLower;\n for (var j = 0; j < selections.length; j++) {\n var toSwap = selections[j];\n var text = '';\n if (toLower === true) {\n text = toSwap.toLowerCase();\n } else if (toLower === false) {\n text = toSwap.toUpperCase();\n } else {\n for (var i = 0; i < toSwap.length; i++) {\n var character = toSwap.charAt(i);\n text += isUpperCase(character) ? character.toLowerCase() :\n character.toUpperCase();\n }\n }\n swapped.push(text);\n }\n cm.replaceSelections(swapped);\n if (args.shouldMoveCursor){\n return newHead;\n } else if (!cm.state.vim.visualMode && args.linewise && ranges[0].anchor.line + 1 == ranges[0].head.line) {\n return motions.moveToFirstNonWhiteSpaceCharacter(cm, oldAnchor);\n } else if (args.linewise){\n return oldAnchor;\n } else {\n return cursorMin(ranges[0].anchor, ranges[0].head);\n }\n },\n yank: function(cm, args, ranges, oldAnchor) {\n var vim = cm.state.vim;\n var text = cm.getSelection();\n var endPos = vim.visualMode\n ? cursorMin(vim.sel.anchor, vim.sel.head, ranges[0].head, ranges[0].anchor)\n : oldAnchor;\n vimGlobalState.registerController.pushText(\n args.registerName, 'yank',\n text, args.linewise, vim.visualBlock);\n return endPos;\n }\n };\n\n function defineOperator(name, fn) {\n operators[name] = fn;\n }\n\n var actions = {\n jumpListWalk: function(cm, actionArgs, vim) {\n if (vim.visualMode) {\n return;\n }\n var repeat = actionArgs.repeat;\n var forward = actionArgs.forward;\n var jumpList = vimGlobalState.jumpList;\n\n var mark = jumpList.move(cm, forward ? repeat : -repeat);\n var markPos = mark ? mark.find() : undefined;\n markPos = markPos ? markPos : cm.getCursor();\n cm.setCursor(markPos);\n },\n scroll: function(cm, actionArgs, vim) {\n if (vim.visualMode) {\n return;\n }\n var repeat = actionArgs.repeat || 1;\n var lineHeight = cm.defaultTextHeight();\n var top = cm.getScrollInfo().top;\n var delta = lineHeight * repeat;\n var newPos = actionArgs.forward ? top + delta : top - delta;\n var cursor = copyCursor(cm.getCursor());\n var cursorCoords = cm.charCoords(cursor, 'local');\n if (actionArgs.forward) {\n if (newPos > cursorCoords.top) {\n cursor.line += (newPos - cursorCoords.top) / lineHeight;\n cursor.line = Math.ceil(cursor.line);\n cm.setCursor(cursor);\n cursorCoords = cm.charCoords(cursor, 'local');\n cm.scrollTo(null, cursorCoords.top);\n } else {\n // Cursor stays within bounds. Just reposition the scroll window.\n cm.scrollTo(null, newPos);\n }\n } else {\n var newBottom = newPos + cm.getScrollInfo().clientHeight;\n if (newBottom < cursorCoords.bottom) {\n cursor.line -= (cursorCoords.bottom - newBottom) / lineHeight;\n cursor.line = Math.floor(cursor.line);\n cm.setCursor(cursor);\n cursorCoords = cm.charCoords(cursor, 'local');\n cm.scrollTo(\n null, cursorCoords.bottom - cm.getScrollInfo().clientHeight);\n } else {\n // Cursor stays within bounds. Just reposition the scroll window.\n cm.scrollTo(null, newPos);\n }\n }\n },\n scrollToCursor: function(cm, actionArgs) {\n var lineNum = cm.getCursor().line;\n var charCoords = cm.charCoords(Pos(lineNum, 0), 'local');\n var height = cm.getScrollInfo().clientHeight;\n var y = charCoords.top;\n var lineHeight = charCoords.bottom - y;\n switch (actionArgs.position) {\n case 'center': y = y - (height / 2) + lineHeight;\n break;\n case 'bottom': y = y - height + lineHeight;\n break;\n }\n cm.scrollTo(null, y);\n },\n replayMacro: function(cm, actionArgs, vim) {\n var registerName = actionArgs.selectedCharacter;\n var repeat = actionArgs.repeat;\n var macroModeState = vimGlobalState.macroModeState;\n if (registerName == '@') {\n registerName = macroModeState.latestRegister;\n }\n while(repeat--){\n executeMacroRegister(cm, vim, macroModeState, registerName);\n }\n },\n enterMacroRecordMode: function(cm, actionArgs) {\n var macroModeState = vimGlobalState.macroModeState;\n var registerName = actionArgs.selectedCharacter;\n macroModeState.enterMacroRecordMode(cm, registerName);\n },\n enterInsertMode: function(cm, actionArgs, vim) {\n if (cm.getOption('readOnly')) { return; }\n vim.insertMode = true;\n vim.insertModeRepeat = actionArgs && actionArgs.repeat || 1;\n var insertAt = (actionArgs) ? actionArgs.insertAt : null;\n var sel = vim.sel;\n var head = actionArgs.head || cm.getCursor('head');\n var height = cm.listSelections().length;\n if (insertAt == 'eol') {\n head = Pos(head.line, lineLength(cm, head.line));\n } else if (insertAt == 'charAfter') {\n head = offsetCursor(head, 0, 1);\n } else if (insertAt == 'firstNonBlank') {\n head = motions.moveToFirstNonWhiteSpaceCharacter(cm, head);\n } else if (insertAt == 'startOfSelectedArea') {\n if (!vim.visualBlock) {\n if (sel.head.line < sel.anchor.line) {\n head = sel.head;\n } else {\n head = Pos(sel.anchor.line, 0);\n }\n } else {\n head = Pos(\n Math.min(sel.head.line, sel.anchor.line),\n Math.min(sel.head.ch, sel.anchor.ch));\n height = Math.abs(sel.head.line - sel.anchor.line) + 1;\n }\n } else if (insertAt == 'endOfSelectedArea') {\n if (!vim.visualBlock) {\n if (sel.head.line >= sel.anchor.line) {\n head = offsetCursor(sel.head, 0, 1);\n } else {\n head = Pos(sel.anchor.line, 0);\n }\n } else {\n head = Pos(\n Math.min(sel.head.line, sel.anchor.line),\n Math.max(sel.head.ch + 1, sel.anchor.ch));\n height = Math.abs(sel.head.line - sel.anchor.line) + 1;\n }\n } else if (insertAt == 'inplace') {\n if (vim.visualMode){\n return;\n }\n }\n cm.setOption('keyMap', 'vim-insert');\n cm.setOption('disableInput', false);\n if (actionArgs && actionArgs.replace) {\n // Handle Replace-mode as a special case of insert mode.\n cm.toggleOverwrite(true);\n cm.setOption('keyMap', 'vim-replace');\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"replace\"});\n } else {\n cm.setOption('keyMap', 'vim-insert');\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"insert\"});\n }\n if (!vimGlobalState.macroModeState.isPlaying) {\n // Only record if not replaying.\n cm.on('change', onChange);\n CodeMirror.on(cm.getInputField(), 'keydown', onKeyEventTargetKeyDown);\n }\n if (vim.visualMode) {\n exitVisualMode(cm);\n }\n selectForInsert(cm, head, height);\n },\n toggleVisualMode: function(cm, actionArgs, vim) {\n var repeat = actionArgs.repeat;\n var anchor = cm.getCursor();\n var head;\n // TODO: The repeat should actually select number of characters/lines\n // equal to the repeat times the size of the previous visual\n // operation.\n if (!vim.visualMode) {\n // Entering visual mode\n vim.visualMode = true;\n vim.visualLine = !!actionArgs.linewise;\n vim.visualBlock = !!actionArgs.blockwise;\n head = clipCursorToContent(\n cm, Pos(anchor.line, anchor.ch + repeat - 1),\n true /** includeLineBreak */);\n vim.sel = {\n anchor: anchor,\n head: head\n };\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"visual\", subMode: vim.visualLine ? \"linewise\" : vim.visualBlock ? \"blockwise\" : \"\"});\n updateCmSelection(cm);\n updateMark(cm, vim, '<', cursorMin(anchor, head));\n updateMark(cm, vim, '>', cursorMax(anchor, head));\n } else if (vim.visualLine ^ actionArgs.linewise ||\n vim.visualBlock ^ actionArgs.blockwise) {\n // Toggling between modes\n vim.visualLine = !!actionArgs.linewise;\n vim.visualBlock = !!actionArgs.blockwise;\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"visual\", subMode: vim.visualLine ? \"linewise\" : vim.visualBlock ? \"blockwise\" : \"\"});\n updateCmSelection(cm);\n } else {\n exitVisualMode(cm);\n }\n },\n reselectLastSelection: function(cm, _actionArgs, vim) {\n var lastSelection = vim.lastSelection;\n if (vim.visualMode) {\n updateLastSelection(cm, vim);\n }\n if (lastSelection) {\n var anchor = lastSelection.anchorMark.find();\n var head = lastSelection.headMark.find();\n if (!anchor || !head) {\n // If the marks have been destroyed due to edits, do nothing.\n return;\n }\n vim.sel = {\n anchor: anchor,\n head: head\n };\n vim.visualMode = true;\n vim.visualLine = lastSelection.visualLine;\n vim.visualBlock = lastSelection.visualBlock;\n updateCmSelection(cm);\n updateMark(cm, vim, '<', cursorMin(anchor, head));\n updateMark(cm, vim, '>', cursorMax(anchor, head));\n CodeMirror.signal(cm, 'vim-mode-change', {\n mode: 'visual',\n subMode: vim.visualLine ? 'linewise' :\n vim.visualBlock ? 'blockwise' : ''});\n }\n },\n joinLines: function(cm, actionArgs, vim) {\n var curStart, curEnd;\n if (vim.visualMode) {\n curStart = cm.getCursor('anchor');\n curEnd = cm.getCursor('head');\n if (cursorIsBefore(curEnd, curStart)) {\n var tmp = curEnd;\n curEnd = curStart;\n curStart = tmp;\n }\n curEnd.ch = lineLength(cm, curEnd.line) - 1;\n } else {\n // Repeat is the number of lines to join. Minimum 2 lines.\n var repeat = Math.max(actionArgs.repeat, 2);\n curStart = cm.getCursor();\n curEnd = clipCursorToContent(cm, Pos(curStart.line + repeat - 1,\n Infinity));\n }\n var finalCh = 0;\n for (var i = curStart.line; i < curEnd.line; i++) {\n finalCh = lineLength(cm, curStart.line);\n var tmp = Pos(curStart.line + 1,\n lineLength(cm, curStart.line + 1));\n var text = cm.getRange(curStart, tmp);\n text = text.replace(/\\n\\s*/g, ' ');\n cm.replaceRange(text, curStart, tmp);\n }\n var curFinalPos = Pos(curStart.line, finalCh);\n if (vim.visualMode) {\n exitVisualMode(cm, false);\n }\n cm.setCursor(curFinalPos);\n },\n newLineAndEnterInsertMode: function(cm, actionArgs, vim) {\n vim.insertMode = true;\n var insertAt = copyCursor(cm.getCursor());\n if (insertAt.line === cm.firstLine() && !actionArgs.after) {\n // Special case for inserting newline before start of document.\n cm.replaceRange('\\n', Pos(cm.firstLine(), 0));\n cm.setCursor(cm.firstLine(), 0);\n } else {\n insertAt.line = (actionArgs.after) ? insertAt.line :\n insertAt.line - 1;\n insertAt.ch = lineLength(cm, insertAt.line);\n cm.setCursor(insertAt);\n var newlineFn = CodeMirror.commands.newlineAndIndentContinueComment ||\n CodeMirror.commands.newlineAndIndent;\n newlineFn(cm);\n }\n this.enterInsertMode(cm, { repeat: actionArgs.repeat }, vim);\n },\n paste: function(cm, actionArgs, vim) {\n var cur = copyCursor(cm.getCursor());\n var register = vimGlobalState.registerController.getRegister(\n actionArgs.registerName);\n var text = register.toString();\n if (!text) {\n return;\n }\n if (actionArgs.matchIndent) {\n var tabSize = cm.getOption(\"tabSize\");\n // length that considers tabs and tabSize\n var whitespaceLength = function(str) {\n var tabs = (str.split(\"\\t\").length - 1);\n var spaces = (str.split(\" \").length - 1);\n return tabs * tabSize + spaces * 1;\n };\n var currentLine = cm.getLine(cm.getCursor().line);\n var indent = whitespaceLength(currentLine.match(/^\\s*/)[0]);\n // chomp last newline b/c don't want it to match /^\\s*/gm\n var chompedText = text.replace(/\\n$/, '');\n var wasChomped = text !== chompedText;\n var firstIndent = whitespaceLength(text.match(/^\\s*/)[0]);\n var text = chompedText.replace(/^\\s*/gm, function(wspace) {\n var newIndent = indent + (whitespaceLength(wspace) - firstIndent);\n if (newIndent < 0) {\n return \"\";\n }\n else if (cm.getOption(\"indentWithTabs\")) {\n var quotient = Math.floor(newIndent / tabSize);\n return Array(quotient + 1).join('\\t');\n }\n else {\n return Array(newIndent + 1).join(' ');\n }\n });\n text += wasChomped ? \"\\n\" : \"\";\n }\n if (actionArgs.repeat > 1) {\n var text = Array(actionArgs.repeat + 1).join(text);\n }\n var linewise = register.linewise;\n var blockwise = register.blockwise;\n if (linewise) {\n if(vim.visualMode) {\n text = vim.visualLine ? text.slice(0, -1) : '\\n' + text.slice(0, text.length - 1) + '\\n';\n } else if (actionArgs.after) {\n // Move the newline at the end to the start instead, and paste just\n // before the newline character of the line we are on right now.\n text = '\\n' + text.slice(0, text.length - 1);\n cur.ch = lineLength(cm, cur.line);\n } else {\n cur.ch = 0;\n }\n } else {\n if (blockwise) {\n text = text.split('\\n');\n for (var i = 0; i < text.length; i++) {\n text[i] = (text[i] == '') ? ' ' : text[i];\n }\n }\n cur.ch += actionArgs.after ? 1 : 0;\n }\n var curPosFinal;\n var idx;\n if (vim.visualMode) {\n // save the pasted text for reselection if the need arises\n vim.lastPastedText = text;\n var lastSelectionCurEnd;\n var selectedArea = getSelectedAreaRange(cm, vim);\n var selectionStart = selectedArea[0];\n var selectionEnd = selectedArea[1];\n var selectedText = cm.getSelection();\n var selections = cm.listSelections();\n var emptyStrings = new Array(selections.length).join('1').split('1');\n // save the curEnd marker before it get cleared due to cm.replaceRange.\n if (vim.lastSelection) {\n lastSelectionCurEnd = vim.lastSelection.headMark.find();\n }\n // push the previously selected text to unnamed register\n vimGlobalState.registerController.unnamedRegister.setText(selectedText);\n if (blockwise) {\n // first delete the selected text\n cm.replaceSelections(emptyStrings);\n // Set new selections as per the block length of the yanked text\n selectionEnd = Pos(selectionStart.line + text.length-1, selectionStart.ch);\n cm.setCursor(selectionStart);\n selectBlock(cm, selectionEnd);\n cm.replaceSelections(text);\n curPosFinal = selectionStart;\n } else if (vim.visualBlock) {\n cm.replaceSelections(emptyStrings);\n cm.setCursor(selectionStart);\n cm.replaceRange(text, selectionStart, selectionStart);\n curPosFinal = selectionStart;\n } else {\n cm.replaceRange(text, selectionStart, selectionEnd);\n curPosFinal = cm.posFromIndex(cm.indexFromPos(selectionStart) + text.length - 1);\n }\n // restore the the curEnd marker\n if(lastSelectionCurEnd) {\n vim.lastSelection.headMark = cm.setBookmark(lastSelectionCurEnd);\n }\n if (linewise) {\n curPosFinal.ch=0;\n }\n } else {\n if (blockwise) {\n cm.setCursor(cur);\n for (var i = 0; i < text.length; i++) {\n var line = cur.line+i;\n if (line > cm.lastLine()) {\n cm.replaceRange('\\n', Pos(line, 0));\n }\n var lastCh = lineLength(cm, line);\n if (lastCh < cur.ch) {\n extendLineToColumn(cm, line, cur.ch);\n }\n }\n cm.setCursor(cur);\n selectBlock(cm, Pos(cur.line + text.length-1, cur.ch));\n cm.replaceSelections(text);\n curPosFinal = cur;\n } else {\n cm.replaceRange(text, cur);\n // Now fine tune the cursor to where we want it.\n if (linewise && actionArgs.after) {\n curPosFinal = Pos(\n cur.line + 1,\n findFirstNonWhiteSpaceCharacter(cm.getLine(cur.line + 1)));\n } else if (linewise && !actionArgs.after) {\n curPosFinal = Pos(\n cur.line,\n findFirstNonWhiteSpaceCharacter(cm.getLine(cur.line)));\n } else if (!linewise && actionArgs.after) {\n idx = cm.indexFromPos(cur);\n curPosFinal = cm.posFromIndex(idx + text.length - 1);\n } else {\n idx = cm.indexFromPos(cur);\n curPosFinal = cm.posFromIndex(idx + text.length);\n }\n }\n }\n if (vim.visualMode) {\n exitVisualMode(cm, false);\n }\n cm.setCursor(curPosFinal);\n },\n undo: function(cm, actionArgs) {\n cm.operation(function() {\n repeatFn(cm, CodeMirror.commands.undo, actionArgs.repeat)();\n cm.setCursor(cm.getCursor('anchor'));\n });\n },\n redo: function(cm, actionArgs) {\n repeatFn(cm, CodeMirror.commands.redo, actionArgs.repeat)();\n },\n setRegister: function(_cm, actionArgs, vim) {\n vim.inputState.registerName = actionArgs.selectedCharacter;\n },\n setMark: function(cm, actionArgs, vim) {\n var markName = actionArgs.selectedCharacter;\n updateMark(cm, vim, markName, cm.getCursor());\n },\n replace: function(cm, actionArgs, vim) {\n var replaceWith = actionArgs.selectedCharacter;\n var curStart = cm.getCursor();\n var replaceTo;\n var curEnd;\n var selections = cm.listSelections();\n if (vim.visualMode) {\n curStart = cm.getCursor('start');\n curEnd = cm.getCursor('end');\n } else {\n var line = cm.getLine(curStart.line);\n replaceTo = curStart.ch + actionArgs.repeat;\n if (replaceTo > line.length) {\n replaceTo=line.length;\n }\n curEnd = Pos(curStart.line, replaceTo);\n }\n if (replaceWith=='\\n') {\n if (!vim.visualMode) cm.replaceRange('', curStart, curEnd);\n // special case, where vim help says to replace by just one line-break\n (CodeMirror.commands.newlineAndIndentContinueComment || CodeMirror.commands.newlineAndIndent)(cm);\n } else {\n var replaceWithStr = cm.getRange(curStart, curEnd);\n //replace all characters in range by selected, but keep linebreaks\n replaceWithStr = replaceWithStr.replace(/[^\\n]/g, replaceWith);\n if (vim.visualBlock) {\n // Tabs are split in visua block before replacing\n var spaces = new Array(cm.getOption(\"tabSize\")+1).join(' ');\n replaceWithStr = cm.getSelection();\n replaceWithStr = replaceWithStr.replace(/\\t/g, spaces).replace(/[^\\n]/g, replaceWith).split('\\n');\n cm.replaceSelections(replaceWithStr);\n } else {\n cm.replaceRange(replaceWithStr, curStart, curEnd);\n }\n if (vim.visualMode) {\n curStart = cursorIsBefore(selections[0].anchor, selections[0].head) ?\n selections[0].anchor : selections[0].head;\n cm.setCursor(curStart);\n exitVisualMode(cm, false);\n } else {\n cm.setCursor(offsetCursor(curEnd, 0, -1));\n }\n }\n },\n incrementNumberToken: function(cm, actionArgs) {\n var cur = cm.getCursor();\n var lineStr = cm.getLine(cur.line);\n var re = /-?\\d+/g;\n var match;\n var start;\n var end;\n var numberStr;\n var token;\n while ((match = re.exec(lineStr)) !== null) {\n token = match[0];\n start = match.index;\n end = start + token.length;\n if (cur.ch < end)break;\n }\n if (!actionArgs.backtrack && (end <= cur.ch))return;\n if (token) {\n var increment = actionArgs.increase ? 1 : -1;\n var number = parseInt(token) + (increment * actionArgs.repeat);\n var from = Pos(cur.line, start);\n var to = Pos(cur.line, end);\n numberStr = number.toString();\n cm.replaceRange(numberStr, from, to);\n } else {\n return;\n }\n cm.setCursor(Pos(cur.line, start + numberStr.length - 1));\n },\n repeatLastEdit: function(cm, actionArgs, vim) {\n var lastEditInputState = vim.lastEditInputState;\n if (!lastEditInputState) { return; }\n var repeat = actionArgs.repeat;\n if (repeat && actionArgs.repeatIsExplicit) {\n vim.lastEditInputState.repeatOverride = repeat;\n } else {\n repeat = vim.lastEditInputState.repeatOverride || repeat;\n }\n repeatLastEdit(cm, vim, repeat, false /** repeatForInsert */);\n },\n exitInsertMode: exitInsertMode\n };\n\n function defineAction(name, fn) {\n actions[name] = fn;\n }\n\n /*\n * Below are miscellaneous utility functions used by vim.js\n */\n\n /**\n * Clips cursor to ensure that line is within the buffer's range\n * If includeLineBreak is true, then allow cur.ch == lineLength.\n */\n function clipCursorToContent(cm, cur, includeLineBreak) {\n var line = Math.min(Math.max(cm.firstLine(), cur.line), cm.lastLine() );\n var maxCh = lineLength(cm, line) - 1;\n maxCh = (includeLineBreak) ? maxCh + 1 : maxCh;\n var ch = Math.min(Math.max(0, cur.ch), maxCh);\n return Pos(line, ch);\n }\n function copyArgs(args) {\n var ret = {};\n for (var prop in args) {\n if (args.hasOwnProperty(prop)) {\n ret[prop] = args[prop];\n }\n }\n return ret;\n }\n function offsetCursor(cur, offsetLine, offsetCh) {\n if (typeof offsetLine === 'object') {\n offsetCh = offsetLine.ch;\n offsetLine = offsetLine.line;\n }\n return Pos(cur.line + offsetLine, cur.ch + offsetCh);\n }\n function getOffset(anchor, head) {\n return {\n line: head.line - anchor.line,\n ch: head.line - anchor.line\n };\n }\n function commandMatches(keys, keyMap, context, inputState) {\n // Partial matches are not applied. They inform the key handler\n // that the current key sequence is a subsequence of a valid key\n // sequence, so that the key buffer is not cleared.\n var match, partial = [], full = [];\n for (var i = 0; i < keyMap.length; i++) {\n var command = keyMap[i];\n if (context == 'insert' && command.context != 'insert' ||\n command.context && command.context != context ||\n inputState.operator && command.type == 'action' ||\n !(match = commandMatch(keys, command.keys))) { continue; }\n if (match == 'partial') { partial.push(command); }\n if (match == 'full') { full.push(command); }\n }\n return {\n partial: partial.length && partial,\n full: full.length && full\n };\n }\n function commandMatch(pressed, mapped) {\n if (mapped.slice(-11) == '<character>') {\n // Last character matches anything.\n var prefixLen = mapped.length - 11;\n var pressedPrefix = pressed.slice(0, prefixLen);\n var mappedPrefix = mapped.slice(0, prefixLen);\n return pressedPrefix == mappedPrefix && pressed.length > prefixLen ? 'full' :\n mappedPrefix.indexOf(pressedPrefix) == 0 ? 'partial' : false;\n } else {\n return pressed == mapped ? 'full' :\n mapped.indexOf(pressed) == 0 ? 'partial' : false;\n }\n }\n function lastChar(keys) {\n var match = /^.*(<[\\w\\-]+>)$/.exec(keys);\n var selectedCharacter = match ? match[1] : keys.slice(-1);\n if (selectedCharacter.length > 1){\n switch(selectedCharacter){\n case '<CR>':\n selectedCharacter='\\n';\n break;\n case '<Space>':\n selectedCharacter=' ';\n break;\n default:\n break;\n }\n }\n return selectedCharacter;\n }\n function repeatFn(cm, fn, repeat) {\n return function() {\n for (var i = 0; i < repeat; i++) {\n fn(cm);\n }\n };\n }\n function copyCursor(cur) {\n return Pos(cur.line, cur.ch);\n }\n function cursorEqual(cur1, cur2) {\n return cur1.ch == cur2.ch && cur1.line == cur2.line;\n }\n function cursorIsBefore(cur1, cur2) {\n if (cur1.line < cur2.line) {\n return true;\n }\n if (cur1.line == cur2.line && cur1.ch < cur2.ch) {\n return true;\n }\n return false;\n }\n function cursorMin(cur1, cur2) {\n if (arguments.length > 2) {\n cur2 = cursorMin.apply(undefined, Array.prototype.slice.call(arguments, 1));\n }\n return cursorIsBefore(cur1, cur2) ? cur1 : cur2;\n }\n function cursorMax(cur1, cur2) {\n if (arguments.length > 2) {\n cur2 = cursorMax.apply(undefined, Array.prototype.slice.call(arguments, 1));\n }\n return cursorIsBefore(cur1, cur2) ? cur2 : cur1;\n }\n function cursorIsBetween(cur1, cur2, cur3) {\n // returns true if cur2 is between cur1 and cur3.\n var cur1before2 = cursorIsBefore(cur1, cur2);\n var cur2before3 = cursorIsBefore(cur2, cur3);\n return cur1before2 && cur2before3;\n }\n function lineLength(cm, lineNum) {\n return cm.getLine(lineNum).length;\n }\n function trim(s) {\n if (s.trim) {\n return s.trim();\n }\n return s.replace(/^\\s+|\\s+$/g, '');\n }\n function escapeRegex(s) {\n return s.replace(/([.?*+$\\[\\]\\/\\\\(){}|\\-])/g, '\\\\$1');\n }\n function extendLineToColumn(cm, lineNum, column) {\n var endCh = lineLength(cm, lineNum);\n var spaces = new Array(column-endCh+1).join(' ');\n cm.setCursor(Pos(lineNum, endCh));\n cm.replaceRange(spaces, cm.getCursor());\n }\n // This functions selects a rectangular block\n // of text with selectionEnd as any of its corner\n // Height of block:\n // Difference in selectionEnd.line and first/last selection.line\n // Width of the block:\n // Distance between selectionEnd.ch and any(first considered here) selection.ch\n function selectBlock(cm, selectionEnd) {\n var selections = [], ranges = cm.listSelections();\n var head = copyCursor(cm.clipPos(selectionEnd));\n var isClipped = !cursorEqual(selectionEnd, head);\n var curHead = cm.getCursor('head');\n var primIndex = getIndex(ranges, curHead);\n var wasClipped = cursorEqual(ranges[primIndex].head, ranges[primIndex].anchor);\n var max = ranges.length - 1;\n var index = max - primIndex > primIndex ? max : 0;\n var base = ranges[index].anchor;\n\n var firstLine = Math.min(base.line, head.line);\n var lastLine = Math.max(base.line, head.line);\n var baseCh = base.ch, headCh = head.ch;\n\n var dir = ranges[index].head.ch - baseCh;\n var newDir = headCh - baseCh;\n if (dir > 0 && newDir <= 0) {\n baseCh++;\n if (!isClipped) { headCh--; }\n } else if (dir < 0 && newDir >= 0) {\n baseCh--;\n if (!wasClipped) { headCh++; }\n } else if (dir < 0 && newDir == -1) {\n baseCh--;\n headCh++;\n }\n for (var line = firstLine; line <= lastLine; line++) {\n var range = {anchor: new Pos(line, baseCh), head: new Pos(line, headCh)};\n selections.push(range);\n }\n primIndex = head.line == lastLine ? selections.length - 1 : 0;\n cm.setSelections(selections);\n selectionEnd.ch = headCh;\n base.ch = baseCh;\n return base;\n }\n function selectForInsert(cm, head, height) {\n var sel = [];\n for (var i = 0; i < height; i++) {\n var lineHead = offsetCursor(head, i, 0);\n sel.push({anchor: lineHead, head: lineHead});\n }\n cm.setSelections(sel, 0);\n }\n // getIndex returns the index of the cursor in the selections.\n function getIndex(ranges, cursor, end) {\n for (var i = 0; i < ranges.length; i++) {\n var atAnchor = end != 'head' && cursorEqual(ranges[i].anchor, cursor);\n var atHead = end != 'anchor' && cursorEqual(ranges[i].head, cursor);\n if (atAnchor || atHead) {\n return i;\n }\n }\n return -1;\n }\n function getSelectedAreaRange(cm, vim) {\n var lastSelection = vim.lastSelection;\n var getCurrentSelectedAreaRange = function() {\n var selections = cm.listSelections();\n var start = selections[0];\n var end = selections[selections.length-1];\n var selectionStart = cursorIsBefore(start.anchor, start.head) ? start.anchor : start.head;\n var selectionEnd = cursorIsBefore(end.anchor, end.head) ? end.head : end.anchor;\n return [selectionStart, selectionEnd];\n };\n var getLastSelectedAreaRange = function() {\n var selectionStart = cm.getCursor();\n var selectionEnd = cm.getCursor();\n var block = lastSelection.visualBlock;\n if (block) {\n var width = block.width;\n var height = block.height;\n selectionEnd = Pos(selectionStart.line + height, selectionStart.ch + width);\n var selections = [];\n // selectBlock creates a 'proper' rectangular block.\n // We do not want that in all cases, so we manually set selections.\n for (var i = selectionStart.line; i < selectionEnd.line; i++) {\n var anchor = Pos(i, selectionStart.ch);\n var head = Pos(i, selectionEnd.ch);\n var range = {anchor: anchor, head: head};\n selections.push(range);\n }\n cm.setSelections(selections);\n } else {\n var start = lastSelection.anchorMark.find();\n var end = lastSelection.headMark.find();\n var line = end.line - start.line;\n var ch = end.ch - start.ch;\n selectionEnd = {line: selectionEnd.line + line, ch: line ? selectionEnd.ch : ch + selectionEnd.ch};\n if (lastSelection.visualLine) {\n selectionStart = Pos(selectionStart.line, 0);\n selectionEnd = Pos(selectionEnd.line, lineLength(cm, selectionEnd.line));\n }\n cm.setSelection(selectionStart, selectionEnd);\n }\n return [selectionStart, selectionEnd];\n };\n if (!vim.visualMode) {\n // In case of replaying the action.\n return getLastSelectedAreaRange();\n } else {\n return getCurrentSelectedAreaRange();\n }\n }\n // Updates the previous selection with the current selection's values. This\n // should only be called in visual mode.\n function updateLastSelection(cm, vim) {\n var anchor = vim.sel.anchor;\n var head = vim.sel.head;\n // To accommodate the effect of lastPastedText in the last selection\n if (vim.lastPastedText) {\n head = cm.posFromIndex(cm.indexFromPos(anchor) + vim.lastPastedText.length);\n vim.lastPastedText = null;\n }\n vim.lastSelection = {'anchorMark': cm.setBookmark(anchor),\n 'headMark': cm.setBookmark(head),\n 'anchor': copyCursor(anchor),\n 'head': copyCursor(head),\n 'visualMode': vim.visualMode,\n 'visualLine': vim.visualLine,\n 'visualBlock': vim.visualBlock};\n }\n function expandSelection(cm, start, end) {\n var sel = cm.state.vim.sel;\n var head = sel.head;\n var anchor = sel.anchor;\n var tmp;\n if (cursorIsBefore(end, start)) {\n tmp = end;\n end = start;\n start = tmp;\n }\n if (cursorIsBefore(head, anchor)) {\n head = cursorMin(start, head);\n anchor = cursorMax(anchor, end);\n } else {\n anchor = cursorMin(start, anchor);\n head = cursorMax(head, end);\n head = offsetCursor(head, 0, -1);\n if (head.ch == -1 && head.line != cm.firstLine()) {\n head = Pos(head.line - 1, lineLength(cm, head.line - 1));\n }\n }\n return [anchor, head];\n }\n /**\n * Updates the CodeMirror selection to match the provided vim selection.\n * If no arguments are given, it uses the current vim selection state.\n */\n function updateCmSelection(cm, sel, mode) {\n var vim = cm.state.vim;\n sel = sel || vim.sel;\n var mode = mode ||\n vim.visualLine ? 'line' : vim.visualBlock ? 'block' : 'char';\n var cmSel = makeCmSelection(cm, sel, mode);\n cm.setSelections(cmSel.ranges, cmSel.primary);\n updateFakeCursor(cm);\n }\n function makeCmSelection(cm, sel, mode, exclusive) {\n var head = copyCursor(sel.head);\n var anchor = copyCursor(sel.anchor);\n if (mode == 'char') {\n var headOffset = !exclusive && !cursorIsBefore(sel.head, sel.anchor) ? 1 : 0;\n var anchorOffset = cursorIsBefore(sel.head, sel.anchor) ? 1 : 0;\n head = offsetCursor(sel.head, 0, headOffset);\n anchor = offsetCursor(sel.anchor, 0, anchorOffset);\n return {\n ranges: [{anchor: anchor, head: head}],\n primary: 0\n };\n } else if (mode == 'line') {\n if (!cursorIsBefore(sel.head, sel.anchor)) {\n anchor.ch = 0;\n\n var lastLine = cm.lastLine();\n if (head.line > lastLine) {\n head.line = lastLine;\n }\n head.ch = lineLength(cm, head.line);\n } else {\n head.ch = 0;\n anchor.ch = lineLength(cm, anchor.line);\n }\n return {\n ranges: [{anchor: anchor, head: head}],\n primary: 0\n };\n } else if (mode == 'block') {\n var top = Math.min(anchor.line, head.line),\n left = Math.min(anchor.ch, head.ch),\n bottom = Math.max(anchor.line, head.line),\n right = Math.max(anchor.ch, head.ch) + 1;\n var height = bottom - top + 1;\n var primary = head.line == top ? 0 : height - 1;\n var ranges = [];\n for (var i = 0; i < height; i++) {\n ranges.push({\n anchor: Pos(top + i, left),\n head: Pos(top + i, right)\n });\n }\n return {\n ranges: ranges,\n primary: primary\n };\n }\n }\n function getHead(cm) {\n var cur = cm.getCursor('head');\n if (cm.getSelection().length == 1) {\n // Small corner case when only 1 character is selected. The \"real\"\n // head is the left of head and anchor.\n cur = cursorMin(cur, cm.getCursor('anchor'));\n }\n return cur;\n }\n\n /**\n * If moveHead is set to false, the CodeMirror selection will not be\n * touched. The caller assumes the responsibility of putting the cursor\n * in the right place.\n */\n function exitVisualMode(cm, moveHead) {\n var vim = cm.state.vim;\n if (moveHead !== false) {\n cm.setCursor(clipCursorToContent(cm, vim.sel.head));\n }\n updateLastSelection(cm, vim);\n vim.visualMode = false;\n vim.visualLine = false;\n vim.visualBlock = false;\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"normal\"});\n if (vim.fakeCursor) {\n vim.fakeCursor.clear();\n }\n }\n\n // Remove any trailing newlines from the selection. For\n // example, with the caret at the start of the last word on the line,\n // 'dw' should word, but not the newline, while 'w' should advance the\n // caret to the first character of the next line.\n function clipToLine(cm, curStart, curEnd) {\n var selection = cm.getRange(curStart, curEnd);\n // Only clip if the selection ends with trailing newline + whitespace\n if (/\\n\\s*$/.test(selection)) {\n var lines = selection.split('\\n');\n // We know this is all whitepsace.\n lines.pop();\n\n // Cases:\n // 1. Last word is an empty line - do not clip the trailing '\\n'\n // 2. Last word is not an empty line - clip the trailing '\\n'\n var line;\n // Find the line containing the last word, and clip all whitespace up\n // to it.\n for (var line = lines.pop(); lines.length > 0 && line && isWhiteSpaceString(line); line = lines.pop()) {\n curEnd.line--;\n curEnd.ch = 0;\n }\n // If the last word is not an empty line, clip an additional newline\n if (line) {\n curEnd.line--;\n curEnd.ch = lineLength(cm, curEnd.line);\n } else {\n curEnd.ch = 0;\n }\n }\n }\n\n // Expand the selection to line ends.\n function expandSelectionToLine(_cm, curStart, curEnd) {\n curStart.ch = 0;\n curEnd.ch = 0;\n curEnd.line++;\n }\n\n function findFirstNonWhiteSpaceCharacter(text) {\n if (!text) {\n return 0;\n }\n var firstNonWS = text.search(/\\S/);\n return firstNonWS == -1 ? text.length : firstNonWS;\n }\n\n function expandWordUnderCursor(cm, inclusive, _forward, bigWord, noSymbol) {\n var cur = getHead(cm);\n var line = cm.getLine(cur.line);\n var idx = cur.ch;\n\n // Seek to first word or non-whitespace character, depending on if\n // noSymbol is true.\n var test = noSymbol ? wordCharTest[0] : bigWordCharTest [0];\n while (!test(line.charAt(idx))) {\n idx++;\n if (idx >= line.length) { return null; }\n }\n\n if (bigWord) {\n test = bigWordCharTest[0];\n } else {\n test = wordCharTest[0];\n if (!test(line.charAt(idx))) {\n test = wordCharTest[1];\n }\n }\n\n var end = idx, start = idx;\n while (test(line.charAt(end)) && end < line.length) { end++; }\n while (test(line.charAt(start)) && start >= 0) { start--; }\n start++;\n\n if (inclusive) {\n // If present, include all whitespace after word.\n // Otherwise, include all whitespace before word, except indentation.\n var wordEnd = end;\n while (/\\s/.test(line.charAt(end)) && end < line.length) { end++; }\n if (wordEnd == end) {\n var wordStart = start;\n while (/\\s/.test(line.charAt(start - 1)) && start > 0) { start--; }\n if (!start) { start = wordStart; }\n }\n }\n return { start: Pos(cur.line, start), end: Pos(cur.line, end) };\n }\n\n function recordJumpPosition(cm, oldCur, newCur) {\n if (!cursorEqual(oldCur, newCur)) {\n vimGlobalState.jumpList.add(cm, oldCur, newCur);\n }\n }\n\n function recordLastCharacterSearch(increment, args) {\n vimGlobalState.lastChararacterSearch.increment = increment;\n vimGlobalState.lastChararacterSearch.forward = args.forward;\n vimGlobalState.lastChararacterSearch.selectedCharacter = args.selectedCharacter;\n }\n\n var symbolToMode = {\n '(': 'bracket', ')': 'bracket', '{': 'bracket', '}': 'bracket',\n '[': 'section', ']': 'section',\n '*': 'comment', '/': 'comment',\n 'm': 'method', 'M': 'method',\n '#': 'preprocess'\n };\n var findSymbolModes = {\n bracket: {\n isComplete: function(state) {\n if (state.nextCh === state.symb) {\n state.depth++;\n if (state.depth >= 1)return true;\n } else if (state.nextCh === state.reverseSymb) {\n state.depth--;\n }\n return false;\n }\n },\n section: {\n init: function(state) {\n state.curMoveThrough = true;\n state.symb = (state.forward ? ']' : '[') === state.symb ? '{' : '}';\n },\n isComplete: function(state) {\n return state.index === 0 && state.nextCh === state.symb;\n }\n },\n comment: {\n isComplete: function(state) {\n var found = state.lastCh === '*' && state.nextCh === '/';\n state.lastCh = state.nextCh;\n return found;\n }\n },\n // TODO: The original Vim implementation only operates on level 1 and 2.\n // The current implementation doesn't check for code block level and\n // therefore it operates on any levels.\n method: {\n init: function(state) {\n state.symb = (state.symb === 'm' ? '{' : '}');\n state.reverseSymb = state.symb === '{' ? '}' : '{';\n },\n isComplete: function(state) {\n if (state.nextCh === state.symb)return true;\n return false;\n }\n },\n preprocess: {\n init: function(state) {\n state.index = 0;\n },\n isComplete: function(state) {\n if (state.nextCh === '#') {\n var token = state.lineText.match(/#(\\w+)/)[1];\n if (token === 'endif') {\n if (state.forward && state.depth === 0) {\n return true;\n }\n state.depth++;\n } else if (token === 'if') {\n if (!state.forward && state.depth === 0) {\n return true;\n }\n state.depth--;\n }\n if (token === 'else' && state.depth === 0)return true;\n }\n return false;\n }\n }\n };\n function findSymbol(cm, repeat, forward, symb) {\n var cur = copyCursor(cm.getCursor());\n var increment = forward ? 1 : -1;\n var endLine = forward ? cm.lineCount() : -1;\n var curCh = cur.ch;\n var line = cur.line;\n var lineText = cm.getLine(line);\n var state = {\n lineText: lineText,\n nextCh: lineText.charAt(curCh),\n lastCh: null,\n index: curCh,\n symb: symb,\n reverseSymb: (forward ? { ')': '(', '}': '{' } : { '(': ')', '{': '}' })[symb],\n forward: forward,\n depth: 0,\n curMoveThrough: false\n };\n var mode = symbolToMode[symb];\n if (!mode)return cur;\n var init = findSymbolModes[mode].init;\n var isComplete = findSymbolModes[mode].isComplete;\n if (init) { init(state); }\n while (line !== endLine && repeat) {\n state.index += increment;\n state.nextCh = state.lineText.charAt(state.index);\n if (!state.nextCh) {\n line += increment;\n state.lineText = cm.getLine(line) || '';\n if (increment > 0) {\n state.index = 0;\n } else {\n var lineLen = state.lineText.length;\n state.index = (lineLen > 0) ? (lineLen-1) : 0;\n }\n state.nextCh = state.lineText.charAt(state.index);\n }\n if (isComplete(state)) {\n cur.line = line;\n cur.ch = state.index;\n repeat--;\n }\n }\n if (state.nextCh || state.curMoveThrough) {\n return Pos(line, state.index);\n }\n return cur;\n }\n\n /**\n * Returns the boundaries of the next word. If the cursor in the middle of\n * the word, then returns the boundaries of the current word, starting at\n * the cursor. If the cursor is at the start/end of a word, and we are going\n * forward/backward, respectively, find the boundaries of the next word.\n *\n * @param {CodeMirror} cm CodeMirror object.\n * @param {Cursor} cur The cursor position.\n * @param {boolean} forward True to search forward. False to search\n * backward.\n * @param {boolean} bigWord True if punctuation count as part of the word.\n * False if only [a-zA-Z0-9] characters count as part of the word.\n * @param {boolean} emptyLineIsWord True if empty lines should be treated\n * as words.\n * @return {Object{from:number, to:number, line: number}} The boundaries of\n * the word, or null if there are no more words.\n */\n function findWord(cm, cur, forward, bigWord, emptyLineIsWord) {\n var lineNum = cur.line;\n var pos = cur.ch;\n var line = cm.getLine(lineNum);\n var dir = forward ? 1 : -1;\n var charTests = bigWord ? bigWordCharTest: wordCharTest;\n\n if (emptyLineIsWord && line == '') {\n lineNum += dir;\n line = cm.getLine(lineNum);\n if (!isLine(cm, lineNum)) {\n return null;\n }\n pos = (forward) ? 0 : line.length;\n }\n\n while (true) {\n if (emptyLineIsWord && line == '') {\n return { from: 0, to: 0, line: lineNum };\n }\n var stop = (dir > 0) ? line.length : -1;\n var wordStart = stop, wordEnd = stop;\n // Find bounds of next word.\n while (pos != stop) {\n var foundWord = false;\n for (var i = 0; i < charTests.length && !foundWord; ++i) {\n if (charTests[i](line.charAt(pos))) {\n wordStart = pos;\n // Advance to end of word.\n while (pos != stop && charTests[i](line.charAt(pos))) {\n pos += dir;\n }\n wordEnd = pos;\n foundWord = wordStart != wordEnd;\n if (wordStart == cur.ch && lineNum == cur.line &&\n wordEnd == wordStart + dir) {\n // We started at the end of a word. Find the next one.\n continue;\n } else {\n return {\n from: Math.min(wordStart, wordEnd + 1),\n to: Math.max(wordStart, wordEnd),\n line: lineNum };\n }\n }\n }\n if (!foundWord) {\n pos += dir;\n }\n }\n // Advance to next/prev line.\n lineNum += dir;\n if (!isLine(cm, lineNum)) {\n return null;\n }\n line = cm.getLine(lineNum);\n pos = (dir > 0) ? 0 : line.length;\n }\n // Should never get here.\n throw new Error('The impossible happened.');\n }\n\n /**\n * @param {CodeMirror} cm CodeMirror object.\n * @param {Pos} cur The position to start from.\n * @param {int} repeat Number of words to move past.\n * @param {boolean} forward True to search forward. False to search\n * backward.\n * @param {boolean} wordEnd True to move to end of word. False to move to\n * beginning of word.\n * @param {boolean} bigWord True if punctuation count as part of the word.\n * False if only alphabet characters count as part of the word.\n * @return {Cursor} The position the cursor should move to.\n */\n function moveToWord(cm, cur, repeat, forward, wordEnd, bigWord) {\n var curStart = copyCursor(cur);\n var words = [];\n if (forward && !wordEnd || !forward && wordEnd) {\n repeat++;\n }\n // For 'e', empty lines are not considered words, go figure.\n var emptyLineIsWord = !(forward && wordEnd);\n for (var i = 0; i < repeat; i++) {\n var word = findWord(cm, cur, forward, bigWord, emptyLineIsWord);\n if (!word) {\n var eodCh = lineLength(cm, cm.lastLine());\n words.push(forward\n ? {line: cm.lastLine(), from: eodCh, to: eodCh}\n : {line: 0, from: 0, to: 0});\n break;\n }\n words.push(word);\n cur = Pos(word.line, forward ? (word.to - 1) : word.from);\n }\n var shortCircuit = words.length != repeat;\n var firstWord = words[0];\n var lastWord = words.pop();\n if (forward && !wordEnd) {\n // w\n if (!shortCircuit && (firstWord.from != curStart.ch || firstWord.line != curStart.line)) {\n // We did not start in the middle of a word. Discard the extra word at the end.\n lastWord = words.pop();\n }\n return Pos(lastWord.line, lastWord.from);\n } else if (forward && wordEnd) {\n return Pos(lastWord.line, lastWord.to - 1);\n } else if (!forward && wordEnd) {\n // ge\n if (!shortCircuit && (firstWord.to != curStart.ch || firstWord.line != curStart.line)) {\n // We did not start in the middle of a word. Discard the extra word at the end.\n lastWord = words.pop();\n }\n return Pos(lastWord.line, lastWord.to);\n } else {\n // b\n return Pos(lastWord.line, lastWord.from);\n }\n }\n\n function moveToCharacter(cm, repeat, forward, character) {\n var cur = cm.getCursor();\n var start = cur.ch;\n var idx;\n for (var i = 0; i < repeat; i ++) {\n var line = cm.getLine(cur.line);\n idx = charIdxInLine(start, line, character, forward, true);\n if (idx == -1) {\n return null;\n }\n start = idx;\n }\n return Pos(cm.getCursor().line, idx);\n }\n\n function moveToColumn(cm, repeat) {\n // repeat is always >= 1, so repeat - 1 always corresponds\n // to the column we want to go to.\n var line = cm.getCursor().line;\n return clipCursorToContent(cm, Pos(line, repeat - 1));\n }\n\n function updateMark(cm, vim, markName, pos) {\n if (!inArray(markName, validMarks)) {\n return;\n }\n if (vim.marks[markName]) {\n vim.marks[markName].clear();\n }\n vim.marks[markName] = cm.setBookmark(pos);\n }\n\n function charIdxInLine(start, line, character, forward, includeChar) {\n // Search for char in line.\n // motion_options: {forward, includeChar}\n // If includeChar = true, include it too.\n // If forward = true, search forward, else search backwards.\n // If char is not found on this line, do nothing\n var idx;\n if (forward) {\n idx = line.indexOf(character, start + 1);\n if (idx != -1 && !includeChar) {\n idx -= 1;\n }\n } else {\n idx = line.lastIndexOf(character, start - 1);\n if (idx != -1 && !includeChar) {\n idx += 1;\n }\n }\n return idx;\n }\n\n function findParagraph(cm, head, repeat, dir, inclusive) {\n var line = head.line;\n var min = cm.firstLine();\n var max = cm.lastLine();\n var start, end, i = line;\n function isEmpty(i) { return !cm.getLine(i); }\n function isBoundary(i, dir, any) {\n if (any) { return isEmpty(i) != isEmpty(i + dir); }\n return !isEmpty(i) && isEmpty(i + dir);\n }\n if (dir) {\n while (min <= i && i <= max && repeat > 0) {\n if (isBoundary(i, dir)) { repeat--; }\n i += dir;\n }\n return new Pos(i, 0);\n }\n\n var vim = cm.state.vim;\n if (vim.visualLine && isBoundary(line, 1, true)) {\n var anchor = vim.sel.anchor;\n if (isBoundary(anchor.line, -1, true)) {\n if (!inclusive || anchor.line != line) {\n line += 1;\n }\n }\n }\n var startState = isEmpty(line);\n for (i = line; i <= max && repeat; i++) {\n if (isBoundary(i, 1, true)) {\n if (!inclusive || isEmpty(i) != startState) {\n repeat--;\n }\n }\n }\n end = new Pos(i, 0);\n // select boundary before paragraph for the last one\n if (i > max && !startState) { startState = true; }\n else { inclusive = false; }\n for (i = line; i > min; i--) {\n if (!inclusive || isEmpty(i) == startState || i == line) {\n if (isBoundary(i, -1, true)) { break; }\n }\n }\n start = new Pos(i, 0);\n return { start: start, end: end };\n }\n\n // TODO: perhaps this finagling of start and end positions belonds\n // in codmirror/replaceRange?\n function selectCompanionObject(cm, head, symb, inclusive) {\n var cur = head, start, end;\n\n var bracketRegexp = ({\n '(': /[()]/, ')': /[()]/,\n '[': /[[\\]]/, ']': /[[\\]]/,\n '{': /[{}]/, '}': /[{}]/})[symb];\n var openSym = ({\n '(': '(', ')': '(',\n '[': '[', ']': '[',\n '{': '{', '}': '{'})[symb];\n var curChar = cm.getLine(cur.line).charAt(cur.ch);\n // Due to the behavior of scanForBracket, we need to add an offset if the\n // cursor is on a matching open bracket.\n var offset = curChar === openSym ? 1 : 0;\n\n start = cm.scanForBracket(Pos(cur.line, cur.ch + offset), -1, null, {'bracketRegex': bracketRegexp});\n end = cm.scanForBracket(Pos(cur.line, cur.ch + offset), 1, null, {'bracketRegex': bracketRegexp});\n\n if (!start || !end) {\n return { start: cur, end: cur };\n }\n\n start = start.pos;\n end = end.pos;\n\n if ((start.line == end.line && start.ch > end.ch)\n || (start.line > end.line)) {\n var tmp = start;\n start = end;\n end = tmp;\n }\n\n if (inclusive) {\n end.ch += 1;\n } else {\n start.ch += 1;\n }\n\n return { start: start, end: end };\n }\n\n // Takes in a symbol and a cursor and tries to simulate text objects that\n // have identical opening and closing symbols\n // TODO support across multiple lines\n function findBeginningAndEnd(cm, head, symb, inclusive) {\n var cur = copyCursor(head);\n var line = cm.getLine(cur.line);\n var chars = line.split('');\n var start, end, i, len;\n var firstIndex = chars.indexOf(symb);\n\n // the decision tree is to always look backwards for the beginning first,\n // but if the cursor is in front of the first instance of the symb,\n // then move the cursor forward\n if (cur.ch < firstIndex) {\n cur.ch = firstIndex;\n // Why is this line even here???\n // cm.setCursor(cur.line, firstIndex+1);\n }\n // otherwise if the cursor is currently on the closing symbol\n else if (firstIndex < cur.ch && chars[cur.ch] == symb) {\n end = cur.ch; // assign end to the current cursor\n --cur.ch; // make sure to look backwards\n }\n\n // if we're currently on the symbol, we've got a start\n if (chars[cur.ch] == symb && !end) {\n start = cur.ch + 1; // assign start to ahead of the cursor\n } else {\n // go backwards to find the start\n for (i = cur.ch; i > -1 && !start; i--) {\n if (chars[i] == symb) {\n start = i + 1;\n }\n }\n }\n\n // look forwards for the end symbol\n if (start && !end) {\n for (i = start, len = chars.length; i < len && !end; i++) {\n if (chars[i] == symb) {\n end = i;\n }\n }\n }\n\n // nothing found\n if (!start || !end) {\n return { start: cur, end: cur };\n }\n\n // include the symbols\n if (inclusive) {\n --start; ++end;\n }\n\n return {\n start: Pos(cur.line, start),\n end: Pos(cur.line, end)\n };\n }\n\n // Search functions\n defineOption('pcre', true, 'boolean');\n function SearchState() {}\n SearchState.prototype = {\n getQuery: function() {\n return vimGlobalState.query;\n },\n setQuery: function(query) {\n vimGlobalState.query = query;\n },\n getOverlay: function() {\n return this.searchOverlay;\n },\n setOverlay: function(overlay) {\n this.searchOverlay = overlay;\n },\n isReversed: function() {\n return vimGlobalState.isReversed;\n },\n setReversed: function(reversed) {\n vimGlobalState.isReversed = reversed;\n },\n getScrollbarAnnotate: function() {\n return this.annotate;\n },\n setScrollbarAnnotate: function(annotate) {\n this.annotate = annotate;\n }\n };\n function getSearchState(cm) {\n var vim = cm.state.vim;\n return vim.searchState_ || (vim.searchState_ = new SearchState());\n }\n function dialog(cm, template, shortText, onClose, options) {\n if (cm.openDialog) {\n cm.openDialog(template, onClose, { bottom: true, value: options.value,\n onKeyDown: options.onKeyDown, onKeyUp: options.onKeyUp,\n selectValueOnOpen: false});\n }\n else {\n onClose(prompt(shortText, ''));\n }\n }\n function splitBySlash(argString) {\n var slashes = findUnescapedSlashes(argString) || [];\n if (!slashes.length) return [];\n var tokens = [];\n // in case of strings like foo/bar\n if (slashes[0] !== 0) return;\n for (var i = 0; i < slashes.length; i++) {\n if (typeof slashes[i] == 'number')\n tokens.push(argString.substring(slashes[i] + 1, slashes[i+1]));\n }\n return tokens;\n }\n\n function findUnescapedSlashes(str) {\n var escapeNextChar = false;\n var slashes = [];\n for (var i = 0; i < str.length; i++) {\n var c = str.charAt(i);\n if (!escapeNextChar && c == '/') {\n slashes.push(i);\n }\n escapeNextChar = !escapeNextChar && (c == '\\\\');\n }\n return slashes;\n }\n\n // Translates a search string from ex (vim) syntax into javascript form.\n function translateRegex(str) {\n // When these match, add a '\\' if unescaped or remove one if escaped.\n var specials = '|(){';\n // Remove, but never add, a '\\' for these.\n var unescape = '}';\n var escapeNextChar = false;\n var out = [];\n for (var i = -1; i < str.length; i++) {\n var c = str.charAt(i) || '';\n var n = str.charAt(i+1) || '';\n var specialComesNext = (n && specials.indexOf(n) != -1);\n if (escapeNextChar) {\n if (c !== '\\\\' || !specialComesNext) {\n out.push(c);\n }\n escapeNextChar = false;\n } else {\n if (c === '\\\\') {\n escapeNextChar = true;\n // Treat the unescape list as special for removing, but not adding '\\'.\n if (n && unescape.indexOf(n) != -1) {\n specialComesNext = true;\n }\n // Not passing this test means removing a '\\'.\n if (!specialComesNext || n === '\\\\') {\n out.push(c);\n }\n } else {\n out.push(c);\n if (specialComesNext && n !== '\\\\') {\n out.push('\\\\');\n }\n }\n }\n }\n return out.join('');\n }\n\n // Translates the replace part of a search and replace from ex (vim) syntax into\n // javascript form. Similar to translateRegex, but additionally fixes back references\n // (translates '\\[0..9]' to '$[0..9]') and follows different rules for escaping '$'.\n var charUnescapes = {'\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t'};\n function translateRegexReplace(str) {\n var escapeNextChar = false;\n var out = [];\n for (var i = -1; i < str.length; i++) {\n var c = str.charAt(i) || '';\n var n = str.charAt(i+1) || '';\n if (charUnescapes[c + n]) {\n out.push(charUnescapes[c+n]);\n i++;\n } else if (escapeNextChar) {\n // At any point in the loop, escapeNextChar is true if the previous\n // character was a '\\' and was not escaped.\n out.push(c);\n escapeNextChar = false;\n } else {\n if (c === '\\\\') {\n escapeNextChar = true;\n if ((isNumber(n) || n === '$')) {\n out.push('$');\n } else if (n !== '/' && n !== '\\\\') {\n out.push('\\\\');\n }\n } else {\n if (c === '$') {\n out.push('$');\n }\n out.push(c);\n if (n === '/') {\n out.push('\\\\');\n }\n }\n }\n }\n return out.join('');\n }\n\n // Unescape \\ and / in the replace part, for PCRE mode.\n var unescapes = {'\\\\/': '/', '\\\\\\\\': '\\\\', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t'};\n function unescapeRegexReplace(str) {\n var stream = new CodeMirror.StringStream(str);\n var output = [];\n while (!stream.eol()) {\n // Search for \\.\n while (stream.peek() && stream.peek() != '\\\\') {\n output.push(stream.next());\n }\n var matched = false;\n for (var matcher in unescapes) {\n if (stream.match(matcher, true)) {\n matched = true;\n output.push(unescapes[matcher]);\n break;\n }\n }\n if (!matched) {\n // Don't change anything\n output.push(stream.next());\n }\n }\n return output.join('');\n }\n\n /**\n * Extract the regular expression from the query and return a Regexp object.\n * Returns null if the query is blank.\n * If ignoreCase is passed in, the Regexp object will have the 'i' flag set.\n * If smartCase is passed in, and the query contains upper case letters,\n * then ignoreCase is overridden, and the 'i' flag will not be set.\n * If the query contains the /i in the flag part of the regular expression,\n * then both ignoreCase and smartCase are ignored, and 'i' will be passed\n * through to the Regex object.\n */\n function parseQuery(query, ignoreCase, smartCase) {\n // First update the last search register\n var lastSearchRegister = vimGlobalState.registerController.getRegister('/');\n lastSearchRegister.setText(query);\n // Check if the query is already a regex.\n if (query instanceof RegExp) { return query; }\n // First try to extract regex + flags from the input. If no flags found,\n // extract just the regex. IE does not accept flags directly defined in\n // the regex string in the form /regex/flags\n var slashes = findUnescapedSlashes(query);\n var regexPart;\n var forceIgnoreCase;\n if (!slashes.length) {\n // Query looks like 'regexp'\n regexPart = query;\n } else {\n // Query looks like 'regexp/...'\n regexPart = query.substring(0, slashes[0]);\n var flagsPart = query.substring(slashes[0]);\n forceIgnoreCase = (flagsPart.indexOf('i') != -1);\n }\n if (!regexPart) {\n return null;\n }\n if (!getOption('pcre')) {\n regexPart = translateRegex(regexPart);\n }\n if (smartCase) {\n ignoreCase = (/^[^A-Z]*$/).test(regexPart);\n }\n var regexp = new RegExp(regexPart,\n (ignoreCase || forceIgnoreCase) ? 'i' : undefined);\n return regexp;\n }\n function showConfirm(cm, text) {\n if (cm.openNotification) {\n cm.openNotification('<span style=\"color: red\">' + text + '</span>',\n {bottom: true, duration: 5000});\n } else {\n alert(text);\n }\n }\n function makePrompt(prefix, desc) {\n var raw = '';\n if (prefix) {\n raw += '<span style=\"font-family: monospace\">' + prefix + '</span>';\n }\n raw += '<input type=\"text\"/> ' +\n '<span style=\"color: #888\">';\n if (desc) {\n raw += '<span style=\"color: #888\">';\n raw += desc;\n raw += '</span>';\n }\n return raw;\n }\n var searchPromptDesc = '(Javascript regexp)';\n function showPrompt(cm, options) {\n var shortText = (options.prefix || '') + ' ' + (options.desc || '');\n var prompt = makePrompt(options.prefix, options.desc);\n dialog(cm, prompt, shortText, options.onClose, options);\n }\n function regexEqual(r1, r2) {\n if (r1 instanceof RegExp && r2 instanceof RegExp) {\n var props = ['global', 'multiline', 'ignoreCase', 'source'];\n for (var i = 0; i < props.length; i++) {\n var prop = props[i];\n if (r1[prop] !== r2[prop]) {\n return false;\n }\n }\n return true;\n }\n return false;\n }\n // Returns true if the query is valid.\n function updateSearchQuery(cm, rawQuery, ignoreCase, smartCase) {\n if (!rawQuery) {\n return;\n }\n var state = getSearchState(cm);\n var query = parseQuery(rawQuery, !!ignoreCase, !!smartCase);\n if (!query) {\n return;\n }\n highlightSearchMatches(cm, query);\n if (regexEqual(query, state.getQuery())) {\n return query;\n }\n state.setQuery(query);\n return query;\n }\n function searchOverlay(query) {\n if (query.source.charAt(0) == '^') {\n var matchSol = true;\n }\n return {\n token: function(stream) {\n if (matchSol && !stream.sol()) {\n stream.skipToEnd();\n return;\n }\n var match = stream.match(query, false);\n if (match) {\n if (match[0].length == 0) {\n // Matched empty string, skip to next.\n stream.next();\n return 'searching';\n }\n if (!stream.sol()) {\n // Backtrack 1 to match \\b\n stream.backUp(1);\n if (!query.exec(stream.next() + match[0])) {\n stream.next();\n return null;\n }\n }\n stream.match(query);\n return 'searching';\n }\n while (!stream.eol()) {\n stream.next();\n if (stream.match(query, false)) break;\n }\n },\n query: query\n };\n }\n function highlightSearchMatches(cm, query) {\n var searchState = getSearchState(cm);\n var overlay = searchState.getOverlay();\n if (!overlay || query != overlay.query) {\n if (overlay) {\n cm.removeOverlay(overlay);\n }\n overlay = searchOverlay(query);\n cm.addOverlay(overlay);\n if (cm.showMatchesOnScrollbar) {\n if (searchState.getScrollbarAnnotate()) {\n searchState.getScrollbarAnnotate().clear();\n }\n searchState.setScrollbarAnnotate(cm.showMatchesOnScrollbar(query));\n }\n searchState.setOverlay(overlay);\n }\n }\n function findNext(cm, prev, query, repeat) {\n if (repeat === undefined) { repeat = 1; }\n return cm.operation(function() {\n var pos = cm.getCursor();\n var cursor = cm.getSearchCursor(query, pos);\n for (var i = 0; i < repeat; i++) {\n var found = cursor.find(prev);\n if (i == 0 && found && cursorEqual(cursor.from(), pos)) { found = cursor.find(prev); }\n if (!found) {\n // SearchCursor may have returned null because it hit EOF, wrap\n // around and try again.\n cursor = cm.getSearchCursor(query,\n (prev) ? Pos(cm.lastLine()) : Pos(cm.firstLine(), 0) );\n if (!cursor.find(prev)) {\n return;\n }\n }\n }\n return cursor.from();\n });\n }\n function clearSearchHighlight(cm) {\n var state = getSearchState(cm);\n cm.removeOverlay(getSearchState(cm).getOverlay());\n state.setOverlay(null);\n if (state.getScrollbarAnnotate()) {\n state.getScrollbarAnnotate().clear();\n state.setScrollbarAnnotate(null);\n }\n }\n /**\n * Check if pos is in the specified range, INCLUSIVE.\n * Range can be specified with 1 or 2 arguments.\n * If the first range argument is an array, treat it as an array of line\n * numbers. Match pos against any of the lines.\n * If the first range argument is a number,\n * if there is only 1 range argument, check if pos has the same line\n * number\n * if there are 2 range arguments, then check if pos is in between the two\n * range arguments.\n */\n function isInRange(pos, start, end) {\n if (typeof pos != 'number') {\n // Assume it is a cursor position. Get the line number.\n pos = pos.line;\n }\n if (start instanceof Array) {\n return inArray(pos, start);\n } else {\n if (end) {\n return (pos >= start && pos <= end);\n } else {\n return pos == start;\n }\n }\n }\n function getUserVisibleLines(cm) {\n var scrollInfo = cm.getScrollInfo();\n var occludeToleranceTop = 6;\n var occludeToleranceBottom = 10;\n var from = cm.coordsChar({left:0, top: occludeToleranceTop + scrollInfo.top}, 'local');\n var bottomY = scrollInfo.clientHeight - occludeToleranceBottom + scrollInfo.top;\n var to = cm.coordsChar({left:0, top: bottomY}, 'local');\n return {top: from.line, bottom: to.line};\n }\n\n var ExCommandDispatcher = function() {\n this.buildCommandMap_();\n };\n ExCommandDispatcher.prototype = {\n processCommand: function(cm, input, opt_params) {\n var that = this;\n cm.operation(function () {\n cm.curOp.isVimOp = true;\n that._processCommand(cm, input, opt_params);\n });\n },\n _processCommand: function(cm, input, opt_params) {\n var vim = cm.state.vim;\n var commandHistoryRegister = vimGlobalState.registerController.getRegister(':');\n var previousCommand = commandHistoryRegister.toString();\n if (vim.visualMode) {\n exitVisualMode(cm);\n }\n var inputStream = new CodeMirror.StringStream(input);\n // update \": with the latest command whether valid or invalid\n commandHistoryRegister.setText(input);\n var params = opt_params || {};\n params.input = input;\n try {\n this.parseInput_(cm, inputStream, params);\n } catch(e) {\n showConfirm(cm, e);\n throw e;\n }\n var command;\n var commandName;\n if (!params.commandName) {\n // If only a line range is defined, move to the line.\n if (params.line !== undefined) {\n commandName = 'move';\n }\n } else {\n command = this.matchCommand_(params.commandName);\n if (command) {\n commandName = command.name;\n if (command.excludeFromCommandHistory) {\n commandHistoryRegister.setText(previousCommand);\n }\n this.parseCommandArgs_(inputStream, params, command);\n if (command.type == 'exToKey') {\n // Handle Ex to Key mapping.\n for (var i = 0; i < command.toKeys.length; i++) {\n CodeMirror.Vim.handleKey(cm, command.toKeys[i], 'mapping');\n }\n return;\n } else if (command.type == 'exToEx') {\n // Handle Ex to Ex mapping.\n this.processCommand(cm, command.toInput);\n return;\n }\n }\n }\n if (!commandName) {\n showConfirm(cm, 'Not an editor command \":' + input + '\"');\n return;\n }\n try {\n exCommands[commandName](cm, params);\n // Possibly asynchronous commands (e.g. substitute, which might have a\n // user confirmation), are responsible for calling the callback when\n // done. All others have it taken care of for them here.\n if ((!command || !command.possiblyAsync) && params.callback) {\n params.callback();\n }\n } catch(e) {\n showConfirm(cm, e);\n throw e;\n }\n },\n parseInput_: function(cm, inputStream, result) {\n inputStream.eatWhile(':');\n // Parse range.\n if (inputStream.eat('%')) {\n result.line = cm.firstLine();\n result.lineEnd = cm.lastLine();\n } else {\n result.line = this.parseLineSpec_(cm, inputStream);\n if (result.line !== undefined && inputStream.eat(',')) {\n result.lineEnd = this.parseLineSpec_(cm, inputStream);\n }\n }\n\n // Parse command name.\n var commandMatch = inputStream.match(/^(\\w+)/);\n if (commandMatch) {\n result.commandName = commandMatch[1];\n } else {\n result.commandName = inputStream.match(/.*/)[0];\n }\n\n return result;\n },\n parseLineSpec_: function(cm, inputStream) {\n var numberMatch = inputStream.match(/^(\\d+)/);\n if (numberMatch) {\n return parseInt(numberMatch[1], 10) - 1;\n }\n switch (inputStream.next()) {\n case '.':\n return cm.getCursor().line;\n case '$':\n return cm.lastLine();\n case '\\'':\n var mark = cm.state.vim.marks[inputStream.next()];\n if (mark && mark.find()) {\n return mark.find().line;\n }\n throw new Error('Mark not set');\n default:\n inputStream.backUp(1);\n return undefined;\n }\n },\n parseCommandArgs_: function(inputStream, params, command) {\n if (inputStream.eol()) {\n return;\n }\n params.argString = inputStream.match(/.*/)[0];\n // Parse command-line arguments\n var delim = command.argDelimiter || /\\s+/;\n var args = trim(params.argString).split(delim);\n if (args.length && args[0]) {\n params.args = args;\n }\n },\n matchCommand_: function(commandName) {\n // Return the command in the command map that matches the shortest\n // prefix of the passed in command name. The match is guaranteed to be\n // unambiguous if the defaultExCommandMap's shortNames are set up\n // correctly. (see @code{defaultExCommandMap}).\n for (var i = commandName.length; i > 0; i--) {\n var prefix = commandName.substring(0, i);\n if (this.commandMap_[prefix]) {\n var command = this.commandMap_[prefix];\n if (command.name.indexOf(commandName) === 0) {\n return command;\n }\n }\n }\n return null;\n },\n buildCommandMap_: function() {\n this.commandMap_ = {};\n for (var i = 0; i < defaultExCommandMap.length; i++) {\n var command = defaultExCommandMap[i];\n var key = command.shortName || command.name;\n this.commandMap_[key] = command;\n }\n },\n map: function(lhs, rhs, ctx) {\n if (lhs != ':' && lhs.charAt(0) == ':') {\n if (ctx) { throw Error('Mode not supported for ex mappings'); }\n var commandName = lhs.substring(1);\n if (rhs != ':' && rhs.charAt(0) == ':') {\n // Ex to Ex mapping\n this.commandMap_[commandName] = {\n name: commandName,\n type: 'exToEx',\n toInput: rhs.substring(1),\n user: true\n };\n } else {\n // Ex to key mapping\n this.commandMap_[commandName] = {\n name: commandName,\n type: 'exToKey',\n toKeys: rhs,\n user: true\n };\n }\n } else {\n if (rhs != ':' && rhs.charAt(0) == ':') {\n // Key to Ex mapping.\n var mapping = {\n keys: lhs,\n type: 'keyToEx',\n exArgs: { input: rhs.substring(1) },\n user: true};\n if (ctx) { mapping.context = ctx; }\n defaultKeymap.unshift(mapping);\n } else {\n // Key to key mapping\n var mapping = {\n keys: lhs,\n type: 'keyToKey',\n toKeys: rhs,\n user: true\n };\n if (ctx) { mapping.context = ctx; }\n defaultKeymap.unshift(mapping);\n }\n }\n },\n unmap: function(lhs, ctx) {\n if (lhs != ':' && lhs.charAt(0) == ':') {\n // Ex to Ex or Ex to key mapping\n if (ctx) { throw Error('Mode not supported for ex mappings'); }\n var commandName = lhs.substring(1);\n if (this.commandMap_[commandName] && this.commandMap_[commandName].user) {\n delete this.commandMap_[commandName];\n return;\n }\n } else {\n // Key to Ex or key to key mapping\n var keys = lhs;\n for (var i = 0; i < defaultKeymap.length; i++) {\n if (keys == defaultKeymap[i].keys\n && defaultKeymap[i].context === ctx\n && defaultKeymap[i].user) {\n defaultKeymap.splice(i, 1);\n return;\n }\n }\n }\n throw Error('No such mapping.');\n }\n };\n\n var exCommands = {\n colorscheme: function(cm, params) {\n if (!params.args || params.args.length < 1) {\n showConfirm(cm, cm.getOption('theme'));\n return;\n }\n cm.setOption('theme', params.args[0]);\n },\n map: function(cm, params, ctx) {\n var mapArgs = params.args;\n if (!mapArgs || mapArgs.length < 2) {\n if (cm) {\n showConfirm(cm, 'Invalid mapping: ' + params.input);\n }\n return;\n }\n exCommandDispatcher.map(mapArgs[0], mapArgs[1], ctx);\n },\n imap: function(cm, params) { this.map(cm, params, 'insert'); },\n nmap: function(cm, params) { this.map(cm, params, 'normal'); },\n vmap: function(cm, params) { this.map(cm, params, 'visual'); },\n unmap: function(cm, params, ctx) {\n var mapArgs = params.args;\n if (!mapArgs || mapArgs.length < 1) {\n if (cm) {\n showConfirm(cm, 'No such mapping: ' + params.input);\n }\n return;\n }\n exCommandDispatcher.unmap(mapArgs[0], ctx);\n },\n move: function(cm, params) {\n commandDispatcher.processCommand(cm, cm.state.vim, {\n type: 'motion',\n motion: 'moveToLineOrEdgeOfDocument',\n motionArgs: { forward: false, explicitRepeat: true,\n linewise: true },\n repeatOverride: params.line+1});\n },\n set: function(cm, params) {\n var setArgs = params.args;\n // Options passed through to the setOption/getOption calls. May be passed in by the\n // local/global versions of the set command\n var setCfg = params.setCfg || {};\n if (!setArgs || setArgs.length < 1) {\n if (cm) {\n showConfirm(cm, 'Invalid mapping: ' + params.input);\n }\n return;\n }\n var expr = setArgs[0].split('=');\n var optionName = expr[0];\n var value = expr[1];\n var forceGet = false;\n\n if (optionName.charAt(optionName.length - 1) == '?') {\n // If post-fixed with ?, then the set is actually a get.\n if (value) { throw Error('Trailing characters: ' + params.argString); }\n optionName = optionName.substring(0, optionName.length - 1);\n forceGet = true;\n }\n if (value === undefined && optionName.substring(0, 2) == 'no') {\n // To set boolean options to false, the option name is prefixed with\n // 'no'.\n optionName = optionName.substring(2);\n value = false;\n }\n\n var optionIsBoolean = options[optionName] && options[optionName].type == 'boolean';\n if (optionIsBoolean && value == undefined) {\n // Calling set with a boolean option sets it to true.\n value = true;\n }\n // If no value is provided, then we assume this is a get.\n if (!optionIsBoolean && value === undefined || forceGet) {\n var oldValue = getOption(optionName, cm, setCfg);\n if (oldValue === true || oldValue === false) {\n showConfirm(cm, ' ' + (oldValue ? '' : 'no') + optionName);\n } else {\n showConfirm(cm, ' ' + optionName + '=' + oldValue);\n }\n } else {\n setOption(optionName, value, cm, setCfg);\n }\n },\n setlocal: function (cm, params) {\n // setCfg is passed through to setOption\n params.setCfg = {scope: 'local'};\n this.set(cm, params);\n },\n setglobal: function (cm, params) {\n // setCfg is passed through to setOption\n params.setCfg = {scope: 'global'};\n this.set(cm, params);\n },\n registers: function(cm, params) {\n var regArgs = params.args;\n var registers = vimGlobalState.registerController.registers;\n var regInfo = '----------Registers----------<br><br>';\n if (!regArgs) {\n for (var registerName in registers) {\n var text = registers[registerName].toString();\n if (text.length) {\n regInfo += '\"' + registerName + ' ' + text + '<br>';\n }\n }\n } else {\n var registerName;\n regArgs = regArgs.join('');\n for (var i = 0; i < regArgs.length; i++) {\n registerName = regArgs.charAt(i);\n if (!vimGlobalState.registerController.isValidRegister(registerName)) {\n continue;\n }\n var register = registers[registerName] || new Register();\n regInfo += '\"' + registerName + ' ' + register.toString() + '<br>';\n }\n }\n showConfirm(cm, regInfo);\n },\n sort: function(cm, params) {\n var reverse, ignoreCase, unique, number;\n function parseArgs() {\n if (params.argString) {\n var args = new CodeMirror.StringStream(params.argString);\n if (args.eat('!')) { reverse = true; }\n if (args.eol()) { return; }\n if (!args.eatSpace()) { return 'Invalid arguments'; }\n var opts = args.match(/[a-z]+/);\n if (opts) {\n opts = opts[0];\n ignoreCase = opts.indexOf('i') != -1;\n unique = opts.indexOf('u') != -1;\n var decimal = opts.indexOf('d') != -1 && 1;\n var hex = opts.indexOf('x') != -1 && 1;\n var octal = opts.indexOf('o') != -1 && 1;\n if (decimal + hex + octal > 1) { return 'Invalid arguments'; }\n number = decimal && 'decimal' || hex && 'hex' || octal && 'octal';\n }\n if (args.match(/\\/.*\\//)) { return 'patterns not supported'; }\n }\n }\n var err = parseArgs();\n if (err) {\n showConfirm(cm, err + ': ' + params.argString);\n return;\n }\n var lineStart = params.line || cm.firstLine();\n var lineEnd = params.lineEnd || params.line || cm.lastLine();\n if (lineStart == lineEnd) { return; }\n var curStart = Pos(lineStart, 0);\n var curEnd = Pos(lineEnd, lineLength(cm, lineEnd));\n var text = cm.getRange(curStart, curEnd).split('\\n');\n var numberRegex = (number == 'decimal') ? /(-?)([\\d]+)/ :\n (number == 'hex') ? /(-?)(?:0x)?([0-9a-f]+)/i :\n (number == 'octal') ? /([0-7]+)/ : null;\n var radix = (number == 'decimal') ? 10 : (number == 'hex') ? 16 : (number == 'octal') ? 8 : null;\n var numPart = [], textPart = [];\n if (number) {\n for (var i = 0; i < text.length; i++) {\n if (numberRegex.exec(text[i])) {\n numPart.push(text[i]);\n } else {\n textPart.push(text[i]);\n }\n }\n } else {\n textPart = text;\n }\n function compareFn(a, b) {\n if (reverse) { var tmp; tmp = a; a = b; b = tmp; }\n if (ignoreCase) { a = a.toLowerCase(); b = b.toLowerCase(); }\n var anum = number && numberRegex.exec(a);\n var bnum = number && numberRegex.exec(b);\n if (!anum) { return a < b ? -1 : 1; }\n anum = parseInt((anum[1] + anum[2]).toLowerCase(), radix);\n bnum = parseInt((bnum[1] + bnum[2]).toLowerCase(), radix);\n return anum - bnum;\n }\n numPart.sort(compareFn);\n textPart.sort(compareFn);\n text = (!reverse) ? textPart.concat(numPart) : numPart.concat(textPart);\n if (unique) { // Remove duplicate lines\n var textOld = text;\n var lastLine;\n text = [];\n for (var i = 0; i < textOld.length; i++) {\n if (textOld[i] != lastLine) {\n text.push(textOld[i]);\n }\n lastLine = textOld[i];\n }\n }\n cm.replaceRange(text.join('\\n'), curStart, curEnd);\n },\n global: function(cm, params) {\n // a global command is of the form\n // :[range]g/pattern/[cmd]\n // argString holds the string /pattern/[cmd]\n var argString = params.argString;\n if (!argString) {\n showConfirm(cm, 'Regular Expression missing from global');\n return;\n }\n // range is specified here\n var lineStart = (params.line !== undefined) ? params.line : cm.firstLine();\n var lineEnd = params.lineEnd || params.line || cm.lastLine();\n // get the tokens from argString\n var tokens = splitBySlash(argString);\n var regexPart = argString, cmd;\n if (tokens.length) {\n regexPart = tokens[0];\n cmd = tokens.slice(1, tokens.length).join('/');\n }\n if (regexPart) {\n // If regex part is empty, then use the previous query. Otherwise\n // use the regex part as the new query.\n try {\n updateSearchQuery(cm, regexPart, true /** ignoreCase */,\n true /** smartCase */);\n } catch (e) {\n showConfirm(cm, 'Invalid regex: ' + regexPart);\n return;\n }\n }\n // now that we have the regexPart, search for regex matches in the\n // specified range of lines\n var query = getSearchState(cm).getQuery();\n var matchedLines = [], content = '';\n for (var i = lineStart; i <= lineEnd; i++) {\n var matched = query.test(cm.getLine(i));\n if (matched) {\n matchedLines.push(i+1);\n content+= cm.getLine(i) + '<br>';\n }\n }\n // if there is no [cmd], just display the list of matched lines\n if (!cmd) {\n showConfirm(cm, content);\n return;\n }\n var index = 0;\n var nextCommand = function() {\n if (index < matchedLines.length) {\n var command = matchedLines[index] + cmd;\n exCommandDispatcher.processCommand(cm, command, {\n callback: nextCommand\n });\n }\n index++;\n };\n nextCommand();\n },\n substitute: function(cm, params) {\n if (!cm.getSearchCursor) {\n throw new Error('Search feature not available. Requires searchcursor.js or ' +\n 'any other getSearchCursor implementation.');\n }\n var argString = params.argString;\n var tokens = argString ? splitBySlash(argString) : [];\n var regexPart, replacePart = '', trailing, flagsPart, count;\n var confirm = false; // Whether to confirm each replace.\n var global = false; // True to replace all instances on a line, false to replace only 1.\n if (tokens.length) {\n regexPart = tokens[0];\n replacePart = tokens[1];\n if (replacePart !== undefined) {\n if (getOption('pcre')) {\n replacePart = unescapeRegexReplace(replacePart);\n } else {\n replacePart = translateRegexReplace(replacePart);\n }\n vimGlobalState.lastSubstituteReplacePart = replacePart;\n }\n trailing = tokens[2] ? tokens[2].split(' ') : [];\n } else {\n // either the argString is empty or its of the form ' hello/world'\n // actually splitBySlash returns a list of tokens\n // only if the string starts with a '/'\n if (argString && argString.length) {\n showConfirm(cm, 'Substitutions should be of the form ' +\n ':s/pattern/replace/');\n return;\n }\n }\n // After the 3rd slash, we can have flags followed by a space followed\n // by count.\n if (trailing) {\n flagsPart = trailing[0];\n count = parseInt(trailing[1]);\n if (flagsPart) {\n if (flagsPart.indexOf('c') != -1) {\n confirm = true;\n flagsPart.replace('c', '');\n }\n if (flagsPart.indexOf('g') != -1) {\n global = true;\n flagsPart.replace('g', '');\n }\n regexPart = regexPart + '/' + flagsPart;\n }\n }\n if (regexPart) {\n // If regex part is empty, then use the previous query. Otherwise use\n // the regex part as the new query.\n try {\n updateSearchQuery(cm, regexPart, true /** ignoreCase */,\n true /** smartCase */);\n } catch (e) {\n showConfirm(cm, 'Invalid regex: ' + regexPart);\n return;\n }\n }\n replacePart = replacePart || vimGlobalState.lastSubstituteReplacePart;\n if (replacePart === undefined) {\n showConfirm(cm, 'No previous substitute regular expression');\n return;\n }\n var state = getSearchState(cm);\n var query = state.getQuery();\n var lineStart = (params.line !== undefined) ? params.line : cm.getCursor().line;\n var lineEnd = params.lineEnd || lineStart;\n if (lineStart == cm.firstLine() && lineEnd == cm.lastLine()) {\n lineEnd = Infinity;\n }\n if (count) {\n lineStart = lineEnd;\n lineEnd = lineStart + count - 1;\n }\n var startPos = clipCursorToContent(cm, Pos(lineStart, 0));\n var cursor = cm.getSearchCursor(query, startPos);\n doReplace(cm, confirm, global, lineStart, lineEnd, cursor, query, replacePart, params.callback);\n },\n redo: CodeMirror.commands.redo,\n undo: CodeMirror.commands.undo,\n write: function(cm) {\n if (CodeMirror.commands.save) {\n // If a save command is defined, call it.\n CodeMirror.commands.save(cm);\n } else {\n // Saves to text area if no save command is defined.\n cm.save();\n }\n },\n nohlsearch: function(cm) {\n clearSearchHighlight(cm);\n },\n delmarks: function(cm, params) {\n if (!params.argString || !trim(params.argString)) {\n showConfirm(cm, 'Argument required');\n return;\n }\n\n var state = cm.state.vim;\n var stream = new CodeMirror.StringStream(trim(params.argString));\n while (!stream.eol()) {\n stream.eatSpace();\n\n // Record the streams position at the beginning of the loop for use\n // in error messages.\n var count = stream.pos;\n\n if (!stream.match(/[a-zA-Z]/, false)) {\n showConfirm(cm, 'Invalid argument: ' + params.argString.substring(count));\n return;\n }\n\n var sym = stream.next();\n // Check if this symbol is part of a range\n if (stream.match('-', true)) {\n // This symbol is part of a range.\n\n // The range must terminate at an alphabetic character.\n if (!stream.match(/[a-zA-Z]/, false)) {\n showConfirm(cm, 'Invalid argument: ' + params.argString.substring(count));\n return;\n }\n\n var startMark = sym;\n var finishMark = stream.next();\n // The range must terminate at an alphabetic character which\n // shares the same case as the start of the range.\n if (isLowerCase(startMark) && isLowerCase(finishMark) ||\n isUpperCase(startMark) && isUpperCase(finishMark)) {\n var start = startMark.charCodeAt(0);\n var finish = finishMark.charCodeAt(0);\n if (start >= finish) {\n showConfirm(cm, 'Invalid argument: ' + params.argString.substring(count));\n return;\n }\n\n // Because marks are always ASCII values, and we have\n // determined that they are the same case, we can use\n // their char codes to iterate through the defined range.\n for (var j = 0; j <= finish - start; j++) {\n var mark = String.fromCharCode(start + j);\n delete state.marks[mark];\n }\n } else {\n showConfirm(cm, 'Invalid argument: ' + startMark + '-');\n return;\n }\n } else {\n // This symbol is a valid mark, and is not part of a range.\n delete state.marks[sym];\n }\n }\n }\n };\n\n var exCommandDispatcher = new ExCommandDispatcher();\n\n /**\n * @param {CodeMirror} cm CodeMirror instance we are in.\n * @param {boolean} confirm Whether to confirm each replace.\n * @param {Cursor} lineStart Line to start replacing from.\n * @param {Cursor} lineEnd Line to stop replacing at.\n * @param {RegExp} query Query for performing matches with.\n * @param {string} replaceWith Text to replace matches with. May contain $1,\n * $2, etc for replacing captured groups using Javascript replace.\n * @param {function()} callback A callback for when the replace is done.\n */\n function doReplace(cm, confirm, global, lineStart, lineEnd, searchCursor, query,\n replaceWith, callback) {\n // Set up all the functions.\n cm.state.vim.exMode = true;\n var done = false;\n var lastPos = searchCursor.from();\n function replaceAll() {\n cm.operation(function() {\n while (!done) {\n replace();\n next();\n }\n stop();\n });\n }\n function replace() {\n var text = cm.getRange(searchCursor.from(), searchCursor.to());\n var newText = text.replace(query, replaceWith);\n searchCursor.replace(newText);\n }\n function next() {\n // The below only loops to skip over multiple occurrences on the same\n // line when 'global' is not true.\n while(searchCursor.findNext() &&\n isInRange(searchCursor.from(), lineStart, lineEnd)) {\n if (!global && lastPos && searchCursor.from().line == lastPos.line) {\n continue;\n }\n cm.scrollIntoView(searchCursor.from(), 30);\n cm.setSelection(searchCursor.from(), searchCursor.to());\n lastPos = searchCursor.from();\n done = false;\n return;\n }\n done = true;\n }\n function stop(close) {\n if (close) { close(); }\n cm.focus();\n if (lastPos) {\n cm.setCursor(lastPos);\n var vim = cm.state.vim;\n vim.exMode = false;\n vim.lastHPos = vim.lastHSPos = lastPos.ch;\n }\n if (callback) { callback(); }\n }\n function onPromptKeyDown(e, _value, close) {\n // Swallow all keys.\n CodeMirror.e_stop(e);\n var keyName = CodeMirror.keyName(e);\n switch (keyName) {\n case 'Y':\n replace(); next(); break;\n case 'N':\n next(); break;\n case 'A':\n // replaceAll contains a call to close of its own. We don't want it\n // to fire too early or multiple times.\n var savedCallback = callback;\n callback = undefined;\n cm.operation(replaceAll);\n callback = savedCallback;\n break;\n case 'L':\n replace();\n // fall through and exit.\n case 'Q':\n case 'Esc':\n case 'Ctrl-C':\n case 'Ctrl-[':\n stop(close);\n break;\n }\n if (done) { stop(close); }\n return true;\n }\n\n // Actually do replace.\n next();\n if (done) {\n showConfirm(cm, 'No matches for ' + query.source);\n return;\n }\n if (!confirm) {\n replaceAll();\n if (callback) { callback(); };\n return;\n }\n showPrompt(cm, {\n prefix: 'replace with <strong>' + replaceWith + '</strong> (y/n/a/q/l)',\n onKeyDown: onPromptKeyDown\n });\n }\n\n CodeMirror.keyMap.vim = {\n attach: attachVimMap,\n detach: detachVimMap,\n call: cmKey\n };\n\n function exitInsertMode(cm) {\n var vim = cm.state.vim;\n var macroModeState = vimGlobalState.macroModeState;\n var insertModeChangeRegister = vimGlobalState.registerController.getRegister('.');\n var isPlaying = macroModeState.isPlaying;\n var lastChange = macroModeState.lastInsertModeChanges;\n // In case of visual block, the insertModeChanges are not saved as a\n // single word, so we convert them to a single word\n // so as to update the \". register as expected in real vim.\n var text = [];\n if (!isPlaying) {\n var selLength = lastChange.inVisualBlock ? vim.lastSelection.visualBlock.height : 1;\n var changes = lastChange.changes;\n var text = [];\n var i = 0;\n // In case of multiple selections in blockwise visual,\n // the inserted text, for example: 'f<Backspace>oo', is stored as\n // 'f', 'f', InsertModeKey 'o', 'o', 'o', 'o'. (if you have a block with 2 lines).\n // We push the contents of the changes array as per the following:\n // 1. In case of InsertModeKey, just increment by 1.\n // 2. In case of a character, jump by selLength (2 in the example).\n while (i < changes.length) {\n // This loop will convert 'ff<bs>oooo' to 'f<bs>oo'.\n text.push(changes[i]);\n if (changes[i] instanceof InsertModeKey) {\n i++;\n } else {\n i+= selLength;\n }\n }\n lastChange.changes = text;\n cm.off('change', onChange);\n CodeMirror.off(cm.getInputField(), 'keydown', onKeyEventTargetKeyDown);\n }\n if (!isPlaying && vim.insertModeRepeat > 1) {\n // Perform insert mode repeat for commands like 3,a and 3,o.\n repeatLastEdit(cm, vim, vim.insertModeRepeat - 1,\n true /** repeatForInsert */);\n vim.lastEditInputState.repeatOverride = vim.insertModeRepeat;\n }\n delete vim.insertModeRepeat;\n vim.insertMode = false;\n cm.setCursor(cm.getCursor().line, cm.getCursor().ch-1);\n cm.setOption('keyMap', 'vim');\n cm.setOption('disableInput', true);\n cm.toggleOverwrite(false); // exit replace mode if we were in it.\n // update the \". register before exiting insert mode\n insertModeChangeRegister.setText(lastChange.changes.join(''));\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"normal\"});\n if (macroModeState.isRecording) {\n logInsertModeChange(macroModeState);\n }\n }\n\n function _mapCommand(command) {\n defaultKeymap.unshift(command);\n }\n\n function mapCommand(keys, type, name, args, extra) {\n var command = {keys: keys, type: type};\n command[type] = name;\n command[type + \"Args\"] = args;\n for (var key in extra)\n command[key] = extra[key];\n _mapCommand(command);\n }\n\n // The timeout in milliseconds for the two-character ESC keymap should be\n // adjusted according to your typing speed to prevent false positives.\n defineOption('insertModeEscKeysTimeout', 200, 'number');\n\n CodeMirror.keyMap['vim-insert'] = {\n // TODO: override navigation keys so that Esc will cancel automatic\n // indentation from o, O, i_<CR>\n 'Ctrl-N': 'autocomplete',\n 'Ctrl-P': 'autocomplete',\n 'Enter': function(cm) {\n var fn = CodeMirror.commands.newlineAndIndentContinueComment ||\n CodeMirror.commands.newlineAndIndent;\n fn(cm);\n },\n fallthrough: ['default'],\n attach: attachVimMap,\n detach: detachVimMap,\n call: cmKey\n };\n\n CodeMirror.keyMap['vim-replace'] = {\n 'Backspace': 'goCharLeft',\n fallthrough: ['vim-insert'],\n attach: attachVimMap,\n detach: detachVimMap,\n call: cmKey\n };\n\n function executeMacroRegister(cm, vim, macroModeState, registerName) {\n var register = vimGlobalState.registerController.getRegister(registerName);\n if (registerName == ':') {\n // Read-only register containing last Ex command.\n if (register.keyBuffer[0]) {\n exCommandDispatcher.processCommand(cm, register.keyBuffer[0]);\n }\n macroModeState.isPlaying = false;\n return;\n }\n var keyBuffer = register.keyBuffer;\n var imc = 0;\n macroModeState.isPlaying = true;\n macroModeState.replaySearchQueries = register.searchQueries.slice(0);\n for (var i = 0; i < keyBuffer.length; i++) {\n var text = keyBuffer[i];\n var match, key;\n while (text) {\n // Pull off one command key, which is either a single character\n // or a special sequence wrapped in '<' and '>', e.g. '<Space>'.\n match = (/<\\w+-.+?>|<\\w+>|./).exec(text);\n key = match[0];\n text = text.substring(match.index + key.length);\n CodeMirror.Vim.handleKey(cm, key, 'macro');\n if (vim.insertMode) {\n var changes = register.insertModeChanges[imc++].changes;\n vimGlobalState.macroModeState.lastInsertModeChanges.changes =\n changes;\n repeatInsertModeChanges(cm, changes, 1);\n exitInsertMode(cm);\n }\n }\n };\n macroModeState.isPlaying = false;\n }\n\n function logKey(macroModeState, key) {\n if (macroModeState.isPlaying) { return; }\n var registerName = macroModeState.latestRegister;\n var register = vimGlobalState.registerController.getRegister(registerName);\n if (register) {\n register.pushText(key);\n }\n }\n\n function logInsertModeChange(macroModeState) {\n if (macroModeState.isPlaying) { return; }\n var registerName = macroModeState.latestRegister;\n var register = vimGlobalState.registerController.getRegister(registerName);\n if (register && register.pushInsertModeChanges) {\n register.pushInsertModeChanges(macroModeState.lastInsertModeChanges);\n }\n }\n\n function logSearchQuery(macroModeState, query) {\n if (macroModeState.isPlaying) { return; }\n var registerName = macroModeState.latestRegister;\n var register = vimGlobalState.registerController.getRegister(registerName);\n if (register && register.pushSearchQuery) {\n register.pushSearchQuery(query);\n }\n }\n\n /**\n * Listens for changes made in insert mode.\n * Should only be active in insert mode.\n */\n function onChange(_cm, changeObj) {\n var macroModeState = vimGlobalState.macroModeState;\n var lastChange = macroModeState.lastInsertModeChanges;\n if (!macroModeState.isPlaying) {\n while(changeObj) {\n lastChange.expectCursorActivityForChange = true;\n if (changeObj.origin == '+input' || changeObj.origin == 'paste'\n || changeObj.origin === undefined /* only in testing */) {\n var text = changeObj.text.join('\\n');\n lastChange.changes.push(text);\n }\n // Change objects may be chained with next.\n changeObj = changeObj.next;\n }\n }\n }\n\n /**\n * Listens for any kind of cursor activity on CodeMirror.\n */\n function onCursorActivity(cm) {\n var vim = cm.state.vim;\n if (vim.insertMode) {\n // Tracking cursor activity in insert mode (for macro support).\n var macroModeState = vimGlobalState.macroModeState;\n if (macroModeState.isPlaying) { return; }\n var lastChange = macroModeState.lastInsertModeChanges;\n if (lastChange.expectCursorActivityForChange) {\n lastChange.expectCursorActivityForChange = false;\n } else {\n // Cursor moved outside the context of an edit. Reset the change.\n lastChange.changes = [];\n }\n } else if (!cm.curOp.isVimOp) {\n handleExternalSelection(cm, vim);\n }\n if (vim.visualMode) {\n updateFakeCursor(cm);\n }\n }\n function updateFakeCursor(cm) {\n var vim = cm.state.vim;\n var from = clipCursorToContent(cm, copyCursor(vim.sel.head));\n var to = offsetCursor(from, 0, 1);\n if (vim.fakeCursor) {\n vim.fakeCursor.clear();\n }\n vim.fakeCursor = cm.markText(from, to, {className: 'cm-animate-fat-cursor'});\n }\n function handleExternalSelection(cm, vim) {\n var anchor = cm.getCursor('anchor');\n var head = cm.getCursor('head');\n // Enter or exit visual mode to match mouse selection.\n if (vim.visualMode && !cm.somethingSelected()) {\n exitVisualMode(cm, false);\n } else if (!vim.visualMode && !vim.insertMode && cm.somethingSelected()) {\n vim.visualMode = true;\n vim.visualLine = false;\n CodeMirror.signal(cm, \"vim-mode-change\", {mode: \"visual\"});\n }\n if (vim.visualMode) {\n // Bind CodeMirror selection model to vim selection model.\n // Mouse selections are considered visual characterwise.\n var headOffset = !cursorIsBefore(head, anchor) ? -1 : 0;\n var anchorOffset = cursorIsBefore(head, anchor) ? -1 : 0;\n head = offsetCursor(head, 0, headOffset);\n anchor = offsetCursor(anchor, 0, anchorOffset);\n vim.sel = {\n anchor: anchor,\n head: head\n };\n updateMark(cm, vim, '<', cursorMin(head, anchor));\n updateMark(cm, vim, '>', cursorMax(head, anchor));\n } else if (!vim.insertMode) {\n // Reset lastHPos if selection was modified by something outside of vim mode e.g. by mouse.\n vim.lastHPos = cm.getCursor().ch;\n }\n }\n\n /** Wrapper for special keys pressed in insert mode */\n function InsertModeKey(keyName) {\n this.keyName = keyName;\n }\n\n /**\n * Handles raw key down events from the text area.\n * - Should only be active in insert mode.\n * - For recording deletes in insert mode.\n */\n function onKeyEventTargetKeyDown(e) {\n var macroModeState = vimGlobalState.macroModeState;\n var lastChange = macroModeState.lastInsertModeChanges;\n var keyName = CodeMirror.keyName(e);\n if (!keyName) { return; }\n function onKeyFound() {\n lastChange.changes.push(new InsertModeKey(keyName));\n return true;\n }\n if (keyName.indexOf('Delete') != -1 || keyName.indexOf('Backspace') != -1) {\n CodeMirror.lookupKey(keyName, 'vim-insert', onKeyFound);\n }\n }\n\n /**\n * Repeats the last edit, which includes exactly 1 command and at most 1\n * insert. Operator and motion commands are read from lastEditInputState,\n * while action commands are read from lastEditActionCommand.\n *\n * If repeatForInsert is true, then the function was called by\n * exitInsertMode to repeat the insert mode changes the user just made. The\n * corresponding enterInsertMode call was made with a count.\n */\n function repeatLastEdit(cm, vim, repeat, repeatForInsert) {\n var macroModeState = vimGlobalState.macroModeState;\n macroModeState.isPlaying = true;\n var isAction = !!vim.lastEditActionCommand;\n var cachedInputState = vim.inputState;\n function repeatCommand() {\n if (isAction) {\n commandDispatcher.processAction(cm, vim, vim.lastEditActionCommand);\n } else {\n commandDispatcher.evalInput(cm, vim);\n }\n }\n function repeatInsert(repeat) {\n if (macroModeState.lastInsertModeChanges.changes.length > 0) {\n // For some reason, repeat cw in desktop VIM does not repeat\n // insert mode changes. Will conform to that behavior.\n repeat = !vim.lastEditActionCommand ? 1 : repeat;\n var changeObject = macroModeState.lastInsertModeChanges;\n repeatInsertModeChanges(cm, changeObject.changes, repeat);\n }\n }\n vim.inputState = vim.lastEditInputState;\n if (isAction && vim.lastEditActionCommand.interlaceInsertRepeat) {\n // o and O repeat have to be interlaced with insert repeats so that the\n // insertions appear on separate lines instead of the last line.\n for (var i = 0; i < repeat; i++) {\n repeatCommand();\n repeatInsert(1);\n }\n } else {\n if (!repeatForInsert) {\n // Hack to get the cursor to end up at the right place. If I is\n // repeated in insert mode repeat, cursor will be 1 insert\n // change set left of where it should be.\n repeatCommand();\n }\n repeatInsert(repeat);\n }\n vim.inputState = cachedInputState;\n if (vim.insertMode && !repeatForInsert) {\n // Don't exit insert mode twice. If repeatForInsert is set, then we\n // were called by an exitInsertMode call lower on the stack.\n exitInsertMode(cm);\n }\n macroModeState.isPlaying = false;\n };\n\n function repeatInsertModeChanges(cm, changes, repeat) {\n function keyHandler(binding) {\n if (typeof binding == 'string') {\n CodeMirror.commands[binding](cm);\n } else {\n binding(cm);\n }\n return true;\n }\n var head = cm.getCursor('head');\n var inVisualBlock = vimGlobalState.macroModeState.lastInsertModeChanges.inVisualBlock;\n if (inVisualBlock) {\n // Set up block selection again for repeating the changes.\n var vim = cm.state.vim;\n var lastSel = vim.lastSelection;\n var offset = getOffset(lastSel.anchor, lastSel.head);\n selectForInsert(cm, head, offset.line + 1);\n repeat = cm.listSelections().length;\n cm.setCursor(head);\n }\n for (var i = 0; i < repeat; i++) {\n if (inVisualBlock) {\n cm.setCursor(offsetCursor(head, i, 0));\n }\n for (var j = 0; j < changes.length; j++) {\n var change = changes[j];\n if (change instanceof InsertModeKey) {\n CodeMirror.lookupKey(change.keyName, 'vim-insert', keyHandler);\n } else {\n var cur = cm.getCursor();\n cm.replaceRange(change, cur, cur);\n }\n }\n }\n if (inVisualBlock) {\n cm.setCursor(offsetCursor(head, 0, 1));\n }\n }\n\n resetVimGlobalState();\n return vimApi;\n };\n // Initialize Vim and make it available as an API.\n CodeMirror.Vim = Vim();\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/keymap/sublime.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/keymap/sublime.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n// A rough approximation of Sublime Text's keybindings\n// Depends on addon/search/searchcursor.js and optionally addon/dialog/dialogs.js\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../lib/codemirror\"), require(\"../addon/search/searchcursor\"), require(\"../addon/edit/matchbrackets\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../lib/codemirror\", \"../addon/search/searchcursor\", \"../addon/edit/matchbrackets\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n\n var map = CodeMirror.keyMap.sublime = {fallthrough: \"default\"};\n var cmds = CodeMirror.commands;\n var Pos = CodeMirror.Pos;\n var mac = CodeMirror.keyMap[\"default\"] == CodeMirror.keyMap.macDefault;\n var ctrl = mac ? \"Cmd-\" : \"Ctrl-\";\n\n // This is not exactly Sublime's algorithm. I couldn't make heads or tails of that.\n function findPosSubword(doc, start, dir) {\n if (dir < 0 && start.ch == 0) return doc.clipPos(Pos(start.line - 1));\n var line = doc.getLine(start.line);\n if (dir > 0 && start.ch >= line.length) return doc.clipPos(Pos(start.line + 1, 0));\n var state = \"start\", type;\n for (var pos = start.ch, e = dir < 0 ? 0 : line.length, i = 0; pos != e; pos += dir, i++) {\n var next = line.charAt(dir < 0 ? pos - 1 : pos);\n var cat = next != \"_\" && CodeMirror.isWordChar(next) ? \"w\" : \"o\";\n if (cat == \"w\" && next.toUpperCase() == next) cat = \"W\";\n if (state == \"start\") {\n if (cat != \"o\") { state = \"in\"; type = cat; }\n } else if (state == \"in\") {\n if (type != cat) {\n if (type == \"w\" && cat == \"W\" && dir < 0) pos--;\n if (type == \"W\" && cat == \"w\" && dir > 0) { type = \"w\"; continue; }\n break;\n }\n }\n }\n return Pos(start.line, pos);\n }\n\n function moveSubword(cm, dir) {\n cm.extendSelectionsBy(function(range) {\n if (cm.display.shift || cm.doc.extend || range.empty())\n return findPosSubword(cm.doc, range.head, dir);\n else\n return dir < 0 ? range.from() : range.to();\n });\n }\n\n cmds[map[\"Alt-Left\"] = \"goSubwordLeft\"] = function(cm) { moveSubword(cm, -1); };\n cmds[map[\"Alt-Right\"] = \"goSubwordRight\"] = function(cm) { moveSubword(cm, 1); };\n\n var scrollLineCombo = mac ? \"Ctrl-Alt-\" : \"Ctrl-\";\n\n cmds[map[scrollLineCombo + \"Up\"] = \"scrollLineUp\"] = function(cm) {\n var info = cm.getScrollInfo();\n if (!cm.somethingSelected()) {\n var visibleBottomLine = cm.lineAtHeight(info.top + info.clientHeight, \"local\");\n if (cm.getCursor().line >= visibleBottomLine)\n cm.execCommand(\"goLineUp\");\n }\n cm.scrollTo(null, info.top - cm.defaultTextHeight());\n };\n cmds[map[scrollLineCombo + \"Down\"] = \"scrollLineDown\"] = function(cm) {\n var info = cm.getScrollInfo();\n if (!cm.somethingSelected()) {\n var visibleTopLine = cm.lineAtHeight(info.top, \"local\")+1;\n if (cm.getCursor().line <= visibleTopLine)\n cm.execCommand(\"goLineDown\");\n }\n cm.scrollTo(null, info.top + cm.defaultTextHeight());\n };\n\n cmds[map[\"Shift-\" + ctrl + \"L\"] = \"splitSelectionByLine\"] = function(cm) {\n var ranges = cm.listSelections(), lineRanges = [];\n for (var i = 0; i < ranges.length; i++) {\n var from = ranges[i].from(), to = ranges[i].to();\n for (var line = from.line; line <= to.line; ++line)\n if (!(to.line > from.line && line == to.line && to.ch == 0))\n lineRanges.push({anchor: line == from.line ? from : Pos(line, 0),\n head: line == to.line ? to : Pos(line)});\n }\n cm.setSelections(lineRanges, 0);\n };\n\n map[\"Shift-Tab\"] = \"indentLess\";\n\n cmds[map[\"Esc\"] = \"singleSelectionTop\"] = function(cm) {\n var range = cm.listSelections()[0];\n cm.setSelection(range.anchor, range.head, {scroll: false});\n };\n\n cmds[map[ctrl + \"L\"] = \"selectLine\"] = function(cm) {\n var ranges = cm.listSelections(), extended = [];\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n extended.push({anchor: Pos(range.from().line, 0),\n head: Pos(range.to().line + 1, 0)});\n }\n cm.setSelections(extended);\n };\n\n map[\"Shift-Ctrl-K\"] = \"deleteLine\";\n\n function insertLine(cm, above) {\n if (cm.isReadOnly()) return CodeMirror.Pass\n cm.operation(function() {\n var len = cm.listSelections().length, newSelection = [], last = -1;\n for (var i = 0; i < len; i++) {\n var head = cm.listSelections()[i].head;\n if (head.line <= last) continue;\n var at = Pos(head.line + (above ? 0 : 1), 0);\n cm.replaceRange(\"\\n\", at, null, \"+insertLine\");\n cm.indentLine(at.line, null, true);\n newSelection.push({head: at, anchor: at});\n last = head.line + 1;\n }\n cm.setSelections(newSelection);\n });\n }\n\n cmds[map[ctrl + \"Enter\"] = \"insertLineAfter\"] = function(cm) { return insertLine(cm, false); };\n\n cmds[map[\"Shift-\" + ctrl + \"Enter\"] = \"insertLineBefore\"] = function(cm) { return insertLine(cm, true); };\n\n function wordAt(cm, pos) {\n var start = pos.ch, end = start, line = cm.getLine(pos.line);\n while (start && CodeMirror.isWordChar(line.charAt(start - 1))) --start;\n while (end < line.length && CodeMirror.isWordChar(line.charAt(end))) ++end;\n return {from: Pos(pos.line, start), to: Pos(pos.line, end), word: line.slice(start, end)};\n }\n\n cmds[map[ctrl + \"D\"] = \"selectNextOccurrence\"] = function(cm) {\n var from = cm.getCursor(\"from\"), to = cm.getCursor(\"to\");\n var fullWord = cm.state.sublimeFindFullWord == cm.doc.sel;\n if (CodeMirror.cmpPos(from, to) == 0) {\n var word = wordAt(cm, from);\n if (!word.word) return;\n cm.setSelection(word.from, word.to);\n fullWord = true;\n } else {\n var text = cm.getRange(from, to);\n var query = fullWord ? new RegExp(\"\\\\b\" + text + \"\\\\b\") : text;\n var cur = cm.getSearchCursor(query, to);\n if (cur.findNext()) {\n cm.addSelection(cur.from(), cur.to());\n } else {\n cur = cm.getSearchCursor(query, Pos(cm.firstLine(), 0));\n if (cur.findNext())\n cm.addSelection(cur.from(), cur.to());\n }\n }\n if (fullWord)\n cm.state.sublimeFindFullWord = cm.doc.sel;\n };\n\n var mirror = \"(){}[]\";\n function selectBetweenBrackets(cm) {\n var pos = cm.getCursor(), opening = cm.scanForBracket(pos, -1);\n if (!opening) return;\n for (;;) {\n var closing = cm.scanForBracket(pos, 1);\n if (!closing) return;\n if (closing.ch == mirror.charAt(mirror.indexOf(opening.ch) + 1)) {\n cm.setSelection(Pos(opening.pos.line, opening.pos.ch + 1), closing.pos, false);\n return true;\n }\n pos = Pos(closing.pos.line, closing.pos.ch + 1);\n }\n }\n\n cmds[map[\"Shift-\" + ctrl + \"Space\"] = \"selectScope\"] = function(cm) {\n selectBetweenBrackets(cm) || cm.execCommand(\"selectAll\");\n };\n cmds[map[\"Shift-\" + ctrl + \"M\"] = \"selectBetweenBrackets\"] = function(cm) {\n if (!selectBetweenBrackets(cm)) return CodeMirror.Pass;\n };\n\n cmds[map[ctrl + \"M\"] = \"goToBracket\"] = function(cm) {\n cm.extendSelectionsBy(function(range) {\n var next = cm.scanForBracket(range.head, 1);\n if (next && CodeMirror.cmpPos(next.pos, range.head) != 0) return next.pos;\n var prev = cm.scanForBracket(range.head, -1);\n return prev && Pos(prev.pos.line, prev.pos.ch + 1) || range.head;\n });\n };\n\n var swapLineCombo = mac ? \"Cmd-Ctrl-\" : \"Shift-Ctrl-\";\n\n cmds[map[swapLineCombo + \"Up\"] = \"swapLineUp\"] = function(cm) {\n if (cm.isReadOnly()) return CodeMirror.Pass\n var ranges = cm.listSelections(), linesToMove = [], at = cm.firstLine() - 1, newSels = [];\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i], from = range.from().line - 1, to = range.to().line;\n newSels.push({anchor: Pos(range.anchor.line - 1, range.anchor.ch),\n head: Pos(range.head.line - 1, range.head.ch)});\n if (range.to().ch == 0 && !range.empty()) --to;\n if (from > at) linesToMove.push(from, to);\n else if (linesToMove.length) linesToMove[linesToMove.length - 1] = to;\n at = to;\n }\n cm.operation(function() {\n for (var i = 0; i < linesToMove.length; i += 2) {\n var from = linesToMove[i], to = linesToMove[i + 1];\n var line = cm.getLine(from);\n cm.replaceRange(\"\", Pos(from, 0), Pos(from + 1, 0), \"+swapLine\");\n if (to > cm.lastLine())\n cm.replaceRange(\"\\n\" + line, Pos(cm.lastLine()), null, \"+swapLine\");\n else\n cm.replaceRange(line + \"\\n\", Pos(to, 0), null, \"+swapLine\");\n }\n cm.setSelections(newSels);\n cm.scrollIntoView();\n });\n };\n\n cmds[map[swapLineCombo + \"Down\"] = \"swapLineDown\"] = function(cm) {\n if (cm.isReadOnly()) return CodeMirror.Pass\n var ranges = cm.listSelections(), linesToMove = [], at = cm.lastLine() + 1;\n for (var i = ranges.length - 1; i >= 0; i--) {\n var range = ranges[i], from = range.to().line + 1, to = range.from().line;\n if (range.to().ch == 0 && !range.empty()) from--;\n if (from < at) linesToMove.push(from, to);\n else if (linesToMove.length) linesToMove[linesToMove.length - 1] = to;\n at = to;\n }\n cm.operation(function() {\n for (var i = linesToMove.length - 2; i >= 0; i -= 2) {\n var from = linesToMove[i], to = linesToMove[i + 1];\n var line = cm.getLine(from);\n if (from == cm.lastLine())\n cm.replaceRange(\"\", Pos(from - 1), Pos(from), \"+swapLine\");\n else\n cm.replaceRange(\"\", Pos(from, 0), Pos(from + 1, 0), \"+swapLine\");\n cm.replaceRange(line + \"\\n\", Pos(to, 0), null, \"+swapLine\");\n }\n cm.scrollIntoView();\n });\n };\n\n cmds[map[ctrl + \"/\"] = \"toggleCommentIndented\"] = function(cm) {\n cm.toggleComment({ indent: true });\n }\n\n cmds[map[ctrl + \"J\"] = \"joinLines\"] = function(cm) {\n var ranges = cm.listSelections(), joined = [];\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i], from = range.from();\n var start = from.line, end = range.to().line;\n while (i < ranges.length - 1 && ranges[i + 1].from().line == end)\n end = ranges[++i].to().line;\n joined.push({start: start, end: end, anchor: !range.empty() && from});\n }\n cm.operation(function() {\n var offset = 0, ranges = [];\n for (var i = 0; i < joined.length; i++) {\n var obj = joined[i];\n var anchor = obj.anchor && Pos(obj.anchor.line - offset, obj.anchor.ch), head;\n for (var line = obj.start; line <= obj.end; line++) {\n var actual = line - offset;\n if (line == obj.end) head = Pos(actual, cm.getLine(actual).length + 1);\n if (actual < cm.lastLine()) {\n cm.replaceRange(\" \", Pos(actual), Pos(actual + 1, /^\\s*/.exec(cm.getLine(actual + 1))[0].length));\n ++offset;\n }\n }\n ranges.push({anchor: anchor || head, head: head});\n }\n cm.setSelections(ranges, 0);\n });\n };\n\n cmds[map[\"Shift-\" + ctrl + \"D\"] = \"duplicateLine\"] = function(cm) {\n cm.operation(function() {\n var rangeCount = cm.listSelections().length;\n for (var i = 0; i < rangeCount; i++) {\n var range = cm.listSelections()[i];\n if (range.empty())\n cm.replaceRange(cm.getLine(range.head.line) + \"\\n\", Pos(range.head.line, 0));\n else\n cm.replaceRange(cm.getRange(range.from(), range.to()), range.from());\n }\n cm.scrollIntoView();\n });\n };\n\n map[ctrl + \"T\"] = \"transposeChars\";\n\n function sortLines(cm, caseSensitive) {\n if (cm.isReadOnly()) return CodeMirror.Pass\n var ranges = cm.listSelections(), toSort = [], selected;\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n if (range.empty()) continue;\n var from = range.from().line, to = range.to().line;\n while (i < ranges.length - 1 && ranges[i + 1].from().line == to)\n to = range[++i].to().line;\n toSort.push(from, to);\n }\n if (toSort.length) selected = true;\n else toSort.push(cm.firstLine(), cm.lastLine());\n\n cm.operation(function() {\n var ranges = [];\n for (var i = 0; i < toSort.length; i += 2) {\n var from = toSort[i], to = toSort[i + 1];\n var start = Pos(from, 0), end = Pos(to);\n var lines = cm.getRange(start, end, false);\n if (caseSensitive)\n lines.sort();\n else\n lines.sort(function(a, b) {\n var au = a.toUpperCase(), bu = b.toUpperCase();\n if (au != bu) { a = au; b = bu; }\n return a < b ? -1 : a == b ? 0 : 1;\n });\n cm.replaceRange(lines, start, end);\n if (selected) ranges.push({anchor: start, head: end});\n }\n if (selected) cm.setSelections(ranges, 0);\n });\n }\n\n cmds[map[\"F9\"] = \"sortLines\"] = function(cm) { sortLines(cm, true); };\n cmds[map[ctrl + \"F9\"] = \"sortLinesInsensitive\"] = function(cm) { sortLines(cm, false); };\n\n cmds[map[\"F2\"] = \"nextBookmark\"] = function(cm) {\n var marks = cm.state.sublimeBookmarks;\n if (marks) while (marks.length) {\n var current = marks.shift();\n var found = current.find();\n if (found) {\n marks.push(current);\n return cm.setSelection(found.from, found.to);\n }\n }\n };\n\n cmds[map[\"Shift-F2\"] = \"prevBookmark\"] = function(cm) {\n var marks = cm.state.sublimeBookmarks;\n if (marks) while (marks.length) {\n marks.unshift(marks.pop());\n var found = marks[marks.length - 1].find();\n if (!found)\n marks.pop();\n else\n return cm.setSelection(found.from, found.to);\n }\n };\n\n cmds[map[ctrl + \"F2\"] = \"toggleBookmark\"] = function(cm) {\n var ranges = cm.listSelections();\n var marks = cm.state.sublimeBookmarks || (cm.state.sublimeBookmarks = []);\n for (var i = 0; i < ranges.length; i++) {\n var from = ranges[i].from(), to = ranges[i].to();\n var found = cm.findMarks(from, to);\n for (var j = 0; j < found.length; j++) {\n if (found[j].sublimeBookmark) {\n found[j].clear();\n for (var k = 0; k < marks.length; k++)\n if (marks[k] == found[j])\n marks.splice(k--, 1);\n break;\n }\n }\n if (j == found.length)\n marks.push(cm.markText(from, to, {sublimeBookmark: true, clearWhenEmpty: false}));\n }\n };\n\n cmds[map[\"Shift-\" + ctrl + \"F2\"] = \"clearBookmarks\"] = function(cm) {\n var marks = cm.state.sublimeBookmarks;\n if (marks) for (var i = 0; i < marks.length; i++) marks[i].clear();\n marks.length = 0;\n };\n\n cmds[map[\"Alt-F2\"] = \"selectBookmarks\"] = function(cm) {\n var marks = cm.state.sublimeBookmarks, ranges = [];\n if (marks) for (var i = 0; i < marks.length; i++) {\n var found = marks[i].find();\n if (!found)\n marks.splice(i--, 0);\n else\n ranges.push({anchor: found.from, head: found.to});\n }\n if (ranges.length)\n cm.setSelections(ranges, 0);\n };\n\n map[\"Alt-Q\"] = \"wrapLines\";\n\n var cK = ctrl + \"K \";\n\n function modifyWordOrSelection(cm, mod) {\n cm.operation(function() {\n var ranges = cm.listSelections(), indices = [], replacements = [];\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n if (range.empty()) { indices.push(i); replacements.push(\"\"); }\n else replacements.push(mod(cm.getRange(range.from(), range.to())));\n }\n cm.replaceSelections(replacements, \"around\", \"case\");\n for (var i = indices.length - 1, at; i >= 0; i--) {\n var range = ranges[indices[i]];\n if (at && CodeMirror.cmpPos(range.head, at) > 0) continue;\n var word = wordAt(cm, range.head);\n at = word.from;\n cm.replaceRange(mod(word.word), word.from, word.to);\n }\n });\n }\n\n map[cK + ctrl + \"Backspace\"] = \"delLineLeft\";\n\n cmds[map[\"Backspace\"] = \"smartBackspace\"] = function(cm) {\n if (cm.somethingSelected()) return CodeMirror.Pass;\n\n var cursor = cm.getCursor();\n var toStartOfLine = cm.getRange({line: cursor.line, ch: 0}, cursor);\n var column = CodeMirror.countColumn(toStartOfLine, null, cm.getOption(\"tabSize\"));\n var indentUnit = cm.getOption(\"indentUnit\");\n\n if (toStartOfLine && !/\\S/.test(toStartOfLine) && column % indentUnit == 0) {\n var prevIndent = new Pos(cursor.line,\n CodeMirror.findColumn(toStartOfLine, column - indentUnit, indentUnit));\n\n // If no smart delete is happening (due to tab sizing) just do a regular delete\n if (prevIndent.ch == cursor.ch) return CodeMirror.Pass;\n\n return cm.replaceRange(\"\", prevIndent, cursor, \"+delete\");\n } else {\n return CodeMirror.Pass;\n }\n };\n\n cmds[map[cK + ctrl + \"K\"] = \"delLineRight\"] = function(cm) {\n cm.operation(function() {\n var ranges = cm.listSelections();\n for (var i = ranges.length - 1; i >= 0; i--)\n cm.replaceRange(\"\", ranges[i].anchor, Pos(ranges[i].to().line), \"+delete\");\n cm.scrollIntoView();\n });\n };\n\n cmds[map[cK + ctrl + \"U\"] = \"upcaseAtCursor\"] = function(cm) {\n modifyWordOrSelection(cm, function(str) { return str.toUpperCase(); });\n };\n cmds[map[cK + ctrl + \"L\"] = \"downcaseAtCursor\"] = function(cm) {\n modifyWordOrSelection(cm, function(str) { return str.toLowerCase(); });\n };\n\n cmds[map[cK + ctrl + \"Space\"] = \"setSublimeMark\"] = function(cm) {\n if (cm.state.sublimeMark) cm.state.sublimeMark.clear();\n cm.state.sublimeMark = cm.setBookmark(cm.getCursor());\n };\n cmds[map[cK + ctrl + \"A\"] = \"selectToSublimeMark\"] = function(cm) {\n var found = cm.state.sublimeMark && cm.state.sublimeMark.find();\n if (found) cm.setSelection(cm.getCursor(), found);\n };\n cmds[map[cK + ctrl + \"W\"] = \"deleteToSublimeMark\"] = function(cm) {\n var found = cm.state.sublimeMark && cm.state.sublimeMark.find();\n if (found) {\n var from = cm.getCursor(), to = found;\n if (CodeMirror.cmpPos(from, to) > 0) { var tmp = to; to = from; from = tmp; }\n cm.state.sublimeKilled = cm.getRange(from, to);\n cm.replaceRange(\"\", from, to);\n }\n };\n cmds[map[cK + ctrl + \"X\"] = \"swapWithSublimeMark\"] = function(cm) {\n var found = cm.state.sublimeMark && cm.state.sublimeMark.find();\n if (found) {\n cm.state.sublimeMark.clear();\n cm.state.sublimeMark = cm.setBookmark(cm.getCursor());\n cm.setCursor(found);\n }\n };\n cmds[map[cK + ctrl + \"Y\"] = \"sublimeYank\"] = function(cm) {\n if (cm.state.sublimeKilled != null)\n cm.replaceSelection(cm.state.sublimeKilled, null, \"paste\");\n };\n\n map[cK + ctrl + \"G\"] = \"clearBookmarks\";\n cmds[map[cK + ctrl + \"C\"] = \"showInCenter\"] = function(cm) {\n var pos = cm.cursorCoords(null, \"local\");\n cm.scrollTo(null, (pos.top + pos.bottom) / 2 - cm.getScrollInfo().clientHeight / 2);\n };\n\n cmds[map[\"Shift-Alt-Up\"] = \"selectLinesUpward\"] = function(cm) {\n cm.operation(function() {\n var ranges = cm.listSelections();\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n if (range.head.line > cm.firstLine())\n cm.addSelection(Pos(range.head.line - 1, range.head.ch));\n }\n });\n };\n cmds[map[\"Shift-Alt-Down\"] = \"selectLinesDownward\"] = function(cm) {\n cm.operation(function() {\n var ranges = cm.listSelections();\n for (var i = 0; i < ranges.length; i++) {\n var range = ranges[i];\n if (range.head.line < cm.lastLine())\n cm.addSelection(Pos(range.head.line + 1, range.head.ch));\n }\n });\n };\n\n function getTarget(cm) {\n var from = cm.getCursor(\"from\"), to = cm.getCursor(\"to\");\n if (CodeMirror.cmpPos(from, to) == 0) {\n var word = wordAt(cm, from);\n if (!word.word) return;\n from = word.from;\n to = word.to;\n }\n return {from: from, to: to, query: cm.getRange(from, to), word: word};\n }\n\n function findAndGoTo(cm, forward) {\n var target = getTarget(cm);\n if (!target) return;\n var query = target.query;\n var cur = cm.getSearchCursor(query, forward ? target.to : target.from);\n\n if (forward ? cur.findNext() : cur.findPrevious()) {\n cm.setSelection(cur.from(), cur.to());\n } else {\n cur = cm.getSearchCursor(query, forward ? Pos(cm.firstLine(), 0)\n : cm.clipPos(Pos(cm.lastLine())));\n if (forward ? cur.findNext() : cur.findPrevious())\n cm.setSelection(cur.from(), cur.to());\n else if (target.word)\n cm.setSelection(target.from, target.to);\n }\n };\n cmds[map[ctrl + \"F3\"] = \"findUnder\"] = function(cm) { findAndGoTo(cm, true); };\n cmds[map[\"Shift-\" + ctrl + \"F3\"] = \"findUnderPrevious\"] = function(cm) { findAndGoTo(cm,false); };\n cmds[map[\"Alt-F3\"] = \"findAllUnder\"] = function(cm) {\n var target = getTarget(cm);\n if (!target) return;\n var cur = cm.getSearchCursor(target.query);\n var matches = [];\n var primaryIndex = -1;\n while (cur.findNext()) {\n matches.push({anchor: cur.from(), head: cur.to()});\n if (cur.from().line <= target.from.line && cur.from().ch <= target.from.ch)\n primaryIndex++;\n }\n cm.setSelections(matches, primaryIndex);\n };\n\n map[\"Shift-\" + ctrl + \"[\"] = \"fold\";\n map[\"Shift-\" + ctrl + \"]\"] = \"unfold\";\n map[cK + ctrl + \"0\"] = map[cK + ctrl + \"j\"] = \"unfoldAll\";\n\n map[ctrl + \"I\"] = \"findIncremental\";\n map[\"Shift-\" + ctrl + \"I\"] = \"findIncrementalReverse\";\n map[ctrl + \"H\"] = \"replace\";\n map[\"F3\"] = \"findNext\";\n map[\"Shift-F3\"] = \"findPrev\";\n\n CodeMirror.normalizeKeyMap(map);\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/keymap/emacs.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/codemirror/keymap/emacs.js",
"module-type": "library",
"text": "// CodeMirror, copyright (c) by Marijn Haverbeke and others\n// Distributed under an MIT license: http://codemirror.net/LICENSE\n\n(function(mod) {\n if (typeof exports == \"object\" && typeof module == \"object\") // CommonJS\n mod(require(\"../lib/codemirror\"));\n else if (typeof define == \"function\" && define.amd) // AMD\n define([\"../lib/codemirror\"], mod);\n else // Plain browser env\n mod(CodeMirror);\n})(function(CodeMirror) {\n \"use strict\";\n\n var Pos = CodeMirror.Pos;\n function posEq(a, b) { return a.line == b.line && a.ch == b.ch; }\n\n // Kill 'ring'\n\n var killRing = [];\n function addToRing(str) {\n killRing.push(str);\n if (killRing.length > 50) killRing.shift();\n }\n function growRingTop(str) {\n if (!killRing.length) return addToRing(str);\n killRing[killRing.length - 1] += str;\n }\n function getFromRing(n) { return killRing[killRing.length - (n ? Math.min(n, 1) : 1)] || \"\"; }\n function popFromRing() { if (killRing.length > 1) killRing.pop(); return getFromRing(); }\n\n var lastKill = null;\n\n function kill(cm, from, to, mayGrow, text) {\n if (text == null) text = cm.getRange(from, to);\n\n if (mayGrow && lastKill && lastKill.cm == cm && posEq(from, lastKill.pos) && cm.isClean(lastKill.gen))\n growRingTop(text);\n else\n addToRing(text);\n cm.replaceRange(\"\", from, to, \"+delete\");\n\n if (mayGrow) lastKill = {cm: cm, pos: from, gen: cm.changeGeneration()};\n else lastKill = null;\n }\n\n // Boundaries of various units\n\n function byChar(cm, pos, dir) {\n return cm.findPosH(pos, dir, \"char\", true);\n }\n\n function byWord(cm, pos, dir) {\n return cm.findPosH(pos, dir, \"word\", true);\n }\n\n function byLine(cm, pos, dir) {\n return cm.findPosV(pos, dir, \"line\", cm.doc.sel.goalColumn);\n }\n\n function byPage(cm, pos, dir) {\n return cm.findPosV(pos, dir, \"page\", cm.doc.sel.goalColumn);\n }\n\n function byParagraph(cm, pos, dir) {\n var no = pos.line, line = cm.getLine(no);\n var sawText = /\\S/.test(dir < 0 ? line.slice(0, pos.ch) : line.slice(pos.ch));\n var fst = cm.firstLine(), lst = cm.lastLine();\n for (;;) {\n no += dir;\n if (no < fst || no > lst)\n return cm.clipPos(Pos(no - dir, dir < 0 ? 0 : null));\n line = cm.getLine(no);\n var hasText = /\\S/.test(line);\n if (hasText) sawText = true;\n else if (sawText) return Pos(no, 0);\n }\n }\n\n function bySentence(cm, pos, dir) {\n var line = pos.line, ch = pos.ch;\n var text = cm.getLine(pos.line), sawWord = false;\n for (;;) {\n var next = text.charAt(ch + (dir < 0 ? -1 : 0));\n if (!next) { // End/beginning of line reached\n if (line == (dir < 0 ? cm.firstLine() : cm.lastLine())) return Pos(line, ch);\n text = cm.getLine(line + dir);\n if (!/\\S/.test(text)) return Pos(line, ch);\n line += dir;\n ch = dir < 0 ? text.length : 0;\n continue;\n }\n if (sawWord && /[!?.]/.test(next)) return Pos(line, ch + (dir > 0 ? 1 : 0));\n if (!sawWord) sawWord = /\\w/.test(next);\n ch += dir;\n }\n }\n\n function byExpr(cm, pos, dir) {\n var wrap;\n if (cm.findMatchingBracket && (wrap = cm.findMatchingBracket(pos, true))\n && wrap.match && (wrap.forward ? 1 : -1) == dir)\n return dir > 0 ? Pos(wrap.to.line, wrap.to.ch + 1) : wrap.to;\n\n for (var first = true;; first = false) {\n var token = cm.getTokenAt(pos);\n var after = Pos(pos.line, dir < 0 ? token.start : token.end);\n if (first && dir > 0 && token.end == pos.ch || !/\\w/.test(token.string)) {\n var newPos = cm.findPosH(after, dir, \"char\");\n if (posEq(after, newPos)) return pos;\n else pos = newPos;\n } else {\n return after;\n }\n }\n }\n\n // Prefixes (only crudely supported)\n\n function getPrefix(cm, precise) {\n var digits = cm.state.emacsPrefix;\n if (!digits) return precise ? null : 1;\n clearPrefix(cm);\n return digits == \"-\" ? -1 : Number(digits);\n }\n\n function repeated(cmd) {\n var f = typeof cmd == \"string\" ? function(cm) { cm.execCommand(cmd); } : cmd;\n return function(cm) {\n var prefix = getPrefix(cm);\n f(cm);\n for (var i = 1; i < prefix; ++i) f(cm);\n };\n }\n\n function findEnd(cm, pos, by, dir) {\n var prefix = getPrefix(cm);\n if (prefix < 0) { dir = -dir; prefix = -prefix; }\n for (var i = 0; i < prefix; ++i) {\n var newPos = by(cm, pos, dir);\n if (posEq(newPos, pos)) break;\n pos = newPos;\n }\n return pos;\n }\n\n function move(by, dir) {\n var f = function(cm) {\n cm.extendSelection(findEnd(cm, cm.getCursor(), by, dir));\n };\n f.motion = true;\n return f;\n }\n\n function killTo(cm, by, dir) {\n var selections = cm.listSelections(), cursor;\n var i = selections.length;\n while (i--) {\n cursor = selections[i].head;\n kill(cm, cursor, findEnd(cm, cursor, by, dir), true);\n }\n }\n\n function killRegion(cm) {\n if (cm.somethingSelected()) {\n var selections = cm.listSelections(), selection;\n var i = selections.length;\n while (i--) {\n selection = selections[i];\n kill(cm, selection.anchor, selection.head);\n }\n return true;\n }\n }\n\n function addPrefix(cm, digit) {\n if (cm.state.emacsPrefix) {\n if (digit != \"-\") cm.state.emacsPrefix += digit;\n return;\n }\n // Not active yet\n cm.state.emacsPrefix = digit;\n cm.on(\"keyHandled\", maybeClearPrefix);\n cm.on(\"inputRead\", maybeDuplicateInput);\n }\n\n var prefixPreservingKeys = {\"Alt-G\": true, \"Ctrl-X\": true, \"Ctrl-Q\": true, \"Ctrl-U\": true};\n\n function maybeClearPrefix(cm, arg) {\n if (!cm.state.emacsPrefixMap && !prefixPreservingKeys.hasOwnProperty(arg))\n clearPrefix(cm);\n }\n\n function clearPrefix(cm) {\n cm.state.emacsPrefix = null;\n cm.off(\"keyHandled\", maybeClearPrefix);\n cm.off(\"inputRead\", maybeDuplicateInput);\n }\n\n function maybeDuplicateInput(cm, event) {\n var dup = getPrefix(cm);\n if (dup > 1 && event.origin == \"+input\") {\n var one = event.text.join(\"\\n\"), txt = \"\";\n for (var i = 1; i < dup; ++i) txt += one;\n cm.replaceSelection(txt);\n }\n }\n\n function addPrefixMap(cm) {\n cm.state.emacsPrefixMap = true;\n cm.addKeyMap(prefixMap);\n cm.on(\"keyHandled\", maybeRemovePrefixMap);\n cm.on(\"inputRead\", maybeRemovePrefixMap);\n }\n\n function maybeRemovePrefixMap(cm, arg) {\n if (typeof arg == \"string\" && (/^\\d$/.test(arg) || arg == \"Ctrl-U\")) return;\n cm.removeKeyMap(prefixMap);\n cm.state.emacsPrefixMap = false;\n cm.off(\"keyHandled\", maybeRemovePrefixMap);\n cm.off(\"inputRead\", maybeRemovePrefixMap);\n }\n\n // Utilities\n\n function setMark(cm) {\n cm.setCursor(cm.getCursor());\n cm.setExtending(!cm.getExtending());\n cm.on(\"change\", function() { cm.setExtending(false); });\n }\n\n function clearMark(cm) {\n cm.setExtending(false);\n cm.setCursor(cm.getCursor());\n }\n\n function getInput(cm, msg, f) {\n if (cm.openDialog)\n cm.openDialog(msg + \": <input type=\\\"text\\\" style=\\\"width: 10em\\\"/>\", f, {bottom: true});\n else\n f(prompt(msg, \"\"));\n }\n\n function operateOnWord(cm, op) {\n var start = cm.getCursor(), end = cm.findPosH(start, 1, \"word\");\n cm.replaceRange(op(cm.getRange(start, end)), start, end);\n cm.setCursor(end);\n }\n\n function toEnclosingExpr(cm) {\n var pos = cm.getCursor(), line = pos.line, ch = pos.ch;\n var stack = [];\n while (line >= cm.firstLine()) {\n var text = cm.getLine(line);\n for (var i = ch == null ? text.length : ch; i > 0;) {\n var ch = text.charAt(--i);\n if (ch == \")\")\n stack.push(\"(\");\n else if (ch == \"]\")\n stack.push(\"[\");\n else if (ch == \"}\")\n stack.push(\"{\");\n else if (/[\\(\\{\\[]/.test(ch) && (!stack.length || stack.pop() != ch))\n return cm.extendSelection(Pos(line, i));\n }\n --line; ch = null;\n }\n }\n\n function quit(cm) {\n cm.execCommand(\"clearSearch\");\n clearMark(cm);\n }\n\n // Actual keymap\n\n var keyMap = CodeMirror.keyMap.emacs = CodeMirror.normalizeKeyMap({\n \"Ctrl-W\": function(cm) {kill(cm, cm.getCursor(\"start\"), cm.getCursor(\"end\"));},\n \"Ctrl-K\": repeated(function(cm) {\n var start = cm.getCursor(), end = cm.clipPos(Pos(start.line));\n var text = cm.getRange(start, end);\n if (!/\\S/.test(text)) {\n text += \"\\n\";\n end = Pos(start.line + 1, 0);\n }\n kill(cm, start, end, true, text);\n }),\n \"Alt-W\": function(cm) {\n addToRing(cm.getSelection());\n clearMark(cm);\n },\n \"Ctrl-Y\": function(cm) {\n var start = cm.getCursor();\n cm.replaceRange(getFromRing(getPrefix(cm)), start, start, \"paste\");\n cm.setSelection(start, cm.getCursor());\n },\n \"Alt-Y\": function(cm) {cm.replaceSelection(popFromRing(), \"around\", \"paste\");},\n\n \"Ctrl-Space\": setMark, \"Ctrl-Shift-2\": setMark,\n\n \"Ctrl-F\": move(byChar, 1), \"Ctrl-B\": move(byChar, -1),\n \"Right\": move(byChar, 1), \"Left\": move(byChar, -1),\n \"Ctrl-D\": function(cm) { killTo(cm, byChar, 1); },\n \"Delete\": function(cm) { killRegion(cm) || killTo(cm, byChar, 1); },\n \"Ctrl-H\": function(cm) { killTo(cm, byChar, -1); },\n \"Backspace\": function(cm) { killRegion(cm) || killTo(cm, byChar, -1); },\n\n \"Alt-F\": move(byWord, 1), \"Alt-B\": move(byWord, -1),\n \"Alt-D\": function(cm) { killTo(cm, byWord, 1); },\n \"Alt-Backspace\": function(cm) { killTo(cm, byWord, -1); },\n\n \"Ctrl-N\": move(byLine, 1), \"Ctrl-P\": move(byLine, -1),\n \"Down\": move(byLine, 1), \"Up\": move(byLine, -1),\n \"Ctrl-A\": \"goLineStart\", \"Ctrl-E\": \"goLineEnd\",\n \"End\": \"goLineEnd\", \"Home\": \"goLineStart\",\n\n \"Alt-V\": move(byPage, -1), \"Ctrl-V\": move(byPage, 1),\n \"PageUp\": move(byPage, -1), \"PageDown\": move(byPage, 1),\n\n \"Ctrl-Up\": move(byParagraph, -1), \"Ctrl-Down\": move(byParagraph, 1),\n\n \"Alt-A\": move(bySentence, -1), \"Alt-E\": move(bySentence, 1),\n \"Alt-K\": function(cm) { killTo(cm, bySentence, 1); },\n\n \"Ctrl-Alt-K\": function(cm) { killTo(cm, byExpr, 1); },\n \"Ctrl-Alt-Backspace\": function(cm) { killTo(cm, byExpr, -1); },\n \"Ctrl-Alt-F\": move(byExpr, 1), \"Ctrl-Alt-B\": move(byExpr, -1),\n\n \"Shift-Ctrl-Alt-2\": function(cm) {\n var cursor = cm.getCursor();\n cm.setSelection(findEnd(cm, cursor, byExpr, 1), cursor);\n },\n \"Ctrl-Alt-T\": function(cm) {\n var leftStart = byExpr(cm, cm.getCursor(), -1), leftEnd = byExpr(cm, leftStart, 1);\n var rightEnd = byExpr(cm, leftEnd, 1), rightStart = byExpr(cm, rightEnd, -1);\n cm.replaceRange(cm.getRange(rightStart, rightEnd) + cm.getRange(leftEnd, rightStart) +\n cm.getRange(leftStart, leftEnd), leftStart, rightEnd);\n },\n \"Ctrl-Alt-U\": repeated(toEnclosingExpr),\n\n \"Alt-Space\": function(cm) {\n var pos = cm.getCursor(), from = pos.ch, to = pos.ch, text = cm.getLine(pos.line);\n while (from && /\\s/.test(text.charAt(from - 1))) --from;\n while (to < text.length && /\\s/.test(text.charAt(to))) ++to;\n cm.replaceRange(\" \", Pos(pos.line, from), Pos(pos.line, to));\n },\n \"Ctrl-O\": repeated(function(cm) { cm.replaceSelection(\"\\n\", \"start\"); }),\n \"Ctrl-T\": repeated(function(cm) {\n cm.execCommand(\"transposeChars\");\n }),\n\n \"Alt-C\": repeated(function(cm) {\n operateOnWord(cm, function(w) {\n var letter = w.search(/\\w/);\n if (letter == -1) return w;\n return w.slice(0, letter) + w.charAt(letter).toUpperCase() + w.slice(letter + 1).toLowerCase();\n });\n }),\n \"Alt-U\": repeated(function(cm) {\n operateOnWord(cm, function(w) { return w.toUpperCase(); });\n }),\n \"Alt-L\": repeated(function(cm) {\n operateOnWord(cm, function(w) { return w.toLowerCase(); });\n }),\n\n \"Alt-;\": \"toggleComment\",\n\n \"Ctrl-/\": repeated(\"undo\"), \"Shift-Ctrl--\": repeated(\"undo\"),\n \"Ctrl-Z\": repeated(\"undo\"), \"Cmd-Z\": repeated(\"undo\"),\n \"Shift-Alt-,\": \"goDocStart\", \"Shift-Alt-.\": \"goDocEnd\",\n \"Ctrl-S\": \"findNext\", \"Ctrl-R\": \"findPrev\", \"Ctrl-G\": quit, \"Shift-Alt-5\": \"replace\",\n \"Alt-/\": \"autocomplete\",\n \"Ctrl-J\": \"newlineAndIndent\", \"Enter\": false, \"Tab\": \"indentAuto\",\n\n \"Alt-G G\": function(cm) {\n var prefix = getPrefix(cm, true);\n if (prefix != null && prefix > 0) return cm.setCursor(prefix - 1);\n\n getInput(cm, \"Goto line\", function(str) {\n var num;\n if (str && !isNaN(num = Number(str)) && num == (num|0) && num > 0)\n cm.setCursor(num - 1);\n });\n },\n\n \"Ctrl-X Tab\": function(cm) {\n cm.indentSelection(getPrefix(cm, true) || cm.getOption(\"indentUnit\"));\n },\n \"Ctrl-X Ctrl-X\": function(cm) {\n cm.setSelection(cm.getCursor(\"head\"), cm.getCursor(\"anchor\"));\n },\n \"Ctrl-X Ctrl-S\": \"save\",\n \"Ctrl-X Ctrl-W\": \"save\",\n \"Ctrl-X S\": \"saveAll\",\n \"Ctrl-X F\": \"open\",\n \"Ctrl-X U\": repeated(\"undo\"),\n \"Ctrl-X K\": \"close\",\n \"Ctrl-X Delete\": function(cm) { kill(cm, cm.getCursor(), bySentence(cm, cm.getCursor(), 1), true); },\n \"Ctrl-X H\": \"selectAll\",\n\n \"Ctrl-Q Tab\": repeated(\"insertTab\"),\n \"Ctrl-U\": addPrefixMap\n });\n\n var prefixMap = {\"Ctrl-G\": clearPrefix};\n function regPrefix(d) {\n prefixMap[d] = function(cm) { addPrefix(cm, d); };\n keyMap[\"Ctrl-\" + d] = function(cm) { addPrefix(cm, d); };\n prefixPreservingKeys[\"Ctrl-\" + d] = true;\n }\n for (var i = 0; i < 10; ++i) regPrefix(String(i));\n regPrefix(\"-\");\n});\n"
},
"$:/plugins/tiddlywiki/codemirror/readme": {
"title": "$:/plugins/tiddlywiki/codemirror/readme",
"text": "This plugin provides an enhanced text editor component based on [[CodeMirror|http://codemirror.net]]. It provides several advantages over the default browser text editor:\n\n* Code colouring for many languages (see [[the official documentation here|http://codemirror.net/mode/index.html]])\n* Auto closing brackets and tags\n* Folding brackets, comments, and tags\n* Auto-completion\n\n[[Source code|https://github.com/Jermolene/TiddlyWiki5/blob/master/plugins/tiddlywiki/codemirror]]\n\nBased on ~CodeMirror version 5.13.2\n"
},
"$:/plugins/tiddlywiki/codemirror/styles": {
"title": "$:/plugins/tiddlywiki/codemirror/styles",
"tags": "[[$:/tags/Stylesheet]]",
"text": "/* Make the editor resize to fit its content */\n\n.CodeMirror {\n\theight: auto;\n\tborder: 1px solid #ddd;\n\tline-height: 1.5;\n\tfont-family: \"Monaco\", monospace;\n}\n\n.CodeMirror-scroll {\n\toverflow-x: auto;\n\toverflow-y: hidden;\t\n}\n"
},
"$:/plugins/tiddlywiki/codemirror/usage": {
"title": "$:/plugins/tiddlywiki/codemirror/usage",
"text": "! Setting ~CodeMirror Content Types\n\nYou can determine which tiddler content types are edited by the ~CodeMirror widget by creating or modifying special tiddlers whose prefix is comprised of the string `$:/config/EditorTypeMappings/` concatenated with the content type. The text of that tiddler gives the editor type to be used (eg, ''text'', ''bitmap'', ''codemirror'').\n\nThe current editor type mappings are shown in [[$:/ControlPanel]] under the \"Advanced\" tab.\n\n! ~CodeMirror Configuration\n\nYou can configure the ~CodeMirror plugin by creating a tiddler called [[$:/config/CodeMirror]] containing a JSON configuration object. The configuration tiddler must have its type field set to `application/json` to take effect.\n\nSee http://codemirror.net/ for details of available configuration options.\n\nFor example:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/dialog/dialog.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/search/searchcursor.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js\",\n \"$:/plugins/tiddlywiki/codemirror/keymap/vim.js\",\n \"$:/plugins/tiddlywiki/codemirror/keymap/emacs.js\"\n ],\n \"configuration\": {\n \"keyMap\": \"vim\",\n \"matchBrackets\":true,\n \"showCursorWhenSelecting\": true\n }\n}\n```\n\n!! Basic working configuration\n\n# Create a tiddler called `$:/config/CodeMirror`\n\n# The type of the tiddler has to be set to `application/json`\n\n# The text of the tiddler is the following: \n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js\"\n ],\n \"configuration\": {\n \"matchBrackets\":true,\n \"showCursorWhenSelecting\": true\n }\n}\n\n```\n\n# You should see line numbers when editing a tiddler\n# When editing a tiddler, no matter what the type of the tiddler is set to, you should see matching brackets being highlighted whenever the cursor is next to one of them\n# If you edit a tiddler with the type `application/javascript` or `application/json` you should see the code being syntax highlighted\n\n!! Add HTML syntax highlighting\n\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[https://raw.githubusercontent.com/codemirror/CodeMirror/master/mode/xml/xml.js]]\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js\"\n ],\n \"configuration\": {\n \"showCursorWhenSelecting\": true,\n \"matchBrackets\":true\n }\n}\n```\n# Edit a tiddler with the type `text/html` and write some html code. You should see your code being coloured\n\n!! Add a non-existing language mode\n\nHere's an example of adding a new language mode - in this case, the language C.\n\n\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/mode/clike/clike.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[https://raw.githubusercontent.com/codemirror/CodeMirror/master/mode/clike/clike.js]]\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/clike/clike.js\"\n ],\n \"configuration\": {\n \"showCursorWhenSelecting\": true\n }\n}\n```\n\n# Add the correct ~EditorTypeMappings tiddler\n## Find the matching MIME type. If you go on the [[CodeMirror documentation for language modes|http://codemirror.net/mode/index.html]] you can see the [[documentation for the c-like mode|http://codemirror.net/mode/clike/index.html]]. In this documentation, at the end you will be told the MIME types defined. Here it's ''text/x-csrc''\n## Add the tiddler: `$:/config/EditorTypeMappings/text/x-csrc` and fill the text field with : ''codemirror''\n\nIf you edit a tiddler with the type `text/x-csrc` and write some code in C, you should see your text being coloured.\n\n!! Add matching tags\n\n# Add XML and HTML colouring\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/edit/matchtags.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[http://codemirror.net/addon/edit/matchtags.js]]\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchtags.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js\"\n ],\n \"configuration\": {\n \"showCursorWhenSelecting\": true,\n \"matchTags\": {\"bothTags\": true},\n \"extraKeys\": {\"Ctrl-J\": \"toMatchingTag\"}\n }\n}\n```\n\nEdit a tiddler that has the type :`text/htm` and write this code:\n\n```\n<html>\n <div id=\"click here and press CTRL+J\">\n <ul>\n <li>\n </li>\n </ul>\n </div>\n</html>\n```\n\nIf you click on a tag and press CTRL+J, your cursor will select the matching tag. Supposedly, it should highlight the pair when clicking a tag. However, that part doesn't work.\n\n!! Adding closing tags\n\n# Add the xml mode (see \"Add XML and HTML colouring\")\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/edit/closetags.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[http://codemirror.net/addon/edit/closetag.js]]\n\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/closetags.js\"\n ],\n \"configuration\": {\n \"showCursorWhenSelecting\": true,\n \"autoCloseTags\":true\n }\n}\n```\n\nIf you edit a tiddler with the type`text/html` and write:\n\n```\n<html>\n```\n\nThen the closing tag ''</html>'' should automatically appear.\n\n!! Add closing brackets\n\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/edit/closebrackets.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[http://codemirror.net/addon/edit/closebrackets.js]]\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/matchbrackets.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/edit/closebrackets.js\"\n ],\n\n \"configuration\": {\n\n \"showCursorWhenSelecting\": true,\n \"matchBrackets\":true,\n \"autoCloseBrackets\":true\n }\n}\n```\n\n# If you try to edit any tiddler and write `if(` you should see the bracket closing itself automatically (you will get \"if()\"). It works with (), [], and {}\n# If you try and edit a tiddler with the type `application/javascript`, it will auto-close `()`,`[]`,`{}`,`''` and `\"\"`\n\n!! Adding folding tags\n\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/fold/foldcode.js`\n## Add a field `module-type` and set it to ''library''\n## Set the field `type` to ''application/javascript''\n## Set the text field of the tiddler with the javascript code from this link : [[http://codemirror.net/addon/fold/foldcode.js]]\n# Repeat the above process for the following tiddlers, but replace the code with the one from the given link:\n## Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/fold/xml-fold.js`, the code can be found here [[https://raw.githubusercontent.com/codemirror/CodeMirror/master/addon/fold/xml-fold.js]]\n## Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/fold/foldgutter.js`, the code can be found here [[http://codemirror.net/addon/fold/foldgutter.js]]\n# Create a tiddler `$:/plugins/tiddlywiki/codemirror/addon/fold/foldgutter.css`\n## Add the tag `$:/tags/Stylesheet`\n## Set the text field of the tiddler with the css code from this link : [[http://codemirror.net/addon/fold/foldgutter.css]]\n# Set the text field of the tiddler `$:/config/CodeMirror` to:\n\n```\n{\n \"require\": [\n \"$:/plugins/tiddlywiki/codemirror/mode/javascript/javascript.js\",\n \"$:/plugins/tiddlywiki/codemirror/mode/xml/xml.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/fold/foldcode.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/fold/xml-fold.js\",\n \"$:/plugins/tiddlywiki/codemirror/addon/fold/foldgutter.js\"\n ],\n \"configuration\": {\n \"showCursorWhenSelecting\": true,\n \"matchTags\": {\"bothTags\": true},\n \"foldGutter\": true,\n \"gutters\": [\"CodeMirror-linenumbers\", \"CodeMirror-foldgutter\"]\n }\n}\n```\n\nNow if you type the below code in a tiddler with the type `text/html`:\n\n```\n<html>\n <div>\n <ul>\n\n </ul>\n </div>\n</html>\n```\n\nYou should see little arrows just next to the line numbers. Clicking on it will have the effect to fold the code (or unfold it).\n"
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"text": "/*\\\ntitle: $:/plugins/tiddlywiki/highlight/highlightblock.js\ntype: application/javascript\nmodule-type: widget\n\nWraps up the fenced code blocks parser for highlight and use in TiddlyWiki5\n\n\\*/\n(function() {\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar CodeBlockWidget = require(\"$:/core/modules/widgets/codeblock.js\").codeblock;\n\nvar hljs = require(\"$:/plugins/tiddlywiki/highlight/highlight.js\");\n\nhljs.configure({tabReplace: \" \"});\t\n\nCodeBlockWidget.prototype.postRender = function() {\n\tvar domNode = this.domNodes[0];\n\tif($tw.browser && this.document !== $tw.fakeDocument && this.language) {\n\t\tdomNode.className = this.language.toLowerCase();\n\t\thljs.highlightBlock(domNode);\n\t} else if(!$tw.browser && this.language && this.language.indexOf(\"/\") === -1 ){\n\t\ttry {\n\t\t\tdomNode.className = this.language.toLowerCase() + \" hljs\";\n\t\t\tdomNode.children[0].innerHTML = hljs.fixMarkup(hljs.highlight(this.language, this.getAttribute(\"code\")).value);\n\t\t}\n\t\tcatch(err) {\n\t\t\t// Can't easily tell if a language is registered or not in the packed version of hightlight.js,\n\t\t\t// so we silently fail and the codeblock remains unchanged\n\t\t}\n\t}\t\n};\n\n})();\n",
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"$:/plugins/tiddlywiki/highlight/license": {
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"text": "Copyright (c) 2006, Ivan Sagalaev\nAll rights reserved.\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n * Redistributions of source code must retain the above copyright\n notice, this list of conditions and the following disclaimer.\n * Redistributions in binary form must reproduce the above copyright\n notice, this list of conditions and the following disclaimer in the\n documentation and/or other materials provided with the distribution.\n * Neither the name of highlight.js nor the names of its contributors\n may be used to endorse or promote products derived from this software\n without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY\nEXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY\nDIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND\nON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n"
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"$:/plugins/tiddlywiki/highlight/readme": {
"title": "$:/plugins/tiddlywiki/highlight/readme",
"text": "This plugin provides syntax highlighting of code blocks using v8.8.0 of [[highlight.js|https://github.com/isagalaev/highlight.js]] from Ivan Sagalaev.\n\n! Usage\n\nWhen the plugin is installed it automatically applies highlighting to all codeblocks defined with triple backticks or with the CodeBlockWidget.\n\nThe language can optionally be specified after the opening triple braces:\n\n<$codeblock code=\"\"\"```css\n * { margin: 0; padding: 0; } /* micro reset */\n\nhtml { font-size: 62.5%; }\nbody { font-size: 14px; font-size: 1.4rem; } /* =14px */\nh1 { font-size: 24px; font-size: 2.4rem; } /* =24px */\n```\"\"\"/>\n\nIf no language is specified highlight.js will attempt to automatically detect the language.\n\n! Built-in Language Brushes\n\nThe plugin includes support for the following languages (referred to as \"brushes\" by highlight.js):\n\n* apache\n* bash\n* coffeescript\n* cpp\n* cs\n* css\n* diff\n* http\n* ini\n* java\n* javascript\n* json\n* makefile\n* markdown\n* nginx\n* objectivec\n* perl\n* php\n* python\n* ruby\n* sql\n* xml\n\n"
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"text": ".hljs{display:block;overflow-x:auto;padding:.5em;color:#333;background:#f8f8f8;-webkit-text-size-adjust:none}.hljs-comment,.diff .hljs-header,.hljs-javadoc{color:#998;font-style:italic}.hljs-keyword,.css .rule .hljs-keyword,.hljs-winutils,.nginx .hljs-title,.hljs-subst,.hljs-request,.hljs-status{color:#333;font-weight:bold}.hljs-number,.hljs-hexcolor,.ruby .hljs-constant{color:teal}.hljs-string,.hljs-tag .hljs-value,.hljs-phpdoc,.hljs-dartdoc,.tex .hljs-formula{color:#d14}.hljs-title,.hljs-id,.scss .hljs-preprocessor{color:#900;font-weight:bold}.hljs-list .hljs-keyword,.hljs-subst{font-weight:normal}.hljs-class .hljs-title,.hljs-type,.vhdl .hljs-literal,.tex .hljs-command{color:#458;font-weight:bold}.hljs-tag,.hljs-tag .hljs-title,.hljs-rule .hljs-property,.django .hljs-tag .hljs-keyword{color:navy;font-weight:normal}.hljs-attribute,.hljs-variable,.lisp .hljs-body,.hljs-name{color:teal}.hljs-regexp{color:#009926}.hljs-symbol,.ruby .hljs-symbol .hljs-string,.lisp .hljs-keyword,.clojure .hljs-keyword,.scheme .hljs-keyword,.tex .hljs-special,.hljs-prompt{color:#990073}.hljs-built_in{color:#0086b3}.hljs-preprocessor,.hljs-pragma,.hljs-pi,.hljs-doctype,.hljs-shebang,.hljs-cdata{color:#999;font-weight:bold}.hljs-deletion{background:#fdd}.hljs-addition{background:#dfd}.diff .hljs-change{background:#0086b3}.hljs-chunk{color:#aaa}"
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"title": "$:/plugins/tiddlywiki/highlight/usage",
"text": "! Usage\n\nFenced code blocks can have a language specifier added to trigger highlighting in a specific language. Otherwise heuristics are used to detect the language.\n\n```\n ```js\n var a = b + c; // Highlighted as JavaScript\n ```\n```\n! Adding Themes\n\nYou can add themes from highlight.js by copying the CSS to a new tiddler and tagging it with [[$:/tags/Stylesheet]]. The available themes can be found on GitHub:\n\nhttps://github.com/isagalaev/highlight.js/tree/master/src/styles\n"
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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Bold.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Bold.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Regular.woff",
"text": 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5TpOxSKrmxImypIW2z8wshKKnFUa/kNzRuhgnRGZRv3Eg33MxJPtWZnZnO7UZ0b5nLplN8/gYBcz+FvkUaqNV9GhfTWOBQvKIZH3jdXXnUj8H+QRmugEjIeMAWwAkGRIfRJBfA0SP9/PeIHTr/zNqv6+Wu6P5kTpYKF4NcMDhsQEgL7loz63m5o9rnaAHqb3uAm57VoVXD1LThFSEtBtYvFz6WWeq2qpMJEOi3qx27EjAWq/NbC51J19QEhEnaaqW6AsmfNHZdJy+xBy13tKVTnYkETJFA18vVaK56YlpvxOcadc1Kpin7vulm5+tF2/GsqmwY6oUC6omBRa6jwew9NDKxUK6GgvNry1VziAeWz2IrT/D/xpsd6Z/OhQEXBIworkYERCvKQTzbIIYQ8ItgOPbiFBK9hDE7wEC4N7GaKyWTfttTUFt3OalsAd51IY1tyCJwjx5vNRxDcQhxw0tD5e7uTzzTmwA8uYwFUVRl4rlV5+lwsqa0FIFopZHVUx3k3MNXDn/qihr8PF/QyT6O4RiiZpwYyR7/1XxwkcKqwVaLouRT358/PwcgepBF0KAqvAloOrdtyA+Po1G0SzaQe3+xGorp4miQPA6lBsMSyXXAKuEoZ/n52rVuZ35nepsbTbqZN2qc1R0mBR2MZN7nQe/63HuZO579+8c48tOY6/2QHIITQ+Wx3AD5zw7hJ9tbixfNXEkOqublbzfJ9qH21tPmKSSbSlW3Iio/t8c24zIy5Nq2ycTdbE2eyGtr5l5WRadKVu8SG40z0wxf61YKMpKLJcrl3Xb198935fD/bFyQlR9RiScL61Ot6qZmFIvSNm6L+6XSxN/97mV8XJObyhhUfSPzIatqW0vhyr49wBjOmgdLfUXFywiMTAPRUyi7JqMIVYIAigBdkHEKwAow/KM0dKpqd5EowCUSFclhjq4owwLE3e3Bx9z+Dg/BiWIm7TFTQmVSRrwjwBPFDdBTtSz90ASGCpT4qOna2VW3bTNhbFm2OrGywViUtEkm5c0ttafmprdTn0nmB9JRHQs2PF2Od7waxPpkGMazF6ceZ+kLBF9enZvtp7smSGM1fffX2nd+IfVwkwnmsL/zIrFFlfK+kxsNNF4+Fou6tae1N3vCC3yR2gJXUDf2Xi9DHhirC4nBZmMFomIyXrce68M3+9vvB6GQTWoRLLAMZkXb4RvKYDMDMnsOlQjKE/SFTCfsYFE0RQ3496FR4AHCADmMrnz42d5E/qNwVgFxsoKU+QbwylAXRlSfnjG/n7fvHB+pnCmMlYCG6uA/D2O2R4QdXkAt3iYujRKcu2fIvCLOyrETuIbvDr5sve+VIQ38KeJLdyCK6TSBiTtSEihxc2fP/TJUMfklmNjA5BKErHo13KWjak+Eg/5g1mLKiYj+MUXjbx1uZfvklHKtFP3iFGVYF19o5roBkIJYj/+77+fg5SX7Yz9kc++tjUnJoKCJjHbhEOOyViE5aYbAcCtQNv/3s7frP2LudCHfkou2ZRS5GJc5u6b5FXyBnoSvdYPzGJMq0AVdhaAdmWhalIoEw5Yv4F46cUc53ghOORiQZZuKCqgCD0QMaXgLlkmlxnUb4i5eH/8R8xAknzrx07Z78cxun3rkYeuPnj53jNLM1PjY5m034eexE9qkDI4N6SsPF84YnhFw3uZR6ehbPTacCQ3TCXuI8ihYO+4LrMBuTtB7HpewfKy0aWJoFLwhJE2axX5bDwlhWadYKvl842XTKdkGmMpdSwyHoca4I9b/jS7KimCyimucuW9cvSqIxDFGdsxjN6SFvn8g4HEZtMkdMqRzNH+Vqsi+uu1vpjDFzVfSLEskozFRiXTHBGZeTaSv+8TvYV9y3J0Gr73+hu/JVmUCqqBdX9QnAAKp7MbsqA+4sdbqk9Vi+lujYn+C1Pp7OodQ2iasq9gjo6NLui21Y7FBO5j/e5fkBD4eAqd7vcjXEsAeMGVqOsdgPhDhl1tdAjFy827YzXXbderuYzjlxmawlMSeKLYHFIbT0UMrOwZ9siex9rChXS3oOPvW8Hmp1ZPNTZ95fs6H15mCglvEqlsJKK2pFGiRUwxGm/UN7uN89vrLaPxJU2Nnz5XnPzQ9KlXH+guSVC65qk9uhqNylSm4dqIz3QCofLTNx86uHU2mOKYFIBfb5MvoXFQU2P9KuEaFSqZIALvuwUxyWUE6AdRJAewWJtslqqb1Yu2KwG5Ru3AclonChp/DVa6QLqBbn48D2t0v0WXunhSwdOOnaJfCL/+eDIVfvCwfU3JvPzSF9OXzlLJDkY1+UpUEIT+mgH3oNXJA49vXjOs/JZZfPqBTyZF/Mc6UYXlGxIOpOefyY28fOMRBxATct4MyDT4V1iI0fwogRCLnnlqMkesK9/+Zk5obH0yEvLyOAV53AYfL6Pn+yrgN5nCIuMsz3ABFwo5wTcQo6A7RTcnmQA8jhB0ANNdn3MCLJkS5G7dGw7R8U7G7/e1Yr5cKJXKKzLohsCgiDVPsmBuPldqueXfaR6Z9ig2WsOo8oLqT7YzxZ9eA4m0F5Ai2jjIZvnCvRmjWlmIWKlaKbFTMM/OneuqzaBtt37x7PLVUO0Ofqyy1Kz1tiQ8YpjxohnVJNUy60uRxHgyJuiqmRKwkd7LRcamt+yUJoeXdlcmi7XrS9x+/rv/SZiDuLmAg30tABgYoVx6rnsVa5zHEcDYDaTIkqxIt8AeWJSpeE1TyYAcuXB2ZMSN10swr300T2QyE4+nYz7PjURgEWDjB39wbhPmdgZz6a2/1+T+9N9nHmj7vcFsWdreh0oYBP9eQOdWV5yur3SmUHx3Vod6yMWN59dp0m2C/Au7HL7TBajMS543g5zNhj1oyJ/AAtehPKGGYqk3T9p5bFQytmifb+FYtXMm+z15VJiN2lj13biK5UBKJ889p3B6PhHQ6W8KK6POUp6FtjNUS5eAn/pzlkJpqHihQVR2hjyc06iernAxK8diI5YGdIPizNZ9JRB5VPH54hp7fSFVl3BflhQtK1CtoIost/uPf0sbjRPeg7n7Etkj30CX0Kn+wvYiYVIKeDJZB44HywDmwAkDcnswAu/BcNwknOuJB5ALhrRZHR0Zna6Uc24OBI9W6gW2RxE4PeC2aHHi757vHHGH4+bDCdY3ONjxNBLY85XVlVJuOkc1cTJixkbHlm/HyhuzwCHSBVmbWZEdXyHrF8XV837/Sm3KSP7qe+rjo1KlJOJeKFOwDDNJsBqZ35jonqV4fuchp7Sj5H1FTb3yqc07SUlIaiJPEzHlL+/WIOPbBqn1Hqu33v2VlI6laITK8YNQStUs/4QmMFsP5PKf2kNe/vyBkIf8eQz98cbrOQhffxyreAb07RSmbA2LlAId/KGDEhzc9xhGCSGVqIgAqyMyZqD7IUolmAaEWlXxgQCuNVSeGzkX0Aaj4TBSEVavnZwminQPUSoeuPO34/3WcDiSANAk8UdPk4bTEJ8FqWBfv3r/5dVypZYo9Yq2BmkQyA1Y4KA6QMhzD3G4G3jZJKHgwPfdozo5h7s9KBL5AVfhjp0fSKCBSOq65cWDSP4qBuK1T1yeMCXFSrznaSl0WtZqgYAyWS1rwDmKcp5p8WJIc24vBVlFLQq+dx1K8UKQGWN+W9BYoSSNFQxKEsFAKkILY5PJWESSM1BlrGJ/J2cavsXbuziy/nXdimFNiHz8tZ+5roR0oSAGtLhITCU42iZ2Vb31MeBwkYMHepIdhQBI+u9/wQEBKVKixlUFY/vlnXzIVzMVqL347p9C7f0AxMA9aK1/pgejdAyVhLcxQb66KUR5CkFGUZHRa6ATYMKgDGO0uX5qttupldOJkF9T0T34Hi6VitxKnj29CsG/j0Cl2xpQwgUwKhh2yAeHbHAae0rbxSJpeNrCeP1xwAoiqimo2Nq5VrD8K78tSEY8E9gIRAKRXDiYKgl9oxwWZsOqLGrJQoBGHpm5n7S2iz+nCuAeaWHBcpxk0kqNysvgEizrWlLQRTk3o/NuHZU0IyqRSG3yw/uzByPwaaJKI5YWp5qkbFQiFDNGmR4Djh/ozD31ZOViXeF51Lj7krACNjyDrn8NGDjFAwaeAMwmyOuIwsddEUB1igdQhEQDAejnhqfhCG9SiAiKNayQtyN4dSJ4e7/vg0w9g5bnZ9vNkXK9JLFwFQ8r9Akq7YqXgYV5DA9qtAdnC8dGhmFD+ifMK0TuhANmp5nMyHJwrPr0TCDU2Q5YkVQ6SMjZuWJqIUHMkd2+urTuXC6A3gmlkkFRDo7+8qXgIfmSAgzNnzbGP3Hx+UJkodNeUYSxUiHTDEYFYhBVDs8uhUYvsfYX/mhBwczZ1xlc285lVh5yo8jVMf8B+E8B3Y/e37cqUULoaaBAPjC8ADZMgQ0rRzZkRCSMwwAnNFzAD1gvMEyv5TV2bG6O9BC0cH8uExJ+1IT9vt4oFsZCkWo1yxuHuHsM+0cEiL/KJ6SJmCv1PI7sRrXb+OIlsnuSDrmtkXL7qD64vWpeyG2mx6vjKSx3gpbaqhYMgwbjtidF8Guaim2dCbXPjYcMJ/NAUdNHZxSWCfhp4IUdQ2g3KjsizlS/vlFLJ7Mp8s+JmZ585MZnfnKL+FI6jb/46eevnpMUcyg6nlIUy7Cw9uh4KKgXVq5/zi/mMz7HkpXJs9jenPq9KUjmfLn9wZSPpBOx1LG2fAV8soV2+md59zUFBL4JyS8AIwe+gWSwp4xlAfMtDqC7nKFztBCvDRmNscFAKZp0c2vz9GK+UC7mRgsKi1dx+wRYunKOtxuHOzgnhF251MDHHvBQ10OOptun8tyD/5b2EmZjJJb0+cISi/UOLjdMQ5bjxagl2I/NWk4qkt/v1i3VbvotwpxCMTRWy1b3HiE6nYOLGL4GiD9JTMhnjNF3rdxeGm1oCo5EiBF2/BGV6OMXDYGKjiVgxY5phOlOYe/cVy4t1i8quGX69HhE94Vh9Ym736G3wWY3eTd/ukRENJEC+c5R1O0vcUshvhnkCplD3n58kknEDUhBMHnPaf/S5vrpU/GIz9I1dBPf5Fsh2AtHwuk3z+UTrGTYmO0AiHo4eQQBblfuKNkHmOA1dodafEBYPHIH7wPwQzc1YER1RlUmh2NmyAgXk6IaswwQFXKWiCysfGEre69EGXh5JGaPGkZhqlMpZgU51mMkJUuiGCjrcn55McrUaEEkUJBzbdMKiWQr8NxfpYCYveH4rX797f/zwRW/QW3d8GtagGHLqKTiUlz8ha8roOjU375Q2KOA60tnxz/Tm3z1Ey8v9BSctGSplgJUA6h0vvnrv5FRE1jQ0v/kNyZKU1vBF3GygL3eyN0/u/sd4Q+FELrIOSHUM1JUiCByVwD3E0EeceODz3hv6xrDJ32wtrK40KgnYiEfuogvSp4HXCu5vU83Dt0mn9sHZMdqqNyG317vFPIegve4wXTUPT82P2jqPUsQJ5a7bTGYLo41nPZFYguGnFD83UKciv5KrwsQJZWhjOljY5WxkkzE7HSzEYtkJv26DD4IlUwplD0XpVSukDckIfTlr/2DfWX72Q9+/icjbQWrZjWlCH5TUXrv++6/MfgGDSZWgvnXH7z59LMhLKS/+IVX6pFcxF/XPaOaV//iTzKyGXExYPrum4Li6tKZ/mQCLIs5H+CbeGA+ig4IG8bucc9hbqbdHK3Eo5qClvGyZ7wTu3Bj+KgV1BwGMj81iG2PMQ93mT357g0ne5fujeRev720PFVfOIP1xurL8RCRwGBK8vyhji82z0x2Z647obXNUMRXTStaOmuIVE23dm4GyRvPXt9Yf+JrI9Fw8vl7M8qNcy/s+kSsU+bzjf/KDSXzM4vFWPK960tL+0/ovup6UEtCpDvrU5f9XF8E7v4u+Y9Q18+i6X4vBGWHug12b/MAAhziiHHrcGlBiLAHBuHUSCDb604lXP+k7W6rDDsUfGcu7MmwYZtiSIs8Oupqhio+qj88c/2BedIpScP2hderIKlqqZoi75lzZIkonUh0/he3w5TEK9HdpxKBwtxLSRK7NKKp444oG+/KYb4vO2xiHDctsDwTiQNymqcXk6H2vACMWk34MVuaKWbHs5Paf/vbJ21fHPRyFgewJZUSnCEN+hlerbhz971CAOLkAH2Y629MZhtEkrn+HnX7j9yGBOqELEiCzLUsrxy8kQNKll3hsuwAuS3FgQqe+H9mSKIgiYc/biLiNbxUGhsbKQYqObeGH7evBsKVN3uPGl8ntop58Fl4iIBHzP+4KexVHyD4g9Qnn7t+cPnsckSulxbq444ZxHriA+1a5sG93mfOpdKnOw9g4/n9xSVDWH3glBOSRDlZCgr2zWnbKVUbD1+eyBl+K5hQi3vtdrl1KTGCP/Pgc2eX70vmt+ugCrCh6KmyXX/uqVur10wxv/jRjHrzq7M1hwmRrC9sKkmRGKI6cVYVZLWYYVTXjKACmkjXgtFL3V3kxuubwjL5IrqOPt3XoORIUyHiNZR4P6QL9ZtJiAGTEiUGVuW2hWokEEkgh4hQidBDBUvSoDMie0U83m+/k4kIw1SEpWuDafv90H2XL5xfW1mYneyN1UqFVGLSVoG9HuUDsPzm0U59eFiOBtV+UOqOOvSlcq4zT3rNwQMQbhPvmKmVejxTOifTxPfM+eb53b0bxbpgvnCBCL74iC+S8qdt3U74LX9q+b54UqOltC+bjvqCNomXHBoQlsc6ufbPOYSkHgiLwNIklWhPx8QfTJ7eQdC0ookpw9p8OkvFaP9BJ2/ZVtCSsW5k1hyGlVZyZyvuE0wt6oesUSoTy2PhPDat//W/e5ovpYhCDBdAEf5QPvmBe30A8sntZ2zCJwLcDDMCCBaQMMghjA7YkMu6j8S4tWthbqIxUg4FVAVdGtauIcq4WOpu3B018050So+7PW5XlLDQDzx5US4dt4zdHiv+rwv3iqCuSgqVwNPmmdy9UbEY763lpwS9GY89/v53L4Rq1VZYtGJAv0EpPfT+skH8j606EyohSqL43IogcIHwjfqEEQ5oSVDytgHCQA+s+YzRfDSWSzXmDXOmHfWtnY8X5mpVQVPEsCZothONnDofTfulfjvnL9ZZwC9X8mOLDPP9PJS7+0+FRfKv0Cz62b5aA/vF3edSPDGW4juj2FUH5LbbD+XtiYEcw7xJMepJtuNRri7jMphvnruSrQACDt35oTFwlT1+FbfhIWLehTBhwiyaGZ2plbMSiw61hcvUciHv34H1PeMSbt/BVuEAhoZ4Rf58POaz7ZmE88hVSUrqHTFWDHQ0w5ILQTI9RYlCrj1hWEFBqgcN2Yqn7/S0t8iXcooZDOQY0Jx47CfG/q3/vo2Sn2qieX5VfvNPZTA/FSsBUTLSTLQLpdopzkeBP/33u/+FfIX3A7C98boCFrGyWMJTmKDxKggwYX2wtzc4TI8O/8ARBkf2970LFHkTDrDhloxdHnwI1uO64dBtD21wy3lbhtxL1RODKXwDWeamPkQ/egq/kxwclPAd/iTIHT6L+4fwZ0hEcmc4sl/6cYMYuYMYMzeGu4r7fQejC+dOL3ZajXomHfRL4rCt4TaSTrDwYRt8wOoggQZeDR5vM3pVvH284XhMhAZbLVHf6enZTtzKz1lqvuDkVr+6EDaSVB0L+qlst+bCwPHUlGWL9wX94WhDYLcfX56yTZ9cKGuBhTFL0axwMEmW9Eg+086fqez89HQ2V22Hx//yvaOF86IdJZqdLj/7Py8sWxIVTTNdYpHwyq9hKn1suQoJqS6MZUdPvfJoIxW0oaTwPIre/X3yMYiBSdCAkEcEcCiJ0arnoSgSeD3mrSHe1TgcphNPjwB/OuEOnBTuuI9awLlH9/vqZLdacUI5OnzabQD6re6Q95VzHk12t/dOZob3QAlH++h4fKa6r8K9xAOPvxKk9Yw/bFF9rEvDH928fl+YUIMo1nR6xGfZ5Bk7V7nw9vYjihH2XflqX9NTVRIJNRVCl9pa4sUvX7q0o+IIM6tfnvv2Xl0V3TV/m6qw5nvR/f+oX9AFvuE2XDCXMoRy7nsbwgRBmnP+y8Mqc/IcPwyn99zTvCOJxG2Agnsvnd3stBv1VOL4eT8PgC2gfcKwoPWGj9+k8Yn4aJ/YARXAKgNuAqpQOOqYddpjBAw0kVwsh6yYDVSfKRp7Yn8RpJtYD+qCGF62sJDqPRmn6bgeshiz9TaJfuMwYjEsyFN+QaCf/s9hxWSy4TNS0xWLPOPPtCKVnTvXH/MTDCGmfPTn3yULTBbtJJM2vv/Xfpo7+9krhp0sNusKYZFdv/35t9/+uKWa4uqff2+dsbf/3dv/I44dyx+98sz9k/fvjoONgUgIZbDxo+in+naUEkRGAyCWz7rdhUH+qwpoFR5at8CGmG9v8t4CHWS+BOSCHcgYVsA4HMNRCDM+B/FnDDg2gz/u/MCw/T4vr4+iG5cubm/NzXTbE+PZdCJezGq8lzZs7Xi25xvMTnPgkpz7/OjR5vPxMxy9Zvgom6E6cut7eMBHh0/siPHreJI8j5dylQDWr06nAmFVUnhS1T+mk6g1k4zGA3Z29aWorIpGWZTTBU3GWra5HrLSQcYbt1h6/lAmCQFYsTbuRBMjscLcR+qyrCaIRsjDZaJTYaRp+yqJ59UQY4n74tTIUN0eycZTkXBiZteC2vSMf1JOE0kpBouSvb6hMmW+cmEtRI0CBJbqi2fjpZFYrHExjl/szWs8t1H67m3yL8Ffq+jXNl4fA++oZ8A1BhYRf0wE3pDBm8F+QAwcQMEBbja4InGwB4A4VvMLZE6OENyqvcdHeJoSo21AasbFOeE7vyKF7DocDIWwcIdyhYUJL7IBiKhWvZaGNQJIr+JV6QRIO2FfkIWax3Sx0z75kN9JXdo9UuedAelpwMkL/mBrabd5kZDKyw0t7GTNgM6kTLQmJz76+OYrFSqH/bmJeESw1jRWPWcz6j+IjKhKgqwbWrCz/NTbf2msKvXXXsnZ8UgoGioxEsyfSWVuvnVz6xGGmb5YcarhJXCwcgqI6PXTtbfOBEWsDLhgESFyF2x/E0/1zRbcTxbISB+WLwzo/CaQcsokbkqQbpyO82ckIV0IEwGVddVQdYPvzCAVSOs1DUznpQQwR8uyN5BhoAPTBifZaFh9t97RNeEiEmZ7cEWA43uOPuFHXLV/7h1dEFkGMiz0Yy988prg9zJGj914+Pru+Z2t9bWlU3OzzYlGvVrOpKNOKGCZisQbaD6IhZYn4XCeU9gF3HL/9h4TGe44dI+3vdP4SHZYONgKezt6Ljtu4JPtyqGKPObPPP9bZuyXX46MN7SC/EzmoYgZHTl9NlHMq1IyFQ/4lNz75nFAqi8vhUI1M4CJ/+B6zGzopOBTiTrqi7xwR8zPPrLbCmVV1ogxXaaU+jMLB2qu9/CNRioWUnXnIx+MYCY7Fs0+nraxqjnpUCBENKmoN1ZErCkYhzB/dDn8xCMJTMJMsOMAHwxIrPPsVYpVWaiNBLJQOkRrsrIdIKqm6rwPzwOuBqrR+/8Eovf/CSY6rVALfq57X+98HObjYBQfx74KgOGN4ef+LwrpXYkAAAB42q1UwU7bQBAdBwhqKiJyqUSlqitOREqcONADASFFoEhREIgEIW5oSTbxQmJH9iaBey/9gEpVL/2EHvoJ/YZ+QsVv9Hm9FAKUCIpX9r4dz7yZnZldInpjpcmi+NmlrwZblLFeG5ygeStv8AxlrU8Gz9KSdWXwHL1PVAxO0lLis8EL1trcksFpepv8aPAiZZI/Dc7QfPI3mK3ZV1h90V4ibNEyXRmcoLT1zuAZalgfDJ6lkvXD4DnaSlgGJ6mU4AYvJNzEd4PTtJbcM3iRlpPfDM5QOvmLtsmnAV1SQJK65JIiRivUoizmEhUx1imvkYOX0Q4JCrWuh1UTmhISD7OgHCQ1jW1KTWV2aA2ojj9cc1Xwj1MbPH1Y0bY/uAxk11VspZVlpWJxPV8qOkW2I0LZ9VizJYXXEjlW81p26q6ys8bqLvdYpcXbog+2OqgPQX1MJwiMU08HFQANEICEa6rzQ3F8ss17shvwgSshasCiS0Noc+hSQ3SHPQ5QxdY8bCiaA2gIvSVbJ6isNzXNW/4ud9X3VNUPuoKV7CIrs3vR5P96fwb7I2xH0Ax0SX1dBgf7cGgDSGF0YD/E7GtmzxRxpLVWUUo6EkEofY85trPBlOrwofJd6aEQI8dezb50tE9r19wTGjbi2aSxHjZakIPbpTPMF1jHdd6Cn/9t7Ek/50aLT+jc9peDxzE8RdEwnalQV2yEbxuS615ktAeGvu7F6TmPDmgKOtEqnGBpAnWAxroWEVus0dN2UeZC43kI3NaxMB2d0NY1XKmM9uFJ6N3fMO9OMES5f7j37InIJv0yRDXCK3WvnOIbyW7yw7XHCh1orHAaU7pCCvGUqYARgi2q3ACyEL5CzXWd8QIiryLSf10/uQfvH7ayOR6P7T5X7hm/sHGMt7LT7iRjcw4RjyWxXS41lsplDRGKYCTaLLoY2B7vi/tXgp1KHboyjFWafkeNeSAYBD3ZEl4I46HXFgFTrmDN2i7bHwgvVt6NFXLs1vG1YzJjy/iIyx4/7Qmm4+GsWjlgXJVTrlKDcqEQtgI5UKEdyl4UeGG/iqw9K9WPEb7ovf0HmDGZxgAAAHjabYxJDoJAFAXrNxoPgIoISwdQlBachwUJ9F3YsPMEHhxaw9JKXmpTeSh+tB8y/pHYCQoHlzETpnjM8JkTELJgyYo1ETEbtrbesSdFc7B/OUdOnLlw5cadB09eosSRgQxH76bWutBfV8aUvavepgNBrREyAAEAAf//AA8AAAABAAAAAMw9os8AAAAAxvkyTwAAAADRt3yT"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Fraktur-Bold.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Fraktur-Bold.woff",
"text": 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"
},
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"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Fraktur-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Bold.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Bold.woff",
"text": 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"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Italic.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-BoldItalic.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-BoldItalic.woff",
"text": 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"
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"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-Italic.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Bold.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Bold.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Italic.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Italic.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Script-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Script-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size1-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size1-Regular.woff",
"text": 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"
},
"$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size2-Regular.woff": {
"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size2-Regular.woff",
"text": 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"
},
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"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size3-Regular.woff",
"text": 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"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size4-Regular.woff",
"text": 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"
},
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"type": "application/font-woff",
"title": "$:/plugins/tiddlywiki/katex/fonts/KaTeX_Typewriter-Regular.woff",
"text": 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i[this.color]||this.color}};t.exports=a},{}],5:[function(e,t,r){function a(e,t,r){var i=\"KaTeX parse error: \"+e;if(t!==undefined&&r!==undefined){i+=\" at position \"+r+\": \";var n=t._input;n=n.slice(0,r)+\"\\u0332\"+n.slice(r);var s=Math.max(0,r-15);var l=r+15;i+=n.slice(s,l)}var o=new Error(i);o.name=\"ParseError\";o.__proto__=a.prototype;o.position=r;return o}a.prototype.__proto__=Error.prototype;t.exports=a},{}],6:[function(e,t,r){var a=e(\"./functions\");var i=e(\"./environments\");var n=e(\"./Lexer\");var s=e(\"./symbols\");var l=e(\"./utils\");var o=e(\"./parseData\");var u=e(\"./ParseError\");function p(e,t){this.lexer=new n(e);this.settings=t}var h=o.ParseNode;function c(e,t){this.result=e;this.isFunction=t}p.prototype.expect=function(e,t){if(this.nextToken.text!==e){throw new u(\"Expected '\"+e+\"', got '\"+this.nextToken.text+\"'\",this.lexer,this.nextToken.position)}if(t!==false){this.consume()}};p.prototype.consume=function(){this.pos=this.nextToken.position;this.nextToken=this.lexer.lex(this.pos,this.mode)};p.prototype.parse=function(){this.mode=\"math\";this.pos=0;this.nextToken=this.lexer.lex(this.pos,this.mode);var e=this.parseInput();return e};p.prototype.parseInput=function(){var e=this.parseExpression(false);this.expect(\"EOF\",false);return e};var v=[\"}\",\"\\\\end\",\"\\\\right\",\"&\",\"\\\\\\\\\",\"\\\\cr\"];p.prototype.parseExpression=function(e,t){var r=[];while(true){var a=this.nextToken;var i=this.pos;if(v.indexOf(a.text)!==-1){break}if(t&&a.text===t){break}var n=this.parseAtom();if(!n){if(!this.settings.throwOnError&&a.text[0]===\"\\\\\"){var s=this.handleUnsupportedCmd();r.push(s);i=a.position;continue}break}if(e&&n.type===\"infix\"){this.pos=i;this.nextToken=a;break}r.push(n)}return this.handleInfixNodes(r)};p.prototype.handleInfixNodes=function(e){var t=-1;var r;for(var a=0;a<e.length;a++){var i=e[a];if(i.type===\"infix\"){if(t!==-1){throw new u(\"only one infix operator per group\",this.lexer,-1)}t=a;r=i.value.replaceWith}}if(t!==-1){var n;var s;var l=e.slice(0,t);var o=e.slice(t+1);if(l.length===1&&l[0].type===\"ordgroup\"){n=l[0]}else{n=new h(\"ordgroup\",l,this.mode)}if(o.length===1&&o[0].type===\"ordgroup\"){s=o[0]}else{s=new h(\"ordgroup\",o,this.mode)}var p=this.callFunction(r,[n,s],null);return[new h(p.type,p,this.mode)]}else{return e}};var m=1;p.prototype.handleSupSubscript=function(e){var t=this.nextToken.text;var r=this.pos;this.consume();var i=this.parseGroup();if(!i){if(!this.settings.throwOnError&&this.nextToken.text[0]===\"\\\\\"){return this.handleUnsupportedCmd()}else{throw new u(\"Expected group after '\"+t+\"'\",this.lexer,r+1)}}else if(i.isFunction){var n=a[i.result].greediness;if(n>m){return this.parseFunction(i)}else{throw new u(\"Got function '\"+i.result+\"' with no arguments \"+\"as \"+e,this.lexer,r+1)}}else{return i.result}};p.prototype.handleUnsupportedCmd=function(){var e=this.nextToken.text;var t=[];for(var r=0;r<e.length;r++){t.push(new h(\"textord\",e[r],\"text\"))}var a=new h(\"text\",{body:t,type:\"text\"},this.mode);var i=new h(\"color\",{color:this.settings.errorColor,value:[a],type:\"color\"},this.mode);this.consume();return i};p.prototype.parseAtom=function(){var e=this.parseImplicitGroup();if(this.mode===\"text\"){return e}var t;var r;while(true){var a=this.nextToken;if(a.text===\"\\\\limits\"||a.text===\"\\\\nolimits\"){if(!e||e.type!==\"op\"){throw new u(\"Limit controls must follow a math operator\",this.lexer,this.pos)}else{var i=a.text===\"\\\\limits\";e.value.limits=i;e.value.alwaysHandleSupSub=true}this.consume()}else if(a.text===\"^\"){if(t){throw new u(\"Double superscript\",this.lexer,this.pos)}t=this.handleSupSubscript(\"superscript\")}else if(a.text===\"_\"){if(r){throw new u(\"Double subscript\",this.lexer,this.pos)}r=this.handleSupSubscript(\"subscript\")}else if(a.text===\"'\"){var n=new h(\"textord\",\"\\\\prime\",this.mode);var s=[n];this.consume();while(this.nextToken.text===\"'\"){s.push(n);this.consume()}t=new h(\"ordgroup\",s,this.mode)}else{break}}if(t||r){return new h(\"supsub\",{base:e,sup:t,sub:r},this.mode)}else{return e}};var f=[\"\\\\tiny\",\"\\\\scriptsize\",\"\\\\footnotesize\",\"\\\\small\",\"\\\\normalsize\",\"\\\\large\",\"\\\\Large\",\"\\\\LARGE\",\"\\\\huge\",\"\\\\Huge\"];var d=[\"\\\\displaystyle\",\"\\\\textstyle\",\"\\\\scriptstyle\",\"\\\\scriptscriptstyle\"];p.prototype.parseImplicitGroup=function(){var e=this.parseSymbol();if(e==null){return this.parseFunction()}var t=e.result;var r;if(t===\"\\\\left\"){var a=this.parseFunction(e);r=this.parseExpression(false);this.expect(\"\\\\right\",false);var n=this.parseFunction();return new h(\"leftright\",{body:r,left:a.value.value,right:n.value.value},this.mode)}else if(t===\"\\\\begin\"){var s=this.parseFunction(e);var o=s.value.name;if(!i.hasOwnProperty(o)){throw new u(\"No such environment: \"+o,this.lexer,s.value.namepos)}var p=i[o];var c=this.parseArguments(\"\\\\begin{\"+o+\"}\",p);var v={mode:this.mode,envName:o,parser:this,lexer:this.lexer,positions:c.pop()};var m=p.handler(v,c);this.expect(\"\\\\end\",false);var g=this.parseFunction();if(g.value.name!==o){throw new u(\"Mismatch: \\\\begin{\"+o+\"} matched \"+\"by \\\\end{\"+g.value.name+\"}\",this.lexer)}m.position=g.position;return m}else if(l.contains(f,t)){r=this.parseExpression(false);return new h(\"sizing\",{size:\"size\"+(l.indexOf(f,t)+1),value:r},this.mode)}else if(l.contains(d,t)){r=this.parseExpression(true);return new h(\"styling\",{style:t.slice(1,t.length-5),value:r},this.mode)}else{return this.parseFunction(e)}};p.prototype.parseFunction=function(e){if(!e){e=this.parseGroup()}if(e){if(e.isFunction){var t=e.result;var r=a[t];if(this.mode===\"text\"&&!r.allowedInText){throw new u(\"Can't use function '\"+t+\"' in text mode\",this.lexer,e.position)}var i=this.parseArguments(t,r);var n=this.callFunction(t,i,i.pop());return new h(n.type,n,this.mode)}else{return e.result}}else{return null}};p.prototype.callFunction=function(e,t,r){var i={funcName:e,parser:this,lexer:this.lexer,positions:r};return a[e].handler(i,t)};p.prototype.parseArguments=function(e,t){var r=t.numArgs+t.numOptionalArgs;if(r===0){return[[this.pos]]}var i=t.greediness;var n=[this.pos];var s=[];for(var l=0;l<r;l++){var o=t.argTypes&&t.argTypes[l];var p;if(l<t.numOptionalArgs){if(o){p=this.parseSpecialGroup(o,true)}else{p=this.parseOptionalGroup()}if(!p){s.push(null);n.push(this.pos);continue}}else{if(o){p=this.parseSpecialGroup(o)}else{p=this.parseGroup()}if(!p){if(!this.settings.throwOnError&&this.nextToken.text[0]===\"\\\\\"){p=new c(this.handleUnsupportedCmd(this.nextToken.text),false)}else{throw new u(\"Expected group after '\"+e+\"'\",this.lexer,this.pos)}}}var h;if(p.isFunction){var v=a[p.result].greediness;if(v>i){h=this.parseFunction(p)}else{throw new u(\"Got function '\"+p.result+\"' as \"+\"argument to '\"+e+\"'\",this.lexer,this.pos-1)}}else{h=p.result}s.push(h);n.push(this.pos)}s.push(n);return s};p.prototype.parseSpecialGroup=function(e,t){var r=this.mode;if(e===\"original\"){e=r}if(e===\"color\"||e===\"size\"){var a=this.nextToken;if(t&&a.text!==\"[\"){return null}this.mode=e;this.expect(t?\"[\":\"{\");var i=this.nextToken;this.mode=r;var n;if(e===\"color\"){n=i.text}else{n=i.data}this.consume();this.expect(t?\"]\":\"}\");return new c(new h(e,n,r),false)}else if(e===\"text\"){var s=this.lexer.lex(this.pos,\"whitespace\");this.pos=s.position}this.mode=e;this.nextToken=this.lexer.lex(this.pos,e);var l;if(t){l=this.parseOptionalGroup()}else{l=this.parseGroup()}this.mode=r;this.nextToken=this.lexer.lex(this.pos,r);return l};p.prototype.parseGroup=function(){if(this.nextToken.text===\"{\"){this.consume();var e=this.parseExpression(false);this.expect(\"}\");return new c(new h(\"ordgroup\",e,this.mode),false)}else{return this.parseSymbol()}};p.prototype.parseOptionalGroup=function(){if(this.nextToken.text===\"[\"){this.consume();var e=this.parseExpression(false,\"]\");this.expect(\"]\");return new c(new h(\"ordgroup\",e,this.mode),false)}else{return null}};p.prototype.parseSymbol=function(){var e=this.nextToken;if(a[e.text]){this.consume();return new c(e.text,true)}else if(s[this.mode][e.text]){this.consume();return new c(new h(s[this.mode][e.text].group,e.text,this.mode),false)}else{return null}};p.prototype.ParseNode=h;t.exports=p},{\"./Lexer\":3,\"./ParseError\":5,\"./environments\":15,\"./functions\":18,\"./parseData\":20,\"./symbols\":22,\"./utils\":23}],7:[function(e,t,r){function a(e,t){return e===undefined?t:e}function i(e){e=e||{};this.displayMode=a(e.displayMode,false);this.throwOnError=a(e.throwOnError,true);this.errorColor=a(e.errorColor,\"#cc0000\")}t.exports=i},{}],8:[function(e,t,r){function a(e,t,r,a){this.id=e;this.size=t;this.cramped=a;this.sizeMultiplier=r}a.prototype.sup=function(){return m[f[this.id]]};a.prototype.sub=function(){return m[d[this.id]]};a.prototype.fracNum=function(){return m[g[this.id]]};a.prototype.fracDen=function(){return m[y[this.id]]};a.prototype.cramp=function(){return m[b[this.id]]};a.prototype.cls=function(){return c[this.size]+(this.cramped?\" cramped\":\" uncramped\")};a.prototype.reset=function(){return v[this.size]};var i=0;var n=1;var s=2;var l=3;var o=4;var u=5;var p=6;var h=7;var c=[\"displaystyle textstyle\",\"textstyle\",\"scriptstyle\",\"scriptscriptstyle\"];var v=[\"reset-textstyle\",\"reset-textstyle\",\"reset-scriptstyle\",\"reset-scriptscriptstyle\"];var m=[new a(i,0,1,false),new a(n,0,1,true),new a(s,1,1,false),new a(l,1,1,true),new a(o,2,.7,false),new a(u,2,.7,true),new a(p,3,.5,false),new a(h,3,.5,true)];var f=[o,u,o,u,p,h,p,h];var d=[u,u,u,u,h,h,h,h];var g=[s,l,o,u,p,h,p,h];var y=[l,l,u,u,h,h,h,h];var b=[n,n,l,l,u,u,h,h];t.exports={DISPLAY:m[i],TEXT:m[s],SCRIPT:m[o],SCRIPTSCRIPT:m[p]}},{}],9:[function(e,t,r){var a=e(\"./domTree\");var i=e(\"./fontMetrics\");var n=e(\"./symbols\");var s=e(\"./utils\");var l=[\"\\\\Gamma\",\"\\\\Delta\",\"\\\\Theta\",\"\\\\Lambda\",\"\\\\Xi\",\"\\\\Pi\",\"\\\\Sigma\",\"\\\\Upsilon\",\"\\\\Phi\",\"\\\\Psi\",\"\\\\Omega\"];var o=[\"\\u0131\",\"\\u0237\"];var u=function(e,t,r,s,l){if(n[r][e]&&n[r][e].replace){e=n[r][e].replace}var o=i.getCharacterMetrics(e,t);var u;if(o){u=new a.symbolNode(e,o.height,o.depth,o.italic,o.skew,l)}else{typeof console!==\"undefined\"&&console.warn(\"No character metrics for '\"+e+\"' in style '\"+t+\"'\");u=new a.symbolNode(e,0,0,0,0,l)}if(s){u.style.color=s}return u};var p=function(e,t,r,a){if(e===\"\\\\\"||n[t][e].font===\"main\"){return u(e,\"Main-Regular\",t,r,a)}else{return u(e,\"AMS-Regular\",t,r,a.concat([\"amsrm\"]))}};var h=function(e,t,r,a,i){if(i===\"mathord\"){return c(e,t,r,a)}else if(i===\"textord\"){return u(e,\"Main-Regular\",t,r,a.concat([\"mathrm\"]))}else{throw new Error(\"unexpected type: \"+i+\" in mathDefault\")}};var c=function(e,t,r,a){if(/[0-9]/.test(e.charAt(0))||s.contains(o,e)||s.contains(l,e)){return u(e,\"Main-Italic\",t,r,a.concat([\"mainit\"]))}else{return u(e,\"Math-Italic\",t,r,a.concat([\"mathit\"]))}};var v=function(e,t,r){var a=e.mode;var l=e.value;if(n[a][l]&&n[a][l].replace){l=n[a][l].replace}var p=[\"mord\"];var v=t.getColor();var m=t.font;if(m){if(m===\"mathit\"||s.contains(o,l)){return c(l,a,v,p)}else{var f=w[m].fontName;if(i.getCharacterMetrics(l,f)){return u(l,f,a,v,p.concat([m]))}else{return h(l,a,v,p,r)}}}else{return h(l,a,v,p,r)}};var m=function(e){var t=0;var r=0;var a=0;if(e.children){for(var i=0;i<e.children.length;i++){if(e.children[i].height>t){t=e.children[i].height}if(e.children[i].depth>r){r=e.children[i].depth}if(e.children[i].maxFontSize>a){a=e.children[i].maxFontSize}}}e.height=t;e.depth=r;e.maxFontSize=a};var f=function(e,t,r){var i=new a.span(e,t);m(i);if(r){i.style.color=r}return i};var d=function(e){var t=new a.documentFragment(e);m(t);return t};var g=function(e,t){var r=f([],[new a.symbolNode(\"\\u200b\")]);r.style.fontSize=t/e.style.sizeMultiplier+\"em\";var i=f([\"fontsize-ensurer\",\"reset-\"+e.size,\"size5\"],[r]);return i};var y=function(e,t,r,i){var n;var s;var l;if(t===\"individualShift\"){var o=e;e=[o[0]];n=-o[0].shift-o[0].elem.depth;s=n;for(l=1;l<o.length;l++){var u=-o[l].shift-s-o[l].elem.depth;var p=u-(o[l-1].elem.height+o[l-1].elem.depth);s=s+u;e.push({type:\"kern\",size:p});e.push(o[l])}}else if(t===\"top\"){var h=r;for(l=0;l<e.length;l++){if(e[l].type===\"kern\"){h-=e[l].size}else{h-=e[l].elem.height+e[l].elem.depth}}n=h}else if(t===\"bottom\"){n=-r}else if(t===\"shift\"){n=-e[0].elem.depth-r}else if(t===\"firstBaseline\"){n=-e[0].elem.depth}else{n=0}var c=0;for(l=0;l<e.length;l++){if(e[l].type===\"elem\"){c=Math.max(c,e[l].elem.maxFontSize)}}var v=g(i,c);var m=[];s=n;for(l=0;l<e.length;l++){if(e[l].type===\"kern\"){s+=e[l].size}else{var d=e[l].elem;var y=-d.depth-s;s+=d.height+d.depth;var b=f([],[v,d]);b.height-=y;b.depth+=y;b.style.top=y+\"em\";m.push(b)}}var x=f([\"baseline-fix\"],[v,new a.symbolNode(\"\\u200b\")]);m.push(x);var w=f([\"vlist\"],m);w.height=Math.max(s,w.height);w.depth=Math.max(-n,w.depth);return w};var b={size1:.5,size2:.7,size3:.8,size4:.9,size5:1,size6:1.2,size7:1.44,size8:1.73,size9:2.07,size10:2.49};var x={\"\\\\qquad\":{size:\"2em\",className:\"qquad\"},\"\\\\quad\":{size:\"1em\",className:\"quad\"},\"\\\\enspace\":{size:\"0.5em\",className:\"enspace\"},\"\\\\;\":{size:\"0.277778em\",className:\"thickspace\"},\"\\\\:\":{size:\"0.22222em\",className:\"mediumspace\"},\"\\\\,\":{size:\"0.16667em\",className:\"thinspace\"},\"\\\\!\":{size:\"-0.16667em\",className:\"negativethinspace\"}};var w={mathbf:{variant:\"bold\",fontName:\"Main-Bold\"},mathrm:{variant:\"normal\",fontName:\"Main-Regular\"},mathbb:{variant:\"double-struck\",fontName:\"AMS-Regular\"},mathcal:{variant:\"script\",fontName:\"Caligraphic-Regular\"},mathfrak:{variant:\"fraktur\",fontName:\"Fraktur-Regular\"},mathscr:{variant:\"script\",fontName:\"Script-Regular\"},mathsf:{variant:\"sans-serif\",fontName:\"SansSerif-Regular\"},mathtt:{variant:\"monospace\",fontName:\"Typewriter-Regular\"}};t.exports={fontMap:w,makeSymbol:u,mathsym:p,makeSpan:f,makeFragment:d,makeVList:y,makeOrd:v,sizingMultiplier:b,spacingFunctions:x}},{\"./domTree\":14,\"./fontMetrics\":16,\"./symbols\":22,\"./utils\":23}],10:[function(e,t,r){var a=e(\"./ParseError\");var i=e(\"./Style\");var n=e(\"./buildCommon\");var s=e(\"./delimiter\");var l=e(\"./domTree\");var o=e(\"./fontMetrics\");var u=e(\"./utils\");var p=n.makeSpan;var h=function(e,t,r){var a=[];for(var i=0;i<e.length;i++){var n=e[i];a.push(b(n,t,r));r=n}return a};var c={mathord:\"mord\",textord:\"mord\",bin:\"mbin\",rel:\"mrel\",text:\"mord\",open:\"mopen\",close:\"mclose\",inner:\"minner\",genfrac:\"mord\",array:\"mord\",spacing:\"mord\",punct:\"mpunct\",ordgroup:\"mord\",op:\"mop\",katex:\"mord\",overline:\"mord\",underline:\"mord\",rule:\"mord\",leftright:\"minner\",sqrt:\"mord\",accent:\"mord\"};var v=function(e){if(e==null){return c.mathord}else if(e.type===\"supsub\"){return v(e.value.base)}else if(e.type===\"llap\"||e.type===\"rlap\"){return v(e.value)}else if(e.type===\"color\"){return v(e.value.value)}else if(e.type===\"sizing\"){return v(e.value.value)}else if(e.type===\"styling\"){return v(e.value.value)}else if(e.type===\"delimsizing\"){return c[e.value.delimType]}else{return c[e.type]}};var m=function(e,t){if(!e){return false}else if(e.type===\"op\"){return e.value.limits&&(t.style.size===i.DISPLAY.size||e.value.alwaysHandleSupSub)}else if(e.type===\"accent\"){return d(e.value.base)}else{return null}};var f=function(e){if(!e){return 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"$:/plugins/tiddlywiki/katex/latex-parser.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/katex/latex-parser.js\ntype: application/javascript\nmodule-type: wikirule\n\nWiki text inline rule for LaTeX. For example:\n\n```\n\t$$latex-goes-here$$\n```\n\nThis wikiparser can be modified using the rules eg:\n\n```\n\\rules except latex-parser \n\\rules only latex-parser \n```\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"latex-parser\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\$\\$(?!\\$)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\tvar reEnd = /\\$\\$/mg;\n\t// Look for the end marker\n\treEnd.lastIndex = this.parser.pos;\n\tvar match = reEnd.exec(this.parser.source),\n\t\ttext,\n\t\tdisplayMode;\n\t// Process the text\n\tif(match) {\n\t\ttext = this.parser.source.substring(this.parser.pos,match.index);\n\t\tdisplayMode = text.indexOf('\\n') != -1;\n\t\tthis.parser.pos = match.index + match[0].length;\n\t} else {\n\t\ttext = this.parser.source.substr(this.parser.pos);\n\t\tdisplayMode = false;\n\t\tthis.parser.pos = this.parser.sourceLength;\n\t}\n\treturn [{\n\t\ttype: \"latex\",\n\t\tattributes: {\n\t\t\ttext: {\n\t\t\t\ttype: \"text\",\n\t\t\t\tvalue: text\n\t\t\t},\n\t\t\tdisplayMode: {\n\t\t\t\ttype: \"text\",\n\t\t\t\tvalue: displayMode ? \"true\" : \"false\"\n\t\t\t}\n\t\t}\n\t}];\n};\n\n})();\n",
"title": "$:/plugins/tiddlywiki/katex/latex-parser.js",
"type": "application/javascript",
"module-type": "wikirule"
},
"$:/plugins/tiddlywiki/katex/readme": {
"title": "$:/plugins/tiddlywiki/katex/readme",
"text": "This is a TiddlyWiki plugin for mathematical typesetting based on [[KaTeX from Khan Academy|http://khan.github.io/KaTeX/]].\n\nIt is completely self-contained, and doesn't need an Internet connection in order to work. It works both in the browser and under Node.js.\n\nIt is currently based on KaTeX version 0.6.0. See https://github.com/Khan/KaTeX/releases for details of releases.\n\n[[Source code|https://github.com/Jermolene/TiddlyWiki5/blob/master/plugins/tiddlywiki/katex]]\n"
},
"$:/plugins/tiddlywiki/katex/styles": {
"title": "$:/plugins/tiddlywiki/katex/styles",
"tags": "[[$:/tags/Stylesheet]]",
"text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\n/* KaTeX styles */\n\n{{$:/plugins/tiddlywiki/katex/katex.min.css}}\n\n/* Force text-rendering (see https://github.com/Jermolene/TiddlyWiki5/issues/2500) */\n\n.katex {\n text-rendering: auto;\n}\n\n/* Override font URLs */\n\n@font-face {\n\tfont-family: KaTeX_AMS;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_AMS-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Caligraphic;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Bold.woff'>>) format('woff');\n\tfont-weight: 700;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Caligraphic;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Caligraphic-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Fraktur;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Fraktur-Bold.woff'>>) format('woff');\n\tfont-weight: 700;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Fraktur;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Fraktur-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Main;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Bold.woff'>>) format('woff');\n\tfont-weight: 700;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Main;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Italic.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: italic;\n}\n\n@font-face {\n\tfont-family: KaTeX_Main;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Main-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Math;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Math-Italic.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: italic;\n}\n\n@font-face {\n\tfont-family: KaTeX_SansSerif;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_SansSerif-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Script;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Script-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Size1;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size1-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Size2;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size2-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Size3;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size3-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Size4;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Size4-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n\n@font-face {\n\tfont-family: KaTeX_Typewriter;\n\tsrc: url(<<datauri '$:/plugins/tiddlywiki/katex/fonts/KaTeX_Typewriter-Regular.woff'>>) format('woff');\n\tfont-weight: 400;\n\tfont-style: normal;\n}\n"
},
"$:/plugins/tiddlywiki/katex/usage": {
"title": "$:/plugins/tiddlywiki/katex/usage",
"text": "The usual way to include ~LaTeX is to use `$$`. For example:\n\n```\n$$\\displaystyle f(x) = \\int_{-\\infty}^\\infty\\hat f(\\xi)\\,e^{2 \\pi i \\xi x}\\,d\\xi$$\n```\n\nSingle line equations will render in inline mode. If there are newlines between the `$$` delimiters, the equations will be rendered in display mode.\n\nThe underlying widget can also be used directly, giving more flexibility:\n\n```\n<$latex text=\"f(x) = \\int_{-\\infty}^\\infty\\hat f(\\xi)\\,e^{2 \\pi i \\xi x}\\,d\\xi\" displayMode=\"true\"></$latex>\n```\n\nThe KaTeX widget is provided under the name `<$latex>` and is also available under the alias `<$katex>`. It's better to use the generic `<$latex>` name unless you are running multiple ~LaTeX plugins and wish to specifically target KaTeX.\n"
},
"$:/plugins/tiddlywiki/katex/wrapper.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/katex/wrapper.js\ntype: application/javascript\nmodule-type: widget\n\nWrapper for `katex.min.js` that provides a `<$latex>` widget. It is also available under the alias `<$katex>`\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar katex = require(\"$:/plugins/tiddlywiki/katex/katex.min.js\"),\n\tWidget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar KaTeXWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nKaTeXWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nKaTeXWidget.prototype.render = function(parent,nextSibling) {\n\t// Housekeeping\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Get the source text\n\tvar text = this.getAttribute(\"text\",this.parseTreeNode.text || \"\");\n\tvar displayMode = this.getAttribute(\"displayMode\",this.parseTreeNode.displayMode || \"false\") === \"true\";\n\t// Render it into a span\n\tvar span = this.document.createElement(\"span\"),\n\t\toptions = {throwOnError: false, displayMode: displayMode};\n\ttry {\n\t\tif(!this.document.isTiddlyWikiFakeDom) {\n\t\t\tkatex.render(text,span,options);\n\t\t} else {\n\t\t\tspan.innerHTML = katex.renderToString(text,options);\n\t\t}\n\t} catch(ex) {\n\t\tspan.className = \"tc-error\";\n\t\tspan.textContent = ex;\n\t}\n\t// Insert it into the DOM\n\tparent.insertBefore(span,nextSibling);\n\tthis.domNodes.push(span);\n};\n\n/*\nCompute the internal state of the widget\n*/\nKaTeXWidget.prototype.execute = function() {\n\t// Nothing to do for a katex widget\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nKaTeXWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.text) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn false;\t\n\t}\n};\n\nexports.latex = KaTeXWidget;\nexports.katex = KaTeXWidget;\n\n})();\n\n",
"title": "$:/plugins/tiddlywiki/katex/wrapper.js",
"type": "application/javascript",
"module-type": "widget"
}
}
}
{
"tiddlers": {
"$:/plugins/tiddlywiki/railroad/components.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/railroad/components.js\ntype: application/javascript\nmodule-type: library\n\nComponents of a railroad diagram.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar railroad = require(\"$:/plugins/tiddlywiki/railroad/railroad-diagrams.js\");\n\n/////////////////////////// Base component\n\nvar Component = function() {\n\tthis.type = \"Component\";\n};\n\n// Set up a leaf component\nComponent.prototype.initialiseLeaf = function(type,text) {\n\tthis.type = type;\n\tthis.text = text;\n};\n\n// Set up a component with a single child\nComponent.prototype.initialiseWithChild = function(type,content) {\n\tthis.type = type;\n\tthis.child = toSingleChild(content);\n};\n\n// Set up a component with an array of children\nComponent.prototype.initialiseWithChildren = function(type,content) {\n\tthis.type = type;\n\t// Force the content to be an array\n\tthis.children = $tw.utils.isArray(content) ? content : [content];\n}\n\n// Return an array of the SVG strings of an array of children\nComponent.prototype.getSvgOfChildren = function() {\n\treturn this.children.map(function(child) {\n\t\treturn child.toSvg();\n\t});\n}\n\nComponent.prototype.toSvg = function() {\n\treturn \"\";\n}\n\nComponent.prototype.debug = function(output,indent) {\n\toutput.push(indent);\n\toutput.push(this.type);\n\t// Add the text of a leaf component\n\tif(this.text && this.text !== \"\") {\n\t\toutput.push(\": \");\n\t\toutput.push(this.text);\n\t}\n\t// Flag the normal route\n\tif(this.normal !== undefined) {\n\t\tif(this.normal === true) {\n\t\t\toutput.push(\" (normal)\");\n\t\t} else if(this.normal !== false) {\n\t\t\toutput.push(\" (normal: \");\n\t\t\toutput.push(this.normal);\n\t\t\toutput.push(\")\");\n\t\t}\n\t}\n\toutput.push(\"\\n\");\n\tvar contentIndent = indent + \" \";\n\t// Add the one child\n\tif(this.child) {\n\t\tthis.child.debug(output,contentIndent);\n\t}\n\t// Add the array of children\n\tif(this.children) {\n\t\tthis.debugArray(this.children,output,contentIndent);\n\t}\n \t// Add the separator if there is one\n\tif(this.separator) {\n\t\toutput.push(indent);\n\t\toutput.push(\"(separator)\\n\");\n\t\tthis.separator.debug(output,contentIndent);\n\t}\n};\n\nComponent.prototype.debugArray = function(array,output,indent) {\n\tfor(var i=0; i<array.length; i++) {\n\t\tvar item = array[i];\n\t\t// Choice content is a special case: we number the branches\n\t\tif(item.isChoiceBranch) {\n\t\t\toutput.push(indent);\n\t\t\toutput.push(\"(\");\n\t\t\toutput.push(i);\n\t\t\toutput.push(\")\\n\");\n\t\t\titem.debug(output,\" \"+indent);\n\t\t} else {\n\t\t\titem.debug(output,indent);\n\t\t}\n\t}\n}\n\nvar toSingleChild = function(content) {\n\tif($tw.utils.isArray(content)) {\n\t\t// Reduce an array of one child to just the child\n\t\tif(content.length === 1) {\n\t\t\treturn content[0];\n\t\t} else {\n\t\t\t// Never allow an empty sequence\n\t\t \tif(content.length === 0) {\n \t\t\t\tcontent.push(new Dummy());\n\t\t \t}\n\t\t\t// Wrap multiple children into a single sequence component\n\t\t\treturn new Sequence(content);\n\t\t}\n\t} else {\n\t\t// Already single\n\t\treturn content;\n\t}\n}\n\n/////////////////////////// Leaf components\n\nvar Comment = function(text) {\n\tthis.initialiseLeaf(\"Comment\",text);\n};\n\nComment.prototype = new Component();\n\nComment.prototype.toSvg = function() {\n\treturn railroad.Comment(this.text);\n}\n\nvar Dummy = function() {\n\tthis.initialiseLeaf(\"Dummy\");\n};\n\nDummy.prototype = new Component();\n\nDummy.prototype.toSvg = function() {\n\treturn railroad.Skip();\n}\n\nvar Nonterminal = function(text) {\n\tthis.initialiseLeaf(\"Nonterminal\",text);\n};\n\nNonterminal.prototype = new Component();\n\nNonterminal.prototype.toSvg = function() {\n\treturn railroad.NonTerminal(this.text);\n}\n\nvar Terminal = function(text) {\n\tthis.initialiseLeaf(\"Terminal\",text);\n};\n\nTerminal.prototype = new Component();\n\nTerminal.prototype.toSvg = function() {\n\treturn railroad.Terminal(this.text);\n}\n\n/////////////////////////// Components with one child\n\nvar Optional = function(content,normal) {\n\tthis.initialiseWithChild(\"Optional\",content);\n\tthis.normal = normal;\n};\n\nOptional.prototype = new Component();\n\nOptional.prototype.toSvg = function() {\n\t// Call Optional(component,\"skip\")\n\treturn railroad.Optional(this.child.toSvg(), this.normal ? undefined : \"skip\");\n}\n\nvar OptionalRepeated = function(content,separator,normal,wantArrow) {\n\tthis.initialiseWithChild(\"OptionalRepeated\",content);\n\tthis.separator = toSingleChild(separator);\n\tthis.normal = normal;\n\tthis.wantArrow = wantArrow;\n};\n\nOptionalRepeated.prototype = new Component();\n\nOptionalRepeated.prototype.toSvg = function() {\n\t// Call ZeroOrMore(component,separator,\"skip\")\n\tvar separatorSvg = this.separator ? this.separator.toSvg() : null;\n\tvar skip = this.normal ? undefined : \"skip\";\n\treturn railroad.ZeroOrMore(this.child.toSvg(),separatorSvg,skip,this.wantArrow);\n}\n\nvar Repeated = function(content,separator,wantArrow) {\n\tthis.initialiseWithChild(\"Repeated\",content);\n\tthis.separator = toSingleChild(separator);\n\tthis.wantArrow = wantArrow;\n};\n\nRepeated.prototype = new Component();\n\nRepeated.prototype.toSvg = function() {\n\t// Call OneOrMore(component,separator)\n\tvar separatorSvg = this.separator ? this.separator.toSvg() : null;\n\treturn railroad.OneOrMore(this.child.toSvg(),separatorSvg,this.wantArrow);\n}\n\nvar Link = function(content,options) {\n\tthis.initialiseWithChild(\"Link\",content);\n\tthis.options = options;\n};\n\nLink.prototype = new Component();\n\nLink.prototype.toSvg = function() {\n\treturn railroad.Link(this.child.toSvg(),this.options);\n}\n\nvar Transclusion = function(content) {\n\tthis.initialiseWithChild(\"Transclusion\",content);\n};\n\nTransclusion.prototype = new Component();\n\nTransclusion.prototype.toSvg = function() {\n\treturn this.child.toSvg();\n}\n\n/////////////////////////// Components with an array of children\n\nvar Root = function(content) {\n\tthis.initialiseWithChildren(\"Root\",content);\n};\n\nRoot.prototype = new Component();\n\nRoot.prototype.toSvg = function(options) {\n\tvar args = this.getSvgOfChildren();\n\targs.unshift(options);\n\t// Call Diagram(options,component1,component2,...)\n\treturn railroad.Diagram.apply(null,args);\n}\n\nvar Sequence = function(content) {\n\tthis.initialiseWithChildren(\"Sequence\",content);\n};\n\nSequence.prototype = new Component();\n\nSequence.prototype.toSvg = function() {\n\t// Call Sequence(component1,component2,...)\n\treturn railroad.Sequence.apply(null,this.getSvgOfChildren());\n}\n\nvar Choice = function(content,normal) {\n\tthis.initialiseWithChildren(\"Choice\",content.map(toSingleChild));\n\tfor(var i=0; i<this.children.length; i++) {\n\t\tthis.children[i].isChoiceBranch = true;\n\t}\n\tthis.normal = normal;\n};\n\nChoice.prototype = new Component();\n\nChoice.prototype.toSvg = function() {\n\t// Call Choice(normal,component1,component2,...)\n\tvar args = this.getSvgOfChildren();\n\targs.unshift(this.normal);\n\treturn railroad.Choice.apply(null,args);\n}\n\n/////////////////////////// Exports\n\nexports.components = {\n\tChoice: Choice,\n\tComment: Comment,\n\tDummy: Dummy,\n\tLink: Link,\n\tNonterminal: Nonterminal,\n\tOptional: Optional,\n\tOptionalRepeated: OptionalRepeated,\n\tRepeated: Repeated,\n\tRoot: Root,\n\tSequence: Sequence,\n\tTerminal: Terminal,\n\tTransclusion: Transclusion\n};\n\n})();",
"title": "$:/plugins/tiddlywiki/railroad/components.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/tiddlywiki/railroad/example-source": {
"created": "20150103184022184",
"modified": "20150119214125000",
"tags": "",
"title": "$:/plugins/tiddlywiki/railroad/example-source",
"type": "text/vnd.tiddlywiki.railroad",
"text": "[\"+\"]\n({ [[digit|GettingStarted]] } | \"#\" <'escape sequence'>)\n[{(\"@\" name-char | :\"--\" )}]\n"
},
"$:/plugins/tiddlywiki/railroad/example": {
"created": "20150102165032410",
"modified": "20150120090735000",
"tags": "",
"title": "$:/plugins/tiddlywiki/railroad/example",
"text": "Notation:\n\n<pre><code><$text text={{$:/plugins/tiddlywiki/railroad/example-source}}/></code></pre>\n\nDiagram:\n\n{{$:/plugins/tiddlywiki/railroad/example-source}}\n\nDebug mode:\n\n<$railroad debug=\"yes\" text={{$:/plugins/tiddlywiki/railroad/example-source}}/>\n"
},
"$:/plugins/tiddlywiki/railroad/readme": {
"created": "20150102163222184",
"modified": "20150119231005000",
"title": "$:/plugins/tiddlywiki/railroad/readme",
"text": "This plugin provides a `<$railroad>` widget for generating railroad diagrams as SVG images.\n\nAlternatively, the [[diagram notation|$:/plugins/tiddlywiki/railroad/syntax]] can be stored in a dedicated tiddler with its `type` field set to `text/vnd.tiddlywiki.railroad`, and that tiddler can simply be transcluded to wherever it is needed.\n\nThe plugin is based on [[a library by Tab Atkins|https://github.com/tabatkins/railroad-diagrams]], and has been extended to make it more flexible, including allowing components of a diagram to function as links or be transcluded from other tiddlers.\n"
},
"$:/plugins/tiddlywiki/railroad/syntax-string": {
"created": "20150103184022184",
"modified": "20150103184022184",
"title": "$:/plugins/tiddlywiki/railroad/syntax-string",
"text": "('\"' text '\"' | \"'\" text \"'\" | '\"\"\"' text '\"\"\"')"
},
"$:/plugins/tiddlywiki/railroad/syntax": {
"created": "20150103184022184",
"modified": "20150119220342000",
"title": "$:/plugins/tiddlywiki/railroad/syntax",
"text": "The railroad widget uses a special notation to construct the components defined below.\n\n`x` and `y` here stand for any component.\n\nNames (as opposed to quoted strings) are available when a value starts with a letter and contains only letters, digits, underscores, dots and hyphens.\n\n---\n\n; sequence\n: <$railroad text=\"\"\" [\"<-\"] {x} [\"->\"] \"\"\"/>\n* A sequence of components\n* The `<-` and `->` delimiters allow you to force a single component to be treated as a sequence. This is occasionally useful for spacing a diagram out\n\n---\n\n; optional\n: <$railroad text=\"\"\" \"[\" [\":\"] x \"]\" \"\"\"/>\n* A component that can be omitted\n* The colon makes `x` appear straight ahead\n\n---\n\n; repeated\n: <$railroad text=\"\"\" \"{\" x [:\"+\" y] \"}\" \"\"\"/>\n* A list of one or more `x`\n* The `+` suffix adds `y` as a separator between each `x` and the next\n\n---\n\n; optional repeated\n: <$railroad text=\"\"\" \"[{\" [\":\"] x [:\"+\" y] \"}]\" \"\"\"/>\n* An optional list of `x`, i.e. a list of zero or more `x`\n\n---\n\n; choice\n: <$railroad text=\"\"\" \"(\" {[:\":\"] x +\"|\"} \")\" \"\"\"/>\n* A set of alternatives\n* The colon indicates which branch appears straight ahead. By default, it's the first branch\n\n---\n\n; string / terminal\n: <$railroad text={{$:/plugins/tiddlywiki/railroad/syntax-string}}/>\n* A literal or terminal component\n* This follows the normal ~TiddlyWiki rules for quoted strings\n\n---\n\n; nonterminal\n: <$railroad text=\"\"\" (name | \"<\" string \">\") \"\"\"/>\n* A nonterminal component, i.e. the name of another diagram\n\n---\n\n; comment\n: <$railroad text=\"\"\" \"/\" string \"/\" \"\"\"/>\n* A comment\n\n---\n\n; dummy\n: <$railroad text=\"\"\" \"-\" \"\"\"/>\n* The absence of a component\n\n---\n\n; link\n: <$railroad text=\"\"\" \"[[\" x \"|\" (name|string) \"]]\" \"\"\"/>\n* A link to the tiddler title or URI given by the string or name\n\n---\n\n; transclusion\n: <$railroad text=\"\"\" \"{{\" (name|string) \"}}\" \"\"\"/>\n* Treats the content of another tiddler as diagram syntax and transcludes it into the current diagram\n\n---\n\n; arrow pragma\n: <$railroad text=\"\"\" \"\\arrow\" (\"yes\" | \"no\") \"\"\"/>\n* Controls whether repeat paths have an arrow on them\n* Can be toggled on and off in mid-diagram, if desired\n\n---\n\n; debug pragma\n: <$railroad text=\"\"\" \"\\debug\" \"\"\"/>\n* Causes the diagram to display its parse tree\n\n---\n\n; start/end pragma\n: <$railroad text=\"\"\" (\"\\start\" |: \"\\end\") (\"none\" |: \"single\" | \"double\") \"\"\"/>\n* Controls the style of the diagram's startpoint or endpoint\n"
},
"$:/plugins/tiddlywiki/railroad/usage": {
"created": "20150102163222184",
"modified": "20150119231005000",
"title": "$:/plugins/tiddlywiki/railroad/usage",
"text": "The content of the `<$railroad>` widget is ignored.\n\n|!Attribute |!Description |!Default |\n|text |Text in a special notation that defines the diagram's layout |-- |\n|arrow |If set to `no`, repeat paths do not have an arrow on them |`yes` |\n|start |Style of the startpoint: `single`, `double`, `none` |`single` |\n|end |Style of the endpoint: `single`, `double`, `none` |`single` |\n|debug |If set to `yes`, the diagram displays its parse tree |`no` |\n\nThese options can also be specified via pragmas in the diagram notation, or globally via a dictionary tiddler called `$:/config/railroad`:\n\n```\narrow: yes\nstart: single\nend: single\ndebug: no\n```\n"
},
"$:/plugins/tiddlywiki/railroad/railroad-diagrams.css": {
"type": "text/css",
"title": "$:/plugins/tiddlywiki/railroad/railroad-diagrams.css",
"tags": "$:/tags/Stylesheet",
"text": "/* CSS modified for TiddlyWiki */\nsvg.railroad-diagram {\n\tbackground-color: hsl(30,20%,98%);\n\tborder-radius: 5px;\n}\nsvg.railroad-diagram:hover {\n\tbackground-color: hsl(30,20%,96%);\n}\nsvg.railroad-diagram path,\nsvg.railroad-diagram rect {\n\tstroke-width: 2;\n\tstroke: #333;\n}\nsvg.railroad-diagram path {\n\tfill: rgba(0,0,0,0);\n}\nsvg.railroad-diagram rect {\n\tfill: hsl(120,100%,90%);\n}\nsvg.railroad-diagram text {\n\tfont: 14px monospace;\n\ttext-anchor: middle;\n}\nsvg.railroad-diagram text.label {\n\ttext-anchor: start;\n}\nsvg.railroad-diagram text.comment {\n\tfont: italic 12px monospace;\n}\nsvg.railroad-diagram path.arrow {\n stroke-width: 2;\n}"
},
"$:/plugins/tiddlywiki/railroad/railroad-diagrams.js": {
"type": "application/javascript",
"title": "$:/plugins/tiddlywiki/railroad/railroad-diagrams.js",
"module-type": "library",
"text": "(function(document) {\n/* TiddlyWiki: modifications to the original library are commented like this */\n\n/*\nRailroad Diagrams\nby Tab Atkins Jr. (and others)\nhttp://xanthir.com\nhttp://twitter.com/tabatkins\nhttp://github.com/tabatkins/railroad-diagrams\n\nThis document and all associated files in the github project are licensed under CC0: http://creativecommons.org/publicdomain/zero/1.0/\nThis means you can reuse, remix, or otherwise appropriate this project for your own use WITHOUT RESTRICTION.\n(The actual legal meaning can be found at the above link.)\nDon't ask me for permission to use any part of this project, JUST USE IT.\nI would appreciate attribution, but that is not required by the license.\n*/\n\n/*\nThis file uses a module pattern to avoid leaking names into the global scope.\nThe only accidental leakage is the name \"temp\".\nThe exported names can be found at the bottom of this file;\nsimply change the names in the array of strings to change what they are called in your application.\n\nAs well, several configuration constants are passed into the module function at the bottom of this file.\nAt runtime, these constants can be found on the Diagram class.\n*/\n\nvar temp = (function(options) {\n\tfunction subclassOf(baseClass, superClass) {\n\t\tbaseClass.prototype = Object.create(superClass.prototype);\n\t\tbaseClass.prototype.$super = superClass.prototype;\n\t}\n\n\tfunction unnull(/* children */) {\n\t\treturn [].slice.call(arguments).reduce(function(sofar, x) { return sofar !== undefined ? sofar : x; });\n\t}\n\n\tfunction determineGaps(outer, inner) {\n\t\tvar diff = outer - inner;\n\t\tswitch(Diagram.INTERNAL_ALIGNMENT) {\n\t\t\tcase 'left': return [0, diff]; break;\n\t\t\tcase 'right': return [diff, 0]; break;\n\t\t\tcase 'center':\n\t\t\tdefault: return [diff/2, diff/2]; break;\n\t\t}\n\t}\n\n\tfunction wrapString(value) {\n\t\treturn ((typeof value) == 'string') ? new Terminal(value) : value;\n\t}\n\n\n\tfunction SVG(name, attrs, text) {\n\t\tattrs = attrs || {};\n\t\ttext = text || '';\n\t\tvar el = document.createElementNS(\"http://www.w3.org/2000/svg\",name);\n\t\tfor(var attr in attrs) {\n\t\t\tel.setAttribute(attr, attrs[attr]);\n\t\t}\n\t\tel.textContent = text;\n\t\treturn el;\n\t}\n\n\tfunction FakeSVG(tagName, attrs, text){\n\t\tif(!(this instanceof FakeSVG)) return new FakeSVG(tagName, attrs, text);\n\t\tif(text) this.children = text;\n\t\telse this.children = [];\n\t\tthis.tagName = tagName;\n\t\tthis.attrs = unnull(attrs, {});\n\t\treturn this;\n\t};\n\tFakeSVG.prototype.format = function(x, y, width) {\n\t\t// Virtual\n\t};\n\tFakeSVG.prototype.addTo = function(parent) {\n\t\tif(parent instanceof FakeSVG) {\n\t\t\tparent.children.push(this);\n\t\t\treturn this;\n\t\t} else {\n\t\t\tvar svg = this.toSVG();\n\t\t\tparent.appendChild(svg);\n\t\t\treturn svg;\n\t\t}\n\t};\n\tFakeSVG.prototype.toSVG = function() {\n\t\tvar el = SVG(this.tagName, this.attrs);\n\t\tif(typeof this.children == 'string') {\n\t\t\tel.textContent = this.children;\n\t\t} else {\n\t\t\tthis.children.forEach(function(e) {\n\t\t\t\tel.appendChild(e.toSVG());\n\t\t\t});\n\t\t}\n\t\treturn el;\n\t};\n\tFakeSVG.prototype.toString = function() {\n\t\tvar str = '<' + this.tagName;\n\t\tvar group = this.tagName == \"g\" || this.tagName == \"svg\";\n\t\tfor(var attr in this.attrs) {\n\t\t\tstr += ' ' + attr + '=\"' + (this.attrs[attr]+'').replace(/&/g, '&').replace(/\"/g, '"') + '\"';\n\t\t}\n\t\tstr += '>';\n\t\tif(group) str += \"\\n\";\n\t\tif(typeof this.children == 'string') {\n\t\t\tstr += this.children.replace(/&/g, '&').replace(/</g, '<');\n\t\t} else {\n\t\t\tthis.children.forEach(function(e) {\n\t\t\t\tstr += e;\n\t\t\t});\n\t\t}\n\t\tstr += '</' + this.tagName + '>\\n';\n\t\treturn str;\n\t}\n\n\tfunction Path(x,y,attrs) {\n\t\tif(!(this instanceof Path)) return new Path(x,y,attrs);\n\t\tFakeSVG.call(this, 'path', attrs);\n\t\tthis.attrs.d = \"M\"+x+' '+y;\n\t}\n\tsubclassOf(Path, FakeSVG);\n\tPath.prototype.m = function(x,y) {\n\t\tthis.attrs.d += 'm'+x+' '+y;\n\t\treturn this;\n\t}\n\tPath.prototype.h = function(val) {\n\t\tthis.attrs.d += 'h'+val;\n\t\treturn this;\n\t}\n\tPath.prototype.right = Path.prototype.h;\n\tPath.prototype.left = function(val) { return this.h(-val); }\n\tPath.prototype.v = function(val) {\n\t\tthis.attrs.d += 'v'+val;\n\t\treturn this;\n\t}\n\tPath.prototype.down = Path.prototype.v;\n\tPath.prototype.up = function(val) { return this.v(-val); }\n\tPath.prototype.arc = function(sweep){\n\t\tvar x = Diagram.ARC_RADIUS;\n\t\tvar y = Diagram.ARC_RADIUS;\n\t\tif(sweep[0] == 'e' || sweep[1] == 'w') {\n\t\t\tx *= -1;\n\t\t}\n\t\tif(sweep[0] == 's' || sweep[1] == 'n') {\n\t\t\ty *= -1;\n\t\t}\n\t\tif(sweep == 'ne' || sweep == 'es' || sweep == 'sw' || sweep == 'wn') {\n\t\t\tvar cw = 1;\n\t\t} else {\n\t\t\tvar cw = 0;\n\t\t}\n\t\tthis.attrs.d += \"a\"+Diagram.ARC_RADIUS+\" \"+Diagram.ARC_RADIUS+\" 0 0 \"+cw+' '+x+' '+y;\n\t\treturn this;\n\t}\n\tPath.prototype.format = function() {\n\t\t// All paths in this library start/end horizontally.\n\t\t// The extra .5 ensures a minor overlap, so there's no seams in bad rasterizers.\n\t\tthis.attrs.d += 'h.5';\n\t\treturn this;\n\t}\n/* TiddlyWiki: added support for arbitrary straight lines */\n\tPath.prototype.line = function(dx,dy) {\n\t\tthis.attrs.d += \"l\"+dx+\" \"+dy;\n\t\treturn this;\n\t}\n\n/* TiddlyWiki: added twOptions parameter, passing it to Start() and End() */\n\tfunction Diagram(twOptions, items) {\n\t\tif(!(this instanceof Diagram)) return new Diagram(twOptions, [].slice.call(arguments,1));\n\t\tFakeSVG.call(this, 'svg', {class: Diagram.DIAGRAM_CLASS});\n\t\tthis.items = items.map(wrapString);\n\t\tthis.items.unshift(new Start(twOptions.start));\n\t\tthis.items.push(new End(twOptions.end));\n\t\tthis.width = this.items.reduce(function(sofar, el) { return sofar + el.width + (el.needsSpace?20:0)}, 0)+1;\n\t\tthis.up = Math.max.apply(null, this.items.map(function (x) { return x.up; }));\n\t\tthis.down = Math.max.apply(null, this.items.map(function (x) { return x.down; }));\n\t\tthis.formatted = false;\t\t\n\t}\n\tsubclassOf(Diagram, FakeSVG);\n\tfor(var option in options) {\n\t\tDiagram[option] = options[option];\n\t}\n\tDiagram.prototype.format = function(paddingt, paddingr, paddingb, paddingl) {\n\t\tpaddingt = unnull(paddingt, 20);\n\t\tpaddingr = unnull(paddingr, paddingt, 20);\n\t\tpaddingb = unnull(paddingb, paddingt, 20);\n\t\tpaddingl = unnull(paddingl, paddingr, 20);\n\t\tvar x = paddingl;\n\t\tvar y = paddingt;\n\t\ty += this.up;\n\t\tvar g = FakeSVG('g', Diagram.STROKE_ODD_PIXEL_LENGTH ? {transform:'translate(.5 .5)'} : {});\n\t\tfor(var i = 0; i < this.items.length; i++) {\n\t\t\tvar item = this.items[i];\n\t\t\tif(item.needsSpace) {\n\t\t\t\tPath(x,y).h(10).addTo(g);\n\t\t\t\tx += 10;\n\t\t\t}\n\t\t\titem.format(x, y, item.width).addTo(g);\n\t\t\tx += item.width;\n\t\t\tif(item.needsSpace) {\n\t\t\t\tPath(x,y).h(10).addTo(g);\n\t\t\t\tx += 10;\n\t\t\t}\n\t\t}\n\t\tthis.attrs.width = this.width + paddingl + paddingr;\n\t\tthis.attrs.height = this.up + this.down + paddingt + paddingb;\n\t\tthis.attrs.viewBox = \"0 0 \" + this.attrs.width + \" \" + this.attrs.height;\n\t\tg.addTo(this);\n\t\tthis.formatted = true;\n\t\treturn this;\n\t}\n\tDiagram.prototype.addTo = function(parent) {\n\t\tvar scriptTag = document.getElementsByTagName('script');\n\t\tscriptTag = scriptTag[scriptTag.length - 1];\n\t\tvar parentTag = scriptTag.parentNode;\n\t\tparent = parent || parentTag;\n\t\treturn this.$super.addTo.call(this, parent);\n\t}\n\tDiagram.prototype.toSVG = function() {\n\t\tif (!this.formatted) {\n\t\t\tthis.format();\n\t\t}\n\t\treturn this.$super.toSVG.call(this);\n\t}\n\tDiagram.prototype.toString = function() {\n\t\tif (!this.formatted) {\n\t\t\tthis.format();\n\t\t}\n\t\treturn this.$super.toString.call(this);\n\t}\n\n\tfunction Sequence(items) {\n\t\tif(!(this instanceof Sequence)) return new Sequence([].slice.call(arguments));\n\t\tFakeSVG.call(this, 'g');\n\t\tthis.items = items.map(wrapString);\n\t\tthis.width = this.items.reduce(function(sofar, el) { return sofar + el.width + (el.needsSpace?20:0)}, 0);\n\t\tthis.up = this.items.reduce(function(sofar,el) { return Math.max(sofar, el.up)}, 0);\n\t\tthis.down = this.items.reduce(function(sofar,el) { return Math.max(sofar, el.down)}, 0);\n\t}\n\tsubclassOf(Sequence, FakeSVG);\n\tSequence.prototype.format = function(x,y,width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\tfor(var i = 0; i < this.items.length; i++) {\n\t\t\tvar item = this.items[i];\n\t\t\tif(item.needsSpace) {\n\t\t\t\tPath(x,y).h(10).addTo(this);\n\t\t\t\tx += 10;\n\t\t\t}\n\t\t\titem.format(x, y, item.width).addTo(this);\n\t\t\tx += item.width;\n\t\t\tif(item.needsSpace) {\n\t\t\t\tPath(x,y).h(10).addTo(this);\n\t\t\t\tx += 10;\n\t\t\t}\n\t\t}\n\t\treturn this;\n\t}\n\n\tfunction Choice(normal, items) {\n\t\tif(!(this instanceof Choice)) return new Choice(normal, [].slice.call(arguments,1));\n\t\tFakeSVG.call(this, 'g');\n\t\tif( typeof normal !== \"number\" || normal !== Math.floor(normal) ) {\n\t\t\tthrow new TypeError(\"The first argument of Choice() must be an integer.\");\n\t\t} else if(normal < 0 || normal >= items.length) {\n\t\t\tthrow new RangeError(\"The first argument of Choice() must be an index for one of the items.\");\n\t\t} else {\n\t\t\tthis.normal = normal;\n\t\t}\n\t\tthis.items = items.map(wrapString);\n\t\tthis.width = this.items.reduce(function(sofar, el){return Math.max(sofar, el.width)},0) + Diagram.ARC_RADIUS*4;\n\t\tthis.up = this.down = 0;\n\t\tfor(var i = 0; i < this.items.length; i++) {\n\t\t\tvar item = this.items[i];\n\t\t\tif(i < normal) { this.up += Math.max(Diagram.ARC_RADIUS,item.up + item.down + Diagram.VERTICAL_SEPARATION); }\n\t\t\tif(i == normal) { this.up += Math.max(Diagram.ARC_RADIUS, item.up); this.down += Math.max(Diagram.ARC_RADIUS, item.down); }\n\t\t\tif(i > normal) { this.down += Math.max(Diagram.ARC_RADIUS,Diagram.VERTICAL_SEPARATION + item.up + item.down); }\n\t\t}\n\t}\n\tsubclassOf(Choice, FakeSVG);\n\tChoice.prototype.format = function(x,y,width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\tvar last = this.items.length -1;\n\t\tvar innerWidth = this.width - Diagram.ARC_RADIUS*4;\n\n\t\t// Do the elements that curve above\n\t\tfor(var i = this.normal - 1; i >= 0; i--) {\n\t\t\tvar item = this.items[i];\n\t\t\tif( i == this.normal - 1 ) {\n\t\t\t\tvar distanceFromY = Math.max(Diagram.ARC_RADIUS*2, this.items[i+1].up + Diagram.VERTICAL_SEPARATION + item.down);\n\t\t\t}\n\t\t\tPath(x,y).arc('se').up(distanceFromY - Diagram.ARC_RADIUS*2).arc('wn').addTo(this);\n\t\t\titem.format(x+Diagram.ARC_RADIUS*2,y - distanceFromY,innerWidth).addTo(this);\n\t\t\tPath(x+Diagram.ARC_RADIUS*2+innerWidth, y-distanceFromY).arc('ne').down(distanceFromY - Diagram.ARC_RADIUS*2).arc('ws').addTo(this);\n\t\t\tdistanceFromY += Math.max(Diagram.ARC_RADIUS, item.up + Diagram.VERTICAL_SEPARATION + (i == 0 ? 0 : this.items[i-1].down));\n\t\t}\n\n\t\t// Do the straight-line path.\n\t\tPath(x,y).right(Diagram.ARC_RADIUS*2).addTo(this);\n\t\tthis.items[this.normal].format(x+Diagram.ARC_RADIUS*2, y, innerWidth).addTo(this);\n\t\tPath(x+Diagram.ARC_RADIUS*2+innerWidth, y).right(Diagram.ARC_RADIUS*2).addTo(this);\n\n\t\t// Do the elements that curve below\n\t\tfor(var i = this.normal+1; i <= last; i++) {\n\t\t\tvar item = this.items[i];\n\t\t\tif( i == this.normal + 1 ) {\n\t\t\t\tvar distanceFromY = Math.max(Diagram.ARC_RADIUS*2, this.items[i-1].down + Diagram.VERTICAL_SEPARATION + item.up);\n\t\t\t}\n\t\t\tPath(x,y).arc('ne').down(distanceFromY - Diagram.ARC_RADIUS*2).arc('ws').addTo(this);\n\t\t\titem.format(x+Diagram.ARC_RADIUS*2, y+distanceFromY, innerWidth).addTo(this);\n\t\t\tPath(x+Diagram.ARC_RADIUS*2+innerWidth, y+distanceFromY).arc('se').up(distanceFromY - Diagram.ARC_RADIUS*2).arc('wn').addTo(this);\n\t\t\tdistanceFromY += Math.max(Diagram.ARC_RADIUS, item.down + Diagram.VERTICAL_SEPARATION + (i == last ? 0 : this.items[i+1].up));\n\t\t}\n\n\t\treturn this;\n\t}\n\n\tfunction Optional(item, skip) {\n\t\tif( skip === undefined )\n\t\t\treturn Choice(1, Skip(), item);\n\t\telse if ( skip === \"skip\" )\n\t\t\treturn Choice(0, Skip(), item);\n\t\telse\n\t\t\tthrow \"Unknown value for Optional()'s 'skip' argument.\";\n\t}\n\n/* TiddlyWiki: added wantArrow */\n\tfunction OneOrMore(item, rep, wantArrow) {\n\t\tif(!(this instanceof OneOrMore)) return new OneOrMore(item, rep, wantArrow);\n\t\tFakeSVG.call(this, 'g');\n\n/* TiddlyWiki: code added */\n\t\tthis.wantArrow = wantArrow;\n\n\t\trep = rep || (new Skip);\n\t\tthis.item = wrapString(item);\n\t\tthis.rep = wrapString(rep);\n\t\tthis.width = Math.max(this.item.width, this.rep.width) + Diagram.ARC_RADIUS*2;\n\t\tthis.up = this.item.up;\n\t\tthis.down = Math.max(Diagram.ARC_RADIUS*2, this.item.down + Diagram.VERTICAL_SEPARATION + this.rep.up + this.rep.down);\n\n/* TiddlyWiki: moved calculation of distanceFromY (of the repeat arc) to here */\n\t\tthis.distanceFromY = Math.max(Diagram.ARC_RADIUS*2, this.item.down+Diagram.VERTICAL_SEPARATION+this.rep.up);\n\t}\n\tsubclassOf(OneOrMore, FakeSVG);\n\tOneOrMore.prototype.needsSpace = true;\n\tOneOrMore.prototype.format = function(x,y,width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\t// Draw item\n\t\tPath(x,y).right(Diagram.ARC_RADIUS).addTo(this);\n\t\tthis.item.format(x+Diagram.ARC_RADIUS,y,this.width-Diagram.ARC_RADIUS*2).addTo(this);\n\t\tPath(x+this.width-Diagram.ARC_RADIUS,y).right(Diagram.ARC_RADIUS).addTo(this);\n\n\t\t// Draw repeat arc\n/* TiddlyWiki: moved calculation of distanceFromY from here to constructor */\n\t\tvar distanceFromY = this.distanceFromY;\n\t\t\n\t\tPath(x+Diagram.ARC_RADIUS,y).arc('nw').down(distanceFromY-Diagram.ARC_RADIUS*2).arc('ws').addTo(this);\n\t\tthis.rep.format(x+Diagram.ARC_RADIUS, y+distanceFromY, this.width - Diagram.ARC_RADIUS*2).addTo(this);\n\t\tPath(x+this.width-Diagram.ARC_RADIUS, y+distanceFromY).arc('se').up(distanceFromY-Diagram.ARC_RADIUS*2).arc('en').addTo(this);\n\t\t\n/* TiddlyWiki: code added */\n\t\tif(this.wantArrow) {\n\t\t\tvar arrowSize = Diagram.ARC_RADIUS/2;\n\t\t\t// Compensate for the illusion that makes the arrow look unbalanced if it's too close to the curve below it\n\t\t\tvar multiplier = (distanceFromY < arrowSize*5) ? 1.2 : 1;\n\t\t\tPath(x-arrowSize, y+distanceFromY/2 + arrowSize/2, {class:\"arrow\"}).\n\t\t\t\tline(arrowSize, -arrowSize).line(arrowSize*multiplier, arrowSize).addTo(this);\n\t\t}\n\n\t\treturn this;\n\t}\n\n\tfunction ZeroOrMore(item, rep, skip, wantArrow) {\n\t\treturn Optional(OneOrMore(item, rep, wantArrow), skip);\n\t}\n\n/* TiddlyWiki: added type parameter */\n\tfunction Start(type) {\n\t\tif(!(this instanceof Start)) return new Start(type);\n\t\tFakeSVG.call(this, 'path');\n\t\tthis.type = type || 'single'\n\t\tthis.width = (this.type === 'double') ? 20 : 10;\n\t\tthis.up = 10;\n\t\tthis.down = 10;\n\t}\n\tsubclassOf(Start, FakeSVG);\n\tStart.prototype.format = function(x,y) {\n/* TiddlyWiki: added types */\n\t\tif(this.type === 'single') {\n\t\t\tthis.attrs.d = 'M '+x+' '+(y-10)+' v 20 m 0 -10 h 10.5';\n\t\t} else if(this.type === 'double') {\n\t\t\tthis.attrs.d = 'M '+x+' '+(y-10)+' v 20 m 10 -20 v 20 m -10 -10 h 20.5';\n\t\t} else { // 'none'\n\t\t\tthis.attrs.d = 'M '+x+' '+y+' h 10.5';\n\t\t}\n\t\treturn this;\n\t}\n\n/* TiddlyWiki: added type parameter */\n\tfunction End(type) {\n\t\tif(!(this instanceof End)) return new End(type);\n\t\tFakeSVG.call(this, 'path');\n\t\tthis.type = type || 'double';\n\t\tthis.width = (this.type === 'double') ? 20 : 10;\n\t\tthis.up = 10;\n\t\tthis.down = 10;\n\t}\n\tsubclassOf(End, FakeSVG);\n\tEnd.prototype.format = function(x,y) {\n/* TiddlyWiki: added types */\n\t\tif(this.type === 'single') {\n\t\t\tthis.attrs.d = 'M '+x+' '+y+' h 10 m 0 -10 v 20';\n\t\t} else if(this.type === 'double') {\n\t\t\tthis.attrs.d = 'M '+x+' '+y+' h 20 m -10 -10 v 20 m 10 -20 v 20';\n\t\t} else { // 'none'\n\t\t\tthis.attrs.d = 'M '+x+' '+y+' h 10';\n\t\t}\n\t\treturn this;\n\t}\n\n\tfunction Terminal(text) {\n\t\tif(!(this instanceof Terminal)) return new Terminal(text);\n\t\tFakeSVG.call(this, 'g');\n\t\tthis.text = text;\n\t\tthis.width = text.length * 8 + 20; /* Assume that each char is .5em, and that the em is 16px */\n\t\tthis.up = 11;\n\t\tthis.down = 11;\n\t}\n\tsubclassOf(Terminal, FakeSVG);\n\tTerminal.prototype.needsSpace = true;\n\tTerminal.prototype.format = function(x, y, width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\tFakeSVG('rect', {x:x, y:y-11, width:this.width, height:this.up+this.down, rx:10, ry:10}).addTo(this);\n\t\tFakeSVG('text', {x:x+this.width/2, y:y+4}, this.text).addTo(this);\n\t\treturn this;\n\t}\n\n\tfunction NonTerminal(text) {\n\t\tif(!(this instanceof NonTerminal)) return new NonTerminal(text);\n\t\tFakeSVG.call(this, 'g');\n\t\tthis.text = text;\n\t\tthis.width = text.length * 8 + 20;\n\t\tthis.up = 11;\n\t\tthis.down = 11;\n\t}\n\tsubclassOf(NonTerminal, FakeSVG);\n\tNonTerminal.prototype.needsSpace = true;\n\tNonTerminal.prototype.format = function(x, y, width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\tFakeSVG('rect', {x:x, y:y-11, width:this.width, height:this.up+this.down}).addTo(this);\n\t\tFakeSVG('text', {x:x+this.width/2, y:y+4}, this.text).addTo(this);\n\t\treturn this;\n\t}\n\n\tfunction Comment(text) {\n\t\tif(!(this instanceof Comment)) return new Comment(text);\n\t\tFakeSVG.call(this, 'g');\n\t\tthis.text = text;\n\t\tthis.width = text.length * 7 + 10;\n\t\tthis.up = 11;\n\t\tthis.down = 11;\n\t}\n\tsubclassOf(Comment, FakeSVG);\n\tComment.prototype.needsSpace = true;\n\tComment.prototype.format = function(x, y, width) {\n\t\t// Hook up the two sides if this is narrower than its stated width.\n\t\tvar gaps = determineGaps(width, this.width);\n\t\tPath(x,y).h(gaps[0]).addTo(this);\n\t\tPath(x+gaps[0]+this.width,y).h(gaps[1]).addTo(this);\n\t\tx += gaps[0];\n\n\t\tFakeSVG('text', {x:x+this.width/2, y:y+5, class:'comment'}, this.text).addTo(this);\n\t\treturn this;\n\t}\n\n\tfunction Skip() {\n\t\tif(!(this instanceof Skip)) return new Skip();\n\t\tFakeSVG.call(this, 'g');\n\t\tthis.width = 0;\n\t\tthis.up = 0;\n\t\tthis.down = 0;\n\t}\n\tsubclassOf(Skip, FakeSVG);\n\tSkip.prototype.format = function(x, y, width) {\n\t\tPath(x,y).right(width).addTo(this);\n\t\treturn this;\n\t}\n\t\n/* TiddlyWiki: added linking ability */\n\tfunction Link(item,options) {\n\t\tif(!(this instanceof Link)) return new Link(item,options);\n\t\tFakeSVG.call(this,'a',options);\n\t\tthis.item = item;\n\t\tthis.width = item.width;\n\t\tthis.up = item.up;\n\t\tthis.down = item.down;\n\t}\n\tsubclassOf(Link, FakeSVG);\n\tLink.prototype.needsSpace = true;\n\tLink.prototype.format = function(x, y, width) {\n\t\tthis.item.format(x,y,width).addTo(this);\n\t\treturn this;\n\t}\n\n/* TiddlyWiki: this block replaces the export mechanism in the original library */\n\tif (exports) {\n\t\texports.Diagram = Diagram;\n\t\texports.Sequence = Sequence;\n\t\texports.Choice = Choice;\n\t\texports.Optional = Optional;\n\t\texports.OneOrMore = OneOrMore;\n\t\texports.ZeroOrMore = ZeroOrMore;\n\t\texports.Terminal = Terminal;\n\t\texports.NonTerminal = NonTerminal;\n\t\texports.Comment = Comment;\n\t\texports.Skip = Skip;\n\t\texports.Link = Link;\n\t};\n})(\n\t{\n\tVERTICAL_SEPARATION: 8,\n\tARC_RADIUS: 10,\n\tDIAGRAM_CLASS: 'railroad-diagram',\n\tSTROKE_ODD_PIXEL_LENGTH: true,\n\tINTERNAL_ALIGNMENT: 'center',\n\t}\n);\n\n/* TiddlyWiki: removed assignments to properties of the window object */\n\n})($tw.node ? $tw.fakeDocument : window.document)\n"
},
"$:/plugins/tiddlywiki/railroad/parser.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/railroad/parser.js\ntype: application/javascript\nmodule-type: library\n\nParser for the source of a railroad diagram.\n\n[:x]\t\t\toptional, normally included\n[x]\t\t\t\toptional, normally omitted\n{x}\t\t\t\tone or more\n{x +\",\"}\t\tone or more, comma-separated\n[{:x}]\t\t\tzero or more, normally included\n[{:x +\",\"}]\t\tzero or more, comma-separated, normally included\n[{x}]\t\t\tzero or more, normally omitted\n[{x +\",\"}]\t\tzero or more, comma-separated, normally omitted\nx y z\t\t\tsequence\n<-x y z->\t\texplicit sequence\n(x|y|z)\t\t\talternatives\n(x|:y|z)\t\talternatives, normally y\n\"x\"\t\t\t\tterminal\n<\"x\">\t\t\tnonterminal\n/\"blah\"/\t\tcomment\n-\t\t\t\tdummy\n[[x|\"tiddler\"]]\tlink\n{{\"tiddler\"}}\ttransclusion\n\n\"x\" can also be written 'x' or \"\"\"x\"\"\"\n\npragmas:\n\t\\arrow yes|no\n\t\\debug yes|no\n\t\\start single|double|none\n\t\\end single|double|none\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar components = require(\"$:/plugins/tiddlywiki/railroad/components.js\").components;\n\nvar Parser = function(widget,source,options) {\n\tthis.widget = widget;\n\tthis.source = source;\n\tthis.options = options;\n\tthis.tokens = this.tokenise(source);\n\tthis.tokenPos = 0;\n\tthis.advance();\n\tthis.content = this.parseContent();\n\tthis.root = new components.Root(this.content);\n\tthis.checkFinished();\n};\n\n/////////////////////////// Parser dispatch\n\nParser.prototype.parseContent = function() {\n\tvar content = [];\n\t// Parse zero or more components\n\twhile(true) {\n\t\tvar component = this.parseComponent();\n\t\tif(!component) {\n\t\t\tbreak;\n\t\t}\n\t\tif(!component.isPragma) {\n\t\t\tcontent.push(component);\n\t\t}\n\t}\n\treturn content;\n};\n\nParser.prototype.parseComponent = function() {\n\tvar component = null;\n\tif(this.token) {\n\t\tif(this.at(\"string\")) {\n\t\t\tcomponent = this.parseTerminal();\n\t\t} else if(this.at(\"name\")) {\n\t\t\tcomponent = this.parseName();\n\t\t} else if(this.at(\"pragma\")) {\n\t\t\tcomponent = this.parsePragma();\n\t\t} else {\n\t\t\tswitch(this.token.value) {\n\t\t\t\tcase \"[\":\n\t\t\t\t\tcomponent = this.parseOptional();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"{\":\n\t\t\t\t\tcomponent = this.parseRepeated();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"<\":\n\t\t\t\t\tcomponent = this.parseNonterminal();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"(\":\n\t\t\t\t\tcomponent = this.parseChoice();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"/\":\n\t\t\t\t\tcomponent = this.parseComment();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"[[\":\n\t\t\t\t\tcomponent = this.parseLink();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"{{\":\n\t\t\t\t\tcomponent = this.parseTransclusion();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"<-\":\n\t\t\t\t\tcomponent = this.parseSequence();\n\t\t\t\t\tbreak;\n\t\t\t\tcase \"-\":\n\t\t\t\t\tcomponent = this.parseDummy();\n\t\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t}\n\treturn component;\n};\n\n/////////////////////////// Specific components\n\nParser.prototype.parseChoice = function() {\n\t// Consume the (\n\tthis.advance();\n\tvar content = [],\n\t\tcolon = -1;\n\tdo {\n\t\t// Allow at most one branch to be prefixed with a colon\n\t\tif(colon === -1 && this.eat(\":\")) {\n\t\t\tcolon = content.length;\n\t\t}\n\t\t// Parse the next branch\n\t\tcontent.push(this.parseContent());\n\t} while(this.eat(\"|\"));\n\t// Consume the closing bracket\n\tthis.close(\")\");\n\t// Create a component\n\treturn new components.Choice(content,colon === -1 ? 0 : colon);\n};\n\nParser.prototype.parseComment = function() {\n\t// Consume the /\n\tthis.advance();\n\t// The comment's content should be in a string literal\n\tvar content = this.expectString(\"after /\");\n\t// Consume the closing /\n\tthis.close(\"/\");\n\t// Create a component\n\treturn new components.Comment(content);\n};\n\nParser.prototype.parseDummy = function() {\n\t// Consume the -\n\tthis.advance();\n\t// Create a component\n\treturn new components.Dummy();\n};\n\nParser.prototype.parseLink = function() {\n\t// Consume the [[\n\tthis.advance();\n\t// Parse the content\n\tvar content = this.parseContent();\n\t// Consume the |\n\tthis.expect(\"|\");\n\t// Consume the target\n\tvar target = this.expectNameOrString(\"as link target\");\n\t// Prepare some attributes for the SVG \"a\" element to carry\n\tvar options = {\"data-tw-target\": target};\n\tif($tw.utils.isLinkExternal(target)) {\n\t\toptions[\"data-tw-external\"] = true;\n\t}\n\t// Consume the closing ]]\n\tthis.close(\"]]\");\n\t// Create a component\n\treturn new components.Link(content,options);\n};\n\nParser.prototype.parseName = function() {\n\t// Create a component\n\tvar component = new components.Nonterminal(this.token.value);\n\t// Consume the name\n\tthis.advance();\n\treturn component;\n};\n\nParser.prototype.parseNonterminal = function() {\n\t// Consume the <\n\tthis.advance();\n\t// The nonterminal's name should be in a string literal\n\tvar content = this.expectString(\"after <\");\n\t// Consume the closing bracket\n\tthis.close(\">\");\n\t// Create a component\n\treturn new components.Nonterminal(content);\n};\n\nParser.prototype.parseOptional = function() {\n\tvar wantArrow = this.options.arrow;\n\t// Consume the [\n\tthis.advance();\n\t// Consume the { if there is one\n\tvar repeated = this.eat(\"{\");\n\t// Note whether omission is the normal route\n\tvar normal = this.eat(\":\");\n\t// Parse the content\n\tvar content = this.parseContent(),\n\t\tseparator = null;\n\t// Parse the separator if there is one\n\tif(repeated && this.eat(\"+\")) {\n\t\tseparator = this.parseContent();\n\t}\n\t// Consume the closing brackets\n\tif(repeated) {\n\t\tthis.close(\"}\");\n\t}\n\tthis.close(\"]\");\n\t// Create a component\n\treturn repeated ? new components.OptionalRepeated(content,separator,normal,wantArrow)\n\t\t: new components.Optional(content,normal);\n};\n\nParser.prototype.parseRepeated = function() {\n\tvar wantArrow = this.options.arrow;\n\t// Consume the {\n\tthis.advance();\n\t// Parse the content\n\tvar content = this.parseContent(),\n\t\tseparator = null;\n\t// Parse the separator if there is one\n\tif(this.eat(\"+\")) {\n\t\tseparator = this.parseContent();\n\t}\n\t// Consume the closing bracket\n\tthis.close(\"}\");\n\t// Create a component\n\treturn new components.Repeated(content,separator,wantArrow);\n};\n\nParser.prototype.parseSequence = function() {\n\t// Consume the <-\n\tthis.advance();\n\t// Parse the content\n\tvar content = this.parseContent();\n\t// Consume the closing ->\n\tthis.close(\"->\");\n\t// Create a component\n\treturn new components.Sequence(content);\n};\n\nParser.prototype.parseTerminal = function() {\n\tvar component = new components.Terminal(this.token.value);\n\t// Consume the string literal\n\tthis.advance();\n return component;\n};\n\nParser.prototype.parseTransclusion = function() {\n\t// Consume the {{\n\tthis.advance();\n\t// Consume the text reference\n\tvar textRef = this.expectNameOrString(\"as transclusion source\");\n\t// Consume the closing }}\n\tthis.close(\"}}\");\n\t// Retrieve the content of the text reference\n\tvar source = this.widget.wiki.getTextReference(textRef,\"\",this.widget.getVariable(\"currentTiddler\"));\n\t// Parse the content\n\tvar content = new Parser(this.widget,source).content;\n\t// Create a component\n\treturn new components.Transclusion(content);\n};\n\n/////////////////////////// Pragmas\n\nParser.prototype.parsePragma = function() {\n\t// Create a dummy component\n\tvar component = { isPragma: true };\n\t// Consume the pragma\n\tvar pragma = this.token.value;\n\tthis.advance();\n\t// Apply the setting\n\tif(pragma === \"arrow\") {\n\t\tthis.options.arrow = this.parseYesNo(pragma);\t\t\n\t} else if(pragma === \"debug\") {\n\t\tthis.options.debug = true;\n\t} else if(pragma === \"start\") {\n\t\tthis.options.start = this.parseTerminusStyle(pragma);\t\t\n\t} else if(pragma === \"end\") {\n\t\tthis.options.end = this.parseTerminusStyle(pragma);\t\t\n\t} else {\n\t\tthrow \"Invalid pragma\";\n\t}\n\treturn component;\n};\n\nParser.prototype.parseYesNo = function(pragma) {\n\treturn this.parseSetting([\"yes\",\"no\"],pragma) === \"yes\";\n}\n\nParser.prototype.parseTerminusStyle = function(pragma) {\n\treturn this.parseSetting([\"single\",\"double\",\"none\"],pragma);\n}\n\nParser.prototype.parseSetting = function(options,pragma) {\n\tif(this.at(\"name\") && options.indexOf(this.token.value) !== -1) {\n\t\treturn this.tokenValueEaten();\t\t\n\t}\n\tthrow options.join(\" or \") + \" expected after \\\\\" + pragma;\n}\n\n/////////////////////////// Token manipulation\n\nParser.prototype.advance = function() {\n\tif(this.tokenPos >= this.tokens.length) {\n\t\tthis.token = null;\n\t}\n\tthis.token = this.tokens[this.tokenPos++];\n};\n\nParser.prototype.at = function(token) {\n\treturn this.token && (this.token.type === token || this.token.type === \"token\" && this.token.value === token);\n};\n\nParser.prototype.eat = function(token) {\n\tvar at = this.at(token);\n\tif(at) {\n\t\tthis.advance();\n\t}\n\treturn at;\n};\n\nParser.prototype.tokenValueEaten = function() {\n\tvar output = this.token.value;\n\tthis.advance();\n\treturn output;\n};\n\nParser.prototype.close = function(token) {\n\tif(!this.eat(token)) {\n\t\tthrow \"Closing \" + token + \" expected\";\n\t}\n};\n\nParser.prototype.checkFinished = function() {\n\tif(this.token) {\n\t\tthrow \"Syntax error at \" + this.token.value;\n\t}\n};\n\nParser.prototype.expect = function(token) {\n\tif(!this.eat(token)) {\n\t\tthrow token + \" expected\";\n\t}\n};\n\nParser.prototype.expectString = function(context,token) {\n\tif(!this.at(\"string\")) {\n\t\ttoken = token || \"String\";\n\t\tthrow token + \" expected \" + context;\n\t}\n\treturn this.tokenValueEaten();\n};\n\nParser.prototype.expectNameOrString = function(context) {\n\tif(this.at(\"name\")) {\n\t\treturn this.tokenValueEaten();\n\t}\n\treturn this.expectString(context,\"Name or string\");\n};\n\n/////////////////////////// Tokenisation\n\nParser.prototype.tokenise = function(source) {\n\tvar tokens = [],\n\t\tpos = 0,\n\t\tc, s, token;\n\twhile(pos < source.length) {\n\t\t// Initialise this iteration\n\t\ts = token = null;\n\t\t// Skip whitespace\n\t\tpos = $tw.utils.skipWhiteSpace(source,pos);\n\t\t// Avoid falling off the end of the string\n\t\tif (pos >= source.length) {\n\t\t\tbreak;\n\t\t}\n\t\t// Examine the next character\n\t\tc = source.charAt(pos);\n\t\tif(\"\\\"'\".indexOf(c) !== -1) {\n\t\t\t// String literal\n\t\t\ttoken = $tw.utils.parseStringLiteral(source,pos);\n\t\t\tif(!token) {\n\t\t\t\tthrow \"Unterminated string literal\";\n\t\t\t}\n\t\t} else if(\"[]{}\".indexOf(c) !== -1) {\n\t\t\t// Single or double character\n\t\t\ts = source.charAt(pos+1) === c ? c + c : c;\n\t\t} else if(c === \"<\") {\n\t\t\t// < or <-\n\t\t\ts = source.charAt(pos+1) === \"-\" ? \"<-\" : \"<\";\n\t\t} else if(c === \"-\") {\n\t\t\t// - or ->\n\t\t\ts = source.charAt(pos+1) === \">\" ? \"->\" : \"-\";\n\t\t} else if(\"()>+/:|\".indexOf(c) !== -1) {\n\t\t\t// Single character\n\t\t\ts = c;\n\t\t} else if(c.match(/[a-zA-Z]/)) {\n\t\t\t// Name\n\t\t\ttoken = this.readName(source,pos);\n\t\t} else if(c.match(/\\\\/)) {\n\t\t\t// Pragma\n\t\t\ttoken = this.readPragma(source,pos);\n\t\t} else {\n\t\t\tthrow \"Syntax error at \" + c;\n\t\t}\n\t\t// Add our findings to the return array\n\t\tif(token) {\n\t\t\ttokens.push(token);\n\t\t} else {\n\t\t\ttoken = $tw.utils.parseTokenString(source,pos,s);\n\t\t\ttokens.push(token);\n\t\t}\n\t\t// Prepare for the next character\n\t\tpos = token.end;\n\t}\n\treturn tokens;\n};\n\nParser.prototype.readName = function(source,pos) {\n\tvar re = /([a-zA-Z0-9_.-]+)/g;\n\tre.lastIndex = pos;\n\tvar match = re.exec(source);\n\tif(match && match.index === pos) {\n\t\treturn {type: \"name\", value: match[1], start: pos, end: pos+match[1].length};\n\t} else {\n\t\tthrow \"Invalid name\";\n\t}\n};\n\nParser.prototype.readPragma = function(source,pos) {\n\tvar re = /([a-z]+)/g;\n\tpos++;\n\tre.lastIndex = pos;\n\tvar match = re.exec(source);\n\tif(match && match.index === pos) {\n\t\treturn {type: \"pragma\", value: match[1], start: pos, end: pos+match[1].length};\n\t} else {\n\t\tthrow \"Invalid pragma\";\n\t}\n};\n\n/////////////////////////// Exports\n\nexports.parser = Parser;\n\n})();",
"title": "$:/plugins/tiddlywiki/railroad/parser.js",
"type": "application/javascript",
"module-type": "library"
},
"$:/plugins/tiddlywiki/railroad/typed-parser.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/railroad/typed-parser.js\ntype: application/javascript\nmodule-type: parser\n\nThis parser wraps unadorned railroad syntax into a railroad widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar RailroadParser = function(type,text,options) {\n\tvar element = {\n\t\t\ttype: \"railroad\",\n\t\t\ttag: \"$railroad\",\n\t\t\ttext: text\n\t\t};\n\tthis.tree = [element];\nconsole.log(text);\n};\n\nexports[\"text/vnd.tiddlywiki.railroad\"] = RailroadParser;\n\n})();\n\n",
"title": "$:/plugins/tiddlywiki/railroad/typed-parser.js",
"type": "application/javascript",
"module-type": "parser"
},
"$:/plugins/tiddlywiki/railroad/wrapper.js": {
"text": "/*\\\ntitle: $:/plugins/tiddlywiki/railroad/wrapper.js\ntype: application/javascript\nmodule-type: widget\n\nWrapper for `railroad-diagrams.js` that provides a `<$railroad>` widget.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Parser = require(\"$:/plugins/tiddlywiki/railroad/parser.js\").parser,\n\tWidget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar RailroadWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\nvar RAILROAD_OPTIONS = \"$:/config/railroad\";\n\n/*\nInherit from the base widget class\n*/\nRailroadWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nRailroadWidget.prototype.render = function(parent,nextSibling) {\n\t// Housekeeping\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\t// Get the source text\n\tvar source = this.getAttribute(\"text\",this.parseTreeNode.text || \"\");\n\t// Create a div to contain the SVG or error message\n\tvar div = this.document.createElement(\"div\");\n\ttry {\n\t\t// Initialise options from the config tiddler or widget attributes\n\t\tvar config = $tw.wiki.getTiddlerData(RAILROAD_OPTIONS,{});\n\t\tvar options = {\n\t\t\tarrow: this.getAttribute(\"arrow\", config.arrow || \"yes\") === \"yes\",\n\t\t\tdebug: this.getAttribute(\"debug\", config.debug || \"no\") === \"yes\",\n\t\t\tstart: this.getAttribute(\"start\", config.start || \"single\"),\n\t\t\tend: this.getAttribute(\"end\", config.end || \"single\")\n\t\t};\n\t\t// Parse the source\n\t\tvar parser = new Parser(this,source,options);\n\t\t// Generate content into the div\n\t\tif(parser.options.debug) {\n\t\t\tthis.renderDebug(parser,div);\n\t\t} else {\n\t\t\tthis.renderSvg(parser,div);\n\t\t}\n\t} catch(ex) {\n\t\tdiv.className = \"tc-error\";\n\t\tdiv.textContent = ex;\n\t}\n\t// Insert the div into the DOM\n\tparent.insertBefore(div,nextSibling);\n\tthis.domNodes.push(div);\n};\n\nRailroadWidget.prototype.renderDebug = function(parser,div) {\n\tvar output = [\"<pre>\"];\n\tparser.root.debug(output, \"\");\n\toutput.push(\"</pre>\");\n\tdiv.innerHTML = output.join(\"\");\n};\n\nRailroadWidget.prototype.renderSvg = function(parser,div) {\n\t// Generate a model of the diagram\n\tvar fakeSvg = parser.root.toSvg(parser.options);\n\t// Render the model into a tree of SVG DOM nodes\n\tvar svg = fakeSvg.toSVG();\n\t// Fill in the remaining attributes of any link nodes\n\tthis.patchLinks(svg);\n\t// Insert the SVG tree into the div\n\tdiv.appendChild(svg);\n};\n\nRailroadWidget.prototype.patchLinks = function(node) {\n\tvar self = this;\n\tif(!$tw.node && node.hasChildNodes()) {\n\t\tvar children = node.childNodes;\n\t\tfor(var i=0; i<children.length; i++) {\n\t\t\tvar child = children[i];\n\t\t\tvar attributes = child.attributes;\n\t\t\tif(attributes) {\n\t\t\t\t// Find each element that has a data-tw-target attribute\n\t\t\t\tvar target = child.attributes[\"data-tw-target\"];\n\t\t\t\tif(target !== undefined) {\n\t\t\t\t\ttarget = target.value;\n\t\t\t\t\tif(child.attributes[\"data-tw-external\"]) {\n\t\t\t\t\t\t// External links are straightforward\n\t\t\t\t\t\tchild.setAttribute(\"target\",\"_blank\");\n\t\t\t\t\t\tchild.setAttribute(\"rel\",\"noopener noreferrer\");\n\t\t\t\t\t} else {\n\t\t\t\t\t\t// Each internal link gets its own onclick handler, capturing its own copy of target\n\t\t\t\t\t\t(function(myTarget) {\n\t\t\t\t\t\t\tchild.onclick = function(event) {\n\t\t\t\t\t\t\t\tself.dispatchLink(myTarget,event);\n\t\t\t\t\t\t\t\treturn false;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t})(target);\n\t\t\t\t\t\ttarget = \"#\" + target;\n\t\t\t\t\t}\n\t\t\t\t\tchild.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"href\",target);\n\t\t\t\t}\n\t\t\t}\n\t\t\tthis.patchLinks(child);\n\t\t}\n\t}\n};\n\nRailroadWidget.prototype.refresh = function(changedTiddlers) {\n\tvar changedAttributes = this.computeAttributes();\n\tif(changedAttributes.text || changedTiddlers[RAILROAD_OPTIONS]) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t}\n\treturn false;\t\n};\n\nRailroadWidget.prototype.dispatchLink = function(to,event) {\n\t// Send the click on its way as a navigate event\n\tvar bounds = this.domNodes[0].getBoundingClientRect();\n\tthis.dispatchEvent({\n\t\ttype: \"tm-navigate\",\n\t\tnavigateTo: to,\n\t\tnavigateFromTitle: this.getVariable(\"storyTiddler\"),\n\t\tnavigateFromNode: this,\n\t\tnavigateFromClientRect: { top: bounds.top, left: bounds.left, width: bounds.width, right: bounds.right, bottom: bounds.bottom, height: bounds.height\n\t\t},\n\t\tnavigateSuppressNavigation: event.metaKey || event.ctrlKey || (event.button === 1)\n\t});\n\tevent.preventDefault();\n\tevent.stopPropagation();\n\treturn false;\n};\n\nexports.railroad = RailroadWidget;\n\n})();",
"title": "$:/plugins/tiddlywiki/railroad/wrapper.js",
"type": "application/javascript",
"module-type": "widget"
}
}
}
Everything there was, there is, <span class="subtitle-dark">and there will be</span>
{
"tiddlers": {
"$:/info/browser": {
"title": "$:/info/browser",
"text": "no"
},
"$:/info/node": {
"title": "$:/info/node",
"text": "yes"
}
}
}
$:/themes/tiddlywiki/vanilla
{
"tiddlers": {
"$:/themes/tiddlywiki/snowwhite/base": {
"title": "$:/themes/tiddlywiki/snowwhite/base",
"tags": "[[$:/tags/Stylesheet]]",
"text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\n.tc-sidebar-header {\n\ttext-shadow: 0 1px 0 <<colour sidebar-foreground-shadow>>;\n}\n\n.tc-tiddler-info {\n\t<<box-shadow \"inset 1px 2px 3px rgba(0,0,0,0.1)\">>\n}\n\n@media screen {\n\t.tc-tiddler-frame {\n\t\t<<box-shadow \"1px 1px 5px rgba(0, 0, 0, 0.3)\">>\n\t}\n}\n\n@media (max-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\t.tc-tiddler-frame {\n\t\t<<box-shadow none>>\n\t}\n}\n\n.tc-page-controls button svg, .tc-tiddler-controls button svg, .tc-topbar button svg {\n\t<<transition \"fill 150ms ease-in-out\">>\n}\n\n.tc-tiddler-controls button.tc-selected,\n.tc-page-controls button.tc-selected {\n\t<<filter \"drop-shadow(0px -1px 2px rgba(0,0,0,0.25))\">>\n}\n\n.tc-tiddler-frame input.tc-edit-texteditor {\n\t<<box-shadow \"inset 0 1px 8px rgba(0, 0, 0, 0.15)\">>\n}\n\n.tc-edit-tags {\n\t<<box-shadow \"inset 0 1px 8px rgba(0, 0, 0, 0.15)\">>\n}\n\n.tc-tiddler-frame .tc-edit-tags input.tc-edit-texteditor {\n\t<<box-shadow \"none\">>\n\tborder: none;\n\toutline: none;\n}\n\ncanvas.tc-edit-bitmapeditor {\n\t<<box-shadow \"2px 2px 5px rgba(0, 0, 0, 0.5)\">>\n}\n\n.tc-drop-down {\n\tborder-radius: 4px;\n\t<<box-shadow \"2px 2px 10px rgba(0, 0, 0, 0.5)\">>\n}\n\n.tc-block-dropdown {\n\tborder-radius: 4px;\n\t<<box-shadow \"2px 2px 10px rgba(0, 0, 0, 0.5)\">>\n}\n\n.tc-modal {\n\tborder-radius: 6px;\n\t<<box-shadow \"0 3px 7px rgba(0,0,0,0.3)\">>\n}\n\n.tc-modal-footer {\n\tborder-radius: 0 0 6px 6px;\n\t<<box-shadow \"inset 0 1px 0 #fff\">>;\n}\n\n\n.tc-alert {\n\tborder-radius: 6px;\n\t<<box-shadow \"0 3px 7px rgba(0,0,0,0.6)\">>\n}\n\n.tc-notification {\n\tborder-radius: 6px;\n\t<<box-shadow \"0 3px 7px rgba(0,0,0,0.3)\">>\n\ttext-shadow: 0 1px 0 rgba(255,255,255, 0.8);\n}\n\n.tc-sidebar-lists .tc-tab-set .tc-tab-divider {\n\tborder-top: none;\n\theight: 1px;\n\t<<background-linear-gradient \"left, rgba(0,0,0,0.15) 0%, rgba(0,0,0,0.0) 100%\">>\n}\n\n.tc-more-sidebar .tc-tab-buttons button {\n\t<<background-linear-gradient \"left, rgba(0,0,0,0.01) 0%, rgba(0,0,0,0.1) 100%\">>\n}\n\n.tc-more-sidebar .tc-tab-buttons button.tc-tab-selected {\n\t<<background-linear-gradient \"left, rgba(0,0,0,0.05) 0%, rgba(255,255,255,0.05) 100%\">>\n}\n\n.tc-message-box img {\n\t<<box-shadow \"1px 1px 3px rgba(0,0,0,0.5)\">>\n}\n\n.tc-plugin-info {\n\t<<box-shadow \"1px 1px 3px rgba(0,0,0,0.5)\">>\n}\n"
}
}
}
{
"tiddlers": {
"$:/themes/tiddlywiki/vanilla/themetweaks": {
"title": "$:/themes/tiddlywiki/vanilla/themetweaks",
"tags": "$:/tags/ControlPanel/Appearance",
"caption": "{{$:/language/ThemeTweaks/ThemeTweaks}}",
"text": "\\define lingo-base() $:/language/ThemeTweaks/\n\n\\define replacement-text()\n[img[$(imageTitle)$]]\n\\end\n\n\\define backgroundimage-dropdown()\n<div class=\"tc-drop-down-wrapper\">\n<$button popup=<<qualify \"$:/state/popup/themetweaks/backgroundimage\">> class=\"tc-btn-invisible tc-btn-dropdown\">{{$:/core/images/down-arrow}}</$button>\n<$reveal state=<<qualify \"$:/state/popup/themetweaks/backgroundimage\">> type=\"popup\" position=\"belowleft\" text=\"\" default=\"\">\n<div class=\"tc-drop-down\">\n<$macrocall $name=\"image-picker\" actions=\"\"\"\n\n<$action-setfield\n\t$tiddler=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimage\"\n\t$value=<<imageTitle>>\n/>\n\n\"\"\"/>\n</div>\n</$reveal>\n</div>\n\\end\n\n\\define backgroundimageattachment-dropdown()\n<$select tiddler=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimageattachment\" default=\"scroll\">\n<option value=\"scroll\"><<lingo Settings/BackgroundImageAttachment/Scroll>></option>\n<option value=\"fixed\"><<lingo Settings/BackgroundImageAttachment/Fixed>></option>\n</$select>\n\\end\n\n\\define backgroundimagesize-dropdown()\n<$select tiddler=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize\" default=\"scroll\">\n<option value=\"auto\"><<lingo Settings/BackgroundImageSize/Auto>></option>\n<option value=\"cover\"><<lingo Settings/BackgroundImageSize/Cover>></option>\n<option value=\"contain\"><<lingo Settings/BackgroundImageSize/Contain>></option>\n</$select>\n\\end\n\n<<lingo ThemeTweaks/Hint>>\n\n! <<lingo Options>>\n\n|<$link to=\"$:/themes/tiddlywiki/vanilla/options/sidebarlayout\"><<lingo Options/SidebarLayout>></$link> |<$select tiddler=\"$:/themes/tiddlywiki/vanilla/options/sidebarlayout\"><option value=\"fixed-fluid\"><<lingo Options/SidebarLayout/Fixed-Fluid>></option><option value=\"fluid-fixed\"><<lingo Options/SidebarLayout/Fluid-Fixed>></option></$select> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/options/stickytitles\"><<lingo Options/StickyTitles>></$link><br>//<<lingo Options/StickyTitles/Hint>>// |<$select tiddler=\"$:/themes/tiddlywiki/vanilla/options/stickytitles\"><option value=\"no\">{{$:/language/No}}</option><option value=\"yes\">{{$:/language/Yes}}</option></$select> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/options/codewrapping\"><<lingo Options/CodeWrapping>></$link> |<$select tiddler=\"$:/themes/tiddlywiki/vanilla/options/codewrapping\"><option value=\"pre\">{{$:/language/No}}</option><option value=\"pre-wrap\">{{$:/language/Yes}}</option></$select> |\n\n! <<lingo Settings>>\n\n|<$link to=\"$:/themes/tiddlywiki/vanilla/settings/fontfamily\"><<lingo Settings/FontFamily>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/settings/fontfamily\" default=\"\" tag=\"input\"/> | |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/settings/codefontfamily\"><<lingo Settings/CodeFontFamily>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/settings/codefontfamily\" default=\"\" tag=\"input\"/> | |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimage\"><<lingo Settings/BackgroundImage>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimage\" default=\"\" tag=\"input\"/> |<<backgroundimage-dropdown>> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimageattachment\"><<lingo Settings/BackgroundImageAttachment>></$link> |<<backgroundimageattachment-dropdown>> | |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize\"><<lingo Settings/BackgroundImageSize>></$link> |<<backgroundimagesize-dropdown>> | |\n\n! <<lingo Metrics>>\n\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/fontsize\"><<lingo Metrics/FontSize>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/fontsize\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/lineheight\"><<lingo Metrics/LineHeight>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/lineheight\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/bodyfontsize\"><<lingo Metrics/BodyFontSize>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/bodyfontsize\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/bodylineheight\"><<lingo Metrics/BodyLineHeight>></$link> |<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/bodylineheight\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/storyleft\"><<lingo Metrics/StoryLeft>></$link><br>//<<lingo Metrics/StoryLeft/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/storyleft\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/storytop\"><<lingo Metrics/StoryTop>></$link><br>//<<lingo Metrics/StoryTop/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/storytop\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/storyright\"><<lingo Metrics/StoryRight>></$link><br>//<<lingo Metrics/StoryRight/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/storyright\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/storywidth\"><<lingo Metrics/StoryWidth>></$link><br>//<<lingo Metrics/StoryWidth/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/storywidth\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth\"><<lingo Metrics/TiddlerWidth>></$link><br>//<<lingo Metrics/TiddlerWidth/Hint>>//<br> |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint\"><<lingo Metrics/SidebarBreakpoint>></$link><br>//<<lingo Metrics/SidebarBreakpoint/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint\" default=\"\" tag=\"input\"/> |\n|<$link to=\"$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth\"><<lingo Metrics/SidebarWidth>></$link><br>//<<lingo Metrics/SidebarWidth/Hint>>// |^<$edit-text tiddler=\"$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth\" default=\"\" tag=\"input\"/> |\n"
},
"$:/themes/tiddlywiki/vanilla/base": {
"title": "$:/themes/tiddlywiki/vanilla/base",
"tags": "[[$:/tags/Stylesheet]]",
"text": "\\define custom-background-datauri()\n<$set name=\"background\" value={{$:/themes/tiddlywiki/vanilla/settings/backgroundimage}}>\n<$list filter=\"[<background>is[image]]\">\n`background: url(`\n<$list filter=\"[<background>!has[_canonical_uri]]\">\n<$macrocall $name=\"datauri\" title={{$:/themes/tiddlywiki/vanilla/settings/backgroundimage}}/>\n</$list>\n<$list filter=\"[<background>has[_canonical_uri]]\">\n<$view tiddler={{$:/themes/tiddlywiki/vanilla/settings/backgroundimage}} field=\"_canonical_uri\"/>\n</$list>\n`) center center;`\n`background-attachment: `{{$:/themes/tiddlywiki/vanilla/settings/backgroundimageattachment}}`;\n-webkit-background-size:` {{$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize}}`;\n-moz-background-size:` {{$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize}}`;\n-o-background-size:` {{$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize}}`;\nbackground-size:` {{$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize}}`;`\n</$list>\n</$set>\n\\end\n\n\\define if-fluid-fixed(text,hiddenSidebarText)\n<$reveal state=\"$:/themes/tiddlywiki/vanilla/options/sidebarlayout\" type=\"match\" text=\"fluid-fixed\">\n$text$\n<$reveal state=\"$:/state/sidebar\" type=\"nomatch\" text=\"yes\" default=\"yes\">\n$hiddenSidebarText$\n</$reveal>\n</$reveal>\n\\end\n\n\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline macrocallblock\n\n/*\n** Start with the normalize CSS reset, and then belay some of its effects\n*/\n\n{{$:/themes/tiddlywiki/vanilla/reset}}\n\n*, input[type=\"search\"] {\n\tbox-sizing: border-box;\n\t-moz-box-sizing: border-box;\n\t-webkit-box-sizing: border-box;\n}\n\nhtml button {\n\tline-height: 1.2;\n\tcolor: <<colour button-foreground>>;\n\tbackground: <<colour button-background>>;\n\tborder-color: <<colour button-border>>;\n}\n\n/*\n** Basic element styles\n*/\n\nhtml {\n\tfont-family: {{$:/themes/tiddlywiki/vanilla/settings/fontfamily}};\n\ttext-rendering: optimizeLegibility; /* Enables kerning and ligatures etc. */\n\t-webkit-font-smoothing: antialiased;\n\t-moz-osx-font-smoothing: grayscale;\n}\n\nhtml:-webkit-full-screen {\n\tbackground-color: <<colour page-background>>;\n}\n\nbody.tc-body {\n\tfont-size: {{$:/themes/tiddlywiki/vanilla/metrics/fontsize}};\n\tline-height: {{$:/themes/tiddlywiki/vanilla/metrics/lineheight}};\n\tcolor: <<colour foreground>>;\n\tbackground-color: <<colour page-background>>;\n\tfill: <<colour foreground>>;\n\tword-wrap: break-word;\n\t<<custom-background-datauri>>\n}\n\nh1, h2, h3, h4, h5, h6 {\n\tline-height: 1.2;\n\tfont-weight: 300;\n}\n\npre {\n\tdisplay: block;\n\tpadding: 14px;\n\tmargin-top: 1em;\n\tmargin-bottom: 1em;\n\tword-break: normal;\n\tword-wrap: break-word;\n\twhite-space: {{$:/themes/tiddlywiki/vanilla/options/codewrapping}};\n\tbackground-color: <<colour pre-background>>;\n\tborder: 1px solid <<colour pre-border>>;\n\tpadding: 0 3px 2px;\n\tborder-radius: 3px;\n\tfont-family: {{$:/themes/tiddlywiki/vanilla/settings/codefontfamily}};\n}\n\ncode {\n\tcolor: <<colour code-foreground>>;\n\tbackground-color: <<colour code-background>>;\n\tborder: 1px solid <<colour code-border>>;\n\twhite-space: {{$:/themes/tiddlywiki/vanilla/options/codewrapping}};\n\tpadding: 0 3px 2px;\n\tborder-radius: 3px;\n\tfont-family: {{$:/themes/tiddlywiki/vanilla/settings/codefontfamily}};\n}\n\nblockquote {\n\tborder-left: 5px solid <<colour blockquote-bar>>;\n\tmargin-left: 25px;\n\tpadding-left: 10px;\n}\n\ndl dt {\n\tfont-weight: bold;\n\tmargin-top: 6px;\n}\n\ntextarea,\ninput[type=text],\ninput[type=search],\ninput[type=\"\"],\ninput:not([type]) {\n\tcolor: <<colour foreground>>;\n\tbackground: <<colour background>>;\n}\n\n.tc-muted {\n\tcolor: <<colour muted-foreground>>;\n}\n\nsvg.tc-image-button {\n\tpadding: 0px 1px 1px 0px;\n}\n\nkbd {\n\tdisplay: inline-block;\n\tpadding: 3px 5px;\n\tfont-size: 0.8em;\n\tline-height: 1.2;\n\tcolor: <<colour foreground>>;\n\tvertical-align: middle;\n\tbackground-color: <<colour background>>;\n\tborder: solid 1px <<colour muted-foreground>>;\n\tborder-bottom-color: <<colour muted-foreground>>;\n\tborder-radius: 3px;\n\tbox-shadow: inset 0 -1px 0 <<colour muted-foreground>>;\n}\n\n/*\nMarkdown likes putting code elements inside pre elements\n*/\npre > code {\n\tpadding: 0;\n\tborder: none;\n\tbackground-color: inherit;\n\tcolor: inherit;\n}\n\ntable {\n\tborder: 1px solid <<colour table-border>>;\n\twidth: auto;\n\tmax-width: 100%;\n\tcaption-side: bottom;\n\tmargin-top: 1em;\n\tmargin-bottom: 1em;\n}\n\ntable th, table td {\n\tpadding: 0 7px 0 7px;\n\tborder-top: 1px solid <<colour table-border>>;\n\tborder-left: 1px solid <<colour table-border>>;\n}\n\ntable thead tr td, table th {\n\tbackground-color: <<colour table-header-background>>;\n\tfont-weight: bold;\n}\n\ntable tfoot tr td {\n\tbackground-color: <<colour table-footer-background>>;\n}\n\n.tc-csv-table {\n\twhite-space: nowrap;\n}\n\n.tc-tiddler-frame img,\n.tc-tiddler-frame svg,\n.tc-tiddler-frame canvas,\n.tc-tiddler-frame embed,\n.tc-tiddler-frame iframe {\n\tmax-width: 100%;\n}\n\n.tc-tiddler-body > embed,\n.tc-tiddler-body > iframe {\n\twidth: 100%;\n\theight: 600px;\n}\n\n/*\n** Links\n*/\n\nbutton.tc-tiddlylink,\na.tc-tiddlylink {\n\ttext-decoration: none;\n\tfont-weight: normal;\n\tcolor: <<colour tiddler-link-foreground>>;\n\t-webkit-user-select: inherit; /* Otherwise the draggable attribute makes links impossible to select */\n}\n\n.tc-sidebar-lists a.tc-tiddlylink {\n\tcolor: <<colour sidebar-tiddler-link-foreground>>;\n}\n\n.tc-sidebar-lists a.tc-tiddlylink:hover {\n\tcolor: <<colour sidebar-tiddler-link-foreground-hover>>;\n}\n\nbutton.tc-tiddlylink:hover,\na.tc-tiddlylink:hover {\n\ttext-decoration: underline;\n}\n\na.tc-tiddlylink-resolves {\n}\n\na.tc-tiddlylink-shadow {\n\tfont-weight: bold;\n}\n\na.tc-tiddlylink-shadow.tc-tiddlylink-resolves {\n\tfont-weight: normal;\n}\n\na.tc-tiddlylink-missing {\n\tfont-style: italic;\n}\n\na.tc-tiddlylink-external {\n\ttext-decoration: underline;\n\tcolor: <<colour external-link-foreground>>;\n\tbackground-color: <<colour external-link-background>>;\n}\n\na.tc-tiddlylink-external:visited {\n\tcolor: <<colour external-link-foreground-visited>>;\n\tbackground-color: <<colour external-link-background-visited>>;\n}\n\na.tc-tiddlylink-external:hover {\n\tcolor: <<colour external-link-foreground-hover>>;\n\tbackground-color: <<colour external-link-background-hover>>;\n}\n\n/*\n** Drag and drop styles\n*/\n\n.tc-tiddler-dragger {\n\tposition: relative;\n\tz-index: -10000;\n}\n\n.tc-tiddler-dragger-inner {\n\tposition: absolute;\n\tdisplay: inline-block;\n\tpadding: 8px 20px;\n\tfont-size: 16.9px;\n\tfont-weight: bold;\n\tline-height: 20px;\n\tcolor: <<colour dragger-foreground>>;\n\ttext-shadow: 0 1px 0 rgba(0, 0, 0, 1);\n\twhite-space: nowrap;\n\tvertical-align: baseline;\n\tbackground-color: <<colour dragger-background>>;\n\tborder-radius: 20px;\n}\n\n.tc-tiddler-dragger-cover {\n\tposition: absolute;\n\tbackground-color: <<colour page-background>>;\n}\n\n.tc-dropzone {\n\tposition: relative;\n}\n\n.tc-dropzone.tc-dragover:before {\n\tz-index: 10000;\n\tdisplay: block;\n\tposition: fixed;\n\ttop: 0;\n\tleft: 0;\n\tright: 0;\n\tbackground: <<colour dropzone-background>>;\n\ttext-align: center;\n\tcontent: \"<<lingo DropMessage>>\";\n}\n\n/*\n** Plugin reload warning\n*/\n\n.tc-plugin-reload-warning {\n\tz-index: 1000;\n\tdisplay: block;\n\tposition: fixed;\n\ttop: 0;\n\tleft: 0;\n\tright: 0;\n\tbackground: <<colour alert-background>>;\n\ttext-align: center;\n}\n\n/*\n** Buttons\n*/\n\nbutton svg, button img, label svg, label img {\n\tvertical-align: middle;\n}\n\n.tc-btn-invisible {\n\tpadding: 0;\n\tmargin: 0;\n\tbackground: none;\n\tborder: none;\n}\n\n.tc-btn-boxed {\n\tfont-size: 0.6em;\n\tpadding: 0.2em;\n\tmargin: 1px;\n\tbackground: none;\n\tborder: 1px solid <<colour tiddler-controls-foreground>>;\n\tborder-radius: 0.25em;\n}\n\nhtml body.tc-body .tc-btn-boxed svg {\n\tfont-size: 1.6666em;\n}\n\n.tc-btn-boxed:hover {\n\tbackground: <<colour muted-foreground>>;\n\tcolor: <<colour background>>;\n}\n\nhtml body.tc-body .tc-btn-boxed:hover svg {\n\tfill: <<colour background>>;\n}\n\n.tc-btn-rounded {\n\tfont-size: 0.5em;\n\tline-height: 2;\n\tpadding: 0em 0.3em 0.2em 0.4em;\n\tmargin: 1px;\n\tborder: 1px solid <<colour muted-foreground>>;\n\tbackground: <<colour muted-foreground>>;\n\tcolor: <<colour background>>;\n\tborder-radius: 2em;\n}\n\nhtml body.tc-body .tc-btn-rounded svg {\n\tfont-size: 1.6666em;\n\tfill: <<colour background>>;\n}\n\n.tc-btn-rounded:hover {\n\tborder: 1px solid <<colour muted-foreground>>;\n\tbackground: <<colour background>>;\n\tcolor: <<colour muted-foreground>>;\n}\n\nhtml body.tc-body .tc-btn-rounded:hover svg {\n\tfill: <<colour muted-foreground>>;\n}\n\n.tc-btn-icon svg {\n\theight: 1em;\n\twidth: 1em;\n\tfill: <<colour muted-foreground>>;\n}\n\n.tc-btn-text {\n\tpadding: 0;\n\tmargin: 0;\n}\n\n.tc-btn-big-green {\n\tdisplay: inline-block;\n\tpadding: 8px;\n\tmargin: 4px 8px 4px 8px;\n\tbackground: <<colour download-background>>;\n\tcolor: <<colour download-foreground>>;\n\tfill: <<colour download-foreground>>;\n\tborder: none;\n\tfont-size: 1.2em;\n\tline-height: 1.4em;\n\ttext-decoration: none;\n}\n\n.tc-btn-big-green svg,\n.tc-btn-big-green img {\n\theight: 2em;\n\twidth: 2em;\n\tvertical-align: middle;\n\tfill: <<colour download-foreground>>;\n}\n\n.tc-sidebar-lists input {\n\tcolor: <<colour foreground>>;\n}\n\n.tc-sidebar-lists button {\n\tcolor: <<colour sidebar-button-foreground>>;\n\tfill: <<colour sidebar-button-foreground>>;\n}\n\n.tc-sidebar-lists button.tc-btn-mini {\n\tcolor: <<colour sidebar-muted-foreground>>;\n}\n\n.tc-sidebar-lists button.tc-btn-mini:hover {\n\tcolor: <<colour sidebar-muted-foreground-hover>>;\n}\n\nbutton svg.tc-image-button, button .tc-image-button img {\n\theight: 1em;\n\twidth: 1em;\n}\n\n.tc-unfold-banner {\n\tposition: absolute;\n\tpadding: 0;\n\tmargin: 0;\n\tbackground: none;\n\tborder: none;\n\twidth: 100%;\n\twidth: calc(100% + 2px);\n\tmargin-left: -43px;\n\ttext-align: center;\n\tborder-top: 2px solid <<colour tiddler-info-background>>;\n\tmargin-top: 4px;\n}\n\n.tc-unfold-banner:hover {\n\tbackground: <<colour tiddler-info-background>>;\n\tborder-top: 2px solid <<colour tiddler-info-border>>;\n}\n\n.tc-unfold-banner svg, .tc-fold-banner svg {\n\theight: 0.75em;\n\tfill: <<colour tiddler-controls-foreground>>;\n}\n\n.tc-unfold-banner:hover svg, .tc-fold-banner:hover svg {\n\tfill: <<colour tiddler-controls-foreground-hover>>;\n}\n\n.tc-fold-banner {\n\tposition: absolute;\n\tpadding: 0;\n\tmargin: 0;\n\tbackground: none;\n\tborder: none;\n\twidth: 23px;\n\ttext-align: center;\n\tmargin-left: -35px;\n\ttop: 6px;\n\tbottom: 6px;\n}\n\n.tc-fold-banner:hover {\n\tbackground: <<colour tiddler-info-background>>;\n}\n\n@media (max-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\t.tc-unfold-banner {\n\t\tposition: static;\n\t\twidth: calc(100% + 59px);\n\t}\n\n\t.tc-fold-banner {\n\t\twidth: 16px;\n\t\tmargin-left: -16px;\n\t\tfont-size: 0.75em;\n\t}\n\n}\n\n/*\n** Tags and missing tiddlers\n*/\n\n.tc-tag-list-item {\n\tposition: relative;\n\tdisplay: inline-block;\n\tmargin-right: 7px;\n}\n\n.tc-tags-wrapper {\n\tmargin: 4px 0 14px 0;\n}\n\n.tc-missing-tiddler-label {\n\tfont-style: italic;\n\tfont-weight: normal;\n\tdisplay: inline-block;\n\tfont-size: 11.844px;\n\tline-height: 14px;\n\twhite-space: nowrap;\n\tvertical-align: baseline;\n}\n\nbutton.tc-tag-label, span.tc-tag-label {\n\tdisplay: inline-block;\n\tpadding: 0.16em 0.7em;\n\tfont-size: 0.9em;\n\tfont-weight: 300;\n\tline-height: 1.2em;\n\tcolor: <<colour tag-foreground>>;\n\twhite-space: nowrap;\n\tvertical-align: baseline;\n\tbackground-color: <<colour tag-background>>;\n\tborder-radius: 1em;\n}\n\n.tc-untagged-separator {\n\twidth: 10em;\n\tleft: 0;\n\tmargin-left: 0;\n\tborder: 0;\n\theight: 1px;\n\tbackground: <<colour tab-divider>>;\n}\n\nbutton.tc-untagged-label {\n\tbackground-color: <<colour untagged-background>>;\n}\n\n.tc-tag-label svg, .tc-tag-label img {\n\theight: 1em;\n\twidth: 1em;\n\tfill: <<colour tag-foreground>>;\n}\n\n.tc-tag-manager-table .tc-tag-label {\n\twhite-space: normal;\n}\n\n.tc-tag-manager-tag {\n\twidth: 100%;\n}\n\n/*\n** Page layout\n*/\n\n.tc-topbar {\n\tposition: fixed;\n\tz-index: 1200;\n}\n\n.tc-topbar-left {\n\tleft: 29px;\n\ttop: 5px;\n}\n\n.tc-topbar-right {\n\ttop: 5px;\n\tright: 29px;\n}\n\n.tc-topbar button {\n\tpadding: 8px;\n}\n\n.tc-topbar svg {\n\tfill: <<colour muted-foreground>>;\n}\n\n.tc-topbar button:hover svg {\n\tfill: <<colour foreground>>;\n}\n\n.tc-sidebar-header {\n\tcolor: <<colour sidebar-foreground>>;\n\tfill: <<colour sidebar-foreground>>;\n}\n\n.tc-sidebar-header .tc-title a.tc-tiddlylink-resolves {\n\tfont-weight: 300;\n}\n\n.tc-sidebar-header .tc-sidebar-lists p {\n\tmargin-top: 3px;\n\tmargin-bottom: 3px;\n}\n\n.tc-sidebar-header .tc-missing-tiddler-label {\n\tcolor: <<colour sidebar-foreground>>;\n}\n\n.tc-advanced-search input {\n\twidth: 60%;\n}\n\n.tc-search a svg {\n\twidth: 1.2em;\n\theight: 1.2em;\n\tvertical-align: middle;\n}\n\n.tc-page-controls {\n\tmargin-top: 14px;\n\tfont-size: 1.5em;\n}\n\n.tc-page-controls button {\n\tmargin-right: 0.5em;\n}\n\n.tc-page-controls a.tc-tiddlylink:hover {\n\ttext-decoration: none;\n}\n\n.tc-page-controls img {\n\twidth: 1em;\n}\n\n.tc-page-controls svg {\n\tfill: <<colour sidebar-controls-foreground>>;\n}\n\n.tc-page-controls button:hover svg, .tc-page-controls a:hover svg {\n\tfill: <<colour sidebar-controls-foreground-hover>>;\n}\n\n.tc-menu-list-item {\n\twhite-space: nowrap;\n}\n\n.tc-menu-list-count {\n\tfont-weight: bold;\n}\n\n.tc-menu-list-subitem {\n\tpadding-left: 7px;\n}\n\n.tc-story-river {\n\tposition: relative;\n}\n\n@media (max-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\t.tc-sidebar-header {\n\t\tpadding: 14px;\n\t\tmin-height: 32px;\n\t\tmargin-top: {{$:/themes/tiddlywiki/vanilla/metrics/storytop}};\n\t}\n\n\t.tc-story-river {\n\t\tposition: relative;\n\t\tpadding: 0;\n\t}\n}\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\t.tc-message-box {\n\t\tmargin: 21px -21px 21px -21px;\n\t}\n\n\t.tc-sidebar-scrollable {\n\t\tposition: fixed;\n\t\ttop: {{$:/themes/tiddlywiki/vanilla/metrics/storytop}};\n\t\tleft: {{$:/themes/tiddlywiki/vanilla/metrics/storyright}};\n\t\tbottom: 0;\n\t\tright: 0;\n\t\toverflow-y: auto;\n\t\toverflow-x: auto;\n\t\t-webkit-overflow-scrolling: touch;\n\t\tmargin: 0 0 0 -42px;\n\t\tpadding: 71px 0 28px 42px;\n\t}\n\n\t.tc-story-river {\n\t\tposition: relative;\n\t\tleft: {{$:/themes/tiddlywiki/vanilla/metrics/storyleft}};\n\t\ttop: {{$:/themes/tiddlywiki/vanilla/metrics/storytop}};\n\t\twidth: {{$:/themes/tiddlywiki/vanilla/metrics/storywidth}};\n\t\tpadding: 42px 42px 42px 42px;\n\t}\n\n<<if-no-sidebar \"\n\n\t.tc-story-river {\n\t\twidth: calc(100% - {{$:/themes/tiddlywiki/vanilla/metrics/storyleft}});\n\t}\n\n\">>\n\n}\n\n@media print {\n\n\tbody.tc-body {\n\t\tbackground-color: transparent;\n\t}\n\n\t.tc-sidebar-header, .tc-topbar {\n\t\tdisplay: none;\n\t}\n\n\t.tc-story-river {\n\t\tmargin: 0;\n\t\tpadding: 0;\n\t}\n\n\t.tc-story-river .tc-tiddler-frame {\n\t\tmargin: 0;\n\t\tborder: none;\n\t\tpadding: 0;\n\t}\n}\n\n/*\n** Tiddler styles\n*/\n\n.tc-tiddler-frame {\n\tposition: relative;\n\tmargin-bottom: 28px;\n\tbackground-color: <<colour tiddler-background>>;\n\tborder: 1px solid <<colour tiddler-border>>;\n}\n\n{{$:/themes/tiddlywiki/vanilla/sticky}}\n\n.tc-tiddler-info {\n\tpadding: 14px 42px 14px 42px;\n\tbackground-color: <<colour tiddler-info-background>>;\n\tborder-top: 1px solid <<colour tiddler-info-border>>;\n\tborder-bottom: 1px solid <<colour tiddler-info-border>>;\n}\n\n.tc-tiddler-info p {\n\tmargin-top: 3px;\n\tmargin-bottom: 3px;\n}\n\n.tc-tiddler-info .tc-tab-buttons button.tc-tab-selected {\n\tbackground-color: <<colour tiddler-info-tab-background>>;\n\tborder-bottom: 1px solid <<colour tiddler-info-tab-background>>;\n}\n\n.tc-view-field-table {\n\twidth: 100%;\n}\n\n.tc-view-field-name {\n\twidth: 1%; /* Makes this column be as narrow as possible */\n\ttext-align: right;\n\tfont-style: italic;\n\tfont-weight: 200;\n}\n\n.tc-view-field-value {\n}\n\n@media (max-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\t.tc-tiddler-frame {\n\t\tpadding: 14px 14px 14px 14px;\n\t}\n\n\t.tc-tiddler-info {\n\t\tmargin: 0 -14px 0 -14px;\n\t}\n}\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\t.tc-tiddler-frame {\n\t\tpadding: 28px 42px 42px 42px;\n\t\twidth: {{$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth}};\n\t\tborder-radius: 2px;\n\t}\n\n<<if-no-sidebar \"\n\n\t.tc-tiddler-frame {\n\t\twidth: 100%;\n\t}\n\n\">>\n\n\t.tc-tiddler-info {\n\t\tmargin: 0 -42px 0 -42px;\n\t}\n}\n\n.tc-site-title,\n.tc-titlebar {\n\tfont-weight: 300;\n\tfont-size: 2.35em;\n\tline-height: 1.2em;\n\tcolor: <<colour tiddler-title-foreground>>;\n\tmargin: 0;\n}\n\n.tc-site-title {\n\tcolor: <<colour site-title-foreground>>;\n}\n\n.tc-tiddler-title-icon {\n\tvertical-align: middle;\n}\n\n.tc-system-title-prefix {\n\tcolor: <<colour muted-foreground>>;\n}\n\n.tc-titlebar h2 {\n\tfont-size: 1em;\n\tdisplay: inline;\n}\n\n.tc-titlebar img {\n\theight: 1em;\n}\n\n.tc-subtitle {\n\tfont-size: 0.9em;\n\tcolor: <<colour tiddler-subtitle-foreground>>;\n\tfont-weight: 300;\n}\n\n.tc-tiddler-missing .tc-title {\n font-style: italic;\n font-weight: normal;\n}\n\n.tc-tiddler-frame .tc-tiddler-controls {\n\tfloat: right;\n}\n\n.tc-tiddler-controls .tc-drop-down {\n\tfont-size: 0.6em;\n}\n\n.tc-tiddler-controls .tc-drop-down .tc-drop-down {\n\tfont-size: 1em;\n}\n\n.tc-tiddler-controls > span > button {\n\tvertical-align: baseline;\n\tmargin-left:5px;\n}\n\n.tc-tiddler-controls button svg, .tc-tiddler-controls button img,\n.tc-search button svg, .tc-search a svg {\n\theight: 0.75em;\n\tfill: <<colour tiddler-controls-foreground>>;\n}\n\n.tc-tiddler-controls button.tc-selected svg,\n.tc-page-controls button.tc-selected svg {\n\tfill: <<colour tiddler-controls-foreground-selected>>;\n}\n\n.tc-tiddler-controls button.tc-btn-invisible:hover svg,\n.tc-search button:hover svg, .tc-search a:hover svg {\n\tfill: <<colour tiddler-controls-foreground-hover>>;\n}\n\n@media print {\n\t.tc-tiddler-controls {\n\t\tdisplay: none;\n\t}\n}\n\n.tc-tiddler-help { /* Help prompts within tiddler template */\n\tcolor: <<colour muted-foreground>>;\n\tmargin-top: 14px;\n}\n\n.tc-tiddler-help a.tc-tiddlylink {\n\tcolor: <<colour very-muted-foreground>>;\n}\n\n.tc-tiddler-frame .tc-edit-texteditor {\n\twidth: 100%;\n\tmargin: 4px 0 4px 0;\n}\n\n.tc-tiddler-frame input.tc-edit-texteditor,\n.tc-tiddler-frame textarea.tc-edit-texteditor,\n.tc-tiddler-frame iframe.tc-edit-texteditor {\n\tpadding: 3px 3px 3px 3px;\n\tborder: 1px solid <<colour tiddler-editor-border>>;\n\tline-height: 1.3em;\n\t-webkit-appearance: none;\n}\n\n.tc-tiddler-frame .tc-binary-warning {\n\twidth: 100%;\n\theight: 5em;\n\ttext-align: center;\n\tpadding: 3em 3em 6em 3em;\n\tbackground: <<colour alert-background>>;\n\tborder: 1px solid <<colour alert-border>>;\n}\n\n.tc-tiddler-frame input.tc-edit-texteditor {\n\tbackground-color: <<colour tiddler-editor-background>>;\n}\n\ncanvas.tc-edit-bitmapeditor {\n\tborder: 6px solid <<colour tiddler-editor-border-image>>;\n\tcursor: crosshair;\n\t-moz-user-select: none;\n\t-webkit-user-select: none;\n\t-ms-user-select: none;\n\tmargin-top: 6px;\n\tmargin-bottom: 6px;\n}\n\n.tc-edit-bitmapeditor-width {\n\tdisplay: block;\n}\n\n.tc-edit-bitmapeditor-height {\n\tdisplay: block;\n}\n\n.tc-tiddler-body {\n\tclear: both;\n}\n\n.tc-tiddler-frame .tc-tiddler-body {\n\tfont-size: {{$:/themes/tiddlywiki/vanilla/metrics/bodyfontsize}};\n\tline-height: {{$:/themes/tiddlywiki/vanilla/metrics/bodylineheight}};\n}\n\n.tc-titlebar, .tc-tiddler-edit-title {\n\toverflow: hidden; /* https://github.com/Jermolene/TiddlyWiki5/issues/282 */\n}\n\nhtml body.tc-body.tc-single-tiddler-window {\n\tmargin: 1em;\n\tbackground: <<colour tiddler-background>>;\n}\n\n.tc-single-tiddler-window img,\n.tc-single-tiddler-window svg,\n.tc-single-tiddler-window canvas,\n.tc-single-tiddler-window embed,\n.tc-single-tiddler-window iframe {\n\tmax-width: 100%;\n}\n\n/*\n** Editor\n*/\n\n.tc-editor-toolbar {\n\tmargin-top: 8px;\n}\n\n.tc-editor-toolbar button {\n\tvertical-align: middle;\n\tbackground-color: <<colour tiddler-controls-foreground>>;\n\tfill: <<colour tiddler-controls-foreground-selected>>;\n\tborder-radius: 4px;\n\tpadding: 3px;\n\tmargin: 2px 0 2px 4px;\n}\n\n.tc-editor-toolbar button.tc-text-editor-toolbar-item-adjunct {\n\tmargin-left: 1px;\n\twidth: 1em;\n\tborder-radius: 8px;\n}\n\n.tc-editor-toolbar button.tc-text-editor-toolbar-item-start-group {\n\tmargin-left: 11px;\n}\n\n.tc-editor-toolbar button.tc-selected {\n\tbackground-color: <<colour primary>>;\n}\n\n.tc-editor-toolbar button svg {\n\twidth: 1.6em;\n\theight: 1.2em;\n}\n\n.tc-editor-toolbar button:hover {\n\tbackground-color: <<colour tiddler-controls-foreground-selected>>;\n\tfill: <<colour background>>;\n}\n\n.tc-editor-toolbar .tc-text-editor-toolbar-more {\n\twhite-space: normal;\n}\n\n.tc-editor-toolbar .tc-text-editor-toolbar-more button {\n\tdisplay: inline-block;\n\tpadding: 3px;\n\twidth: auto;\n}\n\n.tc-editor-toolbar .tc-search-results {\n\tpadding: 0;\n}\n\n/*\n** Adjustments for fluid-fixed mode\n*/\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n<<if-fluid-fixed text:\"\"\"\n\n\t.tc-story-river {\n\t\tpadding-right: 0;\n\t\tposition: relative;\n\t\twidth: auto;\n\t\tleft: 0;\n\t\tmargin-left: {{$:/themes/tiddlywiki/vanilla/metrics/storyleft}};\n\t\tmargin-right: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth}};\n\t}\n\n\t.tc-tiddler-frame {\n\t\twidth: 100%;\n\t}\n\n\t.tc-sidebar-scrollable {\n\t\tleft: auto;\n\t\tbottom: 0;\n\t\tright: 0;\n\t\twidth: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth}};\n\t}\n\n\tbody.tc-body .tc-storyview-zoomin-tiddler {\n\t\twidth: 100%;\n\t\twidth: calc(100% - 42px);\n\t}\n\n\"\"\" hiddenSidebarText:\"\"\"\n\n\t.tc-story-river {\n\t\tpadding-right: 3em;\n\t\tmargin-right: 0;\n\t}\n\n\tbody.tc-body .tc-storyview-zoomin-tiddler {\n\t\twidth: 100%;\n\t\twidth: calc(100% - 84px);\n\t}\n\n\"\"\">>\n\n}\n\n/*\n** Toolbar buttons\n*/\n\n.tc-page-controls svg.tc-image-new-button {\n fill: <<colour toolbar-new-button>>;\n}\n\n.tc-page-controls svg.tc-image-options-button {\n fill: <<colour toolbar-options-button>>;\n}\n\n.tc-page-controls svg.tc-image-save-button {\n fill: <<colour toolbar-save-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-info-button {\n fill: <<colour toolbar-info-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-edit-button {\n fill: <<colour toolbar-edit-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-close-button {\n fill: <<colour toolbar-close-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-delete-button {\n fill: <<colour toolbar-delete-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-cancel-button {\n fill: <<colour toolbar-cancel-button>>;\n}\n\n.tc-tiddler-controls button svg.tc-image-done-button {\n fill: <<colour toolbar-done-button>>;\n}\n\n/*\n** Tiddler edit mode\n*/\n\n.tc-tiddler-edit-frame em.tc-edit {\n\tcolor: <<colour muted-foreground>>;\n\tfont-style: normal;\n}\n\n.tc-edit-type-dropdown a.tc-tiddlylink-missing {\n\tfont-style: normal;\n}\n\n.tc-edit-tags {\n\tborder: 1px solid <<colour tiddler-editor-border>>;\n\tpadding: 4px 8px 4px 8px;\n}\n\n.tc-edit-add-tag {\n\tdisplay: inline-block;\n}\n\n.tc-edit-add-tag .tc-add-tag-name input {\n\twidth: 50%;\n}\n\n.tc-edit-tags .tc-tag-label {\n\tdisplay: inline-block;\n}\n\n.tc-edit-tags-list {\n\tmargin: 14px 0 14px 0;\n}\n\n.tc-remove-tag-button {\n\tpadding-left: 4px;\n}\n\n.tc-tiddler-preview {\n\toverflow: auto;\n}\n\n.tc-tiddler-preview-preview {\n\tfloat: right;\n\twidth: 49%;\n\tborder: 1px solid <<colour tiddler-editor-border>>;\n\tmargin: 4px 3px 3px 3px;\n\tpadding: 3px 3px 3px 3px;\n}\n\n.tc-tiddler-frame .tc-tiddler-preview .tc-edit-texteditor {\n\twidth: 49%;\n}\n\n.tc-tiddler-frame .tc-tiddler-preview canvas.tc-edit-bitmapeditor {\n\tmax-width: 49%;\n}\n\n.tc-edit-fields {\n\twidth: 100%;\n}\n\n\n.tc-edit-fields table, .tc-edit-fields tr, .tc-edit-fields td {\n\tborder: none;\n\tpadding: 4px;\n}\n\n.tc-edit-fields > tbody > .tc-edit-field:nth-child(odd) {\n\tbackground-color: <<colour tiddler-editor-fields-odd>>;\n}\n\n.tc-edit-fields > tbody > .tc-edit-field:nth-child(even) {\n\tbackground-color: <<colour tiddler-editor-fields-even>>;\n}\n\n.tc-edit-field-name {\n\ttext-align: right;\n}\n\n.tc-edit-field-value input {\n\twidth: 100%;\n}\n\n.tc-edit-field-remove {\n}\n\n.tc-edit-field-remove svg {\n\theight: 1em;\n\twidth: 1em;\n\tfill: <<colour muted-foreground>>;\n\tvertical-align: middle;\n}\n\n.tc-edit-field-add-name {\n\tdisplay: inline-block;\n\twidth: 15%;\n}\n\n.tc-edit-field-add-value {\n\tdisplay: inline-block;\n\twidth: 40%;\n}\n\n.tc-edit-field-add-button {\n\tdisplay: inline-block;\n\twidth: 10%;\n}\n\n/*\n** Storyview Classes\n*/\n\n.tc-storyview-zoomin-tiddler {\n\tposition: absolute;\n\tdisplay: block;\n\twidth: 100%;\n}\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\t.tc-storyview-zoomin-tiddler {\n\t\twidth: calc(100% - 84px);\n\t}\n\n}\n\n/*\n** Dropdowns\n*/\n\n.tc-btn-dropdown {\n\ttext-align: left;\n}\n\n.tc-btn-dropdown svg, .tc-btn-dropdown img {\n\theight: 1em;\n\twidth: 1em;\n\tfill: <<colour muted-foreground>>;\n}\n\n.tc-drop-down-wrapper {\n\tposition: relative;\n}\n\n.tc-drop-down {\n\tmin-width: 380px;\n\tborder: 1px solid <<colour dropdown-border>>;\n\tbackground-color: <<colour dropdown-background>>;\n\tpadding: 7px 0 7px 0;\n\tmargin: 4px 0 0 0;\n\twhite-space: nowrap;\n\ttext-shadow: none;\n\tline-height: 1.4;\n}\n\n.tc-drop-down .tc-drop-down {\n\tmargin-left: 14px;\n}\n\n.tc-drop-down button svg, .tc-drop-down a svg {\n\tfill: <<colour foreground>>;\n}\n\n.tc-drop-down button.tc-btn-invisible:hover svg {\n\tfill: <<colour foreground>>;\n}\n\n.tc-drop-down p {\n\tpadding: 0 14px 0 14px;\n}\n\n.tc-drop-down svg {\n\twidth: 1em;\n\theight: 1em;\n}\n\n.tc-drop-down img {\n\twidth: 1em;\n}\n\n.tc-drop-down-language-chooser img {\n\twidth: 2em;\n\tvertical-align: baseline;\n}\n\n.tc-drop-down a, .tc-drop-down button {\n\tdisplay: block;\n\tpadding: 0 14px 0 14px;\n\twidth: 100%;\n\ttext-align: left;\n\tcolor: <<colour foreground>>;\n\tline-height: 1.4;\n}\n\n.tc-drop-down .tc-tab-set .tc-tab-buttons button {\n\tdisplay: inline-block;\n width: auto;\n margin-bottom: 0px;\n border-bottom-left-radius: 0;\n border-bottom-right-radius: 0;\n}\n\n.tc-drop-down .tc-prompt {\n\tpadding: 0 14px;\n}\n\n.tc-drop-down .tc-chooser {\n\tborder: none;\n}\n\n.tc-drop-down .tc-chooser .tc-swatches-horiz {\n\tfont-size: 0.4em;\n\tpadding-left: 1.2em;\n}\n\n.tc-drop-down .tc-file-input-wrapper {\n\twidth: 100%;\n}\n\n.tc-drop-down .tc-file-input-wrapper button {\n\tcolor: <<colour foreground>>;\n}\n\n.tc-drop-down a:hover, .tc-drop-down button:hover, .tc-drop-down .tc-file-input-wrapper:hover button {\n\tcolor: <<colour tiddler-link-background>>;\n\tbackground-color: <<colour tiddler-link-foreground>>;\n\ttext-decoration: none;\n}\n\n.tc-drop-down .tc-tab-buttons button {\n\tbackground-color: <<colour dropdown-tab-background>>;\n}\n\n.tc-drop-down .tc-tab-buttons button.tc-tab-selected {\n\tbackground-color: <<colour dropdown-tab-background-selected>>;\n\tborder-bottom: 1px solid <<colour dropdown-tab-background-selected>>;\n}\n\n.tc-drop-down-bullet {\n\tdisplay: inline-block;\n\twidth: 0.5em;\n}\n\n.tc-drop-down .tc-tab-contents a {\n\tpadding: 0 0.5em 0 0.5em;\n}\n\n.tc-block-dropdown-wrapper {\n\tposition: relative;\n}\n\n.tc-block-dropdown {\n\tposition: absolute;\n\tmin-width: 220px;\n\tborder: 1px solid <<colour dropdown-border>>;\n\tbackground-color: <<colour dropdown-background>>;\n\tpadding: 7px 0;\n\tmargin: 4px 0 0 0;\n\twhite-space: nowrap;\n\tz-index: 1000;\n\ttext-shadow: none;\n}\n\n.tc-block-dropdown.tc-search-drop-down {\n\tmargin-left: -12px;\n}\n\n.tc-block-dropdown a {\n\tdisplay: block;\n\tpadding: 4px 14px 4px 14px;\n}\n\n.tc-block-dropdown.tc-search-drop-down a {\n\tdisplay: block;\n\tpadding: 0px 10px 0px 10px;\n}\n\n.tc-drop-down .tc-dropdown-item-plain,\n.tc-block-dropdown .tc-dropdown-item-plain {\n\tpadding: 4px 14px 4px 7px;\n}\n\n.tc-drop-down .tc-dropdown-item,\n.tc-block-dropdown .tc-dropdown-item {\n\tpadding: 4px 14px 4px 7px;\n\tcolor: <<colour muted-foreground>>;\n}\n\n.tc-block-dropdown a:hover {\n\tcolor: <<colour tiddler-link-background>>;\n\tbackground-color: <<colour tiddler-link-foreground>>;\n\ttext-decoration: none;\n}\n\n.tc-search-results {\n\tpadding: 0 7px 0 7px;\n}\n\n.tc-image-chooser, .tc-colour-chooser {\n\twhite-space: normal;\n}\n\n.tc-image-chooser a,\n.tc-colour-chooser a {\n\tdisplay: inline-block;\n\tvertical-align: top;\n\ttext-align: center;\n\tposition: relative;\n}\n\n.tc-image-chooser a {\n\tborder: 1px solid <<colour muted-foreground>>;\n\tpadding: 2px;\n\tmargin: 2px;\n\twidth: 4em;\n\theight: 4em;\n}\n\n.tc-colour-chooser a {\n\tpadding: 3px;\n\twidth: 2em;\n\theight: 2em;\n\tvertical-align: middle;\n}\n\n.tc-image-chooser a:hover,\n.tc-colour-chooser a:hover {\n\tbackground: <<colour primary>>;\n\tpadding: 0px;\n\tborder: 3px solid <<colour primary>>;\n}\n\n.tc-image-chooser a svg,\n.tc-image-chooser a img {\n\tdisplay: inline-block;\n\twidth: auto;\n\theight: auto;\n\tmax-width: 3.5em;\n\tmax-height: 3.5em;\n\tposition: absolute;\n\ttop: 0;\n\tbottom: 0;\n\tleft: 0;\n\tright: 0;\n\tmargin: auto;\n}\n\n/*\n** Modals\n*/\n\n.tc-modal-wrapper {\n\tposition: fixed;\n\toverflow: auto;\n\toverflow-y: scroll;\n\ttop: 0;\n\tright: 0;\n\tbottom: 0;\n\tleft: 0;\n\tz-index: 900;\n}\n\n.tc-modal-backdrop {\n\tposition: fixed;\n\ttop: 0;\n\tright: 0;\n\tbottom: 0;\n\tleft: 0;\n\tz-index: 1000;\n\tbackground-color: <<colour modal-backdrop>>;\n}\n\n.tc-modal {\n\tz-index: 1100;\n\tbackground-color: <<colour modal-background>>;\n\tborder: 1px solid <<colour modal-border>>;\n}\n\n@media (max-width: 55em) {\n\t.tc-modal {\n\t\tposition: fixed;\n\t\ttop: 1em;\n\t\tleft: 1em;\n\t\tright: 1em;\n\t}\n\n\t.tc-modal-body {\n\t\toverflow-y: auto;\n\t\tmax-height: 400px;\n\t\tmax-height: 60vh;\n\t}\n}\n\n@media (min-width: 55em) {\n\t.tc-modal {\n\t\tposition: fixed;\n\t\ttop: 2em;\n\t\tleft: 25%;\n\t\twidth: 50%;\n\t}\n\n\t.tc-modal-body {\n\t\toverflow-y: auto;\n\t\tmax-height: 400px;\n\t\tmax-height: 60vh;\n\t}\n}\n\n.tc-modal-header {\n\tpadding: 9px 15px;\n\tborder-bottom: 1px solid <<colour modal-header-border>>;\n}\n\n.tc-modal-header h3 {\n\tmargin: 0;\n\tline-height: 30px;\n}\n\n.tc-modal-header img, .tc-modal-header svg {\n\twidth: 1em;\n\theight: 1em;\n}\n\n.tc-modal-body {\n\tpadding: 15px;\n}\n\n.tc-modal-footer {\n\tpadding: 14px 15px 15px;\n\tmargin-bottom: 0;\n\ttext-align: right;\n\tbackground-color: <<colour modal-footer-background>>;\n\tborder-top: 1px solid <<colour modal-footer-border>>;\n}\n\n/*\n** Notifications\n*/\n\n.tc-notification {\n\tposition: fixed;\n\ttop: 14px;\n\tright: 42px;\n\tz-index: 1300;\n\tmax-width: 280px;\n\tpadding: 0 14px 0 14px;\n\tbackground-color: <<colour notification-background>>;\n\tborder: 1px solid <<colour notification-border>>;\n}\n\n/*\n** Tabs\n*/\n\n.tc-tab-set.tc-vertical {\n\tdisplay: -webkit-flex;\n\tdisplay: flex;\n}\n\n.tc-tab-buttons {\n\tfont-size: 0.85em;\n\tpadding-top: 1em;\n\tmargin-bottom: -2px;\n}\n\n.tc-tab-buttons.tc-vertical {\n\tz-index: 100;\n\tdisplay: block;\n\tpadding-top: 14px;\n\tvertical-align: top;\n\ttext-align: right;\n\tmargin-bottom: inherit;\n\tmargin-right: -1px;\n\tmax-width: 33%;\n\t-webkit-flex: 0 0 auto;\n\tflex: 0 0 auto;\n}\n\n.tc-tab-buttons button.tc-tab-selected {\n\tcolor: <<colour tab-foreground-selected>>;\n\tbackground-color: <<colour tab-background-selected>>;\n\tborder-left: 1px solid <<colour tab-border-selected>>;\n\tborder-top: 1px solid <<colour tab-border-selected>>;\n\tborder-right: 1px solid <<colour tab-border-selected>>;\n}\n\n.tc-tab-buttons button {\n\tcolor: <<colour tab-foreground>>;\n\tpadding: 3px 5px 3px 5px;\n\tmargin-right: 0.3em;\n\tfont-weight: 300;\n\tborder: none;\n\tbackground: inherit;\n\tbackground-color: <<colour tab-background>>;\n\tborder-left: 1px solid <<colour tab-border>>;\n\tborder-top: 1px solid <<colour tab-border>>;\n\tborder-right: 1px solid <<colour tab-border>>;\n\tborder-top-left-radius: 2px;\n\tborder-top-right-radius: 2px;\n}\n\n.tc-tab-buttons.tc-vertical button {\n\tdisplay: block;\n\twidth: 100%;\n\tmargin-top: 3px;\n\tmargin-right: 0;\n\ttext-align: right;\n\tbackground-color: <<colour tab-background>>;\n\tborder-left: 1px solid <<colour tab-border>>;\n\tborder-bottom: 1px solid <<colour tab-border>>;\n\tborder-right: none;\n\tborder-top-left-radius: 2px;\n\tborder-bottom-left-radius: 2px;\n}\n\n.tc-tab-buttons.tc-vertical button.tc-tab-selected {\n\tbackground-color: <<colour tab-background-selected>>;\n\tborder-right: 1px solid <<colour tab-background-selected>>;\n}\n\n.tc-tab-divider {\n\tborder-top: 1px solid <<colour tab-divider>>;\n}\n\n.tc-tab-divider.tc-vertical {\n\tdisplay: none;\n}\n\n.tc-tab-content {\n\tmargin-top: 14px;\n}\n\n.tc-tab-content.tc-vertical {\n\tdisplay: inline-block;\n\tvertical-align: top;\n\tpadding-top: 0;\n\tpadding-left: 14px;\n\tborder-left: 1px solid <<colour tab-border>>;\n\t-webkit-flex: 1 0 70%;\n\tflex: 1 0 70%;\n}\n\n.tc-sidebar-lists .tc-tab-buttons {\n\tmargin-bottom: -1px;\n}\n\n.tc-sidebar-lists .tc-tab-buttons button.tc-tab-selected {\n\tbackground-color: <<colour sidebar-tab-background-selected>>;\n\tcolor: <<colour sidebar-tab-foreground-selected>>;\n\tborder-left: 1px solid <<colour sidebar-tab-border-selected>>;\n\tborder-top: 1px solid <<colour sidebar-tab-border-selected>>;\n\tborder-right: 1px solid <<colour sidebar-tab-border-selected>>;\n}\n\n.tc-sidebar-lists .tc-tab-buttons button {\n\tbackground-color: <<colour sidebar-tab-background>>;\n\tcolor: <<colour sidebar-tab-foreground>>;\n\tborder-left: 1px solid <<colour sidebar-tab-border>>;\n\tborder-top: 1px solid <<colour sidebar-tab-border>>;\n\tborder-right: 1px solid <<colour sidebar-tab-border>>;\n}\n\n.tc-sidebar-lists .tc-tab-divider {\n\tborder-top: 1px solid <<colour sidebar-tab-divider>>;\n}\n\n.tc-more-sidebar .tc-tab-buttons button {\n\tdisplay: block;\n\twidth: 100%;\n\tbackground-color: <<colour sidebar-tab-background>>;\n\tborder-top: none;\n\tborder-left: none;\n\tborder-bottom: none;\n\tborder-right: 1px solid #ccc;\n\tmargin-bottom: inherit;\n}\n\n.tc-more-sidebar .tc-tab-buttons button.tc-tab-selected {\n\tbackground-color: <<colour sidebar-tab-background-selected>>;\n\tborder: none;\n}\n\n/*\n** Alerts\n*/\n\n.tc-alerts {\n\tposition: fixed;\n\ttop: 0;\n\tleft: 0;\n\tmax-width: 500px;\n\tz-index: 20000;\n}\n\n.tc-alert {\n\tposition: relative;\n\tmargin: 28px;\n\tpadding: 14px 14px 14px 14px;\n\tborder: 2px solid <<colour alert-border>>;\n\tbackground-color: <<colour alert-background>>;\n}\n\n.tc-alert-toolbar {\n\tposition: absolute;\n\ttop: 14px;\n\tright: 14px;\n}\n\n.tc-alert-toolbar svg {\n\tfill: <<colour alert-muted-foreground>>;\n}\n\n.tc-alert-subtitle {\n\tcolor: <<colour alert-muted-foreground>>;\n\tfont-weight: bold;\n}\n\n.tc-alert-highlight {\n\tcolor: <<colour alert-highlight>>;\n}\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\t.tc-static-alert {\n\t\tposition: relative;\n\t}\n\n\t.tc-static-alert-inner {\n\t\tposition: absolute;\n\t\tz-index: 100;\n\t}\n\n}\n\n.tc-static-alert-inner {\n\tpadding: 0 2px 2px 42px;\n\tcolor: <<colour static-alert-foreground>>;\n}\n\n/*\n** Control panel\n*/\n\n.tc-control-panel td {\n\tpadding: 4px;\n}\n\n.tc-control-panel table, .tc-control-panel table input, .tc-control-panel table textarea {\n\twidth: 100%;\n}\n\n.tc-plugin-info {\n\tdisplay: block;\n\tborder: 1px solid <<colour muted-foreground>>;\n\tbackground-colour: <<colour background>>;\n\tmargin: 0.5em 0 0.5em 0;\n\tpadding: 4px;\n}\n\n.tc-plugin-info-disabled {\n\tbackground: -webkit-repeating-linear-gradient(45deg, #ff0, #ff0 10px, #eee 10px, #eee 20px);\n\tbackground: repeating-linear-gradient(45deg, #ff0, #ff0 10px, #eee 10px, #eee 20px);\n}\n\n.tc-plugin-info-disabled:hover {\n\tbackground: -webkit-repeating-linear-gradient(45deg, #aa0, #aa0 10px, #888 10px, #888 20px);\n\tbackground: repeating-linear-gradient(45deg, #aa0, #aa0 10px, #888 10px, #888 20px);\n}\n\na.tc-tiddlylink.tc-plugin-info:hover {\n\ttext-decoration: none;\n\tbackground-color: <<colour primary>>;\n\tcolor: <<colour background>>;\n\tfill: <<colour foreground>>;\n}\n\na.tc-tiddlylink.tc-plugin-info:hover .tc-plugin-info > .tc-plugin-info-chunk > svg {\n\tfill: <<colour foreground>>;\n}\n\n.tc-plugin-info-chunk {\n\tdisplay: inline-block;\n\tvertical-align: middle;\n}\n\n.tc-plugin-info-chunk h1 {\n\tfont-size: 1em;\n\tmargin: 2px 0 2px 0;\n}\n\n.tc-plugin-info-chunk h2 {\n\tfont-size: 0.8em;\n\tmargin: 2px 0 2px 0;\n}\n\n.tc-plugin-info-chunk div {\n\tfont-size: 0.7em;\n\tmargin: 2px 0 2px 0;\n}\n\n.tc-plugin-info:hover > .tc-plugin-info-chunk > img, .tc-plugin-info:hover > .tc-plugin-info-chunk > svg {\n\twidth: 2em;\n\theight: 2em;\n\tfill: <<colour foreground>>;\n}\n\n.tc-plugin-info > .tc-plugin-info-chunk > img, .tc-plugin-info > .tc-plugin-info-chunk > svg {\n\twidth: 2em;\n\theight: 2em;\n\tfill: <<colour muted-foreground>>;\n}\n\n.tc-plugin-info.tc-small-icon > .tc-plugin-info-chunk > img, .tc-plugin-info.tc-small-icon > .tc-plugin-info-chunk > svg {\n\twidth: 1em;\n\theight: 1em;\n}\n\n.tc-plugin-info-dropdown {\n\tborder: 1px solid <<colour muted-foreground>>;\n\tmargin-top: -8px;\n}\n\n.tc-plugin-info-dropdown-message {\n\tbackground: <<colour message-background>>;\n\tpadding: 0.5em 1em 0.5em 1em;\n\tfont-weight: bold;\n\tfont-size: 0.8em;\n}\n\n.tc-plugin-info-dropdown-body {\n\tpadding: 1em 1em 1em 1em;\n}\n\n/*\n** Message boxes\n*/\n\n.tc-message-box {\n\tborder: 1px solid <<colour message-border>>;\n\tbackground: <<colour message-background>>;\n\tpadding: 0px 21px 0px 21px;\n\tfont-size: 12px;\n\tline-height: 18px;\n\tcolor: <<colour message-foreground>>;\n}\n\n/*\n** Pictures\n*/\n\n.tc-bordered-image {\n\tborder: 1px solid <<colour muted-foreground>>;\n\tpadding: 5px;\n\tmargin: 5px;\n}\n\n/*\n** Floats\n*/\n\n.tc-float-right {\n\tfloat: right;\n}\n\n/*\n** Chooser\n*/\n\n.tc-chooser {\n\tborder: 1px solid <<colour table-border>>;\n}\n\n.tc-chooser-item {\n\tborder: 8px;\n\tpadding: 2px 4px;\n}\n\n.tc-chooser-item a.tc-tiddlylink {\n\tdisplay: block;\n\ttext-decoration: none;\n\tcolor: <<colour tiddler-link-foreground>>;\n\tbackground-color: <<colour tiddler-link-background>>;\n}\n\n.tc-chooser-item a.tc-tiddlylink:hover {\n\ttext-decoration: none;\n\tcolor: <<colour tiddler-link-background>>;\n\tbackground-color: <<colour tiddler-link-foreground>>;\n}\n\n/*\n** Palette swatches\n*/\n\n.tc-swatches-horiz {\n}\n\n.tc-swatches-horiz .tc-swatch {\n\tdisplay: inline-block;\n}\n\n.tc-swatch {\n\twidth: 2em;\n\theight: 2em;\n\tmargin: 0.4em;\n\tborder: 1px solid #888;\n}\n\n/*\n** Table of contents\n*/\n\n.tc-sidebar-lists .tc-table-of-contents {\n\twhite-space: nowrap;\n}\n\n.tc-table-of-contents button {\n\tcolor: <<colour sidebar-foreground>>;\n}\n\n.tc-table-of-contents svg {\n\twidth: 0.7em;\n\theight: 0.7em;\n\tvertical-align: middle;\n\tfill: <<colour sidebar-foreground>>;\n}\n\n.tc-table-of-contents ol {\n\tlist-style-type: none;\n\tpadding-left: 0;\n}\n\n.tc-table-of-contents ol ol {\n\tpadding-left: 1em;\n}\n\n.tc-table-of-contents li {\n\tfont-size: 1.0em;\n\tfont-weight: bold;\n}\n\n.tc-table-of-contents li a {\n\tfont-weight: bold;\n}\n\n.tc-table-of-contents li li {\n\tfont-size: 0.95em;\n\tfont-weight: normal;\n\tline-height: 1.4;\n}\n\n.tc-table-of-contents li li a {\n\tfont-weight: normal;\n}\n\n.tc-table-of-contents li li li {\n\tfont-size: 0.95em;\n\tfont-weight: 200;\n\tline-height: 1.5;\n}\n\n.tc-table-of-contents li li li a {\n\tfont-weight: bold;\n}\n\n.tc-table-of-contents li li li li {\n\tfont-size: 0.95em;\n\tfont-weight: 200;\n}\n\n.tc-tabbed-table-of-contents {\n\tdisplay: -webkit-flex;\n\tdisplay: flex;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents {\n\tz-index: 100;\n\tdisplay: inline-block;\n\tpadding-left: 1em;\n\tmax-width: 50%;\n\t-webkit-flex: 0 0 auto;\n\tflex: 0 0 auto;\n\tbackground: <<colour tab-background>>;\n\tborder-left: 1px solid <<colour tab-border>>;\n\tborder-top: 1px solid <<colour tab-border>>;\n\tborder-bottom: 1px solid <<colour tab-border>>;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item > a,\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item-selected > a {\n\tdisplay: block;\n\tpadding: 0.12em 1em 0.12em 0.25em;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item > a {\n\tborder-top: 1px solid <<colour tab-background>>;\n\tborder-left: 1px solid <<colour tab-background>>;\n\tborder-bottom: 1px solid <<colour tab-background>>;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item > a:hover {\n\ttext-decoration: none;\n\tborder-top: 1px solid <<colour tab-border>>;\n\tborder-left: 1px solid <<colour tab-border>>;\n\tborder-bottom: 1px solid <<colour tab-border>>;\n\tbackground: <<colour tab-border>>;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item-selected > a {\n\tborder-top: 1px solid <<colour tab-border>>;\n\tborder-left: 1px solid <<colour tab-border>>;\n\tborder-bottom: 1px solid <<colour tab-border>>;\n\tbackground: <<colour background>>;\n\tmargin-right: -1px;\n}\n\n.tc-tabbed-table-of-contents .tc-table-of-contents .toc-item-selected > a:hover {\n\ttext-decoration: none;\n}\n\n.tc-tabbed-table-of-contents .tc-tabbed-table-of-contents-content {\n\tdisplay: inline-block;\n\tvertical-align: top;\n\tpadding-left: 1.5em;\n\tpadding-right: 1.5em;\n\tborder: 1px solid <<colour tab-border>>;\n\t-webkit-flex: 1 0 50%;\n\tflex: 1 0 50%;\n}\n\n/*\n** Dirty indicator\n*/\n\nbody.tc-dirty span.tc-dirty-indicator, body.tc-dirty span.tc-dirty-indicator svg {\n\tfill: <<colour dirty-indicator>>;\n\tcolor: <<colour dirty-indicator>>;\n}\n\n/*\n** File inputs\n*/\n\n.tc-file-input-wrapper {\n\tposition: relative;\n\toverflow: hidden;\n\tdisplay: inline-block;\n\tvertical-align: middle;\n}\n\n.tc-file-input-wrapper input[type=file] {\n\tposition: absolute;\n\ttop: 0;\n\tleft: 0;\n\tright: 0;\n\tbottom: 0;\n\tfont-size: 999px;\n\tmax-width: 100%;\n\tmax-height: 100%;\n\tfilter: alpha(opacity=0);\n\topacity: 0;\n\toutline: none;\n\tbackground: white;\n\tcursor: pointer;\n\tdisplay: inline-block;\n}\n\n/*\n** Thumbnail macros\n*/\n\n.tc-thumbnail-wrapper {\n\tposition: relative;\n\tdisplay: inline-block;\n\tmargin: 6px;\n\tvertical-align: top;\n}\n\n.tc-thumbnail-right-wrapper {\n\tfloat:right;\n\tmargin: 0.5em 0 0.5em 0.5em;\n}\n\n.tc-thumbnail-image {\n\ttext-align: center;\n\toverflow: hidden;\n\tborder-radius: 3px;\n}\n\n.tc-thumbnail-image svg,\n.tc-thumbnail-image img {\n\tfilter: alpha(opacity=1);\n\topacity: 1;\n\tmin-width: 100%;\n\tmin-height: 100%;\n\tmax-width: 100%;\n}\n\n.tc-thumbnail-wrapper:hover .tc-thumbnail-image svg,\n.tc-thumbnail-wrapper:hover .tc-thumbnail-image img {\n\tfilter: alpha(opacity=0.8);\n\topacity: 0.8;\n}\n\n.tc-thumbnail-background {\n\tposition: absolute;\n\tborder-radius: 3px;\n}\n\n.tc-thumbnail-icon svg,\n.tc-thumbnail-icon img {\n\twidth: 3em;\n\theight: 3em;\n\t<<filter \"drop-shadow(2px 2px 4px rgba(0,0,0,0.3))\">>\n}\n\n.tc-thumbnail-wrapper:hover .tc-thumbnail-icon svg,\n.tc-thumbnail-wrapper:hover .tc-thumbnail-icon img {\n\tfill: #fff;\n\t<<filter \"drop-shadow(3px 3px 4px rgba(0,0,0,0.6))\">>\n}\n\n.tc-thumbnail-icon {\n\tposition: absolute;\n\ttop: 0;\n\tleft: 0;\n\tright: 0;\n\tbottom: 0;\n\tdisplay: -webkit-flex;\n\t-webkit-align-items: center;\n\t-webkit-justify-content: center;\n\tdisplay: flex;\n\talign-items: center;\n\tjustify-content: center;\n}\n\n.tc-thumbnail-caption {\n\tposition: absolute;\n\tbackground-color: #777;\n\tcolor: #fff;\n\ttext-align: center;\n\tbottom: 0;\n\twidth: 100%;\n\tfilter: alpha(opacity=0.9);\n\topacity: 0.9;\n\tline-height: 1.4;\n\tborder-bottom-left-radius: 3px;\n\tborder-bottom-right-radius: 3px;\n}\n\n.tc-thumbnail-wrapper:hover .tc-thumbnail-caption {\n\tfilter: alpha(opacity=1);\n\topacity: 1;\n}\n\n/*\n** Errors\n*/\n\n.tc-error {\n\tbackground: #f00;\n\tcolor: #fff;\n}\n"
},
"$:/themes/tiddlywiki/vanilla/metrics/bodyfontsize": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/bodyfontsize",
"text": "15px"
},
"$:/themes/tiddlywiki/vanilla/metrics/bodylineheight": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/bodylineheight",
"text": "22px"
},
"$:/themes/tiddlywiki/vanilla/metrics/fontsize": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/fontsize",
"text": "14px"
},
"$:/themes/tiddlywiki/vanilla/metrics/lineheight": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/lineheight",
"text": "20px"
},
"$:/themes/tiddlywiki/vanilla/metrics/storyleft": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/storyleft",
"text": "0px"
},
"$:/themes/tiddlywiki/vanilla/metrics/storytop": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/storytop",
"text": "0px"
},
"$:/themes/tiddlywiki/vanilla/metrics/storyright": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/storyright",
"text": "770px"
},
"$:/themes/tiddlywiki/vanilla/metrics/storywidth": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/storywidth",
"text": "770px"
},
"$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/tiddlerwidth",
"text": "686px"
},
"$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint",
"text": "960px"
},
"$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth": {
"title": "$:/themes/tiddlywiki/vanilla/metrics/sidebarwidth",
"text": "350px"
},
"$:/themes/tiddlywiki/vanilla/options/stickytitles": {
"title": "$:/themes/tiddlywiki/vanilla/options/stickytitles",
"text": "no"
},
"$:/themes/tiddlywiki/vanilla/options/sidebarlayout": {
"title": "$:/themes/tiddlywiki/vanilla/options/sidebarlayout",
"text": "fixed-fluid"
},
"$:/themes/tiddlywiki/vanilla/options/codewrapping": {
"title": "$:/themes/tiddlywiki/vanilla/options/codewrapping",
"text": "pre-wrap"
},
"$:/themes/tiddlywiki/vanilla/reset": {
"title": "$:/themes/tiddlywiki/vanilla/reset",
"type": "text/plain",
"text": "/*! normalize.css v3.0.0 | MIT License | git.io/normalize */\n\n/**\n * 1. Set default font family to sans-serif.\n * 2. Prevent iOS text size adjust after orientation change, without disabling\n * user zoom.\n */\n\nhtml {\n font-family: sans-serif; /* 1 */\n -ms-text-size-adjust: 100%; /* 2 */\n -webkit-text-size-adjust: 100%; /* 2 */\n}\n\n/**\n * Remove default margin.\n */\n\nbody {\n margin: 0;\n}\n\n/* HTML5 display definitions\n ========================================================================== */\n\n/**\n * Correct `block` display not defined in IE 8/9.\n */\n\narticle,\naside,\ndetails,\nfigcaption,\nfigure,\nfooter,\nheader,\nhgroup,\nmain,\nnav,\nsection,\nsummary {\n display: block;\n}\n\n/**\n * 1. Correct `inline-block` display not defined in IE 8/9.\n * 2. Normalize vertical alignment of `progress` in Chrome, Firefox, and Opera.\n */\n\naudio,\ncanvas,\nprogress,\nvideo {\n display: inline-block; /* 1 */\n vertical-align: baseline; /* 2 */\n}\n\n/**\n * Prevent modern browsers from displaying `audio` without controls.\n * Remove excess height in iOS 5 devices.\n */\n\naudio:not([controls]) {\n display: none;\n height: 0;\n}\n\n/**\n * Address `[hidden]` styling not present in IE 8/9.\n * Hide the `template` element in IE, Safari, and Firefox < 22.\n */\n\n[hidden],\ntemplate {\n display: none;\n}\n\n/* Links\n ========================================================================== */\n\n/**\n * Remove the gray background color from active links in IE 10.\n */\n\na {\n background: transparent;\n}\n\n/**\n * Improve readability when focused and also mouse hovered in all browsers.\n */\n\na:active,\na:hover {\n outline: 0;\n}\n\n/* Text-level semantics\n ========================================================================== */\n\n/**\n * Address styling not present in IE 8/9, Safari 5, and Chrome.\n */\n\nabbr[title] {\n border-bottom: 1px dotted;\n}\n\n/**\n * Address style set to `bolder` in Firefox 4+, Safari 5, and Chrome.\n */\n\nb,\nstrong {\n font-weight: bold;\n}\n\n/**\n * Address styling not present in Safari 5 and Chrome.\n */\n\ndfn {\n font-style: italic;\n}\n\n/**\n * Address variable `h1` font-size and margin within `section` and `article`\n * contexts in Firefox 4+, Safari 5, and Chrome.\n */\n\nh1 {\n font-size: 2em;\n margin: 0.67em 0;\n}\n\n/**\n * Address styling not present in IE 8/9.\n */\n\nmark {\n background: #ff0;\n color: #000;\n}\n\n/**\n * Address inconsistent and variable font size in all browsers.\n */\n\nsmall {\n font-size: 80%;\n}\n\n/**\n * Prevent `sub` and `sup` affecting `line-height` in all browsers.\n */\n\nsub,\nsup {\n font-size: 75%;\n line-height: 0;\n position: relative;\n vertical-align: baseline;\n}\n\nsup {\n top: -0.5em;\n}\n\nsub {\n bottom: -0.25em;\n}\n\n/* Embedded content\n ========================================================================== */\n\n/**\n * Remove border when inside `a` element in IE 8/9.\n */\n\nimg {\n border: 0;\n}\n\n/**\n * Correct overflow displayed oddly in IE 9.\n */\n\nsvg:not(:root) {\n overflow: hidden;\n}\n\n/* Grouping content\n ========================================================================== */\n\n/**\n * Address margin not present in IE 8/9 and Safari 5.\n */\n\nfigure {\n margin: 1em 40px;\n}\n\n/**\n * Address differences between Firefox and other browsers.\n */\n\nhr {\n -moz-box-sizing: content-box;\n box-sizing: content-box;\n height: 0;\n}\n\n/**\n * Contain overflow in all browsers.\n */\n\npre {\n overflow: auto;\n}\n\n/**\n * Address odd `em`-unit font size rendering in all browsers.\n */\n\ncode,\nkbd,\npre,\nsamp {\n font-family: monospace, monospace;\n font-size: 1em;\n}\n\n/* Forms\n ========================================================================== */\n\n/**\n * Known limitation: by default, Chrome and Safari on OS X allow very limited\n * styling of `select`, unless a `border` property is set.\n */\n\n/**\n * 1. Correct color not being inherited.\n * Known issue: affects color of disabled elements.\n * 2. Correct font properties not being inherited.\n * 3. Address margins set differently in Firefox 4+, Safari 5, and Chrome.\n */\n\nbutton,\ninput,\noptgroup,\nselect,\ntextarea {\n color: inherit; /* 1 */\n font: inherit; /* 2 */\n margin: 0; /* 3 */\n}\n\n/**\n * Address `overflow` set to `hidden` in IE 8/9/10.\n */\n\nbutton {\n overflow: visible;\n}\n\n/**\n * Address inconsistent `text-transform` inheritance for `button` and `select`.\n * All other form control elements do not inherit `text-transform` values.\n * Correct `button` style inheritance in Firefox, IE 8+, and Opera\n * Correct `select` style inheritance in Firefox.\n */\n\nbutton,\nselect {\n text-transform: none;\n}\n\n/**\n * 1. Avoid the WebKit bug in Android 4.0.* where (2) destroys native `audio`\n * and `video` controls.\n * 2. Correct inability to style clickable `input` types in iOS.\n * 3. Improve usability and consistency of cursor style between image-type\n * `input` and others.\n */\n\nbutton,\nhtml input[type=\"button\"], /* 1 */\ninput[type=\"reset\"],\ninput[type=\"submit\"] {\n -webkit-appearance: button; /* 2 */\n cursor: pointer; /* 3 */\n}\n\n/**\n * Re-set default cursor for disabled elements.\n */\n\nbutton[disabled],\nhtml input[disabled] {\n cursor: default;\n}\n\n/**\n * Remove inner padding and border in Firefox 4+.\n */\n\nbutton::-moz-focus-inner,\ninput::-moz-focus-inner {\n border: 0;\n padding: 0;\n}\n\n/**\n * Address Firefox 4+ setting `line-height` on `input` using `!important` in\n * the UA stylesheet.\n */\n\ninput {\n line-height: normal;\n}\n\n/**\n * It's recommended that you don't attempt to style these elements.\n * Firefox's implementation doesn't respect box-sizing, padding, or width.\n *\n * 1. Address box sizing set to `content-box` in IE 8/9/10.\n * 2. Remove excess padding in IE 8/9/10.\n */\n\ninput[type=\"checkbox\"],\ninput[type=\"radio\"] {\n box-sizing: border-box; /* 1 */\n padding: 0; /* 2 */\n}\n\n/**\n * Fix the cursor style for Chrome's increment/decrement buttons. For certain\n * `font-size` values of the `input`, it causes the cursor style of the\n * decrement button to change from `default` to `text`.\n */\n\ninput[type=\"number\"]::-webkit-inner-spin-button,\ninput[type=\"number\"]::-webkit-outer-spin-button {\n height: auto;\n}\n\n/**\n * 1. Address `appearance` set to `searchfield` in Safari 5 and Chrome.\n * 2. Address `box-sizing` set to `border-box` in Safari 5 and Chrome\n * (include `-moz` to future-proof).\n */\n\ninput[type=\"search\"] {\n -webkit-appearance: textfield; /* 1 */\n -moz-box-sizing: content-box;\n -webkit-box-sizing: content-box; /* 2 */\n box-sizing: content-box;\n}\n\n/**\n * Remove inner padding and search cancel button in Safari and Chrome on OS X.\n * Safari (but not Chrome) clips the cancel button when the search input has\n * padding (and `textfield` appearance).\n */\n\ninput[type=\"search\"]::-webkit-search-cancel-button,\ninput[type=\"search\"]::-webkit-search-decoration {\n -webkit-appearance: none;\n}\n\n/**\n * Define consistent border, margin, and padding.\n */\n\nfieldset {\n border: 1px solid #c0c0c0;\n margin: 0 2px;\n padding: 0.35em 0.625em 0.75em;\n}\n\n/**\n * 1. Correct `color` not being inherited in IE 8/9.\n * 2. Remove padding so people aren't caught out if they zero out fieldsets.\n */\n\nlegend {\n border: 0; /* 1 */\n padding: 0; /* 2 */\n}\n\n/**\n * Remove default vertical scrollbar in IE 8/9.\n */\n\ntextarea {\n overflow: auto;\n}\n\n/**\n * Don't inherit the `font-weight` (applied by a rule above).\n * NOTE: the default cannot safely be changed in Chrome and Safari on OS X.\n */\n\noptgroup {\n font-weight: bold;\n}\n\n/* Tables\n ========================================================================== */\n\n/**\n * Remove most spacing between table cells.\n */\n\ntable {\n border-collapse: collapse;\n border-spacing: 0;\n}\n\ntd,\nth {\n padding: 0;\n}\n"
},
"$:/themes/tiddlywiki/vanilla/settings/fontfamily": {
"title": "$:/themes/tiddlywiki/vanilla/settings/fontfamily",
"text": "\"Helvetica Neue\", Helvetica, Arial, \"Lucida Grande\", \"DejaVu Sans\", sans-serif"
},
"$:/themes/tiddlywiki/vanilla/settings/codefontfamily": {
"title": "$:/themes/tiddlywiki/vanilla/settings/codefontfamily",
"text": "Monaco, Consolas, \"Lucida Console\", \"DejaVu Sans Mono\", monospace"
},
"$:/themes/tiddlywiki/vanilla/settings/backgroundimageattachment": {
"title": "$:/themes/tiddlywiki/vanilla/settings/backgroundimageattachment",
"text": "fixed"
},
"$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize": {
"title": "$:/themes/tiddlywiki/vanilla/settings/backgroundimagesize",
"text": "auto"
},
"$:/themes/tiddlywiki/vanilla/sticky": {
"title": "$:/themes/tiddlywiki/vanilla/sticky",
"text": "<$reveal state=\"$:/themes/tiddlywiki/vanilla/options/stickytitles\" type=\"match\" text=\"yes\">\n``\n.tc-tiddler-title {\n\tposition: -webkit-sticky;\n\tposition: -moz-sticky;\n\tposition: -o-sticky;\n\tposition: -ms-sticky;\n\tposition: sticky;\n\ttop: 0px;\n\tbackground: ``<<colour tiddler-background>>``;\n\tz-index: 500;\n}\n``\n</$reveal>\n"
}
}
}
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
See Hagan Baley website
Membrane properties.
Protein pores: transport polymers across membranes. Often they have to unfold and fold.
Stocastic sensing.
SIgle-molecule chemistry
Protein engineering, chemical synthesis, biophysical methods
alpha-Hemolysin protein pore.
How can a water souble protein assemble into a transmembrane pore?
3D droplet networks are tissue-like materials. aqueous droplets networks.
Synthetic biology Woolfosn Bromley 2011.
Nice diagram
Synthia
...completelly synthetic cells.
Protein components for nanodevices, Bayey, et al.
Droplets water in an oil form monolayer, but two of tese wil tend to come togehter and forma bilayer. There is a force that attracts them. Probably kinetically stable.
Lipid coated hydrogels as components...
The 7R "diode"
Folding dropplet networks using osmolarity, different salt concentrations in eac.
Soft robots. Light for sensing, power generation and patterning.. Bacteriorhodopsin:light-driven proton pump.
https://clara.io/
Autodesk Maya
Smartphone-powered 3D printer: http://www.olo3d.net/
Autodesk Project Escher
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
[[WHY DID THE WORLD TRADE CENTER COLLAPSE? SIMPLE ANALYSIS|http://sci-hub.cc/10.1142/s0219455401000366]]
[ext[Mechanics of Progressive Collapse: Learning from World Trade Center and Building Demolitions|http://sci-hub.cc/10.1061/(ASCE)0733-9399(2007)133:3(308)]] -- [[DISCUSSIONS AND CLOSURES|http://sci-hub.cc/10.1061/%28ASCE%290733-9399%282008%29134%3A10%28915%29?journalCode=jenmdt]]
[[Some claimed missunderstandings|http://sci-hub.cc/10.1260/2041-4196.4.2.117]]
https://en.wikipedia.org/wiki/Construction_of_the_World_Trade_Center
[ext[What Did and Did Not Cause Collapse of World Trade Center Twin Towers in New York?|http://heiwaco.tripod.com/blgb.pdf]]
9/11 truth movement paper, citing some of the above: [[paper|http://www.europhysicsnews.org/articles/epn/pdf/2016/04/epn2016-47-4.pdf]] (2016)
----------------
One of their main calculations, in page 4 in here: http://sci-hub.cc/10.1260/2041-4196.4.2.117 , which also appears in on of the basic miss-understandings pointed out in http://sci-hub.cc/10.1061/%28ASCE%290733-9399%282008%29134%3A10%28915%29?journalCode=jenmdt appears wrong to me. They assume the force of the buckling columns on the damaged story to be equal to the weight of the part of the building above. However, that would imply no net force, and constant velocity, which is against the very clear constant acceleration, they themselves report.
In the closure Bazant et all also point out several other places where Szuladzinski seems to lack not only understanding of structural mechanics, but of basic physics. This may not be surprising given that he isn't an engineer or physicist, but a "specialist in homeland security".
Again, the paper by the Architects and Engineers for 9/11 Truth mainly cites Szuladzinski et al.'s paper, and their conclusions are based on incorrect calculations.
Their comments on the pitfalls of the NIST report also seem unbased when you actually look at what's in the report.
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[[NIST report|http://ws680.nist.gov/publication/get_pdf.cfm?pub_id=861610]]
See [[draft paper|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/APrioriProbabilityComplexity.pdf]].
See [[MMathPhys oral presentation]]
Coding theorem connects probability and complexity
AIT differs fundamentally from Shannon information theory because the latter is fundamentally a theory about distributions, whereas the former is a theory about the information content of individual objects (see [[Descriptional complexity]]).
If one assumes that the probability of generating a binary input string of length l issimply $$2^l$$ (which is true for prefix codes, see Appendix A) then the most likely way to obtain output $$x$$ by random sampling of inputs is with the shortest program that generates it, a string of length $$K(x)$$.
__Direct application of these results__ fromAIT to many practical systems in science or engineering suf-fers from a number of well known __problems__:
* $$K(x)$$ is formally uncomputable (due to halting problem).
* Most results in AIT only hold asymptotically, up to $$O(1)$$.
* Many of the input-output maps in science and engineering are not UTMs.
The way these problems are tackled is described in the next sections.
''Coding theorem for computable functions''. We begin with a weaker form of the coding theorem, applicable to real world (computable) functions
$$P(x)\leq 2^{-K(x|f,n)+O(1)}$$
Eq. (2)
where $$K(x|f,n)$$ is the complexity of output $$x$$, given the map $$f$$ and the value $$n$$ which is
(see [[M. Li and P.M.B. Vitanyi. An introduction to Kolmogorov complexity and its applications. Springer-Verlag New York Inc, 2008.|file:///home/guillefix/Dropbox/NewForCosmos/%5BMing_Li,_Paul_Vitanyi%5D_An_introduction_to_Kolmogo(BookZZ.org).djvu]], and [ext[Lecture notes on descriptional complexity and randomness|http://www.cs.bu.edu/~gacs/papers/ait-notes.pdf]]).
[img[https://s14.postimg.org/lys5n35b5/Selection_596.png]]
We provide a derivation of equation (2) in Appendix B, using standard results from AIT such as: //The complexity of a whole set is often much less than the complexity of individual members of the set// (9). Informally , $$K(x|f, n)$$ can be viewed as the length of computer code required to specify $$x$$, given the function $$f$$ and value $$n$$ are already pre-programmed in to the computer. Note that equation (2) is just an upper bound. In contrast to the the full coding theorem of equation (1), there is no lower bound.
We mainly consider maps that comply witha few simple __restrictions__:
* # inputs $$\gg$$ # outputs.
* # outpus $$\gg 1$$, to avoid finite size effects.
* Descriptional complexity of the map $$f$$ itself doesn't grow with $$n$$. ,,Basically the map is represented by fixed rule-set for computing outputs from inputs, that is largely independently of n.,,
* Due to how the algorithmic complexity is approximated in practice, the map needs to be 'well-behaved' in the sense of not producing many outputs like the digit of $$\pi$$ which are algorithmically simple, but which have large entropy values and thus large values of $$\tilde{K}x)$$ (the computed approximation of $$K(x)$$). This is a pratical problem, that depends on the complexity measure we use. The "complexity estimator" they used is described in Appendix F.
If instead the map is allowed to contain arbitrary amounts of information, then the map could assign arbitrary probabilties to the outputs, and any coding theorem-like behaviour would be lost. We discuss this fixed complexity condition further in Appendix C.
as we show in Appendix E , it turns out that a reasonably broad range of complexities will follow under quite general conditions for fixed complexity maps.
They use the above conditions to argue that $$K(x|f, n) \approx K(x)$$.
''Approximately computing $$K(x)$$''. $$K(x)$$ although uncomputable has been approximated using standard compression algorithms. $$\tilde{K}(x)$$ is used to denote some real-world (computable) approximation to $$K(x)$$.
''Importance of $$O(1)$$ terms''. Experimental results on apply the coding theorem to short strings suggest that the $$O(1)$$ terms are not very important.
!!!__''Central //ansatz// and simplicity bias''__:
$$P(x)\lesssim 2^{-a\tilde{K}x)-b}$$
where the constants $$a>0$$, and $$b$$ depend on the mapping, but not on $$x$$.
We call this upper bound of the probability ''//simplicity bias//'': High probability outputs must be 'simple', complex outputs must have exponentially lower probabilities. In contrast to the full coding theorem, the lack of a lower bound means that simple outputs may also have low probabilities.
They off <b>estimates for $$a$$ and $$b$$</b> in appendix D. In Appendix B, they also argue that: <span style="color:aqua;">the upper bound of equation (3) should be tight for most inputs, but weak for many outputs.</span>
!!Examples of simplicity bias in maps
<mark>See them!</mark>
Discrete [[RNA]] sequence to structure mapping
Coarse-grained ordinary differential equation
Coarse-grained stochastic partial differential equation. Black Scholes equation
Polynomial curves
Random matrix -- bias but not simplicity bias
[[L-system]]s
[[Random walk|Brownian motion]] map
Logistic map (see [[Nonlinear maps]])
//Predicting which of two outputs has higher probability//
--------------
Connection to Chomsky hierarchy (see [[Formal language]]), [[Sloppy systems]]..
---------------
Appendix A: AIT
Appendix B: Upper and lower bound for computable maps
Upper bound: following derivation using Shannon-Fano code as in InfoTheory book.
Lower bound: <big><mark>Not sure. Ask!, or read!</mark></big> Page 12.
Also many outputs must have probability below their upper bounds.
Appendix C: Fixed complexity map
Appendix D: Making predictions for P(x) in computable maps
''Appendix E: Estimating the range of $$K(x|f,n)$$''.
Arguments based on bounding complexity given the description: //map// + //index of output//. This gives upper bounds to min and max complexities to be $$0$$, and $$\log_2{N_0}$$ (everything up to additive constant, $$O(1)$$).
For the max, we also need a lower bound, and this is given by the well known fact in AIT that if one has $$N_0$$ different strings, not all of them can have complexity lower than $$\log_2{N_0}$$, as there are not enough such descriptions. In fact, most of the strings need to have a complexity of $$\log_2{N_0}$$.
Appendix F: Approximations to $$K(x)$$.
Appendix G: Simplicity bias and system size
Appendix H: On the intuitive connection of probability and complexity
Appendix I: Simplicity bias in the logbinomial distribution
Appendix J: Predicting the number of outputs, $$N_0$$. By fitting $$\alpha$$ and estimating $$max(K)$$ from the known details of the system.
Appendix K: Further examples and figures
Continuous systems are sampled and discretized to create the output.
L-systems, Circadian rhythm
Cell cycle
Feed forward network. Sample networks, measure complexity of given network. by entropy of the distribution of outputs.
Logic gate
Appendix L: Histograms of complexity
''[[Abiogenesis|https://en.wikipedia.org/wiki/Abiogenesis]]'' or biopoiesis or OoL (''Origins of Life''), is the natural process of life arising from non-living matter, such as simple organic compounds. [[Self-organization]] is expected to play a major role, both in the origin of life and in its subsequent [[Evolution]].
[[A New Physics Theory of Life|http://www.scientificamerican.com/article/a-new-physics-theory-of-life/]]
Work of M. Eigen
See book by Prigogine, etc.
[[Artificial chemistry]]
* replicator-based "genetics-first" approach
* "metabolism-first" apprach
See references at the end of page 54 in [[here|http://fontana.med.harvard.edu/www/Documents/WF/Papers/arrival.pdf]]
[[On Nature’s Strategy for Assigning Genetic Code Multiplicity|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148174]]
[[Origin and evolution of the genetic code: the universal enigma|http://www.ncbi.nlm.nih.gov/pubmed/19117371]]
[[Self-Organisation and Evolution of Biological and Social Systems|https://books.google.co.uk/books?hl=en&lr=&id=E9DmJpm7xNsC&oi=fnd&pg=PA151&dq=genotype-phenotype&ots=2LW4Y82VRZ&sig=Xi5Yw84SkW8_vBdkGHd5VqJqTts#v=onepage&q=genotype-phenotype&f=false]]
[[‘RNA world’ inches closer to explaining origins of life|http://www.sciencemag.org/news/2016/05/rna-world-inches-closer-explaining-origins-life?utm_source=sciencemagazine&utm_medium=facebook-text&utm_campaign=rnaworld-4268]]
[[Kauffman talk|https://www.youtube.com/watch?v=EWo7-azGHic]]. Ideas: <b>As evolution progresses it creates new opportunities and richer context for evolution to find evolve further</b>. Function can be defined as that subset of causal effects that contribute to causing a particular goal. In biology that goal is survival. The appropriate language in evolution goes beyond cause and effect, and includes ''enabling''. Organisms are [[Kantian wholes|https://www.youtube.com/watch?v=EWo7-azGHic#t=12m44s]], where the parts exist for and by means of the whole. The rest of the ideas seem to basically say that biology and evolution is too complex to (fully) describe with mathematical laws. [[Maybe we can understand the adjacent possible, look at convergence evolution|https://www.youtube.com/watch?v=EWo7-azGHic#t=51m40s]]....
//Things often have relations//
[ext[wayback.archive-it.org/3671/20150528171650/https://www.extension.harvard.edu/open-learning-initiative/abstract-algebra]]
See Wiki and CosmosBrain, [[Algebraic structure]]
[[Group theory]]
http://math.stackexchange.com/questions/105285/the-most-common-theorems-taught-in-abstract-algebra
The [[Cognitive process]] by which a [[Concept]] is produced.
An [[Organic compound]] with two [[Oxygen]] atoms single bonded to a single [[Carbon]]
An ''Achlioptas process'' is a type of [[Explosive percolation]], also known as $$m$$-edge processes, that involve choosing $$m$$ candidate edges uniformly at random between any pair of nodes (compare with other [[Spanning cluster-avoiding process]])and applying a rule to select which one is actually chosen. These have been proven to be continuous in the thermodynamic limit, for a fixed $$m$$. They are generalizations of Erdos-Renyi [[Random graph]]s.
The first proposed type, were proposed (in [[Explosive Percolation in Random Networks|http://science.sciencemag.org/content/323/5920/1453]]) and thought to maybe show a discontinuous phase transition.
__Achlioptas processes phase transitions are continuous__
It has now been show that the [[Percolation phase transition]] for Achlioptas processes (and in fact a more general class of [[k-vertex rule percolation process]]) is continuous (in the thermodynamic limit), but very steep (see [[Explosive Percolation Transition is Actually Continuous|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.105.255701]] and [[Achlioptas process phase transitions are continuous|http://projecteuclid.org/euclid.aoap/1344614200]]). One can prove the continuity by looking at the asymptotic effect of removing a single link, as the total size goes to infinity. However, Oliver Riordan and Lutz Warnke proved it by proving, in essence, that the number of subcritical components that join together to form the emergent macroscopic-sized component is not sub-extensive in system size. In the words of Friedman and Landsberg, Achlioptas Processes do not lead to the build-up of a “powder keg" (which is a type of cluster configuration that does lead to discontinuous transitions).
However, the model can be generalized to one that shows genuinely discontinuous transitions (see [[Anomalous critical and supercritical phenomena in explosive percolation|http://www.nature.com/nphys/journal/v11/n7/full/nphys3378.html]]). One way to achieve discontinuity is actually to allow the number of edges in the rule, $$m$$ to scale up with $$N$$, the network size, in a certain way.
__$$2$$-edge Achli Achlioptas process__ is the simplest type: Start with N isolated nodes and add undirected, unweighted edges one at a time. This is done by choosing, at each step, two possible edges uniformly (and independently) at random from the set of $$N(N-1)/2$$ possible {edges between a pair of distinct nodes}. One adds only one of these edges, making a choice based on a systematic rule that affects the speed of development of a GCC.
$$m$$-edge rules are defined similarly.
!!__Selection rules__
__Product rule__. One choice that yields "explosive" percolation is to use the so-called "product rule", in which one always retains the edge that minimizes the product of the sizes of the two components that it merges (with an arbitrary choice when there is a tie).
__Sum rule__. The size of the new component
formed is minimized.
__Bohman–Frieze (BF) rule__. edge 1 is chosen if it joins two isolated vertices, and edge 2 otherwise.
A selection rule can be classified as a bounded-size or an unbounded-size rule. In a bounded-size selection rule, decisions depend only on the sizes of the components and, moreover, all sizes greater than some (rule-specific) constant $$K$$ are treated identically.
There are also the more general $$m$$-edge rules based on chosing $$m$$ edges at each step, and selecting one (or potentially more).
See more rules here: [[Explosive percolation: Unusual transitions of a simple model|https://arxiv.org/abs/1405.0388]]
[[ The Evolution of Random Graphs |http://www.jstor.org/stable/1999405?origin=crossref&seq=1#page_scan_tab_contents]] (product rule first suggested here).
[[Avoiding a giant component|http://onlinelibrary.wiley.com/doi/10.1002/rsa.1019/abstract;jsessionid=27435A3DA431DF30487AE510D226EB1E.f02t02]]. Bounded-size rules are able to switch the percolation threshold.
[[Birth control for giants|http://link.springer.com/article/10.1007%2Fs00493-007-2163-2]]. The percolation transition is strongly conjectured to be continuous for all bounded-size rules
[[Product rule wins a competitive game|https://www.scopus.com/record/display.uri?eid=2-s2.0-60349090497&origin=inward&txGid=0]]
[[Hamiltonicity thresholds in Achlioptas processes|http://onlinelibrary.wiley.com/doi/10.1002/rsa.20302/abstract]]
An ''acid''
[[Acid-base reaction]]
Rain that contains dissolved acidic gases such as nitrogen oxides and sulfur dioxide.
http://www.bbc.co.uk/education/guides/z6xbkqt/revision/2
http://www.bbc.co.uk/education/guides/z6xbkqt/revision/3
!!__$$pK_a$$ value__
[img[pka_equil.png]]
!!__$$pK_b$$ value__
A [[Chemical reaction]] between an [[Acid]] and a [[Base]].
In acid-base reactions, [[Hydron]]s are added to molecules or removed from them.
!!__Acids and bases__
[[pH]] measures the concentration of hydrogen ions.
[[Acids and bases - Chemistry - Khan Academy|https://www.khanacademy.org/science/chemistry/acids-and-bases-topic]]
https://www.wikiwand.com/en/Acid%E2%80%93base_reaction
http://www.bbc.co.uk/education/guides/znhcwmn/revision/4
!!![[Acid-base equilibria]]
!!![[Buffer solution]]
!!__Types of acid-base reactions__
[[Neutralization reaction]]
http://plasticity.szynalski.com/tone-generator.htm
[[Membrane potential]] that transmits as a [[Wave]] signal, mostly in [[Neuron]] [[Axon]]s
[img[https://dundeemedstudentnotes.files.wordpress.com/2012/04/picture22.jpg]]
* Muscle action potential
* [[Neuron action potential]]
A [[colloidal particle|Colloid]] that is an [[active system|Active system]].
Common types are catalytic colloids, that [[catalyze|Catalysis]] some [[reaction|Chemical reaction]], often due to its surface chemical properties or those of a coating. This is often done so that the particle is [[self-propelling|Self-propelled particle]].
See also:
* [[Phoretic mechanisms of self-propelled colloids]]
* [[Collective behaviour of active colloids]]
* [[Self-assembly of active colloids]]
* [[Boundary effects on the motion of active colloids]]
[[Individual and collective behavior of artificial swimmers: "Janus particles"|https://www.youtube.com/watch?v=vxW7_-ei8Bw]]
We have shown recently that adaptive behaviour can be prescribed by prior expectations about sensory inputs, which action tries to fulfill [6]. This is calledactive inference
See [[Free energy principle]], [[Inference]], [[Machine learning]], [[Reinforcement learning]]
Essentially, active inference replaces value-learning with perceptual learning that optimises empirical (acquired) priors in the agent’s internal model of its world. These priors specify the free energy associated with sensory signals and guide action to ensure sensations conform to prior beliefs.
''Active matter'' refers to a type of [[bulk matter|Bulk matter]], often [[soft condensed matter|Soft matter physics]] that is an [[Active system]], i.e. that it produces its own driving energy (for example, [[self-propelling particles|Self-propelled particle]], and micro-swimmers).
[[Driven matter]] is a closely related type of matter, where the system is externally driven.
[[The Hydrodynamics of Active Systems|https://arxiv.org/abs/1603.00194]]
[[Life at low Reynold's numbers|https://www.ethz.ch/content/dam/ethz/special-interest/mavt/robotics-n-intelligent-systems/multiscaleroboticlab-dam/documents/microrobotics/HS2015/Purcell1977.pdf]], see [[Low Reynolds number]]
[[topics on active and soft matter physics assignment|topics-soft-active (1).pdf]]
See also [[Complex fluid dynamics]], [[Colloid physics]]
!!<span style="color:Gold">__Single swimmer hydrodynamics: background__</span>
Swimming at low Reynolds number: ''Stokes equation''
Important consequence for swimmers: ''Scallop theorem'' (see [[Kinematic reversibility in fluid dynamics]])
__Swimmer models__
* Squirmer. ,,[[Swimming efficiency of spherical squirmers: Beyond the Lighthill theory|http://journals.aps.org/pre/pdf/10.1103/PhysRevE.90.012704]],,
!!!__''Far-flow fields''__
,,Used to calculate __hydrodynamic interactions__, for instance,,
Point-force problem for Stokes equation, can be solved using its Green function, often called the ''Oseen tensor'' (see [[here|http://arxiv.org/pdf/1312.6231v1.pdf]]):
<big>$$G_{ij}(\vec{r}) = \frac{1}{8\pi \mu} \left(\frac{\delta_{ij}}{|\vec{r}|}+\frac{r_i r_j}{|\vec{r}|^3}\right)$$</big>
,,where the $$\frac{1}{8\pi \mu}$$ is often omitted in the definition of the Oseen tensor.,,
Using the Green function to construct general solution, one can construct a ''multipole expansion''. As swimmers (in average, in steady state) don't accelerate, the fluid isn't exerting a net force on them, so they can't be exerting a net force on the fluid ([[Netwon's third law]]). Therefore the monopole term (called the ''Stokelet'') isn't present. ,,An exception for this is the relatively large microorganism //Volvox//, for which gravity force is significant, giving a net force to the problem and creating a Stokelet flow,,. Therefore, the dominant term is generally the ''dipolar'' term:
$$v_i (\vec{r}) \approx \frac{\partial G_{ij}}{\partial x_k} (\vec{r}) D_{jk}$$
where $$v_i (\vec{r})$$ is the velocity field, and
$$D_{jk} = - \int f_j \xi_k d\vec{\xi}$$
It is conventional to let:
$$D_{jk} \rightarrow D_{jk} -\frac{1}{3}D_{ii} \delta_{jk} \equiv S_{jk} + T_{jk}$$
where the addition of $$\frac{1}{3}D_{ii}$$ doesn't change the velocity field $$v_i (\vec{r})$$ because $$\vec{\nabla} \cdot \mathbf{G} = \vec{0}$$. $$S_{jk}$$ is called the ''stresslet'', and $$T_{jk}$$ is called the ''rotlet''. The rotlet is zero if the net torque on the fluid is zero, which it is for active microswimmers.
Note that the dipolar flow has __nematic symmetry__; this is important in the collective behavior of active swimmers.
We can have two __kinds of dipolar flow__ around a swimmer:
* ''pusher'', or ''extensive'' <span style="color:Dodgerblue"><i class="fa fa-long-arrow-left" aria-hidden="true"></i> <i class="fa fa-long-arrow-right" aria-hidden="true"></i></span>. Like that of the //E. Coli//
* ''puller'', or ''contractile'' <span style="color:Dodgerblue"><i class="fa fa-long-arrow-right" aria-hidden="true"></i> <i class="fa fa-long-arrow-left" aria-hidden="true"></i></span>Like that of the //[[Chlamydomonas|https://en.wikipedia.org/wiki/Chlamydomonas]]//. See figure of //chlamydomonas flow//
[img[http://soft-matter.seas.harvard.edu/images/thumb/6/6a/Drescher4.jpg/900px-Drescher4.jpg]]
//chlamydomonas flow// [[source|http://soft-matter.seas.harvard.edu/index.php/Direct_Measurement_of_the_Flow_Field_around_Swimming_Microorganisms]]
!!<span style="color:Gold">__[[Single microswimmer hydrodynamics: applications]]__</span>
* bacteria <span style="color:LightSalmon">enhance diffusion</span> as a result of the flow fields they produce
* motion of swimmers in background/external flow.
* interactions with surfaces.
!!<span style="color:Gold">__[[Collective hydrodynamics of active entities]]__</span>
* ''Beris-Edwards equations''
* extra stress from active particles, equals the average value of the stresslet, and gives the ''active stress'' $$-\zeta Q_{jk}$$
* Different kinds of instabilities and patterns arise.
!!<span style="color:Gold">__[[Collective hydrodynamics of active entities: applications]]__</span>
* ''active turbulence''
* interactions between topological defects, walls (regions of high bend perturbation), and flows (jets, and vortical).
* ''Lyotropic active nematics'' and ''active anchoring''
* Example system: microtubules and [[Molecular motors]].
!!<span style="color:Gold">__Other applications__</span>
* More general ''[[Active system]]s'' and types of active matter: [[dry systems|Dry active matter]], systems with polar symmetry, density variations, inertia.
* ''Active machines'' and [[Self-assembly]]
* Microswimmers moving in a viscoelastic medium. Living liquid crystals represent a novel system where bacteria swim in a nematic liquid.
* Biological systems (see [[Biological matter]]):
**molecular motors walking along microtubules contribute to cell division resulting from spindle mitosis.
**cytoplasmic streaming, flow driven by the motion of motors along the cell walls, presumably to aid the transport of nutrients around the cell.
** The extent to which hydrodynamics (even at nanometre scales) affects motor motion [74], the way in which multiple motors can combine to move cargo and mechanisms for cargo transport in the crowded cellular environment remain largely unexplored.
** there is increasing evidence that cell motility is linked to the physical environment. Interactions between cells, the spreading of cellular layers and the possible role of flow in [[Morphogenesis]] are also of interest.
* [[Active gel physics|http://www.nature.com/nphys/journal/v11/n2/abs/nphys3224.html]]
[[Physics of Microswimmers – Single Particle Motion and Collective Behavior|http://arxiv.org/pdf/1412.2692v1.pdf]]
[[In pursuit of propulsion at the nanoscale|http://pubs.rsc.org/en/content/articlelanding/2010/sm/b918598d#!divAbstract]]
[[Biphasic, Lyotropic, Active Nematics|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.113.248303]]
[[Papers on active matter]]
!!__Self organization in active matter__
__Cytoplasmic streaming__
[[A physical perspective on cytoplasmic streaming|http://rsfs.royalsocietypublishing.org/content/5/4/20150030]]
[[Cytoplasmic streaming in plant cells emerges naturally by microfilament self-organization|http://www.pnas.org/content/110/35/14132.full#xref-ref-35-1]]
[[Spontaneous Circulation of Confined Active Suspensions|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.109.168105]]
[[Instabilities, pattern formation, and mixing in active suspensions|http://scitation.aip.org/content/aip/journal/pof2/20/12/10.1063/1.3041776]]
__[[Spindle self-organization]]__
[[Physical basis of spindle self-organization|http://www.pnas.org/content/111/52/18496.short]]
A system with constituents that are able to [[produce their own energy|Energy production]]. For instance, they are often ''self-propelling''. See also the [[wiki article|https://en.wikipedia.org/wiki/Active_matter]]. Due to the energy consumption, these systems are intrinsically [[out of thermal equilibrium|Non-equilibrium statistical physics]].
If the system is made of [[bulk matter|Bulk matter]], it's called [[Active matter]].
Examples of active systems are schools of fish, flocks of birds, bacteria, artificial self-propelled particles, and self-organising bio-polymers such as microtubules and actin, both of which are part of the cytoskeleton of living cells.
Dry active systems
---------
A prominent example of active system are [[Active colloid]]s
[[Biophysics]] (biological systems are active systems).
[[Flocks, herds, and schools: A quantitative theory of flocking|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.58.4828]]. See [[Complex systems]]
DNA nanomachines in [[DNA nanotechnology]]
[[Self-assembled artificial cilia|http://www.pnas.org/content/107/5/1844]]
[[Microscopic artificial swimmers|http://www.nature.com/nature/journal/v437/n7060/full/nature04090.html]]
See [[Dynamical Instability in Boolean Networks as a percolation Problem]], [[Boolean network]]
New paper: [[Network Structure and Activity in Boolean Networks|http://link.springer.com/chapter/10.1007%2F978-3-662-47221-7_16]]
[[Activities and Sensitivities in Boolean Network Models|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.93.048701]]
Boolean functions in which few variables have high importance and most other variables have low importance play a role in eliciting order from Boolean networks.
We should mention in passing that much of the discussion in this Letter can be formulated in terms of spectral methods or harmonic analysis on the $$n$$ cube.
__Boolean function derivative__
[img[http://i.imgur.com/2z9wHHU.png]]
__Activity__
[img[http://i.imgur.com/6lkjX2c.png]]
__Sensitivity__
[img[http://i.imgur.com/3UWrawk.png]]
[img[http://i.imgur.com/CPR0PI8.png]]
For a random Boolean function with bias $$p$$ (so that each bit in the truth table is $$1$$ with probability $$p$$ and $$0$$ otherwise), the probability that two Hamming neighbors are different is equal to $$2p(1-p)$$, since one can be $$1$$ (with probability $$p$$) and the other 0 (with probability $$1-p$$), and vice versa.
From this one can see that $$E[\alpha_i^f] = 2p(1-p)$$, and $$E[s^f] = K2p(1-p)$$, where $$E$$ means expectation value w.r.t. the prob. distribution of the truth tables. We can then conclude that highly biased functions ($$p$$ far away from 0.5) are expected to have low average sensitivity.
For a Boolean function $$f$$, a canalizing variable is a variable that determines (canalizes) the value of $$f$$ if it has a given value. See the article for more precise definition. A random Boolean function with a single canalizing variable, it is shown [[here|http://journals.aps.org/prl/supplemental/10.1103/PhysRevLett.93.048701/influencesupplementarymaterial.pdf]] that the expected activity of the canalizing variable is $$1/2$$, while that of the rest of the variables is $$1/4$$
The average sensitivity (when averaged over all the functions in the network) appears to be a good parameter for predicting whether the dynamics of the Boolean network are ordered or chaotic. This can be observed by looking at Derrida curves.
A [[Process]] carried out by a sentient being.
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
They can always be drawn with the vertices arranged so that all edges point downward as in Fig 1. Also all cycles that can be arranged like this are acyclic.
[img[Acyclic Network Figure]] Fig 1.
From the proof of this fact one can deduce an algorithm for finding if a network is acyclic or not:
[img[network2.PNG]]
Furthermore, the //adjacency matrix// of such a graph can always be made upper-diagonal with zeros on diagonal (as no self-loops). The eigenvalues of an acyclic graph are thus all zero. One can also show the opposite, thus:
|!A network is acyclic //if and only if// it has a nilpotent adjacency matrix|
A [[Chemical reaction]] in which one molecule combines with another to form a larger molecule with no other products.
See chemtube3d, and wiki for mechanisms
!!__Types__
* [[Electrophilic addition]]
* [[Nucleophilic addition]]
http://www.xjet3d.com/technology.html
[[Liquid-phase sintering]]
[[Adhesives|https://en.wikipedia.org/wiki/Adhesive]] is any substance applied to one surface, or both surfaces, of two separate items that binds them together and resists their separation.
Some synonyms: glue, cement, mucilage, or paste
A [[Matrix]] that defines a [[Graph]] or a [[Network]]. $$A$$
$$A_{ij} = 1 \text{ if edge (j,i) exists}$$.
$$A_{ij} = 0 \text{ if edge (j,i) doesn't exist}$$
$$A^T=A$$ if undirected.
$$A$$ describes same network if we permute columns and rows in the same
way.
''Weighted adjacency matrix'' (or weight matrix) $$W$$ assigns a weight
to edges. Usually weight is a real number: $$w: E \rightarrow
\mathbb{R}$$
"Topology" represented by $$A$$.
"Geometry represented by $$W$$.
Related: [[Graph laplacian]]
https://en.wikipedia.org/wiki/AdS/CFT_correspondence
[[Aerosol|https://en.wikipedia.org/wiki/Aerosol]] is a [[Colloid]] of fine solid particles or liquid droplets, in air or another gas.
//What is beauty?//
pleasing to the senses? emotions?
https://en.wikipedia.org/wiki/Agarose_gel_electrophoresis
[[Sens Foundation|http://www.sens.org/]]
[[Biogerontology Research Foundation|http://www.bg-rf.org.uk/]]
[[Rejuvenation Research Journal|http://www.liebertpub.com/REJ]]
[[Why Do We Age? The Molecular Mechanisms of Ageing |https://www.futurelearn.com/courses/ageing]]
__The 9 hallmarks of ageing__
[[The Hallmarks of Aging.pdf]]
[img width=500 class=img-centered [9 hallmarks of aging.jpg]]
[img width=300 [the_imortalist.jpg]]
[[Causes of death|http://flowingdata.com/2016/01/05/causes-of-death/]]
[[Great Desire for Extended Life and Health amongst the American Public|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4718974/]]
[[Aging: where physics meets biology|http://nautil.us/issue/36/aging/physics-makes-aging-inevitable-not-biology]] (see comments). Further commentary [[here|http://nautil.us/blog/physics-makes-aging-inevitablea-response-to-comments]] (see my comment there too). See [[here|http://blogs.wayne.edu/phoffmann/2016/05/13/physics-aging-and-immortality/]] and [[The thermodynamics of life|http://blogs.wayne.edu/phoffmann/2014/06/29/the-thermodynamics-of-life/]]
Agriculture is the cultivation of animals, plants, fungi, and other life forms for food, fiber, biofuel, medicinal and other products used to sustain and enhance human life (https://en.wikipedia.org/wiki/Agriculture)
[[Agronomy|https://en.wikipedia.org/wiki/Agronomy]]: agriculture of plants
[[Agriculture & Agronomy|http://www.springer.com/gp/life-sciences/agriculture-agronomy]]
[[Google DeepMind pairs with NHS to use machine learning to fight blindness|https://www.theguardian.com/technology/2016/jul/05/google-deepmind-nhs-machine-learning-blindness]]
[[Artificial Intelligence Could Help Catch Alzheimer's Early|http://www.livescience.com/55313-artificial-intelligence-alzheimers-early-detection.html]]
http://insilicomedicine.com/
https://www.wikiwand.com/en/Alex_Zhavoronkov
----------------
http://www.kheironmed.com/
Mamography ROI. CNN. Can't use all of the mamography data.
[[Oncology]] CT. 3D seg
Peter. Tobias. PhD, high performance computing for genetics. Chris. Combining data. Half-labelled data set. Semi-supervised learning.
[[Artificial intelligence]]
[[OpenAI - Concrete AI safety problems|https://openai.com/blog/concrete-ai-safety-problems/]] [[paper|https://arxiv.org/abs/1606.06565]]
The [[Mixture]] of [[Gas]]es, which composes the [[Earth atmosphere]]
An [[Organic compound]], often a [[Hydrocarbon]], with a [[Hydroxyl]] group.
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/d/d4/Alcohol_general.svg/320px-Alcohol_general.svg.png?1473060561502]]
http://www.bbc.co.uk/education/guides/zyf82hv/revision
An alcohol can be oxidized to produce a [[Carboxylic acid]]
//aka alkanal//
An [[Organic compound]] containing a functional group with the structure −CHO
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Aldehyd_-_Aldehyde.svg/320px-Aldehyd_-_Aldehyde.svg.png?1473061621341]]
An ''algebra'' is a family $$R$$ of subsets of a set $$X$$ s.t.:
* $$\emptyset \in R$$
* Closed under finite unions. $$A,B \in R \Rightarrow A \cup B \in R$$
* Closed under complements. $$A \in R \Rightarrow X \setminus A \in R$$
If the algebra is closed under countable unions (not just finite), then it is a [[Sigma-algebra]]
[[video|https://www.youtube.com/watch?v=WKdy_OxdUbk#t=17m20s]]
[[Algebra (algebraic structure)]]
In mathematics, and more specifically in abstract algebra, an algebraic structure is a set (called carrier set or underlying set) with one or more finitary operations defined on it that satisfies a list of axioms.
https://en.wikipedia.org/wiki/Algebraic_structure
[[Group-like algebraic structures]]
[[Ring-like algebraic structures]]
[[Lattice-like algebraic structures]]
[[Module-like algebraic structures]]
[[Algebra-like algebraic structures]]
!!!https://en.wikipedia.org/wiki/List_of_cohomology_theories
[[K-theory]]
https://en.wikipedia.org/wiki/Floer_homology
!!Algorithm to compute [[LZ complexity measure]]
written in [[Python|Python (programming language)]]
```
def KC_LZ(string):
n=len(string)
s = '0'+string
c=1
l=1
i=0
k=1
k_max=1
stop=0
while stop==0:
if s[i+k] != s[l+k]:
if k>k_max:
k_max=k # k_max stores the length of the longest pattern in the LA that has been matched somewhere in the SB
i=i+1 # we increase i while the bit doesn't match, looking for a previous occurence of a pattern. s[i+k] is scanning the "search buffer" (SB)
if i==l: # we stop looking when i catches up with the first bit of the "look-ahead" (LA) part.
c=c+1 # If we were actually compressing, we would add the new token here. here we just count recounstruction STEPs
l=l+k_max # we move the beginning of the LA to the end of the newly matched pattern.
if l+1>n: # if the LA surpasses length of string, then we stop.
stop=1
else: #after STEP,
i=0 # we reset the searching index to beginning of SB (beginning of string)
k=1 # we reset pattern matching index. Note that we are actually matching against the first bit of the string, because we added an extra 0 above, so i+k is the first bit of the string.
k_max=1 # and we reset max lenght of matched pattern to k.
else:
k=1 #we've finished matching a pattern in the SB, and we reset the matched pattern length counter.
else: # I increase k as long as the pattern matches, i.e. as long as s[l+k] bit string can be reconstructed by s[i+k] bit string. Note that the matched pattern can "run over" l because the pattern starts copying itself (see LZ 76 paper). This is just what happens when you apply the cloning tool on photoshop to a region where you've already cloned...
k=k+1
if l+k>n: # if we reach the end of the string while matching, we need to add that to the tokens, and stop.
c=c+1
stop=1
# a la Lempel and Ziv (IEEE trans inf theory it-22, 75 (1976),
# h(n)=c(n)/b(n) where c(n) is the kolmogorov complexity
# and h(n) is a normalised measure of complexity.
complexity=c;
#b=n*1.0/np.log2(n)
#complexity=c/b;
```
See [[Descriptional complexity]] and [[MMathPhys oral presentation]]. See also [[Information theory]], [[Theory of computation]], [[Complexity theory]], and [[Computational complexity]]
<mark>Good lecture notes for AIT</mark>: http://www.cse.iitk.ac.in/users/satyadev/a10/a10.html
!!__[[Kolmogorov complexity]]__
''[[Plain Kolmogorov Complexity|http://www.cse.iitk.ac.in/users/satyadev/a10/kolm_2.pdf]]''
See //Elements of information theory// by Cover and Thomas (chap 14)
[img width=500 class=img-centered [Kolmogorov_complexity_definition.png]]
__Conditional Kolmogorov complexity__
[img[conditional_kolmogorov.png]]
$$<x, y>$$ is the pairing function (see [[Computability theory]]). The conditional Kolmogorov complexity is often defined as in Def. 2.0.1, but with $$y$$ is $$l(x)$$, the length of $$x$$.
__''Universality of Kolmogorov complexity''__
,,aka Invariance theorem,,
[img class=img-centered [kolmogorov_universality.png]]
<b>For sufficiently long x</b>, the length of this
simulation program can be neglected, and we can discuss Kolmogorov
complexity without talking about the constants.
<small>Note in the book on info theory, they use the [[ceiling function|https://en.wikipedia.org/wiki/Floor_and_ceiling_functions]] for the {number of bits in a binary representation of a number}; however, as mentioned [[here|http://www.exploringbinary.com/number-of-bits-in-a-decimal-integer/]] that fails for multiples of $$2$$, so we need to use $$\lfloor log(n) \rfloor +1$$</small>
!!!''Bounds''
__Upper bound on Kolmogorov complexity__
[img[Selection_162.png]]
where $$log^*(x) = \log(x) + \log(\log(x)) + \log(\log(\log(x))) + ...$$
__Lower bounds on Kolmogorov complexity__
::<big><big><i class="fa fa-lightbulb-o" aria-hidden="true"></i></big> There are very few sequences with low complexity</big>
[img width = 500 [Selection_163.png]]
[img[Selection_164.png]]
!!__Relations to entropy__
__Kraft inequality__
[img[Selection_165.png]]
__Relation to entropy__
[img[Selection_166.png]]
as $$n \rightarrow \infty$$. See proof in the book (uses Kraft's inequality, Jensen's inequality, and the concavity of the entropy) Therefore the average Kolmogorov complexity of the string approaches the entropy of the random variable from which the letters of the string are sampled. The compressibility achieved by the computer goes to the entropy limit.
__Theorem__ 14.4.3 //There are an infinite number of integers $$n$$ such that $$K(n) > \log{n}$$//.
!!__Algorithmic randomness and incompressible sequences__
__Theorem__ 14.5.1 //Let $$X_1, X_2, ..., X_n$$ be drawn according to a Bernoulli $$(\frac{1}{2})$$ process. Then//
$$P(K(X_1 X_2 ... X_n | n) < n-k) < 2^{-k}$$
For example, the fraction of sequences of length n that have complexity less than n − 5 is less than 1/32. This motivates the following definition.
__Definitions__ of ''algorithmic randomness'', ''incompressibility''.
//Strong law of large numbers for incompressible sequences//
[img[Selection_167.png]]
In general, we
can show that if a sequence is incompressible, it will satisfy all computable
statistical tests for randomness. (Otherwise, identification of the test that x
fails will reduce the descriptive complexity of x, yielding a contradiction.)
''In this sense, the algorithmic test for randomness is the ultimate test,
including within it all other computable tests for randomness.''
We now remove the //expectation// from Theorem 14.3.1
[img[Selection_168.png]]
!!__''[[Universal probability]]''__
Probability distribution of outputs of a [[Turing machine]], when fed random inputs. Apparently, the distribution is rather robust to the probability distribution of inputs, thus it being called "universal"
!!__The //halting problem// <i class="fa fa-long-arrow-right" aria-hidden="true"></i> noncomputability of Kolmogorov complexity__
//Epimenides liar pradox// <i class="fa fa-long-arrow-right" aria-hidden="true"></i> Godels incompleteness theorem <i class="fa fa-long-arrow-right" aria-hidden="true"></i> Halting problem
Related: //Berry's paradox// and //Bechenbach's paradox//
!!__Chaitin's $$\Omega$$__
__Definition__
[img[Selection_172.png]]
__Properties__:
1. $$\Omega$$ //is noncomputable//
2. $$\Omega$$ //is a "philosopher's stone"//, or an oracle. Knowledge of $$\Omega$$ to $$n$$ bits can be used to prove any theorem for which {a proof expressible in less than $$n$$ bits exists}.
3. $$\Omega$$ //is algorithmically random//.
__Theorem__ 14.8.1. $$\Omega$$ //cannot be compressed by more than a constant; that is, there exits a constant $$c$$ such that//
$$K(\omega_1\omega_2...\omega_n) \geq n-c$$ //for all $$n$$//
!!__Universal gambling__
the universal gambling scheme on a
random sequence does asymptotically as well as a scheme that uses prior
knowledge of the true distribution!
!!![[Universal prediction|http://cbio.ensmp.fr/~jvert/svn/bibli/local/Merhav1998Universal.pdf]]
!!__Occam's razor__
......
!!__''Coding theorem''__
[img[Coding_theorem.png]]
Proof involves an extension of the {//tree construction// used for ''Shannon-Fano-Elias code''s for computable probability distributions} to the uncomputable universal probability distributions.
As stated in the proof in the InfoTheory book, "However, there is no effective procedure to find the lowest depth node corresponding to x". This means that the coding they use in the proof is incomputable. However, they show it exist, and that it can be decoded in finite time, giving a description of the string.
---------------
See also [[Sequence space]]s
---------
http://www.scholarpedia.org/article/Algorithmic_information_theory
<mark>[ext[The discovery of algorithmic probability|http://world.std.com/~rjs/barc97.pdf]]</mark> Seems like vary nice read. [[Solomonoff's theory of inductive inference|https://en.wikipedia.org/wiki/Solomonoff's_theory_of_inductive_inference]]
[ext[An Introduction to Kolmogorov Complexity and Its Applications (1 cr)|http://users.ics.aalto.fi/pkaski/kca/]]
[ext[Algorithmic Learning Theory (ALT) 2016|http://www.comp.nus.edu.sg/~fstephan/alt/alt2016/id.html]]
[[Expanded and improved proof of the relationbetween description complexity and algorithmicprobability|http://www.cs.bu.edu/faculty/gacs/papers/day.pdf]]
[ext[http://www-igm.univ-mlv.fr/~berstel/Articles/2010HandbookCodes.pdf]]
[ext[ALGORITHMS OF INFORMATICS|http://compalg.inf.elte.hu/~tony/Oktatas/AlgofInf-Vol1-HTML/Volume1.html]]
[[Grammar Compression, LZ-Encodings, and String Algorithms with Implicit Input|http://link.springer.com/chapter/10.1007%2F978-3-540-27836-8_5]]
See [[Algorithms]], [[Data compression]]
Also called //imperative knowledge// in [[Computer science]]
[[Analysis of algorithms]]
https://www.youtube.com/watch?v=gwlevtaC-u0&list=PL6ED884C7AEE68027
[[Discrete algorithms conference papers|http://www.wisdom.weizmann.ac.il/~robi/SODA16-AcceptedListAbstracts.html]]
[[http://www2.idsia.ch/cms/fun16/
FUN with biological algorithms FUN with combinatorial algorithms
FUN with cryptographic algorithms FUN with distributed algorithms
FUN with game-theoretic algorithms FUN with geometrical algorithms
FUN with graph algorithms FUN with mobile algorithms
FUN with Internet algorithms FUN with parallel algorithms
FUN with optimization algorithms FUN with randomized algorithms
FUN with robotics algorithms FUN with space-conscious algorithms
FUN with string algorithms FUN with visualization of algorithms
[[ALGORITHMS OF INFORMATICS|http://compalg.inf.elte.hu/~tony/Oktatas/AlgofInf-Vol1-HTML/Volume1.html]]
!!![[Algorithm visualizer|http://jasonpark.me/AlgorithmVisualizer/]]
https://www.youtube.com/channel/UCC_RpWFSbwHib_LLhHJwB3w/videos?shelf_id=0&view=0&sort=dd
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/
[[Algorithmics on compressed objects]]
An [[Organic compound]] that is not an [[Aromatic compound]], i.e. it doesn't contain an aromatic ring.
A [[Base]] that disoves in [[Water]]
The Group 1 elements in the periodic table are known as the ''alkali metals''. They include lithium, sodium and potassium, which all react vigorously with water to produce an alkaline solution (a [[basic|Base]] solution)
http://www.bbc.co.uk/education/guides/zvydmp3/revision
They must be stored under oil to keep air and water away from them.
!!!__Reactions of alkali metals with water__
All the alkali metals react vigorously with cold water. In each reaction, hydrogen gas is given off and the metal hydroxide is produced. The speed and violence of the reaction increases as you go down the group, as the atoms attract the electron less strongly, so less potential energy needs to be spent, and more is available for kinetic energy
More details: http://www.chemguide.co.uk/inorganic/group1/reacth2o.html
http://www.bbc.co.uk/education/guides/zvydmp3/revision/2
Group 2 elements in the [[Periodic table]], and are [[Metal]]s
The alkaline earth metals are named after their oxides, the alkaline earths. These oxides are basic ([[Alkaline]]) when combined with water.
http://www.chemguide.co.uk/inorganic/group2/reacth2o.html
An alkane, is an acyclic saturated hydrocarbon. In other words, an alkane consists of hydrogen and carbon atoms arranged in a tree structure in which all the carbon-carbon bonds are single.
http://www.bbc.co.uk/education/guides/zvvwxnb/revision/2
See also [[Alkene]]s
!!__Reactions__
[[Combustion]]
Alkanes undergo a [[Substitution reaction]] with halogens in the presence of light. See [[here|http://www.bbc.co.uk/education/guides/zvvwxnb/revision/3]]
An alkene is an unsaturated hydrocarbon that contains at least one carbon–carbon double bond.
http://www.bbc.co.uk/education/guides/zvvwxnb/revision/4
!!__Reactions__
[[Combustion]]
The reaction between bromine and alkenes is an example of a type of reaction called an [[Addition reaction]]. See [[here|http://www.bbc.co.uk/education/guides/zvvwxnb/revision/5]].
Hydrogenation (adding [[Hydrogen]]), to saturate it into an [[Alkane]].
Adding [[Water]], gives an [[Alcohol]]
A [[Functional group]] that is an [[Alkyl]] (carbon and hydrogen chain) group singular bonded to oxygen
A [[Functional group]] derived by removing a [[Hydrogen]] from an [[Alkane]]
An [[Organic compound]] that is a [[Halide]] with an [[Alkyl]] group
A [[Hydrocarbon]] that contains at least one triple Carbon-Carbon bond.
An ''allele'' is [[a version/type of a gene|https://www.youtube.com/watch?v=H6gwYdyn7II#t=1m]], coding for a specific protein.
A type of [[Enzyme inhibition]] that appears in [[Metabolic network]]s. [[Video|https://www.youtube.com/watch?v=Lt5SiDZsBig#t=3m04s]] A molecule binds to an [[Enzyme]] and produces a conformational change (changes shape), so that it regulates the rate of a reaction in the metabolic network.
!!!__Mechanisms__
* Feedback inhibition
* Feedforward activation
An alloy is a mixture of two or more elements, where at least one element is a metal. Most alloys are mixtures of two or more metals.
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/6
[[Steel]]
A famous example of [[Deep reinforcement learning]]
[[Mastering the game of Go with deep neural networks and tree search|http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html]]
[[Two+ Minute Papers - How DeepMind's AlphaGo Defeated Lee Sedol|https://www.youtube.com/watch?v=a-ovvd_ZrmA]]
https://www.reddit.com/r/baduk/comments/49y17z/the_true_strength_of_alphago/
Aluminium is the most abundant [[Metal]] on Earth. But it is expensive, largely because of the amount of electricity used in the extraction process.
!!__[[Aluminium extraction]]__
!!__Uses__
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/5
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/6
Aluminium ore is called bauxite. The bauxite is purified to yield a white powder - aluminium oxide - from which aluminium can be extracted.
The extraction is done by [[Electrolysis]].
[img[http://a.files.bbci.co.uk/bam/live/content/z2vw6sg/large]]
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/3
https://en.wikipedia.org/wiki/Alzheimer%27s_disease
[[Alzheimer's and the Brain|https://www.youtube.com/watch?v=dWcdBOYy_bU]] [[Relations with chromosome 21|https://www.youtube.com/watch?v=dWcdBOYy_bU#t=9m40s]]. Alzheimer's disease seems to be related to the accumulation of plaques in the brain, and with tangles.
[[Artificial Intelligence Could Help Catch Alzheimer's Early|http://www.livescience.com/55313-artificial-intelligence-alzheimers-early-detection.html]]
[[Alzheimer's is a chronic disease|https://www.youtube.com/watch?v=l6jafQERb7E#t=11m20]]
---------------
[[Molecular Mechanisms of Memory Loss in Alzheimer's Disease|https://www.youtube.com/watch?v=l6jafQERb7E]]
__Common features__
* [[Dementia]]
* [[Neurodegeneration]]
__Structural consequences in the brain__,, (first 90 years of research),,
* [[Amyloid plaques]]
** amyloid-β (Aβ) protein
* [[Neurofibrillary tangle]]s
** [[Tau protein]]
__Functional consequences in the brain__,, (last 15 years of research),,
* Memory loss
* Cognitive impairement
!!__Molecular mechanisms__
Transgenic mice models: [[vid|https://www.youtube.com/watch?v=l6jafQERb7E#t=14m55]]. These models don't model AD, but only //endophenotypes// of the disease.
!!!__Amyloid hypothesis__
https://www.wikiwand.com/en/Alzheimer's_disease#/Amyloid_hypothesis
//Amyloid precursor protein transgenic mouse models//
* Tg2576
Transgenic (Tg) mice that overexpress mutant familial Alzheimer's disease (AD) amyloid precursor protein (APP)
[[vid|https://www.youtube.com/watch?v=l6jafQERb7E#t=8m24s]] -- [[vid2|https://www.youtube.com/watch?v=l6jafQERb7E#t=21m]]
[[APP transgenic mice: their use and limitations.|https://www.ncbi.nlm.nih.gov/pubmed/21152995]]
[[Amyloid precursor protein transgenic mouse models and Alzheimer's disease: understanding the paradigms, limitations, and contributions.|https://www.ncbi.nlm.nih.gov/pubmed/19560104]]
These observations suggest that the pathogenesis of AD is by far more intricate than can be explained by a straightforward accumulation of Abeta.
[[Memory problems preceded the plaque formation by 6 months, so it didn't seem as though the plaques were the cause|https://www.youtube.com/watch?v=l6jafQERb7E#t=23m26]], but it seems to be A$$\beta$$ related, because if you give a$$\beta$$ antibodies, it seems to reverse the existing memory deficits. --> Brain disfunction and plaque pathology were mediated by different pathways. As it was independent of neuronal or synapse loss, they hypothesiced that the memory problems were mediated by a new species A$$\beta$$* [[vid|https://www.youtube.com/watch?v=l6jafQERb7E#t=24m30]] --> A$$\beta$$* 56 --> [[particles are spheroids|https://www.youtube.com/watch?v=l6jafQERb7E#t=29m]]. Probably as 12 mer. --> [[experiment by injecting into healthy rats|https://www.youtube.com/watch?v=l6jafQERb7E#t=30m50]]
__[[Low-end oligamers|https://www.youtube.com/watch?v=l6jafQERb7E#t=32m20]] (low end refers to monomers, dimers, etc. low end in the spectrum of aggregation)__
Researchers have been led to suspect non-plaque Aβ oligomers (aggregates of many monomers) as the primary pathogenic form of Aβ.
[[Aβ Oligomer-Induced Synapse Degeneration in Alzheimer’s Disease|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3146579/]]
__N-APP/DR6 pathway__
However, in 2009, this theory was updated, suggesting that a close relative of the beta-amyloid protein, and not necessarily the beta-amyloid itself, may be a major culprit in the disease. The theory holds that an amyloid-related mechanism that prunes neuronal connections in the brain in the fast-growth phase of early life may be triggered by ageing-related processes in later life to cause the neuronal withering of Alzheimer's disease.[64] N-APP, a fragment of APP from the peptide's N-terminus, is adjacent to beta-amyloid and is cleaved from APP by one of the same enzymes. N-APP triggers the self-destruct pathway by binding to a neuronal receptor called death receptor 6 (DR6, also known as TNFRSF21).[64] DR6 is highly expressed in the human brain regions most affected by Alzheimer's, so it is possible that the N-APP/DR6 pathway might be hijacked in the ageing brain to cause damage. In this model, beta-amyloid plays a complementary role, by depressing synaptic function.
!!!__Tau hypothesis__
//Tau transgenic mice//
* rTg4510 (r stands for regulatable)
[[vid|https://www.youtube.com/watch?v=l6jafQERb7E#t=10m28]]
Hyper[[phosphorylated|Phosphorylation]] Tau is the principal component in neurofibrillary tangles. It was found that certain mutations of Tau caused dementia
[[It doesn't seem that tangles are the cause of memory problems, though they correlate very well in humans|https://www.youtube.com/watch?v=l6jafQERb7E#t=20m]]. It supports the hypothesis that there is some form of soluble dysfunctional tau species that precedes structural changes like the tangles or the neuronal loss.
!!__Risk factors__
While in familial forms of AD, mutations result in an increased Aβ production or aggregation, in sporadic AD, failure of the clearance mechanisms might play a central role
!!__[[Early-onset Alzheimer's]]__
[[Familial Alzheimer's disease]]
An [[Organic compound]] with the functional group RnE(O)xNR′2 (R and R′ refer to H or organic groups).
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/8/85/Amide_types.svg/640px-Amide_types.svg.png?1473062984261]]
An [[Organic compound]] that contains a basic [[Nitrogen]] atom with a [[Lone pair]]. It can also refer to the corresponding [[Functional group]].
[img[http://figures.boundless-cdn.com/12387/raw/amine-2d-general.svg]]
An [[Organic compound]] with an amino group bound to a [[Carbon]] atom (known as $$\alpha$$), which is itself bound to a [[Hydrogen]], and a [[Carboxyl]] group (making it an acid). The $$\alpha$$ carbon is also bound to a ''side chain''.
[img width=400 [https://qph.ec.quoracdn.net/main-qimg-629ad92247b6be02f036cd330e39ddf2-c?convert_to_webp=true]]
!!__Categories of biological amino acids__
Charge refers to the charge at neutral pH. They have a 3 letter code to identify them
__Polar; uncharged__
__Polar; negatively charged__
__Polar; positively charged__
__Non-polar__
__Hydrophobic__
__Special__
Proline, which is technically an //Imino acid//, instead of an amino aicid. Cysteine, which can make a covalent disulfide bond.
[img[http://biologii.net/world/images/prot/aminoacids.jpg]]
[img[https://www.researchgate.net/profile/Alexandre_De_Brevern/publication/222435889/figure/fig1/AS:305097729953792@1449752375118/Figure-1-Venn-diagram-grouping-amino-acids-according-to-their-properties-adapted-from.png]]
All amino acids in [[Human]]s are L (see [[Chiral molecule]]), but [[Bacteria]] have both
//aka amphiphatic//
Refers to a molecule that has a [[Hydrophobic]] functional group at one end, and a [[Hydrophilic]] one at the other end.
It can help stabilize [[Emulsion]]s, in which case it's known as an [[Emulsifier]]
//There's many many things//, thus it makes sense we look at what happens when we got more and more things
[[Real Analysis: Lectures by Professor Francis Su|https://www.youtube.com/playlist?list=PL0E754696F72137EC]]
[[Mathematics - Measure and Integration|https://www.youtube.com/playlist?list=PLbMVogVj5nJTsl6c-UDL1luTVMT8v_RLQ]]
,,//AofA//,,
Analysis of the [[Computational complexity]] of [[Algorithms]], i.e. find out how much time, and how much memory does an algorithm take to run.
[[Analytic Combinatorics, Part I (Analysis of Algorithms)|https://www.youtube.com/playlist?list=PLhsb6tmzSpixf8y0IG6ckJCNP4Fdjcxxs]]
Already recognized as important by Babbage, Turing. However, the modern field of analysis of algorithms was started by Donald Knuth, who recognized that mathematics had the tools to analyze algorithms. Things like the following are useful tools for this:
* [[Recurrence relation]]s
* [[Generating function]]s
* [[Asymptotic analysis]]
Books: four volumes of //The art of computer programming//.
''Analytic combinatorics'' is a calculus (set of mathematical tools) for analyzing properties of large combinatorial structures.
[[Book|http://algo.inria.fr/flajolet/Publications/book.pdf]] [[website of book|http://ac.cs.princeton.edu/10ogf/]] [[videocourse|https://www.youtube.com/playlist?list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o]]
[img width=400 class=img-centered [http://i.imgur.com/VMuVMA8.png]]
!!__Symbolic method__
* Define a ''combinatorial class'':
** Define a //class// of combinatorial objects
** Define a notion of //size// (and an associated generating function)
* Use standard operations to develop a //specification// of the structure
Result: A direct derivation of a ''GF equation'' (implicit of explicit), i.e. an equation that the [[Generating function]] must satisfy.
Classic next steps:
* Extract coefficients
* Use classic asymptotics to estimate coefficients
Result: Asymptotic estimates that quantify the desired properties.
!!!__[[Symbolic method for unlabelled structures]] (Ordinary generating function)__
!!!__[[Symbolic method for labelled structures]] (Exponential generating function)__
--------------------------------
__Video course__
[[Analytic Combinatorics, Part II (Analytic Combinatorics)|https://www.youtube.com/playlist?list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o]]
In Coursera: [[Analytic Combinatorics|https://www.coursera.org/course/ac]]
Applications: [[Analysis of algorithms]], [[Random deterministic automata]], ...
https://en.wikipedia.org/wiki/Analytical_chemistry
Studies the structure of organisms. Goes together with [[Physiology]], which studies the function of organisms.
[[BioDigital- 3D Human Visualization Platform for Anatomy and Disease|https://www.biodigital.com/]]
!!!__Tissues__
Epithelial tissue. Covers stuff
Connective tissue. Connects stuff (like bones and muscles). Defined by presence of an extracellular matrix. Blood and fat are thus considered connective tissue.
Muscle tissue. [[Actin]] & [[Myosin]]
Nerve tissue. Neurons, glial cell.
!!!__Organs__
!!!__[[Organ systems]]__
[[Kindergarten Cop (4/10) Movie CLIP - Shut Up! (1990) HD|https://www.youtube.com/watch?v=tO4X8_c80kg]]
[img[http://66.media.tumblr.com/5e0747dd8b96fa6656e5041cfa81285b/tumblr_o9cks0fPHr1sk2szio1_540.gif]]
https://www.wikiwand.com/en/Bisection#/Angle_bisector
[img[https://upload.wikimedia.org/wikipedia/commons/1/14/Bisection_construction.gif]]
[[
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
[[Animal & veterinary sciences - Springer|http://www.springer.com/gp/life-sciences/animal-sciences]]
!!__[[Blood]] cell__
* [[Red blood cell]]
* [[White blood cell]]
* [[Epithelium]]
* [[Connective tissue]]
* [[Muscle tissue]]
* [[Nervous tissue]]
Part of the vision of [[AugMath]]
3Blue1Brown
https://www.youtube.com/watch?v=uXPb9iBDwsw
https://www.youtube.com/watch?v=RU0wScIj36o
https://github.com/3b1b/manim
Jim Blinn, algebraic ballet
http://kotaku.com/ibm-is-making-sword-art-online-for-real-1760758238
ergo proxy
[[Cyberpunk anime|https://www.youtube.com/watch?v=23HPiGe6WW4]]
Metropolis. Last scene: [[Metropolis (2001) - I can't stop loving you|https://www.youtube.com/watch?v=Nrb3EqGEI_E]]
Loved this when I was <big>very</big> small: https://en.wikipedia.org/wiki/Montana_Jones
http://scifi.stackexchange.com/questions/128187/animated-film-where-protagonists-travel-to-the-future-and-save-a-robot-enslaved
[[Disorder]] of a system at thermal equilibrium. This can be physically achieved by cooling the system down sufficiently slowly so that the system is in quasi-equilibrium at all times.
See density estimation in [[Unsupervised learning]]
[[Using PCA|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h08m30s]]
Anthropology is the study of humans and their societies in the past and present.
https://en.wikipedia.org/wiki/Anthropology
[[Wikipedia's contents: People and self|https://en.wikipedia.org/wiki/Portal:Contents/People_and_self]]
Bioviva
<big>[[FIRST GENE THERAPY SUCCESSFUL AGAINST HUMAN AGING|http://bioviva-science.com/2016/04/21/first-gene-therapy-successful-against-human-aging/]]</big>
[[About Deep Knowledge Life Sciences (DKLS)|http://deepknowledge.life]], [[BGRF|http://bg-rf.org.uk/]] and [[Avi Roy|https://about.me/agingroy]], [[SENS|http://www.sens.org/]] and [[Aubrey de Grey|https://en.wikipedia.org/wiki/Aubrey_de_Grey]]
TAME. Metmorfin
https://www.wikiwand.com/en/Senolytic
[[Can we engineer the end of ageing? - Daisy Robinton - TEDxLondonSalon|https://www.youtube.com/watch?v=sAChp49XgWA&feature=share]]
[[Drugs to Extend Life - Nathaniel David, CEO of Unity Biotechnology|https://www.youtube.com/watch?v=5YQDd8whJAA&feature=youtu.be]] -- [[Unity biotechnology|http://unitybiotechnology.com/#publications]]
http://www.longevityreporter.org/
,,https://global-longevity-initiative.webflow.io/,,
PREVENT . RESTORE . PRESERVE
Do not go gentle into that good night,
Old age should burn and rave at close of day;
Rage, rage against the dying of the light.
— Dylan Thomas
[[NLA, CASMI, Oxford and BGRF to develop the Global Healthspan Extension Initiative|https://nla.nu.edu.kz/en/news/3857.html]]
<<<
two of her own company’s experimental gene therapies:
*one to protect against loss of muscle mass with age,
*another to battle stem cell depletion responsible for diverse age-related diseases and infirmities.
[[Telomere]]s are short segments of DNA which cap the ends of every chromosome, acting as ‘buffers’ against wear and tear. They shorten with every cell division, eventually getting too short to protect the chromosome, causing the cell to malfunction and the body to age.
“Current therapeutics offer only marginal benefits for people suffering from diseases of aging. Additionally, lifestyle modification has limited impact for treating these diseases. Advances in biotechnology is the best solution, and if these results are anywhere near accurate, we’ve made history”
Note: this is awesome
It remains to be seen whether the success in leukocytes can expanded to other tissues and organs, and repeated in future patients
<<<
[[Gene therapy to save the world|https://www.youtube.com/watch?v=JdEyd1CZYvo]]
[[IVAO to announce plans to invest over $1 billion in aging and longevity projects at a conference in St Petersburg.|http://www.prweb.com/releases/2016/04/prweb13352737.htm]]
[[10 responses to “Hacking Aging” |http://lifeboat.com/blog/2016/05/10-responses-to-hacking-aging]]
What would you say if I told you that aging happens not because of accumulation of stresses, but rather because of the intrinsic properties of the gene network of the organism? I’m guessing you’d be like: :o .
C-elegans 10-fold lifespan increase [[paper|http://onlinelibrary.wiley.com/doi/10.1111/j.1474-9726.2007.00348.x/full]]
--------------------------
Liz talk
.......
* Telomerase gene therapy.
* * To avoid stem cell depletion (as it controls how many times a cell can divide)
** Remethylates genes. As we grow old, more genes are activated, eventually causing cancer. We want to disactivate them
* Muscle mass. Myostatin inhibition, AAV Follistan
* CRISPR - many genes could be targeted.
------------------
* Parabiosis. blood borne factors in young blood can rejuvenate old mice. Human trial going on now. Both positive factors from young mouse, and negative factors being cleared
* Senecent cell removal. Liposomal targeting, gene therapy
* Glycation. AGE breakers
* Mitochondria.
__Cell therapy and tissue bioprinting___
IPSC/ESCs/Adult stem cells
. Ex vivo gene correction
Repurposing of pharmaceuticals in market.
Metmorfin, senolytic drugs.
Gene editing, gene therapy, stem cell therapies
Immunotherapy, targeted cancer approaches. T-cell. Ablation. Modulate allergies!
Monoclonal antibiotics. Non-permanent gene ..
Rapid genomics
Big data crunching.
-------------
https://books.google.co.uk/books?id=0sqPrvwRfQsC&pg=PA625&lpg=PA625&dq=c+elegans+lifespan+extended+10+fold&source=bl&ots=dRq6otX_Mh&sig=s7ZpqykoHZtFkhitPGlJaocDhRQ&hl=en&sa=X&ved=0ahUKEwi515ry-arQAhWBbhQKHVXUAGEQ6AEIOzAE#v=onepage&q=c%20elegans%20lifespan%20extended%2010%20fold&f=false
An unstable [[resonant|Resonance (Chemistry)]] ring.
See [[Aromatic compound]]
https://checkvist.com/checklists/563670#
http://beyondplm.com/ PLM/PDM in cloud, in blockchain. supply chain management. healthcare system.
SAP, grabcapd, onshape
[[Ethereum]] Provenance
Ascribe, legal stuff
[[Web development]]
[[Apollonian gasket|https://www.jasondavies.com/apollonian-gasket/]] (see [[Apollonian networks]])
http://bl.ocks.org/mbostock/7115f7a0393de96f2fdc
<div style="width: 600px; height:500px; overflow : hidden; position : relative;" overflow="scroll">
<iframe src="https://www.jasondavies.com/apollonian-gasket/" scrolling="no" style="position : absolute;top: -165px;left: -50px; width : 1280px; height : 1200px;">
</div>
[[Apollonian networks|file:///home/guillefix/Dropbox/Oxford/MMathPhys/Complex%20systems/apollonian_nets.pdf]]
[[online (annotated) pdf|https://files.acrobat.com/a/preview/b5406b81-d817-40f3-baee-1fe6bf09da5f]]
[[Random Apollonian Networks|https://arxiv.org/pdf/cond-mat/0409414v2.pdf]]
[[Apollonian network|https://en.wikipedia.org/wiki/Apollonian_network]]
[img[https://upload.wikimedia.org/wikipedia/commons/8/80/Apollonian-network.svg]]
See [[Apollonian gasket]]
A device or piece of equipment designed to perform a specific task, typically a domestic one.
[[Topography]] studies features of the surface of the [[Earth|Planet Earth]], as well as other planets. These can be described as //landscapes// [[Percolation]] models and [[Percolation theory]] have been applied to understand these.
A landscape is a height profile usually defined on a square lattice where each cell’s elevation value at position x represents the average elevation over the entire footprint of the cell (site). Now imagine that the water is dripping uniformly over the landscape and fills it from the valleys to the mountains, letting the water flow out through the open boundaries. During the raining, watershed lines may also form which divide the landscape into different drainage basins. These are important in geomorphology in e.g., water management [113] and landslide and flood prevention [114]
it is possible to determine the watershed lines based on the iterative application of invasion percolation [115].
Another kind of percolation that can occur: Raising the water level makes lakes join together, and eventually a lake that spans the whole landscape may form. However, whether the percolation transition is critical or not depends on the properties of the surface landscape (in particular on correlation functions).
These ideas have been applied to study the topography of the Earth, where they found that the present sea level is a critical level in their model. This finding elucidates the origins of the appearance of ubiquitous scaling relations observed in the various terrestrial features on Earth.
//[[AI|Artificial intelligence]] is promising to be applicable to almost any aspect of [[Cosmos]], for it is its essence.//
[[Deep learning companies and projects]]
[[Artificial intelligence innovation]]
|[img width=400 [Machine_learning_uses1.png]]| [img width=300 [Machine_learning_uses2.png]]|
!!__Perception__
[[Image classification]]
!!__[[Science]] and [[Engineering]]__
[[AI for science|http://slides.com/guillermovalle/deck-3/fullscreen#/]]
[[Machine learning in science and engineering]]
__Computer science__
[[Data compression]], [[Image processing]]: [[Autoencoder]]
__Robotics__
[[Reinforcement learning]]
__Healthcare__
!!__[[Art]]/[[Design]]__
[[Deep art]]
[[Procedural generation]]
!!__[[Human-computer interaction]] and [[Communication]]__
[[Speech synthesis]]
[[Speech recognition]]
[[Machine translation]]
[[Oxford course|https://www0.maths.ox.ac.uk/courses/course/28755]]
Syllabus: Review of core complex analysis, especially continuation, multifunctions, contour integration, conformal mapping and Fourier transforms. Riemann mapping theorem (in statement only). Schwarz-Christoffel formula. Solution of Laplace's equation by conformal mapping onto a canonical domain. Applications to inviscid hydrodynamics: flow past an aerofoil and other obstacles by conformal mapping; free streamline flows of hodograph plane. Unsteady flow with free boundaries in porous media. Application of Cauchy integrals and Plemelj formulae. Solution of mixed boundary value problems motivated by thin aerofoil theory and the theory of cracks in elastic solids. Reimann-Hilbert problems. Cauchy singular integral equations. Transform methods, complex Fourier transform. Contour integral solutions of ODE's. Wiener-Hopf method.
Jordan's lemma
The art and science of designing and making building and other spaces for the use of [[People|Person]]
Also use tools from [[Design optimization]], including [[Genetic algorithms applied to grid structure optimization|https://www.youtube.com/watch?v=3U4TbXMn41E]] which look really cool.
[[Simulating rain for architecture|https://www.youtube.com/watch?v=NVcGRC38ttM]]
[[Programming architecture|http://www.programmingarchitecture.com]] is a company that solves problems in the design and construction phase of complex architectural objects. Offers software and knowledge.
https://www.youtube.com/watch?v=YxJJeU9mVSU&list=PLhOObpoQndRmAGJh1mvnE6ye0z-bmIhxF
https://en.wikipedia.org/wiki/Area_studies
!!__Peano arithmetic__
Typographical number theory, see chapter VIII of GEB
$$\omega $$-incompleteness., $$\omega $$-inconsistency
''Rule of induction''
[[Arithmetic Compression (Ep 5, Compressor Head) Google|https://www.youtube.com/watch?v=FdMoL3PzmSA&index=7&list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H]]
[[(IC 5.1) Arithmetic coding - introduction|https://www.youtube.com/watch?v=ouYV3rBtrTI]]
https://www.youtube.com/watch?v=7vfqhoJVwuc
https://www.youtube.com/watch?v=CXCWQy9N2ag
An [[Organic compound]] that contains at least one cyclic (ring-shaped), planar (flat) [[Moiety]] with a ring of resonance bonds (most often a [[Conjugated system]]) that exhibits more stability than other geometric or connective arrangements with the same set of atoms. Aromatic moieties are very stable and do not easily break apart and react with other substances.
The most common of these rings is the [[Benzene]] ring.
Existence of such a stable [[resonant|Resonance (Chemistry)]] cyclic can often be determined using [[Huckel's rule]]
[[Aromatic Compounds and Huckel's Rule|https://www.youtube.com/watch?v=RaBI3lAACKg]]
There is a class of resonant rings that are very unstable, known as [[Antiaromatic compound]]s. Finally there are resonant rings which are non-aromatic (neither aromatic nor antiaromatic).
[[Aromatic, Antiaromatic, or Nonaromatic: How To Tell The Difference|https://www.youtube.com/watch?v=eK8S51L8juo]]
[[Aromatic Heterocycles I|https://www.youtube.com/watch?v=vAW9t5uBr08]]
See [[MMathPhys oral presentation]].
------------
!!__Theoretical framework__
Following [[The Arrival of the Frequent: How Bias in Genotype-Phenotype Maps Can Steer Populations to Local Optima|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086635]] (remember notes here are complementary to paper, and don't cover all of its content, only those parts where I thought were gaps for me to understand it), we can study the effect of the structure of the ''genotype-phenotype (GP) map'', in the model of [[Evolution]] known as the [[Wright-Fisher model]] (see [[Population genetics]]). We use the //Haploid Wright-Fisher model with selection//, where for each individual in the generation at time $$t+1$$, we choose a single parent from the individuals at the previous generation $$t$$, according to the rule described [[there|Wright-Fisher model]]. We then include the effect of ''mutations'', by assigning to the new individual a genotype of length $$L$$ as follows:
* Copy the genotype of parent.
* For each of the letters in the genotype, replace it with probability $$\mu$$, the //point mutation rate//. When you replace, you replace it by a //different// letter, chosen uniformly at random from the different letters.
Note: the genotype is defined as a sequence of $$L$$ letters taken from an alphabet of $$K$$ letters.
<big><i class="fa fa-star-o" aria-hidden="true"></i> See [[Mean field approximation to average number of phenotypes discovered in Wright-Fisher model]] <i class="fa fa-star-o" aria-hidden="true"></i></big>, some equations are found there. The main result is that the expected number of individuals with genotype $$p$$ that arises at generation $$t$$ can be approximated as
|$$m_p(t) \approx L\mu \sum_{i=1}^N \Phi_{pq} = N L\mu \Phi_{pq}$$|Eq.3|
under certain assumptions, explained in that tiddler.
!!!''Polymorphic limit''
If $$NL\mu \gg 1$$, the population naturally spreads over different genotypes, a regime called the //polymorphic limit//. See [[Polymorphic limit (Wright-Fisher model)]] tiddler for details. Main points:
To __model neutral exploration__, we __let__ $$1+s_p = \delta_{pq}$$, where $$ \delta_{pq}$$ is a [[Kronecker delta|https://en.wikipedia.org/wiki/Kronecker_delta]]
The time when {{the probability of having discovered a p-type individual (produced a p-type offspring)} is $$\alpha$$} is found by:
|$$ T = \frac{-\ln{1- \alpha}}{N L\mu \Phi_{pq}}$$|Eq. 4|
!!!''Monomorphic limit''
Neutral spaces can be astronomically large, much bigger than even the largest viral or bacterial populations (see [[this paper|http://www.ncbi.nlm.nih.gov/pubmed/18973652]]). In that case, the local neighborhood of the population may not be fully representative of the neighborhood of the entire space.
This scenario can most easily understood in the //monomorphic limit//: when mutants are rare, $$NL \mu \ll 1$$
Now, the (average) rate of neutral mutations (per individual) is $$\nu = L \mu \rho$$, as $$\rho$$ is the probability that a mutation is neutral.
<big><i class="fa fa-arrow-right" aria-hidden="true"></i> See more in the [[Monomorphic limit (Wright-Fisher model)]] tiddler, and at [[the paper|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086635]].</big>
[img[img/arrivalfrequent2.png]]
We can see that in the large genome limit, the phenotype $$p$$ is found quicker as the population $$N$$ increases. However, when the population becomes so large that all the 1-mutation neighbourhood is thoroughly explored (while still staying in the monomorphic limit), the discovery time saturates because increasing the population doesn't increase the number of explored phenotypes (during a fixation period).
These results suggest that for intermediate $$NL\mu$$ there should be a smooth transition between these two regimes. To quantify the crossover we introduce a factor $$\gamma$$.
[See Figure 1.]
!!__Simulations in model GP maps__
The ''genotype'' is defined by:
* //Alphabet length//: $$K$$
* //Genotype length//: $$L$$
The number of available genotypes is thus $$K^L$$.
!!!''Random GP map'':
Apart from specifying $$K$$ and $$L$$, we need to specify the set $$\{F_q\}$$ which is the fraction of genotypes mapping to phenotype $$p$$. The map is otherwise random.
In this setting, $$\phi_{pq} = F_p$$ is a good approximation if $$N_q, N_p \gg 1$$, where $$N_i$$ is the number of genotypes mapping to phenotype $$i$$. These also require $$N_P \ll N_G$$ (i.e. {the number of phenotypes } is much less than {the number of genotypes}, i.e the map is //very// many-to-one).
There is also a percolation threshold at a critical frequency ($$F_p$$) $$\lambda(K) = 1 - K^{-1/(K-1)}$$, so that only phenotypes with $$F_p > \lambda(K)$$ have "completely" connected neutral spaces (in the network where edges correspond to a single-point mutations, or genotypes separated by a [[Hamming distance|https://en.wikipedia.org/wiki/Hamming_distance]] of $$1$$). See the theory of percolation in [[Network science]]'s Newman's book, Oxford notes, and problem sheets. See also [[Random Induced Subgraphs of Generalized n-Cubes|http://dl.acm.org/citation.cfm?id=272628]].
Standing variation. [[Adaptation from standing genetic variation.|http://www.ncbi.nlm.nih.gov/pubmed/18006185]]
!!!''RNA secondary structure mapping''
RNA <b>genotypes</b> of length $$L$$ made up of nucleotides G,C,U and A.
The <b>phenotypes</b> are the minimum free-energy secondary structures for the sequences, which can beefficiently calculated (see [[Fast Folding and Comparison of RNA Secondary Structures|http://sci-hub.io/10.1007/BF00818163]]). The number of genotypes grows as $$4^L$$,while the number of phenotypes is thought to grow roughly as $$N_P \sim 1.8^L$$ (see [[Robustness and Evolvability in Living Systems - Andreas Wagner|http://press.princeton.edu/titles/8002.html]]). Also:
[[From sequences to shapes and back: a case study in RNA secondary structures.|http://www.ncbi.nlm.nih.gov/pubmed/7517565]] - [[pdf|http://fontana.med.harvard.edu/www/Documents/WF/Papers/sequences2shapes.pdf]].
[[Epistasis can lead to fragmented neutral spaces and contingency in evolution|http://rspb.royalsocietypublishing.org/content/279/1734/1777]]
[[The Ascent of the Abundant: How Mutational Networks Constrain Evolution|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000110]]
Discovery times are slower than in the random GP map. This reflects the internal structure of the RNA: similar genotypes typically have similar mutational neighbourhoods (see [[Exploring phenotype space through neutral evolution.|http://www.ncbi.nlm.nih.gov/pubmed/8703081]]), and so the population needs to neutrally explore longer in order to find novelty.
:Phenotypic bias leads to a simple, systematic ordering in the discovery of novel phenotypes.
!!''__The arrival of the frequent__''
[img width = 500 [img/arrivalfrequent3.png]]
//Comment//: The fact that this discussion requires speaking about a change in the environment is what makes "the arrival of the frequent" a non-equilibrium effect, I think. Compare this with the survival of the flattest which is an equilibrium effect.
[img width = 500 [img/arrivalfrequent4.png]]
We need to have $$s2, s_1\gtrsim 1/(2N)$$ because the probability of fixation is (see [[here (page 201)|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]] or [[here|http://jaguar.biologie.hu-berlin.de/~wolfram/pages/seminar_theoretische_biologie_2007/ausarbeitungen/zackay.pdf]], or [[here (page 326)|http://evolution.gs.washington.edu/pgbook/pgbook.pdf]]):
$$P = \frac{1-e^{-qs}}{1-e^{-2Ns}}$$
So for $$2Ns \gtrsim 1$$, $$\frac{q(2Ns)}{2N(1-e^{-(2Ns)})} > \frac{q}{2N}$$. We need to have $$s2, s_1\gtrsim 1/(2N)$$ so that the probability of fixation of the two alternative phenotypes is considerably larger than that of the initial phenotype $$q$$, for which $$s=0$$. [[In here (page 321)|http://evolution.gs.washington.edu/pgbook/pgbook.pdf]] an expression for the case of $$N$$ very large is derived without using diffusion approximation.
A more frequent phenotype ($$p1$$, with $$\phi_p1q$$ much larger than competitor $$p2$$) is favoured via two related effects:
* <b>It is discovered much earlier</b>, and so it has a chance to fix //before// $$p2$$.
* Because the discovery time-scale is much smaller, if {we are in the large population monomorphic limit, so that the single-mutation neighbourhood is explored many times before population fixes to a new genotype}, then <b>$$p1$$ is also visited more often</b>. Therefore its fixation probability is larger. Say that $$p1$$ is visited $$n$$ times, then the probability that it fixes is $$1-(1-p)^n \approx np$$, where $$p$$ is the probability that it fixes when it's visited once ($$1/N$$ without selection bias), and it is much smaller than $$1$$ for the approximation ($$N$$ large). >Isn't this the same as the result that "The rate of fixations is equal to the rate of (neutral) mutations of an individual." derived in [[Monomorphic limit (Wright-Fisher model)]]? Yes.This is observed in their microscopic models ([[On the significance of neutral spaces in adaptive evolution|http://ora.ox.ac.uk/objects/uuid:505da0f0-d97b-44c3-a1e2-e84a0753c7e6]]). This effect is ignored in origin-fixation models (see [[Bias in the introduction of variation as an orienting factor in evolution|http://www.ncbi.nlm.nih.gov/pubmed/11341676]]) Hm, how exactly is it ignored? haven't read the paper yet... Well, from what Ard said, the way they ignore is that they ignore the short-time correlations in the monomorphic limit, discussed in the paper.
Another effect that often positively correlates with the frequency of a phenotype is [[Mutational robustness]] (see [[Robustness and evolvability: a paradox resolved|http://rspb.royalsocietypublishing.org/content/275/1630/91]] and [[Epistasis can lead to fragmented neutral spaces and contingency in evolution|http://rspb.royalsocietypublishing.org/content/279/1734/1777]]). Mutational robustness has been shown to offer selective advantage at high mutation rates, because phenotypes which are not robust will often mutate to [[deleterious|http://www.dictionary.com/browse/deleterious]] mutants and probably go extinct, while phenotypes which are robust will survive. This effect is called the ''"survival of the flattest"'', as robust phenotypes correspond to "flat" regions in the fitness landscape (see [[the paper|http://www.ncbi.nlm.nih.gov/pubmed/11460163]]). This effect can also be understood in terms of ''free fitness'' (see [[Free fitness that always increases in evolution|http://www.ncbi.nlm.nih.gov/pubmed/3256719]]), in analogy to "free energy" in [[Statistical physics]] (see [[The application of statistical physics to evolutionary biology|http://www.pnas.org/content/102/27/9541]]), as it incorporates an entropy-like term accounting for the size of the neutral space of the phenotype.
However, <b>{the arrival of the frequent} is a non-equilibrium effect</b> (unlike {the survival of the flattest} which assumes equilibrium or pseudo-equilibrium). This is because it describes how discovery times and discovery frequency depend on the phenotypes frequency ($$F_p$$), after a change in the environment, when the system is out-of-equilibrium.
[img[https://66.media.tumblr.com/fbf8560da873602151edae77f8751e38/tumblr_o7e4xb4xsD1ruo6jxo1_1280.png]]
For the monomorphic limit (small mutation rate, in Figure 4.), the probability.....
!!__Summary/Discussion__
Genotype-phenotype (GP) maps are observed to be highly //biased//: Some phenotypes are realised by orders of magnitude more genotypes than most other phenotypes.
Large bias observed in the GP maps translates into a similar order of magnitude variation in the median discovery times $$T_p$$ for a range of population genetic parameters. However, correlations in the GP map can cause the relation between $$T_p$$ and phenotype frequency $$F_p$$ to have large fluctuations (for example, $$phi_{pq}$$ (which determines $$T_p$$) can be $$0$$ even if $$F_p$$ is quite large).
For the GP mas studied, the strong bias in the GP map leads to a systematic //ordering// of the median discovery times of alternative phenotypes, an effect that we postulate may hold for other GP maps as well.
The correlations in the RNA GP maps mean that close genotypes have similar neighbourhoods, so that one needs to explore further to reach truly new {genotype neighbourhoods}. This is why the fitting parameter $$\gamma$$ is smaller than the value expected in the mean-field approx. This is also why for very similar values of $$\phi_{pq}4$$, there is a range of values of $$T_p$$ spanning about $$1$$ order of magnitude. This probably means that it takes up to $$\sim 10$$ generations to {reach truly novels genotypic neighbourhoods} in the {neutral exploration}. Still, the many orders of magnitude range observed in $$\phi_{pq}$$ dominates the variation in phenotype discovery times ($$T_p$$), providing a //a posteriori// justification for the mean-field approximation.
It is reasonable to expect all these features to arise in other GP maps found in natural (or in artificial systems), including biological systems.
Taken together, these arguments suggest that the vast majority of possible phenotypes may never be found, and thus never fix,even though they may globally be the most fit: Evolutionary search is deeply non-ergodic (I think that this is in the sense that we don't quite reach equilibrium on reasonable time scales, or that the observation time-scales needed for the system to appear ergodic are much larger than those used in experiment. However, this is also true in many other systems like particles in a gas; however, this other system doesn't show the bias needed for the [[Arrival of the frequent]] effect).
When Hugo de Vries was advocating for the importance of mutations in evolution, he famously said ‘‘Natural selection may explain the survival of the fittest, but it cannot explain the arrival of the fittest’’ [2]. Here we argue that the fittest may never arrive.Instead evolutionary dynamics can be dominated by the ‘‘arrival of the frequent’’.
--------
Older comments:
So I think what he was talking about is that we can construct a network of phenotypes which is a projection of the network of genotypes via the genotype-phenotype map. Links in the network of genotypes are possible mutations, and all genes have the same degree. However, not all nodes have the same degree in the network of phenotypes.
We can then apply results from network theory of the steady distribution for a [[random walker on a network|Random walk in a graph]].
So this sets a bias on the distribution on the phenotype network.
Over this bias there will be the fitness surface.
That subtle aspect of the human mind committed to the //creation// of new structures in the World.
That is, by virtue of its extreme complexity, human brains are able to catalyze equally complex structures out the molecular chaos that excites the neurons in random ways. These structures can resonate with the brain/minds of other people in ways that evoke emotion, and may be thus called //beautiful// by these people.
For this reason art may be considered as a language or a means for communicating emotions.
Art itself has been studied, but even more often, it has been //practised//, creating a vast amount of //works of art// throughout human history. The classification of these works, though of course, blurry, is based in part on the medium the art is expressed on, and which senses are primarily used to experience it.
Other interesting definitions discussed here: [[Is Programming Art? - MPJ's Musings - FunFunFunction #33|https://www.youtube.com/watch?v=MdlHgIJrQn0]]
[[Portal:Contents/Culture and the arts|https://en.wikipedia.org/wiki/Portal:Contents/Culture_and_the_arts]]
See also [[Technology & Engineering]]
-----------
Fund artists! https://www.patreon.com/
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http://www.openculture.com/2015/03/download-422-free-art-books-from-the-metropolitan-museum-of-art.html
http://michaelnielsen.org/blog/the-artist-and-the-machine/
[[Artificial chemistry|https://en.wikipedia.org/wiki/Artificial_chemistry]]
[[http://tuvalu.santafe.edu/~walter/AlChemy/alchemy.html]]
[[Arrival of the fittest|http://fontana.med.harvard.edu/www/Documents/WF/Papers/arrival.pdf]] The modern evolutionary synthesis based on [[Population genetics]] has an //existence problem//: it assumes the existence of individuals, genes, alleles, etc. They propose a simple model abstracting from chemistry to explain the [[Self-organization]] of //self-maintaining// and //self-replicating// structures, necessary for the [[origin of life|Abiogenesis]] Darwinian [[Evolution]].
They point out related work in //autopoiesis//, //concurrent computation//, a "chemical abstract machine", //autocatalytic reaction networks//.
[img[Selection_192.png]]
[[Review paper|http://web.cs.mun.ca/~banzhaf/papers/alchemistry_review_MIT.pdf]]
[[Artificial Chemistries|https://books.google.co.uk/books?id=xY4jCgAAQBAJ&pg=PA552&lpg=PA552&dq=random+boolean+networks+python&source=bl&ots=LvRNNWeiCE&sig=459mNE5uZxQ3m7G30eCTYUHnzCA&hl=en&sa=X&ved=0ahUKEwjSit3VorDNAhWIKsAKHb-OCN4Q6AEIUTAH]]
See [[Machine learning]], [[Intelligence]]
[[Computational intelligence - Scholarpedia|http://www.scholarpedia.org/article/Encyclopedia:Computational_intelligence]]
[[Oxford course (with video)|https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/]] [[Deep learning]].
[[Youtube playlist by mathematicalmonk|https://www.youtube.com/watch?v=yDLKJtOVx5c&list=PLD0F06AA0D2E8FFBA]]
Hugo latochelle YB videos
Read Neural Turing machines paper
See also: [[Evolutionary computing]], [[Bio-inspired computing]], [[Sloppy systems]]
[[Artificial Intelligence At Work|http://events.technologyreview.com/video/watch/dileep-george-vicarious-ai-work/]] (http://www.vicarious.com/)
----------
''[[Artificial intelligence]]'' (''AI'') has the overall goal of understanding and engineering //intelligence//, behaviour that involves understanding, and higher [[cognitive|Cognitive science]] functions. It is a broad and very interdisciplinary field. It feeds to and from [[Machine learning]], [[Logic]], [[Cognitive science]], [[Neuroscience]], etc.
!!__Approaches__
* Connectionists. Deep learning, artificial neural network. Backpropagatiob
* Evolutionaries
* Bayesians. Bayesian networks.
* Symbolists
* Analogizers.
!!!__AI and complex systems__
[[Synthetic biology routes to bio-artificial intelligence|http://pure.abdn.ac.uk:8080/portal/en/researchoutput/synthetic-biology-routes-to-bioartificial-intelligence(cb7d62e5-5877-4659-8286-ba1ab187fbc4).html]]
[[Complex Systems, Artificial Intelligence and Theoretical Psychology|https://www.researchgate.net/profile/Richard_Loosemore/publication/228680056_Complex_systems_artificial_intelligence_and_theoretical_psychology/links/02bfe50fea30911805000000.pdf?origin=publication_detail]]
----------------
__[[AI safety]]__
!!!__[[General artificial intelligence]]__
__[[Universal AI]] theory__
!!!__[[Explainable artificial intelligence]]__
------------
[[Integrating symbols into deep learning]]
[[Program induction]], [[Neural networks with memory]], [[Intelligence]]
-------------------
thinking perception action. Loops b?w them
Oxford's society [[OxAI]]
-----------
''Machine intelligence'', is essentially a synonym of AI, but with the connotation of using machines and computers to create and understand intelligence. The biggest part of it, [[Machine learning]], deals with the problem of __learning a model__ from data so as to solve (mostly) __predictive__ tasks.
-----------
!!!__[[Applications of AI]]__
------------
__[[Companies and projects|Deep learning companies and projects]]__
--------
[[Miscellaneous notes from first Nando's first deep learning lecture]]
--------
Challenges: [[One-shot learning]], multi-task & transfer learning, scaling and energy efficiency, ability to generate data (e.g. vision as inverse graphics), architectures for AI.
-------
See more at [[Machine learning]]
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!!!__[[Mathematical modelling of neural networks]]__
Why Deep Learning models perform so well?
Seems to be a result of:
*Very large datasets
*Increasing computing power
*Flexibility of the models. Lots of parameters when lots of layers. Furthermore multiple layers avoide the curse of dimensionality
--------
[[Eric Drexler - A Cambrian explosion in Deep learning|https://www.youtube.com/watch?v=QPWs3BBKBdY&feature=youtu.be]]
--------
[[A Gradient Descent Method for a Neural Fractal Memory|http://www.demo.cs.brandeis.edu/papers/wcci98.pdf]]
[[https://www.oreilly.com/ideas/the-current-state-of-machine-intelligence-2-0|https://www.oreilly.com/ideas/the-current-state-of-machine-intelligence-2-0]]
[[Computer vision]]
[[Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks Paperback – 28 Oct 2015|https://www.amazon.co.uk/Artificial-Intelligence-Humans-Learning-Networks/dp/1505714346/ref=pd_cp_14_1?_encoding=UTF8&psc=1&refRID=QQNERJ110GTGKXQRXNZ8]]
[[Fundamentals of Deep Learning|http://shop.oreilly.com/product/0636920039709.do]]
https://medium.com/machine-learnings/a-humans-guide-to-machine-learning-e179f43b67a0#.gumb86nos
Yes, the idea is not that humans will not do anything. The idea is that we set goals, make individual and collective decisions, just as today. But with higher prowess. As a result, most people will work less, in the sense that they spend almost all their time in leisure, and almost none in rote activities.
In car factories, for instance, you will need less and less people, as the work becomes closer and closer to just deciding the overall high level goals. The remaining jobs, will also become quite close to laisure anyway, with almost all rote aspects removed.
You know, people for fun will stay make cars and other things by hand, and with different degrees of automation. A big thing, I believe, will be people and machines working together as a team, each benefiting from each other's strengths. Later on, we will also become hybridized with machines in more direct ways, until, "we become one". Or how I prefer to put it, we become many (in the sense that the diversity of forms of sentient beings/people will grow drastically, with a huge spectrum of personal choice/journey to explore and expand)
http://www.artificialbrains.com/
[[Nice PhD thesis|http://users.dsic.upv.es/~flip/papers/Thesis_fmartinez.pdf]] -- [[author page|http://users.dsic.upv.es/~fmartinez/]]
[[Prof. Schmidhuber - The Problems of AI Consciousness and Unsupervised Learning Are Already Solved|https://www.youtube.com/watch?v=JJj4allguoU]]
---------------------
Some quick notes to self, on designing cognitive systems (AIs):
System that sees and acts on the world.
It creates models of the world and of itself acting on it.
It meanwhile decides what to do, based on its internal models, and some sort of reward mechanisms. It can decide to act on the world, or run internal simulations (thinking, consciousness), or both, and can organically alternate between the two. Active and passive/reflective modes. Fast and slow thinking.
Creating models <--> Unsupervised learning. Promising approaches: GANs, DBNs. Need more advances in this area.
Models that include the acting agent itself. Juergen Schmidhuber seems to have made work on this, but not sure what is his approach.
Best reward mechanisms unclear. Also, amount of pre-existing structure for system to work appropriately also unclear <> the rebirth of the nurture vs nature problem, now from the "Creator"'s perspective.
[[The AI awakening|http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?mwrsm=Facebook&_r=0]]
See also [[Applications of AI]]
__Google/Deepmind__
[[The meaning of AlphaGo, the AI program that beat a Go champ|http://www.macleans.ca/society/science/the-meaning-of-alphago-the-ai-program-that-beat-a-go-champ/]]
[[Is AlphaGo Really Such a Big Deal?|https://www.quantamagazine.org/20160329-why-alphago-is-really-such-a-big-deal/]]
[[Google Unveils Neural Network with “Superhuman” Ability to Determine the Location of Almost Any Image|https://www.technologyreview.com/s/600889/google-unveils-neural-network-with-superhuman-ability-to-determine-the-location-of-almost/]]
[[Google’s DeepMind AI group unveils health care ambitions|http://venturebeat.com/2016/02/24/googles-deepmind-ai-group-unveils-heath-care-ambitions/]] http://deepmind.com/health
etc etc
__Vicarius__
__Facebook__
See [[New advances in deep learning]] and people I follow on Twitter
[[NNAISENSE|https://nnaisense.com]] leverages the 25-year proven track record of one of the leading research teams in AI to build large-scale neural network solutions for superhuman perception and intelligent automation, with the ultimate goal of marketing general-purpose Artificial Intelligences.
https://github.com/baidu-research/warp-ctc
http://www.cyc.com/
[[On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models|http://arxiv.org/abs/1511.09249]]
[[A Roadmap towards Machine Intelligence|http://arxiv.org/abs/1511.08130]]
[[http://people.idsia.ch/~juergen/rnnai2016.html]]
[[US White House - Preparing for the Future of Artificial Intelligence|https://www.whitehouse.gov/blog/2016/05/03/preparing-future-artificial-intelligence]]
[[New advances in deep learning]]
<small>Aka artificial neural network..</small>
A particularly useful way of representing nonlinear functions, for problems in [[Machine learning]]. It is a very good model for many problems, and learning algorithms produce very good results with them. In particular __deep learning__ (which uses ANNs with many layers). It is a nonlinear [[classifier|Classifier]], and [[Regression analysis]] model.
[[Hugo Larochelle class videos|https://www.youtube.com/watch?v=apPiZd-qnZ8&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=4]] ([[website|http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html]]). [[Andrew Ng intro|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=26m]]. [[NN|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=29m]]. Learning parameters in a NN is generally a [[non-convex optimization problem|Convex optimization]], which makes it very hard to reach global optima.
!!__Definition__
Neuron has:
1) ''inputs''
2) ''weight vectors'', that multiplies the input vector or activation vector of hidden layers.
3) ''bias'', that is added to result
4) ''activation function'' takes as argument the result of the above (called pre-activation or input activation)
5) The result (called ''activation'') may be the input of other neurons in the next ''layer'', in a ''multilayer feedforward neural network''.
6) The activation of the last layer, is the ''output''
Overall... we are multiplying by matrices and applying simple nonlinear function
!!!See [[Neural network theory]], [[Mathematical modelling of neural networks]], for more on the theory
!!__Learning by [[optimization|Optimization]]__
Learning by minimizing cost function (see [[Learning theory]])
[[Training neural networks - optimization|https://www.youtube.com/watch?v=Bver7Ttgb9M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=17]]. There are several global optima, and plateaus. Uses [[Gradient descent]], in particular [[SGD|Stochastic gradient descent]].
An efficient algorithm to compute the gradients of the loss function for (SGD) w.r.t. the ANN's parameters is [[Backpropagation]].
see more at [[Learning theory]]
!!!__Parameter initialization for NNs__
[[Neural networks [2.9] : Training neural networks - parameter initialization|https://www.youtube.com/watch?v=sLfogkzFNfc&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=15]]
!!!__[[Model selection]] for neural networks__
[[Neural networks [2.10] : Training neural networks - model selection|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16]]. How to set the hyperparameters. Can use [[Cross-validation]].
!!__Types of neural networks__
[[NN Zoo|http://www.asimovinstitute.org/neural-network-zoo/]]
* [[Feedforward neural network]] (basic)
* [[Convolutional neural network]]. Good for image recognition for e.g.
* [[Recurrent|Recurrent neural network]]. Good for sequences in time
* Long-Short term memory NN.
* [[Spiking neural network]]
* [[Residual neural network]]
* [[Boltzmann machine]]
* [[Autoencoder]]
* [[Deep belief network]]
* [[Generative adversarial network]]
* [[Hopfield network]]
* [[Binarized neural network]]
* [[Extreme learning machine|http://www.ntu.edu.sg/home/egbhuang/]]
Many models in [[Machine learning]] can be seen as neural networks
[img[http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png]]
--------
[[Early video that created about TTS|https://www.youtube.com/watch?v=qyyJKd-zXRE&list=PLA89DCFA6ADACE599&index=6#t=41m23s]] using ANNs (NetTalk), see [[Speech synthesis]]
[[A Neural Network in 11 Lines of Python|http://fossbytes.com/a-neural-network-in-11-lines-of-python/]]
__More models, and generalizations__
//Backpropagation//, temporal networks, etc..
[[Visualizing and Understanding Deep Neural Networks by Matt Zeiler|https://www.youtube.com/watch?v=ghEmQSxT6tw]]
[[Two Minute Papers - Estimating Matrix Rank With Neural Networks|https://www.youtube.com/watch?v=bLFISzfQCDQ]]
--------
Physical implementations:
[[Chemical implementations of neural networks and Turing machines|http://www.dna.caltech.edu/courses/cs191/paperscs191/PNAS(88)10983.pdf]]
http://knowmtech.com/
--------
//More//
Layerless neural networks? See Chico Calmagro's work with Ard Louis.
On the complex backpropagation algorithm
[[Neural networks for control systems—A survey|http://www.sciencedirect.com/science/article/pii/000510989290053I]]
[[Genetic deep neural networks using different activation functions for financial data mining|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7364099&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7364099]]
[[Structure Discovery of Deep Neural Network Based on Evolutionary Algorithms|http://www.merl.com/publications/docs/TR2015-032.pdf]]
[[Genetic algorithms for evolving deep neural networks|http://dl.acm.org/citation.cfm?id=2602287]]
[[Busqueda de la estructura optima de redes neurales con Algoritmos Geneticos y Simulated Annealing. Verificacion con el benchmark PROBEN1|http://polar.lsi.uned.es/revista/index.php/ia/article/viewFile/532/516]]
[[Implementation of Evolutionary Algorithms for Deep Architectures|http://ceur-ws.org/Vol-1315/paper15.pdf]]
See ideas here: Idea for neural network for chemical synethesis and manufacturing etc. Facebook post: [ext[https://www.facebook.com/guillermovalleperez/posts/10153853693416223?]]
!!!__Statistical mechanics of neural networks__
[[Neural networks and physical systems with emergent collective computational abilities|http://www.pnas.org/content/79/8/2554.short]]
[[Spin-glass models of neural networks|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.32.1007]]
[[Learning and pattern recognition in spin glass models|http://link.springer.com/article/10.1007/BF01304440]]
[[Neural nets : classical results and current problems|http://ir.library.oregonstate.edu/xmlui/handle/1957/28802]]
A [[Functional group]] or [[Substituent]] derived from an aromatic ring, usually an [[aromatic hydrocarbon|Aromatic compound]].
https://www.wikiwand.com/en/Aryl
[[Writing a Function in Assembly: Intel Att Assembly Stack Part 2|https://www.youtube.com/watch?v=7ukTs4Bi7hI]]
See also [[Operating system]]
See [[Measures and metrics for networks]]
''Homophily'' or ''assortative mixing'' is a bias in favour of connections between network nodes with some similar characteristics.
__Assortative mixing by enumerative characteristics__
Enumerative (a.k.a categorical) characteristics are those where the possible values don't have any particular metric for being close (i.e. a distance function). Eg.: gender, school
Measure given by ''modularity'':
$$Q=\frac{1}{2m}\sum_{ij} \left ( A_{ij}-\frac{k_i k_j}{2m} \right) \delta(c_i, c_j)$$
where $$\delta(c_i, c_j)$$ is the Kronecker delta which is 1 if the category of $$i$$, $$c_i$$ is the same as that for $$j$$, and $$0$$ otherwise. Another way to write it turns out to be:
$$Q=\sum_r (e_{rr}-a_r^2)$$
where $$e_{rs}$$ is the fraction of edges that join nodes of type $$r$$ to nodes of type $$s$$, and $$a_r$$ is the fraction of ends of edges attached to nodes of type $$r$$. If we generalize to __weighted networks__ then $$k$$ would be the //strength//, i.e. the weighted degree; and $$e_{rs}$$ would be fraction of edge weights joining nodes in the two sets, and $$a_r$$ would be fraction of //half// the edge weight assigned to nodes in set $$r$$.
This is just equal to the number of edges connecting vertices of alike type, minus the expected such number for a random network (with degrees distributions for each category fixed).
$$B_{ij} = A_{ij}-\frac{k_i k_j}{2m} $$ is called the //modularity matrix//.
The normalized modularity (normalized by its maximum value when all edges fall between alike edges is called an //assortativity coefficient//.
__Assortative mixing by scalar characteristics__
By scalar charactersitics we means does that have a metric that gives a notion of closeness so that two nodes can be approximately alike (age, etc.).
Measure by a [[Pearson coefficient|Pearson coefficients]] (i.e. a normalized covariance) for the correlation of the value of the scalar $$x_i$$ at the two ends of the edge. The covariance turns out to be:
$$Q=\frac{1}{2m}\sum_{ij} \left ( A_{ij}-\frac{k_i k_j}{2m} \right) x_i x_j$$
and one can divide by its max value to get an assortativity coefficient.
If positive assortativity, sometimes the network is said to be //stratified//. Others nonlinear kinds of correlations may not be detected by the Pearson coefficient (for example low and high $$x$$ being more often connected with intermediate $$x$$). Other information theoretic measures may then be used, or a scatter plot of $$x_i$$ vs $$x_j$$ for visual insight, as in figure below:
[img class=img-centered [network_scatter_plot.png]]
<small>Note that in this figure, the values, 9, 10, 11, 12 are bins, and the positions of points (which represent edges, or pairs of nodes) within each bin is just used to visually aid in identifying blocks with more density.</small>
__Assortative mixing by degree__
Degree is special case of scalar because degrees may be close to one another (using usual distance function on integers), so use same formula.
If a network shows assortative mixing by degree, it often displays a core (with high density of nodes) and a periphery (with low) structure See (a). If it shows dissasortative mixing by degree, it often shows star like features and is more uniform See (b).
[img class=img-centered [assortative_dissasortative.png]]
There appears to be another definition of a quantity called ''assortativity'' in this [[review|http://arxiv.org/abs/1010.0302]].
-------
|A network partition with $$Q>0$$ exhibits "assortative mixing"|
|A network partition with $$Q<0$$ exhibits "disassortative mixing"|
Can also rewrite the assortativity coefficient in this case as a Pearson coefficient for the distribution of the "excess degree" of nodes (i.e. follow an edge to a node and look at distribution of remaining stubs). See page 5 in [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/17/4_copy.pdf]].
__Notes:__
Given some network and two partitions (assignment of nodes to categories), we can calculate their modularities, and find which is "more modular"
Maximizing $$G$$ is a good way of finding ''"communities"'' of densely-connected nodes with sparse connections between those sets.
Can define scalar measure of assortativity. See page 3 in [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/17/4_copy.pdf]].
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
https://astrobiology.nasa.gov/
[[What if You Were Born in Space?|https://www.youtube.com/watch?v=jTL_sJycQAA]]
https://en.wikipedia.org/wiki/Astronomy
[[General relativity]], [[Celestial mechanics]]
[[Summer School on Gravitational-Wave Astronomy|https://www.youtube.com/playlist?list=PL04QVxpjcnjjuLDeNFWIlc8fcXSUqqxAG]]
See [[Perturbation methods]] and [[Asymptotic approximation]]
[[Handout from lecture|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3128/8/OHPHandoutLecture3.pdf]]
''Convergence'' ...
''Asymptoticness'' ..., is often more useful in practice, because truncated series give good results, while convergent series often don't unless you take many terms
''Asymptotic approximation'' (or ''asymptotic expansion'')... An example is an ''asymptotic power series''
See notes for definitions.
!!__[[Order notation]]__
Big O: $$f=O(g)$$ as $$\epsilon \rightarrow 0$$
(f could be asymptotic to const*g, or much smaller)
Small o: $$f=o(g)$$
f is strictly much less than g
Strict order: $$f=\text{ord}(g)$$
f is strictly of order g, i.e. asymptotic to some constant times g.
!!__Uniqueness of asymptotic series__
If a function posesses an asymptotic approximation in terms of an asymptotic sequence, then that approximation is unique for that particular sequence.
Note that the uniqueness is for a given sequence. A single function may have many asypmtotic approximations, each in terms of a different sequence.
Note also that the uniqueness is for a given function: two functions may share the same asymptotic approximation, because they differ by a quantity smaller than the last term included. Two functions sharing the same asymptotic power series, as above, can only differ by a quantity which is not analytic, because two analytic functions with the same power series are identical.
Asymptotic approximations can be naively added, subtracted, multiplied or divided, resulting in the correct asymptotic expression for the sum, difference, product or quotient, perhaps based on an enlarged asymptotic sequence.
One asymptotic series can be substituted into another, although care is needed with exponentials.
Asymptotic expansions can be integrated term by term with respect to $$\epsilon$$ resulting in the correct asymptotic expansion of the integral. However, in general they may not be differentiated with safety, i.e., when differentiating there is always the worry that neglected higher-order terms suddenly become important.
!!__Numerical use of divergent series__
''Optimal truncation'': Truncating at the smallest term is known as optimal truncation.
!!__Parametric expansions__
So far we have been considering functions of a single variable as that variable tends to zero. Such problems often occur in ordinary and especially partial differential equations when considering far field behaviour for example, and there are known as //coordinate expansions//.
More common is for the solution of an equation to depend on more than one variable, $$f (x; \epsilon$$) say. Often we have a differential equation in the independent variable $$x$$ which contains a small parameter $$\epsilon$$, hence the name parametric expansion. For functions of two variables the obvious generalisation is to allow the coefficients of the asymptotic expansion to b e functions of the second variable:
$$f(x, \epsilon) \sim \sum_{n=0}^\infty a_n(x) \delta(\epsilon)$$ as $$\epsilon \rightarrow 0$$
!!__Integration by parts__ (IBP)
See examples in notes, and problems.
One has to choose the right functions. Nice because it gives error term explicitly, and can often be bounded.
<i class="fa fa-lightbulb-o" aria-hidden="true"></i>Trick of separating integral domain.
__Failure of integration by parts__
General rule: Integration by parts will not work if the contribution from one of the limits of integration is much larger than the size of the integral.
It can still fail in other cases, if for some reason the terms in the expansion can't be generated by the IBP.
!!__Laplace-type integrals__
$$I(x) = \int_a^b f(t) e^{x\phi(t)} dt$$ as $$x\rightarrow \infty$$
!!![[Laplace method]]
For $$\phi(t)$$ real. Contributions near global maxima of $$\phi(t)$$.
!!![[Method of stationary phase]]
For $$\phi(t)$$ imaginary. Contributions regions of stationary phase $$\psi(t)$$ (where $$\phi(t)=i\psi(t)$$).
!!![[Method of steepest descents]]
Most general and powerful. For $$\phi(t)$$ generally complex, and the integral being along a complex contour in general too.
!!__Splitting range of integration__
splitting the range of integration and using different approximations in each range.
<mark>See examples</mark>
----------
!!!<i class="fa fa-lightbulb-o" aria-hidden="true"></i> Bounding integrals
Trick I use similar to IBP
https://en.wikipedia.org/wiki/Athanasius_Kircher
See [[The Horn of Alexander the Great ]]
https://web.stanford.edu/group/kircher/cgi-bin/site/?page_id=517
//Speaking tubes connected to statues//
[img[http://web.stanford.edu/group/kircher/cgi-bin/site/wp-content/uploads/kircher_073-1024x706.jpg]]
//Hydraulic organ//
[img[http://web.stanford.edu/group/kircher/cgi-bin/site/wp-content/uploads/kircher_076-917x1024.jpg]]
http://machinamenta.blogspot.co.uk/2013/07/athanasius-kircher.html
One of the sources I used about Kircher is now available online. Beyond his ideas about organizing knowledge and automating art, his books are just a kick to look through. They're almost like illustrations for encyclopedia articles, but then you see a dragon, or a ladder to the center of the earth, or a mountain in the shape of a ma
[img[http://jorgeledo.net/wp-content/uploads/2009/02/508584-high-tm.jpg]]
Divisimus altitudinem Turris ad Lunam usque in 5 partes; quatrum unaquæque continet 50 semidiametros globi terreni, 2 semidiametros iuxta distantiam Lunæ proxima a centro terre 52 semidiametrum geocosmi; unde luculenter concluditur globum terrestrem pondere Turris extra centrum motum fuisse tanto spatio quantu est intercapedo inter O et N. Videbis pariter pondus Turris globo terrae M.L. æquilibratum multum excessisse pondus globi terræ.
[img[http://web.stanford.edu/group/kircher/cgi-bin/site/wp-content/uploads/kircher_013-1024x829.jpg]]
//Magic lantern//
//System of subterranean fires//
[img[http://web.stanford.edu/group/kircher/cgi-bin/site/wp-content/uploads/kircher_031-1024x903.jpg]]
What keeps clouds together? [[SX question|http://physics.stackexchange.com/questions/267234/why-do-individual-clouds-not-diffuse-into-a-single-less-dense-cloud/267255#267255]]
An electrically-neutral system of electrons orbiting an [[Atomic nucleus]]. If the system is not electrically-neutral, it is known as an [[Ion]]
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
See [[Atomic structure]]
!!Orbitals of hydrogen-like atom
[img[http://pre14.deviantart.net/2c07/th/pre/f/2012/259/3/d/hydrogen_orbitals___poster_by_darksilverflame-d5ev4l6.png]]
[img[http://i.stack.imgur.com/8aDOv.jpg]]
[img[http://3.bp.blogspot.com/-Omvb4pDzar4/VWdXfGcqauI/AAAAAAAAGMM/DtKqBPpns9I/s1600/electronorbitals.png]]
!![[See here|http://www.chemtube3d.com/orbitals-s.htm]]
[[Atomic physics|https://en.wikipedia.org/wiki/Atomic_physics]] is the field of physics that studies atoms as an isolated system of electrons and an atomic nucleus.
See [ext[Oxford course|https://users.physics.ox.ac.uk/~smithb/qam.html]], [[Quantum mechanics]] [ext[atomic physics notes|https://users.physics.ox.ac.uk/~smithb/website/coursenotes/PE_AP_Notes.pdf]]
[[MIT 8.421 Atomic and Optical Physics I, Spring 2014|https://www.youtube.com/watch?v=iwQ49oG-DO8&list=PLUl4u3cNGP62FPGcyFJkzhqq9c5cHCK32]]
See [[Atomic structure]], [[Quantum mechanics]]
* [[Atomic orbital]]
[[Hyrogen atom|https://www.youtube.com/watch?v=ARe9ML0No6A&index=25&list=PLE73AA240E8655D16]] -- [[Other notes|http://www.nyu.edu/classes/tuckerman/adv.chem/lectures/lecture_8/node5.html]]
[ext[Stark effect in Hydrogen and alkali atoms|bohr.physics.berkeley.edu/classes/221/s16/notes/stark.pdf]]
//Structure of the periodic table//
The periodic table is mostly determines by the electronic structure of atoms (see [[Atomic physics]]). See also [[Chemistry]]
There are three rules of thumb, which were discovered phenomenologically (I think), but are justifiable from quantum mechanics:
''Aufbau principle'': Shells should be filled starting with the lowest available energy state. An entire shell is filled before another shell is started.
''Madelung’s Rule'': The energy ordering is from lowest value of $$n + l$$ to the largest; and when two shells have the same value of $$n + l$$, fill the one with the smaller $$n$$ first.
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/9/95/Klechkovski_rule.svg/330px-Klechkovski_rule.svg.png]] (Mandelung's rule)
''[[Hund's rules]]''
[[Teaching Atomic Structure: Madelung’s and Hund’s Rules in One Chart|http://pubs.acs.org/doi/abs/10.1021/ed5009409]]
The [[Atomic orbital]]s are organized in [[Electron shell]]s, and subshells. The set of occupied orbitals, corresponding to the electronic state of an atom (or molecule), is known as ''electronic configuration''
[[Hydrogen|http://www.cem.msu.edu/~cem883/topics_pdf_2008/hydrogen_atom.pdf]]
Standard solution-phase reactions based on reactivities of different sites in molecules, and don't offer control of relative positioning, other than by statistical mechanics.
__Stereotactic chemical reactions__ use molecular/supramolecular components to guide the relative positioning of reactive components.
It has been demonstrated using tip-based methods to juxtapose reactive molecules, or to remove hydrogen from //hydrogen-passivated// silicon (111) surfaces.
Ribosomes are natural examples.
[[Method by Turberfield et al|http://pubs.rsc.org/en/Content/ArticleLanding/2012/CC/c2cc31975f#!divAbstract]] uses molecular motors to guide reactive monomers to make polymers with controlled sequence. <small>Very slow for bulk production, but maybe good for research..</small>
-------
[[Nano 3D printer]] scheme for APM.
[[Talk at Martin School on Jan 2016|https://www.youtube.com/watch?v=50iAoe7bs9o]]
[[Other talk by John Randall|https://www.youtube.com/watch?v=BLcYGmMDvLw&feature=youtu.be&list=UUubwSalcfmvbaTxiKky9KCg]]
Talk by Merkle. Mechanosynthesis, etc.
---------
Structural [[DNA nanotechnology]] for APM:
[[Mechanical design of DNA nanostructures|http://pubs.rsc.org/en/Content/ArticleLanding/2015/NR/C4NR07153K#!divAbstract]] "As the applications of DNA nanotechnology expand, a consideration of their mechanical behavior is becoming essential to understand how these structures will respond to physical interactions. "
[[Direct Design of an Energy Landscape with Bistable DNA Origami Mechanisms|http://pubs.acs.org/doi/abs/10.1021/nl5045633]] "Recently we have demonstrated the possibility of implementing macroscopic engineering design approaches to construct DNA origami mechanisms (DOM) with programmable motion and tunable flexibility. "
[[Artificial molecular machines|http://pubs.acs.org/doi/10.1021/acs.chemrev.5b00146]]. Large collection of molecular machines, from the fruitful field of supramolecular chemistry, mainly. See book "molecular machines" by Ross Kelly.
[[Artificial molecular machines (2000)|http://www.ncbi.nlm.nih.gov/pubmed/11091368]] [[Artificial molecular-level machines.|http://www.ncbi.nlm.nih.gov/pubmed/11933249]]
[[Light powered molecular machines.|http://www.ncbi.nlm.nih.gov/pubmed/19587950]]
[[Computational Design of a Family of Light-Driven Rotary Molecular Motors with Improved Quantum Efficiency.|http://www.ncbi.nlm.nih.gov/pubmed/26670164]]
http://nextbigfuture.com/2011/03/philip-moriarty-discusses.html
http://www.softmachines.org/wordpress/?p=205
http://www.nottingham.ac.uk/~ppzstm/research.php
http://www.molecularassembler.com/Nanofactory/
http://cofes.com/ADMIN-STUFF/Video/Video-Player/VideoId/489/Mark-Sims-Industry-Update-On-Design-Tools-For-The-Nano-Scale.aspx
------
__More molecular machines__
[img class=img-centered [https://pradipjntu.files.wordpress.com/2011/12/animation2.gif]]
[img[https://pradipjntu.files.wordpress.com/2011/12/srg-ic-povray2.gif]]
[img[http://www.crnano.org/srg-iii-pov-animation2.gif]]
[[More animated simulations from NanoEngineer here|http://www.ebioworld.com/2011_12_01_archive.html]]
[img[http://www.cgl.ucsf.edu/chimera/data/shep-may2009/images/finemotion.png]]
[img[https://i0.wp.com/i61.photobucket.com/albums/h53/mocost/worm_drive_animation5.gif]] [[Source|https://neurophilosophy.wordpress.com/2006/08/22/614/]]
[img[http://faculty.ksu.edu.sa/hisham/Nanotechnology/PublishingImages/Animaions/largebearing_mixed.gif]]
[img[http://49.media.tumblr.com/04e905053df4631ce4e7c084255bbdeb/tumblr_mk0o1zGzm01rk5igso8_400.gif]]
[img[https://ri0jbb.files.wordpress.com/2014/04/molec0200jpg_00000031953.jpg]]
[[Atomistic Design and Simulations of Nanoscale Machines and Assembly|http://www.wag.caltech.edu/gallery/nano_comp.html]]
http://www.wag.caltech.edu/gallery/gallery_nanotec.html
https://www.cgl.ucsf.edu/chimera/data/smart-team-jan2009/smart.html
http://www.imm.org/research/parts/
[[Chimera|http://www.cgl.ucsf.edu/chimera/]] molecular modelling software system. Nice
See [[Computational chemistry]]
https://www.cgl.ucsf.edu/chimera/data/smart-team-jan2009/smart.html
[img[http://www.somewhereville.com/blogimages/qutemol_gallery_june2007.jpg]]
-------
//Diamond mechanosynthesis//: http://www.molecularassembler.com/
-------
__Some examples from Nature__
[img[http://www.responsible-innovation.eu/images/011a4.jpg]]
-------
//Books//:
"Nanosystems" by Eric Drexler (1992)
"molecular machines" by Ross Kelly (2005)
"Nanoelectronics and Nanosystems" Karl Goser et al. (2004)
''Adenosine triphosphate''
Molecule that stores chemical energy for the [[Cell]]. Produced by [[Cellular respiration]]
Adenine + Ribose + 3 [[Phosphate]] groups. These are negative, and the fact that these three negatively charged groups are held together explains why the molecule holds so much (electric) energy.
ATP hydrolyses to ADP (adenosine diphosphate) and phosphate, by unbonding one of the phosphate groups, and releasing energy.
[[Video|https://www.youtube.com/watch?v=KJG6HA5xSxY]]
See [[Metabolic mechanisms]] to see how ATP can make unfarovable reactions happen!
!!__ATP to ADP__
__Energetics__
* Separate negative charges
* Increase electron delocalization ([[Resonance structure]]s)
* More possible interactions with water of the released [[Phosphate]]
High activation energy. needs [[Enzyme]]
-----------------
https://www.wikiwand.com/en/Adenosine_triphosphate
[[Attention in machine learning]]
[[Attention using RL|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=15m33s]]
http://etc.usf.edu/lit2go/genres/15/informational/
http://www.learnoutloud.com/Catalog/Science/Mathematics/Page2#go
audible
See [[Human hearing]], for the physiology of the auditive system.
Interactive computer algebra system. http://guillefix.me/augmath
Nice related software: https://github.com/trebor/algebranch#algebranch
__Get examples from here__: https://brilliant.org/
https://keep.google.com/u/0/#search/text=augmath
Automatic simplification is kept to a minimum, to allow notation tricks used in practice for manipulation. I the future, a setting for which level of auto simplification is desired should be added.
It's hard to practice defensive programming when you are trying to give users so much freedom.
It's interesting how having several different representations of the math (in the latex, the math tree, and the html), I think we can be more efficient by seizing the most appropiate one for each task (like checking some property)
__Parsing__
AugMath at the moment does parsing, but without much validation.
!!__[[Animating maths]]__
__Inputing maths__
http://mathdox.org/formulaeditor/ Check this!!
[[MathQuill|https://github.com/mathquill/mathquill]] Slack channel: https://mathquill.slack.com/messages/mathquill/ See also their [[website|http://mathquill.com/]]
__Displaying maths__
KaTeX, MathJax http://docs.mathjax.org/en/latest/advanced/extension-writing.html https://github.com/mathjax/MathJax-third-party-extensions/tree/master/physics
!!!__Interacting with maths__
[[Maple Clickable maths|http://www.maplesoft.com/products/maple/academic/applications.aspx#]]
|This is just what I meant when I said AugMath aims for Virtual Reality as a platform. And it is awesome: https://vimeo.com/150928998|
[img[http://andsynchrony.net/wp-content/uploads/loop_seq_array.gif]]
---------
__[[Computer algebra system]]__
!!Check [[Ket algebra editor|https://sourceforge.net/projects/ket/]]
__Geometry software__
http://www.cinderella.de/tiki-index.php
GeoGebra
__Mathematical document__
https://trac.omdoc.org/OMDoc
__[[Mathematical markup language]]__
__Handwritten math recognition__: https://www.facebook.com/groups/hackathonhackers/permalink/1265209943534488/
http://cat.prhlt.upv.es/mer/
__Other mathematical software__
http://www.matracas.org/sentido/
--------
See stuff in GKeep and ~KTreeTop in Dropbox
http://cognitivemedium.com/emm/emm.html
http://immersivemath.com/ila/ch02_vectors/ch02.html
[[Mathematical markup language]]
http://worrydream.com/KillMath/
http://glench.com/LegibleMathematics/
https://betterexplained.com/articles/proofs-vs-explanations/?utm_source=twitterfeed&utm_medium=twitter&utm_campaign=Feed%3A+Betterexplained+%28BetterExplained%29
http://simblob.blogspot.co.uk/2016/10/outside-box.html
https://unity3d.com/ar?utm_source=facebook&utm_medium=cpc&utm_campaign=ar_global_generalpromo_2016-11-Global-OS-AR&utm_content=AR_ads_2_1200x630-ARINTGDGP-FB_A-newsfeed_desktop
https://techcrunch.com/2015/06/02/magic-leap-platform/
[[Nice review|http://distill.pub/2016/augmented-rnns/]]
<div style="width:200px; display:inline-block;">
<a style="color:white;" href="http://distill.pub/2016/augmented-rnns/#neural-turing-machines">
<img width=200 src="http://distill.pub/2016/augmented-rnns//assets/rnn_preview_ntm.svg">
<figcaption><b><span>Neural Turing</span> Machines</b> have external memory that they can read and write to.</figcaption>
</a>
</div>
<div style="width:200px; display:inline-block;">
<a style="color:white;" href="http://distill.pub/2016/augmented-rnns/#attentional-interfaces">
<img width=200 src="http://distill.pub/2016/augmented-rnns//assets/rnn_preview_ai.svg">
<figcaption><b><span>Attentional</span> Interfaces</b> allow RNNs to focus on parts of their input.</figcaption>
</a>
</div>
<div style="width:200px; display:inline-block;">
<a style="color:white;" href="http://distill.pub/2016/augmented-rnns/#adaptive-computation-time">
<img width=200 src="http://distill.pub/2016/augmented-rnns//assets/rnn_preview_act.svg">
<p><b><span>Adaptive</span> Computation Time</b> allows for varying amounts of computation per step.</p>
</a>
</div>
<div style="width:200px; display:inline-block;">
<a style="color:white;" href="http://distill.pub/2016/augmented-rnns/#neural-programmer">
<img width=200 src="http://distill.pub/2016/augmented-rnns//assets/rnn_preview_np.svg">
<figcaption><b><span>Neural</span> Programmers</b> can call functions, building programs as they run.</figcaption>
</a>
</div>
!!RNNs with memory
See [[Neural networks with memory]]
!!RNNs with attention
See [[Attention in machine learning]]
!!Adaptive computation time
!!Neural programmers
[[Neural programmer-interpreter]]
An autoclave is a pressure chamber used to carry out industrial processes requiring elevated temperature and pressure different from ambient air pressure.
!!__Applications__
[[Sterilization]]
----------------------
https://www.wikiwand.com/en/Autoclave
A type of [[Artificial neural network]] where the output has the same dimensionality as the input, and the network is train to be able to reproduce the output in the input. The key point is that there is an ''information bottleneck'' in some of the hidden layers, where the number of neurons is limited, so that the network is forced to learn a ''sparse representation'' of the data. For this reason, they can be used for [[Data compression]], and other areas where such a representation may be useful.
As they are designed to extract important features of the data, they are a form of [[Unsupervised learning]], and they can be used as [[Generative model]]s
[img[http://nghiaho.com/wp-content/uploads/2012/12/autoencoder_network1.png]]
[[Neural networks [6.1] : Autoencoder - definition|https://www.youtube.com/watch?v=FzS3tMl4Nsc&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=44]]
[[Two Minute Papers - What is an Autoencoder?|https://www.youtube.com/watch?v=Rdpbnd0pCiI]]
https://probablydance.com/2016/04/30/neural-networks-are-impressively-good-at-compression/
!!__Convolutional autoencoder__
https://pgaleone.eu/neural-networks/deep-learning/2016/12/13/convolutional-autoencoders-in-tensorflow/?utm_content=buffer3ec98&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
!!__Variational autoencoder__
[[Deep Learning Lecture 14: Karol Gregor on Variational Autoencoders and Image Generation|https://www.youtube.com/watch?v=P78QYjWh5sM&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=14]]
!!__Denoising autoencoder__
http://deeplearning.net/tutorial/dA.html
!!__Sparse autoencoder__
---------------
[[Generative adversarial network]] are similar, but we learn the cost function, instead of just using l2 loss ([[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=58m50]])
https://www.wikiwand.com/en/Autoencoder
http://ufldl.stanford.edu/tutorial/unsupervised/Autoencoders/
Related to (part of) [[Theory of computation]].
[[Automata theory|https://en.wikipedia.org/wiki/Automata_theory]] is the study of abstract machines or automata, as well as the computational problems that can be solved using them
An ''automaton'' (plural: automata or automatons) is a self-operating machine, or a machine or control mechanism designed to follow automatically a predetermined sequence of operations, or respond to predetermined instructions. Automata include [[finite-state machines|Finite-state machine]] , etc.
!!Finite automaton
!!!__Input affects dynamics__
[[Finite-state machine]]
!!!__Input affects initial state__
[[Discrete dynamical system]] (e.g., networks of automata)
!!!__Output__
[[Finite-state transducer]], a FSM with output from transitions.
[[Symbolic dynamics]], [[Discrete dynamical system]] with output from states visited.
!!Ifinite automaton
Finite-state machine + infinite data structure
* {FSM + Stack} <=> [[Pushdown Automata|https://www.youtube.com/watch?v=Iz9x2UOt0xQ]] <=> Context-free grammar
* [[Linear bounded automaton|https://en.wikipedia.org/wiki/Linear_bounded_automaton]] <=> Context-sensitive grammars
* {FSM + 2 Stacks} = {FSM + array} = [[Turing machine]]
!!__Networks of automata__
!!!__[[Cellular automata]]__
!!!__[[Graph dynamical system]]__
For instance a [[Boolean network]]
----------
See [[Formal language]]
[[Computer - Theory of Automata, Formal Languages and Computation|https://www.youtube.com/playlist?list=PL85CF9F4A047C7BF7]]
--------
[[Krohn–Rhodes theory]]
-----------
[[a new approach to formal language theory by kolmogorov complexity|https://arxiv.org/pdf/cs/0110040.pdf]]
[ext[http://www.eecs.wsu.edu/~ananth/CptS317/Lectures/IntroToAutomataTheory.pdf]]
[[Automata, Computability, and ComplexityOr, Great Ideas in Theoretical Computer Science Spring, 2010|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-045j-automata-computability-and-complexity-spring-2011/lecture-notes/MIT6_045JS11_lec05.pdf]]
[ext[Grail: finite automata and regular expressions|http://www3.cs.stonybrook.edu/~algorith/implement/grail/implement.shtml]]
[[FAdo|https://github.com/Glavin001/FAdo]]
[[Symbolic Manipulation of Code Properties|http://arxiv.org/pdf/1504.04715.pdf]]
[ext[FAdo Documentation|http://www.dcc.fc.up.pt/~rvr/FAdo.pdf]]
http://fado.dcc.fc.up.pt/software/
[ext[pyfst: OpenFst in Python|http://pyfst.github.io/#]]
Build your own finite transducer: http://examples.mikemccandless.com/fst.py?terms=pepe%2F33%0D%0Amoth%2F1%0D%0Apop%2F2%0D%0Astar%2F3%0D%0Astop%2F4%0D%0Atop%2F5%0D%0A&cmd=Build+it%21
https://www.google.es/search?safe=off&q=Automata+Studies&stick=H4sIAAAAAAAAAONgFuLSz9U3SDYsMcwrVkKwc7R4nPLzs4MzU1LLEyuLAdpMsUQoAAAA&sa=X&ved=0ahUKEwiy8aPe1ZvMAhWMSRoKHVBOA0wQxA0IowEwEQ&biw=1605&bih=965
[[FSM in Sage|http://doc.sagemath.org/html/en/reference/combinat/sage/combinat/finite_state_machine.html#sage.combinat.finite_state_machine.FiniteStateMachine]]
https://en.wikipedia.org/wiki/Alternating_finite_automaton
[ext[http://www.cmi.ac.in/~kumar/words/]]
A computable class of [[Descriptional complexity]] measures, based on [[automata|Automata theory]]
!!__Automatic complexity__
[[Automatic complexity of strings|https://cs.uwaterloo.ca/~shallit/Papers/auto5.pdf]] smallest number of states of a DFA (deterministic finite automaton) that acceptsxand does not accept any other string of length |x|. Note that a DFA recognizing the singleton language {x} always needs |x|+1 states, which is the reason the definition considers only strings of length |x|.
!!__Automaticity__
[[AUTOMATIC SEQUENCES |http://catdir.loc.gov/catdir/samples/cam033/2002041262.pdf]]
[[Automaticity I: Properties of a Measure of Descriptional Complexity|http://www.sciencedirect.com/science/article/pii/S002200009690046X]]
[[Automaticity II|https://math.dartmouth.edu/~carlp/PDF/paper113.pdf]]
is an analogous descriptional complexity measure as Automatic complexity but for languages.
!!__Finite state dimension__
The finite-state dimension is defined in terms of computations of finite transducers on infinite sequences,
[[Entropy rates and finite-state dimension|http://www.sciencedirect.com/science/article/pii/S0304397505005797]]
[[Finite-state dimension and real arithmetic ☆|http://www.sciencedirect.com/science/article/pii/S089054010700065X]]
!!__Finite state complexity__
Newest measure in this area.
Paper: http://www.sciencedirect.com/science/article/pii/S0304397511005408
Finite state complexity defines smallest length of input that will produce result under finite transducer (finite state machine with output basically, which i think can describe the GP maps). Then we can apply Ards argument of how many ways of fitting this shortest string in the fixed-length input of interest (say the genotype). This could be the beginning of the formal theory we need! We probably would also want to develop a concept of algorithmic probability (like Salomonoff's) for finite state machines.
[[Finite-State Complexity and Randomness|https://researchspace.auckland.ac.nz/handle/2292/10527]]
[[Finite-State Complexity and the Size of Transducers|http://arxiv.org/pdf/1008.1667.pdf]]
[[Finite state transducer|https://en.wikipedia.org/wiki/Finite_state_transducer]] [[Finite model theory|https://en.wikipedia.org/wiki/Finite_model_theory]]
--------------
//Others//
!!!__NFA based complexity__
[[Approximating the smallest grammar: Kolmogorov complexity in natural models|http://dl.acm.org/citation.cfm?id=510021]]. ,,However, the model allows the advice strings to be over an arbitrary alphabet with no penalty in terms of complexity and, as observed in [8], consequently the NFAs used for compression can always be assumed to consist of only one state... (so not very good measure).,,
!!!__State complexity__
[[State complexity of regular languages|https://www.semanticscholar.org/paper/State-Complexity-of-Regular-Languages-Yu/2efe616ba8b456177e1a1e19e6558b2d7494a854/pdf]]
http://weburbanist.com/2016/02/02/veggie-factory-worlds-first-vertical-farm-fully-run-by-robots/
http://transformingbusiness.economist.com/#
[[Who owns the robots rules the world (idea)|https://www.google.com/search?q=who%20owns%20the%20robots]]
A [[Mode of inheritance]] where the gene is in a non-sex chromosome (an //autosome//).
!!__Autosomal [[dominant|Genetic dominance]] inheritance__
[[Video|https://www.youtube.com/watch?v=-1GVPjWBFqQ]]
__[[Rules|https://www.youtube.com/watch?v=-1GVPjWBFqQ#t=4m30s]]__
* about 50% of offspring affected
* affects male and female equally
* unaffected never transmit
* never "skips" a generation for [[Heterozygote]]s
* 100% of offspring affected for [[Homozygote]]s
!!__Autosomal [[recesive|Genetic dominance]] inheritance__
[[Video|https://www.youtube.com/watch?v=0I6iJMtsTA4]]
__[[Rules|https://www.youtube.com/watch?v=0I6iJMtsTA4#t=1m10s]]__
* If parents are [[Heterozygote]]s, 1/4 of the offspring affected.
* Not present in every generation (can "skip" generations)
* Parents usually unaffected
* If an affected marries a carrier, half the kids are affected.
[[Population genetics calculation|https://www.youtube.com/watch?v=0I6iJMtsTA4#t=1m40s]]
[img[http://freemanlafleur.com/wp-content/uploads/2012/07/ifa300z_stardust_bl_b1.jpg]]
https://www.wikiwand.com/en/Axial_chirality
A [[Composer]] famous for his use of [[Counterpoint]], and composition of very elaborate [[Fugue]]s and [[Canon]]s.
[img[http://cps-static.rovicorp.com/3/JPG_400/MI0003/738/MI0003738578.jpg?partner=allrovi.com]]
__Frameworks__
node.js
[[Meteor (JS)]]
__Hosting__
[[Nice easy tutorial to deploy meteor apps on DigitalOcean|http://meteortips.com/deployment-tutorial/digitalocean-part-1/]]
__Domains__
[[Setting up DNS records for github pages|https://www.namecheap.com/support/knowledgebase/article.aspx/9645/2208/how-do-i-link-my-domain-to-github-pages]] Remember DNS nameservers are servers that contain DNS records connecting domain names mapped to IP addresses (and more complicated things too). //Domain registrar//s, which let you manage domains you own may offer their own DNS nameservers, or may offer you the capability to use a third-party name server (like [[Namecheap's FreeDNS|https://www.namecheap.com/domains/freedns.aspx]]) to direct domain names to IPs.
[img[http://i.kinja-img.com/gawker-media/image/upload/s--LcGCMziw--/nz6rtxietddjqclusrhc.gif]]
Logstalgia: visualization of http request to a server
--------
http://kubernetes.io/
[[backpropagation|https://www.youtube.com/watch?v=_KoWTD8T45Q&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=13]]. An algorithm to compute the derivatives, needed for [[Gradient descent]], for [[Artificial neural network]]s.
''Backpropagaion''. It effectively uses the chain rule to compute the gradient w.r.t. parameters at one layer with the values of the gradients w.r.t. parameters at the layer above (deeper).
[[Efficient BackProp|http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf]]
[img[https://lh3.googleusercontent.com/meJWmYC_T9cKaz8S8k2j6jmtl1etx-hIwqUN_zl-zgvcGRr1egcKaV_zOzwtIXeKQfyDvTjw51awxmEMwd8iJhN4m9ObNRTPCTNlppjfbrIFGo3ieepSq4EIjx9f4xRPrgpjuHo5PaMCsaM8_weYjQ868FpSHcGcGR5L2IsTgJHiI-AwapSYqofABQYhctmN1-QQTeUSUMM6xui7uX0b9WsTQtyrIPHtwWNczcsYy2vedasGcSOLpP8_8vecJ6hCN_PnkpRa2U8KxhdNiGGshcWeFCvJ48CKQfc_JjLoNDB4D8lDPq8KYnPqzW3zAVzTy6ebBFEXvXnMjwF0vun-j9uJsjadbv3XjJscF2Vw1LkA-msoTk7QBDrfdDy1Sp5l15Kug98zDwvsR-14h5Pv4QmIEm5wlGQfaT9vo7kCYP_b40HMu9umj3gGtMcMNiB1hZ56KWj92hF-PlSYLBA3BRsCuGZlhrON8JMvrYpjHOxf6m5ZVv_XmwJKd8EhoZqozIlQVQssZA8SWqBAAGB8KOsSlElGtmlekDxu6MpiEMMRSYVivwkQAWEKBDPDmVVSWWyZ=w943-h661-no]]
<small>[image above, wait until it loads, you also need to be signed into google]</small>
[[Video|https://www.youtube.com/watch?v=-YRB0eFxeQA&index=8&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=24m00s]]
[[See this too|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=35m25s]]
[[Why backprop is more efficient than naive approach|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=41m50s]]
[[Derivatives wrt the input|https://www.youtube.com/watch?v=-YRB0eFxeQA&index=8&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=43m47s]] give you a way of knowing which part of the input is determining the classification, i.e. where is the cat in the image, for example
[[Derivation of the backwards FP equation for the survival probability|https://www.youtube.com/watch?v=m5RuNNvJdjM&index=6&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=14m55s]], solutions using <b>Laplace transform</b>
One of the most studied model organisms is the [[Escherichia coli|https://en.wikipedia.org/wiki/Escherichia_coli]]
[[Gram staining|https://en.wikipedia.org/wiki/Gram_staining]] is a method of staining used to differentiate bacterial species into two large groups (''gram-positive'' and ''gram-negative''), by detecting [[peptidoglycan|https://en.wikipedia.org/wiki/Peptidoglycan]], which is present in a thick layer in gram-positive bacteria
[[Actinobacteria|https://en.wikipedia.org/wiki/Actinobacteria]] is a phylum of Gram-positive bacteria with high guanine and cytosine content in their DNA
[[Streptomyces|https://en.wikipedia.org/wiki/Streptomyces]] is the largest genus of Actinobacteria
[[Streptomyces hygroscopicus|https://en.wikipedia.org/wiki/Streptomyces_hygroscopicus]] produces [[Sirolimus|https://en.wikipedia.org/wiki/Sirolimus]], also known as rapamycin which is an inhibitor of the [[Kinase]] enzyme [[Mechanistic target of rapamycin]]
https://www.khanacademy.org/economics-finance-domain/core-finance/money-and-banking
http://positivemoney.org/ -- [[Banking 101 (Video Course)|http://positivemoney.org/how-money-works/banking-101-video-course/]]
http://demonocracy.info/infographics/usa/derivatives/bank_exposure.html
A ''base'', see [[Acid-base reaction]].
A base that [[disolves|Solution (Chemistry)]] in water is known as an [[Alkali]]
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
!!! __Expected number of times I get a certain outcome for a set of random variables with the same [[sample space|https://en.wikipedia.org/wiki/Sample_space]], but potentially different and dependent probability distributions__
Imagine I have two random variables ($$X$$ and $$Y$$) each of which can have value $$A$$ or $$B$$. Imagine I want to know the expected number of As I get. This will be:
$$E[\text{number of }A\text{s}]=1\cdot p(X=A\text{ and }Y=B)+2\cdot p(X=A\text{ and }Y=A)$$
$$+1\cdot p(X=B\text{ and }Y=A)$$
$$=(p(X=A\text{ and }Y=B)+p(X=A\text{ and }Y=A))$$
$$+(p(X=B\text{ and }Y=A)+p(X=A\text{ and }Y=A))$$
$$=p(X=A)+p(Y=A)$$
And this result works whether $$X$$ and $$Y$$ are independent random variables or not. The only thing we require is that getting $$X=A$$ and $$X=B$$ are mutually exclusive (and similarly for $$Y$$).
!!!__Inclusion-exclusion principle__
https://en.wikipedia.org/wiki/Inclusion%E2%80%93exclusion_principle
!!!__[[Boole's inequality]]__
Set of all states that evolve into a given [[attractor|Attractor]], under some [[dynamics|Dynamical system]]
See also [[Genotype-phenotype map]], as state-attractor map, can be considered as an example of a GP map.
[[Neutral network sizes of biological RNA molecules can be computed and are not atypically small|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/NNSE.pdf]]
[[Turning intractable counting into sampling: Computing the configurational entropy of three-dimensional jammed packings|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Martiniani1.pdf]]
[[Structural analysis of high-dimensional basins of attraction|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Martiniani2.pdf]]
https://en.wikipedia.org/wiki/Basophil
!!__Granules__
!!__Lipid bodies__
Although basophil and mast cell preformed mediators of inflammation are granule associ-
ated, the subcellular location(s) of this important precursor to the newly generated inflam-
matory mediators has generally been attributed to the plasma membrane. Given the
ubiquitous distribution of lipid bodies in mammalian cells and our demonstration by
electron-microscopic autoradiography of [ 3 H]arachidonic acid within them (Figure 39),
we think that lipid bodies may serve as a major source of this important precursor for the
stimulus-provoked generation of eicosanoids by oxidative cascades.
A method to increase learning rate for [[deep|Deep learning]] [[neural networks|Artificial neural network]], as well as [[regularize|Regularization]] them.
[[Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift|http://arxiv.org/abs/1502.03167]]
[[an explanation|https://standardfrancis.wordpress.com/2015/04/16/batch-normalization/]]
They suggest that a change in the distribution of activations because of parameter updates slows learning. They call this change the internal covariate shift. They propose to normalize the activations (to have zero mean and unit variance) to avoid this.
These have been found to work better for [[Convolutional neural network]]s for [[Image classification]]. I think this may be because for images, you care more about relative differences between pixel values, and so normalizing helps remove unimportant information.
|$$P(A|B) = \frac{P(B | A) \, P(A)}{P(B)}$$|
https://www.wikiwand.com/en/Bayes'_theorem
[[It was Laplace who popularized Baye's theorem|https://www.youtube.com/watch?v=yXkEpzexYIU#t=14m20s]]
[[Example application|https://www.youtube.com/watch?v=yXkEpzexYIU#t=16m58s]]
__Problem of bias__
What biases should be used for [[Induction]]?
First attempt: [[Principle of indifference]]. [[There is still a problem|https://www.youtube.com/watch?v=yXkEpzexYIU#t=25m25s]]
Next step: [[Universal probability]]
!!__Introduction__
!!__Method__
|Likelihood + prior -- [[Baye's theorem]] --> posterior|
# Define variables
# Define [[Probabilistic model]] that we are going to consider.
# We first choose a [[Prior distribution]] over the set of hypotheses, for instance favouring simple ones (see regularization below), which defines the parametrized family of [[Likelihood function]]s
# We then [[calculate posterior from prior|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=5m]] using [[Baye's theorem]]
# And we can then [[make a new prediction|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=6m07s]] by weighting over all hypothesis to calculate the ''expected value'' of the output for a new input. I think one can show (see Elements of statistical learning book) that if we knew the real distribution of output given input, the expectation value is the prediction that minimizes the [[Generalization error]]
The last two steps [[are often computationally very difficult|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=8m20s]]. So, [[what's commonly done|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=9m05s]] is maximizing the posterior distribution (MAP principle, above).
//Credible intervals//
__Ways of dealing with the problem of integrating prior to find normalization__
* [[Conjugate prior]]s are particular choices of prior distributioj which give posterior distributions which are analytically integrable.
* Discretize Baye's rule.
* Sampling
!!__Sampling__
[[slides|https://benlambertdotcom.files.wordpress.com/2016/05/bayesian-course-4-v1-handout.pdf]]. Often, we can't calculate the posterior distritbution directly, and so we [[sample|Sampling]], using [[Monte Carlo]] methods (basically just sampling methods).
* ''Rejection sampling'', creates independent samples, but it becomes increasingly inefficient as dimension increases (one example of the [[Curse of dimensionality]]).
* ''Dependent sampling''. A sampling algorithm where the next sample depends on the current value."
** [[Markov chain Monte Carlo]]. Where to step next is determined via a distribution conditional on the current parameter value (1st order [[Markov chain]]). We want to choose starting position, and conditional sampling distribution so that the distribution converges to the posterior.
*** [[Metropolis algorithm]]. Random walk Metropolis. Under quite general conditions the Random Walk Metropolis sampler converges asymptotically to the posterior. [[Ergodic theorem]]... We move based the ratio of the proposed un-normalised posterior to our current location => no need to calculate troublesome denominator. [[Efficient Bayesian inference with Hamiltonian Monte Carlo -- Michael Betancourt (Part 1)|https://www.youtube.com/watch?v=pHsuIaPbNbY]]. To check for convergence, multiple walkers are used (Multiple chain convergence monitoring). Still the measure to use isn't clear. Gelman and Rubin (1992) had the idea of comparing within-chain to between-chain variability. Dependence $$\uparrow$$ => Effective sample size $$\downarrow$$
**** Metropolis-Hastings. See [[here|https://benlambertdotcom.files.wordpress.com/2016/05/bayesian-course-5-vfinal-v2-handout.pdf]]. Help with uniform convergence near boundaries. For unconstrained parameters we are free to use symmetric jumping kernels. However for constrained parameters we are forced to break this symmetry.
** [[Gibbs sampling]]
** [[Hamiltonian Monte Carlo]]
!!__Hierarchical models__
------------------
[[Lecture course|https://ben-lambert.com/bayesian-lecture-slides/]] - [[notes pdf|https://benlambertdotcom.files.wordpress.com/2016/05/bayesian-course-1-vfinal-vfinal.pdf]]. [[notes2|https://ben-lambert.com/bayesian-lecture-slides/]]
---------------
https://www.wikiwand.com/en/Bayesian_inference
[[Bayesian inference exercises]]
See [[Bayesian inference]]
!!1. Dodgy coins
1.1 $$P(C|H) \propto P(H|C)$$
0.75+0.5+0.25=1.5
1.2 [[Maximum likelihood]] estimate is $$C=1$$
1.3 $$P(C=c|X=H) = \frac{P(X=H \cap C=c)}{P(X=H)}\propto P(X=H \cap C=c) =P(X=H | C=c) \times P(C=c) $$
1.4 & 1.5 Using [[Baye's theorem]]
|C|likelihood|prior|likelihood x prior| posterior|
|1|0.75|1/3|3/4 x 1/3 = 1/4|$$\frac{1/4}{1/2}=1/2$$|
|2|0.5|1/3|1/2 x 1/3 = 1/6|$$\frac{1/6}{1/2}=1/3$$|
|3|0.25|1/3|1/4 x 1/3 = 1/12|$$\frac{1/12}{1/2}=1/6$$|
||||$$P(X=H) = 3/12 + 2/12+1/12 = 6/12 = 1/2$$||
$$1/2 + 1/3 + 1/6 = 3/6+2/6+1/6 = 1$$
1.6
|C|likelihood|prior|likelihood x prior| posterior|
|1|$$0.75^2$$|1/3|3/4 x 3/4 x 1/3 = 3/16|$$\frac{3/16}{7/24}=9/14$$|
|2|$$0.5^2$$|1/3|1/2 x 1/2 x 1/3 = 1/12|$$\frac{1/12}{7/24}=4/14$$|
|3|$$0.25^2$$|1/3|1/4 x 1/4 x 1/3 = 1/48|$$\frac{1/48}{7/24}=1/14$$|
||||<small>$$P(X=H) = 9/48 + 4/48+1/48 = 14/48 = 7/24$$</small>||
1.7
0.11111... use [[this|http://stattrek.com/online-calculator/bayes-rule-calculator.aspx]]
P( C=1|H ) = 0.111111111111111
P( C=2|H ) = 0.37037037037037
P( C=3|H ) = 0.518518518518518. Maximum a posteriori
$$P(\tilde{X}=H|X=H) = 0.75\times 1/2 + 0.5 \times 1/3 + 0.25 \times 1/6 $$ $$= 3/8 + 1/6 + 1/24 = 9/24+4/24+1/24 =14/24=7/12$$
$$P(\tilde{X}=T|X=H) = 5/12$$
1.10
$$P(\tilde{X}=H|X=H) = \sum\limits_{C=1}^r P(\tilde{X} \cap C | X=H) = \sum\limits_{C=1}^r P(\tilde{X} | C \cap X=H) \times P(C | X=H)$$ $$= \sum\limits_{C=1}^r P(\tilde{X} | C) \times P(C | X=H)$$
!!2. The [[Epidemiology]] of Lyme disease
2.1 [[Binomial distribution]] as likelihood of number of ticks with Borrelia bacteria is reasonable because it's the prob dist if the probability of each tick having the bacteria is the same, and they are independent.
2.2
$$L(X_i | \theta) = \binom{n}{X_i} \theta^{X_i} (1-\theta)^{n-X_i}$$
n=10
2.3
$$10 \theta (1-\theta)^{9}$$
https://www.wolframalpha.com/input/?i=10+theta+(1-%5Ctheta)%5E%7B9%7D
$$\theta \approx 0.1$$ is MLE
2.4
https://www.wolframalpha.com/input/?i=integrate+10+q(1-q)%5E%7B9%7D+from+q%3D+0+to+1
2.5
https://www.wolframalpha.com/input/?i=binomial+distribution+with+p%3D0.1,+n%3D10
[img[https://s11.postimg.org/o4kfvny4z/IMG1.png]]
2.6
$$\frac{d}{d\theta} \log{L(X|\theta)} = 0$$
$$\frac{d}{d\theta} \log{ \binom{n}{X_i} \theta^{X_i} (1-\theta)^{n-X_i}} = \frac{d}{d\theta} \left[ \log{ \binom{n}{X_i} } + X_i \log{ \theta} + (n-X_i) \log{ (1-\theta)} \right] $$ $$ 0 + \frac{X_i}{\theta} - \frac{(n-X_i)}{(1-\theta)} = 0$$
$$ X_i - X_i \theta = \theta n - \theta X_i$$
$$ X_i = \theta n$$ =>
$$ \theta = \frac{X_i}{n} = \frac{X_i}{10} $$
2.7
[[Beta distribution]] as [[Prior distribution]]
Plot this on RStudio!
2.8
The expected value (mean) (μ) of a Beta distribution random variable X with two parameters α and β is a function of only the ratio β/α
[img[https://wikimedia.org/api/rest_v1/media/math/render/svg/3905662ceed484cba5580951e29eda96f4d2605e]]
2.9
$$Beta(a, b) = \frac{\Gamma(a+b)}{\Gamma(a)\Gamma(b)}\, \theta^{a-1}(1-\theta)^{b-1}$$
$$\binom{n}{X_i} \theta^{X_i} (1-\theta)^{n-X_i} \frac{\Gamma(a+b)}{\Gamma(a)\Gamma(b)}\, x\theta^{a-1}(1-\theta)^{b-1} = \frac{\Gamma(n+1)}{\Gamma(n+1-X_i)\Gamma(X_i+1)} \frac{\Gamma(a+b)}{\Gamma(a)\Gamma(b)}\, \theta^{X_i +a - 1} (1-\theta)^{n-X_i +b -1} $$ $$ \propto \theta^{X_i +a - 1} (1-\theta)^{n-X_i +b -1} $$, which is propto $$Beta(X_i1+a, n-X_i+b)$$
See [[wiki|https://en.wikipedia.org/wiki/Gamma_function]]
A type of [[Program induction]], that can be used for [[One-shot learning]]
[ext[Human-level concept learning through probabilistic program induction|http://cims.nyu.edu/~brenden/LakeEtAl2015Science.pdf]]
Concepts are represented as simple probabilistic programs—that is, probabilistic generative models expressed as structured procedures in an abstract description language (17,18). Our framework brings together three key ideas—compositionality, causality, and learning to learn—that have been separately influ-ential in cognitive science and machine learning over the past several decades (19–22).
!!__[[Causality]]__
naturally captures the abstract “causal” structure of the real-world processes that produce examples of a category.
!!__[[Learning to learn]]__
Learning proceeds by constructing programs that best explain the observations under a [[Bayesian|Bayesian statistics]] criterion, and the model “learns to learn” (23,24) by developing hierarchical priors that allow previous experience with related concepts to ease learning of new concepts (25,26). These priors represent a learned inductive bias (27) that abstracts the key regularities and dimensions of variation holding across both types of concepts and across instances (or tokens) of a concept in a given domain.
In short, BPL can construct new programs by reusing the pieces of existing ones, capturing the causal and compositional properties of real-world generative processes operating on multiple scales.
!!__BPL__
BPL defines a generative model that can sam-ple new types of concepts (an“A,”“B,”etc.) by combining parts and subparts in new ways. Each new type is also represented as a genera-tive model, and this lower-level generative model produces new examples (or tokens) of the con-cept (Fig. 3A, v), making BPL a generative model for generative models. The final step renders the token-level variables in the format of the raw data
Could we decode representations structurally similar to those in BPL from brain imaging of premotor cortex (or otheraction-oriented regions) in humans perceiving and classifying new char-acters for the first time?
//Everything is probabilities, and probabilities can be subjective//
!![[Bayesian inference]]
-------------------------
https://en.wikipedia.org/wiki/Marginal_likelihood
See also [[Induction]]
[[Coccinellidae|https://en.wikipedia.org/wiki/Coccinellidae]] (ladybugs)
Yo los llamaba //escaomnicolor//
[img[http://www.kerbtier.de/Pages/Themenseiten/Coccinellidae/Varianten.jpg]]
[[Harmonia axyridis|https://en.wikipedia.org/wiki/Harmonia_axyridis]]
[[Some species and descriptions|http://www.uoguelph.ca/debu/posters/coccinellidae.jpg]]
[img[https://upload.wikimedia.org/wikipedia/commons/7/7d/Harmonia_axyridis01.jpg]]
https://en.wikipedia.org/wiki/Behavioural_sciences
The study of the behaviour of animals and humans, with a focus on individual behaviour. For the study of collective behaviour see [[Social sciences]].
''Belief propagation'' can describe a particular kind of [[Message-passing process]] in [[Network]]s, and the related algorithm for performing [[Inference]] in [[Conditional random field]]s.
* The forward-backward algorithm of CRFs is a special case, it is belief propagation for the linear chain case. Belief propagation yields exact inference if the CRF graph is a [[tree|Tree (combinatorial structure)]], by computing marginals. [[How to use|https://www.youtube.com/watch?v=-z5lKPHcumo&index=27&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=22m40s]]
* On graphs with loops, belief propagation can be used to do approximate inference. But one has to be careful with divergences (c.f. infinities in [[Quantum field theory]], and loops in [[Feynman diagram]]s).
[[Neural networks [3.10] : Conditional random fields - belief propagation|https://www.youtube.com/watch?v=-z5lKPHcumo&index=27&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]. See [[Conditional random field]], [[Factor graph]]
[[Example|https://www.youtube.com/watch?v=-z5lKPHcumo&index=27&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=7m]]
[[9 - 1 - Belief Propagation- Probabilistic Graphical Models - Professor Daphne Koller|https://www.youtube.com/watch?v=ASsKAaHlhCU]]
------------------
Many general purpose libraries.
---------------------
See also related concepts/models in [[Dynamical systems on networks]]
[[Portal:Contents/Religion and belief systems|https://en.wikipedia.org/wiki/Portal:Contents/Religion_and_belief_systems]]
A ''belief system'' can refer to a [[Religion]] or a ''world view'', i.e. a framework of ideas and beliefs through which an individual interprets the world and interacts in it.
[[Wikipedia:Portal/Directory/Philosophy, religion, and spirituality|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Philosophy,_religion,_and_spirituality]]
$$V^\pi (s) = R(s) + \gamma \sum\limits_{s'} P_{s \pi(s)} (s') V^\pi (s')$$
If the rewards depend on transitions and not just states ([[state-action reward|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=4m15s]]), then it is:
$$ V_\pi(s) = \sum_{s'} P_{\pi(s)} (s,s') \left( R_{\pi(s)} (s,s') + \gamma V(s') \right) $$
[[Derivation|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=33m20s]] -- [[another derivation|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=30m]], which uses the [[law of iterated expectations|https://www.youtube.com/watch?v=Ki2HpTCPwhM]]. This is for Markov reward processes (see [[Markov decision process]]). For MDPs, [[we need to fix a policy|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=54m20s]].
[[Bellman equation for action-value function|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=54m40s]]
!!![[Bellman optimality equation|https://www.youtube.com/watch?v=lfHX2hHRMVQ&index=2&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h22m40s]] (Bellman equation for the optimal value function)
-------------
See [[Reinforcement learning]]
https://www.wikiwand.com/en/Bellman_equation
A cyclic [[Hydrocarbon]], with a resonant bond structure
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/5/5a/Benzene-aromatic-3D-balls.png/125px-Benzene-aromatic-3D-balls.png]]
See also [[Phenyl]]
[img[ortho_meta_para.png]]
See [[Measures and metrics for networks]]
Measures the extent to which a node (or edge, or other substructure) lies on paths between other vertices. These paths can be defined in many ways, but often they are taken to be geodesic paths.
This is a measure of importance because imagine nodes in the network are sending messages between them, we could be interested how often these messages pass through certain nodes or edges under certain assumptions (like that they follow geodesic paths). Vertices with high betweeness but ranking low on other centrality measures can be for example vertices that connect two barely connected "components". Vertices like this are called //brokers// in socilogical literature.
If we use the //geodesic node betweeness// the definition is:
$$B_{\text{no}}(i)=\sum_{j.n \in G}\frac{\tilde{\psi_{j,n}}(i)}{\tilde{\psi_{j,n}}}$$
where $$\tilde{\psi_{j,n}}(i)$$ is the number of geodesic paths between j & n that traverse i. $$\tilde{\psi_{j,n}}$$ is the total number of geodesic paths between j & n.
For directed, same but take direction of paths into account...
Can also define //geodesic edge betweeness// in similar fashion:
$$B_{\text{e}}(i,l)=\sum_{j.n \in G}\frac{\tilde{\psi_{j,n}}(i,l)}{\tilde{\psi_{j,n}}}$$
with obvious generalization of quantities. This is useful for example in road traffic analysis where we are interested in roads not in junctions.
Some problems with robustness:
[img width=450 [betweeness_robustness_problems.jpg]]
Another extension is //flow betweeness// which is defined as the amount of flow through vertex i when the maximum flow is transmitted from s to t, summed over pairs s and t in the network. To see more about flow see [[Independent paths, connectivity, and cut sets (Graph theory)]]. The problem with this definition is that it sometimes doesn't give a unique answer because the same maximum flow can be achieved using different choices of independent paths. The usual definition is then to define the flow betweeness to be the maximum value that this number can take.
This still has some disadvantages because it doesn't take into account all paths, because it assumes paths are somehow optimal (although in different ways.
A variant that does take all paths into account is the //random-walk betweeness// defined as the expected number of time a vertex is crossed by an [[absorbing random walk|Random walk in a graph]] between nodes s and t, summed over these pairs.
Article by Borgatti[51] draws together many of the possibilities into a general framework for betweeness measures.
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8aAJ6Kg88f3T+Y/xo88f3T+Y/wAaAJ6Kg88f3T+Y/wAaPPH90/mP8aAJ6Kg88f3T+Y/xo88f3T+Y/wAaAJ6Kg88f3T+Y/wAaPPH90/mP8aAJ6Kg88f3T+Y/xo88f3T+Y/wAaAJ6Kg88f3T+Y/wAaPPH90/mP8aAJ6Kg88f3T+Y/xo88f3T+Y/wAaAJ6Kg88f3T+Y/wAaPPH90/mP8aAJ6Kg88f3T+Y/xqJplGWwcf/tfX+7+o680AXKQnAJ9P8cf55/Wq4uUI3AHH/7X/wAT+o560pmXafT/AOyPt6jHXPXk4OQD+df/AIOiGDf8EofjFjPFhqvX/sHye5r/ACN6/wBcT/g6DYN/wSg+MZHT7Bqv/pvl/wAP1HPBr/I7oA/38fJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/Nqno7E+g/+K/8Aif19qAIPJHt+bUeSPb82qVW3Z4xgevvj0/Ggtjtnr39PwoAi8ke35tR5I9vzaplIYdgfTPPVh/7Ln8fbNLQBB5I9vzajyR7fm1TE4BPp/jj0/GmeZ7fr/wDWoAZ5I9vzajyR7fm1SqwbPbHbPXrz19v588HLqAIPJHt+bUeSPb82qYkAH9Pf73v/ALI9fvDrjlqvuOMY/H/e9v8AZ/X2oAj8ke35tR5I9vzap6jYnJ5PQdz/AHpB6+w/Tk4yQBnkj2/NqPJHt+bU+PdznOMcZz/ePTJPYflnk4OZKAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPbj3b3/wDiT/nrPRjgj1GP/Qv8f85oArgKuQGUev3vcdx7fz5JBJ8k+KHxw+EXwX0aTxB8UPH2heDtJV2jN9rE1xFB5ilspuigmOeV4x3A5NdT488XaL4C8Nap4o124Fvp2lw+dczFlUImW5y7ADhe59fTcf8AOO/4LX/t5/HX9t39orxd+yF8ENQi1TwvaXcl5YQQTztMTNrN/aqT9lLjBisYs8kDPU4NAH9+Hwo/be/ZZ+M2pXmkfDv41eDPE97azLbm20q6vZJDKShCHzbRMMRKCBnoVyckV9YIYpUEkbq6MqsrAthlOSpHHfORnsw7Dn/I/wDgVp37Wn/BIP48fA3xL8WEOh+FPil4jttQv5ZZ74GWwW21FmYC4Crw2kdCSCO/Jr/T0/YQ/al8IftdfAfQ/if4N1Eahp0kOn2kk2+Nj9o+yDzB8jsMbkPfPJyTQB9m7FwfXscn3/8Arfr3pkSKQx4HI9ff0z+R6ZGDxVny/f8AT/69RcK20e/TjocZx7/5PegB3kj2/NqPJHt+bVKmcHOevGc/1p1AEHkj2/NqPJHt+bVPRQBB5I9vzajyR7fm1T0UAQeSPb82o8ke35tU9FAEHkj2/NqPJHt+bVPRQBB5I9vzajyR7fm1T0UAQeSPb82o8ke35tU9FAEHkj2/NqPJHt+bVPRQBB5I9vzajyR7fm1T0UAQeSPb82o8ke35tU9FAEHkj2/NqPJHt+bVPRQBB5I9vzajyR7fm1T00tjtnr39PwoAi8ke35tR5I9vzan+Z7fr/wDWpytuzxjGO/X9KAITEACeOPdvXH+ef1qAHDkbdw5/9CI7+wz16ZByBuNmV9iMO+OPruf/AOJ/kM5BzStndt3mYznt3GX/AC5Ue/qeuQCdVBZsjAHTOR3PPBPXHbgcZJzuL9qj5ePbg89e55/r0HanjDHGMdP0MnP44H6cnHPnnxN+Ivhz4U+E9V8b+LLn7LoWjQrLfT7lUqm2Rs5dgOkbEZ9TzwSQDvyqgZ4/NuTyO49h+fXgmhFEmeAMfXuWHb/d9+o5JzX8sfxw/wCDlj9k34dfGGX4cWvjeVWTU9Psgvm2m3/StVnsevnnqYh+fQjJr+gX9l39p34eftM+AbDxj4E1IajbzadBd3Dh4mI8yRlB/dyPjll4Pr14JoA+kyAHZe4+vqR/T68j1zUyxAqDx0Hc+rg/yHfse/VqKkheYdcdfUZb+mPXjvnaKIJd7ugJ+Q4/9C/2j6/njnIOQB/kj2/NqPJHt+bVPRQBB5I9vzajyR7fm1T0UAQeSPb82o8ke35tU9FAEHkj2/NqPJHt+bU9s84zjA9cfecev07+n1pmT6n8z/jQAeSPb82qN0Cg+oK+vff6n/ZH+J5zYBLIxGcggDGc/e/w/SoWUkHOeo5IPbfjr9f0PvQBFgbM989ef72P5f8A6881LsX2/wDHvf0z6Z/EdwaaQAhH09eu4+/cKfp7nqxPNOd2AB0688nkjOeQPqOOf4mAJ/JHt+bUeSPb82p6H72T6Yyfw4yf8+ueakoAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzapS2O2evf0/ClU7hnp/+th6f7Ofx9qAIfJHt+bUeSPb82qfsT6D/AOK/+J/X2pivuOMY/H/e9v8AZ/X2oAj8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUeSPb82qeigCDyR7fm1Hkj2/NqnooAg8ke35tR5I9vzap6KAIPJHt+bUhgBBHHPfJ9T6j/ADx71YooArC3wmwEcdzn1Pt7+vX6mn+Vxjg49z7+3+ePepqKAP5zP+DoYBf+CUPxjXI/48NV9e2ny+o9/fqeTg5/yOq/1x/+Dolcf8EovjGc5/0DVu3/AFD39/Y/n7V/kcUAf7/FFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSH7rfT/AOOUtRsTk8noPX+9IPX/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E0jEx3FmGzI3BiOCWOQD/X08EeNND8f+F9K8T+H51uNO1iwgv7SUMjF4Ji2xiUZgM8d/XnIFdPCpUMvPO0ZI/wBpvf3P8s5BNfi7/wAEVPHXijxn+zZ4Wl8SarcalJB4N07ymnCZG2bTxwVC/wAJbr6nJyPm/aeLBGTwcjb7kM+ex/yQOSCSAKRjv2H82H/sufx9qgkljiy8siRxgctI6oo6jkswAzjjJ9euCTaIXJyT0H5ZfHb1z+lfy8f8HBn/AAU+n/Zd+EPjH4MeBNSfSviTq1hJe6Nf2UoOpRJb217C5igeTY2Zbm3PzRnnZwASCAf04TX9gw2xajZO+eAt3bk5yQBgSHk/n0GScmn2rXLQyGQoW/5ZlTkFdxwcg+n8yOeSf8kjRP8AgpN/wUg+ENj4S+MHjjxH8S7rwXqOqWU8El5ptrHp95DbXUZnijmSFCwcFVba+RvHIOSf72v+CFX/AAUuk/4KJfALW/Ed3ot1pGoeEJrbQrt7sv5t1c2k81jPOQ08wUyPbl8DAG7GDkkAH7wQQy7jJLjccZ564J9vQf8A1yCM6Uf3f8/3pKqQlxmJgSV6P2OSR6AdQD/wI9SKuIMLg9f/ALJ/c9iPz9c0ALRRRQAU0/db/P8AFj1/r/jTqYxG1h3/AB/vH3/2T/nqAJGSS2STx3J/vY9T/nv3qTsT6D/4r/4n9faoFJXOO/HP1z6/5+vNT44I9eP/AEL/AB/l6HIBDkknGT7cnHUen+cnknJMqjA6Y4GeP9/rz9PXt1pFULnBPPHP1z/n/HmnUAJgeg/L6+5/yTyTkn4//bp+L4+BP7Nfjb4kLcC1bRvK/fbzHt3Wupy8srKRzbg9e45yuT9gE4Un0/xx/nmvxh/4L361Pof/AATI+OOoWlwYbiH7LtK43DOk+JGyMnvtX9ecg5AP4rv+CZKJ+0Z/wU+/aF+KF0y3VrZ6vceJLq4YrIFt9O0+O9lk3SE/dRCclu+SR1b6x/4L0/8ABRH4tfHP4keCf2Lv2ZNSj1Pw54y8N6X4c1uyN5dZa907w3pVncoILOR4ztvJJxh1JwBkZ35/m5/YV/bjv/2U/id8XdVh0661XVPH+ia3oNmbfcZ0vNV0k6bA6Ks0eWWRlYDnkgEdM/0M/wDBCH/gmL8Xf2uvjTbfti/GjVNStbLwp4v1bVbTw94itYoJbvTr7xFf/ZVg22xkMYtbVNh80bkZSSSaAP6KP+CBf/BOC1/ZY/Z+8E/ELxXo/wBg+JN5YrY6wxtYkBiXRtOGPNaNZyRLPc8MerdCS9f0fCQIh44Udf8AgT9sH0/l6c4GhaPpPhnTYtG0eyjsbC2x5MEe4RrxsO3cWJ+WNe/TaOSATT8U+KNK8JeHtV8S63dwafpekwG4u7q7kEdvHCGZd8jkjaMn29OccgHT+dEy7tyqOclmAzy3rj0J/E85DUBlILKwI/2SDnkjseen8+SQc/xtf8FSv+DkXwF+zf8AEXXfhR4B0OPxQ+muXTX9FupZ4JfLnmiKKyX0aZ+TONncAnO6vvD/AIIe/wDBZTTv+CmsHj/RYvCFz4duvh9DDFc3Fy02b12j0yUsBJdzjpqKjgL0PJOWoA/oyGZM4+53PQ5yw9fqD6ZX0JIInO5WHyj7nB9T15OPw7Ej1y6MgoCBjIBx68t7/wCeBkjFWVbKknsccZ9ce/8An86AK0QdVYSdc8fTLY78cYwPds5PViPF5jAfe43A4A6t7n6fiRzk1y3izx94J8F2txeeLPFGk+H7WFFeW41K6W3jjQq5DOzfdBAJBOeAe4DVw3hH49fBDx3ftpXgz4oeEvEepKqyNaaVqkdxPsJkwxRRnBCnnn7p4IFAHcfEPx94e+F/gnX/AB54nlNvonh6za91GVNu5IFfaSMkDrg88c5PTn+O7/gr9/wce/CXwv8ACrUvAX7J3jCWb4vNqZht7W4uvs8ZhaY2yZayufPGZQccdzjJOa/rp+NXw4f4vfCnxf4AivFt18T6W1ilySuxQ0gYOSVcYO0dVzjAOc5r+FH9rb/g15+I/jD49v8AEPSfiaj6WupwTtp0MFq6lE1iS5PJ0xm+ZPlHz5xnnPNAHw3Yf8FHP+C0XhTwRafGWKC1/wCEdvdPOvLcjUfE5LWkU0tuXBBI+9DjhuARyetfUXwJ/wCDnfxhf/BbUtA/aU8SzWfjmDUfszRpd35QRQG8hf5r2ZX+8q8+hPJJOP7P/gF+wX8EPD37MXw4+FXjXwJpWu3mi+FG0bU7i5Nwv2tm1K+uCziN0AykyjhRwB0K5P8AIF/wca/sE/syfAf4YeM/FXw60Twv4U1uBfNh0azuJvtztJDcyvKsUrOT8wySDjLjk5zQB/P7+zd8Mbn/AIKM/wDBRHxD8TPDsaapp8PxD8N+ImmlKyH7Pb6lb3Tvlt/RenzHggE/dNf62/wU8H2Hgb4V+AdDtI0Q2XgvwlaTqERQJrXQbGGThRz80TdRnpzkGv8AG5/Yg1v46fsneN/AXxR0fwj4pbRPFXiHQX+02tgfs11apqFukm2QldyMisCQ3rySpY/60/8AwT2/aaf9p74EaD4om0G50OfStG8P6bcQ3Susks8OnJbzSENLJ9+S3ZzyOWxggjIB94DJBI59+cfxdfyHv16ZGWJu+bd+GfXPb2x+vSpASoKjGD/n1/z60n+f5+/t/Png5ADBOcc46+3Xr6dP58nBywqRkr1+vux9en3cjJ/E5NTRYIfHIIXn/vof1P8A+sE0jIcHBOMDnj+8wPp2x+fXIzQBHHMUBWTluO/AGWAxz3GeB+p3Goyskhz1UEYPOfvP15OPXueVxxnM0UQw27kjHP4nsfwx36gk9anUBQQO/r/+r/PrQBEoOMMSAAOTnBOWHc/j64HXipEAAIBzz1H/AOs0MCQQPUfpv/xH59+aEBUEH1oAdRRRQAUUUUARtnnGcYHrj7zj1+nf0+tNBY5wSeB0J+nqf89881Ifut/n+KmR9W+n/s1ACtuycZ6Dpn+8/wDTH4Ypu442859cnPX65/WpqjKnJ4/Uf40AKhI3bie2M5/HGT+f9aadxJxkjtjOO49fb19e4JLmBOMe/wDnrTkGFwev/wBk/uexH5+uaABegz6Dr/wP/wCt+lNY8FfYc/8AAm/+J/X2p9MK5B9eAPwZvf0Pr6dwcgBGAMnIOQOPTlvf/ZH/AH0O45Urnv2A6ehY+vv/AJzTUUqTn09v7319P/15p/Yn0H/xfv8A7I/M80AR4YZA3YHpnB6+/wDnJ75Jds5znvnp759f8+lN3n2/I/8AxVPRi27OOMYxn/E/59aAHUxs8Yz36Z/Cn0UAQ/P/ALX60fP/ALX61KGU8A/off1/3T/nqtAEZJJOCTwOhP8Aek9D6Afhj05E3ZOc9OM5/ve/t+lCKQeR+o/2/c+o/P61JQAxs8Yz36Z/CnJnbznPvnP3n9fbH4Yo7E+g/wDi/f8A2R+Z5pqMWJzjgds+uPU/570APooooAKKKKACiiigAooooAKKKKAI03Z53Y98/wC36/h+lKx4ODzkd+f4/f6fpQWIJ6dB6+rj1/2R+Z5NRk5JPrQA5GPQ85I5J6csP/Zc/j14qWmBAO57enYsf6/y5yCS+gAooooAY2cHnuP/AGp7+w/Tk45YCdpXk5xzz2JPv1x/Prg5kYEggeo/Tf8A4j8+/NRA7Tkf5+9/j/L0OQB8YILZBHHcH+99f8+vemTbtvy9R/IF/f24993ODy7efb8j/wDFUHLKfbIP0+bPU+/v244OQCnHPuD9P3eAx5HdgT19vfpzycmSS5RLK6uFIAit5JMkgZMaTNz+h6noO55YiA7wBt7Nx15PbPt9c5GMgk/GH7e/7R+mfsq/s7eJvihqSI1rZR3FuQ7lBk2dweokQ5x7/iTQB/F3/wAFlP8Agv5+0X8GfiZ4j+F/wS8QQeZoPiO50TU4W1LUYmSNVeTaEtZ+SVdPlI7jrjNetf8ABBD/AILLfHz9o/4z+Cvgl8V9Qlkn8UXfmSRGfU5UZV1JIXP+kyEYIvFIyDyWBOMk/gv+zD+x34z/AOCrH/BRD4peMbe7uovC2j/E+21++s2hSW1u9N+x6cZIWcxTMI28zk7w2dwDZB3f6Pn7K/8AwTK/Zy/ZtuPCfirwn8OtB03xVo2l6aker2rXIuVnWCBppAGk2ZeaBXYFcZ2DBIOAD9LFdIkwwyM4BP1Prn09e45JBrm/Ffi3RvBuj3mu63OtvYWab5pCyKFX5+dzsq9EJ/IdTmugLL84YYCcljnHBbnpwBzn3IGc81/NL/wcHf8ABQOz/Zx+A/jL4R+HdVjs/G/ivw+k2i3VvMBfRObSeTMMTSbWI8xD80bdBjBzkA/nx/4L0/8ABR34pftY/HrxD+xb8MNV/tPwv4b8Q6dewWsF5eOwt77Wp7aY+XbSvEB5OlL0XGNwPCmvzw/aP+FHgr/gn18BNJ8NarF9h8T/AB48JQ3zxCKEPcX11FPcMOAJGJNnnLZbOOuef0S/4IP/ALA+peOfEniH9uv9pvXo9b0Xxd4F1M2X/CTKlrH/AGnp2jatqETpLDBGWl87U4WA8xhu2ZAya+BviM2r/t+f8FIvBngCKyudW8DfDb4oy+GUjSMy6dHpcDy28a+YpdhFtuDgnB5AyQGJAP6Uv+DWj9i7wdp/7Lngv9pa40x4/FtzeQRtcSWcSny0EF2n71oxN98swyxAwD1ya/sSUZ+UccY/Vj0/Dp/tdT1r5v8A2T/2efCn7Mnwd0X4Z+D9OtNN0mzt7WZLaz3+SHNqqEjedwPydD6dSea+jVOxmyepG3r3JB7/AE/XqKALQGBj2A/Ld/j/AJzRSDkA+w/9n9z/AHR+Z5NLQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH86H/B0T/wAoofjF/wBeGq/+m+Sv8jav9cn/AIOif+UUPxi/68NV/wDTfJX+RtQB/v8AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFJ2J9B/8X7/AOyPzPNMVixwcfr/ALfv/sj8zQBJRTCwGcdQQOh9XB7/AOyPzP1pVbKknsccZ9ce/wDn86AHUVGXOTjGO3X/ABpN59vyP/xVAEtFM3HZu4znHfHXHrSoxbdnHGMYz/if8+tADqKQj5SO/wD9l9fT/OaiBK5xjtnPsSPX/ZP+PcgE1FFRliCRxx9f8aAHno30/wDjnv7D9OeOYcn1P5n/ABp7ttHseD6/xY7++fy7g5iHzKcHtwfxcevt/LnjkAmjJO7JJ6Yzn/E/59acRkEevf8AHPrUEe6NSMgk47ehb375z+nbJa+9ujbfp3+9juf59x1O4kAkBRd2eeQOQOMFhxyeu3P0I6809ZFc4XPHqMevv7fqORmqSxy78u2V4GM9eT1/p9e5yasLEVJx39x659fy/Uk80ASl1Gc54/8Ar47/AOyf8D3Th13A8DPb/wCv/X8qQJnIYcfhzz9T25+vvTWmt4UbfKiKASxdgoCgMSeTwAFJ9gDz3oABNGmEJ5PToO7/AO0ff+ZPNTYHJwOOegz/ABe/+z+o5zk15D4z+Nfwm8DW09z4j8eeFNNlgTctvfa5p9tM+C4IVJZ1Zj8vQAnrnhCT+R/7Wv8AwXS/Zr/Zd0vUb29+yeK2tPMUJoupi6dyBJgqtr5pOe2M9RycEEA/czePf8h/8VXgPxs/ab+D37PmiXfiD4o+IzoWm2Ks9xPsgbaqxyykgS3luDhIWblh25IBJ/hi/aY/4OffEXxhfUdD/Z38D/EPTb6Nnt1udN0nXbtQ5aV0fMduoA2MgHPTHJ53fmRoF9/wVc/4KW+K18J6j8QvGeheH9ekdPI8RaHf2kCRz3Atk8xr2dFAEVweo+7nJwvIB/bp8VP+DiH/AIJm+BNK1qK3+OCnXbWyujZW0lto+x75Y5RbRsW8RkhXlVFJ2EjI+VskH+X39pb/AIOm/wBqHxf8SH8A/sy6f4U8VaRqc13BYT3E1rDPKqSslsR5Gj6iRuR8nbITyPvEE19I/s5f8GtfxIuY9P8AEfxt8TeG/Fou2hmnikfThIcZ3hl86VuWGQDz1zyOf3t/Zw/4IH/sQ/CaGy1HxF8HfD+o+I7ExPDqETWhKMMlyClo/LEKT83oOxYgH8T3jb9mD/gs/wD8FM9a07xJq3w61Oy8N+JdX06e+m0DxV4ntkTT/t0ct68cdnoFtHhLaR2ChlU8AsAcn+mH9iT/AINhf2dPBGneEPHnxZ1jxjN45srLT9S1DT9W+3anbDWHVjdwsdQ1nLIrFhl4ASN2UGOf6jvhx8Hfh78J9LttH8DaDBo1jaIY7eGHbtjUgKQMInVVQdM8HOa9RjO0tuPXpx7n6+x9uRknmgDwP4UfsyfB74QeGbfw14d8FeFpre08sx3M/hbRBcny4/LXMjWssnSPP+s6nnJGT7ha2FjZRiGzs7aziA2rHa28MCKMscKkSIoGecAY5PXknSxwR68f+hf4/wAvQ5ZsHqf0/wAKAI44FUhlJzwee/Le5/u+v4nNMkm2nCknpnk8ctzwf69sZ4q0BgY+g/Ld/j/L0OYjDGeoz/k/5/Lk4oAElRhwScAZ/wDH/U/T/IOOS8c6h/YvgfxprMbbZNL8LeIdRQkADfY6RqF0hJycfNECT2yeDtY11yxIoIXIB6/r7f5yepyT/PV/wcLftxeIP2Lv2UE8R+FdTurS98SDVtAnFh5rTNHfT6dphVlhYNhkv3HJPUjBI5AP40fjn4u+J/8AwVJ/4Kb+EvBGsxPfeC/CfxW1Hwxq01ndXEhhsdN/tWxG6FIkRiDOMq8g7AsWGa/0nf2P/wBmXwf+yT8EPD/wb8FLINF0LH2YzwiKbiCCAbl8yUj5YP75xkjPBJ/h9/4NfvgA/wC0H4v+Kfx78Q6a/wDaEPjfXPEcdzfQmOZ3uNc00eYnnLvJYTnBDZ+9xxmv9CzHBHrx/wChf4/y9DkAr9On+evv/nJ98xvt6sfrkZ6FsdT6k+vbuas7B6n9P8KQxqRg5I/D39v85PvkAqW9uqszKx+b1z2L9tx7D+XORzc2e/YDp6fjTlUIMDp/n/P/ANfmloARRtBGc5NLRRQAUmB6D8qWigA/z/P3/wA5PJ5y0gbT/PHP3j7/ANe55Jzl1IRkEev+OfX/AD9eaAIlUNkA/XIHrj+8e/P9Sad5fv8Ap9ff/OTyecuVQucE88c/XP8An/HmnUAVpIFZTlj1A4yOP3nofb9TycVTFrtJIYn6nry3bdx/9cjJGc6tFAFMRnHJx7de7d8/Q9+SOTtyZBkDGT2yeecbuevuPyHNWKKAIBjuT+Az/Uf571G33T9R/wC1O2T6Dv6ckjJslQe57D8ix9/X+XcElNg9T+n+FAFQAOu0np7dRuPv/kE8g5zaiUKCQe2P/Hm5699ufx74pVRVOR1/D39h6+/bqRmn0AMfHHJ79v8A69NBUDBGffA9W9/cfkKV+341HQBYHTjpgf8As2P5H8/c1VG0FgpOTjPHcFvc47nqepGBjNSNnaMHnHX8T/MY+nuSaYAB6Z9cYz97J/HP8+Tk0APK4XOfTt/9euE+JXhvT/Ffw/8AG2g6hBFPDqvhTxHpreZDHMVW90fUbZmQOpw2HypGDnoQQGrvo2JyOOAMdexYep9f5ehz5z8UPFmg+GPA3i+91XXNO0kx+Gdea3lvryG2BnTS74xBDLIuXMm0KAcliADnJIB/ke/8Fkv2XG/Y7/aK1PQvh3qmu2I+IPibW9VuUivb6wHmXzS6m3lrBdH5fMnJXG0YJwAa+cv2ef8AgkX/AMFA/wBqKLRPGnw18Aan4j0XV7yxWTWpNW1w3j2c0sMszmePSrpyVt5/MAM5+Yklgcmv2B/aPFp+1d/wVv8Agj4I8dXcHijw7ffEPVNOlt2lSSCW0RBBGu4tKuwoBg4xjaMYIz/o4/s3/ssfCX9nrwVp3hfwH4YtNGtLARrDFbGPYoSGOFcbI1H3YVAwc4xnkAkA/l3/AOCfP/BuB8DfgfpHhL49/tD3/iq38VeBorfxLe6bqovNU02O9hke2khePU9UjiMPlSE4a32kk/uySCfx1/4LmfFOw/aL/bF1D9ln4DWGlzeDzogEaaNZ2mlSGSzeOy3eRpcLDcVU5O/OeGyTmv79P29tcu/CX7Gf7Quu6ZK0F1pPgG7ubaRM70db+yUFcEHoeee5zwef83f/AIJQTWXx8/4Knjxj8WNTs9QsPJ122kh1OeKBiE1eQL/rmYjAj4xnr1GMkA/IvRvCPhqL9o/4JfCS62nVtN8cadpGtWzQxtIrsbxykhZt8mQF/wBYAeme5b/Vx+Ed18H/APgnp+xtpHinWprbw74fi8M+E9Xv7lbG0gCyz+G59QZirSwqxIEjks4J5OR8+7/K8/af+IHgj4F/8FSvid40fTRf+HvBfxVi1Szt7NjIv2e3tgNsTRKxY5JwVGevGSTX6Ff8FL/+C9HjX9tXQNA+GvwWbxL4c8EW/gvRfD2o+HpINQYXd/pug2ujmdVk8slWYXJGEPDrySM0AfPP7Xvxh8F/tX/8FL/iJ8TG8TX1/wCAtM8caB4p0y5W4aW18jR9Yn1h3+zi9NuigWiMwVyNuc5AzX6kft5/8Fh/it+0R4J8Bfsi/sbyad4i0nWfBPhzwXrM9lcLpmo29/p2iizuUifTLa9m8xbiNVJ85ZCSd2Cpz/Pt+yR+xX+0z+0B47s4fDejeJNFGt32n2dzqt3ol4lpcW95I0MmJpUSPZ5TsGO7ADDJJB3f6BX/AATf/wCCA/gX9lzwZpfxF+L2jaH4q8XPb2uv2d/B9jNxbS3phuirJGsriRVYqwJBDEA4I5AP88v4a/sefGzWP2pNP+DnxF0zUJfGuk65oc2sW15e6he3SxjV1EjST3UIuJMeQ+Q64+8CwO7d/sGf8E+f2fvDfwI/Zr+F1po9uLa/vfAmixaqgt0hYTqRI4LKdzncnO4A9eMmv4Ub3SvCVr/wX8+K+m3a2ulaNC1m0EN7MkESuNb1rADSlRu4AwBkccks1f6JnwhutKb4ZeDIbK8tpYI9BsljMM0bp5Y3BcFTgj6Z6nnuQD0hfnVjk4A+ueSD1P8Aj1PPUn+T3/g6Q/ay8Qfs8fA7wJ4d8O3ghHxAtLvR7xTOYPMS4u9ViK4XdvyLcHB689COf6ndf8Z+E/CllPfa94h0nSbWJT5k2oX9taxLt8w8vNIig8ZOT2OcYzX+fX/wdzftCeCfi9oXwS8N+Btb03XL7Q9W2SDSb+C/cub3V3XCW8kh5EikD0JxwTkA/Bz4V/Fn4baN/wAE3fjX4Y8RTWUfxF8Q+Ol1jT0ksrOW7eC6uPF9xKyXkji5VSbqDIVNpDLycDP6L/8ABDH9tH4M/wDBPDTfHXxh+KfiVPD1z4t8Ca3ZeHpJ47Zo7vWzoOoQadb7rm8g2iW9khjJUOwDjCMQVP8AMn4W8A/Hrxlbjw3pPhHxfd6de7ZNtvoOpSwuVLhTuWEqciQkezDHAav6S/8Agm1/wQW/aS/a5i8Of8J1rKab4O0uTT9VTQ/EFnFZMLS3mgurm3AvJEIaWOMoB5edzEYJHIBk32o/tp/8F6P2nodck0m7m+DWi+I9R8Pzah4d1nVYY5NHTUl0+1mltNPsYLd5JLVSxEk5O4sPMYncP0r/AOCyf/BOD4dfsK/8Exvg/wCGdB03ZqujeOPLkv7ywiXUnUal4DgXzrx3luX4RyA8hAZmxksxH9gH7Dn/AATs+Bn7F/gOy8NeAvBmm6PqAtbFtUubIw7bnUolLXNz+7iRT5swaQcnrgkgA18K/wDBwr+yb4w/au/Y6i8K+EJRHqGjX2r6yp8pZWzbyaHeJtUsOc6ecc9SDwTggHQf8EKL62uv2bPDqRPuaPwdp6ngfwz6YD/ESMlh19h3yf3aHHTj6f8A6/8APrnmv82f/gjP/wAFetd/YL+JXiL9nf8AaJsvEOoC98Q3HhLQr28t7+zsbOKG4sJ4n8xkaLyhHp8wB3BcPgtk5P8Ac34X/wCCjH7PfibR7fVE8aeF7USxxMIZvEFiki+YjNhg8wIPHTHByOSc0AffvPr/AJ59z/knknJP+bB/wdE6Wy/8FMvAWteKb28tPAlv4R1xdTdLiY2wc6hoJQtamWO3cmOOUjewON2OCxP90niv/gop+zz4W0S81mXxp4Xu1tLaS4MEHiCxaRwm75VVJmYscDAAz164Nf59/wDwcJft2/CL9r34vy6R8OfBl/rHiabStTs7G801bi/cFZo4SVWGB8hnEbD5ucLx95iAex/8FOP2g/2Y9d/4JWfsy+APhNcaJf8Ai6PVpLW6MeiaNbXrm41KxSPzLq3lnuH3f7ecA4BJbI/X7/g0V+GHjTwb+zZ8WLzxHpxso9V8W3GoWe1pNr21xrF7PG4DRIACjAgDIwSAzYzX8yn/AASy/wCCVf7Un7efi7wr4c8V3t9ovgjwTqWmeIE0/wASaa1lby2tncpe3FvC98yIzSpDtAUFgzAYJJJ/04v2P/2X/A37J3ws0PwF4N0W10ySPRtJt9Ye08spd6ha2yLcXGYkVf3kvmSD5iBuI3HJNAH11geg/Ie/v/nJ5JyStQLNuYrj7uOcHplge/HQY/4FzkYM4IIyOn/1yO/+6f8APJACiiigAqNsZPJ6Dt/tSe/+eOSc1JUTdT9B/wChSUAAKgYIz74Hq3v7j8hUh6N9P/jnv7D9OeOWKgZckn/Jcen+yO/c0kmccdee3uc9T6DPr0HU8gDcn1P5n/GpIyTuySemM5/xP+fWoYW5bcew7e7eg/3T+mepqxuA7/z/AMKAF/z/AJ5/z9ea/nw/4OM/ir4G8O/8E3fjl4XvdVMXiOZLV7exKx7WUaR4jUnJnDcmRAP3f4gDJ/UH9tb9qXwv+y78IPF3i/XLmOG5tvDOoalp4M4imeSB5UXyVyGdt0RwF5OQvJ5r/LL/AOCmX/BQv9pz9vDUvGvizQ73xYPgzDd6hpGpWk+m6g+mySw3F7BEXu3YRAGKC42g8FS5yQooA4v/AII5f8E+NT/b/wD2khZW+n3l9ZeF9XstauvsomKi10421/MZEh4ZBGcsrnaVYBuAS3+tB+y/+zn4J/Zw+HGg+EPCNhBZrDoGiWt8sdhb2hN1a2USzl/KJLt5+8szfMWyxO4tn+A7/gzcv42/aY+KliI2SWDw/rAcsCMkeH7c9D67jj2B471/o/27bgTjsB+Rx6/59qAEkWORSpyMYJwAO7Y6MPx9OCepz/Mx/wAHDH/BR67/AGS/hRN8GND1K2s9V+K3hyWysg0qQXjylbyYGCUZmRsWn3oyGxjGea/pT8R3a6X4d1/U8kGw0bVL0Edc2ljdz5yBnjyV7/icc/5mn/BZ39ojTf2sf+ChHwD8D+IbgS6P4d8Xy6NfLfSbLcQpYaqpDNK21VzMOTxgk8kPkA/Fz4x/soeOvE/7Iz/tj+Mjq9zc6pq81oby7vtQvIGDhblR5lw5U/67I74xyQa/qD/4Mz/hrr+ial+0jrOu2r21pqKW0+mOGfE0f2Xwum4hkQdY26FhxgH7zV+S/wDwUC+JOnzaXH+wb8K7Oa90q1uLDUY7fRVe+sfndLZiDbhoidsOehIHfABP98P/AARr/Y38Ifs2fsp/DHxHo+hW+la7408E2dzrkiKiXE1z9skiYzpsV1bZZx5DEnAXBIByAfsGgZYwMcgAAewzz356Ej+fNfHX7Z37bHwW/Yr+F+reMvi14nTw9Pc6NqU/hwOltJHdanEkkVpE32i7tgFe7MUZIDn5lwrFW3fR3xB8eaH8NPC154n8SX9pY6dZ5EtzeXEdtAmEnkOZZGVRhYyck9CfTJ/zSP8AgqF+138Yf+Ci/wC1/q37OvgrxBqWqeEfC/jzStLHkRzXemRafcatFczN5yyvAsIiQs7khQpDE4AoA1/2oP8Agsp+35/wUM8XeJfhX+z/AKDpes6Dq+q6poem3elapcWN29rZXt3Y2zqdN0Wdld4vLZikpO4j5mIzXgf/AAS8/am/a5/Zm/br1P4W/FO41OLxPpw0TTdX0fVPEOrXsMAuL/UrViqX8I+b/WYJhU5AyScY/bjxv+zp+zd/wSs/YX8V61cr4Xu/jnc+GNI8T+H9e0rU7F9QsLzVtPbVpE8i23SCaNpFWRN4cSKQ3zHj80P+CDX7OPxB/bW/b38R/H74lWV9qWneINE03VItV1Ozlit5ri0k1y8BS4nVlZwZEYAOTl+pycgH+kt8L9buPEPw38F65dY+1ar4e0y+n2n5fNmtw74Ixxuf09OM5FdZJZ2k7M81rbTScZMsETnqcHLoTnv1PJPOck0PDGhR+G/DWjaDAAqaVp1tYRqpGxUgjCDbjsAoI69RyTuNaayiORkfqvJkP3cAt1z0A2HJz+JwaAOY8feLdO+HvgLxL4y1KVLTTvDelzajdSgIEhgik2s20lFABboSBg8kkZr/ACuv+Djf/goRL+0X+1DqvhfwJrn9qeCRp15ZXbR3JSMXltLDbFTbQvLESCsoyX3fUkmv7Y/+C8X/AAUo8FfshfAXUPh6kh1nX/iz4Zv9F09NIneeazu3udRCieO2Lsp26fu2vtOGzk/Ln/Kt+Kel+NfH2qeJPiJ4hN2jXesalcQwXkEkVx9nu767uI8JKd5GwpzjHTkEEkA/0rv+CYP/AATQ+Fn7Un7Bv7OWq/FTQ7fTrSy0C31HTNRsNJtWurmeKZJlaaUfZHYl8ZLSvjI9Fz/Rp+zx+zn4G/Zj8GzeEfBU1xLpcjxyM1xEI2BQylcL58wAAYgfMBjAAJDZ+NP+CL8Mi/8ABM/9mRRlCnhCHOcjo8fb6Zx6ZHOd2f0Q8f8AjfQfAPh++8R+I9Rs7HTbBA1w93cx28WBHK+WeRlCjbGxyexJ6BsgGT8Sfi94K+EuinxH431MaZo+JGFztjbIix5nEk8IyMpxu7kZ7nivgP8AtSfBb9pWDXJ/hJ4l/wCEgi0C4ntdUbZbp5M1vPHbyr+5vLrOJJlGSVPJyMjn+BP/AILe/wDBafxZ48+KXib9nf4I63qkY07VoLGC90o3N5YyrqGq/ZwI5IZPKYFbfsxGGznB5/cD/g2E+Gnxq8DfBX4meIPi/qd5eXPi57zWNOlvrZ7cpHfato9xGcyM2792jdTzk85FAH9R3i3xXovgbQ7vXddu/slhaQzTSzYXhYEeRyd0ig4XJ+93PoM/yI/8FPf+DmzwL+z7qk/hH9lzxXovirxZolzdad4l0/VF06JbO/hkuiIlZX1Rz+7W2bLRxnLH5cHJo/8ABwt/wVt1L4T+GPFn7LnwnuNT0/4m22qz2D6vpwuJg0Mj/YWURxYXaxJOd+AODwMn+fX9mz/gl1Hr37Ov7SH7SH7SU2lX2u+JfBl34y8Kz669rY3jXsp0uPdbLclnnlJS5yqHd8zc5VqAP6sf+CIP/Baf4k/8FCtJ03Tfi/HomneLtS1UWsFhpLW7I9qbqaIPuSzsmzgx8eV/EfnJBNf08F2A6nP1PHUevtx+PcZP+fF/waveApP+Ey0bxLb2Uhs9P8WXVqlysRMKpFrU6p+8A242wrjnoR0AOf6Cv+C6H/BVXTv+CeXww8L6lYNezap4mnl0+FtMad5bed7maCOSRbfJAUoG+bA9ScYoA/oWBbuSPxPv7+w/P2NTHo30/wDjnv7D9OeOf5NP+CFP/BVn4g/to6TrEni261zVvP8AFGow2tzdw3Zit7QatfpDCXkLgbItq4JzlcYJGT/WLPMsMcjuQERCzMeAqr5pZic4AUDcfbOTwSQCKOSRi+7seCCfX6jtz3+uanZvQnjIP5sB3/2f1HfNfz6f8Fi/+Ctngv8AYk8B674T0XVBP4w1zQZJNHv9LuzK+n3g3yfvFgY4dVXBViCNxHXNfgn/AMEOf+C1Hx6/ar/azsfhj8QPF2u+INPlg05ntrlLoxkzHUwWO+aQf8scnjjjqAcgH9+uT6n8z/jTd0m7H8PHOTnrzxn+vTt/FWfokz3um2l2+cXEKyYPBXlhggjIOQPr82emTpk9v7vA/Nx/7KPzPNACZOOpx35OO/v7fz5yCTXMrYYRct2HIzyRyenXH145HzGuV8V/ELwV4G0+W98V+J9E0KAIzo2q6la2QlKl/ljNxKgYnZjAyeo6ivwV/wCCgP8AwcDfs1/sUahL4ensf+EzvHshdpd+HL+S+jX9yspUmyWZd37xQQTnIxyQTQB/Q3HLtjBmOGJHvgk47n/I7k81IW+TcCccc85x83v7g/1yK/hz8A/8HevwD8R+PPDvh+X4ceLGTxJ4g0PQrQNDq22GfVdUi0+OQ5tSMK9wjNnAAHJO5jX9m/wV+Jth8X/hl4O8f6fazWln4p8PaXrlvDMriRIr+ATIjbwGyFfnIznHvQB6Y8sm0+Xlm9CT0+b3P93JHXpg5zl9vL5nGSWXhhzjPzepPp/9bgZ5TxX4v8NeBbCTWvE+t6bounZZRdaneQ2UG5RIzDzZ5EQkKFJGcgZ4BJNcb8Nvi/4C+Jc2rx+D/FGh62bCUxztpWqWt95ZAU/P5Er7eHUjPrxnJoA9mLAevf8AT8ahdyAWXOAOevQF+R83tz7beeDmpEzYMbNvbI+cZxjJHJyf5nr0IyadscllBwvAbrzy2PfnsecZBxyaALFvL5oY5Jxx367iOhPB4/I9RwS0s+T3HA6nnqOeT19/U8k5JRGSI7VAGRz1xkE//r9OSMg5JS4LFCUP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gR9/b+nUjP8AH/8A8HJ3x8/aZ+FXwdjm+H+j6nbaW2sWkDX2n3dzatLZvqjxT72hjG5DCTuUsQVLKSRzX9f6q2Ock9iAfVv6D+fUg5+Uf2uf2T/hn+1t8M9U8CfEjQRrlv8A2ffDTIWaBRFftb3RtJT59vOpC3JjYgYJAI3KwLEA/wAsn/gkjr3jT49f8FGfgT4r8RQ3D3GkeNHN3JJJJMyTec0Em9yCckqd2453A5IPNf68drALWExhiwAGCSSeN3r/ALvH9M1/L5/wT/8A+CF2g/sn/GW++IepeGrSGWHxXqWr6JNDFZIYLWfVbi5gBKPI2RCyg425IHAyQf6jMcEevH/oX+P8vQ5APnf9qv4en4tfs7fFv4cIZPM8XeFp9JRYt5kJe7tpMKEy2T5XG3nGByATX+Yv8dP+Ccv7cv7FX7Xuq+M/gN8NvEmv6TH/AGjJDeo+rRKzXGoSSgBhp8qjhiR83IJ6hWr/AFaXhQqzHJK8g/jIPT0A/QdBzwOufD3wx4rmefWrH7TuGG+ZBnBI/ijf2znjPTqSAD/JY+Dv/BG/9s79rz46a54l+LHww8Q6DbeJdbiudUvkTVWaOOSMB5DINOiJI7nd6ck5r+qP9mz/AINKv2cvBmoeHvGWuePPEM+oRWdlPdabfLqctuLiVbe4njaOacx/JLGyYK9DjAAYH+xTwt4N8M+FGmGhWX2Uv8shLJ8wwB/DFH6Dgk9uSRz2ZcAE5Bx7/wC8Pf8Auj/vodxkgHyl8A/2PvgX8BfAWgeCfD3w/wDB9xJoEISPWW8N6YuozMiqFke5a2MzMpiDAmQkFuSSa+kbuySfT5LJIESFY1ijhRAsaxpuVVVAMKoAAAAwAQBzknTDxqSQDluCc+u7rx7/AM+Tk1IjgE45yPccZJz/AOOnj9fUA/zif+Cyv7AX7W3hD9vL4jftS/A/wJr2qpfaqsttPYNqUEEsVrqlzdKA8FlJGVYS4IDEYJBJBzXR/C3/AILl/wDBWH4M+E9L8FD9mm01BdB0630oXF7Gkszi2LjezTaOzbzjJJJOMZ5JFf6DnifwjovjWCbR9ftTd2LE5iyoB3bwfvJIORjtn7ucmvnPUP2D/wBmnU57i6vPBJkmuJGklfzLQBnYnJOdOJ/MnknrjBAP8/L9qL/gpj/wVm/bo8KX/wAMLL4I6l4Un1eQn7X4aubqxvI1kMsR8uTT9MilABfOAcAgck16Z+wT/wAG+Pxk/ab8UaV43/ay1z4g6eNMvbXVbS01vU/EWoW0kkTLmPy7womwljkYIx1GTk/3reD/ANiv9nzwLqset+GvCH2PUYQuyfzLUhcNuGQlhGeq569c+5P1JY29tplpFZWybYYFCxqMcLuf2x1z79OSc0Afmp+zX/wSx/Zt/Z90jSLS18F+FPEUllaWUfnar4a0+4lZoYVRizXVvK2XK5bJznGcluP0N0LwV4N8KoIvC/hjQ9AQKECaRplnYLs+cFQttFGAMHp05OegJ6xHDgnoBgcnr1/wz17juaqsjkllPHHb0LZJOeMjbgfXkHNAFqMDbnv68/3n/wDiR/j1zi+IdE0rxBpd1pmr2NrfWt1BPbPFdwRzxhZ0kjY7JFYZIP5g88HOskoC44yOuTju/Tj/ADkdCDmOfc8fy8c/XvnPPHfg+/fOSAfzBft+f8G4fwD/AGqvEknxG0vxXqvgnXrO6bVYE8LR3umPLdsl9Ecvp00BLEXJO488Dn5cn8YfEH/BuJ8XNF1OWw0D42/GmWwQkRNH4s8ZKu1WIXAF6QMjGOTjkEZr/QejXKYfptHPQHn3H/189808JGOh/Ue/fr/Pt1xQB/nzaD/wbg/FnWr+2sdd+N/xpjsp5o4rgyeLPGTIImL7yVa+AIGOhOOnOFNfqT+yN/wa7/s+/Br4k+Hvi/4p+IviTxrrGiBD/ZXil9U1W1uPOltriQSx6ldTxuA1sqkOh4Y+pr+tHan979R/hRtT+9+o/wAKAPHvhj8FPhx8IdFtdK8E+DvDmjPAhia80vRbCxuJUJKkSSW8COw2rjBbgM3TOT65DEsaknkHGPUHLA/h079MDGBmlR13MADlcZyfdhxx7n/E4JpHk3Rvt4Ix068F8du+R+eOeaAFLJnA69D19Tt7+ufxz3zU0f3f8/3pKzII5dxdzkHb7ZwzepJ449sk4zy1acf3f8/3pKAHUUUUAFRN1P0H/oUlS0UANj+7/n+9JQQCDnsOOv8At/8AxI/znLqQ4wee3H/kT3+nr1HJ7gFLcVL9Of1wXxjnrx78k5BJpHlk8iZscpE7J7lVkIH4leR16gninhd5fPJXAXj/AGm5/T9QOoBpTG5jZOeQQeD0+cEc+x49M98k0Af583/BzH+3B8aNS8TeEPhTPp02g+Hzcy6BHd2Nw1sb6zl1PUWMk4iSIyElmQhmbICjcc13n7CX7HXg34if8EEfjFpFj4W0rWPF2s+KLK6g1qXSYJtcjafT/GUkixX5hku1UyTISFfkherDJ++/+DkH/gmX4m/aX8P/AA/8YfBvS1h1jw1YT6jq8xtFu3kuY9V1KUMipNaOD5TpgbnbrzgnP09/wbq/AXxl4Y/4J7638NvjhbTXc7+LVjlt5rOSyLwW76zAMR3ElySNrjByQQPQk0AfzZf8GyWtWP7NH7ffxw8G6+0djNFHqOlCK42hvNuNHggQYlKEEtnHGctjqMn/AEjdMuUvLK1vEIKXVpb3KEdCs8aSqRgnghlI5PU8nBJ/y2/26tB+KH/BOv8A4KN+P/jh4attQ0nwVrXxG0i4lNtpt7iTSft4huU+0WzFfmhhcbjEQOpUgYP9u37An/BZD9m79qn4Q6Nq+j6tb6fc+HtD0TSdWXVtet4ZX1Kytl028ZUvLKzdQ1zZzOFw5VSAXYkuQD9evijcy2/wz+Is6DLw+B/FssfHV00DVGUfiyjPUgZPVhj/ABa/28/it451j9sn4jX8sM1nf+HvHupDSJIZXSVikZVWjdQGQ7XbkHPuMvX+hP8A8FMv+Dg/4A/B/QvGHwn8F3N7P4uk0/WNImuNL1Ka9ilXUIb3S4lWKx0qQNl1lxidgQw4JyT/AJ1/ivw18Uvjf8XPGnxouPC/ie70STxBc65Jnw7rLPLbS4jBR2tssctkMIz1PAHzEA/pl/4N8P2APHH7Snx78PftL/FzRb/UfDN/YQW5v9XS51G1aRXecDN1C0OcOGA35GW77Sf9HPwp4es/B3hrRvDGkxRxWGj2aWdtHFGscaRJJMwCIoCoMueOgJU8ENu/zlv+Cb3/AAXT8H/sU/AzRPhDq/hrxvZjSZEZrdNN1+EKyQpCTsXQJABmPjn1GTg197eKv+Dofw5faDq0XhjSvHUGqPbMthJ9g8SOFnLqFYKPD8TNlewcHIPOCcgH6Of8HJ/7WI+G/wCxx8R/hnoXiGbR/E91bXVxbSafeGz1BR/YOtLmOaGaOZf3ksR+XvjnIJr+Kv8AYE/aZ+Gv7Hml658WotT03x/8RPiBpNyt1aeKUtdTuLTVJtPuLC3aCXUZbh1mV5hJG6KHWUgg7hk/KX/BSf8A4KSfH79tL4m303jDXdTOkXlvcQiw1ay1S0uGgkIij+TUJomI8o9fKx8wOezfvL/wSM/4N1vGHxq8IeAfjp8ZdH0/xB4B8SCx1jRrZbOzjlS2iw77ppb67LEybDn7Mh4PynnIB8dfCj9nf9sL/gsn+0P4cn+IVn4x8O/CS/1O40vU7zSdU1ldMt9Lt7kWVsRBaRR24TyPuJuCgfKuRkj/AEX/ANgH9hL4WfsMfBHwh8KfBNnZXtz4XtGtf+Ejl0+KPWLyMwQQj7ReSK1y4AhYgPKeXfIyWz6t+zT+yD8FP2VfA9h4T+EvhgeHrZLKyF5FvtmD3iQqZ3/cWdsBunVmAwSASNxOWr6bjEaeY8hAdVJdyQqhQWJYk8ADBJOcY3ZPBYgE4myGO7hOpwPUj+nftg5AOT+fv7dv7dHw4/Y/+FWveL/EWu2FhdQQ31ui3jWwHnCCdUGZp0AO8n3yVGCa7n9rn9rX4ZfszfBnx94/1vxLo27w5pEl+9vBrmnrdkpIAVSJHmm3gdVWJmHPy5BNf5v37Qn7TH7Sn/BcD9rKb4RfCbVdSuPhHrF5HqEVhe6Zqd5atDNrMz4+2T3NhalmswgJMIJBU42kigCHU9W/aF/4LC/toLcwaRqus/DTwB8QLSa5vra5urmxg0VrGOSSVoYIpYVjEmon5S4XJbknr5R/wVw+A/h/4IftYeGf2ffAFnBdWd94Msb678q3WKRb6O00pJ1ZFUsWElxICTyTnIypz/oN/wDBPD/gm78Df2E/2aY7nwp4Si8P+Ndd8JE+PNRL2ccd9fJelfNKx2sRiHkWtov7yeYjy+WOVx/AV/wcGfEZfBf/AAUvtvFPhq9idrPQL2JZrSUXADfadNJG6Bm5zHgjORzkggZAP7v/ANgD9rT4Bfsy/wDBPD4EaZ8S/G1j4dutM8JsjQXL2qETQgHaRNdwEZMeCMc/LzkE1/MZ/wAF3/8Agv8AyeMLPXPgD+z1rdlq3hTxFpckd/4o0e8tbe/sbqOwltSkc9pPNMh33cpIWVTuiHGRmvx0/ZJ+Gn/BQ3/gqJY+I/Bvh7xHcp4F+G2k3OrtDqug6mts+k29s97cpb3N5rlnA5aIuAYkfBz8hIbPxP8AEv8AYP8AEeqftX+FP2cvCttDH4p8Q+bBOywRyxSalDd2NpdyGNJ0X57q5ZtrTEgMRvJJegD75/4IZ/8ABOL4gfto/tBW/i34rWutXvhdZdJ1i08Q6k9/fvfyWa31+VlmmRt6l4Ig2ZWH7w5OSxP+lx8Ub3w7+xr+xh4s8UeEdG0uxb4a+BLQn7PZW1otw1n5EJe4KxqGZioZjJk5BJJJBr5s/wCCPn7Dmm/shfsifDHw1rukpB8RdNsng1u+jjihSX/Q7KBQIV811/5b9bh+WOckZPrX/BWO3aL/AIJ6ftOFGVYj4DuPOVjy2bqLnkg/Tg9u+TQB/n1fAXUtS/4K6f8ABWbWPFPi5G/sXVIX1x7a3JnsV2ajNdsRDCWhwBEOgwBnJGST9sf8F2/2ndCu9B/Zv/ZI/Z8v7ePVNNiTwB4nsfDrQ6fcXMy3XiOQxaglhIZbhyptsrMhbAQFTgEfzd/sNftw3v7F3xGHjrwJqU2jeI20yTShextOfkmWaLYFgEbnJbp5h6sPTP7X/wDBIH9izx7/AMFBf2rPFX7RnxPvNPutP8LeN7fxml3q6wWY8p7bTt0kc2pX655vH+YBiCW6kNQB/Un/AMG637Id7+y3+xx/aXxB0l9J8Rtr0Goo19BJ9p8qc6hc7xLPFHJhi4PcEkHJIZq/iu/4L5/t1/Ej9q39qbxN+zvc6ZG+neC/FNnaeH2hdGku552kljTbGrMMyPtH3j7V/c3/AMFO/wDgqR+z/wDsK/BXVvh9o+qW0niWw0u1MMuj63b3Sg2unyRkCOwtLg534wPNyCCOpJP8Fv7EHwaP/BSX/goXr/xKtlhurK28ZaDrlx9t8tpHgtjHI4U3MkLZIPHyk5bG04BIB/W3/wAGnn7Jviv4Y/sneK9f+Jvh2TRNduPFLX+kpcwSCWfT7vU9YuIJkaWGFgrwNC4wGGGHzEAMf6bP2s/2hfBX7PPwj8UeKfGWs2+kJP4d8RxadLcNCgkvotKuzAiGWWIBjKyAEEkErwWAFdh+zr8J/Dfwj+Fng/w14fsRZJB4W8NQ3SqYyHubfSLSKVh5aKADIHOPmxuHzNgmv5t/+Dsvx1q/gb9izwRdeH9QS0ubvxFqFtcHfktE7WMbAqkqEZUnOcjkZyTkgH+fN/wUf/bJ8f8A7UX7QXj671nWtRm0jRvFmu2ekD+0p5YJrBLu4ihIQSlAhTaQvzAADnkg/wBIv/Bqz+w94hPxr8LftOXunXn/AAj+q2umJFeOlwbNjDDfzHGY/J6XiE/PnBXkHr/K1+yf+zx4v/ar/aG8HeA9I0651B/GHic2NxOlhNc2olm812M0gIjQE4OZJBznJJ5r/Xs/4JVfsQT/ALDv7L3gv4NazZQwat4eCCXyI4Y4/ls7a3ACRyTAc256SHjAyQMkA/T6yUwQLbqoWOFQkZA4K7m9fx/Xg9vmn9q39prwR+y18Jte+J/jPWLTS9O0bmee7aBYlxFczEt58safdiJ5boTz8pz9Os0cKNJM6wxRrl5ZGWONFG8bndyFUDuWOOeSTg1/nt/8HUP7bHj+z8XeNP2b9F8Y2k/gnUra/afS7W5+0I7RW0MC/NBeNDkC7kGDGep9CaAPzY/4K0/8FrPj3+2z4zuvhp4CvL3w54O8Kay/2XxB4S1Z9OmvbH7XdSGSeTS3R3Hl7SA0p+XIyRlq/nw8caf8QviR410zwxpvi7xP491jVIFKw6trGo6lN5xEQkhUzz3ThUeUJtAwAACOFx237Onw1+Knxh8YeH/Bfw20vVVv/EepWGk3V0uj39zbOt7L5W52j8iMJh+S0pUAtlgTmv79v+CVn/BuL4e+Ez+GviZ+0z4Rs9e8UP8AY9Z0++ggsLZorK/KXyIyyPqkm7yjCG/eKcqw2AigD8J/+CQH/Bu54r/aX8W+E/iB8drTxF4H0DRbzR/FWlXsC6pHFdaho1zHq0FsSsNupSWe2hjYb2GHOSRnP+kn4Q07wj+zb8EvD+i6xqYs/DXw/wDDelaK+p3BAP2WwgFtHLKZHT5nCcln4JIJJBIuW958J/2cfh3LpFjqGj6F4c8L6dfXsWn3esabayrFZWrzSxqHaH52S3CqBETnAAJUBv4of+C1v/Bcm/8AiPrN7+z1+zFrWoWyakJ9D1qCze/1aG7vbPzRI6iygtI9pkUMo3OOQN5I3UAfNf8AwcR/8Fx/EnjzW/Fn7K3wV1xIfB+j3l5Pp/jHw9qEdjqtz9oe5swpubGc3G1UtkdQZiNzueTkn2r/AINFPHnxj8bv8d7nxT4l8T+KIH1SNlk1vWdR1IW8fkaVu8k3U02wfMSADj5jySTX88n7RX/BOD4o+E/2GfCH7YnxMtB/aniTWnsru5uLA2d2whtbC9cOlxdS3Cgm7J+ZcZByS3J/cL/glh+3L8Bf+CXv7NXi/Ubr9x4u+I/hSPUNKm0/UY/NGoMYI1Z4bWxuZC2LI/IXVjyC2RuIB/dT8av2s/gN+zbpF3f/ABX8b2XhyLT4le6ku5LZfLASVjkz3cHAEbHr/Mg/gF42/wCDkT4L6P8AFeHwh4f8T+Gr/wAOS6/aaadSL6QXFjLMUlnz9rblUYEHfnk/NkZr+Uzxt8Y/23v+C1X7S4+F3hDW9UuPBXjEzwJHqWh6zLaFWvRbRh7m81Cytv8AVXWPmAyMHGCa+sP23f8Ag3r1T9nr9nXw94407wzBF4w0fQX1TxJqNvY2rCW4tZ753k2xTu8YCRR5LSvjn5jgUAf6Cv7O/wC0r8J/2mPAtr4y+FXii18TWD2lhJeXFq8DpDdXEcnmRAwXE6jE8cyD5h91uBt59Z8V+PPC3gXRLzWfE+ox2FnZWtzczTysoVIraJ5pWJeRBhURm57ZGTgmv4df+DYn9uLwT8JfhD4l+D/xD1q1t9aPiu5sITdanDYoi2HiLxBAysk6yDhXQYMgwC3Ubq8y/wCC5H/Barxr438WTfsv/so+IL+DxjP4ns/DurT6eNQ1m1l07W9bOjSrs05bRFjaDz9zG5ZNpJY7ASQD9Kf+Cl//AAcoeFf2WvH2keFv2e7nwz49hIeLXJJzpMjWd5FHKXhy8t0QRIMckHnp0z9U/wDBIj/gtpqH/BRPxZY+C/Edhoml6/Np0d9PY6eLESR7o5nHFuVbG6N+NuM9wBg/zZfs9f8ABv8A+MNS/Za+J3x+/ac0K28SeK9YsE8UaHepY29rNCt9M0p3Rz3epTM+wMD80bAtyCd1Zv8Awbr+GdE+DH/BXzxR4AV7fQ9M0zwjCY4r2eC0jTE/iCP70rQxg4iXI+vGSaAP9Cz49fGXRvgh8LvGXj7WruG2Xw7pP9ox+f5YjYfa4oCXMjquMOevGdvOWzX+Xz/wVf8A+CmPin9t/wDal1zw3o/jPUtG8C3Ed3ZPNoWry21osgvGtGIgsrlY93lljkEHk5OctX9YX/ByJ+1Vf/Dn4Q2XhDwT400j7H4s0KWz1e1stUtbppUFxqEoV1tb0bTutY2w4b+HjIBP+bN+zJ8G/HP7RHxqHgDwPq9hpWtapfzTR3eovClsGudVEQJae/sU+/MrHM44JycAkgH034L8M6z4t8UW/gL4a6LH461HW76DRdTu7iEXV7EbtvKMplaK5mMojYOGJDA5wSCWP9yf/BDn/giH4e/Z8tPDf7RPxOhvNG8ZaVepq1nYX1vdFfJ1CdL9QrXCRAIBEgAC42sMDGDX5f8A7P8Apf7Bv/BKzwppHjT9oTwzbeIviRrFqt1aaloGs6aGXXoi1pbztDZ6RrkvyzxK23zwxBAEmfmryz9qL/g4M/a9+KuovoH7Kmu+LdF8Om1jstNiOh+KL+OOK3ia2tl823GmRkLGEA4UHnGBzQB/fn8Rf24/2Xfg6buDx38RNM0J7MukyyyWaCMrvBB8y+h/unrzyvXg1+S/7V//AAcGfsmfCTQtSufhD8S/DfivVrW3craPLpD5ukMgMZB1Gf8AiTGME89Dj5v5UPhR/wAE2v8Agrb/AMFEdNtPHPjzx1a3+j+Jolv5bfUPD93DOYiHkmDm+8XhgzJgDdFnrwSef04/Zm/4NbdAsbg3Xx48G6frskk4mu2it9Oh3s7K0p/eS6h94h8cnGRySGNAHkWtf8HdPxTstRlg0/wZ4TntwQEkMekHIDuP+eR7YPtknOW4/av/AIJGf8Fybb9vvUPF2k/ESLQvDmo6bcxW2kW9kNOVryV5bABMQNG2dlxK33WPsSQah8Vf8G6f/BLDwN8I/EOra/8AA+3h1yx0HW7qK9lv9CgQXVtpNxNCwMnh1slZo92BLuzjnOCf5EP+CU3h7/hVv/BSfxz4G+HFtLaeD9I+LsenWtrbxvcRw6emn2Mio0tskUeBIVIO0LyBg8kgH+p5BKksUUyHKSJHIhHdGDsp6nqCO/Q9TyakJJ6/5wT7+5/PqaytBIOh6OSDk6Xp5bJx832Vc8FcjkHjtx1xzqUASxggE+uMf+Pe3+z+o5601up+g/8AQpKRWChj/u9/94Hsf7o/76HcZLlkDDOOnv8A73t/s/mSOSpyAR1LvHv+Q/8AiqQMGyDwPXI6gsPT3J//AFGjauD83bjkf7X+A/P3oACwKkc8/wCOfX/P601CF3A5+bHT2z7+5/PrQgDE57Dt9ceh/wA96jLoJPLwc84OfQken0/M+mSATKUz8oOf/wBv3PofzHpQ/wB04GeV49eZM9T6c/pnNRKyuSFzxj8eT049Mfr1IYB6tt3cZzj2xjI9Pb+fOQSQD4//AGxP2aPCv7Tnwo8SeFPFVvDKtt4d8QnTllthPm8k0u88gRhgSrmUJtK8g7cAkEH/ADRNO/Y2+NP7Bf8AwVB+Hd3oWn67Do154/1jWordp9Qhs5rea9luIswPEImQo6kAjGCfmPWv9XqaOOVXjkXcrIVPI6N5inse2fXr3IOfkT4pfsQ/s6fGTx9oXxG8d+Dv7U8T+HwBpt95toPJG0J0k0+Zz8iL0ccsepBoA9A/Zt8b6v8AEH4SeH/FGv2q2t9e586IYwNsNu4xgDvK3buOcZz7+jKQQvQf4t7n3OPqM5Ga5zwx4U0Lwdodv4f0G3FrptpkwQbkO0ldv8KIDxGv8PfvgZ6CFQu4D0/9mI9B65+uPSgCaiiigBpBII9x+m/2PqP1545hqxVegBwQsMgj9fVh6f7Pr3HfNNuJUhjaWRtqRqzMfRQGJP4BCT7d+DRXzT+1T8f/AAd+zz8J9e8X+LbyC1gl0rXobJ5LyK1xeQ6ZM8R3OrkkSPGQAAc55zg0AT+M/wBrX4B/Du9bT/F3jey0y5LNH5Uslsp3IWJ+/dxnjYff64Jr598Vf8FT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95d+t4t/LS0iN8kAKenUYHcv1OenI+ucZPJpYlJUr1z09xznvxnnjtz1OTUMG5jJ6HGT/wB95PXPQdfoTyObKDCsAcAYznvyxGPy+vA4zknz6E1OnUrTSdKq0paapxlOC0dtLXd/W+tkapWjKN+sdfO9/wA/w631DaME9QMZPvuI4BOe36joAaiuEDoyZAGFGcc/x89frn1BH91syKc5APTOR9N3UZ/2RjP94dSMlkh3KwJ+bAx78yKDk+wzyfXsSCVKcfZuNWV17rw+ykpXbjbq7tR+VlvdjTUYu1rLR7aq8k769b3a66dm3+Vf/BQ/9gnwV+1j8K9c0afQtKl1e2g1XVI7u5j3SPcJameIrkkb/Nt1KgclmUHJPH8UP7NPxM+L3/BKX9qd/Bvi3/hIovB/ivxzeoSLaS20xdOhnkkjDyBVXygtqArFu4+YkV/pQSwK0Lo6K6yK6OHUMpQhlYENkfMCcg9RwQcEV+DP/BX/AP4JneHP2qvhrq/i/wAL6cYvF/hnRppdJj0mwjtZbi8JnjAa4tEWQORMTvwW6ZyV5/s/6Mfj5Ty+jiPCbxRVLHcI577TB4apjHzyy+ddTp06lN1YyfK5OD+OKoRjGSV3c+ZzrKXKP9oYP3atLlk+VW50nJ6Wd9LO/wDM2072kz9Sv2Wf2o/AX7SXgKx8W+FdU06Vb1lVbe3vEmkwUDgqPMY9G9emepzu+p3kDlVU5AyM+pJPOQenrj1xk81/nP8A/BM39uT4g/8ABNr9obS/2bv2j7mbwv4a0qG38271XULi5uFna5e12tHfNbk52rjc3UMeuDX9+PwL+Nngr41eB9B8YeD9Wj1Ox1nTYr+KdAgVoXllQONksgHIHcjnGSQWr81+kb4J4nwh4pnmvD7lmXBObqOKweNpfv6EMPinVjh6aqwdSM5J8l253ejaep15DmscwoezqtQxFGycbct2rq7u105mlbvu7s9udFztxkEYPTnl89vTAGe5Jzxz/Ip/wcsfsy33jH4e/D3xX4Ug+yX2k6wNXubm2i3yEWl9dXBdiQ2MBB9AQeQM1/XkFWRNwIJwOe38XqSe3Pf7pzknP5kf8FRPhZ/wsX4A+JStnHdHSPC3iG7bdEshjEVhfS7huRsY25z1AxyTkn476Ouf1uGPFTJI16kcPgcTi7VlKahGdKpCpGMal2k1f3rSTs3Hdts680oxxGBru/NKMVZ8revM9m27Kyu32aV3Zs/Jb/g2Z+KuseJP2ZfG2k+JNal1C90rxjc6REbhwZFSx1fWrMIqgggKIAuOuAM5INf1KpKrFgg5A5I6H73pz2Gfx5ODX+e9/wAEDf2vNB+EXxl8Rfs832qx2194m+Lni3ybN3UOwj8Xa0flRpAcATj5Qp4I4B4r+93xf8SPB/w68NXfiTxXqa6dplra3Fw1ywU8QQvIxJaRB91M8sCcjJBr9D+lpwVmOR+J854HByxD4rxCx2Ahh6bm1TqKVJP92m43lTdk/O+qizy+GsRGph5qc0o4ePJK+ifvPu9dNX6re3MdXqniTRvD+nXuqa1qFrptrZp5k1xeTLDEqKzjczuwAHpnHQ8nJJ/mq/4Kt/8ABZzwb8F9C1/4e/DK7OueJUkureC+8M3rXkz7pZ7SMqIXZT8yBwcHgnj+FvhP/gq//wAFvv8AhMdbk/Z8/ZS1ax8Yaj4nnuPDeoC3ultLu3uo7eQukb2sl1KH85NowQ2MnByK+Uv+Cb3/AARp+MP7R/j3Rvil+03YeJNJsbgWk9z9qvNS1O383et4wKXgjRsszZz1GeMDB/YPBjwE4O8NMsyzxQ+kHWjhOHnTjj8NlNaS+uV/Zy0k8NKpGrLWEkqTg1OLvtynBmeb4nF4ieByeLlNe5KpG/Lulo7NbO907qyW/MfKf7LP7Dn7Wn/BUT45wfEH4ta74mj8EaF4nh1uz0vxdYeTaXWlyxoxgtnmgUvGz3z8qxOVkBJOTX96H7Iv7D3wg/Zd8K6bpvhXwZomlararayC9sI2V/NRP3jD58Zd8MQQec8k5I9++C3wN8F/B3wX4f8ACXhrRtKt4dE02305Lq30mxtbi4SJnYPcSQwB3dvl5ZmPCgkHk+1+UyuGA4HHHQYLY47f/WHJwRX4746fSO4g8UsXVyDh+Mcg4Rw054bA4LA01g6dTL6dScMPOqqMaPO6tCMZzjNP3pOMm1eT9TK8koYSf1iterXtFyc25Pmd20r3ej5reXfWSUQttADYAx169Wx2OOmfXlckkU8dGUjoM5HfHA6nofb60plRThjg9B7nJHc59Oo7nrjJljXcCT/s9AcEZb1PX1+pByBz/NNCmqF6NH35OzqV5Nye7bbbbfXa+jukk1Jv3HHmlzOySs1HRdX06JW9Xe2ul27iqY9SOO/U+3cfj04AzUy/KhI69/8Avogd/T+nfJqFtqEnPcAnHucDrjtz1wPUgipV+dWU/nx6tg+3X/6/NdcXTTlTT5qiV5N2u3rrq9Ol9XpbW/MjRapprorrXvLuu61ts3G+qK12y+USBu5xwD1ycdu/J/A9cCiAER7mPVeB6DL9s54K8f7xGSQcpKu2MrjPI69DhpOeh49O/T3pC2FCnv1x2yWxyfp9evJC1x1avsKVe6tzxVKG13Jya6rvyt77rXe6SXK4taRlzXet99dutvO1lpdM57xJq9vomj3Go3EqRxRYBd22KOJDySR/dJxnOe5BzX+bV+3P42+IH7X/APwUJtfhpbX+p6zovg34leHJDahftNtBbm7SZzwrbVIOSSeOeMkGv7ev+Cq/7TFr+zL+yX458fR3cUV3pYJXzHVFAWz1KXJYsMcxc88ZOcHmv5EP+CGPh5v2qP23/jZ8Sr+0ivlnmtNVikeJLhUMFlGQyF1cLy2dwwfvfMSMn+4voo8OQ4O4D438S8ynGhTwmCqYanUqwXPCteklOk5O6d68FddHZyknJnyGfV1isThsFFXcpQdk201d2v3Vltve73Vn/bl+x38HNP8Ag78I/DejWFrBam50Hw/cTrAu0ecdNheQsM8NvdiQedxIwSDX18ikLk85xg88ffwOv+z/AOPEdiTgeHNPGn6RZWagKLe0tYMYA2iGFY8ADoPl6dBx1wDXRL8qbfxJ7dTk9fXH61/G2d5tjc/4pznM8dJ1p1q9SftpJrnbnZStdp3il1vfd6Xf1FGnClhacY6KMVp21a76Xvfy+bI1PzMPc49zlsnr6DgegGTuzmaMZyewBH6tx17g/njk4OYVxnoc5Jzjt++75yM5GfQgAgmrMYAU45zjP5uOn/AR+Z5NeRgOd+2c1a0rK/b3nfd7/wDyOrabN42sttk//Tiv+C79NW1dw/5/p6/59c81b3hVGCOAM5z/ALeO/wBf05qPgenP644H+efqTzSGPjOeT0/M+2f/ANfXAArthDkUktbtfhfXd927N9d2xpKOi/X9SwhLAk9jjj/9ZpSARj6fpu9j6/y54OWxDCke4H5Ubxz1447erD1/2f1HfNU7dbfP19f63uhjcJ/eP5f/AFqcEUjIJx/9cjuP9k/55Ldh9R+v+FSKNq4P+eXPr7j9fTJmN3pJJJLTR9Gu7fRfmtbu4LRRRVgFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFQHq31/8AZpKnqIqRk8dR6+sh/wA8/n1oAaFJ6c4+n9T/AJ9aeilSc+nt/e+vp/8ArzRGRyPU/wDxXv8A7P6jnrSEnLcn8z/jQAr9vxpuRsx3z7/3vr6e/wCtJye/tznuWHr/ALP6jqc07YfUfr/hQA6MEbs98Y9+v/xJ/wA9X1G2QAM9scZ7Z9/85Pvlycrzz/8AtSD19h39PTJAHUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFV5P4/wqxUMinDEe31/i/+Jz17jqc0ntL0/wDlnn6fete4QFs9PQjn/wDX/n1NIM4cew49w3+f/r0gGfzA/Vh/7Ln8fapscHAGcAc+xbGcg5655zz9c1lG0aUtLrb8Za6/4b+rW2rIpqSi1Lyt0736vv8AffRNmfcjMZx19foW569uvr8xGTgkttCArg8kdzjkfMf/AK+PbrxmpJgTuXP90d+7Ov8Aj+GBzyajtsEOOu0/nyR6nsen05OK46Tj9UxSj2elt9V1f3pu/VO7swp6SlB21as9e73+Sb+5atlXUyPsNxz3J/Dnnn6fy9ef81D9oL/lMX8UyP8AooHh38jrkgPX6fXJPXFf6Vepgmxmx1GD+Rf39Mn9OSa/zUf2gyB/wWJ+KXr/AMLA8Pdh/wBBtgO/sT+JxnDGv7G+gwmuM843v/ZdS+utk99+zWn4Xdz5ziZ/7PGn09pHXy5le/nqn2spep/o0/BPP/Cqfh7z/wAyf4dyPb+zLbtnv6duTnvXrERJdhg9ODjOeee/+e/NeVfBEA/Cn4dgnr4P8Nge5GmQD16H+pzgDJ9fGxFYA4OOuOeS/cdPuj/65yT/ACnns1S4gzurNr2dTH42EW3s/rVVee/K3/m9X7tG8oU2noo00+uyfnp8Kdv7z7Svm3REcEzscKgyWPAwC3U++c/45r+JL/g49/aaudXufEX7NujXdxNcXpWYWtvJvBDO0B/dAkn7+Sfcg85z/YL+0h8SYvhT8E/iN47MiI3hzw9LqQLnCjZcwxZJJwAA/wBSSepBr/PBu9d1j/gpj/wVOtXjRr+wuVltjHbO8sDGHWIo/wDVAOmfk5OPXpnNf099D7hN5Pn+eeIeYQoVMsyOlVqVKuJVP2dDF+zo1sPUi6iko2hGUudW5XdXTfMeBxHiZTjTwcLqdRxUUr3lHmmpLTXra3a1m2z+nT/ggh+xwnwR+C2j/Eya2t4rzx14bhu52EYS4Z/3MX7zgNn9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The effect found in many [[Genotype-phenotype map]]s by which some phenotypes have many more corresponding genotypes, than other phenotypes. This effect is important in [[Evolution]]
See [[MMathPhys oral presentation]]
[[Examples of GP map bias]]
!![[Simplicity bias]]
!__[[Effects of bias in GP maps]]__
!![[Arrival of the frequent]]
: [[The Arrival of the Frequent: How Bias in Genotype-Phenotype Maps Can Steer Populations to Local Optima|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086635]] [[pdf|http://journals.plos.org/plosone/article/asset?id=10.1371%2Fjournal.pone.0086635.PDF]]
--[[The structure of the genotype–phenotype map strongly constrains the evolution of non-coding RNA|http://rsfs.royalsocietypublishing.org/content/5/6/20150053.full]] [[pdf|http://rsfs.royalsocietypublishing.org/content/royfocus/5/6/20150053.full.pdf]]. [[Notes on the RNA GP map bias paper|The structure of the genotype-phenotype map strongly constraints the evolution of non-coding RNA]]
!![[Common features of GP maps]]
[[Examples of GP map bias]]
!__[[Origin of bias in GP maps]]__
* ''Constrained and unconstrained parts''. See [[The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype–phenotype maps|http://rsif.royalsocietypublishing.org/content/12/113/20150724.full]] [[pdf|http://rsif.royalsocietypublishing.org/content/royinterface/12/113/20150724.full.pdf]]
* [[Algorithmic information theory]]: Shannon-Fano code, universal probability. See below. See [[draft paper|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/APrioriProbabilityComplexity.pdf]].
* ''Random finite transducer''. See [[Simplicity bias in finite-state transducers]]
[[Brownian motion]]
[[Biased random walk|http://www.youtube.com/watch?v=Kn6wzdRAdiE&index=1&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=56m10s]]. probability distribution is Binomial
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
https://www.nervanasys.com/accelerating-neural-networks-binary-arithmetic/?utm_content=buffer77278&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer
https://arxiv.org/pdf/1602.02830v3.pdf
Visualization of binary files https://github.com/corkami/pics/blob/master/README.md
The binding problem is expressed by different authors in rather different ways. However, it generally boils down to the question of how the visual system represents which features are bound together as part of the same object.
Tackling this problem requires appears to require [[recurrent|Recurrent neural network]] [[Spiking neural network]]s.
Our laboratory is now exploring the effects of extending the VisNet model to include top-down connections between layers and lateral connections within layers, and spiking dynamics with spike time dependent plasticity, and using this more biologically accurate cortical model to investigate the emergence of polychronization and its role in the development of binding neurons.
A key limitation of the current purely bottom-up VisNet architecture is that the firing rates of the neurons are not able to specify which features are part of which objects. For example, consider an image consisting of the two letters L and T. On the V1 input layer, each of these two letters is represented by one horizontal bar and one vertical bar. So when the two letters are presented together, there will be separate representations of two horizontal bars and two vertical bars. In the output layer, there would be separate representations of the letters L and T. However, it is not possible to read off from the neuronal firing rates within the network which horizontal and vertical bars are part of which letters. <mark>The correct binding between the bars and the letters could be determined if it was possible for neurons in the higher layers of the network to interrogate not only which bar and letter representations were active, but also which synapses between them were active thus specifying which bar representations were driving which letter representations. However, it is not possible for higher level neurons in the network to read off the activity of synapses in such a direct manner.</mark>
In this case, during visually-guided competitive learning, some random subset of neurons in every layer of the network, which we shall call ‘binding neurons’, will become tuned to respond when a particular low-level feature such as a bar is driving the representation of a specific high-level feature or object such as a letter T or L.
This process could occur through polychronization within a spiking network by activation of a temporal attractor loop for each type of binding neuron similar to that described above. <mark>?</mark>
the binding mechanism proposed here is potentially so rich that it would be impossible to describe the process at a high psychological level; it requires a description at the neuronal level.
,,Although backpropagation networks might be efficient at learning arbitrary mappings, and solving narrow tasks like face recognition, they would not be able to represent the essential binding information needed to semantically analyse visual scenes in the same way as the primate brain. ,,
It is hypothesised that a large spiking neural network model with a distribution of randomized axonal delays will develop many such binding neurons if the model incorporates the following elements:
:(i) Bottom-up, top-down, and lateral connections;
:(ii) A randomised distribution of axonal delays;
:(iii) Spike time dependent plasticity;
:(iv) Diluted synaptic connectivity, leaving many hidden neurons to be driven primarily by lateral and top-down connections;
:(v) Inhibitory interneurons mediating competition within layers, and therefore competitive learning needed for binding neurons to refine their selectivity by STDP.
<mark>There are other way in which Equation 1 is satisfied other than neuron 1 causing 2 right?</mark>
Extensions to the theory: binding neurons can learn to represent many different kinds of relationship between visual features
The top-down connections guide competitive learning in lower layers, thus driving the formation of lower level visual representations that are modulated by higher level representations. <mark>How does this work precisely?</mark>
!!__[[Self-organization]] in [[Spiking neural network]]s via [[Spike-timing-dependent plasticity]]__
‘polychronization’ [12]. This phenomenon involves the network learning temporal memory patterns, each of which takes the form of a repeating loop of neuronal firings. These temporal memory loops self-organise automatically when STDP is used to modify the strengths of synapses in a recurrently connected spiking network with randomised distributions of axonal conduction delays between neurons.
[12]: [[Polychronization: computation with spikes.|https://www.ncbi.nlm.nih.gov/pubmed/16378515]] -- [[pdf|http://www.izhikevich.org/publications/spnet.pdf]]
--------------
//aka variable-binding//
the assignment of a particular
datum to a particular slot in a data structure.
__Example__
In language, variable-binding is ubiquitous;
for example, when one produces or interprets a sentence of the form, “Mary spoke to John,”
one has assigned “Mary” the role of subject, “John” the role of object, and “spoke to” the
role of the transitive verb.
https://en.wikipedia.org/wiki/Bio-inspired_computing
genetic algorithms ([[Evolutionary computing]]) ↔ evolution
biodegradability prediction ↔ biodegradation
cellular automata ↔ life
emergent systems ↔ ants, termites, bees, wasps
neural networks ↔ the brain
artificial life ↔ life
artificial immune systems ↔ immune system
rendering (computer graphics) ↔ patterning
and rendering of animal skins, bird feathers, mollusk shells and bacterial colonies
Lindenmayer systems ↔ plant structures
communication networks and protocols ↔ epidemiology and the spread of disease
membrane computers ↔ intra-membrane molecular processes in the living cell
excitable media ↔ forest fires, "the wave", heart conditions, axons, etc.
sensor networks ↔ sensory organs
-------
[[Finite populations induce metastability in evolutionary search ☆|http://www.sciencedirect.com/science/article/pii/S0375960197001928]]
[[The evolution of emergent computation|http://www.pnas.org/content/92/23/10742.abstract]]
[[Membrane computing|https://en.wikipedia.org/wiki/Membrane_computing]]
[[DNA computing|https://en.wikipedia.org/wiki/DNA_computing]]
The field that studies the links between [[Genetics]] and [[Biochemistry]], for instance by finding which [[Gene]]s that control certain [[Metabolic pathway]]s, and how they do it.
One major focus area involves diagnosing and treating metabolic hereditary diseases.
[[Garrod and inborn errors of metabolism|https://www.youtube.com/watch?v=K8TWS0QzsFg]] -- [[Garrod, Beadle, Tatum and the link between genetics and biochemistry|https://www.youtube.com/watch?v=YN7srcX4ias]]
[[Yeast as a model organism|https://www.youtube.com/watch?time_continue=507&v=twoE1twluQw]]
!!__Mutant hunting__
[[How to use genetics to study biochemistry: A mutant hunt|https://www.youtube.com/watch?v=tWCVaP1RaxI]]
__[[Tricks of mutant hunting|https://www.youtube.com/watch?v=hf3G4eD23k0]]__
* [[Replica plating]]
* [[Use haploids|https://www.youtube.com/watch?v=hf3G4eD23k0#t=6m50s]], if you can, [[like in yeast|https://www.youtube.com/watch?v=twoE1twluQw#t=4m30s]]. Benefits depend on whether mutation is [[dominant|Genetic dominance]] or not.
* Test of [[dominance|Genetic dominance]]. [[Mate a heterozygote with a homozygote|https://www.youtube.com/watch?v=xo5UPOB2XGg#t=48s]]
* [[Tests of Complementation|https://www.youtube.com/watch?v=Ff6Vky2YlmY#t=1m]] -- [[explanation|https://www.youtube.com/watch?v=Ff6Vky2YlmY#t=1m42s]], [[only works for recessive|https://www.youtube.com/watch?v=Ff6Vky2YlmY#t=6m18s]]. [[Table to organize complementation tests|https://www.youtube.com/watch?v=Ff6Vky2YlmY#t=9m]]. [[Nice example|https://www.youtube.com/watch?v=Ff6Vky2YlmY#t=14m20s]]
** If the mutations complement each other --> different genes
** If they fail to complement each other --> same gene
** These define //complementation groups//
* [[Epistasis test|https://www.youtube.com/watch?v=_zEV_-BT3LI]]. Sometimes phenotypes of double mutants are the same as hose of single mutants, when the extra mutation affects something upstream in a [[Metabolic pathway]] that the other mutation affects. Can use this to find order of steps in the pathway.
!!![[Gene knock-out]]s are useful in these studies!
The branch of science concerned with the chemical and physicochemical processes that occur within living organisms.
See also [[Molecular biology]], for the way [[Biochemistry]] drives biology at the molecular scale.
!!__[[Metabolism]]__
!!!__[[Metabolic network]]__
!!!__[[Metabolic pathway]]__
!!__[[Biological molecules|Biomolecule]]__
[[Carbohydrate]]
[[Lipid]]
[[Protein]]
[[Nucleic acid]]
[[Biological Molecules - You Are What You Eat: Crash Course Biology #3|https://www.youtube.com/watch?v=H8WJ2KENlK0&index=3&list=PL3EED4C1D684D3ADF]]
__According to size__
* Biological macromolecules are large:
** [[Protein]]s
** [[Nucleic acid]]s
* Metabolites are low-molecular-weight molecules, such as [[Glucose]], or [[Glycerol]]
!!__[[Molecular evolution]]__
In most cases, new challenges that an organism faces, are solved by the adaptation of an existing macromolecule, rather than by the evolution of an entirely new one.
!!__[[Biochemical genetics]]__
-----------------
!!__[[Structural biology]]__
Structural biology has greatly benefited biochemistry, with the discovery of the detailed 3-dimensional structure of macromolecules. See [[Protein structure analysis]]
//there is an intimate relation between structure (form) and function in biology//
--------------
William Prout
!![[Encyclopedia of Life|http://eol.org/]]
[[Tree of life]]
{{Tree of life}}
__[[Evolution]]__
[[Tree of life image|https://goo.gl/photos/Q2gEMi9pDRYxGFz48]]
[[The origin of species by Charles Darwin|http://www.talkorigins.org/faqs/origin.html]]
[[Global Biodiversity Information Facility|http://www.gbif.org/]]
[[Charles Darwin's Beagle library|http://darwin-online.org.uk/BeagleLibrary/Beagle_Library_Introduction.htm]]
[[On the experimental evolution of bet-hedging|https://jabustyerman.wordpress.com/2010/02/06/on-the-experimental-evolution-of-bet-hedging/]]
A Natural history of the sense by Diane Ackerman
Simon Hampton-Essential Evolutionary Psychology
[img width=500 class=img-centered [kiwibirdgeno.jpg]]
[[Electricity]] in [[biological|Biology]] systems, mostly due to movement of free [[Ion]]s (ionic current)
* [[Ion channel]]
__Main biological ions__
* [[Potassium]]
* [[Sodium]]
* [[Calcium]]
* [[Chloride]]
!!__Electrical properties of [[Cell membrane]]s__
* [[Membrane potential]]: -20 to -200mV. [[Voltage]] difference between [[Cytoplasm]] and exterior.
* Membranes are very effective [[Capacitor]]s. Can estimate membrane [[Capacitance]]
3 to 5nm with $$\Delta V$$ = 90mV --> $$3 \times 10^7 $$V/m. Very high!
Using [[Nernst equation]] we can calculate voltage due to separation of a single ion species across membrane. Equilibrium condition..
Goldman-Hotchkin-Katz.. equation.
__Sodium-potassium pump__ pumps 3 sodium ions out per potassium ion in. There are also ion channels that are only permeable to potassium, which increases the membrane potential
!!__History of bioelectricity__
Luigi Galvani. Make muscle moves with tweezers, [[Electrochemistry]] involved. His nephew would reanimate certain parts of the human body --> inspired [[Frankestein]]. Galvanized corpse!
[[Salt]] is actually enough to make muscle twitch, by changing ion balance in the nerves. Don't put salt in a [[Wound]]...
The complexity of biological organisms is often studied under the light of [[Evolution]]
See [[Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments|http://www.mdpi.com/1099-4300/14/11/2173]]
In this paper they argue that the existence of life may be used as an indicator that the natural envirnoment is non-random (See also [[Order]]). They explore this by modeling a biological organism as an information-processing system, that is also an open thermodynamic system. They thus approach its study using [[Thermodynamics of computation]].
------------------
[img[http://i.imgur.com/9B6YzFd.png]]
[img[http://i.imgur.com/Vegi1r2.png]]
--------------------
[[Physical complexity of symbolic sequences|http://sci-hub.bz/10.1016/s0167-2789(99)00179-7]]
[[Information theory and the phenotypic complexity of evolutionary adaptations and innovations|http://biorxiv.org/content/early/2016/08/22/070854]]
------------------------
The computations that an organism performs are mostly about learning abut the world, predicting it, and making decisions that are expected to be the most benefitial (like finding most food).
They use [[HMM|Hidden Markov model]]s to model the environment and the organism's memory and computation. <mark>However, I still don't get how their model works</mark>
They also talk about how to balance memory and channel capacities, which is mirrored in the trade-off between DNA storage versus brain storage. Organisms that don't have memory, and rely on channel capacity to sense as much as possible at every time about the world, are called reactive. Organisms which have memory, so they don't need to sense as much at every instant of time, are called representational. They say that "Representational systems are useful for prediction, while reactive systems are useful for adaptation.", but <mark>I'm not sure why!?</mark>
It is interesting to note that some species enhance their fitness by modifying their environments, bringing about an increase in predictability, a clear evolutionary advantage. This seems particularly obvious in the human species’ ability to fashion stable and predictable environments for itself.
<span style="color:#fce">In evolutionary terms, it is difficult to justify how biological algorithmic complexity could significantly surpass that of the environment itself.</span>
"In a fully predictable environment where benefit returns are constant, one would be at a loss to explain why living organisms would evolve. Therefore, paradoxically, the environment seems to requirestructure and apparent randomness for living systems to evolve."<mark>Why?</mark>
[[The cell as a material.|http://www.ncbi.nlm.nih.gov/pubmed/17174543]]
See [[Active matter]]
[[Active cellular materials.|http://www.ncbi.nlm.nih.gov/pubmed/20089390]]
[[Modeling the mechanics of cells in the cell-spreading process driven by traction forces|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.042404]]
!!__Biological tissue__
https://www.wikiwand.com/en/Biological_system
See [[Biology]]
The study of ''life'', that includes the most [[Complex systems]] known.
!!__Description levels in biology__
[[Systems biology]]. These levels form a nice hierarchy of [[Biological system]]s, which of course interact with and influence each other in crucial ways.
# Biosphere
# Ecosystem
# Organism
# Organ
# [[Tissue|Tissue (Biology)]]
# Cell
# Organelles
# Molecules
!!!__Levels 1,2: [[Ecology]]__
!!!__Levels 2,3: [[Biodiversity & evolution]]__
[[Evolution]]
!!!!__[[Tree of life]]__
!!!__Levels 4,5: [[Organismal biology]]__
[[Developmental biology]]
[[Anatomy]] -- [[Physiology]]
* [[Tissue (Biology)]] --> [[Organ system]]s
!!!__Levels 6,7: [[Cell biology]]__
!!!__Levels 8: [[Molecular biology]]__
|[[Genetics]] <--> [[Biochemistry]]|
-----------------
!__General methods__
!!__Quantitative biology__
Using statistics, etc.
http://quant.bio/
!!__[[Mathematical biology]]__
!!__[[Experimental biology]]__
!![[Biotechnology]]
-------------
[[National Center for Biotechnology Information|http://www.ncbi.nlm.nih.gov/]]
[[books|http://www.ncbi.nlm.nih.gov/books/browse/]]
[[Biology crash course|https://www.youtube.com/playlist?list=PL3EED4C1D684D3ADF]]
[[Edx course|https://courses.edx.org/courses/course-v1:MITx+7.00x_3+2T2015/courseware/Week_1/Introduction/]]
https://www.khanacademy.org/science/biology
http://ocw.mit.edu/courses/biology/7-01sc-fundamentals-of-biology-fall-2011/biochemistry/types-of-organisms-cell-composition/
[img[https://qph.ec.quoracdn.net/main-qimg-0cded91a2f9bc31a5c1403336ca46081?convert_to_webp=true]]
----------------------
[[Haloquadratum|https://en.wikipedia.org/wiki/Haloquadratum]]
http://bionumbers.hms.harvard.edu/
[[Cause and effect in biology - Ernst Mayr|http://isites.harvard.edu/fs/docs/icb.topic100452.files/Mayr_E._1961._Science_V134.pp1501-1506.pdf]]
http://www.biorxiv.org/
[[Corneal biomechanics]]
<iframe src="https://player.vimeo.com/video/180084342" width="640" height="360" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>
A.k.a. ''healthcare sciences'' or ''health sciences''
https://en.wikipedia.org/wiki/Outline_of_health_sciences
[[Biomedical sciences - Springer|http://www.springer.com/gp/biomedical-sciences]]
[[Carbohydrate]]
[[Lipid]]
[[Protein]]
[[Nucleic acid]]
[img[http://66.media.tumblr.com/b5570e3ed742cd0aadcdb837544abeea/tumblr_oa0a97Camy1sk2szio1_1280.gif]]
--------------
https://www.wikiwand.com/en/Biomolecule
[[Physical biology of the cell|http://microsite.garlandscience.com/pboc2/]]
[[Cell biology by the numbers|http://book.bionumbers.org/]]
[[The thermodynamics of life|http://blogs.wayne.edu/phoffmann/2014/06/29/the-thermodynamics-of-life/]]
Biological Physics by P Nelson 2007
[[Non-equilibrium statistical mechanics: from a paradigmatic model to biological transport|http://iopscience.iop.org/article/10.1088/0034-4885/74/11/116601/meta]]
https://scholar.google.co.uk/citations?hl=en&user=aPssfaIAAAAJ&view_op=list_works
* [[Molecular dynamics]]
__Upgrading bios__
See [[here|https://wiki.ubuntu.com/DellBIOS]] and [[here|http://www.chtaube.eu/computers/freedos/bootable-usb/]] to upgrade bios of a Dell, like mine. Find the BIOS upgrade file [[here|http://www.dell.com/support/home/us/en/04/product-support/product/precision-m6700/drivers/advanced]]. Last updated on January 2016
[[Cambrian Genomics|http://cambriangenomics.com/]] DNA laser printing!
http://wyss.harvard.edu/
https://autodeskresearch.com/groups/bionano
https://autodeskresearch.com/projects/cyborg
http://pharma.ai/#Home
''Bipartite Networks'' have two kinds of nodes, and only connections between unlike nodes.
The equivalent of the adjacency matrix is the ''incidence matrix'', $$B$$
It can be converted into a //unipartite// network by a //''one-mode projection''// where two vertices are connected if they both have a connection to the same vertex of the other group (we could improve this by adding a weight: the number of those vertices (groups) they have in common).
This projection generally results in an union of //clique//s, i.e. completely connected components.
The adjacency matrix of the projection is (after we remove the diagonal components) $$P=B^TB$$ .
One can also have directed bipartite networks (as in [[Metabolic Networks]]), and weighted bipartite networks.
Hypergraphs can be represented as bipartite Networks. This is done by mapping the different relations in the hypergraph to a second type of node to which the original nodes can belong by being connected by an edge.
The ''block decomposition method'' (BDM) is an extension of the [[Coding theorem method]] to measure the complexity of $$N$$-dimensional arrays. As a [[Network]] can be expressed via its [[Adjacency matrix]], which is a 2D array, it can be used to measure [[Network complexity]] as well.
[[Original paper|http://arxiv.org/pdf/1212.6745v4.pdf]]
The measure (which we also call BDM) of complexity of array $$A$$ is defined as:
$$K(A) = \sum\limits_{(r,u) \in \mathcal{A}_{d}} \log_2(n) + K_m (r)$$
where $$\mathcal{A}_d$$ is the set with elements $$(r,u)$$ obtained when decomposing the array into non-overlapping subarrays of side length $$d$$. $$r$$ is one unique square, and $$n$$ is its multiplicity (number of times it appears). $$K_m$$ refers to the estimate of Kolmogorov complexity used in the [[Coding theorem method]]. However, for $$N$$-dimensional arrays, one uses $$N$$-dimensional [[Turing machine]]s, or [[Turmite]]s. Note that $$\log_2(n) $$ is the number of bits needed to specify the number $$n$$.
In the original paper, a set of 2-dimensional Turing machines was executed to produce all square arrays of size d = 4. This is why
the BDM is needed in order to decompose objects of larger size into objects for which its Kolmogorov complexity has been
estimated.
The order of the graph nodes in the adjacency matrix is relevant for
the complexity retrieved by the BDM. This is especially important in highly symmetrical graphs.
In estimating complexity,
it is reasonable to consider that the <span style="font-weight:normal;color:#9ED6C7;letter-spacing:0pt;word-spacing:2pt;font-size:14px;text-align:left;font-family:georgia, serif;line-height:1;margin:0px;padding:0px;">complexity of a graph corresponds to the lowest $$K_m$$ value of all permutations of the
adjacency matrix</span>, as the shortest program generating the simplest adjacency matrix is the shortest program generating
the graph.
!!!__Normalized BDM__
The chief advantage of a normalised measure is that it enables
a comparison among objects of different sizes without allowing the size to dominate the measure.
[img[http://i.imgur.com/8iC5ILA.png]]
MaxBDM is calculated approximately, as described in the paper.
!!!__Implementation__
An online implementation and code can be found [[here|http://complexitycalculator.com/]]
[[Stephan Tual - Blockchain beyond Bitcoin - Lift 2016|https://www.youtube.com/watch?v=CnUdwxZsyXc&feature=youtu.be&utm_content=bufferaac0a&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer]]
[[http://backfeed.cc/explore-in-depth]]
https://www.ethereum.org/
An [[Organ system]] that is a [[Liquid]] that distributes signals, nutrients, etc.
!!__Functions__
* Transporation
* Defense: [[Inmune system]]..
* [[Homeostasis]]
!!__Blood flow__
* [[Poiseuille's equation]]
Channels through which [[Blood]] travels
* [[Vein]]. Move [[Blood]] towards [[Heart]]. Have valves.
* [[Artery]]. Move [[Blood]] from [[Heart]]
* [[Capillary]]. Between arteries and veins. Transport oxygen, etc to surrounding tissue.
Physical manifestation of a [[Living being]]
//the shell//
[[Unrestricted Boltzmann machine|https://www.youtube.com/watch?v=iPuqoQih9xk&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=43#t=6m20s]]
[img[Selection_634.png]]
[[Restricted Boltzmann machine]]
//aka union bound, sigma sub-additivity of [[Measure]]s //
It is either a theorem, or an axiom, depending on the formulation of [[Probability theory]]
[[Video|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=19m53s]]
Let $$A_1, A_2, ..., A_k$$ be events (not necessarily independent); then,
$$P(A_1 \cup A_2 \cup ... \cup A_k \leq P(A_1) + P(A_2) + ... + P(A_k)$$
https://www.wikiwand.com/en/Boole's_inequality
A ''Boolean algebra'' is an [[Algebraic structure]] that models the relations between elements which can be either true or false. It is important in [[Mathematical logic]] and in [[Computer science]].
It has the structure of an orthocomplemented, distributed [[Lattice (algebraic structure)]].
See [[Dynamical system]] and [[Network theory]]
https://en.wikipedia.org/wiki/Boolean_network
!!!BN simulator on the web! http://rumo.biologie.hu-berlin.de/boolesim/
[[paper|http://bioinformatics.oxfordjournals.org/content/early/2013/09/28/bioinformatics.btt568.full.pdf]]
!!__[[Dynamics of Boolean networks]]__
!!__Statistical mechanics of Boolean networks__
[[Random Boolean network]]
[ext[Phase Transitions in Two-Dimensional Kauffman Cellular Automata|http://www.lps.ens.fr/~derrida/PAPIERS/1986/stauffer-epl-86.pdf]]
[[Phase transition in cellular random Boolean nets |https://hal.inria.fr/file/index/docid/210412/filename/ajp-jphys_1987_48_1_11_0.pdf]]
[[Kauffman's NK Boolean networks|http://pespmc1.vub.ac.be/BOOLNETW.html]]. "Because the regulatory structures at the edge of chaos (K ~ 2) ensure both stability [robustness] and evolutionary improvements [evolvability], they could provide the background conditions for an evolution of genetic cybernetic systems."
See [[Relations between the stability of Boolean networks and percolation|file:///home/guillefix/Dropbox/Oxford/MMathPhys/Complex%20systems/miniproject/relations-stability-boolean(3).pdf]]
!!__Types__
!!![[Random Boolean network]]
!!![[Hopfield network]]
------------
[[Boolean Network Robotics as an Intermediate Step in the Synthesis of Finite State Machines for Robot Control|https://mitpress.mit.edu/sites/default/files/titles/content/ecal13/978-0-262-31709-2-ch112.pdf]]
[[Random Networks of Automata: A Simple Annealed Approximation|http://iopscience.iop.org/article/10.1209/0295-5075/1/2/001/meta;jsessionid=EBA1AC96EEA63C2A2B773B11D4DF7732.c3.iopscience.cld.iop.org]]
[[Stability in Boolean networks and cellular automata|https://www.youtube.com/watch?v=2owceYMM9rw]]
[[Boolean network models of gene regulation and signal transduction|https://www.youtube.com/watch?v=vA9D727AGHI]]
See also [[Artificial neural network]]
In statistics, boostrap is a [[Monte Carlo]] technique to estimate the [[Sampling distribution]] of an [[Estimator]]
!!__Parametric bootstrap__
Uses estimated parameter to generate samples
!!__Nonparametric bootstrap__
can refer to any test or metric that relies on random sampling with replacement. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods.
[ext[https://www.wikiwand.com/en/Bootstrapping_(statistics)]]
* [[Bootstrap aggregation]] is an example.
Explanation: http://stats.stackexchange.com/questions/26088/explaining-to-laypeople-why-bootstrapping-works
[[An Introduction to the Bootstrap|http://www.hms.harvard.edu/bss/neuro/bornlab/nb204/statistics/bootstrap.pdf]]
!!![[Bootstrap aggregation (Bagging)|https://www.youtube.com/watch?v=5Lu1eTiX7qM&index=10&list=PLD0F06AA0D2E8FFBA#t=4.438496]]
Used to improve [[Classification]] and [[Regression analysis]]
[[(ML 2.7) Bagging for classification|https://www.youtube.com/watch?v=JM4Y0B6Ho90&index=13&list=PLD0F06AA0D2E8FFBA]]
http://research.microsoft.com/en-us/um/people/holroyd/boot/
An "infection" process in which nodes become infected if sufficiently many of their neighbors are infected. Related to the Centola-Many threshold model for social contagions.
[[Bootstrap percolation on spatial networks|http://arxiv.org/abs/1408.1290]] (see [[Spatial networks]]).
[[Bootstrap Percolation - MathWorld|http://mathworld.wolfram.com/BootstrapPercolation.html]]
[img[http://mathworld.wolfram.com/images/gifs/bootperc.gif]]
[[Bootstrap percolation on the random graph |https://arxiv.org/abs/1012.3535]]
In statistics, bootstrapping can refer to any test or metric that relies on random sampling with replacement. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods.
https://www.wikiwand.com/en/Bootstrapping_(statistics)
* [[Bootstrap aggregation]] is an example.
Explanation: http://stats.stackexchange.com/questions/26088/explaining-to-laypeople-why-bootstrapping-works
[[An Introduction to the Bootstrap|http://www.hms.harvard.edu/bss/neuro/bornlab/nb204/statistics/bootstrap.pdf]]
A [[Sigma-algebra]], $$\mathcal{B}$$, on a set, $$\Omega$$, defined as:
$$\mathcal{B} = \sigma(\tau)$$
i.e. the sigma-algebra generated by $$\tau$$, which is the set:{all the open sets of $$\Omega$$}, i.e. the [[topology|Topological space]] on $$\Omega$$. It is the smallest sigma-algebra that contains $$\tau$$. See [[here|https://www.youtube.com/watch?v=WKdy_OxdUbk]]
A Borel measure, is just a [[Measure]] on a Borel $$\sigma$$-algebra. Specifying such a measure is simplified by the [[Caratheodory extension theorem]], that says that to
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
A separation of scales approximation used in [[Molecular physics]], where the electrons "move" much faster than the nuclei.
[[some notes|http://bohr.physics.berkeley.edu/classes/221/s16/notes/adiab.pdf]]
See [[this book too|https://babel.hathitrust.org/cgi/pt?id=uc1.b3754016;view=1up;seq=10]] and my notes, and [[here|https://users.physics.ox.ac.uk/~smithb/website/coursenotes/moleculesandlasers.pdf]]
See [[Tree of life]]
[img width=400 [https://45.media.tumblr.com/c9a039a58acf9655e77e8102b024c692/tumblr_mnax1yyh7x1qbudbro1_500.gif]]
[[Erodium cicutarium|https://en.wikipedia.org/wiki/Erodium_cicutarium]] Aguja de pastor.
[img width=400 [http://floradeiberia.com/wp-content/gallery/Erodium ciconium/Erodium ciconium3.JPG]]
Their achenes curl upon drying (and also when I sqweezed it with my fingers, probably because humidity.). Seed launch is accomplished using a spring mechanism powered by shape changes as the fruits dry. The spiral shape of the awn can unwind during daily changes in humidity, leading to self-burial of the seeds once they are on the ground. The two tasks (springy launch and self-burial) are accomplished with the same tissue (the awn), which is hygroscopically active and warps upon wetting and also gives rise to the draggy hairs on the awn.
[img[https://upload.wikimedia.org/wikipedia/commons/e/e8/Erodium_cicutarium_MHNT.jpg]]
<iframe width="420" height="315" src="https://www.youtube.com/embed/0XTRbYOLjKg" frameborder="0" allowfullscreen></iframe>
__Pepinillos del diablo__
[[Ecballium|https://en.wikipedia.org/wiki/Ecballium]]
<iframe width="420" height="315" src="https://www.youtube.com/embed/gfZ8UHz2ofs" frameborder="0" allowfullscreen></iframe>
[[The Science of Grapevines: Anatomy and Physiology|https://books.google.co.uk/books?hl=en&lr=&id=SrMGBAAAQBAJ&oi=fnd&pg=PP1&ots=b18JdsRtM1&sig=N1EbURpl388owq1vgOeEaHMaa0o&redir_esc=y#v=onepage&q&f=false]]
[[Boundaries can steer active Janus spheres|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/ncomms15_boundary-steering-Janus.pdf]]. Looks at [[Catalytic conductor-insulator Janus swimmer]]s. Note that the method of mirror images used in the paper for estimating effects of some rotational diffusion quenching mechanisms is not the same as used for electrostatic charges near a conductor. It is in fact an instance of the method of mirror images, as applied to [[Diffusion]] equations, where the image is used to satisfy the no-slip boundary condition in the current $$J$$ of ions. As the current satisfies $$J=\sigma E$$ from [[Ohm's law]], the effect on currents should have an accompanying effect on the [[Electric field]].
!!__[[Neuroanatomy]] of the brain__
20% of volume of the brain are [[Blood vessel]]s.
[[Glial cell]]s are more numerous than neurons, except in [[Cerebellum]]
Number of neurons: ...
Density of neurons and conduction velocity is more important than size..
!!!__Brain regions__
* [[Cerebrum]]
* [[Cerebellum]]
* ...
!!!__Connectome__
Large-scale connections
!!__Physiology of the brain__
See [[Neuroscience]]
!!!__[[Neuron]]s__
Very very diverse
__Brain oscillations__
Remarkably conserved accross mammalian species.
!!!__[[Neural system]]s__
!!__Experimental techniques__
[[Electrophysiology]]
C-fos
[[Optogenetics]]
DREADDs -- chemogenetics/pharmacogenetics.
See [[Brain]]
[[Neurophysiological and Computational Principles of Cortical Rhythms in Cognition|http://physrev.physiology.org/content/90/3/1195.short]]
''Brownian motion''
[ext[Brownian Motion: Langevin Equation|http://web.phys.ntnu.no/~ingves/Teaching/TFY4275/Downloads/kap6.pdf]]
!!__Discrete space: ''random walk''__
[[Random walk on 1D lattice|http://www.youtube.com/watch?v=Kn6wzdRAdiE&index=1&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=27m55s]]
[[Biased random walk]], probability distribution is Binomial
__Limits in time variable__
*Discrete time and space: discrete time [[Master equation]]
* [[continuous time limit, but keeping space discrete|http://www.youtube.com/watch?v=XfK1y3YRSxE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=3#t=30m00s]], we get the continuous time [[Master equation]].
A discrete space-time random walk has a standard deviation in position that is proportional to square root of number of steps:
$$\frac{\sigma_x}{a}=\sqrt{n}=\sqrt{\frac{t}{\tau}}$$
$$\sigma_x=\frac{a}{\sqrt{\tau}}\sqrt{t}$$
Clearly if we want $$\sigma_x$$ to stay finite for a finite $$t$$, we want $$\frac{a}{\sqrt{\tau}}$$ to stay finite, and we get $$\sigma_x\propto\sqrt{t}$$ in continuous limit. We also get non-differentiable paths as $$\frac{a}{\tau}\rightarrow \infty$$.
[[Random walk on 2D square lattice|http://www.youtube.com/watch?v=XfK1y3YRSxE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=3#t=19m04s]]. Combinatorics get harder
[[Solving random walk diffusion on a finite domain with different boundary conditions|https://www.youtube.com/watch?v=Ut9tv2O87Vk&index=5&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]]
__[[Polya's recurrence theorem|https://math.dartmouth.edu/~pw/math100w13/mare.pdf]] for random walks__
See also probability distribution for random walk (same as for polymer) [For example [[here|http://www-thphys.physics.ox.ac.uk/people/ArdLouis/teaching/L4-B1-BIOPHYSICS-Notes3-AAL-Nov2015.pdf]] or in Soft Matter Physics notes. The probability density at origin goes like $$1/N^{d/2}$$ (normalization of Gaussian). One can then sum over all possible lengths of time (i.e. $$N$$s) and get the expected number of times one returns to (a neighbourhood of) the origin (See Note 1 in [[Probability theory]] for why). For $$d=1,2$$, this is $$\infty$$, while it's finite for $$d \geq 3$$. This can be interpreted for a polymer as it being "dense" or "sparse", as summing over $$N$$ we are asking the question how many monomers of our very long polymer are close to a given point (say the origin)?
One can also find __probability of //ever// coming back__, and this [[can be related to|https://www.youtube.com/watch?v=Ut9tv2O87Vk&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=5#t=1h12m30s]] __the expected number of times to come back__. [[This can also be derived heuristically for the asymptotic limit of large times|https://www.youtube.com/watch?v=hHciEDpm1sE&index=9&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=30m42s]].
__First passage time__: [[First passage time calculation using generating functions.|https://www.youtube.com/watch?v=hHciEDpm1sE&index=9&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=38m32s]]. The generating functions also give the {survival probability}, which is the same as {probability of ever coming back}.
[img[https://67.media.tumblr.com/394b4aa4c602b5b869a0ccc0b273c63d/tumblr_o6oafpio971ruo6jxo1_500.png]]
[[Random walk in a graph]]
----------
!!__Continuous space__
[[Continuous space-time limit from discrete random walk|https://www.youtube.com/watch?v=XfK1y3YRSxE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=3#t=0m30s]]
<big>''Diffusion''</big> If continuous space and continuous time: ''[[Diffusion]] equation''
Can also have continuous space, and discrete time, although not often used.
[[Phenomenological derivation of Diffusion equation|https://www.youtube.com/watch?v=dUt2bbGREgQ&index=2&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]]
Use [[Fick's laws of diffusion|https://en.wikipedia.org/wiki/Fick%27s_laws_of_diffusion]], and [[Einstein–Smoluchowski relation]]
[[Eistein's original derivation from Chapman-Kolmogorov equation|http://www.youtube.com/watch?v=dUt2bbGREgQ&index=2&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=38m30s]], as Brownian motion is assumed to be a [[Markov process]]
---------
[[Simulate on Matlab|http://www.mathworks.com/matlabcentral/fileexchange/45536-simulation-of-random-walk]]
The [[Fokker-Planck equation]] has a stationary solution, for a biased periodic potential:
[img[tilting_ratchet1.png]]
A ''Brownian ratchet'' occurs when the potential is asymmetric. A particularly nice example is the __sawtooth__ potential, in which the above equation gives:
[img[tilting_ratchet3.png]]
for the first site.
We find three regimes:
[img width=400 class=img-centered [tilting_ratchet4.jpg]]
[img width=400 class=img-centered [tilting_ratchet5.jpg]]
The __drift velocity__ is:
[img[drift.jpg]]
which plotted looks like:
[img[tilting_ratchet7.jpg]]
This shows an asymmetry between the positive and negative force regions, similar to that shown in the current-voltage curve of a diode:
[img width=400 [https://cdn.sparkfun.com/assets/4/4/a/5/b/5175b518ce395f2d49000000.png]]
In fact __ratchets and diodes are very analogous__, and ratchets, including Brownian ratchets can be thought of as mechanical diodes. In fact, the famous Feynman Brownian ratchet paradox was formulated by Brillouin in terms of a diode rectifier ([[Brillouin paradox|https://en.wikipedia.org/wiki/Brownian_ratchet#History]])
This rectification in Brownian ratchets can be used as a basis for ''fluctuation-driven transport'', which is a proposed mechanism for [[molecular motors|Molecular motor]]. See [[here|http://link.springer.com/article/10.1007/s002490050158]]
An example of this is in the __tilting ratchet__, in which the bias $$F$$ used above, oscillates.
__Flashing ratchet__
Another example of a Brownian ratchet is when the potential $$U(x)$$ itself oscillates (fluctuations between a low and a high potential). A special case has the potential turning stochastically between two states, this is known as the __flashing ratchet__, if one of the two states has no potential, this is called the __on-off ratchet__.
A way to solve for the probability in the stochastically flashing ratchet is to add a new label to the probability representing one of the two states of the potential landscape, call them $$+$$ and $$-$$. Then we get a Fokker-Planck/Master equation for our continuous (space labelled by $$\vec{x}$$) and discrete configuration space:
[img[flashing ratchet.png]]
One can the workout the evolution equation for the total probability of being at position $$\vec{x}$$, and it turns out to have the form of a Fokker-Planck equation with an effective potential.
//aka buffer//
A buffer solution (more precisely, pH buffer or hydrogen ion buffer) is an aqueous solution consisting of a mixture of a weak acid and its conjugate base, or vice versa. Its pH changes very little when a small or moderate amount of strong acid or base is added to it and thus it is used to prevent changes in the pH of a solution.
https://www.wikiwand.com/en/Buffer_solution
[img[buffer_solution.png]]
Buffers are important in biology, as they help avoid very acidic or very basic solutions, where the function of biological molecules may be altered, and be lethal for the cell.
A buffer is most effective when the [[pH]] is close to the [[pKa|Acid-base equilibria]] of its acid component
!!__Henderson-Hasselbach equation__
[img[henderson_hasselbach.png]]
Using $$[A^-]+ [HA] = C$$ is a constant, which is the total concentration of HA before dissociating.
gives
$$\frac{C}{(\frac{K_a}{[H^+]}+1)}=[HA]$$
Well I think I need also the water equilibrium equation, etc. really.
See the above function plotted: [ext[here|http://www.wolframalpha.com/input/?i=plot+1-1%2F(1%2B1%2F10%5E-x)]]
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
''Bulk matter'' refers to a piece of [[matter|https://en.wikipedia.org/wiki/Matter#Based_on_quarks_and_leptons]] composed of sufficiently many building blocks (elementary particles, atoms, molecules, ...) in such a way that __a simple [[statistical|Statistical physics]] description is appropriate__, an bulk properties like temperature, [[Viscosity and elasticity]], etc can be defined. These are also called //material properties// or //macroscopic properties//.
Bulk matter can be either composed of a single [[phase|Phase transition]] or a mixture of phases; see for instance [[dispersions|Dispersion (Chemistry)]].
I use the term "form" of matter to refer to a particular type of bulk matter: either a single phase or a mixture of phases. I also use the world //material// (see [[Materials science]]) mostly to refer to a particular form of matter. I think that "phase" is sometimes used more widely in the same sense as I use the term "form".
__When is a system bulk matter?__
Note that many pieces of matter are formed by components interacting in complicated ways, in such a way that a simple statistical description does not appropriately describe its behaviour for many purposes; for instance, a computer, or a cell. These are in most situations not considered as bulk matter, and should be treated as [[Complex systems]] instead. However, whether a statistical description is appropriate, and therefore whether they are considered bulk matter, really depends on the problem, and so for some problems, these systems can be considered bulk matter (for instance, when studying the overall mechanical strength of a computer system). From here on, "matter" refers to bulk matter, unless otherwise specified.
!!__Classification__
Bulk matter can be classified depending on whether the phase (see [[Condensed matter physics]] for more detailed explanation):
* is [[condensed or non-condensed|Condensed matter physics]].
* is a [[fluid|Fluid mechanics]], a [[solid|Solid mechanics]], or a [[viscoelastic material|Viscoelasticity]], depending on its [[elasticity|Viscosity and elasticity]] properties. Fluids flow easily, while solids do not.
* [[Hard|Solid-state physics]] vs [[soft|Soft matter physics]], depending on whether the internal degrees of freedom of the material are affected significantly by thermal fluctuations (soft), or not (hard).
!!__Physics__
!!!__Mechanics__
The [[Mechanics]] of most classical types of bulk matter can be macroscopically described via [[Continuum mechanics]], which __describes matter in terms of //continuum equations//__, based on space-time varying //fields// that evolve according to [[Differential equations]].
This is the foundational theory used in [[Mechanical engineering]], and related areas. Continuum equations are also widely used in physics, particularly in [[Solid mechanics]], [[Fluid mechanics]], [[Soft matter physics]], [[Astrophysics]], rheology, etc.
[[Rheology]] is a branch of continuum mechanics that __studies the flow of matter__, primarily in a liquid state, but also as 'soft solids' or solids under conditions in which they respond with plastic flow rather than deforming elastically in response to an applied force. That is, rheology does not study a particular class of bulk matter, but the flow of any bulk matter.
!!!__Thermodynamics__
[[Thermodynamics]] is the classical theory describing the flow of heat through matter. It is often combined with continuum mechanics to explain phenomena such as convection.
!!!__Modern physics__: statistical physics, quantum mechanics
There are many more complex phases of matter particularly in [[soft condensed matter|Soft matter physics]], that go beyond those simply described by continuum equations (although these are still very useful in many of these). Description of these often needs more advanced ideas from [[Statistical physics]].
The microscopic study of matter, as done for example in [[Quantum condensed matter physics]] and [[Statistical physics]], also goes beyond phenomenological and macroscopic descriptions of classical physics and tries to derive materials properties from microscopic physics.
[[Burrows-Wheeler Transform (Ep 4, Compressor Head) Google|https://www.youtube.com/watch?v=4WRANhDiSHM&index=6&list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H]]
[[Burrows-Wheeler Transform|https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/bwt.pdf]]
https://www.youtube.com/watch?v=4n7NPk5lwbI
Note busy beavers are often defined just for [[Turing machine]]s on an input tape which is initially blank.
Applications in [[Coding theorem method]]
-------------------------
https://en.wikipedia.org/wiki/Busy_beaver
[[Understanding proof for Busy Beaver being uncomputable|http://cs.stackexchange.com/questions/52949/understanding-proof-for-busy-beaver-being-uncomputable]]
http://browser.openworm.org/
[[paper|https://drive.google.com/file/d/0B_t3mQaA-HaMWEJ4aG5fVm9QUWc/view]]
[[The ``Clockwise/Spiral Rule''|http://c-faq.com/decl/spiral.anderson.html]] for parsing C variable declarations!
__Random numbers and probability distributions in C++__
[[rand-Considered-Harmful .. New functions in C++|https://channel9.msdn.com/Events/GoingNative/2013/rand-Considered-Harmful]] See minute 15, for example.
Uses this library: http://www.cplusplus.com/reference/random/. rand() considered deprecated for most uses..
[[C++ tutorial|http://www.cplusplus.com/doc/tutorial/]]
[[volatile qualifier|http://stackoverflow.com/questions/4437527/why-do-we-use-volatile-keyword-in-c]]
[[References|Reference (computer science)]] are nothing but constant pointers in C++ (see [[here|http://www.codeproject.com/Articles/13363/An-Insight-to-References-in-C]]).
See Lynda.com videos.
http://eigen.tuxfamily.org/index.php?title=Main_Page
Armadillo
[[Calabi–Yau manifold|https://en.wikipedia.org/wiki/Calabi%E2%80%93Yau_manifold]]. is a special type of manifold that is described in certain branches of mathematics such as algebraic geometry. The Calabi–Yau manifold's properties, such as Ricci flatness, also yield applications in theoretical physics. Particularly in superstring theory, the extra dimensions of spacetime are sometimes conjectured to take the form of a 6-dimensional Calabi–Yau manifold, which led to the idea of mirror symmetry.
String theory postulates 10 dimensions. The 6 dimensions have to be small (//compactified//) so that the space is approximately 4-dimensional. However the shape of the extra 6-dimensions determines the laws of physics (the fundamental laws of particles). The problem, I think, is that it's hard to relate the two, and also that there are so many candidate manifolds..
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/d/d4/Calabi-Yau.png/220px-Calabi-Yau.png]]
//a.k.a. infinitesimal calculus//
Fundamental theorem of calculus
[[Vector calculus]]
The portion of [[allocated memory|Memory allocation]] of a process, where local variables from functions that are being executed are stored.
https://www.cs.umd.edu/class/sum2003/cmsc311/Notes/Mips/stack.html
Note the code of the functions themselves is stored in the text section of the allocated memory, the stack stores the local variables that the function is using, as well as some other things, like function arguments, and return addresses. The lifo property of the stack allows the easy implementation of recursive function calls.
If the amount of space taken by the stack goes over a certain set limit, we get an //stack overflow//.
https://www.youtube.com/watch?v=HQ3YI70PDe0
http://www.bbc.co.uk/education/guides/znp4jxs/revision/1
A [[Geological period]] of the [[History of Earth]] that marks the beginning of the [[Phanerozoic]] era, the animal era.
[img width=400 [http://www.educatetruth.com/wp-content/uploads/2014/03/Cambrian-animals-2.jpg]]
[img[http://samnoblemuseum.ou.edu/wp-content/uploads/2015/05/Cambrian-community-revised.jpg]]
[[Trilobite]]
[[Tuzoia]]
[[Sponge (animal)]]
[[Laggania]]
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body, forming a [[Malignan tumor]]
https://www.wikiwand.com/en/Cancer
!!__Main types__
* [[Carcinoma]]
** [[Pancreatic cancer]]
** [[Liver cancer]]
** [[Breast cancer]]
** [[Ovarian cancer]]
* [[Melanoma]]
* [[Lymphoma]]
* [[Leukemia]]
A more restricted kind of [[Fugue]].
See description in first chapter of [[GEB]].
Tranports molecules from Blood to tissue.
!!__Mechanisms__
* [[Pressure]]
__Gear box__
[img[http://www.gifbin.com/bin/042015/1431364609_how_manual_transmission_works.gif]]
[[Car driving]]
__Parking__
[img[https://media.giphy.com/media/l0MYvVIBE4hDIkjSw/giphy.gif]]
[[Video|https://www.youtube.com/watch?v=WKdy_OxdUbk#t=15m23s]]
To specify a measure on a [[Sigma-algebra]] it suffices to specify it on an [[Algebra (algebraic structure)]].
The measure then extends to the sigma algebra generated by that algebra, i.e. to the smallest sigma-algebra containing that algebra. The generation can be done by starting with the algebra and taking intersections and unions, so that it satisfies the axioms of a sigma-algebra. The generated sigma-algebra is unique, if the underlying measure is [[sigma-finite|https://www.wikiwand.com/en/%CE%A3-finite_measure]]..
A carbohydrate is a biological molecule consisting of carbon (C), hydrogen (H) and oxygen (O) atoms.
In particular, we have one [[Hydroxyl]] groups (OH) attached to Carbons. These make carbohydrates [[Polar molecule]]s, and [[Hydrophobic]]
See [[this video|https://www.youtube.com/watch?v=KJG6HA5xSxY#t=2m36s]]
The term is most common in biochemistry, where it is a synonym of saccharide, a group that includes sugars, starch, and cellulose. The ''saccharides'' are divided into four chemical groups:
!!__Classification__
*[[Monosaccharide]]. Depending on the number of carbons, we call the sugar: diose, triose, tetrose, pentose, hexose, heptose, octose, etc.
** [[Glucose]] (a cyclic sugar, very important one).
* [[Polysaccharide]]s. Several monosaccharides joined together by [[Dehydration synthesis]].
** disaccharides. Two monosaccharides
** [[Starch]]
** [[Cellulose]]
** [[Glycogen]]
* oligosaccharides,
-------------------------
https://www.wikiwand.com/en/Carbohydrate
A [[Chemical element]] composed of nitrogen atoms. These have 6 proton in the nucleus.
The hydrogen atom tends to form four bond, as it has 4 electrons in its outer shell (see [[Octet rule]]).
http://www.bbc.co.uk/education/guides/z6xbkqt/revision/4
[[C|Carbon]][[O|Oxygen]],,2,,
[[Making carbon dioxide|http://www.bbc.co.uk/education/guides/zjwnb9q/revision/3]]
[[some uses|http://www.bbc.co.uk/education/guides/zjwnb9q/revision/5]]
A [[Geological period]], with lots of [[Plant]]s
A [[Functional group]] where an [[Oxygen]] double bonds to a [[Carbon]]
[img[http://www.ochempal.org/wp-content/images/C/carbonylgroup2.png]]
A [[Functional group]]
[img[http://f.tqn.com/y/chemistry/1/W/j/s/carboxylgroup.jpg]]
An [[Organic compound]] with a [[Carboxyl]] group.
[img width=300 [https://upload.wikimedia.org/wikipedia/commons/thumb/b/b5/Carboxylic-acid.svg/1024px-Carboxylic-acid.svg.png?1473060759218]]
https://www.wikiwand.com/en/Carboxylic_acid
http://www.bbc.co.uk/education/guides/z33j6sg/revision
A cancer arising in the [[epithelial tissue|Epithelium]] of the skin or of the lining of the internal organs.
Carcinomas -- the most commonly diagnosed cancers -- originate in the skin, lungs, breasts, pancreas, and other organs and glands
* [[Pancreatic cancer]]
* [[Liver cancer]]
* [[Breast cancer]]
* [[Ovarian cancer]]
* [[Lung cancer]]
The [[electrophysiological|Electrophysiology]] functioning of the [[Heart]]
Repeated rhythmic contractions. Mechanical activity triggered by ordered ''electrical activation''.
Electricity travels through walls. Atria.
Multi-scale process:
* Initiated by [[Pacemaker cell]]s
* Cardiac myocyates experiance quick changes in [[transmembrane potential|Membrane potential]] => [[Action potential]]
* Neighbouring cells detect this change by diffusion and mimic it.
__Reaction-diffusion model__
//monodomain equations//
$$V=\phi_e - \phi_i$$, where $$\phi_e$$ is the extracellular [[Electric potential]], and $$\phi_i$$ is the intracellular one. We also homogenize the tissue (i.e. ignore the fine cellular detail of the [[Myocardium]]).
Numerical solution, with [[Finite element method]]s.
* [[Heart attack]]
* [[Congestive heart failure]]
* [[Heart]]
* [[Blood vessel]]
* [[Blood]]
------------
cvphysiology.com
The [[Cartesian product]] of a collection of copies of a [[Set]]. For instance the Cartesian square is $$X \times X$$.
https://en.wikipedia.org/wiki/Cartesian_product#Cartesian_power
An [[operation|Operation (Mathematics)]] between [[Set]]s that gives a new set composed of [[Tuple]]s of elements from the original sets.
----------------------
http://mathworld.wolfram.com/CartesianProduct.html
https://en.wikipedia.org/wiki/Cartesian_product
[[Wanderer above the Sea of Fog]]
__The sea of ice__
[img[https://upload.wikimedia.org/wikipedia/commons/0/0c/Caspar_David_Friedrich_-_Das_Eismeer_-_Hamburger_Kunsthalle_-_02.jpg]]
A sequence of numbers that arises in [[Combinatorics]], often of objects defined recursively, like trees. See also [[Analytic combinatorics]]
https://en.wikipedia.org/wiki/Catalan_number
[[Catalan numbers|http://www-groups.dcs.st-and.ac.uk/history/Miscellaneous/CatalanNumbers/catalan.html]]
http://mathworld.wolfram.com/CatalanNumber.html
Biological catalyst are known as [[Enzyme]]s.
http://www.bbc.co.uk/education/guides/z4cmn39/revision/5
[[Phase-transfer catalyst]]
A kind of [[Janus swimmer]].
See [[Electrokinetic effects in catalytic conductor-insulator Janus swimmers]]
[[Category Theory: The Beginner’s Introduction (Lesson 1 Video 1)|https://www.youtube.com/watch?v=P6DvIfTJhx8]]
Relations to [[Functional programming]], lambda calculus, etc.
[[Brian Beckman: Don't fear the Monad|https://www.youtube.com/watch?v=ZhuHCtR3xq8&feature=youtu.be]]
------------------
[[Category Theory Applied to Neural Modeling and Graphical Representations (2000)|http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.2635]]
Modeling cognitive systems with Category Theory
[[Bayesian machine learning via category theory|https://arxiv.org/abs/1312.1445]]
[[What Might Category Theory do for Artificial Intelligence and Cognitive Science?|http://www.j-paine.org/dobbs/why_be_interested_in_categories.html]]
[[Theory of Interface: Category Theory, Directed Networks and Evolution of Biological Networks|https://arxiv.org/abs/1210.6166]]
[[Cauchy–Riemann equations|https://en.wikipedia.org/wiki/Cauchy–Riemann_equations]]
[[Causal Inference and Statistical Learning!|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/schoelkopf.pdf]]
//Learning theory and [[Algorithmic information theory]]//
[[Causal inference using the algorithmic Markov condition|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/paper_IEEE_version3_webseite_6526%255b1%255d%20%25282%2529.pdf]]
[[Causal Markov condition for submodular information measures|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/COLT2010-Steudel_%255b0%255d.pdf]]
[[Probality-free causal inference via the Algorithmic Markov Condition|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/slides_Janzing.pdf]]
[[Celestial mechanics|https://en.wikipedia.org/wiki/Celestial_mechanics]] deals with the motions of celestial objects.
[[Movements of Earth]]
Basic unit of [[Biology]]
[[Cell biology]]
[[Cell organelles]]
[[Cell cycle]]
[[The Cell, 2nd edition. A Molecular Approach|http://www.ncbi.nlm.nih.gov/books/NBK9839/]]
[[Eukaryopolis - The City of Animal Cells: Crash Course Biology #4|https://www.youtube.com/watch?v=cj8dDTHGJBY&list=PL3EED4C1D684D3ADF&index=4]] -- [[video|https://www.youtube.com/watch?v=uLsVEYdn_e4]]
[[Cytology|https://www.wikiwand.com/en/Cytology]]
!!__Cell types__
[[Eukaryote]]
* [[Plant cell]]
* [[Animal cell]]
[[Prokaryotes]]
!!__Cell structure__
[[Cell]]
__[[Cell organelles]]__
!!__Cell processes__
[[Cell division]]
[[Cellular respiration]]
[[Fermentation]]
[[Photosynthesis]]
!!![[Cell signaling]]
!!![[Cell specialization]]
[img[https://media.cellsignal.com/www/images/science/landscapes/ph-vesicle-trafficking.jpg]]
https://www.cellsignal.com/common/content/content.jsp?id=science-landscapes
[img[https://media.cellsignal.com/www/images/science/landscapes/ph-adhesion.jpg]]
http://www.cell.com/cell/home
[[Yeast in the Lab|https://www.youtube.com/watch?v=vXvOuunJYXM]]
-------------------------
https://www.wikiwand.com/en/Cell_culture
Cycle of life of a [[Cell]]
Interphase, S phase, metaphase
!!G1 phase
!!S phase
!!G2 phase
!! M phase
[[Cell division]]
Meta-to-anaphase transition
Other checkpoints.
!!__Regulation of cell cycle__
p53
!!!__Apoptosis__
__Necrosis__ (uncontrolled cell death)
Part of the [[Cell cycle]]
https://en.wikipedia.org/wiki/Cell_division
* [[Mitosis]]
* [[Meiosis]]
The molecule that carries the information is [[DNA]]
[[Cell transport]]
* [[Membrane protein]]
Bilayer of [[Phospholipid]]s. They live in a disordered gel phase (instead of a crystalline form). They are bound by [[Hydrophobic interaction]]s
Cell membranes [[self-assemble|Self-assembly]], as [[Micelle]]s do.
Permeable [[Hydrophobic]] molecules, like gases (CO,,2,,, O,,2,,). A bit permeable to small uncharged molecules, like water.
Immpermeable to [[Ion]]s
[[Nucleolus|https://en.wikipedia.org/wiki/Nucleolus]] where ribosomes (and some signal recognizing molecules) are created
[[Cytoeskeleton|https://en.wikipedia.org/wiki/Cytoskeleton]] mesh of microtubules and actine filaments along which [[molecular motors|Molecular motors]] walk
[[Centrosome|https://en.wikipedia.org/wiki/Centrosome]] organizes microtubules. It's where they originate. I think it's like the seed for [[their self-assembly|https://www.youtube.com/watch?v=OoRQWEeXcQc]]
[[Golgi apparatus|https://en.wikipedia.org/wiki/Golgi_apparatus]] packages proteins into membrane-bound vesicles inside the cell before the vesicles are sent to their destination
[[Endoplsamatic reticulum|https://en.wikipedia.org/wiki/Endoplasmic_reticulum]]. Proteins self-assemble inside them. [[More stuff|http://bscb.org/learning-resources/softcell-e-learning/endoplasmic-reticulum-rough-and-smooth/]]
[img width=450 [https://upload.wikimedia.org/wikipedia/commons/9/9e/Blausen_0350_EndoplasmicReticulum.png]]
This is how proteins are pushed inside the endoplasmatic reticuli while the ribosome assembles them:
[img class=img-centered [https://upload.wikimedia.org/wikipedia/commons/9/94/Protein_translation.gif]]
[[Cytoskeleton]]
........
!!!__Main stages of cell-cell signaling__
# Signal generation
# Transportation
# Reception
# Transduction
# Cellular reponse
!!__Signal transportation__
!!!__Forms of cell-cell signal transportation in vertebrates__
* Juxtacrine. contact deoendent.
* DIrect signalling -- gap junction. In [[Plant cell]]s, plasmodesmata. The fastest. milliseconds. Diffusion + potential.
* Autocrine
** Reinforces the signal
** Community (cooperative effect)
* Paracrine. Affects local environment.
** Examples: wound healing, response to allergens.
* Synaptic. Long-range and fast. [[Neuron]]s in [[Neuronal network]]s.
* Endocrine. Long range and slow. [[Hormone]]s. Travels through the [[Blood vessel]]s
[img[http://images.slideplayer.com/25/8230426/slides/slide_4.jpg]]
!!__Signal reception__
* Receptor on the plasma membrane
* Intracellular response, but then signal needs to be [[Hydrophobic]] to travel [[Cell membrane]]
__Cell-surface receptors__
* [[Ion channel coupled receptor]]s
* [[G-protein coupled receptor]]
* [[Enzyme coupled receptor]]
__Intracellular receptors__
* [[Steroid hormone]] receptors
* [[Estrogen]] receptors
!!__Signal transduction__
Signalling [[pathway|Metabolic pathway]]s
* Molecular switches (activate protein). [[Kinase]]s can work as these
* Second messengers.
__Molecular switches__
__[[Kinase]] signalling cascade__
amplification
scaffolding. different signals with same molecules
__Second messengers__
Intermediary signals, that often ends with activate [[Kinase]]s
__Calcium signalling__
Feedback generates [[Calcium]] ion waves and oscillatoions.
!!!__Signal integration/convergence__
!!!__Cell signalling networks__
!!!__Feedback__
See [[Pathway regulation]]
!!!__Main stages of cell-cell signalling__
# Signal generation
# Transportation
# Reception
# Transduction
# Cellular reponse
!!__Signal transportation__
!!!__Forms of cell-cell signal transportation in vertebrates__
* Juxtacrine. contact deoendent.
* DIrect signalling -- gap junction. In [[Plant cell]]s, plasmodesmata. The fastest. milliseconds. Diffusion + potential.
* Autocrine
** Reinforces the signal
** Community (cooperative effect)
* Paracrine. Affects local environment.
** Examples: wound healing, response to allergens.
* Synaptic. Long-range and fast. [[Neuron]]s in [[Neuronal network]]s.
* Endocrine. Long range and slow. [[Hormone]]s. Travels through the [[Blood vessel]]s
[img[http://images.slideplayer.com/25/8230426/slides/slide_4.jpg]]
!!__Signal reception__
* Receptor on the plasma membrane
* Intracellular response, but then signal needs to be [[Hydrophobic]] to travel [[Cell membrane]]
__Cell-surface receptors__
* [[Ion channel coupled receptor]]s
* [[G-protein coupled receptor]]
* [[Enzyme coupled receptor]]
__Intracellular receptors__
* [[Steroid hormone]] receptors
* [[Estrogen]] receptors
!!__Signal transduction__
Signalling [[pathway|Metabolic pathway]]s
* Molecular switches (activate protein). [[Kinase]]s can work as these
* Second messengers.
__Molecular switches__
__[[Kinase]] signalling cascade__
amplification
scaffolding. different signals with same molecules
__Second messengers__
Intermediary signals, that often ends with activate [[Kinase]]s
__Calcium signalling__
Feedback generates [[Calcium]] ion waves and oscillatoions.
!!!__Signal integration/convergence__
!!!__Cell signalling networks__
!!!__Feedback__
See [[Pathway regulation]]
__Creating assymetry__
* Asymmetric division of [[Stem cell]]s
* SYmmetric division, but [[Cell signaling]] causes asymmetry
** [[Positive feedback]]
** Cell fate induction. Some cells which have specialized can send a signal that makes other cells around specialize. --> Sequential induction
** Morphogen gradients. Turn gradients of information through [[Gene expression]] regulation to different types of cells.
__Organizer__
A group of cells that organizes early development.
''Cell transport'' is movement of materials across cell membranes. Cell transport includes passive and active transport:
* Passive transport does not require energy
* Active transport requires energy to proceed.
Passive transport proceeds through (simple) diffusion, facilitated diffusion and osmosis.
[[Non-equilibrium statistical mechanics: from a paradigmatic model to biological transport|http://iopscience.iop.org/article/10.1088/0034-4885/74/11/116601/meta]]
!!__Passive transport__
__Simple diffusion__
small non-polar molecules, like
* Oxygen
* Carbon dioxide
__Facilitated diffusion__
Large or polar molecules passing through membrane protein channels. Examples of molecules that need protein channels:
* Charged ions
* Glucose
__[[Osmosis]]__
Like water through aquaporins
!!__Active transport__
Requires energy, for e.g. in the form of ATP.
!!!__[[Ion channel]]s__
https://en.wikipedia.org/wiki/Ion_channel
Sodium-potassium pump
!!!__Endocytosis and exocytosis__
----------------
[[Cell Transport|https://www.youtube.com/watch?v=Ptmlvtei8hw]]
https://www.brightstorm.com/science/biology/cell-functions-and-processes/cell-transport/
[[Complex systems]], artificial life in [[Bio-inspired computing]]. See [[Dynamical systems on networks]], [[Discrete dynamical systems]]
[[Cellular automaton|https://en.wikipedia.org/wiki/Cellular_automaton]]
[[Exploring Cellular Automata|https://www.fourmilab.ch/cellab/manual/cellab.html#contents]]
[[Theory of Cellular Automata|https://theory.org/complexity/cdpt/html/node4.html]]
[[Classsification of Cellular Automata|http://www.cs.cmu.edu/~sutner/papers/ecss.pdf]]
[[Computer simulations of cellular automata|http://iopscience.iop.org/article/10.1088/0305-4470/24/5/007/meta]]
[[Automata theory]]
!!__Statistical mechanics of cellular automata__
[[Equivalence of Cellular Automata to Ising Models and Directed Percolation|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.53.311]]
[[Phase Transitions of Cellular Automata|http://download.springer.com/static/pdf/383/art%253A10.1007%252FBF01309255.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2FBF01309255&token2=exp=1466080666~acl=%2Fstatic%2Fpdf%2F383%2Fart%25253A10.1007%25252FBF01309255.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252FBF01309255*~hmac=03be81353c981a73c9671ca9fbfc4e687fa7c3964255a560d0b111f5c8879f11]] See [[Directed percolation]]
[[Statistical Mechanics of Probabilistic Cellular Automata|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.55.2527]]
[[Universality in Elementary Cellular Automata|http://www.complex-systems.com/pdf/15-1-1.pdf]] proves a conjecture made by Stephen Wolfram in 1985, that an elementary one dimensional cellular automaton known as “Rule 110” is capable of universal computation, i.e. it is a [[Turing machine]] (see [[Theory of computation]])
[[Statistical mechanics of cellular automata|http://www.stephenwolfram.com/publications/academic/statistical-mechanics-cellular-automata.pdf]]
!!![[Computation theory of cellular automata|http://www.stephenwolfram.com/publications/academic/computation-theory-cellular-automata.pdf]]
//A new kind of science// - Stephen Wolfram
[[http://www.paradise.caltech.edu/~cook/papers/index.html]]
[[Game of Life Cellular Automata|http://www.springer.com/gp/book/9781849962162]]
!!!__Elementary cellular automaton__ [[(wiki)|https://en.wikipedia.org/wiki/Elementary_cellular_automaton]]
[[Rule 90|https://en.wikipedia.org/wiki/Rule_90]]
[img width=400 [https://upload.wikimedia.org/wikipedia/commons/5/5b/R090_rand_0.png]]
[[Rule 30|https://en.wikipedia.org/wiki/Rule_30]]
[img width=500 [https://upload.wikimedia.org/wikipedia/commons/d/d9/Rule30-first-500-rows.png]]
!!__Examples__
[[Von Neumann cellular automata|https://en.wikipedia.org/wiki/Von_Neumann_cellular_automaton]] are the original expression of cellular automata, the development of which were prompted by suggestions made to John von Neumann by his close friend and fellow mathematician Stanislaw Ulam. Their original purpose was to provide insight into the logical requirements for machine self-replication and were used in von Neumann's universal constructor.
[img[https://upload.wikimedia.org/wikipedia/commons/5/50/VonNeumann_CA_demo.gif]]
[[Codd's cellular automaton|https://en.wikipedia.org/wiki/Codd%27s_cellular_automaton]] designed to recreate the computation- and construction-universality of von Neumann's CA but with fewer states: 8 instead of 29.
[img[https://upload.wikimedia.org/wikipedia/commons/6/69/Codd_CA_RepeaterEmitter.gif]]
[[Conway's Game of Life|https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life]]
[img[https://upload.wikimedia.org/wikipedia/commons/e/e5/Gospers_glider_gun.gif]]
[[Langton's loops|https://en.wikipedia.org/wiki/Langton%27s_loops]] consist of a loop of cells containing genetic information, which flows continuously around the loop and out along an "arm" (or pseudopod), which will become the daughter loop
[img widh=500 [https://upload.wikimedia.org/wikipedia/commons/2/28/Langtons_Loop_Colony.png]]
[[Nobili cellular automata|https://en.wikipedia.org/wiki/Nobili_cellular_automata]] are a variation of von Neumann cellular automata (vNCA), in which additional states provide means of memory and the interference-free crossing of signal.
[img widh=500 [https://upload.wikimedia.org/wikipedia/en/9/98/Lambda-G.png]]
[[Brian's Brain|https://en.wikipedia.org/wiki/Brian%27s_Brain]]
[img[https://upload.wikimedia.org/wikipedia/commons/a/a7/Brian%27s_brain.gif]]
[[Langton's ant|https://en.wikipedia.org/wiki/Langton%27s_ant]]
[img[https://upload.wikimedia.org/wikipedia/commons/f/f9/LangtonsAnt-nColor_LLRRRLRLRLLR_36437.png]]
[img[http://i.imgur.com/YBBk3fl.gif]]
[[Wireworld|https://en.wikipedia.org/wiki/Wireworld]]
[img[https://upload.wikimedia.org/wikipedia/commons/5/5d/Animated_display.gif]]
---------
See also [[Discrete dynamical systems]]
[img[http://www.ddlab.com/gdca_cropped_front_cover.jpg]]
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http://psoup.math.wisc.edu/mcell/ca_gallery.html
//The way [[cells|Cell]] [[produce energy|Energy production]]//
[[ATP & Respiration: Crash Course Biology #7|https://www.youtube.com/watch?v=00jbG_cfGuQ&list=PL3EED4C1D684D3ADF&index=7]] -- [[MIT edx video|https://www.youtube.com/watch?v=U-GyLD1zHms]]
[img[https://s16.postimg.org/6u628q4s5/Selection_603.png]]
Most of the [[Biomolecule]]s that gives us energy are processed and end up as [[Glucose]]
[[Glucose]] + 6 [[Oxygen]] --> 6 [[Carbon dioxide]] + 6 [[Water]] + [[ATP]] ([[Energy]])
!Cellular respiration stages
!!!__[[Glycolysis]]__
Breaking [[Glucose]] into two 3-carbon molecules, called [[Pyruvic acid]]s, or pyruvate molecules. It also uses 2 ATPs, produces 4 ATPs. It also produces NADH
Uses many enzymes, like phosphoglucoisomerase.
It is an anerobic process, as it doesn't need oxygen. If there isn't oxygen the pyrovates undergo [[Fermentation]]. Anaerobic respiration can also produce lactic acid.
However, the next steps in cellular respiration are aerobic and require oxygen.
!!!__[[Krebs cycle]]__
Happens inside inner membrane of the [[Mitochondria]]
Pyruvate molecules >> 2 ATP (per glucose) + Energy
First pyruvates are oxydized. One of the three carbons in the chain bonds with 2 oxygens, and leaves as CO,,2,,. It leaves a 2-carbon compound called Acetyl coA ([[Acetyl coenzyme A]])
Also an NAD+ picks up an H to form NADH
ATP
Form citric acid, from oxaloacetic acid and the Acetyl coA
There's more.... produce NADH and FADH,,2,,
!!!__[[Electron transport chain]]__
On membrane
ATP synthase
[img[https://myorganicchemistry.wikispaces.com/file/view/structureofcellulose.gif/146911585/756x258/structureofcellulose.gif]]
Long cellulose chains can [[Hydrogen bond]] accross themselves, and be very strong. These form the [[Cell wall]]s of [[Plant cell]]s, that make plants, like [[Tree]]s rigid!
[img[http://bio1151.nicerweb.com/Locked/media/ch05/05_08CelluloseArrange.jpg]]
A ''ceramic'' is a rigid material that consists of an infinite three-dimensional network of sintered crystalline grains comprising metals bonded to carbon, nitrogen, or oxygen. ([[IUPAC|http://www.degruyter.com/dg/viewarticle.fullcontentlink:pdfeventlink/$002fj$002fpac.2007.79.issue-10$002fpac200779101801$002fpac200779101801.pdf/pac200779101801.pdf?t:ac=j$002fpac.2007.79.issue-10$002fpac200779101801$002fpac200779101801.xml]])
Note: The term ceramic generally applies to any class of inorganic, non-metallic product subjected to high temperature during manufacture or use.
See also [[https://en.wikipedia.org/wiki/Ceramic]]
The principal and most anterior part of the [[Brain]] in vertebrates, located in the front area of the skull and consisting of two hemispheres, left and right, separated by a fissure
!!__Regions of the cerebrum__
* ...
* [[White matter]]
* [[Cortex]]
[[Chair|https://en.wikipedia.org/wiki/Chair]] is a piece of furniture with a raised surface, commonly used to [[seat|Seat]] a single person.
[img[http://mediatechnologies.com/images/sized/uploads/products/pr_post_chair-0x640.png]]
In [[Data transmission]], the ''channel capacity'' is defined as
$$C=\max_{p(x)} I(X;Y)$$
That is, the maximum mutual information of the conditional probability p above, where the maximization is done over possible proabilities of the outputs (or equivalently, probabilities of inputs). One can show this is equal to the maximum rate of information transfer over a channel such that we can recover the information on the ouput with negligible probability of error.
Note that changing the probabilities of the inputs can be accomplished by choosing different codes to encode the input. Therefore the channel capacity can be considered to be maximizing over codes. In particular:
[[Channel coding theorem]]: Long enough code blocks can achieve the channel capacity limits (similar to arguments for understanding entropy by many trials).
The capacity $$C$$ is the logarithm of the number of distinguishable input signals.
,,aka noisy-channel coding theorem,,
In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem), establishes that for any given degree of noise contamination of a communication channel, it is possible to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel, called the [[Channel capacity]].
In other words, the theorem states that given a noisy channel with channel capacity C and information transmitted at a rate R, then if R<C there exist codes that allow the probability of error at the receiver to be made arbitrarily small. This means that, theoretically, it is possible to transmit information nearly without error at any rate below a limiting rate, C.
,,Long enough code blocks can achieve the channel capacity limits (similar to arguments for understanding entropy by many trials).,,
See [[Data transmission]]
A [[Membrane protein]] that regulates [[Cell transport]]
[[Design a channel protein|https://www.youtube.com/watch?v=CxMrkVsKF8k]]
* [[Ion channel]]
--> See [[Oxford course notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3082/141/main_4.pdf]]
!!__Characteristics of chaos__
* Countable infinity of periodic orbits
* Uncountable infinity of aperiodic orbits
* Sensitive dependence on initial conditions. See Lyapunov exponents in [[Nonlinear dynamical systems]]
* A dense orbit, which comes arbitrarily close to all periodic orbits.
__Chaotic [[maps|Nonlinear maps]]__
[[Symbolic dynamics]] can be used to analyze them
* Logistic map
* Binary shift map
* Skinny baker map
* [[Smale horseshoe map]]
__Chaotic [[Nonlinear dynamical systems]]__
* Lorenz system
* Rossler system
* [[Duffing oscillator]]
!!__Routes to chaos__
!!!__Period doubling__
''Sarkovskii's theorem''
Period 3 implies chaos
!!!__Intermittency__
!!!__Blue sky catastrophe__
--------------
Every chaotic dynamical system is a fractal-manufacturing machine
[img[https://pbs.twimg.com/media/Cgg8HmqXIAAn42P.jpg:large]]
[[An Introduction to chaotic dynamical systems. Second edition|http://www.nehudlit.ru/books/detail5822.html]]
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
* [[Ionic interactions|Ionic bond]] Electronic transfer of electrons between atoms makes them ions which attract via the [[Coulomb interaction]], so $$1/r$$ and isotropic. It is $$\sim 100 k_B T$$. However, interaction is strongly modified in a solution, due to __screening__ (similar to Debye screening in [[Plasma physics]]).
* [[Covalent bond]]s. Due to shared electrons that are attracted to both nuclei (or sometimes a few nuclei, in molecules). These are the most common bonds in molecules (see [[Molecular physics]]). They are short-ranged and highly directional (anistropic). They are $$\sim 30\text{ to }100 k_B T$$ at room $$T$$.
* ''Metallic bonds'', are an special case of covalent bond, where electrons are delocalized over macroscopic regions. Commons in metals.
* “vibrational” chemical bond. http://www.scientificamerican.com/article/chemists-confirm-the-existence-of-new-type-of-bond/
A ''Chemical compound'' refers to a [[Chemical substance]] which includes at least two different [[element|Chemical element]]s (although this condition may be relaxed, I think).
* [[Organic compound]]
* [[Inorganic compound]]
---------------
http://www.bbc.co.uk/education/guides/zb3j6sg/revision/2
Non-metal oxides usually form acids, as they are very electronegative.
Metal oxides tend to form bases, as the metal is not very electronegative.
A [[Chemical substance]] composed of a single type of [[Atom]]
Some properties of the main classes of elements (metals and non-metals): http://www.bbc.co.uk/education/guides/zb3j6sg/revision/2
The study of [[Chemical reaction]]s, using the tools of [[Statistical physics]], in particular [[Thermodynamics]]
[[Chemical energetics|http://www.science.uwaterloo.ca/~cchieh/cact/applychem/chemenergy.html]]
!!__Reaction thermodynamics__
Uses the theory of [[Statistical mechanics of multispecies systems]]
Balance of [[Chemical potential]]s of reactants and products (note that [[Chemical potential]] is proportional to [[Gibbs free energy]] in the [[Grand canonical ensemble]]). See [[video|https://www.youtube.com/watch?v=zfC22N_2hOc#t=7m]].
The chemical potential energy difference can be epxpressed as:
$$\Delta G = \Delta G^0' + RT \ln{\frac{[A]}{[B]}}$$
where $$\Delta G^0' $$ is the change in Gibbs free energy of a reaction of the form $$A \rightarrow B$$, $$[i]$$ represents the [[concetration|Concentration (chemistry)]] of the [[Chemical species|Chemical substance]] $$i$$.
As can be derived from the [[Second law of thermodynamics]], at constant pressure and temperature, an spontaneous process occurs if its Gibbs free energy change is negative.
See note in tablet
[[Chemical equilibrium|http://www.bbc.co.uk/education/guides/z7qfr82/revision/2]] and the effects of [[pressure|http://www.bbc.co.uk/education/guides/z7qfr82/revision/3]] and [[temperature|http://www.bbc.co.uk/education/guides/z7qfr82/revision/4]]
Energy is absorbed to break bonds and released when bonds are made. Energy changes in a reaction are calculated by bond energies and shown by energy diagrams. See [[here|http://www.bbc.co.uk/education/guides/zsn9q6f/revision]]
!!__[[Chemical kinetics]]__
[[Non-equilibrium statistical physics]] of chemical reactions, in particular the rates at which they occur.
https://en.wikipedia.org/wiki/Chemical_engineering
A notation for a [[Chemical reaction]]
http://www.bbc.co.uk/education/guides/zgg7hyc/revision/2
http://www.bbc.co.uk/education/guides/zgg7hyc/revision/1
[[Empirical formula|http://www.bbc.co.uk/education/guides/zgg7hyc/revision/4]] -- [[Finding empirical formulas experimentallly|http://www.bbc.co.uk/education/guides/zgg7hyc/revision/5]]
[[Non-equilibrium statistical physics]] of chemical reactions, in particular the rates at which they occur.
http://www.bbc.co.uk/education/guides/z4cmn39/revision
[[measuring rates|http://www.bbc.co.uk/education/guides/zwdp34j/revision]]
!!!__Examples__
[[Enzyme kinetics]]
[[Molar mass]]
-- [[Relative molecular mass]]
-- [[Relative formula mass]]
[[Unified atomic mass unit]]
[[Relative atomic mass]]
--------------
Related: [[Mole]]
A chemical nomenclature is a set of rules to generate systematic names for chemical compounds. The nomenclature used most frequently worldwide is the one created and developed by the International Union of Pure and Applied Chemistry (IUPAC).
For [[Organic compounds]], usually one part of the name identifies the [[Hydrocarbon]] framework, another identifies the [[Functional group]]s, and another locates the groups in the framework.
https://en.wikipedia.org/wiki/Chemical_nomenclature
https://en.wikipedia.org/wiki/Chemical_potential
[[Chemical Potential, Raoult's Law and Ideal Solutions|http://www.chm.bris.ac.uk/~chdms/Teaching/Chemical_Interactions/page_23.htm]]
[[Aqueous Salt Solutions|http://www.phasediagram.dk/chemical_potentials.htm]]
[[Chemical Potential Phase Transitions Mixtures |http://chemistry.tcd.ie/staff/people/duesberg/ASIN/lecture%20notes/Chapter%205_%20Chemical%20Potential_in_Liquids_annoted.pdf]]
[[The chemical potential|http://www.tf.uni-kiel.de/matwis/amat/def_en/kap_2/advanced/t2_4_1.html]]
[[Chemical Potential |http://staff.um.edu.mt/jgri1/teaching/che2372/notes/05/i_chem_pot.html]]
[[The Chemical Potential and Phase Equilibria |http://stp.clarku.edu/notes/chap7.pdf]]
See books by Kardar, oxford notes, etc.
[[The chemical potential in non-ideal liquid mixtures|http://www.tandfonline.com/doi/abs/10.1080/00268978300101811]]
See [[Solution (Chemistry)]]
A ''chemical reaction'' is a process that leads to the transformation of one set of [[Chemical substance]]s to another.
* [[Organic reaction]]s
* [[Condensation reaction]]
* [[Dehydration synthesis]]
* [[Synthesis reaction]]
* [[Decomposition reaction]]
** [[Hydrolysis]]
* [[Single replacement reaction]]
* [[Double replacement reaction]]
* [[Acid-base reaction]]
* [[Redox reaction]]
* [[Combustion]]
!!![[Chemical energetics]]
[[Continuous dynamical system]] (Systems of [[ODE|Ordinary differential equation]]s), [[Dynamical systems on networks]].
https://crnt.osu.edu/
Based on the theory of [[Chemical kinetics]]
!!__Mass-action dynamical system__
Can write as a dynamical system
$$\dot{\mathbf{x}} = S \cdot \mathbf{v}$$
where $$S$$ is the ''stoichiometrix matrix'', and $$v$$ is the ''flux vector''.
[img[stoichiomestry_matrix.png]]
[img[chem_net_flux_vector.png]]
This assumes the [[Law of mass-action]]. Mass action kinetics does not always capture correct dynamics, because of more complicated constraints and stochastic dynamics.. In more, general models $$v$$ has a more complicated form.
__Steady state__
$$\dot{x}=Sv_s=0$$. $$v_s$$ has to be in the null space of $$S$$.
__Conservation relations__
Vectors that satisfy $$\mathbf{w}^T \dot{\mathbf{x}} = \mathbf{w}^T \mathbf{S} \mathbf{v}=0$$.
$$w$$ lives in the null space of $$S^T$$
!!__Flux analysis (stochiochemistry)__
Because the S matrices are very often fat matrices, the null space is and thus the space of stationary state fluxes is often relatively high dimensional. This is useful for design ([[Synthetic biology]]).
$$\alpha v_1 + \beta v_2 + ... \geq 0$$ is a constraint on the fluxes. This defines a cone (a special case of the polyhedra found in [[Linear programming]])! Hm I can only see it being a cone if there are conditions like $$\alpha \geq 0$$ otherwise, it's just the intersection of the positive part of the full space and the null subspace.
!!!__[[Sensitivity analysis]]__
---------------
!!__Generalized Mass Action/S-Systems__
----------------
Used in [[Biochemistry]], and [[Chemistry]].
A ''chemical substance'' refers to either:
* A [[Molecule]] composed of a given set of [[Atom]]s in a certain configuration.
* or to a [[Substance|Bulk matter]] composed of identthat molecule.MoleculaMolecular physicsA system of [[Atom]]s bound by [[Chemical bond]]s
----------
https://www.google.es/#q=chemical+substance
__[[The synthesis machine|http://science.sciencemag.org/content/347/6227/1190]] !!__
<<<
The ability to make small organic molecules is at the heart of everything from drug development to the making of new dyes and agricultural chemicals. But ever since the dawn of synthetic organic chemistry in the 1820s, the process has required slow, painstaking effort. Now, however, researchers led by Martin Burke, a chemist at the University of Illinois, Urbana-Champaign, have developed a novel machine that may change all that. The machine automatically synthesizes new small organic molecules by welding together premade building blocks that can be put together in any configuration. Two hundred such building blocks already exist. And thousands of other similar molecules can also be used in the process. As a result, the machine has the ability to make billions of different small organic compounds that can then be tested as new drugs or for other uses. If widely adopted, the synthesis machine could revolutionize organic chemistry, turning it from a slow, painstaking process to a made-for-order business.
<<<
Idea for neural network for chemical synethesis and manufacturing etc. Facebook post: [[https://www.facebook.com/guillermovalleperez/posts/10153853693416223?]]
[[Chemical reaction]]
[[Atomic structure]]
[[Experimental chemistry]]
[[Dynamic periodic table|http://www.ptable.com/]]
[img[periodic table.png]]
[[IUPAC nomenclature page|http://www.chem.qmul.ac.uk/iupac/]] [[Gold book|http://goldbook.iupac.org/index.html]]
[[TED-Ed and Periodic Videos|http://ed.ted.com/periodic-videos]]
[[The Photographic Periodic Table of the Elements|http://periodictable.com/]]
John ~McMurry, Robert C. Fay-Chemistry, 6th Edition-Prentice Hall (2012)
[[IUPAC interactive link map|http://goldbook.iupac.org/Graphs/R05063.3.map.html]]
!!![[Croning group|http://www.chem.gla.ac.uk/cronin/research.php]] Very nice research in inorganic biology, evolution, synthesis, and applications..
(Theilheimer's Synthetic Methods of Organic Chemistry ) Alan F. Finch-S Karger Pub (2001)
//Random//
https://en.wikipedia.org/wiki/Hydrolysis
[[scents.jpg]]
[[http://www.compoundchem.com/2016/05/04/oxidation-reactions-of-alcohols/]]
Chemotaxis (from chemo- + taxis) is the movement of an organism in response to a chemical stimulus.
https://en.wikipedia.org/wiki/Chemotaxis
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/d/d8/Chtx-AttrRep-en.png/250px-Chtx-AttrRep-en.png]]
See also [[Phoretic mechanisms of self-propelled colloids]]
https://www.wikiwand.com/en/Chi-squared_test
[[Chiral|Chirality]] [[Molecule]]
Something is chiral when its mirror image cannot be made to coincide with itself using rotations.
[[Molecule]]s are often chiral, and this is important in [[Biology]], where only one [[Steroisomer]] is usually found.
[[Axial chirality]]
Flames without oxygen :)
[[Setting Fire to Glass - The "Nope" Chemical That is Chlorine Trifluoride|https://www.youtube.com/watch?v=dAhiqGZCwNQ]]
https://www.physicsforums.com/threads/substitue-for-oxygen-in-fire.499707/
https://en.wikipedia.org/wiki/Chromatin
!!__Folded chromatin --> [[Chromosome]]__
During [[Cell division]]
<img style="background-color:white;" src="https://upload.wikimedia.org/wikipedia/commons/4/4b/Chromatin_Structures.png">
!!__Unfolded chromatin__
[img[http://www.mun.ca/biology/desmid/brian/BIOL2060/BIOL2060-18/18_21.jpg]]
--------------------
The human genome is made of 23 chromosome pair which are contained within the cell nucleus. During mitosis and
meiosis the chromosome condense into supercoiled chromatids attached into pairs at the centromere. While during normal
cellular growth, known as interphase, the chromosomes need to unfold in order for the DNA to be either replicated or for gene
transcription to occur. The total size of the human genome is approximately 3 thousands Mega-basepairs (3 billion BPs),
which needs to be contained inside the cells nucleus, only ~10 micron (0.01mm) in diameter. The DNA is wrapped around
nucleosomes consisting of an octamer of histone proteins which can be up to 80bp appart. The linker DNA between histones
contains cis-regulatory elements. They are non-coding DNA sequences such as core and proximal promoter regions,
enhancers, silencers and other type of sites that can bind transcription factors and activators, and thus, regulate gene
expression. ~ Nikolai Drouzine
''Chromatography'' (/ˌkroʊməˈtɒɡrəfi/; from Greek χρῶμα chroma which means "color" and γράφειν graphein "to write"[1]) is the collective term for a set of laboratory techniques for the separation of [[Mixture]]s.
* [[Column chromatography]]
* [[Paper chromatography]]
Chromatography is a type of [[Separation process]]
------------------------
https://www.wikiwand.com/en/Chromatography
[[Forster resonance energy transfer]]
''Chromosomal crossover'' (or crossing over) is the exchange of genetic material ([[DNA]]) between [[Homologous chromosome]]s that results in [[recombinant|Genetic recombination]] [[Chromosome]]s during [[Sexual reproduction]].
https://www.wikiwand.com/en/Chromosomal_crossover
A ''chromosome'' is a single molecule of DNA, containing many genes; an organisms often has several chromosomes. In a chromosome, the DNA is wound on //histone// proteins, and very densely packed, so that it can fit inside the nucleus. The packing structure is illustrated [[here|https://en.wikipedia.org/wiki/Chromosome#/media/File:Chromatin_Structures.png]].
[[Chromosome]]s carry the [[Gene]]s that Mendel studied. [[Cytology and the chromosomal theory of inheritance|https://www.youtube.com/watch?v=uLsVEYdn_e4]]
[[Mendel's 2nd law vs chromosome theory|https://www.youtube.com/watch?v=cbbnGiiu_SI#t=9m38s]] [[How to resolve it: Fruit flies and linkage|https://www.youtube.com/watch?v=Pq3l24TyEbw]] (experiments by [[Thomas Hunt Morgan|http://www.nature.com/scitable/topicpage/thomas-hunt-morgan-the-fruit-fly-scientist-6579789]], with //Drosophila melanogaster//
!!!--> [[Genetic linkage]] and [[Homologous recombination]] (caused by [[Chromosomal crossover]], which occurs during [[Meiosis]])
!!!__[[Mode of inheritance]]__
--> [[Genetic dominance]] (gives rise to ''modes of inheritance'')
* [[Diploid]] cells have two copies of each chromosome, called [[Homologous pair]]s, except, maybe for [[Sex chromosome]]s. These "copies" are not identical, the are homologous, they have the same genes (or almost), but just different alleles.
* [[Haploid]]. Just one copy of each chromosome. [[Gamete]]s are haploid.
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https://www.wikiwand.com/en/Boveri%E2%80%93Sutton_chromosome_theory
''Chromostereopsis'' is a visual illusion whereby the impression of depth is conveyed in two-dimensional color images, usually of red-blue or red-green colors, but can also be perceived with red-grey or blue-grey images. Such illusions have been reported for over a century and have generally been attributed to some form of chromatic aberration.
[img[http://i.imgur.com/yUHl7jf.png]]
------------------
https://www.wikiwand.com/en/Chromostereopsis
[[Church-Turing thesis (vid)|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=6m30s]]
''[[Church-Turing thesis|https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis]]''
[[Scott Aaronson, "Remarks on the Physical Church-Turing Thesis" FQXi conference 2014 in Vieques|https://www.youtube.com/watch?v=2jz0ugqghys]]
http://research.cs.queensu.ca/home/akl/cisc879/papers/PAPERS_FROM_MINDS_AND_MACHINES/VOLUME_13_NO_1/V23L84X656370574.pdf This gets quite philosophical of course
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
[[Circular economy: Lessons from China|http://www.nature.com/news/circular-economy-lessons-from-china-1.19593?WT.mc_id=FBK_NA_1603_NEWSCOMMENTLESSOSFROMCHINA_PORTFOLIO]]
[[Circular economy: Getting the circulation going|http://www.nature.com/nature/journal/v531/n7595/full/531443a.html?WT.mc_id=FBK_NA_1603_FHBOOKSARTSCIRCULARECONOMY_PORTFOLIO]]
[[Nature: circular economy|http://www.nature.com/news/circular-economy-1.19546?WT.mc_id=FBK_NA_1603_NATSPCIRCULARECONOMY_PORTFOLIO]]
See [[Architecture]]. Relations to society, and societal organization: infrastructure, economy, governance, culture.
A [[civilization|https://en.wikipedia.org/wiki/Civilization]] is any complex society characterized by urban development, social stratification, symbolic communication forms (typically, [[Writing system]]s), and a perceived separation from and domination over the natural environment by a cultural elite.
[[Structure and interpretation of classical mechanics|http://mitpress.mit.edu/sites/default/files/titles/content/sicm/book.html]]
!!!__Rolling__
[img[https://upload.wikimedia.org/wikipedia/commons/2/2e/Rolling_Racers_-_Moment_of_inertia.gif]]
Note: red is a hollow sphere
!!__Theory__
[[D'Alembert's principle]]
[[Lecture Series on Classical Physics by Prof.V.Balakrishnan|https://www.youtube.com/watch?v=Q6Gw08pwhws&list=PL5E4E56893588CBA8]]
[[11th Class Physics :Mechanics, Heat, Oscillations and Waves By Prof. V. Balakrishnan|https://www.youtube.com/playlist?list=PLq-Gm0yRYwThKeMSP_ii5klqDYvta4HQI]]
//aka pattern recognition//
[[Supervised learning]], where the output value is discrete, or categorical, or qualitative. No implicit ordering, or closeness on the variables. See [[video|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=50m]].
Many of the same methods as in [[regression|Regression analysis]]. In fact, classification is often approached by modelling a posterior probability $$p(y|x)$$, and predicting the most probably $$y$$. Because this is a continuous function of $$x$$, learning it can be done by using [[Regression analysis]]
!!__Supervised classification__
!!!__Binary classification__
[[Logistic regression]] (Classification with 2 classes). A simpler version: [[Perceptron]].
!!!__Multiclass classification__
Classification with $$k $$ classes.
[[Softmax regression]]
See [[Generalized linear model]] for other more generalized methods.
[[Artificial neural network]] (see also [[Deep learning]])
[[Support vector machine]]s. Software for SVMs: http://svmlight.joachims.org/
[[Nonparametric|Nonparametric statistics]] algortihm: [[Nearest-neighbour classification]]
[[Decision tree]]s
*[[Random forest]]
__Multiclass classification using binary classifiers__
see page 16 [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides09.pdf]].
__One-vs-one__
__One-vs-rest__
May create hard learning problems when combining some classes (resulting in regions with weird shapes, that are hard to linearly separate). With decisino trees, this can be exacerbated.
__[[Decision tree]]s__
Reducing Multiclass to Binary.E. Allwein, R. Schapire, Y. Singer
!!!__Multi-label classification__
If the class labels are not mutually exclusive. This can be modelled by using multiple related binary class labels, each marking whether the input belongs to a particular class. This is a //multiple output model//.
!!![[Bootstrap aggregation]]
!!!__[[Generative supervised learning]]__
!!__Unsupervised classification: [[Clustering]]__
----------------
!!!__Ordered categorical classification__
Output has a notion of order, but not closeness, so it's qualitative, aka ordinal learning.
---------------------
!!!__Measuring performance__
using a confusion matrix
can give different [[costs|Loss function]]..
([[Decision theory]])
TPR vs FPR
Precision vs recall
__How to tune classifer to satisfy these criteria?__
..
---------------
[[Pattern Recognition Class|https://www.youtube.com/playlist?list=PLuRaSnb3n4kRDZVU6wxPzGdx1CN12fn0w]]
https://www.wikiwand.com/en/Statistical_classification
An [[Activity]] or [[Process]] aimed at, or resulting in, making something [[Clean|https://www.wikiwand.com/en/Cleanliness]].
//or climate science//
[[Climate - Springer|http://www.springer.com/climate?SGWID=0-1755018-0-0-0]]
https://earth.nullschool.net/
See also [[Environmental studies]]
https://clojure.org/
[[Clojure Made Simple|https://www.youtube.com/watch?v=VSdnJDO-xdg]]
Clothing refers to a traditional set of [[Wearable]]s made mostly from [[Textile]]s found in most human [[Culture]]s, and often having considerable cultural signifiance. They are also known as garment.
https://www.wikiwand.com/en/Clothing
* [[Headgear]]
* [[Footwear]]
[[Amazon Elastic Compute Cloud|http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/concepts.html]]
!!!__Dropbox__
Dropbox bash command line app: https://github.com/andreafabrizi/Dropbox-Uploader
`./dropbox_uploader.sh -sp upload ../st10len30/biases st10len30`
[[Clustering Introduction - Practical Machine Learning Tutorial with Python p.34|https://www.youtube.com/watch?v=ZueoXMgCd1c&index=34&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
!!__Types__
__Flat clustering__
__Hierarchical clustering__
!!__Algorithms__
!!!__[[K-means algorithm]]__
!!!__[[Mixture model]]__
!!!__[[Mean shift]]__ (for hierachical clustering)
!!!__[[UPGMA]]__
-------------------
__Community clustering in networks__
Q measure..
See [[MMathPhys oral presentation]], [[Algorithmic information theory]]
Using the coding theorem to estimate the Kolmogorov complexity of short strings. The estimate is defined as:
$$K_m (s) = -\log_2(D(n,k)(s))$$
where
$$D(n,k)(s) : = \frac{|\{T \in (n,k) : T \text{ produces } s\}|}{|\{T \in (n,k) : T \text{ halts}\}|}$$
where $$(n,k)$$ is the set of [[Turing machine]]s with $$n$$ states and $$k$$ letters in the alphabet of the input tape. The Turing machines are fed a blank tape, and whether the program halts is determined using a [[Busy beaver]] function.
An extension to $$N$$-dimensional arrays has been developed using the [[Block decomposition method]]
----------------------
See [[this paper|http://singmann.org/download/publications/2015_gauvrit_et_al_brm.pdf]] and [[this one|http://www.ncbi.nlm.nih.gov/pubmed/24311059]] For some reason this seems to be a popular idea in [[Psychology]].
Using these methods the people at [[Algorithmic nature group|http://algorithmicnature.org/]] made [[The Online Algorithmic Complexity Calculator|http://www.complexitycalculator.com/index.php]]
More: [[Numerical evaluation of algorithmic complexity for short strings: A glance into the innermost structure of randomness|http://cristal.univ-lille.fr/~jdelahay/dnalor/DelahayeZenilNumerical.pdf]]
[[Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0096223]]
A ''code'' is a representation of data, represented as an injective map between two sets. These sets are often called the //Source alphabet//, and the //code alphabet//, respectively.
''Coding theory'' (and/or //coding methods//) is the study of codes that satisfy certain properties. These properties are often geared towards [[Data transmission]], [[Data compression]], and other areas in [[Information theory]].
!!__Types of codes__
[[Variable-length code]]
!!__Codes for transmission/storage reliability__
Codes that approach the [[Channel capacity]] limit imposed by the [[Channel coding theorem]]
See [[Error-correcting code]]
!!__Codes for transmission/storage efficiency__
Codes that approach the //entropy limit// imposed by the [[Source coding theorem]] for lossless codes, or the limits imposed by [[Rate compression theory]] for lossy codes.
See [[Data compression codes]]
-----------------------------
https://www.youtube.com/channel/UCgzV25kcbpkRMfYSNSgCAFA
[[https://www.youtube.com/playlist?list=PL2E3F2883347BB45B]]
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
[[Conscious|Consciousness]] part of the [[Mind]], I think.
See [[Cognitive science]]
[img[https://cdn-images-2.medium.com/max/2000/1*71TzKnr7bzXU_l_pU6DCNA.jpeg]]
The "too much information" refers to our [[Attention]] mechanisms that the brain develops to deal with information overload.
http://www.research.ibm.com/cognitive-computing/
That is the promise of <b>cognitive systems</b>--a category of technologies that uses <b>natural language processing</b> and <b>machine learning</b> to enable people and machines to interact more naturally to extend and magnify human expertise and cognition. These systems will learn and interact to provide expert assistance to scientists, engineers, lawyers, and other professionals in a fraction of the time it now takes.
* Basics. Exercise diet
* Education
* Collective intelligence
* Extended mind
__Drugs__
* Stimulants
** Caffeine
** Modafinil
** Amphetamine
** ..
** Nicotine
*AMPA modulators
**
* Others
**AChe...
__Electric estimulation__
* Transcranial stimulation
** TMS
*tDCS
* Intracranial stimulation
** DBS. Used for parkinsons, etc.
***Fornix
*** central thalamus
** Electrode array
** Optogenetics
** Transcranial focused [[Ultrasound]]
** Cortical brain-computer interface. Paralized people
** Ted Berger and Kernel startup!
*** Multi-input multi-output model. NN to read activity in multiple parts of hippocampus. --> Memory enhancement!
[[Idea Framing, Metaphors, and Your Brain - George Lakoff|https://www.youtube.com/watch?v=S_CWBjyIERY]]
[[Neuroscience]] to explain the higher-level features of the [[Mind]], studied in [[Cognitive science]]
[[video|https://www.youtube.com/watch?v=w2sSPSVx2f0&list=PLwwc_gbg2bKI_bDJ-cLtvK8h2eq5mE3ZS#t=21m5]]
* [[Representation]]. A physical state that represents [[Information]].
* Cognitive [[Process]]: Transforming information, information //processsing//
[[Consciousness and perception for everyone|https://www.youtube.com/playlist?list=PL0D746480FAEFA3C9]]
!!__Neural foundation of [[Mathematics]]__
!!__Neural theory of [[Language]]__
[[Cognitive framing]]
---------------
[[Cognitive psychology]]
[[Psychological|Psychology]] study of [[Cognition]].
[[Cognitive neuroscience]]
https://www.wikiwand.com/en/Cognitive_science
[[Mind]], [[Consciousness]], [[Thought]], [[Concept]], [[Philosophy]], [[Psychology]]
[[Intelligence]]
[[Neuroscience]] --> __[[Cognitive neuroscience]]__
[[Psychology]] -> [[Cognitive psychology]]
[[Qualia]]
[[Learning]]
* [[One-shot learning]]
[[Cognitive framing]]
[[George Lakoff. The Brain's Mathematics: The Cognitive and Neural Foundations of Mathematics|https://www.youtube.com/watch?v=S-TZBvjc3s8]]
http://cognet.mit.edu/
-----------------
<img style="background: white;" src="https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Cognitive_Science_Hexagon.svg/1024px-Cognitive_Science_Hexagon.svg.png?1477067668045">
[[What is Cognitive Science?|https://www.youtube.com/watch?v=tEuGpc16fB8]]
See [[Active colloid]], [[Self-diffusiophoresis]], [[Self-propelled particle]]. See also [[Collective hydrodynamics of active entities]], [[Self-assembly of active colloids]]
!!!<i class="fa fa-star-o" aria-hidden="true"></i> Recent review: [[Emergent behavior in active colloids|http://iopscience.iop.org/article/10.1088/0953-8984/28/25/253001/meta]]
<span style="color:orange;">Dynamic self-organization of motile components</span> can be
observed in a wide range of length scales, from bird flocks ([[ref|http://www.annualreviews.org/doi/abs/10.1146/annurev-conmatphys-031113-133834]]) to bacterial colonies ([[ref|http://www.tandfonline.com/doi/abs/10.1080/000187300405228]], [[ref|http://www.pnas.org/content/107/31/13626]]) and assemblies of motor and
structural proteins ([[ref|http://www.springer.com/gp/book/9783540738442]]). The fascination with these phenomena has naturally inspired researchers to use a physical under-standing of motility to engineer complex emergent behaviors in model systems that promise revolutionary advances in technological applications if combined with other novel biomimetic functions, such as signal processing and decision making (see [[Swarm robotics]]), or replication (see [[Self-replication of information-bearing nanoscale patterns|http://www.nature.com/nature/journal/v478/n7368/full/nature10500.html]]).
Biological components pose inevitable limitations on this task, while chemical [ 14 ], mechanical [ 15 ], or externally actuated [ 16 ] imitations appear more promising
,,[[Individual and collective behavior of artificial swimmers: "Janus particles"|https://www.youtube.com/watch?v=vxW7_-ei8Bw]],,
[[Transport and Collective Dynamics in Suspensions of Confined Swimming Particles|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.95.204501]]
[[Emergent, Collective Oscillations of Self-Mobile Particles and Patterned Surfaces under Redox Conditions|http://pubs.acs.org/doi/abs/10.1021/nn101289p]]
[[Emergent Cometlike Swarming of Optically Driven Thermally Active Colloids|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.112.068302]]
__[[Collective behaviour of thermally active colloids]]__. This model doesn't consider the dependence of the interaction on the relative orientation of the colloids. This effect is incorporated in their later model described in the paper on chemotactic colloids, and on [[optically driven thermally active colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_colloidalswarm.pdf]]
<i class="fa fa-star-o" aria-hidden="true"></i> [[Clusters, asters, and collective oscillations in chemotactic colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/pre14_chemotaxis.pdf]]
!!--__[[Phoretic mechanisms of self-propelled colloids]]__--
//Behaviour of a single chemotactic colloid in an external substrate concentration gradient//
[[Theory of phoretic mechanisms of self-propelled colloids]]
* "''Chemotaxis''"
* ''Polar run-and-tumble''
* ''Apolar run-and-tumble''
* ''[[Phoretic response|Phoretic mechanisms of colloids]]''
!!--__Collective behaviour__--
//FROM CHEMOTAXIS TO COLLECTIVE MOTION//
!!!__Effective interactions of active colloids__
* Chemical gradient interactions. Driven by [[Phoretic mechanisms of self-propelled colloids]] and the gradients (in the concentration of substrate or product) produced by the [[Active colloid]].
* [[Hydrodynamic interaction]]s.
They consider the former in the paper, and look at pairwise interactions.
!!!__Stochastic equations of motion__
Constructing a [[Langevin equation]] using the drift terms derived in [[here|Theory of phoretic mechanisms of self-propelled colloids]], which depend on
[img[http://i.imgur.com/ta9XORD.png]]
,,note product gradient: gradient in product concentration,,. Extra terms were added because the coefficients $$\Phi_0, \alpha_0$$, etc. only take an external $$s$$ gradient into account, and now we also have external $$p$$ gradients produced by the other catalytic colloids.
These equations can also be derived phenomenologically following from symmetry principles (see citations in paper), but one doesn't get expressions for the coefficients.
!!!__Concentration fields__
The substrate and product fields ($$s$$, and $$p$$) are themselves determined by the distribution of colloid positions and orientations. The substrate is consumed and the product is generated at the rate
$$Q(\mathbf{r}, t) = \kappa(s) \sum_\alpha \int _{|\mathbf{X}_\alpha|} \delta (\mathbf{r} - \mathbf{r}_\alpha -\mathbf{X}_\alpha) \sigma(\mathbf{X}_\alpha \cdot \hat{\mathbf{n}})$$
Evolution equation of concentration fields is obtained depending on averaged colloid number density and orientation density. The steady state is the considered, and the Fourier transform is applied to obtain information on the length scale of the interaction, expressed in the //screening length//.
Saturated vs unsaturated regime. <mark> MM curve?</mark> Refers to Michaelis-Menten rule in [[Enzyme kinetics]]. Saturated and unstaturated regimes refer to regimes where $$\kappa(s)$$ (which has the MM form) is saturated vs unsaturated.
!!!__Colloid number density $$\rho$$ and orientation density $$\mathbf{w}$$ (averaged equations)__
These are obtained from the Langevin equations above. For the orientational equations, the averaged equation involves higher moments, and a closure condition needs to be imposed to express them in terms of lower moments (mean field approximation). See Supplementary Material in [[paper|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.89.062315]].
The equations for $$\rho$$ and $$\mathbf{w}$$ depend on the gradients of $$s$$ and $$p$$, while the equilibrium $$s$$ and $$p$$ fields depend on $$\rho$$ and $$\mathbf{w}$$. The two equations can be combined to obtain closed equations for $$s$$ and $$p$$ with complicated <b>effective interactions</b>, which give rise to a rich diversity of possible phases, depending on the several parameters in the model. The main two regimes are:
__Unsaturated__
__Saturated__
Formation of asters (i.e. [[star-like|https://en.wiktionary.org/wiki/Aster]] formations, I think)...
[[Collective behaviour of active colloids]]
!!!__[[Collective Behavior of Thermally Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl12_thermactive.pdf]]__
This model doesn't consider the dependence of the interaction on the relative orientation of the colloids. This effect is incorporated in their later model described in the paper on chemotactic colloids, see [[here|Collective behaviour of active colloids]]. It is also incorporated on their paper on [[optically driven thermally active colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_colloidalswarm.pdf]]. See below.
__Thermal interactions__
via self-generated temperature gradient (via half-coating of a dark absorbing material and laser radiation bathing the sample), and the Soret effect, also known as [[Thermophoresis]]
__Fokker-Planck description__
__Regimes__
Depend on the Soret number
-------------------------------
!!!__[[Emergent Cometlike Swarming of Optically Driven Thermally Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_colloidalswarm.pdf]]__
__Brownian dynamics simulation__ of [[self-thermophoretic|Self-thermophoresis]] colloids. The colloids don't have an intrinsic asymmetry, but there is an asymmetry in their produced temperature fields because of non-uniform illumination of the light-absorbing (dark) colloid. The illumination is assumed to be directed from above downwards, and the effects of shadowing by the colloids above a particular colloid are taken into account using simple geometric optics (as a better optics treatment using light scattering on the particles is computationally very intensive).
__Comet-like swarms are formed__, with interesting dynamic features, like internal circulation of particles in the swarm, evaporation, and ejection of hot particles from the tip. The high-density head region forms a hot core which pulls the tail of the comet along.
It also drives __thermal and density fluctuations__. The particles at the top have the largest self-propelling velocity $$v_s$$ so that they tend to move up. They are also pulled down by the large hot core (creating large temperature gradients) below them. This interplay of effects cause larger fluctuations than one would expect in an equilibrium system ($$\Delta \rho / \sqrt{\rho}$$). Density fluctuations at the swarm tip and temperature fluctuations are intertwined due to the transient appearance of heat sources.
[img[http://i.imgur.com/mGRuKAK.png]]
|$$\vec{v}_T$$ is the drift velocity of the thermophoretic attraction due to the far-field temperature field gradient created by a particle causing a thermophoretic response on the other (here we assume Soret coefficient is negative so that they attract (particle climbs up $$T$$ gradients)).|
|$$\vec{v}_s$$ is the self-thermophoretic drift velcotiy due to the particle interacting with the temperature gradient on its surface created by its own non-uniform illumination.|
The swarm is a long-lived but transient structure; it is subject to a slow leakage that eventually dissolves it. It looses particles linearly with time
__Velocity of swarm__
If there are approximately $$N_h$$ particles in the head, and $$N_t$$ particles in the tail, then the whole swarm experiences approximately a self-thermophoretic drift velocity (due to the external illumination) of $$v_0 N_h$$ because approximately, only the particles at the head are illuminated. Now the drift for a single particle is $$v_0 = f/\eta$$ where f is the self-thermophoretic force and $$\eta$$ is the drag coefficient. Now the whole swarm experiences a force $$N_h f$$. However, because there are $$N_h + N_t$$ particles in the swarm, its effective drag coefficient is $$N_h + N_t$$ times the drag coefficient of a single particle, i.e. $$(N_h + N_t) \eta$$. Therefore the drift velocity of the swarm, $$V_{\text{swarm}} = \frac{N_h f}{(N_h + N_t) \eta} = \frac{N_h v_0}{N_h + N_t} = \frac{R_\perp v_0}{R_\perp + R_{||}}$$. The last expression comes from estimating the ratio of the number of colloids in the head and in the tail from its shape as $$N_h/R_\perp \sim N_t / R_{||}$$, where $$R_\perp$$ is the width (radius perpendicular to the light source), and $$R_{||}$$ is the length, or height of the swarm.
See [[Active matter]]
Continuum equations of motions for dense active nematics, such as suspensions of microtubules driven by molecular motors, or dense collections of microswimmers. They are described as nematic [[Liquid crystals]], with an extra term in the term that leads to instability (typical of [[Non-equilibrium statistical physics]]), and ''active turbulence''. See [[Complex fluid dynamics]] for the dynamical equations of liquid crystals (Beris-Edwards equations).
Addition to stress, is also discussed in [[Complex fluid dynamics]]. However, <mark>Is there an easier way to see this?</mark> The contribution to stress from the active colloids is the __average value of the stresslet__, which for nematic active particles, turns out to be $$\Pi_{jk} = -\zeta Q_{jk}$$, the active stress, where $$\zeta$$ is a measure of the level of activity.
Note: the velocity of the swimmer doesn't appear in the equations because the velocity of the swimmer determines the velocity of the fluid at the first instant when the swimmers start, and from there on, the velocity of the fluid=the velocity of the swimmer, and it just evolves according to the stresses described on the paper and here. So yeah the fact that they actually swim, only sets up their initial velocities, and from there on, they are equivalent to {rods with symmetric thrust, say two thrusters, one at each end}. However, for other active nematics, like [[Molecular motors]]+[[Microtubule]]s mixtures, the "symmetric pusher" model is reasonable even at the short accelerating phase.
Therefore because the RHS of the momentum equation has $$\partial_i \Pi_{jk}$$, __changes in the direction of orientation of the nematic order induces flow__. From these considerations and looking at the induced flows, one can already find two examples of instabilities:
* extensible systems are unstable to bend perturbations. See a derivation in [[Soft matter physics notes|https://www.dropbox.com/s/mw2fc6b6b2rdfm6/Soft%20matter%20physics.pdf?dl=0]].
* contractile systems are unstable to splay perturbations
Also activity can stabilize or de-stabilize nematic ordering, depending on the kind of activity and shape of particles:
* for __elongated particles__, extensible flow stabilizes nematic order, while contractile flow destabilizes it.
* for __plate-like particles__, contractile flow stabilizes nematic order, while extensible flow destabilizes it.
These can be understood from the pictures in Figure 7 in article, reproduced below:
[img[Selection_196.png]]
[[Fluctuating hydrodynamics and microrheology of a dilute suspension of swimming bacteria|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.80.011917]]
* ''active turbulence''
* interactions between topological defects, walls (regions of high bend perturbation), and flows (jets, and vortical).
* velocity-velocity correlation length independent of activity.
* __Application__: microtubules and [[Molecular motors]] (kinesin). Motor clusters attach to tubes creating bridges between them, and sliding them relative to each other. Adding PEG beads gives depletion interaction, and makes tubes come together into bundles, enhancing the effects of their relative sliding.
* ... <mark>Some doubts about some of the applications, and results.</mark>
* ''Lyotropic active nematics'' Lyotropic refers to concentration dependent effects, and in particular we look at the evolution of localized patches of active material surrounded by iosotropic fluid. Evolution governed by Cahn-Hillard equation, with free energy, and extra stress, described in [[Biphasic, Lyotropic, Active Nematics|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.113.248303]]
* ''Active anchoring'' Anchoring of active nematics at interfaces, due to their activity alone.
A [[colloid|https://en.wikipedia.org/wiki/Colloid]] is most often used to refer to either:
* a ''colloidal dispersion'', or
* a ''colloidal particle''
Colloidal: State of subdivision such that the molecules or polymolecular particles dispersed in a medium have at least one dimension between approximately 1 nm and 1 μm, or that in a system discontinuities are found at distances of that order. (IUPAC)
Colloid: Short synonym for colloidal system. (IUPAC)
A colloidal dispersion is a system in which particles of colloidal size of any nature (e.g. solid, liquid or gas) are [[dispersed|Dispersion (Chemistry)]] in a continuous phase of a different composition (or state). The "name dispersed" phase for the particles should be used only if they have essentially the properties of a bulk phase of the same composition.
([[http://goldbook.iupac.org/C01174.html]])
!!__[[Colloid physics]]__
Branch of [[Physics]] dealing with physical properties of colloidal systems (i.e. motion, forces, etc. at the scale of the colloidal system).
See book by Hunter - Foundations of colloid science
Branch of [[Physics]] dealing with physical properties of [[colloidal systems|Colloid]] (i.e. motion, forces, etc. at the scale of the colloidal system).
The branch of [[soft matter|Soft matter physics]] dealing with colloids has a close connection with the other subjects of [[Condensed matter physics]], like [[Solid-state physics]]. This is because colloidal [[Suspension]]s in many ways can behave analogously to solids, whether crystalline or glassy. Colloidal particles have also been used as model systems for atoms or molecules, and so there are some connections with [[Atomic physics]] and [[Molecular physics]].
!!!__[[Microhydrodynamics]] of colloids__
* [[Low Reynolds number]]
* [[Hydrodynamic interaction]]
!!!__[[Phoretic mechanisms of colloids]]__
These are important in [[Active matter]] (see [[Active colloid]]), in [[Biophysics]], and [[Nanotechnology]].
See [[Human vision]]
[[Colour Rendering of Spectra|http://www.fourmilab.ch/documents/specrend/]]
[[Color: from XYZ to spectrum|https://rip94550.wordpress.com/2010/03/08/color-from-xyz-to-spectrum/]]
http://stackoverflow.com/questions/12239986/convert-rgb-to-light-frequency
!!!__Affinity column chromatography__
[[VIdeo (purifying GFP)|https://www.youtube.com/watch?v=oKAvdAFdweA#t=40s]]
See [[Protein purification]]
See book by Conway
Example: [[Dots and boxes]]
An abstract [[Structure]], as defined in [[Combinatorics]]
* [[Tree (combinatorial structure)]]
A good analysis tool is [[Analytic combinatorics]]
See [[Analytic combinatorics]]
https://en.wikipedia.org/wiki/Latin_square
Combustion is a high-temperature exothermic redox chemical reaction between a fuel and an oxidant, usually atmospheric oxygen, that produces oxidized, often gaseous products, in a mixture termed as smoke. It often is accompanied with a [[Flame]].
https://www.wikiwand.com/en/Combustion
http://www.bbc.co.uk/education/guides/zvvwxnb/revision/1
http://www.bbc.co.uk/education/guides/z6xbkqt/revision
Hydrogen burns in oxygen to form water.
http://www.bbc.co.uk/education/guides/z8ktyrd/revision/2
See discussion in comments [[here|https://charlesmartin14.wordpress.com/2016/09/24/mmds-video-presentation/]] and [[here|https://charlesmartin14.wordpress.com/2016/10/21/improving-rbms-with-physical-chemistry/]]
Following from the comments in https://charlesmartin14.wordpress.com/2016/10/21/improving-rbms-with-physical-chemistry/#comment-1499, which are more relevant here.
“This is the standard ‘picture’. Now this may or may not be a good model for what is going on. ” Ok, I see. Do you know of any other proposed alternatives to the standard “picture which explains how the energy landscape corresponds to overfitting”? Hm, I suppose that in the paper where “It is suggested that having too many Hidden nodes–at a fixed Temp.–leads to a glassy state prone to overtraining small data sets.”, there may a way of looking at overfitting as a glassy state, but I haven’t finished reading the paper yet.
Hm, thinking a bit more, if the spin-glass state has minima which are quite deep, then getting stuck in them would coincide with overfitting/small trainning error. I suppose this could be a kind of overfitting that you get if you have no regularization (or if it isn’t working properly), while the no-early-stopping overfitting is related to global minima in the funnel.. Though, I think I’m now seeing why the whole thing could be more complicated..
Anyway I think I’m starting to get how regularization is a proxy for temperature. Basically, regularization helps either remove bad minima by changing the free energy landscape, or helps escaping from them by adding fluctuations, like dropout. Actually, even dropout can be seen as changing the energy landscape I think, as adding fluctuations is like increasing temperature, which makes entropy matter more (when writting free energy as F=U-TS). Does this sound right?
This last thought made me remember the “survival of the flattest” idea in evolution ( http://www.nature.com/nature/journal/v412/n6844/abs/412331a0.html ) . Let’s say we have a wide funnel, even if it’s not that deep, a system with high mutation rate/temperature will actually end up there over an isolated minimum even if its deeper (say corresponding to overtraining)!
* ''Redundancy''. Many genotypes per phenotype.
* ''Bias''. Highly biased distribution of genotypes per phenotype, i.e. some phenotypes have many more corresponding genotypes than most phenotypes.
* Negative correlation of ''genotypic robustness and evolvability''. This is intuitive because genotype have a __fixed degree__ in the mutational network (with edge corresponding to one-point mutation in genotype). Therefore if if you are connected to many genotypes in the same [[neutral space|Mutational robustness]] (high robustness), you have few possible connections left, and fewer available phenotypes and thus low evolvability. This assumes that genotypes with low robustness aren't just connected only to a few genotypes, but don't have "preference" over genotypes in other neutral spaces.
* ''Phenotypic robustness and evolvability'' are positively correlated. This is because phenotypic robustness correlates positively with neutral space size. A large neutral space means that the phenotype is effectively connected with more genotypes and thus often more phenotypes than phenotypes with small neutral spaces.
* ''Shape-space covering'': one can reach most phenotypes from a single phenotypes with few mutations. This is indicative of the large interconnectivity of the space.
* A roughly logarithmic ''scaling of phenotypic robustness with phenotypic frequency''. I.e. phenotypes with large neutral spaces are more robust.
Defined precisely, genotypic robustness is the fraction of neutral mutations per genotype, and genotypic evolvability is the number of distinct phenotypes that are within one mutation of the genotype (and are not the same phenotype as that of the genotype). By contrast, phenotypic robustness is defined as the average fraction of neutral mutations per genotype across a given phenotype. This correlates positively with phenotypic evolvability, defined as the total number of distinct other phenotypes that are within one mutation of any of the genotypes belonging to the given phenotype.
See [[Communication theory]]
See [[Language]]
!!__Communication modes__
* [[Conversation]]
* [[Presentation]]
* [[Mass media]]
[[Medium]]
-----------------
[ext[A Duet for one|http://www.fil.ion.ucl.ac.uk/~karl/A%20Duet%20for%20one.pdf]]
We suggest that the infinite regress induced by modelling another agent – who is modelling you – can be finessed if you both possess the same model. In other words, the sensations caused by others and oneself are generated by the same process. This leads to a view of communication based upon a narrative that is shared by agents who are exchanging sensory signals. Crucially, this narrative transcends agency – and simply involves intermittently attending to and attenuating sensory input. Attending to sensations enables the shared narrative to predict the sensations generated by another (i.e. to listen), while attenuating sensory input enables one to articulate the narrative (i.e. to speak). This produces a reciprocal exchange of sensory signals that, formally, induces a generalised synchrony between internal (neuronal) brain states generating predictions in both agents.
A ''communication channel'' is a system in which the output depends probabilistically on the input.
The //probability transition matrix//, for a given channel is the conditional probability of output X given input Y, p(X;Y).
https://en.wikipedia.org/wiki/Communication_complexity
A ''communication system'', as studied in [[Communication theory]] is specified by:
* [[Information source]]. Often modelled as a discrete-time random process.
* [[Data transmission system]]
** Transmitter, or sender.
** [[Communication channel]]
** Receiver
* Destination
See [[Information theory]], [[Data transmission]]
[[Communication theory|https://en.wikipedia.org/wiki/Communication_theory]] studies the properties of [[Communication system]]s
[[Source-channel separation theorem]]
!!Properties of communication systems
__Properties of information source__
[[Entropy rate]]
__Properties of data transmission system__
See [[Data transmission]]
__Properties of destination__
https://en.wikipedia.org/wiki/Community
[[Oxford notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/24/6_copy.pdf]]
[[https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/21/community-structure-intro.pdf]] Link doesn't work :(
A [[Topological space]] $$X$$ is //compact// if every [[Filter base]] $$\mathcal{B}$$ on $$X$$ has an accumulation point. That is, there exists $$x \in X$$ such that
for all $$N \in \mathcal{N}(x)$$, for all $$A \in \mathcal{B}$$, $$N \cap A \neq \emptyset$$.
An alternative, well-known definition involves properties of ‘coverings’ of X by families of open sets.
Study of similarities and differences between the anatomy of different organisms
[[Comparative Anatomy: What Makes Us Animals - Crash Course Biology #21|https://www.youtube.com/watch?v=7ABSjKS0hic&list=PL3EED4C1D684D3ADF&index=21]]
See also [[Formal language]], [[Programming language]], [[Assembly (programming language)]]
[[Compiler design lectures|https://www.youtube.com/watch?v=Qkwj65l_96I]]
[[Book|https://www.wikiwand.com/en/Compilers:_Principles,_Techniques,_and_Tools]]
!!__Full compilation process__
The compilation process usually involves these steps:
<div style="text-align: center">
[[HLL|High-level language]]
<i class="fa fa-arrow-down" aria-hidden="true"></i>
<span class="border">Pre-processor</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> Pure HLL
<span class="border">''Compiler''</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> [[Assembly|Assembly (programming language)]]
<span class="border">Assembler</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> [[M/C|Machine code]] (relocatable)
<span class="border"> Loader/linker</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i>
Absolute machine code
</div>
!!__Compiler steps__
<div style="text-align: center">
[[HLL|High-level language]]
<i class="fa fa-arrow-down" aria-hidden="true"></i>
<span class="border">Lexical analysis</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> Stream of tokens
<span class="border">Syntax analysis ([[Parsing]])</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> Parse tree
<span class="border">Semantic analysis</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i> Parse tree (semantically verified)
<span class="border">Intermediate code generator</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i>
Three adress code
<span class="border">Code optimizer</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i>
<span class="border">Target code generator</span>
<i class="fa fa-arrow-down" aria-hidden="true"></i>
Assembly code.
</div>
All these steps will also make use of a <b>symbol table manager</b>, and they communicate with an <b>Error handler</b>
[[Example|https://www.youtube.com/watch?v=Qkwj65l_96I#t=7m44s]]
!!Compiler front-end
!!!__Lexical analsys__
Tool: `lex`
Converts string of characters into string of tokens, using, for instance a [[Regular expression]]. For instance in an anglebraic expression, all things that match `[[a-z]\d]+`, where `[a-z]` is a letter, and `\d` is a digit, are converted into an "identifier" token, which is a fundamental unit in the grammar.
[[Lecture|https://www.youtube.com/watch?v=WccZQSERfCM]]
!!!__Syntax analysis ([[Parsing]])__
Tool: `yacc`
Create parse tree according to rules of some [[Grammar]]
[[Lecture|https://www.youtube.com/watch?v=WccZQSERfCM#t=4m10s]]
!!!__Semantic anlysis__
* Type checking
!!!__Intermediate code generator__
!!Compiler back-end
!!!__Code optimization__
!!!__Target code generator__
https://en.wikipedia.org/wiki/Complex_dynamics
[[http://www.math.harvard.edu/~ctm/papers/home/text/papers/real/book.pdf]]
Related to [[Fractal]]s and [[Complex systems]]
[img[http://math.bu.edu/people/bob/papers/figs/Per%2043.gif]]
[[Complex analytic dynamics on the Riemann sphere|http://projecteuclid.org/euclid.bams/1183551835]]
[[Complex Dynamics: Families and Friends|https://books.google.co.uk/books?id=Ek3rBgAAQBAJ&pg=PA253&lpg=PA253&dq=lyubich+complex+dynamics&source=bl&ots=sUQa6IUAHe&sig=VrC-t2pARBb3nE_TVJPbilTB6yY&hl=en&sa=X&ved=0ahUKEwjzoITw5O3MAhWmHsAKHR7DDe0Q6AEIVzAH#v=onepage&q=lyubich%20complex%20dynamics&f=false]]
[[Attracting Domain of a Dynamical System: A Complex Dance by Sara Lapan|https://vimeo.com/50509048]] [[her webpage|http://www-personal.umich.edu/~swlapan/math.html]] with some notes also on [[Algebraic geometry]].
''Complex fluids'' are fluids with elements (mostly objects suspended in the fluid), whose dynamics couple with the fluid's dynamics, giving a more complex overall behaviour (see [[wiki page|https://en.wikipedia.org/wiki/Complex_fluid]]). Most important types are [[dispersions|Dispersion (Chemistry)]], so that they are composed of two coexisting phases. The main types are:
* Solid--liquid ([[Suspension]]s)
*solid--gas ([[Granular material]]s, and some [[Fibrous material]]s)
*liquid--gas ([[Foam]]s)
*liquid--liquid ([[Emulsion]]s)
See [[Active matter]], for the interesting and important type of complex fluid, composed of active or driven elements.
[[Notes from Paul Dellar's course|http://people.maths.ox.ac.uk/dellar/MMP_NonNewt_HT16.pdf]]
[[his website|http://people.maths.ox.ac.uk/dellar/MMP_Non_Newt_fluids.html]]
• Low Reynolds number hydrodynamics, general mathematical results, flow past a sphere. ''Stresses due to suspended rigid particles''. Calculation of the Einstein viscosity for a dilute suspension
• ''Stresses due to Hookean dumb-bells''. Derivation of the upper convected Maxwell model for a viscoelastic fluid. Properties of such fluids
• Suspensions of orientable particles, Jefferys model, very brief introduction to active suspensions and liquid crystals
!!__Dynamic theory of nematic [[Liquid crystals]]__
Classical models for <b>nematodynamics</b>, dynamics of nematic liquid crystals:
*''Ericksen-Leslie Theory'', in terms of the director field $$\mathbf{n}$$
*''Beris-Edwards model'', in terms of the full tensorial order parameter $$\mathbf{Q}$$, thus the model is more detailed.
,,Doi theory?,,
See also [[Soft matter physics notes|https://www.dropbox.com/s/mw2fc6b6b2rdfm6/Soft%20matter%20physics.pdf?dl=0]]
See Beris A.N. and Edwards B.J., Thermodynamics of Flowing Systems (Oxford University Press) 1994., and I think Doi also has a book on this. See also [[here|http://www.springer.com/cda/content/document/cda_downloaddocument/9783319008578-c2.pdf?SGWID=0-0-45-1418012-p175260985]], and [[here|http://arxiv.org/pdf/1312.5988v2.pdf]].
__''Beris-Edwards equations''__
Contiuum equations of motion of nematic [[Liquid crystals]], in terms of the tensorial order parameter $$\mathbf{Q}$$.
See [[The Hydrodynamics of Active Systems|https://arxiv.org/abs/1603.00194]].
!!__Suspension dynamics__
[[A physical introduction to suspension dynamics - Guazzelli, Morris|file:///home/guillefix/Dropbox/COSMOS/Physics/Fluid%20mechanics%20and%20thermodynamics/Fluid%20mechanics/%5B%C3%89lisabeth_Guazzelli,_Jeffrey_F._Morris,_Sylvie_P(BookZZ.org).pdf]]
Fluid dynamics of fluid with suspended particles.
The suspended particles will (after a short transient) follow the fluid in its translation, and rotation. However, they can't follow it in its strain deformation. Therefore the strain component of the externally imposed flow finds resistance in the suspended particles (spheres for example), and this resistance means the particles disturb the flow. Because the flow determines the stress tensor, they will affect the stress tensor. In particular, the way the suspended sphere will affect the stress tensor is encoded in the ''stresslet''.
Einstein derived the ''Einstein viscosity'' through dissipation arguments. Part of these is also found in the book. Note that the dissipation is basically the integral of the stress times the strain rate $$\mathbf{\sigma}:\mathbf{e}$$, and is derived in Chapter 1.
<mark>There are steps in the derivation, that I don't yet quite follow</mark>
https://en.wikipedia.org/wiki/Complex_geometry
I think it has applications to [[String theory]]..
//aka segregation analysis//
Complex segregation analysis (CSA) is a technique within genetic epidemiology to determine whether there is evidence that a major gene underlies the distribution of a given phenotypic trait.
----------------
https://www.wikiwand.com/en/Complex_segregation_analysis
A complex system is a high-dimensional systems where the variables are strongly interdependent.
See [[Complexity theory]] for more discussion on the definition of a ''complex system''.
-->[[Map of complexity science|http://www.art-sciencefactory.com/complexity-map_feb09.html]]
[[Complex Systems (Mathematics Course at Oxford) blog|http://complex-oxford.blogspot.co.uk/]]
https://en.wikipedia.org/wiki/Complex_system
https://en.wikipedia.org/wiki/Complex_systems
Features of complex systems: [[Self-organization]] and emergence. [[Evolution]]. Adaptation. Homeostasis, autopesis. Crowd-dynamics, [[chaos|Chaos theory]], order and disorder..
Related: [[Soft matter physics]]. [[Non-equilibrium statistical physics]]
Models and examples: [[Boolean network]], [[Automata|Automata theory]], [[Cellular automata]], [[Biology]], [[Artificial chemistry]], [[Fractal]]s. [[Control theory and control systems]], [[Nonlinear system]]s, [[Networks|Network science]] (in particular [[Dynamical systems on networks]]), [[Social system]], [[Percolation|Percolation theory]], [[Self-organized criticality]], [[Agent-based model]]s
Maybe try to categorize these a bit.
|Interesting idea about emergence and complex systems: [[Sloppy model]]|
[[Complex Networks and Energy Landscapes|http://doye.chem.ox.ac.uk/projects/networks.html]] See [[Network theory]].
[[Diffusion-limited aggregation]]
[[Percolation]]
[[Netlogo models library|http://ccl.northwestern.edu/netlogo/models/index.cgi]]
-----------
[[ChaosBook.org videos|http://www.cns.gatech.edu/~predrag/courses/PHYS-7224-14/schedule.xml]]
[[also here|http://www.chaosbook.org/course1/about.html]]
[[YB channel|https://www.youtube.com/playlist?list=PLVcaOb64gCp8CAL-6KMjTAUfOkr624kLT]]
[[Willi Hans - The nonlinear workbook|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Willi-Hans%20Steeb-The%20Nonlinear%20Workbook%20%20-World%20Scientific%20Pub%20Co%20Inc%20%25281999%2529.pdf]]
[[Synergetics|http://www.scholarpedia.org/article/Synergetics]]
[[Chaos book|http://www.streamsound.dk/book1/chaos/chaos.html#4/z]]
!!![[Complex Systems: A Survey|http://arxiv.org/abs/1112.1440]]
!!![[Methods and Techniques of Complex Systems Science: An Overview|https://arxiv.org/abs/nlin/0307015]]
[[Power-law Distributions in Empirical Data|http://tuvalu.santafe.edu/~aaronc/powerlaws/]]
[[Statistical physics of social dynamics|http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.81.591]]
[[Part 1 Symbolic Dynamics and One-dimesional Cellular Automata: an Introduction Лекториум|https://www.youtube.com/watch?v=2SIqrz7NtR0]]
http://www.complex-systems.com/
https://theory.org/complexity/
https://en.wikipedia.org/wiki/Homeostasis
https://www.youtube.com/user/StanfordComplexity/feed
[[Computation, Dynamics and the Phase-Transition|https://theory.org/complexity/cdpt/]]
http://www.maths.qmul.ac.uk/research/applied
[[ABDUS SALAM MEMORIAL LECTURE SERIES|https://www.youtube.com/playlist?list=PL04QVxpjcnjj7geONQCwQA654x10gYq2R]]
[[Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC)|https://www.youtube.com/channel/UCoGb45Ht-Wr2s6-3IEyxwuw]]
[[Hans J. Herrmann|https://scholar.google.co.uk/citations?user=IuhidDAAAAAJ&hl=en&oi=sra]]
[[Researchers in complex systems|https://scholar.google.co.uk/citations?view_op=search_authors&hl=en&mauthors=label:complex_systems]]
[[or here actually|https://scholar.google.co.uk/citations?mauthors=complex+systems&hl=en&view_op=search_authors]]
[[Double pendulum android app|https://play.google.com/store/apps/details?id=org.openpipeflow.doubledoublependulum]]
[[How do I explain to non-mathematical people what "non-linear and complex systems" mean?|https://www.quora.com/How-do-I-explain-to-non-mathematical-people-what-non-linear-and-complex-systems-mean]]
[[ Computational Methods for Nonlinear Systems |http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/index.html]]
[[http://sethna.lassp.cornell.edu/]]
[[http://cosnet.bifi.es/]]
[[p. grassberger|https://scholar.google.co.uk/citations?user=MBpdE_wAAAAJ&hl=en&oi=sra&cstart=40&pagesize=20]]
[ext[Petri net|https://www.wikiwand.com/en/Petri_net]]
See [[Complexity theory]] for definition and theory. See [[Complex systems]] for examples and applications.
Complexity is a general concept that has different meanings in different contexts.
For instance, complexity is related to “incompressibility” in information theory
and computer science. In dynamical systems, complexity is usually measured by
the topological entropy and reflects roughly speaking, the proliferation of periodic
orbits with ever longer periods or the number of orbits that can be distinguished
with increasing precision. In physics, the label “complex” is in principle attached to
any nonlinear system whose numerical solutions exhibit a chaotic behavior. Neurologists claim that the human brain is the most complex system in the solar system,
while entomologists teach us the baffling complexity of some insect societies. The
list could be enlarged with examples from geometry, management science, commu-
nication and social networks, etc.
//from book on Permutation complexity by Amigo//
Complexity can be seen in [[chaotic systems|Chaos theory]], and, depending on interpretation, in [[random|Randomness]] ones. It is also important in biological systems (see [[Biological complexity]]).
!!__Complexity measures__
[[Descriptional complexity]]
[[Computational complexity]]
See also [[Randomness]]
----------------------
[[Shannon entropy: a rigorous notion at the crossroads between probability, information theory, dynamical systems and statistical physics|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Lesne-information-review.pdf]]
Good review: [[RANDOMNESS, INFORMATION, AND COMPLEXITY|http://arxiv.org/abs/1208.3459]]
[[Information and Complexity Measures in Dynamical Systems|http://link.springer.com/chapter/10.1007/978-1-4899-2305-9_2#page-1]]
See also [[Information theory]], [[Statistical physics]], [[Dynamical system]]s, [[Evolution]], [[Simplicity bias]].
Complexity ~ Modular hierarchical structures.
See [[Descriptional complexity]], [[Data compression]]
Some measures of descriptional complexity are based on [[Data compression]] techniques, like the [[Lempel-Ziv complexity]].
__Relations to [[Grammar-based compression]]s used in [[Data compression]]__
[[Application of Lempel–Ziv factorization to the approximation of grammar-based compression |http://www.cs.ucr.edu/~stelo/papers/extra/rytter2.pdf]] Relations between LZ-factorizations and grammar-based factorizations (G-factorization). The G-factorization gives an upper bound for the LZ complexity.
See [[this book|https://books.google.co.uk/books?id=OlqrCAAAQBAJ&pg=PA23&lpg=PA23&dq=chomsky+normal+form+g+factorization&source=bl&ots=3vF4ZgeE8o&sig=jJuYvlN0xjsJe2Hd5IWI0JQrVrE&hl=en&sa=X&ved=0ahUKEwjLp-DNncvNAhXjIsAKHSRpBn0Q6AEILDAC#v=onepage&q=chomsky%20normal%20form%20g%20factorization&f=false]] too (same article), and this: [[Grammar Compression, LZ-Encodings, and String Algorithms with Implicit Input|http://dlx.booksc.org/21200000/libgen.scimag21244000-21244999.zip/browse/10.1007/978-3-540-27836-8_5.pdf]].
''[[Complexity|https://en.wikipedia.org/wiki/Complexity]]'' is generally used to characterize something with many parts where those parts interact with each other in multiple ways. [[Etimologically|http://www.etymonline.com/index.php?term=complex]], complex refers to a system made of ''many intertwined parts'', and that's still the definition we use in science, although a precise measure hasn't been agreed upon. See [[Complexity]].
But how intertwined, i.e. how many and what kind of the interactions does a system need to be called complex? I think a ''complex system'' should be defined as one in which the interactions //significantly alter// the //behaviour// of the system, relative to the one with no interactions. The primary example of interactions that qualitatively affect the behavior of a system are ''nonlinear interactions'' (see [[Nonlinear systems]]).
__Definition by Cosma Shalizi__: a complex system is a high-dimensional systems where the variables are strongly interdependent. Complex systems are ones with a large effective number of strongly-interdependent variables. This excludes both low-dimensional systems, and high-dimensional ones where the variables are either independent, or so strongly coupled that only a few variables effectively determine all the rest. Since the 1980s, an interdisciplinary movement of physicists, mathematicians, economists, computer scientists, biologists, anthropologists and other scientists has explored techniques for modeling a broad range of such systems, and their common features and inter-connections. These techniques rely heavily on intensive, sophisticated computer simulations, and notions of information, search and adaptation feature prominently in the theories. ([[The Statistical Analysis of Complex Systems Models|http://www.stat.cmu.edu/~cshalizi/stacs/]])
,,See also: [[How do I explain to non-mathematical people what "non-linear and complex systems" mean?|https://www.quora.com/How-do-I-explain-to-non-mathematical-people-what-non-linear-and-complex-systems-mean]],,
Furthermore, Warren Weaver [[posited in 1948|http://people.physics.anu.edu.au/~tas110/Teaching/Lectures/L1/Material/WEAVER1947.pdf]] two forms of complexity:
*disorganized complexity
*organized complexity
The way I interpret this, is that ''//organized//'' or //disorganized// refers to the behaviour of the system, at some scale and coarse-graining level. If the system at some coarse-graining level has a behaviour that could be described by a less complex system (for example, as formalized by Kolmogorov complexity in [[AIT|Algorithmic information theory]]) than the original description, we say it displays organized complexity, and that new simpler behavior has ''//emerged//'' (see [[Self-organization]]). This may also be called //complexity reduction//. One can see that coarse-graining will produce less complex descriptions, pretty much by definition. However, to get emergence, the system must allow some coarse-graining procedure that produces reasonable descriptions, in the first place
Disorganized complexity refers to some scale which does not allow a simpler coarse-grained description.
For example, a gas of particles represent a complex system (as the particles interact with each other in complex ways, i.e. ways that change the behavior of the system significantly relative to a system of non-interacting particles). At the scale of particles, we have disorganized complexity, as there is no coarse-grained description that can simplify the dynamics while still talking of all the particles. We may then use probabilistic descriptions. At larger scales, we can talk about large groups of particles, and using, for instance averages from the probabilistic descriptions, we can construct coarse-grained descriptions in terms of "infinitesimal" volume elements interacting on less complex ways. We can say that that "hydrodynamic behvaior has //emerged//".
|Actually here I am referring to "complexity" as used in [[Complex systems]] theory. As [[Wiki|https://en.wikipedia.org/wiki/Complexity_theory]] says, //Complexity theory// can also refer to [[Computational complexity]] or [[Descriptional complexity]] (a fundamental concept in [[Algorithmic information theory]]).|
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[[Complexity and Self-organization|http://pespmc1.vub.ac.be/Papers/ELIS-Complexity.pdf]]
[[Universality-Complexity Classes for Partial Differential Equation Systems (from xmorphia) |http://mrob.com/pub/comp/xmorphia/pde-uc-classes.html]] Taking ideas of [[universality and complexity classes of cellular automata|http://www.stephenwolfram.com/publications/cellular-automata-complexity/pdfs/universality-complexity-cellular-automata.pdf]] from Stephen Wolfram (c.f. A New Kind of Science).
https://en.wikipedia.org/wiki/Complexity_theory
[[Kolmogorov Complexity – A Primer|https://jeremykun.com/2012/04/21/kolmogorov-complexity-a-primer/]]
[[The First Law of Complexodynamics|http://www.scottaaronson.com/blog/?p=762]]
[img[http://www.scottaaronson.com/coffee-small.jpg]]
Well the complexity follows that pattern in the macroscale at least. Also:
Non-equilibrium is more complex; I think: because equilibrium can be described simply: the long time behaviour of the simple dynamical system; while non-eq has many more possibilities
https://jeremykun.com/2012/04/21/kolmogorov-complexity-a-primer/
See also the related: [[Computational complexity]], and also [[Descriptional complexity]], and [[Complex systems]].
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Complexity theory may be seen as part of complexity science, or they may be seen as equivalent disciplines. In any case, this page includes complexity science.
http://www.complexity.ecs.soton.ac.uk/
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//People//
[[http://turing.iimas.unam.mx/~cgg/]]
[[Norbert Wiener|https://en.wikipedia.org/wiki/Norbert_Wiener]], cybernetics
[[William Ross Ashby|https://en.wikipedia.org/wiki/William_Ross_Ashby]]
[[Stuart Kauffman|https://en.wikipedia.org/wiki/Stuart_Kauffman]]
Heinz von Foerster, [[Second-order cybernetics|https://en.wikipedia.org/wiki/Second-order_cybernetics]]
Francis Heylighen, cyberneticist
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[[Introduction to Circuit Complexity|https://books.google.co.uk/books?id=55ZTgOJs8bsC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]]
[[Structural Complexity I|https://books.google.co.uk/books?id=aIuqCAAAQBAJ&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]]
[[Structural Complexity II|https://books.google.co.uk/books?id=9YmqCAAAQBAJ&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]]
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
A //component// is a subset of the network for which all pair of vertices have at least one path, and which is maximal (i.e no extra nodes can be added that preserve this property). A connected graph has only one component, while a disconnected one has more than one.
The adjacency matrix can always be written in block diagonal form with blocks corresponding to components.
__Components in directed networks__
//Weakly connected components// are components of a directed network ignoring the direction.
//Strongly connected components// have a path between any two vertices //in both directions//.
Acyclical graphs can't have strongly connected components with >1 vertex since, they would necessarily include a cycle.
"""
//Out-components// are all the vertices reachable from a certain vertex, including the vertex itself.
//In-components// are all the vertices from which one can reach a certain vertex, including the vertex itself.
"""
Both of these are identical for all vertices in a strongly connected component.
[[Composite material|https://en.wikipedia.org/wiki/Composite_material]] is a material made from two or more constituent materials with significantly different physical or chemical properties.
A material with constituents having different chemical composition is known as a [[Mixture]].
A material with constituents in different physical phases, is known as a [[dispersion|Dispersion (Chemistry)]].
A material can be both a dispersion and a mixture.
[[Textile]]
//,,why spend so much effort acquiring all the data when we know that most of it will be discarded?,,//
''Compressed sensing'' (also known as ''compressive sensing'', ''compressive sampling'', or ''sparse sampling'') is a [[Signal processing]] technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined [[Linear system]]s. This is based on the principle that, through [[Optimization]], the sparsity of a signal can be exploited to recover it from far fewer [[Sample]]s than required by the [[Nyquist-Shannon sampling theorem]]. There are two conditions under which recovery is possible:
* Sparsity which requires the signal to be sparse in some domain.
* Incoherence which is applied through the isometric property which is sufficient for sparse signals.
Basically, as in [[Data compression]], it takes advantage of the order, or [[Randomness deficit]] in the data to sample below the Nyquist-Shannon limit
[[Compressed sampling|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/CompressiveSampling-Review.pdf]]
[[Introduction to compressed sensing|https://www.dropbox.com/s/0sr5as1qip2oz47/ddek-chapter1-2011.pdf?dl=0]]
-----------
https://www.wikiwand.com/en/Compressed_sensing
See [[Theory of computation]]. Here we are focusing on ''Turing computability''. This is because, according to the [[Church-Turing thesis]], [[Turing machine]]s are the most computationally powerful, and all other realizable models of computation, are either special cases (i.e. they will define subsets of Turing computable functions) or equivalent.
__Important concepts__
* [[Formal language]]
* [[Turing machine]]
From [[Naïve Set Theory - Cardinality & Basic Computability Theory|http://www.cse.iitk.ac.in/users/satyadev/a10/kolm_1.pdf]]
!!__Decidability of languages/sets__
An input string $$w$$ is said to be //accepted// by a Turing machine $$M$$ if, the computation of $$M$$ with initial configuration having $$w$$ on the first tape and both heads at the left end of $$w$$, terminates in $$q_a$$, the accepting state.
The machine is said to //reject// the string if the Turing machine terminates in $$q_r$$, the rejecting state.
(There is of course, the possibility that the Turing Machine may not terminate its execution.)
a Turing machine is said to //accept a language// L if every string x in the language is accepted by the Turing Machine in the above sense, and no other string is accepted
Definition 1.2.2. A language is said to be ''acceptable'' if there is a Turing machine which accepts it.
A language L is said to be ''decidable'' if both $$L$$ and $$L^c$$ (complement) are acceptable.
Alternative
[[Definition of decidability of a set|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=3m57s]] based on computability of functions (see below).
[[Semidecidable set definition|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=13m30s]]. It is an acceptable set, that is not decidable. [[Example of semidecidable set|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=17m20s]].
!!__Computability of functions__
Definition of ''computability''
[img[http://guillefix.me/img/arrivalfrequent5.png]]
$$f(x) \uparrow$$ means undefined..
Useful definitions: bit-doubling function, pairing function. The ''pairing function'' is a ''prefix code'' - that is, the encoding of a pair cannot be the prefix of the encoding of another pair. See [[Prefix code|https://en.wikipedia.org/wiki/Prefix_code]]. This makes the code uniquely decodable: a pair can be identified without requiring a special marker between pairs. ([[Pairing function|https://www.youtube.com/watch?v=47KpZvA39dA#t=13m]])
[[Math 574, Lesson 2-4: Computable Functions|https://www.youtube.com/watch?v=qvCXYqjbPD4]]
[[Definition of Turing computability|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=35s]]
[[Partial computability|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=11m]] [[Definition of partial computability|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=12m30s]] <--> [[Semidecidable set definition|https://www.youtube.com/watch?v=qvCXYqjbPD4#t=13m30s]]
A weaker notion is that of //semicomputability//: [[Semicomputable function]]
!!!__Computable enumerability__
[img[http://guillefix.me/img/arrivalfrequent6.png]]
__Theorem__ 1.2.10: //A language is computably enumerable (or recursively enumerable) if and only if it is acceptable//.
__Theorem__ 1.2.11: //A language is decidable if and only if it is computably enumerable in increasing order. That is, a language $$L$$ is decidable if and only if it is finite or there is a total computable bijection $$f: \mathbb{N} \rightarrow L$$ such that for all numbers $$n$$//,
$$f(n) < f(n+1)$$
__Theorem__ 1.2.12. //Every infinite computably enumerable set contains an infinite decidable set//.
See [ext[Computational Complexity problem sheet solutions|http://www.csee.wvu.edu/~ksmani/courses/sp03/cc/qen/scrim1sol.pdf]] [[offline version|file:///home/guillefix/Dropbox/COSMOS/Computer%20Science%20and%20IT/scrim1sol.pdf]]. Also see these [[notes on Kolmogorov complexity|http://www.cse.iitk.ac.in/users/satyadev/a10/kolm_2.pdf]], for proof of Theorem 1.2.12. and more.
__''Universality theorem''__: //There is a [[Universal Turing machine]]//. [[Theorem (vid)|https://www.youtube.com/watch?v=47KpZvA39dA#t=14m07s]] (see also [[Godel numbers for indexing Turing machines|https://www.youtube.com/watch?v=47KpZvA39dA#t=7m10s]])
__Kleene's normal form theorem__. //There is a 3-ary partial computable function $$C$$ and a 1-ary partial computable function $$U$$ such that any 1-ary partial recursive function can be expressed as//
$$f_e(n) = U(\mu z[C(e.n.z) = 0])$$
__Theorem__ 1.2.15 //There is a partial computable function that is not total computable//.
!!__Uncomputable functions__
!!!__Halting problem__
[[Math 574. Lesson 2-5: The Halting Problem|https://www.youtube.com/watch?v=47KpZvA39dA]]
[[Godel numbers for indexing Turing machines|https://www.youtube.com/watch?v=47KpZvA39dA#t=7m10s]]
[[Halting problem statement|https://www.youtube.com/watch?v=47KpZvA39dA#t=17m30s]]
An undecidable problem.
__Proof__
[[Proof That Computers Can't Do Everything (The Halting Problem)|https://www.youtube.com/watch?v=92WHN-pAFCs]]
[[Math 574, Lesson 2-6: Undecidability of the Halting Problem|https://www.youtube.com/watch?v=cCvB2MDdNBg]] with diagonalization argument.
The halting set $$K$$ is semidecidable by the Universal Turing machine.
He will show that the [[diagonal halting problem is undecidable|https://www.youtube.com/watch?v=cCvB2MDdNBg#t=2m50s]]
[[http://cstheory.stackexchange.com/questions/2853/are-there-any-proofs-the-undecidability-of-the-halting-problem-that-does-not-depe/2911#2911]]
[[There exist uncomputable functions|https://www.youtube.com/watch?v=47KpZvA39dA#t=50s]] because the number of TMs is countable.
!!!__Other examples__
Solvability of diophantine equations.
Word problem for groups
[[Kolmogorov complexity]]
Computational biology has two distinct branches: knowl-
edge discovery, or data-mining, which extracts the hidden
patterns from huge quantities of experimental data, form-
ing hypotheses as a result ([[Bioinformatics]]);
and simulation-based analysis,
which tests hypotheses with in silico experiments, providing
predictions to be tested by in vitro and in vivo studies.
------
!!!https://moleculamaxima.com/
Create new exciting organisms with just a few lines of code
Extend nature and develop new drugs with the Synthetic™ bio-programming language and the Cytostudio™ IDE
SyntheticTM
Looks awesome!
https://www.wikiwand.com/en/Computational_biology
[[Modelling biological systems]]
-----
__Molecular modelling, dynamics and design__
[[Molecular dynamics]]
[ext[Introduction to molecular dynamics simulation|http://udel.edu/~arthij/MD.pdf]]
[[Video intro to molecular dynamics simulations|https://www.youtube.com/watch?v=lLFEqKl3sm4]] Watch!
Wiki page: https://en.wikipedia.org/wiki/Molecular_dynamics
[[Geometry (energy) optimization|http://homepages.warwick.ac.uk/~masfk/BindingGeometry.pdf]] is a typical feature of these software
//Software//:
[[Gromacs|http://www.gromacs.org/Documentation/Tutorials]]
[[Chimera|http://www.cgl.ucsf.edu/chimera/]] molecular modelling software system. Nice
[[Delphi|http://compbio.clemson.edu/delphi]] Electrostatic fields
[[Ascalaph designer|http://www.biomolecular-modeling.com/Ascalaph/Ascalaph_Designer.html]] and abalone. [[Tutorial|http://www.biomolecular-modeling.com/Ascalaph/Documents/Molecular_drawing.html]]
[[AMBER|http://ambermd.org/#code]]
http://proteopedia.org/wiki/index.php/Molecular_modeling_and_visualization_software
http://nanohub.org/
http://nanohub.org/resources/4540
https://en.wikipedia.org/wiki/Molecule_editor
https://en.wikipedia.org/wiki/List_of_software_for_Monte_Carlo_molecular_modeling
https://en.wikipedia.org/wiki/List_of_software_for_molecular_mechanics_modeling
https://en.wikipedia.org/wiki/List_of_software_for_nanostructures_modeling
http://www.ch.ic.ac.uk/local/organic/mod/software.html
[[Challenges in computer-aided molecule design|http://link.springer.com/article/10.1007/s10822-011-9504-3]]
//Algorithmic or computational complexity//
The ''computational complexity'' of an algorithm is an [[asymptotic|Asymptotic approximation]] estimate of how the algorithm's running time scales with the size of its input.
https://en.wikipedia.org/wiki/Computational_complexity_theory
https://www.cs.cmu.edu/~adamchik/15-121/lectures/Algorithmic%20Complexity/complexity.html
__[[Time complexity|https://en.wikipedia.org/wiki/Time_complexity]]__
[[Pseudo-polynomial time|https://en.wikipedia.org/wiki/Pseudo-polynomial_time]]: if its running time is polynomial in the numeric value of the input, but is exponential in the length of the input – the number of bits required to represent it. That is because numerical number $$n$$ is related to number of bits (digits in binary), $$b$$, by $$n=2^b$$.
[[P vs. NP and the Computational Complexity Zoo|https://www.youtube.com/watch?v=YX40hbAHx3s]]
!!!__Kolmogorov complexity__
See [[Algorithmic information theory]]
----------------------
https://www.wikiwand.com/en/Structural_complexity_theory
[[Computer algebra]]
__Automatic theorem proving__
[[Machine learning and automatically theorem proving|https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-792.pdf]]. Used for automatic [[Software validation]]
[[Scientific computing]] for [[Neuroscience]]
An [[Information]]-processing [[Machine]]
https://en.wikipedia.org/wiki/Computer_algebra_system
http://epubs.siam.org/doi/book/10.1137/1.9781611971033
http://homepages.math.uic.edu/~jan/mcs320/
Project MAC (the Project on Mathematics and Computation, later backronymed to Multiple Access Computer, Machine Aided Cognitions, or Man and Computer)
Joel Cohen - Computer algebra and symbolic computation books
[[Intelligent computer algebra system: Myth, fancy or reality?|http://link.springer.com/chapter/10.1007/3-540-18928-9_2]]
__CASs__
[[Sage|Sage (CAS)]]/numpy/sympy...
Matlab.
Mathematica.
Maple.
Maxima/Macsyma.
GAP.
Axiom.
Web notebook: [[IPython and Jupyter notebook|https://ipython.org/]] http://jupyter.readthedocs.org/en/latest/running.html
Torch + IPython = iTorch: https://github.com/facebook/iTorch
!!__Computer algebraic geometry__
!!__Computer linear algebra__
[[Basic Linear Algebra Subprograms|https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms]]
http://www.openblas.net/
[[LAPACK |http://www.netlib.org/lapack/]]
!!__Other computer algebras__
A [[Software]] system for [[Computer algebra]]
[[EigenMath manual|http://eigenmath.sourceforge.net/Eigenmath.pdf]]
[[Kevin's|https://github.com/antimatter15?tab=repositories]] Carbide and [[halgebra|https://equation.space/]]. See facebook convo. https://ideapad.io/augmenting-human-intellect/graph
!! [[Ket algebra editor|https://sourceforge.net/projects/ket/]]
<mark>-->http://epsilonwriter.com/start.php <--</mark>
[[Mathematica - Manipulation equations|https://reference.wolfram.com/language/guide/ManipulatingEquations.html/]]
http://matracas.org/algebra/index.html.en
https://github.com/MatthewJA/Graphical-Equation-Manipulator
[[JavaScript mathematics packages]]
http://www.sympy.org/en/index.html
http://nptel.ac.in/courses/106104122/
[[MIT 6.004: Computation Structures|https://www.youtube.com/playlist?list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-]]
[[Spring 2013 -- Computer Architecture -- Carnegie Mellon|https://www.youtube.com/playlist?list=PL5PHm2jkkXmidJOd59REog9jDnPDTG6IJ]]
https://class.coursera.org/comparch-003/lecture
See also [[Software engineering]]
“Set of loosely connected computers that work
together so that in many respects they can be
viewed as a single system”.
Backend manages the [[distributed|Distributed computing]] system.
!!__Cluster frontend__
The frontend, abstracts the system, so that one can interact with it as if it was a single computer.
__Job manager (or scheduler)__: program running
on the cluster frontend.
– Listens for incoming job submissions.
– Schedules jobs in a more or less fair way.
[[Computer architecture]]
[[Distributed computing]]
[[GPU computing]]
[[Software engineering]]
[[SIGGRAPH 2015 - Technical Papers Trailer|https://www.youtube.com/watch?v=XrYkEhs2FdA]]
[[ThreeNodes.js: vvvv "clone" in javascript/webgl|https://github.com/idflood/ThreeNodes.js]]
https://vvvv.org/ <i class="fa fa-thumbs-up"></i> <i class="fa fa-thumbs-up"></i> <mark>Looks very nice</mark> Visual programming language
!!!__GPUs__
For [[Deep learning]] for example
Best GeForce GPU: [[GeForce Titan X|http://www.geforce.com/hardware/desktop-gpus/geforce-gtx-titan-x]]. Titan Z coming soon
[[More CUDA GPUs|https://developer.nvidia.com/cuda-gpus]]
[[ThinkMate computer|http://www.thinkmate.com/system/gpx-xs4-1460-1gpu]] with many GPU customization options.
A particular set of instructions that can be fed to a [[Computer]]
Computer science can refer broadly to [[Computer Science and IT]], or more specifically to [[Theoretical computer science]]
Computer science and [[Information technology]] (IT).
''Computer science'' is what came out of asking: <b>what kind of [[maths|Mathematics]] can actually be //effectively// carried out in the [[physical|Physics]] world?</b>
[[Portal:Computer science|https://en.wikipedia.org/wiki/Portal:Computer_science]]
[[Portal:Information technology|https://en.wikipedia.org/wiki/Portal:Information_technology]]
''Information technology'' is the result of actually carrying out this math, an step that required [[technology|Technology & Engineering]].
----------
http://colorfulengineering.org/SCICOMP.html
http://www.aduni.org/courses/
Nice Math ∩ Programming blog: https://jeremykun.com/
http://it-ebooks.org/
http://en.tldp.org/HOWTO/Unix-and-Internet-Fundamentals-HOWTO/
__Quantum random number generator__: https://qrng.anu.edu.au/
Github
http://www.movidius.com/
[[Convolutional neural network]], [[Image processing]]
[[Cloud vision API|https://www.youtube.com/watch?v=eve8DkkVdhI]]
[[DenseCap: Fully Convolutional Localization Networks for Dense Captioning|http://cs.stanford.edu/people/karpathy/densecap/]]
[img[http://cs.stanford.edu/people/karpathy/densecap/eg/p8.jpeg]]
[img[http://cs.stanford.edu/people/karpathy/densecap/eg/p12.jpeg]]
[[Multi-scale networks|Deep multi-scale video prediction beyond mean square error|http://arxiv.org/abs/1511.05440]] and [[an application|http://yann.lecun.com/exdb/publis/pdf/sermanet-ijcnn-11.pdf]].
[[Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers|http://arxiv.org/abs/1202.2160]]
http://www.clement.farabet.net/research.html#parsing
''Hand-eye coordination''. See work on grabbing objects in [[Robotics]]
http://opencv.org/
!!__[[Spiking neural network]] models__
!!![[Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition|http://www.sciencedirect.com/science/article/pii/S0925231216302880]]
* ''feedforward feature extraction''. studies have suggested that the feedforward information is usually sufficient for invariant object categorization, leading to models like [[Convolutional neural network]]s.
* ''biologically plausible learning rules'' the way that biological visual systems learn the appropriate features has attracted much less attention. Yet the ability of the visual cortex to wire itself, mostly in an unsupervised manner, is remarkable [18] and [19]. Here, we propose that adding bio-inspired learning to bio-inspired architectures could improve the models׳ behavior.
__algorithm__
The algorithm we used here is a scaled-up version of the one presented in [24] ([[Unsupervised Learning of Visual Features through Spike Timing Dependent Plasticity|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.0030031]]). We used a five-layer hierarchical network, with a classifier at the end, similar to HMAX model. ,, Specifically, we alternated simple cells that gain selectivity through a sum operation, and complex cells that gain shift and scale invariance through a max operation. ,, Spike timing -coding (stronger signal fires first). Weight sharing, as in CNNs.
The image is copied and scaled, and presented to copies of the network (like [[Cortical column]]s). To increase the sparsity at a given scale and location (corresponding to one cortical column), only the spike corresponding to the best matching orientation is propagated (i.e. a winner-take-all inhibition is employed).
See also [[Human vision]]
[[A biologically inspired spiking model of visual processing for image feature detection|http://www.sciencedirect.com/science/article/pii/S0925231215000326]]
* Gabon filters.
* receptive fields.
Dynamic vision cameras!!
[[Investigation of event-based memory surfaces for high-speed tracking, unsupervised feature extraction and object recognition|https://arxiv.org/abs/1603.04223]]
[[Unsupervised Learning of Visual Features through Spike Timing Dependent Plasticity|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.0030031]]
Computer-aided engineering (CAE)
[[Computer-aided design]]
amount of substance / extension (volume, area, etc.)
http://www.bbc.co.uk/education/guides/zbbqtfr/revision/3
See [[Self-diffusiophoresis]].
At steady-state, in the reference frame of the object, and neglecting
distortions induced by the flow (small Peclet number), the solute concentration in the liquid is
given by
$$D\nabla^2 c = 0$$ (steady state diffusion)
$$-D\mathbf{n}\cdot\nabla c(\mathbf{r}_s) = \alpha(\mathbf{r}_s)$$
i.e. the flux of solute is given by some space-dependent function that measures the 'surface activity' at the surface of the colloid, i.e. the generation or consumption of solute by a chemical reaction. In general,
describing this process involves additional coupled transport problems for other species involved
in the surface reactions.) Some variations are needed for the cases of [[Self-electrophoresis]] and [[Self-thermophoresis]]. Approximately, these equations give, $$V\sim \alpha \mu /D$$. In particular, once the surface properties, $$\mu$$ and $$\alpha$$ and the shape are given, the velocity turns out to be independent of the size $$R$$ of the object, showing that this method of propulsion is robust under downscaling.
A certain structure in the [[Mind]] that [[represents|Representation]] a [[Set]] of [[Object]]s, often by representing a property that //defines// the set.
http://plato.stanford.edu/entries/concepts/
__ Classical theory__
__Prototype theory__
__Theory theory__
https://en.wikipedia.org/wiki/Concrete_Mathematics. the topics in Concrete Mathematics are "a blend of CONtinuous and disCRETE mathematics." The term "concrete mathematics" also denotes a complement to "abstract mathematics". (by Donald Knuth, author of LaTeX!!)
See [[AugMath]].
These ideas of my mathematical philosophy are also brought to life in <big>[[Iconic mathematics|http://iconicmath.com/]]</big> (maths that looks like what it means):
<<<
Symbols ask us to think. Icons ask us to look.
The symbol 5 tells us nothing about five. The icon ||||| is five.
<<<
More: http://www.wbricken.com/htmls/03words/0303ed/030304iconic.html.
Another keyword, ''experiental mathematics'', a lot of its literature is applied to education, and stays at very shallow level of the idea..
See voxel.css in css part in [[Frontend web development]].
Synthetic mathematics? http://math.andrej.com/wp-content/uploads/2007/05/syncomp-mfps23.pdf
------------
__More visual & concrete mathematics__
https://acko.net/
<mark>"Semi-concrete"</mark>: http://cognitivemedium.com/emm/emm.html
Bret Victor
[[Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain|https://medium.com/guesstimate-blog/introducing-guesstimate-a-spreadsheet-for-things-that-aren-t-certain-2fa54aa9340#.v51ot441e]] <mark>Visual arithmetic on probability distributions!</mark>
http://ncase.me/ <mark>Explorable explanations!</mark>: http://explorableexplanations.com/
https://www.quantamagazine.org/20160531-set-proof-stuns-mathematicians/
[ext[https://en.wikipedia.org/wiki/Concurrency_(computer_science)]]
https://en.wikipedia.org/wiki/Concurrent_computing
See [[Concurrent programming]], [[Operating system]]
[[Multithreading]].
An [[Operating system]] often implements these concurrent tasks (processes and threads) by using an ''scheduler'' that determines when.
Have to think about data dependencies
See [[Concurrent computing]], [[Multithreading]]
[[C++ Threading #1: Introduction|https://www.youtube.com/watch?v=Ps8jOj7diA0&list=PL1D3B7D7242B3C224]]
[[Immutable type]]
[[C++ Lecture Series --- Concurrency --- Part 5 of N --- Promises and Futures|https://www.youtube.com/watch?v=hic5W_UMjqU]] has good outline in description
http://zeromq.org/
A condensation reaction, is a [[Chemical reaction]], often an [[Organic reaction]], in which two molecules or moieties, often functional groups, combine to form a larger molecule, together with the loss of a small molecule.
An example is [[Dehydration synthesis]]
''Condensed matter physics'' is the [[Physics]] of condensed matter. Below we look at the different broad types of condensed matter. The properties of condensed matter systems depend, among other things, on the chemical composition of the system (see [[Chemistry]]), and the [[physical laws|Physics]] the chemical components obey.
!!!__Condensed vs non-condensed__
''Condensed matter'' refers to [[Bulk matter]] in a condensed form, i.e. one that is composed of condensed phases. Condensed phases include mainly ''[[Solid]]'', and ''[[Liquid]]''. However, generally, it is a phase for which the particles adhere to each other strongly enough (by for example [[Intermolecular forces]] or [[Chemical bonds]]) relative to their kinetic energy so that the system remains approximately bound in the absence of external forces, or where the particles are sufficiently highly concentrated so that they interact strongly (for example non-attracting particles can be forced to condense by confining them in a small volume (or by some external force, like gravity), forcing them to be "nearly touching", as in a liquid or solid).
''//Non-condensed// matter'' has constituents that are barely bound together, if at all, and thus often need to be confined, either naturally, or artificially, to be studied as a whole. The main types are: <b>[[Gas]]es</b> (see [[Fluid mechanics]]), and <b>[[plasmas|Plasma physics]]</b>.
!!!__Solid vs fluid__
A ''[[Solid]]'' is a form of matter that can resist a considerable amount of stress without flowing (so that its only response is //elastic//).
A ''[[Fluid]]'' is a form of matter that flows under virtually any amount of stress.
A [[viscoelastic material|Viscoelasticity]] displays solid-like elasticity of short time scales, and fluid-like viscosity on long time scales.
There is really a continuum between these. For instance some [[Rubber]]s are closer to solids, while others are more clearly viscoelastic, depending on the ratio of elastic to viscous [[deformation|https://en.wikipedia.org/wiki/Deformation_(mechanics)]].
!!!__Hard vs soft__
[[Solid-state physics]] studies matter in ''hard form''. Hard forms are characterized by strong inter-particle bonding (often [[Chemical bonds]], when at room temperature). This bonding is strong enough that it makes the relative position of the particles essentially fixed, with thermal fluctuations making particles vibrate only a bit relative to this fixed position. It is also strong enough to resist relatively large external stresses (i.e. it doesn't flow) All forms of hard matter are solids.
[[Soft matter physics]] studies matter in other condensed forms (''soft forms''), where some or all (relative) positional degrees of freedom are "soft", that is, strongly affected by thermal fluctuations, so that they have large variances. It also includes forms with weak bonding so that the material can't resist barely any external stress without flowing. Soft matter can be a solid or a fluid.
Note that given the definition above, one expects an spectrum between the two types of matter, as the definitions involve quantities that can potentially take a continuous of values. Most materials in nature, however, can be classified in one or the other.
One of the most important properties of materials is that they exhibit different ''phases''. These are understood through the study of [[Phase transition]]s. See Paul and Lubenski's book //Principles of condensed matter physics//.
!!!__Condensed forms of matter__
//Hard forms//
* [[Crystalline|https://en.wikipedia.org/wiki/Crystallinity]] solids (crystalline symmetry). See [[Solid-state physics]].
* [[Amorphous solids|https://en.wikipedia.org/wiki/Amorphous_solid]]; in particular glasses (disordered; statistically homogeneous/isotropic, but positions fixed). See discusion in [[Viscosity and elasticity]].
* Nuclear matter.
* Porous solids (see [[Porous material]]).
* Many [[polymers|Polymer]], particularly plastics, are solids.
//[[Soft forms|Soft materials]]//
{{Soft materials}}
!!!__Non-condensed forms of matter__
* simple [[Gas]]es
* Simple [[plasmas|Plasma physics]].
* Quark-gluon plasmas
* Some types of [[complex fluids|Complex fluid dynamics]] are non-condensed phases, for instance [[Aerosol]]s.
There are also phases of matters that exhibit quantum effects. These are studied (along with other non-quantum phases that nontheless can be understood using quantum mechanics) in [[Quantum condensed matter physics]]
[ext[Order and disorder|https://en.wikipedia.org/wiki/Order_and_disorder_(physics)]] designate the presence or absence of some symmetry or correlation in a many-particle system. See [[Disorder]], [[Disordered system]]. See [ext[here|http://bioserv.mps.ohio-state.edu/~rbund/home/anneal.pdf]] and [[here|http://physics.stackexchange.com/questions/16523/should-annealed-disorder-be-characterized-by-the-average-of-the-partition-functi]], and [[here|https://books.google.co.uk/books?id=Wt804S9FjyAC&pg=PA145&lpg=PA145&dq=%22annealed+disorder%22&source=bl&ots=23hEhpqOgD&sig=7U10nV-RzPNBj7iiehMDZoNmtS4&hl=en&sa=X&ved=0ahUKEwjOgdGQ6bnMAhVsAcAKHTnUCa0Q6AEIVzAJ#v=onepage&q=%22annealed%20disorder%22&f=false]]
[[Physics of disordered systems|https://www.lpt.ens.fr/IMG/pdf/journee_meyer_parisi.pdf]]
[[Discussion Meeting: Nonlinear Physics of Disordered Systems: From Amorphous Solids to Complex Flows|https://www.youtube.com/playlist?list=PL04QVxpjcnjhP0xDmdE_dFSaNIM_y3lYj]]
See [[Materials science]] for the __applications__ of the principles of condensed matter physics to understanding and use of the wealth of materials in the world, both natural, and artificial.
For the study of the physics and chemistry at the interface between two phases, see [[Surface science]].
[img width=100 [http://45.media.tumblr.com/445721c345bcad457d093ff9a4e79b48/tumblr_o1ku6soPzW1twd8ddo1_500.gif]]
[[CHANDRASEKHAR LECTURE SERIES|https://www.youtube.com/playlist?list=PL04QVxpjcnjhg4SzXlAyXEvJ2ZA5gqorV]]
[[Strongly correlated systems: From models to materials|https://www.youtube.com/playlist?list=PL04QVxpjcnjiZcPa8AdK6f6IGGb3hAddX]]
[[CMP YB channel|https://www.youtube.com/channel/UCQ92xrVNVgTbq--WQpHPs5Q]]
In [[Information theory]], the ''conditional entropy'' of a [[Random variable]] $$Y$$, conditioning on another random variable $$X$$, is the average entropy of a random variable conditional on another random variable
$$H(Y|X) = \sum_{x,y} p(x,y) \log{p(y|x)}$$
[[Conditional entropy video|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=6m49.5s]]
Some results:
$$H(X,Y) = H(X) + H(Y|X) = H(Y) + H(X|Y)$$
Where we use the [[Entropy]] and [[Joint entropy]] of the random variables.
[[Proof|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=9m55s]]
[[Definition|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=16m50s]]
[[All Shannon's information measures are special cases of conditional mutual information|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=19m30s]], thus mutual information is the most general
A discriminant [[Markov network]], used for [[Supervised learning]] tasks.
[[Neural networks [3.1] : Conditional random fields - motivation|https://www.youtube.com/watch?v=GF3iSJkgPbA&index=18&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]].
__Motivation__: [[Sequence classification]], where the random variables in the sequence aren't i.i.d, in particular, they need not be independent! More generally, CRFs are used when we want to model random variables that have dependencies ([[Graphical model]]).
__Approach of ''conditional random field''s (CRF)__: [[model joint distribution|https://www.youtube.com/watch?v=GF3iSJkgPbA&index=18&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=2m40s]], i.e. model the [[Stochastic process]] generating the data. [[Notation|https://www.youtube.com/watch?v=GF3iSJkgPbA&index=18&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=3m30s]]
!!__Linear chain CRF__
[[Neural networks [3.2] : Conditional random fields - linear chain CRF|https://www.youtube.com/watch?v=PGBlyKtfB74&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=19]]
[[Definition|https://www.youtube.com/watch?v=PGBlyKtfB74&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=19#t=2m47s]]. The current label prediction depends on the just observed input, and the adjacent inputs in the sequence.
[[Informal neural network representation|https://www.youtube.com/watch?v=PGBlyKtfB74&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=19#t=7m40s]]
!!!__Context window__
[[Neural networks [3.3] : Conditional random fields - context window|https://www.youtube.com/watch?v=G4lnHc2M1CA&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=20]]. A context window refers to the set of inputs that affect a particular output label prediction
__[[Unary and pairwise log-factors|https://www.youtube.com/watch?v=G4lnHc2M1CA&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=20#t=9m10s]]__
Terms that go into the exponential of a [[Softmax]]. They are unary, or pairwise, depending on whether these terms depend on one label $$y$$ or on two labels.
!!!__Partition function__
[[Neural networks [3.4] : Conditional random fields - computing the partition function|https://www.youtube.com/watch?v=fGdXkVv1qNQ&index=21&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]], gives rise to the $$\alpha$$ and $$\beta$$ vectors/tables. These give the partial sum in the partition function, involving all the terms to the left of a given position in the sequence for $$\alpha$$, and to the right for $$\beta$$. Thus they will be useful for things like computing [[Marginal probability]]es
Computing these tables is known as the ''forward-backward algorithm'' for CRFs, respetively. It has other names, such as [[Belief propragation]] (see [[Dynamical systems on networks]]), ''sum-product'' algo. Actually more stable implementation by working on log space. [[Further trick to make it more numerically stable|https://www.youtube.com/watch?v=fGdXkVv1qNQ&index=21&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=22m20s]]
!!!__Computing marginals__
[[Neural networks [3.5] : Conditional random fields - computing marginals|https://www.youtube.com/watch?v=hjkwp-eDwt8&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=22]]. For instance, computing the probability of a single label at a given position $$k$$ in the sequence. Uses $$\alpha$$ and $$\beta$$ values above.
!!!__[[Performing classification|https://www.youtube.com/watch?v=pQJvX9U-MyE&index=23&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]__
At each position $$k$$, pick label $$y_k$$ with highest marginal probability $$p(y_k|\mathbf{X})$$. It turns out that this choice is the one that minimizes the sum of classification errors (generalization error) over the whole sequence, assuming the CRF is the true distribution! See [[proof|https://www.youtube.com/watch?v=pQJvX9U-MyE&index=23&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=3m20s]] (see also [[Bayesian statistics]]).
[[The other option: the most probable sequence|https://www.youtube.com/watch?v=pQJvX9U-MyE&index=23&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=11m]], can be performed using [[Viterbi decoding algorithm|https://www.youtube.com/watch?v=pQJvX9U-MyE&index=23&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=11m45s]]
!!__Factors, sufficient statistics__
[[Neural networks [3.7] : Conditional random fields - factors, sufficient statistics and linear CRF|https://www.youtube.com/watch?v=uXV2an9TdJY&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=24]]
Factors or compatibility function, which use [[Sufficient statistic]]s. Often represent a CRF as a product of factors.
!!![[Linear CRF|https://www.youtube.com/watch?v=uXV2an9TdJY&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=24#t=7m2s]] (no hidden units in NNs). It's a log-linear model
!!__Representations__
!!!__[[Markov network]]__
!!!__[[Factor graph]]__
!!__[[Belief propagation]]__
!__Training CRFs__
!!!__Loss function__
[[Neural networks [4.1] : Training CRFs - loss function|https://www.youtube.com/watch?v=6dpGB60Q1Ts&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=28]]
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
''Conflict'' occurs when two [[Sentient being]]s have incompatible goals/desires. It can be manifested in many ways. One such way is through [[Violence]]
[[War]] is a result of large-scale conflict and violence
See MMathPhys course, and [[Critical phenomena]]. [[lecture notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3218/2/CFTlectures.pdf]]
Field theory with conformal invariance.
Conformal invariance seems to be a generic feature of critical phenomena. Although this is not yet completely understood. [[Scale and conformal invariance in quantum field theory|http://www.sciencedirect.com/science/article/pii/0550321388901794]]
https://en.m.wikipedia.org/wiki/Conjugate_prior
See [[Bayesian inference]]
A conjugated system is a system of connected [[p-orbital]]s with [[Delocalized electron]]s in molecules with alternating single and multiple bonds, which in general may lower the overall energy of the molecule and increase stability.
https://www.wikiwand.com/en/Conjugated_system
[[video|https://www.youtube.com/watch?v=RaBI3lAACKg#t=5m56s]]
Awareness of existence.
[[Strange loop]]
[[I]]
[[Hard Problem of Consciousness|https://www.youtube.com/watch?v=13lisRJCqYo&list=PL0D746480FAEFA3C9&index=5]]
I think it is much easier to create a system that exhibits the behaviours of a conscious being, which actually has consciousness, than to create a philosophical zombie.
[[06 Neural Correlates 1|https://www.youtube.com/watch?v=ZopENH601WU&list=PL0D746480FAEFA3C9&index=6]]
David Chalmers
http://centerforsleepandconsciousness.med.wisc.edu/publications.html
[[The Sciences of Consciousness: Progress and Problems|https://www.youtube.com/watch?v=4gT-1S3FO4s&list=PLyGKBDfnk-iCp3oJRW4Cy601beguEVOmR&index=4]]
!!__[[Integrated information theory|http://www.scholarpedia.org/article/Integrated_information_theory]]__
https://www.wikiwand.com/en/Integrated_information_theory
[[Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander)|http://www.scottaaronson.com/blog/?p=1799]]
[[The Problem with Phi: A Critique of Integrated Information Theory|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574706/]]
https://www.quora.com/What-are-the-criticisms-of-Tononi%E2%80%99s-Integrated-Information-Theory
http://www.scottaaronson.com/blog/?p=1823
http://motls.blogspot.co.uk/2016/08/consciousness-trouble-with-tononis.html
--------------------
[[Taking Time Seriously in Tononi's Integrated Information Theory|http://www.ingentaconnect.com/contentone/imp/jcs/2016/00000023/F0020009/art00005]]
,,[[Synthetic consciousness: the distributed adaptive control perspective|http://rstb.royalsocietypublishing.org/content/371/1701/20150448.abstract]],,
[[Prof. Schmidhuber - The Problems of AI Consciousness and Unsupervised Learning Are Already Solved|https://www.youtube.com/watch?v=JJj4allguoU]]
([[wiki|https://en.wikipedia.org/wiki/Constitutive_equation]])
In physics and engineering, a ''constitutive equation'' or ''constitutive relation'' is a relation between two physical quantities (especially kinetic quantities as related to kinematic quantities) that is specific to a material or substance, and approximates the response of that material to external stimuli, usually as applied fields or forces.
They are often just __phenomenological__, because bulk material, or a sufficiently large amount of [[condensed matter|Condensed matter physics]], is a very complex system, made of many interacting particles. However, they should be, in principle, and sometimes are in practice, __derivable from principles of [[Statistical physics]], and often [[Non-equilibrium statistical physics]]__.
Those constitutive relations that are used in the description of the autonomous __time-evolution__ of a system often need [[Non-equilibrium statistical physics]], as systems that macroscopically (i.e. the relevant averaged quantities) evolve in time are by definition out of equilibrium.
Constitutive relations for driven systems, that are in __quasi-equilibrium__, should be derivable from [[Equilibrium statistical physics]].
!!__Constitutive equations in non-equilibrium__
[[Kinetic theory]] offers a foundation to derive constitutive equations from the microscopic details of the material. However, derivations are often hard, and give only qualitatively correct answers (more precisely, the answers are often correct up to an order $$1$$ constant, because of approximations).
[[Non-equilibrium thermodynamics]] is often based itself on more or less phenomenological principles. However, these principles can be very useful for deriving constitutive relations for large classes of systems.
An example, of one of these principles is the principle that //the rate of entropy production be maximal//. This is used in [[this paper|http://ncmm.karlin.mff.cuni.cz/preprints/11289092919pr19.pdf]] to derive the Allen-Cahn equations used to describe the evolution of phase fields (see [[Phase transition]]).
See [[On thermomechanical restrictions of continua|http://rspa.royalsocietypublishing.org/content/royprsa/460/2042/631.full.pdf]] for the paper proposing the above principle.
//I'm sure there are other approaches, and I should learn more about [[Non-equilibrium statistical physics]] in general, to learn, and organize these important ideas better.//
See [[here|http://www.phys.vt.edu/~ersharpe/6455/ch1.pdf]] (page 11) and in [[Notes on Nonequilibrium StatPhys MT2015 Oxford (mostly stochastic processes)|https://files.acrobat.com/a/preview/254ad767-71f3-429e-b36b-3d77cf67a6c7]] (page 42). Generalization of Lagrangian multipliers in finite optimization problems.
# //aka associative memory, although with slightly different connotations/meanings//
A ''Content-addressable memory'' system compares input search data (tag) against a table of stored data, and returns the address of matching data (or in the case of associative memory, the matching data).
An information storage device is called an associa-tive memory, if it permits the recall of information on the basis of a partial knowledge of its content, but without knowing its storage location.
https://www.wikiwand.com/en/Content-addressable_memory
https://www.wikiwand.com/en/Associative_memory
!!__Associative memory in the [[Brain]]__
A lot of [[Memory]] processes in the brain function associatively: by being told partial information about something, we can usually recall the thing they are refering to.
This should not be taken to imply that address-oriented information stor-age has no place in the human memory. Often it is possible to recall a specific event by remembering all related memories in the order in which they oc-curred.
!!__[[Hopfield associative memory|Hopfield network]]__
See Neural Networks: An Introduction [2 ed.] by Muller et al., chapter 3.
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See [[Percolation theory]]
Continuity of the order parameter $$P_\infty (p)$$ (the probability that an occupied site is in the infinite cluster for a given occupancy $$p$$) at $$p_c$$ is an open mathematical problem in
the general case, but it is known to hold rigorously in 2D and $$d \geq 19$$ using lace expansion methods ([[Mean-Field Behaviour and the Lace Expansion|http://link.springer.com/chapter/10.1007%2F978-94-015-8326-8_6]]). The conjecture that
$$P_\infty (p) ( p = p_c ) = 0$$ for $$3 \leq d \leq 18$$ remains however one of the open problems in the field ([[V. Beffara, V. Sidoravicius, Percolation Theory|http://arxiv.org/abs/math/0507220]]).
See [[Nonlinear system]] and [[Nonlinear continuous dynamical system]], as most interesting dynamical systems are nonlinear.
A ''continuous dynamical system'' often refers to a [[Topological dynamical system]] on an infinite topological space. In this way, the system becomes a system of [[Ordinary differential equations]].
[[Hyperbolic fixed point]]
A [[Function]] between two [[Topological spaces]] $$f: (X, \tau) \rightarrow (Y, \tau')$$ is ''continuous'' if, for all $$O \in \tau'$$, $$f^{-1} (O) \in \tau$$.
where $$f^{-1}(O)$$ is the [[Preimage]] of the set $$O$$.
[[Analysis]] offers the foundations of continuous matheatmics
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
See [[Percolation theory]]
The continuum limit, if it is defined, is often a field theory. In particular, at the critical point, it is often a [[Conformal field theory]], as percolation models at the critical point are found to have conformal symmetry.
John Cardy used this idea to find crossing probabilities between the opposite sides of a conformal rectangle filled with a conformally invariant infinitesimal lattice: [[ Critical Percolation in Finite Geometries|https://arxiv.org/abs/hep-th/9111026]]. Smirnov rigorously proved that Cardy’s conjecture holds for the continuum limit of site percolation on a triangular lattice: [[Critical percolation in the plane: conformal invariance, Cardy's formula, scaling limits|http://www.sciencedirect.com/science/article/pii/S0764444201019917]].
Defining the continuum limit is tricky. See [[ Correlation Functions in Two-Dimensional Critical Systems with Conformal Symmetry. |https://deepblue.lib.umich.edu/handle/2027.42/94010]].
,,Only certain CFTs, usually the minimal models, have been observed to possess the right structure to describe a critical lattice model in two dimensions. Due to the relatively few number of such theories, models with the same macroscopic but different microscopic properties are presumed to have identical continuum limits which correspond to the same CFT characterized by the value of the central charge c. This is a restatement of the notion of ''universality'',,
[[Renormalization group]]
A relatively new method to describe the continuum limit of the critical lattice models is [[Schramm–Loewner evolution]]
The [[Mechanics]] of most classical types of [[Bulk matter]] can be macroscopically described via [[continuum mechanics|https://en.wikipedia.org/wiki/Continuum_mechanics]], which __describes matter in terms of //continuum equations//__, based on space-time varying //fields// that evolve according to [[Differential equations]].
See [[Rheology]], for the study of flow in particular.
[[Deformation|https://en.wikipedia.org/wiki/Deformation_(mechanics)]]
A method to train [[Restricted Boltzmann machine]]s
!!!__[[Contrastive divergence|https://www.youtube.com/watch?v=MD8qXWucJBY&index=39&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]] (CD)__
[[Training Products of Experts by Minimizing Contrastive Divergence (Hinton)|http://www.mitpressjournals.org/doi/abs/10.1162/089976602760128018]] -- [[On Contrastive Divergence Learning|http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.221.8829&rep=rep1&type=pdf#page=42]]
[img[Selection_633.png]]
[[contrastive divergence (parameter update)|https://www.youtube.com/watch?v=wMb7cads0go&index=40&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]
[img[Selection_632.png]]
Useful for pre-training (initializing) a neural networs; also for [[Feature selection]] (See [[here|https://www.youtube.com/watch?v=S0kFFiHzR8M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=41#t=0m50s]])
!!!__Persistent CD__
[[Training restricted Boltzmann machines using approximations to the likelihood gradient|http://dl.acm.org/citation.cfm?id=1390290]] -- [[Using fast weights to improve persistent contrastive divergence|http://dl.acm.org/citation.cfm?id=1553506]]
[[Neural networks [5.6] : Restricted Boltzmann machine - persistent CD|https://www.youtube.com/watch?v=S0kFFiHzR8M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=41]]
-->[[Motivation|https://www.youtube.com/watch?v=S0kFFiHzR8M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=41#t=2m20s]] --> [[Idea of persistent CD|https://www.youtube.com/watch?v=S0kFFiHzR8M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=41#t=5m25s]]
Results in much better performance in the negative log likelihood, thus providing a much better estimator of the distribution $$p(x)$$.
See [[Control theory and control systems]]
[[Why learn control theory|https://www.youtube.com/watch?v=oBc_BHxw78s]]
[[Signal processing]]
!![[Control theory]]
!!Control systems
Normal control systems are usually classified as linear systems and nonlinear systems.
!!!Switched systems
A switched system consists of continuous-time=discrete-time dynamical subsystems and a rule (supervisor) that determines the switching among them.
Control techniques by switching among different controllers have been applied extensively in recent years. Indeed, a switched controller can provide a performance improvement over a fixed controller
Switched systems consist of a decision layer and a control layer. The former is logical, i.e., discrete, and decides at a given time, which subsystem is activated. The latter usually corresponds to a set of normal control systems.
[[Periodicity and chaos from switched Mow systems: Contrasting examples of discretely controlled continuous systems|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=186313&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D186313]]
[[Controllability and reachability criteria for switched linear systems|http://dx.doi.org/10.1016%2FS0005-1098(01)00267-9]]
Switching in Systems and Control
[[On partitioned controllability of switched linear systems|http://www.sciencedirect.com/science/article/pii/S000510980800383X]]
[[Finite automata approach to observability of switched Boolean control networks|http://www.sciencedirect.com/science/article/pii/S1751570X15000588]]. Boolean control networks I think are [[Boolean network]]s with an external control.
It is pointed out that “One of the major goals of [[Systems biology]] is to develop a control theory for complex biological systems” [14]
See also [[Robotics]]
,,[[Setting up formally a linear classifier, to explore the problems of learning theory, and using empirical risk minimization as learning principle|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=7m35s]], also uses definitions above.,,
__Hypothesis classes__
[[Hypothesis class and more general def|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=13m45s]]
The simple case of [[finite hypothesis classes|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=28m30s]]
__Lemmas__
[[The union bound|Boole's inequality]]
[[Hoeffding's inequality]]
!!__Results for [[ERM|Empirical risk minimization]] for the case of finite hypothesis classes__
[[Intro|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=28m30s]]
__//Strategy//__
# Training error is a good approximation to generalization error. $$\hat{\epsilon} \approx \epsilon$$ (//uniform convergence//)
# This implies that [[minimizing training error|Empirical risk minimization]] will also do pretty well in minimizing generalization error, and this will give us a bound on the generalization error $$\epsilon(\hat{h})$$, of the hypothesis $$\hat{h}$$ output by ERM.
!!!__1. Uniform convergence__
-->[[Video|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=31m50s]]. The result is a form of //uniform convergence// ([[vid|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=43m]]).
__Other formulations__
''sample complexity'' bound. [[vid|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=47m0s]]
[[Error bound|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=51m]]
!!!__2. Performance of ERM__
[[vid|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=52m30s]]
//Theorem// Let $$|\mathcal{H}| = k$$ (where $$\mathcal{H}$$ is the hypothesis class (set of possible hypothesis)), and let any $$m, \delta$$ be fixed. Then, w.p. at least $$1-\delta$$, the generalization error
$$\epsilon (\hat{h}) \leq \left (\min_{h \in \mathcal{H}} \epsilon (h) \right)+ 2 \sqrt{ \frac{1}{2m} \log{\frac{2k}{\delta}}}$$
-->[[Relation to bias/variance tradeoff|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=1h03m40s]]. First term can be seen as the "bias", and the second as the "variance"
__[[Corollary|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=1h10m30s]]__
The training size, $$m \geq O(\frac{1}{j^2} \log{\frac{k}{\delta}})$$
!!__Results for [[ERM|Empirical risk minimization]] for the case of infinite hypothesis classes__
[[Intuition|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=4m]]
Definition of //shattering//: [[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=8m54s]]
-->[[Theorem|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=17m15s]]. Let a hypothesis class $$H$$ be given, and let the [[VC dimension]] VC(H) = d. Then w.p. at leat$$1-\delta$$, we have that for all $$h \in H$$
$$|\epsilon(h)-\hat{\epsilon}(h)|\leq O\left(\sqrt{\frac{d}{m}\log{\frac{m}{d}}+\frac{1}{m}\log{\frac{1}{d}}}\right)$$
where $$m$$ is the size of the training set. A corollary is that for ERM, the number of training samples needed for a particular performance is roughly linear on the [[VC dimension]] of the hypothesis class (see [[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=22m]]). ''Sample complexity is upper bounded by VC dimension''. Often, the VC dimension is roughly proportional to the number of parameters in your model. [[Lower bound in the worst case|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=24m]]
[[Application to support vector machines|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=26m50s]]
[[smooth loss functions as convex relaxations|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=31m10s]]. Learning algos such as logistic regression or support vector machines (which use the Hinge loss) may be viewed as approximating 0-1 loss-ERM.
!!__[[Neural network theory]] -- [[Deep learning theory]]__
A mode of [[Communication]] involving a group of people communicating among each other. Often, two people communicating.
[img[https://s21.postimg.org/55qxaqm53/Selection_599.png]]
Chico Camargo
Hey man!
I hadn't seen the recording, that's cool! I'll send you the slides via email. What diagrams do you want, just to make sure I send you the right thing?
Guillermo Valle Pérez
4/22, 12:56pm
Guillermo Valle Pérez
Well the ones where you show the tree of binary states evolving to other states, and the ones showing the complexity vs frequency for example
Chico Camargo
4/22, 12:59pm
Chico Camargo
Here's the whole thing - https://docs.google.com/presentation/d/1l-IgqXy1ZdBn__aBQX0fUH8Z2y6iuogwt753omsiyAw/edit?usp=sharing
29-06-2015 - Evolution 2015 Guaruja
What Darwin didn't know: natural variation is structured Chico Camargo University of Oxford Evolution 2015 Guarujá, Brazil
docs.google.com
Chico Camargo
4/22, 1:01pm
Chico Camargo
Just one thing - recently I've changed my definition of phenotype to something more coarse-grained, so the plots for complexity have changed. But they're fine, the new ones say the same as the old ones. The robustness things, however, don't apply so directly to the new phenotype definition I've been exploring, so I would not include that part about robustness. All the rest is fine!
Chico Camargo
4/22, 1:03pm
Chico Camargo
Finally, an interesting paper, in case you haven't seen it:
http://rsif.royalsocietypublishing.org/content/royinterface/12/113/20150724.full.pdf
Chico Camargo
4/22, 1:03pm
Chico Camargo
They say some cool stuff there, like "The properties of genotype –phenotype (GP) maps have been studied in great detail for RNA secondary structure. These include a highly biased distribution of genotypes per phenotype, negative correlation of genotypic robustness and evolvability, positive correlation of phenotypic robustness
and evolvability, shape-space covering, and a roughly logarithmic scaling
of phenotypic robustness with phenotypic frequency. More recently similar
properties have been discovered in other GP maps, suggesting that they may
be fundamental to biological GP maps, in general, rather than specific to the
RNA secondary structure map."
Guillermo Valle Pérez
4/22, 2:53pm
Guillermo Valle Pérez
Yeah i've seen that paper. I've found a way to predict more or less the number of sequences that map to the most frequent sequences, in average over the ensemble of transducers. It's only approximate, but it is about thinking about certain kinds of cycles, and how simpler cycles in the transducer are more probable, so sounds similar to your boolean network cycles thing.
It's also related to the idea about constrained and unconstrained parts, which I think is the most fundamental. The idea for transducers is that there are states that give the same output independent of the output (so they are unconstrained). Outputs that admit cycling through these states have most of the input bits unconstrained. Then if one looks at what kinds of cycles there are, one sees that the most probable are the simplest ones, and these correspond to simple outputs
Guillermo Valle Pérez
4/22, 2:59pm
Guillermo Valle Pérez
It's not totally rigorous, but estimating the probabilities of these cycles roughly gives the right frequency of the most probable strings like 11111111.. 011111111, 101010101... etc
Chico Camargo
4/22, 3:02pm
Chico Camargo
That is very interesting!
On the boolean networks it turns out that the probability of a cyclic output is an exponential with the cycle length, but the complexity bias exists even for cycles of the same length
I still don't understand how the GP map works though, maybe because I don't fully understand what a transducer really is. What is the genotype and the phenotype (and the mapping), in their case?
Guillermo Valle Pérez
4/22, 3:04pm
Guillermo Valle Pérez
grrwhen i said above "same output independent of the output" i meant "same output independent of the input"...
Chico Camargo
4/22, 3:04pm
Chico Camargo
Oh yeah I god that grin emoticon
So, I understand that a finite state transducer is like a finite automaton, but with two tapes: an input tape and an output tape
reads a tape and writes another
Guillermo Valle Pérez
4/22, 3:05pm
Guillermo Valle Pérez
http://galaxy.eti.pg.gda.pl/katedry/kiw/pracownicy/Jan.Daciuk/personal/thesis/img74.gif
Guillermo Valle Pérez
4/22, 3:07pm
Guillermo Valle Pérez
its a finite state machine. You start at a certain state and move to the state according to the symbol you read and following the transition according to the first symbol in "x/y". When you follow that transition you print a "y"
oh sorry
in that picture i showed you the x and y are swapped
relative to my convention
that picture isnt ver good
wait
Guillermo Valle Pérez
4/22, 3:09pm
Guillermo Valle Pérez
Guillermo Valle Pérez
4/22, 3:09pm
Guillermo Valle Pérez
thats one of the ones generated by my actual code
sideways lol
Chico Camargo
4/22, 3:09pm
Chico Camargo
Beautiful!
Ok, it's a finite state machine with two tapes, rather than just traversing (and accepting or rejecting) an input string, it translates an input string to an output string
Guillermo Valle Pérez
4/22, 3:09pm
Guillermo Valle Pérez
so you begin at state 0 and if you see a 0 you go to state 0 printing a 0, and if you see an 1 you go to state 1 also printing a 0
Chico Camargo
4/22, 3:09pm
Chico Camargo
Cool
So you randomly generate a finite state transducer, and see how many input words give you each output word?
Guillermo Valle Pérez
4/22, 3:10pm
Guillermo Valle Pérez
Yep
Chico Camargo
4/22, 3:11pm
Chico Camargo
And the trends are the same even if you generate a lot of those transducers at random?
Guillermo Valle Pérez
4/22, 3:11pm
Guillermo Valle Pérez
yeah the more you generate the more the graph seems to be a linear thing with a given spread in the frequency-vs-complexity, like the one i posted
technically you could enumerate all transducers of a given number of states
Chico Camargo
4/22, 3:13pm
Chico Camargo
So the trend is there even if you have a single transducer, but it's more obvious if you plot the results for a lot of them, is that what you're saying?
I have more questions:
How long are the input strings?
How long are the output strings?
You said you can enumerate them. How is the transducer represented?
I was reading some stuff about formal language theory last night, and it relates so much to that, you have no idea
Guillermo Valle Pérez
4/22, 3:14pm
Guillermo Valle Pérez
Well, the trend is mostly visible if you plot a lot of them. For a single one I tend to find quite some noise.
The input strings ive tried are 9-15 bits long, but they can be anything
I've made it so that the output strings are the same length as the input. I could make the variable length by adding an "empty" symbol as a possibility
but havent tried that
The transducers are represented as strings too I think, but I'm using a finite automaton generator, not generating them on my own
because it's not that trivial to generate them really uniformly apparently. I think it's because many automatons would be equivalent, and it only generates distinct ones..
Chico Camargo
4/22, 3:17pm
Chico Camargo
I see
Guillermo Valle Pérez
4/22, 3:17pm
Guillermo Valle Pérez
Tho I'm not sure how it's generating them under the hood tbh, atm
Chico Camargo
4/22, 3:17pm
Chico Camargo
Sure
Guillermo Valle Pérez
4/22, 3:18pm
Guillermo Valle Pérez
and i dont think the answer should be too different if you generated them in a more naive way
Chico Camargo
4/22, 3:18pm
Chico Camargo
I agree with you
One thing I'm trying to understand is what space is being mapped to what space
But I'm slowly getting it
Any string to any string.
(well, binary strings in both alphabets, in this case)
Guillermo Valle Pérez
4/22, 3:21pm
Guillermo Valle Pérez
yeah you can choose any alphabet. But i chose binary. and in my case its any binary string to given length to the same set
well no there are some strings you can't get in the output
so the output space is some subset of {1,0}^*
{1,0}^n, n fixed i mean
Chico Camargo
4/22, 3:23pm
Chico Camargo
And there are binary strings that can't be generated by that transducer. Sure
Guillermo Valle Pérez
4/22, 3:23pm
Guillermo Valle Pérez
Yeah
quite a few actually
which make sense
Chico Camargo
4/22, 3:24pm
Chico Camargo
It does.
Guillermo Valle Pérez
4/22, 3:24pm
Guillermo Valle Pérez
becuase if there is redundancy, the phenotype space must be smaller, for a deterministic map
smaller than genotype space
Chico Camargo
4/22, 3:25pm
Chico Camargo
And because each transducer will in fact produce strings of a given shape,
like "0 1^n 0 1 0^m 1"
And when you choose the number of states in your transducer.. I would imagine
I imagine very large transducers would be unnecessarily complex
Guillermo Valle Pérez
4/22, 3:27pm
Guillermo Valle Pérez
well i choose a small number of states, like 5 so that it's simple
Chico Camargo
4/22, 3:28pm
Chico Camargo
Yeap
Guillermo Valle Pérez
4/22, 3:28pm
Guillermo Valle Pérez
I've tried more states and results are not too different, but I worry that I am taking a sample that is much smaller than all possible trandsucers of that size
With smaller number of states like 2 or 3, maps seem too trivial also
Chico Camargo
4/22, 3:30pm
Chico Camargo
I'd expect that the complexity bias would become too messy if the transducers were too large: you'd be using a very complex algorithm to map input to output, introducing a lot of complexity into the business
I find it interesting that when you sample different transducers, you're sampling different GP maps.
...which is something that can evolve, as well. Just like you can change the parameters of an ODE instead of changing its initial conditions, you can change the GP map instead of its I/O
Guillermo Valle Pérez
4/22, 3:32pm
Guillermo Valle Pérez
what i can't quite figure is how to relate these results more directly to other results like that of the boolean network or polyominoes. Yeah, in principles these things should map to a transducer, but how simple a transducer, and do they have some features that simply the {ensemble of all transducers} does not capture. I mean this is precisely the same problems with choosing random network null models in network theory..
Guillermo Valle Pérez
4/22, 3:32pm
Guillermo Valle Pérez
Yeah i also expect more noise for more states..
Chico Camargo
4/22, 3:33pm
Chico Camargo
So, normally a boolean network is the genotype, so your input string in this case. Same for an RNA sequence. Your transducer would be the actual map
Guillermo Valle Pérez
4/22, 3:35pm
Guillermo Valle Pérez
"which is something that can evolve". Yeah the whole reason I did was just in the spirit of null models: see if one expects these features just looking at random simple maps, without any other constraint.
But I also thought about, why choose the transducers uniformly at random, why not sample them according to the biased output of another transducer, that will produce simpler transducers more often. One can imagine a potentially infinite chain of GP maps determining GP maps, and it'd be interesting to see what one gets..
Guillermo Valle Pérez
4/22, 3:35pm
Guillermo Valle Pérez
Yeah the whole reason I did -> Yeah the whole reason I did this
Chico Camargo
4/22, 3:36pm
Chico Camargo
I agree with the spirit of null models: that is totally the point
Hoho, I know what you mean!
In fact I think there is something else to it
Guillermo Valle Pérez
4/22, 3:37pm
Guillermo Valle Pérez
Yeah this looks like whats called hyperparameter optimization in machine learning: when you optimize your machine learning model itself
Or genetic programming with evolving GP maps, which has also been tried
Another way to do this would be to make a transducer whose output changes the transducer itself, and see how that evolves
which tbh sounds like the whole idea of genetic regulatory networks where the phenotype (proteins) in some sense change the GP map (genes->proteins)
I guess when one does this one can then still define a meta GP map like what you do in the boolean networks
Chico Camargo
4/22, 3:41pm
Chico Camargo
I think so
Coupling GP maps is an interesting idea
But you've gotta play with the timescales that that involves
For example
- also on that potentially infinite chain of GP maps you mentioned:
Chico Camargo
4/22, 3:42pm
Chico Camargo
So, this chain of GP maps determining GP maps is sequential: once, in the history of life, life "chose" a set of basepairs, A-T, C-G. And it's been working pretty much with all that. And by "choosing" I mean that its rate of change slowed down. It could be from reaching a fitness peak, local or not, but the fact is that it slowed down.
Then, at some point, life "chose" a genetic code: the way codons map to aminoacids. Once that choice was frozen, life has been working with it ever since.
Then it chose some protein families. It chose chromosomes. Yada, yada, yada: (pretty much) frozen choices allowing more complex forms to emerge. And you could argue that the genetic code and these other things are still changing, but they're just changing very slowly, while other things change more quickly
Guillermo Valle Pérez
4/22, 3:43pm
Guillermo Valle Pérez
Hm, I see what you mean
Chico Camargo
4/22, 3:43pm
Chico Camargo
In a similar fashion, I see that with language. We aren't really changing our alphabet, or our grammar structures anymore, it seems like those evolved once and stopped, but they're just changing slowly. On the other hand, new words still appear all the time
I think it makes total sense to get the transducer from a set of transducers
- but if you're picking a simple transducer, you're probably already doing that
Guillermo Valle Pérez
4/22, 3:44pm
Guillermo Valle Pérez
well im picking simple ones in the sens of small number of states
Chico Camargo
4/22, 3:45pm
Chico Camargo
If the transducer can really be represented as a string, then I'd be sure of that
Guillermo Valle Pérez
4/22, 3:45pm
Guillermo Valle Pérez
but i haven tried generating transducers from a transducer
yet
but in your example above
it seems like it would like generating random transducers and then fixing to one. Then using that fixed transducers as maybe a building block out of which new meta transducers can be built...
tho im not sure i understand where GP maps fit in all the biological examples you mention above
Chico Camargo
4/22, 3:49pm
Chico Camargo
a GP map is a translation, an I/O machine, a transducer. Something that converts information of a kind into information of another kind
Guillermo Valle Pérez
4/22, 3:50pm
Guillermo Valle Pérez
first the atcg is an alphabet, not a GP map right? Then it evolved the codon-aminoacid, which i see its a GP map. What is the protein family, and what do the chromosomes have to do with a GP map?
i mean I would understand that gene-> protein is a GP map. Then protein->some cellular phenotype is another one..
Chico Camargo
4/22, 3:52pm
Chico Camargo
Ok, point taken, the ATCG is not a GP map. It is an alphabet.
Let me put it this way:
Chico Camargo
4/22, 3:59pm
Chico Camargo
Nature chooses a way store information, then it pretty much settles for that one according to some criteria like thermodynamical stability and to how much information you can store with that system - for instance, ATCG basepairs. Or, another way to store information, aminoacids. So now we have two alphabets, one with four letters, one with ~20.
Then, once those had been pretty much chosen, eventually nature chose/found a way to translate between them. Or maybe it found the latter alphabet as an outcome of finding the GP map that converts information stored in DNA sequences to information stored in aminoacid sequences. But anyway, it chose the alphabets, then it chose the GP map.
Focusing on the GP maps: DNA-> Proteins, Protein shape-> Protein function in the cell, gene networks -> cellular phenotype, cell type composition -> tissue structure/function/identity, whatever mapping from one kind of information to another (but just mappings, so nothing about the chromosomes I had mentioned). My point is that I think often nature tries many "transducers", many I/O machines, and eventually it chooses some of them, and builds on top of them. So the I/O alphabets and GP maps are conserved along evolution.
In this sense, humans probably use the same cell types as other apes. And we all use the same body plans as other mammals. And the same embryonic development genes as worms. Etc etc downards, ad infinitum.
Chico Camargo
4/22, 4:01pm
Chico Camargo
I'm saying this because some structures evolve quickly and others don't: in the hierarchy of which genes regulate which other ones, the further up a gene is placed, the less it changes over time: the more conserved it is.
And I think that makes total sense, considering that it is part of a GP map that was "chosen" long ago
Guillermo Valle Pérez
4/22, 4:02pm
Guillermo Valle Pérez
and because many things depend on it, it's hard to change right?
Chico Camargo
4/22, 4:02pm
Chico Camargo
that too
in theory you could change it, but today that'd mean a drastic reduction on fitness
it'd be like trying to reinvent the genetic code: it won't work, life relies too much on that
Guillermo Valle Pérez
4/22, 4:03pm
Guillermo Valle Pérez
that's what I mean, unless you change many things along with it, in just the right ways.. which is highly unlikely
Chico Camargo
4/22, 4:03pm
Chico Camargo
Exactly
That'd be like changing the English grammar, or semantics
On the other hand, if the evolutionary innovation is pretty fresh, there's probably not much relying on it, so it's ok to break it
Guillermo Valle Pérez
4/22, 4:06pm
Guillermo Valle Pérez
This is just why it's so hard to say switch from qwerty to dvorak keyboards, it's changing your whole word-hand movement GP map, on which your whole internet life depends
Chico Camargo
4/22, 4:06pm
Chico Camargo
haha
yeah!
So, I think the easiest story you can tell is that a transducer is a very simple a GP map, without all the biological details.
Which features did you say are not captured by the transducers?
Guillermo Valle Pérez
4/22, 4:09pm
Guillermo Valle Pérez
Well in theory all GP maps should potentially be expressed as transducers, though probably of many more states. Having 5 states is like considering the set of sufficiently coarse-grained biological models I suppose..
Chico Camargo
4/22, 4:11pm
Chico Camargo
Hm, there is one thing I still don't see
What you said resonates very well with the ideas in that paper I sent you: that all these properties come from the sequence nature of genotypes and phenotypes
or genotypes at least.
and sequences = I/O strings, great
Guillermo Valle Pérez
4/22, 4:13pm
Guillermo Valle Pérez
If you consider any number of states, transducers pretty much include everything else.. But I'm only considering simple ones.
A simple transducer can either be justified as some process during the earliest stages of evolution of some form of life (natural or artificial) where the system itself is actually simple. Say a few dots in game of life, or a few molecules.
Then the justification to apply to more complex life is probably the same as why we use coarse-grained models: yeah life is full of intricate details, but it is organized in such a way that is approximately simple.
I think this would like saying complex life is really behainv as a transducer with many many states, but this transducer is coarse-grainable to a transducer of few states.
This actually agrees nicely with the idea that life current GP maps were in some way determined by previous GP maps, and thus are expected to be simpler than just a random GP map from ATCG to tissue...
Chico Camargo
4/22, 4:14pm
Chico Camargo
Yeah
I'm happy with that
there is only one thing that I still fail to agree/understand
A transducer translates input to output by treating the input as an (ordered) string: it first reads the first character, then the second, then the third
And even though the map in the end is from string A to string B, it's calculated from this step-by-step reading
Guillermo Valle Pérez
4/22, 4:15pm
Guillermo Valle Pérez
that's how it "mechanically" works yeah
Chico Camargo
4/22, 4:16pm
Chico Camargo
Yeah
But for example, a gene network. The network, really. It can be written as a string, but you can also do any permutations on the gene order, and that'd give you a different string.
The GP map for gene networks is also from string to string, but it doesn't rely on reading anything step by step
and it's harder for me to talk about "what parts of the string are unconstrained", for instance
Guillermo Valle Pérez
4/22, 4:17pm
Guillermo Valle Pérez
"written as a string, but you can also do any permutations on the gene order, and that'd give you a different string." but it'd give you the same network, you mean?
Chico Camargo
4/22, 4:17pm
Chico Camargo
It'd give you a network that is isomorphic to it (like, B->A instead of A->B). That could possibly give you the same phenotype
or an isomorphic phenotype. Hm
Guillermo Valle Pérez
4/22, 4:18pm
Guillermo Valle Pérez
but i mean, if you have some map from finite strings to finite strings, it is always in principle writeable as a finite transducer
Chico Camargo
4/22, 4:18pm
Chico Camargo
Oh. That's true.
Guillermo Valle Pérez
4/22, 4:18pm
Guillermo Valle Pérez
the transducer may be quite large though
Chico Camargo
4/22, 4:18pm
Chico Camargo
There's a theorem that does that, right?
that says that
shit. That's awesome.
Guillermo Valle Pérez
4/22, 4:19pm
Guillermo Valle Pérez
yeah... I mean it's kind of floating around the results of turing and church and co. I think
A Turing machin is just a kind of finite transducer with infinite memory
so like infinite number of states..
Chico Camargo
4/22, 4:20pm
Chico Camargo
yeah yeah
Guillermo Valle Pérez
4/22, 4:20pm
Guillermo Valle Pérez
But the thing is that a map between two finite sets can always be expressible with finite memory
Chico Camargo
4/22, 4:20pm
Chico Camargo
no, there is, I'm sure
I read this theorem yesterday, it's all coming back
Guillermo Valle Pérez
4/22, 4:20pm
Guillermo Valle Pérez
ah cool
Chico Camargo
4/22, 4:21pm
Chico Camargo
What I actually read:
Guillermo Valle Pérez
4/22, 4:21pm
Guillermo Valle Pérez
You can make your own! Map any finite set of inputs to any output: http://examples.mikemccandless.com/fst.py?terms=pepe%2F33%0D%0Amoth%2F1%0D%0Apop%2F2%0D%0Astar%2F3%0D%0Astop%2F4%0D%0Atop%2F5%0D%0A&cmd=Build+it!
examples.mikemccandless.com
examples.mikemccandless.com
Chico Camargo
4/22, 4:23pm
Chico Camargo
There is a correspondence between formal grammars (sets of strings) and automata (that might accept or reject a string, saying that it does or doesn't belong in that grammar).
Finite grammars map to finite automata,
Context-free grammars to push-down automata, and so on,
Until phrase structure grammars that map to Turing machines.
Grammars and finite automata are slightly different from FST, but I'm sure there must be a version of that theorem that talks about FST.
Chico Camargo
4/22, 4:24pm
Chico Camargo
Ah brilliant!
That's really interesting, since any finite set is enumerable (and more specifically enumerable in binary), any finite set can be translated to strings.
But that alone doesn't mean that you would have any bias of any sort
Now it's clear to me that it isn't about the sequence order, as in which part comes first, but simply from the hypercube nature of the space of sequences
Guillermo Valle Pérez
4/22, 4:31pm
Guillermo Valle Pérez
See page 20 of http://web.cs.ucdavis.edu/~rogaway/classes/120/spring13/eric-transducers.pdf there it effectively says what we want, that they can encode any map between finite sets
web.cs.ucdavis.edu
web.cs.ucdavis.edu
Guillermo Valle Pérez
4/22, 4:32pm
Guillermo Valle Pérez
what is comes "from the hypercube nature of the space of sequences"?
Chico Camargo
4/22, 4:32pm
Chico Camargo
yup! I see it
Guillermo Valle Pérez
4/22, 4:33pm
Guillermo Valle Pérez
Also the bias comes from constraining the maps to be simple in the sense of few states in the fst, I think. Clearly if you considered all possible maps between two sets there wouldn't be bias in average
i meant: what comes "from the hypercube nature of the space of sequences"?
my internal fst is making so many mistakes..
Chico Camargo
4/22, 4:34pm
Chico Camargo
I agree that if you considered all the possible FST you wouldn't get any nice average, you need simple FSTs
haha have you switched to dvorak?
Chico Camargo
4/22, 4:34pm
Chico Camargo
What I mean is that the paper I sent you they say:
"The Fibonacci GP map therefore offers strong evidence that the sequential nature of biological information determines the fundamental structure of GP maps, which in turn has a profound impact on the course of biological evolution."
Guillermo Valle Pérez
4/22, 4:35pm
Guillermo Valle Pérez
no i meant internal as in in the brain. I wanted to swithc to dvorak but havent had time tongue emoticon
Yeah I didn't get that part
Chico Camargo
4/22, 4:35pm
Chico Camargo
And when they say "the sequential nature", I think it suggests that the fact that information is stored in ordered sequences. But I think it isn't so much about that
Guillermo Valle Pérez
4/22, 4:35pm
Guillermo Valle Pérez
Yeah I thought it was more about it having constrained and unconstrained parts
which doesnt say anything about how the information is stored/read
Chico Camargo
4/22, 4:36pm
Chico Camargo
Yeah. I think the order doesn't really matter.
exactly.
and the unconstrained parts could be in the beginning, middle, end, or just have no order
Guillermo Valle Pérez
4/22, 4:37pm
Guillermo Valle Pérez
yeah, in fact in the fsts unconstrained parts are not a fixed portion of the input string, but depend on the previous portions of the input string
Chico Camargo
4/22, 4:37pm
Chico Camargo
as long as you have an unconstrained part whose contribution to the designability of your phenotype size grows exponentially (or just a lot) with the size of the unconstrained part: like 4^L, in the case of RNA, or 2^L in the binary case
Guillermo Valle Pérez
4/22, 4:38pm
Guillermo Valle Pérez
"An unconstrained part" should more correctly be a property of the FST mechanism than a part of the input string. In the FSTs, an unconstrained part is a state whose outputs are the same irresepective of input.
Chico Camargo
4/22, 4:39pm
Chico Camargo
indeed
unconstrained means ignored by the GP map
Guillermo Valle Pérez
4/22, 4:40pm
Guillermo Valle Pérez
In the case of the FSTs as you grow the length of the input, the input has more chances of looping through these states and everytime you go through it the number of possibilities multiplies by 2, so it grows almost exponentially
Chico Camargo
4/22, 4:40pm
Chico Camargo
so if the GP map doesn't care about sequence/string order, the unconstrained parts of the genotype won't be ordered, won't be "after a stop codon"
yeah
Guillermo Valle Pérez
4/22, 4:41pm
Guillermo Valle Pérez
well there may be some order to them, but may be more complicated and subtle, and not-apparent
Chico Camargo
4/22, 4:43pm
Chico Camargo
but see, a gene network isn't ordered per se. When you decide to represent it as a string, sure, you've ordered it. For the same GP map, different orderings will produce different transducers, and therefore different orderings of the unconstrained parts, but there is no inherent order on a gene network
Chico Camargo
4/22, 4:44pm
Chico Camargo
There is, though, an exponential contribution to designability: 3^X, where X is the number of "unconstrained" interactions
Guillermo Valle Pérez
4/22, 4:44pm
Guillermo Valle Pérez
And you can actually construct GP maps where the bias is towards some designed complex sequence instead of towards simple ones. However these require very special kinds of structures with the sequence coded into it, while a bias towards a simple output requires a simple structure, and thus appears often in FSTs
Chico Camargo
4/22, 4:45pm
Chico Camargo
precisely.
Guillermo Valle Pérez
4/22, 4:46pm
Guillermo Valle Pérez
yeah i agree that for the network the output shouldnt depend on the ordering. However, maybe due to the nature of the FST different ordering conventions may need different FSTs
Chico Camargo
4/22, 4:46pm
Chico Camargo
Yeah
Guillermo Valle Pérez
4/22, 4:47pm
Guillermo Valle Pérez
"3^X, where X is the number of "unconstrained" interactions". what are the uncstrained interactions?
Chico Camargo
4/22, 4:47pm
Chico Camargo
the genotype for a gene network is the network's directed graph
each link between nodes A and B can be +, -, or non-existent (0). That's what I called 'interactions': these links
Guillermo Valle Pérez
4/22, 4:49pm
Guillermo Valle Pérez
and it is unconstrained if it doesnt affect the phenotype you define?
Chico Camargo
4/22, 4:50pm
Chico Camargo
Exactly. When I said "There is, though, an exponential contribution to designability: 3^X, where X is the number of "unconstrained" interactions", I meant that if there are X interactions that can be a +, a - or an 0 and that won't make a difference for the resulting phenotype, they'll be increasing the designability of that phenotype by 3^X.
Guillermo Valle Pérez
4/22, 4:53pm
Guillermo Valle Pérez
It'd be interesting to find the actual FST for the network description to cycle/phenotype
and see if those unconstrained parts can be seen as unconstrained states in the fst
Chico Camargo
4/22, 4:54pm
Chico Camargo
I mean, if for every GP map there is a FST, it should be
I'm still pondering
This sequence story: The cause for all these properties would not be "sequential nature of biological information", but the fact that in nature you often have unconstrained parts whose contribution to the designability of your phenotype size grows exponentially.
Guillermo Valle Pérez
4/22, 4:58pm
Guillermo Valle Pérez
Yeah
Chico Camargo
4/22, 4:58pm
Chico Camargo
Well, it's from the same principles behind PCA, that most things need a short description
that's sloppiness, essentially
Guillermo Valle Pérez
4/22, 4:58pm
Guillermo Valle Pérez
PCA?
Chico Camargo
4/22, 4:59pm
Chico Camargo
Principal Component Analysis. It's a technique that effectively reduces the dimensionality of a dataset by finding a set of axes (the base, in linear algebra terms) where most of the variation in your dataset can be described by the first axes
Guillermo Valle Pérez
4/22, 5:00pm
Guillermo Valle Pérez
Ah yeah. Yeah I mean, we are trying to find (at least part) of the explanation of the simplicity in the word smile emoticon
Chico Camargo
4/22, 5:01pm
Chico Camargo
in the word and in the world? wink emoticon
Guillermo Valle Pérez
4/22, 5:02pm
Guillermo Valle Pérez
haha yeah lucky mistake
Chico Camargo
4/22, 5:02pm
Chico Camargo
Man, I'm really hungry, I gotta get some lunch
But let's keep talking about this! This is really exciting, and it's awesome to talk to you about that grin emoticon
Also, would you send me your code so I play with it as well?
Guillermo Valle Pérez
4/22, 5:04pm
Guillermo Valle Pérez
Sure, i'll put it on github and share! And yeah we'should talk again
Chico Camargo
4/22, 5:04pm
Chico Camargo
Sweet!
See you later then!
Guillermo Valle Pérez
4/22, 5:04pm
Guillermo Valle Pérez
like emoticon
Guillermo Valle Pérez
4/22, 5:18pm
Guillermo Valle Pérez
https://github.com/guillefix/fst-bias
guillefix/fst-bias
fst-bias - Code for the exploration of bias for simplicity in the output of random finite state transducers
github.com
Chico Camargo
4/22, 5:52pm
Chico Camargo
Cheers!
[[Mathematical|Mathematics]] study of [[Convex function]]s, and [[Convex set]]s.
This has applications to [[Convex optimization]]
https://www.wikiwand.com/en/Convex_hull
__Convex combination__
$$\lambda X_1 + (1-\lambda) X_2$$
See full definition [[here|https://www.wikiwand.com/en/Convex_combination]]
!!__Convex calculus__
Operations on [[Set]]s and [[Function]]s that preserve convexity.
A [[Function]] is ''convex'' over some if it satisfies the inequality
$$f(\alpha x + \beta y) \leq \alpha f(x) + \beta f(y)$$
for all $$x, y \in D$$ (where $$D$$ is the domain) and all $$\alpha, \beta \in \mathbf{R}$$ with $$\alpha+\beta=1, \alpha \geq 0, \beta \geq 0$$ (i.e. this is a [[Convex combination]]
The domain $$D$$ has to be a [[Convex set]] for this to be defined
[img[https://upload.wikimedia.org/wikipedia/commons/c/c7/ConvexFunction.svg]]
Intuitively, a convex function is one for which the weighted average of the inputs produces at most the same weighted averages of the outputs.
__Equivalent conditions for differentiable functions__
*Once-differentiable. Tangent is lower bound. $$g(y) + \nabla g(y)^T (x-y) \leq g(x)$$.
*If the function is twice [[Differentiable]], then it is convex iff $$f'' \geq 0$$. For multivariate, [[Hessian]] has to be positive semi-definite
__Relations to [[Convex set]]s__
All the points above the function (the function's [[Epigraph]]) form a convex set.
__Operations that preserve convexity__
* Non-negative weighted sums of convex functions. If you allow negative weights, we get a problem of [[Difference of convex functions]].
* Pointwise maximum of the functions.
See [[Convex set]]
Smallest convex set that contains all points of a set. Unique because of the property that intersection preserves convexity (if non-unique could always take intersection giving smallest set -> contradiction).
Convex hull of a convex set is the convex set itself
Convex hull of a (finite) set of points is a [[Polytope]]
//aka convex programming//
''Convex optimization'' refers to an [[Optimization]] problem in which the objective and constraint functions are both [[convex|Convex function]]. This implies that the domain of the optimization variable is a convex set. The convexity property can make optimization in some sense "easier" than the general case - for example, any local minimum must be a global minimum. It is a generalization of [[Linear programming]]
See [[slides|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]]
https://www.wikiwand.com/en/Convex_optimization
[ext[Convex optimization|http://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf]] [[pdf|file:///home/guillefix/Dropbox/COSMOS/Mathematics/Mathematical%20methods/bv_cvxbook.pdf]]
Convex optimization problems include least-squares fitting (see [[Linear regression]]), and [[Linear programming]] problems.
See [[Learning theory]], [[Andrew Ng video|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=23m30s]]
[[Dual problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=34m30s]], uses [[Max–min inequality]]
!!__Solution methods__
Log-barrier methods. See page 51 [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]]
Projected subgradients, conditional gradients
Newton's method
quasi-Newton
conjugate-gradient
bundle algorithms
cutting-plane algorithz
Interior-point methods, like in linear programming.
!!!__Applications of convex optimazation to nonconvex optimization problems__
[img[http://i.imgur.com/y90QRNA.jpg]]
See more on this theory here: [[Convex optimization heuristics for linear inverse problems]], [[Linear inverse problem]]
[[The Convex Geometry of Linear Inverse Problems|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Chandra-overview.pdf]]. Seizes [[Simplicity]] of data to solve underdetermined problem. Provides a general framework to convert notions of simplicity into convex penalty functions, resulting in convex optimization solutions to linear, underdetermined in-verse problems. [[Convex optimization]], [[Linear inverse problem]]
"many interesting signals or models in practice contain few degrees of freedom relative to their ambient dimension". We describe a model (or object) as <b>simple</b> if it can be written as a nonnegative linear combination of a few elements from an atomic set (for instance, a specified set of functions, vectors, matrices,...). As they explain, examples of simple objects are sparse vectors, and low-rank matrices. These have been shown to be recoverable from very incomplete information:
*[ext[Robust Uncertainty Principles: Exact Signal Reconstruction From Highly Incomplete Frequency Information|http://people.ee.duke.edu/~lcarin/01580791.pdf]]
*[ext[Exact Matrix Completion via Convex Optimization|http://pages.cs.wisc.edu/~brecht/papers/08.Candes.Recht.MatrixCompletion.pdf]]
*[ext[For Most Large Underdetermined Systems of Equations, the Minimal l1-norm Near-Solution
Approximates the Sparsest Near-Solution|http://statweb.stanford.edu/~donoho/Reports/2004/l1l0approx.pdf]]
* [[Compressed Sensing|http://www.signallake.com/innovation/Donoho0406.pdf]]
''Method'': <span style="color:#FAF;">Under suitable conditions the convex hull $$conv(A)$$ defines the unit ball of a norm, which is called the atomic norm induced by the atomic set $$A$$. We can then minimize the atomic norm subject to measurement constraints, which results in a convex programming heuristic for recovering simple models given linear measurements.</span>
There is a tradeoff between the complexity of the recovery algorithm and the number of measurements required for recovery
!!!__Examples__
See [[Linear inverse problem]] for application to the Matrix completion problem
A [[Set]] where all the points in the line segment connecting two points in the set, lie in the set.
In more general cases the "line segment" is defined as all [[Convex combination]]s of the objects at the end points.
__Operations that preserve convexity__
Pages 13 and 14 [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]]
* Intersection
* [[Affine transformation]]
__Separating hyperplane__
For every convex set, and any point outside the set (but in some underlying space, in particular $$R^n$$..), there exists a [[Hyperplane]] that //separates// the set and the point, i.e. the point is one half-space, and the whole set lies on the other. This is called the separating hyperplane.
Pages 16-20 [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]]
__[[Convex hull]]__
----------------
If $$g$$ is a [[Convex function]], then the [[Set]] $$\{x|g(x) \leq 0 \}$$ is convex.
A type of [[Error-correcting code]]
[[MAP BCJR algorithm - Decoding of convolutional codes|https://www.youtube.com/watch?v=5qT7x81NG0Y]]
[[Introduction to convolutional codes|https://www.youtube.com/watch?v=lZtr9wXeh_Y]]
[[Information Theory And Coding - Convolutional Codes|https://www.youtube.com/watch?v=oI0MwwXJ8dE]]
Introduction of the BCJR algo: [[http://www.wireless.ece.ufl.edu/eel6550/lit/BCJR.pdf]]
[[Nando's vid|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10]]
http://cs231n.github.io/
http://cs231n.github.io/convolutional-networks/
http://cs231n.stanford.edu/syllabus.html
!!![ext[Convnet demo on the web!|http://scs.ryerson.ca/~aharley/vis/conv/]] [ext[details here|http://scs.ryerson.ca/~aharley/vis/]]
[img[http://scs.ryerson.ca/~aharley/vis/images/convnet_480.png]]
[img[http://deeplearning.net/tutorial/_images/mylenet.png]]
''Convolution''
In The "c1 feature maps" are a set of 2D arrays of neurons. Each array looks for a feature, and a point in the array would represent the location of that feature. To accomplish this, that point of that array is connected to a set of pixels centered in the corresponding point in the input image (an array of pixels). We have much less parameters because for each of these 2D arrays we only specify the parameters for one of the neruons in that array, all other neurons are identical, just connected to displaced sets of pixels.
[[What is convolution|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=14m35s]]. [[Correlation|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=18m39s]]. Flip parameters vector (or array..) and rewrite the correlation, [[we get a convolution|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=21m50s]]. Of course, there's much more to [[convolutions|https://en.wikipedia.org/wiki/Convolution]], including the convolution theorem for e.g.
''Stride'' How much you jump in pixel space (or in previous layer) when you move from one point to another in a feature layer.
Can also expand boundary (//zero padding//) to keep layer gotten by convolution is of same size as original layer.
[[Nice example|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=27m06s]]
[[So many indices!|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=35m06s]]
''Pooling''
[[This is what it does|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=9m56s]]. It downsamples. For memory, and invariance (being more insesitive to perturbations).
We can also apply non-linearities in between layers of course, like for contours enhacement
Use as many of these layers Iconvolutions and poolings) as we can train, 20+ ([[Deep learning]])
At the end we may have a fully connected neural layer, to do the classification, but researchers are questioning if it is that useful..
We may [[visualize the features|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=13m30s]] in the feature maps by visualizing the matrices of parameters.
''MaxPooling'' coarse grains by chosing the maximum value in a certain patch of a few pixels. Nearby pixels are likely to be similar, and it is useful to distinguish between the same pattern been seen several times by the filter convolving around it, or several distinct repetitions of the pattern. Maxpool tries to solve for the former fake repetition..
!!!__Sentence ConvNets__
[[Vid|https://www.youtube.com/watch?v=bEUX_56Lojc&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=10#t=44m55s]]
Sentence DynConvNet
Document models (Misha Denil)
[[Natural language processing]]
[[MatConvNet: CNNs for MATLAB|http://www.vlfeat.org/matconvnet/]]
!!![[explanation vid|https://www.youtube.com/watch?v=7Wq-QmMT4gM]]
http://eyewiki.aao.org/Corneal_Biomechanics
//more fully: cerebral cortex//
The outter layer of the [[Cerebrum]], which contains most of the cell bodies (soma) of the [[Neuron]]s in it.
It is where most [[Neural circuit]]s associated with //higher order// [[cognitive|Cognitive science]] reside. See [[Neuroscience]].
!!!__Types of cortex__
The cortex can be divided into:
* The isocortex, or ''neocortex'', the newer [[evolutionarily|Evolution]]. The white matter is inside, and the gray matter outside. It is traditionally divided into six layers. When we say cortex, we will refer to this, in general.
* The allocortex. [[White matter]] is outside; [[Gray matter]] is inside. Three layers. Older evolutionarily. Contains paleocortex, hippothalamus, and the periachicortex (see [[here|http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780198523246.001.0001/acprof-9780198523246-chapter-9]]).
[img width=400 [https://s3.amazonaws.com/classconnection/313/flashcards/1517313/png/screen_shot_2016-03-21_at_100142_am-153997B77D873CD1908.png]]
!!__Cortical anatomy__
see [[here|http://biology.stackexchange.com/questions/29759/is-the-six-layer-cortex-model-of-the-mammalian-cortex-still-the-most-accepted-mo]]
[img width=500 [http://chronopause.com/i293.photobucket.com/albums/mm55/mikedarwin1967/Feline-62a.png]]
[[another image|http://i.stack.imgur.com/Y262W.jpg]]
-- [[another image|http://66.media.tumblr.com/tumblr_m82jct8sDd1rr61aao1_500.jpg]]
!!__Cortical function (information processing)__
Each cortical region applies operations to different types of data and produces different types of results according to the afferent and efferent connections of the region [Braitenberg, 1977].
The study of the foundamtental computations that are applied through out the cortex is known as [[Corticonics]].
!!__Connections with other brain regions ([[Connectomics]])__
The physiological evidence that properties of neurons tend to be organized in radial columns also contributed to the concept that the intracortical mesh of axonal and dendritic branches is used only for local processing of information, not for transmission across the cortex. Therefore information is mostly transmitted, over long distances, through [[White matter]].
There are many statistical properties regarding where the afferents (carrying towards) and efferent (receiving from) nerve endings in the cortex lie, depending on the type of [[White matter]] connection. Also different cortical regions map are connected to different zones.
-------------------
!!__Probability of synaptic contatct between neurons in the cortex__
One of the principal reasons to evaluate the probability of such contact is to compare the evaluated (theoretical) probability and the experimental find-ings. Such comparisons can reveal the existence of rules that govern the connectivity between neurons.
probability of contact between two neurons can be assessed when measurements of the extent of axonal branching for the presynaptic cell and dendritic branching for the postsynaptic cells are available.
__Uniform distribution__
The basic equation for calculating the probability of contact is
obtained by assuming that the presynaptic cell distributes its synapses
uniformly within a given volume and by assuming that all the neurons
within that volume have the same likelihood of receiving those synapses.
$$pr=n/N$$, where $$n$$ is the number of neurons it makes contact with within the synaptic range, and $$N$$ is the total number of neurons within that range.
,,The equations derived thus far present a rather poor approximation of
the real situation in the cortex, because they ignore two important fac-
tors: The synapses generated by an axon usually are not limited to
neurons whose cell bodies are within the axonal range, because neurons
located at the fringe of the axonal range usually have dendrites that
extend into the axonal range and may also receive synapses. Further-
more, the density of the synapses within the axonal range need not be
uniform.,,
__Corrections due to extent of dentritic tree__
__Non-uniform distribution__
----------------------
!!__[[Neuroanatomy]] of the cortex__
[[Neuronal staining method]]s are traditinally used to study the microanatomy of neurons.
!!__Embryogenesis of the cortex__
Embryogenesis of the central nervous system: neural plate-> neural tube.
First, the lateral ventricles precursors, whose walls expand into the white matter and cortex. Simultaneously the thalamus mattures. Then neuroblasts migrate to cortex and specialize. First pyramidal neurons, then stellar neurons. As they arrive these grow their axons and dendrites.
"This chapter has shown that many features of the cortex are results of the processes that lead to its formation. Yet it is impossible to discern which features are merely by-products of these rules, and for which features nature "went out of its way" to assure their generation. Is the radial arrangement of neurons in the mature cortex merely a by-product of their guidance into the cortical plate by the radial glial fibers? There are no clear answers in these matters, but we should remain open to all the possibilities. " ~ Corticonics, Abel, 1994.
!!__Quantitiative data__
* Density of neurons in cortex: about 40000/mm^^3^^. About 2mm thickness.
* Most are pyramidal. 85% are excitatory (pyramidal or spiny stellar), 15% inhibitory (smooth stellar).
* There is considerable variation within cortical regions, and species.
* About $$8\times 10^8$$ synapses/mm^^3^^. About half of the synapses from local cortical neurons, and the other half from farther away cortical neurons through white matter.
The study of the foundamtental computations that are applied through out the cortex
Classification of cortical areas according to structural and functional differences cannot in itself bring about an understanding of the common operations con-ducted by the cortex and the manner in which they are carried out. Corticonics is the study of these common processes and their underlying neural mechanisms.
See [[Cortex]]
!!__Models__
See [[Neuronal network]]
* [[Hopfield network]]
* [[Spiking neural network]]s
Cosine similarity (a.k.a. Salton's cosine) is a measure of structural similarity of two nodes in a network. It counts the number of common neighbours of nodes i and j (given by $$n_{ij} = \sum_k A_{ik}A_{kj}$$) and divide by the geometric mean of the degrees of i and k:
$$\sigma_{ij}= \frac{n_{ij}}{\sqrt{k_i k_j}}$$
where $$\sigma_{ij}$$ is the cosine similarity. The formula is the same as the cosine of the angle between the column of node i and row of node j considered as vectors, hence the name.
https://en.wikipedia.org/wiki/Cosmography
universal chart
Due to shared electrons that are attracted to both nuclei (or sometimes a few nuclei, in molecules). These are the most common bonds in molecules (see [[Molecular physics]]). They are short-ranged and highly directional (anistropic). They are $$\sim 30\text{ to }100 k_B T$$ at room $$T$$.
http://www.bbc.co.uk/education/guides/z94xsbk/revision
!!__Covalently bonded [[compounds|Chemical compound]]__
* [[Simple covalent molecules|http://www.bbc.co.uk/education/guides/z94xsbk/revision/3]]
* [[Giant covalent structure]]s
[img[dna_covalent_structure.png]]
[img[dna_backbone_structure.png]]
[[Structure of DNA (vid)|https://www.youtube.com/watch?v=ecch4eFW9eI]]
In [[RNA]], there is [[Uracil]] instead of Thymine.
Chain of [[Nucleotide]]s. Similar structure for all [[Nucleic acid]]s
See for instance:
[[Textile art tools]]
Creating new maths is often done by generalizing old maths to new places. See [[Generalized function]], or how the reals generalized the fractions, etc.
[[How does it feel like to invent maths?|https://www.youtube.com/watch?v=XFDM1ip5HdU]]
See book by Cardy, and others..
See [[Renormalization group]] for a main idea in critical phenomena. Also see lectures by Balakrishnan on noneq statphys and Kardar on statphys of fields.
See [[Critical phenomena in percolation]]
--------------------
[[Acoustic Emission and Critical Phenomena: From Structural Mechanics to Geophysics|https://books.google.co.uk/books?id=en7MBQAAQBAJ&pg=PA13&lpg=PA13&dq=applications+of+critical+phenomena&source=bl&ots=8iEAC61fTx&sig=gqe0VLLjTe4j3aQKQTLcDmtn3Zs&hl=en&sa=X&ved=0ahUKEwjpxqbDr8DMAhUsDMAKHYRtDuA4FBDoAQgiMAI#v=onepage&q=applications%20of%20critical%20phenomena&f=false]]
[[Energy Emissions from Critical Phenomena and Applications to Structural Health Monitoring|http://porto.polito.it/2499841/]]
[[Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization|https://books.google.co.uk/books?id=uetHAAAAQBAJ&pg=PA440&lpg=PA440&dq=applications+of+critical+phenomena&source=bl&ots=-irVjlddPo&sig=kDrJFZe9gr2nFjFptcL9dbR6TMs&hl=en&sa=X&ved=0ahUKEwjP9PKisMDMAhWoI8AKHTpGBRU4HhDoAQhHMAY#v=onepage&q=applications%20of%20critical%20phenomena&f=false]]
[[Conformal Invariance and Applications to Statistical Mechanics|http://www.worldscientific.com/worldscibooks/10.1142/0608]]
[[Nonequilibrium Critical Phenomena and Phase Transitions into Absorbing States|http://xxx.lanl.gov/pdf/cond-mat/0001070v2]] See [[Non-equilibrium statistical physics]] [[Directed percolation]]
[[UNIVERSAL SCALING BEHAVIOR OF NON-EQUILIBRIUM PHASE TRANSITIONS|http://www.worldscientific.com/doi/abs/10.1142/S0217979204027748]]
[[Are Damage Spreading Transitions Generically in the Universality Class of Directed Percolation?|http://download.springer.com/static/pdf/307/art%253A10.1007%252FBF02179381.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2FBF02179381&token2=exp=1466365946~acl=%2Fstatic%2Fpdf%2F307%2Fart%25253A10.1007%25252FBF02179381.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252FBF02179381*~hmac=ee729eae5dbfc44008b44d744ae03fe0939d59d8b46280ad26f2dc88b2ace63f]]
__Conformal field theory__
[[Conformal Field Theory and Critical Phenomena|http://www.mit.edu/~juven/talk_slides/CFT_and_statmech.pdf]]
[[Conformal Field Theory and Statistical Mechanics|http://arxiv.org/abs/0807.3472]]
[[Critical phenomena]], [[Dynamical systems on networks]], [[Percolation]], [[Random graph]]
[[Critical phenomena in complex networks|https://arxiv.org/pdf/0705.0010.pdf]]
[[Critical phenomena]] in [[Percolation]] occurs at the critical value of the occupation probability corresponding to the [[Percolation phase transition]], which separates the percolating and the non-percolating phases.
!!!__Critical phenomena__
Percolation models at the critical point show several interesting critical phenomena:
* ''Symmetries''
** Scaling invariance.
** Conformal invariance. This has lead to modelling them (as in many other examples of [[Critical phenomena]]) in the continuum limit, as a [[Conformal field theory]].
* __Fractal structure of the critical percolation clusters__. Scaling invariance leads to the self-similarity characteristic of [[Fractal]]s, and indeed the clusters have fractal geometry. Even for $$p\neq p_c$$, the clusters are fractal at length scales $$l\ll\xi$$, the correlation length, and non-fractal (Euclidean) at larger lengthscales. An argument using the scaling hypothesis, and the number of nodes (mass) of clusters, shows that the fractal dimension of the clusters is also universal, as it is related to other universal critical exponents (see pages 13-14 in Saberi's review). There are other fractals dimension that one can define, like the one for the minimum length path between points, or those for perimeter, backbone, dangling ends, and red sites (or bonds).
!!!__Scaling hypotheses__
There are a number of scaling hypotheses for several quantities for percolation near criticality (see [[Renormalization group]] for origin of scaling hypotheses).
!!!__Upper critical dimension__
$$d_c$$. It is believed that when $$d \geq d_c$$ , the percolation process behaves roughly in the same manner as percolation on an infinite regular tree and their critical exponents take on the corresponding values given by mean-field theory
!!!__[[Real-space renormalization group]]__
[[Renormalization Group Theory - Percolation|https://www.youtube.com/watch?v=ihymiZ4zhug]]. In particular, see [[here|https://www.youtube.com/watch?v=ihymiZ4zhug#t=5m41.5s]].
[[A real-space renormalization group for site and bond percolation|http://iopscience.iop.org/article/10.1088/0022-3719/10/8/002/meta]]
See also [[here|http://www.compadre.org/STP/document/ServeFile.cfm?ID=8470&DocID=931&DocFID=2713&Attachment=1]].
[[Scaling theory of percolation clusters|http://www.sciencedirect.com/science/article/pii/0370157379900607]]
In information theory, the cross entropy between two probability distributions p and q over the same underlying set of events measures the average number of bits needed to identify an event drawn from the set, if a coding scheme is used that is optimized for an "unnatural" probability distribution q, rather than the "true" distribution p.
$$H(p, q) = \text{E}_p[-\log q] = H(p) + D_{\mathrm{KL}}(p \| q),\!$$
https://www.wikiwand.com/en/Cross_entropy
Cross entropy is used in [[Machine learning]], as a [[Loss function]]
Test the model on data you haven't used for training.
min-max, average
[ext[https://www.cs.cmu.edu/~schneide/tut5/node42.html]]
Wikipedia has good explanations: [ext[https://en.wikipedia.org/wiki/Cross-validation_(statistics)]]
!!__Hold-out cross-validation__
[[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=41m30s]] -- [[here|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16]]
#Randomly split training set S into two subsets, the training subset S,,train,,, (70%) and the cross-validation subset S,,CV,, (30%).
#Train the model on the training set, and test it on S,,CV,,
#Pick the model (set of [[Hyperparameter]]s) with smallest error on S,,CV,,
To search for best configuration of hyperparameters acoording to the validation error, there are several methods. Some popular ones are:
* [[Grid search|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=4m10s]], try all possible configurations from chosen trial values.
* [[Random search|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=6m05s]]
Sometimes, once a model complexity (and other [[Hyperparameter]]s) are picked, the model is trained on the whole data set.
[[Optimizing the number of epochs|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=9m05s]] See [[Overfitting and underfitting]]
!!!__''Test set''__
To predict the generalization error (see [[Learning theory]]) of the chosen hyperparameters that are best, we can't just look at their result at S,,CV,,, as that set has been by the algorithm to choose the final answer. As a result, the error on S,,CV,, is a biased estimator of generalization error. To have an unbiased estimator, we need a test set, that is only used once the learning algorithm has finished completely. See [[video|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=8m40s]]
!!__k-fold cross-validation__
[[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=44m49s]]
# Split data into k equal pieces. Common k=10.
# For i from 1 to k:
:: Hold-out the ith piece for testing, and use the other k-1 pieces for training.
:3. Average errors from the k iterations
More computationally expensive
!!__Leave-one-out cross-validation__
k-fold CV, for whem k={number of training examples}, so for each iteration, you leave one out.
Even more computationally expensive, but more accurate estimate of generalization error. Only done when the data is very scarce.
---------------------
//Some thoughts// when I misunderstood train/validation/test learning.
What I describe here is some sort of hyperlearning where we have two steps, where we learn two sets of hyperparameters, and use two different validation sets (which I call below validation, and test, mistakenly...)
When we have trained the data using a method as hold-out CV, and with some fixed learning [[Hyperparameter]]s. If we want to learn the hyperparameters, we can do this whole training procedure with several values of the hyperparameter.
However, to choose the hyperparameters that are best, we can't just look at their result at S,,CV,,, as that set has been by the algorithm to choose the final answer. As a result, the error on S,,CV,, is a biased estimator of generalization error (see [[Learning theory]]). To have an unbiased estimator, we need a test set, that is only used once the learning algorithm has finished completely. We can compare the results on the test set to choose the best set of hyperparameters. Note, that once we have done that, the test error is no longer an unbiased estimate of generalization error, as we have used it to output our very final answer; i.e. our final answer depended on it!! We'd need a hypertest set
"While the rabbit's brain can't be revived yet, either, the researchers' success suggests all neural components responsible for forming one's personal identity -- including memory and personality -- can be preserved. "
http://www.natureworldnews.com/articles/19877/20160211/cryogenics-entire-rabbit-brain-successfully-frozen-revived-first-time.htm
''Culture'' (/ˈkʌltʃər/) is, in the words of E.B. Tylor, "that complex whole which includes knowledge, belief, art, morals, law, custom and any other capabilities and habits acquired by man as a member of society."
https://en.wikipedia.org/wiki/Culture
[[Portal:Contents/Culture and the arts|https://en.wikipedia.org/wiki/Portal:Contents/Culture_and_the_arts]]
[[Analysis of flag designs|http://flagstories.co/]]
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=43m]]
The drive to [[Discover]]
[[video|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=27m06s]] -- discretization scales poorly to high dimensional state spaces.
See Elements of Statistical learning
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<pre>
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span.border {
border: 1px solid white;
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[[Color picker|https://developer.mozilla.org/en-US/docs/Web/CSS/CSS_Colors/Color_picker_tool]]
''Opacity of background''
<input id="opacityInput" type="range">
<br>
<span>Opacity: </span><span id="opacityDisplay">50</span>
<iframe style="display:none;" srcdoc='<script>var a = window.parent.document.getElementById("opacityDisplay"), b = window.parent.document.getElementById("opacityInput"), c=window.parent.document.getElementsByClassName("tc-page-container-wrapper")[0];b.addEventListener("input", function() {a.parentElement.removeChild(a);a =document.createElement("span"); a.innerHTML = b.value; b.parentElement.appendChild(a); console.log(a.innerHtml);c.style.background = "rgba(0, 0, 0, "+(b.valueAsNumber/100).toString()+")";});</script>'></iframe>
//aka nitrale//
[[Organic compound]] composed of a [[Hydrocarbon]] bound to the [[Cyano]] group
A [[Functional group]] $$-C \equiv N$$
[img[https://i.ytimg.com/vi/UU4nEOYisCs/maxresdefault.jpg]]
[img[https://cdn3.vox-cdn.com/thumbor/sD_6OsRVaccHRuMqW5oYgHmoWFc=/800x0/filters:no_upscale()/cdn0.vox-cdn.com/uploads/chorus_asset/file/6274065/Apr_01__2016_09_25.0.gif]]
[[Google Keep|https://keep.google.com/]]
[[http://guillefix.me]]
[[Polymath quest|https://guillermovalleperez.wordpress.com/about/]] $$has$$ `Inner Universe` [extension of #cyberself]
Social media
Backup data. Mind data.
[[Overleaf|https://www.overleaf.com/dash]]
See DB\Cosmos, etc.... Dropbox..
https://photos.google.com/
[[Science and Art]]
-------------------
//Records from bioself//
* Born: 30th July 1994, in Cadiz, from //[[parents|Parents]]// Marusela and Carlos. [[Perigree]]. Sister, 9 years older. Alex. See contacts, + //memories// at //Home//
* At the age of 3, we moved to [[El Puerto de Santa Maria]]
*
----------------
Just as a general reminder, if you haven't watched some of these documentaries, I really recommend them:
* Cosmos, by Carl Sagan
* The Ascent of Man, by Jacob Brownoski
* Connections, by James Burke
* The Mechanical Universe ... and Beyond
* Civilization, by Kenneth Clark.
These (together with Feynman, and GITS) have shaped my philosophy and knowledge very much. One dream of mine is to make something that approaches these in terms of ability to inspire and teach. The world should be fuller of such thoughtful inspiration.
Natural [[Open set]]s forming a [[basis|Filter base]] a [[Product topology]]
,,[[Definition|https://www.youtube.com/watch?v=dUofthrSolQ#t=6m0s]]. This is not right I think, he is defining //open cylinders// which form a subbase (and he's not even defining all open cylinders). See [[Product topology]] for more.,,
--------------
https://www.wikiwand.com/en/Cylinder_set
The visualization of vibration of some [[material|Bulk matter]] by its effect on some mobile medium, like thin coating of particles, paste or liquid.
A typical set up uses ''Chladni plate''s and particles of salt, sand, rice, etc, as seen [[in this video|https://www.youtube.com/watch?v=wvJAgrUBF4w]]
-------------------
https://www.wikiwand.com/en/Cymatics
https://www.wikiwand.com/en/Cytoskeleton
https://en.wikipedia.org/wiki/D%27Alembert%27s_principle
See also [[D'Alembert's principle in overdamped dynamics]]
[img[http://i.imgur.com/w4oAijW.png]]
See also [[D'Alembert's principle]]
A [[graphics and visualization web library|Graphics and visualization web libraries]]
[[D3.js tutorial - 6 - Groups and axes|https://www.youtube.com/watch?v=SYuFy1j8SGs&list=PL6il2r9i3BqH9PmbOf5wA5E1wOG3FT22p&index=6]]
The world is full of information, much more than can be captured in this ~TiddlyWiki and its [[Cosmography]] section, and elsewhere..
There are many people who have made great efforts to make a lot of information readily available in an organized fashion (__data__), and also to make sense of it (__knowledge__), for example by visualizing it.
[[United Nations Statistics Division|http://unstats.un.org/unsd/pubs/]]
[[Gapminder|http://www.gapminder.org/]] Hans Rosling website
!!![[Places & places - Mapping science|http://scimaps.org/home.html]]
http://gdeltproject.org/
https://twitter.com/explorables
http://bionumbers.hms.harvard.edu/
http://populate.tools/
-------------
Main portal for all of Wikipedia content: https://en.wikipedia.org/wiki/Portal:Contents
!!!A nice categorization: [[Wiki Category:Fundamental categories|https://en.wikipedia.org/wiki/Category:Fundamental_categories]]
[[Wiki Portal:Contents/Portals|https://en.wikipedia.org/wiki/Portal:Contents/Portals]]
[[Portal:Contents/Categories|https://en.wikipedia.org/wiki/Portal:Contents/Categories]]
https://en.wikipedia.org/wiki/Category:Indexes_of_topics
https://en.wikipedia.org/wiki/User:West.andrew.g/Popular_pages
http://wikitop.alwaysdata.net/wikitop_en_portal.html
[[Wiki Portal:Contents/Reference|https://en.wikipedia.org/wiki/Portal:Contents/Reference]]
[[Portal:Featured portals|https://en.wikipedia.org/wiki/Portal:Featured_portals]]
Dictionaries, for instance: https://en.wiktionary.org/wiki/Wiktionary:Main_Page
[[https://en.wikipedia.org/wiki/Category:Main_topic_classifications]]
[[https://en.wikipedia.org/wiki/Special:AllPages]]
http://nptel.ac.in/course.php?disciplineId=111
---------
[[Knowledge organizing|Knowledge management]]
TW, https://github.com/ether/etherpad-lite, http://kune.cc/
-------
Collections of technical books: https://www.safaribooksonline.com/learn/
Libgen, sci-hub.io, bookzz . org
https://www.reddit.com/r/Scholar/comments/3bs1rm/meta_the_libgenscihub_thread_howtos_updates_and/
------------------------
hmm http://aaaaarg.fail/collection/list
http://corp.yewno.com/
http://luke.deentaylor.com/wikipedia/
AI
https://aigents.com/
See [[Information theory]]
Data compression refers to the problem of finding a [[code|Coding theory]] that makes the average length of an encoded message as short as possible. This is sometimes called "source coding" because the most compressed code depends on the properties of the [[Information source]] producing the message.
https://en.wikipedia.org/wiki/Data_compression
!!Data compression theory
__Lossless compression__
[[Source coding theorem]]
__Lossy compression__
[[Rate compression theory]]
__Why does data compression work?__
Because real-world data very often has [[Order]] (i.e. structure), and is thus compressible. One measure for such order is [[Randomness deficit]], and one explanation for it is that Nature is algorithmic, i.e. the data we observe often is a result of some (relatively simple) [[algorithm|Algorithms]].
,,[[Compression - Computerphile|https://www.youtube.com/watch?annotation_id=annotation_4140410753&feature=iv&src_vid=goOa3DGezUA&v=Lto-ajuqW3w]] [[Entropy in Compression - Computerphile|https://www.youtube.com/watch?v=M5c_RFKVkko]],,
!![[Data compression codes]]
--------
//Related//
[[Algorithmics on compressed objects]]
[[Compressed sensing]]
Codes used for [[Data compression]]
!!!__Lossless coding__
__Symbol codes__
[[Huffman coding]]
__Stream codes__
[[Lempel-Ziv algorithms]]
[[Markov chain compression]]
[[Burrows-Wheeler transform]]
[[Arithmetic compression]]
[[Dynamic statistical encoding]]
[[Grammar-based compression]]
[[Finite State Entropy - A new breed of entropy coder|http://fastcompression.blogspot.co.uk/2013/12/finite-state-entropy-new-breed-of.html]]
Good blog on data compression advancements: http://fastcompression.blogspot.co.uk/
[[(IC 1.2) Applications of Compression codes|https://www.youtube.com/watch?v=fXGTMrw2MA0&index=2&list=PLE125425EC837021F]]
!!!__Lossy coding__
//aka data processing inequality//
[[Data processing theorem|https://www.youtube.com/watch?v=tIt4pJAbCDQ&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=13#t=9m30s]]
An important special case:
For any function, $$f$$, and [[Random variable]]s $$x$$, $$y$$,
|$$I(x,y) \geq I(x, f(y))$$|
where $$I$$ is the [[Mutual information]]
A function $$f$$ for which the above inequality becomes an equality is a [[Sufficient statistic]]
http://crunchbase.linkurio.us/demo/
https://www.crunchbase.com/#/home/index
__Machine learning data sets__
[[IMAGENET|http://www.image-net.org/]] semantically categorized image database
[[WordNet|http://wordnet.princeton.edu/]]. Semantically structured and linked word database
http://imgur.com/a/K4RWn
[[Data & Knowledge]]
-- [[Data analysis]]
-- [[Machine learning]]
-- [[Statistics]]
-- [[Data visualization]]
https://www.continuum.io/why-anaconda
[[https://pythonprogramming.net/data-analysis-tutorials/]]
http://www.science.smith.edu/~amcnamara/FoSP.html
[[Tree (data structure)]]
[[Heap (data structure)]]
[[Tuple]]
Stack
Queue
List
Graph
[[Persistent data structure]]
See Lynda.com videos.
See [[Information theory]] for more details. See also [[Communication theory]]
''Data transmission'' refers to the transfer of information from one entity to another, by means of a [[Data transmission system]] .
!!__Data transmission system__
See more here: [[Data transmission system]]
__Properties of data transmission systems__
* ''Code'' used by the transmitter. See [[Coding theory]].
* [[Entropy rate]] of the transmitter (considered as an [[Information source]]).
* [[Channel capacity]] of the [[Communication channel]]. This quantity gives a limit to the rate at which information can be reliably sent through the channel, as established by the [[Channel coding theorem]].
__Types of communication channel__
* [[Finite state channel]]
__Types of transmitter/receivers__
These are mostly specified by the code they use. In data transmission systems, these are mostly [[Error-correcting code]]s.
!!__Data transmission theory__
The main desired properties of a data transmission system, and thus the main subjects of study are:
* ''Reliability''. How unlikely is the receiver to interpret message wrongly?
* ''Speed''. What is the maximum rate at which information can be sent over the channel? Measured in (bits decoded)/(channel bits sent)
Thus the main problem of study is: for a particular communication channel, find code so that data transmission rate is as high as possible, while receiver receives the information with negligible probability of error.
This is sometimes called "channel coding" because the most reliable code depends on the properties of the channel. This is done by finding codewords (sequences of input values) such that their images are as disjoint as possible. This is equivalent to sphere packing in high dimensions.
The main result in data transmission theory is the [[Channel coding theorem]], which gives a __fundamental limit__ to the data transmission rate that can be achieved by a code, while keeping error rates negligible. This limit turns out to be the [[Channel capacity]].
!!__Data transmission system engineering__
The goals stated above for a data transmission system are achieved in two main ways:
* Design and construction of optimal hardware (see [[Telecommunication engineering|Telecommunication]])
* Design and use of optimal codes. This is one of the main goals of [[Coding theory]], and in particular of [[Error-correcting code]]s.
----------------------
See [[http://pfister.ee.duke.edu/thesis/chap1.pdf]], and other chapters.
[[Entropy in Compression - Computerphile|https://www.youtube.com/watch?v=M5c_RFKVkko]]
A data transmission system is the middle part of a [[Communication system]], composed of:
* Transmitter, or sender.
* [[Communication channel]]
* Receiver
https://en.wikipedia.org/wiki/Data_type
In computer science and computer [[Programming]], a data type or simply type is a classification identifying one of various types of data, such as real, integer or Boolean, that determines the possible values for that type; the operations that can be done on values of that type; the meaning of the data; and the way values of that type can be stored.
http://programmers.stackexchange.com/questions/291950/are-data-type-declarators-like-int-and-char-stored-in-ram-when-a-c-program-e
[[ Weak And Strong Typing|http://c2.com/cgi/wiki?WeakAndStrongTyping]]
static vs dynamic typing: http://stackoverflow.com/questions/1517582/what-is-the-difference-between-statically-typed-and-dynamically-typed-languages (see third answer).
How do compiled dynamically typed languages work? Do they store type data (unlike it says [[here|http://programmers.stackexchange.com/questions/291950/are-data-type-declarators-like-int-and-char-stored-in-ram-when-a-c-program-e]]?)
https://en.wikipedia.org/wiki/Type_inference
http://stackoverflow.com/questions/1393883/why-is-dynamic-typing-so-often-associated-with-interpreted-languages
!!__Data types__
Integer
Float
[[String|String (Computer science)]]
__Other classes__
[[Immutable type]]
http://www.visualcomplexity.com/vc/
See also [[Graphics and visualization web libraries]]
See [[Visualization tools]]
[[https://pythonprogramming.net/matplotlib-intro-tutorial/]]
[[Self-organizing map|https://en.wikipedia.org/wiki/Self-organizing_map]] related to [[Artificial neural network]]s
http://www.science.smith.edu/~amcnamara/FoSP.html
Database theory
Relational databases
See Lynda.com videos.
<small>also known as Price's model.</small> The ''de Solla Price's model'' is a model used to explore the effect of preferential attachment in the formation of a network on the structure of the network. See [[Models of network formation]] for more information.
Proposed in the study of citation networks. These have properties:
*New papers <small>almost</small> only cite existing ones. The network is thus <small>approx.</small> a [[directed acyclic graph|Directed acyclic craph]].
* Node: paper. Edge: citation of a paper to an existing paper.
The model defines the average number of papers cited by a new paper (i.e. the average out-degree) to be $$c$$ (and the distribution around $$c$$ to be sufficiently well-behaved, for instance, the variance should be finite).
The main assumption of the model is that the probability of each new edge created whew we add a new node only depends on the degree of that node (on the //in-degree// to be precise, i.e. the number of citations it has). In particular it assumes an //affine preferential attachment//:
$$q_i=\frac{k_i+a}{\sum_i(k_i+a)}=\frac{k_i+a}{N(a+c)}$$
where$$k_i \equiv k_{i}^{\text{in}}$$ is the in-degree, and we have made use that for directed networks, $$\langle k_{i}^{\text{in}} \rangle =\langle k_i^{\text{out}}\rangle=c$$ . Finally, $$a>0$$ is introduced so that nodes can get edges even if they don't have any in-degree yet (otherwise they will always stay like that, and the model wouldn't really be realistic).
Note that a new paper can cite an existing paper more than one times in this model, but the frequency at which these double-edges occur is low, and in the limit $$N\rightarrow \infty$$ they are subdominant.
$$q_i$$ is the probability that a new edge is connected to node $$i$$. On average $$c$$ edges are added (and the probability over number of edges, whose average is $$c$$, is independent of the probability $$q_i$$), therefore the expected number of edges added to node $$i$$ is $$cq_i$$. Even though the probabilities for each node getting an edge are not independent, the expected number of edges added over a set of nodes, is the sum of the $$cq_i$$ (see [[Probability theory]] Note 1). In particular, the expected number of edges added to all nodes with in-degree $$k$$, $$Np_k(N)$$ of them (where $$p_k(N)$$ is the degree distribution at the when there are $$N$$ nodes in the network (note that this changes, as we are adding nodes in the process of formation)) is:
$$Np_k(N) c \frac{k+a}{N(a+c)}= c \frac{k+a}{a+c} p_k(N)$$
We can now write a __master equation__, which for $$k\geq 1$$ is:
$$(N+1)p_k (N+1) =Np_k(N)+\frac{c(a+k-1)}{a+c}p_{k-1}(N)-\frac{c(a+k)}{a+c}p_k(N)$$
or in words:
$$\# \text{ with degree k when total is } N+1=\# \text{ with degree k when total was N}$$
$$+\#\text{ with degree k-1 when total was N that gained one edge}$$
$$-\#\text{ with degree k when total was N that gained one edge}$$
The equation for $$k=0$$ is a bit different:
$$(N+1)p_0 (N+1) =Np_0(N)+1-\frac{ca}{a+c}p_0(N)$$
where there are no nodes with degree $$-1$$, and there is an extra $$+1$$ due to the node we just added.
Now, taking the limit $$N \rightarrow \infty$$, and using the shorthand $$p_k :=p_k(\infty)$$, the $$k\geq 1$$ eq. becomes:
$$p_k =\frac{c(a+k-1)}{a+c}p_{k-1}-\frac{c(a+k)}{a+c}p_k=\frac{c}{a+c}((a+k-1)p_{k-1}-c(a+k)p_k)$$
$$p_0=+1-\frac{ca}{a+c}p_0$$
where the terms proportional to $$N$$ have cancelled out.
We can then solve these to get a recursion relation for $$p_k$$ with initial condition $$p_0$$ from the second equation. The solution can then be expressed in terms of Euler Beta functions, which in the asymptotic limit of large $$k$$, give a power-law decay with power:
$$\alpha=2+\frac{a}{c}$$.
Thus, many scholars believe that this simple model may describe the fundamental mechanism by which power laws are obtained in many real-world networks.
__Computer simulation of de Solla Price's model__
See section 14.1.1 of Newman's book.
Straighforward simulation of model is slow. Alternative was proposed by Krapivsky and Redner which follows the following rule
<<<
With probability $$c/(c+a)$$ choose a vertex in strict proportion to in-degree. Otherwise choose a vertex uniformly at random from the set of all vertices.
<<<
The trick to do the part of choosing a vertex in proportion to in-degree is done by choosing an edge (stored in a list) with uniform probability and then choosing the vertex it points to, so that the probability of choosing is exactly proportional to how many edges point to it, i.e. its in-degree $$k_{i}$$.
The mathematical study of strategies for optimal decision-making between options involving different risks or expectations of gain or loss depending on the outcome.
https://www.wikiwand.com/en/Decision_theory
See also [[Machine learning]], and [[Reinforcement learning]]
!!![[Decision tree]]
----------------
!!![[Two types of problems in sequential decision-making|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h16m25s]]:
* [[Reinforcement learning]]
* Planning
https://www.wikiwand.com/en/Decision_tree
!!__Classification tree__
[[video|https://www.youtube.com/watch?v=p17C9q2M00Q&list=PLD0F06AA0D2E8FFBA&index=7]]
[[Growing a classification tree (CART)|https://www.youtube.com/watch?v=S51plSJBC2g&index=10&list=PLD0F06AA0D2E8FFBA]], using greedy algo.
Following the CART approach (Breiman et al)
!!__Regression tree (CART)__
[[video|https://www.youtube.com/watch?v=zvUOpbgtW3c&list=PLD0F06AA0D2E8FFBA&index=7#t=499.919073]]
[[Growing a regression tree (CART)|https://www.youtube.com/watch?v=_RxqyvRK0Rw&list=PLD0F06AA0D2E8FFBA&index=9]] via a [[Greedy algorithm]], which later could be prunned
---------------
[[Generalizations for trees (CART)|https://www.youtube.com/watch?v=UMtBWQ2m04g&index=10&list=PLD0F06AA0D2E8FFBA#t=28.466837]]
[[Categorical input|https://www.youtube.com/watch?v=UMtBWQ2m04g&index=10&list=PLD0F06AA0D2E8FFBA#t=8m30s]]
[[Bootstrap aggregation]]
!!![[Random forest]]
//aka Chemical decomposition, analysis or breakdown//
A [[Chemical reaction]], involving the separation of a chemical compound into elements or simpler compounds.
[[Digital art]] based on [[Deep learning]]
Machine-learning extrapolation of art: http://extrapolated-art.com/
https://deepart.io/
[[Random Pics Combined Using Neural Network|http://imgur.com/a/ue6ap]]
Neural doodle
Colorize B&W pictures: http://demos.algorithmia.com/colorize-photos/
!!__Neural Style: A Neural Algorithm of Artistic Style__
[[A Neural Algorithm of Artistic Style|http://arxiv.org/pdf/1508.06576v1.pdf]]
[[Pikazo - neural style video tech demo|https://www.youtube.com/watch?v=FzvTLEB_3KY]] [[Artistic style transfer for videos|https://www.youtube.com/watch?v=Khuj4ASldmU]]
[[Analogy-Driven 3D Style Transfer|https://www.youtube.com/watch?v=h0xF6R5MpyA]]
[[reddit discussion|https://www.reddit.com/r/MachineLearning/comments/3imx1m/a_neural_algorithm_of_artistic_style/]]
Code: [[code|http://gitxiv.com/posts/jG46ukGod8R7Rdtud/a-neural-algorithm-of-artistic-style]]
*[[neural-style|https://github.com/jcjohnson/neural-style]] for torch
* [["Neural Art" in TensorFlow|https://github.com/woodrush/neural-art-tf]]
[[Two Minute Papers - Deep Neural Network Learns Van Gogh's Art|https://www.youtube.com/watch?v=-R9bJGNHltQ&list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2&index=6]]
Neural-style applied to videos too.
!!!__Deep dream__
[[Inceptionism: Going Deeper into Neural Networks|https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html]]
-- [[Going Deeper with Convolutions |http://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf]]
[[How ANYONE can create Deep Style images|https://www.reddit.com/r/deepdream/comments/3jwl76/how_anyone_can_create_deep_style_images/]]
---------------------
[[Style Transfer for Headshot Portraits|https://people.csail.mit.edu/yichangshih/portrait_web/]]
[[ Deep Convolutional Inverse Graphics Network|http://arxiv.org/abs/1503.03167]]
[[Image based relighting using neural networks|http://dl.acm.org/citation.cfm?id=2766899]]
https://magenta.tensorflow.org/welcome-to-magenta
!!__[[Deep learning]] for [[Music]]__
[[Composing Music With Recurrent Neural Networks|http://www.hexahedria.com/2015/08/03/composing-music-with-recurrent-neural-networks/]]
https://www.technologyreview.com/s/603137/deep-learning-machine-listens-to-bach-then-writes-its-own-music-in-the-same-style/
!!!__Music [[recommendation|Recommender system]]__
Long tail ([[Power laws]]) is particularly long in music
* Collaborative filtering. Problem with new users. Performs the best.
* Content-based. No popularity or user usage data required.
Diversity is valuable in long term.
Deep content-based music recommendation.
Model with [[latent factor|Latent variable]]s. Model from raw audio signal to latent space. Map users to latent space, and see songs nearby, to recommend. Use ConvNet to implement the map from audio signal to latent space.
Weighted [[Matrix factorization]] (uses confidence matrix) to find the latent factors (see [[Compressed sensing] video]). Basically implements: probability of having listened to song by vector product between user and song latent representations.
[[Mean squared error]] is [[rotationally invariant|Rotational invariance]], and factorizations are too!
Latent factors split into those predictable from audio, and predictable from metadata.
Datasets: million song dataset, echonest.
Still much poorer performance than collaborative filtering, in general.
Can visualize, using T distributed stochastic neighbour embeding, can identify some genres.
In machine learning, a deep belief network (DBN) is a [[generative|Generative learning]] [[Graphical model]], or alternatively a type of deep neural network, composed of multiple layers of [[Latent variable]]s ("hidden units"), with connections between the layers but not between units within each layer.
It can be seen as a composition of [[Restricted Boltzmann machine]]s
Deep learning [[Machine learning]] in a modular way using ''layers'', like in [[Torch|Torch (Deep learning framework)]]. [[Artificial neural network]]s, with many layers..
[[Two+ Minute Papers - How Does Deep Learning Work?|https://www.youtube.com/watch?v=He4t7Zekob0&index=5&list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2]]
--
[[The computer that mastered Go|https://www.youtube.com/watch?v=g-dKXOlsf98]]
[[Oxford course (with video)|https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/]] on lecture 12
[[matlab|https://uk.mathworks.com/discovery/deep-learning.html]]
The idea is also that layers are //recursive//, i.e. layers can be made up of layers.
[[future|https://www.youtube.com/watch?v=x1kf4Zojtb0#t=43m05]]
Concepts as programs; programs as networks
[[Probabilistic programming]], [[Program induction]]
trainning models based on demonstration
Multi-agents, and [[Communication]]
Generating programs is not that different from generating [[explanations|Explainable artificial intelligence]]
----------------
!!Deep learning methods
!!!__Neural networks for spatially structured data__
[[Convolutional neural network]]
[[Multi-scale networks|Deep multi-scale video prediction beyond mean square error|http://arxiv.org/abs/1511.05440]] and [[an application|http://yann.lecun.com/exdb/publis/pdf/sermanet-ijcnn-11.pdf]].
[[Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers|http://arxiv.org/abs/1202.2160]]
http://www.clement.farabet.net/research.html#parsing
[[Computer vision]]
[[Residual neural network]]
!!!__Neural networks for [[sequential|Sequence]] data__
[[Recurrent neural network]]
!!!__[[Transfer learning]]__
good for generalizing models, ''transfer learning'', ''multi-task learning''. Good when don't have much supervision data.
!!!__[[Neural networks with memory]]__
''Memory'' is good for recognizing time sequence data. See [[Long short-term memory]].
!!!__[[Attention in machine learning]]__
!!!__[[Integrating symbols into deep learning]]__
* [[Neural Turing machine]]
* [[Neural programmer-interpreter]]
* [[Deep symbolic reinforcement learning]]
!!!__[[Deep reinforcement learning]]__
//more...//
[[Structured learning|https://www.youtube.com/watch?v=x1kf4Zojtb0#t=20m]] -- Learning to learn and compositionality with deep recurrent neural networks
------------------
!!!Some techniques for deep learning
__[[Layers for deep learning]]__
!![[New advances in deep learning]]
[[Dropout]]. [[usefulness of dropout|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=50m20s]]
[[Batch normalization]]
[[Predicting Parameters in Deep Learning|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/DeFreitas-NIPS2013_5025.pdf]] The intuition motivating the techniques in this paper is the well known observation that the first layer features of a neural network trained on natural image patches tend to be globally smooth with local edge features, similar to local Gabor features [6, 13]. I.e. they are seizing the [[Simplicity]] often found in real-world structures. Given this structure, representing the value of each pixel in the feature separately is redundant, since it is highly likely that the value of a pixel will be equal to a weighted average of its neighbours.
The core of the technique is based on representing the weight matrix as a low rank product of two smaller matrices.
-----------
!![[Deep learning theory]]
!!Deep learning applications
[[Deep art]]
[[Applications of AI]]
--------
__[[Hardware for deep learning]]__
__[[Software for deep learning]]__
---------
__[[People in deep learning]]__
[[History of deep learning]]
-----------
__Books and reources__
[[Deep learning in neural networks: An overview|http://www.sciencedirect.com/science/article/pii/S0893608014002135]]
https://deepmind.com/publications.html
http://www.deeplearningbook.org/
http://carpedm20.github.io/
--------------
[[Numenta|http://numenta.com/]], different approach to mainstream. See also, http://artificial-intuition.com/ http://monicasmind.com/
[[DeepMind|https://deepmind.com/]]
[[Research at Google|http://research.google.com/pubs/MachineIntelligence.html]]
[[MIRI|https://intelligence.org/?gclid=COb2isn69csCFbYW0wodf8gKnA]]
http://vital.ai/
http://pharma.ai/
https://wit.ai/
https://courses.nucl.ai/
https://api.ai/
https://nice.ai/
http://projectoxford.ai
https://www.captionbot.ai/
Find more here https://domainpunch.com/tlds/topm.php
[img[https://d3ansictanv2wj.cloudfront.net/mi-landscape-2.0-r9_update-f2048bd678f522066e294ba8233b6615.jpg]]
[img[https://pbs.twimg.com/media/CwqxUY7UcAAu7OC.jpg:large]]
<big><i class="fa fa-smile-o" aria-hidden="true"></i>[[Play with a neural network on your browser - Tensorflow Playground!!|http://playground.tensorflow.org/]]<i class="fa fa-smile-o" aria-hidden="true"></i></big>
[img[http://playground.tensorflow.org/preview.png]]
!!![[ConvNetJS|http://cs.stanford.edu/people/karpathy/convnetjs/]]
[[ConvnetJS demo: toy 2d classification with 2-layer neural network|http://cs.stanford.edu/people/karpathy/convnetjs/demo/classify2d.html]]
[[Neural network theory]] -- [[Learning theory]]
//Better understanding the shortcomings and potential of deep learning may suggest ways of improving it, both to make it more capable and to make it more robust [2].//
[[Integrating symbols into deep learning]]
[[A Theoretical Framework for Deep Learning Networks|https://www.youtube.com/watch?v=YVjvRvvVn4w]]
----------------------
!!__Deep learning, [[Spin glass]]es, [[Protein folding]], [[Energy landscape]]s__
<div style="display:inline-block; width:350px;">[img width=350 [deep_learning_random_energy_model_glass_transition.png]]</div>
<div style="display:inline-block;width:300px;">
<p>[[why deep learning works -- spin glasses, protein folding, etc.|https://charlesmartin14.wordpress.com/2015/03/25/why-does-deep-learning-work/]]</p>
<big>-->[[Why Deep Learning Works|https://www.youtube.com/watch?v=kIbKHIPbxiU]]</big>
-- [[Improving RBMs with physical chemistry|https://charlesmartin14.wordpress.com/2016/10/21/improving-rbms-with-physical-chemistry/]]
-- [ext[Energy landscapes of deep networks|http://vision.ucla.edu/~pratikac/pub/chaudhari.cs269.16.pdf]]
</div>
|The primary argument about the funnel is that these learning systems are strongly correlated, and therefore not readily treated by mean field theory. Specifically, the classical idea was that strongly correlated random models lie in a different universality class. So they behave completely differently than a spin glass , and this gives rise to the convexity .|
See discussion in comments [[here|https://charlesmartin14.wordpress.com/2016/09/24/mmds-video-presentation/]] and [[here|https://charlesmartin14.wordpress.com/2016/10/21/improving-rbms-with-physical-chemistry/]]. [[Comments on why deep learning works: perspectives from theoretical chemistry]]
[[The Loss Surfaces of Multilayer Networks |http://www.jmlr.org/proceedings/papers/v38/choromanska15.pdf]]
See [[Statistical mechanics of neural networks]]
!!!-->[[Theoretical neuroscience and deep learning theory|http://videolectures.net/deeplearning2016_ganguli_theoretical_neuroscience/]]
---------------------
!!__[[Renormalization group]] and [[Deep learning]]__
[[Why Deep Learning Works II: the Renormalization Group|https://charlesmartin14.wordpress.com/2015/04/01/why-deep-learning-works-ii-the-renormalization-group/]]
[[An exact mapping between the Variational Renormalization Group and Deep Learning|http://arxiv.org/abs/1410.3831]]
[[WHY DOES UNSUPERVISED DEEP LEARNING WORK?- A PERSPECTIVE FROM GROUP THEORY|http://arxiv.org/pdf/1412.6621v3.pdf]]
[[Supervised Learning with Quantum-Inspired Tensor Networks|https://arxiv.org/abs/1605.05775]]
[[Deep learning and the renormalization group|http://128.84.21.199/pdf/1301.3124v1.pdf]]
<small>See also comments on [[Why does deep and cheap learning work so well?]]</small>
-----------------------
!!__Simplicity and deep learning__
See also [[Simplicity and learning]]
!!![[Why does deep and cheap learning work so well?]]
----------------------------
!!__[[Neuroscience]] and deep learning__
!!!-->[[Theoretical neuroscience and deep learning theory|http://videolectures.net/deeplearning2016_ganguli_theoretical_neuroscience/]]
---------------------------
//More resources//
[[Representational Power of Restricted Boltzmann Machines and Deep Belief Networks|http://www.mitpressjournals.org/doi/abs/10.1162/neco.2008.04-07-510]]
-- [[Deep Belief Networks Are Compact Universal Approximators|http://www.mitpressjournals.org/doi/abs/10.1162/neco.2010.08-09-1081]]
-- [ext[Scaling learning algorithms towards AI|http://www.iro.umontreal.ca/~lisa/bib/pub_subject/language/pointeurs/bengio+lecun-chapter2007.pdf]]
-- [[Hierarchical model of natural images and the origin of scale invariance|http://www.pnas.org/content/110/8/3071.abstract]]
-- [[Why does Deep Learning work?|https://charlesmartin14.wordpress.com/2015/03/25/why-does-deep-learning-work/]], [[Spin glass]], [[Why Deep Learning Works III: a preview|https://charlesmartin14.wordpress.com/2016/06/20/why-deep-learning-works-iii-a-preview/#comments]]
-- [[Lagrangian Relaxation for MAP Estimation in Graphical Models|https://arxiv.org/abs/0710.0013]]
-- [[Models of object recognition|http://www.nature.com/neuro/journal/v3/n11s/full/nn1100_1199.html]]
-- [[Deep neural networks are easily fooled: High confidence predictions for unrecognizable images|http://www.evolvingai.org/fooling]] [[video|https://www.youtube.com/watch?v=M2IebCN9Ht4]]
-- https://scholar.google.co.uk/citations?user=iqDZ9WYAAAAJ
-- [[Accelerated Learning in Layered Neural Networks|http://www.complex-systems.com/pdf/02-6-1.pdf]]
-- [[Yann LeCun: "Deep Learning, Graphical Models, Energy-Based Models, Structured Prediction, Pt. 1"|https://www.youtube.com/watch?v=oOB4evKlEmQ#t=35m]]
-- [[Why does Deep Learning work? - A perspective from Group Theory|https://arxiv.org/abs/1412.6621]]
[[AlphaGo]]
[[Intro vid|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw]]
Combine [[deep|Deep learning]] [[neural networks|Artificial neural network]] with [[Reinforcement learning]]
[[Deep symbolic reinforcement learning]] combines it with symbolic reasoning.
http://gizmodo.com/there-are-some-seriously-gnarly-creatures-at-the-bottom-1775158529?utm_campaign=socialflow_io9_facebook&utm_source=io9_facebook&utm_medium=socialflow
A gorgonocephalid basket stars, a relative of the brittle star.
[img[https://i.kinja-img.com/gawker-media/image/upload/m0hzn03csmgoxwbi0slf.jpg]]
A hydromedusa jellyfish, spotted near “Enigma Seamount” at a depth of 3,700 meters.
[img[https://i.kinja-img.com/gawker-media/image/upload/c8rihlbdzjwppc5wphpl.jpg]]
Applying [[Symbolic deep learning|Integrating symbols into deep learning]] to [[Deep reinforcement learning]]
[[Towards Deep Symbolic Reinforcement Learning|https://arxiv.org/pdf/1609.05518.pdf]]
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
[ext[Degree ceremony 2015-2016|https://www.ox.ac.uk/sites/files/oxford/field/field_document/Degree Ceremony brochure..Degree ceremony_web_15-16.pdf]] [[more|https://www.ox.ac.uk/students/graduation/ceremonies?wssl=1]]
<table class="sitstablegrid">
<caption>Your Degree Ceremony</caption>
<tbody><tr><td>Student Name</td><td>Guillermo Jorge Valle Perez</td></tr>
<tr><td>Award Programme</td><td>MMathPhys Mathematical & Theoretical Physics</td></tr>
<tr><td>College</td><td>Magdalen College</td></tr>
<tr><td>Date of Ceremony</td><td>Friday 30 September 2016 </td></tr>
<tr><td>Time</td><td> 2:30 pm </td></tr>
<tr><td>Number of Guaranteed Ceremony Tickets</td><td>3</td></tr>
<tr><td>Hold Status</td><td><i>None</i></td></tr>
<tr><td>Ceremony Status</td><td>You have chosen to attend the above ceremony</td></tr>
<tr><td colspan="2"><i>You have agreed to the <a href="http://www.ox.ac.uk/students/graduation/ceremonies/" target="blank">University Terms and Conditions regarding Degree Ceremonies</a>.</i></td></tr>
</tbody></table>
The ''degree'', $$k_i$$, of a vertex, $$i$$, is the number of edges connected to the vertex. For an undirected graph with $$n$$ vertices, it is related to the adjacency matrix by:
|$$k_i=\sum_{j=1}^n A_{ij}$$|
Also the __total number of edges__ $$m$$ is:
$$2m=\sum_{j=1}^n k_j=\sum_{ij}A_{ij}$$
as each edge has two ends ('stubs').
The __mean degree__, $$c$$ is then:
$$c=\frac{2m}{n}$$.
"""
<small>Aside: a node with a "high" degree is sometimes called a 'hub'.</small>
<small>A network where all nodes have same degree is called 'regular'.</small>
"""
The number of edges in a complete (i.e. with max # of edges) simple graph can be found by counting the number of edges, where each edge represents a choice of a pair of vertices where the order doesn't matter. The number of such choices is $$\binom{n}{2}$$.
The <big>__density__</big> (or connectance), $$\rho$$, is the fraction of these that are actually present:
$$\rho=\frac{m}{\binom{n}{2}}=\frac{2m}{n(n-1)}=\frac{c}{n-1}\approx\frac{c}{n}$$
the last approx. is for $$n$$ large.
A network is __sparse__ if $$\rho \rightarrow 0$$ as $$n \rightarrow \infty$$. It is __dense__ otherwise. These definitions make sense mathematically when one has a model for an ensemble of graphs, that can be defined for any $$n$$. For an empirical network, one has to situations:
*One has empirical data for the network at different values of $$n$$, and so the behaviour as $$n$$ increased can be deduced.
*One has to find an appropriate model to define an ensemble of random graphs for different values of $$n$$, that somehow captures the type of network of the empirical one.
!!!Directed networks
For directed networks one has two types of degree:
__in-degree__, the number of ingoing edges (sum of a row in adj. matrix)
__out-degree__, the number of outgoing edges (sum of columns in adj. matrix).
Now the __total number of edges__ $$m$$ is:
$$m=\sum_{j=1}^n k_j^{\text{in}}=\sum_{j=1}^n k_j^{\text{out}}=\sum_{ij}A_{ij}$$
as each edge has one ingoing end and one outgoing end. Clearly then the mean degrees are equal: $$c_{\text{in}}=c_{\text{out}}\equiv c=\frac{m}{n}$$.
In a __weighted network__, one defines the __strength__ of a node as the weighted degree:
$$s_i=\sum_{j=1}^{n}w_{ij}$$,
where $$w_{ij}$$ is the weight matrix.
A [[Condensation reaction]], where the small molecule produced when joining the moieties that combine form a [[Water]] molecule.
The opposite is [[Hydrolysis]]
https://en.wikipedia.org/wiki/Depletion_force
//What is the shortest description of an object?// The size of this description, is the ''descriptional complexity''. This general notion may also be called "structural complexity".
See also [[Complexity theory]], for other notions of complexity.
!!__[[Kolmogorov complexity]]__
[ext[Lecture notes on descriptional complexity
and randomness|http://www.cs.bu.edu/~gacs/papers/ait-notes.pdf]]
Based on the minimum size of a program (interpreted by a [[Turing machine]]) that produces (//describes//) the object.
!!__[[Complexity measures based on data compression]]__
!!__[[Automata-based descriptional complexity]]__
!!__[[Entropy-based complexity measures]]__
!!__[[Permutation complexity]]__
!!__[[Network complexity]]__
--------------
YB videos: https://www.youtube.com/watch?v=HWsa_hZ7F3I
Design is the rightful child of [[Art]] and [[Engineering]]
[[Center for Livable Media|http://livable.media/]]
[[Is anything worth maximizing? On metrics, society, and selves|http://nxhx.org/maximizing/]]
https://medium.com/fwd-thoughts/the-future-is-without-apps-ddf43ec52aab#.a0q670oen
[[Bret Victor homepage|http://worrydream.com/]]
__Generative design__
[[Towards an interactive, generative, design system: Integrating a ‘build and evolve’ approach with machine learning for complex freeform design.|http://www.fisheyefocus.com/docs/papers/EvoInteraction2007.pdf]]
--------------
https://medium.com/digital-experience-design/how-to-apply-a-design-thinking-hcd-ux-or-any-creative-process-from-scratch-b8786efbf812#.htbf7kfcs
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=25m]]
See [[Optimization]]
[[Design optimization|http://uk.mathworks.com/discovery/design-optimization.html]] is the process of finding the best design parameters that satisfy project requirements.
[[Multidisciplinary design optimization|https://en.wikipedia.org/wiki/Multidisciplinary_design_optimization]]
__Topology optimization__
[[ToPy|https://github.com/williamhunter/topy]] Topology optimisation (or optimization, if you prefer) using Python. [[More|http://www.topopt.dtu.dk/?q=node/881]] [[Nice example of application|https://www.youtube.com/watch?v=2_K8h5Zqfn8]]
http://web.solidthinking.com/additive_manufacturing_design?_ga=1.67375703.779924460.1456431417
http://www.cloudtopopt.com/
https://en.wikipedia.org/wiki/Topology_optimization
__3D printing design optimization__
[[Autodesk Within|http://www.autodesk.com/products/within/overview]] https://en.wikipedia.org/wiki/Generative_Design
[[Materialize|https://i.materialise.com/info/file-optimization-guide]]
[[Microsoft netfabb|https://modelrepair.azurewebsites.net/]]
See [[Self-diffusiophoresis]]
Small objects can swim by generating around them fields or gradients which in turn induce fluid motion past their surface by phoretic surface effects.
We quantify for arbitrary swimmer shapes and surface patterns, how efficient swimming requires both surface ‘activity’ to generate the fields, and surface ‘phoretic mobility’ (the quantity that determines the direction of the velocity, relative to the driving gradient, which depends on specifics of the solute/surface interactions). We show in particular that
:(i) swimming requires symmetry breaking in either or both of the patterns of ‘activity’ and ‘mobility,’ and
:(ii) for a given geometrical shape and surface pattern, the swimming velocity is size-independent. In addition, for given available surface properties, our calculation framework provides a guide for optimizing the design of swimmers.
[[Designing phoretic micro- and nano-swimmers (pdf)|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/njp07_design-swimmer.pdf]]
|See [[Self-diffusiophoresis]], and [[Diffusiophoresis]] for theory|
!!Designs of self-diffusiophoretic particles
!!!__Spherical__
__Janus particle__
__Saturn particle__
__Three-slice design__
[img[http://i.imgur.com/vw3Qp4f.png]]
!!!__Thin rod__
Use slender body theory
---------
Is there a way for particles to actively "fight" their rotational diffusion and make them go straight for longer, without an external field?
[[video|https://www.youtube.com/embed/PvkJYUP9NVY]]
See [[Loop analysis]]
Derived using [[Topological trace formula]]
[img[http://i.imgur.com/EPjKXGk.png]]
gives topological polynomial, which is just the characteristic polynomial of the transition matrix
[[Topological zeta function]]
-------------------
Examples from fsts. See notebook and [[here|Simplicity bias in finite-state transducers]]
__FST 10__
[[http://www.wolframalpha.com/input/?i=1-3z%5E2%3D0]]
Can analyze forward or backward
__FST 21__
[[1-2*z+z^2-2*z^3+2*z^4=0|http://www.wolframalpha.com/input/?i=1-2*z%2Bz%5E2-2*z%5E3%2B2*z%5E4%3D0]]
[[(2^(-log_2(0.59)*40)/2^40)*10^6|http://www.wolframalpha.com/input/?i=(2%5E(-log_2(0.59)*40)%2F2%5E40)*10%5E6]]
[[-log_2(0.59)|http://www.wolframalpha.com/input/?i=-log_2(0.59)]]
[[2.7*log_2 (100)/(37-14)|http://www.wolframalpha.com/input/?i=2.7*log_2+(100)%2F(37-14)]]
[[Equilibrium OST_05_Evidence|https://www.youtube.com/watch?v=CpAJeXvVm3E]]. Equilibrium movie.
[[https://www.wikiwand.com/en/Determination]]
[[Deterministic finite automaton|https://en.wikipedia.org/wiki/Deterministic_finite_automaton]] (DFA) is a deterministic [[Finite-state machine]]. See ''[[Deterministic machine|https://www.youtube.com/watch?v=jb_H7SGOyyI&index=2&list=PL601FC994BDD963E4#t=4m24.7s]]''
[[Reversing deterministic machines|https://www.youtube.com/watch?v=ceNNyyELhu4&list=PL601FC994BDD963E4&index=6]]
[[Complete and incomplete deterministic finite automata|https://en.wikipedia.org/wiki/Deterministic_finite_automaton#Complete_and_incomplete_deterministic_finite_automata]]
See also [[Random deterministic automata]]
Every organism comes from a single [[Cell]]
//Development// refers to the process by which cells divide, specialize and organize in time and space, into organs and tissue, making the organism. An important constraint is preserving germline.
!!__Developmental processes__
* Proliferation --[[Cell division]]
* [[Cell specialization]]
* Interaction -- [[Cell signalling]]
* Cell movement -- [[Morphogenesis]]
Cell proliferation, specialization, itnteraction, movement. Achieved by a [[Gene expression]] cascade in space!
[[Model organism]]s
A funnction that is a linear combination of [[Convex function]]s where the weights can be negative. Equivalently, it is a linear combination of convex and concave functions.
If it is a function to be [[optimized|Optimization]], there is an efficient method, where we approximate the concave functions in the linear combination by a hyperplane (linear approx, using [[Taylor expansion]]). We then have a convex function overall, which we can optimize using [[Convex optimization]] methods. We then re-approximate the concave functions linearly in the newly found point, and repeat!
See [[General relativity]] and book by Caroll
!!__Coordinate transformation__
__Transformation of ''covariant and contravariant components''__
[img[http://i.imgur.com/INGknH3.png]]
--------------
[[(10) Tensor Calculus, Multilinear Algebra and Differential Geometry (General Relativity Prerequisites)|https://www.youtube.com/playlist?list=PLtku678e9yj725K6hjLqKhJ854nTWWR5e]]
[[http://math.stackexchange.com/questions/140126/is-there-any-good-resource-for-video-lectures-of-differential-geometry]]
http://www.msri.org/summer_schools/351
http://www.msri.org/programs/286
[[https://www.youtube.com/watch?v=R1oU5m69ILk&list=PLIljB45xT85DWUiFYYGqJVtfnkUFWkKtP]]
https://www.youtube.com/watch?v=JCor1st0d2E&list=PLBY4G2o7DhF38OEvEImfR2heX7Szmq5Gs
https://en.wikipedia.org/wiki/Penrose_graphical_notation
[[https://www.maths.tcd.ie/~fionn/dg/dg.pdf]]
An [[Osmotic force|Osmotic forces]] caused by concentration gradients.
[[Diffusio-Osmosis of Electrolyte Solutions in Microscale and Nanoscale|https://www.researchgate.net/profile/Huan_Keh/publication/289739597_Diffusio-Osmosis_of_Electrolyte_Solutions_in_Microscale_and_Nanoscale/links/56949e1108ae820ff072ce1c.pdf]]
[[Osmosis]] is a particular case, in which the diffusio-osmosis drives liquid across a semi-impermeable membrane.
See [[Diffusiophoresis]]
See [[Stochastic process]]
[img[https://upload.wikimedia.org/wikipedia/commons/4/4d/DiffusionMicroMacro.gif]]
See [[Brownian motion]] for derivations. Also [[Fick's laws of diffusion|https://en.wikipedia.org/wiki/Fick%27s_laws_of_diffusion]]
!!Diffusion equation
$$\frac{\partial P}{\partial t} = D \nabla^2 P$$,
where D is the diffusion coefficient, which when derived from a [[random walk|Brownian motion]] is
$$D = \frac{\langle \Delta x^2 \rangle}{2dt}$$
where $$d$$ is the dimension of space. The $$2$$ comes from the fact that walker can jump in any of two directions, per dimension. $$\langle \Delta x^2 \rangle$$ and $$t$$ represent the expected distance squared, and the time step in the random walk, respectively. See for example [[these notes|http://physics-server.uoregon.edu/~raghu/TeachingFiles/Winter08Phys352/Notes_Diffusion.pdf]], for derivation.
See also a [[simple kinetic derivation of diffusion coefficient (in the context of solid state diffusion), see page 7|http://www.uio.no/studier/emner/matnat/kjemi/KJM5120/v05/undervisningsmateriale/KJM5120-Ch5-Diffusion.pdf]]
Also see [[Alex's notes|https://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/A1/]] on kinetic theory.
[[Solutions to diffusion equation|http://www.youtube.com/watch?v=dUt2bbGREgQ&index=2&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=51m02s]], using <b>Fourier transform</b>, and using Green functions. Can also derive from [[Fokker-Planck equation]]
[[Solutions to diffusion equation|https://www.youtube.com/watch?v=m5RuNNvJdjM&index=6&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=0m30s]] for //free//, //absorbing//, and //reflecting// boundary conditions.
https://en.wikipedia.org/wiki/Diffusion
!!Applications
!!!__Smoluchowski capture rate__
Diffusion limit on rate of reaction between molecules.
Begin with an spherical particle, and assume stationary solution, $$\partial_t P = 0$$. Set the concentration to be fixed to $$C_\infty$$ far from particle, and $$0$$ on its surface, as we assume they are assumed to be captured.
To do general case where both particles are moving, one should use relative and center of mass coordinates (#trythis). The answer is:
$$k_{ab}=4\pi(D_a+D_b)(R_a+R_b)$$,
where $$a$$ and $$b$$ are the particle species, $$D$$ and $$R$$ are the diffusion constants and radii.
!!!__[[Phoretic mechanisms of colloids]]__
* [[Diffusiophoresis]]
[[Diffusion-Limited Aggregation, a Kinetic Critical Phenomenon|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.47.1400]]
[[DLA - Diffusion Limited Aggregation|http://paulbourke.net/fractals/dla/]]
[img width=400 [http://paulbourke.net/fractals/dla/dla3.gif]]
[[Review|http://www.thp.uni-koeln.de/krug/teaching-Dateien/SS2012/Sander2000.pdf]]
[[Good notes|http://web.mit.edu/bazant/www/teach/18.325/projects/blanchette.ps]] about ''surface growth'' in general.
Similar models:
Eden growth model
random animals
Diffusiophoresis is the process by which particles move trough a chemical concentration gradient, due to an attractive or repulsive interaction between the particle and the chemical compound. It is a kind of [[phoretic mechanism of colloids|Phoretic mechanisms of colloids]].
[img width=300 [http://www.sas.upenn.edu/~tidema/Images/diffusiophoresis.png]]
Essentially, the surface of the particle, due to [[Intermolecular forces]] (or other entropic forces), can be attracted, or repelled to the solvent molecules. If there is a gradient in the concentration of these, they can exert a net force on the particle causing it to gain a certain velocity (and the particle will exert a force on the fluid, causing it to slip over its surface).
In [[Self-diffusiophoresis]] (a kind of [[self-propulsion|Self-propelled particle]]), the particle itself produces the compound it interacts with.
http://pubs.acs.org/doi/abs/10.1021/la00050a035
https://en.wikipedia.org/wiki/Diffusiophoresis
http://link.springer.com/referenceworkentry/10.1007/978-3-642-27758-0_328-5#page-1
[[Particle motion driven by solute gradients with application to autonomous motion: continuum and colloidal perspectives|http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=7961332&fileId=s0022112010004404]]
__Theory__
When the thickness of the interfacial layer is thin compared to the object,
the resulting flow is most conveniently described by an effective slip velocity of the liquid past
the solid at position $$r_s$$ on the surface, proportional to the local gradient of $$c$$. See a simple derivation below (from [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]).
[img width=600 [http://i.imgur.com/X0Uyz4D.png]]
,,(I think they are missing a d on the bottom in (9)),,
See derivation in the black notebook. Note that at the end you need to use the trick of [[changing order of integration|http://mathinsight.org/double_integral_change_order_integration_examples]], as done in [[Derjaguin's original paper|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/derjaguin1947.pdf]] (on page 7).
The general tensorial equation is:
$$\mathbf{v}_s(\mathbf{r}_s) = \mu (\mathbf{r}_s)(\mathbf{I}-\mathbf{n}\mathbf{n}) \cdot \nabla c (\mathbf{r}_s)$$
$$\mu (\mathbf{r}_s)$$ is the local ''surface phoretic mobility'', which depends on the particular interaction between the particle and the solven molecules (through the integral in (9)).
Then using the //reciprocal theorem// (of [[Low Reynolds number]] flows), one can find the velocity of the particle, knowing the slip velocity of the solvent around it. In a given basis, the drift velocity of the colloid, $$\mathbf{V}$$, is then:
$$\mathbf{V}\cdot \hat{\mathbf{f}}_i = - \int \int_S d \mathbf{r}_s \mathbf{n} \cdot \mathbf{\sigma}_i \cdot \mathbf{v}_i$$
where $$\mathbf{\sigma}_i$$
is the hydrodynamic stress tensor at the surface $$S$$ of an object of the same shape dragged by an applied unit force, $$\hat{\mathbf{f}}_i = \hat{\mathbf{e}}_i$$
exactly equal to $$\hat{\mathbf{e}}_i$$, in the absence of slip.
In the case of spherical particles, the drift velocity turns out to be simply:
$$\mathbf{V} = -\frac{1}{4\pi} \int \mathbf{v}_s d\Omega$$
For uniform motility, $$\mathbf{v}_s = \mu \nabla_{||}c$$, and so
$$\mathbf{V} = -\mu \nabla_{||}c$$
This simple equation for the velocity is appropriate for the [[Active colloid]]s used in studying the [[Self-assembly of active colloids]].
<mark> See [[Hydrodynamic slip]]</mark>
<mark>In the derivation of equation (9) they assumed that $$\Phi$$ doesn't depend on $$x$$. Is this the reason why a particle without a gradient in $$c$$, even if it has a gradient in its phoretic mobility is predicted to have $$0$$ drift velocity? Would you get a non-zero velocity if you took dependence on $$x$$ of $$\Phi$$ into account?</mark>
See [[Diffusiophoresis caused by gradients of strongly adsorbing solutes|http://pubs.acs.org/doi/abs/10.1021/la00050a035]]
[[Giant Amplification of Interfacially Driven Transport by Hydrodynamic Slip: Diffusio-Osmosis and Beyond|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.96.186102]]
[[Diffusiophoresis: Migration of Colloidal Particles in Gradients of Solute Concentration|http://www.tandfonline.com/doi/abs/10.1080/03602548408068407]]
[[Kinetic Phenomena in the boundary layers of liquids 1. the capillary osmosis|http://ezproxy-prd.bodleian.ox.ac.uk:2054/science/article/pii/007968169390023O]]
Online photoshop-like image editor http://www.photopea.com/
[[Virtual reality]]
!!__[[Deep art]]__
Glitch art: http://www.glitchet.com/resources
[[Minterm vs Maxterm Solution|http://www.allaboutcircuits.com/textbook/digital/chpt-8/minterm-maxterm-solution/]]
http://www.allaboutcircuits.com/textbook/digital/
https://en.wikipedia.org/wiki/Digital_physics
See [[Cellular automata]]
Konrad Zuse
[[Edward Fredkin|https://en.wikipedia.org/wiki/Edward_Fredkin]]
[[Gerald Jay Sussman|http://groups.csail.mit.edu/mac/users/gjs/]]
These
are materials in which a very small concentration (at most a
few percent) of a magnetic element, often iron or manganese,
is substituted at random locations inside a nonmagnetic metallic
host, such as one of the noble metals (copper, silver, or gold).
At low densities of the magnetic atoms, their resistance, which in
normal metals decreases and eventually flattens as the temperature
is lowered, starts to rise again at a few degrees above absolute zero.
This came to be known as the [[Kondo effect]].
At higher concentrations (already at about 1%), the impurities in dilute magnetic alloys begin interacting, and they were among the first examples of [[Spin glass]]es.
A cell that contains a two copies of each [[Chromosome]], so that its [[Genotype]] has two [[Allele]]s
[[Percolation]] on a directed [[Network|Network science]]. Most of the time, it refers to percolation on a directed lattice where the direction of the edges is constrained to certain directions in the space. This is applied for instance to water percolating down a porous medium, where in this case gravity imposes a preferred direction.
It is in a different universality class than undirected bond percolation. It can be described by an [[stochastic process|Stochastic processes]] similar to models describing [[Epidemics on networks]].
https://en.wikipedia.org/wiki/Directed_percolation
[[http://guava.physics.uiuc.edu/~nigel/courses/563/Essays_2013/PDF/wolin.pdf]]
[[Directed lattices: site-to-bond conversion and its uses for the percolation and dilute polymer transitions|http://link.springer.com/article/10.1007/BF01357518]]
[[Percolation in directed scale-free networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.66.015104]]
[[New universality for spatially disordered cellular automata and directed percolation|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.57.90]]
[[Exhaustive percolation on random networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.74.036113]]
See also [[Dynamical systems on networks]]. It also has relations to sandpile models in the study [[Self-organized criticality]]
[[Directed percolation and Sandpile models - 1 by Deepak Dhar|https://www.youtube.com/watch?v=30WNNl5Fj7s]]
[[New universality for spatially disordered cellular automata and directed percolation|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.57.90]]
[[Directed percolation and Reggeon field theory|http://iopscience.iop.org/article/10.1088/0305-4470/13/12/002/meta]]
[[Equivalence of Cellular Automata to Ising Models and Directed Percolation|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.53.311]] See [[Cellular automata]]
[[Are Damage Spreading Transitions Generically in the Universality Class of Directed Percolation? |http://download.springer.com/static/pdf/307/art%253A10.1007%252FBF02179381.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2FBF02179381&token2=exp=1466080939~acl=%2Fstatic%2Fpdf%2F307%2Fart%25253A10.1007%25252FBF02179381.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252FBF02179381*~hmac=a987e45e8b3c52785be23f41be3ca9e0aed3b57d84b025add86b7fc995829ded]]
<mark>Understand the different kinds of universality classes better (see [[Critical phenomena]])</mark>.
Discrete dynamical systems, a.k.a. ''maps''
See [[Nonlinear map]]
See [[Automata theory]], [[Cellular automata]], [[Boolean network]], [[Dynamical systems on networks]]..
[[Graph dynamical system]]
[img[http://uncomp.uwe.ac.uk/wuensche/EDDfrontback.gif]]
Great software to explore discrete dynamics: [[Discrete Dynamics Lab|http://www.ddlab.com/]] Tools for researching Cellular Automata, Random Boolean Networks, multi-value Discrete Dynamical Networks, and beyond
Discrete dynamical
[[An Introduction to chaotic dynamical systems. Second edition|http://www.nehudlit.ru/books/detail5822.html]] [[Chaos theory]]
[[Workshop on Combinatorics, Number Theory and Dynamical Systems - Artur Avila|https://www.youtube.com/watch?v=QHslHqKUX24]]
[[Abstract algebra]] offers the foundation of discrete mathematics.
[[Mathematics - Discrete Mathematics|https://www.youtube.com/playlist?list=PL85CF9F4A047C7BF7]]
https://www.youtube.com/watch?v=DBugSTeX1zw&list=PLDDGPdw7e6Aj0amDsYInT_8p6xTSTGEi2
[[MIT - Discrete Mathematics|https://www.youtube.com/playlist?list=PL3o9D4Dl2FJ9q0_gtFXPh_H4POI5dK0yG]]
See [[Mathematical logic]], [[Set theory]], etc.
A ''discrete memoryless source'' is an [[Information source]] which is:
* Memoryless. In this context it means that the random variables in the discrete stochastic process making the source are {{i.i.d.}}
* Discrete. In this context it means that the alphabet is countable.
A [[topology|Topological space]] where every subset of a set $$X$$ is open.
See [[Markov chain]]
[img[http://i.imgur.com/SQZC0oW.png]]
!!__Class structure__
Communicating classes. Set of states that can communicate with each other (which constitutes an [[Equivalence relation]]).
-----------------------
A transition matrix where the whole state space is a communicating class
Stopping time, strong Markov property.
Reccurent vs transient states
Let $$C$$ be a communicating class. Then either all states in $$C$$ are transient or all are recurrent.
A type of [[Supervised learning]] where one learns the function $$p(\text{output}|\text{input})$$. See [[notes|http://cs229.stanford.edu/notes/cs229-notes1.pdf]]
!!!__Learning method__
The learning itself is done by [[Maximum likelihood]], where the likelihood is:
$$p(\theta|(x,y))=\frac{p((x,y)|\theta)p(\theta)}{p(x,y)}$$
where $$\theta$$ are the parameters of the theory, $$y$$ are the outputs, and $$x$$ are the input variables. Now our aim is maximizing this likelihood w.r.t $$\theta$$, and as the denominator doesn't depend on $$\theta$$, we can ignore it. We can also assume that $$p(\theta$$, our prior, is uniform. Then, we want to maximize:
$$p((x,y)|\theta) = \prod_{i}p(y^{(i)}|x^{(i)};\theta)p(x^{(i)})$$
where we assumed that all the data points are independent. We have also <span style="color:coral;">assumed that our model only models $$p(y|x)$$, so that $$\theta$$ doesn't appear in $$p(x)$$</span>. This is the <b>main difference with [[Generative supervised learning]]</b>. While maximizing the log likelihood
$$l(\theta) = \log{(p(x,y)|\theta)} = \sum_i \log{p(y^{(i)}|x^{(i)};\theta)} + \sum_i \log{p(x^{(i)})}$$
only the first term depends on $$\theta$$, the second is fixed (and thus ignored in the optimization procedure).
See also [[Generative vs discriminative models]]
https://www.wikiwand.com/en/Discriminative_model
!!__Deterministic discriminative models__
These have all the probability centered around one output, so they are better described as modelling directly $$y(x)$$, the output as a function of the input
__Examples__
* [[Decision tree]]s
** [[Random forest]]
See [[MMathPhys oral presentation]]
~*Different definition of finite-state complexity here: http://web.mit.edu/cocosci/Papers/complex.pdf (though still not the one we need below)
Using [[finite-state complexity|http://arxiv.org/pdf/1008.1667.pdf]] we can define the complexity of a string produced by a finite transducer. It is effectively the length of the smallest program that describes both a transducer (according to some encoding) and the string itself. This definition is not universal as for Turing machines, because of the non-universality of finite transducers.
This is not what I want, because they don't fix the transducer, while a given GPM would fix the transducer. Assuming we can use the same idea as above, if the length of the input is much larger than the length of the transducer, we are effectively inputing random fixed-length strings to a Turing machine (that we know halt hm..), and by Levins coding theorem (applied here to not asymptotic case..) we expect that "strings with many long descriptions to have a short description too". Furthermore, if we assume that the map is many to one, then each strings would have many long descriptions, so each will have a short description. But if there are many such strings, not all of them can have short descriptions. Thus, the only consistent situation is for a few strings with simple descriptions having many long descriptions too, and a many strings with few long descriptions.
This assumed that the finite transducer is simple (defined by the condition above that the input string to the finite state transducer (FST) be much larger than the FST description). If it isn't, the bias argument above still holds I think, but because the transducer is complex, it's outputs will all be complex, with a complexity dominated by the transducer's.
It seems like the Levin's coding theorem holds for strings of all inputs, which means it works for argument above! However, I don't understand it fully, in particular it's derivation, so I'm not too confident on this. See [[this book|https://books.google.co.uk/books?id=LKEmB_GQ53QC&pg=PA283&lpg=PA283&dq=levin+coding+theorem+finite+state&source=bl&ots=4MYNGplLKI&sig=2oKf7zcSUuX9cfq1nGSSdYbKDug&hl=en&sa=X&ved=0ahUKEwjKgoKwh7LLAhUBQBoKHVlWBFoQ6AEISzAF#v=onepage&q=4.3.4%20the%20coding%20theorem&f=false]]
<mark>SEE EMAIL CONVERSATION FOR FOLLOW UP ON THIS. Reasoning above doesn't hold</mark>. Kamal's answer:
<<<
I read the three papers - thanks for those.
Shallit and Wang (2001) was not super interesting, though obviously relevant in the sense that focus on computable complexities.
Calude (2011) is more interesting. The most interesting result being that a kind of Invariance Theorem holds for finite state transducers (which are weak/weakest type of computation, UTMs being the most powerful because they can compute any algorithm). The Invariance theorm in AIT comes from the fact that any UTM can simulate any other UTM, while their Inv Thm for finite state machines does not invoke this property. Assuming prefix free descriptions of the transducers, this implies a kind of coding theorem for finite state transducers. This is nice because finite state transducers do not have the mystical air that UTMs do (uncomputable). I think it is worth citing this Calude article as a comment, but maybe not making too much of a deal about it.
I also looked Guillermo’s link – just a comment on some reasonsing in there (I know it is just notes):
Furthermore, if we assume that the map is many to one, then each strings would have many long descriptions, so each will have a short [shorter] description. But if there are many such strings, not all of them can have short descriptions[true, but they can all have shorter descriptions]. Thus, the only consistent situation is for a few strings with simple descriptions having many long descriptions too, and a many strings with few long descriptions[hence bias in the map].
The reasoning here is a little rushed – if the map is many to one, then all outputs strings have shorter descriptions. But this does not explain why some outputs have short descriptions and some long (which leads to bias). The central thing to explain in bias is why some outputs will have shorter descriptions than others. The statement "strings with many long descriptions to have a short description too"
does not say anything about how long these short descriptions are, whereas the argument presented assumes that these are short enough to be a problem, in the sense of "not all of them can have short descriptions".
As a trivial but illustrative example, consider the many-to-one map from binary string of length 10 to binary strings of length 5. We can easily construct a uniform distribution for this system. According to the argument above, this system should show bias….but it does not (even though the map is simple).
<<<
https://en.wikipedia.org/wiki/Disease
,,//Sometimes disorder is used as a synonym of randomness, in which case, what I describe here is called quenched disorder//.,,
//Disorder//, I think, refers to a particular kind of randomness in a system, in which there may be spatial randomness, but the random variables are fixed, for each instance of the system. This is in contrast to spatio-temporal disorder due to [[Temperature]], as described by [[Statistical physics]].
As means of illustration, if the disorder is in a parameter in the Hamiltonian, for instance in some couplings (as in [[Spin glass]]es), it means that, before analyzing the Hamiltonian, we first determine all the couplings by coin tossing, or what-ever other method we choose; after that, they remain fixed for all time. This process leads to a particular choice, or realization, of the couplings, and thus a particular realization of the Hamiltonian, or the system.
Disorder affects the behaviour if the system is finite, or if the disorder is non-[[Self-averaging]]. A system that has disorder, specially if the disorder affects its behaviour, is referred to as a [[Disordered system]].
__Types of disorder__
There are two types of disorder:
* <b>[[Annealed disorder]]</b>: disorder of a system at thermal equilibrium. This can be physically achieved by cooling the system down sufficiently slowly so that the system is in quasi-equilibrium at all times.
* <b>[[Quenched disorder]]</b>: disorder of a system in which the disordered variable is out of equilibrium. For instance in [[Glass]]es. This can be achieved by cooling sufficiently rapidly, so that a random configuration is //quenched//, and stays so, due to extremely large relaxation times.
* One could also have a combination of the two.
See [[Condensed matter physics]], [[Complex systems]]
A disordered system is a system that has [[Disorder]]. Disorder affects the behaviour of the system if the system is finite, or if the disorder is non-[[Self-averaging]]
[[http://www.sapienza.isc.cnr.it/disordered-systems.html]]
!!!__Disordered system models__
[[Random map]]
[[Random-cluster model]]
[[Spin glass]]
* [[Random energy model]]
[[Boolean network]]
[[Artificial neural network]] -- [[Hopfield network]]
!!!__[[Self-averaging]]__
[[Random matrix theory]]
[[Free Probability, Random Matrices and Disorder – CME 510|https://www.youtube.com/watch?v=68yy33jOkOs]]
[[Fluctuation-dominated Phase Ordering: Order Parameter Scaling By Mustansir Barma|https://www.youtube.com/watch?v=nsx7TAwETZ8]]
A ''dispersion'' is a [[material|Materials science]] comprising more than one phase where at least one of the phases consists of finely divided phase domains, often in the [[colloidal|Colloid]] size range, dispersed throughout a continuous phase.
A __continuous phase__ is a phase not interrupted in space.
A __dispersed phase__ is a phase constituted of particles of any size and of any nature dispersed in a continuous phase of a different composition.
The __dispersion medium__ is the matrix for the dispersed phase. The dispersion medium is the continuous phase of the dispersion.
Source from IUPAC: [[Terminology of polymers and polymerization processes in dispersed systems (IUPAC Recommendations 2011)*|https://espace.library.uq.edu.au/view/UQ:266979/UQ266979_OA.pdf]].
Depending on the size of the particles in the dispersed phase we have:
* [[Solution|Solution (Chemistry)]], for size less than a nanometer.
* [[Colloid]], for size between a nanometer and a micrometer.
* Coarse dispersion, for a size larger than a micrometer.
"Dispersion", without adjective, is often used to refer to the colloidal regime.
!!__Dispersion types__
For phases with particles of colloidal size or larger. For smaller sizes, see [[solution|Solution (Chemistry)]].
|Medium|<|Dispersed medium|
|~|Gas|Liquid|Solid|
|Continuous medium|Gas|None (because all gases are mutually miscible)|Colloidal: Liquid [[aerosol|Aerosol]]|Colloidal: Solid [[areosol|Aerosol]]. Coarse: [[Dust]]|
|~|Liquid|If dipersed phase has enough concentration: [[Foam]]|Colloidal: [[Emulsion]]|Colloidal: [[Suspension]]|
|~|Solid|[[Porous solid|Porous material]] filled with gas. If dipersed phase has enough concentration: solid [[Foam]]|[[Porous solid|Porous material]] filled with liquid, like [[Gels]]|Colloidal: Solid sol, like [[Cranberry glass|https://en.wikipedia.org/wiki/Cranberry_glass]]. Coarse: [[conglomerates|https://en.wikipedia.org/wiki/Conglomerate_(geology)]]|
See [[https://en.wikipedia.org/wiki/Dispersion_(chemistry)]] for examples.
The distance between the [[Position]] of a [[Point]] (often representing an [[Object]]), and a reference position. What this reference position is depends on the context. It may refer to initial position, to some average position, like [[Center of mass]], or to some equilibrium position.
See [[Stochastic processes]]
[[Fluctuation-dissipation theorem|https://en.wikipedia.org/wiki/Fluctuation-dissipation_theorem]]
[[Einstein–Smoluchowski relation]]
''Distillation'' is a process of separating the component substances from a [[Mixture]] [[solution|Solution (Chemistry)]] by selective evaporation and condensation.
http://www.bbc.co.uk/education/guides/zgbqtfr/revision/5
[img[http://a.files.bbci.co.uk/bam/live/content/zkqfcdm/large]]
https://www.wikiwand.com/en/Distillation#
[[Fractional distillation]]
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
See [[Concurrent computing]]
https://pythonprogramming.net/build-supercomputer-raspberry-pi/
!!__Cable rack__
[img[https://s-media-cache-ak0.pinimg.com/236x/80/b3/b5/80b3b5ab46df7ddee444bb907e153d44.jpg]]
[img[http://cdn1.tnwcdn.com/wp-content/blogs.dir/1/files/2016/09/W6RwWT6.jpg]]
[img[https://img.buzzfeed.com/buzzfeed-static/static/2016-01/19/10/enhanced/webdr13/enhanced-buzz-13110-1453218793-5.jpg]]
[img[http://cdn1.tnwcdn.com/wp-content/blogs.dir/1/files/2016/09/PC67Jr4.jpg]]
http://thenextweb.com/insider/2016/09/04/satisfying-pics-cable-management/#gref
https://www.buzzfeed.com/lukebailey/satisfying-cables?bffbuk&utm_term=.rdVlyDlqa#.auVkYVkLG
A quantity of interesting in [[Percolation theory]] is the distribution of sizes for the small clusters in percolation models.
This can be quantified by the total number of clusters of size $$s$$, $$n_s$$. Sometimes one works with $$n_s/N$$ instead, to eliminate the scaling with $$N$$ that would make $$n_s \rightarrow \infty$$ as $$N \rightarrow \infty$$.
One can also work with the __probability that a random node belongs to a cluster of size $$s$$__, which can be easily seen to be $$\pi_s = \frac{s n_s}{N} = \frac{\#\text{ of nodes in clusters of size }s}{\text{total }\#\text{ of nodes}}$$. This is clearly the probability of picking a node inside a cluster of size $$s$$ given a particular network configuration. In the case of [[Percolation on random graphs and networks]], it's also the probability that a random network configuration (following the appropriate probability distribution defining the network ensemble) makes a particular chosen node be in a cluster of size $$s$$. This is because the two operations are statistically independent.
$$\pi_s$$ can be shown to decrease exponentially with s in the subcritical regime, and it decays more slowly in the supercritical regime. (see [[here|file:///home/guillefix/Dropbox/COSMOS/Mathematics/Others/%5BGeoffrey_R._Grimmett%5D_Percolation.djvu]]). At the critical point, the cluster size follows a power law distribution (as do for instance avalanche sizes in the sandpile model at criticality).
//Desoxyribonucleic acid//
See [[DNA nanotechnology]], [[MMathPhys oral presentation]]
[[https://en.wikipedia.org/wiki/DNA]]
!!__Structure of DNA__
!!![[Covalent structure of DNA]]
!!!DNA complexes
[[Base pair]]ing of [[Nucleobase]]s via [[Hydrogen bond]]ing
[[DNA double helix]]
Can model DNA as a ribbon, and can define it's torsion. Boundaries of ribbon are the backbone, and they form the same surface that you get by twisting a normal ribbon.
Can also coarse-grain more, and model it as a curve.
Packing of DNA in a cell. See [[here|https://en.wikipedia.org/wiki/Chromosome#/media/File:Chromatin_Structures.png]]
[[How DNA unties its own knots - Numberphile|https://www.youtube.com/watch?v=UkmQNbvlK8s]], using [[Type II topoisomerase|https://en.wikipedia.org/wiki/Type_II_topoisomerase]] (see more [[here|https://www.youtube.com/watch?v=EYGrElVyHnU]]). Drugs that target type II topoisomerase are used as antibiotics, because this enzyme is necessary for the cell to replicate correctly in bacteria. This is because the fact that DNA is a helix, and it forms a loop in bacteria means that when DNA is unzipped by helicase, the two single strand loops are interlinked. Topoisomerase then cuts and stiches DNA in such a way as to unlink them. See [[DNA replication]]
!!!__Structure of DNA in the [[Cell nucleus]]__
[[Chromatin]]
!!__Processes of DNA__
!!![[DNA replication]]
!!![[Gene expression]]
* [[DNA transcription]]
* [[mRNA Translation]]
[[DNA repair]]
!!__Chemistry of DNA__
https://www.technologyreview.com/s/419590/quantum-entanglement-holds-dna-together-say-physicists/
!!__[[Molecular genetics]]__
[[DNA and Natural Algorithms Group|http://www.dna.caltech.edu/DNAhome.html]]
[[DNA computing: applications and challenges|http://iopscience.iop.org/article/10.1088/0957-4484/17/2/R01/meta;jsessionid=70D87277E1E032DF4E99AE67EF7AC06B.c1.iopscience.cld.iop.org]]
[[DNA COMPUTING AND ITS APPLICATIONS: SURVEY|http://www2.kuma.u-tokai.ac.jp/~shi/el08-014.pdf]]
See [[Unconventional computing]]
[img[dna_double_helix.png]]
Sugar-phosphate backbone is on the outside, bases in the inside. They form [[base pair|Watson-Crick base pair]]s, which form a [[Hydrogen bond]]:
* A -- T
* G -- C
[[The Shape of DNA - Numberphile|https://www.youtube.com/watch?v=AxxnziuL408]]. DNA is a right-handed [[Helix]].
Both strands are right-handed (almost always in biology) (they have to have the same handedness, as can be seen by looking at a cross-section and seeing the cross-sections of the strands, if they were of opposite handedness, they would collide (given the helices have the same radii)). The two strands of DNA also have a direction associated with them (the backbone determines it), and the strands are antiparalel, as seen in animation below
[img width=300 [http://67.media.tumblr.com/7f270f68b777db5c6e82fdb48d447899/tumblr_o9n0tiMWRl1sk2szio2_r1_1280.gif]]
See also [[Chirality in biology]]
[[DNA double helix formation]]
[img[Selection_643.png]]
[img[Selection_644.png]]
It is easy to see that double helix formation decreases entropy, as the two joined strands are contrained to move together. However, the reaction is spontaneous due to the release of [[Heat]], about -250 mJ $$mol^{-1}$$! (see [[Chemical energetics]])
[[Acid-base reaction]]s that remove or donate protons at specific positions on the DNA bases can disrupt the double helix. Therfore, at [[pH]] above 9-10, and below about 5, DNA separates back into its single stranded form.
[[Automated requirements analysis for a molecular watchdog timer|http://dl.acm.org/citation.cfm?id=2643007]]
See [[Nanoengineering]], [[DNA nanomachines]].
[[Rapid chiral assembly of rigid DNA building blocks for molecular nanofabrication|http://www.ncbi.nlm.nih.gov/pubmed/16339440]] ,,Practical components for three-dimensional molecular nanofabrication must be simple to produce, stereopure, rigid, and adaptable. We report a family of DNA tetrahedra, less than 10 nanometers on a side, that can self-assemble in seconds with near-quantitative yield of one diastereomer. They can be connected by programmable DNA linkers. Their triangulated architecture confers structural stability; by compressing a DNA tetrahedron with an atomic force microscope, we have measured the axial compressibility of DNA and observed the buckling of the double helix under high loads.,,
[[Molecular Machinery from DNA: Synthetic Biology from the Bottom up|http://www.cell.com/biophysj/fulltext/S0006-3495(13)01416-1]]
[[DNA nanomachines|http://www.nature.com/nnano/journal/v2/n5/full/nnano.2007.104.html]]
[[Programmable DNA Nanosystem for Molecular Interrogation|http://www.nature.com/articles/srep27413]] ,, an embedded Förster Resonance Energy Transfer (FRET) system, in which one cyanine 3 (cy3) molecule is positioned on the frame and one cyanine 5 (cy5) molecule is on the ring, reports the relative position of the ring under various conditions,,
[[Hybrid, multiplexed, functional DNA nanotechnology for bioanalysis|http://pubs.rsc.org/en/content/articlelanding/2015/an/c5an00861a#!divAbstract]]
!!![[Programmable motion of DNA origami mechanisms|http://www.pnas.org/content/112/3/713]]
[[Reversible Reconfiguration of DNA Origami Nanochambers Monitored by Single-Molecule FRET|http://onlinelibrary.wiley.com/doi/10.1002/anie.201408941/abstract]]
[[Universal computing by DNA origami robots in a living animal|http://www.nature.com/nnano/journal/v9/n5/full/nnano.2014.58.html]] (see also [[DNA computing]]).
[[Controlled Release of Encapsulated Cargo from a DNA Icosahedron using a Chemical Trigger|http://onlinelibrary.wiley.com/doi/10.1002/anie.201302759/abstract]]
!!![[Mechanical design of DNA nanostructures|http://pubs.rsc.org/en/Content/ArticleLanding/2015/NR/C4NR07153K#!divAbstract]]
[[DNA Scissors Device Used to Measure MutS Binding to DNA Mis-pairs|http://pubs.acs.org/doi/abs/10.1021/ja910188p]]
[[Nanomechanical DNA origami 'single-molecule beacons' directly imaged by atomic force microscopy|http://www.nature.com/ncomms/journal/v2/n8/full/ncomms1452.html]]
[[A DNA-fuelled molecular machine made of DNA|http://www.nature.com/nature/journal/v406/n6796/full/406605a0.html]]
[[Construction of a 4 Zeptoliters Switchable 3D DNA Box Origami|http://pubs.acs.org/doi/abs/10.1021/nn303767b]]
[[Molecular Engineering of DNA: Molecular Beacons|http://onlinelibrary.wiley.com/doi/10.1002/anie.200800370/abstract]]
See also [[Atomically precise manufacturing]]
I think this may be the article Turberfield mentioned: http://www.nature.com/nature/journal/v525/n7567/full/nature14860.html
also this: http://www.nature.com/nnano/journal/v10/n9/full/nnano.2015.204.html
This talks about 3D scafolded dna origami: http://www.nature.com/nmeth/journal/v8/n3/full/nmeth.1570.html
-------
[[Nature - DNA nanotechnology|http://www.nature.com/nnano/focus/dna-nanotechnology/index.html]]
[[Structural DNA Nanotechnology: State of the Art and Future Perspective|http://pubs.acs.org/doi/abs/10.1021/ja505101a]]
[[Challenges and opportunities for structural DNA nanotechnology|http://www.nature.com/nnano/journal/v6/n12/full/nnano.2011.187.html]]
[[DNA nanotechnology from the test tube to the cell|http://www.nature.com/nnano/journal/v10/n9/full/nnano.2015.195.html]]
!!Methods and techniques
__DNA origami__
[[William Shih (Harvard) Part 1: Nanofabrication via DNA Origami|https://www.youtube.com/watch?v=Ek-FDPymyyg]]
[[DNA Origami with Complex Curvatures in Three-Dimensional Space|http://science.sciencemag.org/content/332/6027/342]]
__DNA bricks/tiles__
[[Building with DNA bricks|http://news.harvard.edu/gazette/story/2012/11/building-with-dna-bricks/]]
[[Complex shapes self-assembled from single-stranded DNA tiles|http://www.nature.com/nature/journal/v485/n7400/full/nature11075.html]]
[[DNA brick crystals with prescribed depths|http://www.nature.com/nchem/journal/v6/n11/full/nchem.2083.html]]
[[Polyhedra Self-Assembled from DNA Tripods and Characterized with 3D DNA-PAINT|http://science.sciencemag.org/content/early/2014/03/12/science.1250944.figures-only]]
[[Three-Dimensional Structures Self-Assembled from DNA Bricks|http://science.sciencemag.org/content/338/6111/1177.full]]
[[LEGO-like DNA Structures|http://science.sciencemag.org/content/338/6111/1159.full]]
__Other DNA self-assembly techniques and reviews__
[[Rational design of self-assembly pathways for complex multicomponent structures|http://www.pnas.org/content/112/20/6313.full]]
[[Folding DNA to create nanoscale shapes and patterns|http://www.nature.com/nature/journal/v440/n7082/full/nature04586.html]] (2006, Rothemund).
[[Complex DNA Nanostructures from Oligonucleotide Ensembles|http://pubs.acs.org/doi/abs/10.1021/sb3000518]]
[[Placement and orientation of individual DNA shapes on lithographically patterned surfaces|http://www.nature.com/nnano/journal/v4/n9/full/nnano.2009.220.html]]
[[Self-assembly of DNA into nanoscale three-dimensional shapes|http://www.nature.com/nature/journal/v459/n7245/full/nature08016.html]]
__DNA CAD__
[[Computer-Aided Design of DNA Origami Structures|http://link.springer.com/protocol/10.1007/978-1-4939-1878-2_2]]
[[Computer-assisted design for scaling up systems based on DNA reaction networks|http://rsif.royalsocietypublishing.org/content/11/93/20131167.full]]
-------
[img[dna_self_assembly.png]]
-----
!!Applications and engineering
[[DNA nanostructures: a shift from assembly to applications|http://www.sciencedirect.com/science/article/pii/S2211339815000027]]
__[[DNA nanoengineering]]__
__[[DNA nanomachines]]__
__[[DNA computing]]__
__Single-molecule analysis__
[[Regulation of DNA Methylation Using Different Tensions of Double Strands Constructed in a Defined DNA Nanostructure|http://pubs.acs.org/doi/abs/10.1021/ja907649w]]
[[Single-Molecule Mechanochemical Sensing Using DNA Origami Nanostructures|http://onlinelibrary.wiley.com/doi/10.1002/anie.201404043/abstract;jsessionid=9F180BD1692C8075F736BCFBE9FB064B.f04t03]]
__[[Nanomedicine]]__
------------------
[[Order custom DNA origami parts!|http://shop.tilibit.com/index.php?main_page=index&cPath=70]]
Replication of [[DNA]] is a step in [[Mitosis]]
<iframe width="560" height="315" src="https://www.youtube.com/embed/TNKWgcFPHqw" frameborder="0" allowfullscreen></iframe>
# ''Helicase'' unzips DNA, and forms a replication fork. There are also [[Topoisomerase]]s releasing built up stresses in DNA
# ''Primase'' makes a small piece of RNA called a primer, which is between 7 and 10 [[Nucleobases]], and often being in an A-rich section
# ''DNA polymerase'' enzimes binds to the primer and will make the new strand of DNA. The leading strand is replicated continuously, while the lagging strand is replicated in steps, forming Okazaki fragments. DNA polymerase $$\alpha$$, and then DNA polymerase $$\beta$$. Polymerase works only in one direction, in the 3' -> 5' direction, only bonding 5' to 3'
# ''Exonuclease'' removes all the RNA primers from both strands of DNA
# DNA polymerase enzymes then fill the gaps left behind in DNA.
# ''DNA ligase'' seals up the fragments of DNA
Animation below is missing the steps 4 and 5:
[img[http://67.media.tumblr.com/d4b9974630566b1185f8e3adbcd4bb06/tumblr_o9hrs67V5c1sk2szio1_1280.gif]]
!!Inhibition of DNA replication
Interfere with enzymes, etc
------------------
https://www.wikiwand.com/en/DNA_sequencing
//aka transcription//
[[video (basic)|https://www.youtube.com/watch?v=5MfSYnItYvg]] -- [[video (advanced)|https://www.youtube.com/watch?v=SMtWvDbfHLo]]
http://www.nature.com/scitable/definition/transcription-dna-transcription-87
http://www.nature.com/scitable/topicpage/dna-transcription-426
[ext[https://www.wikiwand.com/en/Transcription_(genetics)]]
<img style="background-color:white;" src="https://upload.wikimedia.org/wikipedia/commons/thumb/9/9b/MRNA.svg/2000px-MRNA.svg.png">
!!__Transcription initiation__
Initiator sequence
Many factors.... Helps with helicase activity. [[phosphorelates|Phosphorelation]] the enzyme (activates it)
* TFIIH
* [[Transcription factor]]s
* [[Promoter region]]. The composition and size of the promoter region affects the probability of that gene bing transcribed.
RNA polymerase levels and ribosome leves is affected by cell growth rates. This affects gene expression.
!!__Transcription elongation__
* Capping the pre-mRNA. The cap binding complex is recognized by nuclear pores to let the completed mRNA out of the nucleus.
* Polyadenylating the pre-mRNA, like telomeres for mRNA... determines its half-life.
!!!__RNA polymerase__
__Eukaryotes__
* [[RNA polymerase]]
** Pol I makes [[Ribosomal RNA]]
** Pol II makes [[Messenger RNA]]
** Pol II makes [[Transfer RNA]]
** Pol IV and V, only in [[Plant cell]]s
__[[Prokaryote]]s__
Only one type of DNA
__Function__
*First unwinds the [[DNA]] (helicase activity)
* Transcribes 3' to 5' end to create a 5' to 3; precursor mRNA strand
* DNA/RNA hybrid is separated at an archway.
[img[https://classconnection.s3.amazonaws.com/185/flashcards/82185/jpg/6_61320375392033.jpg]]
!!!__Pre-mRNA processing - splicing__
One [[Gene]] that can code for multiple variants of the [[Protein]].
* [[Exon]]s, and [[Intron]]s
* snRNA
* splicesome. See video RNA splicing mechanism.
!!__mRNA stability__
* Half-lives around 30min to 10 hours.
!!__Transcription in bacteria__
Much simpler. transcription, and translations coupled. Can code several proteins at the same time, operon.
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
A [[door|https://en.wikipedia.org/wiki/Door]] is a movable structure used to block off, and allow access to an enclosed space, such as a [[Building]] or [[Vehicle]].
An example of a [[Game]]. See also [[Combinatorial game theory]]
[[Dots and boxes player on the web|https://www.math.ucla.edu/~tom/Games/dots&boxes.html]]
[img[http://study.com/cimages/multimages/16/double_displacement_reaction.png]]
http://study.com/academy/lesson/double-displacement-reaction-definition-examples.html
[[Parallel computing]], [[Distributed computing]], [[GPU computing]], [[Neuromorphic computing]]
!!__High-performance computing with [[Matlab]]__
!!!__Code profiling__
Identify bottlenecks in the code.
``tic``, ``toc``
``profile``
code analyzer
__Vector preallocation__. Arrays which dynamically change size can be slow, because array memory has to be reallocated.
Use backlash, and store sparse matrices in sparse format.
vectorization
!!!__[[Parallel computing]]__
parfor: parallel for loops. [[Variable types in parfors|https://uk.mathworks.com/help/distcomp/classification-of-variables-in-parfor-loops.html]]
Multithreading. Several execution threads, [[Concurrent computing]].
MEX functions
Parallel computing with [[Computer cluster]]s
spmd mode: single program multiple data. [[Concurrent computing]].
In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a type of deep neural network, composed of multiple layers of [[Latent variable]]s ("hidden units"), with connections between the layers but not between units within each layer.
It can be seen as a composition of [[Restricted Boltzmann machine]]s
Test the model on data you haven't used for training.
min-max, average
[ext[https://www.cs.cmu.edu/~schneide/tut5/node42.html]]
Wikipedia has good explanations: [ext[https://en.wikipedia.org/wiki/Cross-validation_(statistics)]]
!!__Hold-out cross-validation__
[[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=41m30s]]
#Randomly split training set S into two subsets, the training subset S,,train,,, (70%) and the cross-validation subset S,,CV,, (30%).
#Train the model on the training set, and test it on S,,CV,,
#Pick the model (set of [[Hyperparameter]]s) with smallest error on S,,CV,,
To search for best configuration of hyperparameters acoording to the validation error, there are several methods. Some popular ones are:
* [[Grid search|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=4m10s]], try all possible configurations from chosen trial values.
* [[Random search|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=6m05s]]
Sometimes, once a model complexity (and other [[Hyperparameter]]s) are picked, the model is trained on the whole data set.
!!!__''Test set''__
To predict the generalization error (see [[Learning theory]]) of the chosen hyperparameters that are best, we can't just look at their result at S,,CV,,, as that set has been by the algorithm to choose the final answer. As a result, the error on S,,CV,, is a biased estimator of generalization error. To have an unbiased estimator, we need a test set, that is only used once the learning algorithm has finished completely.
See [[here|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16]]
!!__k-fold cross-validation__
[[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=44m49s]]
# Split data into k equal pieces. Common k=10.
# For i from 1 to k:
:: Hold-out the ith piece for testing, and use the other k-1 pieces for training.
:3. Average errors from the k iterations
More computationally expensive
!!__Leave-one-out cross-validation__
k-fold CV, for whem k={number of training examples}, so for each iteration, you leave one out.
Even more computationally expensive, but more accurate estimate of generalization error. Only done when the data is very scarce.
---------------------
//Some thoughts// when I misunderstood train/validation/test learning.
What I describe here is some sort of hyperlearning where we have two steps, where we learn two sets of hyperparameters, and use two different validation sets (which I call below validation, and test, mistakenly...)
When we have trained the data using a method as hold-out CV, and with some fixed learning [[Hyperparameter]]s. If we want to learn the hyperparameters, we can do this whole training procedure with several values of the hyperparameter.
However, to choose the hyperparameters that are best, we can't just look at their result at S,,CV,,, as that set has been by the algorithm to choose the final answer. As a result, the error on S,,CV,, is a biased estimator of generalization error (see [[Learning theory]]). To have an unbiased estimator, we need a test set, that is only used once the learning algorithm has finished completely. We can compare the results on the test set to choose the best set of hyperparameters. Note, that once we have done that, the test error is no longer an unbiased estimate of generalization error, as we have used it to output our very final answer; i.e. our final answer depended on it!! We'd need a hypertest set
https://www.wikiwand.com/en/Environmental_studies
[img[https://images.washingtonpost.com/?url=https%3A%2F%2Fimg.washingtonpost.com%2Fblogs%2Fworldviews%2Ffiles%2F2014%2F12%2Fland-changes-1900-2010-forward_50perc_res.gif&op=noop]]
"It's mainly because people haven't been cutting down nearly as much wood for fuel, plus there have been concerted efforts to manage and regrow forests. Also some of the areas have been regrowing after the World Wars made them less suitable for farmland." ~Laurie
https://www.wikiwand.com/en/Environmental_studies
__Related areas__
* [[Ecology]]
* [[Climate]]
Recursive processing of variable-length structures continues to be regarded as a hall-
mark of human cognition. In the last decade, a firefight in the linguistics community staked
several leaders of the field against one another. At issue was whether recursive processing
is the “uniquely human” evolutionary innovation that enables language and is specialized to
language, a view supported by Fitch, Hauser, and Chomsky (Fitch et al., 2005), or whether
multiple new adaptations are responsible for human language evolution and recursive pro-
cessing predates language (Jackendoff and Pinker, 2005).
from [[here|https://arxiv.org/pdf/1410.5401v2.pdf]]
http://www.umsu.de/wo/2013/600
[[A free energy principle for the brain|http://www.sciencedirect.com/science/article/pii/S092842570600060X]] -- [[pdf|http://sci-hub.bz/10.1016/j.jphysparis.2006.10.001]]
https://www.wikiwand.com/en/Free_energy_principle
The free energy principle states that systems change to
decrease their free energy. The concept of free-energy arises
in many contexts, especially physics and statistics. In thermodynamics,
free energy is a measure of the amount of
work that can be extracted from a system, and is useful
in engineering applications. It is the difference between
the energy and the entropy of a system. Free-energy also
plays a central role in statistics, where, borrowing from statistical
thermodynamics; approximate inference by variational
free energy minimization (also known as
variational Bayes, or ensemble learning) has maximum
likelihood and maximum a posteriori methods as special
cases. It is this sort of free energy, which is a measure of
statistical probability distributions; we apply to the
exchange of biological systems with the world. The implication
is that these systems make implicit inferences about
their surroundings.
[[Karl Friston talk|https://www.youtube.com/watch?v=zWFfZHqOnvM]]. Systems that have certain measurable characteristics which persist in time, and are thus ergodic in this certain weak sense. This implies the existence of a random global attractor ([[Ergodic theorem]]).
[ext[Free Energy, Value, and Attractors|http://www.fil.ion.ucl.ac.uk/~karl/Free%20Energy%20Value%20and%20Attractors.pdf]]
__Universal Lyapunov function?__
|$$\dot{x} = f(x) + \omega$$ |Steady state: $$f(x)=(\Gamma + Q) \nabla \ln p$$| Lyapunov function: $$-\ln p$$|
$$\omega$$ are random fluctuations, $$f(x)$$ is deterministic flow. $$p$$ is steady state probability. In short, this equation rep-resents “a simple starting point for statistical mechanics and thermodynamics and is consistent with conservative dynam-ics that dominates the physical sciences”. See below for details and derivations.
__Surprisal is a [[Lyapunov function]] of the [[Fokker-Planck equation]]__
See [[Surprisal as a Lyapunov function in stochastic dynamics]]
Flow can be decomposed into a curl-free part increases value while the (con-servative) divergence-free part follows isoprobability con-tours and does not change value. This means every policy (expec-ted flow) reduces surprise as a function of time. In other words, it must direct flow towards states that are more probable (in the steady state), and have a greater sojourn time. This just describes how systems approach the steady state. They do so by uniformly increasing their steady state probability. This corresponds to a decrease in [[Entropy]]. However, the fluctuation due to $$\omega$$ causes a corresponding increase in that means that in steady state entropy is constant, as expected.
---------------------
[ext[Free Energy, Value, and Attractors|http://www.fil.ion.ucl.ac.uk/~karl/Free%20Energy%20Value%20and%20Attractors.pdf]]. ,,We will compare and contrast two perspectives; one based upon a free energy principle [1] and the other on opti-mal control and reinforcement-learning [2–5]. policies can be cast as beliefs about the state-transitions that determine free energy.,,
The main conclusion of this paper is that it is sufficient to minimise the average surprise (conditional entropy) of an agent’s states to explain adaptive behaviour. This can be achieved by policies or empirical priors (equations of motion) that guide action and induce random attractors in its state-space. These attract agents to (low-cost) invariant sets of states and lead to autopoietic and ergodic behaviour.
[[Active inference]]. connection between empirical priors and policies.
-----------------
!![[A free energy principle for the brain|http://www.sciencedirect.com/science/article/pii/S092842570600060X]]
The system can minimise free energy by changing its con-
figuration to affect the way it samples the environment or change the distribution it encodes. These changes correspond to action and
perception respectively and lead to an adaptive exchange with the environment that is characteristic of biological systems.
See [[Philosophy]], [[Science and Art]]
There is something
quite remarkable about the fact that our inferences about
the world, both perceptual and scientific, can be applied
to the very process of making those inferences ([[Strange loop]])
[[Hierarchical inference]]
!!!__Mathematical description__
//Ensemble density//: $$q(\theta;\lambda)$$.
This is some arbitrary density function on the environments
parameters that is specified or encoded by the
systems parameters ($$\lambda$$)
two other sets of variables that
describe, respectively, the effect of the environment on
the system and the effect of the system on the environment.
We will denote these as $$\tilde{y}$$ and $$\alpha$$, respectively.
We also need to define a generative density $$p(\tilde{y}, \theta)$$, which defines a [[Generative model]] of sensory inputs and causes.
See more [[in paper|http://sci-hub.bz/10.1016/j.jphysparis.2006.10.001]] <mark>What is the meaning of this definition of free energy?</mark> It is a [[Kullback-Leibler divergence|Relative entropy]]
The free energy principle states that all the quantities
that can change; i.e., that are owned by the system ($$\lambda$$, and $$\alpha$$), will change to minimise free energy.
Minimizing w.r.t system parameters results in //perception//: it results in the ensemble density to correspond to the [[A posteriori distribution]] of the causes given for the given sensory input.
Mininmizing w.r.t action parameters results in //action//: it enforces a sampling of the environment that is consistent with the ensemble density. In other words, the system will reconfigure itself
to sample sensory inputs that are the most likely
under the ensemble density.
:There are at least two fundamental problems with the simple picture just outlined. One is that it makes little sense without postulating an independent source of goals or desires. Suppose it's true that I reach out for the pizza because I hallucinate (as it were) that that's what I'm doing, and I try to turn this hallucination into reality. Where does the hallucination come from? Surely it's not just a technical glitch in my perceptual system. Otherwise it would be a miraculous coincidence that I mostly hallucinate pleasant and fitness-increasing states. Some further part of my cognitive architecture must trigger the hallucinations that cause me to act. (If there's no such source, the much discussed "dark room problem" arises: why don't we efficiently minimize sensory surprise (and thereby free energy) by sitting still in a dark room until we die?)
:The second problem is that efficient action requires keeping track of both the actual state and the goal state. If I want to reach out for the pizza, I'd better know where my arms are, where the pizza is, what's in between the two, and so on. If my internal representation of the world falsely says that the pizza is already in my mouth, it's hard to explain how I manage to grab it from the plate.
See [[here|http://www.umsu.de/wo/2013/600]]
:->A closer look at Friston's papers suggests that the above rough proposal isn't quite what he has in mind. Recall that minimizing free energy can be seen as an approximate method for bringing one probability function Q close to another function P. If we think of Q as representing the system's beliefs about the present state, and P as a representation of its goals, then we have the required two components for explaining action. What's unusual is only that the goals are represented by a probability function, rather than (say) a utility function.
That version of the story looks much more plausible, and much less revolutionary, than the story outlined above. In the present version, perception and action are not two means to the same end -- minimizing free energy. The free energy that's minimized in perception is a completely different quantity than the free energy that's minimized in action. What's true is that both tasks involve mathematically similar optimization problems. But that isn't too surprising given the well-known mathematical and computational parallels between conditionalizing and maximizing expected utility.
----------------
[img[http://d10k7sivr61qqr.cloudfront.net/content/royinterface/10/86/20130475/F1.large.jpg]]
Applications to [[Neuroscience]], [[Self-organization]], [[Intelligence]], [[Reinforcement learning]]
[ext[http://www.fil.ion.ucl.ac.uk/~karl/]]
Frontend web development
!![[JavaScript]]
https://medium.freecodecamp.com/angular-2-versus-react-there-will-be-blood-66595faafd51#.4bc9n0ott [[ReactJS]] seems better
http://www.infragistics.com/products/jquery?utm_source=facebook&utm_medium=cpc&utm_campaign=ignite looks nice
!!__CSS libraries__
See [[Voxel.css|http://www.voxelcss.com/]] for Minecraft-like stuff in browser
---------
!!!__[[Graphics and visualization web libraries]]__
__<mark>Graphics and visualization</mark>__
~ ~ ~
[[Maths frontend web libraries]]
http://fortawesome.github.io/Font-Awesome/
[[Webgl|https://en.wikipedia.org/wiki/WebGL]] See chromeexperiments website
Nice 2D webgl lib: http://www.pixijs.com/
voxel.css
http://codepen.io/sha99y8oy/pen/GZZXyL
http://www.effectgames.com/demos/canvascycle/
HTML presentations: impress.js, reveal.js, [[deck.js|http://imakewebthings.com/deck.js/]]
https://www.shadertoy.com/
!!!__Audio libraries__
See here: https://musiclab.chromeexperiments.com/Technology
[[Tone.js|https://github.com/Tonejs/Tone.js]]
For microphone input: https://en.wikipedia.org/wiki/WebRTC
!!!__Input libraries__
For accelerometer, gyroscope input (from phone for eg) see chromeexperiments
For microphone input: https://en.wikipedia.org/wiki/WebRTC
!!!__CMS__
[[Jekyll]]
!!!__[[Definitions|https://www.youtube.com/watch?time_continue=35&v=H6gwYdyn7II]]
__
* [[Gene]]
* [[Allele]]
* [[Genotype]], [[Phenotype]], [[Phenotypic trait]].
* [[Chromosome]]
* [[Locus (Genetics)]]
More: [[Genes, Alleles and Loci on Chromosomes|https://www.youtube.com/watch?v=GUS9qmG1wY4&nohtml5=False]] -- [[Genotypes and phenotypes|https://www.stat.washington.edu/thompson/Genetics/1.3_genotypes.html]] -- [[PHENOTYPE AND GENOTYPE|http://biomed.brown.edu/Courses/BIO48/5.Geno.Pheno.HTML]]
[[MIT notes|http://ocw.mit.edu/courses/biology/7-03-genetics-fall-2004/lecture-notes/]]
!!__Mendelian genetics__
[[Intro to Mendel|https://www.youtube.com/watch?v=D8m-ZEr9qV8]] -- [[Mendel experiments|https://www.youtube.com/watch?v=5yY1snYi2x0]]
[[Mendelian genetics video|https://www.youtube.com/watch?v=NWqgZUnJdAY]]
!!!__Mendel's laws__
1. Law of segregation, genes segregate randomly from one generation to another
2. Independent assortment. [[Multiple traits: Mendel's second law|https://www.youtube.com/watch?v=iFlHZ7L7fYI]] [[key|https://www.youtube.com/watch?v=iFlHZ7L7fYI#t=4m]]. Are different [[Gene]]'s correlated in offspring
[[Heredity video|https://www.youtube.com/watch?v=CBezq1fFUEA]]
[[Punnett square]]
https://en.wikipedia.org/wiki/Chromosomal_crossover
!!__[[Chromosome theory of inheritance]] -- [[Inheritance]]__
[[Chromosome]]s carry the [[Gene]]s that Mendel studied. [[Cytology and the chromosomal theory of inheritance|https://www.youtube.com/watch?v=uLsVEYdn_e4]]
!!__[[Population genetics]]__
The genetics of populations of organisms, their [[Evolution]], and [[Ecology]]
!!__[[Biochemical genetics]]__
The field that studies the links between [[Genetics]] and [[Biochemistry]], for instance by finding which [[Gene]]s that control certain [[Metabolic pathway]]s, and how they do it.
!!__[[Molecular genetics]]__
!!![[DNA sequencing]]
!!![[Genetic mutation]]
!!!__[[Genetic epidemiology]]__
!!!__[[Gene expression]]__
[[Epigenetics]]
[[Complex segregation analysis]]
!!__[[Genomics]]__
Studies whole [[Genome]]s
!!__[[Genetic engineering]]__
[[Genetic recombination]] --> [[Homologous recombination]]
* [[Human genetics]]
* [[Genealogy]]
[[Real human genetics|https://www.youtube.com/watch?v=l9_lT0odWww]] (genetics in practice)
!!__[[Systems biology]]__
* [[Genotype-phenotype map]], [[Developmental biology]]
[[Parallel computing]], [[Distributed computing]], [[GPU computing]], [[Neuromorphic computing]]
!!__High-performance computing with [[Matlab]]__
!!!__Code profiling__
Identify bottlenecks in the code.
``tic``, ``toc``
``profile``
code analyzer
__Vector preallocation__. Arrays which dynamically change size can be slow, because array memory has to be reallocated.
Use backlash, and store sparse matrices in sparse format.
[img[http://i.imgur.com/42yTLLV.jpg]]
This has applications in [[Linear regression]], and in [[GPS]]
!__Nonlinear systems__
The effects of small damping, nonlinearity and forcing on a harmonic oscillator:
$$\ddot{x} + \beta \dot{x} + x + \delta x^3 = \Gamma \cos{\omega t}$$
* The simple harmonic oscillator (forced and damped, in general)
* [[Duffing oscillator]]
** Free (unforced) Duffing oscillator
*** Free undamped Duffing oscillator
*** Free damped Duffing oscillator
** Forced damped Duffing oscillator.
There are potentially $$8$$ qualitatively different forms of the equation, depending of which combination of the $$3$$ parameters considered are non-zero.
The Duffing Equation: Nonlinear Oscillators and their Behaviour
//More papers and references//:
https://en.wikipedia.org/wiki/Intermittency
https://en.wikipedia.org/wiki/Crisis_%28dynamical_systems%29
Y. Ueda, Steady Motions Exhibited by Duffing’s Equation: A Picture Book of Regular And Chaotic Motions
[[Catastrophes with Indeterminate Outcome
Stewart, H. B. ; Ueda, Y.|http://ezproxy-prd.bodleian.ox.ac.uk:2084/stable/51909?seq=1#page_scan_tab_contents]]
[[EXPLOSION OF STRANGE ATTRACTORS EXHIBITED BY DUFFING'S EQUATION - Yoshisuke Ueda|http://onlinelibrary.wiley.com/doi/10.1111/j.1749-6632.1980.tb29708.x/abstract]]
[[Common dynamical features on periodically driven strictly dissipative oscillators|http://sci-hub.io/http://www.worldscientific.com/doi/abs/10.1142/S0218127493000611]] (introduces torsion and winding numbers)
[[Comparison of bifurcation sets of driven strictly dissipative oscillators|https://link.springer.com/chapter/10.1007%2F978-3-0348-7004-7_41]]
__Wada basins__
https://en.wikipedia.org/wiki/Lakes_of_Wada
[[Wada basin boundaries and basin cells|http://sci-hub.io/10.1016/0167-2789%2895%2900249-9]] [[Other link|http://www.sciencedirect.com/science/article/pii/0167278995002499]]
[[Unpredictable behavior in the Duffing oscillator: Wada basins|http://www.escet.urjc.es/~fisica/investigacion/publications/Papers/2002/aguirre_wadad.pdf]]
[[Testing for Basins of Wada|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4639726/]]
[[Response Of A Harmonically Excited Hard Duffing Oscillator – Numerical And Experimental Investigation|https://link.springer.com/chapter/10.1007/978-1-4020-9100-1_27]]
[[Experimental investigation of the response of a
harmonically excited hard Duffing oscillator|http://www.ias.ac.in/article/fulltext/pram/068/01/0099-0104]] From [[here|http://www.ias.ac.in/listing/articles/pram/068/01]]
__Analytical methods__
[[Exact analytical solutions for forced cubic restoring force oscillator|https://link.springer.com/article/10.1007%2Fs11071-015-2486-2]] Uses Jacobi elliptic function (only for undamped Ueda oscillator I think).
[[A comparison of classical and high dimensional harmonic balance approaches for a Duffing oscillator|http://www.sciencedirect.com/science/article/pii/S0021999105004894]]
[[Second order averaging and bifurcations to subharmonics in duffing's equation|http://www.sciencedirect.com/science/article/pii/S0022460X81800302]]
[[Subharmonic Oscillations in Nonlinear Systems|http://ezproxy-prd.bodleian.ox.ac.uk:2837/content/aip/journal/jap/24/5/10.1063/1.1721322]]
[[Chaotic states and routes to chaos in the forced pendulum|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.26.3483]]
[[Organization of periodic orbits in the driven Duffing oscillator|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.38.1566]]
[[Structure in the bifurcation diagram of the Duffing oscillator|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.51.935]]
[[superstructure in the bifurcation set of the duffing equation|http://www.dpi.physik.uni-goettingen.de/~ulli/pdf/PL85.pdf]]
[[General case of crisis-induced intermittency in the Duffing equation|http://www.sciencedirect.com/science/article/pii/037596019390732F]] for double-well Duffing oscillator.
[[On the jump-up and jump-down frequencies of the Duffing oscillator|http://www.sciencedirect.com/science/article/pii/S0022460X08003805]]
More books:
Chaos in Nonlinear Oscillators: Controlling and Synchronization
By M Lakshmanan, K Murali
[[Antimonotonicity|http://sci-hub.io/10.1016/0375-9601%2892%2990442-O]] reversal of period-doubling cascades
------
!__Networks__
//Spatial networks//
[img[https://media.giphy.com/media/d2Z80h0V2OAWFNbW/giphy.gif]]
See also [[Biochemistry]]
[[Inner life of the cell video|https://www.youtube.com/watch?v=FzcTgrxMzZk]]
[[Assembly of Bacterial Ribosomes|http://www.jstor.org/stable/1735327?seq=1&cid=pdf-reference#page_scan_tab_contents]]
[[David Odde - Microtubule Self-assembly|https://www.youtube.com/watch?v=OoRQWEeXcQc]]
[[List of protein structure prediction software|https://en.wikipedia.org/wiki/List_of_protein_structure_prediction_software]]
[[My 65 years in protein chemistry|http://www.ncbi.nlm.nih.gov/pubmed/25850343]]
[[Programming the Emergence in Morphogenetically architected complex systems|http://link.springer.com/article/10.1007%2Fs10441-015-9262-z]]
[[Protein folding problem 50 years on|http://science.sciencemag.org/content/338/6110/1042.full]]
[[A review of recent advances in ab initio protein folding by the Folding@home project|http://biochem218.stanford.edu/Projects%202010/Ito%202010.pdf]]
http://molecularmovies.com/
https://en.wikipedia.org/wiki/Ribozyme
See [[DNA]]
[[Foundations of molecular biology|https://courses.edx.org/courses/course-v1:MITx+7.00x_3+2T2015/courseware/Week_6Global/Molecular_Biology_1/]]
[[Transforming principle|https://www.youtube.com/watch?v=gsFld6gZVVw]]: discovery of the substance that carried genetic traits.
[[Network]] of [[Neuron]]s
[[Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits|http://www.ncbi.nlm.nih.gov/pubmed/22991468]]
[[Brain connectivity toolbox|https://sites.google.com/site/bctnet/Home]]
[[Video|https://www.youtube.com/watch?v=cjj9ihYJkOQ#t=1m30s]]
One important thing to model is the output (set of parallel spiking trains)that population of neurons produces upon receiving a certain input (set of parallel spiking trains).
For a single neuron, we can define the asynchronous ''synaptic transmission curve'' (aka ''synaptic response curve''), which is the instantaneous firing rate as a function of time, when the neuron receives a single isolated spike. If integrated it gives the ''asynchronous gain'' (ASG), the total number of output spikes per input spike.
------------
~~https://www.facebook.com/photo.php?fbid=10209945472266759&set=a.10209945472066754.1073741832.1633284755&type=3&theater¬if_t=photo_reply¬if_id=1481327844427895~~
[[Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding|http://sci-hub.bz/10.1038/nrn2886]]
!!![[Neural coding]]
Stimulus or task-related activity is said to be
‘rate coded’ when it can be decoded using only the
firing rates of neurons in an ensemble. On the other
hand, when stimulus or task-related activity can be
decoded using synchrony (BOX 2), it is referred to as a
time (or ‘synchrony’) code
------------
!!__[[Signal transmission and processing by neuronal networks]]__
''Cross-correlation'', post-synaptic potentials..
Neural chains
Synchronous transmission. ''Synchronous gain''
!!__[[Membrane potential and the synaptic response curve]]__
Firing rates of neurons from noise.
Effect of ''postsynaptic potential''s in the firing rate, thus giving a way to compute the synaptic transmission curve ,,(which we can experimentally find with cross-correlations),,.
!!__Neuronal network models__
* [[Hopfield network]], a kind of [[Boolean network]], with thresholded activation. The main model has symmetric synaptic strengths (i.e. same strength from neuron i to j as from j to i).
* [[Spiking neural network]]
* Standard [[Artificial neural network]]s.
** [[Perceptron]]. Multilayer perceptron (now much more developed in [[Deep learning]])
The study of neuronal networks in the [[Cortex]] is known as [[Corticonics]].
[[Neural Networks - intro|https://www.youtube.com/watch?v=aU2pyB-49m8&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp]] -- [[LC circuit]]s -- [[Linear system]]s
-----------------
See [[Neural system]] for well studied neuronal networks
asdasdsadadsasdasdasdadasdas
Formally, the number of "parameters" grows with the training set. Here number of parameters basically refers to "amount of information in learned function". For example, in neares-neighbour models, the parameters are the position of the neighbourhoods, and the categories to which those regions map. The number of these parameters clearly grows as more data points are added.. A more intuitive way of looking at it is that the algorithm doesn't fit parameters, and instead uses some other method to generate the function it is trying to learn. See [[Nonparametric statistics]] An example is [[Nearest-neighbour classification]] (note that the model has parameters, but they are not fitting parameters, instead they are chosen before using the algorithm, and then are fixed)
https://en.wikipedia.org/wiki/Nonparametric_statistics
not based on parameterized families of probability distributions
__Nonparametric models__
* [[Nearest-neighbour classification]]
* [[Locally-weighted linear regression]]
They are both based on looking at local neighbours near points for which we are going to make the prediction.
Any two non-adjacent variables are conditionally independent given all other variables
A [[Layers for deep learning]], that consists on exponentiating all vector elements and normalize them to so sum to unity.
$$\mathbf{\sigma}(\mathbf{y}) \equiv \frac{e^\mathbf{y}}{\sum_i e^{y_i}}$$
where the mathematical operations are element-wise.
As used in [[Protein structure analysis]], Statistical potentials score [[decoys|Protein-decoy structure]] by comparing their features to experimentally-
determined structures, based on the assumption that the observed distributions of
particular features reflect energetics: i.e., a common characteristic is assumed to be
energetically favourable.
__RAPDF (residue-specific all-atom probability discriminatory function)__
Essentially a [[Naive Bayes]] classifier trained on a set $$C$$ of native structures (structures observed experimentally and assumed to be correct).
We wish to evaluate $$P(C|\{d_{ij}^{ab}\})$$, theprobability the structure is a member of the "correct" set $$C$$, given it contains the distances {$$d_{ij}^{ab}$$}. We write this probability, using [[Baye's theorem]] as
$$P(C|\{d_{ij}^{ab}\}) = P(C) \frac{P(\{d_{ij}^{ab}\}|C)}{P(\{d_{ij}^{ab}\})}$$
We then make the assumption that $$P(\{d_{ij}^{ab}\}|C)$$ factorizes as $$\prod\limits_{ij}P(d_{ij}^{ab}|C)$$ (i.e. the [[Naive Bayes]] assumption!).
The score of each decoy (with features $$\{d_{ij}^{ab}\}$$) is then just the log-likelihood
$$S(\{d_{ij}^{ab}\}) = \ln{P(C|\{d_{ij}^{ab}\})} = \sum_{ij} \ln{\left (\frac{P(d^{ij}_{ab}|C)}{P(d^{ij}_{ab})} \right)}$$
where $$S$$ is the score for the decoy, and $$d^{ij}_{ab}$$ is the distance between atoms $$i$$ and $$j$$, of types $$a$$ and $$b$$.
See more explanation [[here|http://moult.ibbr.umd.edu/pdfs/All-atomDistance-dependentConditionalProbability.pdf]]
The probabilites are estimated (as in [[Naive Bayes]]) as sample frequencies:
$$P(d^{ij}_{ab}|C) = \frac{N(d^{ij}_{ab})}{\sum_d (d^{ij}_{ab})}$$
where the distances $$d^{ij}_{ab}$$ have been discretized, and $$N$$ means number of occurrences of distance $$d$$ between residues of type $$a$$ and $$b$$ over all native configurations in $$C$$.
The average over all experimental structures is
$$P(d^{ij}_{ab}) = \frac{N(d^{ij}_{ab})}{\sum_d (d^{ij}_{ab})}$$ over all structures, not just those in $$C$$.
However, they further approximate this, and assume (I guess as over all structures, there is more randomness..) that this is independent of $$a$$ and $$b$$, and that they can estimate this as the average over all $$a$$ and $$b$$ and all structures, in $$C$$ (because we don't have the whole set of possible structures I guess)
$$P(d^{ij}_{ab}) \approx P(d) = \frac{\sum_{ab}N(d^{ij}_{ab})}{\sum_d \sum_{ab} (d^{ij}_{ab})}$$ over structres in $$C$$.
[[Toward an Integration of Deep Learning and Neuroscience|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021692/]]
* Hypothesis 1 – The Brain Optimizes Cost Functions
* Hypothesis 2 – Cost Functions Are Diverse across Areas and Change over Development
* Hypothesis 3 – Specialized Systems Allow Efficient Solution of Key Computational Problems
!!__The Brain Can Optimize Cost Functions__
See notes in [[Spiking neural network]]s.
There may or may not be a separate circuit to compute and impose a cost function on the network, depending on the optimization mechanism.
Optimizing by [[Self-organization]] (without explicit supervision), useful for unsupervised learning, minimizing implicit costs, though they can also give rise to implicit approximations of backprop, or other algorithms that use the gradient.
“biologically plausible” mechanisms can efficiently make use of the __gradient__ (and there are very good reasons regarding efficiency to use the gradient, whenever supervision signal is available). A possible mechanism, by which biological neural networks could approximate backpropagation, is “feedback alignment” (Lillicrap et al., 2014; Liao et al., 2015). Other methods, using special network organizations have been proposed. See Hinton's talk. There are also __diverse mechanism__ that go beyond conventional conceptions of backpropagation, like [[Neuromodulation]] by molecules.
''Temporal credit assignment'' is a difficult problem. Can generic recurrent networks perform temporal credit assignment in in a way that is more biologically plausible than "backpropagation through time" (BPTT)? Indeed, new discoveries are being made about the capacity for supervised learning in continuous-time recurrent networks with more realistic synapses and neural integration properties. BPTT can be achieved by learning to predict the backward-through-time gradient signal (costate) in a manner analogous to the prediction of value functions in reinforcement learning.
Fast connections maintain the network in a state where slow connections have local access to a global error signal.
,,spiking recurrent networks using realistic population coding schemes can, with an appropriate choice of connection weights, compute complicated, cognitively relevant functions17. The question is how the developing brain efficiently learns such complex functions.,,
Individual neurons should not be regarded as single “nodes” but as multi-component sub-networks.
Primary function of the cortex is probably some form of unsupervised learning via prediction. Some cortical learning models are explicit attempts to map cortical structure onto the framework of message-passing algorithms for [[Bayesian inference]]
As we will discuss below, some form of deep [[Reinforcement learning]] may be used by the brain for purposes beyond optimizing global rewards, including the training of local networks based on diverse internally generated cost functions.
!!__The Cost Functions are Diverse across Brain Areas and Time__
__[[Unsupervised learning]]__
__Matching the Statistics of the Input Data Using Generative Models__. Message-passing implementations of probabilistic inference have also been proposed as an explanation and generalization of deep convolutional networks (Chen et al., 2014; Patel et al., 2015). Various mappings of such processes onto neural circuitry have been attempted.
__Cost Functions That Approximate Properties of the World__A perceiving system should exploit statistical regularities in the world that are not present in an arbitrary dataset or input distribution.
__[[Supervised learning]]__
__Cost Functions for Supervised Learning__. Some possible uses of supervised learning, including: deliberative procedures could be compiled down to more rapid and automatic functions by using supervised learning to train a network to mimic the overall input-output behavior of the original multi-step process. Such a process is assumed to occur in cognitive models like ACT-R (Servan-Schreiber and Anderson, 1990),
__Repurposing Reinforcement Learning for Diverse Internal Cost Functions__. [[Reinforcement learning]] rewards plays a role
!!!__Bootstrap cost functions (innate instincts..)__
Special, internally-generated signals are needed specifically for learning problems where standard unsupervised methods—based purely on matching the statistics of the world, or on optimizing simple mathematical objectives like temporal continuity or sparsity—will fail to discover properties of the world which are statistically weak in an objective sense but nevertheless have special significance to the organism (Ullman et al., 2012). [...] How could we hack together cost functions, built on simple genetically specifiable mechanisms, to make it easier for a learning system to discover such behaviorally relevant variables? Ullman refers to such primitive, inbuilt detectors as innate “proto-concepts” (Ullman et al., 2012). Their broader claim is that such pre-specification of mutual supervision signals can make learning the relevant features of the world far easier, by giving an otherwise unsupervised learner the right kinds of hints or heuristic biases at the right times. Here we call these approximate, heuristic cost functions “bootstrap cost functions.” The purpose of the bootstrap cost functions is to reduce the amount of data required to learn a specific feature or task, but at the same time to avoid a need for fully unsupervised learning.
* [[Hand]]s
* [[Face]]s
* [[Emotion]]s
* [[Agency]], [[Ethics]]
[[Evolution]]: it seems likely that the brain would make extensive use of them to ensure that developing animals learn the precise patterns of perception and behavior needed to ensure their later survival and reproduction.
__Cost Functions for Learning by Imitation and through Social Feedback__. Babies and children learn about cause and effect through models based on goals, outcomes and agents, not just pure statistical inference.
cost functions and optimization are not the whole story. To achieve more complex forms of optimization, e.g., for learning to understand complex patterns of cause and effect over long timescales, to plan and reason prospectively, or to effectively coordinate many widely distributed brain resources, the brain seems to invoke specialized, pre-constructed data structures, algorithms and communication systems, which in turn facilitate specific kinds of optimization. Moreover, optimization occurs in a tightly orchestrated multi-stage process, and specialized, pre-structured brain systems need to be invoked to account for this meta-level of control over when, where and how each optimization problem is set up.
__Cost Functions for Story Generation and Understanding__
!!__Optimization Occurs in the Context of Specialized Structures__
pre-structured architectures are needed to allow the brain to find efficient solutions to certain types of problems. the brain may need pre-specialized systems for planning and executing sequential multi-step processes, for accessing memories, and for forming and manipulating compositional and recursive structures
Second, the training of optimization modules may need to be coordinated in a complex and dynamic fashion, including delivering the right training signals and activating the right learning rules in the right places and at the right times. To allow this, the brain may need specialized systems for storing and routing data, and for flexibly routing training signals such as target patterns, training data, reinforcement signals, attention signals, and modulatory signals. These mechanisms may need to be at least partially in place in advance of learning.
specialized structures, including thalamus, hippocampus, basal ganglia and cerebellum (Solari and Stoner, 2011). These structures evolutionarily pre-date (Lee et al., 2015) the cortex, and hence the cortex may have evolved to work in the context of such specialized mechanisms. For example, the cortex may have evolved as a trainable module for which the training is orchestrated by these older structures.
Welcome to this digital dynamic representation of the Cosmos, as experienced by me.
[[Contents]]
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ue+fXsSDnvwDkAkn+7vp/U5VM8+itndJKrleZ/Q18EMPgMwpSpzwuMrYHH8b1cXDD1IzfO6EMzwU6r2TxFGPM5OUT5bhJ2pZ7Sf8SnxBmDnF3TipRoqLatpzOE7eltbk1FMDdRgjoM5JwfmB79OASRzzknJp9fwStdv18/Py/PW6d/rP6/rX+u7CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACuK8d+MtA+HHgXxn8QvFuoxaV4Y8C+GNf8YeJdUnZFi0/QPDekX+s6xfOXeNQlrYWNxcPudVCqN7qqlx2tfhx/wAHE3x7PwB/4JE/tPS2d99m1/4v2Hhn4A6Cm5o/ti/EzxHb6V41s3dCTiT4cweNZNmCszosEpWKSaQfaeGfBGL8TfE7w78OMC5xxHG/GXDfC8a8P+YWnnOc4PL6+NmlGcvZ4OjiJ4qq4xlKNKjUahJqz48fiY4LA4zGSs1hcPWrWd/ecITajv8AakordayerabP5sP+Db7wN4g/bt/4K/8A7Wn/AAUP+I9hLdn4fQ+PvibBc3MiTLovxY/aN8TeJ9E8KaZC5KqbXSPh7b/EjSrCC3hW3soLXTFgS2iitkr/AEElUDHqNoA+gbPReuMH0BI5JVif5jf+DUj9nmP4Uf8ABMi6+Muo2Xk69+0t8Y/HfjaK7ljZLt/BXgS9j+FnhqydGVSLWLWvCnjDWbGR1Z5otdkuEke1ktDX9OuBjGBj0xx+Wf8AH6k81/Sv0/OOsHxt9K3xFy3JeSnwt4X0sj8IOEsFT5I0MtyjgDB1MpxuBw9GlOdOjQhxC87rUYK01CrH2sI1oziePwlhZYbIsNOpd18a6mYYiT3nUxcnOM22rtujGC7bq7vzI/H+XTn29vr17g5/J/8A4LQftG/td/sm/wDBPf4tfHf9jHw1pmt/EvwVfeGr3xDrOqaFH4ol8A/CxtQuP+E1+IemeFZ99p4guvDUEVkbxNRt7nTNH0C71XxbqlrdWGiXkL/rD/n/ADz/AJ+vNU7zT7DUrG703UbK0v8ATr+1nsr+wvbaG6sr2yuopobq0vLWdZYLm2uYpJIriCZHimieSKVXRnr+XuBs9yzhXjfhLijO+Gcq4yyjIM/ynNs04SzyFSeUcR5fgsfQxGLybMFTlGSw+PoUp4eb9+C506tGrTUqUvcxVGdfDV6NKvUw9SrSqU6denbnpTlGajUjfrBtSWqd7WacVJ/51v8AwRA/Z5/aj/4K8/8ABUJf+Ck/7WPiBfiH4Q/Z98W+G/GHjXx1qVv4O0SLxJ8YfB3hfSYPgl8O/DXgvw5Y6daaVaeFmtdF8c6he6X4etdFS20F0vtSbxh4g+3y+k/tG/8AE5/4PGPCdjq5/tCz0v47/ss/2dbXmZ4LP7F+xv8ACbxBZi2jcFYfs2tzPqsGwDy9RkN2pEwdz/eP8KPgn8F/gL4Wn8EfAz4RfDP4N+Dp9UvNdn8I/CrwD4T+H3hebXL9IY9Q1qXQPCOkaPpcmq36Wlsl7qTWv2y5S3tknncQoV/gm/aZ1nRvCn/B4foGt+KNWsfD2kSfH39lG2j1bWbqDTtONxq37HHwb8P6VEt3ePDA0mpa1cw6RZRhy11qk0WnQ7ruRY6/1m8IPpA1vpJfSG+kdxDkfC2H4L4H4W+gh4wcDeF3AGVYehTpcLcJZPj+BFg8DCll8Y0KmMxGJxVecvqdGnSpYX6lleHpyp4SnKf5/mWUrJsoyqlVrvFYqvxPl+KxuKm5XrV5xxalK822oKMY35nfm5pttysv9CBcDP0P/s/t3+X9OTg07jBG4kDbzj03dBnr3IHONoJJqGJ1lRXjcOrKGVlK7WyWAIYEg888HIOcjJIE6qCMHkEDJx1wX4zk47ZJ5PPJO6v8a1eSnFK2rtddbuLXLdNWt70WrrZpTuj9H/r89d32vb11unf+Wn/gvv8A8Ftv2tf+CYPxd+Dfwc/Z7+C/w2vtP+JfwzufH9x8Yfivo/i7xHo93qtn4w13QNU8CeD9C8P+LfB9tHrPhey0/Q9a8Rajq97qkclh4v0O3tNItpo3vn/IaL/g4u/4L4+BrS18Y/EL9hfwXL4KnigkN74j/Y8/al8LaLcWc4julutO8SQ/ErT7eKaa0Qm0uZmvbD7PNJcNp9wRDIv9xP7QH7Jf7Mn7V2meEtH/AGkvgb8N/jRp/gTxDF4q8I2nxA8L6br6aBrqBUluLB72CR0ttQiiih1nSpGbSdbtobe31uwvLeCCJfobyYdgi8qLy1ACx+WmwADAATG0ADgAcAcV/cXAf0ifo0cFeFHA/CWbfQ14C8R+NsGs8h4g8X8W53nWFq586uZyrZFicoxOW4ipiMPWhgJyw2Po1aNLD4WdHCrARqRlXqnzGKyfOsTjsXXpcRYnB4aTo/VKFCnCSpWhNVY1Iyik1zWlB8zb5pczbSP4HfDX/B4z8f8Aw+f7N+Jv7Bvwz1rV7G88jVofD3xi8cfDxl8p2S5s/wCzPEHgP4g3Om3YcOA9zdXPkEqJLSVkcH9dv2LP+DpD9ib9rD41+BPgP44+GPxV/Z48U/EnVvCPhTwT4g8VTeHfFngHU/iB4nurDSbbwhqOveHb+PVNCW88QX0OlaD4i1Pw/FoOoQMt94huPDZZbI/0aeLfhb8L/H9pe6f48+G/gXxpY6jp8mk6jZeLfB/h3xFZ3+lSmbzdMvbbWNMvYbuwl86YyWU6PbN5su+ImR2P5yeEP+CJf/BKjwB8Y/Anx48Ffsa/Dnwz8Rvhv40HxC8Faro2peObLRtE8ZQXdrf6frMfgqHxWvg27bQb+xtdS8K6df6BPpXhXVIItT8K2GnagpuD6WceLf0BuMeF+I6GY/RQ418LuL6+VYynw1mnhh4nZlm+TUc6lhqksBiMzy7iath6NLA4fHQoRq0aGFxCqZfVxcXCVenQZnTy7ivDVaThnuGxtBVIOtDGYKFOpKmppTUJ0VJuThdq8laSTUk3K/6pKSRgsABjkY6ZbHU+gPTkHOQSdxydX1nSfDuj6nruv6tp+i6NpFlPqGravq17babpenadaJNPeX2oahdzQ21jZ2sKPPc3VxMkEMKtJLKI0kc64RQMLtA4AA/4Fg8fQ8dDg56V8Uf8FCv2ONJ/b8/Yv+O37JOqeOda+HcfxZ0LRraw8aaNFHdTaH4g8L+MdB8ceGp9S0qWWFNa8O3Gv+G9NtPFGhrcWtzq/hm51Ww0/VdO1Oay1mH+I+HMHk+YcScPZbxJm9TIOH8fnWVYLP8AiCjgZ5pWyPI8TmGHw+a5zQyyE6VTMamV4OpWxtPARqQni50o4WM1Oom/pq8qsKFadCn7atGlUlRpOShGrUUZ+zpubfuKbilza8t3Jp2PzK/4L2fGj9mD4w/8Eiv2uvhzo/7V/wCz3Y+IfEnhXwP4k8F2cvxe+H9/qPjfV/hr8WfAnxdi8E+EdKs/E7Xuv+JPGNj4IudG0G20uK5lN7eW90bd7SK4r+Vz/gmF/wAHCenf8Eyf+CffiL9mjwx+zT/wsn4yf8La8a+NPCvivUfElt4f+Go0TxTpvhkQ6l42SwW78Ua/4i0fUdN1CyXR9Mg0uzv/AA5DoUK+LbK7hugP0M/Z9/4M5dWku7bU/wBqb9tHT7Swi1S/jvvBfwE+HVxd3eoaPHcBdNvbb4mfEK9s4dH1K6tkke+0uX4XaraWEzxx2+s38cbyyfHf/BVD/gjv8VP+CMfxk+GH7en7E9nqHxR/Z0+H+seDtQv/APhZ+i6H8TdQ+Ffjq0jh0a5t/i7o03h3T9J8RfDb4lXDNHaeKrfTdNi0TXNWn8LGTQNYbwHrVx/uN9HnLf2fj4Qzj6G9Lxgxnj/V4u4/n4p8JvPMmzjwv4GzrxEyjh/A5NlXBVbiqjVjPFQ4ho4OhGhTqUJYbESWNo4Sq8xngsLW/Mc2nxX9YhxC8vWVfV8KsDWdOrTxmKhhZ1qk6mIVBp8vs+dttNSj7l7QVSQ2L4Yf8HGH/Be20Gq+Nb3Wvhh+y/4wnOoWEHima4/Z+/Zql0SaWG4s00jwTp1nqnxG+NWiRLNLcaF4i1nS/H9mtxHcW/8AwmEFwiIP6Ov+Cbv/AAbb/sR/sQTaF8Sfi/bR/tYfHzTksb618WfEjQbKP4YeCtZicTC4+HvwqlbUdLF7bXCxSWXifxvdeJPENnd21vqXhmXw7NNd2bV/2Gv+Dl7/AIJyftM+DPDem/Hfx/a/sl/GiTTrC28UeD/iXb6pb/Di41qKOJNQv/BfxatLO48Lt4bNxIr2cHje78L+JYVeaNtFubO0k1d/2M1b9tv9ivQPDvhrxXrv7Xf7NOi+F/GVxDZ+EPEmrfHv4T6f4e8U3Usy20Vt4c1i98XQWGuzy3DLbpDplzcSvLKsSoZDGD/H/wBIzxx+mPktLMfA3CeC+O+jBwDSxOLy3/iHnhRwVneU0uIMNSX8TMON8owVfG8ZYfEYenLFTxODxdHD4ujUq1K8alGNWmfQZRlvDtRrM5ZlDOcU1Cf1vMMTSnKk25R93DVJKNBptLlnFuLSS97U+qVTClVxjA2gLtGAZAox0AA6AHJHYfeqaq8UkUqLNE6yxyIro6OHjkR9xRlcFgyspyG+6QqkEgmrFf5ywVubdO6Uk73unJappNO+66O+rbdvs15bWXpo5Wt63fy9GFN6pxz06Y45PqfY8Zz0GeadSYHoPy/z/P8AHPNPy6f8P5+b+/cf9fn/AF93mRlAFOeemDjgYJ4xnocYHHGeecZRVDKRkHGMjHclsn3yMHHvjIwxM2B/n2zj/PueSckn+f5+/wDnJ5POZUEnps1Zq8td1d+9Zu3Vpy295WuH9f1r+vzvqNAwPmOcY7ehYdcZ/u88kc8nOadR/n+fv/nJ565Kv/gfr3fX/h29LH9fn3f9adgooooAKKKKACiiigAooooAKKKKACiiigAooooAK/mJ/wCDrL9nV/i3/wAEy7T4yaRambXf2ZvjD4J8c3U8Fs092fA/jee6+F/iezjCfPHbDWPE/hHXb6dAywW2hvPMq2yXFwn9O1fLv7ZXwE079qX9kj9pH9nXUVhCfGD4O/EPwDYTzlVj0/X9d8MavaeG9ZV2O2OfQ9ek0zV7WVx5UV1aW8kqPErLX6x4BeI9Twf8dvCPxOjXlQocH8c5DmeZyp1HTqzyGWYYfC8RYeFT2lNRWLyWtjsLPnl7JxruFWMqXtFLzc2wazDK8fgmlKWIw1WFO6TXtUpyouzTXu1Ywa6rdNS1f5p/8G6P7Q6/tEf8Ej/2bRd6i174j+CVr4h/Z38SI8zStZL8MNXax8C2KuZGkVY/hff+BGWJwnkGQwwobZIZm/c6v4Yf+DPH443umeIP23P2SvEE09nPDF8Pfjh4b0S68y2ubPUNOvdT+HXxPknsJissdwHk+GlrN+6SS2ltzDd5keBR/c9X6Z9Nnw6peFv0tPHHhjBUoU8qxnFcuL8kdGCp4b+yeN8LT4tw1HC0k7UqGAlm1TLYU4xVKEsLOnRvRhFvk4Yxf13IcvrSd6kKEcPV7+0w0pYduT6uSpqd3d2m7u6k2UUUV/LZ7oV/n2f8EOVHiT/g5W/bo17Wx9t1WHW/2+vEMd2d0JTWb79ozRdOu7wRWxhgIls9Z1CEQNF9ljS4JggjkigdP9BOv8+7/gg8M/8ABx/+3Z7H9u/H/iTnhIZ/H/DnOTX98/Q+9zwM+n1Xh7laH0eKdCNaOlSNHE8S0qWJpKafMqWIpqMa0E7VIqMZKSTR8nxDrmnC0Xqnmrdul4w9177q7afTXW7uf6BSjHc8/n99+nPsuOezc4JFT1COcD2H5b3Hr6r069OeCTNX8A0F7kttWnp6u33Lp5vW61+rXXytv13vb8H6trRLUooorUYUUVDk4OWPGMc9T82e54GAffnkEjMuSSb7fjq18tvVtpK8mH9X+/8Ayv8Af1TvNRX45f8ABYf/AIK3fDf/AIJU/AG319rPTPHv7QfxKi1LS/gV8J7y9u4rbUryxBTVfH3jl7Oe2v7H4feEWms21GOyuLbV/Euq3Nh4V0O9snuNR8TWP5y/8G7v/BZ79p7/AIKT/ET9pX4NftVf8IDfeJvAfhjwx8UPh1rngjwqPCUqeHL7xFf+HfF/hrV7CPV7631Gz0a7vfCknh2/WBNWijutXh8Q6pqcs2lSRf0Lkn0XPGnPfADiv6S+H4apYXwv4VxeEwlTMswxscLmWeKtmuHyjF43hvLZ0ZTzPLcpx2Jo4fMMe6tCh7WONo4J4qvgcfTh49TPctpZrRyZ1pSx1aMmoQhzQp2hKcY1p83uTqRjeEbNq8HNxU4N/wBU9FRqSNwJ+YDuSTySFwMkdRz35HY5qSv57i7q+3l6OS7/AN2/e172as/Y/r8/8vxXZhRRRTAKKKKACiiigAooooAKKKKACocnBGewA5GPy+gOeSckcA9ZqhG3ByeR0wOvX/DJzjqMZINTL4Zf4X13+Net+3r1dmS/Xo+vnZdPn5dmz8n/APguN4zvfAn/AASJ/b01myuLy2m1D4Iax4KeWyEfntZ/ETXtJ+Heo28m6aFfsV3Y+KLi11Ehi/8AZk12UgmlKWz/AJS/8GhXgW00T/gnZ8dvHrJbtqnjj9q7xXZtcQsWmGg+EvhR8IrPSbS63W0ZSa31XUvEl3HGk1xCLa/glUx3D3cI+0f+Dl7WH0j/AIIs/tV2qRM7eINf/Z30QyrOYmtUH7TXwo1qWYqI3NwsyaL9ieDfEPLunmaRlie3f5Y/4N0/jp+zx+y//wAEf/2c774+fHf4U/CN/jf8ePjxZeAofiN438L+CpPE+v2vxIvPDB0XRn17VLNtZvIP7ItpbiWE+XZR6lptndmJ5LJpP9A+DsBmkf2YniLg8ny3G43NOPPpX5Dk/wBVyvC4nG5jmuV8N+G+Ez6lReFy+lXxeIoYHFUcZmHJ7KcaHs6uLap0067+SxM4f66YSVSpGNPC5HVqc1RxhCFStjJ0b885KCc1yx3u7xinJ6H86n/Bx9p37Qmgf8Fd9a+JX7Uvw18eePf2Z7C4+Elj8EdMfUb/AMKeA/GvwS0fw/4c1nx38OfBnxC0vRNWh8L65qvi+/8AG9t4ovZbW88Y6PrOpHWl06fQP+ETz/Zr/wAEn/8Agq1+wj/wUC+G+mfDH9l62Pwe8XfCTwHoVpffsueINJ07w9rfw/8AAehwaV4a0+fwRFo7y+G/FXw80OWTT9BsdS8M3CS6LDLolt4o8PeH7rVdF05/1T8d/D74ffFLwhrvgP4m+CPCfxD8F+IrQ2Gv+EvGnh3RvFHhjW7GR3Eltqmha1ZX+najA/Xyrq2lUEKVAKgj/O7/AGLvDHwk+Gv/AAdTaP4P/YL0xr74FeFvjf8AFTw3Y6b4Z1C7m8M6T4T/AOGd/F2j/GVLTUb261qC68F+FfF9x4pbw3JNdNp1/Bp/h6Hw1LZ3V14fWL9S4c4m4F+mz9FvNPDXiHhTPuAePfoeeBmd8WcGcUcOZ3VqeGWe5Vw/gcFTx2G4r4axlKGCyfiLiupgFVnmeFdTF1K0MyzShjq9LCYjLZcFejieG87jjadeli8Ln+ZUqFejWpr67SnWnV5XRqxbnUo0VLSDtBL2dOUYtwk/6Cv+DsP4iaj4L/4JUaV4WsrqeG3+Lf7THwg8BaxFHGXjvtP0zQPiZ8UYra6fzowkK6n8NdPvlkZJwbq2to/IR5Bcp9a/8G7Pwu0f4W/8Edv2SotOtIIb7x/pPj34peJLyPa0urav40+J/i2+srm8kWCLdNY+G4dA0JEKkxWem21u085jNy/wl/wd3aRqOo/8Eyfg3f2kPnW2gftmfDLU9Ufei/Z7Cb4K/tIaFFPhsNJu1HWrCIImXHnCQjy1mY/pT/wQU8SaH4p/4I+/sPXmg6lbajb6b8L77wxfyW00Mv2TXvC/jrxX4f1zTLgQyv5NzZanp1xBLC5WYKI2liUyFK/JuIlUwv7LTw7jgfaUqeZ/Sy4iq5yqLahWxGF8OcwhgIYudN8tSKpxU6ftk1J0qVSLbjBnoUdeN8Y5rWnkVFUm97PGQU3FPrfR211a1a1/XsEjPOc+oHq2ODnOM9evvzX8Dn/B274D1P4UftmfsL/ta+FLZbTWNa+HGu+FbbWV802//CTfAf4l6f450A38VtLC8c6j4qqYbgyx3V/ZW8lrDOY9KHl/3xjkEenfnsXJGM+2c+mOcEmv5o/+DqL9my5+NX/BMWX4r+H9N+2eIP2ZPix4P+J15NHEr3w8AeIRq3w48ZW8AKljZw3Xivw54l1QRkGGz8Pi8dzbW8618J+z+45wnAX0wvBnF5pVhDJ+KM1zPw+zaNRqKqU+OcoxvDeXwbqVIQlBZzmGWVq0J88alOLhCMqk6cl18V4aWK4ezKML+0oQp4um1dW+q1XWm1ZNu9JTt1UtbtI+Nf8Ag6l/ax0XxJ/wTg/Yq8GeD9QhbTv2sfG/h7432Ui3EVy2ofDbwT8NLbxCkasu0SRS658UvA999uiTbus9q4W4Ofxg/wCCIv7RnxG/4JDf8FOvCfwV/aZij+Hnw3/av+Hvwb8PfERNUuli0DQU+J/hDQ/iL+z98SbvVJY7az8rwxqHjE+DvF+ofazofhmHxJ4//tG8muvD0ki/EPgLx58XP+CtPx9/4JR/sQ63b6vJofwj8G/D/wDZZih0p5JzafD7TPiR4k1vx18R7SLfO1nJ4d+CWn+HbLUFYRW0cHgOGaGGOBjI39zH/BbT/gh14W/4KeeA/AvjH4N634R+E/7THwf0P/hEPBmv+IrXUbfwJ44+G3m3d1B8NfG11oGl6pquiWmg6ldTav4R8R6bpGqvost9rulXGgXllq8V9a/6Z5pX8JfofeFnAP0GfHaeAwnC3jdgvHbMPFDivDwr5liuCp5jxrhMD4L8fUKlCWJ58FQw+QTqYqhGjKvha2CwGaYynCphMVhZfFU1j8/x2M4lytTlXyx5XDB0JWgsSoYepLMMK0+V87dRcsr6qc6cZS5lUP53f+C9WuXH/BRH/gu/+zd+w14Eng1TTvAR+C/wC1240xoLhLHxH8SfEp+IfxU1w6hA8ZltvCPgXxBoserWNvcyzaZqfhrX7JFXW2urBf8AQsCDbgkccdDjALDIOf8Ad44PXtk1/Jv/AMEQ/wDg36+Lf7D/AO0l4w/bG/bf8YfDz4gfGHS7DVtL+DeleCvFHibxnFoeseK7a6sfHHxU8WeJ/Evhjw5dXfi690ae+8MaFa2638UWl654l1TVr19YuNIhtf60MD0H5f8A1/8APvX+c30zPEPw6zPD+BfgN4R8W4TjzgH6PPhz/q/HjPAYavRyvifjvirFUM045zrK/rPNiJYPF1suylTjz/V8PmFPHYLCU/q1CGJq/Y8OYPFxebZpmOHeGxebYtVHhpNOdHDYdVKeGpzcXbmSnNrry8kpNybP50/+Chf/AAbufAr/AIKHft1eEv2v/HXxw8X+CPDs3h/wlofxn+EPh3wnptzd/E9fBiXdjotxovxGl160uvh++oaIum+H9fY+F/El1cadp8Uug3miak7Xw9E8Of8ABtR/wRa0FbGSf9k3UvEN7YzLN9v8Q/tA/tLXb3kiyyMgvtLsvi3Y6FdQr/qzbNpAt5UAjuI5CWLfvNsQdFX/AL5H0/z/ADPWl2r/AHR7cD/P+epr8bl9KP6Sy4V4V4Iwnjh4h5RwrwXlGHyDhnI+HuJcbw7hMvybCxlTw2CqPJXg62YRw1FrDYapmFWvUoYKGHwVKUcNQoxPR/sLJ/b4jESy3B1K2JqOrWqVaMaspzbbcv3nMoXfvNQSvJtyu7t/lP8AAv8A4Ipf8EyP2aP2jvDX7UvwQ/Zo0nwF8VPB2mX2n+FLyw8Y/ES/8MaDd6hpF7oN54h0zwbrPirUfDlv4jl0S8u9LOsCw81Irie/jRdcml1R/wBT+cevK5P4jn8T29xyADmyAB0AH0AHTOP8+55POYezcA+nbJBb19eOOuSM528/lPF3GnG3HeMw2Z8ccXcR8X5jgcvoZRgcw4lznMc7x2DyrDYjFV8Pl1DFZhiMRVpYKjWxWIrU8PBqEa1evUblUqVJHdQwuGwsJU8NQpUITm6koUKcaalUacXNqCScmuVXetlHVqLa/h5/4PL9VvobL/gnJoaSAWF/dftcandQeWh8y90iH9mazsJfM2iSMRQ65foY0ISTzw0iM0aCv3q/4Jz/APBI7/gnh+znpnwa/aw+FX7POh6Z8c/E3wf+HOqyePdW1/xj4jOi6xr3w60eLxJrHg3w34g1/UfDXgnVPEf2i+bVdR8MaRp108epanp1pLBpF1caef5J/wDg5U8Tf8FCP2lP2+9D+CnjX9mLxrZfCP4Q+Itf8IfsiXvg74YeM9ag+K1n8TrL4fy6/wCIIPGtnBqWleMfEfiTVPC+i23/AAjmiCzl8IraQ+HNR0p9ch1PU7n/AEPPhh4TTwF8NPAHgaOCK3Twf4M8K+Fore3nnuYIU0HRLPShDBc3JNzcxRC1CRT3JNxLGFknJndjX+iHj9mnGHhN9A76FHhvlHiKsHieKsu8c874yyjgTjV4jL814c4o4pybiPJct4op5NjYwxcqGC4iWExeX46Djh8yp5rlqlU9hj4v4/KqWHzDiniXF1MFzqg8sp4episNyyhWoUatGpUo+0jePNOipKad5QdKdl7sn26qFBUKME84OATubsBwTnGcjvgkE00Iq7wFAyMsVABZskEkDqeOp9uSTzMAPmOD0zg5z96Trkn8Pan7V9B+Q/z/AJ61/mVKk3GUedu7juo2snJtO0E3e6fvNtNJpp6n29t/uvbXr1v/AF7vZ3/zYP8Agoz8b/Hf7AP/AAcm+OP20Pj38C/E/i3w74f+Iuj/ABC+HfhptUPhez+J/gXTfgDYfC/wPr/hTxjqGk69p9xZ6Bf2GnTamtrbXP2DV9GvvC90lhqMbBP2b0P/AIPE/wBkC4imbxN+yJ+0jpMw8nyI9C1r4T69E+5ZPtHnS3/i7w20HlMI/I8uKYTozu/kuojP9XnxI+DXwd+Mul2+ifGH4UfDj4q6PaNK1rpHxI8CeFfG2l2zztA0729h4m0nVLWFpmtrdpWjiUyNDblyzRRkfH2s/wDBJn/glz4glhmvf+Cen7IED28bRIujfs6/Cjw9EVLlj50GgeFNNhuZAc7ZbiOSVVIUOECrX+kmI+lD9ErxR4L8Lsp+kJ9Hbj3N+K/DHw84c8Mstz3w98TK2SZViOHuGqdSngKsMmxEadLC4nEOrWq4n+POPtlQjialHD4ZR+NWRZ/gcRj55Rm2Fp0Mbi6uNnTxWDVSoq1Vty/eLmcox05dl1cVK7P5Hfj5/wAHJ3/BSL9uz4q2fwL/AOCSf7PHin4eyziG/tdQtvh3oPxu+Pms2FnPAt7qer6Rf6T4q+GHw58HRNeQ2ms3Oo6Vrgsx9k1KXx9paTvZD9X/APggZ8If+C1Nl8bf2lv2gf8Agpp8Rfi3Z/D3x/oCaV4Z+EXxg8WWWq3mpfFGfxLpWpy+PvA/gDRNSu/Dvwd8J+GdA0/VvDR0Pw/pnhrSfEDa7p39naDJpvhrTrpf6EPgR+yz+zT+y54f1Pwz+zl8BfhP8E9F1q6XUNdsPhj8P/C/g4a9fp5qw32vz6Dpljca5dwQ7ba1uNWluprWyWOxtpI7KGC2X3cIgBGFCkDI2YDZ3Z4Bx9ceoDcAE/mvij9KDwrxfAXEvhF4B/Rl8O/Dbg3PsFleAxfHPEtKXF3jJjqODx9HMsRVr8S4zmp5dVxuMwtK8sHUqSo0fbKjKLqqnHswOR4+OLo4/Nc6xWMxFKU5xw1C2Hy6LcJU4pUItOSUW3aWjb1d+ZycACDk4wQDnqeW7nkdB9fmyABzi6reWmm6XqOpX86W1lp9nd399dSFlht7O1gmnuLmUqCdkMEMkjYBOwNwSDnYJGT046cD1YdPqo5yeGHHHP4z/wDBdP8Ab80r9gL/AIJ6/FXxLpWuLZ/GP4y6fqfwV+BdhA8T6kvjLxbpGoW2s+NUilEwSw+G/hltT8UyXVxazabNr9v4b8OXrRSa5ZMf5R4A4Ez3xV8QODPDfhfCVcfn3GXEGXcP5dQwyhKXtsdi6NKpiKrlzRo4fBYd1cbjMRUTp4bBUcTiqy9hSrTj7uMxVHA4TE4yvJRpYelOpOTva0FU5YrW7cpJRgk9ZtpNzkkfzQf8Gclldv8AtLftuXsdvM1lafBb4Y2dzdIjeRDdX3j3X5LK3kfBVJbuPTL54UYhnS3nZBtjc1/f7X8j3/BpT+xj4g+Dv7Jfxe/a/wDGcF7puo/tUeJdD0T4f6ZdmSNW+EnwivPEum2niw25ELpN4w8Z6/4shgF5FKsmgeHvD+t6Rcmx1qdpf64a/q79ohxZknF/0yfGPE5BjaeY4HJMTw3wlWx1G/sKub8McMZXk2fUKTcnKSy/OMLjsBOVownVw9WpSU6MqdZ+Jwfh6uH4dwMasXCVVVcQovdQrV6tSk3/AI6fLNJ3aUkm1Zplf58f7Azr8Gf+Dtr4/eDr12tT8SPjv+21ax/2i0E0kjeOPB3xD+NNhHDcW7W0Nt9sazhGnpMk0whlg0m4Euqyi6r/AEHK/wA+n9qwzfC7/g78+GOveGpPJuPF3x4/ZUkvYwXhjgXx38APAHgDxOkbwSpI/wDaNhdajezmRik11f3MU8cloWif6X6Bsf7ah9L3gW7pvij6IHi/Wp12ounSrZTUyGnRlKLV3JTzONaH2f3M4v3pXOfiq9N5Bilb9xn+ATWt2qjrXstekPX3k+a8Wn/oFoTyD2Axx6Fxz79fXjGcnJq3UCYPuO/0BbnpkcbfcjjOc1PX8AUI8sJK99V+Da26Py3XVt2a+sXXzt0ttfu/Lytpq76lFFFbDCiiigAooooAKKKKACiiigAqLP3h6dz1xnHpnnqe+eDkVLUHRST0BGTn0L8cZ64+nA6k5qJNxi2tej1Stq0nqvNPe9r6tqKFe33X2fR/5a+vVs8i+Pfxw+H/AOzT8D/ir8f/AIp6m2leAvhJ4J8SePfFV3H5bXTaV4e067vZbHTLeaaBL3WNWaCPTdE05ZVm1HWbuy063Yz3Ea1/n/8A/BOr4F/F3/g4T/4K0/ED9tr9pvRJI/2cfg/4j8O+KfFPhi4+1XXhUaFo91dyfBP9l3w5dXCpDfWsiWzeIfiXNbWqQ6hpMfizU9XttN17x5o1zJ69/wAHAX/BYHxP+3D8R9T/AOCUH7H/AIO8VXGiaV8e4PhZ8UNab7DHrHx3+L/hDx7N4X0H4Y+CtIjmmWHwHpPxDsra/TX9QvYbzxd4k03QryytNN8J6bNqOqf1r/8ABJb9gXR/+Cbn7Dfws/Z1J0q++ITLd+PPjb4m0nL23ib4weK1tbjxNNbXbQwPfaV4as7TS/BHhu8lgt57nwx4d0e5uraO+luhX+nXDWWZl9Bv6Kub+I2c4Shkn0j/AKTOBqcLeGlCriIPiPw78E6mEw+M4i4xhRw1WTyrMuKZ1cBRwM8ROGMoP+wMbhEq2DzvBHxFadPifPYYOnKVXJ8lmq+Mkk/Y4vMVKoqNC7TVSFBKbko3i71Yt+/Tmfn1/wAHSPjOXwn/AMEfviR4ehvIrZPiN8YPgX4MuYHW7LX8Fh46j+IIs4WidYkkjuPAlvqDNeiS2MVrKiIL57KUek/8G0ngyHwh/wAEZP2X7v7G1pqPjbWfjx401feYXa4muf2gfiZoej3QaIsNlx4Z8P6E6LIzTRxssUoRkWBPmn/g7QI/4dX+Fff9qf4SduuPB3xaP6HB+p6kivuL/g3y/wCUNf7EnT/kS/iD6f8ARcPij/k+5OcnJP53nCeA/ZacH/VWqP8Abf0vczlmTpaPExwfhXmsKEK+iVSMHh6Eo9YunTtZKz66fv8AHGJ5nf2XD8OS+vK5Y6F2tdL3d73vd69/2YDHGAePu4/GTn0/gb35HU5qeoB34z+fo3v7Z/AjJyanr+CabunrdWjbfS/N3fptpr3Ur/WhRRRVgFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUVFk4PJ7c89iQMcnHvjknGScZpbJ+S+/wCLz/ur/wACWrtqf1+Xn8/v6ktf5fH/AAcC/tf+Jv8AgoH/AMFHviv4L8A6smsfBn9jPwz40+HfhEwzySeHftng8fbPjZ4/eaCK7torrxX46s7XwJomoRTf2br1j4f+HscM0N3qMrH/AEO/+Cg3xt8Vfs4fsH/tffHjwSceMPhX+z78W/GfhCZ3AW08UaN4N1y48P38m5ZBJHp+qR2t9LDt/fRQm3DqXEg/yvfAt14T+H3/AATb/aO+JOpXsGr/ABf/AGn/ANoD4ffs6aO17PO2sab8I/hRbaR+0R8Z9fluJjJJqMniT4g3XwAtWEjlkksJb65ufO+xxN/r3+yd4DwWE4o4y8esTlcc6zrIM94N8IuAMsdL6xOlnfiBj1U4x4nhSi3KnPhLg3AYvHSnVjHD1sqxGdUamJpJykfnnHmKlKjh8qjN06dWniMfi53snTwqksNRd9GsRiXGNt1NU3FSkmf1mf8ABnV8ErrR/gf+2h+0ZcxyiL4g/E74bfB/RmljKBIPhX4Y1fxfrlxaSFEaSHUbn4u6VbXMgkkhNxo4ijKTxXQb+0Kvxd/4N/P2frj9nP8A4JIfsn6Dqlj9i8R/Erwvqvx08SNJbm3uLiX4ueINR8Z+GBexSIsqXVh4BvfCWkXAnJlV7Ly8oiJbL+0Vfw19MrxBj4p/Sy8fONqGIjicFi+OsdkeV1qUlLC1co4Qpx4RyuvhJRnOE8PisFklDFQqwajX9r7dpSqSv9Rw3hPqOQ5bhmnGSw1OrNNe97Su516ifZxlUcbPayV1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''Driven matter'' refers to a type of [[bulk matter|Bulk matter]], often [[soft condensed matter|Soft matter physics]], to which energy is being applied in a way that significantly affects some of its degrees of freedom. It is thus a driven system, in the sense of [[Control theory and control systems]]. It is closely related to [[Active matter]].
Or ''Unmanned aerial vehicle''
[[Drones Can Defeat Humans Using Artificial Intelligence|http://thedronenews.com/2016/06/29/drones-can-defeat-humans-using-artificial-intelligence/]]
A [[Regularization]] method for [[deep|Deep learning]] [[neural networks|Artificial neural network]], which works by dropping out random neurons/nodes in the network, while training. This avoids [[overfitting|Overfitting and underfitting]] by forcing the network to learn more robust models, that tend to be simpler.
[[How does the dropout method work in deep learning?|https://www.quora.com/How-does-the-dropout-method-work-in-deep-learning]]
[[ Dropout: A Simple Way to Prevent Neural Networks from Overfitting |http://jmlr.org/papers/v15/srivastava14a.html]]
See also [[New advances in deep learning]]
[img[Rational_scale_to_assess_the_harm_of_drugs_(mean_physical_harm_and_mean_dependence).svg]]
"""
Alcohol
Cannabis
Benzodiazepines
Cocaine
Drug related anxiety
Drug related infections
Drug related mood
Drug related personality
etc.
"""
See [[Active matter]]
[[Continuous descriptions for dry active matter by Eric Bertin|https://www.youtube.com/watch?v=ODAYXt0icI4]]
[[Dual process theory|http://videos.syntience.com/other/sta-dpt.html]]
[[Thinking fast and slow]]
[[Emotion]]
[[Model-free method]]s
[[Duffing oscillator|http://www.scholarpedia.org/article/Duffing_oscillator]] is a [[nonlinear oscillator|Nonlinear oscillations]].
$$\ddot{x} + \beta \dot{x} + x + \delta x^3 = \Gamma \cos{\omega t}$$
__Physical meaning__
<!--For $$\beta >0$$-->
The oscillator corresponds to a nonlinear spring with either //hardening// for $$\delta > 0$$ or //softening// for $$\delta < 0$$ (for amplitude not too large, as then it's motion becomes unbounded).
<!-- The thing below is for when the normal harmonic term has a coefficient in it, which we are not considering here (for the MMathPhys miniproject)
For $$\beta < 0 $$ and $$\delta > 0$$, the system is repelled from the origin at low amplitude, and attracted to it for larger amplitude, which can be realized by a steel beam fixed in one end and deflected by two magnets symmetrically placed to the sides of the other end.
-->
!!__''Free'' (unforced) Duffing oscillator__
!!!__Free ''undamped'' Duffing oscillator__
|$$\Gamma = 0$$ | $$\beta = 0$$ |
The system can be integrated to obtain an energy, and the system is then a ''Hamiltonian system'':
$$E(t) \equiv \frac{1}{2} \dot{x}^2 + \frac{1}{2} x^2 + \frac{1}{4} \delta
x^4 = \text{const}$$
!!!__Free ''damped'' Duffing oscillator__
When $$\beta > 0$$ , $$E(t)$$ satisfies:
$$\frac{d E(t)}{dt} = - \beta \dot{x}^2 \leq 0
$$
One can easily show that this is indeed a ''Lyapunov function'' and the origin is globally asymptotically stable
!!__''Forced'' Duffing oscillator__
More interesting. Nonlinear resonances. Shows chaotic behaviour, intermittency (jump phenomena), etc. See Lakes of Wada..
!!!__Nonlinear resonances__
Treat with multiple scales method
__Primary resonance__
__Secondary resonances__
//Subharmonic//
//Superharmonic//
!!!__Onset of chaos__
__Period-doubling cascade__
//Reverse period doubling and reverse cascade// (bubbles)
__Intermittency__
Lakes of Wada
Other?
https://en.wikipedia.org/wiki/Dynamic_programming
!!!__[[Properties we need|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=4m]]__
*Overlapping subproblems -> memorization: record value 1st time it's computed, then look it up subsequently. Table lookup
*Optimal substructure: global optimal solution can be constructed from optimal solutions to sub-problems.
[[video|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=2m30s]]
[[Dynamic Statistical Encoding (Ep 6, Compressor Head) Google|https://www.youtube.com/watch?v=3RLau7mWdUg&list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H&index=8]]
[[Dynamical Instability in Boolean Networks as a Percolation Problem|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.109.085701]]
[[pdf|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.109.085701]]
[[Phase Transitions in Complex Network Dynamics|http://drum.lib.umd.edu/handle/1903/15248]]
[[A connection between the percolation transition and the onset of chaos in the Kauffman model|http://iopscience.iop.org/article/10.1088/0305-4470/21/10/025/meta]]
[[Percolation and spreading of damage in a simplified Kauffman model|http://www.sciencedirect.com/science/article/pii/0378437188901008]]
[[Activities and Sensitivities in Boolean Network Models|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.93.048701]]
[[Core Percolation and Onset of Complexity in Boolean Networks|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.96.018101]]
Annealed approximation: [[Random Networks of Automata: A Simple Annealed Approximation|http://iopscience.iop.org/article/10.1209/0295-5075/1/2/001/meta]]
Boolean functions in [[Boolean network]]s are represented by a truth table, that in turn can be represented by a $$2^K$$-length vector/string of $$0$$s and $$1$$s, for a $$K$$-input truth table. $$2^K$$ is the number of possible inputs, i.e. the cardinality of the set $$\{1,0\}^K$$. The bit string can be interpreted as a binary decision tree.
!!!__[[Activities and Sensitivities in Boolean Network Models]]__
The average sensitivity (when averaged over all the functions in the network) appears to be a good parameter for predicting whether the dynamics of the Boolean network are ordered or chaotic
[[Activities and Sensitivities in Boolean Network Models|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.93.048701]]
!!!__[[Random Boolean networks: Analogy with percolation (Stauffer)]]__
Some interesting analogies, investigated via computer simulations, between percolation and properties of Kauffman Boolean networks in a 2D lattice
[[Random Boolean networks: Analogy with percolation|http://www.tandfonline.com/doi/abs/10.1080/13642818708215325]]
-----------------------
Connection between sensitivity and complexity of GP map of Boolean networks.. [[MMathPhys oral presentation]]
Relation between Kolmogorov complexity and sensitivity of a Boolean function.
Sensitivity <> constrained/unconstrained, coding/non-coding, etc.
------------------
//More references//:
<small>
[[A geometrical interpretation of the chaotic state of inhomogeneous deterministic cellular automata|http://www.sciencedirect.com/science/article/pii/0378437189904433]]
[[The role of certain Post classes in Boolean network models of genetic networks|http://www.pnas.org/content/100/19/10734.short]]
[[Boolean Dynamics with Random Couplings|http://link.springer.com/chapter/10.1007/978-0-387-21789-5_2]]
[[Isomorphism of Quasispecies and Percolation Models|http://www.sciencedirect.com/science/article/pii/S0022519399910366]]
[[Spectral theory for the robustness and dynamical properties of complex networks|http://dl.acm.org/citation.cfm?id=2521256]]
[[Phase Transitions in Two-Dimensional Kauffman Cellular Automata|http://www.lps.ens.fr/~derrida/PAPIERS/1986/stauffer-epl-86.pdf]]
[[Phase transition in cellular random Boolean nets |https://hal.inria.fr/file/index/docid/210412/filename/ajp-jphys_1987_48_1_11_0.pdf]]
[[The Physics of Structure Formation: Theory and Simulation|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/%5BD._J._Amit__(auth.),__Professor_Dr._Werner_G%C3%BCtti_the%20physics%20of%20structure%20formation.pdf]]
</small>
//How things move//
A space (in the mathematical sense, for a continuous space, one often uses a [[Manifold]], or a [[Topological space]]), with a [[Function]] (a.k.a. a map) that describes how a point in the space evolves (in "time").
!!__Types of dynamical systems__
[[Measure-theoretical dynamical system]]
[[Topological dynamical system]]
''[[Continuous dynamical system]]'' are dynamical systems where the space is continuous. It is often represented as a system of 1st order O.D.Es. Linear dynamical systems (O.D.E.s linear) are easy to analyze, and can be analyzed by looking at the eigenvalues of the Jacobian.
[[Discrete dynamical system]] are those where the space is discrete. They are often represented as systems of difference equations (see [[Nonlinear maps]]).
[[Measure-theoretical dynamical system]]
[[Topological dynamical system]]
The richest class of dynamical systems are [[Nonlinear system]]s
A dynamical system, whether continuous or discrete, can be partitioned (''coarse-grained''), so that its dynamics can be studied as [[Symbolic dynamics]]. If the system is a [[Probabilistic dynamical system]], then the coarse-graining gives rise to a [[stochastic process|Stochastic processes]]
!!__Deterministic vs probabilistic dynamics__
Dynamical systems generally describe deterministic processes. Probabilistic processes are described as [[Stochastic processes]]. However, these can sometimes be described as deterministic dynamics of probability distributions, or as a probability measure over a deterministic process (i.e. a [[Probabilistic dynamical system]]).
--------------------------
[[See Wiki page for good intro and different kinds|https://en.wikipedia.org/wiki/Dynamical_system_(definition)#Geometrical_cases]]
!!![[Encyclopedia:Dynamical systems|http://www.scholarpedia.org/article/Encyclopedia:Dynamical_systems]]
Dynamical systems on complex space (particularly [[discrete|Discrete dynamical systems]] ones): [[Complex dynamics]]
[[Nonlinear Dynamics 1: Geometry of Chaos by Predrag Cvitanović (ChaosBook course)|http://chaosbook.org/course1/Syllabus.html]]
https://en.wikipedia.org/wiki/Floquet_theory
[[Turing instability|http://www.math.lsa.umich.edu/~rauch/256/turingexample.pdf]]
[[Fixed Points|https://www.youtube.com/watch?v=csInNn6pfT4&t=2s]]
-------
[[Oxford notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/25/7_copy.pdf]] [[Network science]]
[[Discrete Dynamical Networksand their Attractor Basins|http://uncomp.uwe.ac.uk/wuensche/downloads/papers/complex98.pdf]]
See [[Discrete dynamical systems]]
See Mason and Gleeson tutorial article
See also [[Temporal networks]]
!!__Deterministic processes on networks__
[[Graph dynamical system]]
[[Epidemics on networks]]
!!!__Type of update rule__
Two main types:
* __Synchronous updating__: all nodes at the same time.
* __Asynchronous updating__: Nodes at different times.
** Serial updating. Only one node is updated at a time.
*** Random serial updating. The node is chosen at random.
*** Sequential serial updating. The nodes are chosen in a fixed sequence.
!!__[[Random processes|Stochastic processes]] on networks__
[[Probability on Graphs |http://www.statslab.cam.ac.uk/~grg/books/USpgs-rev3.pdf]]
[[Critical phenomena in networks]]
[[Percolation]]
[[Random graph]]
[[Directed percolation]]
[[Epidemics on networks]], [[Population dynamics]], [[Random walk in a graph]]
[[Chemical reaction network theory]]
!!__Applications__
[[Systems biology]]
See [[Boolean network]]
See [[Dynamical Instability in Boolean Networks as a percolation Problem]]
[[Dynamics of Boolean Networks|http://arxiv.org/abs/1307.0757]]
[[Dynamics of Boolean Networks: An Exact Solution|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.106.214101]]
[[Influence and Dynamic Behavior in Random Boolean Networks|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.107.108701]]
[[Dynamics of Complex Systems: Scaling Laws for the Period of Boolean Networks|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.84.5660]]. Relation between the (expected) period of a [[RBN|Random Boolean network]] and the number of nodes $$N$$. Using some numerical and analytical results, they find a power law relation.
[[What Darwin didn't know: natural variation is structured|https://docs.google.com/presentation/d/1l-IgqXy1ZdBn__aBQX0fUH8Z2y6iuogwt753omsiyAw/edit#slide=id.i0]] GP map bias in Boolean networks (see [[MMathPhys oral presentation]])
[[Guiding the self-organization of random Boolean networks (RBN)|http://link.springer.com/article/10.1007%2Fs12064-011-0144-x]]. <small>Quote from article: It is useless to enter an ontological discussion on self-organization. Rather, the question is: when is it useful to describe a system as self-organizing? [...] A model cannot be judged independently of the context where it is used. I've always agreed with this philosophy. Things like //self-organizing// or //complex// are perspectives on systems, not hard classifications schemes.</small>
Can explore RBNs with [[RBNLab|https://sourceforge.net/projects/rbn/]]
Since RBNs are finite (they have 2 N possible states) and deterministic, eventually a state will be revisited. Then, the network will have reached an ''attractor''. The number of states in an attractor determines the //period// of the attractor.
Point attractors have period one (a single state), while cyclic attractors have periods greater than one (multiple states, e.g., four in Fig. 2)
[img[https://static-content.springer.com/image/art%3A10.1007%2Fs12064-011-0144-x/MediaObjects/12064_2011_144_Fig2_HTML.jpg]]
Figure 2.
A RBN can have one or more attractors. The set of states visited until an attractor is reached is called a transient. The set of states leading to an attractor form its ''basin''.
The basins of different attractors divide the state space. RBNs are //dissipative//, i.e., many states can flow into a single state (one state can have several predecessors), but from one state the transition is deterministic toward a single state (one state can have only one successor).
The number of predecessors is also called //in-degree//. States without a predecessor are called “Garden of Eden” (GoE) states (in-degree = 0), since they can only be reached from an initial condition. Figure 3 illustrates the concepts presented above.
[img[https://static-content.springer.com/image/art%3A10.1007%2Fs12064-011-0144-x/MediaObjects/12064_2011_144_Fig3_HTML.gif]]
<small>Fig. 3
Example of state transitions. B is a successor state of A and a predecessor of C. States can have many predecessors (e.g., B), but only one successor. G is a Garden of Eden state since it has no predecessors. The attractor C→D→E→F→CC→D→E→F→C has a period four</small>
One of the main topics of RBN research is to understand how changes in the topological network (lower scale) affect the state network (dynamics of higher scale), which is far from obvious.
RBNs are generalizations of Boolean [[Cellular automata]] (von Neumann 1966; Wolfram 1986, 2002), where the states of cells are determined by K neighbors, i.e., not chosen randomly, and all cells are updated using the same Boolean function
~ ~ ~
The self-organization of RBNs can also be interpreted in terms of complexity reduction. For example, the human genome has approximately 25,000 genes. Thus, in principle, each cell could be in one of the $$2^{25,000}$$ possible states of that network. This is much more than the estimated number of elementary particles arising from the Big Bang. However, there are only about 300 cell types (attractors (Kauffman 1993; Huang and Ingber 2000)), i.e., cells self-organize toward a very limited fraction of all possible states.
There are several regimes. In the //critical regime// near in-degree (in topological network) 2: Few nodes have many predecessors, while many nodes have few predecessors. Actually, the in-degree distribution (in state network, I think) approximates a power law ([[Wuensche 1998|http://uncomp.uwe.ac.uk/wuensche/downloads/papers/complex98.pdf]]).
-----------------
See also [[Dynamical systems on networks]]
[[Dynamics of Droplets|https://books.google.co.uk/books?id=MznvCAAAQBAJ&pg=PA163&lpg=PA163&dq=droplets+on+very+smooth+surface&source=bl&ots=nEAm8Mnhmz&sig=iBlgEInD42CfzU4tgwzPn9UcTyc&hl=en&sa=X&ved=0ahUKEwjfu7es2NrQAhWFF8AKHeMxCJUQ6AEISTAL#v=onepage&q=droplets%20on%20very%20smooth%20surface&f=false]]
See [[Surface tension]], [[Surface science]]
https://www.quora.com/Why-some-water-drops-never-roll-down-from-a-vertical-or-sloping-surface/answer/Guillermo-Valle-1?prompt_topic_bio=1
[[non-equilibrium|Non-equilibrium statistical physics]] dynamical properties of [[Spin glass]]es.
!!__"Remanence" behaviour__
As we’ve already seen (and discuss more fully in
section 4.8), a spin glass in the absence of a magnetic field has zero
magnetization. But it shouldn’t be surprising that when placed
inside a uniform magnetic field, the atomic magnetic moments
will try to orient themselves along the field—as occurs in any
magnetic system—resulting in a net magnetization. So far not
very exciting; but what then happens after the field is removed or
altered?
There are any number of ways in which this can be done, and
in the spin glass they all lead to somewhat different outcomes.
One approach is to cool the spin glass in a uniform magnetic
field H from a temperature above T f to one well below, and
then remove the field. On doing so, the spin glass at first retains
a residual internal magnetization, called the ''thermoremanent
magnetization''. The thermoremanent magnetization decays with
time, but so slowly that it remains substantial on experimental
timescales.
Another procedure is to cool the spin glass below T f in zero
field, turn on a field after the cooling stops, and after some
time remove the field. This gives rise to the ''isothermal remanent
magnetization''.
!!__Memory effects__
In the simplest of these, a spin glass is cooled to a temperature
below T f in an external magnetic field, often through a deep
thermal quench. The spin glass then sits at that fixed field
and temperature for a certain “waiting time” $$t_w$$ . After the
waiting time has elapsed, the field is switched off and the decay
of the thermoremanent magnetization is measured at constant
temperature. Interestingly, the spin glass “remembers” the
waiting time: a change in the rate of decay occurs at a time
roughly $$t_w$$ after the field is removed. Aging is not confined to
spin glasses, but their unusual behaviors make them somewhat
special.
!!__Theory of non-equilibrium behaviour of spin glasses__
all share the features of a wide
range of relaxational processes, leading to a broad distribution
of intrinsic relaxation times; a significant amount of metastability,
meaning that most relaxations, whether involving a small or large
number of spins, can only occur after the system surmounts
some energy or free energy barrier; and a consequently compli-
cated “energy landscape,” the meaning of which is discussed in
section 4.9.
------------------
[[Spin-Flip Dynamics of the Curie-Weiss Model: Loss of Gibbsianness with Possibly Broken Symmetry|http://www.rug.nl/research/portal/files/2826562/2007CommMathPhysKulske.pdf]]
Edwards and Anderson (who introduced the [[Edwards-Anderson Hamiltonian]]) asked what kind of ordering the spin glass phase, should it exist, would exhibit.
Their proposal was that the spin glass is disordered in space, but that at the same time, they are ''ordered in time'', representing the “frozenness” of the spins in the spin glass phase. That is, if you measure a spin on a particular site as pointing in a particular direction, wait an arbitrarily long time, and take another look, you’ll see the spin still pointing in that direction. On the other hand, if there is no true spin glass phase, then the time correlation of spin orientation at any given site should gradually decay. This decay would be very slow, similar to the arrested, but not permanently static, flow of atoms in a glass.
[img[Selection_617.png]]
This happens if the ground state is not invariant under the flip of a spin, i.e. there is "broken spin-flip symmetry" (Note that the symmetry is {flipping all spins simultaneously}, not flipping them individually!). Of course, this is true in the ferromagnetic and antiferromagnetic and other magnetically ordered phases as well: it is the lack of any obvious spatial order, coupled with the ordering in time, that sets the spin glass apart.
Actually, it turned out there is an infinity of order parameters, see [[Replica symmetry breaking]]
!!__[[Early-onset familial Alzheimer's disease|Familial |lzheimer's disease]]__
The planet Earth as a system. Also known as ''geoscience''.
[[Hydrology|https://en.wikipedia.org/wiki/Hydrology]]
[[Topography]]
[[Climate]]
[[Geology]]
[[Ultrasound imaging]] for the [[Heart]]
Have to avoid [[Rib]]s
Ecology (from Greek: οἶκος, "house", or "environment"; -λογία, "study of" [A]) is the scientific analysis and study of interactions among organisms and their environment (see also [[Environmental studies]])
!!__Ecological modelling__
Uses [[Systems biology]] to understand ecosystems.
This has been used for [[Policy]], for instance for [[Fishery]].
!!!__[[Population dynamics]]__
See [[Dynamical systems on networks]], [[Epidemics on networks]], [[Dynamical system]], [[Chemical kinetics]]
Trophic cascade
__P2P__
http://www.fermat.org
[[Georgism]]. Don't tax on the wealth owned by the results of your work/labour. Tax on the wealth owned independent of your labour, namely natural resources. But, increasingly, second-natural resources, like robots.
''Economics'' is the [[social science|Social sciences]] that describes the factors that determine the production, distribution and consumption of goods and services. It also includes the methods used for the purposeful [[Engineering]] of such processes, in a complex [[Society]].
An [[https://en.wikipedia.org/wiki/Economy]] (Greek οίκος – "household" and νέμoμαι – "manage") is an area of the production, distribution, or trade, and consumption of goods and services by different agents in a given geographical location.
[[Macroeconomics]]
[[Microeconomics]]
----------
//Economic and product cycle//
[img[https://upload.wikimedia.org/wikipedia/commons/d/d7/Product%E2%80%99s_lifecycle.jpg]]
Diagram of a ''product cycle'' (showing the main phases in the life of a product).
The ''economic cycle'' involves the product cycle, plus steps that control the product cycle, which involves systems like markets.
!!__[[Raw material extraction]]__
!!__Production of goods__
[[Industry]], the production of goods, often by processing raw materials ([[Manufacturing]])
!!__Distribution of goods__
[[Transport]], [[Trading]], markets
!!__Consumptions of goods__
Demand, use, [[Culture]], trends, necessity, [[Psychology]]
!!__Disposal and recycling of goods__
Disposal, [[Recycling]]
---------
[[Economic sector|https://en.wikipedia.org/wiki/Economic_sector]]
* Primary (raw materials)
* Secondary (manufacturing and processing)
* Tertiary (services)
Quaternary: [[Data & Knowledge]], information services
Quinary sector: human services
Economic development correlated with an increase in the complexity of the economic activity.
--------
See also [[Resource management]].
__Tax heavens__
https://panamapapers.icij.org/the_power_players/
https://en.wikipedia.org/wiki/Grundrisse
http://motherboard.vice.com/read/the-future-of-robot-labour-has-everything-to-do-with-capitalism
http://wol.iza.org/articles/who-owns-the-robots-rules-the-world/long
[[Theory of spin glasses|http://iopscience.iop.org/article/10.1088/0305-4608/5/5/017/meta]] -- [[Theory of spin glasses. II|http://iopscience.iop.org/article/10.1088/0305-4608/6/10/022/meta]] asserted that the essential mechanism underlying spin glass behavior was the presence of both ferromagnetic and antiferromagnetic interactions that were quenched randomly in place.
place all the spins on a three-dimensional cubic lattice. Then the Edwards-Anderson (hereafter EA) Hamiltonian is
$$\mathcal{H}_\mathcal{J} = -\sum\limits_{\langle x, y \rangle} J_{xy} \mathbf{m}_x \cdot \mathbf{m}_y - \mathbf{h} \cdot \sum\limits_x \mathbf{m}_x$$
,,where $$x,y$$ denote sites in the cubic lattice and the notation $$\langle x,y \rangle$$ means that the sum is over nearest-neighbor (i.e., adjacent) sites only; $$\mathbf{m}_x$$ denotes the localized magnetic moment (or, more simply, spin), which for now we treat as a classical vector, at site $$x$$; $$J_{xy}$$ is the magnetic coupling between nearest-neighbor sites $$x$$ and $$y$$;and $$\mathbf{h}$$ is a uniform external field (which could be zero) acting on the system. ,,
An even simpler formulation is to treat the spins not as vectors, as in (4.2), but as simple binary variables taking on the values $$\pm 1$$ only. This is known as the ''//EA Ising model//'':
$$\mathcal{H}_\mathcal{J} = -\sum\limits_{\langle x, y \rangle} J_{xy} \sigma_x \cdot \sigma_y - \mathbf{h} \cdot \sum\limits_x \sigma_x$$
The difference with the [[Heisenberg Hamiltonian]] is that ''the couplings $$J_{xy}$$ depend on the particular edge $$\langle x, y \rangle$$'' and are chosen randomly and independently from a probability distribution, at the initial time, and stay fixed thereafter ([[Quenched disorder]]). On the $$\pm J$$ model, there are only two possible values of $$J_{xy}$$. An important question is <span style="color: #fad;">which properties depend on the specific realization and which don’t?</span>
,,The EA Hamiltonian is a very simplified model. If you wanted to faithfully model a dilute magnetic alloy, for example, you would use the RKKY coupling between all pairs of spins with the spins situated at random locations (which would then be quenched).,,
!!__Properties of the model__
!!![[Frustration]]
[[Ground States of the 2D Edwards-Anderson Spin Glass - Michael Damron|https://www.youtube.com/watch?v=3ckXBhP5ju8]]
!!![[Spin glass phase transition]]
__[[EA order parameter]]__
Actually, it turned out there is an infinity of order parameters, see [[Replica symmetry breaking]]
------------------
[[(silent video)|https://www.youtube.com/watch?v=fZ8WCic5u2I&index=2&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5]]
[[Some properties|https://www.youtube.com/watch?v=fZ8WCic5u2I&index=2&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5#t=13m30s]]
Bet-hedging: [[What is bet-hedging, really?|http://rspb.royalsocietypublishing.org/content/277/1685/1153]] [[Bet-hedging as an evolutionary game: the trade-off between egg size and number|http://rspb.royalsocietypublishing.org/content/276/1669/2963]] Bet-hedging theory addresses how individuals should optimize fitness in varying and unpredictable environments by sacrificing mean fitness to decrease variation in fitness
[[Evolution of phenotypic robustness|http://www.mabs.at/hermisson/manuscripts/RobustnessChapter.pdf]]
<i class="fa fa-exchange" aria-hidden="true"></i> [[Symbiosis|https://en.wikipedia.org/wiki/Symbiosis]] <i class="fa fa-exchange" aria-hidden="true"></i>
[img width=300 [https://upload.wikimedia.org/wikipedia/commons/7/70/Common_clownfish_curves_dnsmpl.jpg]]
[[Genome Growth and the Evolution of the Genotype-Phenotype Map|http://dynamics.org/Altenberg/PAPERS/GGEGPM/]]
[[Fundamental Properties of the Evolution of Mutational Robustness|http://dynamics.org/Altenberg/PAPERS/2015_ROBUSTNESS/]]
[[Evolvability and robustness in artificial evolving systems: three perturbations|http://download.springer.com/static/pdf/845/art%3A10.1007%2Fs10710-014-9223-3.pdf?originUrl=http://link.springer.com/article/10.1007/s10710-014-9223-3&token2=exp=1461169130~acl=/static/pdf/845/art%253A10.1007%252Fs10710-014-9223-3.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs10710-014-9223-3*~hmac=19adf54fddccf7493d42560f1737537624b99b4667881d04a23250409388e44b]]
[[SELF-ASSEMBLY , MODULARITY , AND PHYSICAL COMPLEXITY|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.82.026117]] [[pdf|http://www.tcm.phy.cam.ac.uk/~tmf20/PUBLICATIONS/pre_09.pdf]] [[presentation|http://www1.unipa.it/daa_erice11/DAA2011_Conference/Speakers_files/Ahnert.pdf]]
See [[MMathPhys oral presentation]]
!!__[[Arrival of the frequent]]__
: [[The Arrival of the Frequent: How Bias in Genotype-Phenotype Maps Can Steer Populations to Local Optima|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086635]] See notes at [[Arrival of the frequent]].
--[[The structure of the genotype–phenotype map strongly constrains the evolution of non-coding RNA|http://rsfs.royalsocietypublishing.org/content/5/6/20150053.full]]. [[See notes|The structure of the genotype-phenotype map strongly constraints the evolution of non-coding RNA]]
[[Probabilistic bias in genotype-phenotype maps|http://ora.ox.ac.uk/objects/uuid:eba8801e-182e-42f5-aa0a-d3d914fd7923]]. See more here: http://dingleresearch.weebly.com/publications.html
[img width=500 [http://d10k7sivr61qqr.cloudfront.net/content/royinterface/11/95/20140249/F3.large.jpg?width=800&height=600&carousel=1]]
<small>Self-assembling polyominoes model: [[A tractable genotype–phenotype map modelling the self-assembly of protein quaternary structure|http://rsif.royalsocietypublishing.org/content/11/95/20140249]]</small>
More.... [[Modeling the evolution of molecular systems from a mechanistic perspective|http://www.cell.com/trends/plant-science/fulltext/S1360-1385%2814%2900063-6]] [[Adaptive dynamics under development-based genotype–phenotype maps|http://www.nature.com/nature/journal/v497/n7449/full/nature12142.html]] [[Why self-incompatibility in the Brassicaceae is totally cool|http://vincentcastric.weebly.com/how-cool-is-si.html]]
!!__Robustness and evolvability__
3. [[The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype–phenotype maps|http://rsif.royalsocietypublishing.org/content/12/113/20150724.full]]. Features observed in several GP maps (including the simple Fibonacci GP map they use as a model):
[[Common features of GP maps]]
[[Genetic correlations greatly increase mutational robustness and can both reduce and enhance evolvability|http://arxiv.org/abs/1505.07821]]
//random null model//: that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly
''Genetic correlations''
//neutral correlations// can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus <b>neutral correlations increase evolvability</b>.
//non-neutral correlations//: Compared to the null model:
:i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected;
:ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar;
:iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype.
Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may <b>diminish evolvability</b>, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so <b>increase evolvability</b>.
!!__[[Examples of GP map bias]]__
{{Examples of GP map bias}}
See [[Measures and metrics for networks]]
The ''eigenvector centrality'' (first defined by Bonacich in 1987), is defined by:
$$\mathbf{A}\mathbf{x}=\kappa_1 \mathbf{x}$$
where $$\mathbf{x}$$ is the vector of centralities, and $$\kappa_1$$ is the largest eigenvalue of $$\mathbf{A}$$. The reason we choose the largest eigenvalue is that this measure can be obtained by starting from any arbitrary centrality measure $$\mathbf{x_0}$$ and getting new centrality measures by requiring that they be equal, for each node, to the sum of centralities of its neighbours, then the centrality corresponding with the eigenvector with the largest eigenvalue emerges exponentially over the others, and in the limit, we get the centrality defined above (up to normalization).
The centrality, then, has the property that it is equal to the sum over centralities of neighbours for each node $$i$$:
$$x_i = \kappa_1^{-1}\sum_j A_{ij} x_j$$ .....Eq. 1
so that a node can be important because it is connected to many nodes, or because it is connected to important nodes, or both.
Eigenvector centrality has problems for directed networks because defined in the natural way, only vertices in strongly connected components (or their out-components) will have non-zero eigenvector centrality. This is because the map described by Eq.1 passes centrality along edges in the direction they point, so the in-component will "loose" all its centrality in the long time limit.
Katz centrality addresses these problems
~ Need $$G$$ strongly connected for a directed network.
-------
__Perron-Frobenius theorem__
This theorem is related to ergodicity of the map defined by the recursive relation used to define eigenvector centrality <b>[write it here]</b>.
<b>[Look at theorem stuff in Newman books, specially relevant footnotes]</b>.
Ensures centralities are positive.
See [[Dissipation-fluctuation relation]]
[[https://en.wikipedia.org/wiki/Einstein_relation_(kinetic_theory)]]
A fundamental physical property that makes a physical object interact through [[electromagnetic|Electromagnetism]] interactions.
The flow (flux) of [[Electric charge]].
Sometimes called electricity, although [[Electricity]] can refer to any phenomenon involving electric charges.
See [[Electromagnetism]], [[Electrical engineering]]
[img[https://media.giphy.com/media/3o6gDWsfqS6bVxR0Fa/giphy-downsized-large.gif]]
https://en.wikipedia.org/wiki/Marx_generator
[[Electromagnetism]]
[[Electric motor]]
[[Energy production]]
See [[Electronic engineering]]
[[Electrical engineering]] -- [[Electronic engineering]]
[[Electrostatics]]
[[Electrochemistry]]
[[Atmospheric electricity]]
A simple electrochemical cell can be produced by dipping two different metals into an electrolyte and connecting them via wires and a voltmeter, bulb, motor, etc. The bigger the difference in [[reactivity|Reactivity series]] between the two metals, the bigger the voltage produced.
https://www.wikiwand.com/en/Electrochemical_cell
[[Self-propelled particle]], [[Self-electrophoresis]], [[Catalytic conductor-insulator Janus swimmer]]
[[Electrokinetic effects in catalytic platinum-insulator Janus swimmers|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/epl14_salt-janus.pdf]]
"Pt-insulator Janus particles, the absence of conduction between the two hemispheres suggests a mechanism indepen-
dent of electrokinetics." (referring to the mechanisms that involve movement of electrons in bimetallic swimmers, see [[Self-electrophoresis]]). Thus [[Self-diffusiophoresis]] was suggested. However, as they show in that paper, some electrokinetic effects can still play a role in the Pt-insulator Janus particles.
"We find that their motion is due to a combination of neutral and ionic diffusiophoretic as well as electrophoretic effects whose interplay can be changed by varying the ionic properties of the fluid. "
One of their main findings is that a gradient of catalyst is required to produce appreciable propulsion velocity for single metal catalytic swimmers.
__Main mechanisms of the electrokinetic effect__
To see the main mechanism of the effect they discover (the mathematical derivation is outlined in the paper), notice that at the pole the catalytic reaction happens faster, and so there is a higher or lower concentration of $$H^+$$ $$e^-$$ pairs depending on whether the reaction is mostly consuming or producing them (see reaction diagram). ,,Notice that the electrons ($$e^-$$) diffuse much faster inside the Pt metal, so that they spread through the Pt hemisphere, while the proton ions ($$H^+$$) diffuse much slower. Note that the electrons will diffuse in such a way that the tangential component in the metal is $$0$$,,. This distribution of charges creates an electric field, that drives the ions in the fluid, propelling the Janus sphere. In the case in the paper, I think the place where the reaction happens faster (near the pole) also consumes $$H^+$$ faster, so there is a depletion of $$H^+$$ there, and a relatively higher concentration near the equator. There is thus a net electric field that pushes the protons from the equator to the pole (i.e. they push each other). They drag the fluid with them too, so that the particle propels itself by this [[self-electrophoretic|Self-electrophoresis]] mechanism.
See also [[Ion Drive for Vesicles and Cells|http://www.sciencedirect.com/science/article/pii/S0022519396900351]]
See [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]] for matched asymptotic analysis of fluid flow. And see paper for chemical reaction kinetic and diffusion equations.
<mark>Why does the double loop topology mean we can reduce overall catalytic reaction rate without significant reduction of colloid velocity?</mark>
Electrolysis is the process by which ionic substances are decomposed (broken down) into simpler substances when an [[Electric current]] is passed through them. Electrolysis is used to extract and purify metals.
http://www.bbc.co.uk/education/guides/zk96fg8/revision
* Positively charged ions move to the negative electrode during electrolysis. They receive electrons and are reduced.
* Negatively charged ions move to the positive electrode during electrolysis. They lose electrons and are oxidised. The substance that is broken down is called the electrolyte.
A substance with movable ions can be decomposed with electrolysis, and is known as an [[Electrolyte]].
From [[here|http://www.bbc.co.uk/education/guides/zk96fg8/revision/3]], when the metals ion are in an aqueous solution (with H+ and OH- ions), then
*the metal will be produced if it is less reactive than hydrogen
*hydrogen will be produced if the metal is more reactive than hydrogen
Where reactivity can be determined from the [[Reactivity series]].
This is because only if the metal is less reactive than hydrogen, will it be energetically favourable for the electron to jump to the hydrogen at the cathode. Furthermore, if the cathode is made of carbon (most common case), the carbon is more reactive, so a layer of metal would first need to form to give electrons to the hydrogen.
[[Basic electrolysis calculations|http://www.bbc.co.uk/education/guides/zk96fg8/revision/5]]
[[Electroplating|http://www.bbc.co.uk/education/guides/zk96fg8/revision/7]]
A liquid or gel that contains mobile [[Ion]]s and ao can be decomposed by [[Electrolysis]], e.g., that present in a battery.
They are [[electrically conducing|Electrical conductivity]]
!!__[[Electrostatics]]__
!!__Magnetostatics__
!!__Electromagnetism__
[[Electric motor]]
https://www.youtube.com/channel/UCPC6uCfBVSK71MnPPcp8AGA/playlists
[[Electromagnetic theory|https://www.youtube.com/watch?v=pGdr9WLto4A&list=PLl6m4jcR_DbOx6s2toprJQx1MORqPa9rG]]
* [[Atomic orbital]]
* [[Molecular orbital]]
//aka Pauling electronegativity//
An [[Atom]]'s ability to attract [[Electron]]s to itself when bound to another atom.
Electronegativity determines the [[polarity of a molecule|Polar molecule]].
[img[http://butane.chem.uiuc.edu/cyerkes/chem102ae_fa08/homepage/Chem102AEFa07/Lecture_Notes_102/Lecture%2012%20_files/image24.gif]]
https://en.wikipedia.org/wiki/Electronic_circuit
http://www.allaboutcircuits.com/textbook/
[[Analog circuit]]
[[Digital circuit]]
See other uses of circuits: https://en.wikipedia.org/wiki/Circuit
[img[http://i.imgur.com/4BQD1ZU.jpg]]
https://www.adafruit.com/
Sparkfun
[[Electronics]]
[[Electronic circuit]]
[[Electronic design]]
Electronic money (e-money) is electronically (including magnetically) stored monetary value, represented by a claim on the issuer, which is issued on receipt of funds for the purpose of making payment transactions. It is accepted by a person other than the electronic money issuer.
[[FCA|https://www.fca.org.uk/firms/electronic-money-regulations]]
[[Positive money - Electronic money issuers|https://www.google.co.uk/url?sa=t&source=web&rct=j&url=https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/370910/Positive_Money_response.pdf&ved=0ahUKEwjvzurhoqLPAhWTSxoKHUKBDCcQFggrMAU&usg=AFQjCNFmlS96LYrB6W-Yosc4vomGwdqtYg&sig2=hfetsDg8nEjnqjNRFuz9fw]]
https://transferwise.com
The Art of electronics (3rd edition)
__Electrical network__
[[Electrical circuit]]
A [[Molecule]] (or [[Molecular ion]]) which tends to bind to partially negatively charged parts of a [[Molecule]] (where the [[Electron]]s are more present)
[[Addition reaction]] where an [[Electrophile]] is the one being added
[[Substitution reaction]] where an [[Electrophile]] is the one substituting
https://www.wikiwand.com/en/Electrophilic_substitution
See [[Self-electrophoresis]]
https://en.wikipedia.org/wiki/Electrophoresis
https://en.wikipedia.org/wiki/Zeta_potential
[ext[https://en.wikipedia.org/wiki/Double_layer_(surface_science)]]
[[Induced-charge electro-osmosis|http://web.mit.edu/bazant/www/papers/pdf/Bazant_2004_J_Fluid_Mech_ICE2.pdf]]
[[Induced-charge electrokinetics|https://en.wikipedia.org/wiki/Induced-charge_electrokinetics]]
See [[Electrostatics]]
See book by Hunter - Foundations of colloid science.
[[Individual and collective behavior of artificial swimmers: "Janus particles"|https://www.youtube.com/watch?v=vxW7_-ei8Bw]]
!!!See this course: [[MAE6240 Fall 2012 |https://www.youtube.com/playlist?list=PLADE976650940CCCF&spfreload=5]]
The study of [[physiological|Physiology]] effects involving [[Bioelectricity]]
See [[Electromagnetism]]
__Coulomb's law__
[img[https://media.giphy.com/media/l4KhOq7ytSYD0HLXO/giphy.gif]]
[[Electrostatic Machines|http://www.coe.ufrj.br/~acmq/electrostatic.html]]
[[Does any object placed in an electric field change the electric field?|http://physics.stackexchange.com/questions/93911/does-any-object-placed-in-an-electric-field-change-the-electric-field]]
An elimination reaction is a type of [[Chemical reaction]], often an [[Organic reaction]], in which two substituents are removed from a molecule in either a one or two-step mechanism, usually through the action of acids, bases, or metals and, in some cases, by heating to a high temperature. It is the principal process by which organic compounds containing only single carbon-carbon bonds (saturated compounds) are transformed to compounds containing double or triple carbon-carbon bonds (unsaturated compounds).
[[Video|https://www.khanacademy.org/science/organic-chemistry/substitution-elimination-reactions/e1-e2-tutorial/v/e1-elimination-mechanism]]
The one-step mechanism is known as the E2 reaction, and the two-step mechanism is known as the E1 reaction. The numbers do not have to do with the number of steps in the mechanism, but rather the kinetics of the reaction, bimolecular and unimolecular respectively.
!!__E1 mechanism__
Two-step mechanism
https://www.wikiwand.com/en/Elimination_reaction#/E1_mechanism
!!__E2 mechanism__
One-step mechanism
https://www.wikiwand.com/en/Elimination_reaction#/E2_mechanism
The [[expectation–maximization algorithm|https://www.wikiwand.com/en/Expectation%E2%80%93maximization_algorithm]] is an iterative method for finding [[Maximum likelihood]] or [[Maximum a posteriori]] (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables, which is used in models for [[Unsupervised learning]]
[[Bootstrap idea|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=29m45s]] -- [[General EM algorithm|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=42m40s]], see [[Bootstrapping]]
,,[[EM vs graident descent|http://stats.stackexchange.com/questions/45652/what-is-the-difference-between-em-and-gradient-ascent]],, --
[[Why should one use EM vs. say, Gradient Descent with MLE?|http://stats.stackexchange.com/questions/158859/why-should-one-use-em-vs-say-gradient-descent-with-mle]] -- ,,[[see discussion here also|https://www.reddit.com/r/MachineLearning/comments/34lyl2/em_vs_gradient_descent/]],, -- [[see video|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=5m55s]]
!!!__Derivation__
[[Deriving the general version of EM algorithm|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=51m48s]]
Have some predetermined model for $$P(x,z ; \theta)$$, for instance a [[Gaussian mixture model]], but observe only $$x$$. For [[Mixture model]]s, the $$z$$ are often //labels//. Want to maximize the log-[[likelihood|Likelihood function]] (see [[Maximum likelihood]]):
$$l(\theta )=\sum _{i=1}^m\log P\left(x^{\left(i\right)};\theta \right) =\sum _{i=1}^m\log {\sum _{z^{\left(i\right)}}P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}$$
$$=\sum _{i=1}^m\log \sum _{z^{\left(i\right)}}^{ }Q_i\left(z^{\left(i\right)}\right)\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)}$$
[$$Q_i (z^{(i)}) \geq 0 \sum_{z^{(i)}} Q_i(z^{(i)})=1$$, is some [[Probability distribution]] for $$z$$]
$$=\sum _{i=1}^m\log{ \mathbb{E}_{z^{(i)} \sim Q)i} \left[\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)}\right]}$$
We known that $$\log{\mathbb{E}[x]} \geq \mathbb{E}[\log{x}]$$, by the concave version of [[Jensen's inequality]], as log is a concave function, so:
|$$l(\theta ) \geq \sum _{i=1}^m \mathbb{E}_{z^{(i)} \sim Q_i} \left[\log{\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)}}\right]$$ $$= \sum _{i=1}^m\sum _{z^{\left(i\right)}}^{ }Q_i\left(z^{\left(i\right)}\right)\log{\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)}}$$|1|
__[[Intuitive picture|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=55m]] of the algorithm__: the EM algorithm, at each iteration, constructs a lower bound function for $$l(\theta)$$, which is tight at the current value of $$\theta$$ (i.e. at that value the inequality is an equality). The algorithm then maximizes this lower bound function to update $$theta$$. The equality at current $$\theta$$ guarantees that each step actually gives a larger value of the actual $$l(\theta)$$. To ensure this, we <span style="color: #cef; font-weight: bold;">choose the probability distribution $$Q_i (z^{(i)})$$ appropriately</span>. Note that the lower bound [[need not be a concave function of theta|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=1h07m]], which may cause problems? I don't think so, as we are constructively showing that the construction shown in the video can be done.
The inequality becomes an equality if the random variable inside the expectation is a constant (see [[Jensen's inequality]]), so we want to choose $$Q_i$$ s.t.
$$\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)} = const.$$ w.r.t. $$z^{(i)}$$ <b>at the current value of $$\theta$$.</b> [[This is an important point|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=35m10s]], otherwise we would have equality at all $$\theta$$, and we would be just maximizing $$l(\theta)$$ itself directly, so the EM algorithm wouldn't make sense..
$$\therefore Q_i\left(z^{\left(i\right)}\right) \propto P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)$$
From normalization, $$\sum_{z^{(i)}} Q_i(z^{(i)})=1$$, we can determine the constant:
|$$Q_i\left(z^{\left(i\right)}\right) = \frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{\sum_{z^{(i)}} P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)} = \frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{P(x^{(i)}; \theta)} = P(z^{(i)}|x^{(i)}; \theta)$$|2|
-------------------------
!!!__EM algorithm__
# Repeat until convergence
## ''E-step''. Guess values of $$z^{(i)}$$s. In particular, compute the probability distribution of $$Q_i(z^{(i)}=j) = P(z^{(i)} = j | x^{(i)}; \theta) $$, from [2]. This can also be seen as an a-posteriori probability distribution. <b>Note:</b> The value of $$\theta$$ here is the current value of $$\theta$$; it is fixed in the maximization in the next step (despite the unfortunate notation). See [[here|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=35m10s]].
## ''M-step''. Update parameters $$\theta$$ as $$\theta = \arg\max\limits_\theta \sum _{i=1}^m\sum _{z^{\left(i\right)}}^{ }Q_i\left(z^{\left(i\right)}\right)\log{\frac{P\left(x^{\left(i\right)},z^{\left(i\right)};\theta \right)}{Q_i\left(z^{\left(i\right)}\right)}}$$
[img[https://upload.wikimedia.org/wikipedia/commons/6/69/EM_Clustering_of_Old_Faithful_data.gif]]
[[Another way of seeing the EM algorithm|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=7m50s]] as coordinate descen!
----------------------
__My own derivation of the likelihood__ using [[Baye's theorem]]
instead of just maximizing $$P(\theta | z, x)$$, as we don't know $$z$$ with certainty, we need to maximize $$P(\theta|x) = \sum_z P(\theta , z| x)$$ $$= \sum_z \frac{P(x|\theta, z) P(\theta, z)}{\sum_{\theta, z} P(x,z|\theta) P(\theta)} \propto \sum_z P(x|\theta, z) P(\theta, z) $$ $$=\sum_z P(x,z;\theta)$$, where $$z$$ represents the set of $$z^{(i)}$$ and the sum is over all possible configurations. $$P(z)$$ is known from the E-step.
See [[here|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=12m30s]] too.
See this post: https://www.facebook.com/groups/hedonistic.imperative/permalink/10152547241106965/ and movie Phenomenon (1996) Dave says: "it is not emotions we need to control but behaviour. We do not learn from emotions by curbing and suppressing them but by fully experiencing them. "
[[When Emotions Make Better Decisions - Antonio Damasio|https://www.youtube.com/watch?v=1wup_K2WN0I&feature=youtu.be]]
Hm, it seems like emotion is our Q function in [[Reinforcement learning]]. It is kind of a summary of wisdom from past experiencies. Hm this is interesting.. If we are guided by emotions too much then our Q function will learn by trying to amplify the positive emotions it encodes, this may produce a positive feedback loop, which sounds like //addiction// to me. If however, we ignore emotions too much, we are not making use of this awesome machine learning algorithm we have built in in our brain, and may get stalled in philosophical analysis too often in life, by trying to logically deduce everything.
In fact, modern [[Artificial intelligence]] trends seem to show that deep learning, and heuristics based learning are more powerful than the older symbolic/logic approach to AI. However, judging from how our brain works, it appears that the optimal combination may be a combination of the two, using one or the other as appropriate!
[[Antonio Damasio|https://en.wikipedia.org/wiki/Antonio_Damasio]]'s research in neuroscience has shown that emotions play a central role in social cognition and decision-making"
This seems to be related to ''thinking fast & slow'' (<mark>Read that book!</mark>), and also how AIs now seem think more intuitively (so maybe in a sense they have some level of emotion now!).
See this to see how these considerations of thinking fast & slow, heuristically vs deductively, relates to utilitarian ethics issues: [[Facing the unknown: the future of humanity - Nick Bostrom|https://www.youtube.com/watch?v=h9NB0EQ9iQg#t=20m06s]]
--------
[[Wiki: Emotion|https://en.wikipedia.org/wiki/Emotion]]
[img width=500 class=img-centered [https://upload.wikimedia.org/wikipedia/commons/c/ce/Plutchik-wheel.svg]]
Not sure. Hm, of course, this is just a fuzzy representation, but I think I would swap the terror and amazement branch. It'd be interesting to see the logic behind this better though.
-------------------
__More on emotional intelligence__
From Solomonoff's paper, recounting how he was inspired by Freud and Poincare
<<<
2.3 Freud, Poincaré
From Freud I got the idea of the unconscious mind: that there were things going
on in one's brain that one didn't have direct access to. Poincaré, made it clear
that much of his serious problem solving occurred in his subconscious, and I felt
this was very common in problem solving of all kinds in the sciences and the
arts
This view was one important reason for my later rejection of "Expert Sys-
tems" as a significant step toward Artificial Intelligence. Expert Systems were
(at best) expressions of peoples' conscious thought, which was, I felt, a very
small fraction of human problem solving activity
Other implications: Memory is what you invent to explain the things that
you find in your head. Over the years, the "facts" in this paper will be gradually
revised as I reread my research notes
Explanations that people give for their own behavior are not to be taken too
seriously including discussions in this paper
<<<
Risk minimization (see [[Learning theory]]), requires knowing the joint probability distribution $$P(x,y)$$, so one often uses the sample mean of the risk as an estimator for the expected value of the risk. Minimizing this empirical quantity is called empirical risk minimization (ERM).
Depending on the form of the risk function, this optimization problem may be [[convex|Convex optimization]] or non-convex. If one uses a 0-1 loss function, the problem is non-convex, and finding its solution is [[NP-hard]]. A smoothed loss function may convert it into convex problem, solvable by [[Gradient descent]].
!!![[Neural networks [2.1] : Training neural networks - empirical risk minimization|https://www.youtube.com/watch?v=5adNQvSlF50&index=7&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]
Empirical risk minimization is thus defined as the [[Optimization]] problem of minimizing
$$\frac{1}{m} \sum\limits_i l(f(x^{(i)}; \mathbf{\theta}), y ^{(i)}) + \lambda \Omega (\mathbf{\theta})$$
where $$f$$ is our [[Model]] (hypothesis, that depend on the model parameters $$\mathbf{\theta}$$; $$l$$ is the [[Loss function]], $$ \Omega (\mathbf{\theta})$$ is the [[regularizer|Regularization]]. $$\lambda$$ is a hyperparameter that balances the two terms.
When we add the regularizer, ERM is called //structural risk minimization//.
-------------------
,,[[Setting up formally a linear classifier, to explore the problems of learning theory, and using empirical risk minimization as learning principle|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=7m35s]],,
[[Intro to ERM|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=10m30s]] -- [[def|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=12m20s]]
[[Emulsion|https://en.wikipedia.org/wiki/Emulsion]] is a [[colloidal|Colloid]] mixture of two or more liquids that are normally immiscible (unmixable or unblendable). The two liquid form to __coexisting phases__.
[img[http://health.learninginfo.org/images/emulsion.jpg]]
Examples:
* [[Vinaigrette|https://en.wikipedia.org/wiki/Vinaigrette]]
* [[Milk|https://en.wikipedia.org/wiki/Milk]]
* [[Mayonnaise|https://en.wikipedia.org/wiki/Mayonnaise]]
* Some [[cutting fluids|https://en.wikipedia.org/wiki/Cutting_fluid]]
https://en.wikipedia.org/wiki/Outline_of_energy
https://en.wikipedia.org/wiki/Energy_industry
[[Energy - Springer|http://www.springer.com/gp/energy]]
http://www.futureearth.org/
Rocky mountain institute
__Solar energy__
Perovskite solar cell
Producing energy doesn't mean creating it from nothing, as that would violate the principle of conservation of energy, in [[Physics]].
''Energy production'' thus refers to [[converting energy|Energy transduction]] from one form (often an storage form) to another form, which is useful (to do //mechanical work// often).
!!__Fuel-based energy production__
!!__[[Renewable energy production]]__
[[Hydro-electric power]]
[[Wind power]]
[[Solar power]]
Converting energy from one form to another form
[[Probabilistic model]]s whose properties are defined via a global [[Free energy]] (that often is actually a [[Lyapunov function]]), that is minimized via the model's dynamics, which can be its intrinsic dynamics, or some training procedure imposed on the model.
Often, these models can be analyzed via [[Statistical physics]], as these systems tend to minimize [[Free energy]]es.
They appear in several models in [[Machine learning]], such as:
* [[Boltzmann machine]]s
* [[Hopfield network]]s for symmetric connections
* [[Graphical model]]s. Applications to discrete [[Optimization]]
https://github.com/davidBelanger/SPEN
See [[Technology & Engineering]]
Here we include ''applied sciences'' as part of engineering
[[Portal:Engineering|https://en.wikipedia.org/wiki/Portal:Engineering]]
__Problem-solving strategies__
[[How to solve it by Polya|https://en.wikipedia.org/wiki/How_to_Solve_It]]
[[TRIZ - Theory of inventive problem solving|https://en.wikipedia.org/wiki/TRIZ]]. <small>Apparently used by Samsung</small>
[img[https://upload.wikimedia.org/wikipedia/commons/a/a2/Prism_of_TRIZ_Oxford_Creativity.png]]
[img[https://upload.wikimedia.org/wikipedia/commons/b/bf/40_principles_of_TRIZ_method_720dpi.jpg]]
Free MIT books: https://archive.org/details/mitlibraries
https://en.wikipedia.org/wiki/Entertainment
https://www.wikiwand.com/en/Enthalpy
$$H=U + pV$$
!!!__Enthalpy change under constant pressure__
For processes under constant pressure, ΔH is equal to the change in the internal energy of the system, plus the pressure-volume work that the system has done on its surroundings.[3] This means that the change in enthalpy under such conditions is the heat absorbed (or released) by the material through a chemical reaction or by external heat transfer.
The entropy, $$H(X)$$, of a [[Random variable]], $$X$$, is defined as
$$H(X) = - \sum_x p(x) \log{p(x)}$$
[[video|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft]]
The entropy rate of an information source (see [[Data transmission]]) is the average entropy of a letter of the source.
An information source is often modelled as a discrete-time stochastic process $$\{X_k\}$$, where each $$X_k$$ is called a "letter". The entropy rate is then defined as:
$$H_X = \lim_{n\rightarrow \infty} \frac{1}{n} H(X_1, X_2, \cdots, X_n)$$
when the limit exits (see also Shannon-McMillan-Breiman theorem).
[[Chapter 2 Information Measures - Section 2.10 Entropy Rate of a Stationary Source|https://www.youtube.com/watch?v=1-gH2ecuewk]]
One can define a related measure, $$H_X$$, by using conditional entropies. It can be shown that, for an stationary [[Information source]], the entropy rate exists and is equal to $$H_X$$.
[img[http://i.imgur.com/EdV8plQ.png]]
The [[Entropy rate]] of a FSP, as defined in [[Finite state channel]]
See here: http://pfister.ee.duke.edu/thesis/chap4.pdf
Blackwell (1957): [[The entropy of functions of finite state Markov chains|http://people.eng.unimelb.edu.au/rezaeian/blackwell.pdf]]
Birch (1962): [[Approximations for the Entropy for Functions of Markov Chains |http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.406.6016&rep=rep1&type=pdf]]
See [[Random matrix product]]
__Ordering in sequence spaces__
A mathematical theory of ordering (with constraints) in sequence spaces was first presented in [7] and [1]. In their setup, an algorithm is sought which “orders” any sequence of length n, i.e., which transforms the sequence x⃗ into the sequence y⃗ (of the same length and with the same symbols in it), such that the number of possible resulting sequences y⃗ is as small as possible. In this sense ordering is a generalization of sorting x⃗ , as this would yield the absolute minimal number of sequences y⃗ .
[[Ordering in Sequence Spaces: An Overview|http://link.springer.com/chapter/10.1007/978-1-4757-6048-4_48]]
[[Creating order in sequence spaces with simple machines|http://www.sciencedirect.com/science/article/pii/089054019090020I]]
[[Entropy reduction, ordering in sequence spaces, and semigroupss of non-negative matrices|http://sci-hub.cc/10.1109/ISIT.1995.550314]] see [[here|https://scholar.google.co.uk/scholar?cites=9597678491629848145&as_sdt=2005&sciodt=0,5&hl=en]]
[[Creating Order and Ballot Sequences|http://link.springer.com/chapter/10.1007/978-3-642-36899-8_36]]
See [[Descriptional complexity]]
!!__[[Entropy rate]]__
Often defined for a (probabilistic) [[Information source]].
[[Here|https://books.google.co.uk/books?id=Y-FwBPbpnZEC&pg=PA390&lpg=PA390&dq=topological+entropy+lempel+ziv+complexity&source=bl&ots=ZpwVO7C1Z9&sig=1O1bWrg3JvrOvrFgbK9kuksq0hc&hl=en&sa=X&ved=0ahUKEwjnifqH2dzNAhVKDcAKHVNsAdIQ6AEIIzAA#v=onepage&q=topological%20entropy%20lempel%20ziv%20complexity&f=false]] they define a (non-standard) notion of entropy for a specific sequence.
!!__[[Topological entropy]]__
Topological entropy of a string (symbol sequence)
[[Defined here|https://books.google.co.uk/books?id=Y-FwBPbpnZEC&pg=PA390&lpg=PA390&dq=topological+entropy+lempel+ziv+complexity&source=bl&ots=ZpwVO7C1Z9&sig=1O1bWrg3JvrOvrFgbK9kuksq0hc&hl=en&sa=X&ved=0ahUKEwjnifqH2dzNAhVKDcAKHVNsAdIQ6AEIIzAA#v=onepage&q=topological%20entropy%20lempel%20ziv%20complexity&f=false]]
[img[http://i.imgur.com/V3ty0f1.png]]
!!__Metric entropy__
measure-theoretical or
[[Kolmogorov-Sinai entropy]]
------------------
See [[Entropy and complexity of finite sequences as fluctuating quantities|http://sci-hub.cc/10.1016/S0303-2647(01)00171-X]]
https://www.wikiwand.com/en/Environmental_studies
[img[https://images.washingtonpost.com/?url=https%3A%2F%2Fimg.washingtonpost.com%2Fblogs%2Fworldviews%2Ffiles%2F2014%2F12%2Fland-changes-1900-2010-forward_50perc_res.gif&op=noop]]
"It's mainly because people haven't been cutting down nearly as much wood for fuel, plus there have been concerted efforts to manage and regrow forests. Also some of the areas have been regrowing after the World Wars made them less suitable for farmland." ~Laurie
https://www.wikiwand.com/en/Environmental_studies
__Related areas__
* [[Ecology]]
* [[Climate]], [[Earth science]]
[[Catalyst]]s that appear in [[Biology]], and catalyze many biological reactions, particularly, in [[Metabolism]]
https://en.wikipedia.org/wiki/Enzyme
[[What do enzymes do?|https://www.youtube.com/watch?v=56gbYumAXIg]] -- [[How do enzymes work?|https://www.youtube.com/watch?v=k9cI2jwoX20]] -- [[Influenza virus - tricks of a burglar|https://www.youtube.com/watch?v=MBvgV5Xg_ks]]
are macromolecular biological ''catalysts''
!!__Examples of enzymes__
[[Triose phosphate isomerase]] (TIM). It takes a [[Triose]] phosphate (with a [[Phosphate]] group), into an [[Isomer]] of it.
* [[Protease]]
!!__Mechanisms__
''Active site''. 3D cleft or crevice with precisely defined arrangement of atoms. Part of the enzyme that specifically binds the substrate. Substrate binds via multiple [[Intermolecular forces]]
* Lock and key
* Induced fit
* Really, it's a combination of both
Active site is defined by its shape and the chemistry of the [[Amino acid]]s that make it.
!!__Function__
*Stabilize transition states.
*Avoiding side reactions
[img[http://alevelnotes.com/page_images/504px-Carbonic_anhydrase_reaction_in_tissue.svg.png]]
!!!__[[Enzyme kinetics]]__
---------------
!!__Enzyme synthesis__
Using [[Bacteria]]
!!__Applications__
* In [[Food]] industry, washing powders
* Bioremediation, to clean up [[Contamination]]
* Biomimetic catalysts
------------
[[vfun id|https://www.youtube.com/watch?v=XTUm-75-PL4]]
Majority are [[Kinase]]s which [[phosphorylate|Phosphorylation]]
!!__Examples__
Eph receptors, important in [[Developmental biology]]
One of the main types of [[Pathway regulation]]
!!__Reversible inhibition__
Kinases, add phosphate to proteins to activate them.
!!!__Competitive enzyme inhibition__
Binds to active site of [[Enzyme]]
!!!__Non-competitive inhibition__
* [[Allosteric regulation]]
!!__Irreversible inhibition__
[[Covalent bond]] with enzyme
!!__Examples__
* Viagra
* [[Aspirin]], statins
* Fluconazole.
* Penicilin
__Michaelis-Menten rule__
Derived from kinetic rate equations for a simple catalytic reaction. The rate (per unit volume) of catalysis at equilibrium is:
$$k_{\text{eff}} = \frac{k_2 C_S C_E}{C_S+K_M}$$
__Derivation__
[img[http://i.imgur.com/UtOT13V.png]]
See [[sysbio matlab modelling course day 2 morning|Day2_Morning_lecture.pdf]]. There are two time scales in the problem. Can apply [[Method of multiple scales]].
Keywords: [[Network science]], [[Epidemiology]]
[[Cascades on Networks|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/22/soc-influence-dynamics_on_networks.pdf]]. There //Watt's cascade model// is described, among other things.
See Mason and Gleeson "Dynamical systems on networks"
!!__[[Types of contagions]]__
{{Types of contagions}}
There are many [[Epidemic model|https://en.wikipedia.org/wiki/Epidemic_model]]. Some use simple stochastic compartmental models based on a [[Master equation]] (see [[Simple contagion]]). See [[Epidemics on networks]], for models that include the underlying network structure.
!!__[[Types of contagions]]__
{{Types of contagions}}
The study of ''epigenetic factors'', factors other than the sequence of base pairs in [[DNA]] that affects [[Gene expression]] in the cell.
[[Beyond the DNA: Comprehensive map of the human epigenome completed|https://www.sciencedaily.com/releases/2016/11/161117150743.htm?utm_content=bufferb333b&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer]]
[[epistemological holism|https://www.wikiwand.com/en/Confirmation_holism]] is the view that no individual statement can be confirmed or disconfirmed by an empirical test, but only a set of statements (a whole theory).
[[short description (vid)|https://www.youtube.com/watch?v=yXkEpzexYIU#t=8m38s]]
https://www.wikiwand.com/en/Epistemological_pluralism
http://www.papert.org/articles/EpistemologicalPluralism.html
It's an idea, that I'm not sure I agree with.
The theory of Knowledge.
[[Introduction to Epistemology|https://www.youtube.com/watch?v=X3IcbRNQR4c]]
http://plato.stanford.edu/entries/epistemology/
-----------------------
What is the nature of knowledge?
What are the obstacles to the attainment of knowledge?
What can be known?
How does knowledge differ from opinion or belief?
!![[Foundationalism|https://www.wikiwand.com/en/Foundationalism]] vs [[Coherentism|https://www.wikiwand.com/en/Coherentism]]
[w]hat distinguishes a coherence theory is simply the claim that nothing can count as a reason for a belief except another belief” (Davidson, 1986)
An advocate of //weak foundationalism// typically holds that while coherence is incapable of justifying beliefs from scratch, it can provide justification for beliefs that already have some initial, perhaps miniscule, degree of warrant, e.g., for observational beliefs.
I would extend the coherentism picture with what I call the ''Principle of inclusiveness''.
[[Jacob Brownowski|https://www.youtube.com/watch?v=DFgnGUL78MU#t=1h2m20]]
[[Principle of multiple explanations]]
[[Epistemological holism]]
[[Epistemological pluralism]]
https://www.wikiwand.com/en/Willard_Van_Orman_Quine
---------------
See [[Philosophy of science]]
The thin tissue forming the outer layer of the cavities and surfaces of blood vessels and organs throughout the body.
https://www.wikiwand.com/en/Epithelium
[[Statistical Mechanics Lecture notes (Oxford Maths)|#]]
[[Statistical Mechanics Lecture notes (Oxford Physics)|#]]
!!! Ergodic hypothesis
!! Equilibrium ensembles
!! Fundamental postulate
Can formulate as:
*Maximum entropy. Can be formulated as minimum of a [[Thermodynamic Potential]], depending on constraints imposed.
*Equal a-priori probabilities principle
!! Partition function
!! Thermodynamics
!!! Laws
!!!! 1st law
!!!! 2nd law
!!!! 3rd law
!!! Thermodynamic potentials
!! Applications
An ''equivalence relation'' is a binary [[Relation]], $$R$$ on a [[Set]] $$X$$ that satisfies:
* [[Reflexivity]]
* [[Symmetry|Symmetric property]]
* [[Transitivity]]
Ergodic theory (Ancient Greek: ergon work, hodos way) is a branch of mathematics that studies dynamical systems with an [[Invariant measure]] and related problems
An
-----------------
https://en.wikipedia.org/wiki/Ergodic_theory
[[Recent Trends in Ergodic Theory and Dynamical Systems|https://www.youtube.com/playlist?list=PL04QVxpjcnjjbb3Eu1dpa82Ej3mJG7VRr]]
[[Karma Dajani - An introduction to Ergodic Theory of Numbers (Part 1)|https://www.youtube.com/watch?v=eDOXMibODhw]]
[[(ML 18.2) Ergodic theorem for Markov chains|https://www.youtube.com/watch?v=ZjrJpkD3o1w]]
http://mathoverflow.net/questions/82661/book-recommendation-for-ergodic-theory-and-or-topological-dynamics
See [[Coding theory]]
!!__Forward error correction__
[[Forward error correction|https://en.wikipedia.org/wiki/Forward_error_correction]]: forward error correction (FEC) or channel coding[1] is a technique used for controlling errors in data transmission over unreliable or noisy communication channels, where the information flows only one way (see [[here|https://www.youtube.com/watch?v=ydzIhYbG3XI&index=4&list=PLE125425EC837021F]]).. The central idea is the sender encodes the message in a redundant way by using an error-correcting code (ECC). The American mathematician Richard Hamming pioneered this field in the 1940s and invented the first error-correcting code in 1950: the Hamming (7,4) code.[2]
Two way error correction. Things like ARQ (automatic repeat request).
__Main types of FEC codes__:
* Hamming codes
* BCH codes (Reed-Solomon, convolutional coding)
* Turbo codes
* Galleger codes (LDPC)
* [[Convolutional code]] [[Convolutional code|https://en.wikipedia.org/wiki/Convolutional_code]] is a type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream. [[Stability of nonlinear feedback shift registers|http://link.springer.com/article/10.1007%2Fs11432-015-5311-0]]
* [[Block code|https://en.wikipedia.org/wiki/Block_code]] encode data in blocks.
See [[http://pfister.ee.duke.edu/thesis/chap1.pdf]], and other chapters.
[[(IC 1.3) Applications of Error-correcting codes|https://www.youtube.com/watch?v=XjSue2cJWOU&index=3&list=PLE125425EC837021F]]
!!__Quantum error correction__
An [[Artist]] famous for his [[Paradox]]ical pieces which included optical illusions, and [[Strange loop]]s.
[img width=300 [http://totallyhistory.com/wp-content/uploads/2013/01/mc-escher-waterfall.jpg]]
[img width=300 [http://totallyhistory.com/wp-content/uploads/2013/01/Drawing_Hands.jpg]]
[img width=300 [http://www.mcescher.com/wp-content/uploads/2013/10/LW410-MC-Escher-Print-Gallery-19561.jpg]]
An ester is an [[Organic compound]] derived by replacing at least one –OH ([[Hydroxyl]]) group in a [[Carboxyl]] group by an –O–[[Alkyl]] ([[Alkoxy]]) group, or --O--(some other [[Organic compound]]).
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/3/34/Ester-general.svg/130px-Ester-general.svg.png]]
!!__Ester [[Dehydration synthesis]]__
[img[http://a.files.bbci.co.uk/bam/live/content/zhvw6sg/large]]
!!!http://www.bbc.co.uk/education/guides/z33j6sg/revision/2
[[Fat]]s are examples of esters.
An [[Organic compound]]
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/5/51/Ether-(general).png/150px-Ether-(general).png]] that contain an ether group—an oxygen atom connected to two [[Alkyl]] [[Aryl]] groups, or other [[Organic compound]]-derived [[Substituent]]s—of general formula R–O–R′
[[Dapp developer resources|https://github.com/ethereum/wiki/wiki/Dapp-Developer-Resources]]
''Solidity'' -
[[Solidity docs|http://solidity.readthedocs.org/en/latest/index.html]] -
[[Solidity Browser|http://chriseth.github.io/browser-solidity/]] - <small>[[Cosmo|http://cosmo.to/]] (Doesn't really work)</small>
''Local node'' - [[Setting up private network|https://github.com/ethereum/go-ethereum/wiki/Setting-up-private-network-or-local-cluster]] - [[How To Create A Private Ethereum Chain|http://adeduke.com/2015/08/how-to-create-a-private-ethereum-chain/]]
--------------------
Tutorial for a contract example: https://ethereum.org/token#the-code
''Meteor template'': https://github.com/SilentCicero/meteor-dapp-boilerplate
http://www.ethereumoxford.org/tutorials/Tutorial3.html
''The Wallet: https://github.com/ethereum/mist/releases''
See discussion at [[Emotion]]
Morality
[[Jacob Brownoski words|https://www.youtube.com/watch?v=DFgnGUL78MU#t=1h2m20]]
https://en.wikipedia.org/wiki/Outline_of_academic_disciplines#Ethnic_and_cultural_studies
[[Ethology|https://en.wikipedia.org/wiki/Ethology]]. Study of animal behaviour
The domain of [[Life]] characterized by [[cells|Cell]] containing a well-defined nucleus.
[img[http://vignette4.wikia.nocookie.net/dinosaurs/images/2/2b/Eukaryote.jpg/revision/latest?cb=20140715161541]]
http://tolweb.org/Eukaryotes/3
All [[Multicellular organism]]s are eukaryotes
One of the most studied model organisms is the [[Saccharomyces cerevisiae|https://en.wikipedia.org/wiki/Saccharomyces_cerevisiae]] (a species of [[Yeast]])
!!__Types of eukaryotes__
* [[Plant cell]]
* [[Animal cell]]
* [[Protozoa]]
''Evolution'' ([[wiki|https://en.wikipedia.org/wiki/Evolution]]) is a positive feedback loop: it's all about changes that perpetuate those changes. Whenever you change a gene in such a way that it makes that gene more likely to stick around. But it doesn't need to be a gene. You can make self-sustaining cultural changes, like memes, self-fullfilling prophecies. Of course, positive feedback loops are found in maaany places, and they are indeed one of the main causes of self-organization in complex systems, so it is nice to see that evolution is just an example of one.
Dawkins idea of replicators (see [[his article|http://www.stephenjaygould.org/library/dawkins_replicators.html]]) of course fits well, because replicators are just self-sustaining structures. See also [[Units of evolution: A metaphysical essay|http://philpapers.org/rec/HULUOE]] and [[this|http://innovation.ucdavis.edu/people/publications/22 Griesemer 2000 Selection-1.1-67-80.pdf]], and [[The Elementary Units of Heredity|https://books.google.es/books/about/The_Elementary_Units_of_Heredity.html?id=LQDjcQAACAAJ&redir_esc=y]] cited in his article)
See [[MMathPhys oral presentation]], [[Evolutionary computing]], [[Genetics]]
!__Evolutionary biology__
Read book: Dawkins - The extended phenotype, the selfish gene
Evolution also selects other things which are inherited, such as [[Protein]]s and other [[biological systems|Systems biology]].
[[Evolutionary Dynamics- Exploring the Equations of Life - by Martin A. Nowak|http://www.hup.harvard.edu/catalog.php?isbn=9780674023383]]
[[slides|http://www.claymath.org/library/academy/LectureNotes/Nowak.pdf]]
[[website|http://ped.fas.harvard.edu/]]
[[Evolutionary dynamics on graphs|http://www.nature.com/nature/journal/v433/n7023/abs/nature03204.html]]
[[djvu|file:///home/guillefix/Dropbox/COSMOS/Biology%20&%20Medicine/Biodiversity%20and%20evolution/%5BMartin_A._Nowak%5D_Evolutionary_Dynamics_Exploring.djvu]]
!!!''[[Modern evolutionary synthesis|https://en.wikipedia.org/wiki/Modern_evolutionary_synthesis]]''
[[History of evolutionary thought]]
!!__Evolution theory__
[[Theoretical evolutionary genetics - Felsenstein (book)|http://evolution.genetics.washington.edu/pgbook/pgbook.html]], [[pdf|chrome-extension://ecnphlgnajanjnkcmbpancdjoidceilk/http://evolution.gs.washington.edu/pgbook/pgbook.pdf]]
[[ON THE FORMALIZATION OF THE EVOLVING TRANSFORMATION SYSTEM MODEL|http://cs.unb.ca/~goldfarb/oleg.pdf]]
[[Evolutionary Theory and Mathematics|http://dynamics.org/Altenberg/PAPERS/]]
[[Mathematical Modeling of Evolution|http://pespmc1.vub.ac.be/MATHME.html]]
[[“The arrival of the fittest”: Toward a theory of biological organization|http://link.springer.com/article/10.1007/BF02458289]]
!!!__[[Neutral theory of evolution]]__
''Kimura's neutral theory of evolution''. He proposed that (at least for molecular evolution) most mutations are neutral, meaning that they don't lead to a change in fitness.
!!!__[[Evolutionary developmental biology]]__
!!__[[Features of evolving systems]]__
!!__[[Effects in evolution]]__
[[Bias in GP maps]], [[Arrival of the frequent]]
!!__Genetic information and evolution__
See [[Genetics]]
[[Genotype-phenotype map]], [[Bias in GP maps]]
[[Discovery of a fundamental limit to the evolution of the genetic code|http://phys.org/news/2016-05-discovery-fundamental-limit-evolution-genetic.html]]
[[Scientists discover the evolutionary link between protein structure and function|http://phys.org/news/2016-05-scientists-evolutionary-link-protein-function.html]]
!__[[Evolutionary computing]]__
!__Evolution in [[Complex systems]]__
!![[Bias in GP maps]]
-----------
Some older disorganized thoughts:
Replicators at different levels.
Multilevel selection may not be necessary. However, it may be useful, it is just different ways of looking at evolution at different levels, depending on which processes are most important: mostly which (approximate) replicators are being looked at
Group, kin, individual, gene etc selections are just different proximate/ultimate levels of causation on the same evolutionary process
-------
People
https://en.wikipedia.org/wiki/Ernst_Mayr
See in wiki article of evolution
[[Statistical Physics of Adaptation|https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.021036]]
Recursive processing of variable-length structures continues to be regarded as a hall-
mark of human cognition. In the last decade, a firefight in the linguistics community staked
several leaders of the field against one another. At issue was whether recursive processing
is the “uniquely human” evolutionary innovation that enables language and is specialized to
language, a view supported by Fitch, Hauser, and Chomsky (Fitch et al., 2005), or whether
multiple new adaptations are responsible for human language evolution and recursive pro-
cessing predates language (Jackendoff and Pinker, 2005).
from [[here|https://arxiv.org/pdf/1410.5401v2.pdf]].
https://en.wikipedia.org/wiki/Evolutionary_computation
See [[Evolution]]
[[Computational intelligence - Scholarpedia|http://www.scholarpedia.org/article/Encyclopedia:Computational_intelligence]]
[[Evolution of evolvability|https://simons.berkeley.edu/talks/lee-altenberg-2014-03-17]] [[Slides|https://simons.berkeley.edu/sites/default/files/docs/1393/slidesaltenberg.pdf]]
[img[Selection_176.png]]
[ext[Complexity compression and evolution|http://www.cs.mun.ca/~banzhaf/papers/icga95-1.pdf]]
!!__[[Genetic programming|Genetic algorithm]]__
They work by combining concepts that have been useful in the past to generate promising new trial solutions
!!!__Evolvable harware__
https://en.wikipedia.org/wiki/Evolvable_hardware
[[Whatever happened to evolvable hardware?|http://www.eetimes.com/author.asp?section_id=36&doc_id=1266124]]
https://en.wikipedia.org/wiki/Reconfigurable_computing
[[Automated Antenna Design with Evolutionary Algorithms|https://ti.arc.nasa.gov/m/pub-archive/1244h/1244%20(Hornby).pdf]]
!!__Artifical life__
http://www.framsticks.com/
Logos sotware from MIT for agent-based simulation and others
[[Nils Aall Barricelli|http://cultureandcommunication.org/galloway/Barricelli/]]
__Conway's game of life__
http://www.scholarpedia.org/article/Game_of_Life
[[Automata theory]], cellular automata.
Smooth cellular automata: https://www.youtube.com/watch?v=KJe9H6qS82I
[[Life in life|https://www.youtube.com/watch?v=xP5-iIeKXE8]], meta
[[ASCII fluid dynamics|https://www.youtube.com/watch?v=QMYfkOtYYlg]]
Benefits of Sexual Reproduction in Evolutionary Computation
[[Evolutionary developmental biology|https://en.wikipedia.org/wiki/Evolutionary_developmental_biology]]
[[The Changing Role of the Embryo in Evolutionary Thought|http://www.cambridge.org/gb/academic/subjects/philosophy/philosophy-science/changing-role-embryo-evolutionary-thought-roots-evo-devo?format=PB]]
[[Bias in the introduction of variation as an orienting factor in evolution.|http://www.ncbi.nlm.nih.gov/pubmed/11341676]]
[[What is the relationship between developmental and evolutionary biology?|http://www.philosophersmag.com/index.php/footnotes-to-plato/116-the-proximate-ultimate-distinction-and-evolutionary-developmental-biology]]
See [[MMathPhys oral presentation]]. [[Automata theory
---------------------
http://link.springer.com/chapter/10.1007/978-3-642-23780-5_20#page-1
http://www.sciencedirect.com/science/article/pii/S0031320305000294
http://www.mitpressjournals.org/doi/abs/10.1162/neco.1992.4.3.393#.V5JBI-02fCI
http://www.mitpressjournals.org/doi/abs/10.1162/neco.1989.1.3.372#.V5JBB-02fCI
https://scholar.google.com/scholar?start=20&q=learning+finite+state+transducer+complexity&hl=en&as_sdt=0,5
------------------------
__[[Simplicity bias in finite-state transducers]]__
[[Random deterministic automata]]
[[Evolving Finite State Machines with Embedded Genetic Programming for Automatic Target Detection|http://dynamics.org/Altenberg/UH_ICS/EC_REFS/GP_REFS/IEEE/CEC2000/1541.pdf]]
[[Learning Finite-State Transducers: EvolutionVersus Heuristic State Merging|https://www.researchgate.net/profile/Simon_Lucas/publication/3418899_Learning_Finite-State_Transducers_Evolution_Versus_Heuristic_State_Merging/links/00b49537b29f81fc0e000000.pdf?inViewer=0&pdfJsDownload=0&origin=publication_detail]]
[[Boolean network]] and their evolution ([[What Darwin didn't know: natural variation is structured|https://www.youtube.com/watch?v=vLYpjUANUdc&feature=youtu.be]]).
[[Introducing Domain and Typing Bias in Automata Inference|http://link.springer.com/chapter/10.1007%2F978-3-540-30195-0_11]]
[[Random Deterministic Automata|http://link.springer.com/chapter/10.1007%2F978-3-662-44522-8_2]]
[[An Automaton Approach for Waiting Times in DNA Evolution|http://sci-hub.io/10.1089/cmb.2011.0218]]
Also, genetic regulatory networks: [[ Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output|http://www.pnas.org/content/103/11/4180.abstract]], [[Evolvability and robustness in a complex signalling circuit|http://www.ncbi.nlm.nih.gov/pubmed/21225054]]
!!![[Entropy of a Finite State Transducer|http://math.stackexchange.com/questions/81826/entropy-of-a-finite-state-transducer]]
$$H = - \sum_{\beta, \alpha, y} P_{\beta}P_{\alpha} p_{\alpha, \beta}(y)\log{p_{\alpha, \beta}(y)} = - \sum_{\beta, \alpha, y}P_{\beta}P_{\alpha} (\sum_{x\in F^{-1}(y)} p_{\alpha}(x))\log{(\sum_{x\in F^{-1}(y)} p_{\alpha}(x))}$$
[[Ergodicity of Random Walks on Random DFA|http://arxiv.org/abs/1311.6830]]
[[On the Effect of Topology on Learning andGeneralization in Random Automata Networks|https://www.pdx.edu/computer-science/sites/www.pdx.edu.computer-science/files/Goudarzi.pdf]]
[[Quantifying the complexity of random Boolean networks|http://arxiv.org/abs/1202.1540]]
[[The state complexity of random DFAs|http://arxiv.org/abs/1307.0720]]
[[http://tuvalu.santafe.edu/~walter/AlChemy/alchemy.html]] [[Artificial chemistry]]
[[Comparing nondeterministic and quasideterministic finite-statetransducers built from morphological dictionaries|http://www.dlsi.ua.es/~mlf/docum/garrido02j.pdf]]
---------
Is a random transducer an appropriate random model for GP maps in Nature?
For instance, in [[Gene regulatory networks]], when modelled as random [[Boolean network]]s, the state transition network is probably not just a random transducer... Though maybe it depends in the regime. For instance, in the //critical regime// we observe the largest GP map bias apparently
See [[Simplicity bias in finite-state transducers]]
You need to be able to loop around the non-coding region, and around the coding region to get non-trivial designability/complexity plots.
This FST shows a good example of an approximately absorbing region with two non-coding states. The fact that the region is approximately non-absorbing, and as there is a cycle outside that region, means we will get variety in output.
[img[http://i.imgur.com/yoA3f19.jpg]]
FST table:
``0 2 1 1
0 1 0 1
1 4 1 0
1 3 0 0
2 1 1 1
2 0 0 0
3 2 1 0
3 1 0 0
4 1 1 0
4 1 0 0
0
1
2
3
4
``
In this example there is clear bias towards a $$000000...$$ sequence, as there is an absorbing region made entirely of $$0$$-noncoding states. However, the rest of the fst does not have any loop, so there's barely any possibility for variety of outpus, and the designability/complexity plot is trivial.
[img[http://i.imgur.com/IlQBqBy.jpg]]
Here is an example of a FST with an approximately absorbing region with non-coding states that is the whole fst.
[img[http://i.imgur.com/tZ18ciy.jpg]]
* model GP maps for protein tertiary ([[Emergence of Preferred Structures in a Simple Model of Protein Folding|http://cqb.pku.edu.cn/tanglab/pdf/1996-34.pdf]], [[Structural determinant of protein designability|http://www.englandlab.com/uploads/7/8/0/3/7803054/2003prl.pdf]]),
* quaternary structure. Self-assembling polyominoes model ([[A tractable genotype–phenotype map modelling the self-assembly of protein quaternary structure|http://rsif.royalsocietypublishing.org/content/11/95/20140249]]),
* [[Gene regulatory networks]] ([[ Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output|http://www.pnas.org/content/103/11/4180.abstract]], [[Evolvability and robustness in a complex signalling circuit|http://www.ncbi.nlm.nih.gov/pubmed/21225054]])
* and development ([[An End to Endless Forms: Epistasis, Phenotype Distribution Bias, and Nonuniform Evolution|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000202]])
suggesting that some of the results discussed in this paper for
RNA may hold more widely in biology
[img[img/Selection_177.png]]
See also [[Evolving automata]]
Paper with several examples of GP maps, including cellular automata map: [[An investigation of redundant genotype-phenotype mappings and their role in evolutionary search|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=870337&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D870337]]
Physical activity, with benefits for health
See also [[Sport]]
//biology laboratory techniques//
[[Protein purification]], [[Protein structure analysis]]
[[Cell culture]]
''Explainable AI'' (XAI) refers to [[Artificial intelligence]] systems that are able to communicate their internal models and functioning to humans.
See also [[Integrating symbols into deep learning]] for some discussion and ideas.
DARPA is starting a projecg for this: [ext[article|http://www.darpa.mil/program/explainable-artificial-intelligence]]
[img[http://www.darpa.mil/ddm_gallery/xai-flowchart-inline-2.png]]
//Explorable explanations//
http://explorableexplanations.com/
http://bl.ocks.org/
http://bl.ocks.org/blacki/ebba08223eba20b56b62
[[AugMath]]
Percolation processes that show a discontinuous, or at least very steep phase transition. See [[this image|http://i.imgur.com/Q7DPOvl.png]] for a nice sumary of types of explosive percolation processes. The reviews below also summarize results, and below we discuss some of the main types.
[[Explosive Percolation: Novel critical and supercritical phenomena|https://arxiv.org/pdf/1511.01800.pdf]]
[[Impact of single links in competitive percolation|http://www.nature.com/nphys/journal/v7/n3/abs/nphys1860.html]]
!!__[[Achlioptas process]]es__
Achlioptas processes follow $$m$$-edge rules which involve choosing $$m$$ candidate edges uniformly at random between any pair of nodes (compare with other [[Spanning cluster-avoiding process]])and applying a rule to select which one is actually chosen. These have been proven to be continuous in the thermodynamic limit, for a fixed $$m$$
!!__[[k-vertex rule percolation process]]__
Processes based on chosing $$k$$ vertices at random and adding edges among those vertices according to some rule. $$k$$-vertex rules are actually a generalization of $$m$$-edge rules.
!!__Half-restricted processes__
Half-restricted process is a variant of the Erdős–Rényi process which exhibits a discontinuous phase transition.
[[Explosive Percolation in Erdős-Rényi-Like Random Graph Processes|http://www.sciencedirect.com/science/article/pii/S1571065311001831]]
In each step, two vertices are connected by an edge, but one of them is restricted to be within the smaller components (more specifically defined to be a set composed of a given fraction, $$f$$, of the total nodes chosen in ascending order of {the size of the component they belong to}. This is also called the //restricted vertex set//, $$R_f(G)$$). note that the restricted vertex set is recalculated after every step, as the clusters have changed.
[img[http://i.imgur.com/tqD59s8.png]]
This process exhibits a discontinuous percolation transition for any $$f < 1 $$
!!__[[Spanning cluster-avoiding process]]__
An ''spanning cluster-avoiding process'' (SCA) is an [[Explosive percolation]] model based on classifying bonds between those that facilitate the creation of the spanning-cluster, and those that don't, and preferentially selecting those that don't. They are similar to [[Achlioptas process]]es ($$m$$-edge processes). However, they don't require the candidate edges to be chosen at random between any pair of nodes, and instead the candidate edges can belong to a predetermined underlying network, common a hypercubic lattice. They are capable of showing discontinuous transitions, [[for certain choices of the number of candidate edges chosen per step|http://science.sciencemag.org/content/339/6124/1185.full]]
<mark>I think there should be a term used for $$m$$-edge-like processes, that have an underlying network..</mark>
!!__Applications of explosive percolation models__
*Jamming on the Internet. [[Congestion phenomena on complex networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.79.015101]].
*Synchronization phenomena. [[Explosive transitions to synchronization in networks of phase oscillators|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3573336/]] -- [[Explosive Synchronization Transitions in Scale-Free Networks|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.106.128701]]
* Analysis of real-world networks. [[Using explosive percolation in analysis of real-world networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.83.046112]]
A [[family|Set]] of [[Probability distribution]]s, commonly used in [[Generalized linear model]]s
See [[video|https://www.youtube.com/watch?v=nLKOQfKLUks&index=4&list=PLA89DCFA6ADACE599#t=20m40s]].
A probability distribution is in the exponential family if it has the form
$$p(y;\eta) = b(y) \exp{(\eta^T T(y) -a(\eta)}$$
where $$\eta$$ is the ''natural parameter'', and $$T(y)$$ is the ''sufficient statistic''. Most often $$T(y)=y$$.
The Bernoulli and the Gaussian distributions are both examples.
[[Improving RBMs with physical chemistry|https://charlesmartin14.wordpress.com/2016/10/21/improving-rbms-with-physical-chemistry/]]
[[Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy |https://arxiv.org/pdf/1506.02914.pdf]]
Training an RBM requires computing the log Free Energy; this is hard.
See [[Models of network formation]]
* Edges (like hyperlinks) may also disappear. They may also appear at times after the nodes are added.
* Nodes may also disappear (like websites).
* Preferential attachment could be non-linear on degree, or it could depend on other network property of the node.
* Nodes may have some intrinsic fitness too.
__Models with extra edge addition__
Model can consist of the BA model, but with an extra process carried out at each step. A given number of edges $$w$$ is added to the network between two nodes with a probability proportional to their degree. One can again construct a master equation, and get a power law degree distribution.
Similar models exist that generalize the Price's model instead of BA.
__Edge removal__
Simple model: at each update step we remove $$v$$ edges chosen uniformly at random from set of all edges. The probability that node $$i$$ looses an edge connected to it, for each of these removals, is $$2k_i/\sum_i k_i$$. This is because randomly choosing an edge means randomly choosing a pair of stubs, and $$i$$ will loose an edge when either of these randomly chosen stubs coincides with one of the $$k_i$$ stubs incident to $$i$$. The probability of this happening for each of the randomly chosen stubs is $$k_i/\sum_i k_i$$, and the probability that either stubs is from $$i$$ is $$2k_i/\sum_i k_i-\text{probability both ends on same edge}$$. However the $$\text{probability both ends on same edge}$$ is $$0$$ because the BA network formation model doesn't allow self-edges to form. Therefore we are left with $$2k_i/\sum_i k_i$$, as in Newman's book.
__Models with edge addition and removal__
One can also combine the two models above. The master equation in this case, becomes more complicated, because $$p_k$$ now depends on both $$p_{k+1}$$ and $$p_{k-1}$$. Generating function methods need then to be used. Se Newman section 14.4.2 or the paper [[ Exact solutions for models of evolving networks with addition and deletion of nodes|http://arxiv.org/abs/cond-mat/0604069]] for detailed calculation, and a power law degree distribution is still obtained (though with different exponent of course), as long as edge removal rate is not too high.
One can also do analogous for removal and addition of nodes.
__Non-linear preferential attachment__
Attachment probability may depend nonlinearly on degree, i.e. we have a nonlinear attachment kernel.
One can still derive an asymptotic form of the degree distribution for the case $$a_k \propto k^\gamma$$, of interest because empirical networks have shown this form of preferential attachment. For $$1/2 <\gamma <1$$, the degree distribution is no longer a power law, but an "stretched exponential" of the form:
$$p_k \sim k^{-\gamma} \exp{(-\frac{\mu k^{1-\gamma}}{c(1-\gamma)})}$$
This function decays slower than exponential because $$1-\gamma <1$$. There are also similar but more complicated expressions for other $$\gamma$$ in the range $$(0,1)$$.
One can also calculate the case for superlinear preferential attachment with $$\gamma >1$$. In this case it turns out that the behaviour is that a "leader" emerges in the network, gaining a non-zero fraction of all edges, asymptotically, with the rest having degree less than some fixed constant. See [[here|http://www.math.duke.edu/~rtd/math777/Krapivsky.pdf]] for more.
__Nodes with inherent fitness__
Inherent fitness aka attractiveness may vary across nodes in the network.
See [[Bose-Einstein condensation in complex networks|http://barabasi.com/f/91.pdf]] and [[Competition and multiscaling in evolving networks|http://barabasi.com/f/90.pdf]] for a model. In it a fitness value, $$\eta_i$$, is assigned to each node (sampled from a given distribution $$\rho(\eta)$$), and is unchanged thereafter. Now, the attachment kernel depends on $$\eta$$ as well: $$a_k(\eta)$$. The same method used as for the section //Degree distribution as a function of time of creation// above can be used (with $$\eta$$ instead of $$t$$), and a solution can be analytically obtained for the case $$a_k(\eta) = \eta k$$, and a power law distribution is obtained for each $$\eta$$, but not overall, as it depends on what $$\rho(\eta)$$ is.
In [[Bose-Einstein condensation in complex networks|http://barabasi.com/f/91.pdf]], they show an interesting effects that happens for some choices of $$\rho(\eta)$$, where a few nodes (a constant number of them, so as a fraction, they go as $$1/n$$ and go to 0 as $$n \rightarrow \infty$$ and so don't appear in $$p_k$$) have a degree proportional to $$n$$, and so do contribute to quantities like $$\langle k \rangle$$. This is analogous to Bose condensation. However, it is not known which $$\rho(\eta)$$ will produce condensation, and computer simulations suggest, that whether condensation occurs or not may depend on the fluctuations and thus not be deterministic (see Polya's run; is this at all related to [[Ross–Littlewood paradox|https://en.wikipedia.org/wiki/Ross%E2%80%93Littlewood_paradox]]?
There are also interesting work on the statistics of the node with maximum fitness (which changes more and more rarely as a higher value of $$\eta$$ is sampled at some updates). These follow so-called //record dynamics// [[Slow dynamics from noise adaptation|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.71.1482]].
//More relevant review articles//:
[[Statistical mechanics of complex networks|http://barabasi.com/f/103.pdf]]
[[Complex networks: Structure and dynamics|http://www.sciencedirect.com/science/article/pii/S037015730500462X]]
[[ Evolution of networks|http://arxiv.org/abs/cond-mat/0106144]]
//aka eGPU//
https://odd-one-out.serek.eu/external-graphics-card-egpu/
https://www.amazon.com/SAWAKE-Beast-Laptop-External-Independent/dp/B013P0T3AE , has a review that explains how to use for Dell Precision M6700 !!
An extremum of a function $$f$$ occurs where its [[Gradient]] is $$\vec{0}$$.
Let $$H$$ be the Hessian
* $$H \succeq 0$$ $$\Rightarrow$$ [[Local minimum]]
* $$H \preceq 0$$ $$\Rightarrow$$ [[Local maximum]]
* Otherwise $$\Rightarrow$$ [[Saddle point]]
Where $$\succeq 0$$ means [[Positive semi-definite matrix]] and $$\preceq 0$$ means negative semi-definite.
The [[Organ]] to [[see|Vision]]
__Parts of the eye__
* [[Cornea]]
[[Intro|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=31m25s]] -- [[Motivation|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=32m54s]].
__High-dimensional data__
Useful for high-dimensional data, where the dimension is similar or much larger than the number of data samples, $$n \gg m$$. In this regime the maximum likelihood estimate of the parameters for a fitted Gaussian [[have problems|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=35m40s]], and similar problems would occur for [[Gaussian mixture model]] ([[Particular example of this|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=36m50s]]).
To solve this, we could [[constraint the covariance matrix of the Gaussian to be diagonal|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=38m25s]]. You [[could also contrain it to be proportional to identity matrix|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=42m15s]].
The factor analysis model [[is another way to do this that doesn't throw away correlations|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=43m]]
!!__Model__
[[Description of model|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=43m40s]].
Assume a latent variable $$z \sim \mathcal{N}(0, \mathbf{I})$$, $$z \in \mathbb{R}^d$$, $$d < n$$.
Then the data has conditional distribution $$x | z \sim \mathcal{N}(\mu + \mathbf{\Lambda} z, \mathbf{\Psi})$$. Equivalently, $$x = \mu + \mathbf{\Lambda} z + \epsilon$$, where $$\epsilon \sim \mathcal{N}(0, \mathbf{\Psi})$$. We also assume that $$\mathbf{\Psi}$$ is diagonal.
Basically, model the data as lying in some subspace, which is possibly lower-dimensional than that of $$x$$, and having some noise around this subspace.
[[Another example|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=53m40s]]
[[Some notation and some probability results for Gaussians|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=55m40s]] ([[recap|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1m20s]])
[[Distribution of the random variable (z,x)|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=1h3m]]. Result:
$$\begin{bmatrix}\vec{z} \\ \vec{x}\end{bmatrix} \sim \mathcal{N}\left(\begin{bmatrix}\vec{0} \\ \vec{\mu}\end{bmatrix} , \begin{bmatrix} \mathbf{I} & \mathbf{\Lambda}^T \\ \mathbf{\Lambda} & \mathbf{\Lambda} \mathbf{\Lambda}^T + \mathbf{\Psi}\end{bmatrix} \right)$$
This implies that if we marginalize $$\vec{z}$$, we find
$$\vec{x} \sim \mathcal{N}(\vec{\mu}, \mathbf{\Lambda} \mathbf{\Lambda}^T + \mathbf{\Psi} )$$
!!__Learning the parameters__
[[We could use|https://www.youtube.com/watch?v=LBtuYU-HfUg&index=13&list=PLA89DCFA6ADACE599#t=1h10m20s]] [[MLE|Maximum likelihood]] ([[likelihood|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=9m40s]]), but it turns out that the resulting optimization problem can't be solved in closed form, and it's quite hard. Therefore, [[we actually use|https://www.youtube.com/watch?v=LBtuYU-HfUg&index=13&list=PLA89DCFA6ADACE599#t=1h12m40s]] the [[EM algorithm]]. Note that $$z^{(i)}$$ is now continuous, so sum over its values become integrals.
''E-step''. [[Video|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=16m20s]], using the properties of Gaussians he mentioned [[above|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1m20s]]
''M-step''. [[Video|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=18m33s]] (using special trick for Gaussian integral). Go [[here|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=21m44s]] really.
[[Result for \Lambda|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=28m28s]]
A generalization/extension of a [[Markov network]], useful for [[Conditional random field]]s
[[Neural networks [3.9] : Conditional random fields - factor graph|https://www.youtube.com/watch?v=Q5GTCHVsHXY&index=26&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]] -- [[definition|https://www.youtube.com/watch?v=Q5GTCHVsHXY&index=26&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=2m40s]]
One node for each factor.
//aka Early-Onset Familial Alzheimer's Disease (EOFAD)//
Early-onset familial Alzheimer’s disease (EOFAD) is a condition characterized by early
onset dementia (age at onset < 65 years)
[[pdf|https://www.cambridge.org/core/services/aop-cambridge-core/content/view/AB96537F3AB11B3790F957D833CC9C04/S0317167100013949a.pdf/early-onset-familial-alzheimer-s-disease-eofad.pdf]]
Around 0.1% of the cases are familial forms of autosomal (not sex-linked) dominant inheritance, which have an onset before age 65.[37] This form of the disease is known as early onset familial Alzheimer's disease. Most of autosomal dominant familial AD can be attributed to mutations in one of three genes: those encoding amyloid precursor protein (APP) and presenilins 1 and 2.
Most mutations in the APP and presenilin genes increase the production of a small protein called Aβ42, which is the main component of senile plaques.[39] Some of the mutations merely alter the ratio between Aβ42 and the other major forms—particularly Aβ40—without increasing Aβ42 levels.[40][41] This suggests that presenilin mutations can cause disease even if they lower the total amount of Aβ produced and may point to other roles of presenilin or a role for alterations in the function of APP and/or its fragments other than Aβ. There exist variants of the APP gene which are protective.[42]
https://www.wikiwand.com/en/Early-onset_Alzheimer's_disease#/Familial_Alzheimer.27s_disease
[[video|https://www.youtube.com/watch?v=f5lTtDR_-FI]]
!__PSEN1 - Presenilin 1 mutation__
!!![[The mechanism of γ-Secretase dysfunction in familial Alzheimer disease|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/]]
__Mutations__
''To date, approximately 185 different p athogenic mutations in PS1''
The majority of the presenilin mutations are single-nucleotide substitutions, but small deletions and insertions have been described as well
This protein has been identified as part of the enzymatic complex that cleaves amyloid beta peptide from APP.
The gene contains 14 exons, and the coding portion is estimated at 60 kb.
The protein the gene codes for (PS1) is an integral membrane protein. As stated by Ikeuchi (2002)[10] it cleaves the protein Notch1 so is thought by Koizumi (2001)[11] to have a role in somitogenesis in the embryo. It also has an action on an amyloid precursor protein, which gives its probable role in the pathogenesis of FAD. Homologs of PS1 have been found in plants, invertebrates and other vertebrates.
[[prenesilin structure|https://www.youtube.com/watch?v=WafxnJyK5Fs]]
!!__[[Genetic dominance]]__
Some of the mutations in the gene, of which there are over 90, include: His163Arg, Ala246Glu, Leu286Val and Cys410Tyr. Most display complete penetrance, but a common mutation is Glu318Gly and this predisposes individuals to familial Alzheimer disease, with a study by Taddei (2002)[12] finding an incidence of 8.7% in patients with familial AD.
http://www.omim.org/entry/104311?search=PS1&highlight=ps1
!![[PS1 Familial Alzheimer's disease]]
[[pdf of my essay|familial-alzheimers-disease.pdf]]
--------------
Molecular genetics of PS1
[[Summary of yb vid|https://www.youtube.com/watch?v=l6jafQERb7E#t=41m15]]
---------
Literature
[[The amyloid cascade hypothesis: are we poised for success or failure?|http://sci-hub.cc/10.1111/jnc.13632]]
[[Three dimensions of the amyloid hypothesis: time, space and ‘wingmen’|http://sci-hub.cc/10.1038/nn.4018]]
[[Alzheimer's Disease: The Amyloid Cascade Hypothesis|http://search.proquest.com/openview/e965729ff54db4d8a61fdb184525be25/1?pq-origsite=gscholar]]
[[The mechanism of γ-Secretase dysfunction in familial Alzheimer disease|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/]]
[[Twenty Years of the Alzheimer’s Disease Amyloid Hypothesis: A Genetic Perspective|http://www.cell.com/cell/fulltext/S0092-8674(05)00152-2]]
[[Neurotoxicity of Alzheimer's disease Aβ peptides is induced by small changes in the Aβ42 to Aβ40 ratio.|https://www.ncbi.nlm.nih.gov/pubmed/20818335/]]
[[Early-Onset Autosomal Dominant Alzheimer Disease: Prevalence, Genetic Heterogeneity, and Mutation Spectrum|http://www.sciencedirect.com/science/article/pii/S0002929707623179]]
[[Alzheimer's disease.|https://www.ncbi.nlm.nih.gov/pubmed/21371747]] [[pdf|http://linkinghub.elsevier.com.sci-hub.cc/retrieve/pii/S0140-6736(10)61349-9]]
[[APP binds DR6 to trigger axon pruning and neuron death via distinct caspases|http://www.nature.com/nature/journal/v457/n7232/full/nature07767.html]]
[[Abeta42 is essential for parenchymal and vascular amyloid deposition in mice.|https://www.ncbi.nlm.nih.gov/pubmed/16039562/]]
[ext[Mean age-of-onset of familial alzheimer disease caused by presenilin mutations correlates with both increased Aβ42 and decreased Aβ40|http://onlinelibrary.wiley.com/doi/10.1002/humu.20336/abstract?systemMessage=Due+to+essential+maintenance+the+subscribe/renew+pages+will+be+unavailable+on+Wednesday+26+October+between+02:00+-+08:00+BST/+09:00+%E2%80%93+15:00++SGT/+21:00-+03:00+EDT.+Apologies+for+the+inconvenience.]]
[[Neurotoxicity of Alzheimer's disease Aβ peptides is induced by small changes in the Aβ42 to Aβ40 ratio|http://emboj.embopress.org/content/29/19/3408.long]]
[[Photoactivated big gamma-secretase inhibitors directed to the active site covalently label presenilin 1|http://www.nature.com/nature/journal/v405/n6787/full/405689a0.html]]
[[Pathways to Alzheimer's disease|http://onlinelibrary.wiley.com/doi/10.1111/joim.12192/full]]
[[Autosomal-dominant Alzheimer's disease: a review and proposal for the prevention of Alzheimer's disease|http://alzres.biomedcentral.com/articles/10.1186/alzrt59]]
[[Three-amino acid spacing of presenilin endoproteolysis suggests a general stepwise cleavage of gamma-secretase-mediated intramembrane proteolysis.|https://www.ncbi.nlm.nih.gov/pubmed/20534834/]]
[[The Proteolytic Fragments of the Alzheimer’s Disease-associated Presenilin-1 Form Heterodimers and Occur as a 100–150-kDa Molecular Mass Complex|http://www.jbc.org/content/273/6/3205.short]]
[[Three-Amino Acid Spacing of Presenilin Endoproteolysis Suggests a General Stepwise Cleavage of gamma-Secretase-Mediated Intramembrane Proteolysis|http://jneurosci.org/content/jneuro/30/23/7853.full.pdf]]
[[Amyloid β oligomers in Alzheimer’s disease pathogenesis, treatment, and diagnosis|http://link.springer.com/article/10.1007/s00401-015-1386-3]]
[[Loss of proteostasis induced by amyloid beta peptide in brain endothelial cells|http://www.sciencedirect.com/science/article/pii/S016748891400072X]]
[[Structure and function of γ-secretase|http://ezproxy-prd.bodleian.ox.ac.uk:2054/science/article/pii/S1084952108001146?np=y]]
[[Overview of Intracellular Compartments and Trafficking Pathways|https://www.ncbi.nlm.nih.gov/books/NBK7286/]]
[[Take five—BACE and the γ‐secretase quartet conduct Alzheimer's amyloid β‐peptide generation|http://emboj.embopress.org/content/23/3/483.abstract]]
[[Amyloid beta protein gene: cDNA, mRNA distribution, and genetic linkage near the Alzheimer locus|http://science.sciencemag.org/content/235/4791/880]]
[[Synapse Formation and Function Is Modulated by the Amyloid Precursor Protein|http://jneurosci.org/content/26/27/7212.short]]
[[Relationships between the amyloid precursor protein and its various proteolytic fragments and neuronal systems|https://alzres.biomedcentral.com/articles/10.1186/alzrt108]]
[[Trafficking of cell-surface amyloid β-protein precursor|http://jcs.biologists.org/content/joces/109/5/999.full.pdf]] [[pubmed|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3331683/]]
!![[Very nice poster|http://www.nature.com/nrn/posters/ad/nrn_ad_posters.pdf]]
[[A-beta Oligomers Cause Localized Ca2+ Elevation, Missorting of Endogenous Tau into Dendrites, Tau Phosphorylation, and Destruction of Microtubules and Spines|http://jneurosci.org/content/jneuro/30/36/11938.full.pdf]]
[[The Intersection of Amyloid Beta and Tau at Synapses in Alzheimer’s Disease|http://www.sciencedirect.com/science/article/pii/S0896627314003900]]
[[Risk Factors of Aspiration Pneumonia in Alzheimer’s Disease Patients|http://www.karger.com/Article/Abstract/52811]]
[[Relationships between the amyloid precursor protein and its various proteolytic fragments and neuronal systems|https://alzres.biomedcentral.com/articles/10.1186/alzrt108]]
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
JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDMwMjUgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjanVlJk9u4Fb77V/RlKlRViyFIcJtTnDieOIdJV40rlx4f0CQkIZZIDUG6Lf/6vA0U1aYznhy6CTzsb/neor++f/Xnt6q4U2Wcqlzfvd/dVQU067tS5bGq87v37d1j9HZTVpE5uaMzx802S9Lo9fHLwbqTHf7kmdA6b4232FHRbuhPTD5t0iKaRjO6vpOZruPveLCbD+//CeeXy/OzHA5W1V3CRz/8omTWzS2zMk6yedLedmGv6k6puM7zFGdts7SKiySFRhJnKuXZP03ueLTDqYd7wO3+valUZIDC3YdNWkZ2sF+4u+V903K5r0qzWJf5fHzYMP6E+/ylHZu4/xybJp4+rl4rVbHOS/hq+Fa8yc89HvyJTgeuVdHTZgv/7cD3UPf8TRNVyJXqO6XjTBe8pyrruKzV3VansQaW0qbvuk2monHAp6qonRqUg1wpv1NJXCewBJYndJksFxbdijfLF+LNiujXJE9ev4H/igedZzpsrSKZ0+94DKVMjZPZbPMi+k8/cL8xk7f+djKcYp5Ay0Z8/4Vppmt5UmvPwBHgTtfarrkw0Zz6bs8T+2MLzIK34WNUFueivGfmY39GCWtg4TPu3g/H9tm1RCqjx7T8EG+2ZZpF70aeZZqmnzoUx+iZssOrY6NIeNXYc79MfuAGvgMHWuaDik62w8NGZ0B8WtfR88E1uOeBFxATWm7rqrhPEtm6tWY8wC5++SBd84vQgnSiURcSbsH974WW4UMK4PTbTZVdjRbHbqSKhFmq2EGpvt0opaIgW6QOdmcHmU7vha/hD/DjxC16Nx7whr/8yopeCV0n6/fEky4wZ3TQ2q49sAEzQgFXeXR0OP8jmQUqQqVFIypUoY4pYipMdd3BDqBCcgrKAjiS13X0nnQR5vdd2B7f4IW4Y1LgAVNBRUSEvyZKWznZDLKTmcbe9yeCRaC3/cl1hhesPYwMewGHRcJwCN++s9LY8Xc8DFZIiG/+R2BijTBMxnHsXcuD58E20+DJrqjbj5Y2zWuSKZt7lizNPa1VDMoeAOz1w8MaKAAiJOkMsqgT9/OR3nbuGO6u+POt00odp3X+NaLfHpbEeXVzmLBjfpdlXdlqWFVk+paz1/uAlaX4+m/fR5dxURXX+6Tfd58YBZChFhEQwgGICGDkqGaeTybhwYiZYABUA4dQPbakGUAzDCk8+xZmYdkVZnUtMIvTZ7AFasClijaRSxBfiipOS32DfUfrCWJr0CYylqyK1A9MYdCtWNPh2+BdjWByBZCCQKKB8//o8bRnMsFPG/JJqAcaVTRY2YUXHQyO8yQ+BdTxSmqZJpvIGndihO6H0czvgllO7jsB3g8exlrHUF+Hc1cM7Ayw2Z8PZCLe9cd+j6fg7jv+vn5DjhT46Jkwijih+dI6cdZg52myEWMHtFagAXqtHSEUcJ3zI4AgbbIzzdgPch55Eb7J2gOI7Ss6q4q4zorbud+ypDxOilm9CXwVqsmEuKkB2/qOSYzREKshhFkeUxodSQb2ZlC34Q3T0Qz45OVK4gZP/y3Vsttl7AGo8NHYPfYk1Ya4yZMfNfmmMo9+GsC/iTWncYIR2vJhpv20AQ9muoa0sSxZGeD7UhmAFJQQ26f+aOnC3LUgmMw2o2xCOgDfgPBbAIyPs2LCADIUGgVqQomawPKV5cFBprgUpopNwsiN2n8dgYh7Am3ZpjVaMEUAToypRTPLMvFOCTBymBry2Th5N3UctNEQvQC+D7/AmxW3nYzN8XSmbrQBQuUSwtcZyFS+pjQQ9UNkLZO23jaDHSWeF58y9x4z/QGNKCkAX1o5vOfrjuERgGTNwvLB2Enaqc7iulK34gZsAptPQenA73NjFhGJhIbOEsihcJFAR+JAI4ufJGrkjcAKSUVoKt4qhQh4h7AcGIoEZCjPQDvBlu2+XE4W3pfmSizEdPuXW9EDx8E9TSGifmnItDMGEKg+2EAkxAdgFO5R5tB+18mYGcTS8OBayzEwMqD9cDPsOM5wLAMSxCznLKOENaWo67hSeqEUek0pYJIuFi4web22mYKEI81/b68iLm/2UvLS9S0hbYO85o9sqdMfV7dK01il6o9tlYjohKmuA2swGKiTDmdVFqvkBRY/FoRtBUaZHO/WHJ/qBHT28/lonHSeD6KnOIWBNLn1PTzkKPyn5jKsvOcEwXjZmjNG2dvt+MtOClu+p/BETull/BtYkYFaaJX/v1jBeJ7kILv6ljsv4oIi5IWFnqF2JCgBAoNwoSUyzjHdwO4BHWv/5bIHLOKBxgyD42CkTMWEkS42g4ueHSIKEp84eeTOLFFZyykFDFAKSw7+erA/ISx9DethE4xJMkmCMWH6bXIDhzoZgRR+ZwbwFYBCkQrEJ66h5AEoS2+VYU6XcCiw6vtfXw18uyZKxNnvse989gwHQ+qe37grzsBmJ5lWBeMu0DFuxK8HPlhuCmrlkaqrxJOB56DvYSc38g6UgIfTJC6h8c5TRo5tQ3pxQWlQpoPrwIh+m0LEyZnxtkziMstWoDeXG8IXWO3s7MqR8qjKe25llC9rVYndIo28GjboqXl4V57fJl9IaIxvTCujbNgSzWJc6YgHZbJM+3GiR3X3YW9yfrmWAgcs9e5/OhV82Spo1nGZZ78v8+ucvWOTlKsMztNLivnhuMnTADZETneNASSTsAGZETY6Ow39YvFF3gqeFFISYopaVgmY66b1t3xvSNIUE0CPaiL3EkfUcVplL8siCFjmdCIQvWejkvJRdgVKVINJCgxAb+21SPO1ueWhHgbGOu2pakPqMEgtiaAeSJ2Ugtp+esKwmXssW1nCJE6dG8tkLhh9pdk0Rjentcw1qRj1w2CPrD44+OxGqSVJPrFdQwt/OZ3H/oSc1xQyWy5H2THkSFqSV62r6/C1PgRUeioQIa9BiVA1C8yVHI3GvOeJMRwHwL6onlYvsscqZI/4xkFuwjW15ZmNHEjXWTEBzIgljdO6COsKSrICyUhr3UyAQXpZ1li3E6XiQs1xA7tnL/uCuIIPh57hz9Af5SrMqQI4NfQgOpnmpzMXMCHRZT4Vc8h68xL7CTPLRnqG4bifxus0lnNaxUn2wtEu0gXQbU7xs1CE1dcoI/gnqiwFf1OE1PO2tAwCyDKIBJVknQesKS+y6zKXzCp4dWhgRYkaZ6k9QybnJWUD/Lv40Z64zQYKDVZr6aB3xGOeNxl4Zz7we+rWS3jSZbUsjukSqxFgZBQ/KIqvOiZTaPvwIFXPUnQdf/Pgz7gAdsukdzIymM6fLDmrJ2jbcKwU4bAz4xyobK7yKNAJJDtPVAo2V2rXgzsZgFAK5q45fKKkBpwAKztzpqINUh/TmsJQ0BOqYwPpwJFisnTrSDfe96SOkGuyPgJR0ARaPpR6uHiczJrlw/nNceIkHEcbexsiBX1sHQU1wwyxAZprWQPShoy4RWc5DyBjHAV5MAaKv+ca0jOiP0xQ4dE8YVGEM1j1DfsoYTCFV8Duk9sPXNqRYdS8tRotB9rIcoj9vdvDDvxOStTGw4xnhkIUzyNU3aMa2hEagTWYiolXBwD2TiY/qvSeW4rij6ouOP/XnCiK8kCHxVdx0R0+4Ez3Mu/nLVeazDrn+xOnHGVxU4+HrmNhgGwp2EQcFsHD4K3gyyJcx89r6ctoBQ37GWwARcllFySBAx7cZ3xWKWWNxamLySu3/tv1TaGgTq/Iqq+ujcN8bRy8uTYOLSRVRgzXLPgq/IBQcG5Okw+9h7/hcpQEDImD3U/iaV+esGapUu8CnGNEzZY2Qt0Q2bM2C0YTe/vjhauFWagTlAvERHAmPflmMoBoq1P5pSXFqsHZtZLJYB+cUNP7iwAsUsxutAM3CcOOwTLJ53Qya6TYfZ40F2p5F3QsQwiLdIhxYO/PfVjVfzsmASfq8UdBcDPRSX7yRAT1TDIjf68Ah73HTH3gFlXj3D7mngoF+iqN/kW+M2NfOdh7rpsz94F4MMfd9uh2Mgerh0aGFhDJtzJ+4lROc0y8mEQPS9M0riFKwHi0quSXXCrKvvr7+1f/BXqyNv4KZW5kc3RyZWFtCmVuZG9iagoxOCAwIG9iago8PAovTGVuZ3RoIDIwMTggICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjazRjLbuM28J6v8KWADKy44lNiDwXSfaDpYZEiuaV7UGTGFiBLrkR31/36znAoW06UpkF7CAxY5HA4nBdnhvPz7cX7z1wveMZsZvni9mGRi0WuC2YlzFaLu+R+mYoicX4J/9/wz7l2mcrCJDLDr062dYvwvXcDAcp2RRiK5ptu3w9smZosS+5k8Y6gQr+LdEyEyOxrxJJZqrIfaLl7iMe4LR5z35etI8jl9TUN6oFQ/YZ400nVuBKx/1yKPHGr5dfbXxfZIuWSaWVJsMFVvfN1u4YdnMPeJU8cjYEwUuRZ8tCX6y0QBSoeueQ6+bapmxMqHEmYvRs8gaqyJVBUHUFXbt2XK7eipa4fd1UH4HWZAsK4CfYcnvLk2lU3dNuyITTU8UQoTTI1h+GIJGWyK4ECsB7sFvRxGGjljksUR6qofQDxArQPJC8+3V5woJst+IJrwbjMFzovGDCxqLYXf1wwE1bjJ4BUocNESDkC319t+eJjd/Eb/EZy6UgvnRD8+akPcquZ1WahtWK5jfb6XK/3vYu8/rhMlRo9AADl964dpfbgIcMu6L7rfZTuoe+2UXTJvwbVpTzLWSYWqVDgFZJOCRSFEsmuB913PpimQ4Oj6nhSw2ggjGBnHEQ7r+sw58m3GtQeVsqIefRGbZJy7Qhax+21H5Cf95/hyk2UIIRmubaguMDY7xmXhHauK8uMNiMSuNUMJS6YNHJCSM0TksURaajhNoPqhMkSUqXrH7p+i/5LIgcvnTnMcmZF8Squoy8/UUDGBBcvsW1Yro6UUrrU5eDekYlVJpiR9vzmw1WNMlW+/jPEtOawLGQC0UfB7HbjBrQRRJSyj4OqbJogPIUZGrRdm5YhKh2arl51a9fWVdzYRuRn1ulqFmdXE/VtzT+xNxPGrsCLFJfEFA6qcggjgZFzRq05ZyozL6mVcybU0fkmDqzRgYFTJYN744kfrKXBMVoWiSdI77Zl3Q40qVvi68jqNKQHkpL0FpCHI3KU8HFMD8v3OJl1xLQA00NgPNMWiKvnvUho9dSLkCeFwRITU65ydA2CfUm96yHzYdDB+SPRARIEgC8RC/zCrNv7oV5FIpja8OtHqpVrGlSEtlERCMMwg4NjOsHJ5ZzICiKZlOZVV0Zl41WRedg8zSezpxSMF6+7lkqgUDlPStSJUrGQaBqaEVTOn5ZblufFv3BXHXJQwIrBvzngAHxl50Hl8eigc/yC0ns6t3Ht2m+wQslzDRcqGkiNhgGU0TA5OCRkgE1c/zD1ApTkdNnHFAOeZfm5E1K9BGkKqe6bsqfEtOrwrlBW/j3T2eXVh4/w5bRax8xdNkNHOL2DCzG4FZuN+QZKOPOfnV8km2AdyUf3C7cRpqAjKovqYJNQp4QiBhd9d7bnFC0ABvKuHQ3D/c/p/qf3wVbdnvwekma33TXuO2GOuQcXxgoJ4TsIli4lXQvJ+KNI39ZNCDqZCBq9vgE+Oc2xAsPv9Y1AJaNxOd66YBrX17QOJ2zK/tB+J+SVezgF5ZSXJ9KX17/AnMx1Io+lJMDvI3VkdsKSazdlW7k+FXOBPTD86Ut6ZA8TRVBOZkEwCPO+p4iKVbUKpTO4541zhAL1EqORCEsyufI0Lys/0ChGzzBGM/ZDRDnG2lAf4xEU5GGJuLfhbsw4nszB8/S02sjnfK5ghT2rNqKE5NR4arAp1PKsUI+CEtyLECSzqA9lxywBoNrTd3B/7GM8riF3Hwha7YPoMIpXOxhl39A7AOGPYwd69Q7cxlNQwBPaWbnB/UzOT3KLbDZQZUydAtVzlY8ApGmI1c/EPG7OCjaMYFYlH12sH9rVSZEmh1K6OHexrqVcQ7rQQRco7x7kbVCPUP2FeKmfNTeHAktx9ZK5LVOy+Kdqwo4WMaPpqsjTyEA9Xk0IBHXpIy5ZKZqrmIR62EGZE5H6elv2NTmBTe6jZSlCgxoLLc4V83/lPTuvMhyOOD/N346Jk/xfzJi3xIx8S8yERoaiRzn2FebjGhOZfB3d4i0Jqd8SM+INMUMdKZtDXqy6fkUdIXAHLGLQHTrqN6lk24UYs3INze8MJl0NOy/nSzDFDLcvlq4wPMXG2sdqRqkMXu3mcc+qwW4YPBKxOvi2wW5EhTl8g9DYCLP4MO23lPQQuu0GT2MTsjfCqG8FgHnW4RUvhX79LQKCUKoBV1vMI7F6hePKXYzPZT9EBjpC790aSmDvCDoc2hJCeEVruwaKnLqq/dgTs/rY+Eq5LViWPyqtoaLsesQ0ItSMpa8xyeH0ThTBXDJLPuNrGpNcj48A2IEpSBr7nDIkU0b9Czsae8QKloBTJ5YwYtoENKdCFsclfQbnaRC6ngYL3M47eEFHBqHehWdCPVa8mWJcF2fVURtL2HAkvBfgObOHijOlo8m54fHg2r8O29hNQ1+6+vgp1plyfIXj4IvbYd4cpu+SL5+uT8+SO65m2obSMGVtaB+aPHYNLXUN7alrKDVYsIitQ26hkBCqmPQPxdP+YSScnijPtg+x6SMWXNigniftQxHbhze+31f+CJ7vl/CsYLnIX6rGnnlExS7rtP2oYvtR8AJkyGEAqSWnjdc3+H6QOnYPND2adJKnu3KIoNDfPO+GIzh6ChZT4DcQGypE2NAido8DAlRKg4uEak/xBMdo2HLvT0j1EB8ziBgq3oXINLO5AoYtK4qoVzEa/2/KKPl0CmVuZHN0cmVhbQplbmRvYmoKMTQgMCBvYmoKPDwKL1R5cGUgL1hPYmplY3QKL1N1YnR5cGUgL0ltYWdlCi9XaWR0aCA0ODUKL0hlaWdodCAyMzMKL0JpdHNQZXJDb21wb25lbnQgOAovQ29sb3JTcGFjZSAvRGV2aWNlUkdCCi9MZW5ndGggMzI1NzcgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNrsXQVcFdkXHkAxMQgFERFEJQwUW2ywxW6xZdd2zbVjXQs71+7uWLu7RQQVEFAQpRsknf8378jd8T1kVcAF//fwfu83zJs3787Mvd/9zrknRJELFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDhwoULFy5cuHDh8qPl48eP9E7CtpV25uqrS0lJwfvWrVt9fHywkZqayp87Fy5ccgUyJycnE4LRHsAX9tA7hHbSMbSTHZzroBsNJnD29fUtUKDA6dOn6dJy9RzEhQuX/x+4VqLQSp8C39Kl2fKDc9ElA5yxMXr0aEEQ5syZw+GaCxcuOR+4GJd2cnJau3YttpOSkvB++fLldu3atW/f3sHBYePGjXTYggULWrVqhZ29evW6e/cufTHXoRxR64iICCMjI8A1rohsIxyuuXDhkpPhmmwawF5NTc3q1avHx8fTnpkzZ1aqVMnd3f3o0aMlS5Z0dnbGTuwZN26cp6fn9OnTixcvjg0xF1p9iVqfOnVKXV29Ro0auLrY2NjcqCZw4cLl/wquCbuGDh06ZcqUxo0bnzhxgj6aPXt227ZtaXv9+vVVq1bFBt537dpFO5s1azZ37lyGfrnukmfMmKGjo7Njxw4Q7CdPnohpi49cuHDhkmMtIUlJSeXLl/fw8Jg0aVKPHj3oU7DrNm3a0DYYNcAZG1ZWVgTXQLaKFStu2bIl98J1ly5dLCws3rx5A7jevn27yM3XXLhwyfGWkDNnztSqVQsbDx48AG5HRkZie968efr6+kuWLHF0dCxduvSdO3ew09raukWLFthZu3ZtOzu7xMTEXGdDYHBta2tbr149bGhpaQ0fPjzXzTtcuHD5P7SEjBo1qkiRIh07dmzevLmamtqpU6ew848//jAxMVm8ePHatWuDgoLoKzVq1OjQoYOzs/OxY8dobS7XOfIxLz5oCrTIaGNjA+gW+WojFy5ccjBw4T0hIQGMeteuXc+fP3/9+nX37t07d+6M/dOnT2/Xrh0DMQL2qlWr7tmzh3bKXfty11VTgy0sLMjaM2DAgJIlSxKGc7jmwoVLDhRC4EOHDpUrV05Mc/C4ePGitra2qFhqJHs18DxVIdiuXLnypk2baGfudbqmNpubmxNcr1ixQhCEwMBAkcc2cuHCJQdbQv74448pU6ZgIzExETvx3rx5c3d3d7DoESNGMHZNONazZ08yleReJwpmsa9Zs2aDBg1EhekecH379m2RO4dw4cIlp1pCPspETj5/YssAm6caNmxYo0YNbHh7ewOud+zYIfLVRi5cuORsxJaDM4s3V90vymIYcy+SM7ju2LFjxYoVsREfH58vX77JkyeL3JePCxcuOZ5gi5/nCfmSy0fuzROiCteDBg0yMDCgnRUqVAB6c7jmwoULlxwI15MmTSpYsCCoNbbt7OwobDM3pkDhwoULl58brhcsWCAIAsUEDR06VFtbm3JbcbjmwoULlxwiBNcbN24EXPv5+WF75cqV2A4JCRG5Lx8XLly45DC43rJlCyD6zZs32D5+/Di2XVxcRO7Lx4ULFy45Eq79/f2x/ejRI2wDtMXc78v3E1Rn48KFCxdVuH779i22Q0JCsL18+XIx1zqHMIhmmU84YnPhwuXngOujR48Cot3d3UVFRKe2tjbLy5cbI+vFtIBNvCclJXHE5sKFy08D1ydPngRcu7q60s4qVao0b948N8I1i2Aiz5bz58/v27dP5AkGuXDh8rPA9alTp1gdGUi7du0oyDF3GX4ZVtMK6fr16wsVKsSL43DhwuXnEMKxW7duAa6vXr1KO8eNGwego6iZXAHXSsZqUOuhQ4fiihwcHEQe78OFC5efCK7v3bsHcLtw4QLtJDfsgIAAMTe4XjOsJk0hKCiofv36gkKo2iaPpufChctPA9ceHh4At8OHD9NO4Db+vXnzZs43I7BlRDJWu7q6GhkZ5cuXD+1v2LChyH35uHDh8rMIkWc/Pz/g286dO2mnl5eXvMZubsFqzDJ58uSpXr16z5490f7r16+LfJGRCxcuPxdch4WFAd9Wr15N6BcfH6+pqUmVGnKsJUEJq/fv349LaNq06bVr19TV1YcMGcKwmsM1Fy5cfhq4jomJyZs37x9//MHodIUKFdq2bZtj4ZphtTznSbt27TDR2NjYlCpVKiIiQuSLjFy4cPmJhNUULlKkyKRJk7D94cMHvAOrzc3NxRzpy6eE1ZSTqmvXrtgeMWIEtq9cuSKmWd05XHPhwuVngmu8GxgYODk5Mbj+/fffNTU1wbrFHOYcomQDoVrA/fv3x/bWrVux/eeffzIdgWM1Fy5cfjK4hpiamvbo0YPB9b59+wB9z58/F3OScwhz8yA03rRpExo5YMAAbN+5cwfbVAeHm6y5cOHyU8I1kWcrK6s2bdqICsOIqPCIA/odOHBAzEnma2oG8eq9e/eihd27dxcVni0lS5Y0NzdnJmtOrblw4fLzwTWR51q1ajVq1IiZEeLi4jQ1NcmanUPgWh4Lc+7cOWB127ZtgcyxsbE1atQoVKjQixcvRG6y5sKFy88L1wSAwGogNsEdsdPq1asTgOcE12UWY453FxeXvHnz1qlTB3OKqMhwAui+dOmSyE3WXLhw+T+Aazs7O2tra1GWzm7IkCHFihVLTEz8zwGQ5W7C+/v3742MjIyNjbGBf52cnIDVu3bt4ljNhQuX/xO47tGjR7ly5WgnwfWOHTuAhB4eHuJ/6hzCXEGoqba2tvny5aPaZDNnzkQLlyxZIqZZbDhWc+HCJWMY+Tng2szMTJRZs58/fw4w3LZtm/ifmq/pDlOThg8fzgqTkdveuHHj5M3jcM2FC5cvYTWAIlf7IaQL13RFeNfV1e3Xr99/CNfy5UVy25s3bx62b9y4ge0OHTqIstBF5uaX+rl8lAmHdC5c/s9BO/cidrpwzXZ27tzZyMhIfrE//vay5UXmVv3+/Xt9fX1LS8vo6GiCa0iyQlQBWf6M6Bg5gPM+zIXL/wlQR0ZGQhm/e/eumGvXuTKG682bN7Majj/eP4Qhanx8vJWVVenSpcmt2t7ePm/evKyyJPPcY17ZISEhQTLB1+UwTlfHq+5y4fJ/IgQRFEsC/unj4yPmTo/fL8E16Qve3t64wBUrVvx4e4h81pBnApk3bx62qQIjea1AAgICtmzZQpdQqFAhNTU1QSb58+cHG69Vq9aQIUMOHTqESVZMM9ErQT0XLlx+SnZNI71bt24ABBsbm/DwcDEXxtMxSOzevTvBtfh5Sv8qVao0aNBA/LHZ7eQm6+PHj+MOz5w5E9tQZLA9cOBANjleunTJzs6O8NnAwMDBwWH8+PGLFy9etWoVZpmVK1cuW7ZsypQpAwYMsLW1LV68OKG3k5PTq1ev2HNkXiUct7lw+YnhmsLrIC1atIAanuvs2AyumzVrhkmHwTLbP2fOHFydv7//j0RsdhtDQkJ0dXVr165NNxxzh6GhIdHjGzdu1KxZE20rVarU7NmzPT09M7jzzE7y4MEDoH3evHnxxc6dO1NSFL4QyYXLzw3XbICDthFiDx48WJTZeHNLUVqad+rXr1+vXj1Rlh+J9ru7u+PS1q1b98PsIfJf79u3L3798ePH2P7jjz+wDZSOiYkhpaZMmTI7duxgqwb0rSSF0KoiNhISEuLj4/EuN1XhXxBvTATAbUdHx2vXruWEaCAuXLhkNy+l5HWamposeyeFmeSuGuKWlpaU4knuX0Eb1apVA4+VE+8fYwY5deoUbun8+fPFNCfwUaNGnTx5skCBAnny5MF+wlhy+ZBn4ZObOOQXEh4e7urqeuzYsY0bNy5btqxjx47Myp0/f/6zZ8+KOb42JRcuXDIDdIAFKOkY8sAQvO/du1fMPY4irIWGhoaUiZQVZ2Tz0erVq3FdT548EbPfP4SZQaKjo0uVKoVpgvAT0Io2NGvWDO9NmjTx9fWlxig57xF0yx8NcB6qQc+ePU1NTTU0NNj6o7q6eokSJWxsbBo3bty+ffsGDRrcunWLwzUXLj89waYIDsA12FrBggXv3buXWxCbsDEuLg70curUqUpwTZ+GhobmzZuXqh9ma6y3nFqTN8j9+/exDd5LGAsVZu3atezOq7rnMVft27dvDx8+vGTJkvRFbLRt23bGjBkHDx589OiRn59fTEwMz7PKhcv/IcH+8OFDhQoVmEkERC4gIEDMDY4i1MJ3796h2Rs3bhQ/L33O5iNAHyYjyqqUTQuOcqy+du0a2jN9+nT6qGXLlkSqPT096Ri5IZpMH3QhUVFRK1euLFu2LI4vVKhQ586dd+3aBSqu6vUhD5+BcDdsLlz+H4QQhqpQQcUmr4OmTZsmJibmfH8Dwj1ykDt37pwqXBMMAieZN102aQ3yuc/MzMzKyiopKYl+/cSJEwsWLKBtVesHXQK+tWjRoqJFi6KdDRo0AIuOjY1VgnRagiRsVwpO554hXHILOeSS+XsYHR0NUg2sAFwDtLFBpQ/lPr051pizc+dONNjLy0v8PPme3EmjX79+0B2CgoKyg2DLqfWoUaPQGDIoyVk0Q2Z2M9meM2fOGBsbU5T6s2fP5C2XR51zNOaSi4BFlCVPIKZB7/IkOfxGfTfBXr58OXnzAjoaNWqEbWdnZzEHG7EZXE+aNCl//vxUpVGpnYxge3h44IrGjBmT5Vckx2oAL35lxowZcp6frpsHmS/QgYcNG4avVKtW7cGDB6LMLYTnBuGSq4Fayegn/5QtqXPQ/m6CHRcXp6en5+DgQDeZMuefOnVKzKmufYw5Y3IB3KVLm+UhM+PGjZO7iGTJFclLDwQGBurq6taoUYN55almqZVje0BAAA5Gk+bOncswnFuhueR2rJYrkp6enrt37164cCE41Z9//rllyxYXFxf6VFXf5PJNBJss2Ddv3hQV1tQGDRpoamq6urqKOTKjCDUmMTGxWLFicscP1cMITiMjI0uUKEHRNFnig62U0rBFixZ58uSRl19XnTvYrcZhpUuXLly4MOUS4VmbuPwcWE3dGCNiz549bRQClXbp0qU7d+5ctWrVxIkTQQjt7e3Xrl1LVbA5Yn83wY6PjzcwMKASh0QXqVJVcHBwTkNsRq2fPn0qdxdPF67FzzN4YK7PvMrAoJXO8/vvv+PM6KJfMrbI86m+fPkSEwd0GWxQSzhQc/kJsJp6/osXL+zs7Lp373737t101Ux3d/dBgwaBOOXqdKA5gWCTD/b58+dpJ9WBBc0mR5Gc49rHTBykEbx+/Vr8cpEv+ZrjL7/8wkrZfjdiK2E13TQgtvgF1265zQRzn5mZma6uLsNq+TFcuORqrMbIMjc3P3r0qPh5LncmtBOfQou3srLKgOFw+VeCjftmampao0YNhiQUTN27d28xJ2UUYfCLebxixYr/qk+xT6GC4eq0tLTAAeSI/fVXpITVBw8exP0Bl8jg/sjTukIT1NDQoHKNvJdy+WlsIKLCpdbCwsLNzY1GluoijijzSiX9HYPx8OHDYu5M4JwTCDbmO+DPoUOHRIUFG+/r1q3DnokTJ4o5o7CgPGIR0Dd58mTx3zI4yfmtn5+foaFhyZIlqfDuN9ki2HnkWI0pg25UutqHnHtQoqcDBw6IuSo3Cxcu/0qEYmNjbWxsrl69mvGYkjNDvHt5eVWpUsXb21v8sVmOf47bTrfL2tq6QoUKLG8n3qdNmwacWbp0qZgDbK3MErJt2zaW8u5f84HIacDz58/JekzfJSaQMc1W9VBav349YXVcXJz45SBQpgjgt3D8r7/+yu4h75xcfgLcoME4duxYSgTB6h+JaT57TJinFgmOpHHUo0cP8b8o+ZTbhYDl9OnTAJZNmzbJoWzQoEHYuXXr1v8WseWGhfr165ubm3+9NUNpWjczM8MV7dixQ1TJjKfkese6Gd2KhISEoUOH4ru9evXCdgZWffnZ0FpQ+qioKDEXVoLgwiVdYV6sTZo0ofJ26cYLMLVUtZA0/m3duvWjR4/ELy8/cckYCZs2bQrySaHQLOq5U6dOwChaR/ivEJuR1SdPnqAxy5YtE78ll7WcY6N3tWnThoqS+/n5yWGZhCJW5MQAx5w/f97ExATfWrBgAZ0q48oCNDvs378/Y9cRLlxyL7XesGHDpEmTyCSyZcuWd+/e0QHe3t5LlixxdnaeN28ehgBFFuzcuRNjZ+HChRi8ZAbBBkvRxsfFd4DhnTt3WLpmFmSHjRYtWmD/sWPH/hPEloe9DB48OE+ePN8RV84Qm2D2r7/+KlCggLq6upOTE60/pptPKTEx8cyZM2DIuPxKlSqxvIUZYzW7PxUrVrS2tv4S9+DCJVfDBQYjhdRduHABA2Tx4sV0ADT0ChUqAMxXrlxZu3bt8ePHY6exsfG0adMw7oYNG4ahFBcX5+bm1rFjR5Gbr78LD+kRdO/ePV++fCyRHeFSTExM48aN/yuOzci/l5cX2jB27Njvm5GVwq9wjeg5lJAQuDpy5Mjt27dfunTp9u3b6ISrVq3q1q2btrY2lYDZvHkzzRf/uurKZpaTJ0+y1VvOH7j8ZHCBDQcHB0o42b9//xUrVuBfKv+6Zs0a7KGDXVxc6tSpExYWVrNmTWJZoiJfJY0L6LnMlsJv7HdD4ogRI5j+TuDGEJuCU34YYsstz2RIz0wRRvnSIfMz2bhxY7NmzbS0tOS1yNXU1EqVKtW3b18wB1p4/cr4WXYncU4TExMewMXl58MKUZG/om3bthgar1+/tre3x54BAwZs2bIFG2vXroVCevPmTZAfcJ5+/fphJ/j2zp07r1y5sm7duvLly1PQRKdOncggyc3X321wGDNmDPDK3d2dYTUtxsXHx2MCxUeYPf/VJpCFHYPa8OjRI/y03H/v+35XnhxPbk9OSEhAF3rw4AF6lKurK5gA60Jfn51GadZbtGgRp9Zcfla4btWqlahIE1etWjUopEBmUBTsgSoKtRRUB2iMARsdHY3BBRUVx0N579Onz40bN2hYde7cmcN1Jgl2cHBwoUKFOnToIMrcbIjN4l8qHUvRfNmdsEW+DFq3bl19fX0qKZ55Y5cSaCtdhZyEf5PPOZvyyNf6zZs33DTH5Wc1hrRv397Hx6ddu3azZ8/eqhBzc/OAgIBt27Y5OjrKiUpUVJSNjQ0ZQ+TpL0D/uDEk82aHZcuWAW0oE5EcsQnWpk6dik/xsDBvitkWRCP3AF+4cCF+8ciRI2L2pEJl80JKmnxfLlN2fKVKlWxtbTlWc/kpgYLG4Pjx40eOHEnlrWmcDhs2bOLEiXv37qU1RJBq2g+gsLKyIjNmkkJERUgC6DcfI5mfN3Gfy5YtS2HpctRiBgSKVTE1NaWQE1WCmoVYffnyZVY6QV49PAcKKQKvX79Gg6EkcksIl58Yrnfv3l2/fn1KrUCp9jw9PQ8dOvTs2bPTp0/LcTgxMXHnzp0UWca+vnjxYpYlno+RTBJsCrXevn27EqFleTMePnxIFQaXLFkifr5+lxlEVYpXRQcoWrSotbU1BUPlZKxWirtkWVV5V+TyUwJFUFBQy5YtScX+ymp08sPw3adPn4rccJ1pgk03sGHDhvr6+qyAoPxxEC7hSTk6OgKa6tatS0uTRL+/G7SVZoSAgAAQ+BIlSvj4+Ig5PiEMuy39+vVDm3l+VC4/PcGeMGECpRUCfxbT7KWqS1p0vFxlXr16NWWQ49Q6889CHjUze/ZsOcGWl7Kiw44fP66np4cjR40aFRYWJsqSbHy9+Vd+Wnqgbm5umCxwZgpjyfnJu9gllCtXzsHBgVNrLrmCm2VmjebDhw81atSg3Mtfk+KJhjYUz8qVKzOfED5GMv8QCR779++vpqZG5FZ+Y5VM2VFRUeT+V7hwYcB7aGio+HnOjQwqubDewuoVYufevXvz5s1rZGREWJ0rIriZIzfu2Jw5c+QdmAuXnGPEUKp+S7yLZWD4eq2QIMLlyRMLc3Oqr6eUQFUujIb5+/uT45/IE6hm3WMl8MG9VVdX79u3r6iyzCfPZEsHv3r1qlevXgDtfPnyDRw48PHjx6rLlPIeIu8n7LA3b9507NgRJ2nevHlISEgueqbySjfUG7mixyVH6X1Ktsp0wfwroww+6cIKBL5x86aFhQUF0LHMFUpJ+ehHL168aGlpyUJ9OVZn4SxM9xNsGfhDJXtUtXu5jx9tA7SHDRsGmo1vmZiYTJ48+fbt2zExMeIXrNnMWg5479evH75VsGDBVatWiZ/7def8m0a369ixY7gEebFLLlxyCFCzf9++fXvw4MHff/+9a9eurVu3btu2rZOT07p166jakfgVScykd0X3Tgp4Jwa88/H3b92qFYjW1atX5WOWEbZHjx45Ojo2bNiQsvBxrM6mBw2kLVWqVP369cUvVKdVsmYzx/g9e/aAIefNm5f4ds2aNX/55ZcVK1YcP34cAP7ixQsoUOfOnUMnGTBgQOnSpcmWMm7cOHKnz7jD5Fi4XrlyJS6EJV3hHYnLf276YGw5PDx87dq11apVo0wL+fPnNzU1tba2trKyovQ4kKpVq2KEil8OgpNjdWpwcMzQUUBs+qUjR4506NChVatWIGyLFi3auHHj4sWLR48ejRmhZcuW27ZtI3sIz8yQrQQbao68lG0GmhQzQbNnERkZeeHCBczjDRo0YF1CSXR0dDAv79u3j5Hwbw29UbWViZlYSfk+oa44ffp0TU1NefECLlz+K6Bm/gDBwcEgQtBbMdyAz0uWLHFxcaFySIx+v3nzZsOGDRUrVsQxTZo0oZhcuY+ByEaWYiewOtymXtxcRUrhxCRG1V6/fn3o0KGlS5dCMXd2dgZtA2lXCrXjWJ1NBJvuap06dUCA2fPNIB9dBsHd2BkYGOjq6nrjxg3M4BcvXnz8+DH0Mvlh3+oHKP85ec7qL+3Mvnh56tjDhw8vXry4vG1cuPx4rGZuAAkJCQsXLgRQq6mp9enTh8x0ckrDMtsz2b17N/TcokWLUlWvfxiaDKtTXnmHV6sTVtY8NVThDJZmsla1Xn6TSZxLJh893f+bN29izp07d+5X2p1U16DTXXRWys6R+SibjBuTfb2FwfWQIUNKlCjB+QOX/9b6wZb2KJatc+fO5N9FQzJdFw45xfL397exscEXT548+RnHpjTCj13CK9cM0Sgct2CxAsBTlPBfXuODZc7nQP1jCDY9LHLqo8yH3+otKe8SzCFEKTvH9z1N6l3Xr1/v2rVrz549e/XqhZ45cuRI7Pz777+7dOkCRtG7d2+g6KVLl8Rs8/PkcM0lR5HqyMhIWri3srIC1xI/L3UnZmjPJLNebGxsw4YN1dXV79+/TwONsDrxyrUwE4tQbcNwc+sU/7eMWvNHkEO6ASsmjmdHubZyTu4O6pxLly6tUaPGrl271qxZs2rVKirF+Ntvv7Vv3x4E48iRI4sXL9bT0yPv0Oxw2GCdfPz48VAk+cI3lx/MqURZ5NqpU6fAGYDV8+bNoz1faQxUSgERHh5uZmZWunRpcqnFBwnHT4Xqlw01LBdaTD92olS66yPhP+/qOWnWlucFvXXrlphjQvaoYYsWLQI4i2muzixx96xZs8S0/DMtW7ZkRR6zoyUE17hFGhoaLNEr7z9cfpgBhCgxVfGoU6cOlXqR+2t9U21TOqGrqyvO1r1rV2zHbdoaUlg3zKg8vZJfenBqnZOn77i4OEy1GTj1/VdwvXz58qpVq65cufLPP/+cMWPGwYMHieja2dnt3r1727Ztc+bMMTExYeGZ2deSzZs3o3tT8VAO11x+AFaTaREbt2/fLlOmDJVbZWbM7zMzymPGV6xYgXOeOH1a9PIOqV43tKRxSGG9mOG/cWqd8wn2nj178Oz27dsn5gxfd2oDepSFhQWwevLkyaDZO3fuxM5JkyZZWloCvatVq2ZsbBwQEJCtEErK5rVr13B/qF4GzxnC5QeQatoGIUHHM0+LB/8+Vyi5XUVx5k+DpXrVqqUtLCIePY40tQyrXCPMzCrp/kOCa47VOZZg06OsXbs2OHYOyWhKcL1w4cJRo0YpGUNGjx49c+ZMgugmTZpQct3ss7rLk12z+mgcrrlkE1azVcW3b982atQIvW748OFk9/s+Ui331k5j18khIeEpyR8vXr1cSjPPyxJGUUYVkl68TPF9/TEhUZR593HJgZ1E7tQHKpsTCDaD665du4aFhb18+dLLy8vDQ7KqjRgxYtq0aXTY8+fPixQpQkvk2UR6WW/X09OjLCscrrlkB2sSZauKR48eLVy4sJaWFjbk+78jyZ58jD9/4dHHcaS5eaVy5QzKlS1lVqV2s8IGHkX0Uo4e/8hsIIov8IeSk7sKwWPv3r01NDQwrYv/dQpE6l1HjhypUqWKvb09WHTjxo3xnpSUtHLlyvXr14tpS42LFi0aNGiQmJ2+fNSY9u3bly1bVuS+fFyyzQAiKlJMjxw5EsQJHZ5GYmaqXcvzcDo7r8yfT3OQo3Dlb+G9lxDsI/x9QOjSTQ2/tX6jVOs8OTGRtYY/l5zcYag/eHt749kNGTJEzFxd8qztxqz+L9WDk3dd2lbameXNoHH0119/4eawdXmO2Fyy3ABCKaNZOvrMrCoqkY1ly1cXKiA8vqkuinnEj+ovHqldPK4WG4F/1Y7tF/LlVzt79jzv2Lmoz1CHoQK7Dx48+G+fnZLBTSnFK3OxZmCeraYbufna2dmZ20O4ZC2ppg62ceNGNTU1AwODa9euiVlUKZXO7Ov7Wke72PWLgiiqi/HCtAlSSh9NTaGsseDlIu1cu1wwNrZMSIgXeVhB7jGJiIqcezo6Ovb29uJ/5NSnlEybGUbevXuHqWTAgAGXL18WZa4gX1lOLku0D1tb20qVKin9KBcumSTVYWFhnTp1AoTinSo3ZVUiDjr/pEnzOrQFLOdJChPEWMG+ibB8kZASJ4H2zMnYL6TGa1iZC3v3nRC/JX6BXYW8YIdSoDqztcpD1/mkkIUEm7T+v//++wcTbLmvEbUE28uWLQsMDMS2nZ0dWkVRXVQaWM6xvzLVCQuQV/qWfIJQGiZyV1XKYXjlyhWuNnLJTCcXZauHFy5cKFmyJHg1xp2YpdntmB5qb99l1RLAskZyuPAxShCThPgIYfI4QUdbeHxTAN8Gkg/uL/z66xTxy8WSlPJhKg2c9NOxfs6jfkCSn/9Dgo1HbGFhYWVl9SPnQaVHSXANWAY8btq0Cdt58uT5/fffsdGiRQsNDQ0WsSJP0Jdusil2UarmlG+tOPnhwwddXd3mzZuLOSlgn0suJdXoTlRcr2rVqqwcXhYOOqYVNmjQatPaT3CdEiGIyYLrXckSYlxGcLsniHESXI8dIQwcNPFLcK3kYcKK7YoKe3ufPn0iIiLoyPXr13fp0mXQoEE9evRYsEDKwvry5UtsQy/u27fv4MGDyb+LlZ2Sexhy+dbnSx3p+PHjjGBnU3C3qjB/wqZNm27cuJGQmRL5YrtKlSqNGzcWFUlOAN14+qo6o2pYrtyoEhUVdfHixdOnT39KlfB5mTOW1JdqxLMOyRZhg4ODsQG2jyaRdZHXpOPyrWyEkep79+6Zm5ujL02aNImGWJZnImXDuWtXpwljJbhOCpPYNRA7WYJooWF9oZaNICZKcN3CXhg48Dfxy+sybGdMTAxVSGd1qfT09LZu3Uqfdu3adezYsU+ePLl+/Xr16tUxkG/fvo3Be/fuXVzylClT6tSpk7E+y+Vbp+PQ0FBAotwH+4dx+9q1a1N1AycnpwoVKlCiyMePH69ZswYbbm5uOAY0G9s0TT979qxt27Y9e/Y8d+6cmJ69nTmyWlpaduzYEVO/mZnZ/v37xc9dSugywZwpxR/zPKeNX3/99cSJE8SIypUrh+4nTybMew6Xr1FaGameMGECFdFjcbLZlLadfvHAwZMmRkJKrBqIdMw7wcxUmDdTEFMEy4pC7RoSbvv55NHMK1SpUl3MsJafqMi6Bi7dunVrqk0TGBiIbQw9DBz6LRDpPXv20Lfmz58/evToO3fuYITSnvfv31euXDkyMhIbGzZswEnAjjAYQaV4V/luGgAcK168OG61mGa2zW4h2AwLC0M3Xrt27erVqwm0V65cWbp0aaBlfHw8/qUmvXnzBttEsMeNG4dtQ0NDvE+fPl3JTMGqA+MkRIlFRbpgU1NTytcUHR194cIFLy8v+gjEHv+KiqxlOAy98d27dzihp6cnFYIXFRlcKSsauzkcsbn8q/WDuuL58+eJgYwZM4aKE2Vfev/PCpHUs+vfD8icVxTVpo0XFCX5hGJawoO7aqKobtdITVvbqFCh/ESBPjFeZp9M/ZiqmE2ge1asWBEj4unTp2SiXL9+PWgVKcJUeBpwbWdnh9ExceJEzEcPHjwAu8bomzVr1pw5cxo0aEDH29raXr582cXFBTOXg4MDH0SZYdcAq7x585Lz54+Ea3TgAgUKQD3E9tmzZ7t16+br6wtYpkouIMYGBgbUHuA2uhzgHQBbt25dhtunT5+WmyloxocKRhliocRRryBTG1AaqtmgQYNwhiVLlmBPo0aNoMTh8mvWrNmvX79OnTqhf6JVffv2JUJOaiCmD2YS4YjNJQPrBwPqt2/fogNTqmpW0jp7a2YpTkpI63ftmoGg0aKV4P9c8twLeJXnxrk8ccHqHk/UzM0E++Ydnz59grZRjuJPHh0AbWyktZCuYuHChdBScSGUw6Rly5YAXkAxdoJ1Y0/37t3btWu3YsUKHPnw4UMayFBIQcvnzp1LgwjKMm4CDZx69epla0bNn7uPUf+B/oJnR/pOZm6jfAGRlTBIt34B+2n0hKJFixL1lftjgCEfPXoUG8+ePSOkxTZIeMOGDdu0aUMHo1eg88hNItR4dCRKMwLgnTFjxi+//AIAB2L36tWLKulgUihfvnxQUBB0OvSliQohA6O+vj60165du+7evZvdDZynWrVqmERoxfOzyndcuOnjc0aN3gJAy5MnT758+cAKWKrqbF/KTyvFmJKcnNi1t39Jo67Nu2jrFbatLYwYIoz8RahfWyheXHvCxNloLEaktrb2wIEDpbZ9+PAxRRaMFhyS7PWKTBlUOGzr1q3gyRgptWrVAtMGSb558yYQOzY2FmONYT6NixMnTtAIZdMTvmhubk7bGL/u7u4iT3T5vWYQUVGaUF1dnZbkvuM2ynE4XZ+NdD+lx/fo0SNm9KB8UwEBAdizatWqwMBAbOzatYtOYmFhAWxv3bp17dq1aY+zszMOkFfGYVmhhg0bRqYPTPpQykqVKnX48GHQAAoIEiVnJ/tbt25BL7tx4wbAmSzh4NLg2yDb4AwE16zLAeFLlixpamrq7+8vytbTOWL/n9NpVoSa+s/69et1dXXRLXv37v3u3bsfQarl7SF2sXBpoKAR5yyRWG8vn9Vrdo4a/cdvY+dt2XIoMDCIjXpwFYwpkZJdYwSFhCaeORc9eFhkm45JiiTY4WFhNjY2GD4TJkyYrpAxY8aIaekgoAuDVEPxJI9EkBw6LeCanKlwGLszrVq1OnnyJMbyiBEj5s2bR7MAl296uARuL168QO8ifPsOHxvVJJD0L/oqFKjbCsGMjLlA/ikdTN148uTJaMCZM2dYkzBx29nZiQp3PhBj+hambGhSkyZNKly4MFUHBvFWSgNLJwQCGxsbUwYG2oNe9/fff/fo0YOYAFgBtDMPDw+cE/PF0KFDyQfJ09MTgAx2BLimBRT5aXE5+OkyZcqQF1a2xsJzyckQzUoiMj8H9Kh169aBFaBDNm3aFHxS/JGFaD9htdRLk67eCMlfLKpLL2mUfcF1ikx8s2bOzJNPM8LbJ3n3vqi+g8Ir1wjJqxVmXjXZQ0q8QFYRDFvwlmPHjmEIoNuTuxQLZMMI8vHxoZ1sMgLbefnypZItHbotlGUqiXL+/HmKreDy9UyY1a2wtrbW09Oje/5NeZPki+AEXJhPjx8/DqwDERVUxMjIaNCgQZcuXaKfZgECwD0Q5hIlSoSGhtIJR44cWahQIRyG2Z+tMnfq1Kl69eqnTp3CqYD/pHVqaWmxFVI2jkTFInXZsmVHjRo1ceJEYHXjxo1xMGYEKGUYVh07duzVq5coeag2uH79Ojpe1apVx44dC/qtr68Pkt+5c2di9Wy4UZvd3NxKly6dP39+8huRMysO2j83PjMirWTW8Pb2Rh8rWrQouiW6Ey1wMH/RH2E0o0Yqfis1MCjcolqYmVXq2wDsTVF02sePXSf9vsChff+27RyHj5h+8eLNpCQJrk8ePYY2X9+1J7GseVDRkiGF9SKbtEwl7P3cgi23N35T8ItqTA33sPoOOxupLdHR0ZRil5zZvsmvWCmxGIAamhEFIRYrVgx4uHjx4iNHjty8eRN4eODAgT///LNly5ZgpzgA1Bcsl5g8TfTEk6nyl6hIzYd/MXFDozQxMWFwXalSJXBmfMR8hyiDn5ief8jz58+XLl0K3AZKs2no4cOHUO5AyKnZ4OEgA/7+/u7u7ufOncOntra2MTEx2PDz8xM/j8+irwDbcQzpI8xnmxEt3g9/jmGiVApcDrz0fNFnMO/XqVMHPUFDQwMUBWqa+Lmv9Y+ZxFlzpRHtODAkj1bimXM0DCKjIrp1G6SjrdGhjfDHVGHZfGFgH6F0KaFylfo+mGb8/XTy5L3doFmcUfngYvoRjZunvg+UYzUb4DS4lFymU9NEFcBVbxe7LTxM5puAmvU9IGSFChXQ2SjF7jelvFbCaoCemZkZTtWkSROAHpm20g02BL4dPHgQdBcH16xZkxYdyLIxfPhw7CQ1ClCJ7a1bt+7cuRMb5HfXoUMHcGNQX3V1dcwFdGYME4B/un1DNaCGER62h9q/cuXKevXqQVPr0aMHLb6o9iil80yfPp1i5GneUbLMc9DOdchM4Awao1pnnN7Rq9E5Dx06BJUNSh8pjNhgaROU7Ng/NDpY0Y3j16wPFvLGzv6Tfj46KqKiec1mDYXQN+qiqJGapJESpSGKeZKj1aeMEQrqGFyZPivWyCy6Ss3oiVMj7dumKiztH3ksWA7Q5uQdCYg3c+ZM8l4mF6PMYPXy5cspBODixYuizOuD9Xz6afwrJ8AAbV1d3Tx58uzdu5dOC9aaN29eqggAKV++PCg6rTauXr0aexwdHdFg8sGmOi+iwmcvf/78BPhKQ4yFqzNuICrcqzAL0FXLARxzFrj95s2bSe+Qa7JKF85sOC4uLvXr10djTE1NN27cSJ7/8hQ3nG/nKEyWwzJ1SFVklj9ldMjbt2+vXbt2yJAhNWrUKFiwIEE0Npo2bQqU9vDwkNtJvrX07bcOYTnbl0fmEsAm3bkXolUisnWHj4qBhj2du/Rv1UwQRc2kWEFMFQb1FUxNhIQQITVGCnhc6CyYC/kXaOYfPUDhHBIc8jHNosK763/VRRlK0yOAmo9upqOjg143ePBgcp/7Vj4gd8OjeMPevXuTU4f851TZKYPQlLRVDHt7e3wdgE/HzJo1i3nujRw5skCBAomJiSAwzZo1E9PqS8pdoCGrVq3Cv7QEr+TTIjetk8nF09OT4muYw4nqkn3GQbKq66pnzpwhZaFQoUKYa65cuaI0d7CpSo7e2RcikbWSW3BYFZCVMDldLJWPi1evXp0/f37FihVOTk62trbk3UFSvHhx7BkzZgz6DPRBVi8vW+1gShpxukmTpGtMSpKcOiIiwqvXDTUsl/LKm8bAExc3g5J53r2RMvKJKcKpw9KFmJkKiaGCGC0khQPA1Zrba2Jnwwb1RIW3Nsfq/6QDM1Yp78aurq5Q4rS0tPCA7OzsyM72HS5GcivuokWLKAeC+NWLbkpwh6YC4nASqqIL1AXfxjwipsUSPn36dOLEiUBCqKI4uGHDhtgJeAT8UstBa7GHnOtU4Vr8vHoOfgtUHKCNO4DxyHBVrg58zSXIKzcxk/igQYNovQnv3bp1w9CGIqCqUyuxOwYmLGPJl4QOYAfLc1RSHQf2b4qKqJ5KVeSqkNKZ5SdP91fkGVfSla+cHTK4dqW2Kd29f51kmS0OXQUP69ChQ87OzkBmMIEyZcpoamrKwbl27dp4mitXrsTk6+fnpzRGGAvKJjotpldvEX31yZMnR44c2bBhw44dO6DJUo1pUhojnYaHqBVMOKpIiPpBMkXOn7+2TUuJRYsxwntfoYKZ9CpnIsQHC9gjJVYVhc1rpcoyFcqb/qNcc6z+UVoe9WElIz/gburUqdDWFfnJNXv16kUuRkor19/Ui6j3nj59Wl6J5ptOJfcnwXbLli1xKgqJAnnOly8fhlVcXJy6uvq0adPOnTuHT58/fy4q/Pa3bNni4+MjpvmOovd+Ca7ZHkxVwM8uXbpoa2v37NmTNZ58rVXDgpTq2ijtEVX8zNlh4F1gaP3799fT06OxDzKP312yZMmlS5eA3kTyOYHJJqMfukR4eDgAFgoaAA0zJjAZrBiPAAiMZ4GuJXdVQn+oVq1a9+7d0c2Agffv36cUBKqGNSWz9g/woGY2Ny8vL1wCppWOHTuCcc2ePRsqbb9+/Vq0aNHBwWHfyZOpW3fEqhWMHPc7GUZoXPzy6+QxwxRw/VFwaCMMdxJWL5cSqH5MkuA6Gez6o/D3QQmudXW1g4KCRB63kp26HiMYqouwUVFRAAc8YmNjYzwO8NXGjRtv3ryZkmBkZuWa4VVERIS+vr61tTVIrxzEvrVPUjPQsBIlSmDgYPvBgwdoM8Wutm/f3sTE5MKFC9jDyukqEea1a9fiU2Ia8v7GWgVsJ+NP3rx5WeqPyMhIjFzy6M6gUsyXMv1msDTArsvNzW316tVdu3Y1MjJi+ADtxtLSsk2bNsOHD//zzz83bdp0/Pjx69evY1bFqPT19Q0MDHyvItj59u1bKAVQ2DH13L59G185duzY4cOHoVysW7du7ty5s2bNGjlyJE7bo0ePzp07t2vXrn79+lDhGzRoAKQyU0j58uXLlStXtWpV7KRPSbDdtm1bYBq+CEwYMGAATjV06NDRo0fPUQjOj19Zv349Jkf86DGF3Lhx486dO2gMZlI0DM3DfMTaj04YK5MMegi7aehLMTExdHxISAhduLe3N+6Mi4sLfgg94ejRo8DVNWvW4O5NmDABilinTp3QvStXrly6dOkiRYrQU2aipqaGe45rb9SoUZ8+ffDEcQk4D9ocHBys1Kp0Vz1+8AKEPG0dfn3y5Ml4fMuWLcPdUBrmmPqvXLrU3dHRVl3jZp0GVI1GTBsXU6cs7NReguvdm6T7sHOD0LengMnq9GHJPELseudWwHWeAgU0KY6AYQKXjKFYSelTUm//1fIGUufh4YFxNG7cOBsbG+qx0PrBWnfu3EnlKpgRIzMaHANJMlmzkmHffTZGbinenErogpqC8GADqiiGm4WFBfQCQBnGMnPIx7eIqUJ3KFCggNxczIQ1tVChQuC3NH4XLVpEnwK1mjZtKn7ZCQTogTEiHyDyBsgd1JW0eHyLkvmw7+Jbly9fXrBgwW+//da6dWsrK6uiRYvi0oQsEszIeOjFihUDXYQmZW5uXqlSpYYNGwKWgcZNmjTpnCbA5ObNmxOMM8GRgLuKFSvii7jbpUqVwqkwx6GRdGa8f2uTMBsWlImurm6JDKVkyZIAWzxKOh6KVcbn19DQwGH4IpoNQENXd3R0BEWZP38+9K+///4bnRM4j86f7jK6EjIz5vzfrg7L3VDBiMCoMf+yvk3+t/JVezry4u1blWrW2KNYspeuQnG9V24/Km0ECq22bKGgpyOYlBWKFpHuW7PGUnmChBDAtVqPLkLtOs01NdUpeoXD9ZdE7rEgfoWrOYNlDHx0QpCr3bt3o2eCXYBagEUTRGO0YmyCDuGA6Oho9l1WozYzXZF1D3Ae/BzUMfEbXUoyXrXEhYCxi4ocX2BKdE7yYME74S0gDp+CxbGfxreqVKkiplfegg4ArcIxZP1glnZp3bxzZ1DNdO32DK5B+KEgi2lRYFBFQWLZvwy0lZKygp1S4ilyaKSrAzns1q2bfCkTDB9zENR2cNSzZ89iwoLyDt64TkWgQYBF44AjR46cOXOGAkXxRVBEf39/6O941mCkWZiOm+kIZJXC+QMUgp/Dj7q7u0N3QBswzKH1QEFAw8C3gZPUfjQYnXDGjBkzFYINcHUnJ6dffvnFKT3B/iFDhowfPx63F8dPnz7d2dn5r7/+wtmgZ+HC6aqBwPhpqEt0yV+Ta0tJ/ZGvPOZAvx25ooE5dNWqVWxVSDXlDrsoyUj47l3NGjX2UnivYvFRdH1aPa/OhIkSwY6XwFmYNUUoXlxIDFNYQkSNE4eEMkbG58+fZ3nSeM6lrzS4UT5Y4DA65MWLF9H50fOXLl2KfjtixIiePXva29uDNgNeQHtUWVnx4sVbtGgBNR+3HQiA6fiL68iZYNcMjhYvXowfhX4qZkVJLAbXGJLk8oGZCBuEyQSMUBzITo6xDKYN5gaSjMZQvhEgg6pNg6EoeCa4+qVLl4iFdu3alQ4AEwN7JOqiqhTTlQJkANF0AFALhNzV1VVURFPi8lnVAwhAjCVlhWpJdic8WYAq2dXRgHr16tHxeNbYn8mZLgNoYk5fctOZfIlQaWUwXa+VnO8WonSx8vXHdDE5Vzi60FiApjBt2jTq/1+yI7EromkL3aySldUzd3cxJTVy+pzYwrqPG9trlTCaPk4QUzSAz88eqx/eqS6mStt/H1TTUBf27TsYFhbKvKQ4XH9Jxo0b17t3bzBhIECZMmW0tLT+VfuTq5nQGaHgFy5cuJBCSItU0o7BVOvUqQPqAooCikjxd6reR9+0Pkg9p3r16lTwJUtK8codlqAR9+/fn3KYsMyoYBqGhoYgG3Q8QBI0ldxf8W5paUnJUVXdQqj71a9fv1WrVjt37sQtqlmzJrUcsmDBAijUZClSDYugs+G+YZYkSN+3bx80blERdIzZE1MAeDvV3/n999+7dOmCnWD+oiIfINgyToLf7dChA1R1fBcTMeV93bZtm62tLWYNfMTKqn6TfMnlIzsc+TJw0kjXRyVdr5LvkAyuOoPrze3kjbAabA3sS5QlpVE1uCnFFRKrOXDwYLs2bZJaOAQX0o1dLoUqPHNzMzOztqggLJytduuC8PS2sHGlWtMGQpEiunv2HBQVvliUTo3DdQYCqAHMAqWBtEZGRhYWFjVq1AB6t2vXDlwauuHEiRPBllevXr19+3ZwS1BuaJ2PHz8GqXv16pWXirx8+fLhw4dQTgEgmzZtglLZr18/IJW2tjYDefwLjII6ma4r2r/2dmYJwdlY3ZmsGiPMjKCnpwfyiZ9gcYvAOhYmjztAbiG45NmzZ69YsQLaBAuiVGKGdM6OHTsCcnEkbjX5chP1Xb9+PQVR4lZ/8on6fGGRrtfOzg5qvqgockQZ2tu3b08mESgCAH+01sTEhKrekO29devWV69eXbhwISUEvnfvHrSkGzduNG3aFCp8hQoVKJZz+PDhlFYrC28jl1wN19Tl0MGuX78ufp5XQTWKR7naqYJjO3TseNKxvxjwPjXNCpeYmLBx457mLbpVrmJjaVm1QYPWs2YvI1cQUZGGIn/+/JTonsN1BtDHmEk2ZXVj8OXn53fq1KkJEyZUqlSJoNvMzGzu3LksJ8ZXgjY9TTJ2Uf7DrIr9Z0yYQs49PDwwhVERClERZl6iRAlRkSmd2g9Id3Z2Bul9/fo10I+S6TEfFWbw+bREPnUqSPuYMWNA0Q8ePMicTDAPqqmp9erVi9WpUTIP0tehm6Al0E2gqlDcYr169cCrHRwcMKxq1aoVHBwMGEeDsU0OLSDhmF4HDRpEAZtEzrEHZBuKg66uLpC/bdu2OAld4zel1eKSVcPjG14/ChNEhWcUW+MAr4iJiaFP0aUxYJ8/fw5iQOY1UVGMCXwDsz/eaXUb3Gbw0KHSaE1IFNNz1lXq3vHx8SCNkydPFn9UXZKfw4KtZIJT1Qf/NZhCNY5A1ccPNBLKeIMGDQj3QObB/cSvSyDG4OtLUYSZVwPRGJz8woULgETKcC4qcp9SVCNAG0riuXPnyE+b3APw3rp1K1ElGpFpiMBMTU3NDh06AFExEVB9MTEtRpI8T7ABFUb8PIs1XR3uGJAZ9APzHbUHSgrUVVGxdg/i/fbtW+g1OPj27dv4CVwC5pfLly+DPC9dupT0EeD52bNnAdGenp74OQLwp0+f4jAO1//NcEurnPIxWfWV/O2vFOlUGb/wi6ov2dik8QXuMX/+fKIfoCIUMiYq6tnp6+t36dIFBKN69erUG0EYqlWrBj0aIwLdEpwZfbJVy5bxaY5JoiyuVoEhySDb6H5yhQ5khqIn0i2JzkX8ipDhLPwJ1QgaWpiAhk4OyU2aNCH/B8L8L9Fs6k7Tpk2D9kRTeRb61dOpwJYp2x6YZ+vWrekj6AKOjo5kZNuyZQu1Db33r7/+On/+Qq9ePdCN581fU9+2TZWqdWxqNOjcZciJkxcUaW+kBj979gxwXbZs2TJlykRGRmpra//666/YT9E36urqjx8/rlu3brly5VhaV/Fz1+4RI0ZgXqCqdpDNmzdjBoHC0qdPHyAwbiyGz9q1a6HANmzYEEMGg+j48eMuLi4YbuDbGF9g2rjDVFWhU6dOIPNnzpypXLkyGU9+VmOIfOJTSt2WE0bcJ46dY+4VdTYgJ63agGaAJwCHaQkb3bhGjRp0MLQ8TPogEiAhRDPItkYJLfEtiimTOywpuZTIex2GD/onZ9c5cHaQ2wpIFVq1ahWF4AF8yKn4S/YZBtesOkAWjjv6RcLkXTt3NrK1bdOqFX1Uq1YtMG1KqUr9kPpVsiIZu5PTEOxvZafx1zLh7iXh1EFh/CjB0ECoW69FQMBbss4BqHEM3nHhYCNU6oKib9BXcV0U8A4ExsGsvCMj2NA0aemc7cGR48ePx7SClkBdhQZatWpVTCvOzs6Aa5yZtI+bN2+OHTsW+gh5g5w8eVJUeJXgno8bN47KMfyU1Fq1cKFqrpV/v+rPEUZ1EfTTS85gMyDAjN8q9LjIQ0ff9Orn/+uIdxOmvJs07d2kqdL7xKnvp8wMWrjk02vR0qAFi4OXrgzbvC1s01bptXlr6MYt4bv3Rh47GXn0uOJ1IvLI8eiz52Ou3oi5ej3m2o2Y6zfxHv/oSbyrW/xT1/gnT7Ed9+DRB/fnH56/iHd9Ju154oKPEn18k94GJIeFf0xK/pg2BHr27EnhvZ07d75x48Yff/xB5eqgi4EVYMCiD7u7u1esWBGgDWJABjd8t2vXrrSkAm5DGXWY0i1K4cBBmzYf/G3sH6NGz1q1euerV6/FNOM2xkXv3r35GkoOJzxsKAF70SXAM7W0tCiPdLrx6QyuCxQoECfTtrKcXS9avryYnt4khT0N0rdPH2MjoyaNGpmmJb5mWbIXOa8soiXcOi/lh0xM1Dh7RD3ovbSdHK3h2F0oY2wVHBxIxmScFqoErqtp06bEUgiuwVIo4kZXVxeaJmgzqzvwUQUu6F+Wsu/o0aMYI/b29iAnc+bM+fPPP0eOHAmlAOeB5gL+z65LTizl7P2nLEYjd1oQPzkuhj1x8XwbEMTuRgqB59fDbBbRclKZsAEcfpqnsLu+sZuuoZuO4Wfv6bxKffpUt7SbXmm3EkZueoqXtFHaTbuUtB/b2qWeFS35rLCua8Hi2HArboCXu4HJC1OLl5bWXrZNfdt39RvgFDB+Mn49bOv26PMXgeQJ3j6pMm9SwDXoQUhICJQvHx+fQ4cO1axZk4whRYoUgfrWrFkz9FJoc6JiUdvY2BjdG+phjx49yEUKutuVK1fYgE1M/DBy5BQdnSJ1awpO/YThg4VmjQQ9vfxduw0OCZHoGYYAK63I4TrHkm3x8/TXvr6+6AlAMIAPMUylsAt6+qtXr8YxFBKb5bbrO7dv4+QzatTslb/grY0bRcU6y98Kl2nIEoXNWdIOEiXAdHd7XqxowTuXpRAAMVXKvg65eFIQk4TESClvZKe2Qtt2UsmYiRMnUhA6mg1qjd4uKtb+sBNkm66iY8eO9CsYJvLUT+wuyTXW/fv3A/MHDx4M/qzklwLx8PCYN28eRhAYOOY1lqhHKS129iUIyhYb3T9sNg1mv2zmTVVYQZOTk5Yu21i5Sr1KlsVrVM9rUlarYsXq06cvouWzVLr2b6IZYBEJialgmNExIKVJ/m8TX78BawVljb19N/bGLbDcqFOnw3fvC9++K2TV2uBlqwJnzX0/ffbbkWP9h4564zjwdc++Pm07+rRu71Gtzotyli/KV/rsVaHyi4qVX1as8tK8Knu9qFhF+qic5XMT8+dlyruXMnUvWYZegGh3g7ISGltYe1jXftW4+evOPf0G/QquHrx4Wdi2nVGnz8bdvZ/w0jM5OATNziCVNOseffv2dXNz2759u5WVFaUCKFu2LLqZn58fNDiK8UenooMB11u2bMG/0IvZGbp36/ZYEW6MJ5WYGF+njp11JeHlQzXxo3rqxzwfP2qIqRpvX6q1shNKG1nGxEThtATX38quVVM0qJabUfXX4imFM0+E2JOiJHu0bCF+HmBOSEUmX9K2st4zZNcunPyRrn58aZMoiyqhVWtEOnSKHzthtqnZb7Vqf/Dy+piQAG0wSXHwwEFjHXsDlvPEBwmt7AUKHrp0SkJvKUtkguDrJehoA6JDjh07SlCMxoOfNG7cmME1+ir9NHo+uTviXV4DXVRxxh4+fDjOQGUUWG4HtsIrD0EFXNepU4cq/6ZkU9b3jC0GX4TZLxNa2RJYZhSloKD31tUaWVQQdm9S279dMlK98xROH1KraS0Ym1Zxu35d9PSKffQEaBZz7QZ4ZuSxkxF794dt2R6y+q/gxcsDZ897P2XG21Fj/X8dIcFs9z4+bTt5t2gHjupZq8FLy2oA1U/4WRIMufSzInquBbWf5tVKexWWXnk+vbvmK/KskM6zYiVBhgGwz40r4Lsvylt9QmmCYuwsXQ6fSjz5H1JdCgz8edmKwG1Pm3redq1fd+vt7zT8/dSZIStWR+w7EH3+UtzDx4k+vikREakKkvOlW/cPWKkuQco88aCXrVmzBr3xxo0b9MXly5eDS/j7+6OvKmmX4B6g36IstWZcbGybDh1CFTQb0qPn4Eb1QGY0RVHN5ZagpysoqjkJY8dgmOTt20Owb965atVKVF/vK+FaHiiarls4Y4ByLwi2MEQfcSafSabNbunZs2dBRCtUqCAvTcvAiszL2eR3PVRRUOagtU1Cjz6hNeuGmVYMLFgsTKNAirZ+UsnS0SYVouo2eNWiddjUGeLpvy1NrY4fllIfBPsIU8cLR/co2PUJCa6TI4QURaRt3VrC3r2nnj59THA9ZMgQAwMDkBYG1xRpCMZC+Y3BmcuUKUOeVEoLNHT5ID+0jC4vipRuWQS6bwcOHMCdlBtGVLO+ZISxn1kMvgyz0gGfw2wmnss/V40zJyWnxsWnxsYlBQYlvXuf4Pkq4aUHACru/sOYK9eiL1yKPHw0Yv/B0I1bQtduCFq4OHDugvcTp7wbP9GqjFXPboKYmKdbJ418+dQwDdapIcRGSqaqyRMEHUHznrHZSx1DVy091wLFZTCrJWEsvTQKueYv5lpIR7Iq6JZ2L2UCcJYocYXK4MZedRq+atLCp6WDb8fu4Mx+A38Bfw4Y//v76XOC5i0KWb4a7QnfuRtti/r7LKaD2Ju34+7d//DM7YObe0pUVMjqda6aRSSDho6hu6EpTguGjHP6tGr/ple/tyN+C5wzP3TdhsjDx3CZ8S6uYPIpMTG4G2K6iUbZHSOHE+B2YmKq4iVtQ9fAKwNzuizdGUW/Tpo0iXw5aMT179//8ePHw4YNY76mdDD4AHlos/529f69zgaGH+fMF8+ee3T0lL5+Pn8fQYyT1M9Na4V8msKWtcJKZ+HvQ3g0QnykUK2qFF7Xq1cPmi8+MhRVcfxTmom+VLFRdb/SRmxsLICFY3WW2LTJMOvi4qKtrV2+fHl5pjt2w6tVq1a9enUxq6Ma8dOWlpZyu0eCh6f4xCVk3fp3Y8ZGOfb3tqrqq13yQ0mj6Hxa7wRNE0Ht9l3J9EHpxR7f+4ddA64pMYJDW2HVqp2PH93TEIQqlStTqqKDB6V4rksK2zV5Pv/111/0u+j/GBqq1cRo4OBTR0dH+ehI9/LZzSQKtH///lq1asltJmlgyPjVxyyGWZwzKSn1wwfJaACYDQgAzH548TLu0eO4ew8kmAWbPXQ0Yt/B0A2bQ9euD5rvDJh9N2FywJgJfoN/9es32LdTD1+HLq+atHzVyB7Y+LKSjWQoMLVwB//UN3bTNpDYbP5iTzW1nmoWkcPsY41Cb/IX+VUoVKsB7r/6BakMsnDzvODtKm2sXqywXIkanXsIHYuUieo34PWgX/1/GfFu4hTwVWldb8kKNCls207MAlEn/465dCX2+s24h4/inz5L8PRKfP0mOSg4JTISyJka/+FjWjHlb1JbKAn/B1e3wFlzQeajjp+KvXHrw/MXmIwUgJyUQd5FurEfE5MUIKxsWhczPRBEhf+enZ0dxYKx8SVfCPjSF6mLDps4YV29hil1GqUYmkwQtDtI6qfwIUh6HzZEKFxImDtdOLFfEJM/jZp5c6RcQ337pMH1JxfHFNX8FUobcXFx7dq1O3/+PLXhwYMH9vb24DmdOnXq3LkzVRjB4GrTpk337t1btWpF5Z+gk4LpbdiwYdq0aTxfa+Z7C/O7cHV1zZ8/P3CG+ewxk4WzszMeMWXPyMKcIWD1hKUjFRybZooVmzYVLlXqgCKusGG9elZ6ei10dC8PGyHOm29VWP/AoTTTR6Lw8LoCrk+msesICRaqWwvHTlw5elKq+Hz07Nk8+fPr6uiQnef6zZvYSf1t4IABBNf379+fMWNG4cKF5TMUoz116tRhVRXEryhhwBB7ypQp8gDGL2WHk0YKKFlCAjTr5ODgRD+/hFfeH9yexz92ib1zN+bajagz5yKPHAvfvTds49aQVWuDFi4JnP0nsO7tqHH+Q4a+cRzo27mnr0PnV01bejVo5mFdy6MyYLaSBLOGEsw+K67/DGw2X1EQSyWYBZXFNoguDpDYbAmjT2xWYZj1tKnnVbeRd7NWYLOvu/R83b2PH2D21xHvJk2TXCkWLQ1esjxs89awrTuijp2IPn6ion7ZE0clxSf2vRD46p/J9MgeieaJCWpP7ghGRqVCwyO+cwVETvlopRLTExHaBHolKL8+sdzkT1Nk5lcNmP82LgDn/5CQHBomPTXf13hqmF+kp3bzVszV65h38NQwB4Vt2hq8fBWe2vsZc95NmPJ2xBhMVZgWo06dIcs8ja8lS5YQi2A5rOSZxJRWVeTMHCyrbt26lK9PTEnsZtd96iRpFEgDJFlo3lQoVlRo30ZhDBkplZjB69h+icD07iuF3yY8epJ0++4/N5YsY2l3KTQ0lJLkUCOhNpYrV448AImTNGzY0M/Pz9fXd/78+bVr10YbQOqOHz+Onffu3TMxMUHzAB20SApsx0ccdbOK6OL98uXLeJSUeU+esBHamYaGBkUCZmFGviZNmpQsWRIbFMwC3D529JPNeY2CbBcqVKhD164FtQpv2bFDYUOe0lZRLyM+SOqNj2/8A9cJwRLrdndT080reNu3vtWw8ejiOqm3bg9u2Wow1YJMSfFevWZkp05kBu/v5CQtcU6diu0J48fjh9hIYfcEPIGKUbIUSfL2M9s1s9rJ9wC0cXWUFCuVvpiaGrx0pb/TcMk226vf6669fVp38LZr7VWvsUe12hKbrVj5uYm5xGZLlJFgtrCOBLOEtHKMVS8I4JVgtkgJBcyWYbZZnMSjel2v+k2B3ji5b6fu+CG/AU5vh4+R2Oz0ORKbXbYqdOPm8O27gCdRp07HXL4KqqlwQnuW4O2T+MYPEJQSHp4aG0srZRnXh/rk3hMQZGxSJNhbEOPVUiKlNPh+nkIpfcGmmvAxWqo89TFKypBf0Uy4dkVRJzT+gwxpZQD7QQazMh6bKaRlX6eZkVYtg4KT3r/H9UIHiXdxjX/8BDdBgtnjpySY3boDkyPmo2DnpVAB3k2a+nbYKH+nYa979H3dpZd3i3aYxTxr2XpY135pWQ06CG6+u6GpZE4vpu9aUJue2lOlp6ZRSNpfoLibTikXIX/o+s2iIk6AgbCtrS2hWaLMHp4u4ZcbhBva2h5QaI4JirXyIU6ThjlJAyQ5TFGSIEKICZZGx8ihQhEtyqEqrFov1BI0PavXjF+1LnroqJAiJaMdByVevPwxOUVOpfbs2dOrV6/27duPGzeOGtC6detz58517Njxzp07dACZEEVFUh1ra+vw8PBGjRp5enrSTlDxI0eOLF26VBEucR6Um2KEuWQJzSa8WrFihXzpjRFs8rVgFcTETOe7PnHiBCuYiy6qr68/cOBAcPsqVaqA5K9cuTIiIgIHTJ0ypVCBAnsUlcJ8fXxx2ImDipIZicKDqxJcXzguQXdKPN416jUR+mqVEsuYJOgZisblY4uXDDEoE1ytZkzfATHTZoQbm0VXrBTVvVfipi1vrlwJCgykPu/Yt6+hgQEtrLPueuHChQ4dOoiyNA5fb7WjC0QvHT16tELlTCYq5VG15lO1AoBiN20DydMAMKtgsx5Vakq2Wdtmkm22bSffjt3e9Bng139IwOjxAeN/B52WbLOr1oWu3xS+Z3/koSOg3NEXL8fevkvOvQleryRv3pBQUHRgUeoHhdEgkwudkrVW+vuHzSoMAkowm6IoYvjymYepSf7wAAmZ8VxeuQv6JQQbayFCMYemRijg+oNgZSlcuHxX/JY0y8w/BA1QOIeEJb17l/j6TYKH5wdXt7iHj2Jv3cGtAJuNOHA4bNsu3CLMiUHznSWYhQ4CmB08FDALHQQwi1nMs2Z9ydRjaS3BbBkFzOoYPitW0rVAMclsLp8caWYkmC2oLfnpaZeSnhp0EOMKL8pZelStBR3kVSN7nBaEWZoc+w7yG/hLwNhJ7yZMDpy7AM0IXbchdMPmiAOHIg8djT5/EU2Nu/cg7t795LS6IYwRubm5WVhYPHnyhEaiUgkb1WJGUr8d+utYWRk+aeF+x+FKllI6vtRIqTjjpDHCkb0SRP8ySNAurtBJRbVO3YVqQr6nllUibeqFGpYLNTAJKagTUkA7ok6j+BVrUvz86eSNGzem0IOtW7dS8yjlGog0qY2HDx82NDQcO3bsmDFjqlatChUVOytXrtylS5fx48d37tyZ3LFmzpyJgQA92s7OjrLlc8kqmk3jqEWLFkWKFKEIGjaPh4WF6enp4RFQ4Grmq8kAeKtVq8ZMK1TbVFNTc8uWLfh1wLiPjw/QeNOmTUDvzZs300natm2LnRtXqIsp6qkpeeIDNZITpPyQ71+p17YRqlVvKCYnjmjZ8hfTclvr1LtsbRPfok2ocfnggkVD8hYMMzUPKVUuqJh+kJZudAWrOIeOkTNni09cmtaqVbtBAyX7D5CWIhBpFnv+/DkNJbr2mzdvQjekzMyUZO/FixfQDrBz3759VKrD398fXVTuIhh783b02fNxd+/H3X/44aVHgqdX0vtAhW02KiUqGuiXrh01Cx8wkczUuLjkkJBUUFwF5H5Ml81+XeqMTy4xCQkmZma3r0rFW2NDhCqVBC0tyXz99LbkHCJVeo0T/LyF0gYFPc5d/uj1KgZ34M696HMXov4+E7F3f/jOPSFr/gpZsTrwj/nvp88G3L0dMQZKAVQD3w7dfFo6ABI9a6ax2fKVJDZbykSC2SIlvgizknNI0WeFdZ8VLSG5fEAHMTSVJscKlTE54myvGth527fxadf5dZeemBz9hwwL+G3Cu0nT0IagRUtD164P27Q1Yv8hkO3oc2kw+/ARpglMjslBQcnBwSlRUSnR0Z/uXibKf7BBcevWLXNzc/QoUVbfU6meJo27yMjINu3bDyyuJ3pJdXUZS09IiC9rbPHXKgWfiRU6tFXknWglvc+ZJq0snD8pGBjoq6upDRoihbpHTpgCuI6o2ziiScvIZq0iWzrETp2Z5Cv5Nd2/e7devXoYoevWrcO/c+fONTU1nTRpEth12bJlsefYsWNWVlaAdBxAPi0U7Qt8xhDGKCBDyuTJkykwGTgPfZMjbRYSbOo2lM4UkyYj2LT/5MmT2D+U8slkrlYjOdFRMBf1TJBq7DEwMMCjl8zOR4+6u7tTfHq+fPkoM56vr2++fJrtHDpVq25bwUwYN0Jt2zph6TyhQxvoeup9HIfGxkraVr/+/cmiMlERdxPz6lXig4dxc+YGFyoWpmOYUNb8Q1mLEB3DoEIgFcXC9Eo9LWl4x7ZR8oFDKW/8GI2BGkgBlXTtoBbMAzAuLq58+fIDBgyYMmUKYxFDhgzBBjjG8OHDzczMQCdERfg5MYqvstamZ54Fp1Ww2YTPoPULlth/PFViY5MC3n14/gLkEwo+kAf8PGDcJL9+QwBQnjZ1fTt2/6iS6l9uUcePpkRGSmyWXJ2fv/zg5o5ZBpT+k6vznv3hO3aHrF4XuGxVovPiDqUrO/aXUGLNUkFRJFTySZCytTgrbNei2pwFgrVQwLd02We6hq6FdV0LFJeQ9h+YVWAsXnm1AL/PtBQwq2soWdQBs0blJT/nyjW86jSEDgKe7NO24+tuvd/07u8/dNTbUePApaGDBC9dgfaEbduJKSDy+KnoM+dirt2IvXMv/onLhxcvE31fJwUGYp7CdaXGxEJB+Jj59ONKThSfhVuqevXIPlWpv0xdy9PTE5jWp08fSuGo6pgRGxu7ds0am9q1l06bnmJlE16lVsrbAFJA0taDzmtqahzeJfm7piSp79msNnSQ2rlj6vj39iU1rULC+g1bLCpWGKQwbCaGhKYGBn6MjvkoswRSYzDu4uPj379/b2lpee/ePVC48+fPv3nzBkSradOmoNbnzp1zcHCQL2ZBR65Tpw6lbqA6OLSIQ/wcwE4jhUsWIjZ1m19//VVDQyMwMFCJc/75558Yg5RH/bsroQ9QLPNRJXRamLt79y65cDRr1uz6dWkFEd2V6guAr+KdfE3/+OMPbFNGhd27j/UfMNa+eReH9n2nTnV+5vaSNd7n1aueivzYcyhLpOInkoFd/Qe9d+h0Rt/wqn7pENvG0Y2ahVevHVKpWnCZcjGGxiHFdEP1jaIc++Pg8IiIdu3a0ZIrrTl279598ODB1Obo6GiwDnJ6JGUEExlmt9WrV9MeqAYAaqLoFDL8SbclEE43so+5fqk4VqVzMzHBRUZKKOrqFnP1esSBw1C6gVdvR/wGRurdvK1n7QYAN2nBUd9Ycl0D7mkbSE7FUpSHibt+2ZeVqpNzCIAOrPLtsFF+/QbjuwBzsFmvek2kM1St+dKquuSiDDZbsgw4qmshHck2q4BZhW1WorJP1Aq80Ch0oYhOAUHYtklIjNB4clO4d0V63bkovH8tYfjFk0KBwvmPNW0R6NDZBzDbZ8Db4aMlmJ0+W4LZ5atCVq0F+Ifv2Rd18nTU6bOxN25hool3fYYZJ9HPP+ndO4VFPQJ6QeqHhI+ZjwyVw6xSVHtKhjD7Wb6mf08e/k1KCssquXHjRnt7ezCB2bNng6ZevHjx1KlT6FQYlY0bN3ZycvL2ktxEP9y4FaJVIqKBXapiAfdjyqfllaNHTxYurNvKTjh5QC3wlRD+RjIb9u4m5M2bb906aKmpBQsWlGfk+8wNBl1LcXvxW23atAH9wM+hD7dSJIig43fs2IHufeLECYwR8mxJS9wqwTUlFqacdaLCq7xv376YhsB/SF3lkoWITXf+2bNngLvly5fLfRvoo3HjxtFyZLzCbimvMPuloCfmBRcWFgZwk9z2liyRe8ehZ+ro6Ojq6gISycUOfYCM21QLjMwLenp6VC9AablTTt3phFSuFwQAc/0vTk4vFFwFsnLdOsrydHjv3mSgcWrqFmdnPUHwuXJV9HqVcOVqwuUroqI4L9Wg+eQrNWwYRg3mFKITMTExlStXxsnRCS9fvgym/fr1a3Rv3BnQD0w0uEb0UhyJ4Ua6ZLr+IRlba1PCw0EI411cYy5didizP2Tl2vcz5rwdOgqskpa6XlpWk4BU39i9RBkpJlq7lBQSUtJYMq4amUmLj6YWL8yspBcL4qN/zayel634z6plQW3JaFBcX4oQUVjUJecQ86oe1rU9azd81cge+O/r0Pl1116AdMnV+bcJ76fNCvxjfvCylSFr1odv3xW6Z3/qmXN/r12vWaj4+OFCXIga9O5UqYiJemyYMHcabrja5s3bPqkqWeEG+mnpUBlmk78OZr+qrMMPTgalVAwdHeb+/ftLly797bffoLihd2EggLSwyqEpCjBMPHchJH/xyJYOH4lapH393bt3I0dNt7KqWd6sTHkzowoVqvbrN/r5c4nSBAUFof9TbnnJke8LRR/wDlJ9+vRpkJbw8HBmGsV+jE0/P7+oqCiic/KvgMOwMnk0dgD4uAqcCsOHA2x2WLBJc7e2tq5Vq5b4efoL6gzk1weYolBHhsnyunjyeqD09aNHjwJv0VVY4SE6G1k/0BsB1wsWLHB0dCxTpoyoKLGB/ebm5iaKzCGU/vTChQuirBqL3L4nT6lHVQnQaYGr+BaF3IaHhZUzNaUaxJJbiCI9TqPGjctVqKB07b6+vl26dKF7AvUTJ9m0aROmDyMjI7KQmJmZgUiAcoAFka43aNCgUqVKAc+hKk6cOJGY+Zw5cxhcMwIjmTViY6GYJ3h4xj18LKHx/oMhq9a9nz4HLPd19z4SGtvUfWlexb10uWfFSkqWAS0pgk/CVS09ac1Lx1BCaQbLFLJXzhIwKwXr4VW2ooTVqi8cowjoe1mxCght5JFjkUdPRF+4FHP1RtyDR/FPXSVXZ4nNvpcWLiMjJTabNvq+SPjFTxZxhZOtR5OmnXR1NOvXkSxUjW0FA311mxpNbt1SrDDimPTZbAa5SXM6zGY5Yqumyfrip4pOlXDwSEgeraguvaCd4Q6nyIgBDgsLiwyPiEKnY2Y99G2yMYrplSdQiucVZa7gSkzsX6+FVdMjnZQ1m0vW9hm6z2CGeKy0XiBHbPoUQG2qgD6gEyA03Zqn9O+HDx8A1DY2NpSvg5y35WwT8wIw2cXFBQcA+sqVK0c1WdYpmDDk999/FxV5aShUJ4P0s6yRVFOMquu2bdsW0I1fXLlyJWXMprJr9evXB9uXZgrFonZyYiJBh6jIV4lvkd/RwYMHa9eu7awQXCwZgqpWrUrGEGajwyxD/qV0f2jnmDFjKELnE2UKDYu9fQcIKbnjLl4eOGfeu/GT3/QeAIh+3bW3b6cer7v0Ih8Gn9btJReR9l2k6JX2XcFvvVu2k14tpNerJi286jTyqttIeq/TEBuSt4NV9ZeVbBQvaUOi0IBx4DZ7GZkB/6X3UiYA7eSgYDEthORrMORfs+GlpFnGPD19t247vGjRhg0b9j11fZE2TaVkdwLhn8kmyUJlGSdh5OezIaDobB+27AgS8kX1HyJ+GnEJoaER0dExchJCZxAVFZ/lOSUyaAArYqLkWqBaYFppv3wn1FvCEB6Enq1wTUVk5I9VtSwFVCqqNaajo9OtW7cVK1aAgkKJg+IDiF64cCHYppaWFg4AL928eTOzzrGTbNy4EZ9euXKFXL4B13jfvn07Wc+omoCXl9fVq5LT3j6q+/zlQHhqJ61RouVjx441NjamgjVPnjyhqgQlSpSgNoMbk+GFLC1KPbNjx47kCgKIJsiFYA9mFn9/f0wxVOADjSHfj169ei1btoyAmhEJnOST6zVRFFkAsvgtuRqUApklDzrJmYS9okGGk969Ayv+9HofmPj6dYLXq4RX3uwV/8Ql7v6DuAcP4+4/BJdOjY37J2N/ZowGn4fCKXUVuYLPYfm7Fd50bh27w+hsopi4Zn1CEd3dXfo3c3A0MS5jaWFoYmJUu07zDRt3p6QkMcSmJT95n+d3OLcLQQ3YIx4redDJcx/JDcUE2seOHQNWAwZViwIbGhr269cPyE8zu3zk0ncNDAzIvWf06NGgxPPnz8e3KEUSxadTio+aNWuamJgkfb5+rSrUzr179+KL27Ztw1d69+6NGSFfvny0TAnwt7W1xX6q/wW63kDmwiefjEDpySccXwTNpsgXfAqODdAGUQ8PD5cbiHbs2MHK7dGd8fb2btmy5WdardIKF5HVz7KFpKZbgkTMDTlXVWlhzkxC+DNBOdOPYsPD7IwtShQXFs1Re3Rd8HEVnj8Q1i5VMzMRrK1t3771Z8v6s2bNypMnT3R0tJil1UYysMbzDvAD4Do2NhaPNd0SnErOHgzAgfCPHj26rBCwyvfv38ujaOVuJHRCsGjAJgVJ6evrA9j79u0LhMe/Z86cIcAfNmzYtGnTmHNIxioVi8wlQw3af+/ePUoXDOSsXLlypUqVGjZsiDkCn9aqVYulE5G37VNm1zt3KGuZUj3HjPue3Lvmf+1dCViNafs/p6RGUqJvIsqSREIjE4PITqYMEUUGfdnGTOmPJvsWMVmmGLvJDD6yfD5bYbJMTWT3NYSYkQptqEizeP73OffXcz29p9LupPt3dXW955x3ed7t9/ye+7mXoKCgOcqoSdXSHhVRsLzoDFFF/UksxvQSvSfCW7Fobz+wZ2/Z6ywtxjTfvJGzP+RvXsvfME32Z63PR8tatGyfnf0CVx06dChOBtFg532ynkFfrK+vP2vWrKKmJETuVfXoK+ZXTtfAh+hyj04g4eHhoKgxlrBbt26NGzeGX5G0sdcQJy6Lb/zLly9B60L3geHtK1euhF198cUXoNItLS319PTQb7Bjx46qip3bQ4YPH75v3z4m+DuJiaxV7QA8Gp0pqzp27dr1t99+Y1SZkVDJdss1azdZmsv+ytX8O0cRPXrikKy5mSK5k5+PMjUf03LoIfOa9H+4FXA1eplSKZn3ia5zc3N1dXX9/f3Z2wrci4XG/hKgOqcsoXoLCwtnZ2dYsLOza926NUadb968GStzgfaeMmUKsDe6AJWcq3kOXqYMqtLR0Tl69CgK6d69e2NRMJC+aDBRfW45XcNIwdbW9vnz56L1vihboiQpn6enJ4bl0ktBqFR1DQvtre12hyqCFlm2LPmeIkZpqqcib6qGhuzyOUWMUvRZmbFxo1evXqWlpcFjHxgY+NaXmlC9jCHp6elwZ4ODgyv8znKDQ5cuXXr27Pnvf/8buRRdjBYuXNigQYO+ffuywtI5lsSDiAnlYNq1a+fi4gLMKZfLgXjt7e25P/mNGzfQ96PQXDo8FSF6eosFHYrqfXgpdti/2H6i63dhIigLquN7mpKS2ryZYbIi2F/OmOwHxdS97JfTiipLibcV2Vrg7+8sOejtGzfvRUUpYtCio6MZuWq8L087ciloS7izmCWswjtisawYoF+/fkxZlxY/Wlpa8lpjZZuu4pSLJvGmTZuOHj2aKUtDcge8YjKfiGFBM2fOHDJkCMYE8bwNktccXa1wb2vWrOnUqRMmEnkvKzOqFRXz2iXcAx89c8RsG28F35AHDkhusTrT9YMHSebmeqm/y1iWgq6XKOZ5ZO3ayhoYyrp0lr18qkjNx17LLSxkN2/enzfPX0tLKycnh1XyPCOhig1i6FMnVkWp8EHc69evvb29J06ciPmoscoYCGBeIqHMyTP5Vh06dMAKX5ifhGeFldifi9ocGTsgIKBjx46YTFVi+RHt1Y8ePRo+fLijoyPIeAz+klAHL41EXsdvVcLF8DD3B668rlAco6HDsxp6OPAsIqamTa/EyFiugq5XKKIlZJd/lj1X1ICSbQ1RZORLui8zbaJ99+5vVlZt+vfvT9L6/aPrkSNHNmnSRHwwKs/4hke8dOkSSFMxz3Z5smqLwT7Atyx/NrCE751kVvTChQswBHByctq9ezf0JmLzMjMzz58/P2PGjN69e2MAV/EMLHojczIvVBP+XRDvamhfdu+VgihKzYpnXZL7zm8NdIgwiklMTLx582ZkZGRYWNjmzZtXrFgxe/bsSZMmubm5DRo0CP2C2rZta6UC+NLOzq5v377QyXp5ec2dOzc4OPjAgQPwHMItlhRQZkJKczWhbi4nPhs23mu8IqcTy5Md2KVg6bgbsjd/g0qRLZuvyNkSuERm32PwnXhFPMKWLVsYTam8R2qHKcP6dHV1J0+eXEl3VuI3Ir6kxZc9Ku0h4KX77bffyibGRI2NyydPnvznP/85cODAIUOGjB49GsYFnp6eQAtjxoxZtmxZbGwsvOm7du3asGFDUFDQaiW+//77PXv2HD9+PCYm5u7duzCOADlUziGDOKv7Z9H4oyD+LBn+UEFJtip+crm0Jwh37dmzZ48fP75z5w50lEePHoXL+M0338ycOdPDwwP0IQyaQEvo6+tramqqevt/8MEH//jHP1q0aIGJFKAbhfvlqAL4smfPnra2thYWFrB+7dq1xZ3o6em1a9cO7jIc98yZMxiaJ6Hud+tVzlXNrVu39PTqHt6nYObnT2VmpgrPEAd72Qc6sqdJGnfiasGJRR04PG+xQrqIeduI8ao7REsIekRXUuiTalF7iW92heycGyvKzJASPz28ROnp6ffv3z9x4sTXX38NLz681/Xr15eVDEAmjRo1atOmDXDFiBEj0LEc6H3btm179+6NiIg4e/bs9evX4+LikpKSQOaBgHz+/Hl2djZyqZr7S4tVm1++fAkth2uVkpICnSZoYODe06dPHzp06Mcff1y/fn1gYCBcQFAFo0aNGjBgAFBr69atGzdubGBggJ6WEtSpUwdY2sbGBkY67u7uvr6+K1euBCbH3vDXX3999OgRHLG05TO45yp0EHDZT506tXHjRm9vb2gSHA4PraGhAawOTQX5zVMbsYIFl6v4vohJj3fv3iuXa65YKPsrW56WrDnn/zSneGpei5Lv2y7TMtD219JnfQZZ1Dd0Gj5csQkXYMTY1d+QyJQJOjA5bdUYVyU+zBW7z/IPXUXHD1wG2nF1dcVUUfBGDxs2bOnSpcBCoK5BQgM7gTjMVOL333+/d+/elStXgIT3798fEhIC5AyyHEge2Mnc3LxBgwYSXScBEAVwF5A8rGloaGhqatq8eXNLS0uQhTCWR90I8h6G87Db2bNnz58/Hw6xaNGi9UrAEeE/DPO3b9+OBRSKBzAVboLbwkgBKHHOnDnzlPD394fxBYwp4HAwrBg8eLCTkxMMN6AxnTt3tra2btasGchaEKvQWhigQcsxQ0uhkMvlcA25Era3t3d2dh43bhzwcEBAAAzbgRvPnTt37do16BzhYkqSVLz1YeZGmEKnHSWziqywmvVMmcIO7t2KFStA1WNGBTgjkPdwhaFXFT08q563Rcb+JeaidftPTBrJXJxl82crfPnaW4HSbnvoxCl28SJr3vbUBwZRx44r1hcqFBNjV1OuZvnxIJs3b4ZnEkagNCWhmg0DVByGQxoZGfn5+d24caOcpdDQVRu46OHDhzD2v3z5cnR0NGjsI0eOhCqxatUqUKFAlV999ZWPjw+oStCiQJIODg6gz4EhgTqAJEGxm5iYgP4E8tfW1i5UnZYNwE6ww9pKALvigeA/HBQODQ0AueugBMhRaNvIkSOnTJkC6hSUM7R8zZo1cBa7d+8ODw//6aefLl68CDI7ISEBNOqLFy9K66LJDUFFmb7LYOSXTB9zo5BqMBTcKbhBy5cvh2cA7TBwHb788kvovnnSRbSTVI19W+LpCgeNjr68LOA7nxkBc+etCw+PQs/SjFevZn3cJUmjTt5Q179evXrzIuuNkACK2K86cjXSTmJiIgg51fjrGntZ+GxjVlYWCEtMVwX8I4Y6Fkoakik2iX24wt9ofhNx57m5uampqWlKwEJ6ejrc2fj4+DtvA7AobsK3RVLl9FixLCQhYcmsq8SppsrcaVSnCf5XbVygOLg4e/bsgTcF+jJ4KoyNjWFQAN23xCJUGSPH4u114g1Cug5eswZaeHbGzJz6jZ+N8ng+eOirdYp8OJjQjwR2ZdgHKttnCWkHBqSg0EDpsZrtmcmvP9LypUuXMDEUDIHxFRAnm8o2j1mU31pJJhBFf7by1gov97yD2PK3TlBKerSiUvyp7cuI5ygSY3Z2dlhYmKOjIxq1LCwsYECECRurzEgiTouLjwpT+pfCmGgYVtZYviqtjmF6/UaZbTr+r2qYMgk58W0FGpMryX1IdaTv4eEBzxsMw5lKxZaarKvhZZTL5S1atLh69WqVqaYSUmXJ/egkKQKKwt+F4X0NDCzncICX2MAvMzIyduzY0aVLFzQiOTg4HDx4EAtVVKWRRBI14OTkBPof09c8dxuX9oFhhoV1Wr0Ps7/wYVhlnkwiFXTNX79+zW83J4pyuksxFX8kPJCrqys8Y1hPrSZztSiKWL6TTP/+/TF5iERZEWj8pcrbwI2LFy82NTWFJ0dfX3/q1KmY9rwKjCSSUSFmJMYE8n9CS5NTsjynpOkZpZu0TP/QLO+nM8jYZBIp5zVHrvD394eecdq0aYcPH8a4ZlWP5VINISXPGDLPnTt3MPqPZ7euydF2YuQOljZwc3MTSyqQGiG89Z3Cjz///DM8POhB1K5du/Xr14v+2xVuJJFwNSZ+nzJlCiuYIS03dFdGizZpOgbPBzi9EaKB6FaW+bLjTQeWbtq0KY6tjIyMhg4dumHDhrt376q6K4uTMsVPfItT3jk5ORj3Bzv/6aefWMHkzDWcq0+fPg1XxtnZmV86EtWEkvM2f0NhXAZCyMbGBnOww1scERHBS9BWCG+Lhk3k6n/9619Y+a5AJK+yfpBitTv3nju5pMq0aM6xYu9+bm7uypUrDQwMRN8q4PCJEyfu27fv0aNHqnM0fE5EkstUvK0pKSlLlizB4I5x48alp6cTV3MDEVMmg4Jr3rlzZ7j+5Q+KJ9RM3ubJ3vGb27dvz5w588MPP8R6ed7e3teuXSs0UrLM42X8GBgYiBWl0ZQq8Rh58+dfSNEvlwVmNG31Z/wdNImI8ctIIKhSqJJFCe8CnwQE9kDbsr6+PrDr2LFjGzZsyAtsQX8NN+jkyZMgvLmtW1K5GJCRkRETE7Nq1aquXbvK5XK8obyYIBXUE2s19urVS1dX98GDB6xgqUoCoVSPk+okI6hfeFWHDRuGHoDNmzeHEe6tW7ckIll1sMwKlv8Qd85JFYiib9++sFsvLy8+cczE8nO4H2VFIVjIOx6RM3+x+PCrFk4iui6V2OMGsRMnTpibm8O98PX1ffr06cOHD4ODg4GrzczMeOyYpqYmEHiHDh3slejRowf879ixo1hL0crKCqQ1ThbzbrSG3xHRDLJu3Tq4SpJSMvRAEsoptvkkI08OtnPnThAGGHHTqlWrOXPmxMbGinYSUTlz90h0lZTEeCYlJfn4+AAP1K1bF3bLVDyxVduDMvuvx0/Yy5ev//gjNDQ0NTWVH/HQoUMhISEYLkfG7dKapJBJYGyOtQvhpuDMID4GwN6gnH/44YeFCxeOHz9+0KBBdnZ2XZSAhf79+3t6eoKuDg8Px2ylEvVOjMR19aNHj7S0tEaMGMGEWVd6FAkVayQRh2xAkjt27ADexlhUGEEPHjwYNEN0dDRaKYuqXgRPLIguoNl+/frheBlENb7gbzFscpWeTyyYvhgrdwC+//772bNnwwLoPVCJjMqml+MuwyB9yJAhOJI6cOBAyR05JIqdhjlit4jPLYYuohmEUrgTKu91LtRzG15neAIxJgvRqFGjbt26ubi4fPHFF75KeHt7jxo1qnv37twi2qRJkwULFvDSGyU1OAtlOMaOHbtmzRpHR0esxLF8+XL4CAuurq5nz54lui6/beTMmTPW1tboI3T48GF+32EwBSJcTOcuhpUVz9KFJsqrOdIaS/H6+fmxGu98TnhXvI14/PgxKN7AwEAPDw8YIwOBN2jQoH4+mjZt2rlz5wkTJmzcuPHWrVt821IZNvljHxcXh+Xq3NzcwsLCYGHFihUwGAeFD52CWBqJUDbbCN4g+A+Xt1WrVkAyLVq0CA4O5o6dTJibLt7BTxJKXBmpIdT/wiI5T506Fa4kLz1GXE2oet5Wffv4xEqeEmIeXfFNL3nGQsljv3jxYugRoHcYOnSokzJcPSAgICgoiClDP9zd3RlVNCj3zRVJ+8iRI127dkXHzv79++/YseP3339nKhO7xdQrZwWTw+B0Rk1gbK4xnj17pq2t7enpychqTVAb6pZ4ZaumBymzrx0fsPfo0WPp0qVbt24Frd62bdvMzMy1a9ciXYeHh9va2jKabayg2yraN27fvj179myeU71Zs2Zjx44NCQmJiop6+PBhbm4uK6zwNyI7OzshIeH06dOrV68eNWqUg4MD0FcNoWvUGKGhoYo6d0JVR3rMCOowoK6kPC0o9g4ePGhvb8/ynaBArixYsGD79u2TJk2Cj35+fmPGjCF1XeGkzecCgL1v3br17bfffvrpp6L/HkhHExMTGxsbewHQsVpZWcFqvI4SJhZD14iawFp8tqVPnz6WlpasqooyEAjqMKiMjIzEstFYnjIuLu7o0aMbNmyYOHHi/v37Fy1aJNpXCRVrHpEYvuCb5OTkc+fObdq0CTpKENsDBw785JNPunfv3k0JWABWh1uzcOHCbdu2Ac/v3LkT6Bq9d2pCl4oPbXp6OnRYc+fOJSFBqIHUIck3AgJ73bp1jKyCVcjbpTJq8ZsCertZs2bvKkFo1QMtIdA9QScVHR1NlhBCjaILPgUmRoodPHjw/PnzjFJQVuG9kJQ0EtPaq9atQ8v28ePHJan53vurhHJi1qxZWlpaWVlZjHyWCISCEo5QIYOXshF4oV586LBtqURRmUIlFcaroA5dZafB54brXr16dezYkZH/HoEYRvkWkKiuwIspulmWn/xRYfr6+oK0xnkH1SAmSZWKCk+rLsnyKhbpk5RE4ZVPK6RSAy4YGxuPGzeOkeGaQCBdXTkauwy+8arMjylltm7dClw9f/58VjCZuWqfC0hISCh/HI0kq1hpY3NU006WoT149TIzM2vVqrVkyRKW785EIBAIFTJyX7VqlZ+fHw9jkVSWKZ6yVPM6wpcbNmwArkYHS0kBdNWuwdvbG4Vomafkisp1A/tPTk6OiIj45ptvvLy8BgwY0L59+5YtW5orAQs2NjaDBg2aNm1aSEhIdHS06Bmu6hVTcrq+f/8+nP4PP/zA8qdaCAQCoZx0jfQyefJkjIIBSZydnS2hrKLMCNySIEbWAOONHTsWixQUKDwhMD8v6ZiRkYFpt318fMpgN5DskH+ENhw8ePDzzz83MTHhXuKGhoYdOnQAxnZxcRmuBCz06dPHysqqXr16uA5IYltb26VLl965c4epJGkvSduws4iLi4O9HTt2jOiaQCBUuE0pKioKmApIpmHDhtOnT4+MjMTaryVU1yy/oIy+vj7sZPXq1axgglxVIzkcAjoI5Mnly5eXlq4lRA3LeXl5R48e/fTTT7W0tGCf9evXHzZs2LfffnvhwoXU1NRCKZf3SomJiadOnZo7dy7obUwdaWdnd+jQISTbkie6QbqGiyl68dFjRiAQys/VXEMio4IoxYIFmGjR0dHR398/NDT07Nmz8fHxT548yczMzFACCPDBgwcXL14MCwuDdTp37owVDZydne/evcsKJsjlnttIek+fPkUFDsSIKXmxYHoJzbyq5hRoT0BAAFZBMjY2Bq0OFF1oVnZJOkFJ8gRcTk5OBpLH62BhYREREcFUvEmLp2voicTwc3rSCARCBTI2pyPgzF27dllZWYnFHFFwFgVQsx999BFI6/v37/O9SViaF7xYsGCBtra2jo6Ol5eXiYkJGiJAx5bEbsCpkrc2PT3dz88Pa0MPGDDg9OnT3AJf2vyB6B8irglavW3btrDnkSNHQsuZkAS1KNLGVp07dw62io2NJbomEAiVRNpcr4I0Bdncs2dPVL+tWrXy9vYOCQnZsWPHtm3bgoODQX8Cq588efL69eui2QQ2fP36tVjTE3cOTD5jxgxdXV3Ym6urK+b3y8nJ2bt3L3xz6dKltzKbxO4N1Lp27Vo9PT3Y3M3NDSW9pBJ0aT1DVOdM4SMcBQ5hZmaGZSiLT1uNp/Df//4XNuGynB4wAoFQ2aQNyxcvXpw8ebKRkRGStq+vL0hHnouv+F0BU8XHxwPdderUCSfyRo8ejUU/Yf+YAWbLli3wU3JyMis6+k81L/fPP//cunVr2NDJyenevXussAwn5fSdFv1M4uLiWrRoUbt27cjIyOIZG9eHvoMXZ6SpRgKBUDWkjR+zsrKAfIYNG1a3bl00gDRu3NjR0dHPzw/49tixY8Cf58+fj4qKCg8PBwXu7+8/cOBAXkvIysoqKCgIs/RzwwvymI+PDyhkrBBUfD0aXlxy2rRpaFVG8uQ7rNgKCJKQn4yMDBsbG21t7atXr7Kiq5lz4zyfbyW6JhAIVUPakmrLeXl5sbGxQESfffYZECb6YKgCaK1Nmzbu7u6hoaG8rgGXx2IpQ+B8zDJaaLC2hKuvXbsGB4X9Q3eALComeq3wsCl+1nj09PR00NhmZmZYn7SYBsP6BgYG06dPR6MNxXMRCIQqIO2i4gRxAbTuw4cPr1y5gtIa/l++fBn4GQ0dqv57qpk6zM3NnZ2dWWFefBJj9aZNm9CGfOHCBVbWMJYy91zYhhs3bqBLOSssVJMJruzW1tYDBgxglI6PQCC8I7EtFgkqiiolhR0Lrb2LnJadna2pqblo0SJVuuZqHDdHA8jw4cNfvHiBK1dlxhhevwz+r1y5ElrCqzmr0jUSu5ubW5MmTSpJ9hMIBEJpqVu1VqNqoqRipuSuX78O1Ie1kkUbL+dqpjSbDx48GFZbtmwZ8rxY4rmKBxpMWSPD1NTUwcGhKHsIsvrq1auhzUlJSYyS8hEIhOpM+EjO6MUXHx/PBIc3kaufPHmCsZac0t9VGkbRJBIcHAxN4nOOksZgy2NiYsQ4dKJrAoFQren6q6++0tXVffnyJTePiFz9+PFjS0tLbW3tc+fOMWHO7l1RH7dLo+PHzJkzC6ViXCcnJ6dOnTpwgoxmGwkEQnWma+S07t27YxV7MWsf/vTixYtOnTppaWlh5o13ztW85diV9O7dWyybW+g6/fr1a926NaNkvwQCoTrTNVP6BNatW/fLL79kQsFNnsDE0dERFCzX1WpCenxcsGLFCmheamoqU4nu4ets3LhRNPUQYxMIhGrH1Sg+b968CWy2Z88e0aSARDdjxgz4ae/evWrF1WLjz5w5Ay2MiYlhhYWZI4EnJiaWLdkggUAgqAmQk0NDQ4HNEhISOL/h92FhYfD9vHnzuA1ErYwJSM737t2DRu7cuZMVFrfIWb1Pnz6iPYQYm0AgVC91jfzm4eFhZGTEvfKQsZOSkvT09Hr16sUE/ze1YjlsZ3p6OtD12rVrWWF5X/k57tu3D1bDYHmyhxAIhGpH17jQsmXLIUOGcEMB8vbIkSPlcjmm16uMkrsV1f68vLzatWvjEKDQeEwe9WloaOjo6MiKiIIkEAgEtQVX0SA716xZw4S8H8eOHeOStfg8pe+crl+9eqWlpVVoPKZEYAcEBMBJ3bx5kwQ2gUCoXkASO3jwIK+3wgtstW7d2trauoQlfd9td5OWliYxhkiCPbl5B9bU0dFxcXEhgU0gEKqXJQTJecqUKfXq1cO82Uh327ZtAwIMDw9XZ2nN6TohIQFa++OPP0pay6PyxZPFNCPnz59n6mrhIRAIBFW6RqaytLTEhHVIaPC/WbNmn3zyCSsYMqOGQL4F7uVu4SIDwzKWkheFNPRKZmZmnTp1kmQjJBAIBLUFStPU1FTgOtCcSGUsP3nIiRMnmNobeLF/2bp1KzQ4MTFR0r88e/asS5cuJ0+exFEDV9r/+c9/YP2goCCJ8YRAIBDUmetOnToF3HXmzBnOXXZ2dhYWFhIFrp6jAzyFSZMmGRoaiiE8SMvh4eFwahoaGiEhISy/HAP+9Pnnn0vM9cTYBAJBzbkOk4umpaXh9xjeuH79eqb20X+8K+nQoQM6h0uK4wAnGxgYuLm5wRl5eHhgUTNk9czMzObNm7ds2RIrEb+r1IIEAoFQcnU9YcIEY2Njrkh9fX1r1aqF7K3mqaGRY4F45XL5woULmZDthCm9++rVq+fq6grLQUFBwNiWlpY3btxgyizZ8P/SpUvw5eDBg//OBzE2gUBQZ3UNfGVtbY1fAmM3btx4xIgR1UJaY/sjIiIkBWVE70T4FdePiYlp2rQpHzjk5eWxfCs9iHCWXyuHGJtAIKgh3SE7denSpXv37vhlVFQU0Nfhw4erEV17e3vr6OigBwgOB3CY0L9/f1NTU1xGA8iLFy9GjhwJJ+js7MyNP2vXroVvYIjBChbHoSeEQCCoG90NHDiQq+sZM2Zoa2tjBUY1t4Twtpmbm4tx5dgH3b59G0g4ICCACYE/+NP27ds1NTUNDQ2PHz+Oe1i1ahWWnkTJzWceibQJBIKaAHlp6tSpPEYGqA/Ym6m9/x6X0L/++isw7datW/lwAE9q8uTJGhoaT548EfsdXsb97t27dnZ2sOH06dOxeg6GBcFA4/Hjx+LIghibQCCoj7rev38/MNW1a9eAqWBhw4YN1cgSEhgYKHpci6mtxVILrGBFeBTh8+bNg9Xatm175coV+OnEiRM6OjrGxsaxsbHsnVaiJBAIBAmQjrKysvT09Dw8PDC/6K1bt6qFusbGf/zxxx999BGX0Mjhnp6ecCIPHz5kBU063L4BZ4drRkVF4fwjhsyA6m7VqhV83LJlC8v30ybGJhAI6qNRcbqtUaNGFhYW6h/lx7k6JSUFmr1kyRImJBK8fPkyfPn111+zgn594ubiuUNvNWbMGNikV69eIMvh+1GjRsFHLy8vMmUTCAT14T1OfRMmTACOAuKqRpaQPXv2QJuvXr3KhJnErl27Ghsb42xpURzLv+T6effu3TDEkMvlixcvZvlR7ba2tg8ePGBkyiYQCGrAe6JYnTp16nfffVeN6NrNzQ2YWXTVW758OdDsoUOHWAmy7UnmH1NTUz08PGDzunXrgmIPDAzU0dFp2LAhenSruZ8MgUCoUYzNiUvNeYnbn42MjMaNG8fyM1NFRkYC2U6aNImVOJc1P30uzuPi4lxdXTU0NEBpw3+ZEsuWLSN7CIFAUB/Grhbp+rkLX2xsLBDpgQMH8Pv4+Hg9PT0bGxt0zCv5ifA1MUYGlzMyMsLCwmbNmjV+/Hh3d/cRI0bA/kljEwgE9WFs9bfQckvIokWLgK5TUlKYsjyBiRLo0VcGdw6xz6K5RQKBQCg/V3NLe/v27bt16wYLv/zyi4GBAXD1vXv3WPkKxIimoT+V+EMJmmokEAiE0nIpsvGVK1dAWu/YsWP79u2w0K5dO+7CQaRKIBAI6sDYKK1dXFyApTGkxd3dPScnh1HhRQKBQFAzrvbz80OHDTMzsyNHjjAKPyQQCAQ1o2vk5IkTJ7Zp02bXrl0YdUh5qgkEAkENGZspKwtgUAxOCNIkIIFAIKghV3PnECJqAoFAqBaMTURNIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCNUO/w+w7delCmVuZHN0cmVhbQplbmRvYmoKMTUgMCBvYmoKPDwKL1R5cGUgL1hPYmplY3QKL1N1YnR5cGUgL0ltYWdlCi9XaWR0aCA1NjIKL0hlaWdodCAzMDIKL0JpdHNQZXJDb21wb25lbnQgOAovTGVuZ3RoIDU3Nzg2Ci9Db2xvclNwYWNlIC9EZXZpY2VSR0IKL0ZpbHRlciAvRENURGVjb2RlCj4+CnN0cmVhbQr/2P/gABBKRklGAAEBAQBxAHEAAP/+AC5IYW5kbWFkZSBTb2Z0d2FyZSwgSW5jLiBJbWFnZSBBbGNoZW15IHYxLjEzCv/tNlBQaG90b3Nob3AgMy4wADhCSU0EBAAAAAAAIxwCAAACAAIcAgUAF0ZJTkFMRklHVVJFUyBGT1IgUkVWSUVXADhCSU0EJQAAAAAAEPriE9771mPS2trR+ucA52s4QklNA+oAAAAAHaY8P3htbCB2ZXJzaW9uPSIxLjAiIGVuY29kaW5nPSJVVEYtOCI/Pgo8IURPQ1RZUEUgcGxpc3QgUFVCTElDICItLy9BcHBsZSBDb21wdXRlci8vRFREIFBMSVNUIDEuMC8vRU4iICJodHRwOi8vd3d3LmFwcGxlLmNvbS9EVERzL1Byb3BlcnR5TGlzdC0xLjAuZHRkIj4KPHBsaXN0IHZlcnNpb249IjEuMCI+CjxkaWN0PgoJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTUhvcml6b250YWxSZXM8L2tleT4KCTxkaWN0PgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jcmVhdG9yPC9rZXk+CgkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lml0ZW1BcnJheTwva2V5PgoJCTxhcnJheT4KCQkJPGRpY3Q+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNSG9yaXpvbnRhbFJlczwva2V5PgoJCQkJPHJlYWw+NzI8L3JlYWw+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY2xpZW50PC9rZXk+CgkJCQk8c3RyaW5nPmNvbS5hcHBsZS5wcmludGluZ21hbmFnZXI8L3N0cmluZz4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5tb2REYXRlPC9rZXk+CgkJCQk8ZGF0ZT4yMDA4LTEwLTIyVDEwOjEzOjExWjwvZGF0ZT4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5zdGF0ZUZsYWc8L2tleT4KCQkJCTxpbnRlZ2VyPjA8L2ludGVnZXI+CgkJCTwvZGljdD4KCQk8L2FycmF5PgoJPC9kaWN0PgoJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTU9yaWVudGF0aW9uPC9rZXk+Cgk8ZGljdD4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY3JlYXRvcjwva2V5PgoJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQk8YXJyYXk+CgkJCTxkaWN0PgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTU9yaWVudGF0aW9uPC9rZXk+CgkJCQk8aW50ZWdlcj4xPC9pbnRlZ2VyPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LmNsaWVudDwva2V5PgoJCQkJPHN0cmluZz5jb20uYXBwbGUucHJpbnRpbmdtYW5hZ2VyPC9zdHJpbmc+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQubW9kRGF0ZTwva2V5PgoJCQkJPGRhdGU+MjAwOC0xMC0yMlQxMDoxMzoxMVo8L2RhdGU+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuc3RhdGVGbGFnPC9rZXk+CgkJCQk8aW50ZWdlcj4wPC9pbnRlZ2VyPgoJCQk8L2RpY3Q+CgkJPC9hcnJheT4KCTwvZGljdD4KCTxrZXk+Y29tLmFwcGxlLnByaW50LlBhZ2VGb3JtYXQuUE1TY2FsaW5nPC9rZXk+Cgk8ZGljdD4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY3JlYXRvcjwva2V5PgoJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQk8YXJyYXk+CgkJCTxkaWN0PgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTVNjYWxpbmc8L2tleT4KCQkJCTxyZWFsPjE8L3JlYWw+CgkJCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY2xpZW50PC9rZXk+CgkJCQk8c3RyaW5nPmNvbS5hcHBsZS5wcmludGluZ21hbmFnZXI8L3N0cmluZz4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5tb2REYXRlPC9rZXk+CgkJCQk8ZGF0ZT4yMDA4LTEwLTIyVDEwOjEzOjExWjwvZGF0ZT4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5zdGF0ZUZsYWc8L2tleT4KCQkJCTxpbnRlZ2VyPjA8L2ludGVnZXI+CgkJCTwvZGljdD4KCQk8L2FycmF5PgoJPC9kaWN0PgoJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTVZlcnRpY2FsUmVzPC9rZXk+Cgk8ZGljdD4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY3JlYXRvcjwva2V5PgoJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQk8YXJyYXk+CgkJCTxkaWN0PgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTVZlcnRpY2FsUmVzPC9rZXk+CgkJCQk8cmVhbD43MjwvcmVhbD4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jbGllbnQ8L2tleT4KCQkJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lm1vZERhdGU8L2tleT4KCQkJCTxkYXRlPjIwMDgtMTAtMjJUMTA6MTM6MTFaPC9kYXRlPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0LnN0YXRlRmxhZzwva2V5PgoJCQkJPGludGVnZXI+MDwvaW50ZWdlcj4KCQkJPC9kaWN0PgoJCTwvYXJyYXk+Cgk8L2RpY3Q+Cgk8a2V5PmNvbS5hcHBsZS5wcmludC5QYWdlRm9ybWF0LlBNVmVydGljYWxTY2FsaW5nPC9rZXk+Cgk8ZGljdD4KCQk8a2V5PmNvbS5hcHBsZS5wcmludC50aWNrZXQuY3JlYXRvcjwva2V5PgoJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5pdGVtQXJyYXk8L2tleT4KCQk8YXJyYXk+CgkJCTxkaWN0PgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQuUGFnZUZvcm1hdC5QTVZlcnRpY2FsU2NhbGluZzwva2V5PgoJCQkJPHJlYWw+MTwvcmVhbD4KCQkJCTxrZXk+Y29tLmFwcGxlLnByaW50LnRpY2tldC5jbGllbnQ8L2tleT4KCQkJCTxzdHJpbmc+Y29tLmFwcGxlLnByaW50aW5nbWFuYWdlcjwvc3RyaW5nPgoJCQkJPGtleT5jb20uYXBwbGUucHJpbnQudGlja2V0Lm1vZERhdGU8L2tleT4KCQkJCTxkYXRlPjIwMDgtMTAtMjJUMTA6MTM6MTFaPC9kYXRlPgoJCQkJPGtleT5j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
[[vid|https://www.youtube.com/watch?v=71XbdtoG7P8&index=4&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
Simple network, described above.
''[[Acyclic networks]]'' have no cycles. A [[Directed Acyclic Graph (DAG)|Directed acyclic craph]] is a well known sub-type.
<span id="hypergraph">[[Hypergraphs]]</span> are sets of
elements with
[[relations|https://simple.wikipedia.org/wiki/Relation_%28mathematics%29]]
that include more than a pair of elements (i.e. they are members of a
higher [[cartesian product|https://en.wikipedia.org/wiki/Cartesian_product]]).
Hypergraphs can equivalently be represented as [[Bipartite Networks]], where there are two types of edges (a special case of a //multipartite network//, where there are many types). On the other hand, a //multiplex network// is one that has multiple types of edges.
[[Trees|Tree (Graph Theory)]] are connected (<small>can reach all
vertices following edges</small>), undirected networks that
contain no closed loops. A //forest// is a disconnected graph whose
connected parts are trees.
A [[Planar network]] is a network that can be drawn on a plane without having any edges cross. It is a special case of a [[Spatial network]].
//Temporal networks// are those for which the set of edges and/or nodes varies with a time parameter.
A [[Similarity network]] is one that expressed how similar entities (expressed as the nodes) are. The degree of similarity being the weight of the node.
[[Fano's inequality|https://www.youtube.com/watch?v=0ClUyuzcst0&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=14#t=8m22s]]
https://www.wikiwand.com/en/Fat
Fats, also known as triglycerides, are [[Ester]] of three [[Fatty acid]] chains and the alcohol [[Glycerol]].
[img[http://a.files.bbci.co.uk/bam/live/content/zp3jtfr/large]]
//aka feature extraction//
[[Machine learning]] applied to [[Feature selection]]
Often uses [[Unsupervised learning]], and in particular [[Generative model]]s.
[[GANs for feature learning|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=33m25]]
[[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=54m28s]]
In feature selection, we would like to select a subset of the features (input variables to a supervised learning algo) that are the most ''relevant'' ones for a specific learning problem, so as to get a simpler hypothesis class, and reduce the risk of overfitting. This is useful mostly when we have many features.
What we do is use heuristics to search the [[huge space|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=56m54s]].
__"Wrapper" feature selection__
[[vid|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=1h01m47s]]. Feature selections that repeatedly call your learning algo. Work well, but are computationally expensive.
* [[Forward search|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=57m30s]]
* [[Backward search|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=1h02m30s]]
Number of features to include can be chosen by optimizing generalization error (estimated by cross-validation), or by chosen a plausible number..
__"Filter" feature selection__
[[vid|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=1h05m47s]]. Less computationally expensive, but often less effective. For each feature i, we'll compute some measure of how informative x,,i,, is about y, for instance by computing:
* [[Correlation]] between x,,i,, and y, or
* Empirical [[Mutual information]]
!!__Learning meaningful ''representations'' of the data__
Can learn from [[Unsupervised learning]], or [[Supervised learning]] algorithms!
See [[Transfer learning]]
__[[Restricted Boltzmann machine]] feature learning__
See [[here|https://www.youtube.com/watch?v=S0kFFiHzR8M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=41#t=0m50s]]
Some features that are important in the behaviour of an [[evolving|Evolution]] system.
//Important features//:
* ''Evolvability'' ([[wiki page|https://en.wikipedia.org/wiki/Evolvability]]). May be defined as "the capacity of a system for adaptive evolution"; however, this is often called ''adaptability'' (I think). Evolvability is then defined just as "the number of other phenotypes //potentially// accessible from a phenotype" (see [[this paper|http://rsif.royalsocietypublishing.org/content/11/95/20140249]] or [[Robustness and evolvability: a paradox resolved|http://rspb.royalsocietypublishing.org/content/275/1630/91]])
* ''Modularity''. See [[Self-assembly, modularity, and physical complexity|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.82.026117]], and ''complexity''. [[Homologues, Natural Kinds and the Evolution of Modularity|http://az.oxfordjournals.org/content/36/1/36.abstract]]
*''Robustness''. See [[Mutational robustness]]. [[Environmental robustness|http://www.youtube.com/watch?v=vLYpjUANUdc&feature=youtu.be#t=4m40s]]. There are genotypic and phenotypic robustness. See [[Common features of GP maps]]
[[The Evolution of Evolvability - Dawkins|http://www.notionparallax.co.uk/wordpress/wp-content/uploads/2011/03/Dawkins-1988-Evolution-of-evolvability.pdf]]
[[Evolution of evolvability|https://simons.berkeley.edu/talks/lee-altenberg-2014-03-17]]
An [[Artificial neural network]], where there is no recurrent connections (loops).
[[video|https://courses.edx.org/courses/course-v1:MITx+7.00x_3+2T2015/courseware/Week_1/Biochemistry_1/]] -- other [[video|https://www.youtube.com/watch?v=U-GyLD1zHms]]
Fermentation takes in [[Pyruvate]]s, produced by [[Glycolysis]], and it is anaerobic. If oxygen is available, some organisms carry out [[Cellular respiration]] instead.
[img[https://s16.postimg.org/wg352k4h1/Selection_602.png]]
Lactate ([[Lactic acid]] ion) is produced during unaccustomed or strenuous [[Physical exercise]]; however, it isn't the cause of [[muscle fever|https://www.wikiwand.com/en/Delayed_onset_muscle_soreness]], as previously thought.
A ''fibrous material'' is any material system formed by fiber-like constituents such as felt, cloth, paper, muscle and wood.
[[On uniqueness of fibrous materials|http://ningpan.net/publications/51-100/89.pdf]]
[[Fibrous Materials|http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511525209]]
[[https://en.wikipedia.org/wiki/Filter_(signal_processing)]]
Main types:
* [[Linear filter]]
* [[Nonlinear filter]]
A ''filter'' $$\mathcal{F}$$ on $$X$$ is a family of subsets of $$X$$ such that:
(a) $$\emptyset \notin \mathcal{F}$$;
(b) $$\mathcal{F}$$ is algebraically closed under finite intersections;
(c) $$\mathcal{F}$$ is an upper family.
An //upper family// refers to a family of subsets, which is an [[Upper set]] w.r.t. the [[Lattice of subsets]] of $$X$$, that is if a set is in the family, then any subset of that set is also in the family.
See also [[Filter base]]
A ''filter base'' $$\mathcal{B}$$ is a family of non-empty subsets of a [[Set]] $$X$$ such that if $$A, B \in \mathcal{B}$$ then there exists $$C \in \mathcal{B}$$ such that $$C \in A \cap B$$.
This can be used to construct a [[Filter (Topology)]]:
[img[http://i.imgur.com/OEOLd0t.png]]
This notion can also be extended so that a family of filter bases (which we call a base, or a ''basis'') generates the filters forming the [[Neighbourhood structure]] of a [[Neighbourhood space]], or of a [[Topological space]]. For a topological space, the arbitrary unions of set in the filter base can be considered to generate the open sets
A filter base can in turn be generated by a [[Filter subbase]]
[img[http://i.imgur.com/i0vZ63R.png]]
A filter subbase can generate a [[Filter base]], and like it, it can be extended so that a family of filter subbases (which we call ''subbase'') to generate a whole [[Topological space]].
Note that the sets forming the subbase are part of the base they generate, because finite intersections include the intersection of a set with itself.
A [[Separation process]] to separate [[Solid]]s from [[Fluid]]s in a [[Mixture]] (liquids or gases) by adding a medium through which only the fluid can pass.
https://www.wikiwand.com/en/Filtration
http://www.bbc.co.uk/education/guides/zgbqtfr/revision/8
[img[http://a.files.bbci.co.uk/bam/live/content/z6sk2hv/large]]
----------------
When a product is made as a solution, one way to separate it from the solvent is to make crystals. This involves evaporating the solution to a much smaller volume and then leaving it to cool. As the solution cools, [[crystals form|Crystallization]], and these can be obtained by filtration.
https://www.khanacademy.org/economics-finance-domain/core-finance
[[Banking]]
http://money.visualcapitalist.com/all-of-the-worlds-money-and-markets-in-one-visualization/
A set of methods to solve [[Boundary value problem]]s for [[Partial differential equation]]s.
They are often based on approximating [[Derivative]]s by evaluating the function at points in a grid or set of discrete points (''discretization'').
See more at [[Numerical methods for differential equations]]
In [[Information theory]], and in particular, [[Data transmission]], a ''finite state channel'' (FSC) is a discrete-time channel where the distribution of the channel output depends on both the channel input and the underlying channel state. This allows the channel output to depend implicitly on previous inputs and outputs via the channel state.
The channel can be modelled as a stochastic [[Finite-state transducer]].
__See here for more__: http://pfister.ee.duke.edu/thesis/chap4.pdf
[ext[Entropy and Mutual Information for Markov Channels with General Inputs |http://web.stanford.edu/~glynn/papers/2002/HollidayGoldsmithG02a.pdf]]
Blackwell, Breiman, and Thomasian introduced indecomposable FSC (IFSC) in [7] and proved the natural analogue of the channel coding theorem for them. Birch discusses the achievable information rates of IFSCs in [5], and computes bounds for a few simple examples.
!!!__Examples of finite state channels__
* Discrete-time [[Linear filter]] channels with AWGN
* Dicode erasure channel
* Finite state Z-channel
!!!__[[Trellis diagram]]s__
Similar to the mapping between Boolean lattices and directed percolation. See [[Relations between the stability of Boolean networks and percolation]].
!!!__Definitions and basic properties of FSCs__
[img width=500 [http://i.imgur.com/kUKuIuz.png]]
See [[Markov chain]]
In the thesis he considers a [[Markov input process]] as [[Information source]]
Combining the Markov Input Process and the Finite State Channel, gives a new Markov process over the states given by the cross product of the states of the channel and of the input. They label this new set of states by integers too. This combined process is what they call a <b>Finite state process</b> (FSP).
!!!__[[Entropy rate of a finite state process]]__
See [[Random matrix product]]
[[Capacity of finite state markov channels with general inputs|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1228304&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F8703%2F27553%2F01228304.pdf%3Farnumber%3D1228304]]
[[A Randomized Approach to the Capacity of Finite-State Channels|http://arxiv.org/pdf/1303.3656v1.pdf]]
[[Capacity, mutual information, and coding for finite-state Markov channels|http://cs-www.cs.yale.edu/homes/yry/readings/wireless/wireless_readings/fsmc.pdf]]
See [[Automata theory]]
Finite number of states, transitions between them are followed according to sequentially read (a.k.a. on-line) input string.
[[Math 574, Lesson 2-1: Finite Automata|https://www.youtube.com/watch?v=ZqfLzZVhn7U]]
Formally, a finite automaton on an alphabet $$A$$ is a tuple $$(Q,I,F,E)$$, where $$Q$$ is the set of states, the subsets of $$Q$$, $$I$$ and $$F$$, which are the set of input and final states, respectively. $$E \subset Q \times A \times Q$$ is the set of edges between states, labelled by a letter in the alphabet. The transition encoded by the edge is performed, when the automaton //reads// the letter, while being at the first state in the transition.
!![[Deterministic finite automaton]]
''[[Deterministic machine|https://www.youtube.com/watch?v=jb_H7SGOyyI&index=2&list=PL601FC994BDD963E4#t=4m24.7s]]''
[[Reversing deterministic machines|https://www.youtube.com/watch?v=ceNNyyELhu4&list=PL601FC994BDD963E4&index=6]]
!!Non-deterministic finite automaton
''[[Non-determinstic finite state machines|https://www.youtube.com/watch?v=lk3LHnM8SxA&list=PL601FC994BDD963E4&index=8]]'' can have more than one transition that may be done when reading a certain input symbol on a state. They may also have epsilon transitions which can be done without reading a symbol. A string is accepted if there is //at least one// path through the machine that ends in an accepting state
Determinsitic equivalent in power to non-determinstic. But non-deterministic sometimes much easier to think with.
[[Convert non-determinsitic machine to deterministic machine|https://www.youtube.com/watch?v=pYoELTvm8Hg&index=9&list=PL601FC994BDD963E4&spfreload=1#t=4m30s]]
Equivalence between non-deterministic and deterministic machines is the key in proving that regular sets are closed under reversal.
To construct a FSM that accepts the complement of a regular set, just swap accepting and non-accepting states.
[[Closure under union|https://www.youtube.com/watch?v=24jxBQovUvo&index=16&list=PL601FC994BDD963E4#t=4m43s]] [[key point|https://www.youtube.com/watch?v=24jxBQovUvo&index=16&list=PL601FC994BDD963E4#t=5m56s]]
[[Closure under intersection|http://www.youtube.com/watch?v=cOyFWkphA04&index=17&list=PL601FC994BDD963E4#t=3m04s]]
[[Why are regular sets called regular?|http://www.youtube.com/watch?v=lP3Lxsf-MNc&list=PL601FC994BDD963E4&index=17#t=5m33s]] he uses a nice heuristic explanation of the [[pumping lemma|https://en.wikipedia.org/wiki/Pumping_lemma_for_regular_languages]]
!!!See also [[Finite-state transducer]]
-----------
Build an fst on the web: http://madebyevan.com/fsm/
https://www.youtube.com/watch?v=GwsU2LPs85U
A [[Finite-state machine]] with outputs.
See [[Simplicity bias in finite-state transducers]]
[[Mealy and Moore Machines|https://www.cs.umd.edu/class/sum2003/cmsc311/Notes/Seq/fsm.html]]
The [[Energy]] of the [[Universe]] is constant.
//Energy is neither created nor destroyed, it is only transformed//
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H9tn4sfHHXgbtNHufGvgu0co3lbdH8RavbQFQzMpIWNSGGDgg5yGJ/qjsLqeS3iWQnKgDGPc/jx6k4yTxgYP4Rf8ERPgd4k8NfCDxd428U6XNYXniv4geLNesnniO6fTdc1S91OzmR2Qbo5obpHUgnKkHLYJP782tlHChVjyAMZA6At+vfH0AyQCPm+BMv8A7P4crRlLnnjMXPGU6svilSm24xTbbaV+v97V3ufsv0r+Jnxf4sYKeEUMPR4e4bwvD+IwcJL2EMZhXRUpOCfLGU+WTva+r95u7F07/VzEg5EnuD3BI5zj68+54xcKsVIPTuc9ecevryM/zpbVFRJRzncABjrncAcY6ck9euOpOKmYEghRk4AYY/3h69fXtyO+7P1d/epuV3ZLmvfZOS1330utWndN6Jn8+xhKNKCcYwleN4qyju72s7bK7876tp3qlTtDD7uw4wO2WGScn+737A85Bz+An/BdLws+ufAvwTdq6oNI+JHhjVW3EgstlrOk3DL94feEPAPqRk4Nfv8AsGXaMYG0Z9iCw6Z/znk8DP4rf8FmNA1HWP2e45beJnj03WrTUbjCkhbe2ntZpZDwfl2QsSegG7JO0E+PxJeWUYhxTlHlloldXvZXuvNavbzbP1bwXryw3iJlbjNRbrUU5N/zOSdtHr1Xk5aNpX+qv+CcXimDxN+zJ4D1RAUE+mw/K2AflithkgDjOfT06g5r9CEO5OOcEc/Rmz19MjHfAH0r8nv+CSGt6dr/AOyD8OtSsZUktpNOXayEFTiO0B7kE/dzg9wckg5/V2PBjJX7o2EfTLj9c8e2euK0yKbnk9KTl73JTu1dpLlinbXtH7pPS6bfkeJVCOG4+4gw8W2o4rENqSaleVeo7taaOz+d76ol2DGM9+D/APWz/n1NPHfPHPHfI9fbPpTYyShDc4J9fXjkn0/zilzgEnt/iR/T36j0Jr2VZqDb3s1pvq/PTZff1sz4an8K5dY3Wvld7Xb028/Vt2a3ALewUfi0nPX2H6dxzWkJCPgjOOB77m56+i8fjkgjm1gOp+oI/Bnx39j+YznFVZoz5bnHRf8A2Zsc5I7n8cZODRtON3o276eqXT+6te7jdN6kVed0cRbWyjyW3T55X6q7sn56vW++ZJdMkbHgkEAED/abjk46D9D1JNfml/wU1+NeofCr9mnx7c6ZfLZ6lquiatp9k25lka4NurIIirKxkzyNp3DJ68E/pc1o7RE44JDE464LEknp0IOM9h1HNfzhf8FrvGQ8S+Jvgb8FdG1Erc618TNJstWs4jlriw1G2WMwyx5YsjmN8jbk5xzjB+a4rxdbCcOY/wCr642dRU8PZSvLnSSWl73S6vr3vf8AYPo6cP4LP/GnhyGdRi+HcLQ+t5nKaXsoKgpTc5c2jakoPu73Tabv7b/wRe+BPh7R/gRa/GrW7KW58X/FG0sNf1q/vm86VryDdaB4TOskkIKWyZAkJPqSCa/diBoYowqphdq7cgcAbgMZ/wA4Y9cEn5L/AGTvhknwt+CfgzwVBALaHRtKjtYrdU8sRgXE7kbdox97IGM/e5/vfVEEbtF+8PIIAznoCw7nv2H1HOAw7OH8FDCZBlkXT5K9egquLtv7W7cubZ6SUmut73d/el4Hi5xDiOI/FPj6pHFPE5XluaSwuRzlKc4xwNOdWlTVHmd1F0qdJuK0s4pbNvUidXaQrxkD8cMPT8eecZI5LHEwcKGHqB+Q3j9c8e+eDjNVreMFGI6rjcf+BMBg546j8hnJ5qxz065OPwy4/r+h6nmvVTV49NUn52cnfpv1vortXu7n51FyjTT3lUkui927evVrRfirq6ZUilIBDZ4bgd25YHkk546c+vcAjw79oXwPZfEj4WeLvC11A8i6hp8kZVTgthZmGCcnJ9PTIzwCPffs4UbtucY529OW5Bx3xzn1UZOKpXdjFPFIkmCsqlWGOxDKQePQ9PQkZzg1VWlGtSq0pXtONnvZXutHpdWbvvZvvqd+WYvF5VjsNjsNpWw1WlVjK9k5U5uaa17qN1ezV000tf8AOG0HRfG1/wDHaT4ELY3sNjZfH3SvEEdtPbzGRrbT/G1nP5qEt/qtkBOcYK54r/RE+F2lf2T4I8PWOzYYdNslK7doBFrbqeO2Suecngck818j6d/wT5/Z3tfiy/xbPgrRJvExleYXZs1FwJmnMvm+b5WSRIFbG4nODngg/fNlbJbWyQxoFSJERAM4CrtVQPoACPYHBI6/nvAPB+YcLLMZZhiI4mtiMROdKom3+6c6rjG7u9pLfRcuqunf+tvpXfSI4R8ecVwtDhHJKmSYPJMow+Hx1BwUI1sdChhqVWsuRuLbnQnKT10mtU9R8ePmGOhH5DJ/mQO/TjBBNSqAufc/1OMf5+pIwA5ML1zx0x65PXJ7/wA8dBmjufc/1c+vuP154yf0SLkt9bta9lt20227t66I/kO8VZ66JR1Tu0vP5306aXdkNI4I55/xPv8A17/WgAKDjOB/i/8Agf05yWyuD/kH6ev+fc809ARuBBw2ATg9vM6c/T8x+IuZN31V1rt5LRO1vW+t+rTHFuV7bLvv+b/rqNiJz3A7c9fvdgeO3X2564GI3lfpz+fv7H9BznNShApyCf8AO729/wCXocoUUknnP/6/b/OTyectc1td7rXyu2/w0+7rdlCD5M9934dPz61HtXJwc5wCcHpn0J9Of05NWAMDH0H5bv8AH+XocwMAGAxkcZPpy/8A8SMe5IyTzRZ669rb6WbbvZ63032+bYtfLpfTzd7a+nyb6rWNlwGCdSRzzyBvz1Pv0J5yOvNV3QqpyTxg9eCdzd+g5BJ9yenU2Rg/MCcfp1YdP+A/qO+aa5G1lPOcDHYct7Z5+vHB44qIyTfLy6K2traty2d7201trvd3ZjOMZRfPJpNrTXdOS69nr97VtSsYzNHtByABnHH8R6885H44BwTgV4H8ev2dfh7+0H4PuvCHxB0lNR066WSNsCFbiNXUJuhlkhkaJ8AFXX5gcYO4bj9BgCKNivGcduActjgk9cHP4dSKiw8mc7gAc9+uT29On68moxGHo4mjOhWpxqwmkmpxTi1eW97qzutFvd3Sdk+7KMyxuR5nhs2yvG18Fj8LaWHr0Kk6dSm03ZxnGSkns1Z9XrdXf56fBz/gmp+zL8Gfh5rXw58KeFpm0fW7KOx1MarPBqE1zEjoR5k81oWZv3MZJfd9eTlvw2/4Jufs1fCfx0vxG8OeHLtPEEZeOF7q8juLaKOZjuEUDWoWMDqgVgF4IwcV+hTeZmRRnHHrxy/oMjI6e+ck7eYmgMqkMCSuPp8rMQRnp1z7dhxk+a+H8otTf9nYbmoxjGmvZQtBRbs46WV733vfrdtn1T8VOP6ksyp1OMM8qf2lOpWxk5Y3FP6zUqPlnCpeq+ZcqUU5N3imtbMwbnw9bXWnzab5cclnLAsEkcyLJG0a5AUow2lQAvBHQDIySa/nd/bH/wCCZPxr0b42RfHv9knxFp3hXWt17qGuWV6lxc2N7qVxI/zrp9tfWMLL5MMQVWWQhsYYgsD/AEgiN1QqC3oeOGHzDHU+gPXuOcHNQRQ7WkDnAblgR8oOT05PucevXpkTm2S4HOsPSo42LTw3L9VqxXvQnBtRs1quivdK3No3ZnR4aeJ3Fnhfj8xzLhysp08456edYDEPmoYqhUb51WpzbjJbyvZtTtom3f8Ai/8Ajr+zn/wVH+KHgvUfiZ8RPiDY6VYfDuGfVVs9F03VdDmuB4ZRpFkdbbXlE0VwtmrkOjCQH5gwyT+3H/BH/wDaQ8QfGb9mHwofGOrR6j4n07QtPbVyGbzxPKlsP3iPJLIpLM2Q7EjHU5BP6W/G/S7bWfhR4/0S4+e21bwvrWnSKy5XbdWM8L5GOeDz3+bGRgk/zo/8EhmvPh5+0t+0N8G7R2fQ9Ev9I0/T0HyRW0SzonyRDAGfLXIx6dQMn4OOWPhni/K6lLE4mvh8zp1lj41pylatSqQjQcYyk7Jxcm9OW7imm27/ANXYzjun43/R045o5tkWTZXnHAmYZVHhKeXYWlSlPLsfQxtTM51KlOnHmlTq0KChGb5rTm1pG7/qSt3aW3V1P93nBxj58fzzjt0JJIqwpZe+TkbvQjLdRn6498856V4VEFnGufmCqM+vL9ee5HHfJbkkGnw5EZds84/9CYfrj8hnnPP6qpRc5xTs5csoK2tuZpXd/XfSytbS7/g+kqsaFFTSk4e7Vlf3uZOSe7u72Tt69Wm7QThj13fy3HHIz6e/44NNLfeUj0xzyMZGffr+eck5p3OwMp42jsPVh3/4ET17cDBqJAS5LHPH9XI6em3nr1HPy5JyK7ldKW19fe36Pta27eq1dmbSk9EteZpX8ry1tbs7/ertth168/5Pv/nJ565cykZA5+U49+Se57YHfv7GonDDccnaDjjPH3/Tr9z+YwMZpYnBz3IxnHORlh68Hrx9ecDNZcr92ScfiV297XtbV9k9NrWu3F3eF4tyg7x1SS3u09LXfdt9bPTdsRcEMT8rAjJOfVsHGe4GRn34yDmNnOcN3HXHBGW55bPYHn1GMHJL58DcA+1sdPXlh6/X3JOCflya3nwFViLjzduOnOQ0hPc598e/OATVRtGvJWSTitG7J3l9nW61S8rd2ta9jOcOaE6knBpy5It8sbu7aXVJd9NL6/EkzJHBI7cBcsSTxwXJ9cYHJHTkDJJNfyw/8FQ9cX9or9un9mb4MaUo1eHwz8QprPWrSFVuIoIbjTtdAF5ENyqhMqnEgI3OoyTyf6U/iR4qbRvC/iC5hIV7PS7u4DBgDmKGU5HzcdPXHXkYLH+bb/gn14dk+PH/AAUb/aT+JerxfbpPCGuaZqmnTSr5ps5PNsYS8chLbci4IJz0LDJ7/DcY15VKuVcNSpybzarTnKEdefDRm5VHe+tkuvRq75mf099GrA0cuwPHnjGsQo0eA8urYbD4maa9lnNROlhdb3XNUaV903bW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[[First-passage time|http://www.youtube.com/watch?v=YZUYPiDA-iQ&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=4#t=42m20.9s]]
Can also calculate using survival probabilities. See notes!!
See [[Backwards Fokker-Planck equation]]
The ''Fisher information matrix'' (FIM) is the Hessian of the $$\log$$ [[Likelihood function]].
If one [[Taylor expands|Taylor series]] the log-likelihood around a maximum, and keeps only terms up to second-order, we are approximating the peak by a Gaussian peak, and this is what is done to find the FIM
[[Intro to Fisher Matrices|https://www.youtube.com/watch?v=m62I5_ow3O8]]
The [[Covariance matrix]] is the inverse of the Fisher matrix.
$$\chi^2$$ can be calculated as $$\chi^2 = \delta F \delta^T$$, where $$F$$ is the FIM, and $$\delta$$ is a small step in parameter space from the maximum of the likelihood.
Fishing is the capture of fish, and all the related art and science
[img[https://upload.wikimedia.org/wikipedia/commons/7/72/A_Brixham_trawler.jpg]]
__[[Under-ice fishing|https://www.youtube.com/watch?v=VIs00QjiJZQ]]__
[img[https://media.giphy.com/media/26FPHxvWv0SV9Fsg8/giphy.gif]]
An approach for solving [[Reinforcement learning in continuous state space]]
[[value iteration|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=50m30s]] --> [[Fitted value iteration|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=51m14s]] approximates this for continuous state spaces. Essentially getting samples from the model, and fitting using [[Linear regression]]
[[Obtaining the optimal policy|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=1h6m40s]]
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
faster if expansion sequence is unknown (i.e. we don't know it it's a power series or a log series for instance); slower, if the expansion sequence is known.
For example to find roots of an equation we need to express it as:
$$x^* = g(x^*; \epsilon)$$
where $$x^*$$ is the solution we're looking for. Then starting from a guess $$x_0$$ (which if possible should be chosen to be the solution for $$\epsilon =0$$, so that the solution is right to order 1 at least.), then we iterate:
$$x_{n+1} = g(x_n; \epsilon)$$
and the iterations should get better if $$|g'(x^*; \epsilon)| <1$$ (prime = derivative), and $$x_0$$ is suitably chosen. However, to get asymptotic expansion we actually require $$g'(x^*; \epsilon) \rightarrow 0$$ as $$\epsilon \rightarrow 0$$. In particular, if $$g'(x^*; \epsilon) = o(\epsilon)$$, one gets one term in a power-series expansion, per iteration, as can be seen from argument in notes, where we see that the difference between true answer and answer gets multiplied by $$g'(x^*; \epsilon)$$ at every iteration. If we don't know the order of $$g'(x^*; \epsilon)$$, the way to check if the iteration is right up to some order is to try one more iteration and seeing if the term changes (Though I don't think that's definite proof).
The usual procedure is to place the dominant term of the equation on the $$x_{n+1}$$ side (i.e., the side that will give the new value), so that it can be calculated as a function of the terms on the $$x_n$$ side (i.e., the previously-obtained value). As we will see later, the identity of the dominant term can be adjusted by scaling. I think we place the dominant term of the equation on the $$x_{n+1}$$ side because that ensures we choose that term to be right to first order in the 0th iteration, and so the equation is right to first order. In the simple example of $$x = \pm \sqrt{1-\epsilon x}$$, which comes from $$x^2+\epsilon x -1 =0$$, we selected the $$x^2$$ term, if we had selected the $$\epsilon x$$, we would have to divide by $$\epsilon$$ and the $$\epsilon =0$$ case would not be well defined, indicating that we want to get the dominant term right in the equation. Another way to look at it, is __dominant balance__, by putting the dominant term on the LHS, the $$x^* = g(x^*; \epsilon)$$ approximately expresses dominant balance!
<i class="fa fa-exclamation-triangle" aria-hidden="true"></i> For the iterative method, different functions $$g$$ may be needed to find different perturbed roots of an algebraic equation, so that condition $$g'(x^*; \epsilon) \rightarrow 0$$ as $$\epsilon \rightarrow 0$$ is satisfied.
The proof that this method works is based on a [[Fixed-point theorem|https://en.wikipedia.org/wiki/Fixed-point_theorem]], in particular on the [[contraction mapping theorem|https://en.wikipedia.org/wiki/Banach_fixed-point_theorem]], also used proof [[Fractal]]s are well defined.
See more at [[Fixed-point iteration|https://en.wikipedia.org/wiki/Fixed-point_iteration]]
[img[http://www.mathsnetalevel.com/images/fixedpointiteration.gif]]
[img[https://metodepuntofijo.files.wordpress.com/2010/03/dibujo3.jpg]]
If |gradient|<1, iteration doesn't converge:
[img[http://wwwf.imperial.ac.uk/metric/metric_public/numerical_methods/iteration/fixed_point_iteration_im3.png]]
A piece of equipment or furniture that is fixed in position in a building or vehicle.
Light from excited atoms in a self-sustained exothermic chemical reaction, often [[Combustion]]
[img width=400 [https://upload.wikimedia.org/wikipedia/commons/thumb/3/3c/Et_baal.jpg/640px-Et_baal.jpg]]
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
See [[Independent paths, connectivity, and cut sets]]
!!![[Max-flow min-cut theorem]]
A ''Fluid'' is a form of matter that flows under virtually any amount of stress. See [[Condensed matter physics]].
Canonical types are:
* [[Gas]]
* [[Liquid]]
* [[Plasma]] (ionized gas)
''Fluid dynamics'' is the branch of [[Fluid mechanics]] that describes the causes of motion, i.e. the forces and torques that can affect fluids, and how these affect their motion.
The equations of fluid dynamics can be derived from the principles of [[Mechanics]] (in particular continuum mechanics). More recently they have also been derived from the microscopic statistical picture of moving and interacting particles thanks to the development of [[Kinetic theory]].
''Navier-Stokes equation''
https://en.wikipedia.org/wiki/Navier%E2%80%93Stokes_equations
Oxford course. Bachelor's book, etc.
https://www.youtube.com/watch?v=pqWwHxn6LNo&list=PL0EC6527BE871ABA3&index=2
https://en.wikipedia.org/wiki/Strain_rate_tensor
See table I made for 3rd year revision
!!__Convection-diffusion__
of heat, particles, etc.
https://en.wikipedia.org/wiki/Convection%E2%80%93diffusion_equation
http://www.cfm.brown.edu/people/gk/chap9/node1.html
''Fluid kinematics'' is the branch of [[Fluid mechanics]] that (just like kinematics, in [[Mechanics]]) describes the possible motion of fluids.
Flow can be decomposed into:
* translation
* rotation
* strain
Pure shear is a combination of rotation and strain.
[[Kevin's circulation theorem]]
The branch of [[Mechanics]] that deals with the motion and the forces that affect ''fluids''
A ''fluid'' is a piece of matter that has no, or negligible, [[elasticity|Viscosity and elasticity]]. This means it flows under virtually any applied force.
There are three main [[phases|Phase transition]] of matter that are fluid:
* ''Liquid''. Fully homogeneous/isotropic [[condensed|Condensed matter physics]] phase composed of atoms.
* ''Gas''. Fully homogeneous/isotropic [[non-condensed|Condensed matter physics]] phase composed of atoms.
* ''Plasma''. Fully homogeneous/isotropic [[non-condensed|Condensed matter physics]] phase composed of ionized atoms and/or other charged particles. See [[Plasma physics]].
More complex fluid phases, often composed of mixtures are called [[complex fluids|Complex fluid dynamics]].
[[Fluid dynamics]] describes the causes of motion, i.e. the forces and torques that can affect fluids, and how these affect their motion.
[[Magnetohydrodynamics]] and [[Electrohydrodynamics]] describe the dynamics of an electrically conductive fluid.
[[Fluid kinematics]] (just like kinematics, in [[Mechanics]]) describes the possible motion of fluids.
https://www.wikiwand.com/en/Fluorophore
[[Foam|https://en.wikipedia.org/wiki/Foam]] is a substance that is formed by trapping pockets of gas in a liquid or solid, where the concentration of the gas phase is high (i.e. it occupies the majority of the volume).
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[[Deriving FP eq from Langevin equation|http://www.youtube.com/watch?v=m5RuNNvJdjM&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=6#t=1h13m45s]]. Fokker-Planck equation works for Markov processes in space, so it is derived from the [[Langevin equation]] that ignores inertia.
$$\partial_t P(\vec{r},t)+\vec{\nabla}\cdot[\vec{v}(\vec{r})P(\vec{r},t)-D\vec{\nabla}P(\vec{r},t)] = 0$$
where:
[img[Fokker_Planck.png]]
__Detailed balance and equilibrium__
Setting $$\partial_t P(\vec{r},t) = 0$$ __and__ $$\vec{J}=0$$, and using __Einstein's relation__, we get [[Boltzmann Distribution]].
__N-non-interacting particles__
We get Smoluchowski equation.
__N interacting particles__
We get [[BBGKY hierarchy]], as in [[Kinetic theory]]
__[[Backwards Fokker-Planck equation]]__ Tells you how likely different initial conditions is to arrive at a certain fixed point in the future.
!!Applications of Fokker-Planck equation
__[[First-passage time]]__ Calculation of the mean time required to leave a region.
__[[Kramers rate theory]]__ The rate at which fluctuations push particles over a barrier.
[[Survival probability|http://www.youtube.com/watch?v=YZUYPiDA-iQ&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=4#t=3m36s]]
[[Crucial argument: reflecting parts of the trajectory leaves same probability|http://www.youtube.com/watch?v=YZUYPiDA-iQ&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=4#t=20m30s]] See also [[here for nice derivation from boundary conditions|https://www.youtube.com/watch?v=m5RuNNvJdjM&index=6&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=0m30s]]
[img[Selection_194.png]]
__Stationary solution of 1D FP equation__
<div id="stat1dfp">
[img width=300 class=img-centered [Stationary_solution_to_FP_eq.png]]
</div>
__[[Brownian ratchets]]__
Assume a periodic potential $$U(x)$$ with a bias:
$$V(x)=U(x)-Fx$$
and assume the solution is periodic:
$$P(x+L)=P(x)$$
This is not the equilibrium solution <small>(which would be an exponential growing P to compensate bias, just as the exponential growth of density in gravity or constant electric field)</small>. Therefore $$J \neq 0$$ even though it is stationary $$\partial_t P=0$$. If we integrate <a href="http://kosmos.tiddlyspot.com#stat1dfp">this</a> from $$0$$ to $$L$$ taking this periodicity into account:
[img[tilting_ratchet1.png]]
The easiest way to calculate escape time from one well to the next is to assume there is one particle per well:
[img[tilting_ratchet2.png]]
The average drift velocity is $$v_{drift} \equiv \frac{L}{T_{esc}}=JL$$.
__Fluctuation-driver transport__
Analogous to AC rectification in diodes!
!!__Mathematical properties of FP eq__
__Quantum mechanical analogy__
See [[video|http://www.youtube.com/watch?v=YZUYPiDA-iQ&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=4#t=61m28s]], and the lecture notes!
Also applicable in [[Path integrals for stochastic processes]]
[[Stochastic quantization and path integral formulation of Fokker-Planck equation|http://www.sciencedirect.com/science/article/pii/0375960178902918]]
[img[https://media.giphy.com/media/4ZXsRRZzacnBe/giphy.gif]]
!!__[[Food innovation]]__
https://en.wikipedia.org/wiki/Molecular_gastronomy
http://genomicgastronomy.com/about/
[[Staple food]]
3D printed food.
[[Stigler diet]]
//includes shoes//
https://www.wikiwand.com/en/Footwear
!!__Footwear innovation__
[[skinners|https://www.indiegogo.com/projects/skinners-revolutionary-ultraportable-footwear-shoes-design#/?ref=backercamp&utm_medium=referral&utm_source=17.backer.camp]]
//aka Forensic science//
-------------
https://www.wikiwand.com/en/Forensic_science
See [[Formal language]]
!!!__Formal grammar__
Defined by either:
* variables, terminals, production rules, and starting symbols. See [[Formal language]].
* an [[automaton|Automata theory]].
[[Ambiguous grammar|https://www.youtube.com/watch?v=WccZQSERfCM#t=11m10s]] is one in which a given string in its language has more than one valid derivation/parse tree. The problem of knowing whether a grammar is ambiguous or not is [[Undecidable]]
[[Parsing expression grammar|https://www.wikiwand.com/en/Parsing_expression_grammar]] are a class of grammars, similar to [[Context-free grammar]]s, but that cannot be ambiguous. It is conjectured that there exist context-free languages that cannot be parsed by a PEG, but this is not yet proven.[1] PEGs are well-suited to parsing computer languages.
[img[http://i.imgur.com/gcQfgpD.jpg]]
[[Grammar learning]]
A [[formal language|https://en.wikipedia.org/wiki/Formal_language]] //is a set of strings of symbols// that may be constrained by rules that are specific to it.
$$\Sigma^*$$ is the set of strings formed by symbols in the set $$\Sigma$$.
Relations to [[compilers|Compiler]], [[parsers|Parsing]], etc. [[Grammar]]s, etc.
A nice new language for this: [[Ohm|https://github.com/cdglabs/ohm#readme]]
See [[Automata theory]], [[Grammar]].
''Chomsky hierarchy''. (see also [[Theory of computation]]).
[[Mathematics - Formal Languages and Automata Theory|https://www.youtube.com/playlist?list=PLbMVogVj5nJSMghTc2Qu0tk-lwY4ui7iY]]
[img[http://i.imgur.com/xDA0gCo.png]]
[img[http://i.imgur.com/hBuur1g.png]]
[img[http://i.imgur.com/K5o8OyH.png]]
[img[http://i.imgur.com/pD2JOER.png]]
__Probabilistic languages and grammars__
See paper on algorithmic probability by Solomonoff.
A ''Formal system'' is a [[Set]] of rules you can apply to a set of objects.
[[Formal language]]
https://en.wikipedia.org/wiki/Formal_grammar
[[Formal systems and semantics]]
MU-puzzle
!!__Rewrite systems__
The most common type of formal system. (Are there other types actually?)
__(Abstract) Rewrite systems__
A set of objects, and a binary operation, $$\rightarrow$$, that tells us how we are allowed to transforms expressions. If these rules act on //terms// out of which an expression can be built, then this is a term rewrite system.
They are non-deterministic Markov algorithms, and they are Turing complete. They are related to normal forms, lambda calculus, and combinatory logic
[ext[http://www.cs.tau.ac.il/~nachum/papers/survey-draft.pdf]]
Initial strings in a formal theorem are called //axioms//, while any string producible by its rules are konwn as //theorem//s.
The rules themselves are knwon as production rules or rules of inference.
A series of production rules that leads to a theorem is known as a derivation of that theorem.
!!!__Decision procedure and [[Decidability|Decidable]]__
A ''decision procedure'' is a [[Computable]] procedure (i.e. one that is guaranteed to finish in a finite amount of time) that determines whether a theorem will be reached by the production rules of the formal system, or not.
A theorem is [[Decidable]] if it has a decision procedure for it.
The axioms must always be decidable. Their decision procedure is often in the form of an //axiom schema//, with substitutable variables which are clearly defined.
Formal systems with only //lengthening// rules always have a decision procedure for all strings. See page 48 of GEB.
See [[Computability theory]]
''Languages'', ''grammars'', etc.
[[Chomsky hierarchy|https://www.youtube.com/watch?v=224plb3bCog]]
See [[Theory of computation]]
[[Formal system]]
[[CM20019—Computation III: Formal Logic and Semantics|http://cs.bath.ac.uk/ag/CM20019/index.html]]
[[Semantics]] -- the study of [[Meaning]]. Hofstadter argues that meaning is a [[Morphism]] (often an [[Isomorphism]]) between a [[language|Formal language]] (produced by a [[Formal system]]) and another space. The mapping itself is known as an interpretation.
''Meaningfull'' interpretations are those where there is an identifications between the theorems and non-theorems of the [[Formal system]], and a pair of sets that correspond to some aspects of [[Reality]], for instance a set of true and false statements. See page 51 of [[GEB|Godel, Escher, Bach]]. An interpretation is otherwise known as //meaningless//.
//symbols of a formal system, though initally without meaning, cannot avoid taking on "meaning" of sorts, at least if an isomorphism is found.// However, unlike [[Natural language]] and other non-[[Formal system]]s, we can't add new rules or axioms because the meaning we have found; by definition of //formality//, the rules are fixed. To distinguish these we call these active and passive [[Meaning]]s
https://www.wikiwand.com/en/F%C3%B6rster_resonance_energy_transfer
[[Draw solutions for forward osmosis processes: Developments, challenges, and prospects for the future|http://sci-hub.cc/10.1016/j.memsci.2013.03.046]]
[[Relating performance of thin-film composite forward osmosis membranes to support layer formation and structure|http://www.sciencedirect.com/science/article/pii/S0376738810008677]]
[[Forward osmosis: Principles, applications, and recent developments|http://sci-hub.cc/10.1016/j.memsci.2006.05.048]]
See [[Complex systems]]. Related to [[Discrete dynamical system]], and [[Symbolic dynamics]]
[[Synopsis: Fractals for Sharper Vision|https://physics.aps.org/synopsis-for/10.1103/PhysRevB.93.180201]] See [[Limits and infinity]]
[[Lecture Notes on Fractals, Iterated Function Systems, and Related Topics (updated, 5/02/16)|http://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3217/5/0Intro_and_1Fractals-map-mode-updated_copy.pdf]]
[[Hausdorff dimension|http://mathworld.wolfram.com/CapacityDimension.html]]
!!__Iterated function system__
See [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3217/5/0Intro_and_1Fractals-map-mode-updated_copy.pdf]]
[[Iterated function systems and the code space|http://www.sciencedirect.com/science/article/pii/S0166864101001341]]
[[Codes as fractals and noncommutative spaces|http://link.springer.com/article/10.1007/s11786-012-0114-9]]
------------
[[Apollonian gasket]]
Coasts are fractals. Here's a perfect fractal coast
[img[https://media.giphy.com/media/wv0xhsG4tt3xe/giphy.gif]]
Fractional distillation is the separation of a mixture into its component parts, or fractions, separating chemical compounds by their boiling point by heating them to a temperature at which one or more fractions of the compound will vaporize. It uses [[Distillation]] to [[fractionate|Fractionation]].
https://www.wikiwand.com/en/Fractional_distillation
For many cases, the boiling points of the components in the mixture will be sufficiently close that Raoult's law must be taken into consideration. Therefore, fractional distillation must be used in order to separate the components by repeated vaporization-condensation cycles within a packed fractionating column. This separation, by successive distillations, is also referred to as rectification.
https://www.wikiwand.com/en/Distillation#/Fractional_distillation
This is used to separate [[Crude oil]] into useful liquids that have different boiling points. Petrol and diesel are useful fractions of crude oil.
!!![[Fractional distillation of crude oil|http://www.bbc.co.uk/education/guides/zm2v4wx/revision/1]]
[[Cracking|http://www.bbc.co.uk/education/guides/zm2v4wx/revision/2]]
Fractionation is a separation process in which a certain quantity of a mixture (gas, solid, liquid, enzymes, suspension, or isotope) is divided during a phase transition, into a number of smaller quantities (fractions) in which the composition varies according to a gradient.
https://www.wikiwand.com/en/Fractionation
Stroke volume $$\propto$$ preload
__Twilight in the Wilderness__
[img[https://upload.wikimedia.org/wikipedia/commons/9/98/Twilight_in_the_Wilderness_by_Frederic_Edwin_Church_(3).jpg]]
__Oil Study of Cotopaxi__
[img[https://upload.wikimedia.org/wikipedia/commons/a/af/Oil_Study_of_Cotopaxi_Frederic_Edwin_Church.jpg]]
__Above the clouds__
[img[http://hamiltonauctiongalleries.com/Church-Above-the-Clouds.jpg]]
__The icebergs__
[img[https://upload.wikimedia.org/wikipedia/commons/4/44/Frederic_Edwin_Church_The_Icebergs.jpg]]
__Aurora Borealis__
[img[http://theredlist.com/media/database/fine_arts/arthistory/painting/xix/hudson-river-school/frederic-edwin-church/021-frederic-edwin-church-theredlist.jpg]]
__River__
[img[http://www.artcyclopedia.org/art/frederic-edwin-church-river.jpg]]
__more__
http://www.wikiart.org/en/frederic-edwin-church/morning-in-the-tropics-ca-1858?utm_source=returned&utm_medium=referral&utm_campaign=referral
http://www.umsu.de/wo/2013/600
[[A free energy principle for the brain|http://www.sciencedirect.com/science/article/pii/S092842570600060X]] -- [[pdf|http://sci-hub.bz/10.1016/j.jphysparis.2006.10.001]]
https://www.wikiwand.com/en/Free_energy_principle
The free energy principle states that systems change to
decrease their free energy. The concept of free-energy arises
in many contexts, especially physics and statistics. In thermodynamics,
free energy is a measure of the amount of
work that can be extracted from a system, and is useful
in engineering applications. It is the difference between
the energy and the entropy of a system. Free-energy also
plays a central role in statistics, where, borrowing from statistical
thermodynamics; approximate inference by variational
free energy minimization (also known as
variational Bayes, or ensemble learning) has maximum
likelihood and maximum a posteriori methods as special
cases. It is this sort of free energy, which is a measure of
statistical probability distributions; we apply to the
exchange of biological systems with the world. The implication
is that these systems make implicit inferences about
their surroundings.
[[Karl Friston talk|https://www.youtube.com/watch?v=zWFfZHqOnvM]]. Systems that have certain measurable characteristics which persist in time, and are thus ergodic in this certain weak sense. This implies the existence of a random global attractor ([[Ergodic theorem]]).
[ext[Free Energy, Value, and Attractors|http://www.fil.ion.ucl.ac.uk/~karl/Free%20Energy%20Value%20and%20Attractors.pdf]]
__Universal Lyapunov function?__
|$$\dot{x} = f(x) + \omega$$ |Steady state: $$f(x)=(\Gamma + Q) \nabla \ln p$$| Lyapunov function: $$-\ln p$$|
$$\omega$$ are random fluctuations, $$f(x)$$ is deterministic flow. $$p$$ is steady state probability. In short, this equation rep-resents “a simple starting point for statistical mechanics and thermodynamics and is consistent with conservative dynam-ics that dominates the physical sciences”. See below for details and derivations.
__Surprisal is a [[Lyapunov function]] of the [[Fokker-Planck equation]]__
See [[Surprisal as a Lyapunov function in stochastic dynamics]]
Flow can be decomposed into a curl-free part increases value while the (con-servative) divergence-free part follows isoprobability con-tours and does not change value. This means every policy (expec-ted flow) reduces surprise as a function of time. In other words, it must direct flow towards states that are more probable (in the steady state), and have a greater sojourn time. This just describes how systems approach the steady state. They do so by uniformly increasing their steady state probability. This corresponds to a decrease in [[Entropy]]. However, the fluctuation due to $$\omega$$ causes a corresponding increase in that means that in steady state entropy is constant, as expected.
---------------------
[ext[Free Energy, Value, and Attractors|http://www.fil.ion.ucl.ac.uk/~karl/Free%20Energy%20Value%20and%20Attractors.pdf]]. ,,We will compare and contrast two perspectives; one based upon a free energy principle [1] and the other on opti-mal control and reinforcement-learning [2–5]. policies can be cast as beliefs about the state-transitions that determine free energy.,,
The main conclusion of this paper is that it is sufficient to minimise the average surprise (conditional entropy) of an agent’s states to explain adaptive behaviour. This can be achieved by policies or empirical priors (equations of motion) that guide action and induce random attractors in its state-space. These attract agents to (low-cost) invariant sets of states and lead to autopoietic and ergodic behaviour.
[[Active inference]]. connection between empirical priors and policies.
-----------------
!![[A free energy principle for the brain|http://www.sciencedirect.com/science/article/pii/S092842570600060X]]
The system can minimise free energy by changing its con-
figuration to affect the way it samples the environment or change the distribution it encodes. These changes correspond to action and
perception respectively and lead to an adaptive exchange with the environment that is characteristic of biological systems.
See [[Philosophy]], [[Science and Art]]
There is something
quite remarkable about the fact that our inferences about
the world, both perceptual and scientific, can be applied
to the very process of making those inferences ([[Strange loop]])
[[Hierarchical inference]]
!!!__Mathematical description__
//Ensemble density//: $$q(\theta;\lambda)$$.
This is some arbitrary density function on the environments
parameters that is specified or encoded by the
systems parameters ($$\lambda$$)
two other sets of variables that
describe, respectively, the effect of the environment on
the system and the effect of the system on the environment.
We will denote these as $$\tilde{y}$$ and $$\alpha$$, respectively.
We also need to define a generative density $$p(\tilde{y}, \theta)$$, which defines a [[Generative model]] of sensory inputs and causes.
See more [[in paper|http://sci-hub.bz/10.1016/j.jphysparis.2006.10.001]] <mark>What is the meaning of this definition of free energy?</mark> It is a [[Kullback-Leibler divergence|Relative entropy]]
The free energy principle states that all the quantities
that can change; i.e., that are owned by the system ($$\lambda$$, and $$\alpha$$), will change to minimise free energy.
Minimizing w.r.t system parameters results in //perception//: it results in the ensemble density to correspond to the [[A posteriori distribution]] of the causes given for the given sensory input.
Mininmizing w.r.t action parameters results in //action//: it enforces a sampling of the environment that is consistent with the ensemble density. In other words, the system will reconfigure itself
to sample sensory inputs that are the most likely
under the ensemble density.
:There are at least two fundamental problems with the simple picture just outlined. One is that it makes little sense without postulating an independent source of goals or desires. Suppose it's true that I reach out for the pizza because I hallucinate (as it were) that that's what I'm doing, and I try to turn this hallucination into reality. Where does the hallucination come from? Surely it's not just a technical glitch in my perceptual system. Otherwise it would be a miraculous coincidence that I mostly hallucinate pleasant and fitness-increasing states. Some further part of my cognitive architecture must trigger the hallucinations that cause me to act. (If there's no such source, the much discussed "dark room problem" arises: why don't we efficiently minimize sensory surprise (and thereby free energy) by sitting still in a dark room until we die?)
:The second problem is that efficient action requires keeping track of both the actual state and the goal state. If I want to reach out for the pizza, I'd better know where my arms are, where the pizza is, what's in between the two, and so on. If my internal representation of the world falsely says that the pizza is already in my mouth, it's hard to explain how I manage to grab it from the plate.
See [[here|http://www.umsu.de/wo/2013/600]]
:->A closer look at Friston's papers suggests that the above rough proposal isn't quite what he has in mind. Recall that minimizing free energy can be seen as an approximate method for bringing one probability function Q close to another function P. If we think of Q as representing the system's beliefs about the present state, and P as a representation of its goals, then we have the required two components for explaining action. What's unusual is only that the goals are represented by a probability function, rather than (say) a utility function.
That version of the story looks much more plausible, and much less revolutionary, than the story outlined above. In the present version, perception and action are not two means to the same end -- minimizing free energy. The free energy that's minimized in perception is a completely different quantity than the free energy that's minimized in action. What's true is that both tasks involve mathematically similar optimization problems. But that isn't too surprising given the well-known mathematical and computational parallels between conditionalizing and maximizing expected utility.
----------------
[img[http://d10k7sivr61qqr.cloudfront.net/content/royinterface/10/86/20130475/F1.large.jpg]]
Applications to [[Neuroscience]], [[Self-organization]], [[Intelligence]], [[Reinforcement learning]]
[ext[http://www.fil.ion.ucl.ac.uk/~karl/]]
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+ZzIitvYhHVMFU5SMQ++jOFwQ4q/tRrg05knlWNGo9FIPLh1NnbNfOylcUxRtIXL52yrsH4v1pXsG5Dz+CyPXUv2nvJdC8OYLMeXy+eIW6b39x617OLyOeKWoW9rUw/kX9RYlKwwY4JR77ckBPjt+Bi1IQg/5kvd9O+b4eIx9Gzx58oHl5O9uX6xR3MyP0fHjEbjmHmairfxOdEW529cc2o7n8ONaTIrPuLGX0I46zM6H1m/KP8NLp8TPEHMoc9ivVfusvE9dPW7J4RoTHE692T3kKJiiy0TGo1jstKta0KOWkn9CL2tIWb07FNFnOCiG99PiGqsYDJVZ6LS4NmjZd13r+X4cvlbP0YfXC5NOHj6BmY0amp32I5nTHn0Tb+Y85iF8zXYuNGIXSv7r9obmr7M9VNcbawzjs/h7rKIOXG7LKP4a83tshAOlx/79YQRPbWdz4m0ivAUzkBP7fbzjpsQ1bsnwzlcvu/hvjErGSP5U0X+MctXHxfgHV07MRcnwzncgMxZGHh2Yt5vyT1ce1vTHSuYNMVj15K9uQGpXZhxTHnqv07fGGyPXcnnRLc80LTnHsio/5YwjiuPivicN208mKcY21PhueRjRzpKylQA4BQQYIr2EaZ5CWWoW64DgCUI1Ryds4J2+jMdARwYb273Mt/uFf6uLx0AEHdR2ApzYkWPWTIYT32vA+LiSgNgBG13Nw2KRjfnqRZnj67jcmRR9jwYMN0oINNsMCd7Tp5S4Mrj0aEhO6LC3xGL30usGvHyWev/Jst8MfIrCgAwt8WGraAAwvAJ4Do5AOCq5l4ARxbbWk/I5Ls7AgxcNmeoBuoK20lYEfKmbQbYOWDfBgqA9qMKUxcVUnEyt2GYsi46cLY6Nwcq25s/ZbkMPZ1Zo3WPDmVNWvs1F3g+nmJtzTsuB/auaM/Z1qd07cVVg1jXkSjRWxHhO8VRe+MSz4KPrzB4zaum20wbXWgsPtu6CER1D/IEAGzImiYbJQC0nx6vQ0cBAJAVUdliUzk0xcmdy3tpfuvbK0L+H1cAtLHNvD0U76n9hrlzl8/jZRQUOg0w3ejirQyplBiAi5fbtOtcxN+uowBOdNXxUvxf81I2MQBGv1NqAFYILZUyeNuRnLbxwPTtLACAEWl5mZK9LSc7cNqlphkvRlih8dvdSNV3BJCKwdf3b2MhlnV/XHLiIxR4EQHmbR4OFBoFAMw1dERvUVKVlhefYN00hbzEogPAqJ4YN3FmZWyelPleTqSVd0ZVnQMArgJTHRbiHpUuFtLUkiEAjwB382cRquNplRpB4n4vCwstZXkwpmcnzdmsxBaIPBzLs8wXMShRELZUnZlKL4ce3CdElHIM6H+Ac3mtrOQjUTwq4KgUBWCvsYilVtI5TMoaWlHCxPkMqgMAVbAvLZxnkMtGAPHyY090XtD2DAA4CyzVvxSPfTnxGxgubiwAwHCLqtK2N2vc4vOimNMJI/pRamEf/d3EUKuoOrHoAEA8IqxvUQwDIK96LJ95VagiMat7+YGscEvVIa7oVQO4+cy8jXIOYjqL0rPCPZwZPGebKQZcVn+TFpidvpYKiFt0WpQHJlcYwIWjLz8iXZ+VE7aCAo/UMi0g7kJLmffTjO3p8Dx2seG3WkwLCbqqqFVVtsqU4sKi/3KG4hfKr36DAEyyXGbpmrtwZl73Im77Tn21zwDgQKKXqquqPmnoXXi5NqbTWx7CdHdZnAIokjQAQnnMmhDK5m4M3DNqPwudfZOZk/Nk/WnACQMAgZPWZSEHhEYBMPyG6gAAoLneMQQAziz6pPFT2Bvc4YKc6LuOEkIPUDe06KdsepsXixGqhrNaoAuZ8yte0HXX9RCAuLnRZyMmrmzpAxAU1Zeum+mx09yOUKiTBu+0IWr9sczOSwUhGxvDklIObLcteUfmK3kOrOBtrPISdcNF9b59LNBLapSv789mTUcZxDS5i1UfgPaqAYDNpc9iTaEXDzpjbnlBoFKFAVx8LZZAXVfSTtKCt3g46GVnPymvVTHF1XXbWNP7MXNcjCukagD6pv2BNhqcvPvVTQJobOtSI/EQ1QOs8POgAoC+rbxOB9wDG2zGbwACAJYxaEsAQN/85wrUgZsdNjEkoq/12ijQOG40GzrcvqQEYG3ypFp8qRM1WopPGn9ujsMlx49JgZ0QbbWsQKIXOnRAWW+l6pwfLlEDQI9keWmxiOkAAORQ900CGOusT3B+3ccZaq4UhOxS5R9Lsd2rjd+6jALwNtjQHFf2DAOs5U/ZAkShM5wAsEc4ABUA7/qwDvYUvTsdl5mq68E1Npht8+M4AQA0poVsP2gVegA2d8aNRvr2wpNq8M3Zbn0FLm/qBXB9fcZtlPMhJgA40JnLAPR6c68udWNh3+vpNRMdb/T9Uh0AfCX3qCgwVYcQA+0KAPZaC9/OY2zEiB6bHAXR6PSnKFB9HvYSu/Odaai8I+3VgT+mKmKDXlZfefxkXc+IW1hqdhE9MfHCwkzmqPqapekML/D1RfpUCs0BiB8ei3l/0KIjAI5a3ABPtpOJ6raeDTL0ZrOSXCegmKonFCOABAT+wREASOxv0xcq0ZYvRwAIAicA4Ae1Qg8AFORJHbgftLJhAOo86UzqlVoAQBxnrUIw4HfvkQDY0OjCurk4i46dgby0nAalqiFP3HA6NL8sI+jJq5LZm0PYJcXolx2omEW9VKfbkDB9l4lxnAAKBVk0ZlaoSADWajZ1emsqVQPQw/ISrCVp+hvXdUALXmmO/9H2VhQAUZ2K+/flHgHhh08nzMJXc1xMaGUDAIyQSPdJ/IHjYwCgxwmTm4tLqxuGacHpoUxr2sOZa6t/CZ1KD0DjcOkOAMMdVVdI8Aqxjh8M2obyVgyAJ7AxMAZ1Tx8JdL7Pv1gKjxolBLitm0d1KS6tu4iDyzvCCRuvl5TV6m2pOteHqzsVAIjwwGFLNyuDvue6HqgiH2uaxVGQXlUASSk1ysbUUKXmdOU+jjmzdbtbBcDa5EW3ed51DQB7zdTdFwiNQQUgRwgAIJTVJWpRdtb0ng0xcL4TB8T3ddvQU/edHoDiYSmSIu6r9ADIq6yZvFJdd10nAbzgCZ9D113XNQoIa8ZtlPMhpulT6Msp0Pd30gAA+uaSc8yk0k1LbYrUutUAtOC0TEtfLRKVTPI/5h4bIS/cLq6xrYRyEBZdKtr05LriGdvLEbVi1OrDACpVE4HcH8tWaYO25v3wvCskOAjSG0sjXyZ7ri64PrH/XKfJ1lBF+zcuUsE0QmcsBUyPT98eSyuR6WPZzk/yQAdWZGZU057qpj+dCPrvhHXL9G0llQq6f36aPxUAgIL8mgIAMKzVG2BSesfkANIYtCUADqYcGo7qSaA/edIDVyoeAm8+pgihAAA2+HCO7mAOAKDu6scjnRfkpSAsUfZnAdEtRamH6hSDjakHX+Wdnj7HNRsYAWErigsHGtsG/CmNRHDm9DxPjugxoLsslgM5qr6mAXCcIaVm0PQpSVgqDJvYB4srutUA3HXmjRg4ekUNQA9Kzc8WzDmmuS4eUfYMA7KZP5l0FPcAL7gk7alp1/mG0rSNefmq1eknD5u6cOhVKGHhLmtCr0eKAS042B0B0F1pVQA4rXS36BNSUVHQcB8AGKttrYle3qUFJMCSrDMZMIf50BmXfSklgMKzOBBgUNfkV6MGAKqbhapzffgDuWwEaNtigqwiiau6UABv4R9sE/IM//Qzjby03akXVCWFLW+dCnUCAIOmpxcD+haLpQcA0MhVGNA2Pb77gkqnAWi+JwmDuiZfsi69cqZmk9gdJQbgxKDZRouybi04CMIs7aVIrWoIgO01Qy4B8L5WOQBj9WuWYWhb/1wuJQDYM26jnA8xLY64Mw2AwAyAXyoug5iKzXRbx6uznwTXqH3WPiEGveyqHhz9fVznPbYljKCsAh/bRA711XVPJXeLsH5JWMbxWAREykrikurVdEu2BDtb3HDvxxJbEgN15VdIAAC23/rJinu22Mdg+crxx64yqGuOtWIAALRNWQnrlgIY9G3HEsN3iNNOq55+b4kD/XcvAQyrp/YW/xWL5wwAqvIzqiddb6V6J3zyWYLP/erEnRHi+Nw2Zsq5LwusEs5cw6UBANqhmDxobFhLADit4TMdABxf9XEFAG3bRc2TvZ366mpXAFB99Nl8hk1xMcmwvLFnZDYSebxGAyA7TzZqnjq9adB31XboDABAYQem1J3N8EEA+jtkc87c4290YLwZygLQ1lScaKCEBrFnUGSDWgC6x0uLtMRyX44SMON+c/y7Hg2Ah3BiUz+h7hwAcBV6LDP/N4bD46E8gU8rDXNcTKCSSSt21oz31oyiCDfozvUPiEo6iQeVVhdFmK8x5y0MOGEjUE1faMF9zz5vCgCp79cCAN11OWLOshaVQWgQDcCBtZJp64lJUACPDZZkHflQMzK/uMCAK74jAeiMpWYHoqf0hCYgxGkcwJVv6VMxx4fjiqkJVWKgXWEA9trH+nU4MIJyS/e5AoySkyw9V2iTFMVRqRrgVR82BQw4qrQJkShUGgIEjmnqjzZzU/ZzZuQi0vT8URtp03bU9IHTzom0h+6OBmbZE2nep0R1MbHKiKTwmGp1IAuAwnajL4CY5i9BnKgABKaTlpTh0WmTWxg+lMv0QPO2CVJxVRsK4B5gfsh8xuZA523w3xRg8ydgPV3YtnB7SYK19AYnJ8nWcPvxJozJYSDcKHMobZDnhUakVbR29cp72htLkqPEFWqT7SFnUUPTacCJyX/qe61VPQOtzUocCA1qXnrEdLMcr0FYbvtBjxsmadu2vMTCfgCg+KSdzN9MBwDiSkFqlUQxIG8qzKxRPzWFqR5rWTB4HZ1SGIK4hb3NAoChqrik03Lc6tadLq6xbpSc3njgiqYTqf9R53S45ZsLtRUfFB2J87flYMQ7Zp87gEFa9qXt9kP9tRYVOHD3vcNFAMCBFbSbCwBDJzPLbPbck/jfZ6IdYYlut5turIpLPS230lB36UTe6WnO2aCuiQmjAxCSrLzGCcs8jmNjth9I4UVucQKA/mJxVqOVULruykLrdlLDDE4dAIxb4pX6ovI+C+mcBetcARyXTw2eJxZ9TaHvQ+X9aRiQ+UYIG0B3QeISIZohPMXRXg2whRPpR1xa+LbQc624XPk0iwK6/utDAIjr9PvNCY0UNYCLt01nH+112QjQOG5Ib115kxYAoS0DAH3PVc0En9TnppZN21Fhjos1N1QE0HnutMc9iU17xGFe3INVlaWHo9bZLN0hy16lA4BGrrFO35dHPxp2iz8cYSriwEZJq2XStBQcusJNjviNbBDgFS79fkd5henV5N1LNwlgrGaqq9JTyvtJcPgNFQEg1DcGLbZc21GYdmI6NwgfGwMAEidJMOi7jmV+4Ry731WFGsCJw8CvVJdfmJNK5N2rKgDW6hUTZNZclWNA43GIrqrKtmEAvbSmRmL26pDlv6PTeNuFTmZL34ECsH2pPaUpabXqCWOwlMUEbfPRgjbcRsk7UOm/Akx9Lq/p1fT9syXtaK4MANCp1JhlwF0lHyoY4Uf2W9v9kxqFHuDV1TO2fCAwAgBIjATQduSld3gkxTAH1ABM3kv6rqrKrpGnI6ZFxpdSAB72lBZrtqeETU6V4QMSFIBtc4gFgbYrDODiy9JfqCy/gj/V2J4eC87Hjqq7bli8HmVdfTdj/StUZBzXqeUNZQU9BCt+BRUQtwPHYmXvnJARAAZ1U0lmk4lbfFPqolgm2zNk/ipcoyOBQQEAbPihWbc9siQGiYdDj8yuuWaYAJNL9bT3Iu6hb7HrylEAUJXsDCijMjxeophiy560gFUVUdWfJDyW4sBl3Tct5lZaVtVB3+pGG9Ojckl9dWUbCsAWHcxMibZmOUir8cAxgpxUmoRrzew7+lA/CjBrDyr2en+Xks8vouQ6r0kMzY7KP9gdVdiLdRaK3zjj5uNOx+6oMGH2JyvMl2EjGABgemLSsp5Bf7GssnMQkOOpWDuDbkqsUqgu7n5BgQKmI4ADK/pYjmx3ZlthYqFr0YHHQvXxAAAgAElEQVQNDARItL4gT84KO5Jv7b7G3J6TLxWnXlCV7912LTBkNRv0AypUowIA4sonx6u+420I3cSiwCiOAcDoQ2LcXHTD3J6TfWV3VjvWVihuO+3mw6HDPRVKDT/2wXROnyM3/i8xsj2Vigu5W5QdYZu59O/VyjtadBgA1A0fVoLg9aCtAiev2GPR16Oq1ENNuSHtlTxvN9ojlWJJaOmHlkUP/CEBQIz83SavS+A4CQC4aTnNgcqmakuSMjyqcsNYFNBK2gYpvAOW0r5xXP+95Voz6DwBHZT6puwcdzGXVGrZexI2OU9OyeoC3107Q96HUHfKSZfgCceZUJ5rUJIA8oYW9bvuT3h0iUHbViufZaEX65frgLLe5gQPXH0dBYDu3ESH9/LTGQDgJRLAFSlaEhf3KJwH6h6pCtmYkX9w2kaG1Fkv1iuuagG4POfH9a++IS2lpg9cqlrWp4ZOijOchdG+kHpFcrRKzovjjl07kVZBRJYU7TOvgFJcViwHwNCTmYlXCZyTUJQuoN6rRkcB0E+S/hSSfiSBakrW3cAAsPK0U/FH8/dxKADuwWsobZe05e+n4NvdEM3NnnuM6LyUaQ75cVj+u5cAtPqG7BQNgjOj8o9spuNNKh0ANGWlGhLyU+eikuntjqts8o16mVQLAG3pmRBfkO5MyvKy8mr1hV+GHojgI3daG5yTS7ebWJQcuqIiABSFmU1JBfkRLAAAAzaEA4y2JO1WB6UWHZyUAUZoCED/debJWp7j7Mmk8GCqpKnvw+OXhOlrEfRMZp7aP78ixYc6oRDu3iOBwZ2xcmcJ1YUGMKI+Hh/VQOXG/yVj0zJt+R0SQP1pWu6m/dkHlz4lMU34JRUB0Lc9jDm/bcoKjYkmdN5rE46X5oYKA8A+ScnblnIsngrw5GNbABz++Mc/PnVkKTsSGZRYefl/W374P9rLf22oOfNp9acNDeclCj3A0g0H3lv/0hJYQl8ZFMKhjeKjxP/cf0QgztzQ2EPH0950+WcSLd8XFPeR4v+YrcetL1pH/YNfahCHFt42WFaJqy8Z/N+E4+HiarNTYvjb+Y9a//eqlcrMkKe8d02YP0fozxlXywc0hNP6dw8V/9fBUM6jby7fwhib3vvj/8oOZ0/WPERfQdhbqR/dsEZ5hvvfXKw782l149d9wwaXVaHilJz8hGD+byduQ5xfW3K7s2donL0tJSvM7demYB6XpO3Yk1raft8Shrd9/FH1hf/PM2S9yz/PQOmlzPH2j87hwsj1zpMcnCXLeIGBr/9qRP8/o4/U3307usx/b07RPq4jAAy35qVmFnY8NADou8533Ppu9PdreMsdAAB+scznjRWjf+v/5uadv925o1CqFEqVol/ec6m5uvMHv8A1LyEA1NdEYRte+j/q1oo/F358vqur8/IIN7nkT9FeNqL5C+rvN0eIXsY19+7Jem7rkVdF//Yf8byBc1LEb8sa3utc3u+p6H9nHsj7ZGAUYEzV9pXs/m9Wrv89FX5B9XgzyI9O6rEfHn13B9Ut+V1QYtGhsN//aoY1xZcEEdtXLtHd0yiu99wlf7sm/OD/G+R4teP+a29uWu3G43FeoTsuAeQl31DRq4D/z8gj3T10iHxlS2JRThj7VwC4vDzjP7NPyjEjwOClDgXp4it46V5dRuofy3pwA4Cms/PWGGO9z2vs111hUPLpf1dWn+9o/XqYF5d7KPw1RwDdpeLk1L80DhIAeE9r260Rxmpf11+Dg9Mf3Mb7e75RKAcJ53WR+4JsG5j+AkHQ1iueiUnr6dP6pITqo+wzP0QcivVZZpnMXyP3O9tvEZx/TYoS/su8l0yHW/P+8y/Hi//coDYb3S+uyGRDLwt9bE8XJAe+7NC4hcVtXfnSLy0/qS+eu/lSxL//KT92jdM/AwD8eoXP77Hrl2/d+1alJZzX7E7744FNMx5ON9vFo3eq61VOwdFRb7B+PTWB5ejCXvLNuevfKjpr6mWjr6xcxaJa6OP4+7VrlgzevHz2o4oLPX8b58fnp4SumOA3mgvj/tftmqVub+7LyQ5fgQAApmq+oOfvTcnLCjcXwxr1186e13FjCksyQs3TgbC92Y96e2797c4g5uix+d9y0sI9l05LXsffuv5w+aJyye/Wig/90eT1knc7zn3rGpWa86cYgdOSuT78e3lDB87b/W4wz0r8UcW5Lwd+vys977DYZ+kScHjpNebo3+4MyK5+c+fhL4Wxf44XLnOwrDC3N7QZhQeP/jl5E8NMk1/806OuvyqZQQdzc6NXTraK/4Rf/7RuYOOfTux6bQ7XCnFd57dMq7jR+vFH566qHv1u15E/RvL+L5sLxpRV/6tZ4/PeQRFz+vjpF8tcHe/89crfPQL3/Sn33VU0AKP+ZkvHI693k/+YEcl1fGpimlnxb+crzlMPlmWu/7+nPORRV32PYe0u8RbOMsv1j643tuGCvf/xp7y33X/9i6cb29Pjn4xGI9jxowd+KXNLOpHfVLA453kZ9F2lBfUQsD9C6EGnEoRe09takl3cNgw+R9orAql2gi+YwtqqPZmQVxH98vTz2ZW8LRWyzx8V/kPRmhhoLauS4Cv4zIFPCpvUAMCOLKpIFjo52DnmCSnZWxyerk+uyVkEhXCvOiT4hEtJa+kLOf7IoG2IF9cISuuiWT8Buhvt+GlA15Qo2lqiHFuENjDoqf0Bvge7sandYfLfmOgNZMfCaKwo2iGevoWh0Wgc+7Zia0By0z8WpYnbZ5K3BGdcvG9tr1QRI+RzuPxdi9207OePR92Zb4pSv8YW5WHYVwnegtgZuwM+Y664eyrGN7Li7thPg/C/sHtqPxHQg7Kz10sLjvcttKkC3n608ApG5zy+o4tOtd1VbccCXObmwlYnaxebqUv+8rIcyfojmUH/SJTWtWSIj3TQxRNLvFRBTEVtho8DyFrkuJ1nniggy8pq885IX5xwkLx7RYUE7PJ5EUeI430nEsuI6MNR7J/Igax2e/nTAVVwsOQ9WnVOg3YRHoa2mNtxWcVG0dRKBibuWWEn9EKVgKw0Jav/9Uhf6vTKLr8aYqfUbvz8aaJs7MDgsfpCZ64PE1zWuNkXAOZtLPVtWeKs3lXZaYuUySfUbdeXR4tfwLoA0V8Z+2/VsCfn3RU/mXOT7euX/3gYlZfsEpejgHBCD+z257lSiWF1z4VzXSDKPxz+U3H0frTQ1Ii3HJEjAUVfH5tBBxmmbc73c48vmxJD0yUYwo0+nPJugJsTAoRW2nzyVLNDSPZBEdPOdfM0ltm7E8+Sm459VhRAX+Cjmo/kXgTuHwzXZa7Jx6JZz3kGCGW1+J1imWvsuU9ifkI6x24v/zFDIHXzyeKqCzcVWgyWMjw8BUFR70X72jOxi2EY2nPFWVKfY3XpAoqdGpM8iUuVx6saO/u0mAFoDDeP1QFhYSFBXnaumzcBz+YelTPe3B4StPDDlkelWdvjmg3csLiMg9uet7EEXF6SVU36hkYGC5mOP6UpsNtLO+ywww477Jgb9vVLO+ywww477LDbSzvssMMOO+yw20s77LDDDjvssNvLJwN+T95cU5z2XoT/2ycUBvvMPj0Ivaqr/kTW+1H+b59QEM/33Xp1V31lXnyUaEeBbLpX42ppc1VB4p5QUbKE+AflOlLT21F1LFP8VqC4SW9nVzueUsy1cnTkH+RbcbRPuyjq4gXbS01tov/qwMSFiz2hvnhBorjW3nRFrXNg0O3ttWYwR23poas2xFXNcljKqKrhZF1zy7mGbpXOQKcteZ4SrKo5+UlzS13NJdWQA8vp8Vffayw7fa65vq6tVwsM+ouvQn8RXKdrr6hqbGmoae1BSSdnmp2n7XgaA3KlOOnIdeznqCcJbUdJsljkK/B7O7dt2Pwjdr0g6Zh04W0xlrzQT9P3NEl0BKDDOMDCKqQRVpg4luh72NDeiHDd7VpkRlt4UUsQpGZ08mEptnB0i0zLiFSekL1diXHcnsAGGLTNR3LLLvShprMAl9BoVAoCJDE6ZjqbxWNvdV3crC0iEbfItIyw/oKenXXAne7VL4cezArVVKk6j2nY3oxnSiq0PrewVqq4/3cCAEF+Q6VTERKQpXQXb9G/Roh49BfGdU4BsekBePNgR2rvLAcw2TGzPh2oK+xwi9/HfXFNEvDmPQGpvfO71jXm3NlY9qIaNqL/RGwBvv9UgumQFmKgOuk/TnUOWM77Wkp3QgAMJKbHCAAAxr7PG+NXvPhhzysAa8lNPU0JOxCzj1qcdVatMzdDo/LEOZHZ4tjSnIo4t4X42S/WXtKD8kqRb4AXuDiddjGVEgPwWc143pHHqB5H6NQfv7PmKDz8YU7XiFvQ1NNlSVwPVJuTHnH1zSEAnuBJKOnACEovDdpZHbKtGAVudkuF9Sg7YlhyfG9KD2NeCgobUOkAfLxnPOod7dUAMNeteLbqjr09ozRQnrdNXDNM2fRhS5EvBYDUXak9lJYZVXYi8oPqdMtBXS+A6wi1bBDAeeYDmH6KZkyPA5367GmIXystqrkk8Iko2rT0hX0sbSkFgEQ4ojDv2dIkxCNp873FzqPg8sK0c/SkWmujdmRFVOnnUWhVRMgxNTBi6ppiPcyqjETPZkQduolb3OsXOez5sFBvgThNsu7jxjAvCvgKg5IAmRAQ6rr4hPrtKYVrqtO9n15sXqy9BORlQdDLi/UwEpWqAVg+rOeqRQhlXdIheeSpnHU/hY23Tt6isKlxob7taGoVM6d6tzViI+/2qgEYvNeePOhHEAQAXPk8m1sRZ0HQZnc9kzavSbz6HQDDx506UxR7Y4CEpVybIwafHXciVAcAcF9v7tdFcfKNys9TbXm/tSavMuys6XjUF8F1D1UyPSBr+S4/k7Y4pOZsTuJFYekHIqdnntKSVF0iwSCp6tZvCn5RrRKoq6NDndrrdDgjMmmWIIxUHJPjG2c6b/xpEye1uTUQcu6x3rNMjhsN1NgSsOEpCntbyoGG3T2jL37Y88lv1eTXDTlHhZkPTLU1lqa4WRj/NhL+p7rIz2KeOvD9GdXHGjR9ShKobl7OzzOzIkndU9CJ8N0df6pkQ0/HJdZoPSa1WcdQuR4Qlg/zyb2H+yoNAPIaf7K0UFxE773rPo/koUGvUGHgOPMkPlJf0wKw+b97DqZiVK8chinn6FI9hWwA0MoV+AvjOgKVogDMNYttonFVw2mJ7rnXyhH9RVGHWglvN6dn/y7NxTqFIwUAZGc6dC8wTvCM2ucOMPh5+ZWZ19T07WVy/r7Fbew6Ki3/WM2OCJ3GYFCmlSj6+gj/P9Be9LDnw0UDdR8pgSbwm6W7Hjs4nD3wSXnv0x9Z8TOyl/h3PYMArnz2czRdxKCkbxRc1nKdfqpU08va1YC4rWfbGLNRdefTUlKvUmIAbN+p2VTqCsG8koejqq6/AbCEM72aGJSgAC6C59Kh+74cNQCyYnIYN4oTAObT7V8Q12nkKgJoPM6ihkej8pI9UXlXyV8+92UF/dXrOqDx+Mxn/iaDurleH5SdyAOA/rrmey9O7BwYwXH+CGBN5e0awwxRWk0dRCxyP2eir+7iCCt47ROs/TODU/ZZl29e0LDnJRSd7ToAtq/7bG92FgaxsYu1T1/4sxj2ktC2laaEbE7pMo+CRFuK497auGrHCesJGLruysQdGz03pLTZVMLiytaS5Aj/91qnOHrEvY6SNLHIV+DpHSg+PvnbcFXDsZSozUJPL4Gnl8BzY4F1wwPxNykK4OQ9V9kFoW4+lhK+Wei5ISqtVm26m1DWpe0IDC+fKBsllJXijRujKtSWx+OK+oK4HYGrVgdG5bXqDKC7kBu+NVS0t04HMPRJoigwVLRzohwLcFVDYUrUVqGnlzAkvXGCt4YlVWlR/nsbdZZwqqs8JXyD0D9bbn6RAZfVZIZvFK7aU6cxzBaH9ZQnitZGldtWumrrxO+cQK13jUjzdmwMybMSkNS0V6a9Expuqo4dVZW/HyHa/HZWHwAhzYoIFQVGiCtUBAAM30RHgebGNVfc6OVV6VH+3hvjzs5ZxkwO9aoB6Dw3mq1LmxU/6VsIdUf5obiQDQJP740hSZU9I7bmUI4awMlaO4OrGg5F+XlvFNeaz2TR96swoLhzmRZWac3bE7jKN6pESdoSR1ZTELczcJWXwG9nQZdl1HhfXdae0KjTWjDouwqj/LwD4+pnO+oFv3N9CIDpOymMw29JUADg+Hs4zsp1Bn1PTUHc24GrTIzqFVE+oZ1xRX1BVGCEdczEQGPe3tBVqyNKBqaOQdddnbU31M9b4LlRnNeuN98u1QK86uNKsVxzIi5QuGprgSVvNiPPyOqL43aGrvISrAoU5zWpCduM6KXqTweAuHViV+BGTy+B59rQqPTqHv10Meg0jE2iTcXirRGF/SSMyMvfC/RcKy4fIOcSW7znmFgUGBheogbA2pLDRYGhIcl1FqVBaq7U5b0f4b9a4Lk2VHx8cuA7LKlKixK934oDqWnKDfEVig5J5lSChLKuwSAKE/pH+gKAuqFF/QIdVeoa8bsMgL4Pa5TThTt6SZmUvz9gcTPGJNp+k1jKXc34aQ17jjip50jEKi9ByAdaAJClB6zaEBqeNwMzONB5K2lEr+Qu8aLspV5S+J44sawDHQFwAMDlVemJeRfUKIoRGrXOADCqbsiOS6tVagYxGFHdfmRRGTUpu/Zmll9QE8uX2+gaXHY6JSpP/rvtCelJoS4GfY/0O8wqky0F4r0Veu/YY2fqzpVEuQAAS2D1/TGVXAfgMXuJyogk772jCtfQ+P0RPgZVU7sKA8D7Toj3FDQN6BXdKqvlJrVymR6TdatIADDom9MTjw9zI+Niwl7Ty5okKAFOmzPqvqw+6A4A3PzGxtaWxtYzGaaz/XTtBVF7KrANiSfKCqJdSbSppKyPBAC8rzIuOqWwRaUzICYtmfV+as0tLTpC6tRaEoC411EYn1req9XoSQJV6cZnUnza5rys419KhnBVz4CVMfCukg97BrQ6YiJW6xnA0O7rOgMAoW44FBOedKKpT0tj0AEAHN32fVDbeCzECcBpd2VrS2NrS22F2A0BwNXXUQC2gIEAqajPFSdXyu6pdQZM0T/XHiaDpu8OCcDyecXikBpwWfWH15ZZi11JtD4zPK6FGpF/rr29+r3fou0n4tImHCZMKdUBsE21M8MdWTujsrpJptcqy6mcOHpVDcDyWUEBAFxaHLU9s1m/3EMg9GFSrBY0bWfipxTR4dLS7GAa1l+XV6s2vXdXclFDrxYDvOtY6lHJQ8xA0qiUWW2/FoDG+wPdln+OFkoIYESnhpoSztNyHd5fl7Un8QvwP/jB6XNncoLpAI5uXsvNzkJDulicXSfTEuBAAYO+qzRRnC9B1VqC0GhHSFu3ouGQOOkSNSgp42CEG+jlXf0PCQAg1D0oAIPvsQwASEVVnOj9apTmzhMKZnPqR6Qle3fnqfnppxovt+S8OSqvSU883k8CgO7SicT3YhOPdGBA25SUc6Lqs/OfFcR7/V3WVCyOr7Z1dKZnbIO2LS827kh1zyAOhLI8LbcJxYBEqL+mzCW2VJ+kitb67NWOACsS6loaW1sazx0NZyMABn1bXkxUBb7pcG3H17Xpnvqek4lxp7UW8lbHvZdb2KIaImDoQkFihVQ/SsKv5sz247LTHZRgkQdCXx8hRADQL1pf5EZtxC1yLxdAX3NyGuWONlRDRLjHIkdpmEKuB+brCzoN5gUMew4L7pNW+821irClAA7Com7pN5ca69JnSgdTmNzfgl6ueOqNpws6bXpcU3+04upgd8IaPieiduh+d/HBnHqUMI4pcwP4nG0Vd3XXig9mnFEQRqOuPpLPWRl7ETMajcahL4qKz6NDn+/icPkxf8Umzto+E+sdkNNpOel7bFA59L3lcPaTu7yFyU2Ww9nHbuW/weVvKUOt91496Mfhhp8anO0g8c7UAN/Ua+ajvB9phjCj8X5L7uHa25ruWAGfE1xxd9zy/GvJ3tyA1C7MaDQ++DLWW1R023TbmO7ufcJyUV/mej4nuNR6l9FoxC7nbxGEFN8izG9M9ONwd50aNBrvtx/9oP3uN0VvcPlbSpQPZBWp/3n6NmY0Dp7eyuW/kdv34Nbp1IMVVx8ZjVh3rIDPiah9MMNnPOg6Xa8gsK8TOFz+js90FoIUbeHyOdyYJus56bqzO7j8LX9Rjhl1F0uK6hWaiwf8ONzwUzan2T/4fBeHy4+ddFA7cfuoiMMVHb2l6fxLQurHfZjROOVdMxO4O3Yln8PlcwR+3gI/b9O/ufwdn5tvxL7OeIMbclRGWK9PEPA53F31OsskpvpxuOFlqNGoacmMTi67PPmNY8qjb/I5Afk3xowPuopi4oouDhKTLrjfkhDgt+NjM1c8+DKGw+XHfKkbQ88Wf658cDnZm+sXezQn83N0zGg0znGku64+ks/hhpcpCKPRaMQ0Vz/Lj1nP5whjjn6tm4XrsGv5W1aKMi9bSPp9d4KAz4k8+8BoNBqxG2VF9bfQM5F8zprkqzq0Pish968ao5G4mhow6TnjuqaDAb5xLQ/MrEUMKVDM9G/N6a1cvndiN2bEbpQlxBw+e/f7ueR0DD2128877qzlaca7J8M5XL7v4b4xo3EMw8bGsYtiPocbO8E8j9pjBXwON8QqYTMx9tBfS898o7txVMRZGXM0N6PsFmE0GsfG5ym2RiNasYXL983qs5kN4sZfQjjrMyb0gCz/Da5FPL/vO1XWclfTsovLfyM1P/W/2h+MG43jxNzK6lF77PpdZgpj3Qlr+ByuKPcWMW9lh12M8zPx8yx/3tFnH8xff35/LXM936wfJg81dXfRjTHjImNMmRvA9068Nu2Dx2Q5vtyp2uxHMez5QHd2F3eSAp+RBteSvbmiXBnxdO9ZWH2sAyPsYAyoKw+NgpM71B+7/ofUjE10gGGlTA80b2pTYcfvknKCGACj6muDAGxzFou5LSEeyJ5kNQBrnafFFbhXm3pE6pHVMlHo/LKbKe9G9BbFlah5h4uCLFUVWL9cB5TglcyJyEZJAtWN9y+zZWI7pRg2fq5rWLDJGWApgwkAVFF6FoBBzXOGzlE9MW46mxCX1d+kBWanr6UCkMoLfYRW09Abk+5LBYTOtlZ2PJTLRgBZbVPbMiovyajTrSnYw6EAANFfV3KVtik9J/JlAPA/GAe6+godUNbTJX9uXH4gO5TpAHjvdQ0Ajyn/8xlkX24UGwEYkKMEOK3hzpRYdlobFQZAEHQaAEGQpoiz4bjUXUAbkuo1jwCWAgDopOdRemjpXjcEYNOBBCBUhUoSnIU+y23yM1fVAKzVbOpUJxTc4GzBRa+UI8EMAED71QB0HmeuAleNHDUAsqHocokQsSTiyvekDL1GAwAY6chMa8U2FOz3soQCjgz2cgAtif1gmcR+EqhuXtCaliXfdKRg05QiGlwpGwYQcGnSgrQmt+y/hE72lPG2Izlt44HV21mmiKq8TMnelpMdSEccQuNZoKn6jgBSMfh6dRILAQBkjlWGa4MAVCpaFivqVQ798Eu2+yrenqLzkcKJlz7OdSMdmfF12OaiZOth0Rq5kgAngSlhS+XtS+CNShPVACx3xfETWGhOujcVDFqFCoOl/tbn6C7kZl34zbufi5wcLH6xu3nPFT5wXQPAXk2/W55ZToktzZp7Pxn6UWphH33f56GWp4ETiw6gJh4RAIBQqUCoetQArq9PrDFTX+UxoRMlTXtnZ2Fs5OXYSNA3F+nBQMqYGRUcCgAgDvMTWwBceX0IgLdmYsGb6C1KqtLysiom9MBLLDqAziSejtzofVyiv0ADoFORQaf8nRxgxs3Etpntr6plr4QfNlXjUwWRG2htLfrmeuVBDnd+4RB13eG683NWilDoT1DK4CiIfofVUKL66GN5ZPrEMND6aiwsnzffKA3vOpZToyYpDFFy8qxVqQZMNwrIsgVHf4sz7EVdl9WYygzd5i7KpdBpgOlGn/JFi7CfRNcnGQKAXqlLSe4mukkGOlAA4paEVlIQZMqVD16X4eC0jTuxCZ1Qd/WR4Mz3MesIsufDUwrgZq+lP55+bCis01FFRzZb/5f+WosKwG21ZQkH8O96NACewtlSDQjDh0uraW9N3KaNPpJ/cAPdNq/NXAag15tzv+rGwr7X02tMQT2FvdYdLslr3tumiT+WL57Y5mzWXDairmsprtGDTzCfOqJuO3Oi7CoS9mFtpNfEHcpuNQCpuASlfzEl9Mi73SoCQNGOH/ggypRP01yXDAEleO1ch9IhVASA/IEAAPzSiebXErKZR9ukD9FHJLAoQKg+KtcE5eb7UCese+cwIJtt6sdM6n4pd5KTQWivoQCgkjFzKoIZ5pqgq1pAhOtd59BKuPr6EADbduskleHBYjGZFADQfFnRNkpZv50/YZzHSdIAAFQnqs0kMuGL+MwmLPRfqY87PNdRAKdlktT4VnRtAW0KgdR1Je0kLXiLh4NedvaT8loVU1xdN3G2H66QqgHom/YHzqvS/aH8Ng7gG5V+zH/G2qKpXEcqThe1jTKiowXWWzSSjiGA9V42CVvNdeUowJ1WdG9ptmkr2CN5GwqwVmgu+iVUH5VICNfYYPY07xySqwmg0ZTF4rNSdnrG3NppVFr+sRqmPG2cAACadYfPiFKmB2TzpKrmsTEAYLDplLkZm9D2oACOq/Zvt5n6+YgtkHelKgDG6tesBNO3ldfpgHvAVjwNQADAMoa12xSmlOsA2MG71s1zD6VB21yjZEflW4wZhRfhT2tpxC7UyQ5yfeZXq4XQGYteksQOjV1fltLZWNm2vyjIvOYgKb/ktu/DeS8BGvChqx2dSgCGW3zyHOuXpAEQCvLih23Q1uwJz+ubw/tA1hZ9/cG8Cm2xeyodANtrHgd5LkFMdHhR9T4kKlEC0DYdSAkzdxshh66oCKD47E2JNm9cA80NyRBQvIQ232Y+xe0AACAASURBVPNQ3jMMiJfQrL5H+764hAFj0r49MwZba/oB8RXxrGx9r7WqF2CpO3up1b+QogZwWcma1bmjbzpyMjuYAaPyqvjQuFrbegeEvpwCo38nDQCgby45x0xKsW5nZkYUVR8UOgHWWSIOSWu11B2QQ70qAug+E6Ue+q5GOQBoalLj8up0KxOrP86xMZYAhLannwREsC89xhRng0Evu64HcIvOFPOoFrV+SQXgvm7FHMYJQagIABAkMSovOw3RewVODAYANqQnAACtLejkZ0xEOQD4rQ4UwGODzRSYajun7M14IL+NA3il5O+2XDmq7hwAYAnZ1DmLfbQAFLYbfZJXnlsQRAcAfU+LCoC52rbPAKlH9QCufFNYY5pEGNZSuQwYaanqnbo+operMACdGuGtAKK7rnNyNQra3ooCEKpTcf9e3GbwP3y6NN32IFxCKxsAYIREus+rJw6ByjUALtxXqbN5tZO5jlA2nNUCXRhkbbtDqOrr1QAMnk3NkE4uGQJwichIt5RFEAPtCgCPtZai38H2Ni3QuK9PZ9f1qFQLgGlGX/VAQFHbqplL8omB8504IO6Tnqb7Tg9A8fA2W3Fi8LoGgC2YxBt9wwDuIp9l82DsB3IZDrSA8NXUJxNbMOgVcgwc3SZ2LuGq5t6prRgInUoPQONwJ1bBr6oB3CLn3eeEGKj7VOMVaeOLI5yQIDoA3l6zCF3SFgC6cF8YHQhJWYPaEqV9oguO4j2TcmsKzQGIH4gXP2wHRlhJY8dXLbP/tR6Z564UUn9LC0Bhz6difBwngPLUPsOC7aVB03OLBOeQ/VZ/0KDvua4HasC+QMbESvtXKgD3N21sAK6UKAA8NliyScM3ZTjAMsbjXXI0V9tRW2Em1FVH6hQA8ArfGk1iSrkOKHP3SENYYXl1dQcFCJCdhSeu2UTlNGcaAIEZAL9UXAYx6ZsnKX3e7qJzp2I8HEDXUlxuLgzDFDf04ODGszrLo+prAwCI8OCx0tKjKZG+j1UePZT3DAMtYE+YtUUDLu9CAXzFkVbKjCrb+gBW+PPm5BSESgEgvifQ+ko0OHbTUqDQGU4A2D2c0NblNbmlxwtsTdNdiQqAtcnmOHtTbeeUvRk4el0D4BHqb1WvxOBl5Sg4reTOxYyYol8PwOS5TDZICMVsrjQAQHWx1YOoRGEAl4AAc+1Mv1wH4POf+Qffj/IAsq1aMrlw2hQgsuKPpsRHC8AgrWrRThr4FTUAPSg1v+KDnIPbuU5TGGlE2TMMiCd/ntuoNbdVBADTfbaPnsJ1hLqjS29bg4bLygu+GARA3DwmEsuk8qoawG3fbmsii0Sv3iSA7rOSbmtQaa9M1yGF0HahAM7hRw4nHniTBgOf1AzM4aRjd5QYAI1hm0vXy7q14OAVZml0ou9XYZPz7Xhvo8xA2bRfxHSYm7Fx9DoKwF47qZR/PmILo+quwcnbh/QqlACgMWwbF2t6pBjQ1gdbnm/KizgLePPtWUHKas7pBOHrbScTcQ8LpAOQbbXX52cw8bb3LfW9M/+t2tP4hNs6Kbx3YjwA0E8qe3AAXFLVztgX/CQFrA6MyM+kt/qkt1rm6j+H0BlLAdPj5GKY3gUOG1lKd6LP9TffTWMEqtIDsKxFf7OxwogeA7oL9UXZS728Sws0b5ssH67qQgHchX+wysCo8mI/ANuft8xGfXffBGCtt6hv4pEaMwfLj0UtfWoAoDlTzXmVwhNYgNAFwInLok1ah2OuXkEFAsfn8J8oHrvzS7fRYPzvxIRvTkGcqAAEppOWlOHRadP0GaF6x5bmCREgCcJiHVEANt/DEQBXK4ZJMJC6UQCgIJNmjcRHrflbCQrgETChVogBiQKALZywWMTg5Z5RcOIL5m7cSqHQAAht63EJ92AwAwAQGoMKoEflDUca2QdjfaiT3JprvRjQrdlvAAD9bbkOKO4rmQCgU6pNWmOoV00AY52NccT6pUNA8fCdq9+baYna8dXpO+8YCIwEACAIGy3WcF6HCA7sNPlMpkY5bkG+dIThHykAuHJikjEgtD0DAK7+m1wp1LW7NjmC4mSlzQ4KAsMBABDHScMkLMqBQCXo5OT57MoR7dUCMDxm6+E3levIQdUQAI25nGL6v7UFn1JDfKgArlybHLi65xYJrsKJPIpBL7uqB8fXrftDcC0OAJRpGeCB/DYONF+RhyOFt3OLE+hrSiWzK2hylAQAGLWRCm1HTR847UywJDNxtFcDDjbqxqCuKZXA2pRkUxeYORibHJqaU52n2AJo5Chh3j5EaFWaUSAInAAAg40QG9RNX2jBfc8+b+vii6pzEGAFd77tjUakNRdgne1CgEkPhIa4AMCV6ovzOu6Buu5w3fmWxtn/zh0NfOKt2AxR/GYajLQe/0qLnv1EExjj84z28jrQf/cSwLAaW5Sq4Oc27LnNpVahgf+fvXOPiurKEv6eob+6PUxXLTIWY6bK2KlKXEDKFIhVIpagoNFiRHDQIk3ABMHBQJaAPQis8MgXHtPy6ObhCgRGkAiRDgQiBhuiBFqwooCtRRmtqibeShuqJqSuS9a9E8Z7P1l+f/CoAoqHgrw8v+XKWoHLveecvc/Z++xzzj7AFswm5xd5zwjAdXqRtTj2ku6dOAzRva2aIRC6m9f5aP03PYNgv8GBvlpVepEYGb67SbATO5kaUo8VdFIjq3GAK/HREdB0tTwxs80EwAwwAEBTALS+PjVbszU+yPb7PgC+iG24WF7Rw4wcY2A7vPJzW+5vsy/9ZL1NO6obRs+TsdcIVtlvU1haFLYdC+B+Z1GBYX98gMVsAG+qqr894oBy1vLsebtH8i0NfH+HAlgt4BDKwszzBhsWsNj2bAD6VvvYKE/rL5xIzmk1WoSpeW4WAUnDNTUJXDdXs3EiupUmYDltYmlqiuunPx6GcTAA8nIbP2Jk4RPYfA4A2ZRTvTY+Tjp+cHigbr8HmKOYbi2ITRsOKQ+PaNzXuLSmJuP3NxnWcLjvphEwwYYXLQIBl/UA/E084kJplWoaV3w4QsB1tMes+7avcQHA2GkYbRx9Te6XD93ikkc2gwwHKrhioR0AcN8IlXPA+MlJpQkAKIIaAhhQqwjABGK+DQBbemQ/FwYaTjYaAYDup2jAOC8AANF5zWCej9ZlJJSMhNsMN3U0cF1mmRSd1rdrAIDr9OJ0kZUJWveQIkftNqWqSC4cUCTtoO5QgAkErN6G0jo9DQCEttMI2Kti8zSX0rX0AghkfH1DYaWOHusK3TpqLDxTmZFaZwQAqvcbHEC4gYcBYI4h7zgCfTm/WssAMCbC+rSBs5YHACadfjSdNtVR+LGGpzhxZDS0M0Tc7GWALxmNt1OdhSkVrJCizJEzMzMpNqnqJgBz2MCf4MjP1G0BqHu3+gC461YxN8o/OKUFDLAXXuYCgEFtGBsHvsz5pN8h+sPAsckTPTyddZ1tzgrDxfIW2Lh/ctZQoTxgLcCQurrJONv1S95M/7hPMRCzN0UcWAOgyktJbeSF+j67iwTYTlsFcO86bnW3C0PD8PrOo6VW7Jn4X6OmH2CdbBbnZCj8hgGEMqdFml8yePctGrhO6yxcxm41CZzXLCYohLrbBGC6mJp6mbtnOGz7QNd+D2CgISH3+zcSY9zYgAm8POwAqOZj72UUlhakvhcS1cB+55iXPQD7JS4AqHLCFb/J6dufHreNQ9zQA4CmKD73+9f3r2cBTeA/AlDNsdFN/KMpAdYS0lLd2bEnMsL3ReVWN9RXZKS2StI+GLeP45dsDIBoue+ftM9C8ERTamJB6luBUSdrL5wr/yDr+389ETsco6dJIwUAVzMU0W2vHIvZyQXABHvcWQBEdXRsZlF57gexit9kaNzj04Y1aXipclxojui8Yhzn1wOlUeoBmM7MhD+C957pV2dsfsW2Bcw73ux3s361hg2w2i8tauKWv+GJLH0lPfWaw/GE4V2XNNXPABhL3gvJHVB8GOSAjYX7+GK+rXn2c7OXAdB/8tucu6/Lp44SM5pzDX3TlVawZ78DAHEhv0ZDAW1sy0yqtX+vOD9wtLUf6LqMAHzxsNKz3cN+IwT6cnLU8fjw6HIVBXRvNw7AH9lMxHJ6K8wFQJUZGZUYG16oJIfYznIpAOCFUVG55aW5KeFvhp+875ceN7wEQmiuGQF4LqtnNZxRN863DJ/QmmbsmKR1v+RyMQC6NSPkQHipTXhWhJj1t+sGALqrIKqC8dglwEb9S77Flij6b934EID246ii+557HTAAvsxrDQBcTQ9LKi49mR31VmQp43d8Pw+A6evSw1h3s+HtP+KFgbH0vdjE6MgPLhmsj2quCl82QM/HJy8T9BClqUzJ1HtllcWbnUVK12UEIPUqLUERugu5sbn9iqrTMW525lWM6RSb0nXqAfiOE05/ztxtAch+AgA0heHBleyI4SOtq2Wh7gC0MqdCTQ2B6WpxYhkdVJgfYbHqTNxUkxOXyaeW0g8NmXlqYFszZDZcp1dZAKApyb9ghEUEW6eIkAIMqEmfYI9nmblK6Om1hr51CbfiWhG3deRwPJxacsWeQcSGbhxgjfss8inS+nY1s8ZT9vS5bed47KUxLiwyx/IEmKkxLizyd+fuWJwJ6zsT5r7veMHXBvPJHMO5ME+/sMLWvoeWJxeLwrwlIrH33iNZZy0P3uGVwbItu48Wtf84dkBQsf1g+tm/mMbOFRXs9wv+3bk75DRnhvC6DyN3b5aIPBVhGeOKN/L1ryNF4uDT+MQf3zyTHCzfIpLKDxwdf9rP1BTpLT/wfs24jz7oKjgiF4klIu/gmD80jfsV2ZUSGpNytocc95PIlDNdpGV7Rsl3R+U3/nUWx4Me9qTsizxrsDwOixfsV+RYO1pE/vn4du+wjC9xy1Nud/6gcPeNyRkvl5jQ4zl/Mox7Z6D8wPuV136cqhz03c/SI4Pk5iNo8rCwhMq7k49hPTK1/yFyt0wi8lSEJRRNqONDVX5YeHJJh8niJ2Vhnlu2H8xqNDx+/Pjx3dMxwXFFlwwW3z0bs13qfeD9cyPfemS69Ltgd7FEJPULTii7hFu8/+eelMDgyD+0/jTj8axvyxKigt3HTtTJFGFH89tN1k+zTdS6n3ty9m9xD0w+/RdyVKWTd8sjMz7Xjj1y93RM2LhaPH74l/Td3mEpZ3tIc9nIO6djdkslos1+wallFlo3qbs9MjW+r3DdrIg53TON7j/U1CQEyV3FW3YfjEk50zWhEUZON8q8ReItu6Pyz3YZrJygm1qxH2qKgvdHZnyOT/yrGbvt48cPu5K3eypiTo0v0oOekliF+waJ676wGCudmrwUqzgwfFJ5ptHpUqrCdUyUnoqYzy3a3dSaILc8Oul94P2mGdXj2fGwK3275/F28hl/5pHh9H7J9gzL066PH/61MjJQbtkUuwOPn723lIo9LT99ESwSe6f8ZeYx8+G3Wds3KErwp//W3z1+/BgQQ8b66PBqaVFtqAA1BuK5wlQX4pV2P+hMQ5Izuk1z5UNdTtmdRGc1ZnvYrYwKMaokn5DLW8oups+0gEp1HN+XAGlf5Tx9Mvi/RwoEwOCVKbkPFFlByFginj/l79YD8Jz4yFg+F7C3xSRJb+VU6uiVUZ8hQ7ua5OxQzHiUhe6tzbmxMSlhTjenIHsJVE9xbAkd+mGIEEONgXjOGCJ6dAxwHYRs1BbPCdw9aWme3dkne5iVUJv+6x2EQ8ThmZI0DapL0pWeJ1L2zC0V/PNuL+nb5ZH/XgWH0t9Zh/xrxPPHoF71N4DVDnzkLD5Hc0xpXOG7nKr0euNyrQFFjOxKwpuaITA+6KXpnUJjfVYVROZPPDXw5PzieVYbWlsVfqhYtTby/DsCNFwgnssu0KYaAsCwX6K2eK6wk0bkSJftJKdA8VYVuMs9VlOaR375aTNNLm14AanZMB8Xuz7H80tKXVKidonL/+pMGIrEIp6/maWu4niI1+EGEgBupLhv8lHkqmnULIglD8Z52VHI6vtWZ+IHF6f5z+pwyDzdgo72xyIQCAQCMTO/QE2AQCAQU0E1RW1PMjhtEnDZgH+txLnSnc6/Yh5839mt58c1nD/IQ02E7CUCgUAgKFUr/c7Z2mhHFgx2J15VwlvJ+aE8AEZzIqxEwEUN9FyxlNcvGVOvsr40O/Ytf3lS94wrK9SNqtS3fTY6y/w+qKouzYg64B91kXo+e7imx7hcFqJoo1ozsFIFwZi0yvqijKg3/RUndWhpcFlCG++uDTtkThk9loePxXWVef76ud1U/5zq9tK1l7S2obS6uaWptuW2kSXkTr8jx1CXEtvI3nM0JkjKoQzfd3zW0N77P5wXFnUbz6D+Qm6sYpds/Y7w3AW7Y4/W1ycmVP8Ay2UDEwbG6riUej2z8roWdaOmtLqh/rOGdq0Re2nVlBIxNkTtkHkdazAMAWLpKahD6NGRE+60odtgcV2d/a7IgJdmHMTKQ7bK5GnKee//z+7N86nbK46lG4/FHBVJqQpDma690CB8bbqLzenbBZGFVHSDv5sduEnlcUC1HG5oJ/5lk2DRvD+6tzYhuW1N6KHo1ezM3Fb8AQ3w7A+EDxEXPkiod8wqG7krgOrIjM1sUPeNuH8s+9UcAKApghy+oGBr/tWPZM+uWJS2ra6u4cIVHTEEQDO07cubdviFhvqPuxKcJ09KIqJ+m4x9nL1n9cQXXDjknXBjdh9bG3b+nPn+P7wyNuqkcrTiHKH3ofwT5nwU1OWMsMwGTf+wnvFcfCPzkuT2NvNcfbZrSJIro/rAJ+Qca5p7Uaie8+0EA98Zl6OTPisRL+G5Y2djwxeNbZ33KACgHwHXSeYbGPyOt/XTZYT2e3qq6+qm8uOVzSqKAT3xcL77/7N78zzqNrKXCz3r7/vWACBwE05t+YaM9VlVuDDd2c6iG+gBVkudFitlyUDbB4ez8eCafB8BgLR5XwqwF8JyG86lZn4nr/pwrLezPZLKmqOViT6xjRS45TWXeY+2yEB34ZGoUop6Vp1tUF+fm5JZpxcGxidV5g+PnpS2uTA5JeRsbWhhfpzlTfeCkCTfkJCkWpcSxYSt4Rw7FgCDieQBrtMFGOgH3Rd+GPeA8GB+815lrG9sC8Xa+dG5/K3jasnellwr3Z24K6pRGFn7cZjTs7u3b4jQ3CYBk01zky3bO70ss5tx9hHOh8GmCQq47Jn8fYYigM1lLZiIlyCmq+UfJBe323hFJ2YleQvYAEAbO6qyE44FVnsnl53wn3TGjOm7YYAX/dY8yWRKGJhVvErH3iq3n+/yP7s3z6Nur0AeL2Ue4SX7JCLP9JsPp37mr0W7xZK9ZyxuHvjx3AGxRBTVukhJ8+k7OXKRWHHasLCffXAlRrYl8uvJlTacDZSIxJKwP4/71cO/pO8OrOybzYUMT3ppA9lTcFAiEnvHfGmYXMgUb4loQ9hpnJ5UeO+YP08s/MjVGb5Fdx9N2+B/CEuwUnGyPXaLSCw58IWV60XIb5K3b46se9YyIq/ESCWi/bNr5zkrXt8XyQeimn6aQZqmS78LCz4zt5o/hYiXEn1fJm8XS0RBRTcnac3dM2EisWR76hVy8s0e+ySucV0PHyMWXreXCks7X8GgUWUAEEpemdqnw9vb+oDzmqPZmaXvXccBhFKHxZleDvZ8co4Anpfb6gX9rKGpuAW839k8udIszMZquNsvQDqLKQbVFuIqi73KzN7rvJAUWdoDwiNFWZOvkLWTHT3iAEPqk1mtpnE/lwZtg5ai5glreNj6kAhHgHufl16depmGaC1RSyKsxJXZwk0CADCoJ4U6h4x1J7/hRiUHPOuzAD+qtTRwxGKuzTNXAPp2fsgHzbTrDLcA4pVRsdVGJ/EcJn9PJ+KlE4W9XRyZ1Gxie2XlRU6+z1W4PybADkznsku043We1qsMwBehvIGLoNtLh79f4iLBaVgjnmYdklBd1gOscraICRjUOho4r4kWJxxE937VTgG2XiJcSDUaMl6q02FS+WuzDy3aiiPi5n/RznQxI/UyA1xFWqiD1ZHFfqtcCEBfre3oH2fUX/PZiGlrL01IaGnD843ywoBsLG2dYjsMo6muhUCF1QxNXAdHDgCp1ZMTfICrxZ882J20/5mfnDPprvcBCKULkW2RuHbdBBwXCX/6p1StesAcPIWsBRfxErGWupNx5TiAS3TsHqsera3jnk0sAGN9jXacm9Wvw+nZXlL9PLCQur0S7eUQ0VmdHfWmz0Zn6Xpn6XrnwNIfzAOUpi47xCewcNRlo3sbMg/7b9wUWNg76T0Duvq8eMUu2Xpn6foD5X0AQlfelCKhjSocwPZlofkuNwrv1gNM2uxD6S4UxYfs3bHeWeb1Vkr1bfN8xdBaEL5jR/g5wtKXLH0rqr7fwqFO9N/ydrGGnn4cSZG7Sje+3UAC0BejNrr7yA8XqwYXRIwP1C29INzqwF7swai6UEkDOIWGTHm9jp2DEAMAbfv4S97Z62RC0Lf8hZg4Sdwc/g4PoOfjaq21OS6hLOmWHPG2Popha1/nA4DhlsFScEP66vzrzsfCXGbpW9D6C8MKuS0ksUZPjypeR2m8347waqPlgw2ZhwOjGseqwBi6vwfgbXqVDQC0vq00McRrk3Tj2+U4bVbgjrIUxY7A3PG1o/VthYlRftuk6zf5x064eonS1efFK3bI1jvL5NFVmkGqMy9c7uOjKNQDkC3HFXIff7/jtfgEXR3Ulb4XKN/1ZmoPAN2dGugv9wkMLxt98xChqiuIest/o7N0o094ZqOefgYiXhKj/OXiaiMAW37UdypvibVGxAcAUq0mLFw06p7acnPsrBhQ1+fG+vnEd1gOAkZlaWK43F268d/iK24z0wynHWUpUYcCN7rK5O9ml5YV52amxCaWdw5YfTOD16X47TAPsABgqIv12hZSaPkJSlefGx+yV7beWeaXZN6PTRuVpccDvaLbqLGRvCxesU265Vjb1FGdGXWbMTRlK3b4Z/ZYFilevi0k98Yy3gw/P/aSul2beij2C/CK+6jy/Nl0Xy6ArYPzqpGuX58UHp5WqzLSYMOCIaKjKDY8S4nrjTRtMA5Yth2DN2aHHCkjnMOLzin/crEqzZsDIHCxetUQrSs97LNle3g9BTCoTAwOCXk3vvAqNWJBx2/2oW5XRQWmdK6NLPvy67aP/LHbzZlHsjsoAGDwmpSEU82dBKm5Zh4jTE05hbf1+IPRsj26r7lhJHuU058UtN+V3nyjtXgbC4ATcFr57dWm5lORLrYLYqfuXceB4/TqIm9Uo/XNXxgBwCFgx9RTNxuM8w8AwBAD48dkO4GTHeDdk2KnmEPQYTEAUX3KytZ5vL4KAhVOU/lTbEcXLsCAFrcQHHW5uJoVfHzH7CYKA8rMd3M0a/2jjwS6DekaW3UkAAyoS2MiYz9qwwngsCy099zH1d2049gUZIhQ3SbB1sHtRUpVmXKsqBvWCtg00D21I7a/vy333w9GFjZrCMtKU51FUYos7YYjaWV5kU60sSWvuGu05qYrxVFHyghRSFJq5E4u03ftuoFhux0ra65L22QLsC6mtqmhuanhfM6kCbetQ8RHNQ15fvYA9gfLm5samptqysIdMAAY6C48fDBTL0k63fBNU/obg+rqpNiTUwzlcxLx4kN01ShpAM42v2k6Jmt4d94DI/nILNy+bh1tw31l1ncsm7rLo4IiUyuVOAjGtqLRPeXhSW3sXWFHD8k4eNuFG4T1P+5vSz1wsMI2LO90zTenQ+BqbWFhM24rCY0Lc7Ob/GZKVRoZktaME/ou8xjGmLQ604CuQzsSWzG1ZoccKiO3xRaXZIeuZfDGwpIeZjjWEhUaX3hRbxpiDc9kUo8kfNJjxAeA/IEgh6Y059PqNoNXxysSazWEsfO62X00qf/SN6Brv00sX3s5D/tjqe5sxZG2TR/VnHBnAwDYsh9SAK9KhLYAQKk+OQ9vZR3VB2bqHdxe0NenFWg2x1dFcTsTfTqbVjm+aBFHrYlVnCCP1lWFDl/bbLsK7pNgu9HZ6gZuzCHiVNM7NzK8DjXQ3vnNedIRnSS0nf0AW8XmbWzGhoTDBaYjNXm+AgzAfmtYhHNtak9z9Y14j3XX2+0iy/K6Q3ZlaAYYBgADAEr5+7xuAFbfg7FGYnH+EUAkd5txjB0iND8wAAKXtbP1Q2ltseKtcnz6s3c23IBTDWmuU76TNOpJWCX8p0XeqEYolSYAWC11mWbP/RBNMgAAE1dVf8EV2gP5g54E8YQVOHufdwMKo+pby+p+8Aq1PPE20FZ6RRz6X1NLBeO5rIVq4r+7DEzAatawm1VyUrfz/2bMKkczUB0nUi+sPtG2X4qBzGOHwmDDsx8iLpxWChPSA46EV9tInF4wC0FzkwBbL7exgOigvusewFpHQ0m66tXYvBweBhS/uznhBkkxAP1tmYVazw+LONEhhQa+y8iCAqMpioyqc8yvi/SwA+DJXLjFGhvB8Doz3VMcfrzZ8+PaCGcWgDi/TqYZ5DsNj+D9t7SDwBHNsJhEartNAJ5Si4ANra+Ijv2EHd98TGZvA8CTR7xd3lior6/THhVZufZhTiK2aNiW9+SxV2aYZ2Cuyc2n/edz/+eg7pIaAMBpm+M0UURmkAEAYGFjdS7N+7S6kQAgclKz+w7HBolYM3XqqlK1Q1JeOP5msWlsaYbWnTxeBnHNQd5s8JZ5+hphNc/qTKDw3fh6u+S2IAEGAOv9f7OuPLeXu+eQv4udlTebWssvrIpv+LhM/m4b8QMxuuGdhXFYgEmDtnIBgLqafTBR+a+na0NFLAC226usinv/IrRnwQ8NJbfESZk+IYcbuJt5D68Wp9SzQ/PKXKhaxeVsXPDylOo0rW5TV4orBoNrT3MVhxoIA0HDiL5hbBZgsiO7eM+xvRxoS4muJXflH3cfndAZ1Foa7KXDp3LYLhExLoPdsXoAgaPmZDHpn57kyoYho0ZHgp2Xyz+PNPL0VgAAIABJREFUvqe3PDKzm/9eTZDArNztvQBrpcKpPUHSqCcBhM7mRXhaf90AIHQdjUwOGeuTMtpZ/lWBY3F2jvAlDvSQJAXA8wrlAQxy7W1AQ1MjA1ZluWmTA1zUGfpJAO5wCOWSQRBxJnDmQZY2qgwAXPHsb9/F1oWUNfrPFKFgcVZN10WZBxQAi/MPi6tLw4d/APji6fbcU0bDIABw+BNOiNiw7G0BKIoZmnSZgK009G1BfaHukzPqoCTzII7XVZEBWS7TrZ9gQjEXbhB3dAS48gDA0FDQ8nJspfPsHAta395Nko/Od/RLd64GsOPxAQC4e45FQn9DST9guyRmlaB0LVqAV2Vj6kobruM0AN6sCi9K8xkx6hgGAFyeHQtWeyVlesGgsq4fgD/sXALdW5VQonNKyvawAwDG0FBw4ZE0+g9hThgArTuZWG6QZh8ZK7ydwGl0ukNpr/cBuGyefjGJwa/pAQSbLLQT/yQht4cb8bn/2Eq2vYALoKcf0PMvYouJv8eHtV/NGJZjcef5sMR9PU4DANdp7XTm0vTdfQCAF14eKT5XFpEpi8h8gu9gjiFJjkA1lfcBuHiP2majsr2fMdQ349sUQgzYPOtmg1IWf4KDywlv+9F+wWGNKo61N9t7xyQBQK/AHtpokqGHnX5ad+ni/7glJAesBhhUFybXmjZnHxKxAIC+XVt4jbMzKT3oJQDwj4sAQ2UBCVxPOJ/Z7HD8hJxvA1RPNw4gnFqdptdt9rqYtK0AhJEPDfgDyryu8TXj9n7yntWwfJmjvWQ0lfktg7zQUPNFnAZlWx+Ap7OFD2u4rh0E+K4ZP1yU5soeWW/DAbbKRje+Ehd+X4bbiNMCzBKie5q7BoEjcpg6yMgQWiMAS/iqeYZB3NaRwPEc3f5H99aevAGc/X6WZ+zooYcALK45KwWLgwHQ9EMAtrHp5A1Z3FEq6qKO+oEC4AJQHR/X0gezjziyZtMh+2gAkfiV2S+C27DteXNddqQZAMCweQgWMKpM/5CaSQGTd2XrLf93XeT5z8ImbWiiKYoBAMzuV9O0FI0rcQCwmbzlBMNsAB4xVsdpoX+kZ0l8e0N5y5H8kRvSKWXpZYeIj6ef8rPWiAQAhOGGgQ7iYZTy5Gn6N6Vesx2FMZ6bmFPd2hy7zxh6Iitum/lbVK8SB3CSmdXVdLW2k4Y1UvPhbVKr7gPg+MQc9xmL0FJ9BADmsOHFscibDqcBe9WBbwMAVFdRGQ4OSVt5tF5ZXVJ+gZbl1YUNRzVMrcXVRpZbosSarjB3u3Vji0lTT/sMPVoG7MRmJ3Wwu/SMHtZG+gotHntEAwCHb7XbzVHEFk3L5fHnrKuakyGKU/oZnlrtX/Vl8ohT9ZBiAADY3H+c5jw3obpNAowT5dMV785lLYBg5/pRoax+3W01VF/N9gvWZeXF73nJahmYu1/fooEjHBs+6fs4AbBui8UC06Q3A8A/clkAJDXSewwNBX969XjlPh4AmJoKqglw85WwB/QtZ4tLrmEBH9cEOY/9LaVR6gGgU7mqqEDOtwEApu/KLRp4HlNvop6Vbtvy+BiMxe1MTQUXfh1dtXd5b5ia2xBLa+vPGYGr2DO2uYbW1dXpAXguArMsTWplH8CawOQk7zEz1qoBcBrbn9LfVnGVAWc/j7HGHDLWlzaTAC7T7b+iDVoCQOBizuI4vNnHYdNoONTQ3mqa+BLScI8BcDDnQLDBWCyAIYYZojo+Oi+MKnZ6sYkLgN8jaBDA7fJCvTwr1WE2FpDuUxsA7EULnVgIswUAmp6H1SKW03tlX71t2TNaY98q4KRWpW1iW9p4a1NtjP0CC4ChmdHItlV73PgXGgBzV7hNXAqiSRoAY1n/Q64sIoDbXq0sqdfviRAAAF73qck3ecblYfba19dAd993t4ghZ7KyQLUt+cOXZt8a3J0nTqWlxaY2qiui/fGkqryRKAXT132LBt6msT3YlPJkppIGlqM51Dm8IYIb8JbFne4P1B04YO4+Y8cYqHtqHEDoKsAAgFLXKRmA+xfSYjt5Et8jxbVmPaJ6GpQ0OHg4sq2vAqhJsN3oNr0Jor7vvAfgaj6dNbKX2/11S2mavicAWE7WN9nNUcTzC8spvKwtaCal/wVmP1bQfxxemaSZR1M/36+80AsAvH/1cZjTzs8hfWcPA1yJ2z+bwyRJFdlwLL5a25DgrzVUlkdYi+tS1EMAICgagAUAVHdVfT/HN8nilsfJbwYAFgsDoAdpAID+5pw6XlLJ8O53oqNBDQCG6oSoSy97BMRWRY2XLK1v1wBgsqMfhozsAxgiOq8TwJZPrU6z0m2w4dizAQaJhwBsqvvkJxBROLu7KleqvaT1bR0EgFQ6GpyhVKXZX9wDwByczJNuRntND+AQcXAsksbg127RwHXbwB31zZs1APYbxhw6RlOWXf8jAPA2CdjTeIJ3+gGwl19ZZQ6HdvYCrJaOxqkYQ48RgLXGMi5E6Vq+A3D097TIMMPBABia/LaqAkLyXVkwyLXHQNN/n6R11Vlqj9Rip9l1HUL3PQ0gFPNm39PmZf2Ss5oLYOgjAeYc68DseHzLYY7iY8Bi8wT8l2b0AVhrXAVwUQdGPTkkY1vtGAPKTy6RANyAyeclhyiCAljN51jvUSyXt8OcqrM1n5Z3BqW7gbKilRfx8SwWQviOfBvoM6g1eFP1ly/HVYqfbBDEBAGZtU6OsSG53e25xV2+2R62AECqrlksVQ4RF/IaSHuAAYHbOrZ5mnKHBFsvDwvfyXSltnOIExBqrrtJrYfR08O04XoPDSB6N+8j/4nnfIYHNRvuGrb1xaSOe+NCwdY17W/dOMAai3PJ5HdaEsCeZzmPIlRXjGAjDXBlz7+ILbRqftYvbdn2tk8Sm7FzeI0NOEXcMTBg3adl8LoqDQBIw4LWza0jEeoOI2DesnGBa55X0tkGl8SDCRd1hblN/2aldixHb2e43N1Z3Wpy9+cYGzKzdJuSTn24jT3DmzEOBkAPMjBkrM+sXROX72E3ohtdvQCYLC4vf6dV9+UntWoAOPvCzGFSSteBA7jKpjycNjvdhl+w+RwAhmaGGFVJgSEgO+0lWO7MyV4y93R9ABz+8Noag9dk/5Ht58ZWN74oNm/PG9J3fsvAWpk5peQQMTLcjMwCGeK2EQC4a0cipKbW/BLw38NRavoFG6ZxmWmjth9AIDV/i9Kq+gHcxxZXaHoQAIC08EGpq7WdNMf3qNzs6Qxv53moqy+m96RGsgHAhiu0g/YH+p5PzndtjS9znOV0kem7bQDgOQueoA/Py/oli+dgDz04wcC6xdzyw98qdwKdBm9u7w8J4lmbeZzKb6fBfl9y9OQVRJq4Q4D9Nt6UFeDJo3d9HHmx+eTXkfbUpwafZLfZ7D22fdl5NXQab1Wk6+DNsp1PEw1iOR3MKvpuX/iX/0MPjQ4o+jH7RKkqCjSbFcKrbbBa6mJOyqjvMoxf56P11Z+oMe/so1KLcEiP0RwOGaRoAPgF9ktLOzTEUMBiM/cNA1NO6MCgxmmwFztyAGijjrBz4FtrGeKO2gSsnRv4AGDS6n/pKBjZ2DJo0T2MbdU9YH8wxsPuGYjYYtq/OOuXto57tnIam8iuSz30VqmV5uxvyqw0go04Lsl/jkeTKa0SB3DaNumIlw1vT0bRXW1I6aD1+tvvTc6/HZ9Qk+HlXeu5XR5UVOUx3lW1/mYbFscGYJDSnM24sD6+aGziN8SYBgEwFjbuHQw1yGLbDkdjv8EBPLdZLIT1tmqGQLhVzJ56njQL3QawYdmzAUyUSVuVe1uedmwlXBQ6p/MkDykSAGiSAqBUFcmFA4qkHdQdCjCBgNXbUFqnpwGA0HYaAXtVPG5nRC+AQMbXNxRW6mgAcpABAJpiAMDQlP3BVfHxwF+p7gH8Wsz9sa20bIrbPe7r+2iwFzuMbeKi793CAYTSlx/ers3MVVKAcQUcAAa/Yxj1xNUleUpsV/J/uI+LLrJZAMbmTtfIPbwRz4jLAbhXlXlFkvbOrMMyQ4RGz4Ctw4YnWpmxYdvzePwZ/s2QEhTjS5wxRnvLYNWKD4/y9ALs7X/JP24/F0B38iMrZz9Ml7OPVRoxaUzZ+9ZmHv238EGWk3SaqTl7U8SBNQCqvJTURl6o7+y6nw33tV8DAKn60Ssu8El6LG3sqG7oHFnJZa8RrLLfpnBjm+0TRyDgAKUqS6+wDTvqer/LCNg6Med2beHwGc0BYx8N8A9s1lgK+PqMT36WZyVarJ7SRtU9AK54OByCsVdxAKC3VTVgjg0WJqY33mPA5ldsDIDW37w3eoLZ2JabWKyihoO6t/oAuOtWMTfKPzilncKsMn09egDua1xaU5Px+5sMC4CzlgcAJt1YPgeqo/BjDU9x4sjUOj8XEVtqLHdGnefxufPu/LE93jvkYgPklx9X9zKTzUBFYnYnzQvIywoVzPFDzN3Lt2jgbeLrK5LiS28zQHRXVytHjjxiq17hclz2y6x7Aza8nYfCA5zFcRXlRR+GeEyM60x6s2VAVlueeWN3WriF+FhsezYAfat9rL60/sKJ5JxW48jbrukABJvWmcVluKYmgeMiojsqylusZpyYjW4Pz3ltAahbFVlKz/cDhSsiDdCc7OUvuVwMgG7NCDkQXmoTnhUhZv3tugGA7iqIqmA8dgkwALpXiQPwXS38l79140MA2o+jiu577nXAgLVm3SoAwE+lxL4bkvqdV1aSnE/p8EEA/NNj/6l28pVa7XvDi4WWCSYYo54EwD9PiDpFBxyRsYHltN/PHqDvTHH9DwwM6uszM9rXx1dleI13HjGOLQBXkRQy+iob9ho7ABAEpYQInyC0alAZANbJHG0XXIxssa+U1fdntZUMZJS+xwAAQNxegBsw2G5x+XHuLLIxNuykcjhLAE0xMERp6lIORjex96Wf/8h6k5p6lDjmHODMnnYuroiQAgyoSZ9gj9nO4dlCEQ+A5Tn7BAXDzdadHXsiI3xfVG51Q31FRmqrJO0Dr5F7nSi9CYC88nHCewl/ZEdmBQng3nUcgL6RHVlJv+EjwIZDhQCgPf9FD0UPGjsr42O/dMiqTN+5epxoVP0AgtHljLUyDy7AYFtsVEZhWXHmsXC/Y22vRKcECVhg6+i7mQVgLH0vPrOoODcpKiRR6fRe+PBaEdlPAICmMDy4kh2RMNUSEU31MwDGkvdCcgcUHwY5YABsV4UvG6Dn45OXCXqI0lSmZOq9ssri3djPRMRLgpdC8nL91wypc99Nrh9OWjLE0ENAG5WF74bk4s7Rp6vSts15T8oQobpJAhhLE08z+1MiRKAqSc08Eet3MKPiXHN1bkbF6uN5U6aXIuoT46t71H+saMIHZ3yzeRMGhwXAcjjywXgFwAR73FkARHV0bGZRee4HsYrfZGjc49OG3c3ht427dIVQdRsByJaklEtcucfqKcLgM+o2AADGYrOA6sY3x7+zbqXkZJ9T9tmfe3L2b3EPTD79F3IsjfVueWTG59qxbMV3T8eExRVdMozP9O0dlnK2hxxL1Gu6kuK7xX3/8ZKO0dTY92qCvYMTTl2ZJplv3xnFhLTmZEfydnlMzpc4aZmE+sv0YPkW0Qb5gajkkj8brKVLptuP+sV8ZZmVm775vl/wafzJcivjZbvFkt0l+OJkP+447r4hrO5Hy5+ZLmWE7d4sEYlH/rm+oQjOeMKE0WRrsHhLzDdPkjv7EXnz86zIQLm7p99umUQklrjLtuyNLapTTZMA31QXusU97sqMKfIfdqVv9zze/iSp9MmvY9wDK+8+aVbon/G6DyN3b5aIPBVhGefu/GyZwf5cmGzL9tD0um9Js0q/MU7tHz+m736WfOCNLSLxlu2BMTlfaicX+aEq3V0s2WuhweS3lTFyiUgscd8fk/GZRQd5/Pjxj60ZQd7Dv8r5fNyvHnYlb/dUxJzq+mmGrPQKd9+YnK/HdYGHmpqEILmreMvugzEpZ6Z/wxxFvIR4eK+15P2w3Z7e233lrmKJaLO3q2dYypkrffOVTP0RXhLovTe27NrYoGJozYlSuG+QuPuGJZwdL9nJGqsqC94gEYklIs/ICfKy8uaRKmlz9gcXfGutnz7oKjgiF4klIu/gmD803SHH5UxPCY3J+KyHHNcTvXcfLbo0Xbr8mXV7dBT1Fvnm31lBKeph2Zacvha3ReRbdnfJZMcnv44Uif0K/rp4d7ns37L3FL6khPTTn4vCPCUisUT0RkzJN6Ypn7tXuVeqKMEfP1f89FmwSCzP0dDLuxazFPESvWRDW5eqEIklIvGWAxlNd39eArb8r00F7ydnnD53+v3hgkn2/u7KT8vxDpAHVxLkihwVvZL67LK1l4/wArlkd6F26djvm6neInnRItrvh5qivd7HLy21Iesh3pgT5i6WiMSS3QmV16xdrnUpVr63UPuc3ZREX0tYZIVZQBEvbZP/l8oYX4lILBHJwnL+hC+eHtJ3zh7f7Zt8aTRKRHaVhckkIrEk+KxhmbXpI1PjUe/dOT0rrFMvW3v547ngzYrT95aS/fb1DvtykYeKvs+P7409twRvpCP/2lQQq3AVS0Ri7+CMmpsW7fTTl0u0zM88HrBvS/DnhhVToWlEvCzG92tn0oO9JSKxRLTveMnXi2A1f/rTcXexJHjCda2Gc2EbJKKDTeRyak367ukwV3nWzZ9XWq/9xTJddjVd/YrYGrl/0Q/0DBC0HRcDoL8938I9lP/GImev4O/PyLfJzikSZB0VL6ktF+x18ug8efSAUdOrx+8ZcT3hwuUCAN1TnHlDln9i2R9kfmKMykuswDRf3oqp0FQiXh7YcN0OJrsdjDf1arV6fV+/zkALFnbXEqVtaCNh0hG/1WI3Phg2L/bVQ0+yNxiviw/JMwacLnaxXWm99u8eP368jIpLdWdHZn2/ZsMqkw4L+kPyzsXtj5Qy0Tf20j/J9kjYBj07KDN+5xJJjTg5BStiiTCgLPyw1sjlwQ+E439khK6YfYOIuc8BGmP9k5QkJg79MP4dbwd7DGhj94VTpy/Y+KXFyZfJRdWMoS5ZkdaGBZWdTxSzV5yMltn8ktR/j+M68qXgpD+EuS2688riOq7nXbp6S+PwblqewmnpaAcylksVGm/74nI3tinwaELGHgEylggz9r75tezykxUN9UkhFUPA4Tk4bfIOCEgrc14203S6tybnGjcir2b/NgF7Jcpomc0vEQgEAoFYFP4eNQECgUAgEMheIhAIBAKB7CUCgUAgEMheIhAIBAKB7CUCgUAgEMheIhAIBAKB7CUCgUAgEMheIhAIBAKBQPYSgUAgEAhkLxEIBAKBQPYSgUAgEAhkLxEIBAKBQPYSgUAgEAhkLxEIBAKBQPYSgUAgEAhkLxEIBAKBQCB7iUAgEAgEspcIBAKBQCB7iUAgEAgEspcIBAKBQCB7iUAgEAgEspcIBAKBQCB7iUAgEAgEAtlLBAKBQCCQvUQgEAgEAtlLBAKBQCCQvUQgEAgEAtlLBAKBQCCQvUQgEAgEAtlLBAKBQCCQvVx5mG7rTENLu4iDRpWeWvF69vSCeD7aB4FAIHu5iDCaivjEJmKpF9OG1pQkpC79ci6WIFZ++yAQzxe0UY0PLOQHKbzHSM/Hi/7u8ePHK1IkhprY8CteZXn+fJs5S7c7RZ7lUPVZyNxfNcUUSl14OIOKKkvayn4uBDGgV+EWU0YbzN7RgY+N/u8QhX+rJ82TUcx+DV0Xu2LbB4F4rqCuFiRUsyMyw1wWrjdTqrKUUjI465h0jt/8xcr0X3rLYz+iIqr9n5WFm19sxUcSJP6/TW/5LHsnd+ULgv5R115X9UmjjgbAXP3f8Za8IbSwl48o/I6yvamqvocBO3HAm34Bb/kv5fahbxfI36oyze5ht8LWsm3Lz+o/fR2HiAupUZmNenLE+eG5HUwvOioelTajyotMrFH3DQIAANdh5+H0/CDBEtbn2tw2h+gI8VIWIaVtLimr7dRTwOK57A2LCBTb2ywdRSqOzKaOnI4ZMZaD6tIPCuq/VvcN+8dsrvDFVRgwNE1Tgwx77esuUlnAfh+X1axZvbxf19Ha3KLlRaQqhOOqzHYJTw9KC48sSi+LcsCQvRwPcSGrjNhRvIe3bEqMOYdFrPXPPKX2SBRjK10QmKM8OlPySr9PQjc4BcVE7xo/+GC8nUHh3N7z9fjrWTXZe1YDAIDd0m0fzJbNBjAB1zNQLpyucDR+sY3DXpbiffo62nD3ZNbsDMyWv11rAnHWn8r2jPN4WC7Hypp9i+UHylkHiz6Nky5tV4LqKsqvvix1C8zfabdUi9hdEHykhvNecXmOmKVvSAgN97+R3nBCviRMJqXOTTzPPVbjYWeeKkTklL0z4o2JsxrL9oz9iiY0l5s/Kc0IKcl2OpiRf8xrmskPra9K+G1xC84AAHAV7zwCmPgw2yM6pm5/fO7mqiTXOWjZ45WHpmi3WJ6joefrfQ+7krfvr+x79GxLTX4V6SqNbHzwvAii74xCJJbs/gi38jtTU+Rm75ivTMukfUx1oRKReEvk1+S0TzVFhpbdfbRMZTm3Oj7UZnhLRGK/EivSpu8U+rkGlt19uPTboClsg0QklgR/aVqiJSS7UrwlIovBivwqxlW8JeyLJVHgu6cUIt8iK+rxoClYLBGJwy5NVq6HeF2cXCSWuB89N/MIfK/mgFgi8s66M4Uu3S1RuO6fUx9cjvt9KM252o4p938wmsbzfVyvnQLW8qoV29XPie6uvrJiNrbMIAiuowMHoO/G99TkP6ws7nR89/gO7jJpH+4bEXIOMO0lDYahqVujupYVNCFMNHutXvRuNbc6Yjw3AQAQqnuTpE20nvwMglJDhEt+4m24VKuxZQGA6mzbrELT/crqOj29gCU0fX26ngCn/d5jUzG2u8INYzrLavFFPyYw2F16Ri8M9LeiHjbYlMLHBAEfZgWtBvJyRkKdcYZP2HE50/5e6KsQ9n5aeoN56kosO3tJdeaGK7KUMFUDDxEdSgIcpa8su7jXCw6ea0HztW5ZHJ6gBwhq+h44kyCwtRI+ANxT900YUfpbc+uwdxImrT0vRPsw+MVmzZN/gL0pLFQIoP20pGeKrki0ltyQHJly5XImrV70bjXXOrKFrjwABtcRE01sRbHGPf6I6Jl7t9Tt5pbepx8oYUh/oY7YkxbrAgC3ay/8MNPzPzRE7Y+tHlhIkVJdDd0AXBexhaPJFngIAO41t9xb7BGjp/bSgMB3q9VFsmmlbysOPeQAAKqSKtUcvY/Vsj1C8lJN91OPIcvNXhLXP6nRw+CtnLd9trhK1zvLvN5Kqei26ISDus6/wRrnl632WlpbG+sj8zpudg9NV4rDd8m2HCrH58EPZAwXi2P/zSd81A+if2jLPRayZZN/5tgQQ+mq06Lk7jJFhX6Sk8V3ErBorXphDoxSPbWZ74X7+ezY6O6jOF7e0Q8wZKxPDNniLF3vLF3vLPV6rwqnwVCXIneWrneWbtwRGJ6rvP+DsvpkSvi/7di4LfYSwZh6GjIP+2x0lq7fFhJboR6nhdMKAgDATuDCBehXj7dPjOp0Mb7j+CFH1iK0zxChaS1Q7I+vftKB1UbwbxEyDIj60laT1YlXTS0EKpywp9XqRe9Wc66jvUiAAfT1GMdJu78pt4kbcUz27JctGZP6fGpwSGrTU54roLW19UPyAJlXkDsA6Oub9DMEV86Vt1OAf54g3yZb7yzduC0wPLcZH3ymFknf0QsAq5zG7Y7hCnksAGP77cX1wxm89RZtJ970VHtK+BLZGgAg2lr0zJxKYcN12cChbyjvPu1ov3zsJW3sKEsJeSu+nQb7/cn5/1XzVVNVfqgjebs593BC9dhMfUBvGgLuS9a2UfY3Jxyv6rnPmC4WD7uHVHdBeOJ5EzDkAD1nc0mpimJD0spbcMI0CAAM3pgREl2F39eTtLHzDgEAVHd51NspLUZD3yCD3yYmf5G7lgP3dYZnH8ExNKaEFVM7Pyw73/T1N6fDOJeLI9/K6KB4ASeqvrmYvpMNALw9UYFCDPi+Yf+6luNyrOqbr2vK4mS/esTisMGAkwD66qT4zKb7/G2KgF0O2ICuJS9c8YHSPJJOI4jRSIvLWgD4XmVgLAfQk62CuKPW93088/ax4e05UVO2737umyGpF59sYLX3DgvgAlwt/6J30u8GlCXXxEe8uU+v1YvereZSx5EJpng4nGDh7jCqknKTb3zAQuzLYwmDihpOSFRJipA85ZO7XJSqso3lK3fCuJ6BMgwA/6JZMzTVRLYh972Q8FNGAIe43KLaxoavTsW/gek7K1NCsrqfYeem9HcpAOBwxrss2Au/BACi10gv5vBNatQE8F/nP910296RCwBAaOZaCRZf/C9AqDVPe/pz+eyPva8zCULSjuj90vRO3hIhlw3gsDM6/ajSP7dXfaGLCNrHBQCapCiANVZ2IVIdp697FtYmaWO9Erv/+KU+aL8u5T/1QZUNQQIWPQTY3PaP0bcbWrgxZdHpfpl64assTWV8qtor64/J9pfD3XvUa3hsU2tGVAU7+nTNJjzF66qRs447qYgs7AU20BTJANhO2Sda3pPHXpnBycJck5tP+9tP9Wt9VewJY1BduhsXAABz9A+V5Xe2NhR+/a7Hfi6sliclNnckKSvSagLOhmCNOX9yTK4MHdmEjQmke9Zy79Y1l97jv5GUHTGyNhkW6p2iSGzuO5dx0r8hzZU1rSDMxRSKeXDDqNGR4Dw8zjKdJeX0W/l7rI+689Y+rJfWwA990z9Uf1yB6/LzoqSz3ViIiUMPO1Sf0FVUdAdljrP3eE0VE5BlfeI1O622Nt0pVrxVPsOilA034NSIOObYreZUx2FWvS60BdxwCx8E4fBf/lCTe9XhePVs9/cbqsP9TqhnGC9/uebF/9f34/TNUhHr/11M0YmQJzj/N3D9k6urAt4TAABbqvCwVbYYz9drw5PvFj4LAAAgAElEQVSshJGpu73gEXec/Daq/p+8PR25bBtgSxVJH6rb320m//yVhpa6YM+ma//vfRoAsF+NH8pY2Au/AiDJgUU1l/R9DQGYmMd5SjPH4mIANJAPaIA5BSM4fB4Gt/AfGVj9NEsAy8de8rwCeEzncT0A30PIHhsRnF7lQC9J/u+onj2iAVgsK2Mc2yMxGQCAq/DEutvPlWfe0NvHFwcJWABzNZYAgIlC4kRUxzE9gOA1XXaqVp5/Qs63AVxHAPCERPmxxlVJH0W6sMFwW0cCy8XByjiIsQCAph9N8x22x4e1X80Yk2Bx7acOjHSeOq2hHp4M9a/4RzZmi3FsMaCd3bb+yk0w0o/tfeLj6vwzbxSklgH361VJJV4T3vbL4W/YmhWO7xOTVNec0E20NGqTXMXYdIIwl3KNswDAiHfr6UAuBgA/1Jy8KYuLm/L43by1z9Dfgc0MaTroH5WFiVH+2icYWPm+kTsLY1saP74ULQ1YbZ54lV4RR/wXd05aPbkp1oWUNfrPVFEWZxVrfrrVXOo4UmK+Gx9aevUqA7PTkQVAtRTWwtvFHrM+mMH3zzq/baYaD/0/sPk/Mzzzs/7C71NDAnVpRSkBs9sVaPq6SvVrxYcvDauYNGgbp6WJuFCnjRNNPt3EdtnnD8aqzAHguL9u3nfzazEfmkmGpoeeWdce7RcTqoSN/+3iMESaBgF74ekXc5lHAACcF+a8HMzicoA0PW1gfFmdvxwydGoZsBM7rTIPawxFAsAa3mhXxzAAhmLoKdeQ2ZIAKav9SrPqzZpa93ldN6GN7WoG4L/rL3vnfSTn2wAAobpqBGC1VBNHP0p3YQMApVHqARw8HK18mv5fGoDNmVYlMC6PP6dCai9cIcExueazqSegNryg1Mj6fcWqj4p35jTPbkTjbtrlAN068t59ZriLzigIALZAvAaUfd/piCEp34ZqKTzPiShysZ267AvQPmZDosiv4aXujw05zJw/Ezar3Zts6ZG3eC2n1KVndXuOjUyb8HPlpH+WCzY3rbYiI7Y9j71w3WqOdQQAG67wVQ70Eio9DY4s+nZ54XfeWRlPEoq15fJt50e0ER99xo/zT3jzPpwrmjkaPGS8UK0VhmSN9heWS6AXp6mBvFirihO7WSsSpb2OA7hsFpibhKYoAOAK7LFnprq2qzAAoP9n/EY8hiQZgDnZqvmAYYYAYz1tGSjCNAQAPCfenGvxC2y4ME/HstrvQ+m67gGsk5m3XNLGzl4AkO4RjXRs7AUeF4Akpgk+sJ23CQCAGZrvrWs/dXcSADYvv5MW5mQ7UuCW7wCA45EQP3Lunta3awB4MhcrvjhD/vg/wOaxn+nJ4v814gMApHGG3a2CkKQgLgDTdVk9y30CHB4XA8Be+BVrtoIAWP26oy2A4To+CLS2qqRfHrdrmjnKgrSPOQSnLk1MrWfJ007M/qgDyykwzM0G+mrKuoYXSChlaatDhA93jlq96N1qrnUcDie4/gsAGG4Y6SFjfW6rMDbMaVHG8CGiozAhVckPOpE2m6VTurf2jwbnoK1ci2CS3x4uANVabX2jJdPXpQPgujiao49U7/U+AHuZ7BlmHGPz+LYAQJPj+xw9QAIA99VVi2owWRybYX/3qTRUq8QBwE46D6cEH1E0sJ7acC+n+SWNX8cB1mwyb7mkv2u+0A+cfYc8x5SZ/TLfFnp679PAtd4mRNvvq+9jAH1NbYZwwTyqL/XtNzjAmsPJQS+NFu+eUkMDtis5emytx3hdNQDYJom1c3i0QU/Ciw5rppPlfKxfAoBRqSIihaunfmBQ26JmC20JvDGjcH9DkuvMasoMMTSAk+voiv6MgrCI0d00GE0n25yOlgmnE8e8tc9s1i8BgLM1prYmxOmJbNZqn4i9hZ3n2gqbjB5BPMO5T02+yS62c9ZqK2GCeVq/fIoCPHkdR0IQrwo4oDPd1houX/8EQsqeMBvwvK1fAgBPnvbZLIOxjKr6vEmaPK4pMMcAH251JdFSc53a5jWpGqTqJgGYzI0/9n6ivb4bwCEieJrF2jl3bVuBpwBabhtxggHu2KdJg4EB4Lk5chZz7Ma4PDsgCYqBp5ilUO01ShrA6VCwy5xtPjNAkMBd87SO6HKyl4RaTQLLc8NY0IJoKaoxsb3yLbdT2go810GLWkuCg7210Er1B8UQmR9XEZJ5u/nCvbCIectVydy53APA3eltjqkQ3ddNAG5vmLNNDjtKLtsEVuRO61X3wN5bzJ3OZsx5keMfBC6rQdWvs4ynTVbQzsJszd78Ml6xf3Rz9QdlAZ9HzjgVMN02ADgEbOPNShCjA7qTAwd6jR3n8sEmuGj6bGjz2D7TrV/SfU05xwp7hIefZLOPRdO7hQYLzxVrTlWpvL3qm3gRJbx50OrJ4898rV8+TQGeuI6j3pGYD83kd7WpOczO3JQndVXnvn5Ja2tTE6tw6ZNs9hnorr4IHick7AmTbH+/NZXlfVerLhFeARO8ikFdpx5grUw46kPQtz89eRWc3ksJeOlZdm3guu11gNs6lZYEx9EyDeq79ABc2SLnb7HhvvIiQL+eHJJZiw+NVtuao0N1F+ReYWBdWNp8JBYm7xkBuE4vPm1rLJ+MXOSlIxKROLjONJpG61SYqzSsRDUxh1Lf2WCRNGZ8aiW6Dzc9fGRq/51i9/tXyOFnxJLtOdqHDw1178ecxuecD++hNucNiWhz8rWfzemzGkMlIrHi9D1zMa697y0S+xWotHV/KLs5oeB42V6xd0IXvRBZqcQSkdg78kzPaBHIm2fyz/515NNkR/ruwKI7Dx8/fmxqjNoiEksOnLJooEd4ia9EJA6u+9HipT/3ZLwh2Z3T83AGQUzkp8+DRWKJSKwo+OtMFV+I9iGvfRTmKlWkfGWYk6Ie3SISS/YeCQ47Y5gvrV70bjWHOo71kZ4EmUQklrjHtZILPnz89HXWXumW4MKun54kHVrfZ2GizcfbJxd3pBdIDkyu/l+Ldosl7h+O9gVTa8Ibku0JTX0LkArxQWvMZoko9NxPY3L6JtldLDlwerSQP7ZmHI1JOatd+OSDd08pRNKYdquCH8mHN6aEFnr2bVmwVCLal9VuMuf8ywncIpKFlUxOtEm2hk2bD+/xY7I9doto39OnxFtO5y87ewHgv1salBq9ruVkbFQjL+nT4gjniY4i/40QN+huvGFeWjDVRe7e57NR6hN53SsvScYG4Hv7uwCYKsPkuxQV3LB5cFzuqzv7AdZJxpxKGNRf0gLYiV3+2bxwotGRAMbS99JxV78JHq7hcjPO3f0b8TN3A4UhWXGuLACyPTd8u09I1LHYkL2BqYYtvutYAED/0JCQqHSJDXHCAIC7JzFSCKApTCnVTnB9/7vl8miuL0pXnZTQ4ZxcdmzcdsHJgrAS83QU2wNwfGMOrZuh4gvTPgyIkz6tSts1lyOBbI8j/vYA+LeC0H28+dLqRe9WT19H8wST58wHAPHRaK+Fz6vO0NjOjNqyo08QM6B/aMjMUwObz2VZC428ygIATUn+BeOEQMv1PgBS3Xzhhh7vrk3892zTvvyaTPlC3JVk55WU5MW5UZjZZByempX8ZzPtHJkVNCwjRnM2u/qysr6wSjW40O0v9PRaQ9+6hFuZQdM/6gkAAH3LNXOKDKpXWZ0Zvvvgp1hQ9vk/xntwx4IE5+u1DFDq+qZJuQYHCXL4v0NTxqja1cwaz6dfRV5G5y/VKgIAA9VHseFNXr8JjTn/uYP1rR9c76MBBeEVraZtI4H+X/IchLZaxjX8ROboTpzV/nGHG8JP33cKTsuKmIcrLyhcTQvFAYFSc7TEcIvgOnju9TNHMm1YHDvOGvfdEf8RGzDBPNC66rMGt6gilwVYlMcEoR/XvlJVXHFRrdHq2oewoCP5cfsdMKIt87fZ9T0EDYDlZzu/mB60Wl2YehoHANAVvimrcJQn5aWPbFwCsj0zcONHPKdfs2kKey0wqzZQPFEckwRhNUYntPt+T/RMGV4WqH3YHlEx89DAjiERzg3V28I82POn1YverZ66jhbekZMjd400ftqw5LOC7xMT/SSLPy0fRCWc09MAMFil2KXcGZ2fv3/UMyDaEg/GNw6bSaotwWdHhe/xorThO0AY/Nr3AMAxNaQebnPbHxZa2ODx0sLFQu19sxvY5ZlFkX4VbBhk7GXJtdH+oxvWWGtcZcKaNsxf/prtggtA6P+bdeWfNGppZ4vxVl+bmtvcdVXdBwDAtCf5rM/hCe0xAJb9S47O7mFVl2XCCdcXrZPvEbZW/+j4r7vMq1p0b9UHJ7+5e7tbAwCDbVFvhru8Kg5Kiplw/R/9XXPLA0HQvjlc6bVsorEdMa5iyd6zswv+kF0pcr+UrvmJ+izA/SR9n4VtD63pWxaXV4xEohQlHVfqTtc0qkwPn70gllP7PDutXokFWGk8wkv2TViXQYwq25+T3WXH2xftiiGyPc7bPe7KXAaj5RKPZfq6dTRwrB7ztzZPkCblKQy5BR0Dy6ButL4qtU6QlKNYHrdbj208WCcLCFXsceZiz1gQy7N9noFWr8ACrDio7ztxgLUW6zKIscFgW0yS9FZOpW5RUg3RvbU5NzYmJcwpWfFysZekppsAeNll7WwjG5hjSH6qw4XMKpxe2jUbUOYW3g8qTN65QoesuQpiJbfPE2v1iivASoP+m1IDYC8WcFBbWIG7Jy3Nszv7ZA+z0F8eVJekKz1PpOyZ2zCyTNYvKV27HoDr8ESH4dgixYkTky/afvIRX5re9vkzq5qdLClPtsL9yrkIYgW3z1Np9YoqwIqDuKkmAVyceRhqC+tjgTSuEEoz0+vt0xckzz4AAAwZ67OqIDI/TjpXRV8e9tJ0pbZjEMAW6CfNY2SDNHS+eUSZBgGAIgaRIBZJq1dKAVYag7q6Oj0AAI3aYhoPWBqRI13QL9rwAlKz52UI+rvHjx8vbR+8Ozc6teLG2D5jlktibVUQD2nd4oywFws+KDvfriUBAOwc3Jwd9xxPXpTtjst8ZrnYWo261XxjqImPzGsz33C5Wl52Lt0NrWKuLJa8vUQgEAgEYgnw96gJEAgEAoFA9hKBQCAQCGQvEQgEAoFA9hKBQCAQCGQvEQgEAoFA9hKBQCAQCGQvEQgEAoFA9hKBQCAQCASylwgEAoFAIHuJQCAQCASylwgEAoFAIHuJQCAQCASylwgEAoFAIHuJQCAQCASylwgEAoFAIHuJQCAQCAQC2UsEAoFAIJC9RCAQCAQC2UsEAoFAIJC9RCAQCAQC2UsEAoFAIJC9RCAQCAQC2UsEAoFAIBDIXiIQCAQCgewlAoFAIBDIXiIQCAQCgewlAoFAIBDIXiIQCAQCgewlAoFAIBD/n713j2vqyvf+v+fgye4wkzx4TB46CbVNWgeY2A3SREQEC0UNPyw4aOgg2CL4gOAjxBlup1ysXGYUmSPgoxSOIFaUFgoFhQEVYeRSRbxAKg2pNWmRZKSJj5y9Tyl7P+bw+4M7cgkIqNP1fvny9SLZ2Xvd9vez1vp+11pILxEIBAKBQHr54kMqStOC3nVcafOONKle9wJnhNbdba2tbNUZUBNF/GPRq26pLslKjQ7aHl3Wg4oDgfTymWDQ1ybJcvocg/fJvK36VWo9/UKKDa0qiPZ0cHTZFiY7fEHzGDVRxD8Umqv1tVdqThXXt3R8R8zyDaW09VlRQRIH8dr3UmqR1iIWnSVPfwuqI3//kZqWuw8pAFjCYC9dhpnQgLF5b4g2+0rdVjAXJyeq07LEb71K4hx5JmDvKk0y6kf6xiNpOZX1bXoAAMDYFsuXMYi/a0hgvWzp5rMz2FvMwRa5RhiCgLRz6ws9t2Sq5v3ePTWxuw+3mO88nulvvXD5WpynAFm10zXmlnHXLg88Vx4qMHnhXs+555HqyA7bl98yLCosK0nkkWRv7vDF2orY8KzKu8Rgk7MQ+8SlRziZLUaWeO6BcRtdmB0+uV2zFNrqlJjTDO+9gcHMzMRytY5ewGJvTJWlVsi7qaFXkmPOAgCK1BN9AACwLuPqMUcmANWRKdleaOQ8ln1WXd76YWPY25walljUQQz9aY77xmXEjXxLqQuiYnKvqAe/Zq1wDDiQFixkPFWe9PKqsnNlF1tVBA0Gmnr8K4GDxDfA38NqnH3WnPbZlK427o6WSRcLvc1hHnNEXk0LjL2AbTmSvQ9nPpcv5DzoJSYMPHhCWrtPIqujOTsKSyItMQDqfn1OYrxsW7Z1SGFhmOWCi46+Jv24kr3XkTc7m8h22pfmtKs51l1WSTLc/r0iYx0DAEDfnBUVnXswrOxqfM0RL87i21k2jwMw73pJ3a25pCIo1bm2h/7W3IVK++I8BQBYZgwAGhNKvO3Y0zQw6lFr1X02Bi8kc84jJgzNq5aWhbgntgLHJ68mDh/3c67Xwc9d3Xa7yu44JhWleb/CWNxsYaxZGh7qVlpQbLPTJxXeNgxwcPTYB9gCGlSmU1xeTfigWQD7IzV5riM615oVEpZLkv0ATADMlMkE0AHb2UcimK6FUaqL9SzmmCvMHOPOXvbN8/HMUoMg9NzngeM6cxg/IKvYo9jfJfWh95HTSa7sp5T/tqLk2IP1hNg/LqVwUCCpHnnZkYSY9wrLwrMzgkbFicFkAgAwxd5bLFnT3PKxpuESzRqb5XnIEX2vrl7RS0B1fXcYbv18vrED8wN17UNXIb42tJEY/UxXHbhKJMT9zmoGFpruz/yEuOSwgprLjx9rTm4RCfG1EdfH/PxBuR8umvs9nxKiKRAXCZ2Tb/fP9Q79qpOyiIkl36+qzEpOOdtOjP1QUx4Tcvzr/gV+ygLQ33bobVwk3Hz83uPpWubX/x4Yc5kYeDF5yjz+cD5QiIvs9jZN8p2uOnSNa8zfnkXJDL1x0pMao6/3EQk3ZHzdv5ip1Jz1EQlxUeD4Iuq/mbzJ53T3UHXoSgNEQnxt6PQNTFcdGpA3SQ12nX53qtf8seas79pNh9tnyPHjGYtO15AiFeKiTSlNPzye+FXl3rVCfG3oF7rRDx81RawRCfHA6Y020Zjs9+fJ0vaUOXrQlHPg0MlG3Zyq6ynsmNHMl/+S0KgJAJ6TYEyvbynu9CoAqBtV9AKLvr6lUgnAt+XNqZtswsCe/J2ZlS0XAPSKHuoFHJboa2P90+u0E5OO8T32xsf5jpnr6JMn7kipnGMFGf2UBRqkrPQPtgLo+jz3Kjl1Guty5KJgx6nT0tNcVKp+lnU8bQKeMo+cN0QWAJRa+UTgGK04nd1mF/XH9cznvzVTd0tOdQJLvFawqGMOBjbZxBJm5ektZg8bDPaGYAkL6IacCs2UvlhaUVTC8JVO4g5YZvlbJkBvp+qJuiWvZ+f2uMaF4NPlmKz3t3OUXZ3u5VWdjQktVoNddF6s48R5MhO2x15/C6Ab0jNbRhJgJg7x4QLIc88qp3wpDNrSQq3H+5Ol7SlzZO4YnBgdsG724+mnsmOzYJ70ktJe7wIww62XjSsioh8AXmKZLrSXR1nbCWBuyZvrrNLUVcjimb2AM3kGuvs745oOrVXpF/4pC4QJd3OYCwZEZW7dFNaKVhSVgI90Sjt7vyJsq6yoF55ZHc+YgKfMI89KYALQI9f0TRDp6vRyZkCkhPMiNGdNQ50OQOBg9Vy8iqZ4cKRkRHuYqwMDBACdZ3La6Sl7M7dEIZP2S0z5q3kA8Pc2zfjfGtSlGV8KwiKcnrIzc78wJl0OwA/+0GtyR9VyVzdzALLu1K0RfWNYbw+0NQFdaV5j7xTm9lZ+LXen96SuloXO0ULYsWeglw/lX5MAK0Svj23RPfJGLQD2ppuAMdiPLoj1l+ypIYHWVKZ4OjhK9jeP1BKlrs/dH+a5XrzS7h3PffktE6uK1lwtSd3j47JavHKdV9DR5nH95QdyFQXAs7SYv/eJ6mpu0ALY7Q5ZyQBSnhXus9ZGvNJGvNLGKyi9XmcAoNQFsUEugx9ulBVN9JGTivK0sN1h/tvc33Jw9z8ipwDAoC5LT5DtDpK+6yOrHqxeWlWcFhslC3rfR/KurGpCyJ+B0lyryIryd1ktXungJQ3PrFLTE7optUejg3aHSTc6vvWOf+IVPQDoKqNdHLzSVQCgTncXr7QTv/W7TMVIX7FX3daqJgEAyMZUn7dcE9oAoKdQ6iBeaSd2iW2ljEuk0U8B6NO2VRemx4V5bgwq6wGyoyJ1l9dbNuKV7/jLCuQTu6E9rQVxYf67wqTu7i7bo1OPZqenpsTui06s1E7uaFoT9AEXoP3jos7JrJW+OadVFDKl+4dWlOc3kKD6PEay3nGljfit9T5B6TWqvkUzvUYl4KnyaPqaLQ+AUivGWRO67WS+6p0IX/7MKdQ0laRH+bvYid/aGJQ4ZhxM9Shri7MT9/i4vJetomhVdWbY795ZaSNe+ztZVtMkpou8W5+7P0zq7v6WjXjluh1HjXLOky0Hfd6yEXse0wJAW5zrW+u9pKnN5HMl5ib83wU7YqAvy63TTVrFxSXgI53CG8cSCFkAhOJbYly2m7JP0dsiNz+l25JuOXFSAQAOgb4rphhJYFzrlwGAVlwdM0tk7rrXnQV99TnntZMOLivztG47xVPY2qfNEalVtnQM17BRpmMKOzZ8Q11rYeLuIP+dQdLf+Uh3JWQ9OR+2+P7L/sYoO1y0KUc1dra6UuYqxEXbTqr6BwaIO6dDt0iEuEgYVP31heRtWzwdcNGmP18nBgYGBqh7n8e/K4k6e4cYeEzczvET4iK7kOofxsyzX0rxezso75puYOBH1dmQtUJctO2kZmBgoL/tuJ+rq90qkRAXCVdJNvkEBsoyLj2YbfJ1pT7j/Jc/tBXHbF77dlje7UdjXUGhdrhI6FP8w5hp/MoAkV1I+Q+Pn/SnhjpIDt0mBgYGqO4vohxc4wcn9Imu6zk7REJctO3z4Tn6H3X3rp8OFIuEuN/ZB+P9l7g04WzdtZvXG744nRLiKsRFQtwz4cLI5L7uUqSrQ2TdD4NeigOeDmF1xNT+oXufJQducRXiIqFkjDPsUbUfPtEzZGwijXtK/zfVOQcCHXCREJdEJEYEhsUfzsnLPBDqgIuE+NrQ0ewM9KtOB4pFbx9oIgYGBh5rSveuFeIiO9+oiAPFX0/tHvrh80AhLrKT1T15yb2cwIjzk/tCiDvlh8OkDrhIiPudvKMjCF339eKYDSIhLnJIvL4IbrJZJWBueRx0bTbI1gpxUehYJ5ym2G9DROWMTqIHTZlBnttSqr9+oLt3OWPbKpEQ98z8ZriFXz6dEiYR4iKhY2hCZGhgzKGcE8dT9noK8Se9X8TtnFAH58DDF1T9AwMDj4l7fz30Lm60/7K/PcFZJFwVcWmxPa26Ut9J/JeTpjDFVSTEpTnfPPHVo7qIHdO5XQcdzA6JY7x6j1WZWyUxjUbklqjzw9dGfDlFgMWP1yPWiIS4KPACMV3zCBMJcZGdbHyTU+W9i4uErodu//hEXm8e8ktsmuaOc8zRY03lnyPedRYJcZHDh0O/Nd50TGrHBn23do6hJwdjUB7rGg5LhbhoU2L1D4+fqf9S87WSAmAvwygAoEjVlcLEHdKYOob9nrz8AD7WJy9tZkcei7AF4LDlp245Hv+84stbzTWxYiYAeSU5KEnufDDFV8gEE6atb6gbBtTVwkb9cF84K0h2kZ+UHmjPBjDle4d6cQAUpTUqA2A2oYWXL5fs4gKAbVJxzWd5eUci3Mzn2B1r/FOo/3YfFzuxy/tpl0zdfTc7vj5m9oDjunMDE6CzprFntGtf1sn9QOY+0TFAKQtOtBKvil9nAgCDtyXh0AamngQAYL4idhOPn8gwZQvsXO15k6XIDPf2drG3Eztt8Y/7uLwwxBJAWxafODQMvV+TdZHgid/kAIAJ2yky+ffmxDQL2gRbI+JCXYyZf5tdImd6CrZCEhwX//vlAEC/5Bifdyw5MjgwPPF4SaQlAN1QdGO4n6ivSs1soSyDdzkyAcCE673X3wKAovGoOKn11NM4HPfd3mZA1eWV3h//RW99bhMesGHSLi157y44RUa5mQEIXJ2t2EwmmyeWxh2QsACIv11QTNkFJWv3OK4cmmmY8t9bOytmWmMwuwTMKY9D02sCOx4AqOT60UFbTiH1XoTH9H19g7ZgjyxX7RgXKbE2ZwtcQ+O2sAC015VD1cVz9Y9L3G0NAAaGbVhG3sHo4KDQuKy8Qw4MAHnR5dGhieq0zP+Y2iMrO3IjHwMAE6Zgo7+3wHhvi1rVC8DDBUa7dTRFQW/NVEcrHWSN8zVQxfCAXZYA6oKC1gm3VBUX0t5+04R6svg4B4DoVI4Mx3TVmV+Y7f6jw9NOXFLq+vY+AOC7rZzmVhTVBwCATUgh3zNkHQP0FUev6Ce0iqq879wCpgkHmGuOTLgee6KjtowzO0abjimaQXFMaLHaNjYpwIox6K912pcRaQXd5Qn7irVzK9Ul89FeSNUtLQCbdSvNP+crlb6fJbCxEcnyjkjtzYdm/AOCcaojTQOgU9IeJ104JgDAGHzhE2JriPVpITbDMwamXMEyAC1N/AQAQN3K2FegtU3MG1kchr3MZwPo+vTUYwATAKA1nXoAtjX/KWdjGU4fZmeIGQC0rrOu6GhmVmxFVq4kKSthKNre1Ob377Aqy+VlTXrvrWwA0NWVKISBB62enOugyD6Aq9k5TW9GrmMDMJ1io8e0jMmebYSK2QYl+Jb7F/W05lzUeuzgQj9JA6hOfFzlEO3xCgNM8fBEfNoWyRTYiXhQYdRysTkmcqqnDK4f+LWNzaiR5q1xtABlN6knDMA0ASCVVbcATPmCkVWAPJGVaX733S8Vff68ad41U3HA+/yyLOWpT+S+Y1ZNqEoLCe9DttgUhbnFC7SFqb3AcnhzxLXDfBXnQQ1BU9SU3Q6m04GSCzM6bRlszoy1OasEzCWPQ7CtLDFQd7d/RwKfCUDdLUm/JY6MnGkq1oTrEUr78cIAACAASURBVBOPUY7DN2dw+MsACIqiAIYrA8MwADCztF0+0jTYqzfw4aqS7CGpwbAAfU3qUTkIIgJWzjG4gNIoNQDYG5bGLxXjeR06t96ISpo/Xxpvc6hblqy28uNL4eKxSxJzm/Dg/5iuY4LxcAGArkuu6pNyTAH65Lk52t8ddn/6NWx0l1IHAKavCaZZVmvQf60HAGAtn7Baie0W7MVpKmnJPafaOLoyhLpTWMb0y5627cw9R0zuajEfK5igZEaYjsnbjTznYzkA7j02esiE67FDnB7X2nayUOEdPYclK/MxvqS0bSoAM8fgxIySi5dv3mqu//x4RuywWA5DdMp1AILNfmOXRWvO59X2Mey3ikab7mOaNgAAk8MEAH1tbokOcO/1Y/JsAAoAlnKHlnAZ9Pe0NADXljdfa8gYHCtJ+LHTGRtZoKpJDM4e7uwzrL03cQDaKpp1g12tUr1biPsklhGz+uA9PoC6YI+7JDy7Vj1PQTEY30PMAgDNLQ0FAAKv39sA9FTEbPYKSq9R9C5W72i+nvJL5rgKM5CUAYAiR3dlMsFYDADsV8yZ3jSBV6gzBrqK/NrRQVRz7hXL4I3TmSqy84YKQLBmTD+LIkkAYPOn2aQCY3N53Jn+sY1qirNKwNzyOGK/oGtw9b2+KqOCE7Lb3gip4Ii9fAdtjYFUVGamnjVqGftLzHFJ1zWVtFCAWVqy5yoAxH2lDoBnM5vusCl75jrizuuSXKY4ZPvEsFJVeT7h5Td9bwaYXGsuQJ9S8XBwPJrWiEfstJq0/dBtqe7jhsjrotuArt09fsJjW77KAADQT1KDRcGapuQfKa93AQDLVjxx7ghb6R8sBFCdyb0+MorTV+UpnYMcmTBfOXqyl8aYi+mYYnjd2Atgxuf9YnyrFooEANBzo+3hXOp5PvSSVLf1ALz8Jm+6lkGrrqkBLH3dx3ZO9C3VSgDe6rF7ANF6lR5guciaOTzmMMfHTsdROqUegCXEh95AStP5AIBtKfjF/Fp9tlvwNgsA0J4bibPArLw8zAHazzX2AKgqysArwG7SimNYhx3P2+PIAei+ki/b4hKUJ5+PuR8G69VfjQqSCTfgWGHcRi6AvuV0gtTVP71pUULEFgimpbMAwPBV1UhUS69S0QuYo/tvZ5yIYzsGe7OBas4pUw8PvM7oNvvbTvdDuvu6EoBtazW6LJu8e6MbgOM4210v5jgAmF0C5pJHAABY9trrTIAeuYoEsvXjXL1XpLuxgSRUj7zsaEJQSHJZn+iDbfw55FHfqQUAzHTO2kTr72gBGAIh+/luvgxrn0B7E+guzrveO9ybqbMMnrGoTbi2PADQtH1Pg74+6zNWcPhUgsSw3pN3obJi9N/ZCGsA+8TCcR9mDS1ceWkwsP8xPU14C3mrpg0AzFx+9+TmQSbczSFDgdmDc0VUx5kyzN93BcxfjhaSRxpi0s+XclmDMvLjM9JLSnNDBcB6gz/dfhAGTXsnDeZi22XjB6YaAGBajJVDVbPCABaurjwTAL1SRQGwuGN3A9G0tBLAct48HFxOau+RADx8/ndwedmKBwBAaHqp0RGeOxtAXtakVVTUc3w8p9xizYRtH5xRfzkv0pUNQLdk7Tt89ekVk6YIGgB4+HDPhGnpe7ji6tn4zQIAg7LgDylVL65imvB9E/wFQFT+KbtRD2DQ12blK9guSbEuRrxsDNv3A60BVGfyW0gAsrmgjhu8efq9hYi223rALO1HpyX0DWWtAJbBftNsRzVf/ss5JGAOeRxqtDY8APiuRa0sOtK6OlJq5L6AmvJoycagAkpyMCctzsfRYm6rwjAGABBdD+c6x0KplHoAvv1sZo8W2385iLl78Lss6KvPqtYCgKbcuN4MMAU2XAC682t1y4ls1f8X4TF1+AVmxuW9Mubfch4GDCaXP+5D7tDrwliOWwBAr1ozVTYN2sqCZgAQvO9nP1k6hwKzb+UXddIA+toc+eogY5RvFjlaQAadBb1a/U+TJ9Ji6QLOnU2HXtlJAFivnFawSGVDF8A6fNySD8Og/YcxPhG6reyCDhMf2m6JAVAUSQ3O1I3+RF35hRasIoKHB3bUg680ABZi/tOsJJu8C9ZHEAAAbGvzkUQzBO4STkFhW1H2UXjNd9fknUfqbkUZ7e4rZAAbDzhSYZvu5X9a33hFSzmM2kGKnIMBIRRyPYCl99tcANBUl3Q7SO3NgCn0OvgpLnjfJ6uz9VIn7bGOMXbu+ql6QkYmcp72tWfaRZz5bJlsZ6Zse7PtCi5HGH3uvIuxUR5cSfjGj0Mv1hy9HMohz2jc4+2n/2GfskUNsNxx5P5Ux5mjV8F6T4L3K9OlcZ78l3NKwGzzOATL+g0WdBKNOcnY0tDTYuP6+mTz4T/V60wck0Icn8KXxrCw4WOgpeQVLb0ubnPYn5bSKjQATP74hd0zsPj+y8Eb2gf4CcqzFScK21xdyqq5wTlG7QbJEfIAtN3nM1PBMursvG0divElbuaFBT2dVbdIj42TZJVsyj7aASAIPOQ/xcwBZukbIs7d33oqr9U3QF5kIj1i3LTqAuVodtkXuNqa1DQYlLV3aTfxmGTr1HoAELjazkkvn358Saqa1AAM3ivsaXuJN1QAAjvLcfWGsX/LBgBty8jiVnVx+vl++8j4wS4JtvQ1NgBoRldb684fPtVjGX7AZ6SPTNxXE8AQrBpummRr1k4vye7sNuM7jwaaogGAnjBzoWs6pwAAod/Y1UsYX+JhDnC3pk3oP+X+1D3NuUdG9vtgWK9/EwNg8oYcOxibCQCqi80jy8/JzrrGB5MJj2F83Ie6pqgdLHZE+74CADRxqzC9eHg9HMZzErMBWEOdJpPBbv3Dzgf0DP0DEwwDAL1aM74XZlQijX8KAD2zspKKyuyYfyvhHKi+ebE471jGwTAXwSzGNMzVwdssANqOJCRWcgNmHHhp5J0UsPBhv5q+fv++Qso9OSNohtd73vyXc0nALPM4bMd5Nr8GAF0r7S0zeoMCSq+hAAzae0N+cZp4RAEA0LSx3c2hMUqgNxuAak5MrdCMXPd4cCcTI3paP2kVPQArHHmzMrrz47+kB98+yvj1enxp+HoG6EsS92dq3APtjdNj5itvWgBAVysrIHQ+l/Njlh/sc8SAbjia3/bkkmJtRUJcDWHmknQsdJqwF87Gnd5mQF1Mi01ttt3lamTjmXuODJM0KCNMx2R2zMwxeDsXgLhUMG5drKa5vhsYzqGeczt94an1Ut9cdI2e6a0B/W05AQyBJXvCFJzHVksAfVVGsYIESlufGlfC2ZOd4TNsCMwdAxwAqObDBXLSALqr2bF5lG9WRvBoN2fQQcIf2YePvHUy95a2++rnZcbvjdSnbtMBACiaOqlR250WlCqHFdKMI/688RsHe2xkA3B/7z/1xk5sHrSmyY4PBpeTbRe/osy9ot4dyhTPQWINAB1p/uFpWbnZifuCZKcfcpgAoC47kV9UqRwVerIut3ToT7KzRBaSTW5Ozts3+FwGS4ApjslS6/SDWbjUrGet3+07VDJsWzEbgKhMSi4oL8k9mDl0+FEfSQBA30Nq5JgwU0unFQCG5tQD+WWl+akHSwaDBYxLpNFPeUzqfgQAcqzPgCIe0gDwIznkZjDoL+XkN6i0l47GhMUmJO5PSdyfkpiamVvaqjFuAwFshTRYDNArJ9z9ZnxLdR03ugEIeU3VLbWqtST2f6XptmQUp0p4i7W3/twSMKs8jg4w3+CzAFhbo2Z2Po2wVOwrBgB1erAs9Whm7B7ZUTkNAIqTaampmVWDMYykfmJFAxAPKQCgHg07j0zx8H8PtDYB4mLKpm2yxKP5WQcTwvak/bUHANRlH+cXlE93yCulaVUBWDhYPoN9iEh1uwYAQN9h/Ap3plOIFwdAdYcfsMXoowZetuKZACwPjNs8z6cTcNyTj++yhK7CoD8UtuiH3k0KQHerMMw3pVHgn12c5j39M03FAe/zAbQtptIPjD8gZa45ovv+iwKgyDGdMmNMx+R2jGG7NyPSgUE1Je/LlQ+2MbI9PyZHYx2QcWjjHN3hJh999NEca6O3Oeujg6l/LmzrBwCD6q9V9TflD15db//yk288ef30ue9X+IRsE1m8NP5NftP5Teqbm01leZ/WtmuZLn/48z437hgdMv3NujVLur76svxU3sWW7x+Lwg9Fe60YO+jou/4f2bX/7R4etIazZNBd8vib+muk1e/3+a55ecY+qUFdlHIgKfU/rhMAAH13zp36oqHxSm3Zp2WNP5h77P3wL5FeT6z8M2H9t/xTlev+XThris7GkqVvWDP/685fPzmef662rr79Jc+kQ/977UgF/Q/c8fWf7nZ0ftPx1Z0eU9Hvo5OC8QeXa7teFtn/hv+blb8VvGy6BFv6pqUZ/PjwZtWpnPzPv/j0TEWHqeP//vPBwFVLhx/Keg1/+adv68/+R3ZpTe2lFmr9HzNiJLx/GUok57eWjztabio6uyhzJ99gj9fptuMJe1PP3O0D6FfWXm578KtVzr9hwj8zrYWmnVdvKzruPTJb4xvs9eZgNKoxiTTuKa9/nR2bnFX1PQVA3rzS0oXhbkJD49GPYtLOqfoByNt/u3Yfs3V981+X2r+9ou/7jptfffv9t98qOpWKTqWiQ95ypaqw4ae17kbUJpgKfv3DFw3c+BSfV2e4mL5TcOzctxTrv7+t+bxWha3yif1orxv/l4t3GuycE2B8Hsc0yH9+WHOeDj8UvPJXxnekmdbOq5Z0fa3o6Oz5hVAambBvy6q+L/+m+Z+rPHYEewnIxsyPItM+HaroL781WK1/61cduR9+mHTq6z4A6pvGRpXhzXWrOP8C2Mtin62rlujuaxQ3Wu7Rv14jjfyjh+m1+gdvbHBbbWlrK3yVbTqVW+jRl9nH//b/3MJCXX69mIcE6WtT94YlnLrxIwAA0VZ26ovaxq7XPJx5M7qvlizjY9fKNFuSY9cYPd+3BL6/WP/rqGTf2W6PS39Xll9nujlA8spUhYNZ2HtLbU0ftZ/Lzsov+TT7YGb+qU9PlbSzJBF/+kukZIUR7WGpgH2n9PbaAwmSl00WMEeUuiA+cn/ObWIADN/XXbj+nYnNun+98hejTMdSmNyOLVlq6+61lv3TnS+OHcr6tLb5y3o5uMT/nz95P8XSw4EXmv7OlA0ihwPti3huAfX1Yb/AL3QDiPk/tkLXkBUVkVX99QNi4PFA/4+6e42nIzaIhLgo8K/zurnLY1XOFpFwTfy1H59VTp91Al4MqNsfugodUSnNk7FUVafsWCvERcJV0pjP2glUIs/ufJJnRG9nWw/L2X0RN2Im209d4/q+zQbE/EKpC/a8F9PllbxXYm3OBBPATNmCdf6HDks5AETfvJ4gQn7XogJYLhKYPqPMPvMEvBAYNA1ygvWO1BaV0rw4NPmSuE9qShK9BEvUlalBb7+XUtZBomJZXP/lM4XsbNZwPT/AF+20W1pVlNkmlC7OSfQ/K8i6w+lXCbaQP2H+G2OxmcB1wuezg0J936wA4ODTroBa0L7Bs07Ai0HPjUa9ZfAuHENFMW8wrbfGn7uYl+TryLlbkbjd1WVPZlUnUs2fhV6SbdVK613SRTuJW3clLezYQydvG/QCLxCq6hrV+OA4RWUN7S7buWI+n6K/LScAeDbcZ1WPzzwBz/VbrSdHGgP4DEaDI+YVM9w7NqPmavW5T47HuXN1nVokmEay5AVMM60qTk6/xbZdrm+BwKQt3MV5KtWZHRRe0c2WelgxULuZ/37v+t3BgtbczmzpTu3eHS62y5lUj7rl4rlGkB4/4DKfK+X6lKWlaoDpA7oXkmeegOcYqiNTur0QHCRO5qTisWdGEhpcLhgYW2DDFtiIUUkYzz8NDAy8aGnW10btkDUxnH1kcWEuvEV7n7QVsqA01buFJWF89A4vzMhCXXUis+DiVwotAWZc65ViD//dAQ7zOROrKY4OPVI/esCkuSSvPNl+Ed1jzzwBzzv3K2ThabU6ntv7UclBYqYJKhEE0ksEAoFAIF4o/hkVAQKBQCAQSC8RCAQCgZgHFireh+pVt11X0jYSJ/PnLMektu1W6/XWr3RvBMZNEStE9SivX21tuf0d2z86YAXjeUq5khK62LOfo7JCIBAIpJdzVcq7hfvCsxu0NADD7YSrk/nzFE1KtmYlffzXy/JuA1gESIeOgJ+Q/s7C/ekll1q1FLA2b45+HlJN3S2M+beTtXcJANbmE472bMZzUlYIBAKB9HLuYCv8j5c6Fu3ySe2Yz9tqytNSiy40dA5uscvgcNkYAEX/F6EnKAAw9y85HzHzQkymOPyweOtpn03pUx4Wj1n5Hzzh5bTTNebWImiSPDcps+iifHAHfcycL1gKVB9FUsCzkfj6Sz1s2INFmnHGscDPJ/3uIjYNI8oKgUAgfj4sjP/SlCfgzfMYiLcl+vhn5RkOAACsrdk11RU11RX1ly/fbK8riXNk9WkIo09hZDBnXM6HsZiLMoZj4sGH82pOerEAwEScUVpc8lnxufMV57JCrdX5Me+7S4/LR07sev1ZTIgaUVYIBAKB9NJItBWxu7MVi7H4GuO98aTvjmm9NSJAQM/iAObnbJMGjGfJAwBgwPBqM6aVJO5whABAkZNyanR09yxmtpf8gzZ8Sl2wT1ak/Tm/+2Tb8TBZHdraBYFYNL3skyfuSKk0/rDJpxvtYKaTaYYJ/3cxgda/eGErwYQ5yUQyV+xsDgDqS6161EznG31trH96nfbnvMGOpljmn9Oqf4waAwKxaHpJa1WLac+nGO5whDjvxQ1HmTRTSxisXwIAUH30P2rjo3r1pOFZPNhAd39H/7xffJpQaQGBQMyD/hgF2ZgaJCtVUwDQUyh1KAQAzsbjNQfFo8r1mNI1FaYePVPbSWBsS6cd0ck78PF7XNGqyuys4ubO7zU64NlvCZ39Fnd028HoNr+MgJF9mfvUVTnZRfKHQJEEzbRYJQneI7Wd6kQRSl3wh7D0Jj0AsIQu3jtkke5P+Am1FbKQlNouAGAI1nsF7JV5Dy4yobS1edlFV5SqLg3FtvEIigjfYskEoHqUjVfqGq7UN+pd8j7xJ4oSYnNaYX10XqoXz/j9vSi9SgcADMEb03kQybv1paUVZdXNKpprv1WWtM9l6BF92rYrdbVNXza0UgGn8zboK7KO5Je1aim2pduO6OQAfOJNe5Vlp/PK6r5SqPQUk++8NTQu3GViao0pq2F0rYVH8+pVFFC9JCyzdNoeGuI6tL04db+5rLymtu7LFtWvky7mOz2ozj36cVmrnjKzdNv5ZNqmaCHjMpjtdDcvNqlQsdTr0LFoJ/ZQAbZVl3xaUXPplhazkgR/GB1gwwQAXWW0T1K9jgIAdbq7ON0EsFf9Cz8dDhabtvEYW7MGdVFsTPpFNQUAwLJ29Us6GGiNAQBZGx7UElQYZ8MAoBW58amf17f1AADbOfb4cV8+AJDtJVm5NS2q7zS9DME6aXhk4DQrssj2iqzsc6rHlEb9kGHl4maFkXq97hHY703wHWyi+taCoyer5GqNhmBZuX4gi/a1Y4K6MCggs6UXAKAtynVlLACGRxbnBaCdzRGI6XnaAzQfVfvhIuGGjK/HHdlMXYtcK8RFm8IiAmXJmSdOZ6ZEbMJFQlzk95lmzGW6hhQ/vz/XdfcPDAxQ3eejHHCR3d7yHx5P+bR7OZ5CfPwB0Q+aEjb7newaPhNVcTrUee2mA3WDN+lXFIc6ioSOoTl3qJFf/HA+UIiLNv175+BN+m8eenuVNOXy2COgqYa9a4W4a8z1wV9R945Jha5RpV2jNxkg2jOD/GK+UPUPHnSc4inERX6fqPoHBrovn04JkwhxkVCScemTUAfxWiEumu7Y28EyXBXRMOaCH/4aYYeLhJKRgp2QpIGBfk1lSuCmgOMNKl33neqEzeOKt/+b6pwDgQ64SIhLIhIjAsPiD+fkZR4IdcBFQnxt6IVx510TX2b4bQ48fL69+4Hm68bimK0ioTji0iMjy2qyY59TpHaOoScV1NCfh6VCXLQpsXqoUlTXK0/Gb8JFQnzttqCIiD/nnfwkLyXSzw4XCXHRpsSmH4xoIWMy6Hfy8vFta9YKcZEQ9zysoAYGBoibeaGbpTGft3c/UDWcCLXDRULn5NsjxftYc3KLSIhLT2rGH6g7U+OZVc12f+YnxEV2kddH26quOnCVyOHD0U/6FRlvr5LmqIZ/cj5+W0jeNd3Q0wPFIqFrcsOjyYv5h/NRDrhrxHndwMDAgK4uxlUkxEXvhkUl5FwnhtpAcejWqLN3iIGBgYFH7Zk+IiEuPdw21KS//rNEiIv8LqBjgxEIY1lYvdz2iWrkY+LCoAAcv/d45IWPcNiSN/LnQH9niqtIiHtmfjODXgpxkZ14rd2gtcJFQlw6pJfE9QTXiYkhGuMdcJHQNfkaMZle/tiessUzYaIAjBOn/m/ytm2IKB1nW4mGDyVvj5Xtrrx3B43y4EcPyrfhIiEuCcy6/sPjAULR1PANNUMZ4oFn7+j6Hw8MEJqGT+I34SKhJH6MQk+U8K//LBHio6aW+FuEHS6ykzWNJumxKnOzSIi7xoxRx+5P/IS4SBhQPWIm+7/J2yb2HDajgz8kftBRRpfVEzpxNlCIiwLPj7nsseakj0iIi/zOasanTZqjGn1u91/jBwU+4SZlVAsZuolo097Tt4mBAV17w5ea/mFZspM1EcPPytk8ppFMpZfGNZ5Z1Kyu2m9skxgY+OHzQCEuEq6JaiBGNdUhoHyof6A6vc0xsPTBmEYoWyvERds+n6zAiaaINePepkF5fvvwUM9moL/z8GbXiMujckicDxTiImFYHYH0EoGYEwsa/sjgWY3OrTIdvGyhueWhWkeBwBSAUp7Kaib0X4VtqWGYMlimLAwDarnYHrdctXSG+7K25tUnDh/009Ocuit7aA7wYmaZHjg7JIIxM7pMsb+3eU1BT0Xuld32myeE15ItR9JUXhnHXafeModSnkqusz+Y7T126vF+RValXseM8brNZP6CgWEszIRiicXO/Dc5gyWKYRgAMEXBAWKOCYCVo9PMxaWtzYk51d7ZTb5ksfItp8iM4O2OnCnnbxkCv/i4FczN/OG/zfksaNaN88phrCUA8Gsbm9Hc8dY4WoCym9QTBmCaABi0ZcnZCl5ExsoxgVQmTM4k5WFEWQEAJc/5WA6Ae68bc5kJ12OHOD2ute1kocI7enDm8yUAAAZ7TAAXzz0irrQmplVfW9kZZ4djM7eQwQyy3cJ8bJkATHxoJpbtuDcpWm8jHprXNWEL2ABdFD1tbIuxjcf4mmWLvG2grb25qpO2tWGAQVtbqbc2B0VPc9FV0mkjE4Bsu/h3662OHAAAuuXESQXZfzTAq+CXTMwUY5liQNnYr/uV/WTH4VB366/3AVhZjbQQtlDMAaWuVa43WPJMQFeXWdBFYAf9JUcx5i+YmCmGAdg7OHLWvIaOo0MgFt9/OVv1XMZhAtAwZNK1zbU9YBFyoiaM/1S3NRd7b2lWmAAA2V6tBAD2G8vGGRiMb2/FKOih25rU1Gb2yFcUqa49mpbaJM4rn+p8rn6iq7ngdFoRN/6c3Tifmu56jQJY3lkVSXbTGh8ml2P8UU0mlgEHM5yMvh57xXHkKF3drZLco+d0xvzsl+MXlmrritoBW89nT+tYNaKsRlyc9Y29AGZ83vhwZY5QJIBWVc+NtodgPaXTk716oyW0KomuhzQAZmwLWcZbOqEWmLabpcMqr64tys5qn9kZP6vGY1zNsp28cGiX11arI20sMW1dFUiTIuX+UfUNxc26jRIOKb/UZem9hg0AQHVWNRFgFV/8mRfHmHrsIygAoIh+gMGmiZkyMQAwZbJMAIDsrG4HEGeUHndCC2gRiHnime23Tj3o1AEQGvKpY/oZ1kHR3lwAA9n9cDDa4gm7xWUBANVL0+MCUs4VfS4ntIUxx+VTrEGjFdUln17R66pTDl8Zewmtv/sQgND0Puv1CJS2sShTtisstZnhFrCJM5dakGsAqJFOzJTBOzOW1TCPNMSkny/lsgAAKN2P084ccNkYALb0V4ynbiFkR03ufllQ7JluS/8Am5munmXjMRLOOok1gK6uRkWB6mI9tllivU66gQnQWtLYA1RnTafAc/XgmPgnraoXgNAaGTCMrXC0NgH4tv66fqRjINcB2LrjTAAwkPfu0wBEdx8ycQjEi6+XgxDyZs18rSgwYWCDIYFdDydaWMOgLR43tLJwjcgrinc2BVXBvoTKSdfEsOxDDp0+ImGBvixKVqCmJwzLFU3qZyiYVGdh0DtesovMgCPHM/Z62Zo/xXqa7290T5sTI8pqxJBjGAD0avU/TT7itph2sp020BSAwG50Gn8uLcSgr03ycdieqVoTffxYfMB6Pmu+G4+xsB29rQB66i59q6y9wvRezwZTm99vZgPIi+rUbdVKgZdoXC9H29xm5Oosc/ekPThQzelHajQGgN7WnCPNmEN0ktfw4N0EANSNHWg7AgTixddL7FUxDwC6Pi+4OptXejoXFNt+HRcAdNfk+nEWltLc1wMwVrs+MZfI9Tp02IsDRG1cWFbHpOMHjOOakLeLD5Q8PSStsXdoRGsh5AMAUZlf2zMfZTGUKRpmIQz6qkOZLSTLQ+Zv+xQTbthysQAAtOdOtc5UCzOXFQAAJnC1NQEAZe3d8dfo1HoAELjaTquXug4NgKX3eu7cWwgA1ZmfWqoG4e4/unNn6EQYnqLxGNWH4zpvsQTQfpGTfWmZlzMbABi2Wz0tABSfZJ+6zfUQD3t5f8G3NQcAZe5ZpXGdMIYgKPvCAReqMsF/W1BQYgkEFV74WDrkfDVhW7/BAqAbTlTM0NswIBuIQCyaXppgGADo1ZqfjJS3YTPKdQkQAwBRFiXLujrcqe5Tl6Xnt01pHunBxftU3+QmReATaI8BdBYWdY4x1qS8LgO1BwAAIABJREFU9g6AwD9kOP5jbKqY66Lzwi0B1Lkh8VWTix/DOiwjaR0DeipkkSWD1ofp4OfGBKCaY8LTarVDz6Lu12cdbZ7gRDTK9hlICgAM1CxGqwZSrwcAQnN/aPqTfkRSAECNmzakZ7SJ5pIQVwYAURkVkztSCwayrSAt9xY5+7ICMHMM3s4FIC4V1I0tCk1zfTcwnEM9BdM4SvvkReVaix3RQ6FVRrSQyTOo1+oAQP+dnhrKjq4PAICg6JGxF8YAgIedD+hZN55Z1SwAb51EAKC70srbKhq6hcDr9ysAtPUN5hLnkaAozNL7PT4AdBeE7Ts9MulNtp3OLLo7We+kT12bGy/LofeWN9d/kZeXlRa5xXJMEhm2vps4ANCRGZRYoRqeldU15adXDm5TwBgsAv23aPcoBGLR9NLU0mkFgKE59UB+WWl+6sESlQEAKJKkAWhyrO+Jfkj0AVAkMfT6s72T4t2YAH3y3N3uLu+FycLDPN+VXRd6Tj1golTf6gGA+lapn1QDzL0OHpZagLZgX3LV4PSpQVubnnbJ1CUpK2jk9BLyIQkAhH7oqBNBQEbSegaQ9TF7hhZxAxC6XhqA0D2iBkcJ3qlp3mygWtP8k+p1BgAzx7hULw4AdJbI3N09d8lku/0lQRWczeKh6TVSTwAAqSWMMKtUl1IDAKBt65rGR0YQg0kaLFITvtu7fABoSQyLPZKdGhUmK9QCANzKTk1Ny7qiBwB4TOp+BAByrMuQIh7SAPAjOexlZLrFpXlzAfpas3a7r30vLCw8TOq+JfWBo68d07iymti9sN2bEenAoJqS9+XKdQYAALI9PyZHYx2QcWjjhNjav9deGZ7TJpVFcTGNNvF5+4Yjn2dsIY9J4okMAgBm4+XGBOgpDItIyzqSEhaS0kgDgLYsIy31YImKAgC2rZgNQFQmJReUl+QezKztMbbxzKpmAQC4rt4CAKar70jImAnXwxcHAHsvx7EtXeB/KNKOAUA0pAe97e4ftk/m/65Pombt5klPYO29UXCsXqFtPrU/WhaXkrg/JXF/Smp6dtEVNTlUCKFHAvgA0F2Z4vmOl/+e6LDtXj654OE6NGFrIbZkAXSfTEgtqig6mpZ1Fc3cIhAzDQ8/+uijpxNcprXQtPPqbUXHvUdma3yDvd4kL6VGHTh6tdcAoGlouPOQvdqB33shLTY+u+H/GgB6ai+2PTBb5fIbJjCtJJ6rTH/s7fvxP1X31Ppf4f4f/SXSefIJO015Wuz+1Lw2CgDg/7YUnm+5eVP7qrP45X8Zd9kvX3OUSlbA/eb8I3/Jrfryy8tffr/c/y9HQtf+qwkAgLYmNfajQyXfUgDUN5dq2x9iNo7WZqbWDlYPqmsUXfJzxQ09feqKY3/Ja+8DAE3dpS/VBlsnfOmvlq8VGWpLb2s6L3166T7H0VWEO291Njc86iXIB6pvtfCbrfH//m8eFiYAtCLvo31/OqP4EYD+9sKlNsVDs7dEy385ac+kpz49IWV/ZsMjAIC+ttJz9Tdv3H1J5Pz6uOBLqj0//t/SjreRAKD526Wb3xneXIcLRC6/ob65o+z46qGZ8/vRcSFur/fUf/njcgdP/51uy/XlabHJWVXfUwDkzSstXRjuJjQ0Hv0oJu2cqh+AvP23a/cxW9c3lwKYLnfxWv/yfz969ON/PfjmW83/47mEHkrfhZsaUVaPljtPSCoAwJKltu5ea9k/3fni2KGsT2ubv6yXg0v8//mT95gpzYHem5+WtPwn9X1jSe6nVfX1VYWftfz3xvijEevHRepO3ULIq9kxHx4uU1MA5M3q2pvfkK/ar3p58AEv8R3tl/Z0KBVffUev8Ijc/0dfhyXXL363dOUG32CvN/+HCYAJ57eWjztabio6uyhzJ99gj9exmRvPrGp2zAvC+rG28deh+94xHwlG/+X/xG5eoH3/4CV4aUK5ub/5i179f/Y9Un/3Td9Sl13JGcH45HG4TKGT7RKNUt729Xeqb5SKTqWiU3lHfruxuuTcgxUeLvxfAvayg5fkNSD/s/eR7r6qm351kywj2VswHLeM8Va9+ujGlwrlHY1hxYbAnS7m6HxTBGJ6/mlgYACVAmKxMahzt/hkdfHDj0Wwv9Viq1zcbNjIXs8OUl6QWqhf4+/7thWPyaBIteLymcSkChXwI6uLA7iogBCIeWYJKgLEs4PBXuHovQ6Vw+zRVsgCsvQhnxVuGZrixsz4tlvjM3rlnlkUTaECQiDmn39GRYBAvGjQLVlptT0Ma6uJK2WY5kwwE9uYoyJCIJBeIhAIGAwJ1jee7xwXpWPQVpVq7cMD7U1RASEQ8w+aj0U8Cx4PrvEg9WgDmrnAsA0Ltb2c2VYU5PcwNGCzyNqM0quVlypq9OsOZWxFrksEYkFA8T6IxUZ3MXN/3rmGTgIAwMzS3sbKIyreGx2+OEuo+/U5WYV/vd7Z3UuzuJbWdq6+u/3dXkG7qSMQSC8RCAQCgXh2IP8lAoFAIBBILxEIBAKBQHqJQCAQCATSSwQCgUAgkF4iEAgEAoH0EoFAIBAIpJcIBAKBQCC9RCAQCAQCgfQSgUAgEAiklwgEAoFAIL1EIBAIBALpJQKBQCAQSC8RCAQCgUB6iUAgEAgE0ksEAoFAIJBeIhAIBAKBQHqJQCAQCATSSwQCgUAgkF4iEAgEAoH0EoFAIBAIpJcIBAKBQCC9RCAQCAQC6SUCgUAgEAiklwgEAoFAIL1EIBAIBALpJQKBQCAQSC8RCAQCgUB6iUAgEAgE0ksEAoFAIJBeIhAIBAKB9BKB+Dmhby3IayUX9hm0oiC/sQeVNQKB9BKBeEHpk6fvSVG9YcVc2McwLIT6w7vTWkhU4ggE0ksE4sWDbDkUU2UVH7XeCLnsU1ely6QbHVe+E5Q+++EoUyxLsm+OTarXoVJHIF5wljxXqdFUZpYy/cLXs5/XQUmr7J2w2j6jrmVtyas/gGNP8zhKnr4noaxVSwz+ibE4Zgww0MQjgjIAAFgnVpdsZQOA5rTPpnS1cTe1TLpY6G3+7BWraqdrzC3jrl0eeK48VGAyb8+m2vP3V3ODy8UzqiV1tyQmvt4iYGe4OTM1vU71iAKY7YiUYbsrVPBu2tGroiQHJrI4CATSy3kxY/KCI4VFbO7WdVKeyXNZWiYsjilAHwg2Sp3Np5NCorOmjc3EnvJxGB55omJve6bk/UIdWMaVF/pyh9Wmo1C2M1PXSwKwAYDBZA6OZby3WLKmueFjTcMlmoU9F2XJMmMA0JhQ4m3HniZF1KPWqvvs+UyyQV/1l0LdmrTN3Jmu7K3fvytN5Vec4c4HENdsSQAmYy5PZLsGux4O+ktJwGeBAhNkcxAIpJdPP+JoLanSA+hLLmmlAa88l6WFWfq+xy86ptYzJXsjpx47GrQFIWrbrfz5eaYAFwDoALAxppYp9I8LOBf2iKYAMADO24FuprJakrLeHuE7tQyQTSlt4Olk9jwUJXN1gBenrkRHcn33TTN2pBVH5OQ7knnsP1F3z+S2M5yyRDON9WjFibTKXn7k5uF6nJtYDg4xt7qwdp7JveV/UMxARgeBeEF5fvyXZEvRl2AKAOpPzxs1tUjeKilqX+w4CoF3oDMGRPnHtfqpE3Y9v5bv58Gdp0eaMLDJ1IK3QerGYwxptpk4xIcLIM89q6SmVvHSQq3H+1PLPKWuLarRGBar77HSP9gKoOvz3KtTV6K+LkcuCnacx2lMWlVe0w02G2xmumdf+6lyPXBd7GeeuyYV5SWN+mkzu8LFFiMaStspZHIQCKSXT0tPXcHdt+LiXDCA7vJzipnsiq4uwXNnvgoWfW6R7RrsxQZD69Fi9VSyVHlK67FTvNApw1ZII31HhrAM6+2BtiagK81r7J2qe5Ffy93pPZWKU8rc/+Ujq6YYizZhaMLdHOaCAVGZWzeFSNOKohLwkQrmsSgNmktX9CAQWc8kl9TdCw0kYCtFM82gki3pQdJDzTO0RKalEx+IqxcUSDARCKSXT4mq8oxGLHVbL93ABOipKeukp7V62tqcGh3oaz+SujiIV9qI17oHJZYqF2WwybDdGWgN0H02f9JFAtStwiruzs3cRS9Bc9e97izoq885r51cxfO0blOrOHmrpKAd4G5+kPs7K23EKx3cPcOzG7X0giaZuSboAy5A+8dFk1a3vjmnVRTiOq/BX3p5oxaw1yynmeDVXUyQ2Infer+CAKAuhr3l4C7Zld02VZCX/sapYjX0fXX4ffe1duKVNo4u2xMKWp8cbLKshSzolbf9gGwOAoH08mmglGXllJuPDca0+f07LAB9VfFUM1ek6mK2bHtQaifA8sCDWYXnqisKD0jZWnlZUmDMRf1ipJYrCd/IALLm6JOPM2jL8r5z2yl+FnGQTPtdfgIARUHhk8adai+sMvfbOqlXuKe1KClM+ocKAhjOMRl5ReX15RnhdrTqSn5oSN7CjocwS99dOIC+6ETzk30PVVkh+Eit53WcTmluaAA4Au40d+VsTK65VZe9ngHA8j7ZfOdqdc2JUFvTJ++lbcxL8N8e3UABZ2t8xn8UX6guzAiwIjpq0nfFFE3stDA4/GUAmrbvaWR0EAikl09hxeQlVeDqbcUAYFh7b+IAEHUl1ycdLVJ6BYmHJ3paAHDWONq+wmSacW23yA4FsAHolsqpvXd9rbHviFfaTP/P0fO4Ma5T5uogfwuAthNnJsgJ1V5YtWwKWVoE+J4h6xigrzh6RT9BxavyvnMLmNwNqFNpWV5RkXYMACu3dXyOGZPDdww+EGVvAtBV06hd2CRz3Hd7mwFVl1d6f/wXvfW5TXjAhnleWUR0qQkAJnem/oxBr7hPA/zadvnU4TkPlTq+f1KIJQDD2lUkYDOZ5pZu4cl7VwCAvOr6xL4Uy5wJQKvu65HRQSBeUJ6H+Fiy8Ww90/3E4EgCs/LyMC8p6GkuaiWdXJ+waxjfYyufrD7TDWAv5g+PEhgWNnwAPUXSNEzhSDK1iTtbsXemYBYG06iJVMxKGmyXn3irOKc5MGMkkQZ9VZ7SOTKaaWSujyQXqWkGVxIVNV/xn2y3YC9OU0lL7jnVxtGlC9SdwjKmX/YU4bocBy8PSpl+lwZzfNSrx+Rbm0OLliYoGmAhQzpNxQHv88uylKc+kfvGjcYiqUoLCe9Dttg8lyTdSwMAZjrTfSltmwaAjQumqUuuizeXbolSA/CcRq4zYVu/wYK7BPHTxHEkw5QJALQeOTARCDS+nDP6uqJry7zfHTbnmKX3Fi4A3VDcPMWWKPS9a0oArv2KUWPW/4gAABZ/GWMaKTTn8rgz/OMYO5HK9gjzYgFdm1MxEqtC3TlTxvT3NXIViYHsvlbfcKW59op6Hi0ottI/WAigOpM7OjzXV+UpnYOmjTHt7WzpAcxKZDGqIxTRBwDLBEsnLVFacdRnpsG6eOXGlDYj8ibwCnXGQFeRPxpyTDbnXrEM3sie/5IcVNMZY4AfqrspgOX469MLq0HT0kmDGW69bLTcaJIAAIsnh7CGMQlAIBBofDkHNNUlbculSWPGdQJ3L0FOtupqSWOPZJKdaAz6tg4CTNfajH5Fq1r/DsBY7cpftHhZzM4vYEVFVueZgjs+cTYMAH1Vntx5b8Qz3sHFhLs5xCU9vL4yt+6PDl4cAKrjTBnmn71i2tGUqlkFwHPgjyb+obKtF2CFxH5yzWJYB+XV+84kT0swjjH1wXYM9mY3FDXnlKk9gvkAoCo9o9scP4nL8KlhsZkAQPXNsE0P1S3XAHCE/BlG1qTyeheA2HFUVilty10AEHsIJ96fpkgAYLLRFj8IBNLLuWFQlxarBTtcxk2jLZd4r8hOvysvqtN6P7n8vk95XQVgJRKM2FOy/YsmAriBIdPE2fS1xr4bVjmD84ghCCk8F2bcCNGE7xvsmBPVXJZbF3xMwuo4U4b5H1kxC2Hz/azVdwFKlLkm6ANufe6t/KJO93ArojZHvjosdHojrbmtpIBl+9tRbdRcLlEBwzlo6ulNUybHdL5MP8P2/UDrojTFmfwW32R7aC6o4wZ/zF2IkmRw+SyQk5qHFEy3Z5Be+R0FIMC508s9pbqhArBY/dpIQVDf1lT1AGvLTucn+hmElgRg8F5hIaODQCC9nAvUnZIveqz2Ttgw1oS7wccyPVWpKK7T+PhPMNlUV6vCAByx1Yjh0ZRnVpJc3yP+08VSzqv/ckiZ1gd6mzcXNeV/cRfnnZCvDgnlPA9Viln6hohz97eeymv1DZAXmUiPWE0/TNIrWrUAYudXhy8jm4+eUGPi6LiNi7WRL1cSvvHj0Is1Ry+HcsgzGvd4e9OFKRueSAAVCrWeBsupGwvd3aEB4NrwZ+gQ6OVyAhjOq3gjH9QeL9YxXTL2Ptlxo3V3HwLw7F9F+/sgEC8qz9Z/STbmVeisPJ2emHTlrZfaAoDqzJMr84gOuQ4Y1nZDfX+yNTP0yN+dYzMiZ1jEMb/+y0HriwfstARQ5+xPyTFIfa0WxhQaaMoAAIP/GwVn405vM6AupsWmNtvucp1BxSlt412A5aKhmBWDtiwusfJfpRnpi7mLL3N18DYLgLYjCYmV3ICFW766FHcWAKWW66YpTINeoabB1HJUB6dovYpragD+6qFZW1qRF5PYahV+LMGNPdk9lQSYO9ouQzYHgUB6OXt0VzJTr9AsLvelJ78z41uzAUBfkF6sGucmIzuvqgFoRXVNy111W3laYFyr/cHTR3z5z2QXcd7mUDcmUB1q5xDXBRpcUl1yFQDAw3aV0fsxmIoD3ucDaFtMpR8IZ1LxH258TQL0NJddVqo6mwsiQ3NhZ+En0Yu8zSy2QhosBuiVE+5+Tgvn4zPhum3gQteNtmlm5ilNmwZghaOV6Qz9jJa7APD32opmhVpZe1QWVsmNO5MdPOlOe6SyVgWsdS4CDNkcBALp5azok6duf8clvEIHQFSHvf2uLPfu6DiSak3zdAoqGrRotzI93/aRFQ0vizRoWzppAAbVlBa0K+XTh+JDpYVxG7nPzAoxHcO3czHx7pllaU6llL7Lx2V7oQ4AgKjc4+ryO/9Y4/ZkEGwNdWayffe6z6jipOKGCgB+8V1RVGDY8RusHXkVWf62zyAqhe0R4sUxc4map33qpywZdy8ByKum2Xm456vOPrBYh89QdA/lbXoADNqOyYKi8r7mR5z7PNl7xeTNgLxT3WZge2y1QnKJQLy4/NPAwMCLlF59hf87KW3itKsnXFCg4XxAt6V6+RdDwGcVkVY/E9eavjbcK6YvoeaEZFJFJOvCHPZpgj+vCJ82eotskr29p5kXW3HOd8bZY7JxnyS0N7r+hBcHrSdBIND4cnGg1DcUABZ2ryGxnB8MesVtPZhY2vJ+PnEobLd9QYKO/C8m38qJvndFCVzJZsEM/YzuViUFLFtLI0KitDU519jBMe5ILBEIpJeLh+a2nAKGAGejmpsf+tSNXQCv4gLTn1Ou+f5J26Eoq2aSDTEMmoZbYL9HOtOxJISiVQ/w2nQb5o0MLrPy9V7JIVYoMhaBQHq5eOgVV7UAvNWvouHlPI3Xu5oV1AzndfwjwrAOO/QBmb2/dHh73N6hfeqoO+dq2TvjZty3llQ2qAHYljOeC6arTk7tkh7ZhyPPJQLxorPkRUqsur7oFgAA/RhV3LxAtpXW6wAwmHrf3X9UTPgBWRkWF0kKACObY71kl/7V0UPE1KiZ4Qf9Z4xi1TWVNPYBmMJMi3xoknI9kiOxRmqJQLz4vCDxPgZ9baossVRJDH/AWp92IQuF/DzFyLIzf9++vIaREy4xfvAnheE/zzlDSlnwh+ijV/9LsHF3Upx0hiEj2ZoenlhwayRKmWEbW1Loy0UtCoFAeolAIBAIBOJFi/dBIBAIBALpJQKBQCAQSC8RCAQCgUB6iUAgEAgE0ksEAoFAIJBeIhAIBAKBQHqJQCAQCATSSwQCgUAgkF4iEAgEAoH0EoFAIBAIpJcIBAKBQCC9RCAQCAQC6SUCgUAgEAiklwgEAoFAIL1EIBAIBALpJQKBQCAQSC8RCATi/2fv/cOautK973teemW3PLNz4ZhcdBJqTWZ8gMYGyhApRqFQamGw4mChQ8UWwQOFXgLOIPgWtKciZwQ5B4RTER6DWKOcQqFg4UAVoYKpRRyEWExyaJMeSzKliY9c2XMYd15z+f7hL34kIQaCoPfn8h/ZO/vHvda6v+te615rIwjqJYIgCIKgXiIIgiAI6iWCIAiCoF4iCIIgCIJ6+XhADdZXdRoek5ehNbWSdjX9JJUfreuQSBWPySubFDXVPaNPVPszqVuqGzWP6cvp2qsaVBQ6WdTLx0VfpKm7+lherMfkfQiur1malteuNz8pvZ2ef0mtNAr5xOPxOgwPgeHAe0W9T4yL1TdlpzUwfDmP6eu5C8kz2Zl1OvS01vjF7du30Qr2Mt6X+Wpax7hd5zI3Sro+Es6lY6RVZX/MVCYdP7T+YfWS6inILGiWj9wNaxhsdyYA0JTBeOdd1pRe+FhMAtBDB8Pflurtu2hAWackmLz7nzFZQdqe2iHj/YYXl1uae/8oranZmVN1TnPnMHOFOOGjomQBAwDArKl6e1tv7HHJpvlwQtrjsa8X2xkdeO49LY12n1Nv25IZK+Ed+o8M74esFvSwdMf/e7R7+J553VhsAsBsMhqMNAAAJ/mz5vQVs6qf6uOZaeWyezWEyQ/dWro//r6uU+f2JRY0K+6EkgTHd31qSW442wUATAP7Y3Zcz6w7EMKeh/6iw/VzTvhRGh/fFSaVJDw360sZ5K2NpxpP96mNJjCb6Fu/5AeGxyXER3qRc1NdHW6PuuakuPqAI9XJKxjo76fzFJrgIXBhsl0BxoG/LibI3ZbPMyrbB1jk3EYR6tr8Y7c21Ec4EFySa3Ml7emyXRGZLRQElLRLQu/rXF9ZSloVRd0EIAEIV5IE0AMrKDbcZgxEq093MSe+n5s49+TZOEnshjIN8FNPfZbId5kYR/ISyuoi6+JDCq5HlxzfGzrhFVx4cdtX1+wqag0ujXR+2MwgSQAAUhS90ZNp47xb2u4zJubclt+Y7F8PXPHOzfd++MsSK+IPfRavrondUKIBTmJ9S6r3XfOa1E158R9eocZNAIzZ1E/+ltL2N2SZ6zM7KEbYx02layY5bjI4r170+q51aS381PrDid6uDyzquy2V/0ZR+QX/vYGks4vP8fo5e8yGxoIK7asVcbMVS2qgNn/X/i6jKD53n/SOQNKj8saS3TlvSRvTK0qThOTsq6vD7ZETkfVGdXx+c+TRGK4Levxp3EYehu8rYwRC/8CPBm/aOOmW9mhSRoN2Tm98ozPjZf/Nn+lncQntyVh/gdA/8SvjxL/e/Gv+67HHR27d+Z++IcFfIFydetZo60r6ttQEyfe3pv392vE3hP6CoPzLNy3Y5GTc6tcPWLLbTeWBcP9X/mLTpHNmxvMZL/sLhIknbZaOsSd/81w/z/eVMZYtYzc3L+YFCv0F6w9Ntrz+5JbwjK/puaifxu7M1QKh/5ufW6hmxq/zXnk51dKv6G8+CBVsslQf5p7Z1c9ZcPOvha8IN1SqZ3eVW/rufTECof/r+87/fGvqoZbtqwXC1akTjT/L6upYe9TWvSkMzfjKiN5+Ojh/+XDwoxODCDA2He6wnnNDXazu4G2OnNPxRe0Xko5xYfQamyEYremobddanQtkEJY6jITXhmgR697gC+u15HAmmLorm61fx6SorWfExfCnX22p5wskwJhSTU23SUXVaGhuiqUBasIz+vccfWN1z5jzy89NlBLLAZBXnVRZzbkx6xqkush35nQsfbyv6hMNe90Gm8ElpWiq77GRy8Ww+GNWUGzIC8w5qZ8kfxUPALRyHT3dJuVfs9Lyoi38iuG7KYQ5fKKq3+T88ptd/ZzF+GlHVb2eHxW2zOZZo7LaBo2NXC71yZzUOg34ZUt2idlTHs+FFbk93gNM3cUHH8wHz7K6OtYeOeJogbGj0oYneXJBvXzYBhuaHMUCc195ncZa9W05povcKppLb2vWtTaqYEVIgA25pFVV/xSb2UYzHtZNuAqTs8Lvt15yVWICH0B5onLQivszdFb2+6dYnBly5a3iAsDfBrSTf2vWNJR+zU/LWGtlxI4bJGLSstoL85D3y/B+O9HXBfQNEmvyTPVXd3C2Rs9pd4fqrz9DMXxCvazXCqq3OCmmUAYPX2+467PvTj7Nun6yPL2YAEalxjjl4S5UHLvxeq6VOWZiRYgvYexuGJyHtN9Z1U/H5VJWewHYYrGtIcofm9M2ZdaOWS/AH6U5xXIAXvIHUZavsyw0zB2A6jzWT81NdXWwPXICXuHAUP0ZzPtBvZy9w/XdmugNMHKy2mJaIN0vbeVsXT+3ySujsjNqYL8kZLnY8sg1gwDD1UkRr670Ea0MjNiQXtGje/guvwvvD8liAgyNVZ16i533unqIjbESJzH5AiaAUfHdJH9Lna84Znozy3qaEsEXe7vAQNu85LK7h26PYMJ4V+UXOstyItGFzW13B0xX2/5Kg1eQjRwKw6VjdRoYv3LgnYjVfqKVPuKQt3fX9BnmuX4Sy17kAoD2ipae5F5rSy/57Ej0dbUmYp5reWC88OV8rJOZVf10uLvz5QAwvF/mWb+qSdFU3U2B+rOc8GDxSh/R74Jjk4rb1Q9yr0y9R44qACAwMc5aNSA43s8CgElxYUJ8P6vq6mB75PqLmKDp+Ovjsm4N9fJRwglPX8cAqr38tGF69W2U/BC2VTS3mQ+UUqYA4PpYaa6jfbV702L+1GwERlBOqaS2qaupNN3PpD5XnZoiccCFsUMTo1kAF6o/H552bExW+Y0wJdRaS2Nw/ZZPHdAza46WXwn4c7wtF+a6PIAL9ND9/EznhigB2zbzARQ10oFpqaT0oLTVffOm5+b0hmZtr9wILE9vi9WC1vVIdse/nd1NA3tTXun/qfuyTVqa4GUcai/n4qDdAAAgAElEQVTellOrm9/6SXr5sgDGlOoJ0Qx1rqKWsXnnqzYGN5jeAiaMyQd+no/2N4v66WB353uZCoC76nnLOkcNNRe/H590RAfgmVV8qL6l+csj2a8Rmt7ju+ML++7W6PHB2tNGAAiIFltPJCaYJACAcdQ4R9XVwfZ4p9ukOKd6opZGo15OYLxv16uilT62/4k3HLIne5tclRTvATBw5MQUNaIHpa1L59rbAuiHNABMD47lCq5X65hRO7P8GABeYWt4bDeSzRMnf7QzwAXgWnuPAw6XECZs8wTQ1NT0TQlR1HVSU/RmGy2NyROyAYxK1f0Wr287+Lnbe3+2nTzpwuKzAAwq9fys5ONtSFnDAENz+TnDFDlplfwQliCe40TP8R8GtQAsHsui3a6r9Lz4vSmeAAzvUH8+iyTdPcPS87evAAB560UH+vizqJ8Ex3cZAPzt4v0RPFpVWa4Ky4m1mS3JYPOWAmgH/ts0H8U3i/rpEEaF0gguLA83y3L5/TCszdoZ5gbADw3yYpEkiyuKyf0onAlg/OpuzE1rugbHAYAXttJG5aLpcQAAgpiz6upge3TlcF2B/kFlwCnMJ1QvXX1yTzZ/2Wb7X71kC8+uBusVk+wHoKurlE1osGZDq0QVtM1Ob0v1lGSnpWdm7p9xXt2kHTYA/JJDWu7esgOjIr1MA8MmcBc+iGBInrc7AJiMtCMujLs+NcwVjC2Hz4xO6rxXnRcm21zQQnCFfAC4Jr87EjUur6rU/SErgj3DrCpBujMAdArDvDhcYIUlR7HB1Ft1Sj3B+PS30kZy8ya7qgBo24oy0zPTdh6cOU3JoNGbAZZwnrYcDoZEh/L032gAuGv55P0OhPdvmQBg/IcjBplF/ST4QhaA8arqrmvWNh/sWJ6Z7DPDajymOwlgUv84TyN4DtfPCYWtqtqZmZaevadupi4yrVMbAEgOy7INSN+NUQGEamAMmJ4v3u9VkM8LuQBgomkzAIDpmkoPAK7L+W42xiEMVw0AAMxlU3pWjldXB9ujC9ODBPhJM4IB5hOql8Ag3Tlczgz/2PZGFqzItCgmmDom5OnR355oJOPj7PO2YKZGvunqPifrOKeZqU7SxjETAMF82vopY8reUSC8/D2ICb8aB4Cl/CUOrTsmRSlvT03MUzdVG6M2+9ruvJMcbw7AuEpx/U5/v6hHmLHVa+ZnIFyfBjAZbK61p/t2h/jMNEiwKrZs2A5FWRmfLABQn6i6eF9RDK0SVVCSnd0dk1Ep6zgn6z7dN6NPoccNFADxDMOqFczaXqUJ3ITeSx/8yEQZAcCD41is63D9ZHgIeACg7dfSAEDJyo/Sf/zTzHsRMFxJADAZbNqC6koLnHmMJ96e/WUcrp8PClDXe1rWfa6rY5CaoQDNtJ4CeIph48KU8pIagD9xgpOmKABg8dgEAMDNOzdxZTFtCNUN1cVrAMD0FXHnrLo61h6fYjAJgPHrFMaXUwyDJnBwTMhvc8KK5jLliZpvY3N9GACGVok8aHuGU9Zsz5TySqtlagBuII+cMMo3MAawIjzAwakchndsYsDRfb11kotbi9a6AVCyqk7P5MMzXc6F48sF0GkH/tsEz8jKPmUm1zzE8CZjBptn153NmLFkmEvsMSlnfUpIcXpXS1XnnwOj2AD00IlGIr5ihVMqy0xjDaqL1wBE4t8QD2Ka3mEAEEUKyHmun+SyFz2gb+S7Kwazj/H4wYHgvI/smV8w21FRSXHhF203Z7rS0yTLifXTKQ3QNHJRBcDy9XqwqQA1fGkEHqTUPu1GAADcMtnQZqq/fQAA3EL+IGDMWXWdTXt0gcdk30bUy4dmvG/XG2ktMwwXMfgp0lNp9kWILry4ZHHlTlljVWfyx+HMoRONRHyJ/d7WhRP3aV+cfa6P5cYAoI3WPY32sooGpu8LD5yF9my9GhhBSeGOb9LhHpH8RllvU1dZm25tHEfbdEK/Ps9qhuQEp8j34UCfTnlV03u+Qv37/EL7tpSjqZsALBZpUzFdSDZrzjok5MtJ73K6qvqra5UR6V7Gjkr5qrRUu6/O8N7R/O0O+8qPuZQE0P/j7yYrykmrL6kBPFYtv393+rv21lFgbtwa5LD/d7h+cr24LjCilSvUbbVfLM86btc6VBNNAQA5Q+kwSNbclZ+D9fN+8YdIBvvssyST7QpA2whDjQOXDUCIA7j3a6+hu7EPwDN5s+cd6zGWCT1APjKm0VJgOQI261pqZADAf2dzgOscVleH2uMtk5EGcF1K4qZ4T6heuvrknmzePtPwAoN8iIUgZHBitLus9nz158NC7hH5qpRU52yhyWB7s6Dz77oxk5UAzKDo0wGIgu7n71Gy8iMaQpSdu2423W1GQMJmflOF4oh0IDSksY2TXGmXcdgCLoBu5IuDBeC586SnfV1U2jBqAmD9hj2PVYLwjEsRVX3Yd0zSF5cgr3WJKfFyjntYyvMgQH3DYDQDaan7YpDLjcAIeun+KJyh41Cdngwp3T6rRGsH66frch936NVdqclXwVuSMPtqkFFHATC4zzHnsfwcrJ8PX0+WersDDF03WOvvjKt6NQDLxPx7OkcPnSi/AN7v746+F5oTvPAwd2nNqLK1n4pcZ6FUqfMV5UMA/MTCeN7cVldH2qPZODIGsMyTjeOPk8H5S8fmL+/UYGHCVk8ATeWH+yrNMXFezuqMcV/wJMD4vdZoRWt0PcMAy/zvJouYdY25e1p+FVNaPGUHSNOd1APa/jl8Xkx6MAMM9Xs+PKiNSAywzzjkcy96AMC1PmZC6lo77Wk2fK8H4Aj5z8xrnWCv2xrtBvTpol0FMt9toc4Sa4K3igvwk0p/y/I4nOIbDQBvFe9O/TEpJDl7+rzSP949VavuDObRJvqWM+unC+uF5wHAOPBTSFasnQpk0g9fB+AGPD+/8YhD9fPhYXoLWQBatbXRKa1cSQNT6Hl3ebSh68MdUjoivzRpgjgRnu/uEBNg6i6vnr4sBHTNu3PbjW4hez9OtZHc61h1daQ9Uj9oaWD+1pOFW8g+qXrpHCVbnxpGAj2kCUoJdV5oRHiJvQG0l3WWle7nS1cpgFFZ41mVWimryUqtgq3ST7LXTsnEozSDWgAAw5DObsUk16ZEsQHU3/ISNtrdeX/Wi+sCsCwx1/5dG6gfBnVArFw93x+6chUlvMMD0PW6xrwrcJqvd2EF+LOmLGqc2N3pHQaAv3U0yxQaVUd5ZloLJ/dERbLPVN9mGFIZ4eFW3ThUP0m+gAPACLKxQcG07o5CZQR3se/SeW5/DtXPh+9qe6x5kQDdgMay3fVDl0YAjPL21n6Nuq9+1z8V6TeW1hVMnQphR+Qf2uYJ16RJf5L23pHecYoG0PdL0+L29fDjK+qKZthVyrHq+vDtkb4mVwPwg71w/hL1cm4brDj9bQ4hes+J3hYAWKJIARj7L1lceUIpLqkB4Jkfancmph26xNwiaS6L953kbA0dBUnh6zJbKACAkZr41eti4wv67FFNwis+2YfB35q41v7Ou+tyn+dZ63Pi7V8GRw93KoAREPEI2id/U2oQyYrbHuHMkWAGP0LMBE2H0pLDvS4fMAAQMPBxZtJOyVVexqnP8qMnbwFDD0vT3op4vUQDAGDuy3n11fC3smt/dFb9ZAt4TK/ULPsH8ylVhxqYa0Lm/7uejtRPB1r5yogAAgbOW0xlN6m/+QEAmPrmPdvSCk5DZFmzJE1sacEGGbBd2nU4IxJO7dgYEb5OvDIwdHWwOKpQ5Ztb99UnGWvdnVNdH749ar+R0yCM9iMBmQJuOb8o+PnzRIFws6XPFNCX94ULhOEHFPSifTn66l/CBeKd3Y/xFxFuDu4L9Q/84OJNCx+XyPAT+r9xUrt4X87Ys9NPGL7vW/rxLT9jd9ZqQfihq9O/eXJLXbnRX/By3jf/85A1Qt22b8tqgdBf8FJMzqeDC6ju39Ie3egvSGr6Gd0ufp9kkcJe9160m6r2rM7CUNhlA7h4+nIXbSobrWw8Y+C/k7r2Me7OEsKEbZ7Gc6cGpkaYppE+FQ1MX0/Won03aqBBRvu9l+z1GCdTkquS4j10p1qHTdOnEnrVAMv8+a4PWSN44bmftNfvieI/pWkpSHrlrX2NQ9SCeNdr7f+hZsWlRbABwfHYRYqraPsOkfa4dGDKkNC4pucawPPCh22uC8jdnqtuhahcezd6WKxwo7ITyM6qs1OSRoyKPgPAct9li1ZsdO2V37CSc2bcwmmRd3i84nMjTI2SqTvw0f8tUwCwhTyHMoNJ7015p05L9saJ2cPNe94ODXn/YKvy0aqmaeB4vTE4I9kPl5KgXi7qEPONvCxuV3HjpBCTviZT0EAs91ysH0Mfl1eWq4JyMwIe+7kSV2HKnght5eFJnw2hVN0asLoV+2Lo7fSUVRui8lO8Hnv3Sq7N2rmq/+BR5aQQ03BZbgTg+nAcn7p1E0bvKm2/0Hbqk0O5ERy9UvcoBVMjLTjHy9oVjsEl6uUix4UTtz+D9cnuqgeDQtRAQ5ceAMBkWpSvRPWU7OsW780NfSIyC8jA7JLfKz/c33X/Q1T68/U94wAA9OLceEzfll9wLaZkh/CJSKRkhed/JOzIq3gwqD6uamjQAADMfp9VgsX3EYWtj0nY6PnIGsO4qiy3+Tc5e6M5gFjkF7dv30YrLCJonaxV6xktYtHK6h07JN33v3BJ8JI/kaYvrm6+WdfRZgiIEJJP0DIvaqBFxnwtnG/qK07fU9N/f3iW4burXhq3uByVSd3USb8a7v0k5VHq+5oHuVFhHNDWZaeWdD34wqV7uKQpP8B1Mb/bqKxx2DN6DQsQ1EsEQRAEcRgcj0UQBEHmD1onV4/N5w0p9aBuTj5NhnqJIAiCzJd2XTi4Y/8lozOmYMwmatTytvjGS0U7Svpmn0iF47EIgiDIvESWQxVJeddTjubd3a1zXF714cHGs/KRO/luJIv/7FICTDRNU+MmctmLviJx9KYIX/eZ0jJoXUfJ7j21ciMAANN7Y/renCjvSXPJVM/epEpWviTNcza5aaiXCIIgyDyElvKCt3P0O+pKJ+fD00MHw9+W6kFYeE4SeX/Xa9qgONd+rOpgyzDDe8u+0h0hVpfMmXW1KVuqnno9LpjH+EneWtuuoAH8Mr48Ej/pJ2OyzE1F7APS3Fns84fjsQiCIIjTUdftq4UN6cFT5Yrget75lB0xUd4Ilve6+P0n6vauYyqOZ8fsaNZaWXOlrStq9Sk5dTg7OS4mYUd+fUN2gAtA/9Hy/smL7NzE6W8Rjf9Sr57F2i3USwRBEMTJjPdVfaLhx0bxp4eJLoTVMVKCF/1RYZw7GM/ty2nQWTrDoHaJKkwTPhDh56K2b2QBGAf6tFNO5a+P4Q+fqOp3fLE66iWCIAjiXOjB+jNjvPVrLK4wtjk96XrnM64wUDltN1AAANba2ClDtQyuHwcAgDZNPd1dHMk3nqlzPPEH9RJBEARxKiZ15xXaTbjKoQ05uP5iDwAwdHVo7AsNx2kA4HpN26TQheX7EpPul33v6OIS1EsEQRDEqRgVcgNwX+Q6lpzK9mIBABgUdq2ipJR9GiDEcYHT83oYXOGvwSBXOLr6E/USQRAEcSb0dYUBCHcO07GfMxgsAgDAeMMOvTR01pw1eWxJXetm4SCTyyHguvonB6cwn8KiRBAEQZyI2agfB2KJ40sfTbcAAJgzX8E0UFPdy42XJllZZ8lgMcGoH3fwMVAvEQRBEKdiMpmBYDiql5RBbwYAjvdMn02jhyr2NLGyjqb6Wtv4/inizsOgXiIIgiALEAbTBeh/OJhmQyllagBwE4XxbGbSjskKdnW+sEeSsML6abcoGhgOCzfqJYIgCOJMCBbHDYwGygTw8FJFddfJaADvrZt9bfzYrGvcU6TeWCRZZ+t7ZKYxgxFYHo7u8IP5PgiCIIgzcWH95lmAUY3R8kDovewbS0epvoPF502wInFvHM+GpvYeyKxZkl0ycdqSpqhpFzRe0wGwvJ918DvBqJcIgiCIUyG91/Dg2iW1xUQbM00DANDGW9NkcKg69f1mPT+m4nCqN3FXP4vfEq9ck1SlvJ/jalLX5nz43YbSD8TsCRo8UJJacGHKzgSUul8LfLHDXzjH8VgEQRDEufCDQjzKPjujNq31mRrb0T9pDAAAmo5vDNHr746mUsOylrrq8oYfvLcUnUoL4d8LG2nlqUalCUDe2KZ518uTAKDOFSXt76O96IL3v74nwEa9VqM2eBVumyyMtKZbbvJYL+Y6+jUx1EsEQRDE2YIZ9ccV1cdalLSP8MGQqaZ+T3H7xQvyEQAAU3duxMoDHD6bAGCwn/PyCUyUnhPzJ0sesSI8kt9Z+5PX79fxCADQ1WfubNYDgFLeO+WOK0J8l0yWy+/aO27w4jY6/kkv/J4XgiAI4nSoc7tfz6ULW4os7iQwD/fv2bkxB/Z+eUDs8Ae9cP4SQRAEcTpkcEau6MqB4yr6UdydHq4/0P+73BzHxRL1EkEQBJkfWJF79wb1FZUPmub7zuPyynxZ0P7dkaxZXQb1EkEQBJmfGFOUVfYeU5rfqJvHm5p1jYVSSC3NEpGzvBLOXyJ3oXVyrauQ77aYHljtKvR+BA9MKQYpvg+HWDSmotSDFHcxPTCCzK1kArjMwWUwvkQAAKgLB3fsv2R0WUzPTICuNmt3o2Z+x3ZoTeOunNofYXFpj/FS0Y4Sxz+TiyCLmznybBhfLhjG+zJfTeuwb+N85kZJ10fCuXLZ9FBFUt71lKN5VvPWDPLWxlONp/vURhOYTfStX/IDw+MS4iO9Jo1vaI/Hvl6sse+enntPS6Pd7/1vTFaQtqd2yHj3v+7CuNzS3GDyvkTV7MypOqe5c5i5QpzwUVGygAEAtEaa9id59OGiSPf56aUaWnPTar0KJQk8wkrM29vS/HlLV+81CgDoW8DyFq+P3fxu6OTzHS5rs6F1T1pBy11TAMEJ2JJ/aPv9mmAaKEndVScfuXNllmfYtvzSu7uiUD17kypZ+ZI0z7mrNgfD35bq7Ts5oKxTEkxiK0cWNbj+cuH0gJhsV4Bx4K+LCXK35dOMyvYBFjln8Q0lL951irWjzopYUgO1+bv2dxlF8bn7pHcEkh6VN5bsznlL2pheUZokvO8FGSQJAECKojd62vrQ3S1t9xkTc+ILuIlzT56Nk8RuKNMAP/XUZ4n8if1BgpdQVhdZFx9ScD265PjeUNaEI/G56+Pjc+t9K2O4zg+OtU17Cr4Ll35kWSz1F6o/zKvodglJ31WYG8ojAYDW9UiLcnbE1obmSfZH3V9z7XhZu7AiC+rCYovC36nXg7DwPyWT8xcYvjsk7esrwt+sZmw5dGLSdA25Nj2jYVN28cvSXL+50S3ClSQB9MAKig3n23oJWn26i0niYDCy+LmNLBi+r4wRCP0DPxq8aeOkW9qjSRkN2rm76ZEYwfpD39+yeC99974YgdD/9X3nf7419VDL9tUC4erUz/UP/njjfMbL/gJh4kmbj2fsyd/8F0vveO34G0J/QVD+5ZsW3vpk3OrXD1j61Y3zGeLQjK+MTi+eG+czxKtTz1q+0cgXea8I/QVxhy5PO/79J4kCof8re84b56qsbyr3hfoLhBsq1dN/Q18t2+AXK/n+puUK5rdJYrmsHUHfkOAvEFq1yb2z2lIT5vCmCPLIwPnLeYXqr68dtDqLxI9ODCLA2HS4w2D9CherO3ibIzlzNghc9YmGHxvFtxScqU/mpNZpwC9bskvMnnKCCytye7wHmLqLD/befyE3UUosB0BeddL6EiuzrkGqi3zH0mDyUs8XSIAxpZqa/tYVVaOhuSmWfuUmiguGjkPtWrNzy07bVtEBoe++TFoc0E7NbdeTIYUlqb7TjvM3ZUS7gb6pqPLBjpezK2uCE8ADAMPAtWmWMnSWfwpxe+ItBnz89TH84RNV/XM148t6LTmcCabuymbrxjcpausZcTF8a9E/remodXrZIcicgHo5f+g7d2/YWq22kSnCCk2OYoG5r7xOY01sWo7pIreK5mwKarD+zBhv/RpL8vujNKdYDsBL/iDK8lDnstAwdwCq81j/fa/N8H470dcF9A2SnjFrPYbqDs7WaIt678pbxQWAvw1oJzt0s6ah9Gt+WsZay+OIjBcifkco6884NUPdrDvToCJE4S9M/w4trSrPqlYD+KZnWp5GdfWKXMUA0DXWKem5KWuS78cBMKlVhqniVFOhCMxOEVj5/IK7OJJvPFM3Z4k/5KrEBD6A8kSltRV1hs7Kfv8UazOXtKrqn2Iz22iGC7oHBPUSmeD+Oirb9WDo+OeYkEDRSh/R6oikPQ2qyZ6L4bs10Rtg5GR1ryWXRvdLWzlb189VcAkmdecV2k24ysIFTb1HjioAIDAxztrHVwmO97MAYFJc0D2QAffQ7RFMGO+q/EJnWQMkujCres/kC5gARsV3xkkSe77imOnNrPVWVxqTK8R80HT81eDE4rsh7xgG/hrP6Y5ff66iVgdAhm+3WjAMDwEXAIxyucE8N2XNFvAIgJFB3aSfjrYVt7GSd1jfwcSF5fsSk+6XfT9XO6y48P6QLCbA0FjVqbcYXNbVQ2yMN2F1uKVmEGC4Oini1ZU+opWBERvSK3p0JvQWCOrlEwulPl2R+XZSgRJgWeL+MumptmbpRzEsnbxxb2LO6clenhOevo4BVHv5acN0sWmU/BC2VTR3WYZGhdwA3Be5093Z+GDtaSMABERP/ETOVMFkkgAAxtGJ8kYGbNvMB1DUSAfGp4ez0lb3zZues3ZBBtdvOQBo5RME2Kw5Wn4l4M/x3jZiajeetxuo+3TO22eLvnZJDUzv305PYzJcrJPRAMzgDb6uVn/OIBkAADd0k75YNIuyJvlCLgBck+sfCLBpoLJavz472lZ3isEV/hoMcsXYnFmGHZoYzQK4UP358LRjY7LKb4QpoZY6OqN9tXvTYv7UbARGUE6ppLapq6k03c+kPledmiJR0Og0ENTLR8h4365XRSt9bP8Tbzikmftb0wYFJUzfs8EDgP2y2Pc5knTj+G7MLExgAZh6W6ZM9ZGrkuI9AAaOnJjiNehBaetSG2LjwINdVxiAcOdMFwFa0zU4DgC8sJU21JmmxwEAiClKxtuQsoYBhubyc4YpGtAq+SEswdb+jUyekA1gVKruK7C+7eDnbu/9OdBmJ+EpFp8Nxh81RqdVH6NOY4Sl/F9NC7XHVWfkAADewV42BN00bgIAYEw5ZRZlvfRFviuA9sqDDwr+WFd8wXPn1hmWizC5HAKuq3+auxiOECZs8wTQ1NRMHeZV10lN0ZstdnT0ah0zameWHwPAK2wNj+1Gsnni5I92BrgAXGvv0QGCoF4+Olx9ck82f9lm+1+9ZAtv7m9N8CI3idnXrowA8EX3lyIwPHx4AEBTpimui/CKSfYD0NVVyib4H7OhVaIK2mbnZsFUT0l2Wnpm5n6bmRRmo34ciCUW/JnpmkoPAK7LbW33YzZcNQAAMJexJl+CFZYcxQZTb9Up9YS7099KG8nNm2wamOAK+QBwTX5XBsblVZW6P2RFsG3Pb7kw2K4AFGVyWtqI6QYFwGA+M+3AdY2aBgCW9zJbcqn/7joAwJLlUyzleFkT3AAugFlzb66X6iirh3cyZ/7yA4PFBKPe5tJPbVtRZnpm2s6DPfaFodz1qWGuYGw5fGZ0UnBZdV6YHGF5FJ0dGBXpZRoYNoG78MHHe0metzsAmIw0DskiC5EnZ/0lg3TnzHYk06yr3RpTMNNmwcSa0q8+nuLsTN9/owLgBKx48OebN4wAwOQtnRazsCLTooq3NXdUNmuD4+/k2tDfnmgk4yvsVHMzNfJNV7cSgOOZvtOWCpjMQDAsOPqbFA0A4Mpi2hCqG6qL1wCA6SviTrXAyvhkQX3B0ImqizH774aGhlaJKmh79gxFQHK8OdCrUymuQ4ArqOuKeoQZ9V6MGbskhAvALRM99wV3T+xNAEAQT1mwlAkAgGT9L4aNjsXAkBEAPERezLkqaxcW/7dMGDYMaGjwYtBD1WXfhRbus2Nm+yniTrnbqBVGpazjnA7AsDbLvvpGilLe5nQckVedVEXuuBvgqpuqjVGFvjZ6EWPK3lEggv09HpxDG8cBYCl/CQMQBPVycePCiS5rDrs1o/dmkRY9putqnwf5kyZ1398AGKtCLSx+J/w2J6xoLlOeqPk2NteHAWBolciDtmfM9f4oDKYL0P+woDJPuxEANhUIgOpvHwAAt5A/TM/GdOGsTwkpTu9qqer8c2AUG4AeOtFIxFesmNnCvlwAnXbgv03wjKzsU2ZyjT0hNW2kwbLyz7Lg7h9xBQCanm6O/3VnZpI22bj4qKx1GAA4v4/wnLuyZnj4/RrajNp+Hb2ObCzu5GdKve1Jm75F0cBgzPHmAQzv2MSAo/t66yQXtxatdQOgZFWdnsmHbX0MglbL1ADcQN6DN72uGhgDWBEewEJfg6BePkLG+3a9kdYyQwYlg58iPZVmq2NPuLHYjtxddVEN4OXPv58SQg1+ft4InMQUiykdLry4ZHHlTlljVWfyx+HMoRONRHzJCrtv58KJ+7QvbsbTCBbHDYwGygRT17gwlgk9QD4yptFSYDlEMOtaamQAwH9nc4ClPBfy5aR3OV1V/dW1yoh0L2NHpXxVWqodykfyfTjQp1Ne1fSer1D/Pr/Qno3uzJSBAnDn2oiGHSy4ezDdWQDaESPAlOdx83yBBDVluKo1Ac9iVGRSN0gVACBKjLNYgo6WNeu3PCao9ENK7blLxyBessau3pRpzGAElgdpU/x2NH+74yEN5B6R/EZZb1NXWZtubRxH23RCvz7PRgIUAGgvq2hg+r7wQBu1Z+vVwAhKCufi8hIE9fJR4uqTe7J5+0zzWwyS44yb09f6FGZgTxiO0zYdbKE4cSVW0z7J4MRod1nt+erPh4XcI/JVKansOX8sF9ZvngUY1V+w2uIAACAASURBVBjNYnKyhyJ44WHu0ppRZWs/FbnOgnOlzleUDwHwEwvjrXQvCM+4FFHVh33HJH1xCfJal5gSL7sG2dgCLoBu5IuDBeC586R9m53ShqsGYAdznDeKx+B4smFQbTDBlNU1rl6Ra5gtbcaLZwbpNZbWyYy2FRzXgYswKzfK2iysY2VNcIVcaDd+V7/ngCmseLedGmO8pgNgeT8756ZiBCRs5jdVKI5IB0JDGts4yZW2m5JB0acDEAU9f+9JKFn5EQ0hys5dh9ElskB5ctaTMEh3Dpczwz+2c3aENg7J9cDw9rv7QSWq72Bqyd+Cdtn8HhshTNjqCaCp/HBfpTkmzssZWkB6r+HBtUvqcQtq9+4OMQGm7vLq6ctCQNe8O7fd6Bay9+NUG2OA7HVbo92APl20q0Dmuy3UTr0nn3vRAwCu9TETUtfaWRyjV9TjDG+RE79XRXD9fQiT8op2+vOufX+rrwsYvzhcOzxtfpTW1Owq6qU50SWFCTaGLRwrazfP35AAtEq9MtXqBgXT+jnqfi3wxd7OqOe8mPRgBhjq93x4UBuRGGD7FrSuZxhgmT+fvDtc0Zi7p+VXMaXFMRhcIqiXTzKU8oIGwKRoa+8d1gw0FSXm9gXsP14Sx7Pt37nrU8NIoIc0QSmhbOc8GT8oxIO+ckZtIRGGHZF/aJsnXJMm/Unae2cce5yiAfT90rS4fT38+Iq6omjbIYSrKOEdHoCu1zXmXYHdev+sF9cFYFlirt37MugHZWrCJ9rHmZ+/IIXrRYyRr+QWVuU/F19SHOVhlhe/l9c4RAEAmE20GWidrOy9+GK1T/pR6d7gGWImR8qa4PhwAUC4PT3E3jenNd1yk0eQ2DmaRK5NiWIDqL/lJWycqex+vnSVAhiVNZ5VqZWymqzUKtgq/SR7rRu6C2Thgvk+zses61WaABj0+aKkC8L178QXNmTz7fFwpDj9bU5Pf+JDiM1DC2bUH1dUH2tR0j7Tt2YlA7ZLu/yl5cdO7dh4gulqHBk1EW4M4tnQhNy6wnU8e96Avyk16GgRd3vEQ+i963Kf51ls2xsUTMLQ06xkBhcFONfVkgFxYmb6qZ7RqOhpU6rs0LzmFvGxw9KqtI3lTIbxmoF2ZRKM5ZHbir48LOYSTiprprcXy0OUHW33klz6u/aOG7y4jZ5OCsQJr/hkn+ba4MQZBwYoxSU1ADzzQ+3OxI7g2OQESbMfC79ggix0cMt5p6Nv2iz0FyR1Ghfk0xm/ygsU7+y+McNpN9Vt+7asFgj9BS/F5Hw6uIDe5drxN0Qxlr7UMdfcUlduWv3GkZnuZFQ27IkRCP0FwtVv7mv7/n8WUFF3Z4UGZp1fAGVHX94XLhCGH1DQ6B4Q/D4JMnEM7JICwMNv+cL8Wi4ZnJErunLguMr2HmQELzz3k/b6PVH8pzQtBUmvvLXv7tjjox7r7vi3E7Al/12e82/lwnt3XzycrOiwnWVNekZ/VNd1NCNsmUlRt3vDuqTiNs1C2N+NHq4/0P+73Bzxo6+HZoPisgFcPH25uM4SWUygXjod7WU5DQy+cMFm/bEi9+4N6isqH5xxUxXSe1PeqdOSvXFi9nDznrdDQ94/2Kp8lKqpb8kvg/cq0jznZyiP8EqtSIOyguYZvz/F9osvbWqTZEX5EvKaXbG/+0N2VecjVc1xeWW+LGj/7siFUA3HNT3XAJ4X8l3RPSCLiV/cvn0breBMDK1bI3L6eVktdQnPLeDHHOurKjjF2pEfbWeSDW1QKzXqH38YuSXctNHzkYQs9GBFTjMnPSeKP68TXyZ1U1HZjxsKtwvtu61JP6xUajQj14mA6HD+I5mjM+sa95aOhO9OD1wQYxz0UFH42/XG0NKvS8Q4Z4mgXiL30NTHbywaAF56U10yD83xuGAGcMEHdgyqd29sUoOBCC36qiSExLqEoF4iYDZ0FGTuaXjwqQ1mcNGXZeggkCcXWlm9Y4ek+/4XLgle8ifSdC+cxURQLxEEQRDkcQHzfRAEQRAE9RJBEARBUC8RBEEQBPUSQRAEQVAvEQRBEAT1EkEQBEFQLxEEQRAE9RJBEARBENRLBEEQBEG9RBAEQRDUSwRBEARBvUQQBEEQ1EsEQRAEQb1EEARBENRLBEEQBEG9RBAEQRAE9RJBEARBUC8RBEEQBPUSQRAEQVAvEQRBEAT1EkEQBEFQLxEnoh9S6c0L5WFonVw9tpisR+vkijE00cIy0WPfTBDUS2T+MSlqsne1GRbI01AXDu7Yf8nospgsSICuNmt3o8aEJlogJnIWN9p3ZVUrxtFpIPPBL27fvo1WWFBo6zKTzodISqK49/3veF/mq2kd9jkF5kZJ10dCYq6ikKGKpLzrKUfz1rpZkQplV0NDc+t5lcEMQJto1+WrXt2QkBDly5p0VuvW0Jx++265LPFUUyrf5cEDpO2o7h2993Ze4Vkl+dGceyfrmnell7UMGwEAgOEhis0tzrjzqLRGmvYnefThokh3Jwdqc2Mi0B6Pfb1YY989Pfeelka7L0ATOV7Q6uOZaeWyEfruS/BDt5buj+ffq8fUuX2JBc2KO+9IcHzXp5bkhrNdAAD0LdlbWkSHPo7hu6DzQJzLU2iCBQU9XJ35MZVcO0EsAcCFyXYFGAf+upggd1tSaFS2D7DIuRJLoOTFu06xdtRZVoJxTWPx7oIGDT82O/d46R3vTynby/J2x5+sTygrzVrzQBCYbgwAEyEIj/Zj2Xg8+kZf64+TTiAEqZK2mMaUiD19wI6VtOdO7gpwovZ/Fhr2Xmjmt+K9tUXRzzEe/JAXn7s+Pj633rcyhus8Tzp3JmKQJAAAKYre6Mm0ccdb2u4zJiaxQE3kcEHzt5S2vyHLXJ/ZQTHCPm4qXUNOPJ8MzqsXvb5rXVoLP7X+cKK364ND7Ijs5Ka3ciT+0mQegR4EcSq3kQWEviFp9SsfDd6cduD7yhiB0D/Q0qEH3NIeTcpo0M7Z03x/JEaw/tD3tywdMw4e3OIvEIZmfDHtfjfO7w71F7yUeFRN3//bzYHCV4T+Vq92F/rqvyXmnDVOP/DzF4kCob/f9vMWjunbUl8OzfnKwpHbN85niEMzLB5aeCa6feN8xsv+AmHiSZslaOzJ3/wXC9VggZhodgVt7M5cLRD6v/m53sKLf533ysupFqv3zYHCV15ObfgJHQjiXHD+cl6h+utrBymrh5X1VX3MyFiv6d1kfnRiEAHGpsMd1qc1qYvVHbzNkZw5etbxvqpPNPzYKAvDXGZDa25q1SDwUw4Vrp92Pzfx9hRPMMvLCzv190OZlfHJXgDXPqu6YP31DZ2Vcv9kMTn9CPu3/h4AtGZ6codJcbxiwG/nn4Mt/ArcRHHB0HGoXWtnSohZV/OmKGS/in4UJgI3UUosB0BeddL6A5h1DVJd5DsWxtvnyUQzMbuCJvmreACglevo6S9e/jUrLS+aY/GmUX9w67NlNwSZC1Av5w995+4NW6vVYG3QyKRoOTXCCgnjMSwcZIUmR7HA3Fdep7HmSVuO6SK3iuZs5nKw/swYb/0aC/5Jf3rfnnMmYMXsTfC0eDv2mnA+AH2hvmf0/pAyZ31aCAHGlqpOK67ZpKith9gYvsUrcr34LgCjcu2USdzRtuImMiErnG35JRgvRPyOUNaf0Tln8HxuTQQM77cTfV1A3yDpGbPW36ru4Gy1qBkLxUSzK2iWpxcTwKjUGKe8+IWKYzdez91kpTPownstmDXS0qxGwURQLx8HzLqOynY9GDr+OSYkULTSR7Q6ImlPg4qaEJH0yAzgJfqNZcVj+G5N9AYYOVnda6njTvdLWzlb189VcAkmdecV2k24avoFaVVtmYwG8E6I93W18ms3Tz4BAMpu9YP0S/LlpHc5AIOHa5WWcjINsso+/5RQluULui735QLQGsWk8No0cLRa/WpGHM/qa5ArxHzQdPzVGcnGc28icA/dHsGE8a7KL3SWu0QSXZi1LtGCMdFsCppY9iIXALRXtBOVz6ypLb3ksyPRqjGB4RHoCYZLPTp0NAjq5eKGUp+uyHw7qUAJsCxxf5n0VFuz9KMYlk7euDcx5/Q9PzWu6v1v8PBZTlq7DCc8fR0DqPby04bpnrRR8kPYVhE5Z89sVMgNwH2RO80305r2z3UA4Bn9qnVxdiGYzwCAyTA2we0RnnHbhACG2iOy6YqvbpRCbIy3tejYhev9WwaAbuDahJ/qmos7eVlpNt/ajeftBuo+nRMCDyeYCMiAbZv5AIoa6cD49HBW2uq+edNzC95Esylo0suXBTCmnLiYlTpXUcvYvPNVli2RXib0AE2vhkJ3g6Bezprxvl2vilb62P4n3nBIM/e3pg0KSpi+Z4MHAPtlse9zJOnG8d2YWZjAAjD1ttybdBnT6M3Aes6GUyBXJcV7AAwcOaGgp3nSpdY9qSPPfF1hAMKdw7QQHsj0AOAu8l1qI5imjSYAAGLyxB474r1oN6A7JQ0/Tj5/rKvqvDDhNRvvzuD7cQFALb/fV6B6K6X0WxmRLJsv8hSLzwbjj1PH9xasiYC3IWUNAwzN5ecMU7pErZIfwhLE5GIwkeMFTXB8lwHA3y5qTfeD9cpyVVhO7AwZvEs4LAC9xgAI4jSemPUkrj65J5u3z5TUwCA5c39rghe5iUe1nRgBCBDdT3lnePjwAAw0ZTIBEAC0kaIAPGwuBiG8YpL9qvf011XKEktD73lOs6FVogrKyrYruKRVVXkVAzSDtSZ1b6z1QTqzUT8OxJLpD2Ma+VYLAMAVeth4UkqnHQcAJnfKmgJXUcI7vMYy1bFP5HETlj2oG6TG6EJfm1OvLC9PAjQjgz9QwCMB6OH64n5RVhZvhvd1YbBdASjKZAaY21UlTjIRsMKSo9jn63urTqnXJT5Yh/qttJHcXMF7RCays9rMQUETfCEL+g1XVQbw4wCAtvlgx/LM4z6MGZsukwCt3kQD4KoSBPVyljBId85shyvNutqtMQWDM2yJQqwp/erjKXGA6ftvVACcgBUP/nzzhhEAmLyldz3BLRqAwZjBp7Mi06KKtzV3VDZrg+Pv9Ljpb080kvEVPPtewaTrPS3rBWCS8bmxNjyLyWQGgjH9OE1RJgAg3H5pw4HRapkaAFw8g/hTz+JHpQZVZnc3V3eklN6NeyhZ1TnP5MOsGazKFfKhXXFNPkKHeBOG1tJmdookYOYSJQgXgFsmi4ON9PnM1e/Lph4ajv9d7cQLCPf+pySaNX8mIlbGJwvqC4ZOVF2M2R945w0NrRJV0PYZukTOMNFDVpvZFzTDQ8ADMGj7tXQch6Bk5UfpP1aFsO1o4AwXoE2Y8IOgXi4QXDjRZc1ht2b0P6ypPspsGBgygutqnwcbqZjUfX8DYKwKvRdxEgSAiTLRALa60oTf5oQVzWXKEzXfxub6MAAMrRJ50PYMco5flcF0Afof070PQS5hAJho092w2KJzHWj5Kw1ABMYETF/FzxInR7O6a2WVjZrIZB4AqBtO6NfnWU/luMfS5b8hQTEqV1PgIT9cZYg6FMGyJ6A20mBR1gCAEOWdapnQ+7mlrU1PaxQUSd+fmNTKYC2ZXxO5cNanhBSnd7VUdf45MIoNQA+daCTiK1Y8AhM5jqMFTS570QP6Rr67YjD7GI8fHAjO+8iuiQaTiQbCFWNLBPVy9oz37XojrWWG2Q0GP0V6Ks1WpEa4sdiO3F11UQ3g5c+/7yyowc/PG4GTmHIvFYNYwmEBGA00gE3tc+HFJYsrd8oaqzqTPw5nDp1oJOJLVtj9JGSIZLBv5tMIFscNjAZqmsdnePjx4LQKdBqjWUxajIbHZMfOGAFY0RaXUgLD951E79oixYnq3rj8AJDVdHKSD9sxDE7wfLjQovyhV6PSlvStypLatf+ZmTJQAO5cpovl1+RO9MVmYBFAuHG4z3GIR2miOymmXVX91bXKiHQvY0elfFVaKvlITPRQ1WZOCprrxXWBEa1coW6r/WJ51nH7NnccN+jNwOKSKJgI6uWseYTzlwD0tT6FGdgir/u5Idqmgy0UJ64k/kGiILmc6wqDw9dpYNlu82RwYrS7rPZ89efDQu4R+aqUVPacP7EL6zfPAoxa8PjcNeHeoFKo27tH4+M4liKnI6XdNLA35qVbm3PihKevO5x6ur38bCqbOqGNyAtwteeZmN6/ZYLS2FOZTyxJPW5nLjBtuGoAdjCHsbhMRHjGpYiqPuw7JumLS5DXusSUeDEWn4kcK2jX5T7u0Ku7UpOvgrckYSw7X+IHAzB8lrMAQZzGk7OehEG6c7icGf6xSafc2zgk1wPD2+9u1EL1HUwt+VvQrtKsiR7NlRe0AvRy5cxpioQwYasngKbyw32V5pg4L4YTHpn0XsODa5fU0zd5fy4qaxMLQFX+sYXVAvpzRTuO6whRhuQDG5mc5KrkNz0ABkp272nhJNi7aJTB9fk1AOj7TNGZ4fZ2EUavqMcZ3iIOschMBOx1W6PdgD5dtKtA5rstlL04TeRIQbuwXngeAIwDP4VkxdrbfzUq5XrwClrBAARBvVzMUMoLGgCToq29d1gz0FSUmNsXsP94SdyU7aFZARGe8F3XoB1LyLjrU8NIoIc0QSmhbOc8ND8oxIO+ckY9PbmJDMgqzQpkGFsyE8tld9aV05QJzJSiYfeW9DZyY/6pj+P5Nr0vsSImWQQwJjdGbF5rdx+F+VseE4C5aWec3ePP+kGZmvCJ9iEXnYnupJgC6HpdY94VMBapiRwqaJIv4AAwgmxtUDCtiZ1Tgld4wBL0NogTwXwf52PW9SpNAAz6fFHSBeH6d+ILG7L5lnwH97X4gJL8ln4qLHgm10KK09/m9PQn2u9JH14Nov64ovpYi5L2mTaB5OqZ8HG7b1NFVd2+mM8YTLNuhAImyWCJ4pM/abfP87IiU6LKh407N/HsfyKCK+S6XU9IsX9bBkNPs5IZXBTgthhNBPxNqUFHi7jbI9iL10QOFTRbwGN6xWSts3twlZI39EFAVggXP+mFOBXcct75Hx1p2iz0FyR12vENCPryX8L9Epp+XhgPbvwqL1C8s/vGDKf9/NWhxCB/gdBf8FpG5df6BWT5a8ffEMVUqtFEj9JE88DPn6f6vVZ4+X/Q1yD4fZJFDq25pADw8FtuR5ef4fv+3sifqsv7FsS2XmRwRq7oyoHjM3z2gR2cKjldV7hFyByVlb0XEb5L2rsgdlmhOv7tBGzJf5eHJnqUJnI64/KqSm3kR6l2D94iiIO4/PM//zNawalcaz0o7aN9E5Mjl9mRUUFwV/ub/+NfvvzVa0HPP/3In931f4s9tf/n4EV+xOpnbQ51PbXkf6+Oig1b5mL44esz7Y2ffPr1/3XlvyB49tG5MH3L7lxNdEWueMn/gyZ6tCZyruT3/OWDrpf3FW7g4NwS4mx+cfv2bbSCMzG0bo3I6edltdQl2L2/KzVUX1BDJ++bKSVkfhjrqyo4xdqRH21nruKYTjGsUV/T0ctCokWPJr+fHqzIaeak50TNkwHRRI8Gk/p4XhUk5W7xJNHTIKiXix5NffzGogHgpTfVJT/UqNec73eKII8f2EwQ1MvHoiUbOgoy9zSo7q+nZAYXfVkWgh1hBEEQ1EsEQRAEeTzB/FgEQRAEQb1EEARBENRLBEEQBEG9RBAEQRDUSwRBEARBvUQQBEEQ1EsEQRAEQb1EEARBEAT1EkEQBEFQLxEEQRAE9RJBEARBUC8RBEEQBPUSQRAEQVAvEQRBEAT1EkEQBEFQLxEEQRAEQb1EEARBENRLBEEQBEG9RBAEQRDUSwRBEARBvUQQBEEQ1EsEQRAEQb1EEARBEAT1EkEQBEFQLxEEQRAE9RJBEARBUC8RBEEQBPUSQRAEQVAvEQRBEAT1EkEQBEFQLxEEQRAEQb18/DCbtEOy1tMq6hHdXz+k0pvn73a0Tq4Yw1KfJSbtkKyx5uCu95Pii+X0nJfRmKb3dHvP6IJ7bepHeUdLl5Z+4sufNijOt9eU78t8J37XeQrbw0PxFJpgcWLoKcjMqVMZAWBFxpevepIu8+12FTV5xYao/V6ec3/tm2N/G3v6188+PeXPBOhqs+p9c3dH8xhPWMfI0Ft3+FiTrFdpoN08w97JyE8QOVjilLL7dFdPZ3P3NSBc51I96GHpjvSKbp0JgBF2JHSt+0IpI23T7tTCdvU4AAhLg0O4xJMtl9dkZ87Jepq7FDT4jqMjxfjyiYC1Nlfa/HEU81H5oLrsHf3ivTvEbBcAgJvKj7f93u9Xv7jLr3gv+K0W+/m98MILfD7vBXH0tryKTs3f7bjuT50FG/i/eGYJ59fP/IJ8Ib7867FbE45ywnNzPVv/lNdqd/hCXSiKCX41vkS+YDrSJkVVWsia2D2dBnt/oWvfsyWnh5NYcrK5/ZO8aLaqoywt9QuDg/cnhXE78gqzRHP+YsSK+EMN0lzBgmsq3I359Q35QQQ6jTvFFJWeuy83gommQL18smDzl7MeSRd1uDrzYyp5VxT3XojztNf7R/6z/69lLwEAvFj81+Gr/V/L+vuvXr2qVl9uyH3t6a4PXuUv8dt2XHHTllg2xgfGd3ok/fuh4tx/Cl3yd8WJdHFo/uWJPyF48bnrdQW59Vq7xoFN33d2KcaMA21dIwtkIM6s7Wnr01Oa1tMau56I6itI2n1RlL09mEO4MNg+UXtPNFd8VFQYMauSZ7j80iny4crlcxdi6E8s5fHd0GFMMMgzDDQC6uXjjP5cUdLePqe4fVpTsyOzVmfn2YbWQonh1YxIztQDv175wtMA8NTkcVQ379+n/rvsSsP73pcl7/hFlliTzL81Zv+r26GrZw/lvp/6531VZ4caNy8BuFyU95+TQyn+ptRVysMH7Jp6Yfhuy0vfFJO1Z7M3sTCKzIUX90FG3KbEwvd97HkibdPBWh3TN5j34GSCs3bjrAcVXbClIAjq5WMKraxISq8fcMqooqFjV3xxp85e/6Ksr+pjRsZ6WfDYTz39jLVfeUT/e92+l+Bm5582/esVS4o5prkRcaQ44kEU8Os3cv/8IsDNy/85PPl8N1FcMHQcarcrxHQXJ+/JTljDWjhFRoric/ekhj1nTwefGuhUASzlL8FoYCG0FAT1ElkU3NBonXRls2nkB5PdZ5sULadGWCFhVjJunrbxU6/38yKeBlD8a36nhSxXt9VJcd6Tfv4UL9DraYCbN6fKK+OFiN8Ryvozuse9yMyUngIABklMKi9qVKfWGLBNzHdLQeYfs0lvMC2cx5mb/Fh9n7Rc0qWmgR6jYKnn2rdTU0I5xL02r+6XdZ/t7Dh3hbmr7pBAWVN++FibXA8s34j3cnOivF2nRDt9NeVHW+UardbI9Ap9NzM7zo+cuVM53HWspr6lb1A9aiI4ouiUnVkb7w1hjalaG+obW9p61U/zg9/cuSd1LcuhB7NwV11HVWnt0N+N6kG1mRe5p3Rv8IM4hhqsL6tq71X/oB1j8NfEpGclrnUHO49OYlxetm1H1ZARAOB02u/OAgAzqODTQxNnsChV48cHq1r6RsaZHqIN2z9MjZwSvlgxgr4lO3Zvl54GAE1xhKjYBYjn46X/kWF19NJs6JEZwEv0G0fGA90C/+AHbV/f6DrZ//ffh/5yxvNv3vz7TQDvQN5UFSZXiPnQ1fFXQ8JzMweOlE519QYnQHC/FlGKpory9h+MBo1CC96xhZIdQptvY+N8k/Z8c21zc+tZlZEljEzJy93EI2YuMpNeOahdIvK9X+KjsqqSE70Go1apMT4bmlWWH80B/ens2J1degAAVUGEqGDKQ63I+PLTeK6L3TXKbBhoOFHTIhtUa/QUg+lmogFsvbVZU7srp/juJCvTO3Tz3v2J3gQAUB3pSb1J0lwfBoBJUZVX8FnXwCgAsIJ2HToUx73781u0/ry0oPxEh9JIsDzXbsnO3yKcktBr7YH1SllPt6zjK5l6RX7zB6yLx0rLTnQpxhgeotisD23G5fa0FDM1cLyo+HjnwKiJyRf/MTMvPXhKFTKpWyrK6mTK/9bqgRuwMTU3babRb0vFZ+/VxlSNxyWNnVcUagNN8oI2peamh9wrVkrRUFHeojKaaSNlYi4Xx6WlRq649/rjuoFznR3nv+7uoxOOS14zNJeVVDf26WiWZ9iW7PwE4VSnOaZqPS5tPCdXXNMZbzGZTxkfouHO1UPeaK4srW68oDO68sJS8vIThKSZGmiqKD/S3KszMVeEJORkJ4tYd4uprb71bGfHORX9hqQrh+yRVlR+0qWgGB6iqO0fZk7xb7ROdqzsRPcoTVMUzWD5rtu6fYuI7YxJh9uz5Ja+e1+Mnzj1qIK++98DMQKh/+t72n6+dfv27du3jYMNZXlvivwFQv/XP8hPTdq5u0xS+W95b77sLxD6v/LRReOEi938r7rUTTtPfmu8ffv27RuDB2P9BcKYAwO0zSegrx7NeD0u/+RF9c9a9TefFW5+2V8QVzdy6/bt2/TVT/PeCM84elH787XBk1mhAqG/3/bOu3d8mAezhP5MVmhgVufPd976ow2BaZ33fzLyRd6bKZJv9Ldv3759U1GXKPIXhOZ337DrqEVufr3TT+jvl3Xx5sS/ao+/IfQXiBNTkzJy/nLo6JHSnLjVAqG/ILTw8v9MsI8NI9y+ffuW9uhGf4Ew5qjWjuI2dia+5P96pdriwX90J/0aAF76d/X/Z/nX/+jcvAQA4KUjP9pxr3/0/3k5wNojuulXuzm4O8g/8IPBm7ZqprblLxlvBPkLhJPOHPk0NTC88LLx9u3b9MjnOwND8y7buor18386fzBpw5v72q7+pP/+bOmbL/kLhBsO/pfNItOfP5i5+ZWX/AVC/8Sz90rAeHFfeGjiZ9o7dfLgptVvfqqfXDSbT/40oQS+LnxF6C/YdHzk1oSHtFmjbl5r270x9PWcust3Tvjp4tG0UMH06mTh3TdPPU3flviSf+AHD/5yU1H6yksx4HXaIQAAIABJREFU92oE/U3WaoHQ//W0jMTM/INHjh/cl/G60F8g9N/86aTqZfWBb+m/OVmasd5fIPQXxOXlpKRm7DtUWVmasdFfIPQXrD909eYMtcZyS7mpPPCav0AYnro9NfWD0sqjkgNZMQKhv0AYU/lfE92Lvnvf5s1/6Ry5efv2bXrki52BQn+/7U0/37LRIqwX30xX+//be/u4pq5s//9zByenpU1+cg2XNlhr8q0FmnpAJhERxUJ9CF8oOCh0KHhLoRcLvQreojgFaRWYEWQqD1coXEFaUTtQqVgoqBQqiBbxAagaqDapSFJpwoU5p1JOrvny+yM8BIQQFJ127nm//EPNyc46a6+91t5rr7MPdTYj2Cdsz+etXbdV1xpK4tZJxNLoU71D3ilzw1LnwJyvDf/sbc0LXSomZdF/VQwMucqqvJ1hrqRETMqiE6PDohL25BVk7ox0JSVicmnkCY2xjD9+lbHeTRa5/4xBkh+vHItbJRGTkuAT1NQjfoaFPJiZHPkSKRGTS8MOHMvcFBmZmJF3IGdHuExMSsTSyKO3h8LK5RMle0KXikmJeFVY2KakPQdKDmQlha2SiEmJWBp2wKjXuj5LWLNIFv2ZamBwcHCQ6foi4SVS4hyU8XXv4IzzoPGy63CYmJSEfa4x9lMHAiViUhJ8eGSEMJcTPcWkZM2e89Td0WG2hpSIl2z9+o6RTft4Rn852oXU52FiUiI2ikMTCPBppLN7wphgc0fzIzU4ODhINWx1JiXBnw7LdvvYelIi9kw1GnLmCTYhnQdfISWjY+NOa+bOY0MuTHFwvVvY0VEfx9THLBWTkvUGSUx/eh/x0jjWDigyfSRiUhI5rMaplTCteNlZ8AopCf6Cus94ef4dIQA4JMun/qnek8FWePrt2t4JY+GBdRLxhmM/TjHWVfUf+I6JlwPtyask4o0jFkXV/zn1lAnFT3a9QQDP1OFYy1ze6SkmJcGfU6a7bOB264ENY+Llj5+HGQfagW8P7tjfPjB5vBzqdON4adqies/sWCVxDh/j9Cc2pwnmhFXBpETsnjQypfjx0zAxKREv2VpPjcZU19CRjhiKl+s/Voy0TJ2IdiYlYlnOd2YKPDhIfRUpJiXioIJr1GhYinOTiEnZHjnzAPHSN/MKMzr2d8rEpMQ1cXQu9ePn0a5rC0blHGhP9hw/DRqHie4z3drAtwXrpb5jFgN3qR81zNBcPGapmAw40Gn0S7erwqQSMembOaKBu4bB7hlnFB27Pg4WkxJxaNWI5gau5LxCSl7ZrxgwXmP8WWZOvJxJIb9QGc3DwsSkROyZcEo1OqIPB0nGuUGDGTjHGPl/qjUvSCImJeINQ/Y8IM95hZS4xp2hjO9uj69hVfDjTMfLB8vHMm15H7YBpL9xPYWFwHuDND2+ueVAsdx/myGzZyhftnW2H8nJEEKPxbOLu/p66OGqDU1tZlEnRewOkWUT3Me5hCVBAC6ubtZL5k+agumrS0lt5vkXLzYuFrfkWxuyds6RqfGetiPZGK7A1hLyuzrjwhZzBJskWUjrAMX+Dytdt3k/w4EluTmRNGRgmvYfkNMD2aF+RU9wCUuCZ0mAcXRZ9qSLkJjq0/vCar5oJPlCCH1WC/L3q7s6aYBrphKm0eEUTQNzufcr6l3DXuRjs6dMxt6VF8QffeyNo8keEz0HYMGxtgRoWqc3WerJFSyWCoki431Ohu4HzuXmnVkYu4wPcJdv32b6jie5XuAdl0Awbk5DmuBYC+cAFMMwBrVPBmFj72THR6vR7mM/A6g/yS712R0gsgSxIGTXgmnpdAp7k+9PLuvmrEz0up/0FF/i74iW1sbKdp2TIwd6dU2F1sEG8u7GI+fo5au5AN1y8geHdW7WYzeYbe1Hk45cVz8nNDb1KDUMRJYwZwgYHnchhJJRw+bae7+IinNU1wMV8vBfmDfiSzgOPhLe0WpKqdaBJAAwHR9lNVLab6LWVnMsOTxLHkGAmSd1Ie0WWU3e5GTdZ7o1vbosKVduG53xopFvs+BaG4bp9dL0Wh0W+K4yLkG38YxYkdR0Uv1RQfPGPW4Gt8qbBeBpR8dR92u7xG0uOrpoLaUH1wLQq4/sKlSATPWbvn+ZWSGdR6+zXSSZi7YuKzsHm9Go4fKyEFeVdA8N8IfNgAOA4M0Z/Xku+Xp8yJHXijWtxxt6/fz5dENOsQKclX5So1HHcXg1QHQwU3E6t/KWR+gzv5j9S0ZZ19AHzBbaji2LtBZLRGhWdF9o6YGDYFLXwRvTgXR7VSsgzTias5xrrgCac6X1DJxenDOxKVgKVwYKh0S91Xhkf25DPzB1peE4wSZB5PcHx8L01vI4n8ayDdGxb8ocDI6daa88Q8E+oeSvftYTzTBMfToTcG24AKB/QCVMFsYYgMO5342BAa2yFwD/BYepHoZTZr+Zcvediqz/O8mFBGEBmBP1LcbeKmH/+qvCiv3Kore9alaExW4JX2n6qKDJr7eW+gUNb4nJqwqzDyvNVAIxVnvWK0Lc9+6oP53m+3K5/5Ztm9aR0wtsU9hbR1mVFhC6iO6vy/nL/Ui0ttVUKWMd7Qh1bSUCdsW2hWytqy9p1KyWWdNtpzrt/JeY3EXmzLHmAjrozBF4qNcmUBuHO8NFwgRXwANG9/HUjTXdmLtxf3WU0PxGJu0+063dqj3SCmKFkD9RX6su1HUBsBn3KUe0wh4n25jWCwrGbdIKgyfGqkldXdYO2JAi7vQVpH5UQhocl3n9Szzn4cItrqC1Cq0Olu01zTpA8MJTY7/7L6QLHwqtskFOhz7DBXR0NzWmatCCZ82/H3N6sPrYXtXEu8ZWAh4AMJo70ygF/O6WDqC6pnFEk057VQmAMeU1aUVtccrmqC0fdsz1C19uOXOjzUIQuq84frUA0DYd3BHgGZJ+RgsAP6sVfQClnnh5avrTh8XMKYEgAB19n6vTgWunLg8Ajy1/zdnk+nKgOWFd1uw9ZclLn5x8ocsABGf661yOQ1ROwdtu1kDX6cKYtR7hBaaP/jF1PdPdVpa9I3xjUlm/5PX1wvtUqY1s7+Ekf3sO+jvKUsI91iZXTqvudwp7U8q1ADjE/cYa62UyB0BTW61goDhZR/jIHJYFrOICzaUN3WDaq9tFvov5Myfw3w/mdrsGoFQ0MxPdZ7o15nabCmBG5hBj3Rp1c2KT5M2ZQwBgpiEh09WuAkBwiVn3oZBHJOQ0l3hckTUAgv8EB7qeiePFLL6tFQBQBim6q8JWe3kY/3mjWHFf5vdg8ZIgCAB9au3PEy915lpNKwIBUDZcnXbCRXVpkqNS6Las12S+iRdEmzJyUsJW2j/52Awv5eyC9pSfO5zgIwL0HUX/kVypHZ2rtpgo+Df96QzHyplUAmEl4AOU9r7Gwk9nC0t/AIRv/9HT1PLydtm/h3/h+fGh8PmmZldaGphty7uPla4F3yUio+7LglhPPqBrytqy5xx9H9erjm2TrQ4vYmS789LiA93mPsAshBDKdv217vjuAAcC6CyPiy1WTXcwT2ZRFgRhmDDdd1E+383fHuiuPXWjo+Y0138FH5aOf/DhA21HapUtVR0iP8n9ZEoe5RCYDlRb43SVb6L7pmjt5oWJjp3iEE9wAKBbrR33XcM/eQKe+cFvFkEA6FVq7jt8PQIhpzvvvgtw7RzmABYEYQFAe6956/QAYM3nAcBst/istIy9o39yE2W295Uke6B4SYg8nSwAdNRcHyuuRqkFIPJ0spqGF3N4jgfo6veXm22vnLnOdgRAnTpUM9HYU5Qk51/Vzf3X6KAFM/+4t6qqtKkPALhiv92flGy2B5jmU+06PC50sgHQkX+4YwIzM/3pQ2AaSjBH7dz5tpbQXu+ZTPjJj7sbuLw3tuA2hJv2J0gnD9k/XU4JTOjdejR9uVFI7esb3yyjvaaFtb1guv3KXC8/clUHAHwydG958QY+QDWcnvSshkmvpxv3/KlOY+G2daPbA5Wt67UNJXUaPQCOyGtb6bEEFwK4WjeNx+1NW5TlfJd5ANQ1p+73zRwWAve1doD6s7zcU3P83PkAOE7rfOcC8o9zP7os8JZO8yyIRz4EzPVmz0ptAXR+WnSOfvDuM90aMU8qAqA+/lHzBJ/aLiF5ABR18rEfUt1qBrBeIjHf1xPzJLYA6LOVV6c9YXpkQk6P/u/bu8F72dfJErC0W2kPQNfy9djdkLvaLg0AcqWYAwAE32mFx0rP0T/LpYL7K8F4sPXlbLeI1wQAdaqoVmMcSxrrusBxj/QVWZjhi4c+4jgFrbEGcDUzPLFcMbzK1pwpTK+YND/FXRLszQeYxri3M2tuDRsE3XFkd2aDVkepegBQCvVQh/b/ROkBPcPozQsSpuKHjrpUnF4yvK4lbJdL+QBvrhVA2Pm/KgTQVRS15eBI7o5uOZh55Lpuik+nmicynd+bPSlnhuScUgkWIDgAetpvmzGiLIXuC6Bpa584D3934GcAA/eENwzIDwR7J14Wbjj05QdDi8uByykvP/1P/7w4dvTwgrs/lEUFf+Gx/9AGofFXU/yDy26Pba/7G0U/x8Eco9cba8PwqNzIhIzjsGIhAXBtJ69fmux6RqtiAL36u75he+hlAECnm2aX6eRHM/Jbh79lI10+D7CcM7K3opvSFE1blIXQewMJoGv/jjwjr6ejfzI/Vtkuk4kAzelm23WSoV0wkd8fFgDqunobmfuE4fLuBHdqlsAT9toULU9npOgnn+QJPEKlAKiyrTFZ54a/3a8sSy+cfPoyefeZbs1GttGTA1AVW+PyRz7V0y1FafmXaMI5LMIe0DfnfW7s+rTnqzpgQUb86+jjwlObh42n4YfKEtNqjN5SQP2sm3qK/MiEnNZC5WRxk4VbbJSUAGAh8ImS8YCuT4sbjPqIuVHXQMN63VurZvpcrwc834fjtCkj1pXDnEnakt9meBUi3VoYl6dyCM1IXT0qrLaPAjDkU4bUR2n7ATCa4dBIOEbuDRUC6KpI9n3ZL+TtbVGv+QXmw9tTMLn7lm7dE+YAoL04xsfL982YmLdCZD7bWh2Dl/M5Dj5rrAGqalvke7lZKdvCE8o1FgBdm52aljK8C2WOYBPeOE9EyPfFpBjeMtGvPNWo5a14K8ieA0AUkhrrzAGo+vTwl7xCorbEhLwSmKha6rNg6k8nz/m4OVgA7RmJe8vLDmamFHUwAChaB+BOD2XkRGgtDYDuNewxmqMEvpOUD1AVu5KKjpXm786sMfX2D76Llx1u1LVO5EF+aL82AOD6F7U3hiPm3T5lXUGC7wvO2277F1669PFrwlnDYfDTgtrb6G0uLBw6UH3gbJL3uoO3f27Y4b365ZcNf9ydX3jmhYQ+T9exdq9pbVQQjv6OU9cw6Pp/YgCGHo5jfFs0p8XkGEIH3XLyG8bGb+srkxvYZNdbSYOkAJTpETEp2Znb347JbtMBkB9IS0nJNOxgTdxlANWnA0BRDABYcEVc9ZEtCWVKnSFLWdPJcYqKdDJkd+/SGgoAbVwHwFA9NABqtNNNW5TtuqTU1XygI//NtSHbM7PyMxO3RkUWdQBgzh3KLiqtUU41TxJ4+osArufoySEWAu8gEoCLn9vYPmBoWgfoaOPdK10P1Q8wNKUzS2AAOrqHAai+n3SmWzZ/pEw0qBm6hwLQr9UNuXK+/66ElVygvy3/LS+PV6NiNkf5vhJzXuzrNJmhmeo+061xV8an+QuA/uast7yWvhoVtTkqwGttym23IGcuLIShe5NW8iFPj0kfSn7oFEfTUtqE/rtTg0YKPu8aDGO8eegA3KGHZ7Tcle+lBYkAdXnMK4ExKbn52Wnb345MP0cBkB/JzT9SLZ90NvCwhMR4IUcdF/Pf44sjqLa688PBWnM6MyaHeT0ryX+4sJa7bFvORjv0VcfFlw7dSF9z9nsljGt0TqyUO8PhEhbvv//+AzUwy8rJy28p/+crn+1LzfqkpvFsXRs8Ev7zT/5D5cvM9eKE+D/nnO7RA9ozdRd7rSSuz9FfpG1/L/PUD3qgp6GupXfOIvcFXIB4ytVPNh/03/p6NbcUXbpn18RkJPmLHjc5PJ6W+skW4G99/bTq+rdqeo5reFLalmVWAGY9LXV/hpZf7Wj5jn7aIyxxe/iqf752ovWfRO4BbwdJud+bL9gE8OaTT/18o+7wf+Uera451cSseCcjTmb72xGdeC18vE/7t/5e5fff9lt5vJmUEUFawoxPJ50ZzFvIVzdd6rgi736C9NsY/NzNwh2b0j5T9AN021fnb+gcVvzO8kb+u3EpJTf6gf62moZv+593l86dZ0oJ/N8CsLB+we7u1aaL8vZOxmZ5UIS3ycN7eE9bXjx05ObCQNn80ct+KI0N3RQTs++buwD+360v9qVkHSr5a1FB3sHjzepZ5KvJH+XH+//u6ceM7Yb3U11prcYhPH27r/Ax9H0W6hJ1cgADt79XKhXDfzpva/sh3LB7+5qnjXZDtCdS//PiC+9s951nSlBGWZQQ+17eZWoQ+pu1J85/b+G4zElk58D96coXH+cUHq+prWt9zHdX6r8v5Zuw7ucmvv43XAf3RbM6r8mvtnc/Lg6I3bFl7aL+s1+p/mWR94YIvwXERF22yOqH8sR33s04rdUD2oYTde26592X/M55HjobP/mvwuITddVfdTtFJb8X8JwlQJ/J3LLtT5VdeoC+eLL+Sp+N+2LL85nvxqVW3tQBd9pONFzrnSNZKrScwqJ+w31+daDsGVp161ZL0zUtMV/2b3/c7HT9eDOxdM0Sp4Wk0/MC3m9NT6q5vDs1DU9HbnnZZqQXnvgX4uIJXdB/+IlGOlVdnbJ1Z/a5Pj2gqq+/0sNf7CrsO5G2PSG3/r/1QHfNyZbbsxd5PM81JTDdlp/w7q79bdQg0Hm6Tq6b6yp96lZpQtz7eU30UMsDAneXybv+HrXfbczc+sd9p35gDIP69uMveLwwqyF7R1x6tUoH/HfTia9v4cVlTnMswLWX+S6yvNPXf+dviu+U2ifJkPf/EutuYleJsF04cfcBmKI1y3kefiue+n+9vXd+uv3tDdX/2HpEpqa/Odxr3Odk/iue+h9ldcFf0j8+0dBQf7aP3Jr1p1DHoc9Vx9K2J2VV3mQA+uLppk6CXCnWN2S/H5d2XDEA0Je/+voW4eS50Ap4bJ77732eH+y+2Xn1fKsa81aEvPPvsjv1X+nEK1+SOJHiF56xIn4zqTJnUshZ5PKFsy7m7Niy20jIF5cttLiUtSMuteT7fqD/Sv35m3BaTlrNgr6zOv+LW+htq/z4o9Ivz1aWFFbeFG5MTw4ac/Qa8ZTUx28ht7f5k4w9+0vr6uvqOni/T/7PbZ62v535ZPA/DQ4OgoVlGuhadvuFd7xVfeBhPRIzBbeKfdcd9/lrSYSQ7QsWln9YmDMxv3u7kbc6KdWT/q5f4P6y29/9pWzseess00/Cv73L+3ZhdvPf5R0QdM0Hh7Ah6XU2WLKw/G/AUrDYKyB0ndsv4Q2mbLxkmT5cafzeAFV6ZkPfo/5lTUVSFt7KjbIj2F5gYWFh4yXLLx/CPiQj0a4ypVjxCJ8JYFpzUy65Zez2s7Vge4CFheVRM4tVAct9LjLFAbt3mzy+dcaDtGNkhiOreBaW/xVQfTQAppfWmX733COErfdhYWFhYfklwXQUvZf5ycnmLj0AzlxHR3vpG0mbZv75EDZesrCwsLCwzDzs/iULCwsLCwsbL1lYWFhYWGYCtt5nCPqWkpottOWymvjF06dsOneh6VJz61V4700bORmLxVz0tEpB80QCrsWvesC2NZ2/0NR8oaVPkrovTPSI74XRyi9dUBASb2f+P5htKFovKCwkKx1ZV8jGy4nGnfxYbkp6aQsNgOe+ff/eoIlfRM7cqsvbV/zF6bYuCFw8pVxls8o1rXgT+yDgo0Z1rq7mdGNZVRsD4XI9q49peXl1TX5yyv5mDQBLcvOHGRG/Ureo17Z8WVd/prqsWQsbO+buI6zT7m/L2hyX36wFYL2heKUz/x/EA9BtWdt3fHRGzQBzQ4uXO7KejY2X99hIw+7wlJ7gnGNVTFtp+s7Clla1bqJ4qarYEXPSLn5XweZ4Zc3BwoqrjTVXtdbOf2/p2+uOHi2vPNOh1QOMjrGcv/hl39BQP6cxU1668g3PuEvmtTgv7PixyJGpOnM1N2pLYdPw8es8e1ns3iT/kcPJ1eXbN2dVXDecmcyZKw2MT49ePuEZHHrlkS0x2Uq72Lw0f8GD3rWtV1j8ag/u1cD8TuP/1snzY6I+1i7flbPLk88O7Akdff5bcU2eqSVfbm2vyE3c29ikZH6t8dKCvzw0ernXfPnqZPkj/mlLcnNeiXtOSMh+9T+UeXDJzftK3dP9Qg4+wheT9jfHvBxV02/Wtby1BXU7R197ojgYE5XdOPxuTp7I842M3SGi4Y/p08lhKeVyg+8iBE4+kXvjZdYPPKn6Xx0v6dNJcUcQUeEn4gOekQVuIcysCV7txFzNDE/s8D+a5DQbgHBlVJLLyfCaM3/X1932K8vSd6QcVYoCt8UfzDAESLq9OithR8jh0tCsjNhlozGDN5sD6AixzN/kXJjpba68NeYCQhxZUBVQttErsRnWgQXV8eSYrwv8dn/qufItz5grbruOpPk/M/n7VXrbKk+rKagrr9D+ghlx0MT4t9HqVQ1VzRoalSeV8Z58dmp8D7qWrLgslUdpEGlNwDo0rS5QB0vOr/ueDO+r/ztEa+7/seMD6n84I+HYPjcHeISezYJnbQn0Q7Q6wN3GVGdS7dUt/DHOWbQho/qVxhifmBqas3LfsYxlYxwLd0VCqXTN9tVRFaLI0g/DHCxnRt5fW7xUl2/fpX49M9LhwQeKXl2RV0dxZQ5zRobfhO9B1NZkF3dZyhYLfjFKoNuy3g7Pb+WtTCnN8BkVi2svi9/PZdbFFG2O4x/NDRUavCF3caifdW2phhYEbYmcfJtHJ9/bRr98z2vHLfjL15JobqO6J3pqWNtY1srz2Z1kKlgC4HvGJ35/pHN+6LKHtpqxEAa9G62pol3ecGSD5QT0NeaXaUFK545o59ceLB/heGvJiSuyT83w/F+wpTeLeKQKIeyCXhUe2afUcmWbYklicl9dtFHptO6eM6Nnk+uknJpanUrLAOOFoVuPN+mlu3bPWLDEr6w+tr8tcUNyhUI3M60xyoYbgCWfZzHFSu5UK2D5i1my6LWV8ZH5rRBtzEn1uSeGz3bbtNEO+rbs1NE3eBMvhkTYA52f5pt4cby2Nq9NEuE2wQCwfk4yF2CUHRr9PSH2YG6L89Z3Vkw5bLgO66J3bfETWT5ExXClIfGJkSufYcPARMZ+s1nOgLB6ktXOdFGVxITkNWvvspp4KAoR+Ye5E6COfVgz+bKWPl9YIwz2nmDFwhUtFgJQtamZe0Ls0eyz/KgE/xld5/yq4qVOrZjBVIGOphjAgjPFGlvXo+0HLDjEL2MprjmZnHhaB37ArtCJN+Stl8lEAHOutGHktc8WAp8oDwJURX6tSj/J4vJIKQIDRBO2aGsvsgC621Tjthm6q9KPcUNjZdasC/kVzDW1FECw0XL6boJSqFktPESF8D0j/PjQN2eXKCdbXFZ8pPZ+Qzqhc+Lb2fMAql1JjQux53I/6l0Tv26Gs4IPFgT61S2na2vOnK1vZkIPFqzSlmftLSxrVjN8u5UbtiWFkmPXHTpFRW5WSWP7TZUGti5rI+OjPGwJMxuhG1LCY44qGQDdxQGuxQCsV+dU75YSk68LK/Nyj7T1gKEpHXfuIlnE2wFOQ9UodNPu8KgSJQNAXRggLQTAc04ozRt3kPeYy3ylhQAIvl/OsYQXJpkGyY/mZld0UHqGonW8+W5BUZHeCzgA6HOZkQnFLVoAIOZJ/Tftil/NB8C054akC3L2+1kDUFenpBSWnVEyALEgIOfANpd7l21Mx5GsRgZwCA1xmmytNttOREDBtNcrdP42Qw6SuyT8dUFdfuuHR9q9YsX3eE1tY16zZGPEJGUylvOdbFHfqZRrsXxUJF3LgULFywkZZr5Xi9Eq2tQESdqObMi3lu7Jr1PRWnl7D0/6Rs4HISKTS3j6et2R4tJT55UKtZax5BET1AjoNO2tKiupkw3dtDdm+8E2jR4AR+QZnpoS5mAJVUVa4r7SJjXAFfrEZuxeKzDPJnOXXy/YvqtYbuWXum/bcsNWcWt5Vu5xxV1Gpezh2HustCdorVbTC5dNO4IWcACAUdcU5B453aHoVDF8R+/w6M1r7bgA093RcLq2/nRdg9aj4ONw1Oam5x+vV1A8kdsf3knYvGx8FzDX6z4qKq1oblV06wiB1H/j1ti1w/Vo2uai7AOVbUqViuLZe74esy3IeaKFPtOR/29RWa0UAKYi6ndVADgObxXnuKsb6htrvmpULEgqj+OW7YrLrqWdNuXs3WBofxLNmB7Lk/d+S1XpJ+XVpy6pCXtZxLvbQofrjDTtjaNivMs//1FG1qE6eR9nrjQw9r17swU61ZmSopLqhnZlV7eOmM0z87R/TXNxdkGdggHTR2OO3fLXIjd6Cobk1dOKS431X9bWnP6Gt71kr6gxPW5PmWr+63szNluVh4dmNvUBQMtWzxe3AwQZW1IQ+oyRQLeqs3cXlp1RUpYCp9Vh8bF+DlzzHdHI1LO5KOtATTcYlVJrtXClq5CgerRaivNyzK6hHNKkvuXeW8gRtxdlf/hRVZsGfCevt+Lj/MYmJHWqM+VHyssrv+yg+KT3xoT4dUJzk2fKYpMKMSnkpHCc3ghzKEmTHy5s2pB0r9NjLhVXCt7InSTwEfMW2qKcUn2jYvysR25DrzySccFxy0GnGU9oDT4AA99W5e0McyUlYlIWnRgdFpWwJ68gc2ekKykRk0sjT2iMrtXUJwcH/7m2a2BwcJDp+nyrKylx3nTsx7vTaaS3KpiUiFdlXBuYSjD5wUj3pWt21v541/DPkkj+MeSMAAAaIElEQVQ3idgtMu8KM741Wc53d022NdFl1IkwMSl5aU/7qCBUa+aGpc6BOV/3Gr7Vmhe6VEzKov+qGLrmzvkd7hIxGXCgc+Q7zLU/y8Rk8GHVaCunQiWusbXUpPeV8RIpGfuVey9q3eEuEZOS4C/GNPPjp2FiUuIcM0Hj3+WFRX+umbxFpj5mqZiURH5l9FVVSfCq6AqNGUbScjBug6+zQezbIzdSsH5JQN63jKGzwtx8M7810QZ1OS/S1T1szwnFwODg4F3quy9SXyElYjLggEEPmjOZMcEvLZKISUnYl8NCKg6+QkrEiyIreo07LtLZPaGeMt8mgw98mbN+yVIxKRGTvnvkzODg4I+fb3UlPYc0pqmN85SISckrUVt35J2nRowhPDjuM4O0mvpkXzEpCf5YMTA42PXlweQomZiUiN0id8RGhsWl5u3PSd7kKyYlYjJsbLcy1w5ErwlKOnxe8aNK8fWnqcFLJOKgki6DSX9bErlu6+ErlMHYMgMlYjJgTwszaS+c3epMSlzfbR2yxruarw9nRPtIxKTENa7qaKzMWSoRkxLxRoN5TKqZwak/vafzLhZE+gTEfdradVtRvz/SmZSI3ZMu3xkvhjgoIW5jZHRyTl5eRvRaiZiUiH1yxoz0O+2HY2SugalH5dTg4OAgparfF+Y8pUO4q6lPDnB2izwgZ4b+uSdATErWJFYNCUy1Hs1KWC+ViElJ8Ge1yT5LnRdJxKRk/VBnGAapJPjEmHFj8ADOgdFhG7cm7yvIy0oKc5fcO77McUQDioNhUslLO89Qg4ODd1VHNy0VkxLnoK3RO0uuUeb5FqNbWPNuUmT41h1ZBXkfJKxfIhGTkpd2nh8V6faZzHDf9clV125rvvsyY/0iiZgcM/R+/DxMTErWfNA+uUYnVsjUQpqCqo9dKiYlwZ/e41Duqg5vjDTymfdadnuyp0RMBh+9bdTcl1tfCjrYdXdwxsGDNnBXkekjEZOecUaBrevjYDEpEYdWUaPdEO26tmA05Azd5HBXmdeIufGSOr/Dc/xlVEOCKykReyZ9TT2MeKk5FbN0bCwcHLxdFSaViEnfTMNAHbaz9SM2MdCabHC1+xXDHuF8nKcs+cqkXq9rf4B4Sg3cOR+9RCImJWHjDHooYAePN77e2rgNGZdNqrTr4wAxKVmTpRhRwNeJvutHxJ4C5scrxyKXGMdL5uvYpWK3hJEf7fosac/5Se/6u4/DxKQs2TgY3FUdWGsULwcHB263HtgwNl4OairCJWJSEjY6FaBObfJ8JU8xHZuUrNl08DI1OKhprT+rGhgcHKTORC8ZYw9dfw0eawxU/buyl3a2jmq0s+AVQ5Aw/NftY+tJiXhJ9FEFMyrqxqViUvLKx6MBs+vTSGf3hPpe4x7U/EgNibrHxzN69E4Hqc/DxKREHDX5TGtcvDR866tIMSkRuwUnn1ANDDLfNZy51ju1ZqbQ2zg0VWGLJM4xZ6hhd5HnM27WOCxGUME1anQIx7lJxKRsj5wZCXsVMZ5it7EKMcMhdB0OG2sDg4N3VQcCJWJSYjTrZC4neopJiXNgwtFvmcEB1ddftg6Hf5PxclPV6CxBVRI8dlJoniPSHA0fOwP+NmcNKRGvG3H35viW0VtYs+c8dXd0er2GlIiXbP36zvCNr5OIPVOHxx1zeaenmJQEf049cLw0U0gTK5ycNaRELBvflQMXU4PfPUOZdPcVoRIx6Rl3kRkxyD1rfZNbmMGHwIPvXxoq+592dBxNJdkucZsLgNZS+qGM0EdZjdTNQ1FrA31fDQl5Iyo8OlM+T+ri6bnIyuxGprHDl1mmhfVqmXF+jysN8bcBtOX5px9CtfT10vRaHRb4rjJOGth4RqzgAOqPCpoZAOCIvDysAXl5o6ESh2k73sQT8gDFp9UKPQAwnWdbLGX+z02WwdB1XVEBgC0510QChVar+gHwbMeVKFlKQ/9VCHR89HGbcRZLcbSY8g92MpmR4dvbEUBX6/f0UJKwNP2SNDbQzFQsx9qedHpqTIqFpnWga9OL22g9ANiuTYiVTnLX2uqU7DaIgkNfNJXYIWzsnezGJTP57q+5EUBTyZDC0Xeh7Or8UD/hdGySvzIq0IkL8MnlrgICYK7Xne8HnrIfeZaLL5ZaA5rmNq3BUG+VZ1VoNSfj/H4fGPBaSMgbUeE7G3lSqfvqhdaG3Q/DUxCz7ZzmjdwRf/EqIQC6mx7qmr66lNRmnlfIYuPEnSXfmgsAmtrMok6qYXeI7PeBAa+Fh7wZFXMMLq5uPkvmT2uDkmPxJAHgxZCI1QICHNEyN4fZU2lmar2N6wS3Tbu2pf7H8JslLPgiPgBGd3e8GDyhRDSSi+Pae78IgOqiRyo+MlNqKWufsQqZehegLe/DNoD0N050Wwi8N0gBtBwolg+PBOJxDgDbtZH+CzggBC6epDnP6vHmCUerBQUe3vYAehRa3TQcEd1ReQmwFIpG7stWYm8JXD8r7zfftxjdgrP9yLFNhNBj8Wygv8cwymAh8I5LiN8ZNjzYOdbCOQAYhnkkDtBkFLEPiHAG1CV5jUY1iXptZUGH+5tuJusJCRHJB6hrHUOOXVWeWTM/JsLxoezVP5wilie4Y4RVN9Z0Y+7G/dVRwvtvxFzo1qoOAPzn5owJAYTQxZ5T1K1rOaNkfGa42FV1oa4LgI2QP2aMcUQr7HGyjWm9oGDcHAgQ9rLls0vLWo+f1/p58+mWY+1O7yTMTQ3P6jxe1h4eK+ZoG5uxYsfk23gMTesAELNNVTkyikYFAAs7d9H4q0R+ke552+rLC2s2ZngbHAjdmH/aLuLDKR7wJ2xJEarlnW1djIcDoa3MKLfeWOAyjWLycYUmXJcQP+tz5S1Z4a5VstiYyKBlgsluWnOmtIkBYWfHn8p/EfdcwJUGr+I2VrSW1qj9ggSgz5UryJBVNtOyyTm2VmNl76cYAAw1MFzATlhyCQCWXIPr1JyvloPnn1W+y3ka9vvY2EeZNOdK6xk4vThnIrXQ7VWtgDTjaM7yB6zntwAA3hwBz/zRqpzuWOY6+QQMC66sOZKb1TqxGOMNZszop1tKainAyVkwrZHLKOsa+oDZQtvHx9bEiSUiNCu6L7T0wMHIxVvbPIhCCWvu9B2Rnmb0AEPrRlYFFgSPA+ifNIQ9M33LpIuZsR9ZS/2Chrc85VWF2YeVj9IBmi778Y7yS3+zvCavXLUixFBHwlw5VMYNyZ3C0DhzxUJAq7qkYoIEBN2YfYD5Q77HQypCfBT1scztdg1AqWjmEfyYnu7qMfzlng4R8AAwfTrdDP+kjro58XMavDlzCADM8I0T9v4v8YC2smYt6LbPbpD+UtL7NTtAW3a0ndGr60/rVnqZ2HsnuFYcAIzOxC3oWiouMgDhGuAye4LJfoQ/H0xjXplyeHF5SOMTMvWu+Jz5/4cLdLcpaNDNH+Zr/WK9HugMHe6yhOK9IU5c4Hp1+tt+si2liomNQ6dtVwMgLO9rhsN1/IMXH+g4UqUEtPUV6sUbhuaq922TxAI3BwvgRt157UgUaNMATl6GwjSd9noPQKn6HsTYddqrSgATz/v19He3dADV1f93GK33pzf6anX+ezHh2w912YWEOt7PoP7ulg4Ab7rnE/SqqAn/38owRWA0d2ZSdcR9OCKunbsI0H9T2T48pvs65H0g3LxesJyObzG/f7vbyrJ3hG9MKuuXvL5e+EgdoGntOQeHLgDaDxVdMahCW1nQ5h7uMfXDavMWzgWYG99o9Tr5wcyWFdFBzzys8PLonieh2hpVj+C0TwuOYS2j7ey554kcAOAJuDO9UOcQT3AAoFut1U/wi+AJhg+j4Tj4LOUBTeUXFOfKv1vi50DA1jPACaBOlrZ0Nlf2u3k/xzE1k3IWAoBaOWmOuq/xo1MUwPef8FFKcJz+NcwBUBwqbKIBurGoVhDhY0bJNSF0tAXwfZOy48je5sWxAQ9+vLWtZ3Txl+W5G6U8QFObFpXTwUy+NKU6e+5rlsNxWOc7F1B8Wi1XX6js9QgaWxt8PzZp47XrbRJMY/reapUe6GvO29tIuG7b5ScwTtnIzygffHaoujRJIxYAlA1X6b/XaJ2G3vTaml2Brq9lKpZsy9mXELpCyLu/UGRYu6unuZliSH33qbU/T+xp51r9vR2RhTBoR4gIVMWfchu0gF5bk1Uo53vs2m6IE+b7FvMs6tg22erwIka2Oy8tPtBtruUjdoCmNSYMinAjoC3Lr9UAzNVDZUTI7xeY40rsbS0AVZtcUZX++fzYN8mH96z8o4iXxLNSWwCdnxadox/+r/FdlgkAaL5uG9t5jOqWFuAs9hTOuDZtl5A8AIo6+dj7o7rVDGC9RDLymAoh9nXnAueLs4p7lvvYEQBsPEOXcUDXZueUUm4y089U2C6TOQBQVNd3T7K43J9Rz8B6bcLmydL3Atnm1Tz0VWd/qVYcO6TyCnMxa8zwHJ7jAVRDXlKZVeSDvuecbjtSoWQAEILlUTkn9sp4QFd9s1Y/0RTBUUgAaCs3VLFP2/YW+P1BBKiP5x0opV6WjSSFHsAmOaLw3BM7PZiKHSHrw8MTSxFefOLDkUdXDdkhUBWFNd3374DmOtsRAHXq0AQPcVvwHZ7jAbr6/eUPYwJqWjPT1RvTXphyVAnxW+94Ce5/3FnwHcQ8APLPpze/IUSeThYAOmquj51uaZRaACJPJ/Pjpf5hOSKuc/Shv0a73C6OeS0wfHNyje2245+nedtM27eYMe4a9/ypTmPhtnWj24OfpGqskJkSkrsizN8GzJnCz66ra/a3LQ53Myutajnf0QZgvilK+pB5NWblwzw9egbipW5KexJ4hEoBUGVbY7LODTuAfmVZemELbXYjACwIAoBWqfrZ1FWiwDAXAmgvPtKuM/bRNVcAUcjGe3y9mesAxlQmISzCHtA3531u/CSv9nxVByzIiH81mu9YOv7elQN9Rw3ttk40ZCQuQW4EdC0ne9y9porlz/jFruMDHdn7Gu91V5rTaVsOqglpdMG7JnbIuYsj1s8FWvbuSKwQhPqY+Twvx9bxaQCaZp1/zAMcUGDoX726Miu3YdgQuM6eIgBz+JyJBhV3SZg/H2AaE1PKVSN9cJemBszzYhaCVUF2gLamhPH2Es6ATfYra/ITYvJ0m4411n1WUJCVFrvWzljbXNfglVyAaYzbnFajHmqDuVWXld2oMduiuEuCvfkA0xj3dmbNrWEzpjuO7M5s0HKcgtZYA7iaGZ5YrhjOymrOFKZXqKfybszU/2laM2bobQxatQaA9nstM5Sl1PQDAMXophBjqKOH8wRB60UArmYkHjbKQ/RPleib7RbxmgCgThXVGitf1VjXBY57pO9ommRSQ+IYMhzaG1pzXcTdaTkiWl6RG/fHUuudVRdPlhTsy9gd5WF8DNY0fIt+qnHHaFUMoFd/1zecR+1lAMB4e2fqU3smUMg0hJxigkOGvmEHKPPeS87TBwTZm5cKtOC/8CwAquW2R2ygYIpsR7zf75y9okru88iFB673uUtr7gCgjXcCGKpHB+AOTQG2AMD335VQH5hcQ7flv+X1mb3U0QaKq6oXYgv8ueY3AljaLV+ApuuNKTsLqWWQX+cGbZ0oMWjjt3tPx4bNpUVbkhzydngLOdCra9LTTll67MoKH912prUUAFpNMYCJNdZEl1E9NABGS41kEkL3JrVs2FGTHpM+L2PTCgEBneJoWkqb0H936thkOucFPzfiZJ0ocPSkVq5ziPfsujJLmbdwSvvgusRmxKrD0itiwp7KyIhwsyXA0DrCkpEfS9uyq5a7Nqn4XZktYXrJFRAhLUxsbqPeSDC/YIT3nJCHDqzbGrTgfoxEewcAPeTeOHPm0nVxCcXFe0IcuNCcq1JYCCM2TTKXtCQ3fxDW8kah/GTymvY6/9Uk/46y/YZa0Q1AWfZhIaQLvV+RWluA6tMBoKjxJ0naeoa47N7R9GLAyjFDaWqbpO6xSQDou1C0r04OfPTetqZn+IZEE8GdI5LKfFYIuQBmu8Wn+LVuLte0l8Z4nRBJF4pmaVsV/Ii8NGtji+rvMX4LFdXDAGB6hy3KUrp1T5j8jUJ5e3GMz3FDI+1y2ml7QRAf4EfuDb0QUqTsqkj2rS10crbj9XbIZ/nlfDips6D6ehiA6e4xPgRYR/cwANPz09iTgU1rZiq9jTM2R7+V3Maa7uKoaOb3drr2q2roAKjLMtKY+XZBWwJExLAYfcZiDJW20TQDcAAQC8Iztn8Tsru5KT1EdlrmvVgAlVLeqVYA6K7Oy5/jTsr8V/An2IDYlBF7IyT9TNKWfMHecNLaAnRrYVyeyiE0I3U130g/FABqomNI50rteEXqrgM7UvgBIm2HRhK52ZVL9Y3tL4PH6gdAafqn44j02lN5hfWdILLjqFoB37BBy+HOtV/q7SW1tZyGb9EabqHX6Bb0lLYfAKPpB2YDVtIgKRKblekRMar/K6TbOyi9DoD8QFqKQuj0RrS3ALo+GgBlcvd9IoWY7wCnytX5RK7cF1NzVel+2NPseTlXJBbgnNZ9S9gUpRj93xypUDNA/dFG1boA2+kvsi3ef//9+99fOZa2PSmr8iYD0BdPN3US5EqxviH7/bi044oBgL781de3CCfPhVYA117mu8jyTl//nb8pvlNqnyRD3v9LrLvV9Br5DddBbNl+7rL86ne9s5cERfgtnOSNt0/MdwuQLcCtxsK9f8mvPHv2y7M354X8ZW/k0n82XK9THHl/U+IheT+gu3G8ov7KDb3DUrHV+MmDTp7/x6idn1wfAHQ3TtS1aJ9c5PJkY2r8++mHbvQDzI1TNRd/wEL3hVYA9zmZ/4qn/kdZXfCX9I9PNDTUn+0jt2b9KdRxfAcSVpbySrXPOyEOTw7/12+tnuqrvmgXuXmpGamE3/KdvAKX2vS3V32cnVtaWvBB+oeFxYePnNW7he9M2/UHsRlbBZaip3/8rF6QkBz4rNk5slm/6an+XLc5NeLFJ6dnJJrTmVvjPijvZAC6qbrmSp9gsbuzZAGhPV+W/1+fVH5VU6OcF5KU9ObkL5YinpIGrls0S3NLJb/Q9J3u6SUBse94W35dd/u5VSsX2zk5iZ/9+dSud97NOK3VA9qGE3XtuufdFz3125Hbtfnn9lPatf8etGBsX0xuk/S53Lh395QpGYC+WFVz8Vv6WZdFTw2lz8TLnWapOtparn2v+LZD3t4hb++40na5oar0+O0F3h7CJ4An5ruvc7fR9/ZR9G3FDTWeX5fwwR+951pAr23IfD827ZPr/cBAR83ZG3r7Fb978mr+u+/u+uhaP8B829Cg0C9ctsj6tyCelvrJFuBvff206vq3anqOa3hS2pZlVkMqcfWTzQf9t75ezS1Fl+7ZNTEZSf6ixyecU6sr/xy3PecyNQio60q/arne+8xyp/7SnfHxuZepQaDr1IlzN27+Vuz+PHdKzUz96TgeE7q5WHVf7ZB/871ugXfse+8Euc46f/J7qxdXBUX4LfzN1fyEd3ftb6MGgc7TdXLdXFfpU7dKE+Lez2ui9YCqvv7KgMDdZR4BC6uF3oFLrXq7lNcvXZb/bbajT+QfQ21bvuiwXrFqqaPYyVFk/eRE3mCWlZOX31L+z1c+25ea9UlN49m6Nngk/Oef/IdzOd3VKXE70ut6hoznyvf9zy9xmjPaFGG76NneC2flHVdU+gWrwt5Y2l/2XuyugmuUob++7X92iXTuD6WJW5NzWmhAr6itu9InWLx03hNTOyLgN1YuLy3ov3n14jc3bt64YTAn+dW2ptOVxfU/L/Va8hQxtW9hrhcnxP8553SPHtCeqbvYayVxfY7+Im37e5mnftADPQ11Lb1zFrk/L3BwXzSr85r8anv34+KA2B1b1i7qP/uV6l8WeW+I8LO6kBW/809HOvoBpv2rmivdBOnm8P9NNB7HKcTDhsA0HOBUS8x5zw9Ulv3m39LfFD9h/rLvTlPpTb/0bUusTCdMZ3FndZ6ouTHL5c23Qsj72bv+p8HBQbD8atGczt2eWNjUB9i4bd6ZEOHKvvrx4UO3FaUUa5eEBL1kb8vlMLRS/uWhxF3lCghjq0pCBayCWKa1SaFtyEk7Cs+NgW4OfC7DaFWXqrN2ZdZ0w2V3bYEXl9XQL4ffsCr4VWO9IrLgZEnqBpLX3Zj1lpdse3GTltXKw0RdHrNuS410W+xa0nY2BxYgZgud1iVkbBYCjI5hFcQyHRhl0duvxnX6JW2SOdhwYQHCki9aFpK6J8AaoPpZe2LjJcvMQgi9YwtOfJoU4SnUVGWGv/xySEppCxs1Hwq6pqy0mm6Og/34xyK4NlzMljrasCpimU6qonZP+jmKLxaOW0USPD4XguUkmy5i4yXLQ4C7QLZ5b8nF0+Wl+3cF2UOhZAPmw0EPQNvwefuYalC9uvKo2mWzmQ/nsLCMQVFVPfa8Dp28olrnFfPGAlY3vyzY/UsWlmnAKIvD12W26CFaHRnqI3GYzWiVHafKq7XLtqWGk+xeE8v06G/LCg7PV4AQ+23a4OE0j8t0K5tOHm+ALHVngIhgFcTGSxaWX3XIvFWXl1X8xfn2rj4dT2Dn4OwZ9FbIPW9qZGExD1pZuT+z6OQ3cjWF2QKHF6XeIW+FsoV7bLxkYWFhYWH5lcLuX7KwsLCwsLDxkoWFhYWFhY2XLCwsLCwsbLxkYWFhYWFh4yULCwsLCwsbL1lYWFhYWNh4ycLCwsLCwsZLFhYWFhYWFjZesrCwsLCwsPGShYWFhYWFjZcsLCwsLCxsvGRhYWFhYWHjJQsLCwsLCxsvWVhYWFhY2HjJwsLCwsLCxksWFhYWFhYWNl6ysLCwsLCw8ZKFhYWFhYWNlywsLCwsLGy8ZGFhYWFhYeMlCwsLCwsLGy9ZWFhYWFjYeMnCwsLCwsLCxksWFhYWFhY2XrKwsLCwsMwk/z+7L/T7GXV17wAAAABJRU5ErkJggg==
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
------------------
https://www.wikiwand.com/en/Friction#/Coefficient_of_friction
[img[http://www.aplusphysics.com/courses/honors/rotation/images/frog_unicycle_lg_wht.gif]]
Oh shit waddup
Frontend web development
!![[JavaScript]]
https://medium.freecodecamp.com/angular-2-versus-react-there-will-be-blood-66595faafd51#.4bc9n0ott [[ReactJS]] seems better
http://www.infragistics.com/products/jquery?utm_source=facebook&utm_medium=cpc&utm_campaign=ignite looks nice
!!__CSS libraries__
See [[Voxel.css|http://www.voxelcss.com/]] for Minecraft-like stuff in browser
---------
!!!__[[Graphics and visualization web libraries]]__
__<mark>Graphics and visualization</mark>__
~ ~ ~
[[Maths frontend web libraries]]
http://fortawesome.github.io/Font-Awesome/
[[Webgl|https://en.wikipedia.org/wiki/WebGL]] See chromeexperiments website
Nice 2D webgl lib: http://www.pixijs.com/
voxel.css
http://codepen.io/sha99y8oy/pen/GZZXyL
http://www.effectgames.com/demos/canvascycle/
HTML presentations: impress.js, reveal.js, [[deck.js|http://imakewebthings.com/deck.js/]]
!!!__Audio libraries__
See here: https://musiclab.chromeexperiments.com/Technology
[[Tone.js|https://github.com/Tonejs/Tone.js]]
For microphone input: https://en.wikipedia.org/wiki/WebRTC
!!!__Input libraries__
For accelerometer, gyroscope input (from phone for eg) see chromeexperiments
For microphone input: https://en.wikipedia.org/wiki/WebRTC
!!!__CMS__
[[Jekyll]]
''Frustration'' refers to the situation when a [[Signed network]] contains loops with odd numbers of minus signs.
[img[Selection_615.png]]
In spin networks, like [[Spin glass]]es, the sign of the edge correspond to the sign of the coupling in the Hamiltonian, and determines whether the spins tend to align (ferromagnetic interaction) or anti-align (antiferromagnetic interaction).
[img width=500 [Selection_616.png]]
https://www.youtube.com/watch?v=5_y6q4m0vew
A type of [[Relation]] between two [[Set]]s, such that for each element belonging to the set called ''domain'', there is a unique element belonging to the set called ''co-domain''.
!!__Types of function__
* [[Injective function]]
* [[Surjective function]]
* [[Bijection]] or bijective function.
----------------
[[Preimage]]
[[Hermitian operator|http://vergil.chemistry.gatech.edu/notes/quantrev/node16.html]]
[[Functional integration|http://www.alcyone.com/max/reference/maths/hyperbolic.html]]
[[Lecture 18a: Functional Analysis - more about Sequence spaces|https://www.youtube.com/watch?v=FlIsYT-ga2E]]
//Functional derivative//
A [[group of atoms|Moiety]] responsible for the characteristic reactions of a particular compound.
This term is mostly used in [[Organic chemistry]], to classify [[Organic compound]]s.
https://www.wikiwand.com/en/Functional_group
[img[http://www.compoundchem.com/wp-content/uploads/2014/01/Organic-Functional-Groups-2016.png]]
[img[some_moieties.png]]
See also here: https://en.wikipedia.org/wiki/Skeletal_formula
[[John Klauder - Lectures on Functional Integration|http://www.phys.ufl.edu/functional-integration/]]
__Some Recommended Books__
G. Roepstorff, "Path Integral Approach to Quantum Physics", Springer-Verlag, Berlin, 1996
R. Feynman and A. Hibbs, "Quantum Mechanics and Path Integrals", ~McGraw-Hill, New York, 1965
A.V. Skorokhod, "Studies in the Theory of Random Processes", Addison-Wesley Publishing, Reading, Massachusetts, 1965
B. Simon, "Functional Integration and Quantum Physics", Academic Poress, New York, 1979
L. Schulman, "Techniques and Applications of Path Integration", John Wiley & Sons, New York, 1981
J. Klauder and B-S. Skagerstam, "Coherent States", World Scientific, Singapore, 1985
C. Grosche and F. Steiner, "Handbook of Feynman Path Integrals", Springer-Verlag, Berlin, 1998
J. Klauder, "Beyond Conventional Quantization", Cambridge University Press, Cambridge, 2000
H. Kleinert, "Path Integrals in Quantum Mehcanics, Statistics, and Polymer Physics", 3rd Edition, World Scientific, Singapore, 2003
A nconcept in [[Supervised learning]]
[[Intuition of functional margin|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=47m30s]]
[[Definition of functional margin|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=54m02s]] of hyperplane (where $$y^{(i)} \in \{-1, 1\}$$, remember) wrt to data point;
[[def of functional margin wrt to entire training set|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=57m15s]], is just the minimum of the functional margin over all data points. [[We need a normalization|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=58m30s]].
The formula is
$$\gamma^{(i)} = y^{(i)}[(\frac{\omega}{||\omega||})^T x^{(i)} + \frac{b}{||\omega||}]$$
It is very similar to [[Geometric margin]]
[[Introduction to Functional Programming|https://www.edx.org/course/introduction-functional-programming-delftx-fp101x-0]] [[youtube videos|https://www.youtube.com/watch?v=UIUlFQH4Cvo&list=PLTA0Ta9Qyspa5Nayx0VCHj5AHQJqp1clD]]
[[An introduction to functional programming|https://codewords.recurse.com/issues/one/an-introduction-to-functional-programming]]
-------------------
!!!__[[Functional programming on JavaScript]]__
* Higher-order functions: functions that take functions as arguments. Functions are like variables too. Examples:
** Filter
** [[map|https://www.youtube.com/watch?v=bCqtb-Z5YGQ&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84&index=2#t=3m20s]]: Transforms arrays
** [[Reduce|https://www.youtube.com/watch?v=Wl98eZpkp-c&index=3&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=4m14s]]: iterates through objects in array, with an //accumulator//. Accumulator can be any data type, [[including objects|https://www.youtube.com/watch?v=1DMolJ2FrNY&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84&index=4#t=6m30]]. See [[MDN reference|https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/Reduce]] too.
** [[Closures|https://www.youtube.com/watch?v=CQqwU2Ixu-U&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84&index=5#t=55s]]. Functions can access variables outside its scope
** [[Currying|https://www.youtube.com/watch?v=iZLP4qOwY8I&index=6&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84]]. Decompose a function so that you first call it with an argument that returns a function, which you then call with second argument, etc. [[Basic usage|https://www.youtube.com/watch?v=iZLP4qOwY8I&index=6&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=2m]]. Can use [[lodash|https://lodash.com/]] [[to curry existing functions|https://lodash.com/docs#curry]], see [[an example of using lodash|https://www.youtube.com/watch?v=iZLP4qOwY8I&index=6&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=4m]]
** [[Recursion|https://www.youtube.com/watch?v=k7-N8R0-KY4&index=7&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=0m24.5s]] is when a function calls itself, until it doesn't.
** Promises. Like callbacks but more powerful as they are <b>composable</b>. [[Example|https://www.youtube.com/watch?v=2d7s3spWAzo&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84&index=8#t=11m30s]]
* [[Functors|https://www.youtube.com/watch?v=DisD9ftUyCk]]. Objects that hold collections of objects (like arrays) that have the `map()` function so that one can map these collections to other collections of the same size. One can made the analogy more precise between these and functors in [[Category theory]] which is very related to functional programming ideas.
* Monoids.
---------
Nice game to explain map, reduce, filter: http://david-peter.de/cube-composer/
//Functional programming languages//
[[Clojure|https://www.youtube.com/watch?v=yR9oo0ffJ7I]]
The syntax is so nice. As he says in the vid, there is basically no syntax. It also reminds me of the data structures used for [[CAS|Computer algebra]]s
Lisp
Scala. [[yt vids|https://www.youtube.com/results?search_query=Functional+Programming+Principles+in+Scala]]
Scheme
Haskell. http://learnyouahaskell.com/
[[Functional programming]] in [[JavaScript]]. [[Functional programming in Javascript|https://www.youtube.com/watch?v=1DMolJ2FrNY&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=71.591166]]
[[Array.prototype.map()|https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/map]]
[[Array.prototype.reduce()|https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/Reduce]]
[[Promises|https://www.youtube.com/watch?annotation_id=d3718aa0-5465-403b-bd56-2d603793ba62&feature=cards&src_vid=UD2dZw9iHCc&v=2d7s3spWAzo]]
[[Higher-order functions - Part 1 of Functional Programming in JavaScript|https://www.youtube.com/watch?v=BMUiFMZr7vk&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84]]
[[Streams - FunFunFunction #13|https://www.youtube.com/watch?v=UD2dZw9iHCc&index=11&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84]]
[[Monad|https://www.youtube.com/watch?v=9QveBbn7t_c]]
map, filter, reduce. Nice game to explain map, reduce, filter: http://david-peter.de/cube-composer/[img[https://hsto.org/files/fbc/33e/2b2/fbc33e2b26894055b3a2c8d5d272aebb.jpg]]
!!__Libraries__
http://elm-lang.org/
http://cycle.js.org/
https://baconjs.github.io/ (also reactive)
lodash --
underscore --
ramdajs
[[Anjana Vakil: Learning Functional Programming with JavaScript - JSUnconf 2016|https://www.youtube.com/watch?v=e-5obm1G_FY&t=644s]]. Another useful concepts: [[Immutability|Immutable type]] (and [[Persistent data structure]]s to make them feasible). [[slides|https://slidr.io/vakila/learning-functional-programming-with-javascript#31]]
lodash -- underscore -- ramdajs
!!![[Redux|http://redux.js.org/docs/basics/Store.html]] is a nice functional programming-like framework for [[React|https://facebook.github.io/react/]]. Learn [[redux|https://www.youtube.com/watch?annotation_id=d112cc03-a081-455c-99e4-4f6a60460b90&feature=cards&list=PLuykYQ1am9zY9-O-Y8w7uISxLjQLcPmN4&src_vid=j5a9l1Td2Lo&v=hmwBow1PUuo]].
//guanosine triphosphate (GTP)-binding protein//
A class of [[Protein]]s that take in place in [[Cell signalling]], via [[G-protein coupled receptor]]s
http://www.biology-pages.info/G/G_Proteins.html
They are often trimeric (made of three protein chains), $$\alpha$$, $$\beta$$, and $$\gamma$$.
//GPCR//
7 pass [[Membrane protein]]s
[[G-Protein Signaling video|https://www.youtube.com/watch?v=V_0EcUr_txk]]
<iframe width="560" height="315" src="https://www.youtube.com/embed/V_0EcUr_txk" frameborder="0" allowfullscreen></iframe>
__Human GPCRs__
They make really good [[Drug]] targets, because they mediate so many differet responses
__Examples__
Rhodopsin is a receptor for light in the retina
A group of [[Galaxies|Galaxy]]
[[Wikipedia:Portal/Directory/Sports and games|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Sports_and_games]]
[[Sport]]
https://en.wikipedia.org/wiki/Game#Definitions
Computer game designer Chris Crawford, founder of The Journal of Computer Game Design, has attempted to define the term game[8] using a series of dichotomies:
Creative expression is art if made for its own beauty, and entertainment if made for money.
A piece of entertainment is a plaything if it is interactive. Movies and books are cited as examples of non-interactive entertainment.
If no goals are associated with a plaything, it is a toy. (Crawford notes that by his definition, (a) a toy can become a game element if the player makes up rules, and (b) The Sims and SimCity are toys, not games.) If it has goals, a plaything is a challenge.
If a challenge has no "active agent against whom you compete," it is a puzzle; if there is one, it is a conflict. (Crawford admits that this is a subjective test. Video games with noticeably algorithmic artificial intelligence can be played as puzzles; these include the patterns used to evade ghosts in Pac-Man.)
Finally, if the player can only outperform the opponent, but not attack them to interfere with their performance, the conflict is a competition. (Competitions include racing and figure skating.) However, if attacks are allowed, then the conflict qualifies as a game.
!!__Mathematical study of games__
!!!__[[Game theory]]__
!!!__[[Combinatorial game theory]]__
In particular, ''video games'', and ''computer games''.. But generally, any [[Game]]s
https://www.unrealengine.com/what-is-unreal-engine-4
https://goocreate.com/
Unity 5
__Minecraft__
//Mods//
[[Applied Energistics|http://ae-mod.info/]]
Quantum one made by MIT
See [[Voxel.css|http://www.voxelcss.com/]] for Minecraft-like stuff in browser. See //Iconic maths// ideas in [[Concrete mathematics]] in particular [[ones using cubes|http://iconicmath.com/algebra/spatial/]].
A non-condensed [[Fluid]] phase of matter
See [[Condensed matter physics]]
[[Video of iodine gas, which is purple|https://www.youtube.com/watch?v=jX9pskbKSw0]]
A ''Gaussian'' refers to a [[Function]] that belongs to the parametrized family:
$$f\left(x\right) = a e^{- { \frac{(x-b)^2 }{ 2 c^2} } }$$
There are also extensions to the case where the input is a vector: [[Multivariate Gaussian]]. See this [[vid|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=7m50s]] (he's [[missing|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=14m10s]] the determinant of the covariance matrix on the bottom).
The Gaussian is often used to refer to the [[Normal distribution]]
https://www.wikiwand.com/en/Gaussian_function
[[Some probability results for Gaussians|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=55m40s]]
//aka quadratic discriminant analysis//
An example of a [[Generative supervised learning]] algorithm.
[[Lec vid intro|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=6m50s]], where we assume that $$p(x|y)$$ is [[Gaussian]].
[[Definition (vid)|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=13m29s]], for the case where $$y \in \{0,1\}$$
''Learning'' by [[Maximum likelihood]]. The [[log likelihood|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=15m30s]] (see [[Likelihood function]]), uses the joint likelihood $$p(x,y|\theta)$$. We maximize it to find the parameters. See more at [[Generative algorithm]] for the learning method.
''Prediction'', using [[Baye's theorem]] to get $$p(y|x)$$ and using the most likely $$y$$. See [[here|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=22m30s]].
!!!__Comparison with [[Logistic regression]]__
See [[vid|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=26m24s]], [[vid2|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=29m54s]], [[vid3|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=34m]]
[img[https://s4.postimg.org/5frjsqect/Selection_588.png]]
The GDA makes stronger assumptions than Logistic regression. If the GDA Gaussian assumption holds, or roughly holds, GDA may do better than Logistic regression. In other cases, Logistic regression may do better.
Logistic regression is more flexible, but requires more data. GDA is less flexible, but can work well with less data if the stronger assumptions are correct.
!!!__Classification surface__
[img[GDA.png]]
[img[Selection_022.png]]
//aka mixture of Gaussians//
[[Example in 1D|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=22m]]
[[Algo def|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=24m]]
Assume there's a latent (hidden/unobserved) [[Random variable]] $$z$$ and $$x^{(i)}, z^{(i)}$$ have a joint distribution
$$P(x^{(i)}, z^{(i)})=P(x^{(i)}|z^{(i)})P(z^{(i)})$$
$$z^{(i)} \sim \text{Multinomial}(\phi)$$
($$\phi_j \geq 0 \sum_j \phi_j =1 $$)
$$x^{(i)} | (z^{(i)} = j) \sim \mathcal{N}(\mu_j, \Sigma_j)$$
This is very similar to [[Gaussian discriminant analysis]], but where the known labels are substituted by unknown hidden variables $$z$$. ([[vid|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=27m]]).
!!!__Train via the [[EM algorithm]]__
See [[video|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=1m30s]] -- [[EM for mixture of Gaussians|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=10m25s]]
# Repeat until convergence
## ''E-step''. Guess values of $$z^{(i)}$$s. In particular, compute the a-posteriori probability $$w^{(i)}_j = P(z^{(i)} = j | x^{(i)}; \phi, \mu, \Sigma) $$ $$= \frac{P(x^{(i)}|z^{(i)} = j)P(z^{(i)} = j)}{\sum_{l=1}^k P(x^{(i)}|z^{(i)} = l)P(z^{(i)} = l)}$$ $$=\frac{\frac{1}{\left(2\pi \right)^{\frac{d}{2}}\left|\Sigma _j\right|^{\frac{1}{2}}}\exp \left\{\left(x^{\left(i\right)}-\mu _j\right)^T\Sigma _j^{-1}\left(x^{\left(i\right)}-\mu _j\right)\right\}\phi _j}{\sum _{l=1}^k\frac{1}{\left(2\pi \right)^{\frac{d}{2}}\left|\Sigma _l\right|^{\frac{1}{2}}}\exp \left\{\left(x^{\left(i\right)}-\mu _l\right)^T\Sigma _l^{-1}\left(x^{\left(i\right)}-\mu _l\right)\right\}\phi _l}$$
## ''M-step''. $$\phi _j=\frac{1}{m}\sum _{_{i=1}}^mw_j^{\left(i\right)}$$. $$\mu _j=\frac{\sum _{_{i=1}}^mw_j^{\left(i\right)}x^{\left(i\right)}}{\sum _{_{i=1}}^mw_j^{\left(i\right)}}$$. $$\Sigma _j=\frac{\sum _{i=1}^mw_j^{\left(i\right)}\left(x^{\left(i\right)}-\mu _j\right)\left(x^{\left(i\right)}-\mu _j\right)^T}{\sum _{i=1}^mw_j^{\left(i\right)}}$$
[img[https://upload.wikimedia.org/wikipedia/commons/6/69/EM_Clustering_of_Old_Faithful_data.gif]]
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t2/f8J5cy5YtazEDj4CEBw8e4NtVVVXxuMWXL19wtrq6Ogrq9p07dxBCp06dajPnvn37iBfTf//9J91q79q1C9fE09OT6ycDAwP809u3b4W5hb6+/qhRo0RSW7EOPfFJnFJCl4DEyQu9e/fuCKHXr1/Dy1EwYF9bAJA+p0+fHj16NOEqyM/PLy0tbTFnXV3drl27Fi9e7Obm9uuvv/LlukhISPDw8Hj48CF+C2IOHz7c3ItAvj6cHk1LS8vExMSjR48ePHiQ2Eaei1u3bhUWFhKz9sI3SjDCw8OdnZ2vXLlibGzcp0+f/v37r1q1Cp9vyQN9fX08yUvs7cWbpqamhQsXhoeHT5kyJTQ0NDw8nK9Kfvz4ESHUt29f3nOpxK/l5eUU1G1tbW0ydbt48eLGjRvd3Nzw7IGbmxth2UuFhw8f4j+4Nqv68uUL/sLp3r37kCFDWCzWrVu3BDv0pLKyss1ZezIIM/SkKHGqCV0CEicpdDabjaOMunXrBi9H8NoCQLukqqpKQ0Nj06ZNRIqenh6xhIuTrKwsIyMjHx8f7Jj5999/1dXVuZY1tObdTE9PNzMz+/jxI1e6hYUFl5uHfH0IEhMTtbW1VVVVr127xtu3hE+9v3z5Ml+NErnXNikpKaYZlZWVbV64ePFihFBoaGjzny5cuIDXehN4e3v7+/uz2ezv379ra2t36tSp+Q4J2GvboiPH2dkZIbRz507eVSJ2gM/IyKCgeuPIS96tePjwoaKi4ooVK1gs1uPHj3Gwh4aGhrRaVF9fT0zoc3nOwsLCcPq8efPYbPa9e/ew9cPvLZhMpry8/PLly4WsqjBDT4oSp5rQJSBx8kIndkgg80QCWgRMWwCQMkeOHEEIPX78mEgxNTWl0WhFRUWc2Wpra83NzWfPns35zP3nn3/ImIB5eXmmpqa3b9/O/F8yMjLevn0bGhpqbm4uWH0IoqOjVVRUevTokZSU1Fob8/Pzjxw5oqenhx/ZycnJfDWKLebNv8hTXFyso6MzePBgriCB79+/m5mZcW6LFhkZOXXqVMJGj4mJQQgNHz6cK2wAm7by8vJc+xskJSXhsD8yW7/hKNvnz59LphPq6ur27t3r6upqY2OzcOFCTlVpTmNjo5qa2tKlS1vLkJqa2rVr1xkzZuB9gtls9unTp7GeGBoacu4WLDGePHlCeH84V6mXlpYSrn1fX182m71y5crx48cLcIsPHz7goG1h6inM0CMG4M6dOxctWrR69Wo3N7fmW38IQJsSp6DQJSBx8kLH3wYKCgpC7sYApi0AANKBxWIZGxtramo2NTURiXiBV0REBGfOM2fOIISePXvGu8DmJmBJScngwYNbm7f5+eefBasPYQcT+1NaNGPkyJHGxsY6OjpcNy0sLOSrUdQxbbGfzMDAwNLS8uPHj/jdk5aWNmnSJKIVtbW1/v7+cnJy+F1IdKy5uTlCaP78+UQQM2Ha9urVy8bGhtjG8sWLF9ra2hYWFiQ30cTrym/fvi0Zu9bW1jYmJobFYjU2NgYFBdFotO3bt/O4ZOLEiSYmJlyJ3759i4qK2r17t5aWFg4RIX4qLCycMGECVhUbG5uYmJj4+HhJiphzS4rff/+9oaGhqakpPj7e1NSUWMJ/4MCBnJycLl26cO6gR56IiAi8kFGYT2Jhhh6b9ISJALQocSoLXQISJy90fG529+7d4f0Ipi0AtEsYDIaqqirXIq3w8HA1NTUuZ9jKlStVVFRaWyPCwwRcs2YNj5AkrnlD8vVhs9lfvnzh2iiADMrKysTrk2SjKGXastnsqqqqrVu3WltbDx061MnJadmyZcTJF56envLy/7PzDJ1OJyYuN23axLn8mVg3Riwjy83NnTt3rr29va2t7dSpU48ePcr5dcEbvInb+fPnJdB2f3//4OBgzpSFCxcihD58+NDaJXv27KHRaJwGPZvNvnLlCqdWmJmZET/hdUicWFhYSFK+kyZNwvfFSwCVlZU7d+6so6Pj7+/PZDJ9fX27du0qLy+vrKwcGBjIdS1JP+iGDRsMDQ0FtiOFH3rkJ0wEoEWJU1noEpA4eaFjF/KgQYPg/QimLQC0VxoaGponEvN0BOvWrdPT0+NKLCkp4TqMUXgTkGR9RALJRlHNtOXdew0NDTzeXkwms6GhgQhL4LFDAnnc3d0RQn///bcEGjhnzhwjIyPOeIxjx47xXhH/+fNnGo3GtQ1+U1NTfX19U1MT1WZdibBLBQWF6urqkpKStLS0/Px8zg8wJpOZm5tbVlbGdS1JPyiLxTIxMdm2bZsUm0l+wkQAWpQ4ZYUuAYnzJfSoqCiEEOdXB8AvsEMCAEiZFr0vhOePYNmyZQUFBe/evSNSnj17tnDhwqqqKqnURyRIrFGSlKaCggKPfd3pdLqCgoKSkpIIb2pqaoonOiXQQGtr6x49enAqCd48n/OUVy709PQmTZrEtZ2qnJycoqKinJyckHvgi5zk5OTa2lrsNVRVVe3WrZuJiUnv3r05dx6g0+n6+vpcmz3X1dW5uLgMGTJk06ZNOLOamtqOHTuaNzA+Pj49Pf3nn3+WYjPj4+NVVFSaHz4iElqUOGWFLgGJ8yX01NRU7NKGl6PAwJENANA+MDc3j4uL27BhA97ysKGhYdiwYefPn+faXRwa1b5gs9nEvwKD97rHMXziNhrWr1+/fv164r/V1dWnTp0aNGjQqFGjeFy1e/fusWPH5uTkEFuEUhZiEyhbW1u+LoyKinr9+nVwcDCR4urq2mLOkJAQR0dHY2NjKTZTWVlZW1uba6cwBoMhLy8vki3JQOICC/3t27f42QhvPaEerAAAyAztZeIe2oW5efMmdnmSCTjmEeSAT9nNycmRZOWZTKaLi4uent779+/bzLxo0SJ3d3fqS4Q4D/n+/ft8XUgycDw7O7tLly5ZWVnSbWZKSoqSkhLnbgAJCQkODg5fv34V1S1A4gIIncVi6enp0el0BoMBrzOBAa8tAACAFHjz5o2Tk9P3798RQpmZmd26dbO3t4+MjBSgKDqdbmNjEx0dnZSU1K9fP4m5Rby9vRkMRnJyMt6lnzeHDh3CJwuMGTOGynLBJ5jo6upaWlqK3A+K7SEfHx+8y6xsT5iAxAUQelZWVl5e3tixY/HpMAB4bQEAAK9tB+XcuXOopTNCxURTU5Obm5uHhwdeX1hdXU3GyZSamjps2DBijzNqkpqaGhAQkJ+fLw4/qLe399q1azvOfqUgcX6FfvToUUTiwAuANzS2cDFeAABQirlz527YsIF34CO0S/aorKzs0aNHz549MzMzxR1u29DQsHLlygkTJixbtgynnDlzRk1Nbc6cOW1em5ub6+fnxxmeKEs8evRo//79nH7QVatWEX7Qmzdvpqam/vnnn1RbOSdWOrLEBRD6tGnTbt26lZ2dTf0YZSoDpi0AAIAssGDBgoiIiMTERAsLC/HdpaamxsXFpaioCN+FxWJVV1c/fvw4Li7OyMgIpAAAAvPt27c+ffrY2dk13+UX4It2HGubk5Ozd+9evKWi7NFefFRxcXGpqamenp4dyg8BABTE09MzIiLizJkzYjVtvby88NK35ORkIlFJSUnqwaMA0N45c+YMi8VavXo1dIWQtFevbXp6+rx582JiYiS2ZkLCmJubb9++febMmVSoDJPJzMvLq6qqGjhwYPNNTzds2FBdXX306FGwbgFAukyePDkhISE3NxfPkAIA0F6or683MjLq2rVrSkqKnJwcdIgwtMsjG0pKSpydnQ8fPiyrdi11qKys3LlzZ69evYyMjOzs7Dp37rx58+aGhgbOPHv37n337p2shlIBQDti27ZtNTU1/v7+0BUA0L44ceJEXl6er68v2LUd1LT18vKaMGGCnZ0dyE+sZGZmjhkzZtu2bXPmzPn+/XtBQcGkSZP27NmzcuXK/6NDdHpAQICnp2dmZiZ0GgBIkfHjxy9duvTo0aP4hDAAANoFNTU1Pj4+dnZ2Dg4O0Bsd0bRNTEw8ffq0l5cXCE+s5OXlWVpavnv3bsGCBUePHtXS0qLT6XPnzkUInTlzhutITzMzs19++cXT0xP6DQCki5+fn7Ky8tq1a2GJMAC0FzZv3lxdXR0aGgpxfR3UtPX397e1tR00aBAIT3w0NDT89NNPJSUlXbp04QyiJY6Jv379Otcly5cvj4mJSUhIgN4DACmipaUVHh5+7dq1qKgo6A0AoD6PHj0KCAgIDg7u27cv9EZHNG0rKytjYmLWrFkDkhMrvr6+z58/RwgtW7aM80yUwsJC/EdGRgbXJaNHj9bV1T158iT0HgBIF3t7e19f35UrV7579w56AwCozPfv3xcuXPj777///PPP0Bsd1LSNjo6ur68nTnwGeIMPDaqtrWUymeSvKi0tJZahrF27lvOnT58+cdm4/1+T6HRnZ+fIyEiuRWYAAEieP//8c/ny5Y6Ojs2HKgAAFKGystLR0dHOzu7gwYPQG7Jj2rLZbA8PD0dHR3t7+1evXiGE7ty54+Li4uzsbGVldfHiRa784eHhxsbGLR5ynZSU5ODgMHr06J9//rmuro7zp/Pnz+vo6Hz48EGKLX3y5MlPP/00YcIEZ2dnBweHs2fPClng69evaf+XAQMGEL9qaWnRaDQ6na6goKCqqpqSkkK+5OPHj1dUVCCEhg8fzlkmQgi7chFCLe5h6eDgUFFR8fLlSxhXACBdaDTawYMHFyxYMGXKlOrqaugQAKAabDZ7wYIFAwYM+O+//+h0OnSIiDtXuuee+/n5sdlse3t7fX19f39/Nze36upqNpv99OlThNCFCxc486urq7u6ujYvJzc3d+bMmeXl5e/fv0cIHT58mPNXa2trhFBWVpZU2tjY2Lhly5Zu3brFxsbiU6Rzc3MNDAzu3LnD4yozM7MrV67wyFBeXn7z5s1z586pqKhgUQYFBRG/YrfrgAEDAgMDIyMjS0tLyVd42LBhuMDNmzdz/aSnp4d/2r9/f/MLs7KyEEJYoAAAUIHs7Gwmkwn9AAAU5N27dzA8xYGUTVsHB4fi4mI2mz116lSE0Jo1a7Dxx2azWSyWtrZ2v379iMzY97Br167m5SxYsCAzM5PNZl+6dInLJqutrVVUVOzVqxdRcotcvHhRUVFRjh8UFRWjo6N5N5DJZNrb26uqqiYkJBCJNjY2bZqAbZq2BJcuXcLLvPT19X/8+MFmsysqKoYNG6anp/f161d+JZKTk0N89igqKqr9X4ifrl692qIRLy8vj5dm80ZMvQ0AAAAAQAdHmgftMhgMZWVlTU1NNpudnJysoqLi4+NDLMan0Wg9e/Z88+ZNSUmJpqYmQgjv1Kiurs5VTmFhYU1NDZ46v337NkJo/PjxnHPoDQ0NEyZM4L2nxvTp01+9esXmZ7scOp3e5tmSAQEBt2/f3rp1q6WlJZHYrVu3oUOHuri4iKQbZ8+evW/fvg0bNnz69GnmzJlxcXEuLi6fPn16+vRpz549+S2N2OJAWVn52LFjnJ1269atc+fO4b8Jzy4n8vLyGhoaBQUFbd5FTL0NAAAAAEAHR5qmLY1G27VrF0Lo3bt3xcXFkyZN4jRbmUwmXob//ft3bNp+/foVIdSlSxeuchQUFPbs2YMQamxsvHjxYteuXW1tbYlfHz9+jBDCjlIeKCkpmZiYiLaBmZmZmzZtotFoy5cv50zHrmUR4uXllZGRceLEicTERENDw4qKirt37wq2PxqxYe2IESMWLlzI+dO1a9fwH6NGjerTp0+Ll3fu3JmMaSuO3iY4derU58+fYWwDAAAAgCTp27fvkiVLOrRpq6GhgTeWevToEUKI0x5FCH369AmvBtPV1cUpxcXFCCFVVdXWyrl9+3ZJScmSJUuUlJS4TNsJEyZIvoEnTpyor6+fNm0aEaIqvo+EoKCgnJycBw8eFBYWzp8/f9y4cYIVlZ+fj/+wsLDgTG9qarpz5w7+e/78+a1drqKiwmAwpK7WbNisHgAAAAA6JPJUqAQ2bbkcq/fv30cImZiYYJctQqhr164IIR6rfS9cuIAQmjdvHpHS2NiYkJD8wUAxAAAgAElEQVSgo6NDnDUgSeLj4xFCEydOlMC9FBUVp06d+uDBA4TQ+fPnJ02axOUqJklpaSn+w8jIiDP9wYMHZWVl+EOC66BdTqqrq7W1taWrTlT4ZAQAAAAAQCpIf78JNpv96NEjNTW1UaNGcaaHhYUhhFavXk2kYJupvLy8taKSk5PpdDqniZySklJTU9NmoC1CCC9skucHvLCJR5nYf2lsbCyBbrx48eLGjRvd3Nzwl4Cbmxs2c/mld+/e+A8uT/Phw4fxH97e3i1uvoaprKxsHjEimd4GAAAAAACQvtf248ePBQUFkydPVlBQIBLz8vIeP35sbm7+66+/kjRtWSxWVlaWvr6+srIykYj9pmSiEZydndPT0/k62kBOTk5fX59HhgEDBnz48KFXr17Nf6qrq3v9+vWYMWNE0oePHj1ydXVdvnx5UFDQggULJk6c2NjYOGfOnMTERC7na5sQhjj2kRMyio2NRQjZ2dl5eXm1di2LxSovL+fdJ+LrbQAAKAKDwdDQ0GjToQAAQLugoqKCjNOKQkh9j4Z///0XITR27FgipampycnJSVlZOTExkWtvKTU1taVLl7ZWlL6+/pAhQzg3C8OG3bt376TStMDAQITQpUuXuNIrKiqmTZsWGxsrks2/UlNTu3btOmPGjMbGRpxy+vRpLFxDQ8OSkhLOzE+ePOnXr9/y5ctb20vvxYsX+NqwsDCcUlVVhfdD0NXV/fbtG4+a4EMxDhw4ADuPAECHZd++fYaGhrW1tdAVACADsFissWPHent7895BlVJI37TF5yZbWFjgIwyamprWr1/fs2fPpKSk5pknTpxoYmLSWlHr169XVFT88uULNh9nzZqFEOrevbu05NHY2Dhu3LjRo0eXl5fjlNra2rCwsEmTJt2/f5/3tW2att++fYuKitq9e7eWlhZCKDw8nPipsLCQcFTb2NjExMTEx8fjn1atWoXTnzx50lrJOAjE2tq6srLy8+fP06dPRwgNHz788+fPvOscERGBEGpRcAAAdAQCAwM1NTUzMjKgKwBAZigqKhowYMBvv/3WXqxbean7jB89eqSsrHzr1q3169f7+/tXVVUNGjQoKSmpxT1ZJ06cuHnz5srKyhbDPQ8cOKCgoDB16tQBAwYoKSnZ2tpeuXJl4sSJ0poXk5eXv3//vq+v79y5c7t06aKurl5XV2dlZRUbG6uoqChk4c+fP587dy7x33379uGPBITQmzdv8Mo8hNDDhw8fPnxoYWGRmJiIEJo/f35cXJympmZ6enpruygcPny4V69e+/bt6969e11dXZ8+ffbt2+fu7t58bwouUlJSDA0NR4wYAdM3ANABiYiI8PLyunPnDr9xUAAAUBktLa0bN25YWlp269Zt69atEJDQBpmZmQghW1tbkvk/f/5Mo9Fu3LhBJvNff/2Fbbv2+JHUpte2qampvr6+qalJgK+oyMhIrhOMWyw/Ozv7+/fvJMtnsVgmJibbtm2DD1wA4AGTybxz587GjRtlrF1v3rxRVFQMCAgAEQOATHL16lUajXb9+nXqV1XKOyRg56KVlRXJ/Hp6epMmTQoJCeFKz8rKMjMz4/RiFhQUHD16dMSIEdbW1jL5FYXPnpWTkxPAJ52VldXmgQ5ycnIGBgY6Ojoky4+Pj09PTyc8xwAANMfd3X358uU7duy4efOmLLWrrq5uwYIFlpaW69atAykDgEzi5OS0cOFCV1dXfDQslaGEact5Lm6b7N69OzY2NicnhzPxwoULb9++/f79O/4vi8Xy9PRUUVGJjIyEVbrN/fTJycmDBw8WbbEhISGOjo6S2emMIuTl5e3cudPKysrKysrR0XHmzJnBwcEsFuvBgwftY8oGkDhHjx49efKkwCeqUJbNmzd//PjxxIkTdDodpAwAskpAQACdTvf09ATTtlUaGhpu3bqFEBo+fDj5q0aPHu3q6nro0CHORBMTk5EjR0ZFRSGEqqqqli5d+vz58xs3bhgYGIAuNlfNWbNmycnJibDMnJyc2NjYf/75p4P0YX19/YYNG0aOHKmionLlypX4+PjY2NjLly/X1tbOnTt3xowZ4jtGGACoRlZW1uHDh1esWNG/f3/oDQCQYTQ0NLy8vM6fP3/37l0wbVvgr7/+0tLSKioqwoYp5xFibXLo0KHbt2/jdVEYZ2fn+fPnr1ixwsnJydnZ2djYODU1FdYzNSc3Nzc7O9vV1VWEZbLZ7JUrV/r4+HSQFxuDwbCysrp+/XpycvKff/6Jd6hACNHp9D/++KNr167V1dXkY2wAoL3z999/y8nJbdq0SQL3YrPZ2dnZf/zxx7t376DnAVAJybNu3TpNTc3NmzezKXygPY3KleNBWlraokWLoqOjuQ7NkhnMzc23b98+c+ZM6ld148aNVVVVR44c6QixH/X19dbW1u/fv3/79m2LR0jcvHlz/fr1eH0kALQ2ZG7duvX69WsZaEtaWtrQoUMXLVpEbKctPtauXVtTU6OqqhoUFBQTE4P3JQQ6MqASUmHLli0+Pj4PHjzgPPyVUrTXuKghQ4ZcunTJ19dXVlXH0NCwxWPMqMbNmze7devWQexahNCePXtevHjh7+/f2tFovXr1ktWViwDQHHzmzrJlyyRwr8DAwJMnTy5cuBC6HQCVkCK4w/38/Chbw3Yc8t+vX7/g4GBZVZ2oqKhRo0ZRv57Tpk3bsGED1eza4OBgmtD069ePxWJxFltZWXnw4MHu3bsvWrSotVsPHjz4wIEDMvxQmzt3blJSUgd5gneoxgoAPoOmX79+FI/AycnJIU6rAQji4uLw4ZEdqtWgDMJrgrGx8ahRo+Li4goKCqjZInkQKiB7ODo6duvWjcFgGBkZhYeH81gzx2QyGxsbGxoaiouL379///79+/v37+OtNj59+hQfH0+c64YQunXrVnV19fz583mcuCEvL6+hoSHDfZuZmfn161eJfXfV19c3NjbydQmNRlNTU6NyY2tra2tra2VAGa5evVpWVrZ48WIqb4yQnp4+b968mJgYeDByMWXKlHv37rm7ux89epTLPXHx4kXOzTRbpLKyslOnTlQYp6AM4tOE1nBxcUlKSrp8+fKvv/4Kpi0ASAI9Pb2zZ886Ojp+/PjxypUru3fvJn9tY2NjTEzMn3/+mZOTc+rUKU7TNjs7GyE0cOBA6OHm1NXVBQQEJCQkZGdn9+nTx9zc/Pfff9fR0RGmzIyMDAF6W0lJqaamhprG1pYtWz58+PDt27euXbs6OTl16dLl6NGj6urq7VToN27cQAhNnjyZsjUsKSlxdnY+duxYv379YJA2Z+/evRMnTgwODl6zZg1nuq2t7bNnz4j/BgYGhoWFhYSEmJmZEYkqKirta5yCMgigCa1hYWGBEIqMjATTFgAkh4ODw6ZNm/bs2ePj4zNu3Lhp06aRvFBBQWH27NlTpkxZvnx5VFTUkSNHCM9E9+7dEUI8zLUvX76EhYVt3Lixo/V2bm7ukiVLlixZEhkZyWaznzx5smLFiuDg4CNHjvAI3miTAQMG2NjYPHz4kEjZtWsX5zbYTCazrKyMwWCkpaVduHABz47V19f/+PGjxZO6pQ5fX1kUh8VixcXFycvLc37+UQ0vL68JEybY2dnBI7FF6HR6QEDAmDFjJk+ebGhoSKRrampqamoS/42OjkYImZiYjBkzpv2OU1AGATShNYYPH06j0Z4+fVpbW0t85FAIODsOkFUaGxvxS7dbt26fPn3i9/KGhoZp06adOnWK8yhRhNDOnTtbu2TVqlXPnz+X7V5tfgQ0k8m0s7NLSEjgTMzNzVVWVpaXlxeyQ4qLizk3ldPS0srJyWntaGhiOeOTJ08kc941eaqrqytah8lktseTdRFCpqamEr4v9ibGxMSQyUmj0d69ewcPQ96sWLFixowZPDJ4e3sjhOLj48U6TlevXq3ZFnv37hVMJUAZRKIJnODt2x8/fgwH7QKABKck5OUjIiJ69OjBYDB++umnhoYGvi5XUFAIDAwMDw8nUoYOHTpz5syTJ08yGIzm+f/7778ePXqMHj26o/VzbGxsz549LS0tORP19fVdXV2bmpqEPLdGU1MzJiamS5cu+L/FxcUzZsyoqKhonlNOTs7d3R0f9Prp0yfxtdfNzU2rLfbt28d11W+//WbXOrm5ue1O7ikpKXhQULaG/v7+tra2bR4qDixfvjwmJiYhIUG64zQkJKS4LbCRDcpABU3AixCePn1KxZbAZwog29y7dw+Hc61bt06Ay7l8DwwGY9SoUaNGjXr79i2R+OHDh/Xr1/v6+rJYLJnvz+aOzE2bNsnLy//6669cOU+ePIkQUlZWbmhoEPKmN2/e5IzJc3R0bGpqajFnamoqng+lmtdW9vDw8EAItehFo4LXtqKiQllZ+eLFiyCpNmEymbq6uitWrBDYayvdcdqmSoAyiEoTOAkMDEQIzZ07F7y2ACBp7OzsduzYgRA6cuRIZGQkv5dzLTjQ0NBITEx0c3Pz8vKyt7efOnXqtGnTgoOD//zzz40bN3aQzX25KCkpaWpq+vfff7n84nh1VF1dnfAbxEydOjUgIIDTT9ya88bExKRv375i9doKQ0ZGhru7++LFi2fOnOnr61tWViaqkmtra6uqqpqamrjS6+vrKysrGxsbmUxmVVVVXV2dqO6Ynp6OEOrTp4/k9Q0h1OLMCSfR0dH19fX29vaCeXyamppqa2uZTGZHGMJ0Ot3Z2TkyMpLfqS2KjNM2VUJgZQBN4IGpqSlCiJozTrCMDJB9Nm3a9OTJk7i4uOXLl5uZmRkbGws5+JctWyaZPer54tOnT1FRUTzsSGVl5XXr1vXo0UO093V3d//y5Yu9vT3Xnmjv379HCKmpqXGuFBG4ku7u7unp6fiAAITQwYMHBw0atHz5cq5sNBotLCyMa0NiivDmzZv9+/cHBQV16dKlqKho0aJFp06dSkhI4Fyvw5svX77s2bPnx48fdDq9vr7ezMxsy5YtysrKCKFTp05t3bq1uLgY5zQwMMAbety7d2/69OlsNhshpKure/jw4SFDhqxataqkpKS4uNjKyio0NHTHjh2pqakMBkNJScnGxuavv/4ilk7yAB+TLsntHby9vVNSUgoKCoYOHXrw4MGzZ88aGhoGBQW1mDk8PNzY2Lhz585c6a9fvx42bBhnSv/+/bOysvDfWlpa2E7CJCUljRw5UsJ6sn379sjISA8Pj5UrV3Km19XV+fn5lZWV7dy5k4yA+MLBwSEkJOTly5dckUUCPA0kOU5JqkSLykB9TZCKMpDXBPzgysnJoeJbHzzwQEegsLAQn+42ZMiQ6upq2WvgyZMn23zAKSoqpqSkSGyOHu8JNX/+fFFVsqGhgXN1s4KCwqNHjyQcfSEMa9asGTRoEBG1kpeXhxAKCAggefn169e7deu2cePGxsZGNptdWlpqa2s7fPjwkpISIs/Fixfx1EFaWhqROG3aNE1Nzbi4OHzr2trahIQEHAM9ZMgQJyenhIQEvI7t9evXPXv2HDBgwKtXr9qsDz6Q7+nTp9QcEerq6q6urs3Ty8vLb968ee7cOWJZd1BQEPGrv78/QmjAgAGBgYGRkZGlpaUSrjaOYEYI2dvbc/20efNm/NPVq1dFfl9s0vn5+QkTkCCtcSqYMlBcE6SlDLw1gZNv377hOpSXl1Nt+INpC3QUnj59Ki8vjxBavHixjAXFXrt2TV9f/+TJkx8+fCgqKrKyssrKyioqKiosLDQ3Ny/6X+rr60kWWFlZGRISUlFRIbC1l5ycjBBSVVXNy8sTYSVLSkq4tigqKCgQsveEbyxJoqOjOSOS6+rqaDSal5cXmWs/f/6spqZmbW3NuZfCx48f6XS6t7c3Z078Sp4zZw5W8qKiIkNDw8zMTK4CX758iTvwy5cvnOlpaWk0Gs3AwKDNL0C8ZoiaS86rq6tRW6Gcly5dwp8B+vr6P378YLPZFRUVw4YN09PT+/r1q7RqvnPnTqzbGzZsaPFbAiGUnZ0t8vs2NjbKy8uvXbtWeNNWTONUfMpATU2QljLw1gROampqcB0+f/4Mpi0ASI2DBw/ioXj8+HGZaRSDwRgxYsS3b9/wf79+/TpixAj8d0ZGxrRp0wQoc//+/Qihy5cvC2bt1dbWjhw5UkFBITY2VuSV/PDhAzEJ3r9/fwaDIWQHCtlYYSxdHDBAJvPs2bMRQiEhIVzpo0aNUlNT47R3WSzWrFmzsAuKyWROnz49Li6uNYfQuHHjWrvX5s2bedSHCOolZEopMjMzEUJHjhzhnc3Pzw+3YsyYMeXl5ZMnT9bQ0JCusU74O2/cuMGZToSl6ujoiOnLXFtb28XFRSSmrTjGqViVgYKaIEVl4KEJnLBYLByElp6eTrUnAMTaAh0IDw+Px48fX7161d3d3cLCgsr7FpGHxWJFR0fr6uri/0ZERNjY2OC/nz17ZmRkJECZYWFhOjo6U6ZMESzGae3atSkpKefPn3dwcBB5JQ0NDSdPnhwVFTVmzJhr164Jf6yxMI0VmMzMTDc3Nx8fHzIbyDOZzLi4OIRQ863lDAwMkpKS8vPz+/btS0QxhoaGpqSkeHh4pKSkDB8+nN/VM46OjpcvX75x4waPAyaIBXBkYm0rKiqIucs2odFovXv3FvII1q9fvyKEiL2oWsPLyysjI+PEiROJiYmGhoYVFRV3794luT+UOBpVX1+P912Sk5PjPPIAIfTo0SP8h7W1tZiWq3bu3Fn4FZ/iG6diVQZhNEH2lIGkJtBoNHV19cLCQuwXh1hbAJCmj1NPT09ZWVn4qFNqMmzYMMJX6uHhsXXrVn5LePv2LQ8nR5uOzKCgIBUVlWvXromjkjU1NS4uLnjCvaampsU8v/zyy+rVqyXTWMHIysoyMTGJiooimT8jIwM/rhcsWLD4/zJx4sThw4dnZWVxXfL8+XMFBQVlZeXWwuB4eG3xi1NBQYFHcAheOyInJ0fGabRmzRo5fvj777+5SuB94NmECRO48l+8eBEhRKaH6+vrbW1tcTmcceESaFRzHj9+jGsyevRorp+IdatHjx7lV994hNxwYmJiYmJi0uJPnz9/fvbsGfmQSpGPU2EgqQwCa4LsKQMPTeDCwMAAUfLUBjBtgY7FixcvVFVVL1y4IKbySb5FxER6erqcnBxxdxcXF97Tyi2yYcOGPn361NXVCWDtXbt2TVtbm/fSIoErWVxcPHbsWITQH3/80drxXUwms3v37h4eHhJorMAaaGtri+c6q6qq8NHEvCHWIBcXF5O8y7dv3/C2XMuWLePXtH3w4AG+XVVVVWvlf/nyhVipLQHFTklJedA6zT9T79y5g3eNIFM45/ka//33nxSfTrt27cLV8PT0bNGGQAhx7qhNEh4hN5zo6+uPGjVK+FaIY5wKA3lloI4mSFcZyGsCPnz+9evXYNoCgNTIy8vT0dHx8fER3y1IvkXExIYNGywtLYn/WlhYrFmzhq8SmExm7969jx071loGHtbe06dP+/fvzxV39c8//3Au4Re4kllZWYaGhnQ6nbejIjY2lvy2A8I0VjCuX78+a9asjIyM/Pz87OzsY8eOHT58uM2rWCwWns/98OEDmbs0NjZOnDgxPj4eR1mcO3eOL9MW79zUt29fHrcoLS3FL1cpLg/iwevXrxFC//zzT5s5o6KiaDSam5sb3slIXl7+/v370qr2xIkTiSAZzvT8/Hyc3r17dxaLxWQyb968Sf4kFDMzMx0dnTbXBWpqak6cOFHIJohjnArpOCCpDJTSBOkqA0lNIGJtibXCYNoCgKSprKw0MzNbtGiRWLdHIPkWIfPUyMrK8vDwIB+hX1VVpaGhsWnTJiJFT0+PWK3FRW1t7c6dOxctWrR69Wo3NzdifdL9+/cNDAx4PChbs/bS09PNzMw+fvzIlW5hYcHpueGrkgSJiYna2tqqqqq84xyIg+y5Pi1E3ljBOHfunJycHNdkOsllZIsXL0YIhYaGNv/pwoULeFk3gbe3t7+/P5vN/v79u7a2dqdOnZrvkIBN2xZ9M87OzgihnTt38qgPsaN7RkYGBQc7Dq/k3QQ2m/3w4UNFRcUVK1awWKzHjx8rKCgghDQ0NKTSqPr6emIXKi43WFhYGE6fN28em82+d+8e3uSYTLG8Q244P/Pk5eWXL18uTBOEHKdichyQUQZKaYJ0lYG8JhA7JFRWVoJpCwBSoKmpycnJycrKSqzzpyTfIm2yZs2aJUuWrFmzBpE4UJTgyJEjXGFPpqamNBqtqKiouWfFyMjIx8cHG53//vuvuro6tvh37NjB5SQgY+3l5eWZmprevn0783/JyMh4+/ZtaGioubm5YJUkiI6OVlFR6dGjR1JSUmt58vPzjxw5oqenhx+1ycnJ4muswCQlJcU0g+Rbobi4WEdHZ/DgwVxBAt+/fzczM+MMio2MjJw6dSrx/RYTE4MQGj58OJfmY9NWXl6ea4uDpKQkhNCIESPa3CoOHxXx/PlziY3iurq6vXv3urq62tjYLFy4kEeEX2Njo5qa2tKlS3mUlpqa2rVr1xkzZuB9gtls9unTp4klUFxTDRLgyZMnxAcP5wdtaWmpiYkJTvf19WWz2StXrhw/fjzJYnmH3BB8+PABIXTgwAGB6y/kOBWf46BNZaCaJkhXGchrAv5mUFBQoOBmmmDaAh0CLy+v/v37kw9VFAySbxGStHkwOicsFsvY2FhTU5Pz0PYZM2bg7Qg4c9bW1pqbm8+ePZvTDUBm6rY1a6+kpGTw4MGtLfH5+eefBagkpylMbDlp0YyRI0caGxvr6Ohw3bSwsFBMjZUiiYmJBgYGlpaWHz9+xO+StLS0SZMmPXv2jGisv7+/nJwcfucRfW5ubo5XxnDO5GLTtlevXjY2NsS2lC9evNDW1rawsCCzWSZeP3779m2J2bW2trYxMTEsFquxsTEoKIhGo23fvr21/BMnTmxxKcy3b9+ioqJ2796tpaWFz6kifiosLCTW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https://en.wikipedia.org/wiki/Gel_electrophoresis
[[Gel|https://en.wikipedia.org/wiki/Gel]]:
Nonfluid colloidal network or polymer network that is expanded throughout its whole volume by a fluid.
A gel is thus a [[Porous solid|Porous material]] with colloidal size pores, and filled with liquid. See also [[http://www.madsci.org/posts/archives/2001-03/984500675.Ch.r.html]]
It is a substantially dilute cross-linked system, which exhibits no flow when in the steady-state. By weight, gels are mostly liquid, yet they behave like solids due to a three-dimensional cross-linked network within the liquid.
Note 1: A gel has a finite, usually rather small, yield stress.
Note 2: A gel can contain:
(i) a covalent polymer network, e.g., a network formed by crosslinking polymer chains or by nonlinear polymerization;
(ii) a polymer network formed through the physical aggregation of polymer chains, caused by hydrogen bonds, crystallization, helix formation, complexation, etc., that results in regions of local order acting as the network junction points. The resulting swollen network may be termed a “thermoreversible gel” if the regions of local order are thermally reversible;
(iii) a polymer network formed through glassy junction points, e.g., one based on block copolymers. If the junction points are thermally reversible glassy domains, the resulting swollen network may also be termed a thermoreversible gel;
(iv) lamellar structures including mesophases {Ref.[4] defines lamellar crystal and mesophase}, e.g., soap gels, phospholipids, and clays;
(v) particulate disordered structures, e.g., a flocculent precipitate usually consisting of particles with large geometrical anisotropy, such as in V2O5 gels and globular or fibrillar protein gels.
Note 3: Corrected from ref.,[5] where the definition is via the property identified in Note 1 (above) rather than of the structural characteristics that describe a gel.[6]
Hydrogel: Gel in which the swelling agent is water.
Note 1: The network component of a hydrogel is usually a polymer network.
Note 2: A hydrogel in which the network component is a colloidal network may be referred to as an aquagel.
Note 3: Definition quoted from refs.[6][7][8]
[[Theory of Gelation|http://arxiv.org/pdf/cond-mat/0410232.pdf]]
https://www.youtube.com/user/rmaloneymsu/videos
https://www.youtube.com/watch?v=AjWkd0VIsa8
A ''gene'' is [[discrete unit of inheritance|https://www.youtube.com/watch?v=H6gwYdyn7II#t=0m40s]], corresponding to a particular portion of DNA in a chromosome that codes for a protein belonging to a certain family (that may then have some function in an organism or a cell). Every gene is identified with a particular protein, and viceversa (in standard biology).
[img[Selection_649.png]]
* [[DNA transcription]]
* [[mRNA translation]]
* [[Gene splicing]]
* [[Transposon]]
[[Gene regulatory networks]]
Organism where a certain [[Gene]] is removed. Used in [[Biochemical genetics]] studies.
These are often done using [[Model organism]]s, particularly [[mice|Mouse]]
,,change title to singular...,,
Epigenetics..
!!__Regulatory mechanisms__
* [[Transcription factor]]s
* [[Chromatin]] remodelling. Tagging histones, etc. to reveal or conceal certain parts of [[DNA]]
* [[microRNA]]
* [[RNAi]]
!!__Network motiffs__
[img width=400 [geneNet_motiffs.png]]
--------------
!!!__GP map bias__
I.e. ''designability''
They show [[GP map bias|MMathPhys oral presentation]].
[[Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output|http://www.pnas.org/content/103/11/4180.abstract]] certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences.
The network topologies that encode a highly designable dynamical phenotype possess two classes of connections:
*a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and
*a partially conserved set of variable connections that controls the transient dynamical flow.
[[Evolvability and robustness in a complex signalling circuit|http://pubs.rsc.org/en/Content/ArticleLanding/2011/MB/c0mb00165a#!divAbstract]] The number of genotypes with a given phenotype varies very widely among these phenotypes. Some phenotypes have few associated genotypes. Others have many genotypes that form genotype networks extending far through genotype space. A minority of phenotypes accounts for the vast majority of genotypes. Importantly, we find that these phenotypes tend to have large genotype networks, greater robustness and a greater ability to produce novel phenotypes. Thus, over a broad range of phenotypic robustness, robustness facilitates phenotypic variability in our study system.
[[The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks|http://ezproxy-prd.bodleian.ox.ac.uk:2077/S0022519310004054/1-s2.0-S0022519310004054-main.pdf?_tid=27949abe-0a44-11e6-aa9c-00000aab0f27&acdnat=1461520032_af39debef09a1ca8f28624e386c442c2]] We find that SF networks generate oscillations much more easily than ER networks do, and this may explain why SF networks are more evolvable than [[ER networks|Random graph]] are for oscillatory phenotypes.
[[Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks.|http://www.ncbi.nlm.nih.gov/pubmed/11082279?dopt=Abstract]]
!!__Models__
[[Boolean network]]
See [[Dynamical systems on networks]]
//aka Alternative splicing, or differential splicing//
Gene splicing is a regulated post-[[transcriptional|DNA transcription]] process during [[Gene expression]] that results in a single [[Gene]] coding for multiple [[Protein]]s.
https://www.wikiwand.com/en/Alternative_splicing
http://www.premierbiosoft.com/tech_notes/gene-splicing.html
//aka pedigree//
[[Pedigree analysis|https://www.youtube.com/watch?v=VQmZXw8UBh4]]
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jh87VlRcbDIaBULhli1bzOPjJ0+c9LjdOTk5GIRdq6vTjIwESKVVlZVLSpYsKCi43t6+b9++tLS0hQuLCATCS6+8HBwcPB0Gd8a0uojwcFwvcDAMs1qtn37ySUlJydp16xAEOVd2rrGhIVqhgCBILBavXbeOxWKdOH58+7btBYWF27dtp1KpOTk5DqfjypUrTAYDQRC3y52cmpqRkXHgwIErVZeWrViuUCga6htqampIJFJH+3UYgTf/YAsMw8eOHj1Xdu7Pb/9l2z8/e+bZZ1NSUigUyp3vmFCpVCaT5XK53G735H8wPj7e3tb29DPPCIVCCILmzZ//6ccfq1Uqr9crEoklEgmXyw0Jkfv9fv3YWEVFBQzB+/fthWGELxCw2WwMxeQh8miFQqlUNjQ0OGx2PBgHBEFp6el4S0kWKBMKhQiC0On0/t7eaTWmTSQSGQwGQiBYrdYpLd6GhoaU1NTIqCgWixUVFXWtrq6yvCImNpZMoURFR8MwrFAoKBTyyPBwc3OT2Wga043BMEyj07KyslAUpVKpefn5VCq1urpaN6arrKi4fOkSBEHBcjmTyXI6nQwGIyIiAm/b9/X23XTo5H6B3wiLzRq3WLg83uSe4/DQkMlkKikp4fP5KIouLCp647XXDXoDivqD5XI2h8Nms8Vi0eDgYGdnR1Njo91ub2ttgyAoKiqKRCJhGBQXFxcYFNTc0tLV2eHzelWDg7h/Zufk4P8iIiKCwWAEBgV53B6D3sBms6ePZchkMpPF9Pn8DoeDTqdPjFmYjKaKCxd/+9ZbPB4PQZD0jPQD+/fjt8bhcuRyucvlCgkJ7enqMhqNTQ0NAoFgZGgIgmE2hyMSifRjeqFImJyc7PF4rl65YrVYThw7jleosXFxuGoLhUKZTGaz2cQSibK//67PmMhkspy83O7u7sDAwKjoaLyN5/P5/H4/nU63Wix4diKLxUKhUG86BkskkSKjolatXp2Tk0On0/Hm+oXz53FfJ5FICoViyZIlGZmZFArF5/P5fL7R0dGvu55psoufy+XGJybqxsaqKivnL1jAYDBgGMYHIOl0usftcTqdfr/f5XL5fT4Gg4EHZJ8MnU7ncrgrVz6wfsODLBYLN2l3V9fEF1gs1iOPPTZ//nw8PJrX67VYLEe++mo6m4VEIoWGhi4oLDx//nxJSYlUKiUSifitIQhCJBJtNpvP58MwbHx8nMVmEUlECIKnnIHNZqekpv7+j3/AK2Sn00mj0SbUh0qh5OXnFxUXx8XFkUgkr9fr8XiGh4e/xl2mi2XEYnFaRsbI8HBjY2NqaiqNRsMwzOVy+fw+NodtsVjw2tFmsxEIhJtW/nQ6ncvjvvSLVzKzsqhUqsfjQRBk/759+FECggQEBDz+xBP5+fl0Oh1FUa/XazAYTp8q/bpR6rslGRAEbdi48c1f/1qtVq9ZsyYqOtpus+nGxhAEycvPP3P6jFAk4nA4p0tLE5OTFApFbXUNHgsLr3UQBGEwGCtWriw7c5bL4UgCAgYGBiIiIhAYgWEEgqCgoKDwiIgd27eTKZTIyEh8nIbNZiMEZEJ9EBiBEQQhECgUik6nk8vl3zw/dG9ITk5W9vd//OFHNptt/oIFZDK5p6eHQqHk5uXVVFc3NjYmJib29/WZzObC4iIWi4Ugk+4IIXA43OUrV7S3t1eUl2dmZRkNBqfLRSaREMK/xGX5ihXbP//c7/Pl5eVBMGwwGDAMQ2BkQn1gGCYgCAxBdDrdZrVZrVbmzfLa3WOoVOqPnn/+maeeMhmNy5cvDwgI0I2N2e12FpsdKJNVlJfjk8HHjh5du369VColT5oyh2GETqclJSW5XK4d27c/+dRTfr+/vb09Pz8fQf514wmJiT09PQcPHNi4aZNEItHr9WazWSgUEhBkQn0QBIERmEQmQRBkNBgDAgImAjLdRxYvXvyP997b9tlnto0bU1JSfH6/Wq1GEGTzQw+dLi1dvmIFgiBVFZVCoVAREzM8PIzAkx40kcDlch965JEzp89QaTS5XD40NMThcGAYxs3C5nAKCgs/+uADMokcFxdrs9v1ej2VSoUnex0M407IYrEMer3T4SCRSDdWZndgkjUoKOj//fGPObm57/71r/nZOU8/+VRDfX10dHRxcXFaRvrv3nrryccfN5vNGzZuDI+I4AsFAqEQ71nQaFRZUCCXyy0uLl5YXPT73/1u6eLF1+rqIAjiCfhCkZBEIonF4nXr1m3avGXbZ5/nZGS++cYbLqeTTqcHSKUMJhPvAvD4PJFYHBYW9syzzz737LPHjh6dDhOKHA5nw8aNr/369Zbm5gV5+fnZObt37mKz2fn5+QuLimqqq3/y/PNHjxxJT09fvnw5hUoNDA6a6N7LAmVsDnvR4sUFBQXnz51b88Cq37/1OwiCyBRKYHAwHgN53rx5P3/xRdWg6rFHHn36qaeuXrlCo9G4PK44QIK7EZ1ODw6RE4nEF156sezs2Q/ef7+vr+++mwVBkIiIiJ179giFwh8991xuVvZrr/5yeGg4MTGxqLiYyWK9/tprL/z0pzwe7/s/+AGTyQyQSTlcLq50HC5HLBZHRUevW7eOQqE8vGVLUUEBPksaIA3AvxYZGfnY448nJSX94Xe/X7p4yYcffkin02k0WpA8GNcIMpkslog5HE5BYaEiNuaXr7xSWVExTRoaP33hhU2bNx86eHBebt66VavPnS2LiIj40fPPC4XCX/7iF7/65S+JZFJRcXFUVJRAIBCIhLg9mUxGsFwOw/CDGzZkZGa8//e/L1tScujAQbwpKgkIoFAoTCZz2bJlv3zttdJTp0oWLf75Cy+o1Wo6nS4Si7g8HgRBBAKBzWbLAmV0Ov3d99/79Wuv7969W6/Xf20f8zabZyiKejwet9vt83rx2h5PcejxeFwuF4aiZAqFQqEgCOJ0OmEIolCp+OwR3vdGEMTj8bicTp/fT6PRKBQK/s5TqVQEQVAU9fl8bpfL4/HgSVUJBILD4SCTyRQKBf/XPp+PTqd7PB673c5gMKZDKwP6d2BBt9vtdrkgCCZTyHQ6HUEQvNDn8+GNTBKJhGe6nVhtZbFYqFQq3mh3u914545Op8MwbLfbmUwmXhvgRz0eDwRBFAqFTCbjHTcmk4lhGIqi+EgKiqIOu51AJOLnnA6vh9/vx30D9fsJRCKNRiOTyfijxGe7KBQK/hBtViuZQiGTyTAMu1wuv9+PN9rdbrfb7Ub9KIPJoFAoNpuNTCbjX5vwRr/PRyKTcS/CE/ESCAQURZ1OJ4FAIJFILpfL6/HSGfTp0MrA3yOfz+dyubweD4wgFAqFRqPhXVr8jZi4R7fbjaIog8HAfcxut+Nj2x632+V2+30+MoVCpVLxZQq41/3LG11uj8eNEAi4M3jcbhhBcJN6vV6Xy8Visbxer81qo9KouOnuimQAAIA5BdiWBgAAgGQAAAAgGQAA4L5zu0NiWq2WwWDckc2pLperrbWttaUlNDQ0Jy8Xnx2YodhsNrvdPiWT2y3j9Xo1Gs3lS5d0Wm1CYmJScjKfz58+m1O/E2q1WiKR3KlBR6VSWV9fb7VYYmJj4+Li7vsi11vGaDTCMHzj1tXbAUXRsbGxjuvX09LT7+DqtdtqZVgslpMnTvT29NyRS3E6nTab7eKFC+Xl5Xa7febqBb7N5OuWytwCGIbZ7fbh4WGr1dbU1FRdXe1wOGacWVAUNZlMu7744uv2Ot8CVqvVarEYDIayM2cb6uun1YLXb4/dbq+oqKirrb2zpzWZTBXl5Xu/3Gs2m+/gab9ttrQbcTgcpadO7di23WqxuN1uu81GpdGoVKrL5RoeHrZarRwOp7KiwmKxNDc19fT2ut1ufBrV4XAMDg62tLS0t7VhKIpP+cAw7PV6g4KDOtqvo6g/MytrhmZL9Xg8ba2tu3fuqqysZLPZo6MaMpmMrwHVaDRGo5FEJA4MDOAb85qamvCNUvic2ejoaMf1601NTePmcSKRSKFQ8KYEvtQiMiqqZOnS8fHxE8ePZ2VlzawaFUVRs9m8f9++z//5GYvFMhiMPp8Pn2G1WCyjo6Met9uPoleuXHE6HFevXlWpVBAE0el0IpE4Pj7e19fX0tKi7O+HIYhKpU7ssKRQKCkpKbGxsaUnT3k8npTU1GkyafqdKphLVVU7t+/o7+tFCASTyYT7Ax69Ynx8nE6nNzU2akdHuzo7Ozo6bFYrlUql0Wgej2doaKittbWxsdHr9eKzsBMzo3a7va219cTxEz3d3ctWLL+DWQFvXTIsFsv+vfva29tsVuvQ8BAezSU4OHhIrT506BCdwQgJCfnhc885HI6G+oburk7N6CiZRKLT6QMDA1VVVY0NDU0NjQ6nA4JhPPYMvr6gsrICRdGsuxCJ5555QG1t7elTpQaDwWwy9fb2OpzOhIQEFEUP7N9vMholEsmxo0dLT5Vqtdr6a9eGhoYsVqtUKrXb7eXl5Q0NDXW1tTqd1u/349srcMkgk8n4Z5vdfurEyUVLFs+s1JB+v39sbOyfn3wyMjzsdDr6lUqDwSCRSPh8flNj4+VLlzkcjsvt/uUrrxCIxMqKioHBQa1Wy+PxYBhua2urvnq1/tq17q4ul8tFJpEmdnBRqVS73d7a0tLe1hYZGZWYlDRNlp98pybG6VOnqqurx83jWp1WpVIRCISoqCir1frPTz4hk8lBgYF/+uMfu3t6uru621pbRzQjfr+fx+PpdLry8vLGxsbamhqbzYZhmEAgwNcEut3u9vb2+mv1DodDo9GsXPXAHfSWW7evQCD44Y+fV6lUmzZvzszOOnb0aEtzc2JiYk9Pz5VLl59+5hkIgnRaHZvN/t73vkcik/fs3l1RUaFSqzUjIyajqWRpCY1GO3v27OnS0oSEhG/YOTezYDAYixYvNhqMV69cfu+Df9TW1v7z009XrVrlcDjOl53b+szTfIHAYrGiqH/lAw8kJiY2Njbu+uILGIYxDKssr1i2fNnSpUsbGxvr6+s5XC4eUGOie+J2u6/V1T2wetWd7fTeizEzIjE4OPg3b7310MZNv/3d7zAI2r1rV39/v0gkampsVKlUjzz26IBSaTAYAoOCfvijH5lMpr++886F8+cFQmFXZxeHw16/fr3NZquprrbZbMkpKRNnVqlUR48cpVCpIaEh2H3d4H9rcDichx55RKPRSCSSJ7duPXfuXPXVqwUFBWq1+uhXRx597DEqjWY0GAUC4eNPPiEWi0+Xll6qqjKbzZbx8fa29nUPrheLRGfPnq2sqAgNDeVyuX6/X6lU4lsWFy9Z0lBfP72GP3EkEolAIGhva2toaNDqdEuXL5toNsfExDCYTDqdvmLlyqNHjpSeOmUZt4zptPhaXQKBsKCgAIZmJ1QqNSoqyulwtLa0GE2mrNyc8IgIvOUskUiCg4OpVGpCQsKadet2bN+OYZiyr/96e/vEdkPkv5ex+ny+gYGBsrNnf/X66zeNfDeDCAsLo1KpgwMDRCKRRKHkzZuH3xGZRE5KSkIQRCQSPfrYY7t27qytrR3T6awW65HDX0EQxOPxli5fNvlUSUlJf/zzn746fLipqZnD4eCRWWYoXC43UCarqqhobGzUaDTrNjwoFInwzmlYWJhAIGCxWAsKCtxud+mpUy6Xa0ilbm5qwv82OycH/veIwYXz50eGhzdveWh4aMjv942Pj08vycAgjEgkxsXFmUymC+fPu1yuhx5++D+dWAzDa0h8hxyBQMjJzVm7bp1CocCrVgzDvm5p6kwHhmEul/vAqlV1dXXt7e2rVq+eaB1gk/D7/QQCAYbh3//xD5mZmfgO6CmrcjEMMxqN2z77fPOWLTExMTO6UYZBEIlEys3La29rO3P6tCQgYMGCBZNHPfCffr8fRhACgbB+w4alS5cGBQXhDjNliASGYRKJpIiJMZvNMzrqMoZBBAIhJCQkJTW1sqJCqVQ+tXXrxKgNiqG4t6Aoikd4Cw0L+9VrryUnJ095j8bHx7Wj2pPHT5w8fgJFUQiG333nnZ27d9+p67wD76rX6/X7/fKQEAiDTh4yDp0AAAAgAElEQVQ/7vP58GBTOH09vXa73Wg0VpSXEwiEBzdsIFMoH334YU9Pj9/vHxoaqqmpwfdKzDL8fhSPJJKXn7/ri52DyoHYmBgul4sf1Y/pR0ZG8OivVy5dfnDDhnXr1//93XevXL5st9sNBkNra+vIyMjE2Qx6/enS0oTEhFWrV9/feHx3YITY7UZRND4+XtnXf7nqEovJjIyMnPClzo4OFEW1Wu3JEyeio6Ie3LChv69v3969w8PDTqezv7+/ubl54lRdXV0mk0mn0zVcq3c6nCKRaAY7jM/n9XqFIpFMJtu758txszknJ2diaEatVptMJovFUldbO6oZfXDDhrjY2L/86U9tbW0Yhmm12oaGBrw1IZPJfvX6a3WNDXWNDR98/LFUKv3la6/dweu89eFPCIKYTCaRRDxy+Ksh9VC0QuHz+dwez6rVqyP+HaTw008+IRAJO7Ztr6goF4vFhQsXZmRkhIWFERDk4IGD7/zl7f7+/qTkZKlUOrHKoKW5mUqjpaWlzdx1GRQKhc6gDwwod2zblpScLJfLa2tq16xdk56Rgbcgqiorr1+/3tbaumPbdovVMr9gwcKFC8PDw+UhIVcvX3n3nbcrKio4XG54eDgepMdgMJw8cfJv7/y1prrmy927t32+LS4uTiQWz6yhPhiGORwOjCD/eO99BoMRERk5qh0NkMkWLV6MBzoc0+n2fbmXTKb84Xe/b21rjYuPLyoqSkhICA0J0ev1X2zfsX37NrPZnJCQgAcKwSXjzddfP3z4MJfHXbxkcVx8/ExcrkKn0ykUyuXLl69cvhIXH8dgMFQq1YZNm+Li4vBe6qEDB80mU+mpU8ePHSeTKQULC3Nzc8PCwvgCwcnjJ976v9+2trWGh4cHBwfjO/rwrXckEsloMl5vb1++YsUdXJdxu9vSLBbL2NgYnUYjkclnTp++fv36iy+9NNH8zkrPePHllxQKBYPJZLPZHA4HD5Zjt9lNZpPDbmcwGEKRiEajTfRNxnQ6DIL4fP6MG/qejNvtNugNdrstQCodHR196ec///0f/oBHkYIg6He/fWtsTPfwI4+wWGwmi8nlcvEdqE6n02w2W8YtRBKRx+Ox2Wz8+16v12w267TaifPLQ0JuGp5n+mM0Gsd0OqFI5PF4tn3+uVgs3rR5M66M7W1tTz7+xF//9i6Hw6EzGFwul81mE4lEj8djtVrNZrPX62WxWHw+f6I6sVqto5pRFEPZbDaPx5u57S+73a7X62EIYrHZDfX1u3fv/tOf/4zHtYMgaMvGTTm5OfMXFDBZTBaLxeFw8GA5drvdbDJZLBYanS4UCm/MPuFwOMZ0OqlMdgfnnm/3tWSz2Ww2W6/Xnzt3rre3d2FR0ZT1AjweLyo6eiJCGT54zuFyONybLysQ/bsCmdFQKBRZoMztdndcv75927YHVq0KDAycLIJ0Oj1YLp8c7hFffEGn0/EqdzIkEkkkEs3oVvcEfD6fz+cPDw8fOniQRCKlZ2RMHsolIIhILI6MjJyshmQyWSAQ3DTPC4vFuu/xwe8IeKjt8fHx6urqiosXV65cOWVSjM3mhEeET3RsIQhCEOR/3j6dTg8JDb2zl3oHanKfz9fT3W2z2XLz8jIyMiY/7MKFhWKJZIYubb5N8MWO1+rrk1NSSpYuZTKZE4E8FDEKl8s104ckbmfwq7Ghgc5g5OTmRkdHTzgMi81eUFg4Q9fj3InBL//Q0JBarc7IyiooKJj81mRkZcpDQ6ZJoqY7EC/D7/erVCq3yyULDJzSZWptaZHL5UwWaw6qBoqiNputu6tLHhKCh2+cODQ0NISi6DSJInfv8fl8XV1ddBotQCqdPGLlcDj6+vqioqKmSZyke+8weGKR4ODgKU2M7u5uLpc7TXrrIMQOAAD4DoDN7wAAAEgGAAAAkgEAAIBkAAAAIBkAAABIBgAAAADJAAAAQDIAAACQDAAAACQDAAAAyQAAALOU2wqxczcwGAzV1dVDQ0OBgYEIglgslgvnz6MoyuPxZmu8v28PiqKDg4PHjx2TSqV4ZvDW1ta+3j4yhTw3N4AODQ2dOXOGRqNxOBwYhnt7e1tbWolE4h2MKDPT8Xg8PT09x44ejVYoSCQSDMO1NTUjIyM0Gu3WolhNu5cQw7D+vr6qykqlUul0Ojs6Os6eOTtDU9rcJdWorKisra21Wq06ne7K5SsdHdf9fv/ctAaGYXU1tdVXr+r1eqPRWFdX19DQ4PP5gJ9MNpHL5So7W1Z/7Zrb7R4ZGSkvr1AODNyyz9yZvbT9/f1DQ8O30sghEHJzcyY3H4RCYWpa2ulTpaUnT+Xm5Z05fToiMmJyVIWZ+JJfvVp9a08oKCgwPDz8PwKPIOHh4QWFBefLyrgcjlKpNBj08+bNE8+ouET19fV2+y1me+NyOUlJSRO/BgcH58/Lv3L5CofD8Xg8/X19ycnJkzM5zFAcDse1a7eYTCAiInyyBSgUSlRUVOHCwn179/L4/KrKKr/fFx0VdcuZTe6MZFy5cvXkyVO38IcUCiUzM2NK2IiYmJi+3t4zp09rtdoxne7pZ56Z0XElfD7fp5/+0+1238LfrlixfLJk4CxbvvzK5cunS0uHh4eLiotTUlNnVtDDvXv3Dw0N3drfxsbGTpYMCIIKCgvrr127eOGi3WaLiY3Ny8+fJqFobgeTyfzhhx/d2t8+/vhjU0STSqWuXrPm4vkLR7766npb+6OPPx4VHX3LIWymY9XNYDCysrNDw8Jqa6pXr11zY2C7OY5AINi8ZUtDfYNEEpCVnT3H++1cLveB1as1IyMQDC0oWDCzksjdGwgEglgsfnLrUyePHU9JTUlOTrqdPDjTUTL8fr9lfNxht9NotOHh4Vurn2cxXq93dHSURqPZbFaTyTTHu+5er3dMpyMQCR6PR6/Xg2Gvmw5neL3ekeFhDper1xssFsvtDH7d4QYtgiDfqVlIpVKnhGzDMEyv15edLdOOah9/6qnjx46lpaenp6dDEDQLgruRSKTvNCgzpceBh1Dr7e3d9s/PHn7s0ba2ttqamsDAQDwt0Ew0CJFIIBC+gxNO6aJiGKZSqfbu+TI9I93pctVUV4eFh0dERMymOIBkMvk73c6UHgeGYT6fr6Oj44P3//HW//v94cOH6+rqBEKhSCS6NSvdYclISUn+yU9+/O2/D8PwlLfC5/NVVVXZHfYf/OiHoaGhVovl7T//+fPt22dHcN2f/OT5xMTEW378EAS5XK6PPvzwocceXVJSEhsXt+/LL8+fO/fQww/P0OGe1atXr1r1wHeqkyb/6na7d+/alT9/3tJly+w228GDBw8fOvSTn/501qT4hSDoN7954zv1zW+UDL1e/7d33/3Fa7/Ky8+nMxi7d+0SCoVLSkpubQjszrcybtN3lUqlTquLioxKTk4mEAgLi4qUSuX5c+dKli6dBcNaRCLxduzj9/urq6vJZMq8/HkCgYDL5aoGBzUaTVdX13dSomnVzb4dgzQ2Nvr9aEZmZmBgIIZh8+bNa25ubm5qysrOnjWScZs+43A4Ghoa2Gx2UVERg8HIysrq7enRjI4ODgxE/DtJ3f2UjNtHLpdv2LiBRCThZpLJZD947jkqlUqck5kNbnzB0tPTFQqFSCQiEAgEAqF40SKP202f4Vmdb5nExMSw0FAOl4tXmNnZ2YmJibRJSXMANBotPz8/JSWFw+EgCEKhUNasXYv6/YxbXfs37SSDSqVO7oOQSKTJ+YHmODAM47mmJkrm+HQJk8mcvOyVwWQy5moalG+oZrhc7uScSVMyHnznngSwKQAAAJIBAACAZAAAgPvNNF1orFarOzo68c8UCqWgYAF4VJO5evWq1WrDP0dEhEdERMxxg7S3tw8Pj0AQJJPJEhLigYdMAUXRiooKr/dfq/4SEuJveVH1NJWMjo7Obdu24585HA6QjCkcOXJUpVLjn9evXwcko6rqckVFBQRBCxbMB5JxIxiG7dq1x+H4127A73//2VuWDNAxAQAAQDIAAACQDAAAACQDAAAAyQAAAEAyAAAAAEgGAAAAkgEAAIBkAAAAIBkAAABIBgAAmKVMrz0mDofD4XBSKGQMQyeX+3w+i8WCYRibzZ4F4fwAdwq1Ws1ms6ckl/T5fDabzeFwymRSYKLZLxnt7dedTqdKpZoo9Hq9zc3Ng4ODkZGRdDodSAZggpaWFgKBKJNJLRYLXjI+Pt7S0qLVaqlUGpCM2S8ZHA7HaDScOXN2fNwyUeh0Oj/66GMEIaSmps3otGmAOw6DwTx8+DCCEBwOO17S1dU9OKiiUqmPP/4YsM/dYHqNZZBIpMjISLlcPrkQwzC73ZGXlysUCgggaDBgEklJSXw+f2xsbCJ6iMvlslqtAoEgLi4W2Gf2SwYEQZGRkeHh4VPSVRAIhJyc7NmRygRwB+HzeYmJiZNj4UIQJBKJ8vJyQIN0rkgGlUqNjo6OivpPhgUikRAbGyOXy2dWsmLAvSE9PU0oFEzRkaSkZGCZuSIZMAzL5cGRk5KykMmUoqKFJBJpNmXNA9wpgoKC5HI5/d+5S/h8flxcHJ/PA5aZK5IBQRCPxwsODsZbm0QiMTBQhmdOA08LcCNEIjElJUUq/dfkSEBAQGJi4ndKfAuY8ZJBIBDCwkKTk5MgCKLT6RkZGTQaDTQxAF9HZGREUFAgiUSi0+lyebBcHgxschc1enpelkQiiYlRVFfX0On0jIx08Jxw3G7PJ598gqKoXq+fKKypqRkeHo6Ojl62bOncNAuLxVIoFP39SgaDkZiYCIbJJ6PX63fv3oNhmNvtnigsKytramrKyEjPz8+fJZJBoVCCg4MzMtKpVKpYLAYPHsfv99XU1Pr9/smFQ0PDQ0PDMAzPWclAEEShiO7s7KJSKeHhYcBPJmO3O6qra6YU9vX19/X1i8Xi764Y0PSdgxCLxUVFCzEMAxMlgP+JSCTKysqAYYTFYgFrzMWOCQRBDAYjMjISRVHwkP7ztIjExYsX3dQmYWFzunYlkUjx8fEQBIFh8ht6bcwlSxbf9FBUVNSskgwEQcBqnCmQyWSwDvrrAEMYN4XP5z/55BN38sUENgUAAEAyAAAAkAwAAAAkAwAAAMkAAABAMu4JFeXln3/2WUN9Pf6ry+Wqqal54rHHjEYjmHB1u93vv/fe3i+/NJvNeMnIyMjHH330+WefeTyeuWmQN994Y9++fWNjY3jJ0NDQgf379+3bB95tHL1e//577x08cGDCQwYHB//0xz8eO3rU6/XOBslQxMS43e6ysrKBgQGfz6dUKrd//vm69esZDAbYZkIkEouLi8+VldXW1FitVofDcbq01Gw2p2dkzM0FbyQSqai4uLGhoaa62m63GwyGy5cutbW2ZmVlAbHAYTKZmVlZhw4ebGhocLvdNpvtwP79NBotNi7u1tawTDs/EwqFeXl5586dKz11aklJyeXLlxOTkgoKC8lkMpAMBEEiIiOXr1x59uxZoVBoNJmcTmdWVlZ0dPTc3LuJIEhaWppWq+3p6RGJxCaTsaurq3DhwqCgICAWOBQKJSYmZuUDD+zeuVMikbS2tFDI5NzcXLlcfms+M+0kg0gkRkVHm8fHqyord37xBY1Ke+jhhzgcDnj2EATBMEwmkxcuXKgdHT118qTT6czJzU1NTaXRaHO5Fl2wYMHRI0ePHz9Gp9Nj4+LSMzJATOnJPsNisZaUlIwMD+/eudNud5QsXRoTE0OhUGbJWAYEQXQ6PTkpKTg4uLmxKTk1Jfi/Q4ECeDzesuXLe7p7SGRyTGwslzfXw8lIJJKU1BSDXu92uefNm8dms4GTTGmLCYXCNevWXbl8RSwRRyuimbexE2eatma5PJ5IKIJhOCYmBjzyGwkNDcUwTCaTCYVCYA0IgoKDg9lsNp1Om4i1A5jS1oiKinK5XOHh4bcpqWCSFQAAzArJIBAJNBoNRGT7OqhUKhgSntz2plAoJLCP8Ruh0Wi3H0N3WsfLSM/MYDAY4EnflOTUlJDQULDZd+JliI2LA97yzeTk5QZIpbc5Hz99JSM1LS01LQ085q/jhz/6ETDCBGw2e8tDDwE7fDOv//rXs7ljAgAApmMfEJgAAAAAyQAAAEAyAAAAkAwAADCDmKYzJs3NLRcuXMQ/Mxj0733vGfCoJrNz5+6J7Ec5Odm5uTlz3CBnz5a1t1+HICguLrakZAnwkCmgKPrRR59MZD9asmRxfHzcrJIMrVZbW1uLfwZ70m6kra1VpVLjn4ODwa5NqL9fiTsMlUoB1rgRDMPq6+sdDgf+a1paKuiYAACAewGQDAAAACQDAAAAyQAAAEAyAAAAkAwAAAAkAwAAAIBkAAAAIBkAAABIBgAAAJIBAABmEtNrj4nFYvH5fHQ6fUo5hmEWi9Xr9XA4nDmb1cbvR61Wi9fr5fP5Uw55vV6n04miKJfLBT4NmEOSgWFYfX2D0WjSarUThR6Pp7Kyqru7Oy8vj3UbKVtmAV6v7+DBQ1Kp1GKxThQODg6Wlp6GYTgzMwM4NGBuSQaNRrPZbHV1dRaLZaLQ7XafPHnS70eLiopuLfHsLOlDIjCNRtPpdK2tbZPt093do1KpFYrowsIC4NCAu+6H0+pqyGSyQqEQiYRW639qURRFh4aGU1NTxGLR3MxvjgPDMJVKWbhwodvtRlF0cm+ORCIpFNFzvAkGmIuSAUFQcHBQaGgolUqdXEin09PS0qYUzkEIBEJSUqJIJJzc2kIQJDQ0JDExEXgzYC5KBovFiogIDwoK/E/fiUiMiooKDw8D6bxhGOZyuenp6XT6f1K9c7mc0NAQsVgMvBkwFyUDgqCQkBCFQjFRkVKp1Pnz583lLskUsrIyORzORJq8iIjI2Ng4YBbA3JUMkUgUFRWF5zQnEAgikTAtLXUuD3zeKKkTfTcCgSCTSWUyGTALYO5KBgRBMpksLi4OgiAGg56VlUmlUkG+4skUFS0Ui0UQBMXFxSYkxNNoVGATwL1hmrb2JRJxVFTkxYsXmUzmvHnzwXO6saEhEolGRkbCwyOCg4PnrB1ee+3XOp0WgiCn04WXXLlytbGxEYIgkUj8u9/9FrjK0NDQ//3fbzEMmogVDEHQ9u07du/evXTp0nXr1s4SySCRSHJ5cGHhAiaTxeOBFY1ToVKpqakpJBIpIiJsLs+t2u12q9U2ucTn8+EldDrIAg9B/1o0bJtS6HK5XC5oIkfBbJAMGIYlkoCioiK/HwWjGDfpTyJIfHyCWCwWi8UIAjYKAeZ8xwSCIDqdJpfLJ69ZAkxGIOCz2SwwkQQAkvGfipRCAWlsvv7JEYlALzZu3DC5iz4ZGo0GnASvWp5+eutND4WEhMwqyQAA/icgs+T/hMlkFhcX3cm6HNgUAABMI8kwm81erxcYGgC4IzidTpvNdj97xHf7H3R2dlIoVKFQwOPxaDTa/5z+sNlsapVqbGzsX5KGEPh8Xlx8/JxyC6VywGIZhyBIJBJNXtmJoqjBYOjp7vb5fBM99mC5PCAgYBZbY3h4eCLNPYPBjIyMmFIn9ff122z/2vpMJpMlAQFhYWGz1RpjY2NDQ0MikYjP53M4nP85nuXz+cbGxnq6uydKGAxGWHj4jYGapotkaDSaS5cuy2SylJSU0NBQPp9Hp9O/YVxTp9OdPHHiUtUlCMPsDofFYlm2Yvmbv/nNnJKMw4cPX7tWD0HQihXLH3nk4cmS0dvb+8H7/7DZbBiGjmpGg0Pkzzz77OyWjPPnL5SWnsY/x8bG/vrXr00+qlar9+ze1dvTi2GYyWik0Kibtmx5+umnZ6s1LBbrpUuX9Xp9enpGfHycWCxiMBg0Gu3r5trdbndLS8uH7/8DgiAMRdVD6vjExB//+Mf8rKxpIRlut2eigYAjl4dA0JVr1+qvXauXSqUpKUnJycmhoaEUCoVMJt94n+Hh4S++/PKLL7/sdrtramq+2LFj85Yts+Z5j4+PT7HP15nx5k+LSMzNzc3NzcVP9fe//U0SEJCamjpzDWK32/+nQRwO5zccTUxM/Ms77+CnOnTwYF9f3+LFi2eTRphMpslVLIVCFolEjY1NavXQqVOnEhMT0tJS4+LiWCwWhUIhEAhTtlYwGIySkpKSkhIIgoxG42/eeGPeggWRUVHTpWPS2tr64x//9BtaHBqNpqKiKioqMjc3Ny4ujsvl4Dc55T4xDFOpVM1NTdk5OTExMbPm8X/44cd35DwoilZWVNBotLS0tBm97f3kyVMnT566IwZpaW42GAwZmZm3Nnc4bfn97//wdYc8Hk99fUN9fQOLxSwqKkpPT5fJpFQqFUGQG18oDMNOl5YGBgWlpKTweLzpO5Zxs0rD0dLS2tbWTqfT5s+fX1xcLJGIp4xxjI+PV1VUXrl0+f0PPwAjXjeiVqt3fbFzzdo1+OY9gE6nO370GIVKKViwYA7evtVqO378xMmTpxIS4gsLC+Pj45hM5pTv9Pf3f/LRx2/85k25XH47/+v+rMvAMIxIJEZERMTEKNhs1o27VJubmwcGB55+9nu3I4ezmJ1ffFFQtDA3Lw8sWMIpO3uWK+AvXrSIOVd33KAoKpPJFIpomUx641ghiqIffvDBY088Hp+QQCaTZ5JkkEgkmUyanJwUFxcfECBhsVg3bmxXq9WdnZ1cLjcnJwdsoLiRuro63djY4iVLAoOCQEwACII6OjoGBwdjYmNj4+LmoMMwmYykpMTk5BS5XM7jcWk02pRpFI/HU1NTYzKZFhQU8Pn82/SZOyMZxcVFSUk3jz3Z29t34cIFg8EoEPBjY2NjYmKCggIFAgGbzb6p2rlcrprqaoNev2z5cgZjNmxGJBKJL774wnfaLHPw4OGenp6bts6sVuuXe/bk5uZGRETM0MiGzzyz1eVyffvvnzt3vq7u2tcdtdvtp0tLBQLBbIoOKxDwX331lZseMhiMdXXXGhsbyWRyaGhIampKSEioWCzi8Xj4KMaU7/v9fq1W+8WOHavXrJFKpbe/yeDOSIZUKpVKpTc91NLSGhYWlpOTEx4eFhQUJBAIvmFCCIKgoaGhhvr6utpa1cAg3upmMJk/+/kLPB5vhlYgCIIkJCR8t2Z22bmblvv9/ubm5mu1daMjmiuXLhEJRAiCFhQULFlaMoPkNTo6+jt9v6mp+RuO9nR319dds1qtbS2teCUUFR318KOPcjicmSsZVCo1KSnppocaGxvJZNL8+fPCwsLCwkIlEgmLxbpxomQCp9PZ1NhYV1PjdXsulJ3DX6IHVq/Ozcu9tV4t8R74R3JyskQi5nK536YTxWGzFy1eolDETDIfhUwmz6kW+MKFC+Pj4yEICg0N/S/1gWFpQMAPnnvO4/nPLGxgUODsjg+QmZk5MSvE508d2xIIhZs2bzYajRMlAdKAWRxZWigU5ebmBgRIhELht6knSCRSeETEz174+eRC8Q0TDt8eGMOwu3qHPp/vGyQQAAB8J1AUxTDsPlYSd10yAADAbALMRwAAACAZAAAASAYAAACSAQAAgGQAAAAgGQAAAAAkAwAAAMkAAABAMgAAAJAMAAAAJAMAAMxS7mmIncHBwZbmZhaLXbiwEJgeAJjNkqFWq1tbWsIjIm4neG9vb++unTuDg4PvhmRgGOZ2u4eHh4OCgiYHMhsbG+vs7NRptRAEIQgiFAqZLJZqcBBPBcJis+Pj4qxWq1qtjoqKCp29+S8AgHsqGc1NTX/4/f97+LFHp228b7/f397efvzYse//4AeT83r09fX985NPmhqbQkNDSWRSdEwMmUQ6fPCQVBpApdKCgoMYDEZTQ8OJEyee3LoVSAYAcIc7Jj6fb2BggEKh2O12AoIIRSIWi0UkEp1Op8FgMJvNEAYJRUKJROJwOAx6g9lsptPpfAGf9e84rg67o7+/32G3CwQCkVhMIBCcTqdOp7NaLHQ6XSQWs1gsi8ViMBhIRBKK+okkEovFGhsb83g8AoGAx+PZ7Xar1YqhqMfj9XjcAqGQw+Go1ertn287X1aWlpqWmJQoCQig0+kTlx0WFvbyq79AEIREIpWeOgVB0BNPPRUSGkomk0NCQpoaGoArAAB3RTIsFsurr/wiWB48PDQEwfDatWuLFy1is9ktLS3Hjhypra0lIITVa9c89vjjlRWVFy9cqKmuDo+IKCgsKCgsRP1+vHvyzttvt7e2LiwqfvzJJ6QBAdXV1UePHGltbgmWB2/avHn+ggXVV6/u2b1HKBTCMCwJkISFh585fdpoMCwoKFi1enXH9euVFRVer298fFytUi1ZWlJSUnL06NGL5897PJ7f/uY3xUsWP7V16+SAcSwWKyUlBYIgGIZPl5ZCEBQdHR0bF0ckEm8/GiIAACTja/F6vY319a3NzS/94pWK8vKDBw7IAgOZDMaOz7ep1KrVa9YEBARgGNbS3Pz8c8+tXLXq2R98X9mv/PyfnxkNxsCgQAiCKFRKYmJicFDw3j17uDzuwqKiV196OSkl5envPXPyxIkvduwgUyhjY2NXLl0SSyQly5YFBQe/+tLLDz3ySE5Ozhfbt1OpVAKReL39Op1BL160KCBA8tXBQywW64FVq7q7u2uuVr/0i1fSMzImpzKFIEhv0J8+fZpMJsfFxeFRha5cuTqoUoWFhUVERAA/AADulmRAEIQgyNoH169Zs8bv9+/eucug13d1dIxoRlatXr316achCDKZTJ99+k8Ign728xcCAwM9Hs/gwEBHR4fH68Gr96efeaattXXP7l1ms7muttbj8SwoKIhPSHC5XIcPHmpvbRUIhTw+f9mK5c9+//t79+yBYbhoUbFIKDx88ODgwABfIIAgKCUl5amtWy+cP3++7JzH44mMjAwPD79WW5ecnBweHj7lmnu6ul996WWhUPju++/hJe+9+y4Mwz/88fOBgYHADwCAuygZuGogBAKMIBiGQRiEYhgGQQiC4CEJEQRBMRSCIAKBgBfCMDwRlR+GYbwcgiAMw4aHh/1+/xUN090AACAASURBVDt//jORRPJ6PMmpKSmpqWq1msFgyAIDURTVjI6iKPrzn/wUQRCLxfLAqtVEEnHiPDCMQBCEQRAMwxAM4+U3hhrNys7669//jiAIg8E4e+YMBEGfbdsWHaPAU+ACPwAA7q5kTCEpKan+2rWyM2dpdHpISAgMw9k5OZ998umnH3+SnpGuGlT19fYuKlkSFBzc+N8DjQiCpKWnHz38VWJyckyMgkanSySSwKAgtVqNIDCBQKDRaMnJyQf27svOzY1PiHc4HOkZ6b29vd9wMQ0NjQwmUyQSTQ5oTiaTJRIJ3rHClYUv4OMlODarrbOj49KlSxAEkUik7Oxs4BwAwN2SjITExA0bN54uLT24f79AIHjkscdSU1Jee+ONttbWf37yaUBAwAOrVxctKh4eHp7yhwQCITs7+6VfvNLa2lpXW8fmcIqKiyZX+wwGY0FBwQsvvdTS0ny6tDQiIpJEJt805DyJRFq9evWQSr17106JRMzn87/TLRj0+tOnSmuuXoUgiMfjZ3+5BzgHAHAj3zbC+Mjw8PXrHaGhIUHBwefLzgWHyGNiYtRq9YBSqVAogoKDLRaLWqXSaDREIjEuPl4oFJrNZryEy+UGBQeLRCKzydTX10en01NSU81mc/XVq/KQkJiYGIvFMjQ0pBkZIZHJwcHBMplMq9Uq+/tDw8LCwsJQFNXr9Uql0qg38Ph8hUJhs9uU/UqRSBgbFzc6Otra0hISGhoVFeXxeLo6O0dGRhKTkiQSCT4Votfre3t7YQjKzsmBIAhF0c6ODtWgKjcvj8P9V3acnu7urq6uiZulUCiLlywBzgEA3LpkAAAAAAS2pQEAACAZAAAASAYAAACSAQAAgGQAAAAgGbcNiqI2m81utwOj3wiGYT6fz2g0+v1+YI2bOo/D4bBarcAUX4fZbHa5XBNrrO+/ZKAo6vP5bmdG1mw2f/rJJ1/s2HGXXjkURTEMu19zxj6fD7+AW34lhoeHn3riiRtXu90p+9xH42D/dp5bvgCr1XrwwIF33n57VjqP3+/3+/23+d9feeml8vJyp9N5t53n20rG5UuXfvnqqzqd7pb/scfj0Y+NmYymu2F0t9vd3t7ucrnul8a/+cYbJ44fv+U2FIZhTqdTrVJ7vd67cXkjIyNq9d06+f+ks6vrB88+q9FobkeRjQajXjd2lySjra3NarXeL8l4729/271rl8ViuZ2TaEY04+bxu9FKxRdSejye7yYZFotlcGDgNt/JuyfkOp3uxZ/9bGho6B40zG7KkEqt1+vx4IC3bpy7dvGHDx7cvXOX2Wy+L8ZxOZ39vX23WQHePefxer0//8lPO65fn3gr7jEajUY7Onqbgo5h6F2yz8XzFz78xwdGoxH/lfjtH5jf5/P5fFqt9uKFC3a7vfzCRWmg7MENGxITE7Va7eXLl2uqqyEMW71mzcKiIrvdXn7xYnl5OY1Oz83NzcnJwc/T1tb6f2++2d/Xn5mdtWnzZoFA4PF4TpeWHjt6lMvjLSkpiY2Nra2paW9vJyAEl8v5w+efb2xoOF1ayuXxVq1eHR8fX1dbazAYmhobBwcG0zMzVqxcCUHQW7/9rbJf+dPnn6dSaa+98ev4+PjJe9LuUcfEjzqdzt6eno6OjgGlsq+3Lz0rc/PmzUKh0OPxVFVWll+8OG6x5OblzZs3D7dPb2+vXC4vKCxMSEjAz3PwwIHe7h4Wm7Vq9erMrCwKhaJUKk8eP15/rT4pNWXNmjWRkZGvv/ZaWHh4fV1d/rx5UdHRXV1dtdXVRAJx6YrlkZGR1+rqqFTq3j1f8vi8tevXZ2dnHz1y5OiRo5bx8atXrmRkZv7ox89/1w04t1+Ne30+v98/Pj5+4cIFs9lcffkKg8l8YPWq7OxsCoWiVqvLL15saGhg0Olr1q1LTk6+VFVVXl6OYVh6RkZeXh7+NJVK5Z/++Mfmxqak1JQnnnhCJBL5fL7y8vLjR48iCFJYVJSfn6/s7z918qREImlsaHzu+R+5XK6LFy60t7Zl5+YsLCqSyWTK/v6JB5SRlVmydOm777yjUqle/9VrTCbz+Z/8OCc39x5vbvb7/X4/6nK52trampqaNCMjjQ0NScnJTz71FH6PtTU15RcvanW65OTkRYsXMxiMq1ev1tbUeDyewsLCwoUL8QtuqK+vLC93uV3z5s9fUlIilUo1Gs3JEycunr8QGx+3bv16hULx3t//TqfTe3t6o6Ii/z977xnYxnWlfw8w6L0DJCrBDvbeqWZJVrMttzhxlMR2yiaxkzf7XzvJZjd2drOpu4ntuCYucY1jq1uyeqEkkiLFTrBTBEiCYAGJ3oEZvB/GgWk1UyWSSJ7fJ+BiBiTOvfPcc9s5RSUlZrO5saHB5/Fu2rK5rLycwWAcO3bM6XCcbWgkKsg2M/Pu2+9MWCz9fX2pqak//Y+foc8888xCftXg4GBHe/vqNWvsc3O//+3vyisrKiorotFob2+v1+MZHj4fCgVLS0vT0tOZLJZAINi9e/fM9HRVVZVWqx3sH/AH/DQarburKxQMrVl7R2pa2uTk5EB/f2FR0Vtv/tXj9VRUVsrk8rbW1kAg0N/XNzQ4WFFZmZ2dPT4+fn54eNWaNXQa7ejRo6mpqR99+NHU1GRhUVFGZobZZDJ2Gysqytksdl1d3Xe++y+r16zOyMhgsVjE4fqbxs4dO3RJSUqV8uiRowP9/ZXV1WnpaVOTk339/SUlJTu2b7dYLHkFBfl5eUKRyGw29/X2crncouJiKo3W1dlFZ9CpVOrO7dura2qqa2ooFMrAwACDwXA6nadPnRIIhRWVFZFI5NDBg9U1Nb/99W9oNFpVVZVILB4cGCSRkNLSUpVKNWGd6Ors3Lt7t1anW7V6NU/A37f348TExJTUVPOIicfjfenLX66oKE9UKm9yILLJycmDBw5uufuucDj8+9/8NjUtraKykkajDg4M0Gi0YDB4+tQpFEWrqqpS09MRBGlsaLBarQUFBckpKZaxcbvdTqVRTSMjFotl3fp1uXl5MzMzra2tJaWlu3bunJ6ayi8oUGs0/f39fp/P7XLv2bNHn5xcu6LW6/U21DfkF+SXlpVGIpHR0VEkFjvbeDZeQZOTkwMDA3du2PDJ/v0Pf/Wr69evz8rJ5nK5N7nxHD50iMVip6alnWtuPlVXV1ldnZ+fPzMzc+7cuZLS0iOHD58/fz41La2wsFAqkwUCgf6+/rGxseKSkuTk5KGhoZGRkZTU1O0ffSSTyVauWqVPTjEauyetVjabffToUQaDsXLlKiqN9sm+ffkFBW+9+VePx11aVqZUqUwjJo/HU1ZWmpqWarVaR81mqVT6+9/8Ni0jvaLi0woSCAQ0Gi0YDD28bVt1TbVGo6FcbXcRCAbHRkdLSko0Go1YInnuj8+aRkYKC4vKysuys7NjsZjH45manNy1fcfT//WLjIwMHMcREqmjvZ3wmhISE6trajAMCwQCf//gb/fed9+Hf/87i8XSJen8/sD09BSfz/d6fVKpdNXq1Q6H4/e//e2k1Wo2mex2+9TUlNPpnLRa0zPSS0pLhUKh3W4/efwEHovl5edRKGhJaWlqauotDMyHYdjc3CyNRqupqcFxPBQKvfv2O9u2bXv/vfd+9K//WlxSwmQyHQ7HX998E4tiX3n4K4qEhOmpab/Pf/DgwXvvvRdBkIKCgvyCgkSl8tWXXzF2ddNotJ3bd8hkMqlMapuxuT1uv9/v9/szMjJWrlp14sSJE8ePRSPRxMTEUDjkdrnZHM6kdTItLa28osLpdG7/+4fWCWt+QYEiIYHN4VRVV80PpHzziUQiY6OjWQZDUXHx8PDwX159tbenh8/nDw4MfPPb39bpdBiGjY2N/fp//uffnnyyqLiYQqEwGIzWllYMiyIIIhaLq6qr6XQ6QiL96r9/+fDDD3+8Z6/H49FoNBiGTc9M87hcPp/PYDDKysqSU1Ke/eMfG+sbxkbNXC530jrJF/AlEsn8CgoEg397770f/PCHKIrm5eeXlpUyGIxbZRwcx50OZzQSra6uZjAYZDL5F08//cijj+7euWvzXVuqqqt5PF4wGGxsbBweHiosLCwtKyORSFwe77+efrq2thbH8CS9vrKqisFgnB8eMnYb6QzG9g8/kkgkKpXKZrNNTk16PB6/319YVFhTW9vT03PyxHGnw6HWaJFYbHp6Oi09vbSsbGx0NCsrq7CwkKighIQErU43YZmoqKxQq9XItR1+J5FIUqmUQqGIRKJgIOCYdJSWlioUCiIVAIqiY6Nj42Nj6enpdDqdRCJpNJozp0973G4EQVgsFp/P9/l8PB53bnY2HA5PWCzfePRRoVBIIiEsFitBqbTN2JgMhkwmm56a8vv95RWVCQkKBEG4PJ5SpSKTyTwen8VisdlsHo+H4/itGoJejnm/kTc7OxsMBk3nR9QaDZvNJpPJDAbD7XKx2WxFQgKNRhMIBYoExenTp4h7xRIJjUYTCATRaMTjcaMohcGgV9fWUFCUnEMWikRMJpOEIEqlks1m22Zm5HKFWq3m8bgIgjCZrCgW7Whrk8pkJBJJIpFQqdRwJHy7LdyKxWIajcbn86PRqNvljkYigUBArVZTKBQSicRiskwjI5p/mEupVDY1NdkdDgRBGAyGSCQKhUJikWjWZguFw5NWa3VNjVqrIZNIDCbTYDAMDgywmCwiOJPFYlmxcmVCQgKKkjMyMuRyhVKlbG1p+ayCuDz77NxtZRw6g078RpFYbJuxBQPB0dFRiUTK5/NRFOVwOJFIJBAMqtRqFouF43hKcrJpxOT3+/FYTCAQMhgMHo/HZnPCkfDc3ByGYStXraRQKBmZmTw+TyKRkMkkuULB5/MddjuHwzUYsoRCAYIgVCpNq9NdXEF+n4/FZs//D29Ah5yoVEYi0fGxMWKE7HK5eHxeSmpqR0dHfn4+hmHDQ0N8Pl8gFF5wI5lE5vP5+YUFySkpq9es5nA4c3NzHo+HSqUisRihEQWFhVqt9s4NG5hM5uTkpEgkIgJ/XcoFQm7VisCV5ZXFYmVmGYaHhqRSKYvF8vv9QpEoHAqPjY2pVKrZ2dmxsbH09PRLtB46I1GZmJ2TU1xcnJefT0wksViseMwxpUoVCARy8nLLysqYTKbH4+ns7Lx8J4bdhps+qFSKXKGYmJg4PzycmpaGYZjX683MNAwNDYklEgqFYjKZqBSqTCod9Y1ecC+Xw8nOzUlNT1u7bh0RbIFMJptMJuJTGo2WkZHBYDDWb7hTpVKFw2G3232FJa1INHIbnupmMBlp6WmTk1b73JxAKPT7/TQajc1inT9/XqFQkEgkY09PhiGTw+WSyZ+LREen0VUqVW5ebnZuLhEvamJigs/nx8dccrlcrVGnpafVrljB5XK9Xi/hg1zOA4o3noVKBoVCYbHYKIpSqVQOl0O0WhRFWWxWSWmpRCo1Go0TVitKIicqEzMNhvsffKCttXV6aiqGIJZxS3ZOjlqtPtfcTGfQiQeJSqNxuFwej/f1Rx5pa2mNRiNEN6JUqZhMBrHwIZFIqqqqGhvP7vv4YySG8AT86upqJpNJZ9CJX06lUlksFoqidDq9qKTk8KFDNCpVn5x8k+c+Cc+CRqejKMpgMImREYlEolJpXC6Hy+V+dds2s9ns9fkI8c7OyZmanKw/c0YgFPq8vlAwtG79egqFwuFyiN9FJpOZTBabwy4sLPT7/adPn7ZYLMFgUCQWazQaNodDpdFIJFJRUZHT4ejt6XHYHWQymcli+nw+DpdDdNfEf0Wn08lksj5Z39baeraxsbqmZn4sspsDiqIcDpvQes4/ZgpQFGUyWWw2Jz8/PxQKNTY2Dp8/j5LJYonk4W1fNZlMXq8XRdHJyakkfVJKSsrU1BSD+emogUKlcrhcFpv9wIMPnjt37uiRoww6nUKlZBoMVCqVxWahKMpms9ffeeeO7dvrz5yh0WgoigpFIolEMr+CaDQqm8Mmk0iVVVXNZ5uEQiExEXazdYHBZDDoKIrSGXRiIpNEIlGJ38hibb3vPrPJdPz4cSaLxeFwhEJhRmbm8NBwwO+PxWKTk5MPf/WrErGYw+HS6TSi3ml0GpfPy8rOplAoDWfq52ZnfV4fXyiQSqVMFotGo5FIJENWlm12dmhwKBQKkclkGp0uk8mIxGDzK4hGoyuVSi6Pd+bUaRqVmqhULnT6MxAIoBQ0Pz+fSqUG/P7aFSsoFAqxobO0tDQ9Pd3hdHa0t8/NzWbl5KjVaq1WGwgE2lpa3G53bl5eUVGRQCAIBgKKhITU1FRis2MsFqusqlKr1WQUNXZ3G7u6E5XKlJQUMorKZLL09HQajUZ0NWcbG/t6evMLC9Rqtcfr0Scnq9VqKpXq9/tpdFpeXh6Xy9XqdEcOHVKrNYnKxJsvGbNzs2npaYmJidFoVK5QpKWlxWKxaDSCYVhVdbVerw+Hw91dXSaTSS6XFxQWymWyiYmJgf5+JpNZXVNtMBhwHHd7PBUVFWw2OxaL+QN+nU6XnZMjFoudLlfruXOW8fGKykq5XD4zPV1cXCyWSEQikUqlwvFYV2fn8NAgn89PTU1FyeSKykomk0kikWyzNoPBkJCQkJCQ4PF4LOMWtVotlUpvsnHC4XAwFCotK2MwGG6Pu7yigsPhEBs6tVptXn6+SCyemZlpb293OBy5eXmlpaWRSKSrs3N2bi4tPb2kpEQmk4VCIUJtiTkjv99Xu2KFRqul0WiDgwNdnZ18voDIMkGl0fLy8zkcjlwu1+v1o+bR5rNNXp8vSa9XKpWxWGxeBUVxDKuqrk5JS60/Uy8QCFQq1c2PBetwOFRqtU6nw2MxHo+Xk5tL7C7zer0rVq4kYl/39/UNDw3xeLzs7Gy1Wh0Kh3p6eqanpwsKC1evXs1gMm2ztuycnISEBAqF4vV4BAJBUVGRWq0OBPznzp3r7+0rr6hQKpVOp9NgMCQmJgqFQqVSSafTjN1GY7eRyWLm5ubyeDyigthsdryC8gsKYrHYQH+fWqNRKBQQYgcAgKsAjqUBAACSAQAASAYAACAZAACAZAAAsERZ6L4Mj8fjcDgUCsUNWb+MRCLj4+M7d+zo6Tb+8te/UigUl92gtUiwWCzEnsIb8kMikcjZxsaDBw4SxwFWrV692BPHhkKh4eFhg8Fwce7LayAcDre2tu7dsyccDm/YuLG0tJTH4y1q+1itVhKJlJCQcAO/E8OwsdHRM2fObNi4USKR3Gwvw9jd/fpfXosfgL3+H0MmkzMzDeeam10u1xJY6H37r39tbGi43Oa5q64VMpnJYpVVlK9YudI2O7vv449vw42tV/WE9/X1/eF//+9GVTSJROJyuWvXrq2trd21Y2dnZ+eito/D4diza/eJ48dv7NdOTU3t27fvk337b2w0swV5GZ2dne+9++655nNut5vH5ZLJ5Lvv3WowGGg02vDwsNvlEolE4xbL+eFhCoUyPTVdWV1VXFxMpEHs7elpbm6ORCI5OTmGrCyiN6BQKFKpNDs7i5CPxS4Z77/33uFDh9rb2k+fOkWn0VPT0lauXqVSqfx+f39fH4lE0mi1e3btEgiFZpMpITGxvKJCo9GgKOp0ONrb23t6eoQiUU1NjVKpJJwUFEVTUlIyMjIQBNm9a1fdyZP33nffzd+CdQP14k/PPddY3/DMz38uEouJM8psNntsbGzWZpPKZD6fr6G+XiKRtLe1SSSSmhUrMjIyaDSa2Wzu6uoaGhgUCAUlJSX65GQOh0PYR6fTpaen22y2N157bdZmwzDskmk3b388Hs/OHTt27tjOZLLMJnOSPqm8oiIpKSkajXZ1diIIkmkw7N+/n4KiU5NTLpczPSOjuKREpVIFAoG+vr6O9vYx82hZRXluXp5MJosbwW63d3V1dXd12Wy2G3tQYEFeBoNOZ7M5VApFJBIKRSKvz3vgwAG/3x8MBvft3TvQ3+/3+881NdedPBmNRslkUntbW/2ZMwiC9Pf3Nzc3YxgWDodPnz7d1dVF/PcUCoXNZqO37sjpjYXH41EoVA6HIxZLKDTqwOBAW1sbhmETFss7b7+N47jT6fzow4/GxsYYDMbU1NTZs2dHRkbsdntHR8fAwACDyZyZmfnb++/7fL64egoEAuLxIJFIFAp1kT4PyKf7sml8Pp9EIkkkUr/ff+L48bm5uVAodPzYsdaWFiQWGzl/fu/u3RaLRSQWxxBk+0cf9fT0DA4ONtQ3TE9Pc7icYCDY3t7e19sb98IIxfn73/4mkUoVCgVl0bYlMpnM4XDodAaLxaIz6CaTqb6+Hsdxh93+yksvE37roQMHGhsaMCzK5nAGBwePHD48ODjY09PTUN9AIpMlUonJZGpsaHA6HHEZamlp6evtTU1Nu/H/8EIuSs/IqKmtUSQotn3964//4IlHHnusq7PTarWOjY2Nj1sEQiFfIPD7fVwud+OmTdu+/nWZTPbeu+8GAoE9u3efOH7cYbd73O6Ojo6hwcFF7UBejs1btigUiqrq6m9++1vf/d739Hp9j9E4OTlpHh2dm5tLz8ggostkZ2d/7RvfWHPHHSPDw01nzw4MDOzdu7ezoyMSCs9MTR87etTjdl8QVWx8bMzhcBSXlggEgkVqHCqVqtPpNm/ZwmAwHv/BEw9+6Uujo6NjY2Pj4+Pj4+MMBlMml4fDYQzD8/Lzv//441966CEajXbi+PH9+/cfPnRoZPg8CUFcLmd7W9vg4ND8b45Go9EoptFoQ6GQf9GGoSYSlWdkZhQVFz32zW9mZmZ2dnRMT0+bzeYJ60RySgqdTvd6vEKh8K67737sm98sKi62Wq379+//ZP8np+vq3E4Xh8sd6O9vbm52udzERFh3V1d3V5dKpSouKb41kjEfwicUi0R9vb1nTp9OSUvVJycTfSCbzZHJZEKh0GAwtLW2+v3+zs5ODMNGzaPTU9PJer0uKemGzH7dzgiFwkSlMhwOn2tuHh4aWrtuXfyYk1wu53A4GRkZ0ShmGjFZJyZGzeZIODI4MBAOhVatXk2j0+fbx+lw9PX1xWKxVatWLRn7aDQaqURiGhmpr6+XSKWG7CwiZgKTxVQqlWQyWSwWb9q8eWhoqLWlBcdxt8vV19tnm7FJpVKVSjnfeUlPT////vVHSXp9b2/v5NTUEjAOl8tVqVRkMrnl3LmWlpYtd90lEAiIQ2JyuYLL4zGZzOzsbK1W29rSMjg4wGKzzSZTZ3sHmURO1iez2WzCxWg6e9bY1R0IBNpa2wJ+f9flzzf/s+YyCGIxBMMwEonEYDA2bNxYX18/Ojp6//33y2QywnfAMCwUCkWj0dnZWYUigUqlpqamGrKyamtrJRJJMBgkjpwuVbEgolQT0xCjZvORw0dQCvr9xx+PXxAKh6PR6NzcHJlMFggEYrG4tKysqrq6uLiYQqE4nU6RSBQ/m+zz+bq6umamZzIzM4mDSUsAYsZh5apVZ06fPn/+/KrVq4moLQiCYFHM7/cTYZMnJyfFYjGbw0lLTa1dsUKv15PJ5PlxZ4kjWywWC8MwiVTicjlvt5gp19R+YiQSSaVWZ2VlHT582O12/9uTT8YHpIFgIBKJRCIRp9MZCoUUCQlsFquwqGjVqlVcLjcUCgWDQUIyMAzjCwSxGH7i2DGn0+X3+9va2u69776bLRlESJvh4WGJRMLj8YpLSp5/9lkWm52UlCQUConI406Ho8do9Hg8XV1d9z/4AI/H27hp08njJ1gsVoJC4fX51Gp1cnLyZx0FgtDotJscNO2fhEwudzgdVquVxWIpFAouh9vR3r5i1cpP45IhCIIgpvMjZDJ5cGBAJBYVFxdrdbo5u725qRklk2k02ozNtmbNGmINOxwOd3R0nDh+QiQSyWSykZERuVzO/nykk8U1ncFksURiUXdXV2paWnZOzhuvv0Ec35TJZPHht7G7O4bjLre7+WzTylWrGAzGJ/v3k0gkj9tNpdICwQBxOJ0YkvT19dGo1EAw2GPsUamUNzma6Y2FQqEIBMJAwG82myUSSaJSefa55wqLinJycuLXjI2O9hh7+AJ+f19/OBy55557bDbboQMHOByOQqHw+3zhSCQrK0sgEEil0kcfe+zRxx5DEORs49lfPP008fpGsdDD7zw+PxaLvfPXtxJVSr1eT6fT29rb79y4Mb+ggMVi+Xy+1paWrq4us9l88viJVatX33X33RQKRaVSUWnUfXv3vv/e+wwGIzc3d/6YPBQMdnV1rb/zzvmRPxarv63VHjl8eHxsTK3RyOVyp8vpDwbuv/9+4rS13W7fvWtXJBzeu3s3jUbfsGljTk4On8+XSqUz09NvvP76gf37V65eTSyjIAhis9nee/ud48eO9RiN+/ftMxp7kvT6xMTERfxI8PlUGu1//vuXefn5KpVqcHCwrKysoqKCWEHr7++vO1kXjUTffONNu92+5o47ampq9Hq9PjnZbDa/9867J0+cYLFYWVlZfD6fkIyhoaFn/uM/Ozra8/Lz1q5bt3iNQ0xncHm8tta2ttaW7JwcOp1umZh4eNs2rVZLXLDjo+0Bf6Chvv7MmdMSiWT1mtVFRUVarTYhIeHQwUMv/elPlokJg8GgUqku2DblcjnHLZaVq1YRU+k3hthVQuRA6unp+cpDD3V2dhJhL6anp//7F7/4yVM/ji17cBy32Wxvv/XWj596KhAIxGIxDMMGBgYqSsu6OjvBPhiGDQ4Ofu+73z129GgkEiEKd+3c+cB995lMJmg8Tqdz7969jz3yCDFMI3jogQffeO11h8NxO/yTV700FY1Gu7q6fvXLXz781a9qtdqlMay4gUxNTe3etWt4ePir27Yt4Ymba6a3t/cP//d/tStWZGVnL/Ytvzccu91+6NChk8ePP/atb93CwMU3ZmASn3ZyOZ07d+7ctHlzdU0Nj8cjJCMWi2E4npiYeMkYlsuHSCTS3t7u83rv3LDBYDDENwsQvWtJaSmX5CtdtAAAIABJREFUy122xonFYqFQaOeOHRUVFStWrpRIJPH+JhyJsNnsvLy8mx8R6/YhGo0ODAyMms0bN28uKCiYv9PE6/UaDAalUnk7bM+5uqhcROwzm83G4/Hm5wrBsE+nuxf7Vv/rXzTxejzhSITL5cZdDEIvHA6HQCBYvDuybtQQeGZmhs1mExFb4x8FAoFAIMDj8ShLZXfftdnH5/MF/H4uj3eBi2G32xkMBpGpYJFJBgAAyxyYiQAAACQDAACQDAAAQDIAAADJAAAAJAMAAAAkAwAAkAwAAEAyAAAAyQAAYDFxdcfSbjgYhnV0dPzmV79KTUsjomYcOXy4saGRxWYt6qApN4qpqam9e/YcOXKkqLgYRdFQKPSH//2/QDAol8tvSEKZxY7RaHzu2Wd5XK5CoSCTyWcbzx46dIhOp8cj9yxz3G533cmTL7744oqVK1EUJZFIb/31rVHzqFAovOYIGrfYyyCTycnJyVQa7eSJE7aZmeHh4a6urlgMX6QB+G84QqFQrlDYZmbqTp4MBoPNTU0DgwNqtRr0gkCr1bKYrKamJiIEcUdnh9/vu7EJhBY1LBZLo9GEQ+G9e/ZEIpGOjo7e3h4en3c9J6pvsZdBRBJlszk7PvqIzqAfPXwERVEiOdiSDyy8ECgUCpPJtNlsBz85IBQKX3np5a333VtYWEj/fGDhZQudTmezWUcOHfb7/a2trXO22bXr1ul0OgjjEu+SGUwmmUz+8yuvpqSl/vmVV/Ly8ioqKgQCwTW3n2s5a4xh2LvvvndtAVpzcrLLy8svKMwvyC8pKz129BidRquprSHCwy5mb7mnsbHx2u594IH7L8g/IJFISsvKhgYH33n77eSUlBUrVjCZzEWtF9u373D8I+PG1ZKQkLB586b5JYasrJKysuazZxEScscdazMzMxd15B6z2XzkyNFrvn316lXzw+siCMJkMkvLypqamv7y6qsioaiislIqlV7P83UtkhGLxerqTgUCgWu4l8FgXCwZbDY7Jzf34CcHMjIzEhMTb9t4RAvEYrEcP37i2u7duHHjBZJBpVIVcrlarT5+9Niq1avjUeoXL01NzRaL5druzczMvEAymExmRmbGoYMHOGyOSqOOp4BYpNhss9fceBAEycrKukAyUBTl8/lFRUV7du36+iOPSKXS6wzacls0PqfTebahMSU1NYphZrPZ6/WCSxknFAqNjo4ODw9XVld1d3fPzMzc2Hx5ix23293W2iqVyphs1vnz591uN9hkPtFo1DYzU3eybvWaNZbx8QmLJRQKXddg+Tr/IYPBIBIJF359UlLSBQ4LhmFnzpwZHTXfd//9Q0ND3d3dcrm8sKhoCQxH2Wx2QUH+Vd3CYn0ukh2O41artbm5mUajPbxt21/ffHPfxx8/9NBDHC53acxlaDQajUa98OsviCSOYVhLS8vw0FDtilq/3z88NNTW1lZTU7NkooqWlZVelVMglUoueL7cbnfdqVM2m+0/n/7539577/Tp00KRSKPRXPPzdb2SsXnzpqt9Ki74SdPT00cOH7l769bSsjJ9cvJHH37Y1tamT05eAousEon4+9//3vV8g8/n6+npmZ2dfeSxx5KTkx948ME/PfdceUVFenr60lg0KS8v27r1nmu+fXZ2tu7kyYrKyhUrVwaDwb179jQ3NRkMhiWzyProo4/yeNe+uhEOh00mU9PZs//6b/8vNTX1/gcffP211/r7+iQSyWJdZI3FYmNjYykpyUVFRXw+Pzk5uba2VigUzkxPg0tJeN1YNJqbm2swGOh0eklJydp16yYmJq7Tt1wyTExMKBOVhYWFUqlUrVZXV1er1WrrxARYhiAYDNrt9uzsHCIjX25u7qrVq8Ph8PUM325xdFYURSsqKioqKuIllVVVUNNxlEqlUvlZIlIajfbYN78JZolTWFhYWFgYf5uXn5+Xnw9micPn89euXbt27dp4yT333HOd3wnL1wAAgGQAAACSAQAASAYAAIuJ2yg51d/+9oHJZEYQpLq6qra2BupmPlar9a9/fZt4/cQT31/OiRovyf79n3R2diEIkpubc8H2UMDj8fzpTy8Sr7/+9W3zJ9QXt2SYTObu7m4EQVJTU6CaL8DvDxDGQRAkGo2CQS5gfNxC2EcoFIA1LiAajcYbj9/vh4EJAAA3D5AMAABAMgAAAMkAAAAkAwAAkAwAAEAyAAAAQDIAAADJAAAAJAMAAJAMAABAMhZGLBYLh8M+nw/H8Ys/jUajgUAQagi4An5/4JLx1qPRqMsFocb/KdziY2k4jn/00XatVpuUpIvHs7Tb7WfPNs3Ozmq1mpycHKgk4HIcO3aMQqFotRqf79NEFj6fz2g0jo2N8Xi86upqMNGSkgwSiUQmo8Fg8OjRYxKJeGZmhijv7x8YH7dwudz09DSoIeDKrmpj49mOjo7JyUni/ejo2N69H4dC4Y0b7wTrLLWBCYIgFAq6cuUKm83W3HzO6XQShVNTU9PT0wkJCo1GAzUEXIHS0lIEiRmNPTbbLFEyOzvb3z/AYjHT09PBPktQMkgkUnJyskajviC/S2JiQnZ2Np1OhxoCroBcLk9JSeFw2PMLBQJ+dnbWBXkqgaUjGVQqtba2hsvlzHM9KImJiXp9ElQPsBBHQyqVzW9RUqk0Ly8PLLM0JYMgJydHLBbHk+KJxeKkpCToJYCFkJysT0hQxHPHsdlsrVajUqnAMktZMoRCYV5eHo/HI3qJ9PS0nJxsqBtgIVCp1KKiQqXy01ytKpWyqKgYzLLEJQNBkOLiIrFYhCAIi8XSaDQJCQlQNwiCRCIRv9/v9/vnZ1QMBIJEIQQBJcjIyFAoFCQSiUQiyWQyiB1LEI1GiXYyf39TKBQiCiORyLV97e0SLlij0Wg0Wqt1Mjs7C9ZW4xw5cuT99z+4oPCpp35MvPj+979XUVEOVuLz+RkZGWazmcVi5efnXVWq9CVMa2trPLB4nN/85nfEi6985aGNGzcuYskgkUiVleUWy7hWq4WBaBwcj128uzFeEovFwERE48nISO/p6WWz2QaDgUQigU2+sPHg+DU2ntsoKYFWq62trUlISIC1VeBqSUhIKC0tJpPJkOHln81tJBksFqu4uJhGo0EvAVwtVCo1NzcXQRAyGU5aLhvJIJPJfD4fqmQ+BQUFIpHocp+mpaWCieKAf3EBqakpTzzx+BWc+kUvGcDFKJWJ8eVDALgqJBKJRCK58V07WBYAAJAMAABAMgAAWOaSEYvFMAwzGo0zMzPx7Wg+n29iYiIePmM5g+P47OzsQH+/x+OJF87Ozo6azYFAAOyD4/jgwIDVao3vjg0EAlar1Wq1gnFisZjL5erp6XG5XPFCu90+NjY2vzktPi8jEon8+dVXP967d2ZmBsfxcDjc3d29Z/futrY2qHUcx7u7u//yl780NTVFIpFYLBYIBD7Zv3/fvn2zs7Ngn0gk8v777+/csWN8fBzDsEgkMjw8vGf37vr6ejAOjuMmk+mlF188ffp0OByOxWLBYPDE8eMf791rsVgWq2SQSCQGg/Hd732vuamptaXF4/GMjo6eqquLRqMQhQ1BEAqFkp+fX15evmvnzrGxsWg0eu7cuSOHD9fU1ioUCrAPnU7/6rZtY2NjjQ0NTqdzcnLyzOnT09PT69evB+OgKJqSknL3Pfd88P77IyMjGIZ1dnYeO3o0KytLr9cv7rmMzMzMBx58sK21zWg0frJ/fywW23rvvRwOB2odQRChUFhVXV1cXPzu2+84HI7f/OpXj33rW6mpqXCSgoB4KizjluamplN1dWNjY9u+9jXiVDTA4XBKS0s3btr051dedTgcL73wwro77ywoLLyeDda3y/TnipUrpTLZSy+84LDb169fr1Qqob7jyOXy2toVMzMz3/uXf3noy18uKipiMBhgljhlZWUajeZv7/+tu6tr85YtOp0ObBKHz+evW78ew7DvfOtbFZWVFRUV16mnt4tkUKnUNXesoVFpKpU602CAbb+fqyQyWa6Qb9i00TRi2nLXXWw2G/bUXzB8q6iqlEokfD6/qKgoHqsJIMb+PB7voa982Wwyr1ixQiKRXGfjuY2eTDabTUbJVCoVjqVdclzK4XCwaJTNZoOeXgyTyaRQKSiKgv91yS6Hz+dj0SiLxbp+PYXGBwDA4pQMKpUqEAiYLCbUyiU7CiaDIb5ur3IJj014PB6bDVPml4ZGo4mlEvKNGLLdRsfSeDzePVu3ymHt8DKPhFan+/4Tj8Oo5JJwOJx169fTYEh7mf5GKpU+/sQTNyQE9+0VL6OmthYq+JKgKKpQKO697z4wxSVhMpklpaVgh8tJBp/Pv1GNB7osAABAMgAAAMkAAAAkAwCAxcRtNP0ZDAaJiOlUKjWeLw8gwDAsGPw0gQ2TyYR1kwsIhUJEIigKhQJbAS8Ax/F4qAQGg3Gdu7luI8l49tnnuruNCIJs3XrP/ffD0sDnMJvNP//5M8TrF154XigUgk3m89Zbb9fVnUIQpLa25jvf+TYYZD4ul+vxx39AvP7FL55OSUlZIpKB4zEcxxHI6HMpYjGEMA5w5cYDVrqco/GPhnS9Dxf4twAAgGQAAACSAQAASAYAACAZAACAZAAAAIBkAAAAkgEAAEgGAAAgGQAAgGQAAACSAQAAQAETAIuX9957j8fj5+bmRiIRoiQYDA0ODvX0GHE8dt999y5n4wwPD58+fSY9PU2lUscLfT5/S0trX19fdnZ2QUE+SAawvJDLFSdOnKirO+VyuYiSnp4ei2WcyWTdddfmZW4cNptNoVA/+ODvdPpn6aDeeuttHMcLCvLEYhEMTIBlR25uDo7jExMTXq/3H72ob3Z2js/nZWZmLnPjCIXC5GS91+u1WCzxwqmpKZfLlZCQIJVKQTKAZYdYLM7KyuLzP5eXmM/nZ2dnc7ncZW4cOp2uUqkMBsMF5ZmZGTqd7ppjl4FkAIsYFEVLS0vmd5goiioU8pycbDAOiUQSiYQFBYUXSUamQqG45liQIBnA4kar1Wo0GtY/8nLyeNzkZL0Ccu4hCIIgTCYzJSU5KUkXL1GpVElJSdeTiRIkA1j07ndOTrZcLifeyuXy7OwcCgXm9T/1ucRiUUVFebykpKQoMTGBQrn2iMEgGcCiJyMjQ6VSUSgUBoOuVquTk/VgkzgMBiMzM5OY2eHzeRkZmTwe73q+8BaLMY7jw8PDOB5DEMTn8xGFs7Nz/f0DCIKwWCyNRr2c69tut8/M2BAEmZiYiBcOD58nWkBiYsJ1Vv/SQCAQ6PX6wcEhNpuVkZHOYDDAJp894RRKQkJCXl5uY+PZnJwchUJBpVIXsWSEw+Ff/vJX8X04BKdOnTp16hSCIFlZhv/4j58t5/puaGh87733Lyj8wx/+SLx44onHKysr4KlAECQnJ3tkZIROp8Pa6sXQaLQVK2qNRmNBQT6Hw75eDQKDAksAmUyWkZFBoaCQ4eViqFSqwWAoKSnJyspisVggGQCAUCiUmppqsMPlIJFIX/7yQzckj9wtlgw6nf7CC89fLh0LzHuvXXvHFZ6E6+8xltIjAa3lytyoKR7KLa9pmMC7sqRChtGFtyUwwk0wDiyyAgAAkgEAwD+HGzwwcTgcw8PDVCpVo9GIRAs9XTswMLBv78dOp4N4KxAKKyorKysrl0kdOByOHTt2xd9u3rxJoZDH3zqdznPNzafq6uIlGZmGTZs3CQSCZWKfs2fPGo29xOuEBMWmTRvnfzoyMnLo4EHrP/atcLjcwqKitWvXLj07TE5OWa1WOp2uUikXWPter7ejo+PQgQPxkkSlcvPmzWqN5naRDBzHp6en29s7EhMTk5OTk5P1UqmUTqdfeShFp9OlMimDQccwrLmpmcmaKiktXT6y7fP5jh07Fn9bXV01XzJQFOVyuQqFIhZDAoHA9o8+VCQkLKv85oODQ3H7ZGZmXiAZNBpNIpbgGIZhuNHYPTw8nJOTszRHBGTS0NDQyMiIWq3W6XRarUYmkzMY9CveQmaz2cSJm2g0unv37pWrVmHX13husGRwuVyVSn3o0JG+vn6jsSctLVWtVqvVKqVSyefzL7ftTKfT6XQ6BEHMZjOG40KhcKnW+rWZtLyioryiIhQKdXR09Pb1rlq9msPhgGUIVCrVA196EEEQ68QEi83y+nylZWVL8pdKJBKBQGC1WgcGBmUyaVKSXq1WpaenyeVyLpd7yZOpLBaroKCgoKAgFosZu7tHRkbWrlsXP49zaySjt7c3Ht0k7kizWMzZ2djU1NTU1BSDwdDptGlpaTqdLjExQSwWs1isS/48n8934tgxEolUVFS0NDbk+Hy+06fPLGRg8oXXYBg2NTm5/cMP165dm6TT0Wi0pfEYjI6OfqGJJiasX/g9gUCgsaHRbrfXrlghkUiWjEw0NTXNXxy12+1MJnNuzm6xTFgsEzQaLTc3JykpSa1WEw/XJT16HMddLtff3n+/oLAwLS2NyWTeSsnYt2//lS8IBoP9/QP9/QNisSgrK6u4uCg9Pf2SC6s9PT1dXd0VlRWpaWlLo75nZ+deeunlG/JVHo+n8exZs8n805/9jL6EzlA0NTU3NTVf//cMDQ11dHQoVcq8vLyl5Fm88cabV/g0HA63tLS2tLSKxeLi4qKiokK9Xs9msy++rKG+vr+//xuPPnr9U2A3aV8GnU6PxWIWi0UgEMhk8oslw+v1Hj58OC8/r7qmBo4VXUAkEhkbHa2rq/t/Tz0pEAiuOTjKUsXv958+dUqeoLhzw4br7EIXIwwGg0wmj46a2WyWRCK5QDIwDJuZmfnggw8e/8EP1Gr19W94u8b7RSJRMBi8XPv2eDzEhk4SicRg0Gk0empqSkFBQU5O9iUjDuI4Xl9fHwgEsrKzExMTl0AVisXihV+PYZjT6bzcp7FYbGZmprm5WSqRlJeXL4EmLhAIAoHAVY3vLtfYiMbT2to6Z7dXlJcTM2KLGhqNdoXGEwwG/X4/8XChKEqn0xgMZnp6WlVVZWpqKofDuaA7icViLper7uRJvkBQXl5+Q/T0WiSDQqH87//+7pIfRaPRgYGB55573ufzk8lkgYBfXV1dUVGRkHClI7d2u/3vH3ywYcMGrVZLNCYURalU6iLdz7dy5YqVK1cs/HqLxfLkkz++3KehUKjHaKyvr3/yqafiTxqNRiOTyYvUPj/72U+v6vq3337nwIGDl/vU5XJ9vHdvampqVlY2YR8ymUyj0RapcfLycl944fnLdR4HDx7au/djt9tNp9MVCnlFRXlZWZlUKr3cj41EIiMjI7t27nzmv/4rhuOEfahUKoqi12yfGzww8fl8JpM5EomWl5eVlZVmZ2cvpHE3NzUNDw79/Ew9in4aLGjzXVue/PGPr6qvXqpMT0+3nDtXf+p0c+PZuBlf/vOrJaWlMIJDEKSzo6O/t2/vrt3P/uGPhHXKyst//bvfymSyJfZL7Xb7+Pg4hmEVFRWrVq3UajUMBiP+yFwSp9PZ1NjY3dn15QcejDeeX/zyv+/csOHiKY8FQrrckbBrw+l0jo2N8fkCkUhIp9MX6CkEAgG3y4VhWLyEyWLxeLwrm2PJEI1G5w9MLliNjkajPp/P9/llKdFl5saXJF6vLxj81L2iUql8Pv8CX93jds8PuUKj04VC4dJrPFNTU7OzsywWSyqVMhgMCoXyhQ0AwzC/3+9xu+cX8gUCJpN5zTNiN1gyotFoJBKh0WjL5GkHgJtGJBLBMIxCodzaM7s3WDIAAFjawHIdAAAgGQAAgGQAAACSAQAASAYAACAZAAAAIBkAAIBkAAAAkgEAAEgGAAAgGQAAgGQAAACAZAAAAJIBAABIBgAAIBkAAIBkAAAAkgEAAACSAQAASAYAACAZAACAZAAAAJIBAABIBgAAAEgGAAAgGQAAgGQAAACSAQAASAYAAEuUq8g673K5jEZjwO+vrKpiMpkkEgnMBwAgGZfFZDL94umnXQ7n9t27lEolSAYAgGRcCZ/XOzJ8XiwWg9WumWAw6HA4gsEgi8Xi8/kMBgNsAiyEaDTq9XpdLheGYVwOh8fn0+n0210yCGKxmM/nczgcKIrSaDQ6nY6iKNToQsBxvKOjY+eOHSMjIwUFBfds3ZqVlQVmwTAsFAqFQ6EYgtBoNGLMCz7sBUxOTp6qqzvwyQGX07ly9ap7tm5NTk5eHJLh8/le/NMLg4MDQpFo5cqVW+66KzExESp4Ibjd7heee371HWt+8tOf+ny+WCwGNonFYqOjo5988snJEyeikUh1Tc0jjz4qEonAMhewY/v2SCTys//8D7FYPDs7y+PxFsHAhCAUCh09fDhRpezu6Ozu6Ozt6fn2d76TnZMDlboQ02E4RqPSGAyGQCAAgyAI0tzc/Obrr5+uOxWNRmOxmNPhfOTRR8EsF+NyuRgMBpVKlUgkYrH4FnbS6DPPPLPAS8fHxnbv3MXj837z+99/69vfLiktbW9v7+npSUlN0Scn02g0qNcrw2AwSCTS/o/3GY3dYolEIpEs8zGd3+/ftXPn3t17snOyf/HLX373e99bd+edarUaBiYXw2QyOzo6jhw+bLfb5XI5n89fNF4GhUI1GAxqtVoqlfK43LHRUY/HE4lEoFIXYDrK2rVrNVqtsbv78KHDthnb2nVrl7NBfD6fw+4IBAIyuaKsrIzBYGAYBlNjlyQnJ0chlw8MDracO/fXN97YvGVLXn7+LflPrnorFwlBKBQKgiA2m41QCgadQaVSoVIXgkAoLCgoWLduHRKLnT51am5ubjlbg0ajUakUBEGCwYDT6cRxPBgMQiO5JCwWS6vTVVZW3rF2bSyG7Nq5a9EMTHAct1one3qM+z/+uK+vNy8vf+PmTVqdjkxe1htJo9Go2Ww+d66lubn5/PkRh8M5OWk1m0cFAkF8MWx4eNhisTCZTIRE6urqHDWbuVwuGUVjOP7mG28YDAYqlbqsHHIURT0ej2XcMmo2m0ymHqPRaDSWlZUtt8bjdDqHhoYaGhpbWlqmp6dtNpvZPOpyueVyGXGB2+3u6uyMRiJisTgUCo2OjjodDpRCCYVCPB7vT889p0tKYjKZN+cZvIqBiVKl+to3vjHQ3280djfW10tlssqqqs1btmQaDITfsZyxWq0nT9ZNT8+QSAiO4729vSQSWaNRJyUl8XjcuKwMDw+fPH4iGAqiKLpq9Wocx/fv36/TagOBwDJ0yKlUall5eTAQPHr0yODg4MjIyDLUi2g02t7e3tXVHQgESSSSxWIJhUI8Ht9gyMzJyY5fNjU11dLSEgwGo5GoUCy6Y+3aGI7v27cvOzvb6/ORyeSb1tlcjWQold/6zrf7+/utVqtlbEyfnJKSmpKamsrhcMBvbG/vsFgsqamper0+EAg4HI5YLKbX61ks5nwDBgIB+9wcjU7Lzs7Oys6enp5uaGgY7O//4Y9+xGQyl6HdFArF2vXrkvRJZrM5FArl5OYuNwv4/f6enl6/P1BSUiwSCW22WYfDIRKJNBrN/FFJWnp6OBweHxsTi8X5Bflp6eket7uuru7dt9/5yU9/IhQKb5qbfxWSQaVSExISEhISQCAu6WXQ6fTs7Kycy683c7ncgoKCgoKCeInNZiOTycFg8Fbt5LsdEIlEpWVlpcvPvyAIBAJ+v1+pTCwoyL/c1moKhZKenp6enj6/0Ov1UqnUgN9PZzBu5ngWTrLeGORyeSAQ9Hp9C7/F7XabTSYyibT+zjs/3rs3EAjA5q5lCJVKRVE0EAgEAoGr8k1MJpPb5frq17bt3bPH4XDgOA6ScfsSi8Wi0ajP5/P5fJFINBaLKRRyv9/v8XgW/iW2mRkcx7/57W/X1NSMj4+73W6QjGXSeMLhsMvl8vv9OI5zuVw6ne50Ol0u18K/xOl02mZmvvPd727ctGnCYnE6nRiG3XYDEyBOJBKxWq0jIyMIgiQmKsVikdvtQVHyVU0DJ6ekJKekEK9/89vfglWXAziOBwKBkRHT+fPnRSJRUpKOxWJFItGr/Z7ExMS77r6beP2HZ5+9mT8BJOPq+of4zMXzz7/gcNgRhITjuFarmZmxJSfrlcpEsBJwhcYTDAabm5tfe+0NOp2O4ziLxZRKpQ6Ho7KyUqlULoofApJxFWAYFovFcByfnp4JhYJPPvlvPB5/YGBgaGgoMzOzsLBQq9WAlYDL+RcYhgUCgeHh81lZhm984xszM9MjIyMul7uqqio3N+cW7gEHyfhnMT4+Pj09w+NxBwYGUZSi1WoZDIZUKikvLyOTycQ8FlgJuJhoNDowMNDX15efn9/a2rZ+/TqxWCyVStLT02OxGIqiFAplseziA8m4ilo/f37k3LlzAoFgbGwsMzODiOxAp9OX8xIpsBDsdkd3t7G9vSMYDOE4lpysp1BQFEUX40kLkIyF4nA4LBbL4OAQhUIRCPhVVVXLfI88sHAsFktnZ9fk5GQoFEpPT09OTl68jQckY6EMDQ0NDAwQ56bIZHJnZyeTyUhJSYFj2sCVcbvdZrPZarVGIpHZ2VkKhdLZ2anX66VS6WIcyUI/uSC8Xu/IiMlqnSTe4jgeCoWi0ShYBvhCJiYmhoeHw+FwvPF4PF4cX6y7cMDLWBDj4+Pj4xYKBVWpkpRKpUqlTE1NTUyEJVXgC4hEIiaT2WQycbncpCSdUqlUq9UpKckCgWCRjk1AMhaE3e6QSMTEyVSdTieTSeHwLrAQPB4vgiCZmZmJiYmZmRlKpXKxx3AkwSblhTA8PIwgJKUycXmeNwWumbm5ObfbzeFwhELh0uhmQDIAALgKYPoTQRAkHA7bbLapqSniOCCGYdYJq8vlummnA4FFCrEIMjk5STQVHMetViuRoAgkYyljs9k+/PvfX3rxRY/Hg+O43W7/za9/3dDQAKEogSszOzu7Y/v25559ljiI7HG7f//b3505c+aqTrKDZCw+lEplQUEhFsUOHjjg8XhOnjzp9rhLSkogASJwZRJ46qmqAAAgAElEQVQSEgoLC8kk8v59+3w+37Hjxx1OR2FhIYvFWqo/Gab9PyUrO2t4aOi9d94NhUKvvvzKy39+VSAQwDYt4AtJz8jIy8t78403UBT9v9/9/tXXX7u1qYlAMi7N7t17Tpw4cc23P/PM00KhcH4Jl8utqa2xTlrff/fd7/zLv2RkZKAoCpKxJKmrO7Vz585ru/ff//2ncrl8fgmHw6moqhy3jL/257989/HvL/lI8YtVMrxe78yM7Zpvv3h2ikwmU2k0lEx2OBwYjkHytyVMIBC45sYTjV6i5dCoVAqF4rDbMQxb8pklYC7jMw1qa201Go1ffvjhs42N58+fX8KT3sANxOfzdXR0tJw79/VHH2lsaBgeHl7aJwmWwlyGXC7fuvWeq7rlgkQKGIYN9Pf39PRU19SsWr06HA6/9pe//OSnP+XxeDA2WcJIJJL777/vqm4RCgUXtJyhoaH29vbKquqNmzaGQqE333jjyaeeuplZAkAyrhoej7diRe31fMPc3Nzg0BCdTt+8ZYtYLN6wceOfnn++x2gsLCqCRZMlDIfDuc6W43A4hgYHyWTy3ffcLZPJttx117N//GNPT09xcfFSXTSBFRMEQRAURfV6fWpKKpGlJS0t7cEvfYnNZoOLAXzBwJ5M1ul0Go2WiNyZkpLy4IMPLm3nFCQDQRBELBbPzzpDp9PvuOMOMAvwhYhEIlFp6WePE4Wyes2aJa6SUOsAAIBkAAAAkgEAwK0G5jI+IxqNEufQSCQSm80GgwBX23IIWCzWEg4lDZLxGa2tbc899zyCIHw+/+WXXwSDAAvEaDT+7nf/G3/74ot/uuA4AkjGUiVGBByCsEPAVbabZdRmYC4DAACQDAAAQDIAALjlwFzGTWViYqKhoWHCYklKSiouKSF2GQPAF+L1evv6+lrOnfN5vVk5OUVFRTKZDCRjiRMMBvfs2u3xuMUSCYIgfr8fbAIskLNnz54fHo7hOIvFDgYC8dxrIBlLGZ/PV3/mzLr167fedy+GYbAuAyyc1pYWEol09z33JCYmer1eLpd7q/4TmMu4ifJMoeiSdBMTE11dXRiGLfasWcDNRCaThUKhrq6uCYuFy+VeEPAFJGNpwufzt953n9fr/WTf/ob6BqvVCjYBFsjqNWsSEhLONTd/vG9fy7lzDocDBibLguLi4tTU1Obm5lN1dbaZmW1f/xoEGQUWglar/ea3vjU6Onrgk0/27NnjdDrv2boVvIxbQyAQ8Hq9oVAIxz+bXMBxPBgMut3uBcZxjMVioVDI5XLZ7Xan0+n1en0+n8fjmR9ANBQKBQIBNptdXV0tEYu7urqsVqvdbscwDMdxt9sdDAYhP9sigmgkPp/vgkYSjUb9fn8wGFxg+FgMw/x+v8PhnJuzu1wun8/n9Xrnz45jGObz+cLhsEajufuee7QazaGDB4n2GYvFotGo3W6/aQFHwctA6uvrR0ZMOTk5Xq833hRmZ+e6urq6uroefPABlUr1hV8SCoXa2trr6urGx8eFQqFOp2MwGD6f795775XJpMQ1ra2tTqfTYDCEQiF/IKDVaU0m064dO5788Y+FQuEbr7+eX1BQWlq6hLPmLDFcLldra+vMjI1CQeeXj4+Pj46O8vn83NxciUTyhZ3N5ORkc/O5pqZmh8Oh02nValU4HBGJhFv/4UfMzc3VnTyp1emysrKmp6ZQCiW/sLCxsbGrs/P7jz8+Njr6xz/+8cknn9RotSAZN4O0tLTBwaGXX34lvoTh8XieeurHGIbdddeWBc4zdXR07tu3n8vlVFVVut3u4eHhQCBYXV01/5qkpKS6kyf/9Yc/DIZC6zds2Lx5c2JiIglB/vNnP3vksceIYQtkll9ECAQCKpV29myT3W6fX/7ss8/HYrEf/eiHC5nhjkQiR48e6+426vX6/Py88+fPnzvXKpVKkpOT49fweDwen//OW291tLfL5PKt99675o47EATpMRoPHDjw83//2St/+YtcoQAv4yaRmJioUqlQ9FwwGJrvNSAIkpeXu0DJaGtr4/F4a9euycjIwHE8EonEYjEGgzE/2rBMJtu8ZcuqVatjSIzFYrFYLBRFs7Kz16xd+9abbz773HMsFguijS4iSCRScrI+Jyf7+PETF6hAeXmZQqFAUXQhrsrs7JzBkLl+/TqhUBiJRDAMQ1F0fsuh0+m1tbXFRUWhcBhFUTabTXQtGzdu/OlPfvKzn/+nIctw0ybFQDIQCoWSkpKSkZHZ0dExv7yyskIqlS6k1hEEEQqFHo+HTCZfIdAGiqIcDucCDeLxeAaD4VRdHY/Ph7pYdEgkEp1Ox2QyAoHPZfwuKysTiUQL6QBwHMdxDEVROp1+ucZDIpGYTObFHiiHy6XR6cUlJUwm86Z1NjD9iSAIolarU1KSLyisrKxceLevUMjdbo/T6brqCiCTWSyWSCiCWliM0Gi0pCRddnbO/MKUlGS1WrXAbl8gEDCZTKfT6XJddeNBUVQsEjMYjJvpnIJkIAiCsNmspKSkpCRdvCZSUpKTknRUKvVyPYPf7x8cHBocHLLbHRiG0en0SCQSiUSuodYTExMf+vKXoRYWI2QyWSaTZ2RkzC+sqqoUCASXC8yFYZjNZuvt7bVYLH6/n0qloijq9/sDgcDV/nUOh7Pta9v4fP7NDAIGA5NPK16lUmZlZZlMZgRBqFRqVVUVh8O5XE04nc6jR4+bTCPEyEKhUIyMmJhMxjVs6CSTyXw+v6CwAGphMfc3Wr0+aWTERHgNWVnZl8uYFQ6Hx8bGDh485HK5WSwWl8sRiUQWy4RKlcjj8a72T9Pp9KLi4pv9sECV/8M/FKakpEgkYjKZLBKJiooKKRTKxc4FhmFErdfXn+FyuXK5IhAIDA4OBQKBvLw8tVoFllxuoCiqUCiKi4uJ16WlJWKx6OIpMKLxBIPB7u7uoaEhnU7LZDJsNtvAwIBEIs7Ly7tVJ1PBy7jmQSlVqVRmZWW1tLTm5+dJpdKLr3E4HD6fj0KhmM2jOI7fe+9WHo83NTU9MzNDpVJVKpVYDFMSyxEOh5ueniaRiEOhUE1N9cWzGDiOz83Nzc7O8nj8np5eg8HwwAP3u1yumRmbx+Pm8/lKpXKxrK+DZHyGWCzKyckeHx+/YD9FvNZNJtPQ0JBYLDGbzSKRWKFQIAii1yfp9UlgveUMlUqRyWRFRUUzMzNKpfJiF8Pv9xuNxu5uY1FRkdk8WltbQyaTpVLpJXsmkIxFA5PJTE5OLikpvmTkm0AgMDo61tzcwmazAwH/ihUrwGLAPEeDU15e5vP56XT6xesXU1NTHR2dAwODoVCYz+elpaUt3qwFIBmfQyaTbdy48ZLLYxbLhMlknpqaQhBEqVRmZGT4/f6buR4O3M4wGIz09PRwOHxxe4hGoxbLxODgkMvl6unpycvLZTAY0WiUSqUuxsYD05+fNweZfEm9wHF8cHBwaGiIeDs3N/fhhx+1trZBlBwgDolEuqSLMTc3ZzKZnE4ngiChUMho7NmzZ6/FYrlpB8lAMm4BdrvdYrG43W4EQSgUilQqycnJSktLAw8D+EJMJvPg4GDcGcnMzEhNTZXL5QvcWAwDk0XJ4ODg+LhFJBLl5+eWlpZqNBoWi3W5jV4AECcQCJpMpqmpab0+qbS0JD+/QCqVUqmUi5fwQTKWFHQ6Y9OmjSqVSiDgM5nMRToKBW4+Xq8nNTUlNTVFqVRyuVwGg3nBSXmQjKVJenoaiURiMJgoCkM54Crg8/mZmZkoitJotKWR2xkkY0HcwuiswKKGRqMtsViN0Gci0Wi0oaFh544dk5OTREkkEmlpadm/b188ThcAXJLz588fPnSot6eHeIvj+NjY2MsvvTQ5OblUYzKCZCAkEikWiw0MDBw/ftzr9UYiEbPZ/OEHH8QQBCYsgCuDksnj4+OHDh2yWq04jrtcrvffe8/n8y3hnwySgaAompOTk5eXN2o2t7W12e32fR9/zOFyKyoqIKwecGWUKlVOTo7P5zty5IjL5Wpqapq12TZv2SKRSJbGzMXFwFwGgiAIj8crKi72+/0njh+ftFonJiYef+KJK4Q8AAACKpWaaTB4vN4jhw8z6PTent77HnhAr9cv4QV4eCQ+RS6X5+bmBQOBv3/wwf3336/T6RbpThvgJsPlcgsKCnJzc19/7TWJVFpaWrq0c9OAZHxGQmJCYVFxwB8or6gAawALRyQSZWVl+b2+OzfcueQ9U5AMAABAMq4VEgkhwyoJcE1Nh0ReFi0HJOMzUBTl8/kJykQwBXC10Gk0lVq9HJbYYMXkMxgMRnVNTWFREZgCuFqSU1L+9OKL1xAvGiRjMXtcZPIlE8wAwBdCpVK/MP0qDEwAAFh+PSuYAAAAkAwAAEAyAAC41cD0JwBcL7Ozsx0dHfG3NTU1dDodJGPpY7fbiRjiVCq1sLAQDAIskPFxy+uvvxl/W1RUBJKxLBgaGnr22ecRBOHz+a+88hIYBAAuBuYyAAAAyQAAACQDAACQDAAAQDIAAADJAAAAAMkAAAAkAwAAkAwAAP7/9s48uI3rvuPv7S4WxH0SIAACBEiRBEmJoiRKtg7SsnxISeyoY0eN26Q5ZpqJ7SaZTtp0pp1pk0kbp50kk0yuTmeaNHWsyIljO3EcyZRiKaRI8RAtnuYNkABBAMRFgLiv3f4BiaElStVlwlj+PrN/kG85b5fvfd/3/d7u2/fAMu6MfD5/s33rWJZNpdIsy95pntlsLpfLbXgql8vdRYbAB5NsNpvL5TdUTjqdhoq+TUpswng4HPZ4vEKhMJFIrJNCxulcDAQCBoOhvFx9p7siejyeSCQil8vX8mRZNhqNBoNBv99vtVolEgkIhQPMzy+k0ym1Wp1OpwspDJOPRCLLy8uh0EpLS0tZGR9KiWuWkUqlOjs7GYb1er1riSsr4dOnz3g87ueee/Yu8vT7fQMDlwmCyGavxhqZTKa7u2dubpZhWIOhEiyDGzidzvHxcblcvrKyUkiJxeKdnV2Tk5MKhbypqREsg4MDE4PBoFaXT0xM2O32tcRIJNLX16dUqrRa7V1sPGOxWIRC4cWL3T09PWvG9OKLP+/vH2ht3SOXy0Al3KCxsQEhdPbsuYGBy4WUUCh06tTLMzOz+/fvLysrgyLioGUghLZvb9LpKq5LlEjER48+dncZKpVKi8Vy41qvarXabDaDkjiDXq83Go1iseg9YTZFWSzm+vp6Du+iutUto7Z2m8lkWt+SKYrSaDRWqxXf7a5F1dXVTU2N1yW2t7fLZLCTM6fYsWN7bW3t+hQ+n9/W1kYQsP8udy2Dx+NZrfWGdRsUKRSKhx9++F7y1Go11dUWofBP2xFgjPft2ycQQIjBKcxms8FgWJ9C0/Teva0kCR0Ddy0DY9zQ0GAymdaNSiQ7d+68lzwpiqqqMm/fvmNNRo8//qhKpYQQg2MU+hurtX5NOYcPt8PONXfWWErxpiUSSXW1ZXJyyuv1qlSqvXv3iETCe7ShioqK+vq6gYGBgrD27t1L0zSG/Vm5Bca4pqamrq5uamq6IKSDBw/dSy13dV08ffp0Mplcn/jCC98kSfJzn/vrmpoaiDI+GDdNEPX19bW12xBCKpWqpaXl3sMBoVBQU1Pd1NTI4/EsFnN1dTWEGJxELBabzWa9Xi8SierqarVazb3ktrq66nA4fT7/+kSXa8nhcCaTKRiYfIDQaDRms1mv19XUVOt0uvtiQxqNpqmpSSgUPvDAPoFAACEGJyFJ0mistFrrlUrlAw/soyhY/nYLDEwQQnw+v7rakskcqqqqul+rOYvF4rq6usXFxV27doEyOIxarW5sbGRZ9rq3J8BtDe5Kd2p9LBaLx+MCgUAqld6vPKPRqMvlamhoAGVwm0Ag4PcHGhqs95jPzMzM6OjYhqfa29s0Gg1YBgAAWxp4wgcAwB1QAs8y8rmca9GZy2aKextiqUyuUHJ4FyzuwbJsPB73ez0Mky9mt0ySMrlCqVKDZWwSiUTix9//npLPFPEFRjqb27aj9dAjR41GIzTFUiGfz09NTna8+hLJ5ojivf9K5nHLg+3Hnz4BlrFJpNLp13/75ql//YxIQBfrHibnPfHEymokgsAySirKcLvdajrdWq8TCYoWHv6iY3BoZBwsY1PBCFXpy6Wion3xsRrPLOVgSFKSqBXSKn25VFS0WeEKqTgCzzKKYBqYKObDWkwgBDO7ShOMESaL+qSfU8opnalcmERF/EIZEwgmg5aqZRDFFg9YRtEqnoBaB+4yRMUQZWwxy8AEUcyOgoAoo4QHJkUWD+bU7KfSiTIIEhez1kl4llGylkEWWzwQZRSn2Is5HMWYhCijZC2DwEV/EAaWUZwoA9+01pPpzOj0QkNNpVgoWJu0MzbrIDCuMenKaB5CKM8wwXC0+8rkR4/sS6UzHd3DK6sxhJBBq7RaDLpyRRlN32pgAlFGyTrGrcXDsOzlsdltVTq5REQSBEIolck63b4cw9SbDWspv7tw+ciDO+RSUdfld53uQDafl4gEVTp1jamiXCG79cCIS+VZOv5XGI5udORY5PKt/PT1CxP2pTyL1tL/ODh58vfdIzPOdI4p/JlzOfSjU2/lGHYlmvzp6xf6RufmFn2jM86zl0Z7hmaiyczNLgFvTEpb5DcXD4OJUDTxk9fOD00tJLP5QmI8nb04NP1KR++Mw1tISWZy33/p9JI/nGfxrzr6zvWNTy14pxc870zOXxqZnVpw5xG+lXggyijSiHTjok8m01Pz7lmH943zlxtrzRSPLrTuwEpscNwmFgkoHtVcb2ERkcrkguEYi4lMnmFZ9JmnHn1gZ92cw/3G+YG3uodpPt3W2nTz2BIso0TDDHwL8WSzuUn7kt3lO9M1VFdtFAmFGKM8gzyByKWhmYpypVIp06rkDMKBcDSdzbOYiMSSR9t2HX/kgXyembK7xqbn3b6QSCQ06sq3wrOM0vG/wnuyGw4G4WAkPjq98MiB5nOXRj3+cJ5hr53FdRYDSZIdF4ecngDzp1Hl1ZABY8zj8Rq2VX3y+JFKnbqjeyidzW94FYwxOEYpW8bG4mEREU9mOi+PH23bNThuc7oDmVz+WkSJZRIRQvhC31gsmbmqHIzxVQlhhAmVQnZwT9OjB3cjTJy7NHKzq3CssyFKp94JjMkbj0yWsTm9/SOzn/joIwd2W99515ZIZa+eRVhbrmzf11yuknd0X/GHoizCCGG8NrK9lkllhUarVrl9K75QdMOrIIIEzyhZxyAwsbF4cgzr8gbfvDB44kMPte/bPuvwhFeT187iWrNhb7N1ZsE9MDKTy7EIoatiQHi9GlUKuaCs7EzXlQ0vwb0H56VjGRR144FIKhJPuv2h1uZauVz2xCMHzveNhONJRJKYohCBMSZqLcbH2/eSJPXz356PJlIIIUySmCARxpgkCvkwBMFiTJAkyaM2vFDh76H5labGSUxuLJ5kJje9sHRgd4NUKnmsrXV40u4JhlmCxCSJMEFSVJO1+vD+Xad+3znjdBc6G0SSGGNMEJgkC/kQFI/m0zTN21g5FIUJeJZRNHe7vujzeWZ23vOzX591+1Z++WYXi1iWYfuGp+VSmVwqQggjhBEizZWGxw7h/3nl9Euvv40QQohEiFyf58Kid8kbsBgqDFrtza8Oy5eVapyxoXgYhl3yhv775TNOj7+j6wqLWJZlG+uqK3VahArTcHAZX9DSWBcMR7/xw19ckwG57gcCIeTxrURWE8888fDNO2CYl1EMWEywNzx5DkZX7UvepjrLL//z64WUc10Dix5fJJ6QySQIYRZjlsCIIIzGio8ff+wHP3sVIcQSBEtghDCLiXSeGXl37uRvzjEM++wnP4oIYkNjYAmMMFhGqY5MNhTPajI+vbCkUspO/vCrhZSLAyMLLo8vFClXyRHGCGNEEBKp+KH9u6OJ9Dd/dLKgJfaqrghPIDw4OjU8MatSyA8f2MPe5M0IC5ZRpH6CRMT1d+vyBpeD4SceaytXqQop7fv3vPCD/3X7wxUVWrlMwuNRPLoMERSPJmtrqr742RMKeQdJ0WUCAUEQ//LtnwgEfOu2qgN7dzY3bKs26W68xLUbgD07S5VgJJpn8Y01GwhHJ23OE08+uiae/a07B0ennZ6ASqVUyKWpdAYRFIGQXC7/0JEDvmBYLpNhkipXyX/+2tmX3zivVSt2NNQ8dKC1qdYilkhuOnTFBJci1BJYLnglFPrUXz7zrX961mLSU+R7mu5qLL4SiSpkEum17byzuZzdsaTVqKRikXvZT2CsUSkpikQIsYjNZnMeX9Co12azuWm7M5lKI4RkEpFGpZCIhbybb2lx5sKlBCF5sP3R9Rs7Ah9w8vn8+NjYmV+/+OmPHdOoFNedTSRTy4GQXCZRSCWFlFw+73B5ZRKRRCIKhiIMw1Tqri4RnmcYX2BFLhPzadruWAqvxvIMU0bz5DKJSiETC2+6GEcskXz5jbcZgfq5L3wRoozNukWK2rFje2g1bmIR9d5pv1Kp9LodCXg0WV9bXfi5Uq+7LlKh+VSV0YAQ4pNUc2Pd7d+DLxjhKyUikQjaYUmNSLBCqZyxu9KFOVrvRSgSWd5boRRB1liudgl63XvWcyIJUldx1T62VVfd/j1EYglemUBaXg4Dk028RR5vx86WRY+/yVrLL8aXArF40h9aNaopsVgM7bC0LEOpVIajiZXVREUF4lFFEI8vFOELxEYOBacl8PqHR1Hbm1vOdvZHYgkW33Tm7/t3LHp8vDKRRlsBy4uXnGWIxeKGxsb5RU8skdp85eRZPGt3ZVnSVGWGKGPzICnKbLEkM6xjaVmlVArKNrXdZrLZy8MT5brK2ro6aISlyLEPf+S3vz5VbTHKZDJyc6dI+IIhTyCit1So1GrOlGcJRBkYY5FIdOLjf97Ze2VpOZBHGBHUph02h9vh9ldUmnR6PTS/UmR3a2s8zUzbnJFYYjOVk8oxXX1XSL7I2tBA0zRYxma7Rvvhh+cc3itjUyur8U0bnkQTybe7+qqq6+rq67lU61uKQn8z5/BMzTlS2dzmKIdBeNbufGdkSqM31tVbuVSeJWMZKpXq2eefm5xbHJ2YjafS73eVswSZSGU6ewbti8tNzS2VlbB9SQlz8FAbQYt6BkZmbI5Mnnnf/QITS8v+jvM9La372trbhEIhWEZxeHD/gZr6hs5Lg8NjU6lM7v2LNVhMZLL57v53fvyTk8efPtG8cydJwlSuEobP53/+uee8wdXX3zxnd7hyDHr/ehoWE4FQ+GcnX03k0J59D3KvsyG/9rWvldDtWhsa5uz2zq5ukiJNRhNJ8fDV9W/uz8FiAiGcymT7B4f/8Z9f+Luv/MPBtjaYjsEBBAJBTU3N+QsXJyamLNUWhUKBMHGfxYMIFqFYIvmd7/9XJJ76q0991trQQBBc2ym9BGZ/rqewMe8fznZ0df6xybrtqeNPymTS+5g/wzKBYOjMW3/41au/+erX/625uVkgEGD4hpUTMAzjdrtf/sXJJefCU3/25N7WXTSPdx/zz+fzTtfSN/79OzXb6p75xCdNJhNFUdwTT4lZRsE1ksnk6MjIq6+8koxHP/PpT2xvauLT96Hu44nEO0PDr73+O72h8vhTT5vNZj6fD37BJfL5fCAQ6O/r7e3pVsqlf/HMCYNOdx+yZRh/INjRce7Fl049/6Uvtbc/pFQqSZLkpHhKzzIKJBKJJZdrZHh4ZHiIZXJPPvGRluZmmn+XLzVCodDo2Hhvb/9KZPWRxx9rbt6p0Wi5WuUQa0SjUZtt7lJ399TExO7dLW2HDtRYLHe3qkUmk3F7PH19A5f6BqrM5v0HDzU1NUmlUu6NR0reMgo9RiQcts/bbbNzS4uLU5OTjx99tL6+3myuEolEBPH/t/ZAMORYcIyNjzudLrFEUrOtttJorK2tve67FYB7pNMpj8drm5vzeNxT706IxaKWlubaulqDXl92G3MFk8mU3++32+f7+wd8Pn9j03a90VhfV2fk6GCEI5ZRIJvNhsNhp8MxOTHJo3nhleC8zV6u0ZiqTDpdhVAoFInEMpms0L3EYtFoNJZOp5eXl4eHhimK0up0UqlUKpUZKiuNRqNMJoOXI1sElmXT6bTf57Pb5/1+XzqdWvZ6A36/yWSq2VYjk0kFAqFYIhaUCQri8Xo9CCG/P+ByuWxzNolEojcYaJovk8vrrdaKioot8pi85C1jLdpMpVJ+v9/tXrLN2XK5XFlZGZ9PMwwTjcZWozGEEEWRCrlMIBBkszkejxcMBuVyuclk0uv1SpVKIBBAK9qy3hGJRHw+n9PhWHK5+PwyHs3DuDCEiUVjcYQQQWBNuZqm6Xw+n0gks9msVqutMldptRUymWxLTfPjiGVcRyQSicViiUQilUz29w+8ff4CQkitVj/z8RMKpRIhpFappDIZTdMcHnMCd0Eul4vH4yuhUCKZTKVSo6NjHR1nEUJCofCLX3iepmmhSCQUCmUy2Zb9RpHi5H8lk8kKgxGE0KJrqfCDWCw+eOgQtArgVu2BotaLJ5fLFyyDoqiWXbugfFBpzf4EAAAsAwAAsAwAAMAyAAAAwDIAAADLAAAALAMAALAMAADAMgAA4CjcnDC+HqdzcXZ2FiEkkUj27dsLVQ7cPj6fb2xsHCFE07y2tjYokC1hGQAA3EcoDv9vwWBwZHjE4Vgo/Mrj8SqNxsOHD0OtA7cmFAqNjY7a7farjYSiDJWVR44cgZLhuGUkk0mn0zE+OsawTDAQdDqdT5/4GFgGcDvKWVxcHB8dY1k2FArZbLanPvY0WMYWGphEo9Genp63Tp/+2y9/2Ww2Q60Dt0k8Hu/r7X3ttdf+/itfsVgsUCBoK7wxyeVys7Ozo8PDBw8dAr8A7kg5dpttcHCwra0N/GILWUYgELjU02O32Y8eOwb1Ddw+oVCot7d3enLqQx/+MJTGVrEMhmGuXLmy7PN97tnPwyLAwAiGdPYAAAE3SURBVB0pZ3R0dGFh4dm/eX5txR2A+5Zhs9lmZmYqKipaWlqgsoHbZ2FhYWpqqry8fM+ePVAaW8UyEonExa6uRDx+7NgxWDccuCPlXOrpCQWDTzz5JCjnOrj8knXebh8eGu7v7e3u7KJ4PISQUqX8j299S6PRwJ5GwC1wLCwMDw11/rGzt+cSj8dDCEmlkm9/97sajQbWl+byS9ZIJLLodIZCobUUmqZbdu2CbROBW7O6urq4uBgMBP7UtVLUrt27y8rKQDkwYRwAgDsAvmQFAAAsAwAAsAwAAMAyAAAAywAAACwDAAAALAMAALAMAADAMgAAAMsAAAAsAwAAsAwAAACwDAAAwDIAAADLAAAALAMAALAMAADAMgAAAMAyAAAAywAAACwDAACwDAAAwDIAAADLAAAA+D/aHwanuWOo3wAAAABJRU5ErkJggg==
An [[Artificial intelligence]] that displays the full range of features associated with [[Intelligence]]
!!__Approaches__
[[Symbolic reasoning]] -- [[Logic]]
!!!''cognitive structures'' built with [[Artificial neural network]]s
[[Integrating symbols into deep learning]]
[[Augmented RNN]]
* [[Neural networks with memory]]
** [[Neural Turing machine]]
!!!Other approaches
[[Program induction]]
[[Universal AI]] theory
[[Spiking neural network]] -- [[Hybrid neural network]].. -- inspiration from [[Neuroscience]]
!!__Problems__
[[Binding problem]]
See [[Intelligence]] for more.
http://blog.stephenwolfram.com/2016/02/black-hole-tech/
[[EINSTEIN LECTURE SERIES|https://www.youtube.com/playlist?list=PL04QVxpjcnjgWzsghVaOsDJEZQ01UCOkQ]]
[[Warp drive]]
[[Astronomy]]
Gravity waves observed! : [[Observation of Gravitational Waves from a Binary Black Hole Merger|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.116.061102]]
__Notes from David Wallace's talk__
Standard approach at theories:
Start with manifold and geometric objects
There are some absolute objects, and dynamical objects.
Spacetime symmetry group leaves absolute objects invariant. In GR, no absolute objects, so full diffeomorfism groups.
----------
Alternative: G-structured space
Kleinian geometry: substractive construction.
vs Riemann geometry: additive construction
------
Check video of David wallace seminar 11/feb/2016
''Generalized function'', also called ''distribution''.
http://www.damtp.cam.ac.uk/user/dbs26/1BMethods/Distributions.pdf
The are found as limiting cases of functions, where the limit itself is not a function, in the mathematical sense. However, they can be useful
"They’re designed to fulfill an apparently mutually contradictory pair of requirements: they are sufficiently well-behaved that they are infinitely differentiable and thus have a chance to satisfy partial differential equations, yet at the same time they can be arbitrarily singular -- neither smooth, nor differentiable, nor continuous, nor even //finite// -- if interpreted naively as 'ordinary functions'.
One defines distributions as linear maps from the space of //test functions// (smooth functions with compact support) to the Real numbers. One can add distributions, multiply distributions by smooth functions, but in general //there is no way to multiply two distributions together//.
The most important example of a distribution that isn't just a function is the __Dirac delta__
See part III in [[here|http://cs229.stanford.edu/notes/cs229-notes1.pdf]], [[video|https://www.youtube.com/watch?v=nLKOQfKLUks&index=4&list=PLA89DCFA6ADACE599#t=16m40s]]. [[video2|https://www.youtube.com/watch?v=nLKOQfKLUks&index=4&list=PLA89DCFA6ADACE599#t=38m27s]]
A generalization of [[Linear regression]], where $$p(y|x;\theta)=f (y;\theta^T x)$$. This means that the model output has the form $$h_\theta (x)=E [y|x;\theta]=g (\theta^T x)$$, i.e. the model is a function of the linear model, and the errors aren't necessarely Gaussian. Here $$g $$ is called the canonical response function
In GLM, a common family of probability distributions is the [[Exponential family distributions]]
https://www.wikiwand.com/en/Generalized_linear_model
Assumptions:
* $$y|x;\theta \sim \text{ExpFamily}(\eta)$$, for some chosen functions $$a$$ and $$b$$
* Given $$x$$, goal is to output $$E[T(y)|x]$$. Want $$h(x) = E[T(y)|x]$$. Therefore we're really learning a function (and thus this is an example of [[Regression|Regression analysis]]). However, $$y$$ itself can be categorical, so GLM can be applied to [[Classification]].
* ,,(assumption/design choice),, $$\eta = \theta^T x$$.
Note that $$\eta $$ can be a vector (as in the multinomial example below), in which case $$\theta $$ is a matrix.
__Example__:
Min 43 of lect4 (Ng)
Classification with Bernoulli distribution (parametrized by $$\eta $$) ([[Logistic regression]])
Regression with Gaussian distribution (the mean being $$\eta $$) ([[Linear regression]]).
Classification over $$k $$ categories with multinomial distribution (min 52, lec4 (Ng))
An architecture to train generative neural networks, i.e. [[neural networks|Artificial neural network]] which act as [[Generative model]]s, i.e. their inputs are [[Latent variable]]s, and their output is the observed data.
!!__Adversarial networks__
The way the network is trained is by having the generative network produce images, while training a different discriminative network to discriminate between real and generated images. In this way, the discriminative network can be used as a very good cost function, which penalized generated images which are distinguishably different from the real images that the generative network is train to model.
We are in effect learning the cost function
[[video|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=14m30]]
!!__Trining GANs__
[[Trained|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=18m05]] via [[Gradient descent]] and [[Backpropagation]]
I think that the discriminator needs to have a separate cost function which measures the number of images the discriminator missclassified as being real or generated. [[Discriminator is optimized to not be fooled by the generator|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=19m47]]
On the other hand, the generative network uses the discriminative network as cost. [[Generator to fool discriminator, i.e. it is trained to maximize the mistakes the the discriminator does|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=19m20]], that's why they are called ''adversarial''
The discriminator is //teaching// the generator, and it's adapting to the generator's knowledge and flaws. //Machine teaching//, not just machine learning.
!!!__Alternating [[Optimization]]__
[[video|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=19m59]]
[[Improved Techniques for Training GANs|https://arxiv.org/abs/1606.03498]] [[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=45m30]]
!!__Theoretical properties__
If you have an optimal discriminator, the generator minimizes the [[Jensen-Shanon divergence]]
!!__Variants__
[[Original GANs were diffucult to train|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=23m15]]
!!!__Class-conditional GANs__
They are [[supervised|Supervised learning]]
[[Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks|https://arxiv.org/abs/1506.05751]] [[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=24m]]
!!!__Video-prediction GANs__
[[Deep multi-scale video prediction beyond mean square error|https://arxiv.org/abs/1511.05440]]
[[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=25m45s]]
!!!__DCGANs__
[[Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks|https://arxiv.org/abs/1511.06434]]
[[Latent space arithmetic|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=30m30s]]
!!__In-painting GANs__
[[Context Encoders: Feature Learning by Inpainting|https://arxiv.org/abs/1604.07379]]
[[video|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=39m05]]
!!__Applications__
!!!__[[Feature learning]] for [[Semi-supervised learning]]__
[[GANs for feature learning|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=33m25]].
[[Two Minute Papers - Image Editing with Generative Adversarial Networks|https://www.youtube.com/watch?v=pqkpIfu36Os&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e&index=108]]
!!!__Disentangling representations__
[[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=41m50s]]
[[InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets|https://arxiv.org/abs/1606.03657]] (from [[OpenAI]])
---------------
They are similar to [[Autoencoder]]s but we learn the cost function, instead of just using l2 loss ([[vid|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=58m50]])
[[vid|https://www.youtube.com/watch?v=deyOX6Mt_As]]
[[Generative Adversarial Networks|https://arxiv.org/abs/1406.2661]]
https://www.wikiwand.com/en/Generative_adversarial_networks
[[the future|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=51m20]]
[[Connecting Generative Adversarial Networks and Actor-Critic Methods|https://arxiv.org/abs/1610.01945]]
[[Procedural generation]] applied to [[Computer-aided design]]
[[Video|https://www.facebook.com/ox3dp/posts/1199803410076356?notif_t=like¬if_id=1474187139914897]]
A class of [[Unsupervised learning]], where given a data set of $$x$$s, the task is to build a [[Probabilistic model]] $$P(x)$$, for the training data. This model is then able to //generate// new data by sampling new $$x$$s from $$P$$
[[Vid|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=18m20s]], can be used for [[Anomaly detection]].
!!!__[[Mixture model]]__
[[Gaussian mixture model]]
!!!__[[Factor analysis model]]__
!!!__[[Density estimation]]__
Often refers to [[non-parametric|Nonparametric statistics]] generative models. In fact, when one says generative model, one often refers to a parametric model for $$P(x)$$.
Using [[Baye's theorem]], generative models can be applied to [[Supervised learning]], see [[Generative supervised learning]]
[[What is the relationship between generative models and density estimation?|http://stats.stackexchange.com/questions/190214/what-is-the-relationship-between-generative-models-and-density-estimation]]
[[wiki|https://www.wikiwand.com/en/Generative_model]]
!!![[Autoencoder]]
!!![[Generative adversarial network]]
GAN-visual analogy making
[[Pixel-RNN|https://arxiv.org/abs/1601.06759]], [[code|https://github.com/carpedm20/pixel-rnn-tensorflow]]-- [[Recurrent neural network]]
!!__[[Latent variable]]s__
Often, generative models have certain parameters which are particularly important, because they may represent a particular feature or structure that the generative model may be able to extract in its learning process. Generative models are in fact often designed with this in mind, as the task of [[Unsupervised learning]] is to find some interesting structure in the data.
See this [[video|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=10m37]]
https://openai.com/blog/generative-models/deploy@guillefix:~/cosmos.git/tiddlers
''Generative unsupervised learning'' refers to a kind of [[Supervised learning]] task where the objective is learning the function $$p(\text{input}|\text{output})$$, together with $$p(\text{output})$$, which can be used to find $$p(\text{output}|\text{input})$$ using [[Baye's theorem]].
See [[notes|http://cs229.stanford.edu/notes/cs229-notes2.pdf]]. See [[lecture video|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=51s]] [[def|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=4m50s]]. The method effectively builds a kind of [[Generative model]] of the training data, i.e., it models the probability distribution $$p((x,y))$$.
[[slides|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides07.pdf]]
When applied to [[Classification]], this types of models are called ''generative classifier''s.
The difference between generative models and discriminative models that have the same conditional probability p (y|x) , i.e. same predictive model, is that they are trained differently and will learn different sets of parameters. The difference boils down to the generative model making extra assumptions (about the distribution of the data) which the discriminative model doesn't make. The performance of one versus the other will depend on how well or how badly these assumptions hold.
An example to explore these isues is [[Logistic regression]], and binary [[linear discriminant analysis]].
!!!__Learning method__
The learning method is similar to that described in [[Discriminative learning]]. However, the crucial differences is in how we model the joint likelihood
$$p((x,y)|\theta) = \prod_{i}p(x^{(i)}|y^{(i)};\theta)p(y^{(i)};\phi)$$
where $$\phi$$ are some more parameters in the generative model.
Now to compare with the discriminative case, we can compute
$$p(y^{(i)}|x^{(i)};\theta, \phi) = \frac{p(x^{(i)}|y^{(i)};\theta) p(y^{(i)};\phi) }{p(x^{(i)};\phi,\theta)}$$
where $$p(x^{(i)};\phi,\theta) = \sum_{y\in M} p(x^{(i)}|y;\theta) p(y;\phi) $$
where $$M$$ is the range of values that $$y$$ can take.
Then, another way to write the joint likelihood is:
$$p((x,y)|\theta) = \prod_{i}p(y^{(i)}|x^{(i)};\theta, \phi)p(x^{(i)};\theta, \phi)$$
We can see that <span style="color:coral;">the generative model also indirectly models $$p(x)$$</span>, and if the $$y$$ are considered as [[Latent variable]]s, then the model can be used as a [[Generative model]] of the inputs. This is often the approach in [[Semi-supervised learning]]
See more at [[Generative vs discriminative models]]
!!__Methods__
* [[Gaussian discriminant analysis]]
* [[Linear discriminant analysis]]
* [[Naive Bayes]]
!!__Training and prediction with missing data__
<span style="color:coral;">Generative models can be used for prediction with missing input features, because we can estimate them from their marginal distribution computed using the model. </span>
Can also train with missing data. See chapter 8 in Murphy's book
Comparison of [[Generative learning]] and [[Discriminative learning]]
If you have enough data, and you only care about $$p(y|x)$$ (prediction), ''discriminative models'' tend to be best, because you are modelling what you care directly, and not constraining other aspects of the system.
''Generative models'' model more about the system producing the data. This means one is often constraining more (by focusing on a particular family of models for more aspects of the system), so that the model is less flexible, but if the assumptions are OK, the model can work well with much less data. Also, one may want to model these extra aspects of the system because one is interested in more than just prediction, but also generation of samples, for instance.
See [[here|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=38m]] (Andrew Ng lec)
------------------
I'd be interested, however, on knowing under what circumstances the two approaches give the same result or differ. For instance, if you make an equivalent set of assumptions, they should give the same result, as you are then maximizing the same quantity ([[likelihood|Likelihood function]]), <mark>right?</mark> So the only difference is in the set of assumptions, i.e. the family of models describing your system, that you consider, and parametrize.
See [[Learning theory]].
https://en.wikipedia.org/wiki/Genetic_programming
https://en.wikipedia.org/wiki/Gene_expression_programming
[[presentation|https://engineering.purdue.edu/~sudhoff/ee630/Lecture02.pdf]]
See Holland's work. For e.g.
Holland, J. H. (1992). Adaptation in Natural and Artificial Systems, MIT Press, Cambridge MA.
[[Three Elements of a Theory of Representations|http://link.springer.com/chapter/10.1007/3-540-32444-5_3]]
[[Redundant Representations in Evolutionary Computation|http://www.mitpressjournals.org/doi/abs/10.1162/106365603322519288#.Vx6xwmqKHCI]]
As a result, uniformly redundant representations do not change the behavior of GAs. Only by increasing r, which means overrepresenting the optimal solution, does GA performance increase. Therefore, non-uniformly redundant representations can only be used advantageously if a-priori information exists regarding the optimal solution.
Bias towards simplicity (see [[MMathPhys oral presentation]]) similar to regularization in [[Machine learning]]?
Phenotype 1 is ''dominant'' to over phenotype 2 (coded by the same [[Gene]], or set of genes), if a hybrid having an allele for each, expresses phenotype 1. Phenotype 2 is then called ''recessive''. See [[video|https://www.youtube.com/watch?v=H6gwYdyn7II#t=3m54s]]. This is called ''total dominance'', or ''full penetrance''.
[[Wiki|https://www.wikiwand.com/en/Dominance_(genetics)]] (it talks about it being a property of gealleles, but it's a property of phenotypes!, see [[here|https://www.youtube.com/watch?v=H6gwYdyn7II#t=5m]])
Pleiotropic genes. May have both dominant and recessive traits, see [[video|https://www.youtube.com/watch?v=H6gwYdyn7II#t=5m44s]]. Sickle cell anemia is caused by a particular mutation in the gene of the $$\beta$$ globin protein of hemoglobin. That mutation gives rise to sickle cell anemia, which is a recessive trait, but it gives rise to sickle cells, which is a dominant trait. See [[here|https://www.youtube.com/watch?v=H6gwYdyn7II#t=6m07.5s]]
These properties as well as the [[Locus (Genetics)]], give rise to different [[modes of inheritance|Mode of inheritance]].
[[PHENOTYPE AND GENOTYPE|http://biomed.brown.edu/Courses/BIO48/5.Geno.Pheno.HTML]]
!!!A full understanding of genetic dominance requires looking at the [[Genotype-phenotype map]], which often requires [[Systems biology]] approaches.
!!!__Codominance__
!!!__Partial dominance__
Or ''incomplete penetrance''. See [[video|https://www.youtube.com/watch?v=-1GVPjWBFqQ#t=12m]]
__Incomplete dominance__
!!!__Pseudodominance__
!!__Molecular basis of dominance__
If you are [[Heterozygote]], and one of the alleles gives rise to an [[Enzyme]] that doesn't work, that may give rise to a recessive or a dominant trait.
If the enzymes don't interact, the ineffective enzyme won't change the phenotype (unless that enzyme is the rate limiting effect, and then the pathway will go more slowly). This is essentially a recessive trait. See [[video|https://www.youtube.com/watch?v=hf3G4eD23k0#t=7m46s]]
If the ineffective enzymes interact with and negatively affect the other enzymes, it virtually stop the pathway, resulting in a [[Dominant negative trait|https://www.youtube.com/watch?time_continue=528&v=hf3G4eD23k0#t=8m48s]].
[[Gene editing with CRISPR/Cas9|https://www.youtube.com/watch?v=SuAxDVBt7kQ]] Cas9 refers to a protein that has been found in bacteria inmune systems that is able to cut a DNA double strand at a point which matches the sequence of an RNA chimera (i.e. a molecule made of several RNA parts). This allows the programmable cutting of DNA. It is a particular type of a [[restriction enzime|https://en.wikipedia.org/wiki/Restriction_enzyme]], which are enzymes which cut DNA at certain sites.
[img width= 400 class=img-centered [https://upload.wikimedia.org/wikipedia/commons/7/7f/Crystal_Structure_of_Cas9_in_Complex_with_Guide_RNA_and_Target_DNA.jpg]]
This is important for genetic engineering because it is known that when you cut DNA, one way DNA repairs is by rejoining the two ends of the cut by introducing a new piece of DNA.
[[Paper that announced discovery|http://www.ncbi.nlm.nih.gov/pubmed/22745249]]
[[Personal genome project|http://www.personalgenomes.org/uk]], for "donating" your genome for research.
[[Cambrian Genomics|http://cambriangenomics.com/]] DNA laser printing!
[[Gene therapy to save the world by Liz Parrish|https://www.youtube.com/watch?v=JdEyd1CZYvo]], CEO of BioViva. See [[Anti-ageing innovation]].
Uses tools of [[Statistics]], [[Data science]]
!!__Methods__
[[Complex segregation analysis]]
Genetic linkage is the tendency of alleles that are close together on a chromosome to be inherited together during the meiosis phase of sexual reproduction.
Genes whose loci are nearer to each other are less likely to be separated onto different chromatids during [[Chromosomal crossover]], and are therefore said to be ''genetically linked''. In other words, the nearer two genes are on a chromosome, the lower is the chance of a swap occurring between them, and the more likely they are to be inherited together.
https://www.wikiwand.com/en/Genetic_linkage
[[Linkage map (vid)|https://www.youtube.com/watch?v=gY5bf7dEJes]]
[[Linkage mapping (vid)|https://www.youtube.com/watch?v=gYkcrsvEhRM]]
[[More details on linkage|https://www.youtube.com/watch?v=gYkcrsvEhRM#t=5m40s]]
!!Types of mutation
* Deletion
* Insertion
* Addition of stop codon
* ...
See more [ext[here|https://www.ndsu.edu/pubweb/~mcclean/plsc431/mutation/mutation4.htm]]
Genetic recombination is the production of offspring with combinations of traits that differ from those found in either parent.
[[Example of recombination|https://www.youtube.com/watch?v=Pq3l24TyEbw#t=6m30s]] (fruit fly experiments)
https://www.wikiwand.com/en/Genetic_recombination
!!__Types of recombination__
[[Homologous recombination]]
!!!__[[Definitions|https://www.youtube.com/watch?time_continue=35&v=H6gwYdyn7II]]
__
* [[Gene]]
* [[Allele]]
* [[Genotype]], [[Phenotype]], [[Phenotypic trait]].
* [[Chromosome]]
* [[Locus (Genetics)]]
More: [[Genes, Alleles and Loci on Chromosomes|https://www.youtube.com/watch?v=GUS9qmG1wY4&nohtml5=False]] -- [[Genotypes and phenotypes|https://www.stat.washington.edu/thompson/Genetics/1.3_genotypes.html]] -- [[PHENOTYPE AND GENOTYPE|http://biomed.brown.edu/Courses/BIO48/5.Geno.Pheno.HTML]]
[[MIT notes|http://ocw.mit.edu/courses/biology/7-03-genetics-fall-2004/lecture-notes/]]
!!__Mendelian genetics__
[[Intro to Mendel|https://www.youtube.com/watch?v=D8m-ZEr9qV8]] -- [[Mendel experiments|https://www.youtube.com/watch?v=5yY1snYi2x0]]
[[Mendelian genetics video|https://www.youtube.com/watch?v=NWqgZUnJdAY]]
!!!__Mendel's laws__
1. Law of segregation, genes segregate randomly from one generation to another
2. Independent assortment. [[Multiple traits: Mendel's second law|https://www.youtube.com/watch?v=iFlHZ7L7fYI]] [[key|https://www.youtube.com/watch?v=iFlHZ7L7fYI#t=4m]]. Are different [[Gene]]'s correlated in offspring
[[Heredity video|https://www.youtube.com/watch?v=CBezq1fFUEA]]
[[Punnett square]]
https://en.wikipedia.org/wiki/Chromosomal_crossover
!!__[[Chromosome theory of inheritance]] -- [[Inheritance]]__
[[Chromosome]]s carry the [[Gene]]s that Mendel studied. [[Cytology and the chromosomal theory of inheritance|https://www.youtube.com/watch?v=uLsVEYdn_e4]]
!!__[[Population genetics]]__
The genetics of populations of organisms, their [[Evolution]], and [[Ecology]]
!!__[[Biochemical genetics]]__
The field that studies the links between [[Genetics]] and [[Biochemistry]], for instance by finding which [[Gene]]s that control certain [[Metabolic pathway]]s, and how they do it.
!!__[[Molecular genetics]]__
!!![[DNA sequencing]]
!!![[Genetic mutation]]
!!!__[[Genetic epidemiology]]__
!!!__[[Gene expression]]__
[[Epigenetics]]
[[Complex segregation analysis]]
!!__[[Genomics]]__
Studies whole [[Genome]]s
!!__[[Genetic engineering]]__
[[Genetic recombination]] --> [[Homologous recombination]]
* [[Human genetics]]
* [[Genealogy]]
[[Real human genetics|https://www.youtube.com/watch?v=l9_lT0odWww]] (genetics in practice)
!!__[[Systems biology]]__
* [[Genotype-phenotype map]], [[Developmental biology]]
The complete set of DNA within a single cell of an organism. The set of all [[Genotype]]s
The study of [[Genome]]s of organisms
https://www.wikiwand.com/en/Genomics
https://genome-euro.ucsc.edu/cgi-bin/hgGateway?hgsid=218799371_GrzgaLCTgLS4ixN0o64W7m83y2na
!!__Comparative genomics__
Has uses in [[Biochemical genetics]], [[Population genetics]], etc.
The ''genotype'' is the set of [[Allele]]s corresponding to a particular [[Gene]] of an individual ([[vid|https://www.youtube.com/watch?v=H6gwYdyn7II#t=1m40s]]). Sometimes, it can refer to the set of alleles of a set of genes, I think. The set of alleles for all genes, is called the [[Genome]].
__[[Ploidy|https://global.britannica.com/science/ploidy]]__
* [[Haploid]], if the genotype contains a single allele.
* [[Diploid]], if the genotype contains a two alleles.
* [[Polyploid]], if the genotype contains a more than two alleles.
__Zygosity__
* [[Homozygote]], if the genotype is diploid and the two alleles are the same.
* [[Heterozygote]], if the genotype is diploid and the two alleles are the same.
Map between a //coding space// (genotype), and another space, called the //phenotype//. These appear, for instance, in [[Evolution]].
See [[MMathPhys oral presentation]]
!!__Types of GP relation__
* [[Genetic dominance]] -- [[Mode of inheritance]]. Traditional picture applies only sometimes, to traits called Mendelian traits. Modern picture shows it can all be much more complicated: partial dominance, pleiotropy, etc.
* [[Pleiotropy]]. Genes that affect many traits.
* [[Epistasis]]. Gene whose effect depends on other genes.
!!__Structure of the GP map__
[img[http://1.bp.blogspot.com/-T7ODIpnghZ4/UGY43-q09OI/AAAAAAAABgA/5I_P0s_I8A4/s1600/Stadler2002_fig1.png]]
[img[http://vincentcastric.weebly.com/uploads/4/8/6/3/48639343/1427140115.png]]
[[Genotype–phenotype mapping and the end of the ‘genes as blueprint’ metaphor|http://rstb.royalsocietypublishing.org/content/365/1540/557#sec-4]]
//Developmental encoding// or indirect encoding: you encode the instructions to //build// the system (by [[Morphogenesis]]), instead of the system itself (direct encoding). See [[Neuroevolution: Direct and Indirect Encoding of Networks|https://en.wikipedia.org/wiki/Neuroevolution#Direct_and_Indirect_Encoding_of_Networks]]. [[Comparing direct and developmental encoding schemes in artificial evolution|http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.343.1539&rep=rep1&type=pdf]]
[[Genotype-phenotype maps - Stadler|https://www.tbi.univie.ac.at/papers/Abstracts/02-pfs-002.pdf]] Ideas extending standard topology to explore the spaces defined by GPMs
[[Evolving scalable and modular adaptive networks with Developmental Symbolic Encoding|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3161195/]] Ideas of evolvable GPMs, evolving evolvability, etc.
__Effects__
[[Bias in GP maps]]
[[Simplicity bias]]
__Related concepts__
[[Basin of attraction]]
--------------------
!!![[Network]] topology of neutral networks
[[Topological Structure of the Space of Phenotypes: The Case of RNA Neutral Networks|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0026324]]
Genotyping is the process of determining differences in the genetic make-up ([[Genotype]]) of an individual by examining the individual's DNA sequence using biological assays and comparing it to another individual's sequence or a reference sequence. It reveals the alleles an individual has inherited from their parents.
https://www.wikiwand.com/en/Genotyping
//Shortest path// (computed using the [[Metric tensor]]
[[Portal:Contents/Geography and places|https://en.wikipedia.org/wiki/Portal:Contents/Geography_and_places]]
[[Physical geography]]
[[Human geography]]
[[Places]]
http://scimaps.org/maps/map/in_terms_of_geograph_92/detail
A [[geological time span|Geological time spans]] corresponding to tens to ~one hundred million years. See the timeline of the [[History of Earth]]
* ''Eon''. half a billion years or more
* ''Era''. several hundred million years
* ''[[Period|Geological period]]''. tens to ~one hundred million years
* ''Epoch''. tens of millions of years
* ''Age''. millions of years
* Chron. Smaller than an age (not common).
------------
https://www.wikiwand.com/en/Period_(geology)
Geology (from the Ancient Greek γῆ, gē, i.e. "earth" and -λoγία, -logia, i.e. "study of, discourse") is an earth science comprising the study of solid Earth, the rocks of which it is composed, and the processes by which they change.
See [[Mineralogy]]
https://www.wikiwand.com/en/Geology
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/6/6b/Rock_cycle.gif/600px-Rock_cycle.gif]]
[img[https://s-media-cache-ak0.pinimg.com/originals/84/63/9f/84639fb19e78cf27fe81528c2e966e49.jpg]]
A concept in [[Supervised learning]]
[[Intuition of geometric margins|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=49m]] -- [[definition of geometric margin|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=1h0m50s]], and [[derivation|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=1h2m20s]]
The formula is
$$\gamma^{(i)} = y^{(i)}[(\frac{\omega}{||\omega||})^T x^{(i)} + \frac{b}{||\omega||}]$$
It is very similar to [[Functional margin]], and in fact equal if $$omega = 1$$.
W.r.t. an entire training set , the geometric margin is the min of thec$$v$$ ofver all data points $$i$$ inn the training set.
//Things often have a shape//
What is ''space''? Well, it can be Euclidean, but it may also be non-Euclidean, and have curvature!
[[Trigonometry]]
https://en.wikipedia.org/wiki/Geometry
[[New Horizons in Geometry (Dolciani Mathematical Expositions) 1st Edition|http://www.amazon.com/dp/088385354X]]
See part of the book here: http://www.mamikon.com/VisualCalc.pdf
http://world.mathigon.org/
!!__[[Euclidean geometry]]__
The elements. Has some subtle flaws in mathematical rigour. Fifth postulate, in particular, was controversial.
!!!__[[Geometrical construction]]s__
[[Angle bisector]]
!!__[[Non-Euclidean geometry]]__
[[Elliptic geometry]]
[[Hyperbolic geometry]]
Riemannian geomtry
[[Differential geometry]]
See pages 88 and forth in [[GEB|Godel, Escher, Bach]].
//one can let the meanings of "point" and "line", and so on be determined by the set of theorems (or propositions) in which they occur//. These are called //undefined terms//, and they only get meaning through these theorems.
!!__[[Projective geometry]]__
!!__[[Complex geometry]]__
[[Mathematical Perspectives on Clouds, Climate, and Tropical|https://www.youtube.com/playlist?list=PL04QVxpjcnjhAX_DXNr3bWnXJMYKx8mtI]]
[[Georges Méliès|https://en.wikipedia.org/wiki/Georges_M%C3%A9li%C3%A8s]]. An important figure in the [[History of cinema]]
[img width=400 [https://upload.wikimedia.org/wikipedia/commons/6/63/George_Melies.jpg]]
https://www.youtube.com/watch?v=ok2uR3btMrE
[[Henry George and The Single Tax|https://www.youtube.com/watch?v=TpqtfMraJvU]]
https://www.wikiwand.com/en/Georgism
[[North Germanic languages]]
[img[https://66.media.tumblr.com/9afabe9497c1285b482554eea25e0ace/tumblr_n2vk5bSD4b1qdo7sio1_500.gif]]
Good discussion on Reddit: https://www.reddit.com/r/Ghost_in_the_Shell/comments/2dsuzs/opening_screen_for_sac/
Tachikomas philosophy discussions: [[vid1|https://www.youtube.com/watch?v=xQDbxw8ErAE#t=4m40s]], [[vid2|https://www.youtube.com/watch?v=xQDbxw8ErAE#t=12m50s]], [[vid3|https://www.youtube.com/watch?v=jDJ_JPdq-HM#t=4m35s]]
I love that they think so differently from humans. It shows how AIs could really be.
A [[covalently bonded|Covalent bond]] [[compound|Chemical compound]], in which the atoms form a single covalently bonded structure (like a giant [[Molecule]]), often a [[Crystal]].
[img[http://a.files.bbci.co.uk/bam/live/content/zxr2n39/large]]
http://www.bbc.co.uk/education/guides/z94xsbk/revision/4
!!!__Some properties__
*Very high melting points – this is because a lot of strong covalent bonds must be broken. Graphite, for example, has a melting point of more than 3,600°C.
*Variable electrical conductivity - diamond does not conduct electricity, whereas graphite contains free electrons so it does conduct electricity. Silicon is a semi-conductor – it is midway between non-conductive and conductive.
A glass is a system that shows [[Quenched disorder]] may be refered to as a //glass//. Often it refers to ''amorphous solid''s.
[[Glass transition]]
[[Spin glass]]
A dramatic change in the [[Kinetic property]]es of a [[Material]], as some thermodynamic property is varied, usually [[Temperature]], for instance, the [[Viscosity]] when a [[Supercooled liquid]] becomes a [[Glass]]. The term is used more generally though, as for instance in [[Protein folding]] theory.
[[Glass: The Cinderella Problem of Condensed-Matter Physics (Lecture 8) - Anthony Leggett 2012|https://www.youtube.com/watch?v=QeHWAIg1biM]]
See [[Viscosity and elasticity]]
[[Entropy crisis, ideal glass transition, and polymer melting: Exact solution on a Husimi cactus|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.68.031502]]
__Kauzmann paradox__
----------
https://www.wikiwand.com/en/Glass_transition
Any two subsets of variables are conditionally independent given a separating subset
A hexose, a 6-carbon [[Monosaccharide]]
See [[this video|https://www.youtube.com/watch?v=KJG6HA5xSxY#t=4m25s]]
The way you store [[Sugar]]s in your [[Liver]]
The [[Metabolic pathway]] to break down [[Sugar]]. [[The point is to make ATP (that stores energy)|https://www.youtube.com/watch?v=DnT3AHElIoY#t=2m30s]]
[img[https://d37djvu3ytnwxt.cloudfront.net/assets/courseware/v1/23d3c787298c150ae550865d52b1cd80/asset-v1:MITx+7.00x_3+2T2015+type@asset+block/G05_4.jpg]]
[[Glycolysis: a pathway to break down sugar|https://www.youtube.com/watch?v=DnT3AHElIoY]]
[[Pathway|https://www.youtube.com/watch?v=DnT3AHElIoY#t=5m10s]]
[img[https://d37djvu3ytnwxt.cloudfront.net/assets/courseware/v1/b77be9886ee47507344e7b174b71b49a/asset-v1:MITx+7.00x_3+2T2015+type@asset+block/G05_5.jpg]]
,,There is a [[Phosphorus]] that should be consumed in the last reaction in the diagram above.,,
[img[https://d37djvu3ytnwxt.cloudfront.net/assets/courseware/v1/bab5d8ba9c4ec3f2333b1ab5a6e80052/asset-v1:MITx+7.00x_3+2T2015+type@asset+block/G05_6.jpg]]
__Summary__
[img[https://s9.postimg.org/xxw4s4agf/Selection_600.png]]
[[Glucose]] --> [[Pyruvate]] --> [[Fermentation]]
!!__[[Glycolysis regulation|https://www.youtube.com/watch?v=Lt5SiDZsBig#t=7m03s]]__
A [[Mathematician]] that developed [[Godel incompleteness theorems]]
Using ''Godel numbering'' (an encoding of statements in number theory), Godel managed to find a theorem, which in English is like:
> This statement of number theory does not have any proof in the system of //Principia Mathematica// (and related systems)
which can't be proved in the system but is (thus) true.
This showed that the system (and indeed all [[Formal system]]s that tried to do the same thing) was either incomplete or inconsistent.
-----------
https://www.quora.com/Do-G%C3%B6dels-Incompleteness-Theorems-imply-that-the-human-mind-is-fundamentally-different-from-machines
Infinite hierarchy of formal systems vs chomsky hierarchy of machines.
Formal system = machine + info deacribing the formal system.
Hierarchy of formal systems just describes a hierarchy in their axioms/deacription.
Intuition isn't proving.
---------------
Godel hierarchy of formal systems is a more fined grained hierarchy than Chomsky's.
It might even be suggested that a theory of reasoning could be identical to its own metatheory, if it were worked out carefully. Then, it might seem, all levels would collapse into one, and thinking about the system would be just one way of working in the system! But it is not that easy. Even if a system can "think about itself", it still is not outside itself. You, outside the system, perceive it differently from the way it perceives itself. So there still is a metatheory-a view from outside-even for a theory which can "think about itself" inside itself. We will find that there are theories which can "think about themselves". In fact, we will soon see a system in which this happens completely accidentally, without our even intending it! And we will see what kinds of effects this produces.
The Gödel Machine (Schmidhuber, 2006) is a general paradigm for solving arbitrary problems, including optimization problems and reinforcement learning.
Gödel machines: self-referential universal problem solvers making provably optimal self- improvements.
[[Video|https://www.youtube.com/watch?v=mF5-tr7qAF4#t=12m34s]]
http://www.scholarpedia.org/article/Universal_search#G.C3.B6del_machine
https://www.wikiwand.com/en/G%C3%B6del_machine
[ext[http://people.idsia.ch/~juergen/goedelmachine.html]]
[ext[GÖDEL MACHINE SUMMARY|http://people.idsia.ch/~juergen/gmsummary.html]]
[[Gödel Machines, deep learning and the limits of AI|https://storagemojo.com/2016/01/13/godel-machines-deep-learning-and-the-limits-of-ai/]]
Any utility function (such as expected future reward in the remaining lifetime) can be plugged in as an axiom stored in initial program p. Among other things, p systematically makes pairs (switchprog, proof) until it finds a proof of: "the rewrite of p through current program switchprog implies higher utility than leaving p as is." Since the utility of 'leaving p as is' implicitly evaluates all possible alternative switchprogs which an unmodified p might find later, we obtain a globally optimal self-change by executing the current switchprog.
The switchprog holds a potentially unrestricted program whose execution could completely rewrite any part of the Gödel machine's current software. Normally the current switchprog is not executed. However, proof techniques may invoke a special subroutine check() which tests whether proof currently holds a proof showing that the utility of stopping the systematic proof searcher and transferring control to the current switchprog at a precisely defined point in the near future exceeds the utility of continuing the search until some alternative switchprog is found. Such proofs are derivable from the proof searcher's axiom scheme which formally describes the utility function to be maximized (typically the expected future reward in the expected remaining lifetime of the Gödel machine), the computational costs of hardware instructions (from which all programs are composed), and the effects of hardware instructions on the Gödel machine's state.
https://www.semanticscholar.org/paper/Goedel-Machines-Self-Referential-Universal-Problem-Schmidhuber/2e45fd58329558b0c9e73cbc1fb9f4f60dbb5ca7/pdf
[img width=300 [http://people.idsia.ch/~juergen/robohorsegm1.jpg]]
An [[Isomorphism]] between [[Formal system]]s (typographical systems), and [[Number theory]].
>CENTRAL PROPOSITION: If there is a typographical rule which tells how certain digits are to be shifted, changed, dropped, or inserted in any number represented decimally, then this rule can be represented equally well by an arithmetical counterpart which involves arithmetical operations with powers of 10 as well as additions, subtractions, and so forth.
More briefly:
>Typographical rules for manipulating numerals are actually arithmetical rules for operating on numbers.
This is central to the proof of [[Godel incompleteness theorems]].
See also [[Godel, Escher, Bach]]
__//Producible numbers//__
Just as any set of typographical rules generates a set of theorems, a corresponding set of natural numbers will be generated by repeated applications of arithmetical rules. These producible numbers play the same role inside number theory as theorems do inside any formal system.
* <big>[[Strange loop]]s</big>
* [[Formal system]]
** [[Propositional logic]]. you can't go on defending your patterns of reasoning forever. There comes a point where faith takes over. Nice discussion at end of chapter VII. ''Metatheories'' and so-on. Formalizing higher-level theories, i.e. being able to create models, automatic reductionism, see [[Dual-process theory]]. See also [[Godel incompleteness theorems]]. [[Proof]]
** Typographical number theory (TNT) a [[Formal system]] for [[Number theory]] ([[Logic]]+[[Peano arithmetic]]).
** [[Godel numbering]] -- we can transfer the study of any formal system-in fact the study of all formal systems-into number theory. --> ''Central Dogma of [[Mathematical logic]]'': TNT -> N -> meta-TNT. TNT can talk about itself!
* Humans, unlike most machines we have built, are introspectively observing what they themselves do. See page 26.
* Thinking inside and outside formal systems.. Machine, Intelligent, and Un- mode (Zen..)
* //Do words and thoughts follow formal rules, or do they not?//
* [[Formal systems and semantics]] -- [[Semantics]]: //meaningfull vs meaningless interpretations//
** Formal systems can have more than one meaningfull interpreation
** Limits in the [[decidability|Undecidable]] of [[Formal system]]s. See chapter III, page 72. Not all recursivelly enumerable sets are recursive <> i.e. there exists a [[Formal language]] (set of strings), which can be generated by a [[Formal system]], whose complement can't be generated by a formal system. This implies that there exist formal systems for wchich there is no typographical (computable) decision procedure. //Figure and ground//
** ,,If you add or changes rules of the system, it is not the same system, so meaningfull interpreations may become meaningless,, For example, [[Geometry]].
** Meaning of consistency. Dependent on interpretation of formal system. Page 94. ,,Hypothetical worlds; is it possible to think an impossible thought?,, ,,Internal vs external consistency, see also apge 99,,.
* More on [[Meaning]], as isomorphism ([[Function]]s) on chapter VI. Analogy with [[Genotype-phenotype map]]s. ,,"To put it as succintly as possible, one view says that in order for DNA to have meaning, //chemical context// is necessary; the other view says that only //intelligence// is necessary to reveal the "intrinsic meaning" of a strand of DNA.",,. Example from ancient language deciphering. Generally, we can say: meaning is part of an object to the extent that it acts upon intelligence in a predictable way.
**To understand the ''inner message'' is to have extracted the meaning intended by the sender..
** To understand the ''frame message'' is to recognize the need for a decoding-mechanism. Frame messages often take the form of [[Aperiodic crystal]]s, or their analogues.
**To understand the ''outer message'' is to build, or know how to build, the correct decoding mechanism for the inner message.
** There are often many levels of these kinds of messages. Meaning is deconstructed in layers of meaning extraction / mappings. See the paper on why deep and cheap learning works on [[Deep learning theory]]. Deeper levels of meaning extraction (approaching the frame and outer levels (which are said to give triggers, instead of explicit meaning) are being researched, I think they are called progressive neural nets). Decoding the outer message is a fallible enterprise, just like [[Intelligence]] (see [[Dual process theory]] video).
** Universal [[Language]] for intelligences... ,,[[Machine learning]] may be discovering it/..,,. [[Relativity]]...
*<big> [[Intelligence]]</big>
* "What is [[Consciousness]]?". It will be the unraveling of the nature of the isomorphisms that underlies [[Meaning]] that will be the key element in answering this question.
* ,,Truth vs theoremhood.., how we think vs standard machines. page 86-87,,
* [[Theoretical computer science]]
** [[Recursion]]. Loops, subroutines. Things which are //the same// in a certain sense, but different in other sense, taking part in some [[Structure]], like a simple recursive structure or a loop. Often one just wraps them in functions. These are prevalent in computer science. He also describes ideas similar to [[Godel machine]]s, programs which can modify themselves as probably being key for intelligence.
* //When are two things the same?// Come at it from many angles, and at the end see how simply it is connected with the nature of [[Intelligence]]. Appears in
** [[Recursion]]
* <big>[[Zen]]</big>
** Koans -> free [[Mind]], of [[Logic]] and structure..
** Enlightment: transcending dualism.
** a major part of Zen is the fight against reliance on words
------------------
$$G(n) = \lfloor\frac{n+G(G(n-1))}{2}\rfloor
$$r^2$$, p-values, $$\chi^2$$, etc.
,,[[R Squared Theory - Practical Machine Learning Tutorial with Python p.10|https://www.youtube.com/watch?v=-fgYp74SNtk&index=10&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]],,
See [[Computer hardware]] and [[Cloud computing]]
[[External GPU]]
[[Installing the GPU version of TensorFlow for making use of your CUDA GPU|https://www.youtube.com/watch?v=io6Ajf5XkaM&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=52]] -- [[more details|https://pythonprogramming.net/how-to-cuda-gpu-tensorflow-deep-learning-tutorial/]]
Useful for [[Data science]]/big data
A vector given by components $$\frac{\delta f}{\delta x_i}$$, which points towards the direction along which $$f$$ increases most rapidly, at a given point.
A [[Local optimization]] technique based on following gradients to decrease a function.
Take steps of a size given by the learning rate along the [[Gradient]].
Can prove convergence for [[Convex function]]s
!!![[Newton's method]]
* [[Quasi-Newton method]]
!!![[Stochastic gradient descent]]
!!![[Convergence conditions for gradient descent|https://www.youtube.com/watch?v=Bver7Ttgb9M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=17#t=8m]], to determine ''learning rate''
Nesterov's accelerated gradient
line-search to find step-size
__Constrained optimization with projection based methods__
Gradient step and project on the surface of the constraint area..
A set of rules that defines a language. See [[Formal grammar]]
The task of [[learning|Machine learning]] a [[Formal grammar]].
<<<
At the time of Chomsky's paper, I was trying to find a satisfactory utility
evaluation function for my own system. I continued working on this with no
great success until 1958, when I decided to look at Chomsky's paper more
closely. It was easy for me to understand and build upon. In a short time, I
devised a fast left to right parser for context free languages and an extremely
fast matrix parser for context sensitive languages
It took advantage of special
32 bit parallel processing instructions that most computers have
My main interest, however, was learning. I was trying to find an algo
rithm for the discovery of the "best" grammar for a given set of acceptable
sentences. One of the things sought for: Given a set of positive cases of ac
ceptable sentences and several grammars, any of which is able to generate all
of the sentences
what goodness of fit criterion should be used? It is clear
that the "Ad-hoc grammar
that lists all of the sentences in the corpus, fits
perfectly. The "promiscuous grammar" that accepts any conceivable sentence
also fits perfectly. The first grammar has a long description, the second has a
short description. It seemed that some grammar half way between these, was
but what criterion should be used?
correct
There are other modes of learning in which the "goodness of fit" criterion is
clearer
<<<
https://books.google.co.uk/books?hl=en&lr=&id=XAOE5V9B4dUC&oi=fnd&pg=PR9&ots=rbA1pmUJgB&sig=wjS3fuyps3_LPb3YH6hoSaz6zIY#v=onepage&q&f=false
http://link.springer.com/chapter/10.1007/3-540-33486-6_7#page-1
See [[Evolving automata]]
[[Approximation algorithms for grammar-based data compression|https://dspace.mit.edu/handle/1721.1/87172]]
smallest grammar problem: find the smallest context-free grammar that generates exactly one given string.
[[Grammar-based code|https://en.wikipedia.org/wiki/Grammar-based_code]]
[[Grammatical codings|http://www.eanw.info/isdatelistvo/Kniga-Scheremet.pdf]]
A ''granular material'' (also known as ''granular media'' or ''granular matter'') is a dense packing of non-cohesive solid particles.
See [[Soft matter physics]] and [[Complex systems]]
!!__Force networks__
[img[http://www.phy.duke.edu/~bob/images/56373557.jpg]]
[[Force Distributions in Dense Two-Dimensional Granular Systems|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.77.274]]
Despite the highly uniform density of a random packing of non-cohesive particles, photoelastic visualizations provide a striking evidence of the heterogeneous distribution of contact forces on a scale definitely larger than the typical particle size
[[Bimodal Character of Stress Transmission in Granular Packings|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.80.61]]
[[Shear-Jamming in Two-Dimensional Granular Materials with Power-Law Grain-Size Distribution|http://www.mdpi.com/1099-4300/15/11/4802/htm]]
[[Apollonian Networks: Simultaneously Scale-Free, Small World, Euclidean, Space Filling, and with Matching Graphs|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.94.018702]]
[[http://www.phy.duke.edu/~bob/]]
[[The role of particle shape on the stress distribution in a sandpile|http://rspa.royalsocietypublishing.org/content/464/2089/99]]
[[Scattering of waves by impurities in precompressed granular chains|http://people.maths.ox.ac.uk/porterm/papers/RT-granular-final.pdf]]
------------
__Fragmentation process__
[[Fragmentation of grains in a two-dimensional packing|http://link.springer.com/article/10.1007/s100510050476]]
[[Statistical Models for the Fracture of Disordered Media|https://books.google.co.uk/books?hl=en&lr=&id=QufMBQAAQBAJ&oi=fnd&pg=PP1&dq=info:BxjT8FidHe4J:scholar.google.com&ots=t-6Mw3v9Xu&sig=vE16KKRBTEOOkeU0V8CYeQ_m_DM&redir_esc=y#v=onepage&q&f=false]]
* [[Basophil]]
* [[Neutrophil]]
See [[Graph theory]]
A graph $$g$$, consists of a set of vertices $$V$$, and a set of edges $$E \in V \times V $$.
See [[Graph theory]]
A (graph) ''automorphism'' is an isomorphism from a graph to itself, i.e., where $$G=G'$$.
Automorphisms capture the notion of symmetry for a graph because imposing the above condition of edge preserving is that same than imposing that if we move vertices in a geometrical representation of a graph from their positions to the positions previously occupied by other nodes while carrying their connections with them (because if connections exist between $$i$$ and $$j$$, they must exist between $$f(i)$$ and $$f(j)$$, so that it is a homomorphism, i.e. a structure preserving map), then the new connections will be the same as those of the original graph (because the homomorphism property implies they are a subset of the connections. However, for it to be an isomorphism, the inverse map must also be a homomorphism, so that a connection $$(k,l)$$ must correspond to connections $$(f^{-1}(k), f^{-1}(l))$$, so that it is also a superset, and so the sets of edges are equal).
->Another way of looking at a graph automorphism is as a permutation $$\lambda$$ of the node labels $$V$$, such that a pair of vertices $$(i,j)$$ are connected if and only if $$(\lambda(i), \lambda(j)$$ are connected.
->Yet another way of looking at graph automorphisms is, I think, as symmetries of the [[Adjacency matrix]]. Any permutation of the node labels that leaves the adjacency matrix unchanged is a graph automorphism.
The set of all automorphisms of an object forms a group, called the ''automorphism group''. Intuitively, the size of the auto- morphism group A ( g ) provides a direct measure of the abundance of symmetries in a graph or network. Every graph has a trivial symmetry (the identity) that maps each vertex to itself.
https://www.wikiwand.com/en/Graph_dynamical_system
A particular kind is a [[Boolean network]], if the state of each node is binary.
See also [[Sequential dynamical system]], and [[Dynamical systems on networks]]
See [[Graph theory]]
A (graph) ''isomorphism'' is a mapping between vertices of two graphs $$G=(V_G, E_G)$$ and $$G'=(V_G', E_G')$$ ($$i \mapsto f(i)$$ such that $$i \in V_G$$ and $$j \in V_G'$$) such that the edge $$(i,j)$$ is contained in the set of edges of $$G$$, //if and only if// the edge $$(f(i), g(i))$$ is contained in the set of edges of $$G'$$. To graphs are //isomorphic// if there exists an isomorphism between them. They are then also called "topologically equivalent".
We can describe difussion of a quantity $$\Psi_i$$ associated with node $$i$$ in a network with adjacency matrix $$A$$, with the equation:
$$\frac{\partial \Psi_i}{\partial t}=\sum_j A_{ij}C(\Psi_j-\Psi_i)=C\sum_j (A_{ij}-\delta_{ij}k_j)\Psi_j)$$
where $$C$$ is the diffusion constant. In vector form:
$$\frac{\partial \mathbf{\Psi}}{\partial t}=C(\mathbf{A}-\mathbf{D})\mathbf{\Psi} \equiv -C\mathbf{L}\mathbf{\Psi}$$
where $$\mathbf{D}=diag(k_1,...,k_n)$$ is the diagonal matrix of degrees, and ''$$\mathbf{L}=\mathbf{D}-\mathbf{A}$$'' is the (combinatorial) ''graph laplacian'', which is then:
$$
L_{ij}=
\begin{cases}
k_i &\text{if } i=j,\\
-1 &\text{if }i\neq j \text{ and there is an edge } (i,j),\\
0 &\text{otherwise}
\end{cases}
$$
We can solve this diffusion equation by writting any initial condition as a linear combination of eigenvectors of $$L$$, and the coefficients will then evolve exponentiall with exponents given by the eigenvalues of the matrix.
The graph laplacian can be related to the //edge incidence matrix//, $$\mathbf{B}$$. This is defined by first labelling the ends of each edge as $$1$$ and $$2$$. Then:
$$
B_{ij}=
\begin{cases}
+1 &\text{if end 1 of edge i is attached to vertex j,}\\
-1 &\text{if end 2 of edge i is attached to vertex j,}\\
0 &\text{otherwise}
\end{cases}
$$
Then, $$\mathbf{L}=\mathbf{B}^T\mathbf{B}$$, from which one can show that the eigenvalues of $$\mathbf{L}$$ are not only real (as it is symmetric), but also non-negative. This is an important physical property of the Laplacian, because it means the solutions of the diffusion equation only includes non-diverging solutions, which makes sense since diffusion is constructed to conserve the quantity $$\Psi_i$$.
In particular the vector $$\mathbf{1}=(1,1,1,...)$$ always has eigenvalue $$0$$ (this implies $$\mathbf{L}$$ is singular). It can be shown, that more generally, the number of eigenvectors with $$0$$ eigenvalue is always equal to the number of components in the network. Thus the second eigenvalue of the Laplacian (when arranged in ascending order) is non-zero if and only if the network is connected. This eigenvalue is called the //algebraic connectivity// or ''//spectral gap//'', and is useful in a technique known as spectral partitioning.
Mathematical study of [[Graph]]s. These are very similar to [[Network]]s studied in [[Network theory]].
[[Graph Theory by Sarada Herke|https://www.youtube.com/playlist?list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
[[Definition of a graph|https://www.youtube.com/watch?v=S1Zwhz-MhCs&index=2&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
[[notes|https://courses.maths.ox.ac.uk/node/view_material/1300]]
!! See [[Mathematics of networks]]
[[Path (Graph theory)]]
[[Families of graphs]] and [[Network]]s. [[Connected and Regular Graphs|https://www.youtube.com/watch?v=BEyuUXQs5ko&index=5&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
!!!__Graph isomorphism and automorphism__
Often we do not make a distinctio
n between isomorphic
graphs, treating them as the same.
http://math.stackexchange.com/questions/790110/whats-the-difference-between-the-automorphism-and-isomorphism-of-graph
[[Graph isomorphism]] -- [[video|https://www.youtube.com/watch?v=yFpRpxOry-A&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg&index=10]]. [[Isomorphic and Non-Isomorphic Graphs|https://www.youtube.com/watch?v=z-GfKbzvtBA&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg&index=11]]
[[Graph automorphism]]
See [[here|https://en.wikipedia.org/wiki/Graph_homomorphism]] for definition of graph homomorphism.
!!__Graph colouring__
https://www.wikiwand.com/en/List_coloring
[[Introduction to Graph Colouring|https://www.youtube.com/watch?v=RSSfO0lnEp8]]
------------------
https://www.youtube.com/watch?v=Gc8emFk-2vc&list=PLwygftUY318G_Yo5pp1UDU613ey0nNlIj
''Probabilistic graphical model''
[[1.0 - Welcome-Probabilistic Graphical Models - Professor Daphne Koller|https://www.youtube.com/watch?v=WPSQfOkb1M8&list=PL50E6E80E8525B59C]]
[[Jeffrey A. Bilmes|https://www.youtube.com/channel/UCvPnLF7oUh4p-m575fZcUxg/videos]]
* [[Undirected graphical model|Markov network]]
* Directed graphical models: [[Hidden Markov model]], Bayesian networks
See [[here|https://www.youtube.com/watch?v=ZYUnyyVgtyA&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=25#t=7m10s]] for the distinction of directed vs undirected graphical models. The difference, is that a directed graphical model is an undirected one, but where the factors that correspond to the edges, are normalized, because they correspond to [[Conditional probability]]es
__[[Graphical models|https://en.wikipedia.org/wiki/Graphical_model]]__
They can often be represented as kinds of [[Artificial neural network]]s
[[Energy minimization|http://mpawankumar.info/teaching/cdt-optimization/lecture2_2.pdf]]
--------------------
!!![[Composing graphical models with neural networks|https://www.youtube.com/watch?v=btr1poCYIzw]]
Graphics and visualization libraries for [[Frontend web development]]
* [[Bokeh|http://bokeh.pydata.org/en/latest/docs/gallery.html]]
* https://d3js.org/ [[d3js]]
* http://visjs.org/
* [[Raphael|http://dmitrybaranovskiy.github.io/raphael/]]
* https://bonsaijs.org/
* http://paperjs.org/
* [[D3xter.js|http://d3xter.io/]] easier to use version of d3.js ! -- See also https://d3plus.org/ !
* http://processingjs.org/ -- https://p5js.org/
* http://www.x3dom.org/
[[ThreeNodes.js: vvvv "clone" in javascript/webgl|https://github.com/idflood/ThreeNodes.js]] <i class="fa fa-thumbs-up"></i> <i class="fa fa-thumbs-up"></i>
<i class="fa fa-arrow-right"></i> <b>http://threejs.org/</b>
http://www.sitepoint.com/twelve-javascript-libraries-data-visualization/
https://webvr.info/
!!!https://goocreate.com/
http://benalderfer.com/playground/particle/
Natural extension of the [[meet|Meet operation]] of two elements to an arbitrary [[Set]] of elements of a [[poset|Partially ordered set]]
Interpreting the [[Partial ordering]] as "less than or equal", it can be understood as the greatest point that is less than or equal to all the points in the set.
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oEQPeQphMBDKC1dJcF1EWJd1+6/B/RbH++BFUJSkisJW3Uc8ggzklCQa74AYIELp6hEkSBETot19ZywCIURVmioqIj3uP8/9xx7+eW3oOrByOp0anI+I8Gjrtqm358cke67y8sHbM/Zw055dBWg8Ui4OqOjZ7FQCAIXR6XbjoivZXG2wBWo2Vep8vU8fRT56Rp7toa1awRrrgZ6iabfZporr+jqLxgzAIIApwiAh1Oi+TAEDIGICICe1QbFIjfCl1gU81jxhcz1ths1cFgQMqrT90z0qwPru6/eHw9MwpBcvbnc3N7fXd/VUWZ68QhwMKgPEZjukMdd5WaLCMCS7fX313V+/j8CYYZYY6lW8urPYoMOU67U76jIHC4bX9rM/+Uka02+//vowH17e3sZcBxsQeP/u/t3X93WudGak+Th/s3xzOFyNm2mY8nQ97bbXh9NjGyuzbCqLn5qCrBRCavG6AAthQIYlITnPC4CcRgaPx7mcajnMIul4PNYaEdFm0N2jRhvD7voJEQQxl1j4mGzKw5DHFG6SPI+plGXxeZ4dJqYDIiIqDWk0S1oXIlC95EgA1URDXFEKhgG3N9ebcftw//jw/n4+LayQUFOAEU6Ggwb489KSZwFLusxzXl0NH5tIB+UPj4/p27T9LJ1srl6bwSXNrPQSUZxMNmaBsM7LvNTTEiG7zWaz2Zrw4fHp4XTkgjTa1ZtxuN5ULZ5Yam2kwNRySl5LmWvzkQoIRAItJctowZZChId7RISIhMjvZPXn+NIWczRS0INIYxjh3v5+riNZz/YcfbonIGutq/NtJv/DIsWzf7gw4CZwEw4iGEIJEag1AVo8qCRCFM2AzzlWnAkL0Nl3hwvd7/e4wO4eRVXbCUhGnG/moxtcMTqben4RB1vhQErJkgSfV8gnj0dSOoLoPO78xsu5eIYanwTL5m9NpCVgmt7QKhCka/E/CM3PPrFxH+kYq/MmaAsbz7DkYkI/Elj+ABXlDzjaEr286Hkm/38+fvB5/3ABCx8LSbgg1e03Zzm5Q7R1Gv5ZAlb7VBvElceexZpnibGHwTP8bKuSaAlIx/P0e3U1lWYj3jEEBKVUgsM4AFKrL2Vx90TVZClZNSO8xe5oKVYBiAhHkIRZMtGIKEuIUhXRErRCAArxparklFOSLLCmXLGGhoYHfRXaIUR4rQHCmstQZwEMKm3GxAht9RYI0jvhCyhUJSgiLRnR07NNI2HXsLQZHiG9qEcAFSrdQvWSL0RKk0KSShJFxTIvXlAXCWeEN6GMpimpDKoZyESiDYYkw27UZLQgwlmXZfHqEdRBsiZfAh4yCCXCPRIBpUogImJ3dXU8HJdlAamqJokt8YgQg1pGsC4lvCgBiPI86SGDru6MYoamzXvP2Rye9jcvdtvtVHRp9YCmrioqZkY/VXeiyxe6QthnhQVAMLSxClorXegyGMk1Y99cIynCCKq2xHgzjej+8OyvPzpIChjUbkcCrJrWWU+5MDQRqCrp1GcO0KHkc96FEDDogaCQ0goR1PRYjoSqpmHIVBznYzksUhyMCCdqSmbZJIllu7m5qyVOLKU6E1oCu9mRWhfNvFJEQBFViRAVNgJDxco2z3j8bOKXAYYgVoKDFgdbUjZaoV1IgiYbkjCxVkdjwkkry3EJrxFCDLKx7c4kTXncZZ20RDkt88PhgwcA2CAlBlW1pJrUzGrF8eQCjBNytpSsMYrmfCJYFrVtKnN5fP84n4iCSDCg5YOypmnYXu9u5kP9q9/87fKEEwoiT9PV6XAIbzUFWIMpAUG3NZHzpKJDwwYvOgn2QOcVqtYyQxIrD+FZ7vyBIP3s8Z/5y/Oon0PmeqGIi2mQpHkptc7VKTjFt1+9+3f/dt5e/6uXX16XWKZxt/hhN+0KAKm+UR9gMIJe5/f7p/RGrq6uX7+5ihr7p5qHtkyk1bCQFNWr3VVEOhwe6NUShnEYhoGlTTRTyikNGS3FqAKo6nazLaWI6PF4fHzaP3543G6u5AYA3P3p8dFSComlLKWUpS4wtTx4WupS5sOc1HbbrYUuhxOBIEMlmaUhXV3tbMhmJiqjsLKCeHX34k9/9osEHWV4uv8w7w8q6WZ3/Yuf/XxEGizDI6cUx7rZTsPubjttaizL6bgMY1ztllKXKFDkcdwfjwE9npZXr14/PT0e9nOylKf08P7+7ddffbh/vLm6e/Hy9ZizQrwUlHx1uxmGpI8fxs1Gkh6Op6TYL1jspBjuXtxE+BEHBsZxFB0PR7+vT8uxNKtSNRNpBXdoecAGBQ0i9IhLO+thYnUu4VwJo3SecBHZP1pj30/pXXKKjrNXiiptzBuxJLJqMpiIARoEHR4SIew1SOezQJpUsfpCYasKoYBnQN+jOgC6r6AAKjCzKKpQ6flgiqhIz0at2L5rJJd4BnIuY/z0uVUCLQw3KNC9W4gklRWYS9cQms9d7bW/bn/p8GZV5S4PVV3FQlFRAAI55+gb7u1SQScKcvYDEbEGHTSdqiXkm8DgdACMS4/QTtqIz1kpW90DKf2hiKY2Nu2iR5dnlsVLF7PmbRSGFoQC0BBqyFq6AyLQMhfP+saqlUGAQK8DUm2JKCLcqSFwrAz2Y5WEF0E2SIn2XCtcRCO6DW2JPOuznXaACl0Dr/S4TqqpmXmlaVC1mVQSbaBTASoF0soERQViXUCWqOFArPD1UzYmH2tYZ3bwkf4UBOP8XMt8auwTTTtUbQumMboQX8sXvhcXCGuVaM1qzoVfH9Gzzn+7uWkvHYRgiRVhRDtFrHaC9V7bxOoqCv4g1F95MS/XbAv2a/lFT0oKIQjQpHsoEYChDH0+hwKiYqYiDI+uEAhDAVBNNQOCPKRpMxxKsoFT0mA4QwfdTtvNtEWIuj18/SGCd8MtlMtplll5Ah2yUx1NKqRIFrsbN4MOPsAXn+clqRkRZBJBOKHJ9LPP7/xUl6dlORYnJSU1k5SJKDrboMs+pl26/fnNyy9u89bmZZnr03bK0zQk1Sg4HZf94/54XNSRdQABVzie6n45lulqQBpPp+F0mjXMCZNsQ/7wbq+cF/ioExyqg9qCEWlMaZem3ZDGHOGiomrzXJ8Ox9PT4rOrNLzeCJM859yIWhxESjbJJEkWLad9jYWqkTcpmRXHNBo1Kmul0+TqajfkJF6Pp4N73W4nNboXEBFRfGlaTMoqCCHvdnd3t7cGffubr99+9XV5ClQ0HcRCuzELRXyNLOwLen0hACRWb6gtGFCjOZmnp+Py9vT6j2+PeljKQqAsFTXNSzkeTss8F/Ms6WpzNeXN4XFfazCgk26HjSQ+7Z8e338YMFkahmnIm2G8uakW+8P+dFxqcVXLeYjFUVDh4qIAQhiN5VEICWiAgHv0HQbPJofnwCkX1iEEIQpQVLsNXBpqAHo22o888HOkWW1UQNH1MirSiUZPxa+XZi+WxxrZmmmamQBBeHhEQCCWc8oCEq26gCTFACWoQqrIqjJypeurHNQiA6SVE0fEGoqhjYGB7gRgah/7FhCgQqAq5FrEKcD5QVU7Wu6DfAbeq6NiJ2qhXIPNx46KpGp/cQnbOzJpGoCqqlLRPDNWWI7AuQT1PLlywSI/Thg/qxnSyhPWxMZ5MXysdfyBxz/52R9Ad59iu9/3VP9fHD94J/8iAQs/9CTfh7lc9awVUnyvVPKfOrpQ/Y8rX1zXz3m1MrzV7QgcARUG6rKYZne36DIWJVYdtttsq5N3d5NBRTXJMNCYCG/7zSQlTVDTthBzzq18XVWmaSAQ3gtVAKiJpYSFhoQqFEQE3cMZ1RGd1+qqqokK4c5eIiSirZ6/26kRyUXEV3ki3AWksIGYLo8KVCSkI7k2JIKeZIMqJUK7yxGFS6hSzHoykkrGNE1RHB5enZVlrixgVUTA13mV8CQs0AwmIIUNSbMMOg7TsLna5NEWnz88fDgejy41WTK1vjPOEGANl4AmhQohhZ6GJHO33ugQENQASYMkNO0P3jIOIHQVGyCESmojIyJnh4LGVyumaZOyHWIvWWotTUZXiIos7t1zt1AZznBGsEHPVThKmkAE6I64oP382GE1z0dExIW22+0Q0QvlPzKTpnDhIkF6XtqdBnaytNJBcGVPZzDaSYCsEbF75lWkcHe4k1SRWEp1ZqjABPDjXPezLAIy6CGUkcYwSYJ0e7V73D9B90FP41DnhcHa0h2O6s4IVZF1J28fhA6B1wdAv/GzdyZXlLQ+lns0eaxjZkHbOqoQKBZfJKlkMTG3UE0UlmUph6KCrHkahmEY8qhIlKQ2KhO91CoutgJmjeILHO6uUEsSPYeNYUjjmHM2QIJRa63Va8FmzEny6Wl5/937qBkCCREg5yGbG9Pt7u56e/3tf3n/7/7yl9jjJItyIjUcrRQm4jlGiqw1kqConiNfn0k9c3dB1PNLkb4zKhidDH+fDH1ynPWx9eKX/PIcGrkG1NXBCiqihkdp2zP2H57288N/86c/ffn5Xc7DNGw5L4MNEOaM7UZVsqot82m/n0vFshwZw243vPn8OuXjYS7HY4XmaTOapVLDVHd3t8AmJS/zh91uu91ucs5uVQSmGIaUBxugZPVSnZEsWbJSyjzPp3l+2j8dDovwdDgcNtMmpWQpqWog3KMs5bQcLQ3ceJSaoWmzzZaYaWFK0WSVPnsRU8upRjzc31Ow2e3G7TSmfDqdotS73dXd7vrl9YtYynI81cLB8ud3b6IUzoHmxgh4BFlP81xOtS7VowQXcva4vbndbKYqkuvCRzMbHj48PT093l7fvBhvP9w/PLy/f//dfTkUoZFyNU3LZgeRQVMe0zyfVGTMyave7jZRj5oWFU7jcJyfKF4jkpU0bsbdlB/mI8p5mkXUzEKdbb8YzqtF2h7S5tZwVr3XNE8wyCaWNnRGwRlCdXF1FUefHR/XXCYusNeKwftidAAGSZCUdFBJggwaQwBESETPMuNSf3lm4uvy7XWuTd7uAL7bSIuD7rW5HzNJlubm2dkfs6MRgE4AulazUD8i/Rce9ROzokhLd3+knpCQtl96LVRZCcCFXgyItO1pTXqTJmDJ9xBaj+Q99H9UfiWyZk7OUWV1qO1HRKz1NNrqlgLQ5l/OGd3fAabkfOLnklACAVEBJQhtyh6bfMdV+QyRtci2PzFb/VW7VzVJKkJRreHR6tdjpQi9UOyZwj0TujZf3vatBRFQdXc2NnaGOs9hsX2I7OVAay1093J95rvTFUmqF+J9W+4tA9gWZZ8dUwPETBqwE5Gm4fVRb2KXoA+xiiSA6nAPJ2OlJdoDN56tDitv/CjD3h+i+26yZzk7DA4SHqK9iEKV5wUWcTbP1VQvypqIYRjY9ues247IXq7WysUbqKCu7iIA5Rm9rHseiehcdBWb1pv+XiHnP+t4xgbrj1jxQwDslZsiGlRpcioVMGFSaKiCwS6UAxBMuzENFgzNhgGwoEBNxyFTAVOFHZ9O47R5efXy62++2U1XV5uNZk2wjWyRKAg/+onzzXg7pmHcDGVZBk1urCLB8OJ1vyTJacyIqFHB+uLLq+VhfkSdC6NClaGhozFQPKjEhLuf3Pz8L760Qf/zr/7+tJSULI1Wfb7ZvHo87E+Px1h8qyOhUWNZ5mxjyjbXshzmZZmP5VCk1Jin6w2NUChlPgA1jrFMFoOlZMN2q4DbYMNuGjYpDB41apCy7Ovx4VibWiTYvb4G2IwL6FtKIShlAbDZbDZpCvH94XFZasxwRiACKD7fbl+UWNwdgaQ6DHk7jgYX9aVgHHP4UnzBCDXUUgDkQYdhkKy78frF7m4zbI7vj1/95u3D/ZwKlILKCMBDRJOkANoOsVW9gmr7zbn2qr1oxU+6kiABgYrlkYxYylLqEorT8TDE1fFp3j+dYubMReNpoxsN9VKzTbvt9u7m7vbmtmDZHPd1Agq81FLKguXq9ZUlzsu8LE977pdjndJgMESLDwyHVLAiAtpcRXQBpLmg7qBV13DcbfaMx1r46yBfoRQBaqHIc0jRNYV+PhvWGH9ULnUAACAASURBVNfN6RyODaYZF1sIz3rQD1ngOXDh/ELVxED2Qukk1shv21wROLsViATQkvAigkKyB/m2XVq6z4vOAFpE0lb4fJZOgqiwrbWgzHMtCwhCtec9zpqDibWSFLaiGYId2/PyKQUSvZVCjxHP9AxtZwwYbAmk5xFaVbe2ydDUxERMA+EMhngvURRUINao1yEEn4HCGWSvoOs5NslHkKO9YcUz/n1p5fc8zrjufLl//G28qBP6XW/7r+T4FwlYZ1PhhaB4NoxPhuCyiur3v0RbV2cBCxfje37RkflK588WRzLqWrapaMIyvDX4qeoaYDIL0eoVAY+otYqIe69odHh1N6wgwVIR0oBskkRUIyqJISkFtS6qMo5DRCwFHkt4Q1dqomoioVFYa/FKeNAZ7ioqoArE1LKKCgRV1SRcRFQFrcxGYV364Lr3oVkWcdazWyT3PhHrdHS0xlY3JiLCToXp7lSi7dxCtGIhUVUnaSYa4WUunB1OiRBPRkVYMGp1rDlUgwo8KOGoUbXgyZ92t1fb7XZMo5nN4+zutW3tE1BJDVcPRCVazWn7Ixyz18Zz4ACjBCCt1Qm79AanrrRF1iwkgZ7l7p5RTaVlIMTVJMIt2TSOm6tJCitcrQcCoURQ1XvnjnABw0lW1ooVzLZlkDSBrN0tIhhrLY2sO0qeyUsTGi5x+XnTH7CSvWcGeEbYOIPu7mebqbXlzY/J3LriuQLRjyULABDt3bjYNnkthR7hLkaHVAKAH071UGxJgLQmJ+5enOEU0Zvrm/WGMeRc5wWtriuUQPGikCRZKNHZZdP9os1c980iPT0irf3V+oQkTNaHiz6Va9Rs0QhqCpyWedBsOcGgSXPKlowepZSIamZ5tDQYNYgAvCnRhYW2NMJrCkc9LodaQ4iUEhEiGEeoyDgO4zioQRVtW28DaJvdpCLlGKc9krqYSggj0pi205QwvHzxqhb+6u9/83f/+TdQeEkmeT7W6pGdLUvYOGNLcclKFAn0hj3PK0J6sxIIWhmNdga7rosueKHVx19KExeHmfVFdyFcEJ/63+87ZAHKUlhBJ1ShE+qMI96/ff/5Y3795bZyBLYRXtxrdYEMQx6GQYXzSd98llXq09N9skl1yBlxXPb7SskQw1JPp6opZxNLDmAYhu12M40TAPeah2EY0pCTmShXmThQtYpLrbWU6l5FZBxFDcuyjHncbrevXr0ieSzHYJyWAwpMdcrjJg/DOI5pEshpPyfJ07S53lznzVQjTmUZOf7bf/OXeczDOI2babu7msbdkPJunByWKFrixdXt9sUXc/HjfDRIeEhQhYBsh6kGH58+fP3t2w/37wDKmIvy/sPD/rj/yR/95PruRkRynm5vXxJwZ11qLTWCLD7mPKR8Oh4eP3y4vb57efviendzKPMwjlV9O000bIaRUV6/fJFzWryKMLx4FIgXL/PyIFGqeJqGNMy1eoRHZZx1CGm+i0BvvyQiLZDIeRdXV86bQsq2LvvyWD1Y2wex7mB45pkr9GmLRygQKPSs13QMHoBmoEW6bEiCLKERQmk9d8SbV5c1OYzOpp9Xa68c5nNmgiu0gKiSKyzRYBNxeruAINrurnPxmQij1Yo0FnGBc88whuRqRx8ZSLMm+eTuoOjbqbqcwmcS8ZGBrtjURMTd0dJdl9qZrB/ERUrgnJA4n0FW1QIEnlvbRYSoSg/5vXQpICoqeL7S8yyuUynnECbnq5w9E0WoChLWmg2IaI83PSEddMjF7Zki+mb5LkiqGJTWdvldbJlcqwCfAdyK6M+BrYH785bCVR3tnSlJUOIsPMlFYP1k2J9rn3sfNX1uZtZFota18VLAAleV8TwXEHEGuZay9c1zItY2MUr32a0laF9XAVBXwIC1Jut8b3IhRqJDgrUVBunnHeldJJMeR1RUzlX2IiLUXoXSknjof0XLdPJi7LlWKbQdj4y1MjHWsLHeEwVA6jbS7/Iy+dRvW0Xl04H/ZxwfEYeeYl17wWmrqFQxwARGWosqimRd25KuevTFbLi626WUlrIc/XQsh8NysCLuKY9XORsEtfphv49rXm135aomSeUwK+3F7au3X31NdTV48bqp9lp3m+vTZtk/PB5Px/3jIWb1BTawnqjuGw1jylO6ud7tPzwkse11CuDdB8TscEcUZGACMqeM65eZUudadXBjSZrGyUzHx++ePnz3+HR/SirDpIR5DToCCKG4IKC0MvvxOEMjOyPoKEu4JDCAitkrTCYbck4RLkL3pdSotS6lVA9Qlr3HTKjqMECYUipVQxwiqpYlaTaCpSwQ7HY7JC4+OyoVh1wGGdJoIjBmmEAY4ZWleI1qJjElhQQQRD2ejiHLdmcAj8dgQEWGMZnal6++mGyzPC0fvnv/eH+wpvUEwuG1SogYVA0SLlUASJybR53xb7OLMytp61FFe8PQDFSklKJEwEVQahlDfen77jFjGZeENE3T1XQ7pkFFluPywEeZoGZXVzs/xcO8fzoeo+BVLZqSmkFQ3Wv1WlrnE4hIOFjJaJPFtjNezwCvmdc5lbvC/tUEzlzgOQCoqvbn6w0cV0+7muk51osGQ6GXykWzT+OFPHTB3C/Dk5xR5WqD7YiI1pGuu3G1ZGZqQZAu7OiSHhChUJBEeu0YvNcBtL53hMoKXINcPWArGTvLWdEQSU65FUteqgc9x9B6Ta6Bg2RrutITVBFm+cK1rBUeilU3YJDadnSvw46Vk6SUVvGrXVFEoSZru8nGz9VbLQLR9rgiABeh9o1B53FdnfD6UlQ1wokOmNrpVbV6lfU4z0hDNeeF/nv60svj9//UJ1jlv+bjDxew2gQ3XakJTHKx3a+953cNhPxuee/7RzvhWVjFOp3PKkHbOfsJmFyp76ocrJ4gC4W1Vimo8Aaz4WgKfZGSUk7ZAlhqLHP1WrWZnMqPvvziVJcCjyS0WLxWr1Grl9YGyFS1d3u1JEmMQQUVtdad7bz4cjyVuaA0VKPw8M4rmK0p9xrJGzJO1h5SxnGUKqwM94pWZd1GO85gU+T5YVvesVt1L/DqdnRmwpDzrrfejpRAqKuIhJioQA+Ho5+qH4s4EtRkMM2kFK/1VHuDKm0yhtt5i3BFJMS83M/vDvvD5noaNhnGaRhrsnk+uTuMDFQWPm+S1lb/BVgNT0NOmn2uvjhr778gySBSaulJ99T0QVFtKDkiAErbB6SkmkkSj4qElPNSlt3NaMnGcSgyIU4AmWmirREWRymIUt2DpCMEZ9y5rvm2INFdH9HgWgPbKghcBKW2ClejUBWyt5poG+JW9ewSZ7N7VUjT9dmacwtWNNl0IYkO5yBggNrkxaARbKmDRnaiwbiUx5TGYRhb8Vqp4UtRVZAVVSoYEaeiReLY0j6koBTUGjwth2V59eY1gzlnj9hcT4d5n/KQx5THLMrsuTW4bbbt7l4rWp+INTOuKq31W5ugZ/TcdrkH+oaYy3TamVUQGhFJHQilGtXEIMOY02BePcRRtPjy7cMRC6CwDbZXGYPQQgebps3T+z0AMYjBa10cSrgvpS7b7eb66gqIlExVzSBKCTWznEOFcKaUc6N+AZEEwgOscbXZbjbDF28+e/vrb/7y3/zfb38DNcSSkFI8ndKQIxY+b/3pDnC1wjMKWdnLWmvXaLemJEDL7bOBg5XS4dyx5Yfc5oWOuupkQNtiEivTvdRVeZGEgKCWEChFBZbzwKwFT7/8T3+9eTP/6Mf/Wmm329vv7r89nQ6HucxLvb6SlFIebNoOIi4CRCHTOI4311N1HI5Px2NZyneHIx72uLnSx01KicnqdjJTBXA8HveHw7WZaIZgWeZSHaCKeNT5FAgJMudhnDbTdhuF2fJm2E7TNI1TzhkADB5OxLSbTG2Th+203Ww2SVJZqqnmnHMeXr18dX17u5yW/Xy0k/3yb/7DdrtTy3mc7u7ufvqTn93e3BoxqB0f9qdvHsrt3Wdv3kzbG68VID1AmNg4bvZeynx6/PDw7dtvvnv/7W4zpavtoy9ffffN22/e/uabt2pye3P7+eef/9GPf3zcP7357IsxTwqWU31xezduhs2wOz4dh3Fzd3UzbLdq6VjmD4f9t++/Vco0TsOgp1mutyPAp+Myn/bv3/u4y3lMT8flu3f3y+k+63Ycd69fv358/+RzqVyChLiyq8Zc5eLWr6d1GRdt+8mbdrza6kXbUZ5hZpNjHL3d0sfL7gyDydZ0qn9zgOKySzgkqya1wZC1dagh4GzG39IsWEnIKqzF8730GvvzEm+qsJ71tXDnmdVr6+/O8N4lRFZE0JmOdGrfu7MTLPRAB7/rfnAgn13RxYP0HUwfJ0671NOKkCiircLr+0BIAFFtCIpk0OmMH7Tk53nQHxj0VkKMNasvWIM+Qai0rWGt/rMnpwTi4WcodXFnorImi/vpz/vd2FTwVs/UuuRKQIOi624xAQXemKfgnK5gyxy23Xw1xOHea9S0JdzNNKkkdcYnVWEN6dV151wXVs/Qbi2LTqYovXYZ0QOwPB/rYlopQSN4bVbOdetYp2995H4VOAMwMw8XIBw9pbTeAS8WFQCBgqjhVM1m0doGPNsTgF5LpWKrLPixjVzIaehV84rKaF+q4ERAx3QGdW0c+j6gVUVWrJVgrV5lzY0JZJ5n4Ll9W8vfSN+PCHneY3SWcXsVGwAZWpyStUpYW1czEQh7d40+DOcn+jRhckHqvvf/XBl+P8G6y756dHNrbTezUSOMrRxbs1IYZDZQxL0liHqoNFMbVCjz6RQHxwyfiPXbnyIYXsvsX/39N7s395vt1Y9//KW4sOLN689up2tR0YSUxQb96Zc/Hcccv4jvvvuunvjbX//2q19/+9uvvkKAjmo8nRbFIhix23z++Wcvru9udzd0fXzcv//w9HRYPnzYW5Jxk6B1dzMOo9zv3wXqF1+8Ps3z4XgU0Ve3L//P/+OXIBRSnYf9KUlOSKqbWr1G+0IpE6imGIax+ByOyjL7CUVMIaNQhXO4eyhzEihKzLLANYWEe9SC6sACUMZpm21TluV4nJeyIGiarXWkFhGT6+3OrY7TdCqH4lWSXN1sdzdZ3DSMwOZqKH6qsZRaSvVSUHkUukluXcWXZX58mjdD2myGaBpahSVJ2RRytdvxxIfvHv7hH96WPXaW5qWyEhFGExjbV1ekVsLkzSNdIJZmMD23tyb32k+KiprRPCosJREZcs6bRAfvGSUSECYhTJKyTcOQb3a3cH711W/3j1Uzrl9lZFwN1znlYUi5ChMfHz9MugOZUzZYxHI6zeXxhAJqRKEU0VjVK5emeasAJrXW6GIsCfRuyqspXIhJ3Q3KyhZUYPaRluHnBk3dIZLa2cmKKp+Tx2Wu8r1dUJfwr/17abvnmym1DClLT/ZEb6nuAW87imrA1w0YIWJirRKtbfBYz8qWMVAEevvmiHO8bhEgovXDUclKQc65urN9HVVr2w5AiSSmuuYHovntaC2x0B/8XOGFZ71P1qFrTVVwxuPStxYKgxHYpOTVAXpEY5qioqZUiuG89FQloB8VFTAYcvbGn8odPHN2MTOFwXtJSZKkoqf5hDUxsV5CZe3MeP5iDfxzjvP8/iMfvFwDq+f/gebxf5h89i8/flBN+gMFrE7d1wqsTph/EKj90G9+nyE4z9lHsut63TMW6QkgYP36Fqx7oFfTbR+BmBggVK8g3KMgWd+tY2hdxdGEU1WtISJC0At8rVrQZEkyIUXcGe7FoyJqIRJyNmFgKa6qmiznIRsqfa5LqS4ET4wjMUNcpBlwab0/AMBTgEVo7ZsITZKqakoqKcaQJFEb/iMJaM9DUoIKWmuzSV8zfezV+yGiupZQEqC1Bu69THJtgND5i5DavviJotDT8YCFqJCAqJnlxBxVlqVgIRywM4uACy1EVKmISjqxx/J4Wh7mzdVmuh1tNBUzzaZp4RzSPJGSSmZBFmm97YOQYcpJtAzzfHSvkGB4AEaGSIiCELW+e6GlmaMiwhloveShkMxGYfJoliW8AChLieCY8+l4YETWLj+JJc/BWl3cW24/2ndqnD14SxXQxUGtLYPSXB/VrKF0jd40pW0l6X1GBOhN0dA6/7UpJ5TSaGF/d3P/jtYCUlp1NroA2dSwZnFNfQxSqAQJddWqElSqJIGBzorSxX5KEjEKBN50UaINfri6C8NYMwq5QBXJUqmlt1ozhGGei8ORYCo6CgIa0BAJikoSFYMjvEb7FspmMu3bO7CWdPd6oxaA2fp6QKhtp4fSQKICCm3fwiG9JVSvy1BKavuPECXUTCBZhmHUKU0KMVFfapkX1xiu8u52JwmnOFbUNBne7QGY5TFPzlpxEiUFNIRWURUNMdHka2bPRWCqOeuyr1dDygkQSGQFED6aMArdX119lnF7/O7+7d8Dj+DYihoXYjbNIXPvbdU9YONYPcPWsAWFEr2hCOT8/YH/L2tvtiTbclyJLXeP2ENm1nDOuQNwQRBEy6S2ptR604O+Wc960S9ILZOZTC1STTYBAsSdzlBDDntHhLvrwWNn1b0gCZDgtnvL6lRVZu4hBvfly9cKSkfwsqG9Z4N6fE/9Lr6yltjWychBpEf/AMgiT4Nyr1RSZ0p3zIEj9Nl2eeEcosTe+zaEfXz4dn3/u3U5cuZboYWdamllKeuC3VCsNpAPLI9Pp91umKZ5GnbTOJcMI7mstq7HVrCcgQsqmZUyzRj3idxaKeuahP281Gmy2kjVWlUyTYmTiLGrGtwkp2makRKrE2TM45iHzMmZn9aLELsqc97vb/eANmX3hJQ8rWu5nC61aq0tcQIDQkhwhQpoPz2uy7I8zONumCcQEvM0TPs0rjKU5xMnMoKA5jwLRk5ubiYJyB8+Pqwoz8/Py7pAWMaBp5yNdzeH/Xpxx9PzszbcHG6HPFUqb2/ficrp6Xk9LTdf7oecRwzLvCbJ0zQRU3MdmNj09PQEkXmevJrX5mauRVtZ16XSMsyfESVyKSuez9gP591wu7u9ocbP/gwp7oBT7F/dzyPyPIVMor1e6BK832uPgxFfax4ONvaQi9r+IIVtnyNYTQ29kzi24z6qGR6bEXdMI9ZqSkQJlIiFwBSUAnelEITehr2QiMu1AOMuDnZv22wBdeM2IidobxIjdrboRKfoGNz6pJAk2HJwJzMN6J+JhMHBTiU2t4gqGHDQi/MIsBVnYwYGp5tCdugFyvMoO/cXEWHT7ZKr3qxe0TgmF+YkTugetcwuji0+d2C7ywAzQM2U3IlsU7yzDl6HREgv44VKipMSCUdlzvuFd1AJ3vEN6XXyK7jSEQ7rOywAswA4YkO73oouCky+RWEbXtW1Dhnc70Rom4RZnRs56dZUQsRIiPRYkrBQK2oce2HfCdkAMmZYh1QdXRLF3SligSQilIybG0IWAo4uMBmVqVjEHDDecJctQmAmATH1/rlXflHYrvUqFWq9zkm9+QRhH8MexgjdZSXqVLRRGg0xm0B9o+7abYD36LvHcdhU52L0bbAvgZiEQOrNjVy7qkJy9qsELQWKSVEGcOLEqcd8tNHGrsPUEf4nHR7mTqnoQWBHuWzL9wJSfHm1bB1QJNHKHqIdPR4nonDR6ps/Nixru5geyhARBE4U2Nl2E6JsdlXjusKx7rbxswlkzgCbBf1KQEJ5TOaq2pzIbUOvpKd8l7Jm9tJaM2XncBDjmXw0J1+eLm1VOzWMeHfz+Z//5Bc///nPHx8e/+Zv/ub9bz9cni5mbqggV66/+au/j1PKafjplz95O72Vt2ls6el0elwvzZaBRwCltqfj8/n8XLAWrInS0kqTknY+s1zWc2EyrmPyy7qeyuOQRx4k+ZgbWtW2Ak8YdinnZBVtaSwp5wzBwGbkzdalqS46zizqZqBmMHjzNOalaE6ScjLXVqyQRotl+DMJWR5GUpg1bc0NxAM8W0NtZmgwgbgznLyhOYHY5914c3dnqS7redVL85JyyswQd7SY+lpK01pLqxUg7PI4D8M0Do2LkS+XSwdyE1w5jSknTil5OKQv0JMuD6U+g5TcqC0QSKaBiM1CeMWJLSikRDFQvNf/7RXqCvTCiDuYmLP6Kpw8sS015URMKdEwZ0b6+PWC1dmZmUrSadiVUutaa9G21tOx4QQMeOSKBN8vN4dh3B2Mk3o7PazWBCBeGe68WllXPSlWOBNqjx+x1RQiwQwcKtzPQRu4swmKMG2UMXRpvb7AehTCCSBKQh7pGsxAtin6BSTWpcn52tdL20pNTEtd2a+dwtwBLo7Ke1RDf5hyB8NtOzmDRiujxGJD1tCaq7q61b5g9rJCTyeZyZ3FyUjiEwgSYT+5utvVI5uInF1NiXmzERQIb7kUbNvQr9vjVjTqDCgnEnphpjp587qtPETevdvIwYYA3/u+aMQOV5DxxgvZEmQyQKmbexEEYDi7E6JCxojCvIGIo5mHnN071dkjw+mEAvR1kfo590aTLWXk69dN2Iy2xu9t/dxu1Svo49VxbYfsc+GPQFpeQzSvX/svFXr6gx/xRyI/f/B9Xh9/LID1ow9+DVfR1tz3I5iJtuNHP8cfupJAxJi5W1aHv+b2nq+pdPHHqtpzuD7pr0gqNl0dJ2c2dkZUzs1V2FMaiBmCPKei1eGSSBIRuTinKRctV79kVDw+PHpmJFRqq1cNz94cbsVSqnk1rcogGXzigUXgFMbQdWn1WPTSoCCCOHkza91xW7upjcLMG5LlhDA0ZhIYKVJYCipCDEqIEgfhxROMu0GNRtRGPQxxV0YiQKEGd3JnhxA5Wl03sJw4CcRi3WOQhJmQOprDogjOMAoONzywJPCUJLOrq6uTkfZMIPyh27Nyhg+ERmuprSjPkmbJu2EYU8pCfFFr5smdXbM3cWEwmMTcIJCRMEhL0KVZJapdiHV7ui4sBJB5eEFY6gorBS2L5DGDvJRLI52HfRpYndZLfXz6dHtzM91N3336ppQyD6OZJxlyktpVUQMC/SFe3ykIjYhBApgGKM+hWEh5hDEZuzcNanRn9oWQu0dE7w5lAYhUu6mku4eHzkY7ct/KAJEJ9pRnE3QAARRO6gpF6vZURBWk1qNRFwYrNNhqkiVKmNWciE0VwS8QqLorWATGVh2tsbs4j3m0dg5aY/U68PD4+IQBJsojGxXSOLWmpjwkScwiBGgptSlCZ1OA5hxFU3QyhUGjzh9pCrsAZFAzciXAoQBRSokzzLW59hA9OQsPc+SDcNeBR6ugxPXUSL1LjSlLzZabFrdGnMiMLqVYUQjQwEhTnpupiyA1jGpe1etxreOAQYaUBTDX8PjlRsZOp/NSJrVGWOAiTNC2jvc5s5fl9Oc/++X73y7f/eqEZ4DZKyC11E8Yob7Mo7iFo0qMpThTv273G4HBCAaWLirsZHBhtzCxioHR8wRsXPn+48jqt0pcHyfKRuG2HPm+kTOZBBJh7gRzMgqNEcCNNSp4IJY0RTJsZqUtwklkMLb3361//f9889/9x7dtXcY87KebpnJ+vmjVuqzDmKZxr7PP4zgOwzAMYxoEZnta7rxVd+V5WNZ91Ybbw+7t5/vbm7yW43o5nqS9eXN/Oq8il6UambnrOKRxSCmFUAkxg7J4JiU2kWGYJA1grs1bbW0trkqG3TTf3Ny72qIXV9XFqrdlWU/HszvWUsyMhKvW/WF/e3+4f3v/3C7DMLkPz+vpd998fdgdyHz6/EunIY95zm8EcHY3jLxrRjLuKHvRtrbTw+noiYoqshymW8yyop3KstR12k3abCzT6Xx+ejg+fnjKnMeUamoVTVsTTwNpmnc3857ApbVS1tKaMc/DsB930343z7vj6TERq7Uh8ZjNKCv7cl4pDa3CFDA0xVrKfqTbu1tTO55WL9rCJtNc+4xzV8DASVptZhbi2OpgJW+OBjQTJzdArRtzk3CQaXpgSthGs5uCyYxB4o6e8XIwc81hRokTJ5Gg0FhySnDG5j9gFiRThhCMg0QDoURgU0XUySgYFkbEZFEjJQDkJC5h4AuAecOFExikV90uM2YOMNwiR+6LO0Q4XAVUm4VIMF+JVAB6KoQeXXTabZ+zTFc20Gash9eJFDs1Q+aEXkSAaRA4oUCKOBgwmJE7b01e22drUw59wkhPIsSGdQAbXQidCWC3YIzR1u5m5M27iKNFIafDfeRgZyYWTkoV1KKc1ov2hszJyUJNP/pzyOEu8aGB17iacGKhjk2hd0ywpWgQ6e0g2nD1EWcKtAhOqmbatoxJqyrsuhIi4nhQ97siITLALO5v7NKttfD0YyGBWCIns9bgMINSAymFzTwIqjAiYldzNt66RiP5IOAK2ZJtaBwioQGFBVuXu3RcvVXgBOgLWzjgluBaE7MAHe+EuZCwk0HtRQEnsg34BkhGokrb7hD6E9f2V21o1XoMBnCDh4G2OZiRnEUicgs8SWHY2qtCyuBKRiBiv1aYwsGPhWI4GSJYie0aYCcNOiGiq511a8GMTLDfySAMm2k8Rifu1oBdpsYBIHEfo5SIEingFj1/bl2T6WX/wlamJReE4RkQ9C5mZTc2EjJygx2mXVP4qkmSgjPAg8BgatV03O+dHK0OQ5Ys4IoEmtxy2w3z918/0yIHuv2zn/+cidKan39z/PjNx/e//ng8PfmR3L1B4049f/M7SWDADOffXX76+U+Y6af3P91NFz9+ev/hH/SCaUw8pUbVkz3j2Wsj41aqNVagyMoHUObW1qPWlFl2g4E+fHxOMgzDHm7vv3uGgC7wQgK26l5hzThxyqLcQDwzNzUy0+W83+9zHlety2WF8Dzs0phTStpsvZSllEWVsyXh1mwehmG311XbuggYWZgGXbGWAnIeBrAJxSC1Yi0lkimlAx8+353qsXEpvqgW9VSswjyllJOQurnCaeBRMjljHIZxGKdpXpnzblraZb5hc1MyJU85D9MA47aCVT7+7kFP7fTxRBWJpVwIJsSZaGTnGLpBVnJrxnDrKNnoogAAIABJREFUthJGThyFdI4Cs6EXImOoMPG61GEYJadKdZjGdOIKzSlNw/jt5cEq4CwT5+z7w83xdLJmrbTT0xEKGkBMXNwqjijjSLvdfqR0Oh7bqR6fz8ySksCMlfW86gIoW3U4hypwX9NIHUZbORk1pDQ4tCkD1CZAMksSjWLlhraD6RrouZp1Sy+Gg8xYQ8U5qsKkHeVCDze7ITjHgiVdS7pDZebKAG3VnWh5NrWucnjFSNzdfciDq6k1Fo7GvWoFLErWIe9Y5wP0jl1AhDMRoyoiCyBwKMJGv91WUqNeXuKA1biThYWIqZmqqbraFQWKAi5FfGpd0CrKDcJXgosR6lo6DggQUXJig6tz6OdtbrUUzU/aHwZALGhWHUHTAuDM8ASVRnLVpgcTuTHHVkQkwmYgMVKjLqjpXfyrn3NE68E0j+W4a9AEzm9wCnwyShVmwS5Tb7iyvmjbbV5hWtfjCpL4VQfth7/FD6GYKyr0mhh05ej9m0BO8TUa1P7IN/x9rOoKKL3+/t/AhfC1FyHRS6uC/9MktD/m8FfHj37++hlsn/tiRXS92l4rDUpDTF937bpUmyiWGjlJlpxY4ebWVIlJOOcMDKnV1nUEGcfTkcfEA2tyo8gDCJIIBLV2aV4BR4O76opChVychQ/DrE+rq0GBhh4uK0BIKaWcGlrTahWxXKgYZxENXxs0rUzsDrBF6wflBAm7pp7Ibk0fL0kuwM7moQLmL8T7bnnYPU4J6E0k5lB1eDNzNsAk0CtmitZra604aXMTgEBClEVGoHoLNMbgGlEshiGZa1sd1b2ZETOMEo8uBJmnWZIcH49NDcxmWqqREw2QxMQwLdpSyjzvRnhZm5s5iTDIoUyceHB3djCLmZXWCMySJOd6OiqQ50G1taZRBIiSr7nWVkIVH07rpXqzlIZxkHEYL8/hTQaHQ3irEFJv7oh2RUgUKSSw/k4k8DQkRdS4iND7z81D7cotOi3JrynPa+ychbbEKAhliM0gIkO/gr1bfI++khEQDs3RB+oKNTYQSYxtsoA4YWRu1RuLkLiThaGykQJkTuqahYdpAEi1RIemjGwcNoto2pZ1kZx4EBdrbl5RaqVGopxgoCGRMFgoCTsEW2144xkFBYFBTqrWZ2p0MTnCF3ODn2OpR9iWi3ovusLdNSepTZ0py5AomRMZlaWuSymXc0CucECAGzwvRxoo7YQnMWvMfUtQVWbaTROPblKWRYlotxvn3XTYTzeHnUNP5+daVgs9Exf1dj6v69nRQImZqQqs+HAjt/ubL958+Z//7//6q7/+DZQTj+aNPao0LgkibAR3N7oqj/Q9fqs2k3ddlL4pxbQEeYheRm9PoM1RkvYXNZY+woBuHHTd1CLfVjcJuRhP4RzTu4aD/ganXjKPj+hkFlVjDuEJMjfV5sQs+f2Hh//0f/5fX/3F/zzuaBznW2HK/PBwvpwvu3nez6NImoch58TMSTjlzFxL82min/30bp4O58u6LjUm1v4wTwOdzq2UlohaLWp4Oh7lfGZCzuw2RtG2QXNKOUtt7fl4dBqm/W3O42VdyrJ600TS1lqXEh0Ddzd3aci61sv5UtyZsJumw243TNPXX3/z/v13Hz5+T+zDlN7Md/u8v729m8b95XT++P37j5++/4ffTkkxQOxwt5vmd3fvkgsR1tIu5ZRY5nmfebiU9dPTp8P93dIWWfM4j565ermU9dv33z8+Pr55+/b8fAxs4XQ6fvfdt//xL/9HAUiROJU227AksKm32sq61qruTqBaqrq/ububbw7H8/n5+Vmp5SnnPMgodDkWs6qmrdbSyCEMKM71NLT5/vbN/bs3y1qeH56D1+e2bRAMJIJ5TxcdcA+jNmvuwas1D/5n328RTBLaqn5bQ1EsRNIDSguNKWxF0YAtBFFG58QRbzYqhmirVoebN0NnyfROBwQcowHP9L2MAEdi6dQXMw+bB+dOEHZE5RdMWpuH3zp7t/RmqDZ27lm8XXdL33rrOBq9jMx+L2gj6mWEPjcZru4ONWMODShcDWb0R1GMwaBgxATvW62Zw5o5K5tbqbWTewwAovxMTOGM/IMlg+x1w3nsImpBzex6iyAJQICsE6tfXrE1HXPXx2Li5NhquR5EdEsi2jcZjQ7ODvYYISTGetC1mV/FjXTzEBCnSL4omjmIhRjRAaRmau7aoT7v0Wyw+SBDNvRH7hyPwS3itmuftPe104NpYGFIr+G31QXrA11huGtvq4uDQ7sXKQUWHgGgdqEokBC7bI0oulUHHO5GhJA6Yb4Snpgo0kXatufr/nx9/P3mb15Y21h+DXOS/+CFRMIJiLkUuJO5kVnPc7dADtew293IyMi2SNAdm/X2Fih498lyuHNKoOsc2PCtLclSt41ltbEDYtBTz7gih9yuDO4UrTobxIiQeXZotAoFBAegQ7Hmvd+JnbrFbi+h/PjoF+vmyCEZQgwhSiKZjbWxcSYjb01r02aac86SiJgptWqqNuR5PuzNq6K69iItMipqrezZ4Pjy8y/e7t99dvj84f3Df/rf/4/npzMqwJjmYXkoESxxplg+N1ASv/v6+9/+/ffvbm9+8ctf3L67H+4Oa3t+Pj6R5DSyuX32bsqDGFlrpdXqyqDMadztdzzQ8rEsq2ZnovT0eHr88PzTz95+9ZN3Zbl8+N2jeCpnc1uyDACTU2nmrC6Ns8vIECaxPKb9fre/O1CSdjEYzpdlPszm1kwh4FGgDjVTlGYAhjwOaVyXxR2JU5pGmJQahn8waXlKSZJps2qDDHlIu8N0++aGiZe1gLKtshZ3q+51HFDLejFkSeva9rvDm/ubJLlUuyzLel7Y3Mgyy263r7U5jJhaaaKwPjoocXp6eL58OD18evLSoWxO7Ao1i5oDE3PmFiPHQK8m0NYLEQsnJ2ZYtEJQ1eauIDSvXBgzWitMMNVaypRGkFpo+oswC4HKUh4en4S4rRUrQEhZjGHeom0T0UevWJ8WOCC0mydJokV1NVTqpucv6E/vvwchOrqvwNArHAEO0Ka1GFSeDf5A7xEJbIdYL0UtbMXJzcgZW0UTDgpACFFAcgY7O3OPw4dhaK2Fx1gIxRmbN3dyemlGgWtvLPZt74nQM7y7us0Fw9xrKdEIHo13rptaRl/onBwCamoM8q7mZ24O860sGwnAhs9Q92/pOlNMVVvvng5uVFDLfrDOAle4zd3MAoWwHy3H6Gv1RnDpoopE1OOhvvlv5HPQFRgEAUKUWDJ1/ZPt43wToQ74h4UZbNSi7NOfMwNbe74Hm4GinMOdLmzbWO6whWtIrG5L/A8v+J87/AX3+APHFUh5DTNdf0V/MmHq9SnRH3Th+yPOM/7J/IJR/kkA1lVR8iVCeIX8/atP9/oO2B7G7//29fc/ujygM7x+jHwB7p4SWXLJwikTc/QBshvYFa1UI8AF8+DMkseUkljRVrRZb/xhcosadCwpTgSyanYxaLRVEtj1XD05JcrTMI1j6WauDYE7d5YiIhZKSM5mqnBAYbU1JmIMKYmIXhokRSAhTEkYwmCu5uGN/Woh7EUvEnYmV/JQIeIXqDXMrP2K1NKWKhPMQKrmTtpZ4MyISBfmquZwY+KRrEn4mEgSj3eAXdX4yIlEYExWumxKNavw5lqs6brf5znPq5S1nEEA5xCozBAR6XG/NiNmQ5aE0Zqbu6m6MDGzCHsEry0cIHtmDzawGLyWGuJUFtl4Sikl81abu4eyfmoNbuqqOljxNk+z6bKm2pomFgqHbDeKvsaoHhgLRM20mYPINWRyU85k6HZDpPBQoOxRoUOd1EGCASHK7w4OaZANsRHH1U+r33wmInFTDRWwiHNpG+OIVdvdEWaJDu9qzexOyj1ngpO6OSmbirgRKAncoQpxuHL2lHk3D7yflnS6LKsOLRT5vTkGmNllXYZxHMes7mVdeSBWamZW1INXvI2ozLlRdSUyELGzxy2KnY/A6lvdm6hjWOixpSFUw3tdAgQSJjMwnAnCqibCZKTNx2k8Xpany/N6KVoaqhOQU0o5V60goMK87W4Ph9t9Qflm/cYF5lrLCic2zpVdQS1N87gbdlPO8zDP054FBH5qD7VezMCE0uy0LGaM/TyOc1nO3rkhSCntd/tv/+Gb3333O6HRjV3ZkwNMpCISZsAdi2KYgoB0tSCgrY+XmIC2bXne7cx+mIBulZdr9hA/3hKZbcPeUE5/iYIQVDeOldW8t7z4NS/vSnM9PfEW/7jSUcwU0CkN331Yickd4zit1sYx7w8gYN4N8zzVUqZprHVtzXiaxnHIOZV2Zm45j/tDnnejUBqG4cP378t6uaiaLjkxi5eyiGBdTZulhP2eWk5NW1IK1fZ5GNdWPz0c11rv39huGmvVp0+PrZQp5bd379jgzaHWahVmERmGHKXO25ubm5ub/c1BRIj8fDlLkiTiZs/l+Zc//8XD0/P56XkahnHeHeZdWZePHz4m42TMd8REay2Xp3O7YBrHnIc8ZIMtdTWmpS5LXY2QMi9LO1/Op+VUWj0ej999/93lfNmP8+3+5un49Ob+3qoK0e3tAWy//u6/5DQhO7wsl2paJWWHiWpVzTkPKR+fTk9PT8hOVThL0QbQPM56qa06mU8ZZLDG2srz+pyHPOTxcLNTLet5rdoCVnF2Ek6gV41sQCjYeJDdtxAhKoGBRME44jwnJiiQe/dpjLjojNK2te7318diNSCNJEMWoSB1mYV+ZR+VvSu2Kwl1E0AKVSx1Iuo2G+6AM7GaW7NwC4QJOxPItkb8YIlZc2dDd/2I30fTQL9I22ZHLKUGBDzg7rpp614nUd+mqauzd6yXOKoE12CDmV4Z0r6EHFHgiE4Efx14U680E5iFg9R8rar2gJj7Co+tUEW+GQnTBiJEF4Q7QV5nRjCYG/uVTvaydriHoV5wX8L6UYOXB4OaS8x7jhqCx4bC4Ogo79dLG57RK4WBX0Wk7dEg0oGv0K1iMjdiJtvAMYAEFGyCuCYR6iBN+P4S9U93s64CGSOnX4p7CJxZRR5HYYKQuRHZC6gJA0XJXGgTe8KmXAaQQMz0CuTH42Fipw3xif+tU6EDFCK6BlQ/zhO6/tm2ZgcM5p3d15GqTcrt5dG8+uS+g8NMuxk1NjIFvVR4hBjSpwYTi0TrrMG3hk9cc4aX/SJmJ5ETgzSsiog82gL6XmFRy3A3Q9z6Dh5R1w4LkLE3CW+X4b1DjRnkFDRfRdQzkUQg1FS3zcYczeACQnhGx6OlV/jcq9nnjpySkznzJiMqTpDODbVqVluD81oL3KdhpCxOKoMcbvbPyyMR1rLUVjwlyhhGJrExT+/uP1vv62d3b1PLv/6bX3/4/pOe7G66wY6WZSnnihRjlUwd5taQw9pYkVKSITX13/7m63doX/67n/2Hv/z3/9+v/98HO6aKdsLPf3kfK2bwWMdxTvlwLvbwaUkZmQ+c/HI5L+vZKu5v9jeHNwRZz+X8fPHGUIbCSZiziFBiQ2vwarW2KkR5zm8+v7v9bKfAaT1fyqWyDmMyt6WsMAWYRPI0QJO2dd4dUmJ2Kee1laq1iadpyvDUxYuGhFuiDGhrrSj525vDzc3tMAyJuC71ctKUJNFuFi66DDnf3Ozb2p6fn6palmkad/O0T5RNl7ZeLpfz48MDMY9zvnmzH4as0LJUkDknYiLrmcmUpmN5auqU4NW1NZaQGW0amSV1xus2h/rEYZbadBPUZhYJhSYzC0om77JQVlRTGz5Hq+swJl65tVJL2e335XRx52HIEY05YcxDW5pF/7WiLSq7RApUQ1WjUo7n9XjJY66lJkpDHlPOK1f19mqikZsZ9No6dh3Q3icoDFf4G8wIUamY4U6ggJ8IbBu0EPu2ubXOpI7pQUy9o673bP+gyEEvU99FtpTfOaSmtujx+jX0ZeSKX/S9PmZuaE25sbBbAP3mJIDDmPp+vs1d6wv0ts8IX9sUmSwYVdhCBfRNrYsAwdzZTAnWmrpvAomdKua0LbM/SvPDfte2pfjVjQ9wXzmCnp6pdt1Hg1rrsfQ2sOCJGW5gCmeSlDgRJQZhU4nvQEeAFS9UHu/5UNSe/GVhoy7yFX3/0vczBvdgK1ZSkJmTb84rPV7BH3/8o7DJ6+NH8NYPB4BfH/2fjmH96N3+pS//Eab2+yf8JwFYrbU4P2YOGVR6pel+/Zh/xeE/JHb96PpfP57rH7xgOC/h3QuyGD9z9zRkCCSLpIRub2XkQhAGQCWm5WUpSTBPc0qDiRJWwEyVGhq7ubk4xOFBxiZvQAMaWKKxVys3KJBAO2u7tJ/3pxXrpRoZgyRnGGqtqvCiECdO0zhoQkWFNi0VgjxmZnG4k4J7CAsBwU3Vm5qqub6YxgIgQiLucjqxVoA4RVdb16bwBnJiYUEXhBdml0Ct3QzqrpqEwy68+8WJE1EaE5y0tVor3J0jFnLfCKGJmIQupyW6M0zckoMYq60P57JenCz5m88+v52+nN9//HCxImM2tOpVVXXB4W4niZigpZHpbpzGm9mdnh+Op9PZqru1S237ce/kay2J0zjMZr4uK6zMh4OprnWZ5+mwPyzreTmvai0PDMZa0KrVYq1AK9ShUrQ9Hi/6l//+lzwM7nA8M9MgQyt6Xs9Jck4JBm3WVIchk1OtxasqSUoDsyCLkQYvNfZZAY/TPoYyWYcCXAF/aYIlUzhaMWIKQV819Wp+VYMhoq6r4b1ovP083qGU2vt9rmGwBbTn5CARwNB75MlJDUxCQsw5r88Kgbs2rmMehpkHHmiCPjkRpDLR4GaN1NmRPI1p2E2ZXVM7ywkWfA00AqXGYE7CJgYnY1zda6Pth9iJet+aeCcS93naETzr0iocCbCZOZSoy65LFslSan3z7t6KP12epzw9L5fT+ycwYEAjh1fRVszZWEhrM8ZlPOdJXNqQs0kLPVFtrqWNMg4ysA+u9O2HT89LmWfsdnj7+duvfvaTz959cVlOD08PD5+epmk6n5Z6ITTFRLVchgE399Pdbvrplz99fPj08P2n08cj086aR8suCJzYjT2kXpgybQVEc3QaWuy1xMQRfLDBvG3SaMZZYmr1Ks915KCzKfACO/RfXOM7Fr6y3+C9gwytspG5s8aA4Q2eBTE5E5MRcauuHmwSB0vOmQeWBLMzjmCkL7/4ajooP3yT1uOUuKklQkpElLTp0/Pj8fRw2N9HXNVaffNmPj6fLxdNPN7c3E+zDF/eL+vw9PTQWFi4tfXx4XR/f/P4fFnXNo90ONzs5onMnp+P2mqbxzlnwIXJKlqpdSlmpqVcTqdzW3/6xVf7eWZHoiQiQ8qHN1N+96aUZV3L5Xwsdfn08IGZv/j83Vpu5nmexrwu58enh8N8wy4TpXpboI7il9Na8lrncqbldLrsxtkaVKOviqsboypZnsav339/aZfzeq7UCOzCEH7z9m0anp8fH//8z//s7/72V+ta7u5v9oe5YX06Pn368MHMWDjl0UhTSsyjI02tuePj40NOI8vYYHe3b778Qj21p+Xpu4/fXWrjRLdv337++ZdPf/fbVtSrJ4wKXZYGTw31m4/f7If9bre7kZs0SJ1rW9t6CZ9QBsibUyRm7FBmCWSDGECDN4dD9WVEWU8w3SOxp9SJUEFgiuGXEVOVk7AwC6WcOInkLIkQgQEMa/aNchKqggA8KIH8ov/tMOcOX3dNjzCh69VvNwOzIErLXTTCqUM9BrCTCMXfsrtxSm4G7TbmgkBXAjHpdVh0xs8/EbTQD6YfQB302uZfxD8vMQxA7jkN5t2RFW5EpOTaGy1jswQ7R1JAunFp3WCWRJyg8LhLIfrY53TgRwiuK8GgAUI5+vMT2ipkW/bBvaJ+DdHdzFVba60pQhjLYeZLXSGgxJxAKYXUlxNdaWbUPQFCIG/DBa+1ejMDmV4xOFRtTEJMnNgBY/diwa0SZmwaZBoQ4ZbiAWChxExdpGLzZgJZsA8iP3IltTQKsTOC7ICQOjK3AORJIjNFEo5zVtXgoaUkp6VwZCyRIzO7G3WFdQOc4Q6/8iMAMut7FxQ/Gi5EQbSmDcaSQE079AXquj0d+aHtEW2XTIkpbZkMB2znDgm1tY1UB0RgR3Byps418K60+I+MYCLEEADcXU2hVwtIJyIOsTzA2fuHXjuTukEmGYFTRzfh3hVkIwklwImd2FyYKCUldbiTi5AMLEOiCjMPWwN2B7srzK0TMGMKEHrwyp2YEVBhMXVEny9cARVkpCm7ejN1gjWL0Qv3cbI0MCRxTjefHf727389jVmpIYEn5jHf3MxE+tn95199+TP96HbB3/3Vr77/+hNW4EKgFewQsNA47pupWfPWunEQxBqVc1ldcyowPPrxu+8/XPzyP/xP/0F2/+1j/UgHa2llRm1tOV4eP16WE8Qf9/M79+HDt19DcPji/u7NLcy9NmFJaTwel/NzPT1faBj8tMAmZtGGVi8QlmnwFGKA5LBhmt5++Wb/ZuLJj8fzuV6Q6eZ+Px5mkvSGWc3WZSmlpMxsg655zON+N0/TtJ4vl+dT1UrZKSm501gTQyY5/Gx3KedyrkOiw3T7Z1/94t3dZ+fj5de/+vvj+fL4+Lifd19+9SWN7Uk/smPEIaXasgI43NwwyXqs51aq6iTjsM+n9bhcLs/Pyxc/+zwlOl9OK1aRQJsAkKqL49PHx6ePJ5yjssd5kDHNHF1dZkq9icYNZCzuWwWAiGSeRni0YVsrNRaonHKpFezDmCpUFXdv5//mv/9zR5l3aaF8Wi9P7ePN/VetUDPLw9CKgnmaJkH69PzRi+Us1tyreVE0kFs7r+20PD08t0V5SigwcShxkqAR0pDQwgXSgTBR5g2wj8ok3E26rjl5x2IoFsGtwd2DjWNqpq6GTvsywJCmhN7IHSBX6JAF3taX4+s3TqpK1mKB0JyFiHLO0ScFdndXq5FgW+xU1zp6P8W+nkSzHkXhvq8dnHkw9WbKDYx+Db1L0ZmMzMhcIUSyGZKDANt6+q+mDyAgulq8S2WFvpSbd3pg/ztBFL7jpm6Wsv8IIhMR9g/h+5dviLv9i4PSOGDob0IM4r4TgCGbkbqLIOO6/l77z5iZhQOv1C1skiRu1uG+ePJ944YzAGi0VkCA3pdxLXxsRJOoD/aCyO+v6P/M8a8DXlprW4nuBXX5tzr+IKb2zxzXs4qjtXY9vT8JwMKWUr3+ev2Y16f+r3jnf+qC/9EfvkYKf/TRG3q1rQmK2FYp6kQkcFd1goEgnA3VHTBopNDc3CHCNKTzsakrTJGBBElEIuQJBnbXwHIrkUIokVPV6goW4uySEnOSlGBNwAlZoURsZmpO6nlIaUjE0BCZUrOmrVaqEEnMRBwaHl0rwjvXIGLTLeiPWA3GqYMdSsa8uSe8JLcMMo5FYsOIRRIbIYA6U6gTGGqqZkF4TAx4sUIgY0PuxUU4kbOZcrR1iySWs10oMadQPwqSPwklMlQvx4dTRp4P0243C6TBmrEpFW2oXpZLSsJEpgVuOZFpA1EeafLcVoXRgGSmpRYvpoMnhym8NpkGrRUAE6+ljIOM48hMYM8pj8Pa3JMkAgvlaRg3PMlR9Hg8Jk55EGFRLc2hbgEeNbOw/TZY4kQJmpo6MSTC79pK06auCo8W8WhTjfRIYV2kxBiObotE2Lr3jTb2IhMrGWKl8yBfOYLs8/vm1BStABu8AYYTSe/1MPHYH83UkgNQdwQklNzJ++w3KJXiXEHq9djORxyFk1LbMDFHAo3JhQwgxjiNj34UZ3TYEmampmTEzImTwhB9De6gKEKFSjPgzim8cq9dTZ3S2DMtdkREjtCadQtJnQjBOYUNC0PqqloUFZAoEMOdEoskcTYGqbfmVi/l8nySiXfj1Ky22qw2hzNzopxsLGupFeup4IxayWRYT+399w/jJDx4ShmEn/78Z3//d9+fTxdAiUlyygPD6P7u7pd/8cu/+y//tS4FJOywEhX/IEArwLUWSdR9y7Z1iDexWr8CU1tJJwIR6qnUy3r2GtP0vje7U09KY1r33pne3AMm4hRKIeYVbkbqnZ1gPSjsAwlwZknRMyyttO5xGTxqcleUtjYuGKHVb2/uiz64GsEPu71kGQY5n07n82W3n+EOpFLK8XgS4drW2uplOZKR8DxmImq1VrM2ZMqS88hE026/+/bTGVARCBMRuUWhzs2s1Los6zDk+7vbeWw5TVAT4DDvxLFc+Hw83u4PwzhlTswcTeNDzint4DidTpfLeS0lD8MwZGFx91abCGtt7+7f3c775zx+bB9Oy2mScUrjkLK4WFN2SmmEljx4Fh6GgYQaNITXnp8+NfFS66VeVqsaLlhC7l7W8u4v3i2n5ftvvx/ycP/u7ePTY2krEiUe8jRY0VYXcyZh4RSKcbvdrqkX08vpuZyXKeX94ebia1NczkDycS5adcqT1YKc2aDrCmtRsShtFaZkzIxxn8cprUtR1Fa8enMDGmhMDO6tXkbGRuwufWD4SwfDS03SmYDo2Y0uLcImJgXAg37FoATJRMwyJhYy0uBS25a5bvm6uTv3uARA9zfsuzkB7NeQP3QV2ThUHN0YRl1Zyd3VwpqHDSzEQo4umcYMgqoycXCKeoB4VdkIBaIQIon6+2si0zW6eBEw3zD3OKstegYCL9682a43JQAUM/OAg4UJ6JReClZTlCi4J6bR4G/uAEl44/iGdISKFeLhcNBfOoIEfgGT0OftxhMCKB40R6+YOcPJzIxatVoUBQj0GYGF2RYZxC5EEAebb6Vm4c546wHA74Vj8LAnD9a0qzrYJeprzAHkRWG/q6yBQtgxBhKu5x0QBhGBwiaym6b32xt7n4IxBOhPIHLiJpmIxAxmHQYNeMe9a404/GWVjHumIJCxszquDCnfUqffqx5vWN4/frzYCvYnuEFzW5bS8am+13c6IFFiTz2lsd72t7keB/OqF/ObKq7Sz0F7C5bly6AF/Kqu3nOAuKpNg/LqAAAgAElEQVQoPfa/3naemAKBU3mIpkXasGkqbHdDtnSxbx1Rc+pPyni7SuNEmRMJKEfzoOVBmmlAfuRkFQS3qh4PgoAEYo583b3rZ0Vv1JAGc2MQ2J1BLB4jphpgRANTNjJi9eZqzaAauohtMWlIiTolzKKwd7+/2w37y9Pl6ePT5UP5/h8+4REQDOPA3TVAvcFUDZsUAwFOtSiqyZiF2YqbGrE523fff/P89NX+dk785miPRLW0VVVVLYricGnqpg6e0dbjtw+XZc2DlKWaFx2M5zRmMWt2WXgauCUQWwsfUzNuxO5eIAbBosuxPM+QxAnJeEjMtK7r8vREzPvbw24355EuF5R1ASEPuZa1tTxOySF4cCcUbcf6AOe1FXJm0P3uTUotZ9mNN/fzm7vDrq6X3/76N++/fZ/TJE1O749fnx3QivP92zdiA1NyPX94+GTKrTZtIObddHj39p0M8nDMx8zPy9Numg01xlTMRyO4aa2NGuqlMCWlGiueU+iFQ1mdzIW9s16U+jQIEEOI6HK5EBIzCXOSFK3RDoa2xOLUaivTbdrfDW/e3vztd39198VeBGkAY3w8Pq/azLwup8vpMkxzlmQMK0AFT5ITGTmxa7I551HSuqzWlIXs3DpbqEfoKRpwQo8YL/TMDu5vSIS5m6Tkti0g0TYR1krhQRDqSQZxZic182ZbZ2IgWST9/XpA2U2iOtWjO/bQtgJ1fo9zKY0zJUm80TMjdI6lIviyCuuAIV3XWABQDU9xDp5YVKjJmdzJCKq+gWCvTA0R6ScgzlCEmjJREhgzNs/xvqBsC/WVjMIAkATmZNt663KVLsRL+Whb4raltF85dWXJK1wIc40AwwAnpc3HDeZwMrbtTZASOUdjNnW2mketyW2jx8YWy90BqgcwURN2xsZiD22vuCKiSOKBanE3rlfRz5M55K1fl9L+BRjWH4O3XLGaH73kT4GZ/vnz+dEn/jHHFVb6QV3wh+DanwRgXWGjiELiY+zV8ae8+T9z/OguXK/zNeUK28O4ir5HUlhOxTM4mzskCzGTizZ1M06cUjbmVpuzkkBVrRrU2SnnPE7NhJT7TBLmlAbypD1K8hBxpwZhFmFVqIELuKBxNVNmopTZoc3MjFmurcBqzmH/DkdYVxjKWoqXcUoQD0HNmIEMJmPyTfEHvVCG4H9Sp/AH58Vz1JcjkFVgc5+QLQeGgxJRbAehY2pNAYaaWQXMkcCJKIuEG4gRu7h5aJhcaecRabLINI+SE4Saq7mRAdVBRiyJc3ks356+v3l7uP3yRhKvy6peiZBTUq/LpSapKWFIKecBanW9DPNwc7sb5/zx/cN6wSAC8pQEuyGlLDwwuU9+9+72/cfvdvP+sD88Pz+a2s3drbkuy6W1Zkra7zcIlCUTIyUC7DK0h4dPb9++HXfjvK7rWsyqg4c0aDNTYxCL7NLQrHk1hF5grxBYIahqN3klJAZzqFEoTA2tGUzBauEHBweHsFNnypAGSctDARdubtYzFKIfT+OXgwXubgTrWU1I9YdROoO6wqI4ulpKcPAd8LSDBfCnKFguhiFP+TbdTIc8jMtpKbW0qiwscxr3E2duVmHEkvbzzsRK6TUHMwv7ocAFmFlAG33AtE/LHjULZwRqanCHhp/KNVamngFFtO6hAgaEsCUleX48JckweXo4LceFc+YGj/3VTI2YJE+Z4CxgUWttPa9TGnb7XVVazEvTcRjyPOzo1o58fL702oljzHkcprL6N7/79nA3f/nVZ7v9YXg+HW73efiEgeHMmaxV5DSPw7u3b7/8/PP/9X/5306PNvAISyBEHEVs4MYC0hBHJ1AI7zoMbKCXTvVwT9ryYQoufGYhayW226DaB4MyCCPu3uvW22YeOUqQ28BubhLzmsmMeluWBXUE6Oor7ozeE9Kti6NFo4lEZANV0tbMWxIfhqHw8tf/+Vdf/GR3c0+3h4MvjdmFqZZlUW2t/ub9c8oOoLW6rst+v9vNE/F4d3Nwxel0Vj2fTzWlvN9NN3M6X05NixDt593ugpxmOKZp2M1jZnG3eR7X5dJqUVWm8fbmznde1qZlncZpf3d/d7hZL5fDPO93834+DDkLs5a6nBZqdZrGJEzw1upyubRa3WZJUsqqrR5uDmPOYxpI/WZ32H21a2srx4WaHaYbBqMhyTjSsNRLq+quVEV1ZBEzL6WAZMicam7LsV4qDSIsg8j97Z2Vdnw+3d/fv717c39/98Xnn396+Khqx9OpNeWcH56+L7Xsdrvbw40ID3k35Gyg4/kCs+VSmE+ceZ52B9x+9vazPByLNRFZlyIIAzcyGBq0wbQp2jBmyXI8Hd18N4+7eUaytQlnCMTM29A0SJ79P+tgsr0KkyLZ3fQs+qwkAqGh92dx2pYmIRIBExFSSpyYhR1oUDO1SMFpizxiVwL6Xrc1A8TUD2ApXAu2MeruDvU+4EPt3PsKiZ7ZaDT1m0HAICQQcYIQU7Lkra2RRgSbhMPuh8g7qd8jzA3rpg3geMVt/OHSy8ScJAhMsagRUefw9Fgz4hBvrVkIeABgiEMkpZRUGydJwu7OAqtXMAFXhhWuQUzH0yhwlsCmrDOzequBac9Sojgdqtc9ZgY7awBY/z93b9okSZJjiT0Aqmpm7h5HZt1VfczMLrmHUEih7P//BVyhUDgUcmdnumf6mOqqyurMON0OVQD8ADWPqOqekT16ucK2DyUVkREedqhBgYeH99Q7sV3dvUGrYgM2QEAxf0MxgUFkDg20R92JEquZ24XrGyEH/UlGzu9B4+tkbA8Z/x38iJCvMHOjJJLI1XuOb2ZEOyr6g6zOOyNrN0rf1aP8AsF4aNxalw1mZ3diESY2bs32HhWZawwHMDMTO5O7taYXCZnerw90MsZG9hXww+ffES3vw4Y/SsqJX/1cFKwU+GHAWbTjVwQKqLjfP4gLk3ggV4ru6Geh3MYEUIcWQzMG9OpMogL0yxgvgGh6unMXz+HYRGpr1PPhncvAZJdasENGzizEZB2Q6jl372f0VeBuIdIebY9osRngagrYMExpTEZWrW5tkyQXf2KC+Y6DMwkAl27+wElCBWeHI3mfjiIAJMTCnDMSUebm2ogO46HltumWpW3rYm7qbdNt2So/JclABoGhYBFDTZyuD7es9Jtf/PYX/89v0iIDDTiSb+armxuzlFSMfGm1OyIzO9ybCxMPA+DUiAksSbXZsJ2/W3/7q1//j//LX11//Hb9/eP7xweXeNhODBFkEpEEF+SE5CLInKw1N0+h12aVOV1dDdNXn3zz4fdQggOJuAgl5kLuzdzySabbwch8aHfzXfa0rJvB02Fw9vW8Dcdh0zWpSCLOaMuyrSLecpJK83fv123dKm88wRQLt8RICVnSeCVLvXfU4+n40fVh5Hz3+2/uvn/+7pvv1vvmSakhUdoeZm0bxB7rIxYfTkmQroerVm1b6zJvUGqDFwwyyPP8bPDWIkdUZpA41B1q1pr6VptuZuctNh1oZ/s2q0RqbsTgBCczrbtfbV+SbCCmLGPfP9xdmxmMxADzKpk3XWH4+LPbr/7iky9/9tn/9ot/P76hdKDkwiTf3T2yIrGYui1goePh1JLeHe5mrdF3SMTR0+eJmGDNTJEzW1MwRJgg3rpxucUbEBBQBKvXYLF3ghRL17iLqNN1wUMcqpOqPGQ/yImN1F8ii1UPUd+eKKs72z4xH+ROYuKdh7XrUToA1FaLZEqhB60WsDdfYnjIljCMyF7UK4IzbWrR+hFiCiVKNYDJwE4gsrZX/fEik4tQSkKFUfuOoA5iDrhRCGQUHUoCMcjMyPVlyzMCQZKQdc0+6kJWFOd76TUR+c7IuzSZ9h5bJNq92bJvo32oP54WhcqauzrBQnPAwSzObiA1M4pKqd8RMw1amDPUYkKlf7yIpCRbq9jHbl4lWp0DC3LTYGEZCF3NI2ozgImNfF8v6PTU/7Tjgsm8BkP+KdjoR//0h1/iPxNy+meO/+LPuTzT1wLwF1Tnv5aBdTk51Z4c+H78ST75R3/ln/r+a6wumPxxwXiVCgZQ2hS9yxg0iZwSwd2Yk5N7U4eHJl2kzHALhT9hOV2dNq/Nm5EhkbBIZMzMLDLXRYzFuVU1KGcaOCvcVqu8ccmSczFUr7q18JjpDs3oenWhlyHOuveW1Qwb6FBCMiDY00R7WmsEdQjCPtnIA54mA0eKGHEjUkNTEDmFNjiSSDS4ImoykDgNqVjTuhkssvtO7NmVTTiMx8NMDhaUHkIzkFNmAiODE3OS8XRwt2rt0hNwWKuNzVBC5tCX543vn+iIQxmry1IXEFLO81JDN2Eax1IE5hUb2MrIZRy1nh5xfnrcMlhykpS8oWmFgzIPh6E8DqPk2CzyUNrWONO2NC1an+zwNm0623NrW3W1nFLOCWQpkTZnppRSHqVqKGZIToWRWq3PTzPMS0513mprIXsszFC0WeVmdILk0It3c63uQsyJXNla4P3QbhcZiS/1JI17ouN7fOTODtgFLAxh1BH9hB8sfgKBu55J5Phm3tzhBvXGYAN3bWYPul+8pmR5TG1ukjAdRybatllXz2Mpp+Lm6SgDX2ltBptOx6WtUsQI1dratjwVCCjRuq3q2lWrgjRrzsSUUts0WEduBgu/qnhdk/u+kUSnFX3zdvHE7AJwnKRbcG6ZlNxdyYTJkkMkzQ9nMhJJ5DDVvYck5CyUmm2uRELbBm56OJyICE5DHhLS0/z8k89++uHrxzZTm3Vbl3I9alu9ynpWS9VZ3bnkkYuzyNPjg6Flsca8rk+kzqle35yurq5OV6e//7/vDiOpF/IS3WNhNriqQWgYRuUKwCL56ozkQJu9t8CtS30SsYhIkiRZEs+67c15BpMwB+63s9coRrsivnlg1AgNT7jDu4X7Lgvg3vddg5uzgIRzEhcyNjCMDEaEPt8kzGbQQAqMwrIeil/+4h//13/3l28/ems05I1KlpCi2ZoS6MPdenWFw3EYyigskst0yEOhw3RsTf/j3/zdtrUh51yuxyknlmZbO29mqm35+KPbZs5EJeWSc6CadUvsbpKGYcicSyoO9WRaLYlcnw5M/AAcjxMDro1yYsApROBABm0tp8SG4zjF4BITb+taiVspxo0GK5xOV1PJI5nP9+e21EEGVhrSIEjkJJwTmYETSSj+FM4l5eN0oIGrt7Wt1Wt02w7TJEceuXzz26+/+vKLLz79/Obmpm3123fv7u7uH54f53XZtNW6kvDV8fT5p58lkZ//5Kvj8Ugidw8PyzJrq61ucFKqKfHN7VUe5LwuTmwa5Cmva13ObVs2NoComWmzKttaN3KMJMrVWDmDhLLEtiDff3cPJrib7UZqtANYr/KtnoL3L3caPwcflIPixEyUhLIQszCIgsfltbVmzfp8YCSU0JhEih0Zu1YE+kRsEE/Qg2VgE+YGVyeIbi3YX3Aip9QxNhcWQVRFtrPx0SevvA+ahZQ7kQiECMwSeUEg7N7zR/PYJPsL18+JmcmpazNZV2cisIQpBsgspPe567FG9I343Noe1BF7tGmfk+S9xCFKRCG63cuMSGe06YsoPrC7O1EviTqVjUwjsHLULUQd8Y8vg7Em8WtmBDI3a2ox9R9GwwnMQk5RMxcpzh7vfRhuYJ9XBnF3XNybZQFTeZ8Dp07boqibujJtfKlubtTb1rEAwop9p3HppmE75YBb7ILhNWXO3kUe9oO7CXqsI1etIBJwWCgT3MlIeEzZ3btucVc1JoQAjXYCk5DsgFvfoWJ1/uHxkkyit2B2Rd+X34iPCSpGyKJlyTG8qTGDSX3HK7mYNu8oIDEccG1qzZqatdbzhJg+7M/c+1tIzMLEHIk3QgTikkJ0mbmdeHWBQxF9Drwss043uEjzw/dv9KQa+3qLjapFsbUL+YN3mCmmcRsTp8RpyJobCGZqrAal5GBvvdUNu2i+sJsrBJwkSyLhvaV6oZwRE2/PK8JyjkI8KaQJeEgCb622PJQyFKb1MKXVtqWuJpRTOS/P5KAMNUeBuuYkYx4ziq363W/f4RltVTYRF3dGt5AWNG/aWLpLwwua7QSQVjOHkAS1ypVB9vvf3rV/29zTOI7TNm62PZ8XrZ6keAIaE0EEQxFJCWLDoQC6Jpg109ramShfXQ0ype2b5endvD02ZOJB0lQcrbaaT3z6eBxvs3IFadXl+dy0IQ1F69aaAhivJ1WtthHEENWISqY0Jee6tmpDTcUTkERyTmZemxERFTtMJJynLEOG2PZ4//3vv/ugCzNQ13lIk3bhbSppWp/mtS0f85t8zAa9ubp5AuqiddPz8vS7tUriheZh4OvjoW4bkoXTLHNsKmau1TYYqTVtDkefxnL1yAnZJQuP7ORUe5cOFnwj6gTgzN52E0QyMxNOxGTcUslaLR/w2U8/+uQnH53Xp5/99OPGy7pt6ta8wuACczNyueHN63mbociHvMzcViWCB4vY4LBlXUKRlpnBCsdpOo3DqKrLsjInqy1L4ZzW88rCBNIWUz8dpOjv4m6Sgk5zNWYhSiHiHbwqGCFEeppT3/V6/AftfBH3roneO1IRjRhw0xhgpO73FztShiVTVb+QPODkYBFiimHNPcw5+d44UMA9SF8MmPZ4CZBpx/vp4hEY6iBwI1MyIQvxE/TZZHYiD0Ph6E9w34YVDmsUVqY9zDgYU87Rg434dgnMwVLda/8ee38csvd9uONZjm6iTOaBxAX07ohJ/EvzCUwK7c2tSH5U3cmIXDWUtgBYc2dvpqbeqzb16q2LyTIuQGKPvobQCCTsygl9wyTumljkrt5T9F0k+Z/Yj/7ocaHy/DMgzI/+6U+LVf1JjsvJXNhRl++8Zin9VwFYP66l/5hr4/83h78eFdwPEfnRj8VYBBxkBEU3phQSShwCIJFwu0tB79JCqL8qGnlzd/cUkQCqAZFkjNCki5jqDkGYpKqZt6Y5Zm6FjGIX7603Rx/8IUG8T2Ks1OJ8e8ZhFx7K3ij0LlmOfU7AEUo7DCAMnzigciel3rANvQ93DWFt7Fz6nm92gofB0XFhNRCRuHdah4DIyMLEEb0psOd7O6vXRY2IMlsAgLDgdAVaHlbo4QtrzR8fnkfKx+mQWEx1aUvPSYOZKZSEkSCUPFvV+Tid/up/+Nnz4/rbf/j6/m5W27ZVXV0gKQ+JsW1rdG9s2xR1HE/z/MwmijrlMuftdBolQbWqNvfqoRTMkETDwCk7k7GQJLiamRo0JRGQJLJq5urskih8QJwI4p69YQvaTFCJwuBatUkI0/JFgh19LoCce97an5pf5FYvieM+HdZhHwu71bjbfZsxQh8Y3/PSMLvrklsxLcYXWUW/JGPu4ExoSDmNx8GazguWdeW2lqHU2gYZDteHdDqstUpJ89P7q/GUs6zLen54fJM+ZZCwZe7cK0rCSRD7HpkHnrZnxT0DDs3VeAkjl+8zEVE6GEWFQX1SwAl9hxN00iG8EKVUxH3xGW79pVYnczAJi7D0gYjUA0JKeZqmzdbQsEycRQZhrts2P6sTkJOaAU6czLjVzRnzvD4+Pk5X5Xg4QBtLg2mIV/GAUjCOJWdWbWhQsMI5+kIMYoa1Bk1SFBpVtKHnQSG7GVuqiADUaY2O7r/ubqrAJZ0hdEcXZzD6jv9iNfKanPeyWf4gQO633AHA0L1cmEmSuDgRh/Gbme5tqjBBC1VNCeMIM0dDWwkuWcZNiYDjNDnIDcuyVm2HCeOYj8fTNI5EZIZ1qdpcJJOT2eaeWsMyz6XkMWd3jOOUkpi5S7FOmCByCPXpqsIpjcNhGphZiE1wyAWJpzKOKas5O7V125q2Ul11GIZMKQ/j1eHIROu6uqSUUs7Z3Tl1udRhGOBYntdW1iSZhQQknMrphg5UKLPxICVzAcmUDmnKADNL5lKoSCl+wPP1uUKXuk5lFBMXNPgoY5Jcrmn8Kv/ky8/fvnn79Pz0q1//+lf/+NvH89Nmuta6bNumKxN/eHhctrVIfvP2Rkpu8FzKYDWV1Gxbn+sm1bIl4iSSmLfWlvPTOBznc/Omddu0GTuQwMRNm1WAwQywNatGTQoTJEtiToyUp8LG1sybeTNSkJJxg4bEF8gcxAbSUH3GrmtJPg2lqzXDu941hzFRcyf0WSatgay4XgLPXiG/lpXdt+aYKTOYd4m8CIlm7mpkREZmDcZQImdGF3zci3MD4q0P7Jbg5kYOqzBz49ST/x83aS+vCfX5Db6cUOy0r14j35FiRmJKDArBIGVyM21N3V3NL0JaexO4f4YD5krmLVoRO+Gy829e52fUwTu84CLxCX45kz4BFwnLfmkA9r4Y76ijRQ9qh3vYEZsXGQHOQiEnC4O6untKiQBiib/CQZgw30W0OjB42fv3LvN+nnEmEcaxJy270xwR+e4/yC+bHdyDcHRhAcWV8OW29zR+p3Tt8zjBg4KacReG6JtgYP7EHENxYVwQLaMYODVDtLsv99hCa9267NqPaobXOfS+JmKidfcR6j/Tk0wzmCkR7xa6+3g4ha5/vzXmCgsoDFC3Ztqsthotil3o5uWWxL26OG3Fx8aw+f6i7QDm68cTz+rlVl5W9cvyfr0E+2KiDvbtSxIw3YWnOZJDAgklkJurqqbElBJnh7CiNYW7QpwEkjmRakDe7g0xudNJN57MEztZDDoa+35LYSBLwUwnJEYiB1xVYQSGt7phGMaSM2DOZiuW2vKUqFDdqnCkJToOIzPdXt8UGR9//7Tcn5/u5rjiba2pOSoLJIT3zN2bswjcO4uOyKFOZOpELCRoFFkuF6aDr0/tm2++O+lAxzaUsp4Xs0ZUxvGQyHQRJm6o0yR5zK1twq5uORNM1BuxEreUSxbSsuQ3vk3xfrd1aRgwfYw05nT0dHBJUHNGpirbpmBat23bGhxba9u2OlJKgwiGEQ4MgxwOKSVmGYndrC3LLJJzyVr1fJ63ut5V/KtPvlznZ7Z8NYwTn+7z/XvHoVB1nB+xtBkroMjHPBTZVqChbeqDPWznaxwlsRSuq6KhntdakI/p6ni6+fiUMjU0R5UUjTeBJ1eUmoTEU3JSYw07+QBSgNBbsyRRkDj6fC31cRMYIdX5HIxEkXgqbG6NkMbk2dIBH31xffpo8qzvHt+PV2N1P9cGRc4FXJ3QyDmhlNysPsyPtpmJ0gDbzJnQLWoxXo2EZK1C0NAAQDCMwzAMy7ygVUgKjIcTkXQSAFz7SA2MXmA3fxXAYmC7o0J9W3A3i6uPZi/tYDEh2rv7LupAcGV39z4SdJG9kNWIHDk6pn1b2QPZJfrucJjBwSSEvRfeLc4BRyopSgfzFtC8G9yCIGkcGDpfiA+XQsAUBomIYQBgpghx8tghvI8r9hDVHTP8JSRdWkA/BBz2H3kdqPsejX1qMHaslw+LBkZ8bU697RP3Gy86JkREGreKEXRdhDWgsYUWwu5juwOB1nsQMQvS7Y/3/RJ7CHdHKAew9qmpKHWZdxmV/dEwdc2wcKz5kb/xf/Lxukz4z/3F/7K/+Kc6LjtafPlHr+JPw8C6HP887Pff9Lgkl5cTCDakvz7Qa+fufeTmtrmAkxBIMueUNq3bukXpGytd1UytQWttnEmyMAsbaQNYw+IKzPAOqbpBueNVBjdvW7NsVd0VCnGkkLliEu7rmjmGwCSRKAlC+M9/EHEimwQo4rSBkxlMgn3q4P4eullom4oLgS4t70BQuo9FT25Jw22KIO5Nnd1aNCKFqM7GiTgVAkEInJwsAD32kOyEeBfjjNK3MYHQyMYyUN1zb4O57TR9ACAOazr2xVZe69jG03iaUtJSbVv02RytadWWOU3TwCLV5qrL5vlwyKfTMQm9+/b948P58W7xRswm0gi0rI+cffOFnZPwdBiaLk/zuQw4XR1l5Ddvb65ujuuylYym1czb1ijBodMhE7t64+RlSti8nnXzLeSMODtgzRoXQmZnV0Ddk0gauLXmUIUKsUVjQaFBOt3HAKPi6Oi4WYvAaz6koamG9gQRSYTG3dPqJdPcJTyI+bKPQUK6uHdsXB3OfZ6ECeQsguSWDeLEgW6+VEE5I5ckIkychwyyRCkygLpt8/mZWfJQchaCn+eZVjSyYRp1bUiJk6RSxJmIRIgpQbU1VWseFmM7oE2EEPVnSnWpAOll39k1v9CZj3CGMJGQMlEyZ4fAhXbTWU/DkAZ5ev/U2mqwTj3r6wpOqFpdLOfUgsotHKCig5Z5zZw/++TTr3/7j+tiy7bBfToM8/ycx6GMRb02NWM8PK74+ncffXb76cdv26Ln61yf6xl1yv68ohqcMJ3GeVtRsG0uXNzhYqkkiDtpAqXMT+tMF+M29ExCCb3tIhyCwdFGMyM3061Vqw5LQr35zqzuAnHxWDbxCOPd7+1s6tNPUasmocAFYoorxKRjnEGIulsV9z78DpO6wWHghAa1FvScxFyYMzF5U2yAcuHD7dVbPz88b6lwcaZSyu3tG07l+/f/R05lHA7Hq2tzn8/rua6Ap0zTOHzx5V+JCMzXdSNJzYkklywism5rWzeQNNXaGsymMpRSpjyMVynnUlJSNdNWypAOIsyJhIC6ra7VNbda2aEpNyLKnmUQkMcEJ/gwHlLOOWcWBnAwSymZ2Wbbdl5SIUKCVRY+DYexTGMeMw/kkiknCEtf7WoGZVIaJcvE7cY/PH+4a/dcqUiWxOAElUTpUK7+53/3P5Usy7r88m///hd/+8vfvvudDAOPeW510W2YhvPz87u733397a/IcV6fv/rii7dv3xyuD9cfndKYz/MZz0+mFQTKYsaqydyW2tIk3Gt1AJ0PwtSNeMqQAAUZkbEgACwQ16bW6vF0cHVvZs1cIZVgwABSsqpoIVEVwBFRYKg9y/ZxmiKl7YN+7nCvurm6Vusqey8sb5hfsjj0Oao966RunEkcRDkLMZ0Y13FV9dZnqdyDxdqxEoN6kI6I+zBFUKcBJ3V4deLwQXBVN1DLpa0AACAASURBVPFCFwnzHWQJ2iNsb1d2JlacUFAZHZGP9tu7b2Bm1ppFyDbX7vF9caq74F/hY6u4IMoRvwS0C4IwEXsorqu58T4fYX8sjwqYOLLvsHYAQlGqw+EEISIXJ9I98BL5hfS0R9z9P9yNHjjmMVXVzYdx2H+sd7nQ2y6XmivIRQGg2AX4iPMgEEeFRD0NMziiEJO454QLLNPzEnK6WFperivgT8duotkvFrt4oBPM0Jt7oZ3QWVnNTcBCpGaqlwG8DowDUDUHSczVafTWIC7RwLuI1e9XtVdXPz7Ia3fXiZ/cNdD4koS6edexvPx+37lJNayVOezhtcHNrLEp+vgYwgG0E5L2NQAApN7nCUMTIYzamSPJio6V7WPBFyjrQvvAjnZekNxdaOuScDj1OT4i7O23Xm2iA2tOgLEICdy9NQv8NwaeAkzu/AXAgTwWY5ApkQhIBlWFNbamcHdxlZhR6tICO9pGBMaBiVNAZQDMqru2GIB1yFQwDmkQT2nzrbYKICSRqDEyqW5Z5Hg4FMn/4uf/4u7r999/+/23v/6uPQALEgSKtjRyBlwizTBTb7Lfsx0uz9jnPT0E6Y2gYMuFp/P58e/+5hefzLdvf3aNQssyw3kcx8zT0lpzrW2rdR3GkrOYe2vruiyqNWcpJQlTa+s826piQ/3iq8/evH07DhNYiLDpdvf04Wm5W3227Ei6bVviQ/LUmm2qrTUuaZym8/MjFEpOUx7HYUykpHnMeUxMXiSVkpgl548Z0qq7ec7D9dXNm9ubv/vf/33GwJ7a1mafRz98dvy4FZZjeipnkqzm5/ncarM6gzAe8cVP33z+88/KlP/6r//6cDWUkp7S/Pyw2AoROk7TRx/f3r49bv60bCtJG0ZyTyIZnonEwaUNH0r1THBYVAZw7iCvdQialNg1gTjs7Xqm2NOTnITI0cyU4MpwIS/g4n/5b376s3/5pZf67uHdU71X2tIknLK7GXE6dXOIcRiGMhINtmnVJpOc5LjkzWrLkpyMC7396pO6tQc84glanQo5wQXqrVkFIYl4JtUmnnJKMLba8PICXVJvUrRLT4GIw1CM3E3N3LjB4a7OyuQM7zzPnRQZ8FAQX80j1EvkksKxMhskeFgEopjohYfQ+w9AgaCqv+wLgf67Mym15jvtF2BkziGTYm1P6x3uLbrwzt6JCTGaRyCBszc2osZE0TZAV6EODh4hvDFCkcDZjJqiKzvHYdDWtUUilMQUy8uY9g9xjb2X0E1ldW/87Fdt1i+nR2Tb3YHhMHrprLlb7y8pgz0Jm3cGNUXWsR+RWf/gHMAOvyh17ABan/tmJwJZiHgyGBT1F5xMPXjBxCIhCOYOYzNVbYQ/cqU/PvwHP/DfHYT6b3H4zi8joj8xgPXf/YjGFF5d5KVJtVPRLm9way4WbjNq1JiQy1AywUg33VlQ6q5O2mdgmQnC0LBZUxUFazDQIaAYieCeTTuTC0wBoU2bknEYQRXpbVq55G9AgrMTU4phamZjM453zoDuSw0iokRITE6sJOwsHCb30V1Ug3sDEZoDGC85J3Y5g92Xcy9We0HsbtZM1VqLlxoKJCIWYnFi6xB239CJYsgCkQC7mrEbqpOSS6ak0mVZxSjgCkrMLEhCmUJml+B11Yd3j9rs9PZ0e3WLhOev/56A2nyeZ86YDgkCJyX38/nhm2+/vrm+vbo+lJQer+a76WGZ27Zs1ixJqaZDyZFdc3JmT4lBSJKI7frmeDpOw5DM6jimZmTemjZhEJCLdIXFTCmPKWWzZVmrgYUlZalmVVtJmUGkhCHEHjziNgRgI0aYxDpIKBPgasRsEvpjwCVKdoTZqDCH4NVevoXSX2cLeJ+G+UFs6g+AVHqzg4xAzhy619F/MTCROAmIycIvEn3izDgmQEib1a3mPFxdXZNz4gTDsqzLedZNl7ZcMSemlPLaZjMMh3L75ubDPz4P0WZPcITdVCjCaLWq3oiZBbZn3r36NXdW6l3zVxcUKYuEm5KRB7TDLGrEzkH68xgPARNnSkgUFoum1oysDypad9w1ykK5q2eo29N5Hqah1aWdTZKPw+H7bx9Pw2HI6bzNziUdhul0AvO2NU6Up+zczrNN59nc3rw5kjabbVmr2SaCnFAKg/x33/wOCb4SOMGBYshwUVB4HzgQ442vr/eSLEBtXy6vmkyBrodDak98zDhEne3Cp9ubSp2NFcyCWFOBjjF5J1rHaBUIlEBJmLmrBoGqqUcZ5ebcFTVZoA19Ujj82iK2sIeEJhPnXFSxndenpycA6ebN8XQ8TIfjdGDJzKnkAcRwMZ3KUK6vbsxtmGTIIsLbsoVvaqlNhJvWVuen+wcmabWt6wq4TUefDukwjbkIiS0VQJZ0GMaUOGqcbVmXedHa0sRKlFPKORPQatucHpsxiMFFcpLEzLmUXLKHiy6cmY+Ho9dGycjdqqkpFylShjQmZBglTgx2qBgnJDJVVWJnosLlqhwe7u9sab4ZZRrGIqlsaxO1UoaPT2/v7z98/auvHz88iOTT8UaOpTJWODPSVKAL5vH5cdGGv/v1L87r/Bf2088//+zmeHXz5oYK8UB5oWqLrzO5DZlTmSajD3f383mprTqZJLiTBfDtyCmPYzHdTFt1V9VWDd6Y1BSteWaBxyBpWAb1UpWCHtIV1/ZxpQBCe8nqzWrX+L4AQjHdbPHtveC7YBEBrl6YIPsbALw0Xr1DGn1tM5IDZkBQZ2KmsBe07mRkbmC3zjfe3YT2YbYwGAo2zAVf2Rt6dMnirRf/l/eyn1sXno0PQ3dVfpUvusM7V9tULUYIX10WIr1l5tbaLoVCgKO5c5+85/D1kM7oBoUtKIVO+Y4U/Ci/uQCG8Eva7AB5N/yL8tr7oBn3/nOwXMnh7KToM+WINH1vIV/isWm400bjSS1Qpy4aHGjI5UPjefi+SOI6L18ShRY4yEHiZE5OHAop2CdJA+ygyyOKT49Tdwv9j07Xshc5XjjBWx9zAdz67CD1uc8opIJGbTsWt/9F36+AhIjNdyvBAIV2ltJl6YfjVQ+hr0K4E1z1hc5KMHIOrXzrb0u/n5fVEby4eGaOTtgNrDUu1y/PsD+z/mL+aCXshRn7y2gvzHvH/8IUi73+FUfscuaX8uaCYb0mG0bbhNB7UKHK1RdV/GDw/HeqJBBwICnbapUrIXsKn2tmQ6vNDR5EBhCMwZJI0Nhc4OqUiQXEpKa2m8P0v0cGBgmSCIPcmm7W73xIgtStrVsrKRUhJCUGKSWRLFwJbHWzknPhdDUej2X8/tzqY2uP4JiBAhNRyQlG2qxZYyODgQMhvaS8IOrRKFFyNbgIMznVWqUCjvkeaBmG58fztjmIQhlp2banp9nNu3Mz+ao1JRZJbkgpjWNOzFkY6rVWDHhoT/PvKztzEsmSSkoD6+brVpkwDLkItrlZw2ba1N0xlun29u323cYFKfUoZuRkLoBYGES5gkjw+HCen5fnxydT3Fx9Kl+Mt8w/u/nXV+OBIPPTts3ts69+Pv3VaRwOrbbfffPu4fHx/d3dd+++sWNrNC+zQvA8f3j/3vNU0kBDSTnDjZiEreTCw0FyFtW6trm1BdTATswpE5xSopSRJFEiTqQKUJBeHMTMpDE2Y83JiZ2kJ44UGa8BTuX6RIhE3tQdDMpIAzjL8bZMN+Pqy93d+2e9Q7bqNZFMp9NhmB7vn25vjufnzdQ5CRIJU5LscK8+HMfD1WF+Prs6hMqY8tVQn8yKYwQU4zhotdq2qnVdVhKajqOt7fHpOTDrkIUhEYA4cBKLQihIPLHAe46K3gFxd6hpxIHLu8z80oEg3gMlHBcJdOx7VPyOOoxC/9a6+vurBure0ngVpTuU1vGrPSFwIJQrRET3I9JLCZ++aD6QsUOjd0V+6UODFXBSeYmxe8ShGHgP7T0zWMwpWL8mf0kRVHukRDcupShtLrELe73/gwAJ7+3zl+7ZzsLuuoMAAugyB+kOJ8L2noX3bIYdbMTETlDXndeiLxl4v7HUxQY7eQ6dSOaXNkKobF5wfb8wwnti5ABgZiEKRNhPd99Z/+jRUU0iAnbA9PWd/jM5frRbxf71ZwVgvQatLt/Zg8MlZQH3LqnD1ZScHeKUmNxCCyJL1hjXd7g6qbMxgJISh88nuG9qppuuME9IeUgpJ3VD2zxaaORG7klSls02xOAhJ2J2hzUNk2ALJFrc2QAjdgFCbQrc3/sAJLyDu4xdqhQkDlKHhRxfAMkGuLk2U+ORgF1QBBeBT0KYkPU3HObOXdRPvUtFROvpMsdFBiKjSycTe2rq3ofFelkgRkBFCzVxSoAihbJIkiTiSaRkSqKmat62tpzX1oxFboabaRxujlerrnPd5g20zEcdxlFKyhvca4UYCzj51fWxlCJEj4/Pj1BVuzodPnx4TEkAJwGLLPM5ZRqKmLd5vv/09sthLA5tuoBbThzir+NYkrScRRJDfeBSymhGLOL3jxxd8gwNISeyaqpiOSVrrlVhjgJhiFDwSqF9St4awnY2GkfE1L2lIleG9RKLd+uJKCD3wjH+4/5S+L3eeEDEKVimnYFFatR9DD2GB8MTMXxhI0Z2ncDoqJCp6rys7jzkgY3b3LxZW6s4D+M03g4Gs6pq7TidpLBSneeZM0eF06ya1h4ozcm9moKRKHgGnW4Ul2zajIgheMlPEYZaMXYXJMIo48AMst5Nph14ZaIkSr61sP6FBf2vJwQWExmevRQyQW1KCcZ0ns/T6VBn1WrG2NaKM2ikdBCs2NBOV8fxOC7nuWkbpzwdkvpcreq2Pd7f/cUXHw3M88P27vvHzLh+W37y5cdf/uyju/u7v/2/fgMCDUXnYFrDuSkQlLdmreuLXNpnftnC3M0blGCuMTpJ4kJECOVa2KW0Y/qBt3H8NrqATOdIhOIV9jiAnYsVAztEQCKimOPkIE07oNYsFmkvAeEMFgoBAOKoOOHWW/ogtNWeH8+Pd0/vv39/f39f18qStPlynteltprXZ6/bvK3sIDNjTuMhm57vPjye52UceJzKOMg4lbEMechDyWpqSh++e0/alnmelwUOaW5b02U9TEcmJvdxnKYQd7fW6dumUEvEWjdrTQ4ylOzmppZIhCRJGsexmbr7Vqv10Bg2Gpwkjcfp+ffPQpwpZc5F0pBSlhQ6qx0xJHJFgowyUCJtjZkTDQRSrhMPV/nkoynpIIchD+qNWQ7TJErnu+dvf/vt+rQex5PnPFNb66LMTlxhlORwc5QUvgf2tD5/8/03m66f1I8P03FrC2BjyUnrtjhZK4llGJ3TP/z6N4/POC+IaTDda3kQEnMSqQpV9ZB2b2A2FsqcUpKnx5kM2gzN0NCUYWAlMmJFDOsSoEQKisHXMPwweNO2Z8y+7xK7KTqRx6hZB1g8YOf+qnawHdhh9JD06TuTE3WKNLGLu7NJiI/8AOrurrGx4l1dAdpNSt2oe2BzbFwRpciAFxaMY0/NI7U129GfTvDak0oQkcUa+CH8QWrQwE8dIZv5ir4SIEp0d9iCxuKEPlnY92Mma96sSU4kzC8oEzOx7v5QfyzL6bCy78ggekShDlkh2gM7eYYQs3WXPPvVx4ZsoTMZgYlj5MXVlXrG4DGLuQ+vBJDZ7Y7xKq3aQZm9K9F3p6DHRcUQpul7HRUkYo+yzWmHCaKw6SBSTIfSbnhoex4PernsS/FwSUgiwroHOSmaNJ0b5u578N0R2b7T9h25zx/u22uwyTrFD8Af6LXvCVSvRGPt9BvnhB5S3bQDV9TlzwC4WUcraYe+vLrH8CIR9lDeK7VX93hfqORgIovWIoe9Z1R4uIwMvV41l+cet5H264xvvaBb5EGfdFyY/y9/NACE/U51OFPNwESJAuVvrlBPzChFhIhMTWGo2tRUTYmMiVkKJSI2qEOBDKSQ0mLssHLX2WPZNmcWFmGHVYCdGCmWZeKUhd2gzYxNRCQZwt5eOHffL3InxSDlw7fv797dPX04YwMxwdwNwlLGwdRnm6u1mGLuqkDxfrtDCSGYAEYSdxdQltTgtW5tAXIG6jgc3Pnxad4UYBNu5us8L9u8xQOdsTl5Gsar07W51roxAdZac8mUcxbh40c2z8t3H55hePv26vb4ppEv67mRmZATS85gtqqtQshbSMwptNmbNx8Tq9nW6qptbduq5jCd3twcD9dFkqutS801F5lurz5hT4S0fV9/9/7b6XFYfbXqy3lrm54nnE40jb627flxTmP+4rPPf/Lll4dTar5Ur/fr/bM9nO1pOT+d16dmjTwbYRjLVK7GMadiTL6s57Wd1TcjJQFnghjMiJXYiFDGvM4GRWcD9kguMISaAjFCdFXhHDbVSvv8llltzTYnHY4yDlmGNJzGq7enw+1wf/7917/4zXDDNBozVbVlaePpehyGJ17HKc1LrbX6tqy15lxLGVR0WZZhup5Ok4lqa9W0Jp9tO7fFsp0+Oo15rEvd5lp909XO65JEhqE0Z6Jnh4FAziQSQ6hRF/AuUHhxr+0Z2o6DEDGHJYUDYWlCvjeyLwG0dw0cDnam3VQFbq5kZGqmDnMykHLwkBkvPaALphMhumtAvZTP2P86mTATJ+bEMq9Lh4wv4Yj63M8OcYd0IcII2xnGELIXHCcwMoLE6J6zk7lq0ETc4brPCBHAYBEWVttVKQH3cAnuBJxXd6ZHttftqH2DfAma1l9retlcyZ13yu3+DJwc5kly9PjIibt8pJtztHCs+8PHrB8BIOfozxg6RO9E4Sbbo7GHeg5ZZDWXfWxv1ex7dt+qtOcnZLsQ1h8el5sQ/6/4p37wz+S4IJXxxP6sACzsGRV1lri+6g3uj9l7VqYNcI82aPhHuFcY0pClpCEPxI6mzRW9vSTMFDrYMVdDmZg5XkHiNE5TclnrukmACeZEJsTMMpbNZyYhyZkzJXL3uvbMmKORwO4cOjjGxC4hAANDi5wiskP33l71/qaBOnvKvcPlRByC3c02FIQQmP9oXb8kNI5eTkPdWa2ZGTuYOGUnDjVXcxBCY054v6Vxv8OFAUCA6mBhZvbaQYfIusztokHYEzQmNbSlJRfkXNf1w7s7JzifPv308/vznT28nzfdGrZWJ0plHCRxrVkS7+YRjVhPV8Mw5Czy+PTo1NxNraYkwzCkTN98891Hn1wfD9PT+WlruL45XV0f5nlpdWG0VDgBxHQ8DsCg5EmIKJljGApzjrDUmmmzcHVyqjB481LK6XBFkPPz+fl8zmxMlEImJLwlPMTuXTvsLyAT4bAZ8vBtDGGruKGy66bGEVVQp0r22+sIV9qufGxELBJeHcHA6pUWcR8sInQKDXlgrtR9bZmETTWlxGCtui5bXdTOrT5samZAyZI48TSSCDOPKY1TQaaneTk/zMfx1pq3VmtbvTWg107sBHKWLi9OIA5ClJlbN2lJkl5vLNEMIQITGe9wQR8Moi7j1RFnB2cuqaqu50VhyICCpN8g57hgd1d1mIuxH47TeByU9Pn8/PT4VFsdynR39whFba2UnE+pwTjT1tZFF2JwEgdUNWUQ08Pj+7p9fpyGTz6+mp/ncTgW4c8/++Ttx7e/+cXX/+E//AMIxIlInBUJis2JUiIArdVYFOQ7iYOiQvOX3cs8GlDECEdeIXaBM1lre9O+LxMCLp4yu1gzwYLSeSH37QvG3C3cLY05EYXcDfvLNPWlVCd6hRUCEAkYOwHs28UlGTBsa3t6PD88PK1LFU7H0ylJLqVsa3063z883j88gvn+3XvUBhFM4zSMN830179+547TCVfHdDydrk7Hm6ur6TDeXF+Nw3g84otPP5+fnlxb3RZTtLo10KawTRPL9fX1aTpMeWh13epSSqBZOZFsKZsZE4Qlp2xmLj6N08BFmI/H03k+u/u61nlZaqu1tWmajlcnSZnAOaUkUnIpaciUCKTNhE2YzHw9LwB7dWEuKY150qQhf+2gzOXmdAPm6+XqYXk0skIpHaZpmN6+eUMVUCQIk4ylVKPH810zT8PY1NNUBDWVJFkOw/h8d+9kd4/3H+7fn9fnn//8Zw/PDwRMRYYk05CrDpSEclnUxlKeZbMd5qRwyzI0Mze0rWprRJBERC7MwiVxdmdTbtoI7KYhyxb/NSd28n0KkJwCwNol6nrWq7GeY91YmNtRh1Beepd7k7xrQUSEQItNIdgl2EGwvRt6qaHDyIkaue4Zc29Fdh4+yHcJcVA4rTC97jEHDcl73ICZkXXDvv1V6sqDe1GwZ/f+8tdevXS0n6KbmSloq6TYxX37r3QUg0AONlBX8xKCg1yjv2za011zJYUTl90S3buMCRHRC3Ps9dEBGv/RP/mrFrTvsfhl+90v6TUQGBctodEkuyxTzxBZCIIww4qSHRQNBkLIavkOZ+8n8JJfXbarwJKIiMnigXSHeCeR3vlWdQ8qXKyTnliYO/c2hlGvO4gYL3IIe2OSLmGPAnhhd2rcEAy+bi6Z3HeiHCG20Dh9s4vaShSTjq4v/IJt7bCX/+h59IZEdJLCvivk4XfdWRHZy0HCvi/uubf3eor7X9EA8kJPDoEUdvz88uAuAFpXmDDrPEEnWFfB7P+07zWXTK9fUv/+a0iYoqy0WPXhRcvogjWv/nr83S7ADQMYobHj3cMwCHcAiBkgdTeFizsRBKoxyI4OFhZmYRNDbWBAHMk8PEQhFghG4pQyJ/HKOUbpqrkTNkMw+diHMXe5W9VWqwIkEhNWcSNzTiKcKaFZofTLv/m7h2/O81ODQxcjQFsjJyoc3KgYKgZzvB+x3B3o3G6HMDOLwojAwmQGZ1dJ09C8WvO6tLa1YeQWDqm1ttp2pp4TSZJyPBxPx6t5WZd5W+q2PZ5dbZryYRrBfnx7RWNueNxazccBibe6OmE4nrySeVvW1rRpixFeSikRMTFr08PxALT5vD4/LQ5NAiJQtZHK7Xgax8mrrqhP67MZsRWrtJ7r+enZZv3b//Mf8QiseGkyhgIpAVf4q7/8yZu3t28/uT1cT3m0Tz57e6vj93f8m3ePyzpT0uqzt+Yq5INqq5urVzYgVbXNoCaxfrzbN0hYrWA4FJutaYUS1PeqpL8mqmCAhWL+CgAJOV+ykQ3WOPnt9e3bt1enq4kSyZin28ly/fo3j/d1/dnpjUp7rs+bmRo+3D8c22k8HHWloaxNrWnTtVWtLnDD2ubVx0Sy+kJCxt7Qnpbnuc0y8u3NR9eHq9/88teppIwMqyCDCfZEPuekrt4sXiY3MHddPtqZyv3l2i9yR5M4hgc9AiAFG7gj4h5p3kU9OW5FJ3D2dkBscwDgZho+pMFfZGKuVPdWS3+p42VXU/LOHIa7mbKxu/M+K4eQfotNJcpFdWJz4T4AyJFNIiV2cSY3hksfnmQn6sYNr3JM6wN8cf09UnYAi0TCsDef57PI7qQKjwGTKItedAr2MHfBsHZIinYOtu9b7G6E4S/RLwxt8NIBZCZkyebNm/V6281bzPfxJXu/lMEvpRuBnIRTBMbICLoiww5gBemj/1V31WjCMcdMf0pufZQqxkocrz7/9Qb0Q7LVj07m8q9/sHH9//t4fbf/3ACsOH70wCiMk5mJSLf28hNtD80EGGzztW0AOKWSR06ovimtFtoBTGutYXWEBFFOKCIyJmnaRFIZM7uszzWYEo00sgCRXMowLwCcmFNJMEjjpmaq4Hj/HcLOkfhocK2ZIUwGJo4gQQ4LLXZFJDsKV4OEyhQEQkTCZG7mrTU4QhKIL3T2fkdAr+9SdPNwMWyObyDnpJ137IDBs4gXhMJr3NhgmLubmTCRcdinpawwcnLtYxbN4epCLSS0SAXirbU2b1dXp+tP3jyc7x8f7j/QBy/2b/7iX/vv28N8h1W1Fwc+lHw8DncfHr/9+t35av7JV19VbdtW39y+ORxP35/e/8e/ufvV1++FgW19c5pSLuMhLY/IX3LO6bszoHj79ur29ub+vT2IpwTqjx8lJyfouiJa0k5mypCU5Xg8LMuyUVOGd8lcYsE4Dh998ialfPdB7MO6LsYciaSDyNTcWNVNu4VWNGOZLy6OXbT4BaIK/lHfotAz55081/u5QtEqj5IK5MSO3WXVoQYCW1ha7Vuke68YL9N8RExJ5OF+ub5OYxrVTdXOT4ueGyqScE6JzZ/ePz3dP336+acff/SWCE/1+eHd4/L/cvemTZIkSXbYU1Uzd48rM+vsnhuzs7sDCECQQoAEQApBEQr/Aj7xf/IzRfgZAoIgSGJxbM/R3VVdV2ZkRPhhpqr8oOaR1TOzu6AQwIrQpaW7Kysjwt3DXE316dP3dMmbtJTFFarFtYlZRgEYymYEIiYvMVzJEIMT2DiYCgHfUCxPUBOEImJnpqqK2HA/m/6Bx6SrsyBl0bKM40WhSCBzSoTYVGI4nqpXW9RElTMNu3532C26TON5motk9Nu+FMUmMCPa3+7P50tVvZxPwpyGzIwyl3GxfaKUpNb65ptvf/zjH3/xg7vdbrPZHI73n9zK5TL2w0awAY1eDH1mIvPitcCFObl7WTRlrP2jdY+hqz1Kk3SMxheHtRIE3MC+9XlFUC+ZQNHVQYwgh+LwWnr7KnDW/hiq7OGIws3qNPHq/NQU+8L8yUk9zCFaIuIcUY8yWTdH2gCCRP0RLSG5PdxsyeZ5cULuhnEuj+dp6HCOB8thiiTo+/3h5vb+08PDEVkAw+Wkw/H+cLg/Pd5ut5ullGe3tzD/z/7uf/7+7Ztvvv7mw4e8zDOzDHnIKZd5IaL9ze722U0t5XK6WF2Gvj/s90ycuDvLBeaES5YkLO4uIl3XUbOi9ZAU11LPj6fj43FZlldffnl7e8fE82Xu8yCcwwEA4HGaVZC3fZa01PLwcFR1cUH2TdptMjOg6uZqUAHdbva73fZh2uI9Pj5+KBV9P+z3u9fDi3fn9x3nw+4w3Ox9k/3hw7ePn4qpCp+mpd93tRYmJuH97cFU+yzT+fLp0/vtcx5CvgAAIABJREFUYc/CWjVLyiyJgd2eE5vwYvZ4PL1++brU+2k8XQzOSL0LYQagvtQFM5lb33ebYQMiUyKIVh/HZbqcc+qgpgIYuzRlPAaxE8iM4KoNWWKiJtka2aWnLsPJr2K0MAOHJSuvTnHedhJIOKI1TMYcSitMej34CSFa9SjMvUJVUVeshj1yvBCGcCJFE9qgIOYj3Cy8KWWZUpMp9/CrZm2n1LAosifEJyiuraH6GRbTNscGpeCaepqFNDcDBguaUdgfA01+g5mJuJgztRlzYoaaN8QihsYszFEgzI6GQzJbPNL01KNtZ/IEj60+hys80mCWBv6Trfkrty2EWxxxEEiDDkXeCoMAsAyh+8EMEqZEgNo6KEbwVfYDDasMz8WWYl0xkTbYKJ8DmjHKZBRjP8GICksKUzSunsIlHDywfsBan6H1ctrudS39rjQGoMFSxITGWXD3MBBIxMyNSWdRcHECnNpota3dPV+rOvvsD3GNrR6g7y1btLot+NPMrdxsYu0t7WzwXIPmyGC2om/QqOcFRCGlZBp20y2Gk7s7XZ2Rrq8DELJTwHX6JtSjwhjG2XkVGnsqOfF5SQP4qiQRK8rR9o6GZgXv1j0qalvF3a5z7nRNO5r0qsZkLGUiJheq5FqLuZE5J+IUoFd7+I2NEiSzQQjsrg5UU4Yyt/wlCZEIJ5LE+81gGm5w8GLqjfafCMIswlVVq9Wl1FigbqbqSmrWDbmnnE1o9o7z26+OWLDB4Mmn89zlbrFSpmWm2c0VlVI8EG7qveRAEQmtEQRGWLlq5TDZNnOWLlESpjphPk11oyK8O+ymZYanuljYfUIcHYah2263u36fKM2PDx+/u/elYnIwXLlO42ma//jls/2hz92mzCWl7jSdj8f7Luf9813KnRoxpJN8vFzG80yMftj0267vN7vddpovzDadp8uDIuHVS2xyN+QuW/KREnVDNzw/5JOOH98fv/7q2/dv7i8PWpbKDnpLMM9dhqEsRYS7vqumy1TA+O43H371r387bLvbL9PN6/QP/7t/cPPi4Ac7nR9EeOg2y6LzqIvZXMfjZbbq7uXu2dDv4VRaC4/BjiwMl8SVRQk19zT3hCU8W+BaG+HbGwP3yhR0DmlsA6CxCOoChW3w4vWzn/74y9vb29mXT+fHh+PxOH4qOr+8226GbaV6mefMOnTd43mshf70l39zfJhdJfeXcRwf/WzkEuYcHUh8nMaH02nIQ9p2DC9eipbU95vdsNtviy2bvNv1uyJlXqZlWmqtbi6S+r5brMylRErWOD8BDxuI9Cl6o2XOLUwGv5jM2UFMTkwMeFj4+TptbaskVhxMEu7UMI8agJmsIKJbYpawdBWCl6DSc1MJYGqoGjX5iEjvqulKcYrNRU05GJ9x1gpXONsV93aJGOeUmBOMjNibGR+QkJyblA+UHEZGqk5w1zbPxytHO8IQs6SUc864+PVa10WAeJwAI5KVZ4sVcL12oqiFvvU+r9FzrSrQOhwiJEhubh5SKwz3zKKhtGFr48rMokNATe8wRFSDK/M5zCRRcxMUxsHjRrREiEAwdg98wMwd6oBH71o4IZlWqKqZutpqnIvfOa4oVWw0n4f3721S//9Cr37nIBGx78tA4C+4Eb9//Ae/Nb//uW3X//4ZPsGuf+lrf/+6ABAJMxKHkbq7q8HczYWMXAl5yHnT8zZbivGDULmo5ubLgmqrLgw4gTtOm0wppSRg0uruXpdap+pjxeIwStJDQC9YSZlbq5+IzOtSl1rK55J4qaeUOGYMo/9WYcNmo5GAsVEizkmcqTLUtFRdVKu6OrRNXAlJktyxaPbTfrSka/W8avGuMhUiIYTaSDzs4qpePMqGTEmreTGvAGGz2aSUai3TPDlj6DsXcGISVliFSSLOAoJ59VoAd4UVWIUw+tTlLHMpRNJtBjOfp8m0upsCyEAHdADj7md3X/7w5e3L3cf79//2n3/98k+6Mi/PbtF14m7b7f7u2Z0QTdNcigmlrtswJ6HUdf3ltIzTdP/p/tOn+2nWYUhdRz/58Y9/9vOfvHjx4nR6/Obbb9+9e3d8/MhZzKzWstns+r6b5+nVqy+FGYZpnJZqu822P+wr6OHh4eH4OJ4uy7KUUpnTph8ONzdDP4ikRClnfvfdG2YCaJnrp/uPL1588eHdPascj5ebzV4XzOdpGSsXCBLAtURbiVPqoBEc1VTDwys5ZQptFJhT8aLqpg4GdSnlBCZ1N9d+mxRO0RUkN3WzWku1BSBQRkoAkLsMgZNVVsmch5S7bplKouyVlkuZTpMXQIkM0THX4sKUMleqOuOLP3leklpnlepSl2XSnAcCdC5aFIQu5ZySqdWlajFhZElJehiXpdS5lFJRAEU3CNrQuXvM/DXXAkgGD8nJqxuSIxN3QllYSM1MC7J3PWfubLJyLvXsqEjErq7FJUMVm+3gPWYslC1v8/b5ptuKerks8+VSfnD7pRO9+c23KMQ5w42JmaXWMgy91lJ0uX2+VdHjOD9/3u3vhvHy+IufvCIbX726uz3sp8v51//u17e7V6+f/fL4Tv+X//mfHd8uTLc578wmtRFazStYE7MIaVU3NFMWa9KdVy0+Mna0FrprdKgaec3h0kt1DVErTpySpJQkJYWGgLSZ+irT3qpZgWTmnNbNm9yb4EobanaHKhwkLCmF61NYnbh7mAfnhLJg222Fhumx1Mr73Qauj+f3ee/DRv7J//Q//v1/9Ldyd386v/mX/+e//upX/9Ygz16+unm2W+o42zJPy+N5nmff7J49u7vdbLt5HO8f7z+++6CKruNhGO7ubl69fi3Cp9P58fRY5/mwuXl29/yL168O+xuY39/fX06P0ziWZSKyRL6U+csvvtj1/fh47rr++bNXOffu3Peb5bIALkI5p9wlM63T8unt+/dvv2OmH33xo8PhMGw2wzDM0/Tdh49mfvfi5f7mYMXqqfzo9Y/6fnM8Ho8Pj7X4kIcs/XKeb3d3P/ziB0PuBFmwmc715eGuLnPHKSW2MjvZZHMBNPsZ84b2BcstdsULEc06/+btb//821+fbD5T/c3D+/fj48Q2wc7jYx0/JnISyTkV0/PxcVnmZSrj6dwx/od//N//rT/95en++Js//7Obfd4chknnT6fjZame+//9X/7rYtmMKCUQTqfj+VSXygwZJ5sumlK3390Q5DRO4/0DKpApdUOXug5S5rKMo84qSh3lTOLFpsuii8GbEtMqILTqP/PK7yE0JaO2cQU9h4MKoapm1vSJorEZjeRE7gUU4upwRxsvWEVbyVmIiMQqXH1lJyKMy1S1IQUA3DVoO9GaxgrZO5AgiblLIU3eXE3dmkNoPBStMeLeFOKBgK4SWXB9aNVqcmbO0WMy81rNVL0qzRq5LxITuSIQXjSiSAgRk8tmq8E8XacC3dxrbYZUFB4O1HWJhWutZSm1VAAiolVBFKPDAZy1LrF9JnNLhOCSx3Q6iACFdQeknolFVUvUUUmYudTqgQkyWIhCSlZh5uzCoa7NXGHqZqhOLgIXkIDDhYPFzbRqLe2SsVICHEi5bz5P8Gu5QQzTK63C1RRIrbVSnZTIwE4N+nIQO4dTjqCStaXnHNQMrRWq0NZvI5DBuzvmnlnE3NQUKQWzJsZncuA9bqZEzg0yRcyE2NAPpZRSSusPhhAmiCWlJKELY00M/mnWJJYP9fxE+wNWAhohUCeJfrtBHcQpJxb2JvurcM/cCYsVL/Nik5ILQQJYI6LAwrbDYKrTPAsF0Ya01mIWy7MpZgJEzMJwD+KCmZVSKjklSakjcjOrpWhZUpcCd3YPnTMAgAQ5l4jZgnu1TveCG2rIEBgLUWCZzqaAwxy18XQS5z5zJ1Wqim5Sv+s3iXOpZVxG3mYVm3U2rvvdpuvyPM7nywgmzl3PwiARHoaemUop0zxNdYJQ6tJ8Lr/45c+z5PffvT/dPw7dcPz4yIbtZivMx4ezFu96ys+G/evb03jq+q7octGTJzhhO2QuvNfDi/7Fv/xf/xXNwJjEWU19VhClnM3cmtj1U62bo8cvbmxg91CcNvcCIPVpz56tYClTf5t9d5q75ad/89nwQ3/U++cvXw7bw/k4f/3n7x/fL5sOnGlyH4bNy7tnZSlv375LJkx5HhebTLquGwYHTfNl87L7oz/+WUr8zZuv3739JAN0QTfg5tk2993p8TTOdchpK5KJU9+RMLKQCBJ99as32y3tN9vtZthutrths+mGXdqQoi7++Pb426++/fWfP+DdGkbWua0E+JHZxExjajzYO0igDM6JMzGzky5dhQAVGPDDP+n+/j/8u3/77/3pv/hX/2zx8tXXb998fNzuWPr++H6cH9ENePGaN7fWbxlMS6WcD0T9eJmneZJk+25/+bp//LAsn5b790ek/nb/suMO6nWegTpejtNlloF875ZaMc+gw/Zw2O//8X/7j71oGZfH++Pj/XEaJ2VWoeqah/Ti5UGp/ubb3xzH+/6QFyv343nY5v3dlkUu9/P9h/OPfvjjzd3uN3/2KwxQnZl4WfTmZm8zTh9P/XAwKwXT7d1+O+ynx/HyeNnm3aev7zEDQGKId13qhmHQUj4+PGy6zTyONgN1VXSyJk/JknIk5a6wqwyjEwlz1GPRznQzT2AxblhGq18jS1PQiu2bQznpql9iXouZauLEzAQxVa0xVmGb13tPkNAHh861gMOI1sMKu7pBQUps7BYtAQmzi+kyoQnZOROxwJkUqNUAcOaUU+ifGcGsmnsjzhJYPNhVHo6MEEYisAXcX9ehYScijijnbrVqqTWJRDlvYZPiLkLSPXU1YluPAP15se8Ac/aA/towll8hBWaWRG5eq6qGbAYHRRREiVi1BUdmTsQAB0geOGKEXPKGTjBSSiIsDlcth/1+KVOpNQTZw38xBOSTCLOYW6k1wozHrFgjg3NoJoYzSRyfwRdP1KrVsGT9eVTwRT//4bWJEicZPbYwpfn9468L6rriOVeM8g/47/3erYgjXVGez1/z+5/x1wjj/XuCa/+eZ0jRwQ2ROXMQr9OsbgQIGp5aWF0BWFPWs8bvD712AhESE3MSiIcbkZOH8XSC90BluKJEvUpWnTsWFgeqGXPwJWNMuUHOYFR4dRXVUI8ICTnVauTKjcAJVycnNgIL2Cy4FK1laE4wIyuFXd2E2RoJ4ekGErVWWCx7I2cWJhbnam5oCnQhnxslNQPkJmZmECNzWFEOhmm4fJpWIBHATUCD2rxBpISoVr1UVSfyshQLBTKyoHCuzWOAoFWXafG6vT3c/OSX03m67wWZZci9k2+63AkzkefkXqyUZQFBhBPg293QD3m77Z4/P1QtKWcR3m63tZaHh0+1VrdalzJNNaMSk7B0Ofcps/n7N99tt5u+6wnohLNQJ9J13bLMqnXIMo7z6XRZ5mVZxrJ0Q5eyiFud5/r4+HGz2aWUjErq5P3Ht6BsDDCMA6kCJ4a23WkVX+SVUh8BsfFcDeGMpIjfYxIm5DC59UoWvV4mgcOsmplHaXcF4tMqHAiAoKagoPGxG9XqQGWwq3t1VCdlFMCIiMXJzROcDFDKqVNZ5qlap7nP0iUwV51zn5Ik7dI8jfWiy1yKlU5yHlLXkZm6cyi3gkGZE4mxteYpELywYPi27DjBCDpXJKQhO0O9WAkPr5jFFeldVamWPnXdLl1sKmdTDfWEmBlZ53rYXLHUkhemLhmqWUW4KBBJn8EkkpZlYYCZupRSYq/RWYl6De6sFUWhBQ47nY9EI1mVhJxSl8S01uJwglDVEvijx6oORRin8Gtfi3mE5PR1JClGagCKphw3lkUwJmzVDYqmMsVWhGZ8YqoWFe3TSFGwHiBsXGr1lbXwNBHlTe0/Zqedgm4QjaV1YKXpZ0PVE1NKCRaoxESdGyF3abvfqvvDx4fj48PjeWLeB/kjd5tPp/dG8ET9tpeOh25IWdxLqZMQnr94pqrLMu8P++1+X2q9vz8fjw/mvt1s5mpfv33zzdu3Q799dnf36uXLl1/+EKaPD58+fnx3Hk/LMn33/sOLm4MXXZYyT1UVzHm3O3z5+gcAkjRQgNmZWWPmG3IZz4HTb/pht929dh6X2VXPD4+11L/x5d/IOU/TeDqdLtNoRrVYpjLkAYmrFpNErEReoRVu5KXOqEg5q+l0mR6m0+S6sD5/nXSuJ3CXkiQstU7zPI7zzIU3cnNzGKVO4+kynk/nY1eX4tYEAeEFViOxZcwF337z9gcvvtz2/bbfaqnzZUbGMGwWHR8vU5f7OtlSZtQZXIsqJRw2maUfFjrlYirEQshdIt261mqutZR6HhfpGUgpddRhMZ+1qjEksYADvVhlOACsc0Pe1uEqdrRWeo2JBbcw7DN3M19dV9ueE5YCWF94DU50fRTAxCF2QhyuKS05cZg9LeDGKG3IAQf+6sRoIK0gRsBaZFECu6opgVd59cZV+V5q2PhNsbFiVRkJMQA3twpTWDVTJyO4uKkTxMg56CgOWgWX1o9RMk9g5xigRggUtT0PQCh/McJO5Yl+C0ewdpgbfuCmbfShgUF2vZNPiomxpcvKH2Ks3eh4i2BoShv/MjitVuBhYBcATDFVNydtUt/sV14cwO41Ki4gaNvXwBNfR5tEbAje58S69v6hXqtO/HQ3mNxIhNcs1VeC2nUqrb0LBWLFxLZyAL3NgzQtcwfagEmjajUBT/j64fx0hwlOpLDGMCJq8p7GoVyMp5UQlQDhGskBpyeF75ZhtSy62SnSdRWFYECjjHljRDnc1SoaPSf8EKu292bhSKEskikhhDEQASQSjvVxPm5mwVy55njePpiDw/XUBm6J4Gf7xUrdaySs0GK5kr2o5dYEKJmQKPH12YqmDIRAADtnogQIkAFydS1lcZiaqep+d1dZqfJs42LqUy2mSAwDA0M3dCmzOzujuiqxcrJMxKSUO9NSvFqtBYzcd7fPb7z6Mi7TvAQTs5h3LJxIWAjXaIG8oWHbYyKMJKmDA1XExNVXE1So6TUQPSXkTs0SL77zRsp0EJCCvRLTPchdMlS1iox+J/2AaRGFL0tZluJmECTivh+6JNUMoO1md7eZ7z8exZlVjEmoE2Rw6joS8DRWN318OGOCJsDAjq7rN5tNmXUaH0/H2u1pt8uS+TJN58dRurS/OfzyFz8dL5daCmtKln2W8bh8Oj7Mj6WMaqONH7U/0VycDRnkTm5u6uwiJjCOzMAj9gFe10BvAiEQb/JgpFVGN5zf6P/9T7969+3Hm5e9Zhqwu9lelHS7yY88FfMNYy62Afa7fpzMllnN+pz3XddRHqeH++OH282P7SCsSRbmSufL44TMYAG6LqWug86SSbpu0UWLb+7y6xevn93c7bf7/+Nf/G+2WLks42laxlLm6kSWUoWa1W/3m802F1/2h9vdsKXs+925eJnO8/H48NOf/jhxKjovHwv3oqj9MKhWVj1fTsk2adgsWr1WZJS5jHqxomR+eTxzgin61N3uDr307qylHI8PmSUlntZuCrTN2HlYAjrDmby687r+IhaQWyuF/GpborDoVK7KUF5dRIzh7sE2bQJR1raetQ3QopJFMIcRkxNSSlFIBi806D9ERNI2YmmCE02oxpzIFSTu3gJg67KuOzm18QtKAVZJVNiExB5pLhE8cdDVQaG36q7exp/NIllvAR5wc2OQuQPOTLa2DSjmOSId+Wzv9qvKyvePlZNF12h3PSNZXYks6CsetgMEczWDu4Zv4qr6ai18o6FGbY6yTW3D4GS6ElHUrJRFa1VVCpsN5muwtRinb3DV9XuNPZyjP0FtIPQvxzT8c6gdbdcgWrc/fJ/rc0VO6A+5E/7BH/6nOdqX+9kJNNucdWtru+0fOr10ffGVBW1mNURtPjuub/cf80L+6uP/+2kwN4ZhoyuYX+NFa6HFFJkWjXYprauyZT5h6+HC1NILdoe6w40hDmJOnChbbcSqMEaFpQ4pIN7qmhKnnHLelbIsZakhViJs0bRuHWByYgC1KgRrLFgrBnYiJwIbsXE1jcZ4dNYUDpi5MfOam65t82vJcMU7fZXghEsI3zbd3BhjcFBr+iohmCLmKFWFPEOosUXMzFXBJCxUC7IwJwZZdTWDhum6gdiqLgZSj0n4tZkfzxdjPJ7vMw+7fPd894uf/+yf/vMPmz0TKJHkvjtsdtthw8SZa+JFxR3sbaIYfd8BNAzdsOnNNKUEOBGmaVStw9Bvt8NmM3QX5NSlJEnyYbfv+25Z5uPj2x3tuq5zp2VZxmkqbspyfDyp1s1mGPq+y2m+zMuyjKdHUqPDfuiHnIXchr7v+76rNaX0q9/cP78TnUk6gM1FqBNSIAx21FbIwuAhUNkUyhGT/ZH0RVHHFO6NxEHVcocSMaXEIgwXZdOq5pSIY+4rbOibJBQohCpUOTWM21RnLdt+Z4patVY1NSio8bOvY/quqpKYiC6Xk8MHedltsi+YVdXVqsKcEucdu0Yml3NKXm1ZrBZ1VbEUk2sEIlJms4BNrnqWAoT4CzMQp0Ei4uRm7GaoGgk8EWXhqaqZS5YudXVWnxemaLxbYqmukf0P3aYfJO1Sd8jSo/h8HGdhrBrQ3qo8UycnEsmSJFWq5jB1FkoCIoYzQaalCNnlMgnrbtMNQy9CpmpWYAYxkLpRgwCJbS1s/NoocX/aUv9wdGvVHn32g1YotgBu7hz9N4c1d8EmBfQ9ACvKZ9PaqCCN0gWDr0M6kbhfi5lVZuxpCwEqFGq9SRIzGGp13W03k43dVrb7Qc2+fvv2w6ev3374tJTqAI3jzkolWPhGZSZCxbLUFO6Q/WbYDJuq+ng8dn3PwsuyPJ4ej6eHLg+77fb4eB7HZTzPBHl2e5wv9fZ2f7PfvXjx+rC7vf/04cOHd2VZxssUk47zUi+XuSye8rvddsssXZfjyeiSpJQ2u+1mt0ssAM9zqUM5ny6b7fbu7nazlMs4VdVN15dl7iTlLt09vxt2+3lelrGwc7ft0yCW3BMtVkmnscwVJYuoFS2665K5L6WczudLLco4PKvzNFWvt4cbQtJQKRHSquS83Q43tB19ulTGtl8+Hplci1VXBapZNVMAJMui33797cOPfrb/4sv99sZtMqpOYPgyl4f7h8P+AFrADDgkE13mZOZgpn5ITF0t5C6MJCIpca21lHG6XMxR51lSyilLElMstrCiY2IWSdBaVBGOYZ8tz+tiWf8nphwCNzIHhVxDcJ8jkLRfjZ4RM7m2l3KrCLEOSQdKESNgBKKnUcNANAxhEe7uFoZ6Af7Q02e0GSgmtA5zyxGvRCGjBjG15+z60FzfhqlZrIR0a4wFMExNi9WiUEMo3Dvc2lD/E3CA1nIWYmJ2oeoGiWYUQ3H1K2w1slOIiJkbYZ0sj1LRLbpKxG0yMZrYbGTElaov1zjS5IGvs3XmkBUqjG9LG9rwdJZX2AVELIAhUHd3lFob+yaUx9sMaJO6D0CSmZwjHj1dPwHM7E8Lpf28YVIU82hYAXpCQwyJLYxOeZ3SQEgntRvVwNMWniiEo4IiGN84rYT1Ro/6C/Nd0JOJa2CAIFQzA5xBja2HAMCBGEx3rBP/1LQYjFpfcv0U+t7h7qa0/u21KfD0HDERmM1qc7CsbmZEiZk0crfre3ETDr2qg3mTFXt6Ntspqvm1mF1nGFtCaEaEzyuBFRL8nWc7cM5IEOmqpB6Ltb2SPb5Dj6IOStTUWp1JEpGAY5wW7tWWMldfHF5dl3m2HJ6LyWtdrHDqdvtNmUuow7BiGYtXdfda61KqqoLMxXlHl8dJiHVWK65Vu9wb9Dyfy2IpsxA5+VyWPM3LVBymrrHUhaXrelvUrn0jg8NMFRYGx+QhP82tofhkmMLUViF970ZJEqYU6RyEci8LLS62v6HtXd/teM7z8XzKScti0vHhkPfdZrM/eE7Hx8e5VKGccs+UlrkAYMlGXlRXHwvMS9FSp8VB6LutUqmml3MxpaoqmQCnjCpetVzKPFUchn477PtuY7MlzQP3XORyHKeP0/1v70/303xGZ/AF5REoYAZxYoNVa8kBrxjDCrs2Cg1RMxZwApEq1KFKgD9UPZ7f/9m/e//Hf/PFix8+u7t5IZ18++FNsvzFy1ednxc7v3hxePZSQCVnvtvfCvZDf7fJm1KW4/HjuZzYtMtmW9/uSGe/PJ4lbYX7Oi1QTbt+n+FW1Uw7//mPf/qTn/xkt92eT6fxcfrq3/y6Trpc5jIDClTAAWlUn/OHR+6Rejy/eSmj8AEySEqJjGu16XQ5HHZl0ctUnr949u27b1Pqk6T+pj8/XsA43O3G0zT51OeOXGrRxJxSPj2OjV0FcJK86aBYYH3XoaOU0lP8bUGBLYD0gEFjS3vCidGQ/TU8rTHKmwpM8AIJIBKSdS4uRJQIq63GZ3lgq5Q1BjsAkeQiuesI1VxNXbWaKUU5Qs4g5uiNuws3wbbw+XEz91D4IxK4RSfBw+MyBf3zuk4QnYWr/UkkrkGvCD62AAhvIWvq70HxXp8zNW8YD5Gr1haSnuKge0hJBiK/xuErRnONa+um0eAgInYHO4kwYMvipuZA8uZ+EtwBc2dtDhZPuA9Wy9unbza6IC13NosxTrj7vJRq1Q2rM0p7QUTRForXYfPoK1FDsKL8Zvrsg/7iw9f9r4XndXSRrnfj+u8rOem6SV1Xy+/dt/+kx+f41PVsr2f4B7G26/+nz396FXHA713S9Y+ff9h/Gjzrd67h3x8p/MO/tgpQREYVQjuUmMKnoSMSQQSEUK4lb89MyFG1B3zVWmAY1BrB2rGO/hBBBibAYLYYXAmpYapmbgahLBIcHpoZ8wUACztCJY5CaBkAA4tqiGJen2IE54rZCZTChtCBUKZxt5awVljPicOQaTVzim+y5SjXu7KqWiEkP1pX01vDMjLISFmiojd3hYpnOAsDxB5eZk7MIlIwE7GIEMTFtbSKnlPLVw3Oqb3siBfwAAAgAElEQVSt82dSkUBVe3x82HxM+1139/rF7W73/HabZNn2fTd0Q993nFkI6shd6joSKYst82JmZZlBFBQPU/OcJHHOudQq7F3eYLc53Gwv0yalLElSytvNkHI21cP+5nA4bDebZSnn8/l4fFT44j5eFhG8ePFsu9nthr4XOZ39+PF0XO7JNd9Rn4af/Ognu91OcrrMI5+41nvJIiK5TEauxZCZzL1yU3yIVNixasa2LnK0sMNXpPFq2CWBEgkTDGYKd0j7J3N2M7dkLSlzAiAsAaEQiFmYzTxmcoSYiMx1qbjZdUspqqrVGo08cDUHOROpN6kjB2NZDAlZcr/pZ5sp8bIULwVAyl3XZyJyNU5JCeq6UK0UvTywCDGRXOFXunbD4VcaIBQgJklCiYISxMGmQDxIal79JguDQZH2M3HXZThXqtUNqbXHCZ67/ubZPu8Tb7D4VC81JzAhZZhSMI5NaxDEuKn2RkcItVpKEE4i4S2jS9FNL2aoakk6ovM0XS50JnfJITJXWv23xp3gAEdhirjSGOX7SzelSADgoBXgW8NZlEJGFhYGbZ4lYlR7uCmqu8DVkSWv3L4GfDbnQrnuExEncS1Qrp/lK5dNzZJkSaZmkrE9DONpOtxlEp/m8d2nT9++f//x4RIVcz17vu/SkMtyqVrNpFR3M0Xd74bcd7lPQql4pcTjMhYUgVCm7f4Q0j+n6cGcXayW8uHTdLl86iS/ePbi5z/76d3t4dWrl/vdZhmnWsa6XJonNXOt0/l8+ubbb/p+2G03w9ANm83Q7Ya+4xcvMici4urLsgB8Pp3I8fz2Wd9tk2Q1G4bN6cPD0He7ze7Q3cx7/XD/cVnmcV7KWcd5NLJFl1p9ufjpftxs+2fDDXespkqmBEl5M+zI62xKzvNSJ63DYUcQyrI77J8vz+zkS3Kl2mfebTLSnnn33eXorpPpZBoUHxOCsBOL6HyZy1iW85w8ST540urLuBQ3hlHXDUNPYBYhEs3JaK6XyeY6MnLu9ynLMoMAasZVSXIP1iUVuzg7V1U1R7VIGMxiRAaN1/dE24tHENcdZJ1y9daabEhq+KLF4l+9amPc3teGS0hHtbqYrmNlq4TFEw+KyY3WXN4D3GpD/Q2vYCZf5y2wdlsa4NKIE2si4N2Qg/wZj6Q8rXQYQVaSIphi44e1zTSitKlpNZQaZMfm29S6xv7EeyWQE5oElhjDqBAzuL1vULlXgOAJ6on7/QQbxbMs1FzYiBDav07kzAGRiLmtnnMkDRJqpY47WiS8otutZ01EQNA+8STL0XibK+BiTwU8BVwFYolORttlUhQk4SnuKwjuEdvXJbPe/zYk42Fh3CKiX79UahblLYI1EMpcKQgGAb09ye23leKRa2FdQVEBPi2G30vKHQ5EnzHQy7gvZqbxpQZw5dAVojWK9kN86yuOFuSA2L2uljarjjtaqXRF7wCgtTuJVjgAAmituJZw1lDUlFNIrlD70mGm17TvmnibrbOx8fHr9cbvmRsTMXNrbrStQq/8vuvDAjQ087rRrGcZT/b3ca5YOWRog5jWlmuIlwm5tGakEMNFa53nQiHsmv3x/oiN8DaLiEHNScCdZGLSUnUqY13G40UXJYcWt6slGUMNj3zabAcy8mrj44getWipBgEl1qrEKMtyGad5GV16YufEEFgwLaqjxsD9FVJdyRSNhRY3T9rjGHdHyNBkb548KAkcjDhfcYUOWkvaYXs7pK14UmY5P8xMCs3cpcQEEiWkJH2/MbNSVONxZLCklLID1QtMlTWjUzU167tBJR92d+N0OU+n46fzYzpvdmm727DArJ7KbO6U5W677/tBFW9+83bbbw/DzUa66TJ++ubT5btx/m6pF+CCpQKGpOh4YGcv7lVJmYlYJLK+YLf6GuY5hXUbg8NjhrW6wmEdxKmQq+Jcv/q/PpRZ/vS/+MX29qbMqNP48vUzJjlezl/88Pnhjj99+rDtN2lz48tGdAPtfLY0b3bJu04EJ3LrLzyh4MGM5sXLUidQ2uWNDNRvtjf7w2bfvXr9+uZwc344v/nt2zffvJkepjKZT9FQYY5AW0BGlAjVrPhyxpuP79EDN7h7trl5cdMPPR/o62++++nPX3dJFvHDzfbNB3FQ1w2H2z1BlqmmjlOHzlLi5Oauzl3HQuyTVQehWn0cT8U0kzB4u98t09JydwYMAgGD/HNI4g9X5o144k8Vbgh7uzs37XuAiIwQ0oTRyQnDk5bLtRjPgnW2o7k5USJJzMLkBIW5VqtQc4KrwoHEzczXmUVA7NVbc2TdickBUnImkJM5eYzeSXOWAqEZpVznwUMFuVwl80BMbQrU9dqw8aZg6Ksh4ucOqP4Znt8y9RX5WcMw0e9RlqKo4NXJxdc0AgQDMTtgepUviFeTxZbqa9thrXxDrfjzN/eWL5CDlYwsvJBBICbSSDaw9iu4fX0tgD8BWJFncbsIXDeO66X/lVjH9wL0VZXye79xbX54S02wbiKftTr+OjGs6/FZi+WvxnkoqB2f87Wuf/E713MdMMRn/K6/aJbyP+DxO9cQJ3ZVtfydn/+VL0fM/dOqaU1oTComQJ0hWZAkJlujFgXCYZp5VQQgDiJjZE9W442CPyJQaOhlcCL0gWFVqxAmd9eqGn6hYI2xw8gOidQsJqqMQBYdP7rusEGeIgIjiJ0Kqk6CgBoSGuXSrxCEO7mzsdDKwmB/MuNch4W9RUJ39VAkWZsuaLlrjP3Hc8gWXe9rA4A8EhcmCGdoAYGJRK6cr+9xSkgopcTCi4HhxGJQUCUmZ3IhJAdsu99Xu4zjeD5fpnH6xc/+6LCXUk6JmQQC1lKtQpdiZpQ6IVK4V62qTQPSXGt1V3Mk6vo+p0REKGUpy0LufT+wCAExdGeq8zzvttsuZyKqtc7zfBkvzuAMArTi8eG+LHMWgVEi2m2TmrqWZR6zUN93bkouQ+5KX37wA7q53deKeVnmuRYUkQwBZyEQzJqlo7qHlZkRs8DhZIJEpJ6cdEW0GC5OBBKwiUEBGIeSo3DUFmtb2GLokJsRFZhZxN3ILNqcJAxzqKW+q3MzgVofGATFjgjMbERk1cy9awCKkBCzujNzN/Ted1FRFK8wgFxVzbyW4nAkmJGUtUNCsZ1ERLfo+wAu0Y8Bmxux5D5B2NyIkIidLEYWYGrVTZWEhcVMi4GYcy8wcgVp5SQwNSghsUiSRMA0zY/j8eFhvPuiI1A3ZHLeHzYXnUpRMFJmlhgOCi9f1FpRBYkJzJS6PGidZdsRFa3FmWqdz4/zQKN5khQXqAQJ0bz2bKzJ8lWv/S/fjD6PYOsD2Ay8nn4ewr7B/v787Z5S67VCWqcRm8ZClEkUMkYBElxfguve/1mFCAic3FQVFYCR9R27qLL/+GdfGtWH06fzMo3FzgoGJGFUfXf/7k9++Tf8YmwFSLmilgSCQ4dtz8LH48Pp9LjMS60qSfa7XTd0w7YzNXMfFyUoCMHPfzwVr+V0vBw/vf/ZT3/yD/6rv/fy+bPj/f04Pl4u6Xw81WIiaRh6Znnz9s1+v5+n3WYz7JZl23dD7oftkDm5updaS7FiHIJxTv3QC1FVzV3/6kfPmXlG+XR5eDyN796/++79xzdvvlvGut1sfvqjn7168WLb78/H+eH9Y+qkvvry+fbAHU06C3O3GZ5tuuI4LVPm7CBln10dxZj2tzevktGGP83HZZkT+bZLnL1L7Dc3pZTHZdK6LGYUNqggm7QbrOOh5+SL6uJCqes7OAvPu80B3B8n3Ril3EkiSipiSJWzTZPW4mpzrTwv5raYuaoSMQv6TU5ZFNDFyjTbXKR6osRCXr2EbihCy/wpdMfmR84g4/bAYkV84YH4tMZPEExaaA0eCjncjMDs0jLJBpKuEIu3bSlm6yn0qlZTprasmZtaqjnzuh22ebY1cW9lqBFJtCIj8KSUNEbF1t+np/y3wTghsKvtnBD2J0xcS/HqpM3fREDSHh5Sc7CThQx+igTfsdJ8iJyjHWROZGRgAyMAkki51qjb5sSi89DqkEjqA/wIEXlzGIyYmUCs0AZzxMlGXmPNjzju7DUFdnNnNFwj2lwWP6PWXCZHSGJxy/MDjKBoL4V1H8GrAc4cOJCRc+T660TjE2qIzz45BtMsQJNgCAPNgFnaZJzVoCV4DI94TJM1Fur3+AXxRTTBqitiBf78F9bc43sxMkKprtNfbX2uMTcWmTVsI5qB8dlXDpU7P30KgGZY+P1hje8Vp0QgZ2KWxk1rf0creMhQAmjVDw77qrWT76Fw0cq02FvcKGrEJzLhZzIiHHfcKEz7sFaCvjqVtaumFYxuwnZPN6kBOcQxBEDuV+wajgowmJCYmTRUNcSjQcWJXMjZoqSFYinhleRgqBVUT9QNQ2+Fx9HKvMA5SybnMi9cHYvb7FDYEgtQCKhsGH2SaZs3HfeavJZKGwYUAk6RwjkAzmnoh1qriBjcUaIGnefZFk/azcsMgwtQLFpELcNeeY5tzgFG4NasJUfIfnFDVwkwVwJx66/ZjMlo2b0Ytne9SpnnUTvttnmaqxYWFyv1NC18Hnd3h/12l1jKVGgMKxS4qKGohug2Acq5MyzmJiKUEqUUz7gx9R1vtn23EZCN83LRykw3u93Qbebz8uHNw/k4//TV0PcDLzx9WO6/eVjeI495o6LwWpWUEqUeHZy01lodppIoiRQvjTPuMS/brjmK+6aZ5QBJAsW0NhMbXDHXS/3Vv/3uxbNXX/7Ri1/8+I9//e2/8aKS7dUXzzh5Kct2u61ToprK2T+9f6gXXcbZSkmp/snf/akI+k5rtQc6ncgKFmTIHUP8PD92HX/5+mc/+sEPsyRXf/P1t9/++s13v3k3PyrIvQAGIRG0cghOS5lRXUSYlBOqu02AoaBQ5892zw4vtr/+7jtdCrOZl3E8390czD1Jznnohmkax8v4UJbiKkspdVYREauubuQYICJkNC1T1SosGUmMy1LCtp0zoRKchCkYpf6EnF6R9jVIrbHm+2nimgeujZ1IhOMrIriTo8Ldgwp9BX2IsO4jHsWpiHAWCzm/WqtWs7UejN3KHBzmIEQUjj+IoLQK2kSxGNwBd4Oyk0ASMYd0l7oDhui1uBPU3aEGR70GWArNDmoQUCilNITf4UaNh3udg5OEla17DeTXy7yG2j8gee1GJBQD5G7rzXUHqRnU2aAW3eCGIXkM8VubC4G3YfB2T6C49tRaqi3hnu4hWMnMDmM2X4EBkajFWurufr2uJ5xu9dMgULBDnT4Xn//DR8AWT1DX55vj57/2fQaWr9r8n6Mo11P6azl+B32K4y9Cr556NkQA0ueA3BWT+0suJi719yGk/3jHX4nD/b97N7r204iJwCTCLOzmyiQpURKHW4x7RY6kFTAPR+RVhCBOTF2rI5EQMxI0iFtmYOpyEmaL+MGWO6mqparDUxIH1VrquUhihVnkEEItm/J45FpflrvV/ycsg+AAqoODaMXwBGEGYOIwIiNGYhEwg0mI21tRVNrBxgjOfLvBXlVdQ6WkTeUSu4AQQx8OIhcHuwOcyQWucGkta1C0w7n5CSEItORGVy9rB5gl50zCtS4GSBaCL86cBEwkcd2Wu7yc7XK6fHj3qc7jf/OP/mvhMo1drXOpi6uZWRJJJGZal0VLUXUGhtw5WcqZhTtNMQnrrmYqwrXWT58+mleI7Xc7YamlMEufOhCypK7fENE8TZdxVLfdftd1OXXitzpdxsfH+TiecsJ2s9ntti9vb5alLKVsu+52v//6698upexvb/c3exH623/774xzeTxdTqOM87Q4MlVPlDIxWY22uRuYUAwiYeUDgFunlgEhb050ymbkYRLHksKJ2FxVa5lriikQERDVuqgqhJpOI4wElEhcPPxYhSFCZBB0fbek5SkpCzshc4OBOaXMZMVcUVOGOjk7O5OhzpWYhn4QkVqXcRrLXIBwyfOGkyaAKFOXRbwNhrhFK8cRpkkwtLYemCECN3g1S8J93zt51VqtxpClgK1z9yD/GZOIiPSSqRvyZr7MZSnDZqilgpB3Q9qlbpBKCzNvNr3LHL5jKfHQDS9e3PacTo8XVd/2fUr5/DjWNjsDc4oJ4FpQqxPzXCqQ3ZkobTe77fa2TqcA7LQaCMKGMlcLWgDQOlG+NvqjtnMgnihaCSp/4Ig0JdJrXo2s3JuyDxH9gYBIT6+NbZCYbCqt/IuS1uHc5G8o5ruo1UXX6Pj5fykROVWLbIxBixNO5wrF3/kvfym9fnh4P+miuVOe1Cl12cXfPZS/tdlkncQ7SqksVk9LWZaLL6kjVDw8fjweZ/dY9e6s6lUVxJRTevXFTa0KRZ86cp7P4zxOy8m++tX49W//7P7j2y9fffnll19u98OOE1N3GadlnlmkG/zh030ty+Xiy3Qp07jJCeqbbtOlXHUZhl1/011Op/k8lbk+fPx0++x5zl1KWViO48Plcnn/6dPpcsl9v7u9+fmz28Pd7Vdf/Wqa5l9/95vvHt598eqLreyPy/Grb/58mh9/8ZM/ut3spvN4u7+lzB26LFKFRLqUs2RW2Gk6i0iXu8PhsKCMn0acayfY5+Tz+P8Q92ZNkiTJmdinqmbuHkdm1tU9fUzPYABQcJBYLIUruw8rwv/Cf0o+kHxYASBLLpcyIGVmMEd3V3dV5RWHu5mpKh/UPDK7ewjMYmVl/aElOyoyMsLD3Uz10++op3Kz3ZayNOgZbVbJIsncRW2wDUtqvMnT1bgfeKIsJLWq5jRtBuc0KYpDrCxEEOKc8+jgIV9d5eNhefv1+4f7pgptaA3MGIdxmgZmliGfqEYxaczWWefkzVurtUKoB16aBTN5BTkYDmTJURnHPR0WkuvsBMyQ4EB1KV6MGpUI7kKUEJMS9Aoc5sGkC/zFzImMiZyMOFLtkYI4TdHgRZFsHB0kGGSwroQHh19qoAxdZU8ENVVX9b4XuYSs2hHyoZXuBLgHxbXvx5xYjo8HNvLqbOFdy+xRFtvKUViLT6wTPiUiNjIZxJLBjVyYyUXizOFpUuruUequM2XxoK0ZGQjETqvij4ndLFIZNO7gJ6PJwLXh0buE9IOjiOmVD8w9EQtL+AvEoJk6jnfprFbbs7V7AhyuZuxMjqq1i9T7IK/be5E98XhWSLH3a0ERDY+XlaLn4ZRC6DpKZlmWs3dVhUOihl/fxWWRWilFMMSquC6tcH8qzH4P/So+inUTlR53BXgA/Z2Azljdo9za+t30g5n7Gk6+mmE5Cz/HyZ56yLj8WBDfSOcpwtQ6NEaAg4WFRYC6VC/WQoSyBhdEP6Nm8SVf2jY3yEAXgqT3bx7SNbZQVSISiJOEl1zPTaAuQYiKrmODtBKdLhsI9c8bwiQijlslYE0XI2FODuEsFMEgnAgJlIQFIEopwYlEldsaJI00jCo+5nG/udJU2rnMZd6l/OLqpkm9P31o56bVqAIN3ChTHmRipMXKjKOf3SenkUfJQx5evX79+Ph4OJ5M1cXCeGtztdte7dQaCzdrMbkZhnFZijckH87nMwo4CaDB14a6uyXJTzN/7yInIhibiwc5DwKOuFbzVrVYGZJnJjVTWTDgo5+83n0kluuxHKa8m/bTcT6eSkkuAJobtEqlrSR1cSrDxscbwhnmbrV6WkFVxdWNuLS2lFM7wUgSn+ZjGuTm9c3+auBcnYpkHq6vh6qn03w6L4f7pRxLPfjr3Sspw/nbpR2X27e3p7fAI6iSG8g5ewLg1ZbaGGSkPdUgMZL3SVe/fgE3MMcVb3A0cgHgXgsLMws1scIGhUuWoT7Q//3vfn579+pf/us//+zlj749ftt03k8bwO/u7tyY2vjw7vTVrw7vf1GwAIFvDuBMNOH169effrp5/XE9tL8feZgPPqP+6OP9j7/48etXrz569REv/NtffvXv//bvPny9YAYIV5vt4/tTTlk4uZEWmHkGwcGVCdasESFPstsNzdvpUI8P7fjVN19efzNe4y/++888q8ES8O6b37359LNlaVXt/uGhFjUr8wwBckrlsflstMkxa9hf7bMMBESIFgHn8/l0OLNiO2xzzsKLkBCTVzBLrO9muqLYdoHmn+Dpvmd9dz0xdDwHJLFYubt5WCkRuTV3d+uujgC1y2t2flMw5zJx5qalaKlWTbUv9QSSALhIuBMWQsZt4ax1mchQuHxc5DwRmtvVml5UYx5vMakmNphRCAUhCdTlchr+WgQCm6s7zBVuxJIogwyu4aMQi3POXUlwQXy6m5/jQjsNfN6e4MB+H0t43ltHr6L/IIKpUszjiczMmjssEZETIm67FxpgZ4IwJwqDlXV4l8Ax0QnxYQ1vbdfVbRF+WbI7Utk9Gy08RB1kvhZC7g5FFCr2NE/+Rw/uoxR6juI9//j03eMpzXbFfJ4zkP6rA1hx/OFozxOA9QzCjO/6+wCWPzvw7Cv5z3mv3gHUf4IndnnaBXj73utc/veHJKyVZfgDYI+AS7UZbEdyFiFeh0yEqFLiOvSeWKxrVFiUDoGFUcdi195SPYa4bKRgprT6h8LN1LWBSQmJk0K1aWIBGwmRMCUWWoVDtu4goYmQiIKI7tjjKS0gD4TRKWggSUwm5OH8yuD0VJus2G7cXk6X+8yfYf4xeIORuRmLdCFItDDc5REQQUBzRAZXb/5E6ugw6JAyEUcxZt0gFbhIHCQArT5ldjhdhl2OMpfW0BoO9w+lPnToDgRnpqRoTJimjbsxp3kurTZ3DHkYN9sKTePAxLUWNzNr2ux8Pg3DUEstZWbmMedBskjS1tQ850TMwzCM42hmtbXWWkr5an/FAtOahkGIzuelLQBhyHI1TbvdflnKMi/73f7Vyxdvv/ryXJc6L7oZmpacpJqmxOOYKQGOCJZAoggXcQAa9Ht3cXPlqHMZ1i+nTraLFS2o6kzMCQCraUzCvVplypFdHYAhO8e4np2IweQSPQqD1BggNXIwqBvBxoydwiKYCG5EXY/izgYCjGgIU0nX5lZtGIcAs6DELokzGClld1NrjVuo8jkxOQcJKLqzbiLH7hSWOTFIWGE709aUTAce3Fc6b8ikhIlh5K05XMdxGvKIxZdSD4dTPTdrbT7PqpqGIXmz2UGtUrFR08Y48zK3nNG0kIybzaBzq6UuS5OULqtHSin+cHCJa2llaZLNW6tKMVLZba+O22Om/WD5YTn3ZtFjaQniZPQwFNTudfgT99k66O21cucbXAZvdOGD9AWrr0Zro9xf4HLXdsy7Q07MIuH77I6mHTyjy71N1CWqK0zmq4zI1zKq36cKJhEZetoxVWJUL2VxVHz6xY/uH7+9PXwo1hTUHO6+5cQJdq7nc1lKA5wbDof57t2xtbrfijCxsJsFVDkOMo0jE83zWVubxmk7TlkSORFzToM3a7XOJ1PFRx9htxnu3t8fHh5qrT/+4vObm5vdZv/4+PD48LDQUufy4uZmGkYJno55q62V0jzlkd2RWDbj6KWd7g7z6ayliaSbl6/yMDAxyIqW03w+nA7Z6rDfDTnLKM7ubMUXNs6bfHV1re6nw/HDgd+cXw4DzzpPthHJDCga4GqVEyNLBM2pqiaGk6u12rxpFnZmNquH48thi6ZBY51SZmYlI7DSwoSytHHI19fX6g6RczuUpal6bfrweF6an89lLhVszBrxkZIp51yrznM7nSGANaDBEmTkIQ8g16plKeIiImnMELe5mUZZvOoUojrum+XFNwhwIuYQGVLssS7wJ9PMPmaJ+8npwj+M0iFezmB4iuMMnhX8slfTCvUSgcKPmYhgzQi02tg4AgfrvoHeyUpCHTnuxlfdWqJpjWZgRZOjNWcCUY9xA0D9l2zd1N1hQAmzW/QhQoAGcBBJt7wOajQ8/AsvlQM5JxEhNwTrNidRN9UA+8zis5N1OkxciL7Wvv2v2KW8iCrYKc6+9uWGiZxjnO7BTGInEY+J+BPt+qmO6oVvz3MM/pSvX1KsFF0aRs/oOWoapl+As+rl1SI9xANuWmPWL9XVpRXGKuLgaIm6eEEkFjHvro9Rez2V/9aB9gsxLVZOu7zgs/KlfzR/OoNPj6O/Hbhjze27vCB99+R4UAwuVRH3hPi1xOmFDiFGNt8pYum7fWk/nwAcqvGV2eUfKYBe7j0YNPBTgOBp3RaMjFyEfZXLOpBF4tVXO5X4OSDh1YJZn5RFWOm365noH6PPSqSjaSzcfeVopXddtgZ0kh8oaPbMiZwBImE3NmGSxCQwuDCzkTIzwxMokSfPSRTqauSUSJKm0cfdsHmxv2m53X75rRajym3RuNecKG5lYhool1Za1WFksGw242a7mc9zD2DK4JEps2QBnJgNpkGXcIybaZnvRAaFn+YZA6N2jjmaG1xEeBUNYKU9RDPbJZNMLhRbK4UNd1MQjLRxMzEXYIebT67ztZ5s8dbGzfBYj7pmGg7baRgBbzJ683NpKkRpK3skGUtrsLomowKLYXOFqrqcKryCcKr3sDZutttd3l4N6oWYp+3Im62c6/lUHx5POGGk8dV+9/H+R+2xPnx7ON8dj/czzuCKttSqzKCRBzeoK7wRM3NA/67SIGy62hTFGgZyWm+X3vkyMalVbYV4dIdqx0HbSYfdcH54/O0vvnl5s/2zv/6JJT0/LqUUwmjqdx8eB0ptofN9xSOyTFmyt0Vr+T//9stXn4377UcvP3qpqH/553+q3Mz13Yd3r17s/82//RdE9Pa3b3/991+9/dX7u7tlSJz20o72+PaUUk4YEmWNVaRUBSXQQJkZqrUstTalVoI4FdYlw3mg5K+3r890VKqttQ930LKoeqteyyLMzJJZk3AyMaaWNOec0yDMQ0rWwETFS8hxChUzF6Kcc1d+g5jZ+Qlbp4A/+7n1FT/GWhnSDxtW69tJgDcEujSm1JtEfWIyY21vw/qmi6yJSYJCSFWrRsBswNnRXDHL6oG9cu+CJxDFqzMEQEQMg0xDAuB3B6QAACAASURBVM7ORM5rHdvb3Ji+x94MgOBGTpEmAXToq5kyhSlKtzN3uLoyi6+usf3UrNfeOrmIt0eyShZ7CevPF9ynu9iNCN5toPumTTC4GnVpH4UnL4MtBkeOMANWsssEx2OKHhtOXzefVdExi+uRS+RMXvsO4KvRFYGIIuXNHd4/z+WNxnsOU/+432wV40epAnr21Cdg5Ds/Ry+9bpTf3e6/u8H9Z2A4/7zj+Tv54fHDx38voPa9T01E6QLLfY9R9r3fDOr+Pw+lixPX4czVJuD537LfQ/7rRzz/ImC8iDafv+wF2/reF/Y8P7K/CNOl0I6iSE2tObtwZjjqUqCch8RCjohC8osoj4SBHhamMULs7jkU+kHq7R9DvakmuAjLmFKSuZwIvYBwN0OSJIkEAoMjORMjTLidXB3mxByg98qODYtbdzdiE6amnWvOgLuxZBKCpcDZenZDaMocHbq+ILUU+iCAEdHY7M4knYFuZoY8Rdpr//wAm4MSJ8mkqKihJWzaogmI78Fcm7ZxnKDuqqYeTQQLgX2us0dachKwc2I20lZdUqA2rno+H9MorgpgzMOH9x9evbqapq1IqnU51epEKQ21FiJStdP5DAdtObu+fPHC4LXWak7hbhRJHe7ClDgRwZsCnDKzJG1LmRdibq2l1uZ5vn94PC/LOI7DOExjzsyA76YNKc1j2W6m7Waapk1iRkrb6+nm+vrF9fUXn/34/ft3LmDyVsrXX325u74RoVevrlurtRxjiU0sIkKidTGNqPjEIOPgNpD1fmrVXcNJJBLH4wrsHDrAok/0wYjgYsYWWnuASRgAEoVjuZEpdZN4hbkq4BhQ2tJMjRyJyImNHRzXE2dxdjWFYJhymdt0nRXttMzyIMupvtxet9Jqa00bAQIhsEAUBF+p5hR9pDbTZt0+hmMp5g6lAGQWqQiImpJJqms9Proqkm920zAOxKRNaysERkNz99EBVG3LXMtcrLo7yuMBhF1OUF1aKe2MbEOWcZx2N8M/fHm7mVLTuZREQsRGRK3p6XiOTdfMU2JJYlZMQUK1VTsdRTAOVKsSuRmGYVTD65dvTnc4Ho4sjhYb0WpP46vCr+958V12jBuAx4yrmwWg1xxBZVxdXWJZMbNQil5Wzb7u2WUrXEsWBifhJBzzUtfe33m/34kQ0g9/2ndhpkFwfprhhAFfUXOEaYJ6BTklL/Cra6QdSPzxdPfh4ZvTMi+lrm+Bxzy8fkEJmZRLWcqyPDycyomYBjROGAYZZJe2Q621pZyGnAGUalrVGK60yRsaJEue8uSGifZt39qihPM0yodv7se8rWU+Ph7fvPzo1esXY877aVtKebh/2A4j3LW1VmsWGSVnyCgpuYgwTOt5SUgvb17OwzSXev/wWNVEUmvq1JZWJUkesrmVuvCQps34sz/5mZl/9dXXh8fDYT7stvurl/tSzpXKh+PtZjtNu/HD4f007gaZKEtK/HA61laaYZzGKQ1CKKWYqVf3uZXjzMZpog3nQrLbbLX5uJQdeBrzDK+tujpvFOclj2naTtv9Zl4a51TmuTzWd9/e3h4ff/Gbt6eFmxklTgOM2jTRdLXZTDtTCGQQ7CfA+eymDnLklLbTxrw9no6tNXUfiJIkcive5lK9QohYHKBu4XCpgJ8NkLwnJKH7F5oBFEkRiJ9W3p8/224AgIxBbkQW0ULmwaMiNoabdVCfBCu7JI6YRJkpEUlmmLtHLCZRjgpBIoOVCC5k2poZESSsLsw17kfrG1pM6ShxpGpFc+DufYDKzCwRHajeOqgC6gw0cqOV2MQ9kQ0gC0tnJjCMXRiSRL0SMeBqOvBIGQAJUz1XZ+TQF7gZGTOxMAi8qhzR0SALfR8RQsJtoXlwgBzqzImIvVmrCjckppQkS/Nm2sLBhxyh7Rdmd4/RK4kQuxt5ddjKzYxuIMCObjobzgJUVdHtgKBuHBIWTizdf72pknHESsWlohF8js7q8hC3MbsFUsMxw+pVfr9IsCKU7u7UXJIAMFWzLl/tjR891ffP60fH2gL0tRO9U/De7TybBiCW/d6+ddTKAXAi83Xc+cSXfULQ4BdUjJ7XtL3N6ESJsLbq/Wo0qP2Ry6vhu8v40wtFY+auEdJOsbV6B9QiP9I7QzcEJ+bNlPipFTbXgPgupsAgkHDXIjpATxVspNc3WxN8Lo021h2j98Z0qcqdrMfkugOUkiCRt+aOwMOJkSdKQ8IgkrMqlnN50HtWq4dmxR7bYWjjMKR5qZklZikpESGRkao5gn7uSMjb/OrN62YNRLWW0goGz3mg5OFd666Hx4daqrp58nE78IDdbjOfz0MereLx3UPap/ZtScFlAUBgiQ2aY8DTE8KdjVwSNApTIU5EwTM0RwYTjL35wpkw+vXn48uPrk9+Z60NmwkCFpq2Y6uLNyBBMidJmw2LuGSaWBLLMKRxu8ucRJKaaVMWycNQ8yxied9ucmZObqg72l9lyou6Xl1PzQqx16WcHs/zvIychv10la+u+EW5bY/fPNx9fVceC1s4vvFlfVEzCHFKFHAkh52HO5sH5LmiBRcE2OFEwkGWJxA5CTEMVuFIkoEMJq1nNORE0vxv//dfvXqz/fhPPs4vNh+O37AzU04yHR/UzqgFIE55GpDLqbWKvBlv78q7Lx+HafP+/puf/DefLnbe7MYft4/d65/95U/vbu9++6tffvX1b84Hp4oedOIi7KxszQpKeBiZIjGJJFcjUOLkyQCgsS7mjrxjc5RW2fz2d4/DS+YJk8iLPcp8n8bd+VSFhpyyLkLiMNNShCceExmgSiSmOD6ctptJSzsdTsKSONEWIw1wP56OZtb9ecDu3lrrYLu71vqMRm+X2z762SdDj0APYzOEoVncDEwSDszhstol+xyxPtYxfV6DCAhIoBQCF53LsmandkYVERGEgkkUrjXdlc97/l+3VCZJySOFF0YMTgI2hapZUyNFHy85EAbSvT91d2fq1nIEcwO5Waz8ttaoDlevXPvKtxYcAFT1IpGOXl7CrZBWYM8dCAraxdxmvXA9UpUodnkKb3gDLMLBzdWhIVWOf7JeNZtz4m4oS32SFA1MQJNmag5vxtL7LnNTW8kH6DW5U7h2AhTemgY14s49v6B0fTeLXjsY8SHKcX96wnqd+Ap/UtDHAqJgDhl3/9J+H54TJ7XW+hwDin/6Q/yg/nEQ6h//rcsf+uGv/4GWUJd3e/n47p7wBx//PPTqe794gdByzk946hrx+/xEx80cvvIB/V6UsX3PXn/38vzv4YuXJzCziCQRTnKYC/C8OHZTMzPXtS4ZqMKHrQRAsOLIsUGHQzbQqxf3zjcneASrgRC2NRYdACfOlJjYQwhk1kxBqF6IchqzwsxsjRQ1tSg2WHIShPc1NW1OIFz4cQCEuoMfAKgD1rtN164kiDGL10jFBfCdyKY+Y2frFmAOd1iYVIRmQcBCQYsK2M6sO1mwMGRQMmeCUGepO9SbA4lZRMJlWntsnodOEwTV8NH0LJTToFB1DaMNYXaGMogaESFBHQ+P5Ztv3g2Zf/z5m2U5391VdyeS0+m8LGdVVW2xkLWmyzyX2pZ5LrW6eZYkIuGmNA6DWvAySq01p0zdQJBigcsi4zgeDsfz+bSUEoTaYcgjS06JmHbjZIbr/ZWpqWprliD73f7V6zf7/S7/jPdX41zLXJaHw/3xcCTB/urmar8juDer1WA0eCLF+VQoVy2ACSBladzvT/T6AOjCKnjOQ7Rh/fpprUPyUeUnBFjZvApL3mbzpNYQTDe2SPdjzuS+qMIrGJRYUl6sGBsShTI0nLbcG2WhRIampJJ6pvxms4s7QWcfbExV6rnM53OpRbJM29GdaqnjZkzCh2KwktPoDnMlIQaZOjTIyYHTBfkuPB/cvKU0EBHDWpglB3WRnQcGk1qtbskNAhhKKWjU5taWVpeGBjihAYJaqwucKbF4ckksiVOS6yu8eHG1mQY3JWKQqlUznMoCQ06JOZXS1JqRsaSchZhKKXWp19e8lJYSCycHu1GtNp9bbVZnAyilwRvBY9undSqzjnNAxCAomRP31aIvQmudwbySKTvS1W0vY/9ajSwvG8C6DXT0iiCExE7U/dzXXfyym0fJ8nwd7isn+jT+8m9R2jiozEuYHuRE5s0LXv7R1b/6t3/xD7/95YeHt83tcHhU0JBhCjKf0rTdXZ3uTq2YVdcZeoKdKifkzX6k3TZvTUyzxZUc3RANY0Fhp/KIq+1LhqSUhjSKyHV+kUXM9Pb9O23lpz/Zv3h5TaBa7dtv3t99uG2l7vfblzfXr6+vidDmMp/PtTQmHjhBvc1lnNI0jNGiT9O4nTanPPjDo5odjkdVPZdFhDf73dXVFed0XJZmWuqShuGLjz9KktT0eHr86qvfHR8OH7/+eHc9JZLj/PBw3qYXrwrqw/3Xw7B5+eJV4iwD2KGllNlO9eEnb37SqJnx1fZqv7nyt968jHna5Y3coC2W8rjfXlmZVWgapKkeHw+N/Ljc/5t/9T/evLqpVo7no2ie63z3cP/2m2+/un375dvzt7fgDMlgBgQvbuQleNxsW3VXf/PyjV5lM3m8P4fQUigxOMm429K8pza3uhTVM4WlHq9cKQ5tb9A2V5gm+E1gItJmK8IQj0BjROkAunfsZW968hgCAAhJgArmbsE3iQs46kYOZkQAv51/sRYGzinmm6vNOcJ3UtaSfXXZC5+slTTGzCCHP6vPqGMcHFhbBxiiSAXAiUWI/RKqLZTAjMRKpqrNlYwkEDyPUwIihz1FkTCMHVBrASOoGVyMmSWRI4gqoIwYRJEQpZVaFp/OEOMK6w5/gTwQMSfOwXMxVU5dVhK7mCszCQnbOkzrCn/qRY9HHcAcbYo9LyjX51jD+tS+/vgTLhNmJSIspmbRBwDRF6jqRkbtHlydYKBAOBGDqIc+d14tdwBopXrALRy/OvvdQ2z3/HsL/IS825NfWmxE32VmcOdVIvHDoyNOHtLHnom+2vw8nYMAMNU0ov3iMuTuOfLU1mNV0X7nEl8bUTyre7nHA8cdFuIfWGtmplDTKCNBxJTFuxI0ft3A3crNVu94ZrJ1GPn9foDWT0EEeJLUm8lomAQARNhMFL3kVTcJouAKewVr78mzHN//C97jRHh1PDfqBA64uanOtbjCWgNRSmkYs2zGx/kEYbd2PC06Nz8bDMupHA/HaZrEqVZzgHI/tWph2UEuWr0iY9jkzW5a2nJ3+3Bajkr64tWLcbsppRh5ykmpze00lxkK3pDkcboem9U0SHssIillOi3LOgVEuGtE85YkP0MQI3RGgZ6bELNjMDnMqKWRkFnV0GDu+zfTT//0i92L7d27r9Mg+93uXM7MtL2aGOl4v5zm45iHNKQ0UhLSqrVVg4B13PJ+N2y322Up5/ksSa6ut7/55paSbK9k/2IYhglAqRWEnNO5nN7srk+3h1Lq3f1yXtqIadhNO77eY7+l/b/7+7+TI/RQUREDK3NQhN/0fZ4IZNYMDQJiI4GLEXGbwxTPKdbiPvkKva8D6s7kBm5ExtJXTwqEmqmdlusX22aKw/wf/uY//utX15/8+Se7q3F3nf7Dz9+XWe/ujlwSMyNzKa0tRc+LGTa7XT232/ePOtnbD78bbmh7PXDWcZDzXL/++qu793enw+l0PC0nIQepm4GVEicv0KZmQf2jIadMYuqtNeqhUzwMGYAmBWjgZAQDktMv/+Nv3/zR1ZvP9tM27TfJB6aBW0m18sCZx723Usvc3Idh2I5jKXU+n8tSp2F8vL/XedFmbSmSB+KUKA15cENKUpZaa/XmCRkOWFfiExGJwNrvu7fwvbs59LkOOBnYoQDcWdD5T0QAGxOR9PVKG1p0bH0L7Lb7BDIlcmvrMsq8sq6oK9HXBBODNTU36DqdAQHwVnVVItNqHxxrYPd99R600iXNfZl0kPfMUn+a9nR0ykA99h5wkISJcW//1z3Eo+4l8s67IgDPEo48Vn1gZfl630XXp/g6D/GeleItjA1DQxSD/j696BEujjwNFxIEuIe5CaQbczp5NzNJBFhUSgHXQTF0PIJJelnRAQAH1vwWdyYyjgkAmOJdk7Zn0rHv4j5PyM5zT6tLGY+Q6D/Rei6gin93s3gOtvRV/Z+Cd/7Z+M9/uYOI0n8qnPaHvOjvffB5RIv/wGSenw0GLy8SD34Povohkrfeg9+ByS6srguAJSlJFpwXAKuk30OmxcIhv4r9i5mqNvdmvCLZvXI255XO76RhImGIUW0Yr1EfsvVVP1KEhCWN3TWDlNUaJRhbQ22mqg22esVF0045pApGLkASaWhrOrkbK8BGsbb1iWLovxxBY/GwgpToE7xLHvvFvnayzypXCtfDfpszkEjIwyKKSQgSoLS5K4MoqGPJYt1iIkfR6u4ixMyZU6utNdNaTZUJKWcSUlh3zUR3fycnAZutdyYBTDmPRLZUNAMq3t3e7rbj61dXQ84sEWKbQwbNSUaSnAcAzElE3r17v8zLsiwivNvtrq+vwrFFOAMQFmMhtCwpi0AkpZSHgUTGYdhe3zw8PhJRaMocsOpzO29e3Oy2Oxs2rTXhNLeZwZtxGHd5t9sL+N3Xb3/ysy/c22E+PZ6P0/3w9vah6uPV1W4atrtp2A5JBSnlzNmbUnI+oWbAmDhxJjRvzZv2YNmQ4eSUY8eLUjWlpKq11uht4oKXkbWZmxspMYk4oBoCcnMQUs4QpJzcQVXdFKwuToLi1ZPTACzk1Z2cMss4JMkpcynFqjGJtgZgO23N0Jqq6i7v7r68NTMzTcRkom4QDHnY530a8yTH4/mkqmbK4duYBlerTT0SmJmQGCxARKiYgCQBQDOLEBxkIGPRBRUpJ+RwkHYkkBIxNdfzecYZSAQQ1OJubW5Wq7ITm1X3ufLRjZZPP/34ar/Vqm1pQx7GITmUOSdJzaopiNzV1J0HHsbMQs1aLRUFtXlTExk4jaW2+7t7bMZWB1dpS4TFJA1blhhw9dbvMnyg1X+lsytoTdt61nF0mhT1Yfd3VlDuLBh/3rL0V2b3JGByDvegp5CGaPU9vFjDEOiJteyI8vxZ+9WRM4LkTCRtae4tpYETqht2uHm9+eJnn/7um/9XNsZJzJGF88iqNKY88rDh4eH9u8QsNAxGO+ScfMj5xebF6FeiwygZ7LVW5A6RqzQdNMaLL6fXHMZG6l6QRUwbaf3sR39k3mDt6mqbhB9ubx8+PDw8fFCtX/z48zcvbl7st+d5psSVqKkx0yhp4ORFOfv1ZiuU5/M5sYikYRhzXjyQGIJ4fv/+/cfjsLu+Hne7cT6f68IseRwOhwODX79+Re7fvH3b2gJoGiiLAH6up9sHy5xP7VRQ20Nz8+3+ar+bzFtZyjdfv/38zae6VCG63l6Xlx/dPdzel9u2VIhth+1hPjtYkDKEQUkpOc3VHj7cfv2V/dX/9Be7aXP37e0vfvkLSJquN7cPt6fl5OCrm8m4VpOiXmpz8+PZ/cMBTiIyn9uY9nmzdUtepRVbdGmLlrkOQxrSsNno2Za2lFYrjLj7EnWj5+cdOBMQXPrO5IFpeIcj0CsX9q5DawjBOfX9KK6ydSobh5EB5mxQX4GRPrWJmjvkQ+Lw4O5yJ04FPRkwW6eRHiHVgYR0zAR93+/EmBC9gEr7zoBx/afOKiHmZt0VKjFnEDmbelPVosxMHgkbQL81vSNE5BDugugAsCjUEt4AAgmxq1p1d2/eOGdicjZjg4Oyg83ciD14Z+uaEUtDIH0WDtXM7CBJnpI4g9SpunT5Y2jGItYFvKYqPhVFl9cEqE8ExeACj1stwLv46iNPuTu4xwzryb56JVtH02NPDlAWYB+MmkWQrVPU/z3VESGcXZE0jzA7uLvFYLxXIkxgMlsFVXRZ6HrhQBdw6oJfSWdIXSp6M3vO4LscTGQU7Jl+AXd21nrivV/lsb/a5e/gmeVKv9DgAIeY5od/6DsX21oUr4q8dUMIN66OS1Fkcz67VzoVJjz8L6y8+GbtuVX/s+/3efVNPcm6bzEh1L1QsYg4mBS43KldO28WFpXsv+8UujuZ9vBRQcgPmd3NUEsDuzVv2lwdqgwI1JHhvrS6yzt3LEv12XYpC6W5qoCpgTjrqSADAm0OUiTAGlz7zwPOer473tVa7893BMrjMGym3dXOj6itGlEaZcxDq0sjhzjI1DQN4zCkh/Zwk1/KXk4+Q8CZmVgQpwRE0s+mXz5nnFYVJulsrYDIQXBK0thNHRnY483nb1598qLYcipHpzqMWaF39+ftZjdskjYzbwRTq8dzzUKttPlo5BgEuw3nkUfP1ZZzOXrxRsuyFBJIkpwlj8rMlElbS6NQ8w+394dDcfMsA6XRK5IJN5Sl6HLAfdWWyFJwWV1hpi4RQtGt09jJYMSwNYYNq1bDgDWXldarNzp2BSjQ55TBksngZq7NXF2dM1ctwhvJdMiox/zud7f7j1588pPPKc/iaT7XDw+4ZpYh8ZjNoGhh8D8fF5AbcSmtVPvm27d866e5wHm3XT559dnd+/uvf3t3/4DRwMymXuZKBWi8ka16KEadhNIgDK5tad7Y3Tls2UjV3JyYzMjc1VVPcKH5ti1XZbvx6122UShlq/RQzJolZEqC5pxsGofr3b4sldTKXL0pGho1VxclJmYhMyte4KRmBDI4M3vMUyw8h/vi+XuXjB9gCoiYLr8MIaOKpNVDKsR6Hey+dMd9eXFyCFISTgSGknoU3gQwywpgrZ1hF+2YmZu6Gtk6U0dvZTthI9AXJzcNT5seLWLdgtJXPMW4RxK4XQSEsTr3jwulGLK7rxbqTV08pRS+IsFZ4TDe6j7xoC5qpvWMXWSPF3WXd74VIUIWCEyArCwwbUFn844eqV8W3T7EiuJCIj6rj20cwSe77BOMFTOI0UNXUwK97Yo9xcnW+JeuAe/5sc+02bFud4IrUkrepyNPIAaeTUTii7YVJbygK6GUvIAhz1GqH/7wveN7gMwP//V7P/zjl+5/5vGHv9p/AgPrn32ISEppHMeUkru31lprpZQnBPG7B9bTFF9Say3nHCM1Wmdr33va5W/5syOlp0/XzekbhQmjX/BQgySkzDwkSty8BmVLyYwhiSmRhfcTDOYkIomZ4GZagHA6NsA6Ok4caUXEFBA1tdYWmylzYFIpExFDGEIKNW6I7OHItq9Ag8fEloxdFCyy1hYwD6Koht1BlwUgGF6rwS2ACJGIQE+CuPdw07jbIqt0bW6d1wyLjmoLCbEkOh9KEndyIYvPAiGklMYkiaUl1RqVXbMOCa5FmmqDFWtFoTABJxMXECSxsYskEm6mwp6FVcJHIjJdbdhs4S1PwmIPh+U0z19++3bcyE9/8tl2v29a8pQJnsYEImtWVbVZa7WUJjym5PO53D0+3N3dHw4vrq52u93OvbVWTcGccqJW29ks55xyTpI4CTPd39+/+/bd3d1JEmpdita2v3lzdV3ndmhHa3o6n4+Phxc3L6+vb4Y8JBGt9vXvfvvzv//53/zd/6xEH338+edf/Piv/uq//fwnt4+Hg6RByF2ruI05bzcThGqjZmJoJMFvJYeYqi5GzSx2BzMynjaTiMzzrKoiYmaqKsTGJkH4F9psx6JFTaO0cli3SBRurUnOw3Yi5tqqmslExrnDRsC5ntgZ4jQS3FMW9kycchYR0pStekoiSXa73Wbc3d8/nL49HY8PebetD6dLkwOUuIDTfhw85Zu0SzsjPM4PzZoLhCXeXmIxiFajqAoRxTh3Dy03VXWqPABMPIixURKZhjQmg1nFPJ9BEOFxnAYe26EZ+7AdoKy1adZQClvMS5gNqgazZo6bF3uYnZZzKy1lUV/qouXMOWeGaVWiJJLEPA9pmkalWpqSQK6pLF6rkaSUxvO5vP3m6NcPN5vPNtOWTZqxNWmlgdyoQRGzFBEmStY07L6+d/QeM+J6/dmDPxjo82pchRgmrUg0YoPmECxxTxTt9iWArBMp6j46WDe2/kpPg6yOqcUdDIA4M3HKaBbW2abAv/zLP/nv/oc/Grc5TbS9GrcLXz3ClZlTnjZX++vttEXRv/jZXyzH+XwqNqT96xevXnyS82ZZyul4Pj+eFNy0Pj7Ut1+/Pc+nHn4GAqBqf/lnV2MexymnlJg5jcM05Y8+fvHy5dXp9PDh7lutzUGvbjLflI/evIK3q93Wan3/7t0Xn31e8ilVvz+WTPLJxz/6+Oajdq7n07nNypmmYdxMuyxDzkOpbX68v3t8uLt7fDweHG4Eh7x883q73Z9uy93tw3arNzc3Y8qFePrk0y8++/x4OJj6cj5vb6bXNy+F+MOHb5e5Hh4eUxp2+70D6Xa4uX55s3tTjstyOH3561+70evXr222SbZ//MUff/3hy9988+tDOQ2b8eb1m/uHoy9L5jwynZdlmc9c2mev3ryYvn7z5uXvfvflr377D//w1a+E5YvNT5Fsez35ZrhOm9v/6xdLweFYmyINbI9+OJSt2HaflkO1VCvNZcHd+4fb+zs9+JIe7m8fNuOw3W4l7YgqC3tK1AyrcIH6rBMggoGZTAxO6grtAbsBK4kLwmUcbBQTKQIZOKLDsNoloWfPOQSotbAiTPGEgp7TMQsnaAvVk8IVHtATkUiOoj/oMNGC9CEyNX5yXYI71LKIUw98z8IiAqZTXNlBOlnRELVOMNbAyMzJnB1wcTcrZqV5BcHqSggVJElMRJUqMzxMDNlBTmOmRJRh0eUmTsIjUlkWRVNXba0C4zAO02CkbjaMA4CctLbWzETEYPashg7xoHf/KQKQSDxlsHtyBwwWPuGQqKVcWCiFxwYIPd8oPm+EPEro9wluznBYY5iSu0Z2DDj87BlIxJEmQk7cPXjdwoLehMLSjnpLASTQfDy5uhMkEQsnZnW21hDoHCEnIWY1VbWg063vDavJ5ndgE3ESEDlpRzu7j9maRxGjQhvGwCYWIAAAIABJREFUAdRslb94a/3vfbcUZhB3hh+jq1lW618N5iDIoeZVu3EyqLd6Tz1A5379E+X+E95EFOVav3/IHOTkOedgM1BiJ2+uXl1r7aIiFuob5OV89JDN/iZWiBarSWl0NJcHAVhrts5GIBSemKba0eGI107i7rWW6IfVjCj6vh98LsAbIHBzbwoFMGROJKhaVFutLJk51HxwAKpYYMYz+/Lq5noct/Nhno8HHLBw3W6GTR7vb++n6+GzP/r89Prw7v5bYuJBmLMreQuKPk1vMO3TdpMqzYXa5mqrqsfTSeF+ouPxVGrTWpErMnKm3S7nbc67hAEfffTqXh6Wx9MGY+Lh/voeSpnYarSJbkQ5sxvUwlqbwx+HTIWYyYU6h5GFQV4MFL5XE168efHFz77YvZqM7Ldf/+64nFs5bmjK43Bz4625tpYSbXcbdjezWgPCZZATfBiEJVW101zUVIHTuX14fLy6GQ3OQubtXB5TSsyyu9oN05Ty9O//j9+MI66217tpymilFiq2nM537+4fvz2jgBuzEhSqpjWw+16AWIcATCJ/CRy8xX7XMaMbo+JpzEYKh0NjCTB3swiT7b2Umbp5Vc1peHxYyuOMgnuu/9v/+vPXP/r8r//680N59/Hrz999dSIcZRDWqW6hVicZZStLmxtVGuTD8dv3zTZXgGCuS5nb/Qkfv/r8N//Ph1//6qvb3z62ExILAWrFC1BAkfLucDKHuVqdZ2cBkYs5sbur2VJL+JoyoKrm3tzMmW7tW5lvrsdPfrK/+uxqkeXhrPe35+PxEWVKngeRZS4OJ5yXnBiSUyq2HI9HHFGowcAEEs3sza1w6dR7j56IPMiEPQvFfyAVfjo6D3i91zs0xeFxSC4EJXK21hyiZHwxnXC3GiIZjeuXCCllSmAJDpCrqbrl3RQ6m35/a1ChNVwJ2wpl8TP+aCDmvqJj7hEuZeaR1kKwCI4OMDvgJo/MJ/Qgo84PceucD4BdrVa7kDb6kYEBQLuIrlSDdfX9M/b7EBn/4dOkl85BEwxBt3VzXetGb25QMojHDR6Bqi4WO7szORshihYz8xRCKygxCaVA0sSF2R1OEO53Vm/bKRgzFtktdqEV25N4jjz4J+7uvtvuWm0W8MSFOUU/OJjNTJ4R6RBn+Jl70g9O0dN3+vznCyL2ey/LfxK9+q94/KEMrD/wrT/fOy+HqgKUknai4joDvEgCO4aFriuM33r+xsKB6/L67n75zi5w1fe859evmC+Px9eTUngoaAAuxpc71mEeCUaXQE4nAyUQORShXRKAw7nc3CHGlIVA/ersnhGOYD8jUFSYGom5RCdpIHBiJ2vaACDFy8LNOQkRx+Ia0UJEcSFS8JN6qlO/58mZCSn83cLGA7hYlsTttM47o8i84Mfo/123LQrdr6MnbTOJSAGCMmJOTpzIvWojJYerNjUjWiei/ZsFgKYKPJOO9JPSjTNJIrPNPeg51KebwaMHkaq6t3FIwzQM5/Z4OJdyfLHff/TR6812GqYtC0RADDOrVVW1tlZKqaXlLASepo2711bNbFkqcE6pw0XhiVWbWWsiIixC3e0iswAYR9rurkCAsKre3d0f6XEcxzdv3nx286K+bCIyjCMZVLVpPT4evn17/PSnW2GYWal13I7TMPDV1W63X+Z6YN5vpt12v9lsD/OpWOHkKVPsonAr7agNTdHppQQ2r015Kczcmpqpuw952Gy2MC+llLIsuohwo8XhLJJSlkGIiEyrIeXk6pJERnZAS23uzMKZSSguhmkabFZ1Q4MpalXoDHCxNIzJySnB2Xe73Y8+/vTu/V09l9YaYUDBmDbWVEuznjnIYGu2PIJdMW6nAcPN/sVpORQ9VdV1QsTC0jXvvoI6TOw99UO9geJti8LNLUmikTBQq21uZwA5p4QEQFg2282hHOtS2aW1FqNjbTHU7mGLTMg5b7fjMi9mrWkxs/l8LMtMDigauS8Kd5lkGFJT9C5eaJzSyMID37+fWw0fQG5N6wJVH9K03YhQcnNTR2NPT6bHRAgFbpfEO1Yznz7x7ygT0zpcv6x74XGFTmBYoS70XntlIiBa+F5rBl9aLw0gM5hWBde67K59hfvl0R8s4MHVcrTWIlii1WXYps3QPv3sk9dvXn7z7dd39x8e5jbXUxa4mZvmTNs8btOoXkdM1y+u5WVuJZ0P+uuff3l7ez6f2uPj8Xg8sjDgx+Nxnhc4QsdDvUuk/+WXfzON4zRNOWcRyYOAfZh4uxumbf7jP/nx6zevX764fnHF1h6++earuw+P5XTym6ur/fbh7sPN/vqLzz99eXV9eDw93t3TbJs0JfCQ0jiMROyms52rtjQOW983QmmmbsfT+XA8p9u7vN3u9zsiLqUs80KO6/21m9Vlqe5DykiuSxmmvJ22DjWyUzkcl+Pg9Wa8mXbbD+9uj1+e8ifDmMef/vjH97f3280+I0tOlGjcDRXt7vjweD7c3z5uX368ND0f53mZJZFpK4fTZkif/+kX+5t/cTge3t+9X2xxweF8z8lI3Mgejg/NlpsXb/igrc3nUoWlWW1zXY46DdoW3Q9jUymnUzktqJwSEaOWZm6yHZdamjZdp0dhLB2XPa+wAoh6HC4anl1kYen6JFKFr9eMAeK8chWIAF3VhnAKB0jz9RlPD8bNQusmdbkTvIch9roi2IIru5Avj/cxbweyVNXVmjoTPFMyc6JxGMKe+DLV7FpmJmGJezKcbRgEDZqYhbLB1LuiGawd8rdQ2YuQhekcr5SiLpeDw6pjnwevSgImbtr1hGQmTMqsKA6YmCtdBqadf7mel3DccIeZAl6bOhmDOAEgN2swdomAFjARG4TD0uvJ3zsap5W71Cui4AbE5CmkhhKmtuZB3iAO1qatNC/v5XiUGQR09KrXYO5WVq2hO2BCtII26DKV6CE6uhQw6QUOco/vhfxCgIlLzKk3Az2Ey71vlty3FGHuqExv01fi/HcPd2d3SOA/6EWSWai13YNFDydv3sN3+sfEdwcLT6SI/5/jWdWPDjfhsvaHhW+UdMwsnJzcGxq64Vp/r3GZrs1kd+mCm1s439OzCa67+zOd7BO2ZR6dLjw8gol5vWPpYoJDQep+zsb93ieOaySSPvsIpTpPa5IXRYPsRl3CaQKIgOItmVsk+VkAhcwY/z/i3qTXtiVJE/rMzH2ttZvT3O51kRFJZAaVpCoBoaJqABISKgkGiBED6rcxYsgfYMKQCQgVmanMoiqDjKzoXnu7c8/ZzWrczYyB+drn3BcNCaVS7cG7993T7LXXcjc3++z7PiO2uersRCLSnU9nGnh7tTuXsyYzVAUcBmGg3Lx60W8TQOfTeFomXRZw7jadE83LMs9zY/mVtiu7PuecAK9aX7/+9nB/mpZ6qscru3r57Nl5nub3Mzxgbmg1ZY3FhDamMZIVWaaT9GRC3pRTnLqUc56soMfudre53pl40VLn+cOHd96VsYK6us38+RefvntzuBuPZuj6nIlr9aVY4zdvFljJwzD0vTCXalWtKpWC0wmffLYDccpQW5ZyVrZ+2A27zk3MFRO4v7LaH9+PqdRs2RaM9+Px/VjvFSWYqgE5U06sj7Oc2jSCGJhEYPLaKpXWwk5PFrZf8oSAhWm146ylooI4C6UY0uYEW2bJOzZZypSHAWr4sLz/6uHbL99sn6Uhbbqu321OTpT6lHsvh7GYO7vCOVXppNt2aePXL7c5+zTb/mr34nb7o8///f/tf/3zD28eMA+CrlaFUnO7ltRLb7WRRB2oLa437zkI3KDmboWIwjzKEJ5eQiCb2U+wycXRMZ3LNE9zgpNBq9YqTiizk2hJs+qGhSQxw7VEfwBs6EQyJXEC8WyLu4UQGurqFhvkUrf9Brn+aUj56P/jUIW7kQWFnpkI7BbTUvHIfm2an0ilLQ5uEmImCoMzgJnVnAUEiWeKRgsyba0pa26HHgD/5aIcMDJiXp0r14jd4snKdiU8aRjEpUlwuglmbGS4YEaBkXFrh7VS1cNwSwUgpTXKuvul0I9FuTLYCE+iapMgNUqtE2AWzXp3gNtHczNqsX7VQgDsbmisE5bMktnFSy0NqoJZU0o+BmZfGypPIu7liVDM62isK/NQcT/6omB9eIHf0dPzwfHk9Li0uf1jECYgj8vdfrw5K9wRGfXl3y/f9ruQnP/Xf3961vzm6++JI/39X78fdLu8/m0wsB7D3/qHV12m2ZOW4C+x8CYPVbWUUmt1N3MTEUmyJkKRKzsxwh9UdbVwanUhi0g8oVLKBcB6epeZL5wDXMgHXU4RjGPcBnuNNRmThhevIswiTECi1He5z2h2rmZulDixwL2WZaaFaoOyI8GCX6w23CoqVSJJJElk8TmGWysQ6jvKkS46i1Bmg2spiEmHplAoedBJPKbJcTjAcwzmaSarxG0Agq59Mzd3vTQ2iWkdgBG+f+uNpTipG1MltP0XBXEMmQGRG2qtoZQnri6ETXKIgqqbwZjamKjLgw+8jTl7SAbcYpBhpEwKR+i0QO6o7hwgdzwlIhfabbcPx/txmpVlqZbMsPiHu4f379+/oOfxjJnZndSaTUWASil193fnrhv6fthsNlrrvMzLsqhq3/ciJCmpYSnFao2BT1H51FqL1tQPAJgl51TVStHiFerFiVmGbrPfXp19NNMsKZxl4X61v9rt+vPpnDf5fDp/uLtLOV3vr1TLNJbxeJoOpwTbdrlPiXabvJGp76apLpNqJXdeyqRKzOF5BSLkbrPtu2ma51KEmSWpaZkrgbq+c7ipApBE++urqU6llmpa50pORk49UwqsVNVrrWoCYfEYet2qJRihmppbypwpVTWrDiJzczLOcKUYqdYN6Ztvv6GFYZxSh1m9gsGgJETEbuxG7OZ6qof5YezG/e3+9uVtyvQwlaXUWhVwkQ4JCK66kZmCiFnMA/Q0h4LAQiTU5czGc53nBca9ElLuOPt+t7OC6TjprATKndRZw+omU5+7rOZLWZxBwsrKgi6nzWazLGOX036/00WXqTLz/monMtTFpnGmlPrNkDP7oktdfB43uR92W7BXrV0fZsOmVkstoW8RSn2fmg1zpEzMCoJ6IwtEpQcKje5aIzVTx1ZD2KoFeYyZbXKYm19o0S2XiTXnbUBcKyGbn28cxk+OuhbxqZVA7OFsFYcqGnzgj5H6MX5TSnlappwSsdeiwzB8/qNXn/zodpyPv/jlv17obsvd0A/9TSeWdYTI9mp7fbu/yZzZcHg7H949nO78+GH66su3371+/+bhCAALwEAHOFDCeD6ZO2L2VgIWBh2BtYBnQLDdghm3Vzf1zM9up5efnK6ul6urenNz3X2yOR0/3N0f7t7fJ+gPPvv801ef9v0glM2cwEPeXA9XEFQtcJRSICmnfHWd+92222wopdTn3ay1lr7vc86bze7WKUk+n8/Hw6nMNZMs8wzyzXaz329vbm+GTV+xqClncXg3ZBDG5UwdO9UPhwea+Y//vZ/84Q9+9L9/+X/0abPMy+1+b8UM/ur5J5LTdr/59t1r5tR1Q879Mi3JqO+3V/3w8tXz62f7Zy+ff/nVl+8/3N0f7zkhdfL8xTN0aTJ6fyzjsbpL7vqu93kx0/CtAbu4Qkvpu4zZx+M4HRcoJAsx67lWMwDLXOpSvBSvTE3B3YRjbohcMnw03Br5P6bdAXANixxElmvNc/ES/RsVlMMZhVbnHsCBFGC1I6oMBzTYV65Eq1U2EWwFZ/GYy1wsj8wfkwFJ7B5HWuAqaHixKVYXVCdIStBH7AporOwLCNBQZQohX2PlJCIjqPpaPbATacROIeKY3EbOrhTiR1oz7ki9IcREkhjGZo+TV50yC6xacTgLIzL0i3FT2GBVsFBYa5uaBdHAUbQmYUlC5FqVPBzDKCSQYOLEZa5rVrvmxNHwCyWzmZmVpaxzgsnNWwEvpEsrHtbRTWGyvmJhFJUghYhtpQy7mZq6ELm6AW4xVkrdsbp8AA4zfVRjtVwprs9XLcgahdp6fITdsWbqvgZCMFNiFjJXM1NbdRi8eiKsAbGVOmbq2tA3orCSimbaJVBeZH6PmFrUgI8XDKyl2m/N5x34aBJh21sOuhSv9Pi5mZqpSqADIo0IB7hpDB4LLVIQIcIzVbrHnnzcKzN3KK3JWOtipDDJgJG5m6nCkLZdMyQmshC8EqUuw10tTM287bc2U+RikeiJE9Y6FjHEiBnkIsnJ1WPsLoK3hiQMzyThJFrmxavP02LqSSBEQCYXEcupd+Dlq5d73X13/52SOagj6VK/3ez7QXR7JrHxNJ6WE4t0m51aM3+rWm2cIQlCyJDc3GAlMQQkVosJ5ef7zfJhKXW+eX5DRz68HfskWTKzjbZotZwzXfLqSK2Ti0smJiYzU1Rh5szOjgWpw8tPXvAmvb57vZnk+raf55m8lAorPJ7Gvp+1FGEbhtzljgBePOaMJ6JqdZl9soqFRThlSOKr7e725ibn/t39/bDbSE661HlRNu8HjMfpdDodHpYXn7y42r+0iru7X/cig2zvT6fDm2O9R5auaPXmSmsAAscw00uG3kJd6GhJqC19c1qJKC1CX3KWoOSuYZhCn8aygn0A3A3SGcBCKHnY7k73B1zR3/7t3/lu/M//6X9aJ9ttN5++uDmPss/Pt4Jvz3U+nJJ47uGZrNbcp/1tv913Yzma2fXu2dXu2W777MNPH7DfJu+YFTQXLW2EhgjFIvZG9QEhCEeRg5lrgwCEG67hcFdq1r8E6rD4dJjv3znt6CwHXciMmeAsZu7q5VylAwaLKrKNuDL0G7HFRDlzEie3mA9rUY9EYSjMHBP5CJfper+z2P84ZhBIwwg9Dltqro2cpJmOBzjiEGbJYsoaE5oIRGx+eXDxoDkRB++18a/cL5B6RKMIJeFlF2o5cxBFb8Y9XN0jLhNJ85Z0amTRKCrc2MMSMX5jY+kRAcahP2x698AcOVgTLful5oNJaJIBxqXHAl8nHvlKNX3sWKz6PV9TDWukDmvorJGreXVcZH/RsyNecahQIcY1N2NuIloHr7U3WpvRbdaxwYTC+w9rGgKgFb2AN++v1SNs9Qi67KSnRo7tdWH2IGZHMNPH9KgnCFrDPS6HItkjuefjn/robewJbf3p7/xdr9+PXv07fP1OAOt7aN/f89t8lXECoSYgQngCu6K6q7kKCTNJ6kHEFFNx4M7EcG4cQ7c2LICbATJU3RzCLl22UsHeeoagxKJArRqFXFwWMzk5C3U5ees9GVoLMKxXY/0kgzpcY3AyuTavdBg899JtM3Vi4mA/z6MkliQEYHFNhtlqjTYmAAdTqB7M2FgBchGlEEetLu9hWJ6A3PAaMJkQMedOfDabw/AqKF2R6Ds5kZMzObj1gmL7tE6er5kzgOC6t1Q9Jo8Q4CQORLlMzODwWqLEKecEgbkXrI1NghOTZFO10voaXRJEom3qsL7PRWFunJhEQB0cQcAkRzU1qAMklCR02Igh7a2XHRpLETRdympFC0/CXUrH80QF213nXsz94XS6uzua0YtXN/M8O+dqPsdZLasgDfz6uzsW7ijnrss5GZQqhIjcEydXjYhkZuQkTolYmNWsVqUMSVkdx3Faqjo8uXSSSaSal2qncfr622+1lB/84Ad/8Ac/mMZJax12m+evrt7dzz1nN57PpZwL98zo5rJIsd653+6Tau/GxKAk2QdJc66lGpFUHbT4OGI8Va2QREPuBRvPxMuiqiknjLZMc5GZ+i11SISU0m6/l2GD0vn5PC1jrQ4tIMpdAkS4m8sMnY3Q951kMrJipZgCDsa5lsycNinVLJoYWuZKxFWrcs29TGPd7ze7550MVkvBjCHtrGI5zJJblkjE1JYSVa1FS2Wr40Lq26EftinfPPv2/Wsi71LvvWstnsyVAJAxgs1I4fivzFCDqe27rfRpuV9ur5+flhNVdCmPVgCkToxdD2Uq05BT2gsS26wuDnIlgxAzVNQZnJAywKZ1nudJrjc3N88q++HNWy/pk5efjWf59rvXnkBwyl5dKyln4UySsnBWL1r8ertNbOTuvoxTAWOpy+7q2hfnjeCoKQcGpyBn4rYpHdGOWzGAWHQKxDAtixIhnPXaGcRrlhl7mJk5bGg85MOtzDM4e9cxE6mrR2AI4gQQQ9msFKzvssIFcBMPggc9VmwgIoqBw/AYCaEkMoAdPGODfjf96Z/9YH9rv/j1353HN9ur3LHc7K6l77AIDd02X+e0n+/17Yfj66/ffffVd7/4+bvjewDICewQSxotI3NMoNAlUUuZ27iwgq5LjSSjHmQbcaozFvXjw/2X7/85AHT4D3509aMfvPrxj3+42/VqdVnU6rwZZPr63bnIqxcvhpz3+911vt3y1ZC2iy2JS9UinIjZYWaWRW6udsQubHOxqjXnnDODbLvphSmn9IDjeB4P88KgYbtxZpdMjIfjWTc+5C7lbpqXl69elVLuDw/jsmx3u5vnL15/ebd9++7Zs09evPxMi59Oc05n6dOmJ+MkN8iJbvc376dpc533xsd+S/DnL672uy0nOy3T3Xev3775TohuNvsO3L14AZMf/fAn/fbVvHTvPoz/98+/Gc/jMi2COs11O6SzwdxTn55/cpO3WqmS6FIrDMPm+nw+euGcYV7EEYI3tRpFMiWyJayLgEuW5y2rXJNgB2IpuiFyazThelADYwTI6t7UWoeXat/h4RCPlsYREHhW0AGcyZsAA7CmPSRq9lCRjbmg2WkTYhQhhU17VOxghzt7YmaGhJKQyEQsRBIAyF1DL4DwmFqNLVtxwZFhmpFzYjGPwS8N2SIKJ1ZKuePEhdThIE5dAjsLpSRmqlACxvFcSpXMLIlIFSYdG8GsspAbiyRy51SgoAyIoAA10AGIQww5ZSS2SqozCMzCEEECKZjCwgoWMFaja6nVC/xwKVzJXZjJXLWomWsMeYvcVGgdFcKdAHCG8YoGemNlhd1YQyBpnaUDhrmro8JLNBfDNMfIIwUnSmxkhoAdLNCxABOjK8zSjNYuXBGiMEKQeKbBpncC1ECArLkUEyVRcqWQsjIFSw7GDeNXODejcYk6pXkGXwbuxX9sLeia9dqKZJHB4eso9nV+H9ydsiRfCWiPVU6wyulidhGUAeNLheph1KUEMfIKNXLrIGBbnJSBMAHzVhYCzr42FRO5IrE/mRNIgJGzcDOqUDOCACThWoMLRAcAEiKfmE4N0zBKbxRKEm7FbMvLot4NhLtR9XkdagyHmYGRJBGjLhNqFG/G7iASEjC5w9XKVLlrqEoFZiYhZ6LtsDUxY0p7KYXtbJSpTz1AHedhyP2QNi/S63ffnaajJPSbziuW86Kz93kQIxhh1rTN/TZ3W+43QyGblrrttzc3z5mJBpruz/AjuXcb4o3urvrjYR72u6Jz7Aw3IZaG9AatKAmqkSuB8tDl7EXK4lWrYYur57v+hhSLTafztHTj9dXmZZh8z16l53TtXA9UwQl9lpx2nKme5+P9GYbrnIrlaZpHm1PGdtv1adh0MmxyHrpff3cwqiJbAkxhRsvZD+fTMmmd8PL2xa7f3I+nF5sX+zy8//r9+KHWB3QYYIC2PQtWh9cGBEQwbwPdmtp0TTRw6afxuizCEovaYqd1Y0ZtwYEIx+gWrG68bmqV1IR8OY7kZcvdh28Od88flvvlqtuzYtsPibMgyy7dPLu+K4tOEwSUuRZNIsM2J3HM9Xq33/U7Mv75z34BB5tSquQGdSZCJ1ZVl6JCiujdmHtwRf3RRqHBF815NJDoFYEzOIMNXu/vy/Z13by4wbDVMqtSWSAwEEqt4ASYWCaQwyoVz5YH8rMLEUBVTcmd3chhLsRuxg4RgnkTHoV7cFyoKkt6yo6hcGTn5vTC3GbjBsjCIHh0KWEw6ZrPKcic3MgI4kCb1hCyHCYSV7YLNYviWCZyaITasDAjB3Mb3BFYjLVxXRGEWzQ2RErWzllypyZoSaF0a4hJ60SQh2I6hnYQ2mGB9kQQdmRokP4KoRETubi08ziUPa66AlhGaLYrzbzECWrmZu15eoMxHc6Sc0r1MpEk+iNBKo6bytaGDoOwJiWhr4QTexs7Zq3KjmBMLUdxZ3Dr6jzqLWMvNeQ3IEhv+FsrbpvXO6R9ZxDcqd3o6FFrKWbubhI9i6iOmS5dpMspQoC7aY0LcHfPktaW4qXBQVhFZSKCxjDBowsJ4B9PLXz68t/wK18PtY/IWb/rx/ExfPT7YbLf//qtP/vbAayn1/d73lJELif55Ucdq2JVhBnExGxGZK5G7mJGhZHAXXi8gQguQmzwoubkjyMNyMMeKjJKJ6Qu95vhcH8gMjiF/2DYTkYEBgXcoy5sVpkluFFqBQBIPFCVdsHGiBGhTaTrvgY2goSvnIA6MHtlcxiyh+iVmcVJiWxRq95sZiPTivmFwXdorVdrIuFg5idIipkVjMQVXjySZYITh9+MAXCFsvFle0f8sFYDGBHc1aOZ0ujfl0Zl/NmeRXAb177lhSX96KFAcIJhxYODgK8rlAV1OJNneHWt4cCVIU6u7kJrjyDamt76geoW+5wQBndrCf3Y5Iq2Dps3ETu5u+vpeKxWSJBzlzp5OM21YOTxeDxL4k8/fzXP8zgvtVZd901rbphfXV/l3KUsgUIHD6sus2mtBaXOKSW4Z5H0OBs+nPl5mRdi4ZRC6+ig6q7AbrPZbrfdZuCUQLRoPU1jKeV0Po/jOC7Tze3N3/ziLXfnlBKUYCKWCJ5dstFVP3z+2WemauZ3h6POy7LMRqpaQS45P3u+naeF2AheijIlEXJVziQMW5AHBkmx4ozKCzO38TGZTtOkxZZi5tL1HZhUFybx6qoOA4t0OUnUiqZeKywG6+Jqv+2kl8I2wmZHpapqWqsvWHD0AsZwk569utluBmRgRC3FZ4eZKdU21FyZKHWZwWbK5tynYnU+nR/e3b3cvuo3XccJiaQFIKzuAAAgAElEQVRnS7ZMlbaR3BOAMJB2didXQ+xBxIxdFnWTJDyxFzhgxQxadCGAeuSMYZNRadG5KLBA3cAliZiruSIhdyBGKcvxuHS9n041ga3Q+ThCu6sd95uu36S55nqejYwTAZDMkkndpmVRrVrrzc0105jE3RdVA6N6lT5JckochatTJW/ZH9ETHXyzfnQEBTLM8aydq47mSde2ZxiURcLoWA9TONlaO10KCzA7s2uxNQIbPLo29CjsjbMtONWt37Y690ZiwbbugvXrpinnnIhlURpR8Y//sz/79IdXnMdxeb3ZpOvd/nw+zrJ06F7uP/3xH/4Jof/l3339f/3FX/3Lv/zldKd1KbVik3gYcp/SovhwnGAQySRkakxkqiHDfaQMEKg5eobGSIJ8scwWZAwUpASu+PnPzr/8+S//z7/4cn+dXry6/uIPXn766lo228nKYZErzZy7c0E277u8pFzVhZNIl5MZtFJBncyU2LuEoUvPXlyfzudaldxVi1DKOfVdz3Sutaob52zAeZ6RJLGQ+jAMECHmYbPJOTvAKZeqXddvN9vTsd6fD68/vH/26uX4MLnTeZx3IsOQq3tGut1cDbnfTeO8TOdhOz9/JkLX17v99eY8nX76s59+8+3XxvTyk1ck8nA6dsNmnO1F3j+76j59uXTD9O79DP2wzBPUoT50rIrNfvPik2fEVms5zbNLRQKUIdkpYcPdnnMWr0wK56JEaE4NFwVAS/rbeL31bF8lg7Gsm0FQ+240TOCSWVpjnLiRPOoCLy3Z782IIzgziJ0E0Q6KhejmYd3ulzdqDVJ3hOTd1NkF8SHW/iOCe8LkREpwOCduJgDkjV4W/SyYo81zImaYusBMVqlDuHkzh3uSo7nWMhODhDmJECrA5CwMNmESdnJ4NWI7TQcHb4YNbxItxd00OcyLl0SZCCTkoVkWIAlJyDYBQibBYggHPZE+DRPYovCHmBGML4oMaukHkcOqYQUOm2gPl5M/GsIGNQq+Xgw+brky1Ey6iAgAtX1IzuwNiMAlR4c6OUPWDrsAZmrUMQeAFd7vbCQUTaTGDCfnVtdQ84wGQprWqgkHgVJo3aMDHqGSnqxA4ZaexKhoZgtTNlBIXKMmbDncJRfi6IBHEKWWZj0GoFZukAO+Ssk43JcbjFtbLbyWPUitZG7rtiVW6/1uv9mgYGN/ZBGSr5UpoK5GzgmI9RpOJrLmYRYbpElvQWCScLswPBGJAsTtqi3Euo9iYLPGeQjCiq1althicRDHrXC6MG3iscaB5cHY8YsXBV1ULQ6yVQkcWkF3VG0YpbibVUUly5yyJNrwMi11toUtsyUxhS5lrp7fn+7Gej7Z2KPPybn4Mo06FYP+wx/9odyRmVZFxajFymwCFmbhNHddNd12w26fZeepzxleCVl6VPniix/dv757//buw9uHK8lXL3/AX/D5/jvcz6d5LFU59+wJHuo5cgGJg83gklLuOu5JxRYsc9h9brB/2e1ebKZ6nOeTiKYMUN12L1hp9vNyOPh4Ks/OSXE1YNPXYZuyDVbrvEw3XKvq9DC546a/Cp7Fftv3vRDpcjwdDx+6DMdUCnddt93uGGKFxuNshTdp04Gm9x9o0ufbW5/57etf6tGid1ZnhQd0ak5BTDGAYseBmsFIeO3RGsGplUROrBfUdHVDuJSBgVI1yDdkig3rpTAOA6C1VsBrPafMWnQpdfww/+xf/O0/+i/+4S9/9YsPy12S/nw4lLFLfR6G4bSMXScLAQOGXb/dD5xKnnnTb/qcxuP8619+hy2oMxGzWU2ViElIGYAVqmAHGEbOIMhKEvL1OAOIdK2I4jJXzo2CHV7GxZaJtfYwgcWcRQg34TJEMktCcnMT4+RpkIz0cBzFBRZpp0eXpU0wCbBjHYqC4GahbSG44+I283gIXoKGX9olcH5yeq6Bl+Ax6oTd2ClKLVUwIajBgmbS0vhEUZeHLbk64K6wFbRZT9a4hHjY2qb+rAgFnAgxG2rNHNmDscQcLjf0sXkhxZjXyD1bMzeiA+DhshaSIGJ+HLGKVVjUaNkIt5ymGG33hBo6GT01Wxlaq74PUGvWA8zWTkZQnDqRcAegK40X6zGKPQXPen0MAdzAw2NsPR/QPBV8/a8BH+E7bdXFb2JAV20WtU6xXJrGgMdQSKLLEd0kh/FhmiRxpVmFy/5l1dBKam6YFj2C0eE2wMxAuDcCiDDvT57qR6/fg/PEly4wVvzl/ysb698Euvo9r/R7ruMRHn7yoS//6O4BYPnHI/+oFV5GlCRx6og4OUFRDYoGu5izQYiY2BhEEr6eHmNC21qBgUSInN0cJCn1/abbDKfzCQSrVTWkf0HpITAbHGxOZGREVN1qUVuJhETVV2YfEIsaiGFolxwGAMDCBqu1ZnNmVoG79kPPiaQ1tVyTuYMpoTVc4dQShSBEEAMxQs5NHRcfUzCIs+Schp6zVFdbzm7GnLhL7gyvFYriZloCN2W6eFJAmciJYeZB+Ipk7AmK+P1nqnxpwsLhDCNmQiK0AsXMKgzuEZjMTclca2PmAmAL7M/coK7mpeZq1YGqGux0iz4pCCF6vCwccrXqEcXZ19gY+LQFG7O5jDiQMI5nsHughCwi0gux4P39h0nHL374uTPVWqZpMqurqL9a9Vrss88+q0tVVSISkdxt3W0ceZ7nRXUuyzalYejFsqsWrVSWTjgg8lJLymnoB2NitWow8wpPfZf7bqmFRa5vrzebYVmWN2/eLsty/+H+eDxshuG//+/+6X63Z6JaatelnLNW1Wp0I5L77faq1kXNn3XbPaBalWyuy1IXMJ3P00Em9ZSyaoUuthQ7n0+1qAVjLlOfe+c2HcDci7pZpWlU52mpdZlBoJ4pOgbVct9JImVKKcFQS2F2SqtfMWNgSsS9JKHsAATFa5eTkBhMsUzz+fbF9fNnzyRJrRUC3rLPbqboks9VCRrdLxYiCvcEd4K6EHTBh/eH3fW2oz5T57KAjAjScUrJwjBFDWTh5rK2BZp3SXC0+r5flrHWxay6s1lNOymmrg6xroth97a97rDD6b7o7MNGWLioyiD7q510XH1RWual5j6dDrWMd5l6Yi5F7w8fQEkyrm42dzoXPbMTizPDHOfzVL3CUR1/9MMNAUOPxEYUnunQMmmBkEPNOWr2IAm7u8GIjFcQavV5aVvCV6QXF8oBCRwxd4aa6gYxeo0AMrgbxeD7S1lKJBdHgnamEmJCPFl0AB1rM4Dc2al55aCRVtwj74vKKDmjnU6dAxXQlDFv8F/9N//lv/qbv/ibn/5LU2ix/fDyZv/Z7e3Lm+7V+2+P/+P/8D/99V/d4TVAwAaoEMo5sak93M9aZxBxFjKIMIGMou/H7SwXXEwo4QyvcA9+lkhydkINkNnJ3b0uTlAxPBz83cPyy1+d//wvvwXjP/zTrev5s1ef/ckf/+SPf/zjf/BHf7S5+mTA7jSeDof76/02JSxWcuIk4jl7NTNNoKHrbrZXdSnzeT4th1qXvhtSzpsudZm32yHGjzwcT9NxnpZpN2wTyzzPSaRoefbiOQBzz1nmsqReuj6//MGL493xzfG7//jHX3R9Nx6mJBJ6N3djoswdZeK+m0t3vd+QvMoZQlS9HE4PSfrbZ8/7ze72xfN5Kf32+nAe//Iv/8Vf/6ufq6elkvS758+egcSJ3r+7R60sttsjD+j7nthKWbTW3GHopI40jadM4CGnRHWeyTsyeMzPNbSu+1pdt5PQnmTSeJJkXUpwf5IkXA7VWG7f89Nppw+pOwRODI5meHDyY1J9LL4ABy7+DmYWDaMmL/T1K02f69HVdMBJSIhzzsTs0NC2ATB41wnIKjNppIPB9Q7EI8gHIDgCLYs52kxgGCAS+D8Te3CiJQWxSFg4hQafjLjBIXFbVAGDF0CMCCKcczZ1IjKsk7+IotelFFgRPBSJosHUrbWUUrVQz6nb9AlpXBAqFjKN7d560lEwqZuaaWXh9bE8goXc4EPA2M2eFCzB4fLG1HFuYA5aDzN+fIWaLllGBKiIMRSiG5UI48FGbzOgHA43MAmt/PGmEgmoZ8VBL/MmwyuTWYjY3WCqK0ZvDgaE18nn4ccrj607Im22oMDHSeyl29qqD21/+V4Xly+wLHn4qLg7mXtKADGxPQZVCvQ/GnjwdRwFt8qCIE5hS+iP33a5gXGFIVQJWiwRhNW15XNxKY08A3PDOjgM5C4GW4cvtM++XnwL864edjhgYmKwsDM1mkcoAtaC6LJbf3+l4VVd3OHCMdBIhNjcrVYjzZwc7uqmcIe6gj2SVRC6HRGTdKnbdkqzuxmpJp5tSoPsb3Zv370d5xGCuc52VjJOlvd9f7Xfvfny7XJeMrEDtmhRJ0HqEjp3sm7fbfb87OY2b1EweaWUcgIv9/Xw3bvytpLixe7Fpz9+NR3O07jUai8/fzEven4YSbjfbQRpmYqqEht3QpnN66LTdjt0+046PpdRtW732+3tcPViv78dKPvrd9+O43R1tRcyXfxUxvmM88N4HE82ln/yT/5kLu9LOS+LzQ/4cDhkTTfdq3zdA+l4HKex5q6XJMyURTJTEkdS57q9nSz5OBUn3G66lLrX374Fldzl3SYn8m/f/url/ke7bvPtN++XbxYoofJSis+aKUfd/RiBV4IgGs+quQO3LzbENOKh02VLrnv8N/8SkuOna5kFuctVq1olIhEyh85VOrx99/p//l9e/7f/7L/+5Fef/+r16/n48Pb16fxAV3kHNsmicNMiAza7LiVeaq218kZE+HQ4vPnmjhLnPlN97MGbWZAl3B8r8wg1xObrTnskj1DDFdpne/w47sRqVkotpfYsOWVJZdPDlLThAqoV43ksXji7uXv1jFwLUB0xORzMQQVu9KBWDoO+v6HW0qcdY5d72M5NB5zILRAcZlozu3bWmnszk1lRunALQcMfIcIQpkQx17n1O4lJOCUqs63Ixwp4OC4JZOMa+RqSV15VWybrE78QXFoHyFvMb+j4ChUQIjq2DgSciWJ+cZuXhwbQXP4hwIE2P/2jw2Zdyiu83jhDLV0IpIebtPCSPK93NkzBQEYxjg052KrGiRGt20wuAU3BVlVhfHZrZ1I7EFS18arWQ+DSUcblqPSgkDEB3GDEAPpiFsQ6NbK5Zn9veQBrp9lbZ8DtiRPiZTX9ljjdvsHagopuw8ffF1f+/wNNuoBWTyEgPN1i/y5ej2f3ZVGuoe7x+vDkKp9e7tOgtv5juL80WxfiBE7RfIukBM03A3GkuQFtIp4TU76Usu5q0Vcj8uCME4RdyIG8HbyaerWAhFclgsOJ3EEslCRFzAoD7Mv3ILosvrJ/IsUTImFnCug9eopWUatWrdkzswDFyQxcoURQUUrOJNInXWop5rVhoQpFOyTaggp/EnUwgwjsbPQkaWCASUhSkkTkIszMUnVRK26qkgQUI4vjbjsMUdNdXsBHK/URl6SnVMH2tcgdhSmak+uSXuMWxUTAeuGAREA2rMzDZiGirSfvwW00b0+0QftEgET5HdonMzFafVKB9s4aYlGsvVgDBTSuprXmPm02m6u+6wTzfJ7ujsfTqesSAFVVUwanJMLJmxaTq7mW4gByltSxpJRzzCA0OISlz6xWZqu16BxTJrm6SUqb7XZRW8pikT3DJCUXLmancUwpXd1cL+P87u3bcRxzzgQaz2czu3tzV8cSnl/b3e76qiPmzWZ7c317/3BnRIt6yllrKWah8y7q52leTGNAZz8MXYZWP9wflvN8HGcokABF1dTlbthtVLWWmI8ENbdpHLZ7IoVVAMtiAHyxtE2b7Qbux+PDfJ6WuUAxbGRztRGh0eda3WY/jsdZpkE2u/5qs91MPo86TacpZemHzt1y6h8ejvf1ftfvYNhsBxeeyyyUiymD2mHjbmaiLsJkUF173hWvv37bn7rNVV+Vz8s47PtXn754eLjnTBpptrt5bXuTENoEEXK4qkqicZziQUdGkvvO3M0r2J19XCZ2eX6776TruuMy1c1m6+5G3G36zW5r0HF2qwr48aFKopT3Q94I19NxKj4uszmoH3K3g6RgMymJmWoprrWV8MI1JfQd5cRdR5seTMs0nUplSQ5VT0ogVxCCy8gwd1cCt55+i3zcjqWV+eiQcCQJlxNO5OzczuBoJcEBdtKql20aJfEa2ECtZwNe/bBCSrImarZ2JJv8o9X2l8qRGOv9dxAEcz1Kp+rli0/2/+gffDKOD1WXvs+3N7eHD8eeroU280P665///KufvfnVT+9SAd+gzrAzsXRwUoUZAbnrkgibW7UgTSrUTEhyZmJ3i16qu8KhtPKkm99E9LIkkjgCBXNdkJKkPAixFS2mDqV33xrA0+nucP+3b9/OzDfDHz6/uu44aRoWA52nZZ6OwyDbXZdFKCczB5kmefjwrkyLzvN5nM5Eu6ur7X6fu77LGTvabLdLWQ7jKUa+TsvsVWFeVck9c+r7fqlFYRCupqeHt1Op2tmxHADnnjpN224Q5nk+lTpTNkM9zaeRZkokQsykaostS13mZbl5djtc76s5OBn04XB88/7u17/+zjipS7XEebPZ70B8fbWHqelydbVj9tTRw8N91eJuzHz77HboeTrzNJoI7/dDSl7K/N3X77W6lrrak0f5QhRg65qc/QYG9Xi4rMYULXN9TIg/zjy/96q8CglBj2lmyPlDEsCtjQLWQFfQskQLTVY7q7ylgNS4+sH45pSSsICb9YSv8044R9s19L2iVNmao0akImQUHTAYNCwiCGAyA2RVcKxQV9C4zCtpiokn0alyWDTQzExrA4oBmFe1Ur1QsxILylMMX+d1fxsC9QHDRUi0mHnwUjWZChGxpJxNq1k1b7Mfg2HJHPh3HMaWSC6Pq/3ZHmhc5ZoTGWHt60bGbQ6Yr6m3++pLtoJNK5jlLpFqE3gtc4wcDENMEyZmssaxiq6EB2Rt0QfmEDBfCqwLAhopf1RshNX/+NJJR9DjL5fFEU9XEJOc10tewR26rO64D9qIrx+taeBSoOEJmZ3WCBuVFyyYBWgZTqunL80IMXrSnI7R1JevNrzw8i4BJFn7N3G4y2VogV/2BkKmgNWXH8SkVuM6AyKMpohbYw20G0XB5WtWqixEzBDMZWll5JPC6zfh5seP8aTSNXMKvgkRx6JXd6hahUCSOLSqQYOHQjAzXtXtROM8GcA9b/uNqmtRxbLZ9bubbd7l8cuRwSTQyUqpcOQu7a+vPv/kk5/++i+QMaTtbp+V9X48mnHqpbj2iXfPB3ZG9qquTjBWaF3m8XQ+Hk+89/Nh7Kjrc67L8tlnn7N03YY+/cGn3/Lr8d25YnaYZ/NkYKPePLF7tbLUjs5uVH3h2u26V3/w6ubltQw8LacyzSmlYdiawotVXcr8YTzjfFpsKVhweHPOOe2H57IdvM+6633Ew+sPX333/nCaTLnUWqpKSgR3TNKn6+vds2dXw1X+4X/0I0vlw4f7w3iEEJFVHXe7zbYbSFnnSeCJ/XR/fv/tB5wjWSBfqlBHzh6x6nE9tydNFwDladXmlz+xwgHrcI+PqRaPWEZkLrRuESaAJHG1RtWK5UzEKUutird2Po/b7a7D8N3dm3lmnOxIdnW1v77eH08HEvQ9cUKtyzgea9XUhmMWLMh97jgpeRKvYnWuHvPPEwtJKMiebKyGD2CFIR4xrCebHe3QELCao6qpQiRn8pSw2QzzRLMXMAhktc6Lj1okxnwYeyU0KiPFgaXucBJQY3SYu/oaNNsZ2RBjEP/GfqMVz/KWCzeAxwlsboF4uXsY1a2kHWJyIpBTc6gJzqxGGyLeGUAzlmrNhkcCUXOkQGhCG0z2vePbV7rYil6tHZ+4yidVZ/zKBj99HF5dQev4lSbPJgr2AhE3aLWR1daA9ORlbgEKMXO8hcVJEmJYb4ZZxn6ZwLauU/U28ZNidkcU/q0+j74ZEydycb1Mi4yshh/RpdbhivtnHx8f3kpmPPnQ1MjOq+KSCIg3bI77WNm/v5ktXYJxgFZtXdgTf6bL+z7e4La61qW0iiouz8W/B0z/G2FYePKAvjc979/e67e+S7p8If57mb/4PTTkEs78iSTSn7zat7qHGQYccFUNjzdAYAKSUGuBAGtJTmP4KJyEuy57W5zOzWkVGhO+AIgXr7pYN3R1KWYaDMXM4kTFtKGLBEnS9T0BVasXa6kikcFrH5h6dPQvq4s4CYQ91AvizkpoqJi5M7mkNE6jSMqSkkjX9V2fTN2LQ0gZKi2DikYcEZEwHF7h5kjNT93IjZ3i0C8LQV2ciUggAmYGA5wocZFSuHp1Z2tWOIHPayDDgc3/di7f+ska9XJlwLdKxYmFwRH7AEez0WAmgN1iJJxBGCnyTyej+PEL/CQk7hUtRSdr4BOteHgM5I06mrRqdLUfQ5u7hxHoWvk0pIxh1TgzZ0pd4sRSmJklk6i48lJVrTqqhWaawMw555QSg6fjqEvVWonYxVSVncDgnDJTsYVzkpSBYu7zslR3kkQpqaok6bqcWM5VDSDnNlmHSboE4bhLCquqpdbNMAybQYiPDw831zdlqRTOfxhr0VKWpSzDMKjpp59+Qun4/t3dt28+nGYtiypsqUvxArHPvnjFKW13Gc7TuNiHD6XOIJBAcvihKSXASdUWNXf3uLksyzIpagBGIpw5VdKh7/qUx9P59DDCwQ4ydJq3NFCHJGkqY5mUmayqdZq2PAy5zLPWWke1s3lxZNZFiy4wbDoAqK5wczZmzn0WZ1dU0nB0NXMWJrBqJSIWMKMctWK8ub0y+LLMpNgNm8PDHZOQkKUghIXtf2ucMEEyA6ZecsfHU40Myd0poZZqZCIYNpuuT14UVqVHzrRD15fUpaS1KkkaAC7zskzTuNTKCaczXj7fDv117jqiZS7VDcTy4XBw6iTRZp8BnuYzqDIg6aKzQNVznyCchNHnvN2gJ6l1Yul3++6No9YaZfeFPeXU3NXDqx6tRAxlYZNaA07UXLJBgBBJTDeP3mBzWb/ATZccJwpdb4QFFmrjn6JsJ1czYyFgHXbVFPOIDMQBGDfiYxODxO8EERSKdNaMVze7H//J5//JP/7TP/+rfz70cr29fXg43e4/6+X2u68+vPv63S//5qvvvnkndbejNC/FpiLovDQTIYbH4kUTOStCtUQQlszJ4FVLpEfq5tXCbwLBMFU0+5kw2YAxEwmTSE4bAo+n2VElIXWSdvT1d+Puqj8Xf/f29Zuv6vnQf/Xjd3/2kx/+yU/+6Pr6xTIf7+/elzKOk41T2u1y6jjlJMRpy7/41VcsImZlHMdpHqfxtpbr29tG6XbdbIdXr14ssxpRmedpXo7nE9yEpU85dRlClKSX7v393ddvvj0v52fXL3rq3/kbsTRsN2p1mcfj4QFsA3VEUNXD+X5z1Uvq3KlqrXUmoavrGzqfs9l5Xg6n86+++ubnv/ryPC2Hw0KZz2P9cPgwLsunX3y62W1ub69vb/YvXl7fPts7lLPd378/HA7CqSxgk2Gzgfv54Z4seU2l6uH+cDqdyLkV4twq3Qtu1Zj2H6eyvkpOLoXNR1nmYzX8O1/WsJqnbZfHnGtN3p2dKK01V6Tl9DQbWZVmDgKJO0fUIAhLkhRrScljfzRzDAbYKLUPKCxWtdZw1/LAJBjMSrElmrkBX84ob3lqE4Q4TKmSk0tK3qoUcw+edSi+DA7OMIe5qVVTdcRQ8MRmzI8WriwcYm/qMlwspY7ldHxo8jF4cYUWYU6Ji7dGcjyqFYCUdpiHNiXUg5d82rHiee7mVg3NfF1dLwgSAc0KywE359Ykbr93rb7g7hZFgRu54OmTl7UKIolI84QgSsziiHjIYd6FNhVs7dtTS0Ja9zFG8sLASCxqpKYI65QLxCMgCVTTLgQGUBCWLLhkKykAoSshXQHK72NYF1pJS1Mi0FIUf7EMKGbbOohBpKGJgV8IjE235b+xI2gtXSjIr/E4rKVFgfjFHRACMdkTVvKK33kDnVax4iU5Zw4qIjGjDRINBNEBxNyk9XFQe5jN+n/1sGsXgY/TySdgnDsRBB7jj4JEYrXCzMjMjA2NdNCckmN2NbVykRws43Qmls3Vtu87dVqWGeL7Z1fdkJay9Pu8312lnMq5YnFUJiWbfDmUT6++GPVcqTJzSZbzMpZ5rgbmTZ83m2EZ5w8P7xP3HXdetIzzdJiW82ILju+P47FMvGCALkbes9Nuf717dv2sVoKcx7GUM+feE0hgyZ1hqNRhlnmyGYDs+Or51f7FVjZy/3D37t1bo+X29rrPdHg4shoqzoe6jGZGQz9wPz/Ln+52stv1dfG3bw7vfn1YjjY9zG+/Gd/fn+AQBiVhNjctapKWZUfzNfGAFz+8lq310vmwXWy5PxxMkbrU5zxOSznr9fa6zNP7r04P3zyAQCZsrIa+66yYszmYoNRi5eMm/u2vC0z65FsuQf4phPX4R9TA5A4PP7oQ0DS/FyYiSllArLVgwL/+2S+Y5Kp/fpzeDF137otPJon3+wFSu+cb6jX1XG2ude66/ur6yhcy036XhrxpRk/izNXR/E0kS4IsixJRE9AFfYcu0Br8EQZoH/IRyw6NGAGhiqjOlFOirsNuC9PqmEVSywFD155AxO5UqsFgFldC8Ag1DcExc1e4AeaycnScmuAyAjY3zlMgKkbELQzgglRYk96FEPD/Ie7NemzLjvSwLyLW2nufc3K6N28NLFYVya4me6LRkGTAgGSp0YY8yS+GH/wD/Jv87B9gQ5atB0HwBD0IaBjuRg9ucRLZrCpWFevWHXI8Zw9rRYQfYu2TeUn2YMmQD4nEJfNk5tl7rxUr4osvvs8jkHu8o4F0dGwOIMBr95Cn9Ch8jo+zBV5dn5+tNwiP8EpVtDSVH0CZQNobyfaIXrUAHODICm342l86hpF2KWpKMWtsQHhrryQmhzbpgHZKPaxKX4GSBjt0O+QAACAASURBVMEkZuJ2YtkqAWCtswUCB8vqAbd1END6vA4PjTuCgdRXpcIwHwQAZ4YpVtsaipMuMuqgUIXOBqNNQqBxQd7YRwhCzgrFrVuprT5fReG9ffmV2/GX2EKtJ9GafvawnNtTpKPJ2wMas/67vc/XlOoxYPM3f/0VKNW/ya/7/+j1MEL4OKn8lS/6JZpP4FxvQl0tVsSpXk1RbH3EzKulFhFMS2vwIYAtCeux5tZqIGGYa6g1hHxoYnOtZbnoT6FwcWcXJknClBhWqmqpcA8jHma24ohUVliYRVBlieLS41xt8QyUhZryaKyyEOXgqoplhrDCU5+oY+lJMhExlLx6nSvF2PFSW9tDQUCiJJzJvZKSV+m7yETN1ckUgJtWdy+UkHPmxE6uUCKiFPGDAAPDOO7I2jFjQg3trgauA3BzP6L69BC2ALSEm9ZMKL7PFEIVAT4Ee3PV0oqJcZcuOcOhICUFARrSdixMliSZw6FMHHs/Tq3IL9nIiRGCvu5NnhAUmlgIkwpDM7SOA1aaNpO5M4UyOwGk0KUWAJISuJ/nyawwu0i0RtTUCJSEs6SlmhBLP4gIrVPsImmzzTuR1EvX913fLQdV6KI1MfduIWpaak2SupxDy5CNJ7Vxmad56rpOkk3LXEqpy0LCkkTVhqG/fPbs7vaWIUPe9EPvQNXlxYsXr1+/utvvc86b3ebpW5cKfPXq6ief/vTusOxHVIcTco9ug7zp+tzttru+6wR0nThl9APA3PVpv19iaIKcKkLNTcACsDMVnURIBjY1Emembe5PT04yy6HoScq73WmS5MUTS+YctzEhLzqlxCzSpU6IlmWepnGaxv00YwEmdKcy1n2/2YRSNXqUspCLixtq5OBMJGCL6ezQxWc2sLkJmAgsbgtIsR02Iry3+/vrWzgRe0rs5ERadFV2jKKLIxmqiWSzHa6u71LP5FSqUkZZChK6od+cbrZ9dq1apqKTlwrxJAwUIo0io5ItOs26uCNRf7rJXd7VKqrVgyWaICLLjXudweg3stlsDgeqWgGYuaqVUvazwyeATE0rCXWbDQbe9L2IDE8vzz5Or92NQknGmsL0EaOqFp4kkWs4o20Np+YmGPWvkwfGLQJaJ22N1yCJldemiGTG1kKSmYmMyBuE7ubwat512SKrQWuSrhPwRACULbx+EWyJBm4BIHLeQBnf/o1v/fpvvyudv3j55bMnTzN3qF3ykx/82Wc//ddffvLDlz2l3rdJshboXYXz2dOnVy9fh75/6rIIu6nqoqW4ecqZGGrMHPLVzWaahcWkWDUzhBEEscNNPdSX47/MwQXlOi7uVMhZ2M2X2WypaRBK2YinylcvXv3Fv/yX/9cfpb/zG7/5H/3e3/3ub//GxdlWOZWKsYz3+3J149ttfnJxerLdJhm23YbAlLBNU6WlHOaD3A/9JmUp1cfxsJPd6elJGVydtF8SS1nKshS3OZ2eXN1cDZvh4umFuv2r7/2rz199UVMtXFLtPn318Tubd/tNN5YZxcyqaS2zS6JEtD/cmcygbd93RO7ktWo155RP+sHT+PMXVz/64U8PRTenZ9zt7vbT1dV4N2nK9Pyr1xcXJ+fnJ5eXl8+enZ6dbe7H21fXr+/2+/3h0Odh3BuMLk53iTFO9612t/rixTUUTp44kRDItNg6c4GW+PlR/aot51/42pKBowrqX5o4vPFycjCDubnfHiW7G9/G2T002RHmEI1DwwSyozJTNEQdCUgOYXaGkrq5VjVzFdeAMwRN94fU2dbOJEEIq/kcr6khByrhFEZO4Unu5OtEypGchsZacpXgdEEC56JYoyJiJglqLePkxJyYna1J0HpM/rvC2L1aGzKQxCIOUqKcUhRpkUdXa0e+yJqn0doQhhuMnYmaMQIzGYx8HRLzFdCKi1F4jYlkUEXTsyfngLFjYI1a+t4qjWOa3sIFEIxsBx1dJwEn50yt3ZicUmAxYY/oRImZDU5hEElEoexxxAeBCBtMDIepukHNQGARFiZTLyGcaoiSlZwFLND4ow2rD3SmaW6uQGnDXuGOdXhqpWQ1gOih6qLAqVqmRLFUQxTBzZsYmhMDdcXCCI/67euNelyfULtvtH6v2dIjZBUgwuFow8zsZM6qqqqtBS8c3iABEBKLu65F0mpMLdzwsRjwYlrtqMANJ4S5gjxogw20DMprgx3p2GX/FbXASk8wA8xdNZgRCHcfwEukhFH5ubs7gyPDJ5Si6siZOZOJO1samDvKp0yMLOkb3/gGHGWudVVxG/eH67ubeliefu2E6qxalrpYh5ySiR+WGWwz5uRp8bnIwtotky23h8PNXu8MC4TAiXplIvECLXZ7O83L/TuUumE4v3xy+dZbr19dffniuWql5JLZqKi7EzhBgW5Lm91us9ukId8v93W8ub55Pc6H092OKNVlGe8XLPCKZQ/M6IbN5enlk4vd26fv1eVw//P9i69effzTL3/yg1e4ARhIdDLsAFlqJQ8XNusAdzvc6t3daziGP9Lhgj781vtPnz471PFnP/tZWXAok8+WLFuhk/707vny5acv9QZDdzIflkxZWDLnBQuB9aHbBQr2x3Fm8E3aweNWwspVeuAoHP/PdV+sESCyNke4kBNTKcWJWASAwZmYSVxRZmCLLz57/s6Hb12cnSdAi8IBwTSPw0AXl6dPP3zrUK5J6rIs1XC67S7OL26/Wu73+9wlApdSXGG1Ag4miAulxOLVWl8f6+dn4CjVtuJsKyIN4AGPI5BqjSmxWlCLmxGn3HW02co0HkAmzO5W1KFARpLUdX11LcGwbbiyh45pVNHOdlR0Wm/qG9BhwLneMK2I4gSAPSDAgMoDVTZqJ3P72EKs1HJJP2I1fBw+BIH0yOxsNW6QJ1Xt2II43ozIOiVYq6qRaxKzgEI+PYgG7u6SGuT9GCuwVWbP11ZpUCuOATcaVrVWILibsfwIDlUjEgeC5xL8rXXV+fHRrTEaiGgcDm+NRtbwSQro7xfgpONzp/UfQUmN32vOHhmwuTfxAlu5VcFFiKjYfg8RESURV1eCw6Jejp+P/kfwQBqGFzhYG9f2loc32O5N3s+bryPk2tZIrN913srRdHabqsYbkCK7anxkerTgf+Vf+Ru+VsTm4Wu87OEM/Xc3QvjLR1KKzyFrWvTLb/I35mAfPi4Rqeov/4WohKKlqw6oewrxP7eQjotkZYmEhVgksVASYtZm5teWk8GqFjcDCSWGsJnBiiWyBQrzgFQSpZwY5POstbSOUuRxEu4M1LLKDLQtak5stHbDOLgPqEZGMe4XQI/Oi86HBQbv9cl7zyBOyR1QW6opA8jc7KujG+oBLzMxsxA5h++2bHt3U9PYQkpO7ERetTBT5sRJqqqHsTcTxDyZVUOFSQWTh3Mq3N3JeC1qW+T24wBwPKO2l8m0BuctMtK1cWegFBqDkYtGmyXyb4OTuZJLTg63Gppebk3pN9IiSZydvVigi6KoUSA7hZoPkTERC8HUGojGTWfUVyrrmlqSy0p0Z6JEYCylTuPsbCLMSapVZl6W5ebmlljPT3dmupRpnmdhWeZZ684H67sucUpdSjk7YVymuSxVddgM3dAvKCmlgFKxUlqpVVOkVfth2AzDNE1MXKvN8zgt083dXVU92W43/SDEcO83Q7/d1Llsh+FrX3/v6ZMnN9f77XZ7eXkpOd3c3n72xRcvX72e6pRS3i+Hl69f1apzWdycmXZbpkTqEQnx+edfXT493w6bPne09WHTdSPGCk7W9WlaFkUFWeqGTnUZJ1iUPlbN05a7JK4+HaxMWmw835zu+k0its3JOxfPLp48tWr1UHTxuYxqmlPuh0FpN02HYRiEpU51P969vr6e9kiU0IMyutzf7/ebTsY6L7vKGcLSpV7Z6lzrUrK4sKANVHgbaUnCbqZmZlQhiW22cT8/PX2yOR2mq8PLL6+HJwIIS7jPaomI0qqNWNJWTXdpM+w2YEgHVi5VHZH/oety1ydKMKtOZlb3ZRbB0G0MBnjKqR96MFUr5sS0GbrTzfbMjcfDYSljPyDIC8TYbLDbde52crrZ7nYpc601KiJVnaap1EnYHbUsxnD3bUoyDN3utB9wcn6xQQdfEJ6/a2PKmUFHdcnGemrSTr76HrRTLhKWGIKOIXyOQdoYBXRYIFnWZH0d8HBQsbDVY2IOkmT4IKi7uXPX+LCN6wqsmQmcanggahBr1vHdNt2j1gP3+OAb733tvcuf/uQH2+3uxYvXb529/52Pvvv887t/8b/8+Um/6eWEFx/vZ4alrmPOSaGlnJycTNNYl8lMJIm7aV18KZySdAL2WmvRYq6mZqqcWXJyd6sKYSYSYWJ29+IVizkZElFOBnNTrwvlLYREwEmkZ86M5PM8H+bCRP1mc3J6Po3z85vrP/nBD5xR3P/R7//+6TunP/vix+O0L0vZH14PvTjQD5tBug/efX+e58Ph0Of+9PRsnOdZyzSNz07fYuGrm5v9vUvOKQ9Dv5W+73O3v7ub9uM0L92z/PnnX7z3tQ/e+tpb9+Xu088/nXA4e/d8rPd1tKv7lxf9k3kZzW272Yps9/d3+8MdC1H2q6uX97NM0+nFxXnfd8uy7KexKrrNFlWvru/uD2O/3d68vk2K3O9kdkMh1r7vbg5zSneHw97sfBi466jcTM+/er7f36duON09hU3sw+npbuk8ZyFwOPaGoYYkSSknIqtmpUTPlhqPaD1o3mi+HxP/B+WGY4nubfv+5R2wR7/IGd78Z6lteic3r1oAZ4gInAENmfJIGcjVGn8bHGGbCIkCNDcDFa3m7gkWtClmIiEiEpjVwLCIwgnR26AiYORNENwcDGdSOFa7Ike0WwMhaCwaoDXqoqyJmUDixv7OOZMjVQWpGsBISYauI8JSC4GgZqogNnUX8+qmDjZSi6adqlUxSCMawOEoBnMW95bPOLeRsUjSbB0MDrGjGnKiAMeh3YAuRwjgq8NADA8GAWOF7Fb80pom0xupYEsdjplhvNUBD9TLzSSLoQIgAedg+cA1QqCBI6ihlTqPUJ5WiDHnnIXEzRd3DTFaYk4iWUwdxlBde3IWTo2cpFZvd6oNVbZlFZM0LYF1MK+zjat2ObU55YfavX09DiLSWjhQawHAfRWIx5F4FX8QsVhDucbf/FbctIf/x5Mkcphp1P85JL+ImBMRVA0wA3mQTUQgFOCUWc1ZzGBmbtayZmJJFCMUjW9AIBECSXMocjOL2UPE+g67A4KRPapB/K9Ao8PooFVRVYNlIgmUmDmhenAooasTPMfiAIgOh5l7SMeV6mEeQZANC3FPeZOHs9OLty/f/uqzl88/+aTcLbonLF5uFzMrT06vX7/gE0rb5AMB1m2HbhhyyfvpcLc/7PeH083w9ttv0WEYX9bDeNB7w4ze0HHvB83SEUl1hyqqYI+7fI/El08vv/nRN/vT4fP7z3FTPGPJQAEWQKA9MODZe0/efu/d3Ofrm7svnn+5Pxy6nN9++93LiyelLLev7+YZXQUbZ5imNPTbty7e+uYH7w989vHnX/34+z/8/NNXh73ucjc822n1/X4/7ReCVDMigStIwUwJJNRxNql/8Wc3/Vv46P3fevvJ12+m69s7mGJZyljLe0/fY/ZtOh/ne70FCvd9N5U5D52Lccvha6DkBoYrEfiB6R2b9+F5t6YWHwe0G3zwmPwS3cqV0PH4BDjGfapVOScRMXMzk8TupO6oCVxRcbI5Oz+/Pxs2L1+OMM5DHqepS/7+N7/15Om23NyO035/mMcZ223NfcfmL1/vB89Wp3GcWdm1ikgSqsmTMBktsfNXqW1fI1Pb8b5yHd9cxetGhtfFGTCoolav1Z1FpO8ys8yBCZBEZoeuT6enZ8PQzwcdl+nebxtuBYXBPNw6mw6WB8YUCEbALW0Qr4WJle72OHY8ggzj4zUL6eOTgoWl4SOaFtycTENBRQRAhxyixAHXtBuh68fAI0xjrcJjNI9W5qYIA6TuZOtGfsSgWOGSX7ytb0Ayjmg7tc+vccY/YGcrVcuBdii12vkBSG1Qz/EvHemxzbLrUYNg/UAr2LSWwu1L04AORY5A9xrIwEQO9tXoEIDz+va4IlsRIpBAiCkIboHKh5bcOnXY4BEiMnMOS0aLJsVKMVlxuuZUh78s1vp6D9uMJAuaCa27U7NuA0JsJEwmhSWAwvXe/dLTWffEXxXhH78eI5V4BA25exw0Ryzo3xmG9Yuf8PLyclmWZVlKKQBSSgGXxgdaLVeNiALkcnfVo/nbr3gd1xAxPAEM6tmzcyfcsQhDSFimuxFq7mChlHJsvPW+WK2ViHPuzFBLLaW4VaSU+37ouv1+n+OwJiJ1mGvVZbHA1GJVLWVBAQTE4u45567rjHzEPQSrcizcTViYuWhB5tOTMwjPy1IxOZknw5Zpw+jN2bbvnBj7UkZz2217OO8P4zun7/Tb7vnnz51Ql5qQWISIeungMEVorN7e71PXAV7rEt1tBqFjc+2GLEnGZYYaZyYhVYWBWTabzW63e/H8qyyZiT1cu5aCglSEVvWPAKQttJG83fxwEJcu1VJrqXAgoeuzJAGh1qKqnEREmFw6cdiihUBEyZ2h3qdBi9lctKjX6OcyJxEWCAzOAk5sMNVavYAJQgHbSWV21GqlqKkG6OXsCoVAeuZMETfMHYkkeF0peMJYtACgDMlwQBVQdAnnZ/3J6fDWs4vTk6HrOQlP02RWzs/OmfnFly8+fPtbZS5qWmqdlhlCue9IyOC561x8KYuaUqmkZVlqrVVYNpvdsNvN46JqVW2a5nEcWfJ2t53L/PLly/v7u90w7HYnH33zoz7nw93d1dXVdDhsuuH89IyYvvPN3+j7vmjdHw7LMv/z//1/22661HWnZyfVdF6m3/7ud8fD/H9//3upG7puGOfp5u5+nKoDS0Hu8Du//tH5k+Hq5cuzk9PqXMGl6vXVzc3dfrs7HcdlnkqtWGoo2hKBHSo89n2ns84H3W3T5ZNnYsmmen5ynlP/yb/++OWrWzgwA7WRjUFAuBacIWW8/fZb73/w3tnZ6f7+/ubF/sufvVp0OcyHk7Pd7eEOHeB4ev7k4vTi7vX94fpQplrGurEexUQSDNNhKkvNWaIZ2+96h43L2HUSehSV8ezdM9mm6/l1AXbnueszzMtcYgi/VkxTbdwrBRi7kz4PKfep3wxLmfeH/VzKovjWd96/v7ufxtFpzp10nBzmal1Kpycny1TGcXr27C0Rvtvf9X3ebIbXr2/mST98/9f/+I9/uMzkdaQun593F0+GlG0uS1mWwLtLWarathvc9d133pckN1d3L1497xI+/Fp/ftqlTFoX0+ndt75+9eL2YvP++fbtFz+b/vF/93+ygsoGxGoF6hyMU3c3TTmrlhpVXELuOiRppCx2IKT6tRnZsJMQJTCTsRuxkwulJAnu06FYVQnZHgs2ALlDuBLHwRQlqBhBVTk86ImQPKfEwrr4Ms3bi7Ocu5ub+46zu5fD/eZ0x27CXOo8ob7/3d3v/O63v/XhBwL74fe/99bFs4uTJ19+/Pp//Kd/iOtI8TuRTadKWrXYrBVOwqkZNsPUK2IgtJPEzGBTM9PapACdmD18y9xBLmtB5REx2SUxSQJBQyh1TUydyd0IoEwkZGROChgPfcuGAmgwkNbe6jQDe/xn//lv/tf/1X/5u7/5nUH89vbF65dfLvP9ON4y4/z87De/9e1aigPVbD+Nr69vFi2Haczb4dvf/M6C+X7az0uZFUEkgdoyTeO4r/N8fXf79OmT7em2GwYn+/Rnn/30+V8caHT16+c3Xzv5+t/9W3/vo/e+PfAw383z/X4YutPzE7heHa6vlpevrl7eXL0m4aeXl9uTXVGVftNtNkr8P/2zf/bq1fX13f520n2xu9vx7jDtDwXgzXZzc7/vOrz/zuW7Xz97+52L+/uXxerNNNZCZTHBxpUPt/Prl69uboERIEhCWJRWNfKWzLk5KbcOrgFKrhrjD60jw6Dw5yEC0Pe91morh99jZgLRqEDqMjMbGpc/nK+bzisBKSEJwsXPYprMyOFFU58unlww4bAfl8MINzKoww1CRJIESQ1maMbZah2kIzGtarXCnM0IGBIleAInQYpc37Z9tyxj1ab71g2y3WxqsfHukCnrXDvJArEFdfbpfsbi4erl4E66IAybaRjmAqAEEjiDu4TEppUSNQ2gqnAMXe433X7cb093nFM0ad2hppthIKLb65tlXDABAMJuuWNs8u7idOg7M7366fOUBRVqkL7P/YbIyG2ZxjIuIBYRnasQ5y4n4lrqMhVzF2ENlmPsf/OAi2FOzuQCNa0GXcdIEpJwYH0erFphJ9hquU3CIFKYozrQQkqopynCDdWVrFrXiZs2XcvgtQlJ4qO5TTRJY1yEjAlE3uZKhJNVi1FLAmVmEJmpN4KvtsPLAQZ3STKDoKamipXHICzCglVKVZLAofOi5sxk6isLAEBD4x5a7GCKCUoKefS4dqScU07MUNXFKlyZ2JnMLXOKfg2AY5IcJzTecCZpiJipQVd8rKKVUQoP7+kgIHvctE5EJEk0fs1QrUadRYBWbR/dEbAdABCllFJKUV0AqLUGFGnNrMHN0W26tb5tE0NECea2VADcZ2bWWj24YKu9hllYXhi1PqUjkMvopK7N1FbjxEmUCOIuMHIQTt7d3k+HPEh30hkrd9xt81zmw/0ydHyxeXJ3db9/PeMeqGBkUbZqOiuKoQMGpAt++v7FxftPcEr39f7m6gbJ+m0+Ozm9enn19OTZ9JV99fGtfnHPzttuSMrz3dxxUlAhm0WRADL0IY5RsUmXl88++PD9b3z04fnl2fOvvvjs5x8/vTz7+ofviuDq5urjLz7Lub+6uf3y5ZeJ+93JCUDs1Ek37g8vP7nqd8wL17mWCX3qhPN//B/+J9/81jc+/fin/+S//Z9xemw4AQphkpRUjSBxY6tWjXEkCWYqwGRs1jm2QMZv/fsf/P5/8Q/+yT//x/v7adrjrOvff+sb75998KM//fGPvvdJuu1S6ab9CMPQDTnlWqt6AeBkTmbBkgGx0bE6MzcCBUsocH5eldRq/UVSgrf5KfZHwsTxHUocbt8i7MzLMsc5gbACjNiQUtrUwvN7H+W//w9/z5z+4E/++PpqvL/egzBs8sX5MOnd+9/5Wrejw3i4vrtmwW99+6MnZ++9/nT8P/7gD7s5PTl5+/Xz11St33bzNKOgT73NprMN3fbu6i5gZTM18wZu08P1xgZn/sWi3UGZNouPOLGzdyRf6u/9p//g9Xgr/TDN9urV9Q++96NN7jBjvFtyorzpODNRyrw5SdtPf/QFT5ycN9thOM3KdSmzLqWa16XqYuSUWMgE5qhsaq5hAKgJWLkHAIGUqWlGBLGtJUJkGli7eWDQMIcMor4OHufEKTGZucI1xKIewzoBp5mZRdPiqHcJAGB/jNKvnratA+tH27v4ga7PLdq0n1Ff+6JRTYccl1azqLwpZC7M4FoLQGTNal4c7qERASKCkMf0AqnDOSGnJCLmrqrtITbyF4diq1e3I0oOImZXd4eIcJPXMHWlDQy6YrFYlRIbyx/qDk+cyBvfyuxhFKmU2ig9DU1yBidKBDaziO3M3G7TiuCsmEkF4hYIvLHSdKlaHI5I4M3bJMYjQBHu6LocGAsRpZT6vieieZ6XeXFD6piIVdXUEYNKREDQYSFtUCE+g9Zqkb9hRQyPj/vxPwKl+itQnb/29W/zs3/D12Mo7fhK8zzXWo+r5K9V5PprkbYWrh//DncyuJlXaAgxkfV97+ruzsJJBCAz1XBIJSYSdyulEJiJ+64z5EinDtPk5spK0YllhbmRsaCBpAATCYsmlZSYxN1FBETuhpTBttZ57WI5cz/0zjSVEQoXJmajikyUQOLGAEOhYCZiFBvnJQsTcD/ezdpRx11KkriUGu0yk9Bw9lC+6M57EdaqWNo9MXOUUFMwW/1VzTxQfGcztmJlKqOTV2jILgTgiXCjWJskbf1z8DzWRmKo8XgohcC9qdXGM2xE3/BPFw7l15V/79FwLlbcIu01MMKtNBQi2Tm4Vk1ZgSFISubsinBA1Wi9rb9xnXAOOJybVGAMBjmFwig5O8iHrkvhhUcKuLkxIWUQYdFi3t/d3w9D2u62GqoxxMsyu7vD7vd311e30zxLSpyFhKdaUpbNyXbYDAqttZoHyil9J8JCIBHJLJMazNg8gyrY1cs0j9OopTCxGUqp17c356eneejPLi606n6elLAZhi9fPr+8fDZsNrnLcx2HHqlLu5Pddrc1t27pkogIvfXsSXWo2obzUvKyVAeEwIrrqyvTTohfPP8q9X0xvt2Py7Is01xLHacSzGmsTujuCjJOZF42J9uzs+TFtOjZ5owzjbfj7Xg33U4pRk8qyMjcPTqiBhA6JVW/eX6DGecXp7nrEuUnZ0+ub69r0mmeiQjmKefDPPVp2myHeT/v9/vNblhuJxHx8K8kTT1LTmVRXSqSS8dOKKohiACBkkNNmIZdNkSB47XWgCbNInvjlKnriRPvTjbcC6DzMlYtkmmX+xPB/v7WTVOCQ5i477uuyxyNDqf9/bTfLzntUxYDMdFSZtOFYPv9XYY40WKdF5tHvZND7t3ZS23mp6rGHLNTVGtVrWWpWrE4CFbKLDIk6YoB4GG3lQxw3ZxmZBBT4294IvZWuYd+SqiZR3NJmlMUkTlgUIfFsg/FOiaIOKiFzBClZVYjJiJJ3CgyIVEX4phHHgCvZVxMHJMgomJzLYbBixTa8mG862x7erqt1ZZpQscs0Dq7C6i64Z3Lp7/24QcMvn51fb579vbTD3/4Zz/53p/8pJtAwozdOJlXV7iYmqsAzk5ciRhsQGU3hJsYmSO3LlQUPivpDI3/3GxiWpbSsqpg3ZhF16lx04D1xCe29VxrwaS1W4MyTwRySQBoEB/OXq7koAAAIABJREFU8aMff/bf/w//dPxH//B3v/sb52fPlqrTOBgLkx+mssVJzXWq8zjvrfjlk2dgurq5QqKlTs6067aZNVetjmWcS1lgdrbd5YuLrsupz65alhlCBEvCUCeHkNRSp2k6jHvOTOypFxef68RiwzZlS0M/zMMm+oHzPM+1ZDAkLW7TNBVTZ64o07Lcj+M4qRpyl3PXMe/dUbWUOmudmV2YCBjH6bCvm9x1khP3fT7dpPvRHY6Mrs8b7uX27hYrskROqeVzoQFuro43m6XA6mQNtA5JK1Yp5NUJvrYkebVJskfJ7vrPgJDcAHZyjvkTd2co6rxMMRieN4ndqrqrakUxJyuzFWaWlBOnBmSq6VKdzNxjIBfk8OoKMMwVyiG6uyxLrdYSFIKRV1czVyDhUc7zQMBxOBAwcxOCDyHd4+oFNcxjFceN2wEJPXc116pw0qKmpnG0O5u7sgmRL0QFvnKsIIRqKK5LWYjItNt2mURJUSvB4Wru5CqSrHNVc4CFWqWx9vdjSxA/lHDeihKHM3lwoGI+M/jnD/SgMMuxmMk/Stiu/K3Wb20WW+0oR+jguoCYSNsBZTEA7cRMQhBq45mtg06hmRjMD6yN6wcKOUJqQbH2iw0WA4MrUwsk0YYJ7IbRCGdv5LjurlWjvGnFGR7SpeOyXPkEdEyS48YwsTtYQnAfbXYDtrIKmmCWPypAmpPNynTg1lVY8V+EMigISCxK68BK/LbGql/rQTd3qEHNLLj9DJYVT+KVQL4Sx+LTNxfoxodrA0B+HFxpqafHd+L6Q66iSeO3iE1HSAOPXsyMZle35qEU9D4njyH1dk99ZT34+rxAGMcJjG7bbU62i05TnW3WlHm766hgvJswM89ki5MTGZFBnEmoUt2c9oVmrXY4TJu5bM6G7XbLQtN0gFP2/PVnX/cZL69eYA7xXLLiVkGWnFOM6Can6g5iOmpvK93d3Hz88fLy5quTi410ePbWkw9/7YOz892Lr7788sXPv3z+fLvblVr71BEnreoaQGdFYQhQWRegZizlnffefefpOwb94fd++OlPP8EFiJvvMzkImQGEMeM6eyZHxzSKe8YIWMGIKs0o45X+/NOrjDMhFjpYTXXi6zIuB2AirkxOQmKkRObkYIMCFBO9TcSA3gzDj8dpj4QXekR4edgfb77MVngkjlpzgxOhupMflcUJWEVLIe5slcCAZokdG4RTAoi11nGZFkO3odxzDxlqW6O1lmWqmFFKvbu+VVWrhmkxq6pel0rKDBnnA0vw9ykGzBoCgyPBt3GwfmXhSkQwgqHv+rOzzTguL19cTep9vxWWZxcXZjpOI0bozk+H7EzzXLzwot3Z7lTJURRwrbXyXLWoqTuFrFIcF0xt6GQNPg73dboZBCJv7Nk4Mhlok/OtrFt1BLGyugi0uqQRVl07IMQoKPZ1PNw2bhQi7+6OJBy6W77ywuxB8NuitMCjMp9+Ba3pjZsXNWOEF/PgwTmBmJjCDQ3g5sPWcrejMiPWi2qH58OR+sD8YeZa6wPw0pYqfiHUP4TuAKHikoi11KaBBQDNV03igHdXr+5evLbEOcQo44O0IH/8E8QgdsF67x92Cj06QttlrbCQrw88ONxAEmkC/3ENqxrY4x9X1WDDRR5VSqHjuFuIKWHdxsdFFXewqZT7EcahR+853r7j86VHYqb/f1Go/i1faZ5nW1mCEaGOYmB49JDipjz+Fv2ltLHj01yTYAPUvTbwH+RKkJxauuFsBlNVU1MnchFhQlFTLeKcJOUuQ7haXZZFawHDXAwUsxDRpmVilnioDDiqk7AkZiRzo0cNBDRV91DCVid3ckmisFJmODhnyk4MT46OqWfu3NgMlnMCkmqNTkROvD8cME6b7SYPXeoyxsncSMjFzU2pGqs5mMxYjCukNRIZLMLE1G16ZmKCqrGIuS+6wCKMafUKjkkAYovEVGK44SEOBI0Q4o3W19S9WqOsidyG9VMrf1kYJFrU3JjYW/AEguBg5IRGTyejzCzkFVZh2h5qO6ocFAJy5IFaGVbhncj7yZwi6eEmscUhiAcnJxESiQZUoGIG5ySSxMmLlaUsAERo6AdzVRRiur2/uby8SDnPy1RrzTmXsniQ75LMtd4d7omZU3I3g6cs53qRUhIhq6qlJKKUMoOEWdXYQeqJ2ABiSplJbZkV6lBloixpWRZ3e/niJRF2260zFfjNeL9f5lOriVPqc7ftUi8+oR8GYt4M/W67lcSqttsMWaTqs9d3t/vDYTv07m5qRHI4HMhxuL/pZffB19+7efXlsNmMo15f3aYEOE3jPE/oekiWLJ2qL7Xaejyredd1p7tTn6sXIdC8L69+fjXdT9N9ESevYeQUHAunwLAYeoA69vfL4frF7cnd+eWTs83pyXbn7oNtPn/1mUhyQFK3lGmcp+70vN90uIeTc8eJBEZRVIW+K2fS6B4JcVMmRo1qRhiJGLnfDtMyipABIonRBu+cQES5ExJOWYZNLx1PZZwPEwt2u2HYbHKflmUx11q5VjI3rVrBZFiWaob7u2V/ANME+LDth07qOJrOOXVW52U+1JJRDNUWWaSjcAuMUrAWmKHvUMTMrdYKwN1EkBOIeVmWnDecs7kacT8MRLbYNOzOkODCAPsSQ7AOrw5lAlPEn1b0ctAcBMRuZubawCYOPNgli6RA5MzdoxRXOMWZxM6JQh4aK1oFhzVmyQoYo4neEa8Cl00F1JmZEte7xWpNJyfuC6eQ8amAFbXdBk/O8ff/3n/Ame6v9z2fnJw/+5M/+PGf/+GPbm9HmnM9+JD75BUOh1YrioaeEzmxRem7JjIhoFwN0oIMH6sfgN3NGiBLbW4rUhongMzW3lf8p+UL7iB1MgqFvQe5Jm1sB4/hKFIDk+Sei+kXV/fT8qOu67747NWvfeOdv/13fmc7nTNvru5e3l7fffryqycnJ33f7wZK3HFOJBw6XF7MmYe+T8mYdCplP8/j/Z6Y+tOT3WYrjKplP4+1LOQswp0kzC7IJ92Wwa5ea1l8zpK7XQfoYiNgqU+bYRMNvKUuIlJKmefZKHGXx7Lc7e+mealmc5kP43g/1lIhTCknyWm3GZY61aqqxW3RZawEc9vvl+vXOqXbofMylWUpWA9kGEGZXDKLmqqF+gQxi4ANVqONXUFrhYMGZLUhKg/LWUfLnCmek61u0wgasGPV0v6Flzm0OYoG2MGrPLbDljonCCdmiDtIjZRIHAqrkJ6ZRZiJ42NUFHOvjmi+PqrSpJkSShZiAazv01LI3ZxRtNZqhfUImrbL8PAiBBMZrWSC6Hq3oQ2PWRI0rk40YzjshdYtCPLAAbVUypy8elEtWkLUwB1KCiJfzAtQImCu57kUnTMTQY1ZCASDVSevBeRwZu9SBuDLDDMQo42Uu5OTgJ2cwCKENuW4IhjUCtomvMINYYysoBUP8V47djs15LqCjRdnyBHC85Z7hLldo+ixuYfvE8CtHcncspC2BBgxxwdjh3s0DdqTOMr0eTVFpDkRPI/04ajipCnlgiwczyIlcbTRKQIMMFUiEhEGvOr6N+KSAII3eJ+PGJBHYF2VTMASH64N0kRwbXqjFEZjIfQZhbKv1X3LjtBmYOEPxQqv1Vfkae6+DmEeIWNzkDbozlfVdApSHRM5qv+iAm1cjoc22ZEX6UCzhV4/i6q2PUyt6mEiMHsCrSQyvNlUbxseTXSaV/SqVQfHZX/M/tlACFlqYjKGk7Nko8Xcq1Z3Z2YyCNK27w/7w/71nmrCAVSYnMkC8Y0fDCVIJjI3sqJaFOQ55YIE85Pu5J2n71z/7Pb7z3+CSQJTq8U8lKMhRu7QYNaBAI16NLGhlOX6ZrweX5+PZyfnm91Jf3d7ozbvxzHn7vWrSatxkuj/LIdS5+pGhbJVZ+XIem3Rftj8znd+J0l+/eXVJz/56VevXoLgytBIhjmmpBvhsGXPa9srEIQHNFmSdr4QlvLq+d2nP/7iZHNRK1BlQycJw4svr/ZXM6ZQ4K+xEYycoOrq9LAmqEHOx/9N5OFcCVVvEOQKE/NDvG9Eksdf12KwTcF6Q7VjWErdm39FiJG3GtEFxq4EwzI5I7OIK3nxJo3kttQyEiQj9wBLtaxamNlMy1RC7fcwHzbd1mFO2vV9tbrU2qeUOeuiBoppaAKBV4sPi3bXWrI/zjrWRU1GUcg4ICK77cnd7Xj16vb59dWzy3cun10+u3wK8mu6Yr3r+z5lHudlGqfEhOTb3bZYLT47tJQAsLSoJUqxj46xkoOCE3OXkbAxqGlvNGzq+HCOMQBoUE48nOP4XwAmx0DJD1Ofx28SBXvAmyI1x/F11Ldvoaa1KJrGRZzwEY6O7zkiQ38pAMjuhtVS1c2DOvEw62jkFnr0jzK19sPHK40ykpp+46OYA0Ti137OH761YkS+DiJx6GoFq7RRsdTjXjdMio9AGR3BHgCu5ACiHo9QdgzF5N5KaIPDbG23xAd7DPj60e7gMWzk4eGCAOOIE6lVK4G2rl0ZetQgan30I/U15uGCL/nAIlwfSPQn1g0Z/YUG1BwxvhWxwXqMNDbWEeQ5Pstf9Yj/+te/8Q/+v339MuKUaq0B9T0GpB6/7wEQeVO1nZl/hQYWVtbPcU85jsJ0kQBFK7BosZXq6QSrGjBTDJe046aEn5gmIqbcNp45hIzcVjakUsvBnRzckrWWRKPVMupO7qoG0yBBuMQIIjl5rUW9mlgo7HhShAZHBvWQQaiHCYPR9R26FFlUn7OR1b3ZpDYYEUtm1kVNIfAUbnEBDqKUKiINJGKASYhzl5i46xJTkpSYSCQvpSz3oS0AYuLEaELN3MRN2Yid2NodfUCr3b3p8BHQMCSPzdxiUws0zbUpNq/FkzU3rPAuKEwshAxEnDiJo7K7oZbG+4zs3agZLHLwv8LBCWzhT0RvnhmBzDMLi7ODrAmZtNw0kiQqWkUkNP9ZmN1Tzpvd1k2rLcSpaKU2X2AWOQGBhLabASLDdliszssyLbNaJaai8GsQ0Xbb11JLWVLXceJEFPLyVrXOc2ZRcybpOYuB61zZhSVLEpZaFrgfxv3d3VBqVdVFK5gr2aEsF+T78f6snm+Gvu+7J5fP7u6u1ZSZNkOXUhr67mS7IanFRngaNkNOTK6SstsCczbtU3778tnNq5en50+s7r2GTg3XUliQc+r6LuV+KVWtmhqxgz0L11pN9ez0nBc5XB+ef/7Vzat7L6AFwkLEsZ7ULGSXmAlCeq/cCTFprffLVKeraTc9fXK53W53/cnnrz5za85Iwmle5nHcp006Oz+9f32XREjIHVYNAjUjq5SQEudeFAZCN2Rjr7pQxu5i1++6u0LSS2ZNOVlxzw4GObs3MUgRli7nnFIWyYyKWhchkYRh0+Uudb1M0wSvDHaXeZ4P91OdfJk9ZbhlIRv3tZTqnvfdPM97YXQbtXpYCz2CuypMuTprdVM2t7KAgJx4WTTIYXHibTfbvoOTleJLATPVimLO7lrHRbFLW2QwqBYDBYHZQ36ciDixhp5WZOAiECE2Dy0qMydnBsVYlSTJzEIGEGnI4wsJvAnJRXREis30SI/Ujjr4kQsQQK4x5dVcf8UAJgsga0ic81KXootk2IyyLLmDAk8ut//e3/rNb3z49e/9+fd0Sb3srl4c/sX/+qe4x9n5pRHmw61tIeDw2AhhotaHAzlc1jQ30h6KIhrhmaxAFKzUyhNZ1Rw8UI+WLDlTq6FoTZUbYOd2TBMezvF4h64qfMH5hJlDsouM0/Ls9KQf8h/96ff/6M/+5BvvPaX+v3n/a+8NZ08HBnH3vT//0Uff/PC99742dDvh7vr+ttRle7JNSe4O90UraxyE8GpetZZC8NJ1upQh55k8Fy6mDM9Z+tTzQoml70873266TeZs4XLU9w6/H+dlGTvuQNz3w8mJjvNkblqWolVg1XSpRa0qbKnzVMbFFxJ0CcyZElWzfhjqYSLyLsvQd/v7Ok7zYdZS1ByETrjnLtfZRGy3U1iCyjLVUpbcM0zbFBitRbOZq7muWqe8JgKtBG9aFbWEwoBHyhuKdx6diXiMhhhQ/IW8hhwk0srrSDQdYKFEJHBDqcVhObfZAQCUKWWhakWs3+YAjsxMa11qJXL0R4J/yzcCW0oppZwkJWZhhnphgFKixFAvRU2dQ7fdvaX6huOkIx2zWGsTbqGKGwmkM442xjH4bBa8VmaGc4wYQKtvho1arcW8wMkhZuYqBiYUQ1kZGdyMf2Hual7NTWM0TUu1xSElLo+ykBCDqXBgJ7BGwoqszAP7jSEyWxNjX2U/WgQBg51aSWH0oHYV1JygV/vKLoqb8waRgyjkaX0FM9eHoEraSAKtwkLjPq2K/OuMTCuHV9iPAJDEoKprDYuvI4rEzGE003BSD1MtDmTb6chToAbWByQUf7p5T0W9xO3CiKlZMRLcLVTsV/ZG2MtE2mrm7fLdbL0JhFW6ccU2I8atVBasVRevpZI5EdxC5vTBRZGoMRX4OCMUF9gQM4McDRDRzLlJWixascl2GsRowRFXoiPpLRiRbW2b/3LeDqBBV1H8EFPgsI9BMl+xP19hxGAQRP/EV3zxQdiRQQILsWHynLOqznMxNsouOZEbL9L1/X4a6y0ywIW9MkfebBWBuTLmWdEROdytqi6luJmRLofFq9Gp7ORkXBbcIjooYA45Y06iDHM3RzhpOzvMOby8QSll6uDZ5nmaXx1ubm9/+vEn5082T59dXL51ichwjGFUTef9opMBWLCQkleuqlny+cnF5eVbm2Hz4vlXH//kLz7/7IvMHYzgArTZfhABaogONB1ZbEceR0xRgYiM2XpbDCz72/GzT37+7b/9kZol6s6789N89smffX+6mchT/J5W+HC0is0pyNyBc+C4X9bn3BY486MeOKIlcHwLYcWtjlh2gzDXajcQDgO5GzsRObNEIF3fSkQSthwgWEGXBskJ5lYVIGZWUhY6G9ypghMn5F5EKSV28zIXKIiIjPquR0b1SRJ7MTBSlk7Sor5AmUDrqKYjgmDbyIEZrb2WNwpgZ1etnEgBVc/dcHNzt0xa97jv9idnp5uu22w7Ie+Evfp+nqZ5MgXIzTRE6dxdtZgVlVINbnBp0L1yM7oIptKaEmGFqkKpDsdDNnCMAGYCBLfjrnrA3ygi+NH0kNtoDDX0ypxBwf0kJ9fIvCBgAupcjoOLtMLN1FDKIIkSQJG+HhfDwyr9FWHjiLYdMzgOfwt4jCBReK2C1km2uNh2Zq8gX4s85iuLKr5lES4jBVnpQgH++KO1Gqu9JQEWqcv/Q927/UiXJHlCPzNz93NORGTmd6l7Vc/O7ExrBoR2xSAkhFbMCgmeeEEC8U/s34O4vCIekHjiAYRWixA88TIIgRgN29PTQ3dPd1V9l7xEnIu7mfFgfiKzphtYIcEu0aqqrvoyIyPP8eNu9rPfxRmUpfgzSuYAmfXwJAvUtUNhAPqIl+ia/B3fx4Tdohd9hOH9UIwPEodc/EG/DlcgGHEoBGQiLGB1App3P9pwudx3gxcLNK66mWn4OaADb/gNfOblou6P5Y5Y/Y2v/38JaPpNXOn/s1cCEAbnsTJ2TSmua+V6CZ5Xz//5i8KzkYAubTG4QztESDGai3vGDjMNI2HALUota1Yjvxmx6BtaM6ZVzJSd4kHMkX1twVJSgsS0tMs4e4mDQM/MzIyoO6vFbBhM0h9dcWqmvT/CEWlMzjBuEFB4bAzMg1gyRUtJ3DnlRI5EosTDWGaaO0pKZuTObqIkslN4iWEpc87JFbVVAsPczLZWEwsrC5O7c8oiKRvGXBb2lLgMOSUJAgs5k3cDGCAqsm7hQCxhTmedWo59UZlqUPyDcrbfXyZVxFzOAdXatwPa5wVO7i7MbsbMKSV2MjNQGPEH9mhmREbiAHVNYh/+kJsF7t2PwCi0+iYlYEG4Ye9If8ezATfybV0ThDODkVJy9pQKpySUxVjNiaVZq3UjchF2dxYuKZOnp/niSQ6nIy9iFxdIKUWEVHW+XMwqxYkbR5DDzZgI5laV4L4pJx5LLuDksqLN2yocnsJUysDM27bO67zVyjmV44GYyH08jqtuyzIPQ5aSvvzqc/9lQEabaaKcrG2Hm1ebjzfrQKTMoo2GIadUsgDgkvNxmkoqX3zyWRqPl9mLAHvmUmIkpiSSM7XmZtXNnHyaMjPVWrdtk1Ny+NPD5eOHJyimVNqmYqGPRHUzaxE4EOABmkpKSZKybG1bPizL/VLn9vaLN8UPh+FmbqvZZhvGaXS1x/P57avXd29vL+fzdlGSauoKRQEUakpAysKF2qoWEr7kMMiYbl7fHe4mfVL1Ci5JUtVmBm3GzRXm7A4nGRKBBZxioGvqgOlWt8v8hAUl8TJfWtUylJyyqW/LpVaoIfswDCdYW5YFmqDDtsx1BWVYbsv2cJpkW/PcXNXQIngzA67a3X5Cvavqqmitm4aknHIh9+rAtqlZrc3WtdVtJqOBwHrBAUW5XQyIKUyMmpzJkTh6SxARJRKGECUG18BwQj8LdklCItQlSXH5MKQUB2ZTbVCOBDchoigJaAcb+gMcPZUjuukIIvOdLdAjaUzbdDoVGS7npba1JFI2XzyNeH2D3/ndz//on/vbD+8/nqbTpdpP/uyv/pc//RlmlPKqXhK3xGzsGdzqOjuqB8ws11PC+XpeAkDPSAOZdc2gWUSRorP+d5fRwPic0dErB4O099N9i+g9Xy+Grke3E16MXBGJrA5nbinMZQun/HjZHh7WV5P8r3/+/j/4D//Tf+ff+7f+/r/yJ39w/Gb7/OnP3n9MUqyRZU5pYM51m60aKHk1Ml3Wqm5UCpimYaRmak2IXOu8Vkok0fQTTyXfTKd7fnL1MU1Zh0OZSi5tbWpqXl1s9eVpfSiebZMkmUlSyptuodEIF5tcyt2rW57Xy9bMNsk43DChNKPWdF5mIXNgGsvt6XiYyj1FJU2HaYKB22DG5Hw4HI/j4Gpo0laen9xa1XaJfiVgJm/aQKa2Ywyxi19npPsr6Aut+XUzh5uaw4mJY+xAcXb0g/2H340iSWMjgvfajSw6//jqzVWbubo5iJFTkiSU2GqFwMncg/Jpe5pMJ5JcYxE6zz5YA+pmzYF5vTDZeDoeTkfn262tprY8LSCEXwEZEIRjdZhTDOaD/RJ6HHpW/sTVeSFp2xk9ABETd4tTM8s5c8VmDQpKgBLUvDqEoBzax+RCgJI28tCzkDvMh5S5mVGrz1fRYOx7owBCLPQ41Ai0W6uaCIeVspmbW7xtZyw5yMkC++Idt8Feo1HsGz2UEe5+1VJEjxhZMrzDeu5OHna/Dg0iXojbxP2qtohCJdiY7k5g7BuFe6834M7Eexg03PaY1GDXc+yWCBbnPmy+YlIxPNvbGeqdUoCMu2bDiSmEivs4mp4r/mvd2wuh6xi940/Y+aA7k7y3Ld3ay0ldydkodNIdtAh74Ctl1rxbEHXzfHoe1rtA7Ap/7aqivX0NbBMGkLHbDs4FxXwHmK4TduoawHi8452uGKXvrszPD7o74CH+7YjVFfjcK/+4svtz3YHHvX16wb3aL79JB3lZiJjBqFVJ+vySCdrUmiYqrWm7KC5wIWpMyuxkFprx3pOKJHXzinmZyzLmllhSqzo/bsvjep/u3+H94/tHaDwTHBdQiTSWWudPAmQcwGjbZQeZEknwwmC2tPa0zkbrmzev725evbkt5HldttqsNrOzQ8FFYGybQeHVprvT3es3X3399bvv3v30p3/x7tffwzHcHOry2N1GA2YldycJ99JrSx5D5SuSG4xiZzIiUC7Z1vbrX//6X7r9Fz8+vMMwHA/Hg4wfvv0Ol1Q8xRMQEgcwnE3jWdp33yv6Yb/R8D9vy3tTZ9Y9oYmev+qKJvQdvP+DAO5yWsDhFn7mXbZHvYd3cidxjrnAWAYphcB93sHkhDKkmzfi3szcvLlbj1RSrbVBYeS5FDiEyY3rtq61wtFU3WprtS987NsYsBONcG1ge7Hxw1+cAGtNSlKCGw3l8P7hF+qKAlVbl5W4SjJiN2vrum51TQlyFDQ/X85pq7ZqravaZqKBkMSJaYEYPmfWAkHs5fggfYU+z4euxRv1Wga0L/0X4NEO+e//2gk5sQVCQezggJvA7AEhuauh547yWmu/dTFhIupuUM/+MsAPrxNFptBvAz88frVnjJsoZqRBGnX2MAEIAtKO4z5/9xWw6QypoKjqddU5rmJnxJHX38M92Gn7NdkxVrsCZPG+YXTjHbmy69bnxPHVu7OHw8MunY3Mr/Xp8+4Wi94ZV+KSOfPVAtCj6d1/tV2ej159u2Pvvy1oAbFNh8H7Cw4KfD9fgAAJrqAydrT0efzwm2DMDhL6i5X/g1v58huvz8j+H/+p4VD/JK/f+vESduyTOfgs+BsY1lVdCDwfaVfG1t+4Rr2qAhAJOk771AOBGTMARnJPUshVTRFtGLtbt4e3uklKzJw4ISmp11W3ppSIi+RSUulFcIhFQaCw6A+nmahPxN3cYn7myiSd/EMjkTOHeMBjdEwCFMhI5VQkiydU4kaVMnEWSEi5wSy11m3d5vOZKTVOTPTq1etbv/vw8DGXXNu26eak5t29EjnsWcW3lkZicFYGCErb1rZtQ8pIXNe6LIs5ihRmnqbhdrph4drWdVtBgRgZjFRNa0MzXDtTCvdnRFGl3GMLsD/qRATEzAem4WOFrYXJHAhozWOM3Kd3INsDyRBsVCbu0uwG40h2VWthd2OgLOyJgR0HZIqJ767WfQkRd+IbEQispiCGa3ApiWFmxLSsVQxlLKUUCOC0zMswDsL0+Hg/DPL0dD4MqZSsqbW2MoaxDGtzyVI4WU4gaqoR8giCEG/Lejk/5pxfv7ojorpuMBOWLDlILm1TqKY8HKep5NI2m22b67auSzPdVj8cnIDLPJ/ny6p2c3s8HA7ocWm6Xs7lfqhe1exWge9wAAAgAElEQVTN27dOZk2FubWN5jYTPvvkzeefvrl7PS1LfTqvD/fnV7dbTsPl4cGbv755/fb1K6v1y88/P296mGrJcp61NXV03+suoWEDFOTjMORBLk9ntmSG9+/vP/zi3f23Z1SgwtitmqeUqDgZu4mb93w6N6OSj7Zpq8rChYbNNpg9vH88r2eZ8mc/+nK17fHxYVmeMI6lpHWZnfTmdPrym88/fvfRmi+X1QVlyOJY12bNFVaIuCSgVlcjh4ATe/J5nT98eK9oN7fH2Ijr1uqmVBEecw1wXiUz2HkjZ9+2LZxNzXVZL7Wtx6ForcIpi2RJ0wCvTLrJODINdeO2VluFczZjrVQKhgFw1E1LztaI2bUBoJTKkA/kVqubI8RGIklbI0DVal0iztuVTkdxLvPWbKmAnc/r48OH03SXR72s57s7lHa6PK6o/cACDKYm0rfAHYKmxMTs3IhdGAliFHATdXTJYNYNXdyoSAKgrg7AiBIHJdPCSIO7MFiIycyNLFgk2vU1JByCw11B7CBAEolwljIlYm11ubsdzrRywj//Rz/+O3/842GU99+9Ex9/9bPv/uE/+h/0W+R8hzbMjzrkcjjcrZcnIU1EG4AkzEzci45Odw2rNtvPHXfL3UmIgu7BUdwiTvIr14P3bpm6Q9+1te5FAnBlhkioomAGNsARQ3Vi6SAig6k6wYyFL0t9fDyPgkp2ej395V//8t//j/+j/+K//K//5O//a//G3/t7f+fv/sunLLW283mZpuGT27en4aDWrGmi/Pru9flyWbeVUh5Luj1Myzhdzme4qur7d++Pt0cEgM9+PBxFBtLy7tv3GRlIU56mMl3qeatrOy+UbW3LZqs3//huvjvdDUNiFnGRlDKsDCkNImn86ptvzvPlvNR8kSOKWa6Nnh62dVnUXIC7W377yavj8di0zctZzabp9jAeyep3v1y2dS4kBIVudattgVZGHUjJy0ocnH0y9VqbG0LP2vEBABbnxn6493vww/keEZn1rGiiIP44/G82Cy9PAAfcyV1ySsKSGEICJXYIm1trtef6MDgRZ2rVjLx5RYgOxQVIJVVYgwUtS5zdQQoBswsUqtpqbbW6OzGQSZiHXJCYhOu2gdZYbRTgVXPTFyVzMIzUIb6PprvnrXZxXuANV6GhcaC5Er2Ju3sKBTEAgkBgbGZQAoiUsovDI5DVOfihDjNXM7XTzcmruvrWlqs1b6ib3T10/65wXDMDQwfS0W+OzweHBa+nC3P3c1goRouIZunaYjglIWFiMrh3U+A+h97BESImF/cuKYs77GaOBEOX+zlDrvaxBKfd7cP3/+2Pdzznqpq4q2aYqV1FVcwiHEaBBmJm4+jVYkdwILo3dlxn1X3Fhfmp1bbHDhIR7eDSPkkPAvlL6Jaf6WFhGwzyLuXzEOCHytCh4AARzSnG+/FjnHxX1cB7ohFdq6FdYuk746J/YrkSK0LUSQ5SU+9QYKfWK1uR4jFR7AxV713o3ky6NUfIXMl7cRizZYiIm/m1fw5pBe2DxhdKi+gHdoyRQJSL7Ggz3N2eBbh8RXYBGClF5DShhz4zmyonFk7CzOxqSsqmen582h4qVig12iQZg0iYXRKkubizO3sqbBkk3FTneRHlOm/L44oF28P2s49/dXl3oQRSQE3V3SWYyZYEHhhLizE9GwVHqZoKw9jUN3fwyDLAzJ4+Lr/6xa8Z8vnrr96/+/h4Pm8r4D3UN1EhooqWU1aUb7740Reffrms63//X/23dMLx5lAWf3r/EZzh1PcMMpCREzyRMNzUmqnLDqIiTJ2pW/DYasaWRjYX/a6lLMt2ccW6zK1MeABxMyUijnBVeLgMwEh3CG/HP519l2W96Pn3jXlv+ONZfPbkevFHtlM7be84dlLR1QkR3cQ3PGLM3KHqBEczZyATKQ1plFwSJYa4NTMyRsp8e3vD0gyt1lbbBketNcFihk2E43RczstURknpMp+tekoC93VdA/IiAgORFUKkvY4IPOkHMBZ29G0/i/bfaBzHt2/f/uRXP5nXjUmSSEqyras+LOt8OZ8focQsOWf3tF1029bzhzM1pma9iOsoUB/HWfjVQNSMusFdHJFkTCFfCEbhvvN4WArCwyaK0FXeUTX1beL6PlfbJvRNULjXSrE7M8fqd7gFH5olhckdds4f1F32z+3uuNqTh+qPdm//vmv+BoIQzN9nnI2YKfT85AZ1qGszNwvRAPbNry/Gjjbuv5ggzpVdBhg/3P7Gz/WOXvXL8oy/dFl0YIQ7XNSuVWfHy8I3JpAtjQM3uHJxorfonJ37k7jrggJQDMbDHpER7il9Jwwnyg6kds1333w79uqtqqnCEZajqmpk3n2tO4DFxDlnNW21hXiLCCzPj2TXe3KXzb58xTOJHVH0q6TxN559EXJ/vqH/jENX/xevBLiThj1Cj4eMOVVk1jN16LKXnddZKzOzpNRnU88wqndq5F6p9FtPTi2OuA7QJhUzI4t7JkmSs27bEnFTSsqEJAImbS0CFOJ+CAeBobkLmQeDRjhJEmtGXexPkmDVhBiCqgqnLCnskUEeyaOx7JSQCsvIMqaUBQmSGZmcoGJaFIkMZOqDZyzuj4ZHmLQlayEZb1OZynx5BCmS9xXJTskiYiCsQNYKeEsizCQkBM5CnHgoQ0nD4/rQtoYNCzcMPExpkCwlOfQyn0FwagpTksCPd03Dfhu7heuOF6Fv0UTYXbsZL8fcEQNN4dUeAxOoe4IIRJCMnc3D49bJM/k+4AZiA4o3MyjB1VlJYkzn5OZsHRSNaq8/HRJhEw4S7z5BcG/WTQICOxbZR9tQsJE4sUtTq00TN2Pftiact6W1aqfjVNe1T5phta5vP/3m4eGyLAslglDddKvVmuYiAC7z4+l4y5HD6KZVxyxpSJkzg9a6NKdEfCzj4XCwCYNu757un86PrVVtWC6bZKnWanU1LHMlrJKzMB4f7rWujylZ24Tl9El5c7oTpnW+XLSirsnH7E2XVpiypKbnVauwJdHPbidTf3V7fHV7yBllSMo+lHYYfF1RHSRgQUqeshIbsUmizDRNSZttF9yWIpoevn+6//mZFnF1WqmSUSOQIRmTsTXtajK4AwYh1q01bUPJuQhTaVih5E+2Pa3pK7578zY5//XTk+qWchmPufK6kZw+GSXfLU+bWlNtlImR2A0MA6o7JUlBRWTDABR+vFxarR8/nOEYy6BEqo3YRcLBDpTgDVVtaQ2JsdWmrbaaJZVBijATch6TUMmJOTGLWRimpZyJkUx9mS/bPKN5LmJtgfp4OA6DwSwhvXs6N+1jlimfpnSbU9a2xACRIpGTxRM5bFOH89a0buta8NaHJNKab5sL53n1ecM0MQ1ol4UGgI0G81VhkoBmWlJ2N7h27zl2sCupMTGM0R2svYeBeYgo/XmzBdwbKzFcwCxu7olia4qQL0gnn5AQCVlzkPVG1FwSm2s30/WeGOUetuqtmbBQmdJQppISbtfbo/zod7746ovP7z989Ev5yV/8/H/+05/qO9y9ujs/VN285MRYiUptSzgKw7kzRnbC/h5lgzg+4pgMrgR6QcS+e676LmWi+C/u7ld55I4D+h5ht9NEKXaicATcS2eP+odYdlYFXAMXBMNUG9N0yKa6mNHWnOXdgx7ulz//6S/PT//wH/zb/24CzvX+clnqun719o6yuNf5cj7y+KacDpIul1nJU87ruiYenOu2VSyEmmwlLgQINiljOd1MeTvZAy9PM2MQHzKNKbV12+blgqZzW5vpINzW1UflIQ+SmEiLMnPhlCVD5OtPPv3uw/uD8ABKzJVgrbnVqp3K/ur29u0nd3nM9/P7D5s2F4EJecokYpl6p+/NaQNVFk1EiUquOgPdnprIFK3PPCgY9N1OVvrgEUZBJu6VbxBW/AUgEh1vNNvqGt5Q1itVf76j3hwGCnc2o5w5J07MMEpMiVr8Eq0ZPCVGJiVrrA7Q2KuNEGMwWBI1xDRfAOEGVhIIO+umXlvT5s2h8AlqXmu7zLO7n5dLjFKSiLBUahE/BFCUon4FTQ3IYTvrMbQNPZTtjR73qL6ODvQKSjpFx7wZNYiTotcGbk5mMUMLrItg7LbPeekKeJVcI8FE0KUm5Cy99sVOOHJ0JMipF2xBdTKL/BUnDVSLqIe+9/LMOUAf7TWEE9gRpGbuKgx0nyzGPiUnDi+PKBCuPWDI7KwbRsWS4L0Q6f++d7vEbmAX644vfQppWtUdbAx2U0AJhnDhZ0PQnggQTuzOISXeDX/60rgCcbEldBmUPjfeHkVoYHtEFNwE9+CD9fciEmYJwHKfyXq8CznYQV2T1pUDMYYnJwuJet+iyK9oOyjoZiEaop3v0AfDREwxVvJweber7mT/uf0zMDNTT3oPlhV1rl8YgQRrIdoX7D1nvwfUgc69e93bHeyjR+3c/SszpOOA/dLhuchEMJqcLOyzeO8R0eFK2vHO/TmAI2XmTEQe0c+Zi2TB5vPT7IuzcbKsiwWhVxOFdtLZKam5UpZ0yDImZp7P1efmC1KjBr+Zbt/9/Pvzh8cRSZvVeq10w/mYEFifm5OFttaZSZAITITm2pAPOQ3Cmba61apPj+3dd+dXh9f3bbY5Y3WQQcDkrOH6qEz89Refffbp6/n88OH7e6zggZe66urE2RvD4gI4YEQGiAVzibgnkAVZz/uTfC3e1WfuJB3Divq02mpk2Np8//gRALlo+EkKGIJYcY7EYdEbWEqcEs+3/PokYuf1EPqYKf5f10/tX7WXit51aFdrnRCIE5wMZM4eetXoQ8IsAGAYeXUkQ3NXuJupGyR8WC0MtjJoNGW4WbW2KaBQuBAoAQO8IU3iG0wsS2w/XnKBQgEWVolDJx7DyFaMS8p9LrbTGmN67t6JPATh4s0UwHQ4TcNhXWvdamTEEXua8rbNl1otSckZxG7cGtikpFTXLeYGwgIGeSRw7aM5uJP3nIa+yzn2+gy7RLfvE3Gc7Hfh+iw937RnKIKe/xE8HbProQg4U/fRgYHMu4VTtGzmJXMfGqA/+Z2j1GcIbt2NYudk0b5RdKjI+0EeO4ajF5gOAOIMJ3Pz7l4YiI4BQTnz/on3X8XDgobgYIvJJrmjOwntZ0UwMvbjGM87a6A++5OOfXIGZgm3Kw7sgq6fNd4vRsUER5ioEpGAzNX2sqpTjHfoKi6CU6QNXT/GPmrob99tCPYdN2x9+4gE7gD3YdAO9Qantz//YYu4izkjmtsNRJSEiTgqq/2AQvfye7km9g03yoEAxGynG79cRNHy91vgvv+X/1/CWMkJ6mZaefc02I+e+IIgw8cV68mdLJJyTin7tprFrGNXXMPIFRBQX7DeZ3hwDoZqj9mrS9VmagYGZZbEYELOliNex4W5DEnhZsRVzRVMSuRmDHJniuPTnEkkCTEZmffqJ3IXPGcBqC4bkeUocd20M/k0HMphcGcHq9uQisFASENWIeXFCywbEahilJEr10vDE1CAhs3afP9Yyk3JvK4XHnOe8uYrMjSBoAYXYcn5phziByu6bxE7tq2aO8HPl5mZPDsSXOzx6eO2rofD0ZM7HAIXB5y26FTFzd3bfiwFqi/PDV6UXExMsCZhGgKzZ7DfkQREbGoAsUiLyEQQsyQKz0tvZGBx8uqW1JiQhDUcrMIzEQ6GOdQ9swAIN9NkZIkZrFHnx18CpDjzunFhVw1TeHJ5D3MiWHNmZAgbeXXdqoFcdfHVrLnR+am+OpGq5zwCT8JctV2W+bJcPi206XJZz7XVTbeq6u6qKpQlMbaUxoLEDajmTTUnZ06H6ThIrmlsa7053Ly+uyulmHmycns63T+MIDodzk/nOh0MzNNQBiZzN/WSRWAfPvz6Zprqct7gh/GwPpzvbu7evLp5vP/4RMRon3zyul6eHh8ehmkaUp6aUsJwOJzubg9eq7mkMhyyDMP3370/3h6nsX36dhqnen/ZgMQ5pTFLTg4vhQ4TgzwLsPlNGQcZfKb6YGwjiKi5CJMaiQItdkmGCkzZ4EG84Lo1VU2gzFIgRtgqV9Y8YF7wq7/8xY/vfnw6HctxJNalnj//+i1cPy5/Pfnx7u3b8VDUatPHhsbMriQiIslc1ZoxrBkfJJ8GHtL3H9479DiNcLs8PpWSc86nm8lVCWLCG+ky122tTu7Ey9Iu88ysr1/fjGMBtSx8PI3vPn4nkilyDJ0YuZQxZ1ovdd2q+wo0CERqq1WrHMa3x9MAt1Lyz3/1k9aqM25vbu7u3gzjcfPN9Bw7m7k5xMB5GBxmbqebo/rT02VFgtFGMnHKBnWT+8dFjaqrJ8NgwxF62aYDLucG55ySbzYcD/VpZTcGjIwonDQANLaApNgZbuoAJQFHuyyB28TweNGGTMNUUhJvZkyUBTCPYBaOfB+YKxHAFtGjRoBCUlfghXzAhJgTNgOISJbtUutyd3ucxnL5+PijH33y49/70ddff1bX9Xw/v/u5/vn/+It//I9/nQTbOsNVRPNEtrZlu0gyNaiBBY6muvc4HKkxHnHgvWONYCDvoezMHMzXqC2M4i/ZJ0f5Coq4mUM9Bg296uhDJgrYgiQ6JXOQe9h2ElGfh7mCgzvhzKTeWIiEtdpGBOIn6M/evVv/7M9++vPpDz//vT/85kevbm/ScPfdr395N94xW2aZuLDwdjkz/CRi7hOVb5+ebm/vpsO4DgpmbaKumTPE52XmlG+mV8PNnb2V9/hwmk7jcCQSpkSSrGJZ5rnOEANoymUqeSojMWVTV3O15DJwnpf17ek4Pz68OoyfHG8e1rpeLtYgqd0eQIzX091XX3x6e3dSWt89PCwEzgLo5fzRW87ZuFE9r9tcA8IQJ1PXWs0qxuxOZtzhUhKwRWoc9blkp9HziwJoBybJ+3jDJJgrBEoUmsNQIVpwZajLOqlPKmHcwJwkEzMJUxZnqu4GJLAZNWNOA3EyslwE3La2NjKMGO9yq9o2082aIpMYM+Xi5iSJkdQ0U0qeBAzdahwuBf2BIlA4MW9bwLsKkyQsomxqRITUOSz9azu7hRkew1aKXjxq1PCXdFX0KD5y01aVyMHMwuRWbalWlY0y+rCagUKpFFW1TdsadYjrs+cvWFgKr62uWldqlkIiBzgkSRmLL1jrnFLuY6hwsAxPIsCMTF2bWTUoBBIAVtTZZhpDIpJn0CGwOxA5EzM0fsvugeDBpg/6gAT/qvN6AKLuMCuAwFNHPQJXaghykrOBOz/hGioRSYhOHX1zqLtX96BTOpFDwilfA1glocQR5BqO7XtsoYO894rh3x7tILo6OTife2dBDgMxhyq0F7pEnZ3KTjFD0+hsOqHO1JwoZocOYwM5XKHaAs/rxYvvbR4RhRdgl5XHWtwb51081snxHTp2cjIij+zniA64bnoOIhIwQ4il1mWnRkSVDuyeYf3S095rOa5+wD1+UC184oI3GwEgDLg1dyKE6T6Y2bCTgSmsRlBdqd8choN3sn0HYAghI+3h8eAd1lZzpJRSEXVb19pc727vbg6n2rbH5YGcM+eRpwZlZze05g1u1NFbPrGKqqqosyaIeCM3dRMs7TSe3m/f+cYJYhXUKsEhBHbzRjDn6xGF2O2aGBMksRChwZ25MWZ2ZaAwe13Tw/32dpjskmyWUP2RW85WRJkwV707TL/7+197237xV3/58P1DmggLYl0xS1PryQJk7orw3CFugVCwxEEV0lfe7yUAmBotOfHSvCVHwsN3D0c5GVWu+Mu/+AlG+EXIRa2xI0ny/TFNKbddn62RxsBGAPd+e++A/bnJk30BgeAa6OpV22gv4WD0UbiLxUHsCtgeKY4EArnzbgzHHKWmV2zI7Nbq1qyZuwtSSVOqvB3eDOVIszVShxhxatqGaUhInk0OsDNWbJR8bbMpSFu0VlpdWyMXShz2pn3jJgoB5g5uWzzfXUbHYkaRswrifDu280NJY8pDraZtyUyewKmel4+HwwmZLDGVZEa6eT1X25ytiCdw+BolDtDIjOCe+pYaMISZkifakz933YwKJbsCSf0hp+6r0m1hdzAz9tMXersQdsT808ysqbEj0gWJhcTcrDUNyNSJiN3R1KCeJzFvvs8YgwDorogarTvad1PhblQYmych/jjgoJ3jQ+xC+5YTawQa9oQIukt8ao69MdCvXc8bjwPIweLEDmraHNqNCLDDTkwvli7IXcNIEP19zBzaYB7wlDCHzRyAlMW6c06fLTVF667cO4c8jj7tCAg9F9boJhf9wYysMriZm1GEIXRffOKd0hEfWiR6XVftoYP7802A634D4oAgioBbBxkRta2qao8up55zo1dqMTpidn3RDkb3zcMc2JNz/QcjDH+mJPYBZCcavYCx/p+9/mmBXwlx7fyKE/cjkAVwtGZERkxX7IMIzJEdR613TfEb9PVhQEy8rs8bsA9wwvebCMzbVk3N3UBoZFsFC3ESEUrUqV6NlETE2QnWI2nUWuV0IDV1Ju27q2oDSfygrbXwbJSSJIk2BcFNq1YC6zUJIlj2DIeZqVcjAYM5MYQUMIdGlAK7SErEJaWwIoACDSgOxoeHhyZ1uj2e63yZZ8pU8uACEDk4CY/DcJgO9akavGpVa05EmZloKAMB67aiIWimAcC3Cm9rkZKQi5QllA59zOrksV/3yx4UbYCYUmQ3BfZuDKbYXHZjqn0hc1/xO1dOncJficpAWSg1aPUmwr31CL+xZu5IiU3Ndv1wvF2PXgaLiINY2LyT0uOmOEGY+3+H2R5UyIlJyF2D89kHAEAWTpLgVLdmpk4Izw6P4WOvp1NrpqrMydy3bYPj4f5+21Z3U9XaNnfknEsppWQWyCoObLUWydZzplFyvjmdTtMRTclR0pBTarVuW23k0zicDgdVtaaJMQ4l5SRlKOMAJhZJKZPVpw8PWXgYyjQMgwhU27qw3Rynydt2c5revLn76V/87Jd//YvXr+9ubm6W5TzPF3aHHX7vb33zcLls1ZxF4fPy1NDU/XR3MxzBD0+bQnIxEpKcUkkpscg8z8u6jDIiYVtqW51ImES3liWzkROYrE9++0n5HJPhTG4WlJimSjAmyiVxomZtPLBk/tUvf/36yzdff/3F4/bw/ffvL0+XNLjBztvjmIfT7enT/DqNPJ+3ttqQOHESkfOluunt7Zhywk2Wm3y5nB8/POUickqm3qoxe0qIhZQypwJ1yk4gkSTmVmtrq0mBsAizGoiQy2BKy7Kui7ljGMrNYSRKrbVWrTUN7jEn2nRpDSNRKnI8HZ0U8DKCCMVx82q6vTuYybK2rW2SWITdmupq4trIvRElRxPxVGJmTmadn3y+LCKaBzf3da2jDG8/PW1P0/ZwQWl+mU0Gyamum3qjsLF0N4O5QQDEeCxcPrg3hkKUROCmSbX1nTQ2ZXY17fyKsEulIIKHKpoMbqrwThdgYWFQplpbKtKaezMU5DEDKY1Scga7rjUTG9qyrp9+cfP1N1/8wY9//5NP3pzvP2bO/80/+u/OH40Nblh1gyIxq9V+RNCeF/jDQWFvB/d9P2Yh11AyepYPC8hM+7mzD0z6sRreGt6LJsQkCrsUo4//AjWnLhoM5zDTTl0J6x8G1KzLeBKcMgkTSdv8sm6Habg7HRz+8ePjdln+k//8P/tX//iP/80/+de/+uwtSfqrX/z868/fcuJpHN3r+fxg0HEaksPh0/E4jCNEWa2ZH8djc0uDgGFN62U769Ox3H312ZdfffblmKdXr1+vdVPVkgvnYwbx6pvNzfR0czydTsfjiZk3q83aqhsnFmFt7Xx+FMKXX37GJf3v33334eHJFLc3YxkOmdPvfPn13e1Y1+X7j9/OyzodJlBez22el3bZtkWpZWteN7A7GlxVm6I5DNAUCEUwRMhiAyCJHoTg5FEDRmVGnXECB2QvV9iJEZkDCr4WaNHFdIMO3/MFoo5ShzBS5pSSESmsqSrc3NSVmA1gTrkUSk7s1aoHOEJwsyTiTCR0OxxSGjfWmevWGilDISZCaciFwdaqmmIfP0NR8nCcDtPxmIc8LzOBLtulbo0yh2c1HNcZKREIHP2bqsVi9u55FbWz47kFCVOXXg0iaDGC8B3ftNYKMLiwG7mpFJlux5T58jhvurE7CSGFbx04UcpMiZa6SRZOgkt1NmIJZ9GUhMbsqtgFftd5dQyEQ/DWHcE6F2cHlXbIpwNi3ZYKzExCwUgxU2N07tV11J06Ccu6nI7smYB35V/ai6f/+RXrwqgTRdBH11EJGPnOJec+0CLa39L6HK4HTfXJ8V6oXreel4ZOQQSjcKyQ8ATlJKYaWLbDKdx7cHWZ2kf0ez/pnQdLBNrtUjubhzoaBopAoOfI947Uxt9fYEt9k+vYFT2X2Tt4dr1mV6LG3nbELd0tqGLslESIeTXrRir7B/AwO+tkk+vFoWsqvV+dQDSclpmZzd29UU9robgmdP1MREFS6CgaQRH++H3fDVjHryG4cYtoFz5h/4UAMIJ+VVurawOhlHI8nebLuQXC415bpV3N1E3czQJ4lSKmhgptFTTlXOCmWteQqdXKwtU23pJZYhZid4J5C0G07tXy1bUuOtTQyhpAJpE2SwIRIeFSyjhMHz9+nC9n2ypxciFipCw3t4dxSPf33/3hj398d3f785/86q9+/ouh5Wk4aPNlXk1RxtxsAdtOY9SdBGL94vae/0V/+eLFEmJhmAICGB2nU63z+em8LQ0N6N0ygE68jFWj1+ReBFrnAMR/y1MZy6wv1L5w2TYN9WoXeuyrdvfz3e8xO4yd9/KSgAA+QWRsxGBiFyZx6l3em89P02k8Lw1kYIckCA4ThkNKWcY0DGMmr084X7Q7YQkxAcLctrYsG7bKpQxlNMa2WosySSs49VUWj2svg3Z7OO/4oDnMm0VvysEUq21zTO3t52+PdwMlX9W3hten4dMv38x1mdf7w/E0HrIlruf1/r5iReKU3bUpcv9woE8AACAASURBVGSCxJDM2FlNvRmAIMmTY+czgyKmKHqxK83tJQwBYpFOIwqaIO3uWXT9GyhYee5wC7rAHtQRa6qzL72j4C4mMYcxdzNNlPb80edl8qzM6edHePL3ZPC4sNef4TudLV5Ce45G1LhBH4lZQjTLBhi6DVqgu/0sCjrtHugbqfdqIJOwgnWYqZrxb3ErcjPbN+5ON4srFH0l9g3XX+ih9919Nzpw320NgeZwcCIRCUjEzEDSxwf733fkrr/Ija92C7vzUr8suykshXWhgsiut7sPcfDySvbv7nKD/vt6vDNiVHb94hdX4uUZsb9R/zzA1SXbr98el6czSK6Y4P+dufk/s68U9OGrF+ZziUHs6Gnk8JANUofhES6sre95Is5sbnCLWLm+prxDpCQ9Rg+pm2cxsa61730MziSZIQAzJQbDDebV3YIizQDbbsFu6KpvtiilCWEF7yxCBG0NDjCISQElR4IHO7K5dQmjO54Fom7u1dHdo6IBQnRHgBGzJE65LOcVjcGOARAggRxr00H1k+NxflidIJwNEaeI8IuCCjYe2lhr80rJUyl5yhOKWbHQUny4vxflpp3VJCmdxuNhOFJmd+Lt0QyuLnAR2VRDdXTFpbpVKjk5CSUj7QU4McIDx9UiFm2H9c1sfzKFnBgMpxhTwZwZ4qzVAhlzNzUnEDNLTptWM4V0uRAh+hvDHkW9/xDsIPMzuNtxfg8fjWDCh6VeX4Pu0d5kZmqqtTV3S6lISizJQUIInz9VW5albjpOmdgAK8O4bZWIcs6tKRzMNAxD5GuERw4AM+NMKQlSkhSvLCKn46ltVauZKoBat8UquWYhYR8GTFM+3RycUIY8nQ4swpyIyS0VuzlN03GaDsNQODOkbfX8+DiNw83x9u72NE2TO+blPM7jMB5qs1qruZZSSMhM52VuTs5yvjxyjZiszCkxb1CtyuqO2irbvn9CtSFhWZb1qaVWfE1tq+z7lIS6wWJHAM3CJzOszQA3U2IBfNPN3Idccsd8nRIzy3fffnd8dbr74laqf//d+/cP59MNpolKSU/L/eFYjq8nzrfnh6VetuXSns5nN2wVOODmszydRs1UyedtwQgkrarzI774YhrGkpLUdZvbsqxbq9gcTCyJc84pCcHWhUScmVpr8zJXgaR8Or599+5+WWYmlCTrqtrOl/MadssioglJSIrK4OPBndbL8lDrttX1009un54u69oc21qfmIqjAj5OAxMv81OtmyGyv6uBzF2KHo5xXpiqMrEItrURWy4gYNusTBjHlFwOd2m72PJha4pS0vw4s7MbiSRyd1K47RL9EAzGQRbWLZQIGl6AvgdFuWOImkyEBdpF+zFlcuYkcbeja+jLe4+hIQenUswbzKbpMIzDWrWUcRhKa6sopBRmIzQS+/Krz3ISb67VLo/nX/78fBh5HLOr1c04MRNZs30mxtHG2A+rmevr+aglEhIPT+JO5n2ORutfvCNX7tbdbTuHCl2Bc+VH4HkkiX1xdxEhjLQ30jtYCIAli6p2Yx4iYk45taYi+XCYam2X+akt/D/97KOz//gP/+gPvvnb/8Lv/93/7ad/+u277z+5OwG5DHK8O5GTkQbZfzxOIHExAGutp7vbbdtYQEze6sNSm2+c/NXpeJiOwgLw/eUM8nHKm6emnFKCF0np5uY4jCMY1Vuz1uDNbG2Vtm1ttTY1psNhGs/ldMg3J9CGNPo0pSFN0yBw+/j+47fff8sDT9O0NqubuokbaTVUd4NIiJ6gThBxZPdILthvlRsUFAYoTmTOjXzXbBq5h5eydwGU73fdicycmYnDSYOjkAoJgqoRufOu5KA+yQiBhQd5rnkUqaZNa6XIKICN4yRDrrq0rak5BMxY5jaWQTgNudyebhOPq7ZTpnWtHqTdKY9lrOtqZi2lblswICfmmgRs6lpbq+oKTpRTrrWyQ0hCRk8gkLA7kbCzEztX74lIDCISJxBsn+5fqcgdNtgzFVJYGtOzzxDBCQgYKBMJeOCkQhVweDKIIwEMygSBolHi8TiY63peetMIpJzi2Segqe6GXR0uMe/uYe6dUwpHeoZHepPTS9ooGxgUny2SrSgcul401vQMkHUEBJ171X/xF9Xx9c/3745v9mvh/PxHhN7O7JV/7xEQXGyIhOCNYq4B3klK3DPiAymND2OtgwMWiArFWC2c+cIfqpuZdHoW74IpQFXB+8MQ23NPVXYSIumeLn2z6sRSmLuawz1SBq+t/t7x9ET22M7th7tkhzJ+C3Dhe4fFe7F9vZy4Vi8gCIv/sHUhJuz2vtdyi54Brr1j2S+y47oJ/0CN8oMuiShALhACyYpLSs6dIBGMxR0+pYiIJQJb+EWQgMIyjHye1zFlyoQKGJZt2bQaeaBi1ZuqJctJotWL6ThzEhRSNDCQMR7GaZqMXNXgbtqgWJZVMhN8qTWTvDgiCESwPkHBbgrD1l0ryJhMCEoOM7JmJgZQHkoZ0uGYt/vZvEHUOTJLTfIwHoYsGMbhiy+/WOf2+OFsF2xQk5YkT4djXXXbKogAQ5DqOoRk6JFx++3wTop4+VKygZN39A4uOJ/nu7enkvh+vV/mLZzb9wW59+Q9DjYcoWjHtgN+whVfx3V/6KjFM+QZjpLu7D3PgoBn/37rQAaCneqI3EP33claOLKOwm+XOGUoaTWDIuF3fu+bu9c324d756a60jhUa6dxSkXM9XgYpsNAKFa3dZ7d1LTWc21nkFp2FyRKkiUdhmJGqme4MFFD84h23NHXjlAHPt9zQro0z5rDGwlJygDUtLaKA77+3c++/FufqCxbAwbcvh0Od3l7mDdrPKAYr7o1NySMOY8yUU22UMop2W7o4B1lsB6FHHseCBz08KA4oW89v61m2of91NH6/hA+Y9kvHlPvHudXBKqDT+H61usrMzcw74ZaAOBGEfO3f4J4crvVA/qc0QnCHRu/7gr9wA9S1jN0GmAdLKiEtvstAtht8QLc7GYE+2rbt1MIOAkxLLoVGAxmV2AoWF4R6vZcLvZdrRclMVW4Hks/eHVjKrffvOQ7avM8uQgAFICTm5pwelGjYh/PXV3/0PuovZT9bShx/yX6P2kfwfzWr7q+j18twIA4nqiHsL08Rq5H7PXbrz+ql8xEInFnnqv06y90vQgvRy//JK9/pqCuxKmDgT3DPWUA27Y2bQANYzH3ujZXC4yCCOpN0UiJc7L49Z0Y7G6ZZMg54gU7oZvRtCnU2Tp6FQx0Mw6zBZE8pDTmsPZzciW1pugaAwKQiJiSesCqXm0jAOIOJBFyIuKAjYhFPFlVYjHVuV6SFB5zAJtm6roPQLDTGwVhE43N13lFdRUbxsMwlFQEg3LhnPIg+elxHqSMNyMGrlaVK5GlRKfbExKP0+Fw90qhT5czQRKnVttlvszLh4f2Ht8CrQsZMAAH5KG8urs73R5vXh3fvnnTWqvbdnO6s0r1qQpl3Ui3rfr25ubNZX5qbCOPUhIv61Jn0h5A0mW+aOCg8TMEJCn6CGay/WRD515BLaZPTiQMhnN9am1rWwUAZGAAMtOQkVlSCsZ4kiyUoNKa9iUfOm5A1Zq2mHo4mak64WpO2Och5KqRUkSSUhR4atasdV5G1/92qHRdrYb9mcCs2mXjxEaWGK1C/P5wGIaSNjVpRmTujci2elYngLatzvPcqk3jNB2nWjc1z7kc/g/m3qXXtiQ5D/siIjPX2o9z7qMet7qrmt0kRIpNSBYnlmFYgg3ZEz8AjfyTPPMvMTywIXlgwCPDMAwBkgGJFGlLFPtV3VVd99a957H3XiszI8KDyLXPqWaDgA0Y0kajcepiP9fKjIz44ovv2+8OhwOZG9FU0rzLkrhbPZ16X+tyOtd1vb19+dmbzw63t998+GbR8/fffPLF97/3+ZtPv7378M3bd62tk9yK9cTIInkuWYrsiR2JpTAmoURpTuUwz0RUptk614v/zg9/9/MffgH423dv3377zde/+tXbb9+vrX/xOz9Ylsvj42N3y7t94OMkE7ibcyrH/czd6fHxcW1ra83MhGk359vj4Tjdnu5/vivzNO/uTyfqKvPOFoOaaU8A3EiD7+OqEXuUnIyRd0WYmQAVcitzoUQK51RW61kVHV//6ut8K59875O8B0lTq81X8+64nP3Ovad9vp3ndpa51k/kUOYE9tvbQ9mV+4f7D6f7u3f35wWfflqmuVhTvPK2VlWkPN/eHm5vDpdluah2UMgSqvq6Xk4PCzGmKVP0w82btfN5cSuP9219RNlx6/Rw9+26Yjenuez2x73Dl0t1bUhrnvqLFxO4nc6X3hsRHW+P05zWRddFL5f7nPdm6tApTzmTduoK9no8HiQXIc+Z94fdi5c7Yc2ykmcgiRjAdbXzCXdS225lLWu9zLvdj37/zeOhfmm/Pt+tJUtfcsas1dgFboKuZN6VSgwYCTErPCZ7SakHHaKP4gIsYM/TzqEppZyzSureiDnkgTgxgw2u0LzLkoXUralqjxmm4+HG3dXOudDh9uiA9tq9k6lD54NkcVO93d+UYv/Rf/Af3r97t56WL3/y1f/0j/83KVATbdq7bbm2bSQIH443hN+UkRwbfmv685PzlRC7RVplwXy8mjlsT3F3c9m0jwG4K2koLg5b5nCXo6GhES0+R3PAHEkAjWbbKKshoUYKuDdbWxMiEubufF5WI2i3tfbOdPx4+md/+ZN/9d/+N//kP/nP/uv/6j//9373x+/ff9naBVU/nC/IOh92U84EfrxcdvO+qxq4lL0lmXjX9o3cJxIcXumr6gpQLrkkKg5L4MM8nduiup6W0935/apnmTi7v379kcM/nO6/eff2w/39eT2d6yopzccdl5TmaWZf6uV7bz76/T/40d+b/t67h8dv706tYSrTn/yzf3FzPK7nU1ubiHx4/3h/Xy8XFN4z5fP5DkuHgjoIoAYzR+8AwQU62qpkgNuY+CcDyNy0GRweDCQ40cYTJBbybk6BaqkpwRNThpQQiorWyMiPmGWep5xTcDe6NQ3tbWZKwiKcUm9dlws0bqVCtLnKi4Nk7iGXmThEsfaHXeLiq1v1+7cPl4d3l8czFFCgAQmyL3nKH330+vbV7bzLSnW1dX/czdP8q//rq3Wt58sFGQDylG9vb3fT3juExWtj1h76CYSRZ8CZCCJuTBvKE8jHEPYelQWNEVYiGjrCICMRZoiaylRK1trUu2GiMk088aldzDTtZc97IldTZZUkEOQiKrrWJUlx9jKnclvIKOdMhpyTq/a1tnW1PphEgNPgg6mF50qPyOLDni8a1L71fhAQOlhCJg2IwQgY3PNcwg1iwFiBcZptSMhweAzVXLq2x90dsBBe94FYUXCCMFQDjGgM9hAHOqHuztdiaksqHMSMeFZk4uTEm+PDllQ4woQRTuCZ6ZqTg5iZHb1bMwuXh2ASkhDgcBrybAxyTGHzMeSWIMKbA1hohbKZoVvwWNxcgRiuGyVX6CvhivGBWXiD/Jxgzt6frKOAGK5xFMZvPCgmTxEsgIHCPCtczEy19+bTlG0TijY32qAz3+7Idi2f0Ctg0LuQGO7W24BSOMQmhqzbc9AssI+rbrQBKbEPwibcVVVxpe9s8CKBIPAESsSZIHBSZ4CdMicm6aTwpa/nenZ2HEFZmIV568GC3ITEnIzc1FxEXMBZeMosAbRorSvUIXC3jz79iHr68me/ZhdTDen5xMKcVUPK1f1ac4KgoDH8Rg5RNSnk7nWpKMh7ypn2+3z+8MGkIgHcwUhFjNrD4/1xP3/25ove7N/8xU+++sVXqDCwkldUBqk5eucpJLYIg4U0BskwpHTii/hYOfS0tt2dJZmZcIewcv/1179+8fJmNx9q7bVGq1iIi4e6sLANLTwYICVvDMkNqfBhLxALI7YtbT51thFLSDURX+WkIhENGWQMicmIbm5klAFiJ93mxFGXlS2bGRqHw2yWIjMjkWX8zt/4PB2wvD2ZLDTp/mZ67JfjzYvdfjY6mbWmPiUcj6XwzedvPqF2+LDvaGBDX9Wra9M6WWKCU++tdoMRunHJCJpw/ORottPgZMRdVzgn4uDRM4yGNMH+C76Q7V/n/Ut5//j2D378Ih/K/fnD23enajrNk/oJ4i6GZGWP5NDW0T3zlGJOrUe3DRRdjRB1IsSU8egjb8btcCfSLWZvOCuGcpgiJKGgEZyfNRG+Ez1iCV/xku1u0W9goTTE2WMNMsGMPBxInuBxIxYmCRLC0GLDk4oD4crJdCIZ4ZXEXYh0uAZF5PeRj8X7MhNzoiHaZ9qGX8qGkw4G1qAeE4VnD5GB0FWhKszMXEoKDW5mu2JYW3ALoaCAlIZB2fbFBzprg73/9LLnnRgS2S5U7AO01rFJ18fztwx3i6jhPKi2oflP3KtojsQLmyqP4SUCB/d42K4MEoc9/zrPbho9AVM0pOjHAf3dp/2VZbH97msvKcyszay1dl0pz56J62kef/Tef/ub/jv8SNa3+zP8l53jKHEOug3Bza0tpn2A9aFWGvTCgV0yxXoF0Lw74gCBkxHIyC10M9hA7kIMzyVFaCGBixsZKCxPvEdXhSAiw+GIaNjPE5FIXVZhHk21UZPDNLphJDmBObaUmzXtTAxmuJPI2Dk+iAsjmWKO4LcuFQLLzmtDJkqq3bpXba1x2+0P1KFm7CTGkJwSylRc6P7xBOHMrM2mtJ+maZ6m1rp0eThZvVQocxAr3NBYztKr+eTpRSppAoMEeS67ab+0evf4AF0yJ5lEJkFDksJk1s1qdWhOKVKmsJWLXaFqUOdCzAKwRIWpNmpkB2grGiPeG7EQgtpmoE5eHTEYIgzmviqcFO4EcXcnZiZILtnJm7Vhc4Thm0Q8rG0M6nCKmXje1GY33QwePXk3NzXzMbzt10TLDc161w0Bi0wRlDhzjkC8mqJ3JRJy1LUSwdGXuty8/BjuoT/hTqpWa1sul9pqUGXd3VSh5ma55KlMSUR7b10TpVRyN22trr2WUna76SXdtNYv68WtF8GUZJ4OL18cb25vWFiSlGnKWexiVldThTeWvBMRosvjSdVfvXqdc5rmw2cff3H3+P793dtc5jefff7y1aub4/7zL77/s5//zICUhSjtdmV/3Hekh/u61l7VHs4XzgXMTs5C1N2tkaTdbnp5e2trKinBc3JBc+/wNHACd8eQ6fUIz9uhThAm3jjWDiIj8maNTIzJWQTUVVH4cjkvp0vJH90eDqf1/tKrU2excihrr+1smUvmYmKe9Kzr+WxS0E5nWr1rRZZpTu4950jJbbc/LOe7WhVo4pJSYk7iALOIaFfVqhbCmrisbV7O++PucNi1Sq32WlVVKeSn4UmSi6l3tbVrqEmuTn0qPh9SKmymDp9201TmdW2pFOLsaOvSW1+6u2rA0NM8Z2CdpiTJksCs19oLlZxSb31XRJDNhMjneW79cV1hIHUy+GlZmS7H29vyycHXj//0T37GunJiKGs3poy4/FZRSEJmgtgp7IE41n+kllsjJ/rYI8V0cyIWcVgyGLlnyZwS3Gtv2jWLhOB2dGGYOaVsZupGSQS81LX1pl2JUM867fhwmJnUWj3eTD/8/PNSknC6nOr7t3dUi1Bzpd4cHZQTJ3aNWG9bhRqiO7+ltSWynYvbv7hjyH2MXiU9cXIwkjF3uNMAuZ5YGQ7BmFZ8KsWIbeNtXTtLAKfN5NjhBhYw2FmiCoyUNsB8InKl5VJBYClg7yUXpm/vzv/8z/7Vxy9vvv8PX827XTlMOfn5/eWbd+/2ff/R69f3D48/+/nPXr36eGltv7/59OPvOdFa77y7OCHnXZrmdKBEQXBSX1rrVHZZqICUmcl7b7VXYVa15p3A3fR0Od893C+6NtW2nHF5KLvpeHNs2s/Lcjnfg+sxfyLeez2fH5dHxeuXN9M0AceGtnh7e39/fw/vKHNmKkLZXAcD4dqeo1He99pHGjxqOB13AWPWIm7vEF6gDbIhENitjQQ8+jHuRLL18j0QnFD8UVVVZWYRIgIzG1sLIp9yHmqbzszKtOWIkGi5wh2WUipTJsdDfTweXtRTjcz7cr5cPlywAiQwRzdyKT0z8enuVEpON8KZxYUKIUXfxhFrmMFTVGMWSYSHGieLcHI2iwEQQJg5kSlo02rENbV1jmH9kUwQsKmBgSGhAxxl4cCaYWqciDM7e+1na8q7HSaUMqWcKBHgCgW7unZLTet5OSVK075YQ8k5UbKudVnXutKYhMAQiAsi0OB0wEczfAspEGx9d0Pc46AqUKDS0YcHuxFYiEgIoTMy9IjD3yua3KPVzUPeGcHA2q7LuEpxqcbujLJofAOCuyucrh7hQUvF1RSeAQ6Jga0oC1JJCPmEw1h0w8fzyOHMgijRjUQYGJJVNjDJbWiFeDj8jbhB7hbvHK55Si5swgHPE1wdG3vODeqDpx+/8grx0Vbh/JXigp5VDnStrX5rG/uJyEYsI1/ZriAiaxvUKQqt9vGIUuo5hvXsLa917oD2B2Fu7O2tb0/Xanm7MMwULP4twg4Y0tXA4xsE3UeYgopGwXfa+H2DhBUMe5Qb4UzNVNmRkIqYeEXNx9lgdmrI4s3ZmUAKVVPrHQos8Bfk5Kp2voSgGiM0aDIAPF5O0+2rkot2BTVz82YwUyZOKTG7SwS1cducY2IaJG5MwdxzCjwODpARd0fj1JA6BGAHQwohkaTy5rPP/uD3fv8v/uynX3359cPpEYZp2peUHk4nXVfKuez3TWu4RFKcmOPEG1aDGPvmOWD4hOQ6kRERJRAgfPf+IVZdqx0WyK6IiMIggUtAr6odTDAf7km+KYdEMTw+JvxgUgApdgX2Aiy2MC52JoCfyfEDgEsYQnDowA1wYPDaXEAxNAgHJ7CTG3dLCuDm9XRpdx8e3170wQW5OFT3u3ma01L1eDx0XbRbzjS/2B93E9J03O9RoQZSy8hDCfeyRMAVJnVDImJ3pdH3dYQeEflw7Bv8GweLQMA2UoyAcKraq09yecHIdmnnlx+9fKyn7tq75znneQJQZmFKbiBTqmiX1TonKW4GJVcP5UoHQLZ5/AUhlNwdGrYlvs3OEQ+d9qc7PtaAjz0eDDcbIMzzZ1x5N3QlaNLV3WLkRuzuQ6jwGpWZhoQxPb2pXwNLIPYWbxUhkrExPLExlFQ1TEJoZFOjHzlQE3v2ZSMBfPb/TTCg4w0jj4YQGOAAnjZwIGSkEN+Dr5Z/UbJ/B4N5CuKjwrzGwC0Tdh4U0ae2x3Ou0fV9Y15hGEe6jRrVKFbKmJygYKBt0Nu14YKnDsEVym/96WBEHLDxLHui1I2A8J13uZ4eo3WB4erhT6DiuDTXn/4EYwKQJ6LW9vXo+dfD9WJGev78pHj+91//8O/chX+bj3T9y83VNaxtQ3lBEmt4syee9pniP7DZnMTQPTaeFQ0zaOtq6H0UxoBvLOKAMIbqrk+5mGmIoRm1bkpGEPaYTQ/fVzK4UnSBnQkiAcukMXuDsX9CNIvMm4hwEmHpTamId6Cp0diazJIkbSnAWBXOJsQu1M0itc45aeu+OmWodw3GgdfDq+N6WZdzba150t3xOM2ZyE+X5XJZDjfHh/ePvSs5ryX77S2BaWWqQk3o7AkZlJzcu2o1J11zXY5rmk8PDw+c6eZ4Y/D10ta1UkdHl4WkcOE0H2YQHu8fz+clQeZp8tDogtPQEovt5xwCNdEDFOp9eerEhH4ZM5isqTuRjakKbzQmnMKJSNk7wQwJ0ZaFIbmbIzFyzgbrtcVcTjzUNQ2joI3ayluCt2koQDhFzIKrajMFWTRJononcgJyKu4mDEoCgnaNckhYcpaU2bxy4qYKFuHcbc2ZRLIvi5vF7AuziLAId+3ny0W15ywAVHVdVm3NVC0ldkJTcdRlKd9Lr19/NM3z/d3d22/fvnj5IuV04H1rTbUK/PXtzXG3M7fj7XF/OLTeaq/eltZ8EjQYuyVKhWnOiTm7Q8lTLm7062++/cnPf3V/emh6yYVubo7zYdfb+tU37+b9IUNd6PFyOS/nt+++NSqaJyRqbX374VtikSwp5SScJKyPmttC2D88nETImvXWKYEmDlrF5hrDLFcN8S3ZYCFhTqK9DZ6KgAgdjUDmHENSD5eHlKULPd7fXy4XmUgk3Mbd3JfW62ram+CSZZpSFhEwuTuyPNY7Xelw3Anoo4+OzHld2vm8aMflUnsVBeq5nV2ZCOKW3LLnnBBzkW7EUEVQAo+HQ0pyeri/f3hMeXe82bXazBXQ/bHQEWut5GHYxbt92s83016Qe2u91tXNU0+12W4+LEu/nNfLubXmcO5uwmBGmTjLPE9eJs4ZIqSG3jwLMVlt63rJc5msGzl2u7lbvyyLdriz5OyMZqvTeni1n+STP/3zn/UV01RoTYBB2SJWchi0u5OZMpggQqRMwszOWzOH7JqqMFE3mEG7u2vt1QHJkkgS59FG73quZz6TJDFVN59KyUJKmlIq09R6e1weu7Y87R3elmXaz/M+uWrz9vLV7T/4+//x3YcPQvn0bf3zP/1LU/dOzMJiZj2UMZ00Ss/wXIvw+1sTrGtL51pUu3t/RqEnoa3TvxWAG4J1BZn9mnxdy/LNfhmAqT0hZ+HSTpDh8TZENjjskHRrtgSrweDdeE6SpPUeR0LX7jk3s2k3/fTtl//of7n/7NWrv/vHf+vzN687Wprn4+tXeZdP1t493v3i11891HZ3/3Bz+1KFiNJxdxT33s1796yeJubBUrGuvbVeSG11q5JkyimntHRal7XVx/ub+/3uwMQOv9TLuVdz7bDT6SJnMdKcS87Jp+TWTg/v12XJrFOh9dJ2+0zuSWQ373qFGaBoFSs0w2Cjd07bLCZt1bEQdzU4DQGNqzrllleFqXQcm9hwyBiHC33gMcNlDoZIFmFFc8eWAgLkkoQIvXczFWFOiRIZ1MhCuy0IlxHqTWAMYRaWMmV31aa9K4GmVW5GjwAAIABJREFUNLm7NRzm4/rhW69OSno2VJAiNwahNfeqi52cgAdwwSHv17ZefGlLPS8X4eTch+yAQlet5wWEVhtSbq3BQgFDjIBxsjIYLLLVC2bjj1iCPjaAD6ZSoADDJC7aMoimuhNYcpLiEFbtat1M1TpVqFqeU9kXENa6rHU1mJm2tckka12RSYTbsjQznklV17pq77lkN/SqWkOlmHwIcisGvhCGWwH5DGg7dK+AGEh0DJJFkOuYhIzjif60w0kxxvEAbD8rNuzobQcaBmy2kz7KycAY4lns45/dCa7Rvxqv3gp3B2DkHL114S2+DAY3iK5jKQRxj+EsApxFSKLqMDg4JQpJYANGBzuABIzZHriHrkBwY+Lz40oxjH0TfDNiiSADJkgMK0eb7hnaQxvqxMEU/U0I6VqqPNU035nbe4qf5s4bQhf/UwvRHqIQXXcn5977NmU9yqPrR8cVHQXRsws88sArjSHuDLbBiuuM5JXIQTbkk2MSlgCYdkVk29HHjrAaFV1shFh35LFKGEYBIBC6GoUVcgJnuLiiy04OL4+P9d7dfQIreq8MFpEkbGFEDu3a5sOu7CcIGXvtVbVTczhY0K1Nh8lfxEQSiWfn3uoYnd6uQ3AnYnkyUeIQAoMoiMhMu4XPoIDZ1NelPx5ezNNJzn1MpEMMYrcvjp9/8f03bz77H//7f/T4jVmnnGcyaRdFc8kTZ/Gq4LGEsM3z+Rjt2a6wP18dhucrgkjN1Z3UAdjZYOhVW1UogKjqmZlsdG184LPMNvbetoLcHeyhJULkNkCzoREdrNON90HabYS1CMgDKsR36lvyUCob4HdMIRMicxk61k7szopiaUZnvHpzTEekqacCSyg7UMf+mI83E18Sk66Xk2m72U/7+ViyE+jmsEMHFDCTnAA4dF27qaeSWNjMMZHWjm30F6NcZ3hnZubk5kqmatoNIiJCqg6TzJq07PG9H34qO7o73d2d71988uInX/3UkxxfHCRJrU1Vc57UXN0kUUkzN308r+fLycyhIHXrQ/wAEtKgANwtqK/Bcd4AzBFo/Gmg+imBuoIjxDEITTE4t5Hcx14Os6uxz2nb/tuqifGmwKDMzDnk/DZ4BNGZeYpHcHKDum+xcbwR+PkSCtBT3c2Vx4wuAFfz4P4+RzQ2DH/IMAEOs+ve29AzirnCIKxdPS4VDg+rn80y8onkexVqitXOz37Gb4FUNuiIr1d9g3Ke8lIbYKaBI1Bse0E4LAfj2I/Eh3nEN/fnnzgazs+gIiJicSYac6PuHi5Lw8p57KXND9IHhrhNe8eb23DxGE8eJfz1Gj9d7Kf5ZDhEkntXdbPQxfXrBdy+9vXy+LMr+u8QJvX/6pHylLEtiE3lDGBISgbtS3NACicRLsLEvbfaWijVDZ28aOaJSBEBqq3MzKzaEcQiIriE6zWzhAWzeHMHPDofGHwtIeYkEO6uCMHS+E4U4VKHgKiMjomROceWJBYyc90mkEkiTwnPXAM0rDoTj+A9ltoQ83MYwh6Lwd6du5MRKZxJN1XE1rS1trbFu4HQeqUON19rBXhZ1uW04tyjd73cL7t5zyDu5BelxiCwCAkp2HR1x/n+3KXdPyTKtPR6Q9StA46uJe1Qbb1c0MCH3bQvkiUU5tKUCmZT7atab5FrXkd5TA2qEOaUEsuqPaBEScTCIf08esbEUA9RbVROGrPcUHVm5ZS35nYYSrg6ZXYiJjZJkj1V6x661BxdHSMe7fba+hC5jdl4dmIi4cFzJQdT5mQwpT4q3gF4eSlFRLT3GKg3N6sGhYmhhPmfJ0lTmVQVQqVMKQHknFJrDc45swiXkm1j7pdSchne5q23tq691kbkTbWsULs8nj756OPa1vu7x1999avdfuYk63oG2ryb6rJ89uaT2qpq771PcylCrh5ikLUuwjmVyUgzpeNu/+JwcOPePB2mnPMvf/32l19/9bNffvnV2y/zjB/+zu9+/3ufEexyeTRrb773RrLkaebWHh4f7u7fp91NylxVzVvKOF2Uux72LmXKKSXpTDxnuLXzw32SbJnrpZMQGfKca4e5ihAY3TTJGBEnYgqvADYnIBGHRjo73MitezNPkku3bq4wEPyynL/8xZe//0e/s2jUnObwpdqyQCuywEs0tNbW2/4w55wz315OD7ToXFBYjoebJLou1LWezu3uQwVC4hEgcAIVlBsRETcnwjRNruvSrBRMs8xzKtNkvT6c7m9vd4+PF0ddL3hc6h/83uvWa29yPp3d+v4wHQ7zNJWU09rq5VzXSzWDSAOQ+NCqnh7X+/tmipwRPg+91d6IyYkt51RK+Jx4SRQiKknS+aFpqYCDpv2hvL9/T4SlVkl8vtTP3nxSl1qtHifjicoOE7GfXXslJlV1ixSfWCn0Y03hbKPdBbMe+u4RtAQeSY4Jh6IEal1NrVsPbWHrqty09r426+rmqqaV45o2h3W9eXm7O+wkp8fHB3tQyUVrS0WIU+1rmXg518Nx98UXn928OBYqv/rJr3/yF7/66ZePxak7s7oTQcTgIaW5tYuQsrh7DAR/t7kF4Kqv9yyvcrjaKHKB5/rFTydr4N5p6275lhqoG5RCcCsUlDCyuw2WHwo+2mO2gkkc8KiwzDBMaTnUTA2ANe0Eg3OYZgGndSVtn378sqj+65+9/e/+8f/w4f7tf/kP/tPbl7v7dXn58pP7evft2/dfv33XQd8+3nXX84dvzrpkyX/nb/8xOyVJuuplOSvVlLiUqZRC7MzW2qJaHUrkOXPJiRbvtfXa3Ae+E4Sf5XzhnJp1Fno8P77ot2Wi4/HQuBN5awu8i3jJIJflVM1ItbbatSGn3f5g7FaX1p1UwRB3N6NIo0dd4m6wORV3D5V7e5riwnYvr3fnOzqy8ffYFeRIJJKEmYhEpPU4awbEELfVNskXcnMjgzHzUGkF3MMokgHf73ajq+S+LOtuOujaQWhLAwiGem5kbM3WpbbHDgcaMsJ3Sbu5hHOFyOO3D9OrrE3NbS02M7fWo9B2ByXqZo8Pp91ufzgel/OFIhMYTRdCjEpErTlkpQLKiU6KE5hZgtPQY3ePLCUKiq1MgR2ON/fLo7e62827/U7NLutS6xJJQrUK+KVe/NGk5PCxsTDXTiglr+tq2gHuvbtrSsnc1TWVzJL6Uh2eMjsCpqEhZwwV5GjPDWTCwgCZJDGIuyrISIZEVGTJPFBF8i3tAq4EDr8ydAZmdy2ermBXrBl+ajqPGmvARTYquA1CcAwO19OCGYsPRqF/7wNhGPAchnrXEKfwEXWIiYySpJIAeAcRpZzgnrp0U0lJeydnEvJwzhgIT/TMBvpCwiyAhFmkgVQSwbj1Ho6aLGTK4Ah6zDT6YVuMA6JKjeJtI665Xvnv26ba+CqqFoZ/zKAoZxhQWMwYPVVZisHHiczJ3d2aXXGrjTcx+h9ElCTFdwu66xWZJoIzY3MhHMXSGNkeTprB+whhH97QxGvxaRqDT0PiOTxIhuvXgG2j9xD5HlgYbMxw8drM0GiilMmB1movZd7tAazn3I8VzSwjZyEjh1MiSeKEbh1ONze3Lz9+5ezn5fTh8a6ti1cjhjGq1jRLfpn2b+b1Q2fHbnfYLX65XJhk00i6rtEBsoccKEdfk6ShEdwTpKDMIskv9fT5p592ry53d6c1M8osInj1ye20n+4f7j/8wphFIG5c16ZrhYBzgqP2VbL7FnBpDCCPwv9aRw62ziiAnzZdd+tuSGQEmEnixMIgmBJHl2ZDJ/06WhXHqNI4GjcJ84AvMcrvKHsCB70ClHF5aGAqgx20xTIfkIeDWIjIcIVOY+HH69m6pSQuZN1YmBIc3bmWG6IDPn5z7HndvfSPPsL9CWXuN4abm+mwLw+P9fywrMu5N9zuy2efvvrw/t0Xn3yUE0FQBPWxJeuSpJqnnJe1yswgar2TRkfc6NncG4FA2cEWAl1ELHBVr91ZeUqZicg5+3TLLz99qeTv379Dkm/evl9WJMsi01TKN1//UoS0cKu6rG3mIiQsDriamRq6o5u3UelEbSIShF/yazvHR2Z3XQEU48uxrXzs6Zh4pDFhHNvoyqAbFJwr6LBlYyNsbsAZVIfXaMTrMNgGEOUeMgEeVkLbIRVMjgjWvKGq5lv8eVJPuwLhtGFa16akb2EcA4Y3epbkwYYDzxbqB4cokPpx6gPuzMO5MkCbIfM1EonR29xO12cDhY6RF3pQQn3A81vAxJZnDg4580CItuRzmyWWceqDBw0imFkeNjOuIRTgMLfnM/XbXn6Cn6557oDzNlTzCnptJ9q29/E0yhfA3/jyg77zdI5uN+IpY3sOPUn4ALiauQ7hIGdmkQR4C2LYtniuSNyzr/2bj+edmOd//zVPe/bF/n8HxdI0TYhhO5i6mZlCQS4JzLm7mvecJFackXfzToZEJGLw0Z7l4JI7GJIECOOPMUpNaejnOrmTOZG6ew9Us+tYu+YguA1ye/TNaUvBeGywUMi7Vjzx0YJn9pfYmg6xRhKD2K846MhVnt98EDEFjyssL6KN0B3dSSX46vGCtlZ3kpQ6NYjXtjTvKZV53ieW9bzg6ifvrJdu6ElyMmaX0CuHuzUPf3ewqfbLY78o5o9LEVnXSzcFCGZEiLwGQK1d1iUhOSPPGZ2CFoemTh7K3FAFMdjNOjpYyI0GXy72IoF4m6W1IFGTg0k7NO5nIuukGs4/KeXGPZI838yqzE2tu4MFQjkbulXbClcnhIEwhONuD+WNkPmD8xCCxGBtMlnYVTFzUG+HtREzmzGPAr5Qc3UylphVpZRonqfdfkdEEU7V4Ojmtq6rG435OeZSyjSVlJIIiwwtl8DcVZUcTVplph49PX14vH/37fuHxztnv3u4f//tN6bLbjedz+cf//iPLsvlw917d02CkpmQSHIS0b6ryzJLpoIi+dXN8bjbu1NvkDLTNP/sy59//e7dtx8e7s/QMyi9heTDfqrr2nV9+OlP9vtD2U3uLrnsDjtkWeppbQri/YG7GQipUM4oknZpV3IqJYdfZxIx4RUN7uhD2uYaTs36KOV96H3GoL7BYariGHLcatBm7kyArkuDqSngaCt9+c27L84fn8/n2lZDhaTEJScIrEhhSsulrm0xgERdZNoLcUplzim3pZ/Pra6+XnRd/HxSaIR1kVBCY1OoGwNSCpeSUuJ5J7VeUuL9YWKBezWvDlVbDZVFJYMUZYJak6IHJuFyc9xNU3LXGEhWvdLxSpIEsBu3inoBgDJJmSaepdbz+dRyIbPamgOk3n3MjXfr0A6rgPWUKQcuwZoyzI1kTnniRPcPD8uiyXYzHT76dH/5Wh/vVhDt9i9PDwtjTMfF7kNoiHQHEYQoyJSIdIKDwsQQB+WSVbWp9lZVexxWVQ3qUhnu2hqaUhYPuNkpDqrW2rzOx+MB7tq7uR128+n8aMw0IQocSfjB51+8+d5Hp/Vhmj75xS+++suf/ryvMazDuq0jj3kkIjIPKY2BTtG1OHoGYj0ZoAzRw63FzFsONoL9RrCKeD1itojYlZXuW2o1auPxWg0l5Wu+FAwLgqoxUUgNDG0RXKuC+M6jqQG4WidJY0aJ3cymPFFK5pYn/vrD3T/5F//8Bz/80b//d/92Pr64uB3nj768f/vLr79++erluw/vcynn9XL/zf08z5/dfX3I80055CRmCtXupLCYyjcYuYXdtMOIPGdJKaXOtvUTwqE15yxJyn5mbcmyul3Wy243l1KQs1ntvZs1WAeMGdOcWvWuttbazCVNu9mtar80HcNZY2qSt/bGYOG7ASF2coW0NjGW6NJegYcY/9/mja5pVBQFzEJZttKQRj7LAwYKXduhQgJ8NxUemkpmZqradbQfQZy4997XurddXRRqfVGRDMX7t/dznsz66XRyQ0rkA+p0Ie5hqJfgYm210+nEiZlBCcfDcenvxsACIeA601AaFCxEicjJ1S0E62VAHB5jdMNOMXgF0fu10eonxtYkId56vUMHCCBUbcTOUyJhd8/CllI9AwYI0B2K9bzwa55LJmFylpQzY0JeT2cAaqq9e/dqRueFiXV0vWEU/DiWaGRjUO0iRwpEZLSpAvYJS8bQ8+JoO40TXqLkpRg2CatTC0NAH0WGBcdnSHv4tnW3fbhVyttu3equse5CGW3bi8ROYFW9MrgpZKcJIHIiZWIMTG3US/GTPbpskf7RsGchcahDyKFuwhyBRkN+hjiw6pipgWPQ6NxD+wTeIcQMZ3YyIjIyYmdJJu7alZAoO0BCnjeHNYcr2P+KjtU1tfQt4vu19owZTNo2RFzyocMCj5FsbILQT5hUTIQ9v6BPFeN3SxFsmN6okdyi6tlqn/iYDXOgK+L2hDvHeogP0ZDA2j7w6ebSFpij6BImBnhTdAphtgGrxZChO5AE3VwcTFDz2lqqa8jL8QTsYYvB0XuDQc2xghsbGRzHT1/cHF7eHl50dHevbSH4yR5dAUVjrdxoj+PL/Xn9Vh975kQc0tE2OA4jajnAoQxn7k5GyoMJEqMGBM4kEyFZ08vN6x+utqtU56VISsxcJH3vB284yc9/8SUUnEhP5quRCiRJCrTWNijbntfx19vwG4+tfhwHKTMZoGwsyTGmuZk4S0oiwugeR1gD6zYXGLdnMHgC/NhufPxr8Gk9kvM4TYl8sy3AAJc54gRGJNm8f0dGOZBmghHkuiI4NrQOpMbCSpWZOrrT+uL17e/9+FPjy2W9U3548Sq9uO83t1QdvZ+W03J///D9L24I6An7KR0P0/3X70Qsz55ugMeIxgZOZCz5ikFsVffTrx9AnoOJkju7A2EJH6Ase5pymcWs9V5bt9effMSF11YvdaXCv/rmq9aRCpNneC55BoV8b2hwREUFFqZE3Y2Bbd4eMDiBDMxOGJNcdIX3A1YZB+wGQoE2at8IBxsMM9pN1305nv08AuAJvcIG6lzRMtrKVruuATc80amvb7qBKFt0GcjUhitdW0rf+dAn9ugV9nz2hCvcssWV67w1Nh7W89hFA5gZcnTYwCY8C2h49v5PEM4zEmtcm2iwx0uvhZ5vj3gmh63qiMNjLjFiA644xHYN42nMYqYwj0nR4IXFgcrCz7/w4N3roMuMG09PJ2L8KvouuOPuz5wW/TpZf70r9HyAcLtHv/3xnbfFWAkUrkt4OoJ/80VPV/u3Pv4a6Orf7iPlNBPD2NxdTdWaGhvMhVOR43xU667W1btp791ag4Oz5Dmvy8oiCFGhtipBSs7TFK5n0cNx3lwGzM1d2+Azicu4kyCjp7ViMaAyMhtJSUjIzH3T4wCwqWxEtnPtX4WBohORqpoqkYUbbqzUaG3xiCy0+Ss6fHiBmrF3dYBEyJg6krLkxEwKc0NfmnDe7W4c1rCuXr1bKuXF7UsG1YcV1QFkzqaGptUvLl1VidxFQXBQb03ViIiFHebd0dCrvvrsRW+tt3Zzc5MO2cORMAEKNb1/eCw9z9N+f1POD5flsk4yqUA5EtVYeZFJM9xNzVrr6MzeNQZCopIkODhkRkF1NW0egmNExCKh+BDiB0lEt2OCSNGsGUydRSRRyokd7NStO4WhdGSfgIPDQ8g1ejrmgHdTBjkLwzk6vcw8oKwRvYQoNOe8967uzEkk8ySdOhPB1YlLlpvj7nDYlYnuT4vVJllEYNDL4+JGOVdm6b2LlGmaUgp7WnuKd0QkQS93IkpZ5t3O3Je1OuPmxYuym8/r+f7h7vHhrmTZ7+cXL17s9/vHh/u1XxLLXKYsRExlykL57tv3JU1zyvsy7ctMoN76/eNFcSrH4//6f/yfa8fa0RirY7cYlcPuxW398O7D2/d39+/2x5ub2+Px9kWeCnIxhpoyWyk5Ta+m+QynnAqDtHZ2Y3PUvvYmLIlJG7a2uKk2cyV2EmFyCGmAhxGyowc7TpduMRdBcLYeJm7UW1e4UaK0T5y8qWLB6XxqrTEJ8dTNbveveibrDqS+2rn29cLo9qEuOC37nShpEXFJvevjw3I+rR/uztZYF0MjpEySEwep0CR1dzuf2u3tbppmFpvnA2jH7POUHPV8WS/LgzseHz+oU8pcJhxcHU2tt355eXt8cXszzUV7762f166uMaMXEx+199ucSNrQxhVwolyEmM9NT9oPjlzGWIU4qycz693r6q2COhIhF0oJ0yz7I8zJNKINuvk33y4JAv3w+jD96Pd/9yf6yw9373kFT90eVzCTh+qusZGpoyoyC0mk+5DN65uc3IQlwtph3p2XpdemVdEC5IKzr22hzFMp4uIWYtrANjka59vp8TTNU5qzuUPocNiXkrVpt1NJUtfL4Zj+6Md/80c/+kE7ta/uf/1nf/6v//IXv1hXNCVPV6fn6Bxce4lBlh1eXBRJw7annh8tz5s8AAR0ZV8/b1ttzx4xbIgfb540Uac5OxkIMIaHVig/WVE/S+MQVRQGjjLAGqanHPEpi4qWAoPINs8yeTydfF1N/EOz//3PfrLq//zo64//8G8U4OYmv/1w/vLLr483R4W2drn0y7leNPk//Zf/9OMXr9+8/PjlfJw4506JJaNXrwTknBNzeOk276otJ95Pc+trW5u1TiXKPUxz3vfDfNwrrNb1eLP/2V/+9PXxRZ7ZONXlcvd4f7HmTA2wboJ5rZfz+XS6nM/qxlME/1ordUN3GMVElW8X0zdtELU2CuiYKYiTlMhG/AawwYTXhuK1TjBAWHISSZCBhQ+3m9DKInIZXWUPRyszcmHmaEqrVbh2InfTbqZIhatWZj7uj35xU0eHXxQVymoFcLr/+r58+omZ28XhkJQ1azeDd55potS8SxZzR8b5/fL9P/zMxR/q/auXr96Wd4myRiFiQAIyZMeSWQqL5hjq72hKW4OaxqDblLMO2MND8jiGaGMuxJ/K9QEAgRXMIeV1OT9ON7uSi/W+XC77af741Uc//OIHl8uiYZRLSKUYm5LXvrbWlraEWrevKJO4Wq+diNCx1IoMMJpqoprmHJo4Y74uzOtiVtlpeFJhtLpB4uzdlAm5JOdAtdRpaxLH9jSnNOwoQbjKXLrRVsM+7V6/SviMbW5ET1gpMEYuYmZrLDcACAoeiKINHtMgfq2OibZ9zE4Sa24I4w30ijB4F0Hhij4zFPBOHZQkvAlCh450kMTpGRA7UqEhChQEKCcPLIaIwY4EJhEnKAjsDZ4oQZIzmVvV7obviLP/5oPDr2v7tvEvioCUCMDm9DUCWCgEDo/pmN1yH+KDhuDePt+MUaGFY9d3KqKtavvryo4NYYzb6VfIbGAo/MRo2V5BxFGXjXlkFgq6RPQp6PmTBnAEcNABnLDbz1UrUrjnetN+WS6GnpCl8P52suwqnSoJkkBqVzXdTXPZzdO84y6nby/n9rDomuciJTn1y3nxjt3rXHlJczp+enThb/7vt2c9sUuZsq62XWqAyBmAh86fubvCq3uCB/OOwXMIXbklVa8yKVK9ebX7ZH8EZFnWIunT7318/rD86Z/8KRJmKY9tYeMkiZncu7aqpOH9trVNNpxwLN3vFIoDvYqS+3qMJoKzC0JPwLwTLDPljRXupm40tuWYBsJWGDuP4ooGvEUEjlwXIhwnt6mZ2XBFHiW9N7vaqwYOBLsW+gOAeQZaW/y3jE6CerPm7iRCyZ26UQXj889f/Rf/8O/fPf7yYX3H+eHv/PHf/J3fvXz80Q++/ubXuz1POwXdvPn09XnNbbnsd+RYygxQvf1IfveL6d/8yxUMZFevIGfOSNEUd0lwIWtRqW/wBxE8Zqif4yXucJmn3XFy1MvpbA4k/OHf+oPHdv9welQ373r3iJII6N5c0X/w/R8sl9p7f2h3lap144QiycvElBprjDEGFyNOWPJgg5HZExBBG0Vps4GHbWLnNHZrpEdGG9HiysG4rgkeauWDGPB8DREQ0tRjwYkAcFfoxql6FggSP3uRbzjZCFAjw9yo6qNniA0YIYDtmZTDb8VRaIsp2CKLP4OutsyQxrsHQBP8DnIdSJBtTRJzTyLP8Laxm7+LaxGBJGa9besUD5aL+rU+3tCk0Mo1d8EonmmsmTjlMZxxjTZSlDAnM3M17822lurV4TXutKpekaCB/cU3FQ6Gu5kNiJG+izSNfoCRORH18M4cGOBficJ/7WOTTXx2XaK03iC2f1eRqP+Pj9R7oxDJ59AyFxJWWFiOCguIlFzZabhlG1RNhneJCBNBAbWu2s2IPcMhLJRHCgMmIMzpTCPjUNBudAAQLXMmI5gaE1wBs7BOEBFxriE5Hk03GjKkFAqDYyKYh7JhoESIEG8OECPFfo431qARfgdXDttKH/qc7ILQsmYnosSiRq5mqAzixOLCBHIiNUsiDHbVgJwYBDV069GAZ8o5pyz3Hx4w1ZxLSolaZK426DAGrnzYH8zNd/pq9+Jyd17uVw14IYjOHV2NcyqpXC61eyP0jmYC5I3v6w6OQT0PJUbrT2XHwG0jLEISJQNcx+C/whQkZt3JyZshaZNpMlYnT+RkRDDTakgJ5pxotKNBQk7ROyR3+FC24nBT3+btPRyuCKTuEqGLrsXnFnFGkts5lOu6NW7jx6l1GCoZQNxzlpITqNdau64TZRYWkd4v2oM5ya21qYiORzfXlCilOMExScol7Xb7w7zPnGy3OxwP87y7ffkShK7q7tprSSnntN/P7t56c8CsqxowmCKmTIL9/oadp5znaTLzdrmoObEvy4JemuNwix3zRdMh8Wc/+MHLN5+VOaXlMh9vH5dzUz/XlnvjKXeYORME7kwy58kU1pEoae9eGUSm1F27QcIJxp2BJFTJQ6WCRSjGNp3NNHKcUCIkJg9B/ZIoEycmgcMTozu5SBh2pjnv9zNnX9ty9gaAwCJFpaG2JLNVU+2ucONdPrCXerkQyJqerMGxFsvUzVyYraNeOozhAopWk8UySinTlDva4/lOiAEF9HBIu30WIcBar2s9O1qZ0CqYkRIWLgaeAAAgAElEQVSVkqcpu3tKaa2j67gutWsdM/mkKZM7ta6t9rXi4489Jd7vc+vNHSlBtfVuZk6O1pASMQuHzmoW7XAzoe5sZiDKRMLilHsukJzq/8Pdm/RKsyTZYcfM3D0ihzt8w/veVK+qq6tHNtUQ0BAkatoIAgRIBP+BAP0IQYD+hH6AdgKkBQGtuBAkgAClhVoEyAa72QPR1WJ11/CGb7w3b2ZGhLubmRbukfe+V02JglateIv33SkjM3wyO3bsnAWn6WyGFzevzFHNH05znt5+8fGvfPzFxzjxV3/5btIH4grjThswakBVCy8VldE9Snrh090BFV9Tgr6ZNSQCTTFXSFUZTTOItVQUfWzeuWQmZg/397fybBwGHNzNbm9vz3fnw/mQZ9Oa99vbm/1+M4ynuw9f/fT1lz//5jBZikP19lJdpRVmTTvnolLt1jGktRoArHX7ywHpT+tETfH6oqXZQyRff61Had5MKH29E/VUjdZ+F+7Ffb8EJX65IzV5+ZYGkMJDK1teUocuU9FaOB1NQ5+8qblw9Xk6V4YIufACG0b++Ydvfv8P/sg5/N1/6z/+YG9fvfz01cvPfvbll59977M39++yFRlDkXo8HqvlXKfT9uZms7veXA1hcA61ViKqrEmiCBuslkWthhCGlOIcAwdUc1VjZyDFNAwxBCEnFdnvdw3kaV6t81yOD+cZhVIweC51frifZ51yNsBJmtsGt663WuDsMFoLrGs9vuFTq0IY9xizRZy9kZuclQBnZndoMy1t9kLtoTdJSWGO4uxQMmh7dQKxNA5Ph3fUHo9aombVBGsnsQAOMzT34FpLpJSGwZ2kavCACmahwHBYNi8+nc7sFJJUU0XlkfNUwNhtBwYtS21WS3FgdrnZXxvZeT5arjcvrqE0zVNeMgAeOaaQtikOMQyh1Ar1ahZYEQgBTaatS9fEZmHXSYL9xGrmv9STOpJVuJrAvAqNC+IQJYhQc5UxVEOu2Zfj3eF0OuWyiKRxN463OxqFSEIIyVLNWWelhmZX14wkxJFyNmJGZM/ViDgI1470dvzM3LkN3wrVdh4WmsGTuzoJM7mQm67HQgOXGw/PSRJRj6e8Q7ze0JOLxEs7v3sHCC6sdr48oJWCti73x1o6QE7cpHocjbjQ3p/1tri1mxEgdl4zfm+Eh29T6L2zk4I01jlgq54XIClUqyJBrdswdWhSL92LBHTF67YnOBMHMHFLJiBMgbgRY1WJnCUwCNWd3a0SC75NwvJeYaVWVAcTrDWmroLz6CQsepIJ9gSj5T2deOprDHvZBi9shceNkb6VnPTLn1x/TfF8RSAff7pOXVzm9/pt0CMKY23fePwN7fac6MyUvrdQy+SJlUhacg4A0mS0QU2fFIWKFa1FhEKUdLXxYDOWsElDGALikou67Xa7m9vbb755d7w7LWW+nw406ItPbuNGxs1AwSG+f7Y722TZ0vV4G+Kbn70Fg5UgQIWr9mOrk0O711BTqa+eu95r9LAJ2+vkm1xJRwm7zdX98e4436dhP+xCNaD4YvPheFzOy5tvDmB2MMsYECME5Fm1lkrBQxKg2uMIX8TznpySlxx8jc3799uEExBj7VBpyX3tanYGcJcac/d28vMjeuXee8pW78Pme8gwImGlLs/v7s1jqQ1nG6QVIe07fe9N8wbEtj7rHtP3N0pAYzUD3rtfRSjASEGOHZ693P7o1z//p3/8h4XP2y2cUAoHWZ7fjjE5uO53cbcZhJYZhalOpwORn6Z7SfHVJy9/9pNf6AyPhkrdwHhFMUJgFp609ufKnTfbKymPyI0BjuAsVuppWc5GePXR5vmn+9tnm7uvv17KQ0jSdJpiYECbyuqrlx+zn/KyzMyB4Nbq+2DhgNB2frY+OKuKOeGRo7ouonVBrQHUUwibQGhWXLRinU8PGqx/fQGF/JdXNODuvK7VdrFQ37pbBYGJWy2w7U1Y+eHf3hraUm9liAtS9pSa4703kC5ZG/m3/rr9i1tu3+Izf/JzMOBM0uT+xMnZuWtDUbc9boykvmyePkZaP+wF2rv8sKmS0wU8aud1W2GX5cZdSLCNQg9BewdqO8caAbH9V01FWi25j4mtp1ib9MzSscJHl150mUj0vbDpofqT3oXLUvd+8D3CXpegtr1n7wHtLw/3v+p6bB59hAsfT4Sn9///xxWmaSJmDsyhq3iCKDBVKzXX1run5hISxyBEUkKtVZpmJIMYwsQURMnVtHQ9CGaWEFoQoqtYJ5HRevpKDJcZaWRG1hWYjIicneDUsgw4NSK1uYPIZV3EdAkAiKhV4QxE7AJiF7FaoepkBm0oaSu4eavA9LnWjMDAxGZNQc4biI7iujhLD1JhMHXUauzgbhIsLHCap1lzEaLtsKlTqXM1BTNC4s2Qhs02pPBwehiGGCWSsdZYcqmmCqXQ01YGxyGGDTbjsN0PZLR4NqCwhhCqeBqTxAAWjiGH6kWN3cW7eLE6mhpVo3M3J1b31rXurUbZYP+G9wdhMleFenegbHlqy3JciyIJoVWUmYUcZE04tCqInKUNnBOTMBt3/AqAmz+aNTQryvWgW4UAWjrfzMzWoaCuE9g6bITFkdtOxICbqZsagiOkFsy5muY6m9XoAQIypBgrnJjNvFaFLc1JNOfF4cMgKaUYKIAi8ziO+91ut9kECl5ts9vGlITF3E7n85i2n3/+vfryJTOZ6Yf7+4eH+2metLW/d72JBt7T1f5mnmYJKYSkSy61SIy7cTfr8TydPnp1tb26OpUyUtQgs+GvfvYVvAjrs2cvPxzvq9ap1KFoYkqbrTnlh/M8FS0sAdNUNBuTBpar4WYzJKputThweHhnrladCZs0niWbaSOUNCJyizm6jUYTTu6opoftQNz4WEYAhAIEIcJRC4jdrHp1IgsEONVq7lpLWXIONk/HMp0XryQSUxy3Y4wSICi6wK1W9YpajaGthRPtbA8iITQ3OiJjsTgEHqJXgoXT+Zyb4o0J8ZCG5jJhLJ4GjkkerACRCUHiMIzzNDFTDNEMx4eplMXdU4wQkeDDSCFIKMgMJwPVNPLVzUBSa61EUM8lqzDcsSxgtjEVa9MewRRa2F0YIQ0xxYHZzKo7QkQaYErL5LlMt88/evbs4e7t4e5+WpbTzfXL56+e+4S3d+9oKQiAKWrPFrvVvMHVAFjD7C5hfushVqviIC+5aFPxFQEU3kVPzFWIAos1r7AmR9W5A2hoUuJ4fJhvr328SsHFqkYOgaVkqwUpxI9evkS0eZlKrX/8p3/27sMhykbCqNXMzs1goac03muIK9GaWohMtHYMrkH409PFuw4pWnbsuIQydAGX1ms9Wqt6J+O3cwJrlavDZWg+0L5qm/J3Y6RLBqatDksdtupqiq1htoU61PRNHS56XrzUdHM17obT+WHKC7Hc5eUP/8VffPn163/3b/8dkHzv0x88nN7+/j/9RzHGqjotMzOf5nJze7Xo8vb0bqlT9lse2oHa2HaWl1Js3owjmErNBgsxxBiHmDBaY5VaUQI2w3AqwVRzyaVm2Pbm5noIwa2pqAlx688nNTX3t+/fmEdFGjYbGGcOgiB1mrahAks2mHkDIdd0lL3hEtxl21s2wtzPUF4PVXPAhaU/57at21rbi4A42Js3RDutsc6OzqFbkQ3gscXDzccUasdNqMljmziYWMgrmQPCMSWySpWgkCQSQi7VM3jg0/l8NW6vbvY5LssyyyC5KCJs7DGZkoNBwiGJFStayrkcyv3+al9ydTEEN9I4phgDJ26xB9iNFOwcxMm07Uwrrr/2U+DRJJTgdU3XW4/lRdi28ycJQmAfd6OTq2mzDfNaz3cnRl7Oi1fz4lNdllOZtISrMW1ikBg2IYuoKVsjODd+m7EzmHgQDkGJCahuSgCDe/uWr7gwr8LZLVthb12Bbj2aXSPsbjHWel6oDZGt4FO3J+9Dy/3MfVzaHeRo+UTrmrELmNNdt7grCDTur/c6e08DmNkf1UqoRQIrVt1q5Y0ygxbfNVj0OyyqFpyRSMOZSEBCEpiZBySDM7Fq6Yoj/ZEQfJ38vUuWml9BQ83ABpACZO5E3uRquGm16boMjGiFbb6z66GHOqAm6NV+99LZB/RmtafZ7ZrxALigzOtmSSvvrWU9LaByWlMpf7zzU2f3J4jIty7iC3m1bQuthmyX9K1HvO1jrhhW/9RrO7GvoRzRmn2ZdwcAWslEHWppOKgv56xUwQxDGEKzuxQhFg8i22FDAwWOlg3mSynZigOL5vM0nQ6ntAzFFjMV9uk0FWNKvr0ex93AI5/m8+n4cDu8iGnALTY+LrbUCm8liibvzQD3ZkyrztKyZWoKURjCsN2M+2iJKClFSmOalgdIlYEgZm6crEz65ddf6slqNZjlSRkRjSKIVjlQIooipfVe9PHkPl3pETFoE4Q6RnDJPBloxRVwaBruCNK+bUFYiOAQaoo94FYjbiPUUU9dj0zwelR6X3WuRC2FgkDWns/Lwd3EQlYsBl0WxNccG2hAeCd2eUc4ccmT4RCQwFidDWK/+auffPq9Z2qnN+9+kq5k2G7O5+n+fjkdy26/GYagmgNjmc6qGdCa58Ndhab3H75O+Ojlx7cffX7/s4ejiROgpfOFW+cdMWLkSZoqALmzO7G1llVt0Cq8FdeV2JRKyQUBn7wafv03v/e9H318//D64fRhKdMY90MKNzsMYxBhs0yFjw93p8Mx55yXxQuseqlVp1om83aGApAGNQAKamr54Efl9Z7yPNlI+1qlC95k1OpM/ZRuwSGe4FfkuKiLM7E25VFfNxlHr3U6yLyFFO7WuNCdYcRgJiE2rczUZPPM3Ii46V31u3GfresBse7z3wE8LopWtrbsrVtJCzAeZ0PHsLoKrxMTo/frSYORu6I9dez7gtes8+q7r375qgM8T77VH+0KYsEM0kMfatW1i/DfI8blvbDna6Ne/zzcLW4Mq3El4NZPivXVLtYZ38KEmlB069lsXkhucO21l6ef8Nv1hvbYeQXFLh8H//dc2sf7wkyfAlgXO6WGoKwnyHfi9L/BV6i1goiMWFmiBGI0aU+4ulmp3Ty7SYX0niQEoiCR5+6FMYSAEGvOuZSsSkQiPDQR6VZbhwQiIxaxBmSKRF9Z6y1wQpf5FmYokbcN1qCm3tQo0aaoNqoVX6IQrIW8tfVXRKhBLO7mas3GztzhQmGFt71DsmASYmG4tTffSVXVylJZwAwXMjPxoFVrLQajSBhBwuSFjLxqkkTk82zZKgOh0aAFwiDSH/3WF/M0L1O27FSFBZwpO1FAobrdb9zI1NXqlE8kdnOzm5HOYfbANdZxO6bdICFUdY5h2IyLLgho1IbW+osenin1FFDVQWnV6/M11nwE+3uDCXE72GkNTgxMwq2u49zUPcGtf1rVFEbOAqIAZogEF21FS6zxlbn2sgytKI9QO/K6Fen6plbUvDFpDeamziwS2QnFKgCCc9NaadsRIwRu4tfemjBpQwSD7Xbbkg3EpdR5LrXWXLKbL0s2B5GyMJOIkISw2273+/2YBjJUFBG5+/DhdJrmPE/T9NnnX3z0/MX1bpdLnufz+TQty8LEIQ49kRQOQUIQNz6ezw93hzlE3W09l5rLPob91a4Q/+yb19//lc95HN/eHw4Lzuf8+ic/16UA+ZNPbtN2kDTMp1qmiWNMu43ENEhazmp1nkoV5mWuVhyOMUYKscy0nGZU3e63MKtWajUiGTcjwsGLd21Ec3eIkGnTROjLpicCbnGIZtVQ4UowMJxMxCVEiFltmm86DBIjhAMcudTiuRYcpkM+1fOpuCLGiJFDikIC8gohF5CmIcWAspxrzeYqEeJi1u05yJ1ZQQBElao6S3JHXmoIULVlWdSyG8UkIi5MqtRImKowY3f58P5hu03MUrNXMlOEkGIcZXD1Mi/aaGgiHKKlgd2hSqmQCIhJVcxY3Zp/dnPs1WruzuBaUbO7CbtsNlcxEGGuuqhVCRhGNqOSWatd7a+vr54d3izHKUNxOJ1vdrc3r64+/+Llhy/fL2cThTmg3qveRHCjli60VSPr+bv2AQsBgZdlUXcRYSSjqq0ibx4oREnCQg4hdnInlo4huDcPHHUYtFRoiEMU5uW8mKmQQPT25uaL732RhjhNU4zhD/74z3wZxrRdSgTWrhXqIjs9+DIwBV8j3DUF6/0nHa8Cnh6P/f22uukaB1M7Tn75TO65ZecOoUNc3bh2LU95dx7DY+TyGABd6tlwBxlc3Fmo5xfrub4m394sU5lMZ92MKQUxNQMq4ViyI9a7+7/66s3/9L/+w7/zu7/3g88++fTVZ7/+o187HB4kCgU+TUcPbrSd6+ylVl1i4mvbD76BBRjgtS45FpLIgYJ6JeEQOGoYUkoSxpjEyVSZaEgpTGEqyzLPS14OTp998ulms2k2rCJxt7tOVKuol7mYgWHV1KyiLpWVSUKMUYYxsHk5WztcmVZynrf6j4Bg/KRrqGMT1LAsRxexamdLMDE3d7ZupdnpRRXKZrwCjAC6wkYLmNYupl6mbn4+akMKzVqJmDgwmAEvZu4ggQuqq5NbVTeBCzl7NisGeAgxLws57662z5/dvvnm9VIy9pDIGRWGMPZWcUBvn9883D8UzeIyz0ujfeyvdvubXfGSc65Wsy5qdcmLWjWyEDhGMQqmBiMmFhI35JwvdeULk03Q3b96itQ5xS1YanQerLYkJkQxJmYrp+XhdDgfjQlD4lGGQeDMebHMp1JjCBxjIHAMyWo1dWYeIlspcIspQtjZ4xhMUZbicCJpXCLvfr6XJKmNCq+KH4CDWYismJGbU++R6L1p8AY4tGnTJaCbKNgTrOISbT9ZwJf01pjEu8ZhA60YeMSuexJHBDfr67hNBWLmauDODu618oaB4GkOImsYYx1cp6ZpQh2qWLMPsJBIkFCJuEO0PeiDuLScse0y1pObDoW3XcgbdOgKaqkmJASHmhqsUqulRtZ5Vej6665HzOkCb/Kj7tRayF/Rq8vgNT0UdOCvT6sLgoXWCNY8LXqu6XA3Z3pMzy5OGr98cUMTzR7xLXqcNOtcWadPe0GsD6c3LzzydrBOCSNVoBs8mKy/zY0CROTTQ8EAkGLRqhpSALmZViCIhEHikBhyvj+fj/PxsFgxCJ2X6XD3kBe4krGyEAGnhyMmj7dye3WVNulhfihWspb3hw8b3nz08YuRxyOOH97eU6PwXUJH6oq9zRvdHEwIaYhjopHDwBIkbsa0Bw0+l5lR4iAkepqOzVudA72/e3P/1VRawVuJnMqUnan1/SsTEV1ksLghGx3ZVTw+9KfX4xRqC6WBgLzSqES4tQKMQ4pBJlYhNuNWiHgcr7ZyVam3ZBHg2uAo7g+BqJP6RFrN+ZInAwAFeqw7OADpCC/hMtGdmognUQ89eo8hE7kIRyKBeiFmEH7nt3/7R7/2yVdf//TD3fFaYLQcH3RZyrncb8ZPtMSlHhj14f59SjwkUQrLMpPT+fT+2f7Zy09e/ug3+Wd/+c8pgIjFQghhDXFgZmYamjyBsTt3zcIOna6HPBmgYAXpMOLFy+FHv/7Zr/zqR1cvxh//xR9Ny0NVdwzDML56dZ2GYc7Fqgnh9ddfzuesxYjgCjao6XQqy9ldyJvPmBCoa/GyNakAaiKnffjX50aX9bJuaMxNgxONRfG4BonWNdchxp6C8/qXWNGr9mdr3789wjJ2WbntGXjDzLQx57nvTHB0qQC6hE4rse8ScH0bnXmcs/xLwNa39qr2UXuLfaudoRVNqFUxXK1z/XuDtIOMutjJIyr6RBPq2zsTHnfADsT5ykFytM7HPtm9ryahnsO2XdM74+LCK3S07unGIo2pHzXNtMDXksnK3np6DvYKl7WOW4txKFrdnYVZxGsbnT4ovDqTtDPNrKkSdDFvFvEVWvt/gV4BeKwm4zt36bEY9+dJ9NcP6d+4K0ig9vgURmzmCV69GklDqxQEEGut6kYsUHN3CjExwDBTOIcQgsik6qU0Eim4YeSkZszMQkAzBgwdPZIeKrT6R8tvgkgQkSBi7HAStqqmWnVlOooD4NBXJl1mnfczmxvO3DjKkVwtl5Jz9roScQdw73y7HNAUo1AgeMiuwhJCksBKVZRYSVRAzGZJUq7Vraxu93Bmr8zbCKcQhMyJiWLLylHJTss81zr56d//j/69n//iy+PPvz6WSYyjDBbN2WtQALvnO+NatOZ8ChNV8qtn1yyS72scx4d83F3t024oReflTEHihvPclByrK9C8Cx0OVFobBxTVEQfr2B63FJBsPcKIqJUz2o4iLGykDCNwEo7SEW5Cw5lNmlCjQeEwdhYOEoNEMRZ3JaLOzHBYLt5v48RrmhPWSsOj6lmbh9Sg/o6fLebbtvKZjMwsCKchrMGAMSOmEFO0UonIvdU2SdW2252EyiRLLvOUFyuEhk5CK1wNamAOIQ5x3Gy32904hJSXYosR0zevX//0r756OD4oljhsr/d7xHA+n8x1GIY4SMllmk7DsAkhqrKIwKWq/tWXX394d7cN8aPbG4IFgwUe7YZTOJwePv7klXJQkvtfvH/37vDw7ghDTDge5q++fPPi2dX5fJ7noriXMS5lub0ar2+fn6Zacgm0MakgJgticv8+H97e3b0+DdFeff5x2G5KWUqpjBBj7PkCs7tXVHIWYhKYu5ApYZXwVUCZqVpz0Spo65McZCkKxZRdiQHyEEVSHcdhKFFrNQ/kOB9nrX0LrLXM83HAJo2pLbNAIW3Di+cvSMrb8910vl+WDIEQPFvRuRXWDVTUPM+afTIP0rlEEiCCUrTqSgAM7GqllKV4EHU307FWff0GN9d5s2WhMI7DdnO92272+61JnpaHnMucz7UCADE2Wy6lns+L2uKMYQiEwa3My2KG3ZZvrjbjJi3zoubkzK28KYEoDsPIotXhNcNTCBiHxE5lrm8PVkqxllMRNjd7JZyW024cb19dv379FtyEWhoJGbBu3tSyPm82VrbKBDTNCgaHIFGyFjCLkDMbwYq2OCOGwIk4spMhusLEpWcPzYLEMeccEnKdMfkwpCHGw+E+Bt6khDRtNunzzz7d78b5XG6f3d7/HDfXQxiG+QxrbtiN5toUYXt2Reisg0bqWzHRlvOuHLLvnIxt2/HV5BY9jeSLPPC3LmEyQye9uCuInHhFptzNui/0YxXwMZprmSF37gAYqJ2cjvWdUYfmvGvXtqjNE+Rqs89ZH+7ubcvjdl9qnmtVs8+ev/xf/ud/9L2Xn3/28Seb8fr3fu/f/h//wd//+Aef+UDH1/fXN1en86HUhZ23YRt3w3CzEwnT8UwOmM15SipX2EmrAwQOkkKwIQ3CkkIUDqRZhNM4CJHWuizLdD4v0/T53/6dSFJquT8cjWkcxiCaPeeaXfX6+vr9h9PxPD3MOEwwlpv9VoyqFvdgbkzCgRqDqIfOK86i2lRaGhcf3DuD2hCj0d2bbBUFQl2TGAIMFJr0tarCnSWEHm5yF4c3WgMwWknyravQDe2u1nPzxhaucDOLEsFcq6J6LYWHcUgCQBeDVdkkdxMWM5XIn3z+6el8OHyYsAPY6hlQYNOmFzL7zYurr7/5GoLNfsy5vPnm3fPb2/2z59vdJuflq7evz9Ps3WV1FocTJAQZAqBendTBDiJhqkVbtazJVgPGrcmnx7VoaUxjVRI3MKVllzYvc0gcYhokUbHsmUCbgcts+WyVizCFbaJFzcuyLDqm8dnN1dW1CP3lj39CRJtxiJtUzkzONMZJF1WNY3R310LcxHK8Q2Xrelup5M7NtNThCoeJBBcxLQAQsNLZDRfxqhUG9o4eN7jFmzdCj6nN0Ow+6NK23Nc2A2j8JbrMtp4Cu4Op07HM0VS0exjWdhFqoMxKFu5p6Po95iYw3fCmC3mGyJy8mLoLvMl/c9dShhYtMcTe4XRBDrztM9SVsqijbAZ1gBC8EdhU4Y17xgwTie7IVN1M0OKTgClfGIb92aHnWRdw+GIA1yId9G3eLqbq/bvN5uIpiaG7Gq101EtZ3pyidPWs/vwvqV2HtBoMgiew1CWZbZha309bDbfzHOhbv9O2eKDPjQZftjaG1lpEZCtMYOSKi0FkGxvHoxsCkQEVFPpkMVGERIjzcQlsCKrhepMCItdYJ2QrFUacIkB5Or+4/r7mcipHgIQimKouy0n1GdT1w93ddj/EGA/3Uw7lh5/+8Hq4eVveffhw72xOMLJege1dhOit/AYE5x2PzzaVapZCpFfb7fb5mH368P6+Br262lku53nS6iFsrtJVLfrNTz+0ttQhDqLhsNwXERkCC0WOTpprkRDQUdKLPsAKUOER7F5T336ceZvS0NXCILgUFglDSIOE5GFwBBCYqsAr8+q00KmNrupC5K1lrMUc3IOKji50FcjGu1mPd3h/UM5Yu8/7nPNHKaVHNMPhrbcYDjA7vGkJCyspUB3AjO9/8cmnP3jx5z/58emEcQ+OswObLeaJUgKoWtFxMx4Pb9NwfXV15Vbv7+9UZcn3TvnZi/T9Hz5DRCEdozkQEoFRrFJFVVDzuOzsFaK2ptHt/AByqiADVbC7YBnx/JP06ot93NU3dz+9Px8qAwJwGXf8ariNYXj3/q6WGiS+/vpeKyJBIglJirFkeK2oruIAtwVC3EU6TV060YJaF9xKbfLL4dsWM7dW57b6esdci2A64GC+rlNaMe5LdeTJRrN2k+IJz7mlwi5rhaXFls7eBQ07vsROYFLt1D2sOmq9lOG46AJ2lAfr/9ZAav0w37466oQeLbY31oK/ToLosZl1YfxVdt0dxO4tWWRikhbdOR43wMtNvnPLFQHoEeKFQnjBc7i7s0l/2+2Qe1SM5bb/9vEkAlNAUHdT1VYKvnzY5oZrhhUkcm+GOPAuwYqwDQY3M+LeoKRou2f3K+MV6GvvzdG0dwjmq0miP5LeLw/+/+ky64/9KQKINYjczzEAACAASURBVHLmS5kN3ylB/U29iAcAnQjNEeN2SJtRkiw5T8ukRSlwGAJFgTRipDMjhZBCnOdMClR4da8gg7HNVrwoAN6EIUW058VuZmYVzDFIHNLd4YCuH7genQCzhBREuJo6IMxBWusxFC2VgQuX6UQhMLM3dlWjCyh3WoCjcarGcSQiL7WqqmmbtQOLeVOsUr3kVMIU2AnQhqk7BiCsadKAYRCJYbMZ1WypNZel2TxxICSKKe6ur7a7XbF6mo7TdFarLWcg4RhjDctv/e5vvn3/JvB4tdmVuRzvTkS0u93tbjZpF2nj53x88+7tw/Jg7qxxQNrIZoybIPH+wxHA3fEQQ0ppvPvwAeeasN3vdrXWw5v3w7hJMdlStNY8ZSsgwmaUcTscS1U3U/Nq0KYvhEGGq+0e5u/fHWyuIhRDIIe6OQGBPLAFpP2mLTd3d6tq6kWrVmZ2MleDAJHTdggphkgGzbXWWswtthB/lRPtQh2ACIGpLX5v5Qt5gjDTGs45EJDSGEKoteacYcYBZnjx0faLH3y63Q3v796clsPVfhsiHx6O07JcbQfmGCRB/Xyep2n26ky8226f3V6lFNwrATCLHK93u5tn23EQERqGYb+7+Wd/8Cdfffnum9cPKQqLPn/x4jd+9Qevnl3BvWq+u7vb7/fb7fbm5kYCHx+Ob9++vbu/I2Bztf/yeJxL3oUYyQ/v3n768hMC/a3f+jd21/u37+7+t9//xx9//PnDofzjP/7T8wmeeUyxTDVnxYj/9D/5ncP89jAdqpTnnzw3yDBevX99EorTaYnYJB5OH5a//IufLaeiByB3AQLAcA0s+PjVi48/f7XZ7P7Fn/z5/d0BBSwch+hF81JDYI7S4PcmbxdiTJvhfD5t9mNe5moV7K40ph3bWLUOWzHNp+kBEZ987+bTH3yURnl793rOp81+k9LmT3//a4xgIVd3BQKGgbbbTRrGEEOIAxOpG5OmgcdxAOnpeH7/7uH+frYjJA0ig5lWqzFx2lLYcK7zkisKdnu6vt1sN8ldS5ndnBmtxX3Jdbu92mw2BKm1kal5WfL7tx+WrDE2wiMk0Xa7f/H85up2k0acp8P792+rKwHDsMmLLUWTDLpQsKS15nImsgp7dnu92Q7nZdYKBx8f5vN5CTLUyXf7cX8lw0Y5ZITK7MtMecHd+/rx808/++xXf/Hjd3/4k39xc/Oi5Pnl/urTj15Eo2e7q3/wP/w+CnCGmATaCG/UlwUPXTGHiFm4uVq5gczYKSBEMcHwYj/p4qbMRmxaHQpIYz7i+bNnt89uY0oPh/nN27vzw31K4xCDaS0lN27Bq49fvvzkRXXLdUkx3b85PJxffzjjv/tv/6t//qd/cL2/IYt/9M9+/Pf/+38y8shFzhPtxn0+fmgHvDXiTRdxp5W+uv5jLRr2+q3R45fNg+6xjN8YlheaVK/VrSu/a4h2rMrR5Pxa081TfQFfj3R/WkQiAJBt6OUqZiJHCEDxRrpkMrPeEtX44k8KmGy0WwZVL6wWyQcJA4KQm0nR6aH+4PbmX/7k/r/5r//Lv/uf/YdHff1P/uR/LzK/ffj6w/mbu/l9QR7HYb+7qdnv3x1u9i9/+Pn3fv0HX2yHdPfuPnFgZ3Jsx10MEcY5L7lWkIwp2pzP51N2g8hc1QKFIc1lOR4Pu6t9ivzVl7/4+S9+HjZX43bn4qWec53BPozp//zLnxYL7x/md/fLabbjYmVSUoFGnTk/aD1XL9ZktgJBOFimnBUEHsWpPK3CCQsxV62Ad0KRW+DEzOZkWt09cAiRa1Zztc7G8sQJbK3ib7Ba6tpUwBCJIXAQONRUrTqVIE2HgqqqFYeBIkKKCjfUNAzXN9f7YadLuT8eTqeTunGAJPZqZthshhcvnm02m2ma5nIe9mkuy2l62Oz2wzikzbjb71g45+nD3d3rd/coiAOe7199ePsewEevXo3b7fHu/nB/KiVvN1uR8OGb9yiIuzCOAzGOx5NXbHdbgE/vjghMxuIEI2oUZnMoubk1qLidWlHaiceJUxJiz1qH23ReMhTJgy21HoACBiJTilFAVUs1qwOqIbyQmAYWWsQ2++3D9IAlA0AMQYSZoZzPCxzQSiJRgueqs5KDrUGDTa5DRux10WXJNVdXDURMAqZq5qjeAq0g6Pao3XWH1i/R6CRCLJ1JQMTaweOmWUaEplplK2IGBupsrcS/yuP0rYFFyF1rJUNomxeRm1etcGcWCRIkNDjVHc2e0hqQ1GmbLMLMspYPrfPD4Er+6nufTXleDlOu082z6/v3BzCeXV1dXe2PD8f5nFVV3TbbjTHVueSscIoyxJjqnHPJQthshzSEqjVrjZvRzU93BzCEGKoCIWeubMW0aM1qBaB4oZg3RYvOUmu7Zuu1RlMA7ZatXfB/BZtMe6rl1lqQvptVPK3zXygHRSsxpM2K9XeaAVKTh/YLlLZ29FxezUy57YmPhXgnbvzZvjvr2sTZSo/cJcnJ1nCyBWvc9FbNm3sjMTGLs+tQPSAEJI7Cob2SOaVtmms5LScESVebEAVeofri6tmzmxf5OL3++u2H93eeEUIIIZihqgVO/sAhJI9WeNGQsQO2zhsb9sIbjyOTeCkln+BZ9sP++f7FKBtfzIu9/ubdw4d7Lcaxa1OHQRpHb7zeLp55iOk6efJFp0lPTQsJCc/2Y77Xq90uz/X9wzE6fuN739/K9d1fnX/8h/+SlogHkEYrGeYghwhzkxc1c08pmlXzCljzFmZmOKuZNWV+AgghCjOjmX52zMXDRqZJ4/bGQ6zT/e6LzW//rU9/87c++fDm9f/xD//s/U+cTzvodggT6JSrkxCHBJLa5SkVbuSV3eFQBsKld3E1qWCwgEL31lBTd2y2u1qK1mK1IVLEIK0OdVMISDgKh1IqSRyCaK7zeQmQIW2dw5Tn56+ufefvPnx19fn47/wHv/Jb/+b1uPVqRe0MKfNyzDqZajEzZUKCBzeefdrvd0FkmSe1+fnN9WYcp/OyHW7mE/3JH/3sFz89fXiH84RN3G03z/KEh/s5zwtIUzIRkHvNZCUIbYBQtDpMdd5eb1TPi57hePEF/vP/4u8ZTtXO797/ImP6UKdJa81qGuAh0gCP5PH4MD3cnbVWVz8fl1rYsmuhSMkWXo65ThXKYGEICzWsgR1sBIMWrdng3tp1O4wlTUbQQTxyEBIH1VxzXrR2nS6+NBa2RiWW1s3SVNtaVYmpsRx7qKVgBgla31kvYaDT3ltT72XgkULoiE3bHLwvcFNT07Z3MIkYe1OKM2iXqW9VKX4SrYHM3eq3QzgPktqXrYoFh7lut7GZfLYvm/HLKi3kF43UVcWzR3QGc7PNZrPWTNzda+vI7ULKLU7xtfGduDUJVWtAlGVtIlSrcDvc3dRaE9gwJHcvS7bmg4wnkA+hlmJPCh/eCuECZg4hSBCtukyZhVj40k7YtvLcsYj+922ztV77MRAxS2AGQavqUhqGJimGEFR1Hb4+eASQtgOlf2T6V3QCppQuZ4F3bwdvb5iISqlmSk0A6peuWusvf/P/43V5LPbE1OA759G/Jhns8jqXF2Hm4GsN2x1Q1FKZi5vXWmAuIiJCLlA07RH1WuFetYSK2kr1Qg5h5hAAjQBvk5nmkqepQhBDQEVFZebA5ERFazv5Lkhy/zDrJ0Jr8AfZRdif3MlacxTQ+M8QZomkXl2pNdC4NwMBU9N5mtGaGN1hrqZuGMcIM7D1Ppiew/SeBsQAtEKS9iokQZSoCDkZubpBDcVJW5DvEiSyaK4PelBxChKvNtCspcDVGZbAIS60LJynMs91qrmq6yaNmZbldLa58hYeVGOmStXccpmXcqTTy5uXL5/t/K4yxSGkZtIrEmkQcTYyZvA2xCTM0Ork4NjLredFZzvTyF3WrYFxvRzg6s7uTG5NEcC1MTW1V+vZIVoriJokEAAzeFuKDGoNg0zUDr9aG49YTa35NK1yhFhrcmvbziqO5c7E3rWfqWezjeFhFmJgYVOb8+RwFpIkqgbxOCSRQERpGJ2NiM2aUgXUyasBdbVeac0IaO5vcMQQxyEOISYZkoQoHIPExCA9nQ/H03HJxQ0iYRzG/W47jqPEECWAR0LYXW2vrq6DBIcB8zTnw+FMoCrpYc5ONIYAt8xc2JNItizLVDSHQCBzVwHYQcyRExjqqhV1rmyUgkiEG+6PD+Gsd4cFKq52e7XXgvmU87lYxiqtEQIiBGU5AThOU3x7NwznEGUY42LF1JZlkcAyMhFTEGfu9VKnrEs+LTEFNS2lEBPHyAOFkDAzKcqcq01gDBtIxLycc9XzdFLLvKx8eIORgyERaQjDGLe77TCMbpimCaBxHMdxDNHdSylL0QmU04B5gpZFywImigwWdSWDiG62FJw327QZN0G4FORFSzEmhIgQmBmm2X3YbLZMUrIuS6nFWlnRFSCSEIc4Co9qXIulQYZh2F9tN7vN4XDIS11qNWNl1JLJTJjGGCV6tUXYgCJkFMEspUpTfCuTVl1yDmCP7pGIScgcqjGgajmfj0i63Qw5n6GadT7Oh43Et/fzpz8czu/14U3VSdVzVHEqFHtOIs5ws9JsK6hXcHrwgGmePZhEjilKgFpR1TadCyHTdK4BhRfT8Sqm4VnVfDqfbPa23oeIimmup5hCCsxeONRxxK99itP0fkgkbA8Pxzev3w0jxAwUOOucHzq8Q6u0ziNXe61crafIZfNu+tytcNd/tLIDVqbTk82enpaUnvyLuBezzLUDTb90+VrU7BsKrQrEjUvfCl2N5tHI9eLmvfXwMTxaBYCI2FkVcIa5mcPUVZRA2oi2OJ7nqx3+5Md//v0/f/G7v/FrtUBiEo7T+ezQELjkfLAHq7SoHubp3f2HZ3ebT1683GzH6eFETlFC62UWSSFFjsmdHLrdbw3qORczIiclq2ZF4QRzAouEmNLD6eGwTFEYVEBVAmd2YTHmNKTNhlzcqExep1PJc80TB5fWP954JUogVoutgUA8lm+PBikZYByJJUQJRvCGRDXkQ1mrFa9aezTbnjkRlGoXcabeuLxWNFufAD3aqLmTrMinQ7wLE0HJS2NksavnebnPaqYKlUHc3FpIaIDhNC98vKukQiRJDMZCMcUQGeIk9v7uzVIXc5/zxAEcERMXzeN+EyWp6d2H9w+HoxaNMdSqOZewiU3epCNxAnMYWUxheLZZThOIOo/B2oECa5ro1AmI61Nsqs3eZE2c0LT2ukEvCYk2vR1vNrsMACLs4hipTgorVy+ur693BfownxEDCCxSTZEX4iHut6iuJZM5uZlrECJzV5iC3YWZOSxLNjOFOimJO3etz8alApGt1aXW30crtktEJIHgnWRmqzFlG4Ym9N4YSm2b6sX1Ts0g7vH6pWtuRVIaPZLAbg3NbrOEO1rde6G4pTHu6JZAErqstMNBbl4b2gK4urb8P0UeN+MwbqYY5ylKEChQUZa8DKdSl2qZmLbDWL3MS/Ymm+Ccdcklo1aSMGyG3dU+BD6dDlbU3UMQGQRq1PaKZuhp3bjCG7kK3gTAmn503ywv9KZuvGEO91VehtC92IHQnn1XFPp2NHzhSD398kLFQNcK++XdkdY+zUvk9Us///Y32x5HK/mnvXu63NEBuK2qO6vKxPq37QWakEfLOX1t4aH1fkSBhCGnaZIQgfbBNVc1U4ZH4nnOBz94thTjbtie67nJWsMJxasVquLcLLEJIDRkywiNVaAwN82wCjfNtRym40nP9ZzrotfPbuM2DCkNm1SttIxuWRZjyCCWjx7gg1GCl8Yh7cHqNNch7c2jFUNBcdRsxkQqMIhFNQ3ESmxcnWyVEuOm++XuWN8wuZMbuuE6Ady6U/uwmysb9ZE1c4grgrAEDwlpQxwWzYq62YXbj8L7n5WwYzuH2kR9BUpNCdVBaC3zgJORt+40RleCbGirMBgk5HCDmerj8F26S+ixF5mZGoka1lAHN4LpUrKiOhPHYRi32/uHU9rGY33QY4bixafjcK0m01xrVo3CIhtwhmZDqXUpmaxW01QNdw+n8hLPbm6GtCuFD4fj4XBHZOSaxv0Pf/Xl9dXVT/7i/devc86nt3fKOnJIaTu4FugCBtgRXQAhYRaCV1WRMJWjn+f0El/88MX3f/Tyo8+e3R2XfMphx5vtdeLNmw8f7t5NS83iAnLXUhaURRtuxMzDkNhNQZthHMImT64VtfbBNXIzaw/Sm69YZ7t5k8RqS4yZHd2Zh8lr7bS4rmhH7tKRfyIC2M2YqLk/N7GJHrQAqwBL3xmYjFz8yV7rf82yX9P8Hiet67dzcbyjI9Qmo5G1D4bHGz+iV493cHoaAa65tFnfZtCbwbvVX3sNX+OHtl22P7x8ImosXL/UODsXv29U/nj/Trd/3CFxqX6gB6ZMTGJEzNwOGOJWV7g8Q219A+tB1bvF+1VRG6JARMzk8XHDVK19WMNase31g/5AA1gvu+vjNulP9ng3dHNtCDWPHFPVVtV4gl6tn7c90X8ttOfpL3VGXy8CrVWT77z+39grNCCmZyWGvCg8c9Vci4kPQwoizdy3swEN2voNS6XeXKxkpBAhNCXUFJM3CNxMWo+AVgeoiQ8RVJVlbWBoy+fyMNsUN+9zsxsLw7kLarl7GgY1Y+IUhZmyUbYK89XO19wIalorBIgxiMAYqtXVArmRa4dL2rwB9dw3hujutZq32dcmNnUkuFEHa1WtDkeXrVE1dS05z4WSjFeblBI5lQhzDkGGYeAB7+/en+czlArU1ccx8UgVOUQeNwmDTbWUotNsEnFzc0XqyAbYfJ7m8xLENFcEYgVVgLiaep6ChDhEMKlWCiQxhSFarlq6P3V1dVrNd3zFsBoK7sTCYAX1cNKowyMtDaxaidZGIhDMGauqPRFTABEYjaThyiv4iMsu9vgM0cMzpyffoX5XYgKttYdOSxECuRYrCoJIYCZVDQHb7TbGqGruxCRqZlbNjJkYyLUEdzhb0yBgEwkppRiDBImRUkopRnEyK3l2kRBCcJBWvbm+mo71GGcmi4lTlDSEzX6fYnK3w8M05TKoOrG5zaXePZxev/sgzDfCkOgAEAAzRS7FSvlw/34pOzWLm0jRXKpEcGj00wIyCmDBnJcKBwROefEPb4/EZTp5XpRcb7ev5mU5Hk51AmobxNbsBwYhI21SXfT+3Z1Evr65Cowjn6ZzNgMEwsEN1RSuYJIowlKVtGStikAUZRwHHiTnRbUQXG3Wmh2W9nj24mqzi+5lKTOQwVAtOc/YQbiLkQ1j2u3GmGKKiZmXuZzPZzfAEVMiUfdadQFKTO5ADMkKTAFyDiBWI62KEClGGUPcbIdhTExQqx1HZg5BYgxXu20plVodg2Wel8PhdDxMOfdqjjafUEC1TLNJSONmk4bhan+z3Y3LXGueyRFC2oxX6jX+X9y9ybIkyZIddnQwc4+IO2RmVXZND42egJ4AAtxwyQ8gWoQr/gKF/8IF9/wKLrjhiguuKIRQQDTZRHNqortf1ashh3tvDO5mpqpcmHncm/VeUwRctTAWVZmRMXi4u6mpHj16TlBOAjLitqxOYubm3kg5TTo7tUaEOIe15uvaHOFBzEqkbtZaIeB0PCX9kHbzm9e3P757L4SIdV15PtxczvWLbz5/zCf48fShtdqAxtz7CRExaMwUPa3ckHsZsgceDWAWTkk1M0jcq8NSyklVs5ZWTk8XjVlSnm8UwDzzJNPtzeH94/fTnFImj7O7Gpwcu5u4S7d/+Mf/4P2H74mdxM/nx++++26/Q7s0ommatbWw4tSFCiiIHc5bUfIpCPV3PDZkibb/frpZ/ibxhGv4x4tELCKIOvnuk1058CILok192SlobCXuwSM/4xjDL4ShyLhBckFD/WDA6CNERcDc+5BJJwkfz+su43/41//y/g1//cXrr778ZvHHD08/lbXJrA+PD9Uay5J0F5RKKz/+9JPYOnH67NXrdV2FhIJsPSnrlHf7/X6apoioJZJCBdSriHBiECKltMe8n+ecp7vD3fnunGYzJkczW5st5rWsLWWNkJxpnpkUrFPKzezpclxgFoqk0npEJgTBmUIIyiwaZEOMFAOJ6OmlaOoR0txbbQgws7K6ay211WbRuvlAhyp6CYSRIVwr3he8atuUs9wpBr4zwG+Pzp4OhLXWGSze7HK+kLAIp5xkp+ZtrWtrJgJl1aSsfF5O0QgUOZKZe+OWvFkJD51UWEspzq6TB8LNj8tpnuc0q5k9nZ9KqQAU0qyUWl9/9vqSLhTY3e6BqG6Xc6lu5C5ZsDKCyJmsc2iCQOLkPG6eIQbH4waiDc7oi0AlIeAlECDuVUAf24sx3o4A+TSn9rE01Lvd3e2rV+8+vp9lDkmsLMyt1uoFm8rYUCAnElFmoEWt1gEWJVXVZa3gQFeHieg1JwIkREwOCnLrl477mOcYawiC8CiA/UqkHGTJPpgREeROY53yi5ScsI1FUF+V/elRsxAR99EeOA0HgHG3CEgDFMOFisPCgr3fY+iMJR995XH6aOw+u9007/et1HneYZopQhRIYIAVDg/yNKmq7nezUaSqrTlT4lCrVtZmBA+UWo+nEwsty1KtTtilJHnKXmqYE1N4uA0tVQzFX9kaZeN3XsVonsGfccowQKqtIvIIkeeabNCs8BzoegZ15V6N5RS92N3A998Ye1+UK9enrs/TCMg/x7AG2BK9ZqQXR4Uu+NUP44Vx4lbF9vroKmtK238ZzKIqKqqsBDroXvfTJKSmi9fG7mEWlVNeYmmnEiV8sdqaA+Ru8Gjw1mOEEYLAEQ2wLpSuLASKhuh+I5uMTGu2xMVXX8+llSqkrJz3+eb2pno1M1XJJTVESFz84hoE8mbRAoYkkiYRYQ6eeBedZdkAoJVm2twMDocN8UmKTVPfaQjJDtH1Duxt5f7GdtwuQT9j/oI1c11HrTdx0Gf5qbX6/v2Hy+nz29ubL776/P+S70SAFt4oAMmJgOYOMggH2bZMgWBiHw2knloLkzAxoXMibfBi+nDlmEsJdCUQbL5t7s7k6BtlV7T0IIROSVgDcV6OIa57Xr1UWfEl/vCffvXqbVp9CS9mHjSpeW2t1tbca0Wt0Wq15rXBHU+PZzjd3uxFZF2qednvUqlrBN/evbq9eSUy5d2HH368/PK4oCxTnlJOsMY1QtxQg0SUkhDIlnIsvqaM+5u8+603v/fHv/jmd9/cfzY1a+fz+fHxqbllTkyWxOaJkihMLue1LkHIrJwyfLTto7lZCxZ1GASk4NSVuQEPuMMcHb+QnrAMKmw3+xvtVTC6xB9TszaQBQbSiIu9stq6/X0CcAAusa23iI3Vfl3cIzI8F9FbCN5ixksk5Nd4O9eVjk2xFIjuGXIVsozo7Rh6se5HrHrB5dn4Rx59ZoKIqO83XZwxhjlj9G2j2ziNPaCHHv4UwwdeKEw9HyfFM5ATiA0jGjN5m8YfdTWrYZN6PVF0PXG+0ZRiZEDXfZA2jtLzouyU1b4DmZmZu7euprwZY26j3oiITXVn/GAQHC/jeJfyuUKQzFfZMatVVD+hV42Duop0vQjsn/65f28ncF03jusJfPEW+v8HgBUROlQF+20egKOFU3V3h0ISExEMJEFE3K9DF3OxkfLDDAa4ERnCkIhWUpUpTaHeKegUEd7ltPo7jLr117giwzhhEBB6KEA8H1VP3Drfh1gzU20dYR109YB1CEOYIB1q6nGZiVike4aSeMgL6Tva5IkBACwkTBEw2hQAe6FlcAQM0awTKvuH92lxb1HWAicTMKxYUSg00pRUpzTpNGWZ+MfTr2hiWNR1NQOasUFFrXZrXF9sXb3ev7pJqt7CWr3CPsePJySggFIOChSTPHl4bXWfb2TKfXmLsEoS4pislWLNDVH7wMhWN/RdzeHmjYMhRLqtvDFEwBBAGDKsizDyNRIKbDNBm8IkOXVWZpDTaDf055v1W2zDq66nudfFvQ/Re05OvoHeIICUe9fdGMyaLaqbOcgJN7t5nmdzPy+ny3L2aEG1DxywKKfka7F+0P26B6noPOdpmlJiHs7uLQwS7hRu7haqqim9/fx1vxg55Xmfbg6TKJOog9bSvvvhh1Lq69cPd3d3KaWn0+l0Xp9OTRW6rPnNq9NyqdUls6TJws6XM/3w3es3r+5evbq526WdyBy7A6/Fz9WjrAjkGfMezaO4L27uaGTHI0Q9Cj99NATq23Z8PJ+eLl3em1XZ1AJhcCd4Ep7Z4rw+heLN5/eiqUFb1HWNIASTwb31mVZVTn1yxKMFgoVVk+4mFpwuJ2/Ozi0qODTj/s3+7RevdKbmF4LeTXfVSmnVrN7eq1uAYprSYb/fH3bM3JqdTsfzeb1czq2htebQNLtqiEI05h2nzOsl9GZmFjerbQlsAyzUZVWttbouIKC1SkTTJHNO05xV5fZm//R4LKVc/BghHz88PjxcTmeIYp5EkwbBAqVWa2stEZ7yhFvZiaRWg5FVWXklyvvpDuoTIScp9VL9hBqtXeBUWjBRAqt6ngJwzWAJc0MFEVKaiARBrZJbHM8Xog9ffPnF3d304SGYAlw8mGRnUqbdfPv5Pkigx6ePq1tLiQTs1pmLEFIRxSiLzMkhBEZj12kyDgKaNTJOEyhJYr29v005l1KW43q0kr0KkCmpCmfOB99/xvn+NStZW0tZqy+lVgp68+r27dvP/vCPfu/9h+9vb29S4trK5VIDWKpr1N5z865vPIoZepYJ3Rb0z7Csl49ty9zCbO/ubzXVeJqvI3w/25S2N75o9G/v3VKZ2GCo4aOHAUVdG319owkfSXgDpCsFjV8RG77SMx4PgGTsFgPfIveARTBxgpvMt4dvf/rVv/7zv/js891//C/+7NvT//3LH/96zgea/K/++pdQqNbDzbTbZwQ/nZ7s/Pj2/rPb/cE9mMPdba0VREG7ecqqIGIKZkuJpQDNBGwIhCdVs4/pxAAAIABJREFUZkqac8q3N3et2S28RpzWp2WJy1qX5XI+XyTPUazWtdTqlKd5kqyOKKsdvSYWckILIEahrYBjK7KkN3s7b8odEdbDi0xCqmjFvaMArKLuFBzgYMdqhYa8RUQA5huguN0RG0LIEdF8bCLmEcGyAWZdScd6txrYWhrRvJr1iITMmliI4eBaRTmnrCJe7Xw8r2eDAxcgwIKUkySdZZdSbt68upIiwdzWupZLBZMmjX420phP6KbJu5s54PDIu+zhUhW1NK8wECu6GmS3+7J+IwacyEOIDKCuc9OdVK6JMgKASGbVgK/LGt4LAQDMKl3cnZjNW63QTfc365Q52dpu8j7IRYUoVmfqeIdZ/x9RMCsngcHcQd2cpXMwmFNXqEYIwrpzS69RmbWfaB/dOw50tR3u8cdFxJ36FYotOwRigGEDWN5+5svqqEeMPibTHW97GhcYNJ3eBe0LtQ919CqLAUbzugEiw8vSwy1ah/Q732ycXwIxcqJpmvaHeTfvfvrpCRbhBm9zmu/vppRUErfWWrT9YacqwQOUJ3OW0C6yKcQ3u3Iul/VSzwuu9RRClFTZjCyGt0ZXPQsjdyISbOI713PQVwJtmNUIe1e86Bo8R1S7JsDPJ3DEqN9UXdCLNxMxOLDJkMUom54RslGSPVezLzCsnmltpU8v4a7hehAbfhZ8NxRSqfMQOgqD7bdT7xHQZv7QfSF4k9brI0Myq2TmWYk4bGErFlGbUw5iYudq9el8jsuIxO7wYghP02SxBlcLhBsiJEmecp4TyFsr7i6ZJ86QoCAGe8AREMpzfvf+He9ZZg72ta6llJyTCAfB3UstRELVK1bzlsCTTod5p8pugarNawSyAt37z926dkEABOZwG6z4q+dbh/LdaZPUJjA8RnwYGfGAIH1Ah35FAPqNBDAsHFYBW5b1l+/KP7m0L7+6//KbL3H4DmsNLeAIKE2JEGQ1KEgimj3jFkQeskHP6AGBusVEvy39Gb0ignvPQjb4BR2gAxE5BIiu/zN6biqas7CUpZbjcf78rnGprR5e4fVv4/5zutgHK1WTOGg9HwNmdjEr7tUNTEiSJRIDacb5cjo+nea8O7y6UYrSTvPMwlzW06XY3c3bL768ybvdzatTtW8/vDcOowThSAnRYrnQera1Pq2+pol3d35gSrv8i9/+6vVn91998/nNq1zs+K/+/F8dl4fmp90umXiTj/DLzSEJ77xyW0+rVyYWzlOSYl7relnMDM1Q66WZMzRNNOX904cTB3kLr1dw4cUsG3nf6Gjzs+tdDup2ytyxHeHgYIoGINxG5To+i8KDgrv5z3OkGIpQV3yj8/VHQbvFkS02dyuWwNWe49cCywsNqr5Rd85IxDYFd60dr4Sp7Tt4Cy8vkkLqMP8WZwaK52YbNoZNVx3j7iKMsnIIU8Qw3MGAXH9+zHGNSgPJGuj7UAwb7+yHFVvoup6uLYEENiJSbEH6eop7fMQzdQnotOJBs+oEZAeoj+aNQ+iy8de2zIbYBRBdDAtdKLNfu2FyuCFN1AU7wuHsLw9yZNCjkTQ+/Dd0hbcjpxfh++q6iK0j0n8FfRLin8/Mrz/59+dxrQLiBaypHYgBXcVN4C9Kh7aasDd3SRAwqSg0GM1bANRzYCF3RLXYRihLWc0kpcQiQzZLOPogg/sVHcKLnRUbZEgD7HIADuPeI5eeYRGpEnMfoIZ7WGMa8hzEMhQBGB1z82pAuHtr3QPAo0/KsY/NVhwhjI1ET9EzFNoWI9NQyvQWQWFoI7cYQsuEiHC0aiBwSiLcrMCdFClrminPrBNr5vW9QQEABqxYF1tPRziww91bvdkdZp1YeZdnt3h8Op2PixhoR1POmJCYaoQKBVh28/6wX5fzpcZ8u0NEWQvqBk65N3iFNW/urmnT0eydFQcCHmHREExKbBw2SJ+kzMwQ6lZHzIQxJUY0GklbskMQSCemEUV00ZmujkFMzKXrwz+j271cZCYOJu7956GyIFcbla6yxsK1rR6RUpLEMK+tISLvaX+zA+jp6fRwfKh1AXlwJYA4Uk61tcGpYDATJRmWF53D3+2GJFg4Cyd4ypiyqHSGhz89PqREX3752av7V/Ocm69B/u7jh1rr+XL+6+/+9nJef/r47s2bNze3t2ZWormgAaUZGY6nErXx7UTCQVTM3j18yAf5fPfZfDNporTnm7vdup7KirVEEkx7PdzOYG0Ny+rRYlIRglBqABpQsC7l9HQ5LwsYRKykAHv1znCGJStk3mF3XC5HEQQ1nWONbvcVwYycGM6soLBoDg/23f4gWZe6lrqyAxQu5t44gTLu7qc3n9/dvtoHtUstSYUTnRcuj7W1Ns2prhGIlCnPLAp4lLI+Pj2tS3VHGC6X4lRyxc0BsyZNrClH4Hi8HG52+/3Ova2rWTTmiTj3ecZm9XIpy6WHKDDHNGlKoiLC3NaLt2K1tWru3EkiTlCCZNU8l9bW0hK31lmUVHaHlLOqSoFZo3Buhay1JXlipH3e7SZVXtwdxQzVWgTMwr0QkyYQxeGAcTsH3LQWohAEhytRLRVLeXJ/NWXcHai1YDKgVLtQQmnrdLu/T9kIC2w9rsKqTKjEEXBikd51sZ4zCvtw1KI85YIa0aq5G3NoSjLvcpqVBEJ8ozfzYT49PC2X9bIWqkgZGVSxILvDQypp81qFjQL7/fTl1599/tnd//nwtzm/iQi3ePNmf3x6IkarqzuR8xak+y8e/f7Y+v/PZd7fveX9xj0SuLIB6OfV24td6hOY7Gf/NP4CAIPEMtjXUO6D3w7HcBfvsaAPyPUKYVTmAiaExUhSulJNl111AXkEPDzMXVQFE8mUaY1/++23/9V//Zd/9i/+TGS6u3vz+vRbLhcGNE0kbOFGbs1qWZTo8enxeDrl3dxRVVGlQAxVMU+aNWdGjcPU0IJQHWu1ZkbEbr5cVm8tLKY0tbautsCsZ9bVU2mFVNplPZ9Pj48n8DTtbinP+5v55nUhZq6TFS/VB3FDwcpuDIugiBrdW3uQ4axPAFJINJhbsbAWlYJghCjop1WIWTgzd28gD2AzI/q0d8qB7bR6eJCPUo5tGx3oxMMOyoOJ2CPcLLyPGXqlgBUTYQUlSRmiIiwUFE5pN02TTJKmPC/rxb3dzAdi7KeDilYqVRrX2vegVgMTKsrZKDFzIg6gWxNLwFGtGgxMxauHBTvP6tZ6iwoyGuG9Pu10ExYnkLuLDDkBIiIeq+MFKwnKycjc13AQBGRBTCqdWcTCrbhXq4shYcqTlXJ5OrVLmQ8HQyMjM2+LWfGUNM/JoyFaK2UMJHXdECZSMCSIzYMVDhaDt2g9i4oObbnxlu9JrxCImUivbUwPCLgPDG5gBm3awhtcs/3TNeMf/wdFXDWwmIhJAh4OG/Im3NXbMfzIx3InDxLzSizcJwJ6497cGoKCOIg7eRnMICBl3u/3+91Ok4KslmU5k7sxu94f7u9u0yRLWc7ntlTcpABHaUttrTSzAhVDpqRZJNdqlCi7NtsgQkKQd7JPlzLwMLcr/YRHawjU7+BnKGr8oa+HjRMxiKKfBka61oXPNVXE1kx8UYe8hO/7vznw4t9fXIMXKf7o23+CeY3U/zmQviiTrlXcwL6unQfCyzB9ZQH0D/YOJg7mPoOJBETkDALMrARac0R4WFsoFZ1jx7M4qrFFGBIoQya5S7c1l/VpXS9tRJUGhAOswhDyPtHNgCJPaZ7nlKTYatWMnSGSlTmInLvORSARJU73r17BI89TMJrZpS2rrWYt5wTl0opqokqGSEk1TVlUIdTCFvPWWm2B2M2Zw4SFnLz1nrYzBVEwj3nqa23QL41vc+uIzj3lIAfHc+OANvQKuLoEcnfPECbWzumCCtyxojRL8+7128+//sXu4y+tLmdiAkujAEd0lwVxjCq5TywNdSRCp2BGh2H75FQALIBcPX87BNfv7QBozFH4oBYSd2wrRJOZh9dqjYR4EkIqcfHWcB//4B/dfPX7h3S3nk8fWuNd3gfwdH6KVlMmIo+ACInO8NRIieJii3Kap91ud3M43GI3lZoizlmVgOPTe2aap/vdQe/e6P1b+2FBfWxoDYpv7rCuaAUmwB7zHpIhqbx5c//5Z2//5E/++O7VDXE8HN9//+6HP/+L/3neYT7kz+i+0fr2yx1Ra2uvb2jOU81khYRYkmTNOZfwpzNqa1gvqGVVKVlyTinN3CVXwim8z6gE98GHsVls0HVEr6bI0fsQ6L7aLLQt+M7a8CAMc2oMoKPHQ9+Icr2t9nJRXjOm5wgz1m0vuTrcsolM/Z0Z28vIEAjejB3GbTNCyRWMx/j8YYjz4nOYGDxsmkZlyXTdNTpws0FUg9Y5vn/D30ct+yJ6PUNVAdoG0MeSG6/3cAZ/elZwNWUcXrjPOD4QYW4vT0hsodi96+ANtZvegbuiXUTd83C8/tcpTgCo5zwRGEZpIAw5DOkfGxsb7WdpcsDdn3si/YD9yjL6BHv6WYrd8/OfJd79r1dJrOuTv56fjxry7/3j5ZErIL211omszEwdZmIKi3JeBy3GiZ0TiJWJtW9yziSiTOJBps2W2vXJwrxZ8wgVYSVza2YgmFkgOIkmrV76WRyDYyGDfkNozdE654m6zlRfeIPzw/x0PA+bLEAYWVV3ibi71IHCzYgUjbqDQDN77uc3WHck2dIkouitVAZ5bTXCiFiJg5klsVA3qHH38DZWlAMMgQLRqKNj8DBQUGJWCvE1FnOyqpVXdvmj3/8DlQxDOS/1slpxuAV5PsyvP3slO37/8P7h9PD48MCic1Ka0rrUWpdlEUmMIHZvrYSFq/Grfc67uni6SXWty3l1NwUznC2qWYtGGgxm2fyl+vBT6002a51txSDlQYXVCIFLQKlPsmwpUxfYCAZ34dpe0nZdPDMboxPee0qds0mqGtRPmw9ZUaIQCmZiis2D48pK3UgaQQHnykzwaFasE0EYMuH27rDb7U7L5Xh8PB6PosSKQFhAGFrr5VLv7vdwbMaJ8GgecVrXIIhEVrnjmzlnt7aWYuGSJjI5Py6PD8df/s0P03S7392KIs9iF7ss53cfz9//8EMp5fHpVCuOy8NpbW/Wst/tIUmzltKeLsvl8fzwcCwJrWpbjkn2hsoiJK4zu7bKITPuXh+I8zzXWhwmWVOedSntdGmnSyUVnVXoRkJLW0deiLxcyqjESbtMiKMBRCRMuZxbypFSlql++PC4v6FpP803d3xcnh6Kh0F00iQCD5jX2hoYSBJiMolSWJTmjghOSBmqPB/Sm8/vbu7noOpoQV35T1uz88Vqwy61Xp6qUErE7BZuXtxrSpxTXi7L2FP9OjzEzMKkOV9EKCXRlOYdLYXMQSQakicNy6WUUgoTmCmLTDnlrnsW7jX20zSneS12OlcCUtYDmgdEUpr2SK3Vldw4YIZwRHO3cMbptD4+nM6n9vi4mMd64TA73h7evn017fhm/3qe5+aXtZyIH2v1LtczKZhE7iWca7FSIhxeqRpSylkNSPN0ZsLl/DTv0tdfv/7w8b3V0ORrOx52d8tpjWna7fPb3Su51e++/ak9NSvCoqAII3O3UgfUQtwF24zgaK0ZNIi7k2ewQlVAOC8XEhxuDof5xop99uq1F3s4Pj4cH8+X4sdjJL+721ldZ6V5TmuUiTQJPr+/+/rt2yQyp1mQv/3rn375tz/eHN5Yfdrv963w8bR2c6znInyYLvQhqReci99IocK1HU/w6E5HfXW/eMHICX5jMnVth71kDbzMb2JrP45spid/jFBCL6C3luToMgdDgp09rNdkPRsHbfJ+YNuKOXLq3ULiYKLiLYlGtFMtlPn7jw//27f4b/67//Yf/s6X33z5O6f1dCofP3/9Zd5Px+V8XhfD0YOsLrPM3//00/6w/5M/+CMhbpcFLayaN7tcjkTY7XY5a6lnokhJdrucwLT6eV1LKcu6llKUmJkjfLXLuZ2rLZR4P+0kManQPF/MQQ+lovnaIrgVaNrtk5KuJyxuPLGTRUAySZZoiBLmjrUESx9ocESMmXlYq8UgLEHU055mTYSJSIj7KFZIuHm08LbpSI7qphNcRyHf4y+jhSMM0fNvH5c4HL2a62MKzETm3YeHd+Rh0cK4sXGXHRjiSiIq+bBTgSQkCV5Oa7n44/Hp/bsnGPY377/86rfmw6RN1RMrZ5nqFCuvzbx58SAHdFIhMvPEqpKOy9HMVPlSrYVBMB9yRG7FWnMgIB7ejRsJ8NSzW4qw3iXvrIWRlvvGbghgXQprdrewrukr0BBhzlJLNUZOTKRMrZS2v9tN03w6nk/ni4Qsj+fue+PurdQkMkmeJm0tCsgMiP6vBBAlVSY0ckTxtkYTImIggbqWivcqtptED0kQwEezRwhAl7clchuKtQAFCTPxplcWtE2abJ3pQWXvzUdzZ+4Uj+hZ1oZhOgeY5dp0hkYf9vBwi3AKUgoebWuPiGEpM6zoNUGEuB8nfMp6e7+b5/26lKfHp1oqmjezeS9ZVTRrkmIXkkgZ05xIVD3tAt4lMJwIzMIiaflYgh0KgMMMJGCLaLWh2iohROTu5oAjnLvUAkFA3IepRjS7zpBgjNxcCzB6gfF9GtYAsjEIsKFgfqU2dNDwGUncisghV0VdWOc5Tj8PD9IVU3sp4T76Ds95F/rF2Zbry6cH135jJoyaelvBG45FAMG5T0l1KXEmppQV7ADc3MxqG7dfQ/MpUsrVS8XaCUFNm6K4WD7k/eu52tEv8NWZiHMKx6WueR8s0WEYmTAlTUxRzJvb4kEh5r72tnY0IWYPd2FOUyLhx48PH44fA7C1ogEJSNjTLKS1VVR4IMSmaZ7TDPdyLGtZjk8LYceIlHGz28ONg1szN7/6uTF3NGjbGEeYG/1woENx25AgAWGdozhaOBt61UNcdJ9OJmNACIggxyTQhGg/vX94//FBWX//j3/v39S/Ppcn8jkgFhUcLNz19KMPDoMFAjBDgRYjDRrwCBrAQYyctafKZmYeFCTo2XdXdhpEzAEoc7+pSdLkbHGprTXOIlPK87SWI7/Cv/fPf/Gn/8GX8+tS6ceJqbnVKNV8bQXhu+kmcbiviRJc6kqtlPO5PJby5s3ru7tXbvz+3fHuJh/297VJWR9EsdsraAnS3/rqq29+56t/9u//Y4CEp5z3h5vb/+I//y/fvj58wTKlw6tXb7/58nfvXs95FxZWSj0ej//T//q/l7amnC3awxEt+MNTWdfjvLc/+Ed/4NU/rOfz8akWbSUl7IW5FQbp7e2d3ORdOr6XD/CnWi0MxaLYWlqVxA4K7c7mIOawMHOQIa54yzCSI3MmEEtPM6JzY9nDItiHBjOru4d159URJl7A0xuGZV2JsIfnjZs10GkeMTlAJPycTkWfJ4rt/vzksa17ouEpsf11BLZRh4eNbGqLEBtI30UupQNsLArQBvcgosFMecLWDo0XhxvPIPuw8QE2bhKeR6rjZbI4mh7Pe1DHs/oe0+vVeB543F57lW3dxg977/YlyB8vtM/d/eqP0cNpKaWvHVUWYYNHhJl1EtYnmuvEiH52EIPhGAP/Hd80fmTvVxD34NtVTzvVZ1wF4msu/An4+BtRs+vz15/TNdSvqJyI/F1v/Pv/uAJwz7tbhHaafyD67T5u/W6eMtQ0AwyncEQTYRIQCYkLrBUn7rLeIWJscIP1vRDezAhCqWuQ9Gvi4SQMpVEgBToLmjec1z3iSpi0fh8GxiUYd7KSer87PAIQEc0ZrG5df46ZkUgZaBXdqgwACGA4DORju+gbBAbBIHzQG0WCSIKFuI/QjAwdm6M8ukULEAQWMXZE9A4KE7r2BAtZ2KUVgcLwzf0/qE9tPS+Xx9P5eCqn4u5CHPL49Oq0v5+huM13TMngiaVRc68pp5vbQwR5iWUq3ohCprybDvnSLtGsYK1eW1xQUVQmIZMwc86SJYnwul4Gr1mIlDsyGIDDDMQMZpgAQRCQdGGvMaHb5cng3u3GudOme2wcZ9+iu4uGRwQPt16AXVm7Pd12lYHeDeinSbi/R1lGer01dsFh5ioswrU2t4BCZ8y7PM2TqFxOl8t5LQ07Ve7dSLfarNtR3t1f1VRH5HVr61JgHlF3k85zqlMqp/Pl6SkJWtwcDrvHp+PffvurWlHaaS2eZi1+QNRQX2r54d37PlHljNZwWctpXXaHA2XROVdvzRo1Y9baLo8Pl7q0nB5zitu7+2mXl7oSRWlri8i7fE+7w0HKxZeLWW2gOJ7Pl7WcT5UU086UsjvCiRmWwWCzAIGU3cyNRwoSTkrkHCYKIiVNOJfiSPN+r9NkxOeCaOwWEeY0tDwZEQxOspRFdixZ4LDmIBBj2suU07TLeU6sUeri7EG+1pY5arFSAHQ9uyACa99k3d2IortgeKOUU0pJEwONEAghJCYBeJ5uIqRWV1WRCXFupYBomnPSKdxVKOdO7wyO0MQipAolScxJ1Z3dF4/FrAWRKBM4mFRFiJtQ1ELemJGnlDQTSQQt5/Xx4+nx0dYVqvxky3JeTu+XVv31ZzfMM4mIzDl5Tmv4hdBNhZyZBWiNwsmNLHi4SwVNKYPssDsTo7bzQW9ubvbu+6enE1GATTJQscZCpPs3B9lrofXDd0/Lj5bAJBzu1cNb1wMgIoZykLgZwNUq2EQYTCwg4oCfzqXasjvsd7v9eqnHpxMVCEmETvnAKd3d33z19efH03uiYAqlKE6Ap8T3h8PdfNAQxWSF3v94+pt/+yvhNx+fcDcLBY9oyWNEoic8Wxtj/JmYhoPry41wK2r6dvOirAIInXY5so6fA1/XlEnCai+Kru0KRPSEbntNPNMARjIWXQCFggn2gksQQxR1cOiDMPi523d2/grRAOLJLTa1kAgGCY0xuIjTsk45hWa08t//y//x9vY//Prrr+/3nxcrdzefc0IxPy3LWlYHhbWzrQ/Hx2+///6f/5N/lilVcF0LgZa6Hk/H1qq7mafHjz/OuzlYg6GsiULd1rWY2WVZ2COnZG6FinmprWTNgARHkM9zmnLOs+YELwgrrZGbIyYwo6vucHfXie7bDO7gn8M6yIdB3Oj6HQRYgMjVt4oZ3ecaBJcgJlFJSRuaXWUieQAd1+vSn2NwUMACw15tvBzoF6u3+KO3f6LFGNBjhHXDnmAWScqZwebw1S6slKfbWad6tuWyoHJ5KuWx4AIw0EDK77/7qFlDPTRu893N7e2rV2/+za/+krRv8cEiOSdhrtWEKIkWq5xIOlvZLcApcQRVt2gVgtEuI++qO9f7nZ5v5o1jM3CdQcrwxX3vQ0yFoKo1gpSdgMThbuyhoBAsLae83+1Kqcu6HG5vnx4fgc5JYoVMMiWWKNaTMlSYBCUPp3AWJgqBwPuIjxfr7OMgkEMHogKioIDElsEEONCRzAhjh8ExlAexUbu6aHoAzLw11ccQKZ6XJRjoEpmD096pXghi4hj6Jr0pxgIID+mXIYseeZp6I31rdfeNBqKkKsSmyvOcI7y1qok1CQuatfP50lZrZAjkic0rJ3Y3ANPMmklynqeJu1q+odVWqzVzN2+13N8dlks5tZObEVEkYQpNQkTWnHtHwV+Etx4hRsk1zsxGR3umYD1HuZ5sbtjTFcMaOGAAL3vjfd1tD7zA8a//3erL2C4ENp25AWm5e3SJtK5z95KbMU7rcw0zmA49yetxkrYadbQOttdcKx8C+thsXwMEkAd36SdmYUnd2s6j6wl2kuYOnFmTpKTkbs0aGjGSJDc/nU4TMgnt9tPqta3ucGEJd1gzBQlYoMKSBQErZmERJo2dESt5C+tUGIvgYanWWguP2pqtFVuEGZx7ICKExCy8mXP4FKHw2tzNi9kFiIsyOzGmIJDVliPLuPJxJbWhI1k+sMwB6l6pc91ejXwsKhpxuP9l415Fj9b9UZsBzmSa1AmaUrHL4+PjDz/9+Pru/v7NPt8S9qCuYFVDUzdboMSpXArpmOQUUTcoa7dy901UFOgUVDCJiGCUUy4kXRMEPgLE9Z4mZlWKsI6oEpSmKdgMFmY16vyGfvv3v/yDP/2Hr7+Yj+VvPpx+kMQkubTaWrjbbt5N06zs7iTOVqnWejqtj0/VE1QzgT+8P55Pl2++vtsfXk9pfz49ECwlVqE84Xj6Ccvjbr7NeSZOpZ6Wdz/9Z//pf9KMjsf1dCzhmlJe6+nbv/2by2WpLT5+fHz38f1nn30B0mDKGUB+fFysXWRCK1oXKWdez7JcwkvXIp3KpVFQIeTMk9zcHyhcmJ5aa7XGukZpnsmjn2YhMg/uko4RZAS27mACe5GysIUxqMsTjwnjcHP3gHQrO6MgGi6fzH337YxyOI/cqW3YTecSbOD0Mw10iw3PAegatT6hPr0MDAPXoPElz/3CLRpQV2/7NMnzDa69PtfzDSJwdNfa7h8oG7B0JVhdKaVbIjZ+w6fkI8TzseHFl4x3j3C0vWTzYe2IxpYIduOELXLG9Rs74vBzPcGXR3j9ao/BGyahviV6n+P65JfTdtRBLwfZ6MXp3R7uQbGRIge0PT5g2/p6ny9EPukrXL/o5VW7nrBn7ekN6PnZo7/+eX/9tc/82eP/M+D1cgv72Ve8NMD9d/3klxcFgKaczZqHcR+YG1DRMIQeOY4hGBXRYuXGnASJGTzn2QBmFlFVouCoLEEiRLLNiDEiQYWqla6DaGbkDKZwC+80EhB5BIVHK81q6yu275oOwLvmeHQu/LSbm1krxaqZo7rBDB61tegOwURMxFm7kKL12VQmKHzjrvfMyt36XJs1s56kMJyClUkoqPfXDOwIEpZAcwcTCZMqu4ZMJBzVi2QNitZqq02T5KzBMLfL0nDB8m59+O54fniytZWlWG0AEDDH6ceyu0nTbp5uJ77VNDs57fMhIYGs1lYuNQBICNOUJ2a9lIulRhzHp0fJiaYkjJSyaipL8bokzpzZLZwdLSKgokJi5uhdR0aVAAAgAElEQVQk/CAAQkwUzmwRUJEkAVh4IEg4Irx5hHdXFRZmlobYUhY4IQTcdfpkqIRERLS2289wJyEycu6a7gFEJ/eJKgX1ATeMFeURHhThzjr0hcXJEZo5z7K/mfOcqtXz6VybTTlpyppEE5vXpazmTYHlvAbAJMICENysNqut1TUcKtTlWp9O56fHjwTwRClPkqbD7WffH98BjcWWUvYx73apQQJULfrAhzdPCYZaWz3c3uiURdLj00Ot9ubLL83a5fjh8eNPaG1ZQhU3N/vdfvrV978K4LIstRKJ5P08x3yi9Xx5Oi+XZpYnQCggD8cq+bi/vS+XSsFCspsyg0HQpKzSLtZaYxZSDhgzaq1gWlvTFlFDBGX1dWlOIprefPamVDs9nks9oUFFSEmzBHn1+vnnrypqsbK0CsL928PNYc4K92rh5+VkpMHGSvMuPzyewKKa7m4nZtRS0kTd0HctC7O4hQgfDvP5vF7qRTjlnFLKtZb1cmFCTolU3dAKrad6efTl0KYdmbEbiVJOkyovp2NrlWionhgqWhHOOc/TlMqlIKJUP53Pl2UxR067+XZHzJw0KJqZtaoUKUlKsj/MKWcrdqnL6bReLnY6ISmSZjfmyI8Pa/UfLms5X/K0o9u7KQB3Vs5JJxEZzsRUhcBQAVWKVuHWGpAnBfz2JhO5Jk+C/U4obi/nkxvt93O1tXq1VoKxn/b3t4dCryadP7Tzh/dPSuIEmZQ5Or4eJJLUO7mDAe7jN84esGjGGlNSrU284v0PD81sPRYUFpG0SzKL6BSgy6Xt9rdh2S9neFNitHrQ2y/v39ylfVz86YfjXl7ZSR/enUT2uODSCoFJdZrypT0M7QTfJqa3gbBezZDADeHXdLjvLhgb8M82RwazxHBC7pEvrtVUbBp8G+WQtuGXgSYxdROKXuyNaXe6fnPfJ5jYOxsGm/L0OBazTjMBEfWpQe4CqdccjiKcQehGEAFDDHU8SWIeAVqswfhmrziWv/jLv3r7xRdf/+Kb+7u3i13u9q+KL/uptfBTOa/W0jSj+Xld/+qv/xfm/wjgpdZaliTavL378A6E1+tye7P7/odf3d7e5rwzYpIEzh4OxjSldRVYI0ZZ11N5elwfL2Wd9tP+bhcKUlnW1bymLDe3WVcHi7NeCq2lLCevF2qltrWGBxPCvZTi0VkuINXrGEIERddAAgwNRBQUm2gFEay3ZY3QDRqJWChlVQmz1moM2NCvgt+biPvWMyaCCAtvzDgM8JGG9DnczAnS+9LNwxlCktO0z5TJozWv9VJrsaZ1XfHw0+Pl4UJNynFBCEsmt3A7PSx4AhhIyLNwk0nm29+6M8O8T0LCYFVlZqtGZKW2da2dp2zhLEFEU07TNAcoT4nj/sfvfxDXaAEPcoKNe88jOmxO/f4kaUbN2jBXhQMmrPvdzr1dCAjoLpmbC4ihU6qtQuE1zBsyUs455/Pp/HR8UknrcRXqyDWL6tKW1nC4390d7qY0fYzHZrWh9Syqe4UTU7Rwc8jWumXAeysZRCBhj3ACcXc26Pu4d+w8s/LEl2Udy4ohyqoaiOo1EKoJBu8iOxSg6K58V1S406s9uhtbL+IDIBaigG+OfqIcit64vq5gmcTMogydEQg4SIXSnHLm2tzD0yQA+9pIgpi6NsVSWkqUUmKhea+tliS61mVd1wi/u3slrOiO9afiNUqpgGtSUQX51199+e7dh/PTCavFrDllYT7sDyJ0Oa2wMOvtSwLHxonYisUhhhQR3ToMiHju9m/qbtdMvmem/fR6aS/4WIQ+jrDRWl/WGFu5dW3zOQljUxF0hCMiggms0jEjIlJV4TTIbC8k4V8WORh1zovigMavcdsyvYFqUc/en0tjGi1J0g0tUyala5PAzLzr+vCmEQ4PDyVJ0xxhi/nN/ub29lCXcnx3XOoSFwdxnlK6QxjZak4hmnQf5o0YmlVEainLxbtas5AIMTXurgAiXdyjN129llpsCRvD5YhxSxtaKyaAqrYuXV6iLiXM1nXZ52k3TXzgh8fSzFW8rksSDfZ5N5cUPVwoqVVTEod3WIrBV37jqFe7fC+2e2OgV9TBLtpmQaxzNGggkilNPY3Nu2n1dTdPsNy8LWuRLCbnV293Vu3pYV0v5u55P1Fwq42Zg5MkseIgynNuxZJwWRq6gjtTn41HG6aSXoOZhZJHJerq1n3etzskx+h5YCzzZpVCJM/ztItYmy1GgcCf/tN//Lt//OUXv7hZyk9P548B8yCrpVYIZ9V5vzuoqLAR1Iu5R4R5tFrxi99+m/N0Oi2/+u7DT+9Wb6tI3N5pkrm2o7XGLMyeBUFW6/tasd/td7tbkXTYf9ZC11raw1rr8vHh/ePT4/uHH4/H01LOy2qgdL6cwdLMyopwI0OriRNdTrg8oS7Ji5SjHR/M2woPa8Ecp4+P07S8fv1qTref3efMealrbdUd3vDh4xMjOCi6jKt17kLXWegMBgz4ibpEe19IAYHX5uwmEs3RDLwJnBORcIe9RNiDvG1ZDtMQjO8Pv7L9Bi4TiC7pGDTGDju6vOEW/dI+t1roBbDyHAoQJF332a/p0fjG4Ojc6dFj7IqdAR5afB2V6De2d6PbrZGz4VxbcHsZb16ARGEWblcCapdL7F2TK+Qxmid8pTj2SDuIu9493DA+08xfdg7GizEErfokcPhgPGyv/AQiIcKwLtxOXX9BP5aOmFxBsYgh1Ejx3IShTQ3Q3XvuMSAsB8IHXvyCY8ZCeKGxHhG8HU+8IFVtPz1wbdAS1nUdH9J/oJmZXU97HxL89Nf9Wnfk08fLJ/9fwKZPD2m88Uphuz7TH1cA699paPHle698N93t57WspYSHq3DKOSJiXQKI4Ks/4HUEwOFEEAE5Djc33TmSSBCIBBCUOCkzUx0ArEGU3B1mXSaWmaWTLEeNsU2mhJkNhJhIWEUk2AeKFGFuVMNbPdzuCUEicIfF2pqjiCQzCw8P65rw3QARw/cHvG2iQ/xyG0n14Q8d13l+FjK2bmoaHkHemfbgbfFyUGLN6lMgEeXOyIhmVbOCCe6tNhZn4cPkOe/+5v/49vJ+9WNBAwzMmPL/Q9q79EqWZWlC33rs8zK7L/dwj4iszKysrEwKUU2DaGghNUJMmMAMMe0ZA34VE34BTKCFYAATGKBuCglKpazKrMyqjIe735c9zjl777UWg33sukdUVnV1Y4qQ/N5rj2PHju291re+h4rQWkqtmOcyc0F/GN90ssfV3f7m7iamejg/Hw6PT/eVRvQdd9o5l2XNp3KcrnecaD0tw9W4HI9dv5uud17jPJ/hMPKlLjYXSogtFMmb6b03wQ2HSJMB+rbISEtEauVnRFhYW1MRDmfUCAp3Btqm1oKNGCEBZRKBhDWthMF2dfsIE5tRre5ewxrFm9xa2izVsFb9BQyERjuXJI0hwF2kTnbjqF0rQb2aFyvVnUPcgRAiVeWeKGBMOM8zQCroE4twLWEVAOfiXQ9RrdUsoF2/29/B85rj6TAP/fjm87fLGWAZhm5/dZX6ntjco3qRRNTChxhBcCAo+rG/urm6vrnePY6H07zfDR42dGXscl4qIl/vp/3VcJ6Xx6en4shGEWoOqyWfy9Pj/Ph0nI9LqXXo9epV108qxY6ns6aBgr3WJN3Q933qkyolgjEElb3RQCtQbYV0QHjUnAsF0oDq9d2H537odtfX4zT0oGk31jot6+k4nwkQ5gjA4KkOfbru98RsUYmjVyW35VS6IWkv5/UMCmJKfWJJRDpNAzEfDuf5tPmyR5RaC7MQkUqXUjdNYuYl25pbGGMpNRNz11kpUVZ/fDwtq0cBd7i50aurUbuRhWquCCGWCJvPxQ2aMPZNOWJA8cC8zgTNpc4517pZPaSeicTD53le1rWUsutsmni3H/uuR2BZlvN5fvww19yC6WHViFiEwZjP8c03D88n2u91XvphkAhTFeXE1EI93NHclDkicrZlmUuBKMaq46TD0GsKYpum7u72WvXc33On+/31/vn5JFo9YsnL/eOHcT/dvB7vdq8Hfna2p8OJXYLcawvNbKZD7mFBjgSrKyUCoZpLAgFevOu7/Xg1z+fH5zkp6glxAhjppp94MqvPp+ff/NXX/+E/+Qf5tKjqXvvVjDK92d/83qs3n023v/3mqzj7xDvK/cM9ojxKl8q6IvVp7DmxdkptlN+cXy6DorYHBEBgRssiexmUxdbUtk3h0+3s5dG4wFbfBb5eaiQWuZCrtmrsk40QL9MjurgEvNAVNpCEHGGXLJ22VhMTAiRNxYTG3Sa8iEAQTth0attYzlvD1iQrxKyJnKlQHHL9/MurX391/7/8b//rz3/283/33/+j6+v9X/7lX0AocUm8imSNUKGuV8/1fEaGPRyf7t99myD7cVw9n9fz+XyutYA/W0qm8znmJVuwJtYxmJTTOIxgLKdzrQUUy3p+Pjwczsd+6Y1fTbf7YRofDgcwrq532nfrWnO2OXPJsdbqa9TVokBc4c6MBIlgbxJxlejWMHc3bzot6YjIzc2teTDAAgQob6ilAYiKSkEQVe2mITFzKeV4OJa5hF3mtluDFN4cyQC0aCZhZmSvsXm3g0HCGiDfOFoNI3CnsEbRtai5MjEUouKsEXb/cF8Pxc+BCmRBFjAjiKDMJG7mwQwz5Cd7f3qcc3lly34cxv2kqi/krxJlnucI15RUkrkRUGolqdqPrGTm3ZB2u6t3D+8k2Mnq6qjNhgASW08hiZklgiAizl7ADCiHU4RNV+M0TdlXCJDBAukkwqXXnJdgUK+wCsbt7W03dk9Pj6fzUUHP90+RrdKlwmuRxwnTNPZpIOY3X/TH0+H+8bFZd3tAEAQyc7OKtJFoIsBCH61BWt3F2zyeFU5oTYuK9H2fUjeX9YWBRcKsHAjkECZuGE3j7/in32IDOKhZ8GxVliM288mmsuMQVUYw2Lmhlk2KRaqaNJW1uLtbm5uCABIgbZSugINRLHd9kiYvG/pxmo6nORwhkUbeTeO0H8fdIBxdl0TTvMx3N68D+HB///RwfH7MWNFM8KZduru7vbq+Sqqdys3NddJ+LWuQB1OpRqSaFBRiFWZR0AgRm1dNUIS3MWcjd8JxCfq7qMe+W/B/Ooe/tEP0qT8WASKyIUgf5/DxMjRvKYwRLtpF4CUxsN3TGz7c4muIRBUXoxa8MAv+RmMQEaDW835skwItI+ll1P+d9wEEmJibgwhIEUxQbtLRywtehhuX4xu6wSmEVEmEaTURk0Q9W5LqEhruFuEefd9fv7pR7ZZ5PZ8Xp5DJc13DnLcY7ECNZS0irKrsrXMOcERTEgAgD6GWn97ITy3DYNRBVM91zrmgFG688AAJknZEYRU5St/pMHVP36xISKJd0kQ8jsPVbr90hgAHvDrWSBMxpHi95IRc6MLRLKjbBhXM7ISL0X9c2KfbsEYu31KP8Orj2LtTdbNS3CtC+6RmmYn7sSO1H//0s6ur8S9+8av6noiilqoqKqmTRENVTjWMQEqcJqEI8nQ+V68hSqJCRo5QVYVGoPHyycnMAQgxiN1gxSVcui7CLPJaVubQnr0UtzDjIIs+bu9ouqV/9B/9GzrYcfnwOP+18YkHqlYZws5h9fbqbhz6LrFbXpZzWZcuDdNuJKh2889+/pOvvvrw4d3Duq4qeHxYfoWvPnuze/NmGoerY7lf11W16wYFhZXzWpdAr51dXb36P/7FPyPsH97P375/XyoQKBlrAQhDP0gaa3UiPp5Oh8N5nhHwdYUk+vztm3XWnIe84Hwojx+Wd1/lsiwtXQRKo/Z9350fltdvX73+/FWS/nB8ep4ftdfUD0s51czZa9hFL0zNksei7Q9NYncB973R8AggpiEBCDdYQ4rCvFgU0Y5YmGkjngcLkb0Qh17A8Rfcql1rtAXavPz6u7cL1B1NBPoxxuGCXODli4+AOzhenilePKvjhVS0favbOoAL+rFVaw1IutRnDCGQy0Vzs9V17iBmuaDjH0lBgUs1tx1iQ6U+QUe2xfNv3Jg4BI2IeGnuP0J1Da9rsxbRpgoPZv5eBugLSvJyVC9BhVude5kHtB2wwpg/oj8bgBUv7/VlZXZibsLmDUOIbW7DLWFlMz3bYPBoabxAM+G/fFbUsLAXUOmTUcR2/C9v5HvDj8tH8523+fJXuiBq38OwPh2i/Etv33vspzDZp6/7cm6/Q7T+e9++9xDFZo0Pb7VG48q9LLLYCp6Ii3sFAeLiwqCylg3hcEbALMjMqRFvBObVq0XVlESk4y5ztfAQtggSbs3OFkAYm9t6UxyAmkWTOINYgIhmq0kBRLUaAWImuXgOtqjbCAtnb6m27cDCI9pAeANZGdHkDW1vYXq55BqVV4SY1cldQlXCfbODEEY0zjICcKqhqT2k4ebRrBNB0qzrqxGzEvdDf9PfffOrcx/9jIpwGKKAg1KvADqCswaTiuTHdSn51U2fQrNVAd/e3Ljfk6YGshlVJAJAimHog4PEQFht3fFEAosMg2t0SYG48NwaqZH88jYNIezWzspFN93aUGY0m2FcoOXm5AtyInjbeC/4PqTVJxHcahpGEhFxGNMFfgYSwUPc3WqLTy1bWWP0cYW8XP/92J2Ws1eoYjf1++uJlZY6Pz0/lRJBUE3rXMKZSKGNX0AAhSAXWA3lIpOqqAoLKyHO5xMgETjPS0rp+uoGu+tlPszr6ekwm8tuv/u9H//ELIjRJfaww3muTiw8DJ275VxSgiirKBFyyeM03e132kl6PDydH/su7Xf9q+u3iW6ZVlF0nT48Ph8Px5BedApIQEqxh+f58fF4Ps1rCQDsRdM0Tn1wmIMIVm1dlz5NqetUmdrJB1ipI4UR3Ig93LlTZnKwBwecZRClXPPxlCFzgPph/OKL14b89Pw+Hs/HEzw7Aqi4X44/vHv9xQ8+G6bheDp+/dXXD4dnBbvVqZt2+50WmefjWvK6uhsRqTnW1ZZlPa/oHWLNSgR9DxEJjm7QrhP3ONMchmVelzkDKL2tuXqN43GZT5uNBgWW2YnWlBgCuA1Dt78axnGERbGaOgwjuo5ZnKUC1E1duDjzEERiVrhafXz4kPrOPU6ntQkF1IHBU0rM7Gal1FzK8ey7EcPY14J1KcUjaXf7+mZZ52w517Co4V0tOVBFk3mz7zMieFgLOVVlTYDUqPBAsdp5l7ohJXFgGse+T+dZUupaj9L3w/7q7ng6PR+Pj6dvF5vArybVmzej89v+/eO3v3zwYuiAWhGACERbGhCUIEi9hMOrp9RN48gicCSS1N/QkABe+7L62piGYdEPXbCXUu8/3Pt6upuG/bgbvIbwm6vbN7t956jHeZeGfbcfZTifkE/l8x998fw8O4M6WvKceiULdyGyiBp22Yu9fduxJdm/bFoXqTVtFpVb4R4X8OtlurXtaH+bgdZl/70UbE7glz+0jaJBTOwI3kq4bS/ZmPmfKNk2hfrW0bAjKMwb7ubE23tAS8cD2IM21i1AwbLlpaJTJpjFuhZ9/crmw6/eHf/sz37945/+4CeffbEfbo7lmQwUEFCpa3Xsr+6k6+bl4Rzlq3ffzsfDqJ3VSkSp75IV6kS7NO72qrpmW8ti2SAVoHGYUpdSJ/PZA5YSvXnzerxOD89PoejHngjV6rIuwTxOfRqGeV7u7x9rhhe1FXUJz5Igqmy1MFxcrHqUICJNuua5cfsp0HyZmFAjam2f2EX33XaHtll7s2K2iGBiSlsETz/0ZLR6JuLLIHXr3LbJJFOwgBnM5LUZQ4QjOFSatFE2LpYgWIgd5qgwcyqNdk2sMe33Pffz45xr7rRP0pXsOS9I7NkBV5WW1CIBSTBBJPTa9d34oze/n7Eu81JKUdGkGhGpS52kYejNMC9Lp8qGEnVd53leaqldN6aUknIUD5gqiMGOqFRLEyYwlLyRDVrsGNOGzjTrZAKRay/j9S6fFmJ3FBYGe6UacC/mnY3TfpzGNefn8xFuLJQX6/pNubfV/WBkf3r3fF5m5/jBj3545pVFUtfXalZqdQjYYB4FjTvhAGAbroHmLEwqzZmBiSQJUQ0HGJSYlUU3bKXRH92tVgScmzVOq0FbjuE2bXyZg0eEQzb5aPBl8N7wHIpmm8nR4qdpIzm6M7OKdl23rEsj8bWhN4gQlFdzC28hy4mIqetTPySmTlRKLYEYdnQ+R5BJknE33FzvNamHD3mttaau//Du4fg0z6fcI3FCKaVWLOdSptKn7hd/+mesutvt91f7D/cPD+/uAUSp49S7XcgTbWEjZkJQ4+Y301hs/sYR2P526WZjU861Kuh3jLI3dgNfei16+dXLegc0QD4+vbU7bz4x7Wy2XBza2B6tI/HtGb7zQPyunmGD3C4rdmyV4OWv9HJ4QaxABIOFKDGrQCMIokQdk4RFRLhFDffaxFGXt9QPkwhY2Vavq+XTuq71aX1exoXMo3riLnXInpnRjWm62ve5p2deysJD8uwlm7dysQYMbKCAeXixjcCiQUk21xF2EoY4q0hQkqTEACd0SRJ3msuaLRsQYbC4ubnZ34zV1lrOBDffXCm7jq920zSmqFWYpmmYxoIMJ9cQqx5tBLyd3W23Imx9DXPjYIGwSQk3oi9xkPO2gbFqk4IaLMJRlgKnamZeIkrd73iIWup8PK/r8tnra0l093r3m69+tb6PuxuMOnB0T/fz6Wm2guglaVJlouiUl2XVlERKWWutlpSFRZmUlYIRLdOEgKjRYmt926LdPDxKABa0eQB6BIlb2HIGBLev8cf/8Pf+6N/+A+jzaT2+e/zt7O9ffXE17rtlXsjkvObzaX29F3KQb3NtGfrdeMVI0xA3t7fj2Jvl6vnqandzlcLyfD7ffzjf3exurndMOJ9PpVT3c0qJqDBmr2vJuq707t1D2PHpwY8HXNp97PfQNFxd3Vrlh6dDKXOpsSynAMxMRtze7d989vnx5E8P9v7b+fC4Pj/kMoM9ifZm7rnOc5mP+fB0qEutxW4/uwZkmast89UtxuvdfFxLuZCinBAR+eKQL0JMYZuIMLb2uX17vR8mtzAjj9qIykSsKSmnaMyUTWUW5CHWcrYCfhksfcRAwBfixaffarpAIt/5il+M7T4hGTUu04WbeYFdmsfWZfWKi0HVJ091QT/a/r25PQCxmVoCaPsFAVsLv7kMBMARAZaNthMb2mDh0RCaZqN8WSDbE26gBH13MPqdRawdF9F2smPb/y7Iz4Vn+gkAKBcq0Lbv8PY2G5TDzGaGFyxum6p8RPqwAZRonKrt5ETA4S8jo2iAQ7suG7xSm9ltq31edo8Nz6KtIrqs2NuHeFm0PyrvXtSgl9/8Lefl4/n5HQDT383A+hTz+ld68u8eWPzOH3H5aP6eL/G9u7Uf9XQ+ZDN4BSjXNduKT5TaRGAFGgxL1Iw5mdtJlryu7dJoVy05IaKaAdpITWhTSXdiUlWIWFjT+HRDCt8uG0TzeqzbpNcu+KsTSZvcMguayUYwrcsMVWGRTsNDmJnYLUigzfYhAuZgBqMT/XimKIoUkpdJe5R2aWKrOphJkoqodkp90sTubqUykFRLzrWWuq4WIGFPBoWBrVSTGFLv4azca1ciPOcIr8VRvSIOXz2iMgHCGmzc/LTXjf9fUCzgnlwiAuvTit0+Je27TkZ9M76ttc7zsubMDAjGriuxdtBXb26+/vW3w74jp1rybrf/4osvT9O5zcMraMlzm4gyi0DgWZJ2qpYNNSgCiTpJJVeLaubEHJeTw1PHHgFnkBAnRpA6C8irWwkDXJI0dy1OFAhh6YdhnPrD46N5bRxyZtnUDeGQAKORv4jIarTAr1Z+tXlkRe5GSkmnqU9D51FzrR7m5vnk+WxISOMA1mJANvdafAEVYWGk7KU6uhodWFNi+Dov6wJhy71FRB7qmYtVy0spDmE+LZbtNB8rSLpOx1HTQMrsgNXSd2oGtzoMQ9/37euzzOdpHPpOvZbj4Wl/dcuIXmM3aZ+k5hpu67KcTqeUum64hfTL4iAxASIHhNOwS0wp3r65nnZ96vj21Q0cDx+OD4djruh0W73cvZSMAuWu67QW81o5Eal4mVm6JOLoDRGhbs3yO9fiD08P+7J89vb6D//wx+P+Z7nMHx7uH54eQDHsBiY6nE/v3n/VLpKu12m8TtSVWp+Pz0F2fXtdI5z0fF4en0+Bbl3q6bTe3r0duwXwUkvOa61gDgAiAJCSXl3vU0q1OlF2iyhhBXnNbXdKSVR7ZvGoVpfDc9YEIpwzdmPZjf3+ajf2qeSzqA+DMJuwp066oY8jlRwwaIdgyewUmHTUlErOtawBCGM3YtqPEnR6PqxWrPrpWH/vy7FLoxueD2spZVDqOiUWStp5mUa+uxv3Vz1RQWDoVIRLKREuknoZWIRIh46GLu13g1sz+Kgi6DtJSSKklPz+/fti2E379+8fv3n3zIy7V2+GcfjxqztWXpb5/fuvP8z3U7q9+/L6ix//+M0Prp4+HJ7eHddciISgzFw8qlkI+uuUBjUzKhiG4ebmbjftjvfnX//Vb3bjFZusS5l02k3jvJ4KmXsBswqjYM1Hz+cFuQ4ydfzq9rM//vlPf/bll/cf7nfgN1c3vsyWc0/IgtRJP3GOAjWlSo2g6ReVijf6LDn7xWaKLva03ymc2m6xjec+8Xb53r9/5wwNm26FXhyEmQXAJjPa2jHGFmkHjlY2tX4YJedoVt9EEGJpYUBBdNHCb6z2iGbL4iBuQw32UkHYGO+w5qdpFCGA2Ma8DafEXz09CXE5+n//P/yPc376L/+L//zf+Yf/+M//8v85nB7rUgAbUreu+ZuHDwJaVxSrp+V8mo8nC7LYjePYD1Pak/Ba19dvPncCzeclYp3XvCzVLZdcPANeatZEu+s9SehMa81LXUstka0SljwHsWgSVobn5XB65tPzcHqsx+eMRQI9WBkEp1zLmtdagKiqa8VMDOI0QjQAACAASURBVNnyL9vWEKgVtiHLjZYRa0AgY5dSGz+YF69LzpSX45xSUlUhHvq+41Ryybk05dFmCt6IDUQhHMQBUk0VZhupBLXdt3VP2wiEIMxRA9xJUuWWaMhEx6cnHq5irVgRHrWUnClNt1HdIocbETrSXrh6NQtWmOF8nO3r93/0+z+9P+R8zmZVOi5WluNyfJ7vbjrmtJ5mz9ZPu7evb5d8vn94MMskYHar2c28QED7q2k37MTjfFweHg9MYBaIAAyL0phr2rLYSElCZRy7NS+WLXVsVS3MyVPfQWM/jhA+rIc//P2fTv307qsP79+/o4Ay1eqkENkkt7GpRRyB83HG/Yxb8O8rwMRpupo8PB9ny0bmqSOXrlSHCci3tMdLy+LwLvXSJY+QJJRKwUIRIiKs1WtZc9MWUUKnoqoAs0QaBw+UXIoXSCu4hbSNBKlxFkFGXDUxCTfHc1Fp5kDhDQiVMKulWZ1x1OZYTl4CShKaa2m2mGElDNQRsbCyqO6uuq7jQKlh0zB2aTqfz8/PJ4A/+/LLz27vzoeTeQ3BXFZbznnNvXavXr+5//D4i1/8NRxiKHNpl2RrButSvUQtmczPcXKP0/MRDlJZc+m6fhimMq8qTErVCpjQUueEPwJ3m9/MhpmHBF0ob7TR3RBOv6tK/0h/2NbGuFiqX3Kj0FR7sQm3mZlARpth4nfKeqLGmGoYMtzNXVtKQ2y8sb/ttmHWCGzGg+TY9I8bbnVpT5gbPAQWYhVWcbYSFc0xmokJDiIjctYkDgirahLV0/Pp+nrvFs+Hp7xuI8x8XDOvICSR6CBMYX5aDyXsDkW7VHg95Oek45prXYt4sDNyJYOSWvVwC4BFhDVyeGmsvZZX6JHkPM+I6IRBbNUWP89n8gRO0neDTIkTUQoSLqUQx83NzTgkIJbzig594qHXIaWlFph3qtM4tD6FVEnCKipFkPhL4hgxGpGiuVpJQ92cmEiElJkRAFGQkMOZiJQb6OgWQFg1tEA6d1D0mojC6/r09Ph0v/9P/7P/ZJ6fEP4f/5N//Mtf/Oa//W/+u29+ebQHIND1Yz3mOs99l6Qn0vLZZz9Yns8f3j1ev7q++/ymlHo6nJd5CQuilcAqaRzHpIlUgFO9lO3RnF6a9IwcCV2XACvFhXC9ww9+NP7wp3c/+Ondlz95/eqLm//zT/539NLvl12/v7qZasxh3qHf9ynF0Ovo7pYtIsN8nEZJdDoe5zmnbvpw/82ynlSkG0Y3Pp6WeQWiPj4stzdXdzdfDP3p+emx5qwEVmdyhHs91axXE87nMk4YJxqG3sOP5/L0FMSLxyLaszhqHcchaCi21Iqf/eTtD3//h6/ubv/kn/9fT/fHx/u1roiqqevJJM8VxbCWhtQY8M3xwze/+fDH/8G/iY4muv7N4bdQmq4mB4LV1vBC0XMsZuclPCJIicIoiFhb22wh0E67vlPVmt1hIiJdB8e6rrDoNDHLuuSai6oKKEqNvM0QgKZKh/QXBOuF0kKNb+IeCLssKy94zQugvj3sI47QumX8TvThO7+7GKMiLl7taLRNlRf6wwbw+JYEoi/rBhHZmjeuGBMTqcoLqICAk1/oXW2baljblhziF1LTZcHclsrv3ZrQb/Pa2jbOeDGVI2JsUbLk4U1z34kwbTgUXQhN7eXcYxyGyyp7ObJPgB5RbnTYiySQcMHsgoMlfQwTJGqt0QvtaKOm04Z2U4NWcMElPnm5uJB7XiYQDfW7SN/+ddCrT0lM8Uku7d9kYP3/v30Pvaq1orGML1QsVX2RPf79nw2Xd6Q5rwAQgFxoNXEJxbj8t/1PzZOAmDcr71xykkRMYV6LkQUFiMKsggnElFg6jnZlREsIaF+MdtkQcwOPiJqqtSnH23WLjQPmLY6DmdodL3Lb4Mang3DzA/iEwN0YWWZtm98uO1AgRBh80ZQCbA400t42CUFiCLk4iUMVbuEexOjCWyWhFB4VTjVDREiIoMqqysadpqHvqbpZMJN5sdUsVTAgokLSokzdg7wB7cyJ4WDukppEncvx/eGz1zfTbrBSzvNRpwQN6jlJIlapgMOXsq6zJAYw7Uc2fjocRGXsp3Ea6lrneVlOMyUEgwmsLCTwjmo7q2Fh7N6MxYiZLMwNCJJmGAMvuS0qRnCiaGIESSQswTVXR1h4y712RKkV5CSSPJEww9yslVJETsQiW1IVkQe81ssX7zJzbD/Npe733dXNbtoN5vXp6fm0rLux/+zzV/aavv7th+VchIQ1gcg3UWElAiSSiEr7gnNeLZrdZ6kgMElKQ98Ls85LyWuxWgORozw+Lcvy4BXM2vXpat/tb/rr60TMmuTqajfP8+m8zPO8LPMwTH0vEX44PD0/P7979+6rr7/+2c9+XsqyJsATjWJ1rWV9Pi6Hw3F/8xk5z3N+9/6wZHjI4bTOS15nI4Z6PD4ej6fnvpf9OKTUeRhgnRAQAlJhQlgJGJiqGbmbJlFFrV4LgmoQgZRA1cgcgEunQuJRlmX58P5b7srN3b4b++Ph6d27b4PiJl+RyvH8fJ7PIEji6mE1IMIqqskcOdfzKR+OR/eoJaU0eLXT/Hhev/3JD3+Y8xqByuZR1+y1ZncvxVJKyh0AwIexn6ZpnLTrpZT84f3D4SFf3Y1WyYqZV6douYcE7qUSoZRqllhYVUShyqBCFCKeEue6HM/1dFqsgogRJJz6XkSIiff7NHmo8JC473t3y2UFuO+GmHLfjWaxrOuaFw+kJKLEEqlPIFzt9fqmHzpa1gVcWRRUqi1WnSmWatQWXVKAUsdEiqBc3N1qzUQdM5VSci7DuLu7fZVXenx8fzjFeX53dTXcvbqb9mOEiXKN+ZuH81IPX7x5+8OfvH792f7X+vX9w33OlhcTAiXqeqJE3ZjAUE2h2obkYz/Ols/v8pw+9DoQ6XS7u309WeSTzXPMxctaZ8wIOHMcT/M91uHV9Zdvf+/tq716ud31f/zznwH9u3np+be7HruhW5ejduQUSHG3v333F/fCAxMFOAUsGqRA5uZhbRGPwIv/5aVEIiIq+MSIki5I1qcz/cvM6e/eql7253DHy6yGGqslKDZKCIKaT8cl8AUh227WOEGIoJYZsrHF4zIsAy7voJZKRMHgxgsGhMGKYHZu/bdAVKexns/O2g32/ji//+bxeJj/4EdvP1zddNrneT3mZ56SCC9rXop1HViVu1TcPNcoVVX2V3sONS+LlR/c3BSz4khdUQ8Xj5yfT8fDfGTyTnU3DUBfyjqfz6fT4VwW7pPSKENXa83VQEvSrhRr0ZW2RhSiwrGiugVwvZuAWpZDrKDKiKgoSAhGaCC8uW4QsUK8BbvSxZ7Am+IrNppIRLirqlUruZpZ3/edNhEOtmqPQEQs3E56ix5AXHaQFp0mgaam2Lg4FK1PblozIjjCnKq3uF4EMQsKChWvIcGojiJdJAoppRKYwstcuBNOvPkQMBAoqyXz9+/v53puebs553Up83JW5TZj64eeRW5vbm5uxsM5lnVJKa25LMt8nmc7A4ZKUXMpNJdKxQonasNVSNs/WZpTEgUxkWymYsM4nA/HdVlLqbVUKEdTi9RImsZpOAV2+900TvcfnlS17xPVyOdVhMKaHGnzh46XPZIA0tPhXEotOS/nza/TYU3in1JXiiOa9tMBeIM+IiKCguBwd1F2d6fasChiuHuphVIruVmTdqljFk40TClAy7K4oynEo3mGgje+ngfCaCJiavUdg1Lfiai7RTUATORboDMRnC6K41LKVpCFE6mwOBkA4eQCEjCzqhLHMpd5WXPO0xiP988PH9au19ev0+5qX2s9n+vpdLz/sK5rrjXf7V/vd7c5F2QIEzkhO4ypIxZYseW4nJ6ep36UlCLouJy9VgTCDIIwNJGsm3kJq8EwoC2Km8tbxaYHfMHmW83Jn6yKl8n996v5bf5+cSmmlz9dmha/fOqt1ufW/F2apZfnufSiG3q1PfOnLrnfudvvnJYHQNuXky4uhxcOxsv9X5rLNsBo/INmc+dRPagFKhLB3FGtBlEA0mYKwgGBWi1+dmRQAoDIm6KTd6KhyiLixey8nOWkPfqMtbKxN6c3YbS+NsK8VAuLZkrbzHhrrRFGTiEe3DA5Q97aMyeLalERlbL5IEpBdSlslDgRhVt1tyRNjOWgGHqY13WZOfJ8XocYa6kRjtQ80Z1Iw9nbnrGpQTdgsfkqMMfW8VNsK8WWxG0gIiaOjx0KiFiII7wGc4tt5gLnCGHhNHrF49N9kiiK4/HwJ7/6C5vjH/6Dn3y9P/2Lf/4OH6BJ0fW25lpyXiO6OvWp62Tcj52qVZ+Py3yeUVqcMddSci4S7BK1rjoSYNREZswRDDBpeCCs5lMBA4Khx+dv+n/vH/3sD/+tt/2NHcq7P//ln+5ujDqiNBJjrfPz8b7OSJqud7fpdhLvarhwZAeL7XZjSl3NVosNYzcvh4CziGfP2UCStCO4G5cCq0ShqoOAlSJiZUAVzO6W97th6PrrfWohtR71zvD2Lda1Mqd1qUwZVJZ1tYq3nw/jsP+Dn/4IhF/98s//+qsPZQaC+34k0uLMLmkYjHKuHlb4EsyHivff3Hd7LZ7D8fC0UCdOJL2Eu9dwgfYs0dW1WPEKMLFTCIKEiIUTSaecWJTX8+KGFooiKuFeorg5QGZ143RFeDEUw0teSgCAsFwoJu1jIiDcC9r07dJMXW4faaBoO/onOIC788X+Mj5J+fjuArE9I5FcQhU3MGprxS8U0k0yR5f80o8rFUXzd7vwmC5E/E0PSXDa4g0jLprLbeGiDVHCi9J6W4W+Xz9esgtfIIsG1H1kYL3cD4GGekOlWWm1UuElomSzErtQWZk/rqV0yW1gbhPSeDmTLwATEYiFmF8yDdthA816kl8+THPnQEMyGq5kFhce2HYSXnSCW/H70en+ZTf5+M5eRN8vD8fHc/bxN+21aGPhxff++p3P/u8Haf3dLKrvca9aHuLlXP2rQWYfgVcAgCLx5lPAYCZIwxHb24qXZXUDkJi2V4wwryoqokxsVmBuazBDlKyGeYCdg0g6VgZgVku7EJkkabXqcGmWWMzNQo3CDR7FNgbudp49LlS9loikw9DSQj8RPDJTS0lvR+dO4WgHoG3DaJeybIgWBSGaMxy2b2hzdGLAqNWrwSCPWlA4mAEndzbXaPYptumUjRIzc6ml5sy7sWbLaw2OXpnBCGcSGBClGIoDFVu9T2CmFr9NHm4ODjgsx/l4dqlVy26/ezo/VbfTUtw89SlJYqDrNKUkoC8/f+Nmx8dzOdWn/DTLEo6+68dpYA+jGtVbFnZEuFtYMMK3mpYYHI38FB61FZ9ETAU0pB7YPnFm8MWZj5MiiIxhdeO6hQirSFg0MrWLcpAGEap5NLaKi7Ik7bt+HEbVRETr3CwRI5oPKYWjdjvtJ52mIfXCTrurqR86ZtRiNYNIoLW6aQQTmbWqI1hByuGknIgIQeuSF/cI33A0kBMscDieW9oiUwrwui6Pj6eHJzTRl6qcznJro9M0DUPXaddfT7vevbrHmss0Ddc30/5qerh/uL9/vn+4rwW/+cvf5pKHnsqbnby56hRE7AY4xm63Vjo8n7795unpXPq+U5261IcVwFUpl8WJPNacT8rJnaSTvgthsIQqiXIjFrn5vC4qMuwmCipPR+maTNaYlVlbFgpp715KNmN39/fvvz3lp7vz9d2ru8PpcF6OALTjYdcHWTeIqLBKydXdV8++RF7rOpfD83pe1lwDAZzLeqq3d7dX43VZy+n4HGGJ03jVs7JVq1bXPC/zvC7zfnetqsIIMhYWadB47QZ+9Xqc61IrvISITH0/TKqJI6zrtpThvBZNHggltBTxbNWsVgfLmEs+HGGGafRpGIZ+nKYdU4Rrl4gIKrwbx2naLfO85EW5075nFgeG1E3j7tUdl+qlVEewcKCaI3UExJpzKYsmpEREXFYyeCCLpJdigTYrJavWkNlNJ08kjVtUc0kp3d1erWupf/0YFeFuNZdMAVOW/X7oumBajvMHIrt5ffdHux8/P7z68OH5q99+Ww1EwQIokYaZpdSz0jKvx+Ppendt1SDAghw59TQ/nffXylopal6WrKXvo7/j8/F4O7IKBH6z33/x9tXt1ahhKYkI9d2t9cvVflJFvx+/fjjcfnEL01M5cdrX8ERGLETM0MsoCahw+7hj0qebCS4ARlxwCaChIXQZn13u6xHBn7LBL4UXX0ZVrYd7adxxkSxiWzmbcSLxFpBmjeeLy4t6QCyCXwKhGorSkl8iGjni4kFA3Ly3pVU+F4ruRgUDwQ1AUBK3CJKAdUMntnzz7fv/6Z/9z//1f/VP377+4g9/8oeLnfLX5xqZteuGNN3eXe2G07I8PD3lWjku1maKMI+Adv1qNWdb1rzkXD1UBdJnK8syE6zvVJKywKoFXJJKqEWsy1rzKpxKWXMuosXN8op1tuVYyoxYgdwsX00mDQ9bLDIIhOCwSkJhYdlDHD24o9SlTrpoPixuFuY1tE+cWDhRAM6AqIiZwbehbF2qkbeBl5lTUPOoCRCrtCA6NKPJ5uDszi/iggZltdC6bSa5XSDCQgAcVgyomlIS7fuOnc1qMx5OEEpdLeG1jmPPIqd1BrSR85KycaBWZXl1fXd8POggGnqez2vOZa3h4IjzPGMhd7Maz3LwWI3m690+pT4XOzwd5nP2O+skCXFUq2umCFXuB20KqRoVIeGAKPOlAGkXHMfhdLCcg52UEGRkYBCRU5yWebwemfF0eDweD+f5qIlb2U5KCHjdBshM1GQmXiAQ2Wte89d/9dXweuq1n58P6LXvVFTcQR6SOKUEJjcG+WVOz4jIVli25F9zEyERoYg06ND1FGzVDniyCq9eayVCUm2lT+pTHwkROdfwNbxRfhggd7g10NqcnBAewQJR1o6thNMlic0JDK/G0cxoER5mdcmWUkIFC6lIiIBIVQsZCyRx6pTF/bw1Prlk8yAgr/X9w7vPnl5VK5xknu3D/dN6RkqQOPz2r75aloJolR2gvMUOCdyslrosi3kZRcyj5EJA6tQ9LFvVGha5lMYPsM0svakGjBjUTDHppW2KS/m5rTAvXcZlDfud5NMLevU3mAUE8th8f7//mEsA1yctSvsRba67yXNqXHSeeFmUP+kZLsdFYGFsDWezJfVP+pqXLuBCUiAPi7AgQpCTkDXfuya3ZISZO1p8kNfsTrXGbrxK2tlaosSWBhhCaKiTiwu7ELZewCrO6zmjWFiQ1VrbK4aT1/DsniM8aHPBgIeV0lJG4RYhHtKKSvbSAGgLMhiYBRzNXcjNT/OJVQbqu0nhtXhe4GtZul6T6vXVdHw6nw7zcsZ8BOen0925VMcIqiirJSgxh5FvVtCEzb69sdmCGkhLm7698YkZ/PE6uAx/NkyUIQqvYKGm6S1V3cAOL7BqT08Pv/71X17f9l/99bs//b//373e3L367LOrH3958/Nf/MlXv/mrb90IARUOjrwir8vpfGak5bx6mFVP0lnLZHHAwEQi2vddSjzbIQIkLEQI1FrdHG6cIOTK+OLzNz/5gy8/fzt+9qb74U9vxpt6soeIh77PoELq/bQL8Po8T8PVtN+r6dhfmdMvf/WVeXQ9k7h5nVe/vvZiBoIQPn/z1vKH9fh0ns/LAgGPo15d9Xe3tyn1h8Op5EWE3OHkfZfGNIm6I+bTcehUp4lprI5cCgjaD2by/HQoFgCub8ZrXKVufHx83l3vrq5uXn+2+/brb5+ev+oSwYi8TzQEsZdm+spNUBe+2RNERX81vfv1+/5Vunt788O3bw/rs4dr39GQiKzWDJCosjDgLEjaqzQTuk132RJ5c11LzWbeYjFlEO5EVD0iiWrSZntGcMse1S7Z72CCE7wRlNuVw41sztjKJNrKmsu3/QXO2qx2gAsmfinnvPm2+csK9B0+VryMGhssQO5tjthQDwbgcHK6bHvxAqa3ku1yfYcKXw4mXpCmhk9tB84XovELNkXbF6J5lr5g/Jdl8uWdvhztBccnQduBwmH+Avl/x1rioubcEKLNKGkDRz66j0e8/Nua88SGTX9kXbVJQ2xXC4kQMZPI5gS2sXBiQ60aheNl3d4Qv0bPaSbgHxGluNzx8lKxtez4SJv67rv/Tgrhy40+IY7hu4jVp3/93u+/9+O/9Pa94/lbpiz08tZerpZ/jVtc8hx1S6RrwP8FaCQilZY55cWq1yDyZvLIbbjusOLSqygRsVUKAhjCmoJbsHM1p0pRwiNC3CXogpEFo5qRMDcTyO1DgiZhpkpkbgYPMYdFWECihf40bXbX7CUi3OBmIEA6qDJTg2k4mFApHO7ibbNiZuZW0zdz4MZCCmIi3XqrEDcykDsbsddWQkgEwgATgigJo5ZNU8JRUDrpWLGUFYZq2VbMy8IKThAV7frU9W2is03qFMyIgG9aWSsAzMtzoYn6KylW81w0EQ982109fPseHrTYukThdTeppE5V9v1+SEMa5PD0dCqnSaRWP53OJGCJru94B2TWPnmJuhbLXqtxSN8n7qQspa7WymN3M2/9XZBDVDqR3c20lkwETmxuHu5ugXCOywCWQAznqAblThOzJlUFUz9lKyjFkb1uCKQXk0S9ChRpUhEFSyw5rBIkwsGhrNP+ClwdURu1Sj0puftpfTo8l7WClYLM6mpBbtVRVViIyTlJDyFClFrzuppXZrTyby12PBfYShTjbkpdn1jXdT2foxSZenl8ziqoYVhMTiRDctddL6JQ4dtXw7qcb9NuHIf97ko1AYrQ/XQnLPMZtkawRB1PJ6opSLS6kE7npRgomxHpmksatFjt94OMXPLKEpqEOECSzc/LmrRLKY07TizDwNrF1dX0+HAikFe4wQALYoiDU6JLWK21NDEQCbNqV2MV6rpec8n3h7Xou/H6Rrr9NNlSZtGhn0ZOUsrqIBH1WkxghQ7Pp+q2zAYDHH1PuUZHSM477SnRTF5zEW6J2eKBRrNseYIsIWESEWFuZc0xL5GSp077xHoDzKgpAOr7NE5j6jSsWin73ZCSpI6FQZsXsKpKtShWzeCRPa6Eh7GH1ehTN437YRj2+4kpluXQj+OynJj/P97ebEeSZMkSOyKiqrb4EpEZudTS1dV9bzebgyaag3nhD/GVD/y94SsBggTnhSCbwAwH3bz31pZLLL6ZmaqKCB/UPDLqzp0GB+yhVQGVWeHuYW5uripyzpFzbHuzibGrqsNmY0osMoxDziVF7vvY9b25T5fzeSpmxBKnuSxTJne34gah6CrDpmcEP31mwn7TNyNiYoEjFy1qMJ3n0nUyjp0TQEoOJql5KiV3aXjzevS6fPw8vXk1vHq9M9PT+RLJdts+dV0ppeSqeioWtze71G/jQBTr4XhZllpr682XudrNbi8RpczE5loBRYY7Iltd5pPm+svTm282p+VeAiemyLbf92WaYvEBeL999fXt3S4Oo8gY6DKXw+G8e/emIMXdTkecfOF9KmxLLovS/cPRBEWqkMPEbEW1zc05kghc3aglJOKa5ndl5AQSCc0Qai1OvlhnXZ0Inpm5a0XRNjkjWj14rpx0G9W51lvPjR6zw4nZm67EyMGrg3GLdXIib4FrVy+eRpERiNjN25A1i0tYo+/gzy4LDKgzwcmqubTTs6DBc6ECJtfkZvS7n374P3/83X//3/53MT68ffXmm/dvEA//+Ms/mFtK/bfffv3V3fs//OGnp8MlNH+n4NRMXoS7fhj3OyOvVk6X4/3hc1UdNxuO0g2BOTVENsXU9wMSzVJ3ZDRdHk/nh8fjeZk5pFL9MpnqHNryCaGCfK4AYh/rolFi8apVswOOEFe6FvPaARuhqgYgEHFsungNKUiM8zQJS5IQOJlpNWcXJnYFV1LVBuAAYGrOgBQQndpEQLNSbRks7V+DgLJxUwOJANQ2FAec0V4dgJt5EJYAIvcKMwYlEel6ndSrtLxgV4+dmFawcoIpEICOTRwkHsnNEGXox0AplUQOna0+ar5UJsQQvfoy5+UxN3CDii9zJKn7/X7zuo8J2KCLebocuxhSEBjpUksuqi6VlsVL1uqVKLpTDE2/Z4oWz2lqdLYSImIfA6IJlikjwAKxSIQXnffbfilPddHj00ViAHypxdxCiI6gBlK4elMtR2cR9uoE1HlJfBN7WS4nqBoFFnKGwbXB361obPO0KyKLELh6JiP1PHZjt02ZLBB3XScsZs6BXqX95Thdzks1JVPyIs6LFvbx1d3Njz/+3I2hKpViTCRwInaQGwxeRSFO4h0LRwkJxEqspjUIbze7h8+PYOYAy0bEsUtaVUt1kMIkBgrs5BTITGtx6RACJBhYKKLfCAKNwzAM+7r4gXMglBlEFlPSy7LM1TWgVgOQ0/kxqxoXePXISQLNy2IrXgOJYRw3Hx9+ud2+8WM+ni7cUepEp0oVhqJaYgqtf8plVroKGtyb5w1ffUxWYr8tIW3AsAmArtK5XzVbTgCZO2PlilvHtbq8PjsAE0jaTfWrBbApX5lg9uJlCatvBzXpD2CuLUS2+bzL2ljwKktYR1jcnYnbJEGrpw0mvIpo/UtEIQjQUihKMz/2Wvnq4iJgNTVrdnYiEg1ea0ZLNwAnCpuuZycURwXKuv6j6UYMZS4ESpQgIBfUkk+1LupMDlRaoEDxWkEFKMrKpEROpq7mhpV9XUt/BxnBYNVRAF+bfxDE1QksbFpNTYiqVVNZshoVI3WAzMmg1YIMXUSZ65TzMuP10D/eP4nFt3fbj9MJpbqLwsHCQu4K9xYCCXhK4qTubmQr4M8OrkTX2XdcYXyYgxTezIRcPCQ3VQodxYEpLjnwQFqMlqxT+d0ffvza3h4P+u/+8ZT09Nd/Obze7d795V3Ydpt/SD/+4eNy1nlSLY6AD/cP3JFLZmJXBzsCo9XmUERCJz6QJiMim6VWAErkVqtFRcKbf9XaAwAAIABJREFU18M3371KPe32/du3r+7e3Lz5Ko3bGsPprIfLcg8vYxcuD4fQEbGLxJtw142bzbjNc/78+enDp6c/fPycDcMmmaqTygPuXqWhG1Pg0/H85+9/Yzs+/lI+nj6Ugv4WVbHZ78Z9CMEWrUu5JONaJjVNMQxDikKlLLCslLsUQ5JLrtNyKmadbIDgfs7z0qXBvYaYNpvYd71p3XQl0qmPUxLb38b5EvJCghC7sZY558xu03J2q8LJsnpRVMgQl4fL5Mv3X+9v3mw+THgqBw3ZoNrD1f1ipSizazSPzr2ZlS4FYapqWkxBuWjJFQWkxCFVrXNZPAknrkRE5qTSBzfVrG3CbtXnEUAUGG0tJ24FDgzurOSOIF5byGsLK5A2ggqQWkv3A9w4hWYQ/gVCWYMNW7ydCNNqU+5giJORXaF4e9YfYd3EfU1q8BWhXRcnXI1LAW8rJodGNBqedSgO86uayPhZIN84T5Dj2R/er5LSFqujL50Xva2s7r6yZb5yqAwmYkO5lpZwc77GXjiIzGupdC096Tqv58+Plyse1xRkKzoGU1O/4mINjjG/An/t2hnH56rHV3iRmEVa9GAreYA2fO9tM2qYPr7IyJ6lc3atmZm5hbnYM23xEin6k0DP8x/8V29vxXn+6JH/ASjmf/SH/9jxJ4Gzl0e7vG14sL2amf0nDS3+EWZ3BbDa+QG48tttdHPNClyltN6Mv4mkpRd78/PWqo3Ya01Mi1x1Ehc3VJhXq0txJQSnTpp31hqlog0AAsjJ2tIPImERIVJ1J/JAAAI7B2rknVJj1zN7oyjV1IkgLQccwmh+XHByEjDBoCSArPb9rm5uV8iYXJzYm8KgfT2U6vWaWHUnsDM5sQmxJ3clUmaYVfdmcOsQR3CvhgB1jRK7PqxTKIG5i7HvQBBw81Mnbk5P7mtssoMJgWBO4hIpV0SWRF25LE8/HsPUuaMvkbVooUAxYtPFsdfUaxeIuk336vtXHz788nT6WAJccTpONE3O2MQuxmDkOedsCocQk4hVL7XW5hTmqO5GBDIH1DR4aJ9vrQsJs3N2XbTAaxAKrJXVRMFxFVyoW67MMUUh9+Uypds96drVOjNKBaopHF5Qda7GHkLMuUxTXuZ5FZgySWCSiUXNA5vP+TwtMxFtNt12v2NZ7j+da3ERJYeqqSkztShlGLcCzl0tWy1rSFrT3pv6+ZyrlrHfJGevms3zojkHt2iqsfmZBBgwZztdsitb9i4hdr7fD2Xwrh+C9F3smNNmvCUfVFUr3tz0l8uUku92HVEuWshtms5LRtZz7MhdQ0eIUMd0OVF0ZoIUhWqzcmdxdzUIU9fzuBs7SV3Xh4jb283xeMwXLVCLbiLVYFqVPLEQFE7q5l6Ikq/kqbgzs0gIDHVgrjAIhRDiBqqGUJaWSQA3JgiczbTmerrkwBSY4VYnLMUh2N4MYzfYUk7Hp/uHH37zm9+UnPNczpfldJ7Op4WFuz7Vxc1h+RxTAxogDBZ0kURQtZRib+7Gpag7QkhNe0Vk26Hvu67rEhGWvCzzRQIalicSiJjZYredl5vdRgPPWlU4ptgHkSAdUzVzYmO2zXaTy3w+X8wodcNKSBPN0+IwkBKVLhHA7nw41VIsT1m1aGkFAJh8Eh2HEIQCxyCU5CqfdqxxpOaqalqr2rxMIB/GsY+dV13mmYi77bgZNoHUMI0DM7JqIcudSBdlSKEyaqBSbFkOppk4Dvv4lzffLVN9eDx++PD5x/vz3Y5jhSRNKez2w1ev75JI1RkCArTCiiurmkraSEZINi+YnmDT8hffbqfHU9/hmzdv3+z3XHU+HY61Vk/FTBFUhIZBtmFaKkQyahWPGOZSkaBiAHklK22sBAa5BrlSQ3zcHdx208YwtYpLrk7HANAMcq4eB3xlwF5KFAgrDmX8hSO7ir4JzxL3F7usK0FW+m5N7XjexmBN1cuAGsxX1bVdGzegMRJt5IOuRJ4Dzu50NRptz3ASYsAMVDUWtkIexNWq2lPFcsSH+VGLD7F/tduH4e2MH89L7cfX3371/tX+7ufff1jmzFFiFAmw6JkKUxCRSs5BJDIJ1MpSFloQPTEzBGTNhtspSJKuQ9+XsqibXo7H+f4wzWWKiVtu1DB0zNr33WaUw+EQhbyoByOK2YuTcUpG2QWrZH4RoohmCWvk1VUMxEaosBQCA5TZSzUnlQKAjMmciaJHbdKO6q2oJSJqbvsEYrCziZlXM/drgG+rKF1aj8nNBFzVWuq1syOQB2KGuRnRtRZlNdeSl4ludzeV9HJaJsoSAisBRuJIpNCKBQGFq8E4crHiZNvNftyMVvX48EQSvKpeDDOYmaOYOdT6mMyRLduE2ZdsUznbMikJVS0ceBgGYYvRYmDadXnxutg8e4whq5mKgx0SY3RgqTN7BRmRMdBszfsgRD0lrSJavOQZBiRIwn4/kuuk5ITYMSPAqlV4bFEw8ObAZhBbqXUtSskJLEYghgAiZmYGF3bCopXUUF3N6ar2MG8JuqhNH60mwSWB1RSuKHAlJgmsxWNvG1lrbzKjaDFC7VwtjttILvPFzU2EpHFIagzhQHETESkGCSIsTMRm1xRXCXEIEDJ2Emqhk8QMMjCBxddS3m3N06sK9Bzc3Vw5iMQYqtjsxeroLEwi6AMmxZu3b06n+fRweTg8eSYoWFLgXkgc1QzCEGJKXJThFRBncCDpZHtzc3t3e6ATPsDEi5uL9iOHjoktxqDawpef0StcUXWjZ8GBPTcx7Tqvi5exEwjmV5T+KreBw9xoRaDMHOB1qbRflenm9gznX6t9+3IqL0RSTSMFWqULTfZ4nZcmXEcL12X5C8vv8CbUc25Zv3Bwsyxd9QDtrTjYac1ixvP8S+tV3UiJASYKHBiscCXzNvoV+77rtFQQrc4RDigMBliTljTRl+n6IyjgBI7BydwcrcBxKuTVubZxACIDqYuiwbS2ijaITa6bDMHy81bSaDFzBAK7gxFirLaUWp0cYggggZFnrbr4FpvU7bzkU66oZjUcnk6v9ze3r7effj55REsYaD4cADuUXK/dpQPmvN4yIECw1lnr1KnDEAggK9b6IQJRdd/eheOpEpFyQIiXUpHNWS2XsiCb//zp4ZePBwZNs/9f//BLFx9/8/1ff/Xd+zd/fuf/y7/59OnT0w8VT0BA5uP27mZejqY+n2su10vRCVhg1SifUc/FAFBK3jqgq00kdvj6r/lv/6uv3n/1+s/+7G3fpzmfTvmng93X8yXPl5IngoYo9WKo1dzD2G3S0KcbQXi8nD/eP/386cOloABt0C1KWBbrJ+oCx74LTvlh4kWTeccIPbYb5Ip+0Fovl4UDIQq5V/MFajARj4kkxbBJo+gjS1E/15pLORsLUU+OZT49PvrNPsMROSbRTcen85E0WAmMCVr3tzcGm5fFdGHpIU6RZK1zyJ28itfAYKkCBybUY0H2bbf5MH9YZjTTe07RarBaoaXdZpmWXGCCoQsuQOBA0bJUNmPgbB4AkFmtZBKlOmotXEtwd1RrBlJMxOyraMQZBHYja9WRw1t8WgNk1+RkXIsxBzk/zwM2RZJw8NWYgZoglK7r2irh8cY807Wm46vTqX/RKH0hINe0NH/2e3I0+dqXFcwN7Uu+wv7ro9pJuXN7gedlEevjBFf1vAHUkly86RjXk25vYl2MXjCXa4j0qtMR+BqjjUYUPLOq7qbaTrXJrK4QyVU2tYZsN/UpPQ9wP08Lvlylr9Vs+6gc5Ap3viqjaC0nvQnQ2ukTtfl7c/MrxcHSiI1n20G6Imvt9PACTaIrobuKp/yqF3s+GkL0Evp5KYx6ftYLwdc/2/FPC7j+Pyqwno/w61eEuZsa3JSj4/pRybWUB9BcxAKBqZTFtQichEOKtWY1zQpmBhM3ZLc41OEIyYUDALVqrfkxtBRRAYGEHM2Yn0VI2OFNy8lMHIKu3yHHKnRocbPeYv0qOYXKZCTNCMVsFQYQ2kBri6+8ShtXlbUQEa1he3zluJ47rAYEc5vPJYeHPpTsYA/MIKmlmlcInMkADwSHugciScHIqqq6xi6RAD2kiFWDw1i4Oe+5tyKDrqEVxJaXuhlS4o149/Bwfjp8PD8pXtwJJ1/Aj+gBAQLtx93dm9u7u1ffvv+zN2/eXJbjlOepLrlmM2UjIzMoxGNHCAz1rIsWK7XCUTy7gSWQsLPB3QXFsxl70UUXIREkZyMzFu6HPqbUVV+W7E2DYVrLolqWWiHRUS9Lff1qcHIOFIXFQ82mlaAeEiC2LAtnJFcjMtaiedXIgmCyFCdzjjEIAR5IJHIIAc1XLWJtlUDM7KbwFQAmoNbKbFo152xmIgBBQmBCKWVaijr65NOUi1bN1ZVRqcx1WaoI3OEVBXAqRrbIdBGMI2/3adzsQ4imVlShuYvWxcE7ORyOp8P0D//+7/OCEDD2AECM3ZZJknoNnb5+fzOOY6081+LM0xFWKodg6rX6djvmvFixFuQGK8xdv0lJYgxymU+bm+Fdfv3p46PCE3OMqea6TAtYtS09bQ1f62NzQ61uVjSwI4QgXCjPPl/mEDozr1lPT5fjaTavpVQ1pC4x9QFcl4qM6g723biJY0wStpvxm2++fnf3uosRsCD/9f/x9/8bg9m6TRr6+Pr9LXK1y3QZu62jOioHj5EpAGzcpJYMdRuG+u7d2/NlmpZZDUTm7swWY+i60HWh1lrycj5fLpOldN7fQERAmpJUnfa33xGZq1zKXItNpnlR5tR3DAswFh634+u7uzdl0YeHwzRNWs0VAIY4iFDXd10Xqy6Px8eH+/Pnx8syQwgx0oIijBgA0wiqewvCSboQhJmzlpyrOrlTrlaKFq0Sgqnf389BeEgc+mBuMXBK3W4cQ4ru9fvwddU6X455yUQ+hMTwPJ+FJRA5o9ZlyjNxHMfdq5t9vEtv3+2/fn/723n+cH9/vkz3jw+1IAm+ffvV6fQkAe/eD9N5OT3YMEg/hN2+3/Tbvh9CJ7lcLtOTW0HJr2/kt99+8/337xLzZXnMiCV2xPDijpok9p0MQ58tz7WqVRgCS61FEgIJu6gCZBXOQJAAwIyaaBrUnJpXDArrLrz+jW2lrp6bPqxZGdaADidqtBsRteX+17k569EU3S+MAOyqqf6ikMev+JlfvwiBGxm21i70vHE2IkGb8amtZj600mO0npERG4MAU3UlE1dA2hS55KKY8a//h3/9r/7l3/RbMae+2/z2t3/z+eHp5ubPvnr7TiiZVVWtQmPqYwhGfF6yWj7OdpyWm3EbAu/3m9fzzcPhyVxLmdWs5OzuYctgL1pAEIkxdhKyEZZs04THIzY7Sx2llELqHTV1XZCm/KX5bBB40KxTkDjsu2X2WooRMFAIQs4GUq1GuqiVWiPHJohYW1/3UjXnNkeWQlOK+jXJ2xpd2GprK1q8TYUFBl/n/5uQ8kuNAQnXD7ShwDCYN34MgTkKMbjN2QWlFJhMDUvV+Xz57ttvtIceD9WeRAISVS9g6fteYUpAL5UUbjFIPRpGvL67HXb9/f2np4+XtdhRQFHdal6IqO/Spt9C6LJcXH0516VgPl3uHy5g9CPfvXn16ekBsCjoe8TU7mOJfUp9GFzMuVaYEphqrVRUSyVB14e+E6oLucQYA3fjkN6+GkJMqjpNFxF8/c3r7a4vefrpdx+f7s8xJdV1vqLUIs5t8tLNmjKamk8v3NRJ6zJfuAup7ylKzhPU+q4nhOk0R+ZV877W3dx4YxBYkJJoQtrE1IVaaJ5n5MwQYYmBv3r/dRTuYgoibjpN+TKfT5fD+XL5+OnDn3/354ens0Ri4r7r3GU6z6o1JBm2PY1ggYiItPFvq+5VqwCRCVZTpGVxMrDAobW6mYFcrq4K5s3/qoU8trleEMvQb/tNRzblrF232Yz7wGk7jPvNELsYSdwsz0UXcBNwUS26SDeEEMCgSEql6/pt7GZFk2Zvbjeb/ZjGuN1t81yQgALNhSKGfuiGzoGqrqrPlPeXrqF1Ns8Q/PNNji+F6heRA/4UQb5GBq7uxfDi+GJw0ha1P90G/If/o+HwIs222Nc+z5+Hgpo6Vtqyqde1tOkFfJUFgNeTIeY/+p3kvqIrQYRCG+zH6qHBJGtUo5u6MRps7SZgCGKMKYaYwvl4YuJi6qHZsV37VoCFW6RpKUVds+YGxLGDnYVoXgorvMBbzV/dzLh5eSvMwA39a3kQba6CqCl8V4FDcy4jYmmlErmRiKQUUbHowkwsArJmBcYEJb9M5fXNHTzj8YhipzlP0+Xd63fvv/nmx398ONfFIeyRyd3r6saIq/uW89UVyL9MO7UenuCrEQG0oY3kqNArOHpz8ybXxzwTw0jIPJ+nadgWMGLC2/fvf/f73//04cNPHx0X/NV/sR+H8bBclh//AOCv/va3/yL8l9vdJko4nY5P94/TdHk63J+O0+PDcb6YGZZFAU6p67o2AWMiFJOczstud/PNt199//03b9/t37692WxkO6YY7Xx+dORPDz/94z/+u8Xu+0H6PgYmDlJKzfN0vqCHjbswjCNRfzpezvP088efPz89TAtcEJ8TBZzKYstl8XHXp2Gbulf73b4bIuObrzaUZLffXfJEjHm5lMscxz4QV1PhRFxD6CWMEjiFsBnHw0MRGZ2CUA5RnIR5O3Tb3/72q7/922Ec9x9++fTzzx+WGXlx977rd5vxVivf3pwrDw/6dDllr+BxSDGGnqlaDJzhVjJcmJmdtChzsFJ//umjb8rrv7hxXb/UMUofNjH06Jlr0yIpm17CYTsMXYolVwUTiyPPS15bUlSQIYZ+6IbtmJZ0OZ5cNWdtRknNJAttC2zSPgc71pk3AAQFOYyIwE6RxAN5M8EhMrgQHM2iBvCWFoA/hWi09UK15T00Dx/6Umm1+uq5Bntukddv8UvgiegaA03PeNoXgc/ViNHp+p+rmKqB2n5d96xFTDcoixvL1dp5+vVSysxo04qrdKVBdW7mgEYJ6xm+AJ2e3/IfLaENAGoCgGd8ha6rK4OJiJhF5CX+0ua1m57IVyGMa6nelFYvDFdb6iSu6ifyNklg2gwrqSXkoWqLRPFncM2vT/GrdumP5Egv38XLvzbF0/Nzn5/1/IL/4Sv85ztenvM/F1gWrjfNKnV2ayMh6yesqt6kUmhKDXUja9aM9GyLRiwCUE3mqmZGwiTEztdSFwDaMAIYFW6qRvAv06nglWX/4j1p5oYamqK6eV21WFEghEAga17+a7qo5ezMDAW3aO42udqyzb254wFkkiJauGYgiBAMqCvaJWj2q0RspC4uDdKAq7uaJk5gdzNi5iCAZgMFMmlzdw4iY826MJPBilYAParChk3gmXUmNSIShNjyuIWUuLGcuvr9OG72d+7h8qSXhzo9EUogJhGWQA5YVWtgO4EZh/ngi5ZLfvv+jpP0cZNin+o8L4sTjErJJS/FRVNMbJwnmy+ZCdSRL+7uCITABKCupU8lVWsEmUkQjgRwBbFQ7EPXJQCSxJsGqjIGLqUWXYppjGEY4zQfi/lqZiccIkCsrDFJjFzViI3EQY5gSOtN2BZix8o1hxBiIt5AogBSSrVqXTdEwbJUM7U1XccB12quFJQCB61Vc233pwMeYIBWb6PG8zkvy2LNxb6YFrgCRqU6CSjAAQhCcXWXlEIUNT2ejlUzUwziXex0af7oTx8+fH56etyPr5/ywYpVYocx26HavMzDBsMWm24bJZdOd5ue0liXues7q4CyVt0Nt2ecVDORqWdyy/l8Oi0p9YLL5Vz2u1ccXaKFaEYSEtVicKXI1uw13ZpDDVDQ8rNN4dU8mFUSZ5Cpl1K0cl3qdFmqLl1PTlYKtGLJuU+sIJ0VBmLs+s27u3fjuBlSn2Iq0/L3//u/PTw+wnwYolnRUvNiOauWNrXraYibTS+pJ8qBueMudnAqOS91KSzUDd1uGHOezbJ7owKNmWA2LReQmo+rxy/zMEg/yGY7xsiOyuwh9LX45TR9/vR0eDqVUmOKMYa81O2uy0vuegajVv7lp88//fjTjz8+lIyhD7f7/X63kyBd1wXqAsearcxUZ9Y5nQ85BXhyVYjAOmhBoEy1Uf5jl1bt5rwsuZgZV21LiqQusVCmuVY9HC5C3kfeboYYO6DkqdSy3OzGOS9Wy3yppWofO3Gqml3Ynb2qV3VDYKr59PhQQ0xdN7x9s/1u8277c384naP8cjqeAtB34fh4ANWUZJkQO9zcDuMwKPLT56d+MzCQRLrNjqmgLv/ib/7mt9+933aST0dQsICnMt0/ff7xw9O3sUe3P9dDDNynSCxV3WomKLsLkzCRNUFEU7MTpA1pNDsbdzXol2qiFeSrxtOA1fyqWeMYCL+qIHjVFOCakYMvg/2/2tvcqYmCnZ7pLFwLpFbSPLcHK0rWdBANhfp1d/nleI5q9qu9YguJIjyzaQZ3EhLnJhn21aEIWmsQksAMm0f/n/+nf/NXv/1u3O1KseN03n213WZjw/npyIhD6l7d3NSymHsFLfMyLXleVE3Y8GbYbPsuhfj61StmnmtWs/PlrKrMNIxD13e5LHmp55zPl6mqx9Td3OwoROmWNIQYuhijhGCa4VRr8QboOyCg4A7jlLoUTXKd2u7n1NyuFNr2NrJ21USYGGjupM2npTZJhIYQmwWcl4rnDw/XPhgOh7o60LLnSIhJicloNQBpV9paVAs1BTkghEAgIAABLo0qVYrOgVpvbHA1QBC7EKKAAFE1tqIsMYQIM0gQCYZaa6HISBh3/bjviXE6HjkBRqZrzDE13ZlZcV1kocBWDewUWcBmjtK6OjLDOG5NF9DiBKcQpaltNARh4lJB5jAvueaSlyXnihDQdxZDV+vCzEEkBiYPKXQhdCVnt6RWp2kh8lIWNWcJRKRarMm0W7F1Le/hMCA4M5OTw+CK6Tz1MvSpU9es7hXcETNBIYmJmd25xWEQKdwRqhYS78bEgW5ud/0upIWmFE215FLKvCwgL8IdsQEQoZSoGkumEPh0sSBUNYdoEmKXhCnCK7Nuxv72ze0hH4rlMi8OE6GuSyIENiZy0lJyiJwil2rNM97VYM1hlQCwsLuqaYsVMHemEBIFMXdmiiGo1vPptCSc4E7Mfddvdptffvk5V1UtISFJyNwsV3V/sxk344eHHwmecwFaXImqYxzC/tVm3A2PT/O0TMXKmJIGX84lCMZxHHfD+TzVOuVloTbt10B5JnK6pjX/R49rq9DwrD/1wPbloWuTc/0u/WqZInq5fv2qdfzVL6cXbspXfns1CVxbl9Z9MZFdq/IrvgYAarr+teWHmq9ztY1noKZoQGjJOQ3i5tXijp3hMFcyQoGRkbq6uYKYvNYqhfI6fsGR05hKyTrblesAB3FhVVWtLe8WABhszYSQqAAKqvCKJhZcc4iuo+EOmHNTG9IaxYGWEyAkBlsvUfM9hMFJi6l73PRRkgGxE4psVMAeOcYknfCnh+n1a5GYIALUxWyZLqq832/3d7vzaaHgXJ1YvK6561jTK5yUwLJq4tCupzempJnHEZGTNzsdwN3VHcykpIE3gfPSLMDYwRm+xBTiYLt9Sv3mdF4eT4fXb8Zy8eL048dPVZfduLm93U96KfOUUhyHgYWHPt292X/dvTqfptNprplNMU3L5TynGLf7kRiOmpJ0XTdutqkL+912HIJbeZj+8DiXeFD3fD7dp47zMs84neepAsP2brMd3fVyovNJu23qh6HfbCSmp8PlH/7vHx4Px+wzSRi3XXCAREIyVQFdyiEwxtS9vr19NW59WjTnyL7fbPptn4Z+9C6XxS0vVi3bslRhHsctoCF0xF01Eosku5vX38d+dOnGrONlmXIliYHC+TQ93B/z8qDqjA2cYxxevd598837cdNr/Xno7j8d5uUyLzPYs5alQ3CGqnIrKcwZCCxWveSaQirqp4dL94n23+6GkPq+jf1EriFaJBGr5tBadMlaZvcYuE/MkBBCSGY0yVzYuiG6+gKn1g6biXA3dF7r0upfQvUWfNaUDgDg5M5wb9qo1Y/dV62FCfPKMDWY1J3RLCdBDnZSmJO9hDCeURg3B614x7OVG9aIQ2IHAQ3ewkut1DMC8gy7Xx9B3tjKK0qw/txXayqXhg59QXX9ywLn1uL5fNVYYcWC4E6t0XkJRTXXP2LXVu+tvwFmq/75+i5XHy1eRStf1sCrNWGzKXq5xr5YhPGMVrwUMdELw6xnHZM7mm3qFZaippxpaZK+Onw7iPha3rR3xEwiUkt+ltH8Ecb0/xL3eX7Wr6Rwf0qH9Z/0sv8sx5db7p/jl4Z2n12hU2qCNhaRZhVm5OoQkHCjFawR4EbQ57i6ZoBFEsQ7IgFLAIPs+uWDk0Bo3e2cKFBQkKHlXazZHeTruZib1qpuDm9CYFLX1qWjkXJMDjg7m9EVvW0aK1AwMAsTJLCTNKXXVTy85h8TOQWhwAJ3p2pOQhBIaK5cogAEMQYzOBoD505mpAZVd/fm1kIe4OJGTklE0JAsTkJgZQuRJSVnbG8HPWkBawbAHmKzyucQKSgoNx/iaIjEX7199/h4fvxwPDwUKwnqYCJhqtTGjl3AYCOPIp79eDkfD2c96/h62L/bK3G9XADa3+2rXy7TJWvhjDZtRsUh4MDUS+GCDIoEcQAkjfJdL2m1aoDxamaj6nBb6oIAIoEghBApBAmxD1rK8fQE8s04hD7+4f4XbfYL4ChRggs5BJIodBI9SGhNiHukNHZu1uJdSDBPteuZuBNiM11yDjlu9v12s9+O9vBwmM5LEl/UHcpr4oB7BYprVYmhVTkQgMnMTZyNYJS6WKuWpZIShxBIsmupNUBSly5PE0Jb5BAcTCGIDJths0uOOZe51ioSuthpxf3h+Pnj8Zef7w+HKSt2iWxhLXVexI20AIRljeqpKPBqNS9C1nW82w4h9MtkiT31G8uMKoFiSgQR04XY1EuNg5QFAAAgAElEQVRVWtTOS5bI5iQdpBIWNS4uFR04QJfn2eMrmruOyCtIHVADk1O0vkcfk7kUIgJZ8c3dVgSl1mnKqupq5rCqcNxs+u/+7Lub/avD0+np01GIz8fT50+fj6cLBH2PUEmrLxlWAQMhxMC+EZ9LCExsw042XZeIlGAoJZsiB4GM8vPHj6mLXZ8kBjOfllxr8aoOraYigQOP2wFA16WYkruVWmupbpd+PB4Pp4eHh8eHigrqymaIMcR5meflvNv3fS958T514mM+P8wTTod6uL8futPd3R5OMTz2fer6uB/f7Ppws80fP3w+nY7zPOeCwLACJiSGWwjSRakxCGgBsRE3iTVRJAKYhWMMEZs4T9PpNEUy2cU4bqzmy2khoiDoutD3MRDlaZ4nLcu0HW9v9zfLkqdprvO5qLf1T61AMyGZFC1luSy3N91mE283g2bPU95t+uMDPZ4uhovDU4d+wzEChmUufR+X08LBuuSVpv/mX/3d3/zVd2OkOp+3N1sx+3w+HU/zH376+PnhzLdvd28obfjt3Wv7dJDsKQ3TtCzzkrxcluXFHeUNVnYvQCA0X6k1pGrVs9tanzebgoZLrW6f/kJZ5S825pbZgFYTAKtA69q9PB+2Vle4tiBrIULXYJpmH9NICGonhNV89YVN/LXqcmD1H2mRJGamtgr2VzHE9XRWwa4SO6DEkLUcM8+LRmNmcMC//7cfPn18/Pa71/v9q4cPP51PS802T0/nhyXKMAyb25vb4/HRvFatx8vl/ulwmUpWQal3wu/vXt29eYPAEjlxDDGMm2GeZyK6vXuVYrz//PnxeDwvy3lZjIhDeP3m7vatyM8fi7oqg4KbVK3VjZJvN1yry6aVki49h86lQxKxyKqmdc2mNnOv1t41CbjlgUozelhtASCr0MrMXISYVxP/1oZdO+XrpWtEBIiQJEKCE8y1uprVhqkprKLBm47oxMJRHE4BHABezWI8VBdQ8MBNae9Zl8SgzjE2cs2MSYgltEIEEtjAVOHi+7vx9s2NJD+djrlUaVOo5l4BRwiRmF0dSss5V5iThSC8Xgomh1bNWc/H+Td//X3VueqU67nUqagSI7CRuKOqea3VlMycifoudlFZ0MeYomDBZhw2mz0sPj3O9x+fyKKQVFW1mqfzuBtCoFKqmaqqm8UgNFIK3enhfP22XG9LYgKEpS3Wy7Rs9xuKdFnyCj6ak1sIzb3WHSBhhOfRWYCcBGkIMXG/ibt9n5T2ZTC1eZrOp/M8T6kTkF0u57rUGEMMQuRdF4g7ZtS6uC+bTZ9CChJJRQSbsR832/3t5vJwKEtZ8mKGYeC+24QYU2oTg1IWRR/zHGbKMTAaDcDgIM1VhUVUTc2FmUlQK1OIMbgv02UG83zJpmTVTnoBQKbnOElgIgsMdtcKZydyBPTbePfVq7u7u58//16rHQ7HaSmJYQkgDLuURrksJ4ifLk/Fyt3bu77rf/rxlxRkf7sbxv58ubirVgd0nZBtTojWcqSvreTLw9d/viiwXk7HvDzo+my6WhmvDdz60wY/4eWTrz9/CXRd+6pntcQaibXiS0RfrEZau/uCin9+XSf4Opm0PnDtYtcnok1WSwitVMC6+nKb3242WNfIFTeotYKd4KbumssyjmPRKswSBy4y8Qx1IgkiImJmVdWKXmt1MBGZA8ZgqiBFM8/yClKQkdVniBDNKX3NnWr/p/32Jrx6jkhrYYAgV1KCm1txMAeOQSKocfbFAwSBY3S/LLW4GUJEKE6A4Xg6Dbv0zfdf/fT7TxBXUtaW9Y0XmouWXLQqCXl1djTzhgkKrzK3NubBxHAXazVHCMtMwMBMZhVUKWaPCD1v98Pdm7dPh/PxNBdDiF3mcpwvENy+esvinw+PfYnny1PXybaOxNzH7ha7LQ0qJjvuqHfiMIW0xBhD36eqOS+mbDV6pQjkyasp5Xyal0f3OUYV1stySAYiG27j9u6OTIvVh+OpOegixvfv3hEnTv3hcvnhw6ff/fDhcEba4Pa1dH0XFEXdzMg9SAvogKsFUGK5XB7yZV5KpsBW+XzOTna5XOb5UmqdbV7m6fWru91uW+pCHEC9GS0lTHP68+//7nCePt4f7h9Pjwd9Ovh0vpzPp9CZQR/uD6bClrowpoHjd2DadHH/6oZ/+xfDT//r/8jkfYAWLNNU1aGOYiIIQhUuDf0hwND1vZEqTBddzosgpJRCl2rGMtXpfOYSgwUttS5V1TCLJcyUc8njLm0225g6YvLq27KZTpfD6Xgpy/l8zGUmYQ5xDVITosABut7L2vAOQJrAot3YROzPJYtd92AGGwHkRr6yfs11ip2uXkW/QhB+jYQ3mLtxf89W5Vei8PqsLxBOK5XImVvcbdPbuzuZUzMqbdVaGxJ+1i01l7j1VV9or7BWnU4wWLPvcV4RH78urmt5iSuj6cCqsXJ3tFw3XGVqz0VoO3itNxt8diWH/FcWTr9eWp9BOry8Um1RfSlxenFVvkh3qKkyCAD0Wc/jqza2DfkTtWqK2h7YFv8XS/OLIvbXEqp/+ng+pf8/8al/+vjPoMACcL0TWsTK9XO6vnMCC0uMzqa+els5G5QocbM50KapYop9DB7grlbU7LoHAgSr2iwwfd1TGGipeA4mZUbLATSoW7W6DiGzXwl6ZwZYwHydSSUmhmgzr3URcwO8dSPNuoQEjblrH6WLFy1OJiIUWBI7cwC7VWe4OIuQgIXgIpFTTGYOYaoGh5IaN+ebqkYphiCiYhTYyWIMIXH16uQs4kKiykGc/TyfN7fdjEXqek09iLMQOYJ5MBJnAjmSc4S/fn3z+HA6Ph3tUki2XoyYLJtaYWiMJFHKxdSr95yoK+7Rw0+/fAwHfGPfyBDOpyl75sRh6/2mg9D5iFpr4Njvo3RScnWDjEFjbW0ogSAgJ2gDsKENeJcVxgarOqY6W1YHB5a+G1IMfR+HzWBaPFZmbMaeY7ipm9NlznN1GFFtXDo164ngIbCRlkWrk3SpHzpVvZwutVaOKNZs/qyWkvN8OS8hlNDFEDti6mK0BHJWBYFCCACpWrZsZi3GyI1gICZSVlMPJBKcnBEDN0MKdhc1mBI5Mwm5oN1cbbFTchMDqla1AEKUKCJwyYvP5+n+w3z/8enzQ7YFqcfHz5+9ch+2AF+mqS4qzM42nXC84HyYXCq5ByaGuSrIBRKoJw7TqRTzcUjbsQ+pap2qzyFIkOC59mMoOsU4jLvkgsthKWWx4DyCyL08dzeNzxQIgVfgCqS1OszTlje7brfd5exWbOwGggeWYUyAB5mnqZoRq8Xk+3F8/ep133XT+fLxhw8//fDLM+6wGYcYxV3PjxMZ3NAABybUrId8gaw7wXgT81Jfve3Hm/Bq92q/3y/lrFS0FjNw8NSRBCpVkStIJQCoqswM4SgS3WHmp9Ml53lZFlUA2OSYlxLENgPM4Iw2q7IseV6mV2ErMeSqXRThrh9CjFwXzFN+WvL58XPjkAJjtxu+fvdu3N2Ocf/+rtsOp+PxcZ6meb54gTq0SZEql8XMtBtXDldCIDBTpwoHCUfhMHSRnacJpeR5LiEEEXI3Zk4x5Xwe+r5L3CURBqwGwpCS5sVqrsXJEZKXPLtjGFKS2CeHTafD03D73ti/er9LoT8dzgGR7c1mlHzez5eyXPLQDURUKtO8fPX2a9VMXIchAMO//Lu/Hfswn44pDYnpxx9++PD58w8fH57Oj0TYfvz2HafNzebN63c//P6hTP7u21e7hAe9P5fjqSwMW3fkL716m8agFoaxLswV1HgMW5uHtiOvvRLwXA+0aosdTCD+f5h7kx7bsixNaDW7OefczrrXexcRGZGJqgCRKgmJCVIJiTkDxJjfxQyJcYkBlBCVApUEEpCCojJaovNw9/DXmD2z25xu773WYrDPtffcI4AqqYTyTN4zs3vvud1Ze+1vfU2dTCMsToDLbMP0z61s520ePhLgVa1urs4ame+tiI8d0Xn9gccO5fwYj/aNWilitSXCao2MlWGBpgaCYMDmfI0TRyQiEU2mjgEEDg/pZz//9YtPrrrtLsbV3d2XoEDizLCAgFEI0QWfDUT0fd9/e/cwJUW/CmqnoV8FDk0ApmN/EoTVZr1er3cXW0T03k/jeDgd3z889NM8zIljoCbG2HDTXRd6d3t/6k+E5hhStpzERew27ek0bLtmOCVSdB2TA3PiHfv1qkiZxzmfMhjpOZSIHDCz8y6EQIiiWhIYGTDgYhxpuWRA8N4JCCEYLUusqKDB4mKGHw5mRkYjMCNUEsACxRyYLbxZYARidhXAUnLoPQGDAIKZsAoWRGQ29sREBYpD7zpeX/gySpoFHAIkQagC82IFyYhgnKcXr17dPLlM83x/vKVg+WS8zGuhRih654AJEBWUzYyNCMucRBQDYXQABlmHcSR0oYlsUoahzAoIgcF5RLRSckolZQElQt80rfOEJmqFmZwxhaZrulXTzLNO4+n16z3MixUOIKy3LXlar1c1Q9aw+kQiOfLBLSO38ze4Gpqo2nmAB5ChdY057UdtnHPOg6gWWXfdVBKYIhB74sCOyADUBL1zzvlIAnlKPY/ZUIL3cdV2XejaMM9dbHxJeRz2/Wm/3V5uNjcNO59QpHn6JB4Px1XXNLH17KVYmkvDTEDOY8mj5ElFEMAz+EAhUIwueI6hYedPh6GIpT4PmDyzEpkJAjnnAICInGPVYqaEnhiwFDOsmkJVAEMRSLkM/XAsRzBgBEcFMK83m1zk6NgEioghNJH92mPAuAnXL66DD7fvbh+O+/V6xYhF8sXFLsbw/v3tZrM9HO4J3JObJzdXT46Hk0pmxznn06knIg4oedFCExIILqTDGvDwp8d30Ct4hDS+j2TxUohgcU6puQqLj1OlgxLC2cGltr1LeOoiv/1wvsoCUKx3q64USFXNRueMdl3OdN5cAQLWnufsZXP+uqkZGmH91hkiGhkBACOplerSxUiMTIBWgLkGMIBakawfXH0JFLSAQNGm0VwKOxeij4GVzBQduegDgPX9oKnUV1PDvBgYFUENUDEDykK/qsZwoGDl0UunDt/RjLDuO3R5JZXxYKiVP1sJZZWESuQA1TIUVCVFp+C0lCKozmlhIzJs/JhGKwKeIFIBAQfvTm/iiJ/+xad/+z//HQfDItLX+JE6xzEAw/PAH85pu4iAUG1L6o4IDatVdl3/qu8NEjkf4jQWx00TYZz3piN7bTa42obr64snz5798es3/Zid67SY71y3agHk4slGTN48vB4Q+3FeWSgM05TneQ5voF1B8A1zG12L5EsWQmLv8FSGqR+GB1VhhtBACHBxsd1tOu/QsbYNxm2Tc5qnIwBvN82T640VOu2nw/5Q0ojonAscAjet4wbAj8fT/rAfJ5BqJ2EaEHxgKDqchjJn9pwGgAmmzTQdT71BTsMw9wbG5LLQ8XhUhIf9aS6zGoiqankau3a1k+NBAQFbAGfqRDdv387ffHv72y+//vb29jAc3tzZt+8BBP7ik/bq5qI/6Zxyfzw+9G9DgC8etnPCV69ertfti1efxH8RNiuyae5PMB7ncZo9+sYFHzw0grmQohVFZKuXqlnwjpDH09BsWjLy6D2TEpz6w3wSLQRJaookTHK0AUcoJbkQEdF7F6JDBxebNYFNeRgFrEgGAUfREcfohOcyEyJ4tGImUOMXkIAZ2TGqGS/dFCItMaOV4gxC9gjLWLWvq2DzQoyqndIHZhR86NA+YuUYVt7VGQvQKtxbUKNH+AFxCdUzAK0GewBmCrJg5LTMGkGWJ/mIvmPFjWDx1XukjZ2fwBkxN6g+gRWNXq73Cj6db1l7ODS1xY/n497z/GhLIVgYVFgRvTqZw/O88rs13B6Nseov9ByeiGcZ5FJhlrnDolvDc9LdY8WvIwgEcNWgYnmZZrW20yJCRKw8n4WydQboluPxySCiiHx42t89HmcVj9DVx7OK72Fhj7/5/w3h+jd+okcPrPpiFABBa0t/7kUZnHMueAE1LQIL1gXVfI1QEcpcLGfk4IMPIeQ5zbMs8YDnZIA6Y6zsEEUyJjXQosv0nKm6/hra4ljDCA7RVWyyjoEZidmxFCGorafVnTWxYxdEShFZrL2xYjKoYFitygnQrJQCDMDIHigQOacglWpWDTuMUEkBwDnvg1cALDWiD0rJwADVUkdNWTmQkKIHNHSRQ+tRcZzGakVZSlYQHWTIh8/XT9M4ihfIAFbULd9+ZQHMRJmCeQZMKjP4FhFL0hEwBGZh5xG1pJIVoITQhNhNqsf+UCSzY0OkyLt2cxr6t3+4e/rZzdXuen/cf/v1m/ULf/30Yt10SdJ8TDHEVbvRbLfv3uc5+zaYc5qqCmL5HigBFKgXHBBQYPIkViABACiDgs4lByavbISCc1E0K+wsRE+e5jTsrrYZU8oABgUkem8CUkA1qTkDyUWmAcQgrqRZ7zTnogUSzKw3N5uSU5FsUy6SYmD2/nQc3r4+qtmT68vdbr1/6NOcmHxwkYhyEhVLNIOYAweIAImBTZfAGucCFJBsiBRDK6hTKmUqJojAqjhLatutaS42q2gpZgJFLYlkKSFwu1qr6Nin42HqDzINFsPmZlumaTIzAdldXG5Wu7FP/cNkA0hU9jANIAnGMW22zcXmYihzVhtPA8QAGkGwJHPOB4SuaS62qxh1GHmYRK26LWm36frjITabpiVDG4ZpGoEYXICSrG6Elk+urkwMUBOA2QCgqJpCAxaCa9oIlrN3XRud05Iyb9oQPIELwXLSMoyRwueffRFC/O1vvtrfH8fDFHxExpwmJHDBAeB4nMr0CBIwAAthtfwlCsgmeZ725c18mNLpqa2fXH3abUM/t4fT3Tgfry8DEJQ8z/NYVAmt63wTIlrt7hwRM7lxnOY5zfM0T1kUvIfYuIfDPSNvNr7rMCcZcjZNRWYkXa3jk2dPzEqWfHu7f/3t++OhRN967wkapvD6t7ftzrchppRefzO+//rr0Ly9fnr9/NWLVy8+1WcvHu7ff/X1lzn3gIAmJpQmPT4chfKN3+SURRTRx9AwNaoookgMQAgYQsMMabR5Tqt1adpOi0zTeJx6AJTVBhRRSyBwBDmN72+naerH0VAgROq6FRiM81hSmodTYCRHJinPx8Oh590NdrnkIYTNZ188/fzT55I0zfL2j29TSiVLLpyy/vVf/2VsfNP63XbVeEYoqtA06+Dc/e27n/7iy9f7h0GoXV1ud+1oepqmzz55tW63D3fDfHBfvGxXsTmW0/gwmoKCnuNZDakSYgXQmJnAFjH/kjO9LLhoRtV0tNLbz1+RqulfeqVzt7DYhyKc53sAf46oQITE7k9Wvo8Wb8Rl3mVLk2OP3dnj8PA7N18gLKoTQqXHqDAwMwUiFDBSRAY0RF20J4FDSrOxOg5ZBQGIHHFuOvrd77/66qvPf/QPbtrVTnsO3rUhBtf2Yz6djqEpofWeeZzKmNL9MBUNm7Zxzr949XLjiRwdh+H2/g4dFyvA+OTJE+fd0A+H02F/OpzG4TRMU05exSF4YKXy/MXzY5/e358UAIFUfS6pqJKDYna5bdOUVck1ZKDKJUTXNFFEMMB4HBfIGwAINAB5dIFdcAggybRYtWheMJRsUoqRoqMCmZBxGawaElJNAFEzUEUjsgUApMWiovJrQFBcXhRCCMDGHtETkiEReeBA5MkjTkWyaVIAsUDAoEjkPDqHceO7Me7LAAbgTC1lU+daNZvnsVY/GGG9a7eXq/1bPRxL10F+AIqETKWIZi2lQAZR9U103gHDYk1dEGYwUozMDo3FU7y9u19tHHlNWeYk5MA7MFAFzEWmSeYZEDQGYqJV7AggpzHllNK0altQmMc0jimnyTkwANHli05EzB7ROR+d8waQZoEC2YHpkhXxWN4VgQxENDo8F3yIPhbOKnMTui42Yz+WklfbrYMgqojovPfBM7OBqoloYgJucDiMd/v50COC7C42FxcXnl27alZdIzmplJJLKeAdX17unKPj6IrI1dXNL3/1y22zbkIEwb7vswwm5thP45yP5XAa6sfrPDCoSpZCANg0oevWaChqp4f+cADnSQVyKY44BFetw5mZkKFyj4gJZxUrWYxh1W0vLq4Ijg8Pg6ZiSQ2BHDjnuq6dp5EdkwPwEEL1/dVh3r/f317ebNa79dOnN7517SncXF+H4DSX9Xo9DMM3r79uNd4/3HXx4uWLeHVzCaDTOJ5Op3nO+3fj9lnXdu3Qj9X1SdSYAfW7apM/c3zYM6D9+RsR1Q3gAs8booFUVtGZCVGvGj1jWOdPfTHt+6ig4dK9IxGeB/W1bFX5dX1Ciy1xpWYinvexhAiVG4PnPVItt2gI1UNwYQlAFVnDouwjJlfvSoxI3gRUVJcnDFjbdKhWbJRSmdLUQINty8wRG1OMLjSxKaX0w/DBDaxuNRFq3pIB6hnAsgxQoOqRP6KtGYKrqWyVXYEEZovWvSZVmC2RtooKagTogIGCKZYiBbMRUCCoiJOgFiiWus7PpYdi4ARIFSby8G56uJja55/9uyCAwby3NBRGsgrrqwHUJVOM6dFun8HgzLBQNTMTUFMxT4AO1KqBiAEguiQYOw++zGKSxRiaxjkPTdNu2u3Pf/77fkhQwu3Dw83VxavPn93f32WbyVG3aVQ12WwpFZen2XKGxoNMEFQQRtOZyJviPCU1AbAiJRcFAnLwcgMzwFCmFrhpm822bRvHVNBTK15K2venXAopWgYfwnqzZg5SZJrk/cPx6rpdr1ZhKlZjfhnQQZFk5rt2paIyjs5ZF/3kS03P8ogMJpEsAzvXdJE9jYcBiKaS+zFJtTQ3EBfQRzEnBQA7H1aIsVs9+Sf/9X97OE539w/G3KyuuvZh14gaADUKkai7uOjaJl1fq0jpT/OvfvWHu/fHT1998vkPXjmCJkDuvCQdLYMAOnWMTQgkarNJsgqyi+SUSGZhz2a4v394dvM8wcyKMbZu5ScepzTBiCAADM77sijCtRSYh3me5jnP9/f3lgq3drg/Hk+jlqr0Rx9D17Vt154Q5nmoiVdYnXigxoUBOkZX97QLWnJeIarpXIWA9JF6blB5VwvR3R7NQ/8EyHj8/zJeQrYlC9DA6rX2gVn60e0BgRQX5tcZ+65P8LtcrVpOzmjOYyl7nHSeG7BHrB4+VFcDBLbFMIuqxB6WaWmlOiyWD6BG1QHg8dEe6VOPD/ud6ryUaDpr2D9+bR//RrXCImAAVZR9djBc3mc465MrEvbB6L3+o7o0nvbRL+qdPXDg6gCIhjUq8dGD0D46Po7w+386vvfXP0Wv/vTuf3/4Wf/qx+NHg+A8AHxAPnGxe6tFv5pnI5GgFlJ2jN7QMTtUh3Pfg3fsvCMHBlrUzBrvY4yq2venlCZaZPlGBERAVbZBroBDx2ZacpKSgYCYKBB7MtJkhbyPTSRUtbRI+JBqYyMiDh0DoqHl+giwBAqjATsgBCjgGBwwc93km6mauJUrVhZI1oFvA0cCMmBQFDWtPfe6XYvI/uEICYAAPIDzoOLb2DSeHBqoqRYSZTM01eKDB8acctM2vuU5pTlP3WrtgpuOpxfNdh1X8wzffnV/eHeiZhPajZhIGU1H7rBoCh7WHq667ZPdi2/+cPfw9XA6qqNoM7CiQ/NMhGIlzSK9wCLhIAWsOnkADxAAAKCFq2c3F8/XeXfMMGkxQCpJtpudJBtO0zykcZxkXi49OI+GJBcVIwDnwIyAoWnDerfdXOxCE9VKTnmaJnb0+y+/8oRE9uTZ1dNnT//w1W9L1mkubePQlx/86McKOA6jGTRt/NlPfx0dRN+sNo2KBnYiYgDg4pjy2A/Be+/dPE4PD9PVzjvn29g0IbLDnNUFn3r9zS+/aXbQrhrvg2bwLiDQMEzzNKOSKqSxNKWFAkVyLslMwBN7AlJDjTHELqqWYZrEjJBNQBXJmNEFdkScLYeIvnFi2aC4Vp48Xbtg03B/dXN19+b9p89+NPXlFz/98uEWtm1jgsMwIdnl08tpTJpRCs6H2cYCYO26iZfu4d3xi3+4Xm0ie51kEsA00cP7/nhvMJ+vSD5j9Tv4qx9ePHl+1axjzpkZ/sVPf31zvUbEnApi6Lp1KfDHP7y7v0+7dUzHLBkli5a6HwpgBpDJQRFFgdAAOri+6bpt6103DeXN29tTn4Fgu8MnT69efvJyHOaf/vRXz55/8uLmaSS8ff3u9ds3t7czzECea5292F1e31zHEA77/e3rd3k/e4qGVBLkLGDkvGPvcpkUBC0bml9ZVvAX8B//R3+93jRJT6f+/fv9mxefPt0fH/Z9rwY++hAiIUvWnMT74DgOw9j3wzwVNRAFBIgRmWFOdn0ZU1YT9L5tV5s2bpAoixgYEoxTfzg9pDkFu3x28/k//6f/y/PPn6JwSfr+dt81rYpadRXOOUtZaMYCAOAu4IefffrJZy+I9e79t4Dp2fOL2ODrd2++/Hr/o5/42EYEPhzGh30igRipbVeOvJo6hyHGUpKUw811u9utcs7BuxDc1I+3t+/HAZjg6nJ3dXWz6tbBOUR7/frtcRhuXx+7dXS+8c5XHkqIIUaPjMR4dzhVVpNj38SmazYOyZSCD03snAuE5JANMjlddV303lRANfjQxIhI3/7x3T/77//mX/5s/+kLfD9aCrC7DGDpR5//+Nn180+e/+S3P3v9X/0X/3TqBTw8u372/PnT0NG3h6+P/XHOSQxygtj6NjYpJcs29clG8J6cczKqziZZSdGbq5uwPOYlowKh2icYWjar6YUAi1F6ffsJwDExEYAVUal2nGYf4C98lOl8aD/Ou74zHHWeVn28yFk1I6lbO4PKNaBF8rKM7QCrTarDghWGQ6qm1waIAmCqqkVrQH2VRkJ1a0Jwi7K6Y7JG/vP/7D/5R//4B9od/5u/+S/BeLg/bVbb9eYyZU1FNrvt9nqbSf+7/2VHpJYAACAASURBVPF/EwNwK4Fw2t//p//oL5/vVnHVIjN6/umvfqGqV5dXV1dXc5qvLq+GYUCAVCyJnobhNA5jKQJEsflf//efBh+luGmSaRIVcsColqYkZtv1drXZAqIUPRyPb28fmGG99jFGBEyzBm5DE4LzJjKOc05ZRXIuRK71Ied8Oo1lEshkZdlXe++Cb3zw8zxLLogMACklzIqGItasmtjEmlFI7GpAioLklBUhtn6WwXdOi5VZMBA3vkhBVCMIrbu62pWckkxGxTXQtE2NIHPOxdjcv7/btFtULHNBo37oh72WGYkohMhMAOSdv9iuleSzV6/W27Y/HX79m5/fvh1hQklYsloBBAwQHTsiR0hmZgir9Woch/2w32y3vmmmuZ90oojiijkBhU8/vel2cBrer9btzfWFd/zHr1+PQwrUMbeem+vdky62IDZP0zQNZuoDD+PJObdeb+eUf/+7r9+8OzmGnMEFN+fy9ObJ5eVVbCIZDH1/OBzmNIlInvM8Zo9cJrUZWJnUaTYrAlJUASLEtR9L/vRHr66fXz7s7+dxMhU2TvMkIrxukmQkZGIACE303iEaBZzmfn/YiwIx7FbsnR4O9m/91WefvHrp2YmUeRx/+Ytfv7/rNx1tt+uXL15cXV+/u7v79s2XXbP+/e9vf/D5y2fPnkxTMrPoGnbueOhvb2+HaZhVYtOYCSK0XTNN08P+uO42T26umrYLoX37+vZ3v/vDMEHXrVarlQicjv0wzGZmSTCG6huAaFWPhojslYJ1beTowXA4paGfIUHT0m7btJFVxxfPnj19+mxK+Tf/15dff3vwATbb9Y9/8pe7y91vf/ubKc/O0+7iomk9e3LOz9N0OD4cHg6n/eHZk+fzWEpSUDJFKKgqqjqO4zBM46wXFxswLkmCc5Kg3x80CQGrGsvZAMXq3LemqVbHrPMIXcGyLpSpitcTEIJzUUREZInewwpAfWjQHwMrHvdXi1WwgOt4cV9HYCLnfJ3Mi8g5r6hucf3jJs3q0NlquFLd+52LaGXFVj7rYzT5WZP4eHZDSJoey27lzRIxOyImJDIz0SKiIkVBkcAIkAAdGpkLsf64bNGYq2uPqBBR4zwAalbNhZmjD6Za5jTPSUvOfbYMouCRnTkVkiRpTGAIwQEAlAKMVS6AgYnIEFQLmIE/ryMM4MA5h8yIlKGE1odNe5qO5IBWLqeBIrebJqWUNV9fXSRIBsgYEEjn0h/3MsB2Dc9fXT5/8iSN9ttff/nwbbKDD6UpSSGbYw9I8zSXUir0gB7RgZkQErsAlSsGZmjKALkYCkYyqoZ1hOS6i2frq83Q397dfe3XsLoiIP3xT3746Ref7o+nf/bP/3bbts65pmNkKSZ1QWTnQmjHee5PoxoAgoKMdwk8gAd2sFltV902pXI4HOZxWtg5HtZb17a+6PT559sQITif5n7ox+Bg1cJmxevOp5QAzDtbd3HX7bqw9qGd53I6DtNU1Ph4GryLm81FiNEUf/u736SSwJOYljlfXz69uriYh/Hu9nY8nFrnf/jpiy8+edk430/D//Gzv3324tV6swbUuaTL68u3726//ub127uiAH/xkxfPn79E9AE8Znv58os02s//7nd/8z/8T7/4CjqCroVuFUMbYxu6VUee7+6O376+nQv8+//ev62Cd+/u9/t7QkCzYeyLwqsXzz77/Nl/+I//nV//+jc//7s//PT//KYknIfqxMgeuQxznsCpk8nSg4T1erfdVJ7+07+6/If/wV9tX63288NcZlQaH6Yvf/7V+/ezM84iXdMODycoELcNMkz76eKTjaF554/pnh18tvtk7Kf7h8OxT4tUXyE0cXW5LlnHcWQkFYUJcDYQK1J0Uufo8uridDwujCnHyARLEkrJc1aDwB4MLInm6paPolbN3g3AuwBL5ukCi3xUbezsNVUZ8h8BWwYG4JBqkVts58CW+WNd5KEiTYsnFOoj8AIGYOnjDm7xFwM7x/8ZwaJYBDWBAqZmS6gVao0vIQPGCokiVTPoimXRYiZXISE53xcQTMkRgNijcNgMzsGpFYSq1uuPEdmP6H/dt0IVJuqHaYEsOCHUtfXRYX0p/4shn8Fs56Qx4Fo/rWIGtkTiMjnnjEBAtVgRqaWCEEvRpdp+F178wOr6VxAGPvKw6mfwPXgOvwuQfe8u37vBx+f6+Pb/n8efcsT+zTOwzmc4Q51LZuZi5aiiAoWdq5+5itZwb1GwjEBAdYdSpwbsFodYMEBlhx4c0ZJVBNW0sEpCqz1nPSUiECKji+waZ6TJFASMRCijRzJURax7CKx5PFXAzgSgpEiMzkARVJehD5shItdUdAU80wMJS0nACAwACAzZsik7z+iQmEFBQQQkSTIBJDL/yIQurm2IQUBEKqvdDNRQFQEdhia4wMmTkRL5EL3hkojomA7z+zmdpDgN2W25yDRNGUqBLrSbNq54HLOBCcHuejvP05j6EUe/idJPwKQIHyjjWGAR3djCQ6xQeeVrGhoZg7cEaSjd8zansUxa61kuOeeiIIpqhBCAkAmojqRqu5KTaIY0wdXzDpGNoB+GYZpC6wl5TlNK8/XV5eefPXeOTv3JB8556Ps0TWAKgYUI5nlSw5ySiWpJOYFl8KQqSgoKMM8lp9kFMcA2hLZtnGM2kzZVpnzNBUdhMDQBMYUAUwLnxbOlOU1jYuKcpGTFJUAzSwmkVD0algGjmhgAQVFlkToFs2SEiOQUABQcsvNhfzgwAwBlzaLZRUK1LAqKWflwmIYR3t+f8qBlBiyQJq1Ooo54nnMWYXRMzNELegQbcxrfj+Ah+lX0QSmP+/44pDSCKjZNyAgyFkAGLUDmI0aC/e3Yn77tdu1q3ThPbHA6nrwPPvgqBAGT2FFXQGxGzwSgQNW6vQZxVgUUIYQWug7IwWrju1VgdioSgoMhgwKRqc796cGMX754enN9bSbDkI+nYZ4UEYxg4VEC9MMJ7zH6MAzDmCcyyzkbkCoBEyKDoyqsIIfkvVXXG4Bc4P5wyDbHFrrtOmy4yMiOuzaIqAHKnAWFyMemcRzmOacsxL5bRVVNaVQFYmaH3rLzhqSIMTiHqKf+PmcrakWFyIppyULkurhKWZ5//iTlctwfHATngxoDcNUkGBoIIBR0YE7NoMzw7bdvjv1xvQkvP7n54ocvkPL+8M552mxgvdkAIQJvtkSIx/08TWrWr7p108QQfSn5dOo9V9ETW511qzqGrvG7LoARMZdh7pMeVAEguPbFzdXLJy5nm2cBJGJiR845diAmueRPn91UMoL3zvvofXREiFzRGFg2EehiIGfMVObpuD9M4+SYTWno0x/+8Ob+NG8uqS+xl9H5UDAiYCpFikZqduuLhlrzKc3Q3833eOy2YbvdtG1zOJze7/cAUEruTRz7Oi00Z4IKkhEJGFCwjtdYF/t2+4gTZefYD1lMdZdqbNUuAZcB+iMnRZcIQLAzGf5PeA4fyOSPDHj8zszu8T4fPfZihbCM4RbUq9rt2sIIQ6himrMGcjnQFh8VJgRdzB4QDFHBlA0xJzkchsNpXLfOx12aJ0GYVaIpBe+YBWFIZZL5/gClgG+k24TL7RNlVxxF7yEwMnMMkvJhHGxPkvJqtRYRU5hSPg3j2/d3+75XhNB1q+APJyCayzynGaQAGgdvXePXF2si3zVd07VEfujHpmlurjeVYT/0fT8ZG3iXWmm1abz3vgnAeDqdZpnTOJ4ImIkCNb5BoTLnXAoAehdCDCklIREsqhkRwBMwQTZAm/KYdDRE57xDFVPVqv0HBBDRdh1960tRc5PznoMngaq8IQ8cED1romJIZM4zkwcEZtc0zXuFXGbJUnJpvOtWzIwloxSY5ykrBI5J5O3DuNmsVtum7UIqrlm13XZK5JDRKAsaao3P1VJmMzNTZqfY+jaEEkxVSi4qdfBMRmAisNAMERkVJCkDd80mkKFFNu+5m0+lf/8w7E99fzLV9ard7tbBdzc3T7quOxyOT58kx40ZTlPZ9/vo3X5/yFnX63UIIc9zKUWkiCiSxdaVWZ0jMNSEUlc0MCQgh4KWNV8/vbi43jnv2PF605mYJhmH0zgms1REAYCdI8Ki0rZhs1mtd12RoDoN42wIU5JSgAm8YwDLOZWcVXSz7hxCE2PbNERUNLPHrluvutXnn8F606hKKVmKaCnOeYPUtt751ViUmESL97xerdu2ccz9MLx99w4AvvjiRz64p0+fjHMhCqo2jlMuiciYgzKIShGJwa/WKwCZxjmlGYCkSM4CTJXi6bwvkvHcFQLYnMbD8b3z4fpm6xxnhc1ml9P8y5/9ct8/XF5dXlxcHI6H/WG+fnJFBON0kpI3q671YZ4mACTEOc3TlPIkZkqI41jm3jhCPxxzAVLIHBkYCdk7NCKxUjIB25mk8ChdOVeiM/lpmc0/liYEgFLKsoE8uyed/aaWw841Sk3xTH5CokpxOE/48ewRb9VQ2M7OOWYLHWs56dmFNqeE8KEpBqiJFsvmDXAxST4/ddM6RDICMELUs9WmAHLF7QDMUKlQzc2s9Chc0BtEqkLicyQpEmAt9GAqaNVeLyuYmWRFNVU1MVOVnEUEAYlZVciqK5jjGtuHDhBQqSbgVr0emNV3AOsyr5UrcX5DDdEQFZCQgKwYlGWLAApoBIpaDA3YEMTYVasPk5zVStMBrrBtQsFxkmG92z7/7Ebz+/t5AvbeU5mkH4+ovm3bMhhVHmr1B6mvG7mu2aqlqJkUF5lcAIZiolJSUUCQpmnNXz1fU3v57vZeRL/45Nn1xeXpfnr3Zg9HGKbJe28ZKGqIwQcXYoxNF5o2v7v1LgAxMQNCzsdQvQuAnGuIoveh6zDGFZKqZWZbrXxsvWogcgRWA+JNlnSttlmt1y1CZjItEwOboghgKjnnaS7DlNWk72fnlDggoWO/Xq2KBUMbx7GIHO/vbB4dwSbw1dPLJ5eXr54+u9ysS5pNy82LV3G7ErZ5nlKatroOkbeXbeyUnNttt4CmKsW8h/a4L998ffub37w9HuAqwDQDUQzNtls1HEnRcioCurtcOXLNqpvHFEIwxbkUUCmZpOjD+97w63H6sfPctjE2AIaTaVYgUnbs1g1qKZOyd2Hn0jg+7AuywRrIERj2fX+aTrnMDrxmITQCkSJoUNIMAuydY6+gFHnqZ2MrbQ7BI9nd4XYa5mE2QwgtAUEuCgFKzjlnZnLO5zkXyKoFBJwjXnkVOR5P9eKs9eBM+alUQwADk0WbqlL5SRUIgbMR0//bgR+bhn7/T3/md7TYcT12Y+efKttzgc6/d/9zIVyAEsIFUIPanOG5msGZ+LkIqWspw/OE8ztAyodHJ0Sjs/k8LEZgy0j0HPdQdXZ4NpMgAKPlNSwWVACI1cTuuzPRpWtcZqu6DAPAzk4UC3oFgIHqS1/ol2cyaK1fdNZy6kKmQ8eVYnaWWH7kRfin7/u/Fgz0Z5WGf/ZxKs71wTDxu/jX95CsvyeHq3xXODf1gDUBDJjZ1HIpVYvExERoYGp2HvHUL6uImLEx8pn4pmZ1olQZ8rhAVfi4uGN16Tzz7gAcEoOLHFtfSBUAtIBHDOaDQ0BULCIgqoagILYQ+AER2QwMBUnQiAyMHAKBAS250+evKiCAKQWPnsgxkhkZsKFDjkyByGHRXBS0aNZcKYIL1AUGas4hOkSHyzfWqlEXmCoRkgNmQLAixcx557TKTABc4HWzBlUS2jZNWMM0aBpyyUpBqvMLAHpnz5+++PSHPzjdn+7uTtMkBDSWOYGSoClW43hFKcTsqnZJAdlwkQBX7TGgKUIepN8PW94AWC5ipjE6H/ycSpZiCM6xEdZ8xxpjHLxHAyiqRVVUsobogDDlPAwn7JmIibHtYtu1q3UDqN4TkolmNTAF75fOSgXSPA39WFJiokDgGTw7NieqwfkuOghrH3wxzSXVt7aJHtZd08SSpGQ9pQEMVIAcu+CePrtghLZrQghH7I+nnomddw4ADFVNNOZhNmOpQHfF5Bi9q5aHtMRNEnIkds5hyHMpUymawSh6H6JzgcQykrUx+IaKgGYtgvMsTO506qeDzhNYgaQZMqgCOprmXExdbY8IwSkhgrFz9OyT6xi7aZrGaXq4ywIQXcxqKakJuRCrHoscBkYs9nA7jwIXF+XiSQnRrbtVLrnMmRDM6TT3KtB2jlwzjyJKSsCoSlgzvpAUGAghMqxWvlt5JPFeEBIRx4jrlROBonCxa7rOqc4htK8+edbG1Tdffds/9A+Hw5iy9wyOiPj83sqYhqK5WPKBNWlJxRSQvHcOmNUslbnGIAJXCREZqxIchlGoXMbmcr1abS5++at/iYTMDkBLVhEVVQMjp2DldBrHITvnnSM1q7YYnpC9I0YfuEUXYuf9Kme4u+uPp/5wnEUVGBwjOguhmcvcD7c//gd/8cevXs9DGseZCqGnKiuunT4zq5qqEFN1VTr1aSpJbfu06DTNczmxd598+mm32nYrUhMi3m7i5db269PpOE3jQTVLQXFaci45OwI0dOQEiokYGhO2Ie42F6Y0TdkxO/ImklW6dtU265evvigZc9IskFK+u7s77ftcEoCKiWYzUEQ1y6aTiKGh8+S988G3bfTeI4ENBbgwwtgP97f3w7EHgMuri4f9+Ptv3vRC1LWHIZ8EGyEnwGhznnOaGu82beeUnYZ5mPtpJIF5cNfd9vLqCo0Px95HRkf9NAIKIdY5NgCIGCECgXGdd1WuGCrYI2XKyIxQcaEYnBNfqhvWUlmrVBaWy9U+Cpn5oMP53rpVQamPQCuzahNw3j2ej0qIWPB9WM720VBrebRqHnNWEuJym8oDN/tAViA0qLo5WJxRQTWrlgm+/sOb5191P9g+iXEzpVkY+jzRNDYNJdU8T6OWAloSpASpJNWJTY/z3CayHDw3waGSSzLvTw/H42AqF1c3VlRFxmk6Dse797cPfQGGNSjGcLlzKVOfUxZIM1RdTWy4jYHIFZFxnJm1iDgfLmMDYCnNvbHkScXMLOeMiDkXUZEiYtlHx15LUUNFptZHUJ492Gxm5IILrTvdncyZglk2MwBWx44ichEDEBEEcJEAIKdkxdARMplB1tT4yI4MjJXQAbGhmWgBAxUTS4iGJGiCBExIRLUXL6l0TXTMoAII7cav21YKqYac7LQfGMNqtc6zqOp6u3IxjGlOOZEjYKKWwKE5R16tIC0jYkm5gKqAJJ2dY/akUPPTpPqimYEnFhPPrg2BrHRdbEIXfKBNnPqyv59OxxFyksnynIf9OE8jAc2rMq6zX7kmbhw2ILxut/Hlmtndvzu+vb9fdbE/jaLA7KH6vCCIWZJEZkwsWREICA1MioIYA5JzymrZQHh3tSXG+/v703jabTYIliSN8zxPAGSaAQCKK8CgkJnW/mp3udsaFNFxnSbvHaiiqWTZbtfe8TxNJSfLZb1quiYE57133jtQC86tupX3/tWrF2aWi6y6VtXMlNFF9m1oimo2KGpFkvdus92Aade0r799d3t3vz/BF58ZGmzW69BoMTwd+1xSlkzkfPClaJkEJAP6EAMzmlX9kUqBaSoCRsiq1Q0EDEyklAIA4gMM43HDu+cvnjx/8RzAOx/fvrkb+qFr1oeHY3Bx2uexHHe7DcRQ5pkNmiZmouPhuGo3jDT04+k4pgyOoQ2BmSGUJ8+vx3Ge52QFCZCRsQmaVZPURCOtzKu6pdHHTFVYdk2PteP7NYxKFvxggLJsyqpwaNkn0IdJ+yK5JkIAPg/36+b0cdOEiI/QmS0Ps3A1luHkuZldnuKZu4q4gGhnw6ZKVUBVODvKAIBa5UFUoG7hZKGpgliN+lHTJROjvmLCirgSMcBi5LzsGwWxZgbigm6bgYqaFlNQVTGRmmkO6IiQARUYiIEZSNSIkJmkxneYgRjQQqYGMH00orElEK1uWBbzuLr4qMGynwHGWtGMKutbjQFN5Xp9oWgqKAQYoGmvYoOxgWnu+7RvN+3u6ebUz/cP03QcHXles1Ms44zcnoWmsGwJsaq7FGmxkq5AkZYz2WGJHwFA8NGG6X23654877pN3l2uX758SRrevn7Y344drayY5jxKoWASNXtJQVNUF3J0jXigGk1r1sQUo2ciEQEjUGPCGAJhQDaETF7X6xAbr+o0nxSJeck5NQRUjhQb1zCG6GBC1pxRMGse83w4TcfTlAWY45zyOM01znazWd1cb5GxlDKN7dis8pQi48V2s2nbdRuvdpfrptGUpuE49cfd1aUyjONpfzhO42m3WyHKxW4dfOtig9yIgqiZYjH3zbcPP/v5H372i2/evofguagpRHQR2avleRqzlCQzeTbTw2k/9POUpyxpTrMWmBPYDON8erOH+/s7AG272LRB1AAUMmSnGqxrGplgGKeWKXS+TCWnKaxjRV93FxffHH7/7v5d3w+RfaTQBnexDtNYqmjXR9c0DSJJ0dg249SDh9Vus9qFlOZtsz3cH2Y5qQCHSj8HlVKU2JF3kaq3axJlAwV05JDyLNOYyEOlFDEaASMxmKEhLd2OioItRsZ1E4yPtCNYcIoPLdX30Iq6iV/CeB55N0tBOVPjP7rXmfDyAfqqnlgfZbp8YF481sDaES4gslldavUcOQoApkvBe2Sm4vlZmFm9VJdmjei8v691sha66nttqt8JBVp4YwvnBhYRMtYR5gchYX1/RGSpjR/4/lC5AY8W8gpgZzrbx6fh6BfFYZUeqlaJIVWndkBYJI9qUNNcARFMzsXWvjeN/dc+Pkad/uxfv/cfOKOC3wOtlm79Iw7a36vD2eNStsCKiGREjpgUFSuvDdA7Z3V9QkA0rdnYyYy0ppwjGVRXcoOSTEGkpAojIFWL3g+fs5qFEKqNO7ARAHlChxgoePLeFVZBAVRiIERVpmJaAFVVAQQMTEGxko7IiAgIVQAQiEEJ0AzIjADZkPExWo+ip8DeO2BQVEABNnTEnsAhCdYlUJOCgpHVsValVgqad+QCAxGaiZhgqWfEauEFZqhasooP3gXvDMw7x466NasWyVASgBPy1K6iaZPmMk09zESgXVxfXl9yE3ZPr7o3b+9Px3QSbRZZcw11KQaAsCyMpouPSYXZyc7YPBhqGvIMIrljQkYSU+fYOVevN+edDwxGOZV5zszsnI8xBu99tb43e3f7rpRiBUsSFYAswuJaj0g5FzNDMOe5lGRaths3B2kaX3nsKCpJQBQUS9Gr3drUgguOAoK2oSViQiaHOadJTTVDsYDMq67xcZ9OQz+NQ1EBQHXevXj1/PL5RS655JRzzqk4ck0MpoRkUhTVQGgsRwRXKxwgEBMxAhkgAZEsvRqBVfMJZCQlZnSeXVbx3hNZKWqgTMzEc8mSZi3Fc9jttuMhDcNYr3otANnqjLKYKWIxBclQ2WAA5svm8vrJsyf7w/vjcExpmieLjWt8ayXPeTQxbgJZTdYEEE05lwQAMPYZyELkL37wcsrjsX9fcsFS1OZqfN91wVEZtUgGcKbZQMDEkMAHCB5i47bbpmlZtaQ8z/NMhE0TL6+60IBBcV5DQOeha91u10nBU3/cH45q0MRoRmbgXCCiUiTnVKm9wOY6nnpZhgukSrkSZAELBAO/aMd8x6Hx6rI5GkuKmba4im0c595xrPWGgJEcIsw5T/0sKvOkIsCsNewTapS7d03TIBSGEmNomxYozNM0DOPpMO2PJgYhgAvmFJjh7uH+4TD86C//b+berUeSLEkP+8zsXNw9IjIrs6q6ey5L7lCkAEIQoN+gFz1JP1evehKlFwmCFoSWnJ1dznRPd9c1L3Fx93OOmenheGTVzsxSkCACDBS6sqMiIj0i/Jgf++y7/PX+lA7ntLy7tNkoGEHIGexEHojcA5wdptagcKAqzsvz6XL48d384eH93d3tb/7Ft7/669eKZqrunQ6CW8IwxPORWi1AczVCG7LnDOFILuTUaiVnYaSUUohupOxJ4jTubaC51Jz2hDSk29W8WHn49Pjw+fkP3//08eOneT33k5LIWSDCROzY5GwcaJqGnHPKkYiX9VJQOOJmNwhRmS9lWZiZUmggZGaOzXxtxYmLw4AcJQZm9imHBDDq+eHCLVDw0+PxdFQ5+LgbhWOMMUwRgZe61taCcLcP6aNsM39R5JlTg4nDu3KE4EIm3oOqvmQC6rWdYJD286bP/93ZcXVm2qhT/9TtSp7afu5/sbw0jRtd5brLub4iNpTt+mM/BR1G0vFfujZl5Jttp3/ZFmHbuDF6nHX/A5aAtf3h+z/e/y5889c303R7qScpeV3WY7nMZrUaM4WcYs5DAhzn2crlWFd7+tc3cmyz29Dajqbqvro/Ho9kFEVbU1Ora13WZSmzQYkBQdN6Oh+/+e7ucjGR4rTOrLAo4kau7q2Wea4ECRy7U3pMkZiFPYWsgy/ntXNvTV21rOvSrKUUxzFToHWpTVciokhQ8gZTd28mwcQrioiwiAbrcUJgJyMOwsy1kZpRJHfvXopXgBKArevqrE2t1BZgTta0hUAUYHAWC1EQUkKMMeQ4mHlrq6q2pQ55CEIi5mT7m3zYZTU2j60AoQUe9rv9upQp72OMl3WeLyfVAkJtUKqURIQ4iS2uVdEtuLvZG2y11TwgwFzNmqPhqjQVjjBNMe6n/S7HcQo5D4yEsj5dHn7+/sPjx4alMwyBnpVmNj+ewWfscDwu3/7ymzTG1ur+1c3d/f363LBCUyd+cGu6rgXUOqouSr19twoV61MXR7e2ZggcDQTJEof8fDz9+POP1WtKEU0vpzLPACELr8367s0ctWJZ1nme13UFa2CZXt3e3OyYoLUen59DCLXW5TKrKpmP48REQhxCyCES0W63CyG42+3N3bouZa1Dzu7eihLQjR1KbWk6rLWVshD5EGPXmU3DMQo6jlxLaX1X6a7aVNUdLMRCdS5d01RLmed5HIceK24wVLTa7WlYVbvgSKu1oQAAIABJREFUosMlfQnv9+PDw+fzmafd/vbmsN/dxzS4ekxpmnZ/82//pi5lzHm3f/369n6321lVM9NWH58fTs9zkiwca2vLAhhMwJFT4Djw3Zs7e/d5LSWkwE7swsTNqnrrtDj/QlX6qtT0QrOZFf+JdcyXIsZMwsTSGazu5rY1Mb4VuS7QwQYZbXSeq4kSsLUdZvYXbFxA5g7fRA/XSfVXNDB/KWpfnrr9ct9ivMx7q8e98G3aN+/JsNTTW5sbs0GZr+oi7zxbZ4DdBEoApF8c+u81bMgeezfU86beaY99pq6uZgCJMEn0UAH0rFFsdDQT6Z/wVx+wYxs8q33Jh/yarutMzuKdxkwOoKkDUcTI6tWjihzEDEPisCxVayOEmFKKIQRLOTr7vBwvdR2H3eHt/v5pfvTL+lRiFIwOQ/EVqNZ36U3YiUjdyRpEqMdWbJEStW2GOHJNfQ1AWJ7KOZ3HX969+vaX303jXmj49O786afn+aI3+dXlcqnValEXb8GcVtBKAcb49T//BZrGmIShUOHGnVqsTb2uaERipiRMDJYWA6UYcjI4rbNGSlOKmSk5AvsupUiBG7upNuPqDI4SStHPn58/PlyW1cbdNE7jAfFyOZZ1OZ+Yqd3f3YxDJhDd7NxsXS7suN3vb/eHKeXAbHUty5mhN7f7Y5S5rrWUdV7OxzYfn0RkjHk/5JCGpVhtFikbwulU/+7f//i73/34/tNcFRJSHALHQZ2KVcKqtCq1orND2qrD8QMsDLvhVm/Wy9rWkovWUImAhO9/+H6/30mUPOa1lB6vYYC6932OA9oHuKm74AvmVUTu37z+P3//v33+/On5CSnOr/dpn3dMDJzrqgBYUkxpPpa1rLubHRow4PZwc7gbn4+P92/vq+nT+eQVtbW+2nLiV4dDzrk1K6V6EB+SEFl1N62t9fzfjsl0cITIjMDWLWTYe/Rl6z5xgHbIhtg3xe/XPJo/5+b86T0vQNdXz/KN6wWiDZDacCYAm2EmgSD9CLtJF5NeZULXQ3eA2KUvTHbeXvYLZrI9jryrwWijPnUF38seka4mwL7BTL0bNrdOSGvWM8o2AjUzCJ1pw3SFbKzng/yj907oroBX2P+lkPgVhduO8UUz+PJ0IsCZpXvtbfrHLYSUuoMSmNzMrQe/u2OjPm2J2y9v/i+jT//El7Ud4Zdv1v8Jo/c/efDXP/zFB/znxrr6+ha+wli3LX3Xo262bR3bdHTBkW8zoX4dZCXtWdrSp0jdB8DUralrbddsyn6KvZwGvemQbuDU5YWGwC4w1hBDmGKMqGhNa7NCcGN3ccC9wck363l3N4O596BTEACFOTuxA27kTH1JbYOkjnYZvHmDkbEyO5gIVtWdVLU2b8RgEbQrqTpIEOkjJghRIBLvQxVyGDxEjiHkFEOMJMxzT4JxIeq9WQhhtRkwJygZRZ/ymGUInOfjMl9Sjtkd0zg65I/vP72+vRsOh/3N+tP8cfcqnNQg8AZ1qDEZw817GaMrvN2/Pb3C0A26uPp6OZ/TTbJRz0s1s1JqazWlLJwkBEKotcVYtVZ3a9oCS/ekgeO7b7+7XObj8bQuazcmpMCo/vTu6eH58b+++S+HHOb5fL48s/C0G1Nq0zSdjvOsl3WprtgNO8+YL8vN4eZ8uQgkIjLMlZe5rMtKMCJjoRCCMLFwEl7mdb2sl2MpM0DgjFYbGjtoPs+X+dSqWqVlmVttbrTOqsWg8NLPJ+0nBJgogCOTEEeRJCFLL7uBhEFWvJAKKTsL83pSa9pU13V1aaWKramUupaFCCnYm7t9OV7W8rSxPxxO4I0tG0jI4BAjcph68zzmYYrHy/kPP/wQQsxDGqOUS3k4nUl4GCZTW8tKEoUD3GuxujYHycDufD7WZW2MuB/ZtM7r0aHuSuTmTSgOYy5zJWJFg0OvsL0IUuY8hpRZgkNVXIkQkw85phTTwObrx4+f00DTLk27CLSmNQpSHIKwqc3zupa1NQ0hbu/HrZkzIwhbX4YCZ1UodN12YAHO0AYQcgzjYUCaZBiW9enh9DwcZTqIxGRq1lw4xpCYcjVba6u1qbowOJHItpV0V2I3V9UGqwhMJOZUL+vj4/Hh4XyZkRMMiDFwDCxwiKJ4xPny3nmebuVVG9rBnx5mGKCEBjhJvyDpthUAI+5wuMkx22k5HX9az2UZ93FtC1t6/eZ1K21Zyjwv67q2WokwjlkTM3sgNC05Y8xpGCehQKA+UmbHkKZSilW3BoeLS8p52t/d3LwhxMtZ//jDh3/43Y9/+OHd8Th/eng8neZau6xKJGvO2O/Gw81ud3Ozm7JqPc0na2N1qtVKOX96+Py0qAvub+LdzTBEZo4U5B/+8P10e4Ps1dYVPt6Pvtj5vK7Fkmht53l+KutZ2P/lv/pn73/7t8NtDlHm+VRnPHx6irvozG6kzUBOLCBzZhEz2UL6tkRa9m6Niy1zjol65DNYGELa12MnVDPBDO6kcBhaz4xF51frdQuybVf6Tf5spwVcKehf9g3EGyv4ZYfk7i9O5b1C+lVD+PU1uSeZe/d36GQugn/FH+8N3hc+RG/qsEHjOQ1N1/eP73/8cTid/otpf4jL6FGs8ep6Op/qWkXCnvcxjzGhFmiFNUNFcXpa51OreS13bIuaGpZq3jBmMAfX2pqtZVXTlMJOmjO5UGu1NFUTEko5EjIhEylTUdem/cIIVdOm5LpeCsxrqWVZaq2lqERDxjgGSUOMsVlRVwjUrXk1Rk5Bram16rWiAihYyYEAExemjNhXpjZvXiIJBAwq1Za6ijAYCKDYvxYmQUiccgwKMElkFia1GCVkarqCXAJRjDGGnIbIoZRW16ZaDWbsxgCbMEkwiEmkHGJdtTTSqque16rMfF4sXYiYUgwx5zzIUymBIEG6HKHUBkdHAxEBA4L1lCCtqqYSiEDak5nd4Igi0zBoA1StuoRQ1+X4cHl6aqw85MErWQWDHYqmrq6uTPTx01FCPLzaN2uS8s1tM1IIlmWFk7nP81JWSMA4DrvdOAxxXZayrpBtAyYinJkbg9xQnQg7398fnHA6n9elgtCsullHdiAIIlXMHd0CVBvKUufz5fj8DFYzG3Ie0tjKutZyPB4fPn8W5rKWnNK3b97GblOvGiSQ+WVd4DqOg5vVWpd5cXMaByGBOoiGPAhLLc1CMl+W2UtZ1mVJKYnwzc2BWXbTcRymMZfSdGmtqbo7d9oskalpKRABs5X2/Hw0M2YPwgqhnlbNFAK7exS4IwTESN1B8eZmX+pcS50vpxzzmGuKwzev397dvB53+/2w2x8OKefny8dhHwMLuc+X84f373/+6RGAWROWGHncwQ3jGIYh9fxQApVS1rUMSVozttbdrwxOTL336F3H17yGLyC6v0zSvy45BCCE3tLQtQhtFKGvGpcNtaJtv9u9/3ovem0svW+E7euB+bVkbRyDF6jL+q/YYH/CV+SCL48xcnfo1t31hog3iIvs68rs25tzc3OQdffUq1+6EExABCM36vmJxFvuBwTE5qbNVIIQkdV2PSlo830nJjCzkLD1crtldBBIfUPjuqync5e2z6lnKBKYegYjsaEzHehqlEHkTg5rqsoMZWZihI4nbuCgk/np8bJcSm0e44BJYPr0NFNo402IOYFDY8r78Vd//U2Wzz+sz7UqGEgwbxTJG2DC/c2wmHlrhSDgrg9wIpIAC9087Uq7YFg4f3O/e3U3TLsw7ZLVdnx6fPq4Pn+6XJ7rlHeX48WpbVSxGF2cxF0N7J/efaLoMUjMAazCa2AXpsCAO7HCVb21VsgM0UMUuBECyMgsAJElhOgxZMIYYuKUKLS2ttrILKeUQ9Jay6LL2RTIcby9vTezp6dwOT/Py7msT1Pyw/D2zf1dDpGZ6rq4tsBspZZzWd1cG5Pc3h7yfvfbj5+DpCHmm3HksiQwqQkr10LOQSmAQ07HM3/4+Pxv//ZvP382UEiJjeKQJyOUVqlaHtpuSpBIQddaToqqMywIU8zMnC2HqXmrKhJ2e/7hhz/84pe/iuGw34/zrBTBEWRw9moNQnFEK+qlxSFO426eLxDEYXDYw9O75ggTdhF5iJGEgBi8VRdikLda61J8bTUVGAIjpZRzTiUVVwvOWWAaEoSixnrY7+/v7mKMnz8/1rK6U8qRh0HXej6dWlUIeAT6CiUOwhSEmeFmqjDqVik9o5Osm/fQBgRd03Ouw6StSmykh+v/fl13/E/LmX/9RHyFYb0UNfIrl3NjNm2e2l1s6Oiwrb8g+9vrgPDCSvRt5+bA12T5/jJ9qtghoV7KOvffN2zJAXIzM2J3I1gHsqm3g0x0rS3+guVduWIb9AO8vHF6KRZ9ZmAOd9vuBb4qrV99LgBA4ts+tA/wCD26oYdgbJTR7Xjd8JLIQS8V4E/s7/9f3l6gq38KqfwT4tVXh09f/7CR8r56qf/cbuHP73J3Ve3y/E4tNtVlXpzVGRB3us7Ye/Z26O33ZkigXnv9J4D69evlxO8qQyIHhSBGXZVKbiByZ22dWefOROZN0bq9ChgsBGMKDqe1N4Lqtgnm0C9gRvaSfrWBbddcFVyXT8jJaLPcJEKIgSOM1NC0NbVGghQTnGpraABZEEpjlBibV2JqqtaKujIDTFF4HIcQgogIg6O4RlUtpaiqNgURBbt5w6BKIM5hGEJkDoBrBTeGJ5FWUVf/D79/t9i8HycmvviChBWNd/AKryAV9oGMXdRlZSd364DjlcgOdNIaCYNV6fnp8ZdvvxuT8DO5IxAHCSkmbShrUS2tqjZtS2m1EJBD2uUxp8yE+1dvAkdmAXhpdRiHYRrrUk6nZ1saui+XY11mIj8cbsEWJUQRz8mq17mZuLnPx9O399+oODnKUp+eTqa6XubLAhCGgGmHaTft9tM+7sZpPD+/J1AQqh1fteDatOj5dL7MlyjBzQKzqsQo2ojYnMmJmQkn/VLdhIk5xZimHuUtzqZubqarzfNyfDz54tuwomL/7Q0RqbbaGhOaNqtUuwUE4fnBvnsDaJgXSIMrhIgj82YD6F3WSY4ogWHrMn9z/yZPw7v37+sT5E1YZiXDfDHMKgPLXoIIgi/r4poA0uZugVkiBaxaUeuKH75/d/9mPwxTs2JWp90u57yuxRzTNP3mN/+yFiul1bXU0rS2VlfXOk0pRE8BeRAWX5eLaRmHcRimpi4XK8VuX6VxjPe3N2lI735+p5VF2OHrstZai6qqayulFQgzd4QCCsD0/le7HIaUMhBqs1Zs29CTE2ttF0cdxoHGpIGc6XhZH49PIdq4i9N0ezmdzFYhYgStuqxlWYqZxxCZg6oSUQgBBO/J8KrLstRSb6ZD5CyU5lpr8RSHGKOE2Mf6xv0qy4dX9Mt/tv/8/JM2j6O8+eX+7d23v//t91rtcprXS63FYWAnKIuEEHn/av/dd6+/+cXrNPi7j3/8489/uL1J405+evfHx6fTt9+8Zo6BIxFKKctlhltOgdmzRBYbc9hNN7thGmJ2MtXErkzKzOOQHz48auMp78igVYfd8Pa7X0/7V8+P8//yb/6P3/32x3/3d394+AmowIBhymMKTnA1NC+l/fQw/8Fn+EcIbvbhV7++TyGmXT4cdjGEaXqkj+8ezs+fn6opHaaYgktYT5e1iJuExgtSuP/2Fp8vBm/tfL7g+PzA8+nD+z/eTb/+H/77/+7f/I9/O01Jm7K4BJS1/fzTu7QbjH2Zlxym/WE3L3Pg2Golc1Y3IxeHOcTc6SUQnIU7vOMCFrYA6mF26LMQ4q6J7Jd4cXR3dELXm7hvapSXCLZ/alT49X//0cNeNlt07Qf9OkH5k1e6ah23CNotKdl1m3ZsLRFR2Jw4VXuPR51FTkIkqsgxLWX++P7x+flEt1wN53aRPAjiZZ3n6pm9VgV4zIDm83ldG7sZxXyu83q8hNOshONl8aqOwNxyHnOe5nZW89Zaa8W8SmCJETEZ8fsfnhxSWlAPBpj2YYCWZXGlQOJml7msc4/0Kx1hNoUXcKK2WqtrazWPYxoDE6tra61auVQVAVsrTbV5vW7ymjdSClOAGWAcAnPk1rwaKrlab2DJtjCyDmBxYAIxhzzEvONhTM0Us3m3gjDEGIYpXOa2lgsQUwzn83y0c2BelnK5VGsA8N13k1PXRSgRQjR1v6xPx+fL48Pp4RHLiuhgYC341Tf30zAyodbl/u2rUFY102I62wa6GqNxKw0EFFdvkQMHuJq7UkhM0GadkZ0DpnHYDbvj0/rp46fT6bIsDg2PD7MvTCsuVlAYlVCden6sw+AtOMx+XD7mh0/jfjotp9PpFFK4f71/+nxWh7upNndIkDzmw2GC2cPnj8u8xAFe0B1kmZlYVBtFTjmlXTjcHZ6en4/LiQe2YqXWXRrDfWh2Xmeg8zlEUowGW0pphnUu62WNo0zTNA2jqT49PT0/P374OKfwlFMKItOrPZEIQillnRc3e3x6+vDwbre7+c1vfjNN0w9//P7x8Smw/PTHP7ZaVX3Iw3fffvf69esY42q8LvXx8fHz50/u9vbt/d3d62+//e6Xv4rHpxNRuL29VcdlXU7Lsi51XUurZuat1W3XztQNpWotIhQDC7MTqXlKEmMcUnQDzELQaeT9xCFUYn/79k1rbo3U6vF4ulwqIfz844ff/u7vPz9+Oj0BJ+AN7t7gzaubm9vbw24/xPTP/+rt+/cfUog5Z7kNKUU4x5BVvTUfd9N8mde25JyYuFqrpUVOnWAUclhLgYOYyLYN85X8/fWOuheeq9qGrjCFCBx2jQlk8W7Q+ZJgRURMDPmSadUhpd4/XXla13vdt7Aj937CdD/Bl76jt1tfm9xc9YOdbqC9c9M+Q3hR3vQwQ0G3xTNqXYX9hfNk/iX+Dy4gB9smuCCnHrrJzqhawL5FK4ozUeNWuaYYWKR2d9b+qwkUEwsDvEkExd36oZID1hPogU646u5awjDvaU5fNeTUDXHgBGYIByEmh6mqaTP1CiOFb2ZVRGTmZsZwq/b97z9t3yWfEAKSQWzacZzt7v4VR121wCADv/2rO4r0+aen8wP6JYSjONS0h4ewkDNAkTf8cQMWwEEoOEiVEZMM0ySD/+Jf3ecbOkxxTLSu849/+PTp58v5E5ZzbM/FM7XzigRwpJDhIqG7WDekdvxU0h58U8Wd0cQbw3IMIlEkwKmUtZQV3pggjMAtMIQF5onFm9XL0sqyzEdPyDLJYZxScrb1cqlWpGs5RVKM0zArxWGcxjyeL5chJ235fDpeLpjvjvM5nZjWEHRdCB6Y1/lSLrMw76bdzeGwm3ZJghENMQnL7d0b3Bye98PtmMs6ExCqRm9DnFLMcTycHutPP374h7+3cUCKQ2tUlWq1ouulzGkpuwNTzjnFYR+kEfE65fjw8PTw6dkqooQhDUFEIg0p7vf549PH2/vlzevXN3evHp/rMFz20wEKW1XXGmK6vb05PS7LXEKipcyrzW9+eX+42/327387LwgDXu3pdtzf5MMh7smwn+L5VN3k40/H0/GoYAhKbSAIBXV1dwnh89MnCnj97d1rg1CoS1uXNcVYa71cLh8+fJjXdT/up2kXJFRHiIHchcTNdW3ecxBEaJvyujVnI1ZvCu+AUU/zNMCwGY0S/C/NAv3P91T/qE58XcpemE8vd/1jZP5a77bqZPjyDAcZbzjtlq3Y4SMG7AUivy5qkH89nCRiEHdX6S10YmNl9dVmKl8xo7ruT4jU2hXW7vMkfimb1+rHzK6b3VW/2G7AVBAhfokNtZdCu5UJ2qhWpvrlMLsaHKitXrk/ANPLp9Qt5q+H6Zvg/AW3ImIhVfvyrfx/vf0/0q9eHvby8wtU9/WO+s/Fg/9ZIVmB8LVGtJ9n3lnM/Qzp0K01M984F2CQgBhJIsD96uVAMzO/mrOTMaGHZ/dkTmffLsidSGebxpZAEGrSsUtrTbkQETurukkABaYtaYu0qqlhbpvtpXnHKbaoKXJCNzQBricxgeHGTgYGbEypemtoxs6RwiQUyDuKZmAJQSTG2A0DURWAw0gQIwdKzWptrbRqbiEyRYQQ0zDEEObLXCuFEEJIrc3LujS1tfbpLnbfhdoA9SyWcoDRsizzY3l+mC9njHJxCzDiMQw3Q21tHIebN4e8z8+Pj43UK1CAxt60J0poUyf0oKwu0RECCW+CHXYiA6M9hx1ux3GUkqKEpkqZiOT5+Xk5lzLX1gzO1AwN7qQRdXDOJiJHmodd3h9uTCgu83gYdrtdK3V3SMsyl6VoZTchjG4lhFjLalZCVBHOHJayPF/OdfVztb/6DofhtpX28fPnp4/nNm/OmiLSCs7F67x6ifsh3kyvj8OZjKwpYV1W92YigTkkjjc7mS8nd1sXnefWqlujdW5oTGDTzfa0I98IKjlwAke4qKot57W2pk0joq7uDXAgECWiwcGqrqrd4hSkTs1FWHhQXUWlXUDKGVzUoGDpptbupmxC7sTOgpAsCMUs999MKeUP75WiiMr58QQKoIio5liXmgcac9baTBucEwcekhtZU1WVFBj28PEpp5THAxCNLOdxnDIRtdb20/Dp4wdtXEsta221tVpAloJgUa42DKwkeYgcO0wDyUqKqN68ffPNawly8+q2NX98fFpXWJHL+XSZ+24WEslBZgZ2STFQ6FEAYDotF5tgDlCt0MaNmVmkWQW5R2ta17KmdIg5zW1Z1rkVXM5zuZRISShWb+pe1eZlPV3W5hoi5yEzc6uk1jgAQHACYk5ZRBIrtcieI41jSrcTka0KWauu68VgqnB3Zspxv8vDx+MnAQXxmH2c7F//V7+4nOenx6fHx9N8qWoIToFilJCG8OrV7v7N+OouPB0/l/Y87TBNoqoi/M3b+9/97tNulJvb27vb2/1+zGlalssyH7WWJfBulN0uT2M+7HYMaW2JIiQBPcKUQ63FNPAkLIJAMQ0p3bQ1/vzT+//5f/rfHx/L4xNCDsgOIm+8Nmvu2qybRMIZjCBIgcusf/fv3796ddzdDt989+bm1Z4ov7n7Jufx+enB1VohGND89TffndeLw1Iaco5D4H1Ou1dDmbmtRzOoe0MJO//l4TUC1nau1Zq5A2KkFzYC7yTLOMYhDLHBuA/aQzN2M+crcg7aZhvqsGvqE200RQZTb2oAEiFvXbjl4N6OXA1I0fdj7P1fuLO7/8KF+HrXda3/o/3Uxi5wtysxfXts3yBd9xJ+hbR6wAh3CaG74cri7mJDIhCZE4hZ1dVB7EzKqAwgSFlXSWIYqscPny/f3e1OZ71cMO2SSAoJejkapDqK4vbmG6IyHNe2mBXENJ4ux9OlSdD4PNdaCRayMHg67FXMgpmYsjXTooA7J8TAFDIxOsZm1kpFLUVYhdWaE2BI3uj8tNoKGMgppyhBnK2i7vbTupZS2nq09XIOWVgoZolTEomQubSqVhmBjQK5cpeLerM2TLksRc1MlBLHMUpjabzOq7mmOBh5qY0Mbh3iIwAxUt6lpRZlbdrmtcJbBy53N9tUxaAkg4OILQQwKCYZ0BMnQEFJIK4sEPYUQwg5zHguMyllErgJhzYb5nZ8ntdLdTcJuMn7N692a13Xy3pp6s0T5YBJC63UatFmi64wBiFQ00CSODmpU22GQDaNU86DIAmm42P99Olcm9zcDofDLbVSTlqPamAJIiFGCTCr61rbanAfCK5i4f7mlbFezpdXw+s3r785Pv9eVZl8CKDoQ7LDPtzsc6vlGOAGZtStQa8MUwGgOdKwj3EMtSzHp0cSj0HW1Votw+1NEF7XNJfi3TGLwEJBonubi+narJXgeTfkIcZlvlgtVtfMFFlSCCnlKY/3r+6HIR+fj61V07as6+m45tAHM1gv63qZK/E6L2upZrg5uKrGGPf7m3cfH6yVMq/n52NtuH91K8RDyjkPWu3jx09mnvOwPwzG7fjsPU7K3Q0g2eYjlDBkJy7qYApMJgEESLCcLUdiIjgRU04chzDENM+X/e4gKTpLSoe64MPDp/Npefx8/PnHTznFcTDPZubPH5BtnbINd0OIlHL6/PED3Mg0BfIc4epkTRUMtXKeTynnwNHBZlhr2xLUGU7kQhunoPMHrKNLX4tlehkh5y+dQHf03STU13R2VlzpBJ3Y0BO+NpJW759erPdIG9nG2enk0C4KoCtjirs+L5C5k3U09Vo0ibZuBdeO0cmNyd0MpOT2Yp0B6HVH332yrEtg/IXo2rG0jfLK7ERdXS7dKPnFyZnNCcbmApCLs3f3LOo7wR7mtKXLE8Cba31vhhsczk5G7t66/IY6nZoIICEn3qYgMDABBoELusYCcN4YXd1Zx8wMZiC3phzEW3cvEzcYo0HIIcaoyClJiiBUV4KnKCnGuranz8Ux51EBq+UyxfT617cxh5/54fLBrDZop1KgOdjdOyuNqNv7GNTJICjcAECAhHhIt/c30236xa9fP50/uoEsXT6vn79/fniH8gkhS+Ykzg2BQKqJKKCyWbVSjSvEwohoJBaS53Vxu6AVX9cWAyEJGbeCViQIx4RInsHRozTWVqYhRiZCM1u0+7j7BZhYJmbS1s/VVurF3MeR93WoysFrW0+np0/CllGNQYyoFJrLXGubL+ezBBmGXKsaWCQOh5vbt9+M49haK7WRcAoyxRSgCZS8cauwJq1EiSNzijnHEUs5frqgoglCEA5iq87nhbkQ1XYGikWf21ScPaacxumwG72Udp4fL1BpYitCjEGigMnFEDSMEndDFGgawribXGn1sizHw37XSuUZiIDE5fGIEW9/9WZ3l7//+R+KIUVIdBXlSaZX+1GG4TANT+d5bu8+PlYHZ6LMjoqIOJGGeXUgtct8nMbdMGb2QBW6GCpaa6f5+Xya56eVGDIQixuXRkVGzuNeq1uxUpyawwH1EAiAKm3QNAVg80veCH2bk9QLw8+MjK8AFG1wE11L1VYg+Asq/qIp9m5sRfgyVuwIS+v2AAAgAElEQVQQwQv8slGmejHYqtPG8JLNzuGF27RF+fXtGW+wSTcTNLUtyMcYAIQ7PYY6WL6Z6F3hqq68huMqG+RurdWxJPPQcXTDSywizNqGQ2wV8TpbJfYXwXWvQUJ+NQUz917etxr+gpJjc1ju+BUTgUhbA7btGQzcDcrMyLZndkQOLA5XtSvUxRCBl63y/0eRov/fgaS/OBXGn/Gw/iIu9h+hcf2nONSXW2D/E4DtS2DK9ka20xdEsO7yINe+obE7VLX1nCkzd3PeEl27cI+6K6ST+2aXCAYRjMXgCnM2MJn7qhvjCQ0cOYYQYkBwZQvMEiJD6lLXeY0piEhbtbXWkw5NnQIFbETlDczcjEu2CyybA62ta/Wq1DzCAzUzNxibkxOLEDMFOBNTyiDCWksjJbI8BGJeFm3NXd0KmrswiIPkGEN69/7dkIfBiIW12Rim8TDU1uZlabIYhUptXnQQPRyG2+HWMx7O53fLrAWntYYAOEVBWRGTLG3d3+4xsq8iou3cwezmsNQV7bq5xdDmJ+NuROoQJ1LrtDZTe4q57nfDrng7jOPj40PK+2Wpn57Wcl7EBm5MJFaKtkIuvmK+rCu3Bvvn/+KmLFq8zPPceL073Ly629fz8rEspPzT379PuxRzaJU5xDFPpsV92R0ILRzfzbpoObXLGQA+/PD57etvlnN9+PEZRtQ4soSQ3ElNbfbz3GytNzuT76LVFoVeHabdsLtcrBQwcV3bfr/b73d/9x9+/+qQmjUAqorKpCxIwtnVKq/d7IEEIXCIgGhpM7kQ8fPxmClFjlqglcmSo8INIA5UrZhW905iA8zRjCkQpCy4OQy6CAH3h7un8ny51AAOHL1BXVOIVRdmhOCOswt2+2l6xVFoGvlZtF7mQFGVnISEUowxMpmVuQTmtRS3FhOnvhbW2mwdJHJmVCrV1gZIIncF1lqbNbM6X04//3AmBOuzV5ijuftCyrOFxHfx0FblGNwUWihcvCizcFRRr1qM0ul0Pp/K8Xl5PNd9zCLh9jaY2dPzQkxXowbv0KyrtNoQubQFPjdVMBkbJWoEMEy1ljrsMrmAuEkNIuf5CFImWPFyXg+7XdyHNe9q07VHSDKE0zRNeYhOFrLAMwBTEwoxxCEOKcUISUYD7ce43w9xP9npXNZaT5c5UFzbelzOp8vJMLVlfPhwzmGaxpAjC9ky//ybv/6r06nFKfLI5zPMkEgiQNAQ6dW9D7vlsp4Vy/4gebhJQxZBa225aFnQis7LcVnw6tV+2g15nLozWClrFNZWbqbdYdy7O5q6NmttCzQyIwf1bz6HOOU07E7P9Yffv/vtv/v+P/zbcvPNPvjMICdSrWpKEOIkktSWa3oRzLwtbuQgfH6Yn87z+bLcv7m9u3+VstwM08hBtZhXInOScbo9r2W5HCXG4DI/PA40hRzj9Hq9xMzr3f09DeLZKk54jWMrSRAC64q2eEwCorhLN3eHFlpzjYFrbdUqgjGJm1I17v2cgMVdublSEG/aL+fdvo+ZVNzdiFmIjbzzsfs6dUIPkmdy9y/BWdvc7S/daNPLvBATrmAZroSHjTmwtRDEV8946il0eOnd+vWBuEekXnWDnfz11VPQs3D74QiYTVAIRhjW1jQmBxTxb/6vv/uX/81/uyyYL0SMKhZSbjguysH5srZX9/fux+Wwos0PBc3k81M5nZbDLh9P52nKQSzFnVubXk3H9dFICxdla2TNALhsCkbvrvNupqqlujkHokASskQJz0/nssJ1YzRIkpijSHAzZoFzkIjEXuHmddGGRsqS05BTdFlp7fsOgytRQ1Nzc2yzygxyV24IFIeQMWRNRHxZzuNhrFqcHY6myuyQRkScggyhlLas14gNAwJx8pByGsZqOD89B0gTm+clJR/HNE4pDztVNashcM/qgXlZlrpkSrlc2nxcrcrNNF7Q5ufmDRL4+LwMQxqnBOKHh+c3nMgbexFUBoJIJClF2AO1hqraDE4hZ21wtuCBAoQjiY9j/vbbtznm54e5rDg96XyCkYJFKKmuTY1jDJBW1LQ5i7k1a4pOS2VzTSHe3908X47zuuY4jNP+zdvLTw8/wyox58H2k7x+Nez3Q1lFy00k+ennTxTQfTFUmiTKMQyBdrdJVd99/NkM+/2QUtylvNvnm1e7nAOxcnhYi0aQVgVrHmMMI9MSIuUYXt3s7/c7JqytJjZxP0wUelioQavudvuU0of3n9+9f59zLLqSY5cndn/89FlLCSTanCApsLbmZufz+Xw+7/cHqHotmeXu8Op8uezyNOaRieq6Wivz5bmWSre3HKW1pbXZfRYhwF0tj6EvypBomBhuc6nNmgCSEIAgOo6+34G24CqKQVKOMYYhZ2veSk2SIg3H0+n9z48f3n9+fD6WFSANIZixlqbmx0e9v9PdOIZI2spu3LHD1UQ4RQcpwE2NQMfz03lZpmlvjVppDjfzCg0sHMQVHEIPNiJjsJMZQCzcA9Ov/saAXHmgW/kC4FsGIVNHpjqLtaM/AGjzjt2wHcGm6XE1Q+seUnTtPrvBIJF1+cK2x+6OG1uu1wu1ANJz8DYNHnMfO28MHvfqQNe8hE1jr2aAsrGT2zUg62XocO0igatzMkC66W+66XuvsU5upj2/JQyhC4/d0KyBRYR7f8kECZyiEHGnpwHcVBlsbrW5VkAdYCfvPaczgWGmXSm0hS8FkygcWL0RgXpryd4ddLyTtQhQhBxaNTPzQAp4AFgQ2RCxojVigCPIjRpcA2oOIRwfn2p9/OZX98PEpbXn+vj2/te/fv2r6eb2p99+OD+V5WEFSfSARtasqoF1o4rB4NZBqzRGSRyGMExxuhl3hymNpNyYGRqPn/THvzs+/hGD52EI87xKCG0tzGINwuTmXqpxAVcJzkRDDKykM1Xm07GdP4HJQ3JYCcGFg5qzsIpbJB+cKxcErFQbpjsWsiBOmQNjP8XbQ0yDSqgChAjmqKprOxrxuAvMUy1EYqjPtr7b7w6cPdR4s9dX+fY+HWSt8+PT09Pnt9/+ohW7uX3dXM/L8vPD5fHykSg0NSOioaWYh3yYYtiFgcplH2IrZ2EiClPOIikixSbL53nIqApzkmHIXrGUIQwEMlvi6qHmUARRs3OMUazejGnJczgIIyzLej7Xwz7LbrBaRopBJVF4tR/2O358MkBbo7Xpea2/+uXu04d3jQsyIwgFuvtnd3d/dUNj/fzHT/d3cvfNPufUmrbQnttpbs2azdpWNIyMWzg0RoBxc7+//+6Goj4un4zcUyu0tqZSRWool1rOFcyu7fRwQQMnEmeHVl/O7ZzjLqW0nqobu8JWhUJSCCSubmrXlWZwd4P6FhaKzZiPu2BI0UBwAtNmsPCyfr23ky+bro0i7/SCTvXi1W2kcDW7oq2574LkLqa6PnwTxlJXWcG7gdVLJeyEz82encg6uGNw27gp/Y+LXruQXlyZAHRdDKCmV4gN7ugQOoDuiCUsV4iOHFdErosO4UI9qqGzVsm9J0tsLlVqRiDp+aGg61hzEwHaF2Z0983YgqGIiISLrrgKnIlJegCrd8Bkk0H3LCniqzs4wYV8G1ugdw0vZN5/TOrt388XC8MXfu6fPOAvbp7/qX/q7+jPeVh/EZz6iy/45wQuZvYt6e8/CYYV/uxjuR7lV0dCRJ3V1E9pGLzBDWtbEYiCQMjJYQryzVOdCURurt7cr0EshA4LuCGSmrtB9cX6kl6odPTScqh59ebGRCqdQMi+u99bUbOlb82LNgCSuUf28LYCN0tLdvduNmwG5/PlbKIIQIAq6lrQQEJExMIOOCsBWmuQsLvZyRqblTzmw6ub8+XU2WYkhOjEgEhBeXx8en13P427tup5mVMMWlQih13IUxxSRDx8Pj44QBXe0C7OkUNIIaytIAl4HFozDkHdnj4950N8e3htrs3q21+9+f5vf9y454FSStzYXLc+5jr9uio4wU0p9YW9eRC35vNcPn749PAA1TblvMzF3KwhJOIg7axuxiSmpqYwwAlmy7x4s4JlrRcL2qyUdSnzcnp+fnicsSDpGlOyVuMAcokSWDBEDuPwN//rT+MgwjFnXS/27tPnZVErPp8LRaEgJBEs2lpT7xT5tSzPz8cPH95/+PB+2o/7w2GaBqb1qay1tLNdJMgNTTdjCiwUQVpd4SKNDQ3ebENIBf83c2/aI0manInZ8R7uHmdmXX3P9MwOZ3dIgqulBOiLIO1f1n8QP4ha7BIiBfGe6e6q7qrKIy4/3sPM9ME9sqp7houFIGkVKKCzM7O8PCIz7DV77DnIAXlABtE6qyS9D857Ty5EH32boIJW711FU8mmWhUq6BIliQCzZz2zJ6611GKllFKzqqJH8gQAYkKsCKRF2NhAiJ2LKIrkbbtfcbDH+4dZgmMAwMsLa6KIyI61yjhNJspIhFxTLUMlIjPw6KBCNmWm/jzFTWy3DarlUs1QRVJKQ5+/u0uRgAmYwQfn2SHoTMyVqsMwOAdNcFKL2UDOic56japiyA0RvX17d3d3qLV0nnJOzgfnqNZZEAZ47bxFKy8ZsFBV19u1WK2mMCsPcEERpIpUEBDnHDEpWa6TVUOQVUebdRu8jzF67zrsximX45GYd9st+xhCzJJPpyMQ7XabtlmZWR6l5lqSlTGTkDc3XUYXhNkpzagJxBi/+vkXqab7x/vLOYzT5fHwQ9Py7X4N4EUUSB1LldEgxUC7/Wq1XiE5D46VpjHlPFXJubp5RPG+2e2fdevVNI1vf3h7/3D2HhSwip4uvYBm0Ta61Wrfxqaky3g65QzrZti0UxsiA1rRaRjRpAmxpHKzv0UO3rfogpqOYzo+fP+//MV/+ud/+h5aYk/kOZeCiC44ZofgFJwaSl000ktZnMP0yAxUqh0PY8rl4fGw26/3t5v9zb7WfDw/jCkh1Uvfe+9abKsmsgqmeTpfxuHZfrvbrcto2/2z89B7Or7a3zz7AtIdXE7gQCkGRjSxKU0rXq1W6+8fvjOHxbKLvqU49GNVIQ9GCDwv4UHnHR2jqQAqEBpdTYDR2JHqnDuDNrNyDNCAxESvVZ+wlvp0hv54Qfajs/P3j8MPqyH8kRXNx07wSydGV9eZJ1HhR7vHhfhN1+YJYcbCFsWHIwAiFADQebrTSiEQE3j/9v7h4DI517ZdFRv60XsXu4YcG9plSABTdG3btbv9CkGB0zAN4zQMozFObUcrDD44EMi5THnqx8HMihQkiqGxDQKTix6RRY1pbvWkioqCghCFbt2smhUhn/sCOXPjzJEpIkCuylqJCB2fhwshETM1bKqQDCqWWsdpRG/OL3XPZDYAUBfIIYlKriaaVpuVC36cxmGcahWO1IQwE7SzZPAYfDAzy4o4Q9++a9v1ev3+NIGBVoE5JZaQEJoYm9j0/QXN3t7fOyBDc2vY3NyuVisR7ftzP57ZWgZQcGAVJEr2UxFU/+WnXx0OF61uHd37dDjm3gTNVIuComcfmYb+5BwxUds60zqeU6lohXNh0aXtMFVmYkepTDlnx+Aj+JZMrFs3sQ2Hh+ObN+/uH85ZoO2QGRvn9/utRXAaJcnpOJweH/J4AgBg8utQPQAWCOBbJ1hLLeTc6XLa7Hf/6o9+2f/NgQlUi4gYcK0pZ1dFnXfrXfu87schjWNWNSK36jabdQjepilNl+T8/Karhq5Zeeddynm97T758lWziefDIALTlLSqd861wQeSOq7a+NknL1er9nC8I9TofQy+5PF8vhCO69Vm1a4u54v3brj0eRrRBNUcQ87T6Xgcx8lUCbGaAFgIDoJT1b4fUkrsnKkyu2fPb199+rK/9Nubfde2TNwPQ855tVpln8dxGE7jlDKhdU3nyFKqWUsT26aJxKCaDGpVdY6iI0NlBgR1nrxHZlAppSY0dNggeABgdNFF13Sm7vB4/N033797ezj3Yyl1Zh2YATOB85s29sP5zQ9vP3n18vknax/Cy08+TWPOOYtVkcIO2JEPeB6GKY8KACgKcBnOmmABZubYIERgVDA1pKV9JdC5YZ5lBDDb0n/AyhGeCpvZ8h+4LrcJiMGp6pzrPk8lczUkQpjJ3qJQzXmer/gvOP1e+2mcGV1LEuuMYOE8lCEuqe1LPogtE+8V/4fFX3genWaigyzywaXxfOJi0NMEJTNPQZHAZuIB4mxSS6J5FpIbzDnmBkxgMmc7OiR0RGg8z6joVMWqmKGh2uzTIABiCygvV3fDhdSBT93wUlgYick5VilABIt/CRCQLumDZga4bFKAkQVqFQNTCOiRHHtQECvTVGbHRgamqjlXLVIFpin3575b75o2qlFs43a77poNEX//7d2UUxfbxrdWMQ3jcB4QgVsSEybyMXBk9OAb5oDdutnebELjpym9Pzy6zfPOd8Pj9Pof3t69PpcLGGgbgBSHY9/uVyhQy0SBTKpKBa7YgA8uNNSEmCX35zGN+Xzpp/NytkE2gAxYgBh8WLeBAhIVFzUNuF43xE43jUAhMCJoIu22zc1utV3HGCOCiUiakuRCBMyI7D0HFZ6Bg9vtbtVGrRVSJudud5tnN/vh8eCDZ8Zf/frXxcyY396/v1zG1+/ejGPJBUqFUuGXv/7cc4xfr7YvXyDrattB20ru2yaM/RjbPWMrFoNrwcgEmtZVq2WaYmyZyKGSVTPyXprgmyYIFK0iWOdl2W63XbekxQ2uSakwwjTllMqm45J7Jn32fPX1L1/+9s1hnM5WaRzTDIbWqlUA0LJe9l9vvvqjT7HJ949vT0n/9Ne3+93eeT9NNY3l7v5+POZ0qlKhaTpmd7PzwTccmIK9+uzF9vn6eLp/PD32U97su1qKDElH4OzypU5DnlMf57ehZJvGCVeBGkLCXLJ3gZgUwXL9QDSfFbZqBiCqMqfPPHGiGGayEsJCS4In1d3ybplj6J9gADSbUzMJgBa8CeZCcv2WuZ+7Vqaf9GLXteDTetCuWTz2cbO1ELUM4ENw6NUO6God9fRnTltYZFVqivNztKd/266FCwHmXA80nZF0r3Qtex/wJ/j4pn9E0bdrn2eIKKooOIP5NveERibzkmHWJQMzL7D7kqFxhX+IAXXx29IFySIEMSBEmV0DAebwDWYGRAEzFS3laX/7L1b3/08e/7chp4/pWn8QWft/8OH+4IVnI5B5EPh4HCBaSIRLy8cAC8JqiIjsjZZ0NzU1sVkIDzyLwGfpqBlAFZtzrIgYmMCbeANv4Az46rOuRUWLqIEqFFD0DGKmBuiA0UWM7FFqnZFK5Kff9dmdeclpVwVRkaoCoqohBp1ZVg7AKxIbSjUBtHm2Ny1ZQEXbtm1D1zhUcaFtfOvruaaai1ZAIwdAoCAys89Ncy55FKymVIeTAJaG47ObZ8A25MnXZtV1vCJUCxJrj2ZiRaIHMJjSBBlAMu8QCMijC2ymotKGFhigAQCAogSADsljUKekCorzC0zIDqtKqQZi7NAHl7nGfZw0j5fx/eEhy6QZdtsmxDasIueca3YMlQpAJXIUrt4zomDw7vvvm5umu2l2q7VRnYb+bpzSuZZU121jDRK6POZUyygw9BMgMLEp1awgIIZMHhjBZaYI5IAVIhmQqSQFyAlIwCE4h4gV7DIe3z8YsYFZLaVWPR4u9/cjKVGkKhmg3u5uFKTWQsa1aK2GYFJLrQpVwQMwokf0M/tvDhfjWqoUTb3oJNllyQZGgOYDG3gDU6jeM3ogxmUfgYae2JMIAEGV2k+XOhVRsyDgIUM1NPIsWCgEVQMHojIV2+zC7navBd7dvS1WAaCIAIr3XRWzlNKoqo4JCSFlIA8AqEVKVjIkR75xWq0UxYClKKPvuk1VJzoRiYFlgfMpQYXC82ZiLhPCDCG0gGKSUSqYoRoTGURCV4ucz8MwFFN4+UmL4HIex6EQM5NTMQRXSk45g4CLgMQKqgoqRcUxI8ZAhOv1ZhguU5pUhYgAUU3AyJbFLaqq9w5Qcp5MoYu03Wx2u23XtpfjsenaXOvhcBqm0bkYQoPgzof+cD5NU15tmtrg6mZvCtP5YTjX6TJNQ8pjnY5ChnOgNzlw0XXr+MlXr563MQTe7RridHrzAAQhiOppGi14WLWN9/50eshZpKJnF2PD7FGwThICIDGQn6ZyPl+QyMfYggNzIjwlu/QKAG0bYhOJWZWmUcAobGJsAhGnYZIppyxjP0Wg6L1DxqpmBh7M6PbZXo37sYpAKXkc7n94nR6PD1PK6Oz4cOHGOeeBgBwikipUEZXZTmQeIHBJG1cTrcDL2mlKVU1zfZhqUQWjeumnlM+KsK+lW8cGWSH4xo9jf3fu370Xzfn2tvGM45RkPEBqX926P/vNH//D33x3GY4Oowk65wUka7ZiJeeHx1Oz8a5x7JgcRdFpmqSaEbADMNBiUA1MwXmYKhgY1IV2roDVkSM1Y52tGxicu7YqMgc/02KOOU84CleXTcAlZvjjJc9PTscf7YU+OtKu1lrXrooAEeZfV4MlUOYpVmbBzXDJxrp+7sPVFlyNyECWRQ4aoCBGZAqtT5bPD+CcY0dmMA6lNsU3wfko1UQ15XQZBy1mCE0bbz2KTCJ5TAAGPgyOK8AqOJYqU5r6fiBiVWTnfWPgAJnIOQVCwdh6LI5SJVLmedPHoijIApirGrrQtKCk1SRrLgWKEgI7NE+1VKgVgJHJggCBskFQjqCkpaaxZhOwCuCgCSHEqCZUEju33rQuBgMdxiRJRh0hwzRNY05FKxPFppnNAcws+MCO0VHV2XYOEMHIkJlIq5hKvVxOx+Nx1bRmdSraOejizbq53a9v2XHZFhF5fLyLMRhU0+IieQhNbPevnoFR6x+Oh6FkAz0UK4gIAqqiUkoBqHV3s3Os3hOCxTChjWM/TRcqeY50UAArgsEKuIqWdfZWUMsj+CaJ5ctwfDjeH47vFaFpIbaUxr5Zx5999ZkVvjz2x4dzLLSGTqrUUooW5WyGVgQcFKwP58P7+/fdaptKBsJnz2+++PzLKn2ahpLOsWnU9Nyfx2GapqyKt8+345hLFgBEdG3TNg1LHXMZAXPbOnKe2YcQXfAGMuU8pdy5plt3JVdTI7Y0JtNM5EME8H6zXW0269hwqW3wcLm4cRofD2NKuQnObX0M8fx43O/3m271/OalgqQhNdGvNgEQVC2EaAY5V5EUY3TO9X3f95dpmpi4lLrf7YBQVRBxvV6HGJl5hqfX63Wt9XQ5n/pLLRUWOydFMDXYrNdtF5mxVJ9rL8PgEJo2lJoJgRicQ0aQWszEwZIXCSoOZ+OqZrPZ52Svv73/4YfvL4NE3zoXRaVIKaUSgiF16+5wPB9ORhq61coAnt2Gw+GAREim4ofpLLWGEFoJqhqj29/cgDEqni9jGYsWUSQAtCLM82lnCEtUpM4z1BO2NJMQ6GpiPi+HEQCg1mVSsytHYPbke5JsfATDm5mp6pWR9OPH1WwYfm/cWZxdZhBKZ8tUY2Igs6u4T81ADNTQiAxl7ukXpgLYjJzNqbJmztHTNPg0ltiCc32Yu2YXYwBUnJUwemV4ABAYKQDNUyCokCGIKRkYoc3/PmmttdY5jQKZQHQWqFsBKAaVUBGUZoddXHbkH16BpxW8gpH3y1CJ83QyO3aZ0TKMz3+AAJEcC3mm4Jx3nhGiBwPgMv8Yq4nm0WqOXdysNknO59MltrS9iaFpVOXu8Y4t+savd930Iq/CKrpoFUKL3BiiuZaKFGJcbzrfOmBVrKIVQhLkZJRsLHpc+5+XQe5/ON59fy4DeAd1KKWEpu2S9DGGaZic8wZVawEPPlLTRRcJSKVoqbWIElOeBAE8RRSXVeZsI1D27CWzqRXQkoCRGEOI7ofvh83Gda0TzVKLZ7deMVAzjJWgmiACs/MApAoqhmiemZABZffqE5MpjSOt20ihCYxg7aZTgrhbf/Ly83eX+3/67Xfv7+8O53NK4lyMwYtorvKPf/8aDOrosODtutt3HQDuNzvHGGM5n/KnL74o1saYGBdIQk2LFiqMqhUqoxCZAuSaWBAIRCoiiwiBu715EXmTE/SXJGKenfdoMKb8nW9tqsc2xN1N/OIzuFxSOoecFQxySlmEGKAzDvVnv35588IP5TLW+xe3MKeslqkOp2EaS+qljHo+pnHSNlZQWHXr1XoTm9Csm65r+348nYdarQrs1zf9aRxksCySlYAdxnFIAKhiFEAVppRcgdAEU5OpChcUJ1WvdYIACZgYySOUkpe34WwzJTAD1AQzkZNmMHkZ5P8AnWdRXMFHb+2FsHJdDD41YFfC+/WN/1GDdE1ytitH/nodfEKmcAaNfmqt9COG10Iyn2+ZidUUn6qNGlzJnjCbul+x+oUQOpsdzJxQ8j9y/Vue5NWy76MvPDFoEK/oG89KnMVujwh0Aa/wqUQvt/3hWma2LDRmRgwBwVKDl1UAXjXYT3+BEJFwxuev5P//mo+P8aafdNdPbK+fPH7CzPr9K/xnMKx/idX1n7mrp8cfMHEHgKtv16zCADMjXo5JR2iIhKYIoWmqioCAIZP3gdEtw3+VMou8gIGYmIkYiXDW5rKTakXQjBEDQkCODMEwkrKyB+cdOWLHQbFUNVVAqmZVatGaT8dV2zWbxq99TsnMiFHRYFa9KpoqiMw3rwoggAJYERWzFVADAfbs2fkmsiclU1MRKaXUWuYQh7GOvvgQYwjOWC99fx7OQxq0APLsBYaK+vLm+bNXz84Pp/4hb9dtTYUKfvH85je//s0Xn39epvz69euH4WG8lBVtujayo0B+47tVt/rVZ//6l1+d3rx5+/b9XbdaGeLb+7cTnF1wl8uFGI3w8fHx619+LllP9/3p3WWs49pv2IfCYGKQBQqSAQHWJEbAjjAYBsTASPXm1e1xPOVxsqCdbx/ux1Oets5tbrfGfLg/OU8+tOk0aRF2jtHZzNCptWK9XC6TXrotdtumDbFxTYtQp3Lpp9IDeFhENQkOD6XrGzwAACAASURBVMfttmnWK8Q6jrm99QTNPIMDohEomjE0605ES84xBGs1pwHYfAAiKhX6lMv7u9/85ss8TWnKx8fz8TFZAfMoRc6POdf81c8/zWnIKUmddUg4N2SCCg7jpgWo84HsAqNHNqvjJGKIAtUEikmpE4ABBfTBO+eATACadaOoorP3vjGDYSmjmCg5wEDqtFJ1DW+alts0XHIp4sGwJQ7aucZHqLWqh5efvvzsZ59djuP6ftuuiXFKg0oyEXNG6hswnSNWmT1CkjzH/3Agp7mCEjivUKCCrehm/2x/8wK0ghH5CDCnrMNUgcK1zDIYgoAyknMEKtVAxUBASu7WDbqmadqci55TykUUnj/7lCCs2+e328/TVE0JjIbLeLxcck7rtSDh6XEwBZqX0p689z76tls/vr+fhpxTBgQO5oJnZEeu3bQGqqJTmkwstI4okOYuulUbgiNEKKX4Gu7eP7z+4XG9adc735/L5Xg+HM8+wNdf/3J3sxexf/6779+8eX34ASADIEAFGKDZBBEsUkArIEDMDw/Dd988wh6e38Kv/ujrX/7iy69/8eq7775J5aFred2223XHiEM/lDzkJLUgcXTKo2RJtWYFI2aO3quqGNRShd2YTLEcj8PDYXp8hCZCTkkx1QpGsN2Ergnnx3h7u9lvt59/uT0dHh1amUADNG3k1Z5Uc87e83AZNtv9DK537TqE5nyG9+/e/x+/PcEZ9jdd31cQRAYgLLWqVRBckBW36C/AbEazDGiWkZmKFcgJMiu1cJyO7++P3dptt123viEnD4fHarFbuc223W67kyvjZXz1ytWUTqf86sWL16/fvdh9sl+Dj+FP/+zP3n8/hLenxm9qksvhMawaMuoPF3XlZrv1m2Ckh+NBTbtu1bl2uiRHxOJKqoWqOWDwgePk0arOCYSmhgbmoNYCpkKk6BY6AiEaAs8OTaZgiNQ0fjaie/ItBgNFfSI2X0+mKxXdPrjhLjv4p1YJnrhr8zH5B7ZZH5+cT/3WT7/nemVY4m5moQoQA5g3C6AuS9FcLBicAVBj49fr9tSPTdvFGNk34zDVosCuqhGjD56ZotG/+tXPug2eT8fgqG1D2wTvuJaiKgDUj0nEVLXWlMtQa7UZ/mOnxqv1mifINaUsBurYex8JeSpZRLNpDI2LsUyCZtwyMEqtCAgegqciAIQhhBiiouWUHMPzz57vbjc5jZceY05pyKVURAgR2M08VS0lnfujS15EmwYtIJml0pszViipUufZkw+BCmtVYpZqD8dzfrh3rmPPgFyEnEMEJYAmRhc4cihDDth89dWL2+1zTfTw/ePf/tVfHe/P0ANkaH8WnaNcZ787AAUQAAe7F/DVF19//vnPEdhhF373+ng5FZhMdbqMQz8WA+8xeKI1rjruutXNzao/ye/kERxIBhMi9DEw+CyYBYw9hA67bQRK/+7P//x0vnz729/+7vWRDV59viXAMk1pGi96okLTubz7/q7m7DjGJnYhirhSSBESEzGEFbebaGzgSFEP/ek8XYqkP/6TXx1P749nBGhD9M6FYRyGNE7TJAbEIIBxFRxzES1ygQoOrVl7jjcqaOAReBjG9/d3uWb28Pffvpk3i//dH/8cDEJ0JfI4Dia1aen5s5cvXm5L7kV0t2lVAzOlNJ0OZxV6cfvy88+/ePbs2Xa1VZPjw7E/n9W0i+12u372/KZt2xhDrbXvB0Ta7TbrzboWTalcLue7u4c3b96kkp89f3k6nv7xH3+X0vSzXzpRWK1XxL6Uy+lyzjlfLpdck6mmMU1TlQKIrou03XSxCU0TYnMTAucynfvT4+lxZv8wAaGYZk9d261W7dpMTa2JzWa1peL683T3/puH+8vvfvv9kEoTV4g+eCcqNmitCgQl1ct4YYbVLexebGK7/uHdPRFnQfbtdtchWX0rfX9RBSJwjlKqptV7t7/duODff39vModoU9ZKoIuQWQ3UVHRWtCDCPDPOSDc7xoXAvDAm1AA0G15lNgCgaDCnSM5lB+fgiLkYlpxnIB6Z0KNVm8H3BZHnWfUDhqAIfC2SC2RkM0PKCEjNnHOzWFpFVESrkgEZLJx+A5mDuwGWwZdpJpOZQa7lOuUuxfkntZIQYdbRzH72qGoiqqCLc+48UKgqELCBIZmiqlUrpqgis2u/qUoVUXBIRAxVUE2rQQGogGILLCazkGcR+CwGJgQAIKoq1UybLi7Ti12NRQCZGUAVjBzNAiEERCJ27BvH0SMBCgIXNHKOOEA11dkppZqE4I206jDYOziqtbfPN+TpdLyHym2zffbpTYgBDCVLzdp0vnt1a1BTvgRw5Cg04iI5j0asYMBi3CfN1Nqnu+e36xd/+Vf/+7d/+x4qkGKZrKG42W+mMcFQU5dFlRiNTDzs95vVukHCVKap1PNhBAOYhSYGIFA0gSSr807fgUkRX6yCUwjogrlBiDUX+ubd/c8/2z1/sWX2YFG1VQmPD8Pp+I5Zd9tV8L5pOlKZpuF8uUilENbdetUG9/XPPnt8eFcat/7kVRe7mnWa+ttnLz//2c/ZhX/4/rc/3N3/8+9+myscj8PDUT3XLppjQmTHTX+e/u5v/25FzYt/92+fh0/f52/u70+n0wOz+4u/+Mt//+8D0vru/pGI1SCX2m7WXQjjkISMoPpIPkTDVFS5FkSYF4GlZEK0FfXT9Prb+3/8h/cwQbODT1693N/6m9vu089eIJfj+d7F5n/8n/7tN7+7+z//+t3jA5QMl/6REDeb7uaV/+zn+9/86R89HN7hQ/0k7lxwImZVTo/929fvhwswOq1ULgZnGH0BgdJdUpbbZ7fr/W6aym/ffDPmowseBYbDpKNGaL2DoR9O9xNMgAxWDRvY3GyqViAwtCqiAio2jlmnVJMCE4iCWdUiQuQdEULV+XecHBqQmoIY4ZMYatb36RKlM5vQ6cwiB4JZYEu4iIE/ZKFdmaKIT0zHK6vlih/9BMP6CcfrR3j7lRODAEDwe6q4KwbOc+zPE5N1Bp1RVZfd4hMBav4Omzlmdo0j/Kg+ySw1/xglQZzF2GZGtOiW5ieGAEiorIRkAE0br8iTLKmzhEQ8wzEiMiuHZnKszXC/LjEdRIRodL09UzWbjR5nZIs/bjvn8ji7rAKz5fz/EwzrCabEH2sD/8svMsfj/r9xh/PjD6UQ/ugOnj6cn8C8wl62OTarAE0N0bAaAQCjAyTyEBBBTe3DiYUKyxxCSIVE52gqMmAAFmBEFCQwosU0nR37RiqWUsBUFxm/1WPqqbdgITg1LTkDQCUlIgRSmg0awXmHTKCIZMpmDGBIxZZkXseOffQeHcpsgAkIgExuGWPIqlYoxo4xUS4pS1GD2RsSANhRu26U6+l4en777HBzOL69vOqev3h269Gf3pz/t7/7j2++ez2M55ubZ8dxGH9IjGhmnmm9XXer5sWnr569ev6rrzfr9fZ0ufzwzQ+X45l3UFOuNW/3m/V6bWbDqe+abrdfB+Q81OPhbBO0TVwOY0IQUzFqseHIHovVSaWUBAar2+7d4/u+70UrBoKZleDQHDRdbHKbplLGDAjkuZqgmqoYKDggD4rADF3b7XZtaBwq56rtKgDAOSdDW9K7CqiKD75tG8OcsxaroJUQfOtddMzMHph8u23zOD0eBo4AwMKkqOB0AeppZqyrgYiUWkupAIqoOCtT06HkcRymYRimWqEKaAaSud0i9CRQjWTuVUyBCjh2bdOKVDSYJBEiKsisesOZFa9mVkxat2SaFpCZaciET9mWxbJNZZhK4zk2nltEAUCY9YHJxshBTAvUpgFgPPd9VfFtM40DRibBlFNFCJ6ibxjQipQplTxLVk1EIjOTrwAApBWACBxhpf32Nvr47vFhkDMxkFPvAJwDyi7OzxyutBKya3kmhDYyMzbBhxhFQSsQcgzNeqXONSXB8fAw9Hka5XKepikzeqhQrHbr9uWLG+edd4/H/kRE5KOZTdM0DEMayunUQ62zhlfYIjpk897F2CBilVylilQn7Blj8DE4pjlxK6/X3TBM58NYJshRz4fxcprGS3YYNu3aYXN5zI8Ph8PxolMAy8gQ2JF3wjaNwEgEwVCA1CFxA+ys7+udQnTflJK++OrTX/ziy5S3/fHRtKIZIqgUESs5l6JMmIuMQ56mZIpSzXtPDkKMvvGay6w1ULMikquWOmerUwiOPORSHx7yI+Z1c0mpoNEXn728fRah1k2glXeBY+tD413Ok5qmkh1HAw7BNbElF8lVI+wclAilVACg6NVErapdJSfkAAkwAQrYzFu0a67wom2b19g45xoVSRWcA9tyaLpuxY+H78ZR2LmVMkJoAtzuOsc8TXWahrv74/lxdLq53eW7x8du3e1udo7c8XQioRja6P1Y6zBMw5vpT/6Hf/Pu8P796eHVi+exCY+Ph8tlaFzwzkMyqECOjBANq9bYeEnF1MxUTZmQCBhYBExNRdFMREiJCR2zICEpiQIgEhPoNaJw3v8tQBUCEKLNNPtl1LKPtoL2dFB9YC5c/2feuT25N8CH/mpmnpugLgjWj7sxWEQ2yzh33UICECgSKQJQt+5CLZfywK1CBkRcr7pV21QZ1+s2tA0WGIZyGUeGrB20MaIDh+RC++13/3TpD2BGFEXK6TTg7ChfNbioiiKqZlWkqFYFVSMVFFQ0HyOSMgM7dB6IzHlwjmd7fvBmoGLFSMkzEzGzCDCRD5ShEjgFA9RJxpQTGLg2ojcjNRZwSkbtNkbzIIaEpgCixLDZr8FQRQSECYHAEbvWMblSysP7i2+9a/3Qj8M4EVDTdeSYvCNTsRqcA0QxY0dd0wEYmDr0X372afB+GpNV+P6f36W+nk6Xy+UCFbj1fhdgIowumDecihVTm7Wglzv4od6lEyhgyunFixfPXz5/9+6Ht/d3ZQJqIK5AK1H0IfgYyXslpCb6mtvDw3g+QX/RWvM5510TXajZgDxsbpqXn912m2ZMl3E6jzkHDzFADCGNGYE9UZ3Km/sfhkuyRGSUawIzpIAM7aaNbVO76FvHbKVeUs5TVapZVaZcvnn37Z+3fzKlyD2UKtMkg04ppVQzMkfnxpKIyCEqmUpJkqpp45mdb3ysFYdLGYahJFUBxyEERshVJURQqI5otercriu5k1qbJrx8frPumjT1OdfggIm60Lx88TJil0vZ725fvXixW2+b2FWp69g1vp3GAYkCeUfcxcaxK1NWES3qnIshFpN113ridbMysa7tSimHw/GHH7699LbarOVWQ/AxxrZtT5czAHjvTcVUPDlh80RNbH0TUVWllCRohBAcQhPcugtoWVWdY2Z0RGnstRZn6JxHJC0yDul2tS0T5XQ4HS/9mKVgtmpWvcWl5yQiotWGVVUEEKDUknPxPiKwd0VEa0GzAkCIXEquVdKQzgM4dwqhlKyI2jbNIBMxMjM7hnpVB9ri5WAGs9MrzdwBMCNjz+iQjRcflqogV93OTDawp5rz02U1IdoHgsD8GVK8Il147VwRdalm16q1UMAWAurMA1gICk8PXVIr6Ap1zTFMBmYiRsg0hycuoJvzbon/+5h/pYsbK36gjwEgAi9HwFxqbRZhEBnMHoizyIlNVFVEbF42C+tsQY9KbIBArMRKKooCVmG2f0XFRdZjZmaM1woOiIT2RDcxnL1s5hdLZ8doq7OQneYcPtAqQuJnui8Io5iKWjXneMbagJEQVYGIxbDUWi4VTIGADC6XkZxt1tuc83CZjufeY9zv9ymVMfd9GlOqaMgOfANtE9DBpAMrNRwARU1CJCTQknx0N/utVcrHCgnarkHBnCs531+GoR/COm7323649FNPBE3jQnAiVqY0TEMqFXUO3gKoADDnqizKMiYwrGqAmtEhRwce1Oo4TlUmAdiGpmaXR+u60LZut93tdluz6fD4ziyLxAzKqF3wrY/FwaSKoB6pacJ4uYBK9BwDM9kw9ZfLuNk9Q3Z9TX/5n/7XYVTFsN3tfLPe34LnoFX7Sz8M/brbSIHhNL1/9/Du3d0vn39qyswhhOicq2KAsNvvmN6NfV8FZuU1IcWImopCAWb2WA3ERI1neyMAbJuVqTudLtPFTocBCpBDVH86jEN/bleB2fuI1S4+lM+/3MfICPDsth8v6Glt4psmWDw8+9R123wcR2omT2pWSF1J03geUw9QiNFpJs0VzIi8gUmx82kkPIU2+I6lmlZXUFTg/vsHB7ELXSSfIMOUYAQLi+2mmapJjLFZR2CzDiESFOiHkQC1CCw1w4pWrbNeCs1mtgAZK8gCPi0qvCvPfOGj2yI0/FB2AJ8sQwGWXImlO/qI8/7EkJ+H+g9FyhYG6ZWg9QTDz0AYXBEZnDXNSzP1dN3rjSnMorvFEx2uXCf7cKdPRPkfke7/gNYOlwZxubsrBLN88MQYfVp1GgDR0l4CAIJzTkTEFr0ZoM0biBmjI0W9NoNLubveyNP+dLm7GbyS2QkXiT5oxp++AWZeEDMRlZT/K+JXH0NXT65YT1/FH9/5v/T5nzCwfr9L//2/+19+bx8/nH74vfjwol1PxiurcE58AQREm/c2MywJCWbvMgJTy1NBLhRdiC7EEMAVqaJ1tpDU6z4ciYys3TQFxdjUqQbDgOAB3czYMkQDUwQDARQkI2TyDC44J16Dm2Qyb27lUamcsyCGLiIhIyOiVVOxUmpVZSYwQGOe78IjIyITMprpNE0KJqawxJJyiIEcOc8ANqVpysmSkSMfPDG7IHr9kRATEaoYOmDgVzcvf775OWfiyud35+/efH8eTjlVBpimchlH7yoA1lqsGrjHbhWGt+V4e+medZVLF9ovv/zCb32v5/Nw0gwDTqjovJvSiGBsrlmF/X63XrWHu/NlGAMysoGiiqqac+wcCkERVdLVtu1uuqxlqsNURlXDUJoV72+3jh2xe/bi5mdf/aI/j29fvzsejrXUPCUQQcKmiS7wMA2A4Bw0La/XLXmTrBZ0s40+8pSnWsEEDEAEmiaEwICmWgFks10NfcmlgLl5iygMq13TNd0w2GMPFScEhKAEoFAZwUVoW9xsggu8CZt1t3E85OlwvisyVd94v3bDw5hSFhHvXfBYi1U0FK5o1YA8KhecoU92OCuiZcleJ0eO0RGZQPWCtEAEwFcKKDI6JA/B0NCIIXLDFnJKUnPXeufYe1e1UADfetc5AkagnEobN00bxapA6lYeGH549z2iK1YfzoeG12EVRdVVULEqGckRAxBWqVYBBGA+dEgdO0PUKhTJh4AFmq6rxe4fH/t0LrV2G//sxTbExvuh6zaqM7q7tC1mVqWCCiF0TfCeVl0E5rHklAoYqkDw7Xq9Y/SXU37z7UOaxDe+TngZT5IBAHLO3rn1duMD++xCjN1qXaqInC79BIZNiOaiSBWpBqqqjtFMy5QQgaMjwinlKhAiNGuew6uZoAkuhvj+3YPodHuzEsTzaSjJVu3Nbrsnpm9/+/Z4uAxpkgwqQMogVDI6ZEcu22g4B4UQOmTvETVN2Rm0ju/eiU4PL25evXzxQm11wDD1PSOblDJWQLSqBBADEwcQUJFUKjAAFXBVkIqkKlXBhnTxGtVqu3IvX+rj/ZwqgszIBkiEhiJ6d3eahuTZvXzx7MXLV88CNjoxY/DYxVgkT3kKqt7HIuA9E/tcZJzyVKbYgvM8HEs1igQEbCZMvASQ2xzRN1sE6LJdB0JDQgcIBjInQhKjFgHPsXMKejgMYpKr2+6eVTnXUobLBerEXttuRS62zb4W/fu//aft9qZZdeR8P/UvP3v+3/73/83h3fDX//HvgBrvHAOZGSnq2X7xi6/xW9hsV5WLigFY9D6EQEJSlZx3DtEop1rGcb16lgxqKTOJChmdd44o56IyCwZVisCcM8XsEERRYH7WeqU0mOGPVkDzkbD4hs6tyfXwurKzPzq9PhyPVzo6Lmt4vcZ+LV+9HqI2kyWeLrI4cMLS3cxgFhHQ7N01K11ATavU0DZg3K7ocqlD34NUAkME50hFa9Vxyv2QVWCa6nbVrpuw6da3zza/ff035Gi16lbrCCDnc0mpmIgjb5FEIKUqtShUBRQFNajVFGo1XGEpVatUURUFs5wLFi3OOWMFtSxZVaIPjgm0ZCuzYa6yaztXpJZSRBIS7ffrEHxYBddw0TLVNOU0TlNgF7zjyPNyKDYBAEQUgWqBUorOTGc2ZIiNd9HB6eIb9pH7XqUUMeDgfWBkRkdWEpE3k1prE2m32TARE6GaJ5+PuT+Nx8P5eDeQOhVg4RlillScd2weyIE4EIVS50gZQHj/7nw6pCZG5z2NR7fi/W6/6trHx8NpOOsIPZem8cGHpkFyGax6715+snbONY3dbj1D9D5Q0AopS+JoLz/Zvfj0puni3/z1f/BuG1paVwI1IiRjQt+fz2XQmqsWcMimVotqzaVUctitGtdGBYnrDkEuh5zqqAaGQMwNsg9USkbUWur5chGDPIqoMmPThrZr+mEw01xT1VxrMZB5R25I7Myhrzo9Ho5lhNAEjtwPIyKG6Mzq4+NjE0PTht3+JoS9Z46BHaJJ8Y6san8+N00Mvnu12X5y+1l/GQi5a1rPYRwmRvIcOt9KymQYXdx069v9TlX7y6RVHfhaBQTRcNNt9xt3s7/ZrNY+tu/v7oe+966pZewvl816Y6JN1+W2Dc6XlLVIzWImDOiZTHHmlDqG6AgRpOTK0q7WoVkjZpBUK4QYZig8J9RShv6yXm1XXes51ixf/uqrO3/q+2p2T4QhOiSe7XIX6Z2oinU+FC3rXXj57BaYzucxTeqcU+FpzNOYiHWzvvn01eeM+O79+9ffvz1cpn4YL+dUUm27drNdAYBlVFUxdehlFg7S4lYwFyIiYCZyjmeRiEfguZSgidkcGrZwnK4wuRoiM7H9+AGzVbDDmdxlZlLl2pgDACiCQ5whiytp9SqoMUBbkuPnPG4EqLnCTBkTAwMkIAEUIFr8imWeh1VB54hrBDAFEzP2tJTKuSLPHzCb6jIdzDpHnIcFvWYCLgzZ2SkGDVQX2+l5bDVBU0MBM5ht8olwgQJRqwAbo8J8NoDOrzeAzR59S7zi1ZoZAJCJ0CE6NLJaqy1kDQAABkVQouU4mBE9zWqEVq0WlVp9DYAmVfY3u3Ecqk4Gc9YZABoSA5GZxraLLbqozmvJ2vcDIJHjS9/3U2+uAKIFc1uUEVLKk0Cj0DSeAwx9JoXAjGwiWZB9dF3Tbvebn33x1X/4n/9pPGcgsIpaAIAMaUzFt3H/fJdLyjl366ZZBQ5MRMMwXPpeDYKPYqqAJkutAVXUNP8IcZFbARGiIhQFIl2GdzSE4PzlOGqeXr5qX764ffH8+XYT7+6O41SCF8fmvAYP0TNzcNhOSVQpBt94n/ph1YboSUo9Hx/GPhGFLPnN/dsf3r/PFSoSEhzPqWZj9p7YO79bx033HKLGGKdmBNTX33xz/OWXUmvJU4xhHAd29u79m9jt1qvGEe5bcJ3rdZhSfn77/PI4WC0GZkwmhg7JEQKaqXPu1atP0Nz/xdqb9TqSJWlin5mdxd1J3i0iIzOrKqtqekY93dC0oBdJEKAnvehNL/qnAvQ+b4KgBRqgB1BPd0/31JJLRMZduLmfxcz04OSNqKWnMS0RgbxM0i/pJC/tHPvsW3749un55eV0LhQwjkOQcDrN5dTzdr5/+/jNL+63243Tcjp+GKf4z/7k/u2bu9Pe2yzwJElmPyEdfnz5u05LHKqTE8Xd8PbDty/nfaknjDEmnohoTPHUDoToUCYOEspSf/ju/eZ+zHlo2ud62ozDy28WbkvPNsYM49uHjVavteUpI3pprdQ67MY0ZLWeYkpjLoeq5QBjGIhZJMQQCFBb81VWHNnttZ74muxgBL5M3lb/O/JXlR6cLiHS5MRmEL964f0uVrDWtU/iwU/ojNunI19FxJ9GiK8smOvs9fq7q9vs64btMpC8wA0rReRzmaK/QmmrL/gr6uXu9pk3/AXtuu7wVjP4FVW7ep/+scv64tbcuRUKIVczdTXXVb7MQnC46oUexlfwg1+DhvzTIOP1kf2CXl1BOF8ZIut5X5Cv1c19zZB7fbTfmaX+/3DxfyBA8B86+PdueUUA/yOnRZ/pRv8JT/pPuISUwutTrpMZuhhGul3/stdFhZkIYGIHwVcbOWLwmhxpgFozBwde/dZML8aLZkaC9ZggMQ8JwYe7XHzppBrMpDdRF5eBQwhMCCzM1Ft3XXpDV5VIaYyShENMd1N5+kCBeBRV1WJg4YlzynDUUrEGehmcVEKEQ5sKy268Wc6zgA3etPdSe9d1nE4AhNOUY0rDMICsau3am1eAgoemNUShmNXU3UREVQ8vp/vt7Rf3D3W//PKrX54/nN9/++H5u+enH5/6wdwQiJ3s5Xy8pD5vhlqotBKTnPf1r3/8e2Rgh4evdm+++OLNl2/fPrwNJyrncp7Loc61zjHz7c1dWUq1crO52d4N003Ku5h+ODy/7G2BGMLIkslUF1etQMLNw/DFl2+3727//ulXc5spIzgV1fu77fZu1+ZWa+2DXswHRsl9mIx8d9OWUmohppBYOqxDHc5maASQmAyIZHOr0zaYs3artYcBTr2jlu6qS9X65t1kHw7lYHVFRABCHTY3N7exmn7x5dR7X0plRTe4ghnTJt7fTbc3YxoDmXdGymHcxuOhe3dz64vKCNUeUxDD6hsvEVbpur0wE4SAOIQcBxgtc+m1uVprNaxxR+ySeQhsbikmCrFqq6pBRHGRJq1oEK+ihaq9KwnyNKQUpHHvaw21lMM4DCBejoSGrh1sKUUOfDqX1muKqVuXyEupSZA3EUrLXM6Hc/eQYrpsXpunIbFxW3rrjYndXKLEJIv34Wacz3NbylJKt94MpXZ3Gqdxc9NZhlXSJGDVdt6/zGdTtpwwDCCilJKa1vNyWopWI+LWNEpiTvPcX55PHz4uUGyUUyxMtgAAIABJREFUBTFT1ljWFejp6Xkpy7SddtNm6RVmtVYhTjExi3cCEIKAvDeFI8bITDEGYu/aYN26F4MZvryPkYncBD4Nw+l06lqHYZOH7bn6kNPtZjulnaru9/unx5fz3MzBxpcINGPhFDmHIMCLEzszCCB2coYAFHKw7ub47sNy/zcfYgrv3t1Gudvc3QXx/cuPsJhzwCAADUPikJhBoqG6mYqIRBdWlu5UzLU2AvWQ6M3bnd9bnT/kGLv1XjWGGHJgInPbPy37U9mM36YYf/6Tn2zHQLOxm7Awu7mFEF19nhfnGHM292mz/dWvH+d6JkE5uSRGDU4E0tUsxgDr1tWB637T/JWWxHSxMxCn7h1Gq5HRapXd+7Lfl9LKqeDuzTfMNUTS3k6nZTNRnsa7u800bee5z8uClObem9v377/92V/8/N3p4ZtvfvKX/+bfSeRWSu9wubgXbDabN28f8pK++/AdCweJyETEUJIQrK+GO5wpk1PXDsGYBgaW5ayq7uqGGAKF0KqZdig4rgaXvkrT0czUrmO8z8Yyn41YLhscXLcrlzbuunauh19uXPdSTq6vo5l1kbuENl+2Fpd7JKV1KnHlYa2U3HVwBKzbsDUnDA7Ga9Czwwy2lCXnbLogYT4ee1ms1UDIISxd56WczrUrmNFVD4dTX+qY8jQNQ47NmntvvWrvtS5YW0uDue9Pc6tdtavphYRBUEdXb+rj6N0M5DE4EsxBXEhKN+nq0wbezWEsxKxQE2kMj0HSiM4qbMQOkmncTptNSolEunZThVPvpmrNK9NlOxhDTDnHEH/4/vsgCQBhzQlB5+awoGLuYHRTRecIGQOcFeZt6U21lZil9SWxbKYYc3Dz3c1OwG2pT8/Pv/31D6WBC2wG0EG8pqUR2BUxxQvLoprXNeIPcIQQcoi99sWKzvPH8yM2+OZnX9/cb77evNs8px9+/FjLMp9QZulTYBSWzpziQONOOGC3/VI89u5qrRiDQppk2samM0oZpgnuEshhD3fvDs+zayj7Ph+tFyULVqyaMTEheeutGRjWz8U0hMlelNlqr+o6bAKYoepAa205n5Z5LmWZ53NpWKNRpxExRZCYel+1uTGYqVljSI7R0XNO55MHCeqAgCMP4xg11HaG2zTmp+fTdlrGIey2OeVNzmlMyU2X0kz7mLMIE3FOaUyZkLxZKa0tzVh7aSBJHB92D1McCBwnupk297f3bg576VXZTwVV1cxsTOP93cP9/X2McdzdfvvbH2opQxre3DOUxjTCsJyWGBIZWbc1jpWJRZSJ3SAC73XYbbabcbVMilnub2/ndjyzTMMgsj0cn2NM0zBE7lDabna7m7scsym66ZA242jW+GX/omYSU1NDYMBabe7WuhFQa5nn9tNfvPnmp99498f9y/sffqzLRa9c22LWfvrN23dvNrvd5nRattvDD48Ls5azzdXT2HOizXaa9/W8PxMHM2D1xHPAr6mDgnXgi1UgSOiu5BfZi8HU1buR8NpAroATr1I2M199SHGBe15/C86AYhVUhqDX8TgTO187h2vlsxVzXwM2VpWirc7ppOgXtsMVD4KtlfJq64fXQfzaAKw9qjtgv990XmvxenWlzBKbO0wv7Nb1rBwgmLl3ZyHii0DyYrjaFR0XqhYBcFO4A+pKgLiAaZUMO8HBq+eY+mdRH5eX7nadV/D6b7Vqeu2+rKkSLBBFZg5BYWZdDTarB4egWYMjpMjgcTdR8KbcrbbSXeFmIKUk4zBsboaQzLAwd7demw5j3N5MHMhl3i+HPMY85DyyTJKVtTvUOQdnR1hTTCkmoRZInKNMY7q7v3n75uEv/+pfx3ME0Ho3BTF3qAwScli0PC8fEfDVVz/b3G7O8/nleb/Uan1NYAyr/BzucIbRKmmRdeij7upYDT1WAaYqCBxhAEeqyzLXNsQYYxoH/he//Nn7H/72+eP31qoRbjYxBArC4gghDFkANaUxp2kcytKGPKRIS+vWmhAP45hSfDmfv//hfcxj3uWltMenw/PTOQV6+/BV4jRI+vLd/WLLOETa3aD1w/7jmMLh6cRQuD483DrV9x9/e//2J7tdfvf2dvZTvNnQc1Hh3S7MxxYixQgiCwmSwzoby2nIQ1yWZbe5naYpxSNTnTZ5SJmMT3pEwFJwOJTeaXe7cabz+cmMVSUPg1B48bN7UzOOJxm02EvVioApjezDzbT5vj/Xc7MKcxgDKiHGnLi26k4SQ5Cg3vYfnqeHMYYoHLoixggsMcB6PzcXj5vNKNvYmlatzaskQcP6PZrnhZRClGJwQgyhoYYQUspEZKoGAwMODmTqpkoO8OWLZADsClMBBqOrlAlX7JeIfA0GZmcmkPS28iEvor8L4nQldNL16+x+jQvEWmDWPOpPWzJera9B1PUVWn/ddf3hNo+IjCAgYia+nJupfmJOXa+YvTJJLoDRGgbkr88LXA5bBZSMC1n1qgK7nDCtc9RLCMcrxQqg1qtf4ybokvjqaxDyhe5zUVza6/5zjYwlkBIusfDmatd5wxp/uv40v6KEDuELvLiikCJXXMuh/jma9Idg0NU8/sKW+j10SURwRZFe0aVXUOn19vXSe8cfu3z+mHal7/7RI//wBD77rP9BGOufBtSt5xwuL8zMAeZ14gF8BiFe5HQsIsIBq8SDlHW1uLrIAwGAzMGkqr01N7P1S+Gm5JFlHQpJCDElJKQhGjpALNaDK1knc3JiMK0CUtLel2Oti7oaEtUW4xA9uKSNsRcvWNC0WgdI59PcarNL9h7QETmOcRpjBrhJixK3u10pyxrtCPWuioaVx+wA3Ho3+CWAoLRSdBEOMYnDW2tgGqfsHuZ5ab2HKFFwPh/78fZ+vJufz7/6q19999ff6gkJObN0tV6aGtxss7vtrePMqK/fJ6U1TveE44+n+bC8PL/8/E9+vk03j/4MLxHwguPebrfY7bYhCDMVm4ch3391gwCP9elp0RcgWA7wBu2A4O4hf/WzL7/48ovxfvo3v/lLjogDhKIAwzjCSM1fnl8Oz6cf+MNyrt3sJ+++HqexLW3//FIe61yXueHhzWaup2GDkGnpBb2ZKpSYJI1IeQuKdemlFPVWdT6e3TlIcEkQ9LyxDcE6TEGM7RSHDRRnie2Lr3bu/vKyf9kvvQECCkiD50FCormcWm29amkUAsfR6ww11apxAzDFFNTRtBm0wwxkzBSh2tMkIiyRwdDutbRWCxmZobsSg8xTkJhjVxNmioRC2tRBVCvYO3WzDkI3pRCjR3eDWWl1nfGBCexRJMTAkVptS19ePhy02jCFzU3SfTfqKUlrPXC8fbj54dvn+WONMbAQnCSil27FyMjZQcAal85mZikNzKxsitpLuf/qq9JOp36al4Ui0oiQ3NwlhPuHh+XstZdaKztce2u9dMSMEJGTrHvE1vt+Xg7nAuMY4mrk0Jsv5VyLBUJ3nE9N3GIIOU8UEJPUNi9zefv2DQnhcDidT/vDadU0Nete4QALGwzkIsgxxhxCZCfty7rThBCiYMgxkDF5YOQk7384tGVRTSGM93nKUWFixT+8//j49Fi7Bg5OomZuCgVzFE7uvMwLIsAGNhA5O10dPQGpXSUEyf15P3/44XSzvbMSkNndvIcYhmHIwLn3DjOCB6KcOOVBVqqwLkUJ1KYpiqSUc84pxuxE7OHXf/uBuXiHEDZTmjZT6/10ONzecqv2/Hz8zW++/frdm5svHzYhxEC91fl8BGnKqbTSWnUmDkrkechKJonHTVKt+2cwxEgdXV6XbSdAYQ55RW0c0CtHCWtiE5FgbTGYYN7rGu0LNZzOOJ8XCYg5ikDIAkd2VV2Oh+fTqS8F87yfl9rKMsb453/6Z8bLsAvYwLUa1BQxBd6yTeXl+eXl+eXx8Eigh7sH6/54eupLEY+Bo/VeSouSUhqnaVpOZwJCCkyOgtpdvTG78GVhZmHLzsIAuiqBBHLdOhA5iC8JOJ+vbZ9RhIHrhmftkdaO5fdHhn9wDZ91W34Vwlx4Ckzk5Oarzh1+Oc/rIqiXZyRgjaWn1XXe2alZ195TIFdFAjvlJPe7yfZna+18rEvR9QlbRTeYeORa67J/efri3RePLx9aX06nbqpmiCmJQpt3tVK6qbtz70qr69Yq4gciQVJKUHdmkp7XpduJHSAz0qy19lagrfaGUmCKHDBOtNmFx9MSIkKO47DZbm84pN6slnqeFxBaK610phglwGxeSu82ZhUKgUNv5lZEApEzQRWqSkQhCjNvNuKu59O5aZVIcFLtrRsMYBu3w/5w3m1vh80Es95aClFMXvaH/eOxHCErxY1Bhl4vvs8kkYW1d8DA7itsxhAOBNKubl2hm2GTx6Q7Pc3HX/+H776od7/4k5/d3989vL37zfe/drTTaR+zpKHF7C5GktPA7hyirvM2IxUyTjyM0ajujyd3mzapzBYChhxvbnbff/fRz/H01HQ2pkjG1myFMFxIJIPUvFuj82F58/Pbpc9mDdYBEuFWtM1t7dXn89J7i1GmcQC13tUMMTJBtGNZau9dLnFzZobe1JIIc+/96emwnNwUFGTlqoQQzROLT9Pw8lzmWZ+fX1Ik0yZmgikQESBAEBnymGKKMbuhlrm2SkaBQgr5VOZhjLeb3SbmXquaUbTdOGSKHMQmiyYJqQ3NzMvSQ0gPD29ub2+JGYEEzKDIcUgqxDGId+vWp2kcU7Y8RQ4vXVV7CCEQCAxArU/jsJ0yCwEmIuM4sJjf3h6FRAStTdvpZrftVc2wmXbb8VbVzstczv18rHWu5dSeDkuviLks1QAmg7klkRzhCiaeNun+9l4gTx9fHh+fnh5fvvt2H4gliLm2brXMZS7v3r115a+/+tnj42PII0w7VRbuvToJxM0tBTJVXOzJ3S8mJ5dmyVYEnAgEZ4Cd5NIbQdlF4UwXM+FLkrw7dCVU28X4du3ELsVqBaQuln/0WpFWxxZcGzAmNlp35Py70meHk1+LKr2SWC///EpN/eQ+v1YbMK5Bw59KMl1fCnxt4V6bQ9BFTHi5k14rp64dI8xY2A3MRDCiTtTh1+6JVhEgMZmt+ZusZGvCUnfvICM3rCS2S0EGALvIpOiz/uZ6kqt5DYPM6JWdARYQYLSOvmC+NrkGJ6XokYV6bxRoHAf16HI8nRXmYJIY8zAMQ+KgXXtp1dCDIyajGCRzNkopyGWep0qdAqUsKQxjHsx69yxCIYUY2RGYNQRmJoapNZwQI+e8EY69rsRZqb3WcvTeb7+4HTf57t1tiPFYTs/nPZojClEA2NsCFiBc5qPwrtaXdu3lgLh+Nq8qVFhDXRzk8s5ywt1tenOfN9lT6HV5HlOf3lEQn5I0LYFk1WgycxRykZzGIY2kJYgkZuSBttCOMOy22+1cm3Ulpu1uO23FOIIlh3HI+eXj/v3+9Pz08c/+i39hJgPnfq4vfYlEwsZwdx0GZkD7gb3vxvGrd9vf/IhAdZxcyXrbx+iRiUXBYAaTE3nKklKQwOf5hZlqbeqV2IQAUlNzcgz4yU/exjiW0lujcROIY+9de2l9MaSQAar1dDY+kcA8lnowDFFGYTkd5+VcegMBWnzR5uB1muwuq8E6M6k5OlJKLB6ioKD3vtmlUbI3P7+U83xOHMM4oOvxcOyib756CFNQ6rWU3i24mFOM8e72dozjd+fvJVydmFYQF8RCZp+Ue2wEdleCQWF8NTUnujb3V9yHXndB65XPJoQXyyo4VlU0ffIUveIRF8R6LS+qCqxpexd6PTMTCRF1M/bfCdUjrGq9V4dROLDm9fgfc1z6/H//CIZyYV6tLnv0aa9Ir8XqIrR+VZZdgP0L2v364PSpGL8WymuZ8+uBfiW1mitBVjbqa9l5ZQOpGy4eS9c02gsRVa5TgpUHdCnyrzStS+V0+OtA1j+BdwBWb6nrO0yvv6Kqv/eOMfOrEdUrhvWH7+0/ypPyz4z5/5Mgp3/04D96wD96PhcAa+X1XQY4AIQ+UfvWz54JcA7CImvcI8GBTkTmzbs5QXH9VNysW+mVA0kKxLBVXk/XdRdOJMSupsq+ZpZRFObOIJCDTShEFih1UyvdF0MH1BtK0wLCw1f3b8YHJW3eHMyTrd5FDIo5brfbxKmc63w8W3cvbtraUrs3XTTmGGJY//56753Wz/u6yBL5xSzOoErmEhFEzL1T19rCduLAZVmq65f3b969eagvy/n7/e5u87/96/+j/hbB2A5WrNFKMFCHOtR20+0yL8uypDB68Xosw12OInMt/ay1Gcjm54/v/++PeIv/8r/5i83t5un547c/flv9dNrPdIuURb2VevI03u7uv7n5+sufvqlz+fH7H8U4SShz7d6HzXTz5mZzuwX7y/IIxe42CnOUuNvdecPhZT8f6+FpRsNFJy/49+//Boy0yZtx8+7du/uH2/v7249P3xtVJIW00k+LniI4SVBTCmHIQ5BBN1Dttde6nLr30zyLuJOx4OHN+O6rHTt6a8wSY67LcjwVYq+tbzabd1893L8xQoghxBiZoVbNavemaAg83ozjlLc3b5e5l3npWiVj3A0c3Vun6r23qgA4DlEQDX26j+7dOrVSy1nrecEChyOBw2VPFoeQh1xqa80ACiEGRWtlt73n4Igwq90rC1hlOXRXt25truIeIrNhTMPd/U5CXJZ6Op8OT3M7AgeU3iF2rj0I3nyRU85DHKa32920++2vvz88NxTkHIYpLd60WJAw7XbnflCBWbfozBwGiUnaoodyQsTufvh4fjzXuTfLGTe3mxSDu/XSdrub23G3f94fDgeYxXF6uLsn6BhpMyUR7f1c2lyW+eXUjw1D8BAjEbuhtf6r//Dd/rn2DnYmDzAhESIhNVc5n3sQ0+5DTjmn796/Lws2eQopnk7FewORkYfAElIeckpRAko5m6lDRTwmDIybDQYRmAZYiiHn8OGH704nhIAccp52S533+9PHHx5/+OEJhryRNRp4XZEosAgz0Gup5Rhu4Ays5pGstiI4QZq5hEAsNzcPtfSPPzz/9Ku3bnZqBb6UpeSQ7ra3j7Wfl/mslcNi6tVqGuJut3H3p6dHVQx5UDPV0poRNaDGmAjhv/2v/uX+5fDh8WlZinl5fjyVit0U0hBNKxn1dn7/w7dvBmze3I67zX5f5joTI01prnPtq18g5U0MIaQUbx92ikQ/G/6P//2vPJhbMVMVBCYSATOpe9fVjxb6CXeBEeDESsR87ToCyEsv2oZNnjaDUT+U+TS3McOHwCRmej4XbgapXSPTzU9+8vbpufz6u4P2X/3069tizzcP25//2cN//ndf//qvP3bQcm7qenO7/cWf/tm//9t//3j8+P7w9O7+QXfmzedDxRlNlUMxdRQUmrHhKY/jOKk2hzfVauu0ya01tUYEkTTEFERUrfW+bnqMIcw5Ry/ryAkA6+sO+xOlao3puixg7tfsnH94tbM/uMevGSXAZ/QuQGn14Ls+LME/cc4vTyvMEBDZSvKFExFLCK3V2lSoA9hNk8hDCMVRT62cjgfi7e1uZ/309FK0YrzBbjNE1pfHD3/y5z8/HvfnfZutu2MckUKmIMd+rq2XVnzNgXYwE0mMMbKsCgAqi6qZqQEIYSWzmwQSFubICDDASLu3UpbTYqY5hXEccoo5G4nkYby5eTON2+f9+cfn55en/Xkuat61w2naTQJyVWoWEQIla34qJyiIOMYUEgcptTYDpRTHcRzH0UHzeT4elqV04VWXBCJIChzCZhNPC25ux7df3ralP71/smrl1N7/5sfjfsEJvo65zE07+uW9Z4YErnVhlRAgQjxG9+5qOrs5KK0TOI4xuFoeMmAfnp7Tb8M//9N//uf/6i/u3t6c549Nn8GVmEIQYe7WJYQ08NJOhAAhdgK7BDhKr0upc+3l4fZNYJrGEGmT4ng8aH9RnAEVYxaN5Orm3kHKIQmH2K33ueIIdoer1WZag4h11KWhEkXyYvvDYRj44eFh2mwPx3lIixuvBUeLl5OqQQQMY3YQlNArOOJ8PP3mNwdUCEXJ0ZRb1Zx5yDnnMI5pmZ/nBY/PlfEB8DHGILwSK1q3/fOxpn5//zCf90/P++ePL9p9O928uTNUf3Nzf7O5ud3tQgitlra05suih3KsQx5ux7tM4zbvgmSAW1UinqbNMIxOmPu8icMYcg21zgu6adUwMEPYaDds0QyG2+2NiAw5hRjXKbFae7i/j0l6r7UWFhpS2Ix3u+1wGMfe+zZNm+1mO21aabWpUApIvbVyttOhaLVlqcupzSegQ4NBADNnTEP0bkmydc1p+OonP90M6btfv3//4cP7Hw4ASLmfrYvRyCB8+K58eP/rr754+rN/9ae/+Gc/PxyWuZynscXDniiUczETEpJBgJXL5BeH87U5NEDgDBasqxMIFJgCOLBAVCzClahXAzMr1ibHiUhfO8Tr+vfHQqCY5bXorVl8r6CNg16r28qHghH5lZ2OlTC5jmtXDeB1VbELwcLA6yifhCAMAYSIL1jXapqOVxXhpRvk32mBLvQEvl5fC5i7XskaZp3gvQsYBOtudongukq9V3IWkwFGJNxbg8P1KmV0path+2vX/qpR+qxLvpyT4SL2IefLvJ6ISAjUetUOOMAwXr0mJOSYOLHwy+Elb9I4bFIKaYgc59asdmfx3vv53M2XbnMzhWAYTbHERMzIOaccHFZ7K7W2jpgwhDxMYxqyu3EAs203A5MxNSYZJAjQSz2+vOCIJRejskZV8BBjynETBEib7Zsv70Ok4T6d9vPLsod5mGLO2Z3a0u6+eiAipisrzxRae+lwIvaUWJJQ5LxJeYzjJnJmYls3FWKn25vhl//sZ7/85Re3d+knu6l9fb/Ly83uK2ETpufHsouRKLkFUCAwPARi7TpNU4wh5zANW5+sFYOkYdiWyR5u70/ax2FCiJLy/f3bMU3ozk5D4Lvd7XZIMYbMQ5EzyuZ4fNmklFJQmyXobocYzPX8k3c/++//u//64+HbJvHNmKp5ra0XJCGGq8PY3d1Mmd3RVBuztXaal+ZeNjtKYTTz2WuIUOBf/vl/1vTg3s2MmTdx7KH35ViWIyilcWCODVARIp+XpRQEdggM9PH908vz3CrYuDcspwWqkrKZB2aWddSl8I4ACQbyEJETlj5P4+Z2dysISQ4vj4fmlqhz5Ol2Q5GdMI7DXMrL/uDuEYE6RQu7ccphmMaRRdy0W29ugAsxMbwDzDFEBkFhXY2M2uXLvTa47FcABuRraw6GQ82cjNdS4tcx2VW194qDv/53vUtZhfhSQ+xSIVYhHq7snpVFSsyfMIVLbaPf+aq+VrDXfB7YlcV6odVcQhjcV7T9eu/14fgyieTrbtEv26bPWJq/e1khObue1xW6W6n3bqC1mn5yDPtdDO7Tu/F5sXF3oqtRIF4fd/3Jn70lrzXaL7j5BZZaCdpw2NUmcYX5/vBF/Ef2va+8qs/hoT+KXv2jl88Bsv/U3/1Hz/P/4yW8Inb+yhLG73xGtBqW2cVOAFgNhdTd9OJVsm7tiYnAATBzJQt8edMdIIWTUXelrlwL3PxoPRSPRAyEiz52HR8RU5BIBrUeCLquK7imDhGOp6MMXL0d6wkEycGaU2lDGF2tH7uTt6UHC7gGjeY8MjgO8egvJBQpePcSSheNnGKO6romuJlZa42Dxyi9i/Ze3UKUaczLstQyc2cJdD9u725vbqddK2G/Pzx/97H+CD4hpRiIerVqHUQgjmnKu3x8Prqb9T5OG3aq5yqeqAv3DtMAVrPQGHfUuv7qr37z8z/55m53X7bl+fl0eJ7PyzwtPO0GHnBszY6awxQgIcfd3egdVlsOYZfH6WYbxlT1fDgej+V49yC3dxtXwGmI6XA4Pn54ajPIkOIokOJNW49ZQmLm0Fo7nU7E3nrd3o6cBw99bi+2uBso5hjjcq7dVLp36726masDnIhZvdZSm7rZ8WYXp+k+hdgquxFg83xiopzG9z88arP7hzt2iGC72YYoy3I+HF72h+e1/gRC4Cq85bgZZUgxlL6Q9DiwUYepUu8EI3BwSRRFQBKj9e5dW6u9lXXsf50xssTsITKEneDsa/BeHAaOw1JSPRdOzOrm2q0RO5m0ZrU2Ih+d3NFK663FEIRj5Fi99WLlCBgwsIHa7MxIQcrSuvYay3xeMuf7+10/P84NtXUD1BFzCJzcLG4HbabuIYgIN2+1LGoaJ7z5ye257I/zc2fb3cU4yDQOIUhZlpeXl179/PK0nGspcxCeNiNPOQUiDiGnwN609O61q9qlTLIISyAVApdSzzNQkYac0+Qman05L+o1Ve4N2uz56XnqU++9nAFClEyBmbsFY6YQJOWQh5RzJPKyLIfzHrBhjCE4M+fgt7uNCHVVchJ2Vz0e8XB7s7v9Ig3b49yfHl+efjx8+PCEjrwNeUzLUmqvIiGGLC7atLRGkLwdmxxxrQZO62hp3W8bBwmJpt1Yj70te7UTrJsuprNrSVlyDOQoc51nODc3GIHZ2UMakt2QqokEg3d1d4QQ0pBzyknS9x9/0+oyZru92eVhat1Op3mej733GPDl24cYA6i+HJ/HDMqEFDZ3N0s5PR1eTstZ1ZfmXOqOpdaltIUD3d3d7G6/+Lu//94aH19O1hSKzh6DsayJNE5y9eMFuV5dQ+xKGYKTu5MH4u5GzQUcQ+5O0LlViFBTiQbr0kzYGkkzTylt3339ZR5nM9V+3p9e/vL/+b++vPupZL5/O/y7v6wMtgBjI6JxO/7bf/tvQsqi2D/ve9VWG61pVB1W/IKDB7S57pf25s0b+Bq/bsR08SVdB8CMEIhFVhYsgdZ4FyJeU7o6+rWn+uNzm+vQnS4bhFeE64+ukfT7vK3LL/3Bg6/EXfqcmbX+/qd1cB1n0SUn+nIu6NZ309RatV6bGwgBSMJZeEoJTLsRFjbm4RhqkuIR4xDGIcYgxHo+zWXpvV+76YcvAAAgAElEQVReR+9o3ZlWXj6Zkemq6hciEUkcokggIib6/sN7W1N6fU1Mk5xkSFGII3MKKUgSDm1pReImpUAsq4xa+5cPN60rSRiYqNv8eHj58LR/PreGi0DSvLsqGZHlnMdxGMZRrR2Xo3dICtM4jtNYWznPZzUiZu1almJqKaXNBmq9d3f3lEKIQVhA1q3c3WDcxXHI27wph3I8nB5/+/L8YQmQyLFXb9UjHCAhMgKxrFqYNdTtWsbIPFhrphg347gdlzq3Xl6eZ06SpxTzZul1rvXHH59A/rNffDkvaV7SXD6oz2Zg4tattkZOTXsI2c1r7a4QX5VfjciHHA/7o2AQHkBJq/cjUMEhODEpQZ1BxIGECfCqvaiRksEJx5dDvpEc02JqHaYuLGk3ENF5Ph4OJ0dMw5Qk5+hIDBLm2KvOpSUeixV2kIq5MtQJ2l2ZYIQKKFgYCu29mUWJMbAwARjy2PtMAMsQJRLI1J1JgjSl48v5TAupSAqt1vlcGMwTJYlRYqAAdTKJSO69u2aO7vlwPqg3DuzVNnEzTTsCt2ba3RX12B2WNnG32Tzc3IlzJN5sNrs8bofJATefctY2miq5O1NgiSGEIMJk4C+/eOjWy8JurbZ6fHkJOYYgt9u72mqlJVD0zq6iRburcbdOmTc3mzzkMYWjrNiuIEVIiDGFJCmyHPf7xByH9Obuqy+/+PL58cP3336/fzzjBWETmGOVArAYG7qpgfD8eHz8cLi7O4/jtps58aSb1vTssymEgyRGc4fRil6tQIpcuEt+HTqs0XcGhxmvTAgQmEmcmHg1pSFyWpsXv7q4XIvda4e2mjK/Eos+1aWrZwp96nOcrsmGl0bxEi92ab/sFSK7bI0u5Awid3JemWMr09zAArE18YYA75dWDn8gQnktku5XI2Q4g9aumVcx08q6WJU75gZXM7JP/lKvBCoQkV0eyWkNsL9WZCJc2Vfruw2C0YUTsWaqrX7y7mvE2pViQES0SpoikxMHh5sC/TrC9ouLNqmwBjDMWdVVzQGJYRqnlj1W6+61LnM7m5sT0sAhCjioaptrCJxysBXTvMw4nIMQw7ybErGLICXJKTi6KTGZsLGhl9P58Lz9E+DEx5NBgRHDLhMzR755eJOn0K0dln3sfG5zw0m2CAkg60tvXo9FGSByhq4kWRGkHWJAykhJKTYInM8hI23yOA2SWCJH4ofpi5vt9PXXu4ebkEPrfb9LTJuR3SLJzWbHzXMeDKGaWCFT9G6n83w8H7756Ts3VaMUB2ayXlonXfoQ0sPurrw8H/Z7Ez6ea+12O7VIMk7xYfeTr959IaKs0Fr7uUaXD9+9//rLm2mQUnuAvPviq2VpL/uPt9P+m6/vv/nqzW+fH2fr5B7ENyOSBFMrvTOLAbX1UhYHQqBhHJg8DZ5HjHmMIaoaoUiCEiBN2GKCez+diutiaue5rFaHp9OZJKzxAK16r24dHoKpkPN86qUoHCyhV7JS2VnJAA8hMLlqg7qaggDS2oqj5xxa7yC4IMSwedi4oy1m7nlMb75609D/5j/8bW6JiMpcV9jD6hy6BJPZlxjiGtHZVv3gSl1yvhjdMRHYzYhZQMYGvWLZK4R5QcavVeP6ww3OryAAPv9G4xPNihz2uukysrV4uDtdiEufgUeAqbqB+HeZpH9Ap3q9Yr/H7nGH45Wt9PnO7XfAlAvVdfU+WllSfEXsPlMe/gM8o89v9c+vXGYBnwFAtFKqLjjJ5TVeobRXvO9aK6+JS+sTsK/o1YpV+WeKPweI1yTF38GbaP3ELhQseq2un94us1eR4OfEqD98sZdT/Xx2+8cu/yjS5Nel4o/ejs/+bP6TWFr/5Eu4KifXs1hP4XWDfr2RvHeFe+eLJ5bD4M5B/Dq4uajoL5kpfMUXQQQz8zWY0ry15gRrHaKWlcAhsUCIL0+7vsOr9omdMosEL+wUwEk8orje3dxocPaijGbNGGOI23g/xkF7Px3Pp9K0dqtEHWwcQxKIkNjS6dbDGgPH4maJBpEQUmjaqtaVluXQ6GChnOK8aGkWhIcUU5C5FtWWh2GaRgbKYY4VsfG3f/cYDa2hzZplYBBLoBCqd3d3yHF+GlMWETgxCYitOFxX14Rowbyyss0O4xb689+/zDfn2y9u/6f/4X/8X/7X/3nKOQ9BEjqaxBAmhvfj6cxORCY5wLvWXq33c7PFm6uycsDbN7sYo3dy417q/unQ9oBDODIxlMUEYHFajaKIiBQLCwDjOiDCdG61aHOBkc9Fa7MQBpY0L3o8nOdTdVNm4uhp8GEcNwNHwTjINOSccgupVnWzzbRhknHassXW2+HlVGZLMZCxiCxtaa1LWLEmrHxqFo8S2OJZOxkM2szV69xaMVcCRRDcWY1VmECX/OXWuhpIRGKAQdFFQsxEwbu3XnprWqrGyDnHnFIMubTKYFIl95XvzxRcHMGIXTi4oddeSg88l02TMUQPmzjcjG1/7nnamrc2z2kXcs5uLYXh7vZ2meelnKft8LNffvn84+m4P84HwBGnwODzcRnG0VCYSAITsNQK4O4ubh7SV7989ze//mtE2WzHzW12MnLXWrW2ssznl+Xpsa9LWE7RFH1ZiG0zJeLblFBrU7ikFLTT1YuIGSub8qsvf6rlx30pwkE41dZ7VSdWpQYbU6SAeVlKL+4OQgrStGOGNXV3ZgoBKcdxzBLcrKv21kwCiD0IC8uY5XY7ERqT55RyjqZdBO/evd3evn18bh/eP354/3g6FhGWnYQcem8GTTGsomVXtFK0tZSmcTeWcrwUdPG1bQTITAGjoHFgCp2GJulMvFcrTlXEJGC7yarVrK87c5FMMUmgm80QeUicwiYvtZzP8+lUajN3j0mGUW00i/3N/fYUvdTKkSX6iLDZ7Ag3pqrattNI5EOUpc3ffazndn64393sNkb9/YfvezeQzHNtegLz8fbh448ff/jwktPdsLn72Tc/nc/V2Q+HpqtmkJ3kwhxanSOh5Kt1uFxjZWjNRjFQF0LgxCTV1Hpf5qVZQ8X+UGpDCIghD3k3JMTcl3Y4n/p+/7zZjjHJ1z+9nxeydvr7X/9VYvr6/hd/9ue/nF/0//zXvxrvQ9rkOIbjfJwPyLvKwHLsy/nlbrsbOBcrURigruoCFnE1XfScZxYaxokkL731dnZfzWRXfc3awqywC7OImwNQM0C1K5wunjT/8YXwMg5cJ2b0Dx30R+659kKfbqDV2eQTe3td9z6jXr8+58ULAboeoGZc5wVmMQYKslQ97/en8jSXo7U6hOnu5rYhP73MvbYgGBKNOTAA0yD48cPj6bwASJHdrTvmUtaeTCQ4oV8cGsmM1QgNqzU1EWpxM+8GACHAXQkhcRrTMOSBXMrSTvPcq2k3cqMkY05DTiHy/vCjWdfa50aE+fx8qPtzO6E3SACcvPpcihOIzUZiDUk8pXwzysvzkSEpphijmaUY1UnVj+dZ22FZ6mY7DlMGvLa27rFCEHf03rr23XYkbssy30w3QuHx8eXD+2c0DJstNFFXLb3pDHbmQEJwsu7WOyLDdW0mHQ72kPMQ4zANechVl6qt955pKKUqdQg54XH//MPzdw/v/iIPCGmyw3A8nctSNcpScT5VJluWllJtzc6HEphu7jfMmUS8EzE9PpcxhiGoVi21oYLW2HFQ7633zhbEeM1lrnWBawico/RMfV7u3j6kGMms1kbMFCjF7HB02p9O3bhrYXCrWhZdx89l6efzMg7bdfCzGnSbKTNgLBAJQ07QygBbham60Gpqo7VW6iGknMqQ85uHt/d3dzlnOHrXSIElbcYbBq/m/OMwvbmTwOH/pe1NmiVJsyyhO3yDDja8wZ+PkZERmZVVQFU3IDSL3oNIC7DhN7BhzxphwX9BBGGBIIIgIOyARS9q0y1UV04VkTF6+PAGG3T4hntvL9TsuUdmVtaipFVc3M3N9Jmpqj29373nnnvOxfpiu96smvXl5sKha3xsYxOI26jMcpxI5wLCpkoVgw/e3NnFoMzTnFM11E2zfnbzNLDbb/Y558urq6ZrnXM552EcN/06utA3XapZwZid8+wcOYeI5pic830T2ybc3t2+ffMDIF5eXT97+gyVhbSkKjkBMJgjdQjes++3TdN0jpxznoiAAQh8QHbUr7quacqUQ/SR/dPrp89vXqm5929v729HqEARYtMMdyOgB+KaFAgcAXsnot/87vXhOL789Ok85VQmYnaAxKxq7NhVV1QAT6Z9QIueny4lniIggiAQgqGaVjNREwJGxcXPipjJkIwAQU8h5yMAHR9Bpo+j2amOqXBWXjk/e94BT/yBUygjXIbmFPE0oXIST/+Q5Suc7Sr4pAZLuJiIAJ4mpYHOjq5nbZ0Tf+IsOrMQsk7DMsvx2wIX4ZmERojAi+qN8VKOqqnVc7S1c3m21G3nMZ1TyD6hUI/jNmj44dLYGcZaJkHwpBRvYGBquGSzqmBGCIaMi04JuZPamJy8IBbcESuBgGSVou26Eyy5FLUqVqsgkfPRWylFqoiyAw7QtjF0LXsqknKWKoIVnBISMrFjq6ALrEgkYopVTetijk6oBJVUFnVhLTqP+z//2avDrezuh2oQusYcjjlVLJMMOWHFkux4rNH1dHWzHocxpzzNRQnCGtYNe6Ym+CZyCC44itFvNn3b+KYLbe/YGZKyR+fNN8TOAAVIyfCmvQjsQgRnqQzjve4JS53y7v591zTPNk+5IyKeTFSskAGhgaVUpvnwySfPU05SRR048iWbVgNWyaWmfNzv78cj+GBEhk6thKZZ933jgg/sDNMwz5Nokjaubt+8//T5daBQYdIil5vLd/l+PBzxWbm5XP2z/+gvN99/++W711Mp5APUOfhYssBsiizEViZmcs6INQRQqU0H69JYccNwNLV+TS+2N6tNM87vmh58Gw3q7uE+TXumYOodNYj+4eF2ztB2AZ2wRymoFYAcW8PUEmZTAkNEpyaAi1TSogOpiCY1KaqxQQMxumk4GEtsGJLE4IZ8HI4DFFQyJKhSsGKptVhRUFU5pTiEzjkWLKXM42jV+tAvtl1LrW2gi6knIiy+6rjEBqIFAD5PHJ/wJbNldm7BeBkB4Mx1Oqc/eMKBPuQ9iADnQ/oQkxTPJnAIsLT3gNDsLEi8sDUNBKPzdp5B+z1gBT9S/razpPzjywCgS+9QT3DRAnSf6WDn5Gy5pU/xC1FPKR4+gkA/TgTPWNv5wpjhojiLBnCyHTxRpH78c4s64cdPnrSsTpDHQjk1RAePaN7JedVwCbMnBffF//X8MfARWZ1ouWx0sr5YDoY+fOIjfraMKhAtYNZjzvyHUN2HLsifJG39fS/93vf1J3783Og9HdI/+Ib/yM19WATwwwMjfByLPeO1iwDjspsur7rGqapqNTNTq7mCgnkgx4i4GFAqLN8TocNF301MrQpUAQYTU1NUFFUDEzPQggiCkZXJ0BGyYwbl6F0XIVKG3DRhn0ZF48C5ikp23G66TePiNEyHdEj7ZLMicM0Vkk08ghKIAdt2vQIwF5iApCqjLeryJNXMpIhKRbKcITYYo8e28UWYQKvEJhQpZkgAUss0jo3jWMLx/fDmix0MAAWcOQI2Ix9a30bL45iGMtZutfLMpnY8DojYNt08zxEis2vQuLJVUNWmX0HNhzeHw90hXvlf9D8Pwf2Tv/irhEdtcuFyTHslFaxpysdhQtMA3PqmmhhVkZLHqqzgCJlUbNP1ZZ7bpveufXh/2O8nMAjMoJTHorkQLmMpaqBatZaaIB3GAzzAU73qIUKUsQ4Vi2+o1LrfJ8nW9U30rohNCY5DgVIAAAJ05kIbmjZuOpqnYTgMNQoia1VCd3nxRIrUok3blf3x8HBMOXdd8IEMLJcJSPu+A861VgNzi8pmrVUVyBRVFt0UzVOuxND2gOC1gBQtVkRtFVqpCKAiAArEHFxDzAaVPBiVKrWqqIKIlQJmNcTqXHTOT3NCE7Eqkg0rNsQe2hijDwbiCBxh0/k+ahOdB+fBdV3jITS8+XLatV1f6iyzmqgZMjsCIMK2jceSasld37exm7eXd+/30zgDsAmgI9FKHsk5AK21hpZWXXz18qpdB3BSBNYX7Fr0gdVgGMd5Lg7BMZeiUE/pap11yvOM4IPFyKUKMMylLIYD7BVmqcVqqS56733bNroND/04HZOdFIWT1OLb4NhXyQ37dtWo5XmaRGXdtwCUppJTIe88o/fsHTsmYsw55TIJmAoED8zIjCGEvg1d16ZZYvDr9WqzXgUX2haQYHe//+bru+9eP+x3yZT7dec8z2keU/EeyaGBiVUVVSzgAFCKZEAEWkQeiYhdZEIoNSEZOeWgc925xi6vfdOncdiTWmD2xD6YSnGO+37ddyGGDfmGSMlpzVpLYcd5tt3dcPdwLBUQIUTo+1jzevbw+YuLGNqc/ZzrOB8UaLXa3NzceMfHw34axlISIhnRYZ6P4y7LdYjPOTgXPJAQBZprmceaS0rzfn/87vv7vs9z0ucvf3bYz2LCAVIeq2QjO013mJEnEDQzYEMFPFVLYCBwJg0xIZh4BHRUSklS1IOL7nic5gSIEhw2oev7ru0rDfOcZLgbAEc1dh5jwxAh5TnVPXF99dOb6Nd/82++/snLTyhygvT27RsgqOVUabDBqltjGeZj8uy94ww11Qpnq+bjNEQfYhsdO3YMATpqPbh5TiKFFqvMU+GDzrGKmWGttdYKVUDxkYawrMQ/6kp9+PdRWRPgT0Fd+OMfBPgwenimDCyAxEdsLgB7hMUQiVCXAoyWBJBAzvsSwGG/ZzAO7D3NVSSXPM8qNU9HCr7xHUMo82EcEyK0q9DFhgCkJhWpQlKBGb13IlKLFKsA5nyLSEWsVoyRkNiIRVFN1apUUxMkRDMiIIIYXdP4zvnIvglNH3upmEXKVEpOYCelaSGm0LQ+DKDOkyADgImtmq5ugGTc75NWImCVKopAhgjHlPOx1qTby3XsQy0gxeYp51LmeRIU7xsA0lqmaR6G6hw7dm0b2zbWWlNKJSdAZILYOFEZh8GKsPF+v9/fHyUDO2fqZFLSgBRAwYwBEASN0BYDLSUkUAMVIYIm+C6sGo5IpCYpTQpGDqbDDBV8jyXbNOXQztzIV9988ezZar0OTfSibc65ZBkOMs8leDwMudMsAqUAejJVkQoqIkqMUpbZ8GTZnTiQaGayeEyAwKKeZhWsKtXKDJ7QIZmKY9/46B1PyIomSFVEydh58NbGziw9POxI0RRzUhWSCjnrMKX+5QbVKVStAEBqDCQMHFzruAuOU0ZTAgMAFxatO5M8pyp6cb1F0IuL7fPnL55cbclEUtFaVSGE5uZJb4ZkCFwv4vrJ9gmja3y76jbrZg2GpZSZkkMGNUIIzgcOZFxFuqbvoveuQUFRI0CHjtQxAHuqKT+/uVm13V1zC4hPnz2dcxap+yo5pdVq5dq2CSGpVtNF9AfJTnLiZgAam8Z5mqbheNyJ4Kq/QCOrEFzDIKDoXbTArF4ERbAJ/cX2MudSpaopEDiEEIMRNm10jo4P03rdtT58+ulPWr/59a9+9+03r2UCZPDB11mhOt/27BxYUWLPAg6yyP3d8f7++PLT58f9PKd586SPMTRNW0i8C1pNKpx83Zjg3IVdlHsXXxVcCDCIi5KMVRVQAPaE7JxUI0M2NjRTJD2P2J2IpR/BUKdgeKYnEeGZrwUfaq3HXj8s4QtOEiqnF0/kCgMiB4uI1JnXcKI2LGxehA/vetb9WHYGBGQE5VNZ8Htc2R/NcCwXYxETXI4UTdTOrW0AsDOydormuhyxnZS3cJE7XghlcDoTBEA6lbQGYGh4pn4sF4DR+PQZy9mZKHoys1orwalkX5IHIgZFPU9/fID0DE2gpDrVObZRWEsFBRSpWYxIzbCKiJx4s0RAjsktw1tWaxGTWmUY0kIJrKKqxg486aK7IrWAKiNLNXaIUBBk0WchFND0k89f3vUzBD3MM3soaqpSNE2HIzRwebV2wc0wb2LTXbjQ91ZbrdB4v1mv1quuDb5rfQzMbFIzAAffN8E3nW8654MRaWgwNtS05DwhioGg2pVbk1kpwziM47ifDtPFtscs4+6AqWBGpwGAVKVKNSDnAhEDcdHMzk2TjdMw4tyGrnF9G2Pjm4eH/TzOoIoGouK8qyZznjer1WbTk8Lh8HDdX9RUJWsfVtfb7ddf/K0Je4hkfphGB4wKTWgbz6bzn//Zp/G6Kb8sb+/vU5H1uom+mSdRAEBXkJFq18emBdGZHVapPvjY8Cxpd0jBw6sXzz77/NnVzepu/N77CjilMk3jEcRiG0UdYSRuyFbzdMw1dx03yKakRapCdcjexdghOlHTKiLL9BovTpmwIPsiSOAirLd0ebWZ5ZjB0JGYKsphmqa9sEDA4NRpxSQ11SJWu6atVmut4NDEDMw5X7SUZIywSJ8Qk+OgDKVmKYpqCxlHi5qBR0Y42wkiABrhEj8YQR+tBxd1H2A2E9QTnsXwAUJ65P8sMPnSv/s41fr47lvufV1YWY87/H678BQzHnGQR2zlzAQ99yYBTrwtUXwMX/BIwsbTcCAsbFPDRf2McIkV8BEn6/FEPn4Ap6QRTnAdAC3QlZ3jJ8BHMP/5BP8gyTw3ET7+lFNHgXChVsHim0hnxcPFzFjPlLfTVbLTrCR7jwBkhgInrNFwGXr+vRT3D9Pjx+d/j/L2+PgfRKD+6GYfrvw/sOfH8NnHh/fviJDlEM9LnMHJt51OH7/0kxZkctFiAyNDtYUnrdqEIFWq2PK3qi60aSMEQqn1zKcCNHMUDBWZkCCbmShUAwErUF09VTQECgqUCreErECpqpYKDIiAHl10yDxP8253j96FvpEqc2YXGQpI0TpVnUxGsaMhGGSDChSYXUAERTm8OyIQq1fRaZ6WlgoiFStVaq0ZgAAVDKBAG9u+j2Iy5/mQB2EAdo4IwMqchTwTHu8O+/e7NoDMwIFhVikiVZTJjMxETZE55VmYEHge9uvL609evHr3/v1xOETvkQkYqAAhSykqQo7JUTnKV7/96ph3/+K//s//9qv//3Z6GxsvGO6Oh919zpMCwLZ36Dw6JoMhpSrFNWG93brW74+H29tDxzwexk3cbtv1QUZJEIi8RQKX1UQkhhB9YyjVKNvZJEEAAHLOLgOYFK0UgNEDUMp13ENKe9OolQyQYxBHUBMAjLmGIavJ8+sX+4f9cdj37Xq93gbXALD3Lah8+8138zBNUyak7fby6uri5ul1qeV+924uR8cWu9Vu/1CKuRbY4WE6HO/TtC9VlYP2WyaPIUJsYttFppCmetiPOc1VLYatFkmkYBkUzCk5Y4/EgZzt06FkCwFUQBSgQpEyu4mYCFytWUxLzbVkQMAKGDiGZt22iCa5tDFeXWy7vg3EZBhCjKGpTV376d3bL0RtSUDKfTmIXN70UuyH12+ePn1yeXlxf/8wjLtnV88vtmvn7auvd8N9WrJEycANk+M0FyjWbuD5q8tXP31StPzdN78DB75hsTInYO/maXp4gKs+XlyuMTqbxlosl1lqLWqIoADH49R0vjHKuThPLgRngFRKBTN0FNpmtVlf3f7wvakxOVBRKGZqqloEPdksyZXVtgflWiVVePFkVavBNGfJ/WUXPLIHRGOHZmUY94dBEEEyOA8IQkxNwyH60Pg8awi4Xa8uNltTu7y4KEW/e/3m62/vjjOQdyroQgjBj3MCAwpORUsVMLRkxMCOain5kGFFxoBMiEiMLpBjgwzEAChIcn+wm224uu43W19LtVK9iwha69iFVRO99Oi4b5sNu7bUnNIwjmOupW1aA0XFyMAIquAJHDETBMLX33y1WrWbzaazgHc1i3gSkEkVyzzkNMzTYR7dyxcvfID7h3u8rZeX3eV2c3l9NQ5j8G0VLLk6z94zVDwOQDDM4/BX/+SfIez2hyZLy9mmrCIqqgUWC/JF6wP17PYCtLTmFwTLkJDJl1zNGXdNrVVNuma1fbL54e5bzXA85sZDYFz1jY+IxtHFtpvbPhyG+Thl7227voRUjOgwHbat+8nnN//xf/JXq83Vfjp+8/ab96/voAVZBvLdYoXjCXkpcYiJvbOUtSgwAkP0IZW83+04uCpltdps2hUJwsN+nETBlg64GZopESOaVFNRK8sK8rhMApwSoAU1ALRzNw0fE4sP5dsf2x5NSX600we6ApzqQkd0auM/Vkqw8BYQEc+5EuKpJAOFk0YCIBCiSBVRVwUI+q4Ht8Y5VVGZp7BaeQZQHTIEB0zQtD6y5XFKKbeX3YKLLWekp/4fEJKC5QRSrYkYQ0RmMKqqUi2VnEsyOU0IMYFj38Z1y96jo+q1sAO/7eIqXDUuhhCY2ESlFgAjtefXn4fg1FgK5oytr+s4sbx7OHxfZwWnSMGRcw4AdZ7nnHWPByRrpakV5nlS0FLrNEvTwsVF0zStA2dVh+GoiwN6E2MTudA4joehdg2sLlbtim/f77ICrflo4/37h+OgiOA4pHGut3PoLnxs2EVYsB5VRSNHwKSm7BkYqhkixbZvYoMVDCyXVCYDBGjBr5yxllmBgTtSqnmvv/vyB4QLokvnXdusTIeSZ1DtYuz6bpzyarUJ3h/DJEVzznU/A1XvsQ99CDlNopLYmsAIBCCgouSJHKgjUFg8zAGN44LpQ5Y8T3LpWwSrtYiIAYhImlNwbWxC3LY3T29y3t/flZRHEKqFUsp5tlIAMkiFuvhI4ilBUwMA9j4y+0MWSBA8A4En6FvXRFdqzbVIrW3wlWyzWl1fXt9cX2gt6TikaUJFR77xsaRy2O2RYbXtL7aXhM4KLmrkIlJSIeTALFKW6nY4Hg6HB1XYbi62m0sDHI4TqC09BBWLTehW/eu7r169euGAj7s9IEQf5nn25KTI7u7eqjjnDIy8j469c8hoqrWmWnO7WQ3jkMcZAFDRpKA6Dx6FJTFIaWoAACAASURBVGuMLUd/rrIYwU1jnodpEurbTlhLkpoFBDhCaAISdU1UleN0fHp9FZ17+uRasrt7f1sOAAEWjnA6ZlA8Nd8VQSDlpDOCZyAHc+26dZ1MshJCiK5pIkJ2zktVEUuUwfjsEX9WkjUABkNDPmMt+NFUIQMzexfSPJ8ISkpEIKhLsQLnvrWd5ZYfhRCWzg0gIi3lnsIygnjmTJwjJ58G+YyW/padkSgAY6LFDETO00BmJgZgFQgXJ9ZTZDWChR1gp6E/Yo8ngy39QBb7vW1hVyGQLbj/MrZnORciMkJCtjNBgx5LPtDTuT+yDgwMRIF4KS0JDOgUH21RzOLTUBHpqUxmRiZaxOvNEEEVAnIVkbo4VSE5NTspTNtyXqdVYEHc1MBEVDWXPOfdxC2x74ILQIaadZHyYnMAVUEMtALMkywmpCgAJgJFwEyZdCGvMUPjHDFM0wCqIoAGnk9tKtMCAERGjARALE9eXarufriTh3f7CmQeRBU8QAebTduu3O44HOaUpn0wuLm6uLl+sV1fbPvNRb9d9V3X+DZGtTrsH969e3c85OFBR8xEyXnwAZix6Xi9aZ89X68v120XmcmB9mYENc2NJU0wz/PYXq01UMNN4E6yjeNM3mWt2QpgaKLzockl+EihafRhtztMJAQrv7nyF+3Wk6MKDbhnF0/Y7Xd5MrV5PA7lXR/bT1980sWWgTVpSUqKq2775PLp3+z+uibw0Djz85DnsUjRq+113/bDYX9xdYXev373bn+4u7991zcb750plMJI3gOCYhuoi5xzdaBZchtCMpOS8gxNgO3GXV00fUvmw37YP+yGksp01M2afWwRqBZq2mZ9cZm0THMKMfZ9c5xSyppkZByxa4KjKnlK4GqRshS6pFJBqwITlYWGyR76bfvkyfYw345JFHSC8uauwAhQoCog5lJrKboKKzVJJZPDPGQfPAHWodZSJDotBgncypeaEcn54BtnhIK6yLA67830JHbmTvrkJ2tPAITlLjxxeZa7Vgn4lFCZ8SNqc7IdRVxcqHGxjjCmpbx/7C/SAh8BwskA4gN0hWf8goiJyPRDlPg9ROMj+pWd+J64+BOdUq9c0/L5jxgWnrGtJe4BnlLDhVt/ioOLmKnpecjaAAyRT9bSpy7B4tK6kFD1TNdZiLQfNPU+Dm1L5/ScUS4EKAY0Wq7VCdpZ5pkJyVDtlECqCSqDAQMDA6gZm52MM/TcRgBVFwIZ2CJSKLbYYHyEEz5Cah+BRLCYcuh5lfjRof99zd0/ZGmdGrp/AJP9if/+3kuP6NUfImj/LrYlIT/3fc4DGfDh1/68nOAJyVrydSYipJQKITAvXVEzAA0ADSKBERqoIaLDxbbcCAGWsO3YszYFwpJuEq88rVDZpjKBARBGv2KBkqpmMVVFAWcQMTQ+NC6lsQldHko6FM8ehfKYwspfPbmSosPtqMlq0jpkEERiIEYiBBTMcUOVU7Ntu+tWgmROoWtM4P6He+YYaxwfUsBgAOjk6lXnr3BXdvua/YrKAM73LzbP65Be/+brf/7P/2r/zW3+Hn7z16+JgEeK4r14T06tZqsJpTCaYyOEWk+zPyc1uwTETKioiGikTAhs9UPv7lQrQoL/8r/5z2Y57Ov9UB/8SvfT7VTxblIUCBQixjLKbj9CBnBAAbjlbtVgpDrPV2bb2BPGw+109+ZweA82ExQAck3oVLWUjMxGGLvYruJcxiHtgZU7CL179pPr0Llh2KU6Os8IIc06DFlE+q5tux6Rl5E9VXGOYgzMhFYjQSlT322cc7e39+9uj00ITWxVqRa7ffsQfPA+mCpYFqqeoWlCbJm9PH1xffdwN0/JRR9CmHMZhzzPy+8rhEAueHYkIgAWQ9s0jXNOxEqqLy5evX397v3t3TylUk2rgcDN05vQht3Dw8319f3bu+E4ABMS+8DDYXr+8jr0/rDf39+OUIASkPL6YvPzz39xc/PEoL774Yc3P7x5uL+f51wrwAxgAA1cbdY3l09unjxpV6ubnz9/GHdv33737vbNNB93x2NOEDtSUA5wfbNabxrCwlLbGC+vnjVN9/AwvHl7dzgMKlBrITAmDNE9ubzYXqxKScM8+K75/v1b5ND03Tzl928fpgNs2ugtWhbPzfdf3tLKWVWryj2ECFOBz1/dXLwIx+G+aQORllonqRWgzAUyR+4vu+uL1fXrr96/e/1+tztIBciABOQCIimCkjx/dUMeDsPOoBpZKVkUzJbiDdwGmtb3XRMDiaSSZjVoIoYGEAk85VRCE7suMunnL55EyS+fXF9fXSm4/+9f/qsfbuffvT7uDgAIsetQuIy17ToOnCVlnRFNq6gJG0gCWEbhWmcROXhEiJ42qy42IQ2jlCF6ytN0db159er5T37yfL2xlN/Nx6HmtHg7iRgpmiGYrxkOQzKjrltvt1siYk8hhNdv33z3/XdqGpsQWy+qpRYFbRznhyE68B6224ur6yciuj8O+93+OE6XV9c3N0+01ClNSXexxS5285hQ8CcvP/uLP/+LX//qS0L/7v19EXv64vluf/zi797+5le3r98eieH2Hv69f/r5f/CX/5Q9f/Xt17/78rdmsun7XPP7Nw/TbIy0NMwiB1PUIlChlOpDW1IlZABzDg2laAU09EQB1el6HfbD1EW4vKL12j29uX563W22/uGw/+7Nu0llf9Si0LW9I9rG9qJpn2y6z14++7PP//J//z/+1Vz417/83a+//sqtARwBOOYABTrXXTaXTv10HI67h3HYlyqOnRnUUkHRivlNRKJci/e+6VuoOh3GOufTmqIAjI1vvQ/OOyk1TSmnZAYwKC5+uHha/8wWJfazFzvR4jQDaHjutSwrt0kFXNKVD809AmR3kgnQs/H846un+scsxngSdDxlQMu6K0YoZgt6t6RUxBTCIiWhJWPJEPyF92w5Y9gNCv/D//hfCe3e3H3z+v3rCjxmwNC+vzumkjbri+26z/N42N2jQdfR9dOnx+k4z7MZEGEpRSqEGLu2FYOSpFStRQ+HdBg0K3SbuLq4uLy6frK92r2/r8e5zIWQ2JOYQhbL6tEhOsl23E/jYbp7/7A7AOwA0kd51w1AARCAAM+fb37xZ7949vT55dWVD2Ecxy+/+PLtD+/mNI/jqFoqylTmLKYewMNnP3vK3pvB8XjcPYxpXwBhddlutmsfKJfRoHrPChWgxq4DwMMwqdTtxQadHfaHMsg6XPXx4m//+gs4ICpaxUXnWwWcc8yqVoyEvAe2YkUKxE0Uq7VKE9rNdsvEwzDUOrdNd3l5+fTZ05zL17/7+u3tWw5weX199fQqrmKpeZrGd2+/dQEuLpqf/fw58TxMt2ZFBUuxJjREQcWtV9vQNrmkcThMZU55IsZ+s/6bf3MXPIwjeHbXV8+mQd589QMNQIZyBCzEviHhMiSt4pomRhbJqSQD/ff/xWeF63ic7+/2U8og3LhIROPhuLnuXn1ypZIPh53HPnD7w+s3JSGoU7M8zKvrTQhsIKVMxNJ0rmn85fV2u90isCm+/u7tt1+9SQlaB8RACH3Lfd+yo6YPL1+++PnPf/bk+mqeD7c/vEnjgIDBOUbum/XF+qKJTaqSswzDxMRX2yvPfn+3e/n8RZqmYdjvHx5ynq+vLq9vtqLp669+V6p88uqTWu35sxfPn7+axgSAtRgi5ySppM8+++z27v1u/6CqvgkppzTPx2HY7R+6VX95eWlnrGJ/2G23W1V9//79t999XWu5ubmZ57lpms165TyHGJu4GodyOBz7vgshglFKSdViE8FoTgkM5jnf3d13F9cV7OF4/8vf/vJvfvWrbHp51Xz2k586j7u72yfbm7/4xS/KXP7l//uv370+DFM2g5xrTRWAu/UGlRarPVMxLUVVvTMr9TD/p//Ff1jk+HB8n2WeSur6ddutH+6H9z/sIEN0XRmr1QIMptatuzQmQqoq6822VAshquqcRtUiWQgJkUmsZFm3Wy1Sq0iShT0GoqgnV29aIPWlB0zkmZfQpqpqFUFOsREBCBgDICqcOt6qCAsYVIR08a098QQRwGxRubNTt+AkaE4LKQORyDExLRYWpS4GgQhLJn8SwfpxDWO2CBMvozGw9FqYPXsmMjMTU1HvvYmqKuhCKgDAUzV9gtbUFFTsVFg+WtrjiS32oZm/1ChnvsbJcwPIYMGXl5J1IccB+siLxKHhIuyFjtkFQsDFFVpBxEyqqCoRsiNAUDWBYtfgeg9gFWoTPDHnmupk4KDfxDmnrglX15v1emugx/H+MO7ULHS+7bu7h+NqtfbREysHYLfYvCbP7AnaGKyWzWp1ddE7Z8fh9jgMfe/7VSgJ/XyTEw7z/Pb24fWbMRv4CI5ptemYMHpu2/DJi+fX627TNjdPXgRqp2PZvT/Ox/p//5//1/dvcvkWYALw5++Kzg/0/McB8ImlAy1sX8LVGv77/+6/vblaX1xuQ0DEkst+HO+AsuPysH+7XTfsBAj3GfapmmSzKlqnksekSOHp9csIfni3s2l6sbm6urhcbTb7Ybzd7zMyr+Ks9ZsfvhvT6Ju4Xl141w+H9HB7T/P4/Or51foJqYOCV5t23fu2sSqH/fH2h/evU8kxrOoc23D5yWefNN3qttz/9tsv375/d/vwkIrMaWHN4pxrqTNy7lftAqM452pOP7x+2O1yG+HVq5tPP/1k1XdZ8hGnh+PtcdgTyXq7Go91s75m7m5vD8dxvLl50q7ibnf7ML1RlnnQPEN0q8B9me3Z9U/u3k2//tfffvnLh1q4b55osnE+olODBGxhBf0FXD7pLq67uI5zTilnH0K32uzuxcRbBZjBkmEmE3PEhnCc9kMZ98NOFCCTJsfI3hOISspahJBiExBR0HyM6LgMadwNMTQhhJryOM6BHBpKNSj1pMGFwOhkwmUqakGtFkOYJZCIVJBTtKFFwVTBQFFPsA4Tn5DwE1/qfOMiuDMMjbCwuwztQ/6mqt4H+DF09YfQhgGAO4UdUANVUAUx4JNtEwAs4Nnj536MMTEx4kJa0hOcAdC4AACqy4Gf5v/OAwBLnCEiEBOF3z+eRSLJFrI9kWMHALVmRAI8ufgsfU01RUM9wVAGAE4RlzY7IBjaMuBUai0GBswIAFKXdwb05JxHRKtWco6xO9NHAWwxqpcqVWURXEMwUwFm+tCyOG/6OIj9B4pXH3PE/sjFN3NuGXvExwwZP7Id/MCT+2PbPwao+jgh/8Mn//Tm4KO16FElERGBH1+xUy/k/ITZ4gFw6p/Qh18nAAMTWwbYwQBOBgX6IXoigC2+SYYG7BgLYwHIBt4ccFWBhYZNTN4xOhXNkgArEjnHznvQloxRBCugAFcEA1bUubJQAFdE8pBhVvTeu2hgYgKE3nsQQ6Oa6ziOVXNtRNWIGAKAgoihoedg1UqSaUy48a4hJ1BUwXMFGFNis/V1n6fctyvlCRygACMyedSF+myAiqREKLT4Sj9CgUoEAAwIcpLXM1RQJBAgB8YnxPB0iwb44tdfNVsOW44uShnKZOC4jW6e6jRnRWLjddNlLKkWLeAaRxxrrcejdKxrVh9cE9royogzx8jRDQ/jOO+brm9jQ8xVrGQpu8EwE5GaygDZSyklLJxspTqLSAbwXdeKaC4p77Lz3ju3JE7MtOiHIvB+v2cCk9EA0yTROUdeBc1QRKFCMUUCEJCKVSAh5Jw747bn3cO4mAsuEH/XtsxecSzFSgWoik4cctd2Bqpiucyqjp2L0eWczSg2bYhNVZnTnEtWKuR91zfjMOZaFhs+rVXQAIEZGIxMlmtODTzfPn+yvYHE3/7q2/v7dynP8zSXVKmiVxAFUKOR5lJuj/fHd5OL/ovvvuQW2UHnmmbtPcXd/ng8pG7t113rCXOa2w5NJdXdNIdquUINHa19v3BpGG1xLSFfqk1Zk3EF0qaNHBrnwzQUVAoIHiKJn44yzgcAgEJoZgSOmJYRbl3aIVhKARAxq2oVQCqVuRadXZ08pJKqFDEFTyxBl2WriJpZ27boeJyGagq06BPhwuVHBmBQAGQjB+gwet+26BhC4CqlSlk8mAAFScHMagWrjrD1HrlTJUBH5IELAOUqZICO55JQT/oYUvMirWqMHNBQq0Ada4xAVJsQ2uiCkzLe5WnsYgwsvoWfvnixXW28MM7VSRsB2tATmFappbS+NyPigOieqjlunfOqkFLKOTkfnl0+vei3w3Qc5uMwDSntRAEJUoF1IFC1Auk4jf5A5DSVPE6aYdwd3lUBAGYMvW+8b0PEinmq+/uHv/vNF6+evnh3+xDYOcdWrYvty6cv717Dd98dieDqgm/fvf3i735z8+JZ28SLi4u7u3d3D7fe4WYbci7BsYnWKmLi0KN3YhUVmVFogWYWNhqxIqCRJ/bEHkRKE6BpmJFLhnHIx+CQjDA0Tby/Py5tfRFwGFLCwfK6DcM8fP39b3/6+dNf//Yb43HzBLiN+ykhWts2jWtlFABbr/uG2TN4T7vdrta62IG4QEKmqmDKTOxYRKwK0XmKfyFuAaiJaMV68lZn7wgxj+nMrfqoTPqwRNG54YbwR8jpj3Fz+d+Sk+DH7/T44CwavLDZgIhAz3mOmS70KjwvWWcuGLMjBlvEr9QWb4Raq2MAthBhMFitVsO8gAU++qbIDAhXFyu1ddt2fd/UhqMHAmtiCJF8wcwgUh8VixfKRvSMxqppLhnU+pavN73v+lns66+++83xdx2FVWg23apxMeey2+3SMekkJqAKmjRPkseaE1IxBcCAjoMjD4xSJkEBNlI63OW/++U3P3xzG1zMOa0u2s9++vknL17N43TYH969f/erb345J4AGyIMW+PSnn373/evDYe99eP78yb1/2O+m+ZgIjBmSzk3r2r53rqlWmakurN6zkxkQkyN2wXEMIUgEZ16SkBErCApiNVCjioTAAnxSnBBIwERIFSSl5JwnJodeTG/v7467sUo97PaQQArcyX2akm+9mOQyG7AS1AzzVNuWCJkcIIN31rW9py7NphUOD8eqxXm/Cj7EWGvRAteXHonWm9B1V223ffP6LrYhpYyFqCGKDAK5zhiJogdvk0xaM7XYXgYOPEzH43AsUprQELpaai3Zd7had13biDGRaSbJNudaMzTkyBE4iDHE6JhNlAxL14emi7FtDCGlKc8plSFE8A6QgBQ8Q/RGUKdxfv7iZzE4UgOpzqhvYiAihMAezRoXATSXLIKIC/fCVAwdh649Ho/jdJyGYy4J0NgBgKlVH72PER3laXrz7q0oOA7bi6s6z/M8MrrtZnvY78fjNB4nIg6+6UNPilIsXAXfehQsNQXvCYENy5REqswZK5BgHjMI+NYFjgQIxcSUKkdsHbZOHXsXKKoKOVdr8cxMHL0jxKkYojHyuls9vb4c0nHd923rQTV4/+mnrzab/t3hNpc5lTRMs3fOzIAptn2pBW0ZpjVSUxVVqJLBG3go4xx7f3N9PeXjlCYjjwbO+3bbkrpyX9gh+gCoORdkEBIO1Lm2WjWwnEFEllrCLV6hC2zgUaUKGJjigigswznwGKCWFRfBFMzE7KSDbqoni4ylNf+jKsaWrNzsrB+uBCeB5UfiASEaEaieldDtHHMW/Apg0VZfoCMmhLDUU1D1o7rg47iLP3q8nISq0sJKPFW8KnLiWC3VqfEpti4EgnNpvJyUmS2sq2UXBgeLeswJt1pGf+yDyTyc3ctOAX8ZLiRAIFvMH5axKUBDNVumgwkdMSJ6RlNPImpnOpqCGQI6JAZ27IGZUQnImJwoGhK00RnYbj/sd0d2GFtcr3pgU4RS5GJ70Xa9oeU6lDKrqQE65pRkLtV6ZMB5qnOjwYMKE3lkj+xiy19++WXb9LHtn73c9Ns4ZVn1F69evkSi4XgAkavt5ctnz67WK0nz6y/fvP7u/bvXu+NtkgnSg28mE1esA8eEilXkLKm0LGNgDDFEdqhYVSsz+LGtQP/r//z/bDf+p5998me/+Pzlq5ur6xft6mqq9+N8W0q8vZ/G+WG93qyunq5JUjoyi1oth5rGvVIzr3PT9pvNBYc2sK8pS6qr0E2uPLy/m+8fxIGOWXIadsNwO/rYgwUr0MVWShmHoXObPnbRd8E778Vsdq5xrp3mOs+5ceuu76OPi33988ur5zdX/8v/9j+FeMHcxhDByANmEgMpx1FEnSPXNZum2Xz+HMC6rru83LZtM03jMN7XqACZqAKZiOaa51K8KbInjrv9OOeUq6BzgFnBxCDVUUS1wru774JbPXmxengY377Jx7Rj8NySagU030Lbg48ElKsSZMvzbAZogEpf/vargB1Ug4xWDBJqFUYExmKJWzbD81C1CehCE6kmhtB0DglqrUWkkrKwqfrgzbTWqqJnwi4AqCGdxMg/JFMnGuMjj2hJg5ZhNwBAXmBuwMW29Cx7JyfX0nN2do5TS0OCCBea1VJ8MACc6IUnMpb9eGzwj9OC7KN3XtK5kwfX8qG2YOP2+PcZbTFEwzO3amHlLKLbtf6YPvSY0Z32BXzU7fsosBnCWTXvdDxq+uhFuFBD4ZxeLi2Zjz7ijLItQwsLN4wADJk8nuKu6uKg/tFlwiXykS1EaDUDVAUC1RO/++PT+AC6nJ6yxxmFx0j8R4Chv2/7+OuwE//uQ8PgT0BX//jt8TgX5ayPj+Ef3Nz5LeC0khksreBFnAAAzFROLpynX9ylRIbzV3caXV/eSAEq2Nmud7lTOLilI6ILEwuYEKsqA3twHv1yA4BWAiI1VQXSRWeaiK0akCoSEzv2nhw6sKqqagrFioqCgKRSjnNwTd/GalKHnBw4BxxUREzy0hUSEAWpKmYuxNBtgouuijR9YzPImAFUoYrWUse5hKjsnW+cZoUMwNWG6dihu7zc3N/fPW2vFzhWDcwQkQFAFn02WkzMwZY1nM7JySNUfVaCs5N5gRECunOIWFRwDADhqy9+9+QnF8/X17FtRpmrAAXufMRaSq2sFLz3MdRQU0qz5cDOIYoYiI0Cx1CAihCqw2zg56qk6IGAs8xmLrqGPRaRIsW3GNtoTHPNIaL33jnHRABQipai7Cj64AMiWSlVtZaq59tvoch7z84UkPw45uEw5QRIkFAB59Vqs1mvFsEvZm+Kmv08DaXUPAGxAEnft8E1wlVUUqohUAx+s+nmOc1zNQNmCIG8JxHNOWsRZnbOeYpv3r8dx0TM7ao1BByAixNSJGq65t33b0spJ2onqBp4D977wK6NPdT06dWLTX+havP9NN/td4eH++kOHDCAlNP5LcC3VBvTPB7mUxi5haYLbRtC67p1c3N58+zq5e37h/eHtzKARmQnDM4YzCCXYpwF0AXvG5emRESLb0lOU6pVp3GaZ7FqzjGxZ1ezlrmSsUeyTGnM424ug0AAqwJm6ICAQAQEVAwBnAvsVQSYwKshMlWtmErJM6eUUyoplawC5GAR40SGGJwR+tYZSKpJQMCg6ge5B0Tn2YQFmQBN/y1tb9ZrS3acicWwhszc0xnuULfmKhZVJFtqeegGDBgw/OAXw//QL37zk/1iwHD7pQHDRjesbqktiaJEkV1kqcRi1R3OsIfMXENE+GHlPvcUSanVkJ2oW/fcc3Jn5s6zM1bEF198n1Zk67rYRyYymUSqeubYcexicA5qZTMy9MTRBfLh5s3L48nXXJgJ2aMxIlLPpeQK4omoOXt4IwIH5BwjgxYrpew6v9r47Xrdd5EA04gJ6Gp7fX11ETn88IefqSqDOapGW9dhF6JnUpGS6269NWDnO+c6USAM5BwanebTcTx4x7nmorVqTXmeU1HVNtzFYIdXX2jNuVRiij567xlXUoIbZ8OiRZCRfYyuD+glW51zmets8wFvf++Tz+Yp5bmkrJoluP7Jk4snTwv//MtSYLVxt8fTN9/+SrEOm+HqyZadHPc3IoWQLlfBEOZJczWD0nfOcRitGACyAhVVA9WcEQsoGiCIoRiTWLcJMVDwVKuUXDyl6Akxd5sYQqz56DxJwfGYLFDVnKB0BJveT+P0hz/6r25vX329xmQBgjM1BR+YyGwcR6vZFZVU0zibQBd68FZKmXMWVRe4agWEvuv7IVaRVCsQkCN4sD9GE60ggICtKU+Mnl3GBPiwdtqjjOPRqrUoZrZJvgcK+m8KRv49K6C9XbEAcRlMXGjqrdZqoz+Pq7V2IYQAVqvYOZdDZhVhF5GMPUHVy4sLubmzamzkOaDMSPb06kk3DN6H4DmnKfcRVIKnzCUVn0taYDlCdhA8E4EZeO+d8z4M65WkXGe18TDtT/nmdqwj1DDG7TUGUrDTfnz97e14l2UGK1ArQHPXqgDlwcCXTUkJLCtE4uaYJno6zKf9DLi8ZHPR+dxfXV1aVXD09Pr5R+99Coh30+0xHU3NsetjV/vsvGfn+rXPOeckc5qJQBkAkB3HPrJWREAz530pVUzTmHKqUjRDTpaqFjI2E61iYN751s9UlKauhIyLmDSbGHjHDCRVxzRG6D0zoyupzKd0m28BAYEIWKvoQQ/pCGH58HSXXqRMSQ6HY4ixingCIGjGjlpxnnPOcxUhx5uwiiEAUJrLOM4Xm+3t3SlnCVjV1VXX89NniabbV/dZi4EBCPeOKqiKOTVScLC+HK7fvwTUaZpP44wKPjpV1Cq11uvr3WazAgAVUWkzhrVUgALqKjgAB/0Qu+hdgJxtTllqEWFVK6WmlFV0t10/v77y6K1amrKprFdxu1k79hhtiD2alpxMq3OeERkgho6RAi2c5egDuuCQVbTvu9WwGrrucHsvVaUKIAYfYuxDCFBlu905F7zrcjrcvP7mcDddXz293D4l8zUl9rjuN4f9YR7TfEreB1pTF3o0YvQ+OB99mtKUxhiDgtZcSimlVCLabnYAwEzc8W5zsV1vRFWkEjICRNd59CaGjI6IXCDCU85QKnlk5j4EH4Mi9H10Dochvj68TXvOqgAAIABJREFUAZT2wA7D8Nn3v3ex3spk/RC7IaUye+9SFknFRT4dEgHV5v+uhlbF2Eyb++Wrl6/eee+q34SUkJFL1VRynrMVVdU8Jed9CAFAixTPzAjRxTjE435UM6lF1ZAM0ZpLJBqpgqGJVlNQFV1GP86REZbO/kO0AjBT1YfmudmCdJ9Bp6VMbPmkWmMrNP0tQyRYuAHLbI2eg+N3Krez2SkhNMxMDRHZOyJSValiVhD50XTGeTtfmD0c1hYKgTb9miYzTWgK1hhhetZBpjYBc+bDPoTtt5YagA2ws+bh2LhbC5iFS9VsC+OM4FFvYqFs2QJL2QNYZ9aUhUgBiIGIEIGBCaTUIq24QGhrFjH5EBqbQtGYlgOG4BBdqSWXnLM4BkO/Cl0ITgGsWhc7IqwqZs0hRKxN/ANUVROnCCnZeBJcuWF1sdoO5GrVeRyny6stASALMj8ZtkN/EfyKzMUQ37t4/vTiKQLcv7n727+5O9ycvvrF11//6tuXb27HE0ACz1BmgAyAKIsYE4CcSVgLnoCqahUQVRVqgVQmv4f/481Ptj198N7dz//y9tnz6+//4NnHHzy9frHrOr+TWOphzo5wYFqpHKbTHDx0Q7zcXnq/+vLrV5LVgoUQAjPmmnO2qtvNGq/8XGQ/TwVqcZ1WSeUwjafipOvWHYcXz64lVUYahvjk4nI7DJ5U9JjV0Ierq6exX0vVPlyu+zU5LDaLpC76oR/+y3/236Djqjqd0t3d/ttvXkFNKedpPgYP29WTJ5dXz589u7jaOUfOE5idTsfD6XZOB/MGLnMw1aKQU052GkEhz7Tfl/F0cpGGDfsNKwMReU+ovjnRAYhy7rf84qOL1VqOtzqOKdcstRLD7knYXYbYk0AqIjKllIsZVyk5HadvZOLDsi5ngNSmgQEYXITVxcp3LpWsMwsAgXlPoOi5BzNkU1UBEVSVUqU49D6EmkspuQ0+KSyydYBnaSBAaDNU2EBzfLBLAGjyrSSNbdQYRg1Vad4ghgYID4COnePSwxd4ZjnZmf5z7sSdk7HvZGN/Bw/IzBRkkVN4hCro29Odv7nACy1zI2rasC3+vQUkELUKLokVvg0Ki71gq7MbTcrgEULUJsLP1qjLXURt6ny0vM+H6PywF76NqAJGuuSwiEjnF7NjUmsqZmenuwX1a75MCGgmsEQ6VVO1Nun8mxG3xVs63+PmhauKvz35+JjN9PcAQ78xoADwHTbW3//af8z2mBr2MHgorR/+H9pca2Qsg5TW7uNyUGYCABFbht7hnMy3If3zSMcCBp5/tNQRTbdEABjYU/MYFIBl6lbRK7CSV+/UkYC0EXxTNCEgqALgCJGMACC6CGzokZFAkYkrLB84E6gmAKDFCmTXc+w7N3C3cuCqmRRIwIpO1UBAgGH5z2MYwvpijY6mcbIhzDnVnKBAKicrBg6MrKpAVXDgIwOYFMl5GnzvV+HlN99sn65UFQjalImgmUKbeawq8nZxFWR4sGOBh88YEagttjBGaEptrUUAADUCMiAbj+Xu9v7i2XroA5FTBVQgxSF2ykbVoRADh973fZ81VRCrQgB9R3WSMWWmHMNqvdscb6dpKjACdUTOSqqpFPRmhCIKLGqoRoAKDp4+v9pdbJBhmhmJmQUMDLTmOXZxt9nUmk+nsZRsjW4qiCDekXeh61egWEo5jWAFwENLovpOQvDDukspARgoE3pnvlgFgTnBbPDJJxsFyWU+jac0JSk1Dv3QRUfoXZYqzpFjBBOTilZBRbTWkpLl2zelFNish4idmIoaEFXVItU7nuaCCuiMEEyASWPo1sOqi6H3nU24HnpS2N8cX379So6AAITAwAYGWRsniDw3YqiZiYKpggAnn6XO+wwG3RbWw/bqnQtmPs73p9MeAnSARHG1InYRHAloEc1VgDTXxOwA2bTmnAykKKSUFY1yRmBGPp3mPGWPUQHnQ57vcjkJAIMiVGgGGpJFnIJC89jx0TuHGSdtcvgUNGh2KmAiUnLu+96FALkuEj9q4Gh9sSFPp/k0lYki1WqiVc+9O2Ji59hj16Pv2NiKZNHa9WREhqJWq0LnIHi/Xg2BGKY5EAcVBwhiYnV/D3MpqhDYofNpymhIgRbdSxVEIwdmIBUYlB2tV90QB+cwro6x4+ABagHT6/W6v3r64um77714x7vwzrMX0ziS4BAjG4TA0XuHmHNJczLFKgbK+WT74+lweGNg3jmxmkuKXRQVRXBd3/Ow2Xl2xJ5jjH10N6uVShFVQgBG5yiXeehe3u/vU5m9c41eZImmBCq1pooAHNkjnfb3u/WAgq9e39VSESx4//TZ1YsXl19+dVtqdQxpPnz7bdnl7bNn1y/euaxX/f3+/v7u1gUkBBCxCkjQbxARpmzICl6xVmxh9oEujADALYYTOsfe1Oa51KrRW0mQotBcEDhGIB/yrCnlyFaqjuPc02EzhD7g0NVPPri8fXN5+PlLRbocVgo+jXp/dzPez1RtfH2wolIMGIfVEDtPzEVqyQJBrBo5jL3rVyHnWSrlUpFQy3l1UBBQwEpIuvjUgmETOgHAxho4z/S9XTeXdlhLO+wB2FqKOnzbjP+719rf+aPfWqetdfHPld6ySrYhFz2fjZkJQ1ZjJiQsojDDejPc7VlzgapQq+Tk2a/7/vr6ihyj1uJxZqnzJFoJgdm8R+c8EZuhqmGbLldAxuC7rucy59ubu9uX+/sR5grRwfXleu2GDkM65Pv5cHe/P9zlMgLM5z4COtRl9KZRGsBIBKsI1NSFuKQIhqQAjR5AwA4Ph/mP/vWfAAF4uL7afPD+B9/7fNtto7+gK3cR1uHHP/1TBY3RiUrOxXlY7+LxfqwKyDD0FKMHRGJmNCAgxBBd1Vq1zmkuFWqGsc4ooxYzVZFsVYGcgV+InoTgGAIbg1GbdzBTBUYiFrCSK0l23BFgmUudCwggEZMDaJzmCgVbB9oMgvdAYmLTOKnGkgsYIWHfOal63B/297MJEXtvIIXBOzJP6k2EIaTpze0d1KRtweq76HZQajaBmvV4P8lshmROIVrXOXREHWRIONd5SiIQ2ZlpnnOdauh4vR76LpSSx3E8HY4ELvphtwnVKxi76IIPhLAYtdV8PEyq1k9ZAbbrtXeOnCPEy912MwyOWEop8xyDv7682u62X/3t1957kZqmCbSqCCN65uhDYOe4Q0AwQUJmohDNLIYYvRekEEIpwaRTYe/Z+0Ds2Hzfr/p+BYoxdLfz/s1456CzD7FzvXgDICjoyUf2gQIBoZIHb2zG5sl7Cq4PwUViqpZTSKfDSUSij5vnmxhCqUKE6/W66+I8p2yJMIBz7NmHILV45wnNOQSAUQxFnbfoHAabK/u+Q7fZbleXV9tX+9dTGnOZHbOKXFxcDKHr+9gNfrWNRRN5L0fLGYomANEHZlCDsQgYiEBU8e725vK6j10/j7OCMnkRc0ZsfJomJupC6LvOTEFr1/ellEbirKUYolQhICMjAEZFIDBppoCiBQRNTe1c67xlBzxg90vdZm3s57xpE73CJRtv1Qs2JQ+xpRYzXeJooyTouUmt8qgQXahaQIhExAiNsKENAwMGXHj1D9H3dw93PETNh32sYVYPpA1tSv0PAJbCeQbnAao6TwU+Ouq5yiYEssXhjM4zUGTQ7D9btd5O0wK2Paj7toCNBkaK+tapDBAapwZMzMw5bhpkogq6lAnOMREyEXtCJM9g4MQ0EPjgp3kqRQAVEYrBXIsTZiFiJlJCKqUUzeQoxCgmeS41oXfsjAhczQLZXqd9Lt17m6ebi525fBpvdJ521xTDylFXK2rl4FxwHqsfaLVz2/kmf/v1t3/0r/74r/76JWSA82g+Nl3XsdVjDoEXIojpUpG1Ep8AELQCMRozERBoVUgFJMN40pvDl//6J1+CwB/+weoPfv8Hf/AHv/f5Dz/cbZ/v+nfUr+7uX1ecs+T5lCqbY97sdk+22ylhH3qpUkEDkfMeTaAaGWx8//7z57eH46vb25OMUUNQV/OsJZtljLYdwqjCxn0XhlUXyCvkuebDcWRvu8vrzQWoQcABjUVSslTTnOpUyukPP//MAAvYaZzevLzZ9av98XC/v1d7cnGxffb86W63vrq+Ch1XyeN82u/3h/Gu6tz37ogH9pUVtJhCSUXE5ulU5pFubk+vXufYwfsfPrvoHCr0YU0xgnoVULUy1+N8mLK4NV8N3eYZ13mLwrmkIlO/hn7tAcuUCjIROUTIWebDmKcJKoAAKZq0Wf5WOQIICEObva1awYGERkU8W+QBppTBAAg8O0WotZpBc1+VKtrKykWSEQCQFlD6rA0Fi6XEQtQCRAJsbWMkNUNCahV8Q6OQwRpp6O9Kqd4+rPAAYjfkZnmWFy7PbwSOxzDW8jJdIJ8zpwYJUJrg3cLlfBtg7IywIAJgQ7CWvPHcAX3LFoEGjjSNLDuPjbXEAttdokdNTUJrToaG3IJQe3GblYZFJex86Y9uwW+CJOdeA56jrVmTmlygwha41AxFCQGM1axpvrcOgIEJwPn5Xa7vOyd8+MoWou3vjM//0O2hD/EfReD6x2y6GJLYYyTrH7gtQ4+PtPrPzZDz21huIpyRe0J6AFnrI3zy/OWC8htJa2IoaG5Dg6amhsCk6Bw6lXbFqCRUq1ZfgJWJgIEqmIigVRVURm8ICNUUVVQoeFRkduSrAkCF9rxJrbWUEhIghrXHzqY811LJg4uoCLUaMLT2ZsViCKKCYiF4Z86S5b6oqdYKBjBA6GKtkk6TdhZ8jwZmRRGII5gckh2PowmDA3SgYpWbe+fCkDbTNioI7eFYEpJHcK0t6msAgAqIZNKoXI3XhudoA/t9vr85wjAoaxWwXFApuM45L1lLSqmad6Hr+8F3p/k0zgkYOu9ylQpaETarbugjqNvH4/3Nvp5Uk0IAQkiWTKBlCKImGVp8vHxyEfuYylSlImHf96ZUqk3zxAW2mxWzno7GLddrNrJgTOYdYRjG06iiMQJ1GEIPAPOcp3m8vbVpnHNRRIu+986HjoE5ZwEGIVit17VmQC0lq2YAUclm4ANQs94DAyuAiKTOA7um+wAqhQMAA0eqJqdxPI1j8BGBTtMYgwdcAn0VU4Ou97v1dj2sHDNg99F/8r2/+OOf/OTPv8AZutUQHOecGDyoqthCZCCoKg9gPbZpW1YdNQ7ReZjLPN/aVz//FYp78u6TD997/9vbX9xNU+xss+I4uKqiqCJlSmWcshh6DrXmogZSSk3OkWfnghOoTORD1w3D4TbnMXkjmXne53JfQTD2XbUCaoastZZZuQP2EDo2I6liCHPKYqbIQKgZpEqpkiTt4bgbrogRFCqKERKTD9xvO/Z0mO+T1m6INVEp56iIgEzOexdo2EWBLLWISSBFAmJgIvboFcgZM/jAPTmsrveei6Bqnua55mmCVEAqxCGEfvAQTmVMdbbWkFJAhsgQPaEpVQusqx4vNnHV+5RPUMYyHUF1tbr63ouPPvnws48++GSIgyRl8tRz9OEaryOEJrFadDrW09FO05TG0/F2f/z1N69+9sUX//7nv7g/HM0gRPIBn7zzdL0eVpvVOy/e6dYdczZS59324uJq13/20X8ukgGg1jJOx1Ln6rPtYnS7VGcGmEs6nk7TaUbAGHzn1p4tENVSX/761x9/+MnVZj0dp3muJmJYr57sPv+9703zj1/ezLGDalrKOJ7y8WjX11cXV6vYo2P95f2rbYcxBufTOMK3b0ZQ8ASlglGSZomKwMiM2MyTwTEyEqMamlHJdZ5MFFQ8mEOwecrmYLvZVcMTjkPXd31ns1QYT+O0vx9x49+8+psnF8On7199+zIeZ67Eai6XabodrQADjFMCAVSwggizVFGrgBZWlFWBgQP6gIgVnTqPQqCEpgBii/QGGRIsKgGgVQ1rm/lYiqW3gdIe5QXL95a0xR4692rgaNn/Yfs7VvPHbHZAoEcWxe2nby/hrYtX6/Esg4MIQNTcNn2acq3FIAsCzBCCl5rRBE1MaiSMgQkqaEEVMHVYA2qVNI8nGzxo9YzkfFN+ykXU0AdvSlOSUiYTmE/T4XAsFZhh46CLwy5ut36T7ufbN/f398dxKkUBKqJ4M2pwlVWDrISuNSEZCJBMrZDWVKsJNNCKiVqDxdRAUZa7zIb7V6e/+Pqv//3Pvvz+73/y+T/5/sVmN1t678m7h/n+MB2yJECoYt7TdrfKeQ592GwGH3y3isamzcLEs/OeSwaEbh3dJNkqKSEbBGAgyFRDceisleBNy8YReTJn0BJSMHRUUZGUPYlJtaLqQbEWAQNkRkHJsuSbyEaL3DSYOSJgJgYRCSHgCADIxMF3om6ajnMqwQ0iJFUdF6bArl/1buhVqj6/fPeyVx9Xfb86neb9cT8djtUKACqbXyGtcU4ZAHbXm+31SqHe3N3d/fr0Trc1k+gByVKay6xAMGz61XpFRKWImUlRZAghbHcrWYEJsfNStZSccgWsKaXjydTAMPdDWvXDdrPxDg/3d29evbSL3ZPrq6vrbUpdzUl0TjNfbjdmQAhaq0kBUGIXfOOOBkYHCmKiougsxsDEq6737GoqABB9IACVbKZVLGcppaoSk0P0lxdPymj7+xOb8xj7YfDYT6f5tB/XQy/9BVQ2s447j4GdY3AiQkLrYQ2D5VqO856J53EygM16fXXxpB86qVprdexAQYqBcvDdMKxD7GL0NRfnudZUSlItbBCYVl23GoYc7fXNtIpdHGLSGAL7QLPOxAgANefj/nC0/atXr/bjXYVqVKqCkICDXNJb2g5C4y3holqOYMAE0TmHzIYhxthtSsXS0RBrz0eMEH3wwYlWszp0oZQ4TdM0lWqVWm+fkAmasLhq1aqggEiqdZlUeBTZFpbQmRL1aCTEHsKQLZDUUpctVWnDpMRMzNSaxE1TkjI7KzEvmuV6BvqtZXrYXH2RFvQKgKiN/+F5BONs1vW7qoul0H1c5yylyAMnohWOZzuOxqSwB5rIuXRZMLwGay2WOOeGLy5HWoqNM3kBzxxdXArE9hcuOljW5iPQDBCo0SDUzCESGqGAadvAPBIyKFlLEcERBHWBDUS1gjgkZe+cdyvogIAdTlMqCUIP6CAG3u6GzXYVIldRyZmACcyRCwFDB1NOuSTJpfedMtQC6VQn1e12TdiLkYBDEBf7q+uLb3/55t3n8eJi3cUt22DZX23f/fjdT2++3f/sL372v/zP/+vhTQXIcYaSQZsVNXhQAkUwZGYiMgMRAQNGz0y6zEQRkSERIJoqIrgQyRmJ5FxqAmJw3F33PE6nv/zT0xc//Xe/+OLNfz2Wz3/48e9/+tkHV89C99X9/leked1dgCXLWCf1rB+9+LAq1VlR1DuOnXPeViGCKjNt/VA7vZG76fZ0nKbD3X6aJiAs3XTy4D//uHMuum6IgRBnmXKZDqfD4Xjqeh8GZecjdx3EonkuiVA9w5zLcX+see6H1XrYPR12Vx9vPnzxXlEpoogWu8hEYx1zno+HQyrTzf72cLif84gI6213e3hFBKZWBEjVEEXscCh3d+X+vt4dIBZ4NhNaRFsFN3i3looVDD3d3/1aQE91urvTPIcY6XJ9fX15aaBTOopOSJqzsKcQokGkkkqeTgc57RUESMnEQAwqntW3ARS0gFYBNi0iIrkoCBRKpNDGKdRAAAI7F0M1BRURqW20ibFRIlpIIAQkooXcA+exKbAz+6TxNpGaZDqbAD08WwBkDV4/I8dwlkvX34hXZ87lQ0PxLA51RhVQRB4rKy37PB5bO8eRJSEzoAcOGT6iy5zTwBbZiOjtFOH5cgAXn+lz7CBsStNvIxLCOUswPBtNwNuQioYN1lvIJHau2psMIDRUEJZ5Z9C3EE8DzJt+n1pD1c6xDVUNQExb89MMYfGRULPFUfx8P5fq/4GT+p0+bqOM/QasZG+5ad+Bn9rXj/f+Tvb7d2+/8ZL/4P7/mO0Ba/qPQq/gYYTwnJ2fP0yL3q1Ba5vYgmYyIz1k+2YK0tocD1Q7QmRkQjJQOzuzgCjaYiQMZuaMTHKqkKHkgjNQjzCYRXQdUST2Dhq7RosUUyUgM68ukIuMjoaNM0P2HIcuz1lQoYIpVLaEBWTqhn5zua4qPvljOlZVYEOE5htCgZSNAhlbrbVmYSQPLsbgngQHXnJF5H7dh42bYRzVqRN2/k26A4HOu34ViXC3g1QrKoQIiDHtSzUlJjQEI2MjJmACdsCIWmFRrXz4pYEZtMiy/OYQtFiDAI1MWQEMGJi4TjIfszuBuRkVovelKKDWko77aTwWreAZNptdt+lUFaqggTozAHNOkXNVRN1crGLsunV38+1dmqsPago5m3NoDOiQArqeKKJxmdNYLE/zaRyPRByHFRLhlIh6Yix1NtNhcGpI3MTeFBHF0pzp6uLF/f4gZsN6jYAi6pyLgPeHk+JBBKBpMXPiAF3kIKHWRKzsYFj58ZS84HoVht5VK1UVQJgdswMQM2BG57hWq1UAIAQXuxjD4DilAsFHUZ3m2bJZVADYT/uuBl5Bi9GIwARPLi836x0Dnm5OVvX/+h/+Xfeee3J5MR/S8W7s/WoIqymdqqAZOQTjRoBvNdHSxEAkAk9GNiKv/Cq4KY93X5/u3vzk3Q+f/eg/+/yT7724m75M9T7pYcpZDFVEzMaxzlmBnXcx5VTz3DQxNhuPjhGUjIE0hLDqek/H6QRzmmzCMhkgI/qahHoGEmhCGRUcw2obh3UvVfeHk+sxSybilEWqYdVSDQyS5Hq4ub58Ymig0Ab81v3gV6FSyaoWJXRRWUyU4GyBZ4hE7JyPLkvONdU0E1hcgY/MgVQye3RNr1CkluSjc+w6YnYO1KZput3n55fwck9p1EC46vpVMJ/5VMZSEyENnQsOQPNm6HpPHTGBeaA+5i7Yjz76EQGtV9vd9nLVb55dvNN3u/2bcaqnwN23X//6q7/52//nT/7s3/zff3Z4A5AAMsAI8ApAASIAAVwCbAEQoAB4iBeADHMB+Mt7yI2buYxCt+QeOoAB4Nfg3oN//sOPfvjDz97/6P2PPv7g6mK4WH+EJAr1dNi/uX39yl5WXx1TjBR8MRtzPuR0PB3vTse766tnH7x4dvPmOB5rRtus+t//0e91Hf3L//OPnAMBiD2S1zTt7+6K4bbvuqunm3/6g88O96eXL9/c3xyNKHTrlORXv3o5zdXQqrYMvdkmgSCAEVQxY5A2NOBBQSoik6kzJec4lQRIF7vd69t9iNR1PQiIWuwGIDlNJTD89V/9+fc//d6LZ9t/+vmPfvE3b776+lBTnu5nZ67UigiDJ2TT4kuGdEhpShhgvem219v9eGtoXd+FjkWzyOx84O0qzfkkYtUwIFSgVlKzwwpqUovkmhubteXWLUgCwIP31OPVaqly2pr1KG163JQ67/67l8zlGE3d+LzOte8/zMu/hbbOpDZEQijnHiGYVh84pSSQVhuY17DiIeeTZ+0C+o6d34b1ppbT7euZmLvAwSNBMhmn8YZgLSKOKHiHTDkXJI0cQnTTWA+HQ06ChlYFVLcDAAfDyNoHjG9+dTPdTYfb45zOFVslEwRpJl269O2kSTgzoDI2kWNX84yIxNw0YGqtVSrCQu0AMkSwYmLWxTAf05/8ix//yf/24+EH8KM/+Cef/uDDEF3XdcfxcJwPoAKMEEk0huCMoEpl7o2sVqlWHHhDddE5R92wTmEaIUM2Zut6JsepZgqtjlAzJefAGwTE6AxFVCsqkPoQSsoC4GMI5HKqqUyQUEoFQgaqIihtZAIBEduYEJKSpDnFFTUcYrtdT2UVo/Ped3E4niRVPc31VE+SQUTuu+nqqmy2Q+xCDMM4z+u+mzRLBaqIBWrOzjsf3OkwIsAHn7x45513dle72/3dl3/7i2O+8dE9/+Rivd68/Orbrusc2zymMqrv4PLi8vmzp6tVdxqPdc6O2Ad/92Y83I6HIwSGPq4Mxv3t9L3f++jNzet5PqmBFlivYbdbOXbH/cEhffDeO2Ryf/v6eHzTR9wOITgjhZrn23H89NPP5ymbFVMVMNDqgUiIjT1y4OZczGbofIzdsIr9erUtuU77iZRW3ZpXVEsapyMZMXhjsJpRfeR+c30ZYL3v95vV9nLzJIbO4VjGOh7n3bDdDNvO97VWH3wXOvZsptM4CugQBudpTrNIkb5G3wPAetjuNhc++JrqqY5pzrXUac4xhD5u1sN1jF2IPo9j0TQd9i9ffTPPp9NhbyA1T2ka5lQuLt7brXfg7Hh3d3fz6uZ0myT54Jg5xPDLX/6ii/H16zfjeKfolWxKmRz2F0Erp0lAEaB5i7bPPojVprn05PJ6t92is77rYtcrhrkkMtf7ToLO0yhaTIotglG06oOp3twcXMBqRo6QwDOzQxAoOUs1B847nmqi1l+XB+RlGXaxx/Z83ylFGkOxSSTD0lZqKsvtCE0DfpEvV3T8gMUjmRmCATk0ezRybQ6pWbsvyjitJmwqNrVmO8vYLGrKv7XhQwP7YaCDyPCtnSKc3w7iuR9gj/5/jun2QNwgBFAkRFosOcwWz/mHvoapPQz+nEtiNDB4MBZsfy8EMDMDIwBVJILGODlXJApqULIAEJEnDGiAPjjfB9/RnGUqCUsClGr9xg+hC4DmHHMEQ4i99yHELm53a++xlpLmnEqWMnZDP3QduQo2m9pmM1y884whHPczCPdepdac06uXh9N84L4iH9EBMby4uDgexv3Nl5erZx+///kHL74/H/R//O//p//9X/xbeAVQoN8izA7RR+8l11wEDMh5x8HImBlRSylWCzRTOnRERqCITJ6YSbSWmkWABJEdAKmVi6dPj/eH/U1xgz15+mx3vZrH8d/++Jd/9stfUoD/7r/9L/75P/tPv/fp+9vNC6uebVvLUWSyZJOOw/YanDNHzrRj9lLYtHNDZF8BEHDXrT58+gITv76ysgQjAAAgAElEQVS91yN4x+xxvVmHDi6GntbbPl54Ws/z+ObNm/v97d3hJZH2m+7V7a0oPLl++s6TpyBqZiEQcRTxaP7uzWtNc5kmqXB/f7y9va9FumGzu9htLtbDetCa7u9u7o+3orlYAixEmkqqUz0di+swzTgn8I68Yx/WcRAej8OWfCeu89urTddRGstYSLWcplKyOE/b3XPD2q3mMJxub6ec8n3+dd1PT64vIus4J0BwAZEZicuoh9v5cJ9K0mC+iGAmzQJyzm3wXI4bkDECdBzDuqtSa64EhGoiQMilyDRPyAwMUgXMVKUKhBgIWLQs6kxv2ThnNAnQUAAQqBFNUbGZ4nAjGDGi2IIWLyQgNDPDphPEjUDaGEgtS2gywmcuqC0YE+KjUyIhopZ6xrJwgeYBG76zvPuG1ehC63h8hCbdDm9BKgAEdu3fDQQ/q3fhQ3xoYmPcLspkcb1uiBRyI0WpgQIhoL6Nti3UAQCAZCFc3OsQoKWIi0/io6gFdLZtfQz0oKFr/VlUM9SG10OzqneBAUFFARXBTFroXJq6RmZqKA1c09+ZvyKcJYbO28Nc+MOV/E4M6++Bon57rvP/b9zq8XnhEfnrH745RDiDmM1W1tqvSXUBctsRmRma2zd9525ak3miBa8lImJGBLAzIQCJeBn3YCNDRSIkglwREQi0PSELBQkdOkY2FFBEISimVU0rENRewMBFMAEwcOzBI9UqogqghkigJNxB7YB30XuERJrgeBpTrsDADkDABxc673o3dB16Ssd8PO0DRyzoOIToqqM0zWOx6WSjHE8yAQDcARA4hKELXUdUdRgGPQoSUXRaALhZHACd19TFDBQYkYHKGWVeWlVm0IQA7DxRjYZKZgpM0AKLAQgoGbWhWhQQgui9p8AdmWDOaRpLzUAGSYBOI0dmoi50RVLNJfoBCURsmqekxRJgBd/z1YvtPM33+2OdAQLUZuhLsOq430TuSMDf7u/7waeUc5a+d0TYSHWx80TNYoG972stqlUXzLOaakppeP4xEdSaCRlQ55S8BCb2HrrOu9AoDIgAhAWpolV26j2xUx+QZkBU54mIRDDXWlSZiJmYSETeMugVRCH4JiXekS8REclSrda4HkxgCIpzzpsh1iI518AQGVar1XpY10nuXt+lU+Z3IE/19e2dNx9dTPNc5+I7DyiA0GRpxBQI2lTyOW1EQwu+E6lpTOwACZlZsty/PL759ob85ur6SQZ3f9L76S4XKRVUMYsJABkUlSIyTlISeAd9V3MpqppzAeD1CqVKSbUWsASQrCnlmKDkChGaRAwSGIMPfhhW7NyYTyknC55dcN7lWhqpGMjIIVSsVfrBh47BA3Tw7Ol1CFHZkk7VSuwDBswlAQm5ZQSbANkBkhraOE5zTVKg97AovRrUWswqGGgFU1MpJhVUvSPTZf0suXz6yWf6q9fTN3eqVfOoAmB13XVVmFG26+hIUaj36El2g2e03vvV0HUuvnf93ibunj179/LiiRS4e3N8+c39Fz//6mc//WI8psNtqkX/9ouv4Q1cW2fO0IF1WjZ1TtZ1YS4FHXnnFahAVa35Rt2AHbNzvqKIKKEaqBAgYTWDCWAP3MEw+q+/OB5e//zP/82X24vV9mr15PnFex+8+9HH7z179v3L3UcfvZgOh/uSTynf53KniiAl68lTPO1PVxu53mx1snq6R8RJynbof/jZp3/2Z39UBdA5cmZkRFUkzdMRSTy7169/Hf3wySfvdz9YG/CrV/f3h5Gdn+aSUn5zf3NKqgVEoQnPAqlDR8TImErxjMxATN675iPe2jNE5JgZKcauZD2NSZP2nn0IRq6o3b55eX95/fT59v133x1H/ulffV1Sn04aKNQkRcBFZ6KaQIsCADIF52LXhT5cdBfQBKHAcsql1uijDx0yl5LTXJgZ2AIH550jNgCsBR50Ouys6fKdVW5Zb/CBVvU4oVl2wXMh+N02weO1fKkSHyFfD6nS8mdp3527XrakYHjeZ9GGBGhakKZEwawSaN/D0ydgYETgnPYduUh96CiG2/vDOM7IZH2Hq4Ba1DIh1FwAAYnRFM20VlP1PSNaKXkcJ1NeDSsfwbtiY8oVGTmADxR++uUrziAZyBDZigIIEICqgBkRExMQSBYTRRBVbJQHVfWRAZ1zjsm1risbKdam5KoqaISIUnVMMwDACvxANtGf/vFfzNN8+Xy7vV77NZuIiohIziUE55hfvnpDQR1jt+6YaJyyYZOMYec4OFTHTFi0VCshoFaVaqAirAReyVwgYBBWYLSWRsBZDpUbLCcckcXKVKAgIRMhFCQg5x0YoaE1OKwJTbDWWrw6di5E9t6thiF2HplUwcDmVI8HmKZWTkCpE7NTxa7T2Ol4nEzs9au74/F4tXsagq+pIEHsggt8ezPd3d4S41ROSRJ5ZeQMOZ/ycTpE3xuClCQViGC7WT25vry4vDDNUrOhMbFj7ryvGVkzOXDOIdLQW9etHN3XCiIQPQ/dMMQVkR6Od31wiPb0+mq7CmkeHWMtqYsxroa22AUfUNHUqZRqZoXBzKpCNUBwznsOLoRcK5vr0PWh713U2bRYcHHVD967lCcA8oRdWBlIsjlyH/zQhyH3xuqvLp9s1xtTSpAdesaiCsGFEKM6QUbPgZnMNGNRKTVVEKcFAof1sNptLxFgt7lY9SsEUpxA0SrWrFahW6/6buhC59lH9qPqNI6Hw5EIh/UAUKtmHx15tKTrVd/38TAe3rx689Wvvvrm7uWYRkVbr1dPnl6D2sV264PrhijA+1NxHpmd81GE0nwCdrhY3S2hhBEMBAhiDIyEaH3sfYivX+/3h1Qyofl5KtPdHgmZ0TmsKIQXzvngFAxiCJITIRE3QVc0NUYGbGvLOVbZmTr0EMceSJ9gb8fr3rJQz317WmacbUFy7MzDasR+pDOa/2j4BBCbyastTXw8Az0LHm/4EOseOtmNM0BEaAD8GxXGuUz9LiXgLEvy292EZaQQl5HG70TWRaHmodLFh6Od35w2lzMAaFHlfKrzhdCZPftoW0oZfKig290yM0RqMpdgrTFPBmzISI4wEEVwgS1pLdVa0U5T13vnWWplR5v1RqXGPjofDHme5sM+p3kquajoeuMceDYiFYeEApEiGE5T2t8fZTatWHOtNZNXIzcQ+9gDiWf8xc/unuy6j9773gcvPl3Hq3/1L//ky5/++ou/+Br2sNsO5WQ0kxarBiyA5hyQmrEyESlUbDojIEytSGYVFVEzJTZGhwTQ9LhUxRQERRWADuPkV71bdyr19nD6Zv+6j3z1dJfyRC5/++39j3/yRTX9/seX6+4iSDrlQmhM5Dimwxz7VfAuIHsTxIqAssioVDXsqesunq/C5d396WJ1eZqPvsPdZd+vfBdD8EPAWBXGcXxzc3OaDs6FOLgu+lRyKRXBSTUydURoRgDRedTu68NXMfg+do7dqot1GKYpN2RwPnGRpFDTPJYyA5lnRnZVUx7nw3iYRggAJZtUKBWYg5jmXMZ5FgXfOx+h6pRTMO3v79M0pv0xV6mhC9MkApkDxGH1NMbTsdzd3s9yUh7C4MiIEDBjrVazTGOZj3k+KqiL2IPmxpRU1YUHiYCGYgoGWs0Rs3GeUqm5poJAIgaKBvTs+ikCzjWLiC46AKCg0pZ/au0rAIZ2MENGRWsm4tiAkiXvAVJAAgJAtaZa0EDf5nSgjyZ4oTkWLiROIzNdnlB6iAMEdB51IyCgt5NZ1nCYFnIWXtKSwGGTYzM7EzMXz7PGDG0/ffSEL4Lx+F1vnt8IRw/BBhcMS1WXEcSGXtmCehkiQBsSJFrO1QhMBgaiRq2lsbCh2kW268G3uSKd3fqW6wQE0pYq4sMJFdAWiSriNvKGhqCqRrKkmtSiETbaLOgDWIYA1nS83r7zB82Mt8ysx1/j47ux3LrfUrl6HJaZ+WEHOy8EvxW6/7/fHs77+BS/fZG/8+yOuV3l2/eJ2FhX0H67Dd5ywQGCve1SGxgAAxIRkcFiSghM6AgBwRSBtImQ1eXWL590NVWJMVJjsrOICVTAbGKKIlDA2BDREZtZtUbVb36TQIHqXIDReeccZE+MnpAUVEoVsNrZfT3IrNthW0CAOfieq8QumOkubgws9KFCqVDzKc3HSaoUKaAoasPQo9c8J7LKyobU+U5RVQuSDSteDYxUtGV2AcVX9JA1gUNAVNVaSoP1WB0QgBiiKRjy8qkU1TazaWDIgI0+8/+y9ibNsmXZmdBqdnMad7/da6PNyJSUqTKlUGclGivAwODnMGJA/YgyqykDmDKqQWEMoAArKCSZSVAlRCjVREamMiPiRbzmdt6dZu+91mKwj9/3IpUqyoAzePau33uPH/frZzXf+tb3LaxpqCwKREJCIwAyNavb+M45ZB87ErC+X6Wx7O72uUDTOASc5zymfIYQQmBPc6ZSooveBCPHddOT0T7v98ddSdJ3bbsJsb3qYr8+W83zPIxD0cQt+c4p6yzzNB6RAlRNEuKU8jTMKtp20YeAiHVej45StpJmYmza0MRI5Ifx3gdooiOEEGPTBBUzlKCgJkTsPDBhaEhKmafkPTRNExsPYPM0pDSkPFZX42oCzYhm5p2PgYZhnOdZRJY+V0HFcspmBy0J0A3jdDjMSkoNqyoThcCqEhvPDqLHzsU+tkxMgON2evXi2kbSCVjJIYMiKHgOBialSquClDprWIwSkE45oIZd1djELDZMR/YcVkFMj+Pw5c9e7Mfuh2cfKoBnT+iZkciropqoKZIzM+dc8A61dB374EVUTVIBJ2amN9c3d9ubNkIRqIr4CgWQuXXkMpAgc3Teda5bhdDEVMp+OApAzuYJUioilbRlACpmWiQl4IA+UuiwWTUXj8+HwyCQBYQchjYexqOikGcQQDP27JAdOSYwzWbmyMUofeu7vvEcPAP7MGkBliLABAzmiBjNO3847Exhc7YRih/92odXP3u1/uzLL795eRj2MmNWQ++YqYglm1zUi3V3sY5s8t2PPnJIZ+v+4nzduNV7Z7+x387bb45f/9XPdrfj66/2t9d3n//sJy/+5vV2u00CZQAo4NEpACODgRpJIStCPkKykoGMjZZhJKLmgwgrZOAQvOOSctZMDonBEzvv2LvtuE/qX+x3ZboBBVjB5aZ79uTx02evP/n47sMPP8Ao73306L33PnRep3Q/jffI0zxv37x54SiXUdIx+96vmvZAe5VieQDC9x9f/YPf+f3Xt9c3u+shjRR8s+pcDOgpaRnHw3Sd1+twdnb+7Pnjtj/z8fXVrM/GPM95mOac8jSmYT/eX2+Hw3QcxkmmysliZZChJMDIRBCC2x+3Ty2YYfDBGDWXzXoFMB12+/12TAPYOjZNIB+MlLi7ub0lv2n7x5988skf/uGnh3GCBGoIQqwsM5VZNSsYASEqoFCay/3t7vL5xkhF8jiNJefdQTarWdEZAEfnzRAZQNkzLXsNAoTAiAQ222JIVbsW+hYkhbZM8NTUql0tAJyI3fa2AT2NNE89WNWGhGqNVcuft/nuW/Mb1Dr212WgaFbdOZeTLdZdpxJCVU0QhNjY8fn52W/99geHsj0/3wxDmyVkMyVMaToOx+3+6DwEPgsBTROArlbdKNEADUtOJYuknBRgotF70FqHInJwpMYszgVVr4WmKU/jNu+BGCM6hWoeKgxEjmp3ttzrqoCKvHRneJozqSIYpFIQCzOzY4wswjklUSUCIgQDh87IBA1M86B5UkD4809/8v711dP3H7ebSMRn8VJUXu2/EcD1qr++S2drGMKsKORpniZiDyR9c1ahvRicdj4bU9H1WTNAamZKg5oDBJNUChaOnh0bgpoYgfPBR1aRxgfJpUjuug7BxmkGA/ZkAgZKdWWKCABKFlCtSrUK0HfBtWWz6S6vGjPpuhbYpjnN01zE5VKyQghgBYKLq3VDzOOYpik75+fD6JzLkx7vYbp/s1o3CtavWyTanK3TKOM8X1+/Vpqpceyd6WyIzGSAORcUSNOcVddn7tHVZd93YDIej3lOzJST5GSlQJ4LM0iG4Th2XXd+eebZBd9E1woWQpSEeRZWaUJcrdYgBipSZB5TGefG+VXbxhDR0HGQVEDq8E8JapFhDB4EAesuVBBJAb0jT4I266xpPIzzMHVt78CREAo33LYxtKFVFQ4+utj4LnJz1vO6gWfPnreh3e8PpnC2Oeu6Dg0Ynfd+6U/QGMhQHTkpkuY0T6lIMWf9avXs0dMi5fzsfLPeTFMqszgK6J0WcE243Dw6W52b0s31NSF88/obg+w8nZ2fhdbPZ91ufwdkU5mHdGTH3ntAmKbpeDze3tzshvus5erqkVp6/+kH3rmubx4/frI7DmbDeuPTBHkuoghScLGKXjgANasnMWB4//33mtaxh6YLMbZffPEqj3J9tysTADiYCjEAQQiUUNum5eJU4NHj865v9eZunhNVbqChIweOUc2KySJ5cgpX9oAg6WlIrBXEUTW1E6cCkRhwkSN9h2wFBItt1hL56slUzUAXAa0T70Gq1zqKGZkaWEYlQl7ahlNvplqF19Gg0qDQwOiXNT81TMED8ET0bt9lVvvFdxqHhzi9/MKpWVra1hNjCsB00e+qTfnDtk5toet8fNlDB0AARYJFUGyJYGp2wr8WAKs+rUhlowEikmNkMqeKoiwc2DVMDgtmVRIpWttvhVysSAa0/bALOazXK+bI3iHyNKXtbjeOMyg03rWhx0K7633W3G78kw82eRIMNg5JEqjYdrdNVSEjw+rMNdx5ABRE5JTS997/4abtNs3V7nV5ef3NH/x3f/r1F1sQaCGUA1FxkkyKIpuBIpFnNjIRmaeZPVV6GpGagxNoyQBYpTNqSW2owMiOpWpkIGDwMh8MInsyBkd03p77ljKmBOrU/9mPfvzjn315t79H+NXvvnfx/UfPpaQyAIgGCNM4zTKrF/DOBddwCC2zOq0wDSChmuIqrOPl2aa/SjpyKLFR4jxoKlKO03YY9XCYkFxsWsBMhPOcuq6XdBj2R+nXTRsdQ5aZwfWhJYCLs8vz1aZpWjMm8oSu7USRDLRovr/ZsWfnuYUmyTTnVDSVknLO8yyS2HxgEMaUJmPni0CMxA4I4OKq95Ez7K9voPPr168O93fTcFBi74KUR9D0LhLPk+ZS1mfrKoAw5tG3vQsYfRxlHsdRkxt3lkbVBJoBrbA6VQGlqpdekY26B9uwQwEolseSZVY0EFBVUAYj0eLJd+0Kp2FIg6kiAyJqtpQTMbroDE3SSQNbwHRRLbEswAh1nQKXQTsyImNVvMG3fHMEBMPFhKF65jjn4EFoadEtqojT6W5HRHqLWdfwplrl9E5USDKsbsvv4Oon+NvgZFX9Npjgw829HA/F2Nvb+V2smxbwpdJSmZ0piJXqSwFLHAJyDhlUq/mSMzDnHCGXlJbLVQM+GWLQYsSoD8uZFQir0e0E+uA71yxLfDFa1qDJwESUHFH1GUSstC8iUhY4IUvMpAKAVQgLgBBET2/uW6SswsJv+aynsH9ioi0X86CJzszLNOKXMa0eHsTT+X/hcVie5dvD4P9vx7uXge/MP34pdvbwrV94xCGSqlZTDjyx++hEs3ogZzESIhYSk2Vp3BRc44kZTn6TlQGgUDsEInJaspQq3X7CZWBpTFYXayAiZ1LnIaKWTIuCihUwrD5QKIuLaN0iActWJlEEYiAm9By71kx9G4vKfntH0U8uG+QjYB5Knmcg9MG3Xdu1bUl5s1nleXbBH6e83+6mnOYk7LDpWufcPOViRVHBm7KKQVFFh84zkOQijpEdGBYBRVbXxnDm5lFU0jwmLQkQDZUQCU1VqSg6Q7U8J3R0mt0vuCBbZRJV2U0wXFBuqe8SmJiCaskGBETVgpmYUUpCBec4Z4QE2BApacnQQmwa55kdxLh23r18eYPKyGlSH7xv2oi2ORwOSWdEDKsY1hzWriXfTHw47JKWYklFVEvbR3ZMTMwVXyMzHIbUtsFEpnkSLW0T1UrJMygQA6ERSQj+61dfl2wYAFDBSRsbZk5pTjIBaGiZHQFkUTOw2MJq1a9WKyYnRbbbXbW1MhMDk5QU2UcPqAxMRJIFFCSLqpYMIiAkoEjgYigKvNsNadbYOefC8TgghraLCKYqAOXq6vyi30Rs5qHc325vX+2He4WsMIExIBJ5BwpSxBbf1tMu8kNhVUush4ABqhSyWNGCjORQDcUAkO62u+v5/oPvbiiMs6WURAGaLoI5saRozkUAKAZd37oVOmfBMaBOaWgb1zTNOIzzVK4uzjuf79/s0g5UFTw6z8QGHoqBobgmxN6Rh7nMOhcDRWIRLXMRtRN9rY5awADAQZIRgpw9WTVtO6T9YTxCoFnmyB4RxIqIIAE7qho5wXuPDgxExcSYsAmh65u2Dc45z8ahdWQpY16ITo4de+MkBYlijJvzzfqq2U3uw4+eCVGx+Sc/vT+MhgAy1zkQxBifXV1+/PzZ+08e53R8enWx7rsnV48d4+G+fPn57c8+/+bP/uzTv/qrT3/20uAAYAAFYAfgIXR9ZCTHmnJJWp1uTReHgZJQMxqBZlA0MXFA5BmBypymeQxt220aH6PTXEpSUWYfYoyhmSclZRMnRiYz7OF2N9z+/Od/0f/8n5f/AzLwc/iP/93f/+G/9b2ry/bRk83F5fri/AlSWrUXnnUej8G5MlKk9mJ94WZxRkhQ9rv/4N/5nc/+5m8+/cv5epdXF2fnj6+EcFbZDcM4Dq9uD3OGR4+2z54Lo5uT3N3u51mGYRS12DarTds0LjYhDflwHIdpGsfxOI7DtPedM8upZASjVLJIKaltV8R6mA6IbtV18ySeCAGHg4HO3iOiFVe+/2vvXb/6+v7wxXd/pX/y5Lu///d//4//6P+6fnkPU266Vmc0YVRGKx6dMuUyT4dpEoARNs86E52m6eb+IAJcsIiM0945h4z9ugOkNM8pzygEZlJETIEMK1q/sNKrVNap+bATmQAAapaFB7+ROtD/VuUD3+Yd/EIWfDcNvy04To8zoCwnkFryqL5TahG8Qxs3teJdnIcx9Pbo0eV3Pv5O55p+1V1dXR2mIRm8erMTIgU+TqUxMA5AHtTYdU0bjjeDAqiZWDE055yaTtM4TnmexTkEYCmSUx6Pg/Pr8/OL/ba8/vp+uBugABgSOSQy0CKoJgjGDsxMc65pGh7KR3ygmcE8yQOQp2qahRmZnXlFEVUtRVWsbSIxqqlIES2iBgBuhhdf3rx4cQMtPH9/8xs//I3NRQe5XN+/kTGvAwwHYJgEILYueGgCgyMfasJXRG0CthxJ/UGGPFnpIBUABWEBZwlzwx4cFcnZxDlo+6Zfd4dhByJSQFVFM4AigzKUVEzAcwDEnIojQ0RgLSiACszgzXlwbF3n15uWGEpKqtUfMIMFH8LmwkCZzLWxb9smz3k4DmVO7PzNl9vH7503TduGNO7L1ib2oACNlnXfnV+uRGRO4zwnB2JkMYToGkMpqex3x9Z7H9xFwM16vTlbB+8O++08Dcw4jgOATdNcioQQYyARUJVSspl6z2bivWemw34opfRr7wOownA4xA+fHw/393c3u+11G7vLs40UVYImtOvVJh2TlJJTBhVHGH3DxKjoIETXrrpN4Gj5yMyOnRTNhyykeUg6WeiizFY0q4Ln2MVVFxophYvDQqXkbtOfr/vNerNZndU5XIjO+8hMu9tt8CH4wJ5Pt5AUKc75Uso0TSWXLDn0ru8u+YoOw7Du1327Goe7NJaSlIBa3zvvu9CT0eF4vLm5HobDyzffXF6ePXnv8eZivdo0iufttj0Mh3meggp5PhyPt9v7oqVbtevNakjHYTgWyYjYdfH+7m6z6R9dPrrd/pQZ1+v1wfL9YUdGYGAiUJszRiZGMKOCymWU3/qd3371+qvd/h6R1EDE5jGVEcCA2RsaG5qoFjAGRmeSRHW1WTvnkEhB85zRDD1xcESOCZUqrrI0dXV3jk5GglZnAqfau9bPRvYQrNAqroRY2VMV7YeTYgueTIKqBcCCai0h006GXLDoYplJxYyWGFe/kLpts2wDLTJb+rZF+lt9xdJ1LPsWiKimYmoiYEDkGHnZCscHhPAEcD3ASt+mTy309mWnWwzgpIpTr6wSx3TZaloSxYPGLNgpU7AjqNrxACBqsIgD1Tk7mRKhj75gNitGYGzGCg6Y6DgdCgB5wGpJ5QBp+ZCIJmLsVp2qHg7H7W53uBMo0Hewit2qP//8x184zxSwbaJOMB9SYlSTeczH3Zxn8wQUwEVqW2pDjOyOY3Genz35zvPLj/KxfPHXN5/96POf/PlNa27t+mGeSyHIBqIOnHOu2CySCahqrCEBI4IKLMYcC+XaxECN2LnoiKvEXKng/uLxSkhIQCaIKrMWoDa4dWzWDbKmnNF4stkKXN8cjn/8x+Px9c2vf/Txf/qfbNaPEtKw32JBD14LTONggc+uLiI4A9ET6LhoX4sQui50XTw3mAWPAtsCeRyPKeN4tHHUOasCIJEaEnEIftOvdBZEdOQYPQIwCBCaWXTyyUefsHeiUNQ4oPNNK1rMUknDNByHIwduKRrUNCZI5JwHg/EIUkCTQwSHvgkth1YsTNPUdRCa+OTZJpX05vrWlVYQxzEdDzrsASADgwtN1/fRhykfD4e57zar1bqU8ub1m9vb/bpz8bxRgTLLfMiHe0tHwBlJ2BTznCFXe0gEUxATMyjgem5jh4K5lDKp1oyrZkZoiEBsIU/at33XtG7Pd7ub8nA/CRgaBzICKQpVa8lOy4BLp/IOvERQ0StAq7tzD8aBtYaqHScogGK1ND2Rt+Q0WlzO9EtKLHgHabEF/z7dloCnL99CPgRmD2LnC7QhFWitbfM7BHuoMBri28uuqNiD3RzUV8TEXGU1T6i2ACMH5uCAQRWRwTkW0Go5vfBN7SROiEYOFwRJkiIAACAASURBVGuLLCgPVLKKkiCAfqsvXF79SUocFZZyVpHAVxVmAxOQamRBD6/XlvsRwKpOlp3Ur+orRKzz0wfo6luB7u1xKvJO6BV8m4dlp0XCB+ToAbr6BeO/v02Gehdm+v/rwBP/7t2r+jc/XK1iRd5u4b8FVE9PUDGn2j7Yw5PY2zfo4VkVLYMQGBMB1WlRHf0sbzqcwMJcW0kDRVUwK0UZKDhAMgWpL4ZM6/iHGNAICIQkmW9YTcyMK/8LESMRKihwy0DQrdZaypxz0gyipUihQkIgsoedprw+2zhkLBbAh9bPJUtRIkDEWUua5mMePJAU1ikDoVu50FU+mhIWNS0iiuoiNj6WLAo4b5MdDQKetlHRpELstTyoloS4JBkEYASoWgZWMVZFaBuHxGh1JnJqPqiGC0VETzyn4TjsmRoXQgh4RJCsiooNrFcrA0gpsYL3DIiHu6MklEmQblZ9PN9s2q593F0d9of7/d3ufj/kcchDF4OZJJ0O03GWzB64oY7XakCMzgdAUDXnsGshp8mMvHcOXJGEKIQgCDmbasopMQ8CVgCyQsrF55mcKvhxGtlZ3/v1WWeW51QINARY9xdtt2J2aZKsOg5ZiqpwJQ05CtnyNGZE0pKIUFWJXBujqpa8Lxmi5+C6Vb8ugnNR74l9BQmBmBjROXYEoMUK9G276nqvfvvmzXE77bcDIHRtHHIRBS0FrVRiaCVf2OLaUfU/gd56AJ3UFoCTJCvVjxAKGoioCjfOeRYYDWiaym44zpbBoxRh9p69GQA5UMuSggttE1RyzjMxAJCZqGqWzI6ePnpyvB81l3kc5hEgWdEEBDGSqilBcFmZC5qaooEiAJGiELoQHBgRBWeIplpEEDyAWm46N6eSdZrHfBhHzFxIOFAueZwSGrgG2DGDMpN34NDKXPKcU84xegBOY9qV2Wa/6v1mFT070EAAznPjPSGZg+NwDI5dGzh4jvH6mxfcnF9crZ4/u3z5+qevvgJIAKu6xg2R5if92SdPPuxj5Hj2uz/4vZXvBfTVq1f71zf/+X/2j1eum9KoamtjDCQKWdFW4FxD5LNKtTnKWhZgWPFkOc5IFcQDAqsMZ83G7MhTNYOajxM7Z2REiODKXNKUDnpYdRclCxBQIAsRQIuUMk4wAzW4vurH4/wv/tmf/skf/dnmEn7t+x/98Dd//Xd/7zd/5XsfP3/yqy/2n3deGCQ657zJiLnsG+9dDPth3zt/Hv3VqheZmElzgehqUe9j+8GHEl1QtDfXt1+/vP/Tf/mXL768JmZEB4SSi/O86vury0erVR/bbpXSdr/LdzKWKUNZTJodJCfOAbF455IMKU3g1IeApuu+KxcwDUcwOA4TQJl8mdUKupSnu+1d29/91m9///Zm++WX92mANoa7+70r0TctiPNMFGk2nnAwZ+CXt1yBnMMYXUH1IaKBd96sNlWipkVLNWRXUZA6EiRwi4tt7W1QvzWsOyUhMJKaq04JGAHJVB8Gd/+aRPhu5n6YAtnSRy1rNfj2x+D0AwC2KAOjWx5XBTUlQkBM2ZjpydMnCuqCu3j8fHz1taVyfX/PsT9OJYS232za7tLHWHBCyE3TEKpKIbQYg1HZDbspmSFMUwKAtmkNfIX0QtOwi6VomosqgAXISQQyaeWMApJZKan4QMwEIsJQ1R4WDFeXtRsDYeeZXI1vcBokJkk1yzjnVBVAFcS0ZnkidGiqIE5DGz04y5oP1+lnf/3i8vGq65qPnn2YSnp01ovZkAbL5Prw+Owy9iyQiAsgkBhoUZlRHKg0LWuJx/GgVNX9DRwB8SwzIofGBe6RlZnFivdsCJmzKBgk0cqWqf21LsW3gzwlQKOWCbHaOgFAksQA7JXYhvFYJIUm+uj0OOWSjTEEyhlBSVDnMpciSaRCeVKgFOxi7FY9wJGAjCFLSttZizx6/EhFzGwe52k2F5mCR8BxyvubUTNs+tB1HQIwc85JNR8Pe1PZbNamGmPwFO5ky8AheGanCinncToCCpKKzaqmzjZnm6aNooNK3t7vPf8ADRofYHXexsjIkg08xdB2Tb97vSMiRuecj963TRPYM7An38Z+1Z5FF1u/8khMWEr91HPvS8ToXZNSyZYd+a5tL9fnbdNoKdIUQi4l930fYowxAug0J9XCjnxAIlqv1kzsvWfHBjbPs6oycde2VSgTAetuq6ZccnHoTGA8jIft4fb6DpBW/Yq998E7jszEjMfj9vbuepqPob06v9g8//h5E5vR9tBCXzbkyYF/8/NdDOQid+u+LX3YhdD4M3/OjHmaV11/d3Mb+9iGNk3jNKB3oW/duknOt7fjHRiCaA1bysCMLrhxmgDAB7fd7l5dvwSCJva3t/dpAADnQ3Acx/2MDk2gFAWCw2G4v9/e73dXT65Gm4dhAANTswJKRkQOOBMkMytWQXuFKjTzMAMneKdneDdkLcwCVUQCrJtHtjRQRij2UK/X9m5pq05gFpxIC0QVnCKt/KRl6r7oZj30EKZWCQKISNWn9DTF+4UDT/Qrejs5X7gZf+fxQBKr5fEJqAJQOynpVERxIXFxVes8Nd71J+G0G4hQxRMRGIlBDAmxanAQsiNVedD9sqoWyWB1r5rZE4cQ0CzrDAgKWszMkARi64mkttLoYLVq1uuVC47Z5jS2XbPa9PM0TRM5YkBBBkeIBeb9HCkwBkIK2GAJ4x44YGh5mqZ0NFBwHXiCJ1eXPpDMaS7ShtXVxZOPHn803urP/vrrL3/84tXLG9yiBJUxR24MwIgIHbNznm1OSYs3VrWTS6O5RfhMFxNdA6tIoiPvHDlQs+r1DFi9mwiJjcywSvwYMbPDLOPt7QAMviNzSgRtH0OexwJ//tnfHLcvfvP7v/bdx48uu6cRAxMwzOB4X1RzMVMEyKUQmogSCHsOGMx3OTtJyI6BSSTPOqifXr58FZszHzab2OaM0zyLzczqnAaGVdeVOaFxGxpGJ6WYkFpWFRFxTRCBImpELjbgIR2P97u7XPJ+v31587pp4zmeqZZSMgfnA7NQG4e2HQ5bY2NidMwxBCR26C7Oe9EL3zSXl6s5TQBnNgcnAQxLAahiMAzHfbnzQymFnARqm7ia8nA4Hm7uhVDAbN1LKcAYTEoaMxRyGMwCGCeZ3hm6AdjiENU0jXcxjXmaplyy1i0+AbPFUdgAxu3IwO26PVtt1PJ2vytm4JdVuKKyqKAzUE3nD+M8PLF0as5HExCyd/z3akEGdtJHZwAEAVRTAa6dvJkKo4ma2WIL+o7eg70NVgtu9o5T2SkQmZ0cUR8i3VsOFXzrZGCGTNUGXR++U0md+OBbZxWqfgAollhnhYjsRP8EVCNCRnRMnoCX9hsYzayQoiVhQVJUMpOqRk2MrpqBIGmqNQcgIlMlvb71wj69cABY+FkPkLyBMnKlQZlV5S44wVsAD8QzhBpFlRDUgM1UTsFyAbDghM8gwoOlXmX4IOGDA8/D9cCprH0w+/vbONEDUWvBEokeNGHxHX9A+FuJ6W04/zejZf0CKHYaoP7i/uAv/P/vegQqgEVEIQQzE5FSssjSCJgB0fIaUlZY8qIhIiEqWcoJlkV7A1MgBtRK+y9KIQTPwbeu/p5WhShTMzCEWSZAYnRMTEhiwVKRKYuDt9guAjQAEcAhEZMQCChomUuhomgMoqRKAvMEDXRXawBlwsdPzo+7Yf/yJRRYN51NMB6m/V0xkDvQJromRO/dOvQcAwd3vz/c77fsU3e2jl2TrUABY0BAYASitmnW64A0OF8UsmYx5Ha1DsDH+93MxXUOVgximAmMSA2SWAb26A3TLD52wEZc70g1AvLmQoNogEqWpOaR4AGYBUwETUwBNIfWW8yx9eu2odbDlLYFDoexP6OrJ4+y3ExHjX08767ath3GQ06zD4ST7O4P0zUAADmM3jFSHud5GIGh69vzq4vdeARH3Lis2bOuLzoa7TgdOPhu1Spg9bMBhONxuJuGyLxZh1ruIJoP3rkAIGqiWhCNHYXgvOckBYAQHJhLSQ/7cZ53PuIqhvWm9YFFS2y99+16fXZ2dpVGuXlzd3ezT7OWrCoARo44eh9iw16Ai4GJlMN+n4vF6B8/fuwcM/vUzs55MzjujtM0TtPUNuxDe9iPlunq7JwQ05wAoe+bkiDlMc0tEb9+9eZwMw9vACYYXGb0hmhc54kKCIoGJksIOjkzGwKiWmUpnuaiDKaiSEiODUkMgaIyzHOCHXz66V9cXMbujIOPCWQeS9NBCI2BSUGRIhnEDCOhUU5iqIYmKjBPJJRzno5j47uziy7GOBzy8TBLQR/86qIpKqrFwChwaDwyzvM85TmVgh76PrRt6zgQBVYJDjyD5FKknF+uYuu+eXHz8vWtC9Cu4nHKwQdEqkCBd7TugyMyE4fkCEDFIKnlzWrVdh2ZDPv9fk54PrVubY1nIEUyJAbSlLFhF/j69TfnfX+7u89fqAD9N//kD86v6KOP/t6vf/8H/+E/+F2dx9s3u3EnVxdXF6vz9x498+oC+j6steDrL27+8X/1X//T//JfwS3Ae8AXMNpuEdFXhVKVYhWQi8yg2VTZMUZynjSDKZARAyGikqIzIiBSA0VSrulNCzqMzovJPI86CTDEpnGBPZMZqJrIJCWllAiJPbFjHzz1Mec0TdP2+gAFXEv7o95v4YsfffY//ZPPYPVPYQNwgE//5L+d073ZFFh6x5vuyTjeb49vOLqn5/1xHD9+9rjv/F/9zU+/ePPmzatX3eXlBLg9jACUsnz/134lhtWPfvTjP/2zL4YRGoBpRkBjBJkABFy3/fHxaxCAS3h+9ej86uIHP/het2ru9reIWcp4ft61bXj86KJt/M3rr4/HfUqjYimlmDkzCZ4eP2rneU5Z5ywh+M++/KIPnh2+3H4z6PRbP/y3f/N3v6tF/ugP/1zSCKToUbJSAURChTpRgBmA4PbuHpnVLISu67tXwxuepWs7Zj4Ox+N2AAN0sEzlFks/AARgo9YhEFSfBK3iHCcx4KUWB6jcq1+WMRHfHav8nXn03QlVzdPMjKfho4qKSq0PlvrjNNVbhoTv9mYGprra9AfZl5IvL8+ypZff3PzFZ58ex+Hs6mmIT86uHrdreHNzq+b2B58Lo7Wk0SbftY/Wq46DjdN2d7xvYwmNHYZZVYgBHaZ5nobchu7p0/fnhJ//+OvtTYIc0iAAULIWnQERHEJkqA6+ZMCAjuoAiD2BgZUqMVZ7Q0xTFtKTAgCASS0j2BFT1cRCJswyq1WWQzVSYwTOB9VcFLXkPGHe3/18dQYffefJ+x89X7V933W32+sm+THvyfTJo3N0MhYZp5EQSXQVfM+recp5nmPXrfrzpmter3aHQzLw1QMMhTyH2HqDMpd8HI55L8+fXWG04MlEg/fzcdJxNsfOexCbp9kQODrzhIw+sJoVM2AQJ8+enz977/yDD59w0Ov7rxHNUOqqU5E8zzllmkcTHfUAZtCFZtWu/GpDQHdfH3f3+9JqF5t40W5vt8NurH/8HPRic7Hf7e6nMo5jMRCE0FCzag2ILKw6anyLBof9fkpjG0LbNmUWUYkxSC5CrGIAIuU4ZOj7ZrNZx7gx23iX3nt+vr3ncRweu54dT8eD2rDZrFbrc0TLeToO+7Zp29g6CtG1kdvd3fHFz1+3zndtt+q6JvjAPngfXGhDA4pQaHt9CD5t+k10vvUhriJzJAqlyLhJd/e7TCmlhExd23dh7YFSsS52Z2dn5JkZp3ne7rZzTqkkUQsxGotnd3HxSIpWfyVVzZaHcRCRtmtW/aprO1ExtCL5cNxdv7nZrM/mY9rO+zSmvu2ci23bg2HXd08fPyuabm9fP3v+6Hf+/m+0q9Us41cvv/of/vk/e/Hqqx99/umb+9dn52cffPTJ1fnjf+/X//33nz75aPPx4+tnP/nyJ+GsebJ7Ok4jgdzf3t7f38/z1Lfder2+unj24usvhsOYZhMFzIZc7dukOnIiMpFlkbOzdvO91ec//clPvvj8xdevnz1+yk+iGCBT2zVgfjrMKMjOm6nKDAbbu/31/c3Z5iI27f39Fh72EQXm2RonCjBPeRqT5Wqztdi9c5WNqNouFU6ChfgpsqDn79T6wjUcGiwOSiYnRRR8aIzN4N2+CHBZtqu4rzGYoikQ17hWGQwn2EsVFs1MBVq6TlRT/0ti6buT7HqFqmpgRFznc2Agqu/uJy1aySfGx6lT0hP9Y3mkNoAKQO4dbi0vqBry8pIQ66QDpVgRoCrgx0gVrmIirObRCMtCJFT1DkAwKGjIZLmOkRnIg4/ovCPCTbcZj8MwjQYWPKxWq27Ve+8MFQYzUJWiqjll1bTpsG+63rcy0X43f/87P/jm5c3N6+v97W4cN0mgD4E5OjdRyA5hteY2cPD56eNnDCFN+vTJ+4j8J//rjz79738MeHKSYYu0ggjjcSJjQjQWwSQKhROgSVW2WyAOIHKAhsimACYLk8OJEoiJIhkVZAUGIwMkwLoXj2AGqmET2q4zgFSSSFFUUUXQAhAIwHNRudnB7i79j//zv/iPfv93f+/v/Wp0zfbuNnZd07SsNE17zKaUSlGFoiWlPASmdQuRIygjBEdBUKY03+7fTLI7v3yUChdFZoyr/uLxI++wlOM87/M0MEEfmyb0a39mgEIJ2BVjUa4+pwqQPWQAATiOwy6NGUuCJGTkWQHGaeZAoWu7riOCeZ7PNuBCH9qxaZtiac6TadkP0/44be/1/iDZwH76TYhwft5fbtZszvnsHGgAhQDEw5sh5+F48BzUR3py9RSR2YX1BjTDfpd3/hgwOAsy5ekIlJEFZC6Sk49h8dk0UNC6NcvEwbsyp+PhOM8FTourUADUTiqn8ObuzZv+zZPnjx4/v/zgyXuR8XbY+74jcmlI42HwQLGNZRI1WeZ7hMampujR9ERpV1AQACVigyoqUNFkEwU0IRI2AkUQMKs6BO8cRu84Qfzi8UBzgRqS3iGvvI0VViFyhJOpXuU91QUuJMLK+tJqPvFuzAGwd0ETfDinPDjKnYCx+vSEpGjkeBE7WggIVX4GwAN6JEMfnCNmZM3laCNVtgkTmBGSAyz29qnfTk//Fi+VmKyuXEPtHdkAiskyQ2BDBEJ38gVdimAkQzQkR2YAlcLKdVETpQIy+rANwEwnSXJBW/KHiL4TTk+w5Ol4S+k9vQMP0bv+5115jXcxrHd/5V8zG/5/PN6Fw9497f/rc7qHi66J5y0tbcmXsNS3C4QJ1RYEEKiKACHqw+elsoqqHDgDh0p6IVFRMBQU0EpEOpkGVO4IY9WdE0BgrBpqVXGtEr/UCIiBl61cAMlZsCiL86pODYBU29jGVcgleefNNER6fHbuzF1uLnGC3e3ekqV5evqdcyRYrzfjPI/HKU1zSgWVZFIpieJE0WMgSFBEoSQw9LFxLpraOI6rFXRtQB/mScf9UZ21Z41pNheGjQzjaCk7RyyURdAgsPPk53HgxttCF6ylgVVCN7ApLWMwYFKuIQtrQqq1SCmlPwtt3/jgFEt0PgY/5BkHdByZmTw4duy8C8GORkwxxJzmcQccnIyisw1zynM6IBSFpnWhi6t179pwnMb7/T1bboLz6otmICiaxxmd92lOqkhEzBQ9NYGbNsToRcp+v5sTrPqmWzVEHkAUhBCccyE4E0nzUIQQIjKHhtjFOulRKCmPCsmxD3EVQizZbm+2L758c3ebYZEARzR0xN75GJFjCb31q865cNjPIrPjkJNKMabQdYGJx3G6u78W0yKwXvu+a624VMw7LznP42gezvqQiwxlTwk7yne3cxmBkTCSActuBu8peCYUEM2TKWh13jlRrBc+IgKSGQGgVUdVETEydogEJRcDB+RM1XlfWj0e5NGjpm3iPu1SLoRGmBFxmss8a84yTaNDtFKa1qORSOJA7IIjbtpWi+7uD8fDDaNz1LRr36xCjN3ZxcWb2zeWtSQREQYVYEI0UgU1AEcEBlJ0PB7Vjq2n4Pni8swzE5JZ6VZN00VBMIG+Q8wgFX5mq3wTIvKBmZxHAjUppY0uhjCIZ3AqRbJqAVQkYIfsvfNMeTY1yynf7+4fnV91Z5tHjx8B2Gc//eyrr6+/+92rcZbt9varL3+Sp3sPppOtwhrGYRKz5tyFTcPd559++Uf/27/6y//zZz/57Kv3fvWRmh+GYXcYmJe0RADkCcyKat3ORQeIzI5FUsHKCgZYjBZJbFaUqowhJgBAHBAo5VxmAXXAwFRnzpbzrIrk2Dl2jkwGswJWsoAamHK1rDAEJtcEJ1kUjJGIS24QkJyjkGnw8z/8L/7RBx9e/OZvfO/Xv/9x87jzHFwLWg7Xd6+Kllc3b568//zD58+GNA9Sjtc6z3kyGMd0nIZn6zNwYRjT3f1hPkLD2Mau79zufu+R3Zmf5zEn8z0gQsrwzZvr7XB/ftysNl23CSGwefIBUtqNI6o4QCMiR6SSsy2T6hhj9P04pv1+Xxe5k4AH8kgFUtLhdvfN+qL7zq88+emPN5//eOeda0OTjzanGUVAVb2gBwhgHkSM2AwAiZkCKMxjIkAffM4F0pIuatpixloIISITmyNcTGtt+buZokE1h35IeQtP+i09qorXPPCqQHUZrPxdefRd9EpUHLhFzP2hMFqM4090AKjShLXYWqA0A0CCNE/k4qqBrm9jjDc3XxTRi8vnfprIt8fp5uXnX9/eD9NUnAtdd4zOm4iJBMLvfvx8059163h9Z9v9vUMfG2+GqgNwBAjTNKrB/ngIcTNNcH8/lDk05JkUHLGhqNhDieeqjwoRMhAao6pqUTOwggsORYRMD12iqEBtamsFw8tMTFVOXBAzBFUxM9Pay6IZIBOpVxA4wAx6d3PvGK8eP7p4fPnq9ddoFnwIns82fdYJijPgNoT99RBijG1M3u30qKUgCQdsOj+VlKoVC7iV7yN5BZvmXHLOIgBwOO4dc50dmKlINgVmrAqYxCQgwApmYqXkvFTXASDC8/eePnvvbLXqhnSf8yw6D7ujVANWgqJQrWCKggogADmOXdf4pgofpLEwpovNxWZ9vmo32/12t9uN+/FwM2+3h8PuoEkkQS5gAMXA9836fPPoHNGySj4eD8Mw1rWDksucsmgexyH4gIje09XVuqTpcMi5TEWo865tW5N81oXV5lLlgtDd399f3xwIPbM7P7+4fnMdm+aD9z94dHGBhnmqevomGY674ezxU8/eITM4RCJ0jjwolkmncRoPU/ANq/N917Jv+4ZcJPRZTZmeXMQiWnJOuShKHjJ6vwqrvu037UaszJLKnBnROVc0K6rYNCVJxL1bz1PWSgMBSHOapkmkxDaEEJx3ueQihQXHqZrBOQBgduv12gRFjNkj0qrbrPqVYvnOJx8dhv1c5j/4w//lxetvtsPhzf31/bg9TKlZnXPT7aaxXF//8b/83z/77PP3vvPeB9/58OPvffLi+uuvvv7qMAzPHl1dXl42Tdw0Xdv1w1SePnn+3pvtOKXDPplyxsTVcI+qwiMRUJJUID96+t53vvfeV19/s98f5gG220OzihVuqoshJkZInn2xUps/x8FjAMDhOB63hwXAsqphSlUBHYE9efCg86KthFo/GgsVaanATyPfh7WZGpSWf/G0bVjhiUWI/dQsLijVyYwCoBKvanITO5X4lTlVhaaq7mp9Fl08w+HEzVwIVozyd4TUhdhxGvW/7VLgnc2fb48cTuzXtwEWTnQrOBFj4WHnhcCgNiAIZMh1h9IM0WpjXYnyuHAYlvh22oEEwrrEZlTVmoEYnSMjLSoiWkpWq0Z+EBsX2+CiI8I0TzmXUhQRgo8COo7jNOmUplzSbreb59l5LqUw4vp8fbE6b6iddgJpfPHTl7v9Qea5u1ydtRcsyOwNcL1Z9Z2PJKvGBSIodnf94unjT7738SeH+/SjP//sL3/8EyBcBMcKeuf2d3sicOiIhJgUcqlawnWPVE/wgCIA5Ky4zHgMjNQUGIERUQsYaQKHSGBcV/UFqgll/Uh5REeKagaK6KJDh4qqWpjUkJSoW9OGQyt6d7d7+eZ6v/vwYtWsu42YkELjA0PniFHVOwf/N2Vv9iNplt2HneUu3xJLLlXVVb1Oz8LhUFxsEiJMQx7IkmEIMOAHv/vBgF/8//jVbzJgwPCLbUACaMuQbIIUySE1g+FwOEtPT3dX15aVSyzfcu895/jhfpFVMyMJo0BVIjMiMvKL+CLOPfd3fgs6YNNsU5odTRy1pGIys2/AaJym19fXt8Pz3/n9j6fitHiAxvkYuSHIAohmJc3zEfI8da41gKKGys41CMhEjLbPAzpvYMU0q2VAI1ZGEQh988677/roCSrPDETKOM4pJSZ3vr149vJHiXORVKz4EJtAACtCUNwfhjIWYIR1v2KHmiZiiA2AUilOCyC7xgcmK1NOOUsqyjAcJlMGkzJDKdA1kUhNABUcEhhZNihg3gBr6BcYKDF7FxxzTiXNaZ4KlPpJBNQaVFqVPQhgxKzHsn+9bxrXlVCmXLJ5AHaMrqYMW22oljapAiOV7ulAtVqpLJhJxYkMCBFOcXpoVQCsWkzJAIzYUARBwfTkAowVf38bvan8oIo844l+VKmJslSA053rHz+Rw+75WgAAxqYLNXBRN9dfuEe3YQG0TofxFhpSSYdL6UE0VdMlYxaZiBbUu9LLxAAUgUzREEWRqHpVA4AAx8pHNKDTTt0xGUvRe9Xb8vqeeKsnIMYIyXApo3aSZr5BPpYXYLHkur/iVLaWdaBSX0+VFaq3IKKC3Uscl/+n742J7ulw9/KCpSADMvOvluh7tOvtOQS+yfTTt+lX/y6k6ddnYP3SPd+GtN6+9deEtFw9SpGFLv8r5LL7PwwA1TTfjOqqaU3bGlhRESlg91J+AEAK7CITYSlF67GxqRqgKooC+DYaIhF75wippFxquWUCRCFBsBppb16dc+yZ/5welwAAIABJREFUPKNH9QYRQCd06Bwro1S6iuR5qEaPdP3y1Xa1PVtvyrHIochByq1AgjKJrkiDHOZhLrO30LbrWbLBHNs4W5oOR2XzrXvw8GKe5/3NMTbN9vzMBxrG67P1ucFxGhNaMvHMkYmzJAXzjWtXcdplLMqFcFYVYCPHnpmt1CwgQkJFVYTTh46ADQmqsomZRUQV1FBBrAJZBES0PVudX658sGNK7Khf9U45Zbm5uRuThNCIyPX1rSEoWGxi3/fJM7s7HBEUgg991/rIYxosT7mUm9c7Reu2fYhhGMZ5zuMhsYfQ+tgHdKymOZXjMNXBZMnmEMmhiOYkyNj1K0BEtorIIJpaAVNxolqazscQCSNjAHAqVe5DZhqjdw5THotIExumZn87vH51d3ub0wxNiMfdXJHvbDpiYhDw8/rSd/06+qByM08wexXZl1zMqG2bvu9VKCdVAO+B0Lxz5xfd8TjllMDMEYXg2RESRtfkKY825RFIwUeH4PNooW+NUBAERK0Aw2LLhDWEA4CqFeapMSKrpHlAkyxM5IJXAygFALz3ljIzSZ8ti+MA6ufjZASuCQicc5nGeU4yjnPJZgqOcL3q+1U8zo4clpKH4+xA+77NrZhMac7H+cCOY2giR6PSbZp0N5c5I7OPzjksWnLJulhG4DyWw92cixaETQPnZ9u46rs2OuL9/na92a424eyMr69FrITgUlYAI+Lo0DEjEgB6dg7RUFDRex+a1e0XO8lgMptqEyF4hwAM2PhojguBqKacCajve/PY9c18HKZ5UqRSUtf1IYRx2F1flYfbsz6sWnCrpl/FbT7kH/zshzdflk9++OJf/+lff/7F9eEW1/0Gye/26NYBuQBUi1mtJiA11MNU6kQo5XFRwiMAgRihoQIxgUEGRiOoTZ1ZKUVrc5tLBgFyCIqKZgiyeAOKqHHtohnUQAQMhBw44pxLziVE5zznUqyQWfDL5BnSbGz0z//4zy/P/ac/fP7Tbz39+CuX3/zmB08et+vmzF+6MQ/XVzevnj3v88W7jx6HVQ8/+dknz5959g/PL92tOzvfenbDPIpKaKANkSB4Do2vBBxJoxGQj44dOdCikudyd3MYh+lMmvPLzntgssPhgJgdU+Nj2zUpDynPsXMpzabsPDP5EEPTOlVpIvlw9E10zALlON19+tmPv/L+bzx+7/z3/uPf2N185+XT4vIM7JvWk1rBxToRUE2h7ToOnOeUi+QioKCq0zgZABNxR6aqNXMQAR0xUbVm8RSOx3FxCkRDMjQk4Pqj0aItXyaKiIa6UNYXh84T0wAQQcHe8gl463I/s7lfy6vhHWI19SckZGAzPbVjULsnXAiYagbwxi4A2TnR/GB78cEH77dd8+mPr7KajxuY8NXV4ec/v7m6mmYRDqFtPaI75HTz+mY6TI4g7eD26vDBVx6ePbxs2vbZi89uj9clCwI659UICX0IBfFuv7++mo4HCGZGFGJTQiZEdiImgrYsK0TFjMDYsSMn1fRCTEnri6T1zc2nPU99iWqniGr3o0IAppMffJ3uKdUJlaiiIJotrCy1POjhKuX5xc313X/66J2P3v3Kcd7fDM+jp+B4npIWAYEYOl61DEzInl0MKuRi7Jousj8Cx90wKTCiq0IidhjAKXhSNVSVYmSIRszeozTeN7kcpZSxiNTxcCkFAJo2bs83ofEUyHUuNBgal9L09Iubu+Gq2OHsfJUnzWWOoQdA5qxMsUFIYgEChdAGRZ3zDAVXD/vxbpyntL/bBxc229X6or++bW+vr+eUgnPzPE1jnhMwQ9uGbt2frbZdXBnolPbDlMZxjCGuVytETWkmgpzhcDiue5rGJKU4UmJcryEXmNNwOKjZrApzcmdnFw8fvONds9ut33l06Zxbr7sP3n/y53/5Jwyr2Lb7u0FSAXNuFdwqht7N63RxcekIEVBECcm3IYYo2XLOWtRxiKFpYtPGtm3bpukQnQhU8zdE7Lvee2/Lnhg9uejZO1dyef7y+d3hdpiPc5nJu9Wm61YtEhQVURnTPE0JzNq28d55H0IMSKFp2hijoeUxHfYHseLY9e2qGrWs2s67uN8fybRp2r5fn5+dA8Dt7fXVzbOnz5+9ur76s+/82RevPr873k6mHCGu147cbji+3u+06KGbjrfz5YMHv/f3f+fjb3706PHj3yy//d3vfveTn33ylfc+WLVdu94O+/00TB++92GZ9Yc/+unzcWg8ixRCqjQVBQU1KWku8/nD89V574J7/tmzYUxCMJZjsXMfQlZMcyFk9A7GrAbVHQKCdW3f9aNzrq4LvgkipqpAgMC2TO+pGgYfpgNZpcFYDacCtCIFoIZTA9YdK8KJenTKzwMgWzyfdOFSAMBJcIfV8MCW3Q2+2eZUnOLNDsJqT49U6y0CURVigwHUwTyYnW5iJMy/wrkws1LKm5L61mxAtZKCkJHZ0ZKYBm9mD8vvn+o0nhTctkQRvkG9bNkMg9bnh7oY31RP5MUCZzmLYma0yIrEtA7VscJYjOQYEZjAOVbAYllFSs7ozHsgj84REoqKmI13gyogYBNjiFFE7+7uFrQLVW1mN5yfnbVNjM63oSXgnMpwnI674erlDRQAD13b9av1fJxSyWkYt5uu3QQPiSSncdg0m8dnH6PFH333ky9/fvP582dyBEAmdYhmbGTkguOKhYIqiEA1BwKwk7s9ACBXg+uqAyNAQGdoDkDIjBbQ9Z5PtxD0aroHLba8gFrp/94HBp7LrCocqIiqwjjPSfRi07J3bYOvXo/f//6Pz333O7/50ZOLB7mkLMUjNo2LzhBnVRNE70PTNnmYCdk7j+qLeUYH6L2LbdNiPEdA5wiYq7NDhhGhAFrwQWMTfNSkHiODKyqIREBqaiaGKILANkkZ0iyAiNS3nWtoP94houdtiD7Nc5EyjseXr66GYXBEfd81jVM9ljLnXMBB2663cZOKv7nL4yy5TOyBWI+HUWRy4JyH1SpE9uOAQ57jJqCBZA1em96jlmEY5mlG4y62DZbAfhpymooJoAET1o0zIJAH5JrpZQDmo/Pstcg8zWksaMBMoAiqVk/e0s2iIbhABS2n9Prl9d0BE8xGMM2zERhA0/UeuAylVMEsGhHhQtxDQ1vQKrQ660JENaFT2m+1+0HSCouDAQOzMSOnlCoC8Fb5+IXv6vuxDsGsPl5FJHCxKV3ep7WXRroHzCui9uZxlynhSWt3z6U6fa0piUtFPBVHIrJq8FIxF0ImllEWWLweCgESsCfyRB5VFVSBlLxDVyurIQOAKSoHRj2BQwhARI4J2BRExax6eiPVbLbq0n0KYVRbzBoWpoqevA4UTE/WhG87qyIuVn6IpZTlj9Zaq0pIRIzVtBChxnqYLvLQCqYpAIqx9/e0q+V8LGNaQEbnFsCnlGJvYT31GyKq4Ob9j28q9L8fw1ogun/P5ZdJar9Kwjq9DEtb/msCWByCF5FSSily8qj/hX/3f74upXA/1laIXVh0mFyTxsHIasqRc7xAYyZqoiBqpiaGZoTG6IJjR44d30c8LW8yADJkMwJgraYqIXofnQuEHoEstE5JjQw9c2D2TknJoajkPHsK03FqqYVEh6vjy5+/vPr8ZvfsuL8+lmN5/sX1q+d3Vy+vp7sJxYXYGAARPnx02a3au3EnpfhIXd9xdAjiPPSdbxxiyg0H1jbYtqWLLpxv+rNVWNtMh9sDZl43K4c0T5PMAqTMroiYgIAZmfHi0YlVgIZWWSvV85tq8D2zZUUxBkZkQDAsQNZe2te+efn4o02G4/XdawNo+3Vs1lLw9esdGHjn8pynPJJpCNz1TdPEnOfD4ZAPCgQU0TWOIla8zIiylVTyer29u97fXO9TgmQwJ3Seu2blXMhTKalMg6QEVsPHUInIkTMjIG7alh0fhrzbTdOctRRCChxb10aK62a9bjZ96J15mTQfRSaFhF3oLjcPzlbnTl06Sh4RS4Ti08Gm/axJWEmyMp7QUlEtkg1CiAA07GcD0mIiAorzLMd9yjMFXjX+LLpebEAQ72Pbdkw450kkA2rfN+tVD6LMznGgQt78i8/3ntm7ThLmIhwJnCEXhQIgwIAOyAEQkjf2hGx1Xw2MxEiOnCNmJkeGgo4AHYAzCuQaYgdEqkVBI/PmfKNiKc+EsN1erFdnOcnheCSEaSp96z27ENz777+voowhjzDs5vGQ56GYetDgfcscDsdpmm1OeUoTsYXo53kSSdH7pmscsarO46xFAwcTmI5FsiFCcBCDc46ZWIrs9zvy0PbRBRqHfP1yPj9fAYKJKthqtYoc+3YVOEaOeS4XZ+fDcQBV5wmIpwHTVMo8e9J17y7ON+tVCM4YtfWO0bQkD3jWbR+dXXpgJkh5UMsx6vn56nzbX6zX56tNMN7GszVuz93jDrbjrX7/Oz/5l//3X/7P/8sf/+W//PHVzb4NLToYxmGeR/ImlNREqwMiwmJ1cV8SEUzVRBEJ6hkihmq7beqCJ14UYMtAw9AUT4Ojqmlf9BsIWPXDtcUTQAEQW9wVVUHEihRAJGJVS0lKLtWtjpmcq8FWZqTrTXM73P3oky/+9G++/8nPfnC3z1ev7/KMbXvx4OK9LDBOMwL1bdN1UUpK0wAlB7SGoHMcg0ez6Tje7Q5n51sBCDFWNXdKRURcIABEMh9cJT5IyXPJoKmUYnU2YQZAUsyKocGcspk4doBSSlbJzBYDN63v+na9bvaHl23XGeHhcNjtdl3bet+cnT1wHLfby7/9888LZiLiljBgYcsIVvW0yZ589aFzUMo0zWMppuBMjZbxORFRtZclBHbkXA2KICZyjsf9aGxYQ4jpzcTKxEyBPTMzINmSVGhmiriYnFG1bIAlXR607ryMmZloESkiweLTaQuLXQ0M6qd1cfalBaQ+zbmqeyqSI/RmrCYAxoyNo9Zh2GxX+6vdt//o73/9t969vNxe39wgNbPg7W76/POrH39yc3Wj8wzrzbpfbZji/jDu9odhtjnB9ev9zfXrNJa+6z9474M0zeNxGI+as4TYzEVrlfGxHSe5vh5lAkhOJyJxqGggimKs5tTYgM1IDdSYXfCIVKqHQt2iVC47o3cokmtaMNBprYfqq1OxI6rN8v3wE95evcAWjicqkAEaFDOhnP317XzRbz786P22pWl6XfTunSfnd3d3w6hNeJQGN762/XU57vS4t8NOSglEbdNumqZLKTNDDJSmaRrnIgIk7C00HCKyF0UNEdGbOeCGLaKgqdH24uzi8jw2YbPZrDarzfnq4XsX73zwYP0wtheuvwjrizAdb8fxeH1zdRh2iPbOkye7u/08Fc9tE3pNCmaOmJic5xC9C97QcpqH4divOtVUSjnO4zQcvSuhBYrabd2DR5uzi7VaNiht41Z97Pu2bWMTAwPmlI7TdDwOoti1qxCbnHUaMxgxhsNhfnBxPk/TcRi0JMfSdT4GjwsJzhz7NOfIzfn6/KzfrJt+s+rOt+3DB2cOLB0nZzjtjndXt3nKm35zcXax6lfOO++9dx4Ei4gpeudW3aaJLRhIkbZttmeb1arv+rbtGo6BgleHhTRZySiFCkdyrfeNC9FxJHSYJAMRO/5Xf/r/3t3dIMAwHOd5VM1AGJsYYkTEvjmbUyGiru9j0yCScz7G2IY2eI8K8zAddsdxnnwMwbcpZUbu23VwEZEQMDbx7HJ7EbfPrp/+7LOf/PUP/upP/+pP/u6TH9yOO/BIIYS+8X2nBFOaDsdhnJNJzpM+e/XlT589/Zuf/vXdfnz3/ffPLy7mqTx79vT1i9cPzs805TROKeUmto8uH95cv853+fY4GggYhEDkiBzlY5Is28ebB++vubX9eHd9+6WieQ+Pnzw8P7vomm4axuNusCLBY8kzUY3WAi363tffTTK7hhVkmMYQGbRotmqETNXgVave2koqlfgEAAY1Nkuru989oMNIZFjbQTYmBZTqCAwVr37Tmi8CwMrLuk8tXBLHqtN5nQ1I1uoftQBqC5sLGKpkB6lGedbNdmVtMdeZQRGpCupKvaiQPiFQdZqWqu03JDzt3RQQiJkclZKXw6vVZvkzRIj4ZqO1EChOPArACrAx1CNhx6d/hEwKZmQcHDEaqhqZIpgCVdaVqRUkNDJlACb0BA6ZFyotMRpmVSMGF7BpgwssIMCoqOOY5sG0ACG37bpbbUxpSnmey5zEOWeiIHC2OYuu8dSUYs7Hu9vj8y+v9rujQ2cA4DH2HhtIlEadMwo5bTs43h2gDB2dffjoW627fPaT3fe+8+PnP73RBA1TOcii0xApkuucVCpmoyYKpmACpETKZBWBhPqVyBANTu0HIpgDdLhIwAnhLe92YERmduQ9+cYXFfCOHQOqQfZOorcQoGvJOVPT4CEEZstYjsN+OuxvmfyDy7NHDy4bDgTRQ9e6NrIDG1UU0KGSZgyuaeOKiSUjYRPdmom9K21buhVMnIvNCoPaYDYwZQYJBIRk6snatrlo4jmQUwRiRgiCmMWSAHpP5MygSNGSHVvw6AIHT9ERMuY0D8Nhmsbj4XB983q/34mo97Fp4izHpo1Ijjl03VbVte1KjaZ5AjLAzB6YS60PTMSOAEBMDCQGNMxqOQTr13R53ozzIefsCboYGk9lLtMwzsc5zwWEUNnEqZJJwZUaKzJggPVmXc1apuOEhqykRVHAAbHVE+aMAJmQiQiJUSUbWgKZi5y/++igRw1MwdfPKpFTgZLL0iRVPIgNGM0hUgV3HBM7YkJaQkIR2BE4NjKuG3NgAsfIgX1gP48T2uIKL3afFm3EVJ3gsQZ6EgKoiJmaETCT85RyBZKwNh0LmbJ24GZyAuLJMXtHjMQErMZmpGKKrFixhRNAhLUAUe38AMCMCci0NiSERoCAVhRQpfZI3iAaeMMIS0obKrABY3DBAWmpsgxERGA0UyAiYABmdWQeyKnVT57UYntfvBeuK9UtyQI51sDFupWwBTo5aQRqybZlSEqABLWOYsll+eWKr50q7UIwRdMTXc3q4RJDLb8G6Hjpa8EUq/3pAlsvMQpgAKZ1ulA7W0QAMzXnCO9Xhfq0TgOJt7+BX6RHISISGtVnzrXHR3JQUweQAQGQYdmtWR1f3BPW/q1A1a+JXgGAE3nDvjod0L/t4U7zkOWa0z3rSy/V7lXEwCobGdBEikH16xU9WSkB1P0g5jI7YiA1ZFzMGK0SH4HMGJC0TosBQcnb8p5QM01JMiQxdQXJHBE5F9jXQVej2dZxKxPsrm+n23l+LTADJWJwjQ+SDs68FRuOaTq8Ph4Hvw6rB6u2bRzh2dQf5mOax3FwbRf7PszjoUy30beR2Ea36S8uzh6s1r1zlEsykdLJCjZ31wcs1PReOYkDyUBssKIpZTRr+sZUuApbl95BpJhlZXYVWgUyQ/VM7JyBLwJJrWZwvf+19fqhgzjJPBglxcDsipiadW2Y02RQyOs6RucNQUvO84wGsDlb7aZRi+Vc7oY9jEBESBYabwZMPvjGhCADdq7p2jxPBj4nRACdZRxTyeA8NK2j4JA4utj7zlST5MOYRMvd/rg/QGDYNoC99ivf0qrz7cp1ZZbDYbh6df3i5fXtDvoGHj18Z7ou6ca6rislT0ccpik2rmn7COuWh1Hncc6Xm+0w7vaDQgEk6CIowd3VfNjNRfX99y+Cd0S46tc5lzzepknnEVZt16xX+/G5CIAxIYoWtExeVQSIACWVRMQ5Fy7GC6uCjMhQOPpimSkjClYqrS0Ob2BGBMh1pKBLjivxaTBqYEjOWd3PKSExGAMgMeWiBMbMkRoC89iSl77pfPBgVnIiR96D84iBvHOImLOCep3K7iqlpKo6Hw+xbXzwQM5xdE6L6TiXw35g70WyqamqZkEHZETGJQlKQWIU8I6cN26MCUvRcU7zrMNwd4arc9yE6Lrer85ARfOUkHXVrvumL1xEtEyCDoch08NgimAgqvM0zJNOhySl+B4YLHhsgnMkkkZjbZg5BDJc+bDioA0a5xkxRkYOMXAXg0NnM0jhVTj7yuU3z+id7/31D7/zl9/7f/6vP716oVqgPQtS4G46MBI6MQAffdZicF/+oFatewzcrOJvAEaori6lSFXmLrb4tuKJDLjU0gXdIVycYA1wsZNAqfErBBRMzBRPJhpLtuqbbQkAoDGZuvqoWGeeCCizjuTYdcIIz67SP/sX//pfefyD3/mtf/JffrvpH//uh9/ev/vy3/z0L7745Onmovv44cPI8P0f/vD51ZdN7NRmib5vNg8v1q/OXjS9L5aJwHe+mMBo4EnRzIoVQwZi51zl5EgpsLsd5tnNSfpVRGBGLTqrZdXSrfu2DalMZkPOuZRsMIfYBe6QsSgchgEQx3GWBHeHg9nz6M+3l2e/vXr0f378JzYAlKwkRSwnAoWaQgomXdMOeVbLAqqWQtsLskyj5AIGwXn2pDrXMaNjR4hY+VNm4ABY6zxKpZokaJWe161VneYZyP06t6xOC1cAEKotIzKwoBBSzfpQVbKa4WyqisvcbAFnjJdF+43B1Zslb4E7iVGqx3wB0ADUMDlCdaRg8PjR5aNHF3e3O0eroYy7fXp1tXt9c9ACjYfYtCFEKTgOw+3dIRUJkR2QjflwgL/7uy+Hw6QZtufbdx98nKfPj8MujbmY+aYFgTnBlGWeQQUhAxUgJKFiJAWSIpAHQAdkQAaKRgZMimoFVAsCoIKS3j/Z+5YI3kRnG7yxcF7WWgQkqJ97W3jwVsAEnANmAAHNoEDswGLeC2T40fc/Cx7f+bA5X3Uvdtdp2KFC77eez44j/OB730lHUkFyWEybJq426cm77sE7D9558GjKx93+5vbV9Vwg9Bw6Z1ZU02oTLy4efOe7n4a2+MjIkHl+dcgqcPagf3R5cbF9gIUajqowHA/sjEKZZAKcKbi2bz79/Omm3zRtu3LdLMNxV16/mphA5qnrQ991nss8C6SUa1OKxRCVFbyCL661DgEVJE03+2ca1w/ff3Bx8WSz3iASN7LeRgRW0fEwlSxQEiASmar5tnXFitBuN6dxVLGmCaYlF4ihlVYAAHUfPMQQmZ2IFQVTWHXbRDm4hoQsic5ilqkxyPM0l0dn55rKbUYXeL3aPHnweLs9Y+dUreubcT+iIDJ1TeNCawBTmq1Iu2r7ruvaLoSw6deeI4NHcAI2Uxponil1qw4YDVRAE5R5nhlC47sJsoEaadu27GgdVkA2TOPh6bPj8fjoyaPt9tJBJJ6JyPnGEYcA3ofacoMAGXlygb0iOtc471XQk29cS4ibyw0wOiJwsLebL55++tmzT3/+7OdDGcOm3VgjbIJ2mIa55HncT/OUMzgPMXgwCH2XpuHFK/iLv/qry3cefvXjr56dXb77zkc//uF3y1xmmbq2PV9vJKeLy4e/8bWvlhFf/OjQBDATACvZwFBI+ov1R994f/soXt282O3vlAG9NQznl2cXF2fnG7ICef5sd5fnKZ8/PAMDNcmplFzabRdTo1Iis49Q8pwTMAE5Dth65wEALCfLWgrUkXrN8Vm0GoKEpgYEqHDfMqMxG4ChKoACiqJ7s5Gg6pi94D3wppE+7UPq9Qio1XNL5ETJqiQrQDRyWPEePA2uT/sYWPLH6nX6llBv2QWcxIuqogs99qQbhCpMPokHa3tPYGYnlgZRDZWvjltmUElWiysiERKRYU0iRyREQmZGh4AgJoJKgMCASCZGnhGhZEMDJANVQMMK9WPF9w2IFBXUVJRrAAcYmrIRAWTVbILmiByS1D1mFhNDRTYyAxZblNgpF1YgpRA6RRrGmwhYDGbKsQ/Di4QR2j6a1yEdtFd0EEJALne3x3Ffzh9s3n/wEZT4kx+/+tt/8/NhhzE2BklyZRaX5bwtE59FgrRsMA1AgRTrkyFEhUWSVveSVvWSuIiRrLYuSCdJKhJRtbyvMmoiIEbwrESTJEgJUbctRoc+eN/4OVPQ4kJs2qZj7R35jXfF9smudoer3e2723dQjLX1hqyDKjkUXl73lhk8ObOiktnEijMgh13rGjUG4tpuG4hAQShSYJoJLag45DaEDbowliOARGoAoAAVcMUM1IEWQo7eoc05D3PRzKYoYDpNw263uzvcmaqIMHOMEZHNIImcbbdAxj6Pg5SMt7f7pofjnBDFRxjmgobErCag0PUecbGT9F6a0KqhqfgIXVuaVttk4ywmJHmUarjR9Q1HhpyP0zBmA6IQIAZrJ8mlGrdzpJTFBFQLFKx+/AQLY4qqBxySUsWLlQxVF4YTMPTn5zc2FJyUsObhsJpoUbsf56ksKWpE7BQJpXLPgcSqake1brQZ2KzU9GVcHFNqkgsKKlj1zTJQMKyQKZ6qSMVDCU/6tuVGIAV27PzCHhVdspWgGmKDAhovkEadZBqCkQKe0KhaqBBP8JlWctIpwm9RCALqwkU9XS9QiKsCUoGgZhajR2ASWmCeCio5ZBTLObFDIVBGQBASBjYlBFIgNjaDjGp1HGgKS7hdLZNS6/Uyc73vSu/ZRqfZQm2zlppcdx1Wbweze73eCYXRWqorZAaKiHbCSxihTmShvhZoKlny21wnOR1C/cvZFAwZ0dRAl+FEZRpVnzOApQ2v3l2n0r4sNPe0qforbwhcy2qAJzyv3pNPFDI+PSP7JSrW2w/7S1f+mheXc377UH49JeNyUdU62yYk0dPyWfMLFNWkqKjdq23hNNxBZJSsxdRMGYkRAZC9Y3KGaqgF1dAMERgAa/kupgRkisJEVfwOIIYsZoSgpQ4tedrN7370broqXz59DjPABB6CJ0+FuLCOwDU0qmCaNenRlaMFo56UhZm6rj0ex2F/iJ4a77LgPCbf8CqsJcMXn3zxnau/gWNdKAAEwMHDR9sudu+cP37/4QfvPXr/i0+ePv30WRkldBECprlQA2kuCGpYoxVPJleVQSBGBoJqCJuuRUYRKSDKEiJPXr71279VeH/lTeYoAAAgAElEQVQYj1NOsWvZB/A2jLeT7B+9t7l+XUS09cGxJ3I5lymNVUj48OE7N88+ZXSOVUnImWM2hXFKwNB0nQKgJ4iwWW+aVby9nvOcjqalgGoCA+cgNtR1EYOr2tH9tDe1LLNoYXRNiOtH1Drf+aYLcd1229V61XSN783TWbQnW/i9b7i22wDA7fXd4XAYhiHvMPjmots+2HDbtP2qhyecPy6iyhx+8pMfTeN0HI5zGnOepmlIiBRwLDMFeO/9J9M4soOcs0iaU0k35Xj789c31+tVzDbXZRzNqqAjiBwOac4HlWTZELGM2ScXmwgMgmYqguA8q0k1KUArYkCVlWOkVhM1Gd7GjBVAq7BbAY17X6xOc6s5YSFXPamyUpmLgNPVtpWjgwAAUmTOZRaFknW1cmYQggvMd3fXh/0eLAy7vL8ptUm8zRMcprYJbRvbdtX1zZynq9c3d7vjXEopswggyjwlYkfIKpAzmGrTuBg9gIVAiCJJLGNSRCxlhv3dkC9HczEG//WP3/vZT5/mDNvt+eXlBRgZwuGwG4fBexrTsYggsqFmlXE87PZgGaKHtuV+3fWtZ9IiyZMeDrdayna1ffLkvU1/tu7Xr29ezuM4jhOBu9g83u8GQ7/dPHj0+P3LzTtl5mc/3/2P/9M//eN/8VM4ADCAwqqNjtpJBRIoGDJ5R8x+LvkXih0CVM4I2EIhRrbFqbp2dGCmsEQsnfq+RQdRBaJV118dkAhPQD4uwhADNUWj4BZcigy01mREIzMTFDJGQGJWtZQVShYGZAACY2ALIoIAgDTO5e71Ho7wk7/5s//1n/+Zj/A//Lf/5B/+oz/84P2/9+4HHx3TbbN2Dx4+arvwk581xey73/9RE9pNt92uu02/mkpyCOywu9g6F7IY5ZKmBJqLQZmyj+aYRK3MIA0ktTlnNTCCrOrMLM8pDSHC2eW2axoWR+zGabi+TTAOvRitCLJ//OTdm5vrPGdmz8GePr157e4std/46rcePXz4X/9X3/7sZ88++9mXd3dHrLk8znMMofMQWlGaRpnnVAQcKjFw9MdxNNGCGgMzMZUCZuQcOQcAKqpmaOIjL/MpASKEOkVaJkiwrPVkpqcl6355NQA9zT+sTsGAiZARXO184ERLqO7s9xdErBEMywpb/T4RbBkZITJXJgQCgGkB8rjMQwFRDodb9xDOHrSPn5w9e/EUSPZ31y9efPnls0/3hxwC+Aa2Z6vt+fk4pZcvXx/2AxK64BDRLHv282Q/+sn1Yfj//tE//vajxw9v7/ZfvPxiKgfqYmQGpMNhmse5zAB5sXYmRCEFZ6TAROSRgheEAqZFEMFImYjbWAAlC2iNTgUFEbnf7OLSbp38WdHoF1qAulM1BCBb2iyEkiuT957AWOkkNhYwePH5zYurm2//w6/97h9+/fF7D12Ph+OLYcqf/uxvX70Y5hGHO4UC1BAgzMN4dzPOQwHG9aa/OD8HlH51m29TSgc4DPMsoIA6tQ3/5je2Y8rHYW5j+/HXP/4vvvIxWzhcDbcv766eXb/+8nXjGyZnWsREYIKgzcavQwdKX/vwt+9uru9u7gw02/juk48uthfPn1/PZTad+vV524TDOI83t2meshYzCIFDdE1ww/5AHvt+3YU4H4fd7fD8ap84rc660J4Nx+n1zcurq5fOGhUbh9kUVm3fdi0gt23TU7+/O1xfXc85MxAozMOsokWAwXWx3/Yr5y68s6aJzgU1yLmkOa/7bXI5+iDFpjGVMWcdXAEQ62L36NGD4P34aEhTWq83jx4+djEoYozNZrUZ9sN0nEvOzjkfPBQtIiGGrl+x4zmnwzh8/uVTZtd2fdv1PgRyhEjckIIOedjLnYkwUhcbQJ5tbLgxsI+++qEDuru7yyU7RBUdDqOI9f1q3V3KspsmK1a0MLL3rCLjOM5zDiG0vte1NZY5Rk++cQ0heXZmOuX5rD/Llj797JMf/fSH3/3B9ycdIOL6cutDvDvuDof9cR4UFBi8923bOpe847Zdfe+vr588io+fPH78xJ4+fflP/7f/449+97f/6D/5w29+81tpGF8+u37yzsNHD843Z2dXr2/7VfP7v/8fNd1q1F0We/X69ngs7EAVzp/03/rmNzcPVi+vv/ji6dPNavWb3/g6IfVdj8pMvl2tP/zQN2H96tX1sB9efvmacBFzAcNx2JuJC46Rur7d747A0EQfXCRqEFCzQLa6SydHNQ63atqx2EmHUveDdfNw6jqUTNEUbdn+ncY0tpj2VYlKZVLcx5vZgmkg1HSq6rkl9/uj5eYKY99LRd5sIfDkUfILQ+vlm1+63MNt8Es7E6wj/rpAv30vXFILDQ2AASvTf6ntdQ7EiIxIJKaVeoAAqkpKRvDWDsqg5tp7MkKg0xBCAY0oUn0ljEDRgFXMAJQRtTpEO0BG9GyERUwIDNB7z8QuaZ5T1qJW5PRVoPjokaEoVBJJlnQ8zp9/8SKEF3bEcgcFkl/T+mzVb7vi8wgDGTStI85appvX8hvvXbz/8EOn/Y9/8OmP/vaz8fNMnuOqAQhzykxau4tKFMY6q9P7PWb1a6mSQrV7K523TgrRwndZktwB4RdP2YIDsilURMDMMkRnli1nEEMHgMbeNzEQsTGwD7HpfPCeS9s2oTTH27uff/GcbXr2xSf//X/z3wmIw8DIRWc0Fz0CEGFUR6rKSITONy1b68ibFYbgsIu0ubo9Krkic5rmeZpKEQJqY981mxh6H5RcMssp7Q2X4X6FS4kt5UksoVPvwYhur+5eH+5mtdB459w4DzfXr69vrshx368uzs7NbM4FjHLJbdMCUZE0j4fDYXj69CW6l0pMvmVPZsu7MaXCDhoX3coHD+uVlaxtt9KSADI7IZJ+FcYSE0Ca8zwmLdC34cH5OVkMYdjfprQroJN3znmGhsGXllsfXAh+d7szMXScxgyp7qFdxYxPntALmbLydioeawbA0LXtpltdT7OBaRZNaspWBBCRGarW9OR3B4TVXUGzVfu32joDGjtGJAMFBCkFDAM4AFA1KTnlafmk3dN/7ivC6Y1Vb8LT1fWzbmYi4j2Zoomc4rEqR1QrtYcZEclO1KTl0WopQiCPWJmhxqYGzky0cvCXekWntNL7Jh+XIyDPoGoExgh0QueXvIh76pfNMquqiSmZSSFAAa1qZebFjlVUioqYIhgSkYHK4iT15qDrU65n7E1CKmDts8xAT1GCFcs/4flmUEF1AKNqvQVmesovOqWHQRVPIzK/cVs3NTBEMkAy+xVbfTuBZ/XwTkWzxmhUf2szA0RVWXY/eC/bRAS8N8xSVToNg98+42bVhx7eAHZLo/3vvODJ+uo/CK761YsTOdnF/IdAVwAACCkl55z3Hrm+DmyABlrfbia2iN6X1I96NokYiUg9LcLPk6iWCNhzDfs21Eo+AkJgM9RiyKZ19h6apqgaCnAN9wWQYpMuieB7DBTJGGaABDCDiWoWy4pkLCCjGKGiQQAoUCaYDnNznDWIc75puxDjOB2tpCSIRR1RAIcZdaC8M7gFmAECND0iUUmad2WHx+nms9ftdXRt23cXjy5flatUMjNTS4WzYV5U6NWBkhEYMAB5AocLnI42a5p1LhkEtVm1Zw+2/TknLWOexnwc02RV/+2FnSnMqy1Ps5+m7NjMCjI0Luiybzcj+OpvfKhFcs7zOB+Oh+NdggLQQtOE2IVxnnJJHByygqaSkwo4UA2GaJttyFrQOQNL01yqp1/JTdOEGBEa730X20DOY/CKKHK8zdPt9TXsP3z3G8f9eHt7+/r17rgfJUHw0Tl/2B+Ow1FMvPfecy5JLXvfBO+bpun6lY/x469+JZckWnKe98fdy1fPD3k+zvMxzWRQcpGSiggRtV24uIzXOKcRxmEv5dBvFz4jkQmo88QOaAIRNZvr2zAXw6JFBRBEi1pSQO/qTBCQ0JTIFJGJHBiZvFkBUE2luiYvmTkAoKBN7w1OFjlkJmAmYMpsWiCxGuamXyVwk8zDuMPsAHNsQBX6VZtS7rpIhofjXcopjfOwUxCInUNPJYsZlKzFGxgReSZF46J6fT03EWP0CJhzng+JENhhG13TBGbOpZgpImnRnIVQ0IBYEcARzNN8TNM05AcPn3Rd7Cw0TafJ9vs7BJoO43Ecg+ekleuERCQmwwA2gXewXeH5tukbZ5LSVJi0W3fJymEYYwyP33nUNn1K5fr2ahjHaZ68cw6toW2DZ6vwqHOXww7/2f/+x59878sXPz66GbglUJMccO5ypiIG6q12pAp5NgKnUO5rY62XVQ2uKtWGFhd6cV1mlw8DVCS8+srVX0UwAME3+u37UrogIjXsFhBICb0BamWsLDNjhAXkAoVa2dEUpa5cCoaECCYIjsC8qaiiY7feOtpSOpQyTx7hz//i73766Wf/4B/8wX/2n/9BG3A4XLtGP3r4Xuvd65urnzafeDWZRiziGV9eXRcLTe/a1brtY1+6lIuY5pTRwBRSKuIQmULni0kdzGTRaRJVcKBQCqFzPs6TIqXQuKbpVYExpbqCWpnn9MGHHw/DqJKaGAj49voKLewO+6fPvwDjb/69j9ZbLzbaF8c8454MiUMMsWuaPhwOw2FIRSEwC0jKEwkZAjkHiCklgGqlCHDK1ap52GbgnIN6cyVl1akbGTm0k9vBqUV665wt5OjFyrwuBIhgVd5eGyM8bZiwIp6wNFu1y68DtGXXU6X0XO9f812q46gpnNRAwFjB0DTO8M2v9dtHrDb7qFe3V7d3r292L0Vz1zN5y0qx9S4yTCYiiOTIS4FSRCbYtH2zoZz2t7f55Ys7Hz2Qi6GZbVJFRIdIOakUAARyjsxhAQUBNljc3ZCjJ1eTGQQAqkunYyDPJs5Mixhw1eqg/mqX89bn6e0fK6xbw4IQ0IwQgGIrpVjO4IicBzMt4gggOGDftn5/s//sx68vH/YffP3Bo4cXr66Oh3RIQ572sF31kKciEkMUs2GYYIbbVzefYFlftB995XHfdh9++OTi4TClPI0HH8UxtK2TMp6fnz+MrYuxW63XZ5vj7nC8GY+vhi+/eP7zL57ZK/AdRd8Mx0EV4hq2lxtFTSntXh/DaGJpvTnrVmF3uB32eX83gwXQJIVzMsdYBQlqKkXquBodGKKSksfQOP//s/ZmPbJtyXnYF7GGvXcOlVV15nOH7tsT2c1mtyS7SUgibdGAJBu2ZNmyXwzDhn6BX/xX7Hc/2w+WDU8aIAGmJEpsS+LQTfZw+45nrjGHPay1IsIPa2ed200KIGAnLi4OathVlZk7VsQX3xC9SlhtOiUlb/v+5mYXYayQIQEyBka7CF3bbU5OF4sFyL15s1fRcZjGQwbAkaRIGgEHeHgX2aiNnqmYpPGgRJMRlSLTlB6cL5yOZCS5kI9t27bsQ7TguA1NE5pF254uN9ubrYLHfrAhkXeBg2OO3o/o94ddf+iLZFWQ6Xq9fvjwUds1UBwO+5evXo/j6LwHbEhpGMZcclH98le+tL/Z7W62eUyrRffO03fPN/cePnjy3sN3I4en776TUwLj+vKqFHEc1quTpuvKqM8+efb+O9+QXFj9OAw5F+/cyWpppmM/iIhj3zbR0ckhDWpwRC60BKvkiHbRGHR7uH326tmHn320O9zsZbh6c8UxnJydCCN0MbIcxgOBuq6LMeQ0qYqJfumdhRlevXjddAsXHHblk8+efendV1/58nvf+c53/97/8nfvnz9gClKUSEVksQrvvPfo2/tf2R32Pn4mGYvlkkBn5+fvvfv+JP31LiwX4fGjhw/uP3z58tXL5xeXF9cm3PAS5qQgZ3XOA9AG1avaR28w8pxLFikhxs2GdRYMsmpRQU6pSAEjxihFjqQKghJ7WE3HJbK6m69i5jqCKFXhPNSKWe3Y6Ivr64o1z37ClaYKRvXGO5INDGaoGtUjCDZ/7y+cfZUnMF+W8DbgiXBETjCTXWm+kB0/daRToWoW6e1l69FMd3TpedQ5UhRm3wiG4bj+YRhsvp6ipkkQ+dn7cM5q1JIhtQ1wADnzVVkIeHg4DlTdvwRW67nVMFlHSlDAeTKmyswSUTGUXFTUBb/ahKFnmwZjNSrG2ViA6sloJ5vYxhC7EHysB1oZATO0gOHdrzyJTXCRD2V/GIuotKyBjMit73Vfe++b/XX59Kef/+zHn6dD5gWZyGF3CMxdtxzGgYA6VkJNbF61ATg+g5UUUGfyupTB0X8H9c+v5fvY7dRXeLYHMtKjQn921KGqHGcBCbE5Q+MQGnaezCSNRYza1Sr6LqWSNOVJXMr9zU4O293NxY9/jL/znzr2IdCaSCx5ctFTMcCDwVFZATA8+QiNpNVvsiNeAVOjcT+kw+146AfR1LZNbNtFXLYxhkBM2WwoRUGZILvDdX84gGm5XLSLpsgwyejMXIjElvKw297sc1mslstuoSZV3WZm3rvNZk3k+2EYxySQacocnKqKoOQ8DDA2uBK73Pi2CdXkUaeiXtSFQDB23C4cIy4WvhRz7Nghl8F7DpFX3KbgfFAILdq2WToUahZ+sWnWiaYDSs5Z1FlabZrHDx4v22U65FfPX5ZM3pwLHmaaqBQlI6eoC1Q9voweas7V81gNKCg5Sy4AkdT+xBw5I/J+Zi9V+AtkTFQqz1HMyFRFS529hRypmfv5o3+GaSAiRYoF8FxB/s2Ygx0/S0fOSh2UxHTW21UlGvR4+SrYoiOybUZmJEp6hGzgw4zFmhHNuZxkwOzyd7eM5LkS0cw3xOwJp2wwdYoKbVO9C1BbvLmIgchgHq6mrTNqOJ1Bjdhm5YmKmALO7uCdOSzoLdwzY1akRb4waNyRoGBm0NnYq3Zjd4xIzCAdicEdIa1645M70lN1ro1VzWezB4aaEcHuBpmffxAdzfkxQ1LkaIbz7jYWZnYnwpsFLZUcoPbF6n1Xt4/qh+N1dZZQMI5WjDgSzb74qxyhK3wBw/o3vpn+DA8/Cwborv79mRExQkmzbRYbHxUZBiUyR3cYawXzaFaHsmdmJs+QAkAgospVeagggZIqmTklT+SJPNSp1AzJo5d/MRETpTKvbWBQBZszZqWiedj2ZScoQAIGaC6SjYtXpkW3Snkqli2AAmCwCakvUnR5svRrj0iNTNETSrKUlrHdLE+8+sN1+unvvQLgNJAjE023RU0I2OaD92GPPoXy4H7wPpzeOzXQ1cWV5MIuTJLgjxm9HhzgooMncsTBkWeBsomRJWRTg0ezas4ebO493qzP48fPPnGtGOekkxgKMTfcrfxCmb24KCglSVGFcbNcNkwhpTzlQSTriBjdatOc3lveL5t+n9KUhUtsm6Zt+sM4yQAupfREVGek0Li2c2TSLLucJwWJqZZUisbYLDanMQRin4dJkhaz4B3IqXI+lOF2zEMiocs//sk0TvvD/na/3w9jNZWakzUI8A5cb1AAgDuAwA5tCML5JJ8mScoZrTXL7pe+8i0LfNXf7g+3CrGi0Xs1m/IApvOzk2Wn+92Yp6ywk3VrQNc2BJSUkyQfadH5zNaEYAIzo1xgSn72szQTEJRUYewq14PJiMiz8wRnRUy0apaAGtAhKGZHMMQIRYpUA2h2YgaIkIEkRIXY6X24qORybKlkS6lnCrGhE25U0bTM7JfLRrIMfW7bOB5GNYKDApzrLA0zy0l3h8nYmZaSTQhIQOO8bxw7NVIdi6J16JZd17UiWbQYiOGJOLAngorCxDl0nc9p3G+zlMR49OTxQ8l+f0i3lzc3N9vYxDRlZGQTGEREVIIjAklB9FivcHbWrpc+cMlp4oD1crledmG9bN97/8H9+6tltz/0293+4uqyFM2pMLwM4enDJ0/Pv9L504//6M2Hf/T8+3//41cfX15tyyI2knW6yXHhwsliHDJATRPNFKSAFZnYO+BuUTBH8OrxWCXW6sZnNcRJ543QXT2lo3K81g2tCu3j4uZIap4NOeoJU2ELRzzLJ8xQvYFsnjcAMB815oGpHr3Vq6DqwI0cBzWXU8qaoue2a+KyzVvsd+Pv/+FHDaMcFjc34wdfO/+lbz+NXsBNfOA3y+Xrr94mpTEJlXK6WHySbpMmuD6mTtj5RSwJmJiMPdjUikgx63xoll0/7EEKMlUeJ8lZGBbMlovGc7fbpcMw3H+wWZ60gK2W/TCkENl7sqLDOI5JUrbgyYWm6bourpYnGw48yO16sbj3tP1avueXw831SK96USIoWJRQsuRk3rUhhiGPaRzYvHOVqKvjNFaQyYioCj7Vqk0XoN61dvSn+uKZxzUMtK6ojjPUPIfM+c9kzmhGIao/wTxNzXEwRxEi1Z1XNXystDomM2HMh0z1NyUmdu7IGUZdcdscBlSxMAFEddps8O1f+aWHT9Y32zdTOXz+/KOL7e2Q9t0ydhR5LOMIYr25urq96XPOIUTngooo0DWrKaNkyxNNE37205dZcrem9Wrtih8MIcR0KP1+lKyBiGNw3BigKhxQcwvMWTXiVaruYtXlq6iBmVxgK05cBur0Bi5USOgL/c5MyHr7kfkfRIy75w5zYxJCI1mQBcbkHJupCjsGyBTBNWh2L5/d/PQHzclm841vPj7tXvQ7XTergXdQxxbSVHRKRoAxHAr06mo35N2DByen5+vNZnXv/oYcTdO0u70pOZ+fnT189Hi9Wk6l7Pt+Srq93F9fbi9eXL94+TllLNhNCyGl4WowhWuw7s42yxNBurm6HqdRt2gY52e0OtWsYvcbSCcpO+7M4n6bgCIGAntXjwkteSo5iehy0ZIoOSRNGaVZxmbp1aerm+thHB48eLjcdPfLEsZkJFMhsyxpmAhwFxcXBJfGKQYPmIo5c6cn69PzEx/4vcdfKpJjcMHBLKdUiuRa28zQ+i4uGhJrQ+zaxbLtiJWdQCW6WJKMmlwXTjfnjr33PuWStYz9sHO3tze34zDsdtt93xtstVy33fLk/PTk3ibl6Sc//unzFy9ubm93h20N/dgddvt+lyWpTr+m/06/PdzeXO9vbyF6ujl/dPbOB+994/7ZvbZp/vy3f3W5XJy7e+uTk2EYri+vp3Fy5KZh2m9vvvrer0SOzC5Pentz672LHJroTaBFNat5OPKe/FSyGZxDyZIlmUMb3OXu4sNPP/zws5+9unqVuSgpGl/YRkkCmIMyXAjMZKqlSM4FpmDXdUGN93069HsOHAMur65//McfPn7w6Btf+9b/rv8jLBwOOUnxnsfpkK5Gg7773qN9vyZvMbZdtyCizcmGQbevtmPabdbr5bJNqfT74fb6MB5yf0j9dgtDDGHRrmITvvHNL3GAqGRThe6H7ZRyTiWX3HVd23Qi2m8P4zSZmiQtucAQfIgh9AeZK9UMxtiRsMRExMrzCGDzjKJqKjY3vHQEjOrtSUY2sykr/bwSEgh8JPLYTJ7AnDalOEJUADBHXh+1PXWpjmoBXb9g5l3wHc4PqsbPM//rjupRHWkAstk7BbgDzOex5+6H3hEL6o9mMhg5Vwdb1HSmOxu++bY4DhQ0j4YKSJHjRTNcqRUeZI55zrOf63dVLRIZvGcfvUIhSh5COpUMNiGFYhoKh7Rwvl02YjmDXTB2VkjJGwKMCruwOTldLTrvghliF5ZtpOJ859sQwTh7fJrKmDEJkjnhoF2D00U47R527nS44R/962evPrqYBqXioAoDmzPxNjmTykwz1WrzeJxzcSfnng/AOx4ASOlINKa7Fmd+Sx190o4wQSXBmMIgddUNAAz4xB6N45a5YQquumYRmJvQrlenzjfb7W476EFGS4mSkrnrg7ya8NnN6wfd03XTkWWPlmjBus/SZ5ijtXO+Tu6lZE0TW47B+9g4OmHoWdxQPmSzouQDnW/Wq/WyW7aOWaEGZYiihAAxjLfb2+1NaELTOQMVm0RGMeOsxoU8xa6J7Ahk0BjCsuumaaGq0YdqNzF7cUJTEc9sRux80/B6Fdg3SlACgxZNy56mXIY8qYizZJbMEFz0MRoZOFUjKctpSiSSQhNj2ywyq5nnYCglC0U9fbCKDcY9Drt86A8UsVx39x+dLZvV9ZubQoCYksbYgmksk+TqZQGYHGEOqve5FHFHAEsTxr4fxsFVRx4QyAV25hlmrGw826MTEZjN8lG1wOZZ640zE81qnAQxuCLTdLxtj2BLZTXd1YljFfgCnEFHk6qqfKz9sqpqqUgVHFck7bhWBOyYtGdWK5fNhNIq+iPj4GbamR7ZQzrzM2xuEN9C5zzXBWYmB0dkpkpGYMCZuYqZW30DsKteuY4MakVJXHAcSKsGp0g1QarEsupHNY8RZq6C/HQsTvOWdHaXU+jcLs237WxpX5+xOSfVzMyK1YQoAFUJDUkCYlaYwcmMy8lxg4Cjq5ah1kazOZlhtsTBFx53BQJHttqxXvBcROZcEIjOxCM6NoNHchBVntadp/sXHz9HoVKdCf2Gt3/7L3w9z7/JFzGsP3nZP/vDz0/H0UjR5E+H8f4N0B7MTIrUV2s+g5nJzy8rMxOzsRmZzfn05Fylx0h9xlFTncjBFHpkbHmA2bwjN59qCoFRNTERLWJF1WpIZt05BWJVY6Lz89PtzW66nOqkwUYNRc/BsfPsFUKOPPnii9Hc9Kcx77eH7qyLTTOUcRqmwA7kjP299en9zb3D1fji1Q12gGebb2LfNQuQ7qd9s4jBxzSl6+F2u9+fn56fnp4+fO9Rs+4u3lyMY8/Ec2AygzwogBsmT8qgwOzJQDBnZAQxkm4Z7z88P7t37lsaSv/65mJ9ugwdF3VTmZL0Cluu42a1ySnDcvQwBxEQkukAFpWUc4ILw7QXLFxct3HVrdrlphUtuYiaOe+msm8W6oU8FSY4j2WHs7OuW4dpGr0ndpHYKcCefcq+CbH1JUnup8PNKJOkplhLQsTJ9jf7m4urfpcoY7h4M/vyze/mMLcQjkFEGVAxAzNicM44F0l96TWD8ff+z38IBhosTwZF4JUAACAASURBVMPTp08++OqXl/dWD+89eO/9d7pF/OMf/QH7cLO9kpzBCE1crJki58zs/LpbA4itMyo5TykdmNs2cHShbRrNpqokphRCE+BmeAKmhTIz4GdFtxlXd30yBzVRNdXZb/COQFv3mQAYWQo57zzV8AJxohCzQo2h4Je+9V63CEl6wRQCE7GQiqn3RuSmaWR2xFb9LdYnJ7fXvTpyLedSkOEXkcFZiqFklWqxKUWVAUOedEDywZtxE4OqeueIZonlzIgEAoWu60BIaQCsa5lhWqRryC3WDHv69OH1xXB9sbu+uCmqWjSrVl+jQnAgR9TEQN6tlvvzhlbLdr1uojdYagI26+WD89Ozk5M2xtOTk8Viddj1V9c3/TgOfa/qNdOyWZ0tn757/+s0dX/8h5/903/0/3z/+x+NlwiKBkEmpAznF86126tdKdauVk30KSeRBMwcGpirXReBGb7W0bk/12NXe2z+cOz66o53Hhdqn00AG8ihannrqazHPtGAes4ZKdNcyGBiYnIMv6txP0RkTMYwEjWtIS8VQlMDkYg59iBibsw0CUmfYtvwsgGjwJPi//gn3/9H3//+X/61L//Nv/Wb739wf3MauuWqWy3+3Df55cXVZ89eiPcfvLd59vLy+pBTGbfbG4SoCEKCxjkNVPMRAYCEUESaphvGQUp2PkSKImWa0igqBS405JRyycnYQhupbbuckyNzrOT55auXh3GfRlXlxrvl6syRdyE0y4aCXu5fLBf+0XuLbBsK2k+HaZI0TmOR0svqdG26IwpEruo1icHO33lKzv8xC8DFREVFQMTkjoQFmCpmyUhNVMLxUKVqCH/s5ueuymBEjqoRNObD08iKqTt6aYJQM5LNAJkTr4iIHBxIa1583bk4OOecDyA2g0HnX8fquTYfYkR5KvLB+6uv/vK7p/eXz1+9efHq04vrl9eHXtm5wGIWAoM9nN5c7G52gyrVdAUIB/ar9aa/3m/7vvQJGT/+0aui6Su/fH+xWGmCiHbtYne93+6m1ENy3VbW1JTK61YIlLQgk5LCxKrN6HySE2gua5mrnRsZjMlGuZtzABxrGdPdODmf8ARi6JFTXpvqIo6c+haAJgURmSspm8LUDgYPP+7Lj3/0Kmn/5N33luHs0TlyztvrXdm7RbMw5WFICguxYY+CSUw12267B5XQ0OZ0sTjpzuPp+sSXKT169PiDD77C5l68evPs8+cffvLRfuynEWWEK0AhFLMMJiL2dVXmzFthESujOQv9No+GfncdL9Gu8OQdGg+2u0lNt0geQz8Z2Hk2IgfHYebXTXkaJlmtISqZxBMLiZmyGaB96hV2n2mxWhQ1MrZi2+vdcBiGNAEsWa9vExuij13XpJSh0i7aB4/vP3n8KE1T8E3JZRzyIU2mpYgWSSLKTM65xoVFt1iu2mXTLbs2OE55mMaJgFXTrNqFimq2pmm6bkHEJW/Hw5jGxIbb21szDTGcL86atlutVuR4zOmTl5+/efPmBz/84cvXL9XUN44DZcl77QdL5OH94na6dQ0vzxfqyvbm6tnlp2+uXj97/dmyWznj0PL5yebe5v6D8wcndhpCc3lxMQ1J1Zh41a0sEwh9f+h3B8DWi2UbNt5FAnkwG4PIc8wwp0xMOecsuW3aVNLry1cff/bR84vPt9NNaBsj6hYLAchxmgbBXF2VTEpJaRLJjY9d01z1B8CtNk3fYyrFOTf08urlxZs3V3/uV7/7nW//5sMHj4jNe16tW5Dd3t5MUlzwXRdONovlcjmOEzP7qLub2+3+arloHt4/N8Pzz1/cXO3HQ2Z4MkEpMCQpKONuOHzn175SdOr7sR+nMeebm20pOk5T8DGEmMYpJ8lFUplM6Y6yXd1dawhXLXJat+nVypdcHTfvJgPArM5PWp+CWRONeSSoAMYsiyHMvGAyY/MMV8ttpdlgHovrrEHzUWd3VJ3jw6rn+xE3mvEru5uP7sahP3UysLkxmkkJqEaT9dCsesS7ideOIpt6DJMxG5xR1b4dP1eLPbvZxJ0dquKbiQRqWmdLgBVzrqOpgR3BQVXumNfEqOFhPoa2jaKSSq2fkqbsGK7zJkULNFv0Ua0YCbFRUI4ISi5TBDw7F6lbtk3Xjv0gyZq4CJ2zQm0Mq+XSRSouTXJINmUawLrsmnUb76+aByenw237z//FTz//8QvKTfRtGgcbzQcXQ6PZT/2RYVYpFkZz5NpsTWOmZHfAH/0c7cDIyFENFcTs0E3GUNIKgACoolcxmanIVA9o9oGtIR+pC6H1LsIoZYI4CsvlMsSOjMbD0B/6fT8mSQ37RdOFSCyHAP1n3/9Xf/k767OH7zFcjCeEIeVdGcdSSgx+0Z2wVSoUkwFqrMSIpg2sOWljdMu1X6YyOkfLkyZGX92NCnKxbJUwR2pgZnjPbRtj9GpSJ8RckvSFA9p2ce9eWKQ0ThMzNU0kWhUppWTvXZpGMxIR79j5Fk5AmHL2Ttn7szMJTVfU+jSlkmHG5KgaBNWukkytGJQYqUwlZ/OBlYfhUEo+jFPjaLleoXPTMJApkQkVc9auQ2ia9SauBxvGlYUBkGHawyzpRB7m61pNAEcu1NEVpcy7IyLUJAMiLXosE6YKEyNDgPMVwqw6QFEtUBU6vsgMMycuunkPC2NAtO6zTXlOkcCcrE42q1bFREHwjqlUetMdhP2n3Pu1iybAKo/UTKvm1/s5Wscq2QnzjrmqJYjmgL0KLjqrWcTkSUnZz47oJFSjDUBHnnwFy2uVYKq51WAwE89AeDEFoKCKD9mcHcGOmBw5gnPkfHSAKCl5gkfRokng6jOgMJ19QFHLqplW0/C3JKb5+aCZ4lTLstmdFJCO+1PGHNJav3vOkDoaZ1k1RgIrDE7NqFqqQGmWGdQfZJhVQHBER+qZzfPL28dbwPotcY4IrFVcbVUmYkaqpI6O+nBAZuUK6Asm7vYnHjgiYnaUfQFvjxL6ud+lPn98R7z6/wXD8gDAdeVztK+1+ZWoP/PuhfnFh8EHVz8rIlKV1AQfHRszZgySnavPjkFASuSA6sV7vLQDyDEIHNhF0WJW4M0cak5f/cvlSJ0g09DGUopShmfj+mYqnoIUQds+fvzk5acvr3e3ECCD5zgORoFC9uNts17ENpjZJJMTH5aeI+92h8Whi5tmymkYx6Vnb+ZDWK9OThab/nW6fTWBEKllDWnMUqY0mmvdZrEhT4eLQ0klrAMR3+y3rg1f/9I7p4/OxjKMn+11rXfkI3FAUAm5+vSxI3XOSM1MIEqCgMW97v6791cni5vt1bPnz9k7JQf2BELWwyENQ2acb07XN7c3WmzRtG3bTlPq+z5NexinpKbGEefna1Utctj3KeTovQshMMsw9I1r29bO7y8kSx4Tq8SI9RqnZ4u4iHQQU/Psm6Yzx37w4zgp2e52d9jnPGjqsQx8cnJ+ujiPFnJJhzTlW0y3gIANWtkKcESe2UNVSkbBPPp7Ds5TERMTkpwLBBRdu+iGw54jEdHhKn94/enzj96EE/fBr3z5V/+tX/3lr/7yy88/5Yirq4up32WDn7wLbFB2vFyExnuAgq/OaMIERhGFYw6OsqojZAY1ITZhhqtmmm6m4GuMpoFq4KrV7LJS5ck1fcKooihc91hwBHEwUYK6wCGwqWUHUQXq2xhf++UPhuH2+Ytn07Rr26ZpQ5+maZqyIDb+5qYsFty2bRpTLrltWxUZMxZdJ6IjphgbE4UlMXPw7KozhDNT31HJ2h8mxGndLTebMyKbpmmacs4HkMbIznvJyblmsVgy8cAMhNNNszu8ijGen5913aoUfnB+tr3sh904HXSx8cNUYPANQvCw0kQ/RbdcdW3HkvpY0ETvWaZxKKUsWyzazclqdf/e+TiOF68vvd+PwwTnmtCYuXE/lkmevPv173zjL77/9Bv/4H/77f/rf/oXP/yjT73i/GR1dbGnqZgALohkkehjFJ0IwuxVUkoDOyJSx86UqQrgmef2vb48ZmbGM6OYahKRHgMF5xP3yGqdB4CZfcM49tdf3Boc+TpMBAeW2vOrzTqyuVTOZ3rdL81ei2zVPkHVoOxDKFlhYOd9CCommqcyoQiAaUxx3d3rzm6317/9Tz6+vd7/9X//137r3/u109MHwPT+o0Ue+YVeLHxz78nTH65/OuarMpZ+f0uxtRizgYJJtjIkKoACbCml1I+Pv/RuP4wyghZxsTiZpiH1Mmxlu83OT2f3l+y8FBKB985gKQE0Nq0jdof9SOwAHgZJPDx5cJZSvt1tY2suLHb9m8X6jOJIcRC6Jg8qSShl8QrE5oEKcikGlVFI4QITXJ6yFoUPd8+z1UhgqTt2cuzmdkpra3YkKNRDCiQGscLHp/ztgsuAWRnzhZ1/NT8zQe2bAa5wLBFU7ggPVntBJtKj1wuDHXMg5x1AYqQKqYs4AMRqAnbkC0OKoFnK5t4iLrhZ+BevnquVlIU6n1X6cWTXNl0UYfLadY0mVqFpTFrQxcVuu09D8mi5i2hzP477QypiixC4UHRxsViiTNsdaIAdUEIhLz44z5yLCiRX0NKUdJpB1XmnigIjmGdXKVqq8J4rClibprdCIT12Lm+3om/PfiY+pkKDgDyOTdsx+zRNZRqVg48BJORdjE3OObgmhiDT+KPf3f30O59+8Evvni75urmxUkTKYrmJbcfusO97KSpmygqzKeHi8mLf88mmTXLdpnj/7N5quWzPNuvFcjz06+WpZtnd7C9e9n3GeolljPWNowb41PglPDMF0ZL7ssV+zP2oebVcOpcbH4rkPME5bK+ny9e77R6LLOw0jwCUos86KeWma2MbweARZv0w9KLqvGvazqnrD/3+elDQau03986bdnk7bHe7AUoMRxyazkGRUk5lXDau7wVmamVIaRH808fvfOuXv3nv/PwnP/nJRx99+uzzz24v99OYnDP2JCIi5hwZy2/+5X+7a5Ynm9Oz9Ukb4rDfqwwmcEzLxer85HS/3++3Ow/nKajq1cXV9c3N5nTz6OHD7X5r7JrYrNbrpmvg/TAenj17/q/+9e+/ePHcmBQqKp1vfCRhTVwkaAghLpqr/cVquVwum7VfUCz97kDFN6tmc3pyeXX1g5/8fh7k29/8tn4VD88ePnn0Tmjiq2evx36KkRqKuRUz6/f7/tCrap4KAO+8dz6GGELwzgMkInUZrCpm2rTN69tXry5fv7x8eb27PqR+0dIoYwFx9H2ZXl9dyFzj1XnfsO/ajqyJ3rdNd7sbLy529+6fd8v1ze1ufxhRoAU321sY/9r3ft0Rj4d9t6KmoyRle9hud9fs3GK9qoFrl5cvYozLlS/aE5XNyebxk0eXb27evP7R/jZbCZrlsCsECk0DpSKqKRk069RPh/3YF5GL29vKgVl2J03TvXnxJg+ZvbNKbAgkZFCISSqJZgEd7oQkNLfaVDcmsMrwrTSsOk3NHKlaPHEko878DNM7AaEePeCryzmR1fHOyBSqdOzuZ/OKL2gI8VYH9MUP/bx06OfQq7fDgf3cpFC5ZLgrSLXmHm3z5q83BY4eGrC6q64d2OwLXBnxanUk9d65wPDMdQVKYFQFg4KtsILhHKmoKRSFiRSl/ryjE4Qyu9C42MYspVBWs+p+LcCibZ2UYRqDb9ar1e3NdZFJkIic8waQn1AUMZLzgdnUyjiOh91wsiLNRTILtDRSUEg0cVLKlWzbeO5c4MnKLl18Pnz+wxfIreeFjBmioUF0HoUkE8xZMYPc9SNmRsRMXBNnjr0KjKFmx/NtHl498+wd5irdiIUM+paJU72x73YUdaZ2nr1nNMYBIZB3YDVFkQxlbbuGyV1eXl5e7W9vx4kUAW5lHEP13+SI3/2Xv/f19777wUMOaAIR7DBmsIhMYqSBgjlWo+gWiCtNDXMg1SSckmSZmhhXp/eIkSWJieasZs6xGsMCMUhMLRkj+niyWq1OVk3bDqmvOWc5y5RT1Nh0q7iE7/tcsmoOYRGjVyvTNIGo5CyqxKHruqaLPrskpR/3BgTnu7Ztl8splaxlmA59PzQWpJgZvKMYvUFZzDk4LzmXLBMBrDT0pUTpezOfNmdODeM4OA7tuqNkQlnYqI3dIq7OFqBThOmzTz558ep5G1oT7xjSwCZLaYI4dq3znsQIQmJgqFFlWjJZEgS85be0TRf6kHXycKqiqmbQopKFDBBSVQIEBtHYdPA1t9lIHII5ZililXNWWyVU4aSJiEohNQax4wqkw+4aanp7w7/FcOiuQs3+82amCE047pjNtM67lkVmYRY74mr9BGKFZw7EnjgQsZ9rXY3SViPS2RSV7qpPbRFNWV0VyBHYgYisGEjvHFPrTs/PWhlm+IrZNDHCqZggAAwtAiFiwKBWlcr1Au5YHnV2RubjaEGz6LLaLdCR/D8b1+kcpMDHKFhVnU0dmO+04UdrmhlerH9ZxZXuMOzZugS4o9O6mkKoWoE1/MLDfg4gesu/MBDgOcygIapz8OzVdex14XA0gSUSkV9Ar3AEsKqe/Ys/5k+eB3cw0v934tXba5Kbr1hNrNycwi6lFIN59gCKFFWj40YFVYmpcC3PH2H44L33AOcsKpIlAVaNHkIbfc1jjk7JcklJci4ZAWDvOPBxEgWRsSlJ0WRWwEBD7JkDiAFPITrXUA4aVzGhjGlEi+5k6TxLKnnKMD1f3H909vDyw4vnP3uJAdjDTxRKaNBGF7HUfurHMlrLcePDJpaYUkzakbK9/533d9O2bZsyDvurLSf/9Q8etdRdfHb76rPr3bPC1HptXD2BNQmJOVIyLZkc+c4rQyzDAxHn9x588JUvr0/X0zj87m//s8AxNJxSGXPZnC+JWbQItN9NiGgX7WLVLR4szp+cNU149erF1e3LJnRt267Xq34amMwHFklmakrDPsUYTzaLIkM/3nZt2y0bs5LTlEuRGikgQCFRc4yu62LXAhDVnPNh6F1wnun6tjy8t1kvOlIqpfTDXnQCsxna5eL8/Ny5uN/1u93+8uLmYod15xzj9la+8e7763hmA/ZX/evPX19/dFutwdigY73xmNkDzgxSjImdd6oVuxaqeb4yty5HaTIE6honmkGKAPbQuvTzQA+s8Df/i99anjSjHKZy6Mf9zz7/8XK9OvQpBPLRXT7rY4PFqnGRkiTn1Xl4H9uWHfmTxeajnz0rEz84Pfdu9fmnlzdX036fmmYlKiUP7aJtulbUhiG1zaJtunF/OOwPBEBgOXnnoSZZTI5kDSHNtvz6SZ9GLQnsvWfAiuauxb2Hi8dPz7/29fdUp5cvP5uG29CE1XpdzN5cbC+uB1GcrIMIQmg2q03w8fbqendbdreAOe/DOOQiZeyzQtvlgoj6cQcoObZRYxfOH2y6duF9CDHe3mxfv35Npt2qUSttEzanK2Ya97kkef7ixke88+j+6Xln6G93l22DJ48ent+751336c9elBz6vd7cbAlsTNvb7aGX4HH/8fLdd+/F1ikmchIdBaGrN6+k6P37yydP733p3cenJ+vo/TSM25vd9cW25PL1r/3S7tD/wR/+YNjR+0/f+43v/rV3n35lezX9jaf/Db4OGFyCJEI2Ig8iE6nEHJCHkXPOzBSFag4SAxAXvEipgDkIwTsiElVVZSbvAwFFxFTYMdf4JNWSzQTN2gFzALjWdXWtX85XOb6IWJHjkADn2LMLIbAjiRATk9muRRXQenh4OqYikiPhUrQA4Oi9D1q0pAQO1cnIMRtA4MLJ/AgwBEwxOG8iaZjaVoKz3SVwgr/917/11/7qb/6lv/KdZNOuH15cXvzgw5+E5eLDF89//w8/+vjyWVKcPLr/+vpi2a7bGPfX++FyIs/NqlVF2vbNyaoiesFXXmDJKU/DaEDb4cmTs4cPN8ulN5rYldgAkFzGcRxzSdQspVBO2G/Hpjl58+IqZyw7KBBb/Lu/8c0i+0XXPn38JcfL/+6//7sBcHRm4oeeglvd3G5FM7OMqVfVGGMXVwD3hz6nkZwnM83lbpn2FhCc05bh5vGIiYgdOzhiUlEppZSjd0P9koraKEIMplBVqJI5ZoIzdZXaAJ7XP6SqRojOk3NctYamsEwORE6J1FQLiqqCOAYVgxT4APYkYmn88le/dthuS5qut7fo8T/8z/9ts7BPP//p7/7Lf/rq8s16fW8/pX1K7IOavXpz2JyeGje77XRzNeyup+DaEBZWbJry6frk6sUVig8+ljSYG9Zn+It/6Sunj8ObmxdxeRK69fPPDr//B5+6zNNgGGqGAEOVAxZLdpFK0VwshIXzAcB4GFJOpGQHW66XoYn7mz0Mq+UqD9Nh6O+d3Ntf7ZGQs6gKEwVXUx6kZDUVhseM54FpXsCZks1B7tBqJi0GEBSocdRExOzmMGgUTacPmpv9+B/859/7C7/+ravbF7/3g9+7ughddwZ225vDy9dvDrs9SLtVE9c8TkO31s1ZE1tql+Yb8wivXx3yiKePl48fvv/d73zvH/z9f/x7P/i0a7HenKhYmkp/Me0vFIAzSI/gA7MzpeyKUe0xAOB8czLcTDBFhxDpL/3mb/zO7/yzm6sBQOjw6NFj33T94eCjLFZeoFmn1WbBgd9cvVHORFwhmOC8KVRlGPM0pe0F/sO/+Rsvnr3o98Nue4DxcBgO/bhqFm2zyCntb7Yp4WTZPXjw+OTk9KRdx9i9efH6+z/4VxiBdHQILYCDc6hYrgtoW9cnebgJh30+X3Z//rvf/lv/0X9smg+H293NzWq5isyvX7++d3r+4Px8TOnq6mpM02q96hZtP47tps2Sm7ZtF4spT//4t//vjz7+6XZ/23QnznsQu+gXy+6QDm+uX6aU2zamLGOWRcQ00q9/79vnJ5uLN6+ff/bZ/dPzj3767N7Jk/fffxy5efzwyfWbW51k2awih//yP/uv7i0e1NV44BixkqK3t7c5TUz08ceffPzxzx4/evjVr35Vzd5/8qSL3SEdUi5qKqZqamzmzKL90U9/+PGLj3/4sx988uqTPvcULSw61zVqVkwPh/3ri8vXF4dpwqLDo7NF1y48BSZ453784efnZ6fsY8pmzB9+/MoDDvj173zvO7/yK3/7b/ytn/zRDz/7+KP9eLFcuZv99uXrVxTcyeZECey57w+73X63u33//ff3u+2U5Z13P0hJf/THH/7OP//J0rEJ5USaIVOBEpxnItV0+iWc3T9xPt7u9odhZA7eNYvlCSm/fvU675JvGssqmmsLH6Mno5LFzJyGGdcR0yIQQwGZcy4C0Em0FMChGFRYXYVrnLExtBXjaogKUzVRAphYciEghuC9gxEKSyFVqUJDMSlayNkcdOiIHSvM5O2GFUTsHLvqeXekAR3nIuI7/MzeTm6OK9vZOYbN+DgRCL4u56uaP1RORpX/HBXcnj0YoiJSwEAkjgw2c9V1ZKZ8RNfMVAAmYkhdJcGMjDyH4NmRwpKlUSYbDYD3HGMIPgzb0erK3BMcO+fI1ZkSsY2+CVnTlCcXHUVfLPvguuUCwNXu8tGjzba/9TEs162xgtV7n1I2VSY/7ft+xOlqUUaZxmnhNkGDFnHRtZsgi6k7CYfpNg9y2Obvfu3L76xPnm5Ofv93P/mH/+tnsOhlQZkQyeRAKBC1EpAaFQptNitWdaN1uK2UDRxZbLNK9G7ZWt3uTWn2lT9+kIlUWcXPLy45MwYYHGjeYTi4ltq25UaefvPRYbzVNDWwSM6JWS4QdvBDkuvbSQQhNokkkzZh7QnexoDk1b50vv6v/5O/81t/4a+euzXjMB0+7pprp2+GASrLuLjvm6BQsybwecBjKIOS4SqXqwxh51LOIhKbxrtQTAxK5AxWkHMpApmsV56ccwIRlYICtrEMAi2mWZOIFC2CUixNeRTNBs0lj9MwTdN+vxvGvFgsmtjloknyxe7NYrkC/L7P/WGCa0PsfIwgut3dvL56NU2jAAKnzIsmtl0EcNgdbm7TvfNOiox9MsN6tVLl3bBvTzbE1nWN8xiGKYZl13VXb/b/9Hdeph6r6NjJ9hZP3m1yzoGbxi02q/OPf/jJ7UXyYBsZ4qO2MK9FOA0kKcPATCATkWSLNhDIRR7d9OSr72vk8ydnqYzPnz9fxO7Zj16wEBFLP0dMAQDPWXBPvvXO9uZ2PPQNxYbC2Kepn1RmMIoXvDxZsvfDYUgiwZzmIkNBTU6q/7f5gnSH5hzpj0dMYQa2zexOhKjHWAmuTcXx67niVkzFTE2IlYOLbcORBFJKKkU4ksK62HVta8XGcRITITGQSmFyTdc4diVnI2NwKSWXXHkMrBCTpos++lSmYtp2nRY79H2MIW0zMhDQrdp2GWMT+zLshgMIbRfGbYYACSggQaQIdSmLpYKks7CAj0kUREQkpmJqal2zkKIioqJ10iCQJ8/OG1CmhJqiQCYqkgvyrFRwQOnhHRzhGPYGDSSMovOUQUwGtbe7jBmGJqoXOCq178BvMzp6ZvGMeM1ywSouqI87eAcwUTUBqn0c5thBPSKB9CceksovkJy+SNp6+ysBBqtwGI6gGx2ttb74XX8SifsF2KvywqoAZyYYQ6BVx1jPHBxtRIy+aMdVVzwgmJlzzntfvdBKKWaVNcmO/Tzim6pYyRlkZBlEokWoIp0zFglQ3cJb1d6yMUiqkZqaqqA4dkZkIgSh2HoGMwiOKgVRzJQBRyLOBZ9LCet4cn+5f3PQAdwwgFJyJQ66wDFGashFT1ylRFXMCCZH5qYps8I5FqUpWfAM83nSauhamcikAqirHQUsV5c6gYrAUYyRI49j/+rVi6STc/S9v/i9IulwOHz22bNxW271EAkikBGIoCXOHm7Wp+vmpO1OlsFhse4mOck57w574mDGznkzSlOaxpEtOnQwr733btGBGqCxQOyb6MVLSnkc0tDb2WZRhVBE0LFkzSmNKc9wQFyGszVK2h1kWnSr5bLzAblEF7wLQVRvQcmwqAAAIABJREFUbm77Q1ZR78NysTSdmAOrO2+0QZe3+frlbn95mG4SgCrDNlFTrUyQuXwqkd39Q8ikvuOqmeQXkNnjjKkOZkBhgWNypgIzhi3AAX/wuz90EV/++juP3r1/enr2h3/04+B01ayWa7/d7bdbnKzQdRac8zGESD4SMwfvA0cVLLuGGl9K2W0vL693BHhPROYccWxCE1xwJmKwwziIKJkQW/CeFBOocgzJWZ7UFMQIDZkjIovRmW/VVDWLGoDNevXO0wfrTby8eNWPO2jyPqjqNKakKlIcgxjeB1WZpnw5XTM8RJhd01CaKlQisQkueuf8ar00wN1qkRxCoLXdOz/tFq0pTVPqD3kYxko6n6YM5CZ6VRGxqWQpCkEpmMY8DGYYutazKwaUIjDh4AOHtkjTejMTASAmCB3aBp61TH0uQ2z5/6Xs3Xoty67zsHGZc67L3vvcq7qr+kZSJEVTEknRDGGJuQB+MJA/kx+SGPCzf4AFBPFDkDhwEMCJJMQxpVBMZJEim2w2u1ld1VXnvm9rrXkZY+Rhrn2qmlIcZ6OBbuw+Z59z1pprzjG+8V24b3fbddv45Xl3cXF8tFoC4DQldQrGMUrOslychWa11Oadx1/5xh99a9VekC7+8t/+5KOfPoPfgQVjmVgKsiIQIxqgKtQ62AjKHEFHs6BzJh+DgioBEROQGc2h0Iw8mxYZVleH2Qapqn0NazpHJd4DwmypVYu/yglFRANCMgYFgQMXR8GKFDTk4Ooyra0AzQx+fJiQHjr5eiogGlVDAjHnZgKLGmqV5ju0DHUKBsTGnpFYRRADo/ar6Ml+9eHdvxr/XbNYfPXrXz4+OgVcdf3FIFPMdvlofbN7HgFY88miY0dk2rVsJ64USSkCELVBkkJ9cLIaKqoZAKFTE8m220zBOxEfGvNBvecaf84Eytx2XS7AqDmIYwgOCMAHRrAm6M3NbS77pvFx0vfe+dp/9oPf/eWHn3z+/K4kBm2mfdqvRwTwLaEAZjDRDNkMpRTQSo6vGhmdoauHCkjnlv4w7tcDTVzRXtspUqUOE88HpIJpJd8ZHJyFEcF45kmbWZXBzf4DAMUMVXA+37X1PKOadYnQwUqZYeY0MAKIkYLAdtiIjllL6GH1PnTLJsp6TBM63y2OF8dnrmgoCckX0W71qCjc303b3TYVYUb2hDXBBsQHBk+QLScBMRfYezEzZmi7BghyLqWUwMDaGksK6sixI4XouIA3ZPLsKZgpqgkCkiOqLAcP6BCoFpI1NoQgQSzRyKDO3pQAwOrTZwZcI+0LIYIaPhja1AeQAAGklHkAinhIyaHXljc0j91QcRpg0TYvPrl6//1NWHRH/dktrY1KCH550h/l5ViilgkYAQGdOY+GogZgJKUAQNvA2eLs8cXF+fGjH//Fj3frYdUAUdBk05SmfSwZkMEyaAFCQmUyVgBWUmJTq+naoWn9owaqN52j5795mScAA0iQI4x9PsIOIlxd3Tx6a/noyaMkXnJRK33TjqVG0pqBJcl1IA9AwYXHTzlOGdGXPKpgmvK0zyCYwTRPpeSmZVFp2rBYdt7zzd1tHNPt9T0nQCYL81ywmBEBMyHVzHIEQyuQInvw06i/+vjTn//iVxdnRydHfXPuzKxlvji/ANXbu9siQoTn52dN26Qcd+Ouv+iKlPXd1fBivF/fr3dr1zYLPhuncT8O7EPnu6lwlKQIBWAqKSsUhUkg9LSf9m3nyYFvXLtonr73KHDAgOBwkEG8ItI27W8v7/7Hf/M/fev3v/2Nd3+3C/1m2Jz3fYwRCZquBdXQ+JPTk9PT067vavaBmKiZqIjmIpo1q4mQQsHLq8v1blNMfBOCK0Y6+0WIihkR9313cpRTKk3rQmjMLKZJcjHTvmsUNMY4xWTAkEEZSoLnL56fHC12+x0zhyY02gBIyUVVUWEYhjHGMQ2OHRJ67/f7QcW6tpvGeHO13qx3oVrTGoOCiQF6ovm8UAPvmuVqKYKm2yYEER6HSBCb0Hr0uSRFq+n1htJ43zatZJE0SjJ2Fcox0wPVlGpQiNmcL0HzIYMPjMhae1u1UPmC93qNi4KZNTCT1Wa68EzHsnr0YZUVzpVXfc7hoBac8eovtiM4a7VnEcsX//UGE+PwOx42jUonI4MD48cOPRLOfAI7/FBAQgbyhA6NDHmOqzcEAGXPoGhoKqWIWtVNESgYiop4YjKCbMXMgKqqhFDBip2dnhSVIiWJlFxizIaFA4SuIQfVVKT1HToEs1Is5mTFkAAmAADnHJiUlEPv2DtRkZK0aE4pRwiEYIaEILDbrTtYtE3X+jY4gg58S5zp+KTv5B639pWvfu3lR5d/+afPmAASqYBjD6pmvvaSCGhk+KDYnIczh1vwcFln4t7hXZxpeFrbPJzhw4Mg6KA+QiQCq74ZCADmHIFHBSVGH1y36Kdx1FLY0DvnGRm1CE5TKimNE4gAIIgm14JzjFZMJWtUgFzA9X4fpyHGk/4IlQlaEFQ1NGZqHXlEj5DVtGg02UlGZnWsiERYEMwhILMj78ADsJjWcDU2BhCCUjQaEM3mNDA7LBWpJz6bA2IEx5TQ1NCpYg2D0iJSCrNbLkMTWkAkw8D+vffe34/DOJWmCUR+s4ub9X0ulosUS6BaIYFu0XLTkGFKeRimcZ+kwPNnY9uCZ+i74645VsUpkyTyDedk93cbZkZLzG5KkwI4Dxwo+HDWQCqx67o2dFAol5ghUUBWVk8ili0zAgcmdJaLFlFTRGJm35hzbrsbO+bF0aLvl682V3atzuGi6bTovDBEZ+vuw2pBAEOYpjFLrLiwgpqJ2iwpNQBQkCyi1ZkH3wS/0GpmwPx59rA/2BtbAHyRgPlQ0+FDEQE2y1jnNW1oh5VsiIjMyDXdHQ0VGADBBa+q5NBq2A4BIPrQiIglUZWYIyCaKjMD2PxRCMiYJQOCkqIDx47AiFGLQaUkIqAjdqSiaUoxxywJALouLPt+2t3XcrL+lSIGKrMjPr/xlx6IqHbgYRmiFK3Q1QN6VXf4uV49yN3UVEUerjM96AqqTRGZaUWkXv+omhals5/7PEqYLXiRTF5f9offD8AqRWn2DrYZSMLDnl3/oXnXr1QiMtR6HlWYpn7Cm9yrN7Gnv0PZPfxqle718B1v4FAP05HKVHh4B+D1N/x/vtzrRCdEATMzRiLmmp2LPBsC2TyxOHANAAxhJm0x1xFKKcUEyZiZEV0ltAGilCLVok6MHAMZEaJ3s1+NgZnUEQ3aIR/S0cNFsZl5CCgAairG7AGJUB24Alb9txXRiEyyMgx57I97KDbtY9oWZTOVLNnQsKBRIYfo0dBKKZmKkFkGYDA1yZpydIBZUEbZ7mK7WhE3YB4sQZ3wg6EVBEGkOdCXnMyZAVX2qmo2TSPcqZI0fdOeP+4Wi2bZUfCd704vTlKKd/d3qro8X17fX5sT9jpNY7opInGzvwOTZbfExhP6aUr7lM0k5RTHrFFYyvHJanF8dHzaxrRLedcAMwIFAMBMea8Dl0mGSm0yMTDU0Ll+cR68F8jjNDTOdxxq4iOjghUkcN674Di4cb27vlpvtrbs4OjoODjfB0IL3rXEbHvcXO2uP70e7kdIQIIICAKk4AjnnNN6raoUd7bjrMEvNVnGAA7H6eyXXfezqpKuUvnKArA6oLJin3/yahLQaGlrq8fNN979vfV4L2VCcV3ojxYDE0xDNpTuiFerpW/8frctqTjf5Fza0GnBHG25WHz9K6ci9PzTm7v9tm0acoRk6MCRc41Lk5aSMGfTgsSOsRRA0FJUVF0Ah4RI7Ig9T3EyriWEBI9933VtOLtYBs9pnATGKe6ZzTli8iG0nkiNiu6GMe12eZYAqJlmywKAzrtSVFWzlsrgbTu/XHVAmMowTdp1ITT86K1TJoqxpJTGcYhxRER2HLxn59u2dc4bKFHOB5xQwZDJuaZpnVoEYjEtKU0po1m24hogZCl6fNyulth1dH66XC1cyshojdfWQ3925piXq/70ZNV1QVWHIW7zsFuPV682KQo9kbu7/XF/9v7bX//g6TeuX2x/9bfPfvin//7ZT69ggjiRZTKp8gAm0ioWkKoYtze657l6njdCNSFydKBsigrYvPNWRYaKSpkLP1SwSow1nG04DkMAOxzBaIaKczBdbUyJ7MH7cGbuKivUeSVCJYTpw7E0V44zjflgtlSli4IMGJDFREQUzYAdO8Qa0mumoJAFyQQMsRhScYiUs3788d3Pf/V525584w8uv/v9bz9++uitk5OEUZVvrzfb3X1Cu97fhSZklZRTaDw7nsYUx6IC7DjHzMQgKFLUjAld8E3TlpJSmdbrUVViDsfHYYGuAyZEMmJkIySwwOxbBwWC79NqijGJFlVwAq8u75jLcrFgi9fh9nvf++47b3/wf/3Fr//dj3+5ZATNbCoClhCRglfnGI2khhZnM6me77VuqYfdAaKEOkiYp8Uw37y6K8zH/CGjCxFn96tKomKmWWWjVBsxI6tptrNlf7UQqW0j2IOLuYIiudkp2Q62/4QIWFvXWh2DKTFqD4J5LIORvPvu8rvf/5o53Wy3t9v1kEsseL+ZNru43efl8TIswgcffOnmbr25udwNQgrskKhuImZgyOIClIQz0RAZUWKOBtS2PqrttrvdbiDwBA6rHx0hoIroYhUUEznz3gP6OFlOhZgCeSTQLNGybz0AGCkBkyeHjieOEoHrlgOoh3apzvvmRwDmZ2O+O9UrtF5/s2oY9pA6NlsI11GdIipU8Jho2k5Hj1a//MUn7zx958v/4PGX3v/q5f1P9uNmt98DsKEslo1pwKDkzTP6FilgaNk5TLmIFAI4Plod9ScI7kc/+knfdJ1fEHsmN+U87cEmIAARsAxsD+7UiArArzvsIU6ro0VFPRj5+W+ek5EnX0gs6ebVVrZqpG8vnjw6PV71i1fXL9b7beh96LnvOtGih4orFwElR863zaPzxzfXt9OQYoxoGKc4jtIGX3IZ8lgM3nl7dX7enp1dtE13d7N+8fwqxZTHIgCt89nSvCURICN7zwgMRgjkCLBMUyajIeXLu+nRox9/7Svvf+87v//WkyfjfgRJbdeN++H+7qaINCEslr1vvOyl7duMej9un3/24vnnLy6vbtAhe8et0wxTTJ6xpdbIyFHTtUoEYN6Z8+Ydgpb7zXrZtU3TtG2zWHTLxaoUAzQMcL25noZYJhs24/p27T9sBE1V33v73b5dZE1DHExtsewJ8fzRedOGk+PVctWbqZJlyAZiIGJSJKeScskZChT7+JNfDTKUIl3XO3JZU0EFRlUBU++4a1tZFRH13ncuiOgUYy65lNR1K3LO0LiwGAJDCCQGlzeXzae02d6JFWYixpzTFKdKAtput9e3t3frzdn58fn5uffNer1pQ3N6djxN+bNPX9xc3pKBFrRCms2E6t2ZyaIIcRIRqBuHqObR4jY7iIE8I4OCFXONZ+cMi2fP6ObsAq3m1AAKqDiPn6HSnsRqN4kGRnNJWb20zfAB0ZibDzv0qbNYxBCKaU2o18qbJK0WLHP1zgdBDCIQwcG+t77zpuPJG03FAXei2XKpnrYH8dpvv+zQ1s4fhQAGJoIHUxY8bDEPKBY7Rx5qZa5kxmgkVk8CI2IymJNkspRZIcm160Oj2gzW/sWzJ0IkBRTUYkmyiFYktHLRgIBb7LrgGj/lOnx1RUopSbKoaTZjJCgguXimLFpyXKAPTSiSAy9SzJtpQoPAzoppVhXADE3THLVHq6NldxE2eDOOm+BcH9qi+g9/97s3n+4+/OHl9hkcP+rWQ/RtjwRSDNDVW4mgiKpsgsVMDAHQ7JDkWAuXw9DsACLSrPuZz8PaUB/k9VTLlnqtawA6glHd5cEF5xrOkrMWNWVHJWcC9OyD44aJKLOZlWJmLOCpumWZ6whIVQqANsGtel4G7tqw3m+2w076RwRMFMCYjD01SC1RU6kGuSTEEcvWxHkA4oIInr0CGDsrKqUoAQAzhfqXMLKQFAXzTc2Uy5LNBECB1CHVuOE5xtNMiByCNyolD8Ou5DwM+1wSMfd951xIpbAAE6yOVzFF1ehDG4Kbkmy3u8vr+2GE1TGcnKw69OTJvAMfUGnYx806xREIoGvOll3Xt91iuVws+mmKUyJw2PetaNmmoVm0hM005hTT2QkE7hGdZGOD2/uxaZA8i2iSQsy+BSdeAU2l7LOYBheqNXTdD5CsmrYagiTojpeLo2Vom+vn6y7uTo4WbQj3693s8Sm1UILDRG6OtRn2u1IyIRmZiGrNmsKHLQSqeKfW21WQOD/IX1Qrf+Fpx8OSfP00zxGB9gVg64B+4YEXdgDgD0i8AZGRqYoqAhsw0pz3ZVYJpCZigo45sCmCFTRg5wDAceMcM1EpmXMBA2ZCZ4jGgdBzYJdLkZleMReTjp1zPgQXWucaLlZSSRnyNGZHAIp62GKlCOgBHSLiw05XK9XXcA0AIeZcHhSXYIrgalFkUptfmv0rHpQgBJXoxESZc+0jDha+M6xV7aOJeR7Q1kAjnM0SDQ1MiRiUXv8682Vm4rqra7VHrBZXhDSX14hGeAjCONzKKv8Wq2jmf2ifh/nC4OH78fUEel4vX5AxvoGCweFoef1Rf1cF+f/+cqAVQ0AmPsj4ZlkmvvHD5kHKPIyeQVR2XBUZqlXbIShYZYE1yHK2zZAZ2wUEYPKO0WEhRdTX8SCmZkY2A4nz5TIARILZPhnByAjM2EhEicmRA6jjOTSH4BCKTRpTSd2q88tAC4IAUu1ACBQjFiMHDAiGKlCyGgE085VGQxPLuRQjEbaSdvt43AJxYPZgpcb5oiliARBCrD47jpgQRKvvDkgqiIgEOef1Zs2ju7y7vDi/OD09WT5avffeu289fbTbb+g5rXd3i9NmBy6mMqT9ZpwywS6uweDiqPOBUbhMNG1kvx0IjLzlEWRU0ph9U4bSnDaLRaO2BChFcokiYlg8JwrFgTXOOSQspRhqR9yHpulcyqM3FktxSovlwocwpXh7ewcI3ao30HHc32+2Y7TgoW17EIhDssydb1teodL187u7F/fD/YiRWMkKaBFVYwbn2ah6RtIcMkFgBmKKc4yFzjNEOuxkYAYP9HSAmoOqiAKABNW6WVWKcGgaLJ/86vLy9vLp+2+9/5V3kjZJoERA8E/ePt8P2zGmlGWJ3DXBBxeJUyrGSECe2/04xCk1y251thT1N5dbGIEcjnEqhQSUfUPMgFakQEogAJqBufLffeDWNc6xieRcxFTVuAH27F3jHPV9e3TSL5aNc7BZ34zT9vS8D+yzTEBM3hEyutB1OIwyjHmzzkzQNL5vW0ZOmmJKRZKSIjOlklUkAzGm3BBTKXFKk6HkQuPUeefVyKBMcUhpQiTvXN93oSHvCQAIgR05Q2iAHDSd71eLplHRfRFFJlEY9uP9egtGJefQBEAuJXULd3J8FBpadL7vXNs0YEYsAOXo7BSR+65pu5Yd7Tab/W63vl1fX90MWygZiHwTTo7D09PF6Yd/8+xH//avf/pXv/7Z3z6LrwAyFiUo1ewQKg3UHo5QMQMDBjgQkFHQ5uEFqCk7eZOealU9iGhSE7WlGuYJgDkFrsNyRDTValt52GLraEVrYfyFyfAso6gvPIBfFfaovfyDrXX9xatPpmFFTh6mAWg2i9hqTaGGdaYhysCKpkWNpUBSUSBnpkkpuMY7J1niZP/dv/rzr/7keLOW7//xH54+OlaaFr7/zu//Qeh4E3c/+ulfgccklMZRVFXBM1HjU9KSshYhxjpJIwOus00XAFCkxJRpTORz23LXh5l7VkAVCDGn5F3rPeOyXbSLnOI48P39NsfaWKW+D8uuM22ePXvxlS995Z13H2/Xw69/88vN9Z657/pWE5ZSpCgSWAtEAKpUk23qrjs/+TOEhQYz6jcnxADATI81eqAKSKUE1bfmwV0Fu6piAqvzghIgIivJbHv2Gis7EAQq8IKEhB6dASJwzWio+1VlWVi9doTgABSIbHV01Lb+/lYeX3Tf/NbXv/+D793v159fv3pxdXm73u12JUu+ud1f38Jbj+LR4/6DDxrnOkKHBExkAiJFMogaI4xxi97CIljyGUw1pQyb/fYsWrN0mimmbZzGZXPEvkeNhBEIALMWRW8qIKjBATuOuRgIs2PPyAheyTE3pGLgKq0M0BF5yjlTdfdDqJxFM5t9G8zqc1FpH7NRaK14CMCMqt5XZmY2mAMjRDRUIEFSIKnf7UMT1wXAD7fw6w9fLs+6b3//m//+45+9urt7eTUQguPG+ZYdEQOyABkyorNu2XqGlFJO4sk1oTOlm6v1/T00pxaa4Lj1Powuk0wlVT1lxScZlWogGzCCIKCBABBs95uw8CgECuTp9n59cf6Izd8Pa8cuj+n+PvXHXTg5ajhYNE2gMYszbVy3aGOGlLOIipiIgWTnyHte9OGXv/xYIphq3/VM6BnalkBABQrCe+8/dc6F0O2349XN1c3mvuXgGt9U4n2cuXF1QRoBMnPdcdBC60sSh2oMsIFffPRxjMN7T956972nzrthu/VEznHOMaaICKnEYok9PX3nyYeff/z88vNfP/vNi1fPbtfp7KxzGjyEOuxLOcWS2JwhuhACkJkwEzM6wvXd/WazLucXR4u+6zpmXi5XwxS3+4HJ3Wyvd9tx3CbNcnJ2bp39+uWv77d33/jaN77zzT88XTxGj1AMUIFodbJaHvVNcC4wokslIRyibGp9rFasTGU0tWfPP8OWINhiuYBmEcs45Vg0gwpoyVJtNTF4H3xgdqaFmbzzxJxSCkjO+bbjWAQQnOfAGMf08uqzu/VNHibAQgS5KCG1bWuEMe3Gcbxfj33fmSKh227uwlnbhn57f//q5c39OqJgjmZZqzQcCQEr0FAnVmW33bdN37WLtNmOYwYDECXgxndjiJ5c6xv0kAVLVi1Rs4CCc17FcPZln61n5idwpkVYDVushIJqtoL4mq+gBq8PnpmfbA8zqgLKxIamJDVMhB64GDxzmomrhSTL/NQj4sEoHMxq2Be8mfUwz+yxUp8fsjTgIZDpdfvy5usL6g+bR/wzQIYzgMvM5AAcICOzCmNVWSABGM3OTyaiYm9Ilpyjpm9D48wsSQFRIt84D2aiRVM20bvtUFtrq5I6ZnOAUGWgUEpRNCXIQ0olUeDWNbVzC4iSMgYlAzAjxsCO0JARxLxDNvSO4ySq0jah52VPSzYnUcskUadow8nJgrJ+/ckfLKT9N//z//7xT2+6ttPsQEezbBVlMjJr0AQwG2Wo8uw3YIXDqOWB+DL/j7o0rHox49w/I6DOfRwazQO1mYZFQIRGoGBNCE3XuoYgWoqllBxj7JeesIZeMZMxCgdy3PZLjLnshlQU2CORMkMITdOGRc9HR3TUBhxps7/d7LdwAUjkQnDqHTWOesPWwGVJSVIWYUbHPQJUY9NixUGPoIACCFLUwBwDEYNJxT8RTU0agAw2lmGMQ9KEDlwgJgVCQzLEys1TMBU1UFXJOcZxGsfBwBoi771zTtWMDJnXm/v9uIsxOYXg+6YJp2cn7P3t7U238H3vUopFCjcceuexKwn2OyAFTwtVMu3i6CTLtIvb3fZ+s0OHF4+db/lk9fjo5Kjtwt36vmvlvfeOveuGfbm+vo/D5DwUkJRSyRocUnCcVUohdlRJ01KKgJmAiTmAWaSgZjZlBYZ+uegX/RQjDHGMsGBPavu7kQyIWExmjL0+nwf6ZEwJCBgRzES0HDCSCmgS06HBNVORAiB6eMIPHM0H1Mm+CF4f0Oo3sIsvbAEPy9ZgDlKob1oF1mkm5auJ1jCzOQgaixYFQCmqWoqoKAdUUiBAj4jkgydEFQVSZEabTb4M9eh0qahmRkzOuSxlGidLAAKFCgiYAzXzzrdt1/XByHZxv9lutrt98L52q1qn6gKmc+wPINWAQ1N4GB7UbbN+gaocXKEQkE1nwW81LGU7XNTamZAhICPX+FlwNU2HQE1qPCxhFQrX+Mw6iqh5SFirUzAwUDNH85Wd+ykzJHKOK4uqFCugWvf1eRyCgABkaDb7csz365BCOzfn9luokx2M2F8vgzf5wG+sCjhA6X/Pqni9Og772n8096q+agrhTKSi2R6/hprrw2+sRfiNDMU3Yb36xWKl6FwHo1ULY0NBAECewUCAA10BkZmzlTkzDPCAsleUWEwJsOovAYEIGOHgIlubR1ExMY/kCECkKDpSAjMC72NJZLjPI6KFZTMdJxtnj5WKRpMD9YZshqAMzESOxKuSEnkC5ymIkW995JvdmMdJGVhqDEBdJ1AAZL49c/KLIZFZIQIFkGzIRoEIMce4H4fV2epud1+wnNJpIaGGdYLPX332i49+3YZ2ecKn5yeNY0oISoumaxycrFbBhSnq559dygQlW/DcsFedZAJNYMvkVDtu28aJhKOjlUi5vr4fU4RiXnqzsllvjx+fXzw+axo/pXGYtikOu3FiRsfdtE9Xl9O+y+996W0CHIeJA/XQmemwmwykbXHRLrvQ77fjdjt0eETm0pBkssvfXOXbwshsjo1FSk6lFkLokZAUCR7u7zy3M6x2gJVMAwZUH0PB2TbY0A7Tf62IIgCginGhtmlinspe26OWLI/Pywt5Rc4/ee/itG+ypJzHyBvVhC6tVv35+YnznGIyU+eYnTtenopgF+KG1zlOL26eh2aJLCHAsJuaFYuIqjik0DgV1gSFIxggChKxAyI4Wi5DcKK2HzZDESRoA3ztd37XBde2jffVkdAM8jhtUowpxZI9MzIFAIqxjOOdkiN2ZkjoAHLKICUzlL5t2tYj0W6877q+DV3TBFXMpU6tJxUyKMCSRCaBVy+f94tF1y6KxGmactamIQNTVVVMKVsqiFbEiKjrMQTX9I0LnlyZhlJKzkURy24/bLZ7JEJU1zlT2U/7LgRi6RrvWcmSc+o8o+rmHcyJAAAgAElEQVQUU5ymtu2ZHSLnXG5u765eXa/vEhqRg7hVxGa1Oj85eXLWPvrLP/1ffvLXH/36oxc+tdZQGgWUKl/e0FS1enlXb3Y4dHSEDIAHMcQ86gBVKVJraDycf3CYFdcogIMqDbTiJDQzpcigzPXyLB5EUDjwsowqrweg+mwQkWMmqm+mNAKAVTvmSt8xm1GAA7hmZCYGVPEAUDUHwAooymoIIAgARWtboJ4QGIScOe/EWVE1NVEsZkCIPvTInruPPrr/H/7l/3Z1ff9P/sv/4ve+/dVBNv2yLTI9v/oMy16VQb2JjEVygib44IOKjbmAglhGq4UikYEWiZgAFBHZ1ZG+K1lyEikGICllM3GewABMQAsDOodd59E0l2CScgJTGPdl6yWN+yLT1eXNYtF/8KXHP/ijb//Zn/31iw8H74PnptJxcgbVwjLp/Pg7tcLMFXA0NDrUWAYzeoWz+SwqvnG2ASChqRER6uF7YO6qar2OAKhWu706iaGZ4KzwcOhWRlGdyTAxs2eWmOudr71hvYOGVXynyI4DqIAC9MsWwMDD0w+efO2bX3nr6cWzFx8+f/nixcvb6/thnCA455vFclH2UyrX+tmLK0I0hL4NKlij04oaGrL3Y96yax17JV9SMQQpsNttp4mOLs582/vrkR2vjk9IFo6mmCdALTjhVBRyNhAxlswGMeVcJHiPxMzofYsY6xSWvQOl6vBsjKhUJQmvPSrMELkCT7XYmiemggcMS3GepCFX+A8JpRoNoWm9U4p04CArOEfZYckAys+efb583P7eH34TMAsOoYUmhFxsu18HFxanHZAyoqBEAfLsHDM5AXDUegrTvjz79FXLoEJWmJhNEI08e8FsefZ/QCUyrmXEPJkzBDVDMAdZoiaForkEMOhCI+ru9/fWyqpbbtNOxrK5WYPl1cmidc35yfkgm9ub3ZfPlilFKSUlqR5VKmakjCXn/W4/7jewatA7U03swDlDAgNoEN794Olnz55dfnY97sdxGroGvXeoJApSBASAASu326yoEiEpHYa+pmRA1LiAZykXefHy+c9+/ou3n56//eRtZN6Pe4fYdo1rOKW4n3Zm1nZdH/qf/erD6/ubV7dXUVLbAzoeS9pOAzHlrNmE/FAzKwU051JKbtuWnRMtAJCmgkptaLumrUPjonlMO3KYNI1lmCxenD95552nmmCM43Czp0BNE97/1u8sln3JJedcSjIz50hBxzR1TZtSQgDfOAoYjJG8gERBK5olb3frBvomhKZpXO85MzCCeW3blNN6P+ScmxBERFSzpFxEVIiQudlsb9H5tmk5OEgJPRDPa/h2B+vtbRmilowERNS2LQcnCGJwfHS2GyfvWxE0sxgLoVOlOOh6F2OEFpwUg2IgDMRgAJANjFCR4ez0zBQI3aJbxalEP4JDJibDxvujxZIQHbliIkXHYUBFMGSkEEJMkxmZzDLqw4mmOp8Qc5mNCLM2HiuGhYRmhw1tzpF7EPfRIaAQwahKgyuuZVgXZY06VJl1Noi1l1GAWTtYD8iHduU1h+LQn+KBifwgoH9zwP4FO/hDa1eH1K8xrC90KZU6Rch1tFlZDQbVqkmNgIA1H5J/wZAOmBojBxeaEIIrIqjCyIF8cMGKWpY8yWxlXTsxRVREMTAo0dIYwaGpAJPkLLmAgkPy5FQVwZxzWoQJvEN2zlS1iIFKsZJLcK7rVo7DiGPTBk+BdiHepFdXl0OapLH3vrd49Pjx6elikf1/+o0//pN/9i+e/3Kz3zTOYYyx6buU901zop6nbFx5BFCA1GoCEBwoDXBwynsAI+ZGbZYszeDUXC3PQsI3+kVExNrvIKhRFchb04YQGB06Cx0ZoKWcFtIAqoIWVWJlMgBA1r5tG3NCJRV1nvsGV317dvHOYrV0Tgy2UFLXLtbr291+X09yx4HAIwaUBsAnxaKSJGfLwXHjlBw4BMMiuRBwNiL0IbCIVkYFzFY2iihg2WQCnszGNG3itFfQxvnWtdvNmpxH5wDJEExBLRWIRoaI3ofFcgEMKSUidM6FEMBIRQX18vJlElHFlKIZtt1isVj0fcNc1IpIjnGYEjBO1lDo2q5fnhz76Dm4ow9/9hvvSHM2A+95GLf3611RWN+Nq9Pw3ntPrGCcpGuWeOaz4LAvwyBF8xjT8VlPSFklSw6+CcHDlDcpOhMAcg1X+yHNlXxUW+QKYGkWoAVAQDG9u72doetimqUUcYbVpV3nOGKYW281YHAOwIFTBDk4mx/4fcEF5ppwWuush8iIwzKiBxXr33nNG8O8n/w9X1MHvjZjsHj4pvl8rv+X6MCN0hknIkPHOhUAKFAESYvULzZCrTpiUAUxw1wyIrR1VOeQgJDRNR5YSymE2HQ+plREAaFZhZbbXdkTIBvFMRUp0+i4YUFhoOAciJnVjCeo2V5avegORSk+ELEehG94YFO9Zq3WC6I2Z2sYVLc6RFUjOAzbYLZmFzBgNCIgAjUQKwCuXtoZ7gKF2Y7KHiDp+hNel7ZwMMiyQyU8T7LxgUluCkz02zvLG7eMAA2JqTJbX9sgvgE21f/WSjj4rdcbJ8K8AAAqzGwH/64HYtdrstj/TyTLzU76RIA4GwWq5uoBfqAhaL2UbyBwdaHWlIF5aoOv8xvNzNSkRgzUbHQyqKdntUDOKlqAwBAImQEOS9iguiRDOVwUM1UEmu9/AUQoSRMWIoYKGBcBJRM1NGzclONRu9rngYUWpwsQ21/vgAE7LJOxQJ3zKIISOAfgzcCISVGtqKoxNSLgQh/9pmTNSYkCeQ802rwe61gMCNVKyVmRTR0qaLW/LFiNOTWj+sB9E7a7LUywuds8v3rx6u7ynWdvLRbNW08eKeWbuyvFvNvfA9HJ6WPgMA43Oe/3+93N/u7uVYY1ULty5ss+jik3bXP0mN8+f/SlL733pQ8+WB0vNuv7q6urH//wbz57/umrVwDDYUJTAI6aX/7kM8gADP4Y3n/nyeqoXRy1q9Ol83bcHa+a41hGzeo9Pbo4SZJTTnEv95vp0dsn2/XAPGccdG17Gk7jHXz+6WeaNd8UzGgAaUqk4J1rg6uGkyUVcf7g+/8wwqMZ1p3niWqmYmIgUDl9BlDTLw6Gfw8rjsxhQVXzrk1pinslT/2Jl1J+/sPnP//bz/7xP/5H73zlPYH46bNftG0KSI8enz56cjxM+3EYHj96u2uWOdtJezEO+WTp3nr81rDdPXt25f2yX5wc785efP4SHEzTUGfR3neOCdKoTnMcfXDe+RDIBx+8a7tmuVyRezuEcHpyev7o/NNPPgHAymMvmkRiztMU9whwvFwt+9U4bmOcDCxJGQYgD8vVEbBDoCZQKZaTbbf7HK1vO+IaEkw+YBJjIG+hFAMw0dz2bnly5jznNK7vdqGNxH1VfwNC33Xe+2mapiRt45A05wjousVydbJq25YbP8Z4v7krus9RAccmlP04iULbEDkMLSLgQl1wiFwAEjv2jgjFo3Ig7xpy3XJ15ByvN5v1/f2LFy/v77MJHC06U3j67sm3vvMP++boz/7X/2P9fP8v/9u/gHuADCAFpSHsoFIyrYCqUs12RKw0RlRAZPLeeTMoJZsZGjI7IkxxDwqSlAiI2HsHCDVEW4pAATCoHTY+KMrnE5OqM7gpAiogz3ONSjoHAAVEqFRbQAQmrHWAKUINGwYzA5lNb2tC9byPy6F/OBQMknXe4AklT0TkiZhAwCRnUY/gqvVP/VWJCkgxMt/5nEuMxWMILuz26XT11uXN/k/++b/+k3/xr/+bf/ZfffcffevoaPU773754tHR3frVzfrm6v7OuMimTAWM1TfIbdBscZ+qTzIjMSMIJM1FCrEhAjMDaIplt83Oa9+RWYxxIlLnWjYoMWaZikjXhDag565rmn0bd7v9xenjly9vLp9v3np86n37k5/8FLF842u/950//IN33v7yP/2v/3vSMuySp7Zrl9xoljTsIxA1TQMGmouJQXX0nGdAgFW+B6b6hUDfuZ96XcrXkxjNAEWhZiLPlTzCIVsPaqwKVVDKpFK1YZZOzJsLifHciapoJVQTmCKqFRFFrgwIQAfsSVE7x1EGsfL+V0++/Z/8g3c/eJokffjRL56//Ozm/n6MMCVg37Vdyyzr7VoKf/rJi7Pzk2LqnE+SVQHAPCMiIxYDYA+QRQSNNAQOTSkCItq2QTGIaIyZIHH0MUYFdYEdOfbU9a3FsSgUzVk0lSIJRhxFChF774FoN+6DC75xUixrVlUl822QJJZfT9wqcgs6M2LtwB8/NMivaYtAJjPP2JAEjarJDwIiFUOroy4jKJJ4uRjHCOx2++Hjj37zFz/8qx/85z8Y/zze/M3LdJ8EYbls274jRt85aoLYLueanUhoPnjfhkXj+zjq7eUtKUgybj2zG/ZTiaVvGhthmLIn730okxK6KhcFIJidohHQmtZNEiFPkAF1DE2IMaLi8mxRYi5TCegklatPNlefbtq34N0vP37ypUdh8XgoO3HmOYNFs0IITIG89R6905zG9985+czuG6S+9V3j+rBYdAvvgnOh7Zvr66vnr16+fLnLEVCgdcSOpZiAFRNwEBaND76kLFUVBSqgYqoiqNCEAApmeHZ25thN0/3//bc/bnr4wR/98fnpyc3N9TiMi77ru6btujEOYxy315tPXv3mR3/9f5IjIt+vVt2iH8ZhHuGiFjAkQNSUpmHKwJRTGScpRcFCzlPXdJrGyoNsQqsqKcUxTfthJ6qGYiiL46V6WY/by88+P16eBPS//PTnzz799IOTr7776L2+62KZYolqCsmmcfTBPX37iYCYCQEyoSEFdupC1jQktGKOXWWv4myPig7QN65p2iIqaAYSSpNSqU5/cZpSTGDsnTF7Eck5IYGqBg9N67UoTQij5RTHYasl+Wr6Sg5EEXGxWD19p3FN430oueZzAFMYh7hdj1LAAxgQmBF5rexPVQNFyOgBGR5fPNqmKU5TEQ2+XfY4DjHGuLWtQ++ITWCKMeZpihMIoCOq5KrK4zdDAVND5Gq7N49757bTTOddDUjRZm0IYr2TamoEdkAuEKvpR+1O6kPpiUDMqvU5Q53BqBLU0r3STKF2ujXo72He/kUiFT5U/g9vPTQwv91s2DwEApg33WrcPrvOHLieDx+i1ahuVi0pqKmIoc0GmPXPYqqY1qzGIAMEZDKzFGPWXErJKbJ59p4IJZtEKVElmXd8aCNRBVCxCgJSntDANy2HEGNWp1U8EYuiat/1RyfHO7w1tBCCbymllHMMwYvYsJva0CwXS0++df3N7c2r+yu7J9w7GU1dTgqr/u3g/fnx2dvh4vqzqx//+eZsebzAoymNFEaRkUhLGY06NA9GAGSVfPlw5e1QvDy4EemhyDCA+Wtr8w8PPeGbXSgiVst2JlQ0NSA1YvLOqek0TiTEwS2aTlRSmuI+ApSIJZG1gbAjX1NQTJ3jk/PjmlyzCrDqwsnpoumDQs4ZC+iy6T5/frsf9gJiAAy+mqsBsoorBlJ9ONGATCnTnCSXDS0D5QKePaFDLgzoAAtE02xYCMVkUtlu72636X6zvd9POyNtF02/6oY0cXDctBxaZAIgYvXIyAjgQ3CLRW8g+2Ecp4mcb5o2eBWR3bT/1ceXvgEVSAmI4eT4/Pj0bLVaOv9WTFEgnp2vxIoEZ76RiOMw3d7sLj8fdpvPrl4koDl/42jZisgwgXNw+WJ7fQuPzh9//vLVEO8vLt5qu4bDYrvbxZirv6HUQ9SwZLVATd86C7tdtCQKwkjo5rQ9Q6waJkOoRalT6NowlmHa5av7G+gb0MhMR/3SLvTuZi1FHEJF3atCkAiZGbCsjo8VFAvIVCCXEAgdgYKKee/JY5ais4EGGQggcLXUVIMMVu3AD7ZGfxdlqMjpaw3Yf5B0M08T33gRoREZGzl0jsgROU6UAIGY0VBZvAsU3MzNZwIARWBE9uzY+RDAwKQYIBPu9hsXnJo0bdMtWlHdjbvA7enqJGBTJsmxqOgwDCAKAZrehUWDjI1vxv2elEGZ6ubLCIIC5cDIqWNWPBRJM04/P4BIWLGValUODPMk1cAQ+MEcBapovEabzaWrc1XGoWgHvfqhlaFDgqGIARADO0dMBlakmFku5aErqddfQEop3ntissO0o262hpVRf9iP+Y3dm5CZuWaViIoIvDnVeGP3ni+Gx7/nZtsDelXXLzFw9RGqWFx9PXz4G0voPxrAYuZ5JVqd/1dtJCgCMzXBE7GolFyKFKvBRPWZAFDR+keyGZaYymzlU3m/xKQogIZMSGCkMPf3841Cg3qYI0AtrozQZgGsGUIVNwAAkAJVAh4hI2dQNHJGzhhQQEyyU0JPYlA1FHlXwLRte7/scBiAgQ2NVQfTCqUR1JQTM9As7MA50GHyqSiCZAX2wAQlCmQMIRzzcF1A0MCkKBRgRwR+KlK0ePZkKEZWkB1Xw08UEhVjbJp+2CZACC6g0u3lXRkn39Kjxydnp0ddQ5dXr+IuEYW8vc8Zh2EHOi0WC0ddyzCReWI0nVJMQ1m0R4+OL965eHvpV9ef3/zkxz+9fHlzs77NScaRYWeoRMxMDTYY7wZgDwRkgGt7Nd1dsZ1crNKT4nt+/Pj0/SePUx7vh+sCw+nyNJZ4t9nfr683Cd5qWP4fxt6sV7IkSQ/7zMzdzzkRcbdcqipr6aneuczSwlCihkNRJCGKEglJBPSmVz0I+gV61m8hBEHiEwVIBEiIQw0xIkVyOMNmc2Z671q6crt5t4g4i7ubmR78RFZrSBEM5EMmKvPeqLjHzc0++xapxzq5hxiGxxcXIfd5PMyviy6ODDKmyhjNQNgECezBi+ZSW9INTrjASaeKhsFiRRVA7ef/1o10vYO9xR6/7eU8SSSSuSybmIS6vGTP5ovurvp339+8/PTmD3/vRzA8+8rTx5dP3jxUNYoxdLE/7B/YmTy4ye2b/evp+euXd1GGR08uJDjHrQsZjKKmHvtxXBYEqdpNgSVw4M5MQAHu4M4Zkrr+vXfeu3r06Pz8bKn5/v7u5uHNw/hwc3s7HadpHN08JokdxcQhsCOl1KV0XjLvH6x6VWdzDdyxbEDE1LT/BHip5ZgPxWvqQKSe85zrw/0sIsLBwblUM5XIu67bbHvXbpkOw9CHwMSQiK3w2S6JyDxnLTVtJASBMigPsW76EKJw8CUvt/djTCHPOcVi1TTnTUebDTtrCLUTOR+6PsYhIXHuY4iBhUg4pBCc+fLpM4n9tIx3rx9+/uLlw75IQDeg7zYPN2/+5J/689/6+E9eP7+/ezE+/9k9ZmyGaB3mPWBG0Z2bXK2CjVydBRJdxEEgJWYiEYnesrDNAAre2AnSFrZmtsr7Tqm0q2CZTgBpk6ESNdjUW8p4s7NtPeDK6SJrmAcTNRUNrbI0d/dq5k7uXle984qBGJjB7m4geDNeNWgjYq0rbFDz/DBF4LZUIXNVUoMz3A3GTsUrmaJaMe4kdAGmOS8FNRAJxbvb49CH7ePN8W78B3//dx+O45/5jV/ZPhrevXj/4w8+DkJ397fn/ZkITdNNYGVGt+mIYs7HNaxpxYAyiJquMpCouletBWZIXT1uM0nJVlMki+QFOddS1FCnMqUuBeKQhIVDlN3ubJPG5ZCvrx8o2GVNlxfd/uHu8eXFxx+99x//xtdffjp+/uO7w2GK0vXbwT2wNxI8kRo7vLYl2xqd3MiXQlyqEsPdnNmEuA0sxFDzFtNC7goCkZMzr9m/JMyipay3pa/bqZWnbifWNZ14WAwBDOa1GpuJaws6ppXfAA/cGA9sTbUKQc/YdDSPY+jsax9/9PVvvtdv5f748NPPnh+PWsoAJzdbJjcvpVgp7ETjcbq82sGrWTGtZhASCcmVFTUNVqsDJXuB55D47KwfuswQtgTEcijzfV3mO9R5rgXk3bajZIdlfvLsXY5cVWtWV4ZWdtYF1SwGcXEr1ZYKD6tmqLqbC4UgofngVK/exJRBBGy1Kq+yFW2bvubIbs1EDC3oQF0VSrS2ZULBXRnObG0WJiaCLyUPQ285O8Esjrf1u7//gz/9m1/bbftnz9JxynWJ9zdzXvDovUf9VkKfcxm9wBiVFEGJKPSMZGXKi2quSF1IaRNSKofDrEuMHXcRx2JwDzBWo0Lglm1nASYEIQQzUM0FzgFBS02S5nkZwubp03ePt4c3z291rl0fh6tgbMfjcvN6f/Xo6vzy0XC+vR9fdZFjpFzhTLFLibCN1HexT+HybJunYy0wn+Hg0HNEGtKm3262u3/8u7+7f8hsYGdbbILF3qQLoqRwdoReUoxBCO5mvuY/29rJhT5arkueNzJwdLbwsD/87GefffTh5x998Gxe5tfXL5bzc5fL3XC22ZwvD/by1fMfffazF/fYndvlxTZue+milyXFQMzTNEmqXer77bYWFQpW4MXF2LJlUjPfXgyFzeHVVLqY57q4KtyYD/OUi7oICRevY57QSXc2RAnzOOf58C//6LtJuq988BETRKSP/c319Zvr6/OLc7XqqM6mKAALIhETVyWv5IVc+kRBvLlyuKtaydWVArk7goqYOCyFKBxNAVJ1ENgQFLVkncviXM0MzfGvY+vLtKhErXrQmg0EoeO8b+ocDqnfdFePrlR1v3+olvteJNhSx6UuCI2/SCLELKYKMoOSKzOCNC2kiPI4Tsdx2m0vgiQr07IUWxCpRoquXkvNVaFMZNzSkxxmytBVudtadmvKdCZjt1Ubts4BRM0XlLHaWbk3fro0B3ig4fLUMktABiYPRNIAECLiJiCABCva5mInl7cXoRi3ifK0SF7HD2dum3wnhwqifVlFV7rWytQ4yQ2ZyMmt2aqg2TuuNyI3xK4tFlqphoIUgEHJyby2suPWLHR5HQi1Ufad4KtLlxCYTC1r9qX59cBdI2pl9WJWDQpmzvOqluD2UCaWjrn3OGxCjDEJiPJSWrOg6qpKAdtO0q7Xmcwd3DP3Ok9WRzEuueYRURfr86IQxKSpK/1xgi1h7XHLso0y31xvn36FKv/W3/nnZxt43sDsbNgosBwKbeCmTkUYRApSt/pWHvkLSOGJA4fVi+PL/0IKIqA5zjqoZZ3wKixiKLQh0c6+CpgaakC8lFxRRWngQUIHIncsY4FVUK3iME6xJxYOYsyhi7s+SgrMTGXSWg73r/IYUiAJHrlnpLnaWPOC0iGUqozBfHDnytW8OgoLgwKxOWZ1LcQBGogLjhrJQQUEM+FgYKfqXAFV8uquRiyp63aDuoKqZXcpmUyJlLgagrIIBVJ3RV1jeWASmCn6limwKpgZghCEmIceFGLxsgazsdU6jaOae6lH1ZK6JBSWGeN+nsZ5PDg5d6mzgWGZA3tAiBL6PjEojqpZDccRqnzY5/2x1HKz2WwuziiobIMUzgedjrdzlzZJiFRqtsghbfj8bDMf8pxr9cIS3BEDkTOqwg0CikJOISZjOpQJ40LGfd/DggeEoTt7fHkc5/m4cFhBz/VpYUdwCPrUFStmqgQwJAmBrRopQmQQtTxTMBOJc2PACzORotYCJtc2sNFbi6C3uAMTscOAL9XKJ1pP6x/ePtUEgMyZWsrKyg8idnYEZyGJgaOQsJPH1KtrW3CnQMSE4MbmACIYElIMHAKIiYXJ1UqFanXCOC6pNwlsgdxoGIYgzJAowbLWXPKUyQi6BtQ0krmp5VqqEzesXwhKTUZBzeGEyJzALI2rRmt1ah+1E6/RcIDZCTBCO6AnLmqDXNY/rYyo1RKxO3XFRNY6Umkur9b4smbaaLNtqqa1MDDYbZ268daaA4AbstVALa2sWWpQY2Y1XlEbllrgUVuotweAiJvnyXpJnTh0/9/dBlrvfgJZceJznUr86W8zN3sHOH9pgrZ+OKdi94sLkn/7qyFcgRmq1V1gtApwTtRrcJPiGMFZSIiLaXv37g5DqcosIYgAcFOyFt/V3CnbMs3ggZkDKU43IxxAaJ+6NRa0sXBbp6iZkiESCGt0F8wRmnCTQCEEXczYLXpQD+xWrKKmbpAgx7t9HHYwU83uEmoOm7B7fJ6Pc52zwxmhVl9noGb+Cu+i9FH6bQwlD0AutZrmac/slELh2bv+yUeX+7s7vS/uSJSCBy+qxNUKMUkQiGhxzUZElSF9kMimnqfab5wXUOKAKBwtT7fX++0ZP3l05rmII++dEeYpQ6GVl7G6IlUOifXgKYmgsnNIooxf+uAbT87PuhAOb5aXL1/9/h99b3kAi8DJ1MmEKHjlXCuqhq4jYgLDzZdaj65u4+31dL0MZ4Md6Svf2Jw/esxBHqbbPNUu7S6GNJa8udTb471Gr2Wh3G18u+suX31yM72ewhz0WNjJFmNIiB3AblIqDK4mvtqZaZtL/a2Nu5uTm0MEICNydoHJiRzhtv5OT+Ds6plVvBIhdDHDDM4SnM1BZfaR8rDrnr+4Fg/Hm/kbf+aJdH483udxPtzt79/cEYX9zXhr5dXz/cOdvnx+F2Tz7MZIlHqcX51tLvowcOhw88NPIGABk5oeCRFSw1Co47LUq8dPL3aPLs4fbTZbSRGOeVzu3jy8vrk+LkcvnsuyLGgnaNNj6Debbdd14aHWuzc3IAd1zrFarTXX6rUuqUsp7fLNPvb95qwDUc7LlA9aKJDHIO6eC6KzC9VSASU2UZ6PE5mxOHNwp2la5vkYO+uDxFjgpQ8G4KyXEEQsiNi2rxxlWqZSyrzUw2g77hxaSg1krst2QJeUgzPPfZcenw/bPkVGybOWsUxMXd/JFohaKSvg+eF4fHW7//n1nBjvPj7b9tsPn35tvqq//mv/QT34qx/dfe+f/eTVZ7e9QIRtBmjhntmKq6EW1/UYgsmFjNiaA7TDgKpG6lA0zwszs9Z8vL0diVSt0W9aMZTwZeV/21pjRchJVYmJ2l9xbx2vkDOxBEZgahjTqUC2bXDjolqxlS7VAHxr78JqMQwWTC8AACAASURBVDBSCgZo0XUhSi2A0wGCcFFdHNHB4BZkCsBRiShKYAGaTkKLLqrIcAcryNSWXnZGasbkKfT6W//gd378o0+PD/XX/6Nvv/fB5S99+PW+T9M00/XDZei9WPWy1CoBqU8pwiAVVes01zkQPLTbVYhFs2opIWIGHg45bihtHAESSQMdXy1uCtbY81LGbhCwlyWTcN9xXg5XlzuY343Hori9Pzjm3fDz823sqfuv/tpf+d7vffZ79uPf+1d/lKfcxeSVMQFwK7XUIgntWm0yRl8TXogANpC5M/kpJ4ud18SyZkfVrhfwiXrFBG7S83nO3KhE6nB3YSgpmkUx0SpKXac8ZjRLX1czVCUzOJtQC6YlZjYmcBIi785kXKaz810XdDnYr//q137l3/vao3fi85effvbFi5evDyXHeZJSmUhKYTMgdDFR1rFzS0lqlFozEaVIZuIenEJVSsnNVXpJ4MLa7/jySbc7Kyl0pLJN22Shh9we9m5aAZB7gBBcMWyGfghuev/moSiCs8Q4T6Uqx4HyMedpYaeaCwDXpkthApuhk2SogVhV21rK2zPdluIMAFoBAlqefUOvrHHOFdTAK2tfmMzYEUPIBWYURBxO0GUZQ5eqVqjlyT//g9d5RgxhE3dvbm8ExJpiOK+Zich8CZ1v+6huWqvFaq4mm9kOY84VrgRFRBxClzjF+ZCrkwojQbUscARXnDweAiiColBkD971g09jCCmwzHlaxuyMkFK2GkP37Nmzw/Vhmo5eiLeMB9zcTM8eKiPutulhfCnBJToy3J0CupASIYkMXeg6eXS1vb+/U4Upss6dDeY+zctxtLs3No0E7vpN0q4S3ASqFcmDSNzEyBICIQg7uWGaLS+TGdDSVKIgEMQmPVI39EOwY3pze/9P//k/+c/+078cujgtc72vw8XQ05b7cP9q+cPPPv3hJ59UxmIhk0eiaZwW0yAShZw5djGmjljAJBzmQ6mV+k6s5qXm7RZDFwWdeimaQx/e3E8Bmk3D0N/e3E3TdLa7gPHxcHzYPzx98k7cRVVbskqS7/7ge3232Z7thtSDKUgcj2NespubOdhYmBjVtUV0FK1zzXMt2ev24sKCcwIJO9y0uoKc82FRGIoH41q0ieqEU0xw9BxC6vqfv/wJwOpLo9+xSC0GIIle7rDdhGs7BHEjiv1wfffSSbJq1w2b7TYOAdnAWvW42UnqzansHvdPn569fr4H2XregjIHV3XT2GO367iXqcxzzUW1aqm1BoQo0QioyJqzViEOEoLECjarWhVMUaQxnZi8qR+aQbGbM5hc5GRQxXRqihgAGVamqVXQOibxibp6Uu82TYowBwYbMxO3zVDbwLdUC/M2ibk71GEkYHJufAI7qQKbNQ0TTmnrKQW1qmYGAoMlOLyW4tWaVczK3GwzXjMLk5PORN3a2pJW7YuRm2vzYneuK0jXSnVr0tv8xjyOhxXVZeIQQgx0cimtpWrRttI3WPFMzihWihqcICEyAGshLl7be1DmtNluNgPc5nkyVZizICSWFGMXkOjNdHu0WqpxgnQDe3QVz1aOZWBwhU7Lcixi/cMX0zIa5Y4QqY/cSc3LB5eXgmF+dfOTP3r+4+++2T88ueo78oNnr5q71OcxkxCkAlWiGNSo+Im/8lY9/xYl+HK4+1KzaU75tPg90bZIG4VRXQFnImcyNzdwIg6rk45BW5eSyxp0p0Wjw7Uq3CNqZKMOMYSOY6KQ2v1Z3SnEQG5kM80OkEtSHu5oUooLyoz5HBdTrrvhLOtsDYcihxVeWXnmNhuWogSSIPLJzQ+qKRoBtWoX+0236WKKErvQCbFKpG4XIYxN7C82Z1Ouc3WFoC57J5uWijLHTs191MPBj8Rglrv7vUjcbTcGzyXXqsQcQggpnoeLZ+99XUGlFq0FpCLEohJs6LrNEB1sbofDWBfc387X1w9uHSx2fez67tMvbvuEZbJS7DiPqUvOIOdaDYr74+xIwPb+Jj/c3j+EvNvuhDlkOgub53dHjVUjovCi89lmI5HOLzd9l+70MB8rOqDCi4NcRIiIkkgMjUw1l1KKohTZdoGFhCcrD2VOgdMm5bqIckgUs5XsBpiAgzrBqtVcmiIeTCHF9WjAKLib15KZAgITMUmgto1qzW/2E5gOWsP18DY/oEl+sWZcrGAICG4gB+lJsUyNO9m8Ck4hX6FxKk0F3lhFgVnEAa0eYnItRB77KElKyUsD+BqQTkaBYgjipLkucyXzstRaKjNsQi6lG/pRJ9PXT54+0apJSM0OD3sBdyHVrJbUAzgB4iCwhCSS88Ec5hVghMZcIq7SSqT5GsVs7L76JDVKJKFNNICbAnyyB3TAidncq5UG4TTKZbO+cEaj1L4Vdzd9n0ikqM7V25aesKpMAICa0T4RNaaQk63rkBVuolYuwOuCwpzdlSJWwcIKNrWw6dWnyk8jDhmtDudujdv7VhXV7o4vq9IpMIdWsWi7ZNBYlmZvPePZ4a5NceXrYnXlPX0JS/1bEKtTJVxZWkFVzSHN84Vp7WUVYJhbzrkdHuYGZ9NqReVog2UppVEh3JG6ZIKStdSsqFBHJKS2XyIWMmk7bQDo+1Cr1uxanABJys2QBicBGTHYoE0poidCjrpxUVWqbFBD1VrV4NBSndQVeRpJrR82danFyqOLq4vzs8Ptw/H+Qc4SL32e6jyPxQtYXdoeCxePH73zzuNu19+8ub65vxFhO85WSr/r1UvV/P777//oez9EWKNP3MwqzGoIDfCDVSWnPiYDUItlkUiBxVm01G7b1UbEY0hILOSkt7d7SRiG/jhldpQRXl2ocyUYe6XqrrOZazyLgD89f/zonccfffTB8c3dz58//+Snn766PsQkKVEe62oGqdaOExsMxCES1ug0cEiBQJbVX1/vcbP//M2r65vrb//yN5+8f/lLHzz+7POf5VpilEdX52+mm2K+6bdLseWwJO8OeZoe5ldfvCnHCgdDDEagIJGI1N3UFLpa2QjD3K052RG+pFg6ccssqAQ6ZRI21GI9HCTAyhJvdGqsSZ7tEBARuzNq0Zpr7AITS+HPf/bi8x+82D37ta9/6/2zfvv5Fz863B+SDIdxPB4P9/u83+v9A2qVouUnP/0pCPEqPdP6Dl+dnQ0Xl7uHh4fxMJlqENSa1XIKcn6x227OdsNFlzZd3ELluD8+7PcvXrx483A95trMRpcHhB59J6aWi48HjOM4juN26Gutd3c1Cq4ebzhCUui7iyXn/e2Yuro521ycPeYIjuzskFogddFSQWwp9f3gblTVl1JS6rpuMNTjNB6mg2olwP2hT7HrQtediZG7llr6oTk4uVlhsZhEiGqp85wX46W4GeYlM1wkbjYdIpU8ApqEt8NwvhvONrELFBnsQd2ZQrOq5RCrSy7q7Dc3D2/e3MeIq/PzwF0Xzp6989Hjr7/77OKrf+/v/p+/8/f+2WefveJZSoZxDdxtdjs3YmOrqgJrUlu4kzkZoIC29a9pLWYEZ2ISWLVcFBWyY+fVrcPczNYtqzcalKycXgZh1YqfiK8Va0qNr44g7S6AQIKEGBG4mqlpsw4I9DZXnABYBbELrUFt3tJPpbX4hGbzrg5u+YPNJXEdK8DCxI7V2cLpJIsIfFpRUQiSujgt83KYIQhdBHlejufbx+NhnOdxc7Y9Oz87TvWPvvvZlP+3l3ff+favfPUv/ZXfiEGWpS72s/1SvvbVD2/2b168eHg47HfnjyoVSUE4YqlUq6CCooTOjVBdiJVEXa1iWTBOBRFJyJy02pvrPHTotpDQ1BtVqztq12+mnInCZjtMo9BitWQosLMg0Dq9fv35n/3OnxriZeLtzf7mk09eHUfdboZt31ctDve6yvRZwGAyMVUt7tXhiH1oBF5i5vXHuc4s5labDVUbUk+NAtSKmptbVmtRKgY4mA0B1vwvWSSsS6SYIshV61sOe4VZBTUiATFYqIlgIEJE0VLopuMyH0rY2uMn+LN/7juP3jm/u7v5wx/+weub+6WUefFpNtPAYoEBNmbiaFEcVIvmWqsqGJAAW6zkGTWAdFkMkJhiCMmT7M5ps4upR7WS83J+Hq8eX7x+NY3HeTpmOPW73kWXvHBCqcvQhwYE1FrJWShYLeZKOjORVRUROMzcW4ormheb9SkKC1iMLdeyLLkp2BrPm5jMfsGs4rRvc4a7s7RTQV9GYLdNNyzGYO7qziwhcjWrJbMId52p4g5WjBGEhQy1ZnDPMQKc58V13F0ySEouWhf3IkCpeclLrtXcc8GSy8P9QX0gFhimuYQY064vS7GxglCaKy1bIw5ICtIFRHdv0asSOIQQKtViepzHMhcoPX305MNvffTiZ19cH14PfeSBzP3u/uHuZhuGXV6WWhfXIoAI5IQP5GUx093u3SdPHjXuRl7MlIgkl3z75s3L5/fliJq1G1IXOqQObCy0zPPaYLkrnM0SSyQqq5KaAxExxz4Sr9LpUuYlTyml0MVS8/Xt62mZu74fdltm6jbbYbv70Wefff8HP/n0+c8P8zJXUKmHcVa3Wsq8jMK02wxdSsyyLHkpBUbzQcexEFvXhS5KiLLZRDMlBomEkFR1HKdlv+83Gyeoeh97qxZCiCG0xaqZV7WcMxb6+e3nf/Dj3dP3nv7yN395G3d1yU8fP7GqzempC13zJlFSd1tqraU2cGReFpiRwdRrKWAJIchmiE7m5rW2Db8wm5q5azU1JyIJsev7g9ZtEGpBNoboKExqGEJ8/10ehj6FAKscRM3u7u4exmWelu35+eOnjy+vrszV3HMuqhXE3dB//VsfuMubl/9imTKxWGm5qQZSI1DA5nw4f3x+ezxMy6JWRWLOS9Hi7jGGUmotlU1IUExPxuMNfSJVWxfUq/wBDmNIo8esFtxG66r4F/bdvppteAgRp2SRBmSsVIe1MHKzBnFpc1CLWaA17jlXsKM5BsEYbOan2CWsQjWCa5tFvAFYwkyOEJmcSckIxi4sTgYKlWFVYeud25zxAG58HzopM94OIPjFutIWTMzE7M1njMnFVp9L4pPFU8utdYcSBRFyMEr1prRyeHVJ7LB5OcLITjgYzBHoxLCARvNgErt2uTOHEEPXdySuXjjysOtCH5ayHB5G7R3AXJa+1L7vTdzy0Vw7gWfUSa3g7uXd3avj+n/jGsSSABu8+/i9XSf/8v/+6W/93T/Eazy6+MbNp8/TDmKkVolDrerVpGPixkRrDGNiphVn+ze9qCGQb73GGsj1tlZTY2lZU1GTsANmLQAY5g514SApBA5JupDE2UotRbMWUMcAhJAC9X232Wy2uxgichmnaZaKZi296TqJQQIHUDAQB5L4+c9fkw8hCOAOYw45z9WdBcQuYHc9Hg/mGqK4KJOww5xKDN//yQ+ylt1216X+cDhuu82Tp+902qXYD+wddyxM0i3LrORhs9lgSKjqxcjKgZYyz8fDkueQKwvNWseaRXicHn74ox9ySO+//2y7O6+lzmUJEvvNdhiGzZCuLg+SApGXmg/H/f3D/XysueoZx/Pz877f7vfH6+vD9euH17fz7W0l5BT7ELZdih9//Dhnu70+jA9lWbJCI3EMYSkZGfuHCQhWaRwLgFnLm1cPfUpPrp5+46tfff7PfjdTVi1D4rTpQ0eRqes2jBiTfPbzN7YUKNXiBE/naRg2ISViAfHr19dEJF2IIkGCOJvVanq4P5D6Mi0AQggMUlSIiYQQI4so2TiNLUuaEShw4ORmOhd3ZCuoVA3kNcUYiCuf8hvaM9fsXd9GNXxZltaH7xctlE6A+lq/TmBHs/pjb9CPatO3QkBCK6+ewULE1IpbNVUzI4uRY4wxCpFrNVshW2aRxDFJWMZ5PIzzOKMCBXBI5JZemW1RdrV6eakt+81MjYyDmLppc6iFVXgwEEISCeFwPIAJ6k0CwjEKIOymRkba9tt+Ih6x+8mzGSuPtRU9d7gQua9mVQ3sW2GOt2yo1fYPcLC0ns6bBRPYGq5rK0K0RluYOeBmTM3vzJu6eE3XbmyyVvLdnciBFnXup3H7F7mc664dK523OY8znWRqrcdDIxStCrovS/dKNmIQObfYrAYwVWMSnLi8Xy6SnZu/UFsU///UuX+nVzBd2anMLCJm1ZvlhwjgpVYzSym17yMizXHXzJw9hGBmpRSiJpgUagsqP1mJibfQRxAau8+acN9Wraz7mnTiamEVk73lyzbkFk7OgtW0l72QxrAeACcQM7G5oC41InQpmdk0z9thJ5s0H+e5zmebXdjEhP5q93j/KleR6ovncV01J1y9986zr3z4zntPUxdcyGLYT+N+nGBQ0+N0DByEgQTewQzLQ8aExCISqpYYIxG5OgNBpJp5cYd6x9IJ3MtS0jYurrWUQMxJiDXP9fl4P5wNj9+5DAleO/dclUGEUqFes4YumNiTR0+m43S4P4QY333nqZVy/eL1y0+fl8X7KHMjSEtgEtO1igRiEXG3nBcigrmrkmshSKCQsO0Sgh4Xff75m1LLX3j85y7PLq/j7vrFp4e8995c/PLqKnXdIU8Uyi5c3H5+e/vqLo8VAItAVy92tdKSULxdxLTyAlvfsp7S9pOGooFeKz+mMc3p7Qlq13J7NojWY0dEaLZvvE7/zZFIEoMwjkvjw0gSjfr97/7kbLt5592Ljz/85rDhz158snAuSx73GiSqlrRJsEB9V62U+/GzwxfHh/3HX3v/o6+89/Sdq9vgx8PdtJS7CTA8SUhx+MoHH73z9P271w/jsbx+8eqTn35+OIzjsnDAdhhCCsRu/SHFDoBqgXnX8bYbgoQyZ6s0CKva/evZyM4f9Y/Pn15sw8Nhf3t/8+LVy9/4ze/sD3d3+7txOVJEipKYSq4xppTSAXnOWQuqIibEFCUks7rkaRqxGwCyEOXsbNd1idTnaR6PD10c4MjLVKu6OzMtlbRKzmUpqN4CXioJi1Dfx7CR5ahEttsOmz52MVjV4s5MQ0qUeuLQp03f71hiMe4vn3z2/OX19e28lL6LQxqGcP7+068tR7987739ff6D3//0d/7xDwcFsaSIXCxGCIVlXkLsiQnaeIHkrgZxxxoczusu1xHAxAJ2NkJx9aZCbr3eyr1trhAKhjAz8booDtwGbHa3U6vX9MJ/LNDntOxYoVI0QTt/meLhZjAnAa90Qmdbv4grqIHqOEXzrptwYM0IWa8hd1dtoWhEYgRuaU9muiwLEdUol1fnDi9TZuYYg7sr1fs312BG4CVPJIk9cNLr65t/+Nv/5Eef/uGf/4u/+e7lxzc3x8vtPuttnsfN0Ic4HY/HYMdl2UtUoUSMwCESMyU1yrk6tzZCDOoMI6h7rRQrR8ReuvOLMTE4gExVi2kAIUYO7CHBazVanHPfwximTZtfS529eNaHj77y3pCG29vX9/Orux9l7Fw6qmocGjU5klNZslUOLA5ir97yHN4iJo3NfLplRQQGaIV9mcS0amlWu0noaURa0ZZGKlolio2n3AYyxBhiitVkzouqsZDOLYnDAQsifeidACEheni47/pu053d3t7fz/jOt4ePv/417vz6Z7fXtzcvXt7loiyx3/SmXEudlkNWTZ3Ejolsnu14GK1aLTBzMVSr6gAKHDVDhBBUxHmQYWCOqFbH8f7+EJ998EuPnpxtdzd3h3FpVgpdUFe1AsO87GPcsHPJJeeyLGSUydir5VKCcExdF2MtVVvHpwBW3DbrHIOIhCDB3V28oJiBmUBufuJ1y5fiwZUF75DYKL3U9odoja2aqaaug+my5CQhxLDmr4tQiE0Yd/3y9nxzlS/9zd1r8rNxtOl2z7KZx4m6DI9BpOSqqoERJBJxKVqWqupwlKK3d3dznmLPUcKilTvuzns+8FxGDsTtBpQAZm75huREdLi7hxN3oOhM1HWdUBBnVByOe/2ifvjVjy6eXd5/+rDYYgEY8eqL12lnFq4gGoW3KVlZlopoHoAGuC7LXErebAb3K7gQRXgkdIf9NM83d3eTz4DBmS1WiGerw9BfXF7uH/aHcb/MJURJMUnsAFpKKaWuKAJxXWrJOaUYhGtVAjtYIoZhMy/3b+7ul6qPHj8hxma3u77b//inn/7s859X5bPzizIfPDDAtWitxQ0GL6WkNnZWXvKyzKUWSETX8XYb+yQS0Q8R7il1EsXcS1FVH48TOA5934d+t9s93O/H/XG3Pd90jGr7h8M8L9M4esY7l0/2+eGTLz756MMPnm2fUWd9uJr3U8k5QlLo1KuqUuNtgIQ5htinzsju7+66syFIgBszb7tewAGwqnPJTVlczcZlXoqWCs1LVlc3wH/p2RMiyllLrmakWkkrkfZ9//57H6jCXYKIwkvWOc+1VHXLpRyPM9EehCVXg4jzspTq0+7Mzi82l0/iy0OJyXMt4OaPjThgd7nZXu76s+H+0xfzUsmJSZZ50cWFglfUXFBPTEbXdUZqIJF7M3pd75uTNUpT8rWjdppD6N+4kG7L/dVZqqkh6O1cuc4up9vx9E/oNJgQKIgbQ61ZPPoqsW5mvwSDr1ARABiBTx55TARptlxN8QNH881iAxmBtJEyVyInncaoBrutQ8xbvy53tI6PVrwtiDQJorHBhci8rX2YQxdc19UHi7AwmGrWUqqZxSjM4qqVDZECR1M3Ug4sEpZ5Xm8FAfU4O99iw7ZhEGopIXKIYXu2GZCmZVpKVq+uttRF3REBQaVcbY5pMJLDmF0rc1Cv97ej55gnTX0PEBCYabY5he6X3/8g0Pb1Fze3z5f2tvsUEOEwb6uZQE1QY2wEh3Mbf4gcLI2g0fQ1b2elX/hprj9nAtnbPF9e78vQxarasjskBgCOCoEEUJBiBVpN5ezsPPaRIuUy22LBg4gWrYHQ93x+sbu42Jzvego+T8dpPqjnfggSyKxe78fEeHo+vHN+ud3tAiVFN02vdl2fWCKkYkZenDMHmDurqqjWMo77XHIIIce5YeaBQ4h8/ea2Mqrz+VmQ1KXdJm22qeus2mLFEUzLNE+FFk7eoTLYQErioGF36fUopg6zICFK50I1mtsCQFOtNB2MPFfVpWhMLNE3m5i6XksmUocuy7J/eLh+db0UbM/6Wrkqh5D3xzkrV4Wjdh0IHCXEGEKgs/PNPNZpM4+5tHawmgVKF+cXdlbdgtZ6uMvHCbtNjKFb5vlhykOwiyt79sGj43yYxoygsXejeTHfdpuhHwzb4zLe3086uwuIsL0Yzs4vUkq5lHnJrgt1KcUhhcgOU/NsmuvhUEzViweQsoGJiFMKse9iSsRUXff5cHLBeBsDi9LyudUafceBpjhuW+LWA69z+gm4OPXQ+AUw+m3n5qcq5Y2U5AT2lqKKZtnRMrpWCw8BAkEaWmaBkCSCWdVrrWbKwg6DrFWp2XVXtxRSGPohpC52UEdlMg4WmvyYgETR4WbFlcigWeHU912K0dmy5lyzOTytuzoPCF2gwGrmtbIwrdTFUw8E5iBECm3dadPguaM1n2/jM9oRbX+0E+JMzdhirXqEZsWONtQK4N6MHVwUzeTvVIHBq75wDccGtH2yDUxamSG+wk++WmbRqgn32rplOHvL4lnr7skO9vSG/viuxFffeTja8mZtAP00qrclzCpaaMBaY8yuj5EQg9e3t1az0/f740/Lv3bH/btpCcMf+3Jt1EldEhFVtWlapZrmAFpSYXP1dvcY4zIvS1lOs5tby8AkrBsPoUaSaGya9WMxwDGNpX1jDiucS2AO5K5KJyNZgAI4ceqSE9QVAhMfdj35IolCFAqcpGMhI1O1alpKxYwy5LCJYx7nu1lFqTOwY4sPv/nxeMgXh4dcZoJzYkUttvzgpz/7f773T9cIsw7Pnrz76OLyEB9qzdVR6/Ti+ov//K/9pZ/9wSef/uDniy/9WSoHncYlEq0MT6/qvkyLNQyuGrKxRLDprDkUIwYxjN3ICjvbcB5L9eOY93tAF1RgzgUBiOAKYWew883ttTG+851f/cY3v3Z1cfk//09/8/AjhQEV6DHsBgOWebEmca9woLJa8+MkFyEJYsRaTbWYgzgK+XxQVByzH8f7v/mDv/POt/Ff/vW/8dG///GnX3z+O9/9recP+BO/Guqky6Fs5Oxqe/XdH/wIXwAgGNwanaT52Bu5SRCIu0OtqqrUsB75NgtZeVvuWo7C2sCsqRdtMclhHUmpFbj1ISazpudq3JVWEx0wCylthsGBJS91znA8/3T/28d/9Ff/k7/867/5q4/eOfvB//p9K7TM6o7NZiAqcCfynCs5E8SLPtzvX3zxoiyH3/xzv7Eso4gwy7IsBDk/3z6+vAyUfvqTT//Rb//Du9vpcAvNAAMzQMjDtLnszq7O+uSA56WUyeBIKfVho9mON8dcasdUMywbHG9u57r/4vLRo9CnjnZd0evPX1H0QNj0whEgq0DXpxgihOeclxkSmRXjvBh0s+27LjhQZpSIGJ2oIcku7hLs6vF5H1Ot5f4mg2qMMYYUU29RsoZ5GXOutWJzFoN4YGLimDjxFlY3kYOb5QWM2Kdtv8lLXnJhMtSgdQSFudo7F49/8pOffPbZ9XaI23iefLeJjx7tPvr6B9965/zDv/r1/waPsRmiVTWHuWn2BYXJ8zRxiA5zdsTGZjAyvDWZ8iAwRbup2NeIJkHoxJMZwfUUj8IAgSMLry8AzREwr6ETXy5CHEgxafPPWmHWRqYgN8s5G7U1JolIoxe6Q1VNFcU33WDVtCrUiJFCglvJtZqpoVZlocBiAjQHLV6dJqjNunpi6zaWLrMECsxqCIwmKpmPY64FgFVbDpMZsMBRdtuLWsrh4f64zLELIgjWvfjJ+OnfPvwP9j/+d//9f/sn/uSvb3fvfO/H/+qffvd3dleby8d3S+BiM58joNJC5q4FOlviApjWLCnIEBASmELy2DMxWakqFtFv0vl3fvnZOB7uH24P034+5igl9b25xSNlFQAAIABJREFUzXXenJ31YdDsm7Mn5mFapuP+FWx62N/U5UC1/PyDr6J8dnX+7K//jf/wN/7Cn/5b/8vf+v73X+5vUDKCInLs4tYq1cJaIVGoCfhhgb1qXS9tNnYm4+Y/zCxN9LR6VQFuppoVYKYoQQJXgTDB0MCONpXVxb2x0/NbfdzSncWz8zNUMUAJEsLmCakqFHAJlDqJBipWAoWrs0dJwlLyt7/51b/wF7/zjW+9+8Xr59//8R/95NPvj0s28ZsRiZcWp6lalZQjuo2fnW8AevPmcNyPjOAGLdCKFGVz0ZFT1bJQDoGA6pRDCLFzcFXPTFbq2G/w/oeP3tzcW/Tq3TjO81yqOVUeD3Z1ue1CqtlilKHjsS55qdAAJSgsUuhCCp1OtkxlvS9O8pTRPQqFGGKMHGWz6cx1zosZqrXc6raCAgBfAQeYGbs3VOvLXwAIru600rzMW0SDgdyJqykVAwFX+N//9v/xX/zXf/WDJ9t//vvf97w/i0/2Y66HqR+s2XR0ISSWqhwCBeKASERmqtW7FKLEkvU+7y8uNrvdJeF4nJd+k/ptTGGbOIpJzsVUFaauqrW4Y6EYU625LEtdsim8gr1Y9SH2u6vd/ubhs1dfdF26/ODs4vxZiPHV9QsP5fx8d3Vxecj50dlZ0fmlv7m5nzqiJGxauhSnKV9fX282274fQDT0w9Bf3lwfXr64ff78xiegPc5FNWcXlJKn+Rj2wggx9RSoVl1y1amwmlarFeZgEZgSoWhFrSVyVpXIc6mH4zjP+eV+fnV7d5jmELrd+ZlC/v7/9duffPHFy9vXIQ6UYgybRZdlzpmaxAAAHh7KPJXNJj569Ijo/P72YeQDGfqBu00TGaDWvDnf9f0Ao9u7/X5/tAovfPdmP8ZRVZ9cPamdWyYrzgACkdOQhsQdwx/mO0n0hz/93jDE73z71x4NV1Lk6uIqT8tZ3AkoI0/LWGqWFLuuc8dMy67fbM83jy6vhotN2DBFr6yas7k72M2Eqe/7uWQ/HiKzDDEawGTTXMpca2YUU/dao4TU9/OMw3EpS/3wnfNvfu1bbtx3Gxa4UD4ecikx9pvdZeoGZnnyzrvuuDh/xIQYw9kwvLm5+e6/+L2a9cMPH1/fjGe7dOBi1UjA7FdX50/ffdR1Yb8ccs5aEEMSluxV1Ym1ZnNv+VDs5par8woetZeZmyFy+72tkRSnhv6EWfzCovtfe5WST9DVusgGt2x3MphbsSq1ZXyJMpwgTs3VwUMSMoeyVbPqK1629mZoVpFN4+cA1pST5spOxYuR66mXb+dfhBGJiVz+X87epMmyLTsT+tZauznnXncPj/71+V5KSqVSpJSCkmQyOhmMmIgyCmPCrH4GsxoyZwQTBnRlhjHBmIgBVZKgZEKFEknZKZXN6+LFi9bdb3PO2XuvtRjscz1eqcEMfPDMw93jhr97ztl7r68FWy/rgnvHZ9YBo4sSVkmXA2+C52l1DKxU0loY4XBTNe3dieVyMzYlVlMATB7g7M7Wy2CqmbibugePW7p7eVlL3d3s3TGMWTZdlatOzhHYeNxGDLyUMi9zCJyHmIcYJbiAicAorTZvdIbt3QAyLWaYqsW2zMdpxw0xD3fvXvzsB08O1y2nES7l5sCZh4ucfL5zcf6db38H0/h//dFPfvDHP8cVaMbLp19wBCfn5AaXzNJ9QELOsF566w7pPRSnYIQ1QOfv/jDuzb4rVIheGshdQ8cQRhD3RkQSSFJMKSWP5hpTHIaBE89lnqbpOB8NCIyceJPDxcX2/OIsb0It07w73uyvwAgRGowgDgOsqB/m5bgptBwP16+eP70qU56XI1VNkDovmTzlxDGbU9Pi5swUGC7EZK3OMKWUg5B6/Xd/93cXWFmKiJxvzyPi7Mtu2u93e2ecn5+32l68fPX89dOjHdxdrREQY2DBr3zzV0KKd+7fHZfNtMy73Q3chrS5vr62hS/G+4f5+OUXLyBg4ZjT2fl5HrXUJkv52nuP5mU6HGfXer4d/eGDw7HMReep7XavPvvi+f6IOxebs8uzR8OwuzkejwpzsDq11goHvnN5FlIopdXaytyiDA8fPhzG8ermuhbXQtjjoBV5LJOU6/bJqy8++fyLf+8//O2PP/vJ55++WBqUC6K0Uva1QjBs0wcfvVWrtmK6eKvOxJtxYJFyUw43u8t37pExNbSlHQ/zsptXvUj3MDCKe7F2ebnNQ5TEzlR0WeZSa1VZQ3nQNXk692fDQQows6S4SgaaedO1ssLMTKXXmK5Y93qy1lvA/PRfP61jeIPhoBuBvIu4CQp3dl+9w/AoLuxwYU6BowR171UdUO8QbfWmKcbIgSVLhPrZeDbmIYDLVHevb/Y3O5+sb7iogGHiBU4g55GcqR291tpUHTUNadgOtTWbNQ2xi8rv3r04v7xj5IfpUFsxWE6DkxdUOPeEG5L1qRRel13VHrnJDjcmPjW0rhpb6g+jOWGlBW7RFgYFkCDGIBKYpGf6Ho+zr+vrLdnuRELM/Uo5ehSpdXKsv91YG2scpwCuk3/J1zhXKBEJ+gTP5ivHcKLuwXpSBLiZUbdwmrc+NL2RfH5FMkVrOBCFGLvGk/oq5k4gYaZe+nNC2sysmZN9xYeIEx7//+ujG2VuN08Aa5F5v0jMbGbmZrpuq/2Lb5gBWk1dsi7G5mS9kB5CxO6wTvafdHKr8LAV8OrnJbgbS/eMcNfkMDtb3+vUrXnxno/DsMDILMaSJeRAcCMPHIT5WKZ5noVYYbVWoRC3SYTiNogE8xZz/usf/NhmmpdZtTEzC0mgnEOzRnOUQEaaKC1zJfbIAWIskOCH4xWJXdzb3H1w9uy4zFMJgwwiaMyRvLmTw7zU1vPvYLBiLkqBhGmZW8gRJFY9sBu5E7EKOw9hfPvBw6uX++k4YQGkYUgcQkyZg5NwHtL5sH1w/x7Mf/7jn+2fKyVkS0ZQszop+tmhH4vciZjdyVuv/DDqsm/09EJ3t+LCEmPQqCTQ5uZ49iV++P2ffO2j9+qxJgoPztp8vUhA5nx3e/fOcIkDQITi6AmoxMRCWJ+sXkBvamqKBiUlevNsdNawg0duxKdUO5LTsYXXewsEc/W/AcH2sZ/8BEx3B1YUEahXVavGnERoE/jVk+n5x7v9Ly9vP3qceIMYIx9SQAwxJ5SqZBQlEwUlND0QvC51Os5/8n/+H8OQ7t+7f3a21aYisRypps28LJ/99NOrVxMKj4HmRU3hQ5eAODX2BabWf0ERdjUvNHtrRdvsVGhpDkMekxNqqdefTPPN80dvP3zw4OE7b71TbM8J3lotR2eXqBJYC+ZljsGZECKlHBqstDbPjXkOYZQgeYNhoJhEApvXqrU1NdNSyHM0U/PFDK21IAMgHFOIKjJH0RAohp6J6E1LdA7CcJ+nQyDOUfKYIweGCImQMSXhICQOCiyffPLz11fPmTDGPMhwsbl3d3vv/vZR8s2/+Of/EsBmyD5zWypFJ0hMYBEGhZxqretCwG+EriwgW7uTzG4F76Zduko9q53gp8ZWBwQinY+xVX9r1jrcftopHL0pAMagyKwwM17JFO66K7N+VHYi7otuDy9c95u+TVhnTwjgNz0aXftjMEaP0mJaC4C7xr/f11h3iv4EwB3a1NV1dWf3pY9aVZglEXXzugY5QzAv+1YbCaeUSWAqy95lwJ1/K/74e5/+l//Ff/uf/Kf/6Nu/+a3v/Gvx1fWXT64+b1ru3b/IZ2dfXn/WlqJLQQG1JC2oOWxhahKCkIDBgUnMVOdZPWpkbrMfb+YPH70XgwAN3Eqb3FzIhhxq05QtBpB4iqksZk4+5lKm1nBspVWkbEWPVV+7z+fn9EvfeHi+OfuLv/jJ55+jTfBgmyFIiNJLk40cbU3/hiGgE3RYn3hnZwJZU2IKEozc3ah554bgMPPmTVxc+wuh8xDKIIYEQqefbhXTDctUOR3Mu3wDzXXM55hrrdVqK6ZKjUMAWfV2ce/cXWu9+dVv/tYHH77vVH/y84+fvXx9XLS6lIa7l1QKlanNVc2RE2JCHp1F4eyOeSk2tzoDDlRU0mgmEgKxpBxCDMKRaIguydWL2hyEpmV3nHd5GB4+Or/a7/aLJScKYpDR6zguZ5tN4FjQNnmTKLyUZ2gOtY5VOZtWr6zmFkS6BqefZ4jcmjb11mormoaUMxNz4OjkRLxogTvxehlozaN0J5j150IZbKe0Unc3cgRppq5OAuuMQ3dHuYPAHMCQdiZIhMYdYzTgcKBxKyAGAkmO0ZoIgwOJcaAYOTAxDMuulXDwBqDdkA0WEWg8y8QuSUDRqqnV7hXqZTCqTR1wJATWtcs6kLiQsHCUaVm2gbf372hr1ZeAMJfjwGcsLCG12q5fXZ/d24xJgtoQQgZ6JFupC/WIGSYi2mw27hJDZgq16jIXOIWR25UyEyuRIsZISXr5t5rV1tYGOqAU9eInNz0Aa4bNZmRhwEwtCoPQTBW42s91wub8zv4wCVPebg/z9JNPf74/WG1ZAbfmQ49yo7UVmS0EyhFublZPTbuUh44stFI1GCOIE202mxhSrTovy2F/DBxiGqi1utTW7PWrnTdz9aWWGMKQNzkO5LTYsizzOEaMWvj45asvnjx/9NE3vlZQYGGIKVAya5Fj42AhSw5M7O6t1nmerXlcD/JM7G46l+KqTgHwkGKOaZPzPkUSphBKc3dvqu7V3HMKPSG3FDMtWpZybBsJj+8/fP+991tTiQPQQGit7XeLBD+TgTaBRVLcHg6H66u9mQ45k1FTjcLKmgf56Gt3g+QhL/v9vrm6O5JX1Om4f/7sBVMKYkxsCjiJ0Bqa0NuBzF3V1dAzotc9ap0CcZKXmjvc6StV5J21/ntZaIJ7b3TDKiplMDHxysqvPnxYB8RsTWA55fsyILz63N2ZhaBdf7WKWbsd/hZuO00ZRKZQ62h2b4J1Z2Jjd+9Zp8xdp1nX/sSuAcCa+LJy1Sf/m3uvKYfxKZl+nSGYfK3/7QK7Dk+as/c2RWODo1lzJrAHCYkjC882hxTGiyHW2Kw282GbD6+uh81mHDMnJnFjcvFWy1QXcXcSnUpp4mQVLW9EYoA1BZxxef+stKqLibn6bF6EGIBw3qQzK8CENhtylDS6zObTvcvh7cf3z/Lmu3/8vSc/vZ5eI/owno/tWJd2MEodTSOrCgV7N09h5eqA1WbwN9Grr94LK75JJ0qm44K8AoTVtQOLBjdtLHCgVm1m7saBKDAJQ6Cu07Q/zrMaQpQQ/N7lRthDhHtZpuU43cxlBmHMEvMauJNSFIGZhRQNNJe220+7XbHJH739zmaIjGYoeZOBxawRu5ICFqNstgPLhpm1VGJOIcYgEA7NRIjcqtZmoszNWxo8qDrB47LU6dhe1zCBqjYttbhZaxwQvvdXf/no8aMHl/eGPOQsIdJ8PO5eX+9vboz84mybh7ifjg4NOaYxpSE6yuF4dZzt/t0tWYEu7C0F3g6jW2y6qHJTLCXs9y0mjAYSZmbVY6stKImQQ5njMMaY4lK0LMXP6Gy42G63eRh++vFPrXnRigRvmOvcioIYzfHSW6kxymbk3WRNG0fPIcG4erHmZmxmBihpRdVmrbaIZNKGi+iNbbbaap1KmRcyokZr+v9JmufAdJzBvhk3xKTVtL+T/SjtQBcErYkvRMR9mRAJAGlzU1VVMpBT75dYwQ13eNcX3aIGKzrdl4w3cPi6VpEzzG5lCui+CiPzDrxGUBQlmNtGQgzCTFrNmnrvSVZAEDlGlihBTYXjNoYx5RwiGS9a2lQ7ekVODOm+c3Z2wMgCB2erZCHGYRwl8Hix4cgKu7ZdsRopwF3dDV5anaap1AoF5R4Z5EIciEnBxGuNua6zC9kafbXmL3XUjk6FsW4nQKsHRXW9OoOdAGeFwMUQnLiXFAFReysscSAiU2OwcOxXkEEnRVg/y/W619XpTWin+Rinq3OaQfrfWH8ZsnUwAZ0EnWuZeqcdu8BkFVx10p3WGZzWq9zhL2Jeg4H9zY522sW8D0497KUrnOC3KX8n4djftc39vyuwblfFIMJq2rExh3VxS4++cjgz9291tz2dPvpLqGprzd07kQuAmGyN5UcQoijOLoGJ18rGLpgz1x5HRuD1cEsd7jLHGscFIWMlcQRUst7CICluNqmhOLsEERHVVuZSvQixu23TZrg4m9tiwTsTC6fdbsdRJNE4bl+/eCaatVV0+RC5WTuQIwqx5zTWuiz7hd0NGjNfXlyEQBJoGLJaydu4vbfZ7g41upbqzuZeraoqE6chSpPaatfKWTVjCxAO7MdKcECbVasiyYyUothcUOzO9mx6vUw6hzFyGBrczELgzXYITJnDhx988OjR/asXV9//k++j4HI4LwftEkRiIbB3uAr9WVrtSVALKQKmzbq3k9xTSMyyzHMaszeUuW0uNh50Oi5//d1P7pxdXjw4e3z3g589/WT3qlzcSWfDEDyUfcEVOLNVrN08zMykrQYOYDL0kDkXBiKp+SolPO21Zv2+IMKpLbpPPt4Ldzo41VOFupzdb92ktPaldn5stUpLEAJKaQYQByJmIt07Cn74Fz8Lg8fAD+68dWzHF+NhWoqZjXlc6qJmEQlGBA6chBSGWgzq02F63p6/en5VlzaMeTq/8Mnb4l98/BwVaGizsQYGGswJAcEb17l1D40V8wZyrm5ei05me2WRFFIrFQvT6irnZVeuZT/kzcXFhXlJAU1ZawNZTJCQ5kbzYfJMKWfqNT1kXWKqqu46jjnnkKQJQ4RjELBpU9WFidVcmIdhIK7alFiYoxq0tbq0skAikauEKAyz2iqBLcByzElkzGkzRiLa7w6BJbCQhBhSTMmdGXjy5efvvfVOu2tWLPF47+zeB4+/PobtX/7pj/74f/2z9C7pkckEJlqMmEMQJzYFRym1oPdsnCibzk93xiEIm6FHUdGafuZmpuq9hpt4xT3Re8UdZqbdjtpfVHgVtd7yyqc4JSd3sn4f9lvLT2fDvgvAzKwfqfv4x87mweep9HJ3Jrj6Utv694hlHRXpdinmLp/uKUqENUIQhB6zRA53a+qmwkRB3LwulQSdOXDtZi+EiFaqehXimAIRoBRCdLK2gJSOqH+y/9Hl2R9Wrb/yGx/97m/9+//79/75k1dPZl1qWT54e7N/VQ5LsypkQjV4K6QtJI4iTAIYJKq3aZrmo+KMtinMBz3efPnRu+8y8+WdizzyNF83mpgUDmE7Hnczl5wGr6rKLLbZ5LPtQ2FHa8u8f33ztM1Ylpta7N7lg2/96ru//Zvv/8a3f+sP/tmffffPfng4aFkmVvOiDrb+tnRhHBuv/I6jO/oc5gYlN5cgIUWHl9bErTsmujRT1bW18/NNVyub2lpSab4shdZLf9quIzn5dFwQQIG7obk1bi3UqqgGQFnJnMXhbXdTvv5L7/7mh9/8zm984+xi86Of/uWPfvpXh3l3PLKxDZswXRuLcPTo7m5poJzRi0RT2rz1aHtxdvd4XYGBSbypk0ukHEPK/PLwPGVKgQNTiqCg6gWsEDpMuL65uji7f36R00aO1y+nmXKMVnxZdMjh6sX1drPRSsvcyBIhOzVmQU+XcFdtywJT426mPGUgwDlF9HDOpqa6tGIkLCmwhCTwgB6pSx1gNO+5KreH0w4TMuBgdzYzZwlBllrdTaKYeT9ZafPOTDkIDSyEyjnmh5fnr18sS1H0421VY5C7AK1VIycjN1trnrFWc7Nz3mxTThzJvRjBofM0DykNKS2qivUwo2q9pqHfTeXQwGAGC6/TcnOOlGKY23K2Pa+tWGlCpq3A2dURaH9z3B2u/82vfYtjE7LzYavbTlRDRXb7idm3220p9eZ6H2Oe3co8vXyxK6UxszOhqcPVrUkLIhIIIGIRQiBT02LFam+NWx1jXeoCM2+WcjK05jWkSOLL0ggcIjCaEu+P0/n5+dXu8Onnn72+uSo1FTNVkHBOWYRzjimKWjErzNbnVnc7HPY555glxtGszLO25sKec87jeDgcicoy11qqqW02WzOQsVDIY6pzE2bhyEwppcCh55ZEiS3W7YNNWZZd8Y+/+IQb/843fhtMajaE3FpbyjRuxih5qnOdpt7KmlPawiq1+/fuxzHIgJCkoeYplGWxqqp661pgQGtttS3Njsd5mebWFIzSMG5ijDwdjzoXKxYj3n/3rfffe+/OxeWTzz8p8zEEgZi5p4SYN8Nm3G7PYhqGvLm+3r96sb+52g1jkK9HYhpyqrU8efL8ax99EGSY53Z1dT0ty7IsIbEHa9qUpJZGFGpRLapqUKBpt5bDYNoAkpycV5fCrQlnDVrAratknTZuYxeAE5X9t4/yjhDETdf+dgDu5nY6Vq0xyX1LxZuZak0h0VY7CQ0BgaTHcOgaEG/mpGt4A3roSX/uGUaIobtDqEMnbmt+DYNaz4Fxd73tOrlVWDmdpt6Vi6ceRrIy+B187LAdywqkrSpQcwDzoVDPygmrbRJkFElc1L3XBYGJnKuWuc7WvLk207lN48VWElMiC2rsIKhjqZUIecwiPE2HaT4ioLfkbOIowuOQwkbc3U3hZm7TXFGM2VPKbbGrOk0HpCGXfSVKmzvnRZu38taj+197/+06lf/tn/1LeU2oSGn04gSTAGMj8maViJRNhHuVmNObtdVcV17vK4PcV5CsE+1H0C5y6Q8GnwZXdpKwzlzkLCHEBIqlzFVLkJgkxBiWZVnqcjzMzS1mHsaUIuUxtuU4HWstBwro/ZkpYzPmmPhYDsyhPzVEnIObtqub49XNfDjgbh5+5Rd/8d0HD4HqqCzh+uYVySEOUnVhphRCyMHMFOYCFnIhJXNblvmKs4xZotm0PCeRGEOtVWKBsEGrHxCOFCeiKsGFynycjlMxtePxeHXz9MXdu5fnF5d3Ls6259u0zY6cpGm7Od5sKF7SprSFxOMQndG8ND1oKVCO7OebPA5pqtV9aiZz9VdX81LJXFpr+5033+WNpZiHYawMVZvmw9VVpZ7nKBHOOceuXJiWYxrCNB+y5JxjGpPOVia9PDsfLodyrK9ev/jpjz8+f5Aev/Vo2O3M51JVSJjQatWyTPuq1ZkDmBqakk3HmTkmSeP5MO+KkpZlWY4FC8ghzla9y32cqfN2RTW5h5AUau5qRgwt3hna9fk+tQY6uJkLnJlWltWIjFefX4+4PMmv+m24Qli2Pth+grRus8DfgBGOZspMJEwsHIhCULK1lkdYBU5Ac2aKLCBUt3U5JYQxSuRxO2w2Gw6YD/OyLIC0qQlLoFCXpZV2+6/1BCmQsoiTmzszmwCMNOaNmJI2tOI1jnJB2yQDNczHpba6Px6mZbrZ3XSsRl37uyGR8pDRnBVQstY7MLxrRLAWla0j66kKcNUGdbiEqI8Ka7BFn4RVyMVdYKI9vwIgCz0ZGMRKxOYmFLoeyt1hDDIj9e4RJVqnpB6Z0W1YwMlM2Bn8W0yRyUFM/iYzr38wAcK8bjirbRE4iQz6J3RiVm7/ib5SM1HTtqZJ9O7CvmCpOVj78LZWjdC/emv8f/j46kp4i+wHN+88mKp2lKonxtup+WvlVvruIt4dOv3HYozrRgi4dzCQmZVjEAkUvOsDJbLDmhUz63rXwFK0ua01wj2+kYnXUDT3ICI5cESlxWKRkNW1sUlmHkSthRhZqJZWlmVZFlffSKbALHLn4o7dvLbgzVttCwgLFhRPLSZJqE1LA1g4uDarDQAHIXUWGCq7C5HNWr2mkIcY0xicTIQp4NnLZw36+INHzz9/8fKTBWYEODhukhi3qggQFnc2bwQ3NWtM8Is8LkuttQEGi8xIgVCbz/Xm2QuqLZKJOoQhlphDyiAzrzHyu++9896777ap/vj7f/X0s+ebQXTRcqwiKUqo2tyNRUCucAZLv4G6CzUFdUNTc4NBVtzAgkRrMKXACWA3ZeDZZ9c//+tPf3nzC4/uP359ePXyeFWnIjHVuf38s0+g4MaO3l8fRBiASW+aR9dl0e1z0eCOPr6vAPEbLOu0/vUDXEf11+JfB0ObncotVoHiLbEAXs3Fqzx1vV37n82J98dlCHG/233/z3/oaL/1u7/+9OXn9+/sj/OxmF1cXliYjvuiBWIrINxMp+VY/Xhx+eB43OnV0hSqWGb8yocfzjv98smLJ0+fzEdsU4wRLtyaenUSipJ6pbeaq2pbFA0SmFxaszIV8ph5iCFTnedpIbaYc0yxWtlfH0DPpvmQL3lUdtHEUpptx7Ho6UrBAKgZwUIgNtI+VxNiDHnY6HJEX+b7+0sAeYg0DDGGMPlSqjGDGTnH5gxDWXxawGo5eYwwczcxZ5GQmccYzsbNJmfXWpZZi0Iop1RqG7K7GRG528V2KNVaQGXPNHzjo288vvPB049f/w//3X//k794gYZN6gugmCmZu1hfTk6r5Zusu1WB14EnAqHTM2itdWFHv3mYvFfPOUiYJQQmVlNTJSdh6b/Y6iqHUU9A7LQAEzOfVK09XY0IkL46d8Er3AF1W5MhWUzXoqauGOzwFYPN1ZqZQ5iEhQKvMpUeHMQEIV6ZcdcO6XbHBK0HBuqnt/Ux8O4zF5eTm70LDW/foU6gW1MXSlq9QUl4Ng85kuL3/+gPJ+xe7X/9H/4Hv/f6m69eH66+98l39zfP33v73Wf+2id7vdcxkBFSitDagFbK9mLjREupDdWaglELpkNj85zyl09fbLbx8u7mznBnHGk/GQcq5VgWO84YxwWuMbTAI2dJPDAD1lqx2iyM4lQOx5fHm6mU3cP7j9565+Lxow+M6nsfPvqn/9UfLOlodZIwBnK11mUhII8xqrcTT0Qr1+f92ndFg6GLt8XZ4cw9xb9Ph5y6EJhUFTA38mbSpI+41GNZAoHggeAORdpkCTIfllYjIwcJTRemFgKxVFOVCAT7te989M1vfePsIv74Zz968frVuDk/1qXYMi1ztNC0IzgIWUKhvvYPAAAgAElEQVSQMXPOHBN6vubjtx67pul6pwZJIYRo1sxra40DHXY1RZYsLE7szZVRghCxMLfr3WEz3jm/PH///XdL4R/9+GkgP+60VUTC/uamTjXIsBnOW405DDP23VUkYyQmde2khsJVV1cPertAj0g1EMHUFy3MFNQkRhKCEXdaoZcOknYyDQ4K8OJOUIAIPSHCHEbmPcRZyFbhVSfuTsuzOxjLrrWqKcfNsL2R1loBw7Qtc4sC1dZDA0kI7tO8nG1SijFKsKo8wIo7EFKSQEZQwjIvpZazzYYDszgY1tZ01TWOZyVcIARy5p77Y15VtanEIMJzmaou3rQoCJimxbzxzPujHhT/Dgdyixy348bVS1EEKq3U5jnJ4TAvyz7n6Wx7Z5l1nvzls/1+X0zRal3N8s3KXB2ezjIzL0sJHGJOgVybNWj3XAWJwgFwUyNv1lSZEJxZ0EPG3K1ZHASM0tqL11cxj9N8/N73f3Szc8WiIIRIApQSk/TVVUTcqav3ERhutVaRMG5ykLwsFTNIEHNMQx6HzeeffkFg074MxuO0lKVotc1ms92eBRJza61qNTiZmaoSewhhk7aSqJktrbw+vH7x2bN//Hv/uJmGDt2x3Ox2Rn69e/35i8/2886Z7t6/+/DB45DT9bJ7+/FbnOhY9krt7vld0xoRDu1wdX0dczi/vBCWIJFQ2HtCN4RI4e6oddrvWEiy0P5Ys6QHb9/91re+8dFHX6+1uuo0LXlMWmut9f7DdyWk8ezOZnMGko8//fzZsy+ffPbs6evrGBBiGAaJoe52x6UcXjx7/f6H727OzkOkm8NhmgMLN9Wilse47GdSb61p89VRy8zsVhyGGIRZ3FDd3hx6gBPotBopVsXuLRHeH1B747x4s032uQAuDCfv9hQ/HeuFiWMwuLUqjJySsys1W09KfhLmKFFg9LzdThmwyPriuC1N76ZHd1X3Xj/CK5Il0rX1Bur0Ajhy5KClqYEILOyn39ZPUS0kRKsq80TU+xpk2+VX1guI2hoss8q0DOiBmQzhlRQy6m8OKBAatVIJFIjjGI7H8vLVawIFiSlKsRpzpMSV2rIsVWpMTBydYWacaMz5OO2aITAioVWbDyWM8fzsPG1kf3yl1oQgQFNohRhUbarlcLwOHNxIYla11iq8LoS37719eXHx5Gev8BSKxBjaQqhVpEqgAmWiEJnIelI1Wy+h74iCA7BTQ8nfN8WtEvPO0tEa9ryChuv74uvkCQdTTBJSgCizbM43zl7LMi1T0VKaSsA4jpvtGFhbWcyr9lYTW8dfEaiv/UwhhJyH84tLJi7luD9Mr3f7/b6VirO7+cN33314/xxYxswvbp4cDi+MDndkG6Ko+2KV2LXVWmtrLYS02QQilDYHKSGIm5f5UMschtxYqhYJDKbmKlI2Z8CYFqN5nkwrywKa4W0zYJlevizX9XgOfZSj5rg5O4/j+cVxmjgVIzXX41KKLuASIpM14jYkjqKcuXsCpYSlmZHup1rrPC12c1NqxVymXPH++YWqnp+dHQ71+mbPLGr1eKitImWcnV0kltbKMt/klEXa3Yuz/WHKwxhZ5qoQT1m2w0CAHOTFl1cP3/6li4st6MvDtNvt95txw+7HwwJjUyxzY4IMTAmkWHRxXRoGdZMQVbXVBkUABVtV60zca504rnhT6+5xYlXrKbRQmNtK8DrxWhPH/ZNTqh5RN70ZdVECObkBa172aiHr4hlheYNI+Ang8tvDa1+aVrGC9Id6tWcFIYWQSy/HAIQkSDfHWbcFCUREgqQUe9K0trosy3ScXQEcAOQwSHc7rwIxczZi4hiDBCUj0lqrkcUzXupMCWWej7tDWepm3Ny7cxE5LjdLa7bUBWUhRgixHqu7g52FIDDSEJmF29L6QR7OXe3u3IPRV30G9/ZG425d6ytnX8rUlAOxgISd3N0kEoKLEN/yV3DxXv/na96JuLlx4JRy01bnim60Zqc+Y3fYEE4EPem9VlPx6ltZDeCrGql1+RCfLhn1VdjhTERh3RLczLFKSvpl51V5clqbTry/E6yt7YfoOmDuwR9munYn4hbUXDfA0+1B66L3VenWV5Wnt3vfibi4vakcQFAz5jff8xPG1lVXOMGqK+pg6AwnAFUNIfTfrAfwiIiS9zR4DvDuHISZmpFqb/giZ1mD51cepcf0mzuZd8MiGTGFyCQwJo5JknRYzcWNnUUkBHcqyzJPxYpD0YL1Qb8VW6aqorINMaRKJpEdam6lLKBuMHHnBnVpBLBXBZMH0lIlUAxk5Aq0WdtSJQLiBvz8s59dH6+9ysCb8e44TMt8pV5h5IjQ5qW1HkTQGaYeNN3XlCGLKcGoObw0ChD2AM/EiTQmaWfj9Oq4LzMJb4cxbzKoLWUh8vPzTU7x9bPD0yefqkI8HnZHqjGmJEmozcXaGu/mhNW4BDcHwfqq1PEghjM5TLvWe40nQ521sW4uNosfv/zy+b0v7ly8vT0bz0xa4JAlt2JXz1/DAe2Ul5obMxE7h+7wsltk/s3x5GSkMvIuTFwfGfLVoQpSOv1U35dXGLn1cZ/fbOMrnrUea1ZM2d3R47GYmDqWapFEXPH65f4HP/zuv/Fv/9o4blPI6MBCCud0Hrged6YLmirDJBAHcjJmznlTmbhWREqxbc7P2sE/+/xT1xgDzIi4Y+ZOMGYBk7m30tSbnzTgkVPiqLUtzdYkPXWYBE6OGkhizOwBuhx2x5vl+i2+BKfxIpxvN1O73qRs08zsKWIYk2lpDcxxSMkA08KCFLvztjGCmqlZZZVg/TSs2nuuuWPfzKxaW10o5phoswULmmPMPkSkKLz65oiCcIgsou7LXL0hhhSixJisaYyRpWsTqxCuX766en59sXn06J13H9199Pyz53/6R3/+9IsXKaGVYOZaFWCz1oldwyriEGZzA1bJUgf3+dZtRwCYu2y5B7A7wE5MbGCW1RojwiJocHd2537YNjo1P/RRglZTrcPMQgj9KaATFnpafUBwEjaA+ySx4vK3uliwdKpj9R4iBO5p4kKnDazvFCeug6hvLz062wmdUe7Sr/5S9BWRLU7WkhNX0DEAsKxnBaBn7TERByd14whXqNYk8U/+8C8//vKv/vXf/gdff/iN+mtlN7/8/k9/MBLunW3i/SjTQedwcygCksyozVGIyasu8xEREAlBAV9KSzHcudi+eP36vMU88jgKiwQJOTNMtBo7vKHqARHpbIwhMrGr1qZqzGEsWqrO++nmZr87HK8uLjZzeTXE9OEvPLp7//yf/s9/0I4WBqAsVZFignfnNfKQj0ujrqPugnN29CcI1m3+JOvbyz23QLmDlSCUugSETsaQMIsQOI2ZlupMzlpVe1vK7eGKmSUImLxxCpss/dx8MJ/bYnXBeAcffn3zq9/+6OHjs1dXrz774mevpnl/mI7zUnR2xzyrI5g5wBIoDTSOISYwea2orZr5NB2P++P1ly9EIkd2ckMjMmakESF6iM5Ujc28AQoRdYmBS/Hj3B4/fPT+O2e10POnT121L/ZQkJnWIpRTytbQE4+9B91ETuNm9Vg6gcmswUlAcOlVjZ1rY2YhVHNTK3OR5izkvetVmMDGRoC5an/ACJ5B3cjbgEa9d8xI1ZXotudmzc0k5lWJ3p8PY3ePQc6351fjfNg3CsSCIEihY1nNPTAxg+o8I296SI0ktqeGWD27MAcRieIc5uUo3GsTAeIQuM2tVe1BV7di9Z7PwGB2dgK7BxZ3N1UnaFngDqHIDLPSKhHRmrro19f77ZmwkIiM45gCirdYS4pgpmmaj0dv1YUiPE3HeSlLa2q2vlsMcodWd6+SAkdBc6UmzNZgzagbaZWIuUdp9OGBnV2Ve2cjqQLUUzNigCsJj9ttbfXlq9dPnj3dHxETEEhY3FFbleCq3JqDtJdhg6DqTA5wlz67A84hIEgYhpEQy6L7w2IKqyRCKdUQI7wnoLmpUY5o1prW0hq0NQ0iMYQYIkVCGrx60aLVr66ef7l/fk7nY964gYRe766O7fj0xRff/f6fvdy/iCk/fuvxL3/jm/cf3j8/O3/r8ePDvL+6fjXVw9lmTBRBmHbz1aurmGNMWdUIdHl+h6JMVXOchHb7/WGphaCtKnGtFa8PeHRRvvbe+7/+7W/fvXtnv78ehmGaDrWWaktz24xZ4pDzQEyt2seffnJzfXPcT9xQFa9e3cRo52dB1YZBPv/i6dnFeHF5GSLHFKtWB9d5mebSS+D7pNGHCCIWiLGbNxB6E7BWPcmf1kKR/lyeTjcnLm4tplo3k1v51d8WYbmrcR89OjcOAH0uAhORM6h7xCSyUOqKfjJT6rml7NS5FHcYiJ3sJJ+Ce2//xXqUdOqdux0xUTR26pOsuXXvt8OjSCcXV1qe0KO3/NbRz9Q5hXU4oRVOv30PvEfHE9Y4gDUaa8WwmG/BGVorUzodxZEzOTxxTGNuWbGfoqRmJkFCDIHCq93r87gNQ8gpirAkcmPVqrVO0xQCuWvKwuLFzGa0pSb1JMkyh5SYKQlHQuOlGkBkR/NqdTIQm5PEzo00b/7gEYZB9tf7j3/6CSLYE2kyNQmdgbuVyPEajbz2rgvZG9B/vdr9ePTVme00OxqA276rW0IYK3zAgU/oFUBQ19rgzCAKOeQhNmv7Y511IQEEHDlGiTkJt7rs1hSyfhEFRCBmCQnkrXmpqua9RlObQUIa8vaiZcLdO9u7F5vtIMDiZNfTs6I3pe1oalvZJCGFizCJk3mX2DZyIeYYcxCg3Ez7q6vXRrgIFxzz+Zj6BqbAEMazzbDTw7FOxwNn4TFFO2sE++zTvx7SxcX55t7lxXYMh93VItPFxd0UQkyb7UVqtuyPN0t97fUooCGOLgRwCJFQGWRriJQG4Zwp5ziOyRgxlTNBWRASxmFcyhJTCrMxI8XEvKSEzuzM87Ty7tRqs93eU+ZUIaJaVX1xs2U5cLO6KNC8xGA58IaRGWWabphMS5uOi1BEwXRQc83OWYRFJIo6iNhgWpZSiqqht3WBzYjMuo/YvKk6ApyhsLksBjU3MHrskTivXDeBmPREa/W7ywzs6IQKA3p7Pl0fxr85ktEt2LCeYled0L8CSPTTHJN32B0GktXSxqeXEY4SJQQCe1UDgcHEHGWpi8GMrGlR0mWZvdeV948AYbYoauJk5CQi/f9IokzLERkWIaMMl0OxxdWnOtXWtNYQQkqZjedaSitzm3VWSYxgyACQciD1UgExJ3c2JQODBNSVk+au1MU+PT6ESQIH5a469Tfv3YmA5xAosHcjYDBEJjnpMryvlKEb3Lx5XxIdABNFZjAE1OPc1Z35RHD0dVL9tGp2VGudcdZ1GXB219U3iu4F7wgUWRfWUq9j6l5T9GGHTFc/eA8I/Hs0VLfb1jqn9wHqNN10gsb9KxuZ/92vc3sr/e0v/u2vByK8AaoIQYSIzDqpCgDEFII4oKau7uo9SBGK2qp/xVro7ghMoXsy5LQpe2tqaIrW8SozMwIn6XosNz7JcOCs7tpvjD5FhhiQQAHsIg4JEmMwNwh7c6tmi2EGDItUD0hEbWkwmsqyTRIoMlVyIglMJIphpFa8Hby3MkVictIChxu5JeNBJItqg2I2PYxTQ+XsxunFi1eP7j843pSb/fU7jz+4OL/3yc+fHG8OWvzY1iA96/3vPV6gb8JuqKjzHCWKhEm9NPMKyQiMIWEzBFU9e+euEH3y9Nmx2FwOFCeF5SE9uP/g0cP7bS7PPn2+ewI4YgliMebM5Npaa81g4nJSLa29JGtcTzdWMSN0wduaUNYVmuagbtVpSLLhMbx4dvPzn3z+4fbtB/cf0N7HvMmWr+phORY4WElYSK25qZows7jROqvcrmrAavTyrmruCpR1tyWsp/r+qTucxB3WHORMt3oi9q+qtuykxPKTJrMHkFLP+HOHmykCR+Y4zYci2D3DX//4Zx/+8vvndy/DsygSm/o45jFvyI97X6DOgWIOEJ0q5lZTjs4O4hjTe+++P/D55x+/fPYEl5cU0zAfi3ACQcEUpIdwqrZmpTXtc7cESTEFCugHRNPSanMzN4nMHIm96dLt4qaGCS+eXhFt7z946+L+ZbEthzphZugmh+1mEGOhRThvxg0E3rKRElTrsc7eGtVS3DRE5AFDVwMxamnw2qq6wsGlFp1uso154MeP7tRaDsfpnbcfxigxEaDmVcmr+sFbqYdW5raUi83Z2dl5jomZ7mTejhuDH46H6bB/cPfhdNXCRf7m17/za7/8D3iOf/qH3/2f/sffnw8YJJqrqlaz0ymYyeC0Cg1WD3QvHCLqjScQNrfVQ+eu1MHWfqnXztj1J9FdAE21qarBmNlZAbK1WomIe1QFQGS6mqMJ7OvQtoK93cKxFtB2CwKI1uT1N54LwF0ccHNlAEySuBu7mWEwo1U0DNdOYjExuiKsB3zQ2k/r6y/lxOtqzD3bEsApodG965IdQEwr1XX7zW6fZSdnd6vuXuZ68XD45AfHf/JP/vN/9B//3m/+zrf/4e/+Rx8+/pMf/vjP7+Z09jBHi8ddeH1zmJsGgkaEGABtrcAsIgpLzoNEJVJ1zOb7w6EYhRQvzkNMTUuzEMe8DVytHmvzonAtLFMJZo2Px7ksS05hHNPUVL1VqsXnZZ6+fPFFa3TnbPfg0Xsf/eJ7/81//Z/95f/909//X/7FD370MVWu9RBjTDG22g77fRyGbhzFyvavEKPbSRhuDDcR6qGLJOynSMiQA4habbM2GGKAeGIKlEIMgQTSqlH3vEC9kkhKKcSg2XmRTYpEtCutHI+IuDjHb/3Oh9/+jV/48KO3797PH3/6wx/86AevrtvVoT358slSQAFOqM0dxiRBKEsYIw8ZIbI2I7TW2jTdzLObFkSoVI4ypJRyEna15cGjIWYm8uaFxVmYWJZi87REBtv+1YtjwMU3fumXHt996046//KL588unmlrBMubjbtIHInPli074v7y7ObqRSklZh7Pg5kvS3F1MFjZHd6YWn8YQqfJunMfbmgGhUpTduIQglBAEAazsp2OnGqutHUxsBKJOJvXtRSnWz67mYDWVNNVV3Cq0IG5am2b7ebBw/vPXr5Wm8YhxWibTcibFkO32JEwEVkzq22B6zDEy7uBzMbh3pguam2vXv0/fL1Jr2RJdib2nXPM7N7r7m+IeBGRc1XWyCpWNUl0kxTVDVALLSRoIwH6DVpqJegf6M9IkBYS0EA30BqaYItNsKvJFlks1pBVlVmZMWQMb3D3O5jZOUcLu/4yiyi2LxKBiHT399zvNTv2jW+m6QYRgUNd8KpcW1mjW9es+pZo621yJFq7Rgh8Kj8CMZG3Gjs9Bdoxm8GqkpAbV1U4Pvv0xVc/fDv1rJW6YRt2w93hrjeo0TQdl9lNMc81hvLOO289ffrTEGLiOJURFUQtNcOhbo66lOAouTKxa3YlywoFgYlYi3ure2gaNnFuNwC11QHE4IAY4xkvZvbWW289f/r0Zx/97M2ba1R4RySioFJyFFNFqRlgJlVbpy8mhwiRwMWNqhEQ+r7v+00IaZ7yeLw1Rc7I2YXcLG9FCJSLgmYjyrVqKeM4uhkzYQGzdDFtNptOknp3s7+7+/woey63+//7//mTP/7Hf3z57qN5HGHjTz/7GQd+/vLZxy8/PubDstSPPvv58+tX3/v+93/7t3+72wzPPn/+8c8/uTvc6FJDoJi6y/MHgMQ+XVzsqtfd2flcypxzqXsiChL6biMhHqa626bz3WUf+t/7Tve97/zONz785vnZ2e31m7vrGwm+2Q03++vDdMia1Sqjgszdi9uvPvtkHlHHNfv2+mbvVhI/ubh6uN2e7+9+td8fN9utOWmtrpRrPe6X/e1MzmbkZq3WpiET65zNzdoDNrhTBHQd6E8jvTVB0/2w7vd7zt+b0f8eetX+xtxImoeEIS1Ava2ZZoQQIjMpWcMtWqM3CQmJkUGdxMFYa1xdnU9yndaQQYAB3mqCTyQ2APKYEtycaTUvusNh65EAQKvMJXJpup125msGSs2+cqyrJn9d11tDu5uDmxhtZdHboNggNC9A63NhswafExwGLqELIaQu9kO/OYxHLG7Zy5wLFiRmod12t9lu4zZUrtWXKY9zXtS8YTep63ZnZ8JytttWreM4qlnsu7P+vO86XFwsdR/Fo3hd5smzEvJCc7VcFM4iJASHMldG+N63f2t3dv7pL55/9KOPIYTsZpXcIBT7gaVmn06HsfsjH9yMmPne8rweS++1Ce7uqyxrJXFPqggiQ6uDNZzSxvp+U7SqW3MYudo0ZSrW952I1FKnMpVc4GjVhCzUZrEQWLxVxQMAx6YUAwfiGNTVHHPVcSooRwFx9C71/VXy7YVt56+//8HF+UBY5nLcl8Ob6YXEUmV6dRhruLw827mZOlHgGHqqNudyyHPuPDCXok5WijuEmUFSst3u75zYGwUTJaR0Fh/tgudhMdXmS2LCd7/1u1BlhrAseXn5/OXnr1/c7P/6/OLi0aMHb7/zJKUwDGkzdCIaO4q9hMDMiDEej5UlqGktWqqmwKHrIBEsc3GWUJ3nWRXeDxuWKBxYcgiRWZwwbLhLdBz1bl/MSt8hRSrVx2U6224vLs601P04m1pkHA/H2+XIChB88WVfciyeg2u0gnnyWo0oCXWl5poBxRKMonVDJAqBqYtdF4bPnj/FAlSIgZShRAZoUacwdKpmWWOf4kZiF6dlmeoUhYdNylMJLRK2xW0DUCJvpe4ApA1SZmADjKgVqnmDvhqita5AfpLiENp026obTnLQJkw5waoOo46NvHnXfNXt2AlyAQWkEPuuD63KOtdaKxFI2N3PtmfFSi55zkUBKO5F93ColsrsYhypkrt64aUN0JUrdtg83Ay7nnuSLmTkaRonzUPqQ0iqdntzi4LlmPOc4VjKwkbDptueDVXr0A95zrwsDFeqtdqitaFCzOTNUOFEDhFZZ/MWZeO6tic0rQUTM5hJgkhgyHoOtsgeQAxiJjC5q3tK0dxUuRZVMwaLR28idzYK7FVZ4AqszYDcqtLdDNJymuAN+zLnNvFqO44AIFQ4jMDeNLncVn1mdhBbW41hRquRmaTp6Bv+/htQJLQl/NcfjQzBadT6jc+638++DGZ92Sp4/4d/6OlBhFVbcTxJkBDEm1MD60oqwiEEB6CoVr9A3xiatV2qTh5CaDufu6uZE8UgzXsDd4IEIghaIae5y9pLf1LZEDXTRyPeV+CCVi1CIBZmI0gMIcZxnpI7Ezc2s3WKuwAGItFqXddTYl+DVVycArGweParqwd7Ox50sQmoUHgEAklVXfN/yZxIpeXg+jwvFjIris5XV5ehC7H3Wuy4zDH2V+882p6f7W/2480RBRA4XF3vOZT1P4559r5TZzZzEKRDGEiiI2j2o5qdPdi91z2svLy8uV0yFEaMs/Ph3feePHr84G9/8HfPPn0Gxyb0daaI1HWx1DrlqdZKiaUPBDbSJkFvptzV6CHridChbZ6ntcTUWQKLcBC3ME2Fg8Pw6vWby9ebb3/w9Wevf7Ubdq6+jLnmSqEtlMrsEWxsIG1jxqoqbUMPHGA0WpzJyQAY2QmHPt396+Hi18TSLVRwHaFw2qaZ7xOx2sv7SRHoqyOXqJVVUEPk2JmGTjLpT376i0fvXV09enDx/PL2ON7t9zEpS+ekCBVcIG7M5rYoJIbYd6peNFfPIW1fPr99+vQVFNXJFeBQ1FxNUVkYkVyaEVbhDXdFIAksAVzboEamVowURCIcOjHUpc52Un8YWx19vz+i0pCGjrGUfSCBVWZPAUU8CgkDnsk4BCIWNVtKXXKZjqgF7kgdWGiIMYRmnBNV19owbzI3LUf3EmPabTfM3WYIV4/ORZjIS51zMbOaTeclu+l0N7KhSxtnaT0L/TDEKMsylfmY5ykf6pPzd5588P7X3v92Hy7/t//5X/7rf/Xn8y02aTAHtCo3RZ2gxU9Ryx80h9u6/TjawZHcmFe6d+Wc1y93vXt8raJ1NJZjVce2nOa2wrYU8Ia8e8s5bPbw9kEDwqyqKwXgJ0fGPX10T1jeGx/aIsfMzGYKeHWFO4MEAAcKIGtiwsaVG0G8CXUZ3joNmgGC3XDKBwCoddnayhkoN20i+ckVsZJjLQEKZrR+bEBt0l5mRiPRI7EEF5+ygbF/nn/4Vz975/GTr3ztyT/7R//JzdNfTWU8lLLpOYb+6tHmeMjzvEAgYqVkq3XXbWIS5xqYY4xKebH6Zn84G2Qu5TDOJNxXy/MR3u12mz50kyyaKxvYmSFGUhWLinmSOGy2vbpI7DZnZ1Z9PizjvHTTvt9sn7/82Q9//O9/7/v/9Pd+/xuxo8s/TT/88U9ffIRsJXVMcF/gmxXCQ/PqA1hDK7GmYp3WDSNieJuJ2sce+wRhFPZw2kQqu64RaZEl9l2IwcmdVC2CTYhcTeDuk1ZXzdO4R8X7H2zf+8rlH/zh73z/d7+5veh/8tHffPLZJ0tdQuhUy7zgMCMFhNhYK2mCByKY1ZxdtW1eRqQstR/YLilOUIWqqk+gEGJk98ePL4vN8zKi1hBD10VQN41lHKsQaR5vbyYuv+g4nW82jy7OdJyi2zyP43hclv2crXoA3Zmn1PWXj/rQ73LJxGTky5JrqAa4wtha1bFIuwYJ+GLWaTJdAFCHAqwAwxQhgCmwtJ6s6qdgdm6IlMOZXG01ebZ7tim6iRoDaesprfXjOHuuC7F1XQRsKcuuCwRwFEkhxOitOisIixGh1qyao4Tz883x9khu8zyVXOHGoUvC0klM2qVu8mODadT8NOMSvB2ouerUtj1tuXRAy51ipghSXofvmou12Z3Zna0Yil+/Obz/FRhoLiUypT6ouTsxR7i4l1WnQNhutmY1ho13xHNzQsFw73cCGbn6mmaxFFOQuutKIzWLIDutm7g1KhFQVzL1VmAMdwuMZZn7PltupUAAACAASURBVO1vD58+/VXJxgkpRZdQ3VGMhrW5t0nav8hNRZuryJ3c2EzMU58GoaFmP9zlN28O7YtLCYEhIaiqOYrW4KHWkpcll2xVhVmcuSFsbcCKMk7T3f54ezumKQQLP/rx3/3ON38P76JyXfL0/OZzSXgzv5Ft2Ox2y/Xd8XB49ur59tOzbhje/8p719c32+3ZsiyoAmKyQB7OtucgPx6nooWEAgd4NfUg4fL8gh9EJ9+efUNrGdLufHOx7XfvvfXe2WZjtSx5NitWzEnN6jge5jLd7K+7uqMw9NuuHzoRCKEKQkCIQiAFhIfd7iExzs9vtfg8llJ1PE7u7EaW2TKTkRZvJGH7ppuVoFHcjQU52UjuYz+bX/A0Mv094u8feBDdz8RAUzkInAlBRBhhTY1SN3MnhsTgBNWqpcBcm6FMhANBGORrGdXa5rsGsJ9iAlsKvTAYbW/FScJPSCm5mblpu/fJzFxV7ykXBoSFnE1pFWC1Tb0JltcOnnuic5UheyOPmgpshcxOe2bjf9QIBG2tsW0sJDCJBOHQcb+JQ5+6buhYOPVpognkCFS9XlxcSGrGf61WS6laHAT01G+HYbtxMzYwiFV63jjDFcvdUpby+OGVWRYqUcAhLD6ps0ggdrBDYFbVzLyS4erRxQfvfS1CPvv05TiitS/Dam3JeyGQOFestK35aR7gU/Pi6VNqns/Th+QrmtWOlW1MOonv3JjoPn/I1rXcXM1NmwoP5lAjQkiRme+Oh2mZHIi9hI6NXFFzKaksQkgSOICZwUTCAncmEoxzq6Xegul4nOa6JJbhbNjsUkqdcDLl7373mw/PN27ztNzM5W7CzTYlmOe8FJsqorlBEaRjpgqdcjHU7NSluGSJMaa+v4gPOIjElGsBjSHElAYK0gopi7vC4Ft2EKubuquIjNNBa0ld6tLZo7fOzh58oO7EiC3RxTwGfvRQSp1KPZoXdk8cosRZHMy1tlChyiIS0Tttd7FTnsvWEQ6HPE5lmQtARVskn+ec+04YUkAxUAxasi8zyuJgUEUfVfpEzuTokoQQseSazRSphxU73I4gyssCohZfIMSBu4gwZWTRYtUK8gyz7LAUE6cQYufHlarx5qKvDFMwKSy2DgUFB+mGPiQel9lKlbSJSeqipM7ejCu+FhOhQSEE1FMUHbOD1E/yyvuNY70I70fzZp5Zh2/VFbNoq8BJXUmrr4KIHExOpqcXYG7orbrDRSlaVavLMs9zbaybk1m9uHpvXqZpPk6LwmwlMtvN03xZAgmBI6G4VgVWY7VKvfzgcrjoJXH1YqI5l+yZQaELiVIZ63Scl7sFy+kIEBBiSH0XolDllcsmOJFpKaqlVm61Cy2LQEHODAacmWG0rm60/s7tfLtOCA0JYidxQ6O0253ePkX301ooFFYuzcEiAkJpqkdjdmUjduIGWKAxdW34Eo6+iuZ8lVI6tLbWyCancTRUuEkJGqrF7uSrM27dEdZF6H7dRsv2WqVUv2GDuoc7vgCb1rX/xIv85oeLBHd3XUeUUx/gKcDqP4J8AYFZ2jFJgoQQWu0gURPO+Mnp0qRl3ELI7n+2k5xgPeZJCM5eXQ1G0BaQqw40i20IxOSutapZ9VVRw2s4UguraZKNFQRjVK9eKRC8FXWt1FOjvMhJEAInCWRwE0cgkVBzDX0MIbqYelfL4tCOYuTg6tvzoc5Wi2WrtbotboQQghDD3FnVoEVX3R81cS9KKdlx9VZ3e73Xyib04tXnfdw+efz25VtX6eUbDzTFkY2h5It6BczuPx8ilAVkTqzOjohul/ozShv1pMdyYKbFx263eeeDB8NlWJaiVEF0+fD8/HzYbPrnT589f/V8GPoN78bDDMM0jgZzKAdGYIc5rUmnflKO0AofEuQLk541kA2AIAizCJjZu/kwyiAppanku9uDiEzHfd1czke9vb1dppwkkcKtiDBEKnmjaph4hVAJBD65qQTtvqZ7ou3ENDae/rQKEX0xXLf7rbmEWpoQkTdNjdHpw7SGBNiXb53mG1OYepkrcWTp4tDpz3/x6QffePsbv/3hw4dX14fDfr8HZeYoIXH01JNBqxsREBD7jiWACZLcuRh9+vTF01ev0y4ihLJol4ZpWqpWMHFkCnAxM3VACEJNZXmCZIViH8pS3dUJLGKsSuqkITFakoiZLY4OhxHLWLVoGmIF97GLknOpWhY3hRdTFKscOHRdDCJGKmAgL4CTiAdBlNSlISYWdqy1oYFa/xeqsRqyuwunYRiGPsSGTcFrI4bNzFlJzCw7EpGz5GqMIuThXJjdrZqWyNJjc/X4va+9+1tsw0c/+vRf/fM/e/Ni7FMCQp0qEI1iU6OCiJtsuF16BNN1kG3fGp/Ouc6tcfDLCxYBpy4lENzklA3m5gaskdVNq7q2cJ6g+waEcoNLiVlKGdvdyN5M8+JrqNqvLbnUDBerlZBFpG3P6465MqOVCSTNHmTtL1c5NDePRjsnUqOa/YRe4R7jBVYglpyYWzeJGeTe4mhE7I2TdQBQONaiEGp+DGMBBzJyZua+f/Hi9i/+5C+fDJfn6Xfef+/xH/2j3//46S8+ef4s59FD93A6l8083yzNuFu1lLJsYtcxq1NAa0uTuSxadLNNpphL7QpHplwwjzlyTDGyc6QYI0noStHjeDzc1eNobj7Otj/OFw83XaAQ4rDdxbDZyFlI4c3tyy52Lvrq9pe3t+XdD6/+20f/xR98+vt//qc/+tmPP/701TUAOoe7rkSfN72MNYbkS6R8Y+t9LcPDml1MhCkvsYsUOEoXYowSvFI56DLN1a31GBqtoR4hhGp5HidVNTWf9sqSkj66Cg8eXP3j3//ut7/z1W9/6+sI5fOXz3/805++uX095Xq7n+/2hYEhwIBaoO5dFxpg71rLkrVmFoRILMxB02AxhL4LJr1WLGMmomFIm6GP8WwzxCkvuViIljoOXSQPCxFQmNLhUG9u8ZOfPA1Y3nt8+d47X3n30YP3Hj8ax/3d4eaTT39pNi6zL3VfLQybx/12QOqqirofxrksSyEjEQ+MNjwJWYsVo9CybXDSgxAIwtCV2kBxJQWXNVRR1hKxdqcoryoBCrQWOdsqEHdvya8Oa37C9gbrRc8BpS5qeZ3ACtSqupsxyFiEOQIdi0ukvoewqxYR2W0351svix8O+3muDdPWrK7OIsaw7F6But4tBHZj9sAkAlEtaJnTTXtPTe4BiUJC4qRezdEaRWI3NI1jNQPZtCgkOnh/HMvdHpzGuVR1N2ZOTLM6hMnMDsdjreBgxDz0SeHzba6qcG9ZYOYO8yABhlqqVxeHredOrEIea157g4tXNzYnq25NY92QgpRQSlZg3E/PP39TM6VIIXBp0n1ZE9/W6F6+33DbOGtEXLnFogVQdE3zaOM03VyPd7fW9+hS7LvAgdzrotkNIXahiySspagpCTUbGgcJIcQUU5+6Tff6cF0riLjvN9tumJfyZn99qEfqJC+Td+4DiYeWUr272sZN6of+MB9//snPv/PN7777znvzOL94/iww7w93gTF0O7AXzVmXy8sHV2893va7UfPN/k7dQ0os0VyzHfZ3d1Rp0+2E43Jcno/PQ6BlmYLwUpcWtQuoWSl5pBAc1nWx63ckYCYWZ0GQoLXZKUIpMFOtfDwcprGGKDlnpg4UrDgKwdhrBU6KP4ebq/lJjYX7PFkDN6pmteo3ceJJtrSqcdZl7D/2OPnvyFuTSWAXIWEnW2EmB6SdsNzV6yqzXwFWEeHISzHwl9/o1H6F9urSInAI1EqcWqdBOwe4tlFhnf6FpYWTCEmbLvnkAG97pXpr8F05GawaolWhcVIb07pntxBVd3fjtd4JjZ0IjpPjFQR2MgqgxNRyKckKZSrUcc8qZax1qhLE1UrJ036y0TQUdB42Ybc7n7tlqQWOeZn2e87jEklYqS4GY2GuRZeSjax7OBzLMXWVdkJQ9+qeiIkEHFizOkxdo6ASvvWtr26H85tnt59++lwVEEI0uMGogMZiAESiQpuxsn0p5Dg1E1k7xlJbNe/z/P20PjTg8kvzUdsNme7LCKFEtRZtazsZcatqQUyx6zoiTMvkFXEj/dBRQK5ZFaXUeV7cHJK7SH2UmGJrfHB2d5uWiYXOdjsHpuNIoxqLswPVN90udV0fvvWtr++403qcluvDcr1fXtOwDcyUXDkXz8LsxMf5WJTmaZmzx24jJJVj6B87sWl1cooJLMyWUjVCSNuEbuGlukUKodVdcNPNVkPpkLAbTTUGESLFEfU4Hw95WUqdgNL3YXfe77YXKW0nT3k5Mln0GJxjMmdyEQMgpC7VreTJdDZjRjao1nF/WA5HP7/YEbGqgUS17rbbUszdt9u+72lZLC95Xuam/Z/GXBYna6HPkSq3nGdXmAKq493eUJWUe4lBUowESqETF8qwwRdaslfNXmsFIwjD2dRXibGDXMyIdd3uiKBUnR0JiHD2ClOrMFStVB3upN52GVtv4tVxtnq7/JSLtALvdBI6nWZZ4KQbNLQrQ615uLzJuNpO84UJlU6Atd/rs8ndVFmYQNLeTN1yWeDUmpF99dIaAcIGd4bR6X7g9S2atij1cXs+xJTMbc5LrdkJ7VAG8Yv3zsIgc57HeSQiDUWDA1iWRa1SDUGCsRfOEAITR+qGPqRYtRQtTl6tgiHN2uLmBHX9QuJtEI/e6NTTgd/dCYxWTn76arAebdTWQr/14OC+pkA3tMfdReyEJcHRWDapUFdtWbBmdS0LbEcBxxdDDwdrrK65rekFbmrry5mdzIVNN9fUV24tPCXwqiEmWlNNsRLtqxTXV8XdPaS1rkFOLAHrpvAl/ZTZPfnyD+JQDhGxdjG2qPs1prjxnn6vpvqNrxDu8dF2VDNrTan+xXHLTVXb7HVy9jEAVU0p3b/oiiM0jMuaEtjMvSUxN/Uct3sNBoOW6o27I4ZIe3Yb76CotWIxY7dYJcX2HuZmpSh5CBFOmq0uSkoxbijCxDhJSDGXGppGQjhyMBR3TxKH1Lt7PlRjcJI4CNVSimkjSSmEABM2ctXKIs7adXHbb7m3xcfK5e727jBO5MEKjzmbyVRmHgL33J2nEEMwqbPVqXq1Mi9a6/qFMqG6B3AXgiB26LZd3CBtq1LNlh89vDrUfaa6Oe/6s8tlWeaaQ4y7s4sQqZZlGqc8YwuJ0lueXW3BEhIkMgKbUDV1PkUW0HroO+WlU/NGtUXB19UPoJVmM6ugAAVLDKG6c1nyPE273XmI4TBPNze3ecYmiOXmRySDebN1NafUKmVe39hBa5Q8ud+PXCc47/T+9wNMG9zud/LTQrCaxVYcbv1lnOyEYDWAu6k01qhvOHXJVDn6Uqzf4O6An3/8y0fvX+3Odu0anedFfTm7uEi9hDgsy1iqRsHDLXIpOVc1dP02xp44TlOBIu2G2MW8LBQj5yqRJBBFBqui9V5ZvOcFTy3VKYn2nVYzM4kEQK1aVQ6eYiKGV1ipKAhnVBcvx7rMpe+7QHGzGaaSSylaFlhbd7I6E5j7GJgVawWtVqQUu467xEGCe+tmQ1W1arW2YZokIMSGbZt5Ye66rtvf3cQkICwlL3lRrSRRUk/gNOhZ1w/bXXUc5zmRc2hzA/pedpvzq917VxcfTAf96d/+6M/+5K+e/90YtiyhU5NajGLnAJhh2r7qhvCsh1g6oT0t4wjiQGkR0PzF8vdluHw9PbPcrz9Gyl9e7NqWZ6fbjXh1Gfgpea1xrAB8PUWc8FUiW7fGdROxNZ0jyOoShbudlq51F2qGHjJvF/5KVDIITqe2b1o7dJs+6H65/9Iiv67gvgIJOEEzJ94AWKvVjcDMLsyhDbQGM6sAQhCHLVrgTCKf/erlv/m//m0fcveffu93v/m9LsFgiz2fnIbzqJ1MoYy3oykCC49YxokRJTIDWutky0KaOnZhNaiTk4AJBqtuBSQcKMY+BukRwl0p87K/uRvnzIFTsen1zfLwUbo8i5e7vhu2QwodBnd9ff0rhz159O5iN8d5n3p+/2vf3jwaxnoMZ+g+6l6/PNRqx0PhdRS/p3TW/ZnuvyM0eNa/oK0IIKqusOZTcw/MYBCbkDG0WvGK4qQlhtAPse86KTgcj0vJseFPpG8/ufjOd7/+9W989evf/ODqySULfvmrTz95+vHT5y+K6WFcPn81jxnqJOJMXJWsqElrgm2DXK0VxDB4JyoBIZWuCzHgIUcAeYKpxxjPtpvNZtAyMXlKFCikLlSvea77Qwb6EIab48vEdLufPvn503p49eTB5eXFw6uHV0s5H+eL7Zm/ur15fXt4fTu+us5zvSOtylobmZWAjgAkSVBWMyMgt1sJzLKu4KtEqul+mnKEIhgOrVrIiShyEGHnhvCAOpCDLZwYBgdA9US6WtP40kpdnK5xwoolgwyMmOTsbAu+djIw1LSagYglqJLB+iRn2x0ZtWai84vdxz97DetMaykzRPqUAFRVkWCKMtemY0LrTasEbeBaC3UIaLKRxs8BYGsoFQBSMAmTGzFzlNhZE9oSo4MqgGCO28P+1etRUq/FCWRGw7Bl5nkeN5sNwK9fvSLCssyEEKOQYrOJZS5FMweOKTIT3GKI5lrMrXogkK5IB/mJsW2wAbHCqlZrgpFIBIrwFKXfXgrR8bgvtexnRPg2BoC0FEiUwNQS99aekpboAHfU6qYOFHcSiV3aiqRS/Hg87m/3x8O8FFw9PE9Jui4QqVoWBUAsEUQGSJLYKr3bK2klhnoiQezSq0/eWEEIYRO2Oz5PXffJp7969+13v/bBVznxxVsPVMqBDlKC2xrGXUnnMu/Hw+u7N9vd7re+/Z1HDx5Nh/2zZ8+Gs03aJg5sZLEPFw8vHz58mHN+dvPyZn+XczZQTOywYdgQyLNrttubm8PrI9yGIZnX1AcO2OwGRb7dR+NuuzvrNtvNJsUkzLgZkcyH1EkAE0/LwoKS9eb6OE3j3e14OOYuTueXZznXvGSmOE9VJ4Xrepa6v8ptBbOITjFE5nAnbjfWPU+C07kRf38spy9THG0OWvWkp38nAOCWw07O7ito5i2auQWsVKx+BvDpXNVyJJlb72A7j95PZd7GrrWik8Ctf2etIWNoo6GXOa/3EYDAQkGYOXCzqnk75TQgjoG67qjrtNZUxV8s7Se1QhveqOkx1qHQzLmhV0QMbo2Ja54lw4MbA6YVplAzXTyLThs+Gw8TCOM0pRA8wmBvXrxBcvToLlK360IMSlpZNes0TjUXqnWXzqaSp/2xZg0U53nRxSEIb6dDvd3taJOGPlEMsdIKyDm8qhIsJnQJh4Jvf+fbWnH9+fH48rRjiXIiGMOQ1Vm8wWr6hdmK2uEIjaADAcQQ/RKr+wV6hV+7WtaT2/2fW8YRkWtLLRDAXbWVwFJg1YrGFyaEFACvqqq1XRtqdZwLxeoACbkQQ5qGkJhSGkgoV6uqpXoPQaXpMC55ymXYPeouLx+cyabqPE9387Kf6+FueoWUL8/ON7uNsy916mJP8MO03+/n47FwHB5sdin1xB3zeYFVyxVmGjR7LjoepxevXtX6OnBUVyc2oJjWWs2qw5mdyVIICo2Rt5ths+1YZJnD9es8jmMpE6PERLu75dGj890mRN7FmFic4XmeXJp6gzfSi6WSba7GohJNi8FnUyzTdH2dX76CSEgpNOVFKbUbBlXuusDcwyVnX+YSp2maJnevteYlJ4ld6L3YtF/ypC28qWaIIE8zRXBHgRheCRYkilAEy6Yj80h8zPOi1dVDF6P05JLnDF795O4E5XXbFSdGdXV26hkBpdbVI5aklKK1kq9WsDXI2lesZbX1nqboVRzoJ9DB1nv1i3XJAed2bbietAS27lz3axSvCSFkxLVlVq3G46ZG8Ba+Syxq1Ustqi3vNKao7kQcU5QuHY7H+xivFU/xdcYHIQRJXew2HcipIFcYtSMtUYSlUqLNeRp1DCzM5AGuPh8zFJebB9uhH/MIoOt7iqyWWVqokc95Th7NNUXu+yQuLRTIqtWi0HVR44ZdGYmsKYDspG0PoPX0Tevhp/HicDjWaNBGlq+R6mbW8sRjjKcpwJsmQq1qrsxMQAMlT7uDt0VkJQYcgLSvdq0+Mq/u61fdbCktbNEdvkpwV8zxtMP46tA67UJfCLNObDLu/+d1NxM+WVnWZWr97Vr8wb2vBf/Q4wskYH36PYD1Dz4FAFrkbdvpmJ1gZkXrfSqWGyoMuvp2mFlYGi1jsO12q6otMXr96YlTklyoWd3NzIq2XiQ3gMmNGoTc/hKiFiIzi4vCcUrXqqUayNyYSMwZYjCol1qsLlePHpdcS815Xly972MckvXcdYGj7A8HLQVK492iVnQpLEgaBhCIbo77pWRj4yQlKgKsqqlS6GIUkuheoeTsYPdI/XaQLUEhtLy+nbbbVDKmOffnXaTw4voFrl+0WWR7vuk45UOWhJrrbPWeDXZyCEo0DC5dlB6+QY3KoqUqRVy99fDzF6/Hed93EkM4zvO0HM77h2e7oY9pGZckCY5lmihcwQHYduiU1NxMzQkuJ8EVrUHHbeZZcR4GOWvzN50uWWICrQH8JIwYNtthKreqzi5lLu88+WqUcETJC1AQu1ilNP+BmhZ3CpDA3iwjaBqoRgqBBM6N64cT4TTztKMMvJWAtkzLlYI7oVq2DnprkqitC+yXaPz1lWgNims3scPM9Oz87G5/ZzAbrT+PicvrN69uXo7bq44c2+1Gy4KCELwfhJjtLs9Vo2BzvlvyUhYTdOBcq73+/Oblq1skgDl2nfTGQiZwJg5CwWvTzZrB0Cw3DhAZ2Cm1Hk6z8QgAkdzMtEChDMu5pb+7ABsiZoxqhdTALEGCJJryvD8cTt2j3npIyYN5dSPXWosuE7qUhuF8u4ldJzFZEFct85RryVVVZ1V1haeATeq7LpaczYu5hiA3N6+6bgPhqs1zby4ukEDCqds9eLi7OPdSlnkiphBiFI6xbIbd+ebqg0cf7rq3f/nTp3/zlz/6mx/8HBEhRMsAUYhd6jbjPJ7Oxq5qa6a5uzskgKxZBLiJdG11zfGXhaZ0AqfkpCYFYU3bILRyVqLGawGA1wYztfA8bt3eqmpNCq3Maz5hw4faiXXlvVdNNa/kcsO9nJgYAjZjCH0JdAVa6ebpR7VVoErqBGI+6fCMGvJ/vzn4aelv47qvurTTlA80gyWwotFOTA5nZoYwRCSYWdUFZFBICH3XO3knw3E/bnfnqodPf/mrv/lB9/5b59//rT9+sHt8uXsTw8u78QDMoQvdjvfXFYTt2aBjOdwuERR2PUOWpRzmTFs8PNvEFKorSWAOTFQKIiHG1KfBlVO3jdIZcx6PcjyC0Ke06XfudnT9+UfPvv7Vx1fnD3dnZzbreDe5T2cPNixuMt2Nrx6+9TBweXH90f5Wt+f8e//kW++889Zf/Lu//rsfPAVBY/uGmEhoVfYAvo5MvtaqrMP6aY8jdb88vyhm8zjlaV4OyyxMGryQFiXhEBKJC3Ng2fWbi4ttXqTmSQ27HtcMKK7eln/yh9/49ne/TWzH6fbNq+tnr5+9vr25PWQDz0sEjMjHY2FB6ilIQJKSZ4oiLEEqE2CoCs7gBCEEWCA18RRrkJhEavEUw2YXz882z5/fMKPreo4ECfPttL87XF/7k4tt16Ul29XFNk+2P07X13OtpU/x4fYMvHW5eOvtB69vr19c33z0ydNj/vnzN8eKY1VeioUYQ4r9hotr10U2mqq2WccMZpAuuDnquvyKsKtZVZgT8Ym5g5YKhiSyqtbKmx39toMBLU7LTcXJmkm8BU67t/4yhpqui0Bz/wJKalQkotvE3UWPCJdq7NUaTkQgcq/QnOLGt8myi3iMstnx5zfL1XngxDTDXREshq7jjciaWbk60o3Q0KsKM4WTk0tkBeDa6mIASMOgyjqesBCLOAk4EaiUUsuCDrEPDnZiNRzG6fOXePT4mGLPBEB327PNkMY5Prx8mEt9/uzzYehu3izCQoRay8Ort/Y3R2ROXeg3vVqtpQgFInLNXt0EbmgjlhNLU52AyCkKrx/nGgAYAqPvOAxh6PvYpXJbJfAQIYTtdsjudZpA5IL1SetaAlY0akMrtELVCRbEN30K0k3LMo759nYsBRBstmfCzmxqFYSYInOo1edlCSH0XQJ5Lrl5IHJZShUWrrZl4c+eHXYdOttp8KpWyX/2yc/fef/dDz74wJkvH1/ejG/mOivVXOcXr1+9fnl9sXnw4fsfvv/eB3/5Vz/4zre+8/aTt4bQ7W/vtPiTt996/P7jxjMT0YxlKtMnz57+9Y9/+G/+3z9/8eJ11w8PH1/1m/TH/9kfdqlLmzTqpOqpT11MgB/HmY0utrvzi91cFo4yxGF3ftYP264fyDFNM26Qe5yfbWJi03pzM8FRCvyYD4cxL8qE3ebywcXD/f44T7dmrfo4Baa6LOvSbqcRxlf0htdOXUIrp2eQs3u1Jh5uVpj7LeRLjN79a9Gq220nIV7lvO0oyey0WtjNvZqCjChEaRGsaEM5r1z/ysOrFmfn9iO28YnIzGWtAaTWYeJNKkjUCtfdzJpjHShaWhQFCQWQiPDai4CKlamqBGmd68ROds+R28oUUfvV6ITj/f3DkJ8sjXAiakqGdjgkUWeQODGD1AzeaqMiC4RqmKc5T3NKCcXUjIRiHzWXNc+XqJRyN91kNR7YyJCw6XrK3schINRRcz5mLToDCmwBFdIohihd19GSCmTOthi4aIUaB+r6AC54hXfeevL0l2+WQ8UCBGB2MBAgJOLBnImNqWX/NLgQBCdaZXmnmNcvzrugL428pwPkCoS2dWKV7BG8vY6TGTVjKXnVumrlxJe61H1hRoiJBeQ+T0WpOiNESTER8TRN54ldbcm1qhFD3Yiw2Z6dX1wQ0evXL+dl7lMXuhSq7ed9GUEwfvT44mwLWLVJaUmbsPE+jB2EEGi715p8DQAAIABJREFU2ZSqx6WAOpiNi+0P+c3NuNmlS2xYthVhQS8Yush9pAob58Pr/fVPf/LZX/7V//fpZ8/MnCB9P0zLcjiO0zjlrMzoeukGEeFaa4zh3XeefOs73/yd733/wYOrq8cP0+216mKa5/nu7nYUJqHh4cUmBAfqPB/v9nPtDZ3GlJKkKHJnk5imkBJVdbOaS6mHQ5mOuN3jPZSW6pq17ietfhu4DyLMZE5BSDY9ge/2R8AjRybr0+Zsuxv34/VydEWKDCCrwVFKjkVC3zFhKgstEEmq1TgGRGEHKshIHO4phaHviHjaTwgQFxOA1ABHcDIErBSagLvgTOZqjpi6YLbMsxbtQ2JyIjI2aCUHnKSp3J3cmVYAGSdpVnMkfPkOPd21Dji7uVZb1ZsrJII1kLyN79wyY1cUbF0naTWCijALEzPBqlpVT0JdlySkau7grkvdZjgc7iQQcXCk7HNbM1gIQFFf8jLnzImNvWrJtRjcXMHEge7Gu8RdLrmqS4KemhRBQI/LB+di4Xh3LKGcXZzFPtwdlgmTUqQO9c4hRchDTP2wIXcjoqAll+pt3nDmSCAYc2C2tckRzqDsRCCj5iFoVDnDA4PB0kjv1UdCBMfaeO5rGo7xuuo7y5pN4apGRs6uTTK//iKrCMu9Sbbb4o0vltZ2em7MHjt5U33cn4V0zdZtq0oTz59OI1hhH2DNWKDTNfJrD2/EJDdPKreI49O+A6wNgidVFf36k2FmaroW3TZEj6hheV8WSOE3PWj7cGMEq1pqMTUitH66k0oHEjnF5A6rXmsFqLUiuPvZ2dk0TeM4eVEESilBPKMKCwhqBUTM4mhxKdI0D00lxClq64QCmMHCYFOoiyOYB4fABf0u9g+64WxTqR7ycdIFhP5yqKXUpaIAitDyC4Y+xRSIg1PNZbw71OVLxH2g3WaXtsmvSFFRMB6P7739lbtXd3nMy6FYdlNjjgJWrxbG8w8uP/zmV6Y8fvbis7FM3UYK1AUxcoodi6haizec5kVzwWHBgtAhSbjcXLz98O0U0nKcj3fH4zQ++cZXF13uDnf7+UDBuoGMFkI538UuEcrShbgdNoxYFW+/+yRrPt6Nb16+Rt309cGP/t0vbn9RSImq996ToRalSPOSeWCIewBHdjY7SVhaMKObIkYKQnDTsnI8ACMYMZyYRSS6m0HNK4JJMkTTGf/df/9fW/Uf/+CjP/3XP+QJSTtS0lLATAEUWqocWKSlBsDIlMjcWqA6fMV11yqxE6R68k4TwdodAwODm4c1SM7ZZZVzgbzdyQ3gaMf79hrSTKnmdgpaYRadfDg7B9lSJwqWzupk9b/8z//pW9948OLVs3/xf/77zcBaYGy7M+o3HQu2Z13Xh5zz1dXjNy/3z56//PD9D7/zre/+1V/+cH+9THsruVatfRpqKefn56mLh8Ph9vZNax50BxO6EL1ZN1tmsLObsyGk5I48F21SRHEn1epuYBKWwBL6PlGwbMdvfv3x17/zGHK8PV5Puby+2QcJ1dPhMA7Dzg3zMjHbbtOlCCCT92V6vL+rqnPqhESzj0H47HxYlvn27gDCgwdD3/XEkiQwZ0bdbbuUQp7K/jCpcjEb83KYKhgSEbqw22w74W2Mjy8uHl1cTrd3L55++uG770+H27PN7r13nmy6h3/wzf/qz/7kP/wf//u/+Ld/8bHOwAKdSKRnTmuJhru6mc9Opa1AcKKWPG4mxNJMxQCACi9N6dlMxLTayBs+1davVXIj3BrSmmtVdS1FhSoIHCIAU4XVlbtg4TWrmpZpbrgIt05BJnfkuogEJhDLGpas5m25Jj+xT+RqtJZ4w6p6XfdqNGvG+i5sBm2OwnajMRO7dMFMV61wI48MMGdpkyas6U9UhajvtzFEGJVcljpvznttICnarxKZqPm+zLzCTKuDzCIZq04BCzOyA3+D/+Xv/qcn71zFM/oPH//gxd0n/+s//5eX7z94M/u0r9PrvH+aO+91xN1+vrzY7h4NR+xzWjYPZXe+yYt2US533YNdHKK+/+6D5XhjpTChFg3S7XaXaehrsFeH6199+rIsrBaX2faH47e/8eGuj+e7tEkUqFqZjeap3N7cTiK4PNuktI0ydPE8hfNEZ27BSnQPQYYf/OBHH//y6ScfPz/soW5dHyX0Wa2YVtOVJiKE4FHcwO2TI7CEBNBu2OWpjNd7ACzJi7o2pIuHYch5cqvdIE7LrHh4jnc/uOyH8OLzV//D//jfPHi4GTZDsXqzv5mXfDfNnz1789d/+5PD0dTPSuXjMR+zEgeJRGRa6zzP81wfvzVYXWIkguaCzRZXF9shDuaVyDmAqJqV2HUsvN1uCfz559e3t8ftrs+GEBORHPf7Za5f//Ab05incQzCb16/FBY3ffTw8qzv7l7uz4fun/3RH33/t75Fbrd3ry4vL3740x8/v3558dZbF0+efH5z/dHPn330y6d3d/NhPpxf/v+EvVmPZEmWHvadc8zu4u6x51aVVdVd09Xr9DSb4ogUJYAAJRGEAEICIehVD/pV0n/QiwgBEiWSgERwEdchhzM9PVNde1UuERmbu9/FzM45erDrkTnDIXhRyIzMivSI8GvX7JzvfMtmt98ztXDvZIPc3LzYDnejlwBluxtDt2pDsFzyMJbJySCMGKI756xmxFEgRaVECu/9+H1u5Xp/p6TDsIOTOMSZjTybZiUObWhcLVCA83g/pnk+OdpIiPe7O5bQdnGX97/1i6O/+bf+2sWjs+++/fbV1eX93fbTz79s27g+puzpyZMzIpRSwHPR1EacHp+fHF+0ciJ8/L/8z//guAmMdp7LuJulwenZWb86Gsf57vq+jDOZ+KRIDmMyYSMyh8LNPFIlCws7MWoEZOUUZAVHdL20fVeSD+McYr85OaHIY9kO5fbJ06O/+tf+E2L//T/8199+u/3eh0/mci9xEsHx8WnbtkURpbm52X3xxY0V3qy7eVJ36eNmfF1QqPLQzSuWbmalqAJgJqhXghWxNCEEEjK4qqq6uLKpODqhjtAIXN3K+4/P/srv/u7f/C//67/3f/7f/+yf/1M3UvX7aT9kNwYCufDxUV/SDPKuCU0TzEpOaZ5NmGIUcSHipu1OTs9CjHd3u8vLy/021Q3t2dOTGDw2TKxmswS0zXqzPgH41atXJc3Hx0fznEqeUtLVqk1pfv7e+48eneWi//KP/+io74M2bVk92Tw57y50zv/d3/hvf/d3/wJB/87/8b/+6GefUPBfff7rz7/98urVZUSIFFvp+7D67R/9vG/6ZxfPzk8vnl48a0O3L4OS7+f9N99980/+1T/69MtPf/Xpv7ufh83mmNFsh/3d7TjMKAwP+MH7eO/xh0+efPDxRz94/vwDZn756mVK4+nZ+rPPP12tm/VRd7d789WLr5jap0+e50z3d/MwZOL4qz/4dBqzNGGcxt12ePbk6ZPHz7SU33z6Wds3w+3YSBM3Meesc9FqcWduhTBalXy7e52pACDhajlVLS+qkRkTx5pFp6655KJcaTxGh1m7RxchhpuZqy25q+DqKcq8jNRd3bgXg7KEGCPLwkh1uARmZpCr2VJgO8AuIhIlNEGiMGNM85QmADFKiAFGWqwNDVysKBkJB6IDK5jh5EVTzkWvSwVO3AFGu2qbpgGRuZtqtiVsHMlqGM/S6hjBwcv5arU6InPUsLSFTULEBKkesg6hKlOt9pgNi7pmSt5Aemo3DbecS1Hzvu23b7bYAw5MQBXZkzh5JXtCEM8YTFn1ySdnH/3o+Zvt9bfX3zUh5qGsfHO+Pr97sb16eY0EOBAAAwmvTtfxYjVj2x/Z5pRjV9ZHXR/XN6/Hl9/cbl9g1bbTXaGID59v/vJf+Z3nx7/19/63//ff/pMvMEO4UXaw1akcE4mLw9WXe3VQs7ztQ92XYnbpFR8mvlhQ0SrOrJ6GlVsnXQxdlCiqmksh8djImKfYRIeXXADElbTrTtpY7Yx30zhM+8XcBwYGRW7apu3btpGWCjA7MkWrmDtzMApzKsN+4ECmadW3R03Y3eyfXPRlGjYN/uLPfvt/+Ft/i5HTsJ2n/XZ/f7u7caGT49WHT95zp5vb3cXxk3Ew5n6zPgd1UY6AZpxTyhbD6k9evvqXv/f7/98//6d/9MWnl3doG3QRdzfABHToOkwTsK+tXJWBH/4DFmKOAgWoUR5U9fLAET54jufvPb04P7q42Dx+dPSf/uVfPn58enq02u23d8OLwT775uWviZDK/NVXN3/7b/83r67u1SQrrm7vv/j6s8K6H/b7bX+39TfbSQVxha6X9aoP1t5fDyVJ0xwXi1e3uzxp3/YE2m2Hu/t7oRC5Oe6PWeX6xe3diy0mhCBG2h7xxz99Dyyvt5eyaT/84fd243B3d3/1+jLvrBEc913bNvt5HnyOAUwxcOzCatMd/cnvfY4JmEAZPiEAzFzMjR2Rji7O4qpNlsdxUC0ARVCN7PFUdIeFbOm00FwM0FptB3mwqs3FXBegyhbHdGJZ1DIHNYy41XCjt3451bHEKXmpjknCTEImNfROQY7A3AqLi5CLq6sEYqGii9oeDuYgoQkxSPDYylymoskrRpCJipK5tGCRbtXGrsk63+0GOPqjGGIz7Gcv3hzFR987i30wsu24v76+ff7957thSENKt8mzSstlKhdHZ81Rs03brQ5N11YgrCUp9yVkpkmOj4/LrOvN2f3uRj25OYO5SB7zuJ19MjiLiRX3YihVjSp4QGAqp5F9cXBlcI+mC7GLxWy2wszSMLMUK3lOsWlMTYuiOIzJCerI5oeYGkK9awf66oN0zxFLFIoPIrmcSxVqgKrYG+YG88ZIDKVmRlINx8D6eJUtG8wZqEGOxTw9uA4vk3/HgZTHVBtwV8cIAoTl8BmVSUrCAQ5TrW7FlVy1BK7Wd+eQ8F4hKjPTpTR6V38D/AfYWCGbOpa3+rBXOohrhlr1czEmNma2aq/FIvXrpZRUlZk0ElefeYdwsOqHXouzUqr1huPAqX6AJoio6uOrr5zCYVT7s6rKJ6jmPEu3Mkg1M2NlA8BCIbLDXXwhJ5pKlD52LYUiM5IP096sHgxgF58osVnKHp2JC+f7dFeCdmf9+vxk2k9pytDqjBxmVpVys79L81S0stCqfBnJrOgYmJVMEUCCrGCiNXvjIG+7pl031FrWMSPFPpyfXux1SJTnkJIkgyZzIAe2kAkkEZxLvt/dw1uYvLm+cVhJJYY+yFo8htAgZCZmR5lnNnFnskquwsFt6i1eB2fyw6gOlelUaYrLIjAcFM1OqgpY1fFW/DWANLir2DyTehPBBh0dZlUAVhtokoMc9iHVgtxrlk+lny3wPT98Ww/Y7UEphYO6kACz6pAUFkjfF7PLxfDhnVD0xUL4AAnUVyM1Z+Gq22KIO5k6uJSiMYSTk5O+B5Mr0AaKTSPCjlxycpSU0+Xl62GXGRBiNxv3w/5uf3enQUIIUjSnMs9pTGXYDztFEhFAzMzh1MSqaK5tClyZGSEoWQiy6TbuVkrRUoOynFkkNCE0gZvtbhecA8dcbJ7T6XmfPSXdEZDVAWvarutWDhi85H3KqfpexSDTmNOs6gZyFiiYwTnBIcRiqtOUc1GYxBACWwyliUzk05zbZj3MOaecZqQMCZCIyNLG0MbATrv9ft7tLeW2609OT7VoykbSf/ThD//Vv/j9Lz795v564gR3iLBHqTJhosVNdNlfD9ciIUAdKy8uL3UlHBKhffm8t5Xvoot+2LzMFM7Eh2RxelhMlRB7AP8Pr+MPG58dUtdoGXku/hNCTm5EdFCCVDYWVdw01DkItDrLMhPAEbokKtavT4e5wTL5WKbbvKTpBRKtoYXvjC7q7LueBbWajxJrj2JqcGKmJjZ5ym5qbhWOQyhEh/ew0mMd7t5wIJbo2V0JZSUYfoS//3f/yX/x1//yj3/n42fn7+3Gy4+e4Xq8QUYX+s35Rvbj9s08T9a3LZi3+2HmLAKop3ler86nYbi+vi9JLk67punIj3Z319M4E2g/7m/uhuOzk/XZWojXXXc3jyUVuPQdnr/3fp7HPI/bOQXJAVl5nlSloSAym5VpjKFGwYt0wdEUn0oBlf1Pf/b84tHq+ffOr97cv3x5+fl3I+4zCBBAhMLC7D0EfhicpDr8uTeh5Wo/RszEXdOBC7Ro1lJmTShJSWzYFjD4DE+fNb/4+Q9++OPv92tcnIXYFLVd1mw+bcftq6u7r759OSWbC15fXu1HFAMkNE1sEYTJXUO0lUDL6A5hxIZi5+t1u950LYWSLXSBCOOopqyZmIKXYE6MhjHe308UY4wUWDTx3TW+sK/nITUhPHl88cHTD/pWxmkrIpv+7PSjJx8+e/bBB7/Vr84i/GR9/m/+8N/MMzGt7m/G/fSygJ4+enJx8d7L169fX76629000VOa2hBDLCLx4smq78N+O6V9kU3MeSqDwcCM0AIZrlAzEEkT2MnMjbyJwZkMptm0FGdvug5qUARfbGGMkHMqUzJHQ1FYJHBLrbrnaTR4jExCNuGTn3wUO2yH2910JxHnTzbPyykxmpa3u61qzrlMaSJAGMKY0r4ZW1l1Xc9PH0NnpClLoHYVc8nb3T7pYigNd1fUgOtFekRggvPBM5usipBg5O4mleOLICBCzlpshBIzxyC5THkuylNosTqORaeSUilTCBDx4JAmMFdPERdhiaFpmr6nNNXne6kgtWQUNlP3mk/s5ma6zGWECAEg9eIORSWzeSWcLhslFhIni8MZTYNu1TljN4z7YTTzeUxqaoYQyKqld+BpnOEugc0oZ3UoiLuWrVZ3JCJN064cmNM8z1NO6aFdSWVWh7OwWLEcCMG9FM15ZqambcyMBQHBTGMTibSJIiIKtBHmNM0pJ7Bel72haM5FIBHh4tHjJjbFUtf2m/VmG+80WYyxb7uIEKOUVK6v39zdbr/5+sWHH3548ehxSvMXX371xVefXV/fT3MhbBieM7E4KMQYe8/uaFuUKV5d3e93X93fjXfb8fHjC4kxwO62e3Uj5qbtmtzF2GjBNE9WggRerfoXL69Y4JTHaZqmue0CxO+3d8N+GMcJ7MW0iyFIQxD1PI7TPE0wMCR4ZBDcrM7algn/UohV/uEy9AaZOxvc7IGIuxRFh18P8ZOOgykNMeo/BhneuitUM5Mq4lGyGspuS9Qm+QOtF/A6BOJlkrPYUbKjkRiChCZWo48yF5/g7qT1yEtMBKLQsIjUnpfIq0ejL/PCSv1ZUnecUQGYtyS0h5LvgX/8Z2MWjZzqaN4W0ws6EDyWYlEdcGQ42Cprf5H9GqGQFVXY2+DR+s5VBiM5mIycA2DuDESwUElqpQgBitOj06a0Opc6PTKBZ69xTCKSUuLSzFpIlBtq2Y8k9EfrlBivbp2QaZZVbCOfnZ+2sbu+vk7jzIzFfZnZiYmcl7LaCBBixYM5sdX4weWHrT5hNbXZ7aGQebtA/DDKW8oMAGRGrIeQhgN1zaqFFgGMEEKQ6E4pac6qxRaJNxb/4cAhcBAEdp6nicU5gJ3UfE4KJgeZEXED05x9ZhWj0/Ozedix4Uc//J1f/OynAZjSeLe9HcYdBZycnse2EeLb7dS369XqvI0X/dl6LKBwDMSb+3R59d1vPv38N59++erNTW7ab1+8vLy64tI9XVOILXPAZj/wyCHE0HubZ09sVuFcMBWySvxwDw6HwSNTI0KBORNmRwmR5238royXryYJL9rWvnux+8EPPvoLv/jpk2eP339y8dnr++PNuN/f3d+8Gnf41b/7bJw9tOuzR4/PTsJu2t+PN+5aZt70gVpKpLMVdUt5OD4+QSHSJjbH44y73b6wE6NtGmImkZyyzqZmDmYJ1B7oOXAzS2miGMBkhN0w7IdhnCYslEoALsRNJ+pC7kGkDW1k0VLOL47uX2/LHk6QFcTI1K04Gop9RyLFyjRNVRzKZgCbOxWHLU+mww5240upTAu/3WulfKjTGQ7Qu0cRvzWmebt/PZB9Dn+gasJRGdEH/GMhaBE5ahRjXYiAu5GRu1IFTxY+grqxgZyKEjQEBoKSmxGR1jbj+HTdbzbb7e7ubgCjX3VefDeOm2599vS8Xbcpj8ak5p4Ahyu8WNs2/dPeiw03O0+Y0gw1owJGqhg2QdncwJGgNgz7aUwuMZUypqFpYuSYdcpqEFDD7IEKqrUYYu07FEDNcDx0J4CwRAqRuWUJXv8BiCRIjFGCsDIIWt3xaiwhqk98vSuH0DMl0sVXp5LeF4dHJxAfeF1wODEIVO32HjLOFyfD6kXNAIEFzjSnUevSCw+Dh2VgjAMztPIG6nZWEfWDbb3zopMHarT6MpRZXCAPKaq1X3onJ3BZGm+7vP8Q2erPvcJBoVlBPaWF9UfmBrbKV6gy/uXLHV7d3VNK7i4iCz8CzsTCpLrQH0DkpYK3bmTMJNUjSMiAujOS0zIuIeWFdk1Aqb+ZelFTNQRmEuEA9pIKEwcWbgAzKDHMA4cQQghwUvOSiypcK6kZ5oUwGUgmCDOEKYZxHEUk9BKDmAiiuVOQwMJIxS1v77e5pFIUDksaQ1BTN2cTSC0DAzWhMBFQyVsoWUJw+H6cypTnMQcKrdAomtmKm7IbWW3Bijnm7G59pGSm2aAKxZSSw2PgLm4ktule1QAGGbt7KS5u/IAKLfq7ZZs4qO+W28TLbQDg7BVFIIdDK8OEnWoSnC0W1G7mXl30kpZScnYNDdyDzg54YF6GirQ8HpXIzVbp5+QgBozk7fHrvuxiZA8m3Qv+wItBUX2a6gxKhBdjbDwc2zXj9bBsCUt064P4aiGxEkk4GCeQ+XKwb7fbYTheb9ZdC/Lg5iROFExNYaLGgQl0f78zRdc2Xdv3bW8lw7CObYgRTKqapmnmULMp3cANDvo1o0Ut6QvCbOrVFEvdQ6yPeCkFavV540oVdc3IWsxdi9v2fri6okePn7exb5vStv2U1BxS2Ys1zEdJmayKeRFzLjnnrLMqEbtRNg2xiSwhSCxuWlCy5pyE0AT0K5TSBkHOKuKEGGNsTbLtDYUcKJrH0SbOjiwI7qum5RjudzsOcb1ZQeLtdvcP/+G/ePXl/bdfX007cICISFWTvlWD2qGQXXa4h4uW8d9iYruIwd+Cm1UM+06Kyds/+qK1MapKB1qG2FZrOxTDA135Adt6Z2ekh1c7SP4P4RBU97S3Wr7K26lmIQQtTiJMJETVHN/U/B1/Qfflh3UyOBMbmFhAzBVlPaz7+lSCmCvXGiQsIEao60RNS6lovzAP87h8T/WHKou2Dg+WBfW5ic3h4+WcloB/8Hf/GUU5OludPDv98P3v/ed/6a///meffvby22J+fLru8vrbdDNvdwiYbZ72yRusekIJVsLtm0Ft6hoy46y2H1PJOTnNqiJhyHm7Tdspn+bMTSAPJVlOenKyOb94/t57FzdvLu+v78dxB5/JSvHsUdt+FZswTylPo5AGKeveTyyQ55IcCFHo6ZOztpeLp8fDkN9cfviDF7thl67ub97c3L65n1yXAWyIEIJZ1cvUcrF6ptVe3cncciJzJlJ2hSumo3V88ujZ7/z4Z0/eOz9+HDbn/PT9k8dPT7tWX1/9QdZSzHfDuBvzN99dvr7ZvnmznSZXC3NGKYiRKSBGbxsGrKgGcm4gAQDaPqxWgcXXm9XxUcuuw5BDI/OUh3EO0jRNl2e8vNlqcYVrbvf7cXPKeTKjVOZ01Hbvn3wUL7qT483Tx4/Oz05i5O3d3TzN5NSEeLxZvXx199Vnr8rsPff/+Pf/VdtHaoQbaTer80dPTk9OODYXJ49+9P1PXl29yiVfX99e317td7txHNq4Oj7hVdfReXP9esj7Mo+zF2fnA+WRrYYHVnJIdUoIZGyppOJlzFOMomowJaMCFhAJBQSYpanAkZDZS9d0EkIqmtLEwhRE4Zjwo598HFu7ur7Zj/dt126O1uN8pF5i20B8tWrnNBMjBuo66XshhqE4adPwb//sk6+/uP7uu2t423UdTTTNKauH0NiiJQeEERxKoEW7uARDiC7PKVCrZGg1AyMhmJNms2xCiJ3ElhSl2GiUFHj67BQyzdOOQ15vIE1mKAeEECEMZpHIQUiEAhssm6rDwVl1miZSqqx4FibATQ2lHsT1pAKxUk1MLlSNoR4e7MO2RIZDS0GxjcS0293fbe9yySFGpgggu2d4hpmalhwiC1G2ks0AZWIhykWZ3QgcAgtKKXNOwzglBQQhoDj6VQdobAKJeio1p2K72477MURq2kbVgogTtMxNI8IxxoO/oiGlkvcFU0qaBxtQ8jTNBgdYSG7e3A3j1rJ1oQ/clDKGLq7aXpMdHR+nsQzjvN9ea9bVUd+frC9vr3/1x7/+7MvffHv54vXN61eXN8lzu85t2wMkTWDznIvEZjek+92d2d3X37x+fXn30Ucffu/7H/Srdrsb1HzOWc1FJMZgVsZxsCIS+qaJm81K3n9y/ebu1ZvLlP3iuOu6CC3DuI1t5d2qeQmxCyFmxzynitYsRY0fRmhLj7dcbubC71Y77q62WPe+M6P5M9fh9Fnwiren5uGV/OFkc69iHHJe8A5zqyIdW6IBlox2ZmESMizs3exC0oY+xjhPSZP6jJwSDA+5JlSNL6URD8tXNO9WLdTV1N1ZpFKPQVTHOVwRODtMLv1Qq9Vn05aZ0eEwfpCZ1BrRYORwEji/O/J0wNWdmasTHwh1OgQjm02tIAEJsEOGAxNATHWsqxKlWiYhgMB5TjllztG0HB0fY8Cbm5v9djB1JlEoFKENsQ2zZbVkWlIyGoEAonZzdNa3Z3dvRkn7PvYBIQpfPDlrmubTP/zy5vaeAY6BwM7VimRZJA+tUy1sHsrZBQF8KD+8dogPmN87y+Lti1Q7/Bprb2ZUsxtRTbVrf3ioNEJsQohZyzzOi3NLHfZRHcmJsEgtxA3jPDYNRWEGGSgVc1I4q1G+P7QHAAAgAElEQVQpEELOCGQOafrVmKdH5yc//dFPf+vjHxgVCRRCEBZ3MEdCEOqYOvCqCd0uoWub7f1w9+bF/X765uvX33z78rPPvvzii68vb/eywX4GDE0bYmxKVrOSUzEDiisptFIa6nIWs7qxEy1S0tok1AVVYASKAGnx3a7sdlMxNAFecPfy93/z715evxp//oufPH92/uz5L9xW8/hNlHJ6wv/23/56t8fF0yc/bPqj85OPv//97y6Dw6yga/tN8MI+llJqFJ2SkHCNAKNimqdx0uzYsIh0fcfMo6b9NJBJRuYmmGodlvYnIh1RpEYitTJP8ziOwzhWZw04hJou9jE2UiSnHEPXtStW1tkN1h+v0HAZ5nHMRN723fq8VVgxSzo5yFzrm2E1dtBBal5qe2iLWOxAJVnkY+/CCg/NXNXx1H9QZW0Vbz6g45V8ZYzDkHnBuqq7Cx3w6rdhdssDvcyWFy7P0u1XxGfR1Bc1BsjMoAjKkYIQNwECVzSMrm2OTo+IuW2aZ2dPTs9POIbLq6u0v3S4j15Ud9OABoWzR+ulOzs6FmA/7EmVTYLEuGma2FBGQGgBLfAAJmpISkwNQqGSprlkH4atqi42uJWoQMqNEPNiAG3VU4rAh/HDwjl1FAcczNJI00ZpxD2rqqsBLo00IUoTRJmAYRwJJMw1WLZ2lAv0hDo/IFs8WBb0yQleA8Qetou3LY8sor4HQHxB+w8hElK5d1XubYC/awr80IDXT67TC0MlBBw6G1t2ajr0Tn5ozkHVd7Sq7hde1Z/hUj1sgA+/HvD9//gVpJJ4hBmkIGBhPmtZ4HkAVrSy3x++CQXMPMZQG7wHvSLVxowWOT4cxbO/e64ThAksxYs/tIiVX0OwhYTm2QoKiEkaISIzIl0YxmRahiRhAS2r9Uwh04aIqJRSsk3zNM/J9fAwAAAUamQ6edv2fd8GDnf3dyHElloOTJ0TQXOZPRNIubiqDaPDA4KjlGTCDZScXEwqHVo4BGnn4poLCwTsFIbdfrgfPLPmbOrsAGTz4VkRqBWDGVcpKTnRbCZq0jQxBLfMaNzs6s2YMo6P8OTiKDbt9XCfqx88yNzqfK0JgaS6SbubwYidCe8qTKu1tFAtf92r04cT17LHF4edOi2qU+sqfV7es+1uy4A3zB1ygbFyEFSltMEXH+ua610nf3ywVqdKVnGYL4hGlYUx+HDYLOgbFs5hpReSqaOp1l0Pzw8Ou947F/GyxB84mqgkP6lA6gKkuHsgvHr9evWCP/7ke00UplZLKtBcNKsWaGhj07R93zHtraDhvguxDU2ZE4G6tmGS4pazIpup1Zh4FCibiQMgkZzzUnw8hMlaQVFmMU0pJStmXqJEIphm9RpeCyji6rioFte7+x1ejT/8yfccITbN0dEG+zTsUy7F9oMWnaaZSYK0MYiQA0FLUc0ppZS8mliZou207RrhaGSVYVcKFkTRq/V5EwJiWNd4gVRAPqmWSCAuaVdc0Xfo+lUIYbVZC+Hy9ubJ+dPj88d3w/z5n/zer//o8/tL297rwi5GYJJKS67l73IsLQPRupsf7h1VfGsporQi+n6wqXio8xYRfW0zq+0DqRWQgerjg4X4WelReHB4exj/4qFpffsHr9TOw/7Ob7+i/6nfFsBr0TBWAfQBJa6Jk3p40bcvv8xQrY7jq9xdS7L6xFQclyAHTyuqQHw9ZhymmtRUi5sTsQib2tsfC0CBkzvrnwavUUoCEbywW20SGsJvvrj0/+sfPHl28Vf/q599fPL9/sdKQmmaXry8bFA2T85L9v0+39/PsMUtXgtZEu67F99eN8doYlfUd/v5ejswcgith7yfU3Kjlndpnl7frFdrNZsnZcLjRyeffPI9LTumFCNMRRMN4zRmlXVYHa/bvst5N5ec06hlbJu0n4tQy5C+24ROdtNV8dJ0oV3F1dHp2dPeLYzTB1999d2ry5t6zozj5ApLZTfOcyqVQ0SsYANbbHTVe5lTseTAySY+vzjfrI+6ddv24dl7T376sx9+8OGTi8e9+jRNd1e3393efJfSF8KQ0O2GMhd++epqN3nJYb8fFdK2gWOlMaBppe3ETFGM4Cw4OerM5tU6rlcNC1br2G9Y80RpKmbb3bzbl9OTNXN7f7f79tsbAs7OTll6KylC5v2WiVexe/r+Rz/9wW83YeXFAwUfwu0wbO+meZ5KLiL8kq7f3Fx+/tUffXcDJ6wj2gZdh359fHJyOtxRjPfF9P2Pnj19//Gqa0LLN7dvrq43ry8vv/v2pZjCvUQTjnd3Kca2WYc8apmKzcTC1LBXCa1ZLba60HfHzawJAZoN7Igo+/mATnNkqW5ttbZiwBWWPVNh4VyKKzySuro6COvjZj9fDcNtsakh5EJTGoq5RG462Zxsutw1bVz1zWrVxcanaZinKeX9MN3/5Ld/a7+3b765noZ51YvEVgxqxeEhhBx1IY8fpshYyC9VfrNE6tQqUJdEB6pxeBASBGECZWYHDGyhQSHojPc+OIPMth+6DrFBiDprBoUQG2HhIDFGd1JTVU/FzbIaM3MxVc2o+zzxEiHqIKpPm5up+9tyzQBeCs+lH1vGUg43q1JqJ5fATrafht2wnzVt+pVIndhUcqIWL07KQcCuVcntYLHiyBnM1jQ5eMxW3Mqc5mwZAU2Qto3L5lwnBsw1XYmIppS2w3x22jaNjOPAEo2dApaUC7biuZQ0T9A5IxEXDMM0D0MpmMZUVEWwvx/24/Z2e90cteQeOWRIpNC3vQvatlmvNm+ubmiis4uL0eYvXn794tXrl9eXuzRNJQ85KemUUcbilGJsJbbByN2b0M1TMiXA7/Z5v//8+uo2pfT9jz/IJTdNk+a8H/ZqWVhEbJ7HnND3gSJfPDp1p67rClII90+fPVr3q3mYX10OElktU3Dp0DSx5JJzcvcYo5qhHKAH84eb+HAQGbBMOPzh6PHasz2ciX/mcrhhoZrTg8n64VNrTaMPR6oDBmNnODubaw1PcjOnSv1CHfJXzzWzyuwzU82lBAmIRMQ6ahks5FhS9mJgX4Qh5AY3rS8MU1W1TddqKp7d4NWj2fyhJV160oea7aFYwzLCh9dhZX1X6l/z4QT1xaxFOLgQ2MEVI6xsApAwBWBJgAc7szMSrCgSFhKWHg7uunzhNSI9K8gQGFZ02E0lW4NGjXvpZivTbkpTJfSIiTl57GLbtZqdCUE4VEDHPBU2p/6oP3t21K1C8MiGAOnXUdV+9atfvbkqrnViZkxBq3gSS6X6TlTZ2yXx5zAOHhqmQyl1mOIeCqtl5kbklcVV0QOvuhwYLdZjVE3KxB1arEzZXSkuCbLgCt9LHXJrMTdThbkQSbXjMyMDE4WSTStrxiAcAuLt6/snj85+/uMffe+j54G4aHa1ftXBbT+MadK2PWm7Ey1tJxddWP3+53+yu7/86quXf/zrz6/e3L58/Wa/300zNIOF07wYSpfkbkWtlFI9JaDmhALnJdb24GTKh5hGrjtm9fSFE7GD2MVNXN3ZiAJbibEtXl6/nr/+5sWry7tf/eFXT947/R//p/9+1fzg+bMnQifr7lL4VZDp9etvmr49Hba/88ufZkxZJ7Z5nkjIqWt778Yp5eS7N/d5VMGcYt4Pc0536rACnqSJgVhiK+5xl/ZaEoRCSym75eKw9fkKjRsXqKmX29vbYZhUSytNaC062ti2TYeGillWIxFBdb1Kt/v9SXfU952tm3C7zymvNv3meDPN6W63HeeBXGpwl5tDbbE1Ul9OIls0AhU84sP8f9m+/ICU4AAs0dKLsbxFNNy9qhIqV+sQbnfYBg59YF34h1Zu6eIWAEbx0KYJAURsS0A5ClBdWMjc1KU4IOIUVJrYNo1ZaqKtNysKFCk+e/8IBqEw7GfdF57D7na3e7GDAAFogRbNUfRViU4t82RupUQOoVv3RxsrPs27hluRxoWlbbq27WJzM762OXtRh7frdp6nSLHfdK6qbhy4IVZ1iNdN+SEDHQznt1Ae1CGVzWQQOLtb5YaUUtwYHgzqbMvGLgfJkhPcqZpjoQo86gfG7Ad2m3O9kQ94ZE3a8cP0ggnmdKDXHfaiqiIVMIGFSKoncEOmVlujimY+bOa8dHPLKeULoAaqRv7vzG2W/2+HnemtOT0O4NTD7vfuB3/+Tvgfu4IWJTIicqvBmk6oaWUgkLC4W3G1UgUwC53B3aGOGJhFhLXo2+BCAovwof2TGFSLH2YtD9+02jJIobevCSIWHOSE7MxgEoZocSx3GERAhpkVVRKOQQgEIZhrzqaZDczcrrrZZ52Xe1ALR6g30jQUNs06HjVlKhZQSk6amMkijDRbcgcbkUFzJggxwwKXoqWYHWKqhUAoqbi6as45C0MaqXSSpFoymhj7Prr6kMb9sPVGQK4oqI7PEoMQu7GwhFaYAzfROop+cztNMzarFiwOzKkU9Uqrqm8fCXEksFPBAmKre3goi7wu5CqyOdCVKm2QhWsMBQAjCgSyJaLUwUIPz57gxeXrp48fb86O1qfHb8Y92L1lywQjZl5guGXR+ULwqh/CI4ube/XrOWCrwnBQhSqW85ccpKhAxLLVvRPCc9gTD8DIAdpYcITDQ7twVRfzW4MSAUKmCESBw+XN1dFl+4MfftKEIBwmyiUrhJZpHnPXd20T+66bdrNYtFLyNL++GptEcEV17HaHQ5jBxCSGUunyNTcx57J8O+/UJ8zSNJGI1NTFI7Vd0xDBrTE3WCU/CyBZHU5T8nxTzCVnA2i9Pio2bu/HaUpmOc2WCtYd0zrE0DJDqAVPoGJe9EChL6GoPmwWy9PaCNqW2oZiIyIhxKbrwtHm/Pp2vL/b3t7sb7czCZoNxZYiu0TabFarVedqLHx6ejbuJo799f3w6sXrF1+8eXM1pC07IC1EGvJY96nlBrlXbulC+sOybR5uH3nNjjg4EdrDdrYcl3hb4VcuZy3lHLQYtqM6Kh6YCVRLw8pJYl4ItXgojd+5lqC/ejHejclgekdy+PbzF0LfUpy7+1JF12V7wF4XWXg9G2qZWdXl7zhpYWGkMXEgJhJmCYfphuZStJRStKi5EpEqM8Wl762Td/O3RwUdJLhEZvmhi2Bng7CVJxdnr767/tW//uL5R6dHv/zARzw+Ovnxh8+nuzvLY7vxk/PV5rS9H2Y4EAGhnC2NaFtBRCm4v53nEZuNf/RRkFaczEMz7vbZrelXRiWNGVYcGgNOTo7PT1dN0G+/+SowNVG6uJonTtOsaTQL4F7CKnbEU0lpO84+pmEqmSk0oTshjT2mm5GJ+tV61R6HNvSbzj1Msx2dfvBzfCxtNwzDm6vr3/zJl68vX+wnZKvJenURzYjzsm9Um4wW7328+ou//OmPfvTjs9OTcdo3Tez7GLo0TMPt9vX19avXly9efvfFe08doK4/mhJLPBn3OZeQJ767deXZCQjIZm2okeUzizUCYZGgjx4fzTM1behaJtamcZGkOoFzTlkXfE3u74fXr7fXdzjdRKLg5qrKNPQRJ0dPT48f/eCjnz05f26JXn335qtvXt6+ufvmy6/u7+5ySuM2I8j6EXNEhqxaalbNd18NUlOGmt2qn75uriViddLO+1knO39ytNlsTp6vL85OL05Ozzab7f329vbm9evdbrubFKsGXduFQBNDRci4JDPzYgbJkIBAj997dHy+fv3mSqEpJdvnecjoUN0nHV4TXFBQZiNGEHHybGZuWtTMEAiMKc9N0+IZdvvb7Xg1THeGOSVNebjdXgORQzZ3VVVTc1ejnN1c55SnNOWkKenHH/5yc9y2bRhvykhD120kiqoTQQJr25jlOlhyMIoudVEV69JhzGHwqoMngnPlcjIJhyCBsnux5Jk4cmiJA/KAo9NuP+xI5tUGzNFdMQPOIlyBCxbR4mqqaqnAyGramxeLHaOw1qEVc634YCREbl6K6oOrbB3WHrjKqGGmXOmaS9vKgUIbQhMgpK5TmXcJTiMLO0cPwjH00kIk5XuzrJbhBobUQtbAAU1E2zbEnnWumw2xNxFtI/2qC4HnNLhbbFhIiElCbLrOjffD0Lax79uUB4dS9SQgNc9F55RpmnMpyLP3HPu2TSkXL+4lTbNmY2n2+3HYj+N+NgZH2fQn0Zu+6fqm35wfjeN4etqFKJuzzW/98JNf/+bTl5/9+tsXL/fjgDZQw7Ft23U3+ZANY8pOIYYQYwvilNWMiUKMLbMO++GbVzdt+2WIfHzWH23aYUrb+63JDKK2bdM85pxCHMys6SDS9Kv46PHZydnR+dmjtolXL95MGVoMg61Pw+nFURQehzSMgxavSX5qCRQXgOUALbwzzTicJA9M4cqWOUxq/uxQrrYXf3ZSB6pj98MYaMGu6t8eUE6umSBkb1/o8M0wVwyH3X3pmZxMlZWVS0rIQ9HRxANrMFMG1xOripksW+J8ELYDROqWVc2MhR2o8eWHURURDkL6PwW8LVwMr71x/dlr6bZ0APVgO5DaGODKjq5Ai8GdAnEkhbsr1DlwgCDDYFQYRtXtDkwwpppmvRzrDK0ZKJRTGYepFHU1Nk7bNNyOmhQKciGn2EQSSCMkHFhIIMKxCU0UwMeh3N6Nj7ru8XuPmw9kd31jRVtqVm0vHF+9KEiIVcUOWuIhFrchHCqDQx/kD13+n1oAb288HiBMWzQK/sCBqPuXVBB82TsIAFS18ue8jgAhnl2plJRdDQZnW4aOjTBYSAispW78yhQBBgWQKLwUBwmz1FZbgpEhSBDCdn//k//slz//2Y+Pjvvb26tVz8P9bde2hOiwpunOTz44lvcUvYJe3Lz5O//7P/zs02+GfdoNoxmBhPgEGIcxpdFWjwTmta0TgxsXVbAEYVN4OXgp+QNUhwf0b8FHBWTL3JIcZqRKbsaymEHMkxpstVrP8/7F18Ob159OXH7y8999//nFD374ydHHT69vvnD6A5GXkGdXl1ffvPj640/ej0KPLs5Ib6/fbO/3g3urLGnM4z61oZWWxYORxpBPT2Pby37kYvM87gNzDBGMbsNkzEmmhtVL2Rkcp0/WHixpNlZz3+53JaEJse9X0kCKd7GDQme3hDxkFA7UEDjlslr1291OOZ+dnR2dbsb7cZ6nyQYEjr0wqpzjHVTYHXrQoJlTHYhW0rIvdeS7D+gDerU8o/UhqqW3HwbGZHByVz/0awvOeqhyDwjsO1X0Q0SpEQxERPpAZACDuMBrvF6pHag71/aw+myAoCLKgiY261UTApekF6dHx6vTq1eXn//xl9uX+1xy6ELwCPe+XVvPhZNqTvcJO9y8eJUtH6/61emmk9XVy/uGmqSme+OApm9hYRU2J6vNuu9xkxPNHa3UvFuvX7y5FHi36tI4aynSCoyRtLhSfa+cFzdmWfbmJXzMAWNUf1wqpVhxz/VwdoChWS2rM7srqQdi+GHWviTAEcBq5urQKvYhhhyOG6ocLDevdKIHZHzRl7jXo+dhEF6NFpayo4ZO8eLX8/azykIGwBJQ60sPU29+XV112KLLxM0Px54trOQKdL1tDP999Orfv/5DDKw/F94KKakcWFSqBndTFHJ3CyFITXM0dslE6lWGX6liBicjcWczUvVsZsGimAuzuWsqXu/n8n64WoEzAuBWOYquVtxhXr1+mAhW7c/AQhLEldJsikSBKkDDLA33pkVnyzqKTyzRoqJzDkFY+tA0bRu5idLM4zTtZyicAFIY0ouULlN4HFYXq3Q55ZjHABCol9AEEgqBgkRmdtcxjV4qqx+skudcUT2OwRhmliTTaLFhPth6ElGavBTAkZYkC7eMkpLUqHIYc5CqAiQKIiGIm2S1apnQN6vYoCe0XQ+X29utSMMiEHrLLMYDngomsodwYvCB/FdDY8BUM1NVayHrtowpYE41PB7FyVlJAHYXQmXjBXz1zdfvP3//6QfvvXh1c3P1JeBoAtSZg5ODqwN7DRVebLb+1Gp769iwoAPVhdQO1RUxmRdFtbr0h23PD9cCYS/7Ih8wrIeYQl+kqzXxp+ZreIYboyWulHUKkUctwvHRo0dt05QCUysKGIlQiBRCYGZij0GUiQxlTnma7R6TOWyGAwxupO6kKLYwtEWI2N2tOCPU3OplhzBnCswMcyaiGFjZzfbbvS2iWnAgkY6F+tXaRjMq5lZ2Wgrvd8lYV5teJM8ppRkOSwkpgcz6NnehX63aVdevVgOgFFjN4AitdF27WnV933C2oiMziDwKr/suNiAydQLHbt28udnfXO+vrm5u7vdzxuaI+hA3IhI8tuH0+KjrulKKk19cPLqX8e5m+Obr12+uLtd49M3L1M6UC5gExrlkV9JiD2ASLTcFh5byINvDw3D5YFn1dtaMur/UlWBmzKxe0yYPSFwMZq5qb3sGgIhEGEApmYiYKs3PDkPLRV9di/h390c3dxjVbAmqFAccFtXibMVcbSngDwide/GK3x4I0k4cCOTVcmDxQaG6dVPbte6lHitY0DqokZC7ldlIi1pRW1yy6rbPgsOQA0KHR8MEDjcv70zHKvHRa3wnQ9iYjM3Dy2+uEfCP/p9/tjm21Yo//OTxk9OT46bFVL7+9s3teCchnjxqthq2U0FmAJZ8sEw+nR+d7Ya7/WBgHDGZxHGepvGubbvTJ++N43B7u805d3GtyUqZnjx99MknH4UGn336q3G8Pj0+Xx0dR45uyjHEtqFmZR5zCSFu1hvOSiXvzHRM2T1LmDRo9t3756s8j/P25uoGu/047OfYHJ+fP22aVdusOWi/tmfN5he/+Btt003zXEzVUIE/AgUOgUQg7uaq7inrpEVf3fzx1R2p2mbTHR2vaWu73dX97tp8LmXOtPvgox9cXV5KoD5ujk+ftb+52t3m/TSzQELIVkio7SQ2JjEzpRAlxhAFxDg963a7iaAS4K512JItGUFaevrsZBpp2Ond3TBN5XSNi/OmiVa0nJ3J7/7yL8UQN/35tNW7N9vf+0d//8XXl7/+k+/wCgjACLRAI03rqzWvunPu4uR51Hk7lf6sI4NPWsa83aUc3Qt9frv7g3/8Bt3vXTzHo2fxg+/9/4y9SY9kSZIm9omIqr73bHH38NhyqX3ppXqGhW6AxBx6gBlwQAIkwBlgjgR5IMg7fwNv5Jk/gjwNQBAEhgvQA4KY3nu6pqu7qrqrK6sqMyNjcQ932957qioiPOgzj6jq4mKHRKaHR7qZuZqoyCff8uVf+81vXV1vLr/1a6fp9Pbu7dXjz19+8fKvj1k5GwwxhrVIDEzDJsTpNBNje7EOUUqZd8f7w5vd/d19WEUWjo+61MVxf7LoILASEzPY2Yeehn4wtZpriJ5zNjUEhI4cjuqry9V3v/P1u/3NYXp7nI7VcgHHEEPnIYgETON8OB616pxLnnEKNXYVlNW1ep2P5dWbT9PKn318OeabeUSxQiIiXK0KSUohK8jaCkmXj1pbUci5Jz6v2JgY4GUgdAKYjWGwBwkHrOvScJmG633VPM+j2tT1McZ+PhQGEMgIeZ6dZFitSURiiJ2QKABilhirWhqSF5JaW+GBwY1IKAi7OVzbB7uNGEsdXAB/IgaEhVviESKziMUkzAgiaehT30FwnOdiAEYKkvpVN/SBedisT6d9nWdmdCmkJAxTVQL6rheJ0zSf5qMWY5IY2R0gJa4SYs9JNacupC5UFeaWNgEWUODQxW4YXAvcuMKpVK9Fcy4+lyyOKcMjS5eEnSIlrvM05Zy5X+3u9sTopNPJAVxvHtW0qXMh4ifXj6vqNI2zznHdxU36oz//w09+9vNxLlfXj2MfJ6uVUUAm8IpxMvO86mMMMaZwOBycUs0655z6frXZ0jT9/OWLsR6/8o2Pv/n1j4v64XSgULqeh2GdZz2NY9VcStmfdoTghhhps70wn9TMqa7XEMhO9erRZr0ZplN2N7hrWxCBmWNj4S6bEzzcZuf7ZUG1lqaoubnD8ata8XePdhPa0gydoSCCnQ1NABdhVfNm7+7CApC07EA4lp20g0QoUozCxLWaqWvWlHonIqMy1eKqxVDcciXmgKDFnJwasU5R5qqo7OTiCDBSdTM1GAxmyCyy3NANvmornAcpUusMiUFwdSJaNj1EvqxKFwY+zsQys+Zlcl4dEbx9ciJxCGbuVlUNToFj009GFUZw94pKtJATlhub1DlAEFIQCbVUZJS5TKc5Sfdqej3dj9GjhFgb1SJ1cQjVdSojJThUtaoG9QjF7qD1xctD3l1edPGif7n7WzJ/evWx0gVBcAAHdBIVJJKmMrl5a5L5jLgY1N55uTbyqrap/zwtteFvMRg7z4VnlsvCMD2bcrQzVh1MJNRmTyIQGNyMBlCLulotCmsrNzGtYIgTgwUMczXLc9ZSu23U6rlCM7x6Vgc8CGqhGEg4MEOg616/+psf/JN//DsXmzSPtze3n62G+OXnH8XQC/pn6My747F879Wn//L/+MN/8b/877d7PFtDkO7u87gHejx9vN1sVmlIvR9lKMexDKsuMBNYJNaqOk5ewVHMW6CFk5OZSzMp8fbWGoGrLnW89Utc2cB+Jn205DlzgxpM47YjgxodTxWK/+a//u/xIf7zf/5Pf/cf/b0vf/Vr/+Qf/NqPv/jLz15+8smnP/qrv/7k5ua1Yhq24dFVdJWjjscy5symSEnm/X1AIpaayzxlIWwvUrfp3t4fDvdZDKswiSD2XSDpr/qLmlYXlGeNEc++fH2YDxjzEMklHvLEbL302/U2GGOsZHS8P1WyQx7vb3NMuWSTEErW1WZ12o+TTdzJ5mJTLN9P8+FwWK83nBA11GJejIgd1hgCZNQcIMms4Sr0HrdzUd0QorMzDG5NBHdmAp31DI4l484aB7JdW+dGe/l/GYzb9PXeEV18+RowZWAjAKa2SMrETMzqg99TC/5ayogzUfAQQeIKzTqR1rEUcrJc9zf3XOPbl3eWkbrUS2fZrTjM99MOwsaj1zgAACAASURBVOiFUpUB2uGj6+fGdcqFCvKYx7ujrPp8n3evDn1iT6US5nWpF+WYTp5xvbkOl/F291a6NGx6uOeSERFDNLNqRVk9tswHEWGP8EogWNCH94Q4BAps0FK9aK7VMhobLhCBSRRUASGmRhQNbmaoru7qTYfSJk2trmaBmIkCC7m0ccDcW2BH4NDecHMTCM5sJFV9jxTiHJo1VNMKOggGz3lybXrAJUS2lSVq18xZr+KOivOGYpnjfgW61BgGD1yU8xd/BW7lf4d79T5R6//9seSF4YwXLGXWmgN3y+piMzPTs/i8LfwNAtBCM1M7Z9U/rJzctJ5Do9rxt/b93kwY6Qztup2t+82NURgSz94QxpahZO6FAnNkiSIciLwozbkgmxqM4Mnh5sHAYkN0JgmSeiKgqtapLhaPBBjEGBPxxENcieSqRcWDBq6kVSu5sa14cCcqQCU2hrlXYCbhEKIEtP2bRlVmSkGMYVapwOEMF4Evltva4I9oJBUKd3LOzmzO7opGiZyPE7t71uzmPcWw7jqkLuSqp9206Z90qR85kzAAiaxm6hVLIKZRE2Euv5o2PWPZ2y0AUEPMl19wo4G0IR1ELG7SVl5GxBByIcCPp+xC60fbi6sLEkAMaNweIQERG6nDqQEQyw+gVtiYGibg0mpXWw82klRjrYL8fDXj3XOhltq8fNKaEebygh5e17tkV0ej2yyLSmI3N2c2mDuxoBVqIfQxdV0ahs3u7qha3MDMIXAIxkJmWuZcZ625JEKDBEEIAUSs6jHEbhjG06lMMxioRhJiTCJSSy21nEEbMNBI/ASgevZCxJHZzL2eBXcEFg4SQowk0cyWrbsyVGvF/jhBNCY1JTeEEM0cVOFoSX1mDmNmGdaBRELXqRkTp75LXQwhpJ4hoibEiww+BI5hMd13N5Hw05/9eJ5pHDMBfYftZj0MIQQlLzVPMV6HwCF2QVLsV/N8uLk5vvx8lzNvtxvcY244TWCFeT03Tg5bOm00+PRdHTpvZv1hEfDe18+lCwvM1J6l6UK5wsNWmZuDoz0ATNRyCRtJj8+o1jvG66+sjEQtFfeh9BLeYfwPJllnlJjaAuK8O8WZZX3+uwuhY7FWfN/l0t09RjEl4waq6OLjbNXBgJui1IKyKMnbqouIGle+mjePchCImBs9+JyBe16/A4FBLM5wQmVVwLhLm35NN/f7H/7lJ8OWfv0b/yzg+NHls8OXvuaaXnz/BxY3qcfl9SDHevd2RAG5oPLpkLerAPBmCJstxxTcw5vb+3l++/z5B8+uH4d9evPm7nBA6OBFRdKzx4+fP3u8P9zevH57dSWBrW0x3JRAIXSSenWai4mwxNT161q91rmUqmoVPuYTeM5G47wrxdzYGKvLjsjv9l+oUqlu5n2/udheHX5+Z2osEmOUGAlQty7E/TwLUaCgOcM9RpGAasrRY0pUy6yTHfc5n97cvMplXK9T18ft5SoNPYSP00TSr6rd3x+mCSGEq8sLimGqmQKvNz1oVj+RW0yUEgWBOzE7i5uqqhIZwL5I7SlId7m+FNLj7l6kbDbYrIf1umMGs2w2H2w32y6sBP2b3Zuf/+TVn//5D/ZvdW39MU3DMIRtjDGa1vv7+33I/cYIOpNPSlPR7fYqIhiV42E370Zn7bt4ddVrtalqeav3blcr/av5x9vr/tmHjylCJD1/9tF2++TVF39Glo6HXKsSOggZplzmY5m6GAf0BJrq3G262Ies2QWmVspcS3E1KFrgCZEwB0k0xL6LseQCA8FUxNQQnBOVogBW2/7jr35wnH4+lrFYMSswShI32yHGRCyxpX+2GCMOZmJuMaYorLWWbK9uX8V4+fyjJ/OMl1/caFFiEMxdFRJZJDIytJUPsuY+awtPEURNZyJETGdBChYWCGvLkIsqIhzY2CXIZrN6tOnH8ThOI9xFIpxbwDzTYr2X53mec4w9gWOQIakpMUubpySIqbYJ3BaPDBCkzbBMQmJEXJuPiy/kiqXaNQyEzlorgkhwL3CwCIn0q6HvoCWUubKzTTrrPtfCkT+6eprzkWYSRoyS+gAzFAsSUhcBgFrwNFIkYpZAIFXL5kid1CrMblbNlAg5z3PODtRaVWvqgitqmWMMy3ISxYmanswctWrl7F5b4ISqmqvDT6dTN3QGznnsknSxDy5jMXaICJiP44m7QFFu9rd/8cPvz6oxdh60ksy1zFqrwzmATYvV4pq87UNhxBzhZZqLeR6GISY/ncrnr3apD8+fP44Jc1HUeb2+IKIYY+o601qKgWUcRwJLjLn44bDfrLcs9vh603eD2+v1ugeslFlEhqHXOmkxDtL3nR3rL9xlD4V/kd28c355/9HwruXKoXdfffgbePgbtKxoGpX3vS7ofMG9u+9AizZsWdMsW0IWYXZQC7iDITBX86UlfthGq0oDUM2dlJnQVtSAGRgIwgzjxuXj8wBDC60sBHl4IYuWa7nbF4XFWdXfLtzWlvoiPm50IWomkm08WNCatpd1cokRQs5OgBA3u6xGrWIncmFrmxwH3MXb/0dhRnA2JrAwCRozFApXsFA+5TL7ZkgcZDxN6i5LmnCedRaV5FTVWE0qHMyKUm2ap42TKsC1KiRgzvOLm9eoYKFlnLIz1+CcZtxooGeewsNBacLr1kqwu/0qZh4/oJ7LWnfpZXgRLy0YxJmm7i2khomFmiS8uquRE0jg7V12hggI6u4wVSuKAlQoE2VTc2PUplsRhYMcgcEOLdPQ4+9955tfeXJxsLe3ty9zObrK29Vh1cfNsBJsbm4Pv/+vv/fDH7/4yc9ue7p43OX9bhrHTEKrqz6I1Cq398d5nkrNzGAKcGFEENxYazVtdMXGKIG6wpzInZsJeiNGkDvBtYUkYAkFM3drv/CllzJmExZR5VqcTEIUI1eHU4/X+9//vX/7ySc/+eo3L/6L/+qff/T4m7X44bD70gcnnepYDiJd34XLq3iyNR1nmwpLWKXVwU+ruIocT9NMwYorUpxNslI1kKHrwKB5mqsDgbth6C/WXehWq0F6D45gFCkYpO/6QhYoCHOgUMlqLeM4ZtO5ZijqjJHmEM0J0Wx9uQoiLrqf98f5VElDCmBv3mFERIFQHZUN2gK63vtg0rmynK+YM8z0TjpIAL8LPWpfXVRWdHaV5YXYBQIE1FCQ5XR7e+Nx1rKZGdoAavC2lG4fE14oYm6EsjwXav95pvugBYMJQgwIXHNxnS+6VYpxqvPu7liPEEXUKM5WKJ/GPvYp9VPOLtFgnl1hUOTDLJGDyxdfvJqOhikYqY6qBx2RlWHqYzwdhkMgbDar/lkna6lTna2WomRea16tVw6rWZXU2BkQieKsMHNuW+uUUkV189bLB1nS0xVUalk+qgRiFpLAgZy1mjOEhdxqi65dXIIfJomzeRUc77jZjpZVQ2zNmQtnTi41qyJffvW+yE3MQcIkxL6k2ixg1LlkcWOtcqNktX4FxCwtigTGfnbp9xYiu5yhh8Ll/l4bAzDzO3u19x7v0KT/B2zr//MRCNBaAX+gGbcbRySEEAB4m64flNzLjYJ2XKcyL7smxoMqeZnGG3kgSmvCHkgPTJRiKp6FZbmAtKEXYKKm8BQhAqx49tnUtQYOKkkCuhRSmWcUoplQBE4swas2DXzxYsGzl75LMQURokBlzFoUgLCUSbuuy1N+89ncr3uaSz1V6hlo/kzm5tmKECO7TRBjAnt2nQpZ4CBsgrrYnHEkYq+65PEpKQlClMCo7W0LQUIMTKwnNhRXc7hWkJNwC0juQ/fZqzfbjq2Y2bzbnYah2647CI6ncZzq0yfrYTXc0SF1cT6VIKKnbDAi4UAKiJA/aK8aTfQBXmdigjObLwm97M6BhAjm5soMTkzkRmriYCYhBHK4mt3d3V+sL7bb1cXl9vXuxnN152V9JvbAN3I0TiozBbi7mgHEjZwobWtpjZb+IBL1RaXfwHq31jk5BC00gQAiaehzq4B+rrEEEDWfiEZ9tCVcCtTiKU21VqPIZjaO2RJKKaf94eriajzlFOLkRUhC01YAVfOUR69qWUnAnZtXdKACUzd3CZK6NM+TLiapTMQMEQQjhxYtGc0ptX08Wi5UM6Vgr24kxMwLy4hbnB2pGqzUuchZJ9Iwzt39vlqexiopdWnTD5KzqU6wEgN3fQJwOp3cq3mW4BEk1jx6XK1qzk4cO+lXJCK1eJ0zQ7vYh8iSYtVaxtNhmrRwUTeHnCMv3NB1Xa52dXV5mk7DatV3693u8KO//vnuZnYbhrTZ3WQQmh+BhGjm2jJdFyjIzZXe6a6XkvZQohbTzYc/Ol+RDvwC6uTeAKvFSR1YjsHyfa3BbbcAn4smmskHCTHLL1REXwr0UtCJiMRxjrbFO96fm8OWSEIibxHDHFrw02JyhTMzl9rKmxmEZiiOxVYAzMv51OptSDYywFxhqq7qjpYTwmBjX6zn2qRC2tKXlvth8alYbiAmaUzY6lXan53jDt2obcetlLTamBtr95O/ffE3L376X/5n/+nxcC+SPnr6scTNp692b45HnuaLi+SM3QGWW7mgMs2ETYwhJiqzvzgd/v53e5YupctpzHdvdynI9dUjK/fH/XGd4pc//vDxo8s6j3k8PrrsHl+vhQWqRbVq8RYEolpzcbMgQkJ915vZnBFSBCyXCqokzJFMvBQDGQWKHccYS/b7+8OYJ6bkWafbg1YDKASJKYUupdRJDHPx+7u3XYyb1SpPk5Y8DH2IiZjU9LivLNR1SSvd3r357OUXxEBYd+uri0fb6vbso48Pex9n2Y+nVze7rtu6uwQBIUZSN6u5G6wLxBKFPQhiFAlxHPe1lFKLwGMkj1aAWqCZWKhEm8YxBnry+LEW7fsQBCnJxcXm8fWTPq32t+OrF1/85McvfvLDT+9uQI7RKnWx5Jq63o1Oc9lcbTdPVxzT/niaSF3ICupJ4eSZGV0Q0zGPU+UQUieR/HijZbKflM+4p+1l98Xnb9MqXD7ZPnl+/fjJ1W9/93cOh9Pnn75+/fLe1AtNNROcY0+ho9vjbQoRZinGXHJapWYmGlSoAIFrVlU1QzVXqwk85zljdreGVoRARMIdFVRPuHjUX38wyIBXty85zBKInM3raRpFopObWr8a3NjIFF6LRQnBWE3BpIaci9X95ebiybNHIQzDsH758vWc87JC9EoUA1O2aqZwEIuTuyqoBQK1SZHYhIih3LYtWlVVh9DnOhtUelJymPdDv75YXzza9lu9vb2by6lLQSTsdsfplEPqRcTVmfh0PFr16+unWirBuyRaxRTzOGlGcjHXamrVFjGQgWBtwRzAtCT2AIAu8UutwLXidDb/c7gZGZUp57GOp+lwOJhRVYhwl3hYbedTCV0Ew9hjkBhjSoFgRNBa3RroGFSLmQMWA5zB5EEsxsAMCRyCjcfMgXIxrnC3IIGZVus+JAaQc44pOJlAtkOwqswuASDnwGlIfVGbylwRRcC2P8KgLD77VLVGC7nMWWsHCjENsduut5vVAPdXL196oI+/+pVjnf/gj/7oLz752be/9mUZYiHVfNpNx7e7/VyKL72FV7WSlaFm5iRMHPvOmUvR0zS1oAzAXry5ff7F6w8+vCaWUrzrVsfjUUQuLrZ3b+9VS4riKEyRyE+nQwghRoHqo0ePYkhvXr8uNU9HvXu7C6FfdNtn39rzTbW0zW1JfYalvB1FLLBCw5OWRYW5R2Y4kXDDgBpM4YtkHlBv1CUsQKs3UvGyB2omAQ64mypRoMUTfRFuNOsI0xpafH2tc55rqXDknGutDAkpxJiCWEUtyO1pUCCiloNnCKAACGKKoRdV5SgUCeUBWUOT5IsEFlarDiVmMEiXy1obm4icWXCWL2GZu9qKvoneqE1OJCBmCJE0J3QyYu4EDCOnyEIJZmgzUoUCoqpFBUECe3CO5MEqVWomOMGHLoUhSmKF5pKtmFAQkarqjlJrJG6NmZPNeSyoRFRqiRxC4CAJFNXNDOo6z/PpNGupq9UwncZS8/5w+v4f/hBrsJNVIwq1Fm6Kt9aYLHD5mVd3bnPMXeS9BoZIVZ3e4V84A6LLMWuZ19y8i2lpVpq/gTXjWRbmtiQ9439tAoOwLCyFFkVjVgu0mpNpm3wBdoFRzVazFlLiQIzQOzORZ4auEq428e9/52vf/e6X7vVnb29vT+Nue7VNvIp8OU5y8+rtqy8+/9EPPvvjP/yrn37++mY8kctcfM4igViCgYtRKaVahXuMHTNvNpuc85xLKcUdzYmIHONxMrhEWWgaxOYtnKmlV5LDmESYhASAYbEVBLRtr5s2lYmajaBqDTESwDADgYOE6x/9+G9/9ENcPcdHj7/05S8/sX7+8Ok3Hz9+FIb54mI1lrea59U6PpGrk72i7EFUYr18tOooMgIFUPDJbHYqc1ltOHYgD0146+5aMdVD7OqzZ88vL69DDD/+yY9r9VxdneZctJoVqyiH3WEVujoXlDrPZayzAhzghDzVXGta9Rzjpk+mdT8dreo8z0YmXTLyoqWqkZOrBw/EvIx5as3szEmxAFQL3uTubtqqip1r2IJ9S0swXcyX+GyMt1gNnSuVG0C+HEddUlaFZEGgWkv9XsOv7mqVBczU8BFVf8D0FxmoLSWPH0g8BImSht69nPIcJfUx7U5HNkrENWvk4BnzcQzOKURhabh5YzkZY/ZSJz8dxpzz4c00j5pseHn7EpkkS861zcsoVE5zMeMDXuwLdcQbkW2E+mm/X237kGTORSITRzODISJ4Rrbq6nBW814C3MGASIt/FTCiuDrHEjkImJS8uKmXbFUnZeVAq9UQ2tLLgcZYhVVdXGxAbYCoy3Xi560At0POuWYmXmx1qWlGbWkveNmctEGz+TGxtB0TM0hCgMFpsczmRhm3cwlpAzpBW1Th8l3tN3POXDv/ivk8CrYh7pe8232h1lILAMRCVjB3b9/5dx/vMw8ehkF3Dw/wP4MfXjAcKaSWouzu3Hwvzez8A4jIoLWUd7Q0JmFmoja0c5vpSGIIIJirmqlaC7sjtDQxbgtUGJmCuUVYENOSH+dOcIEZVbjBzNRr1rnmXNvGQJ1BLGxwbsGaBHG2YqNPXddL4D50aYhmykDgwHPSane7u3E6lWlWbifDqhdS4ihiXosTkxbXo1r1SCQuqSaAfPbqaqQgInHqlP0MSwlSR3EIAcEJItQGrBhjDEEPtbH8qlol6KgIFiNT8DJXLcgwAWr1adScTxzRa9DqXTc4oWgFVW/WAN76xYWowY6l41lOpwO+KCMIIgGu1BD4BUZo+r6zZ5QQsxg7kzpzI9ZRQyTJ73d39uFH281mfTG8ntE26nBXMpi20AiSlrLXVt1Ojf/Jugz51By4FlW+kjYkH4020paJQgt38b1d5bLhOz9NLN6ATgtmAGF6oN6cqTIuIs1rcEH44abwE6ZxNvUupVXX7+PJp6JZpQ9JWGBapnE8PX18tbu5m6Zdjltme/oI+zugSmA29uN0ylYfba9IeJ7neZ7rnI3UHexiBnLhxT+spas3x6+2LiJYsx0TBsNqXaRm1UGh69WgKBQNazisVtzdz3d38+pi2Gw3aths+8223N/vyjzVmk9Vya3UQFwb/UnV5rlma7Q1bC7TJvRE1gopCoL4sIrDaoDI8TDf3u1LQZ4c8BDgDtNJtVOlfrXpw8qZwTJsNl7xk09+9r3vffZonb7+4W/NJ//+936IVpdCFAkgU5TWaS0sqwWPsgXIBqh5YrXfrJ1N/9o5PPuot6yudyjScmLNFwoCHFBbVjMt/IgeiFLLCcFZWreUpfdKIB5q6DtY7Sz6fx/+PydSg87kXTARwchwFjbI+Xm27xU3gNWcA/sCqII4xBCCSK1LzkHbqrA3+iNpUxUSE4gJEqO7W4WZNhkU3Ini0u02M/f242hJ7ZRlhoGrm3uDeiGgABikC0C1ym9uxgL8z//b733nOx987auPeD1w2vzD3w1/9L2/fHH7p+aDoD696ubOT7uSc4191FyJ2dVOUx4L3NCn7pin3d2eTJ89uR5iTGzS4aMPnn/rG18VsTcvX5ZyeP7k8snT62maT6d5nqZxmnKZ5tlrLm7adX3oO+YAcBSh1EmQENncSp3J9TBlhDRsydRyrkYqibtVqlZzzdM0FdQoqd3KalTKZOp+bPsjK/O4XV9wnHOd8zzNGkNMXdc5WZmrk2WNpvrm7u3+iPUGsQupDyJ0f5pX/TatE6V0OFiuyGXPIZCEGDtoLXk8HiARl9tuvV5VrVpy38fr68sXLz4bT3WeXATD4ITMJLXidDSROXBlyGYVhAPMSpmfP7lerVd9F4e+//lPX/zt33x68+butK+7E2CgCFIGcS3z/f5t3KzWV6vrpxdplfZ5rFaNXEJKcTi+eg0P5N2ANKT1PHGeKxSqZExmmNzValxTrXZ3OBTCxePVR7fHYbv+9je+tdvtOaTN1Xac8osXr8cpw8HGpZopMpmpzeMMdjMVkRRi13Xc8SqtD7vTKZ9yVi+wamOZx2Z7wJBAIgyGBw8d11vvP8K3fvMrT790vTveHE/HbpCYBARTzDmDSkyRODC5qZymPJ5yHqnv+s2GJBYJhQlmTBymPKe1f/Tlp8Om3403+y80RYoBrlbK5EVATMIOFzTviPOHUUAucFnWK9WEQpe6TNnZjKtxlQAKMLUCbHu+fnJx+WhNYbw7vEqdxJi0aJmsZqy6uF4P42naHY5ebdRT3dTAXKtaQYpRwdU1SZhOU2tSz3cB3LEsVgG4NWaKLUJGNKSbiMFwVBKyJi2qyNNsTrNjd7e/eX378QdfKlnHAwIVCMAWVjKsezMrWuZ5cjUiuFrJ5uYxcEzRrdYyuxMz+l5g7gYm7/qUkhC5en17m2MCAUGY3FwJ3qWUHG6mVSuKi1g39EFQS6FqsYtd1wnzemum9TSfSi1DSih2MHCg6nl/0thx9axWYhfbHfHo8ePtag2zWsrbt28/+PjDvh/ubo+/96/+z4t1ikP36Mkjd7y9vXWGGsa5wMEUmcRKnY6TVSOimKI3AgszsVdVZgc4CpnqX//opxdX64uLTRar1Xa743o9CAu1LZLWYRi06jgd51w26wsAZjYMfQzd1eWTIN3t2+NuP3epRu5SSjH0Ve00Hnt0v0yveq/HbmSjBdV6Z8/u7aps7tp0BjPazkNYQGS+iOAXetXCXHrfApeoESIWT4imLKTGflhutqbRV9Xa1n8LjFvnCgLEjRRCwzDYoKe9aVE1ZxJ3V68g5wAXpD706y52oaqxiYRAQZYM4fOturQDLEba+vzFsfXdgtN50SX6w5+0kWyhTbWXR2CmttwlaYaDIEJVbdDWYh0JJmHLBgGZqxVSdrSgIufAcBibNfhPvNv23SqRePGaD3kuNkRhEemEZ21+yi01pWg1MmUjpiDMTFFivxqkW53yNE4HSF6v28kxuKUQLlbbNy/mw2Fsv5lSSjBKqc8+L9xpW5ocgBat8LujgqUXbyi1WWuZHwwQ0OhVzkTNXB/v2mHYAxq6MJDcjYg5PIwCZExBgOpWmRbqXMu7r7M6jB6iEgE4kkSDtbB1hzsbicJdtVxsxfJxu8G/+zvf/o3ffH5xKbv9F6qq5iTd1aOPxnv5qx/8/M/++Ec/+tHPXn5x8/YWk1JIg8HNhNgdAmJVN1QiMzIJHPrYxdh1gxlKrm4wd2GPIYQYSsml1Lbta+thN25PD2dPhiRt9Fty0RuuZVYWPPdsDtuSLgRoGhGHAeKnCauU0lpSPu3Kf/vf/Q/PPsI/+6f/8Lf/vV/vhscfPO3f7H72xZvPEMZuHahPT58+S+v5cDyWabq8emIToHLZb64e9xW0n/PNYb+pg9YtwaBmVusjH8c8TvPFRX/5ZNV1OJ32+9MteciF5tnHsR6PqBls8J7CII1PUFTNydytoM1lIFTTi8uLKc/zbjqNI5mTECNUdcYSPUoO8sYSJmdxIXd3RWmHipoQsJUIP5OkWq+7qBlA7rygDCB+z/TIjVvu4FklIwS3xtZ0tPm0feqXwnQuAf6L7TgeVsS0bIWX+Q8ODuLMEKYAYpUkiAVYviPEEFMHZTaJJNNUddLoqUFAQ+rPpAdlRtUsWDZkcFgWzXx/e5r3dR5tmg6YzyaqZwEEgjSqwfHNaTwykvFJNnw1bFfMZBiL5lxKaFB+bRI+9UpsNKTVurvoU/fy9vPNakNCYEiKDmj1xJ49p5A6SlDNY1FTnUo5Ts1sPiSZeOrXnRNxEDhp1cYpZGrl0wncEtu0qpsuo5aBmM42Ve8uFPzCSN0WKwSCukMbPwvcgnaJQaUJiFpYVUtDiCILNYYWKB0tHYDe/Yhf+GFYavxS95e76h3q9Mt35HvjGC0B8b90UH758fA91KxklxMsC5jQiGFNYbyslLhRRoTOyFkbL7XUFiQgLCwcQoCjZZubL3GE3Dj71mgXcIOpmZrnSiCiIC4EVA7CHENquMlSmswaLwSViB3uahXF8zgbfKFGEFNggtLMDIIwm6iVrKp+kkQxBQntitdi9uzJk/E4j+U0lrGiAovjGpMECl1MVctcKSJJtTnPKCCRRD0xBY6l5KnO1ZTEmSS4BBD7XMzcETrpuNOi1dTcTVTES7AU5lAdMGHuJDqKKhyOZthC1HVIkVfdZhp1Oh1bQjFABusix7ioD7VWExczI4hAmBY5JvMZKGgfxQcUk30JyAGEqEUUUyPjno8Vw9kpwIlE2MBGTkLEGIZU5ilJilfd4+urT+qncRCAGxPFsfBQiA3aJgRv3CgiOLlJwwDMvTnAmdOiPF3WkuwgF5CwGJnqmTK5KAz/LgLxfilsf2xEDGorPkBQTdGYneTUWh1QrW7VAepilMBaTGeUMLtRYJJAzAgBfUdT4tNkh9P+cNo/ff5M5DTnKCS11lotpZS6xMJmVkrx5qRFFCDViFiafTxg5GEBFu3sa9Akb9XMALHz7Ly3HAAAIABJREFUuGLtqkFgVCc271GtNii4Kvb7cbXemJlIWK0k59F0qjo7SIjNMPRdVXGoaQXUzVVBBK1WazXPLOItlpqVoCESh7Cn6XDaZ8Wcfb3C1eVAsNh5ShxSqk5CVB0KL1XHw3zz5k6AgS4SreZptjmAlu1wAwmZzxeXN7UqGtzC73XnDxXLFqOrpSA+qGber01YsjVaG+50/rqZEdNSqvnc8/r5Nm03IdF7Zfzdo9a68GWxcEjpzO36BfoqLdX0Xavoy/N/YJS1jfrDf5I1P+O2MG48JhEJzELUxP3uilZWl7TQdsoNjoVm3N7DxTSwGQMTuxFAZsS8YGftyJ37XXhL4jUouwRblCRC3tFcRxGOQzQvZa7/67/810+e/Idf+dqHpeTt5nq12/3Gt7/22Rcv/+SvPmPBZtsPXcpjzZOnTu6P90PfdV1MsNGyK83Hcn93t+5CJ4GLeZ4j7MmTRx9+eLm96ObxmKfRrPQXV4GCoLRVu5MReQwaJfYBUYxh0KK1Wq1wCCiFyIzMyPP05u1RGCEEh+ecKdepukgYc8leipqbqilLaBNBRW05w4YqYCUUn07Za5lzzU4p9hISSMS9VlVndmjqsbnEagUOnKvWqTx6dHV3nOZ5EtmoSehwOGLdVdNaci5mNaMorgXDIH0v01RqKSx936dcijZmjSCIuHIx0hrzbAybUnatQvL46ZVXe3tzYsgQB1be3Z5+8IMfv351byWEuLp4lO98shk4ZiQgAhHYGFZepOZcd4e7cRpjlxITXOLVk3Kc66maVfFAzDF1IXYOVRNiwDRP2vWJLdZcD/M05dN4ell4/OZXf/3Jkw8uLq6+eP3y0y8+99uCNeCwybLOqOhS6LvVNJ+qlzZUu6NkpaqXfaI61dksO7mgKHvgyGYKELN7Cy6usGS4xgcfXVw+76WrNzdviDprkIqboY2kVLWysZPO1ac5j1OeTqhVzVhCWW3Cqu9EqMx+KiehXYxRYqFwrIJB3AzmalVV2YugLlNvIEGAazUzpvRg2S5Y8kSKFkV10SV0vElmBFhhuOBuzbEzkBIrgWotea5WLUgvHAIJOzTbuo9zLuLcxUhmmmnomIkzSGI4z6faaiA/0PUdsvCMm0G3PuyZncACYi7FRSgIIToxohCDxNyKn47TarW5uNyuEp9OBkPJM4hIE8ysFm6+FlWn2YSx3SIliUEWBqszMwWWWs3VU+DUSYjsXnPRq4vmpQe4UZOlqXmgRt4x09Wq6/uh6ZmZKaUoITADAdVqGmSKrNVChGwS3eU0RBfdHfeSeC65oATgNJ5OqxUAET6eTrc3N+zOLNM8v3r1+qef/vhLX/v6oyePNlfrw3Hcn45EHIJQCKzkzS5XUVEZcPd+1ZdSVdXcljvYnQgxBWeM83x3t7+6vtx0l3nOb2/vQgjD0DNTCCGmyCyHw3G/3+cyMwVTd7UQOtUyDMNq2EwHw+0dM3ddB4hWYJ4LcTt85xXasjppjFhvDYATMUgboaA17ksUEM4TxfJ3H/r/RS/+sME7L3twZtkT3lvwwN1Nz07eC9+h3XEmIRAtigkJ0iqlsbXuq3iBjgxIJ6Ksc6Vq7al7dQc4olulOEQO5GzCBKUQQgih2OKpRECQEEKIIUK9llrNyJpd9DKRvqMAvP8yF68bp3bOyNqLdcCgBGa35lbuUBYxUjewURBnCWAvtYLhMHVrHWCt1Zt5OwHsHoAAJU+r0K3jNE+l5lorCNIRxCAwNiumFdvVGpFLrc0RhYlc3MjAgSWGEEVzURXxGImgqy5Vs/v7nW1CFOm7IQ+jZFGvqhqT+eJ1veB7OP/j/WajEe8XcGD5Fzq7CZzpDQDayrxJAJsConkFtVb8DD85QOcMMnNDC9MyJmdpVqSNjOp+pq+TL017W3l7IKnm9V1cFLwU0tol6oMdJzy+xK9/68Nvf/1D+On29VgyVY3u20388p/8zZ/8wR/88Pf/r+/f3JQudkTc6BqN8AUiN6vVSQByhcHVVTFX95JP2gykRaTZjs2Yq9aSq9Ul60fgJOE8+9I7Uk8bVgGyd7b3zIuH6CJda40W7PxWk7uTGWKoJWOuXc/Xjx/fvrkpN92/+p9+kCf+7X/wzafD1//6hz/cvS7305vuEs+/+pWL68u4KqlPOtnji+en+2wat5unw/rRXHBzvOf+1VzmeRzrPMONqOv6rmbdHY7Msfo8Hce7t7vLi617nIthn3N2YYUQNVeTLkiwTOri86xgIJ69MZhIWv8INStaidBLclCZKjlbdXZiFyIWCgz20ChrzTn2PPe180LkLfWUARJvrP4FDnmAEZrKxs2NRcgrL9S3M1Su53NCS0PbgLaGIJyf9IObyAMU74udtrudMVm0vZOAAxMHZzJSc5elqqGUSnOpSqzk2aZcLMMzgoqYaFG4xxhBrl7czcViJ6XOpWZEQDDt62GcT7vqc+jMzclcObBlq0Xb3EFGBIL55ebaWOc61axi4Wp7XWXeTa+rlrlUEw0i5qZm0RCk49RvwuZiuOpTd/Pq1WCduhcqKSVKIfuca+YQutWwknTYHef5qJNpdQgoMOBVtWYdLtbU8nSZXHCmuzqFFirK1ka9ZqlohHOSVSMb4Uz2/aXx5wH0ae+0E85ZEPTwm2nDyEIHcYJwCHIeuxfxE85uWu7v/vkrHmeN78Pa5d2R+kU862Ho+/+DXr3/cogotButfakpFVu5HacpxTgMg4hYu4taPaDl3QQcAcRYwO8AsJM9oHRgNzhUVVjOdRoOVK1UGNnUlQNzi3GU5A2OcTNTbZF5ICsG1ba0AS8fFiEQIO3TzAwHmagXVKYITWSAsYPJhV1cyc1K9UJmd/kt2GWLIaZSSlFjkCQmIRFmsCAEqE61HAw7eLEqtUhlF0mo2cpc3ItHuCtzNCKiEFDNzUabNFer5WwgCJkhAHMXjRnDpk+rzqyMPitb6BLHUMmlAyLHVXJxOp7ADa/SPE+F/N/59advPrzzOz3dnSSAF4MmB0GI2/j7QB5/QFzb8qlWbWEoLMJCEDN21YXcJkSVnEkJxiJg1gXFpBTDNJ7+7d/89Nsf/Npv/dZvPP3H/+jP/+wvyi4TggOgClp8IBfIBsTtQjUmUo+t/zVDSxU1CHOUkEIIQQmm6u5eNbgxE7S9rAW4bUfo3RFfkhGWSnrGPJRbs8jMBAlMgaZcfPnJYAFzBFnlIkFiiEPfDykJcYroWBJ5EomMECBrmaZT18c6+26/e/HqxeNnlyXzzWd37FxKEYmllrv7eyKxUmutVs1dYQ4n1HBOh37YOWjLpXjobhus0+BtCg6GCBkHIotdBGKFpohpPgGU4nqzlbf3+/v7+5gS8Y4FVafm+pS6OPTD0A/7/WGe8/E05+zu4AAJFAIIXKtW9RA9BoohBvA8j3EOnXCM6Pv48cfhcMirbvXoclPruLu/O0zUr1bHXK62W0pdnU4vX78+7vLNzd2Tq+2KL24/v3/xye10VyARBrNaq5tr21XWkpcNzLvlKvgMUDV/FwdSSmbWGpaGRS5SC1+MHkIQd9FaF3W0tfAIpzMv3mEOdtOWItjU+gZvpLdfPDvvHqlLbt4EjETUspMaIbqxopci+35tNWs5n0TipA8frsW07OxWq80AAChqBIoxigg5lVKzVVWFUxP2NoANfjb0tSUFGk4t4vx8nzeaFy+mMrpEHzcFgVllIcAXzZFXEJGLUpVIRkAEg6BUneAhxB718Ed//LcffeXPLh5vvvaND920k+E3vvFtJr/Y/tlPP/viZj+liOtnibq51OnRZjuXqYwzB3s04NHF1bi7u3mF01Tf6s11l7718cdXv/kb+/Fwf9h9+vO/2a7W14+vrBRS+/xnLyVFFu67zpkkBmbZrLcSO3PKU51zLtNYpmzuZRzHE6cUiGCOcaJcMtEcY2iDfa5zjCYhri4uRPLucDodam2AdKvXEZJCCDyXkguq5WIlsgzbzXro+9R1QydCLKQWhMVh3RCfPFtsGkp1h/yP/+LfPHmMR1fXVxdPHj95/h/9x79bK169en0aT6rW5pfYyVh3FaN5Na9MpLXudvs+dENkX1sXh2EYSqm7u/m4q/NEApx4zPOJgfkwfvD8o//g3/9PBOnFp6//9E//zff/8mcXT65YVvv96XTarbrh+VeeB+li6EqpVUtKIQjnXMbTscxlrv83YW/Sa8m2nId9EbHWyszdnK6629/3LsnXkI+kJZumJUGQbAEyDA819MA/wT/BP8ADTwxPTcDwzDBge2IYhgFSpmiKokg9Nrp8/Xu3qVvtaXaTmWutiPBg5T5VVyThM6g6p+o0++ydGSvii6+ZGOo1j7e5zuXy4kEQqYIy65izFReJilpK8TrDFQwIRikkwqvASpqx32kl/M7/9L988sGTJ+8+Ortaffs73/i1X//mq9c3f/lvPx33dT5gf6MASinuziCtxYo6tJMUOE13cz7MNhsVZhKHmBY3baYrC+uE4QHrM/yd/+hX40CH+fbZ05ckWA89yNRVtTiUHRwlSFBnBQdJqyFI0L6DqY/TnQEUCLDxOLmFIGqKqeyZ8UvfevzRBzhe1+dPd69ellpALSjNHComzoFCs3mpNU/thHLyQM0a3bTaTKJdIu6oZFufsXd2doWPPvlkc7ZG0HF+lXX37MWh67BZYdVtLi6uNMeqeXdzp7V2AWfrzQ57ct8Mw3a1GW/3qAYjVzOtaHXJCeowWEtvXBAWWrbhaHFL992cq7u7cZAQQ+pEAogcZGruOV+/utlNr//hP/iHVxeXH3740Q8++xkMAs8lQ7sUZRhWWnIU4aFPYSayoQtJhMmjEHGiZonhtO5S33dD1xF7rXNVWq141cFAZa61GrFEkRjjsN7EfiVTNx524zjnMgl7SvFss+r7jgi3u931zYHCcLZdB+DwakfJU+TzDSjoWO5e3rzYjzf7aSylxi4Sh/Pt+jDvrc6H2/3ubvetb317++BKg9Rqf//v/eOzh5f7eV90qjUfD/uqlEv1Wlk6N65F4dLFxIRxGtXKrNNcCoyII6cgTKt1X/J83M2rC/6j7/9QOP7yt94nFuHEFIN0fT+krrvb791onmYW3vZn6/U6xa7Ofnu7e/nydRnL+cXV7nYGEGIKEo5jHo9zrRUgs8Ue475tAXDaxyxjwd/SktObLchb2orqygstubGQpOFj94NG24CfvoQJ7tW0sa4YtswZurAjnGGktuiGJJKDPVuIgYgMrkEtGUcQuUSwChETOKhUs9jx6nwFwVQmnTSElChQ4NAHJ1VTIgosKaYQuCW9t2nKHdyCU+4hhdOzY4uS5bSkPFEf2grH6SRxaU8iL72exJhVzdSyVTAzZUOpGQEwh6ABWDEl7gTJEd2jejIkl4HDOiDRPNepjmEVVuep75Jm9awUFyp5t+pBpG6kBDTllZdsxjXMMzgSYbPq1xtlzJqn7XDhJNfTXd5TmXwcS71FC0MJMUgQzWrNYsrJVUm5Ed++fhUsVp50ig9TVdjXP+fN57aXvEGSTduz1A1fVmhEoFrUW1iAtb8XpgUcrUdtfDwWZpFTILmzN46AmlWQi5CEZFFikO3ZKh8P1zf73/ju9j/8u998/53NYX+4fnHd9RfbywddevAXf/aL//F/+O//9//uR/gA27XEOMzZi1YnwCpJW7I3Z0hfVGmB3KBqJaPMypTR/NmX5bjXWrRkIktdSwAwPs290rKpmkDzxMpv67zFIN+95WI29nybaE4+yNyuyGasHyMYERqQfffK88+R3h+ezuV3/pvf/Z3Pf/e//d3/8rf+/j/t8OSf/9n/vLl6Mh7jZ88+P5Td+eXDq8uLx0/e+/nd0+df3Tw3jUMuVUbdF85znqbjocxzH+N6s573s7rHGKepHF69Vic1K67sDXHzFirlisDEzCIEIlZQImR0KfbrVVU97o+u5u7X19e0xHaKVZ21eHEbHeVUdYDQ8uaJiMVC845rltUnIURLBWz3TRBqhsm6NMPkxN6gUIW5uVevQycwMZi0WEB3KBEJd5GFxaXWWnP2YjiZNTGWxphEcOLaLNtaakSuRaLmDmIQGwQsAnKDqylq9SokYIcrSql5Ns5+2I/j3YwRyJSI61xIQSEAqFbnOjsjdFRRC+Hq4vL80bmBXj47Xn/xDEuoC6EA2QUqjMgwY3hgDa4ENYUWzLNljP46vArbrruS7dnZYdxjmtKQuq63YjZZ8j7kWIseb8fDV2OdynTYlW4uVgvb+qpsHmxBPo+llAxjiVKKGqgaCZN0QWGqhSJvt1sOYlUUubqaO2IjDXmgIBASmMAKmM3UtHozIl80mEzUQi8WQPye7XGPzJCDBGGpKS0i3aHVQh8WaKfNcOrunqsthcQWFl5Du98aaf82BAutirbj7Ot17K1lzEkTc//O/X/9ter3NZCrGcsEXmCjZTez+EmfqqqZEUhdT1ru5bEuesWG9nkzjvJWoYWk1eJGNIQZ2yL5YfZF1qWKZkjd4A2AKMCpujnDyIzcefHFahKAFvfaJI5qvlB/mOFM5q7m7QkvRbqsokjucDV1taViwIj81fFZDEkShwDLbNkBELsEcqpzUa2q1aREFIcSjMjZKkwLKmutviTZE4PJiF2YBBwV1Uwt10UOaosigMAEztmcEdSZ2cHVmKLETU9JCip3yYWqoK2wQWpm/apbr1a9rK+vr1fb4fLy8vbVTWQe+q7msRmH6Zs4klMPZARyMnY0yjobKTWjoCDayKSGdgErnMgVBDi7MsX2IjOTBIHbw94JqqX2sXuyvXp2uK1VifmEVuLEumnN1b0I0IjIaLHNX9hG5Na4UoEYbgQoJBK7sFMzi21yQaMlLhhYtol+UoWddout+2mVEMS+aLUZm20HDiUjFxOJoWNVxVTc3N9gFDQk6fqYRGKQwMRkJJ7znGKfBtYaKfDZ2eZzuylmEWTwLgh5VDUUdW0EW174bU1B6s3mwBt86uSoi+UBe0udBULwtpCn+5QKM6sOIXifZHsWp7mJrzymOKxW5B4kmJuW6u4sCIFSJ13PMUqZMY103PuUkQT9po8hhuAhCJPCc5BuGGIyJ9XqeZqPLqymImDh8/N1ir1EZ+F+QMlZDcN2PZyd7/aH17e7JEk4lMk2cb2JF8edvnj6Kt/N7Kn58qo53KhpmU+eaA1Bcsd91kljruJ+7dyyM3nx7Vi+2P20PCVmMm7WDgvc39icsGXN3eq1NZ4eLxV64bXS0gO9Xf4cTW1wvxE9lULCwkX3N7hX+7lLJb+HU/1r344WxezpuwNozSVL6zBVrRbVUuFCDWdbhpZ2Ey4/cSGB+RKIcardpz+1xV40YhVOJ5Wd2MD3P11wmoYW2xQAHEqxMueeB46p6+L3/+JH//5v/ea3v/OdY7nbDJvnz54G4O/+xq8N6/SH//oHRafVdpvdnn+VgUNV26xTlxKFMU95d3s3H6AZFx0enl+89/Dh0Pepo1x2x92hdiFwNx/n3f7u9uZue7Ht171CS60s6JL0nYiQVjfSbOqlNH+AalbnwsDQdzEO1/ta1MyrE3GgQKxGZSp9F7q+D9I7R8eI3FjV4EASOUQJgWTgVDLBRBjsJNFAuWY71uaGQ8ROnnN1d2FxkFZXrQ6+eoDq6e5QQpr68cAcrl9fv3r1/PZ2V9S26361WvWrLq5IYiIgpbUr3JqttQ9d1yxbasFhX+5upsNNcfN+CEn6kFiYP/7g43cfvz/t7M//9Ps//KtfHHblydWH1+NN6PtuwDjtC9ATGyF7PupxnA6cPUQuJeusqExkIRJctRhX7F+/6niIHCVKVq9BQUZikchCMAXYIZ5S13UrBBet1RUmAV0UHg/l+vqaU5G+7A43U54++eX3n37x+kXd1arulYn79dpY58PRplJUKXDs4v52n6diBSimVlEAGAKDoKVqMUSEHhfn4cGTsw8+fPfm+PzmWBTl4vzMCwmDGDEE8wjWhbK1OOZUU4Ix3IhYQgxk62GzWvWux5I1xd7JdvsbIr28HC42F4fg+ajj/o6yV20thQBu1Qxii9SGfG6ZyEREIkRMxCQsDjeqBoegX9ujD86v3tk+fvfSoHf73d3h+e4wrVeICat1d7baMPrdtZY6uZrWMqTYwmq0lLG65mIKmPddR84528yVhNQNjcfUlPLqrSlsYyXRfbeAxSGbici7vmtsdGg7WxVAAM1HO15jOs7DMDx89OCL55+Z+nq9inNOSWIM3ap7dv2y61LXpaEXQFk8BEpBWuxzYIQQQwh97Pou9kMHWCleqjsocAdwiVUVURKzGCVmGWI/rPqz9SqXyV1rmeZ8ePHiVYi0WvV9Hx4/efT0ZRlWHapansRBiu0aacVgzWW8Pd6UWmupFV0ahtgFEalVQXS2PWtn9Kvnr7569lWK6eWLV693LzeXfbUiIq/vdqU4wO0ZXtASJ0ZzSh7V66Int9KcEdzNJsUMIcHBxn3Z7w9nm2G9PiOSUkrOWjUL8zhP5hZjBKjWEqTTit3d+PLlbAWgnYPPN5u+H0ipllJLASiG4PleDvqm0fYlT29Bbtpapp1ub2+z1LSZLLx1sLxlFns6Bk5783tY7BS3tHzgDriejLXaV8mJueVmSualyccaaOUFhStHsJALCrIZIVlIAQ4yEpbIQSRAwJGNtIK1VmbMeWaKIQYCaq3UcjKZVdXUrdQFQFuAA7L73/ftkxhf+wVAQEv4aSxmhjMToRlz8mkNSEwwbkShqtWgRooEMVJ2EJoarnpFrQp3RiBQwGo7THn0iqKzOoY+rDeDMB9qyVaqQeApCgdyJw7EJIGo5S26u5Y6TpNRQPQhSRCtOp0FcdWOV5ebd1GDltwwJVqUfKSqi43Z0kXQou30t7ogIn5rinvzjv8N/HGitzgUJ+q6vf35vmB5rvV+JljQsbYTQ/NxX4z2HNYESa1LqzA4ylwUigCJTCE4szCOu/317SF1+Hu//Rvf+84762R318fPP3v5jY/flf7qz7//9H/7X3//yy/uVt9GLbzbe4RTIGJhYKqTQFsYNUtLpjE0wyRpmRaAoe/7MlvNuY1XIQQiaqCVCLt5UThUwE5kp+v8vlvy1lH5qTfz1iAuE0T7Dam5US+dIntzEi/FyYgSU6S5Sw/eryPX68PZg8u77vr//j/+tVt9/5uP/8k/+mff/8mf/ujHX7z/yYfTXffpp88eXD375rvf2e3nzz5/dnuDvt+vt4+RisfJXWvGPJYy1VqcCBzEKWgtVd2YiYPp5AYzTiGshqHmMlstpTaRhpbZvHJCN3CMUWJwJklSqzPxYTymEK0tO6urOymTi2ttnBpTUyJ1g5HXZYYiIZbAJ0NIGJbw+oWGwwQyAVmjri7/cbplDXA1a2SIxlZeOHu0XJsggp/8N05Xc/tRi4H4W6WMiQiCRRV7irwhQIBoLG7esk25lYIWEw+iQIECM4DZsJ8ZDEOUCGreUFDOEDjDGRwwrPvjPIEwz0WNj4cKSyTBrbKBzd0qmbcMcSZ2EnKBMdTKoZqARaxWP9b97VFjwKZUVw5IfYxBSnU1h5kXL1Mth1p2te4LCo77zIG45/F2H7u0Ot9uN3F3d1ey3k67cX+wohKCMFdTUwXQdcP55cVhOvji+0Ms3ChMHNqLxHTSbyzyJpQWubcA2bSEQvz1N3enNgGBCM274DToLPa7i915+9DcYU3d3ATKy6b9pI97U83fHp2W+xIEguvJyv3r4NQ9FOV//XS4f6h/exChn4SARBSYxJhgTXtCRORmxBRCIKY5z00DqKyNKt10Lq0sdqlreVq6EChazTQSNjM1LGaCDiIwSwjeFECNieHVa63tCzkYmJwBJmcDK8AuQnZCD5nYheHqtXGNF2q1u7l5MA7cbv0yFUvOglrUXd2qkzY9vwSCwIMisEBiQOgjOcFcQoRTyVndJAgBZLRgxWCoa1Gro7o6GcICIjPxSWy8HAPs3FzqKk54DgA4J1a1qZjlkr24VxfOtc5WzHLDvbPWYb1+aFeH442qunlIMYa0P+6fPH7cH7uf/einpZiltjJZ2FZ+6npw2lwttIxGDGzhMNQ65Wbp9qZ/IFmuzeafbu0RE4iDcCMt8avXr54//+ob733yvV/9ziZ98Vef/TxJBNypavNFe7NGa4iAObxpBpcNJJFTS1SGeS2LhNpZICBxMnMzd7Snkl0b4X45f7RNqsLu/PZFzQIOp2uMlps3z0rBa4EVJ7ApiKwb0PUxJQ6RJSBFmrK6EjHFmEIEBzIwdxRFZM1n64sHl48Sb8Z8DMLColZVzesSg936PCi8Nrp3E0o2be2CadBi4eAgJ19UnbpMUcvrQiBpfCIrJnp5tn70+AzkWadxAgd/9OSBs4YkYCvFCIGQmdCs63OZiSLMzcirm0Cki5Jioi4yx6qahUUaPwluRfM8KTBOtt+PxyMeXF0E8fF4EKqrIc5cUr++evAwBP6zP/+ru7vjb/7qd1Nkrbbers+6bXl+mO7mJEOeJjixMDOpmlrByWb8Tft9eqnotOlphe3NRbPw0bAs0N4spL0VKWZu0SdL/04nFGxp6JeG7vQNWrVpEOrb1W95701IhRMzMQvRgsUvbhJN1ur3J++pGsOFWN+gWd5ygltVN39zYkiIFJhApqbVtBoq4NZgKmJu1k0tUAE4gXlopzhR6+xsydK5l9Qu0N5yDDRSPHOT55KhmcefPmW5cwhM6CXOozu5ZadN/KufvvzTP/7Bkw8efPJLH5AHMR5SQtVPPvyAuX/2+u4ua78qZ2v7+WfPjeDIWtkdXmuK8vEHj7ZDfO/J+ZNHD4Ulz5NZ7gcRXjHj9ub29vpatdzeVZf9WOaplKmW1TrqUMo0d6kHeJ51zlpy0WqSkqnNcza1KCGI39yOTc6vqgbrU+j7GEJwMEFS37NEljiNVSHNtKGpSIx0u9rCKxPIrOZ5zl7KTDoDxsx9n1LXiZlIUNU5NwNHVtOTyo9rAAAgAElEQVSqKmE9jSXXkSXEmM4vNoY5RIgAjsBwK2XW2ZU6X/V9l3ozzOM8HWcmCSHBKc+a53LYzfu7PB2RIvp+ePTgUZfC+fayD8Nxp3/xr/78pz94+vLFXUprL2Qh1akSx5i642Eca91uNqv1an3ehxXt9jfZC0WwsjXg0uCVvIIciYKVnItagZYGpJurchQhsaqAM1HRrNr3se9JZy/Vap7nlLbHwzxN8/5ufDgO54+7dRxqzZeXZ+erh5eraX9bdnfTPGcSTymSCAoEQoDWEjlIJyZkxbWlhpAKwxRO2G7S1Ttnl483j9+/yDq+vn11N1671MN+8rLE13CwfpDtZpu6pI6ca551HMs4TfNYc7a+72KXiDzGLoQhRINZTAlQNdR63B9nDUbYPHp8vl5t7l7nV893r19PnhUGVKvNYcpNy30ELy1zH5GTVS/qdejo4uFme7b51nc/+uCXH7gcb/e3++Nd7OqD7uzsoi/1hhiRyUxFvF+l1J1V7XZ3NyIyTqMW1ZrdVZi7CBGJIVT2Mh1UHXpSIDewYqFtMhOzN5qNL55HLdBBRERIiEVymXRSwDigDyBmEekZh6mKBFOrs46j9in0XWqSnKzq5mQ8zZlmxOBd4phiFIbbPNZpypGw2a77bU9EpRRARZrGzUspRBQCM0etCCFqtTzPd3s1IzhCQNdz36cQ2KH7rF4tzzkIJaEQKdex1okDBM5k3Qoc3VyrlZv9DbOUUvoofaDYp9RHn6qIdF3q+2G9Xv/siy8P+8Pr29sa6TAeD3UXUnT24760paWOM1wAdqu1EJiFaJoLB4Qg6m7VqmV3OWrWWmVNpRoCXrx8cXYZL7dnlxdXIM1lGsfxOB4l8H5/NIUaDuOcZDrbUpnpeJisIATAKXUpSs8UpsNsbixtIdti2tpxhZMSY+nV/aQMW/K27nd9yxzgpmhSqPuF8+mUIwDqRk6LJ/r9Euh0IJktcR6n7s/eyCOYfLGgXRR5ANBGMyJyWj9cgcGBQa6mpcy5WuwoxY6IoCQSUjd0fTeOx/1u5+zVtVa1MruHGESCgMiZoMZEqmqlqqqrmbkIWjxZEyf5vS3OYneFN2d0axqXDgBYyEJ+6mcJ6sRk5p4zRcQUOcDYTCsZOCB1LJUhjeaoC70npn6Q7iwNl0N3Fj3a8+unRjQMKSaJMW62qxBEa81DQcmiMcWuRe8wcYzR2aq7qYEJ6lq11ELsBtdqQ9edbVfTYU7x/NHVu4drmg4HV0DQzCnVqigzM6ilry1GFy2R+55p3noTWjhCDlq+vG183x4JF9CP/PRE4dSG3ntlnaqbA97QQGYSZ1k2Xm00aEh6++LGDCDh1oC4u1utWHy00Ajg1VRJ/JP3t++8Q//eb3x3Onzx7PXrcly9+/h7+dj/wZ/88F/+wY//5N987nOY5sBoscDi8Gk8wJVTg9nUTh3dEo1Yvd0CbTapczVrlg5wmKm2XqdN2GROgIh4C9K0UxsHuKMZNN9fYUQQFiFuDAycHKb55Jxz39uZa5+GkivU1G08jBeX7x7vjmm4vLt+BcEf/96Pd9eHf/Zf/MePv/3Bo6s90pm4dSGfn51rzV9++erZs91XX06vnnsM1+szkaHScLfddoHFCuc8z4d5WG3APpfJmdLQe+B5nvmE7RI16Q8R0zDErk8SJM/V4ZSITXKt5biXIHFIkfoY4/54MOXmUsOBh9SLh3L07JO7k7NCyalWtWrQlonObRDAybvovpVt61ujFnlxvzlt6ULeqLrNhrjW0grWQuqhNpZTa1fZAfjSY5ufRJtLRTutiE+ItXOzJGvkw3sfbpe2FXYwuGX5Bjhps/hmd5HQpV4Kz7sDgMCSS3UgiNRcq9aQWCKFQErOnUvCkFLXhXmeXt1NpIKhRyWYNdqyLctjN4DdmZkhBLbF15w5cRa3ovNu0o5SdOlkter7fvDqec7Tfp5y4YPUG8WRuMYkXUBSL92q8572+XC8PkCCBCGRlBJV5Clzx1TZszNRiAkRw3qIsSv7WwcJRwqnGAxyEm7Z7uTEAnK0amunW7vhUbQ4LJ4QorfmGD+BTwDBmoyrTVFog0zJBS1eGYtzHAOyJI+1PZsvSPjp/nkzI7Uvo3tEc/kQ9wPMW9Sqe3zKT+TTr01rf5OQsEFP/w6kxcwhdit2WzLArZ6mTzcojIxNmGOITEweodbOWG4jYKvNDjLyxZUeFUrNfUBCg3gCB5B5NVNvGW7GFkN0N9Ul9tG8AktjB6YQEzWffqtNtu1N5cMgilazM5gXzKCxulpsHpjqVJpBjsE9mAe14BAQsRNBXFKMMVmx6ubqTBJCQLPZQWKvpgCZJyDBvSoaC01LrmAi8eUFr1aoKmuCwEldwZCYiBymvPicEZOAkIJoNIeXsVZRRAB6PO6dzFRJEQOqz+Fsc3l5Zl5u726EYiC9e/Xy8dk7V1eXYSeIwIzxJptDxDkwAaXWRTvljCaYJXIiJaqEIQEtW9EXA9F2FrIQmB1G7iwEJhOXk1cfE3EMs5fbaVy9fpGuuo9+5eO/8w++c5hvnl7Hac59Fw9Hh0MiwUmtJaGg6QI5oIupNg7fCR5gFgg5jNgh6mpGRDGwU520QjmxENdiiGgSUmqHnlcjdgYHZkhd0gpA4ghudMqhMhf3UQsUNoGoV4HVHJJvNrh8mK4edenzebulfqXHiow6a9uIi5NJDKaqsNh1m9U6rSQS0uDMtc4moDxOUlkkmDo7scLUYOa1ZXPMIPZFantic/OCpxgv6Ao5Fl8FI2ol2Z2ERKqFujnrP/rwg914PWeAEZLH6BJBXFInmqQWK3Go1VBrNYgg9hzUOqPUhZT6fkgxhpRIgju0iwab85wLnGHEAopWkI95OrhlolLYzctkZMEsYLjYXkVZv375/LMvjwQIRxLNFReX/QBxrTjCZWmHsLjzN+Nca5tTYjdtqB41WegCuS/9cyMGNhtIB9AyMwCc4k7MGujZ+hcssYNGSr5QM3Dy01iUg/ciaCyDhKOlCSz9Ci3NkBC8hV6SExkTO7c8bG/5e2R6L8pHIzo3GNu1IUIOEHHj2zf/CAqnZXcr8m5W1W1hWziYUJd+y+2eoQacHAKxMP2XPp8aXY+8+eVwDK3rbR6ZjR5MLMICQNpDYTailisOa8+sO9zYQBXs7roeunGafMIf/dGfPHi4+fCd9yL69x6+s59ff/niM675ycPV9qK/GXM1lrA6H0KUrtRpvR5ix+89uHywSW7j+XYYhlimw/72ukvhmI8Vtup7K0pahKBEBdAoWe12X1ok4vE4dSn2nQF8dn5VpzsKEkMsWqc5j6POsxJkRWmelSQAZhOIIVT7LnYxSgitYsXIXWIzN67E4ual1PZmQ3fyuGiWD06OgIHIrepxhKoPPVOAG7mRq7mZqbnBrfaJzH2erl9fTyE+3m5ikO1qYG+BV87TPB9eHyXacJnCunWWuc5HhnQ9aaFxNPUOWCuqdN5tqNvE84eXj67eQY3PP7/92Q+/+sN/8f1pj02XvB/zdOwue+54CHG46r/S5wg+6UHcuv4sRplvK2aLQyIGWM3YG5m4tqpO5gvBXxcjC5iTToWELSgIFtCfddiY9hXelguOQNW8TpjL+OLl4asb/PpvfHT54Hw67JhCv0of/8rZ4S5//vMvxv1c5jzNITJzYq9ai4M9DYlXotnmcdZco1sUzUdVxcfffnDxcNudy+XjMyT9xec/vxlfIVrqOrAed2MzBiSCedxsNkE6NjdCcXVV06JaHZjmcb0+d8OcpeR6czOebc6ZQ0oUE82z1XI4lEPHFDfD2Yql527TP3p3ddgVnTEfMB1LzlYL3CwM3LIRiJ1YK4PEtuf92cVFt5WrR9vN+XD2ziqswzjb7rgvOq+3fUzdNB+Ox5aQpVry0PXdqhPv8sxQPYz7UkoIzEGJaHPWzblMc6Fa5lp2u/F+TFg6SaEFKFK4Gd3bWp/qAjmYnMlBlA9TpdqOKHMUhpCFGELgQ6jMKsGm+aAFSLWWTM7zVFXdDhl9GsdJS+aA7SaE1EuQOue727rfY5Xg7jWXEIuIpi52nRBTzmV/2D9+/LCaEnE/dA7aH2+vb+bbu5orxgwRnG/D2dmq6yJx3G4vhAyoWjx7PuyPrgjGQ0fj9bw938JAwbPl28OdCo7TDEIMLn2QyHPJbEQkpXitlCc97I9ffPX5y/3d1TsP7443iJq0VxRknF0NZbJJxCuYiKXTubhrWoWSc9+viGmcJihSLxIolwLSYRgACI9fvrp5cHG5/s5F1/VTPsx5khA4xP1hnGYnsBabDrVS7VJ2lcNxih2GJCnFruu6OMxzPR73c87STrxaFj370oO0rWEzaPAlG7wpdczZ5J6hvrTzimZh+macBIjv3Y2Xo4uwbGewNDru7sThrf053qBXAOBCCNyikmHiClMCCVMgEvJEKcVIoeZSjqXO6o26VoqI1GKFLcSeqo657OuJvRWShHgYZ/MSSEio7UuKqpZqRb06OZghIointrxFjrCbukHvvZVwchVotsHteWt4RFvJLubQC7GIyD3EGJjI3aoJIQRmgTtMVRJYPTBLPyAKBwo9pxS72PUhUfKz/vzueJePGnobhiFGYqFh1bHSXTlMe1WtcLZq1ZUE6kVNXRxGUJCo1kkbXW/FfVrDY5f6Lz57/dGTh1B98ex1mRQVRCRtqaXVTJ3fIHZYJAt+Il81tc9ijwDAoK1BpNaf25vS0OqHh0adwWKj4e7Srglecse9TeQMJzT8EwbA2NC+OTf4wIngYBZq/oZt4jQinbrQb8p8oED9SvbjvlthvfZvffuD//Q/+e397nZ3/Vqn6Wr7nXF//vu/98e/9//8/s8/R3DAK1yIHW55ruaVWkNmrfujFnpnaosu1Jdrtl3qaovgrF0V3ubKRpfQ5XIgQM1PgYkOgi/5y9TMFsiWxaWf7qCWc0c4rSdJyWWxoHZnRqnVAGIlZx5Q/Nb4eJxqCBVMX/74+OVXP4nU/wf/9LtPvv3+k1/64N98+oeq9cPHT0r1f/UvP3321fh6p3cTtN7Q7YGidWu6uto8frQZ+rPr/fNaa2QIp/FY5zpuLrjfRngx+CkyIVKy6nmuWA+e1mFYd4eZc64exVSzFhQECqvNJsZYizbihgRaDwMzUgiCEFxhXGtlRwzs1bwauWlzLHIlGMiNKzXXdAHcxeHqbi1Zi0DkYpTcm8EdW6AgAMCOcCjTycHDA0kKEYELXGuF2uLF3rAPbXgUw1vSFphKgw7cYa6+xIpRi3VzwJlMQJEQuZIB2RvBJrK7EvfqWYvSPG8ebuttPoHhFgKrVUAtKDE8QoORMLFmgfv03gePBcPTL1/hOHab7TQXL2BHG0JIQNLuKYK1qV2ZWhaNTF6hxlFsMj/k83cupXNEPLq8mvKULZOhFsdccCjIzFU0q2Y7W632x7lMlaOQcJ6naF1RFLYHD660auF5fH2sJQPOTP1mlfpEQvu7XRnLol0xcnO3pt9oN43dC9SM28arqSt9sfUNTVu6cFkAasVicdo7bQ3cqluDJRug0zDENxIa5jaQePXqIDSX+BPFkU4l+017c2phCNyS+NzcUNpUpar3OBS+/vY3Mq3+NlrW2++rqrsHA5oR+HK0kEOAACMwGxFIzNkCgpmrt9i0xT+vNZpmttgtn34XgjMLMzfLMThMobXhYw5yKMWBq3qzMj+VsfancdN1CTvAErTtQGC1Wiv77dpzMj6xHJsq0bmNi+ZCVpqq3E/2ceREFUYgNdTqmq3OasUVqqQi0ZxyVjMwCwTeKUq70z06GXPVUydhIHUnUq8gc48sbRXWKCDt1SVmJmGhwERi4MgKM3VhKLOT1lqEIQ4CWGE5lzlLF7RqmZCTT2K3u33Um5uLG4deXax285hnk2aXT02aqtQQE0bTKemygaEmbW+SQXJtt8Gie2KGLISZhbohEPEGt4bIoZO70Y1xo/vPXj/92fOffPLuu08+Pn/39eWzp8+Jq7KJMAVyJ3IhRwsGslqZ2QW8xBJCfeGUg8hISUCJUMwJFIQIMBN3YSHwPQ+edAFKnOBk2rJphNBuKEZr4dpLbwYmrdXAcAOC9KuzEKP5nuL4wXvvvffBlcSZw9j1utoYEk9qEjR0DjbVisCqKi0BWhxSY0ePnlwdb+9e7u/62Jeamz0JKXyh5pIXQlM0BMcimQzszkvnsgA85O582v8Di+ZtQejauOJdh2Gdzi/OjvM+Jbij61n9aMWIa9+t+p40hAk+aS3V1Y1Zeeg6EKceSIETOTtKKUpkoJFCXWoLwZjIWNzFhT0mKl10nadehiHEaToCeHDx8Origbkd7sbjAe89gWKscyVB13HZj/M0AShVhZZJrEE/zWYNb8VDtO7VyO0Ul30SQTjx8g/sjtMHAMBLOsR9h7+058thRS35qFFEm807sKid72vbCUm6X/AuuyKHNzC1cejc0PwPyZlB6iASApFr66nJhZuZMrGRV9UFXEJzXwBAbkqnzFoAINfGnLyP1GwLjiV49a1Bdfmd6XQaAK2/Awla+OBSD70lX+Mel8PC2mpzjzvbyQKvrRFAUF5WrEApc4ghJnE3VzvbpN3dzWc/+fLLnz373q9/VBGF6ysO+Xh3u7+L681H7z26evSOe3y0vkyxK2UaVh2zf/jhu+a5lGnOh93u5sXN9f64S0k4eNcxR4J7YKQoSNxv57QeDlmLTwDc+qmUaa5FKXUdOFBI4iQSLGeMMwhmGMdc/bBZb5xhWuY5W7NQab7DVYsvylzTDJpa31PNS61ldq3YXd80NKpxzkVClMCxE2G3WnUuxYK4lmpm7QlxBawFBucUojmVijmPZd5thsvuYui7UKu9fnWTc52nUkZjRdAULZoamwsBXuCq6nnO1aRakJDSYKuzdH51vjrbOIcXz3ef/tsvP/vRq+kaDPaIMmfVWql022F9sd4+2BpVE91Nx+O809sCkr7rMnKtimItgd1ZOAIs5FwrYgpdz2xqWsjcjMaqtaUuE2TNmweb7qzj6AVlqsfZsgEIGA9zH/shrmZM01398ifXNsb12da0qM6Vps1Z/yvfffLiqXz1+bPbuzoXgNERBFhtt0OK5HzY73LeawfNyDsgYfUI3/rV9y6enPdn3Yvr509ff74frzVgNaTNtlttVmUcGVRru7vrPFdgVNVpnHLJcHQRbvACNQ+Jp4Pu7iYtdnO9Z3TufQwphGjeGYqVWmgk1hDi9oFsrway8PjBR2Xiv/z+T//8B59jDzBwEeqLugyEopYABgZcfbD98KP3H7/7oN8Gg07z8Uc/+9lxvCvlMKwiiEIIa9mamSnnac5emUqIxY3qXAOHGMNmLRJC15OZp54ksc25WOUY4jqWqSy3op5ycojA7HN1B4kI3MzwFkLh2vA9lFIogsOJUg0YgwJxJ5sA86I6psGuHgKGPGeRJNxp0VJqNi2nKnSYjO7GlIKrlmwMuMl0pOmYOXpMtR/QZSO2UvM4Ilcq1WKMKUYh5hhZKlBb1shUcHNXD8fd+fl6e9av15tVHyJDyGPHP/n8hyGgj2kVonY5Jd6uH/VDMsd+PoKDi4aQYpdiHxsJnYugQudshtu7u+vXt1989YvRyvrRkHWUKMSWuoiB+lVPVr1qcSUlYXKoehUwgYVC6/NAEIawCKuaoVmKK1CgmYIMIuKkIcXVeh27fp59tVpp9VnnxMW8lDmLpPU6Vi2BhIj6voshlFKYqUssElStqC7kmbZOaXsSnEo9TlbHcHYhpfvZehHavLEbWbryNum/6dQXNtb9P/j9Kns5Hdo/LtK15sJ8/0iMmhWKq5EZAWwsQRId94e6Sn3qYU5uzdpRC1QrQgVjFu3mQhKcY4idCJGQREl9d5jGQlXN2gRo5jA1V7QeVBv/hY1hUk2XYNzWo1tz5qJlh9+29IvLORq+cKISMCC+vHM6+V3Nq1rrZSKlGDqJJlCqQVWUA0dKQ2UGm5lNx6p+OE7HfiOBpBO5Pc6s2J5ls2xG3Jphs6p1rJRay8YoXkrJTgjd0j0wwVRRpjJH9xRCTx5K9q+evn730izj5vbaCwFgl0BcrdRq6ss4tAx4pn5P1ab7mWdpVLTFOLQprAV/ncCm5kEOXujq3sgt5jA/mRC37v90mbTrwIE3hHgzqvfPefspCxuqOVSBABcWs2gaSwZHUjUn3xX89ie/+o/+8a89eefix5/+yaYLm9V7n/9i94O/eP7//sGnL7+CFMQom7Pt61c3J+AI3NotYsfikkAL3go3kNMyG5yua4F4SyZwB5hP7BAsVEaCN1ekE6Dnb26Q089EY2q5O7mqW9MJ4uQH9MbPojVc5I5QtfV7ymScuPhrGYxKqbPBfOilTPpHv/upp/ib9Mv/5D//rV90P7bDcZvOVw8v/q//84dCKcbtZot5snksZeZq7DYJ8aPLBGPUWEZ4ZNJU5uN+d+CQJLm6GTlHTrGTZPvtsThC5xwdwRCcnAOH7AqvAEwcAQYd56OqsWtkksRROAZmB4w6Z85EbgxBda/Qgkq2SMygbTPqC9+J2pIUgka7exPD18ALAOTiFprKlCCVndnaMweQMoQcFXzP7TN3a0oK8rZf5oWFybJclW065pOe1BZHNiMDuRCMHdR8ar1lFnQpgkWVTE3DkcWc6oJUsHGSlsHdrNCpcxOomAuUEVdYX3Z1xGz7ZjoMr4QmtCM09UQTPzaFg6s7jJyZs6uhLihz9V7ixfYsbmWfd13saq5Kyh6gTdxPIQSJAc7kXvIEaDalwpYcHXHHiAhw6pzFqbPaT+0JV0W22bPXWnPJzRCnpaV5g/p0GYuMFN4Wr/dzxPL4GS2kkIwWIKdV07axpwXNarJh2Ml7c5lPaQEU78GY5QtODDWA2qFFttyU0u6rZUxD8KCNr8Jt4F0cHln4be7Vv/PWkPx7eOv/9+3tg1BVVTWo5eY8ATdQ85EjSU12RIrGOCU1c7NaK+B0ig+4P0zfrsntMd3/GLNG7lp+O2Axd0RLRdYlz/PUnbUnGUwsLiBwEEOoKKhuCnM1VMhS3K05kQLemHSLyghQWD7dS8zMJLaY59eqrlOmrEXr7KiAAl7ioO5UxxlAGAYSQnQZhCM6dNGCSZ2nTIAZ3KDV4bU1iDkXikhpIEfOpXgFtVBhkhbGyK6qzst2BKAAckN1ZaaYQiQiA9SmaSwlj9MegLnlnLXo519+IbN88PD9jz7+5o/vflSm2R3GqKpa1QpigNP9taVvLlRy1QWDJ2lBm6fjZTm2iBjUzHcDNS2xM8UUQ5AuJWc+zPvPPr/ryL7xzn/27e/+MpA82IuXr5DRrwMJz8UYJBSZpBSmIkxBawZBHb4oCtmogsExILAwQjQ3dXcj5xQCMVMgQwImy6RYFL/Eblbdmp8LwnKNiCBEISGrXl1VoQaYIwIK4jQMvQSesu9K/vCdjx6/8/CLLz5XzcMqfvTxeze76TBO2ScCTWMec3XCeoD07lrn8ZCk23T60fsf6qubl5/fmSiUGLCqcIYCTRuicAUM3C3TB1tpTHA2PUXKLRMINRuERtRywNCCUVOS/awfXj149PhhSsncnjx5PI2ZGFq11KMEpMgpDiGIiFIzbm3GLUapS6tVR5RqxXF3mOfJfOqVRWq63+IyLbI5EuGQErruuOq28zyHkGKgeRrPNleffPJJ6lbPXz6vZRbHu08eMPz167vNgMTpi6cvXz67hgFmEuIpK2cpK83uq5GU7C1Imt/WR/z1CvZWLcMJtPpawTqhNgsfefmPJuGneybq18oc7ucIAI0bCrh7OOVFuXs7H9oxeXqQzQH3BME1UGn5ht5kUr48jGXPd6p1y5/MWtxP2datrBGRsyybkHaoNGVHOz8awtm4XoA36z9ZfnlgMcW7x7ruf9nW9pOaA2RU2Y29vdAt8WcZcBwhBGY6HMbUJ4np2dP8z//FH8+6/6+/9V8VK7XYt37p2+9/9N4Pf/ajXzx/mne7sesOh/LJ+98I0jmpBBrH47i/u7l99fPPf3q7f30c9+bKQkOf1psuhh4mZlUNMcZu6GeitFpVyqv1kOKw6da16lxzl7rt+RlztznrVLWUUuwgsQyhY+Jays3d7vLxQ2fSKqNYqSUKByZXVas1q3MGeZmzerEKNWiFVtcCVez3k1Y0YU5KslqxkJdScnGHCpkqcp4Y5I39a07gwEIiq26IXVStx6O5mWp1tygprtM45mk83t3WnEHA0EPa8djit9IabDHxNM374/542Hvtc6kXq7NHl1dXl5dlqj/5+U8//dNf/OWnL3ALgFlCLZ5zdWDa16nu1qszQezDcNBDlOgOAbMIR7aiecyoOE3ETCxMQk71OFfMbo6lQ0UIFLu4PltR4KmOaZUePrwK6zjpVMadam3kwhS4aIVUEiYjTHj6xc6yf/yNd4dN6rr05dOfy4Pzy6sHjy+/9b3vfm8YNq7+7MvnP/z0J/8fZW/WZFmSnId97h5xlrvlWktX98w0ZgaEQIqUYFoAASaYSKPwJuoP6Vm/Qj9AoslkMj3IJBpllIkvICgJgEiQAIiZQc90d+1ZmXc5S0S4ux7i3KxqYIxmvA/ZVdmZWfeevMfD/fNvefPNfj6m5sq7PqxF+21zebG5vbp6en27XnUUmRvcHe5ev/364vZiffv5/anfj/uscy7jNKoDxZ0CYgz9qoOgoBQrQxrcdbu9cG9wHDEnYm771cOHu/uHh5IxDTjNb3bbcDn0q7WwaJ3BnDTbDLE2doEEhpdvf7Jqr/6z//w/+Pu/9/fIW1MRhDKVnHLKyR0cWFoZ5+Gbb7/Oefr229dvP7wNDcZpfPX+fpwQW1xfYneBJzcXLz6/bWLnfZXUmWs+DQ+euczWNmG7uZJ4VVXRabYQNDSROLlr23ZPn9+8fvvKFTovfgIcPbi7ggwiCGyVYcy1B16AdTd3lCJtECGHFjIYigEFIgbOBjhKzuX7P1dpWfoAACAASURBVPjeZrv56quvvv7mftNT162IoFryNFDbSmB4nkdL89Q26Bo0bdP1QYunlFWVi6eCMRlRYXYRSMCbtw/E3nU9qGmaVkLfdh6bOTbUEe9I0mzDWL59eewfjtMwbderKE6mJGgjNuuuCTF6uLwkKP3qj3/t9vbaVIdxyDnHEFfr1Waz3q7WIqLmmnKeynycvif86t3bn3/1zU++PsUWu+d7MwsWm9iht+vrSVjaNqAUy5NVuZiwEzl5qGG7xByYta6TlyKeczE1n2vkb/UGpSbGGELWENuubU9Ns55ndT3YSrXIPM+7i/X3v/+9h4d9STaNsxu0lJRSCKFpWiIeh2nWVIcHelwu/JXHx/OjYpLnzcLZ7eHxvKp/9cePy2eqozi5L6ST+mWEioHRxzOOKpRBqCxgwiKHOKcxCqGSfslZuqZr1xer7a5bM6SccpqnYTgdjqcQQr/eStt0605hSU1CMC8pzTolOjIi4MUUpg61SgVl5iBCxQsVIiGRmpvL9LjQqsolOr/eGpUFJif2KjGy8+QcI0NgDOdltwoHFKUUh0EA8SjNmU7mru4FJamBPM8qDLLsOdGEvSJgfSlXzy422zWCZ08ShIWZAoMf8ukwZQGVXIqWEEPbdwSqesCmiUoe+yBNl9KcEuZZc0ptiE2Qlz//ZjhEkQZaxj2w2OkykbipaeHwyEtYhkAyLC5M7mcy+kI743OnswykZ3Ho0iPx4/sZ7i5gq96yWFqK5Q94RLXqJxd9Yd0m0vn3UDVc1U4MQCCqT81c1Y+MXmLjxPu7cfeEnr3g3/m7/95uJ7/4+V988fyHnvif/dM/+Uf/2x99eIf7PcQgBCt2vB+gi6YVte1dVkmPGWQ1gtU+6dYer40zzmFivgiuz63Zx7Xfcg88XlNfptDHls/PHaNXD6TvPvy8BT3/hUDn9KnlghmBiEGFPSsEoe/SPBzu8Y//hz/+x7//x7/6q9//tS//ztvj9V9++6fH/fyTn+PFZREOMDGtga2xFP9wlz7c3+XPY9cIGcZTIRmdmClO08iHvLlYt01HUKbQtrHruWTv2tGMi42nIatNsQkxinHD0bUtUdqmCWnMaZrgKKRMkVmcqZpaUaDQiZJ5MYdLjGzcFCux5JQ1myuKO6IAWDCmxfIbgQxMCFTpogYnISYKdl5BuxsgMXhgIrg6imVLNfM1SAABuhg5LVr5enErWk0eg1RZirqxS5X4sLCannM/HUAhq5yHMyaggDfNWuuysa7FhRBIg6FdGK8SQr2fOBC1AlbHkkD65Zcv3Gn/cJgnQDAOA9SBsBCO6rzsBneuqjliX+QhNM5jXEdqyKkAuLzeXux2vKb3h3f04MzcxWakaQGwyL060AcSojxPzaZ11hnFCbJpVuvVky+epJRUs8QGtnl2c7PrdvMpHe/32UyLzfMcLe4/7IHAvAjEq7Vb5Y/DgeJa3BSkFa8SAMQiYDDOUqjz2QKASFgWZbK51JnzHBS/8F3PmXNnDOfj9y6oOUC+7CKqyuhclBZxaJDoJdfxpAI+AJjP2lDmR6kgnR/nu/KXHpy//PHXR8jAwd1dKpgAhxHI3dwZXLUycKrqwEroJa7sKgApp0c55PmgwnndgpqoASItusSg8FKs6zfZYsh0rnp2VoYrWXGWWrwXDg87Hk/shXzLy5BZZ8ozQY7g7Gau561mMAqBq8qvAKpFzdmrjMuyQwFGqel1AhAVKkFYiMjOZAclBJIIN6obr/NHnJ8US2Q38qJQA7OzazCCFq+ZMFpZWU5GC91SIruQBApBhMmdYKbuaJo2Bu+6lgzEZAnfvPz62fbZ5mLXb1eHh9kUXGkiC4LMCyxo+OjhU2uBa0UTjMFMXo082UAAOwtLEBJ2kdhQEyMMBVYjS2MMFLjMZGV68+abw/7+cnv9xfefvXz99cNwh8njisGSxAgkEgGGmAuziI6pCsxs2X4YAAg4krMawZzU4VrYDIaqKhMiisSlwpwQCcxiqqbFGBRAAUwCUhbmGEAEU7CTGJzBaNs+zWpGKSVPZUoHELabddvGl6++Bqxfdf2q7zd5mOeU59BSKtMwHc2dmLq2RZWXa87zdLG7vNgUAJYKF+LAXtwJVpwMrsIKmJtZQF1kVlzflhPybHjiH00PCJUjDoAWHV0TG38Yt6vtbrc7HI7j8XSxuw4yHo8PWXNs2hBhhpwUUK0ZMQEBIiHeT2PTVPaQp7lM05DyLMGJOMbYtS5CbmpmHKVt+6bphRorA4AQQoUwCXx5cf3s2Wfr1ebNm7uX334rjOe3uNztggQvenv5pOH1h3ff3L29r/4yqBcf52WY1/pA9Rb8WEHP+M6nQE8lfz4+6Jy49Ag4fWzhP+l1iL7bkTj8HEn5y0rdX/tspUba2YOQ3Jlg9Y5gd5h/asheD2Bfuia4CJSI8OnrWGoDnT3oqjcDES2eWH5uNzksA8hH/WN13jvXwmXfeP5Y3zC1xSJg8bykj1uy8/6gSoOXArj0fcvVJuaiqe1bDpxSBiAs7t6vCfD/91/82YcPh9snm/Uqfji+GsfhaneVTT8c92U49ty8/sXPNutdv+pn6P3h/s3dmykN6sXMKQjMkmoaTghYrRszK0VTSkbe1QOCJMZ2dxk3q13Hzf447e8Ow5SndDI/MJNaaZqgCuPQtbHt2jQnYy9lksBC1jaIUfqujVHI3UytFA0QBpNZtXcocCfhKC2bUdv0qqa5OFxEmIKZHYfjNCdmXF2uQyvL9TqPlsxMQYKEftVW25DVOorwer0mYDidRBo4taFtIjQViYiRKmNoShPD2q6V6CwyMKzgeISVKQZcbi+e3D7ru+bNt2+/+tmrV19/wABicNuws2mGIzYha/EcpjG9e3t39/DhmI6xb/pVt16tReKhHDJY2nbm2RKgcDU1UzOodxcrSzmlub4lJCKG0DRt3/ehEcpw9mmehfKk05QmgEXMCTHE2JqY6qyeCxTR6Lg/ffOzN09fXHzx5bMn19dNR9PwMFPOSZjvmxDbdfhPfvtv7zbb8Xjs2shseTzN8yhMAezqMRYnH3XkOLbsd/cvT3mYytEDQiMkmlJFXhCE+lW33mxiCMvAIUwSur4tqnYYJTQhxhCb4pgTyNB2Mk96OJZSDv2Afs19H2Ngg6smuDHDuZhhfblb95Ga4Tjnh7vxdEzkMQ1Iqcxp1mJFvVgR4Xme3rx/lZGGMX35gxd9d9FxmmygTOOAnL0N6cWLWEoWCV0nJek4pGE4eI6Re7PAFGNsCJo1x9ZB3rWJiec0EKRtV33bFC3ZTQE3BKpqKpBUxYxXwkDFNIiXRtoBuDVtdybpGAgcKASOjRBrG7DdrO3pk9vb29NpAPjN2z+sXidNE4mb6UEDR6YKhqVGuI3SNqHtWuaQUgKBFCIBhDRPuTgRVmvadu3DfgoCLQyEtrVKEOvWApK265pmM85p/3BkDuvVarvZtDGSOZkJa9M+dF0rSpqyODSX50+eX1xt9g+HNM2uOcSma9su9m27CqHB7NWNOKVZopxO+8NpHwirDjHIarWSRoi4lNI3fRoLexOY4YBW5iTcUVQR2NRIKIRQzw1biABk1SqE63Rv8zyjJJc8jNOH/T1LSLmImKkRqOtWJck0pSBNjK2EuO571/1pOMF4vz/abF3XkdQ9JNPZgujMg/noUfR4lsAfqVO1X1y228z8qAXD+bT0T8+zcztd//MIAhFzXVOSY8F0UH0fiACvzjVUyasOgTDADK52p6RzOs3uJ9dOG27LlMs0j6d5Oo4UYj6BGxnXLTWSbAJbiOxgL2RqtOZl+7+07surZmYwCRM5IFxT7eozN3Niliq4r9fjzJx2qmQcgCBMVlVIgRGYl4Z58WOodk01Zo4dqijsrmpTSVMpk9rs0ORSEAMHOGudnpx9nkxV+3Z1vYmhIQqkbk3TKJCzYaohK7BsGTn2rQQJLReyYtq1ncROQqPFQKOA2AnmeSoP9/O62V5ur2Y+YUSdY7245Rr6JmcnheU9UC0Q4EtQMxsgj4OcP74LqhPRGa+q6/zvrABrv8Fnu21aNr28dAQEEfn4Tvv04Y9wK5aVHKyGYC3oDxSYQteKy5yTj9OP/9Mf//rfur26bELQ509vv/nJh7/4k9d/8H/99JuvUDJQUHdzWigXJeEzmlR9lVBf7/lpLDu788T0iEIBOJv9nzlSVcyyfIbIK1z7KXT18cL6+TNVYlVrpz+2pR9f/SMc9vjNXl2XmEFMWpeYUHW30FIpPh6TTr693NEu778a/pd/+H/83j/4zWdffJHSNNHUAF5s0mEYkCaE2Ik0BKKC/DC+D/nqAut+JaExdY7ctSu4pTwfj8fbp5+5D/OcxnEIIYaA1bqZxpzSYIo5504ac4uRRVru+qbphJuRKOfe1LgmmDEKdC4zKQVI8Zwsl+ziiGJRGg5CSlRp4mRkCCHUOR9qdN6exhgXS1WCmhXTygU9Z4U7nAqcm9YjE7GxqeWS1eFe9QcEdTe4ENXIAD/nP9YjjIUg1V+Etea/CS1oYljsb4nImbxGGNf3iDgEClMYC5NAWiIBiRfOaGA1opwMTqbKkRGpKqabjlNjv/Ef/0d/9M//+M2HO2ZQG/RYmCNsUc4REVzgSsi8wKzLm1GxqHykQSYAuLm9kMDTafrw7iEEXq1WTdtotscthbo6MqMUs27TOJ9jwwI2V5uxjIfjPs3T/f1dw43l8uTqNkuZ5vk4jTmVklS1gLxpWl6inah2evWCujsUVmC11Cjqrct1Dlls8z510T8Xkkdg5mM9qGXgLGDDOcb0E/SKzvsRIl7mmjPgXM9dOp9Acj4CzjgYKlz1Kd706eD0naf3y5hZ/5ZH/bF+5joEaUAOczIlXZzhSE2h9ZJZFfm4WbWEDRJEauQYIjWVY/VYJs5vAZxRFMDh5BzkcXtQ4xi1+GIrwyyB3FFcq5WysTu5ijpqrwfTyo1wJlkG3YrZ8NlmqErHq8vZInFmd0NxJCCAI1eeo5OQIyDEGJx1trmcKx0RwqpBECwF1DyrEytZtZKWGK24qXot9bYAlO6OAioEcmTACOwQctRQWjfWECpmxuCPX6xVZW+W2ANTEAkhMHPTNQRyw3xKZhYCpb0d9seLze766c2bNx8wQ0QWcFNcOJBDq8fYkoDjVA15lvcgqBqyBXJypdovOzWRgtSNvgSW0JgWz5pSAuANCYFZ1+smcHp4eL9u2802PHm2uz9t76eH0DkEAigtbtamBAKawBSAotUrzhc6owhLIK+m1sIGUVNVhdbnaC7ctJ2YmDqBQ4yBg+Zs2Q2FG5BUxZ2wiBEtkB1VxkJgDqvVhXBOc055StMA8ZsXuHjWMdNpOBQdgaKG/cM4zspiIXYhSNu0IO+6TijMU1Izcj0c97tmExpabzDuHU6kla3vZMRaJw1msFItKqDqMgN8PGvPWrHlbySgyASwkQAMIgVTu0bsxazcvf4wjINIHMf5eBwl6O7yomsFnq36plgBlAVMCA3pyQsnMzPjNJeimciDUAzStqFtSYLnPKsZBwnSxNiQBzPPGcfjsOq7kpWdbq6f9P327t39Vz/95vXdL559dvu9z59EYTJcbC4vb57t+KYMfjgUoQjhmqu1sLxrNwTQkgv80TH5rywDagEqqvTYSdT/sDPJY5P/Vxfaj+DOJ5ULHyvOLy90ZwyLPhZpdV/8P42cDFYFzrSobc0Xd3avirxKd6kIJAvLUngI7tXwkplrhKuZq5qbcljcqdwX77lltAYtaaznPo2cCeQ1Bfb8DInOwNtjtfelWSGqfrDV3r1u1KFntPA8RC2HMjE7QEZN26jpPM9d2xHzME1NCBLozbfp//7n/+J3fvvv3D7pdcb+7oCgT6+u2lZO86h5nufU9O1KujHNpPM8PKSSx5yGlErV4cNZpJjlrKV1VcvFshaTORf1lIsTh8AhTFPe7+eH+zKMmVA4KAsTWduxQ4mUY2xIYteuaL3fv4/KIXAbOYS2a1siKikz2JiiUD19slvR6rzHMTRBGrjE2Jq5tZXwq2ZWNI9TGgfECMCIqah6xQ3gde1M7grjQKUkc2tj6Pu+a1pmnnOCaRO7p7e3F7t8Os7jdALbOA7Hk+cyN5206ygsqoXd+pb61rmV7ebq+bNnF5ur4+Hh61+8fvf6g6NqwcizFnNXDcJBYtZCkGnMx3Gcy5gLmG1GEoT1Ojy5vKUrMtUyl3nM42nWVKDkSqS4n+5X7Xqz2VSizhlPhprllHPJSooRnnxMo4rGPhJHgzJRDGzZ3SlyMFZNNhV+eXxQmza75rMX14rx/d3b03gaE7l537WXm9324unuqt1dgdyESpQd0zrPQ551OJRxPEzzdByP1HhoiW1GmUHo2qbfNuZ6Oo1Pn93Os5qphGhOU9Kc03CaxqmEwFNXTbBMjZy8qDuIBCGysPSrppSkrknReYhN3zTkllXL0uCxEiEVwzCAXAtefXj37Tdvp5G1kJksidHmKZuZazKQb9frVcfzVMZDno4KJwlC8Jx0f5jevD1c7EIpNs9pHKZxSGlO7OQCU3WQOoVIxGG1aq3ncbL9w3w8jWneN/PMwcXJIwjwCjVo3bIBBmMjg1bAGsRgJ64JQHCU5BQBYYkNCbouth13rTgKxCTIze317mIrQZ49f3Z9dfPh7nA6jswRkMpHI7iJNcz9imPLzKSuqg6m2AaxINKomc1zVjDDnIxEHeRIxWicc6lKNGv6AJBEclGHFXOfHLmU4cRE4hSDNC0JhZJzmtzGOQJPd89vrq5i5OPpMA9DKaWDxxBiaLrYNxKNlBjGVCxnTafhqJif3eLiye3l5WWTp7mkNKfjwyHK+jAdWhYiIkdRldq3E5KWIMHMQggxRnfXol5Tsyq9lcgFBksp7Q8HktSsfBqn93fvVFE0TKOaMju1bReY3Xme03CahvG0ud11Xfew309jPp0mUrAIFS1aQhQtitptLauLRSdz/nAe1f07i5l6kDEvsbJnisrjmfXJ4XbeA/F34QghhsOJzumDi2CfFu/280Kosm54eWIVAbrZ3IyneTxM88PMxmVSJBMjKpGEh/HksLDr0ZIF7Xdd13eRgo8250SLXQVQDXuN3LBMMwymUJOAwKBwThlRhzsR1Tb+41WpYeJc1y11vnJD/eyZHyLMzERsQgYzr845UPdcVFUtmSlFbhEITNnd634IQuwQt+BFfZqnLof1ZrW+6I/D8bg/uUXLmKYMBQSLx5LD4U0TPZjqlN12oQECnILEZtWvWm6CWClTLvOAm2276raR87JdN5SkpMQuxKzLuhsVnmYwHtdn9QkCwnCQ2idjnMOFFsf92uKfR0HzBeIzq56dbKj+HUxcQVtSMuFHdkOlzlQGeuXfPfoq10AQFnNzq2OUQykCnGxiSycIfus3f+OHP9rC7j3rccT/+b//ybc/Gf/8T/dCkUVTsZwQQgixQUCdGh6PoeWtfp4/6sKuCsoIdCYkVCaH25ID5ss2b8FfURux8/KvwmGfNIfmC4nIz2z9j7dbVT2g+tKej/yPa74FECahykMmAoxQQCbCWsCghlcgnY/UxlXT2x/+k5+uwup3fu/Xn7744n66+/4tmPhwqkitp6QMDU0n3GQepwGD0Krt2rAydgSzUNzSrHkYLWctxeYpFR2Fowgzh9igaAaqdUXxKnx2aft137dEUZjavj0eT1hgXzLL85iq12oqmhZ0CmbFAXY29yV5TABCYFl+C1QtFIyIQgiVnckEqBq5OsxQHKZWpx4ltIFQfTXgEJBybaK8rn9RYZYlrc5psSaqvW1ZbgEyuNESdeXuBaZkVT0ABgJQJ6RaDQUQLqZKJTQSWuYIEiirNYYeaoDC2KpFLkWXaOoOQbPrd5v44vMv/r//51/OBW0TLJM1gS0gMzN/NN/QAjeqEjACyJXgbtwSN+R1Uy/YXl1OeTrsD9N9hiBPutn2mgsEHIGyvJmIyIUSsppaBDXwiM3V5t392zfv0+KOBFctp+N+OE2Hw3A6HGGAQVhCCG3fAqCqE1yipYhcoF7d7D++yR3sNR1tMbGyx0yHx7vvcQsPnBmLhAXDYyyw9cLE+gRrpkc0xxdWgn/EwM6+OMv6/HFD8x28+BFXqSOSPWJVn9Kv/l0ZWHUUWnAkICjlejoSMzHykvjMDi+mbl7pBL7IMWvzgCoL7Pv+USGojwWIzgyA5exZZs7qIW9mpRRz1aKmRExNjBKkqKp5LTqkFfwlcyNSJ6vLG64mlMzZ8xI3XQluxELntA2CwwKxE9RLTdakUtM4hIiCiGphZWaRGNg5SVbN0lbauy+ZcjkbSr0WNa6AIlMQNqOz0zkAN1CuvyfKVJxqjDfACztEuaq3zBTGWpOfmRgFNbHFV9VHuKgwulaCsLiImPo4z9M8MZELA/r67k2M8cUPPv/ZX/5k9nOxZycScAVTDM7khR4PjMVsACBAmEUokAuE2Fyd1QnOZAS4i8Mcap61JE1eHApxWjeh62MDevv21bbrLja7739+k/X0fv8QOzgj1frDsKLGBhJpgsTGnNnUTL2yH4EabagGIpEQTb2kOaW57vScIE1YX6xzSSzO4NCGEBrMIFYGUWTi6osDZ1KHPRJAq5eRiBnF2BFJygNKbrb4Gz/+Ub+TDx/enY4Pw/SQUj9Pfv9wSIquixKdmErO6tZ3fU55PE0w5CYdPtzZqmva7vOnn/1s/9LEvPK2DaTiVt2rxA1C7gu3AA5e6jYBtLRzdK45YK7e1DXjAwxmZM0//PKLftPcvX//sL+Tht+9e3d3f0o5b7fCJFQt19yWcAiqNp8uAjDMVNVKRlEjhjAknF2ZIEwgFCZ2p3kupUzkPE9zKRiPMxN13arvt7vdzXBK33z96tWrt8Z6PB5+8CtPtSQFPbl6+uziB/ywZo2YIGDiMGv9kywAVt0Lforx04LI0Ef0/XFptsSI1lauLoqXfdB5P8Z8/r9/rXI9Fr5PFtd/DcVngImXQ7XqGmFmbu5WE4uWn/LRyfB8IFSCJz0qFgkEskUWSY8V+dx0L6C8m1WPhvp9561pVeqDQMzsVBFmNVA962WRUH984Y+v53yY1DOqljrS2uFVRsGjrv3xWMGZ0Vt/KHnOWU2ZOcRgZqpmIagDjN//Z3/0q7/6gydPLrq4IpXD8UNTYt9Kt11Pw/jks8t1v4ldPB3fp9N+PD5QE1MejsMxAbGFByb1Juc5lVKxc6ectQzjaAU+JoNwQ4inD6dvvrl/+X6aRkwFT6+joYhQ3wtEmyBKlFRjDMLoGgDG8DaGLrZEoqp1mc8cmtDGKMW0ONRSyQXnNgnAw8OeqUox1Gp8tGkI2G7RNIGE5pRyScQslZwOuBchJkKIrpbNTFmIuAkxxgYG1ayQGELfddv16mEfxmk4jXNKSQ0spiVx241pdi+bVRTCevXs6urZ7dXtsJ9+9hdf/+Krt2VkOIugqFvKIAK4OM1JQ9O7+3hMQx62F6upDDqaa0Y6BeftalMtqKd2gpzmPGU3CgQwjHxyahBWEmMkc1V1haY8zVPKKXmJDTcWFZZS4bjwqUspSUvbNHCDBwmsnqZpCoFI4v39/NO//OrJZ39zmo9TGods2T0lGxPfH96+fPvTrsWPfvC9PE+RbL3q+y5onuYpnQ7jMA5qdpzmy+vLvluFAs7ONWsiROIGHi6vPjscxuPpOE7zcTikpCnlaSqlIEZ1DLGREPv6GlQ1NGG96dw8zYWFlrshgCSasxoLMzkXzfMw1YEwp70bduMuhtWQj6OWyXEOA2Qirvxodw89tU3PIkwyzIMWU7ImtG0bOaRGqG27XHScJGcbT+mwP52OrgmM3ISxiXGapU+537TrdR+bHuD1Om134/E4Hw5Wyii8SJQlLutTAM4LdcV5iT911PRrYVS+iVU1Rxuapo8k1fPJHZbLHAOlrK/fvLq5vnz3bn7z+n0p+eb66v7D4f7+EESAGGLHzCEQRyIxpuJmc9FpLkS+3q5j25jWOQMxBmaXgCYGN/uYcptSKYWZJVpoajuR52zHYToecxpm8AkAOzoJm367Woebp5uSjyXPUBjwwx/+4ObqSnM+3D+cjof5NK77TRNiG5omtk3oNMweSVMulrPOY5ogen19e3F73TRNIZ1L3u+PH+6O33txzX4kJ2GR2t0AFAhG7q5aUKhtYwixlDKWkbEs5uALrp88jeP4cP/QdN5tNk3TwJHyPM8pTSfh9nJ3EZqGohDHw354//6haGqkV12MHINUX1dKKaeUYwiPmxI6j+50HpodjzkltTj7d1c5TgLC4p6Meh0rzeSTMxTntru2016VVoZAwSsj16nOHx/PQgbJWSvGvnhE1NbT3Mz6dm0TFRvKWJCKzS5KS6YTNzBKOnkyEMzKeYpaiqybyRl1ciZUP1CFugYKEqOZaS5MLoGFuE4OcCI+9wfLNOULhMBnFjihOm6bayWOMbMIhyAkUUv1oihWGwdCqc5VsyMzuQjVFCY/79TNqDibZ4SOQgxGPuccSzSYejmNA5lQAJrzr4gB4RAr8OsS0LSRiEsuXjSE0Oy2mw11jRKQpgxFEEljru0tQWqihqkzCbkzuPrP1p9eEbJHm2RUY6cKZsKrYdbyKbgzalwrmB65DFwWmI8fXQocToaq4apeWe4k55ESqDkyi5rPvzvcYuGdn5d2cDhHZJ1zsd3lavdEfv3XvgTdDaf07v2Hv/jXL//RP/lFNyOdhFhj5C72iEQsZpanmSWQ17UysVes0R//zUeC+7lzo8d7Y8GVHO50zlJjP6NRi/HCo3bQPiJY1YthGYZ8Ga0XUBif7I0fX+75p4FQjWiZAkOIdAF3q9NzqSGJset3cB3GTAff3F6+/MtX/+P/9PvbXf9f/IP/8IsnF3/jB8/vD1nLsS7FDseiORFaptDENWs63Zc+6qqLq1XrnA/pg7oyMcNevbwPASIBYPfM0sZAxETcuDk4C7t7KcWZs7jOHwAAIABJREFUMnNP0JzV3LtVdxwOIGFmCcHBymbZA3HWgqCPF61UfyldLBaJwBKW+inMAMw967kXpgWLcCz23YAuFr4AoTiaxcHdQEAQ9up651rU9Syxcq9hm8vanpc9tjGY3ZZfiHtwZxhscdxw92qWFRwREplEqA5KgdSzu4JrLfdc5oxEK7DDCqDw6mJbYME5wt2p4fXl5tnzJ19/821sm+vt9uHhYBmx7fNgMQi7sAcq5BXi1XCW17LXeZ287VsXFM/GQEDsu3fv3z3s95iBFjarbMJu0+66LSmlo+pkNplOVkoZxxGCi5udr7Af9u26kYMM4wl91zWRFW2MeU5TmqaxVAJHbfE5nLPR1azURgAMqXEERkqk593/J+/tevfUM3Ep/dV6F+6uagsnYJmeqtjNiIUIqH7+7kswel2XLOMPmZ6PMyc4qALK1U34DNi44zHx8/EUAmBmj7DPp2fUp2DWvxOAhTOP4fGfCKlkFgohLoVTAXIWJpCqQf0TJtU5+7ColmKDhW0opSxPzhzZ4YA4AjGHEEKQIEE+taAvpVQqWjGFkyCEEEMQd4ipLjMiAXUJWV2sFMACM9anUgyALb4xIIA5xCCqxdy4UhcF5J6sZjVBXAJFrqkL2YsmVsSuaSQC4LbrNx2Ej+OQ8oiao1ajNb0mGEpwSTR75Xyday8tIysgljU74+x1AcAhDKrPyJfMVIMrGYEL4OSKsI5ReFQ3cwfVRK0onosN41iydbHblwGEd8f3z26fPv/+s9Q6jshehNhgVrdttmwhKiZKgmUjE6j27UxMvCTRROFZFYCLKxUzhzrQhmDmC2usOjQVdUGAG8M+vHs7X1+3F+vnN7th2BIDNsdQGlE1MmiujoPcSZAmNsWMipqjqFVprgQOUUg9cNd1a4Cm4VgwaQEAMGInm11/f3jv2YwUDUkQhZAzOygsq0s7c1VKpZi5wmDEYDkdh67rJLq4Ah5X+OzFLZG9evX1OB+nOV9crtxZAiIgIsJUrEzDPOV8sbucpnk8DU3omHkYTg0eNv369nb353/+sq15DoCVKv4LDCJjdqhTKVgMC+vNVUETqnunUt0kncAQMHmN1WFnsULYj/m3f/QFE/7NV//K3W4vb3/+89ensar0OKVcclEdYyRhX9TFghAoNqxVfWleFEWrBBbErp5TKk1LMUbhKMQGOp1G05GJ0pRVMU0Yx7Tqt5e7m/Xq4sO7b1+/vst53l72h/3ATGlOxXhzdXm5vUlTYGswwUnBDFIw2dL9PFbTc/f9iNd/p6KdCUKgx+TchZDkH5MEF/j7k8K3fIaIzkGqn9bKX1oBa4e9xALTQsLSqpJeSlrtFg2VzERVE+GAi4QFBqkriareU/Xz0z4/quR/wZ7qgs+KojqI19DbRTV9XrADTkvtP78sElA1COSFu1p70YWkuyxU6AxqVVEQzpEbtLzY88FkFYyuBudBZDpOHLlf98ycc5IQimEadNXjq5+8vL8bGF0a4TPGY3rz7uXuZv3lj7/X3Vze9E9hdBiGvzjev3/38sPd3fpqrWo5gTqsL3YKHE7DlFMupRhIIklQkOZKhZ6nYjFCQh6ntD/O8xRL9jwXCW2ZCe65UE2r8WFKJXVt17W43q5zOrlRlCChyXPJyWrMNIGFmxgiWekaJC3TgKLGyJUe/Or1IQhYIAESqscQ+i5ebLexlWkah3HMRUXATKZ4bPW0+GpFQq6KUnQ4JSu2Xq1dTYtPY0opb7fbvuu2mzXBh3mmcyiFldI08TQMrlMMHDbrJzfXz599r+su/+z1n3/1l9/u77HughkR1KszsTAoeEppKs9//PlcJp0LDNv15eE4lHsLa/Amzqfp65/+om2a1XZFQQ7D4e7uriSQIIowh27VK+xwPFhRU1NXdmGrEy8v0nIOIVIuxWDsUkrRyRXlyfOrkw6anZgl9pGjiPusWfObDxlNsML9djXY+zlZrroMxTCCjnj+/P10PLpOp7Ff9a27WirDWEpWI7s/wMM+U85mLCYZmnOectt1q27L1MEtz8PhkKdxSGkRe9QgjnHUEFabTV/K/jQfJchq3TPLNKTTab7/oCJoW3DANM+qhZn7LhKZqruWEElCpEA5+ZhOJCS9XVxjDcwlzimnyVIyK8gKB3Z937Yyj6PB0pSJZbXrOAb1OeV53cp6u9psdg8Pd02IQVZBUPLx4c6s5K631artLLqgXfex6d3Z1GNsVn3Xr6S+tOPBWRAFRKTkZfHZgDOE4CTucK5hNnQG07n2P03f9pvVetOD9TSfhuE42xzELy/6lPHq5dervk1z/snP/vzm6sntk+tXr97sH1J1OkzzxNx10rVNNJqnNJQpmeN4BALWGzRNa2ZpSuopNqEL0jSB2c2z2eL/4EWp2k06nBGb2LSCQiKOADRggAu0oBRPbETz82cvHj7QkMyQKeH7X3x+ud1a0uF0HE6n8bT3y5vAHIX7pu2aNmcrAoenMoPIyEgoNlFCmKZpLrkkPdwfhwesf7jq4iEgMkKQAKr0HIiyupmDVQFICAuzyQyRWbiuQ6FAwZzmKQ0J+ll3s73cbe53fjyO43g45r4TiSGEyC5B2vGk05iz4uW3b5sm9KtV07RwjhyYOc+DZzcy4rqTeOQf1DPuIwMbwCMX5NMTyush5VUdd95AfBzqP34ZgCXMW4K7q2qBSZCF+FCtP+nx62uMZT0CakzV8p5igilpsWmYylQ8uc1AWbxWyqSBRZrYCmdVzQZXNFZSUg3ceNdK09LhXSoBTfAKqBmWNNdSlIRiZDLOOTmcGMLVe9vh5EKowzKxL5Sx6sUEAoir2Y6BXD+KE42Z60mgqi5GxHUd5O4Ks3plVZMWyWzJ0XB9vcpmVI0ysF7Hq+tL6WUsp+Nw6tfNdrudRuMQ+1U/dMlHW4aMRmIbFHlOMxpsNitPntKszquNbFdd13kMiZnMCgE5p4cPD/OcAbCLsxA5VWc+VY5kkOp8WhnzoMKuj1YFtSWq/IZPKPuLhRkIRggEiAuJed3kMNzAFRyFw5zhpMR1WaoL2EOLns5Qg4fqOqzGGy8oReULsgAL2cuJXA1QQ8AXP7h8/sV60/uf/9nPry52b7/N//KPvsIJ04DL7VMOZD7nlOc5ExkxFUMMcraVAth4mdw+NmX1CS8ErPNnlr3bR2+E81quQk6PvLg6cD0CgP74rd/5smUu+/THL3+k737bcumZeVGvgqyqMhWuTkRW/HB/tNGhMitLJErwI+6+Hcc7+/LL7335/Id/aS/fvTsIWdt0c/SsQk4wamRFJR729+LH64vr7nqVfZjGafKhXTdd2/6bn81ffNZeX2+ZqZTEwoDrODctM4dUslVQiBAChYCs0/E45ezr1fZheIjSdk0fuhBCozBEJ8M4TSAgAA7PMCLmGu25OOY5FdYgHJoYGwkAULQUnabJCW6mbllLcQWHugFVh5yZN/YIgQBELIGYCGrZEtSWbtcci7GYVwueWtXbtiFejF4VRIGd/ZynVOpbAISaIIeGqsU7B6FAKJpzcS8KVi1znrNPaAmKqq+y6q5GMC4JBQSP3u3628+e/smf/enV9dVnL3C3/zMYVpf9/XhwCgDBiITU4M6gsMQisZuZEdQ1dG3yVHSRn4cYT6fxeH9EQduzcLhcXV5cXLSxhdLpbhwehmE/DD4UK2iBFpefXaHn/Vd7alhaliTTPIq7T3rRr51xHA5nj2oArlZMpZh7Uc3upnAPFIWEICBbjIZYH8eeZbjxZSlf74a/Yv9m/lHn+Hib1SrEi2LZHVaKP8rbz0bnbF6HVzz6sp8xyApuLtyM6nJen1QVSVRI65dOZ8v3/rL8wX/740yOWgAsdxfaAaEOvZAY1pvNerNtmnahU7GQCMwBqyFdqLWVyRsqWlhEzfKcOIaLm8vVxZpjqOdx27UkPKc0TGNKM4lUzT+LbDbb+TBSCPUYLqpwJ64AsLmpmqqpabHirlhowUTEDELsWmYhZhYhYjMrOblq28QYQykp5VSK1gRCZiFizapJrSiMCMzOZbY0ZyhFksCh5DJPg5ZCYFlsciEk7GTZy6xWvNQoqLpVq9HJlQrDESDPCjjFQCIQQhASXnZf5B5rk2oMjhKYOIYQYhhOY845hDCNpW06jpRScqcQopsLhcvd5X5/XG9bmml//DDr+Du/9Vu7y83L16+s+PpixcA0TyVXQz0KIsSczQLz7mKXLNe9lJkVFGL2cC4f5CANbVhv1pvdtolhnuZpntRyLSWyAgsud6vrq/Xh/nR7seY8/8pnn//63/jRj3745X/5d3/7i+e380mPx7uLi0ty+vJ73181q1YiAU0nL1487/suW7q+uXj+4na1aU397vUxzXlK8/H9h+M4r9bdkye3z1483V6vu3XDAcfxftiXy5vNze2NRBnGYymFBbOmYsXcmIWY1EzdXQuSkQTp2tDFEBpL9uz5bevy/v0btPj7v/e3Vxs6HN85pe1ufXt7YV5yOTZt27Z9sXI8HqZ5jk273mz2D8N2c/H0yZMQwt37d5ZneCsIu+3m8+9dv375phSII3Bom0iQuvt1QCS6B81kGWRBqIGHkj3lwszEkSTEJq5WK1P1wJuLnhuYTxI09Piv/uvfff3m669f/pTIRejt3Zs8oRTc3HSbbT9Nw5zG1Xq13Wz6vgOs5NJEabtQslJo3SlndUfbYrvpuj6GwEG4bZsY4sN+z2hibI/HaX8/FS1aipu1HbeRbm9v/v1f/40nT56PY/6H//M/HU952+/aDR+HtNmi67ourCOvMbX/7X/z3813I8+hem5YK84fSwnVwE0JtSDWyotFzboULDWritGzX8NSxR7ZVTijPMy8GD1UYnMV0LmXUmKM56K8iJHrtE7ffdTqq6ZmbsW0qBZdePYOAFVsIkGqTpqA0IpEcSZAiYibIJE5sLm5F/dFalhvJmCRxpbsanXurHQ4h8PVTWsW4XKyirAIAYsUu84zxO5upRR3E2E6c6mIYWQGU9Omi8REZGpaXKkGrpw9xECo/+wZGyRmliBcKdJe6p2ecko5qRuB3cmgxB7K6nd/9zd/5ftf3mx3t89ufvLTP3379uXh4U5EX738eUvtq9evpjReXu4geLd/d3c/KZXsGGdMZeagEmnTbbartVDYPxzu7x5y0Wa1mlWPUy7mRQHnr37+7n6P02BJDYLPP/+MhUgolcTCc8ovX9u3b7Vv8PmL2z7aPIxds7m9ft6G1TyBPHbtbtXt1puLtlmJRJGoqn3XPrm57tv+dJiPxznEECR3HXU9dz11PfVrX6+67WYL8+PpMOZJgoBQ1M3BIlOyhz0APHt+O6eZWCSEtglt24bQqvmHD6eH+wOgv/bjH+eUDofD8XTcXe6e3T4BUDStVqurq4sqAn16+/mPf/g3Xzz7wa/9+G8dHqY//IN//b/+939wnPRy1z08zE3sNrvNdr1q1m29WdrNbn1z9ezzJ/vD/uHhAwyHw4GZqSEhCSKayjSMh2F8/2Z/d/+Qy7xdb/p1J0xpzvmoq4veTXMqqsokfbdqYsPE1VS1nqPjOI3T5KYBYsWhXu/b+7tj7JrQ9lPWMasZgZkayp6aHn/61cu2s/XF6vJmyyG/eHExjONuI0+ekLD3Xena5ub6ZrVej+N0OBzUuemjtKHtu2ef7a5vr46H/O7uVLIzcwyrVb/rmjVR/yf/6ucfPpyOh3Eaiyk1TRtjWzKOB80J41jevRvevH0oOjVthCPGKIHTPB+Pud8gBnQtYuSbm1shCdIdHubD4dQ2fdv3KWdmvry8urzcxaY9DdM4j03bbi+3JtpvmvVFs93F9TZuNvHictWt4mrdrzft4bS/vr64uN6mMg7pWLT0a7652V5dbruujaE5HtKbVx/evhn2D54GqCL9/3y9Sa8kSZIm9omIqpqZu781tozMrFyrG+zmDJucAZokMOCJAMnB3AhyDkOAF4JHgnf+EP4KXnhjg0s3MRiwu9mF6XW6KqsqsyqXiIzlre5uZqoqIjyoucfL6h5aIF685+HLc3NTURH5Pvm+6rd35Xo7f3+1+9XX17/46sXt1bel6DAMp2dnjy4f9X2Y8wyJMXUxdSn1Q9cPQ0oxuFsMgVi0kik1bNNhhga4OQtTjP1q4EDb7e3V9auccz90XSKg7seaevzDf/C7JU8///kv/vyvvvjZV1//g9/5rc8///zi5PzLl9/UXL1W09mobjbdo8fn+/G261MIEqKcnsb1ZlNKvdvuLs7PP/zRBynykyePADPP99tpteaUWITMnBmnp8Pp2erkpBeRaZxZ+OT0ZOiEUbV6GcGAqY/beXc9F3sTWa3wk7Onv/3ZJ//sP/unAfL27fXN1Y0WLaW4+6effPr+8/en7bbM+ebqOgqfrDd9nz7/7R//2b/+yRdf/XQ4OUGgF69evXz10pyfPn7v8ZOzl9+83N2O97f3V1c3dbbIkmspZbY2mWlw8aJlnnLJxdXc4NVVvZRixZpT4W6avvx/v/sf/qf/bjvefvfNq19/94uuW333akuG+9sqRJ988ul6tXr58tXLl2/3uxICyH2815yLmqbUBZb9fp9LJnECmxkThBlMDpiZqflSBh9yxWPlQEDz3mIiplqqLdQDIuGFayNtog0IoEAcOKRITA6UWs0NBGFuRhOqtc1Jgg883KaDniQXJWYKUGBYDf1qlec65fni5PzNN2/ymK04qYgHZumlH9IANwkBDIWHPkgXtSrYzs5Pzs5PJUjJuUty0vdCQYu6Ghytadv3Q1Wdpskawuiauujuu93o8JCCw9VrG5xgIQrCQUKMXZ9AAFu/GdSsuvbrZO4eAODs8iz0AUBRm8fJysyBuyGdXZxu1utpP9rsIcYuxFxmMPWbDglK1cW4p7RiHvz00em+7ue6lz50fco1j3MupWjVi/OLRxdPtOq0m0EIfWgiWd0mpp7HeVcn2+2nlOL6dJCINOhqTSn6PM2oWaf+d/+dfzi91b/9qy9g8MlYg1eyogBxlMYrNzdTswo1NYMwokAiEy0ejEvTq3m9ENwRBpHIIuKwYllrdRgJg5wEEgM3CSF250YucBYKKYZe3JcprUUGgQmBRWLDW1IK/apnJoPGLoQobYIeQrVU6tjJf+e33/u9//CDf/ZP/8mf/+SP3768/dM//Op/+Z//+tULR6UUTowwTftcSq1GLu5wIxH2pf3jDaBtSGWbGXCH28FL9cg0ezDx17ycxZe6tFGH1LwlUXa8J1HzXWFmYWFiAtVcm7bpsbp+90ILE2VZgS1PJWKA3VxVmTsmAGpWa8maYQWu8AmYzKk3l2FYM3PNZbUarOR/87df329fvf/h+//oH/0H+2n/9vX+xZtrIiZOzY6kTppnzTc7oThnffHi9S9ffPs7v/OJJNpN+XY7gSwKctE+rbo+hCjjOJ6fn65Xq6q56/rz81MJ3HVhGIKZX9/s9/sRDHe/u787OTlLKdZaxnkSEWbOZR7nkYjSkFKMTDR0nRBbNXZKKaWuWw/ri7NHfRis6P3d3e3V7f319v5mt9uOcym55LwvLPz+hx9cXFzmqqVa4Nil1D6Prkvrs1N1y7lUrWaqWktVK+XYOnR1ABzA4YD7tuuTjZmNNOdprDMCXKhSLcgm3m/6tO5M3IPFlYQhhC7GFCmSuuaaIQg9xyFIJLCDdX06pFVMvQzr7uRyvT5drU5Xj95/9Oi9x8/ef++9j99/9PTxXOZffPXLOuYQ4jzmt/fXKDh5vK4lmyqYqqlwCDG6U5nnxjWmEDkGZzLyLFatDuv1+QePPvmdH//xT/747ru71Vl39ngTWN5/9twV99f3r7599fOfffHtF9+/fXl1d3cfOJycnzz60eXnv/vZ5nKdPa8ebX716y8VamwdRwH1HOtc8jhrXRSuWEJM3dAPMYTt7c6qMSFQEAoMgsMqNesMq+5qUDCLkAixEDMokoiIKxpNzm3xhHRzboqbi8oLE7WV0+qRNomtVi0Eaay5Q7OID4A7LRaTC2Fu8dI7FDhM4GMpRwepKCISkd/oPR1l3Y83tlLlWP3x4XjYqGq3YGGTLUdrfgVKaEIw5l7qrFWJhJzdwRKIrHEUiMOiyd32SwfgROFInTCzeZ6ZWQ9OBEcdryhizkclQnc3d6RAzEZGtLCDjD1YqApqfgfutRYzJYYEoiiL3DiTq4PQpkapyWY7QVGzsjtDArmZWzFXa4aZwiIuBKlFCYAB6u5asquQhIKmwA4j4baRuBEKSMkVVjxrtmqk7GrN5qspyRvImk9A87ittjAh2w7c4I42ZM7OxNKsI+rC7eo5GTyPGQXCQvCcqzFCSH0astVxP3dJWFgSquarm6tXVy9k7Z/91sc//4tf7cZ9ZHJC6gK8GfCREDlZVbu/23LfhN7gi0mNWbVsigAEAF5rHaexlAx3MydyEWmDykRU1a1akHB+uhLwtN/X3bQOIahF2CcfPK9ap3L/4tWrjla3r78vmXXWnOfzi/eEOIqcrIa+i2Xc7+5ucvawQgihZqmEIIlZqHWB3QEFTISQYKRZ51w1ewXMfRGtp0N7mMhRK8Bx08UYQZTzPI/b9epyt7sp88gbPHqCfmX9gDlXr5bnXGpVKwCZaVEDEFIiDsShVkppXSvdb6dpP5aixAGkxjmt1ifSrc9hzXVnUiUhsuJaq0aJqet0VhGBeKCwpP6Rg4eqNUXuNysn24+74nOIvRLNeZ9V12tcXCS3OSSEyNM8k2E9dCmy3I+GUiqHyISktU7TlJKYgbj5oDUecGAWETctuUDrFAK6jp0sGgMkHN0XkGGBYrgpS8jqbHj65JmI3Fzfv/zurTgEyFrHyZpBzX6/L+BNtDisUKDO1Qq5U1Ota2QfeggtH/3vDuNtrWd0yN6x+Ij8YOjvYcg7RCtqwr1HrumRxFRrPf7YRir+rlz7u/s/8PHxpmfc0sVDTw3L0ONDcM7MzchE3ZwBt2bJ/ADPI6JFPh2EZpkqYu3nxu73Ix8NWByEHuCDC3PqYHBwSLn8QKeyA2UM3Jbk4pxDDbWlA96+AAqN2PXDt//gezrgFi2TJEZMHWqpmP/4j3/ywfPHn376xIzPzx9n2+3zG9Xi5sbmhGmeVCimeH52UXA9mbHpOqE77SiQmatpKZpRVd0AYmEJ05Tn6hCOFJhjl7AaxIxyUfXW9hQCB4lBhIj7lLmgFr252T/9cFO7kTmW7LX4vKecaXs3ESNGXq/7bhWDyNCfOoq7DF189qxnjqdnZz//xS+IjYOmXiRSqaNVM7N+SBxpu981JxfmNmSoLOhWEOHdNEk38DIUyszCIUWR1JlpdvicM1hTJ7EbYgwgDEPP4dEwxKFL601v6qUyKX/w/KOX31x99cWvf/bTX2IFBm5vJzOM01RrWUianYeUupS6rr+6u8qaEekIJrMKN0lZ4sCBXFm8GPJkOxslCNxDjMJac7GiMHd1c8tWmBaYiYmTJIOxsMGt2jyVd+aYAlrzmCuXWY1D7EzNyCAgEYNG4OrttFoPLJwib+/enqy570JgXw05hFiq7sYpxuQITv1U8lRyDJEjFZujUlUTBlMEgmnIE7TUolZnqoZaCB7gKDOI4MpR4A4rgKPv4mbVn5z0m83a3Uvx09MhBtrt90IhRTE3q5rnEoNE6UvRWpzZa/EMu7m5TymmlCSmqLCKudSQSGGuzfcMBIESlLshxBif+GWUYNVC730AgM1J6NdRUW7vbq34PGUgpkAeHaEWcyKE4MxeK4JgnUDUT3O5u9uFMMMphvDo8tHb21d9TCEwOXLN035PJsOq14JC6sWaaQo1Y2UDyByuVuE0zr6KfYgcNTkZw4gQI5+epcvL0/VqyHVmxuUF8oybm9dDf0pS3n98mid982rX7LxLnbSGmKTvu5Bi3w8S4u3N7u72rhbbdrsQKM971XmeR2Zs1vLsySODa63zNOdaAnOQuBr6XIorkQQW6ULoU7C+JkAgVlCjqpo49vfzEPD82ZMff/qJQIz0ZLN67+njhmDkaoGheWaiFKVGcZh65sBTnu53u+3+zvuhE6TYn589YeYy5/F+bsb2UBKn5jN0qGkBX+x3uI1/Mxs1MWBmIjcSFwIzWQrI59iNewe6PqyGDZgJkMRpbSQyjnNsjPsQ+l5q1VqXtL8NhiiHnEutzTFNcVQ5OoTod+xj+2EgXnZFeicS9IOgfXg8L3X3g2LADhyUxrN1A1b9CmpaazWtUGtAeAMzGNb0ZgQuZNXHnCkIB+68YzQBnAarurkFI6XiiuIFRkZUNXPzZzIjCCl8NsvVJ02xDxyEjYR0QdnN1YvmWjJBiKmJJjT/JwjMfSozMhCpEZTa/tYU6NWrQ71x5khBmHKGIQ5JosQ+1VqnMnX9Cgz3BPFiZTveC7iyIoFEYUk8sAkNTgRScxgYlaAGFzOvWo2LVI3FLOcyz4XdAo06+lwmSo0dr1Pe16yUIAlMqFagqDqrF4TIrGBPfTzxTsy3FaUWNV2UnRgkxMJwiLBabnq+bRgqUHCCUW0EzCUnAayplFDT2lxur23ou3kFNIkhA5G2jMgapwAGWeQuG1/G2Jlg4kCTZGa2pToxWgYdqym0qNc2Sgm4c3UKLBwGtuin5/z0w/Wjy24ar++vb7/7cvvdVzusKNkmz4VWQlCH0mIleViBjRC2eM/ADcS/eZW3HO/BBX+41t8toMM6Wf7xA6iHdh4Y5LzYLFPbMQ+WOcvTULOxerccfemR/XCCciEfkEPdrb1QIKmojfaAQODQhS5P1dq2RK1s7V12r765/7/+4F/99//jf5tkdX6+ev7kYjvr26/uJESRACcYV49aAHdOEEfOs6lKoKHHer3JZccsIiISmUG03e12ZlZKJapmpNXRpLFFY0TTvTA1crz9/hYGRJydnXaxg7tHI8Crz2OxrHAqVT2bVkOhCmVzFlIq25tdmUuZy+Jc7Av/UVhqNHPf7va16n6aQZS1LctEAAAgAElEQVRS1zGr0zSOpeR5moorkYswYK4A1JfRVD/GrqUygDu3j9ABhBSa7bq5O5l6rVbhDvLq1Z1UKiUupFAVVqUoQThRRFyt++pFAkJiok4CEFChSSRxH73TyeZ9dVjRnLezjTDSopXg+1yu7m/VLa1Cnuo4jWmTZBN0wv5m2s1TCiuJqT8ZrMRpmmy6BzkCURBHQe/D5Sr08er6CiThjIduONuc7u+392+3tVRVrbPSFGGl6WLPNqvb0yeP5jJqwTiPKs4xxBjLXKYxTxWcUkIEUZ8kRGh2d2OQlapGqHCCqpvXZSlBoAsubmqt9WGubgCkzWuaGxN5q1UO9CwQDnK9sKUWO7aZls55qx6cH7KzlqmSFlbwQHhuIXe22uPvrTd+eByf693aPngR4kHpd7xPmzo8PvbhNw8HWY5H4NAm8ciqWbVZMzlHSTHFALFSVQ2LdgsdKWGt0nzHAWOC25wzHxkZDxpYLEIPIpe7uxtFbhWkuzOYhUSkGckxUUzBTH3xzgTJQrbypR9E3mxOjNHUEAwKRQYbcyIihpmbQ5aY/o6SSk3ggdhQqlotaBiFAAxlEgECUxtEVHZrXU/TbJ7RhJe4UR9Y0OjaVR3GLC7tkzAsdrpEvIz0EwuxBRYBQR1GXp0CJAnMsxc4nFhVS4aRrQfuu1VgtWInJyeBJVO+uZ9fXF91G3p6/uzsyYpO4ArAKYEIULI23Ro4kDTBwK4LTWrPcJxyNrgRCQkfaKKVzAjNAVmYIwfy4MZFUCSwkHTrDRx5nF98992zZ+dPnj/vJZKVD58//c//k//0b7745f/6B/9KciWICqHa/cvb+X5HQTcn6dHFeSkjtJreTwy3Kiw1SK3Fqrb5WdVSS65azL3r4VyLTrmUatms8d+PmA0tS+aozkhNiRDUx5hszNep008/XH/y2eXJKXW9F1U25GKulRgiYS6lalWDU3RDnso0zcKh73OXIjlC7EwLiVcat5mE03sfPllv5jffjDdjSZgldYEYUDfTUoo6eYPU4Ort6nVyScEZ0zRTMI48dD1SVZ9D8vOT4f2PLt//0aO3Ny9z3lXN41SJ8XjdbU5WqQvzPANFJLijlAJXQmLhGCILm+k0eZmDeQjccRcAJyjxolvbwpNIFAlEkTwDy0bY3JouLy4fP3pqjm++fvHlz7/VCbYiNdvvNQxwYLvbRedpUD+NuEPu1ckXTbaDyfHSIsKBPbR0WQ4ZONDm/g5Byt3xsA1/LEDoGFl5+Yulq/NA9wquVd+1ZH4Y6RzHwN1+OCJ+h33aD733ViceNOLeVSCE4+gyVAm6kPnRglxrWtNBSqs9RFpHhtlNKwAyNPmKtj23JliDHP1A3QcAo+NvjcOr+EGxlR4mesvW0aRWfMm7lmt/Se0OTbgfHg0Fw7vdwlQZZEbzWIeQ/+D//N/+8b/373/2+Y8Cr9er08f87HZvRafdvL++v1PjuRbNRkEuHj/SyDe7Xab7uOqGs00u2QyRQ5MbbWPCRK6K1K0TFYQokogDCSSABbxQnygEAQWAQiQ26rvSHnh7u8OHZ0S9Vtnele12vn475tlLJi0mkVeb3A0xRaROQcUMJCF1fb/ZpLC+vHw2Tve5blU9JOpWPSpIGcKMEAKXoo3dVFVVITGukrj6mEvfdUbEYCFhjhK6EGPfu2t11KmMalUCOUG11FpDkNVq6Loogt39LBxKsRrsZDj9w7/60y9++urX39+enK6CpLv7HcirudYcAiQIicDNg3uw3XRH0U/PTghUS226Kl2XiD3X2b2+U04xzFUjII1wyJL32dVM2wi1enEhRmQmMripOcwI2si5QYQYBDV1M3LRyarNIQ39qnf3ed5VVRBbUQjevs4XZ3a26c9WF9++3Z2drbsuasncA8Z5nupsXefSuv8lm0ESBwk5V7VaqoXQBelBQhygoVYf53z15h4IRB5jCGGRIHD3JsRopQEZxGgUDcl5rnlmss0mpeApDVHifhxl8TRoFtHQ4h4cLrXW1WrdpRRjZJhWnmupxbrNUFTVzRhgQhAKkUymedptx1JLP3Sbs/Vg/W6/H6dtN4SQMNdpvB+teJlhJl3qg7PrjFIhLaAoQzmAiaepmu2sou+7vu+Hflivz/76ixdMmUj6vutWq/WQ8lxKrs173JQrBWsJQev2t7pKmAAWFTaQw7RmnUj7ns4v1k+fXT579hjs+/12mnchkKrf3b81NUnxwx89CxK3498QmTl2002asllmjlZrngoLoLwKG4rC6mUqAqmTlimHyF1KOhsJBYqhD2viFIOT7W5ntTplFfEQyK2uhtin6JXJuIw67eeqFgSmePLsgx9//snnH382brfzbobRyeYE7/GqX+/naS717vYmz8VLGXcjrdeb9eWTk8fEVmrZT4bdftI6m4YhApyz7vfTOE42L7bRC8P2XZXaGPrA4n/mbQadSciIGkXJGYTqjJXd3tyWUiRy7NJ+zLli1XGKUmq9urpOSUq1vhvgstvtplw4kASx2tyHFPAYGMRuVosdNsJDCf1QZ/qI3dCS8x9dOpigC8rj76I1k9OyfWK5GGiRQ25/yAFid27TecLELg1MYaewKAIZGwQUBMFhVqrmWlKMwrBF/G/hqzSNJIN6cCdYcCNFk1RVByFJZGPP6rPp7A1DNjVUIgg7J0aMUSREDrkUkBM5H6yBksWDGoeBHOwkRHyQGV/Eqlzdglcnl05YuFiRGJqmu7FJ4lqKCHMQRc1as5YYQrcJRSo51bl4NBCKmJoqK0WEgUNiE1fUXEs1xUwxh+J1nuf9XCOpQOpk6mVYdykmEhQrWpUEEhECjbND4FxJSkwhJIdUCtKvJdBa9w5xEwMfVKzapyxMQi3ONvyKbIFHhN4NdfqiaerqgKAJ4S/qAQp2yKEELVgwxZZCmWsbSeSAYyVpcCJt8EWTNHa0k9tKEGs0PWNTKh4MCiVrTUqiGmJKqzCchecfnn76W+89fnx2/frtL3/67bdfTN/+ovB0QrKBbt3UpAJKhmaGA1qEu5oYVbsAjssBy4iTH1C7A1LHRzgFgNNiTHnIHv1A5Hq3PpYeLtmhUdZ2xqZh8RsI3iJ+3Z7wIUh5gP780GC22nQZYHBnQTByhlAQ9hADaTZH5kDmxYw5CGv89Vdvvrx681/9N//lxcmjj3/00XYquL+H3AG1kWiFOuUkTPBStdiEMk+GKoJOUtcNIpVJStGSLSZyp91uX2tlFmEozJRYIgfE5LGaVrixkRF41YX9NvchbrohUZimUedKjiCxQJ08xaRV51ysOIq7uVcrgkp1v9u7EupygpZzmkHRwTD1eS61FJSKEJmJmoyFoRqmcTQGRRYWB6yUxbuBDERoDhJ+6EW2WuAwpQFxYmYWdge7sTVxNkpAcoORUOqTCFkLd0wkHKJwIAqwrFBEIg6sXkw99LTqhlVcUYmTz/vtNO5nd9RalRwRHJmEQhe283iyXn/w8fu3q9url7ciHJEgFDZEKWipNWepAEA9Bepc3CMQyW06fXK+fjRkzdd3N0Mn681qNazW/XreTq/fXmlRq+bFdXZkkMMVOZdcynabshSFT3WMq05YFsGjCsyYrYowGUeOQlTFVatVrUWtGHRhULUrtHUUmqq2t7LlIPfWpoR5+SBJQbXaUk+18y58RK95ae0uRJZjJXIAwckXXXb3BzJzx5XVfNPhfqia0Cqag2vJ31N//Ebr6vDSP/ixdYoe3vnvfvP/cwQndmIigSiHVmISCZrToGtTIVwKtsVqgJsK3GIyAuaQkraxP2/qcu2/DtHt8Ju23bsBxk35a7FbZWm/BAsvhrzSAjeB4ID6QpgyhcFiiuSAEfRg6GtNycTYQ2QmPrTtnaDkxYpXq+aCtB6YmEiMCG61tpFXJyFnOEzFIR66IMKM4IC6FVMYu2ZXbhcTLdKT3GjkDhbmZhQAYYosUTgxmtmQKTOTELMwiKqbQamyS9tuhmE91rHU6q7mzSqCiWQ19HETpt0+RrGTGnq7vt4pTRlbSvL805Ptze7ujUlCU4lf3o0QMYcgbQy9jSYxIAthBCmE5p7baFnSgHtrw78cgvSrPqzCdrzvUwwxzGMm8rmqq75+8+qXX62Gs5N+vf7+zSuEeHL56OPPnj9/up7u5JtXd1ahGXd3+zjg4nLz+PJk0w93dRTSzZC6ENxjKWEUneciLIGJ4cKIkYjYvGIAs6rOatoEJhxKbQG3vYlahkUASi5WiwSIcD8ELRPH+b3nFx9+tvn4k0e53s9lBlViNOvXkIiIavVSTQ1Oqortrtzfm/k8dNis+r6PgWFqwFRR7/a3Q3+6Oo9x6PJkYy2ksGIi0sehZt3PE7K5RBAbirujqfL0koaIYPsyknq/SWCvxbj358/XH336/nsfXJ5erP7kz/6aJYkoC9xBgmGVQpLdjlQrYGYKt1rNLKYuCTNg85zv7upUI7GIhBhiTNQlcqhZDUtCz0FCDB2BzXnxv2aiyBLk4uI8pe7mzfj119+++OYNFMydIWitfWR3qpYD0Zz15naHCjWwiJg2R88Hg9a+yFq0vGxprDgfEbAHIQsHxYKlq7LkNP4OcDavXtGErnwhphxeB97U1B6Ev4fxEkeVdxwVCd+1dtwfYAcNBzAnOtQcOOwW7ddaZBlaogmyFoqODbEjdvhOzR0trWqOVMf3bY6wwB3Lo/mAVNniRU6EZhra8rUW95ZHmz04V01E0ZeVjEMaRw+xxYfn+h3KQUfuYtMRU4DCt1/mcedCHWEtoR9WJ56mu/HVmOdfv3y5Wp86UbFCMQzr1bkQUqxssY+p71hA4MhdFwYxOEQV5qr7cdhsZp5cElOwhaGrRBQjxBHEC3vXOGvurhCSFCqMx13e70rNnDOmcbp6M715vZ8mz0XngpAwrMABMWAzgAmqiCluNmfrDa7ejGkVrYY8o4y7vvDp5WoYhjpjnudai8EkCEMkBNaaZ5MQQ+xqsf20n2ZrdVUUlhg4DCwCmjnEWup+HrXMzKxmblMpFmNKKQmLWb25vmYKp5snKfQ3b+9+8q//4v4eHSOmfr06qyrjPDKrkyMaRFVdi5eMWTMoh05STAKeR1i2yCGw5JKnMedSEWCNzstECEws1HQarO5tCYcGbygTqZsykZFraZJ9ipa8tFxBzYuhwKRAAUafTi5PTlJK4667H2+qEhOvQ7ed7vId2aOuH6LP31BJRZFnZZZafc5Va1HHalhJChFJdeIYQooGAiTE5FSFgzuj1eUGBt+/VQRNHQITxSBE6qZVa3EWBEZRlFxKJq3BtJQ8ztPW3YRlvRpSiiKx5rmR6BAMbs1HKogwR2IJwkRoNk9uHmNMIrkoLLBTCIlTDJTcaJqKW3XULoastWz3sWdnI/HYpdR3eRrnMpXJUSHUp65DSGbmMylBtRKQOhGhqmWaa4w1sIQQ3SEi/TCgw5yneQZx7YZVWgXa6ZjnGGIIqWkVZQKKLzwEBtiJnQipExa3Wq0oJuTo67VfXJw9e/bk0aPz66s3r16/vN/dzrObIZfddo8Y+5PTzaMnj2/3r/fTfnc/5aqlzvOsw1CZsb2/dY+CXigFiW7Fiwzr9X7aWeFcK1N6+/q6qVim1EmQUlGs3O9uDFbVYicSZlVLoQtdiJzYeAw5cHXzIHW1xicf/eijDz9Yr9bff/di3k9dHGCSp7nv+/Vms9uNNzc3Wif4mtmYPERZnwwcJITghGnONZe51jSn2AU4mVqZ3YszIBACOx1kfxjN5gKEAyTqh/BHSwbZgAMiwE5OcXNzY5whJCHOebcYFEHyXK6ub4YumSLGXpWYJ6Awk4gcKUugxSalNhEW+jvJeyvgDlZNONJI+J0gIwhNcRbLBne4kQ9mUPTgcIDcfHkPTDTPEx1oWUTEBGeXwAbXJvfhDgHHQOQ+q5qxCJPP+3nZvQjNMJtIXcjFPLpKXZAcBhghxT71UOiklh2ZsxYiy6WUUlg4pijCq3613qzHebq+vs4lt3qmWmUOkoSdrbbW9EGTa/mwiA51mVYrVkm4X3WSwlznGMM476Z5AoOD3N1tu5hijGC4q5FKIBYQkEclVXeoqLfpy4hhHVebQSKp2Jj3RdUYnTkRpZBKqrlWJjLUXHN1GzpZrXuJknXmUpxVIki8X4EFISF0HgeSDiS1qAV4Wm02pxITs7STqQCsdaIJBIQYQNWbsDx5NSMyFkBAgcDsR0EqWowdnBZHLYEFJmECkZJD2I+1pDeqHYHgQv7AVIqWyTzjZnfepvcWrmKrcQjkYIoxOhykbVMo5oIaE33w6eUHH1w8eXZOkK9++e0vf3Z/9Q2mWyA7rUVCKGUXgtLifNkyHWDxvDQcyU4OUFPDahncIiS/UO+wKGUdMimiQ8Z2eNIDIPlgaRHQ7GlbPnOsxsn5XfZzpF8tStWHrllzAmtpKd51tMAFOBjzITQrukYuM1WnyZGJkIbOtRT16IFIdvcFV/iXf/Qnn/27H77/3gc/++rLKHR5Ga5eV1F1VaFAFKIEd9TCUHNYSnIS1y7DsDm9usrufne3n+ZpvU7uNO5zrYiRyVVNtXoQDp1w4BSjEtxEAHENq6Q1xxACRKeyv9tNeUqp61ahT527CuJeR82ODBS4uhZnrhaUDNREvHnBh+GAQatBWgRtY03CxPM451xb9ABQp4JIIpEFxKRNSJQAIsjyiR8bjiwMbh15gqNYFRJnEJgjMXt1NzZKwonNFEScOAzRqEkaEhNRIIqsVsc6iXjCigOXnN10iOvVZhi4m6vO87S73+3u8iK6JkAC92LRn/zo+YvvX5yH0/NHZ906Xl3fqpuWCRUhhK4PGL3W2YRERAIZLxwU0/r4o8v3fvS0Wr36+lXO4+OnJ+tV7EKcp3ncz/vtHBw2wzKgIINAXF2rQXF7ddNj4MiVVCyqKjGZgwOsIs9GKBESWNzItEkbVi1V65LUNW8nOJpLscHRSoG2gtjJCeziQgd7PQKVqgeuoZOweNOm5zbSeyQRPARODpsTHnSvjtVF20CXhwELZE6HrY2WAo3xG3p3f6cPdSxD/O9Tv3p4y5Gf9RvP9hvMrPY1qBs5W3uPQYS5dQqqFjhqyaWYt8Egb16FLMwSgoi0plXjQdZa8zy15z1IL4sTXKuqMbO3biwWLZuFoYCFiV2dl0aaAFgMocDNdxruqGawJWZSlxYCiLm7QtW8mVi6k2oGBQdBRAzmCm+2iaTOGvqeyBnMTuwszounpxHRIoJo0kikYJAZSJkbgdO4RUczJyZvdDdqRN/F/AUEikwRIQpi832Cu7SMi8FkpKqas8EcbubCsu7WCDznClchEYkl60wl9JETM1NKQfrQDY9OzruLi7NIYtl/9NmzF1+/untz1zI6q+YwNVRVCczCIXLOmZggkNaMZTZq78DUHPBm1Wam2nrJQIgg7kMIMaXUMdzfvr06jTGrrrjedel+P3736tXpxcnN3c2LV68vHj9/+vzDf/Ev/vmf/dlf3f/hn7x5CXQQgBWibFO9fv32u5e/vr6rz97bfPDJB07Dt99clzqlbuiG2K7V1KWuZ4fWOt9ub+GoZsQuAWZo9hWt/axkRIflTQjSODEKI8+1qj1+hMfPhtPzWP3++1e/Ykqr1QYIOdc5z0GZ2YqqOZwBErfm02On677Wsp+yu/V9EMhc5zrvh36A5Pu8S3z6+MOLudbvv5+wLSRlWK26YUiKu3wNbl4PDqsQB8MFs+5D4G7N6jqOIxjo8PwxPv3tDz76+HmIvt2+XW82MUo3REnjPBdmmFURSh1rlVzU3HhJaDlINGarVWsuGWpk5o4aondGQZIE9H3fJdFa3aHmZl5rzXNVXWy+g4SU0uXl5TTOr75/8/bq9ZwRA8fYOZHBQ4zVXeJq6NZzzl9+9SsMMAczSWRA+dB88YPjEtDMBBcErcVadxwMcx6EMDMcMNgjOesY2pqxKcyb4N0xEh7LkmOMe8AGpXeh7Rinl1twZDo1fmgzfljmro9JVMunmyk5HXIvAlNr8oKPz79Y/LX/85b9HON7i/oO+AN88fBO7fgWWppa3Q7cswWtane0d420hRh8COft/cL53Rxhe+F3p+aHuwKAIwMLy8VuVh2MUgoI33zz4rvvX33w7KLrN1bHPq23JTnk1y+/P7+oXd8ZnAqHIQ3rQYUKqsLIPUkIIUYZIneoSkTmPhcF5r7rc64UA5Mbaa5gpn6gEJJZDdFprkEkG0rO8zzXWolg1fdFW+dinuzman7zev/mTS0F5DCChGTGVjWIsEeBqWre012p9/d3uebHT86lc4kD2MzmedJAZuq73a7WEjtpW6AEoRDU80JCIAB8dbMnMBEHkfU4W0WfQplnZgZTLnme9+RtC/I81ZhWKSUmuFmXkls4Pb1gSn/x53/z5dfYdOzm++0co4Oi2RSSUDBiA8PMihmKAnuQklDRHJznXa6j9aHTPuU5T2N2QgjEgRphvGV/SYKTKsqk9YjRCaiVLLVWDiBmWhrJTEIG0kkVFSQiPRIuzh8Vy+5+MqxPU5+6kGiVgs5zIIaAq+v+qm7XuqL+vPvIpjrnHTOndap1ZmYlzSV3fer6TiLm3PQgaVgNRIE4l7uay6yVHBSDMckiCccIESEiSBvNpdlAjIWWVwF44OaDV8lVuKliFlAyLVbqNI5EkudMRgBion4IXSegROy15lImEmZKfd/3/aob1r/48lvhyBxYUpAucpIQLy5XUDNzYr++utqP49X19c32fjMgxBRTl6d5yp4YHhDIukgM0kqVeKooFWbWD70E3+/yPLXPgpm5Vh3HsZr/1kfv397d3m13znNRcxcjXZ8QgxplQ6ux2jKibMsiVzc41pGAyqLdClPEkwu+fHx5eXmRUle1fvfiu9vb16XOaggBRDrNd9O8ZdI5dx9/9vT67ubm+nbcbwl6dYuw28cQYMHU7rf3daYYe4mIIw1pXSdYlVprZCbqtfisbtWEq+rM4ierR45qZBLYWU1LqUVrWa+E4d7pUhcHPHl0/vTp5TAM47i9vb21WTXptK/XN7d9v3789Onl5UXfp/1+9+TRk3marXrR+erm6mnfhxCYkHMxkVJz3mmYedUNrcpyBbDQAlr4JmJngzQK6qKK6O7khKaN21i3raauNKy7D957tBv3FCrgQz/EuDtZAS5VUd2mcWIgSlLVaZpLqdClC+DuqmqlqiI0+YXsS/fqHQ3lsJ/4Ut8ffl7c5R/m8SD84JbD1nAM5Aee8SL/Ie9uxLSbG9BLzTNyyZ4PT8MCtpbSE8NbfRiEDbnujnsoE0hcGMZauTigVAEgAEQh8jD0gWOZahlL0eKzbnNjjlRVpw5wYoF2yqAogeGAEWlV1GlmKk3MxB1gRAlL28zbyOMyENZagFUrBBKDs4Mp9bGgM1jN1czgVY3ECNK2XBiZRE7CczAjQNF1HJM4Qbq4Xq+6IanrVMfdTkOABIQYUkrSRQ7MCTBBodH35lCvIYW+T71IV6E8U3DAJp1jIo4hJOJkoSMOXnQE8XoldRUouYsdNcicXBuE5eDADKpkZG024pBOMLxJ5y8MaQMRuH1dJvNC4CiLSBYRhMiIFIf8RATCS+8Bhw7o4Wqpc1Fogy9cD1LqARyYA6kpgJAkdQFkaqrTbBlGioSPPj/frINafvWi/OzfvHzzHSh3SWIupnmOPU9FvRo5zBY82Q1E4ZB92dKvW0ghi6B0I5Y+WA/H4wdV7ruvS8qHd6aN7W7v1Kv9mBW16vLhcez0+YN//u7hZMyM5RNr8mOxva7VajUzXH2KwiQGylUBIwocONah/Ms/+tPnnzy7uDi/PD/b1/nx49Pt9goOrVCrVr16Uyg3EFIK3UkcpKvQNKyD3Knq/Xa6v9urptPzwZ1LMbdaspUMMzDPw7pffD5YqJnKMt9d33lFtbK/3zK47Ge16pLYuU+9aq1j1bHg0FjxNkvgYJfWeXx34h3MRAL1FsqsEelTTMRcxr1tZ1RQAIVWrzetMefmRWOoh47i4hF8yHk5NLOaZlqEPJewmDa4xBCikGFGhpgRezB3VNI6FfXa+jHMws6odHq6CpVT5LTqup45eKlTYFl1SSB3826/30/7DAIiji1KUwfZycXZm5s3+zJ1OVECnWJFEIt3r0rdV6UdQOgMRkt/ofWPeiDgo9967/Gzy9evXs0Y4xrDGbG5Wn3z+mp/N1KBsLBStWoKNmZwa60rmaqLcEwJXgC3XIuZIIQ0mGud8lzUYLXRedSWIkKXsGgLpEFLIXHoULkfgRkndjjxu7u2TnDb7NwJ1ByqFnT73b5j5DA/blzvlsPSqKIDvNHa54fyCQccyI9DKTiOyPxb19hvrLgHy/x4i4gc/Qr/bQ/8wb754AiuKG5itTXqJLBATF1zqaUwXITsQEU4SCovw4OqtdbCxKELIMrzvFAbVA2IMbp7KdWrmnCMcXmgWQHQuPFMgDeAVlEJzkxmVkpxVWZJXWdE1jz6FnJcc6S3ZTnBrCoMEHAQcy+lQJ0TL0Zm75ABANjv9iIhMENNS0UxavzrVtyCmRnONikYSgR1q9Dqpmjc34UQZq0RRMYLWcybr2IQjoIIl+aG6MIMCgX53VWiVmZ1B7wioJJ2RbFoVLFIMsWkpWYdtyORQ7XvhYNvTvqzx6uTs1XeTSFyQHpOT+/vxv1N8YkpQoydQdLECZSZTZ3cmyVaM3Ikp6qLyKIbXL1y5UDMboIoCEFCkBDCOqzAWnb56m3pL+C1cOTb/Xg/T2OeMMmLV6//5mc/Db/+1fr0/OMPf/f3/+Pf//3/6J/85V/+7f/zf//k+1/dzrf59XgHzRdPV+ebdZdKHu32+uZ+++pXX11hBkK4kgpGjNiswsnpiqNP89iFWKsZmwh5gFYnI0bzXwM14M7dQcIUQ3N8VGKv8H/8ez/++KMnT97rq73djt/Hrtai40hd2rijZDVXdyehNAQgVSUzComGTUhppTbCa6tg5ucAACAASURBVOxXJ6cDM6Z8X3bbtArENuZ9GIb1xcnn/cdP3ptf/ur19mae87S/2WMLrDgAcNNanZu3Fzmpw7NCHJIgK3z2+ftPPjz9+JP3Ly83TmW7vzaU09MB5FKZ4FNgh4/jVs2aJnFghnCt2qSrVM1MhWW16s7P+c11mrPux21VpA7TGYYhPHp0vl6tVev9/W6/32eutdJ2N5UZqYOIdF23Wq0uLx//9V9+8fWvv729Q+rZSgCJurGwMRfT1bC6OLu8e6E//eu/xTrRlhttpmqBcKMsvotH7qbelkgD23wZWPQfiqyjzAWAH8JIqzr0INkO4OjnQMQPe1XtqR5EW3e4kCyWTC3SHUA99wdqUW1npaaYsAwwBpCCFvEG9wOU6UtDqL2npcaACNwWmWW865qRWUvHmzYgw9sA4Q+ypvarg+Dwhc/F3Ka5gOYE1Gj3jiNQcngcloLWm+EtmOBgO+xYh/f8G5H/iC8CIF/cW9u5NVMUpE7ubws6/O9/9H/0Z/W//uf/xfP3fvT9bZ7ur9S9O1ndfPP17ZhX62F1sg4pDOyp71NKJycn29225MyByax6gURRwNunCdU6jdM4zmJE4mycC6BOjNU6uQdmAjTEBEKtpWQ1a5sF5wyDmIf9bry62l9f1zzDPMAYBK3dblsMhU/TTokM06TbXVEbJwP28N+Lm7P+4tFqtR6cxly3t9f3eZ5NPaUA4lKqwSR0HNhB0zSOyCAp1XajmVopcP3/6HqTZsmS5Tzsc/eIOOfkcKcaeqge3kAQDxA1mMkkLqiVaNpyIy6ljX4h91pIJq0gA0EBIAUjSL7G6+7q7uqqulNmniEi3F2LOHmr3gOYq7x16+Z4IsL9829ADNPt9uFiM1zuusv90HUy7Dr1XEsWCQw2JTddpqX1GL/4+h8FTtcXn7z+7v4v/uwvn/Uw9mlGRsXjcVmsZYGYK7WqT4AIsIDCdkuuiziLsaWAqmo6jrPDKFAMJDFUs+Zf4KWoiHMIEoQJYRaDVZC2koOcIAwmEY5rFwXSrG4uHLuu22x3u90uDd2w7RZd5mnMy3z/0xsiU2jjrHOQu7d3pj7d5nLIx9v9H/3xL9++/2GejheX200alnIYtv1cpqVM1ZZt6oe0DTOfjsdq2nUJjlJKzrkWW8ZaK7oup5Qc/PwTdH1IKYmIu6taFPQx9MlAXjICY7tL210XiPMywrTvIoHLMrNbXsYy+/EwCdM8OWqJkXf77X6bYmQ1ayMnohBCRxyBUGutj+OL6y+WRU/H6e7xeP/ww+FxwXLOPIr48rNPCdjvtl9//etPysyo11eboQ9Q3W7GwJNmF/eYVEj7UjPISlSzOedSCkuMISLlGBEkwDEfx/tlNsLVpy+uX2wINs3H0+mx5GUzxBi2y2TzWKwod96F9um3gPLViI3gMSIJ933XvbiIkV6+eLHb75FkPI2H4/L+9scgoe8jURGBeWYRJprz4fvXj69++cV13Fw9G1KMwvGb//jbuvD7d+Phbp7HuRSgAD61wTF7GE9HQ1Gr4v7D7w6I2O7w7PnVzfV+N3TzMr178yMHjokkonpu7XEXUXVhINepVguEz7/84sXNTR/D6fFxfjgJiES01MZ1n6dpGqfUdbvtQNAuilVe6jLPOVe/evYidJEpLUtO2z5KmMpsVti5Lsrto9HGSQXYGWd9N+FpsognL2eHagULNYMsw1zzy8vnX3zx5TTNRrNT6bphf3E5jX58zLVWgtTVmZBqKafDsWgFoVnnxSQosFyfNl5XtAnr35sX4+Pdf+0hns4/rCcIP8Xkru0C2VlGuv5ta/7bQm7HwlpsrqQvYrAwhJ2bQwSxcCCSyKXNXN0RAlICs4TAau6+piIyGBCSwFyDW+NQmAMIMYoIE4UYTW0+nmqe3WGGsgDBVjzRMetihFzumoc6s1zs9gbLpeZSci4OImcnd/bQd1WrVjVdxzsCFmESh8LcsWCZFo+uOKccupla0RxT19y2QgwdRaWFgkuUzbBl5eW0UEUU4RhB4MR934N8Os2Px8c+QSJzgJmO4yS1GmlK0RQEjn2qOXNgkBKZREIMnIJ0kEDf3f+cOpEkLuZeJbJEIkFKcbPrT7d5nseqBRGoBHGYU2O5EKz1ioCRswhBHPDm+gE/exU3b/OW7IzVIgAQJ1erqureOg8XttYxCTVoAGYk3IxVWk3RGjQjBc56BSaEdY1IZAlBs6qakikpCC6IPSPa1eXF9Wf9L//4+eP9+7fv3v34t4e/+cv382O4jDsV4Z3O80GDk3At+mH21/prr2sV4r7aeH0oRJ7EgysF8vfXyfme+xNzq8G/dHZfx8dkkQ+P9/GdP+x7Wx/+pP/xlWv08fOhPV0QM4N5cHdXwMiUXNthaKBC7GCdq2YCBzIzVAl92u3k//t33/zFv/7L//Z/+Ce//vWvKPHj+NtffHXz83e3i8FyVecmXMLKGiUi0loP46HcnzbDplQbvZzmpZS66XdlUddRzefZlhlmMMWcTxIRGVH6wCIcQhcf7nOKpEu9nx/7GIOIes1LnmjadD0blmnWWmGAnlPPzUVi5ATjVnOD0KyxWQIJsyuiOIg5mlkIEkMKvU5LJVYJ7PDK3sIKXZu+UUhQV5eDNk8At4qajEjcYV4da66omp6V1JFDYIBrdXJiSimpK7FJDDGkmGIMcbUZZ3r7+g0K5g5KpZu5lOqE/QW6LqGwluyusaMNJQ7BzJdaqikTk6S//jd/jiDCTqNt+/SPf/N5onC8P/abaTnpcvBlLAHR1d0rC0F42IdnL68un+1216HS0cL84rMQojy73oz3evj58O77e0mAwyvgYGVUR3Fnb34OIASmPnYpJa8NgoBwEjApiFiEXd2KWy5eUA3kOEe+Qas3Z6ozvdGB1Zp9BZlaKnRjXtbarvh2fTO3WJhGHDBqllJmbXvRFiVpzVoXROvCaF2Xmz3Bj0QsIq4t6fUjjgLQum/Y+f7fP/7+oVujUP0BgLWyqEKgc2rhf+7PPz46P36EEBHhbkruRm2EyhwCubk4mrUY3E0NTW/MTXxj6qhaADPSNTonSJMPVXNHBRLgbg4F2PjMSGOQmVGglYBFK2e+sbNdxGHNCZ7Jm+yOfEUO4eSNgMMrEuyuLUyXjcg4rhixsTI1P8mmJufVXQaTQmBNhaHq1Vrb+EHCA2Ijy03paS29z6qhIlJzsmd3JSMHOZnTmqqmVLlJ8ojobCvfZoQQgM2ZDEoOM10l2IbG0MvLYmIQgrTRImupc3WrZqWkTk5H7YZE0iiOR7elD0JSL57vvv5Hr77/Tz+9/3l2QhBhMEys1lodzayrNbHtsGrUs3Ygkis72OGejIRNNinFlIaUhiSRWVItS1V1hoceoVMqE+rs3F09Q+L7eR4Nssw0j69//O311e5ye/3rr26u/qf//j/9zc9/9823//GHH358O491/vSTtN3tbq42udjh/T0MoYstEbTl+ESJm80mdZxSmObZTJlJmImhVM2ZkYioAaZA81VTglrJDosJmw0Q8Otf3bz8ZCcx396eptNJ0BlVciO2GIgpkLFDgwBR3MVWjzNn0E8/3ErExW4b4w6yJZYUu+2GtVL12m16SZR99CCb6/hFfHl8mO/eH96/P4KAbDUYCAhggiSn4BRcGbWiGq4uh1dfvvzqj15dPtsM2+7++HD3+HaaDoAaqZurqUFDF3MpZl6KLosGodB3IYrDSdjhuRQ35z6mbrvd4/aeTee6AIpsmBJErCpUwRxLUa2Uy6KVx6MGacRzZg592rjzw8N4e3+sFRJDARbNKNoN7u61Vh52/bB9xPjw/pYjM7VMCrg1ywZbJ81ttkat4G4erq12WSlApEyMpwiKdQf6CPBfJ+XuDY8XZ6XfT2A976AsfP7DVvR8gKmIVm7hxxvqB7Le+jArkI910uDrMUEAmbfX3OooPw8cAMCJo5s330SiBucHchC5WdtAidZoUthaUq5P2dL/1ik8nWOihdkEZGA0lz7/6EUT1v2NRNqL8I837rO14pOUkM/EbXKHNR0nDLy+KQBMK82W4AEhpsxT39PffP/DH/37382F97vrrtvn99Bqw2aYpS7leDqWq4CNbCOTlkIMppBCX5YiCFBUz8oukEquHFRAIRBvBSCPXqmoAsjaGKw1BMlllhBYQopdUVDIZA6JYEJd+n4/PebxlMdjWWaQhy7u3JtfIZeqMJzE+stNF0JKuS9zqVVgC+qSXcY8bAIH6Ta7ROE43p1OHiL62LUgSiDkQuxScpiWZq0C5m4YurzUkqeS4RUzEL1e7TZ9v4nR+z6plpxnpigcwXNdsrmaogsBJXabq8c7++Zvf/7mP+QQ0zxZkE4oeDHRyoHh7pX9fK2FyKELIp1ZrpWyZhSri2NZK3wGnOFOWt2KURcQPbjAUEslEQL3XWyTWGvriY0ZMaaQgrtnbe2PO4OjbIZhM2z7vg9R4Lh7cwvXaZnGaTRTEoBUyTpJQeRwu7Rm6Mf3x8O74x99/ZvpXpdc64A8OcVeYgwec+ZSKIR933ciaVmsumGuBjpNS6nVnRVs8KIFlUn42fMudYlZqtacs3qVZmabuBbNM1LE86vNsOuKTtM8uaNLgZlZYksbNatmgDu3wHd2jkpRIZkkE1HfDUF6piEv/vg4PtwdTqc6HQFnbfnURdnhATEGFoQYrNg4jof7U/f+rnoeBtn0n758fvn8ev/q1fO//n//NYG9qnFhYYoWEiJRrVqKmS8EdB1EEAJYrNRlyeM8T0bgB3rxybOrq4uq3cM9ncYHOLmpaa6qUiARbl5ncOO+iEeRICGFyLAQsNvF/Xaz3XQ3N7tu2I1Zb+/u5vlIvmVG18VhoKrzshy7FLbbzsze3z58990cYrrc73fD9dB3N9c3dYFXef/mrtwDPYSTnioUCDjdH+d5BMgck1tMYobpaG/L4eHd0kJL+03qNx2EFRmAUHVUAsG81DLNtszwilcvXvWh80zj41xH6yUFplwrS7i5vFGiUsvxdGTC4XCc55yXxQ0hdv2wrWYco/CwLFk6EIcYeqBadbdGnIU1pSzgzt6GoI5G1/1g627NVoLJATU2b0UaeZUUL25uHsdbs0wBJDHFXjiYLSUXJo8hugdiYWZTC8yIXhcX5r5LgQXVVTWlaAZdFpy7iTaCOGNAhA+983rmrESb8xylTV+aH7XDwEQOMJohT8OivbkloPUcjYfapiZ0JtQEDuxMaxzvinEYJMSOzE1dG7e3sdA4SJdS9onOcvVVh8UUJBipqYMhPccYtBRnVaW81DxjxUnqCrgR4Np6HhQtx3JA5Iub/WYzkIga5nk5HA8QuHvVHEPi4JxJq0MNBiLiwCtnjNcpsxZlCV2MOpsuCoJVF0TAmJ3Zg3DcDiZxqYu5GhsJEss8zYCl6CIhdKRxUdPJprlgtw9dGACpS3mYM0uVzruBG4khhNRtOIY+u5XlRMUoWidBKHIIhRDEWNzZQda+ZGZJKbKQoc5lypZbkrsTIKDEVECEWs2ZwLLSuwM5wZqEUBziYFttZ4AnX8s2oa1qcDdDtfVhmVyEtF1uq+uQucgqDm/WocIi7BIAao5/YAKIncl5tdNplsHVaquHohP7tsf+OX/66uLlzWd1xA/39z++vj/e1aixkrJRClLNLVPoOjNxqs1Enp7GcwS4gNo3uw7sGgABtbOzhJ+rsI/WBQDg3LrSh//z4fbEOwEItDIZ1wcigq1agJXp2AyUbEXNXOhsPL2CY7ZSWAB29iZddCMnInNUAuAGNl+TFKEOX+CClgRiboZAFA9v57/6s3//J//4N59+/vlPP/6QuMRNPwydLVY8UhBJQWtpbyWr5tGO0/LT28fjsnzx1a84miTn2hDmGCQO/b5UsqoTjVXVnHRyKUBiTh6YmCFASth0UhcsU1U3jpEs5FrY54hAJjAmYiYzJpiAHMzEwQHppapCPnbAd/ViJAJQEAkiJBSYEzOJKKPAHVqs4elk5sZOADGJB0JVdUXjTpjDvJl/NzzSWxbeCmICIDd2C2aNucKw4ByFDRDKXhkaBM1KWKuZW7/hXEwiUoopCTNVK1aLlkU8pMRDL3XrXrLXuiyaKwiwalbrZv/88tObbrDT6fbt3bsuYkjD9mb7+def9bL98ds3P73+eR6nWkCErpN+u7m4vrz55Pr6+fbN29eueeb56sXFptsxIvF8OhzRpLfqXpldmlOfWlVXwBEYwXOBrVaMQUhAElo+TtuxJCmKmxHYHKxKrVlnArHWfGYcrY0O7Iw1NfTKz5wnh9LaFbQFEYjOyNS6FtaBuhmIpAEnzZzlvGw/KFuefBrBvCqc5cxPbADZmQWGNTuvQfFOZykJPgaJn5bvuaf5qIXx31fPPP348b+fe8Q/VBR+/GPYhN7hCqu16mqfRMyc+s5SLKXU2iLkV97rB6TJvZG3DTrliYlCFwD3qs3tvtQFAJE5tY8OWiuqs5O5rnsYE8mqFjD3asYwANTY0rwKBVuyXhtPGKCoTuZkKzOruWUBKCYpClP1ys6MoFa1Otg5tuBIQjbAnWpbYGTk563V3cDEplbMQA6Im1tLwDUoQmSoQ0HWMikFAQCqqZOBTM1VTSuRkICxVilwQJKs15OtnUZTDUjk0AeqbmZ1yZIkbTeddFMZ52Vp5LJ+N0zzqe83Ero3P9++9p+fX28uNvTs6mbY8Ze/fllzcbstB0yPuRyVjYS6LmxcPOvBBU4tpDdAG89TW8fO5F7NSXVSZpIdhV4kipPluvSxK/DiZdhxCdJ3fSmzJbbUWddXqrtn1+HnH00zpF5ehPH4A+WHTbf51Zc3v371y9ff/vL169ePh6PxQl0d86yO/eXlw2ZaxjszLMUiwSpMobMu42wq1epagyrYyR1eoIsJCbt4UQW71pQkBBICiYWAly93X3398vp6+9lnPfN4f397eLgPIaQk5EteallmJiajGPrYd5lOcz1pddWoRfNUqlJecDl0IfbHY717f5Cw2W3Cdntd6nw8HUOIY50YSwxd6jf7Xd9fhucvr/4rvrzorn769qfjePr57du3D/fmsOAh4Opy+/zmxfOb55uLGDfU75Inv314/O6nx2k+1boYilm9uEoi4qCsp77f5pqDpChBuKgWEEREhAEYvJaiaiSBODpoWeZaTWKkpMTGYHgoix0O0267mac5hljmqVY5PtD1TSMSc+R4ffns7377/c8/3U2lhC4tlZB48uyaO4GkBGIHx9hFyaZuOTOFShYdEmRxffLN/LBlMc5y7PM/2lOpTNBV+9boRyt6RWDBamr2tFu1bIwnGV0zw2pLdFX5tT3b4bDmM7niTAABdsZtsZY6Hw0CP+yhipZgoH7e6eGOc0XtDnaWVicagOjeRKd6dh1hJji0Kf0dDVdqKL05QOQQZiEz4xaVwdKoqw5AiIlXG0DgyTSrlaMr9NeQhfbFw87vrlF7mYjX9+VAC9I5T1Bajcht6yQ3oqZBBREoQHScJtmSxGBjuX2Y3t6OPCSzaCpdSN3lljZBLE7zpNO9JTzbvJzH2bLWon0cTnUksNZaPbtkoqjulaXAhbo82zyBSuUgIcjlzeXD/aOZxy5uNv3t7f3F/sZAJVtRcgoUSNsVE7DfXv48vxlPozsxuToxsxm5aq0IYQBF4ThPnj1rsZpRCxlTSLLMdclj1Uzv7Nnz/dXLrfmjM1cYJOW8SOjd+TTWUudSvKiU7Cy0GdLF/nqJme1x0imwdQLXEkMXQgDqOM3mbbqTSGJIrqpVq6l1w9Zy4v7ih79792/+/BvL7h6XsYSevY3nBFTbzIutQrNyy2clMGnsB5FU5lJrZlEeyNWsEX7XFUUc2KDCoY+dm9VStWiQmDYbLebEhupVwWpgCRz7UEoRITAHEelC3w/bzZ5BWurpONdZp/vJTYuXarXZ+oCIhZY6QQEP8NU36/hQx3eLTj70e3J5PIxp0xelaebjyI7y4kUPSiQau6FUHeeq5rnYnE2YYx8TyJ2JiYWGwF3PHDgXKBdldzNI7QL3XbdN3Kf44mYngxymZVmUOEg7h5XGY94Mmxhps6lu1Pdkbv1GJJEkDcnMjSFmVhRefDzWu3f53dvp9rFGNIl0jCIiHJzbyiuLMqQupYsxz+Xx4bYSyPvT4XR4OGDfM8v11YvTaZzGsXghEkoIrpFUa5Y2EJCcQuj7TgSgpejkUlMPdczT4+M9C2vXh2EIjpjznEvZXnYX18PpmN0wjVUn6AwQ7babTT+kGLsuxhCZPMbQ9yGlCM5jPj0eyjjN01REhsPhAZ4+/fy66nI48rCJL15elDofxoPVPOVaZptOebcdtsMm7baf3nz16cX87W/f/u03v9O5kKQQCwWr09hxNEOpfridCdw20WnUiSZEocg5m1WUjobt0PebqqdpPNWMQLlL8uLZ9dBvhtBdba51VB29kLJyyTXGTtVPx/Hy8rLrurv7h1KLiDBx1VrVcqnRCTExy26/324ux7cPNM6h23TDxnXRojHyaFkVzE7ETm5NGUVN3e0hBNVq6md3chEih2vVwGBQDFYUEujqxbO//r//GsCwSReXuzKb1mparYJEg6QQexEJnEEWQnC1qs4ttCeAWUrVdsy5I3CgVlGuw5GzquI8siai1QXJCK36kza1bSMerGQWdqLV8ng9QdEYLXo+0s6HLZETdUO/Bt5xwwwCCzgJwZXUGRKjLotrRYCEliVUA4XQB8gqVoOTO6o7EZNR6mOmGnreX26J6OHhVAAvVFXZuaHnWYvDWUhY3AnOBkVBqebRlr5osWG7CX1PrM4UUjBUmy3topaCYFKtdSdkYIZWr9kgLEGY0fV91/ehCw/3DyWrRHGFkxrZsE+x45h4t994VJxsytNxOjjh6mK3zEXc+igpEpLVUCC0kd5ZOvSsnS6eTzblWZL0G6AUkQCHKkiiAq66LPNUpmHgy7CVTli020JCkBhiF0kkL5VK1qLBSee7pdCYT2MdkcBECufoIuTCZMy5uLWJkoNN2RCMYpsjo7I1znc71mn1viQiJ+Yl69MXvrZqzBJEoNpIW+Qu7qQgduZzgK6CATZmVnJTiykBTCZsYcnTStMQ0qo0E/eUOpaOP3/14qtfX//iV1/MhzDdpdffPLz+9h0EFMo8PVIR8kgSxdgXYgmOAuR2PT+RRIRllW/500s3rMHX69zuI8nS7zWlH00rGziKtnDg59+snfWTLPC8GkBn77sPU0MiCJo5tBMLrd5k60y11aeNoTXPSkziIGq8ISImhOYERLkqmOEgsyANF9NWwrpzJPl3f/XmzX84Xj+7vBx2X3x69e33t0GSsyJEQzE2RW0k38pcFhtHunuvGfH++NgNbGlOFSFYn0IXOlYiE++Qa5p0JhTTSuQSUwip61KS6Ib9vnF/FIpp1soZkShySgNRkCCb7VZnt1iCiGc3hiSRmDJs9+JqznPNxdVgptnUqoiIQL0Gpub/GLahUhnLUmKBrN+kRBZiCRJCAFEt1dlCZKtKhmYRYOrsxM3o1WC+ihQgziIQ8gRKTKlhj4FclbVLQy4V8H7TUVASVM1WKxQECgEsCJICYpAYQwpMV9u+l3Rz+ezV9avHu9P9u2NZbD7Ob35693g8FIUZsCDsO5ppzvOi42Yf+w1qHUuQ7iruhj4+0hX6gB0UtdRZDUFytPvpOL9ffj7+FCIxdN/fXFw9e/279+OjPZ6mtIs6mmVjIxiTUjNqgHiTXsFttxlSiEQsEKYgRr5oKeYZEcGzl0lFiSFMAFzVqrqgMosoHP400W4iPVq5UI1VSe0SbyJdP+ceEAhLQ7fPK8SVVg+SNsmHm6/g4vn/EDU2M9pQgcDcDhkH1MX4bE+3nk0rVb/py9oLoA/bFD6+j4/ted3dmYWIGj8JZ6CqlPJBQHOe8dBHbllPjeHH/OV1VzRT8Bq/ZIpSslplEW729YEA8roayRgZgRzUkGtJQbURR9SEQ0wMVNdGrVLV1olRdAlrKKH5GuZq1ZrHZIhChFxKE4KCFHjyG2cQrO3s5+3KHdUUaGTop31s7UnVueV9BBYQmXO7Q04wbji/uZsp3MEQEQHRanJFK9bvbWpFaKRsoQAhobKUtpLZmElY2BjVbY0fOFccpq05FmkCdzOr3ktHTMHF3FkVRe381bJzjImoojZvXq1eRTh1sQA6KgnFLlbVcZpNYaBxmgKHbS47+G7Xvfz8pkv98qg//O7d7f3Ra/VOHGxaQxeIW7lCa6AuO5pQHQKYQlu/n6vXw1zJOnb2qqghUa1Zqy6joU60rUOg7f6y324lyuPjw2a3ubjaCeF6P+wuumUZ735+08f06fMvXzzbvfzi4uWXG4iXPL67v71/vM/FAD6dtnf3d6a1H7AsLYwVdcl1tq7bbIZ0OmUIM8Sr5GoB2czhmURicBHURd0yIWw6fvHJzfXN8MmnF5+/enFzs/vp3Telznd3d6fjfbdJw6aPEjzwUnItXt2G2G82e3Euc10WhRNzMMvHgz5/0XddX4vevj883GdIennTv3p1EWNk7k7zMde822yE65QPxZcubK8+vX52/eL64mb3Yjg8HC7ebD87TswBEPUce3n2/Prm2bUEP43Hu/vH1+9+mHzq+6SWl2VyyjHwvNTrZxfb7XboWYRrGVvSHxNTCARhQoNSmDnnUnKdkVWxZDpMB+Y4bBKLmy0Gn+YaT/MwdE4cY1T12KW2FrWiVsQYLi/3L188/1f/6n+/e1eIwrAZSrbs3g1C0SXU7W479C2ZVEWYiRrvVBzuUHPI2ebpDxF3f5JANDISreOvJ66phxjWet5tDUMmhqzoe6OSqmrj2J+TT1dbqKdFTwDW1JMP+P1KYj9jS6ZtWAGms4r8XEJ9RMJ6Ij99JPY411F8Hmye/UnPLoZooQfeZqvsDZdqkkBeNxFuf88SpMl3zzke9PQ+P2zcTyXauYhjFghV1XWaQufpI69oQ6Pxo/+M2wAAIABJREFUursbXOHGzcmPnMTduAVxnEdt1AipvrZN7G6oaiAcjqc/+3/+/H/+l/+cKGyGLYUtRd9s+uzBLZeih8OjW+1SPB0XV1U0CglVVYWzAHBzL1bnZdFZQXL/MMWE3eXFMGw7eMnzsiwpBWaextn0ELvh8WHMpRBLO7+JJcVhXnJVlRA3Wy7V7u+WeZooJASC0LDrWSzn6XBYzGqZKwpgQAIKrp/Hucx394+5Yson7j4DRYCqolbrut6MjlN5fBhrNWLuutR1CYAbxRhiSF2QZYikmVAEJCJaNZcx6+zIHFhLZQrQMk9zAC6Gq67b9N1uOtXHt8vf/M0tKgJPEmKZKxgrHkrmbM1qWkRYiJ2smOqyvbxcpuxq0EAsnaRAQk6qamZQylpyUREWaXYpq9+fuW37vbCFELreSi7zPHu1bKXOaqphCKlPu912M2xjjIwwHaaH2/uHu0fMq/k0Itrq9jbFms/BnQRiDhBzL4Qfv39z+fJiuOLZH8dlVMo25cNhvj8eADx/8aAYHPM8LyIpRLal5uzTjBhq3wcJwR0tapaDSeLtbuPYdFMcx1nVmRhqQ9fv+m2gmGIsyG6w6o0LmrMdj1kEBEmpu7jYhRCI2F05keqJCDEEIPRpO59wdzu//eHu8a7Oo+ZakyEEdDEMwxC7yESqmjXP8yxs6ksp2G13Fy8uzS/zssz59NMPP54e7y+vtt0QPv/01ft378mDVmOSkCgaq9ruYuvu07SUXMw9Cpnrkr3rZTP0qmWay2EE5OAowyaF6ASLgWJIm2Hou2G3LW40nfJ4mOuiMXTXV1fDZgNDyeXLLz7TUgAAtizzz+9uDyc9nuw0TrUWYozTbCb7q03saH+522xi6jqnOmz5+OilYCyn48PpYYiX2+uLHV1fbq9fbiFEgY73i5kPQ1zyeHf7flmUV6E3Si5ryUsAIA4B1Vrfvb3tBvlq96JLsZ7AsAD0afjk5fXLl8+vb64uNvvTD5O751rGabJSqaJLsxatlpe6mOXTfBCRlOJuv98Mw7LkUm1Zyg8/vv78i693+83uYguGWvVcRDhEOVe0cIY5hGB0DoEFSIglxBBgMC+rKRAzg0ot6+UsXrQshq7vt/v93373/dUQP3v5mTyTYTOYV6CCQeLERmTmVKyAUNXcHAw1VVcIcaA6q+eFRRCxmoiuJtAOoebTSYR1grnSTGzt9ZlWwsiHEtPRyPEAEzGv79fdzagpSppZ8upgAYc79QSHorZBqgRxcbCnvnP2NovtZMhlNnEyqJVpHJWlagGj6QFhTq4QsLMHp8CWbdhuL68v5tOcs6tnLLCKCAkUHQYqjBVBXC3bHByYEpnp4e4IIF/W0M9ZNddMARQdAc6WNQtJ6AKYPLsuWmo1djA4CguDvFjZ9zsKspTRZ1iL+A1eDS7qDPVFNUonMYTT5AT0KW3i1gaCYtNviHyqM9hTH1OIjLrxi8P78fR4mscFBIUuqO4WgxN5LqoV7kTC5hkM5uDwnHMpOgx9CDHGxIFV/XSciZfthu+XMVEty5BL1loAcIAmuFnRjCoCYQmAG2wNi1kxSTgga/VBBvDZhKRVNGj06RW3XOurBm0JS4rBGNVLhQMMCR5ImtrKmquLuroHsAuzREoQtkpuHkNsee0UhQxZy1b6EFlpubwZXn394pPPbjq/uv3xt9998+PjHbiArIXZyJMzp1Mb3n9EpvIVsV3tzD6uBakthrVso6dS5omd/nHd+Pt3z+STDy0e+VnrdP51E7Q91UzwD4/rfuZtnWGtDyNMb2+g6awczdjZqXncAWBicIN5hQhGECjBzA3CLMIipkZgjPpv//Jvrr8Of/onf/LNz/+268WQC3Lquymh+ISuAEBC1VpqnubZ3WOIx8cxpCElyUvJBcK8323vyzSejkW565JDT6dM5CG6CMUuDJu+D8lUuxSnWvPiZQYUhao7Li8vnr987tXyWHjg0IUlZyxmi8LhkT1oIX/x6fM4h3mcyrKURZ0dFSYmvQSOMQbuyERNyKwaO/ecOJJTDZkhKaSUOmaq1bKWqhXmLWZaREzNs8LBaC0DeXVTdwNFlhgosgfnlkjgLaJLKcX9xX5Z8jRPzMyBUZCnxWq93Fw9u3n2eH8fgoBRtSyPVcQ5iUWukReBwz2LIBEj7vr4qr+/f7y7uzuOY3E83t4/PrzFkHfPOfZDSO4is44/vvvhVu5OyzjsNpu+W+Z5WVyXMFea5uXN6W7RcbvF4NKHCOqW7LfvD9O7RRyUHcW5Yg17Lk4gDgxuNFlFxSevXkpPc87LNAdLDb9d5owCg0plM7ARVuvSFq7g3MwLXRvRyelsYeJwXWlsdL7509TEz9N3Z2s5pHRWzTYE5tzsPIFN66o4wyorH3K9s0pvz2PNFrf3se7lo/WJMwX549vvY1i/95snDvL5R2ZekaLzoz+BVh89CT7+q49vYS4Lt8A9AgillrZ1MjOHQMxGzXHRzEAtTa8Rf2WF6sy1seXOYpwPkV7ERIGpKWCrNtpFU94WsZZo3vxrzv3ZOn4Ka5o8K1oFoM37plEgmMla9qmhiczJ0ci11WuD+yOdG85V13TWWJK2T4nXXZXhzdWq+WitVprtLT7FVbYedZlyu1oal7v11QJ39/qHWzELRw6Etd+oLcTW3K1WVwsxtKa6mdoQceJowecyz/OI5IHSZogLyWk+5VzUPB9ONEISht0mBuSa37y9H0/1s+fmwTeXadNzrfn28ej3VusEAIwU00r0a3y1CgoSQwI5oyESbJYhDnIjy8WRc5REEUQeAncRx4LlYRFb+kt6dv3rr756td/v/vKv/mKpy4uba0J9vLv76fXrTQwX/QW0fv/Dtz+/O+12ly9fPnv58tnu4uaX/unxOH7/3et3t3cXO9xNwNFRgR1SRHZAEGPtIlLk0RSqdfaaKS9eC9QRZakVZQEAzEBFuagvP8Gf/vFXv/7Vq+ubbdeTRH/7RkspkXS36dOmC0GcSASqizWJBwdrZHrpYoDwwER5obIcLi52gOQ85VIADClVxfvbx/3F4ETmXAqqOq/fYEyDqM9v3n77/fe/++/+m3+2TC+//MVXIaZ+GHLWw+Fwf3/3cLj75tvvTuMxlznbMpWl23Zdusx5mmqpWrnnN3fTZrO/2PVBUKtO46qfrbWSYOhZOJJwlwLgM4rqMs3LNOdlgXplJg6x68RMTqecC7YbdbiqpZgKVaag1btukeAMxBC7FJnpt383DRHb3UXstsfTBNXUcehst+uGLnYJKDSdppKNIDCYuRC5m6lR+LAJPu1kHy0B/3g18Nmz1s+9cSOf+4eq4gNQv67ThsycIR5/eqan3D76UAk97Xp/sIe25ctELTV1dYf8CMBqo5M2C6YWz342Z7fGs2JqIUO1EYRVV5QNZyn0mhpE7k7qLYn26cHbs4kIqPHF2ptykPl5AyFirPORp1xHXwWXJGr1zA9d9/P20Cvv98kMuH2WDUNrvhrkFFKzYFhTfhpwZaUpOAxeTWF4eDj8n//X//G//Mt/ISFIEMtW5rwJ3RD7BDw8HJZ58VJjjEHYVZk9SBCR2sYA6xOrw4vaOOZnL3ZdBxImVLXautBlweFwEpnHCWqLZB/HqRQ1Z1NX9W6IKQRiOBsEsU87olLDaTYWCMTJuiHEPpTbeSkzGGlgbANA7lZQwCGljaOoz/Nip+Oyv4x910/5VErdDAMctU611ryAg6dIqYvu5Mal5CQxRSGLro3eoap1WXxcxiWfzK3fdprddNaca/ZNH4iISYZu9/2bu9ff/Yzc4piCG3iNXWqmNuS2rhMWCcQMuFkxm8Y551JLdndh5hC6mFLqGoZbsmJmMCrU4dpG72crSogJS4xMxLVWBMzzXFSRFQALUgrb7W6/2y9Tvn93d3o4Lqelo9jt+3ycicgFBlPTFQ54aplMzVDVnBUBf/fb1//k5lfufHgc76eHfrcB2TTaPMOA0+nIUqrO8zzudpdBElFLyQIRQhBmzjlP0zIvvrmg5EpCXYocSWJsEoM8ZzdalpJd86IQ08U0u6M4l2XBPEMEm6HGGGMIXd8RiaFy8tPBbu8e9kt3sbtwCpbZFlsOp+W0iHf72BMjJgohxhSDBCKoSHLZD1uQs3BKwiIgUmM416Il4/FhWZbCpDcXN0xps91rqXnJZiYSUiemcHdhzSjmXMwb3hQiNTfR5BqKAWusTQixlalMCExuKmYhJB5iH6RL/cX+KqWuFB1PS641djHXvCyLmY6n8af37+7vpmmSXNQdMUINRDwvmSTshyEErtVK1Ri6WnKftpxQas7L8m66mycri2rl3eb6n/6z/1oz3b2/v729v33vr+9a3C6gwALsWxV3FimYqikEICyT/vT67dWV7C546DAM+OT5s1effvLi+c12u+nScPBDhUONsmrOMFZKMK+oox7LoqflMXbdMtFSx2qXXdcHomnOass3v/tPIfLzlxc332FewGzuWiuq1UCxfWTUKLityGQgAIFESMvqJ9zmo9KOhyadY7hgro4AQw3COIK26Ie03Q1a6+XlHmDQgSjGBJBWLdMyqaP17RAoFUjHzIiEADAoAOZQXzm0ZPQhqXyl+DqfxVGOVt0+acHbMKTp3ZupFwmE2h5NT7ni5q56Zp04iJBC4BimeWp6Q4nCwpUKgUJgsBk5sUEY5iDqhk5A0zFPeaoVYoyumWGv/BgSokAsXGqBYbvfMnNZCgrUHAuQiYUZrGqyOrHQeQ4DaCPKCrG3kjx4omarbgZoTNE5OdRbCS9EzO5ecgEI8UwmFiisIE9lTCF12zSHHKNXcyP0l0gbcrelZBqtow5qm9AFifthl6hTdmLW2QgmKcw5z3lkCFkoKMu85Gn2UtFJiCnElnsAVS2lVjUCR4nM3PhM7l5KqTVLJKIYYwghqpU5OxFq5DKjch7CBZFDtEvgxEXM1Nvs2itJCHjS1tBZi3EuUAjNXOBMoDAHE6yNyHhNjWHAQYIUUwoxhBgiF6q1KMNCDCF1SvAGWpm7wsxV3fOKkLojdh0JitesRWulEPtho4tWPWYtkSh0GHZx2Kau76Y38/3Px4e3xU6AIbLEFBbV1qA1oQkAh/5euXWeTf7ev511suc3/IcGzB/f/oFfte78zE1Yhav00fO0RzcI/71HWyedrSpaO+Km/nzqv5v18RNrci2xzuSv9gpk9SVqThlW1UnWck6L1qUOe7z++dv7u6//6Wf/pYhc7DeveZlzjfsFfUVRBAdjt0eu82E83d0fp1kl5TJqd0KInjq443Q65tnmebl7f58NVzeXROqojXMTIoYhDn0kYMnLZr+Dz3We4DCFKmIn28tNP3TTOE15JEXoKWTKpTQHLgxmQRc9lXBhXYEbyIjdgsEQAvWbSMLEoqhVKwq5OgfaXF70sdNSR6I8zi6p6dBMzQXm5gTmFpRXwYTQAiW5mdoZaYPmU9+HJMZeUVuAaUWFVgCx503Xk/pYDqdjIXKwwGkIu2242srl9tklEeZpuj29P94fl7IEop/xKP6WLbCSVs85/+LLr29ePLvZX/Xxiqybl+/zIWPvYUjdTgj57nbaXvrFxSaGTZRNFzeWeR6XH97cWlWhoIgkqe9Tx9uiJ7UxMBPEleexvnt/h/cICjdFdjZic2hz14W5Va3u3k6H/f7i8fT+cPc4ad7H2C7FGDsA3LBnZmqeSE+Y1BMZt8k4aMWym9bW6OkU+D1J3cdAT+s4mlsTMZ4SCA1nPqOd/ZLw+zBTO8GI+aMEdCKQExHb2bfOWxCV4x9Yx/T3fvp4t/vPLHM/J/49/XimHv8DMNY/uHuEFXATCYnZDIVLrVBtNIgQJMaOLOmca8luUDVobh92jH0I3Fzh2mbjoBCD0krDIoYQKayqwioRhRBEAjh0G66ubr76dGDF6RtLXFoYIcwJygjUznRvSv4QhZyfYEFgjfJAVTTI36kFf5qaqrXLYyVemVLgEIMwOUwLCmr7wJqFe1NQunr1RpGwJ/KFpNDyUM28eG3BmSFKM22uqyiw7XXtsmxOXQSHLmrkVlUzYNh23PUdCRWowbVWjpIkMTu4xhD6EGJIIrwsc+uT4VQXL8Xm5dQl6Xo+nubUzRJiFyJIU99//qvLZy/3b17f//Dt+7Lg+dXNj9/8zNKs6ZuTSKhu42niQC5oClBAixo60C6UXJZD2YnvN/3z60tGLRfDLry7fTe9vIpff/3lL3711Xa7vb+/fffup343iFBK/cXu1c3Vf3HZb1EsT7Mbvvn2zXR3d3v43Xc/DfuL7W477HbbX/zi2W9+89W/+B//+f/2v8616DQt3/z227fv3j0eDw05nkuZ5nF8jFKDVUd2cd4PwhtKIjFhf7H509/85tPPXtxcX/adiGiI1Ww+nt7//4S9S7MkWZIm9KnqOcfM/HEfEZGZlZlV1VX9qGlmpAUZYVbIyGzZsmDLki079gg/hL+ACBtA2MECYYAFPUI/6KquZ1ZWRkbEfbi7mZ2HqrI45jeyumsaT0mRGzfC3e9196Om+un3+Pb9Qy6X18f9WujVzY4D55o/PD3lki9rVZNpdxOCECd3yYvVCgmj8CTNJLS0a7e39/Oyqp5NnQVufj6XeVnnNR+O4/5wdHJzU0dt2d2GUWLwGMOwG371u5//+pff/Oznf/+7p6dBYITaXfsZ+zRxkFbzcqlwjMd9XlHK/HyezTEM9ubNTrAvi5yem2rTkkIciKSWC6BjCsyDqwmPxDSNRBRb07yW1opVZC8IJdF+d5gkeqmVgpnpsp4phuv5rsOAwyRx0MNxJKZ3797BwYwYJUSSyJJ4mCgOuL/fd6H0fjicnp+/+d15fV+wAE4ppWkIIni/PstWa+iluJgBtPXNvcgR96hrEF2RZkBb8y2G2a7YFuGak9qHc2f+bpns9G+/kgKuKsPrptqNnF5iVl9u3IlMEoJIkLDUZUO+/OVhIf25+h+7baQb4F222V3kYbDazOBt432aXK87nW0L3+rLRz8usqvh/Lai7GRbtY57bbwzvOwbr78ltosYnEg8IG6F3nvkKuDd/t7678vMAKl3M0DuG9++u9SkDmwXQIIrETuxuIMZMGdHCPT126///v/FjKVnp5fSmpZP71/HNPj9/fPt+fl02k8jM9csMEsx5v0gIp69LsXdqpmaBuFhkFz0fD6HgDQG1bpcTsfj4Wa/awt/++4cBDHwftpZY9jSKlozZgrCQrLmxchdvFquBo7T7i6lJiFMqm0uSxh5OsbShrWcrMEDJBBzIHDA8OHhKQQYtaZWzwC///PjD//oR5+ezqd1ycOwN/PXkrw9vi/P6+Kua17Vncy8ZU8pkmsrq5COg7BzziuYS821qYFi1TRMZS1z8UCYpjGlQVW+/vr9v/3f/vp/+V9/FgK3s+0/PT4/PqJTroKAHC8eAQHu5h6U0KxW82IP/TMQKBCzelua5VaZyOFNrVAzQT9G3sOE+jxElGsOHERCoBAGOYb94XZnrLlWJt5PExPdvbrbj/vfPX39u199g9P2YWtUhdH6j8TgQEOKAGqtBkC7Q7OZw4XAPD+2D++eTKI2jzw+vr/sjkMIvJugDvdWKzf1da1BijCX0sxsmuIwTLtp149ErU1au6xO55OhhRCrNVXTBssaZGCz03kh5/ube5BbjTe712lIzDzPc+KLqQbmZcmGZWw1hNA0px3GKfnc1qUtT49f/fLt+/eIiomnm/HTFIfW6jyfP/3ki9KyatWigDmbBJZIOWcDyKLDa2mXBee55eVEhBDhwFpQln93d7x788mraZjy+nB5PqXxk93+5uHDE0DT/ihxCMISmLF3Lw5dciFvRvjiy08fn0+Pz8talk8+uf3s0/skXsoaWAiYWwWaeL0sTyTH3Pjdw/L8dBYe9/ubp9Pj+3dP58ulK4bBMSTQ2gCtDSIQARHltQLK7JelmhWgmdFnr7/MWZ9PD4+Pl9pw2CGE89sPGSpfff2Ldc378dXN8fUXP/zxP/8X//w/2R/M7OnD8+9+983Dw4e/+j/+NsYI3hAOFjhQVSk5B98H+vzN7U/+/Eeff/5mt0tDpPlyfv/1N784PdVSfvLHfzH7am6rzrksAURxgvuiK19Oa2tLngdMUHt8eNjv9z/60Z8ESVnXTz67M1rffPbmR3/8xc9+/clX33zr5hIwL2tTGwIhSmBy9aZOxHEMJAC7wdx8fV5BYGKm2NcFAMZpMle3FhNbLp9/8mo87t69f4eK07m+ffuuYc55/cmf/eTdu/cPh7FWZ4rulpdq3MYDq7owMUsMgSI53FjTLo7j6O6tqVoDweAMEoSP5CZyZ7gqMdzQ/Tydejg8nJ3IJbCRapfZB0gPVK5qgLltj6MII1PXQxJCCNM4jrsp5HNttZlxIAnMxBIoppTLupQlSGLnVqq5xkluX7+6uT2s50tdCqlTrKxk1S0bGQ9hRwGXZSHyT3/4+s//2T/77W+/WnJ+2UNDuxs5WyYeuUv6eqIYNh8NskXNlKeIak/54bM//mw6DHbKBAuRPYSqZX97aLV6dSe3aEiM1tEQVxjFuN8NMe1BNuzp1bg/L2amVJ0DPvvBLcgvl/U8o2keLQlkAIsHL/LNr7/98GHuxe32dfz0h6/V/fnp7I7XxzdPHx60IoooNVRtJacUg7CZduOUGOKYRnUrbWlq85ybZQClYRwBxzhMQSITF5/y2p6qafFdwnTLuSxV19u7HaLUfGqGIBxTQCWodpYQwfr8sjUHvinqnJjh2tRexr/tk2vDMAlJR42YEWPkwCCodhe/xkmCJHapucznC+qVPGvEzM0b3MHUIsLtfjwm4WV+XgA57G73+8PiMwVdsHz5/S//6E/f/Pgnn007Zvh/81/9t8hAQ2J4Q12VAZFAfOUzwY3Mmv5jOoTq73kwO3pU18du69rK/QEmhTfF73+fiJz5xVh6myeZt2EMwMtg5txpBVcICv2Tudk6g19o7u5bI9q9Z+AWYjKz1hoZyDxIIhD0hax1bTd7ADHg5uwORbfWWRf89G/e//Svf/Gvn/+j//A/+FeP6+Pp/FenuuxHUJJl9eZ6cyuf/+BVQ2lacysxcWn6Zz/6E6J6PIabYxTR4+7w+HDOi4dIpk6+RqLjnhU6Tdgfh5iwlsvldPnw7nx/vBuGkD69Y49wblmXVs6XJ5BN0xgGXud5d7uPoyzHDPMhDikO3mzJ9Hb+mokkBhlk4OFVjP1NlRhyq/M8L3m1YjGM7kRwiozIImEf9rktFnyl4ubVtUZP05BGaa2VWmEeJAxhsGa1tJZrg0mgMARmOd7ekfCS57xma40qXLZmNzAxzFstywoVqhQ53t+/fn33hhwffnP++f/9Ny8yRoDhUmAQRdNtygrgEP/23/4M+jMccff6zWdffPKv/uI/vvv0/r//H/47izRf3BviAZ/f7V69frXMOl+Wy9zKpcFQ3Vmi81Cy1loCRCKVSiWbZghMw7ofQif7e4arUwU7xShOm8NXx3Y44HB/mO6myHI+LaencxxHgbRVmyoRUaWWDZlIvSnBras3XvCk/jUTdQuHPl0QiGWDezpSBuCj0rz/595Hg+5D16ctJ/jmQNzXp1C369D2e0eVAOmGCH6F0rZHfeEQXLHffx+96h/c/hAPyzYV2PV5+w/Fv+9rDBDRP2Ho/t1bgJCZFa0BoWP2nd6KLgqHkRnMKCCS1KLdeH9zxI/u7ETE4I1FSk7CxNGa9jzOj1BfJzjRlrITU7JWmlUz6++QcbfehALEneJkFjaRfy/mBFyXbJv2kq+FxnlzV0YXi3bnMTO3XrfAAEOaKSkRb9int42Ht+mj+2/jV0vJ65vVPysi0u1yN+7Ei+vidyrndcFGvllVbp9IUxNmMt7oD2aupg6DNdL5aZUgHIgHSEDTUoJ79FKqmVurIcZhNzHTWtdWWi6eW4WBgWaN3UKA+pIS3d/cmthpuXzzzfnh8jjdCimbwZo2tVYKEUNYO3pgRkLgSCN4H+OOS1201PWyhtDOz49kbQj86maYWN/c37y5u53Godb89pu3v3372/18c3N7EKGs7fR8sqWi1ZYLOb16c5NLKWWZl8dcnh4faRrG+7vXx93hefdt4IEhren3P7v53me3zZoTzHytNef6+HQhD9DgGgkhIA0jjsfQWnHHJ69eCzOgTJrzpS0XZh1ZMfAgsWlh0zQOYYiqGiiMKcVIDTFNx4cP83ku7jVbqWYh0JgEJMxBOJRSTZVAImAEwK1qKWiaOYSb++Nge/MsQczNoVUvT6e5lepOf/bH9xYyBR0EMUSmGKE9Yy3nNfEUpzTsR0IUjqbWqtOWM4unp/n1vYcw7Sbkkkt9Op/mdc7qiAlEoVWwoBYPkWPkw/7WzC98MZtv7y2OA5HBW9MWIiRwCKhamuL+/p6Il7oCOgw07cK0m25vD0H4/fv3GFEVl/kS3dR1GMY0hHEnMYXaLgyDoDVt3Y4hctSgRat7r5P+nWt8B5K61M5foKeXxoGubrEAOhkTeCmSvQy/LCK6YxTxRpn82O4QM2D8kuH6UlW3o+h+NQK9ov/0wp7dUp+vtILrj7ZdQjsyRuTe40ThcLnml5uZVsOGQlx1K+bMLMyum4zP7YptdVFADxShXrXthffLLC+syxcm8HWzYbwBUoC5oqGBeqF62a90opZv681NWeO+6d7pO5uQzQe+M2OB7mxq21bPGNy8OWIkJsbZvn3/LcVWVS/rWvx0HHdVQcR3+0MgGliaKUzdFRRZIIG4sVrPmTBVSJT9IRkyCMOwm3a7eVlyWd2rSAxB+r6Ut4AVd6MuCBrG2LeaS0ZpmYQoUlmzmZFMgcVR1Zp6WcqZinKy/c3Qcl1XqyXH4DGOQeKatVYrqiJAhdVIFOApht3Dcj6dHhw+jFMIMQgvavOitCgAZlzO6xBhipYxRNwfMYzYIZaCpo2Y2QkU0K13ARIQk6rmnNfny9O3Kx4Q7ofZIWgSAAAgAElEQVTWFrSeL+ncyVdgc3dzEsDBxmREBDFRb2bARkEgp66zU9MiIgSqbk6OyEyA2zVuua/AFA5PMPfWGjlCDHGMPAxU1n4+W2shBtU2X2YUiLCAdHHNFu8kbGzGLb8GG5xFQLepYyJWkNWCA7379jHt76f7Izs/nRem0AeqBqSYUkzMvEoyo3VZ1rWsS3UXuDLlLmUdhsjBG3uMou6lrKXkWiHE4jLPl7qaZ9wdX9/evrk57Nacn54e15yNsBuPx+P9w+MHAMs851K0WRqj2tLANgRTt0Lzs14+wM9SGy3rcoYOMXat4W9++jv1Zq4kFCMPUwyRSVpMcbcb0zSUsqrObS559rYQ2Df73Yq3X8PyfDzc7Hf7/XSY47mUfDo/vP/wME3DzfHoTqUUUZLAUUjNVFsMPA4pr8XNxyHe3e7vbm7GGOE1Co0pRQlUteaaazaDalnWuZQcU7w93r+6//S3X799fLycL3OMw7Sb0u5uT7W0k6Q4qE1jqlpzrYMFceTS1LNaTlHGcXe3Oy5rIS6gVksdRhqGEDgwBRavtc35mUj+6q//cojHN28+O4y7IPLm1d0X3/vkX/7FvyA316atuDViGOl5PV+WC5He3oz3r4+ffHLXPWnzmi+n5zIvieL+eHDAeXOVylZNZIguLHBycmJno0a5Wn1anxrqeX0SiTlnSXw8HMcxHI7j/avjh8fn50sWI+38TnaOBA7GRqQ9+p1C30070E05NhFkL9NmTtQcVlqzABd87wefv/nk9S9/8QskMMBsbupe5/lpWZ5znltVIm6VVLHbT+M01lqJSGLQ5tWrOSrUxSiCiHggVevHxuAQEyciYoLpxuvvYwMcLw2ysxFg8JTC5k7PxIKYBEbVAAc7NSh8s3WXIP3KaG5qVrRON6OtltfSqPtFC0nkRIHjfqA0TDFKqe0yn5vV56eH1tRVD7vx9nj31a9/xRI3TrDCuAEwrtM0HW8Oh8O+Nc0lA2CmbgzvrV9uyY1A1vOUuikREZFxrQpwmgaF1Fqs6BTjYdqd67nVYmxOmsZorlUrRJCYQabKwkSuphSdEhAsJg4TadEEkpB2hBAp7FmtebE+RNRS0ajMJtZ4DPWkQ0kAstU817w0Y1jFWnHmCxkxhJnIOrna3M2MWnNVcwczxyGKKziRlRBYhNyUyWrpRgQGd1XU4utMKQiRMSUg1FootnHHoLi/iU+16mrk1dTFI9yuqhyn7u/rGyp1vXKDQBvFgfz6iUHLzcVFhKg/RmMFMRWtxVpzjSKqyhTEgWaoG12CjLRis+hlQvOadNptg9I07cZpMnVzDYFRQdLSIML2fH5e54onTNOg3LyqVbAxoS/KyMkZpt6NtzZbHLys3f4gReKjY1VnpgNwN37p6T52cn8I1cLH+LMXhpddX6EXkgp9/BcvUJnjBffyzVN8u4u/QF3uMJB8/OH7YmgbDF+aOSLvwn1sh7ET6M1pSJO20lSfH89/+1c/++InX86/Pd9/Ntw9wLRqbjI5M+4/Pbz69Obbb78uTSXQNB4uc/FKp/lsTYQmppY4jcPw2WfDsixrrkS4LIsq0oRhCIGtlrWVVkoRoXfvHsch7cebIaQeRSdgL7W2ZUSKA53ndl7PpkqJduPIFGpbcy0Zy7S/dXi3XCrazLZVGSnnVrMVREgnIlYYUCxrViFKIcQpSSQnaLUmjQQ8xDAJKVEjLU7MHvuMq7UaCA0eAkC+uzk4XLktyqa9XzcYEMGALrVcVmTAcdzdH3c3Xu2bv/+6ZWUWIFGDu7OIBDKDlebzNavI2Zubm8TJqPmlXfj0EKOQXJb53/zrf/P1h1+/ffyqxXJzTyGEp/Plcsp5BVkqcxOTWrXk1XzJpcF4B0+UrGkuNQwjKXIrbOum6sWGSW+SdkZtxdhJGAQeKO3S8fZQa9fOCoOtOvLWr8HgFaQIkuDwCtsy8DbZHwBTe1HbXpfrxHytElf8touOf+/QsZv1qoyOX9sWaLBlhPh3SADfpUj5Vtw3ncZmvOJX4Ob65+u89A+hqa5V/O536N9TEP4gBfMP/TP/x3/1hxlYcYiqqmbqjYmdncEcBzNn6Qx/K7WIbzBQjw0WYRa2HpSF7guztQ9wJyGCUOuMhO0Cj76V6gmGsGbJOh4uV/4sQMLWAz6FiUm7QpA+fmL6rbaCq/oT5HwtUE4uQmTsBhJmUJ/ZvEdUciBCq9XJtagzDG5mLCyBrzwuos1rE07dYxHbZm/ThLiTO1/fQb5O0T2KhuHiFEREiIRBTuLURVMeOSI6aa7FWlNQ4SgxRSauRbVUFVCFBzDDomJwEGKUarWUwkEQpQcbSkrCgVlJ8ofn8xD9/m4a96Mj81g///HrcT8dfv7Nu68f57dKZMZOAew0hOCOtr0Zupn0BPEAIvKesiIAwbRZW/PysLt98/3vfz6GeHfYf/rZ54fj/t2797/45S+HdIxxVEOpSjDxNbFMUYYwhRCf18IgMqpryyVba0+OMq/2+vX7b76Z4hRkiDFNh92wG+/2u2aWc53GGO7jzbQ77O9u9q/HdIAHLQ5aUipmhYD9dDhfTs9PT5fL4/PTh5KfpykKa8uX2tbn83mtZdrtp8POmt/c3Idhusx1adRcHp7mb98/qhqEqtYU7PY+hji6c63t+fk5pRSDBCE12pZFjpaxrLUpgUMUZlGv3UxN4WZUxmH65t0vz+up0UwJHGsMTApvIsVbdegsEqfD0VsoS13mpdSFGMMgIdrnn3252+1a09PzeV6Wh3dzyYDTbj8Gwel5PT2vIk6MGOXNpzev7vcpSWtequ293b2+c9enhw+5rIfDMA5jaxlQYtzf357O55rrOAiZjGOYxribBmI8PT3eT3h6xryUROZMiSimOB6G2pppdaK6rpFukgQnD0MMOda2kFUz8atl1ZWp3QmoBIE7THsLsVW/jqZfGx7/WEA3Z4eebEob77LzLOmqk7oWvg3AZn4xuL5uHrav/mEL9KIANq9WK6AE/nh2nai7s7tzN2hwELm5XR0LeVN6Wa1t4NgDIzaJCpEwC7Oau6krOlGLmLqRyVYMe8um/hKOAYizG/rappca26Lb1a6dWMfezV2Jub9KzER8Jb1tLwfguv1Um1nqFgR5Re460ws9A5KICaTWADCkC5qZRITg5de//s2nX8QtEM4kSpjPz6YqKUZhhrdaallLacys2oipWatVq6OUYk7DMI3TaO6l1WkXd4dkXs0IroQwTenN671weHx4LrmwxBSjqpemrai6GaEC1Vocw+4wrnlZ5mogN1UjNXOu51Kw1mGI036oQkDTRkSi6q21lo0jGDKMYfbijUr2vBgorIt+eHgww+s3r0MI47ArddZmZnAjphgDJeHm1bkxI6Y4JIkx1FZrbWmMEOIQwCEk7PYlsofAJJzi+H/+5U/fv3vGAKsUd4f5sgJMMEaHgdDcDeo9Kr11Nu0mTiISd3f15g2dXEIAcWfR1Z70LqJq0Np3Qp3NAaC2GimAvNRSahssDnEMiFkLKawuVlTN8mV9fnxGuY6bTHEUK+ZCJNvzuap37w/qR7Zjyw4RrB5Cevv28smb17t7uVzK8XAY0mjQxiFxm6ZxGsfn85kpMsVW17y21rzWWmttraYkEsDMUxwy1zhEDqK1qqE2gCBCQsPh5jDQrhb95quH57ASvGirak4+jMzgaTiUVtzm7rzhxGBptTXiN3ffqzM9fP1VzQgGaEQZWrbiawweUljKZSsLghgQhxgShyGOyetAIbbmpUETHT45TvEuqNYlX5blefFVFE8P5WE/H/fHKANzyPP84bHNGcfjsNtN8zz3cyGysWwCsQQOMbz78GyG3RSnaTwcpmEQV2vgAGdTco1MUwqXBSVnITkebve7e+bxMpef/fTburbabNiTI41jNIizT/shDcPN8Xg+nZ9OH3JpBjMjg5o5iEZiGTR5mw5wDrWaBA7MDJgpR+col3N5eP42YoxcHt6fpjG9eXX/g+9/effq1c1uT1B2JVMRGsZgZM+Xp8t8jkmOx4HIiLTk0lpuddXahjAwREI4zZdlWbrmWcnGceQxqKonsHDyWJFzzmtbOXkYOeuMxufT5eH56UugmErEH/3RF+b28199pSBucJBENjcnsmuf6XBz7ROBEA1DhHLPiQW23D3rtR1wwTDEH/zwy+lu/N//r78e9jjswqtXx2kXtC5Pj+/my6nklSAhDhzRiENKwmFdVzVlkVJzKRnE6k2b55rTEOMutFUpoBvKbzlSTiROjbuzsZsTyJqjxy33idrNYD1GwHwjJhtMRGKK7q5mgdG4x3tZCCFIUNXa6lKW1TMZFVRJNKSRmNe8lrUqtRADEbRWbc2qQb3X/zGyCSOQsR3v7gIEjby4N+8e4Ec+gnG+nN4/vF/y7OjIPrNI1zoQkUisnrudl2zTgPQrMSM4XEzMPEh8enyO95h24/n5PC8rJcQprnUtrbQeuSXi4oBT6N2xS6Q4CAdkzbZW1Twe0qtXN0TeXC05GYVMQ0NgabmUxfSMuoBvkmicknRjxpL9/bfP023YT/sxeWRRmLbWO38Z6ObukPZRvfSOt2hza7XmECVGCTykQWJi1cJ51dYZIm6qZa2XU16XFvd7DuqWTKlB44A48TQegwTTD6dvW62eAlmu190TgG2uhBN773i2SZJJNh+0K0hIIF0rQ7DZ6GrV1rkCVWuDI0BV81plFFdjgzlCDylv0KYE4RSd2cxa8VorQkXE4eYoFE/PT7nO2nIc8cMffO9733tzd3/zq6/e/91Pv8YtBo9rsVpskMEcujbaIqfdvXVo2L2znDalT+9k/jEF3gF3xQZd4aqQ+kfUDPoD98VH+KvP67RJEq/tY39IZnLVf/SI3yEfdOiqa6T633UMq6de6vY5J3SmobvblWnWWcj9HTEIRAjEPW+bwcIsEc2Wr3799n/6H//n//Jf/hf73e7+9fC9Hxznmaqt47Q73h2GA+1v0q9/N4PluN8fj6+H59Ur2uyXXOqlWSvxz+J+fyg5A3487HaHaV3WqnU6hrgLba0PD8/zSaHofWVK4ziORFLWUjSrF2K0Vp8eH9ydAy3zcpj2Nzf74/FYazudT8oSdzchDa5oqGtZS14XxZjStJvM1cwAiikIB13M4eM4hCB5ycucBWI9DSgIeIu78+gt+jANI09aTZuSE0eiSBxrKw0OYQZJQ2URjkJCUMCciMYppTEcdvvEcaB4O+72w601Xt6el9OynE9oSJgEbB0ydTW3njALky35iEDEQtul10RYuZ7WD/6+fPPb/+w//09v3qf9O5zbu+GOi5bz+eweSyMrZT0VgpBzKwYyaIWTWjb1mhdk5VGm3TDIMKUx3TBcmlZXMnMluKiaaXAeOO4To1Vqhetq2S/UjcG12XpZUSFRrBm7mCoaXABFB0jEti17RztaBcjB2Pw0CAyHbzSll638x/03Nv8HAtmLa/oVVOr1x75zaPrpxZV2sEG36H67tG3G0Qe2TfWxZWdhQwk+Hrbvsnb+wAn8A7d/QMD8LvHq5Tv0T8qNv3sLMSVujVQNbkQiQQB1YwEHYRFtDiLV1pUF/aoVhhBjLKWpqqluxdmdPja+zJst4lU03enT0v2DvWpp2qy/VEQIm9qZAolIiOIOUyc2Z7dNA8i9BFqzbnZIBAKTw+CNjBjmm3fNxxelG60BQpDALAEwU+2zgAgzMRHHEBxeazU3DuxQg/bCSleqSN+Tg6SbJ6N/B2hqDo9RENnIiJmJGdRTx8ybqgUSaPcEE4osQiEEks2rweuWd+tq3dtL4RhZhEH5cDhcliXX7NWwApHSbhAJZT3LgOfLEhhxhCTbpdFicRluv7f/Mnya9vEbf3sIB+FQSjufL+u5WQNIQxAntz6GRa5cq9a6CoIOI/Z72u9oSnwcXn3xyesvPv/0MO2O02EY9+d5eXw6Lbkdbu4l0mU+v5svU5L05l59o7oZMO33tixmJsS1hEt+rDmvqZweT620/ZtJ8/rw7ts4xv3tnpmfzmc1D3EAQin26m7he6N9CzywsWHO9VmtMDHpvMyX+fzw/v3b+fxkXkzDmITJhyB5XUurDpAIpzGlnXNq1i5zPi/t4fH5/YccIkFQmjPNzeJ+TwClOLbWuMdwBMpL3WAUFmdzyLK0mAig1szdDa20GlmGUcZRSnn2uOzvbTwKCxNkrUpz5QEg3N8d9/s9iC6PueS1YVHCmLDbx2EMX/7w01r16enx23ffPp8uuYIYh+nw5s2bMNC7b795OF0IcMJ+ainNsDhNEyAxDK2dXUuMPCQ2wzDINIY118AeghD0MA2PMCKdJoG3cdiFSCWXrvPaD1gKwCqR1yW/+uxA5Kp1Nw51Pu9vPpM6Lpf3gOpMQsocTNdhHKuafaw11EGfDcklJ5K+c7uiW9gwF2xQt2PL++uMbrqyRv3l1hRbB7MBQR2R6SD7texdcavN8KTjQVtJRze97QI/3Vqfq6XuVnw7qmNQvwJnCne3ICyy5WV09C3FZOzaVK1fRGFqrpvM+Npi9V9vuxD1pweoWdv4sNZlhR18sp6zKyRE5Nq2lSZdmyc1124IRdwhKKYgAqBq7RoT2rIHP9LJrl+4wwNH7xvf7rnr7t1fwLQPNlECk6gaAn7+81/s778fhoGY3KSVmueltjbaCOZW6+V0XpalNGuqBu9dvxNUoU5mXrVFjrvd8PD1anYhcmEP4gQbhhhDiiG0ao9PT7XWXUzTNLjDbMlZoYij3BxIrewO4zG30ymX2gfzZg1Vm7F+9uaTqksp2asRXAIzCdOgSstSPVc1IYZXigyGLOeilTiKSJwvkIDWHGQxpjev96qe10Yku3HvrcYA8ubWYsB+5zFySmxQsbQuLU0BYOIQY9hNoebT/ngYxlEk/ru//nV9BFzKasKsVEWCtuymIDI1M9vUDwqDbueiSyuywc11ayJ6LrmwI0LhVgsAi5HcvW3ZxxBjZhHptL1Wm8P2+/F0OXtx9pJzBiDE7rrMM5qXpYKQJInKWucxDSsqYaPCbcvsfpHtLrYg6xdgJ57Geq4gWIE1JpcYInNwc6GQS7s93p3nsymYkinV2mklDG9u3WXGzV2E2DEeJ7+S4Zmxn4YoCUopTvmiZV5btby0x/e/Ysc0jpIEZBxp2Mf9cS8p7nZHx5kDD2k0l1qfmeI07oJKohtdn2whL5AWgwCNdV2XtcgwbJZGTWu2OlcQIBmCzW4mICUc74ZhxxIjcyCWKY1gW+YH4zZf1tPT5eZuEoRlbiVjDDgchpTEPDIZsbFQEOm/HUFrKW69OVWtayujjCMJtbXlUtkRyBHIB3l1u3/3fHl992a3f3U8vnl6yr/9zW+//vrSO0EpdS02TtldCQ7BMA3jfmyup0v68PgcItLQ50A0d5bz3W00WjjkOGSw9oLcVN2pY87Tjm8Ou1b4clmezx/kgtwe1Oan528+uX9lreyGYRy6uTal3XC+nGrL8HD2OQZuWpblbK0BzsxjHIWDE799eKy1xBBTSpCgQhWm0MaurnmZn05PrdVWW5zS4W5PgbU2o7aW+vD0bq2VeLh/tS/1zSVfHp/nZr5W5eB1bczCCdbcsVFWt52yIWz8pq7R66Ju4gBr4AEAvfne/eFuokQEaMPxsNvtBqClFHrUVwwkLDEFQlDlZrzmnEvZ7UcJIee1eWXmOAT1upZipMMwIuQ+ITCzEHebCmKigK4KMKWNfqVEhE6/dwCCkquz9Y2KNThUNs8TSBRmcgYnTjFyEAapmwNq6tpcAUYIwonMjAKEqdZCDFWtbQbBK1xBA2EwCswsEiMId/d3eV7XWsyUQSRCROamTavmb775XY9frFJc3eEhSVOvqkOKLywA2xTtPeREYojeSr6sFEQit5Yf3j6/+cGtN+NAW2yJa+3LJ3ZzUA8GZw5JTC1OiSJzMDMrbW2KgRvEw8C1FGcPIrv9IMTcgqo5aWuVFFYsL7VXQxLzijXXg+zGYzI1cnr79iGolKoSwMlfvblVslysLrVXITXNeXGK1AUl3XRAhsDwloeeA+VOsKa2ZiS2u/t9kFSLFV0ih91xrKf6R3/8A11xengbCL69RR+xlE1KZ/3Fuw4WTMTs2yDauw8YfJgmd2emcRhFKOecy1JbaQZEEJO7qbVSszej61jERuQUIAZESZQk56WV0szYjSPxQGXJa5nhWSb8+Me3f/pnP7h5NQ0ptUr/z1/+EmcsVrU5nFXh5hDqsQBO1gMLuqcONhuEfziL/v7XV+b9x50l2YuAqc/hIKIuI8KVC/Iy0zJwxfm2rcoLyWq7rzuIwpVc4i9b1d4Buvv16YheCOp2dVWgXqiBrTXc7tZZetZRCt6YEm6AOsLWrnbQFkAivP32+ZePz//17Zvd47Q7yiefTZeZwXJz9/p4fzQvtV1YkFc9TGk/TVM8/t3f/bxZAeViQMGnXx5KbnnRy3KefH/g6XCcFOH21Y4jnh4uwszc3MSNbu8OKU4Gysu6XOacs7qX1kxbc0wjpzRMuzTuYtrFMIiLjUjDbhiH3YevL9TQZm2XphX7/bgf92kY1FqpWosO46hmtWRrejweyT1KWGxuRXuWhSA4uQUXYRNzVkoUYuSgbWk1FzjxIGOatGkrjUBCwUSXvOa6mFi/5kqkEPg4HZjo1c39xOOjP+RLXc/18d0Tlp6s7UWXyMPLh8OdlMBGKH3PTUSgThdx60BzXlrOC56Agq9+8cubT3efv/n0d6d1PMhXH35rhlqbWwKkqI2SpnEsxGudETDEMAwQ1hhRFjB8iGEaUmT6wY8++/Cb50rpclo9WCtGDE8EhSVPr6cwhGq1uc2W81PRqgBp0bXOIII6GlzN1aHcTXXZNqEEfHPJU/fAWyqc9cRAhkP6Ql1YzO1F0nE9bB33QJ+qsEFYG4zl25B1HZQ6VmPoQO3LUXN3Ee6fc8c1zLef324X93IQtnhqMrNe4ziw1d+XD9t1vPLvnumtMvwDzuY/wcD6/72FDYnxDvx4IOnUHDezttEuJQZzAxkEPX6vu2OKSHefcQNxx6kaO7gLjYOwgwF2EnEzFZbAAQRzNVftl5we27WNnM7MLNx3Mv21x6YRwqYK7O9KL05g6QGQ7LzFUbqbMUFVhRhAx4LMzFnhzExw7lYFPV6s56Re52bq/xN1YrdvbvIvpbajlmzmTs5biXyp0Vch0jXLuc+XDGUAbqbkZtSpNBKkmnkxZ6A6Ivf79iptMDdwIIPtDoeQEohqqyc7wbysGVTNNXAwK2vDZVnjoMSEfGZvjEQT333v8MMvvribbstSfvp3v/jmbz40BWJHZBUGNCsBQYoZUICoGJB22O18HF2o/PD7P/ijL79/f3MnHE4P53fvn+emH55OHFJze3x+Pp/PZtVMHp4vqi2P4z5GFvnxn/7x8/lc1sW01ZwfJZ6entZ5PRmNMe3H3ZAmAT+c3z99WGotj6czcxzGUQ0f3j0/3bx/vH1/d7zfT8f9sI+phbi2Vsz0WW3N8zzP1uaUmHkMgSQwERSiDuqhOJSCDK3RPK+PD5d3j+fTUs+XdV4xAJEBx7Kg5FMptt/vhjGuOZPwOIX9fszLfL40AjnTmIYUJ22AaynZdIW1IEgMCTSkFGMwtN0BcZgcQqBSEKoPU4JTiPF4czMMMa/FqgdJaWilFGIMI8ZRSlnmeT2fT61VOMYBTCmmEcRwGobpULNaawom5NXelachLeM4cUArbV3PQIyBMAQhh9bALmKBueZFRIia2+ruYQhpkFrz+Ty3VsYRblTgcSASP5ViXlRBqCFMLuEw7c1SW6s5PDcLYVuTMaMHLV1r32b95p14umFJG5/oxeVqq594IaN+p4RhM8X6zjev587x0TeBr2uHj9bxL7XOvsuJ5evTXX8GItJr47Il/vgVddvQMdoK9/UOfRA1cxBaa91tBddfzDdQHuyE5hsJ9ONCZKurL13eRhhQ6/hd30sKO5EQXEj6D95dhch7oIjDt8WgXds3548bkL74fLFlfKn//SXtPaZdZzyHO4OYHGTaH9utWRgcgp//8lc//vPXt7tgkFqbl1JKqa1KEBZZ1/V0Pq0lO4sWM/LSWm26+XGxayu6rq21GAMxmpacqRsYEXkQ0p60Qj4MIa9tXS8OiQlHnvY7V7eY0rTDkBKPklcfxnMp2Zu7G7HDFIw0clu8trrOVZzYSTgSi1f3tUJGGNxLK9qZ0NpcFUV1XUpP8sprHcc03ewPxzvmeDkv69piCIklMA+Rhog08BDNbD2fHyQIm+SlkHqpldlCiHFgtziOY0qJIc9npEbwQBzVuyt/Y4K5c9MeNS6E7qfmfrXYIDCRFoPZ9TPeT427u7NvQggGvO+/2bsq/9oTXD+WHiIPUzrNaFq9Nm0NDJZQq55PZ3a2tvFqHU7EaRhLW7f1C5Ff6dF+JR52lYSD3SykqbZHDCAKIaQUJsC9barOWsEky5zzWmpTE2nVWqNaTNUpMrYsdHNHU/vk7oullnVd4BTjeNjtd+mYL/r8Yf7db57XSz2kI4pQTq21t+9XJ4ARJkxHfEbxeLufxr3DnQ0k7CZIkZI3iWEiBBaYsxfT5qGHYHtBUUOPcGOQ9Lj0bmSyuRIx2Bw1PH39wcJpPOymaRqncb+/nfapHHbNZpIGhBjitJvG4XHOUEPJ5xPWrknSVoIyDSLigcnMTWuKzPAkxHAt63xp8LJeTlZbCvG4OxLI1SLbwPDqpKIFp8f5t1+9hYMEYJhjzrmahdhu9mMaOQ6sVtSLk68VoigVEjGNBITWXO0CXjlqcO18aoACRaLoJI4onHa7Q1k1Pl0kLHCEwefymL99Ou6DtRLDzrNfWq6l3Nzdri23VktltTLEoNas1S7MDhI1KlFQwCtaAzOps7rnqlxVm16WWZhUda35crkQ0eFwiNPAkQHZHXe7IxPZmk/msylP+3h/M+W6rtWJgwxUnzQKbR4fWyLGNjrd2ZoAACAASURBVHJeVbTSm2awg4ndIe5mLjjeDq8+uTGqZHRzuz88YRxiz5/e70ezWoo0FnfXVt1MlXNpy5qrtWEMIcZhGhQWYjR489ZmL1VJCqetYROGEKu6Q927yxXc4GRkTLRdkrY9O3cb+G64sU0N7t5cXRsTB4EEEZYQQggRDGvW0KyXc8fNq8PaVmauWvLSvGIc0nhIrbRlqd6ACDhCCELI57V6CzGEY+BdMPXLZXn89slmsHe8huLAIGeh8+XZzc2174MdCEE4krN7AEq/ZqLL0M2t27SQiDMZNIVIwd2waGmlxgiMgkBgCimV1hQILOShKy1CEiJHa/vjnsVLm90Nglqx5Ho6X1Kjpa5hjEzBzQMHCVEiIzUfuT9aa62ZErEyHEhRdrtx2k1VK5us5du9MAghQaKIcGm5aTXTEImStKZwa5rZwELoxpjCkGSogUIgDkIWZUoxx1JbXZdKIB6ltebB4jBppelmOt7v0g7lhHAFb3oHw9ehrtdZ6jtQYeqc2u7/C95cbuCcuLVmZj1lgtidXnoTbJQMcvUG32qbwbpzQWDOTZ3U4Y4GgTObKEde69KasXht+P4n+z/5s++rLcLj5bw8vp/zGehIq4vDVKt7P3F9sv5onUNXfsc/vv3+ULo1ctgui9upfXH/3Pq6rXN6eYTvgl7fRcg+8jo2Csq1u3t55u+0kFfY69p8dn59v8fHtnMTF3o/lwBwNXU1s04X23aSvv3zK7/FW2khUAggZZxsWQrMQ3KJNk5x2gceDFSIWyt1v0ukNoSkzerS5sdTCIGktwmInHLWyyW35pd55gcZxzDtBzWta1WtaUiMoWWaLwUIrSHXfDqdTqdFK4hgDigQ4COJSAghpgTi1pRZpmnv7pHS/PQuWKhLq0tzw//H25s1SXIkaWKfqtrh7hGRmXUCDfRcuyR3uUMRkiJ8o/CB/58PQy6HM9wZmb5xVWXlEYe7m5mq8sE8sgo93eQDl4wSAbKQyIzwCDcz1U+/wwMaq9XF3LwiISWkta7WFAxzdVcPSnm7bBMnbi4EAgk5vKKSLaqtNS1WipUoaYgSgogyRwJIKBZaz/W4lgUAIigghTDl4WZ/iBQGSs2LL3Z5PNa5YgEUUTZBR5dH9RBX2mZ/RsTXuRsIgBlBVYyJIL45tDH+4e//j7/N/y6NKcfE7rUYBdGmAOeYb3acKQcJUZAUzVoQEjHVCm8hcJQgIZC4oty83a+X9cPx7LxFmngwOHAT0ziku2ncT81rbYVB849HGJGzW1VVcYIBCrQOlbJbRzfw+YbtIKx/bp8UW+neL5t5yyd9QSRe1to2s3fgswn7zxblF4sGAIEJ1icr2+JD96KyFwTiulBeMnMJRNQN3ekq1X/hloJezOm++Onr7vcnt4j/LI+wlrlfPwPc/WiIhdBg1rSZhhhjFIRB3FiYQD25Y13XnAawu3cxqgsTTExbJ79ttEyHcHBz9wCQgN09OCpajxcEuffsFnbaXPe9e2wR98zhK0UDDiM3TzFvCBg6cCgCdiEzb2h94yEHsfdZsHFXMLGacw9FNCZWZtdrQ9CKgqxzp/rNRkwE4Y3OBXQ8yt26dJJ6xqV38K5/Uhveb+7NtTQBSFic2cWbGllvY5lBOTKzt9bFRDBAu7BkS61p5q02jhxCJPZxl6fd5O4h0sP9ky0LhIebYRiCw5xUHfPqpR5Pl8IeWwNTvJlu//FXf7cfbsY0Hb7O/+O3fzumQZt/un9Y1uV0mWtbQkx5GuIuIrSU4+vX09u3N9MUCO3dq9c5pfPz8offf39zeM0IT8fnv/+n//SbP3xXDU44FuxH5AGB8PHDeQjYDbiZht04fv/p4k6Haf/uzeu723eH4VDfr9TMWwvEy1K10fmylFJYvVYVsIiQk7f2F9/+Ioa0yzIl3w0+Zh8Sj+NEYVdqeXx8UuW7213TrGbaCUButZZmGtIuh5CH3Xg4QNKn++cfPj589/2HT8elGRYlFqh6wgDSea0oNi/H92TvdrfNaMwphchGy1LWuVX1FNKQhzENAay1ltp6hHkMIEMgy2LGOk2RSBlqcCYZUmiWzMEhuBmRaiumZdqLHFJrUkrRpjnn/e7m/tNPx+fL8TjXsk2SWrNTOZ3P55RiyhJjtmJBLOcxhHg6nT7eL7vxcnOYxhTaWopbTpynTKTwMkRhhpC2cqIQb/dhkXQ8zu++urs97NbL+tOPfwDim9evn8JqYQ6DGDRPaLaqw3Vxj2NOOef15FbNFX3puYEcaupum//qF3sRM7sRgVj4ujleoRV30Evdcv1zLR6ue93PNjj6UxUSEbkLAd71cb0yfAlq6vsXywY/9X3Z0QXqXpsTjPuJCHN3NYdz2BR6arZxLKXPXP3aJGFeVmB7jUysgLCEIL5FuKmqmwEBEDiZAmICUoMLhT513Qznoa2PSkgoOrogjLp1irWqPTU9EItI0QrA2dWbOdSUBCyBpOcUW+99NvLxS9Hon9/OjWhDm42SKwjs6LLD3vs5Iv7Xv/uP/93/8De3b++IuDYF3JyBQBDi0JovS6lqeRxAvMzneZ6rmgyHmCeJ1f18uZxL0WGwd2/GeZ4Jxu45RmYBTOviaCHJfgzQ9flULhcQkAYIo1ZczuXjPf7n/ykL+/6Am8OuFKvn1i9NpEtuKmBdg6DVy+IsZUjJVciE08jQ2lpbmgM6OoyWuZwux/v7x7u7XLXFGKfdlOI4TaMZTo7T6VTmKhoFyBn7fdwf4mEfYnAigbu5qaGUplpV8zQyJiEmYod7rYYnVCKhGCS7N/WVTBnSVBXG3I96NusRY4C9lF3XsmYb0G8nuwWFAuywLjuBdxdgEPqwxpmM6tr6scOUTAGDNTP1bpJWW8OKslaoKTcEVG1kREE4MnR7WeCtsVJyckgIYHd1Z2IWaiCQxKQowjyEcZHV2c7L+TQvhqKOddHz6fJ8PJrHnFCKl8XmubkhDRajEPdz1YzAHIQ8Be+ZX4GiKy2n+uH7++MTgoZqXB/16WMBwMIhk7Eviy332B3atOPDzS6mfJxPl8tMqgGpuVxO9v71nZXfBKSY87yYFVdtDCdISKRGBHZ3UB9ZbVR5eFB1kLOABXEaEbgt5eE8G5yYnP2//2///eVSS13qvAa6/cVX7/MYbx+fH58e1S8PnyCCGDtaASGEnIK4wr16YjDxbgiHMaVAZT7X9VxLaRWe6u3+NqdEkFrx1Ztvnx5PU3q9+vrw4enD9xcWhMDOMPemSmwkHgcbDzxOAjgHT5OkFWXFPGN0jEN0D+taSynQZRvtEgNiChYJIUdCqSuRcJRX++n29aD1VbdasmJluRQ/5SRpRwyfT7X4smpQ05A4JirnelmKWZvnSy3VnJLkMQ8iUZ3Gw53ayhB3qdWqNwWp6rLoNOZxP9TWmkIkDON0LvXh+UeG3x3u3tzdutHj4/l8PrLkYQy3r/KlpnktKxlT68sAzBzYnbmLp7uC2lDdQhcxca/3G8jM3ARu+OVfvnvz5mZenx24vd1/8+3bGIO7xhQSD7VSjOtMtdVaStWGVoN5KqXVUh/0mIe1d7sxRhKUEpuXEDmlgOYugJuwMBhNQZ3uCjC59rE2u7EYFE7gPlhxsjwOTvCNHux9kLt6VTImJQJFcGCIm1v11rwaAQIEPH88SeY4xRCzeNNoVPH43YmFYoo3r/Y5J23t/DTbbIgkEoeUX928fvPmzU8//eTdiCtAmKFai7eGYZdEpNRq5HEXXLyczdmUNEyZGjdXF4d1sw2Qc/fQMHaXRuIiDDFFs2h/8e37ouvt3RuZpFhz9uoqxAozhWtj29qwVisLj/vJrcyrNbQxSnCtitNlGdxLM+JUXckkyTDGsalSUt7nIq0Wq6TXzRGIGKY4HabxZqhVvOL2VU6eg3BMkRMvdb3Mx6pLTHEcJ2de5rnUK5NOXIJLAAuBkbHj7gXCGhLlTIddWi56f/98OIxZbkCyLmsKw/5uMrG7r+++/fjtr57+0D9n16322aZJwtTdpHrBY+7oEe79xO5OWWxAsWIwJm9WXMWgYLN+FgiY3Bkc+zrbuO3MQFU1jWkSaqtfoEDSeIjpJmCEl5HIYa3VAsEv//LVv/uvv/nd73/96vXNh++e/u5/+cfTEwIzSde0mLJ26dEGuHXHFP/sD/yvH/+KUtExiI5h4YUH8LlYu5Yp+oWRPX+OY/7jh23K+20+Z1vVQ+6wnmCDz8wsfJ5oUq93+uv6AioDZJsG+Wdk6iUIu7d0XTjweeZ6/Y1czqvcDMzJzKD20/cfhpyHIbkveRj3N7loOc0KVia7vb3bD0J1f7qvP/7uE46EgT0gDRb3iHJArGvEMPqyLN/98BQi3r+/rU7NllZhGglxLfX5WE56HMddDIkoEVVvzR0UQJHHUW52N8xUazs9n58fj2TkzESotbbVlg/OvU0BAVgelvm4EsOpV/zBC2x1EHa7sZWZyEOIr17tL8tcq4IhiUOOHMXgrbZaqlW7LKZtU1I7u6J5z24zI2IXN0VF6WosCHIO0zC+fvX6ZncYOH/47uPx0/GH3/2EBnZk4gb3YsLIIZe1gSB9o+y2PkTOShueGuDbcc5wZhgRkavDGb/+x+9vX+2/+Tdvdnm/4MKAWyBQQEiSh2mMSHUpQnEYGKyqdS1LXWtdESmxB3JpTddy4jDFQ37z19M8r7vd7uZwt9vvien7P3z/6fHTyS+lNofP86UtdSgcEcgIjawiMpELNYWxdb8M75oz2mxT3MmMvFsJi3mn/G0UIndH3+L+VU/k11nm9Vb/Y+9zellqLwvnC9ysf5P7lJQ6Qcu/+Ob2y7v7BAiwK4mgz/hp84FhuY5n4O7E9J8Tpfq/eYS21i1svstUHCAIMVis19Sq5hzkaj1gbm7dKMZf8PVuTMAEMiHhF3rblSnWnfbcvAuPjMw2egRfWYB4IUz4NXJra5f7e/zSBrsLSxfBwJyIBQLqenoTsEHgZm7s3LH+K4huCrLNVd8I3tyog2YEg248DO7ciu6D87M3i7YwegcZgSCAkTog7NtQyhxwZZBLcyMlc2J66ULUWnNlRurOXL0to+tURTfngU11qQRwCOF0PuUcx2lIKY5jPg+hzz27JU4ehpgg7O5a1YJESFyXuSynWte7XxyCs3tZWpkLP509CI93KWq4oVuJrySENCawVV2IbD8h8LIu9XJ63g8C3Y3DNKXD5Vz/5Z9//bvvf/rx8el0gYEhHMhqs+RCESGwBCJhQyiNsl0H+8Qi0UWBtpTCZnnM8zzHmN68fX0og6KpQVgkRXPUUvf7PTlFkSFEoXI6nZ/LGiPd3t6QUJmXtawxxxAHITRo0bYs82Vuy1r2d29DjDEPedxXo9P5w/c/3P/0cZkLhl3YTyPROpfizgROqVVzVZRS1drNYYqR4Urk05jCu0w8sgzq6qpuxCxu7IbAkD7xaAzlVmvy6IZWam3NSSINzhxCCkTNvZQziJgsxyiBa2F3F6bdbnz1+vZ3v//N8RGXGUIEUFnNtXWUY02880ykrVqIktN4OBxc5Xx8OB0b0elv/u1Xl+VJa1VQGCQEJAl5CG5mpq1eUhjfvj7UMsbw8dtv3geRn+bTsnoeUgz5XHSw4EIS6dUBeQgEL62UUoTYVeui1jQwFECPRzLUUo2/4C9tDp2bdmNbz7Qh+nTdJewK//vVDvFLJtGXW/O2w/4pAEtN6YXg9MUQ/vpw4s08q8/QOstz+/2+TTT9ZeABAzlT7M9IBHIKwt2RYSNg2QseRC+v0wF3a9YreTgRuH+Bbd/rpvJO7kZC/W0yc1O1XmYJg82Urx5+xCAzwMx74HjYCK9bGQVyg4EYBu7wQr9GANgwvd6v2stYs298Xdi+7WeuDgazCG+cLwmwQ316WM+XS20HDiHmVJuFnKDKOcWQQk4kwap2ey836rlUTIk4MYecUUptWkC4u7vrb1zXBbij1nVtBSCiSGwx0jBsp2mIoC2GGahYljkwQS2llGOYqdZ+DgBqsNaYEQLvRmmEy1mtqQulONAuujsM1QjderFqcJ4vy+Pj8+mCX/7ytVobpjEPqSzLh4/LfKmf7p8fHh/XBW/Gd+tlcV+mXXx9l+mb2/1NUu9GzASGuZuC1hpCUpOmrday1LmdnwAICSBmBlJ0OIuoT8c7X3CbrjkU/pLoRE4C8utsm7jPF90NbuZyve10q9w3gJbIjcCO6pKEQLXW+bKggENHcLvNMjR4CGJOMcd1rQSnxE44LhdnBnsH0MBboWTwwEwEcLfbEJCpNomihlJbay4cja0Vn0/VxTlAm6+znU8grsIZHtxVlVpzEvQJ1Es58OMPH4hDHmIeBqg9P5+WY33+UM7POEwj5iQ+LOWCVYhFJIg6vBGZZ5qf6+VQd7ccw+h2XuZCRqJ0bpf5qN+8/SuAm5YswzAmBWlppVRmH6dxnc02uMOgW6DUdtHmIDJjOOqyGqtVgwESOEWAv//9D+f5sepF2/jq9e7t+8ObNzd54nG0+TI/tQogCMBgRmAK7MLbcjT1nH035pvdkAc5n87aChxCYCG4hxDzYUpxNw43y+nXQURAgTGNwk2bu7lzQErgRCIObsQtDT4MYx5CCMGsnk6LnU0YxKJKpeg6d5ILO9iNWrXajMkwkhlqa62W2tqSkDKNeWLiVopBJfs//+rv97v9Ut/lyMs8z/PRw9vdYT/upnHKpa6Xy6XV9TzP61zMaDdyyrucpiQJlt3QyULnpTWb45BikhDHNA5uLmF4+3bgwOb29Pj08afvyaC/8GmcDru9ealtToFyioebfFqG43ld1rWWBiBEkoDayHtYqTfvcHAfPAtv0qoOCwCmGEYsjtu7ibg+PvzUF+ZuHFVLazUEEmZtuq04Y3J2c5EUEOdzrStqa8va3LfchjxmYs5jGIZxiGk9PYAZW2YHOmFW1Qhd8dFPRIbCbGNb9LOGKTTt1lkOOJgjRxc00j5uMJipMTNYVK1pNQd4A1bCFPI05JBqrfO82NlBGPd5yuOru1dvX72xZs8PzzdvbiWIQi9lKVpOj6e2qql760IQJ4MW19K5G+pgNXNGnjKIal28wN08mgt0qR0cwNWash/1LupCxG6ChqLWbm/2X//im9//8NsUc4jBbUXA8vzcimJ1tYIKa2iCtQjEcw5lLa0t61ok0jQdJF4cnlMcx5jdLkvThgDiFBxsCtXN8a16owgIOIASEJEGcdHSlmVdqeGbX/7CFq+XZu4UaKlza+oAM8XIFBkUQnUSgAxCMTKRmzZt9WZ6U9a5LIva6kzMNUin96lwBEgkrnU9L3OLMV2OaRhvbg6IoGva1eepUic/d9WbX7UlhC1b+Au+kZObKtiNuHozVUeDbNlSFGAMEiCQZHECB3Mxn806N5aKJ+0YD0aEA8ed8I6laA7DLDjP+MtvpjdfxZvbFH/QFMLyiN//HgeaZlqdbWvxALgrdfZLd+MCbb5Df+LxR+jVRoJ60a/8vJyjn//dekbbdQ39sc37n3u6F47bddD4+ff/0dcE+EYG/sxdwRd1ZPeutg1NuFZT1yLq6sJMYEC6KRbHBHXrbMcBH76/v/s3MoRcllMaDjmPbW3n+cxiMXAMkjy7xed2no8zijALDHlIhylDu3N6hdemdS2YK8bnxcVFGjwtS1nP5fhc52fDsuJ1Tje7cRdJ5BLPMBAhiAzDmGWota3nOYgECutSal1abc3ASplGM1czoUDsZs1WhwMRlYuqOQsIQ0xjTs9PTwDSmPMQiP1SZjAkShwiR67dmccIbpsyWMBCMbDD1vVcq7kiMDsiCed9aMXrrHDEId4cDofDjVUsZfnhd9+vz6UcQY4xSggBra2LkjgFQU9KAqwTzQjgrYgH4GiAvBi607Wo6eCxF3z3ux/zQcZ3AcRQKbX1iwiG9VK0ab2szZc40jgGctOibUZZ8c1XryXknHYh+loup8vx4el8OXtTLrRUrp415WF4lScaj88niKUQWEbk8en+HsTu5s2h28LZppXWg5Xoui9sN2JnC5q5yMtawsv/41cuwMt0/zpf73f4JtMm+pz6eQ3W2yDjPj316z2/LTcGdQqOfwaVv0SwNmiMAP7sS0WbPLAzK7vPEnp610aHMu+xbP+Pq/j/5SNY7TNJbFpHdzJjIg7B3FVVdZOu06aidAAcOAVRM4V18pSxb6f1BuL1AZibX0MB3VWNjFi27smc3K9C8P7ZwXuH1Smdna4GJoJsWsr+sTf3HvKiV9oY90RCBgdhmG2ufkREQszcu0nuTjOfW99t2yMmZmJmF/IXKdOf2EP7FmcbBIye1spbM76B9qBeFTclONRYhBhOfWU5FCZorUlgAjGLiNQEd/dq7kwIjrYZo5g7vNXanXpDlBDCbhyUvMFKXR0e8w7dGU6JBBzyMI7M8cRUdGHnaeBIvszzsi7kFBFrSSx0OEy7fSamEMECrXC3cdSYqtaVqT49fZpluTsEAn/33Yf/85/+5YePx6eKccfMRJHBNM9mZsPEYaIUgjqtDWp1vX+Ce13bYZwOu10IybK6qgCSgs56Kef9bne4uTV1I8QUzFHLmkIchwy3wBzYtCzPj/fn53OUKM67m30IKTlEosK1j6GdFa2iNfiQDyTcjKgRSa4qp/N6WeCMmIZpdwBH9XNtak4pZRErpZS1HI9P795+XeplviyllBj48PZuHF4RDw8Pj4/PD24aB9bqMI4pjJEj+5iGIQ0gXS8tUL7ZjU19WctyWUurKfvNzbCfBmAPdoI3bWbaWEEqIaYUhmEgBLXmBg6RKAQG2BDN3Fg2VnkziBkRD+PYmuWH8+VSnk522O8Z7aLHWhYGDymPQ8pJalkV7ra6yX665f2Qkt/d7kqpxJYScgrLWogoj0ND4+Sv3x3UUS9VVUtdg8s8L6dTK7UGllXsqpVF67lO/gL8v+yK/lI5UDdFZ5D39LuNdU4Es6sdwef6bvuRL7/4kxB+d9z72Tf9C/IRbQkaLyq7rRLp0XHbwt/C17oPFDYbui3tgYi6dsMBtZc1DYpMLn17d3c30y6y7jbdTNT93fvctVdi1OXnsl0U+iCPr2kjm1TQtaPV2mcDZNs51W2KhYLDO9C2YVR+PZVwjVZk4p5w1E949n5GXp+WsX1Q/awRbCmA/c1zFg4Cc7+///TwmFTNFFWNJADUnIQl5zGn8bIstTSAzOAgN58vpRFi4k6pWMuXsT5wh5qtS+sjUuHQyUzDmHLmtZAZxxBjiiCGEQse7h+SsLtEkWmclotpK7XXKwrVJiIpUi0mkX0XoCmnQSg6UW2NnNjQDw8h5JS0+vF0NMM4jWpVgmhrx9PTw+O8zHVZChHfTLuyYD63stbLsS7nyzhQHu5YhFlSGsahkohtjstCRGqttQZb5yMQEShYo6aVuW004peymTr69vLRYeNhONwRjF0dpkTCm/O09axBWJcdkQOk2D5nZjYmYxhBIczk1Fora0VDJ0ewww1BWGS7BdKQ11M1YEzZEy6nc2ABXTNSgI103IkVIA6CTtoLpFoSCRyn8+l0GvI+F63avKyNAgKBPMKlNoigJ3RrpCCLttopXtsA3B1Mjw/PRDwMw34/MeH0dDw9aLkgEt/s7j58fEZdy2wh7ZJk1TZfTqCKCTHy6TSH+5B343iTzQgUA8f1VI/Pp0+Y/5t/X4QJwDJfxHPe7TTQ3FbVtVXqpU2XYhJtcdOg0IfPcMgWvKDkCjhE0Cn77k9Pz/N6QcNjnp8eH8eREFbhcnsI+2kf+NhFPL1UCaETCFSIAmNKachxP8bA8FrqurQKYqREOU8sEmKaxv2rm5TCeHx3zkM2p/1++Or94ePT01LbqpCEYYc0EAnyiDRYHuVwMw5TNrfjeWhqTRdmamq2Vq2lLjcwYQnErOrLvKxFidW8SRAJEWQsxFHjKMNIrTYts8FTCAih+tpQxzyOaWxUPAJCcQwhRyOfy3I5n+fL0poSMiSlPOVxH0L+3W8+lqZgN9jzfFzaJSTe7Yc3b+7WaMeHh7XMb968Jo7z+TivVeJka3k+Hj98umeipgWkjkrs+8Pw3l/V6q2u81KHhJSJSPpY39EZKmACgy3YFgdkZnARMGMa5NWbfUg+DrGW+XI5mrMDra0ssGZ1UWvSJwIp5MjMCC1SUynFrDkUKTELqZmTMzarVmGB+zwv2oUixBSIelUoRtaH1sTgHoWu4nCnvj9vZ5OXpfbhJRPFIJICRdJg6kpErTU1g7ZAMLPqiu720qFnI4HAiJ1f7V7fvNlHifN8Wea1PNXFVoHENhyfn2ubXayiIdE47W52N4eb2+Pu+VP++Hz/tJ4XcpZgSCoiIkG9qqtzCEPIGpdarZixQlypMaMHDW+kUQYEEBg7RLVzMCJ2t/sQI0gu8xqoGZuwtNrHziQIDjc3mDG6Ey1fzpdlvsxFb1/lYZhCIPOWhrSbRlX98ccf0Tgyca4FXs51XQoZEbOixj2bWUhC7BxMEq91Pi1lXUvg9Iu7bys3QVvWIklc5xBFvbKA2EEaAmKKMQWQVVNmmLdaa5kLjdKKF52DeshMrBJIBLspjeNA4BTTOi/Pz8/wlW5wSEQZN6+H9bGCtG/f2wCbhLYuytER1t7V9GKnQ/x9mtUFh0LOpt7MnAgUKAToBoc6BBQQxujiKmpMAJgdzUutMgB9690BQ1t9pgYnygl5J3HFf/kfvvnFX944Ln/1F99YsePDghkx746+BLbPvfF1LgbAO/mil3kvYsIvu6Mve+7PrbW7/czqdON6uG9gGDo+9LNqz/5U7Qf8qae9Bmj5l9ZajpecLWzzROBLZ+gvn/GqNnypiD5f+wuxopM3NkYE+nWO097aXEsLERD84z/8p799+3WOAwFaqyEz4NaaNTdWJdHAVa2ZVUMBi0ARlPfDXV0cSVql06Ve5trP/3lueUdxF5iSWytrMw0xca1WG18uldnNeZz2QlTX0tY6l7lFJZA3qsXcvBYrXMQ3MAAAIABJREFUs1kDBCLxcDjUS1vLQh1vQqjalloResBklTjFNNS2EQXVoNrcKQQaKLqAo0giY5gbB0RJ5DB1awaQsEROptpq7c0wCZjdWMdp0CZnvzT1/W632++06fPH53Jcnz6dUZBCIEW9WLNGLIfd6Ib1okbscCNX6NUbxCEb2ejFZmgjCJqbyhW5sTiEH394vntz4+NQ81pWrcoph0ChLe3p46M06GpFS55CfDOGKAMnhEbakoy1EXlKKYSQi5bqjUIMgmrl8fHeuO6mnZpXW0ub3Zu3DCBCUK2g4krCcXN37YpM755L3SsY1yXT77qOe2yB5j/DiT+Tnr6AiZn5Jai9ryn+ct1cM6foOkC9/r7Npb1DW9u/qEMaV53z554OXfDe0S83EAOyVbC94XMmtis29LLs/79HrwCE6wsGubmTq4KJWHogsekGvKg1B5ggG7+KiahpvRpAOdDxmW5BRUTdwMXhUG/usOamDkKWFGJQNHLug4guBXL/DB697DPcc5L8M/kU7mWumxdaL7c3GI1EJHAgIQW2BC7urBnrd4URruSPLzpnB+A9gETNTLu5Mvqroc/IvpuTubpe/0PHM5lZNjh0o8n212qmFSLsbmAymHeFqQOdZqHWTIlliHFIyQy1VTNnEwtwL9qs1lqoEmlTqrWYpRB4GDMYS11rnaNkOF9Oq5nGJCzQdlGlacp7OZxOpnF+WJ4SyX6aXh0O63ltayOyqsviFfWiVqXIlCOjMhGLjWniIU9ZLud12L0y948/ffj1r/9wf39Uk3FgdW9VXT3mME47c1XztbmQmppWBAZhaa2aLne3u7u7wxgTMaUhMywPaRzfl3VJYw4U1lqaKZGV2lRrHrKrtbYaHFFcq9msbWUXVROSMU+QoNRTe1jSQK7KScMQant8ejTDZV6Haf/m3VfDuBum23z5ZJsxBuc87pyOp7kWjTEFcTetTedlBUxVWytNVyByR8sBIdbaytrMxKoKS5ScowT2HMckqWrxZuM0TdMOJOd5efbjeVmYJJKI9/3U4d5q7V30Yb+PcZymmxjzu7fftvVe20weTIW5h8UWK6tqizH2aCFicoOpC8cYI7jAMZ/nILIbp9O5tdqEMaRIUIIFRmtal7mWOU/jfj+VUk+nU9PLNA7ueHp6pjCN41Bt9eS3d4fn0+nS1o7jWLN1WS6nUssKvxqSM/U4K7MXN6jP+1Tvua9733Z+MXV2+4aj0DVxxtHtQHFFkb+oef78w1/+sXE6rhRN/vxTV2PODpmRO9mWgkwvxcxWf2NLaXB37UFsQZiFhVsnxtjLls49ZZHAMEPnK5sxhITJYUTEBnhHrYiIiXvlqlX7WUIEIXbueEHv6sl7eFgzb1sSXOCNd2NmJNKR+M8143aCu5k3beRdOLM5rIA2kfzPBpLbXAFMDCE3NTO37cJUtS2g9/rDjz++/RjCUE+XcwVA0sy0VJYQUxp2ezmfl7X1PRIOre15Pp4Wmvbx7du7adpLILV6Pp9rrcJJSNyslcWZ08DdYS0IjWMGJK0NJMM47fYHYVZ3YT8/fLcSxTjmOB0OoaxuzqDazOdF4RY4hMjVirjsxmwa2EWrazGtLVz1oY0Rg0zjuLqtpeUEAMzUtM7L5fHx8fGpaQO6eU2Q89KsCUNK0U/PeP34fPd6t79NwQITD5bB3NRaJXBHmtRgplpr7XcRRKBKZODr/GWbXAnMvTNt+0dHn4neXhwGODFzAHXMSt02uQN1DzN0x4Qe401XKQdF7lOnIHEchuNaYW4VJO7wEIKZzec5pbTb705Pp7Y6iCRLaMm9bUukW/xvFD2YOxNJCH2IxhywzswCxvPz8+45f/PqZl6LGbszuREhhBwk94sVDiElt1CTuVuKHCRc7YpBTK6+FKvrhR0pR6tuCnbkOO7y4V+O3/uSuOVgiSgFTjxFSGtU6vGUx/z0dMr3g/GhNYiEQXbGK+nlaa6n53OIGFN4OjYjE44cQxhCWcra1g63E9AdOoUdV3LMJjQWSIB2phsjxRBiJg7mSmRDjCVUFpRSL5ez8ZnCMo5jzoOwW/NeH8UQANS6NvUQY4rxzeE1yMHNWlnXc10KHKHHXOYhpuRAKSUEuSzPr+9u5rW1hjHHN28Oyk3hq63VC0efJkpjur3dH/b7/X5gMV1Ka0W1MvM4Dqqq6qZOyPM5wDoox1Xr83Obl+rU8qB5CGkIachDljzUlI25EhuLmWox3R2k1tqshUGGPFRbSKhaq9qCVSN1dmMKOUkk4SEOgzo/nc5tOf7qV78zJU4EoeN8vNQlJp722cxL3V2eTqUsOU1S64dPj9ba7e1tW5ZlPn26vz+MGWQiXNu6LOdxmt6/u4shDUM6HudqP5rR5onvjk2FtYXwGC1Ove93J0jiIcv7d6+/+eW727uxtvk0n9xqa/7wfDaz12/2zLHU6mUdxx2L5DQAgSjw6lS8WBGiECBCRKDYI0dT7zIY1Fo9H9fIcAcLhxiZmchA4MDkDHcy7qccCZG7dbNC7fGDhHaFdolIWCiCACwb9+OaBPKSCrLlUpFbs7vb/X63J8iyzAwepiFyqmu9PD98eLz/bfv9dmx1jlcER+TDGEMehnGRJaf85tU7KvRpvq+oIRIP1JPVEsV+nuYUWbgUM1WlBhJEd91AeCICk7OTdBjLLXp34cn7FHJ4+PTIJI/Hp6Q5jkLC2gygFNIoA2XWYsrmySiABa22eS5wwIiN4aKqaNyqX+ZyfjRyy4FRC+pal9LUh5BjFqikyE2rRBZyEZJIa1mO89HcX90MTVtppVQ9Hp/TlOdlCQnSww9N3ZxYY4ghkhkR4K5mVmutFafjvFxW4xYHpEQUIpHWYmSJiVR9GMbT4+V08XlZdmlGiTmP33zzzXfzDysuWyWAsG21Pcp9O5mtt1xbm9Q9+rq6vFOOBS6937BIIlECc4OCTTukJeQRSmpiHpwSBWY2orXt7iYLvmCRKXjUU1mIkcLwfHm6GdIvvxn+4m/evH03/PjTb/6Lv/4P//C//fY3v/oBJV8WA0G9OlF3+cFL++N9Us/kJNvr+zPV2ZdQ0BetXG+gO1P/hUWCK+dj66Q3dOzPqo+cN0HNF8ypl3nmNoD80+WjbyUiXYPbmFjdNx7udYXhem9vlLMXadE2Mbx2q87oPntgcoE3VPzv//Efvv6v4vQtDfnmPOvD0ydwMFeDaq1eVCqCi9aGBhiJixmy5P14MOMkY4ym+lwKOgHjdNG9BaBzdoQZIqJC0+1ILGvVUmb3Nk4xcqhLK0urWqfsURJD1qW2UmpzVoqcggThQEQQkJCZEZMEgZOKGZsWT4f87uv3zPT0dO9WX93etlaYyc2IkULwSBzE2KtWbZXgEkPgACKv6go4eWuqjQgh9KmpNW/MRAFReNzHFNLr13djHB9+ePj+9z8tn5ZWgBmRnV3aqj7bsM95nLTZ5fQccrBNUEcgA6lvXFaQfVZAEIn3Fs6caJM4kDNOoCp1tef5pA0xxsjZmy7nMh+XgcgLaUUjoxbGIeeQIjTAHz8cl9Xq4tNtejqdZTSJbK5ucK/N0CwtBTAI6Zhia3Y6Pntt4gEGqxXYzJRQTdXJt/Rc8j5E7oue4ObO6E3VlUK8wU2d2kvE177pj5bPVSziIII5fSHFBfAlQvXlqrxKMro+4zpuITJjp8+L+7MEl4hoE928dDdOrmTc4837K/rZk/z/8QjYojJggJB2ZzbanIFNjBkgCSQRZAQBoKattabKXfthADtk4zpo61YXnVzM3FWHvYPsMGmgPMRaG3dxAV+FRQ530p5bSkxEMMdLjLx3rJWIsMzLVYbtRt5vZ2ISYeHeNIpanxf0hqHvc27eyc+8tb3+GcSVKCGKraV35hvQZGZM/Hlq7i95rb514M4CEbbO8HMQ+1U4YwQzBZH0cofCy/QFQsGN52XOKRkRB2GHtoZS1UFOcKgaVVWoubGW1gqgEjGMwcW18CjD3e0rd5xOZ9Ua8m219vxwWtby7S/f7faTYZnLZRwlxxSYhPz29SDg5bJczka8SJAscTeNhzGhraVWRlvXi6u30mLYf/3uXZnln+9///HDvSog7E5LadO4U2/LcbEJr94cYoDrcinrai0wouD9q32rtZallmrmwqF4WdYlsA9D+uqrt58eHlxdQWutzcyIamshyN3d3Xq51FXXupLFGGhIqQ1GHgEyMxFx91ILOMQYJWYz5eASzIg/fLpflvL4+HT36v3NqzeHw+Hudn9eLktVtdLKGnI6pKlVLe3EbCLE1Zt2o9zZtPWsh7XW8+l4PpnTCABu63IJIQt7RyyFI6Gpoiw6z+tuvxOaAu1iTIEPmW/uWquqrdZP98/ny0mYmMnJ0iB3d7c3N7fTuI9xIE5ff/318Xl9Pi51aXUpzIk5AqalgZDvZL+fCFjKDG61VjOVICnFNPD9T5/evjuM49DqMi+N1QOh1UrWJHAznRd9fnq8sZan6enh8XSZq3rK+9NxfXqqr19jtwtrM2Udx+l0PC1lZUcOkbWpWlmtFGjriHofliJE8nW5yoK+sAfosj1+MST3Tsb0bWPb1Afs7B2ufmHRYxMkXpGXn1Gxvnz8OX8EYurfMrN+xnweWVw5UyShL3ZsAztCTwbt7CkzJ8CZWZiJFe71el1wc5er3viq9UKPG2XuFZ1vxuh9M2di6bVPWYugg9sgBiDW8+YI7GTmrq5N0eNce8MEmJo17ZjZduZI38Z6oevq2l1VaAO4HIyOQPTxZqeWgLomnV7e0V5Ddq5IEJbox/W0v9mvawN4nHZ8DrWUEIODtDVzj8O4m3bDMB7Pl1qViAii6udzezjC3N+/l/3+EFaal9N8OTW1nDjn2FPYhCWIzMvSGlIK0zjUqrUYEQ8p7HJyt+PlPJdVPLTWgoScxpj5cm5LKU5e1YUNPd9ORCQRRmpSm5ZWyR1MtS6U+0CjW/ovKZOv4o6cwTAOgUzXdXVQEABoBZeLXey5nRJDYk7cSql6OrV1KfubBHMWIhZjb1WbklkzyuZkzgZqCqzwHUg4iLCIM1RfHGE5IFToVSreIfGX4TZbU74aZ4KYmQ3E4D6zY2OlTXm4LQsHgQlC7kMaayuqOk3jYX+YLzPcTTUwB6YYYmn1eDp+/f79dDh8+vhQLqVqDZOHLGXVXrD71USt30PNNRFRIFLR1mJMZXEKworzXC6nNYah6aNdGzF1xJBDCP0OZSamEKPEVB2WssQoElzEwbItTwUFhDDEkBhzK6WsGCc57A8ppVopEJH6us5WC2fev705jLvTIsMUn8vDPK9pTmubKSAOeRzjPC15fbwsDSw55jQ2b3aenyMPksLIB2LU9XmDFXvZYBsm3xWO7lByGJurwqMg9XrArGkLbjFxIIwDco4sQdVg8zTs9/sRprXWda4hhJwGM7ucq6vnJLtx+su/+na5zKfz0/Pxsi5nZsSIEGKUlGKKKbdmj48PyZ/OT8dvfvnXyzy3KoF8N4Q3r27zlKqvD6ePp2WOud3sd+/f3t7e3IYwHJ/m0/HxdDyt85mQhpgKtDUNIYxpOD8JzEWYA6+1PX0q59lLc4R1t1tfv813ITMHETNbV7UQwn4/lqWta70/rscjWv0Us79+9Xqt61JKXFcWNB3X0kjCOO5knwlCKiLpPJdP9w/3Hx4//HR2ozhESXxZl7kiZqutDcMwDkPOUwhJKGnTp+eL1/b67pWJny8PWp8p/FWS0NTn43PVlke5ORx2u9vdfv/p4fjb7398PNbItcu+zUydBEyACFaDccO1Ll/NnOzm1f7rr999/e3bf/6nv1/KHENmac/PRRWvX1MIsZS1tjJOO2YWcXLehrjOQx6nqfGC87p5oufRmrauo09DNjeUFROCcwwxpRwlNNIkAS5QNzWtPca29cLVXGGKPhT5OXHY4GA4WanN0YgFBIkccyQirQoGupahOgrgvMv7yOJze/j08Om392zszeZzIUKMwcqmuwlCRFJqmz/O6/H7j99/EI/f/s0vv373VXjN7VSP7Uiw8+mMiJEgU3TyqiXvhhDD+byss3pTMBDguNKv4Ma6jeLFEbvxNxAwvdprsh8ffphu9nMtUSNYhGUtDUBKMgxjYNFq6rro0kwVSImYYQZtrbS61rWsqyvWtj4+njBvebsVtawzGoGIQg6Ds7U4yLqqQhMj5SCJKrXWPArfHG7rRde1LUu5f3waSpzXursNwxA6ANfnXM5upqoKbZ0A29mwDw8Pbi2NyCnv9/umSmjLZfZmtfxftL3JkiRbciWmwx3MzKeYMt+Ur1CFQgEQoNEUCptkryj8C677T7noRS+aTQoxFqZ6c76XGZkR4e423EFVubjmkVmFIgmSQpOQSI9IczcPtzuoHj16zkQ++uBVaS5gMyjZkub97iq6/puvvgYCRaOV2EqXSAmBQETXyKQ1NSOAtjS8ORISgCACEpmqGACJd+Rc60MyK2AGhiJahaTZcjpmYk9Am21/8+JgXkaZweui87xY5yJFOr6fdtty+2KzPbjNxv/N//bdv/njf/ebf/zqh9dvN247PsxgHxGpnllMq5fImoF9XP3/fceawj7HhJdffRTY/c4TDJg+4n3Zmkv+yyYYwsv9Ws/ENVW7YG2GwC3A+y0pH7BncYs24QDNjBHlQ9HUzEBRAC4NXgZAZmTPpPLnvBDQAKikRAjRR3AIOf/4+vF4Gn2lELqHp+n163McOA6B2ERynQylRCsli1aDuYqrAAoVHQStCkaEpKpaBRAgUNczQMkZQLgUVMNaaj7Nm0/3jliVkeo0p3HKDGSlOOeut1cx9DXneVxKKnWpkMCCcy6iWJoXcValSK1q0nicxEidNRev/tB9+uoup7SUh1L0+uqqlCJV52UyhKrV+0AOq6pKqVIa3ZsiO3amlkVUpLZ8zjvvHRqoapGaFLwuDBg6d7e/ubu69RaOeszLUo+22XXjeSlVahbG6HaOiKZxFmnsULjc4FalpSYI1TILsibKYO0uiQIYGK9FxTQnIBg2G8+6nEfv3LDZSuGcdJkqGHgXlC3lLIZoFFxPjKiCol//8A6WYgucjzSNj3dfHg6bO+tkXhaptYCwYjrO87SQQeDOKWkpZQEkAkEoBgYYyDFXA6uKTfxh1W63lgHAmongs1zeqqT+XH4nJgJEfMaqfgf/tYuvHxJqrRd21fPnhc/T8jJbAA2bed0zenWBbmHtn0NcyUmXvOF5cuOFo3NhAuAq0GLP8+j38TP//zkYIhJzDP0mboPrIWNdZDmn5ZTSuZRzrbPoIpLMMjkIHoLH4MB7CIQUfPTBB+8YqS0QhNi2gBi7i2nLKiTSikhVZUozOlWrqiKXLzBhhuB9jJEvzQ8IxoyeHZpp1VqqVHU+rHluo8goSBM9LzktS65JsfpAYFKtiDXZY0ACM/DOo5nJJSVgQAfIUEutuVRTRCAG40txDGyVzVLTywbUOHWtyC5WixSBQs6YL1SOphEmZmpStFYxAxMEMySHyGIgWn0MxlgkK4pypQ6HQx+iB6rAKKA1FyvmGKWCahKda53m9FRR46HPUM/LNKZlTnnY7nz0gLq/6jY7Py5Pj4/3psuO3MaHTeg8s5Z8eno8n8YuuFeffPry5u6qG+bH8/sf3kxvHjBP+37bxS64sNtc3V7f/fkv/+KLl3/w/T88/s//8T9OU/WbHbrewGfRruurVPI4bPpclyWdDTIwGgNG9sEHcF9+9sWf/OpPP3v5KRiez+dlzlr13buH7757fR4TABOFVgNPmlNtDoAdEgUfPvvks8PuynPoXPfl53+w3x9KFfbu+vb23fv3X37x5csXnznvp3l+9/5+Xub7+/tvv/v63bt7IfUdd31MZXrz9nvn4LPPbm9vdkg1eBWc5/wQPN5e77YxzueH8ykT2udfdL/61c8c+3cPTw/vFxV2HEEJOXrXnU6n8/jkGKepzrPsB7q9udoMXc7JFJ2PYP7nX/55mfib37z9L//5L//T//LdN1//+ObHN998+/afvnr/3Xfj/X05HvM8yem9vP5m/oe/efq7f/ppOr4Prttvt9fXV8MwyATvju/7vs9pBoIiCT2Cg25jw44Up35Dw9YTWyl5mpdpSnmRoiVEDM4xmqfy81efSUqS5r6PwTnHtBm67XYYOt70fre9+9tf//Dt95P322F7qPlhmtMynsym83kpxZalOBLvoKRZEmzj7nhfv/76VM4AKRJHZKoqc04OAyiB0qrOo23bh6afXiWLViVQrIJVUJTEuDXyrf1ngIbIiOSQVz+jZ8tPJCJk5rZki4iorJNwLVliy5fbd0Ricghkrf7tHCGu06/9qlnJisKqitWs31ZemVYxUWoMTiRTEFFTNDMVaxQYjNHWZ4MiNWkSRDIAYmfEVRWIgBAcATtDkhUYoLokVW1Xb/It0FrBcjWwEIJrCwdddqp1kUH0DEaEzETsCBAERFXFVqvCBghqa9dTU7HVzgpbt2I7u6rWi7u7KoqAmGQE3B52YDDm2aLmqp/+/LC/7f2Ap/mshvO8TON8nsaHp/ePT4/s3JLrTz/+OE351c9+XgVUnZGgs8dHHc/HwDx0A6hEb4d9HwOZavAhhK0Z5JyHuL25vnbkl3kKPgbv9/tdF4cfX//497/+5rtvHt+/OUuW4ynNc5mmtKS83Q0vP7nb73cpLQbZB2Km02lOI08nfHqc01RzqXlJZTlu77apjKLl7hP6t//dH/zJX7wSeLp/+gcw+KM/fElk43k8Pc1v3r6fZxxHMAjDZkcuzE/L/vqu7wJa8a54tsOGbm8214dd7OK8TEstWXXYbcOmR2f/9JvvplEdbQPvyxz+7q/emFktpmaiAlrNQAQcMZMDAWw8TiA0bsVeMG1mtlSRgAhQzXKtudRapcFdaKBqoEBALnjyqx2UmrYJkeYZkJk55Xw6HrvQ++iEWpJtJZd+6J1zaVlMdbfdAsmocy65SlFRraqm5NmFQAwKxsTOOzMAVSBUFeeh3/vT/ZmHXny8uf3k57/8xZTPD09vTindvej/6Fc/e3p6msu5i4KgjOi8n6b54eFhWqpaNpRU5yolxni4uTke83bYkfma5P6n9466zneMhOR88N9//cZAxCXyVWzEWPuDBy7zcl4kbfo4T8s8zcMw/Om/+dM39z89vH9MS8qpnsecFvnk7lXsYinLeSz7bXDkMNs8Q99vEFLzSW5BSlNT1osd5FrlQiWG1l7tvHOeDOqSzsBlztJ18MlnLz/99NP9dtd14FxdlnMt5e72CkBNspSU5rNjurk+3N29uL66ub66TvPsPKlJldoPw267G/oNoXMUHMfptKgQQUAKPgzjOJs2F1fuu839m5/yPDuGly8Pr748fPbp/uX1Fpb84zf/9Pa7b3/67qfp4SmdZ1LzgL2Pg48okM7zcsrLo5mE4/vpm29/ergfc7Ja4JPbq5ur+PhjfjzXN2/Hx/vj+TzmJYfgCH2tJtUQmAlUy89evXr16rNS5M2bd32/STWfzqeu2xB7AD49zY+Pp+PTqJV2wyH4/u1PD3/51+8zQUXIIEXVkJmRAVXg/n766qv3n9xdn07LNC3Hp2k8z70fvv7qp2XEbhieTmcDZh9CdEAWepqXI3s/LxmBXn356r/9d//NH/3iFZulZVYBNQuRYnRqlqdiBN1AWGC3i/sX+h/+w//0P/4P//1m6x+Pb3+6f/2Xf/23qSRifHxK5OrdTd+Foe+2m2FHSI/v75f5VHI2tZLK8Wl6eji9f/c0Tqnr4n47xA73++5w2BEiIcYQVRDBXV1dX2+uBz9QxeW0jE/j9DSeH+flcV6e5undYlMdeDPwENH1zkXvV6lQRKjI6rp+40NHgf3e88GJ01qrZEHPLrpqtWLtNvFws48xSs1DN9ze3Ryu97/87A8ffnz31d//47tvn9JTrk9SjlUX8QpOGAugEAiyUgtBrQII2GJyErPy7ut33/z6a8f8x7/6Y4/80+MDaQCipFpAiVzYxqfplKV0wfvApk0YzsgF13duE7AjjQBBoQeIAB6gh+0X19sX14uW9+Xtgvm0nKEHcQWQnPcheFMtWgrkRadRz0lz3+2GzVBrOc0nRLh7uYmDKzITC3oVS+O0pMlkBhTPzr+4vf381eeP472xQchxq1d3cXPg2xfxk8/3+6sNEDwdj8enYhV6FwP2kXc/fX//9od7MyiiSJBFF1N0NKX09n1W08N+G0JIKSPQpt+UZGkuh22XcmaGbnDOh5ykFiBgRzzN6TgtLz457Pc7rt13378FhHmZ3z6cQ+dffP7yz//rv/i7v/81KKBD18daRav2mz1ZWJZ5d3O9nM8EwI4UFAiAENkBOQMHANSRVVFV7jnuO+k0U7XOqCeMtj90ty8P221fsk5jhgLB94RuKXWRKiCzLdyTG7DYmCVhdNhtyVsc0s2N/ft//4ttb9//5hsPh8G9+oe/+vH73zyd3+Xbl7v5NBE5cIzMQE1/nYjZ1EAAQREVUQERqDmZ4CqOs2rA2Noka2uNrkkjr19rPw/iugk2DoGpagP4CIiQWrmL2tWfnwuIgCYKRaACKpAiaaMkEl6q/mQrKKAihCttvl16VURd396q4tASyVbUbEVQZFQ0YFjDOTQzRQbn0XWBXFNgQCYkI0OtoJMu4CFcxZ/9ySf7F37J+nSqx9N4Hs0Mtpt98IPjzlG/LPj4sMznYqPUUqrWuAtf/PyLf/7mN+N4LprUKjgpUwWwX/7BL375xz/rIt+/fdBKx/s5TRUivPryVu2c8kOuJ0Bhh96B82xYyNPdi+v94aoRIELoN7t954eyyDxmQldBRLOxuD50u0gDWVBzJt7cFdx+PoArixzdoLyRsT6Odlxopg3GQxcO0W9CMTmfx3GqDBCQyGCZUs3L9fUtM6elFIBcpZpSxxhZHBVXf/6rVz+9e/jk5uUvf/HLbdzYyb779fff/9N3y71ChpIqAIG10EypAAAgAElEQVQSsyMmNalam8uxolhjdoERKgMikgNkZEYm5NWbD0FAxSpABX5W9qBhuCrp/LNffbb/1N8//XT32VUI201/p6U7vkso1A29WrW+Dtfdze3deK4g8f770+uv7uFUUdgWkccZzja9Xaa349320+vN7fKQ60mevh2Xp+wKhexh4vxQ5clo8Z10ZalrX1Y2yU1I35m28QRWBWoF1Sa9KKqrXBICIPjOsSfi9gWX2jOISJXa6ECiIiJS5Znr1Ixy2AVkh8iABMSErM1+HQmYCRnbdySC5kJNq6IhYS0iptZ61QmRiZkAlGiVgSBE7x2AmQiYeee8cwiQluwcg7XeDDGTVVHOGuv4uVH4X4trrRngbx+/90zHIRAjAWlVVc0pSxUwxFXNDgiaXx+BoYKKKDtix+ycFoELVH0hjwICEmPTz2rNnG2mi60laCREBm1lhwshFAwUoBRVzWqCyPaMNGqzYTFQA13XyvVWIyIik0OqgoIXj9MmAmIrde4yLlCRGteQlHRl0F3ewIc1EtYnrKAbXH5uJmuwklZxTZ/X4YNN+8YaE639ysBo5Q0jmjZBejRQQGpSyqjaqHnNEgytJKmE4IIDk+YxZthai0AFRAy4eZ7VNJ7HKRFwcMEHpyZzmhkqDtF755wvpTKo1SqIFTMzE+F2M9RSHWIp2SN2/ebu6vqqHwaPQ2CKXhBMkASCeBbSRSTVeYFxBseZogNTW5JGd3dzQNKn4wmpHA7DnMaaZb/bHA4dmr26e9mRP4/LsqS2T5jIOJ6eHh9LTqHrcxHEx867zvnYd5uha0ioc65jNy9FcrYKYPzmzcP5PI5TNnRPT2OMgxo+HU9Px2NasueOYzhzkgxPp+PdqxtVVZmlZjMzKWglOvzkbn+e47unR5FS8tNSRAvsN/5w4ND7q5v94bB7++YNAXXRRd8H15GRYVeV2KMIpGyeYbeFrncAoiqOQx8H76KK/Of/9Nel6Ok8jkdytSly9OwZdVm0FAUCMuEhDEPQss0COS3y+vWbZVnYeQA2rkA2LuOwG1KpjK7Wsrvyh/0GsRKZSE7ZHEEuWmsBBN8xopZkpZpDJvJSlYmGYes9CpiqkXOOfU75eDx+8tm1QmDnxPw0ZTNwDDGCDywo3gcwK4CqjdtKTXLDMxTn1DkwBgAk8i6YrEI+KxWjNQU+rzLY+gU/4ssjAGrj9rbohRroArjqkP9WcW5F/u2iZvVx9ex3z/2XZT0zvOi4m1mT4gMFZrZWtQG41AtWj97nakKrMBCQgJmRXSqPz31fK42mvYKZffS4UVCAiJifS5jNAPG5ammNCQqqeOkIa/p/pqYqCGSXFkCA1aPkY0qakZFc1qlLpeNDJf+3S6MfHlO7I9AgEFQgNNVaq4i0vmZVG8c5LaUUKsWqai41lZJrRYLmtsHsun6DrnG0PTtlF5gleHMc1GBJaZrH2+vBoJaccs6mtRaWqmi+VstJSim1inOV2TtyYGJijmA7wNDH1z+k7QY327jZbdm7UnM6ZST65LMXu8P2/v37aT7XCqUWqQFBzTkkNAYgO49vwcFmD4e7YdiRj6LNWNCASZj9MPQlJaaujwFBDRxT10WCu0BLs05nEEZQEZWiABi89z5YWZp7cK5Vay618WiC4wjPxajG7DYAdtQkL6HpmxI0bmEbIICgK8O5lULwg+zmat9x2bYIQKB1nK79rGv1rI0ZZN+sfgmoGWFq24MUlCEQO+/QEQOGzoNgN0QAKKVIEZtYQBVETVFVUQkJCEutJhY5OCIFLHVG56BDZASRZZnHeawyK2UfgJyqFfaOKxngMOwQwpyKSBmGbsPMjOgrgJlJqjKel+DDeE5WqR/IuZDmAoKmBAjTNIIHYtRiRQogoAcFMVUBcYyPxyfy2G16A3l6fDifHgNtkGHJCR2Q42pyuDnkeS4pPz2lYJV86HYbZGZ2QIRkVcwAUdEQwDUehLRWq2deXGs6Vq1mgoQiFhzEGJhJtFZxrT0r+i6GgA2thLUvuIrMS85ZEV3wxRESOULXhY3z6B0D2rKkNJe0yDSlvnfD0G37raos47wsS85ZCoA5SUsxMXChq947jsgGpCVydMG0pGxWAUSRCBw6ouDJGBiATuOkAjkXFCRqdHCzSiae/DSwKQAKllFHk+hEN+bYgZKpEfrNJgDaPM+qwozTPM1pCaE7nqc0pVpNFMwwZ9E0dt3Ux8EAQgDyQB672MWuY6ScckppGjMCOA+OB89GiI7hsKXXr3/KWesyzYsWAeJo6BRaMA4FTKWCsUHNaTSzq0P/Z3/2R9dXV+8fTm/ePBxPUynVRRe3KIt99tkn19f7zz/7pB/CJy9vU56qLI+n+3kacwHvEVC73rySgqac3LT4wCJ6c307z2MpisZViQBVSSpqtWUuAGogxFSWnGsVBUMSMVOsbLQdrGrJtSylllqLQQG2i56IYJpShtxtfD/EEPB4zrkUT2F71Wui6GI1XXSuKpLHNW704DwTIwoa2FISjGqCXey2w67ves3607evz++OOgMJOER2K50H22pjBK0dAFYhykt3FhgaF1YTA3i8f/iGviJHN/vr8ziOJjrWcNVxTwISog/eRxexs8B+fJyWsaplRQWrgAAMEAAcAAJ4AAcVEyFyj058teIYEcmqSpWU0u3tbRc7A2VHxWou2YRQcVmWaTqDghJM4+w63Wz7ftMvy5zq0kXabzY/jskycgu9SZAbQQYEEjgIMZADgKIAhsoMwYE12Qig8/FcpIIHIuCATbHIvFMlUfIsTCwKkFUKIEBGrckkQ3ISgiM254PzHTMCGDH6EBTBhclMU62VKgSAGQgJvCZNj+P7eZl++W+/vP/h4enHc5onIApdV6wWqUC4pBkCEQGiUZNCabkt6SWkQWQ0BwKmkpWFHGJoS77zPoQYnHNGxM7VLIxOCqiYSC0lBerRAZCoVWTwjlLNS04hwF/8xRdXVyE/jiVVB7s33z+luVlRwfHx/cdUjDVnBVwtcS9eH7a2CH3MlG/hD67BSjsP/2Vk9vsPurgAGdhHvHH7l4wttDbsLoEMADR5KlvbCc1A4OJic2GmXN717zku2h7rj63/ylYxyGeICwFAmyexNedDRVtFmBABmQ1qqVaKmhJziKHvu021jEAPj8ecszfe9jddN8RYTc/gARR8x+zw/cP794/vtjBswkBch87NAYxBodaSai1IFLvY75BiJQLRBVl8BDHKqCWLIXAb/WU6jieG5TieahU2yKWAkhL4GEIMi43eeSQ01CRJQRSACfpNGLZxGLbeeQR4PB2nfKoCYoBswGqSejfM05KWEkPsHZdc0lhSlS5CDF0IgYjtimiaDZSIXQwIiFCbxPb+4LOmd2/uO+jzm/zmh/s6AyFQIKssqoCXbrSLT9NHDbcKa30b1qF2ad2A9QY2t7TGCWt3XExqsQ4Y5jS6BAJa8qLIaGHJVtXqeXxIMznttwGwHs/HPOqY0+PDiYy0qknF4HyIQM5UlznZhBQ5PRXLCgIkkJYKjnZD731YclrmMs8zt/gPyVBxTTUaVkqIBkRt8DZFNZIGvQI2rc51BVgnE+BF5qn9sCpkXc5oTS9ErXWMcT1hzX1aSkCgCGjWJsbKPod1yjzTI5lpbUy5dAo21/ImRNAutlpngKGZqK78L2ry6c/XXQEXu/zzfzb7/r8fLg6x7WvVpEiuKUOFRleG9e8CaUNJRKuSqy46T94FtrKmmYDPLUAGBA5cazOkJlHOvPI96dLsz1gww0XApi15rZNBzKDdjwYVGV4wehWVj8E8WumkRKs17eXttpdqCJG17JEIyQwRlQCVgIya0maTjhFr2nDQeB1IzWXi8gmsWaIRsppcJhBd/JHXDpDVmUU/WtXXkahgCFqhpS4IUK0l2cqGyLwux6qqauYDu8CtpttWS3RrgixqKmsboiSV0QQqb7gLkQBryezMIQdiQEfmQLMkyFpUxTnnvWNmx84hqWoRiV3Y9D2CbRx5sKKSSjaDjnzHviPvL1PNAICxH4LzirwJwXWMw2bTM1aZD7vhXV6cw1+8/OzTz2/zsmhaxjSX8UlrJaQQXHBOVRVBAMZpOk9jmqc+9Pthd3NzYzsnSrkoQ9EupmlmwE0MPsanxzdTEnKRKE5zvr25NePTcRxPs5h2m433MboRFJY5lZQ3u81mGDy7p8fH8+mp1hK77sXt7ZXZMHTjMosCVl8zVBAXHTpgx1KKYxr66Ng5cCo1LypQXbfd7TvVbc0LgGwG10WPCCWLKojo6TQ9PU5/81f3wTXJQwAHqqCCjtm54NUk11rULBO42IVuM5RK8zy9efvmPJ28D/vD9bALn728/f71u+2uyw9HYkaE2HXO+yrS9mk0EoGSS0liBYxAqk3zcn112GwHgoDsCZXJRPOcc621I1aDXOTHN+ftTUlJq7IgMfPhcC116jtHXaA5dyEiGmLMS20raa2l1moAxKhkJk1GDohQpEUtCq0l7QNf9QKiIMBabntebT56uOLzYGtIgL/TGnhBhz7iov/Wf/9WaGPP1NWVgY5NNu/jzWBlkCNeFnW4TM5LFPL8LuGCBNmz8uGFe2sXfXZ4DuPgWcUCTAEZGsm+Vf0+hsRx1UFazQlNgRthrXGmDKzCKqC12ju1qzzj8g3G++hF8aOm8wvOdgm6zC6t6es2stZy7PKiBlbXTBQBSKqejmNKokKIVKosJc95KbUSYao1lQKEvuvAacqpigBCjHEwVcnDEEMIRGQrEY+9i6ZVhU2ximqtBlKqqCKRY3IxROd8TnVZ0ryAd0CE7EHMcpGcq2+fDAEBBO+3Wzak8TyeT1OelsoF2MDq6jzO0G2gH9zhOl6/2PgOxXK17LtwiMiODSCEKCXP4+Ico3DJUsbkXAhumJdUVFW0jyF6DAHUMKfqYgRAEbWmkl9tWXJaoGdgvNjt4mXTWYcbEQGaiZlIc3NCo0vjTWtQ0Itrdyt94IdqMHw0FJ+bKczMxJpm3NqX0iAwNaNWVYYmaraOEUSzdn+hZqlVNv22326I/enpuJwLC19Gbyt9N/Y0VxNpFsHIjFJVFQUYgCpoRqqhA3S537DrYbsPRA2RzOxcP2y04rRkIgo+iolUEanOGzuWoqfTmbBL0+ywJyMGejwtjHDY3HiKy5yBwBHnXAHBx+C8A6RaxQCdcz4QRgMnyzKejk+mEDqWRXMp294z6+n8sH1x9+oXn+6uwl/97/+8PEkwIZcWKSztU8cLkkgrP36dXQ2AV+JWfkMVNYQm7wgIfU+7w6bvOwBd8myYyFkgFoNxyeOSSwVRqqqWTawAVFB0nCI5VHaenOu6LjTNxbzANJ1TqjkJURz6FkwIoKpKrUkrmsovfvHzx6fjUkdJaTrOpWLwTmZJS2HHwUU0EjECIYzsvCnXLNOY59miI4NkUInNOVZQzbCM1YhR2YQQyDLMkvMiVsoyJO8rgpoWJNzvt8wwjiOAEFvKiwqa4uPj8fHd0ZT6vjNANU2axzQamDkd9oAcDNGT8xTIcM5zWQpUKNrEKkJ06DzFwSHt/vZvXnsHxXLO4AMQeFAyMzJCA0lWUgFAVZyWsy/Vh74fwudfvLx78eJnr2SZa8mqFdTAKh1u9rt9t90NtS7H43GcnqqkF3e3OW+XZfbBHw570ZJyzqmZTxYzI8LYdUWqaAZlIgekSGZQQS3niiTsSARUJOVcqwGSiKkAUjZRIshLWlI2hSYIUovRWjdRyYuomu88BEKsUqVCN/CwHR7HExuJadVaoRIpEq0hHwIRee/RkWcGQM9us9lc7a8YeNL5q29/o7PW2QiBPTnHAFCymK4awA1PMFg9QZq0xgpHNCNcgOPjeZ7ml5+82B52/W6zKeNPb35s9BgFAVJgCoOLm7gZ+q4L0zGxelMTqwpCHvzgXHQ+Bg64lHSeZsWJmB0gIvexQ8MkWUpNOtM1OuQm7UGmvsl2gJ+mAmZNdElNvQ/b3XazGxCxlMLMfb+JsWatVUspC2F3c733gZxH8hoHHoagoLkUywoAzMAMAu0FxUy6zpttEYSdEIsSFsCSq4gQgyMyAaMmUIAXfjdIwe1uY1C8D8wOoSnvkgvOB+dzSKksU6mmu00cawEiJk15ejzeg8DNp7cqtcxpqoUcMqHUDF7YWU5n7xjBtCqugimtVGEAq7kxMhOhmqho0y1ix857x9SIGczUdxEBFiqoJAgIrlTQoP0m9JtIUc1nkkkJNVWEuu/gv/o3fwJpfL0cS6pd7H79d//88HasEoKHvGSg1fJljdaYV74wopGtucBzXPbxVgUt3lg1rtYWvn91L5EBWMuHPwq97LdtzPDClXhum2p6DStw9pw9t9iT1m0TP9Zu/1cd2HZQgOdY8KIzsW7FsCamTcuOVzilZhnHaZoZDH2Iu92OfCk1L3nJGUSkD9UzsAMjwR4sw7AfwtafpocsoFgAJXYcu26p5+C77T6aSakZELsuysGFrI1wxJ4DBEAkrs41UXB0Hj17cg4NybNyUQXPjC1SFIKAVosfAjPXWovU4EOMYbMZwiY672qS99OY85JyFoNmytBCMi2i83w6zQhwvb/adNtlyTOdd4ohsBHkeVlyrlX7GLxvrQmUczGtrLCcR6dOajmNR2N4/+O747sZBMgAiY2wFSEB4AI9NJzwUv5uQhq4xsCXEXOpLLdzoHFKaA2bzEBVeYE9WKwc/e7Qhc5PqaY8qoVuE88nRpH9fru97rLMJSfnYp2rLAuR5+gkFQBjRwC4LBNU6Dh2vtOktUpThgCFCiWXAkJFStUKaLy64QAAmRkpGKjZukEYrQZPqxIWPY/cj4XQoUF0q03gx8PYPpCGWgX+Iyn3pkP+Wz4M2LrPnqcJPEeqax9uS2AYnsXvL0N/5ae3XARbOHRRZ1doLIGWVshHV7zkR2tD4v8r/OpfOWed752qgplUvfgFXT4jWC26TE2krouFIzUBBKPWuqlGBi2UBgOFxogyhVIKgDlaqRDQVrcmMMNUNK/sp9adrCuGRIiKAE3IzJSA0UDBWufPes9W5AqRgAyxbcxAtnp2g7WKQduH2v5g1NDQi83ShXrVhP3ULueuxsCwNpK2b2u6TKvtSnNSJSZWL+aaGGNb+QEVmVdqBOrl/aqZXMC+tjormJhUYEYThAtZxFCNENguWU4TJwNA4ODIewrkCTn6ucioGQpUKJvrgRFJJThkA62VyTw7ZstzUYWsKpLBBGJwxEhkuHanALXAhszUkSOPBNRz10PgrOwhONp1MBcoVcSqc3Y4RFDNy2nT4/U+5iT7Lmxe3u13wx/87NV+v3nz00//+M3X3nskIEAisqqA0HXd3l2VnM3R+XyepyktUrNlg4fz5Ji9c47p+rDP47wdhr7f+n5L4eSMo2syq7bdHpiJ0QffOQDvOyYXOWy77dV2OT49bg/bq6srzy4ty/v798znTz572d/dXvVdZJxSKmIqVBatVsk7IzNT8mwqnpkDSdFpGo+PuRoebm27HW7uBlNfSyYQJK1SrFapkOd6Oi5vXo9whhwBGGgFt1kEHFAIkR2LHZcFygxlmbpSD/u+NY/npArjbueOp+PLF58Of7hdUkJnitWz6/xGqhwfzz4iM3rvEFkqNOAMKlQQM5iSdHF7fXsgzEzJ1GpJ05yOp7MZkHOdmgFXhcdTOo5pnPywhbuba9o5KSfvURDnXFUqqDpmYfLsoZhIXT2eQcFEBU2MrDY5c13XxEbdvjxoJPGPCLH/FyuU2cU/ZI06Lv/VECP7cCbABX5ayxGX3p8PR5MeVANQQ9S1gtMmMDMBgNUWgdBlGYfLPAf4ret/iIdWAAgBVBs3Hi9ol9pFjpE+os2jgoIhXfCt1hL0XAYEM3i+PLZWxA8ktWcD2wZTPWNjtPbDt4rO7/z5uILnKxnswy5IjbHfPltseP7KmANgMjGRpiDedkc5j7MJO9f13e5xOhWVLFrFyGxOyU0TALFzSnY8nVIWETXmGCNh6Ls+xo6dxdiN47Tb9X3fxwg5m0qSaudzQiaVFuYiAHnfhRhNKQTXxaaijS9e9PO8jPNJMHdd13WDjwGA5mUxg82m32yH3W7e9VOalnmclqSt9KQGd3f7EHGz8/0Gq4zHKauU2HeOPaKTCg5ZCp6eIIYZLKZZyjKSH7Zbl5dal8V03nS7fgh9B6pwnhYMOC+5pqKEJVcVU2ncKhDRWgXRgTVnO2x7OjxzhG3dutbhcnGfsmeI1BoVCxFbiewZWEX4EK9Yi+QvIwwMtYFgjbqIz3o6reEBkZxzzmmRVKrMNZ/LGCe7wU03IGNjdNVUAIA8Oeec5ypt76TgWKxqNTN1xIYOsAKAWgEH20N8+fn1D491d4gc3GY7IOoyT7kuEV2tohW99wj+dJzOp7mKcISNYyJfpaapdN6BQr9xwXkp8nSCQ8ebF5vAQ0knBiBywNaFPnAgorQsRcU7DsF3g8+2LClV0Jq3TABY57lUg37bEcPD8W0M9sUXLz/d3jwe3717PU9HRUw1IbFD8AQtZAAwQjCngkTWUl00csBBgdVUAE0ZDQA9sIftobu63Q37zkiWlBSmMIhlnVNBW8ZpYgqEXAVLqVSwUcY9+zFPJtB1MUTnAwmhCIxjefv2fc7AzOwcojNTIgOQEJmpRyWAsNtdewfjgooL+uyDxRAKmCo55xMbs0mtWpEwBPYCjikQeoKsaqXmKkYMIZIIFSwpZWOSAjUbMikDsdMCZ8E8FucqsyImM3pxexN9XJbRIIcQVGofB0B+eHx6+y4hwA3QMGziQGZWrJ7LCBFevjpMJ60Z0ACk8R+8I0Wndc55gZyMKPRx6HvHriJCYFADR9AFMEWphma1gpkucw1+YW6ChjbXqRY7nuacIYRNP2z6TYy9q1W1gqoH1HGa3j+8HefHaX4ikmHT3724Zt5nmUvOwxAMOBZKs4kgKCkIIIzTuKRUq6I5A2YOPlCIkCAriiiiElQS1bJoyUZkKq1EKmeRMAQVbQGe887QilRZxXWsGdPPknE+k9BcCjhAD1XreDpnzkBUqZiKefCRwCEKq1ZUdI5CjI7YVJ1xcJ4Mc8rTccwPdSUOOgBFAl65vdrM/Vop5VJhZ2qLQ9tCzQzQHKGqlbMc45Gj37+43sTuXJ7O08gKYccYrYAJZgw+uOA8b/aDZJMqpaZqhTx0Q+g2YbvfUeDTeK73SyqV0Dyhxxi5M7FqteZSyd69eZ9zMgRgNNQQHHfsAsboYs/FKiLEjoahDyESNTFKr6rzPDsPwXdI4KKRs6ur7eF6x87mPBoWdkxmtRiAERIzOaeIgCiqebvfO+/mOeU0my5qFRBBtNUgNx69c4AgIqYKyLVILSICAFIVwLCaVRXEqlZIULPOc0o5CfrcixkP3W46PggoOahUJjmy4Cmj29rVpxtyUx1NU1WtPhAoiAgTqYKoNt1eans1KYACtdTAEVIDE8kxOVqTQqRUcq215GKqKeecmpiyY24lcs5SUk394MLgNVGqlUDvtnB3DbvO/fjm/Xw+kbnO9X/9V//r9J5d3mLPAlnL0qKfCzjV5D6RuOXhhroCOM/B1Rq74IcfP4Q7l/ju//bAZ1Tso7Dv4/hxZTlcdsRnDOs5VLsEbG2LBAAgoOcg8l+PYa1/QWMvXtCwlYf1gX3WVDO4sU5a0qrVpmmeRqcIhBi8VyJYxJDU0BZTFcXaD+Hl51dvvnkEBbdh8/o0nlwAclJldp5cYO9gM3AIVmsqNSOi8xwCIRoze08oaEas5I1a1RCBvQ+enPdOspgzYSWHoffMnpayzKniAl6gK+jMqTnqDsN+u9t2XacGpZTT6ZyWbIaBd0Q7waqgPgYfnZkkKZE1uriJ++ACescDqVU0G8dpOi1FJHZ+GPqIrKZF1bSaFkZYziMUjM578Fb0+HRiAsmgFUyFKDrnxAykGD6n+q29y5qbssGFq74SXy7h74Vq0gRGVk/wS59HlXnzItCg3MEWozDUJZdq4Gg4dCVtNc/Dvu8GL3OSWQ7X2wTyLry3Utl1Ui6aJWa1pUKGNakVU9G2AiMDI5cqtaTceozJaanYbGvgua68lpQNgBAMkYgbN4cIWr6CdqEVfnxYq65dRvKH4vuHOvwlRWpdibCCCRf86vklP5ondLEJRLNV911VL0+9PKchH4TYms/so6uvVqFrO9rzdddLIq1375Kn/D8CkZ+n9u/88l+e6Vb4SQEZXeAaCfii3WXg2AGg1mc7ebOqBVURWLPrWl3TANVADMAQGQEvvnwt50IisDVrJCJiRiaVFS3FBpVjQ6UuRLX107IVfXqGri5oYPOjRwNAFUAEYCQzANOqgHBxSzG1ZiOxrj+XDkT8QGIAMCbQjz7opgBNSLpi7x/AS2yFeANodXYHFKB5cimtYB8akjbvWDBDNLNmPHlZ6lcxR4MGC6gC1kaMbaRoq1qriqI1erYhkAMffeh779kHJhdE5hh9wmIVo4uOEGr2aFprnqsP0AV27NEXMNB1XVZozUpoiKigS1pUFaom4t65LnbRxUC+oxCUpsdzwG3n+fb6ZtT33z4UcI+OwDFtNiF4IFvyZCqJavjFl19cX195R+++/+Hbr74+j8eu33RdJIcKlnPNpVTV4D0yV9Nqit4Th0p8mpbTtABCF+PQdeRDI/Gf0uxiwBgZAA2JXYix73pAvD5chdjlmgW0lMIIt7td3/uv3v2ziOSUpFYCEKlprg9v7oeuv7658UQByTs4L0uelwrK6tm70IXNdvPDd98BoGOyag24AbBUJk5Fauk7HxmtoloRAROXk6a5Pr5fxiOAA2Jkx8RgZCJWsrC3rg/sOJSQc1YBKTDNmR14T2qoAHmGq2t/PD1cXd1c315/+vntt69fswPvXIhuHM8y1cNVgNBI87V1JPnoqlQQMINSIfh+2O5UpmWeCFHNStZ5AhfQOe9cRO721/Tm3enhOI0zbQ4b7wKqB2NEKaWczzJIBygAACAASURBVBNlqCKhIzPzPlgozlO3cTHA2BgmKg3bd85Mnq2R7UPZ4AMW01aQj7qjLoW752NdoZBMFAl+a8H6OHf/PcvW71nkYSUjNVSt8Wnbmk5E3BbhlDPiKo99WSU/XNcuwdiKYH+Ih4yQUaFh6s1TcaWONtZpg7FEGwIFagrSKkYKSKbrskbY4ilCEAJcrSrau9GVUwor0r8y2gwUFdqiipeN7KICicgAF0tUA9JnK9Sm2g6ghCu/DRpO1pA3BKTmZ2QGSAiu+SKcTgIanOv6fqttv2VuVIIlJxhPznfgiI3f3b/NVU3BBc/BxS4QccmlFKlVtJbddnDOiZhqnufpPObjEZC1ljEEZ0am3nF2HEPwNzfX3rccnjc7T0fMqXnfQK6lmjlmH4Oo5DEPw3Bzu/+TP3qFKA/vjsfjOE+5FDUDH1it+GCGNdWslpEw+p5daL6RiGQVwQCrEThnrqrHwpAQzbV2rJpVOsxVc6VSdJqW02kutYDneVoMnePQhZkIUi6Fig8DVCC3gosAogrY6DttDF42tZU6a2txuJWyjdo+tgb7axH7MiDXadMgOnymH196HMQMxJgMmm1UM9y0RrQlICYSFAgABNM8SxUwddHffbq9P94DAzgmR0QESmYCBsEHAS6lmIILzoiNKjRmNEGIPGy8Wg4Rh90QhzDPc6lZ1apALVKLIcUQvClUEURwjkPonOOUJE2APkWH2010ziEg2ISGJooMXdcHFzyF4pTZh65r3i+qShSI+HQ+Fc3Guhmg6xw8QU7TUgAY2KNYmvP8NL7fT/7F7fWv/uzn11dP33z9+ul9qZPevbyp2dJS0pJLqiYVyFH03MQE1BQV0FSqqpgZEnTR2CMj3NzEq7thdxVjj7XmJZ/VRmNJYKUIGKQF+i6G4M0opWKWaxUADF5tTky4LEuIzkxDCKo6TeV4UhFwrFWeTqdpSdsucheDQ3aOPHrvQq1LH13fHzjufa+H6+BCd3//dAyjKamlWpJZ7Yet5w1TVwq5kDkgKsxna3IFfYTdtiuVAGZm79lXb/O4QC3VoO8D+2gZSq3m1A2hHzbH80PwA6Gv5aT2f3D2bkuSLEuW0FJVu7hHREZm1m3fTvfpPky39DSMCNDCA18wD/wsPCB8AAICL8yIMDCDzMD09OXss3dV5S0i/GJmqsqDeWTV2ZweGLyqUnJH7vTwiDBXU126dC3sdjutNYZdabpMzQ3mWEsbDxRTVrO1rtZMUnj/7du/u/yk8C76mVIehhCEp2kRRquYLmsIMg47OJvSt++OIQgR5xhi4nVtIjWwqbWUuRZdlzUEFQkMndby9Pjyux8/v1xWYZYwmnKraE1b0zdvfpAQcw7ny3Mp54fH0919+tWvPpwvHJMcb3elhHVdzQvgEgjEZW21VACXywlO5gwLaqU2dpKUswNNK4iZxY1N3Rp7VReQy6ZpOFDK2bjVtW6bB7sk1rIpcxNBkpj5uc4EN0FPCU6XMwSAMTgwV6g4xRA5Sau1tlrqmihS76c3a4pJL8vLPJ+X8+P0JUAonLx1z1Nz+BaGbNuZv1Q55K/9dA+MmJK7LVbmafaHz3Ef3tzd/+pPvvtXf/tvVBAHQXYSb16negnOQiHuUmmziZnX1hYyYy22BruUoHFtq/NCwUASeUCLrSiaWzGrDsbDp0e/tmMhsEOKMUqgXcwc7pwaSMcxUqBSytrmdV7dXdXKfOIY728Pu/3IDGavbTUbXW1ZZ7XVaRCGuwlTjOLELNYaghjHkgeOITI3c62lEkyYIlNtYEbOnLMEIRAjxb6BSuBuCfX0fGbyvSUWD9GIzQm16brWWr15KWtNKQ/j3u1JXWOEZISEIYbTy6dDunn77WG32z19Oj/+7kUNzAZHyAAgEITQVZn6iAX1uUffml1Ezr3/JkxEqs08GfmyLGVtQwxWvBVtFQSknCRGhVat04uaNEq7vOeQIrzsD/7rP7r51fc71EtbTjkg7fe7cffjjwiqgZDSfkBavcLsmnRd8yFnYpD0fqPRdsFfIITtX0+rcG2U/Qcd/wDS5L/4/opcvGJYvzwPXTfPTgD7D6ZfbWfpf7Z9eTOCI2CbkiKHg1lI2zVBJXJFLdYaJCfzeS2rwjoJudMf1JST3d3v3ty9/fnHJxB4wIrl4TxjgJI5L2AOMYeIYYRhbmXR1ggw01pba06UiITIzdW8qrXWCOAUKUQH6VIu87RO86KmKtQkIliVUjF70+MHImoiyHEYx/3d8U1KQ1vt+eV0ebmcT3NrGljy4SZLNDQTPewOw2E06M+ffjdEGvMYOFpDIAl5X9a51nU6X6YZEKTIsEY9v/UKNAnIKUVjER5CDDWQ8TJhTGEtauZezRM4iKt1wg4xAV0xwUFO/IXD80rn2Rq810XR14V3l9ouAsJkbB509yZbrJe1rLqs2orC2dXZoTK4ul/KZJOotuaax+RLgcAnb7wCrtDSVgdxiJT46fnFnh7naXZ4H1brbNacUvcgLms1a9c5CerDfbrVEe54pcj8YrnhazrhL1fjl9VNX4SMXpfp9Q9tLfA/XDa9Vj3XzvzrI9vVXHlb1k026bUceoVyiVjYtrFbvGJcTpua/pUFRoxNvHijSeIPvq5/3/H/8bYNa1sA9K5FJME+a1WrpqRsFCTAvWrbJlrYOyykpWpFGMftuWiz6wXM3dBNRyT16+gZoamCrgLMbn3i3Ttjo/ur9B/3S6dN1G8bdSa+zhsT0zYHTeSmW3s6MjOJ9brvOqPZW/PkxtK5uQS35o024hdtSD0RglB3J7oCXHJ9u1+pD/2VdiLYpidDBGFEh3bDxGus6xCZbpuQNcARA28jPmT2ynTz7jW2PVFXIGymragzOJEEgbiEIJHjbpAQFKa1cfPW2pvjGxF5fHzYpUyu53UlNSgxNdoLRWHgeLtjNwdcmHmjmseYxpgA1Lou8+xNLSQLKUgcwiAk7ITqy3yJd/TDhw//2V/+k/vHh/O//F9zDtXW/S7+6ocPOQTUSqZvbr4/3uz/i7/6K231r//Pv/7429+OKd7gFhy0Wa2FiGKMTLSuZVmXUmsModQK9xVmpLG7uhI4hDTQUznnGM7n+dPpcf8wvL29c21YVZjevntj3lrVGPko47zSy+Vclolae3Nz8368XdNqsOfHp1ZrCuHt8TjP63w5f/7djxEeYpwvZwBj3vPN7vl0enn6PJfCIewOh2+/+XZd1lLb7EvOkW+hBBUtpU6T5qTjmCsUJkFCU5nn9fQ0LzMkQVeCR6IgvImjmXmttXPPmSUlpES1oTZ/uZScOSUxt8vq81pL1d/99DPYfvjVt7/93b+7u9l54/kyt9pyYhiRBVWrtTFLCsPNPkCnearDwOoGl1J0upyeHz/v90nYjJwDxjHu98ecxgb58O3bf/k//vPnGbrY46fn39789OEYSilMdV7KdFbOJ3VykiFxzrGWKsLDSOPALYc5MRm5cyROKcxtBTaCEQBQh423ht3VG+/VEKNTUr7047Ypu77qRb4gX1+HsC24dDydrif9g8drIw7YZsK3SIoNjPrCF/NN/+aKW33FY9p2QYCIhMiulCYCoN5R+L5tduSpNww7UL7Rqwhf/m5PcEWYiCCbWbYwK8PJFN5RZQ6bRbSoe29u+NXalOAkfjUHoa0j+AqHg/rbb13EtJcoDBA5sW0XLAQhMWiH5yWIind8jxwiqIaHM9pK2mDOJCmkluBUea11WkppdnPMwxiF4nleSwMM0etODjmHupbz6axaqs7ffrhxp1pbKXWZ19aUxXc7UvMQkhu31mZfRHKMu3fv7m5u7mpt03SepstlKgBNa6uXZra0ChbcHsa37+9FaJkngg6Zfvr0N15nopAHGXaDcIohPzw8zGtramwC75MuVOokoTEnNGbq4uVozYUsyUiJrbIVJpeQcmttmpe11HbPxzfvh2FsbV6WxZiDy3yeJO53+3EcWUDrvFqw290eCpfeGhd3MtPmSraZEohTRyh7lw3cZyU2My9i2uQYt32O7dpRpC8pu2/762vF0NGvbV7Q3eCGFlo3Om1q1BTmQaLEGBhwzOs6LzOA/W5/c39cP1Q0VG2At049cN8UtVhyZqYAdzchJFAhgje8vDz/9rd/G2NwqcReaz2/TNO8MDCm3X6/P73ML+dLTmPMsj9kwNMu5xyZ3J3MYMVyzEkis9zd397ffPamP/38cUzL2/tvbw7HFMdWbFpmYmbmTr9ReKllOi+IGI+4Ox6/efe2tAvAKS7zpSzLWYsRQ30+TQ/Dzr/79nuwXspx0Y8u9Lvf/rgFFEHajznfOnwpq8PNqluBwRoQgAAS5AE3d3F3SKD67sNdGkMYm9Ja/KI0VVvbDCKYIqUsEZJ2Egevy1rrupZS1B1jqvvg63xZF5cY3FtKWYQcGgdEYF2xNJNo1QpVIWgFMVEOMNhf/af/ZVVd6/Jy/vj48tP5+Xz7ZvjjX//mfJlz2gcZY9iryTJZa+JIqnI5r6fTDNj/8b//M9O6LFVC2I+H0+n88PCshhTyzSF9olZK07XoKuLB2ZZaAmvikA/7t0chzeeXcj41IiQOl9PCvNZWl6Uc78aOildrremyLvO6MPMxH9M+fPhws1zq+TTNy3lZzoTBDcJtt2NRY7F5XmKk2mQtl/fvvqmlDOOw3w21luenp1pqFOPgIiM8AsRiwxhC4FYvTaeYPa9Ymy3nCxFySrv9mIe7//l/+r/2e/zqV++HMbz/8GZenkIw1dp01cWZGdBS1rWc3KGNTMMy1blU5rAsLcbgoHVZp8u0zswcQxAXNuPgBBc3Qv+rIAoMZnDzlsfh5nZf17quS1P1nmxFAhCIzMiqNersqpgPEYF2w2jFzg9PMQkpc58hNjT15MYShYJCW1VTbaUGjm5uRc9rWc9zuTgWiAi6+q+iqho2a3aCgCAkDN8QdBK/Vhi+CfkgpiQiZpSHBOAyTZ8+frx5P/7Zn/1mldPkZ+XayCmgSVmmc501ctwP+8PhCLhqrB4NJsmIqVFj4jjGd7v3IGrVp0ed5no5n6FsVa3C3DlyCMSRDVrVSi2lrKWFGGS3y8f7N2bNYVVLbet0meZ5Bpg5EEMyODVIrdqWpX56+Fx0jpGXOpGYBM45EFHKLMFERdVrVSEbBmv6LCFzWEGzRM0DSZBmPGQzs91Oxh1icAkCF1OYurCF6Ezx429PKYDCKqtFB8kaJDCxCITx8tyiPH94c3N/f//p50/VW0yQoJQ87MJAbLrmYX/34W48ZgvWLkt9bHPD3d3u/LiyR5GwaiODkGEz4oMDEro+wDanA0BN0TVYJLiiTZilUQMprAAOJZCQGRMxTNelTJN4CBRlv6dv7tNf/vm7/+QvftgP9kffv5l2fn6IY9yDkHepVmu1lVokBHi7yhcrUaDeaOtCes4w2LYbvUJYG9bjvumnvMIN5v6Hmo1/qP/4VYH9Jfn7g7/6FfHqtSruM7Gv9XPv0/+iJfrvLaH9q6/ETK8dr2sJSF2Vy2Ew28ykhUtVVRWiDstqo1aEo5Slnc4PHLO7qZqaQ+GsgHIwQcsfEEK6/fbGaH3R891bGkYZDxyCvH2zX5anwz6onktbFaaEuS4v57VU2+2SUnRXpwYBQmf7NmVXcgdWWxq77MgT1H3xF1RU3ZwW3v1wqMuZiA674bDfp8BlWR8eHj/+7vPptKIBBTC8+DM4Q1cwbt4d9ne75uXh6ckMOb3klErTQPL27s0379/UWuE0r6fm7XDchwDzRuTemkNDwGGXfdbj7ljO9vDp85vxPRZUaoIYh1SpmbqJOVNXIofBut5/Z4yQb9I83mtohpPr1x+eO5uk2L1EQV2UhBz2wz95991v7ii25+XH1VfOFMYIwjSdl9kYgSM/ny9rw91x3xFArQ0CGcjMOAiBqjaY7W4ON4ebWsrnv/uZRmYnqFEgIs8xDkNyeHMt1ny1jXcigIMUvTDv0ulfyEpdfZauXKhr3/xattAfWqJg4o3s0n/nFamga50F/AK3/fpEG7x1lTrqcM0vb73XB8lBrtTMiYnRnavsCnGzb917c+om8FfzdyHpnRf4l4v5/wUl/78coVkHpzYR+wAS5toZBAbqSh7sXRXeAduMRx0Gde8DDFeuhW3shY7jXJlT2tRsG/TwjYPwWr9e39tetLni6yizSUHTa66+1X9XXRpQD1y+cR96qdancsydr4/aZqu0fYCvpfOrSpWDmZ3Qh677VRmcuPPGem/8K/T/dSkQKBCRwGxrsF9RY+trQ+EBMDD1ItetV/XXip23uOhMAgaxEYxIiMGJQoosSEMygoSgbsu0qrY+BJ+H/TiOiTlHmaellrrx2gKg7mamPux2DICpR4cQAhFJkBySq1lTc7++3u4P5wSCutYmJFnkm3eHf+z/aPf48NLWS5umenp3f/fN+7eilkhu94d9Tm2tATifzp9/+nx6enz/3ff5cLe0UtZSWxXmIQ8xiMPLulqrpdbaamtWkyWoh1ECg6mxF6vTOo2W1stS5mkccxhCUlBV1ZxTqK3M08XNYopM6r5qm5kaByGhN8fb03TxtRGHNEgwShxaSrs8DjGfzufldJ7mufrHYu5EktL98e54f/fuwzfzui5LuZwnrZ7zjrF6QIWta8kZXR5FAicZRIbzWtZVL2dYQwrj3GZnhneggIjUYaaoxVSVSIZhJAKtVltFMxVCFAKRl7palN08T48Pz2/u397f3muT82O5XNbdSClHAgsH1UYAQ0RY2XpZKyKJrLUyz5fTdH65vDjG3S46yB0xxHEcRUJtnMebj081S7KIZV1/+unn+937WksQJfYYAGGmwIScUhBpBECJKOXI8BjZGsOMgBCCYdmShX4PMbs78VfjURt8T6+R6xeQDl1/KszejSte7/trGnSVl3sdfiff+Cl0ZX1tz4AO2/BG8+4tM38lvZr79YkAEF87DB3d+SoOdfOLLVLZJtnJIOv8px5sevvRNwgCZgBCp13iCzLHV2khoEPw/SK5z+rTtY/hpFvUp+u748Ar6bTHCnKQQdA5YN1ghWibg96mpK9mhNddENun4FcI3jeQArLF1Q6CMMhVJYgV9cYEMrXriYXEWLWpVq0gkpjgrITWAEfomQKxma5rWctcGnIe1Gxd11KqmaUUiXOM3tRjyASurXNDjrvxeHt8d7w9EOj5+enj54/HWyOJjk/n0zQvzRrqihdbYjzHFI6HLEJluex2yDcDwK3RstRlXlQh0g1eTc3BYhrXVs1KihQCvLLrolZVMTckXcf9yIZWtWpBQM4xxmEt57Jgf7Sc07AbH18uqi5BAG4VnQ2VJXprag2EPEQY1DSYEcJG3VXp6S8ReS8crx/Jl9aWOxzmzvj9bKPvcH3PMxBvK/Sa5QC+iUUQQ7a1Zu6O5p3Ppc3VG1NoVbU2VXVzuHVB5XVd12V59+HN5WVpl1NttftzCpOETh12lsDOWpszoUgISb0Bdj5Nv/37H/fHfTEz1bKs87ReThgHhBBSSsxLrSuBU0pqGXA11SYuIOJxjDZVdyq1DizjeHh7f/fw+fnxqSzx85v794fbGzcKLL6ep00s2UIQwOtaAEjAzX7/5vb+Zn/49t03BhzG+hRePn76/DJhl2GweT29XOi23FQsacTbb2936f5f1L9mhS1ARalzwSwhpjHlJAa/XIpWIIAHUMIu4uaY3r7d394dJJgkZqlAUa/mC3glhSqYEUPaDUd3CSEzRYK25rV4WQECu93vQ3coVa3zIiCLiCTY7xMLxQUOPd7sd/shCgcB1BgSUkwhG3mIMeaI0EyqYZaYHh9OP398XNbfvjxWc6oNgYeYDsNwTOkAF6LIzP/0n/5XTw8fn55eWmtu+Pnnj8L8/PxS2hxi2I0WpK1wq4ur1dLWpQCI+bKbw7fffyirnV6my9TG3bhIuJxM/exwRh7yXq01a7Vq03qZp6qeBmne1jb98a+/OT+dP3+yT4/z6YyyzmYQwe6Q3o67mFG0TuvzaWqlrLtxZ+7uVJvO87Ssq0OjYLdPDiKRPg4bY2BBa02E7++Ph4MtpZ1P67yUWku5lPPl5ZtvQZSIrWmZJns+Y17Xw019F1hCmKbzNE/mCnBZV1WpRdfivUNMTBQilGsrl7nqBAnmQ3TrYkSw7ind3Np1tIUcDCEKibqcQd5lX1bAibpQKsDEug2XI2LY593t6OwpxNUqmGpVqAqxiXXN99ZaF253c+He9mNyFwrEVJu21UkRUvSlDwT0GaZuvLbln8QbU5eZzV2hfafrpYSZiwR3qCoIIuIwMTlfzuu65Bzu3xxpsafl2ciEYaZr07XApQ6Df/z80PkRRhUCrs6CnKMxQozNlEnK0spiWrQuiqqvg+0xSB6GkEPRtc2zqa/r6k8aIu0PO/eRGGVdQgoS8lpXAGbObCGJFp3Xy7RMrTQSNKVSFAQzyikziRv60CGxhsStISWGmySrl7NaNa8hGBi7vcQQDSEmaFtTRorO0txbrx3MKocm1tSMIzgA8KbVq7PCQ8spx0jLglr0crmUm3U3pPu3h+fz7DAjVarNkfdxPs8tlHjDO0v3dWeX8VlPc1kg3KDi6mCW0L3aN7UQwAkhsbNTYI5scDMDG1NIMUYS7sK/jtQNl1UdHCQxJWOFG7gR0bIu9cWHPe9v7O4Q7m70uGOm6e39LpliFTZGwrCPNNFcJ60lDmLtWpsRdxGqnpwQkzs5E7rv23WsA1/YJFd1BH8tkr6U1F82OPyBw7dxsdcS+g/9T9dn+gUa5e5XttSWSb1Ca19vrFsH8/UavqSmRF8RFb8CAV77ReiCDI7aK1+QOalZgyMIb7UgUW1Wi8uAZVnnuQ2cJEgIUVt1goTkjulyXpfnw+3+eHd8/92dYW1yursLYANbzpHFD4cxCNaymHX+vpW1ttq0WSlkXkUQIqcURFjY1aqwhtgIFCRhh6ZGRubUSq3VOCBFjGPaH2RhMPhwE3aDlLnMp8vj55+n54YFFACGV7AlhjQNQKvnWmPxYN+8fXuZp17BW6tr88f6NL9cQuTS1qJFocOwDrudEdfWRf3cATOFmzZb53Y6LYPOaGiOABJhxFRNm6qIgN0ZwuTObt2yjdy6DkcHVOCmjAAhWEe6OqnTYxYXrK1utkriMPzZf/ynNx/yeXl6/kxQjIe9u1xg6rU2S4Ig0VoccoxDEvbmWrymBGegcggBDp/VKniQw+2hTfUzMIy5LgXMJAhBQggAmm28ASf2i4Gvq9E6Hct809fbUKRXle0v639b+l/18/11TX5Z3qDfu0G+4LaEVvUXjKdf4Lavd8oVVOrn3uo1/zKdRgRsRoXXm3l7dgH1mcFXZxDayL9fv5wvF3dts/6h+/n3rvD/kQb/Yczry+sFQncOBeCutg3/cXQokzVtTc3VyGMMRGRuV/qSg2CqvXrZPPj6TCQ5GM6upqYGwGDq2vmA6samoiSJwc7EPRknJle3hk0UxgkgYRYTdnI1fcUomay2GOMGX6lRIBam7rFKFII4rLaGq6Syw9V6LdynLYi4DyZ2NpiZISYR5qU0AH1gCL2Uc4Nun25IsQOOTjBWBau5mpMAIp2gwSwMgrmZalUjwMEBXjbUqy8N23YIUOyrhEjY4WZOEZKYhbsVJhHFGJQ0BCrazpeLNePII8eyTjHQ+/f3l/NLKeccGbAgyImiMBlJ4FJbyinGQMws0gEsApjE4LW2wDEEGVMKoGa6lhqiwJirvb15p1qz7D7c31XBf/6Xf/Hz5fPT/JSiBPIYZJS4i3EM8TKvH//udyDaD8O7u28yD4c370qppZRa6xXKBeDDmHd5v87zXNZGddVlXiaHxpwlSLnU0/mJmc4X0VJdG4k9PH++kfwm7PZj3uU4TefT80OtZX/YceAgztwCOdjm5Zw4HIbDyIlBQjyl87M/amjv3r7/9ttv/9k/+1/YPEm6O75rTKUVZyy1nZ5W19OlnM1c1VjS3X3WpkWXp+lZgu73ssxlyLLfj4EH8nhGq0VrBRtxSODGJOiyEwpQZx6aWiPRNKaUYmvN3UnYYUTiLkQ8BGsFIYirrtP68OnT99998/jp9PjTSwrIOVpTYvamcKSQUxrcvZW1lgYHtN6/vZXcgEawEGXVeUchxmgKAsY0qGKdCoc2P+H2jjVS0fr58bL+cDOdn4ecOHBOPBVIploNRGtZOiDFQsMQy3p2D33pbo557kwbGkPdnIC37KITr3okvkLPwNd49RV1Bjldq3f+Kir1r3Y1ubjGQWYmlB4bNp/EV5Zr/9p9NDYhkK8yqN4KCByuD2Gz1SAYWRfpM/fAFELo/0kGN0NvPRCp26bLaG6utMEIfSbPacMZrilSlzLdbFNYRDauqW9zZE7oY4Z97oyvqFdHzbqBqhA7oDBn+OYi6E5OBJbNwfqLiikRMaCvsqfGzObKX+Kzm6uauoCZtqaCtxgFQFnXPAiK5pSPt8f1+WmtdW11LcVN+8lbA8AxxnVp/bO260xbkD4ZHJgksOY8TPNJyEJMMTrQct5J2JtRqUouKQ3MSTjMl/bX//rHm90xDWEp0/Np+vD9u3fvZD/er7O+vFx+9/efnl+ey2KXl1mkvn/zq6ZFa60FzCyczLRpr6WROZDEOtd5LTEJwGvZ3hCzFmVnZvlA370fX57X6cFHmFctywpDHCMPadwPcamlTPf3N/ubPcjPl4u7BglqRh5M0VoTlqarSYEbYNhjT7kpNW3CTCRODehOwGyGvudcFW4ZnZLl6N2dtq2E3kfa2mKkXfBz2yV+L7O/pi/kfTy9e8Q4OWk1pW0cNcVo1xk8mKecY4plXmupD0+f/+yP/tzMlzYVs6YNoMAJBFXtdkpsbNUQvSzLcHdww/4upySfPz784x/+6LK2aTnPp8mqrxeMGSBfy6JaQ5Smpa/3PORPj5/cVQKFwMdjfjg/E9E8z0FSqeXtuzfTpT7YpRqez08pH8wgO8EEksLQrgAAIABJREFUw1qbOXnIiYHpPENxd3P44bvvvnl3v1zKfFov0woIGQ7j4XaIcZA4tJx93A1LuZyn02l54Tge3wxv38s+3Y5hFym7+drKWtfzfDZ1Nz/c0i4fJCKM7KIh+vF2//bNzeG4S5k+f/4dyDrVgaQIm0eIs3DajYf9/tYU59OquszzWkojkpwZRCno/d0IFGsoralOQAwpC+jmeAOh8eDrOiO4pJSGPCRJEsecx3gInP/+x4+1qJquOl/Wp2aXmC+XCz59fpiW5W/+9qQNULCPQ77ZDTcxDDGkmEcm2rX4+eePqy6H2/Fws/9Hv/mN/ekfn16e59PUbP3rv/m3p/PzFPVybm4tMoZD3O/G+/eHuzeHMedPnz799NNH1fr2zYDmbnmpL0QWYlyW1WEhhXVdS51rQzNw07Wsl0l3336IktJwf/f2WCvXBaVq1Tru4+5md7lcEMvLedLmN/ubh+fP9/dvmpXz4/PlfCa2aZ5D0PHwHccw7EaHdsAlxhRzNuLAUZ2G2lKe57mWoq16a3Z79/4yz+fz81qKGmKCRCz1vJSbXYzNYM4SIjNP5yqcL7UQxyEJCEu5mJM5KTYvIDV1pUDMwk3VWkVgNXNXMAzNnZg4ZiFB8zrsdm/S2+k8tVLcXWtrRbWZskoiN98dx3yTKZCZqTXAZGSdNIAZklMKe/HBKHMeUtG6LgXeA7XV2hI5Fa5ztRXkCCHM6wy72kUxd0MJM3T7byKFCLPAN6sils4lMYUNu/F0emGW3X4A0bwUkOYR5u3TwyczbVZjDgRnJm9OYGGTwDGkH58/BiGQh8S7XYJzLVUCIkKKw/Pnz0ysC14eLigBDejjBUIhBmsmzCJMXUzGsC5tXtowQoSeHhGTOFoaIrOkHIeal6WYNWY7Hm+d9Pnp/Phi+4ybmxHE62q1eQi0LM1aTTmMhwAqN7djrU7kZa1BfD5dynwhYNxnEaTEIUhMaRx4KXA0puJGpSxDzhTYuHLyFLys7f4uSWBmNTQ3Twx3dEKCNowZ5L6WUyh49+FofJrmiSNxEIlynid1K1hmPVn0N98ddnI8HSf9F//uPJ9lFF3UTYKImYEoDBHEzauTc4SSxRyReG1LIMnDmFIMHMu8ttUkkDhFJJHI45aruYsIL8vMmUNgV1smffMmf/dh/PUf796/3ZmdHfPIh+NxJzo+fm5QEDdKTNrCjlWboSmZxEDEqGpNuaso9JKS4N0QwPnakUGnZAjz1jDcyPDXkhzX2o1eK/MvJXiv1zc9ZFzdB/9BAOvLb30paJl/bwJx2zXpS6YJuH+Rp/86yfzSZ3IA3oeomK8Z2UZm6ZrJBHRLUndqxrQsk7slyYqu5+3TVExFFefz5eUEBN13R2KSnMebw13iMNXLWi9K7fbtPoyotd2+Ge/uhloXtZKSPD9+HvPQuQgQaa0BXtYac5BIZq1UDY6ch3EczKhIAyQFHA47Edmsvo2XeQXxkIYgmUmEg0TLeZ1zNMUw5AA/X07Ty8lLY0AB6qrkBd7MsIliL6fV3fIhvX17K0JrqVotcrgsS13qS8C4DzHxZVUO4EBpCLVZc40sGWEpbarTYOnjp59Z82E/PD09duVlVyxrCRJZqKlKDg42quDAG3GEmMmaXX0Je27kcBMjI3CQrrrT5TFIHAxhTjmNu6HE9f0Pb2c8L6dF1RTYjbvafJYVMDCc1Ih3d8OQ47IWMno+vcy+WoTCXR1YAfaM8Xb/7rt3N8ebxx+fMAIBzXXc5WGXgzCYlnUtVps3ThI4LPPs5AqnjlMxkTPc1VpvK3eUtTMUN8t2vxJ8rmDSVwL1BMBcyUlEehXyVdP79Q6jbk9/xZq+Qo2//p7JdbtNN7DMtzb/1o4m6XcVUWfsdufBKxHhdYzRNmoAE/u15f/1zf3ahX+9hn8IkHo98+s3/8D9f31h1yPkkM3V1LUrwrCCAEEQUbJiql1mPlGv9vr1MctmMb9l3mAntd4G6hbU1lr7ojYDdAi/x56mFqP45qzGQNcmJgTuNDpTABDhJJENRUuvMJmImZXU0H0xgNg1CphBAusglcN6Ue2OzdZlW/wqMfRXvsFq1QBIFgD6VRB0BsS7x3kPqyRspJtHJ5EztFNtV+cUmMmdWCiluAXCZpuFpsINrRl1FvdXMdwDbCPeEoM2i8p+H5JBXdGIIQUc2SF9EgUMNizrGqPHRPMk8/ySkgzDDt6ETRgxhpzyOMbj7b5Z7cOUHV4hkLAIh17zsBMr1mV14XHcDYdxlw9RiZJRCE0rr5M47ob0w5vbcU/tt5fHh08YRiCUtR7eMd8EqTg/vrx98/aPv/3VIe+nZZknTRyHPPBIBJiZkQPGTEZYh/k0XeZ5Oi2uqNSs2Vo3I8am2mFLDDFaTC+PT8X4zbe/vjve5Bh+fnk5vzyrNRGkITO5MJs28wbXMrWU87C/G1Jm5pPkACqlHg/H4+5mP+4U+NNvvx2Px8dpfvj89Hg6f/z48OPHy1xxc8juSCkcjzf3d7fH+7va5kr19nbX6uJ2zkMSFlMV5CAxhiQ0N+WytjgMPcpshmWkjlZr5YCUOYPcUauqWiD2kAik1Qhwl7Z6mav7uss5Sw7MVq2h3ByDqoYgLFxqCyGIRKJuZaohIicAGBJyAvmq5eJWJSDFuN8lco0c1mlu1dGYXdBQlqqNWDzFrnUI0+Ik7rYWeFsdyEmxo8gMaMohJgGh1SJIIuLNa610FVXChl5d846eCVylr9Sujj5XlicRabvKLtqVIdXpRNfe2pVmdY28XyH7r9/7V/H097t6/pp8YEteNhT7+tAXv8O+J9qXEwLYtPX0mgX11GoD57ecrKMRAFwkEEGbqircN2G/LrRFMAfzBpC5d5a9ac+rugw3EEg6SoGNhX/th5ALs9rG1CW6Gq2+ssa+PtytC2bxtg85uUMNTDB3YVgXLVZU2jJE3sKpm8TQ2oKKkHgYIr3AWq1LKfMCJgnsRqpO4BTjMjdyDFnmSc3ATDknM3In1V4vRTdwjDHEVss0LUx8/+bu5ni/Lu3p8bQuproA/PT09K//7d8uEzDg/Q1SxJ9c/sLch2G/2x3H8ZY9397eubaH54/u9enzY0x6uNkF5lbWRUutaI3AIYd4Os+l6vPLNM0tj7h/cxfTYVkvLy8zAz98f2cNKYe7tzuDXp5L88mEwkAwcChupo3AbXfE/ftjyPL08qDWiFFrn4J3kLoaWJkB11bnus5ywF7SpWGdFgiLkJpR/0AYPf0lptfkxGFEV23EzoTbHv/SCntlFvY985XFsB3WxRec+VpFOEwNTiQdrSRXhBDyIa3L2lobd0OMydVqrcu6nqZT8ZUSsbEWQL1q1Vlh0FVRiSBeW+QdUy6nZlT339wfj5kw3ezG2l7OVcuyrot31jMzADPXWudaKYiyCEsSIXPzBmYIB2LOeXT4ZZ7p6SlwvLk73C+TO398+Dzk+d3792kfsyYiWi4rE+c8Csm0nH/zm1/fv725uzusS336+Omnj397WbqjDO+Phw/fvtndZPdVbXLY0/Pj8+l0WStsxWcbjmEc6bCXnKKbXy4qq8icp/PZ0W7vjjc3hxAp72LzutZ5yCTR3JfaTHWKHUW0CmsxIFISHpjybjwkyU+n88ffPZyea21g0d1ehjGllGJ0kQY3477Nu25tPmYJeTcOw2juIkFYUk6Bfb5cpqUMQcd8+Bf/2796fjqfp5kjxhvcv7nNef/8tD49vxCFlLEA5wmtzTbN6/pz5wf047//7/4HKMI9/qM/+dUPv/r+/bv7lORwM/75n/96ni/ql9butejjw3x+mafLOe/j+/f379+9PdzePDw8nk8vrrYb7pZZhX1/vMPq5/PL5TI5nCON7mmIwziq1dPltBbUpXgOT88f2S0M4W6XHNwqmqFpNvdSl+fz57U1Q4NEih6HBPG5zs+nx6en5XBALQgR31iLOTF7rfN5XiSkccchRbCYQcCRKZmFlNyptbYWL4uKeEzdq2eL5bXYujbm0uW6JcRWYBpS3uWczGDmzawZqBmIY0pppKUoWrPVW6cyuRlx00pCnESrXgsNJfKpWLR4SDTuhph5mWZtzSy4mdZWS3HAYfdvj5zDaT6rNRl3cYi7/SgzozrAcYxxH5HNg1FgYeFIdbW1rGSsixZdpQRdGym8oZZydezy690PYhKmLmSiMJgrDOIUiIkhW1hhkHoLKRCTkrk7GJRgjOfz8/CcNVmIcSlraTXnNIx7sbJoEWerBENzwKBuEkzMa1NHBTEg1tCs1hlldtTa0astSTCTyE2bV2vWOt+gD2OpYponRclDHHJYloXYVFuIPFDQ1kqzN9/cwHnIY84X1WZGtbbWmqoRVaumVkpZ1xbyrn0Y7sZRACuxxTjWiYQNzuMwhkjuSmTjkHnMeZXL/Ky6uosaaivu6M1uFuQRI3XOAkxB3ZBIQuCsYnlogcxdm15iHIb9UHUvsXIkCRSGtL5MTLisFzNPabg57gUWb+XDn787P80//s0DnEM0q8WqErsJE23iq1XVIgIbMSRS3uXj8TZEWS7z6fGyvrRelyxex5x2+4M5LbW6UBrTpKcQ2F21GiXcH4fvv717/yGHABEqy3JqbZ++3+3H6RzhMFNiDdndUZYFBmeGOIigBLiZ9j4cubtS0y6jec3MfkGI+mr72rr0Xz/SJbZfXXZwlW/fBFS2Onr7lWvStjVAsfkE/f5TbAmb+/VLVyPZZgLQYQKir6tivz5I18bidhddETS/KklQb0RtuNyGaV1PsunWb1u4q7eqbuwmtdqQYVbNAlMgCCG5BbCkmG+ON3Wd8kHO55dPD7+9Ow73t+9PZy1VTds6L+4UJIJZ1daiy2rEadztCKFpm+anmPIw7tKQa1EUZeqsBQSBpBwkuGKQYOqqQNOQZD8Oh5ts7UWal6XRSgTexz3dJCnDhde2eKRUip51nkpNHIZxj6DF51Lq+rn+o7/8gVhZyAeKKWqzVYtXrOe2ZqSMwzHv92OIQoHJosItOlZnUHksFJFCBMgGgsyuDu2WC0JQB9QKBafwReyTiTlwRTU3V+9wDxhd7pUETubiBoX4ynP3E/Zk6U7ef/v27sPNeX55mD5+evjUgP3NrXCa6lzrujtEZl/PjQjjMIKwtKmVtkuQHO/e3UaOmfLpdLlMFxDtb8bxNlEGBg93MaU4l1kSj/uBiZd1nea5WqOENOachuV5Jucegzdvn44Rbmv8utaBryTr3a9r9RraX8sYv5r8fZmf7VyfK1zsr51+/LI2+HJcz7HdPb2K8deZgKvuCl1xIqCT+7+2EiTVrzXyeiedIb2B8notHdwyGL1e4T9wUZvE6y+u8/X71yt5PcnrT9099HBJwEYX6Dczu4iAxd2vXu/udvXp4J6xipoK4MqAAM6dtIdNd1L1KgZ/pUi8BjpHH9lz2hTkeybfKRbUXeabqrVm4FcGBn9FWN24YOTEIHYicyLr0nFC5MyhWwOChJ0dm5qWhxC2yzPdtHGZmHkLY1uU7IUoTF7ZYNRBYgqE7szB8G7EpohggKs2c0airTAnoL9vDG+9MOkPYpPS6XRNBwgkwlEMBtPOVoWTt6bqBgxjaZVA5kwhoTaQeSMsa9m3uamUNuWQxjERIlMjIEUJIYEkj0OdtJpudA0GAcJhjENzIVGrzVorZbYs+5sDJ5FdSEgyYqTRyOb5sqqZ1qQt1Lp8/vzxb//ukbBDHCR/CMf7t9+9u795fHrJGveH47vD28u6/Df/7X+9P7zZjWMessQIIATe7XZ9FQqBIiXjCFvqZVmmta0sSHmf07AsNTCsNj1dTpPqsDYSekf7fAgIuih5gJlWx8A550HNy7LUtTadni83xxRCTJSZkCiOYQwuXrWu9Yfv/ygPebg5PE/L+eXy408/Pz1PD0/TuoAEL5e1VRCvp8t6Os/v3+v+Jt3e3cFrWYlgzB2CSUnykIPwGb7ApVYEc7B1uKPL0vgmmkpEFEJidlMD8UYebFZXdXcCrabdfGDNpc5FKBHh7jiC+Pn5kiWoqnBklg6ktFbUakw4HMIgLeVW5sdSdJpeusdASny82Q1B2GVMeW4lsSSJUJSLutMwIgcMSeLNISY2lrVdplpaB2nIg6QhMmAxyTAkcqA2p8AStHqpVfh6M25x7qq8uN3wr2jRNQa8piruLNIxoR6g3O1rM8AtSF2D1zVQosPC1/J+e2Nff/p1P+1rci5tr+i1tOsWeL8Mpl/3/DrhZdtWfFPT68/hX0d2d4Ck+5e3ttmf40oOJnNmB9wgIh3T943A5hsSTVuCx0zMYtrcTW0TQWKhq/1g37MB2IbW+SsV58trtC2Ob6VNZ2Z1thrR5oXovHHEaLODDV31yIgrgAOKXk7n57VOBDbV1iwE7iMnblWYrW3dCLiLIEYGobZWay1rXWY3AlMgsKrN8/LyfL5cakrijiGPpus0188fnz/99AIXNfWC4y6OuxRErLV/99d/r2Ypjre3797dvf+j7/5UtT4+/lzW88fn5fnfXL77Dvsx3ty8AfzlPC1zmedSG8H56TQ7+Dy10xm54niLPAzR2uXFS22ttfmyCCcSbShouFwWrIAzyHf3u1Iul7OFiDdHjPsAamolD1E9LqW+pgfuJswkIG9lnafp9CffHy4/o5YFZL2+EaSyzgS4bZpwsmUJ7pD/m7E325FsS67EbNjDGdw9psybmXeoiWJVkRQoNCGxW92A9K4P0Q8I0IfpSW8CBDQgQS/NbhFNsrrZt+6YN29kRLj7mfZgZno4xyPzVlEtHSQSHu4ePpw427bZsmVrEW7XEuBFBuEjTyX4qBx4brxs9jR2aXCt5MVtxPW5mbbmIkSMKGAgAEiBYvCAqLlmUVUNgYOP74/vRVRNXUMUfJqLLSqqSAhsKMCMht7Aom/nPMJiLLhrAsRKZqBFSpZiKOAJow/eE5EhKW4DTNo0Td8349LUmlZChFRlF9h5qTIvg4h0Xe8DvXhzNw3L2++HXM79TdscqEM3pQkG0KJLmdsmAsHPf/WzWsvpaXg6PZznI1LcBTecl3Eqksc+9LUo0iIwI2bgSkz7XVjmep5Ot7fXaDrm49P4KFnWxd0f+l/9+rddG8fhpFrbrg2tX/I8DJVIa53HWUpZ0MSAyQAVTIwAmZ3D4DgSuGVM56fxdBwfH6EaHDqADoPnvgtNg8Pwg3egtolkipgKuRhb33b9ruu6EHzTtkQu1fzjD99/9c33p6cnUI8QpimlVIm579rm0MRD3/hdkTwuIGo3d1elQmynp+OwzOoCYEMmVFOFDLQDKIACX3/9/Tdf/0hKTUO//rMvog+v37z8V//iv0tp+ebrr1/cTsuc7t/fM8P+0He9cyRa51ROaoAkpcg0TbF3IQQ1yLlWAA/AGXa7rusaAGPEYTx5Qoc8jE9WE7kQQsOucS4SoC5ZDYotSadiwA6a4F3HlkVZRGXRMizAAczAO6BAyCjVkAnRncepKJALTXA5l+PpPM2LlMrBOx8RHEn96utvm8Z3bRMOTZV0PM7zAsxpnhdmlgq1QCmyDCUt0O366KVUW2RJeRLVmjORGIfQ+JJZFoBUFXSb1CY0VCRGj+tk+ErwFadtwwplSoNThwbGFUAdIqFHDIi9qtZSfOcNQKxWzVXYWSDC67ur8WmZxrnMxbNHM3HCymYmKjFwGxoyXuoCZuQcEyWoKqqrcTVciLtEeinyjZ5HbgxQkdYyz5DsosFqRSt4RMKqIirAoAg1wbwsRUoIPlhgcZYAjIOLLgQIC1bnKez6fVFNeV6tu0VqyQZamZld9a6ptQhV9OCAjNHMTEBNpUq3b4nRUMlxIJe1goJj2HUxts5QzFRNz8Ox1AoE3lPwrC5gTsM47vdXV3fXPjan43D/42Ne1HsUASIBARVIDJhqb4DEznki0DqLQNO0oKbChMHEDIRIPQUX2Dkm0iWPpUjKIGrswPnLWAyAzHllOiMZrA05ASUAwBhd04dSK0B2oXRtlOqqeAFFYu+atmsQsCxpKmcKMKR0yucYD1/86etlKg/jQ/pec16gIQhm1aoHAAAGYBAGF4FbBA9Q1skSF3ycylRSWTknNVnVArDEtjfUKkVMKtGLu/0iJ0VlB4c9HHom0mVOZ5S+855adM6UmKP3zwCWIlqtxQiIAB0yO0SUAoAGiApIK/6+sYWJNoVi29j3zznXRxQK+ygT/Jg8Zc8GX5e0itcxlxVQ/ci7EC/F43p73V1+mrl9UGq/cFgM6FmgYX3nn9TDZh/4L0SXPAwANqP5C1i1la6IW+YEm68bAQCoVUfRDJFxlW0yAwCOsQ8BnHO3t62g9t2uVE7z/PQ4nh7m6F0fXGjd9e2ua12aJKViQmbCiG2IS8prCorIRAxacs7nM0SnzSE0TQdoTesBRcGmeZqnlBZxWFio5dDs+r7feQ5aTDxMw/zDj+/O56fgu5d3b1y5Gk6DipiAd0g+XsXmZdfBHZ0ex/G8pDk/PDw9HE/AgKxZhrkK2DbZ2vceufXZlyJEXEoBwOWUFIAQ9ofd7Se7w1VbMJVaimUFJY99iI4CNTS+n2EhAvYNAc1WzaAiOQNFRgasIIRGF/UhMxMQUyupAAMysmNAEBEGRs8153WQDTwAgC0AHqAH3MH+Zf/qFy8+/+Wn//6bv5llVIAm7toQawVTiME1Psy+PCxDTTUtycWALjaubWIkQ0du3+/a0MbHJ37EVIpyfZgfeuncnl98ehvQiRYUUFBVzSWnmonBh4gexQSYAHj1i14lvterbl0pH3GR7LlounDMVu7Zxx18NJCtQMEPPf61jPhj9OePj8vaeF6Hz6+/LUC4AEPrzU3FfXvkmVJp288Gzwnn9pFQN0zxA3xlayfg/4+fw3Pt9p956Dkl/gAimSGiG+9P4MH5wJ6QUKoYGDs2MiQM5g2VvbcKUoTqipkTO2bmZSkISEKbSJWCGQoJIaBDxo2Otg4crfIBBkYOPa29Bv3wVcHMUFG9c4gAopJLrZo1e+JVB3ulMax/MFkv3DV0olWrqKCmQMjMjsgU3OqURkiMa926VhG5VqkVVIGAgydaRzEu+C4gEAAbuHW2FhGBiInB6aZpg3QhjxGRY8/ewGpNFWoG9I0HAEFYvU8MFcRyLqsvFDADgyEIilywWPKOvCdGyECwilprXcsWhbu7u3mZlTTEuN/3pZZSUponFRCqHMx5EMjV1HmKIa5CQKnkXOB3/9d3zsH1TX93e+tcUAV0LoTG+wjFKLTdriEAdjXL8nh6fPvw467bv37x5pP97a9++Xp6OA9Pp2VcSq2N97/+5NVvf/7z8+n08O5+eHdsKNzubvYldLHruyZg01gT275G+Z/+x/95raUAN7HRJS9Pp2OVCgBN630IzrmaU8rzPE+pJEJcDQG/+frbvm+n0/ntd9+leX718tXrly//7L/49Rc3nxPYrrkusz4MDxad46ZtenQx1OyWqdrpdhf7pg8UWAAFGm64wypVyR4fjm3bv3z98jTOT0+np+P4+HB+PM/jBCLoHHuPZrJkPf9Y3709Pp7HX/z8zYtX/TLPZtj3fS0VkaKPwXUhVABWQCKHEFQmRiYGIqsmIiJWAUFgHSVUZEbk1nvnQ82ySK6LgAigqw8JW0AHeZQy6+317tPX/nDVvn37Dg3SnE4D3Oxx17eOWUyTzSrmPMSA//V/9Zvz8WFeBtGy21GIDRGYZq3lare/3V23sTsfpynB4fp6twPJMFcLBI2HmpcYXd83WSGETE6coVEFBGKIwdUle6Kuj+SeDTVhTaDJ87ZaaCM5bfkDfowFrVNQW2xSXVWawIcGzdZkZROd++OYe5nC+8M7N/+ENQUxRMRV4wOeQ7Fe0IBtevuSSv3Tx4X88uEpa5DRXKQKKJiaSmUffoIsIAJuw8jbB2LEy7QkrDjSs+bCau17AeYMAAiAV9wKgAEJeQsyiKQihgiemR1rrnqBMda0bKPf/NG3UFS8FDXrCXfeGxji1qLcrHTIP5PR1EopyoFFaxvos1815qeHhx/IaxObJaXisg+h9UHYaWwc4/l4QnRscB6079v9LqjK0+NTTjJPZZxgqXA6nw1Qtc7zkku5ve3v7j7f7V78eP/+P/7uq++/f0CgJcE0Z6gIRhKslgqUay1tE9NSl2GEdA/+727vXry4vfrtb37xJ//y0znf399/ebgKuY7j6ZSlTktOqZSqKUGtEIInF5AZsKjZME6lFjQzRUIoIkZ2fXd4+fKTXyf96uffj+fy7u2xFPPOw5Lbxt30cPOyf/Hyynk9je9j42PH5BTOZwTHzqUqxBA8kwuWc9V5mk//6p//N//6f/vbt3aMsTe1khMTORdWIUyrYgAFmRwQbVeFwoVauHY2nomHl+ud4MLUXRcCIAMA4mqyQ2BAqCqwtrhMN9CWCGUTrJRcS8rz6noJsqgyg3eub9qma8D5ZVlUSogREU/HYaElcHDAyylp0mqCZnbO/pqio+ShDe7q0HQ3YZmftI6OShMgMjnEw66JjQM0Zuz76EP1HEL0sXHeMwCJqK12lqk8nSY1ESlKaMsECEQsKM0BwaDI/OmbNz//0zeo+vj+dHw4BWp3zRWT//u/+3sRSTmVMisIEohCmgEABOjpfp6Gpd1ht2dBqCUjBADMFYYBfnj3dHsDu87XquMgtQIC3D9O37z9sW1gvwvBBzqimuQySzEfwAdC0LTAF5/voaICQvVYwQQzWqXSxJDTdHwcj8fBIfzs084FQlBkCJ5ioC64OUHXtT60KiRCQBEsSAm73SH4fp7q8ZiQc3/oljx/8/39uOTY7YYhf/nlOM7QBGx3drbh69NA39zvowvYpamGNr64u4Yl8SL7g+OQSxHmINVyzmicfz+DQFUtRaAKAJxH+PF//bt//b/8HRzgr//613/1z/7Zf/nbfz4Oj8fT/S9+9npJU5WCLC7Qr/7kzf46ns6TmTelZSkCtYL5xre4yIQQAAAgAElEQVQYVDIRNz4Mx/M0HLuu75rm7uqq67vdLvzt//3vwMC7GsJcVaoCOU/Mh6vb/e1enYpUMBiHdJ4e3r6fb+vSdU1suT9IVri+5uvrJrRuLuOUBgaWLMs89dX6fmdYHx+eHo9PpQgCBrEIzlRzLT/7xatSasrzeRpqNUO4uQlv3tzd3b1wLtR6Oj8M7++fJKEU63eEEBxj2zSh7Y9fj1VVVNkJUeNbIgqFKiI6cs55YiIikVorNI58YAMxUGR48fr2NI0Px/eIEFxwjlRVag3B933f951UmQY7n5/MyGoSrcNYoJBMenX9M+3JEKrValJSIkElNVMf6Krdexc0axmyAXh0SdVWyNiFJAXWftbGBrZVO6uCKSoSASMwG1QDNazrDJSBmqlUcY03tFqqoZHnEBmDCeT37+/T08INU6Q2dp69zpYnqTOyWBG5vrkuWuaZSl2IDYCc192+ja1Dq9E7KbXW1ITgQrAiVaRWMUUTM7Sy1qSsxroiIsGHq+vr/WGX6zjN5yVNKzGZANhRiI6I2jaY2fE8LHMdTtMyVajoXGRkdAWMVEB1k8pmD+djCYF8cOeTHB+PT/cFLRJGggIG3S7u+iYHBDEXm5urTi1PywB4j2TdvnXeS5VUsqhd+woYtOIylnGo42BWc3S5idC2cH136x0haNu53Y4IQ8puWiQXy4v17RWgFu+9w13fnE9P709PefgxOvjs9c//+//hr2qSd9/++M3vf5zG4gljbAGp1GpkpSbnOfbeCPNUqmRTi86DoC0AGYjYFAykyLLUgZyjqFLzvMyHuyuG3HfwyRv/+tX+5jaWNJxPuzefvPHOv3/7LZmPmPatC34HLTRNA9ywEwBzq3YzkvMeiYiCuJKXAgK1CIohAHmPAiRb5kNmKhtD+EJbuggbPIM+l8xq+x+BVtb9KjmKYFK3V/vprzwfazL4EZH+cv9l6HB9gw8pnHxUtttlT/2w1T63Iy8qGLZaeG3zQx+alYSEBIqrQPDKbAAAq8BMqpcRJAQkdBwJndRCRPuuzWre+5JhWeT9jzMsAA4OPcQe/vK//QsX6OrKo/Ulzcf7B9HSttGR864hjLXivJRUcy3aNtw1u67fexdEKrc4jsdhOC9LVYW+b/rQ7H14efVJ2/ZpzE/TlOeapuzJf3HzJ93r3sTGcX76amqaK6kqRaelnMoANjGcCH3jm5c3n332m8/7rle16TyUnBedhvw01WPhBEHP8xBiCF03z6XIQI6uDtev7/ZVSi5D2zsX3LAMcxmSznMGAWg7Olztdt0uHTN4JOO+P/SRf/z66NS7GOtUlvFMTE3XdjEuslQoLrAj/8y+K7nYGuJAEIA8EhIYIjv2FHuvoCnPh9t+/8n+9sU1sJ7G07/9h7/53//m//yrf/6nNWFa5Hg6u0fuD23bBULv2akzZi4qT+MJFs/O77oumaZpRjMj+w9f/oNzARAxojl1HRZN52HY97vom4Puy5iZiYC8sq9kjpBRRZZSYdWSgABqWqSmCrrpL61+VAyICGJbf/2DwunlAv7Is2mrH9bh0Oej1npZF9s6QkTJP5UR//ByHwqxj5fQhiavP8gmz7K1x1eBpzVH3bS7ttoFANd8bltrCFDWiuKyOmCrVP5ovf4TB21M5w/sqo/hKviIe/XxF1pvOMgASOiQkYlwVQBW0GIFyCDAaqS0vqhjt95YzbelCq/QDoApSDUFVdBVShF5Y0YYA6oYrtgXMBI71KobF2ENH+v5FRUQACtFrOrKQNY1b8cVifxwCmHFD3FFOA0vRgWwwuVbdAJE2CRqwACgaLn88kaZA8TV8wsM1r4CEoJT88rMawcBGYmAgFc5NlrH8JxbpWiYqJoEF6oqGEjVqrXWiowueqRVg6asBfc6/lOtGCA6BOJVoovNcMs7AIAIwRM7BgNlohBYVx0DUFRFk7ZDMAsRnOe2b0qe2WEMvm0bREzLMqdlTosCzAV4mImOIcRd0wbyUk3QaqqQjYMLjhSVHTa71gG03S4cmrBvz2kMjXv1+qUWGc9TyrlW1XH54urlK97bjVx3hwjemYuxDaEpYhVMjZZavO8QiZiJUNFW6803d6/mJYmW9aQZWOzJAeSSl5TGeRqnIZ3ylfV76PdtaK6ZbuCLL3724vb2pr8VxQLiqW+jdFFj7Im6kqiaI+IQXROhvcLovanWIkTWxCY4P82Toj0+3dMyI/PTMH711bf3p6FUC6FttbCAb7sxFTFAQue0is1LnaZMdLXvD8fTQ1ryOA11gUOvV4dQC0lVVXLgEJFDAFIAEVHRKrYqBiEygNGaZ8Ymoq32mSpFoRooIxGwd4QgRbKWRepSBSWlWa2GBo6PoBlUZW3HI5tzdHMbr64Ob17dtI0bz1V0JIK2bZ1HUw0epaZkOKFbxuX0MCjE3SH1DAtBgctukHO1khwoeuec9z6VCitwDhhiXOYcQuw6coEBq4GtX2+VZH6ms27w0U87b8+LbL3/AuB/mJHaVjDCHyBMz7EKPzzj0hQzYEfw4X3xpy+0cdI/fggvg45/HNX/Xw8EW6Wo9EL9EkC/wmZw2YTWfApEL9LtzKvNxdo+o43QumFwP5FgfI4DeAG01re7fP6VnSOqVgGZ8HJOED64Ov4Tn5oIVms728xUkQlxZapeJMaANiKbKWgFYzABYsUSon/9+pOrq47YfHDecQihlZaZnfN82UlyKsyrYzRQR965XFV08wBCgOAgLXm3D7VYSnXtD6Wc88P7L//Td+/ePaEGIucd9BGEV8lwWglfJhq48S02ztJc81wfvr9/uL8PBEhvEPPL27umhfv357mMigimzjsDM5Nq2nWRfPAxNl1Bcs651aI++qXUeZnnKmVepoene0Q2EtfC7tp71zWx+ezlTUlzqhOyAJbj+TRO55vbQ99HZmBmxFUutYAoe9dwY4ROnHccye/7NngucwY13tBChE0bxLYVoKbrX2mtz7Zr6xnm3HrC22b4cZKx9avJTOiCED+bFqusp/+i6W6E1YAUEaBqrbJlFW4dMiIwyymbSq4LgDnwwfl2FxFBs9JqDEDgA3MgRQkej6cFAK723Refv3z9xe73P/774KFtCIQNYkDt2gZRVw2s0DhahcBAahWzyszeI4AWrcMsOZ0BwXny3nJZDDGEgE73NzG4Zk6LYkUnjLjbx3Gg4XxcxgWVh3HOKaWcmSAEz8yEpJBLrnMq8/npcBuur190bUhVlmVSy0S+bRvvwYfUtMjBs0N2Ejgys6qQERM4D+uWMS9FxJxbFe2dYwuuSiEBIyS2xkFItZSSAROqE8F5WLRaE1pT0KrEBipoxGRI6l0Ivgm+rcRgVtQ57rr2CtAPp/rj/fv79++Pw9Duwss3V9e3d23XlVp8U9At01INGQhzLXmZCshcWdSmqdRxYtcjcb8/hKqCg1FRg5LzUlPLTXMTZNZSslQAA3boPdsVlCTO4TdfHn98+3/87b/9/V//9W+ubnZzsmE8PTy8EyxdH2MbARfARTWxCwZpWpIgGRgzS8U1k44hGphVQaXAoXHRAd/dOEDqun0IzXlaTucJ2Ldd0/Ztt98p2ZJSTotvo1MKzRxa3101+5v9i0+KqewOrWMC1uN4nKZzwy1DaNr9/vqm63oEMGABzjmVUgRoTkvJOaWsySOpiABQjHg47Lqub5quFF3meZlLyTCNMI5WFgjhCdGFtun2bddFdAACqiBVySXPnQ9shVRNrLI5WtNCMDVFp+BW1j+wB3Ba8rJMCgC1WVwFqZAL9FBdJJhVcp2WidStQLRzrKoG6Jy7f3x05kLwhKyQQEDFdDII0DQeiVQUDJg4SS6DlLlqNb92x9fBD0IEVARag+AqO48AvArvwMaAIcBVhHqlFpmZM1t5oQwusoKUrHc33X63R8UCBY3AKE91OC/LMeUZWACJDp9cgzOwlZ5rIQAxeEcEJlKbxsfoQWFIOS9ZchXRzZuOYSkL8tafVwIgiMHvdru26YIPipkzi7JCdQzOIzPCSj1gWpZcS57GfD5nSYAA0Qc1AnAqJmpiUAUqgDEMp+o8dC3VzCrx/fvisSJQLWlJqQtht3M3Nz402PdNf2jZWymgQgQK4JiCYQGrAFXBiCryKg68sbsdOybcBN8tE4pZBSXCymhS6nBKx6fU7XvvMUSO0ZEH9trswBBKgdlOo6L3fPWKm8OL4TQ/3p/GeVoyEIB3HhEKCGsNIfa7Loam7ZpaVKrZYnAEi+YcC5uhktN27w9tD6zG6e3DjzfX8Pp1++az/sVtG5tq0tzdfdr0t+fh8e9/93XA9vNPriOiVAaEVaylaZC9Oz+eReoqBcvswcgIkAmVlAxkJYzTqj2yZSybtCPZBzIIPvOr6Jmq/9NBww2PuuR6z/2bTUUHf7I3fkikPnqJ5yJW9TJf9ZzA/XGtbh9e7hnDWhOxtQTd9B0+WPVso46EhEQb1wK2JPB5ynEbNZItu/POlVJLHUWqpCqIaRmOTzKcFhDg6IInBDuNpYm+avIMTYx5TOfzE5iZgI+BwZWkKddhWVIRYLi5PrTNteOmFs25VllSSinVkqEYtCq75vZ2d6gTAvtffP4zML5/+3C8P+alPn4//TA8TUMahmEcn24On6iqqJYspWSt6ji0sUPAr927v+V/AECttWnd7Yv9F7/69OXLq0LxtDyd89kHHJfzeRznRQD94fbgrafSAMgwCzph75h1roiELgChhS7EPoY2fPfNN1OCHQZgQMdAUKVI0eibGIN3DkGXtCx1AQ+IhZlXXIaQuqu25FJyUTEDcMwIlksC1Zqh0tJf9S9e3sYuhOCzZVMRrr5zh+AejudSF2bfhN2cpi+/Ob689re3OyZCBO+YOofWCLoKpkTVrIiq1Kku0yC+X5xnFTUBY2V0SiJeF52zlqUsOWVQXJZcRFe5M/YcCeZxwXUAwkA3F8UtQ7aPaIkbFGeboK3aavljG6j6XMvgtgZWvGu92tHQ1Iw/4D7/uePyDP0IJ1qrhD8GmT5UXHhZOCsRa2NsXSZAnrkK9tN/G48BL1Xh/8fxT9ZmH2NY+FPxrGeQy8wcrPKvAlqNkdg5A1FTkWqq6AwQRAWMkbZzepkKt65ryRABRbSUYlWqCcA6qGJgW2RZpa/YPStmoSqo1GcSGzM5dmagsnasqxQFA3TA6Ah5NU/RlXtHyEgXMicC4qpNsl4aClBBUElMYMMwwZ6VpgBB0YCIeQVCVdXAkFY6yKaxBQTkHUYjJlhVaQiIycBoJeAxs3MhejbSCgjgkC02HtTwIv9WwcCqKQMSIkfm1SSFSQEYUEDRkTGZVpVaCgLSpiKoiIguOAqOg03T5BvvHeSc5pRSymrQ76jro/dMHgJ5Zu2apm3avmlVpOScS51nqQaugX53CLEZhvPjj2PD/tC3X7x62ftmdxX3/U5rHudJTJDIxMY52fuH8Tg3X7hGeM+RimlKrfP97ib6LsQolMPB3+yuHbjATanqfFOKovdVZag5hJ2AFK3TPA/zcBoHkcrM6Knrmt3+4NkZqFeMxtiSmpZSUkq11uFm8o6kVH1RWx/2+x178r6RWj01L6/f3B5evHmZuOGM5Tyd55QwUvChiQ0BOHJVi0hF4iZEQzsPw5AmEe32+/MwfvftD0+ncxUAIlOoCkWMFGPsqs7soGlwHKeS7YcfHl7eHT794ubx8WEYRlM8DyUvj2CxLKFWXfFzNfUORGqtYqZK6hyTI3ZoaKqyTEmrqkoMTtVqrlIqGAB5T65YsmS1WiappeZlqbTsdu3NzfU0z//mb75kAqC6pIWJfMQYud/tX71++YsvXj28/R2z9n3btKHtQ9WUU97Y4MUsG1QbTzPxDlVfHBz6qyTW9n7X026ntRTJ2XfN1fV1hjRMI1BpGux33WG/t/nUtW3qmP3KFl/xOeHVxm796qsSO25BDj5ikcBawOu2zHGzgLVnKtZzrHr+4ZJ2bFnMhygGG5GV2T3j/HjpKvwkfOMGF23NjjXW4nODcOvZ/UG03t5lUz5Yk9OLiuemb/gRr3fDoBARVapdJpGfCbkEH8FXFzNWew7MGxC1Wj2DyTpJCkwMhLT2AwwMrGpFv8klridslY23D4IOzwghrCPWdukkrr1RIHzeUbZTppfvQAyGYCaqPiKQMnPXN00jU5kA1DkXvF9jPiFWVanqiErJpYDndZTVs3MhtFJgHmssJURYUrq+aRDYe27b1nF7fDqPw+n9/ZEZ+q4tmVSlLFlEAAmM0JiMPHBepCQxRQIfvJ+z4Zy//fJdyUPb53/xL//chTIObYJkxEQihuzMkKoVYqpValVECjEAQM2S52oqxFxKaduWGZdlVqRxOak6dOZaZKfkbdc2jcC0DLkMSzrnCqLGniPHUqsUK1VyKoDK6JoYAMnV0IaoKX3xizenh/yffve9CfgYZaPN0aryRshIZLBafiCsnGv6uG+MH4Csf+owMJM13YDVwUDVyDGAmei6ILZesYGKIlGIzN5vvTwEMbNqQhUBTGoqYggIWmdx2QXv+33f+AYrStY5zeQRDVwkwAIAV2/gZ3/y4tWra+J5vwucgkIGFTOHqk3kpDUtKeXUOodotWbnAoAYrH8oyKXUcSYCtdUbRZEykSlAFVXTpg23d4fjE2SZEGPXdR55PI/LuJyP5+VJCJ1WBQVDVGVvHpCcAxVk4GpFCqigCqiQKdQKRMaOQqBP3vicc60SOFzt9l3sENFUCaCWdDo/TdMkdVWA9aaQk2jNMTjvOScBM8/kfPCMSS3nhCTeC4Lz3ksFMCy1MnLXRWJpo/eEIHWeM1PUKqJQKgK6Yvz4fj6fH47H82keUpW82P3798OQPv1U+324u/0Eboj9e3t/notWEwrcuiBYWR0WR86nobx/eJKCbWzJsVRp2padA8MlLaY6zYkEnA8xcE01l6KLOvCEvmYbTvb+h6f5oeZx+OyXu9/++a8+/+xnLvA33//Hb7972/eH0zCXWmP0iOqjdezHIg5YtKqad65p2ib6Wkue59PTKU3zdBpCQy9f/nJJg3PeiKukXICUlpkMctEx1QQExL7tY3BxnMYQHTE1jYtXHYAQ4zJPw5RLTSoCnr1rQmiKwNvvH4hp5ZCyR3INIiOC9UbAv//Hb1sfvOPK2Xm6vbvt2v50Op1O52nMpljFmCkwlKrvH44518P+Cgn73c1hd51lSTnXakboyIgYS6hV1Co5cx6Q0bPnahUWcIZs3mNo/d31DRn17cLsiGGe52maYvT7QxuiT2kpNZNj70Ke0jIX8MBunb6i83SO1BCymBSq0JL3FALvr3axicswT/OEgl3fkdLDwxkqBO9RUYvAc1Wz7rNr5F9LBoRtRN3MSIGRmHEjLSMCmOrKyQUGH70PDgB9oKZrmq4puZgCsTPTnMrpnGAGrEjKIno6PbX7hhmZCdH6rnEO97tVayLH4EwFzaSDbJoMqgEgOIfsWNnYOXQmIEZK0XWhiU3MtZRjTmUUzeuoI5O1bfTerY0gcv7944OKq7LO8oOjJvguhgAGCIIgqiVZ2nW0u/F9dzOOp1NO81TmUQlANTBGRvTK02maznkZoLuCsQ/tGGPDyFaKElteCpNb1WiJmWpBFGRygbuWPKApNN57h+xUsaosCAUm86Rqznv2jmqFh0FiK47dqja7LDMy3Nxdd427f7wXtywCiq67avc3/eG2uXl5yLOenpaHp9O45Jcvro/nk1ipCgZsBGbqXbi6upJbmXRmYHbEPnFrHNCoVlUkQ6g3V/CbX3/681/etZ2aDd5z3750fvfv/s037++//+6rct2XQ1MdTHlieIJTXZrONV0Mzl8druZpHpe51FJEwAgVEQkYeHUvFgMBBCBCWzcyeE7/9Dn5ujT7kBifs7fV8XwryC93raY1DFuGueZtGwNlA1xx63Mirn7Q9lyBr5vjCpxdksaPuqgXiMy2jtHHpe/6LBHdWobrx7OL2ulK8IeNWy8rr2NjWwAAqF1syirqCiKAeReJOKcMYCkl9H4c6/E4LzOAYuiafd9E1qhPeVmqzNM0j6fTPAmhiQCTuEAGXGqdU14WUYDoOThvovMyV1Fi+PHd+xCg7/rrg0fE/W5/iHtWZ8XuvzstbzFYO5zH4+N0Pg3vfrh/Ok2Qt/NxevtuS58/QA8J4MzswEg0gwEwH9pwvO+m83z9ctfecf8ifPrqdcFPfrj/EezRu6Jgy7Isi3jN7GgYR5szNr1vraiSxy6gosXGGdg4Da9evXmkAWZIZZGUMIDbeV3QwEAMzGhtsfgoDNVKySsDgHzwqIAem9iAgUhNpYDAfn/9xedfHK52c56Epb9uQufF6lTHVObIsd036DDVZR6Wvtnv9/vD7lq++84SSTFGTUta5uypbfvWXDPMc5pmRFMTXFvRHQBaybUKAAL6FJy4xguW03lOp6kMAAKtD8H53X4X2mAMU5pLSUAoaijFqlpdzRJpw3TwwprdLtSVlw8ARggGJBt0tDZNcLNf1G34TFHXa34b2hVYXe4u5cofJpGXedit9Y2AF+3hFVWzD1fC9vClirm4+8G6GDdtYVy9rcyefeABEYHB1iWybkXrgsDt8Z98nj/C2p6nIJ9htWfE6hm4JqIVTfqD13FY3aa4pFDVyBB4o0TBM3fGAHGD4hFA1KoIaOmaFhBqqSVXMwUTEAACXPdLAzBFw83g1l2oBGZgILqFGkaydfSFEEylylq+rPJ7m72ggmhV0JXYtXJQt9ONgERmoLCpM1c0AFHaZMeQAJ0jIoeAgMucGbZYZgYmAoTg1y9phrS2hmj9HoS2mnUSGIsLvkgxUyFAh7LahIlIFQAwBmLk4Myq90jM1YRRmQhMuQNkAN7IYAAAhmoGuJJvRcSAEEgBrYIaoBKFELClU5oPLQfnpEAuZcnABEjsfWTGnLJzFIIHwlLzlMyRa9qm7ZrzkKTCVex23U7VAPzD+ckhFJO7ly8O+34pFcrMYFlomfE0T1Ndy0cEqb/87Ivj0+kxw4Hbq9BHiH2NV/HKEvrmallkmSk2TTU/axmH4TSNw7yM8zTllIUqWM55GM9PT4/3j+9zWVwIbRf7vr+6uen6lpGDcoOxbbuu7Xb97rC/Puz3dzeeDCUXNmKFxjdZBiMpdSazF31UTUs6g6vJKkeNHhIuS5kjpwItUYwRfaBSS4icpfhIzuimu+6vD0/nUzXLNSM37Ljmxawyk0FFBO8BAZyjJjZvv55LU+ZpSXNxEBw1Cho9pjk/Phw/e/1bwB9BiznTIrlmA8FVf5W3nUGrSRUDLXUpmBFUW267fc1nQkFGBnBMuVo1A4PYtOYk2TlGOBz6pm3dWX/2xdVwnoldjNF5alrXNNg01HZVbWCubeN2vlmNDh+PBYDW1CMwOlIkUxZ2AKT725ZbT4Gbzl9fNSU91EGcj13XVPW7BojUxRiDMVmpS2yC81sTKrTOJoIKDMxIGQS2cnozIUVAv9bWdnEN3WhXeOE6boHULpjLlopsePiH2LRm17aRIhEvwgdKl8e2sLzm65fCnhDXmWEGUdVtottAV7VskC2YbSPgG5D0nO6jilQx3kgUzzJVBkCgvI16rS1Id5GcV1TYkriVukJb8AR6BrxEBAAUzOgZb9rSNQNbZUFUbRVDRIcEtMZqBANe/UsQPmwu63ldd6GNXga8dmS2HQyNFRHJKW5biq3hBj80O4mcWz0CNQnVkmuInsiDwDxJytVAkalWKSWRUVExYEQUkbZjRCu1jNOwv7lq2246pXYXzOV5LhUnCtE3vJc+uNuSmqfz6eH9sS4B2RE0uQzVKjXmPIAJG0Z2jI0I1DpLKWlOBE3fHw6HuIzDeZynL8+hhz//i9r1bNZ2jcu6lDorCBD56HrXunA4naacE6CaLUiqkkWSCLBh23QhhN3+2rE/nUepsKSxllI1Z+/+w1fvdrvu6mqHAYhdGaHrQ2hc3XyJQLAYagzQeCYlyRYwxCYC5N21ETbHdzf/+OX3wXNNyNQgWC3JEDx5VbVS101F9RnrJDMDydtlRh/2efuDIYpVBxPlma64phYIqGses6akZTPuVK3EtMrJe+cUZPUOEAWsaljJsQ9NUUHUUkuaC/R6OITDVR9cqJrE5lqSLEhg6BxF+M1ffv7JL2Khx/eP7/obzsa0IDiUWizYNA8KBhXzDCgZiRAdYchJRCgtws4hNKfT0nWHkqpJWat4s2JiRbNn8OBJylUXEKSk6VxKzeh82O2u5vPjUhaAAgbIwOwReJ7UtKgKEBoZorHjlKoboRgQhBDMrIIN5KhpeqnVBdx1znsUWUzMs2OmlPKSJjVAghDJO2Za1UcRnblg5E1Fi2arQOg4up731So67zhQssa8qXnv+jbe3HQxEGApZZmmha3NE4JHdi1UPh2X8zA9nsbTMAxzbaLv933fRB314f0wn4eXd29auLu+Oby8Cl/9/nfgPIIiu+i5VK5FyjzPSyWEPKdlLMdyRoLo/d0nXdvurOE0yTxOYKAMFgEdYkA4g1VTp5aNGlZXM5W3D9++PX77+l30bfvbP//lFz//uYvw+2/hu++/GkdQhaurLoQdo0PKMYKBLKkSgaoioCqULLXWktM0wvk8hCivPvuLXPw413EeH57OT6dcZM4CwcPh0LRdCNHF4BnROd+GyAw5DTEUxFhKqUs9nycVbeKuaQ5m/nhO03jOtczTYMi7fhdjuw5MMIPzHIIP3u+asNv1BjLPOs3T4dAM5/MwnIZpZvbTXKuAj06qHK5bRETFnOfz2bngmtB5cN4tc5qrSQzZc5s5juPk2YWASCW03nmK5pZEqhIb3zTBFHah1xYCBltnzamKDxx82/UxBjUsCsFHnSXXmhaABVxYl6YDyQWKQTZTYDh0wUd2znnGPC/ew1gnshh2DOKpAS2AyChck4Bb6w/UFZTadha6bLOA5JxjZFMQUzPaaLii1u8PuRYFYRe2IYVIvusHZNEAACAASURBVCfuWT3MpyV0jZmVYpIMMoAAEpJjRDYydqGJ0YdGTZiRHSG5NnomWtIsWpA0dCpmzLbbA5FboYWl1NA6F7xYFZUQXQiuWpnHSS0bzEjgEHyA4CE4Dp4RCZHIBVOrRXJWU4ihi65rQuud11oAAFCd56Zrdge/uwmIWAqcTnmaSs5g1CIEQCJUbkAAVSxXwAlUsvfoyLkADTtjBdUlJVERVMccGJgcAMfoC0F2BmJMRGzMKCDBO+cCm85LFpXgse/4sCOpGlw57Nq2i7WWeVJgH5rQ3PimfekYUayKDvPEmDz5w10XXbhL5eaB3j8er29a/5jP56nWxLQS8AF9FRBsUaOicn/VU2zAJ/O6wIAgDopW+Ms/+/zNm+tXt7c+suGL9w/v7ofyj7/76ptvvn379ty3gARvH45Vn1rXwhEmqXUeoaSm5Vd3n93rsdSaMKkqoBoDgWcjEtLRVAyNDEwgb+jQs/0yrf7Jtjrt4qqdjLBRtNayXTesB9TEDHB1hzdybstQnrEjNQAgQ0T3bFFtm4/YT+riUsvKeodLmxIRkZyo2OY3jSqCFyfBZ3Y+wEZY3Dp+BqAX92pTQHPoAExrUlMiwTXdQyRjY3DEyUm1aqqAQEpd7IJvG2r3/Q5ySQJEbkpA2EgtRSnG9nBwalSXOaVhPI/zVIEhVcgCDNS4SBGWcapavUdUpOqW0wSagDjG0Pr2dt+r1cCu73YxRkRXxvr4lOpUHx+evv76b+F0cX0RgAqA7JAJCJFrVoOLX7gZqtoKxcGal3skcg7Tsnz7fv7mH95DBy9e02e//OL209vDy/1V92L/6e1pPr57fPv+8QeZ4XZ/nQoIptNc9D02e64EnnUfiBkdqy55mpbb25vdNWVXbQFP7vCmnR4TzZynJS2KinfdzT5ezaVOuZQ0AhZgVIYCVYtw62J0nl3H/eu237W7ruuC86tMQS5LOabj/SAqgmJoTA6ZjGR33QGYjk4ys6MDXtdlPv8w9fu4a/pvphl2og7RqaLk5QRGsWm888u0HLpdSVlAPWkBZSPP3jNbrcs417RaAAMirfNYxKwoa1nQx0bz/0PbmzVJlmTnYWfx5d4bEblVdfWK2QcDQAQIAhJolExGM8qoZ/1UPUmimfRCijIJBEUDOJgV0zOYpZeqrsrMiLib+1n04DeyenpISS+4VW2dHRVdGRlx3f2c73yLiao2VJcapNGcWLgtkgb0tCByb2Sn1viobrdpK++N2jJiZ0NHbR0TNfIjAAC1e77BHU9V5NNdvtmuALQI9beGWtsXXwKwLqQvR3RqLvLtS2/aDkBEE1e5NDHNwBepqn2FhAV4yfT9/3d9WUL49Ag+qYx/l6kAAACBtOE5LR4VNgidwTcDYIaWbOVsmyd5G/CbmRWpAUlUxMoTXQwdQLc3g5zMzRtH7vKaLp0ZILbREAGgmDUndWIOiEqbXz9S63gduVE4gJhE5UvI3Paei28S062/xUtAC0LbPKEBda1908aoAHcgcIQNXffNihnFDNQ5BCNzMCBX8pAjKKITURNIuqmqaSmrgAICBcqUKHJKSU1BHAkQVME0OJEiqSP7NsNwcIW2cTIAOdHG91BQBWAMSA6IC1g0QSMgCAFSBCIgIubAjKUsqs6E6zqDewxhvzsMXZ+7HCPc3HS73Z6cj6dRnXI/pBgq+ptxAnpTxnMOOKS0ntf5NB2ns6HGLqUc3fz1/UM9LjvP+8MVh349108+++whzh98+NHt4dmuSwZ81CXRILn+5NWP//bHP/rhT37yy1/9+s3DDMDE7ADuWmpdSlUxYqKAjpAypSEwUPTYx/757bN33333W1/75u9/63tfe294P70XkUOWDjoX2Yfd0V6Oy+sQ+32M8/IQiKPBMo3M5boLO8qj1EddKq6xuxJxA+XAHDGlSA6Hmz2tLOAxp8GGq6vD7rz3kKmwIkDgUlVsFVnBHAPGkDmG22ew20Gty3SecupmilUFwWstk88xRWICBmI3N1kLMBDDxgQ0gxacYRAY3EDNiHC1GoOVUtpAiMjcNObepCpI6mPI5GmJXUzJmGuI/uzZbnfod8NhOOyRnHB1XwhrDIuKIUjz8sh9RiYRq9VUpUUaM7O7rVbItchqtDAH7ro42HDNj6+dI8YUIpM59jFw7DAq+LKu8+waYYDWyyEYClMEQEIzcQ/S9hLaEvG2wVobYW14OQJh+AqJ9Gly9rQftZWITzvu22e2MTJt/FvY2KCbyTl8aaPcCJhtv9uWfZPNb9BA+0524Vg9TR3wwmFibgNBa2RxML/QtbZN+Ml1CgHAtU1G2k+MBJfYh1Z94QUj8zbYu7xBDT9y9y1xp2meaXPtEhC6MO6RsQH33qwE3/6QG3y1QRzb0MUdDcANaZt+NBRr62qwQSKOigDkbSRgTggYHK3NHoFwGPqUeiZGiEtdnVERqqvUCs4AnjPEFINHIg0BkCFmjV0AhLkuApp6LAb93tKgMUS3vdf942u7/0KX0dGTK4o5AHA0ikpiVkGLVEN3FgHRAgDg1IJTmRKFSGCqdHooP/3xL2+f7W/udl1SLWC+iChF5hSlYrfbF2HH5KYh+G4IzL7Ox3Ec3T3n5I5SnDsmj/vhJoe1irhbiPT6zX2FhRLmjolwtzvkLpYqouKuqmpoHDyG0MXEQC6IISBytTntKnF852vx3Q9heo3FElNWqQbS2A/u1Uyh5cdam1212cvlRkRHu6hKG0X8K4vhskIc33rDvR2YbXuOu+l2DJsJCgcCdEQyN6TL0eguDoG5uYkSkYHVWlSF2ELC4Sor3szn+XRcbYUZ5PAR3L7fWzqd5uO53A/43Ak4xJjRqQKsc5nIQ51FF8DEgbOqa/VlLWWqc9HdrgshxOiBeojKoRIIsTMhJ2cCQmewOp1DiDGGdZzezGUZLcer1A2HW69VT+c5MUTOgTJ6KuBSi+oKBuoOEdRNis1jNVCIIQZzMgANwQhrCJUpEXut0zytph5DHLpBrTJvXQ2xObqjERkzhOjEnrugalK0yAouKeR+33NKhBEM59E0KSikOFzt8tVuyB1qnSepDiyGOV53ca8WHk/L5785vXkz3T8ubX+x3rQuc6oGa7ejgW+WE735vNxdDd/5+oc//NH/kYdcoYi6mAEEdxXVdRY3MBdbgdv9Y6CjFqiuGGOH+ziVe69WSilSIFC+TVhhGQt04MDneQXzeOjU9Yvj+h++/+Pq8t3vffTR1775ze9+83/+V/9j19V1KX3e57iXClbWYnOVtdbiAGZaaiVCdw8hIHpZipmqwsuXXxzP03laplmXYrOA2KaqK3WJD4XIuy7cXd0m1MghMIjO4GAu8zIyx76LbinG3iWOq56Oyye/eb1W2PUYE6MbISOhqZovxJBiSDGCADkSs6c8z1MIcD6/eTwei8LdbVe1KeAYwWnopYi6zut6PB2Lru9/8DxSoyBU0TXGEkJQZSgGbB5MXCMmRwJwZosx9F1PzNM0z6e1nqusYk34oYEhWbV5KmooFcwJiW0zPAUwBAvMiSgAjsYKDIEhZugCgeF8Op/uT5PCi7tsBlXWUmcBoADGoA5ECEyI2tYyfLnK9S3qyAk5hBADoIKbiIHhluDmDhiQPRADmFhxUUweu5gOOe+yfKERwNTXaZ3GAiuAggUzckC/vr3td11K2UyXda51XUupVbo+Equ5IDYnqsod9Bn6vgshiZiq42IpMQUiIzYIAQFUXMVWYg+Rmq1YDBAjEhm44Sbp0nGEKtYOh0gYAjMxE4lKKSNgyV3MXcgZEG2axmlex6mOs5YVEmc1VSloCig5O3hTPgIH6GOOAXMk5KAoClrrKqYeCB3qDBg0RCYGdgoduEMI7G5Iiggcc+6il3Udx6I1p9z3eHMNIQBxCVTQ2VTdECmBMwHt+r6FJqoaAiiagJgX73O3Sx/ur977aP+bzz6Lw5QVWAAAXFdHFKsPp/E0KSQ3sJnouk9C9sUyAgJcwe9dwaGHP/yjb+xyd3O45pwXlc9efvrrX3728tNHdBhH2O25ejgX2UkZugQMLZx6rhX3sISJja6Hw+p5LlN1oYBe1SqYoTULLCTAal62Egcv3HNyb2bVrc+izbG0FV8UyN0NfQu0aZXgpexzstY8boz55tVijhgQEOFJDQvQOORfOh+b0O/pnPRLk/lb3+CpRv2ti/hSr8FGv3pqIB3dARUBRau1ADkHVAyNaICIyMjspEaN5IBD33e5W2Zy165L5KgFDSGmpMHFCRBC5hS76XgvuroUjkAxKJHVMqmmWotKBQF2dCAPWLyWEQhz32fKKeL3vvvN48Px+HBaTwVmIBZ5sDe/uJdJSqlxoWpGxrC6KYBHhjYtAzMnzK2UbjgLGGyy4w0UQWghsYE7EkPwBc6fwN/df2Z/85vf/+Nvvvetdw/vDCwcHO8Og3QTwIMVqEYw+tHHCmn/3PsBhwEJCA3EIBi//PRzIECFrrvu+0zAD3l8+PTsBeAadmEXhmQOKoDMnLM6ASkEMKoffOv3Pv/85fRyBIL3v/Pen/+Xf353c3v/8ouXn3z+yd//aj6Ntci6LGVu9DFCQmQiYsH1W3/2YZRoEuWMS5ViIKhGpczlxYfx+Xt9daxeI3HqSYbBVXOXMydZqtYCQIHQAE1MF6mOlIJVN92MIAhpretaalWNNYUuxJRyzHISU2kMIkMEsAugQ/4kyWuoxJM2zzfuEtkFatp0ZbhBSa2ruThPwRPjsAG2iEZvS8e3KsV2oz/xGc3NN4tVu9zr22K4dBPUICy0Fj50EYw4AoA1rlCLdmgrigDQ5avQ0sYv+Mpj/59Sxy8t6i+TsP5z/2NQaL8AsTmMk3sjU1oDc564l28BPdx2jCoCxABAxOAmsPV7YuLIzOwA4kaATttZa+AGig7EgIzA2wfTzK+YOeRAQF5cVAgZWmITEqJTcxChC0ds65mbJgfoSZbcPtV2x1DLrXD0Co5qFkJ0UXEHA0SIEZEQWvD9VmEYIJqYICCVzWC5cdTcmmt7oEBMpuDmClXcTQBahDEtu7znEMCQ3RzNwdW85YgR2DYzs22zRwZgCG1aRugA1bSYto7YzUWUiNZ1BZUYsB/6nERNLsMprOaljCpgCkzQZ2o2SyHQ7e3VLt3ur29T1wEel1Lm9Y2Kn873JlCW0hFa4HUZ63leTueH8xwYrph3h+shd9PDnD0ghfG84nLaxV337Prm7r3D7Ycnt0/uP7s/nf7D9//2X/3r//Vnr16eCxhBDEAMrqDrtroa5siMzjCrmoAB7DtgPADheD6+fPP53/zsFzICAAwHeL5Ld/3zP/uDf/IXf/IX//gP/niXh6WfzWq/O8zrcQX7yc9+Hkge3ny2u4o3z3e3/S5xb8A1APY6l+Hx4Y3WZdgN/aGbpil1Yb/bpS7fnx6tSoyx61I/5BWQlK+uD735vNZ5qY/j0cTZY2Ag1+9+58PxdCzz+XyMd89uiNisSIV5BuhkmqZ+1+8OuhYnB0/k7mZquuV6MiEhORsQu5hWV3TQJeTFZeNcmFUwNycFBYaceRhC1yEznseTnc7jUqappLzrh67PyayMyzpPDypTDHof4G7Y55h2w9Dt+moiIuu6MucugblXU3THQNVkLXWeq3HBLhgkA6LAxNENRBUpxcxEqfp0PpWyzthh5nrVIRJxdlkhBsTMYiKlUk+K9rSz2CWd5mlnac5828ppz/ltpuhvfQGXU/WyeW0PbjJg8O3Jrqq/uy0CgbchB2wklK/IuhGQGNoyBN8Sc/zyzTbaFBE8mTi0bTlsAIG7AyjQBSoAd1B/Yl3xE+zk4LqBR3AJc3fgCwpG25Ckffq4ydfb4UTo4LoRsbClRTiTocETbb2hZpfIwd/a3y8/kINtW7VVj9Tswp58JRqQ2jZ08OZ0IW4CCDmn65urw2FXTQBgWRdM0c1EdVlXNUgxI9P+ap9S/PTlryPCLufhepdznsZ5mkYT6Xu8PsDtza7PQwod7/L5ET7/7NXHv/x8F2Ie8ip1FSP2mBKze5JlLOsIa1mDmhpSqDGl1OVSreiqqqWukZ0CQIEf/ujTwxX8yT/+XndDjkgUShkj5ZSjOvybv/xBi5mHCoBwewcvXuwaYyPGzoxO5/n+4RNzBIAc+5yHLgMS5BSdLCYW9/P9CKA5cgICDGq1zWCYQ0BighCQqSUJmugqpaz1fH149x/96Tek4v/+v/1QXGQxMwiBY2QwR8QQAjQDgsskB7SVHqFxfBGbCxoAGNCTRce2PFCfTl58O7xpSiQkJxdp8ntwB2BQB1mFFUIkDMwtwBQaFZHdoZZSQQIiEoUumMvxPCLwMMwOdri+CilymrjAm+P4F//sD6+fhWl+rPYQB5ymqVYh4q4LxGGpYqa11nESVei6DinM8zivUxE7nU0MUtQ4dPvD9evPppSiu81ldZP9Llxf94d9J7Ws6zxOY9/nlK+Xc/n80/s3X8DttX7w/v7583eu9of/+Fc/NKbJVtcVFIgzM8U+qFUk3B32V1d9zFG1VBGt67o6sKUEkTN4yikgsgrMUxnHxQ1SNK1OAF3XI6KDrkstRQND14W+j10OgZGZmQO6rOtc1tUChjx0uTeDdSmP5+M6VRdn8nOXp/PQ9SGwERlC+G/+2X87neqnn7z+8Y9/+eOffvLwEsCREoEDBHeHssrkyzvvDi/u7hjzL3/+yc9+8Ju//pt//94Hd9/9w983Ws/z8c3xuK4KGFPcKa+EshSro0MFjsAMS6kv5SV3PTJD4NTl93//e9M4j+dTmRZbq8yKCPkQrWEZgJQp5SgLLOf6k3/3yU9++sl3f//wx3/yB9/41off/tafvH79+ng8unERmaZ1KWuBVaQ28bcZrMvCCESUUg+YYmKpCzG+eTif5vJ4qvMKjhA4MqKhEUBZbSyGAENfE8xdTofdtcEKda1SYdHjUW6u036/R8jL7G/uH87nZZ5EhFzhdDKitSx+Os2qWkpdCqhBipATXDOJeL/LIVKXc04H5qza9mNOCQBSiBDQTaO5KJoKqNS11Pe/9pwC9iGF3C1VEYXQOFiI5rhNG0ULILk7c+y6oev6eVrHU/3LX/0ACkAFCAAZUgYO0RnePExIEHNIgckYHSAwgEEzXUM087DvEC0GzCnEtI1Zr69uOITcJRMlP61LmcYFhQIFIZFa2RACoZO7IV6OS9yUyS0UzZmYmZndwW2DurZDhEisUEAKUEVMxAm6HIZD1/UJAywy2wpusFZRd8wQhzj0Qx97ZBzudgqqVqvUeZ0ejo+gAAwhQt/B9fU+d51aRUAmiTFfHW5zNzRbjPM8iYq5MXdEqFZrFTDh6DFhTBFBmD1GjCGEEBDI1c1VzV88y2YAykx9jEPiQQWOp8dVzuN8RoY8eOoDsldZp0WqriH6gMhsUkc1d4MA0EUe+h0RxhR2fQ7BY8cIJYbACcXrqpNJNQBiJmcRYMTAxDFyJEQ0dVWVWsxrypEDRWU3Uy1mwNwPQ+767qbIOFcAmObzulZz2uUY2rGhIGLuYmbgWq2ariKBw253OBx2u5Dy3QffWsta1qpqpiiLLrM8vDljxN01lUXBNdCIXJ7d5P/qj/7497794c3zQ2Qgl1/+3c9vb25Ktb/78U9/+LOPf/Tx62kGFBg6BIBlRTqv86IAnHIPCdiyjmWefT3DdPzs5p27q2fXqxc9KxMT86iTuYEAYggpgDY101akNeyH/JKDzGDePNcAEZloY1IgOTgRlVLhK+XZBr/6RWv4xOO4zDiffqH/bvnHxE+VZysy3d1V4UuKpLemk1+5nNsJ62bu5q14b1niENzQ3N0vKIMDOKgbIRqwLNUDUmBDc/KQ6HAYhl336lhOp/Pheer6YT0XIHBZIXhKajiLCoc6TUdicAIi5LRhZaWup+lkrjGwByguJgpIEDjGFEMW0eU4/9Vffvy1d2/fff6CgF++/OLnP3kJ9wACUAAAQAEqGBisAAbA4IDuZqJQlXuGp8Sl5g7dxq+ECEiO2rDeVQEhBgLiutgyFXD/6/uf/vX/9VN4Dl/77t3vfffDm3eeT+XefRk7AS5znfY3/fXz/sWHudsJ0SrVqHShP9x1OQ9hmefxPK+jrJMuY3XDPGTwOuTBip/LY7MVCEPu+n6tNC+TQw1dOv76zTe+83v/5H/402988PXT/enf/ut/+6Of/q3MABW2vVcvv5/uHNzSPP/m+HPIQBl23c3+cPXOixfU3Xz2+jevvphWffO13//o01f38zpSDDnFcLOvSwnIhBRTun/zJnJoVAAruJrWVaUDxpgTW2/BAhjfHO4I6TSexmmqjwUcwOD53XNAJ6INsyIC26b7vsltmwB3c6c186fs86cbtdmkN8pUa2O+1LdcbtQGxxARESJU3ZDWduc/4VbbwN4vyLIjAjQ12+UveWsk/7bhaKP4CyZsZu1vJtqaCndXVXKCf5jLGrHp4nP3u08IyOjeaG8qzgDASBjIEQwN3F3NFBoJg6jd7RviZ2rqFogCBlMlagD95hVpvnGikFoO7UbccgBrQjrawljN3bUpYjBuqIw4grupVkL+0kfql273LYENG5h14c5dQrvYG1RPAODm4Kbunhtj5IJ6EhExGTq5tnsFbNslzUAd2YmIgMGDrUWIMTb/LAMRsWqiZn4JpyAAInVHMMfWLaATglsbRzARNl9/QncC943Q1boKA6PARIxgYKoAYkgG5MtSjIGG3PWJUxStDl7KmiDGGETDukpAyB0lDuuymNpu2N1c3dU59vFq6Pelsujj8XGcxlUq5Ki7D6+e3xwYXZZ5Ujepg64xpOvhcLe/ut5dddQFZxOcVNKOP3z3/evrFwrhp+PLn//ilz/48c8ejseffvzLTx5mDn1PaqRKvogtBe4Og1WTKk2dqwghhd3QVxXViiF5CAaIMaRhfxO1DgUV+zTkbvc4Ld//2Y++eP36+z/8jx+9/8G/+Of//N2ruxVGccywu3n+zi6FfuiX9eQatHSmalWSY8zhPD6WWkxERb3q8eFN6EI39JwiqI3LGQhVyryMj6vMS0m5C7lLXQgxGugaCiMHApF16PP4KKqyLHPkd2KIKy2+xeXCNE+7/SArvnr9aGh516mIFDE1RMi561JGwHE8mzk23zYzokiBWhQ3IaK7QdXqwBAT5B5yF3IPw5ADwONpZMbcd7vdQOxVFkAFFyZIQ07RSVWLYmiAupuaqZp5jMQhhBhDiESEFIP3IUc1WIr4UjBgTpw4iLnqgnEI0R1R1OZVj+dVKjCIcdU9hBT3t8MrK56cDLygA1Bb1JeN8i3YfYGfLrShthdgq7afOFf/uQ3rqRDZ6FxbcusF+cKvVD7tqQ1ex4Yvfxmt30Z/G9BNxLJBV3TZ4nHz0SOmLZH38hsbZ7Nptcx9E//iBQfyDQnbDoTNWfHtzu+XBNlLitw2AgQAAt/i6N7qzwnB3NFdHZ1aXQFwia14u3f72/fmwr+Ct3YRT+gVNIrP9hLezjO2eSReykNrVHlAiImGfZ9yWE6ylHkuc2YEQFEtFcwgRgI0Zu6H4ebmrpTiAG6uKlaEwJy2zbnvBgBWgVr1dFweHh7sDLp3MVvn6iQpc0NPiSiQuqsVK1bAoDm2pIvrobpaI/wRDH0wkfs38Otfvrpa0/42BO5E7m0tKfc55uiQImAEjbBUSJFDyO48DMOwP7z67PXD4zSOogLIMKQ1d5mZckoywO3tC0c7PT4+3s9F7eoKQgi7fedA5qRSzaSaYCBHM1RmajvwdD5/wZxi/7X3Pvj29z78wfc/Pv/iWCoQpEBMxO4G4ETk5m0sYdZKDANwasOYRib3C2fQ3kJX24D6MluGL8V6tqBfRzAzJpdLqu12vhm4oXmLUMNtcEbITBxw0hWZzJ2JYkpaYJlqnV/3+9x3fd+5g11dHw459I/jH/3pN0/jJ4/ns+C4726ndS7FVgFRKEVqNVFFpBDbDBfXtZQiy6xVHByYUKotc1XFeZzAd4CynAUqAEjfVR2Cg4loqcZBaq2ibhagynQup9M5hjTs9x9+87mbLtN4PBZZoUW9GzsT5b5/551nw9CvdZnmVRTNSMQMwBQCIQUGp6paFlnmtVYIHMHDulQiSClwIHM0UxHDjdvPiOwO81xiiGbohqWY1dVpXMURuFY5n8dpBBMggzmLm9/hbnd3dXt3ddgd0HcP9y9/8fPPfv7xpw+vIWdIOTtSKVZVrWgrHt+8mijyzdVdjCml6gU++/TNt779HoYAEsvk01g5UKBglRlCF1TYZHEF0Fa4m4LPQIgxONgnp6nrhqurq/jOMzSVUqSUZZ7XZUWj7rrX6vM4Y9R0DWUGEPjFL0+l/O3HH//iv/uX/2KeUGoqtczTuKyLWs19ZmYps6EVg1ILM4ZAMcSmI2ve1orEKeYejdwhuEWphugpRCMBmcGNneepno7j8+cfiSIHK3V0lxAAkcyglvXxcT4eH+cJ3MPds52ZvXo5Tmdg9JTJHV3dRdABiRjD8VQAVnfcX+2G4fbFO+/P03o6rY+n41pKKZpziCm6ei2u5EACCcABCE7jY99zYoLQ2lkgtJCgG9wdQgAHZCIiUnFEIuRafBrrPCqcARQBgIgyx/1uz5GmZS5FzayY0EBunmLoulSziLQEl2riu2GQuiACEwdi9YIQInf73X5/Pbx++RqUUENdKwMGToFdSrNoIdBtbtGKyVYDcyuekQzAzFSldTFMgK2qJzQ0QwNQURMXiDAc4tWz3f56Z6Dn+TQLZDAkjB1SYFTu027fH3LsCJEGeDyepmle17KuyyYlUBCDBaAfPKaYUxdZ5mmtReapAkiMkTkQBTInpr7vYuQq67yM61JNxQEQOUTMOQQiJm6MOFM3NQdwFVA0UxeXWiY7q+qyzkVqdRgSxM4waDW1Vcu6EvjukJmTqH/x+WPIHDFGijHEyAGRuy7nLiKIeylVOPIuR0J3CW4UOKSQ8AtMRwAAIABJREFUCXHfdxxC4IRAYiDVVHVdyzSNBnBz7d4nqYKmyBiZcsddTmJGTPvrq+PjOL55nKZKDLtdAtB1LaauIq4C4AReigDA0FuIpro8HsdSa77KouItd4yQE3YBPzgMX//WrVScjqsqxJCvr65C4tBHoGlaSoxh33UY8HSe3rw6f/8HH//071+fZwgEFEAhGOhUgQLk3A+7IYcEBVQZbQhuMq3zWoehyM7EpczVo8VMAECMFrxZOepcHRWaH3Aj9hrIhXLeqBnWaidCoi3tp1VBZkbUmFybAqZNLi9G7NAU8U1ZCAYEunmtAGDTy7y1it8uZv5yAXnR1lymdtuKpt+hX20nbOv7DMD94kyE2EAxs4aFoSM1njq6o6M2ToQZM6G37OemZkAHWWVdS+0qUhYnQQApK3W433Uh61rmaRlvboKjmZioq9amf2LiGNEhATsx5WTrWXUFMGJkrTreL+N5ggeAKwq1I+Cw5iRQHdlpY7YJgAJCuPh2sDcbTEQPpFqacQZeiEoAzZPezM0Ump8GU3B0cSRD4sSZnK3bxVM9wgO8/PghUvf+Ry9SPhhD4DVnv9rHYR92O7i6SiGBiVIFxC7iIdFwO1yf9Ux8Zlos0fWLCM/wzRcP928e3fxxeTCFlFpwH1EGwhpc+m7od8M//e//6fg4/uYXv/rZ9//udH/67JNP5QS0NOeorZ9gR+SWsfpE4iMHwwpgYCOc9OE0TFaW6+f57uo69vRqOaMBEwLqspxj6gIigNeymgs6gYCBgbu2kAgFQFCFLsWrm0GikbJXOJ/ObTwQOWz3B4LUqiKq3kyCkdA2ww9sGK1vcEMbaraAkEaQ8khP5EHwJ9zmy4Sm9ghdUMiLwu5JVXuBfd9+3fIAW/nPiM3hapNhbCAYqMm2XvxL3+iCAjfnYrdtgQC2BHmAzUjuH+T6f+FetStQInN3U0AHNCdCxhCDIQqAmmykSr8Y3G18tWZI05xaEAOBO4WI6ArORAjoqO3k54DEDOiuChfiqBM4miFCs+VDcwd1VVAEcnJQMHdzIzBC8o0YBgiNzdWYClsn1kw32teELS0CzMEciDevmPaRNnceaoldBPiWevql5tifGjwAIgoBAhipzCtGJFZEdvN1XbVYWz2tHXNyTtz4DYQcQ4O0kJUEVmphj8ho0ISx7Q5FdTQndCD0ABxC5lBBxNXNGIKBqUBVsGQElAIzQxEp60rofZ9yjAtIl6kfUgSe56kWwN3hsDtU7HSFV+f7z169mmU9Pq7rAhwAgVPOXT8QWETUsgT0q/0uhXS9v352dXMYDh33ZSyR8/N33nvxznsY8if355///Wc/+/TXv/j7v//pz/7+zfh4nKfqBIwVjRgCMw1xv4ulmCPWlvdOyIGIghEBkgEtVWVcTM1WZ8IQmblT0UnXdV3LuAqXUcaXp5c/+PgHp/X89Y8+fPf53fvPnu/T/ur2HdByx1HkNkRnwmWdfXWmPsY0JL27EZE1hoZKk9Q6T9bhEAi7GA0tMZvZWpZ5WatWKoVCzF337Paq1upm6F5WX+fzsszuoLWqSJezqZfdPC8TMY/T6XD1nCA9nI9m6uDATglBMYW43+36bpCq07yIrJEiBxK1vuv6Ps9nCMSMDVSF3VXo+tDtw93z/W4fQ/KUSRaZ51EcHRjQxvG4roUDSJkc665nCChVDaGusizFAIqKKVADjB3VAJBCTMzQhat+GCiAmOq8rFpE5q99+Iw5iK6lFucqFqra+bSez8UdEoniUgW7fffivXd+Tg/GCogQCLvYaoav5L84vN1DL2sKAHyTL10W4W9FxjaOLLxdfBdC+ka5bQv/7dPp0ts/XX6Z0H0Z6IFt0PEkDUJCdjZy17cveYscbZoM2uoSBwNs1lTwJLyCyBuq1VimzGDtyGkDEtyyCBHxwgVz2/7ZROpPb0kjDtOWSOcG4E6IaFtonbk7GAO1PfSJt/a0p+NTHmuDpLwBZgDQvhVesK3LnralEl7+C9ADAbVtHJDR0ZEopYgES5mXZSqrcGdMrA5iQAQUUFyXusYan714fnx8PJ+mZZrd3ZVSJBUDFxEgCipepT7cz69ejWVdKQMyqbrURgJrgvmQEjGlwLNcXrwV16wtEjcEJggAXa1LFSFiBygCv/n0vnjmdNsfEmEWUTMfhtxnQCOmAAzoxY0QAnFESiLwxevH81mIiBnVbJzLvAoSdLnraj0c3nOQUnCcTRQOBzrPRdxSIiSvaxERRGAIjmRQnRIRCFiVep4fzuO94Xr3ov8v/vQbrx/+Zl0ARK3Nfdr93I6sy6cBGyxrjrwtAXyihDfQ9kusugv0i4hgX7Lw9w2MJGgON96sNIHwEnrcugnaAC8iZg4pYiQHwEStxiJmBQIDJZjWAgBVaq3y/O7mcJdfvPf1Dz66/s3nnz8sVWQq0jMHJJJaTmOZpjItQsi7XY6JVF1Uz+exihNha0arYFl0Hs+1GAi4GBCgQwstLqUuMyF51S0hR7Q6hGF30Jt5nsvrL16b6NXV7g//8DvuUpbl8c345uXxzauHqSogRAQHATR1mcbx4fFsVPf7PucgVl1lXShEVPV5rsu8ujlzRAyqWBYhbLnp25sZA7dH1qWaVHCvVWKIhMGNCVMpssrZzkvgRMgG3HVMTnV2whDTYX949uzZ3c3tfugPP/r+r754dfzi9eier3uQinWxpgh0QA6p6Ql01M9fnmTxslhgRnM5wc9/8unti33qUub92Y7nh9VVZSVdNYaYIlpYwICAjDxExhAERXWdFx3SQUzmsqhJJAwxpBieXd/eHG5CiONpPD6e5tO8LgsxxhDa1hSZ5gke7mtZOeerrnemLAoZcuqpanVzWYWwmlkpS61oXmNEcuOAue9ejRNywhjZHTCVBasoAgMkAHItrrCol2UpdfnmN7+OGHbDAWdzWK+uQgzJHJZlPZ3PtQJTMON10lpdKwDAMm8GEqrgApvI2iO6SuV5Ug41Q0hx2O9v9vvDcTwuy1KqhpRziJxIAWIXehi4q1WkqD2e7gXTwAFZDJQCEFlPGBICUAgMQK4o0oazUQTWeT4fFykACoCBGk0PU6QcQ4BMIrbWBcBQ0Q1DiB2ADjZPaxVBc1MPROKoUgUxEBEyEevsj6fz/FCBLXF2AkElDxiJWIDUHeBid7iNTLb5DG4CBXAwM1MRIuIWrc2RMZCTK7ijFF2BABPkgW5f7K6eH/IhzctcpeQIeZ9MHapSBROEYAp1VXDT67yrPk/lWAXUIXYcUxJREUEGVRblnPqc2GScxje1jONYc84pRXFTE45oZoAcYzAPIlbVRIHNIlIIMcdIyIRBpQXjmKoEIEe/9F5gLqpC7KmjYW+H67y/yt4sPczUxBGIJWWOjnfPUx+HLg4BkwmsUynV56VWdfAKvta6UODcRQ6MwIw5x5RjdjDqIiCYYa1Wiq6LmLmIlAoOoOoiAq4pKEdiDhxAvYiqmt0cbtdlZtqa0UAWgqmUqrUUcTMmcMQYPBDGwIRgUkTXaV0nPTsCEcQYUkp5iJk4MA5d6rtdn3cIVFeJ3In6CiKwvrm/nyeJPqCX4+tPfvPLN59+/loVkEEWgAiCnHKiSEYnTqHrMhPACOAW/Coj+/oAg86nFehRopRaXMHcmIkoKCgLo4IXM/Mmq3kCobYCD5uSxZGAEJzcqfXOvrVa6MgQiFV1Y1w9DUGf+AkXjnzDD8Ad7K0fzCVM8+21kf3fzj7xy49vU0yi/1QnjGpPM6KWMLnxxnADsFw3sSMDELhsrw3BHLs8KJm7XmoxdaylzlUmAy9l1gnE666HyeDuMNzdDollWWYzyLsgpo2pDQAcIQYIIfT7HhxMIIToDpF1OdXT/Vin0jLKz2f4i3/0J7Us88tSj3p+tZQ30Gk0MyuARq7NtK69YHe1jRuyTUW9CSURGAmJCAFsWzjabGOJmCjAVsS6K5qag03L0l3vjGT5fP3N/DKu/bOv9TcfPh96OexryC+5h/2OyFddZ0RK1JXC9/fndTzLwPM4nadlqSsFfufd2/3tIXA3TuPj+cg76mNQ0SoVk1BIKeLh9uadu+fP7p4TglV5ePnmi09en9+M87yiITO5qgjACtgGwCuYPo1uiYgNFSbFjIQRBPWo93Bf5nj30eH2+Y0F12pdl1fR8zr2rkBJpGoRMmIPQNBkZACGoSmlmBmIw363m0olRFEznWOI/W6oKlMZV1nRUdZi1VTVFRq1DTeThxYC/ttkqrdL6KnEB7CLB1YDFN7es1/lEm7cqCdm/pP8xBuFCzZtLECgC7egaUDeKlW2R77CD/DNDOctBQsMiJ5UKfDbKPE/1OWX63f/KHDHLk0A5BAwROLAyIhI6Iyu2w7VuEkIuLEsHBhcTA0QkRuJlNuysRADONSqgB4CM/PmUb/tEVuxbu6uatTEnQAEiKCmDfSAZn1j7gjWQi4AAEAv73FLMuOtJ/QNt2pX+xgRCQ2a/HDDH12qEBIFJmzDg8sH8fTuPLmgOZg9bamobWRuYOrbKKgKiAMCJY5dF0IQr0/gNjG5t0xDbD8vtcZCwcSsKjqCWwtkCsExBE7BFDnFoc+LrZNMCBg4CCpfLFNgE/kGB6stXd0dAfoeYkQAUNMQQt8N+13f5VyO+vr+zeevXn/6xaf9YQCFQJAihIRItq6TaSW3GOm6v77eXScOCVMXup76m92ddbTf3d7cvFOK/t9//bd/+5O/+3c/+v6rx9dmOI6uAMwRAwEhg6lVUedIsUvT6YiG7gbkQGiEi5Zp1twlZxYtay3uIAJIcMgdBYYADUcNN5EG5n3wgJ988ev/5S//p5vvX333o29/7zvfff/FO3/xR39WZez7HaggqrubdSbZABio7+bYpfN4mqejFrk5XM1lOs/ntawU+NndcyOY17obugkMEIvItIzMMeWQ8rDrk5uZVu34/ovXWiGkEAKVsuSc3bEWn+dcq43T+d13P8qx+/RVMKvLvKbAIQV3J0AFLVK1qiMAkTm4I8fQD13XhZiAEQI1v0vf7/H6ptvddNe3OeUWM+FqKq6IocoqVsT0OL5BEBVDghRiikFlFU+CtSzFHYoLGCGSO6xFqmmXunYUETEgisBiUos4wPEE77+4SikSwFrWqRjGwTlVwUbxniYrsJrh1dX+vQ+fQ/ipkRoYccwpOws5IGJzKH/i+XxlCPCWvXohSfqW9fAlohZtJfcmEt/24Y3r5L+tBvxP2AIibKZYl1316eFti21ETyZvvtlNXr6B4O1lESH5RUJ4WfGthtk0hxxJGxQGiMBtpCKtCDN1cwgAhrSNuqDBdridLpszkTeHEiAAczQkvgB+Lf0U0dSs5c0105ILg9Ph4uP1NBG5fNXOLLr8m5ps8Ldw+Q07cQAEYkZksC30EN0pkJgBAgdAsqqraJGGnG0HHqSEIaCpLsusKnd3t/M0OphqrQVdmcCaHSEDuCIyW/XzcXz96ohEd3epqJciZgYYdJXiSgiBc4xdSlpi2dALA9GqLWSPkAnZSJUAgjmIACGMox9mXGaJOeTUkRUiijFeXYXxJO4eI2aAnIiIl1nVRub185crK+Q9moFUcLecQ+BIFMGoGhCzeRAHcxCFcp7XQleHTATLJO7Qd5RjYmoRAcZMlFPXx36Xi46vHz8d+rv/+l/8+c9+/jOG8vBSTFzBm4DPL9E/mzeBPUGa9vRZYVsh21veEmcQnuzcfEspaZ+jgyNsY+E22QsUgcDQVRWaWraV4NWczcwwMAfiEEIiCjl0YZnXZa0hhNCzmSNCrXWVddW1TjAMZ0rpG999t8ijwESx9LnnxLU6cUAyqcsyiyrEjru+izFLteNxXBcFjMzYQkhNtIqJAVNWqG7AyLlL3pXUAYUtHwEAQsSUIxJR4KurPsX+zauH43Hyh1rs/tvffh5CDDE9e2d3c9d1BzyeTrOstcC4rg/HN7n0p9N4Oi3AkJMzoxq7gSDXwrXqPNm6eIqRY3bzpZRSLAbg6mZiDilRCMTEbrauVYoRQa2wzGtgyakf+v1s67isx2Vym5mDFhtyl2MKoQ6pe/Huux98+MHN1X5dp/svvvg3f/V/Broio/3t9drr8XGS2UQ26JwCgZsZpZ7ykExpXkYRD4ym8KuP7wHw+bu3Xdz3SZbxWKrK4jIrRmZMhKF1hkRAxBSo0Slbvmgp6zieTVYgO3S7oe+u3nv/xQfPc+4//81n6zKbBkdGhBAiAJo5ABPEv/73fxcTvvPi9uZ2Bzs0N6MSM1UpUnSllYhKWcxAxHQuSSAn7LvD9d3N6zoDs4lUV6KmnoDAARFVHQzMUYuawVRgLdIM0VVdVPq+DxwBEqGZoBkwB6nwcD+VGYCBGWpxVw+R2ws20VqhrI5C62LzUk/nQrl+9umb87jE0AFGd1Q31VqElmriFDrcd32tcRzHOllVKFqCCoMjOTFwUA4UIyEyc1SFsiqIMcfA/br4eF7nqTJHTl0OXRv+u+gyVlU39MDBMa1lLktlZutSCCEPWcxtFiZOXRdCSsGqgVZd3AHctKzrw/pgYHD3ewMCNpAihqxmTBVpmxgh4ZbP3kLeCLy5BPMm+3BwQGuukMxMkYBRXURW6gAMKMPVs+7qbne4Grgjg/+HuTfptSXLzsNWs5uIOM3tXpd9ZfUski5KJCwYNCHJM43siScG+Dc89j/wyPAvMKyBu4EhwABtwLYsWyJNlcQqVsdiZlZWvnzN7U4T3d57reXBjnPfy2JJ1kCAfV7iInHeu+fEiROx91rf+ppCHoJzsQX2WLQUy2KqAKTEyg7MoMyFis3IwAaiAAQueHKuDGpESEGMpiQOcZpkHItZQSrMMxOszlZqkoqkNIWJ2zayh6b1hskAQgAf2HsfQyAiKZRVUipDP6ckbUtIxkw+OB89M4tqKVlAiezqyVWM/vb2vmQlICDKeXQsTNkMHl11gVuH0QqPfUo5DYPkXCc/4lw2nZuuLYoEHDigWfRN4JBLSvOoZiVrzlaylmJVtrFqgmiapwI2hgi8Ju+MWEuZRSZRI3Lz1COWJqK0AAxtpNgggkpJyQQAmNg75xARwKFji8GFtlmvOttNRyRCUq5scXNmVqSM84BEq1VLCMd+GIdUCs5YkpVX169fvXw9j/Ds4lHLawEnFoql8/OnKZd+7tGHuI6u0SwwzSM5jRHBAcxA5hgi5hg99f1OQLqr7mx1djfvZNb2LDL7GbKpIAL6WtbUvQxBF1hpGUzSUqcpVl681VT1usmJCTkCAKtmWLJUbEykam/mcHiinLw12oET//yrMkITEcQ3/Xvl2zMCM4NZkZMA6zewOVBEsOanWAWvCCr8UZOYtOiSkedORtty4tAgcyiaVQoGswDtCn20UqacRx8AGKc0CNj5Ja02+u7TR13geTwC6dW69Q2RYlZBUSMgBiIIkYjRDAM776Nk0UATyTil/Q58gU1sri43jy6uvvz0xWd/9au7Lw+QwAU0hNyrKRJ5MLBSmSWn7GrQU21svgmmomoAopVCgqagRvbGjB9MTKCmcBKBgRSozkk6qoISEU7+Fz/9/OaOv9t8tLla+21ze3xlkKJvGPM0DSaO1R/v5+ef9vdfTj/61S8AABxAA+vtymHL1Djvzx9dqtd+3LuAMoJkWG/svXceX108akNL5hyEH/z5n+Ve9jfH491kMzQYiUmyEoXowUTmMaXRQIEJGB2iA6SKgZYkwYL3QdVMQHd5N+ac0hWcba82ZbK2aweeEI1IkZQY0BGpYyXvXAwNgJnzVCWxoKaWc8mpDP2RxFmyPGeH7lS+ESJF9poqclGn9aQCJylbNXqruj2yk3MRQtWoASJaNci0U7FX1d8nDezpVjqRA5ZrHk5dQa0Y6xhj6Yzs1NVUDe8Sd3ASiLxpLeDhRU4/FWU54IqQ4JLNV1/tNwBK/9Yeb3CZt47nbz4cN6QZNSsYACuwGS+0SgZQIjIQqBizPrDVTnoGMzHBgurUFAmZEQ2992aWSjIz8oxcm0AyU9O3v5hqj1MZjYgISFj9t+o0SuDkCgJwwm8Wb7/FE9/sVNNX3+WHh2r9jSXvCQGVqh19VnXCnh2zqaqI1dC95V0AoB6GgYAVEzFWXIK8Kmli6dINFGufQN7FpmGPNksp2Rwhcr2E6h8RYB+rXkeLyAwyCoiaGAEQAkf2LgRqxBKwa9sWCiUrSsU5h5rNE5lWP34iB7QoJ7znUkouY4iMAGmcTaxtw9n5drvdOKLPPv1FzrQ79qqwWvGYYT8AAwQPbevA8jQeQHLDHJv11eUlA8+HeT6mDHq1fufddz44a5+8nnb/x5/92X/3P/yjX768pxUqhNBE3wgpiEgaZgjetdEMZE5Sxpw1dLGWZGoiVq3vrW27bt2qlr6XlFQEgAEdFBJENVTwRsSPLx/Nw7jPR3VaIkiEfe7/4hc/+fRXn8fAf/t7f+DdJkNKOTuiwM4Hj9iCGngt/XPXuJzk7uYeQN57/6lquRnn+/395nz7wde+jky3t/fRu03XRB/2/TAORSE3PkxDHzdrdgTEofOf/kKcg3Xbdm0sUkJoiQoReO9Lmcd+jJExOApqIUEP7DEEKlnGMQ1jdjhUm1tmlrmAYYwRvZHTAuBInHOApgC3Y95c3jt/xS6poWgyCErATEA0jEcfAyAiiqmWAkzgiLsmKtN80zv2KiaiWvk8RgBYRAnJAJ3zaMuEuIIeIpAESOB4GDZdoAC7/WHf77szW51FIqcGVmAU8AhE3K7bzWWBAIJiCp5D0zZTGQhMRYlIHkqEr44G3ia1Lv+AEAFFqlEUPNQcb3RSC73o5CoFVfr0ppqBf+2i+YCj/c2/QkBkrqSpylAnAz25TRGhPvzWEoODWg+jQgWOxGRhfhIyMwFAQRURURBDBKzOSBVWeuB8mmkx4BOaZgbICpWrXZb1jYCZHJMZSikFT7NJPM0t33z+ZbF7cx7qGmgP25vRktv4gJfoA7KHgOwQEEAACIlRAapiOZUMqIiAaMCmUn3i68mBGIP3TlVLyeM4PHn6WE0QzXtHaqUklURITOoYTMBxNLY8w+EIjmi9We3203icoIBrXRnFyESQjJxz3nvFtHy5EQxLzgUEnPeoltIkqtvNih3vdjdMlEUZQk46TTmEGNgFx45gu9kM/V3JOVDwwcfYINF46EUtNi0sPrJLQiUjOw5MnHMe07AdVz44EXUM6CA2q344EJBzEaGUAszQNrHrWtQyjQkMfAiOI6CuWpdTvr5/+f47q9//1nf/x3e6/mivbzOaFVNHQA6lvAXEvpHzm5lVeT4sOog6lMClEFmuSVN9c/HbV2odrPbwiMjVC93USlnATTBTzWonJrq44JnIR19kdo69c6Xoqlmxc6GJKrLb3bMD7zGnPFmfIVw+/drz15/c7J6nsn/87Omzd9/90Q//yvk1c3AcnUs++raLITbeRSIlns2AiYraPOdpxlIMEVar9fn26uXz2xhjCOz9ipyGaM6rc2CWeUYfqO1aRGfIwTVtSzml/TgMJbucn7/+6zbwdrvedGfvf3hx9Whztx++fPXy5mZ3/Trt++OWzECAAQwO+/G4nxW0aZoQoqlTURUGI6ZI6NOcxiEDQtsG51xKAwDMSUW0iQQIZIrMPvicp3EERonedd0a1WclmIbDIKVkp+BJPKNkAu/aeHa2ecSML758/qMf/aVRI44MHSghu433XbZ5TrvjEfo5z1BtQMVg5deRfA8TzEmckYc8Q5psGlTAGPh8c1ZaP6DupkNKWi2MwAgEREqBwkTmFD3ENvb90DbduotW4jyNh74/HHoUjS5sV+v+eNgf9tcvbqYxIwEqaalkTCbv86E/e7IB467tDJmAvG+7Lsxp7uOgomZqVsx0BpMMBaFpcbVeXV5dHkmyglzvxjwTGTbOi4FakTzPo1khomoYChkMbJrm2EB/nPuxf/LEO25DaGJE53opxdBKAe+pWrjUdW8xCQQyzVCgmE5QXDYAm5MkMWW4vr3PeQYOSMjOY0k5pynn3T4r6qbbtOu1E57KpIeMbe1ba1jf0kxKEiQAFFHNBcaplFRVyT6TSFJIwG0EYMcBGeY0TXOapymsfLtuoo8MlEteGESleCLng/eiRSM3q3bd+GZmnommaRiPU0mqGSKH2No85TzouE/Bu/XjNpCfcjFEQ6lznYXEWNcDBENUBENwRICAbtltayQJMwGZopQyS8rSAhhohPPHm6sn54YyTH3JKa6aLkZwUEoexzELaI1ODdSu27ZZMdskO3TaroMK6nEuIjW5XEXJOQ7RgPoxpeN+PPZpFPDgPJRSRLU7W6nqnKfKJb96tD6/aDbbxgVBVOcxeN82IfoARqYmkuYp9UMaB3AoiGBOmA0RfKBIpODFNDbh6bOr2DRFpUzA7P0QptkhavAOQYIPYCA5j+N0PMyH/VCyQ25SSmYpBrCFL0tA7MCbauDg0WVN+/u9ApZcg+YYgL3nzWYdG5fS+Prmph+Kc6BKqlpKyXkuBdi5TRd2uxswi3FZ7WPDMWhOk6rUgVfjpY1naZ4lC/um8efbbts1Qcne69ZavcbyNKexlLlIUhBy7XCQ21e/TCn3xzHyNmdIpNS4fi7I8eK8OezHweBwXxR4vblYnW3H3S1Ms2SdMqQCqmCkIUK3ZjiDsCOcgJRIXeOb4+EWg99223Dh+xdHzeZjcM7nuYw2BwoUUArVdh6qJKaK4umUhwsIiFVkc3JmwSo+EtPgPNSAr9oEC4ABuSqH/2ofZ4BKYEBcM9doaea+WtlJqQ4tiy1H3Q2rDLXOKyuC9pt7YFF7Y9hwkm6dbqxKmQEDMEKq0JkuiV+IeS5FMnjxa3BrCN24XjvlUmx2TmMM0zAYQLcJxPzOe+t5PPbD7Br44KPHN/e3aMyCkEEUTMAhsoeiWQQ2bRuiH5KkOZUildHRBnxy9vSdq/f+7H/98/E+D3eTM25iYwJ5FpuJ2YfQgto4j5aWINfZAAAgAElEQVQLYDXiJXZkJjXjpW1CzkVKKaoqIliHR0ZEnjzAA52HzKSUAlr9vJmJ89gjBEVTs2wpmHv95dj85ctvfj9urrpxuPUtrNv1Zu1zGvZ3o858vOPD/TTfpaW0EbCjHaf+eXyphk8/fPL9v/V7r+6e/y9/+r9DAogACuEMvvfvfPObH39bsn3yk89+8ZeffPrpy5BJJiNBJCyloLAVK3PBBAYWfYzbKFlUzFFQsyJSslRxfRYVSgYGJK5zRHbcZX61/8Z73zhav2q7VKaio/cQmJwhEDN4UtcfphCidw5AmVmslJJSX+Z5OKC/vd23FFFxGmcARKaiZcoTevLRazaRrKIq1WkWQFDFyPBBqkFAavrV2EADABGrVeJCp6o3GVVdx1so7VsdwOlnbQMQQd8OsrYHE/cFASY7gVb1667vw3Di7Z9eTRVrVuibI1w0MW/uwcVV5d82mPVrN+y/CsBCeAbggIML0fsQfXRqlksmBjOd8lQvbhUTVQBYIiOJiKg/DIBvjFwAgImddzW2DPGBPFBhdYGqCQIABBV9Q3lb+GmGiCEEYiq5VKa45cVE5o3qB8F5JyKmRkRV/2wGgOQ9I+FcsqlRTQk0U1ioqvW/rl0zOQJULSIFpUYiqqiUmhjjmBiLibI2q8Y1DtiKlQSiKMs7sWNmRFIpRXJVmAJBiE1og6nNaS5zqvaWFTp9+uHH85TH3XG+O8AswC66QAnG3YAdOI95tvbMnb1/yWcNBezTMMgUO7++WA/jfpr7ec6eYbPi7apDsmLFESHK5fnZat30x/1ht3POnj55tllvylSY8Nnj97745P71q9ub+9fHOfUThJa25/7qqv3wvXdXrYNUhv64im3DrnXNsJ8a12yb87P1ZZ7sD/+9v787jP/4n/zZf/3f/8PPfwznX4PV9lIQD8OQs5Yk548uwXCYpzTPZrK+2MTGp5JSKVPJgBqc98ET4ZzmkpNq6bouNG6327MxIYpKjeRsV369bpk55amLreRkWlDMcgGTFZ+tqMvDtFmtf/TTz//wt7/5x//xH3//e99ryDtkE9Fchn643b+6+LjNNuYy3929fvnii1ym9XZVJF3fXQPz03eetatVQfzyeP/icPPJZ7+K7aqUsu/7L1+8ev/990Ty7n63u7shg9UqAFE/zZvtI2aOcaUCh8P8/MWvbm7hm99+L4bu4vzSAJ5/+eKH/+KzikXG6Lx3mjGlnJMSkBmVXNgotP69Dx6vzwMUef3qend76Fo4v+S/9/f/aJz2Q95PqS8ya9VMM6ckQz8BOh9ClgJq3hNYIsubVesYDnf3l/FMBZDJNRGYUsmp5GlOx+PQNH7drRDAO79qzrPgF69vvri+ocbHlsZh/t63npS5l5Jy0aKsFIyaXGi3P+Q03d/YtoPf+tp3vvHBxw2u/vP/9L9dbZ3sDdMKjEUHNamBMnACnipPu96o9XkCeAiIAbNaDzgmANAKZ0M1kgLiNzO004plJzrKadUmnFN+WLoe/vEpOxTf/B4si/6DBaCqIp985WvDfzLMyjmbGDJwZQqoMDtmLrmUnJ1j18T2aiUmWlSqIL76ZSFqLkWylmV+Z2JowOQY6lwPTMWRExOrhBoCYocRKRIuh2cqqqol5ZQzzBVnqrvQic71UNSdhjBvf8y6hbyRWRoBOUQ6bWkKKAtLHhEEpJhrYvBdyqlAblqdjuU/+A+/80d/7/fOrvjnn/zgenf9Yr87e/JYxe7ublTL/X3Zbv12uyJGkXy23Trvf/np6+N+6FpII55dhKGfL87PHj87I3LM/tWLw6efPj/uYbu+Gie7P0zDkEumckzkfIVW2hWen22bpmEOJcMwTn1/WK3XiG44DIf9ERDbuGKieZoqTU9yAoXH77Xrx/Z7v/+943TXT3ccXOy6L55f7/fz/l6Cg8vLs/PtVkCvd/dI9LWPvv7P/vRfmACBq0MP53wIARHTPO+H/tm7F+ttB2bH3b3Z/OTx1WbTjkN/e3NHII8erdI4FZHzFa2bxpT2h+MwwGYNl+erP/z3/85xd7y53qE1Tx5/aHP89Oe3//RPfvaTn/3qbN1AgflQyqDkWLKhYmwa9m4ax7Sb6JyrQQXVmPHFIBHQOQWr7jA+eKiol2qRAgbOOeddTrlaNSOigYmIqmkVw4r4wBx8SXMpGQi49bEJhla0ZEvf/O7XiuShH3e7fp5ngBMkWnBz5UIH623z/d/57sdfPyvl+tNPfrDebjdnrYFNs8wTzYn3+3R/d+ynRARt2148umzbbrc7vPjyRSksxfYHHScggNiEpu0IKSdr/EZyyXkKkc7OOtdiKVPK/ZwGQEXCEHiz2cbQFaHxkEopnolZUhpLGc7OwrvP3o0+pqSf//K1D6t2dSZq+93h7vY4T3kcMnMwg35/1ATA0K2abrPa9TdmoAoE4Bx07cY7Dp6RQDSfrTsDMRMzZQfRM6IVnQggBv/8y92jq/WmO8vJdrt+OI5ztowueF6vNjevdk2IJZfzzfnV+cVvfee3Xr18+YN/9qPP/+p18xSmh0KPwLsQOTD7tm1X3RpAj8ejmTUxbrdnTNz3x/vbu/39LqXCiEhWBvjwG88+/u13u03zo5/8RRppntz++mBA22bVH0ZCAjLy1J55iJB0SjYBQeCz435gQiZM83ix2jx9/BgN9rvdF5/ewB6gA8gncfNif+vACAgBAXQGge4RfO9737m87HbH2y9ef1arr29/++NSypTmUuYQfQjeTJxzZ9vt+ePzH/z8h/vhuD9AzgCAWkJOqhkCB1DI/WimnhAAsthmAx9++HS1YYUZqXz++e7pk+2jy3f6Y/7ZTz8H4/4wMW02Z6uhn477cRoSKAIzEMbQINo8TVYyed/5kKeJyAQtzbZ+BB9+8OiDr31Azp6/+Nx7//L61eGo6KBZxa5dFYG+H6ZpKgUuzzq1xA5Wq9CuPJESmScQKcyOKc5zOewGpm6zubo4e/bjH/18t5tWq62zdnyR81SOwyGnEci48RBMUC7PN65zr7541axjd976QAZFC4GCZHXgm9Buuu3rFzfXL69tkr9ZmENZKP/AEGLYbjaEbp7zPBcpImU20TrpIUYDdd776FLOAKBWSlFCaJrONzEEP6XUj0fTws5t3umevHt58WhrpP24V0vsEchqCMyU0zCO42TEGLxnDCXJOIwg4J3bXKBvvApNY05Z06SlqGbUQcHBxbOrGOLxcDjeH8hgu9kSc9/385iAYH0eqkl0EQgNPH7Ubc86cmWej87zdrtVLbu7XeDQNG3JtLvr726mUsg7fPqoI9SLq/OrJxfs8XDcT/NgaMT8+ub117/x7U8++WTo58Zfnq/PN+tVlmEYD0ywXnfRddev7l69utvvpjJDTjBnTslAlT0hqyIow9fe637/D367lDEGl6bheNyXUj778tp5YHJgbEbMHhHMxHleraP3mMuY8uR9Xq3x8ZOn3rn7293N9WGawTEQw3rVnZ+fxyZOw5TSoWlstdoeD/PTqw8lBU9rz2sQOtyN97e7+93usD9MU1pdXIwlpTSVMovkXPqUdS4QPDQRzs7WKnZ93b94DWoQOoAAoYEQ0LO15EFoHOTYF3Xx8sm7zVm37+9ev3oNU96e4/navvXB9ne+/rU/+O4f/fEf/ReksM6PdeacS4kDRoFg7oK7R932yer5za9U1Qw8eQ9Bk+apWEYUMkVRRbNTWCSUOUMWICDnCWuIOqABEDJglpJzaUIg70AtS5FcKvPXU0QBFTGxUhQVVGp8QhUD0cIWQUNeSqATh8LwrWZ+qYAeIrkqv/6hCPxKuq+ZkTOWolZKDZVD75mWAARVyyVVIpIWFBHkzPWjqlfw5FbKSm2ReJAk/9l/+Z/YZv6XP//rf/nJP//4W0/3004ZDeHR4yeb9bZxMc99f7wv84AE/TBCfRvvjDCL5izHIUHBJm7mobx4eX+2OnPmx0MOEM/jBc7u7ovD7Yv765/twYAUUdxSUwKoVkOKBVXUakqDsGQBkgFYDYuptcTbdfXffGCNzFbDOu1VIAUimuaEABTAEAzBGoAVnL8PTz88/wf/0d/95z/+v7ZXoTujl69ev/hi2L+G3XXUCcY7dHdQjglMoUGIBFEgwgdff6973F69c/Ht3/2mYs55iJ4j0QfvfHi+vvrh//mT/+q/+YfQw+GXAAaQANKbrYqAUI0MsQafKpAxKlWz7yqKELPValUki2RTQVJwYtGgRXEG53D2rfDRd99vL5rZRkXd3R2P92OAltQf7vomdJotpymVGQm32/Vq3U3D9PyzV5YBRoAEUAAByHMIAT0JaCrJksAEbEjApipFLVUyFLERGpER1GwgXDKpqjwNlACh9KVyZJaWCEgJABYuoQ8eEaXISTd3cnUiQsJ5TA/mWKef8KYhOrUR5DwYiSyaWWbC6tNcG7pqcIAEAKUoKGi1FtMTQn1Sg711L/3G6+jf6FGB5oeML/jNZMnf/HC0ImIiZmBUKqIIqNWReHHtMjADdszg9PTIovUTL6ejnkUDYDhFy8NCTTt90BqNCiecscp26plVUDRSEATUYgDK6CqcLyQISFSvSwMAJjrR4cDM1LSeaGZCohOVY3kel/ALWMLsDeacPBkhmRYVQa0youVzahUBW42ZIk0qKOAAGB2RISoo1lQ9YjNEYq2CY2LnPTOhQSlFipxmEcsFdPv63vvGhMG4QrxW0MwwEANpEgAoGeZpBp+5sKAwoaqNw7Db3yMBGViBNMiEc4iVPWBMzI68803TzNOoMksuoMqOSi6vb66JoGvYLjZbKIpy/mh9cXnuGRhlOvQkQqX4EC7XV5Lsxd3L2afz959cPXl3vb78v//iL3/600/+9M9/eBzg/KOOA+52w1xyjNGTczHkUVSEkBy4YipTmYuqFSIDK+wcuprXKY7RkXMutl3jgzPNjBSjS6mkOYmIb4g9EqNDJg/FtEb1KZIHZwTJlFeR1/H9dze7efif/vH//PLmxXe++c3f/uC3iGk/HPo0oHevr2/RCTN2zebZ0/du715PfR+if+/ZB4fjcXd3MKPQNisfz9vNebOec+nvD31/1GnWNJdcrOToyDNF74sZgUXnmq5l1/T9eNiPwwAm0B96XdnW1puz9cer93/4489IQATMjCuAAZzmkrMCgW8oRt+27TDv+lcTFEWAd97dXl6s1ls/TLcpH4sMBhlJmRwAiYIZkGMmH4JHZVRpowdz83ichjE4IiQgBqvIsfNNjNgVEToehmGex0w2eHbgQVw2pZIzWtUKUwyw7rpepjzlkgGdtm0X4krAFylHLWi5FCg5j9MxNCG8A5xLNgBVyeI8EVay5JIy82t74WkNeutJhLfJ34tLu51w/Qe4qt40WPV8ikgPoFQdxz28xJvaBb+yGRtY3bvfPppKnX1DfYGFxwmVyUIL18ng4RAWLykFVLA5TwW0qg9rvAiAqamALDgcwZJ3aqYggKiLS7salDpHqYIOI63qDqpVFi7HT56daVGpnK+KPuGytr4ZEuBpUPP2Q/Ht56zS+hf0anmPU3AhAjhQlXEazMRF4sBg5Vvf+WZswzgfUprYWcqppLJkUSAygmkpOXWu8TFG74GgbRAFgvPOZN3FLvp2FQkocDR0CA4fvncwVUk5a64CAIRqi284DMM0jc4FJKcCwzypGgIXERccARJX6GYRfgISOJxTCoOYABkwsWg6HtOTR+cxTE2YwCgEB2DEsNk2jB5RogclzqnME6iBo1TKyESlCAhM0zE0xoSA2VTSPI6sJU0E5hAI0LPzjrx3RGhI3gXvUprh+q6/v+v3+/44zut21bRrt1o/epfOnz6HX8HuevJrQOL1VZuGwoyOfJpT3x+AMT5qsqU6MqvCHwADqnkHAgjEdKJ7ny5yWrhXgKimaDW77GTpT4BkxFw9vVGyoqFDIBDNcxYAEFNQ+PLzL2ITRUGTQkEABMIQWZ0eDvnxGrp2RZzV5mblLx49ia1HZ8MwHvt02IsUP89miMEHdoTsclbirGZNu56mMk0TIrQNELIPjhkQLATeXd9JkZTH0DiA0pkzEFElYlfJeN4xB1EVyUXHKc2TZRMdJvjwA3d21q3XEdENw/FwuFcb23lmCsT8+MmjsU/Xen9zu4cCBOgcKtg4z7OmtglZkhUotWKsI2diAEFgxJoZ67suek/eoWrJJaoUQlx3riS7n4+lwDyJZGTyzvnd/kDaMHlQalz36Pzpe++9e39z/NmPPtkfdutH1PeK22UZQSBALaiKmY1q4ZtxUjMtRfbG5lKeRIuL7BgRqB9nYBindDzMm0339MmT437+8oujoAbiYZoUREpRLWBIqSGP5qQ6eWsWMAHBRayIIEXymPr7nhXFmavUVgU1QK2RMghGAARagBy4AjO9fH4d+WnbrrfdxZQHlbLb9dM8mImaiJRSillF/D03nkBjcG0skmFKBmVGgxiaNvhScuoVCbp1dES5pM2m9cEDWE5iVhgBwZs5FS0ZQUHNkYIWcOxXKwc2zikjEhiYFbPqs++6prVZmF0xybkAQ2CXxESqoIkErG0btbEgMIOBmiqCMTKQMDsyjIHXq9V60yEVK1lkKlnHlE1LSjJNOYSccxqnfk5pnicm9iT7fiQjcuDIKQo6AQBGKVbYqN34Mc8hswuhiICKCuQ5k6fNer2/26dpAjntOVrXcYe1gDVdtoEZEhRpoVk13kexwzTugRDY2HGzan10aZ5yTpNkQWVGJIqta2LDjovk68OdjQAOmotwdrVNZZrm6X6vRedxPhTNXRvX284hGhFoFjERKGIiiU0QyYfgKTJD21HTekKfogzT3NvUSyqi4IAb8GSmCa0wgWQYhoEdqRX0QAxtF0pJWcV5CBEMZE6jB2DmOkswgzrC9D627QrNO5xUOYaw7iKixRhFQDSplRBcbCIiM4f93dCEs9Y5sgY1lowOu20T0RQmW51fzA1OkS32g2TNo0MvBCJZs5gAeIgBAGC320/jgRkQxFTEhAiCj84FEVNR55iZED1g5dVlgxKD8xGJSkpJRU01RHAe02zBIYKMw2GeB8tapJ97K0N58vijx9tnkpsvPrvb3b6cR7x/tbu93R12Q5pnUasOYIDKjC4w4tqwrJuwaTvnnfQqRVpcPW7KMKV5OjqkEENk5x3Ow6GNqxh5TEUhi82iQJy356tI7mKLjTvElosMYuP5t0BegN5ny6KWAcAMpcxlYOitTRGBcPFUhBMboCaE1KZJxRYbc5EqkQJAVARGXNKFDAAkGxYtpjClzJYJnYGgQ0/MyJAXQOVkZvqmRnyoJ2ut9lDo/Gs6XDzNM9/MPh8qkbeLwuXv0bjqc2okWKU+6BsR04L3PHDhAaj6fGARjWDOO5mk6WzA0beyWoNanuaJAqw2Zz4AUgI2cBm4FJnTlIlc9cnJJVdOFxF1TWNCaZxfvzqQkORSZs2DgPAwzTDm410/3qWaZYrCoLiYblRtQzVwIFJTQIXFBGOh1RsYG8piF7uIg06V+0PlfBJDoC7CQ4UKf5lZyQIK7NERKZioqqCJaR9vXxyG++kbH3x91Ns0T5G7aRh2dwCZmT1YYmNiFBJD0Op0bTRNSXcy5v44710DRVIeJk/Q/d317Yvdy5evhz3EDACAUuEDNEOraj/A2g6Y1akLAJiiLQ6jbPUqFCAARhAEJUMEp0U1AzuTpHlnNmL3uGs7P8kwjz7HPB0mGaZS9L6/l6ygyp7X23az2cYY5nHyAQyxZKvKNFMERRFFBCAjQvNsScm4VvxYUcBaxNvCrj9lgZ+cxBfqk4Gh84iA1Tp4Kecr/5AIAKQILkkFeGL1LIwBAmTydvoabVGFmome6sdaahIYGbxhTi2vdlLsnXoHs6pFfzu1HX/9Lvr/9uHCOtb7mwAUtGhe7lmtoYnVB4Yegh5qLyFmoMZueRJPTZIhPiBWlREKiGY1jbg+u2gbQkVxERBQTODE1EBFEPTOM7FkQbeAi7WJqTdbLvmk8awmgpXroQq1JZSKa7GrUozFV0QREaiMxQgdEZiaKi1I9BteXDUVIUeAoEXVlDxgJEK0k/n6Ym2maCjs0BB8cE0TwSzlXFKx9GDVtZydMqbgOyYGrW0xljmRoWNvpqJGTEg0TqORBg2+a9j7bPl4GHUEt6IQSLJMs3kWYvasYgZVB6mFCYPnrJDmsT+SCUxzMtl/9OQjLdk1JpAV9WzdXGxaxzD1R0bomrZg4iwNeQju/WcfnW0fP372LoT2Zt//oz/537744uaXz5+rwWrtclJTbLlBw2lK3rdpngDReU8KZJjHKaMhG3oEEmJ2DpmgkoCa0LZtcI4N9LgvaISKgRE8JiUUlZxVpGihdUvC1SCbEZg9O4/AJjBigrXf5f6f/+zPX13ffPbii/nfnT589l7TBQ9uOOTjYWAHTfTrdbe6XGnKL4cRlM5W5yDw4vY6j3m7OfdtF0J7WB9u7u9KP+mUWhf3t7ucUsoTorJ3KiIqiOAcrVddLhRDjI1vYwcl3e7u23xcreP6LG7ONl//6Lw/pv39MBeBPKyauNr42FJ/mHNRRFXMYopa1KT1/PjqyTtPHm3PGh9kzndqg9pYEVQAj0AqOqc8jrNqoXFW0RDIEcbAjthEELlpV+QiB/QhNqs2tA0RlVJKEYf7OUuh7DwRo5acUsnTpAIoQua6BldtTAOBAgEEh13rXfRFfRuDzCGGHD0AKrGtN/Fv/e7Tz35yPYCoiqbivLO3rvB/xTDn/2Wpq/VKXX8UoRJQTvTtE4hTtXTLvvrrk+q6A58KD4QT8wuXl30DoehiWgjL+l4nSHVBeguAWyxGaoIqAnANjdBUsYDqiV0TawFVBOiEyZ26PxBQMjvBEZXgqQsDypDr0NyQ1IiUjLCWiEBCbKygWmyBvwmQEd848f2bnd031Yid1uY3YjRb5JlmmgEBCFUNZvit3/lu0dubu/0w7dHj+faycXGaRs2FGNmAETxhE4IP7JnUZN35gK0JBqbNqm2ahp0rYjE0pTCqI4yO5xBcUY2NXxVMBHPKCJW1TyAwz7ko+JBiiIiOgMZxBoMQQttFRjKzORUFsTo/JGKmaS7YQ2XgNhyHNM+pX603TSTtYkqSS+r7woFCw01wJvPFtjXjsc87mZOc2NKmCysPM1P23mnEkiDnsT/OkkoalSN0sXFtByZtQwQyjgWR2rZtm7bt4uvrHSKJ8OubvdnzDz/41gcff/S3/1CPZffJj7/UAiI25UnECF3KqUj2nl3wPjgp6XShLGmSJzWTAoJ3DqnSwes1akCAZkZqrIYmKLB0GFid3wmBHACjiIgZEDjngUwsGyg7JnAll2nKUkQL5akAcWwaJAPIhgpHuHp09uzZBfsypb7btGfnF8Z67A+7/dj3uT+ISCniADgEJgZDHOc5q4HBarNxoeQMhonJETpVkDznbCbUTwMUgAITZdHiuWXvi7BoYs/eOyJCdM4RM6kaMpp4KSlrKlJsiVFHNST0U87psEf0XbParNumi92ma/2qFLnf389zMoR1227W66EcFJxgAVv8BYgYgEoqJZceZ1VhBseM6OrQPsYG1Gp07DSlNM1mhOZFUIqiKKmfp5ynFFfNe88+eHT1ZDymn/7wp198/mIek/cuoJtLghrUzioGJoURk5jMmYiKZTXJaR7HhEKAwgixdYv8BriO/dJcgGi9accpAQpwCaE5HqYmRig2DQkQCmVPxAHJs6nNUwZVNXCOouPovGc3T+n+ZsICaGAFqMoXjECXUnVZAUtBBkQaeh0+v9nE1bOPrs42l7rTJNN+f5zngQiQK3VdxRQgqVFBDc6JiEdhNFruVwrBdV2QQmXqTSBEZGRA5vptLyNoSgnSXPKsabZ5MAOTjEAyzwUBvQ8h1qKgImepjia959i4Meem6cwk5bnqiY6H/rDvtxctO19kZsfNKooqeQKQ2g945x2HENo0z1JQM4N4LZBSylnnZCkVKVoBHSkyz1PwQ8lzKplzb6TTvA++IQZiNTRiMzIfnAvmG76I5+Pr10wEaCVnLaDFpilHbrqu/cXP/1ons6JQxepmpgSKdvIzXLyszWDW8TAQcdO127PterN+cf05yGIkJCqGJrV09YABsQ5wohqbQ3i8vkAjJcBgHEmlZEmcTEEQODoipJJTrXER0DNgi1KgKBQRQmNy9bRPgxKYc4CAnlwMTsUcCBE1XfDech4Jc9tSIk2puMXYjgAUychZw67rQtME50ktl5KpWvlVfT6SczGGdrPeOCplxnkWRHe4L0SWZt3vR7VkmF0AKdA23eXZ1T/9J3+JGKEwW0EdGdA75xyCapnzsA1jnkV4Ex+ddxGUU9L98dhP/VT6ZH0Ibr1uV6t2nKf73V3OYwh+1TXsSApU78U0W0kaojQtOY+qMk2pyBSi27ar2KgZpHlSdgDQNJGdm/s5xsDsTA2kNE0T+Skpn23P33v34+ef3o2H6fO/uv3VL18fD+V4Nx0PxzwDAAAzyB4AgZEih0jEQIQpWLrPzcptNuerGLsWvEyMI85NTvM8FgQDj8F1bdOI11mERFPp86FPMkXXrpqwaj1jAhNFASrf/92nPxtur+9GQhQ2Q2JGIIQi07SMFkoujtmxY3VCwmRKYEagWifrtMiOyACRjIiReBEFLswnADPmavlnRYE5Lyn0jI6dZT119yeOw7IvEwKiUu3PzPRBkVPLv6oQ+vWysFaAbz1ggcC+qj80ADViACSj5WCq8WoVHlYBoSqY8Slj+/QCjEgI2VBLtSjanLnDsVca2UOW2TE1XbtaN8iaZABDLVlkTiUdj7rZ1Gx7lZJTycAu+DZ6J8DDPN/dwtPLiIXyIJS9Fez7cb7N96+Ow10CAVXDZTRpUO1H60HUSakYUA1erFbtWkkdigACigv7Y0EDmd4MRfFNyQhmWE1yHmCSr5TmAIZUvPQwWN7f6/O/fvWt77+zjd1u3DxwxeUAACAASURBVGlpjofrMcHaM3NwXhDMeeeYBSWdnM/6vh8N5Tje9q+adcxz2V0n38LX3vmsvx2uP9vLHoAYRUgIlUBQFcBoIcgYgBoaVvhFzQwKIhiRLJU+K5rRAjIRKBqDEGSCAHKYZWflkJ0QkRtyJlLnqKRpHFMXtjImTWpFEIHr9QHASDEEBTBKRmgEqqCq9Z2RgZjIYYECi+dvLViouqFg7Wds+YGLegtOrQ4AgGNeava3LnKtabIAS1n3xqq7anMNEVWByb/VlyEbWE3RrIqQ5Q+ZnYaiUL/NUyr2mxYDzcBUv/rd//8LvQIAx2HZPRZYSr4CbzMRO0dEZqqqC4+zsigRmE+41Omuxof7YnGRfHO1n7xhoP4vIdPJ9H5hYhDUyp0AHbjq/6JVTUNIBopU+5dSEr6hJFT00XIuvHyLatV9eAELDWss/Vso88J7qBt9pT8QniRNC5BqolWWUa8WAuRAhqgiWll12cBpNWRAMCZSrXpXWWj5BGCAhmaGDDXdGEyqNNxKMqSqsAUE8ADOcimSrd3EdhXNYRlzGicAcMSOnRUrJiZkWnVHYqZpnmcHBBq9d7QqpVzf3OXZEMs6ru/vbvtjDw6aVfTBRWbLOY0Zc1n79ny1PuZ96mdX3GZz8eGzy3ZzMQn89K8+/4sf/+xPfvAXASE0azYdJffHsWubtm3HYZr75NZBciGq/lWKiCXNhkAMaAjRzMQsmRIzhsAxMBPUT+7QgqPGOykFABQF1DSLERYVhi0R1UsA1JAIAwNRnnPS1J03kCUdjz95+aMvdj/aDy//zu//wW9/+7ttF6Fo0AZAS7I8ieewajcX21Qk5VliaDbtlowChdC2MTS3q7P5OHpFJ8jkxn7KZWampuli41SLgqxX7ePHF48ev3N9vW+aNXPrgru7u3t1W0rRYTrsj0EgP3nn0TSmbrW7v9/nbEbG0VzLRpRmTQnYldiSD+g9Prl88uTxs/PNhihnGYAmg9kkqakqqwoiplQO+2l/TFmACQBh1QBaoU3XxDa4VXCu4vIhxK7r2lXHztUgXMcuhEBmnY9NjJvVysyGNOWcTEGLmpTYRIdYHf19wKZtfUDAYkDrronEUKBhbgMHBzHgt7/z9etf7l/DiABALGIG8sCLVKx359t64ro//sYx2WlEAEb4Ftvo12ipb6/sbynmHn4ug4hqYvzmTevUYRnVPcBSD4vPw+vC4sa5KKOXVUvVTBUQTa3m6CAUEDSqZCRXZyqMCIgMAgIqpyNd+E0AYPTGQPHENK0IlylZpfsamqEBneSRi4komcnDiSBiQ7MTGRYeWGoPeBaePhd+5bM9kLYQlqW1YvinEgU9e0QomudZQODy6uL1zc00TzlPjO7x1eNc9DiXNErTubaBbbferLuuadiTiahKF4P7f5h7kx7JkiRN7BMRVX2Lmbl7eERkZGZVZu3LdDcb0wBBgMCABMELAd74x3jmgT+CAHnhaUCAbLA5mF7YPV1d1ZWVlZVVmRmLr2ZvUVUR4UGfRUR19YADHoh5p1jMzW15qiryybc4laVIJ10MFxc7czw8zDF0tbgpwTmFPsaUvA77PkRaZ1tPd6YmQu0wDdwswABWc4QUtRaYgRAThyC1VF8LixEzXKq6u+fFs0BEUD0GkkpCmKaHZa1VSVWXuZBZ7GVAjOxTXfZjJI6RCV5U3aqDnciVoIan18P+ohOWwGXl6la1wCpMwcBh7PvUaS0pQi2XjKEPXbe7unpy9eTyF7/4ed8Pp8f55cvHX39xV3T8yY8ufvSffO+Uj4eL3Z//639ksSjwQjlnN3QphBgIlOtK4W1CpRPB3FtMgLs3f0AQ2td/1nbBHc5uZGjxaNCGE6AduORELkwt9JiFQyQnNwMLD2MvIuu6MLyqNlph6voUO6tlXiYEIOI7n764vt5N6/3dwzReROe4lvn2brm/X2qBIxqksV+YN6PemkspFkLo+wRQP0RhiEQizks9rfM8e81gJyMgeAyIQVKXQoStuhbLVdelgimEHBIxwaq5ewgszKoIktzjNFevPp8sxoPUecqLo1a1Wo0QAds92buDxJbTbPBx1427pKcAcndl9iBJOBDIzPOqORczX/MiTLms/SBDH/s+7fZDF5OpmnutVqsSOgJq8XnJ7jV1aX6Yu9R9cP3iw+cfrfP6i3/45c//+lfdPrnyvNb95WFdMwLA4Oa0KWrqRVV5I7DXFn6uRs7CRpFjCExsxk+fXeWqRec1r7mUEMg8OwoLwEqs/S5Z8YXm1EdJTJGkJxPLa3X1TVkNTyH0qR/SUNiwICWpUFGGCxPDeZs8bnehGeDFhJlB9eRvXj1cPr06PH2yLAscJc+MYF7FN6KCqqkVn7h6ffr8UBZFXSNAHTOiesvH49j3fnVYl7lqyaWUUmMi88oSUkqAT9Pj8XHt4rrMnmcozMxCqHY8Adz3o5mKtP3ctNbzOAEs1U1jlBBTZ0F9Xev6eFMPu/t+Jyl108Nj0RKiOMNMVbVk10qEICRd2K3HcjxOtuo6FbdadAG5uapCte2+YLacV7UiwWMES2EWAEarE2nbocVJQImdKthCYgS0G8/MStW6utWtKVkfMqyJYoiMYYASrBGwGOQMAYEDG2xZ53pvzvT0+dOrp5fodV3n6TTNecICipCBrTqoERoBRuAldSGN6XAxptTltTw8HB/uH+OOWTjEGGIH9IBVXddpiik43NREOPapFl1zqQ6rrqqq2dSi1Nkq8UIIMab9OCQJa1xZzo7KlPsBcTfktT4+rswYxhiCVCspiSN0Y7y8PPR9yHmZ5rzMpVnRptSHEGJMUeK424WQtObHx+n+bnaTh2nuE4YBHOCEww59z7XswvXYx8svfp2T5DydJbFlO3wTIIS/u/kaOzy92F9eXY0HCYHdESUcdrs991X2Ien+sutHmZZlKeV0xGFfLi8P465/cmUsvCx5nuZpQtcv7qnvk3mptlZFSkgpdAm51JyLiRO4S6lLCdVSjETksBTj06fXh/4yWJd4rMf0r//X/+P+hu5v7HgLzYAFWMdtmlFcpDMzU3NDWQ1sBj3WGW7dfvzWp3282ocYD8PY9bVb4pvTq2VZAGMKz64u+yRV1XnIRKdVHx4flgUYPSgW7oKUtSPmtJT8o598/zc/m4s8dF03DN3pNDknhAiqaL7GLAbEGMfYs4aiOTOskUuMtbkzGjExUCUIQ1pB441C79YsZViYhSmoqbehS6vtzFS9kDehjDve9fbvMqDf8a6aics7c9V/Pw3rn170Hnvr/E/YfB22PPrmeeNtDHoOv24wloBos3IgNBo0sxCh5LULiufoep9f3y75wRyq5er6arzcOZtaUVevRjAWi1G6zkSChABy1cZ/dgKsqBX36mPE5X5fZxBZTGNe6/Fuevj6ON8oG5k2jUErBx3C27S13fSNjW/ObERO5LxJvxztDWyTzffBqub6ev6EgY2N65sWs3F5hKlNK2qBO1FIAR1WqnUC7O//8lf7q/Sn/9lPxv3V8fjZ6xvsOjAjLysFqFcmJib42VocXnJJUYLEIfakfn+aLobwrRcf/+xvfjndzqdvyo56VuK6sAoqNxN02LnYtTaZbbAFOZnDlQFq+kkAVtmgzlsz0ixNoipZdij7iul2KveTSXmYbsuqbtRcbbsu1cmrmKoCbO41FzJ1R4zR3DMKEbcb2DdDW+JNCSaMSu8TFbElxgGOjWPfQNjNX/98N2/l++ZM1mRhCsXm+u7+NpJ9o91sP2fn8Sdtf+K3ipIGZhJhczVpYGWDlP3cXm2//S0XDP72aoPe/+Bl9v/vFRTqdOaCmpq/TfCmRupvFhulVNPa3t7b1NK3rIt3wuK2vsmBbYz0zonlvcvgbLyttLZGms6WiBxQapYxbd04Gxmbb/7L2CJR9S3BDq3xrAp2Fm4IGnFjxOFsF0PUmloWFqENw6cz+QJvG8MtvVxtA6EZXs0I6t51O6eCJgo2c4NXQwZFqFUt1c1cbUszo3Zzbi2jec3ryc2RDBlkxh0LE6FSaCpKU7jBQ8Bu1w9DV6C8btQ4rVa8uoIJwilKiElqmZjYVE2VmYZxYKLpeHx8fFwmXB74+vry619/VWsddrthjCHEGEIgLmrBQpJAi/tiERFZo8vTpx9MxT779Rf/+1/8m7/6y88RUQ3uGeYEhqOuOtu0LBkMZhbmtRaGSWCQO3ML1TJ1GGqu0BqjCIcoHbPnZTYtfrYidysCH1LsYgSTExk8W/WqBCSJRFxqUbW1ZlAhgkSki76cZmgIDg/x1y8/T38PpPxHP/nJJ9ffehVu8rKaZqs4PU7wcH31rNS8rFPXDVcHmvNixXpKKcWnu8O8m/bdMB1P05LNq5uFGId+6Hpxt2Al9v319ZOn10++/vpmY684hS6qI3WA+FqmsNKSp27on6er1PObm9vTlOeahWEVxbEaFkXv+YPrw9XV7vmTD3bjjl3zesrlyKm4L47V3NVS845c1jKvJRcwIwT0vUQRM4fzbtyPQwezkstaihEqbKmFtEJNVYV4Pwye0hhSn7qryysiiPDqOJRaCKkPFxd9qSu59Z3EFLuhq8BS5uqWIvcylGVB9WU9naaHx4fhxbMnMQoRwNT1Xa6nDRd6r8L4ffSKzqvz33OdNYRt4f3TB7YBwVt3wLcDgDMOve3Ifzh8O1c/eI8UxkS2YVvbpu+Ak7s5W1ul4Ea93gBuM2y2oL4BAeLn1MKNeg6ASYJou93bkg/n3+egRtQ1sNDZkQHO5AJn9y2OwngrI6idxsTUXKjRQImNAw63dy7z70FZ7z7M974IB9k2MGzgOLZ8O4IzkYEIFGN0spKrE3CNWlZmSGBi5HyKeJrXPJ3WvOKwD7uL/snV5TB0MTIYS8l1XQkkYAX1XTSrQk5OcGdirXVdSlmLKalWrdmhElMoDFevrsbOGpP0vVBkCVLd8qrm2zxQLasGEWLxEFvCo2gl2mzXHIYooZYibCCPHZuXUhdzEZYQAEWKSFED12UtVxf7qiTkbmEtuQ0YiFArPODZ833qAgzwIBCrRgbpMST0EZ0EAamakrJgvzvAA6gzpelUX766nY439w+6rDYOU9d9/vA4/eAHn/7oj7736Xc++fO//ke7w7oA6pxwMRxcLS+rqlJoA+vtftwo3o38T8QMpzaXto1rTNiY0jC4U2zfbbsb1M8ljloNgUMQNWOGozqZOZgQk0gIRalOhUm6II4QRMqS87J4QD/i8ALPn16SrOv9g3k6Hdc1L7ks0zEvM9wgIQmkGQ009IVEiLgULaXWBjFCQ5TAsumpKTryTJhXRwQYMQLQkteqNC/r3f1pXlwdIMSAmMABiZFCHMchxa7rlg8++FhYTkd9uHu8fT2XLNNqi7sEAHa3PNRiQvJw99D3/bOn1/0nz0qp08Pj4+kudZ2TE4N7CZIIWJZ1Xda6ZrPqRvNShUFczIPVrFpTiimEUmqfdtBspZRspeS8WinmTvB6nPOPvv/j73z7O2Wpv/yHX335m99C4ZUi90y2ngqCUDUKzXYcKKoMK00CAZdNBdD+18Srr2w1SGJOh6vDm5v74+M0nmQp88WTEDqqvHDAWhciogByj32KY6BoHoxjcEZd3E0bp91VDcQsSVKSDCBKUs3CESCYNIlq8xGhpjAnqAIKicG4PN5Or7++6S8+2O0uQpTbu9olytqSmwJLZKCqqVrOpYs9WySFACzBLZqaWl2XtetS3/cEm6dpza4VqhXNiEECM5ljmesy11LElYpac1HOWly9qplpioGFxOAOCWBBSCbBDLnkzJKIqaz1dKpacH//uD92wy5V1ZxriByEqnGtBcQhBKEklMi4ZDs9LPPjOp0yM4G0GxNzB9Na5lrdDEwWpMQo+4ueRJmFEdEvIbnBrQAKZ3SJ48AkIFY1HXtwAjHFJFqqGmJCiHI6nVDfnpUt856ocQVaX0NMDAExCQSGUF2XdZnXua8d94FFqmqzyvKA/pBijPfHRytAxOXFcH19ORwixBzkVMktdOBsfb8LMTAJgWut0zTVMhNnoc6ZrFZzMDs1v46AamZFmzGGSKy11KJEGQO6PrDAUWwLfbcQtOuGoRtyVhYD0TgOEmSZ6eJqVCuxC10nxL7meZ7nZVEzEJVaLYaYYk+OkktZj3f3Dw/3p5u7agWowNB2MHAAgUIYum4XqEeNAAbphjG6w4rmWnMuVMCh77vdKo+Y7Xaa7l/NlCR0IcQw7PqrZ5fPPnjeXQhF7Ud+nG7e3N/2u5Rr7YdxdxjHcRiGXSnl/v4xr0spLak4l2IingJCRNchBpEAL1BVAgVpZQJKKWbGxCmErkt9331w/a2r9PHn//jVZ5/95rNf+HzntEIzQF2SnkVcaynZS6ZdD2upT+7kIG3kIwjWKX/5yy9vd/cXl5fPP3qedpw0wCxr2cfu+fUlLJtFwHe7/sluf3OalnxcJnOty7Q+1Nr3pez605Q//+LL/dWFdNIonKnr8FDNBNDWCIlwFBlS6tOQQu/u6sxg37jAJM1BgjeplIgISfOzV63WYmjdiRFjJCIREUHzhDFTrdUdihI1uMHMzk30uXDbqNLvUVbwDr5p1eP7P4BztfjuAe8NOP9QJWBWm1PqpiVs8v0zTkAb29e3UupcaxG3qatJitX5Yh9+8pOFqE7zXdb7fsAwxP3FTrpwnI65ziQWSZvFauoik6xrpY2V4+TQbFaXmsmyBJLry7GPXS4e+0RznOa76W6e7xQrUhcXys3OiBgteM/JnawRyRqC1bIFhZzhgNJ5/tkyyt/WG43k5n9YfiOci8ozBcU9xGia1bYQoSCBMfaQYshy/8Uv7oarn//0T/54f/G0i29guLp8ojnM82l3Mdx/daQqXkzfTqPNySWl1I3x+bOnd493fTj9ix/88Scvvv0//0//i5+w3uH5/lmZC1dnYze0SS6/lc1t94QBcHJjbxwnYwOaMxiMdAO62GFGLkTiRjUrDFxx//Jm+uhSel3Wo9dgyl7NFFX1dJrIHEwiwR01Z1MqJROf8YMmtNicfH2bNTpLY5M25NPcnXgb2aMxnZv/yEYUfMu9OqsCzdyxBce1h7VyfxOXcGsNthZHW8T5uRFTs7PVlfM7RsA588fPopR38pat16CzeAU4g2fn3/7eVPw/uisUL2d2g4PB5kTbWCtIaBmvtdr7Dlt4S2d620ye/6M9zdZ64vf60nf4LjkRlbXwJmFtsTZq7kQkzA5ks0Z80qherXnBtyRyotL3qZXIbxvJZkATYmj37Tl1opX5dmYrOBGzRGrcSjuHuDTQX8+eA2agtrpAQgKYuVXzCu2rqpluCYdQdQcKiOFFi09EHFgoJEFdtZKD3ZkY5JKgehrTcHh6mU9LPs2R4lmLx0mQMzh6HDDuw34/MGNdC+D73f54OpZFi2uKYTceDoeLfoTLCR6IN6fqlGLXRWG2WrvuFNiun15/8MGLv/3L33aRzae1HInxwbPr7sVHTw5PglFS1lMJNTy/+uD7n3w/xPHu9f3/9n/9m//zr/7+59/cyRie71+oUz5lyxpZrq6u5rvj8fZkhP1+V1VZeAj9WtatHEwSAht0zkvqqZiZggL61O2HMQaaXacl15prxqp5PmaqiILUicRgjFxtraUPHROlGJiDF1/zvGqt8JRiZKpcH8pD6Oj6yfN919uy/M0v/+KLr3/+i8//xQ+/+6N/9Uf/9YM9CPcx8sPdq2U6HQ7Dk8vLpQxLXZe1pNCTQXOJXff04mmMwzyVvOSHr3+X3aqBKHd9DiGN+3HfHVLX1Vq//vrrf/fv/rbvL8356smzH/30xx9+9GUcZJpPx+lWvXz+xddPLnfX19effPqtH/zwu9ioPa6qzByIQgjjONQ8lTK76t3dDUy7ROOuf5heq+U26W3bCTNzCDGFPRcWBIl93wlxYAQJzOzmVtXMcq1TXuvdrQMpxsN+P6QuprTf7agamfcxHcZdP6Y0xMP1dWa5P03z+jj0onklaB9lGPvUdQ9LqSUbLPDIgYU4l/JwvLvow6tSv/fij7s+hoBFa4o7VH+HL50lhH9YSfw+Yfuf2QLfKyncCO+IsXTeMvy93XPr8fHWiP2fPNvmQejb/sNn3Pr3X9jZgfA875PGe9peRIPU3c9hqK6Glja8JQuaOanWxt8EeYyigoZot52Imn3pBnMbxxRadjEB3LT8gG8/UOuG5fGmrGMWVhgLJUleAbeGdr19F2e86/xu/pn6A+eZ2/nkfPtxEQcJJetaVgnsZM+eHJ58mB4eHrqhu7o6fPW6e/PyaHS/FofWccDV5WUIvBsGFoabgFxtXSaCsBNI+25c81Ty6GCCutE659Pjen9XVaF4PWddna0EaKSYiJyK1wq4d30feyGhJecl55IBCALUsKxrSJRixJBm5FqbgEjhGPckO7+8uHh1b+5VBF2/W1Ztb7HrYwiBDOOO+xEwy8hXl8Pj4yLE15cfx5iYqeu6FphbLL9+/EqoVq+CPHQsXU/AEPsuBqjVvK711JBWCWHcjXml+/v54f7Nsixu3d394/0DouDk+NkvPv/Fr392c/fjP/uXf/a9b//wv/tv/4svf/nyi7/75ptvbofUNZoVRWaBoxq5sW9WtTBuhqvkEoSYVKuaN1POd+uN4AR1T528pUC+vbXZqGqVICEGUiF2FjYm1OoGh6mXdS5l9sMgMcR11eW4tmruw+dPPvr06oc/+VCkvrl51Xc8HMal1Nc39ylJ7Iew5Pvb2ncKBDPknN1UOsQQSKKVZVnn4/EUQhyGQYhgFELoh67vU0rHhzC/uH6WUi/CJJ6SkJC6DhiXJcNnYyJiERmGGDtOsd+N45PLq92uF/jdzcuS1zffnL755vbuDk/2FyqEKKWolrWsyBlR6vXlBZF9+dvPzW2/233w7Prb3/3BP372KwnE3A39KBwfH06n42meVihiAjOdC5xg5vO8Vq0pRZieTqfD/gpY59Pj6bjMC/oo+3FfsqcQLw+XP/3hT2up//Dzn//sH36BjDR2yOREUEJ1ViZxKUBDrh0gaNPfMeBOASEyRXGGo8wVudYxep/iaTrd3t2WaQl8CTIWJvGrJ/sp5NtXWQJVX4t6tQxVUpJqTtzWDjP6FLRaWdVI87zWnTV2DxvXWbthhDVnjrbrgeBE6qzNGEyLBebIsSz22WdfhgHf+eG3Lg77m5vXzNGLt9qcmQOSR2HmKIE1DjIOXEtZ5iVPJRs4BCl5WtI6pCgh7Pf7IZWS12GMIbC7lZLN/GIPOLuxcCQSFId6M+qCIecZFZFFkrhzTNL1KTQQIXb8NM1TXsosjJwLMfo9iq83NzcvuuchdLkUFjEoQckQmJlj4j5I9/rlzXRc6gIRIHI3DhzAxMykKKarqYrATc1lHLtnz67GXXIHTI7Xj2M3gGnNOZcqibtx4MhOTsGned5d7FIXrXiKO8u+cD7s98M43N6+QSPfByYjaJsHydYRuZOTMAmxmjpcIsfI5vr6zesvX//ux3/8vau0/87waUyhHUxa8+3dTdixo+7GXT8O49BN5fHh+Pp0KnDEkAQxDXFd51rzsixMyOv88LDWiotLjAP3fW/usxYmGveHGHvmWLOtc61ZiWyeXhO23BVXy/Mp51LLNk4WBsG6hJhcRJhHgLp+ICKgmNVa16qL+RIC11oA77qYUopR8lzzUpjJSn20qVY+HZeqte/gCaWErkvdwDEZ0dJe1e10P9/b/euKE6a1JknMbNU9ByosFkQH5L4HV9da1rqumHORTB0fH48vv3j5cwcu8OEP9j/66Xe++8PvfawvLp70v/vtb9ZliilOy+n50w9KVpEYY/f06UokZj4vj8MYx10k0hApJQHUzVUbHgxVm+dVS9VS+5i6cez70ap/9eWbv/rly7/5tz//6797zRm+sEhHnAhCldWLaXVTckJZyCq7kTgzlMC0MZJca55qvp8eHu5+/euf98/S93/6/e//4FsPy/Dw8OpXX7z84AoXh52IhC7txtFTVD0dxvsoV8ujl1wCXDNPp/rF/W9++OI/v3x2mfa3+Y096gN6ARNMIUDAOI4c0dcsJF4sL+u6Flf3Ynbm35+nc0jSpRCJpZZS1MpagLPwzmGowrIxp8hYYG7tHTG4lLJl0p8TlltLbxtE1colI3LIBku91Tb9swAW3gFe3LrXtzY47x+X6k7QLVv+/KMbPuWtvTyzUn6fhsLM85J3V7vJd598cv2v/svvgtZlPaZE3/3gIw79w7zcne6nZcmaU4fDIMJCxMyBEx0f7r3FCpETSKuXUsoKV+zSxX5Ij/enXvZ9HO7fTK+/eXW6dShAqNUJYcNQhFycglMjuoHdN/yC331+eIv0nPklG1kbOCuVfFNHvv1cCBGQVjsTKTlAZi7gxM3gwKoWrkZD2MGt4lhm/dv/+/b7f/733/vTbz+5ePHRs74fdifTcT98fPkhfbPWx7wU9VYjC0RoP+6uLq+4o8N4+Pp3Lz+6+OT59QfzQ1lugAn7tFM1yxy4YxcnM7Lm/QN38y0O8gxMOJr3Qivkm9WAA6yAOTXxIUHBRlqcjDlFnfXuN0Y/iYGQooCiroXEARyPE07qHYUUYD4fp3WdYhQhskqmqApp6Nk71OMM/JibM87zPVeYtV399xV474bteF9CaGdo7K3xEp93FaINCPa3XK23yrG3n4NDNgu4RiVqbr9twLCl4b2DPswdTi6g97Owtv5kqzvf0hT+47uCq75tQAEwN3RPCNyyRVVNtQLepsPvuGft8vfaJ2+jvO3Oeessu82TWmyqNZgseD6D6uaNKwtvYkwD3EwBdgYZKHLjSrScCCdQos2M7NzLbXJnZiIW1K3hoxaQ2lxubIPT2EFuBMAVrtRkNc1Ujnx73V4BIgQOdI4mN9d60hZKvqmN2vfKQGVnMmIOQk0aTY15agpysAmGXmrVYdePcXgkn5a5bZ41gIKhAwJoJ/o/igAAIABJREFUgIxIY6SA7Ll4BtXURc6gAlU4a9fHftdz0LWQWogswsmNidnNixYzG4ZedmEY+0LWP8XF4epw2AcR0+Xp04tnz5/sU/JcfappGHy1cbzq4pOL3YdfffHLx6M/3tL6iIur/vXXN4dhT9mm0yPMLi+vqjgPAarOmHVNEmOM7KTQwBQCxxgMXGrpIyNnJ6TIXdd1XeBmHiQMo7FnZqvFU59iCsMwxr5zYC251lpKEWZmBHEhNV3NxBhrLm6yrNk5pS6FfqAgrCbpsnq8uT9+8eXv6k9L4LAbegRljrni8XEZht3YjXnNHUsfQyTyok42DvuQhg+ePXzz8vXNzWN9vG+ngOaVD13s4/7igiUej/Px8c3D7ZqHu5jGl+vvasnZ527YBfYQPAS6vBhyqW9ubuD18mLvrvM8L9Mk7LtxOIyH2O2CVCSeVn39zZuy5nGIT6/3YxxycUdULeYgDoEZFDqnPq4qFGIqOZd5ka4TDgwpxcu6WFUJ4TTnXMu8zGq16weH4BB33RA7chTNZc0ORFDshz14vRoHgb6cb+ppHi9j3jil5AALgiSiXQyjKVIUhNVAbfqXolwc9l28XTRXLMHFATMjGImcwZHf3+j8/Q2bfs/AHWeu47ZzOP3BLvneNvJ2kPD7lKtz0WF+ptzSBl1Z46psbJ7NKq9tYk2Y3qBCModz04TDiSDM7uoOZyZmOlNsmd3k7XCQ2gyuTVsaa5jA5g63FsTeZCDYJujMsMbIcjgLC2BqdSvWzixuRjPz8oZwEYiJFYbGy+LzgXc+8d4DBM9olm8fWXsA07lcZDQYneDsYPcUw3xcLAYEuzhcfueTF9O09Dvqx24YegB1XWLoLvY98XBxcchlreaua4jkzBBTVC2l85hIApECljNJ6KOQr7VO65rXjFxBJ5lWc6CUzGbDwFDPU0aBsXlQCIGZgocgyEqhHTZurBCjBCFGhharur3B3WF48lxSJ32MZmvPkohFfGI4lLwGBkkgJlNTraZ1muec55Jxd/cIaNelceyHoWchRw1e61LzWq2UKNynxERDirt+qLms86KqYz8MXZLEpnVZ8vH4+Hg8rUs9XD69uvQUdV50muy4zuOIl6/v/v5nPz/eLT/5kx9897uf/tXubx//4vb0sOK0pij9MEBpyYWjq2WgxSQH39h71oBacHA9x26275jfLRPiJnmgVqY251oLDiVlY3YHFN41eqzAyWp1VLeCjkMMqRSty6qL4RL7fffJJx9870cvPv7Wxc3j56fl1UdPPt4dZC6ToJLHPo59tCNN61KE2dy1mrlHDIF7d0aluqJW7xLtd5275ryCjVOi4FI8JJg/klQXLrUuBaVWdTfH8TTn0ibqylGBbABbyey5i11gCvE3X7y0yo835e4NMEG7wBLhk9a6qlm1wCSMh8eHdjQzI5d8nI50R+4wc2GKUYKIBBAbJSSmvkuxk97IzJ1UzVWhqtO0wLDM+bAjLbZOOi8IlFLXRQ5U8/XF5Ucffdyn7ldffPX6qxus4MxbOk0mL56GtKwLhySBwGS1mIM3ayjjQO7EhiiJvVdjq1Tzom7Vhft493Bb1lMaQrqQ0NPtw30u824vQjGf8ql4sVy5OqHkCkLfCYHEaYypikVJQCmrVsVc1tM8ZVdJXKrBSA3cvDypOcu0cpXYg5lGCepaikkKRqZHPL5a/Du82x8Cp5KzqdXiItqhOTAEkRTDsE4e5GLs4+PDm9PDcV4RE0lPaqprlr3tpNvtBhq7deWUhMRVSynZHV0XrUageZB3y1za7BwNZrPYuPtu1LgeqePUcQgUE8b9/ubNfS4FaERtGwYBe7YMIWJh6V27Nc9FoSuZgtmcVcXu7x9KVjXERCGFbkgSuVpxODFiiiTG7CQIkTjacBCEUEv16sNF2O/HEFOpJZdarAKoVtRUS1nrOnYJDOIgFGNMoDz0Q9fFu9f3CBAnUvbKaAlUDuKz5SERNpmJqlVTSGQ41aKo+ovf/PLq4uKDDz94fvm06yLYvnn1uNrE0fpdf7Hvi+XH9XSc57kUj9j3+7HroZxz/eq3N0EgFMhZ1coCd+QVjDB2O5HUlaJmulhdV6Dk1dZlzbnCnCExpiASUpAgqoVQiDD0MUakXua1GtbaAhIFzBKCOzxEubu/U60kUO/G3ZC6McgI42Ho3PX4+JjXaYOSDc0vtEvSBSZOffcBB0nJJWbHHGPr2I2DqNZnH4x5ha6kC2phqkjSFBhqtS7HLCEGDMZBfUbJ7oYOoWePtns6mPFvf/fq9d0txfzjH32XPB6G66GPPtR//MefAWIKM8ClncJdN+zGcRjS/tCv60mETVdWDkhCgSFuCjYHYghdP/Tdxb5/ZllON/LqN9Ptl4ZXQJf8RDUmIXFH0QVQIQ8hECUzE4/uRq13ouZt4LU4gocuEHFwUenzkn/769/GHaHXkML1Fc8ld5pTTIS8lJMwX12Oug9ee7ZyeqhAinI5ds9iwkcfvfj2py9e/mr64uEle8cJTq5ACOGw2w+xj8wrFlNb6lJzsVpModW9NueZzV3bTA9PrkQYROaGSFtgXAPdGCABizfnUNM2D6Tm/gkurtzsafxcGW51mp977sZB+H0IYCsz/wDAevsEBII7AwQzezfyPJerfjZWYCY4rDGW3N23bCK4o7F42HlzNXJ4cIfWE4uEoIfL+KM/+rTqq9jz2NGT667W9NU3N4/LUhqUERHTMPQ7sVSdLHsfH1vuhQmx1dmyOcqKwMwh+eLTw/14OKDi9DCf7h2ZSIDqda0hRABO7mIUQMEdzdnRYd68v52IHeakBjTJ48b4wZky1PQBDAa17hjNhK4Zeyi8tcUA3OBnix2nVkQ6CNV0tRDhVRTBkG/x2d983e36H/3LH6a+Fr3PWkM4MIVxdznXYxE4amXjnjBQf9mnQ+TE07rOunx7tz8+Tl9/9gorYEip11xrVZCbOLwljjT6nbtV37gr2xdKjZPcNk93gIwc0EZpcWpEKNIG2iiYROcMg9TYMfeI5mGuOQq6yFozAiQKs7jaMmV3pC50+yiIDTczA+Fdd7KV37Y5f2+DcNv+3IpaOLFxezPwsxFvMxw5E+Hev02dwN70tWgNAhMRs73zFScC2wadNUMkP5u+gcEGa+F0tPnbExNbQ0GM3ZSayIOACpZzz2Bgl7cULLxt1/5w+b1XnP5/u9pL/ycEiPYW/hlKxO9fQh82GGizqGfanPVAZO5aq2pRVVP3Fh0PAG5Wq5oEanN+aw5qbs3xf4unN6Ntw2n7Q6BN8I/g0SYjExjBYNW9KCnByYu6giANRBNmYQkQMriCmYMQHKZbTMTZZAybJlmEmCDcXGYkBIncBkMgFpFtIVNLf4WRGcw2A2ZC8y9spQMxR5EQhEWIhUjXirMxytZ7EjFz61QlBIgoASFaYBfxIGBxYUQxWuDUdUlSWGstqpRC3HXpKmky2YewYx457jDs02pl1cVQq5fUh65PaYghUYwyjJ1EySVP81SLxhgvDvtaMsyslul0XJY5pjjuxhDDXLTEPh12u8tD6jut1UuFVgHKenLV509eWJXd8PzDD3+Q5Nl//z/8j1//7vTy5WOuuQtdPa0657pkryZMNRBEiuWYOkqM4IpKgVgIrg5jghBFiUOfEDwIpRBSil2KUYKZ1ZrdTGs+7AZmlkBhGFwixRi7Zj2KKAIYw4UoMMgrtDayrKp1MaXUj7td3w191xNEs7mSKda53r65vb64HlJ/eXEx53ld1i52y7LmNQMOq8+vnwwpalmrWq4mqXMWBQvFq4urfRwvdvuLw/7q6urDb38cx9Tv98taX379+tWrG6jXUoduYMbd3UtmD9HBNdd1muf97sky1dN8cjdmK/k0z3fLPBPWKE5kfRcAfzhOr25uvn71ZlnXmCABay55Le5Bjd1ijEPqOiJxpbxWYXpydRmYYoj7Xd93cRxGZrm/P97c3q/ZXt++UXeSQBQAcYgaCUdGCBJ3wyGvdthdhC4NY7cs8/Prq0g+3d/UMj29umqVMkicm4qhE76MoS9rZjIgd5Eud+OTi6vL8dnyqHff5JubKXJ0NXK3djxyYNoWQ9t6WARMGw/yPMc5s5PYaaMpgdt+Q8y/D3a9JQ0BaKjUeQNtoYf+NhlmI2BSM3YEbwZVbTLXnvx8TPiZG/pW+WxQsAdmUYMaODALGxyMkAILEYOFJVAQEiCAW+JJG66oaQiRQ2j9HzEFphAkpcAMh5/rd1f3Zj/JzDF0Eom45bsAci7yWs4xb8RuJgbJ5nn0lnu1IfXvpoXb/rphdbQ9qH26wiLb+S5BiDgQ2IiA0HVeOYgo1+98+umf/OmPL590p+Wm2oNhga992l1dXO33426/218cjtNxWddpmUEotbBgLWspmQ1DiClKn6JbZUIMUTje3N2/fHl6mIoaiA7z0ayKVcpr3h1C6NxZJWE4IO3YvKm/hZyOtzokChES0e0kDgImJV9LKWpkRIgI/OKj/Q9//NHFRQ/UmqfErnm63A0MC02ITpAo7YRy99R1p3ki9mXNaioBHLLTrD6DVw6ap5rnWXMNRIlBpuyUhIMQE7Rqn9J+P+72IxOdTsf7+/uS12HcPX/+4bIWU8kZZXU1cpNazCtKLbf3Ny8+fHZ1vQudfvziw0Pfv3y4KeoAVRUHg11NSUKI0UFOxBzcqZozB4myRQPwmRguIAEEIIhstL1WOAkLhCopBzgju2q7LYkhNPZD3w1mtq5ZqyYRoXB8nJXscOj/0z/7l9/7/rc/+d7Tpy/G0/Kaw1zq8XA57i7YfLHq8zGvkzP1fTecjtOWjkjMnIJ05LGsenycpmMhwm4Mu30KiZwqiXd9lMiASUCQnDoFr4aZxcGNNVlVXQ21woxCkr5D10HE3Ku1/r367357U2ZeZ6uT+YrqQps/S+cK1SpCbk5MEjglEYGTqtZS8rpqrWpufLYLkYBxSE+uD4fLXd/HYey6Prb1KMIpytD3u3G82F/UordvHl++ntxxdb0Lkpbp9HR/+em3vvXRRx//8h8++8XPPvvm5SsqLRRWxIlBnQiDtYIpCAU3UnXfBmVsagIGiArIhTTYQppBLq7iRkRUkEOP73zvxeWHw7gPn3/xD6pG0HFMsadq1dmkYxd3BQjdIcQUGTR0scyWUmfwqhUMIiq1gkFKp9PchoqmpjA/x1C4bTP9WtH1yR21Vo5CAWamXIXD5eWe2Y+nOzOeFw3Rx3EgjmZEFGPsS0bXHQL306ne3055cSGwoxYj94tDFyP6PsYIs+ykIUC11FoAmqYFCIzAFEBynGY3AzFDSIK3wHhmwKsVDjbuQtcTByXR4XKgjkIXpWOK4EixCxRxuNg9f/Hs/v64LLZMtkxZMzRzmT1PKNlL9qY/hCN0PuxDP0rshISqFwkUEiR633cx8eFiGA9dTFxtzXUGmcRud3lIuyRJQidF85xP1aqThUTDQBK06yKM51Mh0Glarw+XKaX7m4ecVYgJDLR5CzGIXZmMyAB1qKGAdPuOyCj4MPbj5bDoauYGNWjR8vSDq5u7l6fpWHWmoOMuFj05WzZN/W63P3QpoWI55ePjUtZKhpptmbRmg8hhjM+u98+ur6+uniTu9/2+k54qPOt6XOq8WC5eiy31evhwCIc+7pJ07BwkpBhj4v1FlGD9PqpniaZarGT33ALaHcZMp9MqIaau67s+pl5CCpTIeJ3W08Myn1bTysRNLR4lRold6/uHcdw9izExO8iIYFrUlIjXXEux6+vnIcS7NzfLo+kqgZzIal1UMxH5CjKBkpXqWgnatNj7/RhDevrimhPdP56+fHlD7HF7VVQXK0UfjrfurmpmptVr9VqVSfq+A/Dtb308zzOBSNVycaVAIkwhUtfHaVrGoRv7UXzs4/Xr3y5ffz7//b/96te/eAUMXkd4ZEQmYTKS2kyL2qjeVciEIHCBCzYzaibZPBFjDP3YQyibreuc65pi2F3srp5cGLKxIZCzLXli0nHfdX2o1eB0f/uIhV88e3ax20cJn378rdPjst7ji999HdKOSq2eIThcjs+eP9VcpodpOs2aKzk015prnbSu6upW3RWuIIMpDrsLEKHZbbNVqiREIoCDSWKUGJsjjZmvpUWjsQOubquT85n/sJU12Kgofh6zngscpvOkstWERG+LH5yJBWfr5ffYJm3+pw3haDWlkZ9DaAXE7uzO2rYasDd3JYKzIbiIAOwmqtHdOarHB9qt3/vJ7r/6b/7s1cOvVU4e7uF+OunjI8dwQdSFEPquuxj3QzyI7XQZ60x91NQRCSkDKZwWjX1n7n03BkrlWHwBqzy+Xl9/9bjeF2YWY8+AIqQABoIjuAf3YMROtOnQt0+hoTxEMDYnB5uLg9oJdK6IG5nbNqmQGzeXqA3DrHCFV3cFzoAl1L24G3MbW7t6NpoJuWaQoXrhFH7w00+/+ObvJHrJZTlielPKnZZcFW7BXcxH+M4vnl7Q4P3F8PL2Vb/rD08Od68eP/v55/qoaZdIvKxryXOuxVEVVb2qVyPbAsC3rmJDLloiM5uwi7hws+oIBFI0YpYLmbiTExVV7kRLRoenH172T6nKKXH3+HCyykwhSMxrlcDkZNWgiBIbJhEkWvV8yr5sOAAIISSRQBzAwsw65xY7hLPzFTd0xQjW2mXalLDne5Xe3uK+3dznFoZbdR/ehum5n23sN90/HNzEiW0lNEfLcza1uQmH5thFDtkMC6i9QleIU1vd2Ixhz8jaNmGns8ZmYw69++v5+n9Fmv5DrrfP9n6b9oc6m/evQN7CQ5noXAiDG6N8o0epmZtWa4cs8+bMItxkd2eSIoGFtmmciLvp/8PcmzVbkmVnQmvae7v7me4QQ45VWZmaqjRgLanBGuiGxgzDeKENgyde+H/w1phhbWBtAkEjWhItNVJJqkFVmVWZlZEZccdzjrvvYa3Fg58TEVUljEd0LOzatRsn4t7r7nvvtb71Da2Z2rJhISLYYlS5BEtSGWdgIFmEqg7NvTkQQCBeNKTqyLggXCSyROWc0cpzNCWcqFYLjOW+4NAG4AYIZ5dkPKWYnUiVp/5mqRkWmPKXLtFCiVA3aMBLAOEbrfBbmKvBokxXtaoK6uYmgsTAxATkCm5o0Far1Tge9sdDzqVVT6suRIkpYoDHY0sDS8dOygKKcDg8NoPQiaTQ9b0E0cW1FFCY5jyO47HkmdBTJEQg8Hk6FtTWZjNwcA4Suy523W/9zq+9eHF7+/Lm8fZmf3eXAK428MGTy2+8897V9VOtMAy7Z0/fR0h/+Md/9H/+q09hBf1Ghn4ouQSJNRdVC0mkiyak2gDdI0Bkm4up6mLcKNRasbmRw2oY1ttVDZkYiAjBF4Ius2xkU1Ps+247DKdnjaM2N3cmMm2MFJgIQEsGdzAjwC6lgJIdijYmtqZGDVmaGjuQCIhpKYdpmtT/pz/4g3/0+//w6uJqHTc21Dweh9A/3t9YmZ4+u1r366LzPE/jlCsWNg19v9tu4icffcu+8eMffn9uGQMOl+t0Ofz05ov7/fHhYX84HKdpVGsswoJ5riU3mqYwk1Od81EbAK8A1CrsH0b08WK3HvpecFar5lBqe3VzM031cZyKViRghOM0lTwhwm7TizAgExGRLA8XMzGjmaNr3/PQrVIMCDCkztwfycbj8e726AIsGoKQiHDoU0pBasm12qYfri8vI0qpBSev6q0UM01Btus1kml1V3YPTSmPNs5zLlViJMzg2q9XzFamQ+y79WbNQs/fe/7BN8oPfvjSQXHx6MRlunMKq1iQnZNLFOAyiXwTQLrszqdc2dNI4Lw7vQlZeP1mO9kQ4Hm4AHBG6xdOuL+93y1c2bc5Xm8NRs4zkIU97QBvJdCiL5sKESIvxg+4iDdQgJAcEYkJbMkJNfDWWtNitkDeQAKE2NDdVIRpcWd3c3IDhWX4QacNekm6YWHhrlpRa3rSyZzGlcxMTKCIBgisVt9Q2H9ue1oOuVN1RiTL5vZ66yciVRUJSNhaW64YIVBAU52OU78e1DyPcHm1/uhb7293/tc/+L8Vb/sNXF5sn15/xNwd53F/ODZrh/2hNAUCDhSjAAWWFINBsaYVPC7lptaq6iyrZVyMAEQJMYIbGQA0gEYU+iHsdg5kxKBac8ksQSRApPUux8hODmxxSBiWUxmYgcJil2/gre/D83ef1FpC4NQl1bY4hW1WXUx2mNtxaogQImlprZXVauXKpbYuoQUEhCUCjYkDhy7Gvb4ShBghRAlC6KBqptmdmTlFYIEQwV1VtZQ8z9OcbZOG1TqRdF+Wm1KmXCpCTIFyo4fDwblNU/ev//hP3n369JNPPvnww4+evPtl9fbp3/7s7lWh5gszlzwAkpm12pwgLBCtmTswBmd0b64GxCjLYdcIESPQkiZjrgoAgBKIyCEsSQ6RT44KudSAIfWJgtRSXDF2cbo7aqophetnT5+///zXf/tX0oBzvf/ss8/meru9wn5YAZqaulnOeRyrGwSJTNL3/dLRSWB3KaW2WkprJRdEYAbHVuvMwEhORMt5LhE74G5zkefZSh5Wfd9varXDWB4fRlVwhdBBFJZAXY99D0JYSz4e63F/0MqMODdtxcwABNSaKnYxEgMiWvFCTgyrKKmTrhdCVK2tlXGacgEAgAZlrkwUIqcU+66LIYqImak2s+DQsaCgq5YuhtUQ+64Xjg93D30HTARemptEf/rs6smzqynv/9Wf/qkYRI4evNZK0BCZkRyQEEIn5xyXk4GFg5sZEJyNE0Br9tYAkEJMXVRvJc+PNw9hI08+3L7/ybvDNuS2bw5JqO+H1bDu18DpeJxKqUalTaE4ANLJ71PthExRIAqkxaaaW7WBGkXiiO2oinUJffNFWIFExAvdQThocwCkwLoYmAvkXF98+ZV5/s7vfOxUXt7cTrmYgat2Q8/oqoSANdcihSgMw2qzXo3TYzm4RTWBEGDouxBPPAZ3JATmCGDjOM3zNE/A3DYruthuU2qPj4/3NYM5CKIgFHV34migDt51Xew6jt6allp4zouWwA3AadUPHDHnhyAECMJspvOo85wZQZVLVq0AnFNIIfLiLMwEXQqrdULCnDUC5DxPU5EA2yuRELsuBiZwE8IU2I3kYoXA8zwfjmOtrdSCiF0XNxfrro9zPuYyhcBg3HR0Bwlg2JpWiecJ83IeLTHceGYquyMSESMDMzXQYsUUZGGfCQVITfXV3d3t46vUx/W2cwdmybXV6sUaEAuLqKGQiJQpHx/286FBg8jYstcM4JCG/vnTd3e7tFp7SlJGe7wfiZgQ50cdD3maSq3t1AsbQE+tWpmao8ZeLq633ToYzXPdF/VpGmMkZirNHC2EgAhqFZCJ5Op6KyISgjOaWSnFq0/HMo5jyy1ESB0To5sTYUwSObHEICmG9Y8+vS3VACpSbW1CKjEyEat6F3i1iptLuXqnHLjkx5rzMQQIPYCpwVxRARWNiRuRRQGLsL7sn314PVysJhtHc5syMgB4nvNX+3E+jl7VwD78+MpRtdl0zMd5LPPoDjNLa3OKnt+/QqiuFay4N9OqyIt3cN/Fy11cPIis2f5u/73vffrl9+bP/3YEDH2/rjMvlBa35lTd29JLuAO4MchpNHViPtBiNw4LmY/J3cbjqOKhExRqLY/7GvqcBn727NnD8b7UY7MaorRGrRERqzbmME/17ssa6adaHzuxf/Cb/86TZ7vdxT1UaGH2VjCdqgoJYX94/OLlC2EIIWx3m7nk2pothHID0DMuBAQO0zhxYkJWMAMHIQIiW0RctozVhHjJ9kKDc3qY29nd+BdpHPi6zjnz8Rfc6a2e9g1Z5eyXirjQF08xOguL6uS0+lbZtEAEFE7V0qljXyKA3qgDcFmLwA7kpmomaMQL5SNCBvjgSffBR08kOUckQZ/jePRXLx/X/Yf7sXmB6pkNHms+OkKpUFde6dvf+bbzNFm9nw9HnWo5APBqWCdcT7eFvNsMm4evD7dfTsf7CgWAwQ2AMHbhxGtDIjYM4Ezo4Od0waWmhROQdwoddANckA56UxmfAb/lvQ4OhLbU78seRMvc9/XFOBN4Xgd+mFe1RtCYIQrMDR7vp+PD9NNPv/i1T77zk599/vLFV8f9Xh+dD8oOJqqoSykuIg0rNMNxP83js6dPkeD4eCQnWXMUAUUHiF1qNZ++9cnqA91sSac8aRWWNgHfCPKWG0ngCvrawB4XZ1sEJGJgM1syNI4PY7gjfpaudlfTwV+O+1kLYQIAbWpm3gDZ4xDjwggFnIt5A2gnxIlZUpeQ2cAbnMg1fgajzg/SqS+yU5ydv0Gs3rob50PhTCN0N1w4Xehnmyo3x8Up2Z2czvwjIjrp3JY2zM2XihkXPSMsdm5oZgiyePCemrbFZNXfQjYcrCn8f+FH/7+/hJwQaBkGOqItmZC28NtOeBY4Itmy5pGACIkZiUop9paQRd0NDIQjizu1pu4ojIIMgGbuzUDVnRQbmCueBHyEaIQgjkQhBEAsZTEOR2JGJ2/aFvMpAgfsmA2XGFN3sLP+yEHd8WRgs+BTdlqwZyAfzvvWybsdF0Tzl62gT8QuczU9mb+jhSANlMEM3JfBEqMRAqqBNUd0c7fanFlI2BExETjlohdXF4gwj9M4Tdo8cASE2CcRZuZu6Ne7IdeZ2Ay03B+bgXSIJChUWl0KCBECh1LmPE3aoEvAaIzqaA5NhJi7WquBl9aKNSGqRfYP9euv9vu7g1eIHdXM+4c673CegCl89OGvPbn88K++++M/+F/+EDawWQdLrGq1KQEjYWSRFJx8Ph4T96vt7jiOdc5dihijm0cJRK5NWqnMSIjE+I1vfICEEkQIEUG1mimia2tV83ZYOSgClea5LGxw11atqQSexlGRF65LhYyAROIn6BO1LoZgGiVEwkSMgdm5etNWv//ZDy8ud9/65rc+fvfD1Wpl08QxyvYzQPexAAAgAElEQVSi5GOiVOfavAFQFztCL2a1VmBOITDxdru7CoKBYKCKWrLd3d3f3t6VUkKICFJKO4771mqu7nOJM4We+q4LofvypzfgOAwQAvR9ijGICCG5QUppHKdSap5rMyMJkUEIwJdAJLCVAUiQiEwioZnWUlrVprnUeX9QdwVbB1mJELEJ0nqVNpuAUEMCZhCEGDmlkIQ7ohTDcT7Mh71dXTN6q8V9nu5Hdz0cVkE4hE44v/j6tro1BwPMrT0cxqlSiDMi9TFc807byb91ruW23K7Wu6dPrsAh6xwpNm0LGmXuYIbMyyxh2aptwbAUzrzW17D967X2drXyiwAWLAzgt2hWfo7qeKPhxpO67pfh/9Ph5nBKfvAzEHYulfzNZM+NltZIUBjcEBAFKeDiQ4RIxKC1EC2+KODojGxuwoSLI7sbuCGjITRQAHB0RXMydHYkcOAzuxXZfZHTAgEIIDmrsoHCWX68XCUEeG1reiLZwhnRO33y5ko6nOMMTyMRcDcnIkBQ1cWLrTkAkDrW0tYXNO7vd5dhdx02uzj01T2Px0fmQIFSCohIBZuWaW4Pjw8OsNpsEYVImCRwBFErTc1yqYgM5A7ESHmurZiZIwojEwbEZmqADCDuTChdF4dVNKh3d/emuIy8TODySe8OzZqzhE6ISNUAMfYCqMdqYAYC/Zqvrrc/+/zHKSERmjlLmPPMMYYkXN1sCjEEJkMlNNM657lkYAZ3YKLAHRO6eZ6slbzuVtqKWWPCKEKE7srELAiutR1zBdXcDSs1aK0tg9xpOtzc4icff6e2lnNlnszEGq654yg5j4dxarU93h9M5Xd+67c//uRXE26I/+T/uv2+tdJfynRs6ItlhQFCSikGmeYMekofdwc1A2BkSSGYtaqOiIHFqy7risndyCEgciBqUB00sAC5akVBQS656DiW0rQaKiqDMmxX9vz9p7/xnV//6JOPDvP9X/7Rn/30y79xhuvH8N43N92axmMtVU0JgM2pNnNT4VjrOM+To4gk4khqZkqEKXrqMaUowhwIlByg1ppznedsqnEltWprHqKEEAi9NT8QOAJH2G2jxARufdf6ASOFIpLnOk8lF3h4BGswNwAE6mA1dLEPFKnUYr7YhoMIEAOLpxRESBtMU9PWQgAAaA3mYuawJlivhvVq1XTxSGgAEGIE1MjAAtYgBWZ2sNL1Ubh2PTjY42GeKvzKu0/e+ejpXA4//uynMIIOoNSAHQAMtaq3ZeqN4Mh2ioYEQ1V9nTkPqicGpYNDBAB3UeB2Gn06WGgxRUOfaxmnWSRJCsTsQE5AIYgCslOI3AVz40gG2mprzVRdFxEcOwi4ea4lUtxs+2ma20PDcJrZui+7IzLxsmEiYm2VmILEqsXBQxIwu705vBoP/8E/+X3HueS6Pz6igyAlCdZa08bgReucpxCs69LV9cWxHA+P2hQAQc8x3e4IKCmuV6tut1vnMh8Pk1nJFYJV89IN1A/r27v1lB/ybOaGYMBAzJSW7pOAWR1BTR3N8LjP89RK1lZc3XgzEAE5pdAF5CF1k+RszRoACgISuLFFiX2fiDz1YA6rddxuh2GIpWbExmxm8zhZaDBNU+9S2edpJEIETyGwpOMIeZ73+4fH/ajqMXLfxdV6tb3YdEM6HMAPjZgkUDVVq+t1jEPw5svsFk/txdKAMAGYLbary35+8jgNRIGDkRnW8TjDONtaOHAAyvM01bkWY4zCMcgqRRbpp+mYS6lNNbdDPQaQyMkFx6mWvWOAYQjb9eVud311/SR1qG2cj9Phcf/q1StCsgrTccnqcNcFXwNA+OnLrwHdCTB4vxUSB+y7NXdx6EP46uYQkwgxJtRqgGCubkAEjsTCIQQUrqVMJZcykzEghiASMAQSAQJolp0odmHohyBxsQH5+vZFq8jsQbDVHBMiiJmJyKT161c3Mabd9brlh32+B4DKUA2gAJYGswFOTqYCIFB7WG3gw0+u3vnmk7ROf/H9L9TbxWX/tI+p61rT+7v7x9tRK5jD7npAXqYdQ9eJ0FxKybnsH9qBoE63AsUggzdCJWwLdYGBAsFq1YNSpA6a1GO5+fr2q68BHLo+AXlrJYVEQmUe1SqRMZ+ykcBJi535575EeZzE4qa0yG3Mq7bAEYkA3SrMtVU4PJbDP3j+SYzJvDada9Gh7wQ5F23NwXy1GqbVeH8Yv35VN6tqrt1Kug3BGtwLOgQBYKBIteWGFpNAhqnW1JVxagTAEazAG+OdRWZHdBwPERKTGFj1uvRdZs3VQK1aATVYrNwBgbA1cFvY6W/7SfxCJYcLX+HUSJu9ASzekh2dtpW3SiN8Aw2ci6TXb1gQK3BEZD5p8n1J5jIwc/g5uOs1+x9ImFSWFDkFA69W4OOPvvXt3/qVYtNhum+VBJ+RkaC2OR7u5+NcEMGCPZaxTXvPXY/AKNvf/aDYY84PZX/IZlZBUvCGjogmQ3fhyF89jnc3GSZAAgKyZq4GDMtAFBmQyE6u1W7nISgSnqKRlrwXsrOHu8NiK/FLfI3XF+3kOAYnvOWErZ8vxmsmnJ+LT2MmZiYIZLETzaVOpgV+8unPfveffPLTz7/aP4DVuOnWx9tXaeipS5XLjCOtYL3uJVLVUg7jPOd+6Ftpj4/3DAgiAGiq7oYQmHBRAxIiMKkCLGjNqR/4hV/HX1OPThAGKpwZRUQI6uBOTO2cHj4epmFKa02RV7u1TSufpvt5nKlHq+7Vl3QOJExdTENquVUW6bk1XQJPCZGXh24Zlpv7krOJJ/kqLaifAfCCPQEAmC+O9j//6OMp6/LE3kJwdDp3M+f5vaO9hpsM/OTpDn4OXF8cAew0OEOgRWWKBgDuS2L16Qde7OXetBGvLepfdxx/59Py9+QlgsHdl5i/JdDZmpoBEzKzEC+weVNSKG6LhS4CIiPF1NHJI8pVtbZqzUpZ/MrAHdmZQYTEDcFqrW7FwKxC6zYd+klwBMCpi2ZeayEhMwU0EpIQYkyAXmux0qABCCBasWpocKaIAsCpEzR3NXQ93UQCWmxT/bQnLfH1fr7Xbyhqv3SfaEHcFjtN88V6WYQFAIEMDBiBCQQdXB2cAdiRwRmVGjKlXhApxESIsUCZM7rzYpuMDkilFHtcSNeVuDfXcR5Tl1iYApOZIU4lt0eY5qO7BeEuJASreTaHLsJmBZ2Y1gk8d10IkdWas7XmajrnzKH963/5f9zfl/F+DwabhB7iPMJXh/G9K4zPdx994zffv/zoL/7ie//8f/gXf/THf7NZgSkc72dgSqseqkpKAFZqrsWISalq8c16LSI1zxLk+vo6CBECIeU8zdOsqo+H/cvvvlCrQz9cXV70fT9Px4eHh/3xAQxKgRihVHCHzQAchu1q0/c9ETIhiohT18Wh60WktlxKMcRsVrUtS6uW4uDWckU4wQwBEAgwBO7+6tPvyf8W/8Pf/4ff/sbHHz37cBr3j3e3GWhN3TiNTVvAKAnQKrhzEAyyWLB965sfSZCvb77+/o9//NXjzYOO2my92uZ8uz88WIO+X282W3O7P9zPeSq1NHBgR+Kri16LGlrfdcPQL2B36geW0Kp98eLraYTVirouIlCI0gUGtzxOx2ONoev7PnU9iRBJVT20/eN8h6hDJ0MXalWEytjAvGTruu7yIqXwZBwnrXCcR3ddR96uBwIC11XAMCRXE6999ChxPx1uXr3oU3d86C4udpvVhoR/8tOfGSdFcqLsUQEMam5VhCvwXCuBb3a70upXX3/Z4/Texfbi+fDOhzzdy/6xQQMkQDkvuPPh5oR2xrCckJaG44RUEyK9nQjhZ8L3azE7vPV3r9/zukxZzgml08SBmJYz46SHP7kfLv/u56Dq0/8DbzCsZZ0v6gxHpSQcXc1ADQODoIdTOgQykpG7mxqSM9OqWxmespGr5eYNAoUYwQEWajxQhLB4g+a5ECwVlSOogbq6Vnd0IpQoxBFP1hDWcrXq5EzAhKS6JLP94uvto8UdzBrAAieezp6Ffnzqj3U51ckBmiJySGvqOtpX+I/+49/7rd9+n/BBtT5/dhFu97kc1v3ms89+lLrVXPJhnDCmzXoNxBwCArXqQZi5C31Un8t0mMoMFIhQJMTYvXhx8/CQp0ObD00VPXmbARSRGCCWo92X/TwL0AWiLk2WGTqQqj19/zrP8zjNBpj6PqYulzKOx93lquVAdGCC6+vV9fOeg+/Hh6zgWhwqkfVdCl1nwLl6DCGmlJIg4Gaz1gbe4pPLjaq3CkTBzadxnuZJmwLaN9677rqUYpQQWs3397c5t6En2VJKMXUp57nUKT/Wki3nEmPYXqxi6BHDly8+c/XdZYqR56nVCqV5qbU1zzlrx/M0Tn/5/T/5N3/+7OrpP/5H//i/+W//63/2X+3//N/82z//s7949fKuVABHZjH1UrOrSWQDkoDMjEgiMcYkIYB7nidvrmZKWM1jCEyRgcxMm4EyQwAFBNIKxIaAYO5aJYWhH1TtsD+OD+Wdj/oPv/nN3/iNbz99+myc5//+n/93N/dfpLhqgOtNuH0sw33dXqR+HRXGOeeXd4eWj13axpTYIYYkHEwdkJhCI1T3WrNaNvPWSimwW286Ds3MGrR2ytD86us9OqQYiMjdYows4qipPxKH1bByx5wnYgtEITGRo7urt6bPn4cgwzTa/mFCD7vNSvpUreaHkRmeP9uJsFoFqISuLS/nPotJhOury1p1nnOt1QyFg1l5+erF4+M4ZagFgOByI4gtBNhtwpPLi2fXu91mTWgxpt/8zrccyID3+zml1cXF1c3Xdz/40d9+7/v3qw+4zBaIclaBQEbYHNriSSC5FkIkIRJy5JJn4tCtQ7NaSm0GJMCR2twcIKw5rAiZ1jH16ySCFPzVzUuOoF7mkvfH7H7o+0OMQ60+t2pA6ma0GA6ZAhSznI0RihU3cPYUMHJEw8the7W9FMafzJM4oLkXAkWkxT1hIXggEdVWieiUcwfKIAbNm8EtPN4+IPJmNbzzdNcPaVitWtNpf9gfHqfDYb3alTy5WYzD9ZOrvk/TPOdaxvFY2ziOWQ+ZGXe7y2EYLi+e9ENq7S5Iv17RxYXcvLx7efPSrD5/5/2PvnV9ed1/+eLu9uZxmisSONiUawgiUeaS54eR2Vkc0AfqD3fleKjgwFEyVULZ7i63w4YAuyBMUHPOExAZ0SLnBMV6nPKv/eqvNF2b536QzS6az7WOJJgkdN3lxUUDNGYaj1OuD62VrutSJ6mPKfbTPAEoLIIQgK6LXZ/MdZ5GQhORzWbDLNPUDAEYVrt+s+vzsSAbKDQHaEpq4IENEVFCcjWA5gpuoO7zPLl4N3TcCRJqK600Ck7I5AizAYJmtQZWYRprnos67Y/3tZzFQg0St4BSRi1H6D1udut33nlvvd5OU/n0hz++v7ub9sfTWKgBBvDl14LTmAkRzdwUQOrpoHYoe314/Fm3gg++cfnBJ0+unlwVPVJAxMY9zBONY3anBaqrtaRhbd7atIxxJ1WIsUtdV1qdpnqYYLORy906YWLm9WYVJOQ8P9zdP+7nqVZUMIPWsBlQYKBV38daS1MNAUAs5+ndj3cff/uJsNZSbl/evvzqMB6MnmPklGLX93G36XcXXUiNUzO+nzWsdhS6rSGuttuc9cXnX929GtEwSgSEH/7wJTKsu+Fid7Fab1bdxto8TXc1z+MMqocojtiUGrrFU5o2gJdWKQXBECOl453d3NzdvIJagCM0nVsuUMkCe/MQPXJ0L6bN1UpTd2RiADrnxrjDkkZlbq4GhpUZiKC2ClOhTkIS7oCTtuqP91PoU79L47wfx0cwN/NSiilMh8P19cXz64uHm5tXN/nuHv7oT/7w/aef/Pq/+85/2r7zp//73x7vagy8u95xDC+++up4mKVnSrRKq+3lVdd1+8N+3mckwCBEy3gNTwwgZmAnAmJ2iObq1WrNUAEULFuW4qER88nkyk9hWYxQf7nIweUDnjrtU6dG8POTPDzDNY74NoZ1/i9+rtleeADLX+AbAjuYLTHwJ5enX/xZ0Bfz+CARPFml1lStdkPi3fzt3/vWR7/x/td333vx6tP9FO4fh5ub8vBQ/u1ffAoFIMHzZ51bvfta60uAhwq+B4E/+5c//N3/5IN//5/+/m/96jcf681f/+B/vr85pgDBp608Y+zub8bHVwUmgAZCIhSKN1BbnHgQTml0J7MnOyM2J4sj9MXydDFVJXddXH7Q/i6k8A2h//wJEQC4gQOCKeISZr2E1CLxmewPSMCg5rUaSHMDaPA33/vx37yAf/qf//427jr4PB/qfnrEqVnXUpRu6C43Q3fdyUqy5TrXkuf1EK+vduPN1FpDlDln1kpG2CzXsjj/LJM6RDI4ZTIvPmV0RmVOcNUJgnNbyMWocJaIOS84DqjZSbcNAAiMRB6nQ/kq36Zh9c6773f97quv746HqWRrXoAdBDBQ9ZYPpc0NG15udoXaeH8UjCxs6rXm3AqYgjuLgDmQsyE6CAgoWjM3cAInXciXrxlk5wcNlnL99OQufxB8AcKWV3NYvMRfcwEcrIJD82V9ICAQLDGhQHBSJS/A2XKtnIjAz6jnwqE05yCL9ZKfszv/XmFVf+dLmNjMmjZtpmpgZ00mOJIjkODCPAgK3lQdnIlZJIiUeXZ2huV59lP+12k5AVNkAFzuh5lV9VwXwBJwiQK310Y2zKdwTFX1RbZBLMLLbrNolBf88EQCA1ru69m9zBfT9Nd8EF/kwGdjHHi9Ywovdl1+Fj39na/lQT+xRpZLgWjWFNzobOYjeIp5dQAGFkAhDO7NHdviW4AGLNKs9JvryNKaWsPWrNZWayUmROy7YTWsjQwcSi5krG5LzpSqYuNSFvt7dR3dgB1SgG1Pq56DIHghVGZQs1pra9VRgEgNxrn97MVNgnXkDqChExizQIq9O6e02e2e3h0Of/XXP/rL7313ziAb4ZS6EBqgq3d9zwiqtVkLAqvrzWrYgFKuVURWfddafXy8b7kieIoRCVRVzaC1Sk2tNVEmHoZBGN08huCmeZ6JcJ5nM3cVB/eqyrUtRGS18TimmBh5ocfE0FEQMa0lI7MEqa20Wkue3WyB6JnIiBq3JJ1nu9nfvbq7ebnavPd89zjOkDVhtKJCYaxTdTXSsRz3OXOXOHWERIi11M1uCwqt6HSci9XDPEoXujTAVsrcRJgQ1RwAYqSUIjAoVNeKaE2bO0Ai5oE5qnltVmYd53r/COMERiYR+yhdGrrApqVRRgSioM2nsQDVELsF5xHGkNJ6PVzu1qXMkUkEay61jkI+dEPcDH0MrWp3RHfcbFe73Yqc0Xy33coT1tK6EI+PWdiErORDx3A8PHQphJS61OXSlDArNSBFai5IwImIEZiqNrSGMghDPsxDD4Y5rv3J86sf392SmDVAZhJ2r754lZxmOIsvj7s74RL+QK9nOK8py2d+1BL7579Qarx+vY6hWV6qC0+JlkbrDUP3rX//2i7e39hw4huvoNffajmSCRwNEJABBUERkVDAeTFDACRClOPxuBwbICCJAiWOwiy+dCEOyECBTK2ZuQEhIoMjuXnsBR2WA8Oamrqpt2JAYAElMAEi8WkGuGRv+ZK4t5AT8fWQaQlphbcArLMScvnw5hq6G0tY8jHMnYiJ2WwxCPRW6/3jLTFcXser69Tscbx/IM9M6FUZkJkAtbYy54ncAEhEzGGei2prTZlwSIl7cJ3dmxM6gJqbec4FnYTEtda5BnKGQIHdjYAJoeSsNod4IPZpLM28REP2qpZrrlpra0XdYTGkkr4bCB29SYIuwGYrsaPbu1cGbZqKWyVuSKYO3JxIalFXKNMUpdusByap1VE5xW6e2v5wMG8MUhuLr9dD3w/xarfSNiMgA4fUy9WqzNM0H6axTeNE6MMw7La7h30ex/txcuFKXJkCotdSRbrtJqUY9zze3R2mqe2PjQinCaZxJIcx1XeePoth+OyLz6rNV5ebX/3t99/5xsW/+B//19ubh/sbh9YgwOU2xZCmqSynLqAyc4wdk5h5LiXnXHMBUFMiiYQiEgBRm7lbIOn6HiAZFPCCjCIsIdWaD9P+flxi6AA6+L1/73eG1brbhPvxLufCAl2/mfPUDSsgOE7lxatjvzk4rdS0ObriPPs87cEfLi62KYVhGFikVT0eSlNPsSPyps7RQ2ARynlWqwYkHIiQiNUtBkLHGCMCT1MmqizcdQGpJyJmK7UylS5J34UYpRIRMhMLV23Ud1HY3VQobrc9iTweK4LFyNvtKkQxq61m1WyaVU2EuiRdwhjFzJjBnRf6o7CIhJQqYm0MRLxarwNb4NonQrRW52k0bSV1se+TOUzTvFrxahVjcukorcP103BxuXn18rAaVsfH3HKtJRcFaAAFwCsMAA1elz3QAGotXE9m/AIyQIicNkk62l5cxD6qNnOVyKXOc67FoBuCCAEk1YyMhgwiXtuU85hrCDGlyIGAkCXGFLtY830JLGqG5EFCDIEcpSNKuNqlzWU4PlYbAc0CJWbSqrU18sUn1Bfk1A0JxZFM3aExQnP43l//8Pm7FzHGbb9NQyDEqUwM0MdBVW9e3bCE1HXDYF1arTer9WbtCON4mKa9o+dCEqgWOGq75WM8zMfDPmft+h7Rh1UvoYUIiDMHkWSxB4lADpEIiNWWdAwzglIaEnADMCBudW5QTuV+ndSskrdVF82KNQ2EgaGLjBgBIPByClkxbW1KHbF0MXmIqM0dmhuwiHA0l1bbOB2bFkDIeSYC5k6YGtXpeMhF3SsitAbTPMUUYoo5T61lOiGqOFdv0GICw1atGDSOZ5HTYipsBRzQGQkdHYkcTslrFATIa9M8FSQAciCIFMDA1aABMBAwGNXZDg8FDBrutRECtamRABPMox2nAg3A4du/++utaMv61f1XDw+Pr25ewgyAkIYQROYpR4waLJeyWNbi0hWZQzNZsZsuLCNEsAnmCnf94em7F6D43rvvN5uP00MpGQkk8MLYVcVaG6LXqjnnWqopmMI0z3MpRBy7sAjmci0IECMaAAqxkhOq2nogodiKzbkwgiocDxMRX15eSMA5j+pT6M3DI6a03m7AieImroJrYO/AydUdVKJ6X7Azxen+4YGCPHl6RSE+HubjYXx4GL98sdcRVkNHcbBmeXZiGhuhF3e53HQpUB9R2/5xv++iBG7MogFrAHcGwKrqaLRkjDogoDXz5n0CW8GYoVkT6XwVSMBrrS2TL/bARoxCAkjNDEGXQOUlCB0Xt3F+zbxAFlyUyK5KGIXIDfNc94/j2lO8SJvVVpjcbBqn1hwMS20d+mq9qtPYSr66oGmexvKwGeSdD9fPvxnx3cvbm2PRXPfT8XEGBA6BI5vCqxc3wzoxiVIOgUnFUX3RS4E7gIE1q64eJAhTaQ3N0QAJzM+Pujm4Lsnpi2uTnzxcfplEf6Jfve7w3R3clmrwDffq5zCsE9ce3pIQvtWEv2n4/Ixh+euyaeki8WwttBC0zj8G8pJvxsvA0xFAoPn87V955/k3t1mP+/m+26wq9Hg/7O/u7m8VHgEErrbrzrs6jWke1cADia4RqJb7L3708N3tZ88+3l68l3YdmEOrICCRFyXvlIuBLjgyEhETKhMwLXrz0zTWTP3s6AULU9JdGAyX6Ec8Kdn8TO35pZZ3+a3fqipPFH4HRDDz11ZKJ+7ruSc3W+ykzlQvA18kfqNDhjJpy5o8gTOrQFqGhg0AgyRkaF6m+TBNxzHbB+/sQhA3aFWpMmTTBo5OhtY0htTwxGlCRKITKHU29DkBVm+q+re+egoAOXFWDPBkXWLmwlwNAKDvhiGuD/P9T774clhvh83WHCiwC6M7GjkrIGcrWsyboUKSlKRna54NGiBQU9VaobbloEdZTIqQTjgEwZLNw6c1sBQErxlvb55Q+Dtu0ZtH1s+hT69v2pmXtXRRGOkkUTkpTE7P8/KVJViQiJf+4hfWHDPDa3uW/xf61ZuV+PfjJQjk5lZdi8I544l4IQielrPBCSparvxJJURUSyXGRgvBDZh4WWjLxiN02sNbVVe1qn5ajbBoys5Gxeiu2nRhsi/LhogcrJZSrDITMjGxsQGAqdFiqrSgl+fdBx3QHBfOnIE7MBMhCYM54KI4RQQ+RY6eNUR4BrL87afHABf54WJLDYhA3hbMFx2JQIiEDd1PlER3ImRABgQnRidoWsnR1Eor+ThZ0VpMm5lBrU1dI4VWNK0lpli9SOBcq1ezk2G+i4RhGI7TRAwxkACaa4qy6cK2pyhAZF2MAACgqtpaNQMWEhYEqrXBCLQiCkHVwZxBUgqdoAN3/bo2++53v/+jH3x+PNh20zW3Vh0MObC7l7GIILILkzOBOjowyXEeq+UkodY65cNcyrKiSCAlSSlKpHnOC57VarOmwjGljsAXSRSYMhG4dWnxOAiM1FpVd63GJK3p4TBOUyHC1WoggDzP4/EgwqvNmk93B504Bu66LgRxtVKrOcQU74733/vhD6ZXd7/9n3286le7NNRas86r1ZBr03qsamWc94+PmEK/3gyrIXY9NsuH8fbV3bg/BpSL9TC3BohPn1wy8uP9/ng81pJzywi63W13Vxujth/32jILSC+I1HcxyCI/xmksj4fJnLoOJWDXxxC7LiWR2LSWuSDhxS6u17tS5uM45VpDnFPfubcuRWHsU+i7aG1WLaaep9lKiUBhWKXYJ64E6Ns1E3cppS4xCjquh1VkGceRnVqkvoup2339ajv0ya3WPLMQGIQgZtJam5s5MQZBFvNai4FDENIyPzBvuzi3uRsiJ99edR988+kXn91OxRfDYxQCRQAEFoST49VJmPKGgfy6Plhir5ZF5w6+THL8l3dTOG0UcD6Ylq1J1YmX/gphKfHPZQe+4V4tG/cC6iy7+IlT7gur8s038JM3NoGzL6eOmzuBk7UliMWdAE75d7UIazcAACAASURBVHA2PzYFQw5Ci8WiKxA4GgYWgFYVT/aY5uBdDOAAtrDptTZ/bXrl6q01BwBFb9bakvdKhIx2PunghPKfJ0anjycWN5yMIBdof3nTYi3JzGbWWnN3JiaWJfWeReeDyQDf+kZ/eR1jqgaT6qPqzAhM7M1iYAdrtc3zJMDutljk5JwPh8M85xQDGG4GCSmZU4hBm9Za81zMUIiFxRrYDJWrKwOIt+xo1kibm+nxOHPAXKwpSKgowRxfvboF8jxbLlAyqLKIiEBp2Xxer2m3XT19flna9OmnN8SW84ykARDMDsdjiG0YVsKp69DUyVGL5TKmbp2EtQBqWKXrGFfrYaOK85zdXIR+9ulLxBZCWK9Xq2G1CjxI266qCCJ6sxmxAYT1qkfsu+5QSgFo03Qw02HYASijJImENh0f91jVoGZ3gMRpOmR2//Lrr3OdKPo0P9w9rN957/L5h1f/5T/7L15+df/5T778/PPPv3j5wrEip9QjM9Ta8pwJWBhNtZQ651mtxRhCHCTQWDLxEltGxMCI4NbqKEzgudYJ2RApBAnRLgNuhutnT5+99967T55dt67MuTw83P3s85fHPH72xU+GVc9RpjrOBzWH0myc7XCsrc37x3w4+DRCYIxhuH+YYijroa7WG0I2g3nODo6oIUq/4tU6DkOY65xLAxJJMUZBTzPUw7jX5m4NUZAcCc0bgDEak7k3odZvAjMwIzO6EyEKcwzh/v7oUAyUg3adhORVSylHt8zMDoqAwhg4qFqpTURWXer6LsZ4fzcyIiOpN0LsU8cs++OECCl1QQyAYpQuehQU9pyn27t5iozQnsanKXb7w7g/PK6Gjft8ez/e7afSfLig4aJ/b7UmlKfPIrlAszarF0NDQjJu81RyKe5OTNbMzDiJRFYzReNADqbcFJtja2bNWi7Zs1fLSEAVcmEgXCJY0NCstTaV0nKpBAQA5t6qASoihigcCTsSFvWmqotMRlWLzdXzsOuvnl00ezk18OaOCsJetdZCLkgdgTGzgbspETuiWSUURAfRz370+W43XA4rWe1ix8fxsebSp5RCuHvYv3xVdrsaorg3gBokEbObyXYVE83zlPPUKmgr8zTevHqQgOYlRGfeSMDValitLEQmqc1ys0xS4ur/Ye7NeiVLkjOxz8zc/SwRcZfMytqru9grySEFStAI0AJooHmU/oR+jSD9GQF6HkCYgQRJECBwRhiSzWZ3s5pVlZmV2703Is7i7mamBz9xK5s9GvBhHniQQCYiYz3H3Y/5Z9/iHkFOau5GZh47SV0XK6vWqrpmZ13Y4zAEOKmp20biF2bXkmIchzjueFm8ZmNBCCyB1SxXlHzuUuemy7yacSnldJ5ZpEuxsVgDSxd6mKtlUy9rZoLWPNFsZoFlP4wiVcKSYhKmknOppfkoV8sk4DTur+XqcHA1sA77LsVn3339W2kt8AI2YTAZSs1MRCIgckDdWzBU80wxGEwBLOcphCCd9LH3jhKnYzU3k4CQ4rMnzwwKwt39u5wzV4xdvNpf7dI+hZ4tTPenV6/eHo8PVh2MftffXF/fXF+VUn/9q99MeYkUupicgWowCARgE4NjrQZ2CSyJPZixLbk8vDuGwX72Jz/I9bzk8+n8momHYSCOWqGuHOR4POVca1VzbfQXc2YWcwTmGFmYSnYWBIOqESjENIxDrjov5904zOecNUdJEngtyzSjH6VnoZS7YETGki2WKhBO/U0MY4phRA2l1LzkdS3umrkQOWEOPS1lyjrmZSVJp/vz23dHnYDKqnFdeJ2Kh4ER1lnn4/nh3WIfXz/7YLi6vQ4co8yHbuc0BTGwqIkamUEqO3nfD13slrNp9VqsVidDEIQIVXBwhamvztayYgBsdv5ORLBiFwmXbRI7Ig7CTIBXV78EJYMITlatrGZcAcznsq4L0eGjT2+vr8a3b18fzyenyNTFEKfpDNfYxY8+ur6+DsfTcjzcdX364NPxP/7Pf/wX/893fldf388EjNdJCSJ8Pd644f7Nu4+//LSUHPlVPpa6aDUyulRUBo9ercCRJMVOwF7y2ggEvsVpwsglsjCLiDqgtCWk/X751yoep8te21uN18rCR/Rq249uGBY98i8aFPO+zHArpX6XgUVMblvPlbkZt3/fTX0ExQIzC6yaaqnKToboaYw//49+fPig//U3vzrb234/vnpr33x9/zd//fL4Lu+v9rUUr3R8PS3HaXoLWhFrz5pKdU/x3VfT18Nr6f3px59FR3WMuzSEHRY/3j1Mx6muSpBWoHpDLtA6nBuTzNzMttPvckGwaPNt3WLOGquHHpUHv4dKfA9UXAgbW8W5oUR0OXMtp6upC1v+JEzhfEmhuJDbyEC+TrUsNWFITk5kzGpqRbkigBSsWqrlaqYV49i7WVnzMpdUQvvsLcKPwMTsTThIjzo9a74L5GaMTYBxQQTab3H/PiLQYQ3RJJCAidU0xFAKYOiHIUpfF/r2+RLCcvtk3T09HK6vKMZa6rrkuharZtVKLZFiSpEh67zmKWupmq11mBkQCYjgZiZ0QY4aAsvExgZrUR1Ngfs7V+R7bhw92nZ9/wA1JA7khJaJZdbQ8Y2lyU4OF2LfjEfgDlcFnMGX6UPePJbatPu9OdcEhe9LZP6RH4GZmS9f93KxXb1pflTVzFioWClaNtizEZ6q+6VBACYWCcK0cZPI3VE2tILczR6dZrePYrmM9nZ5G0LZXBfJHeReawUZXJmCgMHEbu6Le3BoGxqOFoAKdjdTd1cRckYjdrR51tYvFuYgq6puk8MvSOKG22+bP2vrg4A5BmZqYdO1qoaGWDUGFrkzgb/3XVQzR2ViiqKmfeppsR6JEutavnv+HSnV4t745uQQ5LwgIGngCIqobiISUjxOZ8se96k/DDFGEHbDsOsT3LSUKNJ3MQWm1th17/pebbWiMcaare8HSUOtWNcMRxCPLGuBWSYZdrvxMMTdfjwc9lXrX/3iF3/x1/9WJIWUTOtUCpFEBAq0PJy6lLoUgsTi+Xh/mo9r6oZSyjKdtwFD6IZQZ/Xopqi1UoCrdCkQo4uxmUnDTIsuS66l5JxjjORCDivmrtyzUKBAzLzb7d7dvSu5qC4At2SApHGZ51oVwNs370RYhN2VRVLX9+MYYjBVz+KEaHw+Tn/9679JX+jz+1efHG4HiKlmHYuV6/EmlPiwvIucOkkUUxdiF+KuH+bqy7o8vH335rtXPPZPnj1bTdMu7fa74/3D1dU+CJ+OD0CJcbg6jPuxVzZ3XRcPQblzMyKhZVlSHJe1ns/TNOdSfLff7fZXIhIFQr6uOU/ndZnHITz74GmXelWr9TzPcy51zcW9MlchD8JPb676NEznBzdlJ+YuUgwe2YJr3e3GnJfDfh8lLMtyddhbqcGgWkidyPqUxr431i8+/3Q5T8UsBe5i2nfD9dXVVKAoVKw4F9WqteYCMjd3NUGZl5m0WFlynauv49X4wadXTz4ZHk4nSpBAHBhVoBXmIHaztl+yurE9zLDRD7YcXhBfRAj0ePe8YDq/e/wO0N+eaGh5CkwOePVNAd5oopvl8KVjtFkhbMDVhfHpjw24y4onAKCqRYu5uZs6yXarhMGUGAHSfoaAZXMSaLppdZUYJIaNY00iTO7quq2nDKirw5yM+PKTHFBAKIbE7Zs3Q7GWy2Pu1b0aUbOzujh2Nef6jc8GNC/Vx6YCXbqG3O7g3kwoQeIgLapFQxeYebimwPKHf/zDjz+7jlFLXUJ0zgZTIWlaNiU0L6tSqkgopZqjORs+3E8hRHFJ0pubma6lmaTQWlYmrqVaxZqBijxnos7yaqhpkLzkmnMYpRSt1YipS6HU6uel6+K0No5dEOZlVl1PqYsiRlQ45Jvb4cnT/W6f3rx+++rVm2fP9qnvc1lC6J0d67RmUtNnH9xcX3Vv3rwdu5TXo642HPaHq6fnqb749rVlXrKu9ycDr0tZ10zk3734OrJ0/XDYr30/dV2QQNfXuy9+8Ek3yJpPqmXOi5vtdoOqX10dTqdjrWupBq8l54Is3DN53/F+l5bF7qbKAmfvxugKVV1ruTu9vT+tL97qd/dXT588/ad/+s+Hq/HZZ1c/vv/km69fPP/6Ra1lmdd3b49gCNM8L/NirlKqmmsIFBJxUIf1g6iWXEvjbJh5KZq9DmOolqdZY499z+Mh9kP88ssfP3ny5PbJ7e3NkycfPPsX/+pf3p1P33z9/DdfvxPGfgixCxJoOSnMhoHGcQwhFfV5ysfTPC1QRYohdmmeyv20nM/Lk4Jx3NXiy5JLXVIvDooagXAphLzvuq4bS7ZSshnl7LW6WnXkEDkGuJFaFkGM0WF9F0IIpmbq87S4I0gIIsYWI8xr1WxUFXkpx3XVnOdaK7Mt80mLDEOKiRyIxkEopjjuhnHYvXp5T5BAwcRT7MfdyCzLkk+1DmMad4dSLEYGqtaiRc3WuoLG2Hcyz+eui6XM5/NdivEQD8+/+uY3377JBTHKnNcQejBC5BBTRwJ1YQrE7ihaT+fz+extWIPE3YgkpOCb8JlU61Ryrnktiy6m1UqtTri9PdRaSynnJZtvvbSiZlj7dWVK7uzmUKulgMis5FxSjCGwbTILJpi7Fy1aVCBzPleJhydjN3zy+vn92+eTVVUUZQXDtOa8dN3wPbGdHXDmQNWMiwSsMy9Ldjv0/RAD3s1rAHcplVrynMcBKXGKlCJJAFDdbM15muac12mZT6ezA1r5fNZSLQbEhP0hLYPuJLJw7CQmdhRHYdGQsDtEnPU8aa3YqLJi3SDJh3lddVlC8LpalASI1o2NIcxdF2OUIJY6GS1dXe/KWu7ul2VBjBhCTB1LYLNSKshLLvPDUVWxZqSE2xsJIQEUgpCIqsaYRFB0PZ1mAsdEyxK6jvqhT32XIhPHEMK8LM1mWK2aIsUoQZ58cOjTUHNpcY/9EPsdxOCRkdmraFUrqK4M3iQKcAiMWnoSUSCQO9jdQhSHsYRx349X+75Lu93u4XhvjtjH3WFnrlXLoY4PVk+TfXjdf/HF50O3u39z+u3f/t10mk8P52YOnbquG1PomkGypcRrNRZvAhK3LfGXyCUgu1NgFm4ka2YKHY+7lLWcjue7d3f9TkRYnafZ9jvdH0Z3q/NKJK9en8eeAweYq1kXQ+gGkJzP57WsQkOM0UxFQhf6XX+9H3YED5T6eIh2N+6vHu7OtS4skZnVStX1NH2nkMOTQYKZrYq6qNuUhTstDAvGVIuWUpY857IQYyd9YCG4C1mlaV6cElnViuVoUECkViYKNWczIWcC1VLnvEa+17J06fbZ092zZ58Kp6qLk8UocCu2ua9AAhGl0HmHOZOpTucyxG6VVTqgoKIaXMhcjAOJkDm8uqp5M5oWOFmjV2zNddp6VABQ/cJOutAyFG7MEphKnrVg6YfwrN70+6Hv4ryKQUxNS81LJcd+7CGhVjpjeX3/9nCzv3l6oHTzv/8ff54DuhFVYZI/vPn8zdt7Iun7pNc1zwUMIallNiWWEIkqqVkFg5q9eKTUh25IWNyXkgGr7gAHuIOZgjSLyUv5Rxf+SENQHms+34q2R/uIS0X4O56n7g7xC4voIjZsSXqP7/tYQNKFvrKhIQKCEfMmumo8H8CICOYuIiGEWjLgQWIuVuYSh52MaSlTdxNuP96p5PN08l6ev/ru5St6+SKfl9x0uNf9VZJwfHtnEyQjeccWvVAyJrlel9Pf/frb7on+4Z993gXs+mQKgnZ9+O2b5/Ni5sZMDm8KMme/MMDI2f5+0ewb3qRwaY9zizm7KIEfW5u/f2zRShfo6oLgXah+2zl1vxBHgOYHYSAzbQLDms1JOIhpRafBQx96MUFRr7Baa4UJOgrqNfZMzMEilzV2uLo6rPOS54wZuhRStFQNEEKIpSoRRKRdeiNiZtPaRApbgWwGZ7qoLx475CTBXfHoHWIGN7DAXFERAcd+3KXQ37+ZUFArasOBIofEHCMFWpnyvJKTcGAXOLTq+d1R50rFvTbruiAsIRGJiPDDw0MbUpczamSwYtALKoLLBsQvA9sfr8aWS/6oGqSNesZm1nSIbaZ4I9psV38b1e5OYHeDOqqDAEGU6Oa5FjiIuCEWF9yPtiQ4dzM13WbcJTDUHqcbM/+9R/6DHL//bu/zK//9rw3bz2YCE8JlxGJLan9cORgszGbmTSeSS6WKCzet/aNhT7y53bCxb7LAhqCKsJmHjVKxSbu3C0lECsC97U8hbASWaK7ijs15qyXTt70w3Lcgs2bn1shx2yVsBK4tR1EvU5YvZssboEXvLW3MFx6Zu5sqETELE0gIDjdXN94QTBjMwUDzD3V4E7+5w0BEDDUNTA7x6l4UVeu0/TxUNEh/22K61bXe3z2kMYRGX+pjCrysRkSBBcCzm+uh71MQU9VQOwnsPk/TboxMtC4VpCwmEiUglxIkEkRrnU4nCJha6Kmbg2ClrrnY7ZPbH9z+4G+++e2r12+ev35YV8Re02F3O+4yfF4Wm8+pG9ldi2o1IzWy1Vc3ZqGYupRCzrnUUora6mEHMhCRWq1zHfaxS5GIaq0AtNbT6VhrdfOSS4oJIDInhpmpWowQCSIiIvd391UbxE/ObEZpjLks7krULctCG33UQxeipK6rIQWWEKJxZFtKvx+EynGdf/GbX/U//qN0uDVFCAJny9hFNitrvxRz7iMH8aplWVVrivF6t39ydeN92ve70zpLlD7EmTgNo4C8riRGgj6FpkKIjTyQV3cu2asv6mYdz3M1RwjR3Q6Hq6vrGyIs82lZ5rJOuq7umtK43+9Px+M0L6fjdJwqSwXNpugSYoAwSlbh2MeR3CFGxl0YqMZSbJ0q9cFWUCemVCftrvrVlnXKgQIjxZi6QNdX19N6uh4XFPSEodvtxv2wv/rik88fphzT+WHK57X6sqqpu4JhVKspC5vq6mrrfJyP+2GK0vV7+cGPn/3qr04bMZFBW97Zhd8kYIOaEl9Ql22dandGY5INQ9pWceDSQ/mHHNs03YwQGzn9sXP0voquPRttDducCh9vGO8/oUVTk1ljcjKEwUHQ+iiMtqFQ3mJYW1nDLNXUTBXUcQgU1FyLuUFV3QxuDDf3PqXAQiRK1U1FnFgoSAtEEw4OY2qBFtKyqC6GolvCzPfcq8sS98irp8dV/j0Pscf2IwgsgUnMoSVDYV0UeHH9wRf7zz//aNwF99xiJemC95sCRMKSUhj6ITvXavO8VKNmlLiu0FrXXOYM8uJQ0pabKXDs9uPpeObmvMXYNOSqYGNIgQJg4RDE3FnEGSXrkqeqnXOclpLEY2CrNuniVokcpN2Ap7c314e9ai1lkQgzCiE5SJuUV6VWnZelT4vcdIfxeuyCOD29OtzcfmA1rssitPvNr5+/fPWQJ2NmGFsBEzQDpJJOMZ7UAJerq+7nf/LDjz/affjhhyH4PB9fvXl5nB5qzg/385Mn1+O4J+rXMud5bYz6WpdSlNl3Q1evUPJRFVpzkABBLrrM07IihLrqnF+eXr992fHTyP0XP/jij//Jz1Tt777625cvXv3yF784Lu9ev26xjYDnvkcXMc0oK8pSEQDG518+OZ3O53ktesFDFRBEFE6IAfsdhiv7gx998OGHT//kT//09uZJVXv54tUvf/Vvv/rmq6pY1+UwQILsDvth7CTyaQrqWVIIMThzqbYWU0do8G3Tbjm5I2ecTqtbdKM+dk5aSlHDjgTANE3nec6lmmet5+lUHo4TITH17rlkM81OHthjopgs7rq+65xUGFpqKY1g78IiUZiDqocQStVqpSpymVRLznqec6kIwUpd3ClG6/oRCOSVyGuty7zAZJ2KMGl1duEogSMHEWYzBzx1EVTMKnndHAOYHbbm4l6ur69UzYFhGK5urtdlOZ7m4wRXrMXm/MadheM47Ie+TxxalnJkLqrVdF3XpS651kat3DZXFdYAaCKQV83qqqa11lo3KrwEViMiZmc1swrnlqoMt8ASAkOtWnVoAZHDNJvlKhzq6jFEh8KVI7u7Vlspn9eJHbs0dru0f9LnqSzHmpfsDO4JSlaqslnr+23SExIWczOFO1m0u3en2yeHvh9NjcBjP8QuSeHDPo3XCLHruigMcjWrAE3T6fXrN8syr2olQwRmqhVWkZudBxcJK5F1HYcURQhUa13MjQP3Q1DjaVVXSDM2haqWpqsJMUTGfMrmqqplNVdr7i05h1pXh0enruNnz27MTqstq6EAPZWQeIj0cDopIIKckSsIYEbf9SkOzFGr1oq8WK3eDWkc+1LDybSqqmKeFHAJQi7UCMZADMFMW6ig6lqLSYcQgkMBVdNVbVXqR7AGE1ImKwYiE4TAplCtl3sZkwi1EIXWqG1kFDHAuxR2h2HYp6LLspym9WEYQmA7nR9Sl0Rod+jBdd/h9uoJCO/e3L/+7t13r16Lc2DGwBJCTKHW8vbtm2k+kaGF/xZTaCOywQB2YwCGGsApcRQnd7E0pn4f9ocArsfp+O0LfPjJNQekLp2nZV5zP5RSfZrWVtLAzbUKcwwxhEgc1ShJL2l3vTuEEErJ4zDs97ur4eYwjqmTJzfu7q8Or8bx8PBw7rv+7uH47uHtZLgeUBRcLK0ayboOEppMqsWnA24Gu5/fatW8LqWABZQNnCJjmte16hiQurguXquVzS0S5lAFQoBqbVkkITLsdJzX5RRDjfHq6ZPUj4dSkMtDVV2r5lxAwUF5XUs+TkMZ4g3QEQger25umMpDXKdyNlOAKQDm1Us1J3d1ECMk6dJwnk8gQbNh3rAcmLft0eO2eIuLI2+WP0zGgS0vaoLpvLx98464ENM4jmvBcZpzXtZsqmAOXQJgh31wFuWKZIcPBt5jMIQB64SyNnmMPbx9CBzWebl7fZdiKPNKCDEmEjavsGIOJ1NyYpLILGjUJRZJMWYtW7nHiCGIMHDpyQHwC5fEH+n6LRLNNzTrcRd72aD9vYLw4kH9iK3Q7wB/uPAkNvuF79+OGbq5YtH2VdrrG69NtxQ2YtSqUsWMwKDE3AO1fvLl0+4ghTN3Ujl8/e2bFy/DwwnGwIgo3HcJhepiljkYi0cYoMoSABGEZVmmu9Obl6/2w5VJKahBKLE8LOdamIQbYmVQayEhAYiUYnQ4wXSTZjbvZ9AWyuEKcNMhbQmETtjkmrZBdN8ffun4fl+ogy4GeNjEDY8nluiidNiAo7bhDUxeN14LogMoa4bC1aIE6sPptBHnwKYoCAQAgq4LwpVIzsdTnjIytNSWHMjgxDGwrOtKHNtl1UdVwgVlu2g+m8iZ8L1ZFNwRKBR3coepW4OyjIkhKK6IABD7SKDpnEFAgLMv6zKVOaRkMPVSvbQYzSBCSmVRXy3PBRnIIANLCwp0AQszcYRuHrQb2uMGhdUKB8z5cZtyGZHbLN5W/Nap/j7AvW2XNlBuow29N2A3ELuxWRprkb6/kls7ny48x/db95d5Q0SXwKjHx35nhFzQq3/nBPwPfvzDPyKoF4NzoMjBfSMuNYqRwd1VmBwSgghiUTVT1c2ghSOEhZjh8GajRWAJQYSZG2YqLKaXhYrhqlB3dyP/XufzvRuAg+Etbo8oBnElU6jqdoUYbcxtvxPO7b7KYEjji0IIIBG2LczF3GFErhaYOACg7Z5w4WIyt1hFIYKaKTXjZ2+THti0rN5ybuEgNlZidgJCc7MDYiM1bpCZF7hiWk9+8rIUzNs3hgPMERFOZurOXnQ51lprtw9pkJT63WEsOBGpllVcvFpdm1W0CkijE9HV+OTDD293u2h+dqwimstSajmfVYuxoyz68PY+JpjNSoGowmEo+/3uD3/yo5vbm3t6+B/+p/+xnHBzPez31/en+cXdPe6BiO7q5tkPfvrqm+dW8pqzmSMAPSgwzEASWFKM7sbBAayldimq1hADC6kpOcZhVNV1XuVWsuL+7jikoe/jot7HHkqVYxAuuZzPZwKlrlfXep7nXABpzMCcc86aVjFXgsfUX1/fuPk6zefpVEoRj0GCcAwxEkKMsizr7dPr7krefnf/b/76L3fdfvzRYZDoVru4X2frY6LRK2noBg+Y8nqez8vxfH113ff9p598VMhPNSu4k0gkAfFqPBAjAnXpmS0k7ocegYqZtI2/Vml76eoQAQU3FQ4pIgSRQI0pcLy/W6ajKyJjN0jXdcwcYuSypMR7DjHFECOsCkFgAbLOloJE7MqayXG1vz6M15E7q9qN5Wq4SX7uuNdSQ5VDfHbVydXhmoA155zLmlfm/ZefffmDz/LD6TjPZ3eTGOM4/JOf9a/u7ocXL7599UbLgxLAJMTmxmB2cvVaKouvC47nd9e7a6vWXdF/8c/+6f/6v/wGgLsyTJidBe5WN2fCrelhLSwZ7y2G+HdwmNuj/x5q8/uHODM1a2qFu27rnUGbpM6bQ+Fmzo5HIWHD4x2bgrDdMKx1NYkcIGFmam0PCRxErHG0Ye6VEiKzRE5dSimF1IGpaA0hsbBIKLXmea5LcQXU0BjWABiWdNgNXRfWddVcmbWPQwrDiU7qWkvFoxuEQ3jLHQHBGtH0//+4lGzvo/GbxWf7L2ZpkcuqFdkA5DIRa32L//q//89++pMvht5O0x0otzzrhoGwaho7jtE5mEdRP5/nqjqvBY6m9GdytbJmjwkpJWrBOCRBwpCG887H/bzvMFdYLZzExAmumtUzR8SOUhfcUdpWsLoqzmW9/eDp9PAmn9WSiWCIEsVrUQnoE/7gh59KwKtXr0B2e32lTlUldv3p4aRqd3d1ngsBy+kFW/dHP/85E0WWyOmbb1/9b//qX/ztt8jvNsIdCig4k2sF3HsOpmorrQvlrMg6vZxe/MVf/sv/+S9xgx/+qPv5T3/2wy8/++STnxovZnI+37159yqv51rx9IMUQ9fHUIqz6ZDi0B+GIQjT+Ty/e1sINSZmIfV6mk6xYxbPimnWP//XoYd/+gAAIABJREFU/zrF4e3d6/v711fX+34nP/mjz372x5//t/bfBO6s4uuvv/3lX/366799Mc1rqVW1GqkEDzGEZGBQCObc9PIp0tV1uLndf/jR048/vbm93Y9jWpbzeTrfn797+ebb+7vzV1999fLly1MeJPQpdbdPUowxdEmCqJVqVQ0gI0BVJTiFILGnuLhyNay5EicRL7mcj2tZMfb72CeKdjwXZozjMIz96Xic51oK1nV+l5f7O5sXjL0liutaAYRAzECk5h+uBa7kMAixESqYAzOHICF0zMGd+9FtWglQxWSVUWtFEPRX2O36FIK7hRiEKLBU6dTqOtdlOgkvD29mgjmMmGJGDH3qo5qRAFRAxbEs6yyEGKQjZhIzXxY/nfHDL3fVAJLrm2fPPv70//o//+/jNA0Drdk5MHMs6lX97nT3MHFgiYwUgwBrWc5zGcY+dYkjrWsua2vFMRNJSCBoNTNXN3NtkomuYxEB4e71fWtymcIMVsHCLAw1g3ggRhRp0t3s5iwsDM1WSkVFDd5KoxAtpOaYrOs6lTUvstxcXQ/7/uoDVz/WucJBHZGxwY2K87Zw2tYOZTCZM6pV899+8+rDD5998Kyv9dz3fYxCZIHjZ59+FIauqOW1rLmuWZMrJNSSp/NynjYj/yZ8YnZmM0NZUIqveTKL+32MSbo+kFPOuWQN0oswSc+8LqvV2nwk6vn8wBxDCH1K4qJdJm1q6Y1DYIBazWVhL7FoP3T7q/H65urTzz94++bNsq4pxsNhP467h4e7cTfWmu/u7td8ZhZzSqGHplpQMszq6ZjV0QXu4zCkGAjzcqymIYDc61qq5vN5UkXfjxKDKfqYuk787Lnm4/Fo5yMcWsAOL1gmPL0dUEOZbaKsXplCismJlvPq2baCuKqzgcnJnMkvG20l54T+Oh6eDMS4O715/uKbu4d52KPUuq682z+JXVhn6rru6vq6C8Obl2+ff/2yruhSYgoMBrmZrrqaVcBJIRzSLlEoVt0KYAhdi9DaHOURwD217o6kdP3B1XiVOJW53j3crRbWbmeH6+FwNeRSSvF5KXmxvFrOuN3vQELEVs3do3Qp9MyxiDFzL6OW6pO9/O7d3y7fzNN8XND8v+HAAZ9+ED/77ItnTz/47LPP+iEVXX75q788zff9KF1nw0AhOglrxbpYyXWdGoEnfPfdGQRVmEMERiWXYop5gjlCrF1PEih14ZNPnr4Ox7oyacnThJhiYjcFIzAcVhddJrx+cz8e6rB72u2ukgWcvepUaj5PBeQGPp3mN2+069YffDoOYVxzydl2+9vdPu5vZoqvzqd8OlUnI/c2pKGNJhDSMAzjYdaVqLFY3a05DMHc3XnbRDgZeYsmBAk7swuc4FZXHQ6prOXF89em89MPrw67HY7Ld9PUxFdvjlm8aCfvltP5ivuhf5jO3Y6effjxn/wnP/67r948vDmnI3W4rifdd+Pd2/O0Ll6NvJ51hQFSVykUNg8YDsQhcHIRTjE4NOdaaxXhcT+yrKUWqDFx6CIRN3auuqt7basUb3akF+Mlx/tsrMtxQS3+HaXjo5zQL0bZ7+3GGW03R/CLxc/7oIC91z9tnIi2PzRzbWwGcMnZ0cmQKFnxBTP++X/3X334w4S0zou+u5+/fo7TCR4pJPS7OA4dGZbTspxXKiFQgpJZJSgT5cU9KAjHu4f/98//zZ/8lz968fobh/RdX87reQHUQmAa2KGmrlK3TKEE4gZFkLi4u4CNgm6UWXNVVzdDSwDnR38JB2hz7/57NaT79wnW22km8jYiNyyRgXb+Ht/LH89ZBAsHZfNKUOcBlnF8OC7L3PzOhAMEAFV3MYtuzl6tFi+hSwx3xek4zacVpXXsiJkDhygxhW49l/f0Ug3C2dzHgYuDrdOFDPPoLQUnJ5No5F43c283OJtXREAUBLmBd+U052nJxOAEJT0v51Odbm6utGqeS16yr0AFCMFFi1ltWEUD71qHATBYMVclMUYkcAuBc93+wBzNdF59Ewm2k7thrdvqzrKJIrez3G7E5q7N2psBmBpZI2ESNvjXjS98HYI4g9jE3MEmTgRHQDRYu4hbxlPbJhARkEth5kfi1ftCwmZah98Fuf4xHKG5CjTveaAZt7T2G2AGJiNqqOYW8wtqu1N3CEuzIXd39XYThIVazJiZWcGR4cTugYUDAkPZ1cz0Mocu2CARX/zDCLCW2tVojbZdeeCSvHDxXQY1S0veuLTu1U2UiPmCUAHNus7dyeoGdL63ifZt2PgFYG6A85bn1QBtNyIS4ep1ey0ZOBoBASRwAgQkG6vLHeJs2YS4KvJU2LbP9tbc2aQ+BCO4e3IORIa61nVe+kMY+2AWWSivmTKmeR5TL2CvKhSUlZlIScKZ+HB9tXePuRwJMYlAz2UusXNSzjPtB6iakEticgsiRBj68fr6JqL/m1/gdg8rc15RzW6u92G3m0s+T/N3Xz8v89Ju+0yEVkATUaCSi2pRU7WSUuh3PYWp69M8FxHp+gB2K9Z3aVnWWgsAAqlm5n2MqUXPiEQCTPWoD6WWXAuFoGZqNowHACRi7jrPVutStNYqgYjDbndIIZQxx7tYShYKVj2vtVQvddWKwDSMQ6w8ddPb6fzLb77+4MnHP/noy5ynBE6hF4ZTHdNeUqfiRd9pLss0f/rRRyHG/TDuxyFPdspLlACD5RLAphVa3aq49yH0URRm7gEkToVCSJ2oi2tKQz+M86KllihsxK71OJ3P03ldCjm6iL6P/RDd7f7+ndZyf386noozRlCIUaQTeM354f6cl2+H1Pfc7YfDrt8fho+eXj+LnLQ0NN2FRl1wOj5MRz7eBFWd7qZx3IvsQgxxlKc3H3QIBdMQdhaO6zrp6m704e2nhH4+6/FhPctiUpMED1pKafx1d3VVEhbBmpfjfL9Svhqffvnjz3GNbkYp1prwALm2rgFczWHSeERbm+0xOAa+hTw04tR79cjvrYq/R6YCO4iJ6fKyC3t26zU1+0Iiwu/Ygvr3KwGA9+qi9+/jROLSeKduBietarDarOOYhl0KIiGEIIFFGtcsUBCJ3LJR1H1xnxzaEuMbtwsg5KmMqUdkgL3VZgAb3FCrmWUSCjG0n8PUvKxc6aLQ9vf/boDbJo1s9g3k5JtZPi76wkvzxsnbXccAZmK1UpoY8o9+/rMnT/pc35VcOHg1MyMWCSFV96vdQd19rd7C6xOGHmpzrcXMmJESiwgzhygpRXhhQpIoFMusfR9vb+nJ9fS6rtOcETgIg0ytwgsnsABeW5nBzLFncTKnIL2EQesSAw+D7DoRqaZ6+2R3uAq7LhznY81LkjjuDncPp3VVp+50tlrK8VSO94gBEaHvrq8OH8zHKZ/s7en06188/+orWEYUlLp1S4J1LDEIrCoUtubadO6tD9NHFpiVGPj+tf2yPH94m3/0R/n2w93N9Uclq5ZX64quw+mYD3tJfRfEPaYhRQ5jXyKZn7pQ1rdFIcE4gAVQy4uRICXuY1Ql5fr67XcPx1ch8A+/+OSzzz6+vb5KMcIzWfjpTz/98osP17ku83qcjvMyzct8f3y4v7//4g9+sCxrrsohpNRJiF7UtO52aRgChbqsdw+nebcbWfT++O7lizevvnt48eLN+QTlGmLZ8slJVWclNVeQDQNYULWUvLCwmUsIMXVWyCvlVWNgVdQCU2gtpLU6hd73+y4lIkLOxd2bIhYeS/Z1tjzB1toHzxUhIIjEIH0fYkQtc17q+TQJnMckEoMEQiRyU9TsxFqKpq7LWUMKodRaoQ5mjDv0XRqGDo5aHW7LvLb7txuV7KVksnp6ADy3hYBjdvXxaig5C4MZoAqqc64MdNWqIIoHcREW2DDszcBi6lwrvXh5v644L14MIThYSynVEATMqEAVEMVKtmY9ZsS99R27mVWvXN0ZblG61AUHZ1uKmlYl22jz0olwAOzhAYgeA4uEThibAy2TV1Y2h7uFEAMHIRQvkUIQyVqWUuBMxu6AmglZJcDdPOc6L1htEZFdt0tj3N2OtTyUGdrkFQJlpxZY4ZsTrZkTC5k7SuA43xcrElOnvqauB+q8zO467Ha7m6tpXmotpay5qGrtuiGlkLqgpswCd4mdKgEWgpl6KVXda8HxoTDTbu9WwYHgBGKCaVVh+eDZjRY7nedpzvOi6wTi0rkHd/MaIxTGAexgonEM3YDUkVq2mg2ihrUghtQPdnUjXWZmGne828nu8GGQ8O7dfa22LhRjcOO1+vlYidiMa7Vl9qolhLAu2g0cYuy8j2YpRjd2kK+FKVijk1R155SGfuyZZV2X1daKYkaJPLAgOlCvbq6sYA21as3FCwoHJgm+anM9Aqh58vhm1Oib3Qwh7SABYQD3Zq6rzotPJJgn9Ht0vUhQIuqHuNsNbOH0cDqeH1qHt9v1mq3molqdLMbgMYLBsZMgMUXpQs3V1BiIIs14ydSqq4gokZOGGLuxlzGq2FLmXHN1VEO1Cqbdfm/G5/Pqxo3hOPSJKabYA7LqqqZdHPbDwQsf63me1+Myr0uZp6Vx25YZLeY4Bg5R6lzefVtsfvXu+uShPnl6/dGnNz/64ef35y70Cl45qFrNaykr8mJ59bKKSICGoYsSqKX4EVOKIhLcIWK1VHOvWknkcNU/eToG4Yf7ucx6WnLq6fp6cG1wSyG47AIzrq4DRzmv89t37yRaTP1Acc06z3fzmmOMtRIBywxzXrO/fvPw8ru7m92u70Padc8++3B/rutvn5c1B5EQGXCYq6LZES91gTT6OjU2xYVN1Coqa+nO1oBNB9gBIhN3kEdX62LPMdQ6zfOsZZAWXQUMfc8VD+cZiFX54ehryfurk4esPnf78Sd//MP78/z23R0Et1dX37x568pUHKt10gnFuczEcHMjF5FuTP2uGw59t0/PXz6PwiDOtWiptdZIXZ+6gSTWUkrh5n9KGxqxGZADIEizDQa7mTM3isTv2JX+Q45HxeAjvWsr7uixqWcXrxhvdPNGI/LvpQJ0kTUSsbuaNf1KUK8MQWD1rLzgCn/2n/58ou9e3L399uWrV28e1jVdXz3xmo3uhtDnOedVl3OuGcESPDZQgNiEyYpz4BSC1vrV1/M/u/34u7dvxGrNfn9/hiNEkBMHQosESU6BoODE83QWMJypqZs4MBwBbmaKLYht2/puJubYGD2P9eH75wxE7tgs0oELHW172qYfxCZ6o81l6pEAZfAt524TP5krFtRaui6mviu2lGybW77BtvBVM6BqdTct2qVecDZbwCBmMhYiAdFWMF/0j82MyIx+D8h02mR3tOEC22+USm5kRnDSprFssQICoCLiyZMxYz6ecykqvUgvHFlD7WOk6ASKkVFjzaaqWddq0kkXk2SZxTkGEQsM0mpmqqrm2cCB4pYe18xEGltOaRuZdmm2ty96uWCNDBe2E/79Hsad3JoZC6iZLzldyFQbd26T314odgQCo0GcZs72SNbi9kq64B2Xq37h6lyYVvrIQLwc/9jQKwABAv4e2wQ19Khqe0gaLgSrDnHiNl9YGu2QAgMgIiMnazpsQLHR9Rr7taH0QizNDpRqNW6aH+B92qc7mjTTzN3Nm4G6A4ImfrvMWee0jVaDO6PpXr2Fdzkak9KB76dqYxkSqHlnbY9fKHn+vZE0bSbwm/2bwuAgdiKAWhjXVtKBGQJi8kBNcUC8wV+RJEhA9d24TyWtx9cRMXsRF/NGFIYTmImFqyobRwnMXnIty2olppQOu0HVT+d5zXU/7PfjiOpznTxbdjOl5Q4Pb/I6l+4nz2KUdTFhSqkXklI8MgUXNhr6eJpWZkohFvOYumHYPbn9MEj/m99+jYIgyS2ty2ooLMEXhRqpuxafCzHFGDmwsxd3K5pRAO9i6rthLR5E2rCW0CSABHhey37o4QpX4WBmBOzGQ0qBiYdhZApdiinGqsVgpZSQYsuAlcDE1QBigXtj25K4kocYKURQiLHvQi+QdZ3VPUiEoWhZ8zo93N9e38xpLiqS4sr021cvPnvz8gcffckxmdPY78hMNUfpJCQVX8t67gYyBCYrmeB9il2R07xElmmdl2mKMajmnBfLmaCBiM1zzaZV3KWNCUnmJefMYqXU83E5TTmm2A09s5plsxID+i5dH8ahi1EArQ/H+6v9AQALWCQEbtMscko8sPcf3Dy5PdyMadj1u0hpjAfP/Wmu87QKx1/+4uuSqxc93Z3n4/ry11YWTbHrxyGEICGS8/7q0I+Bpcbehl04XI/Xt/txN+Yy79LNR7dWMwTpeD4plZXmZVlqtaK11BWqBAxjUNfTdDdEu7m5AZc/+/nnz3/z8PK7By3GLK5wVebARN5kOLRZiT/eLun/Y+7NeiXNsvO8NezhGyLiDDlWZXVXdzXZ7EGkRIoiZUM2DBkWIIEG7Ev7yoD9E3zhP+ALXdm/wFf+E/aNbAmkCdkS6SZNdZPdNXQNmSfz5Bki4hv2sNbyxY6TVU1BgC4MWIFC5slTefKc+CK+vdde63nf9xRzDHb6H21n+jc2sP71x8Nyrw/IbPNdAj0VLadd4OHbfaNLbWbWzPJajwu+1uCdQmUMAMgIyKqC1ArIYtJs1wTNd6agYiLVNOVaBAEJHRGHEJyLlhATQUYUbFX7O3t4TZrnSshqRsCEVmuRCiUV0yoGqM3FiwCsPTl4tzPZw3/vduZ3H9gDbQW/Ev387jqLnNY1awkZ3iGAST3bxCfvpUfnZx5rFnMcoDmZEvfD4IOuOXfdsKxJqklRDBxjrGZiNs/GnEOE7bYLMQAZOm4/JzO54Bj4cDcxDWdn49OnVWSebw9q2bNHhlwqIPiATZxhBEjomKMPzMGM05qHvg9j10WMrjpYievZ2fjixeN+DIfD28NxX+sc/EDkwXia1uMsh2OqAqU4tbrptk8fP37+9INpn15/df/m87vbm8PLqzeQoecBkFjNkKWoFABlNZNUFQGEI3WITlAFwSpKKeQYK+7frnevrz95fX2c0qP3dh98+yKG8Tvf+bXj4X5ZD9PxjVbRWhFdCL5zPfneF3aEQ+/X9TDNRVtREyK7kEtdUl6yZNZAMyOL1u0ueLCvXn++rPePLy4vL7dD3zH6Lg5n5xvd+mkCd1x3tgEa1zwep62PMRfKVQDJgGquudbGPSZZlsP+uBxKXnwgH/yTy/e3Z+eHveTy9v4AIoVdAQT2MGz62Dl00HUudEOIBCwCRbXkgqWKIbIP3mMxA4W7t5OIigAZoLcMKliHaLvNwGyHwxGOgCgI5tgDdN5jF2tZc11L7bkWMQVHhqDMBgAqEMx5ighiSlVMKwJArTXX7JjIs6juzs+YfT/0zJJzyWJs6JgcM5jWWkuuVcHaDuGjGYqgFDQhrU4ritWqBjM4v3BgF3j0XYjkvKlRiJAWWIoiQBfhbBd327Hzjn3vkZ3S3f3+iy+vjjMYkggGF2OM1QSMHQI7NCtSKiKSR0bMApeb4IJLlnOWrKXb9I79uhSpupYsFdZlVQNPgdnlstZSGJVMS113ZwMSEjKRhxN5gSLmtICZFGnh5t4hCGlBRmCkYCygRRCxadwVCqiqGmRR5tOyXItkzs6H8axnovm4pmMuqwIhiIARGrXVsRnqoVLDXykEmEqtWtWQ3LjZHKe7Ja0i2XXuAW1QlVxLQjTnPTHFwKZOjUSMiNl5cqYCIkoplVKIcV2k6ywtWgYLRMwxmOSqaV2d98P5OQ2M2DwHpHowA9NaclUB16aBBM5DCNyNPnbAHopkxkLOFMqachEAUN+hj8TO9ZFih2mVUm2Z0zKJVPBMYIGwL7lpnVAq1gLLKgBL1wVRJqfOOUSU6kqxIgoGntk5F0JUNUMMoevCAAreh6DFQEVERR0RAcYg49iZove1ATbrmhWqgahrSjFANOATbdBQWvJAzIry6Pkomt1o6AVBesdnFz72pVbYnQXiMk235+fnj589dxyvX97e3d+kUn3nk9RlXkRMpYLZqS1pKEVVi6gyszFjh86A2hEMsJXkAOQHX9dU1Th6Hni1JNNa9OB87QfYnoUQvZkQBR+jr1iSEkPf++A6LTQf17wWH8J2u+1CX1Y5XN/vb6f9fl7XLBWkgieHRiiOUUnVITKRw7P93XE5HsL1gQMwwuPHm0dPd6GX43rbLI5b7U+GvR8j9uKC424cu1qy84KutHRfM9dioWC0lLKpKNQYGEydK9szJufWRV3vzrZ9DEhAIphTNYXNOMSO+56d12k9fPblZz7i40fnF2c7HzaGfUqzAYUYtmc1LZUoLsd6fX1/9Sql7XU/bsLGj/122JwdpvX+7g4eOipoVovVDKmmVApz80755rCNwE5Bck3k1shzIEBrflmne1Yq1GLRgyOqWZdpUQA12Y599ONkeraYcx0hE80pzXf3C7nsfHUvv/z2937j8vl4c90fa3ERr97e8oF1NVsJAzAyF0KCygqoWkRyrYFEnIrrh2iqpZRccikVFQhF0Jx3RqBmKlrbS6CqKie8vLna6Ykga/M2IjjJJf9tHvhQGto3P/ONP7/rtiAycyuhzEBFrJ0uT/DLr3R2mKktNUiEBlqNWBG1Qn10OVx+SMOZu72brq5ff/zpVzf3q9l5d3k5lPuU18jx5eu3sAZZAWAA6lRIJAGIYxEEA3bM6DygpSKMI1OvWNZFbm/3QBCHIEaEgALmgCKiEVRgj3aECgqqD6dxUoKHYvDUIkQ6gVMIYPJ1D+vfdAXxZKH6wFgZPmQ6NqN7Q3yYSjcqyADRmogVRM2aZM6jd0CiRWOM5+dnm+2ksJdyMgg6ETLYcuEAAJe1rAn6ru9CR7QAA7NvP7WaSa0PlkOnW0EemJKvX+jTU9ZW+qoSYuOwgJSwEioa6AOgRXY6whuQdWf8+P1HwnJ/dwAD3wXXMTpzkcbNBhnEqSAyuCySyqJVpSq6gci1NoedMEkAAWtaryZ5aKWtIZhRm2qc7PYR9dQ1BTidgU7txnduVu/Qp3epBd949bTZnFi7+g8NqPZqI4oK4rvmCqDRA7BmDy9ze7MbgP11iQvCN1W6RGQPGQjvIIB/5xpYFEgVTFSbxB4QiJDNFIjJEQNii0qFdv9T6xiZvmuLApABE5t7OCq1lVYNoFQxYkZEpIBIZEgEKszW+qWng+TXuBO0PD1DRGQGA1JzxnYirUxMvPcK0pJlT6JwxNMb/DQ5NABgImxnQjudaw3hYfk/qUTVDEzhBOoqwMlhWk0ajIotvJOImUhBEYEAiICQiY1FCZDpHYlmpsyemTVZx513HkqjPYmUWgcNAEiZjFuaokKBagoqJ+WQOUZ2QdVyylLq0MWx7/NSDqukOQNAKZoXAIRF732sQ4+lHM/Pxu2m2wy7eSqOnJGRofdeNQGQ9wGqetfFOIzDbl3kD//p/wE9IEREp7oQw7pO+8MEASB2ZtgCXEFbbQiIpoRtLBD7OIwDrNU5zrWkKkTknHOeiVFSdn6cp0VNx6FLKaHBo4tLVU1rCj6u8+JD8M4xu3EcRQEJRc0Tha6b1qSip7gaMSQiT8HB2A8xDlK0sPQhet+pGokEF6OPbAKqN7fTwkyKHgOJA81W8cvXr7968frZ2aMI7MAhNvkZIpAn6mJ/ttnqMJiaSI2ezzabFerb6QAAx/1xXebNdgCtQNJ5b4jecU15Ou4zVOfYM5sCIovIkjOyN8j7/XR3gM1YfGBmRqxM0Pdxu93ttqNDBa2SFcCcIx9gJAgxEDtRyQLOxbHvN8P22y++/ejsMlCQDMfb+bMvX83HdHe9n/aL9/3/8k9/cmpwTAAzPH4B17cAAtA97OgTgAfoIXbw4fP4nW9/58MP33/67LIb/Qffeh633ZPzp9H1Y9y8uble6nGqdweklDImVCgiVlLtd2Fd03G+Hy52LtL17Zvf+e2/+X8df3p1vTetxA4NQKD5G9QqpkZ0SoH+ZlVwKodPylw9TR8Avv4NfuUv/7WSAgGknnrTrQX8oMrWd40xeNejevj4XSGI7/JoTv8+nhwPT3XUOyAMW1GD32jr51zYkaoCYCm1LKfyisj3QbsOtQhUpMJYzYBP5opiAOCAc8pt1h1ijyWVrHmdtWibGrWCrh0W3m11J2JNH66Pff2Evl41H64LnmYx764TQMOMCU7ZhHZ6Qp2D58/O//bv/ZiA0ppqqd7HqlKrAmLXj2om07H5mwEgIIE1g6dWdSoibDfjdjtIraVWyiBVyKrnnh2RgJmKlhjHx48vELdffnFQEUTynsWQ0IYhxD5UK4amyEAcYvS+F8XpcH++GfuOyBarC1KOAR4/Gs52vh/jL37xc0UgYO9drWrAh8PxMM2AYIYqtBn7Z4/f++CDF7vNxf/9L//0+tXdLz/+/HCAzsVIvVaQVdh16IJJ0SoGjAAgRbUQIDCT81LFmumRITkvZgAOsPoMf/6zT+EX8MMfXbz/4tGH333adzSvFlxSrWvKDi2GUxcfQTvvoh+XR2fDsBSxvh/Yd1VpXSsel8N+Ohzzs4vu7nhQm8bN4xBiKfPV9durq/9nM5w/evT44uw8+tD3Iyqv8zovxypi1HqScnv8KpWSUskiOefjdCyrEfabsWcPOe3XnA1gM/bDsLk4h9hvt2dwcb6KHK+uZgAAghj8pt9uznsfEJymcgQW0QKmRIqISOC9qw4qWa2l5rocFRig2cSoxcje+xirD6xac6mIECP7wCpequ/j4C6do3x3u1erbdRVqxJBLeYYHQXP3nMUzbVISVnVA9i8zOuaXKCuj+xYBYjcZgywoZRrSpVBsSWb5CpSzZpREwJ7Im+i1FABYaukBQEcmpgpGAeO/RjAFcOEZP1AwHE5UFpMysrsurg5253vdpvDlLuuZ3KHw/r5F1e1gJhpJdcF7zspyUDYUQxUBEquaoYEzIQEZ4+GVHVd1rVkBeg9O++oSBGppllqrQKI7EKgaGJI4F0XvFPVzWasolJUy4lVQGPddFt1AAAgAElEQVRQsEIGIlVUKiq66KGalSoKJERInYtlyXYSzrAZiIgZEINjH0fySESUc6mkwYXxfPAxzG5Z9kmSlqSnfhm0tRqYHChrBXDOkMDDUtLhOHcdXl5cVEt88KUuOad5nkQVCZxnr95775hFwDtXWMpaazVmCMGzg1qMSGqVWpUQU5W0yjznridkzxwRRSSbQc5lnWcfAph1wSFS8KoKKpZSqcm6EWoCZkDz3ofYORcESAAVGYBMsRJClWJWCE8R2bmASL27mYji/n6qpfRx28W+VDLz8zHnXFpA0JrqsqhqHcYFyYdozhszOufSmpZpWZayroZkJWhLq2d2tUitlRiHsXcec87LsrRxrPMgVpG878L2AtERH5eSa87F9WAOVIAMjBsZAc459uQC++DRwcXTIeeFmIArE2zP+gpnKa0G6j1Xycy82XQh8LKsd4e743woCaG4lKtWeOdyK2BSChAAegDLVonMe44xOOfMtJZVpKrJCf7iIq4agHhJmm2tpc7oCnc4bvzZxS5EX6XmtUxTnacCRgCsosdl0YLztIDhOG4d+/398XB9vL+a1qnm5d14qhlPqiAye0ICIBH0fQQsZKJFs5bj/fHN1fW4dTHG67dr7EkBEVznA4Nn3VUZ0sIilleryYjBAzM7AZWKVVRq8c4hg3PUD67vQ0oppfvQIzKQ0815Pw6eyuocEVKtnYowE7FxUHRaU71f9vVYilXvveO42z6u9RaJQ4zkROpihkuq05LXAvvjfFyTW/BsV588ff7sxbN+iLd3t2s6MKG9O9wLgJq0U27buwlB6AErUbBTbE3z2WwiI7MWTUYIDIiH+7kK9BuTCmldyROzf3R5npPNWIdxJHO1QAzbLLasqVRec/nll59efvDesxcXadK/On42LQdYQIp68IiMBRAsQlBVHlyNUrWuaV5lvi/3/siPnz5el7lKFamAELwjxVIKOCxVcikGzaNGRRRET0AMo0MiZVIyBUBCNEIUfLBh+pWa8K8bS5gZN6LiAVFvXT0iPCEU7ZQHTWPW0n5Q4dRObsc9+5VC0xrkQMRmIiJgpGJSDchIBSi/+ODFf/QPf/vu+ObN25dffvXyzc1Si88ZnZ9LnZEt9iEtBmsGiewHlk60Vk1MAA5UEuEGFLWCitv1ssyK0LMLYOs0V0bnfQcRAAUUsILvHRpiISJqm2/rRJxW6SYvbVNYRGBGbGWxkoEQPBCd7Yz8K7X2Sf+ED2R/u2CIhkAPVkrv+lr4wJqcvvYEliAjmqKgmWor29lz7IMPTKzgnRVAJvbiA7NzRI6hhBDSUqGCZ4/ISAgMhIR06gepqp1kHafuwKma16/lGQ/z6hOyitRkVideTEub7SIiMZoQAxOgGisEePT80YsP36+a5pdfGls3dhwh2YyI3eBTzmZVVFUAwZicMYBYqVVVm0JTRJqzFSudtks0JK5ZsYUDGICiKYCc3DUbjEZgAKhmAvqNpwEAIPJwHnlX4iM0DAjARLT5tn3zTjhhgwBVKhDow4GonWgITnJaAraHfhTgOwLs9Bs7B3YCrwBaKGf7ecTetUd+9Qz1//vDOedqzSLNUgaMuMUyYHOz8h7MpFQoRkZM3BpYesIurdkem5mhBXYtEN7ARAGaxZxVUSHw5LTlCJxoJrHTkoxoD82rhsYagSoSITmGBqtSkxMSoJqCCyza4mVPOEJrOZ+6YO3ROCk2M2xR80ZgiEzcbpK2Bmh7MaRxlwYIxkCMBs2w3hAI2z3FbEpI1OSU2KydGYDM2jdCasLu9s44LvNjMTaGFYpmEm5LB55WUWJkdg4RkkpaMjBADzEEZiJmYgbjLggo1VTMW1nyOpX5oOwBHVGHCmKKb9/eT1FjtPPdJsZ+6AetiYitVqjmmKSCsXFbv41AGcRP++Vf/vOf9Q5SUlQxtTj2IJaXlbz34EpaAcCqlloAwNjAAXbMRDWXGRdDXNIyjL3zrjePRKrVuX7Y9DFGQtjPd95FIs45e3a73W6Zlrub23B2vj/s+24gROepqYZEzKS6EDa77TAtKaV1TSJFVBlRRFNah9CZyrSsJWUbVUrNqbJD7/zQj4CWvTseunmdFagPI5QspC76N8f7X3z1xXY86zisRQJRTlZFGZkYHFAfovfOVBAseK/OH8tS1iWpzffH43Tv0dhZ3wcOAQAD8/543N/dGdq42/rOqwLSyWiM0XlmJogeugBDcOCIQMEghDAMXeddLatqQdYY3eF4n1JxnrrozXA+HDRDHAYeQheG3fAo+p2scndz+OIXL3/65x+/eXl3/yblFfoNwz0AQAhsYDVq75+NfAMEwXdN07K3AyGQGUz180/K9Vef/vmffoGAX94d//E//m+eh/Hy0ZNxuKhCx8OaNUXuEiZFt1gyEVVLBfCMVWHJwN77Hm/uX330az/62U9+CQAKRi02qcVynoKd2419omDt684QIDYNf9v4HpgqE9Gva4jT0PEb1Ur7DAHIQ0oTERAjMbdWmDWp8deVyGn+dopQeti1v17y7WFzsAZ4PsQMGxIgkPPkixFTBjNkqGIMwOwImZBRSq0KFVFAq0pWLaZFrShWRNQWFoOEZhpCTLJCLiGELkYitJKXWto1eGepaWCmWLWAICud1JDfEFI+zGJPe3N7ikiEYqfqBaGl6CIAAIMoskdkQBWrJgnEsofN1v3u3/mtXOa17IutrkOpmlIChG7wjpDWudkQBPbB1wKQUlqm45pSSQIM4yZ2XTzuc0orKBMDQtl0A5NTMx95WVbivN11jiMgQILcl8ACqN5D32McuKgpQlUQMHIIJLXUrqPYA2Ce9vta0vkWXIAYrdYZAO7u1+2OiQMxllSYXUrw+rpc7DpELEmGs/58e/7o/BEq/cmf/Jksrhz9eizdRTDDtGRR8gCkVotqVReQmc05UiulWF3VRIBC9D44NSl1LWvGaNvdEKPLmPYl3e6P83JgJ0+fb588fj8w37693h/vBTVwBBMp6zoXZtd3/fnF2G+DGfTDrgjc3E5m0ra3Kvn2eHAMm7PtuNu4CCrZYTwe5OWnd7eHu9/49Y/Ot+dYsfPdsA2uH27vbq/fvtkfDlkl9EMuRRUMnSFRGMiqVFukMICRowBm1dhXJHU4jJsnLs5lxY5u9zMjFAMMJfY8biIHEE2Hac1lBdYQAAy6fhsA0CQtuZTlOKVyNAjQR5AKeQ9lhTqmYdhuNoFZzHQz9l0fYhdLlmWWXCn2vdvsOs5Q7frtVyAgDhy7Yegudn2MVGVlspTyuk7MoLVx0pqWtKwQTfseYnS1FATt+z523ZrLuiYyqznNx5zyIgJNcOVdF30fQ5SqJSkoq8C6ZJBTjluzXAnBj3005jlnKTVs4i6EbRfWVY73wAQ+OB981/Wvrl4PvXUR9vv08cd7YliKcSDvuhj6VNWsMDkg0pqLADG00WwFMEAmF0KvQlJqaSBWrsH53e5cK97CXSlVshaoUg2Ugu+GvvPkl+NaSi1LKakl0hlTIPancVvNJqJVAnswZ4KixgjBO+f9QWaCgOgUG6ZqStp1/TD0XfQIkOb5eJykaozdbtyG3pvGUkqqxcgM8oOPgyEwEaKQqAChYQEPyzrf3L59/HizO3t/yfvh2CsmA13XpYHYIXpAC97H6GoxHx3lrCJgGDyH4IqC1loVpUouxRuDwJp0nqdhxDhQ8GjMpSITLskO9/cuOgPwLoTYIXAVWJdcJC8A37kYl3UpCVW5/fvEyg59CNiip8W6LsSAVVRLFbFaispaKi5HCx5Eqvc8bPvObw7HdH+YD/tpPq7E7LwzqDkrAKS0dgV9IFURKd/7zkdXr27WOadlub8DESECKQAODvdL7NC7MGzGYbMJzpVV0pzmdWrbkGgJPobQxyEY9dWqQAWz4EAC5BWkAhKE0GAN9MF3fQidJ29xYCUQzcUqA3XDdmshJF3Xpcq83Y2PLh93XT/N+1cvb+/e3jL5CrLm4kNIKbczOjH1MXZDB+STgJrVWkULOef7vuuDaJFZZZ2VjYnQ0ZLWtmdVqFamUjOhdh6MjXuKkZl5LeVwnO9ul+PBxj52oV/X/PZqPdzBBy92L97/IPhw8/btZ598udyAJmidCmqwcDHyHXvXn3x+AEFEcF0l+C5EMEy1lJvXJcvLi8uz5986B/XjsJ3TlHPyvnfmQKMWPR6nu/uD1ExhHc2N5EPwwXllDMhGxoRqNTjuhw7ROvOlpOg9ok3T6jyIVOfEBxdjz+SK2PFwmJalaBxG9r2Po5tvy9u7u912vNxd7i52gpJzMQArYgqlakpVQNCBGk1LwgTz/OVmd/78+XvD2E/zcX+n4FowGgAiBAZjKLkZD53meIygZKAPIEXTfdRWEuhDugwYIUKgbtnvQSH0zTsLidAFPwybt28OOWfPoxQwo+3uTIzZH7fbYRjpbj9dvX759NGLzbi5uql0dwWGm6GDqQNEWWtRdd6BlTSnkiuQgQcO3Hddt+sdsZlJrWoQ2Xddb5mWdQWElFNZExAhobXTVmMMCYjBkbd8CgNsvYeGmZwO1+8YtCZL/9UT7Lsqsf11AaWWaN8k2fYQOA8AWpGYOSA111pRAW6WyqejfPt+2CooZhAgqKpmhNziIxQrVNs+Cn/z7/zG2/kXt/u7u/vJFIZ++/p6ud3fs5dNpMe7AQSgGEEf/YbArXo0FXRAjEXBMYtZSdWlctFvp+nIwC7E4tnESU0Q0Dm29rJ7wNjAoQpoEAAEoKCpFatgpATK0vpMLcIMEaF5qL6ToGI7tysYf2PYebqGX7cGEZp7+De6FF/X4w9/MHgAhhiAmRhNgFS1FCUroFDKmmvNVbJZF50okGdwys6xcxiYzAczP+eEtdppYsitr/MgUpRm+UbvlAZw8iWBB10CNG6MwPhU8IPBySwQCUCbfTYa8AlmQt/orAI9jBfj8w8e393fH+qkBKH3ELTmqlnAzoJzslatYkbMxLEzolRTXhaohIzBBapoVlsu0YmcQgOBWpRRT1Ymog3s4cayna4loYJCPV1i+/pKa/tcO+bgqTeHSORYRdvtQ0TvjgGnlkozLrUHvRo0Uq6iUfPvbu1JRBR86LY00yM7sVjMrCIqpqbfNMNqv8Kvtsz+HXng5u9GM6kKBobOETtQW5YZ6imIwIeu87Ezb9mWKaWUVMWxQ4bNdpMlFy0CFUjBIxBWEEA8aWIZQwxMrKLNgBYQmZ1nToeVoc0MCBwSOXiQRjdBLgMgkqqCaAMKGzIOpiHGRngpmjSIClTb8oMPkl8E4BNKh9RkgwiA3kVVFVWQ2lZ3IMAHlINOLhNQzb4BlZ4IPSCCABgdReLozINRqZjazUWD11qYPZPLx+WDZ9+O5ufr48vPriBDcB6UT6J2QEEDBojYbzwEndN+93Rbq7ph+vHf+v5PP/5LF4Z+3GkRNvq197/T+/7w1fq//bM/3jx11eo6A3nYnPvYU+xlu41Dz+MYz3bj08dPDrd7T+Hu5v6Tz764uofNWUcmWqoV+f3f+t0Pnnz0t378e5/94ov/8b//nzIeJCEazVOF5mXU2umIyCSpnN4mjCEE10d1ssKMBOTZRc+egEysbjfDuBmZcOg6drSmZdrfrWn1rju7GJ89e7a/OZjq2Pcp56urV5fnl6XIzd312cX57nKXU96dne3v9q/fXiPR++9/UKsC4OFw+OXnX15cXIBZ791utwGALsSL8/PgXMl5Pk7zfOh86PpepR7mW+jTk2ePLnaXUmG6T7CYl8iFfuP97/3Xf/BfWa1PhguVfLh7q7bc3L969HzHQW6nt3eHu835hSL6voscj3b86cc/++SLz798+2ZdFufgvfeeXTza+sC5pPvD/vXNq3lNS0776fj2Pr336+9Na1IRM6giac051SoGYI7982fvresKgNvdJQDd3b8+Hm+YLUYGKIzUdR1TTKlKgWHYXm7fe3T2wdiNm35nhb767Oqf/K9/9K/+xcuW8cdClkGb36F/0NEhADMH9t6LaTUFAu+cItRS2JBV1bSiAFZgYALxAEeI78M/+vu///f+3u9996Nvm0tfXP3i088+ubp6+d633v/4k7/aH2/70XPE43E5u4gXl+fjGK3039v8g3/xh3/5h//kj6+urtY3QBFRXGBvxXLKguYcq6qoIINjatGtIiLVNtu+lCpSW9XRhNXfVBS3Jf4dttq8lszMREkf5L7NyOgUJ/01HX3aCAiJmcnxCag0NTGBKqWZ0BEjGClW8ICevfPkGR9WDyNEQmYwa+ZvdXs+iKlWlVxzrpIFhAjIBMjQuchAaIBJHXpyMKf5VOsH6M/ZGJCw7/txHFNKx+OxJCmpSYAAANi5vh8ISGutWSRXyVXVvJEqtP2DGV30iKgPiSp4wrEAlICQvQFXA6gVVAAXMqBH50/ytIjcAcGs8Af/4Df/xu9+8N77j10sVZcCU9FFsFQt0zy9fnt9d3ejCor43vMPz87Oq8phml9eXd3eHRUxdLQsEga+uDyruThzgfnVq+uLy9gPjCTExByWKefZPAwI/fnZs1evrn/x6avDIfcbdJE3u22ScliOQOi7DojXkoH8drsLRFLydH883i/R0/c/Gt977zwGm6Z71Up+ECHAcMj11du7n3+c1gMMXcfkD/vDdz989uvf+87f+P5v3Ly6+aN/9kd/+X/eDI+b6tzVIqUoQwiuJ3BSTUo1RQBVFVMxNDQxUHbsXIt6r0UqIGgBChA6UlCLSANuR469eiePL7onjy9+97f/9nqcPvn5L47He88aPG/PLiqwiKWS+nEcz3YAtKz1+ub++u2BuUPw85IP03T5bDOMYbvd9F1QLct0l9Jy2B8Oh2OpMES4fAQv3vvutu83/VBKunrzqoquRb98dbfdPond2eGQDvO0Ods5j2ndq5Q1Hft+nOc5l+pd80Hn0CGziqRSIK/w7cc/no/17Hw7bqNIenX95Tj0x3n66qsr72mz3aqBjx0gCdjYjUTu5mb/5tVtLZyPdV1zF+KLF4+ePj0HrNNyu5Q7g4wE3hO7Zkvp0EJa6biv6wIex64bz86jSCp5TXnOeS41GYB3EDx0fRyGDhFFqko1k1JKEQCEEJzv3DhugbCKzMt0nNeUwBQ8wThsQujynO/uj4e9MkIMDjGkJZUsQ7e5OH9y/zpNh3l/vCsVfA8ffuf86fML9nac9woVUKsUNQGriLAdN2e7Xd/1JrAu+erNza9970dm/k9/8hdffHmXFbwL43jZbYfD8TDnxbC6gNuzEUhub29B4fHj8eJyI1XyCrXIuqzrvKraGDsmt8xrnmtZWn8LyVxrwYOBagU1YAou9F1fSqlrzqmANG+CSEwPU9/mue1rraCCSIDgveu7vhv6aZ2P0wQqm/Oz3cVWrU7H+XDc+8EVrJCAO7y82EUf2BgMckppTTUVFd31u7SWdS7rWiQ1N3HybrC11JIAADr493/rB7/9e9//8Dvv3dxeHaa7N29fv3nz0ghDCN77vuucd6KaktaqVcCEctZPf/lyOs7rCscVAOFyux03WwRclmktc17z+9/anZ13olPRaRzARSaHxLysWasRu5RsmiRnMIBxjOfnl7vdeez94falZyb2tch0XG7vbksG10KmPMQOYxeYset96Hg+rjEORO7q1R0ARL9BCgSeOXTd+NXnL+/36XBTDvcLRdRqLhAI1irPv91/+N0natO03AEKI1iFp4+/ta71s8+u37wpkuDE3BI8erJ9/Pj8+vrm+m5ChqLwox+8R1SRs1qussTe1Wo1m5pn6n3okXhZ0v3dtL9PjsgHl2fJa2Vvj87HcTMQq3MYex8Giz3F4JCsSkpp0iZNMLu7P/zwhz8k9K++uP3ZTz8/3EFdYLcZtfr97ZynHHqflwICrgv9sEHgCqJsolVK4uhDDDkvRdfWFXChZVAaMHBPKhZ8DD6iVhfqMPJ2x9tzNy+3H/36d1PK+8N8d7svBbRQyTLtdZnBA/zgez863k6vvnpz82YGAXKAFXQGUwgBHQ8mTMigJlqlJrOCBI7BHFjv01rAwbANHKFaXgy+9+HT737/2WG+KXr0kbu+i9tzAffmzdvXL1/OszoCMnjxwTOpyTt/th03mxGNpmm9enX95s3tmk/vkCePz3bbDaCaKjvqet91sevC9dUrA2Xnhn5w3s3rsizHlOduCKGjdT1ePtop6Nuro0f4D/7D3zzeH+qaS6rLVB2Mji4Idj//2eu/+LMv3rxK2+04LXvNAAQ//M0fdbEHIg50e3Nzc/1GpdaczXSz3by+uvMeQRALYXWaTLMxea2m+k7bqQAVyJAdoTdyhiZYdo/7DIcMadjB0xfh0bMNYK71OPZPTPvPPrktazy8nuciYOmjH3w7lbeXl+HiaVCd7o/H3/zhjz98/u03v7z/qz/5/H//nz8fxqHexDL53kerK/EKmDA47mPWtMActiFsedXF9d4MTLQW1WxoGFxAgHVJ7SxJRCoG7wATfsA/DEiBwYGBKVQRTSe9FQERMSqqmYpZlQew/x2j8tC7IsCHEDgwq/oAkiByAwIAmim7qDTxzymwjoiJTpnTTUFkZI2HQBRTFduEJ/P+0D3ReTj+wz/47d/5jz/88AdP/vjP/vmf/8W/2h/L00cf9fFyf1+m+dBvAipdf3X8+U++8LqVG9XEAOwAGBJhAUwAZGWXdKZdOXtfn3wEf/c/+f3ru7uc6dUX+5efv3l++d3ldlmnpIAYeCqHKe1j1zPRdLvIlUIBEIohhr5zjkVrKevpYFtEtNUyQI1BawIyNTCIPJiezKSa98tJJnaaLreDcPsa/cZVBgBocFXrL7WPGIgM1bKROg4VuarSULTqf/c//BeffP7JX/3s87/66dvDrXkm7s1vaXjWD8+HFNdixTFNt8f9F/k//0//0c9/8vPD58unP/3cEdfZIGkMvWee93NwCghNo1SFrHgww/bTtHwJUFRsAgwipgaLGoBBAAzBZ9Gs5rpOWFPaP/3wvezz3dXVf/nf/mc3h1ev377K2N1O+fbwFkjJm0GplqNzm81OVr2/Pa6Hcr69kEmmm8kKWjW4kZOMpDIJkQA8iNiMKJWmfHyXAHlCsRCRW/9N2ytTjE7AUDvSmFoDfU5ayXcm7k1lpi0n3EARxADBgSdERG6Nx1RnIATE9n6Gd9CMmj2kdQKQY/cgXrF3v9Zav2nWriIPLcJf6Vv92xNY+K893r3l/r8SJLo2eDcCBDo1zw2ayRk6ChwQsNRiRTGDVkVDVKqqUCD7Ui0LqLJRawQyBefYkYjkXBCRHDV2irBJ6EBBqhoz0EmoCkBg3PjXFmWvLUYYtPHrDTQABkRzYOacM2hZyara/Eax+afjgzbwa28dfLAvAwNQIm7kowFYM+160II+tKERAIhAuBlZQ3NTPDlyGZ4kr1pQUVHbO8fQiJqvKigAOMw5AWo1AQcAkFMBq4CEgCfIAwmBFBRO8T5FTHvfKZgPvZFbU8pz1iLrRbl/c394PcMAKVfy5AZkNueJPDlGNZ3WYlCdw5yzc9T7MDtG00cXYypSpYyBndchhqePHve+u7+e2IEuKNkI21DKKSiYQBVgOymn8cSynZS5Zo4ZyABRVaWIgfrgkJ2p5VpzSjXnw/19v4mANgxxHEfvPBGlUpY1iVQAnKbZzBw7RgIzU8nruixrSTnErqSsaoCkIqCg0op1ZGzR5wimzrFUIoYuhL7vN8NAYF2ko95qhWlJJpYlq1gVc5WP6/yz1x//+MX3M4CnGMNGK4IiFHOBxzgAQDVEYlNMlNOahxCfPn7iu25JC6Jsxp7V1mnKJaHo2I0GVEUDh7FPHQdxWtRExcwYjMnQgNnH2C3LXGsBoONxb2bLMquJI6eqpcDYuek4g65d2Dw6e/Tk8ftnw9PenadVPvniy7/4yV/eXB1vXx98BEmgK0oGUOfIY8elrN8gTQnIK1EDjBFR6cQbgIEigxAhITKCAohXDY9x9P4nf/qz6zdvf//f+51f+8GHTx9/q2RkjPe3d73fDU/OQgdhcPa8xM4BFkAxtKXst5fh/fefffzxVTwjmbWFn68lhxAd4pIWz8wMBvIwvTEiFGow6rsa5EHf9m7Ve5gIvVvgTl9gp7sdvoFT2Tv820571umhDfoyOfnbmWqzPqCTWYCd/Psa/KmmpAT8ICdUwHd7RyM/T7u+qT3YL6qIqWffdUPnu3VN0/1BUw3kODhjdQNVUiSoqOMwhC44dkjIjkMIyzKdfnRsNdYpNaJqe89KG53VRpA1TtQMRFqEmTFiU31DqygIkQEyfEOT2Z1tlrtlPU5I6hwx6/vP4P1vjY8vx2EgxaZ3dlC5pvV4PN4eDtOUAELoQhMMllqqKiOcn5/HvgNE8nR/v08lSS3EiBU9x80QQohiJlXZYAwBWTkYqIIkdqkf6cnz8fxRFJO39/NhukdHITr2zJHFVHNdlrzk6fnlZpmPzPi9jy6fPN6NPVZd5vtjXmd0FEjASA1SLikXBvAeiogqcuTdbnu+O3t7/fbTX3x6eLtuLl3ONaM5J217UtUqhcBMQUGaBJVcg93aEBYRAZ0gQXMyUwPwEDrs+6BgGpA6Dh0xV6nL7W0q6e2nZy97Hy7On41xyGUSmY7H+wrsQwjRhUi1rinVw7TsD8fpeCDqAMKy1Hmd06spdG7sh64PzKA1m5VUlBgDm49UNeSKRfT67Rv0eP7oPJWqh+XFixd/+mdfhHDMxVKV6/t5s41dh2ACFJE7NVHFKkzOATtiR06BvXEih7/84jNUQk5AfbWc1nu1JaUcAoToTa1WjR7JB62Sc0IsWnMMPITuUNau67yjVNa3t69iD8jS+UDkzUSkSlExJFNTyUstSWQFw2QqfejVslolECYzBkQIEZgRSUQKMQGY98TIMfrmVECO2dEwdlWqZmFHXWRuybTaio1EzMPQqSQE9C6AUi2QExznY8kqC1St/YAb57oeYjPVdzIAACAASURBVEcApdYqkhGNo0dC1UqAnsGRSU5zLTXZmtQqlSyl2JoKMnTOA3hmBycQXcEEzKdcDCoA+EA+dkjBTqpF7gJ58mDqjE3NoTMC4CoVNJvUAoynYagaGBBSCy1yyBgCANZS1EDKKgWAARxh2xEJvWdRNFUDq1rnNK81ZS3IAg5LXQ8HdZ6BzfVOQBHAbdB7TpJUzZNzjjGQQwcsWiFT0iCoymDGbVKiVScjoBF2gwuhxgEAq0hKaZqn4zovKSUFffbsSRs2tAEOcdhuN0huXaruJ4NiAEQQCEqF6ThJVUCrpYiWzSZ650xURBEA1KMBE3VdJKJ1qWbAbF1Ez1AUCUlKTWsCq4BiKGYCaMQ1RnCevCMRIYYQQvCBHRtgSeDDJq31cNgvS/be17I6NsfkXHU+i1WVKlbRAZgxU21GThtCxHXJIdJm3BjkWjNjr7lKli7wk0s05SXJsuQudGPczoekRXpGAQKTeZ99qOOWu6ETA4GCKoagmkwBC3OMu4vdsN2cXeaalZFNobSZsSNwRg67IZ6dD1n2OS85i/PoA/VDEG3JvxhD2N9P87RcX62SYduzGwa0cJizqg27cd5PbXArKuu6ADhF68aw2W2r9tNyXJbJrLYN1kUfew9gVcTQxt1QS7WKklOteUAFRRUsySGcIs9KUTP2xBgDaa2+9hu/21x89dnrmiTP2ugIVkIw500EEFgq5FxAanMldyF45xFr64d4F6D7f2l7tx5LkiQ97DMzd4/LuWRmVXVXT890z8zuznBnOFxyuSQlUqSWAoGFQGDBJ/4Mvei/6FeIgB70SEACtBQokQK5F+7scMi59b26Kqsy81wiwt3NTA8eJ7tmL3rQLgOFRlWh81ScczzczT77LhSEnKiUOgMQiBhzSR36kKqVeblXcUWoegjJtoyh4y4G0zsmRDaYzOe6nJfTcZmOD2zoGQBSoF6YtNRa1GtZvC7ISc6RuxjVaJ7z3e2p1hJ77odut70JgQDrIp0OyoxNN0zn6e71eUgdR3948+b+bnpyJYfDixTyfs/f/s7Tl7cfH84PkVl6KqaffPqJxHRz8+TJs+vt1XazCWb5+HA3T4euq9iByG1xNxOqblAD1ezMBgeScFveVF3Z1VrAFRMTiIlBQqAAMBs8Bo5pJPJSsohYYEkBeYbhdDqAilqoRVX93WfPSqnHw1mYvv6N9zB+bKih3wg6nZ25MbPFqulpnn1BbB5cqIrOWeHNfokYoqHZSwWhag5trjKQIAAxdA0MBNwhwquhEoEcLGywVfvnTk6NwfDIyvvTJSOvMEur5N6qLuGt73c0LbBf2OurFI6c6CsTd1q57C2WkAxscBAd72/Hq/354Uvs8Oy9/f7J+OL2xSeffKY1bLp9Xejl7a1W3u03z955+nB7mo+3OKoG59B5dVFqhiyOlRElUXzxFI0jQsR0PsAtT+X+9n456ZfTy/l+NjVwMIZF7cYx9AHq3ZDKptpENruqlSUbhBo00mJTGm+/+SJdKmF4c6MgU22aqQuScHHOunyW7n/GGumtj/nxd375n1t97Axjt1aIi2PGMHRLPs9lmXUGKG12kBKHlDaJAmIUZtdSYhJ0gNt+u8mprtQwMyjM4LRysh6FCC2wCNbUtm3B2GVhODUOC118zIG8LCzEEuDlfH7AIBjC7fml7/zdv/Hs5599VHDO0Den+8OpZC3bYUiD5DzVKZ+XEjmTCpPE+AjzkZvBCAFkTKv/UAOv0DIVyIwa6WlN37ggNWQOdiZ2GDvgziCGcGs8yN2grI7V665JVFY6lTpdUmi/anPcYGChhpQ9Eq8auao5pBB8pffQY7vwmDB4gZB8FXz80t0SHl/0L3H9F5UchlIgAcwgZkNzTWtYDiSEFKOpLstSJnAhL1DVZokGYJ4Xo+rSFMNgBdiFJcYYgjWSGkkDsJjJmdDwKTVjJm9DR77YL/Il4sBg7k3IufrcGPgxJcLRPCVXxxq+pHq15EF4k+T4Y6f79ufvYFlXtl28oGlVEnvLdm5vn1hXBwm6INGtWXbA1R2ua3Y9U3AyCFgZLmQtPiEsy+JUs2XuEKLkrICD1LFa2kPM2VdsOaJoMfJieDgc1NSdypLzvJj6cTp9+dmX82G52neH4+KMMIYQAGZ1V3iuqlZMc2Cbr2+GmLa7Tc3l5np/rqGWEwwCd/XAfLO/enhz98M/+uN5mqajSYFHJ2digrO3WYm5ka8BiwDYjU1Q3bXBe40cV10Bo4J5XlxVazGreZ6nA0iWYQzMRKBSipnVWt0RhEMIU56YOMUUQ4gsBVRLyVPOSwkSl2kCU4yJiVMKY9+Re9/FlIKIBGYiMy2q2b2KcAycYjNaG5uqOJ9LNa2qxZVK9sk+/jL8n//69/72P/8Nq5UQutSZmBnlosljnwYKPJlJ7EC8+AKjcdi+1w/Pnr9npkXn6Xw4nu7zXKoWER6GsajPIW/Gzbjb9l3v7rN6cZDDJDKJqktIQ98fzlNIKcWoNee65DozQ4Tgbhl3p/zk5ur65smQNkO33Q/PEm8+/8XtF5/cfvLRF//hhz/JEzpB2/fWBD8iZhYJ5ZJFCFwWdUNzwd7OZjgJaBWN29ohubmbOLTieM4vD/mjl3eH8+mnP//4+z/4tSfvXn/zg+99/NnHTLdOZX+zccq39y+sFokGtul4/+6Tw7d/9b18Xv7gR3+IxUqRFJJmmDOH1LgEJGs86MqrIiKiIL+0AV3cmfDI4b4AydwGFo9YvZmZAuEi5r9AV/bVafrWg07ub7Fe21ndbHf9Mg1AK4ZWgeMFe27PvLmRrT6TBFCjtDVCujXOJzGDqcKMlRMljiVH6TtyL16NKom1dxd6SUPohoRmRsMmUUjgqbFLYoghxEggbYp7tdUylwFuNLCLTRfjMZzX6UIvBqjxzKgtgkdCskCCu3YDz5MPA37wg1/73vc/fPbOHmJKEpCUaNGpVD0cz3d3D4fTWSR1Q0fQECVEYRci2sWw248kQc1UdXk9zeeJRfZ91/UpxJgrrHrXb/b7q81mH+Nc5qqLlaWkYXPNXb+/KrXcPzycylJUicwA9spELLzdxM1AItIFbK6vx7G/udruxt51WhbLtVQndlrmWs0UlrM2y5txlDKru9/sx29+6+vdEL74+Ysf/fjHt6/K9XZ/fPNAAhFmZiepblUru7XvsgX4MDdPByMmgoAc7NL8Ca1mNQZSz6EPDvMkYQjjmAjlfKr3d+X+dd7ET997551vfvi+7Pe1HM7z689fvHg4vk79uN1tujF50ePp+HB/Oh7O81RA5l6WWUvRc650xEFOMUoMklKL+rUoEVA3mc9VK7vz6XSMfbi+3sXOq9JuP4p8kvMZEDd/fZtV5/69q0Apxm5Mm5lcXcTZMooyioONiCR0fehePtxGwfFAhNmpulWvLrBxkJiCVauuBHfTMi+zFiIqSwnCQ9/X7F03EKHU02meOKXtmIZNxyJa6/lwnqZshlJJiy4zlklLdubi8Lu7nHoehjiMG6JeLZsXUG07lVppgheRmGKIXWLmBiKDiUlqydO0LEtVbbsF5aKz1hjlerfv+m3fd0IphsTGOdt8LvOctRgNgRypk9QHSJWgastSplpnZtRc3ZwJXZQ+hC71DM7nfDrOp9O8v3mXiZYlL/mcYuDQlepOtZirV8BAJEHg1JB5huhix3I6PcwcGE4iHCQQYEspuZoZGCEGBoxXv9eVSbnaEJgC0/nEIiwsSSjQI17fsk3VDDCjlrejTs5MLHDUbMUdFIgZ1XJdlp662MdN3895NveYGGTLvCxWooRhGCQQBJyEAlIIVjkEC4lL1pIVBR0SEw1j2PYCX2IPDibcRIuy227cn4FQq4XAZnWallLKdhdjCkRSi7FQjLLZEG3j+aSn0zIvVqdTq6yFsdmMIrFWzdlIxCyaGZHE1It0jFzVzTPcld0KzHxZsmPKGcyLaaN4kLkSsxBdSjgPQbo+xphK1VptHMfjw8MXX8wpggk5L0Gs6wIRlVzmZSk1c6DUSVEVEc3Wj2l/PQrb6ThJ6DbD1nzJsyYSrYBSH/sAmIYoJlhi6sZ+fH33iiBJuuM8F8XhcBpG7K+uhz4U9fNSmEOMzixAAMxNzZ1DiD25ZjjFFEGel6XUrGYSwMH7LByw5KmUpesiqHfnUkzV4NLHnc58eFNOD8UUQxfGfnc+1iUXI4z7zVLO2sIeRCEm1FDClELwoiVnaKUYSM3dmSiGxEzRHISh64vU5bTMc67Fxh5RJAoL0I99iNHP83SclnOO1KdO9tvtJtJ0rHmqn3z6qqNQs7lCWIgCvK4FJzGcCGQkazicJEQGG1km0xiuQZVFWQqJbzcybvnZuyHGKeuxH9ibqZLMamRdli0Hke3YdTFBQYTILOxazufljRffdtikEFOCo5SF7Cg+SlCgOkBs7NkKdvuvnc825Wk+ZTNcba92/S52EfBqtY/D4XTgEIeuXx5e3n1Z0jvdbntFTy3ybZkfQgi73VVKkobx9/8YPkGbc0CMTsh1OU73/GD9EPbXnRDHboDKfr/77q/+6jzl0/2UTxooBE9aPM95mubjaTqfz7kuWeFrgKEBClJhIcG0HD0U9IgJIV4aI3AuJWfvusQepl4wEQyHw6Hra868LE6Manx3OCW634bdt7/7rQ9//fdvP8qoVbhOpYDhVaEVgZxwcaWGSOgomjXXcG4tlZk1uwjh4GyqCnMwRYlEcLBbfcunvvVlrdxrvQg1MdQ6L2xSp9VC6Je64vYOWxX82JDjQkrgr0ah9qfLxLVYXIs/ag7HDb5qpH4yJhg0XfXvfHj1iy+//MFf/9qvff9Xnjy5+fFHP7p9cTyfidwflsPd5+fYdfKh0Lsgh+YKA6mZKpo70koLagbjHjqG0Wa3Ga90sxtB0g/p7vZw++boVV69eW1nSOCuD4suYSObbmuwaT5DMYyjmuZcrFaFe7DA/DbP5QJWfPVOH811vnKSWmtbfiRh/dLn8eejFn+KidM0USteYmwOWz0xIq6e7k2seNEI3nalTvCyianrg6G61yAIFPb92CmS+JPr7TzOjaYEbf8lo9agryinw0EOVpgT9CtIBpeMRQBQXCyfAB67zXyeOXm/SZHDxLMFc/H99e5Xfv3bn736lJNVK/cP52kxTpS60PeRSGtNJS9aFQWubTkyOQlIzRjiAhGBwkgfoYEGHDJA5tSKdDzqRNDSB535IoJ0BILwCqm2FUpu9YI4EK0PxBp+5eubXCffF0yvPTPuq1U5VoRxpQI8msS/9T0+Oqt8tfxxQT/+Sq+3l9bb3Ku/qiukSByEghBRNYUqgUjErJrp+uk1HbGSqUEdxCHEEGUumcTBaBGw7nCvYJLQrOYYZoCBpIFKTNI4NQ44+6XRMl+BItBqjKztaRdhaUAXk+tqJebuqGhBmkYN0OYGoLVO1IhAFztn4NFnBwCaNTGvkiUGXWz/HNQQrDaFd2IXQiNfoWXRrK/gaOY+TlBDM/gXIuOQglptuH1gLiU7iZHFMYpSPutlFVl7wp2dhJyKwyTCXEOCOu7u76sZiVVzkjimeF7maSq9bPpn/VJeFqbYdRKrk1WrRYkjmNnc5mWe56mXMA59evbE3f/NH/xJFBqDJEHO2I/bm/3Vf/6jz/797/+7vBSfYQ5mqBkROxuavIrcg1F70Agt3MWpurvDmJqI2hlEHNR0Op0XIncToSBpu3dwIY656vF4rtVAkCDCnFLabrf393fMIXUxhhA5BGIhDsSBEITnaQohppD6Ll7txqdPbgIzsweWEGQz9ClFq+ZaBE7CTK5aDKSqm7Sblnm2RckqWeXqbEuZl4fpzRef/4///H9QMnZmji4uErWaqnNg5hjhgXuAs6lVsHESGceu67tS58+/qMfDQ2AR7iFwq0KcYtpsd7vrq+N0JnVWLxxUNZAW1aVkJ5iba930+2EznqdTPp2b0oqJTMkVT29uujDs+6cfvPetGMaPf/HZF5998vOffP7jn3yWZ3SKnskzdHEzChS4i0KRnFvs/VvnCl3oTs0Lad1YiS8kJVu32TZmSn2aSu4E17uOWH/8k89//z9+/od/+B//3n/1t7/2/ns37zzXKks9B07TcvfpJ1+Cy3Y39BvJ53zavPr6t9//dnn3N/7mr/67f/0TCHOIpVjqhlrNyUJKagprLMrL/RGtYsALILPebduCL3vuBV8iorcnDgS4CD+eFWiB0oDZCn75V4d2K30u23Q7pFnI2mImIm/AmjvInKwBXo375fYYIruONF3b3meO9RACABJYqYstYxhTHxE2wqwll1M2AwVwgAKbm1HdFl2YCI5cC4iub/alqKpybKJqKaWqq7oaFASWlinMl1nZSrRqR2KryLgNAehiRs/uYF95rbKcctd1wuoo5+Lf+/Dmt/7OX//2t56rzed5Hrahmp6WKedlyXlaaq6uRpDgFGMnKXXDMDhwOp6Wugql52WptRBQS0WpGIgCKxjKTiGmm6vr9+7vDjmT1VC1nOa8mSYlSpvOFg9Znn/tibsVKwanNZfDxlG6vh+69I3nH6jWMp9Pp8PtqzshlQCRRByr2f1xmbPH1KuLK/WBRMJsykzPno3f+ubXP/n5Rz//+ccvXpXAWLIR0MeQYmLmxQxWTN28thxMpdXyFgyzGli4qc6FgjAHcmIsi7tzBESJTKKkyH3qiGKeyrmUsuBnP3l59zJbpZsnw9Mn/bPt82zqQuf5OC/YYUMsza+TUJlhDlNzB5EkSWZWi+apiNShTzExkSNKE+CaVdQYQzcMvYkuy8wx9J1k1WfPxvNZ3SPP+c0xqzo7UhgiJ8s0Hcv5VABwE8ySgjQl2V9t0tX2an8itZLPh/tJoo+bmLqkqtNs5pUAJitl0rmcj/O8LC0Wikksla4PIQDU5occOoodDWMMEmsO87m6qS7Ii5eMsljNBLAQB6aHh7s9b3a7YbfbpA7uWnTK+UxstdZlmcxaIUUEEaaYQisIwXSe8/k8n47nUo0ZItJ48W5g0r6LXT+MQ+8G4RglwLmUMp2XZS4RY2DpxxQ7npfz4XS75JzrmRjmOD1UMww9xtAnjtvYE9izQ6e84OZqL4yyLLU62Byaa7HFUaWUBeIAxRi6obMaxB3w+bjkOc9vKnUgQerC0CcmKtNSirqBnMHCgdgZgR3eEl2qqpemlrGcjUJlZxGRKClGSUJBzLWUsiyzma7bOYMJQbzB3W7QCocrIAFdH/oxhS5w4FC81KJWlux1AVRzUGVLxmvuFFvaiBbiCEpGmaQwqW+71CXpoliep9OylKnq0fyayLoYwn6Xohj5Lz75eBhHIkzTOedMTERMEmoxYh3GbrMJfTdU5dNxeXg4layqxswhBiLW4tlLzhoiWw3Np6aZ9/d9rOq1kpvCicpSSi3ZpqUE8e22CruIuIut6qFWy6F9sMwcQ3QPVp081UznCTE07k811cBaWYF5ns85A4ggWIFBAYQQx3GT83Q4nEKQlFJVms5WdN6NgZESd0ZG4D717L3BA0U26WPIVtwWAuYpkwAmTFKr5aWGELquA0VTLhm55MO81IJSzLIBLBxMa6kLoYg4Vyp1nvPh/W9ct7aGiGupp0OeJiVwCPLs5on4NsITM/rYdZ0jVFWSsN30m80mRDw83E/T0qXQD2OU3h1MPh+Pc8nRWUm8lfoOK+7VKUoQZuG8FMBNq2aDI0XuYkgBKdBuu6Fq+ZSP9xmO0HWbtI0ynJd8fjjevjjijBwqGwtCoEjE5l6LWgVFZyaIkIgzA17VTJ2ZOXVBBNLBoJ7dSjfqs3f7Z8+H588Ho6n5BzGDmFJPBuk4bkIJzF0kYU8S3Y3BTOwhRtvmHrUGOA2bzdj3pdaS8zyfihUh50BdF/p+I0Gub7avb9/UyXgPCbzbBqFaTsXMq2u/2fhi5Ih93PZjPp3vOe+Hm5tdV86+UGHwbou+o2Honz/FdML9nZWMrkvSc2BC0CnfIUSZA1muOl3vN++8t/1r3/nrr1+++fzTLx/eHIOnjruScTpMhweErV/ZUN1KrtN5KcVzLVnN3IiJmXKZ0WE7YtyGrhfVmnOGmyubdsNwzeDU53HTqeal1Nhhycsy02bfvbx9uN7v7uTYX4/X7+x/6+//zf9n+dHH50Nn2XsS6jJ5zSVxF3p2k0pqcBbuUz/neeUgMK9sdWuu6QQhrUZEwtLsYtgaXUuhfjFrMjQyizkZLlyuxp5vbTbQLI/grQJrPtXN0XgFOECNPtUODVq9Qh9rwEu7h3VI6heeA5oRfqsz3dzJ2WltBhE2frY3H3z35h/89n/99W9+49XrFy8+f3h9O52PoqXOkx2/rOgOxc8psirykhHBTqVqw5PgTXnDTuzwWc/gJfSDdEwxcui7rmdfTmdsJNqkKAixT6EvpZBR4JBzng8zlCISKa2eB6jBWFphu77bX4Ku/uxFl7r30abDvmLc4FJy/zmvcKEC4fEzNGPS1cVVq3ogCIwdX0faBIRavRgQespT6Tv0W+lHPqOqTlaYHddPr/aSXJfNKEMfUdFIEcSRXLy4VueAt4p7W6e2vvYLj9dXlT8eVRcU+6vDYYIvcSMUDKIQfef9d55++yZupdznkutpOp+OGQ7pE6C1OpFvNmPgIAi5aJ6KKryjhlWIg8EQRAoq7gwiGK0izYbGrq6/l79o6YRYf/gxY8oR4EzKvuJQLcrwse1uGsD1vTe3qhXUgIGE12m/g5zcjdfwqV/61vzS7r317V+4h2h9w4qU/X+smb/k9QiSvv0A/pVcIaa4PqMtbq9JWYgNMC2lBCIKQTw4KuXqICfhGGNKaS4TkayPSxPJOwoXDhJiCwuGNsICHNIEzaTmq31zA8RXgyoFPeY6GkmjQbaFS1BTMoe2REhHcQI1oiq3TDNaqaXUtISNrrISNFZdIV1Q3Ismx92abtZX48AVuX7spdsO+IisggABmJgvmiiD2/rEszKUHK5FI3MxJSEJlPqkRZGwyoodzfYHRBJYSeEmkTJ8HFI3ksG6rlMmqjUNadMPc14ocYxdN26G/SzuqQ/OM9jc1NgkphTNa65VT6dTx+JWd9vNMAz/8vf+6Nk1dsOmYypc3n1ys99u58P8xct5g7RQJmYoXN3JEBqATCwMJiNrJ0E7FxsVZZ1tNMd9Jglizuq1rlGpFLsQO6EkXd87ME+zqV1fXwcRN48hxN1unudWWua6pBLMbIhxMw61blLXnaeFQDALRH2X9rtdiqK65DkL+WYzpJjyPFsJibyx+9SKq1mxMeyqeVbV5CTN0Yx4ptP9w+2bxVADS/RktcTA237Pobivz/4yLeYVIlpci+e5Ll5Fa8PXIriPfZdE4epVp1OQsBt3m93u5p2n+bOPkXoBarXqlorNZTHTJdepTinFzdj3fVdt5sXcQQYoAqL04cn+HS+Baj89+CEfP/nJlz/7T1/87Ee3+QQM8AAygrHm6hUAYpAowarXrBcUZt0sycWh1KI+yczU2ZllnQMwGPAWKdv4RoKQun4YwaXoMSq++OL1v/23f/zk6ae/+8/+6fX+efVlWh6Yxu345Hh+fXf3sKlxGMYvX//i6dPrOA7f/d43f/QnP7n9eQnIhC6EMJ1OjhoTt2d/5dxe0H0ifoT8H49MIvBb7pxv4/TUuLANZWAnEbocDCt65c50Odl+ifC6Ij247OmtZGE0DIvX59sBdzInbbfUyhhHrRXOzGBmJq3VqBFxwUwW4GZuQAAn4g4UnIB5Ps91zl7BQIc0IAq6Xffw8FAX7SQR8aLzEDbXV9fLvJymOddqZlVb6qaBQMIgY29mo+7sbo8m8/bIaHM0gydcmAYVzi3/2F3gDJEYxbUuZb56gn/4j37rN//2r283ev9wUD3HsC+lTPPpeDzOU3YQS8eBSDpDSLF5ITiIii73hztTNfPzPM+5uEOYu64DrJpJ7GI3VuN5xouX809/+jGAPnaB/HC4NwfFcP3OMwrSbTbvf/iNbujN9Pb17Wk6LvNcau7H/ub6quu6v//3/s5Hv/jZT/7zfzrev57nU+pCDIlEqmJZ7M1DqRWbzeqIIUAQ73sdhs277+yJ8meffPbxFy8iY7PdPDzkFLsUWaS52/oaW9kiA9whquJrhAg7BZYoxGzsIbAkIXYTBVSCU6ghhDTGGAM3voBHWITVV7f65YvXr14+fPit7d/4G9/+le88/6D/oN+NX3zxac5zzjOzCNnQR9UNXPNCs7ZNhwMPRqi+lEJmqiEwgVmyYZ686zUX1EWEw3Y3zuV8ONzFricOy7z0HRNFM5GA9zmH2IKfME9lOh8///RuPgMVLGglIAl2u9LHLTbh/efvzPPD4WFa5hyB57td6tI8z3kxrQUeyHU+HWsN06nmxSS1J0j5/JDiRs3AHhOlvksdQLXUSWspiy9znSddzl4WqpXLbFrBQuFCinTXWmspmZiIlWCpkxBCrTBDrU1O6IZaS3E3ELGENmyopWoxIsTYi0hgjZSZues6DnAvjfHJQiGEVte4EREF8qEL2/0YI53ORSnyXKQKByklH86oFczoAvdBxhglRga05FKWq90wlWXJkxoMBp+qoeaKABgQ279omzFCQxep5mKlVnMEeIE7MlcmZ6JaqunlAHV1JavNvsoZEJJVCtfaqR4OV1I3NWZhYmFODjUzo6Bwl3YuM6Kwupv6OvJvznoR220ct9t+jE4ws9B1Wfl0qlofuepYtFQgMIJAmCxUM1Wr7hqY4iABtBvj2EWG3b06nSsWnaufqp2W5TRNExFZraVWN8slu3nOS85Zj1pV+2ETJMXIwxBE0tB3Evph7GNH85RLdlUPIeSczUrVXGtNFvICIyOxWlSEW2owcxAmiBOJ1lwKQJkFmzGBQRDm4MLC7r6qAQCr1aZpIQhRLyLnc57nPCTEEJijN8hQm2jam/WHBAd8KZBk/Zi6PgGoxc7nJUgAWG2ZzloeKm54u01RqtQSSwAAIABJREFUkgcyMCCKrLVOx8Vrm36AELvIWud5RlmQi07TkgtCQAiBJeZFS12mRc+LnU5FDZGYqAnDjVxjotgHIjWvx7lKkK7ve3QhBDWdzqeHBwyJwxA7viLrr8ch0dWbuzdzXs7TMucSUuq6jpiun1yDNCQESUMfiUKd6/l4WpaFRYa+X3JezjN4te9whXNzXuL5PElkN3NGDNgMMQUR1MDoYjgfTseHsy7Yb3ZPr98Z0vbLF28+++jLN6+mMkMCBU5uBAJzDCAFqldXq66Q4gawITTptqtDOYQudn2YT8eynIEjegQgpmU3dpuNLsucgibSZYIq8mGBQIAth6Hv+zS6URQxNQYnGdIY5TrBYyk8nWczG4YxxuBQwOb5/Ob+8yXf95xuNvvd1WYYO58PZaqbBKI4T7eLIvBQSlF4gUWrNuvkObF1gUnPgmG3kfMG+91w//o8n+9Td/XOzbMPvoHb1x136eG4iPj9+WE7ppurq2FI4DotD6fDvRtStNM5fe29dy3Xu1evT2ymeVGr1YplBN3sus32OnXJzM/H+TzNx2m6PxzenA91qZjw7vf2/ZbH67i7SsNGFj3kh7zMlZwIMmylZksd768GCeP9w6t+EDiVbMKplHOuNudlLtNxOXzre++/+PzVq4efTy9q2namJIE99EoqQhQYriTEzGBSq5EDgQRscDdz5rXZchKKLT7LzMjQONAtbZkJqquj0AVLeiRRtVZjHdi9xaxaK0i+0B+ajKdxcRpZgN8CsFpFaRdD97eqxMZrMbPQguTQpguNEsPOQix+1tP5y9M//e///vf/1q9Dwn/4ox//9JPPfvYTBFdhJetAFSe8/PT8ZHeQRNPhhMJGFiTBW6iHXUAYMjalCXtgA49SzIdxF2Mie9OK0tZpdjIKR6/QpZa51lI0e+IwnSfK7LUlqJEQmMm+YvU4fDUu/Iva/pY6+NX7NwPw+FdMZH8eUeaiZsAKFrUfVCY0qhRABsaw4R/85jfvT6+znwsqHJWmboNhJ2mAUy7lNJWzO5F53W43/Tid7q67fZcAgxaDsXBgBKvFizvzGuq9Yh/0luftV7X+4/2u4JoD7tNpGfqhhnw+His73kX/DM8+2G2fdbeHF9SHWupU6yUJUJfltBQwc9+PwxB1UVTVqlDWYnWpXp2MQrM/chCDA8E5EBVfLYnacmUncm/EngZgrvQ08WbPToALXBwEbfQCgqutKhMCWVsuDbgj8jVY0Mm9NeVgtO7HCEaPtLoV4vsL0CIiYoY/foTrGP/PJ9395a9HvPjP0q8e9TH/v188uJEBbZRHwikyAFWVIN4iOIlDDN4R4GCy2mQ23nac1l46kxMUCgYLtxDHGGLVmsvsBhHhyCQsTcxMq3DQWt5D28N4BXjd4K4GclRGdHaYElmjyzpAYUWXQK0xdqIgLCvY2ezPLpbwzZOMmC4mqQo186JqFySrNTDwxu8E4L5+v+ufW9g9XEBCFBq+4yAWiHAAkZOLM1eomrNz3xsKCTgGSl7PGrdARc1YuWHsEEeAA+aIAagY+n57leZ8pi6pqamnLm22mx//m5+BcORJ71+qEkKcsQwbT4GIuaJUt0jsxLno6Xhktfv7u+6JjMPwO7/9g2EYepY+dcj0za9/kEh0VlTAnIqElEqpRMFBUEWg9tA0A/2G5DE7hVVR2D5dVaumZCwhiDDMQ+S2oy2nZWZsr/sQEjPXWoppSsnMpmnOVoa+k06s6nQ+H+qSp5lAV7ur/X7XQrBPx4MraVkA1DK7VsTGgsm1Sp4nqtVyTkIcIoHNa62latUKLsLaRTEKUlM1KBuTJT2mfFzu/GGzDGMaTBFSf3PzrvEkKTtXplTvZrNMKQbp9uMVGWg5LnM5+ylE3nabdC25TIsus5aqTntxltB3Au45hMiRgidS+LzUKSyBwr0fTtPdu1/71mY3VK3ElaAtVCKEftfvt/3NN5//mnj/5uXp3/7eD//gD/7k/g12Q3/97Krs1Svu7u4jBaHQ970VXaaSczYyUtSaJZK7ETX9+boTtnhO92qulzoBq0QeTbUCdygQU6IQTnOpujCl611Hzj/98ef/6fz5F1++/Gvf/bXf+ru/8eTJ8+qb0/yGX+ubh2meiuNkPP/Bj/6vD59//9n7u//ud/7hv/if/pUNJoJpXpRAjiXPtC5vB5zNH4lVTKTrLTkTm7dDWC7k5otgbp2HtRgNJvdAl1EELkfUSph8BKnWk41J1p3xcfpAWNGqVai84kDcTggyb0G+TbFnrtowWqMIGKteZMzrNN/MQOYuoEizLqQodTHWtJPt86Ebu5gisatbLiV7UTOJzBBlA7tBjbRoLrVQYK1W1cgcTExEEHYwpMLIm2hwdXBoFQehnY+4ZPeYk8HELcCETNxptx3yfKdW33+e/uFv/8bv/u4/ubmm8/mzEGsM1fQ8nY6H+4fj6TgVr8bMnYRAEpy4G/tc8+n0QCLLMusyZ81LrvPiRWGGzSa88/SZhCQSYteHNE6H8vkXr+4ffvHJixIY79504+j39/nl3Xw4Y7v79Pp6u8zLfn8Vk6SU9tvdkHaBkqmO2+Fqu+u6/uUXr053Zyi62LlXNZ+y51wejstp8lzAgX2NjgCzC9m4699958m3Pnz/hz/8w48/+agUDGMiJAkSma1OcHNTbVYrQQKTOlVdnOBkFYAhdRS70FyQiYyEOJCTpZ4lMMhCDLvtth8HgLVimet8KtPJamYYsePLV7XbnJ++uA2DXT0Zt9vt7mr38ODHhzt37rr+er/tkhKWB1uOh3meaq0QJuZIRGTB4SgEYknBSj4fDcZ3RxzuluVrkaiq1qpFFyWK5lzyPPRX6jJs4jc+fAL4dMr1bNO8nB6OeUYkQgQTi1AIIPZIwi5Q2l8NXVjqUrVmArpEIp4CNmNIlWshaM3VrRQyj4wuwhxLwTLPItFBTO5Mzqgwq0t+KLBQMs8nmk/1dESduWRbcoUhMrSry2JPnu4c+eFwd57uul5S7zFSP8S+72MczLTUJYYYKJBRzrmcq4MkpJTSNOdpmnNG14UUOmYuOocg4zjEGPJyPsxFVV0tSOhi5+6l1FKymm26Kwk7J0YInHSzTfurnoWWeZ6mOfBRjbdD/2zcjBKSIAXqtkMUjwE3T3b55W0K5ekNikcD9e5LLW0mGhLXal3nTNmFokAEJfuYwtjH4zKzMANmWhTMCAzXNpbzotr0Ta3y4F4CB0ncupGWXdREy0qWdam1MBGzU3ShNeOo71Iauhh4WfI0TaRIsmYRDkPf98mZal2qVYeRcIy0S2Oa87yUqgSwaTWDEkJETGKoSkWpUkIfu81m3HTdzX4XGeK2v/JnD69+5Rs3v/JrX3//nXfzfAAKk6QQ5lw/+OCDh+Ph4eGemPqxZ2ZHVZ36PoaQhim6OXF1ZJbadSScJs7zXFVtXs5MXGpVhbsfkHmeKURAVHE8ngAikRAis4dgxGzNB5AwTTmF4B0xUa0oBaXUEKjvI4DzaQqRtXA/9EzhxRcvT6fT1dVIBFUQUa3VzNq+KoKuYxES6YdRYxiePn02z/l4PE7zvCw4PMzzvBAjcCAt86kEWlIUL3Q+zctsOVcQzvdnQ23nUSeJung6z/mM6aRxh7zU/W6XuhBjVEMp0/F0Pk1YCnJGCJAYmsqZJcAKRw9dM0sBoJKkQw92IUauKaTdoM+ffRC4P93Xf//v/+/zCVoBAQw4AwpEoAOAb3/nG/0Y07grVc/TvMwPPqPOObAE4TrnZZmJSZKYoO+7LnXOVLUuSwZq5I6TYENjz5shBHaCNbDr4eHBl/L8+mq3e8YYX33+8PHPXty+nKEITDGO7EFVXVWMOQiJdCIzzda6biGKRh1MEHoOHYfEHF04P3kyuFk/xP013Vzzu8/73T6mhIVTsmG/f3o+LajSpW2Kw2azGYbN2I/CYZnzfnedl1py1aJExBy6uOvT9Tzn8+mUS4khxMTjOIybtNl1MSHn5XC4O55e99v8/OqmfPvXa7FmIF6qvnn95nQ+Nbg2dvvj8T7bXexwtelSMsZx04/f/87XP/ros4m95rP5No7xN/7abx0W+cUXdz/76BcGi5Ntd2FzHSS4q5VcwQgCBeXC/8v//L++evHm009ev7pvkXNAvvQhBMhHIUAI11fbbui7zfDBO+9/ZzPEMYWeX77+YtyGfqR+FOmcp5xjrtVcqZSiKMUzhTp2aX91xSnv9l3Oc66HUqkfr17e3noR+C2R3Gxu/tY/+m4/jv/bv/yhkE63h9RtYpfm82HSAsGwSVdPrqWT++O9u8NXK8+1d61QUigcjd7MrqhF4cZEIG9krdbvrdP9y6+vuERftb0GSPMVIrfVm5jQ3KxXLQ6RA8zkpEbN47v9pDfZTLOQf6wYm0XMOg8EWnwPoE5G5GAQm4s9+VrSp/l3/tk/JvE/+uGf/OF/+PGLl/codHP9PFBaTkvosvIy1XOymETYGLmoz8G4kcGaFRcIYCgpdunq3V33ZHCeHqZz6EYwKNG4ARdL294mSbEjwFR90vPD2UhBCBzOdxM7WIUNLuambuwgb2fF6tGMt4piPJbAzZWs0WEeZQ58+T0uggjSP2W29Nb1FlZEjWDHAlZr5tLsX/vw/X/0T/7Bzz//iaWyebdLS07e22ke94S4TMtsPEcGCQXxXKebYSjTIe233cAQwA1VjKBsrgDErYIvVBJqy2DV0q03bbRqMC43ZpcBfa51d7VhxmFasMUH3xpuPryOT+z24bMvj7fd/qYGHm/2x3AXDCJmXlWNCmCwAkIE0Zg2WizPZT6eaQY7jK0UddSLAIxW5HC13GWCk7m7EfxihAViQEABFIiax2ogCDkRNS2XrorqJhZsEyZS0EXyuQKw1riJK6kLQMv1dHcmWQloKwfN33qg2vf71Tf5F/Kh/gsQsv5qlYOPV6i1mntDkQJFFqIWmtgWtT9qMB3CoafG1jH1RResauFGZGaHQUiCBBFpApj2ut5AKW5bkoCcXIJcMEwYNVslAuBmTTS5QuZraUcgFvGGLMYYHND2uuT2CDe+zb54hBUbLEYX/qPbpaf2dZlcFgocF9dmrKZnjJZWASEmUrc16oKbAw6TceA2tDevTsTUBnmmJGuyrQEI6Mdk2SBai7s9etmsSioijwEhCLMQsVatWtTUyCgAEcMYyVizp3EIw+iSHZOteidfSmFmVCVtVXE+nA5jF4nsB9/7bpR4vL/XpcSQTvd3d3a7nAtmZC1YxJjIBc1qBOymrqbstD6FAKOFuRI3sI/MHNTsDd1qC7pASklY6pKnZfGKuZvLZtN1McbYQK9Sa9Wi6sLMREV1Wcp0zlZssxndvUtpGIbGBIRZKcVU8zQdjg+OgQVwr6UcHx5mJjLvUuQYm+zUTU2VjLQYQ5gCkbIIEcMgKfbbkfaHF69evJ++psHN2UyGfmPEzlJ8YctDt1U3V4kx9V0vLGlJx+W4lMXcx2EMIs2lwuBDGmPXK1Bdl3OOHMkK2t2Yjl3fvthaKgPXuy2Ya57ZPRA1av+m319t3nmyf0+XcH93/uSnX372i9vzayCjwOuyTEuB1qBp2G76rmejvFTPD6XUrNomJ8EDc4PmDebwtcJ1uK+bItCCQYEWyQJxMnITYgG8ViezWt28LOccqev7FHb0i5++qrM+fXLzd5//rTGFyENpZDW1h/vD+N7+y9uPrrZfe3b1wW/85vf/xeZfSUc0K5nGKJarmwRihxevfBmC4RGWag9l22UupOR2nK6ok/v69dGF7QhARO0yyFonQW7rOdx2CuJ1CkEAWvb8RZPYdpEL52uFy9fShcyd3cxaxbOqyR8dGhq7t/F119M+AaauRFAvp3Nt1HhFNfKhG1Mfnfy8zNN8FoocRUTc3VBDCJXq4XTMuRQvRiu1dDVuZGDloNAj/u4tRqSFrTpgtkblMrdDnYVhpmqtMHBiYgTY/TzFiA8//MZ/+9/8nfevnxzsE7UpBOt6yXk+nY4551qsVjO1auZwkRBCt91spvNhmRcSMi+pC6IwQ15KIChAjsDSD4NTkFjnudzfnV++fPjylW03zEKpG9MgQ3lQy6awPDD1wuHN63OtdRiG41hEWDWr5q4LX3QJ5p/uvhg3fR83V3vTe9OsNWOe/O7NfDyDGP0o01kDNRohmOvVbv/s6fbJzeb/+N9/vExIDEDM0A+Dl1JypWr2/7L2Jk2SbMt52OfuZ4iIHKqqu+/Qd3ojHoYHkgAMEgCCMMEoGbdaSWZa6DdiwQV3lIwbwUA8UiAxvgH3voc79lBVWZkZwznH3bWIrL5XBCQjzBjdVlbWVZnVGZXh4f75N5g3NRYJiUIMbk50IVyvlb/LgcMaNkJwcb6kxKzvw2HXm2nsQtcnpjCN5TDN43mp1bxFN3RDjlxi7G8P0/Szhw/L2+8+f7bd3oTQffqLn6bUB5EojER9Z+dTcWva0BpO47QZWorRXR/dSUVIanNhmUedzqgL3NCsNm0s3FpVazFvTVsUIjMW3m57uLZloei5Q4z+7CaxSJQuhJRSDIHMa4jYboeUReuUkwy9lIoga/00Iu+6nJRqdDfWVmHUxBC8y1Kb1rrufKpw5EAOLbWpWwzVCG1praDV6CpatRbUVadmUIaagvHsLS7NSy1EKBXXIa0eZNpMAosEh4uIcPSKWsdSijlEzNTmaSmzWgOCu6q6N1VYde8Bmud5GpspusQxhtwlbWbqFLOEcDoeWCyeEQovZWbxYbPph2GKLIFzymbWpW7fpbSSGFlzDCSdke13+eGU+k14+vSmOjuHanpaHohFXVW1VMRotU6uhmrL1LSUxBxTltgZk6stSzFz5rXdvchlSLAuFRwIkVKSGCMzrTnmD8cDr2RvdTMYq7lGotR1QaTUUmoxgyTJnaSUOMDJzDQEyanb7XZ9n4uW83gayxGuFII7BYoxJB6EQ1RjNaszVFtgpCQxC5ORqDiCcDfE3fXQBVnqsWiLgqrn3FFISlJP8/1pejgc74QiXJalPvvgedUyTULsqUspJXevTR3q3q72u1KqmZkVCZ47DhEsUYTUcB6bOam6KlbPUDG4MXNwp/NxDDGkro8hEllMHmNprag6M8YTNKlZY0KtbRpLqQihrOV/niHVhTVGb17P52NrIYS4WnOKyIU+ACeymFaTTSMKKXHXhf3VoLVN87nWaoayWGseokgO1/tg2spcrZVScH97PJ0WoRS7aGa1Ldpav91IihJTM6CiLWYWgvTDZhMCMYsXBWAKbajlsmNxg8OIWAQNVluToqmjEID1TWHmzZ2gjZL0krkPW6H+4XQ4HYAFXeyU1KAeGYEoCgI51ePxYX895Nzb6TxNx3n07CGFQE5a2jguMHTXSVJQ1pRiTFLVWquK1g1BZMVhpc/EYo6WAqcgfeq/mm77PGyGp27d66+On3z82fFYNjkBNI+VnaDmaxqyVTQjD3SJjnNj4+SSlZPGnvMucSKwOTWYUnjYdHjr6e7ZW8N2xzf71A9RQA1R5cm2f4qck2yuds+6vM0ps4S2tMP9Ybk7fPr5OJ/nh4fT4e7hdDotk9YFy8wprKLpiYVTls3QE3trM1hzJ7urYdjIe9/a9kPs+42wJJZ+6MM+Pb9utZa5zKfTAWTHbt+wq34rOKPi4eXrDZe3vvttX5Z9v58hyzxOp/tvvfdui3G20+cvFnN+//1rjsnRzqcJDrWWU9hvbm5urvru6i/+04/ncxuP4ApmNAAre4PhjjajAR7ptZ6QTtup2+n2Sq6HvCEPRWcq3BxLo24Iragp+m5TFjVrrRWz4tAQpevw5GYfM5k1K6k1S13/cLRgrdlBq8YP5cMPPvrOVN/7yV8+3DXcQkNxEwQnAgXEPg27Hux09DfzzGp3vK7cVNnX2EERAtzN2hqaA+FHk9E3/Zj5unCl9Uv+SLd6nKcvshh8zTNZe6RvtnkkZPRoub2O/Wti3Tpg8uPm030VKQJgZ16VYViZrtxsURizU/ZqeOejJ7/5hz988vz6xz/+yV//+MevXh8fDss2XPfxZjnVw8tbrSN4Df5OQ9d1qTtxpQLT6kxguQhwuIENQpAWt8GCT2WJc5mWJackiXMGyFMXaiMKZKbmjRjN1EhhMAANvtIzhdybqrqxk/jjufkvjjevHaC1f6aLvfcbMeHjyPz1x0ed3te2YhBhe2y/Lw9hgpEIQzgEs+jW4fn7b7/7wbMf/fQ/Si9Png8tDF7j7S8+zRtQNOOW+rDtc+oiu7OChSRCElwKdcAImCLo2pGzyLqMX0d2JgCBGNAG4HEuZQJdsAhe6X3mcBCFPjZogw43Ib/V3v/u2+lJOLTzYX49KXQe83Yftxtmo7qoNg7MkFbbPJcytS50ZBIksKHMBRW+AkxmpmiuDCYIAUpvdHpubuJKzvZNlE2wWraT0CrkIoJHhvhKOIcZ2J3pYlhscAMBzmBjspXJSyTktEZ5moEJRvaGs7jSsegfQoveoJkErFTERxrdo7Lv7/Oh/uG3E/0Dz/+Nse7/73jzbf+t8Kyg6mYXzWXzxljnxgudY6UslbKgkSAmSRyYHNbczNaEFxYmITCcxNiIOMTIwktb1lzGdXplAxGZO4yhj8/+pjLZRdhEADFdYgIv0PhKB11RsnV+XAN7HkV/F0LjZTpdZTjfOGePJNI15MeU3MkeYckVS5JHtEtAwkxE7BCwwLBaEYKEXMGBJIoIO2FVZjfVwASg1pK7VBbTqnNdUperluZCwh5pyJu2NJoqqKqq+SPhjDxm7DY7ZwN5Lc0M52matHISSR5SgCAmtkpm1erMXZJAMWf3ausQzS3F4IYcwSE44+7+taCpLtthe319df/i5ZefffbOzfOHdr/Pz+uyoIBjdLS6tJgyiMCrwENNFby+Ujby1esEF1CPXFUdMUdiq+YwM6B5SzHFEEm9cbVgtWEcZzUduo6YxnmexnOrRVVP51MgalqdW4yhtcYspVTqJERRrbnLRMyM1lRdb29fEd3kHGOUKCFzCETs3uWUUw6MoroQx6TiySePMVWps2rTpmQMIpHc5+7q/T//q78cvr+56Z9GSWYQye61VJtrmduyHfbjvDQzMmaXPvRMpKbj8UyB86YPkZFaDIFVmJsKllZP89y0hfWdK9GdJq2b/RWz5NS52WbIbD6OR7UWifebnc5yvb262rw1xOs64bO//erll3ef/uyrl5/fthkpBpg0pYBgxBy5NVtQoaZFVzmnwQKEJZRlSRKZyNTM4WbEgVbjrYvbHMwNj7Ek/OhiLszNLUAuTkos1owBswp3UEDFq6/u/vw//1Ut5e3392+//y6offVKHs5fVl1ynz3g7nz37jsf3XT7f/Lff3T3xXz32TkOUmvjYJKStQqA+WvfKyJacZwLRfxyMZOauZuIENHFfGq9j64Al3nTBoB5TZC73FXtzQ3jUq1Wux9+U4jtwthcfRguCz0CrT2K25pJC6zCPDOA7I0I/XEfaGbQC6VzJZCJBAnsMG+IIRDh/DBJEklpBaXn86yqnNhQWeR4Pl9db9BwPk7ClHMPw0r+77e5edNaJAaW4M1cFcTMshK57ZGiCiY4izpAMLGmxASDma1BGa5w9UuucDOCTdO46/BPf/Xbf/AH/+Q3fvj9r06fPBw/g59YPAQcHk7TPKrqJTmXoK26c5fzfr8bht5smeeptsWs5RxFkkgo9ZBZcoqAlHl2FuLEkLvXt198eXs6GxPMSGJUUCkOonkBgNM45WNKKU/neZzK8aH2uTLDagFZ14uIl7m95OP11f7mrc32SrabJ7nDp1+8Pp1sWrg1YhamTlWFPa/e90mfPbnabzpY/eRTvLOnGHmZbeizRTnP57aou4oAEFVlJg5CtambO4QvazERNtXFXESYSZvWVpm9eQ097ffbu/vb8/iQkmyH/QKcT6da225zJdQdH6btZn/zZOi39TTdjuXoFJrx/mq4vnryOcUck7XaaAkh7zd9ma0snpIb4v2XU+wDkbsRxxREyG2ZyjhPMYbjUZ/s8PY7T3a7fDrfVfVVbbrKXGMEM8i8LtPhzkPwVpeYhi3Fhwff7qRVDH3uuyHnlLKoLSF636cY7XS4f+utq+vrrulJopk2c7g5UQghiAhM4LIC1hBLKRBV8xpTbmYSmAil1rqUGEEdYoQQO4XiUIUr1WJqlCSC3UkJLoS7+wMLuj50nYjg+uqmtkmbHw4Pq3WmqtkaO97gzU3dDNraUmoIOUUJgfq+G/oeIfQ5tTqnkHabPXnsU9GqZjWGJJwM1RS1qlZmkdLK4Xgwa8uyDEMPeGtVJIQgkZOabftNCp4vtgctxhi7DoIYQo4B5DGFFHLshma1b2ywaVnO5zMAs6ksBndUtII+y27TxRiPcwORc4MxQfkSOSSupFY4QFi8uUNJADaQGshM1dUIIYADrWl0xBDhfpO2uyGEMM/LslQ3l8BgUjcSiV3UBnPvui7nLMK6LOfz3VwgAkFdPRmbGkGY5JLxHWNOFAKlSDFKXSZmT13MKQ1djsLMcDKHknBr09U2bXcxd3QeDyF47gXOQpGEWlvMK4ulKJtN1/e9ux9P53E8Lkt574NvjSPG8zIvEy6h4SBB6tiMttu8lKq6Bo4BMGKEkAhMQtNct5GXpeglq8pTSgBqMzjIKnNiJKbARARjWmOO0+rAA7fVb2ueJyIwt3k+rwzxnHsRiNga8x0ClQIDmk7bzXZ31RG1ZguwEJEamnqKCEG0gVLQWqsuQUhNarVabK5zajpsujKbLtjuY8qd5AgCIrijod+khFcvDsMQuz4Tc4xpGAqYhiEKRwemqZS2qKoEAK4OI09d7HsBbJ7L8TiSe5TUStPZc+jrovf395/8zRcdUq02j0t/vQlDmFHdwCy1zhJQS9EWSVBrdfdukwfOPtn5NK47Wg7ouiRdaK4SWL3NZR6X0aC7m51aEUYeQpc5Jg9iu/3+5np47913f/oKVeigAAAgAElEQVTjv+v77vSwHG5PL7443L4qWZgTu5JwgK3OVk3NmtXIwh61wLSFxIYiARKgDooh906yZsxDG37jh9/uO795stnvkojvhrwb9oKcZb/Lb+uSzie9fXX66qdzGe/RAlOYxvHVy9f3d4e5TWVu5/N4OBzv7u/v7qqVR6YPAzGBFFAoQBePHenx/Nnm5unm7uP3WDzmqe9y6mJMk5FtruT5B09unj5574Pv1lbCB3A5HsevlvlU23lZHjoOG79598l3SrFzRi2BuAqfDfzWU/v+t6+Op2WzxzhPVWE2C8VWa582+92TFPr71/PHPzmCIRz7LgcJGr1yW+bZdL3WVuEDgZdm8/E8N7Tq2pdzyKJBq/pcZjrX7TIAWhbrhxCjxJhrqY7K7E3ncTpsd1t3zTkC3cP9tHs2xJBfHG7PCw6Hw/Pnz16fX2zfSX/wr37rz3/08evU2PN4X62lENhIa62nw5Ejm7oZWTWQwohAwuK2Sq0Ijlp05QOsRj+0BhLRJYomcDAAsFVcuAIoRGtm9KNOxkAMIjDYLs5Na1t5AcFotalZ6RTsb9gX6xzILO6uvpIf1qnTiOG6yrFY26PKywyBcg6Na7rCR8/f//4PP/zt3/+NH/3Zn/7dzz//xc+/PB6nyAM8tcVP96MWl9jHAJN5HheJXItCwUEoBa1GRGBzV6cGAaLnbfRoY5ke5unZpnt9e/f+e+88eXv3wYfP716eXt6Pi3OV4rV2feJBwhCm2WBYvGEgLJeusBkCSETMYGamBmAViLkCbnxxwL2AF+bqTm+CyfCoKHjz+WNrTkziayW+iJTswuZ4Az0QOaGaRoYBktAIP/ylX/7we+/dnV7P7TTss6dUWbx1+7RsNqmSjW2inrdXm5DkfDhP4/mA4+BxbpOF8b13+eXkZXSOYENrnlMuZeRLFByZkTmxgSnCyZ0cTBAwBWEH3OrKUoEwmJXaXA8e8NFHT97//rPd2+Gr4xev5ztICKktumy60G26QGoT1TXYHuSGMi3afG6FKotr4pwlxs2m0WLFymIwPCa8u5nqZQpxwN4QcNzdaR05LjqzC2ASmAjGcHYXIgIJQfli8U/kzaCXwUYI4kIWrK0W5GS0hnmt1I1HrOayGLv4f104dxdZytdQ1Jo/eDFPoq9xGDz+l/9f+NA3FLhvPv59rOoNm++/OOwbOVrf/Pjmx/39h/xjj6B6mXIBmKu5rj4DKYgIo1ktupL3mjerxmBmCSEEDjkwiRMziRuZW4OAI4PRrNW5uJnEwCKrVogc5ExuBuU38Douv9rLibzMrXAzekTHLyxSv/Ahljqv47g90i5AzusU56sEeOUyMBM5X8D49XdsTWm1n3gjhl51gkzOqx8BkxCtPgvsDnU3JzPWmAMziwiIXLW1ChMia6RCHCKnLhpqFeLITauZcQgpZZE45E2TSliIRNVojQ1jU7TcxevrJ83qohMUpr6UakDXSz/kLsuwQ8pSTB2GOjfvIid3r7UuZXHDVohY+k3os4SIpRZvY0o0DPmzz35uZb67fdWWKcfY5dRqJSJEiAguaAWxMMhtBQeIOFAIDCEmM1lP4FosnPmyR8Hq1C/BLjCnVlQ35NyR+MJLs4bFiSjGACDGVFutrbZagoSUwm6/owZtunL4o1kQCTEMm55jiDEuy1K8qrdSl5RCDOl6u9t1PblZaUNOKSUz5bIAbgiBO7cQh85cj/NhOo+UiYRbrdE5pvwXP/6bb731nY/e/VaHyAggdZVavDXApcyNKXZRWBgwQnK2xFHAXo2M+tjJgEYW6ng4H+dWtFkrqq31uZvdVUESiMI29Su51LQ9jPfldJ7GIwlxCvt+n59uctxf90/RutevTn/0R/8ODoxABXMI6InE4Qa4WbFWS5t9CmvLAHUyrLdnAq/1DHgUSDuZc7hcFeALtnshE7HBlVguZpqrmM5xGdkUzNTnqE2nueaeUwo/+etPfvzxJx99d/u//K//8/vvfWsY8s9+XtS9uacunZfD6/tXm7ff/r1/8Vt/8n/8xaefvchIdSphEKOm1NZgPFUDQEKrB7n5ReFr7lgxpAuQRZdaeCHlXtKM7eKlBXNj4Tcq/IufOX3jhopHTih81YVf6u6l8DJdck3B5Mag1ZngTT29YNp0cbVkOK9WCriEqqIxhYsPnsQoKcbEAdaIhYVlLrW4gioChSDMLOIxs6q1YqrugJhatVobGpZSzFxSCF2EkzfTSqZWrAqLiLgaGEyBAHcGdC2EtCrjnWDmRGVRZ5fc+YJWWyTKQR8O8y/9Cv6nf/Wbv/P7v7ZL8bMXL4hrqWOiOLdaW3PYOE2lVrpsLQxuIuj6cDqfzY0D69TmaYpZun6zD+Jo7iwcW3O4l3mppg+HaRwnbZYi+q57fZivUlSzaW7TWOBImdwCudTF5tnmCUxutRKhlMaEVpG7AIsPD/X1iy+3L+Vb33/69J3rru9BD+fpqBqEV3COmKjPYb9LOagBu03eDp2rAaiLE7jrOoMtpaweogCcISGEGFPOMScSqBa1JhEhMhFp86ZupkRKvGrkCxFiD6v68HA8n8bdbm+tHQ8Pp+NEZLvdkELvlpbmLMIpjtM0lnmz5S++fPXq1evvfvfbbz/bfftbv3q4/6rVJRAHZgu8GWJpXe6NuetTnMcyzaMI9ZvkjqmcW9MuYVrqex/kt95+++pZRzBiaU1bKxKEObRaRWRZzq2h6VLvTyAPkoZ9b64stpQZEiRoyJDkJMqsEG3erOpxPF61QUIYhp5YWcSBy2LHoOYGsMQUqCU1WmKUlGUfttvt7tPPX7i2WtVcQ0QXgpDCabvdaI3T8bwsS61EcMFqZmlEnmLsh3B/P3UbbAYZhj7n0PWDnrXWuSlKbeuFmmMKiQJJ322ZlrmUdgG1EQNRCMO22243IQat7XzyICHHxFtewjKepnm2uriV4g540KZjOW93fSm1tgmkrXl7OC/LuNkOQ79JKYUgnQx930VUJnj15h5SiKlniXe3969f3b386v441th3myvJfdh03el0YrOrzdYJtdYUWplrc+yu0GfJESFQqEYSXMSJOahwjBKFQynWtMGVmRBZ1Wk1b3Bz92atuaWOIWAhkrX7cxGE5GqFzfsh7XbbEETVWtM1pDWG3JqWutzcPHFT1RYkbrdXNJ5rawSEkCQmotSalaWqGjPllFKIF8/S1pgop67POcVIjvPx5NoE2kVmdwNC4N2+H4auhVqf7iRFV4ZJqe324b7UuWkho1alBjJ40xKCBNkAXluZ5vNpPAIOF3eYolVT89iRYQXwwYyYkDr0fcxdbq0xY1mqeTNd3JyTxJC22425m9rp4fC4mmEiZuEAzzmlnOXS2zRmPp9Pai2lUEortTETkRMbTEHE4swcIoWA2pA6vP3u9X7/5OWL10WPfZ9Vy2OLBGZhpnletDZTaiqmps2ZmQLKXNVUm61adm1tOS+oGK7o+no79P3xPH3x1flqh91uiDmpOjNFIcQ09DsJcnd3KPdTqerOIIsJOVFMJAEMub07nh6mQLzp2ZqXqVRM9Xz/8ovDy8/PrERgQtz2O0Q+P9xDDYlQvE2te2e/zGWcxnmu7mCHNtdS3ZwILIiJQ2InM6ulmastpVhVOFx0jbyUKLkP/cAp0tW+v76+url+ut/ezBN9+dnr29fzPAKO2qzWmSAhRF8TxNgc6nAlmHkjo+QkHiJih26Lvo+hg8RFBJv95vrmuk/yg+892/Th5uqqy0lLNUXSfhlxdzu+tFudu/vb6eOfffHXf/23P/nk4+UTwIEeCIADZR0xHqd4I1BEzDHGEAOTlFLqMhOBIgtp1aa35dNX50/5/J/x4uvH0uV5rt/GL//go29/58OPvvNu36dhk66e9P32o6f74BhLO6RYMeUP3ho+/+JTSiVdDVOpy/Jl5Py9j65urujFq9u/+JuviKEVZFSbeuNhtx363TSWjz/+HCMQgT6Cs3M0NHeDRUBALNQJohA5mdLsDeOpTeUO91DCt37pKSMSpWVuxzqRW7Mpp81+v2OmV69et7qw8Pm8+jPa1fV1TjeH+4fT+XVfsd/dCD/UOqrjNM+lfPH82Tsf/eCt3KV/+/Dvk+fiJIhdSMuynF8fz69njgjCXr2JBiYGE1iE3NhML9jTZVe4biDZjfji8QMnQB5nN/+akPA1OWjt9y7ZRHC7yA3cDeSGRo+MLFzkgBc7GQbc3pj9+NpC2eMc7YAATaGtGbEZy6rMDGRqCuNM2vuv/fYPfu13vneaxz/78//0+Wdfvr4d3UKfNy9e3M9nr6cF7gbigJjS3eFwGo/TaV4FPSQX7RfEYA24WOdcvb+fdNRaAdyf55evXj55uttfd9ub+NWXtYlePevqPLalOXu/i/1+CEuc4tJxf/fqlcMUTAwImTiJJJG6lFaVCcT0JiLt6zGX1nbRv4le4RsAFn3tUrQCi2vTzCKrZwfXVkWEV+G22dpv5z5qaNVMHKj45V//wfOPnn31+udzPT3bvjOVdnu423Y33SYMu4QUssYFqu5tqeO8qLm5Hc6H3anvruL12/u7V/flAPNqbmvun7q9AVwcLEgi6/IWyiCIra9PzU2bIHWJ2GpdbGr6hN3wKz/83rd/+M727fjp65/GjQyyu7s/bncZKcFVCMN+o5GOp3MtVQ1ulFOuh9lE2R1KTEg5OcSIazD4XIs6LqQZ99WS1wFAXJhJnEFwKC7aCgGLMIRImGh19VrPtgJEvP5hDtDSbCVW2QrXEoFYCat3uGJ1/TZ1N18FjYA5E4Osfa3fXfEvJuZA6z7efB25vvYF/q883lD2/usf8k206x/1wH/UEVJKqqp2KSXAWh6YiFjY6pofRw3u6rp6ZRk7uVOQxFgJVuyAC7PB1BrpeuurTIgxJUm8CnTVyGxNnQidrMZTBjjTatuvpo+Sv/UCdHZ3NTOHXpz/AHiDsdMjgAVC4Ed9OACs+j6/IPHkzOx0CdrUqpfa9eaGtF7k66TKDBEWUGBno8BwYjQQubhC16RCcqhZM4UZvMEgLJuuSzlUF2KSxKYKAkeJOeWQl3NtSy2tmjtzXF3wc5eVWhx4v7mZ29jOSq4p5E2ui5UYOAgRWR5QyzgtWJnErY1E0nWRqNW2NHcRZpauS10nkdXZYGhez8uo1o5d3+dw9fy9q/2OqpRSW2mYUFMDCCseB3VSFnbQuvVysjdm9atPvakSuay3mJWXxgyiKIFEvNVlKUyUQgqRjbHuSFayYmuNhVNKrs1aXT1lYgjGLixd14UUbZWEEoUuppRTTpKkWjW1lHOXcp+7vuuHfsPmxiUKM9CalVLnZXFyFaQUEVRAsohXBwEBkdLQZRT81U9+8oe/9y+duTYncwqBTAJlBO+EzvPc90NIyaDrki4H7PqdXbVSJ3ERkj71yq6uR4xuZNVcjYxM2wqjAxyAPg1NfVqmQNxxmJdzGU8xphRi8ND1+yh7tnj3evziF69hyBQ0kBncsJwniHhmwFmwhvKweddlAmGBFq+1ajNtiBTZ2XXNlIAbuRlcwCQkX+eq2uWvia0cFBYp9eJauboKCLNbMxUJzIXcwBxZfB7r3/709B9/9Ne/+8//2Xe+/atq9Kd/9u9u7x+I2XV5+fqrcsY7739r/1ZIOyx3hQe0pgILWYhCa9pKA1YbAF9ZmbSqk+H6dfDr476ALhaN9IY59XisdM71sRdUe93FP174/oYp+/UywR9fP/tjscEF4r58eb2zr6RdXp/tzc9kOB77VwYxBVn5fyBQiCGnFEPUfGF95t1116f9zS4PnbqepofTeCJIVS2lanN11zYRiAIhw1afhcRg4pUIxFyXYrAoFDupS111xQSyi35ypaf6ehLgBidiiIjO5uMCE2U8LHp9jV/5/kc/+KV3bvbhobwI4k+ePhsXKnV5dX+4e3hoTc291qpUzTxF6UPcbmJOcrw/s5i7Nm1NK2qtLQSRvs+tmbb1hDnMp/N8fDiptmHIqRMJXYMPfZdiLEtbBzNmMYc2IwJTSAHMsesygFYfSm0OV2vk1stVk3malxcvbxvVp+++3282wxallbK0UufewtDLbhuuttl80mbbTd+lfHd7fL5HmYMhschclrGNXRdTv5tOY63KhNzlYdhyEBDNMgGWUuxyIsLDw9kaVJVIiIXEXRniWvFwaO4PxfFO18Ewjqe6lC5nIE7n6Xi4NwvT4XCac61z3C3vf/TBPI/3h9vb15M1/f3f/U0vy/39q3mZY3NwiIFSRFV1W3bbFEMLUUDeZVfTuerdGW/doB/wK7/2nefP37t5sn+4+3xZSlm0atmEDXM4nWYiLmUhSIpBvcbEQ59ChCo2uxgikycmmNfaWrPmqF4XO5emlQstS0kpuru6qYFFiLkVLWVZimlDa9w8GrupVq1dSptNf3Nz/fr+oS7QxQKHHPsuwdFclZBCSH1nKS0zuwSsbB/AL42vW2lIBqIQQ2amVlCLMme4qbbVrNwlW2OOIaXAFM3OZrPDy7KYW2CG6UpEEwn73ZNayrLU6TzP8zyP5TzOF9MMYmIhxBSiOtW2OLzvuu02CHnTOk9100mXemIRDnVpEixEHmtdlurIW+4d8fXt3atX969fnU4L4libpt3V0G04IA4p9n2X+i6EcDwdb1+/GscxEmqrbakxLyEmFgAsIapS4CgSTWFmKcml97jwRE0ixRgliDOcXU2bVTUFXNnYvRnGsZpRjLzZDF1nalFVa2lm1HebrhvgvsyzNbRazRoJbftN36W5llYrS5CQifLstZHXOhMjxBgokGtr2mphuJEaa1No0+k811q7RN5zIc8BOXchkpOBDeIkVlqtFbW0pY248DvKONVpORGFEFPXpS5vYkopRmZKKRBhJQ7U2kBGarUaB8QMiQgBOaMbYohca53nWQLcrClKUVNktmHo+65Ts2WeRQBos8Juq3k0EYjMrLFwypcgq2YLyFNHqxKH2VMMKclsVXVW5RjzfjeIzEspm03e7/unz7Z3ty9ZaszIzWuDGVLilEMSySTNadIyzXOZaZ4NEBbGYtosdoHJzbUu40knEHabbUxhnuvh/pQi3KlWW2kmhJBCYMmRJEjqczfGSCiBTTJyh5wZ0KUUGOYznU4WxFJEpBgCJ2QxCS4poTw42LebDTu3xWxWqDvYzSEYuu54XsZ5qhXmqNrK0mxWEnR9lCgNZS6TBzRUq94MtoYVMEDFqbmAo8SO8hCiEEcOIbijNTINsNSW2VVyIjdqpamrQJZSRFg6CqCmXosBhggO4IyuR0y4vomh03X26hKe3zx574MPrve7t4aw7ftdt40hOrTVMJ/1k7/45M9+9NOPf/LqdCsCGc9VG7kOYWfDZsMSpmlapilvNysHYV2AuxlISJJVK9VWexR4v851HsBuCH2MkkI83i8BYWVGGJl5CxF+TD/+vw9/9R++SjlIoDzQr/3we7/+T3/p9373N9774OmGyXE6+6vT9OX1QLU/V5uOp1tty5Cvhq7vZRe8ftZ9VRRkoOhz89k4pdD3g6kIR+w7UFb4ea5oC6YZ6uAENSiqFYMzo9ViwSEX8IYZEnD36mEesjCsaSAEZqNkjURCjJK7MC/amqrBa6t1gu9jTCFEQgjS5SQhJKARLeDQMN+Nr2rcvP+9d3dP9eHVK5NANkzaxjJJJ3mIDKm1QouTm9kFTXpDUVhdRowu5uIEELNdYBIiGDnzpRLiTT+4Luou9KnHjozgrk7sdDFCuoTWrAktwuu6kchXXxz3r/vBb7C1Hg+HIDarZrjAOkyu7tT6p3nWcytGW/z67/zg6fMnf/PJjz//8qtm1PWdNQOAILUs7o1TMJ3nsW5yVtfpYa7NIDBX94ogRDBukAoAARCkno7Huev6IXXjcjyeTtXKfrMbdkLdHDaQWKd7LaNii13XSUcxRIphE/Z36RUsmYIZLIESUVhjS0JtzRR0cby4nLmvJZpEeiGMfH0K3tBn3rBs7BJM5oA/7pUvpNcLV98BIITIxgR3Ru6wKLBFf5VCxy9+8eVZD/nUPTzIL7549WSzPMuNZZPQFWgxdaXVf/zJ02e7vv/s8LMX93fvXr+9e2u7fXIaH5o1QzE45qIS2M2bOuDMiUMiJoJeNI4XHhY4BgfBl+YNbhYattCHBR/il/+777/77evPbz+Ou/Qrv/qDjz/7pKYWh81U7DhN44nidqOm0zTVqkxCFFfOWdd3iTOqUdXpvKAhUow5A0Q6azUAj3GbwBon4DAyXpHKlZbDq35wHRCJwAx2F4YRVfeLbOIxWopCCqvDtJnyqlpxYRKGKV3E4zBycyNn0DrvX8Rq/IhP2pvpZ+UHELBSF21NO7nQtVZZ1f+XGdY3jn+s+u/N9//9T/4bHiGltGIxuqKvfEGyzK1VN1uYSUKUTEaw6qoGJVVTFChgxkzulzhyh7fW1NsqYCIRdhETIlgxr67VVE3dA5uROtEbAIuZI0esBi+rvL95bYr1dqagx+oWGOR4c9uHe6VaaxURPEJaLOSB31Q9euSkBjZyIpFLKKVc3nAAAHaslr7srrbWQTYnOAOB1pR1N1ddZUW4AOoEZWsiHlyEdDIno0jETJGcCUSff/UlFfgCKCCcc3+2qZQRCSB88tkvoIBh9wSbJ0PXd1pUS1nm88j+O7/9W1/83ecPh7Nz4tChG4iwzOfQ9aa11JkZtbZxUlVCx5s+9al3svvj7YfXH97e3j3ZX93sbw73R52X58+exhhRULlx6iRmM9VlRtTYRQ7BCOpaiweGEeC8hputLBQSUICaw1wiaWtExEBTtFZzTCxCYCIudSbKa+DUw+l+02+GLnMM4ik4iFBb9QamqPD703EaJ/XW9d1m06tbabWocuTYxZhiiOnq6uadZ8+uhi3VZqWt6odlmcM5s8S5LQBP5TTNZw88dNl5f15mV36yedp5ujvc3h7uFtR7HK8scGXSZgzhKEISwzg3kRgoFS1tMScX8C5tN8/6qvNSR4iHKK8eXh3uj9N5KtZMwQgc6Wc/+6sPP/zw/fc/Snm4u3sgYDqO5/EYCE/3V6XENp8gtE1bt3yzf8a0+cVPX/7oT/7qbz+5wxmLN/ha5MQDOzWvE4RJJIisluRjHb2t+RZGkSEOI1rYdDUkuyTsqbqrEQFC9A1DzQun1JmMyZmcc4yXK62uM6y64bgUADGEQHE6e8x9joHc/s2//tFPf/bzP/iD3/3e97/9P/7hsz/+y3+z2Q7U4vk0fvHZn/3+b777O3/wz55u3/mjf/1/Pr3q7l7MMUhT63MOwSaf3kju1/LHzORkZpd/XwFuMyJ6I8/+B+vdY0+0xmHSxfruwo++sJrtgko/UqpW+ApupuuWA18nBzsE9qYg06Ngb93N4RIuYeQcmSOFGAIHANTcmppR0UXZxtNk6q62lBlrrrAAHTAgJn73+TvzPFtS5hokMGj1OVJTg89zCzGoqpMHFkSKCDBECTmnRRehVSAK1fURTE58CQN9dDWDt1lRWu43u66PVL+4u/vf/7f/4fd+75d/+KsfqI+fffGpajscWhziaT7eH0/LXENMfd8pqLolxjub7fZqn3IGk2A3L1Otc+6ieaplGk+HlLogidytaY59122Pp3Y63D8czjF1+31fmk9L/eijd2qtZs6UtOVSl1paYLQ2wcVN1/yU8TS31qbaVkutmGJgJuQg6ryU1uY2p16unuyPJyvFU4yttKHDdgBxIaL9tttubt5//uzu1fmP/68/efvpO69eLtNCAIPLsIt97KUIWHheQkghJ2c+nc/TPC7jQoDkmKUHMJ8f2GEGZoe4GBv5KpNevO33MqQWhAmoS1nKGEJv6kudl0UlRAdSn7qddLvNOOuLF/cvX+Huqy+7Hf7F7/7z6+u3l2k+HF5oqN2w2wy5wZRUq20zvf/eWyKh1qVoJSIOwgwJTMI319v7+08//3JyHXOGGQlH5tVbpJG7VWNedwjc59gPuZRaXfvdEFOs1e9en46nlwC6Dtt97Dpyqk4es5zn5TSN8zKHiJBSADW1eW7jOE2TqxFzJnAzba21pUG86/pSypP903la5pCYESKxGFGDo86WAr/9zrub/vr18PD6q9M0lZBiSplB43k+vKrPPqKuk82mDyGbVVWU4qWM4ziZOlZtV/RA3sc4bLKazVOda2uK7T6RcNenYdMNfWIJ2vxwf7q/O5zO41cv4IbI2HQsTPOs0wSr6DK6TeSOpmJm2A7TbtcHwTLX1qzPy3a706l5oOk8uY058eH+/uEw77fT1VUxpT/9D3/78hWmB8CBYC+6l9Rj06PvRKGngtzh+qbf7beElKIzrJVGwTfb7XmchV2ETMSNJMTW7PDwQICkNKRkulbqbpVXSxASJnEXX8rSlqKuMUnf9UGErEFbK9VdyzQe748PR2hd3Y3x1k29ugacp2n6+c8+DgJhhIjYSTfk2OXQDaVoWRqToLF4CmjsDebezN28GdQPByQpJylRvu7A1fEw6bLgl76brvdPNtvN7d3r48PD4XA8n5ZpKrUanOZlBBAiQhQiAjOzSJBpOj8czlNpOfVd12+2PciIsCxlHEeHcbP9VV9ra6oESin23SZmoUDj+Xh/eBCBEdBABAlwd7OqVpalPpwOz59fm6qpuTuziPQAqapZBXkKAcxuGsCttWWpuUPPSDGHGKdxSZlj7Pq+Xxe6IZPwEEJY6sM0xxCt6WJOwyYMmwhnIgkhdTEuh3sXOLOaqnvqxUzmcwGBU4hdNqvnZUyp23b9bt9fX2+WUl7fH27v74uC4DF6P+T9fj9sdkLdeC7n0yQs3ZOnQ9+51RBZksXOlZZST0uprSGEDfysDa14zNKlvInbOtrd64dScHWTI3Vlrqe7Y+g6QVSraCQx9tv+eHcc57E0SKAooZooNQpIUXLOIUeFVDQKHkNQVAJCpn7oYh/KfIwdUuDYeUiWMneZt/vtsN2Uap99/kKX7i4nu10AACAASURBVPVtGydYUwBBAoigXkpJiUAXV/sQkQYwYcg5dxwDPXm65WBPrrdPbq4ChZjSk5tnH73/rXfeeW8Im4dXt7/42c//7R//+z/+k7/47KfAHVa3Y0SgZ1TjyOLh/6HtzXply5LzsC8i1lp7yOEMd6i52dXVZDe7m4Np07YgmaZEWDYEyPIAG4bf/BP8j/xsvwmwwQcLtiRSEETSHLrJVhXJnqpruFX33jNk5h7WWhHhh5XndnWbsCiD3g8HF3nuydy5h7UjvvgGdTI4g06HydQdntK4LhmtTGiVhlBgB7xqhjqIKcQQghkcWmtzDvVCRsZUGcSNrs5wwHVd7o4ndAzWbuC1zCD86P0/+u3/+Y/w8f+CE7q/g3/4W7/2C1978x/9l3/v+mpRub8rz3q5+PTFh/ef39x++vLp62+/c/304m/vv/3dP7+5n6fVcx8Z2kd4naB5GMKw33T9NsbIhFry6Xgqc9G5IDfukRKMjIfQ2cAUCckRHdEp2uGQ56kIow9x0w8xptXW25t79bLfj1dXF7tdf3t7AB36HvuLDRHd3R2effr840+m6p/d3N8/vX765I0r86U4kdtaV4bd/ejlf/3f/hf/4p//4Q/+9fPPPr2vWVoMN0GWw1Jrba7HDldXc3UzqszGpA9seCOAhF6BVUTGLf9Rz34J/oo3RMCDWxXOzqYgq2YKgvmZR9+ctRgP3oLnZFX/KfOm9o9XgqYv4jUt4ruCwMEpcBAe2RNOh6N39vf/h1//5q98xbfz7/3x73//Rx9/8IPbaLAVumDoHVXdnTsZNl1RJ9PdfkdM9/OpDc6J4W4xBQQHw4RD8m6McRBFTl0cNkNIQmL9plOUivkbv/Le46e73/mnf3J/k/u3cfHONkkswW6mm3ldIm+ijJfvvl3v63xz0ryELo6XIzvm20mC9H1aTtkdHISc3FyaLb0Twd2IRX4mnfBnVF1m7mgEq/bb5gxIIPR97+7nsGzmEISI5mWG175DFP7FX3tPNv7psw8/++zjstH8+W3Ocr0fAofLy53a8vLu9rjORtg9enRxcbXZ+vH+/vj8dCgaal3Inn7pmlSq//DwEvUIREky1uMSYx8ouEnNno81koeetBmJGBm7OySKJAoiWbPDuoEs+T/67//z195+vd+El3ef8MgM+csffS8M6dGj6yXr3XwnirrMN/O8LPO6lt1mNwybddG76X646kcZUJDzmuecs/mCSGXsN/3QB0rLtNSlmheHSxCi4O6q2iT6YANBSMDkQg4ra6YYCM7agFdzApys5gffdcCw2+6B6lAoo0V0OYPIG2jFZtbAEwNR05i0G4QUMUaYqymA5j3n5grlZkHeSAAAs8AbN+JBoOKuWv/teFl/je3/V/QKQDgTM1nc9IHryQDVWhuz6uwew+5EHpp0+cyGat9WHeRn/hsAKMyciSQJk7ihZnX1mqtl06quUHKM5+QvNKUTNQHbF2WF5N7Ue+0man7iaCB8m6icszsbWl+82cQ2roQBoe0PuZ0Vew8t/MMBpUbRakAUuZPbK2urlvBl7mLu2oak4zCaWS3mZ6kxzvLbAIotZqJCnAM4cEjBQBSCE0qtiSMYhao7UGy1QkR9vwu9ZJ0DswelCJCyU5K0YF5KOR0P63R494035vk0TYeQxprX+XgXQ+xTbE6H7lDVZdV2iaQYNpJCCkRqWkIM67oIBXd/eXe7kUep61OXEMFCTaZkRZucNgixkNLZIkzNXJgIftZ3cjtOAoAeuJFFVZWYvYkfDO5WqpqZmqfQD2MCsC5TSolZQmRA2RFiNNVqXqut03FZ1tO0AOjznLpQ3ZC9aDZVYso111KZWTisy1pOs6556LrUJWFhZlU9HU9LXvpx1NUDUui7HoMpQUHK7hQlXT+9ruIO6dO2k6hqTCkEgCrgggATra5FtdqZTV5z18UzKwP6UDaXNa9TXu+n0/3xuNR5v78IIZqjFl2XpRQ63N4f5/u+j8O47cbxfuiJeUid+jB028PL/PzTu88+vbEJnATKVpmbCyHI2qiEzOHVGpTa/ELwoK9u1gBOIHIya1RTd4WqWTah4OxOAq8N6iFpnDkhYjOHa+wDGay6aiOoI4lwoPlUY9f3w/Z0XE73q4Tw9I0rWW9uPl3/6F9+QEi/+Cs/9847v0ChLvfrerzlGI6nl08fvX39dNhfYFmXlMLQdy9uT5KXs8zR2hgXcEgI5y/hfpaEgdzOKPMDXxxtsMFE52AVgpsHFjQu+MPK643g+mp5/Knxkv/Ua3ZOY2jlDBrlixl49UY4T5ketJVE1MwUOAYIziJHB7XIQpBmU1vX02rVoc4ixA4ic3P1VEOM8XScS13bQ0VVQRKFQhRGqFoleOgSci0lAxBwCKGd8VILvKF87ooG8J3NIp0a45hBwhy6lFlVjUnyvHo47Eb8xm/8+ttvjLUcb++faZmvLq6raPFS1WPXjxzUjUuOKZIpCW823WZM7nacppTSmhcQmFmEF9Wc4T5XqVophnEYBnKqRTVXU0jgFEnNhE24FiiBUkw2uDuTly6ByGupbnXNpnXp0tj1fYixag6JQowMTqkrx9mA1GPcJsCW9VjqUnUlkZjIPa+rQu3ej4R+M0SCq6rl9PntzfFEayGFVcpxYHKIpm7sU9epoprm+0PV6gZTctW85IPasqyoZ3K9CQRkBm1js4ghYOgG51xy6VLHIFMorbWC2DaXlAtzIrDHLvV9yFXh44hiWqdJn336cj+O+93VMt+Vss7TEWFdllxLZo4icegxbjpQIqauS1nrNJ3A1Pfp9u7laT6uWV0XmISEZheoBgIu9vvAS6mtqHczzTkvxVRJpCsAUyCKcDWrqtYWF1XPGZcXvSlVNRCHEMwoF82lqgEUzxQ/a0fFIXCgal3zfH+Q/faJUBIsbd3gWiool7IuRVgv9pEZfR8fPdlNx/Ly5v7lfREDgVIvMCMSMyxzzmVhwjKXZanHowPoe3Hl01rErcZcaxVpTqhMZMQUg/Qp9l1MqQ2UeOjHU1xiqEPKQuhSqNlLcVdhgIjMKK/YbwcnLqWWUte5ehI1MoUW1kLLnMchlqKn0zwOXS7RzRyDaVpWnSa4IQyQlFRhHqKamEcexDX6QTSID8vsBIphIPIoVYQ5BLMKNBPNRjhQZooRTDHGJNypttjJB6xQq1otVq1qGrqK4qZ933V9Z2a6mJbChK5LIhFunazqbGqqvq51OmUzmqfFKzGLMAmTQCIHdsprPh3zmpWpgIKpMRACB4OAmEQ4mvl4Hdwc2pJRDKpOiCkZjLxcXz65uLgKQT779PPbu+frXHLxXGtViITNZgTcTEspWs+qHyaKMQUJd8fnrsys465LHYUgEihE2nnPLIA1iwEzF5aUEFNwolyKKVJKtSoxcy6NMq/Wkk5KqSCusGznANsQmEIIwbGs6lYc1c3WtXgzsNBm/MUhkojHxJtxu9lsU+pUdVkWli4EqOo8H+dP5lqUGXl15irCKYlwBFGtJcQgUSSY6pJzboRiSQEdpT6FyKqBQOu61qz7i6HWmu/z3fGlGZ48Hpk5pUCQZSlaJ6vT809v7+6O3dDtdluHxyQphtB5jJZ1zWZwiEBraIPEWlHYhMBJgvA4pgQ/3a2lKpyzei6muQJOTcOkpMUCBYoGUK1UpsJqHKSan+apoyQdSyAESBeQxFClk64PEuk4IQYOHTvZUpai1FEXYiCWNef7IzznZXI3bjwbDkLM4EpwEi8FpoBgTNhdSAxIgbpExLq/DLWs8LzphieXT19/+s5mvJyP+Z//9u9/548+GMru7uX9hz/+6OUziIJ3cINWbPoupXS8m62QsDB5bYMdq9ACDhIdJeNBycLMJAJo1hPEIYFYCK62OoiIG+Dm7lbzkg8xbRiF2sDoPHvTuIlEUKcAMg9WKxHSkOg9ynXdLOO3/9Unf/Fnz/74977/7tce/+Kvvv3uLzx58+mjINc34aPp8OLu0+fSpze//F59Dx9+8vzZ8/up2PFwcl9yOXKg68fb99//PPZd7GKIIlmKErkvtbgCpcLbFd5IcUlEnMxQGyejT15rLatjKZRZhkidpNS7Ieey46HrgwRSawObxldyM4KBKWi202GJ3XEtR7NTCNP1VQqXm7XMFdPXv/Eu5s33fvhnEZpCAmOZ5yUvMcayrqAWfEZnHzuDW2uTrPFA0PJlzvWfPvDb7afoV2epoTd6AF5R89ES3/wcpdfGmcQh8Dngjx4KuzPZ6uF9vsDIbxVc+xCxJiVBlACORtJ2gaO4KC7wzrtv9Jfd/XT3vR9+/9knx6shwWXRvLjOywQTDgGutS6qK5OamWdesgJgCWkcVM1aExstdRIHHrZdt4mcMIZevdaliDABh8Mth+PV5W68kKdvb9WOtzeY1+MQQ4wddxylR8Exn9ZjDdz1+637QKR3p4NOa7DQtQ4rsClCCKjnHIgHOM/czjyOL0IA/tOcmqY09Ici/CxQcHc3Zi6lujsRN0N3CWHYjIWOy2KP3h6vri9Oy+m0PDeyELDmqVRsxj0s3d6/7JJ0fUcpzKWWqvOSQXycVnK/fvJkSPH58fZaLtJOhotuOq3lCMDclWMo2dZ1gkoIm/3lJUNPy3MARn4Gb9iBUlVVKwL213jvq19+8+fe8F4/fPHD+tlye/zsxc3n+0ddF+I0zXCQeRQe++GssHC/Pxa9O+Ri4jGQbMZtnfPxcMx3tYmfmMmAUquwcJAYg63K3LoIQvMgNriBhdjPIQXOZA4ygnlzNEJgJga7N1O2hpk/uO4+YKzUgIg29W/RcK2tUFM7eyCd0zrbBU1MLbj4Ff/RHzhYD5wAPDj5PnDq/NXN9jO9089u/x/sq34GvXpFX/gb3MJZW3xeXRpMBDdVNyKEGJnIzCt59WYRR00SIpBqTb2JM81QiEHGZ5wvUkcOL7YuixXXbFYVjgBhpppNz+RPghgURERy7h4Z7QQDBObGgmwLITOgZu0kO5MTiNncqlUWRkseI8cZEWtGWvaQyvoqkAL+wEsloiCi5A7z9kcKiKCpttXOFH/DOYxdm6bRKQoFcKIQhBojD+ZsCOCAFsaqtbpDa/Ofdwrk6lBq7j6urtVKVicHO7Ji0+TiHoMMXdpsO0LZbPpxiOsSnGma8jTnru8Cb0TYqrkCzm6o1SpjzfU0zfDaJY4SjqdpiN0wbkIIwtQPvcPPliLMZk7iLOLMkAfgkImdiFEflvxmFAE4zIhdQsADX6YJPENqdllqrmteq9Z0GWsBFLWauy6nMvRDv+8BW1ZfcwHDzFShCpANw5C6vpasqMuaYwxnex9uCFWz9/bj6eRTCa6b1AdmJpLUd6USSy56fzylTaquQoEJgbgPPUmsFTUvLhj26Ucf//C91997evF6LbbmhUIRMQDVLXQR5AY1shA4xgCm0gbcjhSTky82OzHHLoUuqzNyrZin/Oj6ws3ymsOQuphKyTnnPK/sRrod+u5ye9EPg8SLUvs6+3e//Rd/8Z1npxvEQLU2KL5dZ25tWhj5bKHo6iDAY2ikPpi5VdWHJAKcgfvzUgV1gyEQh5/gQc1Tkzg8+PF6tUrZ1aqawp2JODKxwBC6YIa8qBlHGVKXlqkejvmANa+VJE6n6Vt/72trufu8fL6M+Wr36NnLT7To/vHw9/+T//B3/o8/ONZSjbfDYOoG7vqu6YMaWG5mLegY8OZKCGaQQwgtHO68fJ8BozNySiBie/iWDxAW2iTuldb/C/o/f/UDfub3SnOUNzMmOIjhrzy1HgByFnFpKbWvDBlABLW6mgW2wKGPPTsvU7airtDZ2kRQV+VAksTIoMhzzWu9eLSPLJq01rKuq5lWIqtOxLlUc+26EJPU+1xKJokxRCYquc5Lhqk7Wi4ygMSRCFUrnQOfyRnS7Myayl1ns/pL3/jmb/3Wv/vzX3kHuL2f7g6HO2I+TZN3dJqnm/tDLrXBiOOWeoLBwdSNfUwxrxlueV3dnIk5JvPObWNmRG7VGXR1ebkZdi9f3s/TvK7qhppLUVuLOsvxeO/OXepDiMwkzMK1T26GdTWrqCWX0nIGnKU1916tQr0GDV0IfYwdEZkjx4hxTC9fvNTKsCIVldFHBOFx3G53W2HRaiy4O+Qu7ljSahnu6qXomkIfkpRSl2mupZalBBYODAeDhSKBrUCE3RozkEGsZnBrJF4z5FJYjMDCEkIcug6Mdc3rDGLXnNOY1jKHbiDuOPDF1TXqyeo0zfN3vv3BL33jS/vt/njY3uY8zUeJfZT05PHTR4+eJGb3qqZMFJIUW9e89GMC3FB/8KPvbbcbCb2qr7mC28xz0mp93+8ut0A8HI5lySDkxaqRkRB1IURi2+33m83F4XBa8xyiXVwNEvQ0H0AnDuLqQmFIXT90TsilEKWuTyERUT5NS86q/qoxANxrqZPOfcjrsk7HZZ4m1cpsYM+WazHV5Xi7xBhF0jgOwzBsxs3hfj4dZ3PlQEMft5txuxlBtmZ3F3Jp+WshIMXendZ5rWqrAVy6LoQgMURGcTsbe5jquiwOd43rqsusWsOQmECmXnJt8uftJpBzzmU6le0VpZAI0FLdKcbUpag1Rwl11bvbYy1+Oswvbg77vQeJHDmmDYWhnOa+G6wa0Ekc59lOc1arq+e6TAYvhFrM9AT21PNm3/Vd6oeR2ddlMqtmRCbubu5qYA6bzdD0UznnnJVZNBic1lq0VnVtzyB1lFolhb7v+7Ff17nMKAVDx30/DMOYojJLyb4sZTrVkm2ashvlpQaOBGfiEEJMwiyqNk/rdFqnBYFUOKghBRcnhCBOwnBiZe67KA6AXL2UWtZaciGPjx91QvXdL3+lT3b78v7TZ8/m5ejOABetRUFWHz16UtY8TVMupeQqMUWwSGsccTxUt8msDKeuH+XiYhyG7vJyv9mO2+3m008/yaXO87yuq2pZq6orS4xRul76vsu5xC4dDyi1gCHBmT06jSOZz2ANkeBEpKDZEYiJeGVB6kJV18XdEALSNkigICHGFENSPTabzmVZcs5mykKl5FIKYHe3p5TC/mJgztOkZc0pyjBGMyyneZ3W3Wbsx65UrEXnWUEmHRPIYWuuRAgdjZsh29oPIsHrauboe+67nkWYqRabTvfz/LxmnQ/17qDbzbTOc1Ht+nBxtek3kgZXrOewyNh//GIu2dK5NGKREGO0ucAgDbltxfKai2eopmEYthtnDRE1HylyZFaFFSNnB6qqCBEFFpYoFRpTGHZdGqR4Nlb3epxz6rHZxc0QoVmQOVjXhdTJWvLxMN+dsI8cAs7QqAgBuS5uLWOUQrQYqOvCuA3jJgXBOKRx7Db9+K1v/iIbb/vt00dPTvfrs+/dn14eXnx69933P/ju+989vg+MgIyJtkOXXFFytpqPq6VY4Jy6IMLZslshajMiUdNSjhLsAU5pVgJnqZ0aYBnN74cMJA4yZWaAQdE4wNfTqxrAHyZiDqmqtYIFrjBDl0Q4MAV4OtyvL28+AeO7H3z01p9efv+Dw1e+dnv1WnryTvf00ZffeOstJzvOx88/fXG1vRreu3jt9fmTz17c3Pz5stzHmMbN9snrO+Rymm+LnUIgECRSvwlMXaFSK7xWkDNTMbYiHMjgam6qZp6G3mm1kpcTFqx0FbahS7HrOg7itRSOGiOPI0Sw5pkQWHgcu8vLpe/CxW47LdPy43muS62RUFK4ZJyC293xxfWj17/+K2++uLn96MO7+9uTq7cuBq5wMuMvaJfYW4R5g6KIztFrzRaiUUcaf8C5JTA/HOJzk312IiX42SQZHIXctdZGKjB3VKX0QCRxa6+Rv2rPX70PnZ8d7sQPNR+hlmoOEaYAg1VYqXbZDW+989XXfv7y3Z9/93sf/esP/vz9Tz558eJZ7ruOmFgKC7SCiWIntZSimcX6sQ99WO8qsRC5sIy7Tc4515WEu12KI6dR0hjiwEs9xS7Mc8m5jGP/8uX9/d3ta2+Owrbdjl9578133qCbZ+v9izXX+uJ0f1q8Ook4OSQRNysXEzALOo4c2vNFWyMNrUYPgIg3xoU1i2P6f3hgncPQWv3cdFQEPh/BtnDD4WLN1c88hsAi67KEovEi9WN/vJve+/rPSaS1TB5LSCH0SYhstpQCe7feLbkEXjkrprlab/NkIQTmaFbmudRqZPWuIIi89tajLpQXPN19fsrLzFnI0adECGpky2pUq5UGVhKJMwA1STT4O6+9/uT1y8un4+Onu/2Ty++/+Oxmulum5XS8f3b3/DUd3nrnrS52x+lI4ESx5lKLlZVKtat+38UuhEgQE91v9jOdMOncz3BYreQxhi4vdV7ngARyBAqIbrDSZGxwQhsZkfPZb8rOqeGUAocoMcYQSYTYlaFsTm7nqDRXR5uuGrmezXjZ4O3eVjO4q9pDv/eq0yEQnEjnSg/tDs75eXS+HfxsRuyOEIweLM9ebf8vONErBIoeUrb++turv/23+qu/5hac7Uw/aM1aw7VbCgHIvTEIH7y8G+DZNkJHweBO3oZ9IJiTOYQlirBHK+pQLVqzoRjpWY4r5OuSz5UxOwSQZiVOCEx0vi6JcJY0gkSEiZphB+ScXibELsQsDhNnJ8fZqKxx58wcDIYZMTMTAYpgVtrJbnOikIQZ5Kbw5hX9AH42lRPpw/3unVl7cLX37SCBERD76K4Oh8jY70I3ZM1znkupYAilGIfMSgIjg4Aik8OtGmCFhchqNbjDq4DmhXpKnez2w/5iiJHujjdpk0bbHQ9lOuYU+5p9phJCSHFkCl4XjlRXhH6oZZ1nK+s6DmnXD2Ecu5hCJ5vt8Nqbj7j2YJuWGWjOViaC0AlMjNml0TqCgI2dvTTttDdlFp+pLg5i4SSiDy2oBGKQO5Vaq1aDb9IGx7lUTZSmab5f1k0xCglWzWmti+VqZuTRwYG46zthmSc6Hsvpbur62PUpxhBj7ELHzBJ4Waa7sl71u07iZhzHYWBiZRT4puzHUjXJVA4xJFtrKacQU+JeMUy5Fsz9JqsdPnn2F/c3v4ZLqlWXcgeeezAoLl5vlwOJE2etS85lv7sseao61VrWnGOfNhe7Lu5j0O22k3TJx/vid4phHPZ1uctawj6OcYNe2JaOumNGGnqdnVJ84/qdIKFi2D9563/93/7p9/78448/ORYTbj0iO8jw6upjEkgLJVA/U/GpmbSRcEBFNctOpmJE3oy4WsGAswqpZWkWc8LZpvFsKOcwd3K3tVT3CvwE8mnxYURhXUsJiDGR27ocTmvZbqLEsOb5T/7kT//gO3/6P371v9lc9JebJ3TlVte7F599fjd96fWvfuVbb2T95X/8P/1Bt9XAQc2NTEKQIGxMBBZapuzEZ/f1Fu3ghpYSC7CAmN1+suQRQ0jaIqhe6Sd15PknPaytD+JBg+m5Yj2/AjQOFxmISABydiZu1Yy1JdkaC4eNhIhI22LIxMLqGlIQFnISiJmVtazLCiNdFNVIors3Jm9Vd/dXlVwiqkJCCAwRbjpAdaiVxdahTxSqLtW8CpvB19WEiYhjlOlUqfFinYgZFAFyAifWXDwaM1dXkc6KJdHi+d/7tW/95t/91X/wD/52TAvQJez5dLq5vy22pE1XSW+nZV6W0HWxi2G74SAGBSjEAAKYY0zzYfYKZgkS4sCBudZMROxiRn1KF5ttnfH+8aPTXHMGiWbTJVvqiaQykTuJIEWK0cgRmErxmAhkLGBC1cXKcj4zDiUIwUVqRatvtep0ug8ctiMeX47394dphlaEEUMX97v948evPX70dNheKO7upry/6lhSLpIXeHUJYYxDL0FLzuuylpOpgVC1AIKsGMI4biXKshRCyUUJJpEpUF0qimlVFydGzbnrY5QUQ0pdp+aqCq2lnEuCWmqKTOy1VunSMHbLUObjwYEfffjj68v+595+HOOW6ORWum6zu7je7C82u/3hMN3ezHf3h3Y5E2Oepu1mu91uHF7XmC72wzAu3pW8apaq+f7OHUhxYxrh6i7aaOVAdEhkM1XUzWYQtuyaBo9DZDYSByN2kWXoksCcKYUYiWVZy7oSnGXohNlRq1rR6m2xb5E+HqwywV98fnM6LMe7loJHDAYbR+YQ3N0kTqUwVdrKdjteP94ty3B7czdPs6PstmG7DTF5qdr1Ukpu80k1MBBjcPOVLBOckdhDpBTFHbmCmcG0FtXDEkUYpBXzBPIhii96quowMQXIU4h9HwFTq+rV8oFFBCqC/dgPfeq7rmol5nktx9OyZpumcnePXKbtZjNsRkrpMM/ZdXPZU6gpXoS4nU7l+ONnRHDlqpa6pJnW+7x2K4Dd1VCWqR80POrGXW81x7jp+46YTGvTF1Q1GFltLNqgxe5PE3BqixLaKMIdhFqXXEtMPESjQFKZnISRUtd1/TB0Map5OR2WNavBSl11cjcGvCyZBZ1BYuN8q8HUNK+wipTci66zKeAb3/Tdtu9iQi3TumhZDs6SYkx96mOYrXrxDvXRdvfmm++UedJsp+lQDKeljpsNiM14KYcuBCWvZMpEMTAEJA4uarXoss7EmkstBYZFDeS55MG8jtu+GwaJA1lhIWesudZ1kVD7oU9dHLdRNafO+97daF7g7hxqiJAEDh5jcysEEzXPU5CauQRzJ3XlwPt9X6urFgneddwPMUiEp77bHQ+6zHfmGgJEQGzuGoSIaL8dU5eYmdzcdVkAVKIswqmzo+VqFANJ8m5kjswc1WmelkW1PZzevL589MZYMYOL6cLJttTBvSxZnVLsJASrWKbVs4xh1+19yctyqHOty1LU6hPZhxRO0yzRx11PFA+nQychBDE1Dx5SlBDymm8OmVbE2KuRKmuM8ApxdAgDcQjV12VaWFmEAGEiZz2jCYJu2/W7joIxIfYkkUIiOC91zbXUotdX3CcEqSI2dEh9kai5HKiWdfIxoqzedRJ5F2QbJNW8oBzmciiLXl1EFut777qSIj299RElLQAAIABJREFUvmDR155cPXr0aNPtrzdPWWM5+V/+ycvvvf/hP/nf/8ln7wMKbNBLxOhMgRUg2KLNBM/dQyQSAokC1YqxubTbR0nOw2+CtOqBz4pYJyIwGvrkai2tmMhaB6HajL6Bs+LGvcW+4kxQqaoNEtFKLVpB4W71nEyVICYOTyl976Pb7/3l/4WA/nX8R//+17/21Td++ZvvvPcLb/W7teqHh/nzR092+113eRle3n14f8BSbkOUEDp06KRoXRcj6QZOPbWWeDUXRiQ3LrUqw4ypGgAWIo+mppXII2VHKTDMh4XYuzFsx1GsrtPSbTj1GLdsZlXnaTFBN26EaZvtPobKvk4zTHF84c7x80jlKpBPu3Fa80ePHj/+W7/xzW///g9/9x9/EF8vVjnKJi+OSud5ID1MVD20DgxkQAUZcK616Nzdg/z8cmNQ4NxvtBNGDyySc0tHrCC4fIEs0qCx1rY+TPsYxAhERJDG5Te0fSDnsziutbv9ONZSDI5OzauMqJ7T1fClb77+X/13//AP/+xffvDB9//8Bz+w0tWMORdTz5PqChBzFPOMUEkqJ+qvOAy8TO6sIHbx4kvh4sliz5vLrvlDgbXQnHbzqpyL1UpLwf29nY6TL/31hnZBHm1p/2ZXv4zTXTge/PkLevb54fnL+e4eZXEaOqia+nyYxqsrV/UEK1OMUdCtx1WrQh3VBRQQmvG9WzWtqz2Qe16RcAAiawHfqg54IHZENXE/n8dWktdlFaahSyyylgzXymamCYwt+osgO7NurpS7fuMcalkap8+0TBkpxvl2eX5TzLAZOz3W3S6FTpZ5upuP44Z3u3616ohpv72iDVNi5vsXBz3VMGIYelfkZTq8fIkEHrkbeocvZRWmbui322H3aPPWl57ur0YWPax3Lz58+Z2//JER3x3v8snQ4f6mPN5Lutiebu67fljuJiGus51uF7Ewbrp+GJiYiVI3hpm7ft9fxTu+W/Na1uyV+ySBfF1zLQsRezASZiMjYaXWZDDBKrMwwa3Wsx6TycUoWkiekgQOLFzMijZaFoOQUU3XkkqxakGpwAugZGqo0Gpe1RTNboge6FrN3qxBZ6gPpEYH0Tn26GyY0kK/HASY6rktehjz05k/8VPb+WXA3VtGPB5aLTzwsOiBI/ZvRpu+QN36m6JiBUXjnL3SpbRdRNMEusMalqUEJXI+08/ak1kaDwdChgdzZRCTMJhNzdzUzGCAMhhEAhZiI2fnBx1io1kxQEIiJI1k0WAsNOEUmfFZiFRNG+GA0DC2B9IFnblyPzn4ZwKqUbPpsvPjq4kkG9WFW7Set3m7C85Bre7OrqwBxqrmYJCFVeCmD7iouYK8TykmMaOipWpzSgwURaL42WIQ4lw7MapQUEAfEwzLUqrnQBJSQDNXC6ihQiR0adhIn4RJ3ez+uIZOBhuPh8O64KIL5JhXTUZdCuRUKsg1BAROZgaPtdSVqSNaiwfLSykI3o+pzqheS60QxBhNAge4nJN17AuHzQ3UpCPewmyd3ZzcmRVgkOEMfT5gg9amKg4gwFpHwhRiNwwUY+qHsaxVAnEIxasVSykFCnmp87xq1RRjzVlzcdZA5BzODkQGgq05H/xeJT4atilGXUsBd0NPFAkybvevpWGbL370428zOYqaFaIQu1iqzKrGnrqC+b7oQXONCBK9Y7ZkyqXCjeOf/sUH/QiJk+m8TMuTq7eXaSr5sK5rqXV3/egxqNtsL3ZPB9KPnn9mllOwR5e7mPz5Z+8PHe/6zRA6Ezf2Qbqr8erx5aNpOb129Q6g0zwHDIeXpz/+g+/cvECp3KW+rAp2uKKJMAH2AEOboJ4fNAA548wZpFc3KwzqBWhq1rNZIAk1uBbNMttbZdBiC80Bp1eI7HkM1T6k1f/MSVXVC0GNcq1r9RICmIXcUc0UocM/++1/9et/55e//O5rZV4+P/2o23GA3s+fPb58++e/8Q5e/wPOKHMpahw4qxIRMzm85OrsD3vy6r5t3AojJkcANWHfKysEAA+Lpn2BYnXe8bP28NXzGHjFLn/g0JI/oF3WrvOWNNfWECfwqyW1gVzNzIHJ3UlAUdRLiF3kgOoO0qUu86pFA0UAzaPaVZXARN6sIHCmxtW8ghEiKEkkMq0Zoh5rVbMSEuBZ6+zuImC3iiyIqeuTxLysUGhb4CxYQzCJqhVzD+ymlkJa7xYynQ4ZwG/+5q//Z//pfxBindcDRatO1PXox9Ph5eGUdxf7y+snNJ3uj7fToiNzg9MdbrUQqKiakxeFOzPHmCQmDmJautSVXEqufer7ro+yVlXixKFyGEQ9Rh36ccmroZi5CHUdp6hanRElMJY6z3Ve4YQgYMEZT2TnZuHGtKrmpXQL9atNx/sujruhD0/32yHeHV4SsNsPV7uL6/1u6LcSenBwZnXizs2swhVGzCl2MSSrpZRcykpkEsBBzDxIXBd1q2oeJGy2u1O+Z1QzR3AJzsHMUF0DMHQYx23XSQhJRFgii7pLF2w7TN7MWMhjZGIrtUiVINqPgWkzDDQt64cffbzbDMMwShiD1M24u7q4kpiWef3jP/ve8bTc3U5aK8F2u6GUfLGjiwvu+56wmU/MFPIa8pJNU1V4HQ06nxBDayvhHhwVJGZc52LqKfm4i6Xk0zwty+LNFHJ1JoQUUqBhk9iNENV4zbYuusymZi2sbcm1Wj0vOm4ECELgJAiBu48//nw+2XRwLSAScjLSfuDUUUwp9X3VYJ4dCtJ+5HE7dqOeTsgLOkYXXW1Zl7WUqoZiXszb3JLIJdAwsmU1bifWmFS9uBkLgcQMai4KVF9ynic63M+1+umwMsUgzBSIPQgRG7MOG5OEwCqiLYXy6nLrhJSCLZpLoeqgkIseTyUXiNCaKBmvpS7L6k6hk94liDAjaeg60bpaNbXKLE29TCoO9cx3p7Is5XJ7LftOpNuOfYzicLMKYF3XZVndnEjcQIQUE23itC7VCgxaoecCCBsRqqWoTbcnUhNGcMQ+BmEWi4lilGVFLpqKhgVWtdTFXQJJNQQBCXFkToRo5JYSjQMiAdVtNTZ3giq0ZnjtUwzjSPt4f/M8BBDMymzqXeebHk+u+sfXw24bXty8kBByyTGMMeXQDyCIVYmUhk7JjZhCiB2HBKIAD7W4QZn5+tHFsqzzPAtzigT4NN8XOxm0VK/KpuKUSEx9WYoJChm8FIcCOabAUvrBWFArJHroyEG1C8LcugAWYmaDOtD43apGEvp+SKmbDsvxeL8slUUHCCBa683L4+mgp2MR8WETU2dAFQlxM3Yx9PsYY1JVJgx9nJZZa616MCM1u3qUhMktS7TtPjJ3RfHy9r6SQsAdgmD3OO6uRImnaVmWxYhTCoxwd3dgTnHTx9CpA/moqyujFlumKoHIUVYsc1F1dyq1uLADpZRxQKToqvM8ac1D6Euoy1zWChS4eMmgtjCQgmChZl/FvVqOKeVSarUQECRQRCEz4WHs4hCra8mrJBCY1aWKUTHNbhYEgd11tYrUIXVgLrnc39ysnVzlVWLEtGp0TZFj6GKIVYgJSSznA6HsR3n8aH+x2xDo6vpqmu8v++3X3vnaa4/fef7p6Q9//7v/4v/842c/vimTHQ9p6AODS17XU5Gu01rMTJphCWoTl7lSXguIIITEwLkb9IfGAmjR8g/2SIA3vEofxvZNld+e/I0B/pOCiNXB3jKoWm3xqvFrzCAPQVikgrKblwkGMMUkMcbTvFLrJxXlBX7vn/3wD3/n+3/6jXd/47d+9atff/3r/86v30wf/fj5+/2FpKvtG6/t+2H+/g8O8wlvv3V9fQ1ADycrM1U95WxEEVUUghBJ3QhmTTYIUhMKoEDGDKmLMrEgOUO95Kx6P4XAQ0ppMBktGTcbTgdqLq61Txi6McVurcaspSCvyIp1lq7v5qnrU++o94c519O4SVePHv/St37ud3/3A4aeJu9TpCWDelir2wxeQRXG52aLW82pTvWhhcVDgwYIUwX9xIv0JzXfQ5n6kGFods6G/iKAdTaTIGoXu5/rZXIhZoDp3Ky0VG5yevhsRy66LsUjYNXUEIEBX/6Fp3/rP/7V3WX3nT/5zscff1aPPUBUbV3VirsFJmFCiOJcwOoBcePpQkLHMjEO8GhOtvCJA3cp9GPcPe67TXSuVQuojI/H+eauElbFMrEeCSvyLR8+s2VT3/3K9X6fDfP4pUfrGj79bPzo4/SDH918+NHp2Ys5T3Pq9510KKVKLi9fgGDb5rZEFNilBmICsRKrQZ0NMGKXDD0b8ZzJOQTys4bhVbHM5o5W/jaGVjMoyXXth95cy5ohlIaUkY2qBzx9a+vJVhwNVHhV+DThNFlVMltyrvcTri6CxDgG1gqa03wsMpfuOiL7fADMAk8uUI+i5DJ0+3Ctu+12POxvbj/NN8+OcGAHjEAPY5tPMyaAoU88XYevf+vrr7/5pNvw7e3zZ59/tuRTP27y0TlwsqHqbCcrB8lHOamVYxh4KHfkIr74kHc+++nFfPQJ0GEzXF1f3K2ni8uLi4urTb9/fvP8iIk6I7PYcXWfS7Y28a6AAxyYOUACszCf8uJCZ/vs1rIEhzjYEE0pA5Urml04u4QYENhJitUS1FBR4Q5UmCpaUVvV1cl+gl4BYH91mzTbo1ddIp2Rq/P/bD0RP0z07a9AkP4KTOnfgDO9Ihn8lYDUz6gOvwh7/U1twYr6uV4CvFmxnzE9nH2CHY7mjnmWJUvzXyFzuIHP5Ft+4AngvKKYVa2mam5nerrR2X0ZzsRnvz4jEKDEgZiFWPiMeUlTAdLZLaelRjaFX4ORz6YwLZvMfgpEPO8EEUHhBpAbgdhBilfEjPb1zM21nU86p5wRgciZSRqy40SO5gDGkaU0r6cKI9foTUy+LGVdKoc15xXmsY8hBgPWvGK2/cW2MhTWpCKWPXgwVQhRaqntlZu3JDx1aRhEAkrJqgtR6LqxJZ7AYK5wlHV2DUSJYe5eC1IIISQtSsaluJasq+64x3bIWovpXBbxVLWoVySkvjMVES51VTc05WgzXoKpGwdqt0ErtRXGhOZ0Zma1lnZPBAlo3uHtDDA4oNQSU1DT0/EEoOv6WvX27tD3gYWjdLmuPQsTq2JZsptHCRJjNw5JOKUUY6TmvKguImTuRYGQ/2/a3qzJkuQ6EzuLLxFx18ysrasbjUY3epoLCALDISiOuAyHEm1GnAeZ5lfpnU/6FXqT0WRG2mggzoiLicCQWBrd6L3WrMy8Syy+nHP0EDcTDYgyiWZimJXVrbqVmVF+w92Pf+dbpuKa1fWrm3EYHr322vrsXMVW3ebsotkNN1eXHztgEh8ctXFJzYokClRlbdiwa9z85IEZWmyDoD9IP9YxxnMfnW/Ah0jAwfvNeksIu3pMUrJIa3oYDi/217tjzzHcf+3hL7/3XgV58vL586efP7r3oOvcve1ZDK0zV4ay7tYX64uz8+3usH/7zXc/+/zT1x49evrs5s//7D9+9D6AQtu1RKHkHiLPz+RpvhsggUJVRWZy4WQNCABIc1irGYqxggMoM33UgBCYiOHWDx0IZ9MmRjNVuY3EsC/Zut8SmeYIQwCkWxYTgJrqiY8MqpBzIgJV8Awh0I9+9MmHTz75o9//nfe++fpbq3evr56/ePJFwklU7t2/+O/+8Nvf/5v3d09KrsLsDUSkEjkAKEnZn3Dy2Rvh5Ow1y34BT40y+9Lid4dSAfCdD95dDYNzEioCgrsdv5kgq3Q7y+EUQgrIejK3V0MANKM7I/eCOCclzoPEgIhszA6ZADSwR8VcKyFWqTkVUDjZvvPcoD9BaA5RERVtHrp72/uCAqyitdScdMBkWoUBG2pa3zQxRGw8HKWKzBMJyTvngg9thGqlSC1zXJzMZFctFZECh1InZxjP6OXL8Xd/771/98d/+Pvf+eeSDi/3l9uzph+OV/urZGm9WRYrz149czE8eu3RYhoOPzn2x+MwDC4G5zjGEEMAgHEYj4feo0ciH6hpGh/JeU45j+O4uznkIXtcdq3sj3J9I8dBq2KRXMSAsGmwbZeqE/M8hsRk6ACNHXrHzb17dRzrlKRUEVURcwSN9z56z+10nKZ+Agd9Y7GtxBWBN8uu65b37p1P05laXS7bRRNaH5kxTVPvxjSVKjYcMyoWpTmJB1XNZuTUiA0JpAKYEmNoXArzZNCubbbb1dMXKQZnZt5751zbNqUmQPUem5ZWyyWgSM3TpNM0lVIJOcawRiLnqoKCmWMxHfo+1VRiXC+W6+W9xtvH73/w/Nn+3bfwvfe+stmuh6l3IVS1zz9/8uTF1Q9/cuUcTDvse4MIj1HSBFdXl85dbrfbyxc314eb1sFmCZtl2JxxbOKia1IeLy+vc66iRaAggvPOeT7ZganVWtMwFJU0TbUWIDIjIuDGL7tuuYxaExOKyDgM+5v++lCkAjHkPBFS0mpmzKfmNRETBcdNcI3j8PEXz32FkgAMZqxAQatoZ5WZQ4gsWMVyzrtdAdTlctE00XnKk4/EjNRPqdaacjIjQ24b7xjmNT/4sNmswQNS7bxvmR1B0VxFnt+8QqwIgM4Ts4qUoodjevFynCYwgWWngLWJrffMNMMQeLZYN43rh50Pftktm0XTts319dXhOB77KecSQsve11qnsVQFAcu1FNH9cZzSGH3rQ2zatt+X/eFg5rZnm1dXlyam1cbD6JomNF2t2RDH1MME1FDT+W7RCCTAPOWsKszovEPGUmW3G0UgJRimMRDESD4SI+WipoAG3qH3FByYQi4wHItqWa/8ctE0bUug7Kp3QgSLjgiDI1MraYQ0Wa3VqMYG2gWt1k23Dhww2wRiMSJuOLHsLqEWW0TghoxVNeUyIK5X627VxfXKM9DUTzfXO6j17OL8/vnZowdnLrABMnMteZomAwQjKQAIpupdG3xnMO9lzEyELoYWyUmFWsUUASil1A8DgjGpWC11FKn7/S5nDXEtArMpm/ehygBoNWVJwATLRVi0DZqpo+AxlULMLnhANCEt1Xt2jmeT2qoEBtU0WTEDRmBkU2y6zhCn9KpbLlZnG+carf67/8dzFEgJCKGtebGEJiKxpZwM1UfnEdjTxWJLxNMw9f3U92OaEoGGwP0xHXvLBQiAeQD2663rVhZb9+DBvaaLDx/f74eb6/2eHQQfZpaDd82Ly8O6qRHEqeZJ86B5xIzjNBbNGtaIiFqNcLa3UOc8gqZUU6oPHtyXSQ/7/uaQtQrVPWs3JYUCIJA1gTJ4h4Egxth4YjQsAkCeGEK1mpKBCgduYxfQlKhdNORgv9+Nklar4BrUkyxrbqcpCpB6FPGRggcmZcKuW6wXa9IOl8vf+51wvJHPP77+8MOXQ/8SJgAF8NBGJILzxfZ86+5t18tutT07/1e/84fnm+3+1f673/1Pf/Kn/9MP/gpgAogAO4AJAAFYmRwYMXmdw1kqGBk69NQCgSdTsyIiVsEczz5zcyWDs3kvAWKRysg4SzNMVcigno55c7ITfxkR+VLVgZRz0TlC7JRr6QAASOajkMLsiqpzgCESI8FcgZVSfHCVKgZwziHi/jhqhf/8Vz/68//tR4Dwb/79w9/9g3/x6//ilwseq41/9Nv//VH6v//h++9/8P5nH/3tH//bX33yZPfhJy+eXOZizrnWCpeqGDrCinQEKTPVbPbAVTOoBsCIVHJmR85j8F4YSy1ysFflaFRW23jmoylVNTOb9RVqpoDkfWAXzHvXivQp9VVBKathP0opN1Umz1O3wDrJL73Vfud3v5lk/C9/+clf/9VnDFhDhOTAGEwABLACFMRi6AABQAHzl2tPmg+dSACMgAb55yu+27LvS0T706XzRzO/j4ikimaoCnDq8hqYoQoRAPDcmieyW5Tr5Jw8+yjH5X3FI7VZQkmk731z/Z3f+dZv/svfuLy6/pM/+R8vXx47v3p6dVMqMDkZK0zgu9a3sZTETC7GDCCcl6u4PdtEHyHpiyMED4xCnmMT19vlctttzhdi0zBNhLhoz/se654hZ284TQmksKPrm8sf/ujy8hW88/YfsblN98i5WvNNcPXxw+0bj19HXgMsPvv05dWr46c/ffo0TsvFAR63mtfjje93Y8rJQIDUSJ0DKCATmAEIsDlDAjenk92Npp2A2xngYDAAQVObALMp4aw7BFQg8h6Dz2mquTbbzkXKU3YL2j7afP1X3jKXro83nfcUbd/v9sMxpfm0iLWqAYgYoY8RKkCZrGTt/PLxozeqXbQvP2FfQqBpSOOUoQwN82LRrlcrKPLVx9+oeVp33Wa1IaUf/N37N9cjuma7PX/w8NH27LwU2R+OH3zwk//43f/09MULmAA8ACJU67YtgBgqJIAMugBKiAY+ednZ8DJpHiRLPgpUYkZRhWI9TJdPrwHgSXj5zte/9vCNh4t2efnyCs2WqyaG0KwWi3UFQ60o2bRq6XMaUh5STgoZ3DqQm3kdWlWNgZmZ5/xBzTlpFZOTv3ZwLbML6JHROI46nZ7zOTh+TowTtFNu3V3S5mkK3PbrAdSYCAHVFE8+dGAGhCfsHm/9+81uJ9L/50tV6TSL/nEI1D8RdDVfrkqdX90Rw5DwF5Cz06U2k2/vrKNM6gzlEZqJAIGZISPMcalqc0QA8Ckn0tCq1pmdwEpkoAZGCoZmIGYIclLxzRpBYqA6C13NANHmyUREM3viblxMTUzvbux05zOchbevZl2KkxkgQDrJjAzmxFWYd6SZeWcKKDPpDslo5sFKMWRiYkMTVGQAmu2DnHPG5EvJiNL4YGBM5NkTUySXMQELdxTYSZYkCRXNKTkWqExUrYiYsJAHIgMTRIdoiEg+mkGaJhHnPC02hKDDmAChajUjFzxzAMveO88epSCgVEp5HAQeLiuHSA53/eH5s+fbCG51zwUHHsxURZkDgKKqEagKGinNVGoDd+oS2y0waHoLB8ySFQP0OBdYZkZExgIITGSqzFxKGacREdumdd6plmm0s/P1+dnFod+nKY1FShImbJq2aVsDE9XNesXMCFClmhmYBo7Rx9aHzoWZIF5K3d3sFssVsL/pD3G9WpFjpVW3IaEY2mXTNG1TsXMSwNUik9UbJrJaRErRZBU4qEJNZUzFYtTVeiXWq1mMvm2adtHlMsXSNiqRcHO+BnZjf7javUo5Xw+71x6/sT3fXpyfn6+6q5c/3izbZdMxedf5PR7vrc6ROFD7xqNz7xZde7ZZn//NX//0e3/7PuiJe6LFVJFsJlDpaVemk4+f2hwPTAYztIgGt2RQmCs8IO8IyHDW5KGdmNtgaopKdEvHnnW1d4zsLxEp76Y5gKmJ1KxV79BrdmRGOhdpBkTgPCMQaXvzWf/hD5+tL5pmge++80sO3OHmcHV9aQv3ztffuHxxaf3NYczIhkBqJ7N/8vwzzqvh7d45p8jALfhtpnZalE+3iGD65aUJT4u24WyTB3MHzn7mVjiv5fPPmf+Hs0EKESIg8fwNYea/EoDxrervhOgjAs0eTkQAHsSJai3KVmsWMGRGqFUVQBGJ5yBnpFMepCDgjM8rmUhRKbWUmtNssw2OmTxxS03DEdsGK/VTn9JYCzDINE3TlGLbSK46h5/OglIRECV0qjkgORfTOGIFMPid//pbv/K1N8u0v9p/dv/BZn98dZwOz148zZYffeX19dlmyGPOOaU0ThMCMNFx6LXvfQhtF2tsAGzs+35/2G4v9PYxMyJkxw58MO9LdYTsne+6Rdmsly5yEUTmIsbBn52f5ZpLIbNsBlKsajGFubQMvjs723YLPRzTOJaca87VM8UQQgjOhZvn+1orI5iACiCQac15cK2LjXe+QdL1euEBQW1Kw5RSFR76LAWGHQAlIM9M5FCkVjDvvHMUYzBLk6pMpyUfHDDT7Hgwl3DOO0T03ofg2LVgHTEgqkERqbkOqoHZpZxVgJ03EFWFIgY4J1gISJFSNIPoplsCQowxNOAQoo+r1XqxXDRt8/zV5Qc//finH3/05Lkw+aZZYS59PrQBuvaCcRr7QYtK8W27ur46jAnGAVKfS+1XK1ytO8SmFnfYj4DCAWPDwbPzZAamWkoep1RyFbOUZRghVyGUpoMVa8k87HMkFcRa4XAY98cyjgAGPkBKmRmRyDtCxJoVAQiD48gcmAJT8ATOARkSOqYA6opOCMlsbo6Tqk1jFquqdRiP2+1ye7aKMcYmtuRMjXIxMzIE8uydD1GqECEhI2IIER0aVEZCJARjYEEVrZIEDLhFjq1rkFMSKd4BBEgJAJRIQ+i8n/trQo6bxi3XbYhGDpeLLjRBVQ/9bhjqlJQZSGobGqnKjiIZESNycFFESyqOQtetHbWHq+vLqxcM7bLbIpDzntDlnGoVork0MhHAFtbbRbcK5ABQnj1/UUpGsMWq67pWqiDBah1rFe8rM8w+omIAaExwMtZw6J1zHgiZQaoCA7SBVh0vFh7JFMVkUIMYFRCRXAhumqzva0pKiI2PTeO6ZfANqeWSdVaLBwJuCFegEds2+paNKjvzHs1KzeMIabVs65TA44PztXfNZr1aLroY/bw4XlycHw6H3f6w7w+q5qdCntWM2SP4aagl15ySqBHOeQKeyDvPqjCOeUqTiIQ4x+saVVdPW1u9uroEcD4EYmai2LREClBNhMm6JrZdNKm1GCDW2X8aiorlUt3M459JundUDkREUpOcpOS+iqmpmhCTiKVJIKBzro1ABp5BFZwDnD/d6MGsik2lsKM4qwhBXaAVN13nS9E5upHCEdxUC4hBTpBr8QQ+QtvBckMhgtqxylAlEfnFstOM47EMfbrXtkSUB819n6Y87bQUZK6WDRSsgpKFiItuSS4AAftGMZVaU4EuIrjZ9A1SgmmSXACMgGHuQoMD1yA2RAu3aKPOxF8Qdi6NAzD4gKWalUzsfRPRs5qmVLIWx8CBY9OEhlxA0YxSToUDBE/QxBBdrbXvabdsAAAgAElEQVSn1q1W6+16m0cg5bfeetzvJQ3l5vCKd3C4AqiwXMODs66J+Ed/+Puap8cPH77z9tfJ3CcfPPmf//P/8vmHz69e7g7X3doPhx7sChAJoiN1KGCi7Hxsw3E8IiAyMxIiiorJvDfZrQpKtSLOOTinUwDewhw/O7aZzaFOOPv2AswPzc8dee5qorvm13wesbmzj4DIc7CMzcfL2UHcUWwax87MSk41F0GZ36y1zCo6py4fCaRsHvKHPzy8ePG/f/b5/te/8+79x+d+0fWvdufLs69/5Wsf1A/ffHMhenx5rZc3UHORUlQ5xDaQo5oLTZYyIWABExRREDhp9JCgipghMnn2HNCwaK5i45B9ZKmtFEjFcjV25B0zEZNT1VQKEHgfV0usFWOsCkhAIvU4pFrh8qpfJUChz8JHy9b9yjffzKNcfjF8/JNXkD3gGYKCKc42PljM7pg9ekdJv/0wCJARCJDvaq6fv36uPr070sGJX4CIs48qzFnWp19mZsimNBOtFBDNDGdqwMkX6sRYAQMahpxEYazgyvIB/MZvff0bv/5GiOPV1RepTzVBGrJPy5InbAIKmWQERsCaqm8IZ8M5B6EJsfNN4LzhbQ/sGJh9cG0XNufNYtX4xqZhyjbENpzfP//xdz/KmTrf+oYo54K27Ch61irHI3hYOGsbbHO+OV6//Oyjp+Ooi8W99RbbFj3nNx6vHl40/a8+zNP07OkX15dHxNVuGiUfT4+tQlVCJUBDAmIxU0UEdyu2sLvhBASQGcmi25FGALx9sA1NSUzJuyxVHYLnjFUMYAX337z34M2zZuOf3TxLNtSRyOAw9sMIQOAZkX1wBDXllMuYyziLbsPCL9jctM/ItmrOfIBcJhNNOZcpueWCOyLWMo438tygoC1AUtcsz766vv/VBw4X+13/5NnHP3j/Bzc3h5v9QSuMaYLCHLFbxmbRRh8///wL1DkICgBg056t2i2I1sPVmHb95QgJYAKsBIjGQIAqRoQ8sbDowb6wJyLKjbcC/XEcy7hct469CKiAZJMsVoEA2JNbt6hAADWL8wQEpgyq6Hg2QVIxzSJV6yzzFAAAshRDRAMyYuST9uz2UWUEYgbHsznmLKKdJSMn4oGSzZCLESHCrBebeZB2atzP0+fEWr0lZf3ifPuHbKq+jDr9Y9GrL0NX/0QYlpuzq28F3oBf+hkn2THckjMN6iw2VjXiObTPzOZgQkRUmPkLYKqGQITIyI5nPskpTQtOImcvCHZy4QcyMwWBokrqjIGYOSAiI55OlbecDTMAYrpb0O5oGLdSqJ8fcbj7L8x/VPL4Jerq6WuReLbAmzW/VuHEw6DZ5xnm3XDsMzoAb0qGjMSExLGJMURinKacUwYBYlJRyYql+IYdEQRXoXBgRqpWpCo6IEcEUATM2+xX1HSBIrCzlCY3moiFBtsuSq3H41EqNU17cbGcBtkfE/C8sVrTODAyAcdE5JgDMzJWrVAyCGBctBbczeHm0yef8qPlxRbaZYQAorkW8J5P6N2cAjnjfXMsg9qJ2jZ7A5ywwDnyDedP0iEBoFYBAu88IVUpqCil4uw8YHgCJ9RKKtOUl4vF2XZtZs8P4/FQSKBpSBVyrkXycdg/fHiPAE2kVFWp4BnEQuPX3bqLzYLcolu6BxxdbGKz3x1evrrk3UEFNuerZbNioZXbbFcLH/x+hKq4cDwYDyWTSqlJpJpVIxKoSSexyt4b6GLVHftBtBK1MUb2Lqsc01RJQ9O4xlczsUIOQG3Mw83+SlCatlt6f77eLBof2DG6Rde8gJfbbl0VvWtXyy1p8/rjr//gRx/8xV/8zWEHIQCAK1NB5tguxRLMQZwAs27L0GD2xSJQFDO9hajATOamKBAgojN3oriDKajcIY1qhEDMCLfBFKcG1F1RBnMg38wyNQVDnd1fcf7NQGo1Q+cdEapVVUEEE5tqWS4Xj9949OJy95ff/eFrb2x+41vfOj871AmuL68dXN27//jtrz8qx/LF7lCtIJCCSVYg88HfifXwS1SqWctnc/alKhggKACIMYIx3YFuNuN3M31qjuUjnEMZ9YRgndaZU6UDp2icueGHcPLFMASe612dF389GYrOt3MSl8/iRGRUq1mY2KMvpeRSHRMR1TpjrCYnb0tEtJNPHKH3LrBNQ51SmqZhSqlIOcGSAOKQPGYprBSa0PjGDCWD1lGsjhlKqfcutmbozM3gvQmoChh4plRAUgGDKvD2Vx/+y9/85h/87m+sfOj3rwzHlOzHP/l7YLs+3CStvg2bexer1XJM6eWLy1e7q1qliU0uNZdUcs7TNHDvHCGAc34YBkGr6ihQ4wnRzfGVhi7l8fLVgWm3O0wpWy04TVpVRc1FYxrQWy2CaEzgHCE4AwMiJjdN0/NnRwP2Ma5XqxmWbZrgPE95HI7jOB6ZoW2giegIggveUalpysdZv4po7CSSs6rDMAE4ouVsLApaQREZybFjQKg5T5Jy8OS8X3ATnBYvChaC75owmycej8epH45jzwzs2FQQo/fOh+A8iuaUUsqllOSYfAg+NFCBmctUpzHXohXM0HwTYxedZ0ULzovINCaU5B0tWt+P/c3Vfnu+fnzxlcM4prH2o8SIhx06z6LKDIA+Z0oJp+RAre9ltbq4OHdpTONh3O9sGo7XTTq7yN0qeu6kTMCAaoTMzhPZ3NAzhVrNqBJzCB7JfBZEW62azbqNMaBJmfbVIGfLWRChbQAJvHMARMzOsZmJVAEjYueCd5EpALBU2y5Bsi9oYJ7IkXlUMco4pziplSL9MIkCErCDKjXnDGgI4FBn3YrOsii02Xm9FjGVYsCOtQoHhwjgHXhUBLFarDaxGXISVSIM0SOJD7ldoA8BkQ83EyL4wM4VIiUSIvOsSKKaQwRy2Cx8CG4YhlRyEZgJhkSO2RmUEIBdh4TOucVyMfXlplwT5vv3lqbOey4lj2NWATNj710I6DmNg5YC7rSmrc7Dct0olmOf+vGw71Mp4B3ETtUAiEPTOQ4qUDvNqZZiIpplEgQ/B3eoEAJjaWMrXIMHBGha2ixDG9C56j3VKlPqgQgJgwO/8rxpa8XjcRqmguAZOQR2Hg2LlESQkGH2bmjb5nzRsgXnAjhTLMTm2BzJ1O/7/eTvn9eU2hjOHz3YbrYIlKa0O+wAyYdw7/49NSN6laaCBKnUEEOIjY+RjI/9kLNMUyql3MJ8HGNcLpcAuD/uxnFERCMWAHZgqAqqUkTh+jqpgXMhBO8c+I6bxjvyZgomzjMTmpmSEFr0nhwDYcpFqhKBSp27nWpGSMzeOdc2zKxSsRbJuSCF2LZd55vWOxdCXHTt9t69FjSWojo7VXBBhJwtRB+iR4IilYQsV5EKqk2My65h8qraj8WYYrMAYDM47FMupe2cc8ReXawC083+hoibtmWKy3abR83Hm/HQP3r4eurluBuO+2Eap5wAxCwCExufNqVV1ywW3VxSIjkEKaZIut/tQajWQgTBQ/AtYzg11QnIO3IYO2cRIJq5ucdiZqZU+1qbyOxJJhGxAuIJDG0YhyIFCEIbQvRNE0ND5LCIcc1MyGaBomOKLhCmNB1tSTNlVVn646HfHbXSa68vHj789ZJw3CmJa9tus1q1Pv7yO++u2kV0Yffs+OPvf/ajH374g++9/8mnlzBBKYBCAbxzTR5zMYuxNdZasxbNmmbZv6O5orEqtdQCBuCBmE50hCIU6O4YAHYrFptNfedKYxZUzKa9tzURAOj/Tb92qpLoJEoxRECa06bA1BCRGVhPZyYkJDJRMZkPjc77UkoMnoClSJ0heyIi4hgl00cfDPXD4er5964/p9e/vv72b31tsb63vX92b3325uPXj3JTyuLYn4kcbvY0jKGKYwqenRapgic/bgTKpNXgJGcCIED2iACCioBMjhxGUCwqWJLmUcYASSRVCw01MZIhKKZpSqn6EJar1Wq9RMc5i6iqSr+HlBIiTCM4hMHrcdz/lx//xW9++7/9tX/+TqDtn/3p31x/Me2vBwSPYKiz7AXIFG7FSvYlxv/seTHTrwDmDjjceuV/afB/Vqv+7Kw2a24QT8lxYKB6W/YpAtyeDRWAjE5cLVOcjzV4Uhzi6Y2EEjeeWnvznbN3vnnx7e+82y7xgw9//P5P/i6GcLy5kSOSejJ04oC4OkQgqWpSkbxh9QG5jS4yMXCkuKYLWxGREYYmkCNupdAwpbIbblIeqVka2PFqt4xnq2WILQbjHGHVybpbLtrufLtq/LJO/Kyf0tBfvqr7Zzgmy8007q7RHbtu2bZx1TYP7m+k5rfefHB9NV5dpzeexldP2uMrTXs7vko5C5pjBHIKnMBkHpWTRQ78POlQwW6RvdkA7s4qC+bIcwMDlJSo8xidlqQe7r9+9vjd+6vzdpDDID03NNZJBx2LAUNsfAgNkQMjZ+5wM+53BTKEEJZt6znWUZ5+8Nysru755rxrnasRUoZSJnUgro4wHeW64dwP+xEXtbsnpJfjlQ0R0+H6enf56tWrm13OYkYpJ+TYbBa11sOYs+Jq6eYcOQNAD6vN8t72gpWvX+5ePbnJfYYDkCFU9uwRuOYitRI5DsiCqhoiT0N68uHTxdlqtViFGG7qTSFTVmImJQNlRyBQerFaQICEwMA3Hue8dAUCdt4758CspKKgCko0B7spqPGp3aZzciGjAyh2K+1kYmZn5kDxJHxWU53dk2bXOZhfzHzMeWk4rXyniXXLV7wDSRDhF6fbP3zd+Vv9g/DW/+t197X/FPQrAHAnLeX8sNoty+NLd3vHgkAitluTI7WZYXU6LCKqzcl6qghARkhECI4AwappUWGbARFGYnKYAYHIBE6Hb4N5zSUAU0Wik43MbdfjlEUBc16h4e3GdDsufHLyOync7RRAeTqfA9z9w1vA7mQ9Zjiz4kVMUWdzM1BiM0Z0tyEZiGBWpgweUMAcgIfAcycUZpf3miuMKgHMrOYKGUoABO+cUyvaiYASY1yGQNHEpFSphqliBGT20RabxjmsmlJKasl5a4tnJhGRKggcm7Ayahrs09RPs6ZMHAMYFjmRc5h8EzwoqmiCXonMc9ayGw83/Q4dtMumW4W2A5ogabU59fDO+X4Og4PZ0Gymw5wyE8HMUFWImRAZsc4sOVWttfrgY4iFSh2rqCKj1Oq9DyGqygmyQGL04zgNQ0Kg4EN0IxAqwjiNuWZmdD567wlQCVxlQ2hj0zXtqlssl4tFaM669aLtNsv1xfnF4XDoX7xEg363PzTt49fur+LSirWuXYQO0CAlycDsHTEBtD54IU/EjA5xkuE47RXFxbZCDsFHbQyKb/wJ42QMXcvgmTlpSSUNpY+rJmBT1cYyXD/ZKdiqid/+Z4/ZpJYCAAteaqoOA5Nvm/Wy2TJ2ovSj7z37D3/56bZxKpWAKRN6Is+mZCanMUcym3GW0ySsWma3NrhblOCE35DxCTxGsHkezU+4oaoh2YkmbzrP8dOujbdNSgJTO4UY26xinFtu6JjMrNYsBs43xGQyf4goajnBtQ5vPjyrU/r+337x/U++eO+X3r44W56fP4CKVtVw+uo7903rq8P+6ZOhDMqRTFCLUqQiMlcVt32eeXriLXBkOBvL2Gk85qBTQCSC2Yf7zuyKEPBkj4C35vRzlLnNxeppoZjfJ4LZFuxuc75Nx7Z5jOZxIARHxLdWC3hindcs3WrpGr65voZq5lCrqhrPEL2aocJtciQSBg5d04U25qHmJNNYxyHnXNQACkBO4IADTouxbLrFahkav112i269298chx6Q2rabmzvsCYxARYuCGqiCQcNYpkQI3/ja67/92//sv/nX33r4YHFz9TTzTRfpxeXnT599EpdtUSmm1zfX3IR2sejY7Q5HrdZ1CwMbp0lEtKqUalXJQvAueHe13ytCEUZP6CmEoIBVYSpyGKY0YfDL/b4eh36awvUujxmqgfdwvdst1q1ZjYEct9z56IPKnJ8C4zR+8bJvGC4uthwdAnnv2rYhorHv97uDVlh0tFnFRYueqmMXvCtSSx3UkoqIypSOgRwqTql6161X5lzo2gb8EQparoLmmBCqqKooEzpHPoYQSBpF5NVq08eQxprLlNK03+/UAB14raqCZE0TiB0ipGma8tg0jgir1FpVxVRUDXIu01RzBt+CKDTs1quVb3yuBUxMRaVeH3ce/XKxfv7i84unHXlWgFytCjFBu+zSq0n6ZKIxrpBtmGpOFYmQsD9Oi+W2WbZlElATgXGAsS/DcL3aNst16BatwgSmBmQGImpzdrADRGBm5yISmZmqscPYuCaGGLzjsBsPOdWUxASaBrxrnY/EzgyYmR2nnMdhQBQAdM4574hAapYKFxcX/SEfZMop11rJilpFD1JqLQwztG4gFWKEJhIjpGkqZWICMc/EOeVapYoQFgCyIkM/qmr0xIWkZgMDhk3TQhvNo0HNmkIIWYtztli0y/VCh6kfx7ZjAo6x7RrKWbRqyZMatg01TfCBAco0pGbpoo/LRYzRi4zegQXoFm2MXS0WYiiltl0Tm6WIImK3WEiapmmcxrTdHh3HZuEvzs6ep+thv6MQS2HnfWiiWKqpIAN6cBEu7q19hEO/KzKJ1PW6SSl775q2I+dFxBHFEM0w51xNPGPjfIcRSB0SmJlWBGOE6KEWQPRd49vWO0eqSXI2ZdVKIABSixmi8xgj+uBEmRw4F4dxMi5FVDSLVCbwRPNS33jaLBbRd8xRsFaogOKwmqWaSzFJw7Fr4sXF5sG9sy40x74/lqnve0PiNJ6dnxNxt1ie1cIc9sdjiLFdLJqmNTViYS7EgtVERHNGImJWM3bkg6vqmQiwGggxzYnTpUiVAgRpgL7PzLnt4Cy2wXVd6xGslCS1pLEiiIogWtsEHyMQEkItFRXMpFapYghAMTrnnGuDx5xkGLIWcs6pYq00jZZzdc6mxqd2PNs8mtvpRIRopeZx6vvxmvxaDPM4gZXVIratB1AErQJVgFCJHXny0QECcWByvuFSStNGIEupz3lQK6mk5XLtvYs+eO/SsaiAx7aMUidLRxn3uVZz5qpWq4YeiGe0CYIPxK7kkjWDFyQzpBDCbjeRQEkACsyA4GeHFQAAhrj0kVzTNRPmhHmqhd1MtQfRAgxKSsiuZVAkzxVURZJksxqcYz+bcpzE7EwYvGOKoNrGzmq2goCsFUuGoZ/GY3+8Ga4v+/6mNr77yhtvnZ+vTDGPxNq0brNZXqzbNRX34vL60w8//z//8vt//hc/gR7gCMvgkJDNVF0MDVEA57wZGeRSS86IMCsd4PawdipemAGMGJEJEAhnsbqpnWyqDHT2Q1AROjm0w6k9aydfb5hFF3MB8osnLAMjdA7sLs0LcL5TnesRRHJ3ZiYqkqYyF1rsmZktm85WroEdz704RxBq1f6YrLq4XHz+afn4h/8BzuHf/w/f/Ma33nrrnXvL9erRaw8+uvwRPGSpHvHVZ18MLy5lygkJTUhgEqzVgQGAc6Skc1zA7Iyi5oNHQDOVLIKVHBETENdch74cdpOQV7JqxI4qo4qaZq1WihAzOyZ20RwHE7VSISckBjOYRiCAxsvuUG9gevrykzdf+9Vf/Y3Xp3T8yd89/es/+wDZ4x2mJ4x2OmMpzESp20JvdhpGAFS8C3n8+QPyLcX+587ZCDiz3BHptm9ooPPh5KSHPJHtwVARGOCEYtnPep94K0ZAhW7ks/Due699+796+9e+/cYkLz/84cd/9/ffu3oeQVbjQcebHiS42GhBECZ2okZmrvWCYipdcM3SG0quUwRyEc7vbxSsaA1tPI7HaRhsArWa0lirweEI+mSzoPMVb7fctoTbrXfLJnLXxO1mu12dffbxEym4u96/ePr8cLM7HAZDF0Imtysi9++pj0ex0i1C2/m3vvaV5rX+4vXhja8tnn4cnn9Wbp7XMSWoAEZWSVQQPCEBAlSBW7QQwexUTaOJggERzYDgSTALAEambIqmpozgUFkAFTp48617D96+3577hMOr/rJZhYolT1JrNYKmcd1iAcC1KJq54OZji/PYNl2MLQpevXp1fLUDgvPclmmzPlu4po1dLapZ827auaDQVlpDyaWHydW+3+v3P/rRsy8AhpOXOSCAg+BiaNtarUKhliO3paTLq0tyJ5xzuW4fvnY/BH9zdf382Yub3Y4reQogRuRQHQpFYPTATKlM036EDnjJTC5d5TS+evT24/V2M6ZBUKUW7zG0njzVpDJVsZJrgjQn0uFisTac3X4MCX30IThTEBFDU1TnZr2UWBVS0qIVq4ply92mKYYi1W4PcQYw152gekraVOD5wZ7Rq3l1U9QqeDttkIDVwWk+IJxoKKcz1i9MN/h/gKjwlr02S/RONKR/5HXHwPr//XInwuCJU3gS28x/gbco3Yx6w3wENjM72ewA4Ml5yn5GiFIVvP2amfArVlXU4HZ7DaFxMZWR7MRQPCGIBHCC1Rn0Fm+6Rcp/9nq2x7Fb9MxuQag5sw2RTlr3+V5PuJzZLWfyy4S4+bsiMjtVE5j1vgonKZEpAqKgoZLOOWhgZLM9uQICmkEpGryic/O3896ZGSgAQ/QcnUekIrmASRVCOF9tztbnNefjfkhjsgKVigEoApBuzrYibc6DQq6SRRwC9ccDADRNE4KXCstVl3LqP78CAgVFFBEpJQF4EHPk2qZj50BtDs4pUqcEKScDWG665bp1gUaAtTdiIAatCnbLWkSbexyApKZkp4YGzjJCBVNF9PM2AoDMrKoiGpFjiIQwTUlElsu2n4b5mSljTccUutB2rQ9YSrp8ebVaL5aLVesXUmTIU0ojMm9X6812G2JkIhA3J+edbzZn6+12tW1C45nW6w2aNSHw0vfj6Nht15v08sVxv7ciTYg5Z6hmWURlOB6H0cTHiqmmjA4A1EwRjEjzNB77a9d5R9ang49+3awdRceWc2bnXIwsYdb3pZKmOlWqBkrMQLgf9k+fPjuOY+vdb/3S27UcxiE5qKu4HvbHEJa+bcj8+fLRUeuHH/z06ZMbeQn4lVCHulg0zvskmg5jWJCehJoAoIgOwZAJCFS0VgEDYgQ6seROU40ACUrNCJ75JHOm2WkfTo/6vDmB6fzAnq6TieNMXjKZq5/5Z4uAKRCRjwBaKzrmWqsqiogBBM9AYFO9uLj/2UfPfAPd0g/H8r/+6V/88b/7g/fefSu48PzJF7vjqzdf/8pi0T55cvPp849AIEY2xlEyIqjO26b+DL06LR44x4oDoBHOcBCeMOyZXgg5T/O+Cqf6xmDOE7gluOodIn/ywLp1ij/R28zQENFAEVkJkAwU9UtLxGz8OvcoZvMRNasiCNA0cdEthn7o9WAKMgkguMYRUsnZZgW9AhE4MCZum3az2X7v7/4+oBdTFTMkRArEvmPRWkWGfdHSS7aLB/c298/aRRObCC+fK8F2u/ns6U8jd0QMDOpQSVAMKtZa1qt4fSNQ4de+8e6/+r3vrDfsYNiex2M/fvzxx1kG3zCyEiFWyzmZmuOQyxhjXCwXsWlevHqVxzxNAyK2cdE20RPXXFKa1LSqQtGUkp+CIojAvh/2h2F36LerBsgTYfBLUQTIVQAARCFlPVz20cFmxatV45wLwanp0I/9sa+lPDgD5s5Ed7tdLoJo69U6Nv7YH/JURCF67romBoPZeXXeN6ESEBBJzTLlIStUqApdiyrKTMH78+3qsEtlzKpKGGN0aIo2N7vUrJqRga0Wq4uLM8/hWm8Oh0RATYyTpODJe89MzByCb2IULSmlVKb1+qxUy2lMSaZJTNCzT2OaMkiF187Op5KX6+5su/WN2+9vSjECIObjVJqOF4v26vLlkyeX6PjBo8f9cXTeL5bnQO12M2YhJlovV7Ol48EkT8l5d7XfP2RYrdflUPYVwMB1xOxSyunFOEzje+99NVVVTVJVKiKoaSlFZnG3iKiOqti2i+WyjZ7VqpZqTLFdLLt1b4PU0Tu3WHTtYu04VFEFcMzk+Nj3OWfESkTeo3MIoGol53rv/hpsdzwchgIgAJIBACoAAbuJCWcDQx+s7VzXBbM6TSlG3y66cXeMvlGpJmI6LzjVDMZpdnTiEBwo1KpM5J1bxNhGJ1Cc0k26Aas+hNVmuT1bJcT98WgwibFzoVs5GuS4z0MCZmga8THEQFLzMAztootNd7btfAzj1JsBMTSN9w5NYdG1pghqoWmmqdRSgmdHrh+0Fv30k09X6/VmfXF+vrzeXecesC1plCJ+telcoJrBAJoOuiWdXSymdOj7XPXYLpqz1WYcJ8chNtFUpRZjcgZm0o/j5asrprDdbDbblfNz21uJNDoKnrSkkgfncLvuui5OaTrsU7+fZkvq5cIjc55SquajMjkxLDlLVR+o1H0pKKJVgAy6FrxTp5ARCKsjbQKGwOa4niwbiICsYau+5OPFxcPXHt1rYjMdh93NqzGJEtZa98dxe7bLVZuufdS2Ibb8/Bn7pusWMYZhTGsKuVbvh8mn/4u3N/u1bMvOvEYzm7XW7k4TfcTt8mZTtjOdWXY6XVW2can8UJYQhRCP/A38A7xREhLvCIQAwRO8WBQCi5JLFp1dxmkndrnJ3pm3vzfujdPuZjWzGWPwsPaJezPtQgUI9sNRRJwm9tlrrb3m/Mb3/b5ck4kaAs7MB0IffJGqWr3n0PiujexRpeYstUItU63TMILlmUZq3nGMngnQynCYiqlntDuMXdu0QKQKKRWoAki1Si2ACKHB4JsYOlFUSVJzrUrkctZ+16eUVcB5bmLv+Prps1dLUQSKTXTshmFgvjECJBjSNB72zsFq1cQYicy0lJx2+8Exh3YxTnQY8jiMRCmEhpHJu9g2BvVwyFWL8xACpTQUIWhIMu92KaeyXm5+8O33IzV5lDzW4EPwsUhOkhSBEe86tU2kTHkUGn3jXCD07J2PXKpYFcgVCGCY0jIXYhjPpAEAACAASURBVAYAYGgWTdc0i1WLZZ/HKaXUhhiaxkynqTYtVDG1GkMMsUWgopJKQgQgMkJVES2lANFcCiOewDtmcIvY3Pb9NGjHqCo5lXFMh5vD+++M4wj3lmAy5LHPg6/VxoNpidCGB+vu0dkrf/atP/uLP/3un/zvf3753gh7uHe+6ftJDrA5XRepQ80iksqh5ELeNa1vAjnnpVZFBQNTFTAUQsfkHQKKiqFVKWCgzIHnNemM7jKw4/IBZM4W0HGsZXNljsDL3Akeh1Q/tTczkMCNHtcZL4vr5ywMwuyGn5NrBICGfv45NO9FQhdyyWUsxMzMCCiqWlISOzm5V7LlnAkde5S+/59/+3s//O47/9a//Rtf+drrh6uyjve7hZGth4Pd3uy2cUhVzWJRTCJJMxjIvPJjAjKA+tJs4MgTkWqdStWcwBMFAhYtlkRinykiR0IOJpinUmpFAGbPgRUUYE7lDqK5qCJibIkiEEGZQJXA/G6Xnj6L4GyS7fn9xS/9yhsnZ+7/+K0fyVmBIzmf0BwIgc4GNj0OQOe9xOyT43ku+9L2Dj/54v8ND5zpy0hH9wGgqSIcQ1d3lhMAIzMxVGQPx4AC2rwOBjUEQzFQUIBmGBbDz/3CN/7O3//qF15/8l/81//J97/3V1rXjuD99y/HGwCg9eJcCQ7jDkzAgWrxgO2m2acdGDSIwDTkgQeNrUPCdtGlkmpRcNBP0/4wIILzQEimsL2tF88vzjs4W+qmhW4RHtx/9OTpI+d47ActcHu7+6e//QeLthn7MtxYGTAPhiw+FmRStB+U6+A5jxIW3J7o3/2VZnGWT5/y+fkmQHu6lt3DUqbDWz+4tjSJOlAEI6bIxGD9fO7CkZFkgETAWquBsTkAsCpMcjRhgTNzqmAqzpFr20lHmJQewxd+5unJKycfbj+83F7d7m9ef/za9fYqFxUEz9DErgmLnEpNSQXSkPd9ATmSpHNKlq3kAgSbk7Uz2t8OxC64QOyM4HY8uAKn5+3ZvdV7L65M86JpdmlKqXzcAzDQAszAzb3VRfOUgAEW3nlnVnMSwAqNaQL0AABx5VZnCynl4vYiybRo2wCxTDLtkmTp4gIUpkOPgH7RNthmLBHceDNhh9w40Trux+X9xesP3/j48uPt7TaV7Gq2IoEbZAQHPjrvXOeaNjZjyYqmdfauATN6780sJ6ooYFCpRh+IWEWrqNZcRYV0lPH0wcNJqZQkc52kqWqpFbSqzXjwYwPBnY1hViQVEECqvmQrzQqMmVWp+Gn25l96cf2Nl9vxvfHuz0T0/0zD+v/ogf5rHu60t6MYhGgGtRZAaJuWmUXVqphZVVWV422AcDZFvQzoIQJ5cp1jYiYCI6kioqDG5Dx7QpKiKaU0pTUsZvh3KjnVjEQUHXmuplXErAAReo6OiGA+DCJSSqlSQQwIkIiJiZCI0ea9LqqpytwpS1r1DqJ0vEsBGTbAjM4zOQZEsLnN1ZBoZt+KyN1e9tMbFhEBGTApCnk6boNbdIuorYvRhxAIrJZS8iilzpliUyOEEAg9rd88rVbJEJUYmNGbas4SQ4hdKKVMZVosujxNN9cvZoxD26FjKGpvfu6V7XYrVfv+sFqev7i8atuQi+VcNuvmsJ+a6Ls2EuCiW9RSnn98FQhef/XVR4/vAaazs/ZsE60Oz997Twf+2Tf+7udf+fpffOvd//Q//K1t2UoGJpg99wqADPPBNVRwRyuQ0R3qD42Z2CEiylHLVGKeFYFqRylEzbiBWQwEBGb23hNaFVGrm80qRldqaprYhJhTLSoAmmtZLrsnT588e/LIAaLpsmk8s0n9+IOPz0/uvfm5N6WUmsvt1c1ht18vVs+ePXv48NE0Tbc3t7XI6b2Tj68+IHAbt16EkFPajTJhW4jV34h9LNtPhg/Lb3793/nVn/v1BcS3Lv/oUC9GObhms9g8NMUQcDd+sru97GK3bB5kSRorENzubkIXimQKbj/23/3B93/89tun9+9dXe2fX7yo0+E3/97Xv/zGl07aze3VbaQmYnfY1xBXq9OHEFqi1b/3H/zjf/p732oYpgmib4Pv0qA513YZU9mhA6SiZgpAwMhzxyWAHaXFYwX0fJUdGQCARla9Va2lHJuCHSKRwXF9xtEH75GwShGtcjduRIbZZqVz8/DxAgEANKXjpIqMmYnnoN4sa97NKgELLZq2VcxVBudrMoU9/KN/4xu/8Zu/cP/s9E/++A9N6vnJg/0NfecvP/jt//abzQJUSIs53zkf0zSJ5Hly6Tw65+Yzr5ZiCs65+b3YDFDvyAZmZhL4p72vgnf+/zvmFMDRmgVHq+Z8LatvWgU1REcMhCIqUgAKODe/L8OMiWlbRa21EJH3nogBwERF5bVHrwDj22+9Lbn64GspCOCQzQzV5hTk6mzR78fNZr1oFvttP+Vpt+2Pdv8jahEJwCOaaT0upwwAwqnvNvFLX/7Sj995G9EePL3vo6s1X11c5rGgcR0rFnDkIVdJueTya7/88//wH/7GN77+tbWfDtO7Uzo4h9v99cXF81TTmKdcyiTqY7s5PQ9NVxXY+dg2RPTJ5YvnnzwfxzGGCKT9oSe1k83JcrEQlVHzx5ef7Ift5uz0/sP7Y0q329tDPw59IvR1wPXmBCHc3KRxsg+ePy9i29upmhnDG28+O+x307QnsqaBNnAIzenpSYxdTrLdjjmpVCqp9MOwOdmkNBBZSvnFxfTmq+vgXLsMLihRbpcQOsx57MdJDchDLZBGyAOAQBvh4cOHD+8/u70t3/3OO++9c3j44HEtuDtsY4Ps5HDoCWC1iovFQgTSVDw3bbPouuWy24zjdPHi6vb6NqeEDg/9YBWW6+b0bNN1bSlJrcTI7FAts4Ptdfrosg8eGo+BI6ObV8zDNAIiOQttbBddt2qZaDwcttvr1sMrTx56suurF48fP3nzi693i8XF7faDDy+eX3wkED66LEUopQEA1stN2zQqOo3zTWRGzoSuW0SLlx9el1qncWRGI1Axt4DXXz959vr95ZqntE1l+uCjm82SFwsnUh8/flYr9IdhHqvWMg3TAUCWi+XJZnPY9bXUkrMAOOdi7Igol9IP4+4w9T0QQtNAStAP4Bge3O9OTk5KypcvLttu7Sl61wDw0Jft9e7QT8z+9GzFjDc3l0B6slmFhhDVIKvWuaUxBBcEYmyRXD/k3TCWas772DYMNAz91UUvAl0DofEExlqbSGebzdn9zfJkeZt2FURNHZNDYgG1Y/Qh5TodhpLFzGZBc9l2TdM4j0SoWpar5vLyYr/fN407P3vQdItcdBzLONShz7mqc00MXSlYpL72yqtq+u5bH3z/r96uAuen7Wq1aWKXUr24vPzwo0FHAAegEFbwxudecwHQCTmb0uF2v2UH3dK1i4aQlt39ccx9P/SHw5SSKqhCnvUWgyZCjME7r1YBq3e+CRSCmxnA987WIUAMRARSS86DGobQNrERkOvr6+1hPK4kGYjc3FEvogZ6mGCxxEXrm+C8w9aH6IImrUn7/bDpznLWbrEAT1nSfn9TUh+8X627ZRv/1pc+n9OYhqE/HNI0lSpALYYFuxBjE0JgDsg0jqnvx77vU8qihkjM/sXlTYhhboRARqbZGGtgUFVMKhB656axF0zBkWHV2UUG/vlHW1MSMTBlB7FhdnJ+dnp+siK073/vncZDDE7EDOTkdLVcnwDT9c3u8nIX2LyjEEJsGu+j41CKvbi8uXixH0ZoGgTlQ1+HEYYJUzHPwATe+xACEm93u7EHSAAe7j1YP3i4efLKWdd5qen7P/zLYQAi2Kzh0cPlyWbV9zuwSszjUETWY9YY27bphiEd9ns1NSjeQdM60TxNqQisVmG1WTZ+fX3Zf/jO9eUnkgaAPc2AXjIkYCIyNggGrKLarPz9x2eb+6ui09XuapJxfdI1i5jytN+Pp13X347jaASwvYEnj8+fPnot9/XPv/MXTx4+3iy7Yeqvr2/344QL2Kw7QJumKRVDmFkT2HVt8E3OdZqK90HGKgz3Hp/ebq/6Q68KqyWc32vvPdgg1KppTvtSCetlh1RDY2f3l8TlxSfXt5f7ZYse/P3NWeB2PJQq4l337OHnX3n4BRnjn37zO//b//p7b//uAEsABlQg9ZaDMyAtKgXAhRgMUUQAZ6iIAYiRAIAhlDwPlu4+IhEBMSORjz7GAAallmxThvJSa5o3XpbtUz/Pp1ufl19xNyP/67syA3B+hjTN5QBHxtad1efuocfyBTOAOcWqoMDsze64KohshCRmRdWbBsYW1FUBx2CYar0BA+jg6auwPIf/6L/8x5P2FaRAmer4H//n/5kLy5vtdL2tVx+BX8ScfNesdMyai0xac9VJoCiooGucYwUhZh9DVZEykYNSMzTQbaDdxM29hY8GVDOUw34aRogBugW89tozM1WrVXI1cY6d8yow9QUKTb2kXhdt7NZJYf/syeb1V18736yx2ON7rzx/6/KPfv973/6DT64vahmIy3LcphgWdSpF69m9h4f+QISqNUuiwMhiUE2zKQD/ta0pzoCpu0NhpmaoCHoMqh8PkKmnEJtWqtacvfeqOu0P56t7oQ2XV1eL1bKKKKqxTfverR2wgJJA0SX8u//+v37vyeLRg0f73eG9t9///d/75uUn++0N9HuwxFbRqgMMwBSjY6fFsjmhIBny+aN2kvH0fPH4tfvNIm63N4e+R4rL9ZIj3+5vrm5ucwUD2CxCjHF/0w+DniyX906Xv/DG4wBwcvKwicv33/nkn/3u73/yIwABCAAMvgVGyAmwAFaoBaACAAH74GIeJzA9MqoAoAB4gKfw5BV4cG/1pS89e/TofNHF64vtD7/z3nf/xcXhhvodWt8QNiC9d6Sl1qrRB+ec5DoNowm0bcuI05Q9e0Lw3hGHlOs0jAIQOldwMq2nz/zP/OJrr33x8Vh371598M7+qltA6Lp+HIYEISKwsXOrxRqVtru9FNmsN23T1CLpUCItT5b3fvDnP9pdb8/XDwDh6sWLxarpL6Yv/Pzri1d95qFZtKmmq9urqQ6LFbFTBCb1IE1JoRw4T7nkREi11JJqiGG5WnrvVWutuUoWzWbCgOXKpNSnD169/+R8szn5nd/5X+AK2lPnIU77nA/FgcNKnFtXPahaVauiImLSdHE/7uKq4ZWb0qhO4BRe/8przb3m7R+8kyDFEKOPDjxUyLcTJjppVi2FNNbr25sxTcQUu8DBtcumbVsg3N3uapH1ek1Gh9v9/urKEkhGD8EMshUDPX/9JFsqmq0qZKAEoL5mrKmYaIQAFWSsNSsYeHBgYKJVdBax5xEs47HP6yVN2EytzrZSMjRF+akrjo5u/ZdjY0REESE68gJF5F8mXTEzfMbF+n8rdfjXv2x+Gv8q3+tE7gxTR9vt3fvCHIsr9UgrlNnRPMcrcQ5wVpPjF8+7xRmaXExRDA1RETgQfbaclohCDMEFKsTkAMCRCRkQIh8h7YhqSMTkmO9k4E/1PzY+ZnINRGoVQKwIxwpRUxU9JnYNfoJ19dJrZgAqZmgAaFaPxgtRPHbnkJmKiN0Ry4/KpZHOoPp5XMDgiIgZjoVmFmP0npyzlBIBO0emUmutouOkXa2pTFoADRvXdG1wLkhJKqqiCEg4IzllGhURQiBTQkdnJ4talCn4hphjCKFtHBEgSdshe2ha9A5ymRy5cTqUqcz9jilNOedFyw4JAZjJe86m43joD7txOCgKIPhAxFhnzhITHlUTM0OyY50BGRnNGXW0OXM+d9UDzsl/Q0BCB+74+oA0TSxSpKiIiYgkcd6RI1Moeda+tLKMNdUq6Nj5EIkQeRzHWceBWg+HA6l0IS67NgS322+D8z/68Y/2252pTTlvD7vQBBQkQEJL/fD8+QfrbrNYN+DZpPT7oZdJY4Q4BF9X66XrzXmfLRGmfX+zy1cZcue7BSlzMKiAigQKCojkXbVSSwYy9nTIaX91sRsP+2mHEUfNfR0nGdnRzTB8cPWinlnbNl1YBm3G/hB8WC7WMZ79s2/+8yHVrgEy552ogNx5giRXnqOuc0bZjnhRRjL79CK2O/MgISjane9a6WUvxR1D4CfGiHaH+pvZpp/+OAADRCSYTxadQ8RodxfMfHW8HGjNFqm79k4z8IGlioISRyYfpU8Brq4P779/ORzSvYdP8rj3kU/Omq989c0//ONvXl9Aix4XeLjtgSdE8t4xYy6pVhWtPiAYqur8EV/q6UB3Fk0ARJ1Lkj8jYhkcuaB2fB0A5wkcGhDSTK8AMCN0829thgqEqhVIgQDYlAzoWLMMbKAGBOzRhbk0JHehE51rDpUciICiAKOKCSgxARMxtV2sVe4/PEek3eGwvdoK49G3awRAsyGMDEwMgR2TEYIHcAaGJdfddi+1VksXV5+o6XIRN+s2x5j6FMhhJiu5z9N20vsr+LW//0tPn545KgkOHKH1Tcp9llFIgC12sXXLNbIBx9D40AQjAahFAYWQg4sTpJRSE8Pp+pQBPHNJaZymsGgDh8CRDKSUUnKVSneDanLYNu2iW4vshnR9GAZiCC05w37SnEutFczomLkgM6iilkqeai21ZJmmMo2pH7P3OuUpBt82/OqTZr0KzOgDIVmd72LCgMAMjCCGiGSqVg0NaoWhHw/tVpXX6ybJrj9cIzrPQkge8WTVIBsC1loAPBMBWEopZ716se0PY38YaqlENI0jELCHUuT2djeOae4uLNUWXbNYdSFwGg2xLwUYDFQcIiOawaJbgJlYlVwHPagW71zNGQ2Y/HwVqWHOlckT+bFP+8OYy1yRXBA5eEdIiDXnqYzTMCXPRAwmKIwMFjyfnW9i2168uLi5uYUMgKAT7Hb9zXVQjUA1ts3JmpaLrml834+XF7c51VKm4OLszkIj5xwaTkOKvmVS55p5fMdEgGSGJhYctWcBDEuttdS2MTQYxxEA2hgfPrp/c7Oda7uci4slMjXLVXS+WXSdQgVY5ZIARaQSAxNwcETgA0fvGyNmFgBmYwYRrZLroapoyZkdBA/M4MkAlWfvq6aSx2mCqkVADO8UaUNE8A5FrWt5ETe11pxK8N5779nNRFNRA7PbqwuHull2gDCOBzPzPjae1VVo3QIcohfVVFMaxt3tBQCUNDoE54Agax3AU/S47vjQQq8ADryH+w83r792bljH6TDlvtTcNkAe2+gbx8hhe7NNyaZxzElN2QEbI1ktKgLgjqdSJSRTV6X0SbID74EJTtZMSEzkHSKKIylKtdbRJlE1s+hJZ/u5c+wCGMwMHgU9PaVcktYMVNq43DRNE5pC9XJ3uWjC6clyHMsnn7zY9Ttw0C3oZL05PducnayXy8WLi0uttdaqYuhCE7himApu9/304krkePNQgVLqNE21KiAxMRJ99Mm1Y6A5iTTXAZD5QN47551jZseZa9M0jYuiOaWaclVRMj07P5cKUqXWYladB8+cxuFFHhnxwfkSwYZ+KlkAod9NZn1o2ui68xP2RCJVVNIk49CrDqXo2KfgPZimLCrVEW9WixBhPOQqphVSsZLKauFb3zZrEYGcJR3yJd4w15PTZYz07Omr2+3VlPrFwrNjUUXEXERLroYVKFetkqak45CGfjRQZoDGhcDE3gfxIN6Rio1lTMMkRQkgMsTzZtrXPFUH5IJDtQyqWJs2uOia1iHJMOxTTVorAaQxl1oQcRnbwCG5iph1Zl5YyrWvZE0HRYfrQ845K1tckosOEUUFAKIHYlgtl6rqXCAEZozROR+qUUr9cOilJMY5lggAxaM4DwAOSdBwsWpLToBysjk9PdlcXL6YRjldnwWn9zbnVHg6FJnw0f3X7t9/smoefPDO9V/+yY//6jvvTdsI5wMBkDg0BxoQA4LQfKdGnLFOinK8Qb/EC8xZfzfXtQAgHgmthMaICIYiWsBAtczsyzvDNdqdQvUZ9Qo/sxv4iX/66X+dP6MIqIDHKRkdgVqABkBAAHf9zWg0a1VACEB07JUGmG1D8xYLEYGAQA0ETAwI5350cGABMEeAuvcHKf/Nf/U/vfmzr37xZ17t1m2u0xffeHJxfV1KFYHF51dvvbv3rnGhUUEDc2SgkrWAApJziGgAampVmczUEFXvnAbmTbkkRcJm0XbdMvgD7/aqgAiljogApODUAXiPzpMpaVVldEnLjCcRNqRiLmse622dDnTTcxe/9o1nm+XiT//wh9//c4Vp5xdNGwItu93N7na3VQPPPOPl55Z3IAJgQytZAX/6tbefODRHx8kx+XK30AMgM8sl1ZQ11bk8inwooForOpe0AplIMdRwz/mWDimHKK8/e3j2hL/w5dNR95e7D56/f/P8o931dR33DZvrPBlzyZCmAibOg1LOkg2mI3feYHEaT5p2ddqRw8N+V2qOcQHkh6laTlMqM6giOPYuskSn+X63eOPp5z/36tPHrV588OEP3nr7+jq/eH64fS9AVqTY+QU5UpnUCmshrMDzlAZBGCuDAEkzhw0ABFCBFczcTejJf3xbKH/UX29fe+McrDx8HJr46MVH6Z2/ur385AAMsEsAEZk9kvNkqqIVcU4OqSp4dqCmRsmInImaOSAUwexbXZ/HR6+t2zUcxovddD3VfYzQLtt2sWDHRnsAh0AojMUTuaA1lZT3JbKb+qlmbRsjUB+oWy6MVItQcAYGHYx5rLfDhAc39AKaS0FPyKHWvFquol/knvIoCq5ZxNXJmoiqSJomAvDeEdndYqLMOxpROL2/3m9HCJptujlcxQ7UgYmJVnAGAefuN60iR4umASIjz5Np7yIYaAZAQgZDqaVMB0O2dVxVq8yOAK0qItaSd+PtNmPui+mcHCHJWvKUcx7bMTZNKbXUvNtvCTnXTN6pmkxikkHQTI+hV2Qmr6RGIiBmVeYyOYMihQEpYCCy2SojZgBIhAFU1XD2mAra0S1FQIQMgMpqOrOSxf6aQjQLWHCnKOEduOrlx/9r49UcIPj/2ZzlZmIMHv1lePTMwGcjRTZDNObMHgIYgYIx6BFcBQAAdGyJRJBZw1OagYvEhGRqYiJwjKcxcckZAQ2woirP4hiaqRGYySwaodlnbW+EOOt8vmmO/4fO+R4wM4WKRoZ6l2nXmfUHgGY6/4aGxjOUEVAFDO4ERURRQabIDhFrrTqbieDO3DrfO18ecQYgIMfesTIBgmhNBWZ7KntyjpvoASznNE0TFdve7LNUFYhE3HgIxo6bEEWEDJHYO8/EMUTvnPPUdXHGYbTN6rDvAbFpfNN4M2OmKpVIF13jg4veEeGwT45Ras5TZgRTGMehlhSWKzZgteB51XbbbT8Oh5xHJKMIMgHgHNQlROY7t/+sVJrp7Bw52n3mCg8z1VmAMiOddcc5AkqzRxuBAG1uWLiDyQEACKipVEiQyuynLjrD/RfrlfPegMVku99dXl013rXOOQOUsorN2dmpGQzjobt37+0P3jrsDtE1uaTDfvvVr37FO79wsSauks0KgJgWFSLQNjjTWHwQ53wIqy74AVzjCVGhTPmw29+ONmb06Nt7p08E0gzhFFEzc85NRcZpADYimEr/8cXz68P24vbFpCKZJk2jJlJ7fnMlVQz49YevANN6dTKN5n2ceQS/9U/+u/c/eJ4ytMEhQS1CIHPPgUolB/gSqogw94Ae7dB6JxvN5x7enYpwVKwMZurcfF5+5t1j9kbO3Zx8ZPYR4DFVO5+qiPO5rHhc8c3x6LtA33zk+O5HzyC0eZZpaCZWjy4wZdXALr/74UfhW3h22vzmb/76eIj73bbk/eufe+Pf/Ee/8c1//pff+e4LqLBYtsOUbc4DAJgZMjAdaxJ17oYANMX5JqRHXV3n1eNxljA/pdnPBHevDNyNZ+fnSIAExEeIniGQOxZzHMs/UIBkzqwDK6jh3CpDZiCIxp7YU62lSkWvqCZW1NRYgcHQkMEU0COxM1N0nKUeLsfHrzwZDkORWp00zWKY6qykz3l1Rj7WxdkxJDL/TtWkEux329j6AGBWS+4X5wsAMMlouWtb9DDs5Oys+wdf+vIXvvj017/x9QkOWW9Nds4VQx3LqGSr0w05nFJark/YhSlJLUYUqmGapjFlQFNRIoeGwTer5XLZdiZSc5ZS29AAcvShhIaAJJU0TTmNUmFedzoXQnTrzZJ8AG8vrj7JxXKxauYKjMNetRyNrogiOqWkuz3TJBVNwEDVSinFFJrW+dC2kVfrZtF1Vqb53K8qWrVmrF6KKACE4KtwEzqsouNAhgSSUjr0uxiXDx+t2b1IeWxC6LoGEZyj0DRqdRzHWmW+d5RSTSXl/nA7TH0FBXbOB7YCFIkIa6lpKj2NIVLbBedxteImdj5ijNOyBbNAx25LFUUAwIrEiABSa1VrWu+YOfrgVsuuaZtWJQX2IiXGBtFt9/3N7a4IKunYi/Mzok6LihqUSbQCtugIp1xBzLratv5ktXr46Mlmtfzow+c5FXI4ycExpVSmCUOE1WqNqEzovU+T5jGBYXCtY2emjjB4DtEBWkm1WW0QBaGIFBWtVc1Uq5qh59DEropOqXofm8aBWa1pmgbPvFouvd+zM3JKXIkJANkhmjKLY1yuYs4wZwuJwHvPDp1n58kTdc6baaqV2BxjRhHRkqEUIIRlh45ZqiAKohEBk84QTancdr4AGwAh8IzpYGCPzrRpuuViJSKH3b7kggaiuWYzlXmlAFIXXYtE4zSlaUSVsDpdL1aBXa0AwLXaNJXCkqlqHc2MsXYRECGwOCxttOVyebZpFq3f7UdjDoHPH5w/frxKud/u0WVyTbsUR56ZqZaa03T1YioV8lRqASAIHpkZgQnMe1q0CxfY5qC4aMpiBuYAWwCeWWZ1RiGDVQMxsCplTElVwMQ7nsutvWfnmABV5zuznt1f7/fboe8dWASLCE6VCDeLRRMX43AYhzKNO1BoffP4/r2HD+6t1ksfHCEyB+LAQUvJJ67LngAAIABJREFU4zj2h74f+9uDjlPu+6EUjY1bLlpmmgWsUkQUpEKpcHqyzkVKKSmlectMBN5DjDPs288T0BgDMYimUpJajiE00bdNZ0JaJZdUJREU56Dkuh+TCbz5+n0Tqwmk9EQOzNU0bz8YFZbLZZrGMac0TdM0HcZcMhAAuRiCA4NiVQxAgRQ9ekIuIFpyrbW6RKSh8Wg0oKSxjId09SLXPLUtv/bG0xgw565pPVKdSgZmQUqpVrOUpmGcAxqp76ehr4jADgDAe++Cgc3bdQaBWqVUUTURKBUim1pRM3NKHsEERNGD77jpfNMG8pbLVCQRQnAeFCSBj37RLLGK5xB9NYe5ldAA+Rw8r0+7WvMwjbUaM3sXeRaD1cyMCJipaWKtMld9O0/OM7M3sTpIvz/UWpmha2lz4k6WsYuIJKYFUMFkvTpB7JApREzDNE25jd1m0eZB+q0tfHOyvP/wlaf37z3Ybcdvf+vdH3/7xTs//Ojy8lYKg4ABmzKCR2QkxpmIZAxgggogs4B15/f/dKPChIpoxwJ5tE8J4GCoFSqoionOspGaAYK+hKC8XBQhvBxK20uwAByfxU91O81fLjo/D0MDgpnKcJTJDAGViACQyBSBZjDTvCghuluWfcblhYRMcykBQAY0ZCRgQHAUEdiq3F7WBPB7/8P33n97N9zal77yKC7jr/zCr/7xn/0R6jXoeHL+OI9hmHi7uw0Gno5jZSAAQkYkMJMKqqIGVJGNkYjBgAHMjKTCOBYlalft5nTTLRtyNo49k80CFjmYC7jYk3PI6BkIzS28pbEyOaCaRYA4S96P4+7m+Xb34vVHn7v/9PzRg6988fNf/uFXL37nf/z96w+nNI1NF6i1iADGtR77y00VRAiECJCwINz1UB+PyJx5sk830nj3IprNCB97+doqIYcYzDnnnKqx52SFiqDDWhO26gIWyNThISks4Rd/6Qu//Pf+9r1nHbXj7vLq+fv7d394tb/CqXdSfR6hZAUFtYpeg2fyUKFYndBBs3FxwQnT5sFisWxD44bxcBj2ZhCbrlTc7g5Vs2AuBaqBJ6hJVk33yrM3TtfnTezgwG9/7+MXH/Yfvn9zedHf7orKmi0aedduiGDKt1VHwALUI2eaaQpiKiLiUNy8/Jhb4ZFI1NUpbg9169LhYrx4dzvt7MHjpXPt4yfx7Ew3Z93FJzvN7tvfOlRNVoyZEpaZf0+BnCMpokjOs5RKLqD3hma1oiuCAgSf/5n7p48W9x4v3UL7vD2k64I1tkAMpaScC2Ns4wqMcxLMHGMbumhBfeMw1P5wkCqiNaUp50HV9odcigDolGtcBG7IpABWqYxMjkORfNjXEMC7pm0WlitCJdDoQ2x9yqmUXEtlQuew5JpSX0pyBG1svPeMnLcZuSzXbdP5y8urtAVsQGeHlSkgCBYEEgTDuUocUefaJpemgoCSRU00GgNJEumrC9RwWC4WU86iOg1JpiqTyVTzlCCBZdTBuHEGWKuUmo0hT4XOyEDEJNfsnQMyAEQFPNZvIaNHRwBExABGhkImKGKmKHMZkooRgXOOPVnRMpmaGoBDBkJN2Wb7BcAMNps3HkdmXwW1WTD5G/xNn5WoPuuKepl/+evf8vIxG6Y+a5v6Vxez/t9oXu6lt2k2xupcGIszHAyI7iKQqrN2Z/O1dMzeARAAw1xSxcQ4a14CKqqoNgMQyQCg1mqKiIBMzC7XVEAM5pOpzlT9z27U5zpWYgdAcqeUGYAhknOmCqYgKIhw7LFHAhCbhyQwe7IBFY3sCPACBSQOcBeXVDNTIyIktLkCbX4OoIBHh/DMYiBEY9By9DAjo5HR7NXzoAillKE/EEGIHIIL0YfWA6h6YeTgak6VGVsfowuBgxbIUlRk3sX54OaCs7j0m3UfmtB1zdhPt/vLoc+73SEER0hNG3LOiGCmzmPXRe85uEgIkR0BTNOkEXyAPEGpfU6jwxUZWKne48lqKTsFLUywXnUn58314cAEAMjACHNDMeixE0QRPk1SotlcFnLcdc+oIQNEtbljeNZ+5zMSNE15/hszExKxN7OSMxikIlQBCcwKEXHwMcSmaRUl5amKvPve+2frxeN794MPCMAIq0U3lWyGy80SyLLkqkYD3mw/VhAxBLVaSy7jydlqGWMI5Bw2oQld7CVsq2aaDKhKEUMFI0A3J/CsTGmQ/a1gOD99kCWrCRLNjGHnXc7p0B+aRRxT3w+HbX97eXNxcf2C2taxiZOMMkxDD/J8e312/vCR1bK7fbR+tj49iX6lIi8On/zuH/zZ2boJoVGDuX5ZtDB4R2ggoGKkR6zCcZyHAISqYEaGCja33wADA+Onfsn5Rn88wc0QTOEzsrIJGKohA88IR5yFSTTQuzklIs6QgPkTd/0Us4o1Y+VmnATYUc4EA9CayDkiZ2YlCVJcdot+L9/59o/bxfSLv/i1JlDbrqxuDftf/df+dtM13r77Z3/5Ni7Mq8u51lrmi90FILZaFe/EKft0LXlH+EQEUAPQT03ld1NVg0/XuwRIeKcDAjMi3723Ic4I3vntHgGB9C6SoDCTGxyQO773EAA7JDYQA4YKGVCzjGJiTsngpR/NNZ7Q5ZyN0Aihhdh1FxeXQxrRu1rq3S8yr2Dn5fKRkiu1mhiIQQWIYB7Gcbz39Iy9jlMfI5iWmiuTcqSSB01ptVp+42s//9Wv/a3XXnmU6s2ku92+90GQ8mEYtrtLQF2uFosmDjm74ENozYpKkiql6G532B/2yNQ0MTgfQmxijKGJIWqtmqsBNT4q07JdMCHwfN4YiJpa8MzkAnmRKafDYtE9Cee3u/svLreXl70ZhAbGaQyBm6YJwQHUMk1SrMqImE2JwalYycnMYoAH908co2NzgZrGHW5GM1KjWqVWcRVVCQyIKcYWkmubUylF2xCdZydIidgWC7den52c/KiMwGxtM6NDgQCraC3zqSU51zypCuYs01Tn7TURm6JvgoGKmFYDAQWYqjJJbNoYWiQGhRDD6cmpgS+5SBGox/1PzVNoGmbnTBQ1eN/E4DgyWRs9O5ZqhMDk23aRch2HdBgGF1owhgJ1FlTNxINzwAzeUROCczQNtRTNUxn8HpvKTmLH7SpQAECLtKo2HvZDlWmxxIdPHiwXGzBBgCY0qNy1C2bWajNcvWmD95zSlEphCKVOaShjGkXrHJNHJGaHwLXIOOXxUHxsvG88s3eNaK7FdrsDEZtZrUVVTKHmWouZMbEEdrEhdr4UVYV5c8KOiNDMSikUndQKWgGEUIiNDYSBFZoAZ2drIhz6oZZMCIEhBmgieYfsLLa+gFYDUEWZ34vUDNhR24b1uks5TRMO/VRLUVUTBLDZJ7derLwjNRVCI3RgpBIY4qpB8KVIztoGHx0FhyerRlSshJyhFjg5WXkfVqv25KRj5uWCdv1BEAkxNFrLdco987Ra0QJa4hUQDkN6sRsuLqb9LdQKJYEKIIG46ryyYyYOLjS+QYIqWrNKqZph3j0GhhDgdLMWncyKWlEtVasAZ5FxrCLWRnKOEZEJPaMnIzQ98n8ES2oYODqrVVMqQMA5+O5svQKjt3/8LgCcnWyWJ+1y1Tx+/GS1WavYdrvb7Q+H4dhvWEUO/XR9s90dSp9AFIYeDgOsFjW0errZNABuHKdxmqapVJkqdCvvMqYkpXCdwXiA5NiQi+iU50MDgMYExMeQlnfkXBQxRnKODIRImNGzTQIgaTzAbntAc4zk0DM3bbNyvq2CU8opC9axSlEzMI9oVrMWEACoJfpmuVgml7e3h/7Q54IEjtmjI5tb+CCjKYI559uGIwdygpr2t9vba3344Lxpu7PzEx/wdnt1u937GNDFSpKL9FOfBSIHZAYGYiACIlA1VdVjq5HWIgziMCzaLq+oTH2vNqRszvwCHMO8ACAP1CIFAyfGFRyCKAMSMBIRk6qxOqg0DpnQLZcr77Fp+tPzRbsgAFis/cXVvqopEQJLETVoGu/Jc0Bm8s4xEfm5QxyICQBmlzyYTUNCgibC+eni/F7TdehYahpFEpIh2vXVR5//whsnpyefXF68895bodmcnp2kvRG011f7N7/8tc4tW7d4/t7u23/+g3/y3/+RfgzY+kjtdEhg7ojSBgU0IzVUI4CZYmk2B8OQCBHQ9OilwmNkcJ5CGdncvgUE5ABAFdG0mtVjPGT2bR9NA8dtwbxcwJfLifl2/5nHTLL66e2RzQIWzWTYoxHh6E9QpDs8DJjSHXD3UzcAvBxK2pGIPY/T/byYQxQgBYGZ3+sJiaKZllwgj2990L919S+uL7ZXF5///M88+KVf/up22zO8s9v/UKbpydPT233VvBv7qSjkoZiI84QAWuYBEZgKIIgUJp4tqVhNUMFIq41DMcZSW+dc0ywBcz+gWREdkBGNEdgQVWutAA7ZcXCOAnetGUARg8zkWAGnrLe7jJJb/3wZy6sPTn726688/dyDm+G9d7972V+Vi4stRnCuqZltXvwAiInWSqrMhgZMPxnxnA/9px42O64Mjwu92RZ3rOMpaaaM0TxCVxMBMTJzxA7TYXLIumR0sL7HDxb4+hef/Z1f+7nPf+nJVA4/fve9jz958dG7u4/e29q0yoVFaBgnKwomgBUDUhPBqWkGD35Bmwft+qw1X9uN5wBZxn48TDkFF0qt+4PcbnuF6iKoAiCcdOtlu7i3uPf49GHHq4uPrr7z/be+/cc/ggxQCaQBbcC15Drvo8dGaipZ1MDN5aB3uzBQs2pQilUhI5rPKjYy4vmThwrsDhMePk7p9ua1L/Dq1J095OXGP3qt3TxMoO3NrRy2urvZa5n1VwEHjKZsZRQ0JC/CMsoE4B0yttou8Ox8s9w0b/7cI79A38IkQ5YCjVs4T51XgzEJGCzbzcnqXArc5sO0y8oTKJCBZX3wuc2YeiijWq01iSV0TPJ/8vZmT5Jk15nfWe7i7rHkUmtXb0CDWIhugRuGi2Qa0UTNUDQbm8f5A/UgvchMD3qaJ40RoriAIDkkhyCABtBLdVVXVS6xuvtdzjl6uJHVDZAjM5lJE5UPmbFkZHlEXL/nnO/7fQCi5FEn48gYyQcP0OeiOWsBTaJTkTfe8FKKupnRel+RM6paCXWc83QEQRdDAMYWXxZXMXIXPXsiwNt53/v+wb17vvM31xtAiI7mpFL11GpQMFPAUknR2JQccVNUalVDUzHFCo5NECYYNF6uzyHXvh9W/eL69nZ3mGRSGAESQAFn3IV4vB5bKHMFMQMIICxpTmJapUAEJlLTaS6QAACQ0RSN0QI4YiNDAKUKREgEzk5lXQNgATKRAwakluasZIiETCgAeNeKalp1BG19dgQkMGhJqv8k8/NL7adml/7F5fH/dY/J/n8Dt3/54k7lHWGjQDe5BeIdIw/gJNpEpNdiGjs59JreAYmcY2gSMjWtekJTgFWtiopEeifbOf12KujuzgqnBNw74dTdjARA9ZSCZ3ryDLY9wd0vASLGlrLUXltEAEMlAQQiJqSTqxHxrhEJiA3Lr02dYifWtTWNkWoFMFUxOOWMECARIRMS1NYX8wSMLfIF0VStgSRrzuzBKFIgDkSeToMChybQe3YuOAoEXFOdd0lFaqmq1g1d14fQ+T706IiYvPPOBbRyPIjKTa05xszsvPcpJee8msTOx+iYuYveVMP5Ijifc9ZSapH9bs+E0SMDsoLmgtEtumjn63zEmvKwGM4vl/DpVTs8jI10dZK7ECIiKzRjP6CaEZgAoNrdpqL5TU3s1B0wNYBTBORdmC217iCePLTsHFkLktTXGwJmJqYqUjXnXMRKnSfP9uTBgxhdrvmw2y2XQz8sALBIXp6v5lpqEQq8Pr9XTdBAci0pi+UYaViE3rmA6BBEDFUJjQiKqoE6Hx25ChUhAyozMgGgishY5lRmNWPmXGQueQhUS0nzzBH3m2mz3RRJReYxH7qO5iQFKGndJHDLfn+7n1RHqbtXV99461shhsDh5589+8u/+0fYQVmaD34ek6gCkJneKQ1VtLKCIegpF9iYiAxVAA1OgLEmtCdkQgTCxqK3k96QCA1IX2dB3602JqItdZhaa/b1DUAtSrTpGexLzsPXyZ6v9wtw6pSdYFkIQGCSySEiq1gt0i+WMfY1jeM0zhW+970//9pX3/qN3/j2YuGff/az8/Ub7733ZP49+5tPf354MfOSicgHTwxVk4gBADGioZKYYltA24YFsfX2jMxOWeBfcgO83o4igjW/CiIgMAGytrCaO9G5iFhtiwUCESCTodwtOAbNx+sQzBgNwZEzZHUBOwDAiqwVspiwByCspW2smYKzCkI2xLBaLR8/eZRLGacpz8X7UOYMBKfxrlHbXN81z82QABWYIJxW1XlKXXDk9DhmQvOMyFDV9od0tS0fvHf2X337g//md7/7/ntfW6L7/o//+Hy1NCjHQ9ofdtc3rza7awBdn63Oz1cplVKt71cqUJLkbFMut7eb3WEXQui6B8OwZOdMhYAcEceeFJLNZuq9J0ddDIK1Ui2aa+lTzmpgUJH0eNia1MtHD1fr/tHjCwFN+WjYsYsffbYNsTJ7RCulTpOlDMTiWJhh2a9C6JxjGTJifvDgou+9aUp5UplF9gAeILQROzEFFxioQmH0aRZGmEdLM4beuchAVa0gl2HJb70Fr16A5WKWT4l8BKVhEAHmKU1TzjOooIohEnomcqZWaxnWy3k8as5gAIygBhVqMkR2LpRcKhoiOx9qbV4QIkYmYmYhjH2HDFwwy1yLlFKYPBhILvv5WNKYc46hi77b7m7SLKWACwBAGMEhVjEToABdXDIhqDXKHRmWYnkuI29Mj8fxMpeDcyZKuWTPLh9y1jxnqAq1ShcDEUipwcec1fuASHkeaxGkViKgCWjRnMp4SLvd8TAd1cB58IFDiM5FBRin6XiYU4KU0jzBoo8hOkRMadptt7FDBCMiZjIzrQLGXdf7qCGAGaqqQW3EBVUQcWYqUmtOywAqtUpVEQAJDp3nEE2rxC6uVgtEQ5Q0ZwIYHAwxDkPoOkK2klNlEDMpYlVZkQk4sEMGtJSmaZqneRTNJ1UDIpF3LniijlVyUSmeKC6XjhjJ8jQuFisfyCN3AZ3zVdbjNK2XZ2p2OD+uln6aprfffNsQnOOWCEwQXahjHnMt43ib0pVi7YchuIjsnHMKNI9TmurmBkBAC6gAVDCALCBVvTMIzgpM42ygpSRN2QTMwAXwDNFDiHBxeTbPNKdDSkmhAhmBIYOhGQKRNe67dxwcB0Y0PVFHUdJx18WwWi5RDE07Fz1HJk65plSHDvrFxcNHj9548nCx7JeLpSFud/txmja73YurqyJaiymagOVcBMKw6olcN6R+HGMXFqt17Hs1MTL27IP3MXV5/vzFpq3SiHC3eSJmRsQGBq/VVGG5XHa9Q5RcJpE6TYVpIqjR954dmDJD14U+8qKPi453YTceJkJ/cXY2dOvgFz4uUpL9bnv1arvdj10EYuj70C+GGJbrlRtd2u+PKanF4jsg4lohV1EFh+DI1FDQRLWPIVUxzcgWQgixJ4+qOKbjeIQXzz+//+jy8nLtOrQ9pyrKwo7Isamyh0DsQ/DkwSxwZcdoRihEEHwQMrMqpRZD3y+Wi551cLQ4DOX585t+8M47NKk1pwzssT8PRKhYKxijZwYxVRFQQggmkFIuyaTKMHR974aFi52tLyKziKDrsBQVBFDLtWgV7/1ysQjBASqRMZNjPsF9i9QqKaWU5nnWxhIYFrAcaL3shs45zFKmWiZC6BywgydvXk7zlW3mvg/379/76JNXzz6ZItGDi7fWq0ff+sZvvnh69Wd//IO/+OO/225GXyDcG6SGcihwTBA6IzHV1rAHUEMRMiIytFMAeBNOA0AzvjTipwGSnK7Gk4kPyIzukm3sRAz8YkNwKlHwiyoGfqFmu9t/3m2ITtKpX5Jg0WmW1+5Lp8khNo8e3AVFgRqq0uuRG2JL7gZ3Ou0rADaFtwNjNEVSRDWrCiIGBMAUkZwKATLwQMa65Y9+/MIg395e//7v/P5vv//fBb64ut5/+MknfvHQTLplzVV1NsmFFJxzoFZnUQM9YYLRRDA459h7r1CrZlMD41otZzkep/1hv153w6JzwapM0zwjWktWN4FSiik6lz05MPPgK5SSi0KtkAA7IoeEamwiP/7w5utf7SwkiLu4lt/6l0/eenf1l9/7ycfPAI4APAPDsOisYi3ayOIIp5krMRv+M6qQ13Qy+6LB1QpjgpYODxhjUJOUCqgRonPOBTQH3cJxxMlBnaUWAYDVk/JH/+YPPvj1r5/f77f7q0+effjRpy+vr6frV/nmJkM6bjcVizMDjs55XyGLTLkqOLNgPkK3xv7cL+9FCoGjprw/juOUk/OOmUsp43HOpfoI3gMRLIbQ9XT/4uKdyzdtomcff/LxTz579dEVfAbAQNH72AF78hQi+GgAh1z3IiOxGEgLcDcBaGYxRRTGKniKJQdWBJYW8YSgjjqm/nDYvfy5lDRdPhmQuYL6WPtlWCzXv/c/fP3jn17/5Cc/3DxPMCo4gADVrKq0kmCEAr5pB0uFAgSwhouv+rfeu7c44wLToc7HOhWuvOyZARwiOsfQewaIkvW4L4fbcb/ZkxBUA1UMJV6+rSWZiZQMQVyIkiVbBQZjAw8YAFs5n2l3ux0nNG/YAwAs+oXWlGcJHM5WFrHOxzzvyKF7tFwPw9K7aGr3Lx/GGGrKKaV5Ps7zVEuFZI8fvfEr774X+z667tmnT7HEMk6nXg3SKbANzaiaCTCjmTNnqsMwJEkVayUUqZoUPJwvz9558CQfJzOKi5jmdIzHOSWRJjoHEwEARO/MaxI1A49Ap8KaHQpx14UQQqrZD8yBdUbLVqaiWaAC+1DbLFVFtALhKWm9zcsJWpFDBsZAnhyYVDtJdAia8qmVOXA342++QkU1BOCGGfzlLpWINEzTL3wAv9Cp/j9dWsPol1RX/wXshI7auUBP2WSnJxZFBGsGvTuaF7T6sOkHEJBQEbxjZgLEKpJKggKkQEjEhICiJqrNCuQoALXSGxQkDJ2BEiEAiFCZwUSQkE4hZNaCEwCg4R4aictMQSVnB9Amxs0miAZQobTOPDVdeVsbEenUXmktANR68kKKNZOWiqrUk01ORBAM8OSUBGowLmJmciwExkYewZlZC6+sOdeGiudIyDDNyUAVPYWeHAOhkhaAjpwUqzVJkZpqzWZymgzllI97iH3PwMZ6e7srRUSgVDGD4yGXAjkbQfFhHsd5teoBAqPVWnLOJac0jxfry0Xf9f0yejeOI5GaCrIOPkQCKVNNslgNuAqHCkR4cb66f3kJ8JFUYAL0dyU+NOoVELfBqbY2pakpiqm2VQYJRfRk7TIDg3Ym4xONyIDV4CTMNtNa82uKmYG2lwUMalUWmee8H49zOmYVQ3h87wwRvHMh+LSTF69e+ugfdkFUfviPn7rgHjy+79kPfT+Evmjpo2MK2FBtPjpPcxoPu2Oaptuj7RLNGGmYFmfzo7cu0ZYc/FzmaqNIQTLXOd+FxbLbHzZF5hiNmdVKyilED00kmMqzV0+v91cQMPSd66KL3fVmkxUPOStCIrs6bsei6miXRgAGxuvN9V98/8//1//93/sLMNOSc06FCSiwVVOpYAhNgdHO0yeC2EnyZNUMgBwTgICotn0aoiMEQBFQUDYiAkRkQFCrrzWMrWnber7KcPcpfq0dNVBRREQ9bfPavIgctTH+6U4mjTJgdvrNRgAKvqeq2SogenQhhA4hzPNBhO6tz/+P//D3r16+6GP4ynsX9x6sx8P+Yn3+jfff+Xf/5r//8Mef/dX3fxSCi31gh/NcShEA9L5FMXCjATcDazMSM4ApqSogWkNGtMvrbxpaqnWvGnjJI7m2kKhaNTUDaFxsADAPwMAESAjuZK8AA3RADIQIFAgICRAtRr9YdEUnImZGKxA6B0rVshmaajXNJTt064vzx288vrw4+w/f+x4hAgKxc0sqh7ktFgACgHKyY98hyRyRcxRILStXmQ0JVfRw3McITAvn3THnGMtvf+eNP/rDf/3rH7xPVv/6H/+8zNurV5994xvvzfPh5dX1NOdc05jK4bC5PWyyvpFzPc6580Prm4+Hsjscb/e7/TSuVquLe/eWq361XEnNaZ7nufSBuhgDOQTYz6N3jgJWKAw4s/Oec4E0zSnn8wVJFeLBIBcB5HpxOcT+HeJ+zsLMMUbnnEo9HqGmYgCA1EUXY7hYny+XS2a2Wg+HTXDkHZhBrbXWxK61F8mJdx66zsfoxjSKpHkur17tloPbXMnmdnN5trq88C4kV6dx4JRXv/adb/3oh58+/+yY8wxChEHViCjGWKsepmm/B1AAaesVIqCINK2vNmfDXZgRMAEpe+8oAPDxOJYyq+puP1axksREPfkYQgjAznnvXWD2iBlUZBrHktETEVSTjFYYoes7A9tsN2nOtUKtiqSXqzNTnHDKc4oUhtA75mmcxnFkR6QIalLK4ailjpvdq5ub3eEwqfI4z2+88Yid85a9RwRTQVU0VQBSxeuXL6d9IqDpeADTvusIwdGi88GWZ7vtcRzT4TBPCZCACKRaORnWUAUByDmbR02z5GmKkZFVSspF5xkIwXv1HojBKoBp9ETmHIGZVayMCmAISkAODYFErOZ6HHeMrGBmAqRd6ELXEVHJFRAAhQiHIQ69eYLec+fZESqaWHn18gqiN0QTQDGHLnjqOIBRzekoVVWXfVz1vRlYRTUDQwJ2jGW3kVxEqvMc2AfnikrNc2IHZt7HwME7R+yCo/WqA6T1ol/2fk7zxdkaCEtJx+MxpaMnvnfZL4Vubq/nNBYBQxAlM5CSakkGjCbLgR89kJuX5gI6MnHtvHgnIzcsc615RmxZe4MzQ64hwrBwixX6kGIIpTQSogJC6AI6R2JGUouFQEPnCGEIXfSewVQAvdPzAAAgAElEQVRKzVqriNgw9J5DF0LvO0/OoSd005TmcQem3/2t3+kWq8ViIZJqmZ893Wz2+6ub7c1muz8efLc8HNJhVgFwDoChSq3piMQ++LOLS/aca73dbs0AUJgoDiEO3mx1e70JfvA+NMeuiOVcDscjmIpIrUZEMXCMfd/37AQnO+wPx6PktJ2OsOhdFyKxem8AfeBu1feR/MX64vZ665xbDOvzs3tE/nDU7ebq2dPrV1eHaYLFEgBgGMqF0GrFTCGwBZdNainlsNkZYOzIOy5ZNBtCMUOmGgnOzuI4ZRFgLGYmggbcxRA89910fbUFktiHfuWlCjk/pQwZiSl2AzHmVAlMoQhX33Hf9WY2zwchC8EhUS2p5mIC85gZmdgvVwvv9N69e0TOe/IeRMrhuDnmVAAMTK2yQ8NaJJeSVQAN05TnCWoF56Yu9hJaeavIhpzFAJ1brh0HqKkNaYlDP/R9Fwd2WOtcTxfrh4EZicFEpvlwOEitBKrg4ckbD71Xg2piiNU5iQMuBne2XoRI64sui89Vnn/+7MOfjXOCZTc9efyd73zz1zF3/8v/9L/97Q/+5ulHAgrRQDLsp5lK4bC4ePL27avPAdVQBSsZgrEiG6Ew3jWYPDK2oTQSQNMBtnkCTgSieMJUAoKRKSlSs2AYADTapMlp0/mfr3rwrgn2BeQF/9lyy9qoD8HaoBzolM/e2lKvy0RQMGMTkKa0Og3TW6C5ta4bIZhUQvBI6ryQK2oiak2bWXGWCpIBLKCLhNHINrty+/2nf/N/PV32//N3/sWvfuP9X1us7v3Hf/zbv/7R3xab/SPfd8PuxmrOMJtJQ71AFTUDh4REFSshMKG2uUHJFNtsF6XCfrd//iyJXp5dLnznNc9L14vWIqKqtWpKWgswz73vTMHY1Vqn+chOFAVwYA6MhLYQnRTKze74tz/6azYxSW8+fvtf/uq3/vW/+r2/+osf/uTHT//8Tz+6fg75MEsFxMhEAA4NmBDIBMsvWEbb4b9zDgIAISko0kmaT18YCK3rY0pZmzEKEclcpOrLbj/DBh59c/nO1x79zn/7a7/+L765unDdUD/fffyXf/9nz1/9lGj1D/+wz6M/bur1Nbg66whAlX2IkWLnUq1zASONA7sF+IF9hxhrxglBCWLSlGtipj4ObCxVyNliCcvV0C1C37k3H7/x7htvL/365YdXP/g///onf3kNR4gd3Ht8mWcQLbVOtd5aNuYhrBZzOaY6utBwnCAFwBwUgoqYiYWweWfNzKo1O0E1pIwuO0DLejKuKt9+srm9uR3n6d7jYXWBccHGm7hePvyVy3c++IOSytNPPvn5j35eZnSEaSxYGAQQwEVcPOwfvfv4g+98fX0W5vFme7xOctjbTtAS5QnraFUEsIqv2PWuC72QO2zz88+fXV3t9QBg2McIxcpczME//PDTy0tHwMi6WPZnZ8vd9kjFwIQ8rO6vfO+NVaqCEFhUS8H5fvDG4+X6POWNs9x7GIYoA9bJax5S0jLVeXP4/Ob59fUuXQMogDs1+5qjYuhp4ZabV7vlSi6He29evHt7vZ0gFVEwIKBaFPQ1e8TUVFEEEQA6CnnKruMQY0qiorCERR+9uXIsNze3y9XaBbfqBxmLkLpIDKSjSZFFXDD5LIlByBFgLVq98906Cojz5KNDhHE/1iIAHLt+0Z91Qz+cDZMdizZUawYFMmRiRBATQ3DesaBmqQrE5DwLEZDUIkUU+bRwYdPruNO4XKCCYlP/ICEZoP7yx+1L6+PJpIaIyPg6dhABW77qP10q/6nY6r9A9woAnCoSohKiAp3GCqamTdR7J6AFYASAhkEmopO1kJkICUDVpAjM0AJAsGHDodnR2pkUgYG5KUEA1NC1WpxO5qXILX6kDetAFRGRGE41aCPhKKiCQJ5ngKaYIyRyREqGzCeZ1smIdML9GDab6Z35E4gaPKuVyHiyDAKfHgmI2JA8aIAtDZbUERARkjGQA2MlQAAxIyI0EUXzwFBMBUYrwsVFFxjBEYfQafUcSq4ppZIUBTwxIAq2PoVWIU1p6rKSHDZlCCZcGWlw3TjPWKAYZII5gpRo0RtYLgVGNZMqOc8S3Exki2XvuUtpTOWoprjP7s23mA3BVFGVYowyWN+HzvfvfOUxKHgGVWdgClVbzgAgMxmhM1ZAVVE0QzWTJsJuMMrGorQGv25vbkM0aoe4qtppDHZ6WQzaewcEjaqCw5NN07BUSaWORQDACHwXEEFMDaFCnXM6jIf1PB2m6Scf/nxxvhhWy/VqPXR9F0KWZNyxZ65Yig7rc1Pbbo8vXj7f3GwOk+1mPVbr1nB5P7z75M3oQ+ZxxikIqOsyuQrovGAoRfZohubMDFDmuu3AjMQ5nOp0nNNUlFwwt+iW9419ytv9lFIGYpim8XC8Sbkgw/r8HMAB0tXu6qefPP34k81qgUlNy0m50VxLAqJVmo/99NWQOt5AqXUR2+pzmvhpc/QpVgRo3XZwwO3gA4ABISr8wmQRWu8WFIDsJKE8WQGBmlAVWjvaTmplA0I2apS5tqmgL2qvO+scky85Exi5FlkpVrNISjWrrmSCp89uvvcnfy/2rW+//9UQYHO73x3Hd969fPzG5V/95Y+ySw5Nzbu4BJlZ1VUFAAQQAgBAx6ZNpAQApu2PB0JDaNkRr3HzDMbtR1EiZAYwddaWLFUwJSMUkZZe2twDhEQESGREBrU9NTvm4E7U9Ua3J2CPPpIJARhQRTSvKNU4QC0GBlUToBpT7MPl5eXbT97K+3+/WqyFq9TCjk8KrJPMjQyxUWsNm8IRVQVEzRkU4AFVK7GxA+dpmjao0EX61a9/87e/+1u/9u1vEpWPP/pwf7h2DiDA59fP5zy/3G0VXdd5xwPpTMEPZ+fHV6+OpRRLzgEhX4/b7f6wPxznkpRxn6bB1n3fddRXqVcvXh4Y14uhj9E7V7YpUO+YzGjOVStoASmSU0m56KIuFv3Zqncm026bD3tUWsZIzpnUD97/mmMvKofjdreHYUVSlcAP/cDsHXHwEDyBsSjvdjfjCDFgkVlqIeecC0RehEDMeQZgKZAnTVg1U8ZpHnWa7OgOZxdrRkQXib1Iffzm49vb42Zz3G2EyLoWH45Ui+Y55wRQWv1BBtxQXAYGhOypjLMVAT11uDByH+NysQihl6JpqsfjpKrTnItImQEECklNmp2EgOwcexdCx9GrFpFkUtTErJoWRgiDjx0Tw263Ea0MUEtlpgCdIioJOWQkqFrF8pzzXBy3gQ5IlRhwiIPn4H0kKkzu8nwgdMFHNojBewd5Zs9O6gEBayq7HaR5S4Y5GzOwFzVqiiRy/c3mpgoBemJDNEQidABUixKxdwxd9EVRqRTQUqeSEA1AxIANjMkYTUFMtZpUUEmqYKYhOGaKwVcmBPAheO/bmRVUpVZybTOkjiB46wMyuwRaSs158j4ER46jZ43eM6OZlFpKknGqLJWcQyMTBBYk8KImYAoueHIcFwGJUFEEahWtBgaOaTvNiISFK4jmWkSJgIhLLczsnYdaq4iqTvOENYUQEcmBLELY3FzH4Esth91unqfFcnG+Xlz0K9JJy3HOpSqgZKuohlUSoEPE1ZmLXXj5cu+83dH3AA3UYFZFzEgQCboIXed8MO/MBxcCxEixb4rUCWw2KAaZHcbOo3OSivdEIN6Tc+wIg3edd47IhAtyRaqYF53TWsjIM0bvrSCaksEydn7Zvf34YdcPPvj9QW539ebm9sXV9e3usJ/SXAHlkCoYAjGy86qMpLHz3nfr1VnX9yIyH8dxHEVrYIKA7JkYCSwM4Jwi1ao1pzqPpVZtX9KqIzQFG+e9YY6dq8VanWYK17cwTzWG6hhCAFHWjJCREJbDYrVaxRiJuEIpKd9sD7f7m1SPLsDCAymIQJpgdJWhsmcTDK4jLCmnlGd02A8dWiiTTiC1ZmNlEkZwwbkaABSVpEAtFTHH4GIfAtLNZj6Mh5vb274GJQ1xSGWfcopdt1gsqgoy57nkLDnn6KLX1kEBFcmiAYE4dDFq1pxLVlFxtUBV6LuhyIjoQ+gCUYCQWVQFiRCdqpnWWqAUQCQESrlOU1MlA7EzIFGdpyqW0uyYLXY89P7yvHv6fGawLtCij33sI3e1ShlpnqXqFBwwWuyciJiaVKkFGJQIfIDlYnCkOd1KBWW9d3bONK+Xfuj9sIgc+XhzePnq8OKzdLiFR/f6b371199+8vVnH22un2//9E9/oPsASRhAKzJ61wfsXJnr7ctPIURsWwoDMUDTk4wEGRoJpu35TfW1CwTNQJFUTRrus8mb7nY2hieqQeOnY/MJNn35F9hQAwBrosDX/748yfuSbuvumtM3hg3UjicDYBN1gb4WX6Gpnibe7fEnyUO7TRqRAbHdWVsNwyfGKalBsywRn/IXUAGoMHPNhRSC75BhGue///5P01SGrn/w9qPvfue3fvbJT47HG9MYfFwtONhqe30YbwUKEDstFYgBER2BADtTy1JUG+o+Gwg76j2Z1HzcpWk9rtaOgpqVoVvNaUIyVShllAyqgEoYPKgD3yGImpJpJHC0BGA1JQ9ai1+ChSIeQ+hUbQ/7n774T76slk+6b5+/fZDxk5/ePP247j4HK0kRnO8JgwiYSjvOXxz9Jjk52TlOhqDTK6vYDJwA3KQouZAos2NwUnOZSoYAvgO/hot78Ad/8P6Trz5452sX2l1/+Py5ebneXr243lzvy3rZffrRMy+xjAoHUAPm4IJTVZE05Rm8IYLroTtjtw5x8MYqHmctVir3YCwckNXF4KCQ8yUMpWOOnV2e9evF8s37j+btdH19/eKj2+3NBAwQgHx3vd1ABWAMfQh+4QI6T7lOKeeqFNmhIpSKmVAZKpi01MEWg9k28A5UFdQMsZCvwIDFVHLyDQAdujmPm2f7s+Vq+eAxm11vrz66/nG37O/du7cYhou3Vvff/e5qWJPS4XY7j1NNE4EtVz0OcPH47OKSihz30+2R9+b1MM7MQb2vWeZaU6qewfUdgiNwIAFztSPQDnUyF1wIvWiZU7YMsHf+wXnfeedgsYr3H66IbbFCBB98x50rJeU8B2KP/v75+dlZBm8ummHsHGB1zqjnfuF6BZgnePUyH3bz4TCmsRz3OW3AOxeiDxRyLSnlCtV5JImf//hmfvl3bnBP3n7z8cVbZa/P5xuuZAY6Kylr1VNbXAEbMgUqIBznsZSEHFz0hE4lL+Mg1babw+bq8HK7O67yg0cPsLoyaeeCiLjgBaoelByciDts0Gl1CgDZso+ePaeURNU8rB8uqBJWp8lkLhkNqxlVqCpJIQMYKBkTMYKCEAITE2It0iaxzcJxqv9MWlre625Si15TMDDUJlxt7RFtRJYvVrsvwCut99V6w03H+kVo2Jfryi8WTGuPf61LvWt+/Wd6WP9fNrac1harCExo2Ewt6ohEhMywIc8NtZ4kbK110UQ4npyKmqhUsWpYmssMQKyKaiNreGo5ssqF1JqqgVhrLkCtdr/rCnILnUICRHaALQoM2vOp3bnQW+8Qm6LSgKyle0m9O4EgAWhVNVQ0bEkXdgeX94B2OgUZoBE3FSpa88o1wRa07qUZohEqoSEIGTADqbKeAFsgKq10YRApswBBXHoO5BwaOED23rsQYQFLHHKYt3A4lllUCZu6WEFEBJyjmmo5iF+4HuM6rsHEeV6E/ribwQAzTSZMtlyvy6QFJVtOXvrezfMUgy9Sxkm6wRctc5nVCpGrOs9pg0LBswikpKs+LhYMLqHLH3zn67CDcN/XQqWIcRtLIQIRMqM3RaUG5C+NYdkODJi07gm2DDwDlNObVZulGBW4iVwNiYjZeQSEVGuTOEqF6H3LviNypkDM67gmj4ZSSmWPh3RclqAE3XLItVxd3dxuNz/96JOvvPcWh+D76DufU9qNYrVCkXl/PIz7X/vq72y3u23dfXx789nTzw15knqYszvSq637xle+dRYp4ahOsxD2q2mP+5JT3pR9urd84KnTbClPRfN+fEmLhIzc0/MXL445V/S3N4fZjML6dj8V7Y5zrhVFrJYZDVKexfTRG2/uIaH4n338/B9+9KGypWQZajFw0SEQGJFDFbViUAwcgbTGoJ3wc6yAyI4bnQJac8nQzExMzRiRsQWHienpBE/a7nWS5wO0YYyWklvzmRAZsOodnMEhniARAGDUmlYC5AhbLKIBnW5lgLsPqwIAaFYQcM4xYkrTKFmH6Jwhdy9urkOP+wP91Y9/1vuzUuNv/Mb76MvyTM8vcDks/tUfffuzZ1dPP7vaHfPFxRsDL1xOsr8mABe5AOWSiaIRFtDXy13bpZKyFjRSJDUwYMAA5AAYT6Q8h6YmDiCgVquizJ7IQSbwitxkUOCYfeDG0gcEBCNG550Prn38jVSlKKCyqbPFss8pMZN3EWRRs9QCeaypZDC8d/6QicnhfBwdeahgtTJRlWwiLd3k5Glo+ZaERGCMyGyAamKGznM5yPKrIae5X/LZetFFjpQC9++985Xf/I0P3nv3K+Px5tXVy1cvn+2P21TGVI6b5IxgX1O1EqFoKcWg7wY3DG4YRDQxFtIi5ePN8+NuNgFyfD3t3OfPChjHuF4uMPhjmvab2/Pl8vHDe6vFYui7YViwp7HO+8ORISAEE+q7YTEsFv2wWi1iINVqKQfAwzQWnQA9oQskXedSFT3OArPvgCpC1a6DrnM5pZRGtAigzsnLl8+Y6cH9tfeMyL5fIZGK5TKLqleqlaRSGsGgPrg8Q6T5uDseYaraLaN32i+cj/001/v3/ZO3H5eMn3x8PR1nYnOOmF2axuNxLgkIHWMAdAhkVg0E2diDd25/ffCAzEzEhBy6GIcQQ/DkyyzjftrvDi4EIoYMWgUqZIA6Z9XceVJBUVisusXZgj1KmS1P8zzWmoN3xPjo0eP1+eA83ty+QMp9h0UEzebDZEpqwkZabJRR1XKeG6R2WPSOswE49s71u9tp2pfjrjiv9+4vb6+3ZiLa0J784un+3a/cN+UpHVRsiGAKVcwHdM7FbgCkVESUgB1QcN7FzpBZGiW/ACkAqPfEhOjZM/chmLnxmMbjLKoAKFLnBLEDR9hE6E2NbwrzlBzXrruIvpOWEAzonHPOMXHwajGkeYPY8jHQI3lvjioRdAEBIM0zmDLG6Nk5QseGJgoZapF5tegAwQBVQRmRnIqNhySzTIeyGPQUDc6+zQnAgIC72MUY+4v7RCq1zPOYpmMp1RHH0DniPnbReRUlALTCMtdReneOxJHIu7C9ufYwoJ6IA2SKtVKVded1tbze7DJIa84Rc4zBCBXR9wEsfvsbZ84FRRDVahXQmKjjDkFQK1oKCMERdJVi6TofHDgyJkX0tWwJU3CK6A1OPnet4ojZE4GBCAKTGQIGDsxBWcT3YJVcErPowDNYrWDsOKwXYbj34N69e10X2dGcxjLuNzevnn766avbSRnCsO5Cl6RgTWmeTLHrBoeDEFgwci50cb+fShZVMIhMAZ2Ru4tQthyWAFhUak6aTZXImNCw94OZ5jyqmVjtQ+9jo9Y454KpAKL31QCqIABB5cOeIFVOU9/7bdmena3XZ0s1PRz31zfbq+utkbt8uF4kTbOUA9RsprXONKOG0CTy2IcQgpvrVE2AZrLB+6BDxlrYAJEBoCqIcalA4ghD751xqVitVJESBl+tTGk0V7tFN/R9Tvk4zohluXIpSy54nOs8ZhXQWIHmPsTFcsmEaa6FITg3uF5RjERZk+Ysh2qiaZGrRIvgF4g8SxHQuU7O+RBjPpZaZZ4sZ/ABPQciCqGy4xADsFOELDIfRsAEVIdFdOTQ8MHD7riZPQfvO0JCk3RMeZJxV3Iq2XKNsFyAEpmJ467rYp7SooPQsfOkdbaAPrqu772rbzx5Yxqvu2ClTGkGT3G/n29epHyAN9cX333/d99989tXz/Y/+v5nn3z02e1LcFjQAaXISGAopRSZHXJcD6W2PsVrrwcqNpDCiUXdiAot1eSkU2x0AFSB13M+u6uUGhug8UJATU0NgRvd6uTda3kzAncekpNv4zTCPo3l7mJN78q7k67KDNSQT6Xh69Ls1FOBBjY5SdrpDkCOX+qSqVREOkVJNS08FGBS5gIEGQx8Q7C0QsBRwc4IEcm8uelYNUnswjDI3/3Hjz9/dtXR8MF//d7XPnj7f/z9P/zB3//gP/34hyltV8vLe2dnHbvrMiYyct20GZHZTNE7q8V5ymXKokRIjJKhThgW0bXOXUnzMe93+9BrteSwk+pCCOgsz7XyzIiMgSkcD2V7rVJtHGt0sF77vKTjbvZdXV/2XZFcj7yUCafb3S0T1+jWMRbYLhZ4fn/93nx/uBcvHufbz8vuurx4tS+pgLIyB/QlF4I7v+jdq6etRwl2F5aNYCinTG1H5BWxCS5Kqb5jDqBgwwD3nnRv/8q9r/zKGw/fWr33/qOwpGSvPr2+ffriWWUoQpO4o5zlDYwH6FMqM2AFzeC8d9yBE7EMnPszF7HEZezu9zR49L5qUbbqwciSZqkF0JjBVKSKYVqcSYgOdX7y8Kyjfv/i9vb5ePP58fNPr1PCxXo1c53Euge91AoA6J0PXqtNoiqo1hNYTWgKJs4JUDEVa60qMJOWen/Sb7gmNnSGrpKpgYmqek8mSoaRHM108+nW1fDGO48/+OZv/8nP/xh6m3BfyqRql6v74cJ7Cn5NWgZnZeh4sXSj7Jf33OF4tZ0OL45X28Noxsd0DKGCUTqmec6e/dAtl4ulCRw283w9TfuCM3n1NWdJMpekImS+G4YkmfE8OFI7bPe3wGaozscurNary6vNTZ51PE6VGFT7pTu/6MAXsYmZb59fRcfLYd3pKm3t5sV2/wr2V/Wwmw+HWWq1CjADefTkY+gZvRlScVRocbZ68eGLq3ikJW+v0nd/9zfPhsNb63q725Rc8lg4uiaLIQVU4LY3dwgEtdR+6IzQzNhzgOX98/upyOfPr3bbo46wr/PZIAjOBM4vz29eXIOpH+gwJ1eSSa6+Qq/izYKBh9GNwflutZx0LCURsnEN3g9d0GLH7TgdduO4G8JQc8HaIlCR2TkiMhCrJm1FREQUM7O7jCswRGO+a+6/vtxJpwwMfqEMaUspvY6dP12HZIBy8gGhQiPBQZOeNu3V6fntSwsmAJx0LK/Xx6ZN+Scqry8Fw/7y33gn+/piIf3n7vZLlxNVEc3AqHGOCckxtfQolRaWhSrNTahIhJ6ZnPdecpGTMrVKlQYYA4RmLnv9v0NCQ1PRChXJNb/Fft414Nbd36l3fsB2QjllCyJTazgRISgQOyCopQCcZipICgBGTaYCxCTU7FAVCAEbHhcMrU1NRAX0Dld2knBRO5XeHafTZAUQTrc2UTNBEUETMyMPjsw5h57bsUZGgDZtAeec8847D0atFe6cG9xi4VZW/Xy4EhATkqImKFmAuB4rAOy3h8v+cn22EpExHwaLamIKVsGK5pxSjGt2yCpZRC2XDGREDhByrirSjSc4Z2h0ZsLDcY9dBxgMXVUrWn2M4EypPnn7IfSgiMw4zhUACJmYCJ1zwTmXawYkYiaGitVI4fVbH6ChCthOud2IRMh4khmitGzPu4FUGxkwYSNeCUvXd4hYUjYEAyNHLjoOKIZShbquVpnmiYgWZysynHNG5LOz9fPPn045n19cgGmZ06TyfP90f3VbU2LCrx+/c3OzeXV9fb3bbccRvctmYx01G+Li5z/99M0HD+aHEwG64IxoyvN+Pkxiu931/bN7UrNUmKYx6bybtl0Ki+XaGG72m81hR11/s9nt0mzeT9UMKIYuZbndlfP1el7ceM9EDpENeJ7L9c3+2edPDZtOEZwjrQCg1HIQmvDJwalJC3hn0rs7YO1djqc1pqkaQU1MgNgxAhJoPUkFzeyLqOTTJxHgRJJSNVIEbrZbachU1ZZFqE341a4DBD0tWYB0kmy3d7lZA2aZAdRSQQWCOSZlN0vKCdgjADBwqlKkEtOf/N1ff3b7M+fpyRv3Hz5+qHXOqfzhv/29P/vTv5nLnJ7vmEVErRalBuNSYEZyOWck1xzFqAoNfK+Gbmg7UWzKKbYGikZmYAMkcqSiBqpiter/TdmbNduSZ/dBa/gPmblzD2e4Q41d1d3Vg1oDBll22OFwwIPxE3wIvhEvfABeiSB4AkOYAAIcSGFZki21utXqru4a7nimPeTwH9ZaPOQ+t0oSYNhx4z6cs+OcPLkzV671W78BBESrMZppXDdgJiWDFfYcmlBNS0lARgQheOfdYpoXggPGedJpngQUOPS7lZE6djFEBGfVJOvICUcoVa6fXjgOr168/tUvf4kCMEIJldyjoTwBIRCzCWg1UTEFYOecAyZgNHTVslYBhLZxF9vV5qLpRjNIF33/ox989tu/9ZMnl9fD4fjLX/5iv39QqadxmMp0HA88EzJPuVSwMLvA1MTYdh2Qy1VKqVDUDIY0v755mybYrfqmaarI/f5QBZj8e8+faRFEzqXc3L6pZe6a9rPv/aCJraENhymnMtVUSyWkrmtD9MEHJFStOVcTccxoNp2OczFDPo2HZtUKyGE4zDXTMiBUN4ymplLqOA77g3RNaybjbD5o0brYVjZtm3NJaT4NE6h575xzy5PNO7dqIxEeIrtQkCF47ldtt/LeYU4pp3R5scNPfUny1ZdvVMTxon8+7+O94xg6NQRDcr5oNi3ojTxu16s0pVQqOwhN065aYMil8ExAMM1lTOBqjm1kZmJRXRZfiGhqfDoNY5mnFCts17sVGUqtJZcq4h2u+tX77z+/vLqsUuZ5EgHnnaGkXMdxNiXVpS8xZgIAXVJpABAhNoHZBU+16MN0PB6HcS6UwczubsalFodxYg8pTduNa1cwz6nv10+ePZ+nGckF77z3TdMgYq6qgI0PXbuWAM5HmoZpPE7TJCqOIUaPRqa2yEyuQ1MAACAASURBVJMcMxEHz9o6EVMVACHv2cHiU4eIxLYs/UKAGCOzQ0RmRiRVVa1mgMSe2chp5XPZc9F7FxqPSKIGjrx3jW8B0LEXSVkFkSlwiD7EaAjH00kMctZSq4gSGYGZltlSKQ+OXpvCpr9sYgsGqASA0UfbILFH800M3UXjHZY8H/d3JtU7RwDBOTJjpiZEoth6MvBd16pCsoqEu/U2hKCgzNQET4yllGLV+3B1de2a9jCcxpTIR/YOfQCiCiYiKvjk/QjglxjFogiIzuFmxdtuFcnl4VTnTKB+1VIUzxQ8BodkgiCH4wEZWueXPMrpOFUF9nG96ghwGoaSErAT9MjgGx+dd0jehSbw/u4rZCH0WAAN+tVm3a5j0+y2F9tuXbBO03j7sH+4vZ3nKQZebzrwIfSda5uH4RDENy0HXq1XW9J4KvPd6bDf39/Uu2nMzNG5IEURzEdoGg6RmFUsbS82tZRZs4EhEXti50If+34Dhg8P+5yy8y6EUIvOY1E171vvQFW61Yn57MioqGIlFdsfNBcK0a36lfcxxHAa0jgMOZXddr3eXKRcjof5xeFheaQ6Ju8Y1aqIQgEiRTU1H0LXdQ5iGms+JiRoArZ917Xdi69v50nLrJ6kCeycE8Jc5umQq+jFNfVd07Wh77vYBYOKoKiguZZpmMa6f0giYgrTCJJrdMG1sYlNcC5N0zgOh/kUqTjkGF2IPgRank93+5MqGCh5B8BTmqsoI6tISSWluVZJVecJRAS7hY6KROzY55qwODFRqWpgKAAZ1FRABD/59GkteDrm4TBKyXkahlPRMYMpeEgEteTQeGaiQG3jdWObVd9E5Fg5DhXzbrN6+t724mITYpzndBwOCHp///LHv/UHedxjHb7z3kcfv/fDTffs5uvD//4v/+R/+R/+OHQYOZQxB4xN3+WpTMcBCGPThBARTcb5cc+/NCiEYIb8rllZRhh6VI490vYfTa/eDRRLvVmcW5dIZqSzC8D5TQaAgOcQcyR6Nw6pKiHau+ziJXzwkeBzbnLw8SecLR3+9gu/oR88DlWPHIUz5LJ4hy6NCj6+n4DAdFE34eKfj4xspiLn3TERMC9WnoyJc0606CEyfPnl8C/+xb98efjiNy8+/U//8/+EIqVcf/bLnyJUQnny3s7H5u2L47AvEAB0mbcAwEzFFk6aGCJudtsi1URKVmrBuTgNM/rcKzpPL97e7XYdkzPQJjYqmrN4x2isKl98fasCZYZVgJwAIJfabS/cak2b1fpwSGJWi2QBBzwmYZ294jS9Du5E0d775OLiGvPghr29+mK8eXm4uznMqQTX3r3OYO4MBxrqMpYuEgQzWT5cNQ7mGlBbJEBmgipaoQDV7oIvrjerPjx/78nTj9onH/mPv/v86fsXkzy8vPnN16+/eHn/dix5s7vgsHGhJeI3L+5IoGaoBZAQAxrUaqlp2HkyR36lHMPuyTrs2op6nNKcEwfnKIbG5XSYx4QVfOeDd+NcQXXTrdfrzbbbXm4u6mC/+PxXv/7Fq4cbsBn6dr3errsV57mEjnJJVpfQTFJVVPTeU2CplqeiIg6Izi4VVasAGJEjJHa8fK5q5+0rkfPelVK0Vql1cRSZjsmvici/+eruzZd3oPjJjz754P33Zz6dxuPN/ZtpHj5/8dcMvoub6+3l9cXu2cXGnLy5u002nNTvH45J5W5/eHV3qgJXF22tIiXPKRlo3693613jm/3d6fXL2xefzzQAyZKHwcRBhUophGCMVqVqrUBzmsZ5TnOZR3MI03RAam9vb1VlOJ5IQBP0l7TexTa2c1IpqWvXUGHe2/j2tL89ffnXd8dbgLKUEPAEBOg95Vw1T8UJGIGgI8/Ekq0LXdasg3z1+VdPnz+5vLyySg/HvRYFNi2CiiaIoEwOBaRWQ3bsgJRbjw7TPGfJzz9+b71bp1pevHhRrbgAtYIptKvV+08/uNheOPN1TlaV1g6M98eDI+caXyBjhLBrlFXRypJDY5bmyZJQtOILnnm1aGbTOKohIbngiXBZq6IoCEiFahXIIROdZ29VO0fVE1H5O5jRuZY9Grq/q2d6tlx+9zIgXIAUAFyi+pCUmBZE5Cwi0XPNW8K+HmEseEx3+xaJ0r4pj98+pL8FVP2d0vr/NbtwebnzZuKxzhrgo4+XmUHNi54aFtdFOxsYIrPzzteU4exOpWaP0kImERE5p7oSEjAA4hL+9c3BnV1qYTH5/tt/HogZqBoTISEZqdmiQDvbJ+mSFWYmaGCgQITIiIDeSAkEllxMQOOFTEwEoLhYMzzKOO2dhdY3X0QAU1ueqma2PPAUAcAxV1DFhWTE4Ii9UzDNKkvqC1hNxcx8UamiqiICYEx+dmW9Ws9jnceiQA55CUkTBB98SSfXxiKgRVbXXdW5yCxGFUQqAJ+fy0iGS344oSNfUlJR5xjB5rl4tmmaQWWeJ0cUgo/BK7ESVTMtBWlmjpVcTvce5Oqy6z6AesxYCN6tp4AQ0NREVaoAAi5dE5Doo+Ly3Uf47XvifPkaAIipa70sJgFmVaooBh+atkEgQpzrtJzwUkspZXGldY0DtnnO3/30+bpfs/MpVYfmFABh3a3a1eoH3v30538xptM4Te2qZe/n0/zm9u7u7ZtAvNtsfv7TnxfRh/vDOE6+abBtjsejOs+Abbd5+/b2suudEIEhivcgJrlkBYNaYwxJasp5nMdk85zmqSQnJWvNWotJIAOmVFKVWo2Kitg5PXO73R27LSKqApAvqnOq86T3e2i6ZqoF1Ihc1bI8kUEXa88zP/DsT/U3buVvag0+4tH2iOwCogMiPAcJPl66Z7zpfBnDY2doIGJIhuwWNYIslsKPsjYA0HeMUgYTOa8Uv9VBLo4y7w7msZM0AGDHIFhKUUCgpRAvbE0jw69f7H/6s5/3ffPs+fV4nN7evP7tn/y9w3487McXd4eb+zeQwDXo1ixqOSlKJe8peBVzAGjAQOd21gSJjZSYiUwQySExVytuCaJwZ1PtnIuCkWP0ZEomBlgRkR0xRwBGjyKSJKdanAdiz46dYzMVLYuvvKiWCqIFoB4OoFpiaMCcSslTmU91OEyIkOf8m8+/RKCHh8MqdvcPt7BZEt/8cDqlocA55VEQER0ikMkSKoIgSkTMoAWqCAS43K27Bhtv4aLtV9sffP8719fX7OnFqxc3b26GcVTD++NxzNNc0v40u8wcnIEhEBE3TXt1dXGx23nv3968ZXIhtEX0eDqlCRgxxNi1nZrlXMdxfPX6dfChC6HfbAEsT8dpnm9v33760fdGnQx1nqZxHN483ORaFj4mEjk2qZqkpDkvvoHOsWfOdS61InpQQbQm+BB9iB7MpUlLqqfjVGsZTnOt6l2zWjXbixlBFvGcWu2wYTLnLDgTBdMKpk10o0cDqTV557yzzXoRL1cTNMF5yIf9nUO+un4endut+0M/jKcMWkWMDNqmNZEqTGSO/eLyxoxqKFZP8/Th9fPx5HieHIemjVXqPExqlmtmx7mc8SQRXaogIyAzAwPDuu+r1rlMd3enYZ4vpk0bAepQcrIliwTZed807TCM4zgrhBiCWi0lBe9FQXXxnAdmBEAR1QIywdxM3apruyZ6B6CItW0FkdQAUFcbFLH57JoDqjKnmQIsqZI9kPOekFfdysfonRdVU3XOtd36sL83MICigiJcC5ihC20TWkSb85yLiEgp2bF37MyAGZ1zRHb95GmtqdTJrCKhc+xInQPn2Dmfc15YV0QoIiKVHSiQikmaRZLWJUGwet+COUDw7FXBcVj3LaIztXk8EWnbdG0XneflsX93e/C+aTwzasolJcm1lpKWirhb96Fp1uvtquvNII9pnud5zgBDrUrRM9m685tV73f0ZLebptM8jqBqIrWc8YU2Nsn5KsbMi4C5lmKqqsLerVZdbIOKVJuVwMeWnDP2GGJTSjUtBkUk51RUxQTMH4+TiE0lpTwrgXcYgkPr++a67bfrtoMcEWxKYykJzRGRI2YiAnKKRaRorSJQa0RiVnZ+3a6YCKvMciI1LdUiNK5pY0OGjOgMr9trsrMRSHDtdnu1Xm27btW6VYV8c3s7TKfDw+F4PCDBhx+8f218SvWQ5mE4gpa2DVdX/abbRd/t76fD23J/c/ewzyowT4BUTNh7ZW/soG25WYUYmVAJIgIykuOqtRarBMZM0zQjcNutmqZXhWlI0zAPw4mIuq5ZdTEE362WMM5SREQ1SV0yNgygSp6mMk5SiiDEGHfBGwKZVgfQRm+WzwJxCiEQI2BxuRQpkuucAVaeu9h5do6tKGvK7KBbucvr/vNfvyKG0EB05iiXlJMWJc0VDICZmuBWTVw1gciy1M6brsAENI/jodQCAAAKRNC3Yddf7TbbJkQAqBPmOQ3H6fZ4IITdrus3K2ZECKHhvmIpBYhr1UWCvwiopzyLaJVqgCGwFkEEqXXpk81M9GwXy3zmKRGCWh2G6lxAxKdPn7598zCdTm9ez6TI7AjQmJcW/skVrNer0IIRkneIiOida8Hlpsd+p2ppd7Fe7cJmu324Pc2Tu72b+g4YNzK3l93HH/7kP/zk4x9uuqf/x//6p3/xp5//8R/9u81uw+Tvbx7AHMWgpqIZPDYxNk0EwDkldu+ihdEWzcPj1GGgYPitBmNBrXQBsb7pZx5bGgPk834Nl/00PPbw8Njbv3u7e+z58V0HBd8oXPCd/fC3B5BHSO3/QfDyt3kOS3ty1oigLe5aj+z1889iYjj789I5GscAUaXWahVMaVmiIwpIHg8xtMZhngZCcw0EhtNQf/YXn//q1V/+/j/5g/effud3f3uqVl+8ejUdT33Xbrbt/v50fxzBgZUluKZSYC2g1dh5AuAQLi4u3t6+qWXykZnM1EoGK4TqpcjhKE2bfGAiWtpM75mAibhf91374LjJAUBnIqg1jyOQc+SC896M02QpiRm4liXjcZ51Tm1s+75ZbVZ1wpTyxbPNsw/WH3yMb18+/Oynv/zTv3gFX45QQawAAzgAxy5GUKvz9A0gyQAMcsYeRc92TQAO4AZgB93z+umPLj/8+PkPPvvkvY8vKx3vj29e3n41pruhHE5pZGfX2x1SKFLYRQK7vdnrBJoB4AySCmekbD7EFQtXajH2vll7brGUmsowzlOELohnITBajG1yzrPOnnyl0NHFR08+XsXuq8+/LJMN+2ndrGE1vz2WUxmhD31/sV6vH4Y7RVAEFQWtdQkWdA4NCIxwEbguV6vYGRRdpm1wjk0WyiHAMrASiaGRAJ0dVlHAeS6DlnlyK4pd+PrLr/+b//q//Y//i3+0z3oo++k0C4ACjHNJ815KnaeT2fWq5f3926In2sPhNF5cXa77RqwC0W53leY8DnMtgkje+1LkdLsf9nMalQGEF2CYkFwTWyA00JrTOB7oigyTkVdUFXWhbcyNR5FaqtTj/R1FBoAQoRCs+tivNggm82jmnn/0ycsvX/7m168f3uQ8imRwBBjJO2bgWosUQwDPzgRTKsssi4YmmvZjWDUIRVUhwa9+8bl9z8pcrEKdKxo5chWEAIgcA1eroiYgYuAcIwER5TEDwvqqN1fHcbi9e4gbZocVLdf8yfUn3Ucrh7wK7Xg4SRbbwBd/+QIQaq2QK0SAFlbrnjyexlOec00l+hgoGhcyrlNOU8lDqUWsgoo5F5z3C7X5bAIu5ySIJesAF0KemIjUrCjIj0rbv1GYFsYJPpr14dnC2JbpDezblSx0HgDO3ryGakrAjAsl5swBRELTM14Gy+B4lsnZ+fd9G+F5Vy7fHdTjIuH/Fqj6/4tewQJgMROd8/qMEQ2kqgDSQv1ZjMbPB7Qk4REjgJyVA4AGTOzYMTM7RsJSSq21LmF2j3tax345+FKKiUEFEzMCRUVUOKca8fnvNwVdTEoQkdEhyNnBhxEvL59qNakqRaXKksgqVparFtEU3ZI0d85ZAyJARWPmEB1UI8GqBgCqRmRqprC4+NoC64ICEoCYsYkzMFHSVdejQjVUVFlOjGotpQ4CDjaX6xA9Ih6PpzlPPLlaqxYAAdB8wvn62kqqdRJwjMwqomoABIKwEOlFxOrmcpWy+dU2Rl8fjryCOgE0GJumWUcBMasueJMlsHnRaJipMldVHcdxnmv03DSFkRIQlTLkJCXFGEpR5+ZAhSSJ+b//977zy7969fZNch6IHCpLtVqLWYVChAiKKAhoRmfPaSUgWAJZFlR2Mb1eWiuVx2VJmQAQgAGZPAfyyMxUSUkrWE2SIaup48CMVUVAAUBFoQI9ut7NIGyqpaRpfjiM681me7n76DufkHPdenN5/aSUvD/c3Z8O98PgEMaSNm+fb7e7ebJXN7fd9iKEeD+9qaIX640h398dypMqtc7lSAaANTYBBihSvMdiZU7jcRwOw6FAHeapm8dksh9HcJRB9/d3FXV3faXId6dxvru7vz+mDACQs5Si81RTUuw4J3j18vaXv/j65jX0F+OpArGjxs7tp74LHVw6JiNc7u0zT3O54RTACB8VzmcIXMDQgBaLc0IA/hbgDQiMALZs9OzR65IXDAuYdcmoZiYzIKZzN2ePwT7Ii13D8gMUTLXiIjTU8xaUEA1VREEgTbNqRUJVATMxIEfsFpdAWLIrhxH+1b/588+//Pl/8JPf+b3f/fE//Pv/6I//7F9/8ulH3/vud3/vd3/+b//s5//6j//dlEm9ByP02YoJADlCMBXzhgy4DHUAYaYlX9RwkXcve7rF5dARO+e8q6px5YmNyatCSVVEkSIbIVqtKlW0WAEQqptN27bNUmKJoFatpeQyIqGKOQQEKNmmcfIxxmbVNatxmE7H/XBMeVIGUIVXr9+CwQfPPnj27BkbPL2+PB0HJFMTYIiearGS1crCsUMizxRg2ceqMoCLSgzbS3h2tXo4vChFfvzjz/7JP/2Hp3GY5+k3X9w+PByGw5Cz5FLuHu7nlKY03R9mDsAePEPfRkcoEkwsTfNwOPbNOjRt0zYP+1Oa78ygaaNj1qqI5EOzv9//8vZXL7/++vuffvcnP/7x5fbi4fatlNx99OlvvvgixtBfbJque/78edFyGIbD8HDKWWuO10+i7wCMoBYtIuK932w2LoVxnruuIUdFqwd2np0PSJEA7u/enIZ58TNsAxQpPm7e235Q0lBKnssYPJnWVRM2fWtXkHKWosv6oO+CqDYBdhebJ1e7InA8DTGGeTrs03Ec59ub/OLLX33n44ePP/zuJ9/5cLfZ/ewvf3X79lirH09zydXMoRGShEhiVkybxjnvaqVprFnHp+9f7nbf77p+mOaf/fQXp/sTBBhzCsGJyLK9WR4RDlkJQAnAOXQ3NwcfSMEkQTlVxKF92l9c7Eqe5jS0bbPbXnTdejjNX778+nCA2KmLzjvyvoL5WqUUUT0Hty3NAXowhn7d9QvxxPs8zseH/cMhIcP11cWTJ9encRjG4/5wfNyZaa316fMPr68v7x8eHh5eDNM0T+Vh/+uUwBQMwREshbxvnk5TytNQSiXHbQhEUCsztd475qYVrSmVWHwM3vnFIAoMqmCtc0pjLhMzrjf91dVu07fR8TiMwzDkPBMYewJADux92zSeiHNJQ5UffPrDkpOaheDbrg0hFNX94TjPGcH1/QaBx3G6eP5R0wQAKGUehuFw3J+G02ZzjezBSFg9SeQCCOwwzckMLrdbVTRFqS6QcyF4bLUqEYE6Uj8dy9vyUGe5vlpvt7t1txrCXkqWMtfigg+77daxz87PUy6mhuDJEdqXX/xqtVqvN5v1pl+3DSIKdkKaaz4eh3EalahtekWYUxqnwzBOVQSJmeHZZc+OwG3FJNVcRRCNEO7vvrh5mVqmXX+xWfWr2BJtiNA7CMxERmjSrUqpc8kVlaOPMUJg8NzElom3sa8pS5F107Wh9RxkrGOatZoz++7FVWAOPsZ2terXIXbIjpiy5tc3b//ypz8bx9OYppmyNY6DRxc3m9VF89S1YT/cj2k8Hk9v375i8HVGKbIK68GOKQNVIwdAVoqNE1QFQKFm6lpghuPxa+dc28TYhKZxZmOVMsyHNNeU1NGqiX0I7aq/iuFC4WYYDochGeLGtf1mbVqqEJe5VgUEMkCDrDCdLH3x+uXL0ziOaOwcx7hCCWko7GC9an70w09Ox2keRgREqGDIDvqmD01UsP3peDwOv757EVu4vOq+8+l7YjaMY6l1HA4ffLRSQRAAYROsRUMJ6GLTONWkkOZxqn2AyiIVbd52frfaljSP2WrGJ5ediuVUPrjeXl8/k6wvvnytgsNpeP1mgANAAogAEUoe54RNGzfbbru5TPPLOek0jLkOuYAqdF10ge8OoxrUGdhZCLDerQAgzVXUiNmHEIJXtbbx5KRyEanM4Ng1TdhtrpwLm359d7sHNPIQkIILWkm4VJGi9v0fftcHEUxFEwXuoUmdG48KmPotfe8Hl8UigvMtDqV++XJvVd6+mZ4/6z779NO7l/hs/VuOu3/7f37xh3/43/2b/+nr5a8Lnebp6KDp1uvheJp1QIami+y5QpVai1UmegSpwBBAddGd2NLwI4GJLa4FZ7a36aIOwW+1RAgGwMv6BwgWq1VDBIblenk3TJ23aeec5XeUrnfQEbybl87BXd/MRd9EcWn9m56i8I59dd7u2btV4IL4LBysbwQwtrh0IQIgIUaHBqSmVRTBqiEQMPCirVFQM0WtpkgumBkYk2MCVk3zoJ//+Qwj/Je7/+qf/2f/7Hd+7yff/d6nf/ZXf/Knf/zn01iC4YefXHznu+//0R/+jJyhgefQxSaNswqjOWNg9kSmRcYyXvYrqXnOpV2Bdy1jk/Ow25ZaM0DXNN00TsG3m822Ztvvh5yKKnTrdrPhm1c5FQVSU61VStJa+LhPpUBKwAxaYYK5pomkEh1jODy5fO5d22x5nm/HdNdvdp+9v/vhf/QP/vmUJMPpjvb388sXb158dXPz5pAeDIDwoidGAzGoAMbOMFRl8ARN69fr9XrdE9s//sd/YFiayAbpONx/dfjTF3+FSROxkJO//vWvBGF7yZvtut9tT6daxDyyJ5xPBgahdd6zqhYpTc+rPnSbptv4gq7duKaPsfWTJikjcY1NaJuGyOVUrCgYm8r+rtzlh+t1c33x/neuvt+V7uvPv/rv/8efOoUg4BG0QsM0JxmOJxVsVq2h4jckCUNCLXI6HSALKIIxqtWSWZmR2YEDNlFREylKqI+xZgBASFm0SkYACEDIBiImbLz0/zLrMM+DzJABZgsUIniopCYFQRQqyO1pP+Z9WCHFi7DuqGqRKeeiZk2MvaoB3r65mecpF4gcurYhMKikM7/96nD/KgPAer3u2y0ojWM6Ho4qFcC4i9iq35Zi+8MJxnmuSYPDxrddv1JhDg5G0CrQQGzdeqvvPb9uYzuOk4Pucnvxr/7nP54e8ukGYAAwYE+IWFTAabFSCpCCY8fEInoeq5VMzUTpRL4FzEiewi4+vH34ir7+8MMPPnz+3uf73+Qp0woDsAGiYFVFdLEJC+si9E3VYqxwCd22u3x+8TDevjm8hjU0vfchXlBom+7rF18zuoc3t7e3D3A4Qzo/+P5nLvjixCKsn/S0olM63Tzc5iI6Z6gYkT252HSOaDhM+5sJZlgoTnEVHHsfHDKJilrVrDYLKHhHDr0qaKm6hEdWswomBmjvhMx/q14tzuv6OEgaAUdAYNRvoj0FjSLbuaqCmZESmpGhkoIBVVo8bB7r34L0n5kMZ27Lwj195671dw6HHuui2bs6vRTgpUL+e/hZf/fllvvnEUEzWEJp7VHUbe+WDYhLWrBziFhKySnXksHAdFkqkOMlUVWXXYQjBIQFJbazgdJCaVIRJceL6A/o/EQxMzknUJ7JHmYgKmRI7MFAqpiqKaUxm4AW0WJSFw/kqiBYxAjBAXoEdyaVKRrIIwVrOfmEDA6W8DGQM39sccU6n93zThvZDGTxKFcURMRFM0egoCIGKABnwGsaZq3mo/e8zJBZF4jbzvZB8zSrGBBBySkLqJIPzFjSDChq5Wy640xKjQ0jKTjpd25iS0Wc59C4VCfT4iKVmh7lrYaITeN4ASZEwUBVU0o55e7iSoABLKtpzsc0hayFKTCc8n592V2/v05ZH/Zl0ZkriC0ic4BlCQN6VgkCnsluiki6mN2ZATAtWO7jfwpgQJ7g/FwHUdECIgqweJKBnkEcExVER0iPaSwIBPM47UWta9dtw84pqAuN817B5lTatqfAQDinlHLan4ZTmioDO1egEAKIllnuT1DduNtufddKzhTccZp2zfq962cX67UjG6fTkE5t3/SlH6YHQ0h5zDYbFfJIhoKSVFNJD+Mpg1Wzu9NxFgUXq8JpGMYhiUATw9rnaUxm4FyIsY1NXxK8fvvw5u2N72FBY2yhDCEZKxjAmdKBgHj2dDvDMecWy7658d7d82ALFRAfV36Pu8RFEvuuBJiZmhrYYulmdnZD17NYEBCZCAjI0M6Xvz3S3XUJMDhzQ1UAFxHvQgGEd7csmTciXrpC77zakpKoYrjgYgAQQgBXCbSW5jTOX718KZp+57d/6+3Lm3E6fvjh1fXl7+ey//NffPF2L5AAPFH0Vm2RF8MC/y8GeETIDvRMzldUg+U75JtAfokbXQikCGAqWkuqImnOYBZjc3lxmXM+HkuuBRmiX4iHGhqHYKUUduTcoisyACillpxLqaZwf9QdiCkBUC12PE7lCEBQE4CCjy742DatdyFN09XV0zc3P5vnpALrVeuZCkuGKrAoygnRqZioOIdiSZJ2PcR2ybqYP/no+affe3b9dF3T4XTc3z8cHu72c6qqIADFtCInsUmgAhiwVHAITbPq+3V0AQGlyDCMiEQAhM6zX6IdQ4zOeeaF2YaqWorOqLcP+/3h9MF7z54+eXJ8uL9582p/OsQS/apZxRB9RKDow7a/EJXYxlXXmwwwqQAAIABJREFUN20jVcEMwWpJhJUZovdm1jW+qOa8aDhBLCvgNMI41pzPUbQxBOd80zSrPp6wZs1k3PVdGgfQJlggXOjyy+IErVlIOtwEZnJzkskMJaMKEzbMjYdS4P7NHVX39Mn7bbv+6L0nHuOLr+7HQzmMAFwQi5mIZSFgh4DeEIwqOCWvhnmYHk7DKeVSJUMAZDLTIufnQ63KS/fEqCIqAGqVFAsYIXsHAUSKCJYiiKFpmzmNIcT1emOKqZThOHUNcWhL1ZyLFjlzhRc1PIHjM17dNMAOtps+xFByPdwfx2Eex+QI2zaG4FXVrBJCv4rrzYoZiVURUlZiL4oCkEXnLMw+NpAmKUUFAAxUwKPMUxlPdcrgULKfnOe+Z6nknYveGdtUQVWWXEGpWU2Z2RF88OGT4+F4Oh2qJEI1lZTS6ZDmYZzTQMTsUVWZKYTQ911svKriXE2btzc3S0KLD67Wuup7RPLs/aphF0Noa1HvbZ5KTuocGyBC20Qi7B1zTmUYp2GYSykATI6JMaUsUmtCFfHkLraoTRNccERCCmaaLbRtSuPwMNcpScooNXicx6mmWWtGNCPUmmvRnHJebjZg55wHXK927apbdV3frppV9I7FdCoZKlAZNRk6YEdt0zhzsy/ZSp7ynFOtoOtD262aVYMImubjMJhiGxm1eoLGeUdikkwcogeFPOdJhMCYYdWvSym+VF00mCGCI2Dw7L2L5BAakFIbHx1wngSr63gTom/JzbdDu1l1zbZvt32/8dxkkEM6naaxKnTrDTgXbTNZLgQCoZIz8yJsRXMyFST0ji36VehWWw0XO312NQLQ8TSN83wahrv9TUWACkDgHDBDCDAOFLwyqvdGDphVtLAL1MVa083tENx0ubuWAiKPTyUTqbJwG9XETGCJG1s26YAmaKJVGhM+HdxwGqP3T5620QcCVVBj8IGbhrRiLVVUmV3jgw9RDXMtVpDUo5KpSpWcixpJXZJt0IDNLM1lmibLGmMTYt+uNp455dM05SqShmSr6PwCAQCCBOe843nOWjMDdtFt1g1qLSl3TZtGgcpOoDJAC8CAADnD4ZCqQNf13rWipAKLTbsKOEfeBeJl787ZV+e4aQIzL/HQSOAcEpOBqqooLCoEVagVVDGGpmmi983heDSzZsVXEiX7eUzjWGA+J3Op5jnNRcdimdU1TePbbtd49k2/s6YPUOrpWMbTXR7Gr768K6l6R4Ad2OrDJz+6fTl+8Ztf/+LnX3z5i1vfg992UFkysjpDTsfZAUFoBLKC5lzBjIk4OK313EYsUx4t7hHwOMjIY28j3+KeL20HyiPA9IgfoRqYyDvTl7OV7TcalrOvAi56wHN/tQBMeia8n8WD77qsdwvFb74Aupgk/3te9ti4nX/juwnMltB2xMWKZFGdGCx+7qaqZ6a7IjyG4CqYSLdpa04lqw8xhCbnIimzBorJXeiLXx7+6H/7k4vtxWc/+ujjDz68eXP768+/Oh4O7JvNZrPbQR5BEmjJ2DTjnKyauSUORfZ391VmAGBEM2yYV010EFFC17jeN1M6nI1lkBFAKzCH3S5IhZI1pTyc5hh1sw677cp5kDIfDmPOOScSWTLdnFQuuU5DJSDvYM5zaEbCmZCjDwpyLGMe7gjQVJB9jRov+f0VPf34fZHvoDW1UkopOGdUaxnEEpFW0MXq1HsXY4hNYLab6dcuwOwIMI92qDSRBTHKU6qSZwUiWPXbZtXFuJ7nqQ3oXeNwAgWYIccqXGUBEL1wX9tL4FhSnUPfxx6yjsUSO+lWsYEYw6qqjcP09s3Yetg0brNtnPHVevfs4qOo6xe/ePPzv/wCHgAMjFGRmqaNLatMuZQgxawRUwWzczZrBVVQAJVF4bMMBrYwvECXq/SsljBQEbWztTYYmFUxUANkJGKDxfgNcxIg8I1TA01iCNDbV7/4avUsbprN0+10SPczZWkJiNGw6zpjehhPgTV69uwVIKUcGw7ss6iKMTWNM0cOgWs1UgUhqwQAjJBStnrwoTE2H6hWE6tSCzzAe7+7K3CqooToo3OuRQyI3jlHjNABCHTBuaAhoJmkebRqHoMlfvsyx+K4qAKSMs0eqDpvoIaKrLakh9W5SlUVBSVY1qQKFFmyWoZaa+wjKMzTpKpd2zEyCKCCi2E4zlYMVMl7YAICARvTWCEDwPqqu3x6cX96e3+6P0labVlAuiYw+GlKkKFreDzOThgYKkgI/OXLr3bXF9wxOZ5LmPfz/fE+l0RErmnzkCRLWuIf2NVZIJ+fpCDgyRERGFoV0SqlSjEr4tARExiZmiigmL1Dix5HwnfF9F1dOleyxbbqkYq1KEy+gTsQQEGsGhgQ4tmdEAnPgyoAAJ0tCR+VgoRnahXqgrzjo4abljiyb3ix35CxHivv41uXwfPx+3g+mL8h9Pp/fTkVhW+yxnThPi252oiIvJR0MgVC9uwdOxFZWHCLaQss1jqGCzmwShUVeFximC3xf8uKApEMiAjYOaeP4nAAXXAu1QqPLLOFBGyiShVdICAxUVEBfXh7t/jKg8JCY0FUxAUgAXQAkSggODayc5oFIAAjQq2VF9k8EerjnP3u5J03JfYN8ERgZqAIRCXXatVAANUMqopWQDP2pKLplCXXnb+82F7Mc7pPD7kmXLTaaGpaanLsY+tLLqxoQE0TyOHpfuaI7LRiQc/srZxGF6KCEevV04uypa9evmbPLrr5dBqn0wrisrEHsJQToIsBkQiR2DnvCxPWWuZJnl0hOo9GmtOYU5V94Nh6udg2YcUJxqcf7mpxbw+vFsqbgQGzZ0/kcIEJ0B4V+s5AQBUWgivbYisucE7He7wSzRDIFnj3rG4j43N4iwLq2XkRDLMkQCBmqSK1LgSE+7vjwY7zdmVXF10MVpURT6f5OMzzy9eu8burCyJ6OB7maTyMp7FMRkTRI2jTNGrmI/c9DHOi4UTBk9o057c3p89+ePX8+ulFv6l1en3z1evDK+zAh1COKpoOw15yNUaOVIVzrad5LIh3x+NhHA7TeJym/TBVoCw6jiVXCT7E2AbXzlM2Q8feuUYV7273f/35b3795VeRoGZAz+xCFVm4Q0oKBLjoXgG/oXcuFz5++44HPYPiqKaK508CCQ0Xw/xFJX8GsJabjpbM528s2OFdwuB5V0jIzGdyvp2FzUi0yHxl2X7TItZddPbLP0RAQkLCUrJrHDtW+Bb+tch4CQ3OBDEicoSp0ou3x7Z9XSW/ff3qk08+AtbNRRtcAKN/8Pu/897zT/7s57/51S+/zrV6tlwqADjvjFGLFFQFNMfsbCGFGiwhRgqqAMSOAKBKtYWMCVpKVrLderPu+9qWlDMRhTaQR4EKvPAErai2AMyQcznsT4yMgM5x08aubS1YjYWIY2ze7G836/Wuvwy+mbmaABRo2yZeNHnKRNiETqrd3tyJyGff//6rN2+O93st4nyYT5PpcoKX87cYzaqhdn1bqkxjVoSPPrx+78PdP/2nv7/Z8PYiHoeb11//elTKJS1mHHMpKcmc5DTOxzFlkQLA7AyNPfer1Wa9tnN+KxHyIvRTUWaOPjgCFTXDtmnVYJiyc/76ydOuaWqVn/3s52VOn3330+3uwtS++M3noWkce0Ji4uij9yGV5LxvumbV9ABWJTG5EJum2jCJSXVM63XfxGbOqSLqon5Wkyp5Vkduu24IMc2zGYXQsPcpl2Ecp3lGVCQ0k3k8TSdEBOd9ExrvScU8k4sheO/IxuE4zbmkqWs3cd3H6GvOjHA6TaBw2D849NfXuNutHbdWXZpKDBnID1MZc15HWK9XXR+VNNURsfoGPvvBJ1Dh9nb/5u3XKSuya9exViuqxIzgFBkXh2EANkLjs00iOfTexIyQvUeHVuFwGFaNXT/tN5vtkydPrq6ua9XhNM5T7fudb1bDnAFqDP14nL0zkcW+h2OMAKCqoqWU5D15RypQazmN4zRB12K/atq2UTVQc+zaNl5d7UTKzd3dWObVpvONn1NqutVxnEPjXQhqCJBSnebZHFMMjeMQvJWoUlPOdpoATHSeIw+whs22Dw2biGoiVFBVSWZAzjhQSbNpIVIH4NjAxBQJkB031HnvmCHn2QcfiZEkF5mmaRyHnEodk3fsPccYCLjtVszE6FbrDRjf3x/vbh/GqcxTMcDgQ4whhOC9Z3Jd04NOk1mepv1xSCkZBe+DqkrRqbEY3NPrDWJQIfaeEYllsbwtc5GiUuqYK0r1kLs21DrleSDQGBwpWKlFrKRaUjFYlJgdEv3khz8mz8TEvGzD1ES90Mav/Mb1oRdQdp6807DaNOtpkw7H08P+cBrGvid0arUUrSh55T0Ct7FZdyE6hFJJq9VSIROQ95yrpDwTYow+hLZWyCXnXAkZ1HEAH33r2ja0DA4cYAAHHgRWrQscPAcEwFJ9t326e9ptemOcZ5xcnWr+4uXrr15+nVXGeZhTUjMBykZTKklK1ilDrVA1nIihVrNCnsZA8H8x9ia9smxZmtBqdmNm3p3utq+NyIxMFJEdSWVBqRBSDZgwgUkhIUCIAUMYIPEPmPBH+AFIhUSRBRIlEEJUZpJZFZnvRcZ7L153+3OON9btvddaDLb5uS+iJAq/g3Pk97i5u9m2tdf61vd9i1CKOiiuiS2tm82aHl3pJ89/IqpjGucyF0tFk1qeh3dsYEXRrA1h3W3FTIpMk0jhkqlkG8bjqT/WTM836FwTG48ORBJgNTNlJiVGRkQgEcgFtBAo9Sc6HemQ83A4XN3k3UVoWp6n4frRBbuuaVxJBQAaDs4HNUzFMDswx5zHeRAY+5NM860iFimiBJAVldHNCY9HGXto4rhac8qcppTyuO4sNo2jwMht8MHDNJ2mYSKUrms/fATAZdWtr68fNbG7vz3MUy+ZclYVqRk88aLrn2dLKacsTdtejml/309TSsnAwBHEwDEGIGyCCyFMDtDIs6s7e1PnGjCJ6JTm8ZhEQ2gQLJsBMyACAk1zEoGXL+5MMXjnd60kmkNc+WS5+EiuAedqb5wIiCLEVoD6GGO7cuTl3W1/PPbH/Xz/7n7q8Xib+x7+5A9+8uzJ00BXx3f21//PN//8z//6xcs3p4MQkQKwY0ekKuDqtqzmTEzEjIiJq9BvYdnjObdXQMKa7NhDzo9Wa087w0i1Y4bLjCZEsNo/w1rJIxCesSbAiiA9uNlaHVmIZ+jrAeuqRb4hgi05KjzUTXZuBNZ/+L5KqS8+Nw5/7VFRqAVcW1AzOJtq2GLzirV5YAAAomC1dUGmhiBIWIsNACCG6vAdvDfBPIsZh3YHJKZGxb77epz7zz/94Lc21yGum9//vd8PvvlMPr+93d/u84cfX757fRzu4ViK88xgSkGh6q3s/u4+rFwMLCUh6mbTNSGMp6yFnn14Tc3ReStF+tOgAv0p3b4ZVl13cXFByN65/f2hlPLhs93jx6uLi23K0929jMMhJUzJiIAIHDgwrwIpAxqKghR2fhYp3sOq88TYRS86ppRUNHjCEFzjNq5ztEEIKG1KNgzatpFYcilFDdGMooGrtY9VNFrz3XRHRXlWw6yWQrAQtiX579/uj6ehXVdVVIPQSHF5BgTnKa7a9c116z9oiR0HYw/gZHVBYQ3c5KzzlBPE5FZx6qeivRkTBVc9fOd0Ok55AsrQbVaffPC89S0L2YS//Pk3X/3tNy9/9To6gIzoQYyUyPsYWEwJDHKaJx0NrErArAoiFQHQuWCimtTEEBHJTFUEKjOvLjxRwbruHS6aLYRqF5arYAIMEX3woipZyTEymyok++avvv8QHz/+6OrJ5SPq8WQjN74oqNpq081S9m8O0eGqs+DK6QQAw/YCnQtWNLrA0YnAPJTTcWB2K3SW2TkMa4CCUuZe5gay8y6uEAo65Da2IdDTp7s390PfF0AWwXLKUzkCOh9C1/mb51dpGnebZr1GwLlIP/TioJ0O+c3bfZwJElJmKo40ePQKOddqsUYDBa1mgAaOAsBSkyCjoyBzoeCgpLmfWRkJJBcfm83lylTKkE3NOybvkEi0iBZFMwfmlZyLDV0/u9xcrj/74rNkcHWz8o3rDwfv/HCY79/uYbLd9mK8nULwhFSyFBVzcn9/x4mdhAkma+tNL9FHVExlTHMCRYXs2nUXOt46MibEcZzICMTUioAVFSnFCoIiEpJSZYkQkAEgKjGpVa8kJMRFGPfroemskl7ArmoHsXi6LzIWAACBsgBMC53KTE2KQR3WQ8uMMYBqB4XnyhIR34NVZxqQArwf9PqAqlViaw3Hi7XWuV1QiQkPljj/PxEsR1DtRk2JiPVcPC9HZeZiYgDMLrgQnFO1knLJWaVAhjpUpHaESimKKipiUnMPRFQUAjSqg4BrCYeVB0JnztdycipiSvUMVdtjIGTHnoCKZEmqWRGhjOd558ur+UwVAqgcB1RFwgeAqt7lRsCUp2TM7JiqMF4X9goRVUqC6XKWF7qdVcmoAcASU9gBKdRpKQKmgEgheCPz3q1it1tfkB1vy50Vc8EjYoFMEVQTRVo1TSkuz1lEMGREwGi+BZG828SLR5s5j+RwnAY18cE1Xdhstv0wpyxTmgRMEeY5xRhC6EpJaRIwc86hac45em6aBkyrEZmLTTGYx3TqBwI5pn672jjfKAp6UE6b9WpzE2IDliwlbXxDhWeRy4vLw+mIlaiG9n5hGNqZIrg4w4nagngCLIgilLI4gRMQAy2YYZ2KZ+rIEZCq8DIRDBYXM0Mx7U8pehyndDyOktWzQyv9cJqmKZV5fbHlJnSnkw8+pURMLsS5TEbYdRtA8N6vNvHq4uL05r5oCU0AxHm/7zzc3+1NxTuahsPh+Pbl6xc3H96YYRE9DUM/9WQoakAkIoowzOlY8rvDfpayPw1z0bloFs2qOZspAWBJVqY0nMZpHJBcEZhAT8P8i1/86ouXrz0ikK8tlBqBABgNF0Ln2eQBgB6oVlXqbmc2UdUfi+qiOF3G6FjJBYqor/AwwLn1t6xcogqVV6SmpnxqhmCEi/GbqYCaqZoqAFgdCkoP0POSqiE+MFNrVFuSTSlSsckKt9WR2MtLGJiYmMaSlJSJAOHV/bukx7Ypf/nzjx5dXX345CmRjn3/49969smPPr26vl47/utffLFu/PeH5EIJwYtYZmN2BphMDLPOYqgLUgYEQIKVz6fznC6ut2oynEYoAAyecb2KyRM76NrWIM/TIJK8JxEposFDDN7UxtNUkvSztIGxFU+bi81lKeV4PKEBg3t69QQIWre6vrhZh/Xp3fBW3jlmFUHC2keSUkop7HgYxqdPnmKB23Q7jtOUkmcffOTg5zmXuQAJB244GBVV3d3A7/3uT/7oT3780SfXu52PTZmG+zQd392+ajaPnfehsSQGWU7TeOr7wzAd+jEVePTo8jgcmhCcYwRw7IBNRXJKhNatV3POTGhgm/WaCUxVpeSSQwiAul6vm6Y10STy7u5uGsfT8fjbP/70gw8/+MXnuxiDAiDxbru72l2OaTZR58LF7jLnlHISNQBi9I6L52IOkGkZ1Vc1EllMwTkmCMHF7RoA0TG1jRPJgDT0Y5Fpvz9OU/YR+n7syOc85lTHoaOylpRNzTMjqFkxKcETmPfE3jGheWYXm6uLqzy/aOLaUwCVw/3derVpY/v82c1qtXr95t33L14awlWzbtYtNY6qYlWDAonQs+fXmmE85lSmEDrvutvbPRKtuxUST+NsCs45y6XkIqIIROgQUHLx5ObxJAJkDGRCOs9FBNQkRv/40eNVt97vD7e3+3nObbt2sSngxCZCDhysSClZTZxzXdcRo4oA4jj0eR6ZoGs8bLs0T/OQAYwYPTMzuc1WJCNBzmWaxv3+eD/Dk8dqgNdXN6/yq9VqPfGcs5ZiRUYpRkQxtqvVVgyQidmRyyhiClDg0Bd8u885rbomrlZoSpyLjjklIiMCJiWE16++NhAi8j7G4GNwMTjyGAIuXBorpgJGpiXNU87peDoOw6gCmiBTcQ4MbLXeEDGTK4RSIOX0i1989e7dXiSXDIpYB/pGF5g9Ij5+9NgMAMJ299j79e393TCN05j7fh5GWDXTxTY+uXnSNivP5MgvwYwBmfeHA/NSPIyWyzZSGwIxEANgICYAVCBDTx4igaFzIZAn5y6fXMxlnuY5pXHOk6qSYeQYYrNt1lOTh2nIRawAeufaFla7tLkYr6ZpGmOL/Xw69qd+GgISNBRDjNGXOVPRdbtqvUfArFgAsxRkt9ps6uwC8hGoADpDEKUpWVBl0KypWTWhCQhkhgEiIbPz0TXRNSXlw2n/ow9+sl6tFfXd6W6yVDze9fd/8fnffvvym9DFOY1TmqdpGEeZEtzew2mGUaEgDAa/+9sREdI8DyfQDAGBsQP0ItB169VmHdqGnffBU+CuaVfcsUd2HBzffv99zqPiHJwFZudRQTNbSsk522xQiisZRItVCybPITjPhFSYyMwQCJ0DU0IkIsk6pTxn0pxR/TTTMNE06P393I/zMDVX1+vVxiHRatWU4PI8gdnN1SMzHPq5nMb1qltvwv19L2r9UMZpEkuVMVMspzJ3bdd2TdttQMeS7vreROacYJqmcSqEvFqvdrvLNkbGoqXILGmcCREwP3/SHaepa+nyInrnDrez6BCbtSncldw0hGYpGzkHCCoCYJK1H+a7/b4fjiKgBs4BEay6rpRCzCpQknpyRUSkVBdf3wZmKiLjPI3DnGZzYULmGLCJMTTgPTv2YHA6DcNwVGVQH1ysTazQUOOb2DA7CA0YUmCvZILFhRJaozC0m4uc8P4OX7/Qt69TmuBive5P+cOn3ccfPr/ePZn3+k/+h//15VdvX7+6neeFMlAs5TmhsamSOmASSCpqIEBoqFpr64Vd/p4gsNil/FC6Z1CzEjunl+eM5tybN3vfi1s4WfUgCA+6lrPx1DlpOVdJi5HQ+XAP6db5MDULososqC7hsIwienjUcu+9XuUBVVsOstC/q5+XPdSLtHwIq/gaYt0H63dgB4AP2prlRyrZIeP5eyI6QAdGqEHzDABvv0v/5H/6pyPf/4N/79+8uVjhb8PUD0Xmt2/2sWlWG0LTELrgSAzA1BOjc2UezSsaNDFkTTKX6Sht66ZTnvr+8ePrbhNVUx5pfzg49v1xGkfNU8opI+Lh/qBSdtuwu2i3u9V60w2DtW1jJjnP41C8h7Zpol97H0oCpqYfpjIAIpS3ewNYrRmdNk2YLedp6odRBWKEGMAZ5FNIUyDoQNdp1mlMSLDeRoNBdQbCIlHUqxmAqpWS55Qn5y1E8MGQioHNBSHL6WhDnpMCJnj0eE0+HnvdHw+nw+SceYYmrJ4/e2KnhOCAi2vMd65bI0YrltVs1zqBVHRirzYYonhGkZJlnsd5PE67zqPkwKH1mydXj1989eLd12+++Ms3717d5R7IgYoRA2FBK7xRR76gpnme80wNiqoVtaJQDAqAABQwBSu6QFqAagBytnQ7p/HnMuEBLKj6JrRqhbksc8NqQax1jjnWe+TFr+6o0yePH202F7/6/tuPf/rRbb9XoiyiZkXyq7tDw/CUfUpCDsQUDTw5RehiKMVySsMp9f3knaMmNLBqujiMfR2SZorgcrGiahRks+4uL7fdxgdSMiOFyNEK3I8nSADstm5NbvPo8cXQY9u4ppHTMe/WETJgkmE/vPrubt4DFCVxHlxAZ4IqklWQgatLkSIscmSq4PSCXxiYgimICBCWVLihVGZi4IiPP7x5/eoteChFHDusCZ2BihkJOEDGxx8/2l52xjLkg2vBMbiOow+4uTwd+jyoTSCjHPIRlBbY0UALBMJxGqvyNWJoXeeiD8XPqQQKIGBloStIVmbfth0jo6Jj3x96qO79piLFBEyAgUDJDM0MFvIymqDpInyqFfqv8a8ATMEq0oWIiHXKlpkhoz5AThW0Iiyl2EI6OtMWrJpa2MPqq314esBGjKwSqs50LHiAtn74MRa8qlJNz+rsM9Bkqmct0hLxKzT5w1bBg8bwNx4OK2oDSmBIi3gbz/EdEYGRjJgYCaVIdXZVKQDvzcWX+L8YTgEhPdjA1/euT9WGWsVDCFBhofAsX8awTmOusyGJ0DmuVzqllOdcJoEMGbQ6yi80NkQ0oqpNE6lPkzEbgSKA6kIzMVBRMRNRRDI6jzLBCi4QkUFlsjzAgrBcN10uY93YmNAQbOHNLLpTRDQ2IjaFeZznaVZdtiwiYiaKYlY42GrtVOh0nKc5CRQx02CuBQ+wu/SrjZvSkPNUJJlpoBbAcp5XmxWNMxJ2q1YsnQ45et7ttqf+MPYFwFREqWo/PROBKRE1rbDzIjqXMqbkCcc5xyYDkYBkmW9urlRgc+mff7j++osTOgAnaiqiUxrNip0JVNXm2yqdrM7ypLqhG5yXLlpdOr+5js0MBZSqq6WZGTPT4nVZw241OyBYnjECMoF5zkxsHhGgGI4pp1L0cDIkVV1tOmZg9t77Eaesgo7v7t4+vn662jZPnz4ZQbKjtm38brMHi614h413rfMjFsOSZS4qWUzRMTkgFJG5zMheAMAHZUpJT9NY1I7jKIYhtFhMkxLOKpCzFptTmec5zdOQU0mpaMPDMB2OQzEI7BARkOV8L9h5Ss1yg5xpnz+Aws9i5fNNq2fQGwwUrU7cqeisC27pS9a/NHtoANaE7r1oGUHBGOxhZass7nzLRqgGTHCOJZXd9cB8/0EwWXIwMDMRM0BH55sRtMK9BlWbiN4xSQZ1BAKYjFjj5198eTodYwzPHl3H1jHZtr257h6nw/7w7ouvv+0/fdop8tv9KYOtLrbry102uXt7l96M2CJWUkX1sCVDBOcdMZID3zgA10ie+gQGJpLTJKV4tqbxp9PpNOzHSQhRzbo27Lbr9ao9nU5jPz99dEPIw9B/8uEnV1fXwfn9/jgd09AP0+nw0z/4/XEYd83uZncDuxuPXDseAAAgAElEQVQd4dX69evXr9+9vc2zNF3DxKoltp0BvHnzOsZ4/fjaQO/u72PwzI4JSyo5J8duvekowtt3t/C1wqfwxz/79O///T/83Z99vF7j7f23w9jf3b82nWL0wGSF5qTjnOeiRVUA0Tnnkb1d3lzK28IEwTvnyXvvGdEEzJgrUQ+rVWjTNtv1NsQ2+gCgIfgL74i8FDsdjlnyNM+n0yHn2TkOwT9+8qRGzHEcQ9hd7C5wv89udi5o0TSmJFkV2NXQj4wUvCciYp7njGoMSAaaRIXQYRsiG085gSghG9k0TDlPovM45VzAeZAioVs5I0+ipoiksjBomJ2qOPDeua6LKaWcJOdckdzqZrrb3gTvQbHejIHdzfXlxx8+ff36VrR/dwerVbx+dBlXXTGdSxLLYqLAReLpuGd0JWcp0LUUAhOZqgbHRgyAFeetYDIUZXSApqIiwsQAykxEllWKWkRoGt91qxD8ZrMF4GlK05TqsNFSNOeSU3YeqAqYABk4BO66JoRqq2x9oGmaYqAQHNNKJZvdEvm2jV3XNKFxTTydjn1/OB2HlCdG6AJ0Xet9AABV67qO2R8PxzHNwzDNCaKnGGPbtqWkUrKCiIkBkAP04BCITTWLFCJddYF8O06l5OQdIgE7Q9TtqgMDJCNi75nQaiipNgBmhdBc9CE6IlQtIsVAiAEUmo6Ca7z33aptV2umUAz6Yb67H0qx29u3wwCmkAoY2aDJLKFNNRB+9vmby8v26ePHN49utk8vbh49vdsfvnvxDbMnPFGlcGeVLCRQODlmroGr5DT2ITgiiM6t27Dp1uu2NeGWnWkxzaiIxo4DATusmzeDsmbjzjsUT1KQHbqsGRVARDUhgKQJsngEZCJBEiDA6OPaRV2t53IMCN4oEJ6mfspJ1OaU09Az2sqCd01wIXuaVUQLOfbBOe+ICIhjt2IfS1ZJkrNAkXRMxYovcesuA0UzNGEU0kyJgD2BNJRkd/nRNE1jHhN0bsVv7l9+f7vfZ8k+hnaFzMheDed+SgWIwQdRUQBrFd68np2DnGE8gmRgBcaJaU5JfBhiewBEARAT8ry72F49urp5fHN9cbVaNZ8+ftYf7u+Ob4bxrpR+zHPKaZjGtmuuLtbjKHMyRJcSlDIjaggYI3hGRB7HqYITDIjsmMgRZS3FkqIWQ49s5BUZWMBsmMGdcuywXTf702m3a2Pj2SGqxdaDUcrFeUJG711sPB+diiuTG+ecRclzbFbrthnTxA48+9DQZishzNWMVQ2zgKCEJmx32651KtM8zqmoKIhJ6k/tqstAxDnnI0BiX2JjjOKCuVBUzQMZSqksI2KgEjwo6Kk/btYbA0UE7x0iXlxcHk9DFnXsRHK1tvDesUNiZI+IKiVlTUkMGEIIXde0kWIDxMpcTd1xGqd5TiIYA4nOOZV5PjlGiNHHGKNP+UTOQiTnMEEODa+26jpxOPdH2r8N+zd0vIMmQHR8sYWf/PjTD5584KF7d3v7Z3/2eciEQm3gWUuZlViraxU6NEi52JJ0UK1N6oD6qmBR+PXi5oz7vE8UF8CmJikPfyuLBcm5H23nYYHn2sN+UNz8UI3yg8cDz8pMqwsCPUhhRN9XSu+PDwagIoAPB10S3HPaWxErQKgzphZ3djzPNLSz7BEUgEEfaAtoSJXYpVC7hg9YBCzse6oMIxUAh4RgWHJGVPBshb3z2fK3X99+/7dvfvWLl//GH/9h6dKPP/n4dLo7Ht7OY46t9xRs1VkOBgBa1BRE1JTR5SQlqRomhTxNTevSWJC0TGrKKqCCJWeGUOuqUmQcBpGci2427tGTbduxyDTNaCAhBJGCCEyFiWNs2rbz3puRKBVlHQZCmzOoAnnxs4ATYMha1cKQFKwAAOzv0927RHAKbi+FhmEuRXdjAMwGRgS5UBI2MSADMFXNAk+egLnAMSBxsalW9+hCt3EUBxBzvuuHPJymnGQcsnOFad01q8urq6/0FwBcbKbZGucgk2PiYG3T+shzOs5zP88iBaInBUy5ZDFJGdRicNu4u7l40vAq9/b9129ffb5/+f0RZwguElGRorlw8GysBUxMUsmSgDHGDtW0GGSFYiBgSlBMtIBAVQ1W5Y4ZnsGDMxfwfBf82q1U61Y6/2ZQtADgQp+pS1sQZju8OfbvxtZ5UJAsKiqmIlZKATVVCE0gTwy63YFjH31wHMyHKed5mE6H6XSchwGil2DJh7haxTmv5nHoR1OxMRdkWLew3ba77XqzjrF1x+NrnbIHTxwKyQLY+WI4jXnvmV1AH4ldBkxtG479PN3Pp/uTTIAGoEhCRGigqGoqZECAZISIpmiVLGFwNlnB9yUoooiAAwBQr4VUWSwUtwLYAAHoCYqUgmWB+ZxCRAhYgnz0Ox9c3ux+9atf/u3XL64v2u1uM8zJOS+Et7e3nNgECdkSELEUQTFHBLig4VUEE31gYpHFw0xNgNhAIJMYzTYrKiHX2XMqRYrhYpCiIGp14LURGCoaqqmYFoVq5G8PYIj9GvnqIQwuxjJQZcyVYFAD3DkiLtHSKvYOP6BTVY3BOcbagy6uBk+DZTAfKvwADoNq+mGLISE+1LoGC562HPpB8V1Rmwd14QM15l/9cIRoVQde4YQFbEImAsRs4ASRvAOPGcY0S814lUDUBb9QP2yBdxSlKvgRIBczkPPglLqFEaKaQlHxuEj5zy0RAwACMl1KdUJyEAxQ5lyFpqAABUwAueInjMBVSYUAiz0QCCExVIlHZYuIKaoCFDEQQFBTkbMFEWKdnVg3SGZWFXi4UgiwXGoFrfu0VoRXKx4ARsiOOc1JVYkppdT3fUrJBwZUNQEzcOACZjOO1m0bz46c0qBSshlsO7i+aYJ3681aHR/u9/04tQ2hI1NBgxcvXzjX5iyQtWm8zBkG4Ater9dImqbBBwdmTOxDiDEgoEqp/XxZxGBE7BV0HCG4MW+Kmk5lfvT0uu+n1WrDtpH0zddfvDPI6EJEPty/daHRikqaVO7UYtRWadmKQFb35vMFrJDkOXlYVgUZGSKigHEVrKGiEpEpnm3E1NQW+001MJhnMZ1ylmGaY4iOIOepH9MslmRG7kPwRLBetZvVxi6SlVIkDcPpu/3QdM1HH3/cbttm7X/57QvL4zAcpuO9FmgebdjprKciPQfzwdUBtV23Xm9bASiS+rFHF408IBm5LHbop1M/vb0/hNh63xESQantH5m1FNAEZc4pyzhOU5qhw2+/fzkME1C9OSoV0N6z3ZfZO/ADnO83gWtbTrc9mDQsXcUzRd4WgBxpIaov/7OEq3OLscoJl93OQIXAgAiNUHIlXi13Qg1JoDWU0AInv+fMP/wEM0Oq6r3ls9Y7qdJaK5XSTMCAfQBHBEhsQpiMPIW//JvPv/rmq7v7/c/+td95/vjR1cVuzeEmNv/1f/yf/6f/8D/4j/6z/6pMWSBfbNvi5JAP968PgAAt7362s7tpHuc0G5K4SIDESC64tm13bpskNU30jkbXM6CJvH39GgF2u61jG4eDifh6Xhh2683TR0932/W7t+9Q6Gr3iIlktP/r//gXMNQLsLhSAMI3//f/AgKwgusPds+fPd9e7J5cPnly9eTLL375/Yvvp3EiFQPpto2ZTWmMK3z20fVmF/irst+fVHJOgEpIWrDs+6lN9MknV7t/vfuH/+G//6NPn11ftS9ff/Xd6+8PhxdI6cXLrwGmDz/68Zcv3k4JDof+NIxZLRVTw27Vhia0bfPk0RVByfO8WflVE7s2BO+0lJQmLTL2hzmLD7Em+I+f3KxXW0QqRTfbTezWKvb2zbtxHlNKoppzvru//cWXv7y7f/vHf/B7nun23e3d7Z0Wubi8lGKr9TY08d3tbfCtD03KWaWUPFtRM6QajQX6w4HYBY7GnCRBQZMyl3HO5Xg67u9nQ2haaBpGFmJAgjZQGz1h9K5l35lpSimlJArM7JwHZHYcYhuarmkaZgYY67jbnGWecpqzFBv7VFLOOQNCyel0Ot3evvmtH//OT3/2775+c/fP/uwv//KvPp8ykAMjaFpY79bbbRfj9qsvPr+6eJxzcg4IxTNdXV3mbEwhl8KoGSSnvCReNbOoW4CqlhkIkA2gAEKIcHXVPn129fTpo81ms9nsDofjYT+8fXM3TMmMktqhP2XVrutidRAEcI4RichidG3XlpLZ4XrbBe+Z3TxNDtchOia/We/W213XrfvjeFI4HsfT6QBo3rWuGYnd/e3peLrv+361WjETMYnkOUHO4EhUTSQjFcNUdK7dmcYjMzY+rFeR0SQPBOvdxaYVOvYKmFJWZnQOAWC7W3EdlLdMQSE2MxWEDJrRNMbQNJEIDMRUmWDddm3wqkDY7LaXm806xEDspin34/T2zX0/TGA8JTJCFVQCQJJKD5VqQ4DNKh77dPvZl/o3X8YIF7vLzWb97NmHCJjzfLndNN4z4v7+UOYxetc1TRO8qZYylzQguFUXLi82j66311e74DDPRs6j2jQNoIpCjIHRgefFTEFN1EoyMhcdeuZcGimFFRoKYDDOU9ESm7jerHwb1CyXoqbE6J13nrrtR8yohElyP453w3Ecp3EYLAtoiRjaGGJo9mncT30/lHke00TkHCI8edK1oXGNJ2TJ2h9HnZIDulht1psdidcJAjcMURTzJKUgrTfXV9cf3XRq2zd3p7GUcLFd73Zf/s3f/PzLL755/c1URn88zrlPc54myAOgEkALrmNPXEpKU1JWQSmlSEnZYAYwJQBNAJzhkJe0kwAQbl8evvz8W3DLqJDf//FHz5/ePP/g8fNHz4fp7vXbbyEffBvrRAtHisGIJHgQQQBwDmKA4Nk5fzreOkImds4HF9gxOyrRZSnk0PlAyjQXOyoFVG8J4H4Ud5ziJhxe3Y5z9/z588vLS4d46k+okGWODaci49hPaRynPmfV7E7HdJrAB7l5xE2zCc3aefTRBwzIGmYCgJxTZKMIj59fPHp2tb1cMWmaZihIzpEPeZ5TljyNIqWU8u42ex+zZA6a00nRdVsuVladd4EPYyJ0MfimbWLDhHbq7y6vdsH7JoQQAjNfXFy+fvX29dt7MsilTBmIgB16T0hArKqqkBCFPHiHu916d7l2VbFpM5iklBHLMAynHjxD2xqhsE9OzXuL3bzahPXa3d8fY9M0nUNnnlzsoOkQPBxvTy+/19ffNeMet/7m6ZPdo6v2H/zdv/vphz8+vS3/+B/90//tH38Gt5BNY0vOVz9HYMbFtfZMijIFQzw38QH1TC+qzpa/luWY6nu/hMXV8oc50A8qqeX3B7r5kg4tthXnxPMHfdOa1J8LNaPFSQiR7CE5RUQ9Tyg3QsDFVOs8c9kKLHLAh89Ukzhb8jiyagsAAjWtq58LDc4mM4hWR+eZAQgiA9ameHU/WXIzOcteQInA6kEAAUwBCwAACoARkGQjIMowvYM//Uc//9P/+ef/7X/3X2yu4k9/+2dt9NfX3Z/+6V+sGnMBAzRkq+9/BccTiiYYDRwS+tQPTB6cJQWY9L7rVWG9jgw8DH3KZmar9pI55uSkTIRYioyTrtb0wUfX1zfbNB32x/2UmtVqQ2REtFqtT8c+BO8cO8c+uA4AiJACMeU85VJULWeYkpEz5xiwZYdWchHdXVwg+JzG4+FQErHfxbZln+Z5ZheLDEjKngQUUQAykLFjx84ox3btG+bIAIUKgQnzau1XYLQBsyLOx+NpeP3ybp5lnsDxyYA/eB5unl7f5T/bduCdc62nBgqjqHDRQBEB5imDWckQnW/jahosTeM8mil2HrZN8/GT5x8+/kB6/f7rN3/9578avgPowZDMg4KBAIFDcZaxjJZKyamAAKDRCqmgFdBiUGf76FlIWP2DlAlIYWFWwXss4gHs/JfEYkhnstZSup5vnWVVKyDMcHynL754s5P20cXNF59/4XctNgGIcy6owgRt1yCK87ZutpYh5VLSBObv3xzv98PpmOcEJYMksHngNe1225snF3nqDqdTytkEvbfL3abtQmTHpGRCI6xgA7F1cbtuDNGfhqNABp7uDpNHaGMXpTPWJsIqti9P92++nQ63wIIkCOYQSLUAiJqYKiiC4dlF772THWqlCFDlX3N1JCdUQmODAL71E43sMMP80z/5+HQ6HW770/1MBatM0zWuWTcY8e/9vX/r1ZuX37371cXz3Z88++mrly/Hedq22zTpeBzhFkSV2bMyKUhRlUrNIWCQLIAAApF4s1oDw91pL5IcujLNl9ttGUt/GEsRnSRDqdPStBiKqQCg1sprwcEW6qaioaiqVKE1gVHFkH6D9FSdYxCRq6/LmamD5+pQzKyyuBZaBAAAOvqNWAsVzGICrYESQNmWAZhYcbUlUCOeaSwVwgeq3XMDBKhDkEAA9Lxq69wMXEy5DMGgKoTA4IGj9a9+uNpolgeJ2NIZqEQ8YCJFJGIPTkVLKVZKPSWG4JxTrQ5XNT4v55GrOi8ntWXvWmpf1cXH3hQQK8FHz3JHRDRDFVABgBrGOSBnM0gJCuCZI0fMVDebWkKgipoWqZ+ZFFWBKkuIgZigCoSVFLWqHbG65taq/QfktIplaWVt4gMUWVskqMXMFKoDssJiAE9oQJKllv9FZJomA/PRK2uak6igAiMmhawiIN4Hv/IrbsSCWeqasNl23hM7zCWnOZtAbAIiFlEE0CL7413KwI7naTTA7VXwLR6PJ0DbbjdMGjx4B94x1RmRxcwshDhOkydP7Ju2My05D8Ng9/v7dbcbhnFOY9u24PnR4+7f/nee//f/4n/MK/BYANA5KiUvzMAlKzkvEeLqc7RcqgXUwPOl/vWswxSUFM8rZBlOtzimGaDSeWIsImh1JgAVm1VyETdNzidygCZzNkLwgZvYrrp1ExtHFEOA7Vak3N3dnY49OB7zyXm46lZzut4f7pPo7XzcNLBx7sMPH19crBAs64xO2bOYAtJqtdvswnB8O0/jaTz5CBRYAKTYMJXTOB+HsT+BlCyxFMFhyNNY8miawRShmIgwgYGaagj+q2++G+YZEARtseqsKdf53CywNy7nDx7OYw1INQ+y939duZA/3J6wrv0zvr4g5yL2gF4tP6vRw5mHCKpKNYwsnu413KlBHd5Ly/tW51HExea9NhBNtZrK1XWhBqRgpGS8QJZ14CcjEAFVQpY5dsZgRAI8C/i4Hub0zas3sWkMYLu7aCmm6fh67tfri//mv/xPPvvyq3/+2S8+/+YVGGy3vkUccplJFEtcASCQA+ec875kFZWUJkRou6iqIXgEaIiDc4f98TiOACDtnOYeNEcP3HpmD4Crros+BAqPLh5Bof3rwzzNh/tTRNCAZTYiZE8iKsnWl62JplLefbfP+/Lk+ZPrx9fdut3ttilN3754NUw5tHlOp6Z1m8b5WHwsN49XbfvR//5//nWdhxRRzUHOCgi/9dOP/s7f+cPf/smPn31wLTZ89ssv++FtsV6hNNE9efYkpV4Qv/3uVcrcD+OUMxCzb5xnH8ImxtW6JbDoKKBfddF5EinqUCTnaZjn4f7+KKouNByCGXSr1Xa7InKi1nadqE1pGsaTSAGydhW7zqPZOJ5+uX/1Wz/6+NHNdYhNSm/fvHnbxAbULi4ufPSH/aHxER2O8zyPo4kRClkppipFTYfTqVttvG/IOzKHhsqBvWfO8zCAAjvomhi8Iweh8T5SCMwOHVk/pi5EXkbWmpkheXbR1ABRFIZxnuciktI8qQCxNzMCIMTQelOzKKbCjrumjcF3MRxPr+e8n2e9uW7/6I8+ffn69eE4jDOggkynCZLw2B+GVTsZqhUY+hGt6do1NDzNOSVFkDoS6wHTNFWwjAZohgwKUIqBALfw5Mn2k08eP376qGli0zSqNgzTYX989/ZuLgoGo8BprCSAEeMCYEkhwMzMiGImuWREiDF6z4hgMgOW9Tq27bpt1ogwDv2rN6/7fsopi1SmMRSBaShG8vrl23E6lny13W6a6NerdrdNgc0xIWpKE+BsMMeWnCMQYEBCaCI3jZMyTfMp55X3a+ddET9PgdmYkR0CCJgQoXNV8GUAUsFuAKgRnRlj9IiWi5WSEdF7H4JH4FMvxJF9C8jjnA/3p/2p3x8HBHYuZKGcEYFEBRxS8Ay0DLUWA/BiNpecJpgSMPZFNZXsHccYbm5u1l13ur93oLaKDNA1oW0iA4ikwzE7T+tVuNi1u23XBAYpWrKqeeToGisKwqKGREwuMAOjKqiplaq7dkzsfSAAzZL7aeGlohEBOWZiKWWepzlNgOC9986V6eA8u+DBcTC7bNpdbPHiMs9JUsICliVPcwDwYuP+eDodlTTGxoU4xg0Aeg6N67yPl82Go9s064vdBRq/+Ob1cJx269iF4DV4IgrhavXo+dWHl93NX/7qs/0+F8bxVAa6//Lr71+9vR+SFMPxNM055wySQQXQkL0DDmZYTFPBxrfMBFZcyGhalCRnXTxHz60XhNAEckv2uxgNqd1/P0zvXnz3xZu44u0uPv3o2QdPf1R0fPvu9e3+neZEjASAbESkpajknJVACUsMEMiIzTt1vjhSYC5QKKgDRs4mrG4qPiODI1SFInbKeT+mJti7w+H65ulqu92uuvvPb6dh8j62q9aG1A99lglZY/QE6IcBesgzTNM0TadHz25ECzsDKCizzn1RoYDrVru2/eCTq27FfdqjZQANnQPXmCvmzETuj9k3zEwipjoXUVWdk5Vc6gAKH0mVqCTnoW14s226VZSS9vthnkfHtXFVPb7FTNI8TtMsBtEjutoPqqMXQLEgiW+AHDTUdKvOsSt5THOvkACsZCGilDIAEAMxMil7WG980+Cq4aYFF0vTUtuFpnPAUojYp1LsdMDb13r3DvI0MYdHV5sPHl9fbttn188OL06f/fn3P/9nn9EIcRXHfs5pUVxUr/33vit4TkWwCueWXrotdum/2aU7J0QPtCetfwn03rjjjFv94CU/LDaWYv691PBfNgCuC/YHr3jvsIXnPl+1ODl/JKtGXksf9lygnL/YOemq2U5tpqMx4sO7my2sgx+8hZkBCtYEb8HQqo1i3eoeeF6GCGSCS4KIsnj9srFzpqUMo+9C41pDdUDHr8df/tW3v/8nP2mte3J5Y/DJXz35C8k2Hnumbt3ttletWu77DALADoGhgCUi8pFo0jGPhk5jiKu2/f7td+g0uHa92qjQyVIVpagpAFxddlfXa8IyTv04T84x1vkKkmMMzjkAS3keppNYAAAiDIHaLkQlEck5IRmRN+UiDgnUQJSlyP09eO9yadTmIaWcR+9NxeZUkkBJhT3HyNmkSBHJxJXjgAgY25YYRFUKFDVC5x0xkwEyuIJkiPNcpiSpQFFQg2N/OI3r3dVqdwWblfchgPOGWNRKsZTFe6W59AdrArYR27gJoUv9kIY0T9B41wV4dLFbN41M8va7/Xdfvh3eABakhjRbnmYogI5j0yCgZBNLImWxxCbAbFREH8SD9SILmNYJFlRT7Mp0QQTTOjSrJuvyUEOcb4ma5z88aWec9aHMqMuLHbk8zXevTrDR508fv/j5fAm5w11oXHSRVEuc2hAREjptYhhLHodRU2JqXr/ZzwOocOtaZeqnuR9np6MLsVk1l09266vtPE+emQg0F5nGU5mi97zqGtjkNJ6mpHw0zwFpt4ncOKQ8T0UzkDMDmefM0KzaC2d3aZh0goBNUWWrhj9WQEBL7ZGD4kK9AgMABUWj822tgKAGDA6JiFhJgIECuo4mHAg00/yjH3869Kvdfrh/fQ8FVbSgoWOOAR0f0yHRjAyTjGmefEsX20eY/d2Ll/27HhQIGDNpUhVAJbJKjzHLQg6xuhYZBXQZi2ZhYiaayuDbrYskrZSpJMmmyEaqZgIeXc4jL2WY0aK7RpWzz7GeVcX1WhOAEYKhUeXonmlnCzunLocFv6pxGB60ZQ/LBwCAgd7rCuH9QQAACRDY1IjRjBWXoXem5zhG9sN3ZQMkohrz1QCoiAADAOLZyg0fMCx8H8kfgj39IOT/fzwc1eh7jvSMpAhqQnqeYIvIRARkZARYM1Sk2iT84RYCBLAMt38gdZyjuYkVlMVdB4GYFlef2oEhXPw6FR4YcapgggAMQstNTlWzB0vfu+JmlSKkCHI2+hGFsvDVyAEhExMSqKkYZjyX4WD0/zL2Jj+3ZVee0Gp2c8653de9LjrbaWfYzghnOjOrkkaooCgKgZAYAEJiwASYIv4S/gmQYMCkEKIGIERbVLqyMtPpqlKmu3DY0b7ma25zmt2stRicc7+wq3LAHYT0XsSLd797995nr19LjGBE88Nk7oFagnx0aWNEwBnUAwBY2KIlAUrNRMUqCgho0dliWbkAATliT464KkoxE8hqoJCrnoaxqKqqi5FB1bBZNUCgaCql5EpkbeO8c6oGJiq6WW9Oh1vNQFjHApeXzc2Ta9X65vZ2s2lXbah1apvWsZmVGZ6rVUQqs5vyoWu64KlpWrOKCKXo4XA/bJ8jHFMqntsqdbXe/dYHH/x3T/6+L0DV1CB2vh7TchwwIpKRzisZiWeH2Vzj+AjL/BoLBmg4f6rzZwWP4p1ziYHRHPR93j9Gcwqdmvrg5jIJVShgAhVlEUt6t1iatVTJJQuQWePD9cUliLzJ02rbCkz7413Xdl3g954/qWpPLy48UkP0rXffi2u+7V89HG5LybVKHaYM4GN0Pt7eP0gdUxpXvmWAVCSV6XgaplRLhVLBxprSUKvlSdOoWoCNCahyMdMmBucJAJzzP//Fz/ppnFeJmoLO9xRcluxXjAoCoshfo/1ciMPlqYU0m7vnGx7A8jkTyYIqIs6auMfLEMKynpeIKtBZTqBz1BudTw+kx79RFBhEAYnmuyT95pkCv3amLDClLt/ecizC+RQjQmZwiA7IITIBWBGzqeRaPYJKLfUhpfrm9uF4Gh7eevvdza4L7adf/iNcixAAACAASURBVOIP//DDZ+88/drXf+trP/npX33ys5999rqacw36QASji8SErTnmYIrHmkoVFZhyGlNo2gCwGOOd4bqNdL0SqY4hj+NuvTn0RzDzzM77JkQCOu2H4/74cH94/fK1VtFKlkmLWgH0zkF0CiJS7yWugkM/pukw9Dl/dHv7enu5uXxyeX19depP98ceSU/jg181T2+e1FKH6c1uvXn3GzffeX3dtS0o9sexJHnx7MXbbz3/8MPvfOPb7z59evXPfvxPSj2d+jdVhpQPpZ7chNc3W3P2xas3fV9S0ZQ0iYkVL+RVffAx+ib4sd9rnZoQosda8+l0KJml5jQMtZbT6d4AqaRQm5RraKJa9c43PhDb61d3D/eHu4cHQGAmEHXOEWKepjTlj37xCyJqY7teb46H49RPzKxVskFwTWhaRa1iEMFxYOd5ctM0FjFEYOcZnWfngJgCGBu7auTZ2WZH1hJDtw4hOPLYtMFHRtSqWWq+v7vLbRdjBASDuZHL1WqzqCrlOj81yGqtOYRmu4m+bYJHMJrjS9QUTB1B0zZN5ODnbMuErLtd3G6fvfXsxfE4vbm96/tTrkMq49DnxnsyYDQwGHpI/f3NE3I+pmGYhmSqjlDZJD9u3SVzkQiIgQmAgDxcXOF77z1/++2bGN04jt7HPNX9w/54HHJWRAQiVg3Blui0uUDBTFVrhuzGiQFARMQ5JrScVERKHsG0jevgqdR0Oo7H/XjoewTv2QenwzQO/TQoWEK39SZWEqRxtFXbdS3vyHHIk8hMZjLtT/vQuLZt0FCrSRKp1TlkllpzFSl1KLVHIlN1jN5FHwhRRBWhoqFVzaWWXA0gBNcGJgLm5WYCaM47JFSttVYRme8245RPwygKVWWc0mF/GqdcRVftBYemCJ36DAbZAFwNXgm9VchZatGSe2YkQB9MAQ59Hko2hCfXF03b1FJF6na39pdrq9Vqjp7bJnhmhLraqHPYxLBeRe+RQJDAM9daybuuaUHBBEQcQGR23nl2DpEBsZRiqIAKaMTgHJi3JkTPTgGqZmIOTTSwUjIFiiUqGDMFZhj2oKXWgp5d8CEGYgazyg7bNpKrqQz90OcMVXvXoCvA0DSrpmulz2BIZBZ9s15tuq3nRgUe3vRpLOMhk0YsETCu4u5i96QJq213sQ5bgJgm8mFHTl7dv/7i489++vOPex1c0xD7Q98DtERiTtHUjI2X8utqUBH6ITGjKpox+8ahF1espkoZAMQUrCKS1ZnUmL0JhIZs+MlHtz76JnLs8Opqw9oNW63YU4jb1fU4HYomZlCjUkFqqdWE1EIBoc2aHRkzOFbkwggV0GpyEYilOlXR0OV2+0icoVRTr30t28uNlONpTFmNgvdNM6XJBXIeY8OxdYIBcF0mSpNlaUXHUUAgT+UwTE4sBwDnAf3o20wKPuBqHS9268snPufh7nQCq00Ttut1CE4pCitUlUNpOTrPZopEklM1qQJFtFYgh+SJRIOAC+ajumChRRMeE/VD73wByKnwnIw2Taeccs7qPXRdMFKVkiEzklNnqOSs9czoAqyZeZpSfzqk1CMDIUipznsD6FoIIThmZgmRdrumbcCzqpYqxQd0zoiNA/kQgGupbtjDsJ9AoGvJo91c84un3bPLa0r8qx9/9pN/9Ombn0Ckzq3crMRjDkSSUpIyG6OXw3C+08i5vftxzDZA0N9g1s+s2/wLAjMwOhOhj+Kj5f/xlWHq18Yae+xnm4lymy9Gs3/vfB2h5aA+Y0gzK70MZnaGl2abnqktf+1cxGyA5H5zYsIzDzsTjGiGoIvqAB//7RlNI/zqZbaMKjRHGDAsP+hcJwdkgLOsEY3MaB6eFpkDVlOQWlQVEDwHBgQFLgww/uP/4y9XbWxb2zzFpzdP/uYf/P4XX7z66Gev8tgrpq7zOWFVTFZBxQwBG1VH6r0PE41WDQg8s3fu9at90+HlbhVWXaq1JhtOyQxChNUGrq420dPxdKj1FAKs1sF5sLGoVtU6Ow1yrga5FD/PumLovDEzUxRtshSpmqtJXxBB1UqFklQVvRdR8rHlBKf+qOMRlMwgaGOqbWiQfGD26FUbdujcQqiUqnOjVilJrXrvwcQ0iagplKLeu6KZPbAt8cpJ+ofjbfNAH3z/ec75cEyHwzBMBoDsKMbA2DBqgIMHjhQCNiReRi0jgEBccRvii6dPyql++cXnn/z0dv8yQQJEJgRgEwF2POeBmlo1AxUBAUPyjh1BUqwK1bCC6ayum4so5/SjWcS3ZA8vosOldcDQ5mZM/DWlAC7z91d7A2FBwQBgcYeBAamnJP390JwcmQMCVEbFwB4QHUAekhbjDmMT2TtEMQNV9Mj3b4ABujauV5eiPI4PWmUYE9wfulra9cbHtorOzMRh34+HnrRebnfq4Nvf+p3Xb+4/f3V7N/SIuNoEiAZhMkAfwCo33kdusPqGuAtXDC+xniBXRQZhADZQhapacK5Us0dniZ7vY4saCxHmWmEAUD0jEQTGwA2GtcPOEo2TnCQmQI2eL+LKiauiRTXVmqqkPH1y+8syZSZyAdDUMTSxAXHjfUoHJWIWlr5qAQT2OA/HpiZVtDVfRchB4yMbTrkgKJOb0Z5xHKCY1rpMUSqzzsAUyRHpnKS0eJIcOjWTKmdZES36upk9RACcfW5nBB3PUr1HMPN8Zj3mp+FSJW9mj/Fos+DnrPc7L6uZmUQwUyJeLIEEOAuBdDZLohnBYhgkBLQlIp4ee2HPtXhnVcUjRgRmgPRoK1o4D/hr8rz+2pebE511+XGREA2gymzCXCphANEUCZiIxXDO9HLea9WZqVggP2IiEJjvuDA7VsUE0OgsAEFYAo+LTDZDIOcBeAaSHPpqYqYAbIYzRD0HgJHRIs9TUZ2hAJjPfGZGR7NQxABMzarMMCXrvCDMDMjMMdVZYCWmS63kfONeJgrEub50xrof8ZX5H4vwBA0MDWevoUguMudUpikpVBc8MggIOvStN5d0pjodAvOY8pASETbBqYlIZkc65a4L3jMYbLoVsqrINGVVrb4wUnDOVBgJSBiZEKuqSdHqUzKpGbcrYsx5Klm992Zaa87ZHfteVrLqmqYJwQfv5mXGwzCmVN578Y03r29N+cX1mh38O//Gv/QXf/6jh5cjkhkIACADEiDTciIYkTGzQ8QqGQz51xxss3ZzvkXMT/eFmjUDPXdn4uOB+8gRLBIhBkIAB/OHjwQEBLPD05AEyyy6y0kOhxOZXl5s2+AcYhtDs9oQAJPd3KxNyhdffhI5xNherFYC8PT6oovRI754euM9ng77U3/IUnLKuWoFYu/dyV7fviYSQlsREvEwlVOR02mcUp5FSLVAlaICNYMWAEEEcuQEq5Tato1zJKZV5ccf/xSH6JBM5+2iaGwGpmogC3JEiMiIWIv8CwDR+TE0l8otC3FxZ86MJs9Ew1xXcC4flEcp//mwWjB4AJiT9cFmCZzq0jNIs9jL5sQ4AJzhfrCF9pmvUWDzA4LOh+b5/S6XxfmK9pgQcUZ8HXv2ZIiqWqSkWiiZ9+hQvejD6TSlvkg+vXnF77//9XffuTu+ci0/eX6xe3Jx9fb28sdr+Uc/enn3KqFVRFVo147MEzpRHsdcREoBQACx8Zicx1JL9N6KjMPIBLvNSq3mkqrUq5vLlFMRa5umW63bpiWA1y/vPvnFp6WWnMARkYJWRHWMiDOMb2iGlIE8IWNw3geSKoe7o4psd5uLm93zF08U8pQnIqiayW0d63Dq+zFtL9yzd2IIgYBvpF216w8/+N43fusbu80WEd7cfvnxxz8mL7HBfty/evVprj0wcHgP2aZUUrZSTY21ypAKTOICEFHXhS6GaTihVk+e0KZpTOPQeIeoJkKEsYk6O1dNT/1hM+2GISCi966U/Ob1y/v7fcqVyDESGxQAE60pmcFHv/glGn7rm9+8uroOPiDier0qWbKki+3ONU0/jd6pI+eIVNfDeBr6U5FMPDdPshkLAgOqoiGRw+B814QnN1DnOBAE8uQcKUrOOZciUo+HVIs1jTRNDDH4EJg45zSmCqDMPLeeAuQ09bmq920bPVOIsUtDBkStUkouZD56dtx05IhzLrkkz65pu+7pZsp5t6O+X03TNIzTONQ39wOqOYarizZN+vpNGvrBe5mmUaVG50Qh1eVxxUQKOl+ciJDIVmu/2jWrTbi8WT9/cR0b/3D/UKs0zSoN/cPDPqXMhBwaJAYnKIuSkYkeGVTnnHPkPIfgVdk5FpHjcT9OU/S46lofqJZ0PO4fHvphTAiRGBEZFCXpVA0qkLrgA6MDg5ymaRxidDH4cBFTmsvgEMkmdcyz156WnFAmR4ikSMpkBmWaeiAqpSBCbHzTOLWScyUmQii1jOMwjhmRRDyBYyakOZihipSmCc4xgI3jmFICAHYcQpOrDg+HU9+nlEoRBSb0U6oUsGk3tY7DUIoURRAtACIFatZcoIuuSgWFGNxutdpdrJmJnTRNg0R3d3f96fDs5qrbdMTAkRxT49k7R0QXV0+9R8cMJgjKBMHH1seSauDQ+NYUVFDNmzqYgwWIiR0zqxgyECsREs9t5Ua8hFsqSpnddrUome8aZ27OS0OTLgbQqmhqAgokhCYi5gCCc63z6MM6hCnLxWpz2a3HkgUMCZGpFkBjRyFy07iGCtQpH/s0DpnRXW2fdXHbxW3nNpvm8nL7tPObwC0ojTk/uXox2DRI/6vXX/z4xx99+fKlW8XLzZYi5Dr5wCI1pTSNlAtUq2ok4NBzoCbX7IgR0YfQ+rWDxorUPKY8idSachHFWV9kiwpeTEGsKkIFIgbgKesn+zcff/aKHGxX/sXXLp+8WLVNS9VUMpozILEKWlUBPBDquotE4tiIhcgAzSODZxekFigZHPum9WE1HU55moyQkRrnggsuV0Pl17e3/ud02O+C992qS2nq70Ygjl2LnolZGgyDVmnBlySVA4cODsNLYjPHFKjpZLNz7GfjMjKnJPssqWKPYFNNnCXGSA2RYK0VEYtgLhVQYxNNSRR8JAObJutW0YeoUDsMyKCYx6whKxMCqg/gHJqVUjIRmBUzcYzRQ4zOBzc/tuY5bO58JjbnXYwtZSdSx3Hoh1Eq+Ai0yLXMMYd1DKFBAu+wa7VbcdMAqNRatVhsWmYAUGLwDVfT4eiPb/j0UBHrxWVoPDx5RpeX3Ab+s//zz3/4xx/95C8OMJF5ToOBIHFgakSzWTLE2XIxT5LzsIiic0zVmdJ6pLx+/XJjCIh2rq/BZZh6lJmb0XkYO2esnO2Gy/C2+DcQv3IenmPUz0McAACqLTwePvJ585k7y8xBDb+KZjj/ITinCtkjpTjfwmgRVC3OBDQ0onPY6HI/MzOjswjizPQvQ5ApGC9VOHQWQ5zTwGZJwnyLOsuvFgwLSgFQQAaPNE0ZhDrrnl6+809/9HFcV9elD1fvbp/G7373/dV6PfT62S9fTqUHqE3niJsDjeNxlGrIUZWlUtsGH4Jp0Tq3UtW+B0PbdkTozUwNpJKo7i7806e7touljlXGpvVN40J0VXKVIlqPp5OqMhO7mTbNtYoYqs65EsE7JCAtXEstRWrJ8y1YFWo1H0oqCZF8Q1sXyJdp0pw0eGhbUOG24xAcISF5nNPkyAxUNR32R+bZKiAGwuiEBGysVVKqOUvXdkjadF6tKlgIgA6mero/6vvvv3N7ez9M4zDlhyMEhq7rXNeSBTIhZQfOmWd1IlizosIqupuL3Xa72nTtx59++tlHd1/+6sHXS4aNaqk4ESJ6mHt7tFqdPUqmCgqMc+aMTNlEScwEZt8ZGuk5fwN0AajsPB8BfAUF4FlR9bgscdFqzatIF2TgN8SIZ5xYvdV0Ok7rUzOd0tffutLG2AfHTlRBQHI9pqndRmRKpdRamNjFJnILE6gDUAbzaM5hlymL1mM/DiXFdkWE4+lUpiyl5mlihXV0aM4q3X/5MJ6m0otl9cE1jbOYk2WDEltw6NE4uqbDxqvX4qceSjKQWJWsohIhoGqdUW6e44bMZNFswgIGGyDBvKsRkZElCzqEWV7pwUUOXWg3sWASK2/6V6UWMiBnRA4cEiAWlTFN1mvSWrPW7FNYdzGEppY8PaR0KrPZU7OpGJqb04Jm3g4RHREbkcK221xud2iUxwxqIhUMmhD7vocMaEDkcU7umueyKkaBkFARVEHRQOcfxpjsLGFY8DrRR43n7LHRxyzAGR6SeR39xlo5I1lASHN234LwPC6W35CwfrXSiOdhHnHOGkNAUDJQIgUlJjsD+XhGVnUpB/uKfZi/qeWUs+W4mw19SxYznuPL/v+93MxgCADNfiBCMBIBIAEkEXCAYKAmqGdZbFm6E7UsEioA8A6RaDEjiQgasUMkMEWix+QuZPbes6epH+Ac1ggzTEGERCJiprXO5iUENTKM7AUEz/8VFK3znyQgR02MTMFm5MxqkWpW55B/JQOdPegGoqKVokcTO9tADIhAZ/X2DAwBogELCc4jPMyQFS5oJM21RQQGCsJAAFiroCcwrVMBlNAENVOpNPciZ5goAYCLPjRRq/anwUCljZJtqllqLhnoCcaLlhx0jVdI9/uH/lSZoQm1VF6v16GoakVSRjvt94q6Xm8d2/5wJIBaxDGJGBh4j4QOjKXCeMoOJgZzTMGF2dcV/GZKYy3lt/7Wv/WLX/xy291c3Ow+++LTv/W3/9VPPv3siy8/DQ5yX2ecl8khMhAiqc3CtTkgydBsDlCbwcElLnB2iJ4f9whqQAsUQkumtDoixywAtugiZ4sdEpIylDEBATpm5xAB0RFX9h7AHEHJVceKdtisGmicDxyDD955WjtnT55vbl+/fPXpfZ3Sult97Z2vpVKhNXLeO89sQFIsFSjCWrAksWJEJemp3B/2sXFtXAjKXMtpTMNUagEDB1pshnjmW7vpLFqdFZ1Tyut1B4S1Si758CUEn84qjfmlMIf7fQXizVU3X+mcHnG/2Y+hhrPhkhGA5s9ZF/0Wms7VnYpIi+wBAIhIRcAMvvI9z7v2fJGcuWub+Rw8yyQNAOQMfM13p9lkDWpEC4k5vzU8kzm6nIjLLiZCIBIUADOpBgSq6hgZcZaPAZqCmMXWmeiMUmexwzh9/vrVz6Lb7FZf/9bXX798U1SIwjffe/vm5vLiYvMnf/5nf/qTj3Wwm0vqQmRiQJemOoikClCh6VxFqYMdy7TJabNeAeGpf8hDWlGDaFUyB2zW0R9cAPfi2dP1+kLExmM+3B77u9JdROCSJ0UFKPNhH1SsaPXkvAvNdp3HaRyO4LS92Diq0zDu74b7i7vNZXex25xOq09eP2waqMXydOi6JnMZhtPt6yySPvv08ybCh9/5g9//3e9/65vf3sTt529e7vv7cTrtrtcP+9d3h/7UP3xxeydQqoFbvyKCNKm5QOCdUyHGWkU0J+hPU9fSpomqxSGCCaLlktLQ5yY0MQTnfPTby52I1SIGUDPk1E8jO6YYg4gM/cMwHoncfj94R9dXFwTYT+Op73OGu7tB8k+f3jy7+fp18GE69tvNxRdfvOyH4fnzd8DzVIoj7xy3bWSmdupibNUkxsgQUq7TMJmIikmtxbQCxKbZbjZts57StD8eBJQRRWRKYz8ec8mIOiUwy2bGLsToveuIMGct+QSo3kfvY2x8rVOuZUrl0I/ThN7LlppPvnhJgGkah+HkHDx/8aTYCn2326yjb8aSTahdxaE/nU4Dol1dXcQYVbUU/fv/6/+d64mpffpkTdyM0yfMSU2JSmzQMaVJypzD6OaJaLlYqhlMcPFUnr118eTZxe6iW12EPI2vXn0em9bsZirDqT+VmkMTY2yMmQWCahYpZayamZaUQufReY7Rr7rGwJzzfX8qpfTDoA20q0CE/TDeP9xPyZq4GseMoKWWcRyHpLMDJsTQNtEH10QAsJJTTSMGcxRAc81TyWKIbRtrLbUkq2BiYMgE3iEROAQfDFFzmqpqKUIMIfi2jaIklgHRANW0lJqzOqel1MEgxhZRVUUERDJA61ww87VqrYYIMbSx3YjBYX8YxzGnBBy9DyJw6E+xXT25ud5u8suXt2/elKWqZU5NUACC4VCBwHdwcdk9fXpzeblzDmuZxv6UhsLrthY7eSXtvIPOOzQa6iyCKN959902EhqNw1ByjiGuuw0DS1YGtgJqRsEjBVHOuegS9okAOI5TMycVNd57nvWkZ5GHVNBTnQ6nQ6kFmVwgIBQtU846Du+tN7R07KiilTIyc9M0kfx8zWXAVdxsAU1RnkM17VM+HI/9qW/WK8boqZGkh4fDq8/fDGPp1lcvXrz31vO327hhjKtm57ElDQA0laLgPAdk9/z6rX15oAHJsH84Tf3oqY4Dt+RNShNjyZCHHgxEaxExMmSIwXtkUcfEpsjoWz+/gTxCduYMhBygMTPPNR9iQoZmplVNrFttreI45qqViCJ4AuhP5ZNfvFK5+tZ33tquLt/cvaqSGZGQ2SoyRIYmsGdjh84BOSAmNBDnIEAFUQS02q642zbmIVPqK7DTrsUQ2bM77Q/r1u2P+XD4yZvbzR/9jd9vu/jRRz978+b1qtu9+962kYBQy6igxceyQu3IcRM40P6YgcFQgMRHuLxaxSaWkk59ur/Nx/7kWGODbRNKyYdT3eC2aRojPPaTj6ta8NSPRMAcCD1RimGFIKfj0K03TAFRDFWtpJxLqY41BCci2127Xq3qzDQ6Co2PjW8aRnTsGSyXWkXBMYCZQpmv9445xpAnUNWci1RzDMGB884vQjCIEWNAUI0RVysXPRJWo+K8OUcxBANQEzBkjLnE0xE+/3Q8HOr2At59S1YNPbtZP7u6gmH1J3/8w8/+KbTDhtb+eJhibIAbZCcCJStRCNHTPCIso8o8gQPOetYFbwL7NVfIo1hqucPPFNj5923WGhgCPUbb0Nm5/ZhzRQDn0qhfR5iQF20CnmXuaDILUGYq6pFzQ11S3ObpeI5fsHPj1ld97jPNDQg4ZyjDuelq/qWAoqHq3GxvOs+Rpoa21G7ToiZQtCXmayY+4FEvcY6xeYQoZvrczrwhGAAwAzHm3oCgSE3DFP06lbq53Nkv4Yd/9ukf/M0PsIaWo6zap09311fx8091nO6LTiFum7YtpY6HUSWTa6sCCge3CS5Ve5BaANAMHQMhMMcQQ87Ze3NRPcL1zfrZs0vnZBwnJFh16xC41tr3U861lHo6mXPATmMMwXsgK2USMZFSK1QsAMouqAIYq0KaMiCzJ0JgpjGdhkGZ4fKqu9x2q7Ubhqnvx7ZZhdimMcdITKjKhEQMzpNBzXnKRU+n1LUxNmE2BTl27JgYGCpkUSmG5jw2QCmhVXMRXABwWRAVMnsLDYYWQoZALoQIxtOYpUzHQ/Uc3LZl7yQZgHgH27V/cnX55PoZqjvdT7df7k9HeLL24JauEhWzChNPTKwESmIGYhVmrYoymJdS0MBk7jJDmk385yu1GoLiwvfjeUkssMQjkvsbmwnOwhY8N2WdQ7LoTECDAUYXSnF1SmWQ0/3x2YsnvY0QnGc/pCFXmaacU76YYJrMEqShYo2BkZ0HBjMopU7jZBgMFIjnIVl73e8Ppno8HWUAMLjexOvN5Xa1iewDuf/5f/jBahsgYLhoVhfrXddKQNaUpXSrLri1lrBpd2tal32eRjkeck4C0BFGldEAAWU2U58lRzNeBLr40IxnNh7nJtG5NI6LZCC0hWwEcMKRm00LCmRuPxzFqidXTomFnA8hNhwpoBdslczHMJ70NGbvbNut85Rffv6Qp+qJJCsU6OIaBWqpuRTTQg5cdOx8hioMzabbXOxGGVMqplCTOKL1djUckwf2wTtyk2CpxQGKqqmhGgGDmSmB2MwIAFPwrGq1VrNzeNU8sCEY0jKM2a+BlgazXgIRmHA5y+bRzXROPCYkw3OvPc1tfgCPZ+l5VS3T6nJeLeFBc3C+LhF+Ssy6gFL41TSr83EIuAAuoKAwpzbbo2KDzkitLSLcGQv4TRDr0bj9z72w+bab/T6GpqDZFmESE7NzjuZ+TiBjLDaNY51EKwTyIYSSF8Oa8845FpBikkEBzQXuVms1SWkskpf36hDc7ANUXIQ587Y660TQHM88NBkAGXAlrJhLKbloUSJyzqmpY8fkAEGq5JxVkMARsWhN0wgIFJAdIYOaGlmIDsymJOE6Ci6OLVskeXOxngCAc44d0ay9IJkTmc7fiEEIsBxDAOw8OSIytVqLmoID9GgMwADOgJU8OO99CBRo0NPlxRUJ9vtjGdKzy2d1rHmaYserVXdxs27akMokVtih9zyW8X5/n0qNYbPZ3oByfxz68cCsbcRqlotNZWLWq4tt0zpEGU59KfnZkysELJOknJqmGQ5Hs3p9ffP8xZVniI1//eXLNKa2XUXfXV89m/rycN/Xiojxe9/+/pdf3v7oj3/6j//sL6HAqtmOfdJswYfgQ85ZTVzrDaSoqBYAIDcjMDMSviB9M/V0jgqY174pqj0SZTRbb0jnVH+Dsw8HwIxdEFvgWGJ0LgAUxYk8AcjlrjMroskz3Fxu3n3xbBXjqm3WTQdsSqPU+qtfvP70V5+T4cXm+u7Nm3eefuN3f/dbp8Ob/+w/+I9fHT999eqzN29e7sf+i/t+PxbwbbfZ7rarw/2rlE6XFxcXVzeHfnx11ydzv/zl3Y8/+tghloze+5pMxGoxLYoAhIyEteS/++9+Mw37P/rwX//ub3/4jSff+Tf/5f/EtxAgALlpSlIEG54hUETUXGfXMCMyuloFZ3/hstEBmdmzKdgiNjx7MMHIyEBhnhkAsFnwr18XCi7CTARYnMjIfq7xVilVREAMKqwv1lK1FtFSVQQexffLFyHAzCEgIaDOYhpZYF9hAANRMCCAAC6yOTI0lQoROZCxEXNoVs5HYio15TRUSQbWNqACXQeXl03XRe+xrdUdT89u4HDmTgAAIABJREFUrr7+9a//23/n7zJRfzyllFbd6q31exnq64c3P/jBn/zDH/zw8z7trm8A+HAaT2M6HKe+z6nWJ08uM+Tf+4Pv7/f7h/1dKn2pQ/DcrVtmTNOYhnG3vXx29dbl5iYdJffln/zoL+/uD1QBhHJWqDOVxahMymaIiiZgYiYWtpuFH0ZVE6mj84oeK2RL8J/+F//efv/m5z//+GH/8skz/+LZDZGoJiIxS++8eOv7v/f993/7fUf+4e5w+/r+mEuv8vL2za8+/ZWh+bZ5dfvm9cMb33BYx3bdtJuu1Pzq5cPhS+uaNSL0fT/1mQhWnX/2dHOx3XgPXfDOc3863j+83G3jO++804QwDP3hsE/TMPbTZr1arVopdRzHEEK33hCFcZpOw/F4HMdJq0BsvJlOoxQFZoqx7YLvAK63l7vt9Yff+eDq6sYmfXN7l1Mepqmo1Frv9w8PD/dQy2bdtbu1MJrjGIJDbig27BxyrbWKKgL6iMSl1mEaP/n0l7kWQ3PRIdqhP94/3E55WK02l5cXVTGn2sTu4vLq6ZNnDw9HmwW5KKUOX778RC0x02kYx0lUIITO+XY4lbv7wzgAMzQNhSYgqfPWtaXrIAZoYrdqL9ar9brdMDkwzFM9HU5pTD6Epmt/54Pv7h/2Dw+H+4fj4dD3/ZSS3u/7Vy+PKZmiOUfjoFaJkUQMQduGLy43q3Xzwffe7/sHkSm07Bz040N/OkLB58/f+ea3vvnf/Lf/0/c++G2t+LA/FcGcRBVSkdMwHE/9zYVTq+xgvVpvtquua8+1tgSIQ99L1fVm03YOENB8Sjqc6jjVWhCBX726PRz2qmV7uX710+n7f+fdi6v2cLx//fqVmlzfrGOMUguihdBKrcf9ScTW6wsxJB+Oh9PLLx+mAdYdbFeddwRQutavO395uX3rxfP1epVSuts/HI4Pp+Ew5X4q+taLm2Hop3FEoKaN23YdgjexXKamCUAypSkE3mwuurYliqUqY2D2ZvSjv/yr2/u7fpht5dA2/vLietWuh36cprTdXF1d3TRNl0o9jelu/3A4HKY0Ghozj+Pp5ubm2dOb3WbFSCVPoEKi03AyrV1kkDr1h6G/LwmaCF9/72u//f77z58/71r/5ac/dQiMrmStSTftdre+fHrz7Gp9PU7T2PdpymDgmrWLrXNetBYpgIie2qadyiBS2ZGa3u7v39zd/uSjn/6zv/zTjz+HZgUU4aEH9NCsoYkABHK2Vf3tP/hdT+76+uLqcus8BXZzDW46nfKp/+Tnv7xY79Ztt7vYrtfrdrVVQ0Am8BVoB1cKDOAImIEdBILGoJvlKBVkSGkciyk6H2LcsHdgpKYmeO2uCPk2v/njv/jj//F/+3v+ir7Yf2ZRV1tfdHKOptQPx3KaqphL2YqiogcKxHG/P4poTllGAwWI0MWujZ13odZ62O/zlNDIRFddt9te1CT7/T6lyWMs+7RoAoCBgRiATHWO+wZgeO+dzR/+jQ92z1zFQz/ux2EPmEMAxPz2u8/u9/ci4mIUtVzFOPjVmp3v+9zvT2akiuxjKbA/HPphqGKlglZ42j1L/bjbrR3rqy+/3G3g9773/c2q+cXPf7Jq/OtXL589fda2XcmSUr24vOmH6XZ/LKYXN9fr7aZaEknVklgFrKBJ9Dgb6VWNiImCKeZch37K2ZhhtdptN5f/7EefXu5u2GFKw1imGcDJqaYChLEkdq6pAkWkapWaAOYKZVWxq8sWzELgGIP3TmqFWlDVzMac+l4NgQOE6IgJHCE5AxQ1qbBr375783A63FfJ7GC7abbbdnfRNg2ZTin1zoN33AZHoEA1BHROSi3TJOMENzfb3cW1GB8Ow8vX9w97Po5htZL33omS+j/84P0VPfnh//X5//O//NVnP6gublbrtZZpHI/oV7YUFBuAzJwUoiKInucLhFm6z7jgQfDIVMPjVQXP4SS01KiHEABARFTkMc13GdDNGvKz/ECX2JWKSEhL/Z8ts4TBHBmv9vhm1Mx7v1CD8wxliAakBgpqgLJIGeYh1xEvae8GZlYLnAVRMwJGyy3XANAIGREQUWnOojexsw4GFdnNYcyzSxxMz0kxgJ69D2BWarJ8JuOR5yAwUEAkZmZHiGpQRWROByZEJq9KqmDVAAo0brtpD9MeHPyH/9H3/vP/8t8v9KuhvhnL9MtP3vz0Z69+8P++HE7o8dK7+LA/3n5xAvDN6kazz6nubnY3z5vD/ctue/rdf+WD//0H/5CdbxpYbanprGltvYlPn18y49D36822FjPTKuOpv3377XdrrcfTaRonYlx1m65bqWDfj+MwHg7H00m96y6frIqklI6OmqG341Fq4VoR0dgpcK4K10/IOZtTI5GoTjXnUoo4jE3TjkMe+unubpoKhBgA4HDMpxGaCJsVfO/Db97dPZxOPRLHGAlZtTgPbQzApiWDs64LOY9FRufQe46Nj010TM7zOIgUBmvShJ9/cri/fUhFtUIWuNzRxUXDDsjKs5snkvPhfv9b7333G++8X0f/X/9X/z2sod20u+2aEHPqi+QqkiYVhLefPG3D6vb1/v7uwWG0orXaql2F0JRpcqBaayl1rhslYwQGQal2jpQkAxMrCmfUZtkPykimqrLUnTETINTHBqevpoBFW/AogCEgbyulTFuJT2HzdvPBv/bdT++/PEzjoeyvr69F86uXdyrw4j24uoImRk3sYG01ng7yoz/9nBw0cUXODynpVNCDaW1b/+1vf/OHP/yr1sOqabarXcCmnOTh9f725RF6AADMQABCAALQwLt/dPnND9+hrpzSXVg1v/zkV2Oi/l43AL/37d+7+2z6yV98fvxk8LBpfTseHgDFoKqhAoAyKbhZWcWEiHMiUM5FVH1wIQYmriVNY2Zd7a4vhMutvYI1fPOPvkZr/OLhC4r43nvvlFKmcaqpIITU59s3dzpXZwTgFaxvLvf9qQzlZr1+7+YpPIx3n4+Hl3L38ggZuHpJ1ln0IeaUgZUDpWkqUv2FL7satqvLi8s2NuPQHx4etIojBoNaSp6KGRCxF4IKlqsWQ0EH3iGnU8UlVAjVQAANKmCefcpLoakux9ms8sQlXBwCYa31Ua7wqC2Y/afLqcJsoFVFqshjnBoBOToH3ZiCQV2W3tzYIyoAQIhETIREHgyq1JqL1oodw6LiOueKL56qxVQJYEwkYkXEyuNpDQDkKcCsATOD2YBlplrgX8CwzH7jdwDAVakIhKiGcFbEGAAKmKrMwzHNbgcFVDAxEDBTrbLob3EuNbNZnBTYzw0RIqImNmuW5hvM45PMjF0wW/oL5/ypBfoAA60CRDS3ZM5Tvc76dEBQVCQGBLUZ5TAinvExQDAyYlJUOCc3Is6xrIwEzhQNCJYWSTQ00KV9Ec5rQMF4kcCQQX0kj+YjxHCO0UMFQINZRqLz05ZxZmto+SYA5uQMU1Ut5phWTRfMYwsr6nhL1sl+f//Fm5f3r+6vnl52mya00USOw6lPfcopNN1mt2ZCI/MNR3Uq4zDmXGo2YAZVeNg/xInbzs9gZ6kVgaqYCGq1zWZX00QANRdBnT9fQBOpkw5qut6u9vvp1evPQ2gmOcbWXb/YPntrffvZ0I8nYu+jU7ExJc9MiNM0kmekOalNl+vD+cyc943O2SG2bCKwx4A41LMc9swKwKPbFc/SI1lERnMpDJmagc29TsyenKtSmSBEFxoXoo9NcM6pCVZDz0S0Xm2fPTWpSOJMwjikLz5/6SlXqOQIyArUYmWUsc9ZqlRGgSoyhwVbFSkiUx76TP0wmQE7Dx6ZfIVqSzSD2hwApgAG9w97zYdhyqmUUcZZTb+seSJgwUXWiqpzzNojv6azW3NmWxZFFJ6ZQDiTc1+pMPXX6MvHPf7PodMLWk2LxmupdT1HsC+bJac8U4vMPPsHzWbrIJ117KRiuOi5BHFOLZgNvWiG8NiJamfInJYy6bk1VurgG+tWXXAezEMqtYr3SNFWXfDeK1gVEHKu2+6LvT72P/zxX7319Onzmycb2Giun736eRtXa/R/9J0P37l+++/9g3/Qrq+GIZexoIfV9VqeQBHJUvJp/PKLz0/9EcnIm2EVDxCUo+9C26zittmt1usQmsn6cUzjsZcRiL2BsSNFOAOFImbzWc2OyDtAl+t80uu5DNW0CFUkB4JgNW+77utvP3nYCrt82u/Vht3Ov/Pinaur3Ye/893Nusvj4fbQ398fH24Pp1pGwlzz7nItQEOaylypnIWMgZts3E+SBbJUStPcymcA3oH34AiDZ2YzA0LcbFZN86LpXPAhldKPY8pZDatAypl5RjJnEzj6JoQmbnfb064/Hvr94QQA7JuLizW7CEiLYvJ4qFrU7HA6dN3manN1Oo0qwCQqWFSjay93KHma43IohNB2RKRT7qcTNZ2PbWAPVsc8Sa0KrGZWiycGqgqzIlytFE/EzWoVG0/Oe99EjmEVQ1srSLFc6pSGGNkFbtu2VKha1dAAxKDUWiWVqo79cSzegaIKZeeJYwByYmmqlms6Dm/8fh85rrr1qm3XzXp3tVOZpYhWy4CUmwavLtr1KuZqqjBO9fSNlKa6P5wMqFQhcwRcaxWpxNC2sWlctSPwiJTRIbKFqLWikjQdMEtsYZp6BF9VajVRFTEz9YRtcD44BHKenKNayvGwxA6qgvcekRE4TSWXUqWMfc1JU9JprGlSqcCOdrstkfmI0p7AKpIa1BB5PgMcGTlUNZMMqo4AtNTaT4mcLzVlVHAM0YNnjIEZab1qL7ZdE2OaklYRrWDatg0x+hw5n1xsWqKm7ZjYMwUXzKzkpAZiyIDsHDmHhPOecaGJvnMcDenhdCdCKloyAMC6IwSYpklFCUBKStMAaqUoCmybrnGcZaUmhio1tF1gKlJ7ZHLOSIwZNt1Oyjjs9/n/Y+zNem3LsjOh0cxmrbX3Pu3tIiLzRmTjLDsLU8gYGYmiBAhEiXrhmXd+DP+DNx4wCAkhISFeoMqqslzYxmlnODIjo7vdOWe3a63ZjDF4mGufeyNtS2zpXuk0++xurjnH+MbXpBOR3F5f9X13e3O12WwE6v3ubpz4+uqWREuRmmaRrMrMES3sjmMa582wXg9UchEKyBEAREGqVagmIGbjfBrncUrzaTw8PGx3p/32eFzffPSPLsX1Tthu01RQXGTvXbVamq0L2Ff3D6D69fZuiL6P/snlxdObm2eXNzlVVLq6ehKdL1nnMYFhKcA+xrBmF5zxQTOCIwUyYAA2AciGYEjMDhBEZM5jLgWSc/lgyNbg3mRXz3sg7gM9fXLxyUe3pUunGi1UdmDVYmRCX1NxGRCMIjuFXDXXlFLZrIdSKzPNNtdiAFBqQrCURhGpUtpwlZgMIM9VpBKhc8GRK5zOphqGwGZGSm3a4RgA4LStv/zFNz+U68snvnOXwjLPW7HiA5syWQQ253oAqnke5yLT3Pek5tCtWshpy+Dput4M55yQK3oc5yOza+jf5nIzDP44jkhyeXWJkr0H0eRcf7G5EIF+WBGjkp3mJDm9eXVSVCMlVmIQKKDJEQA7ZsfsABiBTuM8TXWeTCo4FwpzYurioGaai5oF5lxrqUWWEaczJUKyovM0Z6mmhZlCdDEEJJEqBmq5AhigBnbEzqECYIjoQq4iamZYRdESgFNmZmIXwt3d3fE45lJoqRZqlVQKOoYqU86TKKCB8AoQTbSANepQjPjs+dU8y2F/8H7teQhUu6j9uvMhPzy8+ef/6T/bvz795m+//cs//Wa6H6AjH1ZgoJA5VrVqxt/rjlqtgMQfxqI1FyewFty+0EiWSK3G+UZbcjGWP6Qi7X/7wDW9bYa01OMLNmQLx0kMxB4tPOHsnSIAi/c1tFPcHqd/ZzHWUn+22TQ2o7+zK0zjyQA2IQHzeyrAYnEF8GjOpVYR6LHUWzxdEVujbVoBm7fVmYeGj62E6mIhe2bQWAPGCFoZ1rzvrS7MrAb6ERhAXSAJAm7SqVqrRgpdlw8P+c//9K//nT+4rKnO85FRPvno5gcvD998mV5/dx8cd12/eRIOd7lMJ/SX4EKtOp7SXPNljF3X92F9GMeUtV+5zWZ9fet8tCrHKuY8I5hzdDqVcczjpMf9XKtMU8qlECHhJNUQWaos3TKpc65mm6YyJeuiEnlGroZasdakkMkDMFxd3kgtCAQaCF10SM1auEKa6HTQaYKccE5Waw2Bg4PLFXQdbC7Wv/7163lOotJ3vXfN2h0JUZUBqgCT1VoECQMHIiMGAFWtSnw4TKaOgAjAAa16D1eXOeVU8jgXQ0UPq1WPQvvdt9fr29/50c9uL55//cWbX/75K3gGXoIU3O8ng0lAkAAJ3EAduanMcy5KMqz6mq0IOM9iklIyMQAxlcaxQlo8BFUW/+Wz1rRxLPRx/X2vxP/+d/C3fvzBpfjhFw4hqWpWmTXNWZOCQM3VBGsp5KEbCMFWPXlHUKlmrZKtQMkQBjCBVE6SAaQNVggI+iHUmoFgiHE9rB24cXe6/+6Q9gULGwEmwGqtMVAWAJv3Ne3rquvSiKlMDEPnm7rxdP/wkEsARAidZjgdjgQKVgHOvYm5Zt0uKrlUEBOsiEBMxKwoRYtANVIMBGoPx/saq78Oq6ddyklnWa1X64t1LXb/dnvYnhgYqJRZtAAWAAB2ELiTJtAiyKXOU16R67ruQQ/ggZi8eLKapjzPWbUM3cAdExBMUHLhy14jJhSUlGqZU3Vi4BnESIiRVc2qmQIJWLUlqsG0CeMB0BCNEA0bg07Pfjtt02z772+RkuzMEHmkM9gZebfzDmnQ1KzN9OfMzyNo7qxtq9RFRfV4Z1vYYYi2CAMJUJp1DftlGZz3VNO2/QIgKLf+XRUQW3f1yKI9/6/LN5eyoZEz9L2S/INX93cXtzu3yfZ4OAAALCryFiZrpkDoEKD5mZuZ6rL/NuRCVLC9wQTM7DwjQa5FtBIhIwnqeyEeAJh550BNcWFVLmQdBAOrpqSL1rLpgxVBERVbOC8So7ZKzcys2YiA6Dkz0DUxFRqaIiAhM5J3jknQanvTFmBgQdOaDP/MaVskptSEIu+NxpuqqoE2y0dpYA32g3OEiRmAnrMiERFBwEx0s96gGBBerC4vu8t337w97PcmejhMx4MdjymVd12McR1chH7Dq2EdhlC15DwiZTMnpuRNAUrVogCMziOY5WrkZO2CIkGBXItVywlyzirlk+cfTQamNk8ZqfbRO+c0AADM8zTn+enTp6+/OX735n6zhv3hbtVdf/LyyfH0sqYv7746ca+OuKZaUw2+Q0TIRRmZ6FF/9mh4tAymbHlfEUAJmtOBfm8+AGaLiwE+LmhruaEApiANwiVENFMVUhDHLcqKmalWQ0TmFoaIgFilSq1gmk/loxefDC+fbYb9cZ88xov+NgboYrjYbBQslzLNaXc8PIzH3f6wO2XBqaiUOl2tOqlWynw8bneH0257f8o0nnIVsABNGKmg1thh7fWQIaIxzNNkNUtVAMg5Q/MzFmjgLNBjOgY02HxhWZoZqiqcXfgQcUkCbfphbYj0Yw143oYa7fi8gr93e5QNfvi9x+t/ETwTAGKeMzE7dsxMCKV8gCkiLUk5DewnYF4uXrKzLrLpq+mDw/M8Nj2TKwHQpJQ0jggiVh1TF5lQCBWREV2L/JwAZrG95Jj0T/7irz+6ffvTH3766ccfX/aDQTrsjlB0M2x+/+e/FzZPd2X64ldfmuTt/lCkyefgcEiS6v3rVylP1zdXq/UqVMs1mYpkBFER6y57QiopH/fHw/44JTGBArrEbS+TVQMQQIQmqiEmB8y+HNv+rWYCIMDAnn0AZjtMevfu7WbdX16uyV36YE9unz59evv0yfr6tusHArP77e7+3Xa325cs05yTmXZhzhkRRPJxPNSaY/AViyMm5Okw39+dDofsiEyLmXWB4yZcXw6b1XB5sRr6UGsuaZ5TBRUkVOHDKU/jdNyPJWdEePL0KaF5R00cT+yqGZSK0DiTSOi62DHHELvYDeybBIY984nJoyPG+/uHLqye3b4g5xRwnKZxHKuqmhI7cE6tljQTGQQm5JKSTFMk7ptJO0GVmnJRA3K8bM/etwmEiBDgqlvFPq6GVehiAUDyqng47O/vt9uHQ0pzKfPV9frqZs3MolRTVa1ny/CiYogce1YtbZ8mUucweHQeFVCrqoipEOaJxlrEVPpu1XUeDUupJU9lnrQUAumi6zrfcBhVFMVU5PXrd6UoKIgoWOMAKDP6wCFyleSCGAgzoLPAhkDYh8urnliJ4O27B1A/JxFFBGbHIfhh6G9og5a8Yx+YGUvJp9NYagUAQhqGzWoVkdkMx2PaHw7bh1OthuDSXE8nKwLXl13Xha7vYqRnL8aLzXoY4v1D8R5i7FoYExFU0ZYS6TwCUJEcuxUzmfqryw6MLlb90McuOMd0cTFcXW5M6jyetnk2VHaEjpAJmQCI2RE7RmQiU8mp5lzSPFWpSQRQGlkpZWCXHUUf+z4iQilVNv0zWvHYT7uHY87VETNwF/u4Cq2AIII8j7lYI4IyALfm1eTJsxvVCprncXaEfQzMLjAzyJym7fYeoVxfbq6u1qtVv16vkGwcDylPXQhute586PtVcJsjn0rSw2G8WNX10NHAoesIkdhXc6JOwRAVyFSg1jLl43E+Puzu7x7udvvd/ngomtVDd7nedIE8J02YfNHCjoABClQpVgUM7ndHFDVRVQuO90+O93e7u8397Xo9uECum6YUKYBFhEjYqbiUNOdcK1xdXJgQAoOxIRtwrXKctymXlHLOeUzTaZ7mOYmqICAxESMTZPi4vx76jnu3GcLFRZ89rVOvQdCpTXXZoq2NSQ2paRcklzonWHtGBB8ZMdTSuB+WSpaqpgYK6AgEELDUeqxHFdVStaVlPwoYAMwUBIwMENVABQFsu52m/NV+3D//+OIHL5+u4pPO9VUOpRzSaNOkRdUXFbDdLm2PORVhFhXQauyIGLvOD6v+anOx6vLD9n63382jMpTobcxjLgBoqZZvvnt1c7H55MUNQfXeBceb9eby8rpWy0VPp/G4nw5jKnKa6lEByGHomBzUWqXWQOw9xIDetwR3nEbKOUh2ZiDKk0Iej30cVKtoJgIXPKDWYlIBiYN3BCzVVMtSFyqoKmJlhECoImaKZsCVzXXRO/Zk1cxcQPRYaq1qqSkJEYiUl3GE7U8PpSiShQghoPcKVKqACIuUKuAYHAVHHQFVnWopgBAjh+iJnJkgUhdjKaSlzKepX9XbmyuPP3u6/snn/+rP/uZfbb/4fx7GvXPuip1WnarOyGDLIGcpJ2zJ51l8aB5bDjoH3L+XlCDYh2E1iGho1ITCStDMQ+xxzI4f3gDOzVZ9fAgDqHruvj4A1GyJkoImkIEP2iB7T9fC908CUaGNW5eyrFUvS1Y88W8jAwu48P6vLn31Bw/VwAUT+0A2icuM8mxJau31ypKD05Cus/uGmZmqtEpkcR8Farmo5wa2OTOQmdQigJQSfP7Lb09//Pb3/t3/JrrrGmA90Hq9+tGn2cpuHh/mWZBq33PpHKmVeoSKRfqUyYXaDStmqAkkA3ewHvont7dPbjt0eZy2qup8KGlWpf3Dcbvfzwmin0SkSgMnzCTPXLwPDQpTNYCiiiXPh/10GGG1Sl0AdiFqsGoll1ohEnUR2PqSTcTqLN4TAqlQHiFnBZB5ItShC8ERsXfekQQxqz5gF+Kvf/2aCIIHCGAKqqIgqlpK23gqktZaiJRY2aEqSJVazHne709Dt+q6gYkhuMvL1TD0JdfTeBjmUz+426eri/UQabV9LS8/+vTp9WfTA/3Nn/+bf/uvf+XFWzW1XKqaaYjkHIsJkXMccxIpeQirsOpGnSSrZ6eiqYyMBCCLYova3B4X6xBqTScuhMC/r2lfFGTnHzXW59JovL++/u79loVmCiY2zyCnnFLbmiyECAhg1MUwDG6zDjFYnUxyqblqxjxB55FiR+RFLZcsJkAQg7+4WHnvPvvo2cVq48Ht747H7Xh8myABOw9CkjMaW7vaQK3afnd4uN+HzbUknU4nREZFqzUn2O52N/0PQwzsZytqIGgARgZmSgAMCmaoCE2cSdTC/cDIGsoiIAiAhObNB5fKNFyG+DSun/SnfARnm9W6j/1+tz8+jPNd9QHMzSIWgKqpVpAKjng6JTODAqd5ftA9h9WwWb/4dD3rb9K7PKcRAEIfiTGlMpYRDMDB5sWwfnZxH0YjUK2CaGaemExBrKQqVXBJGlVTE0FTbPSgMzkAUBHO4XrNE7qhVWe62Rkzt7Nt+fkzl7OVX/vaHnlOZxx+2d8aZQRwUWkjAAIjqlrRR5uaZXktz0rPNkAAj18CABIhMizb/we2UI0OtGS9LSeB2Ydb5PIqVBQAccknA1RcNum/p7s9v7LzUnfM2Bw4gJomt7XltHA32nuI0J6joCMUQ4GGYJeKhMDQbHURoZGtwTemXAVQ7wMRgKGZGAEtxlbGSIBGhLoAPrb4e7XtGZodmikhEIgDUQAEQSBSRLRGNFZDMCAHyMYmqIsbePvkUNtwqJHngInB1bMJUHsDdOFKtUoOVRVbIXi2Blq08G16Ivq4BBDBTNEQFAib2yQtn/ZyHzRCJQQwNWWkdMqAE0YS0rs3D/ffPoAAeEAEUhh39VAq8MldwMsf314/2Zgv++P2NO5c6FOziyNijwGJvIoZIogaEnhPPngEEC1GUK1mgVS0VlUDUdOqPGck0UvwoWPWmksupzxPzpPzPBfAE3z76svnt7UfLn/w8tl4PN39+lRKNVRRA9JcZmSi0LTQy0HLzKqgzVnZztDgIhCF9oE0mA+pkaoMVJt35dkOakEJm2G5qQHKGQ9ckBfDCsiwWJJbrcJkAFBVq9QitapaFTAU4XlmLbB7SLv7w9WFI/ZMuFpvfvSjjxXgeDo+7LZ32/vtfDrMp6mEKVhlAAAgAElEQVQCeRMQAw29N8Fa8/FUx9Mx57EUryKIIFJzMQ+gulhFtUXDTERsvpyrOGLiaZ7a1SUqZzwcTEXx/YXX5o5m9hhB/Vug02KABya/hUN/+Mv/0NAF/q5mGBcBY2MSIgBgzbkBcC0/gUjMUG2xMlsCI7UioiEhAAMZglELnzBcDFgfd7o2KQCrqsuYkZDQtE6nBCrAMKx9FyOy5jzOU2WuzpNIzkWTSox+o/jw1de//NWXv/ibX//B7/38Z59+9uOPP5n0eDxsrewB+Mc/fHGsaRPd08uLtw+7L7/+9s393X58yOMYAszHSg7WMVxtBp/0NAkZohgKoaGm+nDazft3r768S2OtE4C21CI776znQWfLNAZVFEFGAJNK5AkNUJA1RIeoiNl7gBO8/vYb98mzTz/95NPPnqwu+NmLm5ubi9UQSxkPp+1vfvPrh4ft3d29AV2sr/zQTfP07v5tFemG3ojYwcXlqtdVUfUxOAySkmaJjMPQIwAh9DFcXKyfPbldDV3wDkxK8eI55zxNqc6l1OqYc57nLKDEBE+ePlcpiGAiU4qOiNiZgpqO07x92KVUiZkCgLEn7yiy8+x8593gX9SUiNx+HP3d3Wef1gZgHY7jdrdldsxkaASKjNUkTaex5uADqTFC1ZJyEpMstZRUSjE1b56cC44CIjLnWlQkcvDeby43w2qFno8lVYX99vDm9dvt9jSOKedqBqkmCsZO1VAUiKDzCOYAvJkzI0T3bD+TgxA5ds557HsXIooWFTAyxgV6yVKOp5PzD6Vm75wJlDzP01jKXKqCIVJRYEM2IwBmwOAAzVS05NGsOhdC4NjFEF3wfPfw4J0iKZIgCZIFdtEPq3UAlPUK3r6a5nFqGa7B9SG6jrnrwnrVp2nfRR+CVxWppRbJWR1j7LvgOwIn1XIux/283U7brRJhDIzAhGkVXU55t9ubDf1w+ZOfvnz20VPfCb8C523oPYAhSTsOBY0JXQyVaUpTP5wnEAZMuO5dF/0Quxj81WZ1sVnP43Q8HPb7nVgNMXBwYjrlfJpGVQRAZbBqKeXj7jSnuUhVFaIZyUSAGMa5IgFa8GFg2uUkp+PpcnN7eXGpF9Lx3eF46HxkdJ0PfdchYs5SSk5zkooGlHMe8ynVmR2Sx+Av5ymn6Vhz9g7ZVuBczjKfxvF0QMy31zfPnlz3fTDVcTo0kyWoeBw170cG2qwuri6vNxe3jC5Q9KFfdRdiFQ1Ei5nNU861OsfoOERGZRZ69/ZhTKf7/eHdbrvfb1Mt6IG8M1JAYWrmHCrWgnms5lTmlHM1hQwafUCzlKcxgcp+u+3m6+fuY4e923Trw35S0pC17+Oqv1agXFUqiWIpqtI47woqZLWInNI4p3m3293f349pFrBxHE/TmGoidsMwrNbrSOHtuy+fPn226S9Ep2k+kMMYvHryPVcpp3Qax1lUqU3ltEoBrQYGxLDbH73nEEM/BDPLOdcMqQXuGLjgHTlQlFJLrSUXqMu4ItsZwFqQAF1abwRQEADnnVodT/CbX+0O+9lb//Kzpze316Vu77YmxaWE++OsWBXc7pR2pzLmOqfTNAMUAAddgOtNvL21+GIdiCN3bEcRHTaOCMd8kCIxgBkfknjyLvghrl9+8jLN0zyNOVdRyDkfjvu7u/1xnASBHYgBOBBBYMsZ8gQ1iWNwbvLOmWGtAAZEzOxDCGZuyprz/PTJOouAKTPHyMxepOQizOgdgIKJmYrzTICzTrVASUqQCbAUcwjowTijMps6IhEtkqsqovno2LBp3pDZxcDsqkjJqYoYgvPgOvAe2BtzBTQDR2idx6Hrhm6IvkcgZKsCZsWA2PvdbhdCv16tgw/j8ZTnCWW+iPHj26sfvvid/+t/++tf/Nn93/7lbtz3KE3mNptOVYUQDBsk2Vjh8jjaPw/98ZyP1nwjzt1Uw3uW0v7s1Iug585MEVTPWNgCLAEtk+QFhUKAVqQjKAATml9CVt73ZgtSps1CavE0xmXlNqq/LTHyZ667EYIpNQY6AOgj+2VpEH6bCHBe4WcIb5nfvk+Aa8H356ZhGYYvfIlz3peBiep51N2aB1ossszMFhscBQAjarYc1LZrOc8oiRCQxGoVIaQq7usvD198Dq//2/HpRzfxYphmq0Y31+vyQxfC6vXr+/v7g6LzG6tzNSiAIJpTpuFSfUTVksrx2e3F8xebH3x2fXUdYlSxQgDee2La329L1dOhjEdIGY77UqQgADlA0GMpxDAMwOS7nn3grkNV3+bN2Iaaap44dN4TE1quNPR+dclSDmqjmoGhVFYFqZaLlmLOcddx368BhpzIICJorkkkIRoobHok54PnLgQClFwqVCBRFTMlEnZAGRC1Zcj6gM5hrUilTiMEBwjEzGg4rCMhSS1uP601Xl32FxeddzYQr+3qpz/8STr0v/ybr//q3/4qnxhSaQYaTYfAFB15ySmnYq7F3gMFduQasw7RQEVqQWYDWXw+ztQNUDBSIzNVBUBrApfvBZS32wcC2fO1hd+r+f/OAPu8MBcWo6FCLSAnyCUTct/3696hg9O8Z6bLi6uhj2RFLJtCzVImybMRuPUwdMOgCHOe53kClBh97BwxfvrpD5z5h1fb/dvDuJ2gAAGzBi0G2bpVX0qxZX/QNMH9232/8UiuTOaiz2PJc50THMfTzz59+u0XW6l7VB+HLh2PDAQKaATGpqSAoIbkHDkiNFJjUykKCtxG0YCgxlB4hsFWHw284YzpmPYhhDT7muX+zTbNBQSsWPSRIznAQvM4ZZCW9QLO2ICtSppKIYudX135px89Tf0ko5WplCmzc8Oq77s+9B4DhMHHq+F4SEXFrJoSI0bvAVWzajHJioBEzMoqoGKoYAvt06DhQmSLUql5mjVYp3XYhAsbhBCWaIqF8rzsRfa9T/zxq3O919QlS392JuT8vevlvDE97oFogEZMAKYmuLRNJqbeu/MJ8NjZNjhElwVtioSP6Gz711zvxSoaN1ec8076D0JXHy5vInJE9AhgkakSnQV92FR8YEAArESIjITEbZs1MBV7PFga+gimJo5FAExE2l9FRhNQWBiybfYPok1wR4CNFreAFYTtJUh7D5DNNVcIp1jNQAkE2v6mqNaC05EVGryLQExqjYWLLWoTQaWFhTxe6u1yN1tIW7bIRM1MRJmJEM1QGlBDAGYMJPKeRrQAFkbvPZ8QG9q6vPmLLT0KAoAd3xyHISZLp7fjndxv3+4gAxJSJTVRBe4cE4jVOsH9u0MYaH3luug4rKY5T2meZ3AM3gEgeO9XfSillJIdQd8H5xwziUTvPQB4g6rVEeyPxzJn55EZEUutCoDOOa1Sa5nTOE0njvXpEygJ3r771rH/+Fn3/MUV4U/+4hdf1snqKITgI1sxBXXBqaGqqMo54e4xLLNBfeeQzIaU0EJ/bqSh5dpTMDZ4PPMVFmO3BcFFA0VpbzCQAbKZacmFGZBIVZkX4VsRybWgKogyhqfPP/3u2+2v/vqrr778bjzUwUfJ8OJF+A//6OdXf/hkknIcp+3xuJ+OsxQgCj27uOo2/TCsDqd9mY9N4zfPCUCQHDkIHgA1VyAujyTFRkryzjnnEB6fNyLi6XgCAZEzRNeSRVWRv8ejAlABQLFWqLW67gzZvZ8WtuX2eLfzLoG/tT093r5/x0UJf7Z0B+QWuwMAWDmfHdkNAYgYEdsgFBuYCGaqhoQkBL79CTUlBEFtzwrfj16Xj53QEJyCIKKVao2PTwAAtcg0p+fPbvaqImkcE4ClXBOYRL8JYZctQ78ft8fTt7EbarUnN0/7ftjc4NvvXn/+q1998uNPb548/b0fv/zdn/7o3f3uT/70z/7yr+fXr7+uCqRweAPDFZCozVmnjHMNwXVd73z0HL11+93x7de7b768dwRQgJBVaKENghARExmJKi6yaRNUEavBkSMU01QyFCvN6N0DGECCw+ntxeaHP/vZZ5/99KO+94EQQGY47ra77169Ok7zKU+TVDCEPNk076fjmEd2gePa+5BqqfN4sV65ENEFBUR10a+i9/evXxMgM62G4eJi3fceUI/HvWoloiF45xhANaJj55i7uFkN2UAApGRbYtRQnIBzFEIAIwQCczs41JqguuN+XG/09ubZ5eW1KUzTvN8fbq7XpdS51jyXWt7dbXcxdH1f2DkDUFMQqFJDoBg9gEtpnFNCxCF2Ac0Ack4iVUxtSXUVBucAIjN5Zu9xgpJzYB9CjBw8sAlO85RF7u/vv3v9Zr8D76EKIMKU5jmlnrzzMcRCLMzkXMcUgLwKguGLj9dqgozMaCDEQsyGTkSb5ySZiWkuZZqnlPO43mzW667rkAGsogmBqoGUkgVFoIoCOWaPkJnMtDIXg8rOfIgxivNELEQ5BGbPqrVKQTB27CMaFJH6ycefbu++3M6ABMwuicwpzym3g8mdibuqIlVUhAC62K/Xmz6uqtjpeHp42O8PeZxrzeC9QwjMGCP2fTwed7tDJtLr29UPfvDR5ToWOPSDw5mRVLWYIjn23ggMgLxzqo7IYnRtrERGnn0XmVHAikMHBlIWd0tEFJUxTZpRzYpKKVCriVQAkyrzPI6n41TEoHkWm2PgAERcVDWLGVKe8zzudum4r5994m8vn15crQN10+XI2DKqIE1zLllFmdgT5jznLFMeT9NBTOIQehesTFYmLZPJBERs3iMIZMK0GdzF1eXVehUDOobWD7N3RDzmeTyM++kQsbNn3dMnm+cvPl77NRiB6e50OOz269UKwU6n0+kootyvhtXFEGMHAFr1eDrMmotlY4NARCBspc65Zkg8bAZiZkJquXVIxVEkLqWA4WlKcdUxUohspQBoLvKw3WqqN+vLf/ZH/1GtMO1OQMHFlQ/rJJrSlEtVoTd392bOlMgYjQnIeVpt4rAJ3SZwsPvdw1QShkid8ihIMGxofcEr33336su+53BJ28Pdt19/GW+GySa/6YgCc9B6lErE3AUnFeqcVY0QQqBI7vVdJqqqZI6WohWN2YFHU3XeO3bY2mrAaqZQQGwZ7DGSESBZc2RQXEY4imaE5AJ7USlzfXhVv4B3DH4zfPL0+Q+vbq6nshuT7fflME4KmiuVzNNRcl16e5hgnmCviWkawrHvfOe7ly8+ocCvtm/FbK4yC7ABB1yt1rdPrkQ5FfHdquR6f3/Y7r4Go6ub674fVqtS6kSO2A+GSwhQLZVU+xDRdfOc05RnMxGpxU5HUCvrVd1suO87MKhFahVCQGZHQGQhuNUQVUcwQgKz2sojxBZ/s5zRTROKDMFBH6GLITCRCaiIlnGeSpHQ+cCBHHkhQHLBxS4g0TxLsbwYV7TKgY0Y2GHskBlA2bkQY08UpAKxOReRDVCZyTnqeu/IAcjpeDjtDqsY1oM+f7J+Mly+2Pzgv/sf/wc/387HbhWDZZ3SUSQhZUAQAcR6LjO+V28sTwWgcZEWaHypnc+41fux/vm3F245oi0A1lJOtulsw7BMsUWSAyw15LkZax5Yukz6PyiBzkNDVNAPCi778JfOngdICEqICrT0Y8tMWxvE9tsVVnvcD4kOrZ4Fe0+xN0AgfUSvzk7CYADU+jMzkbPbfctafG/TZaBArkUntqYWCRdKgSkQmRlQa2AJUEEFiNghlzzDQ/03//KXf/RPf/bRp1fRb/N48KzPnq+vn9xurvyvv0j3u+wivBon8AAMcoTTCP3aA4/zdHj5w5sXH3/8ySfXqw3nup3Gg1rOKQ3DYCK15FokeL3c+HEW77tSmqdEy/QwQPBOVKgWNHNEpooGGLxtNsAEqpnAOedd74miCMUurgeU+h2hsm+satC8mOSogWjBJUAeCIKIVa1gTQcCZPbs6bMWPwZAIlqsmAoAzHMR0RAwILc2v4WJO+edi0hWa1YFUzQjFTFQYmQitTmE4hyvV2h2nE/ZBK79dVD3xefvfvEnXx1/Df5iVcoePTABMdWKNSMiqlBNWtMcfefISRVRlSqqWjWDApOZVThHdjfXWQVtsEVzwgVrqAb8vZ38ey3FIwlLW77S91ap/Z2lC4BSBYGQAKxCBilCnnwIse/mPE7z1EUffYfmazKtBlUk2zzVNGUm9uwdoYDEQN51igXQas2Hw35zu94/7L/98s3rr/eQAI1IvRXQDCAucCctfd25AjPWcn93uLq+WD3psAZyvo5TmrMkuId6eXkRogPLpkZd3657RAZlMDTkZhHUcF0DFWlGBwIOoAm+rbU0UFzePF+vnveFyrHMLvoQ4jzNJdVpTiuM2DGj8+yJwBO7tmtjsWRNvMlKnpggaKU5lyyp34TYe0smo+Ypm5jzfHFxgR6LzKnMu8PDsOpP0wRVpBatWkuBYlgJpDkHNj0lmSpq24ga7+gM4oCePXja1nEOeG0jgrMD0vKts6PUhzsSIBCRmS4WfojUiKnnJYQLAQrPcjs7t2+oZwUgWmOmghkaGiGxY2qwl6qInC0O22O1TdFUW6RHU6aZqjXHLoOF2NA62A93UEA9k1jbI+u5wf37lv0jGAfgRAVACAmg4TUKrbC1RjFnRKAz7ISCKAbNQUwrELAjZFQUa/wOJodEanLe0Be9+weteetntNSz1bc1JON8VJgxtjOsWkUCYiZGJAY2KFq1ArGSAttZ3idGZAwK2s4CsPaWLQ2+iGUtJlqqkF/EmnZ+33SZlGDzSqMzc+8s83q/JM73OWeYwPkqalbZxAAquBQWRETMQEQoBohKPa802f3dFu6Be0/egaIZQs1mSj5ycOAtybTb5e7d1oW+u3AxuGcfPeVv3+52J6bovXfEzdN1GKKI1DwBNi8YmHNlzy44ZCDHnsP27oEABxxKVTVJqYokH1zROpd6yse392/6lfvBD25fvdoeDvNmvZvT6fLJ5Wc//sF//V/9x198/s0Xn3817gsjVVBrrcuZ2W0GWhuEyWDaEqOQFJEWGT8iWLNYM1AibGnDFcxICPlMuDMAAVqwV2MiMV1KBAVkQrQqUsYRIfg4sOfYsXPODHLOjoDUGKAf+l/81VfffPX2uy/faZHY+ej8u93+3eupFHMcv3v35jCecpVqop4YfUDvuyEOXRj826+2KAVVDCjXKrWqeXQYew8Ifi7snKoSmqotnt/UShLUdlAjEeGc5gUSBTBbjAaLSOO0NxB1IfwoqAF7XCh7AK2GElC1D4J0YaG1tUIHlmCBf1D2/hhf2j4jYlQ1A+Qzf72h+qEPjekvqg3Aak+i1ioqzMiICqiqJmAsuLCdTRryy41i1ZS9y66ADmOM7HhOueYCCODBew8g7Qyfxmzg+25j1o9p3B/mkgAcwrHcH04Pu189W1/Os+oEn/+fn//fw+d/+Vd/9Ud/8If/5Oc//+Hv/+7Hv/Py7tWr48OrN69+Y4A3T5/9i//8n/6L/+I/uTvsvnv9+t324X/+X/6nlDCYXaqPtjkps/hQAmlw1Q/9epwTHJUmGGJMtQK4YswtA64d6lqXEepZ1N2ArFI09LWLtCFHTH3nL667f+8P/tHP//HvvPjo+uVnHyGrgY759O2777777ut3d29FMzgTlSnNgDhcX8bY98O6FnXTcAHFe9cNK0BSgvHN9PBwH+KA5Lb74zhmBHbMoEVRCQOBgZTT6VRrmcaTSmWiMXoiQqCcay2TqDjnvGcDrTUFLz6wAKS57PdHz9j3ffBexUT0+ubZ5dULMPS+Q+T9w/Tmu3tiur558uTJs1evv57naT7Nmm08nC7XNz//2T++ubn56NkLMjwejkmKI0YCIhe8C4SsJYTgmAMRiZlVM0NC74iMQSwyksPA6L2LXWQ1VHWACGzFZk1iUvI8aZ3nIgLOw9OnUVUNzHsGMCKKMTiH0wyIFmMXQ4fIKcs0pWfPL0upqrVqSaUgFQNQwKpYqwlAtUpnq5OiFRi7VVyv1x1jOo1k1s4ZQaDa9svquXeOvTPvAcD1Q2dQDcg7dh4Rq6gOq7haBWIYJ8mnUVSMLM3TzvZd9C9f/vi7r+e7N69rIRXSluvnBAAdY++NVLVWqSLFHEVH0Pk+8hD9EJlGqIeHfL+vRC44z+xqQQRl5pSS9+Qj9IM3zMPgT+Nurg+XF7EPejjsS6kUPVBwzMETIIYQmF0M7mF7bwgliQiQr9kkOO87HwJLzdvtbKoo2vWdFTkex1SLIiJ74nA4zqWUli1pYALEDhSaCQWwoxAcEzEzKCIGU85pLHUygFffHD55nnhzvR42q34As3meai61FCjqCB1DLdJ7XIcOXJ91LVpjH1brKJKHgB1HQtcFf7neDF3fxw7NCM1qKTXXkuYpAZECTIc55VpVUfiT20833cWLFx9dXz1j6nI1BADB42m+3+5Tqoh63B9rAeJgpBxAsBzT8eG43R3vwWMc3G13PaSwPW5TnquYY4+MHSOxeWJmH72PzqtWHSqoGhINF4I0TeN8OpAZI6TT/PDu3btX23err//5f/ZffvRRSJfTenXpff9mv3/Y7fbH05zqlCqjJ/LBdSHELnSd73Qqrx+OXd+tN5sf/ezlj+nTXPO7u7uH3f1uv8s1ERLANM0JU811FskpTXfvtjDuMtbh+mJdda5KtoouGELVAqpoADWBgXMOnb9YSxVLqeQsYFhr1dY5EBqSmYkqARgTc2iBeqVkEGAknWorJlu2CyqqmooJkQGgekCEgigeCrz66n487tM8/pM//MnLnz6PpcvG94e5HuckosbOrzbrUGqrKCCnCUGILCU5HE5ocbOKVxd9f9nffvosS5lPk6S8GdafPHtxs7k4PRy/+Pxvtm/fjPsc2G0f0us3b6pqN6yeP3t+eXF5fzf4rnv15q0ipgKp5DkpMzIFyX7apcNRRGDRECjUYu+O9bTdrtdl6AdizFPpBmTnxWZJyl5jJKR+ntWkWK2gzFgXeg8CO3AILkAMfr0Kqz4MQ3CEINKkT8hmoHou4huUQ2QASmjeoXmoAYcBpIL30A3QdbDuaFj5GL1mFQEDzknHw6GU0vfd5dXgIyH70EMcwk1/8fbN/cO7oxbnKH72w09+8vLlR0+f/cW//s1//8d//PAvAWRLq0vP1bSATYBCzIt6RRWg2VQ1ipWhPbKP6H0Jcu6V7IzXICzE78Y/WgAsQgDjNgA1/QADaoXQYtZABkmZzM4rq4VoNduJVhc1hOI8fgOAxVbFwAD8Yzw2np8Svud2KSChIpEhGLSALgRqY+mU0m+VWYht2gpgi5rvXJbBGYsDIAUwdIxLDFT7bSNtzR6YgUh76IXisAwSF6NhIEJVhKXFYWbfZodISPBodCPMBOi0gApSiAEprff/+//6Z6thvbn43XW8BYTDajtX2R7vu9Xp937/+Wp9ixZTwi/+9rtXr+9yzr7T/+Df/4NPf/Jic3nx8cuXIYRUdt9+86tvv/scGC6v4Pb2igzSPG/6VXYVBicUjmNZrS7IMQAzu1o0BF+l9H3X94OpmkyOiAP2Ea4ub53TUvNxd9rtjmYSo8VIKkRU0YBtICvMzpMDIpaEKopSTSThPOq0H2ud9odcMhhADLBaUT/0zsPN7bVqNVORalIIMhCroRYrGTwBB++AEazWWapQ8IE6NZnnHJlNMaVUuJoZG6iWlEbHtYsB7ChpRrEIcaDub//8yz/5P379//75W6hrHYP3F0pHbqZVCmXCUoUdMvWmQuCZ3HSacypkIKXWCtFzcJxLBQRBYEQDhMZVaZEIi33zsmDw3Hr+1s1gsZKDR/HA/48bAtSq5NF5FldVQdVUoeRcrB7GwzyVzgcRmA4ljUWr5URphGmfpqkOA5mJailSFAsRAmgpGRn2+z2M9upXr6Z7gAwoiIm0Gog5CBiiiACY95F7DwKl1nowTN5DBxm7YcAy1WkCgTKBkoWeh5vVuE1z2SMDGKASGIIiGxoaGpiqVANUIEMA9AwOwKmRGhp7tADhid88X8HKas3V6mq9AtAyawB/c3tzup+k1OhDPqQiKcYQOz/EIVu1CtMpMdEQhs2wWfno0E1Tfrt9l3JKO4EJIMBVv7m+uYohAulYpjGdSknZ8mb1XKtIyiJVZknHGTI4oIAxhk6KSq1ttgsAzS/p3C4vFhUL3LCwG95DNgaGfA6pNFh8pRvgbsuOCg3oIWw2lAtORQRw5pY2+OIRcUdYTJkQGJmRAaAuRw8tT0kViJC5+dvIIzqyIERsSzu7ZF+aKaii0eIb3PgaLXV2WY3LzsrLc7DzK7V/gJvx4SZ8BrDscc6gC6a3zDPwzNqABSlejhSwcyQiOEfEjK4pDQUYiblJMtHMMdGZTqZ6hgitDZtV2iZNhGhkUBtiRktM2/khbQlhZCZwzXkLkUQNCZGWoB9AMFJtfFpUPlOVlwDalq5mVq3N4XF5EsvnCnxWC9rjiWaGCsK2vHZsqZwtQWHRJgOcMSwCRiQiAGQk/JDzicvdTeD65nrtV+M8kYACeAw1S02ZfDCgEHsyynMlQwX0Cs5F56KqlHHyvk9TLkmAK5kTqIQSIscYHEISqFVqmZAsl8rMIThm8sF75x/mybNJVAMy0zklRMECtQoiq8p+v3/x/KOLi5tvvrnPBU6n42k8TXmMRD/66UsVHPf5b09fT/tiBGQkVcgjM7dxR2PB2mLAhudDHJYPnJZagWBBY844bCOON0Wp4ZlMiEtgOppBc0JtIzwwkGpgUHw265no/+PrTXotW64zsdVEs5vT3Cb715F8IikRKsNlQVVluEEBNlBV9sBzDz3wn/DMP8M/wCNPDMMuwxNDgOQqGSVKolgSiyzykY8vX7a3Od1uImKt5UHsczOpgfMlMhP33nfuvmfviFjrW1/jvEeiLCVJ4QQMEJwzor/+yc8gBzRvgmXCu3Ewg+9854tHjx4759/e7KeSlQy9E8nENcubDDGLkovE6ImIHM1llgESGqrzDszIZVyQn2XZ1uVNRKIGAM4BMRBRCK7yswp+WGl1+wBb3ickWrHOaYgAACAASURBVGijthQ9Z7jEZFnXD9xiOHPVz4fWeZSJeCbp/z3O8HmSCXWCV3OD9Ay6L9cB3nlV07Ig53VOWKnqpuedrv5WUBWROtepa2dZ2oLGwABARoZKVCnTxIgqiL4qGLAYkhEREUOZBaullrIVQAD2vjoQY8a2WVsqp9Nwsc5ty7949Sr/9V/enI4/+OF3P338+Op6g0VsL7vd/t3rueQ5xGae88q7R59/4f75f1OKGOD+bvj2m7dvptclCWmdXlIaxrIbp/uTDoCoTmBKCdmHEF11/NJqqlsyADpIBvCwT3dw8Qi+950XLz755OnTJ6tN0/XtZtteXK2alu8Pb+Y8TvM45DFrQaauXw3T6TAc7g+7Jy+eEDkDymq7cTodx3E6FU2mQO4uBDeO0+GwN0AmkKLDfrjfzfU+bdaABJ4BoZhJSnOFrkBJVY/HAdC8iwici05TCkGJ2xCCIfumReYi5XBKN/cHU133c3AsRQzo2eMXXbthdqfTrALrdedcPBwO797eDMNpP9yXnOZhsgS797vf/Oabz55/5/ry+mJ7MU3T4X7PQMRkKvOc0MBVWR2RiqqpUyAiV7Mc2HhRjRiZtjG6EJxzbdMAABpU/a+Wkqx0fa956vt4fdWpwvX1FYClVFIaTIspOPJgSuiqwxzVUwZEdO6ajohECAsAErMj5zRLXYBE6JhB1TvHjH3Tr9er9XrVdo0H3L9/z4jkPLNDUAIgECZwDjybc1azFxBRgc7q3mWI2jVd0wREyykRcq1MZiklj1qm4FZt7BFgHJWoIKIoIANh8K5BTGJazz8kcs6bgQGJGoLr1uvDcUb0BOC4894DqGhBVALd78er69D21HXsPaY8TGlfdB8brwVTKqpAqEgZEdgzIXtPRNiY2/SdSCmkYOZ9DK5x7Fdd0zVxmlJKSYoAQohxtlzsNGcAQkdIzh1OY85ZSiZU751zjMB1bCMipKZqAFovwKGp8DDM86B5hgA27MexH1VFi6gmFXVE7H1kVJGc5zJPkoVj7Jq+Q1esICuCBQZE51rnPfVN6Ls2utD4NnhPqNNpLBKQuuA9Es8pH8cxizXdatNvPr/+AWQwxfdvd2/kftNuVqt137Tr1ZVmzPMsJTMFCoaAjkxLOuyPN7vbd3fv5jwG9rEJbQytMAdM02TV7wm1RiQ7BBTjkl1AMjAhMjSiYjQO4/7mdr+/B9HgmU1icI5p1bbTNAfv28ur4PrDePr1q5e39/eplJTlNMxITOSjb7q2W3frtmtXPq63PaAhFYUCqqlMTee22IvN4yTzPI/TOB/Tk8fPYhN63weOMcQCOBzGSYYsCJ7ZB89RwIpNJokkAJiplqSaindNLinPWUEcOYBYD2FVAzMBUTUCqonYhARkRs7AGKhanZxTtACVSFUW6omBoarlJL3fELtxlv276Rf/7tdNB4rzp9990saub1feHYZ0KlKKcMl8PI6lVEeYQghNZOE8jkPAwjgxTrMcU++mlDULG0swVe66Kxndzbvjb7/eWX754vlTF1bEF/v72zevbsAcE5YkzAVEDKDMKQ2aC5g3dgtclTOAgXcUY4yhSXO5uT3tjyoyloLs9PJRx+gcI5ScZTSEEEIbnZU8qRSZVVxtEADQO3AIhOAJ1NJ6fdnFGCObllRKKdnAwBsxOjD2AclVOpAqWJGSM5ERWXC4WYEoeIdd7/rO910IngEs5SSSjZwkOewnKQVQVkYeyXl0ntiZ86RSxtMcHF9uNp8+eRGt/+onb//6z776V//3181FyEfviPJ0MJrYKSAROLCGEBT2D2blS+QLfIxe0bkZITiHfT90IksD9rtcqQ+D4Q/419LGffxVtVVFW2wQEAhAFpkePYSYIyE9cKZqUa8AVYZZO5ilPK1TN1hKKqvsMCQ863VquDwhZcr44TKWlwU711FnRO7cNcIC1CECADNaraZgKZqW/2yho+G5Qfh7k3KsspTF1wQQ0NSAFofZj7gUhgSOWAklmWXi0Dmnb74evvnq7vQP9cmn113r7+9eW05yuJvLG6YNcESYrtYXzz/9fspf7vcHM728XhmcXn57czzSlPJ+//b9zbeHAR495qYJRK6GB0RmAyCOBbEF8t7aLni38q5RoV/++1+LqvfZ8ZDSPE1DbGLXtiH6pnXrTQMiKU2Awiw+OOe8aVUuW+MagIYYnXeI6IAdq0MxmcZRzVSK5KRgUGWAfc/rddOtYojOYAashjKCJOyMFLKgFlABFTJh8gFMVUQVS2bJLKrDqXSdB6NSVFNRLYwmkudx2q4dQGlcEKXg3PPNpy/67/8ff/aTl1+9K0Nsw5UUI1YDMlGsIFSxCmQ6ckbo0KOBZCtTYiArgALoiZm4oJzbYawtkJy1qjWeXPA8O8WHZ+/Dc/i7UsG/x7T6//uUYSnKTAjGhDVfFUyqqeJpGkSQiHLOKdlwmBw5FZZC41zmDJxyb0Lkg6NiNE3DmBI79iRt6G++3e13EJWjRytcFFCR0XlyzCSWiJmYCJ33MZcR5uIoOAwEnozZuEE/YQaCw2Hfb9pHzy7eyfvxzQyMqH6BnxFMM2n1mjEyAwb2QM4pqZIIgKmBBx/NGnj0yVXx5ZSP2RJ7KpKn02wFVu268939eBzuRw2QJU0plbU4530MKlhEH8crM2h8s4mbvu0Z3ZjGYR6d8w3Ibj4Sg2CZ8sQNb7ZrJ44GPJwkjXmeRpmzzIJqlgpkwARIQI48+YxiZqJGQIt19BIa8dGmh3BmOCxwFJy5VFZJIQvmDR/9tTCh6pfVf5+rX3og5T1A/A8IVqVHSBGsw3wiM2PVCq1V+EvB6p5Y8TV8aGkX/OQsn7IzF/tsGH6+QsClfTQmXFyfF/7WeVcGeKDf4uKP/eEBPuu9PhpyALiam4BEgNX1fGF+VLech2aXmBlIimBGdGAKVElVdh4SEC76WraSs4ERExGKqkpRE7FSpVSmCgXMax2oAKChqaqCLcbeZ5YZIampIDKxmQFjHQLqkAGX1qXu5IqAXH+yWj0bkCGSqQErOSJHhAQMKrowd+sbT0iVP6ICAEyISKaashpAZclXchkREZ/Bcl385es5Q0SMJPXJMAMGMFBREsXzRcpYiMDEIBGg5iFDguBbYk6aQ2wBVYoSkufAbES+9gug8u03r9OsKI4oeIxgmNM0pilQbLveU1Mkp5TEMoIdj1Pbeu8JKkKtgACixZRMcbc/tm1QUSJcrVswuL17d3X1aL3d9qttTvfH0/F0Gne7O5D9Klw8enzx5fc/G4fx5fHGPITgkHGcZlUjIgBHxEhMKqUU05q9BwhQTbHg7DVeadJL/bCUEMvzTGBEH1z0kZbdnM7HOaOpIS0uh6QipZJGFVOa+66dwTyRqjY5393OASGQF4V1t3p7877ZwBeffvfzL77wTfjm25fG45RnF0PaTeAti4AqplRyAXYMzIxMPiDwDDJnckxmaZ4RYUq5gtMK5hwjEQfn2GlKjt26731DZrDZbD5ODlERA0CkxRKr0rQWCpaYQlmi0B6Egqjw4Fd13p502ZbgQ7VTP7gchPDRufXxaVb/rtjth5tgZmo+RjNFPFP8l6rKiFEB1XSpBRkQQcRUM54F18vXfijeKtWOwCClxI4RkR0DwmJ9DUaMjp3znOZSJCmoKDjvvAcEnmcI6NqmgYzzUIpm3/iTldNs+1//9vVx92q8/8EXn/8XP/gyOLryF87z7rC/effa+6gKOQtfXP/h7/2eFPEu8twP30v73UkA0TtFSyJm/tW3b/6i/5uf4S+nfExuKpINZ0/kwFAmz85FXrVPLrabZ588ubi+6FerdrXq+jCkdxzy0xePHj993PXNMJ7I0WnYZzhBgTevvmVvuZSpFBdjLuU4T7vj8TSNU9E3b/e+aYjcMKfDcUi5EApyGU6nlKYYu5yzc7xdb1ertWQaV8nmCQCdh6vrSARNE5qmYaY5TSnNkouIElUEWYtHU0qpDMPoE/kY+3Ub2Y2zGpQ0z/f7YXcY62Sn8ex9o4rtasvUVDYegqnoOObXr2/nND5+ejWXAcFyLtMxDyd4/ertty+/ffH42apbX67ml/py3bciZUjDaRrGsuMutKvOs8NSJIlvu7btmuAFBFKt00BE0eBivUbHIuAa5x0T4jCNORcFc0QcXDS+3PZd483Mu0BM0zQlD0iAqpJLmlOZi1oBRSYHRCVnJjQTriip8xF8jB7IJYEY0zxNjpEQ0zSDKRIZwDSnu9vd4XBitcYARNUKIgFVzqiqqWjGAswkknLKYlI3MSEGw6aJIURVNUHRykkiExRFU0s2Szq2zerxkydPH48q96JWihiJc0wURGC9aqTM1bTMU1SDlEoRU6WiOE1yOM65KCGb2jzNamImhEAEfQNtj01LscWrqxXgHALKLGnKp+MBAPqOVn2sUvboI7MHYFNovHNtN08TOGBmU2DH3vngHTsoZXbe5VzMAIjUQARLWdztsJRSklpmgiZ6orqdaX2zRLJ3wTGqmZYCRkBoxdisCdAycS6H+/2m65ompnkEsCZGE5nmSaXM8zTPI1S3UHCrJsYuFMtznoqWUoQZPLtN2636rm0CKpZcSIEZnGPHaGAmpmIxtOvNIxcjIGvBksEy5DmdDsN4mo7N9OjK/OPY+ND43jIG1wSKOU8+cLtqxeS0H077+9NxV6wAKhIGwhjik6uGVC0VERUtwzAkyiEGVCGw6L0nZkBSMO//4qtf7ufpdNynaZIC3MN6ffn80fOn19fXmwtTiG0k4Gme3t68//Vvf30cRhejC4ECppwQRVU0ZeWivpjNmkPbRpGyO94TITM10bPrQuBSLuY0Hw/HYzw9ff7EzAhou9r+oz/6J3/6438N4ob9OM4augYZYt8YIFowhSIZ1AGolDKmmb2WLGgUOQQfib2pzmmyIqUUZF99G6yomNQoaFBTsaxVOI6ERjXWp4oKTFVrKVDLa6ojXecdEh+P8ou/e/Xm7e0/3/5jjuHx9eMxzfltHpOoGTgIhKoJiIFJVVQtZTsej1BQwTOEAmGY+ZRyOhmDs+Qi3slAN2/u3rzd3d3CeHObpvD06dVqdS1G05iP+9N2u+671TQPbQi5lILYxdC2BESqrBmc57ZxJQsYeO8JyXnXNFREwZDQMUKeLHuI0XNsLSXvIEZvBtoYgJ7YihXnMBB7qKG2VfxlIKlpGzOd5imnOecEWuOXChAwOkBWQ1OQYlIqUX0yq/E55dMXV2rgGEJ03jk1ESkmIMJFCY0ICdlZEcACqMWKlAwZiT2oNk18/Gh9vf7k0cUTZ93LX97/3f/78i//n69pwtPO+i6CFKGBAwBCUUsJwAIBIQ9A+Rx29aFxWmoAXWAdq2yCD5jNh/77oUQ5yweplPMoGMHM6PwPWDxSEYkeQmHUANUIxAC02sITeAeIaKoOHdfyu5qHqiJAjZpV02VGTYiIZ7MpQ632yEuFRbbk/qmBgrKnj1pEw1pKqSKcRVt4BrEAARUXsgMCGlYMjMCg0hwFAaiGHJ/RK3zwRV2KrXPbhUjID++USKVsAQAQVz+QxYbYh+C8l8nIyGGjIDrnn/7Vr3/4+188fvb91Wqzavu4AnErDuXu9rg7fN02237l21XsmUPrQoz397f37/f3u1nK5vZ+P073orN3UIocdqOpYyIwnOZ5nrNzOEEyxGHKCC0zgbEUfPXq3or3rqhJllkELy94OJ6aJiCJlm0IxoRtw0zSNDl4MsU8S07axQsRMRNUY4ehiWIQnDjyjuVi3XgXUpLTNJWSXYCmcT6w8+AcllKKFERhRgAjATEg4hhC9MiOQR2oJ0JPMJexZAB1DITqS9EGUbRM4ymX7D04opTBxNIwdxebJLKO68vu6bZ7+ud//nK685wNEUMI03xX7ZjIqvM0AbCWkvJMzgOjnoX1MisoUEBEMDFCLFbvOVg1ChQFA5MH2dC5sz8vMXzANs7t03kY/jsQVX2wFuzqg+RqIezV5VRUdU7QGhj03cpsDGWexoQGms37ULKMp+n+br9ZbZvQeheTADKIGiDUrFQCOw3zcYRNRxTcs+dP//yvfhYd5Em8BDYmR8hExqhaJGOEEIIxiRbyLviYpAQfctLxkEBPaUoOXeugv46vXn97eXXlmfI8jHczIVo2zbpIdEABgLByRc4sJDQFEVB20LX++vHls2dP14/Xr9y7t7t3p/kQQ9P4eDgcxzGvQ8fEh/tjHpNmG9OETmEEiVpmc54DUedc4+N4nNJ92d3tp5hibDMlUGp9w5e0uzs2bUwl74478tivurrNmaGKnXZHLUAFTAQEFuYooKRspmaERrwgUdWuT+C8o1bBGqDpArHUxDN8ANDxDHuf9YYPxM8PuNXZxPwMDtWer/4SJaPKpFp0P/UKVBftGxsSuSrPhGolAQRkYCKlSiIqJ+C89dsSra1qCqqAVVxYASL7ENS6ZK49NLr1Y2iLAG4BDxaK7pIT+BE294DBnR9wc4gIRmD04YelKnoirJehZqLMDOCMDBkXL0QxYUEBQkYiM6QaHGgPvbkWM1RUEAU1siq1qzEB1XCnQm22gFZWCclY5VeIlaZuXBdvVVIq1FgePPfn558ayayy6EwR1FCZPbCJGjN7ZEBYciABz+jjh3afAJHq+1bPOjA6p4sgqFkphckZqlXRqp6/MxGzQ0IVKVAEluQRMsDKu0Mg4Pu7W5whDQURnQtlUsjFh9YHb1odvpU9A1lsg+A0TfNwdCsXGre+HUaE1inko+bj1PggAADMm9jG7fpq9f7mLeNUJOWUS5LJsnjwAT3xxaUjo7YN5CjPKlPKee7a7vJiBUCHw+FwmLru7dPHL37wgx/85C9/PE3lfv8+RgyuLVNum832qvns86ei5eW3u1LUMZmAmpgDMKdiuITpACDyB0nth4nBGXSpsYIP8lZcYNgKnS7/NgCYU6EFV61sLgA0JCCHzrt6L+aEzts05WEY4nZTRMY8xzBjA+UEOY2Nb+qt7iM8e/b0xScvzMpP/+4vLx9tBOdJU0oKkJOQuaLKIDkSeuePw1hK7teXq203wyljKsehqDnHRKiCIMLoqnubiiUtp7mIsHOuLjBmBr9Q3bVOzxAJEYi1IkZL5UNARs4kn6EgBOPzDnUOl1iEhQsX8kFmeN66PqLtL2XWmcD49z4BYFqFDFZDdqwUrjVkdRPD6jQGtYw7HxQfjtPzZgpgAOzAajThw/1WkVKtJKr9JKiaIzaznMRUwQGRp8ApJTWpRaqpKQKrWhLXeCuyafsDeecCOFSkWYQMXh737/72x3/ylz/+/n/33z7p1hfb7WV7ydHd3+7SNKQxE7rju9vTu91mvX3x+ZPHl5/45y1TRCABTCCzFUN+e3j/4pNHP/zR5/v7g4gWsZQUDUAEQRrvYuM2m257uX76ydOL621ctS548lrs/ZiOTJ7ZHYfdLEOa02kcgGQcD/vTfrPtp3nenUb2MUu5v9/th6OKKvNvfvWrfn3JPswpn6YZkZrGr1eNjzhnPZwGVbjY+L5v1uvecwjebddHKUYAsacQKIRIxPM8l1xyKlKKKRSwaRpzKsTsnFMrCkbcuhB8bIMPb9+91Vqlc+xW10TcNBS9xdAiUDGSJCmJKqnC4f746tX7N+9uYnRILsTGTEwoepeC5pTevH59d3P/4ukL3ejzx8/MZJonkTKk+bC/H27vYt9cbbaX69VwOFw2/bpd9X2X8lTmkiQxeR+oQlY1ptd5F2JHnmCnRxVHHPrmVzevyLvgnWfMxSSXOc2q5fnTZ7EJN+/fHfaHaRwVCpGZFSmnmuVR8RcRKVocETF778jHhlxu4jw5EFURK0UFGCjP8/08H4hibDofmlVfSgYFImXvzEBERYS9oQPnUBRFgcDV2KEimclVBC2nScVynsfTPI8FCZhZFUvWJKcYy/aie/xsszsd9odZTLouXF5fXV5s246QE1oGAyIHSE3DhiVNGdAp0L//xW9u7u/nKSdBVFUt+hAQQ/D5dwOzIpW2X682gb2kaZzHYRznYchNi5fbrmsbA/Psg4tqWJLWqc2qW83oVBWZ1ExUo+euiyLmI/vYG/LheDjuhyGnoigGqZiVTIzDaM5DE0FBtfIMwBAFoAQHm1Vs2yanLOQBiDSMJaMqGTDq40eP1l0bmAIThQBgwfEs+XB/O89D07TROVNTFYQqVlJTKSlPaVivO0TzxIjOFCWZGZYswOg9E2DJlnPKqbRdf339pG1XRW0cZ03wzcuXkZs2tm1ckTZ5yrfv7iPFR1ePYlg7aMBKxjk6HyI2scmaB/asZNkI0WbNmEAhNN7H2Lo2Bk6pGOvF9tLU2DkrhQzaEKML0fuAxLH5yb/9ek1+06/CdWjbZrPptuv+xdMnF5s1ZJOk+3Ts+7XnuF1fPr5+MqdXwzi2RP16Pby/ib7KM2WWsZVgzGJ5nm2eJwNrmrBeryWJmq3a3gVW1VN/PMXx4mJ7+25/s3v37PnT/+q//mf/0//8v774ZG2Z96e93O8w+EfPrtfri7ZpyU3HqVipXQF7p6chAyyuOkzskAtUONKYyRETklm1ulAVM1GrkncAKArEQly9TKEslt6qCsC61IA8pBMKhYDoKCV59XJ69dX0vR/95vmnj7vL9eNH14fhwPN9Ez3aqovN/uT2x6EUQYBpLMBAHSRvKaU0A3nYzUfFsLstUtQZNrj65c9evn/93gqWxN/uZJaXOdPjxxefffrlzZtXm/VlG4Pvm29e7jwBOOqaGBuGEIrANCoL+0cbER1O0ziOKnlKmZ2/3G6bMJdiBERo+93oGfs2sneeffDQRJ9LDh6JuGyaUiglmIoo1kjQpagBCNM8TtOY0wxqhGqAMhclAlTvHVPthYApOMZSZsk6gzGTmW6fejN07JldKXLY55SKcwExINE4zczsmkCsXctNGwtMucwszjC8eXPXx/Wz62efP/3uKlz/9V/8/G/+9W/+4k9+8+41rJu2bZxnKpYZgKhiNgjKUFiB2CFWMpAuQ6wHKGsZpQOAgRIuHcbDh+wjI88Pv6pQ8sNcblFUARAwLDnLZrLU24aLB1a1uT5350slvgzaiUSqB4MJAJhKqtgCICMCqi7ZOh/Xp4xoBhWasmraWNsqJjP5nWaRgd3ibIy2eBhZLYOwpj/VVsKsGsTX5o0Wc1g9U9bsgb5QOTh2btgUwCDQwztam8ql7AMDQEEkAFUrUhQwEzj0DEhSLE/qffdvf/r6Rz/+7T/4o++QlyfXT3f5zaHcPHq86lfNq1fvFU7v7n719v5XTROJXNuu7/bHu/v7+/u5yOP9flRIMTJ7A7JU4DRm9lqV7jmJ8zlDEgQtzIhahjylwyHfvQHIOUbFVrxjUFPxopqmcZqnPM3bS7fqfd97gCl4jJ4QvEecTRiRnSN2zEDOAKueyWKM6zUiNiJ0PM2u9VkR0XyoX45N429uTwZVD3cG0oEc82a9QeSUyjznkucYY8p2PKVSIIbcND6G1nBc9DOE5CDGJnpiyN5RQCbxLW8erZ6nY/iTf/VX778GBDGxeZ4jY8kADqhUFQ8TEzLlAqCmcxqNvHOOHfhGIIOoI3bE1YGGQB6YhlbAFFEBdBHkLk/1WfMDv8vFqjyJ+txVBzj4eGWZAZ4N1H6XhGWm0XcCRUrCAhAhhqaAtdImK8M0ISobm8B+N+x2ybmxa1fdprsY1/OUHIFvIjouVgytW6+NZgdx1a2ZPHjQAiikWTULKhAu2QSqBQmUSMFEgByGtkmW67I4DUcAyFMyw6aPIvL+5n0b/ePnV30bHz26/Zs/+yUSAhsSMyMZohkbmGpRKWLFAAqAg9DA9dPtarvaXqyvHm+3zy6/fvkte3Y5lFJUlAA3bduFLk95/+447WcwLFnYDBiKWMqlAVr3q1Xb7d/f5/vp7u3tfAIggNZBwIuLdnu9nY7Ti6dPfPDD8TSMw2F/2N3vU0mAGoP3FIb9AIokQAIkCGUBkERAzEzpvLThvIMZnnlR1Xxm2dyWvo8Ia3T4Arsvpli0dF9mFZLXalpVO7WqIHu4/xWiqmL2WkguRKHzGII8mWgWRUFm9sETMwCKip3ZRpWYDw+y6NrLL36XUIX2NQcDqkmyLpZuFXK1Sv1hOutfEWEBBJZOd9lMcfFlquY8HyBZ+/h5BgDHVDnf1W4doA4XKq3JAETNDFUzFEMzVCTDanYo4CIjcaVdqCoaGaKB2qLjraM3UxUFRYcfHHPqW0z1iDAEsPoJOiumpMrdz8tOAdSIquAPJXz04+rCHFm8lLAyg9iImEnNGMGdSXFYEyrB4Jyw+3Br6XxtorK8JAIwMLMtYYXL9SIRWnXlBIBFx4qIWi+UgcmhB2ICACv1eePN6iINeTiMUiS6EPo22VjyjA7FCioKCRo6YvY4jSXPiOJJYs5lOgIa5KmMh1RmdY7BW7tyTCeGeNk/Iomr2AKJKZreGgoRMjtE2Fz0lpWriwNiPSKZHZFXned5GgbYH47bzfjk0afrdW+wK3Yqtmoc5jTrOIvy+ip8z704nHb3tyXdA0Rw3pW5QBbysRLvoN4bIFj8Wj/suLXQAbKlilEzRtTKtKZlCmU1/JhM1TKoA0ZgIIOFi2gELjrmykOligGHlg0xS2EAJJzybArB8TzPYLK/34UI3//yR9/58nN27v5w8+b2QA0YThllHM1zAWiYPDufSz6cplOZhsOpiK1LaPvL0Kx7zMNYcjmhAqFb8GyzLMWTIyJT0xkOh2nTh3Ech2HYNgABiEgWnfICQCE/BEicbSCMAK26ViwllX2wYzzzO6uV1TlVcNEFnsMjHmB5W9TD8Dsnlj0caRXWr4LeCgjnnBGrbWWF6xnMhIAUC6FKscWWYoFxEQFpgdHYEywpn3V6KQBgy2jRjAICkKIJaAErWuW85kELuMCVUK8GOauKrZumiXF32OsO/sEf/mhK4+0tnNI9MnKEtndN74xUIP0v/9u/vWdVOwAAIABJREFU/KPf/71/9I/++Lub72yfXYl8dbDDRb8N6D01Tv2q31y6fsWO1aeUZyvGSI4i0h4O63X44z/+w//wP/r9BImAIrTOQoEMVswErDhG1awI6CBpPo7D7nR3vN+tL8CoTOmERMDYX/ZlV1jpfr/bHfZGeprT8TTc7PZz0bv7w+3d/ZQKMwET+RZdH9reOCU9iVrKuttNTXRtt9l6Vk1t9M4RmDiAVetJuzKrmu1PNzm7UrJzQURLEcmG6H1wiJhnnSSLlBB9DJGIm9jFmuwr5fLRo9NpKKX4ZtWtMHjnWBhT23ZEAcinYmPW4+GY5zLNczHt1m69ulytt8N0l2bJaQbSppWShps37/NUNl0Pc3l8eT1NE4jt5VSSlCzj6ZDS3HGQprNipOSAPbCAY2BCh0jee+99PdCUwDkmZsy1FRFEY7S792/b1TqEJf4spUTEl5dXV9uN9+7+5r2lYkUMsKDlXIhVNRuC8wkJiBEIRJS0cpoEARjBMVcNoHOcpJSUwYCJQvSNa9qmGYYkOSMzoPdoqWgWK6JlGLNIbCNx3XMQEVlIRKXkcRxKyd77NM+n4XQ4HkRy08Qq1TPRw+lwON6uuqv1lptW7k/ZRbh+tPr086fr9Vqt7PYv1ZbhFSCIaCqSFYoBkPv69W8lswATiZlosRpc26yg66HvPeDU9e76Udf1PM334+leJOWcAaBtqOvaGLypehe9iykVlaxinti7yNwYSy2Y0XHbr1br/nAanXp0iIGUcC4iyi52wVgsi9VCPzMDMxAhOXSOkCAoiAKxBUZH6gIboymmoUga05gsgxH84Y9+r6TCRAgCJiIFyKLnNnqGtu+6GKP3PKcZAKTkacip5GEepnm4vroEEMcOFeYpTWViCm3Xixpk8OwIySFdXK+9j+O+3L17m4ux84Hb7eqyzNkUAzXd2lkLKEjqg+v6ps005Xk2QGAIBJEa7+K2t/lSHccxJ0ETFBODmaxgAkClJm7W61Wl4OVSGh+DYw+u8aFrmsYHF8I//Yd5ssyeulVs2th0EUEkJx3lzZtX02nsQvviubu4bC/XFz/88g+6tv/65cv9cX87TMSUp3k6DmoWg6ci3EvTXzRN472fpqlkPR2HpmkZfJmKFnPO9c2me7wJzvmAcz76ANt2awaeUYZch3RzzjkX7zk0UZFW2wSesCRSidCc0o4AqDYIMwqKqEgRKQIAGMAhgmMUUzGVpchDAwMGF+p8pWZvLyxiUwABlQJA4ACg6YKB5jKpFcfAHkoHv/3q3Tjl3/uDLzb99mK7uv36vg3gHJlxkZByOpbZZgCC0EK38l0EhHIc0mlO/aM+CfRtafzF48vn00nevToc7lPjWxHrWjie4Kuv3k+ptO1n24vHwTeOzbGYFECp6WDGwRNVMx3REkJLFKXM42jjOLbNquua4PoQ8mF/Op2GeU5XF+gZV6t+0zRNRLUDIdTVwcxdj6UgkkynCYCIfE19qQE/p2kYxmkaiyNoIoUQVWmaU/CghGXREwAiOQousllWSyVJMZiOOwDIFBljKTDu81zAB1CTnFWElAgRY3ShaQQw5wKExBEhDCfdxK7x12Vq3t9MP/03v/rF374ddgSCWpyq5jKrZlWAUgEseJAhLPITPcMrHyFBdYqOSGaGZIrV/LR6GGCdtX3M16JzNw4fffyjaqXqtWsS+8P8Ds9D/EXVCmaA58gurTO6pXZiIjAwJM3lQUuyzPgXMsr5wpf/Y+Fh4flLBWRhSNmZam5W063sIXXQlrarSm2WOmuxURE1gloR1ckhLQIZMKDz97Ezx2Ip+8jAQJdXqFx5AD17fpsuPl0mCqYFFIpHQSQDzbloNs8NCNy9P7759m51cekxMjExq+nV1eX+MI7D6XSa2xU2XQQoBlNKY86pvv6ck0EKTSCmXMQ5WK2aEP2cEmmpYeAqVEwlCzqbS9nfTe/enuoNDr5pV75p/DyPMbalyJSG0wFBZsR0tX16sQ0p70uaUlFCluRkhuMIbRNc6whNUprTQExttzYlcSQaCKnvYjrcTnn0zGxYVEHRKMwpVYi8ZnI516BrCJpS0BRy0uNhSHOJMRYph6MFP5d0/+jJpu0aI/HeAYFzjgHapmmiD5RYVNPscb1Z9VjaX/9i96d/8gtQaBtP3JVi83gI0Yl5VIFCBgZUSI1q2GHJZUrgLYYQvFNEK7oIrpfksYo/GQiaVVu58+NcmXgIaNWWbXlGHx7YRYzxETZV21VbjD0e0I/flRAiAELTtlLmow1WAAqULELq2KdU0qhxZcyuzGWch4LAHtmTEfnGK2rXtOTcnHMus2swdg0yO2kI/d3NHibIAs7IFMGMCNghsYEpFunXXVGYpzFpCaFbte0qddNx8petZz8Mx+NBui6IyHCaDodxtQ6PnmyefX519fjib/7NLw0FEphqAYACkAEzgAfzAO2HHxA3cP3iYnuxIccJ05jHcRqlKGpdhhSIo4vrbjPpXPI9zIABAUCSYQur9dpFb8QiMA359a9eQkJOVH3eybVi+Xh3KrMcp9N/8k/+43maXg2vDukgVlJWM+g6HykiOi4TKmpWzSbZLIMDWqQtqpWUVHmgIrKAHvYgt6vKvQWKWnarM49gIWmdPdyX16ltNSKiIRGY4QeG1IJjita4CwBb6HzLNztbiSPAB51zZfoSGlguYmDeeQBQEYDzVgQAC/WJTK061UDdrM4HBD5AM2qK1VIIa0osEZ2f7bPWqD7ttc09+9l/zNh9ALMePu4qJWoZBCAwM4CVcjbqru8aInkANmJy5JBQvKFgSQUVFFRUSjU6YAB/joStv/H8J0Bl1Nblpwi60HaWvd+RY8ZlClHKAiI6UFIAcMhMDgkBgYyx+t2ZKJiILDJGBEAgQiYiZFADrfhSNQGqAewLhkXwcCzV+78AE1VbXyc27B05Z2D16JVSGKmSjNDYSEV0LgIlO3RISOSYdPHjAyJDAyDk4Py6Wd/sb/OpQIbii4EBo3dMrCDCjg01aXYuSAEFaGLbtp1kvn1/vPk2QU4wAQgAQ3GiBvmY9rt0uB299Wp4fXGNrAjgyMZ0IGcEJin54NQk5xlMVdUWrhnPWYriZnNpdldy2R/2l1fTs8+ebk8NaAltIT82odnf3ZiFF589u9h+r+v4l1+9ev36fh7VFHwIgohKgT2gaS1mJYuaGvh+IXg+LDgrAkbLOa0maAjGXGVtgGgmtowdtCrBiY3rs48o7F0MPgQXYkBukIuqbrYbTfn9zbvN6qLv4v1uB3vgLXa0KuOc9vmP//Ef/NP/7D/97PMXh/373XhDBHf7Q9vHdkVdN4duNUkIvi1Gp3GkQu9evx+OkDKMv/22ad+++OSTi6uNY2cK46zRGygBoojArNAguYAGgONm42Ns6qIhoiXRxuqE5Iw9QZXGLDvHGdICakirPH/ZosysEt1roYemtYxcPNQ/2uceQN4PGFZ95d8Fqo2Ijc4sxyo9RCil1JBQsSU0ExDIsymwohYQKWCLddZC7Vxs6IFcHQ7gAz8LzoRIMwbROk4oWRaPfzJAE5WcsqAAKjuHAM5RQkk6p4Q+uBlL04T1ukcSuE+Kmb05BwjiiHwLj7948tW719/+X//nJ0+f/+C7X375yXc+ffrp7eubtJskpWdPnjx79CxQpJTBJoDMCAXt9rB7eftqhHmyDN444pSmIU2ND11sUayNTSSehiFNUw17Gsp4mucxT6Okovl2ksvt+nAY9seBOAzD/Itf/uLt+9t3d/dXV9vvfu97N7vZTDCuxrx/ffvueIIQHLqQcrneXrNfm/lxzO/eH9/fDibQd9C2cHG5/sGXn8bAeTqZ2Tgekx1B0LJaMURcdX3K8zxkC0AVEy2aVBGYCFOSNBsT7fdDiLC5WPtIzDbnlLLMUx6nJApInEWmYXROnz5Zk2+axp/GhOCRw2rd8pY3m/V228foq/yHOE/jMOxOAT1mOr6/xwzrpmsoDuAb9uh0BPfiySfPP/ti0nych2Ky6fvrzeb1V19drLYOvSXzRperSyXVuth5eUiAIUs+DcNwOhaZvWczHYbDj374B+Q9Elays3fOeS9Zpnne3d2edoNkLbNOKc1FAKHtAjHmnEpJRcpq1YXgSy65ZFVg5hi8kZlASuKYuGnZcMqjFItNXLXr4EKaS5kFFD2yau3XrYgdj+M4Dujo8vKKvZumCawwE7F3jlR1nodh0LZtT6fTbn83DHMN9UWCmuwdGzQ8hLb//Lur9dX33r+/f/92R0xih93+NIyn7WWXC1Sd/TCOh/vDOCXmBqlB3+8OED1Vrgs7aDrygdqO+hW3HTkP6+3mk0+ePH5yBZRvbo4+oOO4WXWq4r2L3nl25Nn7EMiDQOGiYIGjDWXVtOwYWGPXXjy+5uDf3e8Vbc753et3p2nORQGcc21J2UxUNEu2QmLQBt9v275zxGIlSU5ktt32/aohA8mZEJFJAX1wfrPehpXndtWvnj9+tNvdp3EEhNB47zvHWHL5zmefIcI8JzDruzZ0DTtywcemIUdJ0jTNpRTnOHoXnEODnLKIIDkAC+xWbbfu+77pQCEnGcfSkKRUhnHeDadHnz7aT3uZs3lp4rrrOwIf2HeuX4c1hI12alamaQeYm7Zx7K/7F58//X4B+Ku//Wv2vu6QNXaYzTXUOfJASI6ZuM7itBTLauaJO+e7aOE//8PnUxkFhdkKlAKTmUjIOaf++aVDPp1O83H+5uZ137cvPvnsu7//xfGH493hfpiGV2/eTHme5wlEqwvQ7t3d6d3+xbMXV9dXTWiIKISQUx7HcTrNc04I4JwjgKsvN9uLwJ6MisD0P/4P//3PfvnVT3/+8/fHO2ESNqPyzetfI4XQNH3XrLaNFwKi2DTI2QTTLJrMLHuCAA6gGWVOc8kygQuM7JCsjpgEFRUNFZlDzEUkTaACaOiYEU1UFUDBJAlkAEqSEY2di65FBJEkaf7lz29/+qvb683z7/0Hj3745Zc///k3c9nf7PepoLHv2977eBymopkdS6YJNRKiAwSL1A67/VX3fLXqSfyf/OmPYYDHV9emnshiCMfD4e2b8e3r8c3rV//in/2XTNq3XvPxi08/ef36WzMoZUhzAscKrJJyMQAoIsM45VJygsPhiO+Pm1XfxB7RgyUt9u03ent3WsXN40fbJ0+f3O2/RmdWRHWoaUSO2ZF4VmOL0cfogo/smL3/u5+9BwMRyAaqSs61IfabDo1TlsNhmMZUvUTbNlxcrJuuN8iis8lwsQnTMI3jOM1pTm4YcZjtdLo7TCV28OL5o9D6IrNHl2Y9vLqZUmnXYJaGQ4nuqo/PIa+/+nd3P/vJb/7l//4NvAVmBwlOeQTR4tk7BCMtBoSmDKDAw8Pgt+YwPTQStahZSo9aKDAAwtn6YWlM/j+63qxXsuw6E1vDHs45Md6cKpNVZBVFiiBNWpThod1AP7jhh/ab/0DDgAH/Aj/4d/nRjYZf3EI3YIhQtyixSZFUFWvK8U4xnHP2sNbywz5xMynJkcDNi4i4Me5h7W99g4p+WK60Dhz+UUP9//fSFBsPz4eNO64ILa7cuFVCc8oNVydHxM4RIaJjEZEq0oofJkYHzQtdtbniQjVzSMjEukCvlzOSvafBLMXZeyuZ955WigDIbqmTzMBQRQVU3nthtCNpE9AgoNIfUQoYH1Q5iFhqWegM7RQrCKyNr2BqItUeOpUGpc6gWhTZPBIdDwkM/uIv/5o2t//HT/43F9bzXf3N3759dX395/9l971PfkQEIaKLiKRv3ry5uT7f3pzevbVpAvCn22MmgthDGKJjMcpZpE4yTmdULKIImERzAlOoTqWmd2/PL1/NfccTSr/2603nnE7pVCqqUC1Vxe4PYGjPHsF6wFJ8nmstnEc53JXTrX7++ztAAAEggAGePIYYMVfLFQyg7zaPrz66enKFq23okmMGxvvD4XAckSH69u0ToUPy0UdHvs56ujvkLCaI4kBsOqUWvjRluIO0GeSjZ09mLc6xIgTvgdg5bxXzVJywTNTB1aPh2d//+pt//+9+/Z//dooDlVI8FyZNx1vX7UCdCQEBYmUqROiAgagyaS61ZlRDw6ZBQq3FENTUFH1s8C0qoJg10yuFxedjKbdRHyLFHgAsBK0f5rf9E5d/TFRZHgHRiiKxI181g0DJRVlN4P7+Rid48unT1bA+H87Dtl/tdbvdpDqd7tPt8cYUui5MeV6srcgfzuf5NK4cjancvj0AAAHXUjf9zg/eQBDNQKpU42QhSFX1CkDkKUui3mSQw+FgBl0Xap3Gc2YB6uDxVSRXX19/9da4zPY//6//47uX45uXN4e7+zLPUucmtkIHsQtX+/3+8X6zXRND1VpKvTvcvHv7ppR5vb06a55yUpHgHCLMcymqXCMJeecLVwLinmqpm/WaQ5dKSven0c5ymk9fFUJwAkpaqQBVCIqEp3dnCFCP9fbd/eH6NN/LYpXLUMGSVJUazEHTNFZVMW7wfQvjMxPTJaLLGgDfpNML20GsdYM+MBhU0If1Fpr5FKI10z4kZDBUVFNttuOKeFEQvh8S7b/LegogFx0qNIUbGCCTo2ZNTmRKWlVA1LQJo8GAmfS9byDA4hyIJs1Wn3FxIKelT3DxZl/aHoBLXoaCXhCCBWptsa/LqyVZlmv7kIH18PPhrbnlmN2OxbSkZbRYTkMwW5x4ihQChLbaE7Bjdo6EiBgU0erF18CAwHhJJARsPmDLvCTA9oJURFRbmicBtM8acWk42GWnaWxiaywdt5B0VYSIW9MCmmjwYVNcPqpq5gCpyT2XxkjL1ry47y9O83jB/ohgyW6zpbXCAA6MCbjpN4GaYVMTdymAPGjyNdcKDM4HRjWDXCsQkKgRNoGlJ+7j4PgAHtgRGeWpsKFzERyiqWiuWk1qzlKLrPfBuziN5Xi8v3l3iLQqpWoRQHNIbCZQFQiy3V7Pv4evYuQ0lW7gJKe5JEOIXehWobFJCICEwNicSZX2YasaEq+HdU71eDyG4L/55g+bTa/K0zgdDqcT4/NHj41nRgld7Qb97E+ecQjBbT7/3cvzIUFH0fdaIOUMBgCVEJjRewJCAXmgB8HDL6YGF7t3VENQJW7z9+G+Bo6JkKhN1SYQAjDVWiqS+t4BQC4ZATfQ55SnGYYOTHWcRohgJsysIuDgxz/+8UcfPROpN9fvrk9vHMPpDOt9IFbU5IgdOOeCCYnY+TiPI5QKCiAZTkiH04Se2sQGydUUDWpVMABuOiNz7FbrkHM5nQ4iGmMXYwQCapk4y5rTqpzGTPtgp2mocQOrLttO4/g8VFC2qAIv4BM8POTlk/1jDOsyqj9UCy83X3qJ2AKYrZqaVasGqC0zkwGVW/gEO0ZGVdVFmt8iF9tk0get/QKcASwNyKaHFgJs6HFLQGDAVvyiqAV0xuYcLaxJhQoCZArAEYoWF5ydNHhPznU9dr0bVmFYxT66U0rTdJa7PM8luPBk+/i72xc//OQH5+3pfH3q0AVjb1RzEauzJvXIIXBUC/nt9TdnOZ3lXKwIVGBgMKjABo/2+12/TtOcU+pKR95lq+c8ndKcpSJROU1FMpEn71Our6+vbw/jzd1o1od+T259c/MWAPxA41yzAHvXrzfeR52SgZ8nqVpOpyknazG6Zl4q5LmasnMBQtaaS5rnlD0FNEIDJJ5zFhEzrAWd913X+9AboBlO03g6jacTdJ16AOwgBBe76KNHoqoQIhkFRELiaWq2kqfr+/vTOKm8+foPN6BUCxKQc/xod/Xk8VXfh3me7u/vvT9/75OPXzx98ezJRx3Ge7eu59zFjpCGLpooG3YujlWElpLIBGqW8TxdrffrbtW7yERmGKLznUPPKadcEhJxIBc4l1JFQ3QurNlxlTrOU6GAzCqiuQJCDBxDzJbH43E+j1YKqWkxqWDmvHMhRObWX8rnc1EZneMiRVRKqbWWnGciyvM8TZmACChPJaVMZtivPAdmL7Uioo8+RE/sqlipKAJATD4gU1VDAB+jKjCKY3COEV1bynLOzND3oc2gYdUhUS4FUdlLrofD2YLvhk18QtGgO5/zlG5UMKX88fajlFMpOc0F55K1pgIRaUr5fBpbeaGAhkAOtrtutQ4hAjs1SN3gY4c+gsJ8Pt1P0wFQhmHYrNeImPLY1ozGr1woqyGogle3DmHlOvQEpCFER9Sc1xGBmA7n+yIY4qCVc6qn03ga05iLGCBpUej6xVdGrNQ6WYXOwRDc1WYttcyjoDYRiLouXK1WZMFR33VdzZOUucoMgMTkCMiF3WbddV3XdVoFCVergQiLiYu+73sXQ675PJ37vjdVtOaES2RURKpYcN6z64IbYrcOAxiWXGsxBG/INVuey27ty9NEGKLvmTyK9xQCxz72jIGBzCmYxZUDqGoqtUVVOEL6wSc/RSZEajVmNUUJWl0tKmarfr3uV8BARioitQZyQ+gCRAdgkHs3G5hCme2cIRpKsdl03nTDtl+du/N8HrcxxsCoXE28uqu433e7nnsRUa1gOs/z9fX1GUZ2DABpni3EvhuC7zf9HrZWqqQ5TdM0T3Mt+a/+6v/drFePnz1/8viFWvqvf/7zd/c325fdq7tDVfBxL6jj6UwucyQKHTFboSJS6rjddFI1MWQomo2wErk+xJJLSSAZrGQwCOwREZUAgJsuRm0pTrG1OUBVgJQMiEC5ZWIYNIM5MFBSRabg3RCDTPM9WLl7e57P292T7dDBdAbNULIpZU8do+tCX8RrLXcp9QH2azcM3TDwfEh1yrv9fr1aH+8yHAEIUHzsNjD04+EIEGPn03x69RYOd6ewH9Jczvf33pfovZE5ojFVrYUcO8cQIOdyOo7zbAjABKs+gJEJlaxprtO55MkcwTxBmrAUZQw514BGCLXmWkDVMxMzRk/GED02TYbIpQuF0IIZK9JUkqiPzMxoArVgKWAKwQfPPbNXsSrS8o4ZFE1IAc2TOhBHRohMODn26EJRHafkHApxKa7WChpVuzSnn/3oxzKGLz+//v0vX/3mP/0BRvbsam3Jd0rMUkGrtThZU4TGo8YKqGi0yOUAFwdOa1bj0LrxgNqIWIa4BKM/sI7+gbsEPqgA/+iy4GAGH2BkdDGGurCc3lf8sBTtF0eCasLUuqGNMIXsud270bNwOW4ANnuXJeZmOQrYZeheytbm9/VHfBe9nKSWcuw9OcJoaVCqXtqR8EfnMkRd3E1taXKqygWeWIyHEQGsFZnWqJCNWrOIxpbKDi+PrACmoGJW1ZoPPXbeayl5gjVtixsR/Ha7++b19bff3j+TnghDtM1V5wOaIbMPofNunBDIRXYZwBRQFQoCISmQVKlVmXyzCCEhQgP0hH0RB1p6L8F7g9lFZFcNixggSozBpIMtahGGCupLdiX7mnE62d07ffcq373LcATXeR/Je3MROnJ96NYdHc7jeM6HKVk+GfjOsgYbhiF2cZplTlPKdrU35zrvAiKrwDQDW5nH6Xg8icBq2K1WcbWCUrSUlMtcSm0uw9F3OWOVIiZqFQFTyjVJPqVt3O/WjyLv09ldf1u+/WoC8eC45Fn9Yd3t3Mq32EMyYlJ06NiQm9YVHbGQaZVaCgMhIBmZqUo7ujMrKKBZmxUK2PzjlmgBtge2DTxQ/R7myQUkRkTQxeP7YSYsd/gHv7e/J6BpnOIqMJEgGEEfOyUsN2OZABzs91dMhIxqBRRTTTVJKpUIvfeplj5yiMFH5kCaznPSzgCNNFu/jpR9LiXnnCUxAXvgAM4Dk79+d+S+qdSo2gzV9wMXrWvvf/Cnn16/e3c8TZBBZlAP+0f73b5XS+fTcTrlrtsfUgFvT54/Wq/7oXcF6904ncdxmsYzzqQnMBpP4/F0LyoAVh2Iuaw6nyepVRUSWbaSZqEKULHj6LyHOJkqu7DerFb7zd14mmrdr7cMdPf26CL4ClihJAAC7AiELCdAWHWbL/7uy9vjba2Zm4ymSTicEZEjKqKogIbVCoJ5ZjRMqRo0W0g0M2t4LYJaIxx9uDriBb1afMKXZNrLievyCMtydsH1cZHetaiH99ylB0vmlq3SFuj3S26TM/Ji9d0O302FqkYX8ym1CztjAYwQGmeqCecWF/XL8wPYsp61mMS23uPFFQvArNlnmiE1Ou3lFoAFgGqmWv8IjX3/VgGcSG1prUYtlbbd0misJiYNEFYRM2DDZg/pHHn0FQssnmFMBoBkTs0BMLQdpzHIsME/i87dTNUEFgHvsik9RElJO/U+vPnlxRNgQ8hUtchCq2u7HzdZfPO7BzBQAWgQpy4AISExkYEhN4RuiURsRKsGlTT8clkz3lNO2o4BzVHRRU/aBoBWvTC/GERV1DwjIje6cvtGVNQEQA2cDo965xgYQMmqIYGYKlqILrBXFjYLQxBWMHj+4qPgfTrXN2/uUbzDXigrZJAKAMjAnoHAu2AEd7fHYd3N5dXVo7ULOucEnIdViOzZQdLJEauyGYhoznWaq9ST9wyom2G12W5DjNvt6nh+9+lnPyaaTKdRlZmQZVj5dC7XN98ejodHu6ff/fTZbvt8vd5+8fdfv7u+SSVHDhG91GqCzVvAlm/7ATbFy3B/8LwC0CVsElrmY1utGwIt6px/YEY+TDsAq1JInPfeE2JRcipmRXM/+BCdETnvfQ/T/ewdhZ4++fjZP/8X//3Q0dubN59/9fnrmy/CahAZKZgCIAOSMwGpmlM9H+bTcSR2xFqKkgcAPtydpaS+i8GHM2URARXIRqHzva+1ztPc98N6vSrl3ThVAh6G3jsHGQpoqcDUECWEpX5q5CxrK8jDZ9QmanuvzGyE8kEKzwIF6h9N42WI6gcY1vtb8FJaXpDepWF3ARUfdjw1tYWAZdr0vQaEzOS8uxhQXEj8BEDLixab0ZpV6TLLmxRYtWVfKwCoGjnf2gXQJhEiM9UqiABAzOS9M8tG4Jz3zmUVMhLxAAAgAElEQVRJv/3N78GUnPSxI7bO46oL6z7G4ALTu7ub3jvuwt14/tXvfkuFb57dfP/pdz95/J1nqyf1LAzkyVGwapaL5TrXkuZynNLh67dfYg/Herif74zURySD+TiWed7ebnbDps6lljIMQ79e+WHIKscyjTkhunQ/vbu+3z96QhS/+vrl3/7yi7lUJH707GrYXFXgOZuaMGpR6YYdIPXDGoBdgio2Ho/H43mcpirVO8cMm3W/2w3D4M1gnpO2JNHTKLkMUT37dtA7Hu9D6Ig555RSjrHzPipQznWeU84QAz95vH30tBu2tBrW7CKQq0VLztNYj6dSslk76msBNJzmlEot+s2bceXJ0RAcqcLt3d15OhDqOB2PpxwJUH06wultvlpv9t16v98BYLOFBgFT6EKHZImx5kmKajVEoIrRdat+u99tHJNIUTIMDhyOU5qnDAw9xta0YcTgI5Cx46pV0aiiEVfRVCSXci615IKGnY+P949JKOWCyjaNHqnrOu+4lLnmYgIx+jSWUQsQeA+S61mOOZ2HoTcxkArg2orj0AUXAwcGFyhg36XTGEIXY1DTNM/jNJVSiNx22xOxgaJR13eITuosokWyIwuhi7G7/foG0bx3zhOhoRkTbTfrWnPX9VVF9Fw1Bzfs9v128+JwP79+c397c6w1H+7vUsql1lp1TrMqEMNuu3UuInMz/4zeXz3axQh9zy4AcQHUoum/+vmfp3LqB2YSqSl4jGG1juur/Y6IxrMXEUAK7AkJlVyEjk0BvDiYi1ZDshjj0G9M7f54ePX6zZhLNphTAt/5LpwP6TROd8fTnAAJQnTk6LtPHhEXolLK7J1sVqveu0joGWtKqkKGMfhAHWG42jx9vH/ehbUpoUEp6erqyqDJ2Cm6EKNnolKy9y46h0TMZAyH83hze/f6za0CpFLmeUaNUgXMuo63m36/25Bz6JzDkEq9eXc3nxMKBg5gqApoHOKwGlZ96FIpIfjVauh4MCUyH7hniCaN1owGZCqeVwRatII2CRQj0EfbRwrNnHOpyAxCqSyGzrmI8fb+9rdf/Pb29Z3WKqpk6AClmtTCWsEUGRRLlqwswCZWsmQDWMdYRR2js7yK8N3vffz4oyf9ehfQqubPHj9t/qGqNZf0Yj8XqcAtr8hM1fsQuY8uMpFG8DRLobGWeS4hxJTzq5cvixqHbtg9/vlPf7rZ7T76w/Mvvvny119+nhTWq7jarVzsus6Fzou683Qaz+fdZpCq2bkz2KSTVRUjqQxidGnYqkAqhREIGC9bTBULasxEwRujSjE1LWZNL9/iXFo5R4jee+oIAoJnds7RmCfi8oevvt5+BKF7+qeffvz5F6/rVKvAXCFPyfd+vdqK1pwmqdBF7rroyInI/e09IoBJnsq7N+9AgJ2rhqUYAN1P8zr2xIhwmgV+/avPf/5nn+W53t+8MRs//u7zHqSKGR77vuewQkgT1jyfU7JaoIWRxOCInKkvRcfTlM/ZsSOqICDF5qmkVGqRrvcmVSvUAkwWncMIiKDMzAhoteZSVRQeP97MqRQ1YkeEKZXpfOqYh36NyNZI0AqrvnchlKyTjCVP7G3oaB5PVoHJO3YFXSmQZjWhLvRdF1IpaTynMiL7jl2MPbL13WY1bMVpGvH1H26+/s3d17+9uXtlPTt1zOhAVNNELmDjB1WsgODAAIAEqSJb0xaoKdiSrgcAJnop7hYHBDN6yFm7nJH+YZXSrm2D5z3G0yJ9WmFil2KcSFuwDy0P2XwUP3R4UQMz5GZxAItdcatzHAawpv/g5ZikJiqtXU4ISLQ0/KyZzMCSU/NwSPmgvbpQ0T+47kJ+h0YwtuVtfVCYIUBL0Wox0guJjFTUDFtBCEBqpiaXorDVcQjWTHHw8pCt2HpPv2p5VMQOBFQrArb8elSQgr/5wxff/9Fq3V11oV93q1ffvEHs1qthmuQ0HmMPZrparfZ7GY94Hs+x6/phRNDYO3KkVgGJnat1sdRXBTVkCtGRWQxuLUVDqOtNsyNn4gqoQHOIEKK2MFNmRjAVKBnRIogertP16/nutZ7uoM6uHcQdE7GCai1FxTvvHBMxTqc8n1+N6bAa0e/KarXfdeuum9gx5FordTH2/caMzqd0PI6SkuaUMwQfHAfvonMeepqms50FUdiDmkzzpGaSUxExEBKaS8ljshm2Hh9dPUmTvn797csvjzc3ABLSXIJ3iKhWwZl3ThUUrIWEqlNmNOOmqm5uaNryyaDx/cAEmsusUjvxtPM8ElwSDNr4tsVezUzbALQPh9sFmUAApPeq1/ezyv7o9ws1crnaeWfeF5rNQez7YprHDBlggBjjPJ1FFFGraS6jqWMPLnoEbu5GOZcs2akjdn0/BNc34AmLWa5MzrtmFV2NRAmAFRkgQOyjtloX+49fPP30sxeh4+vjy/2j/TiOn7zoyiMVhG7Hu0e972xKY6p5zPnrV1+TdcN6t1mto+ec5nEu5zQmzcUJMZ5tKqOqyGme6ljJUa51nNL9lKIRkUOzmqspBPJx6DofCXA9RMh2OpwJMfYdOT6OI3b+8ZOnpHD/5btaISg0X4qW6bNAMQSdj4fb4367Px6OqSZiBL4kRxQT0Og6EC01t2gTRSBYcCZzgEDLiU8/JG8gAKqBYzYDQtIHAAsM6AJqLuQtBQUjwg9W1QUMemgPtH6Cin7I2CNCAO948ThaRMqqVh07WyJZBGFxNyYi5NDADFMBaLl31pDVxfWJCFGBiECb43NbJMnwUjQ1xyVqwkhUUlRrE0LVB3rgVj2MZPwndovL4P/g4vLS1lg8Cxa/+FZjNDar6sWBC8SAwNBhQ47mQ/JgaNjeHi7rKyECIFQrAGBsyEiM5FpyBhAQMIk2XbqqNnZJy1tZ4kPf9zQIwINjz+TMTFQEAEEQH54HHZCqWRWThiVCs2VYWCtgFQ0RjVGBDZumaRkWzXYfCa1Fl+riVeQdKSiKAhg6JDZkUDNzqEpmoAhKuDwfQjWZS8II6pSZOCAwGJiYSdVUikpGNDAQqcjRvAPRpNVzCDEe7u9dBHKAHnOG73/vB1/84cvD/SQzOEdpns2UnGqpougIwUCqkVMmYqSSasnKiE+/s4thdRrr6b52XQ1KqpUcIwIYOmZKWNVuDiMRBA/D+nazWT3a74LD1e5J7GmtXa2euGN0q+3Tu3f31XLJcx2PPtpu8/HTYd9tPnn+3dX/+W/+w7qV+pWcA8lYs2m2imBMfogLEgkXlKP1t9oXe2GiNwHw+y4cggFEF2RpTi3Vg6IAtMqY0RNgM8632+O03e1KTtB56iOPwHJfZiikP/rJn/zoZ99/+umjb199cSN3Xx5fvTm9peDZrXC1QY9MfhSj4NhRPc/zPNYsgXsl9aje+Tnn8VSibTjE/RBvvz2F3qtZxWoqqmQmJWfn3HrVI61CjKWqSvUAcAYKtSNocShJxVKizl24aWjLRAc0kCLLWtb2marGTdCHBsAtPplArKrK+4aKPexLZtoQeVgg+CWjg9uyYKDavPdaPDPgQr5f4hjAtEWjVwImREYGICY2ULXWOEdDM1IkRCImSjOQtj23gdQNjieHy3oLAGq6RP0s1SCCMSgmrZ5QU0Uydrbugqmu+tV2u72/P7x587IP3Hc9VEcMbE4jSaXxXO7zqFAic1x5b6Fm/evf/s0fPv/i9oc/LX+iz1aPn2+eDbauUITUE1/F1Zx5KmWo4fn6o3cv/5/wdFUCcdzcHt7sXZdFR1VBSufT7TTOx6mWslpvd2W/BSuqp3k6zaMUuP76tg/rzKucTr/7wzf/+cvzaoDdbvDD2piv768rVHKorMAKTsysakZk8oZkOc/n82maNXgYVp33sFm5R/veecxplmqi5Xw8nY73KjDG0nedGYjUseRuHWIM4zRP04xeHbGI5jIh1qurSMzdgNvdMKw8kVfD+TzfH8fjaX79+k1RO53sMEFwsNm6dU/MXgFU6MXjdfR9F9eMLqU5TWOai/cQfNjv7euXZbh5+/b2pozjVb/70xc/2Pfr+JPu9PTpo263f7RL43w4nlSrNG/xqZJYF7t9vCK11epxP2wAxHIGUvYh1awaxrNu14Nl9m7QOjkJbLFKrWpZrGbQuTgPJgpzLadxNo19t1qtiTCi3663KZXgwnqzEpDWI6lMvQvVVCTPBqkUYoievXmolQF9YO/92vWOvHdeqhpYpN77GHx07Jid5oqOqmrKZZ6TVCN0IYQQvCLknEGZzAGSGaQ01VKZLRZWdefTWRWabbFWWa26R4+2q9hVVwyFHaU0GaBn9o7iMKziyqO3LOk8TYdbBMxzSqmuV/u7fCKFzodhHV++fPPio56cDy7stx1jRRXA0ne03+377bOf/PB796ebXM61zLhZZ0+o0DOum9vZyOicI09ILSjJDMABIroQruF+mlNP3Wa19d0wyfz6zc3LV6+VqTIVLWxOsVhXJJ1tAkboAvZd5537+OljKRPAbHpGmK9i3G530fc111LKtl+b102/WQ+b6PqnT79ztX3sKGg1Q7o73xqRCZRScxaHqIgp5Tkp5mm77mvOanWstSL9+//4i5zrze1NyalkvbkDRvAONmv46Onw2fe+v9lG58yMj+f55be394exViSITIwMYCUG3u1W2033Z599t++6od8G7EzZwcrB4KBj7GqC6Zi8i/v9IweMaswMRiJaqpjA6+trAFQ1EVgIqRBUfRFpboxff/3Nr371t3/5l7/4+s2XJIAIpcKUAQTgGsABeFiKDgZwAAjgATyAASQAgycb+P7H6//mv/3nP/zRD7b7bdVyGo/f+/QT4uYvUX10z59+tNqu4xBi8KmkB2IdtjQQK2iuC2637YPfOEyiNZd6vDeOir48e/J8WG92jzefffodgPn19ZvQs0nV81hzjtvharfZh+09KLDLUDigDR6gjsdcayoZTcUxpALMwNRKaBATMgIzq6YVUMUjGrKgGVSzxdgFHtopAIjmXEcu+EBIolJT1SlBJe05vrk9ffG7b59/Z/udp0/vru/ub+riF1MhcOijV1AiAbDNwOsumth4msygC4EJSs5vXt/SCrzjbu18oNNxDCv0K7KqLnVwnt/dvXv1dv3R0zW4eD4egu+medwN23W/EwUB9gNLPfpomw0cjqAVgKDqFLk/nhKhW8Kvq4JhHzBNqaSaxtT5nhHVas2ACrXoJMm52PkBmIuWXOYitailXLZXz4lLrUrEBlbmbALFIBdFxCpo4Iipqp7HmUkUZnbKTIqWBdpMRouKLud5HKsosActdT7PomMfIMSa5MzYb3a7rutB4zoOv/yr39+/mt9+OR7e5Vogz4UyERAoMgUzQURwZiJq1mhUiIgYSFvJDATcjt4CtdUisJjAwgWU0kuh8lDHXw7QC0F8OR0xktlFtvdBBGxTjwBiMwxLtSC1iuVCnyLkD7xs0cCQl06+vse/QAGcELFj19wYRKqCAlvrXtPiQgUXvcfFdwhN7MKJ+bB1aGDyIUWrHQsByVoc+sKcQBYQu6BbAACyPJEtnhK2oH4PHINWMOulyb68eoTGzljklhc/+2ZrwgAMqB60qVJSa9RYqqDw5tXp3/6bv/jff/Kvnfv2+eNnh7v7b/J5Oh9rKbFz/QbBVR+rgvRr2+5WpXY5WL8FR65fIZCSaYyeGcxAlNJUmFocYmtxekAlEvYFKc9JQ1fJJzUkKH0PVfN5LtOkVlq6ETgfPHVjnm6vT29epvEWoPbe9c4LsZaSppScB/I8T+V4mqapZDGoYIJlhulId8e86WaGKc8mUpEgdIQOihTJVCscbkZGYggOsSRJLHHtwRhUQuB6GJEhdBF8vj+94yA5zewgdtGA6rnWhA4M+ezCdH93/dXfH/7+N7dwBCiVPAM71TrNGZkrVXPVREwVUUxQiwFr6y+YNmYfmiioiqCZoS5+NuhVTckWnGoh3VgjVMHinasXYso/GGtEjdaCF4XWB4jmP3VZAAVUtX6zqqjg0TzADHGNb28Ox3oDa9hue1U9neZa07rfugAmNOZC5ILH42HykXUuBipWXKKuC8N6ve5W5ViBIJUMida46mJnYlmmClq1qogp0Botmpb2Nqb1pnvx4jmg/O7zX9ciiugGNzwK3dZRZ6rpWOZcc/WoHX316mYV/cZSxlGLvHv3zf1shOAcXO2uGFlTHaea5nw8n+qpJZwBOfDOeQjTODt0kYcipQ/9ZrW1onlKUpIWZeAqtZR0vj53gfph6LooqbJ32VJFIF7SAJEF3ELFzGWKHStUdGAVqix0GTVSDDFENM0lVzD0jABVlcAwOCJWsVrrJXzwwTZm+YYRgdqpua0K7R8iOm9qpirQUGRFcmZWS2FyzK4ti21GOLeIkbWRuwhMoZ3d2gLsiOkihVYDMlIjU2kG7G2xAUVVMF0QU24m1tiy5s0ApHmTG5hVRAOQ5c8WA2xcgj4Q5EJuRTVsC9gipmzMirbkNWrYZeWzSyzrB644H7KxFgaWOW4EkebvjahNB9QgM0YwAjYDREWQNmFQkQSpQqDG2NACikrWxMDWuGTLy2EwepDeXShuDkQq8OWVigCiKbTkiWUCP/CTHbR0O1VRA0MkagyvxmIFAWBFAzJsyiayluix7ACNpisAVqS6AIZqH852NAMENCNQACbkhvgAmkqDXwAZCYpmz4zERmgE6AjVRBUcKGnB7NiBQ2NVjx92aQxApQArMICCOSDnVKwizDV5xxyVAxJVY6YOCPn67e3xPDO7UkVrJrTGK7W27BFcLNXUDKoWJHt7mzFot0LvHTsqyeZp7AdAQmZGZCJfxUqt9WyqAAxTOXNBYDXAzaavknzg0MVxTPeH85PHXrH3fXShjtP93emt77qrfbe5Wj9+3v13r568eXPz7VclC3Dr+TATeqkAKdfIthQxdoFTl57RpbKRRVEKD4Z2LabQBC88vKWF1dBdM4JSyzTNVacK1QWYc93u+iy1qHkzQJ7vAc6wfk6f/fA7f/bn/0Vx85vx9dfXX9mKJLmb092wWW3CyjxIrdM5R44eBEwJEY1b396xR8BiBgo6myTr+tiMzxGAHYuUkgsQoWMDmeeZBhLFWqVoEajwDAaHY4FSQcQQQKn5ebWDZNMqQ5P9SllMFi6czBY3sJA2l55fuxDTw7pmBmqM1LAr0QUiBLrYUFyCBsCo5WouAkNbWuYXevEyF9TU5P20UjK7xBc0WF5NURvYa6aky2rYGpgNMG+rHdClShOT1n5XQjM0xTbwli6WFk8hei+SiTR6GoJfd0DIeRrvb5UQto988D6ECGRTqs+eXY2H+9PdOIS46VYBws35/Mvf/50pfv+jT4d+DZ5rztkKEvpC3mDDnQueY0/VnQ85d+pXLs92qJMRFmJwbFWK4qFqERUREmCBLHKcy2FMeS6vru9ffLS5OZxfv7794psDMITe7x/vQ98bY8pZSRREs07z+Xw+NcJoF4fYuTwnkayqiEDUDuEafGEqpjaOlRxKLedpThVEwJyACiCUksirYa2WqiaDhDQAVgANkcxc1RkUQ+D7u8M44ma9R3KH+9PXX797+WpCttABOxgieAfMzsyktMWWuhAQvCqUnE7H4+FwxwzrrVuvgwvdD3786Gq/hyqnd3dzyn//9VeYpkerJ995/uxx3D15/DitSq5yPB9KqTWJE4ocd2G7jdv9bt/3HXlOaZpqvlgDhtDtdjtaxRCZVn0/UwdC45RzkaJ1rjUnoSLRdauui+A80DgmLTAfR2Qm5sBhs990Qy+Wcp2qXHrXgIj0y1/+x0iOXAEEr8yAjK4j11PsYx9CCD70MUpVNXUWkRwAoRExD0MvZrmWWgsSdbFzzW7ZMTOv4qq51NVqqXLKVDMiapUkAqou53nBh00cd5EHz0Gy1FqHbfCRRNSQUMyKsNIqxqePdgFI1dh5FoNUe8eaQRUi46Ntf7h582i3NcTovTOtqRimGOnJo+1n3//4xYsnDjUyWoEQ4qoLaY7pPFIVKhmNIUvwIbI3AVOsRbUKArLzzvGwezROE3cdhS5VOU/5+ub+/v522D3q1t3+6pESuEDR4daH0JkpR+4HvwoceqJhtx8i5HQ4H966XGScZ6YurvaPnj5/+nEfh+1mv+rXhD76noBFjBHIu+f9foZ0ezpc37559ert6f5IiEPXVZ3UUt9jqRM7Fhf7/e7deAbz7w7FCopA7EAFOEK3grjZCNdkIibjlG+P802ezgrVHJIhVJMsMmNN18qrEfP0NRsQBo/R8+Bgg9qTDJ7XUng+CSrHMDzZPPHoS6mqIFWmOeWc/+Lf/QcETrnMU5qnknOWCnnSWqVRSkuu85jRG0LMuTYf656x7/q8U0K6lEOXeNd2eq1oJkIqUg83+qtD+urrX/T93zBjtVLqbCUOW95edbvHm48/efGzn/30T3742U9/9pM+XK08IFCFjGCzzojm0DCm6Ot+h47ob/76F5v11XobFA0ZAg8ewibyZy8+3W82N29ffrPq3t28mdKcioy3EutmvV2tNquB8PZ4REcEjpicY7Mzzo0KYMBoakykAi3uR4RMrZmCglWtuYkMUIyBCBm8adUWDkSBEFBFFBgNxApYqSgFRc18XJmBGB6O4827u0+/tx36EMN5nqFDMNcHZq1JaXJu7qKuewqsc6rzOasB9o0coUVKjO2kn6uhcBp2MQ6cZ0GjmLGCff3qzWYT1+s9exvHklP1IQyuSzmnXIEweIodhdh1Q5ZC51OdJ3NBFVLwDnpfxKwqo7JDNctzHse5Xw8OimKIDsHcmEqtJQw9clBj1GIqRMZkJJeDqJiWCgasyggiWkoFMBEjJud8lZprZichQgzkQvNkITQG84quVphzTSmpYceOwRjEeVgN1EUkLHG13Wy2oHi6Hw8pvfzquhxdnk2lVbdAxCxOTQxRVYiMyBCXWG8AQvVoHhDB5tY5bhU04YKttBFuF8OeC8H7Ute0SmQRnQDAgyTwcgd7H0Gjl+KckAhgOWgtXKvGZydtEo3LwQYuJIYmT4XF1XYp77V12gguzAEANL64IONyfNT3r5wAG5OA4B/TWz6omP7hlc2EZOEOXLiacPnZ/kzxgz+AxSQCwADlwRb+0r9/IFldrrb3ty8gGzUky5lS84o1rD5ATgAGN9fnv/zFLyr8L2h+N+we79amT85TyXlCHmw0lrO3yYwUYr/aPIL1vRwLGJH5zgyqiYZAzpEZMUFRQG4pB4oOAEy1Vk2iY9XMHvoBYgfsgDl4Lymjgc1VVK134D0wEzJXsemcxhFAgB05z0QqVqtURRCAUsymmkqZk0kFECAfum5jRVKa3n190qphBX0fFHO/8qYypzFPWDKeznkVe2IHaiXVgqY9oFmpCbgSAQaIPfpe1OXT6Ywkq613nqUSCCC4EIoPCez47t392zfy+mUCCY0tYcoiqibEViwBViC9EAkZFC+ZU6ZqcME1WrBZ41Ut7vy1Aqoutf5y68PXTu+/8H9qqF0UtBc/2gdhxT9532U0tt9zyVInjGorAASKpdoJhnnX87DucynjNILZahODhwpIIAIECKUqd02bpaXIWJOaYofAttoNz7/77NX8CsU75VJyzSVZFq5K2uzwoNp0ziAADnyHJc0vv/k25/T29c31zQ1HZk9XT3c2MKSccko1ETmKofdB39wdc5nL9ZzHoV89fvZiV+rhcO1cN3RdnkpKqWTJuWJdghuDc33XRe+Px1kOCl7jxhnYfM4dlehDHss0TTULGCDY6XyctTx9/pSY5/EMYuv9enp9zgBQLpgK12ai4j1AFES8P9+VcvH1Q8DgYz90w7of4t31ddFsaOQIEaAJaq0d4BRxcQOXhWsHsHDljAFNBK3Fl1nTXSuhPeSi6EVVamZmogZ8CQUUMRS+CJEXeMp06Q1cTmkLk+QSXAhgTdtfa14Yn7YwTRRBCYCQabHoW1YzQ2m93DYOG+GzIV9L1Kpra7AhaJPitQc0Q+PLeKQmIFrAuw+X2Ys88mEM4we2zu/RfgDn+GKOCGIqCO7yRGAtfAwRidomxcvkQQBTlW7dMbAZaFGuTQ4IhtK2JyQ2FCRrusrGnwZY5ILoggBAS19Sbd2cFi3atrOLzg/AQFRRwEwRgQANm0uPGhEAECAjEnkVMTMiNANVaFZaulyKqZoKRN8+EbkgnA8BIoZAHpjZBWes0nTsCKTIRkgOBBSN2pZNyN41RBAZBCsFpkCAUFRVDR208yqRr1r67bA69KfzOJ0LkBEaB2ZHtWRTWV9tx+loqo+2V58+ftSkqJvV2od4OhzPeSJyTAgsZIZk6Bx6V9VyyVoVHXLgGOB4d9rtP3r+nU+6nu4PN8fbIzqoqs6FEJgQfehir0WmUnRYe3LhdB4NkDDOUz77KXbsglfVu7v87TffauXtZj9sNz5gzufjdH1zuHYUum7zP/yrf/bm28Pnv/v2d7/+9t3bKd0bM8d+AOE0TSLTUsW0sMEFitIPTDsv9KyHTZoW8mGpydQW1f9CKjID1mrF6jznJlln5EBQk2DBdJywiMzSO3j+4/5f/st/9ef/7M82V8P//W//r7/57X8yb09ePBXFl9flMcz9dooBppSPp9PsrURMpQqgIs1TZvSeXS21FmWCcR7tBp8+fbLZrXPOqoIXhqHreNisEPE8Hs0M9NikHbOM/9O/+Onvf/XtdLonpKkUF1yMUaRUEWADUzM0baeZJgyFNqOJL3O06gUTWhiRiMiEIE0+coGk2AAWJfx7IAoFm1r5wrQEg0v/zpDUFA2RmWwJm35YQ7WWoqDOHAIRglFbNRd6fZN5oipeHpzQHijNlxRXqMvXu6CQl4IXAUTVnGNEZOeY2Xlm5i5ur/b7Vb8i8KghsF++cmfdOqy2PXsc0zHNper6fsrzOOmOV2sPDtOcvrr9NpX07atX1/d3nzx78b2PPrnq9gAmkNW4851DAigfv/j4tygcp2IAACAASURBVG+/PEwHX12t8vr6bVyteBiwFcQGRUEUq2IVm+c8pXQ4nm/u70+HUdWt1uvpJJ//4dWbl/Cznz/ebHaPnjxi4ppn1apqOc9zHk/TOU9ApOYEvTGj1kSonQeHwB4dWouYrnkCsFIygKqq1oIGjEBmVgsSAunjR3skMjV2zBpSSblISkUFidj5HpHEYDWsSs1/97vf399JKQAM6w3EsAnDQM6JqrSUgDqN0+n/Y+zNfyTJkjMxO97hR0TkUUdXHzM9HLLnIrmSAEGQtFphtVoJkP5kCdBvEgQQ4O6SQy7nYHdPTx9VlVV5xOHu7zAz/fA8smquXTkaVZ1ZkZHu4c/tmX322fd13dYRF5H9/fF4nHOGWgERLraA5AzZjKrB67f3ZZ5hzhGonNLxLt3ennKqYhBcvHx6zUDb9OxUy3JcmN3l9uLq4mrs+xhCKuk4HeaUU63MoIKh7y+7+Oz6yfRwP8TQdcF5LjXdKtWlLiUtNZecSap3jtgFF8dhF3xRBCRUsJTzPC855Vyyi6ggIiaiptg8hX/4w89ae1BVCNH1ntFQZeii9775zDp21BEigXBrnRI6ZscOpuUkRRxBH6LvIxErGCF1XUfBHQ/Hmzdv9tOURWqpCOA9o1JV7IYt+2CiwYcuOufcYZ4ejodlPuW6oPugHyIzMnkROR4fSjGE7sPnz//i+3928/IVAp42y3RKPnQ33Us17BG4FM51mu4VQeN4dTlcXg9Pn3589WR7fb19+vTi8nrz+Re/SGkCtHHs+r6PziVkzUVERMQBdiHG2EnVvJSUUloyo+86JoCLzYXnnhlqkuO0f/vw5ua7Nw8HGHd2vdsOw3BMcyrZA8Z+5zYBzZE6Buc5/uZXv/r4ww93HzzdXj1/+uTJk6vN9ZPnodt6H4ZxnI65pHqcy7fffXX75v6rr7756rdfff31zf4EHOG7NwA9gIOOYQyw64EZkMARLBnEgAg+eAYffvpnF8vz2/2bmuPbfWUE5+GzH3xoVq+utt///ounz66knN6+ffvlNzfTskzLUo1hQNCFfcfswCoaM4yEICIGoxYB7NAPaEPOXjLk6TQd9lpdoCEt5eH28OUvv/jm65u7B4AKQAATwAPAEwADqAAKIGel4bhuYqAAAfo+yqI5FTAgNlMzsYWLVfqdWtTOPKz2PVoTnuhiWezl7S0sAAAQATyMV8c3e8u/BjgA5J8D/J+/U5p8CH/9Xz35l//d//hv/+2/+fTTTy6vLtEYQNmxQ/vv/4t/PZfD7d3t65ub03IKb6d+120u+qebJx9cXX/8vz5byvGrr3/zqy9/9d3NN69evxq3mye7DpmOUnpHMQRAL+aWVAJ1x1M64OwIANB5AXPLLFJx3byQgZCYzLslL8SwzhUwusDOMRjmlM3M+VZVWpGk5hQVuTYrHyCWaiUtkf39ffl3/+7vPvvsfxm6cejSw2EiQvIkIst0RJ/jYMMwdDFK0pxzWYoxeNcj+porITkKpcCyZEiFmcMwOEfgtRgC2HSy0/7w9OL+6kcfPXvyg5vX3zAiGRhh6DuxpGSb3UienXNErmS5eX1/e/vg2I+bEkMoCaqWmjBwEJmR5GF/8G/KT55/YjgD2sX2CQDm5a5kAABCkqZHSxRDiEzstOSalrLfT5IKEjSei62EaiBufk+qWlSFANiBD+g9ARpzrAVrtmXKh7meTtNpqswwjH3wPgTvIo4b5z2GEK6vnoYQ794ev/7tzc2308ZtSyrLqcwnqLmplwGYqFXRCs0mjQmkDc6CKQMRPFpK2nm44XFrt7WEO0M3/6ljxZes5TYrMNV8/VT07IKO3OotA1OTqti0z88/Ds3M6w9/12pkDkB0boGenbNE7PF3AZppO4/WPET7/bdqff3f6XQ/ksr+GFqwXlHz5DYwA+Y/8kmcQap3xj7vf9/OQihggCuO8W5Aoa2O95lsAAYCoAhGLV8WAO+dSHXob+/qzWu4ubvtu81ix+127Hf8xW++mh7K8lB1X0OvMRV2BMqxw67vYFrQjWbiHIsouhhD9Oy1mkPPvgI6A2lQpZhpLfOSllyywPNnwzB03jskJQIDBTJ2S+ACBOPQBQdEmHNeliVVYA84EgqkemKqFRIxheCcZ616yrkaiIJlwED9JjJrSnVw3c3XD3enhz//4bMnT5/C/cvri6cp1dkEiqIgAqiUItXEUqpWT4ToHS5lAq6qEBicNyJgpv1exg0gEAKDIZF5z+MYtpvBUff5P//q1deYFvYummgVaaAnGGit4FdFlFborY1kkXXwQKxpY+PvIKCrokgVeQdOrbd0ZZI80vT+yCJ7t9j+8695f+Ws+AGgcVVJzHB56fhJDYFCR1fX29CPwJzLfFyOV+POOadSa61IyAjE6CP7QN6xmJYCkKFwEucQcRi67//ZJ1/9/bcIiYwRoEIpWt7ZFxCMl31KuQv90+vri92FiHz1+W+O88lD2N8d25N8fDgNz9FvzIdgDOwI0aTa9//8cjnlPBWtupSUSvVEF5eX3kVCfrN/ezhmECAAQtf5bhiGoe+8d4howjVLcGG73aHZdJxVdZ7TdFzKXAAacZ5yFejgYnt5OJ1ubl5HF8dhKB9uMVtdSs61mpFnDBg62G62wzjOU0paDQsAqJgZeu+cZwNJaZnSUUUCO3aMihXAVJmIyClWBofQtpxH5z+DpoZslHMh0+ZcitDcNd8TdLc2JYem6wSiilaqYGCm7NUqmpCwPMZZA3s0OV3BIEUwtGqNQ6ViAFirtRbbqvAEYARKgGRKyozG5x8Ha153QKYojGhCZ9JgW+XvEKj173cwla5cUjQwo/firv1pHNbeBUw403MVANzajzijve89PKYGgsarbDOesTsEAEUFEw6ubWhIgK6dILZuiyFgGzhCRG5s98YjaYAGeQwMqtZU7QhEVkfCdVrx3Pc4j/o1oBoAmLCowBljfCTFwbp5nct1M2IEBFY+I1VsjOzcKvrTZHpW0rNiG7QgYs8uuAql4S2PymmEdN5AFBCMaNV6Ml2FgRxgkx9fZTDOjiJETI4ixU3stjFp1ZIrGqEFHzh41SIgy6Jj7wmBwH771VfzdExJkbgcF+r8+j5NQbEtMEETg4ogYAbStv8Ex6vTcrnViq9f3by9qz/chmXJhFKLeQ9m6FyIQUOQYdiI1JTK2FMInZmcTieRgEjDZvPsA/f55y89U31m4YOnwzBsNrHfhNM0ffHlF/vf1M22Cz29+OSKOVy/3H/+q9enuzQvGFwfxjBPhybgAo8IBuDqpAewPrrvtnBaGwqrVpSs+zQBIrbpcD2jPA7YuUDkY2AfCKtCsSVPMiWv7sMX8F/+7Keffv9K8v71y9v98ZbQvX77qoLs5yMi5KpTKoZcSi2lqmSGUoo1W6t5sUAIDlOqpSgzaYZ9Pmw2m6vLy+PxtN/va6mrSSVTjIGJpUzznLoAgFpKTin95b/4F7/94jbLXQxBTPSxwQhnU2p93ICaFer62azZoTZ2FpitO54AONfA5ffU91rOtC5vONP9zNRaRvguZsH6ebdhUgQwBGJSNEJoAhPnN7TmskBkwISrFfrK2m9vrs2udN1EW6gAWw0jHuMsmAF6QGy91FXYFRkVFZFD8M4hokrVmmcrJjtwFKLr05KXeTkcDsh6+ezCCLcXQ9/vQvBv3ryeUyUXne/R+WoKkR120tOR0udvfnM332eWF9dzRG+zpMPE5IaLXdhtfvazn979w+nu5e3pYQbWWpXEUhEkAFUCKAbMgZxXgFRkKaVWBSAiFwfebUdLggj9Dn78488AyHs/p7ksGVQBtFapqTh0u5HYsWNnklOt0TEMMTCpKBAFDsSFMIEWQATTRvpt6h+M5DyFEJhIwY+bTXP96IdxnvP93f407acJQGG7HS52l1X0dFpOpzdAQDxeXmPJMKV8nOdxO5aieV5yLSJVpDqnm74jJEAuUqd5Pt4BCECE66tw/WQYNsE0PRwe/vq//au3b24fXt+h+Z686dLNadwOm2GrKPd3+/GD8YOnH/bTcn+aMpWu6y53FzFEFc1zmvN8mqaUF4UKgCKA6g0xOF5KjiGYAaNj8sHFwY/MIZpIVw8PN6ZQihBhjHGzGV0I5LitwkYzNDQgQTYDEtFatYgC4H5/IEKB0nS/XOQhui4GJlSRtCzLskg9eR+8CwhsSoTkQtf1nZwWT6TOgffOe3bcBn2JGQhzysfj8e7+/vZhn7S6praHvY+oCNura1BVKcwuBHc6HN/evi1pISazfDgtRNR1HSDmXA77oypthzD2YTd2Vz/8VIrkJKUIklsOD8j+4uLS1DZRJPgQu3EYrp9eXF3vvvfJx7vLAbDO8/7hq1eH/Z2BhuBXdBtd13UUu5Kyqnnv24ykgAmT1KlkE1RGRVNPPjpmT2Ca5pKnAlo3HQTnPFHBqqWk01SlxhAwMAJoLQZsmH/02Q+vL6+fXF+NQ991YTsMvu9Oczqdljdvp1/+8tf398fTPptATvX167vbtw8PexCBSPD8Q1+tqppWkAIHwBD8dutcpBgmEe17+OB7H/nB35/u706gNVEH4+A2mz5T3W76qxfXu2cXEOzm7v7l3d3rfZ7nlEVcJ94ToC6SqUL0cYyb6AZSpmK69B4Ckcsz7adyuDtKgjTjm1eH+VQC9aXo4e6UjpMDv41FPSCAOCgd1ApAgKFJOAAimGAtRo4AzASt6nxMQIAEseuCX+URtRozr13GJrr6nnjru8zNQIoROO7QIhABOUCCeW+Axgx0jc4DMaronGsI7AOzs28+P/w/6T/83d/+ahiH58+fPHv+7Ic//MGPf/qjjz98fvXkKXnnLsfL4YOsucqS6pJOp9mS73AIQyT34bZc/dWwnz96efOyiBSVm9vb6f5t3FwAEboA5D05SRXVal0cIyBHj7mCCixatKICgDKSIyQAQ9dcOJEQkNE7dt47Ih9d8xWqtYI6VJGmDoaraAOh02RgHDGKuF/+doph2G2uttvl9dspF1OsqDbPJ2caOiTD1px05DabTZHaxy1CKKlIVgSvUtNSzIAd16JAygimmHLjWsObt8eL1/d998L7waAUUSo1dn0cSaX26Nl5RMy5tLzPMXeRu87FQCpFdJkzbC43aQa1ejxUpAPRDwA8k+/7kZDv/SmnpZW1WSTnZF6ZGb0Ppvtjzbkuc1kmQICuhxAgRtdFj8hMlHISSUjWR+4G9KEJZ2rwvqqfUzkdlum4HA9tJgWCpxidd+A9Bk/eYd/3w7jhEA6H5dXLu9vbaZ7h40+u57d3y7zU3BrNrvVfoGW1SNgISGCIaKstWkOTWjqgv8OwegR6EJAA33OP+VPHuzGQ1iZvucoZoDEwQgZYNVXafUbGxx9UNToT0dd5xJXPhedztjOzqsmfm4rI+1UQop7NANczOueja3lG6z4j61s/PqwNf/j9CzT73T8brs1//Nrb+a4ncy7a/uBDO5/oY9119vc6Nxuhdf0fc2sCxKaJlMwqhKFzKKf99Prb22efRhU00370/QjHpR5uZVpKv/BgFCIQS8DFOddHMKVcqmkB0zbopGKmSOQJEYwIqZhYrcQizR8NARG6vo+xN9BaMzGIyJJAFEPoAIzZkwN0PostpaCH8YJIuvkA5XjSAfohdEPPjmstS1qyNDqcgYfNxbYfutNxqgWun15Nt8f6AK4Ol5stExI4Juyjj85JxlfxxgqkXERAM8yW1e48U1ZBhnED0aPzhgTYZFwRzEgEzCB4j463234cxhh3L1/BfDL2kdCVsoBW4NXtEJAbBgpI2JJ0M1WQR1Wj1upYp6zeleZNUaXZWa33cV2sDRp498r3i/Y/fHx+j5Dyh8c79OpcBYBp6FwtRF5jz5srtz/dz3kKkTabLlWdTpNYHYbOBz9PSymNTQwA4gKjCTEzskRCgi5SjB4ZUkldGEAAHSxliewwAgoYAThoDKycUwz9dtwEH+bj/Obm7e3d3cWw7XZdsEVZVaAede9sQAjeEVAtkktZlqoKnrnvx6EbvYugZKVozo5dTvUwZUgACArATEMYtt3o2WuVXHKeCxgs8/J2vgFFF1x0XZ4WUw3eMztr3T4GA5AsNdWUkpIiy2YzkKCNWmrNKsaMbC6i7zrfR3Re0EoqYFCr1CwAILXmnKSKVGkRwHlnalLUDImJCNgIWBFJRZkJDVajMmukKWpWJy2MnDH492+svgsy1mCjoohgDCjQjOSogrU9+P1obG1jXmXNFeQcRdfpb13j1jm8YQNhjUBIwYCBjc3MBAUBkZpuFIqZW4MSrnRSWHlIq0Ry+1c0wHWWEc/zhY229UdYrn9iPb+/7BHRSRUig1V92ZBXjM5a68XAzEgFgFbRqUcCI5lgWT8LNGUFRDICIxQxU2JEBgBY2WdAJqZioIpk6NoNQFICUEBHaHY2kT0jbKbOVud106ZXBURWTcCUiE35EfACWCWACFVMWqAlgnWvMwBo1Ugr5BnQwAjITAWsbb1ACA6M4Wz1AbjyuxBwFad/RBa18UHdeYLZIwU2Ir9KjjRahYlJtXp3vF9goQ5cpowCWhVKRej6KMq5ZgwQR//0ydPrp9f/+ItfgmFdCnuL2zGladVwo/ecHNXA0BRBuEnMOfLgpGabD4sNzvM49scYx2WZzEAVVZDZxeARWFUQXc5Lyc1eJDi0VCaxFL3bbLaXl09/+U93x6SMt+MYdxdj15gxLvnOKMCX3/6i46tnz7730cefPNzmcfPVF7/45tXru1RzoL5l84+bcwOyVB/3fjynBPSuA/VImEVbH9l1ZBJMAeqaNGkxMgA2Vhq4P+3vLddcgCMMQ/xX/+pf/9VPf9Rvx69fvvzq5Tff/vbLqS6I8PLmJffd02dbjOy6oesdo6UFmmWmmIjBvFhTT0ha8lKhNoo8QtWHh/1HH73gC65L3U8H7IEdGgiRhcghO4S02wyCaX94uOx2L148Z6RUYYjovVtqqbU0BdTmOfDoxQiGzr27dAMwafN9jzteS8IawQnOYDoarlTjc4bzXk5p7za5M3gFeO72gyGgruGFWqMP7TyvbCurXVRbPgrYRqeRFGCFy9SoOZau8lbrwG6LLe9SwlXlC5AJm10VPY4fGCIRkdQqNYOCpQXr1AerWY/38+HhONeZPACeQCnN2fcOSch3IRiCFYXjnHuPFlzXd+PlZR+HlOvXp5f2EivqB7vnfQzLUdJ8LAGvdvHjFx99+vC9Vw/f/eblb+IYgutSllOdjRBEHVLNMnTBxwHZL6nMU6pVHPuhB1d46KJs8scvNi+e49MnF6dpyaloLSq10X3JwDvXedfHjp2TajmnlMvF5VZX9w0VNQYGXJBcCE5VVYpqbV5ckSh45zx75513zlFRMQDnfIyRXDcvMi3mnI7DZhjGUuF4WkpRRBCrpgzmrRkhuE2pcJzmlEtrsjMHZhCzaS4qJhW6YetfoIqyh4tdP2yjc1BLRed++8XN/nAo0zI6Ru9ciLHjLnRd1xO66TjPm+XJxZMwjhu3q6PGGKOPFXSpy83bG7FcNAOAguYikuUwTVprdGy59D4Ex46489317nqz2SlBVRUtN85vdsM4bn3wAiZSjAAJj9M0zdO8pFJKqQVIfWQfO0QUaY7s2HedWtOb4KYVIGpSBWnt0Eity7KkOTkXmCMBRx8pUB/jMkHnnMOViqtg7XETgzwfD4fD27vbw7Sfc84CAJlzzVWLaAjuww/GfjtIrSUXRZ5SvtvvuzDuhqHWdJgWVd0pmOqyJDQbYtdFLyXdv00fXj8VsM1u3G52FxeXV+Ou6wdAmufl42fPmIk9EZnrjTvqoi3zw5JOaTlVzVqKoaJjBCAgTw48E5hVQ0YG9c57DmjgGBx2vgncgbeKJjiEcbMbnQdHOI69od4d79DhdDju51NKs5ZCCgjKrMF7P/jgI5P7yY//cjtud+PO+VhKub99OLx8++b2/nA8Hk+nf/rFL9/e3p+mtfdTC9RCuSKAiWDnsAqoETnvfOy7yE6qT+wAHEdH3cBhF4XkeDwVAB/h+fNhuxt2u12M8epye3m9WyC/fH3z5Vef39+nkkMGMibHwIFcg+04jGEb3UDW1QSIcPh6TooplcN9Ptwv86GkVG7v3hwPlhKQgijIBAwQ1ljbrL2aeMSaYYieu4RoyAgCAIBMyAiKSGggWqyaiBoAsmNatWpQ1xaDNL9rREBGBBRTUBBVMWvN1SoAxQAs9GGVTTWnFfJc1NQFR4KYuBbbn+bbt5+7EKsmqPD0evvjH/3kpz/7549ePP/+h0+6jp4+vfr4ow+vn12jl5Tn6rYEQqoBYCmnD7YfUtweSrgc+v3pdPdwX6akT1+cUjLiNp1kZB1b7QyQ1ZjZT8e8JPMMADUXQyRTBnIIrGZ9PxCfUzgwRiIGIPDOkeIypwoCDhi8ARFXw6qgKggiYB5cjxzQEsxg4rab3dXloe/eiEKpWYUBzDE6IuZVCN6NTKM77KfgR8JYyzRPaqgmVEQAMS9Za0Fv3kdPgZRdAB/17v7wq1+WmvKPPvt+ztM0H1Sr7wCdk5KKqfdORE6nY0q11gIoSIokyJWduAChgPNmQqJZsx6OWnL1gc2I0HkfYugWLiJiUlIp8zKTctc3tz4CqM75GLqallY/E1IMHCM7F7wnmiWl5Bz3vetHB1jNimOMsZsX2e/rw12ZT1ALkMOBqe99jERsjix68oTBexfCvNSXL29fvbyrGa8vdrevTvvbnBZg50KIddKSKwgwETMC0rkXhUSkwgZ0NhQ8FzqrJPF7h0HLTxFR1ex3S64/cdhj3wveITuPmWH7TksWH3twj4nNedBwbc2du3Tn/PIx538EfEREVddWOq8FIKLRecyLz++HZxEsxJVn8N5pvOM/vX/gew3Zc330py8bmn4DPrYY2yW8S+AM0N4148+XD7DqY+G7Ik7ACFAbjkKASATLSQzAegJQGOAffv7r//rqs2G39d6J3sde+5HkRg57yEkFcdxSPwDFym4JVoRVS81STZXIW61qFRQRnBQRUUSWKhnz6kYffaix6pJKRS6l5HmakVCknI62JHLkASxlAUQ1I0fk2RjQETv2wikF3+fxst9sdqK2PxxzbfOtAIiu85vtSIRaSklA4hsTltX3YdP38fMvfmVATL6PO8dspqmoFgAEDuDIxRCCpwiKTi6fxGHHcQAK6hx3HQFYzspkzBRjDMzjMDIG0O6719DN6+gCrlWJAVojOmTJLT1uK+ddEtxeeN4sHhkicCYoPq5wbNBX4+IYrtMWiPbo6XQmdPzh+nl8Rv7kOjsv2sc/Ac1IgWsxSDX1FF6++vaY7qjvljyfpuVwPBYBdhSCX2YUETAQkZKy1rrUiqQhcgjMznlPADrPp2LZj2H36eCrv795yDmbgXmgAC5Qk8X11F/sLjfDKFnu397f3t7BAuo0H7PMigEYgb1rzKKaUZIULYZG7Labi1pSETkcJ0/VswdVy0UJU8qg4DwhuTIXBGBgSZqPU5rnJS3DxXbT8Xyal/sZDK6eX/e+K5aH2Af2ZpCmRUTYcTrp/c1dqoWcM7ClzDqVzgXvHPcuoBNGNZnzlKXmmom8oZHn1rVdTouKgiEUNVg1YQxXAwZDsyZAs3YBDFABYe31IDXvCNNWjJ15CmfY5x3T1cDO66rhU6hNb8ewkdCa8LAaojEjMK9xZl0xaobaYmwTuUIF1JVcSy3sABnQOu1qZrLKe4EhCSIZGwIarm0MWwfHrY0LNioENfW3cyBftXK0kRia4PkZ2EJ4d6n/P1by+2vezJwVNX6cMgKCxixipXVTeTwAhIiICNowOVoRoVVXXo2bFDqitA9ZuZnugTEzE1lFlSpFoTGjHbQCt43LITLgatwACGKNjlaVFRxAwxnbD7wbswckWh3vDFBWbZ22yTRZlHanTKxV8ogkTdaqzQ0iASogMeB51bSb2gT4oOkMEDMSgaFrjBEDEzUTAEYCcE0NEsATdYwM1dqsM6AiqKJCQH/zcOOIeXQRvLBIMgAokBjAQAXl6umWGV0MHzz/4Of/9B+ZCRA4sHmD3KbODaCZeYBWU1EEhibchciEltRFXI71/v547TbjOKZyIgqGGZCIgoEzcIgEaEsu83ISq8x9ETse89A5IpfSkpa06ceh3332589ffndDvKqJpVKm/fxwuuk24bNnl69e3kiFTb3YXV19tLkaxs3Hnzz/8p+/+fa3rx4ejtqegfZk2dqEWGsaJFwdlQmMVnKjvYNs2gyorYPjjx0tBDQoUJZsUAGEigzOpcMSnIsOn18+/4tPPvmX/81fbWL/3eubVy//+fXL796+/Y6HscEy/Ti6PmSo1jRgDYjIhEQ05zLPRRX6LoBwWpLVBkEaoPnoT3en6Wq5urqoF3V/OHgmBZVaQYXQzMQH2Fxs53J6ffPykycfXVxuxk3fOg8Cvsmoo8fGhMe1zQmESIBVztGuRStqfn7n3e7cqFM5d96AEM01UydUPPuUPuZCDahqix4Mzg6da/ewjR43YL8BvoTQ5gLbY6CmoGZiiARI3Ca4GrfSVlRRsJ5j9Pmd4fxYtXtr7+2zZ1pWi6WEUGspGUFJakGw3m9I+eblzbxULQAKgQNRqCXf3Z9O6bSZumEzhMiffO8ZgytlKYueYEFz3iF1rpDs6+RAjerN8nZ42BCHZxfXuPGA5ZBPx1dL/2T3yYsPvnn10Re/+QfzFyH2d8eHBwA1kKIdoyMaB+99b2aHw+n+4a6KsGM06PvY93EcRsC/EEXTKjXP88nMmNAUEICJFNmh8+QRCUk4hC74oQvOe8fOzKqKiQISU0C0lFJetJZsQiGG4LnvovPeOxdiCDF+9/ZmyUkFu27oumHcXBKPJSuikwp39/vjaWJyIVAWOJ5OpQICEAUkP532cypIFvuIAA2qnqCCiaPQxe2wCQ3nRwIGTammXEWLgfv3v/wlEWyYwPeYJGQl8QEs3QAAIABJREFUZUQ2Aw/Rka9ZpOrgYwydBSNkMATJHtmT854J+JRsXqb9dCpaliVNpxOpffz8g5JLcR6ICd2m3xmZIS41z2l+8uzJ9fXV1fW19+5wOt68eXOcTynnOc1393c3b94sy2Jo5CBEjv3onCdyzgcfIgCklJY85ZpMFRbw1NQQQogBkZgdEUtRkWrqEBQVSyxSZTuMpfolLbmUakZEwblisqR0mE739/fzMjPzuNk4sfmUllSXNB+njCQhdE/dM5F6Oh5DCFmhGPQcfOhTyfvbw55pOqXg2TnedNvoA5qWNKnIMru8ZOarrru62PXPX1xcXV4B8uFw6DrJOVetKtVcFZ32D3dLnlUlBrcZ49tpP83TfDw55LHbMIVaq0pBwOA7RmAKhIERmKDrto7VEROyGYHy0G2vLy5DJMd4qTtkda/w9nB7vL87zKfQhavtJro+um4Yus1mu9tth2F0HK+urkz5bn+4ffPN69e3X3759eu3r6d0bIoeKdlcEB1ahVoNiDBaA+3Nu9moGCGa9wq90qjEpgCFqvOyvd70A9NAhNaT+/TPQoj95eWVdz523cXlhfe8yHT76s13L1++eXPUitH7TTdygMA4jGG32UYfHAUnQ55sfzs/3J30aK/+4Tub7GF/enUHcFzFCloGRQZVQQVAQRSSnEMWYFM1hfquhAU8j06v4jrqwDnPSCRVUpY8p3wuql300qjl5+h+Tl2a5uk62IGK0NQozjyWFnTzqYAZMKEYMYt6MIQCAphExrHvO1ZTp+gACsibV4c3X//N//1//A0kgGfw0VP47C9++ld/9bOf/Pgn3//0w9i53cX48cfPO08eTYDAKpsJjBog2hCtG/zu00/w7//xH4RIAATFqCZXASR25HxwrnsINs01BEcsOUMpwcwDBFNUdbE3YgOEWiXnIjU3514CNgBDMVYBY+fWWZxV71JbJoPBz0sBy1Dh9s0DBhqHuBlRFNIhV0N2xGzOUfDchQAVq6JUAPBSEM0huDphgQToGBiZJSUQQ+c1S0FVoi72YGlalnmaU/rqJz/9sTOkVFSLGNWUH/b7JLK73DX11RDCMCqAOgcG1SCxh80WtgOBSBy8mHinVWFO2YVYxXIWYvQxsltyqQCQS5oX8CiiygCmgEhd9LANZG5ZFjpXFmaKqDEyc9f1hGDsAEmcQ+ej9xxj9+rV2/1BDkeoCZyDvu+YyHtkUhXxDH0XQyQEyLkeH9Ld7X5ZoHfjdnP9t3/3BRwBKhA5RKeWQRVWjcpGA7Bmh25GhmvVtfYY3xXMel7O511+9Zv6g4L7949zLg/nNMHOw4CN2Q1r4ii6okBMBCtcvP7sGUVai/PHAwDgDIfB+T9kNrN3031E7/ECUNeO2jlxsvMj+ni2aw7z+Ct+14L+MXd7d/n/qUuHM2a1ymqY2dn/av3jsXAFahMptOZzj21KXLWf253R8/wjASM2BpwPsRYrOUOAv/l/f/7nP/3oz15cjePw+uEr4jl2zE5BYTkBsDlP44ZDhBCq1OK5ZKwoTf2m8UMU0RNxTnVZJESfq2UrzNnHMMRA7IxwXhYgXKZ8PC3kQCvsJ7AknhEQLJIHLiJKTkkFQEgcQxhDBwqQKShwK2Ycu6ggjQ3CHEvKVYpYMQ2nQ2pSSqZmGbtt//bt3hQI8fKChmEbnHMduMEFH4OPnoJjH4IHLBWWJx/0LlbjkmWvVQAxJ1UtBKHrnfPOO2/Gp1N1DuAWKkLNlZnYNXdZUxUmdp6zIjWai5mpNbe3lQ9n9ghgnaWq3q3+9xcJnjeicwL9WPCsm4i9txbPj8w7+OrdCv2j6w7X7Hz9klBQYVUSB+d8rinEroAdT8fbu2k6Fa0gVQGhqqRcHGOtknNueasUMx+9IwdOtaY01wQOHBm9+MHztM9LnfKpoKD3PnYxRE+MADgdq4lOx3nez4e7I2Tou56R86l6CNN+IQPbwXDZeSLLtKQlq8QhxD50fZhV0zJN00kMOg4eiIsFV9Sgj8Fj0Ipi1YGzbNNxmk9zTllAh+0WjcBWaEOSTHkyMTIEQSlFijA4rAYnPNwdKlk/DG2A+jBNGkoIgTwJoSCJyGmZCGGpgcCBmmcffVCVUjKoOXKemSCkWtan9mzcqwZN3l/XckzNAK3Nrmqrd6EFI4Fzl3/9H1xpsdY8sRo8SsjYatTWZmvySo/i32QAwE2UZCX5gIC00rKNJyucATUgJgRs4X91DSM7F5LwaKqBRGZqxvb+0LW1qTTA85jc2cT1d3YCa3NWTaO+ySS3davvawT+6eOxz3Fe2ggADs9ngoiGyND0qhqsYK1roarNHqEVqNCMFAikSoOJzCkYMK/9CRVT0IZMtbYMkTMwMdRqWhQASQwAmBkZEJmYERl5bYCDNhTToVNz7Wbb2siENZ4TYeNYEVNriMK7XUYRVFZAXEWqiGFjnVuT5UJEMtQWfpDQENRUTR2CgChIU1YhZiJsFCwmBkRVUWsewdWQgAnJAAEDusDosUxpqcn7QESevXOOmUved/3W+wBeZ1taAq2q0zKDQfB+2I2Hu+Pt3f2w3XR9V8UgAkdK9wl6htrI1ojE67Juyv4CCOScc+zLMrH3+/1inC52Izk+HOtpSvOcQ+gtOAWUrMS0LHJ/Ny2pXD8ZdrsdMy5L7kO33W3m+bA/vZ2WZUjpL//yJ0y+5HJxcTEMYZr30zIdDgt7/Muf/cBxB+rSdPjiN/90uXv+6ff+4qNPnlw/G4T23/37e1gAnCED07rFNrW4Jktu0qAc1LaklJunHRg2VAVRVKsZGgpYo+Naw4FrqSoiBmxZNznNsLlw2yF+8sGLv/7pTz773vd//eUvvv3283m6Z6fHI/QuJdTd1UUc+v08HfJJyTJbnY7LUhGCQ5tPeTpWRu6H0QrmuULDIhQccz92hzeH4+Hw4oPnm80IHhS11qaKIog1J/EBiHCaT2/v3rjgthfh4uoCHMxLNjJwAKCIroE7DU4nJAJkhJphrWkIELGJrz/maATrh6baspZ2tEENVC2PcUbfa9e0Bride5zWHBbWjG/lNTOu79ekWNs0sqlC66AqyApjPRIPwUBUFNREFZtCHiMQMq1EA3z0dbVmtn5+rzZ+aABqYiDZEEAdGUjnAhOnU6nJgjkKvpTazgeNLGkxyBHGje9ixIyUkZUdowNKpU7TnNMMKGM/Xu/GNOnLh1eH+/nu7vjZp3/+/MmzzXh1Opxe37y+Cvb08uqD3TMUcIAh9PNylwmqQk4gbL0XR47Zi+TD4fD2zakqdB0Gth13TPbkyRUCLUu+fXuXq5Q8+xAc42oxg1hzrblaqsDIhH3f9cMGVJh8DAwApYKCETvnnUhWYTCtFZCUKZsjMKRm8UMhhj7E/v5hurs7en96cv306vLZdjssS/nqy2/vbg9qaOrnpebaEPreMahYKVYlTamCwrjpQ+hTmh/ezGjQX8J2s9ldXI1xs8zlcDg6BkKUWsWSSKo1Z5EnlwMAOQUtOs0Tqb/ot7ELbZLXkyNARxzRAzGAVRURdUgU4ounH6iXWWd90Lvp7ng6idWc8/3d7XKaXjx5WlJOQMnO6oOOq8h8mm8f3l486VvABMCU8t3d/d3+Ts3iEGMXzSzn7LyTqgmqGBKxc2EYOXZkZlXqkpZSMiJo1WJm0XmmECI7YiIzYybnginkVATMudSF5cMPrk/Hh5KLlEVBu2GMQzfltD+eDodDLpWd71zX+z5VFblNuc4LGIgBbO/ux91GijwcDtvd1kXvu56dN+Ql62lSRjXdP3vytIuj977ktNR57DeXF9uL693d29tqeVoOtw/86ubbXJeSy93d3eub1w8P94AWgkMu3MFmM4bgmJ0PHDwSweFhn/Iy9tsPX/gu9qfTYZ4nIg6hr6ZMgcgrGqPG0HeBg/MGqBnSSRi58x25tUPmEKN3eTncHeZUYRj91eVm119Gjtvt9vrJ1ZOnTzf91kF8fbh9+erN3/3df/z7//Dlzc0iUotWF8lFQqR+2JS6FNHYDxBQxEqtWYtVy1jGy0GsikgFRSO2RoZYksjYw+7JOG5jGLjr/JXbPnk+Bh8dx+NxMTMOOi2nN29ef/P169v7Qgjb3l1uNn03gtlymu0UnLsY4DJQV2e4e3n7zee333716nRX7C3WuVliQnOalgJaAQylbS5IyI6JpBTLwtHHrgeAWiVjORe55x5gVa0FHSM5EZVS0QAcgzEyErOKmKqJqtRVPIhb6QutC9h0ysAACYiY2pS1YwRUhVqrFolDr6pFzRRUK4iCCbvIwcsy16qmkKY5sev6zrFIqoDgd6Eb4nJ7vH1Df7v/9c9//sU4/l9Pnlw8eXr5P/2b/+F/+9//50+G5zvYxe5itgdEQjIX511n2+60m4/m7J/drytokmyWnZZIs9DinPZj5wPmpaplMwXTIqGKAwhmoQrWIgYzMYip1VLqMi/rrIwqIGEXmQiqaKkLGAOdnXy4mRuFGLsy7WvN4GG/P+4uCaD6AM6Zik0Zug6sAqh5x330Arrk5fiQRH1OlZAdO8ygohDE+cBIWcGFuN1u0zRPhwnMswvzcXFMiHC3V8BAhMwZKBm6KU23d/sKEvthHLrt5sJ534W5dSAMwSAR0zBS8MP962PsxpSLD75qSTlvaVDDIrVDYxeIuaSEaCpSKqBAWwaIoArexb5HrVCrVJlFQKoVBGILIfSDZ+dzmZdlWhbdbMMwjLELhHG/l2mCJQEoOITYOWYyyyIFazULXdwOfVjU5mXZ708lSeDQu9HjCHNLtLAuRUS1aPMWUKgtLyVCdm2IAJHQdG2xrxLo5xbyGWg5swMQGqu6jQf8J4Gc94/GwDI4p/OI2OZ62nQJEyNTcwSy3+V1rUyC9w7Tx767PsJkhCh2btmpEjzy/u3dZax0rz/An9aXPGrGvwsCv3c0ZPsslgIAICJ/5GVwxrDeY1+twDU8Qh4A0DqXKypHbZxhVYsAOFPs30mctHk7NESIPfX9xjIshz1cwK/+8fbhfkb4wPvueNpnUCRtw6ppxpy0JABAdhC8ZK7RWSZLCgTgGoUekMmRScplnsGw5mJJIcZCjro+AnKu9VAOTTSnKnjwgMaoYlBKBbS+3zRto3mZlzwDA0d2niUjV1gyHNNcDbwbQuzUnMu1FBEVVHy4e6i5kIPOB0kKCru4AYQ0V3Lah+5wWlKxsa/+wu82AwCP/Xbsx64b2TwYOOaqSyr7zdAV2C+1HOcTGJZsywLsNQbpOm5ms8ucdbJu42AC3kJFYwT0BGyiqlrVDDESNcrhauYtTSybmnDbu+IdH8crWvJOCARQAOg88wCNY0Pvjd/iI5j5nzn+9Cse/6VtPK0+zilBWCEdHyI5N2z7qZb5NB+PtdbGp7Bc6jwvc8pDT4BgaM4BKjCDI4zBC+AylVJqVZwrnPbHF89eFMzY6dgPnkN0sY9d8JEJTDmdXh4P03yY8ymBQB9iIJ8OGcCevniir29yrlYVBAP2jl02TeUkCRT1pJNjv91c9kGm0+l4mktCVtMAses2/cZznPcpcAg+olCapvlhAYRujLpI0arVxmHo47B/OORDYu9IEW2ppRLQMA6qVWvmCgiWLaEnT7Tbbh0agKWSC0iuAAjsOMbokJYpqWgXYqllOU3H/YkMvHeOvTUmlYBac8o2NTEjg2aFslZlK2S5Ps5g2vAfPCO3AGfKJaEZnXV3Gg6ERtbYO2SgIgYEzCSq55gCiuDWVQdmICBw9oldOwEr3IrIoAJgj3TzVsURohJRPU8zNprYO/4gnIG287awRtV1L/jDxdlIE+8xSH8f4no82mP03tdnF8LHL2EthX8AQEjMTATUsBgkRmSCVUBMgWAd4HPMhICgYIaChNKspc8fCymyMiEpaBVhwuADGtUsZUq6rIALMcm+rvOxHsg7duQchz4iAToCgKqqVisVgWrvQjsIGDMBnOX5ARTNgXPIIiJa2x0kREB27BxHVck5i4iBjbuxatFGhHZIzEBarBAROXLeKWqVaiTkOcbIzqlYKSWXPPZjroUcO8dF6zIvXRd55NN8hMjdJgKZMRiY8+yDBwMpagAODak0ja0+dCF08zQtUy6TzKeKFQEsxPDRi48+/vjD7f/H2pv2WpYuZ0IR8Q5r2NOZMvNkVmVV3Vt3dHNtc+225ZYxSBjRoDbqFkiABP+AP8BvQeIDn0FICARqLCHzgQZ1221D21WuW9e3Kqsqh5Mnz9nDmt4hIvjwrn1O5h3cLcRSKoeTa++99t7vGyviiSeeZ9k+f/Hi+fOX29v9OARyJAgWLShxEhT1xnn0EnU6jDkkU62YebNequExHQSC2cB3vvXh+tJPuQObK1+NQ7zd3lzf5Pcen7y82hLCojVt23Rdd3uAZQPvPVp/9+OPUjwgxbo2TeUfPXgcRhm60B/6/tD1ww4hu8YuNo1xFKOcby4QrCRRxhQEGJp6dXZ6vl6ftNXZT/7i9vNPvv6r/+eT7fMu55zqaI1jVo65uIYBonfeuppFyThVHoceJDTr9ZhHawpSp0WeTImNI79wZMDXGuJYOIyVg5OFO11vfvNHP/q7P/7x08tHjRyurl7+xb/45F/89efX++5miNeHOCg0p9Bu2kMcbNO0yxpSWFV+6ANnAnE5wM3VPgXNUSUUaLoM+qEqQmasyDk8Pz//wd/54Th2z6++fvbJq/oMjIOq8v0YH176v/uv/7pX06L7g9/5gyqv/pv/6r/9n//XP22pDl2kVZ0kop0dc5AFVKnEHEVOM0qsRzwJAACkQKc58QxVGzCGnPMFjGfmlJM1VFa7mjlzmpmliACaRRGRDApIgoQiAEhonbXW2r4bCl1xHl0uom4ALDyrYpnSFLVkqKitF8I/S46ajj1AsAbBWiJUnOOz4FHowQFaQIOz3YYBMHB2fhqmkYPGHCTBhx882r857G4HOJaUZOzsPgQZUKhBqjGTwAB/9O//HglHnsjBlPbLVfX4vQchDkWy4fbmere9stCe1OeVNu9fPvno/Y8u1pvWN8u6efn8+YPLiz6Nf/aXf/4n/+T/7LgfatsZHKbkDPzg2x9/9MEHi6pO07S7vX327Ge77S4kUIQY4d/7N39rvVivlqsY+cWr11999XXfjc7Xp2fn3ru+79GYEMLQHYq4cdVUm81qs940bfPyxQtjy8Agb7fbrj8Yi+2iHoZhu+3PzpZE1DT1YrFwznpXx5RCCADq6/YnX37pXKOKXddvNqfjkLtuur3dpQiqmBOKiLOeLCXJubinKTKrJkCi5cmqrusYp67vJIvzZByMkZ2Bk+U5Z91utyLS1L7yRjWKsvfkaz8iWLQVWT4MS1v9+re+O1zf/Ef/7n/4B7/9uxZAh4kzf/ZXny7M6sc/+i3nLBDFnEMOh9BXi+bV7tVXV1+9vHm1n/ZZWS0goLf28uzio/c/aJ2fumEcxhzjGIMiuLqu2trXfttfJ4kxxWmaDkO33+/HaRzjGFIQZSCjIiEGhoSkaGyZUMqiOefvfvd7IYSQx5SiiAiyI6q8iyl457a7m9p5ZhZWzupds1quF80a0OQQGgunp5vDvnt5fZWVl5uTEKeqbcDZJOnzz/9mDGPVLLLgFHgKEVF95bz3ztmrq1cxDovFerVeq6rz3gLdvrkRzikGybHytm38ZrU4Wa8vTs8RdBzGGAIpeOfW61WxHqurxesXr5EMc+4OO+dt3/fGmPVmUdXkHDhnRXMIIaWgInWzzJkX7fLx5dPT07MYc9d1Q3e4vr7p+/Hhw8tlu96szhCtMJKaEGKYEgiRcR9/8P3r6ze32+uYOleb07N2dVorya7f9qkPHHzbPHj4aNmsNnSyl0NM8dNPP/+//tn/NgQhWL686r74EhDhyePTn/701teADqqarLHknHNVEh7HGBJPYwQBNNbVlXFmddEKFOUjAc2Ak0BYr5on7522S6MyKCSAdLJZrJeVQT9OIYZc1cvN6vTmZvfVs2dvrqMxJKIPHiysGK/+/PRyVZ1VsEFefP03189/9vrq+e1nn34Ju+NcUATYvVV4KsxjQjP1lcosR0nsSrkKdy0EpGOOhm8xR/hfaUZqzsHuc8q3Ck58e7hjruHvaw4EULAeAFHvqPgl3eOiTaPzIDbOnV04Vt+qAGAWjiUDH+dZyrGd//z278J/+h//5//wH/6D9y7XHA/r1XKUPmm8PVyPcvAtDLkP3A9xf9vdXN+8nmTche765tpXDTMMISamYeCQMCQaRwkBRAnRDNNgjEEkFpmmsO/GnIFF5+nLQrliwOwIjXVAJAqYGSUZBxtlTmOXYw8I/8l/9qPvfP/Bvtv92V/8adbV3/zs0Kxav3CKE9mwaMEZm4cMuVotLz759OUHH753sn7Qd+HP//ln47Zop/umaVztJOd+GpQFBIH8ovbOEUjOcZimRBb+0R/9/ntPH4TQkdP/4X/648WSFM3zq3Syhg+eXnhfee+aplHVvu+22904DkTUNMvUGwQzDvkwvHEV/Nt/+Ns//ZvP9/ttWV9PHp8Rmb6fSnNAYDKVAYI+5EMHxtS1PzHUpJBDmIgQMMa4XbR+tVo0baXKKY2ZI5I6T75yzjoAUfDPv8l9x9MUlu16s9kctrvd/ub0ZLNa2jdvrn7jN77tPD774upmOFw+vazd+pP/+7MWn7Ru8zeffPPmJ3tQA9mAEGRAVlRFTnfMprsyocjYqNAsqwGKEOb+1P2ICwCqHpOWuSdxlHgr+c5McZq320wsgdK2A3NPnir76y2CCRYTcVA1sxrC/cnHHTqDOgWrmicy5j0lLCBgKzsPKmLpphNbEStkDQKAHP/rrW12r9+ANJMP7nxy9Iij4f2ee+ui7o9fOt41B5XjowDgzh3sWNgCAslQ6tWj95goFi+w48vgnXiLKnCLTAgJzKTIy8b3g7VUJUhsuweX7X/xX/6jX/97778+/Fknn+2GZ7c7+/olvX5Z1f7h9e6lb+Lle9V6w7vdUJtiy0DGVQC266Ufc4xAplWwz1+8vr6GpoFqhZlAWNu2PT09N2QO3fDJp1dpBAA42fimbYcuHHajRDLGcoibB4vVunr69JGv4Xb3+vbqZuhB2U89DvuxWoA1pq1W3i5C4DiCcjEmB1SZpm7q+uVqsVk9HA85SN8PN7/3u791/vHizeHldn/zzYtrZjg7X27Wp5cPHz98cDn14Z//sz8PkfMkV7c3j07PT06W69Pq/LLxC8lw6KabYeyevxRnyTnbNFXdVsvKGKBNfQFj9ad/8snzz/t4gy63pAB5EigGcoQGFQFMmS0XnHkxCkWbWEFFC48DFI+Em3l/lMPV5thoJtV5M6ncARnzwi7i8MeNNPeQ7w98F3EVne8vpiDJBD/HW1HwzSbBAEtuLvKwgD/8o3/Nn1TXN7u/+snnaFyaEoo9P1krZdWJWacpVb5ZLBfGmK+fvXIGyAARCug0ggi0tQMABTldnapqCtlhRYwPzx81fnHz8ubVy5dXr3YL04xdlJ5BgKytfUVKKUZhTlM+ebDe3ux/8IPvPfw7D1/3V5988dmqXiSIikqO2tUiM6cYxzBpBMiAAEaAFJzxtW3DmPr9qEGgsAoACKHoJWDtnHfeVYQoWSTmHHnqJ8kqWY4JAFgL5DAblKL/M1eAYAiohEmah4IRsa5q5xwIcmZkjFOIU4QJ7goiYLj86IGCKqtkiSHGKXFmUCRFEcmRVQAVLVsnHgBVJKfMKUuW2jnQ4sxQYk9JPOalg3JcEjJD9UWIRlUVJVmZr4EACdQAmMLRASREQpnBMYISllmAEQRQDGYgJVICAWGRJEIZjM5YlgHjCC2SISVVZEUtaKxBkydEwSKPUIw4RIo92F0wB1B0RTehOG/CLGEYpoiEZMgcbSuEVULxjlX4FYG0HHaeusSZ2DSL3sw3pRkMLmUxqKpwVlXC2WssR4XCkJm/OQFFYFUuWJ8AZM6FJXaXuBEYUmQLYAAtWGOMMWgNGEicEBHFICJjLkqSOF9OAQvB4lFCAua2Bc6EzZKW0lFfsmg/MmMGVUQwxjBITIFLRKHCZUMkqFxlvVXUkELKGeZBgdJIZJ29rqAfB1GtTE3OerLGO7WSNYEBJAVScoXWp0XDALSw49BYFRQiAMWMCVWUuKrtctFePHCELk1i0J9fXEwxfvXps6cfPqUXV2MI2ELbtF3XKyqKzJ4sykmTBgAgspVR5JBjH8AAeSMIAtC09Xqzwl586wCBeTSmMXAANW3lmAXUIviqapsw5ATb2+HLL7559GjtnZ+mEVS6rrNUE0Fd16qceRqGmPoJjFtv1qu2rnwzDFO3PygLs0LmmIbMXdddWVw8ePhrbfWDpx89fHV19ezLr//yJz8ZbwIAUIXeuRizChuLKY1xiuQrV1nrSbHytRu3nRSluaPGk3PGVNjve0H44Olm0bhp3CnA+cnyow+ePHnw8MOP3m/aaoq9yrDYrH74o187e3J5dbP97MtnX7x4/vWbLkxALiyXdbWoUkwSg5DJkSUrikkj93upvaUjzQmUZs2pkrhkjSp9P7x6+bxdNucnp/0Ht8zp0GmMMSk8fHiumodxBFN1U79qTx9dPvjgwcWzF9eu9ioKWcDb2Wz0TgZLABBn7GpuvqlCGY02BkgVykBtKV608LBwbiAaMsxcBunvOnooiEcwqyhZABKQEqIWeQuVXPYxkR7TwvL8ogrCovcD+3MDQYS5dEkRAa1xORX3qLL7ivr8sQIrbtVH2qrOgf1etCuMY2YBhNp5IZnGmGI2glJiEVgUkrLxySgBKqGS1ZxBPFmOGZMSkUdPaGNgFhiGkXMMKSs2QnbSHCW+ONzQtYuQ3jt7eFItN+ulBVr65uHJg4fn5/2rnhhTSqeLxcOLi/cunzSm6vddChOwrJdrAiPCVVNV3p+tNznzbrdNiQ3K2cmmrhtEWi8XKefXV6+sdQ8ePDxZLRGByDhnjSEAHYfROV94fuglAAAgAElEQVSGC4iM95ULUTTlxKpkLQAY56q23TRNE2N6/fp2HEcR9d77CBdn78eUu8M09HtOfZhkHJNmL1lUUBLmnDWB8ahkQEmYc9JZ7hVtjixWFk3bNnUKIXLKOXlEIzQNgVkJSLKMQyQ1VeW8s6o8dNPJ5cXt7fbQ5RNnz843ra/PHr+/bhYVOOEwTsEibparhV9ZT5mzCjAzglbWb29vQhgRwDvno4kxCXNdNxcnZ+enZ8g6hEFiNABgwDuXJYapP3TbKQe/cFmYJaecJasKAIKzThRYMxlCRFc5gazI820YyAMpQNd1AICE3nsRzoDMvN3v94cdgC6bJhqOIYQxARhAr4rGWedq07TXL561TSsKAJRTDFOcYpxStt772p+enC1yRLQsuGggppRzQsSqrparxZvXV22zqpyvvd+cbDabDSoum8VhvwvTlOLAzESO0AGaLEqgSOSryll3/eYKHTlfWV81i0V7EuqqQgUwIMItgfO2WTRta+vaWGvCNGXmlJIAppQBDJEXpSlIf5h22+5w6FLUyi+caULgN+HWuRqUvKmWy9X52RKVYsy32zeiuWl8Xa+sYySZxoEhI/Bq0a6rFVljLU7TcLV//VeffjZN0+Ewhlg7V99uR2vrs7PEbI2v2hWBQTVSLVoF6IcAISIa0XsHekVWFCVy3hIpAE8xMI/W82pRnZx6xJCSNDWuTzbrVR3DoTvchik6WzX1CiVtr19//tmzYQ9WYdMs2sWitm1DdmmrGpbTdfrrTz7rbyjsTHcTuzdY3a5imAi0OJ8qw7FsLtdEJV851gFwd6FaWP84d80UhcDM/qtz+aA/3zr824479GhOYI615z0Rg94VMVWYC2iaBXhw1neYQYL5YTiLVACW/ObuQARVLgq6CIDFn4kAxT5W69A6CWHxj//4n3z66bPzVfPB44f/4D/4+08+eLyuLCwXSxievfprsJBYh2FKU1zV7YKqYewxRgCqXKWGQt9ZJFNX3mNVmXHi7jD0Q6qqplBRrBpjvXUUEo9DzHNii6qqBpXKPDonZRXhTMwm8YEUrZPKUYhSNaaqTCsWEFByVQFA5JTRRkKwhhrvBJwmay04z2PYbWBT1VRXOFqom4bUG2ORkdRUVGVOSoaMkQxc9JYZjIJX+9WzV5WvqtZ6g/0EvpKYpPEgDK9f7xdts1qtjBEiNMat16um9TlHEF6dbzgr4ZAVjAUQNWglAyAwwzRNi7ZdrVoWGNI0TIEll6/IWmjaFgSnKQyHcRpG49AaNUXPQiWnoJABE1JWkJyQUFFn185pCIbqtiZCDWMvGok45Ulh8ejyoarZbbvDMAIA53j95koS1IvGaaUjAgMIARNIGeAUUJ6riXd4G0ezTJwBG9W3zrm7xc/LXPV+VEV/furprZUJiPc77l3x3oLYvPMjnF/ol7Oe7s/6haG+u4cfy8D7F3iLEQNvvWH9lc9yzzJ455n/fzqOFjgKR60kBXauLtLKisrCxd5KYJ5bNogyy+nPuhKKjMiEAgSiggaVjKoCuhT1xYvr99+sTOMlmZTUOdMuqs3JwlmfcOnrqV3YplHO0RGlqJlFRbJwZgEFQwQgCFBXfrWK3lO7qtUCJwZUycH5ZrVsGwcLj9Z4Z12OHMegjJZgFjnlFIOAMBFKDlnEeSsZyQI4ch4NWeNtiV4xJs6giRHAGpjGYK2NIV4P1ynCYu182x6GDt7EjBxCMBaMBWMMEe67LoXnUx+mEA3YyjZLt+x2fZymQ2+yLk8eVvWCLZG1tqkToQO0zCiiZNQiAkAYOU0mDkeOBKiiFvUNPWrA4dsub1oGhwAVQct5OC8TvIv8925Vc5Fxd0uBguaW7kmRkdO7Hoeq3gNVRZr6Vy0/fPfPd3eTIuac1AhItt4+foiursZpHKZBEZTZWNv6tmlbwMQCYUrei7HImVNMD843IcYUI2cug+HKIBmsp5xl3x/Q0GqxbOsGIqDFfuz2h10Yo1XodyNkQEPGWoMks4yDGmO1gjAF3yKjHLb9bts13HqqHfkxjMzCJCICCW2yOWbNR70jtAgmxBSnrOGoTUQzxc0QgqIycOSUIxEpg2bRpLMwpaoKFLVvFNQEqAD2WPyrWCLQMqCnYO7xKU4ZBUjJEDnnMRcdGi7OxWgRHMQplVpOWZhBWEFnI1UUKsJSKiDFAwHekqlCyCJzd+AuMqgpKIiqAjGqASgC3kWu9VhfIRqDR0Ou4xBicborABwd6zrVo3Q3zdN8WPxfQZQRiirU7Jhc1DDJYBEQ17kOLbmLAgEjMMt8MfNxjJbvJEqqZWrnqOpVFufRDBCOvNK5kXi3dO822i8edn7/BCRABmfdZpjJbMeHEZJKEV5SAAIySIZy4cfh/L1igbnwePUEgpqFCYj0HjWU4ihY1HjK/JJBNKgoKScAQ8hoSEAUZ6NILCHjjpx73J3zkHi5Urn7zBSOg/DM5e6HZECFEIG5zAaW4XNkYhQABUOARlWLkiWpVUVlZWbRrMysrEgGj/OGisVuHqC8C0tAXMSSyRDa+RXmbFihaiogURZQQYs1WQPWUmXUkbpJVRmZsR+7n758dvnhYylCagakjNSVNSdQtJo1J4gKigQWs0DMGRJ4tJYUAQSWy+X52VnkcX84kLEpq6gJEfoxshgAYjGArm1dytJ103aXD7s365PWV1UIGQH7cQIOBrx3nnAxjf1uFzKrr0HZKGOc8tANh8MeFCTnHCOhGfq6ck7ZrT/+sFq4B81qfeovH5/+2ve/mwa5eb374qsvv3nzXByAwJAP1nqoEDTN4qAiKY6ASQRknq5A44whtaSrFoKCc3B+cfrg/NsPLs58hSrRIaU0hjQsmiVWDlV927RhtVb8AGhz8fjpdvrm1VXPnVuAb+w2HgQdCk5dlIyV8QaoMqAMKIRyN75uVEpbBArmOXT9y+cvPvzWByfnJ+fnP77dvrl6eS2i7dI9evQASKbQV5WZxqF50Hz3+9/95vP9sy+u3alPWY4IVGGLEupxJkWAZjvU+T6HBdolgyVNKfPEx7JGAcSUuEB3+3ru3d0T6u8b+0SkImgAUXnOL2dM1hBhafYgEKgKASjTfIOG42YqtHxWBQJjjTGGDFFGON5/C3xFc7CcA8YcIfG4X48tWSIYp8mSJcLaN87asRvimDUBCKBQmWcsIq1oEY1RAM6ipJDBWzfyAKIE6H3VNm3pzx4OY4gBQIA8GJcMMcdh+7pPY+C4bNtLe+G9S9PYtu3l+cOP3n/6cne93JyeVk2z8OvlojEu9uP+zXbsD9bSerE422ysM3XbtnVtLR32u67rjbV13ZydrtuQphAJZbGoLx89JjRnZ6fWUuYcYxIWzsKSRZiZRZjZOmedrayZpphDFiBTNSuy3laNr5cCeBgOL17eDNPgrG/b1o5y8fB8GvrxMPS70IEA0xQiZ+KsAEaypKQJsmElhwDEiSEIAIBFFMghs02m8q7yFgkmBEbnKGceh0myAigyqIBmAA8gyFljhMObnmNemfrJo/P3Ly8bV3344PJ0vQaQYehTjL5u1uu1J68oIQcRSSmxCiMMQzfFIYcImQlNYx2QW7Srs/Xpom45RmWunUFvY9Qp99M09HGaYhjj9KB5yFmyqOQinKdwlJgAQeONcxZIBZglJy7aemUmnIhMub1mTjHGMY4ppf1hv91uc5bvffcDBRKkqCyZw26fkkaGzfp02TSKFow1RlUpxmxCjjElZjJhfbJeVMva5ZhyLpuPuGwcC+AAXFEsmqbJmocX55vV0pCpjH3OubYusR/HobLO2BrAiKCgsqICGQTnK1/Vdd1Y431d+6qqm8YQXeBD72xKkwIrqHNqLKWcu2Eap0jGr1fL/W7XtI2vFoqmH8LN9nDYDVMfxzGoQutju1i2q40jG0NR4aWmquu6JTLX17fGAVrHzNaCsUBGyFhrAB1MnK/fbA8/+3oI09X1m+fPv7J+aW0dGEMI28NY1Zt2XaVEZO3Zo4ukKWlq1ssUI49dTGAog2JiBQeI6J2v28ZVljAjKnOUPCKkRWPXK9fUZE20KN5a4DD2eRoPYzdYwM1qsWrX+9109eKmzpWkQLBYwcVHZx/XfmFBty9fPP/m9vp5/OIvb6ZbxFAPO54GSROi+pnsqzIDWPfHO5nE8S9zPvh2gYsASELHTiDetTRAf2W9+/OvcsxK7jp9MmdnxQWrQFP3ucv9gwTmurqkr3k+4y7/mcksP+/hU64VZv14A4U6U6bxk2bGcei/efn5P/3TzxcE33n/g8PePv3wyYPHJ4/eP/n4hx+cLkawk9B4fnrRTbfPr55tu5u1Pasulmhh191m4ca6bhoBtK1Wq1UdohrilPu6bkQVlBXQOlvXFQsMTQgpxZhiVmZmUVEQFIEs5cZfCgLJ3rplUyPC68N4frZarnxWaGpgpsUCkyoZsZ6cF+/Re4NETISYmhbGacc6VVVV1wgCzhZXKUUkQ9ZSRc6VlEwyRxblXBrtkfnzz7682Dx8/OF57avtARYVCFBd2Zzy9jbmCAAuZzEGnce6qZa2zhzjGC42mzAGwqToiZI1ZIm8BUAMrHEKtXPtqgIEJpOYVEQQiMA58N5Oo4xD2O/7EFJVYV0V4S4iAOEEmIgEDYiAiOaYQEAtkeHDfli0xntHCCIRjVhrEbBu6keXD95cv3z54mbf5YtL5739+vqKFGpTywTTPkEmkIJelXp8ZsfdK6CXZQdHCRYAIJ4ZiPIWwjVDLnqXvOiREaLvbrb5AbPCF8Bd2xmOaNhdp12P3bS3FdzhnS35txzlWY7zUsda6ecejr/wzwJdHf+iAIrzlKHeH2+9xh1McP8m9e5l7/5L9Z0zyln385dvf0T61h8KCkCOVEAFRRiVgFGhwPAIqAwF1C5ZJAJwQTeVQA1kzYAVEIFaUJNS/snnXzz9werpd1sQN01A1jR1paeNQYdVayw1DVqjVVUDEiFjYk4QM6eYUwJRwgL3tE4lK2lTG1MZZg0hCQcif7I+XS7AkAd1ykZUva1do6iUYoiYSdmgblZtszK7rRECU3JtFLAASGSMMYYARPIUOsgIka11gA4TLzcnEmW/34H1osZ6SBL7gaP23TD6yjrvq6ZBa3b7/avuOg1pGoIlICXN0B+m3sBuBLCTbU5s5USVOS8XHrAFtQqiJUuzyJz7Trp9hmQALNDs18VFwuio7WvLXOecyauIghDK3bdCoEd5H3q3nQvzNNb9EiyrlUgF5OjLecSL52Rej4uahY9r7C69PuJi5ecKM8bwFl9PVVW5XTVdDvXSnj3cbB7X1uHUDd14MAYQTWXrzWrdeM+imR2zkjFkLAoIS90umCFy4giigBmYQZKiQxU9hGAdbKpVtXQQgYUP++72zW3oAwlaMUiFFGWUtTQ1lcVXHg2K8vnFA1ub7evtm+sb4w0mAsXpEBTUJCPCnFVZkQ3ysVluSQg0cp4yBAAAJHTGEJKZwR7NpYYvn40ACgKDgSLlBMVPBRREdbZbLF8Y0VzVlFsVgVoAR4AAIjnmDNmgrbwDr8761lNogiQBADKEhGmKJXSJqOYZvaJjCCVB4VJbMR9jroCU1hlZUlGSo27mTM9TVSzoytE+hmTWfZkDEAAasgis8wR1AbDm4dRZTbmE7aJ3fITkoJjnGZY7pnQRPzTlF5aab+4Ags5E21LzCSiqMgge1zcBCiEU2ZgSz49hmO4bbiXOAaAlEhHIwkfvgqIGCXoPXf2qFoaF4gRazpkBOizAnxzFFefsDYFnqmRZinjnRIKIimCJBIujjqLO9BlQIC2zwlaAQUWzqijY441EgVWMggAnTQQiYAhFABRFlUG0II04t3hw5l4V6eni41DIMgQqCoRFe7vMNSrP2vNoEJBEckkhobjSluI8swQ2lXGVRQJCyCgCqglYsooqKzAosRKwcMxJlDMkcohOjKMyOQgIRAAoIJA1cuIUMwgI5MuTc9akCAapqnxtnApOh7jfHfIEORoQG0YWmx89fPTi9VUy3JxV0xSKo4eyHtNf0qySVRNDMR9RggxoABRRVDIAQ9PUVVXFnF6+eFU3i+Vy09RLZw/TEO5E3kCxqharJarshsO43cHYh0VrRQCAFOHq1atFu96sTowh4ywictYYYo4BVTTlME6cmHPOMaWQnDFGCLyC8Ms3nxNWzlbO+pNH/uLyHMl2h039E37wZolihnHc77rDoe+7MaZ5tRAC2fjg8SrnGFNKmRUAiRV10SyePHm/XTTNqjo7X33r46cXD0+nsXv+7Mv9brfr6ZFceHNq0EaJ+3F6dXM7TPH09OLB47oLw/l7y92w7aeeNfI4jJwl8TQAqS6XBsg0VRh7AVHkMjVLACTKqgBESKCgLHrou8N+v1z5j77/8eqkrmqKOZ5frKyjYTzENNnFph86Y82H3/rwgw+uYARdC5CitXNaNgNS91UHGYcqiFq6mEBY5LEAoHjbzRqnqiqQIRfBlLLv6Ngcm3U15pvpHQZf6PGIikoldJSJEylY7TFZBJgRfHDoVI6h5C5yKqAwGkUAgwbNLCwqd9xklbKjkBCpRJ4j5lYYBHiktgIIg6IiUV1Vy+Xq1asbSlBih2q5DkIVFVEEcqgimnNZIaqahRkEcjaOmtUqcQgx7ccQYqjr2lrDZFxVIeW+76fDjXP20dn5o9PTi7Yddwcn5nSxfvrkvU+efWGWy2QNKoR9f911HFN32G1vD01jnj59//RsXbeNgEpOE8eh3w/D0NQtVBWoqqQwDjHEi4uH7z25BEAyFlA5SD/0fd+llAEUEa21wkJEVVUpaM4aAqNS0zSL2qloztj1YRrDbrfvh6jgkWoWkybd34bDIe2up/EAidOqWXDgFDMzIJFmkFRm08GAIUIQgiK9QSQhQkWBkFTJGpXECs7UhixpnDhKzKWUcAYRKY5JSt5j4ObV+N571YeP3n/84HxpPEz54vRkuaoP425386atau8drRfKypCiTJk5xBhzElVnCSbgmCFL66um3Rhn0RjI0t/uVXhR1c2yqbw9DPJ6e30YdkGS8W6zWFd1QyljjqpaLJxFNKXMmRXUSIFXQURYOGdmljIDr4Dn5+cxxTGEYRj6vjuMh8w8ToFVskJWkZwUwXinyn3fjyFOKYeYx8Xy7PyiXawGGMk6FSSy3tY5TynkOCZb1ZWpgIk0Jc5jCMDsrTHCcRhb73POw9Ah5zxNEiIa44hQxVqq66Ul45yrfWWdA+NAWTTHlGNMddV4V9dVY8k78s64yvqqrs5PTheL5nDYDn0XUygueVMYQ8yi2NTtZnMagy6Xm6ZdqdphiF0/TWMGcW1dV5Vvmg0n3t8cFu1itdpcnF9UvlLWFAMSWQdUOVuBgq1qch4EwpjGfgy72/2b/e3Vm6tXr18NGfoAZ2fLtjkVsdLzYT9EcQYMIwSNmsPJxSZyHNNovUkCpnIWE4vmpKpgHXhnvXfeo7Wapy5zzMKIvFzC+Um9WFpr2TtoF1XlYRr3t9cTZqgdXJysN80Kkkl7Ht+EJycfmeVi3T5ct+er9vTZF8/3t7svPv3ms796fvMGYAcwAQSA0YN4S4agaI0Cayb7Dt40m1Icq9G7pvidce6cu5T4rPesjdn+DI/g6r/k0CMp/u44SrorQrl3IwCiqMxJ2PFl9RjKUWejjPnxgChv/Wv+9S5igKBZ5h6nHk9AUoUcE4DO4gkAfZ//4p8++4s//68hwQ9/59Hf+4Pf+d3f//HDy/bxB2enFxvG0ZrV+sPLcequDi8Vczcc4vCTTGibyrl6TGGc+pSS9fXF2er0ZP36TccCObGIAhqyxqFB8jipKjNkQMACXDEAasmQQQDUmmybyi8bK5IhwKPLk6pSgHB62oRY1/spj0xkqgqsB2vVGDZorZqc8+aUul6cS77yqxP34qsp55AjSSYCbypvrQUDzJFzSlE4JWAFQINGMV19HftvZ3nf1NWqMhADuMoZ8IyImoVNGDlMHWCuG3uCi9Wq8ZVFYOs1hGgtLxaV820ZyTcGrCMFFuEp9GSRnBFNZMQZkGPmPwz90Mmhi/3IOQOReqfGWCKLSKoZUYkQDYlISsCimhIzEFI/AEovjffOKUqKgSUvlqen52frzeaTTz/98ptwsrKLRV05myZY2laZ+23miSGVK0CYfQMY5+wZ50EVhaNCD8AdUPurSB9vL7t/+ZYoJcnPAccAR6hoxmR/8Yn/VY+5n1Y0RY8bW1FneSygkqXAz2/fuzrwDribIea3nrp8DMcTZgz6nXdwL87y7n/dv8wvR+IQjkSIud3HxbG6DP4okiFRkGL3g6pKpVabVZMVtFi4G0ADDKCkQqiCoBRl+vzzz3/rzXe+/cMLFT+N4GsFVO8FIDZWyACixiApGbDCqgpGVLPkkDlk0GIcT1RXBGpiSjlNZL13jsAwiyWpPT04O+m7dNiHnJDQNVWFXiVzZd0wCQE7Z09OlosTd7Nt/O02hyyiJfTFkFGNeCFklQicIQMoeOMsmSmTN41aBTtUCx/DCBjQgYBcX2+D5M3ZYrlZ1a7NKvuu211vZQRLVZIoKaWQgBFRZYJxyJxZ1ZVphsp761qiKqaQeD9Og9hEtBxGipMAeDQEkkp+fQRIZ65I2ew6fyUoolSiuCLcYVigs64zzrJYZUnKz+Gddwvhfvr2F9fIHUAFb62xd374LpwBRxrX3U8BTIaY1pvNxeO1W0k33U6pTzJWNXjn2rpZtF5iihxEMhE6ZxGNMoJiCokTg5A1HsFkEZRgFEnRWltRYtAkMfBEajjq4bDf74NLUGHFjiCTCGfOykqAaCizxJRcjbby67M1kG6vt6Gf1vYkdAmiaKdQQ8gJMguDKXaoAirMqNYDGNRMyFzu5gbn9jphmfpV4DInl4oQM2lhqhiF4/2xFC+sUvz/yvCIAABk5lkqwACAQUuEiJKKn7xQIkHiZK2vXV27WlhTyinlnFNKZegMVbEgVkUffQbLVKDwBUALc6xE3BmwKiNuhDh7yRX+xEzSKmrdqIggBZua6QuKqmqR6G1GRHnCO886mjF6IkIhRSk1mlJ5igLNwjHAHQEsAjRFrABQtYymzuFa7tDXEvvojqYw75f5HnIP/ysI6jxChHPAIwDgImt/5zcG8/b6W+hXUET6EHBmTogSIc/3ERGQLEoERe9cQGa2FkLhTRnDM0JMCIQGLCGnIm8BYMpbYUQlUiSLYFGYJc3apeWNCzCwqAFBLTw3JBUqN1Ip88Dl+6HZSASMmWPJXbfnHtQyxHJUgUeAeeSqTD7dbXKEwjIkAUK0gA4zMiGRIwDNnJUQCISlkBTK+QpCxjnvbe0EuLIeUA7TvqotmNJVM75yZAwRgUDUKDlzsS0UzZxZcuNtVbuKnGQdON9sd9O+CJf7MKbVo8XJo/PnX3/T1NVJe7a92Y15UFUQJUWLFpDmOUIEzaKS0DpAAiAEAFZgAIEUU993u+12dwgxw2p53tTOezcME8xT9xRjrpIY65u6RUHOQ99P603tXGWttdZ2/V6EEG1tnYrW9dL5uNq0J5s1AE7j2Hf9frfnBJwAGaDixhmDtfFmdWK6fr8dRs5qbdX41tjGueo3f/u77XJ9uD389GdffPP119PPrscRIAEzQAQQSAodHoABMgADGEik5yv4tR985/vf+87Tb713cr7eD9sp9vvDm5zD6mR5crpcLtqqNZECQYXGu2Zhq0aDKGJdN+vTk8dPHvfh8Oybn728+voqhRwmAg8ClYe6qiRhjkKiwoXmduyQF8QYBBAMERkG1a7bb29p0f4IICPIvtsuFos322/6bu/UkKHt7nYKw2q1XK2WgDCOEzUWPanwXTmhAKJKUvAxIwKIYvA4Zj3f4kBUZzgYQQvUDSqqxkLx7jRmTvj0KCsxY/Vvs7MUVeVuCmZG3EvmM7dO7yMMGVQi4NKQmtOjORaJKoowIyjN3vLABY9HVSpXAQLHGePjFem820uxBmTmyzTGLpZLGI4VligW7FBBilcioEHMCsAABODh0HdDHLKmFJJJ+MBcdmPc7g43XS8s6JoEKDGDY+MQGxeG8XY4vHhz1SJ+/KPfrxQrqcHaywdPzk5O9znlbhTlGKPEKcU09JMCN5UjUEuIymEc9ofd2WIhzIjKnPtuP0yh24/9MKzWp9M0KBMQGltljlOYipGwKXEK0TsvVgvChUjWJYyBRQBc5Zf90E9duL0dxnFkZu+XVVVb50U4J76+2g993N6MU4QQYVk75SSZVACFVKT4igALZ0QLgATWgAKAARLvKksmpSghEwiZBqDwWtGCZWAQKV9OjsxJskLbwKKxD87th0+fPr54ZLJ0t7vL5dlmubIGdrc3u+1t+/DSOevIJomCEjQIaIKYOLFIvWzq7BaxMRZd7TZna9/UKfN4OOQYa+9Wy7ZtKpi9ChhJKm/bzWK5WGZxgMgqiAkUy3AqIhpjgLSosHHixDFLmu0clJCsApTEIYZYFA8R0VjTLJp6UTHnYYogTMbmJKJivQMwU05vdtvtbnf5G79Jxjkvi3aZYmqbRRZmRQwBwTgw3lWNa0IYu9xZUYtUeYdkcgwny+UwTjnWbds2viKFNIVhGHOK1rq6qZ13xhhvvXfWWs+SxBjJSVi5m1oXGtuY2jprV83ydHOyXCyaqjIWx0PnjXdoImRBKRKiOWVjLYB5dPmkrltnq2lMIUQRtLa2xrbNYrlcLJbL3XY3doO3tXd+sVwoaz/0iLhcL7/8+suz85Plqq7rRdM60dBN0qf97f72q2+evdndhhxZoFo4bdKTj97rD3JzM42Bs5gx5ghTDHkMydfh7NFpSgiII49TGtGKRYSgags2CsYU5IRTYu+zshBCu4CzTXWyqhcLY60ChNZjVRtH3mPmMS+b9nx5Buq6XZRO1uZcO/O9j3/91773W60//dnn3/yP//v/8clffsq9dHvwBlIGYiQ0TEqaqWR3alStA4sSjjvDkzoAACAASURBVJJXIDg74Sjq0RgHFID0rXrg7TqTZbaHmldkaXv9fz3mMaHjKymAKt2NM5ZksCQ2v3RQ8WhAfXd6EdI5PjnNb1GKh2/JQBV4ttdQRjj2P4TzyeZUV+oc7bvtV1+/+e//uz/+X/7xn/z4d3747/z9f+Pf+sPfe7J5L9vhVfe1AfPkbLndvRkjb5qHm9V5H7ttv3V2NDYoGLRG0YqSM6qqKiEnBjDATMYqq3BmyaC59BLVERo0xpIpgaxCqPJgvCegCMrLFs4v1of++RS2Z2ebbrT1m26MjMDGoLOgLIzJGOucFcknZ5Wrx8USvMUn75999tODipAhUoNKKsipTMnknINklgwgiAqMqALQwetvblaXzcnJyYcPN7fdLkwcQkBEaz2iZ0YFZMksiYyoJlehZh7M/nDYppycd6vVMucU02RdtVhUdROryiIqWWWJItE5JUIBkAwKdt8NItZYbRtQgbp2tS92KCAiZLEYrJdeVXHSK+R7lXSyBAS1KM6AgGbMde3Oztftoh2GKcZEFpbrBsBwipWHZb1M/XT9ag9CIFQ44FDa4b8EyDn+qPB7YFZYQyx76F1QFmcRguNk6x2288vW/jEnud8Mbz/bzDopuT3ePz3+4jb4VS9whIARqDAd5z7cW+/orW11h5a9Mz94pAccz79j2Rw/kjvQAO8f8O7Pf/kH8Kt4ZHejJaUcA4Cc41GStChGEJaKZjb/krvq9C6lRFSygAQqwKRYpImNUUNfvuAcrKEawXGCiDnnSdQwj6ZCpBSTpFGmmG0DrMwMMWtkAQPGQs6acwbo67quawvIU0pCeeVWVeVyzogsnE5OVnHaxZiGHizlqgILSMDWIikQQGUIla1x6+Vi2cBN0My5EChiBIMqImBwFh4qA1nIyopqJIIkqH3jKjocuqZ25CClsN1N7Sm4yjfNAoD6bb/v9zEBJkSrEnMKAmLQOqSsIiBoyDnjEVztKxZwzhK5lKaUgmRGSbVnYQPqSjcZMBaaxHFeC1T1bT8BnZXKQBWV5+EFPP52Bzzpu1//r6CW6Nv47tts4J+TP3v3L6Bv3bzKM5fxi/m08kSIYzyAg/PL9aPHJ7npRunQBF8rWtO2rrZWZOqHbooTEHryRCiizAyIKWZhMOSsrYhs0IACFomU2tZT2/ZxnyB2w4HYuFxN4wQRSJGIxjEpgzJrUkCt69pYZ72NabLe+doLydiP/Ti01dKh64YuDwkUrPjcJ8gKDFDkuTMV0bosilYtWjR11gzFbwpLo14UiiAvioBmKZWdhTKOV4RRgITkOGGDAMxlf8nMJ43HOMEAqGqNMWgBCKMWvhxTVpEYnHPeN2ggZcmZU0hYhkx1HilFnpEsAARBElQ1AIDActe4QkBEayhzprm7cK9cXvQDZswIQLBMfzGXCDCP6sAdVdQU4wcqdRkCyB3tG2BWmVFjlLnwvNAUbGnOF+bSjQAszN2v+TpxtkXNQkqigsXtbqZzIRHCDP7o3A7QAnzNiKqqlobJXbwtsj1v0ciPyOyxjP1bJsitKdJepaZUVZ5p9IrCKqrMWswR5lIJCY0xhsggATo9kjdKR7NQwwSKZhhREagTJGOMNb5yDJqROWfFWIzXFRQIiv8fOQMWwQKYUsHPny3h/W317j4yB4d5G88YlYIaIAZGUJXjI+6CjSpwERAnMoasVQPk0DWWHP6/hL1Jj21Zlia0mr336W5nZq/1PrqKyKjMqkxUiVAJgRBigsSsqEkK/gJCQmIKQgyYwX9gwhAhBghKAqlUUqJqMzIjyMjwJtz9ub/3zJ6Z3e40e++1FoN9jr3nHlmVZ+B23d61e889d+911vrW930LCJKmojHEIiBURUR0zrN35BARPVddTYGypiIHqcG3XZNBBHKZQDLFQVUs4zTGOCokAISU4mnqJWeGRiVl02lMKSUodEWZtdVq8OVvv246HyW1wV1ebY+OD6+OoIaKjETs1JkaqmoyA1DvXRpTjhERuHIuACC8ubnt6f7N7a0IHI7T412u2kDIWYAQRMwx9P2YcnKOEbBrV+uuHfqjZL24WBWO4sXFozTJYb8/AyLparNuGnd1tVl1674f8tQHR13dcRs0AwrVVbteb7umY4fmpj69erO/FYG6XgluIXGcJPjG+YrBP3re/Oinf/wPHv0nnj0Ri8h+v++HPvjQbrYhhKauq7oJVV372lTub97c3d/2Q9+mwA51ytM0AKivKOf07atvfvWXf5Gm6Re/+HVbA1OTsxPDrt12m9V6u7q82m0vVpfr1W71w3VbffX1zfEU31zfkCIDISIbZgWQecIyWQHkC05ulhUCEzOCvrk9vNwfPv7xZ+Nwzjl++/KFQFxfhMN+/7h7gqRvbm8Oh/2j7W5zuV79gKaDSzkjsakhkmmhhsNbWV3RJhcftwJcK4gols0tczYGRf2uAGQGBr6I8H93Uy+MyvI/RESopiBW+qy0QLmabZYE6LyX1Eyj4CJDdIyoM+8SZxIaZM2ZzNVsZkWVWE64bGSzogqepTj4ABwjAM6B0QWwbCmmnKX2AXqgjhyhFN6XGRE6ZhFAh8SAZeKso6qBV7c3KfVZ8s3hTXLw6JPnr2/fvHx58/pucA4i9mY4TefN2Ow2ra8q83xK52+vX6a7+z/+yd+ulZGt9uHD5+99/NEPf/XZb+L5XNd1FWpfN4iQL6NKatqqDmHo+/NggLBuuymOTOAJYxwOx3Q69uM4+NCt2q6pqn7IYNCfTuepz5ZE1VXehyr4wOwOx6P3norhkg/kKvT+NJ451K5ppR/HNN3dHsdpWHXdarNm9tMY+36QaIfbcx7tcD96RzYqW0WaGMvsCkZFACQCM7WsZewpcCWSU8rOB0fsiEq2xYhmNvZjjElEGNCzUxUwkWii5hgu1u7Ro8vNtnv/g0cOEXK6fXUDMf70j/7e86ePTfI09lMc1LJoqkMtghFiP53MIOVsaL5yKnndrtbrDpnQE3lk58ysryo0WLcNgg798Xg6jGnourpePxU2IxAQEVaZ00V2rqoCsFVNZQjIhoQxTcM46GISUUzcARGQ7m5vDUxR6rpumvqCLxTBGFPOOcebmxvPziFuLy8Ce0RniimpZJWUv/7qRXryrG2b7cUjX9Uh1OM4oFLyydcBFBxyFSoGQBMyNQQmBlRhNobKu4vNarfbPXrySFX7aRjOR0/kHHVV673XOYO0JDnGnAXIVZUHS+cAvnb1KjRd1VXrcLm5YARS0DGzWEMeyOc8RDGg0Kwqx8yOwejRoytENw7xeL4bo/iq3XZtTbWZEXHr2/XzTV03z548ZXY3b1598+LF/e2dc2613biWKaBAPg/j6TzdnW6ub17e7q+HOJ2Hc1VXF6sdOvdmOt0cbtrd5ub++tXt3Zv9KeXq7ihIfc4gBhMlID1Px6gxpTzE0QBcYPZYFVG4ZJOsmkuF61vYrLhpq7rlpqEmUBOInZ774XRMOQbvYN3Wu6vLy/XV1cUzD218hMMzmA70b//Bf/h//5//9L/9L/+HP/9fv4EJ4CkAVJCI6i0FtuEWDRiFnKmkJODAO9cSBwPNOgDKQ8E3x0n7DnmpZIjvZFHzY6LZDgCXJOJ77e6/4cC3RlizCNyIoND6C8qGhvDQllwshwqORQ+Gp4BFFfgd9OqtTnt+J4TS8JfMS+tVFUwNDJBQjAHNEpgJZLw/34ECtAxiMSscBrgZXrz+0//tf/5TGOGH/x78Z3/yJ//wP/0HP9z8JOLh2Xo8PT+8vvvqFPdfv/wC0G2cJtApp+MwnE/DMA4fffD+MMZ+GMYpqSG6oIbH4zlK5gRa/I4BquCJnfNArERmyiY+qlrOfX+qW/vwGVzs1p998c3h/vV685wdPXt62W3SmMamI6AxDnEcM/hRVYdhqi5gs6vqVhj0k4/fe37129vXAKKOmCDkpJIzqGYdzCYTBGMogwTMLAIE+OzrL3I7rterP/w7f/zrTz/9/Ouvxyl6x947yZHWTag8giDEaZwAs5uAQcjgeLx3rl6vu81mBaAx9d6HpgnON21XqWbRnFTIUAyT5ZilTBBwzjmuq+B1BaqIpoiCmCVLThocIqCaahYzYAZCr4rJcsq67Rozqirna28m7bpqm7Zp6/v9/sXX3643j9sVhMAp3qvge893u+rpza/lmy+/8DkAMOoC19q8J3ReWnPHfFnoACazRqOQfQp56XsLvLSEARAf0KjfYS7N1BV75x8NbE7tzYpU2uZyZ6lb3hb/8C4U8K8/zBSMkctpwTvFTwGYvochvN1s//pDf/cDz596+bl4PPyNUeHhCe8+s1wWXLrxiDAPdEDRh9Msc8/5e++xEDxFZ56NAyCQDKbZNIMiOMdVk/dnsgrBMzWOXBbNOWU5jnHYNCsDSxGPx2matKt8zGkaNSVAcO1qw+SmPt7vz1PUJuSuDsFXNE0KyqRVRZm95NSfj6apa8PltkMZ+kHHfqgcb7rgiHqnu12323XH8726ipi6bn3YH8Vx0zhJWVCZnWPnvasq1zSQCUAwTUOeoKl2edApJqrATFwD733yzFX+5ubaGHbbbQgNEp/P/atX1/1Z68CQIU+C4LtmlaLGFKFoMgGZmMkh+Zba0yAi0ven/eF+jPFiC6FydVUF75EIcslEDLGMBp8lpmUVM5E+AFk6G7zYPPoJ5n31wN1dlOfwPSTL5j1g8ICuznW+LcDYuzSr7/GwYIGx3rKsHtS4AGq67IVSPxg5/ehnVz/9/Q8ffdhp21xPOR6OW67uj72rTPNwPp3399EQQqBQOxHt+3HsR6awqjdpMjAAIRWcRk1jQseIXHUh1GEUJypjEqeOzRf428RSitJnIESgIpkSEUCo28pVzIFc407DcTpHUl6tNsMwyCkTkqvqHDNEhGQggITOMWQSy+JApszqKTCAiRYpnoqoiJrlMkwdEqqgLcSOPOtyExWwS2elx8xSUHiQOs37TpcHSQGyOjQGNkfOMbMKxCmlJISTC9lUU1JTAXA5yhwoDUhn9MqkOG9jkUnNRuqz/A1LZwlh9rlDMhAsfmfFRGk+sRmvfnDYeBuL1AAyEBYaEBajJyUVFZwBpTIR3jwAA6qZIRmZqRiYsTG9DZfFvKnMsBEVNUEkRjYzVEDB2T6xXDCCwuRSQ0LKJVN5ZymWED9LBCEDIBS5WmFyEDosblumBQxZJrj+DQws9UREhVAMi/EVzq4jUi6/GoLNkP9c2qIiopUhkQoACEKCqmIKRkBoyIV8ZoY6+7IjEwQgYjOXs5Q3NTIjk0I5I0NGIDO0mRxL81jSed+Xa0sID6U+FVUoQRkXAoiMhKTl3kRFLVDQLAI0lCIIQyjjDgOYM/MAgQE1JxBUIlBYxo6QEQJ55IAAxJ7E4tTHSSbBRI7bdVs3LRAe+3tH3gQCVciITj1wxAmCAVNKk+ZczogBckppGnPOhuAbmNA8ClUyTP3w6tD96HGSKCm1XX11tTl8eyx8Fy0G+mVmJBqyqRhkq3wlMUdJmpRqakM7Tine5WlUREgKMUdnWDV+bQ2TO56PWZMOMQkycfBcrdrKu0EECFyoRKZxnNa79XF/GE5DzqkOVfChbTwRTHHIafAOnj66qN5rQb1MYOKdW7XNtq037DCspq56/P5TJeeD9wAsgiJK5JyvHLMhMrpsmmVcVyvX1itS34ambQ6HY6iJvBqnqDnFMypD7dy685EOU3z5+uUXX35+Ph0AxXkg0JSmGKNmefzB+2lMp/N4HmMSPWXz49nfXTcv68urzfsfPNpdrDeriw/fb2/3p88+v5mSjdPE7KtVcz6dDUIh8CEaYYYihbV54gMaahk0CnC82095AJSYhn6K2ytkBGLLOeVhEhBk3T1e/eSTH//mr16k++gwEFG0XAipRgomGYGRVMxwNoxHIJodsoqcS/F7kRQAFZCMitqRVJak0OaOz9zGW2zwrFBWAaGIBnnJQZGw7FBjmLncJW7Nuj8kJHRooloCFYKYoKFlZfOgCsA821W9ZX4uO3W+bZf7ry6JlyIwVzklBcs5pyTz1kZEKlEeiRiBDJkRkYwMlcB7rprq7nwWS2L65ggZYX+c9nfj3ZvhfIZV40YnKnbulYZzZ1BfejY0hGMeZDj/+qsvPrx4vO22jkKF9dPLi75/+vH77wHhOI53+ztmHqcBLDt2aUpTjOaw6prVqr1/vVfTZDbFNMaohKHbdqt1vdl0F1fbxyFm+ebbl/vj7Wk4n44njcDsq6pi5jpUddUGb3XlTbGuNlkA2PngK18xMzkmx5gdclDwOuH5KKejaILDfrRMKgCevCcDIGYUMxUkg2JzT1S82kBzGRaZiwtwnDTnHJEZoAzD0ZQzpnECBa49InpyYpBEAKBtwqNHV8+fPdtddJs1HW+vT/txOu+fXV7+4OP3NuvmfHdUSFUTrNBUK1TVUz6dx6MqSBJHvqpDztI0TbfqAlcKOsYxxiiAbVhXwQXkU39/92Z/OO85YLNuXe2S5dN4nvqByIEoqLJhhawuOGJEBTRiArTJCMmQJBVvgjKzCUBNUxwK5hWC5+CYWVGMbZymlDhWta+q4EPXrgxgGlKcUoyzQ8LLb187qJoP2u1qx8RkYKLRRcfsQ9CcTURTrLyrq+2m68YYJacy0fN4OoaKqqq62O46Duc0cBJO0rIPXDXsvPMiFmMS0ZRSzgnAnPOV5+2jbtu1m7ZpmroJ3gN5sjilQlNaV2sVHafB+j7HKUsKTd2su6ZqidyuvshZRRRGdRHqqlpXXeO6lLL3/nJzFUJYda1mubu7v7u+ns69A0TRw93t7/3kD8nj8XD7+vVXp/Ptm7uXh9OhWfnQhaZustioerw/3AzHuwkmgIls4jwwDmmKMpOZ2MG69mYZZAKNjMAIKlD5NrhKs6Y8xpRFgQhCAO9h04bNtl2vKnZGnB1MmkCzpD7mBFJPzkHkiStfp+5ZV19tnhm2Q8IMzX//X/9P++t098VUPQ25N7YmTgrm9SgjjBAJA5uZZlUFU82gZEJoTBQzAfo5TM4yjxLa51BlS7drMQCcSxAF8A8m6wa64F9zhH33+OvyLFyo9KUfiQBmtAwNhLd9SHtbkMwCMwQwKiKhh2BaXqpwUx9cCqmYW7ytnEoXcY7gqKVwV7VC/QfVIq8ic+CDF7PahyFOBKakwKojNpfIzvo3zT/63//V/Wv88OOrn//Bxz/9+Y8uwhq3fpMPFXXPnxzenK5/+/KzYb+f4uARn16uzzGrmGZRyYYIgOS4XofEObGPxywKZrlCDo69Z+YAgAJoiBF7ozRpXFXw4Ucgeso69mOsmtg13dVlWIkfI2ZNogwJxgzjlEzTmIAFah8ADYlWq03TrojOUwIEtZQUUadFFm9FYwLFtQYEAQIxnkY93E4vv37z9//9v3d9e//y9jZOveTkfdv3MQR0LhQ7PtWsouAMnQGNwIBOm86vN03fj2aSc045OQ8pjwCiIN4HAp6y5aiWM2Rw4J0oEgKzIuQsOUUwYeeIQE2g9JPVzAiRPAV2wdTQJhS9O0xt15Ca5YkDbXcXzlcx25s3+6+/uvvZzy5WXTuO5xQzC/30k5/lc3Ovd3AGcQJkaKimVIq2sjZtQYuWdJvoXXoiLBviXcB0fjhjL4sRSfn9zBsvaYjB3H57eOK8oM1QoFj6Fx84LcByWcuzPgsACEnfpjgPOJjhO6X7fNoP2+mdLOThzBanBcQi2UFcBgz+dQcuoNvbBvrbC7D0z+cHhA9Gz4ilJFG1B/IYGhobSLncD2gfGjzY1cyiZgRDIEQrEhp9gMyX08CHnn6xe1FgJUOk+RVKfaMYy3wuMgaElDUBkffA5MjFqKYioqDZO5dV8hRjtDWsJOU4xZTA+eCqrg4N0XTuZZqGlKVjDt4RQtIUQD0IoKrlLJry5KtqvWMDx4eYRnVeqxbrUFG13l1024supiHtTz5A03KoQc2Y1LEiY3DkmAiYsKrcKiiJ2ZiTZuBQScY0ZYSUaHjvg4vLx7VSznraraGuak+1RZ5OGvdEqr72QGwgddUyOcOckypm8MAePXtCJ5lBMalm7ceYYho1Axo6aD23zglyAkpqrIgKRKxmbJpngBXM1FCBS+U8u0YDwOzKD/MNYQnIb0HHWSw29yUWDuQCHpcEXJfbQ7kVGWCRkqPiQiAs+f0MyvKyCQQe3MIBaXH0KI7hEIAb+vBHF1fv1xSmaoN+LwpTs+oEMcWcJhsGOA8QHDjPYCElGE469EAk27YlwJhGscnAxvNZBpNa64BOQfppmiS0FTEieRIm5wBBBDRnZrSCp6iZ5YSaXKKA5BC8Zp+TTcJKHtF0PPcSZdWsECj3J1QquJIBmNo8261ABlTgqmXIlJFheWoh76NkAMXZ788AxUBnvlLBSpavCIyXLTiXXMrgDNUK6JIBBIQzeXLMjIyCIIoKzsjMpv4MomBAzvvK51EMwKR0SMhgmRhqc1yfwyAViKjo4KjMSDUFZJwj4SzTM8UyXqswwJcM4CEMLfmKqAoCMhIDOSrjwHCxZ5/Nv2HhTsx/O/fxiAjxnR6EzhepmM3PxyyChKVWLOLE+bVms05cMNnZmbz41ixGN3NgnYlHYPM5EjERmpmimaiYEKAAkNqD+5vhnPzAsrucBSp1ImiRVup891HjQj/BeU8BEWG54LZ4SCUotEkDADZDUysqVASEhKXHBYJZRIXQFJGwIofM0gCqAiiakSJlJSjsFyNUFAAtikJFICqiQVI1VLMSqWkRBhoBMBjkrIjgHKMAiJamUPlv1oyITOSg+D84dZBZhUGdCpljLTZlRoyITKimkrOJCeSIyq4xFR9gmuJp7L0DZowpxyRBoW2qdGt1RZKyJkGGqnKNr2p0qmpkU+wDow/c+ODQAar5kIN5Bl9553MWTTJMx1Rd1hJTWwVyiii7R9vP+YWvkNTZiDEriLEgGDGbJjkdT7vLK6tVxuN4GNab7dXjS1e7w/GcBVarupJR3ejr7snzJ2lMour3rMnMsgt67gewNAwpTnJ5uXWVP4+T5DHGYd3VwNquPJlrq1pzBtOUp9s3N46oCU1dN2213q6eBOpU2pTC8ZDevDwe709IAlQy5WgwAaKqqYEPDohzzAZGjORNIddVCHVIMarpet3uT3erVVc3lalOMampqUvJqeEU05u7Ny9fv359/eog977idVdXHs1ySkOc4AcfVsowMZwgJ1XOCmmYpkwEl6cGHCnwqltdXW3rbvv06aen02SsoXNP6uevv/lLgA6QwKLASKUrqQqMgMDEjAwWJUNdwddfv/ANtSu/2a07S8xptQag0/7gnHrv4e7+er3zP//Zj1589SKHQM6bgsWMDoG4xAUjAzbV2e+gxLnZxGEph4p1ngnibCxqiEBiCFkNoKZisF46PUsb5yHRQUBQzfP0hzIDV9FMTdT7AACAqGBqKoogOtOxZhEyGiEhlXy3iMpLrynFXHyzC91KQYuUC7E4Js8NQyojCYsAvNzECdRII2LgnG1/fwAPapZEEAmYZMxN3SBRmqIAuorLkAfnyVf+bhwVMgKKg+DhfErD2TyuHrUQKm9pJIyVEvUaRqExSY5Ue/U0aP5nf/UL+unvc+1DkiEdH+92lWclPI/D9d3dV99+s91uyYXxnMY8VJUP6wodjVnkfDoNvYyxH6YpJeaw2l1UzSrUHTXt/TDeX9+Pvdwd97fT0OdhzADqIaONA4hWWFVu9OSbpneOfv6zn242obNpyoOaZk3I2G1r33gwdzyOabDTfuxP2QT7IYECOkDmblXHlMgzxJxicpUZGjlEMFAlQFQDFWIMjhhDAogpjj14RnaMhJrVsgZiJAwuxDgysve+qXy3aq6udo+fXO52u65zd9e/Oe3f5PP4o/d+8Id/++eX23Yaj6fjnTP39OnTpm4pcAYZhvHucD+No6nlJFUwA7jcXTl2njwpg4pLzoyqEMjDFMf9eI4xA3jPLTEQBlQiAwdV5XEcBURRhMycYQWOoRASEzFUIXgGclYHFzHmlADIEEU1qxAxElKZMwAMho6YWeumyo7X77+nQMzeDGLM2bJDVISUpnFMfgq317cfffDRdrNDg5QiIplkA/Pe5ZzP5/M4nuu6aqvKt40fhv58JsS2aWp2Buadb3zlDc0YfB1WyOyZHQHplE3BJdMkMkZQrULo3KqrwuNt8GQOFS2ZcddWjpC8Pw5HFV01K/JAwo9XvMmrGKOrQuNbhyGL2YROOYhbU9O0vFqv1/WWrZKsTdfu1rucZTqNojKd+uPt4Xw41MFfXV2tLi+v7/dY0bffvvj081+eh9dqw5ThUbdxgeMkxyGJ8WFMp4iK8Or2cNufJp+0oaTiLshjQKHK2W5d94ejR/OB2VUtqyXvfSOCSaIal55N18DlZb3eNF3tmdF5qyusm1qsn8ZjThJ7YISrR0+YKshQa2hkU+f1eA0vPn399V+e5dT+X//LLz2D9sBaeagsalADSnOYhAYjAACqoimhAUAWMRjYuWy8VBBlkPTsmgEzJeg72JN8B04Cw6XiXjikAIjfJ0PN/Wb4zq+AFOjd3xV/noXWD7AgWFgUf/i2JJ9lhFxql7nkNQWU5d8e3l5nPwZbPiAYAZc0d04xAQm0CLNxVrsYAIgJOopTAoVcHHaUyTT3jFW4PqSXf/Hnv/31/cc/fPL1p69ffH63vqz/nX/3j7rmiqDhSranl0zhYv36zf71qb8lD/f7idAzIqEaIVBOFpMJVdo4d4zAQIjkcqpMPa7QKCtpNNU0Toe6hvUOnn8YfvSzp5+9/oVvyMzv7++ev1+DHQikciBjX/lQXWyGUadRzbjdUl1NzJ7Ytd3a182zpx9Mx+sX/X3qo/RDaDoZIxsBOlUEyiVsMDAgC3qJxg6Hg/6//+Jf/kf/8X9gBO2qPd6mY0xt50Xy+aySJ2IJDThHnrCpuGoMNLYdBE+rVVNV7vr6iAgppf7ch6od0sOP+gAAIABJREFUDkdm8lVlAmIsAhJNRjABZqyc14yiwohAqhBVzLkQahLNpYuFSoyEwB5bR85QjQVdPtzpujJzmQBXq65btbf34+Fwfv1qf3OAOOUYBpW+YrZx+sEHH//Vn78+HI7gQLMAmrGAmczyOphtBK0sDi3GKlScANSgkMABiukG4ANuM7vxlj/EOWkoABHp3ETGRauIZksba0F+ba6qDMAKz3FmuICBkgEoGhoRIDsyzbrYWqspWunAzWjCQmIpOJiVTVwsvh4kjjP0gAQEzKV8wLfuw+/s5gdoemZnLKDVu0DW8sCKXw3jwlGb62e1PHvdwSz8M3kwlTdABLGFU28zFgHzpC8gdqXaRXzHlL58gAcAa0YyFDAhFt9qNgNCMgJyAgaqmnoCDzf3h2N/KYZTit26xiGaqkOybHXjE0RCa71zFpwBm4sikxoPamBIoe5qyRlRTYSJN5XPympZ4yApqQmTM8hmkw949Shc7No4gZm1jd/tLr1v+3Hi4KY4jMPtZttUte0uILchRQ8y3k3JOwHN0yTjOUsMmFmiqVJwPgtKyoCYTJra//QPPjE+9dN4eeWIfc2Vg3q4l+PNoJOuuuCsMmT0WtXV/v4AYOihct51FgJ67xn8qc/HYeyt5+DRYdUAEVgOaQziPWLGkKBOJGDqsyoileGlgMDMiGhJAQCNCMr855KGywMW9YARvEVWZ5C4FKczCqugc3JsDzDwvImKzezDn9mMEsyQ6QKSFbTYAWSERQzFM4GXyGWN7Ig9RoOf/J3Lp5+soBr2w10TeUjHpKkKeNWuvvjsdjzknLxnV+4MOdHY5/FsaQQzGFcWe5tOk5qEAKAGGcSAqwa8uz3ejll2DRKxY0dGrvZVjdNgjGDe1ExRIQAwdJtQrQIH57xLmuMUc84ZcxWafjinGCGDqrpIMIBJBkYiBoOsubgxqZpjBoM8TaIqkhFpuVHPOxYBMRsWHV0JMlgeGhUbSwMQmEHm2cK6KO1BDXHu9BsAmNjb/hWRZE0pmQE7V9fOwOIUk5qZUWnjGaqozgPBBYgIkABsxsuLnzouI4hLocaFNGDEi6DZsIRYBCYQMDEjYyle/6Xlv7S15hymLAcyJUDW4pVFTHN5KLYEsSLJeXvA3LF4yG+QCUBBp/L6c02opmXCQC5ipYKSEhaBZ8kzCg4GAAJUmkQ2Q7lL1ILZU76EM9OZMIGz8aIZGhb/lQdhthkSYlFlwnLbQnPOeSqiRlJQhPI9oRECIOPsmr/U0kzE5fzA5reamwSFZsnEjnneagqqCoJFlkdCCMjkHCISuRAK9qWoQopImVRY0aHQ0vTAxUKMgIjQZjv5OOZiIk+ll4YIRjlnnGWiOH+A8m1RCfcFW0QpVzwQBQIv4DQSIkFVVy64OEyUqRjBiUmKmKZYyH6KGjWSopIyAzIuKWAexh5JxzjyEc/nARSaBrrwuKvb0DoCNMZv7r/t6sYzs6BNfrfe1Ls673JFL46noan9MGTNWDMqiKkyuaYO7PB43D/7cBuHNBxjUpWYQVSEUE2zGIBfVWPqnSdCEIQPf/CsvQzn2N8f3nBt7334qB/6ENqubarQDf14PJ4ud5dt14ikaTya6TRO+3vZbmC1apnosD/kPFS1O5/PYLJbbRvvTeS4n47HU62NKiL54NcXm6vLzXvBtYe76frV4XTW29v+0998+atPf3nYl+ndC9ZLS2ApCGrJiAJQDYpQM1QBpgQCsOlg1fi6bkNwWWI/HrMAO0du1Y/T69MAPQBBVXt2XoVNOWVTMRN2rC+vXzbNGohDHQSmYdQUDQCaivpz+vQ3X+5vj5eX26tHTy4eXf3hH/3dv/qr3wxDqhqXJoAMYBGEANSYigF62QAAQECOnAuoINHicX/miFWzq1eNC/UwXddt54QMtaqc2nhzfXPRPf/xj9/7R/8HmVOVmCZjNBEFLtMrAdDUrDDDi8DFxEpjoFRO9tCYAzJTKLsdZjM4NXPkdCFOLhjWQrcvotqZt18k2SU0K4iCWpK4TG8jRGQkK+MCZvi8cKsWWGq+U86xA5fbclHB0JwfzkkiLOoEIkSaM7CHNlPMqcBiTK7gXOUa09J3KqdfXk5NZwNvR6tNtz+dVGEa4rqpLi5W/WnUDOtuzeSY6dxnQglr31h0TNM0nadTBXXbVFVd/ea3n1807bZbb1abm9c3jz94P0nan4/H4+FwPt4f7mJOzA5EffCb3Q4rOsbz4Xy0k9KYh1M/TtH7ZrW9vHr0xIWmH+Pd/eH65vaf/uK3wwTPrhy3ARirprYMOapMAMbX93sHMPRACt0a3n//w6fPrxR8vB/3+/3+cM8+uOCIfN/H+/tDf0zjKecIjhzEOQzOiSuiSmk3ATGqltn0pUeNgCZZwCyEqm1qq5vz+XQ8DWm0hJlKwg7zAA21LNlU0qZpLi43H330wXa3QrSUhv3t+OKLT0ng+aPHP/3xj/7g9/4Aot7fHDXaarXZdLtVs/boD+fT9av7U99XPjR1i468C5Vbr+pLADK1nEUEPQUmS5DjlMYpy6TO1RfbJ9utGmdBURCyRFw3rb1J9+YoVK2Z5pymaRARJBDJpbfknAXfiZPJpnN/zjmrmZEqmvcBqIzy0ZhzSpNBZqfE5NjVTcfkkXgYJnbcbhsgjFO+3x9OdmIKdagcueDcql3FNKhW664exzGleBjHNA5THFDFO/TOBebsXM557IfHjx/FmMDAsw/sMaBjd7ElJhdTPh6PlrJ3znmHKspOGVZtd3l5ebFZ4XRAEBADMU9+1W68C+M4HY/9MIwynZg5JwmuqusaETl4HyrnAyDnnJu6rqgK5kF1t97UvsuTeV/XTXMaegQEo2HohzG6qnnvw91q1TJBAvsXf/Zn1bbe71/f3N0aDFVDoVIfPLI3gmw5G7Fr1tX6om2+/PqbfhwBiX0KAcysDcGpo5xiHHMv6G1z0TjnHSkIqUx9P4y9AEhTQ9NU22273XbdqnIuqUxqMz0nR8mTMPpt21YuSO+Q3JOLJ09XT22Av/jTb77+/PZX/+rLX/zZTf8VQIQUARIQCzlFMi0Z0zsHLrP65gkVs8xaFha+LjXoQwv8oex85zXeBaaWMTiwuCUsfPC3FeTyRPjOyyzn853D3v6NPTgVFrzqO3yuB3rX0md/t2j+XSnVd8hf9nDS7/5rSZgeHCUWHUyZ8K2AiOyKdgXRpUnAhIDEw1f/39dfffn1P/5n//zpI/jwk+f/FfwX26vu0XvrqvKXaw6hOo/v7c+3r9+8url7Uz2zpOn2IG9uz8epT6MqEbELwITYOSgGvpBMRTKOiCbiVFQsnkZQgJ/8uPnR33q83TW3N6/Hfoo5O9JhPItMWWJMMMVcEzddRw7YZ0Rf18FhGIfJVDWnnMZPfvD+/mZ48ds3Yui7Oo/RpmS+IiJi0DxlMSZgUnIoYoggmt/c3gDCq1cvH11c3u7vb+o7muD+9khMQz+lCE1L3boO3oCSmKlAjKlu/Wa1DnXIqi6EdrU5nU7ZNKshVwJT7M+ADflAzN57UbMokjNBmFKUDMzOUNKUskDTZs6olq1MGQY0YDCOqbS8RLKpAhoc9v3ahceXTy6fPr6+Pb5+vb9+fTydomNAwOPx4Dl3TbWpL65f3n/9xcvb1/fwFvxckFhbCqCH1vbM8yg9tFI/L6iq6YN128OKBwTkmQU4L9NlR5bqCuGhQV8eL8gtkOJsDPPOKc1/tJShs46wnAUaFMlteQdGLqWVqRYjlUJJWmq0slEUmeChvYdQhtUQLeXf4o/7XXXh8vmWimtmJyCqgYjAX3fMmDMsl5bmjfYOfAZWbPeKr/yyPeEdclXZvHP9BmDzCLt5/5bdbMXTFJTeRgexxf5bFYjQeTagmJIkBYAxxv3+BF4RQcVCqMyQWNo6eO/ZuboCx3Wckneha73AdOj7/vqO3GnVhjrw7mIFaTDL0zgF5wys6HIKHMDokLJzRFgFCkROs5oxQEAMqnTYj3I7GU0c8jRNVR2ePX3m3Pp0yJJe39ykLHGaIE/Wj3k8G6lD4WL4E6cJRIVhdek//Mnlo8frc0yn6U0IXDVNW61Am9PtYTxGB9y4LvZpHHJwlYlNY0aLxrDadK5SRMlZx2Hsz/04jloBqREjIyQAQgeKaYw5RZO360GLHN4M5uJ8iaXzsl2+ZDNVxcXKtiRcpvqdaPy7R0mPy8w1eKjxAQGAEYFM34nnZjPG+c6z5mm2xZmp3FmNAFxK4tDIiCvOIPAt/Ft//6cj7O8Pt8n1cnIpQdt0YBCjikJKOY5Y1W1OcRiG1INkAGAm1my3r/fTOOiYfA2hqf2azy5CFVabylecIHhLjNkxOYddqJrHoRW/94f+fqjrjp1zNRtrtBwa57vA3jl2U4omqmJmMo6Ty56ZJWdJ2Qp5RgDMjBWQ0ApxERkYC31STVVNjXnGp9/eHY0QZh88fLjhLT9xSQEMwBZxbgljy233IZIYFdoq4uxD/ECKnJMDZGZVETAzySlqVlWdhaU4lzcllM1I/YxFl0mVpqWppoUcW4hXZrOdNxS1GxgwsmN2iMYgxdd4Drtz8WcgSyiel2HBjxbi2vyZCmb0b1iSc9JjhVbxDut8EfQtWRCYmCwsbysNkPkugQ/louFyaylwzDtfAxazfAMDIyNTUy3Co3lO58O0zmLoNBe4CwXX0fIpUYuTiqnOXCQuTkgFOxMBAHVEQGomJmZWfL9MoFj0EBITERGozYsqA6hJzpqkmGAIKzhDc1pqKSrjUBCIAHUB1mzuWDAgg3FBKm0m1y4440zGM5zbHfPvrUzRePeLeJjrYGCKxeBUoAxvY/LOyDskQsQyipgAzZSZsarUQDWFEJz3XdchWYwgxjbrRoEZu67arla3b15bFsgAAwwGzaNm21zUvqp9qFbt3d154y4Cs2gM4jq+vNpdbTebLjz68utvUtavD9/u93e73YWi9seTas2uJYHT8fDBe+8fb08ECjYOBhDBkmoCcBBaWq+6N69unXKupHtSXTzejHA8nO5jsovL0LYNexcnubu7C24cRzkejnVVA5CKeVfttrvUDse7Q3AQvBeRcRxFplD5LELzIqdhGMZxYsfb3eNnj3fDaXzv2Q9X1S641c2rw69++dt/8o//+c3LhEbJ8jiq5zlVmSFUXRoRhoYmAEjggDDP7uIxQpkRHI3uhlSF0XkyM7Uq1M5xw855ghXGkwkoZEmharqqbeuWUNPYKzKg7nZbRRv6qR/i+SzjAKawashTIKDT/TAeh1ffvP7wk4TO/+CTnxjAy1evj/upH0YIAGmEzACMyAVMgnLygKagBkyuCh6yDVMEgc2UzKPFhOSE2ZFj79hD0tPh+HJdd7vLUHf9+JW4kCvfCankXObKqGlppoEJgJnONZGU4bvLpJu3/UMjMAOGIvIrdCie0eg5IJag+rYz+RaUn4NtFgE1kCKFBiIkVmMHZAZoKu/WZMXGHWl52QddzRysFlEAInKBs+3tWNfCJVUrw2uRZvQYCM0AfaFmWcwJHDimbGoy14dJE5thQPBgkBRykWkASlMFAzf1t+t2fXF5cfv6Dsy7ih0xMzCaDyE4H8BDgCgxirrCNQ3uq9d3nzaf/vyj33t8Gfrh7Ji/+eabF9ffJjAMgRz2caxDfbnb1nVVhTBZGsd0OJ2SxBZYlapms9lcrHcXiH6c8uvXd19++UIRP35+VVRswqCM05iO98fpBAhQedpstmSEeh6HOE7w6uV1uwqhsZimw/EwjoNXC4Q529CPMQ2AxARRJYoWCJgdE1HZm6pqYkDAzCJzF8WxA0QVMTVEr6oiEkLVtivv6zjFKY4pCpj5xoFpTJKTKEBTA4dpu62fPtoYyPXrV8fTwbGtfde2+NHTj55sH61cd3h1Px3jttlcra/WYc3ZeV/h1EtPLN168+hid1GIwG3T9qdcVcGxdwRoQuQMo1nfVG0b1rhWQzHQpGPSaczTmEcwR6xI8OTJSuY1qyKS0jRNU0oTEfV9f3t3AwCr9TpBzBnrmnPOOaUsySQ1vgUEM80oYpoymIlkHdOAiKvVpu18CJ4qziyiyi5sWv/o4pEJ3L86OHCgmqcIoJUPWRIYYF05RyYJNI+jc4G8c3VdWQgAcD6fp2mCeZ0rWAihWq3WOad+PIOg5GwijrlpGkJu6rqtMyLWdb1p26auhl7ZleEfjSOvCtOUT6fhdBr3hzPkMwGqyDQNofIXV5ebbUXog6tDqERy27RpipSR0TbdFo2Pw5kBcs77+/urZ8/Wl5fDiyzDuHv85NGTKyL4/IvPfvXrv/zVl59ePbskjAJoRnFSdIDkQ7Xi4KZ8PveTWA6ufvrs+WdffFo166b2oJNDDYRsBDnnFDVNOoEP3KxEJcY45KzEBqyuhhBgu6q6blv5FoGOh7i9zKElAK859X0PYrXb1a6OQ84Rq7D9+P2ffPDs4+FN+vSXX/yT/+dffvbrm/01WIT1pjteD0QEDtBQZNKczRyR/x5MVCZTL00rNDMVIVp6Yu8896E+fzdk/U4uhw+Z30NisXC2/o1lyfzUv+ZJb1GkB3aFkuE7VfF37Nv1LSQA+m4m/s6b/O47fN/b5+FqvPMb0LmfIchMzIAoKbW7zXG/T0OPIbi2CcEjKME4nfXFF2/+u//mf/z9P/rxn/zn//DvXv4eQOKqigNfdptnFz/KNnz58pencV/jpOMtSjwOkCKAi+w79H5yLiVNsdy8LE6DajRjAxKUZ0+BCa4uu7r2WeV0Pjp0xMmApjiSJ++ComDKYpJNgTxQkTGAqk7DOI2H/pjA7p9c/KBd4XpFx7OaTzplRAfIEpOReOeIBE1FLOUoEX3dhLpOoHGK33777eXl7v0n77988Sr6dDrlqnYq2nVdVTkmRlI1Gcc4TJERNpuqaTtVO/c9IDRtk1IkZ6GqvK/V6n44T1kRgYgUyAcG4GgAplwEZKV6maEkVUUxmd0DAJHRgHLKKQlhqdjw4hJEoGu3u92j1ery08/fHPbj/hAZuA1W1bWkRKAa0berLz598fnnX9+8OTliIp9zBgBEMTCjGRFFNKS5Vik4lc4TNB5c1cuwdXvryPYda7dZMDWDsbAUOTb7xwE8+As8ZOMAUOYFQgGIC9hcCh9c6qvSt7FZGrJ0t5bCbEGXceE/lcqSzRaoel7ziLzgVm8/CTxsY/xr9z4uo8FmkKFAa/b9p+IslvnehiyjEhas4eFsHuAMnK/Uch64bF0g0O+SIwCAiJCK+hiXq72kh+98B8srAwISEylnVQAYzv3hbr97ysG3RM55h+RFxDsO3retTn0WpcPh1K22pUEDaqdTShpB0ub5ZVfX4yGn8SRqJgkRQt2EEJzomMWAtqt1luI1r4RCTr1bg62vrw85j29uj2rjxUWj2Q+DBI/s2DluGn78+PL2zTlAzikngayFPJoR0IqbezRAgBY++uQHP/xb7ynmlKLotF6vutUOtUKrSY8Steaa1Z/2+zSYtaiKaGh5wWcNzGAaRzEYpinUjdiYpwzOeWbwWu62OUbN2ZZ6FAEQSSEDAjGDmaogQmH1LMtoKceLjgoW6UFZwd9fV7iMdLNF07W0fL/TTEGegam5VbmsBC4/31lvSLbUCOUklMlVWQckLzKm0SAovA+hci9e32CA7qoRAVG36tbncbq7O/XH5FwlDn3gHG0Y1OLonQuu9sgZVFL2xNRS5anydRO4blPE3LZeXA5KIQREYxNGZdbQsG2DToEhX24eMXlfOWU7jafT0I/DgCM7H1REEpgACcaYySiwy65Y4mabMdoCfhSOpkHh3JThgcUB3Eq3/23oKWCB2AIPP1zkBQkv/NHZWBLmsKOLoOw7X9b8kxAffPHn+ykRppjU9GHzmakoSSEhfHf3IxZtMHz/Dq6mM4RBaEiFjqBF6L18nnmzKzpX3hugsHNm/8E506B5+NXbpVGqbkCYQ/rD73VZt2/TmwcUZUbgdTZvV1vaAm9RMJo9msrZzZhtufRm73xbAPoWCViykPlyGACCiRQIDBVBQRUW5Os7x3x6C3RVDodKyyQnAANNCqYLjAtAi8UVYqE/GWJRN2W1pnIluTLFgl2agiUt/QHIiyNDucQlV8pxypKZc4xABIwYEB2YBwz2/1P2Zr2WZVt60GjmnGut3Z0mTkRkZObNvJ3vdTWu63JJxkVJhSV4sSUsBE+2eeAfgBD/AcEDPCF+AQ+84BLIAtkYhAyFKKqKam9TebvMyOjjxDm7Wc1sxhg8zLV3nIibVZitUCjinN2tteYca4xvfOP7uCr+BjSuPoeoJBVWRqhGi1CXm5qZiIqRGAAIGtF8lhUy4iyqDwbAplhpgghg6CCBxpTqKQyhccEj0XDozbRxDZjFlJRsuVmsVou2C4gQGo/MjijFSWJlPRgzKpp3uGw9sZZrKJja4L72jY/uX10t/frm1e2f/vgHN092MAI08Dg8hXoUDqABKAABPvr00dc+/cY3v/7p0l/97IvP+7Q3gobDNE5EZXO2OD9fjeNuuQkff/SthhfXz28+++zH/Ra4gZLALTi0BAO0wX/4jU++/u2PMw5vXu928XpzBm3rSsmLpi2xf/Hi1TQmx0spGjn1+36Kw/3L8/Pzy27h/NeK6QSgaUwlay5ye3t7uVmrws3N7k2ROEyb5Wq93JydnW/W9w83L68uPn3yxet/+c//xT/73/5k9i9vICy7pmlaH+J4QKiD16blCNoSVpgBAUwsFSAHdfPPciRopiDgDlhUFIoBgVtK22XBlAoAQLcKvm2YOY9xHHJLhQByQisEqHS/ndLQD2XoS1EIHlSpZDyU1HjXki9Zh/30xdMf/PEPfvD3/t6/+cHDR13XffbZT6YpffD1zeGm9NuMmQjZMoBm8mBmCGzZohTfcC4aS+k2znly7QLIDn2f0iRJ7591y/vdMO4O47VRP8ZXF/cu/+E//gf/6X/+TzoGtWJq6Jx3aGgMBKCIKBW7wrex6u0d7Ai+2lE34ehUWpmZUHLRk/jvu526474Hq/i9AoiBClQJGwEgEDRjE8wzjQuB3Uz1mVNRsaJ67EccY6UDU1UwU6s6C2izPJudMlIARBRVKMqVVc8IVfisZAEsMR8K5RgBoaocggEyAYuCEqumLDn7jpebNqwQvW23rxmXbdsEJs+0WSyfDF+ul5cl5SkP3hETLdumacB0MCpFwDfoW0cBxWmf4Ps/efY3v/v60ScP15v1Aprd7c2r18+XF+dnq02zWGQpzbKdcjr0B2ZUB/tp2B0O45i2Aueb86uzq8VyPY7lp188v7nd3W73ucDZ2b1hSrfb/ZSgACxWsF6fLxZnUIZxyIdeV50HAGR2gVXlh5991iz4028+EJE4xaZpm24Rmu6Qh1wyIDVtg6WkKGDogmdi7733XlVjjKUUNEQGZgYAU0AG57mUkqM6j+YgxnSz3V5d3vfOrVdLPmM1VdGk0xB3OeYCuln59bJ5cP/y0QcPusA53Y6HnYw7r4lK+eTeh3/ju7/8G7/2tz6490EAnyRt1psP7n348OyRqe37ISwXl13IF10GvLy8Oluei2kqJfgmkTp2BGwExGqGHrODVYEklLUUQCGCjpcNS/ClgylDKVYUrY/JpOScVdRAkZrlikLrAcBUH32cU0opxymNWaJoLiWrCSESQwh+GPb73a5Me0y2wMbQTdNBB51SHG4m5x0SNW3H3jdtGxZNYGeEYnK2WoGAZ0YDR2QiOcacYgihDb67uDw72+QcRSUE37WtAQTnHfJAvYlJ0VyyGjnnQuiWi3bZLba3bybQZdvNooWIwYX1cjW3eayMu4O30FLjQ2tCr1/d3m6/HGOqjm0E5F1AIBVzvOiatmvWZGE4xN1NLyIPHz4MrV+3y01YgWoec78/xP0hjmM/pWevX2Fo4TAszi7PHn7w6s3r3/vjP//D/+f3Hz/+iTCU4P3Kn23axXJD3DXBOFDTbaZE/ZSePb959uLN7gDdEpars+EWuoYdOMg95vxrv/S9l0/fbF/fFjLwaGBqUiZZnYc2uCLjYontgs/Oz5j8NECObAUJm0B+fZFy2ZdYnOOz1f11cw4R84Bnm/tfe/Ste6sPfvzDn/9n/8l/8xf/7A1EgARwDkAOouU4QgEFBYRCigCkoFBmZ4p3s0GYFRagiv2LqXP+re4UAABZbcLdLS7uRt5fSJ5Of9fY9tXP+1d+vINhzd/q7lG891X0L/3NX/Kt76aqx0+Ekw/j8YVmBCA6J5rH4ZX962tAIOcZWYoM/QgEi7M27vR2m5598fzP/+D5f/tf/+/f+s3wb/+Df+cf/aN/75v3fgNIIsR9fP7XPtpxeAC//J1iNsTh518++fyLZz99/EW3OuOmOffNoe/7MU0lFYBhglwEEbwjIP3tv/tvAI5EfS7b7S6WPDXLs48+/nAYBgDzjbOsChIazhn2+55dI4pFTEq6XLdNE0zt0G+Hw7PLzfnVg+ab337w/f55HgoGWoQVCI/azyfMyGzWhkFE01KSZEsQ4f/63d/9zX/9tx5cXnVNG51MOEgqjW+Hw9QPuUB40K0X3Srlw3Y7fXCfVuvNarNJsdzc3rx+dT2NqQg4B00X244BJGWIuSRLNpScMxEQYikGEJq2CYqSJRdZtmAEzunRGR3NQEVLKiVLjMnMiJEdsMKjDy/bdvng0Yftev3mevjpz569eJ3JiIPb7eM0pLZx/W4L1PB68f0//f7zx2N/AAdehRyH2dK46jrMJD89ErkVqGpHV0HMY0E0Dw3asSyZ191Mzj7+ErGSuE1nUvmsCIRHFes7GKoeqzurva8ZdMKKreoMIAEAABrVdjoSE1a/Yi1FarZT+eOAMzA6t/OgqiWCSEGHRMSOiJkIhTTXM6BqIgBmx9HIuw8CIK6zyLMmrpS5GPr/+TiCTIAIs18WGYGBiMw8tjusdjAUyKcirfJE5bipa9xgZkC6Mx7zzqO9b9/pAAAgAElEQVRilM7QGZJzCdPN9e76lTu/v2BqRGAcchZJqYhi093bnJ1bCbe3Y5x2baeGYqq1c5onGENSEHY+tBQ4eEeNbwCoKBXFKUXJqEiLrgNNIpkchA670II2j3+2+9EPPxeBnKAYbLdpvYHzC/ZOh+GgZd+25/cfXlxuVoddf329vXl9UJOcwDKYM0RwHYQLPF+vrx7cu//xhevk+ua5Ql4suxBaLbrswuHNtH++mx6PedNctOcdr4vG6Wac7OC8r2jTze1hZXB5/1676IZp7Pu49hio2Q8DBlisQ0tekpjmRRtyY02g0qiXjrGRlHO0OtUguWiRouqdx4qZnEBGRPJ0AjJgZpF8VVukrofKsTyCWLVXfVy+cx4+b4dT+8G0uk3fjfqzAjSgQTX2ITMHFtCBDw6xiRC/89ce/O1/61debp/dDNdn7QPyzRCn/U427Levp88/74ce/vq37skK05Sjh6bjsYiIZRXNJQ/Txfpe50NgkjzlMSL61aIb3Vh0HPaHKSffACIoOiQ1zXkfh+uYDgAKr25eErn1+WZ9fta55RCnOKlzLCYp5tjHlLJMCgnMmXMOjSWJKXhHxQLRPIllYNX5Dg1tdsaBmlxJ1NlScEaCARCIfY1q8+mtzj88U0bF5LTv5xAms4fV8XK8vVKVH5dLqW52BoqAIqeLdWxFqYGUStCz4zQKVUbl0ZVu3tfHhULVMtHATMCglCNT/Nhfqxe7zj/GHAFR51J6pplXHSmwyk19610I89qhin7y6aPvNtZO4VjFAN429RTUjORup252jSAE8kzs75Ak7Kh0gAA6k1YQwPSIVxm9Zd/OhLGZwaZgVJGCChOxnUi2/18PN9+P1IgIELRScE8nc86DFJmBjZiRqI6h1LNFXG0FQNVU1NREK/UYcZZTZ3JE4CQUK2JqplJMQeuZUBMyNlAjIPbsG6KWwZmhAmEGEFKq9bSYCaKeLNnAFMXURIBQkY53VCAiZFIWM0GuIjFgNZWtCBgdT+Os5VbKFMEgN4SAJRcTiyE2bTATJAYCIO2ncRrHKUZVYwbv2HlzDlSzh3Zz1i7bxaY7CxBuntx+efvi5tWb/e0AimEd6sCDlgQGjrgMYkUgw83jnfWf716N3PlHV4/2U3fTv3yzPXgPi7ZtGjeMh3sXGzMFLt2S7z1cxfJoGFK/n3bb3nvMMN571F3dv//Rxw/vf3T++dNrpbI5C90GgaTf7yfOh/0wHOI4aXCRyRWTaZriNAZkBHJ8vrlclmyHfieWGAl8QNSm7YLzh+3w6vVNGqFtSiqqQuvV+cefbH72k5ff/7Of/vyH13AAbh0wAGDJCpia4NX4SHeug3iVZIiqQHocKDvOQs2dLkQgKEUWmxYRBSRLBoTVYsUB+kktixYbLamgdz4nk5xv06HqoRMAkh32MalKme8kqoUxLJetJbUiqQioibAzGPvy/PnL1XrhvW8a54M5nwwmy2Ai7BfELQCaJDIkZiggoARsZAVAFC1ryoaghyFOo+YJOtZ0IYyGTpcr13YWWH/t134Zxn+CS0AtAM67Su6UI/+TTv3JY8KG85bEWdukppmmR6+ZU4CeB0BO+eVcgdwNu0BAyqYIUnW+66QkgB0HOU8tTQMjUJoJkbO4IMzdVpvZ/LUTAThnnTZbzM7vNCNdeJwWmPlh8jbJEhAGZHZFhQlFtVs2iDzmyUiNCNgAAAjcwoNpzgJJGmi6RfDN4vMfv7k8WzXeEWAbWlMoKe23Y5ym4LlbchfQESqUbKWYkHPs2MxyyR98stw97V++2V7fvHGeDaRrGkSYUsTDLkny7SJ0bRqmKWdSQsNUSs42JXhwdrHeXIZm3Se7ebN/c9OPkwJ0TFYKpKSEzqNa1hQhBUVBFTIlUJ2moiLTKIzknIuj5izTOI7DeDgcVuuVc8HMKhO1XiRVJYKuaVMUs2piPV9QIjQDRw5pviyOeSbSChibiEhW6GFLW8fOex+Cb5qmWyzaxi3JieTg+KMPrs5Wy3vn66t75+N+9/zx4wXD1aOHwXlJ6e/89X/tax98/NHmo1D8Ydevw+ZscX6xut9gl1W4iNOWiS7PFgX9slt6WKglgKwWAjsxLYCIxEiGLDZNVgpwi01wTqEAyARjAROoyIICFgA7DFMWTUmOJrKIaDaNUqRbLC4v7reqt9vbhV8ClhRTTKNq8cxN41Ia720W99ZXKY7b3fbmzeuUJu833XpRilTGtZg11Da+Xa02i26hqtvdbnu7gwyr1brxftV1CpbTeNhrjpEBVNETe3bkjJjYs2eHTI5c45u02TA775qUkvN+tdqcn180zo3DzrPvQoueRGUcRkQMITgGjwSGoiJFGnNkjpSLgWaMU4kxIwbvQxta74IVUyqOoG0bxgYhMCgSs6lE1QLoyCmXLM+fPr15fdstunFKL97cuOW6Wa4K0dPXb17dXP/88RdPnz95frst3LXLzrfSdm3oOjMC4m4Rms4j8Zvb4c3N7vWbQ0x+0YXgqERZtuARHWLnXcAwHfp+v+sPWwZoA4YGah64Wi1C06YCodWmZe+NWFbktHUlYc4l5wiofb+NfT5fXq3C5rx7ABS8Xy7c5eufpt/5X/+762fbw4vCK4dKhTJLsOgpY/BhkogoAGXOT2zOMb+C5DTbtsxsf6wU+jlI2SlZheN96RQ07Ss6f3O8PYWwuRlzfIc7z3q/TMFfaLXCiTpxxx/aKpRyfAUA3GFgvdPOmPVy3vuK8zHc/eFXltimepfYgoho1eiMyABqjmuIAASEBpBzBhN2HhmnUZ13sE3rR8sp9dC64Xn3u//iT/IAf/PXf/V73/sbH334aNUunvU/xSKi5sBWbvHp/UebbvXJR4/AuWLy+Mmz2+1234/Pb3ZDkbNNG5rFYrlZbdZNF5rWvPcp4xRjLgfvKJfMyEWkqLZdp2g+ixiWVIqoZxDRlKWgaQmMDI4d5aYN+/51twwPHy32b5ZPvujFTDRLzMwMaKUUVSEAh8GzyyZooFEMwa1w+3q6vd5dED08vz/t8lYHADCWPEpCCf2UU6fqDajymEVVqm0UkRmmDClDR1BExzGbaRFFcogYJU8JGg/BEyJ45wg9KCYA0EzMRlXJ1wyA2dlsTE0iFqOJgnPWoneeipTN2aZbLPeH/PnnLw97gcLOBwQCiWlKngwMPHUeV1/8fCw7gExFBKKEpptFie0k2laH9+2tZnjVEK8rn4GsVo9zix0QsHqrvJ1+Oy6yU3F0+vsXFuxpdR4tNGtpeSzU6m9OT5p339FEaq7lKuRmVUjm+J41j5n3gmHtrhEyIgE5IEYkvVOY3unm3+Ey3X0QzTOOlSBj+BZCencLvosjmQEAM93ZzvPBUC3ssKoN35H+PjUpT+XlOxsazNTE6lgazXUxzpfiBK0fiRKmqiIzO8UMELSoZHXkGT0SxDyVbLlI35dhFQlICkxj6tqFc6wGTNS2bTMcRoIUYdjtnY2kqWEIDXtHOek0xTHKMJai5AKLVOt6RSv1YJCWIdBiERBARMYopUCMAOAuzx9459/cbHe7/WHff/OTr5klg8Wi81f3c78tcZKSxdScoy60bdetVhT1Nm41pkNYOELKOedcxt3LNJDkBA6o6LTNcZedMgbvAm/OV7vt7TAcQOHgIDi/Xq2AbDcAEoMBCTgjjyRQQIUJiObJqJKNTQkNbSb0MrMVqVHTjnTBd1b2ncVx5MN9xcLCo3b7XE2fQJSZ8XHkCtWP0bsr7A4883a9Sa3IzaoGuVNjK9i2qzHdKpeLK//ga6vzq/DZ4y8niyuypFDEp+zHnqYDaQEwaEIXNeWx7PcDHhvnBsZEFLpF0zpiMssZ8pAzlqYJgDbt+6LZMzXoQhPunV8EF9IuHqZDZEXMArCbRiaCgbHhiswBwNAPjJzHEocMAlAAFESkWAFFU63VDdHRp3GWvyI0qxLjtVYANURDNXo7xDvvoyP/6PggxDp3UiUn2Wr1pUh6PKt3Sqzj6T4CVIRkRGoCR2WVuiSIyABKLmICx4qsmmDR/EKuY86n+qi21qhSA/XIZzUkg1KMYDZ6MQOQtximqhUFqBNpDshM+SiERWgIbG+NMd+DthHxhIC/w/d8C68THCu2OdHQI+PqtPQqHRyRkGclODMzBZPjkq9nXY6VZQ2eJ3h+xlmtclb1KMz+Np/CYyg+AXDzGXsb4+ztsTkCqtqKVSiKKJtWDXdV0zq0Bwz1VmeiCjBTsQDrrQBpniS0opq1+mwQkmNHzI68mRErORIsJlIRPrdogADIgEGdGpcqdwWM5MhYKmeyYCmmDhmx1miVzwUGx8VaZ2yqiVu9xdaBbM9mBMDoHAJUAoIICCowgkNwCrM5lwJYCAERnQ+qaubzmEwtSY4pEYO5BoHG2McUiwIxIBMSsifvCVQ3i+WnH3/EGuI+9bfD/nq4eXFbonj2QAgHRIR6ldFR4KZ1kCGllIc3/dD3T5+++PjTT68eXrHxw6tHD+/df/76yX47KZTQkpH2+4NJRiiM7uxeuzpf3NwO0GjjmjjEZbe6eLASP724eTbJISz0bN2il1JySnm/3R/2KWcghThGMhHPKioFbt/0h9tp6kfP95lTpatKEQXzjTvsp4cPVt6rCADCYrFpQmeKr1/drhf3/4ff+aevno/9bQIPCB7IoalCJgbXuLJLDl1dgYRzfmEGWj/4rQL/nDHXYhcQRWDoU2g8OSYAMZlSdhU3b9QYLFuUqM66pgO1cR9lyijGTOCMb4eEJaciBRA9k7OMcS+LZYdou+1NHAszhM6TuqePr4N3Z5eL88uN8y6NKfa53wpopQty9QIiAkdsBioCRkTEJrmYakmxdE1YLM5ePXvFBIc+73dxcRG850mT99A1/ur8A2iha5rtbQTvCdFM1bS6hwKA6SwOXFURiOwUJhBnfxNVnYcG3Xw7PHLJ7yQ6p47NnZ0PFYlSspPjYB3jRpMCSECIWOmTlbxQwBxADYdACLPE0pzYmiGCADSOoTpsgL3zHd57VL+nuTdaFWHRDHGBzOy8UxHfNgysC5imREgSUylJrDhCaXS5Cu3KuQCquWSwCCXnzdmiaf1y0ZlM44EO2yEnGL2owLJj70IhjWUUAwdOxXJRBLt8cGVxUC5TjmftGkjv37v8IH6wjeOUooB5wu3hkMZUpmQGWfOQY1ZZLNqLex9432738cWL19evdkbWNC2TichuNxz2kxFpRiHwxhIrDOUckTkY+4hEWgAQDI0iTSnf3u6mKQLiYrEyxO12P/Qpxszk2tBZiqa2WLSEkmKKKeac650S0RcrVT+/wl7VLqo6q0oxs1I9V3NSpVJyGceBmdq+a9e0vBfahi/PNx99fBUQGfL2+oXldL5sofjON1eXl5eri9/+9d+SKJQJiYO1F1f3Fm7hqTFwntuzVef8MqfStVyQgXwBygpFyWHIYGKERAScQPb77f5w8/LVk5dvXk7DaFlFi1rJksUEGBS1uvEa4ZPXT81M6vjM8S7GTMjA5LrQtcvQrZumo7Zz6/WqbS68I0foPFjm4DA4gG69WZ7fP7tvauxcjLHvD4fxAADsXLfoDHSIMR5SiimOybJN/diFFhUYyTMGWuRVapjZUdHESCE0YL6oqJiqOqRF022Wa2L68smzEmUcougUx5yTNsw59VJK1ywWbVekBPY5ZSJCFRNARAZwxAtegGKaSlYrBUKzRNcC+sZ3jW8DBQJEAzYlMjQPQt57FzpACy5ILvtpjyIEqFn7/gAAruvW52ePvvHtsFz++LOf/uzLL5+9fvX4xZMiKQFNCof9YeWdIrSLBbtGNDatQ8Zdf7i+3t7cHnKBtu1W6835ZrVsl4umLTEiKJRC5m5ePx32BxVgBlVDgvV69eDBg3v3NkZpGNUgmub9dgugwXWOWkRyjAYlDnh1/rC5WJJ4LJ3Ly5YuXj8//OjHP335ePs//dM/gFughrvcIToBhAg5Kzn2fhGnPN9GVBgMHSCgqr0XgJjfYvyIAGYIKCKnqnX+g7M0X82Nj1EVfpG6hHT63V0o6/2Q96/IyzjmfEfnwPlldOwC/OK7vPNBJ+Wcd374Pk52p/5/7yvONx08FkhVrJbMzEoBRGQ2nn8CpkCMTESOiNF0eXFWojS0FoyHm/LHf/DD6+c3T3705su/uPnVX/3ux5+cPfj2RwK3Yxz7aa8oZ4uL9fpsyqNgyZrbUGI+K6q7BFFdnSUWA0EDxNfXz1Qns2g2jWNcrynBlGOcYhGVpu1UbBxzKqiCzjECTlPuh+IYezdaKuSZyM42y9vti83q/tXDc4dB5PHrJ0O/60EdI4MZovPsUdEURECSuGWLpgKpDX56BU8fP++69uMPP3r1/LoILIJ3SOiFEOJk213fLHB1tvz4o+biHIFpd9irgCGuz9ZA1A/jerPoFt04DWpKjoEcMlNhIEFGdqzFnA+SQcQYAB2pZDWsSRMCMDtAMgCNkCWlDEXAEL2RAi1Wq6bt9vvpxz979tkPn6dIngKRA1XnwcByipvlasUb0sXwBIjAazDFUor5WRpTTSpGVm1a4ESUQjvOe5xWzlxBlbcjNscCA+pL4ORXiHXkpJYv74n63CWZn0qn2W69JjuzjeDMODetw8AmQHWEoqr/GiAgI2PNeObcxeZRKoNandTd5rxDMqqGbFgVQIm4NrzVFGurBfD9fWRHfjmcFI4B4Aj1/lUPPJ6IO+hzPWcISEY2Dw+eBPbmZxzn0XSuho7nCme/1PlEadWXNpwLtMqI0zvhox5TRVdLAQWsTNSCpQAFl7ONU85FXUn73QHUSgGi4F1iJAMKIXAIMaaY06JFYtNSEBI6b1ZUCRFD8Ko0Thpj7gcFdGLCDI7ZMRAUtZEdLJeGiEWoW3omj0602M3roevakpEwtMFfv3kKpotVc+/qgtCPwzSNOU0lpczONxxSLinv05Q1mfMGSVPKprBcnAkomJEDYNBcYp9LUmYHxUAVihFju/LLdedWSg6LFRHNBVLKhI4Rg3MIkKeMqp6BUMGKFtUEGTOgIwMVNbB5kBPnZHpe0sdlU/V/KtcEjpMQ+lUaWEcc4e6seO36VghgrnWr3J1a1S48QsunfvFpoR6XF1ZPNEM1FMR7F2f9iycQ4Du//K1v/+rDbXx10x/cGtCxgjPg3W2+fXM7bFNrCwoDo2fIDl3JEAK3DWsBFGDm0HkpeRwGjbmkXHJiZb/wi265HbKDQIQ2AYJLe82a8pgQwmbDjUupzzlPzgUF7fu+ihk1vu33o5nlMcNU91UFsDRirvmMZgNDJp2H5djMoGq58rE9pNWcT+E0S3dn/6IZvH8/J5xltBAQzGQe7p45MXAUkEJ8T+puhsirlIwBEuDMla38AjORakRYLzoiYeVlHMOomhIcwTiolNQZfALTmgAQEmHBOXOpKUz1+gJmnmGZquuiVrICoAKQURXnwbkJAceR6tOpmB91/RxpAncDFBCz1TOqajSrdx0TqeMiw4qVUf1Tj1RU/dGd8CSRBdVP4zQhW7OP6kqolU5UlXD0baA8EiQqF/gEZc3NttMuq+kTAAC4CveAopoSIjvHzAZasooqMiAzVCG6YmAglRyCAKAFhYgZjxwyUVBAJZon/qxmg4jEjB5ZlUVEiqiYawJAFd9VICNmI1M1MUUtBlZMBEphM4AMEgjZeVQEgXbREpAJSKoCz/V6FXKOmecWFhkSgpFgmXM1VlMAZgADDxw8N44cAiqgseOmbQgcAEyKOSQfPCIaSFZhQSZSLBwckkE2MMtRyGPgRcv+bHkuOztcx9dfvHn17AYKtNI68qYIgqg45eiYAjkUhCQMzoxjisiIHgHs+dPHL14+XV+tLz44/8a3vlZsvHm93W63ZxRiPBRLCi7J4MgLZUPPHaxwSUSCpVmH0Yb9bquWXdB25Y2p6Oh8e9ji0KdphC44JIpSgU9iwDTl6HQSdX67O28efLDOMeZScilF03aPV+ey3R1A8eLiwrG/uveBiqaxPL1+Ph2e/9H3n555r9qs2vOYRc0oUNs0Anm/2xKhzUxCADCq0pUnez08NosqwbHukRq5ufo7HcsM1ZKzKggVA0Vj5xkRDbDxjefw9PpLFLLJFo3LOe22o2udRkqSXeBF024Phz6PZuCAci6pQMvUD6VMFn/6NObDd37503tXG+85TmNJMhz6/hpKmkiPulMKkgSQGJ0pYnXqK8AtgyCzWy5WMLyCRbjdpXRBq48v9odBRPb77Vn7YO1Xv/XrH734Ml5fJ+fVDIlItGZ5qGiOg0gGMkYGAs0CVahxNvomgNnFwmbLnhpuqt86AB9dUcBEBBT0iDqdGjuz/YOpvOWj0ux+IgBkd/VHUWwe6p7TVkAiRgRAsapNKIgej2jZCcWqsdrMTKW+zNUqkyr3rshx2rvkQkgpJlNtGu98aJGJnRSjFnJKZlnRb9rF5YOzZk0Jh/242+2m6qPEAI4oTbFxbb8f6+kKPN/M2YUsumjvD+OegBkDGsVUiFJYbNzSUQi+aQ77w/lmc5Xu0dhfHw5FZYxxnFIcps53h/2+H2IUPXuwfPjwo6K+v52ur6+fPX+5G+Bs6URLnHIpoKAiFFyAlnJOJohCzgVgpzkBQJwmEFu3SwXph0NLTckSp6wKTL7rljfb3fZ22m6HnO3+5YbReWeJioisV6ut7KZprNeUiFTVwLSUlJJjb6hEpGqmWq8xKoKRoQZ2NYKpSMw5prid4ALh6v6ZiDvs33gAlgI5r5r2rF0i2apZfHL16Jsff9sX58R59q1fbs5d55cMXgTGKK1vgWAYU/CtmGVUB2YgymiIGcr/+Xu/B0i5lJTzOI37/eH1zfUPP/uzL598+eTpF69v30wFEKAIQF3dDqqu/PzvaitX0e8MgMcnCEACWMNH97pf+e6vXF1dXF5cbNbLxSI0gZ2DTz7+cCzZgm+bpg1tFzZNE5aLZUo557Tb7/r+ULQw8xTH20O/3+/U1HvvWtdSu16uTKTfHXzDjrh1ARstOZVYyHm/YMch5phSKjkTIntmcsz8+uV1P/T7Qw+AXdft94fGu0XjGHG1Wq6W6xijFg0c8Ng/YiQiVFXHHgxjjIdpSmqKjOwQPHPjXdv6rpJhWIVqk84QhZm9cxyYTGF7exsP/aOHD8/Pzw3sMA6rs9Wn3/2lF/vDZz///Ac//cmfffajPkX0tD4766P06aUR6EGJcbNZhZZEJrMSU7y9Pby5uTXwpphKck3qus47fvTgwy+fP3mzH0KAzWbx/Nlu2fGiQS3FMZyfLx88uH91/2KKU5wmBE9IpYCkBKbFRuBRDZ1zZ4sA2m7c2WZx5ax1ZfXiZ4f+9faHf/TFn//hj26fAfTssIEDSTLWjOBmUnzWJKOZzGNEVX5k5mHNHjancGcGv6gAdedRQ9WpQMdjVjTnRn85GH96wjv/eOeNfwE1elcaB97G5Hff4dgH1a94i7sfgPYVn/uXPfn9x0wWOKZrb/8NWiGB4/iBVgr9/ArJRcmQVHLm9UJFrIACdBuH0v3khy9+8vsvfue//5//9m/80vf+1rd/++9/8ivf+9SFhSZqFtz3txAUGUuOitPZuctSUpEOFkorQxpj3h8O+76POaGNKR5EJh+ga7xJSaWIoIgWBRUc+6hKcZqSACuylZzzOGUQWKE2jqr2H7HzDRYZ1S3O7y8/+eaDcf8lI049lFIYGIEJPCqVqDlm5oaABVULxEEJ3E8++8mnX/v4/qOr8/Ozs1cvkUlUg2du2DCPQzwc4PLe8sHDS8RDycOQEhgyuyY4W7YIpfHOEXdNF+NgZo48OnLMwYlnIgAz06Ilm2ZgJO/bUm/gOitjDn1pu8axj1bUvJqIiigaMhDfu3+/aRZPnu0ef/lyiJpvxV2wFAXKDy7OmYEQvQveutdPt1DAjEwMLaCBpEygilp7Z0eS1Ek0yo6Fy7xCKhXLCJHQVI9bZ3ZnP5bWZids68hXmHvlp+VWwazqTIwzdnTUb4FjfX7cMse6x2rJaLXyrLY2NhMc0OCoz1LLp2pPDmiAjBWxAvUhKAhUo3U7Wggdy6p5WEXfir+/3TCzZvxc1h4huRl9hlP4ONEQ3t9vd9Gr465HQIdQRX3B0MhE7ajd81bwBu68dD7Jp4IOTnmXgZ00f96y3u/I4s8fbGAZUCmnTOymKSpYKpJi8iFMKXfFmMPZpos3b+ZrooZIi0VnoI3nJrgmcNc0sd8aO3YQU1qvL7oFpzy+fP16jKVpI2DBlrRojrJou+WisSvtB7/bxc15AHQiOI4Qx/L4i+fMLoSwXK380vfDK8eIpGLknC3WHDpKkccIWgBJnAdJWoaYcmLlIWqccvB+0a7bblGGEUBAQQazIG3TGmqOcZgij5pk6tb+4uFydeaN0jAOYzyowTSlQMZAnpln6S5lNkIJgaC4pstpr86pGMxE/pwlFyBw3mu1bb2T+iIiWdXYqWu4/vQr7invhN+3BfzbJx5xgLrc9O2lNjBQIKoKEgAgIiLzJ1XCpmrpFp2g9f2W1q3y9Mk3P7p81H7/5z+hBharDXieYukH2W/z7faNTth27WJ9Pu7jerUsXbk8W4mZFFPEknPRsl6shu0+9lMcCyQAgFVnDkMXFqAu5dQf+jEeIuut9VIKFGhdd3F2cbbZjJz2h2swSkViKsM0fOPr33jx7KUVUzWoEznlyDo0UJA6MgKAjhgUFQ1w1gAgnOdIanNcDEAFbLacOu07BADCOvlbr9DpXFel3jpPZt7gxIGCt5fjLpkOTyCUGQAQ8AxcKkDFiGt4Uz0KowHRkeYDMz3a7CiGZFCKmBodBf5RCY64PEBF6slOvpUVYgeYpRHqAquEAjIoVLtQjIREZnnukB1v8e+FpPpDNYEjQITHKeyKy88HS8f85DjXQ46JSM2oKmAAzZ9hYPZWav3IKASo4831iGiGawlrQ9bqwRxL2epjf4r8Ot9QwABmj8a7DSuZIXQAACAASURBVLk7B2dOTQ2ksiNq2YuEBAS1YclEjhARGGR2MJutmGGO+YagWEeTgNGEABm5joiqmVg54mfzmQIHRuo8GYIaiooePR60iBVWIUQAJmLHJAWVEMk5x47BoVK2hIImACCGpmJGCt6xd84xYl3uVo0s1QohAaHWL88OTJGNAnNTjThJrDCzY4fA3nlUxAbbVYsEY8Isgjl6dgrqGqfeigEgBWbH1LluvVijwOsnN/vrfrieXHIOnAloUlVgds5RIHSMVINOEa1SzBHAGwcDwhKFDMYDDV8O9y43V5dXbes+f7l9eZsefrBxjoJnZMkiqWTRrITNMiDgNJF5TZiSTQBiUOE7a7p2s7n88vMfpQgeIbhg5golNXQcEAAoEpgITEMZDj3piog9BXAmqQxDsvP2cBhXi9XZ5T0Q882CxMZdevLk5dPPryGDaz1gkwFJrJRsRZBMSQTldL8+bgGbs5QjGD2nTciz99wRBAE0EFOBKt1kprOJswIiE8+MHlTTKolSgIAUwQy0YByFXUABKwDOHDfkBigwpeiQkZ3jImpGVge2pzHFsahokXx+viqx5LG8knjYqU2FCBjBFFWzmmPHBKhiqkh1ywqgAjkPHAjbnAXBB98O/QAx6bS9WB4SpN/8zb/zL/+XP/3i+TUTZsnsOjW2WbCBvGcA0HmHCeBM7de3ig5YdzLAUc30ndbobLNZ97+BmVoNSacQdmw3zOVdTX8qxR5OqRPO1wFqRK+4O+FMdcSKMKDiKW3FGeY/pmenLzWHvCO9VhEAC1QWltZYb0aWSiIgJCRHDsDUOzIB9N4zYduGdh2Wq6VvlawUbQh03KtoKTmZNlIyE5ViYLNNTHDcNsvgO0UWseBWJoUlsAYxuN3uWXU79X2crtYXckjO8bJb3E6DqIBhTHmashmT91LAzJaL1dn6ommWT764Phymmzc3fQ8MAEYlQ4w2peTIgQGjR0JFBQFQRCEsYkWhinekwh0BGhTQdsaaCN1qdTYOeb8f+z5O05yXlywilnOWoo66UorWOU2rNOTZeKXkgjR7l1VKX0205xutYYmpxmoDIwdNA9RC19F66RunknpUI7XNYhmMSp8fnN/7zte/+/VPPr1cXsYXcd2dLdolUxCDogTkkhQVcIHZu9b7SZLjjoBGGBWKIhaSDPJf/lf/RWi7YRgO/TBNU8nFGBVgGscpls6vli0SYy6paDJGcMSejbGmTIkLIjhHqloYCJEdA1gBFW+c4fam/O7v/gkBNIFD4KbhrvMC/X/8H/5Hy0VzcXlxebY2U1VBIAJPmK6vb2+3exFpG7/b98NwKKM5a3xwIfgi8p2vf1ih/e2bW0Dr2tZ5VtUSpUwFPaQxFcJSkkip9QaIScw5lcNuN04xTcn5Zq6NDU3QiEq2OKWUMoJrmuCYCKCUYqYIqKQEKAol6zjlYqAODdk5AmAEj8ZoTAZkyASOCRmQiYkZuR/6wcpuu4/DYbVer5fLgrK8d96u1+1y8ae//3+/7odnN9cWGkaImqYSx5SSQHAAJOQB61ImUAUzkSJTLOwgZynGiFokpzi2rT9ft20jy+VqfXb++PGNI0CE1cpfnJ998Ohet2j66fbmdqulbFbn3jWakUG6xfL8ogUdDv3OIDchX/pvYV6s8erDB9+Q3v3h//jPf///+PObpzFvGfbC2rJ6yVJyVC0ITOQceiRG1LlxVm8SRlY7pHdqzrnYtq9I3e4QKN4NVe+2sv+qh733n/eRJnubkd396Ve8+fvZ2NzbQYBZN+gXnwYAc6n+VwBcf+XHHiUq3oPesN4wjp3O42HO2SMeizAzK8AwpbEGm7YJ05BzmRCAzoAJ/uJHP//y6Refv/zw3/8P/t2/+5u/ffVAbvXl6y/3zYqVcxOaQ9xN422BsR+HmFv0FyG0ZOopdcG8g7EX86BMzhEz5KhFSpZTXutA2SE2viMydN65oI1JKWiYcjF1QEKMopmYpziI4DLw/UdnN6/7w7bcvhxvt8k7DuhzgjhlUA5tByCiImbAXpXRu+0w7W/3F1ebr3304YtXz1VsipEcAImaNQE2q3a1bEOg4TBOUx9jJmQfgnchBFbxTGCmDEjIlRtkqrXLwhUfULGsJYEJsnOOfdO4AmWUUqV7Y0zMHsiKgBkhBYDJDIld1626dt335eWL2922J7cGjVKKoTQdLBbMBOzIURi36ckPX1T1gCLqEREZRBRPmprHDE1ODXacBcGPjKm3zS2Eo050nV43AAA5NRvvch3o1FO/ux2rjFC9SRnBSd4WARCOsvVkpkBH8Xc8YU1HfoXCnfrx+AUrZQFwngyp1CmoYlmox5Eve7uJjuUXIVYGRS1S6M5GxzubZd6nesS9Tkz3I0T07mbFr9z4MANXVHWOK5/dAFDrfxVOEPXxKry7hd+NG4jvYWZ43LunZyFA9bg3MTQEVUanOhIxMddhuXGKrY9syOzMNJeUs8ai5Ng7v1oug0OmmoizKhByE8IUM5qIgIhJBlQgxpxtGqbM1gTYrNfMgDSGbnAJXBjHAW5vIScwgaJEVEoDan2M+6urRmXKeej7FEPj2IFRMU0yFbHArTlSMQ7cwRKRYsqACsBFhS0qZmoMl2AZFMXQ2KNrGpdNMRco3jeKCZwjB+zZBWIPpcC6aRE0eBcCihIUJSoiE7M1a5vGOpGSPTlAFJE6VY1MR4T3bUQ9AowIqnfHZ+G4e95fCqcrjaeL+557bCWx2NtMft6J1d/ySOYFABVDBkQFJQcACg7IwX54BZt8/1O/s2efP5NdfLW5XPnVMpUyDPtxABQHOVhJkkyi7V7vWnIEsFx0YxaVyA7NEQiyw0N/sASQAAw4QAgtgmdpvcJwyNNW+z14LjXJVwNYGKxC6FbFT4fhiTNCIFXTEVR1jL1jb4qgYsUgw9zOJJiF8qzWBlgH66rkLhKoIldq1dy6QkKyu9MgR3wZTjOEd7aPHTeGzapMWPs3JwDmdHnwnf+ffv2+VMARxKm4/+wmfLf4mjf1/MH1VlB1J6nmKmxVQgCPLGwGo1m0W48Yms3hgY/vZkxV8PyoK2AEJMcvOc9bvhuFTmi7HvFQPCkmI6gKHsfc6ttVaWYAIGbn3DwkX/EcnA0Hq3jUXQHPU5RSO3bmTkXJsduBRGCGhEiYYkEFk1P6ZCco/xjf8fQ9bU7v5r3lsiXVMitpMwEAAxIhOSRDZiSHwERMDHBUsapLjQDA1IoJFbBiUBSVCIiN1FSLiqpAqdecmCpPpPLRfWA1KzNdWUClEghz1gyAAdgTVeMQBQUrUBiIiIlMUIjZEJkIg3fFlB01xJ6QSEFoJqnpTCTxSAxkhEZSyIwMABwZGhCqyDRMwlxiYg7r1Tp477wDj0ViVdoXlBq/F12AgkPpQezi4soxbZbnq3Z9/fzmxz98AgfgDJidCWhWACYkzTZM0fk8b0MANRM0ASNC5wERUjZECMGVKeVd/uz7P/2l733rgw8fYohfPH2yWC5jJACIJccp9v1Qindu0QYvJlGSDRCCUxODUpKMWZzHi7DpFovrJwAE665z1KWomCkwd6EFM+3alEdBmCaIQ1TRpgneu1hYVBpOKqiIje/athsOBwMOfvXi+vkP/uhnT74ErxD7AjaJMAF5hiw5TgoB2M33aKhIco0beMfC4LidTAQKACOK1WHVSopWKsakJmZmqJbQzLz3hKhiiOoc55JSjLXvAoC5qGaz4f+l7U1ibcuS67AVEXuf5jav/V22VcWqrCoy2YgiKYkgDcqgGssdBMgw7IkGNuCJZ57Yc9sQPPDEgOceGTAMWAJoCYIByyJFUyJhiiyRJRary6zM/Pnb1997zzl774jwYJ/7/vtZWSQh2WfwMt/7955z72liR6xYsZYlybd7ia2cnB5ubjZ5ygbiLpBpTt60OD5Z9cuGg42D3txMu/Hmwb2jNt4/WK6PVjcfff/y5ePBDdwSnFQZBYAHiQpzG71YzmbJyLwJERKgxlAhIqLdbufDsJDFlMZd3vzVf+uvPn8xfO+TD6+vi5K6FSE2klI7mxwlgAA3VeyFU33PbPps4bSPvzTjetXy8/bhsr3bqN/OpxCqpcVnwhnTbNA5z9LskUYyIoLC2YmIHUxGqO7TDjZyhBpEiEhIDA4yI6gaE5FwRetZRDiAKiQ5rwi1kwB1gjMLMVOQEIIwLFvJyswUuY1NCKxJz56dIWTuNC7k+PDk+uJlMWRTbnixXizXq5ubvL3MMGiHtl117ZKphfGzp88f3ju6vrls3SOxq1zeTOM22fit6PzoL93rgC52i7bfbbdpyu6cspZitacEaterxYNHb7Sr/uz86sOPPpoGpAEAmg5uUZ2tODKUjcDkzC5k6m6WXLmUSUsyASE7KmxBCgXMLKtpw9zcv3//j/7oj682N7udRWFmSpNPY8rbMk1mZoJNLgUztlj9OmaWspoKCSrQWVzLDFD6Pnt27LscjL7Hw0dHq6N4eCyH66UQLZtI2aISxgKl08OTr771/k9+6f17i3ul2GLhy+U6hG7SUtRMGOAEpjYOhE+e/kBYXp5d/NEH3/neJz/4vd//vQ8//u7HZ+fTc+B7aH4Waa9oAAEEkWHEbs4As5AC7kQG9rqKVR1dczCJkRLIIApSWFGH6tygdwKCe8OErOX6csC4P0rEf/af/x1MAIBj/PR73V/+pb/y3le++rUv//iDk/v3Hvbvf/FkU25enD/tuwawzeXVdrhxUzPfDduvf+XrFxfnT589uXh5kdO0Wq0ODtb9omulRTQtZbjaOYwZ3PCi67quD8IplzHn+/ceDdM0jcmJm65d9EtoznlCw9sx5WcvCXR4cLhcLLsudqEZxiGnCebUgBF1zKmUlFJhJmmYQwhtDC2zaCEyJ+LA0kpoFh0xm+ViOef8+PHjYdgwECM/P3/26K2fytGpbX7w6dPf/41/8j/+z3//9F6g7nB9fAKmpmumMqYyFYMYTlYcWHPamsG9OEouo3oShlsJEcu+PT1Z5rI9e3npIR8edW+sDpumM8Nf+dWfffny6uL8Ws2klfPrc72eprTb7UoULBYL0bYUC9St+9WDw3XO1z5NxNOj1ZtH+OICD5988PIf/k//y6//o4/xHMiAEqlTiWykubhpbU2JFJ7pEaWaW+0zm5oiCWF2ivLZ9gZ38tU7QdNd6IcSUbzqDdx9KX5oI5+9Kdz3bhafd5TP3f5s2NidpNj3PNJXuMErWtZnpyH+v9joR/xEBbdQ1XdA5MKwrCGEroladEhpNqt2h9P19XD5CT79znf+j7/73/3Cr/6v/+F/9O/9wi/91Nfe/eWPXv5LA4+7Mw5d3yyut1tPedpmY8ViQSG04tK7I2xurIuR0AQRU7tJpsU0KQixaYK3bXQ3RQdORc2hBOdGJErM2zwV7fp20fcknnNu+iaN+WJ3dnzw8N47q6P7vjwQ/8Ew7tJmlzwxSRtjCIE066QTk8cgDirZAXz4ycfdYfMzP/Mz3/vwu9OUjFMukyYs13j7raOvvPf2yb0D093OEwPs5lo8YNEsOIQ+hlJyKVlT1pIJVEzFJbBwkBAFKmR2db0pEzQjhLhc9uvDZWjaZTQjTTkNuzTsctEyjFALJbs6CUnTL45P7jnaTz75+Pvfe3p9g4PDBovWS5JGF8tFaByeY2iW/fL8yfj9bz0Gg9UtIZN2oU1pqPqWrwy39n0u8J42gJob0Ez4IBIXd3Dk28LcyWvaZq97Y9KesoU62Id99KY9rjVXTHT3ZnNmkLNZZW9b5QI4ZhPoJtzlcpGjDoDSnL3MdWUFbAhAtfKqRAAzdQPByWYcrtLcHDwXaPv+337s5tUj8Nm4AQDCcptKWV236G5Tse7gDrr02j4cUFBVNDUQVQHn/azC/hEn+qy4mAN2WxvvK2R2v1M6qkMAZnIFmYOcbO58srvcurERSZTYxFxU1YadQjd9KOtly8zjOG12w5hLbLtuseyalsjHYTvqDikKc4yxbbuleU55u91MKTctJKIOdJtB0HZNf7B4dO/e6Ze+2P/ENO52k1t48WLz8sXu8jyfnw/Pnp3dDFmCLsdJGrz11kkpVRbZzUvKxcBqXlyVKGmekl7fDOOQ22Z5cHAYY7/d2PnNbnMz3js5YaHD+yGE9UU3bi83ZefSI3Q8wTAidmhXvDps1wetMdpOUhEJgCPGCFdmxIY5tCjE0Gy72K3e+/GHv/XxYwpeikaJljWnkUhC0wAopUgVz3nt0rrue/V/wnbn7noN4qrw7Wf2WYEtZvZbv4WaLNU8f86q2ep8VIA0pKlk2lAjGNLJ28uf/6WvhZU+vvjGydsnuV8pt88+vXj66ctIh4H6PvguERcZr6bx6kYU3aKNEsacQdaEtl2GMumku7l6EzQNHR8frQ9OtODmbEhTfvH4MuVkG0ziHKn6wEnsxFrLwTJ1bcvEbm5qGnTZL++d3B+vh6SlRgfI3A6fuYj7p4lmjyrn+YHaFynMVXM8hMCMnPN+NZ/f5/MM3B5cBLzyih1uVvWpfMaBPx9sxi0GfwuKgX6Y273Px+fRzhqg9v0yf+3vXq+bz0zSis87GQECGIGlJrkEImfzyjZn2J7i5HWwCQBm9AoGqtaF82jhTFCdz+JrJIZbxNRnsHDmM6iCHYD4nphOJFQHlOtLK4BVdWb2A9S1o66qMDWVH27o3VkUqoIX1IqDxGrjYjaY5FmgdK/ECIDptor5Udel/ltQaH3onO7YOBNVlpxVnas9h4rNi2NW3yEws6tDXbOzOTuJz5Pq7l5KeQWqEUgoSJAgIgKiolmpYkwKGJhqqQM4FJ5RYHQ7BG4oWrSoUA4kacxExBybEEIT4FCoB1BEvW7qtmcLOwJRIBYGmRmhxOoOoTDXbBXjKshFs6nEsl6tm7aZPA3DbshbI21bsWDFXCIQCFb1Z2x9cNhKCNxsL8anH73ADYIKQTSbZRMKITQsrFpMszmKWfVmIaYQYxRx9uzZzOpYqisgzLG9enr5+OTT91bvvvXGO7GlNKVSLJdcSilTHkeUUgKnPNo0le1unEKKTQix0oMSCTqKm+346ZOXSKAAU5pGHYcpT7roG3e2kuu637UAI0gI0hgVhRO4bbrDQ1f1w8MlSdjtpmHSoj6MdvW8vHiKvMF6IXlymDILxOEIHJzVzCz57aWr2cZ8d97eDrZniFeVOJ3tXyvZiiL4NplwkIKJ4MxK5l6sxCbEEAk+5gSBF6d69wqhuE4mUYSE3C3rYtEz4/L8kqBN6JgRcukW8eBgHdtmN2yur4emFSPb7XZ9252crj3J9ma6fDmUHbJ7ILDAK4e+IjpVDDBrmbLlzKbIu0yhjwjBo1Aax+Ae28ARU74+Onrw9Z/84re++aXf+ed/HBpYUQoEJ1c1UCmlDlHPfW/Zd3dun//bOcvbB5Rr2mZ76bxX3Rye5UtgMK4Uq3l/7lT9Dt0dQkTV1+M28Xq1lO61UV81Kmtj5FVEqWnmHhyfRRnhZkp8x8BetQ5pKwBiCiwkmFKp7X6qhiDCCvNcchpTMh8KOSNaFhSbNjYgYHmAI1mEZVgtORdrOuoXcXWwWB8cXF9Ml+Fq2fX9sgfLNFnWYbOdnn64XdDi8nzLU2MK5dL1B5ub84+fXL1z8swMQYKECKc05DKmaUhTUeFWpHUP68VR33frxeHNdvvx95/cXKMRalsxc3J2hzAHiUWcaolbb+/irsVMQLCUPalRpYdRLsnd4GhjJGIzzkUJ4dOnV6oQQdP2IcZxTLvNqFOplDkzF2Fq49xps1dc3drJYWa4VxIz7RNgAsBo2gBSd5eA9VoePDg8Oe26zgkK1Y67ECSyeNFHp2/+xZ/8xXcefPGwPYF3wWh5EInEAOGma+OIcqXD5bAdxpSK/oO//w8uzq9247hN0+X25sPHn1xtplZifOh6wk6pC4SuqutAJDoF1WoFraZaO94hkAuIqsuumXlRXcS2yrIxSY3T7EwkmFU7iYytIDZNy40bkk9mIIFErJdhSoWIQvRnz8d//Ou/+43f++Ctt795cLRaH67+xl/9a22UZXfa903R0ZfcdauuCU3bmCvyJBRaaRdxORiJCRQBAcShFeWcVVVTjNwvmtVqHdtWzbU4Q6vtgapPeRzGNO4mEW5DAHyaRqjFGJfLNbM0Tb9aLCWEaYgwExIhIRriMDS5FYrS9SxNE/sYGoF4gakbOUVm50ACplJ8mqZJ02a3u7w+Pzo4WPbrQiYs1PKTi7P/55t/8M/++e858PSyHByXsrlqF939N964uS4SvW/RL/DgweF63cbG3Q0o5sksRdGjo+gsWalbLBdL2VxvdptrSDk5XTexA+VhGDm4e277SKDYBGYdi6axxI6aIEm3pqPm3LCkYbo6I2iOulr19+8tvrLevvv9b774xu9+78M/PGuuwTHk7MKBlIu6pio3Jo7gnpyouLrZ3kj47ojdvsXtr3rXtB8h/Gy6s6fH/+jtT0KGfF853/31X3n7vLc76vr3atjk7v/gVWjG7Kfxp28/9JrPhfY+96VV/35fJ1cMy0AgBDcjkLCUbA5I07h7zllYulbGw0whtH381jce/5r85r/4xrf/m//2vzxdf2EzxathPFz2fLAWcCOLrjE1glBxnfKYxmEqOaAwi4QmclCyzFmJCmWWsOwPAvWLpo1iQ0qah1KmUqZpHKepWLCSvWkWbbcEyzANTbs8PDi8utpenl/GofGQVseL2PbOq+dPNi+vALfYQ8jHcRsaw5TAIHE1MiWAnp0/v3921C/7ftGpJaJJAg5X8d0vHb/17r1HDw67TlKRdd+XGMbApWiI0kaJbWyEdjvNu6Q5ewVPnDiIiGgMTWjUWcjSVPKEaYB7HlImkm7VcURoYtsQiMepjCM2O4OX6rsZY+z7fn1w8PijF08/vdhsRqHOXZquSSl1LfcLJk6u0oReJJIn3cW+UWgcsoEKhZZslruq6M8tcWf+QVTH2+qyVmkgbvMrnZVuyy8nq1zUV6yFGT6qPevKMwW4DqTNh6i99NqHx0zB8prumaF6lFSwpi55lSZAVSnU94NCtTu6h8O8CoaAa9FHNE/dwIioqPpeJH5mrgAwmyu8vTmXmXud0X41POS89yKi1xTr6pedz5jvWQmfeaZ++Emv1WIlNkr1YKG5AbNnwM/4oeJHbvsPU1EyvmtRSnuT87tH3DcxmZkYXDMVIiKR0MYgOg2l5MKRV8vlZtqNU57GMozIOsaub7nVnIZtsoLg+XDZu1KaipAknwJjuWSWNhdI4CAr4dC1/Xq1YhzuNnArgOTEboiyPFyvjw5Wp8c58MfPnz/bjpdFERwXZzdN58vlous7CE9TKVnVnUSK2s3NcLMZbza4vsaq3QZZx9Cqxs0WY8bRSeqa5nDRH6wO23b3WC+2SNpAxcBoOhweh2aFbiHtMuymndrkyG3TxC5stwOjSAjtIsaGERhFmWzVdauvPvitX3vswZkrrcrgCEGatim5eDbugntV1fFXF6CO4u6D7WekiPYX5U9cb37EdlsC7Ne7Gqj3GMx8cyukQFLxBHe0+Imf/bHVaVPC5uHxg/64e3xRsuL6cri4wsmirBatN8yFUSwlc8PmfEeFplC2aQfz0HQhBKgNuwECGNAgdA03MZtOu7S9GqzYeDaCBSNYpKFYLac807BJ41A22+s8OkFLTtX9/OzsctimcUg6Fi1Vg5u4GgvX9XouD3k/y0ZwVMtckAERINUCotuGzy3SdHsp9udq/4L52QFAbtX8b1/l1LnkW9SM6O57sX/v5/zqs/7VLaTy6tCYe2u0l2x3d/VbXXT43mTCfV9yuRNJZUb57FXHmFvSVp1ZZ4jT7wy+GNiMleFKHeNWwnBGyOj2877CsMC3n7YaRqnRZ84YAGaRWEVLqqGfz3pjlf81LxfsJJhla/cFv3P9NpWO4Va/B9WTpQBMya1aYjDPbqr1DhaSyj0zeg3D+kz4rVuA3D5PVncwD1ruXa0MyoAosdVusFeFYKhLDKZqWmCGAnHhOu3oREaufie0wtUVxSuuJKQ5O3ntokCcAyMQApsYBBQptLHpIwVXL7MJFwFGampFQUAEJEjDbl7MMhVHZIa6mZf9FCE4sDTEAU6gghAbcoFp0aQ5aSkMkpa1GAyRQ9+2sWlTyinnacqhJxKud3y3js5GTF3fNxIXi76X/uZ88+zj52cfnQOQEH3ihtkFmiv7TEIM0i7Ag7tVqRoHEYRIzCwnNzJEMMMNNll7sBy205Mnz0/vHb715XsPH73xwQ/+GIJSPGczFxZjZVPKU7q+ntRR1LKlDg3EQdRKbNrOwFdXOzDgXCYtU5qGBCOLPm7HlHbuRR3LpcQGXd80TZvUdZpMrWm6tmvPz89F4jjmYbOLoXHD5dn24tm0vQIydBQyabvezVMuIIQmkkjWnKdicb7V7gYJ7EP93JxywMAVU7l1YaoiBjqv7PPAXDWiUHg2pyrfC4e5lbaL0y6Tk5tJFIVbtr5pEMRhaRq7PkogBIscur6xVpi6rm1ijOMuXV5uhmFktuPTbhxGK6kN3WIpDx8dXr8czl4Oqqj3EgkRsao5eU0FXGFT0ZRJCxwUysGClytpGipljMwhuFO+uD4zW3zpvTd+4qe+8jt//McNQiolEFPtBqhmN+KqDjj34khAOtOe9qgUvyrPCERWbQ0Ur+DwzwZcc+OqUEq+N+qoQoX1XEah/Tm/Q86qwBn2JGjUxcTvmPdQZVOzMM2YHoFmcfY5pNaAYpY0A+ReSBACJASJYlr2+yIQzEtKNt0M0zCVbMjOJgxmBTHWseMWQcySb6639+6fTHm3WPRNGx2qri60OlqeHp7G2G13l5fXW9WyuUk497PuZndjkoesk7f65hcf9Yth1C1zjG03XWzbdd9IC6VhN91cb5LzYtGacaBwenIqIuM2PXn8/NknNyDEtomxyVOeppRRuI1BYiAlkKpbVne1KaspRi1huwAAIABJREFUNDGxJvVcXAITE0xLbRXg4GDVNS2MxjG9eHGeBoAQgjDHIN1uukqTRo+hIS1GhBgjgFJKKcXn7hPdjkrN2cy8ALMDVdadGQxj8abFctXcu39wcrI8WAemadpNNhWOTcPdsl184Z0vffntr/742z91wCeEhqwhQUlbDu4sBslqn5w/+/jZs29/9wefPn1WXH/9N3/j46cfFMfkyA6MgCMEtE3TrZpxrJ498+o4aTLN6uJOTqXq6cYglRPtQhTI2NW0qiuSg4nYiZ3IiIiDhNpsrhYrKZWUdNbI5IbYSJwYo4XkGgWhacci3/r4LOmT9Xe+c9QdvnP6lu/69WH33rvvfvWrX2y6ZXPYkWtgMi273U1s46Jd3D99tOzX47ibponILYOY+q4Pi1UuJefEUdsudE3PLFYKETehqZgmgV3dyYhEJKqjTDoMmeBOkpKWYm5gkia2roAZAct+ZeBumjo348hNN/N2DeYe3NmZDSzEEDKoa0ppGIbdtGu7rknd+vjw6N6xMLY2XA2b3/69f/Ebv/3bHz25evj2+vHLm6txswgal03btxfnqYlledKenq4ePDhaLTthKyUxGZHH6OuDtl+2xX07Zgo2jJfb3WaYUmxgPhUbrXgqU54SUxsbGac0bkcRUGMHJ8uujYHYUvY0tR0HUJ52V1Pu47KVQxr66ezgg9969kff+O43fvfbZ5+MABbLQKOlZAFEakxOVM+YK9iK3d7PQTinXAkLrwEx+zGBHybM391+GMB6PVre1gafswd/PYv6UYf419huAYB9QvqZA90BCP5Mpc+/WoX0+tvv1MkOgEwAhjP2EM/eP8fhlFLNyQLnmJQbbn/j138P/8Te/9pPvPWF9aMvtG++8Z602215em/9hWVzs0ubbDnpNKaxpGJ5SONOc4Y0AnIRGLehRxsXfeQQl6t1zrVxBHjMwdhZyVRNUyY34l5Cl5Wvr4bdsDk9bRRMwqFrMkbplOIU2U7favtV7Bfp5mwcd0MpKfRgaBdgDrViNRaL7zJuttuzy7PT+0ckpfhifdA/evPo3S/ea3toGcZBOVjfxZwBtyIZgFnKyUxdS9aS4NaG6A4lrcsAgYQYLIEDAGZx0nFCVoQwLN3bPqykiyEyNarjNGEcoKYcsFw1y/WqW7TE/Iff/O72KhP3bejGcYqtJPOm427hzIWERWQcpt3Nzt1mMMh1z+/YP0Fzz6OOjTgwS6hXLhI5YHtVK6aZCxj2pZ4TuTPYyRm39pg0658QoSY1ILW9yxQBTCQEvkVgeN9jA8yd2KxWObYXSgHqWM5c0nqFq2qGUYtXukvlqr/4PGNVaZO27wLu4ZzZGWfmOFXwrH4Anzln2O9z/uKvb58NJq8O//pjtC9U94Wmo3Zh4DSzqeDwWoLRPvmd36wGf71n+aqoJhCYaO4IEz7zCfeJ4ryRAwwRikEkMMjVXc3NnEW6LqZxZEbThPV69fTls1KKFsBAjiix7/rkPJ8YC0G6kpGn3PQNEULkw6Y7OulyoVLYPWhmVxk2dHV2pkX7rqOAYTdJEKIG6LvWoyzffecr9+7du7r59PL66W4anjzJxyfoOsTQOPO2pHGapuLmMhbfTnmXUAx9BHMzDl6iG2LXt20/9eueoSFS7EKIR0AoBbENoZGmje2Cm54vr8/Or88L70B5seQYZdG1bWzPnr/sIlIuOVuIFCIMzkzLg64Pp1gAGYG54n8cIovMc4KMW0FS3Em/qzj/q/HPz1tQsG80/umb7xlJdy7yrHnqtywAAphEAHUqRgniiFgcNkcPl+/9xLtX6TH63cO3711sr87Or6cUbq4HdjAJOYSo5aBU3NnRDDdJKEySd5raSCALkVJA1gQBFE0bpA0347AZplA4D2m4HpFB7F5ADhvMzJRtxO5ci5Ftd0PT9uYONxaKTdhudyWXGXYikLCrl1xIqs028R1WFFUC8G0vxdxgcFZzh7PaDHjt0+L6rn2nt7I59yfQX10sM4fMafQtV+i2Gf851Mt9r2xuaJndfcoqx2j/kvlwt6iZu89CZlatJmoENCeuNZajSkcxKmPSiZhg7A7H/CL36ljoczOggmZVk1x9Jq3iDvFqZrDCf+hvxDyja7illr9CAGeMb4a6KpfWVd3di+kt0jTHIhAztLyele1VmG/Th1nIcE/Lct9PGDoCMVcYq9rLeMUx77IT7yJxr22BIxsxiqLyTXVeA1gqNQZubpUorEJMkbjM8mQuLA6FeQW6GBRIeEYkIMRUVZ/4FqZ0mKurmxPPJoHEADOHQIE8EAdxgXQS27btmtBAvWg9ee5aVFW9d3OXwBTJxc00e1HSeWK2ksOoWigaRUcDmgnIsIwmBAJ7VlO2PfgqBA1ouzaEJqWiakEkRHZ4VkX0fh1j26RxaqVfLharZgWAWHZX05Onz3EBjo1NbkkFkZmcSioqrg0HiaIAMRPBnc2QsqOUYkXNuBGQu5kWN4IV57ZNY/r0k6dxTY/ePc5Fu6ZjCczZ1CZPxS1QXY6yk2mBBKn7L2Ype2Mk3AhFCDx7docbCnEMRJSGNE4TNxCga2LT1nmvECiKiJrOul1tP4zJ1cgphLjbjk8eb54/vsIGTdONN6lpAwqqihoFmbmUxmB23a++tyMflbrpQK3jK5hs9VafZZlmBxqFFSLwTEoCamvMXav+vKvmKbm75rxeH2rZWnEqDgE7a9ZIjTScMY7jrstRrYRAbd9JYLUiMTjZdrsZRs1ZhzQ1Lyi29uDB/eurF2kY1u3pozdO85ZiePn87LpkWFayApIqS6VkUtmcqq4Kt8Uaiw4PTtbHx4uuk/Fqyk5gGqab8/NtOuWjozfffe/el94+vH5pu8sbCc4szGaztB8RsdorX4o5TZuxI94/wHt9PNq3NucXvyJhvfbTnPg2T5tdA/ehuBp5znHG5gnrmXG7by7WDhLB93xVIgIxuxKoSlwJg8kr4sgwchauOZmZe6mrbCEjZ6ndeyauAnVOMMI0JVLshi0yyImJzd2KOpFERA4ibmbDJl1thq+/cdgat23j0OvN9dX15ZiGGDuO0ZlK1lLKsBuHGyCG4TK5YtyMSvDeiGKIMbaASM5ld3Fxv28DB81lc73d7oq0Tc7aRsS2OT4+3d1sP33y4vHHn4a6gIDdYGpajFCUsyt5MRBrKQVw9ZKzu2t2ZyrFoQbyKOzuKDA4BCeHh4t+qZ7SlJ89v2giskKzT0MWblNSGLWxDa1MmHIulbsLQFX3PWxiJlWt0Oac/jIzxXqdWSQEFBsWXXt6b33/wfroZLFYBkKOZNIEBbUhHK8PvvjwS+9/6afuL9/seGkmDTq2zouldBMlXl9vPnz6+IOnj7/1wfe///jj3/2X3/jg+fPjg8V2yIOBAUNgFvRwmAKZCe7JVcBS1z6CCznBXImkznA4Q6uIAQECCSAhcvb82iBKvY3NrZRCJCwSo8yTYmAAauYlWcmezYpJ2zoHCoFj4zBB6XNTEn188+LjD1781jd+/+gEv/wXfvHPvf/+vcPDh/dPH5wcHR+uhTiPtujbKMp9WC1W5mW7uUlpqq6Zy0Xf9900pWHYKcZAcLOkWrIKcbPo2rZjKSmXlLI5QmzbrjPX3WanhtVi2bZRDVPSnLVoJbKzuatqjG1ophBjiCGDi5ZS1LWISUfNYVx1sQlOMYhwgMNUS84pTWMau2W35oPDk6Oj08PYyIeffrTR/Pz86gfPr64mBM3tslUihY9pGobd5uYqih0u+4NV10YuZby+TFMa2la6vomBjg6Xxfx6O2yGya0Mu5xKDg3Wa1kso3macjLXECITp5Kvr2+ud8Oix/qkX/Vd24corqN5LA2Es2MKKzldtw/zLn763avvPv/g1/7rP+hOYQXM1POqbB3JgzoLhcBA0aJTUohovZkxi+b4HkeZ86Tbdt+dJOdzU5w7d9Nrf3j9f/5MsNTd0PonHOvPuJ/XP8xtkwd7yx/+/E/1rwGgfR437U/5nLXLQi4EcUWkaIaUlCUIWRomDkGalpiKm5DkGwPzyRsHPfdnz5/9V//Ff/8XfvnhX/nrv/grv/qzb767asJxHxcNei9KXsCEKNY3hk4ClcsLBio/KFAMTeybEPslkUhsP3r5eCoKIg6RXfouSCMhiLCZeX/0cDvk8/Pry5uNkTtdb6ey6ONitcjjIC2mdJ1Llk7ur9YPHz68elnOnuzS4G0Tv/f9j9ZrSpNvNgjRgwRFro51n3zy8XvvfeXl2eryannvdH143EqYri+fD9NV33G/ahb9cnAtXCXG4ZaKZlN3LWTahNg0TTHLCgG5qakZmbsQcSlgiIgAaUrY7lIdMHSDO8MFzpV0agY39H1/cHgQYtwMu48f7zqm1erYKOwuLharPgCxoaYlce+6yERnL8+fPrli1t0VYiCJApWSc83Eareg3tEM4sqiJyfQDBvTzMWDwevp8D2PiWoJRDJb6pkzuTnU95XVPLPh7q9M22n+h5l4UBWx5vu/HsyYycxnvQLcCqHcjum8qmuYZ/tdzP/wqmB99XBXRZrZ6IpucyeCMWivsjUrW7ntoSvag2KY3bL2xe/802Zm2bwzxh5L2h90fv1r4EX9/HWprsIuc7m5LyIBqggbMUgqWPyZ53HuNs4V9iwWhFeR4/Yj1S+3h0kIhCAcY4wxEEFNU7aUlUSaGOM88QCJ4lDAhREjQuQmxLZdQInBThAOXbcUcreJiMZh2E66WHYHh51THEbabcv15XB9MY07u7rYXV0PJOgXGEbEBkEAW/ftvb4/OD49Obl3cPogXl7Hs4uPz14OQYiIzVGyTikNYxqS5UJqHGN/cMC5c7aONTK18NC2EhuG7Ig8lzEwEVPoF6FnIWq6sFz33bIl0qbjbZLNxZZ3Q2zEfFkJLg7EiK6PsSXnSvNF1ZKSQG0X7r2Dq6fQ0VohaRoiUtWUEhF1i572cIDfTVo+w9P5YXwRtzfs61ft815TgQ/cud1eFQJeh8gqnvbqrjUytIgrfOErj97/+a9lH8KC40E7lOF6c7kbh5srHkZrAwAft7s8FMvEAINL0eFGFw3RgolQiZIsHJvQNMF7ReSTo5MYurPn5znnNw7uac7bZ9u+i9OQWTkw6VTUFQF50myTksPgYlUKsO3a5WqZ8tjE2DfdeDNmn5xmbWHMX+Mur/AVxbNCLXCYq+k8cpCL1q9fnQTp1eXwW1zmVdkzn7g9IDKL471+/qtC0x0gGPv/VIAKd0LBXKK6+54Dvk8P9qPWe9Ph+UB2+xn2B6zk0qoJU9EiMjjD2bH3ZDXs+VPk2I8H8ty85pkcO2dIt0HAb+Pufoxx/zci5irNNHNKCPugXWPKjLeRqYHs1ilwhrwq32wPz3ttNXweIkt7/HYeivTXfFf3WU/VW2VmAqMqsn8Oy/zz857QsBR2Fbgr+7ykVGmaOt4Ir2zFSq4NwuZsxlBoYDImxV6JQkhIIgWtglZMzBybQELqVjQXVTNV1zoy6NWHkh0BLk6RKMAFYFc3cTVV8hg5CNjgamqmqtof96UUgEi8cBnzWDwTs4u5CBEJCbNkLQYThMiBic3LBE1pZ1GDkEENCvcaBBrhtmlWy1XXtePFZdHMgZumKVbSWNqOHzy8d3l1sR3LYimLVbds+nSTlkycGRlEFClO261Ym0tiCm3bRdepTOMw0aROSrGqEYu6l5zh7kJt38cujJrKNMJUFm0aJ2qdVZ4+Oe8OwrtffjOXtAjLGKVEKVPZ7cZh0FVHTd+E7bYU6ASAOYiTT6OON5ryzckpH64WyEBxiHEQi9y0XYytTRlADGCgbaMEUisE77rOXEHOzOp2cv/k8vwCiuPDkzZ05y9vnj25OHt2jRGLw/Xl5qUzrq8vpY+hC0Jcck6WWbxp2jTtHTpu8xB3t8p+rAu4A1UGBw7hKmxdQRvdr/37H2oOdSKDUAgCRdrNhop9343DNFgideVSn8zAsW0jKY3bnZsxSdctl8tlSnk37nKJXkzztFrePz1d32xuNpvdi+fDr/zKL3xrc7G5eXG4PD45WSPRbhg+urhGAkaAs4Y6LKYQBVU7QidHJCxXWPU4OW6Pjvq+k+1lysVj5Clvn59dHJ2cZlwvTnD6cLXbXeICNRuofPnAxEJANnVHnfGDg9xmDqO71gA5x+I5gDmcSIhqXljxWX+FfN8ChzR3T22GOjDDYiG8AsCInDHL2+37/F7zo7mc2ge62pJkZmZiYQlCXB3ynISNrFLVi2ltpe6RfpjaPAYGcVOtX8+t6BS8qaQ8QYC5l5KSdV0P9XE72aQeTTp4BBwxSIwh57LdbDabm3EoZVIyYYop5baN7CwmB4cHm+uLJgY3zZMWxsH6ZByHMm5z0ZR1SrnpGr3WYRxvbm5M0TcdEMjZwYero9317vrl9vISb711fLbZqXLJxbILSeDGlfKYci4s4kmzOTK5OgAjI2FSuDMDQYKq1xGIELFYLPp+sZscJhcvNovVcjeMmrCddjG0JScAIYQQ4zRO4zg1rUmQosX0lbUtz1MG8wgIEQkHJi7uJMbBEYkU/bK59+Do7Xcfrldhs70Yr65FaNF2wm1MfNId/+Q7P/1w/WaHlaBXD8lIwM58ePDIge9sPv2Hv/7r/+dv/pPvffJ4cqB1IboZc1JVriqSdWq0Rl2GI5XSNFHVStGi5lrtFYAAEidihZpWQ5U6A+LEgYMwRImRjOj1gQx3h8JnrU94UdXQtBTEq3C9EEvDgY2IiLNa2Y5airGKtF3XrxfLsppQStbyf//WN/7pb37j6Eh+7md+8hf+/J//2Z/96S+++c69w4dPzr83jDsGrVbr5fKgb9eqGbBhHPpF2zat69VggxGrkxVXdRTvmqZtDx49fGM7ToaLccxpGMqYqen7ZjFiEmlWy8MYA1M0FS1cisMISl6QUgGoEsndWM1305SSWwEXsrg4Pj5ouzYYBeYoQkCFhBVmMGXjRqQPoW+X6L/38T/TKFfjtlnh3jpcDCn2cbuZkCiV7fXNere7Olk1ZsP5xeXDL7xXdNhuN9O4Ay0Xqz7EBkRTznZ9U/LUhAZUhNF2ODpZrderlKY05Zw1tp7ytN3sbm6GMeHoODZt3A0bNekCIhXhQqV4QRdO3zz98nH/7qcf3PzgXz75F7/5XY4UcgtE0mLKJRXhUJDMipo1wSUwkxVjQEIgc7hpFdnGzMr93GT/T9nos+rM+zvrz7y7u+jV/w/bbZ3zI0Ar2r/oLthFd/719V/51egKObx6Y9391farRmXdzLG9nl+r0pXz4dgJxA5SM4nB1XPOfbNc9P1us9FpYBaHI2X13C+PppQuXpz3B836aHlzvf3WN549f/K/X11c/u3/9G9+7eFPP7cfqMaTJQ32cjve7KZN8hG55N3ucLlUF/PIFJibuFg6SdsuDZyLPj873+2SE6+O1hBedH3bdUaeLeWi73zhCx988PHFh5vzK18d4uJifPly/PKPvbla9tfXV4F8N241o41oQjw56e4/PHj7i767Tqb6R3/4UTr1mwxMKD1KGJAARaHy6dnjX/qVnzs4jZvN4mDdjtPVR598+uTJRwSc3mtBq0cP3jLFNGYKHCQ43MwKShCujjNEcFVyZ0cppiWxR1AdOkMIoWNW81xyiFFiYAkgUXfV4mAOaBrLCiZ0fbdarEKgcTfBQLFpl4vihPMcF+s4BKCE4IFl0S1gfPXy+vzFtuva7YspNCFEzvAyDRL28gzVjquuHxUYcTgZ35bld4Lw3dtzJmHVutEIoTbYzWYlFrA7UcV+6vzLvlgXmqkKPONhoJlSdTsMV+WzbqUe55zQ8NptClRR3TuVJGbewN3HnKtpF82Zi89ZG1Go2rpEMLWZcW6zhDQANifi6mxhrz37r2LGLSWqIpdVoGifsdbTavWg+2qcbU6r9vkVKs3iDgo3s3iYwPw6gDXTqfYkrdvJoPln7QzP+61cB34V3QjEFCUEiswRZqplmqYYg4QFkRTVXJJqiiFGkaapUvihKrGqes4qjsDNqj8QQZou2XF1mc6vcHSyWRy0bdsS+bCbnj29ePF0WzKmLbYDjg77JnTcTSKcs2+up+fD45KfHJ8cfu39d7/69Yf3H/zY29PRH/7B76zXXd9FJlfPimywYrYZAOi90+OmWQ9D9iQ2MRE3TWPOUxpT0fPzCyLlZbQwlmn67qfPGTg66U7kpCm8Hbb3Hx5zi+PT1WLVTtN20pKmNKURDR0eHi0Wsemdw+Q0OSvMtWo9k917cLy9uRiGiXgRu8bg4zShlKZrF6tu3Iwgd7JKF5RbUaHPieA/HNL3HKwKjLzi+TnI3KuHwSz5Ud2Hb99JVMtxnTN12wOizKi3Uwtf4uhh/LH37/+Df/S//fTPfz027R99+4Nko9ByGremaLvei+w2u7QrbLFrOyiVybAFn8a2pQUQghCB2KXhuAhjyTHE9em6De3Ls5e5pMOTtZk+Lk+arhlucsMhtFHMwa5BMyUjh4AbTGUkCFz7rj85Prm6ugRgxcws5UIFBDY3ImbiGaeG06sAdAtRC7SmhFbRby8KYhGJIpVpSjRD0sTuNU2+Cyzux+8qvPIKiyHfh6e7z9eM+txZXefSyuegtu+5+kxS3KNFM7hs5tV3rAI9t2CZVP9E2kepPWbjt9e4aoj4voQjQp2DmblltaqbYwbXAODu1elmT9qrJ2NGWms3Yj+kiduJzdszvP/K5nA3L2pOulfWYo71YFWBnvawnpu57n017m60B8726DzNNl5gwjy8I8ygcTehodqMVzVTUzKSu1jka/vejwcBALXv1+mkWXCx8sdCEADV9aOUkpMyxbZpm75TL5OO6kbCbYjDMJYpEzgg6GTIJWSGmiqYRGLgIFPOikxtCK0gkpKa5uaoyyhOOlunt86RYx+bJsauCyGYmqpq0lTSmEeQUR/6dRcWoV13N7uNwzhIylmnsRboQWjZrfpmgQJN2sSWQMMwDNPO4f2i79f9y93zR2+91beLy/Orl88vLCOQ9LETkKUpgF4+u+oaHH3xfnO0IMeLi+fH9w4SphdXl0ePGgeVcSob3O9P3zl559u///2zJ9c8kg2OCUgBkwe0QrHO+atrcTUraJ0CJIYqUZQrSbfydANxFA5MQhaycpnFGqN7CzB++W/+2CZdDfl63OXhBm+evjkmmwrthhFwCkQEZmpiHNLm4mILp34hfd900uGKzp/cXF2mGOJisbbiOVtoRG1yH1m0ON58Y318v71///Dl0+fmxkKIdHB68PTi2TCUBusHR0fRuq+88eP/+O/99nf/8BkXtmxgMBOIzRUENECEROZAxJJ2Bb4f1mUmQOo9Zoa9J5S7B6fKbDcvureVQTuvuGByIXiVV2OQg5kb4kBgB1dIpoBpltYpYGua2JJ4tlQsQcAB/aKJTQwhqNmYpnGXWABAJ4ILCcfGk+d/85ffffONtefh/Ox5H1dpiu99+c/l0n/zm9/9zre/f3G2yznn5CzgiJIRGPcedacPlqPe/I1/969pGaaby+3Vc8qb08N+2TXHhwfC4cmTl4pwePzg6z/+8x985+p/+Dt/t1g5/0S5aYS6srmRtQAZrBUQgwaoI+nMsbzlHNB+FaN9owLOTX1S5z4M7fn0dbJaVdUMhL5dmCFtB5gLkYBhMxVZTWegrILXFYSnOaDUgFWZ0lUnHo5sabFuXQwiLOwCE3IyM08lNTH0fQ+zYRiTZwAooIAQQ63BJQSDciPGnjB94Z13Pv3k2XSVfADADbfI0FSEmRt4NBPVaO0ihN5PH8ZtGleL7vDweJry9fnNNNnmKpvh0f03mnaxvdmdPz2bbhiZA1PoSGnKISPgL/7ln/n2t745bcuv/txXf/nPvf+Xvv6+kj25PPu/fuef/sEff+/ZNq/XxyT9u2984ed/+uf+/t/7tU8+enJ5velWPJntcpg7ou4wx+1cBs3Z/7ySFYPdzlPUfNS71ZKB3bilCB/xH/ztf+fZ0+cffPiDTz56Dka/CGNWBrd933bt0dFRiHFzs7m+vnHXlJMwAW65aDI2xEgSKE2mhtiLBEyD6gZLaRfrlUeMOo065Kx/4Rd/4o03Th6cHuTh5ubi5enB8ktHj45SjwmttP/+v/238qCLuFaOu1EdMTT9JpXtNFET//rf+jeeboCXQATWgAAMxBDbACHVYiWjznupQ70qPzCBifLkjFmhsS6y1fHSzVg4tAJCJZ+6eGwajgKZR0aCi6uVUnIpr9J61KIaIlwJerdktFkGhQCgXy/U1L1qZ5DIvqWjalBiYvjsV1kAYLHAOw8Ov/TOl+4dHv4nf/M/vn9yMmwHNzs5OZlS2u02i74xzcNu8/DRfbjlMm14uhmvhvOrUOygWyxWy9D3F5Y+PTu7uLqKIa67ZYuY0zCMw/nl5bAbTk8eiEjOJTIt+vbRvXsHBwsv09X5+cvzl6dv3Oe2Pb+8+fDxs08+ef7WF76ckt9c3gSntx6+ce/w/2XvTXpty5LzsC8i1trNOec2774mX7bVZbGUrCrahERSdJGiYImiLTewB/4BBjTx3PBAgMaGNPFEA49kwJoYhgFDNmTQhskCO5NylUSKRVaxqrIqK9vX3+40e++1VkR4sPY592ZmkRZlw/CAG4mb79577mn23itWxBdffN9pR+Gle/c6bksqYxmvp+uL4fnF7vxquHz9zddef/XV9fbqW9/5l0+fPunano8WP3ry4nf+xe+Cw0fP7O79ZS6WpqFp+Kj3k749O2of3D+5d//onfe+NUzIBUHQ9csHLz08OjnZDsPV5QXIsqc6+WpaAos5tttpNyZCbLtlGsswTuvNLhcsl+HO2SIuhFrv2njU9WWTbFvuLR586bWvnPavfOcbH/2T//7r3/rNZ5iAADwmINxi/gi8Zu++58Qf0qy56ptXGMjqZfvXP+hT//j04Z/Mw/4/OuhWU/5Padp/4uH+p39bbbz3E4l7hsdLe8bOAAAgAElEQVSejsFOztVuaE7NP150CfNNtk5VMBuzrzDN8Ni8sxPdvHpNsP3GWh5cdR6wWGB3Cezw9//b//QXfuHnHr58Grrno7737Ooj57wZL7fpaii7p+urDFpPWrxd3rm32aY29s+ePL28uIzt8nI9PL24mnJeD5oMyyUePLx/crpKaXj27PHrL73x4vnl9fVOC8xlmiyn3PXtnburrgugabe7hhsTWNplv1osjvpu2cSGnN768pcvzzfXV7vdruSJ02Sl2PHR0XLRrDfP/4O//Tf/4Fv/7Ic/+M7zF28HIlUft8gTTk66l19+iQNOjo9iDLvddhh2Xd81TRjHKaUEIMao6sNutFmsEgYMU7663l6v1cBdt3DIdjtebyYHYoOzsztHR8uUMoiuNrtnT6/HCYsFlouj07M7Z3fP1tv19777g4tHAELTL0LbZJu6I33woI2hiA2rtmvLyVfe/On3/+D6f/7vfhMFmCBMDLZs1c6l8iucyAgAV1mS2pSCuMPVSwiRBMXdPIMgIUrLiSdw5UjUNSn7y07kCCJc21lWTXO9VH9cL0aGPHt6UAAFjiwsJExqpapyWfWOzVUUl8UZxdzmeYtPOu7dch/zWZ4DHHFLLLS29riqF7n5zFR2IqYYhEBmqlndVGjva1bLxD0xyiIQQEwsUrU962t9akE69iM8BzErVSXMUzz7xTMrxczxj4GPL73Dv9m5zkF+vJnzqYPgYoDuRxXgjkhdHo1diMlLjmwT63/47/3Mz/6Nz37hq3d/61v/9Co9HUoZi6YEOI6PFouuWXTt2cnZ86dX15vpo8fnm8GPT5dn9+8LhZzzh+8/++iD3edeaX7yJ97o25jS5ZiuPni0u/dS/PybX1qenFxvpn/0j7950sINeZBxRygNhehMY9oVTaoIgrZZwdpxsOHqAsDZq/jyVz7/mc+efuHNO9eb5+vN9snFh2h4N41Tts3gKSGGk3Hg3UYX/Sl5ZPDVxWMRdyvTOGrBWz/xORKpYqDFisNyKc/OLy8ut1lx97S5f/9B33fjuC2aqKrWoLibqi3asxhFYmq6vFiCfBq3I2nb850vvPLTX3j1p//xf/0/fftb73ehW1/uht1OqoqYFVVUK0J2hgd3glYOjpuZqZLWti1CYOa60GB7oMqraqrOrnFSM+NS9pANkxsgZlFrnxAKKExBxkAIEYSSVdX6pideMHfKaUjPV6+gObaf/7fffPC5/vH5O81qpWiGHW83ObSr9548v74eNhe7MlKwllKM1CzbZRPjZn15df4Cjpdeu7t4vZtkfHz+4vhE7p7da/t22KVnT68aaTWZwFeLXtjTeTr/4Go4Bwr6RafJ05RCaGIX7r/6UreKz148uXhxiQ5IQMKrD18/uXucxvz2299r0AaKtYutycgQJGpRK0ruZu7ZNZkXjbGrpQmMvF42U/NSNUuEA8xVVSSGGEPTELO5T6UknTj6bTeFwyqrRc6BZ2Vm5koHKB8gQLPfgMp7EWBVrZATbqiQe8RqT8128rCIVskI5qYKhVv12yLSWZ0bPr+SG81u4laDUr1RaC4lDND6dhlMjOrZpICBQIQQKEYJQShQXlHhUm3Kq8397fgi++SCSIhkxsTrXCO8i62qaq664BSZGGSplGQONFGYuaiWbO57wXWGcAADQnVOjvZ2gTVIikiNhF5n8pzYZiWs6qYOqyew4nmAUBRxomox/Qm2+01ZWge+zYJ4IN0PPQKkpKTZjFionnNXJjCTErKWYrmoOYyB7IXBIhGFcjakwpksuytmFMxQpuzuEHItuTgxIxIaafqWwIai7BSdI0knsQsgAhmxk5urqqkVgxIInsswDUTEC842KTyYOBk1wo5AFClEiWKiqehg43pw8ymlktRgvh2m7XT8cAUt4247DoPBlqtl1/SWdFxv0zismq5pAML11YWO13dO7rgiDSqLEKOUUiRwE5vQODmm7aRjQYIlR0Z1YPQaq9zNALL9SFalIZBXNzb4LGM+cxAqkAnaa5szGGByF9YU3czVs7kSsbDNc5JsBjV4S41ansaUmI102YUQQ9PGIBFqr73+mihSejEMeb07tyKk5N6GFg4ppkyITWjayIGMYQpXB3sxlRAoGMAkoZFVGoxIYgSBi5sZTB2uc3FbUxBzGBjOzpj7TXPPa59k1N7dXNyqG7nDi+/JQXPxcpBNqOfD4TqnyFTEnSBAABMgkRkmzl6g3GDpCrUCF0aAmxgsQWcFOYKygGnOZgJc2JhUW8oXLzZHi9C1xizjtFtfl6fPPjo9ef3NL7z+8OV7jz589v77H33w+EnawDIgkCPcvd+/8ur90NwznUqeVBPBWQKh0qFdc5p0dApJN5ebJ9TQV372tV//3/6kOe6QOKXMbctevJKj3PaoR4WoDjjz/twcOjE+N9jYZcbUsS8nfF7K7re6QU6ojtFU24i1oTEzS6twqfNMiD4EeXdnmqtLAshADHdnp2LF4ExuUicGDSASajnO0gA6G/04oeoFBGbhAKDr+imNpWSFISCnIiwSYuG6zsndiKvxAsxVK4fVSQKv12No0IaWnKw4Ey+7tpUFg/su7Dabuq5jkMpDVi3FCwBEfPDB+7ux3FvGo6Nl7NpiKm1QVye///ABrkdI3zUnR8vji/PL84uLPKmALQMkYuwI8xy7+9w2PUh++T6D3Yt1OA4uj55zDsIA2qYNxzqN03q9nsbEjBA4hsY0mcNVNZc0jJpLSqmUbKZNGwH3Us2JYQ4tzuyLhYQu9KuFm1/xxgxiMkybPOUiFnuiHp/53MttgOZJp5HVbSijT6ujh6++8cqDuw9D6QW8vpqarjlenjmap9PlP//2t77+27/14aNnXXz5QZ+uzzbZC0QQ5qFRNYe5aUGdOMVMXa48DqlibWK1wTMDWE6VDm21V5jhXHeW2f2yFlJGgB2Mcm/Sgnpf79te+4R/Hqe9acjDoV7MKi/TYexE1Z/c6mZKagwCRCg21Ik0MYwTv/P+4w8/ePYPH/03X/vZn3nrS2+9+uorRN00TlFWi251eX2eM19e7paLzhFMM6E7XoUVxz6ElKbnj58vHt5vQxMkatIh78zE3YR52S3Zo3ADc+GGAM/IqUCpjYtFO/XN5vp6vTjmNOVhM6gaISz7ruGWFXfP7nYSG+JpSkZmWa+H641uOci9h/df6u8vzroPzz98990fPX3xVNpwfHqERROvsDoK1+tSDBeX65xhwKnY6cmdB3eXx52wlOvr5+MEBZqW27ZnDpdXu80uTzkP4xACqeemldCGwMIiXuAQN1Ynz3p8fPrk+TtXl3j4UvP6Gw/Uy3a8jERuGEdutLm3euWV0zeG8/DuD3/wu7/+Jx9+7xKBCI0PDCnzBZsjk+0blvsYNju5+D47PGSb+H92fHIe5/9nx+1M818BQfM/81sAN5sGDno+87fGdas5rCF8GtI77Dw3dJbKfdu3d29fD7/5KgH7oYp5KxeikoDoJ5/D7/7GH7379tP/+D/6d7701VOxs5ZT2wE5IoTl0env/9Efcnc8QahFk0pWDUHN7PJyXbDeZUo5peKxFSHnIFPRMSlzPD6+y4HaVpomJHcUgpIWTIOtL3d5GY5O2qbt1NJMi2rUw1BYnSJAHz1///pqd3U5jYNp4XEoZfIXF+fMOkznH734S0qZBOaSzcmEuDDDVdIIDjo1hSkCwYx222nYTTnnGGPTVK4wdc0i5amUooacM8MIzNAQwKLE3PWiLikrCUDFoU0rZnDLbYMmUiq+XDV375z0XXd1eRk5wjJgZqUoCrLDipHAAoOdmxA1eUkGgpAoKVX0fn9dfR6So4PtO+qcrgCYW/ZWB+P2Ou61/xgkVPbeLOiqZZauIKtkeqtlFTPqICCMvCa01ajHUefK3Sa1CAZzdnUHE4OJObirmzOEHHCuwsf645iPlUBwq8j5WJt+LlTdas+jbkZcH2yocmdQN7XZlaomQzanplVsjwXO87AO9jSKT4WiWVlrn4XRXPfa/o3t49seHtsDzvVN3WZ17p96ZnzsW0AfX5S49fB6BWe1ifoj3WsGMZNzdSJEiMIsOauAA8cQLUAdCNz1/bIJgdkNmnNyzczoWiz6JgZxh6mSWRBINUbKOaUyJj09bfru5OJi++zFdpj0dIE2BnjLziWVYSqaMyKDLDYIDis0DqNmJYskvZdhupYP3nlxef7sM6//jKozUZA45SlnNZAECiYxRqHeci5FGeAgxydL19HN+6YPIcIYLk7sM8jpHOn4ZNk0wYms6DAO292GCP2i7dqQShrHyVSZeVYoBZthSqWMu/UVSId4shqnTbHx1S+cPX78+MmHF8RxsWqZoblMScGutof+3WGz6DT2ct0zs5orl2huBsxfsXednMl3dQoLVeoaDoI6gbwiGXVkZQ6/7hRixEwYFAINQwKUY6JYMNrp/eXxwzL65fWwaVYSWx93E6gHuvMXQ5S2kRK4MbgVeNKiU9ppG2Qatwc/AabQxPZ02fZ9C7ZxGjbb3eZykDgENItG4BqDhKPO7pLn9bjWYRpnB4EWsgjtcdMdtU3qMIIIq3a1vdqO0y7uxNVRoKrShigNxL1kLSVbhs2MqApb15Wh6vNpqa2ucmsz89rzhzhZ0eJwJ5YZqBESeP70NNoBkLq94G6QKjooYd7QnW96X58ClP3WUX9l8GreVEsn3z+oRlMQzRajc26MfTVMRAYXYXEyqDtzDUIgr+L3LAAINgc7qhVG1aU0uJM6stkc6ivscGg83fq0FS0DULXZ60cspSJf6uZEKM7iYHMGiCDkbkbmtJer5grjubsx/bj0ys2N7JDJG1yMYHtRsuo7S07MMPOZMOp6w03cw/I+zz0eTnh9cgBBlOoiA8A1dzR3AwcxWMkKVOoEg1TV1UpRJXImmFGg0ERR00knm+DZ1eCKGLiJLYimNAk5EatlFCWh2DXctl3fCUShxgXB0ZA0zEJFc1ZngblPedKKlNRPbPCs7ggcOm6LFTJmDmAKhJYDKXuhNI1l0Gk7lVHdrGR3NRCKFGwQj8O6bIkkTwVuMUrfN0MZcppyKokyCZubK03D1NxrutDlKXEXkUmLMrNwYHHLNg7TNIwVWq6e8XxYBdVZkNxoBlGZMEsAuHtl+O/1LvdwphncQyUP8hzyDHCUojlbTqY6GxCXlNbrYTdMJE6tGcxtnishUDGDFo8UmYjQLtuTu4tudCs8TeqKvhFu3MDRA7iQGAd2oiknrz4y6hXlVjNhK+rchIvL61w0hAiDKc3hxQ4FJMOqEPm8Mmk/rzs3fWnvLDN/aJr/3vc3KPYko5lJXvOfGcmZrZGcVK0iLuwzbk1MoUqaMy2a5bAbp2EslkDGhFLcLLmaWwSRF4PSrPBXHGZOMBgzLl5c3zlu4t0FqLneXl1v0qMnj9Xb+/deevjK66+/9spP/MTnN+uBEsN9lzYFu6M78fhOLxHECsoOdbgZ1AiIpWAcp2lKk43UhOfnj5r48l//5Z//9f/1T7oVxlyYQ4ytVnd4lENIniM0U3VonsPdzXDfTSSyfeXDhxmZOX+an6hG35l1WkcW9w2J/VZb/4r3auw3cWMfeg5Z7w2nt6gCBAObG1sdRmAilkiEnLMWrYMSDqdAIsIcmAMAMmISmBJ5I00aM7mwAGK1lzIPUBIALVbqy3Pg2MT1lJaBjVBMi2lsQt8vo0RBFImaS0retzylYmbV2o7FYx/aU7m8OCfGSy/dv3vvbgwx5bzowjCOpuXlhy9RP4yJ7t979Xhx+ujRkw8fP+cMkajqpc40z+SCiqpY3YiqIJPbHNwPp7NeCJr1zQAyMPq+ffX1l6Zxurq8Wq835ogxxhC1aFZTVZumEIIEmaax5KRmQchdvSjcQ0BgCCFECo1IkAr/SEOyFFZ2zcJ0tOrvPjg5PlncO1lpHimnEJrl8nTV9sv25KVX3vjsy28erU6GUs76e4phl8vVxYtf/bXf2Az5j7/z/a//3m98eH2+atva/OY5/6LIxCKqWiwj+3wT2s3nJWJiZuE6mEJEdVAG+1ESOBnMitY4MceNeXJ4zgWrD7f7PnnwmrRhfxPuNYZvLYFDiqFF5zyBaguhqnv6XKY7qMrbV5o6pCS72F5Po6YR7+qHTz84f/srH37lq2+98cZr9+/dOzs5HXaTIyxWd5w08MJJqZRApZXQhiYyJkt5zJHlqOlzn3c2+FRKVhJql31surYtzJJSDszibm45F4C6trdFWgzLJ+vz/shVdRiGkourhSih7VuJJ6tjHacQAjNP05jSlCw1Lbcnx91J2zTh2x/98Q/fefvx4w9YcHS0UgyR+d7Z8nOvvv7+o2dAKebg0DS8WPL9e8d3TvtOtKTdOO6mDApo2maxWOTi19froqbmWXPTBrNk3nccODDIU9aUcypZ3YT8cg0KOLvXntw74hjG3ZCnTOreStuePDx9tbXViw92H3zvg+/88/f/xe88wRaxWVkJOuUbMv/ty/cJuZhbaeLtr39x/LmO23Xx4agBGbcA4h/7sE8/2X4c4dAmmcHlTxz725ysNj0M6h5iCO551N/4+jeWxyi5/NL5l7/01v3XXv43nu3e6xpul8frdNnLQyfJOTk5kkmx0CAQpTTuRhRAmJrIHJtiOqZ0fb4uY2q7yHA5QdOGfhGJbNxp9qwOK1k3ORmOT7umW+QMR3HO2cxTyhqZgzv7k8cXL4bL82kaXQun0UoyKzmlcbTxB2+/07bWxI4paJ7KaCXDFJqRxmQyhUBmOk3p+no9TsnUHb5Y9H3XhtAGEQnBHGCJIizBnVIxxwCqZGgSCsIYp1SswAuTLldLK355qctFYOardbp75/jkeFmybzeXTAoHyFQTqXGwavnLDAERUde2KaWUJhD2krv7ff7TNRlQk1eTSsya3c1t9qrbb+1SfYR5ttNAnfKb13KFheywbHGjUl1/KVXSFCDimak7ExkcVTuLvM6C1HGYQJEdTl4Ad/0xJIpPTGvNMitVZWbu5NXQIvVlHGZubqjzWRUiN/dSt4y9jdAnb+k9heoWbkXgj529mdo1p8IHYvYMjH0cnaL9e6spmjHdLKWP72h+gIwPRfYnl6oDgQ5J2f7/BocIOzERyfzDpmuavgV5jNJydDcnF6YmLhZdzwR4KjlP41iyCbxt0PdtDJRSMZtCY6sFJJjqJBzUXY3uP3jY9MvLy+Gjx4+dWhGAGiByQGy9FGU1iiB2YoJhMk9jyZO2Tdu3Rwk8Drsnj67e+Qhf+9pO4c4xymqXSslw5iZE9gYIabDdJg3bTEC/iA/uHbu6ZnDktmmfvn9NJCCCOEUjdohTsK7t+r578vjZkEczIzYm79tlYIdZzhmO5aKU4uyFI8zInCVYCOLkzy+ffK5cffWnP182+k/e+60FexMbkTCq1oY7DNhLlVW01t3d9XYzgvZmO1bBisPuJzRf39qsg2FWmgUIsq+AQEa1KKo82ArLINT0O0pAIJpS9kJd6Va8PcJnPv/ZxVkO3bjZXaPJCM2Ucik0FdoNO5cG6kLEdUjZOHgkspSzllQJkupWndmW/bKJAvVxN26utpE4WIwSG4riQgXuHlpZnS2avpTRtNRij7iBtBQ7WR13mY672JaNl5STpXEc4Yih0azTMHJHBDYzhYUaHgCz+p/PyJ6rYTYndXOtXWSGz0Z97gY3qh7X5uAQZrISf5K2+bHF4w6iWULoJtO4CSa+DyK3V93HBod//KoEAKjNFq77amr/ZLWw28tVGRzgWajf4ZWOxYfgBIJz9ZN32n8aIjPZp8wEEydGnUnSvfxOHRucEdJDT/3mjdT3zSD2vRCYmvp8zmsNWHUInQi852tXCoqjuvVVtgHUdB7a+1gUww1uV7/QDZZzqCuJSJjrjW57XXzglkPCjGuBeF/Y+g0oGCSR7f3Q9mT9WPdURakvJxRF2EgVZlYqtYbcyT2EECmqqLONKG6gmdomwoGYCxuxuYCAAhMKnbSxCxRYmJnIhCDwqM6WixbNBBEld1ItKVebtX2IV8CxahfBOeVJzYSISSJxF1o12w3D9nJrk5ch67Rn36GCl2TFrx9tqJPF8aIJsSBNwzaSl5yKJQpIWgAiinCGo41tbvKubOrzuEKzGqsXlFLACBzJp3qBuLJobFZ4MjeDOrRyrJi4jvvXjVArdjkTXshd3WpfmuBMkEqgMTWo51TSUJLOTVAtNm7z8xdrKIiRpYSGlqulqxXNbpoKhLFaol+u1psr57I4ajnqNOqoavAiQuoIdnq3abu+WwZjGzUPeQrciJBZJTOQOhRWjEmaZ88vxymplXkIgSsgvvdEqGfZUUFXqM0aB/CKkJIjEGll/VQNPnOmT9Uuh1Vg+4gyk7+5dsLMtMpXVpV3qkQwcpCZgQI5abGMouD53lECeYERk7gBhWh+G1U1yshdCWXEdpOPjhnUDpMbYTutr7ePpSkU8mp1+vLrJyJnsW3cy/X6fLe7JtYQyMmyJ3gmcpFgWlImtZBU1rtpyGXIW+zA5+HspP/yT3759DXEEdc+tU3j5vC9xQDyfrHeVAt7iH4+GcZOs+oVcJDtq0Kr++VN9dIcoC4ihc1oAqotjx+6gLfiMu1j2yH21OBzg8r4HkvYS75XuUEc9F6ZxdxTSlaMw4xkSIWunF1BROvrrURikdg2TRt261GLEldOqxmKmxFRgXnVBiRwgDQhNk1HMNiUCkthBjdRmMxKEA4SFktWC2kcnTN4TmXbHqs7TX+nO7+eugb3752e3jkOIYxT6o+6aRrN9ej46GI0g985PdXJ33vv/XGLPoKFi1nODjLHHsyBwzFPydV73PaKHnuL3Np2pVmen8wNhKaJ9+8/uLq6Wq9341iYEKTOPNQWtpnqOI4hhJyyZgV8GqZaCwghtNSFWKFwFlLL42RVWwoR0nDXLtqFnN5ZvvTSnXt3j1G2LRCFnZomhtfuv/rqndfO7r3andydiuViT4fNB+89+u7b7zy/uPjP/+5/hbMa7nH/3vHF5XUIUQJrvf5mTeia2ExpMs1W9mJE+8bLHnBlcjZVAjE5vBJ9Z/fAqnmGqnbHmAsL7BXaUMdbmAw0zyzRQaHHaxSxOq5JVD1z962y2qV0nckfAKqkm5HfiP0agZmDCAuBSnEUaEbJYIMZfvv3v//bf/j9L3/hd776la/+tV/4a19+6602ytHRyWm/Wk+X6jyMUzEEaSODnDRb4HhyfMLFVk3HRzRyO/FQPDlT3y0lhDaWbAoXFmqE3YpIYOaA0DZd3y/baSMhhNC0bd80WqY82UAU+kU3TWm43ljfRRaDUfSj1aI76WSBdVmfr59941/83uX1iyA4XizHvH5xMZyGB688uFPKKyH43btlO06xaWITmH3RSwgmwdwMRWMLZ1AQiLh5Mc/FVJGLwimpORXiUKS4ey5lGKcxm8OZsN7sTs6OT0+O3cqTp89LnhZRTuLy7urucXe2sONn766/+Zvfeefb5y8+AF6Am96HaBPBO1i5XSPekjq8OQj7tuFfoFf/usefBksdusR+S3H2//Zvb+W9h13pU6k9AFRqdEUpZl4CzBkBZLut7tZY7/A//g+/9t0f/NFP/5U3/7O/83cWi9fyGNfDs1cffuknv3C5Tpunl8+3aYoKNXRMp6v+pbunl5vd9S4ZUawQfoEm7HZ52Oau5RDs5ZeOYoO+D2Y6pcLsLGBGKUgFEprYCMiLbpxK0VJmHoy4E3Nzub54dr4bBsBQMjQBipwwAO+/+6MvfvGNO3dOt+s7m+vr7dVuHBEI1sAUbd+o6na72+12V1eb3a6O7GPYTl3Xd30fJDgANmll2XUcQmjbXq3ujKW4qnFwFopRcnESjWKLXvKkjEJEQbwNOF518Ly73o27y+NV/zgMwuBgEj0EbhoHTITEweRd2w67YZiG2o+qgxf1ajGz3oBL9Zq6s0OsblcuPtNEGBRmHnSdXyHZx10QMwus0NxnqMU7EfNcpav7rNi03wlh5kzMEiSIiEQJBks6YvY2d3dn99mLqjZxxaAMrtZXn7hLDw2727+pfVN3v5HXppoeWZ2I2Df0zOpYgCvgsKpZcciaMN/fXhwCYhDZLDjqn0K5iPbbTv1drbTqWH0Fx+Yeb03B9uyLPZQMITKvPIv5CbGXvqHbjK9Pr7fDbA0OGtD10gmTMcFIADBUu749Pl62DfpFr2nnxQwQohgiM8O0lJwmsqKalRxNkLbhIJg8AWl1xAI0rYJz13cUegS5c+dhUgxjvrzS2MQYTsy4ZCtmHLxbCUOIWS2lolAI4ApMjkBN26GYOVuaMKQffu9Jt8TRnUXgFelgeedCoYlBuu06P358dX2R8qSuiB1ef+WMfVFENGuZ9HvvPWOCEJoWTY8QKDRy5+xkseyX/fLbL94tCV2LpgN5aiOahpoYcsrbwZ2SFmUYZxLh2Cy7hhuOnvj5xQeX60evPvzMq2+cooWmKRcDoru5gylW4fuq7cOYZ1X1IDSxj4gzgHU7IQdY9pPze9L57VBre2yE2Plwq5O4M4FVuagxkUcJIu6mnDXuqAufe/XBT/7UlyY+P9++3y5PPU6xbdoy7c7zxdV6nJzIrBjMqaJERKHhIJJSBgGhAlg5pwlk/bINhFxSGbIOOFkeC2KU2AZh1zKOJSmYV3cWdoI8aJ6KFs8lG5f17sp4crHTu0enx6ePv/98uVzmlMc0WDKOpAU2abW8KLlUBzYvblqNBvcKKjOEuw8kFSq8AWRmM0bfd0lVtTaNCRyYpz+7OzNjxzdgysdQ5k/CMXXF0SfSEqI62zMzsAh1espnZfCPw+z7e2AGY2oBOzMNvMpUsZvOn9GBWW3KDj8AANI9aI7q9oFACEIBxdP8INp7C+5Rs48FrcqimSu7KvVTCTb7gFlvVKu9rtruonrn71kUMzS/h2cDgd1BtficP07dDPZqEA4zc/uYtJm7SxA3r4bjvre7Z67F/mvrevgAACAASURBVEEUnw55y+ErgKDjnufKQGBihnidjweFyOQUmKV+FLMC7C3Snau0LjECQsutiymVogpDKSVNhZmtzCJNIoHICMKQSHGXB2+MhVjIglVoTKFeVboDuyrNQylCAhJQBDdkrGSIJGbBUgJq6wOh54AwpmFYJy6gQqTudZyeOUCYWKF5pzANR3HZ91rSbtoEUTMyQRNDGgpbkCBlLCCkKcOpCS0B0oIIrq5qni1n4Va60O18gpO6U90gzWdiqJlTgShme8hZ4s8BqnJ2h/VjTnLAX4mdiMiNZ5W+CpypmSEySMiNNBkKCPCCNDgWFFaBA7q27duumJpZ13XHR4vd5kK5GKtR9uBHJ+2Uy/piCwN6PFjEbhnBmr0g+1iwbMmFi+UxF2kiZxMJTqFp++cX70+lFHM2dUYgwFmZrObEvB/2dyKQaz4QeSoXllmIiVFJRRXOdRc6GC0cEGISzPe9wyvTuy6M6mls5Oos89CiurpWXrqbW8qDepo9LusT1gSgwN1rBw7Gc3CxOZEwMyeURNeX09FpkRgKpFt145i//8OPVosnZ2fvv/zyK3fP7i9Xy3ZxbG5q6yldjtNGLZmXe/fvu6cQOSz6RELE4E6dh2ROXNyzjtfb52btevf853/uS9/7wyfPno4gK+PAoYULzdl/qRzZuaeEvQPhwWLrcMKYakY2xzQAgFb06sBN5hvAmxxMZLXmn402ZnBszvSqCuEtXKtyWG6jV0R75h3hgJE5COY21zRQM1ODwc3BgLBIAJGaqRkRxushLqK0oe3aJnQvLq6iRKqNCRFXA9fd3QFHAAIkkgiBqV90wzjuxolZiMitZErsSCUTNETrF9he51SR6wQwdgak3XCx65cA0Hdd17XMnFKiPbihWsZxUIvrzWb9Yvf+ex8ygzm6UVWrq+48c+je9wTqW+RbP5gHNfbBGagblJdSIJAgi0X/9g++u9vt4AghAMi5qM3NNXPLOVcTxvpEXD3NGSFSEyUGcSgx98tFaEThakoyJVdq7PTO8eq4XR3FtjWy4f0fvPPZVz5ztDorU2mk+anP/5tfeukr2QnchEZiE3743o9+9eu/+U9/9VdzMXQ4llY6zqRgapsWQXQmVdYEDELMBilzl8IdFG6aig6vJuimxkRW64S6v6l7AdG+GSEAQ5iJWGYLUjczVQ3UwsiN4OKuRDJjgjUhINlvyNVG/LDTOgOmFVasyQ5V5d+6F7p74UogiCG2UC1TLpO6shCHSE3EEcp6bd/7k2fvvvubH3704t/9W7tf+NpfBbeEvmuJHRzavAWjLNs2knlJLCxNNMVKmn7RalxOzTSEbQGa/siZiVI0YwpC1LUNYIsYmCS7OtA0XWyaPKUg4cG9+yF0XmxMQ4ytN3r+/IWOUzX3ODlZ9v2yXTTU4jJd/OiDH7776Icvrp6y+PJ4ya2ur65G4X5qT7E8O+6n+6fd9e7FVXE388lNXUOUxWIRs4Ricny6mHJx8DiVnJ2oCRHuRTW76VjArCLFUQxF1VJxNRg5ldyveo6cSh63u8uLTdciSNfm7rXjz3V88qPvPPn2N957+5vnzz8EEtpm6aVNW0P2brUcffOpnPDHHNWp8TaS8hcw1p/r+NPoV/g4hvXnAbBq8Js7K3UT+XF/6vNIQp0TBsMxTcXVQsuIphMutXzz/3j83e9/+LV/61e++tUvvnz3zJ6HzdXwuYdvPd88tcKyedGQqI2N+9GifeXhvdVm9/7jj4Zkzqyexb0JqMA/m5UJTjk0aBGK0ZhLOzGzOUCCpoFIE2MAlDWrF9+XO0ROEGIjdhKEWMOFuJiAyOwUuLq+6No3z04X0/aSTK/Od0JoI7oudm17ctqlNI5jKkXdKAgg88fXQpoJBjXLNkp2d4QQSylTSqWUxWJBSO5qpg1T27FCnKVpnDy5J3ezAmNdLRGDD8Pl1fVWGCeny34xhEAUQmiitKHps3CaKa2mIcTN+Wa73Rw2qVk6gBCYi+pNJXizqgjskNqVp9qi4QAJ7ET7xoBr0kqzZWIJgcnMLJds5CAY1Z5knTyotxzICeTkdT4BxCQiMcbIomTZiJlVtGYepf6pw53J3NXd1KsS3r/C3U51EMWZ62hMnQSsHdC5neqoFYN65aPfKjD3d/jcjrl99/vh+7np8sk3UDnu84ZTn1Fm+pOT3whC7ufIKmHAZuM1r7NAtn9mB1Xx6ZtyEj82Bh7W4AEprN1yEOBqGhhEDkXXd0cnq6YbQxAuFAK3FFXVTUtK7sW8OKRrW80jE0LgpqEYIFJC1CaENoaOuetlddwtfZVUHPHi/Pr8fJfzwtCItKZFdVBTsIkYgdiQJhs2kCq64IDBTMuYcioiRNRA83e//eHpWXzljYdHZ63m6Baqtn4QHnbD8/MBA5jFzfPO+raHqTiP0/Ti4go7gKoeLiBSr38Mi647Xi2PSgEcfduFqDnlYbeT0Hdt41amMTUNJTjg1SB40TWL5fJoudKp6JRSWRtv2uPhs2/g8hEuz3MbC5xFmijdmDNIAGIydyNyZjIQmTvPatp0AEk+deUOF3OuyOtSvfVgmmWoK2uy9rQZFMy9+mZknQxE0U0Vjs//pc/+3Nf+yp0Hi4368mF3PTw7Xz+Oyy5GydP19ToFCchmpbIS1EsdcnTVpF6cHREIkJZiEGOs2oWRWlEU7hCkCBmxVHsBg5KwxGVkCtOQC09omCNzplzK5fWLoTSxC20fc06hC8zB1K7Xm7IuUJDx8mjBkGE3uBuJmJlWZzU1VzucBSLiSnp07MeXbqAnO2BYmEl4lRbCdRbmhl3xZ8aNW3OBM8ZcxyewF+C89Ve3oav5R/Xe3gNbzHvaTN1naaYRkKASCbAnYB5erFanNZJUKGweaqy+i2S3C+QKXc2WEwEIjMgUmaNgqJDI/qMddu6PDT5X8sf8q31RU3GlG9/D24+em9g2l341TNbhhhlg2teS82XYv8vDdOSMEmqdWZyHfW7EDajqYhsgNxcFs9wV9ifihnl1ALCm64Q6RCjMMUgDJyooJYhE4hgrQy/nrDSZH94RwTRPpq5GpeM+ujg1iYEAU0e2QXdG5GQhRG4EMHdD8jKm1GLrGzZuFpHBZnmyyclD5BhDbCMRqt+wCAtCaCU0Ig1LJBJcPrlgpjxM4zgEEibaFtfej5dHlAgjoBQ5gKBkpSgR2IgKGby9s5ry2pMF4q4NoelXq8VuM623ABkKnLgYORt6Karm1rTNkLbuKuAKULkBudQOk2ZwdpQKGxPchcmJtIJnhOoA6GpuoEooMIfUAlCJCOxwYsC5GiswORO8OMEI6rHpYokMa6QjkUYaZgo8s0otIHAVhZC2646Wqyml3XarSVMqUxkdrqwetG2a46PTO3fu3L1/VvJuvbnUMm7HdcpT3VkUoMjOPE3qu21/vAQHYnFzEnl+fp6mZPst1YmJhO2WjAIOIZg833Sq5t+LuTHMiUiq2OdM267Nt9khFQSKUmV16DBE7E5c8yCoZnImFic1MuM6cVYbaL7ZbAiIMRhDi1K1W64B0BhKXllXyhXbrkwiZwfj+jJPKS+PTo7PekU8PjnmZt0fjX3X9L0nu7rYTJuxff/RmNJompg9NtIvm8XiaByv3KxrF83iKDeFlLrFsXpWiqFbCAaPPNlYNs+/8c3f+OW//Yuuv/viyfXl+ZaIQBGgakwxU/4JxEZgMyeSCmx7bRcSzcBQPdc0h4da8NUOIXFl8u3phwfglJnIbB+yaC8dWOFE+KG22UelW9H/Bvl2R9XlZ55t5Cr2WqPPTMRncB3+RGAOYDPSpKWUKg5XiucyMaRpeh9UjhonkiAQOFiRuXYFBLFlaogDzCylJC1lBaDDMKkqssJp3Frb4vQ4Prz/4LOvv+5vvj6O5hbMLAbul122cr65eP/Dd1MqTQxtE0R43A1FFUS73c4vLsZxiE37ox+9+/zRxZNH56u+12RjzgYPscnTnjkyw7RgAsz2k6+VBlyRxsPpc5C6A2ZC3C2b5WrZdu37j55HIAYJIZh5GkdVDU1kFjWDZjCctAqLcZ0ZDNR2Tds2zOwoTRtP7qxilEnzOE6GrJYXq3B6b3l60omnPFw+vxhOmtXTd99dvhR//i//4k9+/qs9lhdlW7yzbOur9d//L//Bv/yj3/vgI9gIBJzdaUYzI0Lg7bBt+n7MKedibmAO1MApD8nGhGTB5hvQjLMAXt0m3cmNiTkQZvN0d2c3Qm1Cs9fExGfmMIkIEUDF1NWsGAlpnb52x76l4/tYUr8FnG4GUmiuLrw2pqiK185lhrnPMCxBq3hxsEq8mjyPhuJwGNGw1v5Yzu4vmfj6cvdb//sf/NbX/+DoJfytX/qVv/FLv/SLv/i1vm22u9LG48julgzGBGFAEZvgDmahKNbYEI4GM2/bKU3ZtesWTchmZbVaxCZEwCxvNhtXZQ7DbtxdXC/6k1dffu14NT5+9GKaSt80ItisNw/v3ocWtcwtwoImGh8/ffzOh2+/9/S9883zu/dPCyZuYEjc5KZpQIOX4cHZ8uHDs+cX66cvXqzX26fPnxZLTNo2i74X4bibcLy6e70edptxM22mSYUWITRFdTtoDcNNQyVXIVo1JsjMBjAgNvH66voiGTsCcPfowVsP3/r86WcuHm1+9//841/7X75z+SNgByEW9Fw6zc7FQeR53DcNPtYPvM17uB2w/uL4f/f4BP3qz/nH+3La91OEP+6wYnOPpfbszMFsGSxcsi3iYkzb2MSmkccfDP/Jv/93P/MT+Ht/77/463/zL686ebx9+8FRYMNR17mUMqxt3KpZF5iPumk63U6lALsxB/L+tBdpCDyN+Xq7YTcJCCHASHOAdWZMHIsqESl4N5aiZlrrSiFCCBybRliOT5alaNs2hC5IO002bkYdRjI1n8ZhE6Itl81i2ax27Z0TwZF07eqoP+6XvbmmkodxzMVC0zVtFAnMAudSdBgnswSCtOxu293kPpZS6nZtVkAagrpluDFzG0LoI6FM0zW73DmJeelEODk+awKuLq9TuuqjWB5OTiChkdiGpuEucIRqUVU2K57huLq8Wl9tYXBizE0CBdhZyAvYjW8tOrZ5FoqdpEZrV3IlZ4lOrqpmCpBPTuIiQGCCQ+rqnTM3r4opBg9z5XjAjGZvK5CaIWczKxBlza5a3yPY5xrVARRTmLPXfYKs6Kdvto9XNUAV0gJmOQsn2k/HkKNyYGjGF9l93pPo4FNWqy+eqzgnAqxpGTBmpv1LVFWAT97288QfE2o6T0RUSsLHzAT3xRgYbnCygzQE1TKXb6C0ur/uF97h837yBOwfxYDNBWFwYmJWV/MswsSGgqaTxVFTeFdKNtUYxRzQPKURaizeNtR3bXO6YL9MZYxtWHYtt8iF3chUmfh0uTi906+O2hCPiY+++90P/uiP3332Yse8ymWIYaHEzG1sg2Msecwjyha7HdZbHC94uVh4n3MIXdNPuylPO+ma2ITC8u4P0vlFYkzgkDLcG6eSzU00DZkVITbMUdqy3UxptGk3oeh2o08/WKNU2gAXiSxSch6v02b96Pj08jNvvD6sseyJPS7aZS5DHtMkRZZNG5rj40woIurwccy7XZm6KVJ3dtKfLJpIYdTN86v3T17CL//KX/39f/buN7/xaEouUCVmAwrVhMfJGaXKFQVhJ5gp3VT3MwQzt3tr/cy0x3j3EgsHbOLjx8zAqugyCQAza1oGayqjMk5Pmvv3T774U29+8Utvchf+wT/8R0jACm98kc7uH31mcWccNRcPAjKatiM0IFktT9s+dDHmnNvApeF2GZpO7t8/OzpdJUtHi9UwblISGq3x7vrZOk+lodh3bROpbbk5bmLf5JKT7ca8hUn1klcUI7QSQLrZjlfnl1ffT2BA0cYmHDVnJ2fTdnQly7WakCBSUrGsZALdz0vWsm6/KGYVrL0AzJxH7BlYhDoQwHCCmqorKS0+PeBzeDo/fP0EJlXhFd73+G/rO9kBd0IdY5mZGPVqz8iNoU6fzD3W+lFEYEbCdYwZDqql3mGWf3+/3OA/tdQK7HvRXT/cE1ShqxnDskAUHFzncA6N4jl2yCGA3MQXB8hrB8fqGyJzreDD/GmMvBIdHD7bsYIIzHOUPtzbB9KDf/z+rfyAmmHvu/91lfjhHDLzbb1237O8bl8RIqpN6Kq76LekooNNlT0LCcRwBZxKtgKRYNJKIGGFutnBQOEwuWEJZsooHHJLjVCIAURUplKKWVEIgchULZsQubjBypR9Z2WZ2SSYcG3nqzrIKq/S3dRyyVadCOFQIY1swZXh2K2vhUKeSk4wKDtSggxDg0YoYISzG0xYWIRYTU1RGKKuDQCHqcK17xpq4mLZa7F53KyW/e5N161OF0GCaXH3ksr/xd679dqSJOdhX0RkZlWty76cc7pPd8+NM5whZ2iKkkyJgi2RFiybhmzQEmQQerAAG3ow9OBn/xG/6sk2QAO2AUKy5IssW7IhmRQvQ3qG5nCuzb53n8u+rbWqKjMjwg9Ztfdpjiz7QYBsYAqNg71Xr733WrUyIyO++L4v5uJxR0FioODRpUotlcCoIFAzmeSmbmkHpoBAkMXNWG1l0TlATsTNW9HdyZvDphG106ZBAsLNDogRQ+hiUniUCIirk1GbyBQCpwQRJid3toIXz6+Px+PhcGDizbbbP2YiSBAxJ+B4OlbL17fPN9uulPE0Xpc6py4mJnPrukjCZq6OUjWqNm6ksmmt18dD74Ea09nXBMWciNDEfWj9LjCIRaCuDTY2NJ+p1skjYlCbKYgGe2ABRptjuEdIc9BoXUNzNJM6dvP2o0bQps1ddhAvKDlprjGGGIIzVy+qlZ0ETBAYaXWok5EgNJILLTiWu2G8w5gxn7iehxCGbtjWeiIjDmZSxnIAF5IKVuLsOhetZbKqoeqJKRCJBIpNt6+MmMgYoYNWjj3YHWqwj56//ef+3C9+6Sufefdb19efvE+JYYqGTy3hYFXQrOFAmGFNIdx0kitl/RWkm9a6YrkRvlpsExbMi5oqfHEpJSImAdRtIbuhgVNr4FiD6n2OeN94B9ypkf3bSjC4gB5Mu8HEziRMaKa5zKRuK8mSRGBgkzqV+TixL0FzSH2QcPJTm2tJDhaSFCTA2WutOlqEuoEk1orppF596OnsLBC5uZ7G29Pcb/reUauXINz1fYh+Ohzvbp4NQwLVoY/boadiajqOp1zyNI+n5y9Tf9YN/ccfPPvow+denTrS6rkoCXddKMhwfrjfWFsu922iV5u38PuugztihLlfnl/s9xtvLreN+eXQqqq6ZMarm0WDw+BYehKMGMMwDF0X203phy6mIIHmu1Mus9UcA5jr2Vm/66OXerjL5TiVzD/2xpd+5qs/8/k3viCepqlw2I7F/uH/9r+++/Z7/+R3fyf4xX5zGjmD+FSMGIAAVgokeVXVqsQcJKQYGVRz0eKuEG9TbikDuBfdt163UeDWDGW4tfSrWZ60W+SuIAiYIezEzi3Gu9kSO5ZiYs0klv6QLe2dtrCJHuiFa5dtnU1P9+36BYt1gEiI3eDFilot7tlQgGJQVKubJ7s85dPtuN9sh/1O/VaLxnr+e9/89niY9+cXP/mVrzw6fzQInfJV1nIcxyiWxFNMg3RqzUsyQIj7xGaFqJgGpIQkQsU9StimjWnJpcynTG6hk+k4n8ZjH7b7frOJ26sXt6a+HYYUJEe+eLyHVbVC0U/18OL2+gcf/ODtD//wUO6G3UCxkreqx0Pi/cWWWK9efviYn54P/dk2mm7Jq+p2zgKq5Opa4ZUZFBOFaijznE9jiVxiJ3PRxmkOoXUVQGDjEESMyU2tFhju7k42E2sMkG3aPN68tcWTq7ftm7/53jd/872794EJDMGctIqpEqFLArdajg9dZjx0RpdF/0qT0FvfbK1R8aPrn9P1/whd/d/Qr5Y+7KfauD9cbEHMdGmWt76sEwxgDhLKPNUC4aGMdjqMaS+XT4b5OP83v/L3nn/88V/65b9wvnnahwCrQTDV25vYzbWcTqe55tCl8/324jIc5/zy6naalUJKcWPKOh00Q9iI3c2ELIhv+gDuJHTmZOa5lFpKqbPV0tZUCAQnZueAw91NKSOxB6nM7PMkXFJPTFILRGB1co1BDKiPLi8IPHTbLvYk9NGLq7mWacy1unDkEJhTl3pmPh6Pd3enacrDkM6HXRDUUqY5u3ufYpdinucYEYOYW1UjN7AJK4HbvJQnj84kdKXq2fllrV5LZoYkub09bnoOMSxDQPqgxFrN1dy9pcWnUz4exvaJ4j6mLmgHrx8ngBU85lbRANzcJ73xhNS1+Z+gpWJNBE5G2tJXwopeLTg0oXG42pxCWggRBPNekla1ai29Z2Njo9gmVa0ULCeAzY2W+WxgYolc1H543bov7gp2z0R3EAncfSVFNDsCf0hx0ByZEIQAc1/4T41vwaDm7wsigjnFFBcQrtV0Zg7nV2btLEnYPUvjgUTjza3V18cbFQ0k/pBIrR1EXxWAD3ut1c5ED38C6yd4X2VT0z8uhhjNkomQUjQDsbO4USEHOkhisMM159GskkFAWqpbqLUklpTi0PcwqfMwzTMniewh8Sk4s8JKtRLSbrNJQZBSkjh8/PHzZx/fPL8KwzCXwiSIUTa7kIYggcbTPB3q6YR5BBTCKYat7MAcmUTrzDETC4NTJ+W6TgeMBz3eFQsE5hR6BbRqkGAOZph6JBm6dHeTj7cHMp+P9XSHlDqYOESII0VFblY3WsQtPjrbupcQUgi9mRet86REJSXZDNsyT5zElUo2U5TM5r15KpWc+HC6M5u+9Pkvf/Wn37q9st/8xodNvAwrZfHuDHSffqzrgRfijjXe+spgsZW9wkTcrMex6iEe4uu6BFZKkbQRz6AgkhxU3YAGR6kEKOHijfjZL332y1/78ljKe999BxWP3tqNeppGEbno0qPT4aWbwOPpUPXgQmTF4EhC227o+q5qYBlO5bg926Set2ebfrPhGcLMxjZbPal7mG+ynVAx16F2iXnfc2LuxR1GLiHVWkpxdyemrus2m00IXG7K3VWWHl7gBjdn4zKWeSzs7OZCIgxqYxkNq/PTiisRLcIZwoKUuzcP1RXyITiEeaVO+L0XrZGJv4rT/1OutdX58PUSWPz+24e4c49S+b2zIJot1HLarU/2xfq5zaC5/xPU7JZpmUi4NIXcF4u0BzkNrYJEAMsMQizQXMt8HeAIMEzIuflvQD71Sh8w0bWUfsi4HjBxgGhpvj/EfW+h/uHZ7muHoDmLtbdsS9iXphK6D1bLe+d7Ftha0xKBIPdg1YLI1Vrvb76vV/tNDeBjYqdXGhVraUBEoRGBmtLHwZZVUR2upZgVCRJjXMQa/PDOmYSZYbmdcGXOIE+h66SjQqZOBnKHNM9xmJkVbW9rLrMdlTfNLM7ceTle1EtWdcs5O8wUVIFGX1Y3VS0Nq6UkfR5zmZ0N5NAZUGSfDzeHi4tLFPiACvUKZo7b6GXFXBxjHdExR4Qk/XZfMBYrnHizDYGGzOYaTJF6CkGmaZymCcU8GYB+GFIXUeFqgdN4dwI5BzA12sRiTVS1QsHSuBNYB5+0D8DhICZn3A+bbO6YBo+Nre1GTG7mtpTBXUypxinPJRdSTHe35pZEpqoxhBgjgZgDQwD64KMPaoUXOPSYC4VeOupSt9l0XTe88+67fUkpBZItsVdTEMyLBClqm7ONV815FkFMYS6zNhgyuGnBhOZ1aQpy1KYgVQSRxZPpYVt7iKGprszWFdd2BTWx0Lo52oZgaVG9bStu7uXe0hBid3No1WyVhCSwA7UogSi042CpWN29C4GJ2cmJowSoufri2KXQuVZ1AgeJrnD3INLcDEHoujDPlWoHTyn1ah46CRSZoFaOp1vgLHSAmdpcdapazbJb7Hu+ubvbDLvgyUNIYRu6vhq5C8fh6ngNiQyv6qRKoXv7ne+89sbZV/7YW++8//54cCuZPLjBCcJivOiEWWBNACtRszY3IFrQqTa+oZ15tO52YB0y6osyeBmW56bOLJHNhKgC1DTGDxSsNXtrBeOSEfIrx3LTMqu2wQKmBsAIbMTE2jqaTVMMCAXAmIljQ7CoDbaAA+ZeK0VBpKp6c3099L0XVNT9dj8M/Zyn2JzMXFd5HhFg6jpmb6OKgzAErkwqFJmYWQEvprd31+ZbdapuQbrQdSIagm82KVo426XLy912u7n78NlZ6m5vb+9uj3mqzw/v/NhP/umqmO7KyxeH1PNpnGoxLAygxu53B4TWCyAsRxExvxJ2af2Y0I5kYmj1y/PL3X5/dXW93WA+ObkrKaCOZhziqqZFQ2QRMnUYYiJyj1F2++3ubAfyWmcQiRCgIuH27iqKbLvNo0fnqeueXl4erp/rOPmphJJ//s/+O59//Yuff/zFs+4y0vDhy5cv7l58/dvf/4f/y//+9d/9+rPbqWNliMcoQsRUrY75yBWpT2pttjlIOMQQRVpiIsRoOlxekzRAXJZNvpgRLGkGtM08Nri3UZXW3CKImdmrgkODJpugYiExL2EP95YCLa54o1MtHEFa2yjL18RQdXJeuYnkXkC0EEgBkeiGPBUoUGG5ojp7CBwo0DQXCWFIooZ5ymoM86nU7/3hu9/6wQ823e4nvvLln/0Tf/xr/9KXYgj7zaPneTqVU1Xv+g07Qx1OQYQlIQLmbGYBXeidrBrBjRQRPJaqRWvRFELitO227NxLF4kvLy9fv7g+dnm76YlxLlvjkpIkTod8+PDl+99/9wcvDy+P9cQ9d7v+B+9+tx9kf9YHsbnOw77vKKB6LeOLFx+BQ2QbEummu8NcqtY8Hg8zoW4321s1gziLs1SleZoka86qChHEuCQ7MSYChyCIjFJVHUysfYwUpduns0e7x0MZnn1vfPbN59/8J++99+5RnyN4F3kwJa1OroAaGZOyeKNMvppKR9cHGgAAIABJREFUtRylfdUYCL4y0fHK9SMY65/X9Wrn+Z/xhFevxjp51YwHr6T7r17m7lCYEzFRWDQwjjwXcMyTggCyrh9cdbzWUyn/3d//+jyNWvmv/NWflzSc96+pFTvmt568Ndps9PyTFx+nnqmL508ejXPuUjwcpylD1ed5qnPuCOzmplZUS4HVEPsYI0hAQhKub27UDUZWA5kYKtQF7MwGow4xCEHdspZsOhMhiFycn9ca2OvLlx8Hqduhj4He+Nwb8zgHSVFCrvrxJ8/UoYoYEnexVhSvIh6ZHUwcVXPq+hRjTGwVp8NdybAtkUPEGRyE3Jm5lSxa8pjS0KUw5XJ2ths221x8M2w++vh5rSWFSIzTKW/3iB2cnCOGoctW8mxExkRVQR7mY3l+e1hZ0ljcvFsmL0JtmMt9T3rlGJipIHKzuvIlknNgavh3WeKyubfUw2FmK4OJnUVYmEEI8KaV8YW04PCu6+apWC2qFQ6FtUQxpujuXtTRev4kSga4qRszNweuPzrmqs0pY3oo+9Z0hdHMrKxJEL117+8XfrM3ZmZTd9OFUEVwGJhYhISpHSOLLwItGREAkJvPVhbI6qH6bX3YFShrN7MA6/eLISQB0OY27Eyfrp6xbqqmPni1eF50Lw9YZNteICZyNlvanw32d46hzhWE1Efialnf+hzOnwzm6qSn460kQF1I6lxjiF41DnEYur6PbEG3wzRPlDiwMjhPB6CmjqcR43gCnOB5nse7qw8+fBeAac1TIEnX14cUhWWTutD1kqK4VUbQqoG8FplOuttsWHiaToYpJq42ehkDdxJEnErW6ajnr21dc4hc3YTl6dPHP3j7IEwEihKfPn1tPM3TXDZxSCl13XG+9dAFU+RJU0qcIrnMOZ/jQis9efzaH7739m4LU6rF5mxuDBThsD3bHqdDlKHM5obXnjxhhP3ucjzpxy9f1DxHGEu52D19/fLyy1/70s/81DsvPzq994PbmGLfbY4vpiYfRFV3AzcfXgocWAKW3dI+QJfGbCRoE7lqBa/FzZrDOy8tOPdFsAQXd/EFwHOIQ1TEZIBa2V8g9vi5X/iTu4tHN3eHd9796Fvf+bakoBOrkWkS3pY5lDlMI/JE88l77wNIa/XZGpRQc6laJfE85cdvXsZePPjxeBgPR81ZS50P9XBdxdgLISNwlMpzztfTFMt8HowDQb0fhjkHt3IccydETjppt42d9JgncncDtbFDRtNxQvXTNAWSQGLkdapmxiREbAtS/nBSrRg0mxusrnD0ghczkQSGuplbU5i0bcL/rJzhU+fX4jrRfMrRvJoCxQUuu+/V3Cf5D/DLgrksndP7LesPJKUGwy1INa1g+FIoNM5QwwWWnqwu1tgrxnUfRRgUIPIKn2nJlFp0cjVdSAzrE8jar7l3215b7ysOzi3gcAOSHAstq42Pc1NU8sCM1iRotXljDzqttRkJcysYeT1RVhjAyem+Ilh8bxt+3x5qXDqmRmRbPuz1pjXthdliMPypI4CWGB6q3X9LBGZ4bTNrCaYo4+xmHFoHZQngTTrGJIjwAi1mmk2cOQaRmCKIKOQ8ldZEbYGVmCBM3ChpZKqopFWDCjMHjopiBDcQs0gws+IV1YFaCpyEOImQiJRqWhwzmqRRK0KDJByqFWcQhk4wUyTddKkWM0MSCbE/phnsSsXFTKzkOuVcq3aboQubs/PNeCimLsmc6mmaD6fb2IeUhAcMu01MMt6NRatIdGih0g1pvM7SQUeDVyiZNoXV0i5ZVjLZetdBIhKImMFerEJAwsIIUSpMmN2slmqsBGDE2X57qvE0q5YSQF3ayb4z4rvDIXVpGPpadZ5nALGGPC1QXTtVr2+n2GG3kd2+Y06bYW9eQkjCgbgNGBYJUUJSVLVZa10wHiYiqFn1kVCZDAnTsWBhbIJZREJoQ2O8sTvJFuzZtc3pIAY307Tl+qHUmFfCxD1C7AsivXK8yEmIJAbQanloanBWd9DCZzQArm6bzWBummtLPqLEZdCEUwtuUHNHLcXNRSgImZEZ3CAcMdfxrpw756w3H3xwfs6IqlBUHI/F7VA1w1wEQ5e6LuVMgJZcXzy/tXOXfcfomWo/RA6pau23Z9Pzj2GEGO/uRlTdpt2Hn3x0vn3tS1974+rqy7/2P33XOFt1QJp9FdZYg7ZSEBhiBFng4GrQZXqjYbGaamkboZFHW0Woa5iFO9QMVqtqAxSMlNR9nfhLTMwUmGDNnK0FBaxr+D56t6YqgMDiBCKh1kUybp6AVp3Q4G32RswiN1vGCxARRbFJvaqbUuQupc2wAWE6ZiumouwShVmolFxdq1Z1CoElhhjDPI/qCGTSpcjJXd1EvdkpoRqmORt5VXU3LR1T7bvOoZtN56CLi7Pd2TCdTtN8uux64VAmnaZx6B/Nkz57+cnt7V0Dnkyb1pVJHuLm0hFaJgvCrM0YbTzmhbPmKza7YDqMGENG3W225+dnH37woSrcYWYSAnMkV7snxxrcnZm6LoIU5OToNt2wHUIMYz6N0xEwkIKiVgqM813/5PHjx48vCcA4zTcnH6cnu9d/4mt/9md/+ucebZ9u+ezuME+Yf/03v/6N737/7/3aP377Wx/yjs/Oz/NUtBjH6O5V1YlCiACmOUdCG/htblUrDAxibipXhrsr3Wf1vnQ1iMAspKUS4Oqw9rYa83s5lY0g5qRwuGtrHy8lMoiXn7AlBJg9ZA7tnG6nmFc1srbmWQj3nSxfio7mu0WL8sOUmIMxBRGpudSiZCBv4DcTg4jBrO5aiubKEpmjuqMyZvzXf+e/heOv/MV/88//6z//x376K09fe6LC+/i4T3h+9cHm0Wt1NnZGEg4dkwdyCEkXnbVamTNCJHarJZfT5Godp6EbNn1/PpwNcei6TXAWpzdfe/0wjsfpdPnoPKZwnO9up7nY/MmLDz988cGzq2cnnSqpz8i35cX1837uKjZ9otyM4RJSiNd3N9NcJEQJIc+z1kkIBh+Px/Gowyadb8/e/+R0HHXKda46zX46OdNMROaIjNTF7W5zcb5Xr7en29M4U+Wl+it0ttnqyffh8nOXn9/Q/jvf+M73f/tbv/cbH+MFYhgiiCyYEUNY3LU6KVM1rF2LV2LKmuC/0hAE0LjMP6TTaVTzH13/Qq4fBqtoTeVpPb8J8Gb3QwureT3xmQCYO7cEl0Fcx3yb8+Yi7Dv+jd/41v/8q9+6uExf/uqbP/bl116//MJms7u6/XDLsxObZiW7u3pObJuz/euP9vvtcBzt7mbUsTw+27/59HI/cLFxqgqvplV1ghFxMohD8jSREBMLItzNSAKShD6GmHg3bBLP8zzPc1XNVjJ716UYhJjDfJpvrq4vdlthpBjaaWc1g2m7SbkgFwShbjN0aYAHgM1wOo05l80mqU7jNPWTpDT0qY8cj1M5YQ5iT9+4rDoXnUBVxCVA3Ut1c83qIpJSKFX7bogpnU6nEIUDHW7zZoOiRnUGOwm7axCKMbiqO7tpqZZn0xkwwWLMwwsniZnbEb+Mwnk11cK6OQlwFpIgEkSYDc5uHszCfSlCJEJkMKjaUud5c7gKLFiG/rWQrN6yLBGxaKoKdQhIiOClgQoShaVoZSJiAbmTmJvWakVlAaEe0FX/NGEcABy6UP5aaWRtXo1as5JYymA3qKm2JmobdkwAnJhbL5lCG8nMDC4l05LDr5YvwOIjslZhaN6M9FBRr/3a5VUt/7SOIDuo/WWCo80jAVbn96X31caCL3yLVqK3F7j8skZqBtpY5+oFaDmsA15VY4rzmGMKEKtkX/jiW4/fPOuGOBnN08tOztobJOdaMglENimEKJK6OAkJO5MT6jTOp+MxRDEgJYTIAG13u/c/uPnOdz9mIAU62/US+1JF0PIFM3Xy0Hfb7VaQ+XQcy6hHzbVQrRoicj0VmzkitDwq1xiGOtXTdT57lLq0hUUP1oWkJqWYKSTSfrO5fPRodzbcvHyhpvvzM2j48J2XWkePHcxM5+PoHRHcNWPOo1pNfRiGLmseJxxP43Gs2y26zRC7jkmGIRE8Rjx58vj11z8zHosaf/TBs08+fBeKyDg7C997+4N57Ifu0Z/5+T/5nT94dxy/9+LFmKSid4GzAYFUmVxBIiRtZbR6Z/EvaM4SWLh+hGbZxQCRc/MOXZFLXvp/BBCVuTDFNHQOV82VZrB78iq+v4xf+PLrb3z2ycXru9vT6be+/q3vvf1eGvoYh5ur2+3FlmM/T3pzdbx+eTzeZSscedgNO8s268ErsnnOhajcHBZjyjjE1Mcp59sXN+Px+OTikZvlU51HiGY/AZUpBTLxosdTgSFsQ+i5FOs6EmIGI8Pgh3HMXLs3+323vwnH8ZC3aehSLyxerORaarWszmRgcmJIbFRCrIqQdQohojR4acHMWxJKqxtPk+3YskuZZEWWVoL+/5vTre2zFTJDA3/MFlrGA0aOP4KjE1aqBbCwCdyN3KzRU0Gr/58DZtbc2ZmWTisLkS0MM1dfuETttxmI17hBYAYJpBlBN7yH1pjSHLt8OXbp/tF7KputhmJ+H4ioATlYg5i3NQu6l6wu1j4GZzCTtBe8SPm8QfCEhm2hGXstJ8c94N44Y4tJvOFeTN1u9/LZ/RDI2LA15oZYqWojYbVJpveU/ObIFYgJRBxFQgwiCpUqqtZUIFarsjMFCewUmwM2NeE7SUjB4Kbqi2BeARBBEgui1+q1onGMm5czt9Eii9M5EdiFiUWCRKoeDFqtElEnEcKCXFHgDPEQQgghxhhjPOqxFkMGCBQldcTEIQZiqqSP3jibSzlejyBIj0y1wuCgAIrozlEZYUDBXKbxdBqnPBOCG8Pz5uLRPBWDSSccvEOq6IytWLWCrDMjqelcxy50qeuHLdEmjFc5bOI8F7MGTurKZuGlTwRjCW1+LzFL5BADBEYmTVsYSEIgkT6F0zzNdzOEpec2YqAZBBIjBE4NJew66rt+O/RDvx0205xPh7ENRlz6Xe00VOz221ryOGYzyrMNw2aeRnc6HEZiq5VYAlOac53mucy5zS5lATOD624TIscgWur4ZI+Xd/DYXNYMJMRBGne9ZasLcLYEAWZ2s3v0iplZls12v4zVoA/ucMt/RA06biCumTtzkCBoe8QbV8msLlJidnKGw1yhWW2RZSkxRJjAZiBX06UqbpkVzB0Cc3FXhznKqAy+en6zv+kQ8fGzY4xJ9sJEDKqGcZ7dZ3J0nZztdrvttpTheLwbx3noQESt/2zkRk4MNSqOcVIJYsxzlk0aQhre++h9eTO+8frnvvjlp//k179rVxDREIKDSy1AQ3oJ2lylXH0FtLDcnqW9cD+gDcsmg7q7NczlXnvDgLUhd+0Fth9aGYFofbz1mLUF0lqDyX1QfyhX4A5ZZ782+jobrCX2VYm5T4GZq1Zt1ERr/F5bhhn4YlcaiJKELgQDBYpWvHDVNmAFzizBvLZYZRAl5mZkZrrMQAhadNIaKnkvHBhWvViGVs3uVWtWzUPXhxA48DTNF/uzLoWb26vpdOSLJymlGHszurh4RCR3d8fTPIFhxcwgzCICFjPFfROF6H4B6+oe2UjjD50YWszymEGMGKXnutvt9vv971/9/lQgRlqbOUlzOy7VPQaWxb+CmVBN5qx9h5gChMY8Ho6HcRxBMK+gfjt0T59cXp6fne93b1xe9hKunr2ksZ7Fyy8+/bEf+8xXvrj/2pjLkJ7c8ovf/4Pv/s3/7D//4OXNFHHxuQtmmY6ZUzQvudTWSRdhYSEicqlWlqXDpG5wY1BoK/xVPQaWU/Aegl6dKJtXa1tjjAU8Xg81A8wbcOSOBmO186+RM90WD/uFyUbroY6mCFmaIgC3kcPtQGVaeVtrG8e1aZGFhKQNJFAToRCj12qmpqXWoqTx0aC+phJof5mjiAFm+cnFxTiO//gf//ppvLs+/Nxf/6v/4YDh6vTJ7fHw2uPXQYFMvZKLuIbW+O8lqESKNs9jtpM4pZB0rjcvr0OQs+1uP2y62AVnoS56DEpcbb8ZQiBi7YcQevng5fPbw9WLmxdZp9nGsY5TzVVsLmU+TNuzR+N8eH51Exlu9Y259LEL7a4EcrdcZnczrQx0Mc3ZSp3rTNOcX1zdTJVKtlrhDOJlcDU5OGDYpP3Zth9iUZKTTOOJFSEEKGnOm7Ntv9s96p6e0ZPDR6fv/faH3/36s27qZ4A91VxRnWAcCG6GSijqdj/z4RVI/I/mgvdfOP4pic2Prn9x1z+FsOX30NU9VRKrCdHyhGXenZPS8vhSkpdcIEi7ZOanQxHBxVv4r37lf/zLv/wX3vrsZzddX/Nx6F8/6/U4Hh+fP8o2P/vk/Rcfvaz1je3ZLhC2KQyPLx/tLuEx9BLPT6fJdT6yNz6kWWH1GlKvVg+3NwaOQUg5Sb8ZYggUiMVZSG6e3XJgphARilPwybSMJ8zj7DaT4Vrk85/5fNfFs+05O6xa1Zpi7PvubC+nUUW6ruuJJMY+xV7V7uabcTyxwN3GUfue+sQpdEOXylBSkr7fDJvd8VBLNWINnXS9VHedisNKzjFsKQSdtVRL7nd3d2qyGTbu2iWMRwhXjuQetc6K7Nq0Jk6GOvs8VdQH9MTXtvunPsgH8HjV7DioSSK8gSXE4NWflABQ4tZXkxBactUYtmuyRlYdqsrAIm4mgGTReMhCvWcsQpKKsvKsJVROHFla5sK2DpVdmVZo6iK/T0k+BV4tK+teLShYbHSaClLQrOfdWVGVoL4Uoy3ZcEYMgYTIGewOA6w6as5rIrqefPdr/Z6E8MrtXDDAJniSxcmhnWJsTcCA+z7t+iXuH1velat7uGfH+/pSFwSNSIiaMdeKrC1DF1e2HVIXpqMRcVaD+RtvPt2eD7nMTrUqehhDzDwQicTq1VXVailzdBlSGLp4LIfDcTZhAkwVQuf7/rVHT7bbXUp9nl+8996H+93GDSH1zMPhZHnXGZyAUio0DJud7mI55X6jxUYm4cBgcq7EyhGRKYRkKhUy3nktdrw5Hg9EdJ66aGHi6JYLUUXAMPB+Nwzb4DRXzLFjiq5WlRXJzTPM4LV6NSVzRwCH6jyR1K4nZj2Nh+M4E2O3S+cXu66TaR67jXRd1w8xyI6Zb24PJfuHf3j98grbvhVT/PbbLw638jM/8+jf+Ld/sd/9+nd/7118bzw+OsABFooBbE6m1drsKFV1oGNxolVftqATjRK+ahFowY+90SQXd+8VLTGA47CpxefbWwh5bwgKwE6wLT735c987U/+xGtvPvmDb/+f77z3/Or2iBjUybRi03HPSaJqPR4Ox9vjfMw6kyDU0am6mAwhSoqJo7MNfRy1gNAPnULvDofr25syah+PPtt4qJhBAJSQrdbqRsyyGYiiWrap1Ntj7gclkFXAYco6adaStxqGbggDB950mxiT5jpOOZ+yGbrQsTO7tOTDbNGmLaK2BdJ7RdnX4kyzpiJeKKRu1NhajTXazLCogYWvBItPX6/Sr9qG9nWPt+qHiEwbgPWpn/ph3jGtmNL9I+z3TKslRvBDNfapa7EqBhM7SVPyoRYDWoRcqnhmSNNsCRPR4jq72rovFeGSMy11YiNiLTWe/VA21d7Zfa/d7gtJX+Evv0+821BHblLOtVpfqnqw+zojAytZ7j6q+doaAQHETs10sMWsBYqi5lS7vj5fXFP+yCdlbmz86iPtRwIktrLesTDTiBADUaA2VaFNseDWqYavCnJ2d219g45R2Z0nncWlizGIJA7g3jQScclZUcHubK8UOuaFVLTOwmzomElq1TIb3NB5DIlAqUsEAoNFRIRIiGR/dsF0ONoJM2r1wGyEkudu0wWqn/3xz2cdb8a7u7tDqUVdo3MKiUDTWN78wrmxhRhLmW/vjqexptDFGKdpPrp26TDVEer5WBWTcEAACUycBGOZpGMTd3En77apw+CnI64gm4C5BGW2UKe2/pe5xW2gAPWB4dy81gNLjM5uXgEx18AsQZwsq9ZcQgqhk6nki93w1T/1+Q8+eO9Yr0qdAS7loLeHu7G8ODoqELDfcD/soqSUehLG6pvDwhA/HQuczGwax7sw/dTXvvr8+bNnn3wyTsYRjy54uxkIqUw158wkKXAFGWcmrVouL843Yag39Xj77OnrF3Z7+/JIAEHd3HKtbZ8sRG5rHGmIE8Iyt34Bp9xhRnVdf7QGDSdvJjhWlr1DznLf3G0xHeq5nPIycwGvmNihTS1Y+YGGw82J713+CIAyq3ArcZmEF68BFlQ1K6XU1umPwj765mL/4vZ6/7z/7FfO03OcxlwrNpu43QzbjW+GYehTCiHP04vnN9OYd5tt3+0t6q4/y3OptRYzK9N0/UxNjuP0/PnVR8+vH11esPHl5Rd0np+/uDrcvDzbbC7Pzt/83Plf/vd+9lf+09/S3pirQ7waR+66HmpFi2rWKnDnNt3atc0JYgYCCRETq7bDkchR20DGJqlu2EKLrNwkmmAmiNAiu1rGPTaGqaoSjJYk6hVK5w9dJHA1MuLQ+pzsrlioVhUCcAC7V61W3NFJEGZvq6YuQAY1CaPa6XA0Z5tttmxqliuikJOTM0vCoojUuZTZu20qyF5RJlX1XLxaJsFWQ1YiKUSQgNQhBASaORtBO+8YIUbZ77epk+OL6zqPOY9gqlnnOQt1h9N8Ok5zmZc7wGBiFmpHK5jXtMKxtGBXje99Zc7kuvbYGpQvkIgQ6XK33+57Au5uDzhB2aHwamamsMbHVTVziDvMOUoUyaSvP30a+85hp+PxOJ3UEQFT1TxTL1/+4hcvz8/F6er9D883Oz7qOXZ/8Rf+3V/4438+ons5nt5555Pvfv83fvXv/O3f+f3/4/k72L7Bx5N3O3NCPs6SBpGAuRgoSCLAqjMjBFEqCKvaT4TArj7nauoAYpuV6sRNPezk5g3nIm3EG3d3GN2f7K7+ynwTR5tOKbIYLALkpuohJFrGry61wELtfsj4HaAQAxGRGEDqgJuqSoi88LjJQOIt+CCGICEKqOSSx+xZYYAiGAIosphIJVctMMQYKUo+ZMujdAMTMfh4ONZcLM9//x/92n//X/zar/zd//Kv/ft/7V/9V362DzzWso2BOZAwUyIkBwmM1AOQKMVEVjOJSuS7483p9m43bIezrg+9VX169to4T6XUoB7Bu/3uHLvdbvOHn/zgvWfvvvPRD0IXpjLeHK+Pp/HmcJcZceg8EpGMJd8eJjd0CV2EeygK8wxCcb19eZVLSTEGCQFcrTIwpH7oO6F4OJwm78iIQ9yexc0AMx/HkytiROoCqFzdHrab/Xa7zZZFQgidK7vg9bPP7uly/kR/93e/9Qe/9b23f+8GNyAqrFQZWjXFrgtSSy46VxRyML8KQn46mLySriwEXYKuY71+dP1/9nqlpXFvwIhWoS9aYEAXcwG4r4p1R+NhWbU8KQdhhFL8lP0fvPeDf/Crf/PP/NL/8B/9x7/8b/38L5R0+Oj4+288eetsP0x1GqebZ9fPL863EuWT26vD0Xa7xxfnl65hnE/1NOVp8qJDCN1ZT9KNs1/fHDddZ0QfG6bJNJplhN18tnszJC5lqrOSUYqb/e5yv7sQ6uZc55PWWsp4cFcW7wK75U7OXn/y5LXLpx+9/0EJZtAhDvvh4o23Pnt3Kne3p2cvr0/Hebvdn59dppSqe3XtguwfDY+CbFIfSbRWARH47k6vr2/efPM1JzEKIuAQOEovQSLGKVs1CJm7E9/e3lXDzd1cM0IcIHw84sklS0wcB0jvLK1LbY5GH4Kz1aX9gEytBUqmbuag6rrijmu/ngD+VDOcQFWV2Jm5WdGaGQj9pncHmEKbwwO42SbFKAFE85TnMtdSrc1+IybhEFhCIOHdbn9zc+Oe+2EQkfF0sqwxcUyh1pqLspcQIoHMTa2NPwMLxyBZK7B03rB20bBWUe3dMAvxKpZc6ANk7n1KwiTC3GzSPCq8gpgWZ8ZX23VaVU211NZ5RsUrkeuVdb8UubSQFtCMkAFfddBAIL4H1QBAWoW80EgfrHnuRxTey4xYUPEAcBFqaaMZQQRiJhYWgMncDOrszCwSSAIklHEuMYBcoSZ6tut+4id//LWnjz558b3ru7dvbtBv6uXjy5ubCV6Gfj/mycxKKdM0Jaf9bjNpufvw2eGAR2/uXnttm3NRtSBx6LcMub2+da3bXi4fn4uUeKRaoUrP61hKnUbYc4y3ePz4whS7ixiH89241wkiHCNP013RWgxFnXO2Gm1GrQylnHOeT4EpbePddLi+fjFs9m+9+dk/8yeIfXt3m69uPiw+bfv+9dcu2fWQ8xe+8voH7z6vxata2qTdecehjPPkwNPP7R+/sTkeDncztBZmSvsQI87Pu27HpvnueAWh84sLCcPdXf7wo4+/9/33Bd08ihY6FJxe+vNPcheeXTy6+Y1v/N6//NPf/Ikf/6m/8Z/89e986/u//eu/+4Nvv+uF5+NcC8jIm++JuhmB3I2ZiQPnU66o3XYbYjD3uWTNJVBgEoCat21zQWkMaMc6O0+I2PpO6LxzUaPqgqz4D/7GL6UhQejd9977rb//jW9/4+NWEKW+rzVb9e2TzfmjzW4fYnCrE6w2nSM8HK7HSNGNBVFcTqexaPZgqeMcrJrNdZ5qYeEYoIrjeKgngkFi3w3byavmWkclNnUV6LZuXTxYtdG8TY+q0KOigmM4vDiVqNt4VnFdpzrdTdNxyqOiNAYVCYK3wkBhZkJCLOzairW2w/Shp7icNy25BqEp7tBuevOAW3hQ5A9qH3+lO/awidcsvZ1bwGLhuvwE0SoaeOUXPTz/lYuZ6QF2vP/1zfCOHgC4pt4A+dLNtQUkakwoIhZpMH3f01oAE8HJ2cxqLYvv9D3y7UwNf29lCGhheKwhylfl4B8B2WnNxNvLg1EDwVu/wcH30DwRJDCzEMg8q5rqMgOsjfUBQCTuTg9OQU5pypTpAAAgAElEQVSrG1ab8EWtmb2mdvc37b6lzSIPGKV7swlu/3dBr0wBagT89kgjZxFRcAbUrOrEiNQ0jMoigDFxCETkVquCLRA1r6L1TrkqmOFMAlMzN1VVU2ERaYSbgKWjIWCzRllgwBFiUrImyAEgi9saCYtVK6URMbjp1duc0sZxUNXpNBd1DtGKQlGJYpA4xDTECqVOymTc8aPzi6rl+uq6ah32w267I9G4y4aqqqWUXCuLxNSzhJCoozDOY8kzC2ouWbOkkrquG7q4Y/QWtwIGB/SbjgqpmoigAwZMOoNQTMkQUyCIqS3cQmrVMMjhTE5uBIM5kYM4sDg4BA5Sq5VcQse7bjuPBbNv+uGzn/nse4dv9SFFczfKRmMZge7pk3g4TtNcc7WBeLvb5VysViTw+tGzBLLAzCEQ4Id66NK2zB+X2ZAhAYzIHKP0xWeoM4cYheDVShuUE4SDkIuJ+huvP75+PyM4Ozu00WrcDO6rn4K2xW1oc0R5YQe5LzI3WrJZWv81JzODWWsetiVuK8pJ95tsgbIBIwoA0HYbHARhEMhbmBMlXpiJrV8FZ6i4O5wtcAC5gRjBHV6Lr151TEQxCgsqT8cxhadne/SbLgjHEIiCeXUjuJhRrgbnGDYhDDlPh9vTa08urSLFLgSZc7493FWHhL6YnU4lhAKqQ/do35+XVDabGfBxvtltzn/2T/303/r8b+HAp1MhbwQcYSZTd6iIkEstD9JpM6c2NvEefHe4QQTExOZmTovJqAGN49n0WS3Xa/bh7u4iBKxg3wo5MC3Q+D2GtUaW+9BDRNCsRDAjBIa4M5zdzWBgQGt1IlNzvl8RJEIQcl+XiTuplTzPWdXYnObaIijJ4nhviyy1ceZUq1rshDy4U5mrtX4vcUyBKTi8agV7NERaQH8JQVjMXecc+1Tm+XQ6TadTdAdQ1cywGZ6A+OrqphRtTFUChSAEdjdvXdQGczZpW7MnoLVKaxGRuAnoaRmZoWBIQIocQri8eNQN6Xg4KhQZNIBY3L2qt3l2LGTuzBRDEOEYY4whpLg7P0t9V7VUVBe3kok0sseUhPxst910ab477VM3vrx+4/LNn/hjf/arP/ZVddrS/hu//fX3P3r+27/ze9/79sdCZ4++aBawq3Y4nPptL0PSaVSExk5ukgR3c3U1DRtRGBGBubmwOVvOpTk9OpGBlnxrwfLM1KmZGiIs00IaPY2ZiMytNaYYy6iL5fwzuNMiJnSIkBngzQcB9/xNd9j9aBW6PwtbR2eRchKtZyiAlWPMYAKkkbureVEoyMEGdoihoZHkDq9AExQCqOw8l9mL7Ya4GzYjHQJHhl38XLi+Gn/1b/3ts4vNv/Zzf3o+ngpKYul4kNA5R5EIlHo4mJUomxClD5GDcCBL3dluvxs2fdcHkjnn8+0+cThiIiMtpYdkkHk5jHc3h5fdNhTLN8eXt4e7aubCLCQpxaHrxN7/7gem2O/6y8u+S7zdXwi76VxKPtwdnl09q9nP97uL83NhqTPcEGLXd9s4bA8jKmam0EVxI1U3M2Z0Xdhu0/5s2/dBJj8cDyUrEwcJcBKEENPjsyfjx/redz765m985/1v3vU58RCqOkWOLCc9wfI8Z20kvmWeNa3c+B/BUv8/vPyPpMHrw7buunXrrd3RRqC2VfIEsPpyGgEOMwiEhM0oSOQh8A6z3cYeH71/93f/zj9696OPf+kv/eLZ5s2r6SU55TlvuuF8vx+6BCHXcn11NR7naTu5huN4OHvKNWdSjyLqdBqncVStc80TOHRxac1yj83AXecSvJlgutqT154C8XBdr18eXr48zKcqYiJlPB2Pd3fbIYVUe9lZ8cD27tsf9X28vLh4dPno8ePXU3p7493t9Xh3O5eCvrN5nokoBE4phWD/F3vv1qNLllyHrYjYe2fmd6nbOaf79EzP9DTnxiFNUaIoiJQsEYINQ36SHm3/HPvJv8KPfuKLDNsyDMgyYNMUbZEUxyNeZsS59uXcq+q7ZObeOyL8sDPrnCYJgg82DAhMoBt1vqr6Kr/M3LEjVqxYi0VikC5Gqm6GLvZ91GkcxxGn02TmMSaJwgIjsAg7uefU9SEmVTiomt7fHwF0my7GYbePpeSLi1Qd1ahqraUoChFiiAGpbbTuBAkMWQqOlj20qTUsWOPbQEqtA8nkTXadyEEtKxO4uy2KEDBxM2PnakpsXt1UmYgSM3EttU4FTeTAAXYPpi5MBLcgsc2ChBhijKVkcx/6LsYwM6tOWMQhrIXolrYsxHt7W3A+dOCXnIa4NTCFBSygtYXr7mzk4gyFwVxJG41AmVzECM0bztuwT4OXTE21GV2xA8LvcisAtPqzjToBC5bmb7PXFXhqla/7AyEDrQLgZSE9JFQPGNcDw3tJgh+SvuUOAqpO5NAsCAIiA7uxMYOZJQQOkSS6i7B0m84w54rNPgy7gchzngh4770hBq65sEMoEiBEIYgwa81qgXoLBDPU2tSFIkswbQo2IcZ+zOM0TZtBYDWw1ZJPpzFX7iIT2BU52zxiOlX1LF0Mqedsx1K5UFRSLxLRMWvhOlPOjCwMBhsRUky7XU/dNKr3vUzT4e7uzel4FLLDcbw7HzOhH1z6vZcaUr24uixlHs9zUU4Dd1sqOg0dLq82j97r+71Xt+1FyFl32yF20jRyqp2JrR8kdYGAWmvOs1YWlkC9Je/6zXTIYBMPAhnHGnpks+evnzvQDfIf/K2f/+5v/whJSZA2DJUyKTIRWOSBqQImCn1AxXw8zQ4EoOvSZvBJG7HFm1dPK3OFyR3Gq6oCHDXbpLkiAzf4he988M3vfHT5aHd7f3j9+v6nnz27O1YM6EKqo2lR7oMil3pm9F2XJFQ3J1R2bcn5Jg2ekVXh7EJevagxoUvJfLq9uz+Md/NUI0ka4jD0dS4eC3MVk/Ph7BaBxiMpWqpmzBvtL7tN3KrpVKqrIxMKUF2d5lo5xWHPKJ415zmXSdmAwKSkkyqKIBCReIOf2dclQCu63PzvlsXS8vCmfNxmhW0hImGhifK6Iltn9a/EwMI7VNUvAl5/Fq76C9+qVWF4t9/viznYUkyB1hj89veW9+Y2IEYPUFMbZsISlREWtQv2B/Rq/e5ySd6ZlLSVptlOAssoAi219MPnWUD/1hJ4EL33NrX49jOvocqaC6GuGfeaDzRWBBE51ilFoD3SbzEprG2Sds5tH1mmfMjhMca3f7AdZs0+eC1C3zZXHEtB0T5V4BAMBkUbbGSm5vjmMApEFACvWeesHsFdChyIuTU4SEI7XQeIvHkKaC2qNZD0oec2PA+BmS6sheUp4VaiVPdsFhhwMASBJShqqVXzwk12BkcEC2ibhxqY9/st73k6zefj2BajuanXw+l4db59fXhVqQy2oej9ZYL3kliluiuQp/lcCk1FlRBiQKBpyl3qd9vt888+q2MOMRgrIrq+22yHMAglN6nb3fbu7rbm3MeNOOdpjoZ+32+vNqfXZ+7EqpJTjIFcCqrV6u2WC7XinpzMSGwxsCQmInGHRKbApq6woe8dVpGffvTomz//8e5ikInFxYkNEHaJRK6qxGJdoqEfUgpVZ9WSUr/bdm6os821WPUYuzo5TEmAAoaM48Qsode+E6043E7u7KGOc45ijOCuJBRYUsemtVruu83V7rLbbf9dfAarBHIKDaJ2WyZ26J19G3CtCpblkSWC0Apj+cMuTwRiIfiSBy/NMF+cYRZknInUQC6Luw2tMDMAMEkThF5GkWzohta8M1OHY5k0hz0sSyaoEbkzQUACcrhCTbd9P80zC0ottZQgab+9gJCblmLncRIKKTYVuxD71HUDSzTNpjSPlSAxJsDv7u8+f3FrTtePnoL4eE/jeBdigL3ZfPTBMOwJc9F6PN2SeRf2v/H3v/NH3/3kT394H5xJgkJzLl7VHSl1EgK8YrGsbAIKbrZoXEHVCqz5WTcx+3VOEFim6tvCX0VZ34YmW32+WgQSb1DCOrTfEEZ7O064BnYi8pIhDG5QBhZolqlppy1WqHBIIAR3LBQ5CUQixNqmIp2c2phXM6peCb9urqrVCi3yfsvoADvmc5bIBGlzC0GSk8IASLu7IVDXS4hOrMRCxGo2zfl4mv7G3/xODMHVVC0SGxncQhce3TwxDs+ePTscNU+NbkXCDPWqZuQNR1lmE9p4QVvXYRFR9NVHoCGExOwQIhXhECSGeHmxH/p0d3sbIkMhLMLRzNSyOyiQBO6SxC52fRuUDiLi8LlMcRO7Ll6n/V77Mp2t5j7Ik6uLIcVHV4/qNN69urPD+HT/3m/82n/84ZOP39t95eXd8SfPv/8v/qff/sGPf/QHf/xHo1kO49Xj6+PxPOZxO2yMXOdCEmDscKhWtZBCSpHM5zK1z/Gw64jwKtvewOKWLZi+VR9ojFOStjeouZkrGjREDlkGDX3NTdituTk0OBBMBHHm5mLh7Fhzu7Wfw80yk4hc1WEk77RusJC01ynhxgVvuJW5qzXjg8X+FWg2WaDlR80riAA2NVMFHEx96CQhn+ZR581uN091tgknnqn+n9/9/uN/9i8xlb/3t3/ZY4ohJdo4dcXJ3BN3Mfk4HZgkImaJQCH3bb/50vsfpJhS6N3ICWUuu81+O1xk2KzVYYoSIndRJNDN5fXr+xenfKiooUv7zaBMcRik7xB8JRt2Q7+NAYRY6jxN8zxNY6kOMa+51FI1bbpd2M9zBFzVdcwhwBEDBw4x53oaT6rYDGF7sdsMwU3zrLWW0+kErxeXNyltUCVic9k9/vEffvr8B7c//t3nb356SowURCvqPAFuImaKxE20Eg41J2KAV+adPjQn3uY3X8yrsNbU+OLxF2aif338/3UsTJQ/8yoBcMbiLP6w96w1uK3wA1HkSJ2pm1KpGoXVQkzx809u/83v/PiTn95++xt/4+vf3G6ubihgrvXxzXucpPhkbl0vVxdbVa551BqYYFWDpG7XUUhztvP4Wmu2asfDfeq7/W5zJVKq9hFDB/hoGmJgosjcvX5+nkZ/83J+9ex4f5xSF4dNZJpKHZ99XvtU+x5ffTpvt1Nkf/Hi9fXV9aard2/OU37+6Obx4Ty9enHrDhGY2vk0dV3s+yhhkyKKTmU+zwZRZg4pxj7GFMdhwPF0iolSCiEwyNQMxc5nHad5t9sTaBwnIExTefnqzTjJ06c7ibEP8dFjSkl1msucx2LFPSSKgVJICQkqzMFakGNCi8tMi6x6IFICvLn6NeSm3bkHuvZ6K0lYmHhlIoEYzV8cTkQMh1eHGoFdiSmUuaJCEJuap7m6wtyqV2WbxklLdbVaq8GzanBoVZirauDALGZuxdzBwgLy6l61VGvm4PTOsZxjK2ZaL6mxpGmt56h1NcjcAK9mcG2ppzsrg2CrcKi5uxdrKtBwSOsjknhG03xcEwB4Q9lWULdVP85rmuTwJmnRJu9oIVMs6BY5NWvhNR1dOB4PxhZL/ciMRUX0YaE1Gl3bd1tt0ZTInN3gQm1UntkZTlqqhFB0gmN3Gfte3KtZIab333s6l2MMqbuM5/NcTd1qihtmOp8PHzx5EkWi4HK37Ya6iV0le3zzZDvsTbEd9lHiy+Or0+F4sd+XrH0XE/tRxxQ6YeuiUBTGJOBaMJXqJQ+bOuV6OKkwNuglIHZdCn3NfIarQjUgtxNBDLLf9CO72Tj0cRp1PB1O59NuCClS17OQOebzeJskxj46zZeP+u1FJKZ+K7EnogsEk07Np1dvztM4cSz7TSJS6TjFOOcC1hAp9KkP4Xg83d/Xabbd9qbvBqsMshjSaGW/u9QZ83FyoeL4/vd/+OzTlx9/9Xx9ffH0w5t/+p/9wxefvfrRn/7s2fO7WiwKSyetaay11lphEGEygHiz2YcQjSy7wlwgTLJkQiAjLNYBZm8JCGQQ91i/8d57X//21z74+GbzOA274Sef/OzZyzdvbsfPP30zz4bClQKCElm1ebMJm12qfnInd9KctWYzBUyY3CnP83SaXbyPfb/pqfBZRxYmo5zncZwaL0W67vLiKiId82Tng8/u1RryAHZmBgdD7mM/dBvYeDifUSnFLglRT+P92cbCQ5e4y+cyTjOK19JydVB1r948CPgBMQcRkzG1VmUTJm8MJayIcKtW2GgljTLRAiz4Eslowbb/0m7ZguM/NF4ekGdfQ8f63S/mJn8BnuULDvQWuQa88VXResCrBoa5r0O+C3Vn2RidvCnhttEZW1mhSwOfuEkXrsQqAMCih0dOeOcUq62h5h2oi1dGNLfJwZVDsriXtozdW8PpnS1g0e1yVTOz5ca1fWQByRoZiohoHQNq+8aK5i/Q7PIx8XA5/Z3/+RfyurUEbH1zfsuleGh4r6hW+61ABA7BhOBVK6ENjDCMDAJ1Uvfc+C8VTg5xFoDI3CUyOZybS2CzTgMLtJqpe1psDiiaV29m8Q8YoJ6LsSF4VXLl2DNYiChIiDCac51nVW2MNk5MzgSyCBNDoILMzL6tEl1zqYZaDMzvPb16c3w5lpN0dKpFs3WxG4ZeVe+Od8XPT7eP4TpN45wtRWGiPI/znCPDLG6HdKy11oKAoQ+Xl/s4hEmneRpZPR9ED7qRYSObYTM8e/5cDX262D+6mKZsZ4sX0U9edCYlrdbULKua1dKgZHeCQdWVjJ1TnyiglFzgxN7vY2dkXu9eH7pH+Llf+vKXv/V4pil23TSNU9YgkvZ9p5bvci61S5R2fTd01NjEHUjs4mpzPk+KwgzLfp5PUIcCAYh4ffvS2dS06+Nmv7k/3DnIzk7iFeqAgEIkkUBMu27DzqhsZmHTXV/dpIFBk2nwLBKu6ngO3eB+NlQm96ZwZREk8DPUGm+FmspSQ0zauFSTL4SDtIHmgGDBtJwhzcxu6d8aMYG4+aOaKcDeNLiWinh5ukNgY2JucdCbe6Fb42Y0OiOUiSjCNTs7iBp3wxUO5JJnHREshVByZWynyS1UJi/zPJ1s6NhMyGOfYp6mUljNnGLoNvenWUSkc6865/r6zcEJqb9RtVp1s784Hs4v6/Fyf9r1FNLmnGe7m8/j+e7+/Mt/95vnnO8O46vnJcZBZzNnttjMZZv+E8iYjPyB8tKm/bhBz+6uRlaxYFcsFKjxUpwBA8PZ1ZZhYyPhxeavxVjHAoqRgdBQ72UWhBbQpq1cap1KOGhRSCRrMQ1Qbz47bnC3dU5WzdWZmAWxpWoISaCuS68TTkAwJ5bATaa0lqJqrg2P8MZ/IgjYUN3JiIisbVTmhMjMCp0LkhAoxCF2wWyefUIt4q6ljjO++dHXYYzqMQ45n3Mk86ydyRBC7D55MVGFG0BQQiElgQOubsWFxZxsRQPBK0E2QFqcbgKyIHOutOg3KlxNxfVmvwvQMp3yOWNoRNMQIkXIVEYFRJw7G3Z0db0DMM9ZrRLjzf2J+3nDfd+LmyJyHuly6B/v948ubnZh98mL26S7D7/87V/8xi986+NfdYRXY/0//vX3/vff+p3/5r/9TezQJe63G1R+8+a2ZEUAJxbiGq3USkUX2TyGu1pVAohV/WFzN2EimMMjU4EykxC5YiFCN/aTEz8IVqmiLM9aqw+8/REBms8DYEQsrG6l1kUKnlwEzgp46+g07Ui0uNGeOoYtuX4TZ2kPYNskzEwb27k15sQdTCwEclX1qlaNbZFpaNRmZ0CoGSSKgx0CwKAKq9bsNYq6EBKxsivhaPPGImb8j7/1v836OpfxP/l7/6BGgYg4T1kjx3GaN2nY7FMQmE2JOhZRLwZst5cgr45Ra3GQROmHKElqxjy7WidhLL7rh5/76sefHj6dapGUUKbNsDHm6i7iKULJNaPvuI8ypH7oeJ5mkJ6m+XB3r1pjN4SIEAMkcghRpJjN01RPU5nqJqGyEIIpkYlIT6gppj7GSHy6P2itREZWN1tw1ceXF5h2sVxs5if/yz//5/efzm9+dMYJgeSc55qt3Q51IybzlrRYo+k9pHVfzCDffqlrb3DF3dd+6v+bx1/x3f4aI/urXvmFL/Ju8vnW3vyL19Effh5N29bday0gJxIwuelUSrdJtdRs+MH3Pv/Bb3/+3qP/4df/0Tf//n/0jZv3n4hcl1d/8v57/e3x+Zv757sh5k3e7R6fz17mtjtOihLSZthc0FzjMXcWKOg0nw/35w8+uFLTkrXrQoqUS2FwigPQ1xJ/53e+l0fc3kMzQsJ1GGyOjOyuT55s3tyeS8XhOJZiV48uq/rhcFQtr9OrXPOH3/76fttt+x35c2GMp3G7Bbsnkc0wDEM8jzjqpHVulslq5mypCxTq4f548+iy7weSUm0eUj+e5/lU5rP2ov1uyFUdVBUvnk+5CHFv4KrVmZuwYKnjOFUj6oY+dgSvtZSU4nE+hJ4hBUQiQdUcTtzWZIUslcBD3cdo2lfcBA2xippR42ubtYKHWTrqDMFgVt3UvAJGTQmF2JLHRsNF8+dVA4ETiQGO6XSuJZu7adsPVN2nnOEglq7r4FTzXKsuPXYhbwLxK8GWZalqsOSVS3nkzgBpkzt5YJTDjcyBxNz05Jsos0hsYz+G5URaQWZqUCfixdoazM7mRCQNYWhByt2bRRz5SipurI+lSFuUm7H2Ut7Wka4r6+Kta/dDU6yJuK+FWuOGLV1h8sVEnnwV3VwoG+QWiEBaQRWsBnLmKMOUZ4kOVgR8+PXdcJGNXjsObnPfbw2aYmduIXrJc4hltxmGPuh4utxvrdQhhUf7bbXCBCd+0g03NzfzrJvh4ngc61TrPBnS5e56LjKfxnnUGLc/vr8bYuAgfdgbIdBO55IgyXeVZvidZ1iwGLouDcOwy9FyOaPMZEokouQV7PN2oOefPY8oxLgc0jxrErDbdpMoeqHSxUgkRsTBKVSPZ0kUYggdS0Q/JEo2lePtq+Phfrq+7DZ9r7XM01RtTtfbYZuKjsq+6RPOdTqU+1e1lMDFtv1NrQof3eaLG0HlY64Fgkm48usX4/3dYZpO7z+9Otw8+viXv3r1Jbl8X579+NWzT16/fjnqqNGKK3UD3U81dTFI1OKu7iIehCgGVS0GeFU4E5iNrVphGEfmEMiKzTOT9APPaf7oI/zaP/jyV77+gUS5O5xenm7/4Pt/MJ7pdNBXh5ELE4dGj+k2Yb/ru62GwVKvIWUAc81jycVUDbPN9c2sqh7M4dNxDBfDsOmG0M021erllC/ShbtHCV2MVtHxUIJ3IWuGJSq5etO8rkAyRGRUn8dc89XV9TROx+MpSAwcUkpGstkOJHS4P+W5LH1fgxvQ2AVEBDdXdl7c6jnCSE3X9ggxvZ01a+gPkxAthG5yRyByMVQ0wndrwHvj+qOVju/uWe9wq9Z81RcgUcDr/tVCTF2+T6DFe69Rh1bBcm+DFw0Td1r8zd66OxCtSTAUDyj1QwuX2HVlMi1K5+QOCStnswmIw925QgE4OYNWNH3BuB4AbhB4VTF+eJHQAj9anG8oDdyVIA09snUfcH6gebRfXmrLalhkIGiFo3yRgGmEOIbNFQ+jg8uVbqR+NnOr2hheJrySqt4CUmYPZmLt1LxZH5gqC7fhWlVvH7DxG7CG28AMbyK7zu6GNqUQwOROVs2Luy1E21bLmTUJA9LFgathewJzZVqZcOSO4hyblQaEUQRwYWEmZ69jgcCDmSrVWiqRMDfLNRBNgsykCgIFMBEHImEXMjYGnevJxWJk6YBsUCTGZt8P193h5W2ZYeSbXay5HO/nY5hRgQoI4lc2HqQEsjpGidUs5wyD2qQWu11nZCWXrutiRxLgrq6VyTvp7j5/3VF/cXExyHbX707DWUsA6OrRzTTm29NrF0p7qaeaq4JAnJbLzQ/e7/AFkWUnNoa7qqDvg0LNqwjcKl/j/a/e7J52OY63928g6LqBhJqMPYuADqdjZpIYHSjENmxSLjCvwyaos6Ru66Tm5TzXzPOkrb1zON8SOwmqFxKiGIMEiDgyERm5krGQCACK1MFhRadpOqdz/zS9/+WbN59NLz7LcGaPrh2MW+vLlxUEIBASkLE4jS3ScO+29pYHfF3maBt229qXyCK0LKG2KOxhvJfaY8dwI2iTE3pwQFhzsjXdcCJ+V2Lb1XUR4oAQjM3ayRncx3yGGBghCkjI03gumnLfxVzscMJ2o7qlqhSE86xjV1ukmouW80zkxZiZc6mNjElE5oSAEIM71epv7g61pIsdOWEux9vDbZ1/+A//zle+/p2vnA706s0Pio7d9iqfzKqHKM4OKyzmVBccydaI5wIImMXVXbVhRy0xEiJha63HNtS8SChUXzIkB6PMtS3XpfuxXsJ3uJ8PMX4N+etNaUG23RIzMujy7SbRbsYuoCW1VW+C24sOrHtjw8DK6mNHBrgQqVfAVSvqYtdDxrSoebAZiilVZ1YYYNRM6pyDztBQ+xStap6rdNEQUMlQInkARPDo6ubw6lhrDSGejnWygiCF61SnTX+BCUuDhAhAbVgniIzIrOXIS7eU16vGaAMCK4HWncmZFQBVAGpe1cls36WeKbiTVwwIEhNtmMk5V5kNFgZPm9DvpNuKVsulllxA1nUTIHkeAwUhXG13M0r0Gs0xlvtn9/WIj59++1d+4VcfXb9fdbiQx58efvRbv/v7/+K3fxtbpBRd/KxHYhRD7GNKnVa4qbvCteGby/22WrxKg958IVzxonJrUF0G+ZiIw0qLW9MKd3JnJwGsmCtW21UYDEZkYIILnMio6bSQkatXXzVqCWhdw7Wr5CuBmJyIhKgJdQLizB4eOnJE7AQ3XXIUX2R08TCjbubqXhzVSdEmatUNcGMCE5mxgeGB4E5irG61ap6ri0vfHaY81YIo/TYdxxGCrz19Uhy/+d//s/3F5S98/G2+3gYFudzEi8S5qhGLqTKFJB2BYKrmZlQJyqgiRh1Ty7tcnRhc5hy7yOpD7Ieb/vnxWQppu93A5qGXw3ksVikgSIzCAegS7YbuYjP0Qwvd6kkAACAASURBVIrMSj7ncppmItr1fYihi6kbNqHrXGs1q1pNrVQVwFFr8ZxVKw/dwFxjJJCZFsvVVVOUR+/tNxucX2PPO8Z1OQ53L+Yf/+s3vW9D7REc1aoVWozuFy2kJgfz4CCJ9eYuseOLx9u25f+3x18jU3/V4y+eufhzzee3LBhgZVSvrdy/9KCFaeLVC7wsbyHgoONUU2QOVK70u//qB6rlw4+/ev3oK5dpm6/KZJ+/vn3FJLvNRpWfPn16uLP7+zwVO8ByMa8QZw/dsL9GGKdpksjmd8IGnZ0yUTJPBnezUj3P9Xgsnz1HWhxTQIyCHKCblBiy329O41kN96dTrnWz2292WyvlcLqfcqg6n8d7gqTk+x3OJwRBShwjCzeStwWhrusQnZ1r1XnOxUqIHLuUaxYJfb9xzJZLDOlUZ5vMClwpSGImQzwaaqac9XTM1dm81DKbxGmq86TzrBSoukdQYAIrC03Hk8uyg1Kjpy+aFe6qJLF1JpY6jcydFk2CBzcN8rfUgvV+MweBsJOp1qqmxBVwCizRg7iYWhND9aYpor5S71VRmZ2FA1nzq2uD+QZyM2Es2wjghMWsq3WpxAFQbTToRrcH1oDSztbWvlrAMrjneOversQKmLdGKjsJE8zVXGFNQ8fJG0jF0qqk6tqUArRbC0YQkS+j861T9aD78m5wobf/XJT/VgyrRbp3iaUPrxOwimysGFd72defcV4nfh64GSAwmIycCxRe3K04KGz2ropQhiGGPv/SL3/8+L3odsj1cDofhqHj7eU4nabprHUeegqhv9j2/bbvJWyGvnK2msS25tVc3X1L3BtKrZGZgMCipU6lXOye9Knbbnw7FAm9ZhgqLKYUgoSL3TUULOhlqIE6uVM0GpmIdBKimFIk6kzgquauux5DT1FM50O/ZTClTXdXNRhqnmKHFCAcui52XQSD2buefvbsJQAOEqdIRF0/xE5dxmnKc0bVSlMepzEKRQnuTs2UlyqHrhaDkhAUwSqlTQpB3Uue7gmcdULEhnshKTqPxywdvZK76sfnr38sQ/nWR9/45je/+m9//09+/OyT8zPAyhwAxzZi/4hr0XyaAIHwmDPyzGhuKfACZ0IK1DP1IoGcaq0jimEyVNVNOSX8+q+/9+VvDY++mkp69fJ4fH17Gic8v71D7edMkUXJXKu7owtpm4aLQGECl36IMRmzqHZdZ6dgxX2eZzhQgQh0qFSlI4jFLs5nT4LgvE9bGDk7zI+3Z8pURo1IfRemu9dWMx6CggGC0eZxzKraD5uQQtfF8/2pcHx09Xi73TLw+tWb090dKCzCDa1K5NZk9Cb6tajJAjBqoyYPS8TWNbWurgdnPms6uWDygOWsFGQPPU53B7XBxHW1SXt9Xbhka7GzFE4PqfDac2mLjZlpZVOgTfM1CyuQN9KAk9Lin92sxWRZwg/rHGvl1ZDopttuTayY1iuy1KxvSUurNruZNzEt0odWUGvfLnpVbZqFCLpaR5i7N3jrLdrfcml390bvXEgIrWmxzCwvp7wm95BWdi+BbuG1rZpfvv5peoh8C3bvq/hXG6eFwaX5r32BRUtMpubu5sZ4C2+5mRKInEV8zTCW83znCIJQmyaNNxiBmVmEwVAtuWQ4QhAnLPZQtWYoAoxUkrT9hgOTgyBQs1obF7mp2gEgoiDEEkg4hEAiRLh7cwvAzWutNVfME2KIKTGzw71krbUhbW5QVhQyAYSNLGxFnCmEfhNiH7ZwnXMAb3ZbZrne35i+7uLQcUdxDpdycXHVpyFwSF0a82ETI/cSEZ1xGs/kcIGSKmoMcdgPO9nFyKXM0zSGEGKIG+6Dpa99+Wv7YZekP92eyrl6lvE0bvr+0ZNLzfX289f1rCERRRIDO7urZiWRNAzZRm+j6iGwiMREkUAotcYuhq67P9y6KhJ2+/CL3/p4f7Wbtfz0s08q5k8+/+lmG0MKIUiSkHNxYLNJal51zudJgoROOEp7nPttYOKQ+sChT/u714e7u9tSqwS6uNwRWc75PJfxPHchCQsBFIN5JbiA2OFKxZwpkFsp+Xw6BrB885u/9Ms/L4f9v/zku+Batbhw1brAsAvS0aBxYyF3WnwS2rP3dlUuLy6JMq2EwjUjlnUt0Lv5k2GRI+J1s1dDe8LcwE3BB5UVTnBtlqDSADBuOjnqYFNzB7MAvNjHMUFhrFBtvF1qvLNiWbOhpBjNMGeUrGauZqaatfI05lzUai2ZzOZ5PI1z7KKC+57BncNUFeBpOhscZKfTqUwnUxoGI8pW5zzhzeH2az/3dbHrn33+6vOfvgnJ86m4wSBCxMJwdmaDsTkJmgGhE8GNhBVLNwNMTE2dqeV6pCtw6OQGWpw9yLnZt+maBTIBCA2yWKaXvflWEyNIAJE3mNwWvm4bmXNaR9BbgzTyw/1qbUpqAE81gy+2c1hHFt6J7bBFkt/dmpAeFGi+HGYEIrATjL3O4LgAG2reYNmZyqzZAmIXVK3oKdccEg3RJUhi6oTZ5uuLq/uXBxgEYTrn6TxfXF8FxGmcNj1hBsWmVkggcyU1Z3chCRxqrViHWoGH3NTbbKQ5mMAsxMGYIW6NJcgIBFJsUr+JXSQeQhhCTjF0XdcoRdvNjkLd7rrrR/th6FII03Qus7RL/ej9D5htOh/y6RyJh/3NxcVm1+0ebR/33N/s3//Wl779nZ/7pS/dfBQw/F/f+/3vfu9PfvM3/7t/89s/QABfSVNhYERiT1IblKtFVZWZYwhGasXf8UZatoJ2/9puYVWZUGtVbZA0+Wojgtbw0SVNd4c5VJurDNDoxq3/5IuOiTAxmBzNFrMJQbQHb4kDzgtFuJHwOLAQM4xcSFqlxdaY+bQ2sBpSxev22Z4qYg/MomptbtR0FWd55z/3NhPamtzu/ICrk7paVhoCEU15jCHwZpjmiSo++LnH10+uXt3effLJJ//lf/1f/cav/sZ/8U/+81/5zq+IxU9uP4tIV1dXeZ4ADVG4adx7cNNSavaKyByTROq7OE+n4/EeRinGPiRhJkcKMUYR84vN1ryc7l+9ev38J5+8yobrxzdPkEPX/fy3Pkpd2G6HrhP3Ms2mqGDEKCtxnVJKw9Azy1yKOih0MVJg6rpXVGku83gGEe8vr3e7C4lOyKgaOw4U+5R0KlOhx/sPrvonb17qv/6t3/tX//OP8QKTnISTKLRWMgQRkejtnlrrqNlbev5fH/9eH/6g9EF/Lry/cyxp99pT/vOPhjkxoVaPkYXCD7//yQ+/+8l3//j//sf/5O/+7b/7zb/zH35jLz0e4d99Vu6Or7TIPNfTeP7k82d3x/PB82nKDvTDNna9OUuIl9dX+4v91fX+eP+qVCUnMzUrEmLJPk/n29fl+fMjRvjAXeImO6CqRGGz2/Zd6vu0u799+aJ8+tmzq5v49Es3adORh3nSLqVt2tzd3apj2KcPP/rgT/74+X4vMcbYRSeb8ugszNjstkmiZbu7O+Zccs4hdF2XqpWuS13q5jxrsVJKLTpNMzkCC0GGbqeeNBc3zJO9eH63uyjdJuR54k5LreZ18XAyA3mMnEKKlmatpRS0Lho/eHrBFo7pw5CdvXPx2zShuYJksSD0tdjDMtDB5opmqebmVhuH25mJ3VDnWswsxghnCaRr57CowpBzVlVz8ybltFSAjmaeDAUxB+G1neZNx1cE3LoexC3xWeso83UQcq1/FU7UBNXXCdfW2191f3lxZ3erhpY/1JaOgpnZAV2GedxgZklagri0SVgc7liH6819kUFGeId9sBwP2i7+tipcDUvc3e2hSn1nKWEB8UjwUA62by1+hgs1rm177kZgW5IwoCp8zpJtmpmNWbY9fvVXfvXmRqbphc3l2bPPHz++ubjcvLo/390/n6t9+Pi93XZ3fbnturR//0m5G00VQOo6ka6USdVjDG5WSjH1ICHEUIFxKreHe5atw4Yhdf2QIsww5zGXcbfvLi8+6PqdWXXGlGuXUA0SNCYPUVmUg0r0ENSVq2UgP35y9fRL1xw8RcQYjSimXt2H4Vyqu8+cMgVwmJySKdUKtxwjtCJS2nbb1A1BEkXlsI2Xc8+nbdylGPeba3JzcjIrU65GJGyZy8zMYRhckqY0dkMkHiRE024+l5pLSGNgrVmnecSkaqCIauqGwH/8h9/9o29+9Iu/9iu//p/+43/64tOXP/n+T3/vX/3Bj374k9c/zYU9dJz2fH8aA4uAAbQIQ4rolw5SLk4zc5XE1DtijREXF/LRRx9+42sfffjl90a9f3X6/Ec//sk5n8/T+OYu397hzT1gEzJQAIMk5hS7fX/1eLfZ4TzfgyCRJIau64fNBnQ6ne4O9yMyto+25/tzF+P2Zps28erm8vXdq/v7e2aKFL0gnws5He+Ph/tRz8AMTICjj93V1VXOhRKFGI0VDO981FOZK4HevH59c31zc/34andzPp1fv3n9/OULdnQhPfnw/RefvKRmOt26v23x67pyW/BpK5dkWQkrH6etXKwtk4Wt0yhEQKPgi7DBWWDqrVBsusyNJ7RuPW878e++4fqesDZB/HavWtCr9V9teo3ehVDM3E3djY2XObsWU5vD2Dol+DAR+JZ8pA1voTZbBlAbTnAsLhDLabRhZEDWpFjw9gTanutLaPC3ONND5HAnoFYjamp+b8PJg8kpGx5kxIDFRxxL9Gw23yulq82nLNGIGmGUiWEuEr4YwZZruigs89KDNneglZ9LO2JF6+D6FitYUM6/JHlcr0BQ1SWO+wI7wajNUZuqFXNy5tbiFmtsL3OogTyFtJY4cDNnUONEMAzItQrcyYnJyYhF2u4pDkII7N60FVdczbTYvHJoHLaqghGsAmpUycWtqSAHJ/bqBq0phrgZ+tAxk4h8+LWvv394vxSF4e72/vXr289fPHcDM0uU65tdGqKRswVJYh3cUU0NOuZzsSghbPttqXnMJ1LqQ4qWfIKp/Zvf/d7No0eBZDzPBFSvtZpgmqZps+m//NUvHV7cH94c3cCxAVhQsAOU3D0sNDwJHCPHQAHGysIQO52Pfta0T5ub2G/D9nI/6Xh4cT/pYXexSbEnsLgk7rf9sO0wxvM4H9WMK9XqajrNxxijWZMoVCKBABwvrz5wV4pNmdJ3u6HW3J2Cecl5ZmIQ933oO3eCSBhSYqJScillHkvrRwXmPN1N4+H9p09vPyxIQLVqM1H06h6oDS4T2vy/EZSJDQ7SB6vOtm6XtKU9oGZYNPtWDSEA5sxvVeLaw+pYertEvAhp+YJZN5dlcFO7QVkQZgOaFaMsAnMPnI6FJ0SANK/oJeF2Yw7Vs1fkueY551mtA0hatb/f8mbTg7hWCwzmIBJKncbpXGu9uthOZZpqNiaKcdjtzKVardDQYcqzwRW1ZKqoQSAxDH2MUYaen714aeVic3nxN//mL/5h+OGP/vATKFMaGtqmpgAxmLkNFLI0Ywe3RkGzxlgRYQaxALpoeynA6zVfW+QAqCkgMiNg5eJj7fa9c9XfRpLl11pOaLau+RVlbEgW6Atlibs1t4LWA2gFLTlJ2w/aGYi7a6OjsggvqFD7QYe6GsjA5Is4vLd2DRbT6CV0AEpgQrbzafbgqZNChRFIWNw3XX+z38k1CaR5/ymslmLmgVNAQGUrjqYrTK1NgNY0oEVgnYtVomUaf21nrC2J1lIiYibDSqwlMPO2k10KAggRu5OaqIcGCnlxcmFPfRo2w+X15upqFwKXObt7CCzcCdM2JmaPybwWzbMUThK3vLnsL6+21199/+Ori8dX+0fnMVcuv/f73/3d3/vuz37y+c2HV9TR3eHUtEiacoGD1XTOI5yCSAxBq1q15QOsPYyVVocFoXKYmQLaXBIb6Vitpc5AIy+CGmLVOGz+8FzQKn/mrbEOJiYhklbEGika7oRFqw5mbm1EA26tR1cBgTnYXBa+tz9wtWHW5ouBtV21Tl40SrMTDGbw4l4XEvsCmsMXmLVFlGWdLI1ud2MId2xWq5aYEsghwF29+sr1ex88NSsv37y8uNpirP/yt/7Xx/unu+3VN77yre3VPlhUq03tpFQN3MwBApMTChMTB+ZEjFzv78/34+GcJFzHqy51BDer4k7mieXR7jJFOp2u7ifrX6MTXF31lxcbCuHLX3pStJQyTeNpms81T9KlzaYn91LydJ5KKcPQq1vNepqmWjXGmFJU4sv91VTcba55MvjQY7eVmFwraSFJXeQQJG3kupfdhq9f//T4p999+dPvfy4jbCDMpGNVQySO4gAtyPZSN647918f//4eb3PxdzCsvxC8+nOlfdu4/+wrdVYm0WpzqTGF1KWc8nhr//Z3f5Kn8pWvPr14JOyX719/ret2d+dbM8wln8fT/eFUI5eMuWKcTiFllhBSt91vhz7u98M43pZawYFFSq7DZs9Eda7H4/F4jziA2gQZIUWEIE1NiYTNfdjthvMbBU7jOJc5dKlPJKn1ve10vq9qjx99cPPooh9e9pvoZiBV92mai1qX4mbbd93GpZ7PBXTUCkcNlYdhw0w5z/eHw+FwL3FnVpnBRFFizR5DKCPGo6KKFj0dcggh9Wym/bAh9mpeHSYu7EQco3TcxRpmuGlBc15fm91EaOoxpuWdMqdt8wsDvro3Mv2CSK4VyFJw+FIXtZZDE3xA2yBc4aSezdyrB2EKJByUdOkQAMV0haa0ttkZXhi2bZdgAjGLrFMtTLxIIIOapt4qRmmt+b2KSb1b8S0k/gcCwYKWNh+l9XG1NsG1KvK1a7C06Jcpp2bN3rzNVp6ve+P0L1XQA8diAZX+zCHCf+YVc6cG+TnM2W0ptd9ZJG8XkAMPfC1dMg4iIlnmYdom5U1pst0+B9y5zjNULedpdEoY+qHkY4zh8vIyfCJvXrwScpgHTt1gV5vd5eVFH2MtOTHdj2dXr7UKe4yRuM+lGKjJTwQJzT1MzccMu79n5Fo4Z5Y43VxjOmO+hxWYzjFOEs2ZxnE2P5IgBUj0vrOYKkkhLcTZaTYArOjx3gdXT5/eMFnsAwdStWolhHh9sy2Vx7nODmOYaymN0gSW8zyiFGgYo4iQOCtyBWstWeeKoGrETRGNlVCcVdiITGuZZ2dAOupJOc6SCmOjJW22myha6+2cT1N+UzMBTj2FjkIAM8B2vJNax++N/+54qB9/+MmTqyf7xxd/5x/+rV/5tb9Rqn7/j/7002eff/qzT/yAUhRJwatSa4De3aIDemCH3WV/8WhIA2Kw3S5dXnRXFwOG21fn8TSWN4fTaZyMOKT9/tKk809/druQmAIQkIYwbPvhsu+24OTJQ7Y6l5xK4th3gTiEmEIaohGJc2dhGPrd1VYChy4KBzLsdxdkOB/Oh+ORQHksNoFmoAAVbjDyw5sDBEPahChTLTlnZoaR1ppSLHOFcYrxcDrmOQ/dIMzjcTodj3VSYiEDWlecm35eI/e46TJ8xrSOsD2QptYFvNIel4XhakuhyGzVWoRiYjcndtOliw9yNTX6wk5D7+BW78LHS9+SFv7Xu7vbu3/9gSK0/MyC7CyAMpZOAaBLNtqm+hrOQ2ByNxgZLfqsK22DaBWzclddUL2V09Si10oT8fUirG1aXxN3B/iLey1R44UBDHWXh0+0Jmm+hh93p2WW+t2CHQzCOgvdwjLJEkb9oUIARORt8vcAeLV3fXgvWqoLbxphK/MuxNhmBn2dIlwr0pac+/Lryxfrlw44gmZdiWUEc6h7tbbeTc3qqpomBEJgUXL1RitBkNAKUKMmKu1MjoAGQ6qZVluANAaJuoibt6miLnZmWht6iRWSqLaMH9B6xrzCtY2ep3BS4iApcECxnKdaLQxp457yuQYxVA6azrdHy1bvvbyoeaotaqQYn7142e0TJeYe+5vd/nLXdWnM46mcs9Yx1w5BlExrRd7GbfBoRz+/msqx1E/5xZu7XGZUwBGuiVhqgVW73O/f/+D9/Wb3mf3scDybotRKbajCrVimLjQKMwQeHdFNzFmZUFxdZ/S4eLL/4GuPSz0/e/NsymeOJEGmOafYm9apVNTScd/FyGC1CvKul9TFnKtDS1VrstMOM+R6DlHG+ar6OXbuTvOcq47mc9+LcJdz0VpzxnaQoQtOVVj6lNxQppJHPd6PfQzb1G+v+3k83d+/enLxZH8T949wyrAyLeHGBRzgeU0a1GGBiVp5ulIkViRleTTbUBsW17aFh7HEEF+Eu5vi00KIWFF74IH/ssg1L1GCmcjNatOPdYAYEry5w5EQSdPmJne4EZoqfgNZDOQkwlWBGWUsZa6mEArEXKsR+PL64uLyShhWihJJiBLjYotrTiFwDFprcaNaum5wo2JFQtzv+xcvz04w0vNZvZY+dsIpRlct6v7i1etX/w97b9ZrWZKdh60hIvZwpjvlWFmVXROb3eymSZE0YckyDIMGJAGG9aKf4Af/G78K8INs6Em2YMMPMmALNmjKtDmKapKieqyuqqyqHO+9Z9pDRKy1/BB7n5vVTfgHUL0zUZl1781zzh5ixVrf+tb3vRo/evoffPTNp877n/7gCyBygKCaJVvODnHSwwPCIpZdEBazbLkIVwETcMFOSmAHmUSs3w5RNIk7MCGxcwgwD3/abCCrRrO9ZIkbRY+wNA8nYuld9IQpKaS7IFh+mYGaohZMobyWIYCoOFdOiLhsYFpMoLl0WgopdQqXMkctKjrcM1SEPIVKRJjUxUHFUmcQoK648nXFkIZRh3xWtw/u3X/nwePj7shASWyMoykEX4MiKbWuSUMCA0YEYCwcYJ1gQizOSWVjMiMgBZymFiY4Bbg8w4Q2y/4wUQjcNmHZVI2aA0AxZ8AGHgAYIkYgpMCh8c3St6uWA5ukGIeURjMhQAecjn3bhJVvXGiV41V7sQjtk/vvfvDuR+ere5v2alOdIfhPv3zx//zpn/zT/+5/3KXbJMSOh93oQzAwnajNuTSZPVHOklMCKf6hhify8tulwNQGn7rdakVrH2BemyrGZKAIRW/dDLXcdHsr2SYAzOUjKAABTaRuVNNSL5SsrhQACmULQJiriFO/GqjMkpSXKIipqsoJMSsI4vwIT1DalAAIaDLNBnkCPXE+V5vPVNXU3toaAUCBPYPH2I9Jkq981jwejrCC9z7+hkA87Lp9PyK6mFIe4P/943/dVKv/5O/E3/zW38oyVkieEAFzEgPw3pWFVlfLQKRMiqaQP3n+qeZIBuQoWx5zz2CO0CmmYThrl77lJrLgo31unfe+rtdn582yGXNSE5Q8jt3huBWJwTvnp1JKJHfDkTmcg6Wchn7cH46StTFMCqOk5XLRKNUht/UYsyxb510iEKTEzhy4wMFhVck65PXtm/T5D25/9CevXv50XLnl7fGIESCZZx+YzbKIZtG5x2lzPffXohm/OP5GHaeks0ARBqeMFaAgJD9X2E+r8ueeDo1WNcF5GIcxj7mq68a3ty/iH9x+/7OfPnv63qNf/c2nT95/uFgufL0IzeJ6fxOCW60Xo9FuGLzjlFLfgfUJMBn1AHh+ubh067ZdIqH33rO7vdlVVVNVPvVjjG8QoalpGCwlrSrXtlW9YADd7g9ZMjEul+2FRcLULCtfB+eJPNpox26/3W3Xl5sh90Magg8XV1UWNcsCiQCz5TgmMWHPdciEQI6IWQ0kCUD/+MlDZhy7fr/bHTs5OzfveLloEKnyvh8ygWxv4+31cDzo2AMApCgm5hnrisE4Zo2CyVRVTA3RMbMzBsyI6Cb9EJx9zsyMEUEnYvYEXcEMSp3afKcujZmplM44mJiYsC+3uBDc0VzRhwFFdd43bpFzTjEqAXJRDbDJYsbg7OxMQUTzGMcxjsVczMrk5skOCq1wfGfhh6J2AKiTI5DNMyl6KiO/9mzZqTY7UQVsVn8vX1JVEy05/NtAqhYpyLn7MgtP4FzSKUIRZVZCEDAtsNJ0heFtNbj5ZBS//vRjUSJDLBlNGbsv9vBfOwUtGxlNdIjTTFXJ70ola6fLBUyIXOYcUZBBlQjMcuv50T1w6DRLE8L9q3u3jx6/fv2CDe+dX9y72NS1d2SNcyAy7Hd7LsCCSpFzZqx8RY6Z2KwI0FOWvD8Mu2PqEqBXNBm6fNgP+0P3+PHFYT9W9VEE2haqaswmisi59z75ChxDqLFqzAdBisiJaSAWQeAa6hquHq7OLpdGXaiCkYBaShGRN2etmd/tj9uhVwTneJJmEwGAq7N2GBKhec6S9lEEydqmbqp6XbVt0wxDf9htxSIH8AhcWVWzrxwRvRl6R8xVZm9GfZJg5sfcAgdfh3Y19pH3AxgYVey8Q4IsIqJM+PmubxG0zs/gZc5wvOoWdb1ZLS7ubc4vLvwKPxyf9sdY08KxZ4dZ4tD3MY2as2bLmpPlREkoZZeNBDk5BgIdx37/ei8RD92QTJvWV4vAgcED1Xh+OdbVonJt5QIiio6ZonAcc28OXE2gLCD7Yx8FKrYhGnq3Ols6ql59+tzVgRtKEI99xgrVdLM5P1tvcp+O191wHMic9ArjNIomCpAgp5S9BeLgQ6jr1Kck4tRyFlMjIO98Sqk/djnlqcOsANlAMJuc1kFZEYWjAGRmWpRlS1MdANXobWIUAEjOU3o9TeDNaRvCJGJsOvlHEaoKMCEis2MyIKO57WzzlPIkTHHCROYPhoD2dl9lRtfNTKePV76sE7pOqKcyyebxX0IEVJEZTTcoFagRMaoCAhWmlM369CfyQKlvVOPPpE9TKDTAGa7CUoSBzRStkifDnRXWBCD9TJvoDvaaIr9NlTgaFM+9u4BHSDareE1FH4ACFQBrgs2mF72r7eH05ncwGUztD3v7JxQmUwofwttx8pQ92pSQT9jg6eGZUDkzAHAqykWYCllAwMCyZstgllVICcDUFNmcJyZmsmgqBkUCUa3QiYuVEyhM7fTp+hecuLAzEJQMUIpU8NItMJNN6r5qhFYgCUEAQ56IvsQAzWQKKQAAIABJREFU3tAxsCmhoppBVVXKimzBOSMysCF2w/HI5gNVP/yrH4378eb1AToAAE+hdUtEGIcYbyMgxKEHBlqAD6E9a6liZclOUDCnJCRRxipwxU2QIEfpXo6Hlx105NHBkUyMKo79gMlnkNQf+sOx3x8ePXgYmnD15N7i0G9vt8frEUgpAChIzty4iVHGYgzqxMiMxEyM0vnVWdPWq7Nls64sxq++/FwVzi/Oq7bJMRKDCaRRjl2PibRpBCSNWQ0WS9tsVuOY9ocORJHMkTOmnFQ1E1o/bFUTO1LRGA9DTzkPPlhdhZwYjI7Hw7L164VPKqDoCKVIMwsc970Gd3H/7N7Ver+77rr9MBzqNXzj6fkPdrdjTKgefQUGiAHAzJKZmWUzDD6cTGMAgJkRUFQK3cNOwK+KoREwotHkeXoSMTAwtUKwMpwGi075Mc7pMmHxsyAGIAKFCYEvba4pJQGGgkNgGf4VQRQFZZAiEYoGmFOJA4BGhM6hQ1YFGceRwNqq8VVFZmMuVwgELKlmM+d4TCMwgnoxzTE6H7ICIjV12JyvXlx3DpkZhpglWlYlH9ChpJzGdNzfeEy3h+t7F9X733z89FdW118N++vkiFQF0BTx7XaenuAlNZg0jMzAMhgZAioyIWNxAMVJP2yOmQDFMYcKO+oUwk8NQHwLPgYAhGyTdcgU+RgAoPQzpxQNT3F/SoANAEzNCGSaNSvJYPE9FFIq+eGknKNU9iegmXeqU2apE2pZEApTYAQwQmScAu2MmZ24uwqS1aGrkIZ0HBOA4nq5evL48e2LN1UIw3E47vcE2IQm9tGyLarl9S4CABvlbKSk5VMbTntpaQ7PeaOVAXMGQGCi4idamFdgxQhYicA5Ct7VwT9Yb4J3nqit6tr51qtbLnrvBbWqsG5dqJ3zZJZFRpOEmlFyTjrG3GwWjqwObhEaH/iX3v34YnXx8PLxOw/eq3lFFizhp88+/+f/4l/8s//lf/jqJ/ne0yU67ca+rttRMwCWmGpz+cLBGUBKmlKCmTg2Z8JzT32qerDIxU0tb9V5PL00YU2hwEwIandAMKBOyvwl1T4BxCUbn+ZIDaZBj7K1IU+8qJyBzMpAIE6hACY9eJh5z3Tqa5Tn8q79jYgmBAUtAyBAEzABS1YqlmkRWCFfzvuUms4UsZJGlM6+FTI3o2BGNUUFZ/cePQSG16/fHA87ZHq5Pa4Ctevmk9ef9L/b3x73j99579y3VWgA0RAYPYCogIFjIhdYAXuNh25/GG5fXr9ctNWiXhhDnzo4SF25pg39AXbX1x4RVCSOTc3kGoWL5WrdLtfI3A3D5198bmBxPI7jkRjYe2Ycx2F7u+v7MSZoGsxm/RgP3bDd780wqYLB7nA8v9r4UJ9vlpvVaohjToPpaJbQlAzI1DEv3LKxi3Tjv/f7f/rpD1599QPwAlQj7MzAHDo2gsluUucR0FOSURbnLzCsv7HHqUd91ziFn50fvINCTg+HwZyG20yiLj+l7IIqEBK7kHOMowYM3lXdjXwmx//1f/69V6+f/93f+c6TD89bf+4adxy7zdlSYODK9HUdlMwOMXVRDQxShpevb9QigJydtcZ50TSBq922897X1fJwQ8MIzgNjQKJKsap9u/C+MpF07A7aqdp4cfk+81q1V9AsMsoAmbJGAYHiPES03d80dXPv4dmnnz5jCkDiQuUDx5SS5DGlru+55D8lExZIGc7P14g2pt40Bw/LdgGqIycErutqt+/QZHvT3V4fjlvJCk0LhMiEoW4QM7MQK6KAqWpSYRERSFncnBMoTOaxpc9EUHZgLlOEeOrwT1u+zS1IRCKaBulmYiogaAbJc4GCWrpWZQhEUX3lVqtViun2+iZq5lI6lJdnAIJ6UQFYliQgo4wAM4REMFltTMLvCgBExESmMx8iTx0kBROVkiGc1Jnv2i6nOnk6O7x79gigEHxFTRR0JhsbQDFQNrXJBRAnZApgnteZgpmpIIDQnOOQzUMwPzc4iyCqd4/8aYHMHvB0x1hEKSyU09mcytqZ4mVTVYXIMwAGhmW1oDFz2SxNCdWcg6QiaO/cv/gP/9bHy9B28Salo+R4/+pqs2ydp+DJe27a8MPv/6UjCx4hpfF4RKqLlXyWRARVVZW6XUSSZAEQ0WHIWQAYKLQ5Sj/Idp8I0rd/+Xy5qq7u1QBCkNcrvD0cRS1UtlxjVgCGqiIfkBmMcgCpGmsEnIEsYHMGZ1dNvWCx6EMYcu9csEIDQE/sYnbJGkX0vmJ2gVKkVPJIT+W5lBijiDqGhuvNqmJ2wbudQHKZPXElxEYVLFoLLaGh94CG7Ig9JUnD2OeEacgA4qnyDS02VR+PGhjBi0jOVmwFwKBtWhTYj2l4eXPYD6/fvA4Bz8/a1Xp1vjm/vLo8u2oveXl176ppKudhGLrt9s1uvxtHaWvfDzpmiupjwm0vh2Pa3u5jnyRFVswRusNohlXTePCkHEeNWZKgX1uoaLGol+3SMffH7WFMcRxS7kE5eO+ARTSLyBBHOI4jZkVyzjnnGu/ZQQVR4zF2K22rqqq8t2zDcYjHMR0BJVNEFkelNV2YI0QwSzwpSNIMpmYoKgCggm3djP3Q7wfIICJdzJLiZJWevzYw/nWgd4ouU9Hxs3gLGABkMTY1IC5qqzPSM+WnGSZlVitLBgjRMbvgPA3Sn+omvKtPZgLRiWAB05TwVE4UsmrOpT9T1ubEEipxAspw4jwL8taqnwd6JkgLAVSAEYsBLxmoAWqJMkUeWqak9KTGrvO2OV8qw0kDBspQzYn7ajD7O0wNWdOCOJ1qKAMD4vJv7u6Bmc1SggUmNzNwRFr08yc4jxARcqmxzGaWEZTPP9+7EhsJT6Va4SxM5VIZTiQGmPhWp5ygNL0A5rEJm6r74reIqnm+13e5Q5kFBAAEFTBTcKBaIHZEJCMxMYVZMkQL7U2zoBIgErCBoUnh9Y5DNFCj2ZxrTleN5itP8ywoAbrSgMLJqHYulwryZ4hWRk9EAQCJmBjAyCN6Mw/gGNmAQJ3GGFMfrdLlpq7rakhDTAkyXK02y7B+9qMv0yH7gSGRquWYjIwrX7m68jV7ANY+D+mYU5eKvjQyBgoe3ZCHnAUYfPBO0A18PI7ddQ8Ht3abeIjjmKpQN+vFbf9GRzAUCKBi290eAR8+fPj46Ttj16ef5uP1CAhcAxikAbAqqslmYMoERMYqqDAAeHj83tX51UWW9Gb7kgK0i7brxn7I1QKWq7Wk7AINMPT7Y+oEmHwdAsMQoXbV+dn50I/DMSIqew6h8d7HpDknHzjno5qScRrTcZcYbtKodV1VFbWNb+rFdqtt65arehjSOIrmEqOzGRwPSULih/Xl5T3HuLt5E9NQL5r7j64++fFu7ITF0INmQHQGCYAnRPIExk7pADIzlDJu+qrBDDogKSBNZsOFPaXzIrOCXxkYkxbIqtgW2pyQmYniLM5Znn/DCbkqzxhZoWJQEVIooDWqmWDxwgApo7kgw1j0t5wL3lXeeSAbtE9JVHPlRgNi7ygl05xEKMmYJBtUlR/SQMRIpJpzAgFRBWYNTb1Ecu6FA3KefRDMIGpmyBx83fq6/ezZV+8/aY9xi1v84On73/7V9/9o9739F5BrQjehgIY2jXyXqFCs3VQhBNDi91Xmca10BqbgaPB1cruVJh4SEqFGmNhbWFLWuxwLzKaBgakQndO5MpUAxujKlws5smhhgDvNYJdIN03jcYGnEYtBoUJy7E5vNwdXAkBVFZGJKSNwB4vN7QbQAlOSAZX2wtQhyQJm5NDQxiH3+84vQuAgGgkymIHk4/Fw/+rhgag7Hoks+LDbHjVr5Zs03JRiygSnVPZuzyWYphjACCYEFgHMEKl4Wc4nY+UphBKBrSh36OXFeWCHYIHZO2qhbs/WTR2iRvLQVFjkgwCMCCvPpGFMGsduv00f3LtXmeOIjNRU1bv33n36+Btn9RWag0Qrf3Ybt7//f//h7/7u7715ldcPfcq67TtmLrMbgjKjwYhIIiKjBe+99xJTTFHF3FSC3O3xhJbLjUEEnFNtO9G0oDgPTiWoKSjB7DJbeiuFtTx1iRVLuTSN+INO+fjE/0IktBOaJDA3x8rlpAk0A0CYx0AAkEroKG2s8vjczWvY3Y0jNERBmL0WJwIjwKQAOg/1n3pFRdXEDJBAIFs0YCCHqU9QweXjq3a9+OH3f+ACE7GrmtaNItoNWgcG7//gz//0P/30R7/+wbeY1zlHJnJ1ANEUEzF7RwQuQuqH3YsvX3zx6rP2XuUaT4wpR0sptMjsawoo+vLFc2ptkO759quOd9poFlmvl44BSR3poq0UdBzZQIZxNMiVLAFpu+32e6hbaABSzJmsG+NxTIgEznKW7WEEvFmfbeq6bpvKe7i+uc25r70jA1BkocD1yl9V6fKr14cf/NmrtEMWI4HD66MD59mDgeSkkB0570ORR7CZQw6/OP79OOxOAOvnqFYAcIdhwdT1xbez86+VNXXTHLa3QBSqqq4XpRcWh+R93Qb8t3/2LDT2y9/+4OrhlV8156F6wV/6AKqLvh98yJAcGeRsAIAOCCAnGIZ4e3t7ebUEAOeprRcl1w0hIIzdAG0AydY0NbFDApGY+pEIQ92AyTgoe1ajeJQhRTWNKQKyaA7Bn51vfAic836/TWn4xvsf/rsfQFsrO6tqyuIFUs45i/TDwIApZ5WcM6iBI1ivFzENitw0AVE3m5WJHPFoRt75nBJC7A/DOPSSkAhr74PjKvjVikwPgBlRcJpJUxWQlLIyZJYEolEMHEwJwMRAQiySMkViCU6bnM01JFiRwSWi0uae9l2bxLBSTlPyPqMvWkK+CrAtzxYxxv1xr/1ohWRRHEYZIEDfH8mTqqacclaYGVqAQERGYFmyCpgiEBW6PIGU6bVSusJURJ+IBfi1P+BnH0IDxEltvajFqKlphtJimdArKJs7koOZloFTXThrfara/K8NT4Lrk+MLUZGi/tlDRCawae7jIuKJS1I2L0AsZ/NWzEQo1ObymeFu/wNCK6KoMBHGHBNxQcTUzExMJTtfxTiYwdX52be++XHFdEz5+vb17e2r9Xrz9N33NMeYekJY1OH5l5/leP/qYlU554mo8gBqJuM4IIL3DsjFHLPmru/UjNmx43a9xkhEoY/FnxMWLZCDzaJpm7VzGoeuqmB7iFli3TSrNYuIGpA3JiGXkByA1g1mA0fQ76FqoV6CC5azkHOQqKorZlZzY0wIGAI06s08s0dgnUg81HcdAjgmICFWdFBX1Xm7OlucFduUs2ZxuVo5bxmGw/A6wxhYKvJisFrVOZOvnKt9P4zH4zCOQz+OoF1wzWLRLlaLlMehl3HQOCbIgK4KXCHQ0PXeO0LXxX6QlGncnNVB4Obl7V/8+M/+wT/4L/bHbZZ43X9VNa6qKKbj9c3r29s3w3gg0JiTAblQG/nr3bDfDbc36bCFxsP773ywWjVMuzgmci4mS5AEchLJakDQjcesYpgXbWsuoWRLCdgMJeskalRVCyQfB4hJxphTjL1FakhURouq2ucIzppQV1zv3+x3t3vtzZsDMctgyaQ87FkMwAVWsGQppggRhjQqmC/Ul8wp57qqt4dd1/VQuDzJYATy3nkXxzTbLd1tACWEaKnViqA7TgOxzDSB66WZnWHyoJj0zotgDCGe5rMAcE7ZkYABPVPFHFzeHujrIaGsvRk6nrI+JISJFHlq6OOcHBqYGb2Fg5W6Y06NYQ6GOK9TU+MZXEdEPq19u0N/JpYGKvLMYp6BHPpazaZFRlhFJ1wdqEiUnNCt+Q8DBNESnyaHiQKGn3TAcIaK0LCUBDPzC2ySlTeaAHcqlvCznqCdNmybBffePgoTbUbgSku5/JoxqLndXChNJRJOH2xOGrGERURE1JmDYjZ1B3D6N5MoWCku2NXV1A9XyTnmMUrKkrOpFhKgZrUEjlE0pxhjimpSwKaLi3MXKu98YM+OPXvP3vtQVbUPThEMlQjRITCWjURMDY0JKvIFdAQENRPIU13BU5HiHNd18BVz7X3t0YOyKYmSojesKDS+bhpfuXEc+oN++Pgbl5eXn/7w2eH5IDvTzrQ3iMyZNaNEzaPEMTujNKSYEgXoY9zH23bTNusGCKs6OO/AgMi9c+/BB+998Ee/9+/i9Sg75d6lndbUeq4Rue+HhKoxTo+4AioMh/H1zZvt/na5Wr/39L0PvvV0dblImsTEr4gbMbJ6SeuLxjU2DNmZNSt++PTsu7/xrQePLne7my+++mw/7lzlxpTWm00IQaKOY755vXv5/NXNi/5wO758Ptao69XyO9/95auz9e2r7XHba4TVYlP7JnW6uzmMh2QJ+sP44quDSSRLqKI5NzUuWr68WLStT2loKj47a3Mab262aNEzXN925+dn5+cXbbNs6ubjDz94+u6Tugo3b27iEC/Or5p6tVisVejly9e3L2JoK1aLXU9VVYdghctEAALBO4IyyoZgkFOSLGDGVJwx54m4Al7CRI5gYue4G8ZcAFSbqFpYkAFAInTE7Ng5V/SdGBGK9mgWjVKMM+/IO3OyVbwSiR0Y5iSazLKagmVVKUlRrhZL0QgI5/fX9x/fy5S//9mn+25ggjHZt7/58Zdffrnbb0NwyNSP/ZvttQvsvLu+7VetSykhGzAZqWN/eXm1Pts44rap/+33XtQLMFGJ4hCMVG1EB0CUVXOKu8Ph5ZvnKY5I+aOPnn7nu99lDp9/9hV5wAxghoYxpiHFOgTnnfNcNaFZLkbJd6U7IjCSm6i2IYSm8YgouWjnFUS+BCRV03bR+MoRM5WQWIYCELKogjlH7HkyVYAJ25heQaHywcwKpY6YXWBfeWYnIiZGnphYsljSWZvVEZCqqNh6vUIEVRWVbJNGhmXLWcyAkQnfcrU0gAwqgGbEgI598MEFBppUGomdc0goZKFy6HCzXp2frS4vNuOwP1vLb/3ab3/4wRNNMScd+v6wPzLz48ePtrvbtl54ql88v/nDP/g3u2t1IVjSJAmZgmNGMgXNkrOEQMQFagED8JVzwQFa1dTtYhHqUGRTTJU9DTFqtMvL9fmmff3q+d//z37no6fv/+Zv/Mb9Bw8//+zZ9th98erF5188v9leiwy725eLRVMFljikvjvudvk4asyowCLvP3jXCV4uL77z8a/8w7//X377wa+YIlO1dGei/H/+q3/1j//xP/lv/tt/dr3duQZjliS5qitybsxJi9qu2uyegQZoknJpTiAwMxNpNikt7ZkVrADtuk0p5SyETMQqqGKWDVIRHyAkKmA1cahccN4XNUdJiuaK35RzAYk159IrBjLfVM1qwZVLkhQycNECmKBQELAIxR0RrHgpFF3lmejL04anWoS57mjJYMrOSRYTYSLvvWdPxjLoeBhhNPIcXIWKaFM9hwiMgARiUDUVE8OMXbInciwqgAAOLBs3eHZ/0yzbIY5i0uWu1yFZAiJmPgzx4uyCKv/Vi1d//Kd/8vL583euHp6fX3z58uXl8t6YMiJnMfI+mby8efnixfMxjauzRcIjMzExAWqWhw/vM9PN9vVN//rew/PX2+cJB1ehhTxaX0TtY44vX7786aefvHr54tXLlzfXr7Pm5Xodgk8p77bD7Tat13BxsVIzRRalfsyAfr05D80iK5rpbj86SleXD843myq4s81i2VSQRYbcb7uHZx+//+hbaev+5T//g//9f/rX2+9BSkAZ0g6cBZtmT22id5glKTbHcyNtTk9/Ls+5y7d+cfwNO6bM+K9DsWzmUapOv2dUo6T3TMiIbhwikkMgyVZqNU3gyVnK3bFTg5/+8f7TNz9qF2GxaKmy5bpZLipme/XmNdiyrteXl5erZdsPg3N07/6GmQ6Hoal5vawfPrhHTG9e3QDg1b37q+VmOOb94avuAFW16I59Pw7M6DwgZTU5Dv3umGMC0L6pQ86xqlxOw3vvvvvq1cuh64mwG/rtfgeGbdOcbc49u5z2VfApxqHrV8tFcFXsIxq1TUWMYxyI4dE7F0/eOWtb7Pujc5DGMaWOCVaLJYKt2sXl+cXZ+YWj+uGDdyXzp59/2Q+ADOszXm0CuQTYmx2ZuWmWdd2i83VTrzerpqoY/b3Ng/P23u5l//plpyOQutKmUtOsWTWzc4A4eaYjFL/YSVoUUcFEcop5Kl10YjkTEqC1y9ZMxAwR2SGUUoqBHJFDKlPlHskjsSEZBwitb1btYtmMcejjMUkGh4CmYuRoebZYbVbseEwjE9V15TwjY7YsmgtkpGKO2IrupxkxcWAXHDkuPZXCSigmIXMFNA0AmogPwTnHxGaT9goisRHPP1h2PsmqoiqTDUVB74hwaoiWUpkACdkX8VgAAAET1TJthVi+qGKihcpQSGxQZKPETMQkS8w5xhRTjimNxOgc8fzbefYuxGNvmkEzmAEDOwZHqqKmollUShUtKaslIhLRFAWMvefY9as1XlzAr373G3/v7/2di7YWu31z/dnNzUtHeP/e1WF365g982F3WLaroe9ut2/qUD189GjfdaGulsvFYrlgxymLqYWqXq0vHj98utv32/3+y6/efPrly+NoWSglHeNQeUgRmBKiIKpjCBXVtTv2t+gBCc7Pzu49uFytlmdnF1f3LheLJTuqm1BV7D14l5aN/9t/+9vn96uk+7rBH/3kkxjzbtvHJFVovW9ut9tXb25BRsZ+vVzcO79YhVUe7LiLK38RoG3d2fni4dXm8ZLPbAjPP7v9yV89e/bjV7evj+lINjpPi83i4snjb1ydPzDxh+3Y75PzdUx6PMb+yAgL5xY+eF9hyoeYd1VTNfXC1PV9348jszu7uNiszk146DMcU06ZHIcqiMqo2dfOvO6HHXn//U/+6sWblxnk+vD6q9efci1vdi+23atj2u77PmuKWfqct/2wPXZDJONmtbq8d+9+8Jsvvrj+6qvrFNnAsfdVUyeVY98NKQK7r14dVJIPvmkDYDr0t1H2HMBIq8o1y5bIjVFjgsNhfPmqO3YRkdkFMfjww6emmqRUShq7wbLJkLvd8ObltsZKB82DWjIThCJoXGajYjYPXHlzliwBQ5SYxlGzWjbLdjgcUlI0g2yWFYzIOee8Z9827TCOoApZikzQtD7FilGbJywzOqVFXjg5YEaITKSxyNWZiUyeTgWzNdDiPM2Ijjg4Cp6CI0+GEC2PKQbPNEcEmPsopz3q9BfJknOeMBSaBZlpEjrBycICJ049OyIGA1XFmaKJs4BU+S8jn970Z3bJE3TDzFg6sG/9JCIiOgA0wykMZbOCjiA5KkagMBXHNr9fAWuszEDMSVYp+rSI0N5tzROUdvd/k3HfJAQDYGYiIkkkyxxN34qVBn/N74kt8tZPFoOvuT9RulzTO8xlpJqqKjOr6klGBhHNtBS1zOS8KxIfE7sF4OQTBAbOTMvgi5oATjxbJCAkmCR3y0mpGaiUj1l4elCAMhUtjoGFZYsI7IqjGBIyMxmZQJFvnABLBBQRs4mNZVi4efMlpskPIKnQhECQFYosIhCwc9lyGmP0RK726IHy2I9olvsMAmxMwGiOgc1AigyxGaKlPnNDVQhKWUVBGYEIOMekSUVUoxJyPlr0AhEwAQoROMc+RwFEYyBGjy6xGibLBgyuZvJOLHdd/+Of/uh8d/Heu0/uPbpany/7rhPNz7efV41vivRmzk/edc2iVtNDd/ziy58+e2bjOA5prNsmsI/oLaNljSmD0e7msAgLY7i5OcIe6HFV02L3VXfs+8ra9WKzWJ9ptq4boKo41wbkmIMT1xz3+31DsKgXvvU5x37YH+PBe3QAADmnY6j0yTtrIhJV5tJQMh8cQPPjT37S+IYUZYwMsD0fD+f5nQfBhfDw0f2f/uV+jL3jUG1qRIhxzCrsmRxmSzln1EkcB76u8QbzM1weK9WZS1kOBeeKEEF5RA11gk7gzisHCp2jSIiW6bhJfuO0dEuLDAkLul2wKs2Ck6KPFQ2suTdpCClFIAAPQxr3h8Oo47JxI+W+UyUYkhQ3hTELqYxZSiTm4JerkAsHSAUMcobAKafR+8ozI9G7TyogjkNabRaBHNfWLAnQZQUxaJarOOY0pDH3u+N1vYPWXTz56Pz9Nxef/PC6WaPHatglZKhdFVO0aFVTgdpud8NVXVwTwQjIyJBsEiLKWUxRC+sN3x4KLNfTROUUBud6s/QKYIKPpi5BoWTd9dhLQ2BWtpo76jaxYaZJULyTVyVgLN+ZCMkwMe1mDr+Wv1phhpFScdQUEAMz5akXSuWO2ZQZghloSYVRUcFUi/mkGhoc9ocmVBdnl03DKQ4OUDQxuqoOofKL5TLl0TufVeIwohEQ5JzVJn2kic/KVPYEUS2EHmT0TFwFQCj6kWJmBEUcUEEhCRiwA5URtDpbV0+ePMZkY4xm+uu/9ev/2x9+bwDwSyIHMnRPnz5hsHg8kIrEUYbU7wYQuFitnrz34INH73c3h+/+yne/9Uu/nHZyK4fz5dX+MKRaAfmf/Pf/9KsvXr9zuRydDJbBEhCVsUaHboqzcBp+1IlZNDdMyqk6z2AEUs54mvmWlIupiqEJCOjU4jrd09JyKm21Ml0HauXKF53+eawSM7OBACt5Ioe5ZOAmEy+SijL7ZMYw0aOL6KWhIdMsDw5GpEg0Uyx/7phhVoRJgg1JkYAZWSBDAkFV0aklXlTzCAyVGDSKwvRElS0dCAw566y96ixrSnlUANUMBmhYZnZHFXKojODIVf56t/3Tv/yLj975BjfVkwfvPD9cr6slGwqoKZKjum4WixYGNY6sXlVyVkfOV46JBOJRDt3YJQd+6ZFMUg5QtdZKVh88mGnOEqWtGlUgYABGQxGIKcWcmgZCCDFKUmhdhchZYXfs9kNm8gYA6JGAQ70/HI7HvXO4WdUokHuTDh9tPnz/4bdff9F98hevP//+jewBqglEJqQxeohcAAAgAElEQVTAvk/jzNsoC14R6edvxy+OXxxvH6cCAgBwnmAAOA0vI90l8dO3CMowhAFB7avDZty9kT/8v/7ycNj9V//1P/pi91f9KMMxf+fjX/s/fv/Pj/1gxFUIj64uX9y82W/3wLBeMkja3u7aRZCcRMTMXrx4Ec9VcVwulzevu5RHIKtdqGtGkj4NKYMqBAYkcM7NFBom9maogikJIUuC2i+J2JMLVLVNu1mui2jmMPRdd0x9GoehDo2pGJmhGmaATMzNIozDYObJmffkHDpPIJLT2AmoDfvt0blVVcP9q2VdZXJ0dtk2CyAeCIQZmIAYFd0CHFfc1B4ks6AI6Cgp6zQEgmVsbeq4G6GoICJPhIOy/ZcB7rfu1Z105qQcU7aOGFNpbjlmYFJVFSkZgqDeHG7NJIswE1XMjeOJzsXAEI9jUmVSH7zzzjlnBjGOzjlAYMc4ZRxW+hU0VYVqCFoUNCe2rOGc/M1DgPgzozwAs24Lzs/e2zXbBC3BKSm9Y1wTzE4/AGTTpgATJ8FQT7koTLJYpxc9VaH41uU7kQ9PXLETOwFOH2rmg+C8u6pvglmh6iuYiBgQnIQMyLD0YYAQkQGQyDnHJiYxrtZ+16Xf/LVf+tXvftgE6NON6VAHvHe+CZ7TcNSUFWhMOcUsZlVVF7vu3f5QLFSISAtPn8soJ4nkY+z7cRjG1I+SMyQr8+3zdkqaBQ7HgZkI5XbbVQGPXSJHzSIwOzQylWHouz4SETtiYBE0yDHDvStW6roxYRripObDzBwHO0CsGkJg72hRa10BSr9983I8QrDNx4/eiyPfvDm++Wr7+eE2D7E/duMYhzGrQe1g5+MX9kINVpv68vHqo28+Pb+/CuG9i+Z+qofDuDvub/Y3x8NhJB+bdd0sua6crigl8F4R0fuqqpt+6IdDHroeK++YFu1SQz0MHVhOSbLpwntXNeQDZo2ahgGOwyGqXl6tQoXmiCpmdShslByfi0BMsY+pH3WMydScA5RRBkXUtqkr77yvCL0Y+NA0bNLtD4fDomFEFE3Hbp8qQhQmyjbWwTF7SZATDkcbxzEnswyePQKlmOIYP3/2jAldYJHsPNRV01SNDTb2vTOIMYICI83EHdASgsvqYkAuHQc2yPOam0zzyBgQzArQPa9YNQUTkLu1QCXk3/lp4kRImtAfLQrsZX0VDXD/9jKDEh4AFbjwRQvMRLMohNlMWsTyed7mi87HzBV6e/nefW8acBO5I//AVGUi/fWpDpYZEn07lJzeAN9u59m8381t21N0mj5SlgwwFzj21oc0ExWeA/X8iU+csbu3w4kTcvedt5E0szL1drqgkwjuVAzC3T+bByKLvvsMIOHXXu10zUohh3g6ldMJz29qk4BxucKnK55zLg4qRESzfn/5kbtLCAW6MphUa6avOyMtkxRWChSexkBtpusREJCJQj5ZKDIQorFJylmz5JxTMaiaJ5Fw3lDK8z7pbFuh0pTLKpMCYmlrTMr2UxcITNFEMxTeLpoDNkQjRQZgcM7lnCRa7EfvmIADQkpJY46HDAk4M2eH4tm4SLUYmZIQgEhm8ExsZKAq2VJMNFIas6jmmFNKtXdyNHEAHeQIKMCGQBDziFzIKkaEnpwxGkjKWRNgUTcwPR56kxtPvDlb1XVYLBsO+OTjX1tfLEPwL189f/bFMybftCFrHkbsx2EYoikQkifHwDmpxBgHGYZoApD8/tDpaM6gvvQX63sLf9aie+fx+3Xdvr5+lXLe746H69iNOY7IzFjVNbFz4eHmobnBMwbnwFvN63FISa6Dd56dZ0qMjhHJ1U2bhJDh2B9yUkT36vpQ0SEPMB6AAW5v8/Y61u7sYn3xK9/59l/8+Y8PrzMCeXaSsmi2uWr1zsc+FgeDkpUS0d0KnqaQtIiuz0AVGIiqGIL3XgvEcRo2LUNyMK1psokQDqZKcDJwmAehZoIFlmiKYCCTyqkawB2zC06zwQiI2RIQeEfZpBu6XntEJ5LHBJuVi0Pux8SgQIBs/TiOKQJzW9V1WwVQLJQQtaJDqDlLigxMFr71Sx9t94ebN7eovq3a1XnFlY253x+7ro+XF+dAEQwF03HYHgZwC//4G/d/m38V5d/85Ic3GXpEx56Z3JgGyaldtByI9z1IMSVlpCllM9DyS01lNg4qW1FxDiyRCAFkGqEEKDZ/QKcYOoWOomExB9y7LsEsZ2Yzm2Xq5Z5ul80DzwAISEYEbKYIUhoXM/5up2BnamjFl4QJrFgKAEAh5JTtEIFAxdSAyoC3mqKJEdlEuhMqAFrOabfbffiNq8ePHy437RA7VIspEnoOvq7qZtmk7QhEiDr0o5qAAzNDxwhqKAIwzdYZAqjoRBUCQnRu0hYhD4ExMABIykkERNBgtfCrTbtofV1Xy82TdrlIh+HN9Zvtcf/BRx8tVxD3QIKcjRBWVSUypMPAaJAzJaswNO3ynQeP3nvw6JeefvPed6/uXVwxuOVyua42lnnVXHzy7LM/+pM//5e//5eBYbFcUuVyjgLAaIYKAGLqiIFmDi7Og73TdqI6yU2SY0ZEQ5lARAMCEJlYe1D4EkXLHqdlo4KTQAcSlqdJ51oAoeQXhNNYYRm9RE+u8uQpScqaFQ2IsCi6g6GpZVUFKhvFJDxA025aeutQRCWnZXuXgMwIatlhSvPKFBQMxKBQrgynakMA8W6ABgym/o2aWLE0nOTdEJEcoYgRuBo5oFoa46hmWbOaGgGaiaIZ+MoLQlQRtNfb65s3b87CiqvqP/+Pf2fRLoQZFJFZANCk8rRaNoBjlwbvHBB7cp4dmRhAtpQhD9ofuuGQDuJTbx1WVEGdMZlBTjmnjIrO+4pFQquoOZda0uq6qpuG2aUMoOC4GqL0Q77dxzFFQmja5Xrd1E0tSsc+IuTAUDHkIWHCy8Wjjx5/J99Wf/WHP/je73/+2ff7kJ33kGKGDI6cSGkTzLcaARFPsPIvjn/Pj5M59//PMSXBOq3ZuTf+10xhGcyDIQkJAmF+/lm3P/7k2fPP/6O/+9tU69n9B57D+mJ9uX4m6eYwdMG51aLZH8O+P7Zt3TReLXXHw+42ECETV4Gev3qZs1ZhdX5+9uWzXrN6x6EOTVMJDMcIOYMBVB6dN0YGBQRCQ8bgXU0QJFMmUOGYlQgsQw6CilUIxNjLkMY+pj72mjI4FFEhxlB7X1Fdu1CzhzAMW+KFJxBhIkPIIqLRBhn7Ie8Pw2p93rT05N3zISI7t1iFjF0fR8MUPCMxOUYNAEieHbFkBUAVizHlpHOILOLsU0ZORDGPjl1J1U0lC5rdbfk/e6tw1stCM4WsggyOkTwhExqgoomWgWuRBIToCD2x4ypURbpTRFU1Ri3lUiEdOO/Q8Nh1SdJ0rw3UVFUUSulYtBPN0MxYQW02FFNSmjLuabcAmCZs8OTFUSZY5n4UmoEoyJyjzNjU3RnT2+d954dFBmXnAbQyZWOmk8TNW7Xq16pKJCQwnUsm/PlH++7QKYjeFW0GVjdBVZOqZBBVsNmqrawZKmw5QJgSZcLgGUVTjFBVACP81m9+57d+49vr1h37N0xpswiLZjUMUVJ0TIQYU04iSL5ql5Q4Snz15rpaNk6dd8yO2QiRmL3zXgE0pnGM4xjjmIYBBknCZApo3jGByylB33XB1Yhwe3tgsiQQampbL8liikOfbrdHJF8v6lA7ACu2m0jw/kcPQgN93I3p6GPBHAJiyCl2kgB9U6826xXjtYwHTbHym/V6ORyqtONXn6Tdm/zqeby97bZ9lIRgVTGt7pgAoFjSP2+GV880vrq9emTtZVhetM1m9eDqbOj4uebtzTHK8TypiPONGooP3gd2yG1b5ZzGsR+OvUhSiZ5qX/GogmCqxky1a9vFsm6XSKiaYpS+hxhh6Luuz80SNhdL0T7maITtcpVuV91eb/d66NOYJIspQRNi7bBtm2rpLEkaxsNulIxcg28QvaQsMeXVZm0KEnPXH0VptQguBA/Oe5+Sxt5i1O6QDx2AgSciDmCc05g7OdB+s1mToZoiIBMBQIp5uz2yQY7KSlQwgMlfumSEBmhcea6Yg0OHdOczwDAp1RkAgoIjh7MCpsnkUHoaBrsDbk8oBs42IAXbsemhnpcVIhXfqqlKLDtCEcCarP0I2ZFN3qGTBsRUuLzljWtzqnhHEv/6urzr0J9m+t6GT06oydePCe7QGSmfQfZTMVXa7G9PC5RzwLcgotMPA2CRUZoF8PCOl6FgpqKEBMRTWFE6qeWcXudrW/AJ7fnZc58izV1n6XQXp+luvUOitBTcbwFyX3ufWeUdcBo1PJWBU/ydwbiiWEdc6GkFkIKcE8wkFeO5zJgSgzKgPgXsu88/RVlwQKowFfYFAwMDK8YjVkBIRbuTNUICduhCcBUPXZ9NdSZycJlfYofmDAQEDVVR0c1w493lUAQ2Or0pAqPArIZvAASKBiYAEyXCCI2m4VdEJHRiMY8qQZ1zFQckiF0uOtyW7f9j7816bkuS67AVEZl7OMM336luTd1kV3ezOYkCJYoyYQoeZMOw9WLAgF8N6Ff4D/jJD4Zf/WLAsABaMijYhiERlkTSlNWkyG6yp+rqGrumO37DOWfvnZkR4Yfc+7u3utv2gx/Vu4Bb937jPvtkRkasWLGWZ6JSXzO7KBEJszNCkEqQA5wEMBz2Q7JkUCJOu5ym3K16C6TCGGFKUC9W3DwjM5gpVBCZCQCrOyl0UM1KkZt1I60U5Pc++zA+wXazOTs+WW2bo7v3t8er7dE26fDjjz/48acftU9D169CaI43J0erkLPmnJgJhabdVDLSaGkqcIQsxb2lEBo9Odocb05OVxeBseZjUnn28f7y6vLmev/o0fNhTG6IMbSrvm0aJ918aZvG4uS0Cv26Pd3QFA6Pnt2MpRT1vmtgtBt2XXd8cnrEEvbD7vHjqzGVdd/0K0Al7fRmByhyGq8v01Fztv3li/uvvvLWV778Tn73+mlCMRDHEMzh6gpEES8gNqKaMjHNnsgLt8VrhQsTVDrksnkJTBCec9e6CmuL9oUYTsVaaqybdyABxCAmNiYSkPPcf0SNa25u5sQvBaWak9auFrGxhxBKKW3TNn2DQLvrIVlJjlXPF+cXh8O4uzlwXVCRp5QOE4yTtBKEgwhimJkINLlZSsltf7AhSPvawzfd7PLJ0zSlJoamWSN6HsvusLu8yUenJxDp1l1kc7Gih8P07Hh79qW37hH/0geP/jhfIqg7ZeEgLMWyuUdmbsSSVfPpOcqTwuG1w1jM4bPeFTub32q2L+H9Ft4iBlcCzHyCYCa2+W1hushVgIgdWrX6cBsXKy5my1faLT+HUcHpW4lFzBqsC4YIqoFHZnadG8y9LOKrTlgwtIo8UiXFVgysTqOwza1Rq0RRHYZytS+n5yd37p53Xbx6fqk5WSI3bpt12zWppMM0rvpU3Kc8mWuss9lR4ChQI6tqIRWM05fCtJmhJAoS2hj7NjZNyamQFtfgYMH52fHFvROHMrztmimNq03//o8+eHZ1c3Hffvtv/e2/+u73L6+uifx0e6S7qV83Ueywu3TNXejPXzl75f7DB3fvH/fHX/vy1zu0XdNDvW82q3A0mr734cf/6Pf/t3/wD3/v4myTXIurFy+mHBCigJCLFitVYbPuHYLM2pVElfa6nEZ171Xyo/lsnQ4EZlRdwnmDVF8ZYnK1qlhAJFI3tGtVJgGMCKUog0xt6YITBBRdWkagnJN5QZilQNgZcKsKgQWzJKUvuUD1CZ0TIlpKAXqRCf0/XO6z2xSVmQZPJEIsIvMnvfp41iUFCQGGKolpsMoYnmfkApqGpRUnL3kyh3mmiroZQU1ilBCTFj3sJ8uxa9IuffM730YbJrO///f+/qC7SNQ2HTylnFh8tWpSputhNLYututuFYlKGgu0wDiyij7dPf1094k1haIf90dCTbKcppTGXCYVach5vdp2/Xo3HHbT3sxC17bdStVSLiBi4d1hutmP17txP6AOInFDkC42eH79uInb84uTdNhdPd+VYTxp77/54Cv3jr70j//Xf/n9P/3s/e89jrkN0hQkaKkafKmkJbObQ0Bt4P1Eh/Pn18+v/9erHuY1MazUoJ/5RV4NoMBNGpm9Kzf7K8NB83/33/6jf/vv/tpv/c4vnW9Pnz///M2Hr4UgH33y6WF3iRCPVn3XNi7WtTF2q/3Ns3F/OD4+ik2bs01Tevbs8d2LVd83TYvscDiLExvDmMEEZmqbEAILk6mWrCUbQ/p2s2o2B94JAjhqUlWDWuqKJhMnISZ3drMCGIRq401DE7ftRgKJcJV7Wm/afhW0aCnuWkqeyqRQzqkMw94sm+9C056dt+pBYowt7adhKmVK1p12bgJmc1LVPJSSCKbRg5HlTCXNVjZadX1rqfhSWVZnXJwcXiq7YDbvuD0Z/OW3av6MCM1zRaYC58CxCSyccjItc5VaTJ2MLSIQuRYdxmEYMwzUIDRCjJKLmzEz2IsVLVqSLkjmnNrVjpnfupuCquDWSx2zW5yK3P0lnvi8rmp1aWZchUpsEeCdwdOXLDNfdEFers8ohIA6F1A7f8Dt0Xmr+Lzcns8cQpqNr7V2b75w0U99BL648NwyEB0QIWJ2BwWQ85zpaFluVAHUYlHV3TyKkwRCATDu8+sP8Nab91+5cyxySCETlVVHU/bDbiQvXdeYURm0FCUOTRsp8P5gh8ONCsAQ4SAUQ1Q4i0DI1e125seQJoyjZpmCBEYIoSPPOZWbHU63wddSCk3mTYPADaHJI+320zTlwy6HKOA8HMapTEQmEdstHr5x5+b66fX1YZwOqVC/OnJrXBuiMBzSOO3u3Dm/9/B+x0fDzaMyhDZclHH7/P3L733ne9/588dIjNSBgnAXmLw2xovlmpCbIAA3+XKX/vXn72CN7R167bXXzu6uvv6b94Jt75x4mi6fXV3ubobDSNL6aoOj44acgSxiXRc2m40lFpKGg4CFeHczgrxbdf2qC5H67SrEVc5pGKmUyLIhGg6T7j5P/Q537u3URtC4Pe7OLx482gcth90uX96kXAeqgyoXbvvVqm1Zbi6vb65vnj+Z0gQIqEW7wfo4HG2Pmq53w0H3w5gAbDehbZoQozuXcdKsZE0ra26parjFpmMCG3JT1n3HzNOQxlQ6CQ6UkvOYfQTCYtJTk36qU1s6N0Ed7aqRyBKDs98qMVXBrYXH6Euzs/ruwc3VF0tpvEBTKijBVcWUF3RniTO3kE1tktWx3xmzqNV/tX2YhYm8lndEIDhXezu3udQUfqHY9EUgy2fDvbm6+YmE0v3WS+El+tVPJ50+SwYzc1XKm6WkZpm9ms/Ond0asLzSj2l2W5z5E/Nhd/sMCIu8VhV8pRlwd0i9fwYBghdkz5fQMdACxvGMpL1838sNLU/jBVQot6gfgGUmErxgaD8b9sMcNm+1xl5OBl/mqy0StrfzmLNpFxFXm9rlM7OVYuVMzNOCL8L9i7fL3QPJggw6iDiwwFE8V00u1TkEcyBipgCJHNoQmxiiPLu55HncAzwDqcwkDFaHeZWgNyFelsKskMsEF5+RBYKz2+3jri+4NmDYjeEMFQWR0cxZNLMgAUCxnCdll4ZjDEEXAXxLJkp1qocYxIxKnGGSRpRy8RKYKZDDp2mcFE0bJYglswOKeyZXBibU1VOQi2dEArmzORHXpZkspUKRYyMKm1UeUlJSCHLG1fVu3CeIozkMeXf33r1SSmzaKWEYyomn7dEqSKseCGUmRmbooeQCGwElIilDQcDR8dG9OxcP79873mxPjy7Wbf+D7/7g7bfffvudj8mZmcaczYECcCI5BBFiPP7oanPaXdw9C+e9ShSSNsQHd9rLmyeH9HwarRQfJ4WUYkhadodht5+ygmjYHDWWm+mQiJMnHIaw340ffvjkzr1nTei+8ctvWc7vpR9fPSsc0AURjzknLdqEsBzr9AJ+WCgcc5xbUG3ihTtRLXaYDfDKqpqlsQEw2QsfzoXXedvfAjNmaqvJDFxhNkmDo5pMzygszfLPxIBblcGpc1OxiUXH1WZ9dHrUrdvx8X4EYhdOT05OTs+efP5ZziUwijYkZu6pAEnbkomCNA1CCCGKCItYcWaMw2E8JBDdu3Nvv7+5utxFifA0TgPU1LRb9fdW693uECWs29i2IVAZy5BzFmpPtmdvfe3N3/lbTz5+59kP//IxFE1jLAzCMAzZkuZiExxCYnWdkyw5GTEqjiROECID+a2QorlXDTKqDUt2mDH7rEW6nDELjH0bFv1FindbfwAAzO1FC8IX5cGFtVXDFVfAEJURPwMeNQoLmJ3duM4dmpmpEYGNKg+vgvoMnhv1szZGVapwJSDMih6lIOWksNUa9+/d6VdNKuPN4aqkKdIqDSWl4u5DHnfj7sTOrJ5AgBpYQFJbHzUhhXOVx632RLcHhUGNCSStiBhRtpJc0SIEdEDfNTHEMU1TSVMTPvrkk9Pt8TvvvTdpuZqm3/13/k63Wv/lt/6cCefnx2Pebdsj6buPrj5NCXePVl/9hbd+6StfPz095yINmnzQTQxH2+PAzWRlnMrbP3zvf/+Df3q5P8T1pozEK9mPN03kpm2IqJgRuwRoWZrwVVK97hkiMLtXGUOCo5RCgKvNiUIl4/nyds4QMTNZLYHmjeio6pRONhuT2xy/50GHecMRMXuES0FwZzOq09xVhZNdDY4KYEGxAKvzROpil8tcTd69yuba4iz1sy+fu/lGGcgEreYOABGjjoE4ezUgnY9yYyz9QABQ0xqVOIICKIhEVtNSsisTOercoxsUsgogTlo0qWlpV92mXw0343ff/eHz3c1/9vf+8zxNZ/2xkGRNVhSkIh4jAptl5U6a2LYiuf5qL9RQs250VGoNHfXbvtusNPlI0zgOw+6Qs4pzI22/2UDIwDfDIcb2+Oi0X69vdvtpumaOLPH59e759X4/5JRRDBJgFEialIdnl7h71my3x8+HcZz2fVi9+fAXLjYPn3y6/6N/8s3rT2K+amNos2oZMxQk1eW6jgPYDErLsil+CoB4iZT/8+vn14trLhsWZsyCNfyMBUPV35YCC6eREFoQNYQjCd/8ww8evHL/F7781jd+5Y2waa+nK6M7w2H44JMfa0nrk7NtkKvdFZlv+pWXwVxX/QpM5rnv5fo6Hw6jQzab8DxlFFdLRd0pA2BBEzmEIAzTkkYfdkkMecxd7Ppu0zWbwGxs3IRSstoUpemaRlerpgtNCMLoDzkndSOW2PVNt2qOt1sJVErKaYSWs/PtZtONh+mw15xzGoeSvOEVEaKQbFuWlFMCEpzNWlCAT245JwRCIXeHqo7jsB8mIm+Ej9otNcIIt0QEd68eK3N4q86wtKBCtVYSrjj0T5AElqJxmRmhmbGu7qTqJJFAEiDkCoMKc1FVRUkKIDSykj5yADoW2pdEAhYS5pLTmJQFIqxaSlYvcAFesOmrYG+dIqw2fQum9TMWFJjZZsbT8kXut0SquTtjNnfham3IM1T1BdbgfOzNY5MSAsEXZSwyqPvsBLY8UlqeDAGgW136+efPv/3FU/1Z55a7zQS5ZRtkyyCfxy/JFeJWUppfF82Qo5vBbDb0ne+B4Ipf/8ard+917oNj6Fueio15KtO+5CEKWGTImk2LmbNICM4uOYnlm/2uWCb4ZrOKMVQeRinFTCiSiHAIxGyKNIHImmhtjIxohJzLNMGtixL7frvfXwk3Wng4aMnl+maYRk2TOsz36eawu9lhc4QHD49Oz44lIJeD2hgCAbTZngx7S0pa+OpyvNln0/DKvfvkobWLs+P7h6vwyYdXP/rekw++d4k9sbdMbZBAIEs5W3FViDRNA+Ps2c26vjXKKR9wgxv3T/3J5bUkHI5PNxdn949P7zx+9vSDTz64PuQyIApK36ZoppdWzLRrm+78rGFny6bJmOzsbKPq/Wq12qwXcZ2QUtESAzfrlUzNQW0YxpFQ4I2bSqA2HK367b07K814vouHEVpQlaaIyIvuboarcbp5urt5VoqCQp0pwJRwFts7d86LMROTe8lj03rTxBgbpnA4TDkZow2hiUfH5mQKLS6Bmalp2tg0zmUap3GYAMQmNrEh5eIFDay4CFB156iS3xdvbwIITR+dAaY63kGYowl8dkYHMdxVjUCkPqfutmSC1T+TCepLyxRwn8Wl6oxzZVW5u8stJna7cYiWCS9BnYWaG69uXEBSaw9nuMNlbs8uKPIL1tVLf3+pbUIv6svlPKpCzZU09PL3fjEG1UyWqpcYz6omxKjEUbwEky1oe0Xn54bs0lOYf6/XIcwFnn7RsvV5Gm75lhf35C+hWDVtpttAsiTxL8dNx0vsAWC2rIUHDrSMRTsAZvhM1CEir85hVJlZ/hNhjOULM9y128GLJJb7Ynr7Aqx7gbg1TVNVrfiWcvWF2Lh8YHlcL49zBQq3VBeAjUKsv0IMpiDBLDEbAgJDnAI41hFcg0ECiQiTEKrk2K04kbvWtYh5YGl+tqBqL8ZV2hDz/2r9yQuPt96rENghqGNiwMyDKLn0m1VDcRyhSRXKkQFyc2dEp5w8OrHP/In6jtWSNxePfej6zhstpl6cmUMMqkbmwWNSTfsyWU6iKKDAzuTBASOqq8cNZKbVKI2NbDJIiH1Q1zwmBA+rsF31xMgleUlm+Pb3PqN3Pnvj/ua111+7OL8XQ3d5ebPfDXnC7mq3uyluMEPbmG21TAYIGaDsQLNZtxIePnjty1964+z4+Edv//Av/uSv3v5XH9YHtTonK3pILkKRCWAtbpNnImJK+7R/nj//wRUUOMPXf+XhvVfPjy+2D+6uh3KayqHo9ao/Xq2OxyG99+6HBrRrrAKl7AAkhBgRQsqxd+2Q6bNHT77/vXeefv74t3/rN7um6Xn9J3/6fUpQKyFIpAamRBIi80t5gdeRsUV92WzB4rnqWc2rmYmx+De/tC74cJ0AACAASURBVIWJmEjmSUF3n3lOBMwcO6AS6kPQaY4IBjJ3nYv4GcKfobKa2FG1Q3P2AkWBRWrQ4uT85OziBL3tE0KLk+Pt0fFxjPH65nnX923LEkQYIcYgEwAilhDNzNSJERvmtqFWQmhuyt7E1GzY7afDvg0hT3m/uykYPVBCdqbQdDfD0IoE7psQRx33h6t13E7d5ZSCHJ3/R//xv//p+5d/dvf7f/x/frNKiXIM2XLaJ2QgY2a6MFGAxOAMEhATgaswWMUIQT5Hkhq0ljjHVElMQmWBK15uWcyQ4Zwk1njEIDMjJ1A1B3FTrXbHL8VIAF4RbXJZjgcCYDV2AETgqr/o4kX4i11491t+TMUomZnUqoiWLSvK3MGLCVDFr9NYtr28+eZrD165X9LVbvf0MOw0T9yGm2FP4zCW3A4tM7dt06I5Oz/dbDfPDrvQNAgxeyHLblbNHI3cgBhhDmNIw4hBqfpbWDItYxpvrsGyOTreQEIpKU2Xl0+d7Pxoc//+3UePPvvOt//q088+Pzm9GEC/cXb6N37zN//GN36NBeap+NR1slp3XfufkDs7Q33aTx+9/8Hlo+uHv/nw4d2HTHEadbNav/3Re//w93//f/gHv//Oj5/ce2OrUSY9UDIACODIpZSUEghd3+yHNL8RC547N6XnN7HOOEBV4V49LbH0bHRWTqtMJlQSJd3WBrfj5MAMIxpo6ZMxg/mFzEiI0aNngZKCCDzPdEcK5GRaSlFXnbEzAtmtDsLswks/LXDy03hJhaMXv3F3d3UoUCpZD8WseqSLEGTOJSowBoJlBQtxqKQ7A8yUGCEIxAE1h9YRZ9e5k+K3wzVUSgkkxMipqJdMseT84eNPP/jWx//Vf/Nf/+7f/J1f/eovnW83kUlagXnJU2S/OD2SaQUC1GMTpG2zl6eXzy/Hxwc/INLpyR3vCkdmFy8WQis8wEVIOIbjo2NpGiN0/bTZHK83m7PzcwqihqurPXOIsdW8n6acM0qp9FYhCu58dfU8BHBD45RztjsXD9+4+/ppvHj7Wx/8i//lLz96p+AZU+4yK3iCscQIuLnGNkzTREQgm1Hwn18/v166/j/l0OYTGKXm4H7b/f4pcIIpwCkXi6HPRYSbEFbp8vrJcKB1+b3/8Q/TQQ+Xf/Prv/Hqul11D4TIOdDNYchOY5liDCEGK0WzhcDTMHDgEMLDhw93uw+H4dB2/YNXHjx7+j4JiUACOxAiiNAIk7lqSW4ZdHWZhl16cHcPj02zakLPgBOuL29UC3HxLXex78541beH4dC37TQlVyGKYA4bosZCDKopl8ksx4bPzo6bJpZcVFMqmNLgOfS9hE6aTmIXHHp5vb/eXU4TqInHdAxYCIgNxnE0tKBsGSnp7mZfFF3g1dkmxs6bEGJTLYPnBnYtA5hcXxrkAYhIJJjRLMwwA14G+IzvYJHDAYi8FOWGgjBxrKEvhLDarE/jsUQx92y5lAy4hBBCcPPxMIwljfu8OW53N1Ma03q7Xh9tb65vdAK6WiEBASQ0uxYSBGBhEMOUnMgrpdcrM6viWrNMDNVsx4VmrfUXrw1kbiLi1S3erIpGLXZny3KszLMX3zinQS98n2txylL9qsttFjV/tvoNQ5icQdUfuZqQ3FaUt7XxT8XL26YhLUMDDJ/SJEIchCkQQ5jUKVKotJj6UsgggQgoid1RihIMjl/7aw//7t/9d1//xXvuu6I71cExWRmFfLvq16t+TDCz2DRgLm4gMogJS9PePP90mhqotU1c9b0RUsp1Sq7tej9qFWG9ftJGCFCKG1yZcvY0mRkXhXvguFofnR+mkgsO+/GwL8Rxd5OGIYfQmELJ04SU0UZ5+OCVN798b7f7aDdcIUjfraaxwOX66mZ/YzfX0+XzvB9xfqbTIL/4+m/0uvruX77/z/7pn/7ZNz/DFagJyOLkkBEGUGYpkaAMljYG9uKZpkBIg3JrJ/c2zZoK0mE8PH8PT65uHrx6/vqX9OTe+vy0l+7V3W663E/uga1Jh2FKl6WUICdRjrtVl4bpZr8bdkOg8OzZARmIQCvIigREgBqY8Wol0XMZYrDjk6ZpQ8vb7WrbdYiRLi+v+ybH/nJ7OnFHjkZNYCGGVScrG+3x1bi7VlWQEjPHFZOAWwcwjdN2cyrCVoqWsY0QCW4Yxunx50+1SBOZwE3s3CiNqZQiwiFS1ec9DIeSUxBedb1wZOY2tHIimPDss+so7MWJuJpLgwwMBKJILkZB3K1oLlZyKVXWDxB43Xhehay1ZDhxbW3VYZB5Oq1mjzST/A1qznN3dBZmZRZmeUmg3OFeLezrPxcgxq0yvNzNC+BmRA7mGVhhXzwW7It79eV9N8MSCz9qwbBuwZGf0VB5WdtuCR58+8X8UmLMlfQJ1CT2pW/yW6XXqrwLgMwXOXCvCk4L/A53VCuhOmIkDGbQnCkTkRF7Lae+iMLTIgP1RThoKc3o9uvnvy3t7eVV12LAHL6IZfEysc32k1HMZyG0mTJrtTE1nw6YqwlnJhCZe1GvPexKt4oxllKItFLDtHpMLc/fF8Ub4trynlHFiicEtOzFqh8siZjMuto1ohOIJYgIRTGx+hMVpsWhCCRMIhxYBPOAvEMLOYNcmJy4tmlrubpoIxLXaVWtbuwAgY3rVgkQcIV+65erGxhkRMZzoe5mwhRiNNP9sCMQUSylECMwaamYq5MwORspi6qblgJWkg7MIZBhVtcJFrvQD8PAJA01EybLmiipFmRQgBBVdtvCCTQnc4PBAoUQuCTNk7Yhkgg7PFsZyq4UrS88IEQ8uH92dTl88skuyJPT8+NSbBpzSWRJD/t0eXUtFN3JWmEnTQQQDMgFQNeuv/qlt7702pua9O1vv/ftb393uh77TSAnTSg7TQeLUYw8w+Z3mSiIMAnQxTai82kayy7/6K8+fvLjy4dfuvfmVx/eu/N6xvT85lG2qe36lNPVc8SIO0d909H1zZhKERQXC31n1sA7Y9/vh08+fXq1v/rVX/+1s/sX5w+fbN/B7grTIZOQxE4KZTUJAphqJeaQu8/obVVLm5f7PBdY2RVwuBNXQmjdZ+Qz4lwBZ6qknwrl1j1+SwpiQLzOyVXRIjfzoqrzDp0BMjLAzZmC16kldq1mojAlR0S7jqtNs8uXFLBZdafHR22M+5s9S1itmqYRh4KcQIERiCPaXvrD7rmlyRpykLutVqsQwmqzZSrm0jRHfZePT3pNRqR3795PGCYdMrIC1zdX+z23Tdv2bEWuL1HWIOw0h93uu1/78q/de63/8tdOv/c2njwdKHEbuiBNyT5NB0t5lrZid8BIOTBV6wTy+lG3QKwgIyIswvq3nUoCcZXFp2WQY3lcZLdRqe7k2kOhGfKvpgpU8QGwoc5uOrSqwVVwD7SE/cp8YTKb9biYSCiICsBFzW1WXK3KWm6mRMQwBwmcCVJT2QrGEEBQmlX9AtycDeRIGX3sXn/4SmROeRr3e8vFDUlzMSO3NGUxOTna9s1K2tXR6cnR6ZF9vosdU2TL0EyK2SrA4CxwhgEcJbaNRzYt1SUkpzGnjGxNS9u+2bStDuOUh7zXk6PtxfnJm6+/OlzvPn/8aco5a+Y8vffue+umu3tyuuqam91Vv76Y0rBqmjIlLRluh+vdzeW1Zd3E9v753V56ctnZMEL/4i+/9/13Pnw+Pjm7v3q+G9pNv+43k06eo7nnZClpKSQCFG5iqOfiAvbOTNza6BAiJzKFw93Uqh7awlKkshxHs7+CocZArQ7fTk4CIoCdzetPmRskfsvlqnGTQIE4Su2HzQfQ0olRM1elCoHVudPliHUCoE5E7CAjXtIEAipU9dKxTQamuRuF6vyrBquanjValBkLZSFnJyMSEITMCD44glHkWVukFm2BKAo1ZGymVmbl+3lTLMQR1BkYkqon6npQEopt07Td9eb5P/ujP/yFN7/89a++pezw3ErMaqbKoE2zibE5DIOmZA1ijJfj488vP/vs8sc5jlMcG8iULI+HABYVl6bpzru09WwSfLNeT/kw5ZFJV113dnoRpUspWyGHODybT0rjxEmlaLUsaZww5ikV3awh7NPeuPRv3PnGeXfx+P3LP/+jd//VH34WC6hpuWmmw56MKHCUoKpqVa99SXqMnH1WwYC/CBw/v/5NveZcDyC8rKoIeml93G7ZmqzX73PMxkG3/8QMLDCbkbuQsScoIAD4eHV0+e7lX/7ZR3fPHx6fXpx85Y4113fPPafy7PL6nfc/LIrt9rRddbvxepoyhHfDdRebO3fuM+ftplFLLO2dO1thNKJdq31rBZQMeS7L1J3SpMI8TbCC6+uBENlD5MZcye3jjz9lltVKTk+OtPhqvWpj0FKs7QQk3HRdzyza+ORTKVOepjwNTNa2bdOGyFx5NHDAAzERW4gxhCa0QQu0DOOAUhBQPE8hSh8ZhjSAWDk4jMTZMuXJKZjm4NawcNs2xCAygRBI4VSngm7pSWZUHa2waDy4Vy3ceTcz5gSCqaZfhoWXSnM3MVCDQjaZU8jFDofDOB3cYKYhxn7VNzH20rfbNneTmu0uJ50Qj+J2sylD3u1Hz45Z6Z0AN76NILRAnTByIWdaxK4W0lSN04QFFqqlch1HmcsfI7e5m0LGXl8A5lLQa5Nl/m1LMYnbXj8ctTy+/Q0cxB2kta0CYqYv9EXnI4lBTqRQmmvJl3qCLzbEy39gbtFXsJG9MIycXXnWXzMmksBm5k4eAqmVbMGJHF2/mg4ZcIbiBn/7t3/jK7/48GTNk4257Mq0szAFIZLIAUwUI4cSew9N9CGlMU9pKjpC1TWrIlsxNo4m7iCHQiI367CSRrGi0/WqDwgEVbCwGFDUcgblRkA0kUsgE1JVVS8EjyxNoCSIwYW0EeobMOP0uLs46+7fO/r2k2slC2HFYVM8X13Z5XXeXY/7fRkTNiucHb9yunn1+ik+efTkO9/66MP3L7EDQnO0Oj/o5K7QXCxJKCIIwqRV9bTkog5QlNgyCQ7j7qCgBiQUN55u8MnHT6fxcHG5Pb9/fHx8vI7cyM2YCtiGqZTsjloGOqxM++Hmcne4VJR0crzdlYEKB4ScqoddLGoIUTJ7SuQeV8KFuWgTwqqltudh2u1unqcgw3TDkjabPsQNcWsWmGIrnU4+DllILHvR1HTh+Gzd9SE0kJab2AyHXdM0ljMZSvYywpjSSIedhdCOacolN2Il2ZSyao5Rmo4dOk5j6MNg6JrY92vPcDXAY4ibzeYQxlQSKvmQ3amAACFuJLaBA888BFWtNEtVMmEnNzbVuXfooDwv4zp1AcARlTOBCELu7qQ066kyqkoxuGI+LF51jGqDGgaixQHMbrEYo8qTqXycWKmZLzhImFuvS0FTs82l5oTbQsE0XkCxeeSwFojLGeRUC73FNKL2dl/wtmbJExAICqUZlKreQ1VYsMq3voQuLXD5i1DjtzddcYsaTqzCczCHAgSP9fnNsPxtR5dt+Y6Kr8miUzunwpjNx2v9uzydGhCXe1pSWq4suEpgq7Qtr1bv9Q5nXgl40T5e7gHkWavlCjmWbsBcOWBpmRPzPDJz+z6CyG5NGMln4etqNjXf81JWzNaNC0Y2L7Egq1CyQx0hcAxqbrlAYojCYHYnMIu4qFfnQIWWW1dZcRIXAYKRZqfiGbmArBpogqlU+LFS1irAx/WVuN9WQc7CBCMUBBIwGYrBaLa1MiLRIAgwdrBZ8TwmEaJIrqwdcxMcvl6t0ok+e3rNrbjONQwFlyBmZGbVzzFPqQgRo21iXDfRGz2oZ4QuOqDZXY1XFLsIBbnVPSbMlqt7bSVkO4DiLoDESNDpkBGdI0krQaJENpiaujgiYF3T+uHp8OzRzZTHhw9eZW/3z5+XnMwQVGKQnEbj/nAwzeRZQ0NtYBF57eL++fZkvJw++NFHP/z+u4frfUAQE3cT4ZIcMCsU49wlt9qZKmqThdjknB3OLC2x7+Lj6yHffCba0Fv3779xFrby+PJzmtByPO2QDME7mLOMsYmavV1LPzaWYIW5aTPifswI8n/92Z9//etvdefdl7/2+rNHNx/98Hm2RNQ6YZrG1TaSKRJpUSJ2hRZd9sGSJDh0IagyCEZWzApxw+4KWoT82KnyOnwB2ImI6nC1EFU9JXaFulsBXAsUrqjg2ZyvzYAYEUMdFFEcBm6Dw9wyoBJx1PdoMihNaf/avXVYtX3fupdPPv1gs+2bLsCVYLmkPE7iEGMfYYEswUzcJRefpmG1PlHjpm13N3st4dnTaZrC/ppQ+Ppq99pr2zQZWWY2cOm7+PlNXk9mEOX1fpwYAjOzG+bn/Sp+/Stfe+Ur7e/+e7/x4Q8v/+UfvmtqIpEl5im557nxqJUto+ROXIVHedberophBBY2stot8SVuUj054K5kgNeui1WiDKqgI9eDxuEOm1W6ban15+AOUP0cYWHHKhxuVszgvIxuCZViVB1OIWzMhZ2IjYoqVX+MSptkgnvBrPxaxI3MAxV3diMwkwBkjkaikZllNwTBxen2jVfvffn1h/urZ5oPVEoAVPgwJYoxUt9IGymcdseUKWy6i3t37z+892dvfwJkM5/ZNeYVnIM7NygFIJAQd8EIlgscwu4l2zg1DdadrCL1rRRpys0gpK/cvfPl1x++8forf/TP/3loaB37ELmk9OG7771y915vzL5mJ09ugz969FiYG2HLebjeB6eLs/v3zu6ddKtxGNtmnbN9/Pnj//4f/N7jx7v9xGwgaQ5D6mMgY01ZwblMMPSrPgSZ9gnChFlQDovAibqaCTNxHbudrSwMtTOvcHcOxCao7yUBIPcCEiJW0yojQmCq5YyDMRtaEVgkTtNIBGcwk0Rp2sidUc9Jc1ELBK/uttUGM5cqF1Bp00xhhrJ44UiTQ9wZJObkToGZwDxDU76g2YDocpq6a3EvTmpUEeyquctLkrBMMKGeMATA2QiqxdzZQEAgNITq54qSLal5WEqRuSUEd3hKWYTdLZt5JKxBxjZCXZvzzbPd1f/0j//nV+89+Bt//a+xT8WS59SwNKEvUz5Znbba3YyXnkvowo8/++DTpx9/cvVjWnkRHa6H7CXpxFJi0x53D1s57fvAHfU9um683H365PKRIxQL63Z7eXVIJafJN5tNcj0kmxKe3xSi3sGGIhIN+uz5o6Mem9W6kbBtjy0d9Xbv3W89/f6fvv/9bz7qDDdP0R0bWxZxYoF7yRkAE6dUmAW316Iw8UXqJl7O835+/ZtzLc2p+aosl1sG5ct/0ksLp5buLGH+kM8QlqvBOEJQskjl3pa+4bAKeRzQ40ff+Wgdz55f7v+L//LfOkz7Lq4ujk/aGN55+0dHq5MuHjVxdXMzMAX1POYcWc6Ojp68/975xcmzq51TWa3p3gXasIohIvAh0yHDMvoQmxiJ5dNPLrfbNkhqm3BzM2zWx8Jh1a1zGpTy8yvvurI9ald9x85d7FyNDJGCc+77uF51ZrbX7EU1FVKFZScL3HhJiI0XNZUmcpQVBWQfA3FsVu6xa9uAPRsCAep5Sk1oVm0U+M1lDtEBF5I2dILOypAKpoGn0SLF9WYVIjiZGZNDFtM+qnLgNZFlsHAIDYHKPGSnt+8PUdVFnhnw5jBY01HKaqowi6Fp0NqkRTXtDlMph2FfcoIDitC4ti5C/apt+xgRBHrcd7loZI4cGonAWLXfmzbE2KiqsNutmCYv7TIlIieCYm4b+DIVT2CuXaYF83TSpTdX4U9gzniMyAjuKAAH4aqYeUtIEA63SNNMziAU01muff6PQBCImRFVbRSyucbB7MJFNV2t+dHCWa6yLvNKR23Pg+C8FG9gd1f3ucJoqAo0kpXqccUsxHAChJs+KlHZj3lUTDi62JR8Y9myKU7wH/yHv3NyMhW/hN9AD4EzYKv1KqnqkKeS+uY0NRPgBs7JdNxrMi7imQSha7qj1XrT9FHJjXtpwRFoWuOk5bRbPTg7feP+faHpxx8950LMSqTsuWvtaBPW24MwTdO+EbWA2Ma2beDsTk1sRELR1LbcteHkbHP/wdnJlobDk8IH6hr1djc213u6fHZjKruJDhOS4a2Hb7zxylso6x/96NMfv/3pt7/57tWTEa1wafPBRXrVouaGrIYYEImCCzw4m7KqgQKZeKHaVkXk4IxcyvHZyZjGzz4dbq7SuPPXv9T22+6k73fY7abx8tm1VtbeRptVyUX3h31OGknIA3LAIOwcmyjKcDhCKYWc3LSUBKia7kuWMxx1QX2YhnR18yiXIcjaUTCDJiISOQrUp7yfUpnKwC1zg4biah1OTvu2C+46pXE/DvubfdM2JUGTjiVvuiNy0aSBeLvaPvn8uSPkshsOhzmcGpqmbwIZe7OKQxpLVi0mzmXK11PJ+9JK266Dq3KgkkqpzCIDxCWyBJEgZuqmrgqzqkdLRmwEJRi7OhyutTigurS5grnCtcPpjqoOI15JKbPaC2lBhchriHKveuwVMKnUyxesB1rM7IhAJIug0mIJNW/pmfhYdFY+WYZ+vYpk1O77jMa40MvMiRoBZhkLLHDQYtUqePFRgFEVwOvrqAPajIqLz9Nwt2j6TzC6ZnCNycxqxCJ3Y0epYeolrJsBdhMn8urEXru/mJ8nZoUQXsgiPj+u6t4BIn4BkxGDPPsXLFQBVHPt+c4W5K5ii7SsIwKIVBVutPBF65Umq/6Sy10BVb3MnImYhavOlC5t9LmlbmZeSnmBCVbWGOCAau290/LFt/dZRcxBRMFFZFZnDBQYZvWkC7ERYtKa7ENh1f7cFXAWClHi4TACRGyOoi94M8ZVa1pm7wBTBcHJqnwZE2DEjZBUqiJ5VeqFA9BibsaBiMjcA8DMEgKF4MGJzBlWyphGpWLiBJCIEblDmthuurDdq7tPZRqKZyMjITFSEqJAypqRoByU4RSr8TtgbjnnnDMMRtqu2tgFrGBJ4UTglEyIqm0WAPUCdwGHEOvSsErrM3hxRBKJwk6WiysUTx5ddeu47vvrw0BhPPrK8aFPj8rz4TCCONQpWoe5MomqwRFDXPV9CPG3//ZvffDDj/782//6o3d+jAHc9kGEoGkqacoVoI19mKUjidhZVXPOUKQ8gQEOQUQkcOCGwvXl4a/+9fd/9MG7f/23v/bg9bun6wunvB9uVs0qwEQkpyln2257zUwFgygYQOFArayntB+ePifK5vorX//qN371l77zre999P5zc4w6uvH6eEvIwkxWdTNnyl5V3avNO39pDpaoTpuSq7uV2K0q77Se+G4wM4YCNRjBmABnYapDcQ6wGQEg1brMqyAzuMrB221fmIkYDpscYI4RgJcCUjSsJR1tN7kMjx9P6Ozs4niycjhcG6yUzNyJgECqIEKQSK5MDEVOKiShoRDFTKepHA574RamV1dXh51/97NPjs+Oxmt99vQKA374g/dMcvYhrHBycexKd87aNO4ffZ43m+35+cnN5eWz8bDfSZTp9Lj7/g/Sw3tvfPWX37hz/uDp4+tnH483VzcBbdFxdjomUlcnZwkE5CkRMwUOUUiIYE6L7BVVfiTB3HkuLGyJxTOn6aX4jFmVbummV5tbqnxfYD5Kbq1P5yTN54l+gprCKmt/yTxvf5/XYMRzcHCaTzlzwNUlCKq3KwwG9aIGYnYYO1NlmQrXbQxDtw43qSDi9VcffP2XfvHkePPsybPxcHArIbCb51KIgsQYOJKyTnrYD6vjBxfnd1arftVjmsYC5hhFgjtUVRgcuKiFlkod863sWBDgMQRmWM6bdXu07snNXZsoq64R0N3z0zsXp/Dy2aefNM2qaXoRzqrjsHv6VMpheNq0fd81LDnn62fPvJQmhE3Tbdebe+cXb7z22qsnr44p9c3RaPrxp5//wR/+8R9888+g6Lt21NI0HaDTNDmMQmyaYG5qxkEkhNDbYb+vzgnyIqGnmVE1v11Y9iAttOa5l1NpjI4XDWLMENVy+FSs3MxhAcHF69KYeXS3KpsR1BAJaTX70LnjTeKuXnJBmXtkgYSErFQLQLtthKPKszCcCUzObrRQqbjStWacjYCqwOgMJzCWXo7VsX2fW2ZVN9qplnC1vOYoVXxz1tdj5sBVb86KKZup34oWONQNxAQhEoEjSCBhKsWs1COXRVS1aSIYf/x//PHX3vyF9VHzy1/5RSMPElzLqju6Hp51sQVglLIchjI8evL5o6ePJh+DyfPd5U733Wal7iVPlLIerjqRFpvtuttsegrZvYzjrqhkC8N+2u3HYRoKsgmqlPuUCrEArq4SiBlpmoZhvHcctqv+4vjizubOZHj/B5++8xcf/sUfvf3+D262XdNsSx6nIDr7/7yURjCjlCXRwdydq423n18/v/5/Xj8BetYMus62gZzYndzMSi7VfelwwL/682/9yz/51u/+p7+4uaMXd85og8168+r9e8+vhjTupzS4lciS8miltJsWZm3XetKubVz16urZN77+1cPucHN9uN6Pw5RLhrCsNn3bdOpwem5uTcfMEJG2a7uuS4cAkwZY92giujZsN+vj403XxlwGN2dC13SrbiVEKZVpHLJOxB5JIouaWSmWNVnKOZNrkDaExt2mlGKEkcTQw4UlxLadpnwYjCX3fWi7KOTaFQ4Nx5ABZmcuRNCMOp/Ytht3JcKsNOmE25hviC1XdjrBosQ2BGJBKcWLurnVPgAvkI1xrfQIBAizQ4mkaWPXrhppDtPher8ruZTa3w7Ewp6tjKmkDPdpHPp1I01w1/VRD6Y0pcePH08pNetATLkUiRzbKMqqarnAnYhDCMxcqJRS6cH0xaUCq8nGTLCdmRc/a1HZwuBYTAzrEMkt0a82+KUm4W4v+ZrMypFfLD3nLLaSBQDTWWC3olrzVSXqX5yW9Va+iPFXVdB5tgALV50AwaJBtIBnZG7uRMLqRlG2m3W76vbPrvOUsw1GxSXfv1i98hq+8fqXRrw/6KQtEgAAIABJREFUlWcp75ktBnG0BhK2pukk9OqkxVU1W0l5kGDHbefUTFmuB1mtN+vNtm06kLBT07Sr/igVUzUU7VbdK3cvHt5/tk9PfvQ2LE5CtOpiCCHG6fRic+diy+z7fWqCN+s+rlqhMA5JiJqmb2IEaBhumtZe/9K9+6+cp7T/4N0ftutNdoW1w+jPnt5cXe5jCFoQCN0av/6Nv3Zx8vD9H3zyB//kX3zy4T59htjFo9VGR9lf7WPT19n+yg4u5kQeyEWIgkQ1LZqswKslC0ms7gcVkeBAwTzsn5V3rv9v9t6s2bbsOhMazZxzNbs5/W3y3pv3ZqaUSkuWVLJlu2yiULkKB1RUQQQ8EbzDG3+BF34BBL+AICAKKAIKO0xBhMEGGZersC1hlcqSrSYzlXm70+69VzPnHGPwMNfa56SUIoLuiVxx4tx991ln731WM+YY3/jG970auu7Nd9549OYDBNz2W0maFbajkRurqg2+csEDATjzwaWYsyQ0V3IazSJJIQsE7yv2ELJmjQAEHoAUxzh26WYYBnZSGrQGMMY4xq3zwsyIKFk2u93zV1sHsFzUx8frxapmh/3Y9/0uxREZLq62oWJNmHIGhJSFCPphYF8jQga1JFhyIDUg8OiaUC/bOq/0atOtwjqNcXvVtb5lpTzmOMZtv1349t6Ds5yyJM2mo2YdVUioqICgpRRNNRdeXaG20KzchjBzoO7chre0SONClZz8eeDuXWVmWYsCHwIVT1QzLalkub8E7PbOmZiPwRkY4uTxM+MpcPvChAiQTamELkKcKxOwW5NRQzOAorYHt28JBnBLCL69fz8lvtzSsnA/lVjUR36Wkf5TYQRw7qwimLGBIgMlyWVHKrc+o00iObiPPLfvvsfa9+91913n8/NT6dlcnn1iwS2o0Cc+oQIq6jxHsQ9le7jpdle6hfinkhxgX2uYiSqVmToiMpjUSwoEEGO8c0wQEU1NVW7fwwwQVXS6zGw/7kHOAJCYEMkxFoOqogEPiMQIKjFnKRytAmmiAyZgQoaUgRikqL6pqSFSmaQAnOyczObOAxUzLCgtcOccGJQqovTby6WQclbU4NyMuhWaIBIVVR9UhKoh0axqhkiIOaY+CUBGdZnUrQLImPIAbrq1jD3AJM/lWc0AVFNWAAhESOYqH3OMeezHEQxK2Q+k7VnbveqkNzWxEcwjIiAXwTIuk+iSlRGIOTBxIKoopkFiksjgQM00a1ZZrJY1e2wpbnoiXLQL5vOqCtshoaKopiQqkCy2ddVHUIHFsj08WB80h912e3F+cX11BQiubckwjhGyAJj33tiy5CxZe1VVdOV8omOnbNWimoWKUTXlJEgWGo5Zxov4/e/+YBzGd959GuoFEgfXDsPWMlV1g44kmaSsAsTgHHWYMWkI6JyPlnbD7uOPPn772dOjk+P7b9w/vPfjbgOxS6AQhQOZAZmBqhWoAUBMDGfuh1oucZ8m7wGyMhyrYDqb1oEVvUws8sH7Wwfn3hqWmGMzg7uEn4IfTwg7GIACKoAVQ01TQ2JvhpoK8URdHdqDsM03xJhkjH2svWfjnMaYTVQUIFTsPBGQzqzzfe8OEcljFYLzPI5ZFURSTpZHimMax7zr9PCYzh4eBubLlxcvPnqF3jLJ4qA6PAqWwtHRYU/Ddvs69bw+OUUJeZDupl+tIcn40fP38yhf+YVfffLgbHup/8vv/5PzD17Herj35tnVB53joKCWo1omYwAlQ81iJo4VMYsqONprkxSsH2gyzpj0vae5vUkty6DQZgsiDoYIlg1pikyq+yVqAq1uIUmY+Z8GOI2BF9ABybD0G4sfqoKiIqCgQJn6UrCiN1vQcEUARaV9QAQBvwqqhZauagAIKppTzqi196B5uYLTB6fHJ0cpD3EcRXJVBUAZdn2ZP0UgFYgpj+M4DiOYtU1zsFp1V8AOfMMqxkzo/DhkAmTHlrWqQoaRqIxbTvQbz8571jAertbrVTt0u9j1ZNZUvGqXy0Xbb/sfXVxsNpdvPjldrg5zsmxYVTWiXt9cbZAf3LtHVVU3jS5Wm4tLE/NNdbg4PDk4aUObTQDCJg3G7uXl+W//t/8IPoTjLy3FSEzaRd1ljRKNoG6C8y6llHMe+iEiSsq31F8AuJUP2K985dzBfv5+WukMtCj+49RHmVdFADAsvFxGUBWbroS5uVaWH/DBI8+Chg4yJSIT1ayWZF5VaWqSAQJomQ8lR5ysyIPOfbZyJxNMhCyaKN0At3q+86LKqjCPGSIAFgZ60Rac/NihLK/7tGGqjBUksIMpf1FjYCJmJkeAxc1QymcEgALaTX9vqXlEi11h0QlGACBLllb1QtUuLl4fPz39vT/8H09PVser9muP3unpHECIXPCNSEJU59GYR80xDky4qJeJUghh7UK7XnLFw7iLcbSRxrEXywhVcN3RGdWNr+v6ZjPsdt3l9XbX9YKaNOWcx5wRuG7dYuF23TiOqQKnFhxpU8G6WSxC21DDEijDd7/93Q/+4sVukwAAlFDZNCMV9S+9e+UgTnXaJ1Odz/Crz7b/p1uBAz6xIWCZwcBSbpqaMlJKSVFCIAqMCP2Y/vgPv/O1X3vr0dmhBahbeOfZ23/yrT+7PP+QqsYvqi5HhbRaL5ng5ua69j5mMdVhGIduePz5R6b66tXV6/Ndn4FrCAEBUUxFdEzgUwRUZiYCJnBkoBE0+cCHawiBDtdtu/DOTTNqPvhsk6hvTtr3Q993yVJVe3Yc0GUTFCMgyZqzqEC2PI6jGai5KK5S8uSHIcWUJ9ctBFWNY0Q01XR4uFJ0Sh6F/CjOJ18DBWCXDMa68WqSE0g2AmCiKfIVtVFkhFxYAmKmJjRzFAhR7pIF0BhplkKmopuAUtRpp2qKkNBARSwLFMMmRXCuSAuYwSjiNDNz13XtQUtMm912s43OQ9M26MhGAwYjySpJyrgAOefNLOWkoky8F9L96c1MAblcKz8LEJW/4c7QynxZQUkldWZ1FDSqAFhlcGeiMNz5DlDo4QUMK9gSziSN23cukyUwF2PTCOHMLNjLypear5C0bD7gc3Vv09fUHShNl2kOISVxqi54ZLKDZitp0K1Crhp49uzoG9/4xQSXw3gx5hsgQcaMlIWSODVgCo5qMQZk06ySjBJSdoGdJw+hvV4tVqu6XQpSjrFCL2opplC1Cog2SspNqA4PVicHnXfQBvDEqINIAqdNoCZgyslDdjX72nPwoMhki2XVVHWKMXiWrOtV3TaBSbt+s7m5Xq8frJb10NNFtxuGIacMopB1Wdf3js/un7wxbvSjv3rxow93TQa/BBMZdp0mYu/U4oxuTyo9Y9axV6rAN6QAyOACKVoxVXTOGYFKBoTdZoQs3jsMEPt8/mpXt6/u3793cnQCDoc0dl3K0hGhInDwzaL1Vd8NMQ27+8f3RLKOoiSaZUiDGQN4ykZs5JDJAeXjg/rh2VET6j6RxGRZDSinrKpZtOtiSpF9v1yslquGmZrkFyvwFNbLRQg85hhTP6aoEp1jF4IhxCyqQAyu4qTZUh5yF6qFokURi0rT9AAQAgGjkimR4Xgd2QVIpFmTF+frNtQ48HYYljWHpjLAdtWIyW7sRj+yEiGVkkBSkiw555l2TWXKuMAKE8aKhoxoNLdGC9KgIAaqE4upwOpqULSLSh013UZFW3oaPSv/lJHCkmNS0ZVT0DEboBYfeQRA9M4TIxhOo2ZAiOg0YWExzLNxCIBKk1xu+d0JBDKbb74Ccv10jgNz1Pi5z06/pvYpv7xvAX7a8/PRogLxwJ7pWWoyIzMqMnyTuUSJOLq3Jpz6sIBIEwVtfq/5fe8EKNOp0Jtb2iXwEP0MYmeTn7zNA3PlNNyCM/NeSEyzi6oaUXG0k0kjYH6L+dwAaFGIRwMAEZkjZTmTs5rY/tXLES41/uyrWH7CdBIKxYmIjFAAkChUVQjOB8dMxVhckmhWQufQMTAISjKJmZ1nZCum6QaO2QevVjDawgcE28fi0mwgBERfeTUQLfxAgAKmFh14NHRFF96ABdiAWbhQQ8zQNCXN6tlVdSB2yTIAOg4KpiZtWzWrGli4RqoBPLowSYODqTt0EARbqA/C8b2D04enVVv1Yz+mOI4xD4IIi0VLHpumPjs5MdM0RFFFAo3lIiUCJpq062SMOnXkiwsjAUNRQ5m5w0BIbb3o+y7GwbEcro9Oj08+eP/Dy5ebPE6G7ei5WdXLw/robD2OW+/g0b1HTx8/efbk2X/yH/2XH/3k+biNDhgypH6ApFCmW6pQIElEdMFx4P1NQkREMOoomgtRAiZQ2WIyiwAE1y/j+98/H4bN6mB17979y6vt9U2HxvWibpsq5ZSSolLlF941cYhpHCaazpCT2PVV/+P3v59ifvjwjWdP39le9buhW6xW7aLqdx0AZpGcxbNvm4VzIY2p1HwAZY7ZGImJmRwiF8pUiVuiCgAOgRmZXbGHIzIsDxwQTxQKvUPzBJv8hWH+H5WKG5mQUUkigDIoearM2ESZkTwCJdHx+I1ls6Sjs+XpgwPf0iC7mMckSVSQ9Ph4TWUKTzXFOHSp6yDGYmWW2pZCg86zmIjE5eogxtwPcRil60UUri67w/W6qWrJ6er5OEZLPXQ7ubq+OlqdHh0cHR0e1D503dY7WS/b1bKt2vzkySlIbtraTK+vtpLsb/+tf+nX//qvn95b/fjj756/7CpZYa5yVhEzQRUxUSQscYfBaML39g1KnPofRMQMs6FjgRLNQLUsP4BzjMc5VQUqIlVTuGQsgtcGapbLzF2hvhXeDM6eQvt0d3J6kyRoiAooigpgZAImiopmZhlUBEu6IWpSXpAI2RDKEovlrBIiExBWNXFA4/js2dlf+2tfeve9d+oGLi4+HsebHHfOARP2Ma3WxyG03tVsjoFP1kcH6+Pgm9VydXZ2/7/57d9va8YMw5iCrwgp5UxIzjEQNG1NjK7yznkT1ZwNIBRLFMknx4d15Xab7e7yYnPdv/3mwy+++/lHD+712+311eXhwdFbb79zeHSEAM77pq68D6LaDx0yxj522+3uehPInRyefO7JW597+s7jB49WYU3oh4Ha6vg//s/+i3/7X/33XtLlw3dPrnc9MCopNz5ZFMzsMKU0xlFETMUAiJCY2THNCwbMLWXAkkMTlUVBQUUgzwLsOt1BSLifBio04knyH6gQk0rML50FFRBVU2Rm9k5R0aN5A2foAQKiJ/QADMCAHjh4FyoiBgJTg/JhS7+aSCb8FJBIJiAMiQkdAiMUFgbOcmlI02VuVioKMAA1yVmTgsyqXgAA5bXQoFj+EBRYu9wNCGqqJmYADM4ze0ZXyOAimktyAAYmJtONMbWUTHI5JjkmjQIGjpwT3nY3rqmYiQg33c3N5dX25uo3f+0b2+G68SGntGyXUUaBaJAFY4L++euPjG077N7/6IMuJQW4vNn0fRKDlEwTajbJUaUbZXN4EKJ0u364uLp+8QJW60Mg5yqfTLLkUaMa9EO+2Wy7XrPAakmLhVu2br10v/GLX7u/urfkg+5SP/ze+T/8B3/0k+9su6sEI8SbLIM6dqCWssxyAzPceetK/dPJzs95/rPt/+/bpybuP7vPp6T4ZZgEzXRSTBWT4AMxqVrOmkfNg0KED69/+OrF9enx/QdnZ8xWB1wftFeXl113GSqHaN4Fh0yqY+xO7p0lke22H4cBbXzrydt1VRNAP3RJxHtER6o4pjTmfH4Rq2AmsF4uD5b113/pqxcvnw+7K7K0bKvdcHV0fHD/3vHR0bKq2DE2wXl2mkXFRGzox6HrVDKZVcyBWETQpKpqzz4nGbo+xgxIIpYEkWtVEmFVevnq4vnzV+M4OO/Xa79YeOeo6EgikCGRcy4wB+SgdavLBS/aalG3T994+/pis7vot7vsuSUC41IAIRBJuZ+pFE6SU8xZULEQrEqJpJIRganIC2jhIqEDvwzG6pyTJDllJicx9btBs4FZqXQlq8ksWFPOJymQPXj8gDylnJJlrjA0wRxmk6TZwAA05ZRVqqpaLJtQVTnnoR8JoV0sxiGCFX0am9lgU2pNOHmvIxcpz6LyjlP3GgAQSxdjT+NAQCqmZTblL2omIpInkvDkWDJNWkxNUjAok2r7SSMuwZ0+cdHinrR8B8CaLmeAmSuMhmQTf71Iis004tK18VMtN/0ygREYg07JsQJhTNEHblf+4f2TxYIO6/E3fuW9f/ff+TfNXhLsfBAXSMDGLEKBXJOFgCvAoAKAFKpQL4KhbLur11fPL69eXFy9fPj0rcXqsKrqOMbN9SZHzTGlmOuqAeOxj6BQ+fr49GR1tL68+F5TByJZLsNy6d58cnJ2b7VcEKN4T8EzewIqlr7aVJXJeP7q9fPn14jjV77yuQdvHIuMV9evxdLi6H7THF287n74lx/fXA39xi5eKYk9ffDsq1/42tXHu3/yh3/6nX/8l9uPR1PII2gPkHXqbUNGVnQGDMYGaI7JN+w8A6GAKgIHBsfKyt75yqlZ1gxEb569NWxj320lKURQhfPNgAkOj5d12yBj14/bfhiT9LFjH6qmDaFSlTim1XqZJYtlQmNCzxg4OHCQRdIoaWTWpoW3337zwRun9cIN4w5IySGgVm1rRllQsgJAVVdV7UpOHAJ5ZyE40XxxeXF+te1jF6qwWLbIHPOYcsoKxLBYNu1yOfTjEAf2rm4aEem7HhRLm4/Je3akJEm7m+3Vq033PI3PY9qkvMvjy3EYYu1bENjtdqqw7XfjMCzXS3Qw5hhzNNTCTlITyaqiEAGKPY5OI7NqUvAhRDC1ovBARf+KJjhIs5iYilpWy1bGZG1vcziB9KSlSTmJ3RkiEJGO2cQsAySwbJbNxCDvv9SSWlRNkmLUpBKzxixR8piZeILeodxjVO79QrMhZEIsM09SjM8LGndnRPETX/BpJKw9pjUTwKDMGt2Bvj99dYMpEsw8qQnEcZ7JsWdfctsJH+TbVygvWpxR93rRRVIDke9+QMQZSd/3ec1wooXQ/NNpZ70rnj+B/ohIsytikfzQ29ecHwAYs7udJ6QilowwTUjPexLq/KLMRETM7L2HMnB95+D8bMsBAIiZvCvRdv6puQn3omJcPoV2Q8imZWBLTcRURU3mDFZMc/G8AFIAKWImAoREqtlUZVJfo32hhIY6TcQiGWGKyQAmX9ypNaSGRgzIPHnTlZFOtZxFEigAejKAVbtSkBAc19znZNlEbQRJKprTgnzVOn+Ctsl5C6IgoqAACUAgDhEa8AGX68Xp/bOjewdRYrJEzvXUXQ87yxBzku0NM7377PPDMA434zhcE4PxbNOiBoYMDMRQ+dKCUjMVkQzGxZgro5R4CmAw9rHrt8Dw8P6yraux7wGUmWYoUUXVEJpltVgHdw6r5uDhw/sHBwdjN4CAK8u0oKTM4FztEFE0p5TKuQwhqOi0vs7uA0jgnZspjgWSMGZXM8UxMpirud/ln/zwVahDzFr7lef25nrTpa5ZexfAsqoBoiCZ8+Yq0qyaEzIiGnm42cGPP/hwjOlXf/mvf+O3/sb/9s1v/fm3/vnB4TqDeHLEhMyIhI4ZCH1w00Samen+ZlQtl0ABoql4FEKxEZ4EmFBIJq44FqSaTHVme9+9zG/BrLluJwJCIzUgUwB07IufpffOBRTIUbIMcHp2kF1HAalGiXHXXfdp4p5WARBtHCMjFttK5ogApiCiORdfaVHNOecSdkVERJh5ufCocjGMYx+b4E9PT89f7pwnQ9IEw8u8aUe2m3sPDprQBKLu+sLBigyrEETk+vr85PC4WbTX1+cXL64fnL354PTNL3zl6S/88Nn38Ecvv30FqQHIrvYh1EY55yiSGBHVMAMacGET48RAKbHHDIhIVAFKcgqm06z1HYLoNHuwl9ojhCmA5f2kIc47z22EvYBiOVWGUJz8ZiibiyZXIckZTZLbs+SFpknKyEwNjYqTISABIcIwDEbAVNAZYIIsljSj134Hj968//CNe8R6c3N9cfVqVWOynFIG8MxcRlnVch7BK7Hj5XJ5uF4RV9VpCwgkCugcgMbEIXjni251XdcK4Lx33pthTqOJIGAaI4g4JockY5YxkWHr7N7RyaJp4xDPz8+vry/W6zWYEEDwnli980kgWSbvvPcH7QElbVYnLHC8OHhw+vBodeyhUjEx8M3yP//v/+Hv/cE34UsQGC5urtXhLu0geIt9Sh0FZwQgJbKSFXsOtSJSe7vCzhF/v0LAZLkyr6PlGJeTNp9SnMqECVACKgxgVAQbRWnqHOM8wqGqApI0kSESkkMIiIGQMKkqFBYTlj2tNJUdkwIBKYCZMvuSGSGiohKTgRiikQEScYFJp/WViacmn4KpMrppJFbtliWJpS07v/fE5ShaC0iGaghoonmqjxiAkZmwUAVpiiET8LUXKy9HRdWyAaCKZJsFgQXGPC4X6/Xy8OZ6e9iudze7mtx23P3Zd/73H12/vwJq2sPteGnK7EpIMzPJKRsYOw9AKRoHIq40mShhRklAomrRYhy64Wbb37/vs4jzzrma/bBoF+hDokwyqABkzJriGHc7iBFWLRysfRXQM67r9tnDt6jHzat4/fHlh3/5cvgYsEfKDpENzVWAADnHMstTjnbpnH16B/Iz9Oqz7f+N7W5+DDDzI1F0XmAQoe8HQsSamcmKSKG35/8Mhu6vfuUr57/05S+SsYfw+P79D05On7/82OBVtTxs2nU/dBLzOG48v82EjoFQJYP3XPu62/TMnBJ4B760XAwZkR0gg2NoGh88OtDGYwxeSdrAZ0crV/u2Io/Fv6jAPmWpRMkqIsGHynvRSICo4gyZQuObPGY19b5aLykrpiRRMCbLQ9z1smzs4vxqs+0lQ6OxbVrvPZIgGBHWoc6GQqIIxCk0omga1aTf7F7VLZ+eHR0fHX78k+ukI6iZTE72ExOVSr9d1UwzKGZzwJM8xtSxKL7bpaNvYICKjIICRMhsZClLjDEOMafMBUAqTUgofAuFfV8SgTzVbX2zudn2u6TZBUopDWPhW4OxgZmihYqJQcA055wyZMiqOeW5/Np/u5N2lJA81eyfnNIpP5279z/9NADsuQ8w9/wnAtXUpZu4VdP73lGlmfWtcMqmPo37Na2zt3wBAAAr9pUz62qSsC5Urr1rGDpEmbldxSrHiiWjKXgyhG7XGdq2iw/Ojg0T4PW/8lvf+Dt/++tjf75somgCBGBWc8poSNuu22x3iOQoAEKoquAdM3rnHTsmp+oBYbk6cOQZcLSY1FgzI1fIwzCiSeUqQEKmo2WtDF/6wnuvXt5cXW7qugoVP318FipIeZdjbgMkhF4FiZKMhKC5H7qOQB6eLR49OTw8aGPfvb54mdKwWh2Mgw43N69eXFxfj2kAMnAAD48fv/3k3Xfe/IXf/ge/+4Pv/ujl661ntIyQlB3VdWWGw6YvKdB8lZYCgABJTK0IdjJwcMgkKoClYFVAbcNqd91bQm8tUlaX8qiIcHN59fr5cnnc3D95OA4p5XzZ99lsHHMdqFrUYVm5YXhx+cJGAIGsEAiZHZiimWlMWYBhfVQ9fHB0eLSqat+Nuy7usFJfObBKpPBNyTmHRHVdOc+SIyH4EKrWDxaH3XC9BQBYLP1qvVwsF7tuc73tCzAUfCDPiLgbOgBcLpaKNqTovffEllBBGRwa6Jj6fkyj6Q5IHQwAgsZmfQaCsUqIsFysYxr6bqyrOoMQIzojBjOcGFUAQx5BdJ7EKoZmZcpqL7BrNEVqhUmceGJOoijs3SH2GdT+RkYQBELQkp0hgBYnRCS0+UaEmRBS7IFswqenf40VDd2tRR4WGiUVZB2LVRihoRVGqk7NeDY00ML6mRXFf37H5dMTnTvQFcA8yvizoeDTnv1EIAMEsEljdD5WViaftcBOP+eD3SJRE2C+h7HmP+eng9j05C3+Nrk9fuIltYjQ457kBTPY9Mk/Z1Ksv43Sc2mBd+Lx7TSekSrc6a3D3Recss2i5H/n8xVcEYpbIU1FJsPRZFGpxYnKcqF8qYoWUWxJKSXIWizJNYpEkSSQtei7I4LkbDkVQ3WRbKZA6L1jxwW/K4gmTv0GQsY0RiTw3nnnACFnySJAxo7ZUWnlIAGyGZs5FJolJ5kZ0VSJ0BBSjillYhfaxgevlsWG0HCz9L52zMjMTV3X1SKEFgO/+fYbq4O2amtfc6i85Ly52W42N5ZV1WKMlkFAkuYubZ89fQoA3U2/vdkWlWoqUk3F/W5uwiCioalKYaGoStY8cd4AVVRSlqxmCgT3TtdAmciySErW9XFibHkC0mbF7dp3m90bDx49e/xs2Ax/+offvtxuXCJSChQIXRlvKYyqQmlWU0IqEZGJmbicajXlQJPF5DTEigDgHJNHEw2BXbCsdn5xc371+nPvvofktHfvP3/BLosmFTGFlCSmxOiC96mLOY71shbJhBgqQHH9sF2tDler9cHJUfD+/OL1uE3sCQhVrAx5aVbnQmHWwd6wzMAmSVAreDyAOe9wWrCxAMVlflYn/RoCZEAyQy2TbxO7rxApyq03MYtAyYxQCZRLHevJ+VAVSwMqJt3Qc2N6AF//1feaA+8aTdaPedcPYx/BbDIqqOpqu91KNlWNMUsSMyCC4F0I7FxUzSnlGEWyVaHuuzj0guCXy4Obm10IPmdtfP3wwf0f/+QjMjJ1SAzkh24chr6uXN1w0zBADoEdO2Yb03axWOQ8qhKjEzGC4JwD1qPj9Zff++r/+sffXoQFsITacUU5jibqvPPMRKxZNQHYLP03dRan6OQqX0aeSvek8GZVyrWte7xpiouMyFAYT0woUWA+8rgP33tXuAKLI5W+bsE3FArpVYsYKRqSUZnVLwAwAoKCZp0E1MtFYnP7owhlcQYCZEICIDUQIyWvq1Wjdf5bv/nr7Oxme/Hq9Yc3Ny8ePjgJBV4GS9k2u3EstjJJ0exkfXjsA+JKAAAgAElEQVS0Pjo5OK18vWiXf/TN3x0HASNCSlmQnSu6lQCLZTum6ILz3qvo0PValGiZGXBRV8dHhyZp6PtV1dw/PfqFL3xBJacYt9tN1w+q4pz3PnjvvPPee1PLYk3VrJer04NjS7quVw+Ozx7ee/Dm/Tdbt9AMli249lvf++Hv/He/9z/9z99crhZDEvBcL1pgrJpKUTUlqhgBVBSRSkPYzFSVkERyaargPPNuBbQq5wbm0w2lMiQqC5gp0OzwNzlPwkwvZSYuVDhRNdHpBBUAFAoWreBg/jJlBTZDFZWJy0cISIoouQiClvVhavKQ81I64gjoaEbWDLnIW5W4O3MIykdUADURDa7CIqooYGoqAoCgWHZEKO0Unm+BImU2rfcKGRGAkRyyZ18FKmojpY2/N/2dDH2nP6UAvNPM/ATEGggQkidvBuxot+nauvbB9Zv+4+cfPTw7PVkfnxwfiwqhEYuhGOQEcRc37z9/P1ocNQ4SM1gyjFmzGBjmrCnlOIzd7ma7vdputz5okoTkEKssenb2JrBztd90267biqgLPiXJaWwbODr0hwdtYFwvlm89fPrew8/FK3n/ey+/9cff+/6ffXz9o7FuFpg9JAJFzy7F0TnHzGqT0Oo+q/ls+2z7v7T9n9QDP2//eU0xpJnQiwBF284ROkSisqCbGSg57xwv++tdVdGjR2cHB54opzj0wwVz2HVj5RtC17Z1P26fPH2Wck455xQlCxufHh8fHBzkLLvuph9EAZtFVTd18P7V610VYFH7ReUc6te/8uV+c2VpJJPg4Oj0oK550dar1bJtas8MZmmIkgUnI3moqqapAmOhI6hkccSrxVLV5iZ05Z0T1SyQlMcoKafgw/XNNsaRuaQZ6DwH74NjR0TsRVVABLJSFugNlQhMcrfdffHzXx23cv7R5icfvyYKVsyHAICZHds0LjDTHGjKmwyKooApSGkNIAM5EpAyrQ/OoMIs6pxz7JmcJu26jgwZGWHyd2ImYFI04GLnalXjVuvlcrXIKmLqva+aitmZWjYlB86hipmBc47YqeQYo2ouui9Zcml3TYk3TL3Yff9lxoaKPPOnTOt8oqOP0/TgZIc9zU7O0B0iTk63gACKd8alDaBMNjBN+evdWm5+X7wlf9lPfwYAKBIw5eomBEQiNEIoadDEyDB2syUYQMmSypuaSWga711MkQibUA39KLH/ta986V//u7/51feect4FijmPQEQcosF2yN3YX1y/Pr94PfR9zmpqbdOGqiJyyOB8WK/WR8fHB4fHUYzIeXblg7RV3TZt0y5A0YzWy7WI3lzdXG6uFOXhw4dPHj8+PT5dLZum9syRWMZhMwwb7zCEMq7DklMghDwy6KM3Tt9558Gbb74hGm+2l924WyyXh8dnxssXz6/OX16MfU4jsMGioc89ee/xg6er5ujv/6d/f7jSsVfI5KF1GFJMmnKWhArgrNSqExhpqABSSICMhoCMPnjyXkAUDanoH9iiXfWXqXI1IeQhGeTVujk7PUTCm5vr7W779ufeQSQz7OJA5BDZOQdgatl7N/Rj3fgQGMlELYtKzjlnRTMP7QqevHXvS1/7wvK45gZ62Fz1NxkzeAWH45DGQYYxq7J3oa5rR5hiT2TOkeSspimJAbStPzhcrw5WVV0RMxOrSVWHpl0gUkzpejMiATlOWTZXOwL0HEyJgR15yChjkqiWwEagDSM4yACxqAQ5y+rItYsmi6QYQ+0LzJ0lDcOoqgigWfKYYx/NjOaEnKBwGHUa86MCxBYhheIIoZOtnEhQIpvOz75EIC6MqJlwZWZk5c4GnOk0BqpIOFcpQKVcZucIJ3lwmr+XFvgEmpRrQaA0dOdPpQjTIN4EflnJ4czIZrlys3lSzvZ7FaDM8JP39J0Va/bIm9vtsGdg3cI0n/hnwt3nRzMEbjYdgqJeCIAGimYmn7KMzjFnpoISTvov06ekT0TCKcijGSPfPQT7FvVcS0/UVVCc5ugQ9we4PIAZySpbTjqHWdsf8D2UNUc/m8rM25hsZlYk1fa73W0MAMxNdPwEBFgQLiJiW1Hph6uIqQAWhlTB/sVUtGjOC0AGKN9nSWxiT4iFPQSqUC5HBiAgR857YjIEYpp4hjrJKZb2O3tm5xBJ1HKKZkXg35BBCaxUNs6ATSdotsySYLfdqiQwyJLHmNQEg+fgEE1Q2IMrkdnjYtkg0np1WFctoWPP9bHPGA01S7q6ut7sbj56/QqSVVXIIqraNDV7Mpbj46OT40PJ0vX9mAZRgQSgwM5771RUJJuaiMwQb1EbN1M1NOeZmAFMRUzMVV4xs4eqBueVnLF3Bni17YABFHzFviGlmGU4PT59cPpgWS0+/uDld/70L3QDkgzUCAhhGjW1PaA5L+elOCyXcjnHoqKoOhES5rlZ0OJ6IGgGRuSQaBhUfL5//1FTLQwspyGlTrKG4FQsjtG5UNc1GI79kGMuc7mSTQwUtGqa1y9eX22uHzx8cO/RWczjiw9fG6mKqgkxI2IuFuwIDFQE10QKKwhEdHKEQUSeIgw5KmJZWvIvZABGdIQOjEDJBE0JjQEYgdEYkB2WIne6AdGweCcUdzNEYuc0Z1VDhxxUbBDIRw+aL375rc996Yn5FLWP0keNWVNKoApN4+ra5yxDHyWb5JRTlgRm4BzVVVXVHPNAznK2lKyqKkAahjyMmalG9ACeyF3fXDvEtm267a67jpU1rq5kSCIiFg9Xi6Oj5dnpettfNHUrKsG7UPmmqW+uN6pYhcWyOVTFru8N7OTs8I3HD2QHLnCXrw0FnPTbQVFXq3UI9bAZAIOjFrQ4e04Risr0IBOyg4mZVWjxqqqgSHuK7bxSIROS2e3qQBqNiv7h1CUohJSS5GE58nA7cQgw7aKgRmXCUWyaUbC5u2L7HeeIeqdVU7JJbr2RESOgSs7ZxNiqBk7vrz7/+SePntwbxu2HH/z4+csPAbaPH73BqMGzmYWqfnVxwxTAWKMy4Nnh0Xq5WtSLRbv0GF48v9hc9eeX10zUXcnZg+MxxjENzjkzS5brKlTeS8pxGCUbIQSmuqoWTb1etmYCpgfL5dNHj+/dOxvG4ebmpsQTMGzbxaJuggttU+ec1MCRW7aLg8XKRsm70Rs/fvj4rYdvY4bKtTc3O+eCD4t//z/8D/7xP/2Ty27Trpf9GLOIq72iGZpYNpK7kX2/DEyKlEX7FmG/aJTVuyy2MNlOzVa3kxJaWZ7Iih4tAeLt9KcBqBgSViEQQkp5kkUvoWhCisDVnjxhIPIIbELFthBpnvZQAAUEVRABKKp9jAAmCoiiCqBTR7+Y+RIYYslcYHYAZkQEmq9ANIPa1yXqzasMoBIhFcEFJGYiQCxLa0m3JqcZU3QlDwPnuaoqDg4QtRA19/Y2OjXeSxiG+cAjYWkbAIBlNQEkTJbGNBCS5ITESNT13W5INo7vvfv5Z4+fMpKBIuUMI6Bli+c35+c3rxPkUWOXxmgyZu2GYdcNYpBSjmPMcdzttkMXzSDnnWP2vklCRI1BoOAUZdfvri6vOHh2VFV+vQqq473j5XqxPFyuF1X78PjBfX/v6qPuz//pD/70m9/9yQ9HnwLmANFbAsummk0zEkFxwLhzGyPuOa6fbZ9t/ze3T4W07vZj58ezS/GcU5dQpWYqe/41AgDzSkf56MVH/e7CLP6Nr/3KLl+Fiogw5jFGk6yVb5yndtEcHB2JapKEiE2oLl6dn54cHx4eOM8K6WZ30w1GDN47QrA8oBoDLCp/uGx+6Re/1N1cQxoXlQsOT+6t20UdnHNMla8YcRziOKScVRWqUBGy9yE4RlWRJJLFpqmcdrHyPhB7AIopjWNMGQCdd37RtIyQ0miWQyDnoG3r5WrhHKuJIRSB+WxZIAsKciZnCODQM+j942ca6eb1+IMPPmqahpitQO+EiGhFdpSLHzgSGxVKgqmhsWNyRcZlUgEoc9Y+gGs8L1yyDAqefVPX26stAZKVXA6cYyirvOPS/kKPgEaOqiaoSEzR0Jx37FkNBXJWmetM8MxVVXnny6gyMyOBaikXpvGNGSWiKREBKsvUVOjQ5Mtx55qZkxaae51zxjIVxADEZVIEoMw86eQ+rHt+BMDdBnwRmf1ZmAw+ybOYaFk4PTYr2loIRfqgLByOC3o1qbZPx2KyYpt0GeYP74JDJOd8cHzQrgL5rh9A04PD1b/2L//Nf+GXfrGGtK6dYyMi8sHI7aJsuqFPfTdexDTEFJftoqnbo4PDxtWFIBd81TaLtl629fpyc51jQoHaV7WvPPvgKu9DjFkFna8QMIn2cSeYjw6PTo5P6iog6XIRXp9/hJgl95KjY66r4KvKhQCaA0Ed+Oz46O2nj++dHQLI9c2VqrSrFXl3ftUtVw/HwW6udzn23RYOV4tA9Vfe/eUmrH7wz3/8R7//XQ9kSUkDmJ+OJ2REIIcw5fgIREClvY3EgAhgRo4NlJ1TU0Wtm8YHV2rpytfW86JZ7nbb2HcG9uTp46oNsdPr7UU3dovFummaHGUz9JvN0C7qUAUATWkgBwLjYlE1i6oKAcCGqJrBPPgKFgfwzrtP7j85qQ8qcePL65fZxcvuOmGm1nzld9ejmcsZJBmhD84BmGlWU1VNkk1huVyvlitkcs5XdRDJWfJytTLEqqqRKKU8jDHGDAZIqCJxkDxaUfjRqGRUsWdgSJajmABsiYQkKWQtJWNMcVkv2mWzvdpkSehoHEZVFckpjpokj5LGnGIq9W8ZxGPgInQlpjT19nBy+xQDMxCbygEFUGAtDnTTrUGMkwwIzJblM0ixZyyCzZ46gmBlaBEAgCZZbACbnKhLAVOSuSkQmKFa4X8VKRIVnS0twGayPE6m1aCTOso8hjaxIRgmTGemen26Dt8dltD0fdKn2EeDPXtoT04q1a7NLww4f3KCeV65fMgZ2MJbmP4u3/M2EBVqE/HMwSq8NZtX1knSaKax0OyqNe1KRDkXy7Xp/cvxw1l5ff9ed3Gruc8EmqX8VeW3YO/veidVnCk9U5Sc0K4JXJyemUGr29B6i8f9VLA1AwM3hfKZa1GgzGJ4jxPUYVNLgovd4+2JMpgn3U2ndYAR3MSMUS3T8OXImxZdo332y6XhIwAFu9BSpojJZExGVgwOtZAUpwuvqMRzUcWXrJIyICjnkUdkMBBgycSA1tRVG5ax22JGyZkAl+3i+YcfZowuePK4i3F12OAAgCBJUWG1WLarJRHu4ubodCUou7S1IMujhWO33XZGBs4m6RYzxCI2bYWxYmZQ5lBwuhrL6CUICAgQhBrBZ668uRyCX3J4CKvr6113rRkjCKde1MHnnrx1cnS8vdi9/6P3mTCrESGbUwXeT8wiToLiM7uvnHLdy/vjdLAMFYjK/O9cPZqBIRMwApFj8pWy4o/+8sOTeydc+4f33xhleX79AQiYZER1ATyRZm0PGkMbxxEA0EPwDgR2u/51vEogJ69Onjx5/PXf+OVv//53xRuQQQBypL1ZVsFsYqLgXGCHbGhCaEYKe9MBAAQsOHnJJlBNVBmoGAjiJJKsZpJB0NDBlCcggDKXphkgsZmRsTGgETI6DqKaclZTZArBBhm0SsenzVvvPXrrvccaosVsnEwEzQgheFCApqmqKgx9ZPaaJSWTMjkLUwQuNCUip2TsrKobM2eWUzaRlPPQLlY52K7bJRx2/fXyYDF0nUT1MK27miEOOUdBoJQyNBhCww5Uh36IgIFdLUocqqZdEJOgbMftZrP9N/6t3/qv/6t/9O33vws7AAftCamyaziNFsdcLZcEXiSaRMIECGSMhlxcc0p7oCwxZuW6KIsRoKFM2omICDMja3avtrnJOHcZ4LbC3T+eGwzzyZmqj7nfAAagWF7NQEvwmkOYqk4UV5wSwDLyVgU3mBAb0uQvwjUcnLYPn9x79Pjs6ubl5dXr88sXY+qXS1+0yZnZ+yrUi7reNVWLFtSSJ0ZUQnWsZInAf/mLX9zcjC9fnF/3sW5AJAJo7eukOfZjaCtVzTmbmmMGFlLzQBU5R2RilQ+HDx4er1b3z06JXcqy2e4Qcblolss2+BqBCakKlaQMIlmiU43bbc7IggftahmWzJyTKuLpwQMxe//l89/5g9/NY1Cw7dCbRwEb82gEorlwrSeONpbeyx7IuptJz7VgGc/huUM1n6X9nuXslOPvnTMEI8WyHEyZiYKWIiGQZ65YRjHVYoRaxKoAjQMbKziDogYOhmaoVlo25WKbRloKgIQw0cGKDuiMgxbA7bYvDWhWNOOB93xpm4oMBGAizaIiuhdgpPkqNUUq9Y1ZKcqKn6UpmgkqIxX1UGQmz0hkWj54sTg2K9R0xLI0qRbjXJyp3UCAaKSACqZS7Kg45ghMoyUTAEIf4McfffDPvv8XX/z8F944OTMVgCL7qGqaUiw5F7Njds4CYUZmh5SSmQiDuknKGgAhRRoj+Ixg3CyqFCMmGsYxpkTsGFFTZoZFDX2tp4fLyrcea4lGI21f54//6ur977+6egEYgcjnDiAqGRF5sAzAmrMiWiGOTGyA26Tos+2z7f+7bZ/L7hGE/aIx3fGlZC0LkZKnakyZMXz4V5f/w+/8wd/7e9/A0BwsT99+U9H7q6s/N3KaE6g7WB+pmIqYavDOh6q7vkyxy6mra753dnS1vbbXG4ExRxWgtoJk4EHZpA1htWj65aLSsQ3e15A4Nc7HmHMSUzGjFCWOOcakZoSkZpjVnBGxc94QgAnQJNuiWkTNBilhLqPb3mEVfKjqqqrSMOZchwAAJlnqOoSqMtUYo5kuj9ecRkwMMioOolP9Dk5dHRDzcrVYLAIwgEuMJMVOyqxozMwE9YklZFA0ycEKbYo5eM4pKSnwNBVJ3lEF6BHEUko11eQpWw7el2Y3FPdYNGCeGgO4d/IyU7jZbop7fRwzQCHMYMUeHE7OkiZxGMGbqDp2SJRTgpzRAAQQYS9yiFBsfm7XsnKpGN1d2uDO9TNTHe4CTHeSC9j3g+9oZZlBmfPYl1U/9f3nXbq3D3DuecyHGkCRHM42RchICKYqaBOzmBQQqDAPEY3L0QfnGJnMbFE3eeiOjtaMtNtcjBH+xd/49WcPH9aeMWseY1U3TkEt55wlkWQ2MCQJAdFguajqEILzAEVzyTl2gCCQ0bJT3/cdOmtdXdctZAEBUajbRe3bmtoMZsxu7SzAAg8Qwq4egvcig3dkllPqcoreuaZuksLN9eWyqo8PD4+XqxD8erWMKW7HPqUUVQ3i1W77449evOseipj3rmnCso3rdXPYPjg4OBo38qd/8udAgOgBwLDYExkRAQZEQ1QxIQOjQimkcqFMTBZUx6w5axZVg2DeOWLMOen/wd6b9Fi2bOdhq4mI3Zw2M6uy6tate+v2ryEfn9g/NoIIShAoQJLhZqYf4ZEH9kweGBoYsAaGLXtsQwMDgmDIhkQRpEmZfI9i+0i+7nbvNtVXZXuavXdErLU8iH1OZt13SQmG7NHdSGSdzDp5zj6xY0es9a1vfZ+JJMmmg/QCwm2FbIi8XXfb7RbQdxfpB999/5V7L08PZjM/+7R7fkxHlXNZE2BOEu+9cVeT2qBxm9kp+5QjVAGauplMpsf3jqrWbWV18uT5k4v785vtoL1nr465aUS7ytXitJeuSxEViUsqH0FQ1RCdq7iZTNX6fhi6blDLRDiZTJiDZImpH2KKMSOCGuQsI8mSTCVLNIlFTalGxgjJMkAE5zwm5NKVZmZZAcSypiHLkAEgJ1EVIkJSTJSTWOm+uqpPl8EVAB4DegYwGhcRGdXZd25/5VYo+i0jrX+nH77/fxy9NwEBdFSI31Uld3cvGiOCko3FWRFDAAXDfW8cItAooLWv6pqZja+jhobEmtXMiImAkXdvoVcLxfV7udy+V+yocb/5kWMXFY1B0ri8jAyj3UaG+MLyU15u7610HQ3fgTnwmT/Y8ZheXGfgWtZ/3fj0itO0+1w4CnNdG1Uw2KkcX/80zFTEg8anXYOWPovR7/CoXSUbrr3DFfSEO/fAa9cUdojhX3rszvCF8cGxjwRAld1BYOaioIZIwICIUKyUQAkBUBmQAdlwnLe7XvERBEMAImAkx84TeYbdVSkQVS4i4jYKOzvnyJHSqF40wnAliRn786006pVGISGjQBA8BucrH7w3Ldq+ZmC56FuhoUciAxQhc5UPdcXk0Pjs8cX6dHP+5CKtEisMQ5+jsHo0yL0E51LMMUq3HmJOVeWrUE0mjavQ1RRTvDi7GEpfcR166YFRJOecVJUDusoBoRYV6xHFA2BEHu2rRHK5N8wreljeaOY3GvTZ11i3Yb6Y3zy+gWi+pqYNvqK2xVs3Fl9952u3D+88e+/8D37rLyrn06BsfqTKQKEdXDEhi6n5vntIRErfECGxc6U1iNix886zqwN5MjRjNRZyxIzs2Fc0pPT8+Vm/HSZ1c3zzxksv3z4/f5pzziq+qoIPQOiYKxeYYRiiRnMVV1Ul2fptrNqgqqfnpyJ2+/bNv/53vnH80nLI3eZiLUnMqa8CMlgRJCsMVEdMO3SbCRiR0ZiK2DMgAKkV+0BkQFemCCqCIilC3mk7KYIRKoJa8CPheuQZuUCOiRgdcvCKmi2RN9eihYRVfuPLd37i5798963jzFvhLkEvkMWyqgCgD76um6qqmQIAmwJAaUUscqgjDyPL0E5q7yo09q6ZtAtT7rq0Oo+Xl0lV5vPFZDqZtO10UrGzg8ND56qU0rrbhuDQRFWRNFTkPJ2enxkQIIvYatNNJ7PDg1ueJu9+/5Pvfvej3/zWu7//R987efJpCNXB0eFs0fyNv/WNv/N3f2n+kjs5PTm56HLWlIeUFch7qmMSACIsInDFCZCKcfOIwhdu/vgQiKwIG9JVQGiAoDv3PTAyAxTbCfVdKwIUOG73Q3H4QEQAgaJYilAomVoMomGMSn9UWeczYPyuA864xgSJyMibq2B26G7cnNx74+W3vvzqZO4/ffDh/Qc/7Ps0n1cHy9nBYk6oRBhCmEznQ7LJdFFVdWCe1NVyOnGAw6obtr1z/Ma9N165e1d6+M4H7ze1W/db74Ov/SAREHzlc045JlDwxE6QAILjyvu6CtNJe7Ccv/PWW2+9+eby8LDvhkdPnpycnqckRETsU0wIWAW/mEwd0qRuaxcmobYuvnr88u2D4y+9/qVXjl915Jmqy8vtNud//Vu//V//o3/0/ocn2UnxRA51qJrKypo+tlLQnvZ7tfvZrsgxrvwj825c+4sLQwEuVQsDC0aIEff9pUWUcYw1sCBAhb9X8i8ABOc9OTJGdGYO0ZEP3tXsPAMDECoVxAt213okmoOaZYWCYSkwQAF+EEDZVBVMR9/Z8cPuGuZxV8UpfjRmqEal98IouDpnlag5m6kRQCFaWcoA4FzFRJqTquzn6phfoUGFBgaMofI+hKKKJWaF7mFlCMdQaCzvWknbBMgjI7uClhV5UQMAImTEQmZWsWxojLBex/OLp6+9+vorr94lBIJeZDDUXvqTi+fPzp/2GjPKZuiSSTLLouy9gZlq8N57lpxySqhQVQzmiZuqapvJdBjiNm7X3Sr2fV03wxCHvtfco2TG/PKt29PQzMJ04ue356/e/7OLP/m99779B+9tngMJ2sA6gOXCFTfiQnm2XTXyKuD4TATzxfHF8f/i+Nz8/8UYegdQ4wuIA8BI84SyZNFYnRZBQkpd7Lv+w+8Pr7w+u3371uJgbiYHB8vVartYLidtO5vP5ouFGJ6en1+uzplw0jTL2WwxmzBYStHQKHDb+tpzYNacdJASj1QEy0nzSz/7MygpEBxOZzcOF9t+005az14yaNY0aE46dHGzWseYykmbKqGxJ+8DV8G7gERqVjeNKhTrCFU1UedoOqmW02Y5b6vK1ZVbLGezaeMr5zyHUKlBkixihweHhV5rBGKWLZdmn9L88OrtNxfTxfPHF3/+wceE2SCXHpsR0Icxp7lKNA13+zEYgq9cNamMLKH4mnzjQs3oQVAgQFYFhmnd1HW4vFwjIjCXmndWEwBXOWBTU3TkgkcEIAtV8C4QsQkMXey3Awg7cm3dTtvpYrqcNhMyGrrYbWNK2Tl0jsQkixgCGgMUr3u7Ii2UYgTs98CdjuaLx25Gwa6Q9kKuarusfEd7GLMQNgAEdoQ/yjj4y+fwtVcHxB1jqzTdGBghOiIuusBKjrxnFwgdAIiasodQhaoJjhw7R86hY3KOPCMSgrW+ItHz55fH08XUh0Wo795o/5v/6r+8d3zQslWkBOicj2JZMYpsYpekAxoEegP17G4fvdT4JlAlSTRpkTdS0aGL226b+k766IGn7aStG0LOoillF6oM+Pj02ccPH9x//Ojs8qzrt0POSWXazu7cvHP71vHbb79x9+6d+XzByJo1RW3q5q3XX3/r9dfeef21m8tF6jePHz7YbDZgKEhd0tNV9/j04vQsd5v07MmzzXqFZs5p5eY/91O/sJjdfPcHH33rt/4kiwaqchQzzKK7HbhQyckUDGk0aRkviozRCwE7J5JLgc05CsEjWk4p54SAwxBj7g20agM7FrH15SYOkb3rNnJ50p9fPHvnta8ul8uiy45gZinpgJzXm/WQOrFUVf7g4ODuK6+8+vrLr7/92sv37iyOFkr54bPHHz14nyt3887Ny+1K0Ta9PD9JT5+s5+0kuEaVum3q1n0acs455ZTi2PqYBNJgQ2/ri261WsVh6Lth6IY4DI6rvhvWq2676XLUktqhMQgRcnAVgUvbjKqeAqPTrCnmNAiIeXEIaijERgwKQITosO+7QkqwZJDBMaOgJbVklgDy2HpVoGQVGGlNpohAQIyuKO9olrFJCwCNEEs+QSxXpVKEMXAtRKSr8un1uKJIi5Q71ogLs4a5pCVatEjQDAEJR5dqxkLagFFCe59VKF5FyzoCKaM4RimSm+JOTPnaF+H1/ka4ak78KzG/8FkAACAASURBVI6dGnnh54/l0mtLx4uhEyJiQeR2DwgRi0sQlvUZizoX/NXvPL4+IbOHXb9decuyIO79BW3/WYoo0vjmhEgiUqAmIkfERIw7jZGrj/AiNAa7RMPyizFhKTIg7BDKMtTXFt9dvlhebh9c/iUfbWx3uDaS41xynni8XoXIlTXbSNQrRh2ERoykCA5ZRYupk+zr9WCoxMyedh2t49mORnxIoGCgNtqdFbHCcT8RK/5+yEwGoCYlIlEcZyQSOEfkKwhsfvTVql0QSYjoGDxY1AwIDIaIWc0EspgIbmOOw3Z13sMasIPtdhvX23YxySk7ZCKEIWJP3tgM45DVYEXrnIQdWaWnF6dsDpmUchfzpJ4e373ZXQzb801aRUMQNiRRsVG7yY2Kv4A2Uqr3KQAD1Ei1cYsYNFtUAgrCXhDz4qA+OFxsuw6JJk04WC6OD2/KVmStsAUNBEImYKqGAKSFv8wjp8WuX+nyGxEpHHVCyql4G4+pLqEV9ApG5EKUQSkHFwI2qe/OTs6D9752VXM4n964WD8TyQykJiIDm7F35BRZqQJfuZxySgkImnYaY7/qth9/+vE2rv7W3/wbN18+fCu9Bl4/uf/UTiylnryHYGxsWZOKLxpl5AylkA/VANCQ0cgKjgk0UgSJRlYjAhdYpBSxxvqWjmHH3jsNxwyYFQAYkWiIHRDU8yrnIfOgqO989eV3fvy1w9uz082T+08/fOWtlwQze6BMFEvFyyE7ERiGmKKpMAJXISAVreysKiqSkoI5FRJB5z1RRawIXoW7LmdJs82G2M/mU+809tujw7n3TqNerlcGQGwQ4WLVTc98NXFxsNKvi2BD1OCni8WtRx+fP3nWsfHtxcQzR+Hv/eDDH3784K237tx56c7R4uaXf/KN5c3l//a//rOH388pC0hXNRPJKVsKLhQCJGVU1jHsZWNXIRoxAIxcXUQjAjTF3aCW5UVtXGJtx7oCo+uzbnz8wj9QLpOhIoJR4VTCuMeMZEzbVXZATQFg1LaAK+r+uMSNdVDr4wAOhE0UKgfLo+mtl45u3Fpw0C6t++ECCGZzPjo6WCwmIkYE2YTJq0IV6ioEU0LD1nnvESGCpTRstquL+ezw3ssvffntN+/+Ufvxw21YUEoDs1WVEzQzGYYIAq232gdmNgSPXDk/qdvjg6ODG4ujw6Nm0m7W20cnJ89Ozs9Wm6auXAj9cI6gBLSczkEBstahmkwqTeqcfOn1NypqDtsDUN32ed7egGXz/gcf//6ffvu77316cGu+kQEBnfPEaEgOTbPgWGu2kRe0d53dVzn2i4/tyuxjnL5b/nd0rR/dMwBApNh5GmDp1sNR5B3IzLIJA3jnOVTOJA1ZshSZLGbMkm2U5jMg2Geg4/JkpiJXLjZld7BiKcnZ8g7vUjTG0fxQGQmoYElFvYVGNviIuI1vg8XgXKWswiVGKvsUchmCogWnI1Q3vjEYKjhwjokZDNRERUexmN0QjhmQ7fKnMqwKoxkqAiMhsYKoAJihK7vfWBB2ITTeb5+t//iDDz786P7XfuL01nTJhGqoBqKaTcVURQaJKUtWiXFIOTJVznlmairvUTUNMkQy0Oy7rfgK2kndNu3z0/OuvxxyziKz2eLs5CTloa6IGNvgOWdGWcxm8/b4pfm9f/X7//zD7z65PAFSRGWJSobsEEorsci4qV1Rpr84vjj+vz32XHLYFzB2uhy7NOczU9F2agGmaYMUANS5Glb97/5ff3506+CXjn8MdOIr+tKXvnR6cTZkpRDMwXp1enGxulyt27YKTHdvHbch5NSvt+tV1zPj4bI9Plia4vnp6gTPJKFHnvhqUgc0C+TQB8+OjBiwIs9MHQwpgQqQMSEXxb+c1PuykxowEzMLGZhlikmfnZw555xjJq59pZUkjc56EEWx2pObOGQeIktOm77X0s1rjAiPHj9X00wqaJkAoDIDQiViMl6tz6tZE9p8uIQ0QMpGYESYBhXVUe/JxKC0EQDArqhhZqYZJJCRR+/YNd57NjKRbCLJkvMY2NVtcOyAQLMSAnkiQItFMwJKOzl655wrDRaaLavmLGmIMSZRU4gQgTLBgGFez9uZU47bmIYOAGJMAiBZDIAdWgYYHd9xv6PsM6prec9Os/NzDiwONmOThO6ebzv0Cna+y3AlG7vfPffzE3bp3PXp+pe93x5Mg+JSj1CSGlMFMCQjNh+8KhhkICOiUFHwXhKbgYACmCAoGiRxiEh2dnJeR3j2yUM4mP/sT/7EN37ua683NxTOuv5J1sERmTkwV+Q7PWJwSs5FaCQZIjehZQgenJVUjzIqiKYUt8N2nVf9xFdtO2l97YEHU+c9h2od+/Pzk4cPHm+7oarqWy8dAdgnH38ae7h5887B8qAbtjePZ1Vo7t597fDwaLvdonlicB6Wk1lLVbauZm85D0mo0gRuiLrepi6iq6rNpjs7vYgDTCbQNDRt69sv31o9zd///rumRsxCKixgAoxmnA0IiKRc/EBmWljcYxOMGYCpGWhxh3LOcWBiQzOJIjGZAngBlzQZEBfroH7oEXlSzw0FtbcI60fQncTXvvaKaPrmH/2OW4d26Tiomrz8yi3vq0k9a8PEWwXKmpJpBgRiJHVN3bjwCjgz8afPhsVRXXsmSICmQn3OXSc5GWEwhRRzqSGTgXcYk263m9htYg8IYALOEYD2fXd0yN22G7pBEhC5Okyc86YmRfV0UM2pJNVgkHPOSUSVg/OOc3HAKOqhTEToAoPpdrUFRjS0ZOAAMzEgCIJJaYqywlEqJM6dxegoLgpY5KVsLzRU+s6KzMNYJZQrVk5ZbGwMXvecHYRdMFt+trIeYQnlCAGMoOjyCwIAYfETojEgLJceHZCVXBEQ1HSscuxufDMALD26VAK8UmQA2VEld7BWKY7Y9e/wOU2E41Kww2OsVO7/PYp8+8LyDsvZw0N7nB7GkBY/h6n0WYAedlhYWbuISsuFAezPrETfYKAqO8lWu3qRq3PeMZx+hP+FY2/zCF1d41N95uR23xF2tmFo+yTlRz4JXFtIP7OiFs0KIlIRvaKzEaKamXPEWqjP5TLGvJN7BCuyQgQIisToAMEhqXBxsgRCVhRDIAfkkBi1eIeNKzsVJZ3SqWGoBqYwNllCNV6jcYoX5EvH8g4TGRkzsS8W7MEcKUHhxc4m09hvwZQCkTnInaCAiKXSvGkp2layDcY9QA8VO98ymEKEtMlp0EoBgWkgjMzolLWkg7mDAVIcBnLadesqtPPpUrL1/RYCVlXlq6qZhH7VxS72XZ9iJs/j7HBUXBvHCmG5tAzsmWrSqbnWrNKIvaFkjMm61OcU0bl6MgnGufJh1k6DqyDjg48ePHv2DFoAIUggJfMiLR1XjGRgxUezXGaVKxG1/QwwK+JZoACIQgyZ1EiUpXAYBA1ZjYjRVd5bS9vt+tHDp6Jps704fnWRbYDesuYUYxbzaJ7MSNpZ7bkGdOvTlZmBoxhzjuIqF03e/eTdt3/42nRZv/nl124d33rth08+/P6np89ON+sOEMCRgVoSweLsXOZIaaYxA0VmJAUyo70PZ7FdLeC5jhwoKjxyxatEXTULoBbvuxGxA0ACBc0ycHB+2kLSXob2AL7yk2/4KT54+uD+2XvVhLZxhY52lEtAJQNKCttN3/eDGTt2TMw+OEZ2BuDUsuSkgtsueedTzi5hXRua86Gt6gSXlynCydnZputvHB7ODwP4hJwmc7+4WS/WfugTZAAHkmG7jZtNUqtFGbEa+m613m46vc0tSnx6AUuHrSdiXvf5/OxZtKE9oMv+8vjw7ObRS0cvH/z9//Q/evrR5Z//2fd++O79YbthCr51OfWW42jgqGCWVVFJXR0MR7okjqXHYv1ZgjlEKjAnkJFakYHffeE+BBwjSsSdFuzVsqZGV8ytUt0tjWkj1Dv2gxQEwPaQ5Hg1ryMfOBKKicEcsAP0ECqYLSbLo2load2dp7gKDd30k0nbzOeLJtR9P3BFhpazbLabMYIEc57bJviAse+GbdfWc08+bleL9qWf+rGv/vBv/Oq//s1vdtSdb6IMCo0BWc4CAiCQMRuxZ+edP1jOj44OD4+Wr959pZ0GyfLJpw+fPnt+/+GDy8u1AQN7Aa7rCnKq67apGk26ubi0kA9nSyLfzvzNxQGp77q+04wYAHjbD3/0p9/5v//tHyaB4J3mbXDBVzykYei23ntyo+mO7kXHEEZoZozHP5Pr7fbEsc1w9+AzVa9rR06pMOiQAUsnRRHPRDRVFUWAbIhECmreAMDE1MQEi9G4mRrZGGjgGCeMS5bCjmde6KRmBkSOHRWpllIhG7d4K97KAFAatxWJykQpHx/HUvdoKDUWnQzMxukOXIZIR/cn1OvpcFFQUbOikUyEWXLWVNrnrUDhVJrnEcr+LzJmU4hABoU5T0bF5gBh3/MCI9fRgATIKDDVMGzhe+++9+a7r0y//pOBSA1SlpSyZEUkNRvioCoiMsSh63unGpqqLErsXFW3KOg5bC43IpgGVCNAytJvu1VSYA51VXXbTR1C7fyk4qZyAaFGdzhZtmHWn8df/40/bjYBemDymgHU2JEjlCw5JzMpWsL/roLjF8cXx3/gYx/A7LICsrLPAxgI7LindlXQNTDwDSGImGpmaPAv/vTTavr7t+7cfOfrty+GhzcOj5R00/dAYRNzv4nduot9YrQNymUd/BK8c95BTl2fpa7aG8vDtp4eTqfzqnZYTetZzSEATLCR4J00jtAM2rqtQk0owWWQbM5ltRS1CrUL3jR79kCgkIqu65BjTnlIuetTvFy3bT2ZTELwwVeq2aWUdSUDDjiwq5Cc58YcIGbJOVM2YDVUhQcPHhI7DI7rimtn7EYuOqJz/uzsaY111epLd6qzc11fJkI0RwbAjnKvpWMQdx0pRvuVCgBNTPoUgc1575oAZKpZwYghGjQVN3XwwYEZECiZqRATsWNGTUlQjBCwbJM+J805a8rrdS9JNQMyeg4gMMRh2PTGkAdxxzc8V7N27p0fcky5F8kKSh6CD7HXkTQAZrKXMCgz5ir/KpjnZ/c03CdFiABFXHjnxm7wYiWkxELF+xhg75A8zkx4EWD9K9Cr6zN5PIsSxxbIsGhTIwIJgBAZsjIBMwAb0riJK5hAaYg3AhPV9dngFe4cH3386ckv/fibv/rzP/drv/wLq82DtlZNXU6deMfBZTNDIDTntEJhpj61AoSEDltnzoEjRiXNaIJiop4lOL3YbA9vHi8nizrUiChsBnZydvnJgwcPHjw7vbicTNqX77ySRLrLzZMnp7EHpgmY23ars7NnTeuqikXyMKTgMThUTtE8+EE1BqJpPUvpcrsdTvvts3X39LK/TNmAb82na7+JQ/aeqgrvvXYnSn//h8+/84N3q+lULwdB5coli4AIYqCkimaE5ophFZohqFkuzWJjd7+COEGEynkXvJGQQhaxVPyi1LcuxQymOfUhNMg0m8y8d+vLSxMCE4hw8uj8zmu3lu1su4Y6R1+nuqoo8Hw+C1VoqpbNp23enG/SNkECFRFJHCALzOYHQBa7wYmn1BICCyDpdj1YHobOTLmuWjKLse+GThHYwDEjuhS7OEBxozRBXwXn2EwuTi9FVAUcheB95Ssmn1UMMOfYbfrcZ1JCADE1iTmbmjnvahfOz7uKgUaTeqvrylfV0EdLELwTyQIQyFEiNKTSbiVgkk2BCNWuCTwgYHH1ExAVlUJIL7VUHAkEo+k82C4lLiEa7+6Q8jq7b4C6izms8O1L/Ag7CpUaGpAiGPPozFPgKwQYITYcaff7NGR0l75+p45EPSmZ5LgG7Iv44yIwin2OpwPlc5SI8LN3OiJe0Yj+ihXh81YIAJMCPdm+vAy2f2cbBZ5+5E9f0FAfz4GgdBeUcyAi2Cez14B4AFMFE7mOyO9ftpzW2JOouksZXnzaNTR/N6S0P9vdkOMuwr5afj+3GlrO/vpb7D/UjwzqC/gGIBYsAdCMiBBBjEZBqzLftPAvjIHZMTkiI0kmSTSrGYmiorEjYDIo6BUUDylVQWMwICYCGn0idlSLMfPY6eSP4sGMJgoMzAQOnXPsCR0CU0YSzSJilltfpZQJ1WEVnFeyZFEtqhYgKSD5IZkNQokglzEyz+iC7yOklDizS44GggRmEDVBAEMADwDQDwMFJc8ucJKYLBlblztg9JULGNhRPa3qLqSN6ECxT0kiEQKRihoq7LxcffDNpAkTfxEu66nDABlyqAC8dHGrCqhVXdeGcTLxZBD7/vzy/M78lfsfP/zk4QMgIGPQsi1DUWdGRwRkYjnnve20qKhpGccy+QvTgbDgQGAKWRQoAwowABvRqDOloKJaemXAEHp99vTk6ebk5Td+ZjGbI8vp5VnKWQ0BI5qxw6OjZVVNt+th2CYFZ4Cb1Qp2gmdDD7/+rV//sbffeuvNL81vLkNTNfP25NH5Jx/cP31ylobE3imioYiCASE5BgQkIxXF0mFa/CkKMQPVck6oCAqqO7QEyMqI2G5pBC3jj2hGTDZW0xRMTKD2SjnZUC+qo1n70uvLMOXHJ/c/efSAJ/2dW3e6tCFzCFREQyWlZNLltF53w5CdcxAYWIkUCnhb5K0Zifjisgshp6RMUoe+bedV1Uza5NwlAojk88uVqSqFusHz9fPaT+cH9e3u4P6nz4Cs8WTZVDALhDABtDhYt5XLC3j6+Oz2zUzkvQOzsO2NKKsMgOJrfP+T90KoHzx9cOfmvUk1f+2Vd27dvn1wvJy23/7o/QdnJxtXAQKIKBtDGTw1EyvCOwhFPQnIUGFvGVgG00ZkihCNSoVrjy4ByH7F2cdxuGuWxr0y+Bgcj9DViFuRYmkANoDiJDmu2Z+bMO/PRwHNV5RQQ0WLo3Z5Y3p0Y+4D9WkLMBBJO61Qsakr750prFfr2s0cAxj0Xe/qealLOEdV7bxnGbKkKBQq72LX9W61OJz88i99o57N/pd//k9DUyXQIYuYqRo5JAZUkCy+riZN+9Kt2/fuvbpYTI+Pj5L0Dx89+uCTT5+enGy7bVU3k2bifEhq0+ncUpxOZ3Vd5zisVxuo9JUbt28sjhrfOiATkyEC4nTa9JL++Nt/9tv/5pvf+fi9yWRxuVkZm5ElSWZmmEUghNoUyXhUALgiCO0GbP9V1r7dJrjHsQAMR2kA+7w9pTCaEMEQCUBGvlyJ4AkZEAyKILHSuOqXXBLUfAhj3XMHkBFgUe4vIpG2q8YVqnehl6I3t+8F2WGeJc3CHXVPis3U+EkJd8ZDI+nXDACJGAjBVApMBooOEV0B/A1s31Y/VgLRgEANgve+CqoS45BVcBT9RbAiyDYGVDt3lbIIGXDhxiJYYcyTAElRizTcSYYhEEfJQRJXrsb87R98+863D77+1S8vfSXZoqYhppyLlhiKatkQs8oQBwUTEFBjENQaDL1vp810dRYBUZVyhpRzSn2MHVDVtPWkbVOExcR5JofQhjCpq2V7cDhbnjzefvubP4B3oZtFABYBy1rqk2pmIDhiiiMO+MXxxfH/z3EdutphEjASd+2zxVu8/g8CsjIDZ9xuBiD35FH3G7/x5+985Y0bd5swD+jCYjFztV+ts6YYY0bkKgQmyCk+eviITW/cOGpb3/a+Xw0gETU51trTwXw6beaL6UHrGo2xAX+plmNGh+zcweLABb+xvvKZyQirmGWz7uuqadpmvb1kIiOIpllVRDfbrYhqsbexcT1EACaufHDYiyB7MOz7zRZdCJWrQvCecdfilrMOfcoZUDMaKqkxMDkkYDTNuW6bNPQpb5sJ3bh5OMhq2ycyMAQvRBDWQzeWiHREfAARmUaVdzIjjXkgIK4CMAhYNkGmUNU5dlXNPrCigAgwOMIci5azoh/dLUqhwHnvnFOJppZSTttik02MnmC0is+SQXR72a3dajKfHC4Pss7ONxfnl1EBqLQF7XK0kYF1del3EOZup9uxnj4zrwB2gYqZEVARgix5GuqoUk+jppYiEo1eSaiYCyv8evfQi0XiF1Cqz8znF0gKAIXLTrBXajIzyzkClnoOqKnlNIimjsxQ0GTcPoCJIJnE3FQ8baq//vWv/N1f+9u/8vM/eWs2eXb5lEUDg3M+5mIDXwZEECNBj8pktXfBA1U8QQEGRDIuPaQo4EyJHIc4mczracO+NGx48gA2DOnp82dPTh4Zhol3ENx2GNbrjSqw81lABNp2/sOPv+cDAOTtdr1ar+qqmdZhEuBwOXcAbVtNZ9Pjo6UibE8v16uL88v+fJVWGYDySwuctZWk7BwNKb/59qsPPv70vfcewhZgSoAgZkQGDoq+PigCIGMg9poFgBDyHmvQaygDjZClESAgMbEzJgARyCn7aRBHpJgxz5ezPKj3Hg1jyg59MgWzR4+fzD9oXn/n1vEck9HQSbvEW7duHxxNuyGeX55enm7OTi7OTrfWgcswDMAIi2nD7HNvxHixuZzWy6BV7jNkwKDPz8+DR0IXuKlC4wEJKUsaUo4D1DUH50NQHSIhqwoCOPLe+ZyH09NNFSCEUPngXAAjSZq6NPRDiikOGXpQU0IwzCxc/PcQSFSbFptQAVKMSU2bWV2FOvaxkFNSNkfsyZMyakGK0NRI2Ewccoai0A40mrMRGGVRyxnyrphqgMgOGIFGJQIVQzJUw2uQkJWOm89APvvWtpJ7jJyp4jG5v/GRr+5722UShgZUbuMdNLSHTUooCWPMh4WXQwClFREAinA3wehqbwhoo23iWGSHwoT4PIAKS5y6Ozn8y5Caz18iyrqAJUO61jC/i8zHZ/zIG3+m+6ok70UsBl4gh76INY2Dtfvl/tURibkUbcuaVh7vOrQ/+6b7XK/8ulSQ9+NFxV1JcdeBCVdJ4eeM3+egV0Ql44DdCO0yGtxXtgARnRTECYGYjMmhiBV7EjCQcnmzgnMIHj0HQnZiEjVHyVk0E6oW6pqCqYphMZOChMVTlzw5GkFUFc0AAKagMDblF+QMAXg3CRiMi1smAoM5JEQQVdUsGWw4T2e5j94hMYcmVFyzYUIQUiSs25Z8GLrccw6Oe9ykmNMGWqFQ1RW4OGRU1Ky60a3vEmYIAAyQAWrwniVLvx0mBy0RP39+Ggdl5NP12dGMYqY0REvSNM1yubQBLk+26XywjY5JGV/DbBFSSIt23syb58MJ14G8oYOqYULphhy8m88X08lMky0XS4np+aOz+w8++vqXf3rYpqdPz2EDVBOUnjpUICMmFzwbiiTNampcMSLmmBWUmJgZuaQjKqrMFSBpEZNSNMtgAMhExqHMmOL6Jf2Q+20CQPRsovDMHIZqepAkqTwTUfJOJcYkjqrZvAmhHWKuJsGIhhghGU09EatZ21a1Hx49vR9zvHPr1Zdvv/LVr31pe28gx09On8JzkMMMDqQ3UfXgGMHQgSEqFS1TAgDIV0gsGOZoaiYFOdn179qVeX1xnSiyNYWdpQAIioxgInHt53Xqcn++qm/OX//xu6+9feuDj37w4NETZDx+6Ygd5QhcMmYgRcimMeZuiH2fcy4nhaLIasiWFcDENKtkAN1sIUmOEQjidNI3zTz4EIIHhjZQ0zSb9RCHfrONrqrOL88OZtC2i8mi2Xxg8xkEYukR2QCsrupsGRi99wjw6PGzg8UTPfeph+gEBR2TGhAQIK+7wYaeqH0ezuioeXzx9NXb9976sXsGYi6e/R+boYnVHBiAowoYAakRCgIpiB97o21U9r9aKhEUi42GlXbVEgfYXsfRFEbOK468FkbYYRZ78ARwJ494DeJH9AZJdKzD4BVkBlfVhmvLdalLjHgLqUZA1qPjxcv3bs8P6ySbi83JfFa3jdsa9OuIaAxVUr5cXRwuG88BPaeum9SBiDMqGxQeU1TZbjYoVNWeSPq4Jm7efv3endde/e/+2396+JV00B5+evqcHACAc0RgaVCWKEZIbr6Y3rl7q2lCqLm7iI+ePnrw9P7paoVIzXLip5WKbbpNH6MNvSYjY82UBska29C8eufuBKddP0hCR565noflSey/9ft/+Ht/+K18BlvrYMYHR8vYx8vLi9lsNp3NhmEQUQISMCQDQSvIo+1JVdfQq2uAZMG6yMbGfoOdncN4P5WuupExRJ6QCGiPMKopKCgiMrPzpKI55ZyLBmIJC0Y9Ow4BVVCzmACULn4ictlENZmMxQvb1f9VgQvUXBjPYzMpkEHRZjEwJC5K6lc7KeA1aK54EgABEwIyaEZENVEAoMCMaMnEpEjC29iXXPI3Ayr2suyC64eccjIFDDtdfCzDtjPHMChFEWAoQgFZRMchL7gfW6kk7nZeIEBP1kvM2QdsXfXB04/e/+QTCj6DxKKukXJSywBGROwcepeFkUQzCmu0rIpkBIbZSFmBRBMSq0mWPiXLMphJE3g2qWeTOvWAirnPq76rDZr5y8fzl46mtz55/u5v/6tvQgWBlyo5xwHECFAkFQtSZmCgwsvelTX/nce/b8T2xfHF8Vccn4UDcIygP2eC7cJZAECAuLH5IrjaX553YdLEQdKlfvLh0+99+9Nv/MrbPeUcT8hMRSUjKDe+9hUwp5y3wyZvus1kmLAPTROmGtBUddNt9PJimzZWox/QT6beGSbIl2cXFyfP27paHi6Ol8cGNpAwEDISeRE1Uc+urqv1BtXMxLJkDDYMueu6UQoQqWnaEDwWeA7NOWSiQFXV+H5Iq/MT5Doc3fB1XVUdMyOzKiWxro+z6SRLKUAhASGgI8dMw5DbtjUw56GaoKsVXewyeEtgSdEzs1BZ17QgQghgo7wNIpOvvJrkFFU1m3pEVR0k1hzqts7Y+cCElHOUBODAeZ8lQoYkyXnHzpUcw8wyZKRAyGZoGUDAV867oGKpS5oFkTg4MEjbdJpPCelguQQPQ+7PgNRysSWPcTDkQgW3sch/rbhfFGF3P1+bH1B2GrNdhaNwNQohg3b/AZqDsgAAIABJREFUSYiigABEaqNGdKk+EAEi45hdlpoP7lr0d5vpqBL6QuK5f3C9JaKU9EwMCZkomSCAqIiOXl9GUIrJpJo2AAjACJ6AGYhERVO6sZyenq7/7DsP/+F//mt/8xd+8d7h9PHj7x7fmm+GE0YJjrbbC5hWQAkgAaiIpEEyMkio0AV2NcwEBjSDVLzoIrrkSGpv3mh6624VJpIlq3BFwJwlbzbD5eVFVj28ebA8OgpNPW1aZ17S5vKiv7i4DL66eeuGCiJ49t55BU7G3oC67fZ5Gi7OL+smvPHGq9PZsp3Oql7I9+SRAxMqAqU0NDUNAzjKqw289vLLf/HHv/dk9dAf+GHdg3OSooiM6VUCQEMmdr7iarVa8+6S4a7RlBAVwZwxYRZIKXNgYnSegDw7F1POERwYF4WE4OeL6fMnZ6vNCjtAoaaZ5myQ86Nnj248bv/aT7199/arj8+ePXm+XRzrG6/da6aTx4+ePnr67OH9Z6tLM4Eph8azdjFn2crQdd32LHGFTy+23/i5H0PCi/WF9pkaOn0CRzdx1laBPRM74paRHZxeXA5DUgEfquA1sgWufeUq75umUsnbbg0bAKBQ+cAegTVmVcxJunVvph5dwgwR1IBYiRwgmmnOeTvIYtY0VW2AurGY+tDUVVWLnQGBMZgAOQIiUmIiQ1QTBEJIpAQAZCSgiIbIjhwimYFlzXkXFOFImoWdT6gZqBZVa7iqn8I1etN+ESq9dy/EG+PzzVR3aNdODhXHPsE9Rlywo+KXvVsldmlFKTYWJlhRw8Cdn7LtZWdKjoFjX6SRkY7y8jZC2NcWn/1ZXmu/s6vfXMtp9jyizw+Rds+0Ylq2K+LbHr2yawDctT8RkR3QM7KxTIsMxK4wu+MIlOUHS4p8Dc7fLVxlPIG5eMiOYD0VH0UY++Su809/hIqFhFdLb+nSwEIh3Z/4Ltq/ftkLiH89Qdy/flH0Ln88morv0a/dk8wMq68sAVRNDIv9+ChWdUXDHa3UR3gKRgt0RsAAnomZHSGDgWYxZ+BNVQCBirqWWWEwACMTs+NypKFLaciWqHK+8diQkCokY2DvlZSQqqqCYNnEQ2Difhs325VlhSkAAXio6mrWTD35AYZLO0MPQJAAvKfKN3dv3qXMjz98dPrxGW1w4tvGTZ4+fMpEZgpEzjM6xIq4pSgpcbr9zq0o6Xx71h409az2wfX9sF6t1aypau99SikOMaY8KtUJzOr2+ObN+Wzi2GtO6/Uq59Q0zWy5AIBt13V9P0iKIfa6Nd06D1UFdYMEvF3L0Nm0bc3oYrVuazhs5xTtlRtf/rPf++DT9065c9qxDcJMxGBkGfIoEoyA5RrLmPzBnqq3xzpV6+lUck6WgNHVFKa1OUkWlcEoGwEHroOvpYHOtts+xmhmigoG4QZ85Sfevv36jcv+7Onlw/tPLiuCg0k7ny9SxmfPnq42OWdwGJyvQWDYDNYlJA4T9K2+cm+piU/PnyHq3/6V/7jxk+Xs4GBx0G27//G//yfbsyzQy4XZAJ6ZeGLmU9Q4DKCZAjkmR8zkAlUqst5coAIjMjgVy322ItNXVMgKBI5AoYRzqAUSrZGCmU9WwXwJ7/z4K8d3lrfv3EgSP77/0dnp6XJ5OJ1OY8xDHJ6dnNftNOZ0cnG56RIgEJBDT0wxZSAMIaSUkEA1S5a6dnVVaY7bdaLgNtvsHSwXk6ZtPCIhIVjf99v1ZrsRBKhqrGoOgaqqCq6eTObBN6L5t3/z++TAeVguYHmwyBLPN93y6DBU/Oknzyts/tpPfW19MvzbP/1TiEAQCCj3AwDPF5OIl03jq8ozEzub1PUkNF9+40s/+/WfmVXTH7734e/9zrf+4He/O5xDQ5A62GzI85z9NMZszsCLbyFMGQN0sQNJhJhStpgAoKrqdtLmlPq+S4MgAiKbmqXMpeW6lC4KxW/P3UcsWvGIRsyGKlrsdQyYiUhjqtqm8j7HFLc9iLFDBEvZ1IAxAKAU+04G58kwGygyWADX0o3XZ6+9dffG8QIobeJzkU5t2G7PxODGQXX7+ObhYjGsc9zGnDM5qtuKmFKW05MTU5rU85eP79w5vrVo5iGb74yUJ+304OC467PzTTM/pNA8XF3++u/8m//zN37r3U8egwf2MJm6g9lyMWuH9foXfvbnXn/1nnNsklU1Snzv/R98fP/+g8unPJm0beuQCKB2oXbVzenBT3/l6zPfPPzw/vb08pd/9hffvHfnznJpSWrf/skff+dwefNgdvvo5t0B8B//T//zP/vf/+Wff/j+5GjZrdY6xzJujljNVHJxaXHOIaKJmiEzoQpoFh2daMZ2hVHWF4kIiRjRBGPSElJ7dsyMAFlEcsopj/12DEQUtwoExEAOgQwcGAExACG50r5nooBGNk4DKHRsNLCci7l5sQFGRCRH6AFQJNsQIWvJmEqdghHRSlOFblm5OHSUzxHQO0+ekopacVxXM2iq2iHGPqYo3vnAQUVMKSfRqGW6mSiooVmoHDs2s5QkixRWFDjCUSgBgezg7mHKKeYhaXExVxsXVSSCYjwIYEXrihQYCzcZFICnFQbnPDtymtKw6iRmRGTvxAQ8cWCVrCAhhNpz3PZm9s4bb37pjZf/yX/xD7fyfBM3T8+ffvrsU6rs+erkwwc/POtO20XzwUc/rNtW0M76rTI4pIqw9a4JIXhEMSKdztvJrAmN++a3vu0C3Lp19PJLd4ceLk62Z6cXue/fvPfaT3/tx599dHFjevdPfvfjf/w//Es+g/SpD9AW6WUwgZFpLYA7N9hdkPFiQLkPWb44vjj+Ax+fx2QZA3Ak0F1gD1C419cmpkLjmn4bvQvO+WHo1UXzCLX9Z//gG//JP/iVn/n5u/dX3wPfX27o0ePVg+cfdelitX226k6LVbpzfHh4PFs0iPr++x90PdQV3DiYeGpky/Pq8Mb8ZkPt5nz79371752tTtCUEC9Wp1iXjmgsrV+ACMhDTOcXF6vNmpirqg7BuUaSbk9Oz05OztabzgirugawUDGS5bxVGaZtNa0wWASzrPr45Ox81YVm2iwOfT1bdfLx/SfPTs4UuQp1Xm+mk0kzbc1jl4dVXOWsnpEBAsOrt18n0RsHt84u0r/4F39R19D3FcgCLDx9crZ5fgaI5DwaSBcd+3YaDNOQUswGDsB5cIVeSkCpDmG5nFWVi6l79OR8fuCnk5nnIBFWF5v15VY6gQSAQIwIjIimIll/8Zd/4ZMPP37+7Cz3WaJYHFkUZECleoCsTDZ2foGfhNmy9Y0/Oz9p2qaeeBV8tjoLDhw2mlGSpEEgKaADYBCF4npWUkZVxxUxIyJgsiJqzcQOc0oxplyCdgImZmI0KxV6FTEZ202o1CFgP9lGKkj5EW2kJpeUC0tLxDXexA7cKtG3jlO4UPVx9LoSzYbmKx5y184b9JBkKMUhR2hqMphcInMQVvKYKwYySMNB/f+w9269lmXXedg3xphzXfblXOrUpau6+kpSpESRTiTRsiwhjh3DcBIEQaIgyIMCvyTIc35BHvInggDxS4DAiWHAcYxYgQI5ciIpUmyL1oUim012N9ld1V33c/ZlrTXnHGPkYa696xRJC8lDYj/07Eahap+991m3OceY3/jG963Y8mYzfvN//J/ePr8bNFt6FGTrtDcMSjul0TmPnnbjOGb10IWmU6acocaLtl9IyxDyomUqea+6U98V2pMkabyR2JZbu21yoWbVZ8bj/eXVuN9M47Pt1adPnhZ4v1qWUqKHhtrt1XYcUt8v+35ZShnT8OTpI6XS9u2QxudXT0mHddtYUXJdnXS5jD/15T9/7617FuJ/87f+9uVESRYmzf7q6uuvn//sl99RKw8efXyyOv/Gn/83/87f+oe//X/86f5FLGP0Im2UnIbxxQ4GkgbZPYMptLEjMzUtJasnYo8xECgXlcAUYMEpkERmQbvsuq6dxmmz3Wkp1Eh383SY9gG+XC7v3rzz/e9+1McluZTsZpbKPuU9zL/y0/d/7pe+/Afv/U6i4da9u29+8eb919/5r/7rv3dveT7t8OTx1bBXNCAgJjQBpWC8QlyCgJTRNpgmoODs1uLOndvS0wZPnrzYXJydnd/sHH61u1yuFpe7S1Pn2E6jqmEaimrTNothP5TdsFh0bWx2m61NIFi/aG7dulidnj5/8uzTh4/SSMvFQouOmxGldqYCCps1PJhJqvF4sQygCW3bNHULaWammlJ2s9g0bdM2aG3SNOVaPSwpp2kiZ2YWFiK4ueViZlqMgUqPYyJ2DtVb7EChqBgTZqvpynysWn7VFoiuC+LaywbFOSb85LhQYWtVAGBimUUiaLbcqbwdZ2fb2fEXOzngdU1gIhaIsJrlXDKq0IQwzKo8q9YKJYkIhwCBGzmperVoZKcqh6TETOTQ2scKwMk8cDPXjg+kpOt/P64VtUhYT/SwzDBZZY/JkYvk1QH8cEmY5v8AqGpFySuSlauStNrsKztryuNIS63EN8/m+pLaCjOHNxLnwzRXUy8uJCJypJHW41FVVT0SDmaHCg7zSnnsrXbPpXhRwGOILAw/CMaqVYRRWI7Q2PU/a6kCtTpzgDXM7Gi2eKRIhGKZAGOd6VrQlygZAS4H0xcHc6QadoScCDRu9iHE6M5sDHZyd6vWVgfdJbL6zxpffO5XJFedFCCRGAJLJAghEnFwcQ40N8lGCl0gplbbAPGEiUPmRDIrIIiwkDTUEKNgpZ6JaNUGddtvdh8PH63bkyaGft0NeRw0exljH4TISRyuMDP1AQBkyc06Bm6UbLlcpimPZRNjMDci7tum7Voz4yDiITA8zDRVadibMviAaceALNgTFym76WpKeTfsp5SMrRikodA2xNnhaszSNK0LARS32+00YdF2VgtXM8QKz+aFqlloZTTOlG+vfcW19QMzquzublXtrt5zY3It5gozuGuiNBI14MBwVye4m3oplnKiRFa8eotCXKncPL0YthNpPF2fP9s8nnZYniEEFpGU05BKmkAMRdFp31B3erLuLvoo0Sm99lZzuXmSBl31J8zy9Omjk9Xpfne5Hy5Xy+V/8p/92kcfffjH3/zWH//JR8rIWTFdAS1RDMtgxuzVLd5hPk4JQBuXFTGEwrNadiYKREY+q44zQ8hllFDdA0yhcLMMBNx8Lb71hdt33z6dytX3P3nULxbdKtxsb0Hx5NmzPFnbLYIstciwS+POS0G/bPtucbpYs8jldnO5uUwpqxuDc3HLaFsOIYbQEKXdkN1QMsYxg2DCIUgM0jbifSxJ1cCEaSwlo+SSQnGnvlcJ8e59bHcQwenZarFsttvURKQ8FpOuY3Z/8ODTwO2di1vPnl6WpMTCFE21FEjTu3HOlIuF4gyNrE9ePP2nf/RPbl/cvPfa3V/6S79wfmP9/h+//9F3n+4eAVGWZytCm1Nqui75kNJY9hQ9xNAai5cUQjAmK5at7Pb7ut5QXceqiYPMyHjlxlBdtGbxu7npq66ZjuIzjwOVXuUAx1Byhlok6bqmJFUtWmYov3aNEjusuCC2jRFSSUaA4qu/+I701C1EMTGXGIWYs7qESJZLsd1uTwbR4EYsDOYpFTVNOQMEc8s5jeM4TH0o1fU7wLPpOO5LQYyNW8qF2Mr9127//J/72fXJ6vnmUhZ84/xsvVz2baPDcHaygieYSOBxP3z/g+89f/HMPK9WK28CoDknVy0+jMDPvPnusyePBrQni9UX777zxr03LpbnUx72l5ubJ33bdGent5q4VEPHi9/8rX/0/PKy6XqSGFZ94rE6K83enVXV/CXFzWc2HHwOguQ49tUqQFC4u5JWp/XYhKayX0WqbJQLFEQcuJRDsuGz4tO8XyTAZjyKvZK53Q5U5CrnXytncwV0puaBDpSK2QjRaQa8js/DNSKFA8av9JDOTR+EIx2cDuQtMy0zl/jwRuaSZ6553YI4CTCbo5DPRNNa6PaAamPETsRk7FVD3YFXpCbna02z7i+90qfJDlThGVdYLU46MyRwPeDaNU/uwiHERrWYlzFr9T94un3+Jx9s0sEgbD+On3z88K2v3Fe3pusWWJassWmICWZcrVbd1T1bCQUECMwJKVGTENt+2dd+CSslM8W+W/BZFPD56tbV0/Sld77+3W9+/Mn3X5wqhglOgWc2GvxAXafjNX75bH0+Ph//Aked8dcK3nWKzuvJy/cF7iptW7W4GyMIk0h+708+/t9+4/d/+Re/dtLf2JcnixDWSwuPedxuQsB6uX6xuzxZn4BZJArF0PD56Xq1mGJDXRcFHKjtmPK4C0IhUAC3XedqbsbSbDbPQhtijMQwLWMqRcuU8jiO5KhCMO5AMZiRGqxK/nkpqeQCin0Xl/0iSN+1YRkoeoFbKtbFKXAmlwAhc8uJrQSCmqKkRd+GwLWQQE6t9FEQmDQlODHRYtG3bSAeFisfxqwKeBZuukW/i89R3CwxEwIgDvEYBcGpeIaZgBgQwWw4XKY0wKVYWqwRG855GvejKxFjsewmmtK2AGjaxs1zVmaTHmWa0pQ1FTiYWY90AHJyqkosZERV8ZSMnKxYmpI7Ssn7QUmkbcgdxbMTGTuqCw2JkDixVSPYOW6ZVe93rruNwoLqY21uxCQBVY7a523cYddMtVZRs246qHvWoPPScx14Rdylcjro0F30yiP6yiNMdEzTAXIwyNhn5i87xP2gNlN3ukZYL3vbQ1sJqyZbVk0p0GbafO3+/X/7P/rLJ8swjc+DsPs45R3TFDtEbgYdN7vt5BOJ9IsOoTdv0qSu0oVFREOIAqoOMBJc2VKZyAVOYsYEVg6ITswe3RQaAnXLrkmKk2Uubm3fmzoVRqnkMgRhIldNKU0GL+Y65t00jrlEjtJ0HMq437+4Go3w6NmLxcU69CsOWMWVSjcaT0ECdHf1VGFdDKcnJ5pShSdU1epv4JnRAwqzcgIccPNCBIcZykw8YQLAgSmIsxk5sxuZERga3ao0vjlQfNwnU53BXNVx2nsmQcPciITgrM7Kqpb3w/7uvfuDPVucsBbbvtjQgAy3kVmFoAQ0LBLZirkaxGHkCoEzmk5s0lK2eOFbRV7daxaMTgTFpzKkaWxaiSEagySMplZNiOGq6mpwkHGk0Id2uepzzgzyhGkzjPvJCqI0cPasKCAFO8EA9SreMQvamnd9lzLnknPKpWgQIaIQQ9t2MTbDMORSmDkXLZN6USYmQnF1M5Lj5AVQdR2YYDDiI3jh7nXhc9jLRjB3o5lj4SAEN3tZpTx4nxGuW/68EgN+dFwroc20fQCwoyMFDmRMkVB7ATFTm/SYocIZfh17Zpohn7mrgJncYWqOAhdmImKpxEpzq1I9xLM4by1w+mxuVUqZ89sjXGV+PL6ZNkXkPPv/HM6zKirVDT1Ttdmk4HBYOZK8ZupUpTT5XFV1c5rLAvV9Rz/4lwDWkX517NM7XESmawQrEIRYWa8lg6+sZyyzh1LF1+bGCffjOjgzT4GXYfpIiMIBNfuxr71+g+fbfu01wozlHTEvAKG2+x0klclnya4KofGMXjmTOx8As8PbCYBBtS4cqHokpqUYnInEMbeOEhzOlfKHGRfMVlggkSWG0Aga0kCzgHcgV3ciEgK7wTKSqmRNagpH0zXJkwQWERYmp4DYY7EfdxSxWq3bvrO1DfshT0WzhjacXJzkXd5eXkGRBQiVC0IEJqHupO/P+7AM2ad92o26d4IpSsoiiDHCkVMJUeoNiyG4uANCzCIpl5RymkYGxRABFw1Z05TLUCYlYwlTGiMzCUVmIiUwnJvYUAh5st1OxwEnC6gZsqaSS1ZoxQfgbu40P+jXdlBA5eHV+PvSbuAItaJOvypAXG+uGhkTmKii4A4zK5Zz9uLqSkISIkeOEs3s0eNH93f3zs9WN89vf4eeMqEULaWoznXHQEBhTzDoPIWKTylTWeTBAxo47y73f/pH33ntzsXZ2VnTSiq7t+7fv/fmBYV3v/TmPd37pw+eP/jk6WePX4zjVKxDUCsZTkG6an3pRcW5epaZ1TzFyyxGIyCBiItQMCIzYnOFK5Z48417t+5crG/1pd00SzWUrJOEMGmeUmYEZilqz6825cleRAy02U1X24KAfiGMQBAicUeaMsAQMHtObgk5mvWgICE0oRL8taScQcZNACwIdW3DRCUXzRZiIAKxE1HRMo6jSFxIeP3eG48fP44xXlycS6CUps59s91nA5TaaI8fffrWvS/dvXNn2I5X076J0RDG/ZBzYjPNCrh5JvahSanPlvHs0fNPTx7xV8ONG+c//0u/8JUvfvXDbz/45v/13icPnky7HabBmuKkjoHZhMQLUimwAi5c6X5OblZKDiIxBoRQSimpgBCEkOe6wXElq4tpXRXomNAdapB1VatVB5FQUrKSpWljECuqBcJSxUDcoWruBZFDg2JT9owWNy/WNy5O77x+YzteDtMmuUsL5qKWUsk6c1YlZ4xQKhDEtusINE3TOA6p5K5pHerF0n4cd0OOvVAjJASMKQnvTUli25hBy7Jrv/zu2+v16gvvvvX0xbOHzz67eXEuRJoLVsuGaNoNsuhKts3z59/9zndCiBxo3fTKMDPyEGO76harphNzK+nmrTtfuP/u6+evNyFYtqmknGmzH8ZJp1zOTlcPPnv04YOH//uv/+HidZG21zERAZHAR6sUzBrkAKoj1ZzDzY7E/ioEcYh3UCeHB6cgFESIwSJCrG5mhcCBg83dxNXP/eUyAnPnqvoJmpeUQ9/e3IBoPFfSZjTJKkEbc/tfFReonAlUnwZcO8L6Mr0MvMeeUyfwy2j3Sl2u+pFoRfSZnMHOJQ8o1feXZuF4YoXCyW0WLPbDo0mH/SUJi5BZLd39meSig/k85vy3xl24FRjMijCILATAeN4h0QwxighEVNXhxE7A5e7ywaf6ydUnN/tF5GYaxg8/+ODdr75FRItlZ1KebZ7HtgGzu4qIk5GZqxVQcrVC60UrTKZespHzyWqtZMSSszGo6/tOaNkuz07OF81pHuVbf/jht7750eY5fGQSslkJzw8NRPVu0k/KIT8fn49/ycahAlyHkhmUCMJcxShExIp/+1sfP3jx8d/4T/+dxfmyoYyGlr3GwH0bu5OeovNzNnMHw0GQJrQnq1OzScRjaII3bduxRd1nRWqb3qDEXNRTsnHS3W7s0YXYBonuRTWnVIoWACIcQysShMAUI7eLZrFeFCIyeGhjSmMTQxfarm26tum7RryUaUuEENG0Y9cYhdg3XWz6HMu6i7qIZgAkSACxqZZc7bNiYOK6ymUd99Oi6ap86I0b8Qc/zA5jKqHh0xvrzWaRhiEQt0303gUS2xiCM0SKkxcjplgXbFVzkKml4uJUQgSxllKmpAIsuxPpm5F5qwORdG1bssK8a/v1ySqValKdBSIclMphaee6tvNh01lxStUyTiCHBFFCmnKz9KZvpylp0bpXrMRdqhsedtSWkLoazwt4ZekqYKZgQNO80RImMiv50NpXeSFVVJHrPt+ZyV62Jf2ElfAnbb6uPYj//DG37FABDFwgAQ5n65ZtcFZVuKtqKRYYnCWe0X6crh5fLtbtog9Nzn/lG7/y1/6NX/rFr/3sqkEano0Fi9anYrv9Xty7lhxBuJfC4EAczcXd28CIXeBl5CaApdaA2KpFoVowpQroGaxpejN3IWfRpDmpAV3XnQLurvBu0cMxDWncDXuR2NJq0bHIONg4DFWH11yLqZqSe1KPIXBozWy1ahaLpomBBZERongQVuQoLH61uYyNnN24uPf668O4V81q2SGEKAIWMFeKTI3s9aFxM2OuKgpz7e5lRZ/h7E6z1Y07SFNSNphLlSIxHUeQQoKb55QxYqKJ3duWhSOTRIl9K8Vtvx+/8Re/MfF20M2DTz/57vvf2+3Q295z4waJTGJEwQqnPMHBMYhEK+paDGIFPmGfp2lfck6L2zcW3WrZL1jgecgJqhZiLMXcSbNqdqgXTW7QnKBgoqaJrYTAQs4pTfv9lItZ9sANLEBJsyLXyjIqtFuFx2uR3w+qUQe9ECuVvWgIFCq7ys1hVEoppsJMlXAFUGXl0Iz/zFrP81fD4GR1j28+99xJzQbrzlSv1SwJVRME7oe7dn1V91f15uYt8I9MJTpOOT5CM36QqjoMBlEUQq2t18IrOc0NwVVHTXHoazQDMxxSc04BEbKaVUJT9CZGpjmlrHKh4BmpOySFx03OLNd3nWw1X3ae+6PmE6cZvqvPbE2iaW6mooNMOxOcWPygrX54mut2yr0KYVeW0SxZf6hGHiCsWd3jeFFppk4dXvAjc6pWhWds67BSvjyL+S7WfsqXObC9/FF9ff4hH8Cy44279qmX+Nrx++koo3zYzcyvH8rjeHUEcmfi6hpbKbQ+g3xMxADPIgTOs9rQoSvS4dLFKr3OTBVVMNdcEkAmRLMqQAVOMCvxzu0ZZlwkBG5EopAwAigQQ7gRabgUJ6Zu0XpjpeRcEikraeyCC3V9K2AQNSHAPSe1ojmVNGQVbdA2F12/XFDLV+PVbtg00p/cWsXbTd7lsptUSypZVee4F5zX3Kwb7mg37LIllnnH5gphJnCecsr707O1qeLA+hMRBuWcL1MyVStF1aqDauykXbRO0Nr2Flg8lpJBpY2h71pidiWHRGktlLlDti78JeWcc84wuHDTNGnaHVDXKilUHSNftsvWCHxsQ61MGTOHubLWHlYWZuEgUicowAGheKnK61ZbR9khxAEiTILtdre18emnzxdnzZ0bd++df5DTOCHFODpkvVwIT2lUteLO0zRMw3B1uQkmySZgCynrZVusTPvxwfPh6vLqnbdfb3tmsYefvd8vmr5rbr3blrH4uvfTk/go7jbFCn324hESoA5SRzGDasqe59nuoAgIiILbbDUCMFzcCnq9cXN5cnratCGumze+8Pqt++fdip5ePXz0/ONhs3VK6+XmL0nWAAAgAElEQVQ6uV8NuzRo0/TTlK+2+fnztF5CJOTiVZvJMgabbFIOYTfsTcGhEm69csFytnGfNGjOJcReJJuWnNy8tMwhMkAhVp/sCge7RGKmUqyUUgFhjnKxOqfgbdOs1qth2MVW1u0S3Gx3+92+RLbAoYuxP1s9f/r86nKjKTNJDAKntHeHwUtdsHNbxmE7DlPfhkePH49Tfuett96+/9bNN26tT09vvXnvB+9/9sff/PYPPvrhgsPuaoPgVBmgRJZRvLBYXdlBIHYGSeQg4kbmRlxNICsz5tgyaD6XLw7FyAOA7gf0asbD508pMciQS1bVysdRdZAwMZgkMJhc3F1N7OS8vXv/9u27N/pTGcvlbno6ToM01HojrKWkKSUm66LEsArSV2k/UJCw5EBTtlLIMp2enWvK4sQQnTQNiQOTkLMUKzRNbiTDnkNgaSBxHfnNOxe3zk8U/jv/+HeXy+U0jPsxtW0b1YS8AV5cba6ePdu8eH7jxkUnfWhahWsp0vBy0d88u7ixPllwe/v81lfe+eLrt+4uebG52u4dKHR6epFGff2Nd0W6THjvg+//zf/2v0NE6LoMH/K0WLYHNOrQyjWXNeb5Py8ER32AA07Nc8F3Dh9MQu5Vp9dLTTaM4OpaSuHje4SVirvCDpQnxywu6TQHRvdDsJ0pOofo4ofi+lxXxlxRRpUvqzjJHETtEO5Rhc5nbpNVNZg5Qs4OpDjE5utD3Rykh2hfHzHNSkpQFzAzCVjJzOlQbz9UiLweQnW4AQlxCKp26DycD5ro1WxoHse4rnQ4fhwW79mBlk0CTFGVgV1gXoqaMxCEGLXXMkPh+L3/8/d/+c/93MWtcyLa7XYlpRBC13UJWcYQm6aYOZFwBeDMXa2gKIwonKyaGODmxuLN2fpi8qzAmEog7aNIkL5dnC0vvnj/K//D3/yf/+iffP8H739arkSsJThID02/R5YBAdekuz4fn49/GcaB7gJ6Kabt134EwpQGRY4hirBCzIwQ2HnYlSf/FL/567/7r/3Vr9+4ezv4uAm7k2W/WL0mvSdLTSvvvf9BCI11Ro7IoQmtGgL7ousjGi6CUs3DSrdoRoxjyjn5MJQxwVnALBxDaIilU2KRWEqQYuYhRpYAtwAm7rw3gveLhhihDV3fqpoVE+a26Vf9Gp63FoIIRM61YVqR8HK9CiEKiLSctCHnouZTpgIas2U1V4DmLX7LYjpunl+tm0YXyxDo7r2LDz/auyOXPXEfm0XTsxoJU9sHMqgCYlrlxgKEOAahEMy1WCGDBKIICh5Dk8YcxCILqTJx27IwW5G2iFAUcCkqbTg5P3nttdslWbUJghNJbeRxqlghHeR9Xy7LpGaap67p+tUyIU1TakMT+jiWDDeYHur7cGSdpVFKreUQA7VPngkEMxwMuqEFLM7stbDyyo7JvOY6TFxbESuZ4bgL/PEQcKBAvPrnq/WYeRw3YPXMAWID1eaHmUrmbLENgbkGqWnKeZyYsEuboLhxdnZe2k8eXq3vxp//8k//u3/9X//Lv/INsWm3/zRwmjQtZMlkxjaOw1S4aWLfnfu0c+Ya8IQsxgi0hJYRGERQkBBFuIJEEJSieYSRGkmzaBpypkLmlqsOrUBWbU/uBdb1Hcj3oFDy1Ec3WvWdE40xlJKiiAc28Y40exZ4t1h2bYjNOA7b5Xq5XHUhsnsxBTAyY93169fWwfbDfhfi6fnZ6c0bN7/z3qNp3LODWV0MUCcyGOS4iQTY3dxcydhRa/hURV2dYVASN5jzIZtxTCVVUIAjcwVVJLizqZVUckpQkJiplpQBgAoLdzHmVJ4+efbuF9/1Nj169vCDjz568MkjFExTYRMijhxJHAgKVjcmYTBBgGLZclbLhgnGQCA4Tdvcn8TAjZB3sRe+KmqMMo0lZ99tFV7NbVxpAgCBUE1Vwu5qo9nGMRFK7Jw9NNKrORX35MiHxKzQkZ4440WMtB8VykQhRpFABC2aSrK91QoiEakWcwMbk5CQAxzIITopGIcWwNpld5hLLzGOI/hbDc3nDO0ADx1Y++7HfrpXiDd+SHZfefHHAsIR3bg2l2cnoXnmUUWIJIh7raVWSXJ2qlwrNzg5z0bW9feaVQGaiuyQHbJWA1gRAjlVpBuoRY8ZHXp52PXKG4KIH0D1l3+yXz8FdwfPXt90beGoZ1c38UREs6rDEZ1/5RtsxtLmC3Ud4qFrNoV07ZNeeWavMqHoQJWqp+RHStS1s6BriNJx1E8f+y8c1afPfVZorOruMzj1ozfyzxivvrkevB3W9ONVDbBawyZmErjaEQIUApuTKXyuTqO4zl0W5CBrux5MIrV4ZX7gOh6C0vGBOnQqeCUMw80pEAQQGKu6U3VKECd2YygpETm5i5ta0oxCIEhLse2lCZXsQyDNZdgmHVQHdSMFXkxXu8shdkEaJkHbtOOwu9zi/OxsfXfVh4thv99sNsNuyFqY2UgH3WJ0Mrp8cQUCIiTUfSCJC7uUnH3w3BfTYrWNiokdTpxSSkmF0UoAeS42FRMvFsEi2bKqs9lysR6GjauKxLbpVW3MqeSpCLuibRpCIkHx6hRvBz4lMZglMBsR3Kv3W61X4Th93eHmLFzxy3lxMIfBTKmSDESCCHg2Haz3mFncq/ucg6p2PjkThJytmDUiDz/9jHp7+wtv3D577eGjD4WJgBB4vVqQUd7ty+RQQwEmqCaX0LbNs0c7EaROQkvr9cXUPHlxmX74gwccp6989YspZ/fx/Q/fZ7cgTL5e3V6d3L4wawjxN37zESKQUFIqU8IecKAHDNXqYqYGTgUOMBBe/u8Bb//0m1/7V75+4+I8I2VPFtKkm9EmY63yakqqzhY4e948v9o8193Wuw6B26bpYpQok7pp8uKjN03bgpzbpuPAuZRs2ckR4erjUCbklPPp+cqNTZEz2LBqlakVYcBF+OzstGlizjmXpGbEHmKEEwub6e3Xbp+dn4UgZsWpLEsHapqG26ZL+yd5LO2yubx6vlqt7ty++eTRk93zgUCxafrYltGphmjWunIUQlLnokX8crf54acPk+q6W9xY3/zqz//0z3z9a/e/cO8f/cPf+oM/eQ9LIMFGnVRDG4L0EiOkYO5SLjA4cXWzdJ2VrGpZNh6ewfogMjHgNhM6cHxIUf1KCDUyVKaOqQUWYtJScrHIkNDGEN2hXrIrmDjAg9pYsMQ7P/POl7/6rlH65MEHzqPxwE2RNnCYE4+crYmQ2DWxJ+5VYURMERRjbJpoTciRyq2LO5oSirMC6tOQLUJb9FEElGBeymZn7t40HYXWyIXlouu61XL/pZ9KKV2+uLzM2vftlMsidpF4d3m1v7xaNm0gJrXds8uSkwivlouT1fpGu7jRLm/fuPX2/bffvXm/4WY/bjWnJvb98nRzuf3ww49/7l/9xVVzthvKJ48f/8E/+9bZmyuFjymtT08v7t/88OF3qc58P0z1KlDqxj53h5tXH7wZiIJz5TKL1F6bg2YlwdVTSjUUMbO5qRZiEuEQQg3bxuo206vrQs5GYKaZuG8zekaAo/rKkNsxvDkqSbHWLJwd5M6167R+7mXAhfFLstUcpugAfR7qqD8x6rm7AvCDdK/PqsSuXmEtBkDOPlNNtWJYB55YLUM6ORFH4RA5W7FXs4GfNLx6ClYjd/cKoztLo1Qc5VBTqNZOEKEQA5hGy8V0ZnuxmBkzEwesym//9u994d4bF3cuVquT11+/v9/uuraZPICoXy62eZdzgjADwSoah0o6N3MCNbGzUmDsTn239DzsNQ3j1IWwbCm4dM1i2Z0u5PTv/O3/JT8Nuw0hRXgLDAfZ1R8ffO3vP6JJ8fn4fPz/Oo7tg3SohfzEoZpAYAFHYkNR0uIk6CKPYr/xD373tddu/4UbX+/62MWnN2+cmXTb8XJK+75dkBs7M7FQEA4EYeNGeBE64VBKUc1wY/a+b7MXc3IIiTStKe1jCFKtiJnbliQEVW2KmjkFdoOWYmUStobY2iiNcUBswunpyZRKGlQLGnQNLSUyVi0JiYh5ByyY0fdNbKSPTR9kv+iG3W47DJfixQOTYiYWRCcI8WrR5Inz/hmZEvKyl7feuvt7v/dDVZvGcb971vRD20VQ6Jpm0feeyzgkc0slF1UHqIsURKK7GsFE0DQhRGKhpuUFY7Fo2CUGhpOwkZcQvWklSrQMZgsxxkaWq+XHP/gkpQSFolhR8NyzzMc1nZgc1eYcAOAoaGO7WC919EiRI7vA2UVq0RhgQOBa6kaltgcRIEKzOMyhG6YSvJhmZRozp2oCSDyruSvqvpcOkac+Z7VBYaY1/6SH7c+MED/pp3TEsMxf8kYcAhIqVqwKNXJIWoqhKE7WEEXgNJURCV967c6//1f/+l/6hZ/rLK9YnuuTi8VZUXs+PRQOzTLS6DmXkimGltzIwUTCaijFi3s+kC0cNrfGAMyIkXsiU2ejws5Zyb1hEkIh47n5xlli1KBTHigVc2MtbZTT5aKo9010orTso4gH8kAe2COZeJnGMRcwEcuYxnFsppy0qLQUgGEcp80UFvv1MsSIXHLfduvlskH44Pvfu7y6ZEaM4oIyTUVnm/WKxfBBQqmyUEAGeEVL55yDDEzOtZ6G2TCIUbwwMQkHisWs7bucsmnKU0pTgkMoqlNJ2dQ4lNDCjac0fvjwuUNi6ERaCXG1PL11PnZ8ZqXR4ggOsVx4NKjFwDLuBsvFi0PZ1DBZNXMOEimE7dNdsdA1bbcOTR/bNgZiIlZVLcaENrTOnKyIEDG5GMyH7QCl/dXWldJUVD1O1oUOYAGbKgqQD9li9qq4Unf/RETs2TICqhR1jIGYJIiPPo0TCigQCbnVOUGKXHLGYS9ZW5a8stfhTi8xkSMWcqDwvISm58Y59yPF6WWZ8Brs+3Jm/YT582MvHRp3j4D0ETirWfBMZsIhm2SGO4PnbgWCuVNV0UGl/M8JJCogUnNsM3FU0kjtxzR2YlBdQ65RlK4fph+v9oFMdMRujtSk40eY+LiRJ7teHH6F+nRs0avjyLey2pdYs3wwO9mBU3C8HYe0/IheuftBaOTl5cTxp8d/HsCEl4dxHYy7dr71eeEDQaoeUyV61GZJqkjc8UYevtTJ6Ue+9nAABy7YtQN7eRh4+c5QIamq7O/u7LV36LCJUPdiWrxq9lbHSTAogkS0FGZWGBgGNVJnl0bMjUBmDi/qVps5ix02OUZECMxgKlZSKhUf41YIUA2UaRhHAEbGjiHvdAQyUBCEla3J7mQMVvc05e1m71uKU3SwBIFjKtPAA3qcnK8Wy4URbXe73fNdv2veffOdSYYcJu2U4bGR0HQL763KkO0QAjEo7Q3qJkCm0FC1gbdRi6uagUACZQCWJkWBRypuWlwECCCBOYqVoWQAcF3ghDlygJuMYxnHNOymNKrrRriJMSyXgcW1FACh7ZpFh3bPexvHfdsGMgZM3Q6QARNZzQMqKknuUJ3nXuXTCTu7F3d2ZzexokAuUHhwGEG8GndB3I8MLAYLMZMzL9qeBJfPd+MwoOD85sW0Hobyom/bGJrR8yQcxLsO5EIhaIC4dNK3bff06bPiNmYKib3kLizPzjmV/N77DzbD4+UqLE46bnWzvUp7MMblwlerToRKnv6DX/u33NSLenHLVhLSdLXdPoAVywpFG7tFtzg9uYihB4JwZG4ktswNEIb98Oj543/2nT98fPnZi/3jrQIBb97r33j37s27tx4+evDt9z9rFi0CQ4IxFVUzNF0TQifoYI5StLhaLlYaadu2D22z2W3n658hTF3fEqp2jpIxDp2GMJgihCbGWFR32x2RLW/f7hetbspmux3HwV2apnEjVXOn3X7XxMhM4zRsNs+320wkp6e3AuLF+cnTxy/Isd093bxYvnbn1iJ+/Vt/8t6jTy+9TMrSSOPOjuJsLmowz3k7lq0AglwefvL4s/j977z1+tsXNx4/3r64fXbr/k/d/LUv/ep/OO7+wd//e5fPrj795NnmEqUUpwSDs7GAiYRCFb9S9WK5qBIkxLYu/5b1kCiyz21tlf9z0GPSQw7pICHhusbCiFzVIEwkgVmcwYGDBDZVLeqauQF16Lrwxs/f//rP/TRHfXr5iaHc//KtP/3eP2aJbRfaPkqQnM0QYxNaaftu6R53m2nap5KdQFOy2zfPY+hPVxQId87vuBZPOu2HaUhpP5agRoG4NCF0UaaUdpdX0zitFuuT9TqGhmCcQFv/xhe/8vTq+Xhx6+r2JkZ5+Nnjtm1fXF2NV5syTG/euT/lTMxnq37ZdhcXF6/duX3nzu2L84tl07915024X22ejZup4fD6nTdbXqeMvotvvNUtmxtXZfzv/+7f/c//i/8Se5y+vur6hTY8TtsP/+BJc6+t8QCH0DJXIM0JzizuVYERlRZcN3EvQzkAhZsXM/Nao8uVrsVcqb8AE4IHDhKE55yv6JzEwNxrdbiKSsIr/9AZTqitd3PpZq6AuQcRqRaCTmpKRNVAmWDmRcwOwIkDh5wUQG099evQFfvhJK6PeQ0khhjKDN+b2oEwPydXBDY2PhCpqmbhXGeqGa2AA1Hk0Ia6i5uv8z+nUuRz8ONDSqj1xRCCsRHcXNUANQZLgAOhiWBShQlCG0lgbpHbpm0cPuXNe9/9/mePn37R9Oat27/0F3/pg0/eu7E+99G0lLPTs0eXT8ydmNmY2QrzTLAnAjxlXQIAWXFL5sVzzlMZci7tKq6WsZeTexd3bU+//vd/84e/j25Zer+hMex3hYM7aeVD1rTpAAXyj52y4vPx+fgXNGqJapa9wizCjevEFwfIqKm6E3UlUChNky6XnSuj2/7R7//w189+5/bNu+/87PlJv47x3mfPP8lj9mzM/NrFXSdeLpZ91zUSmxCJvY+x4QZqWrSM434zdWf9ar0SCrEVkCRVNhNqOAYP0cFmlrKVUsw8hLBYtCIyTdNQsuYCSsrJLJkO5uYeHn227dp1DOtIUbwj7TguuuUNdw+BFmXpuhTGsg9tdF+U03axa7vn7joNlz6CgwRpjEBkkEpGa6M0EvYmy1UI0YK0N+/caVuoUNnKbtwbj8uT09j162Xfd92wH7MncmjhPBR1XwXreuHANqhpDgIWdfdilLXcOF8LUVEj4iBtI02QDmu+2gxtXAbudrtBKLaBT89WH36U2j7aaevGZbBcproEz6L3VT+/Gtyqc5hbNSBkbIYS2mAC9VLIolTODRBgjCbGwAFKhaEpy6wqA6qeIs5QdzUngCENm1sxhysIJBxICGRuNVtxQA+lk7k7RniOIX6NZvL/bBxorajNQjjsh+srfuA5zBxpppSTki/X/WK5ZJac1VOhCa+/dhYgq9Obf+Pf++X/+Fd/9Y07t4fd08tPP21vx8D5yfjRfniRp7JenZ6sLpplT5ORiaNpYzulfZrGSq4S9oLkGGCiXrtsjM1EIrH0bad0akhq2RxWWgrRiUvRYV/GXcnIxNRTR2o2poSkVph92bfLthumLBJJYtu1H3/6cNKyz6M7c8NN08zCAxxO1sucx6Zfnp6enZyuTuPJ137mjavt9PHDRymnjsrZ6Wqawp1bFyfrtUK/+91vXV1BBG3HrjTtx2L5sMOtMpfElbvicwYEwLnKn8EJHgnBnKzGegqQwF71WAhEQsoEb0OPQqVkzcWSIYEEAipJVVxYdEo7HYug7PDt974b1/j00Sc/+OiHaYc7d96g1E17ylk5eKFkXsDaLdvAMm62NmUKDcfoKD5XFskmY7fdc9sNqQzPzu629966db4+NTaF56gNhz4EpnYa1MZtYGpi48F0LJvN5TS47REEWuAJ0zRR38TAQcTVyQKskJEXp0I+06wPTzVRt+yzTpo1abJoMUQQAoKSFhQvDoeEGKI4QbVo9StzABDmOftkUncqdcbNHHiau/nogDW4zeAiQId0s+Z6s5cDHYUYjhOM6s370Qn1YxOwHg8xObHLPOVsTt6IuXptE5GZHuciQBQAkGol/fOsSUUCV9TWsBpeDGCy4mAWJmFyJlMn0koToVmX1q8bYwMHNVrHoRR6uBpEqGXmw9nSscWPD5K2BELVeJo7KGZdCwBmcD0mpy8779zn7un5bA457gyYzx0MsydgnTpmXpuEya4luj4b+L0kjdZsnl/BlSpGdBD+95fdnwew6fB5v6byjnrqBp6V793c6lXSKoGPIxvvEM8PR3/9t9cl3mfF1vlQg5mCjFRmYEltvoIEU2gxy+5qru564AxGSIzCnFPhYOxV1d0qxknC8zpR/QfMXKoC1gF+NDi7s5ibK0oVRQmAeZQQAhvN+xBzdfWXYi+G4mZT5o7BDgLD1dRywUBpdJihQeQQY4NgqaQ05vOL89i1J6fr/bC/3G8yigWXPkZB0aww1WkcRoeHKKxMgKtjmoFZLUZFOSBQIGOxQK71oiIwDKzsgGdL6nBwy00roRFmKZ6JGIIQmmEYCBZIVH23nfbDoFmsxGGXodPpjb4LQYQDwnw9YiAidqlM67pzISMmrhAxkVTyRV0EHF7qO2eaNEuV30vFCa7mmdQUxTwQe+03JHN1MzeC+AGJRuVYsnCMoZTMk2yH8aPvffLO2++kND54sWHiuhyFIKtVv7vK066kQZHBzmpl2E4lN4tu0bRxKrsnjy7Xp81i3YDsxunixsU5x2TI/arLUAxlN6AMu30hR0w5P3j6A2G0gRkE577puh431ksRBBIBtaFdL9aEkJLtttvNfhxGTVndgk6L7XbY7DZTGia1UgRFobjaTk+fb85u3Wjbkxvn6fl2s91MHTVN6NcnwcswDAXBMqWcy5SSe6nPr2YzBRNrLuqmpq7ujBCigNUdAQ1zjG3bJNMm5xQaxBhFZJr2eRqFNeWTTttcpv1+2G4nAtrOtPgwTCnj3WVfWZ3L1XKxXLQvnjx/vr283J2drs7OTjWXtmn6rlcb21beePPefr/L03B1lbbDfhFOrQL+ELXKfWcKRhEO3+yLBJyG5fd++MEPHz547eLR/Xuvf+HNN04W/TRc/ZW/9heeP33+g+89+Pa33v/TDwdsJ0QwQ4hCaMxUgjCJZTMzOLFICLHKXqU8HB4XAOwMsrn5mOBMBKpseXMC+2xRMuPwpPMzVguwilGnkgqqMEGD9hS3Xrtx87Wz7iQ+3T7wkBXDpOPVw8+GgohMkQxV9Mqb2DSxDYitNG40DmVzudteDTnBiq26xenJoulWi67pYsfRjbJOZdIxFyMgwCgGIx5TKqZONk4j3JvAq5VEitA8babz5WkHOTk5v3NyQZGX/bLr+xeXV8K0H0YlG8YxxijFV01/69bNWzcvzk5O2qYTcHD3glB4EbtFt2Ti3Thsr1SkPTm9fVmmMetmm1Fw90u3Hj59zGVarpb96XLTXbmXIwHYX0KCLoei11w4mvd5dIj4xEZ1zfRiWqqBrMOclGqXuNnstsQOYzd15xofhcmNZ3dhIjImmUNhDUfsZFUisnqmoMLoh/ISsRysbGfEjSvMCXBNeyqT6XCwTkdOOEFqz2GlBHNlsNeiE13bGuDQv8eH0sshJ5ppzF6rsADCwdZC2OHzblhAgUSEG+GGnFHM5kLeK6nTgUaI484GB7fNQ1GTPITKjiq1peF4B3DYv4QYpA3SRYPlMjVN0y/6nCcAU6HL7TAMeblcv/Xm2x988h0RFmLNk8iSK5KHqnMGYbaDRirDk5ZUVFMh2DAmcp/GMWNQLSy27OI6Lm6cnP3gk8e/9b/+LgKQyQuEI6OA7QAY1oxSaN7K+f/bDdvn4/Px/92YQQC8zPuvJbkHGMsRmlhKUiiKuylRcHMGl0LIGHf45j/+zq/8yqev3V8vbi+bgIfjx56sDZ2p3bpxa5jS3KZH/zd7b9ZrS5Kdh31rrYjIzD2dc+5QQ1dVs9mcWmaT3RTZcpO0TEiALcCAXwjDL37yi3+bAcMTn2RYEiRTEGnKkiiCbE7N6q65bt3hDHvIzIhYa/khcp97qrttwYAtv3SigDrn3L1z75wiVnzrGxBjDOBBApnX0pJMKU+zqfddJ5BOumxlznmaJyxjHsw95zyOp5xnItqsN4CHIKrB3MwryExrrUW1mGqpeZzK40erzXo1xAu2nqlHWrMkdUskvL6IciGoKXqMFjwnElKfwiHyXZ6/8Ni7J2GJwqqlmgYmmGsZh566zggjUbfq09UFSu7yoSTFer3K+cTM4M6lFkwVo4Q+pTjrDEU3hK4TdSWy8/hn5u4VZnp1sYZbLYWcuhR2213Jdr3fv3z1vE+7LmymKWv1vov9p+nm5uXhbtYMFPh4zn45UxTcfeEygGvLxGJyeC3Frau1xBjVVNVSCD5Xai0aAREFYhEBAy5EzYAAgDsbUEEOUpAJibCAwC1h3dThLETMpFgoAe1+up9MfdHCc3MNNzkvPx5yGOz+Pa9VJu1+XNZeeL2o86ZMbBYzQkxmxa3pCKzFs6ckm9V6vVqj2CmdDL7e1Xm6/vmf+9Zvffu7v/IL33i82gxKKcbt08dZX10Nq8/uno/jIYSUNY/TKfIqyEpCgnMMaZzKeLpzKt2a+1UgtmonRqBmYWksJOwiFCMFwBVF2QxeHMTB4KWM01RPp7F4bcKZaoUh7qqlSAp9TBKScHYnCil2XYyhWK2llKqC0BZ/6mDSueRxyoBd39xIrOVi3K5XcF9FaAaqPbpc1bq6uNh0MSV0L1/CDDFy4JBnEHutlZxFAtRboE3zF3dVOLMslGqDMQuCIWAxSxFAHIFCFx1WyyLJN4OZaSmoTk6CoHMBwYqRc4Cog8yJpWb1ZFhhvz+tJOzvpuvrE2uKQpY9TzXPGcEr5amUYuiajjUC1VMSMqrVFO7kVLWaRpJmCJ0p14sgFJ48euP2dH2a5lqNjFwZCHWsWowJw9DXqRZgzGSjI6MSYCAX8UAWoEINHlCHEjm3gE42MmtuH8zEShY5VC1Qq7WqVTNr5lXzZsEAACAASURBVOQiYmamJixD14U+mnvNmZ0M2nIhrLw2YKIHWTf0muxECwmn8YLujULhoHAuK5ZKcjFDJfrRouvHtnv05MvzAp2nA/9SjfZlto65tqjQ9g3Pf/czzky2/HZWOTQ/LzZYq7AZvBRyFWeFyQIMLZ/UKIE4H03bvapiEVsu6Ezb+cIv4vOkdmY73ZOTWuULAHZGcNrhGAB62F28J0fdA4MPR6D773IGrr7EpbpHi+4/Ar5YbT88zw85UPTl7f4SNBKZ1cWZdxkHme8vTPOWev2ROM8CZwzO7sdJnEld9CXg7Py+853zWo3oAeSmlk0RRIStqpkFDuCo1efTjAqWQAqvoKZqA7Mzo8WKmHrz4IXDmMBMgQXkxah6gZPrGSZs350I8Jb4vvy1xce4sXuSsMSCNFcVQycp9NEJjQlgbDFEYxURBpPcT0LLSa6l+mgMko69et/1x/FIIFTqJF7fXgMeQghdqFPOeW7tPTeUU00kOmvNTgYyBmCKklUE4CWHrX1hIoK37k4AzNTALpHvpYvZtZbaAEsQTodjYGIONbBpqRWBZdj0VOW0n47H0Sw+GS7WQ9ApmkPdXZ0CxU20sTbug51j3M8XvgU7tgXOgs1qo2Esz5iH1Oon1VoX1xcCBxYXAsxczQwmcXk43MxcQcISa6njOGWa3HD90WnVbXeb3e14cdofYxdFYkpC6GvWOrd1GqNQ0cxgaEfU1UnzXFliUbx6eUhrrDdXu4vLm+MzADF1l4+3+/18zLc3d5PWHELo+jRNd6u1VEBzcXPIJWNVi0uVPgoFKm6TFtVyOuVXr/bXr/b7wzTNVZWP1+RK1Wr1bOQUPKVIgeZZP3/26r2v/axpME1zxnjCVMp2Fb0ILECxH+dAqqYO71LPAvOaa7m7vSXBnKeu65iDVhNmAqnBzIVCip27dX2XEpspizLzPOfxVPKsqwGHw4lITse5Fjcn4lCqT1M9nGCOl6+uYwqbzerR46v1ui+a94dyOs7jMVqtm22/GvrHjx4ReJzuYH55tfrKO0+Znx8PuRwnsCAsaAYTOQuTQJxg1ZWdplokynE8vvrBXx+Ok9bylTcvNquw227e7C4ePd7+8je/eXxF7//l5x8+++SD5x+/ujkWm1dBiKRMptWMDE5eTbUug2MQN3d1v3cQd5gTt4l0QZytVYvgRu0B4AqgaYYJxdzI113XhwRB9iqEn/vFr/Xb2G2DDASp1FeIWq1Fp3E6rta9mwoHgIq2JFMh4i71naT5OI/H093tcX+nN3dYr1/O09N4tV13abdZj4djnzo3mLqqMZPEELtuWK3LnF9dX3chrlYdK1ztNJ66GLsY2KGlvnz2Ra4aNrzbXRrbO0/fJpIuptW6jyHeHvZqFkPowCvpVqs+hABzqi1mRMfjPB/nwF1c9aTS8aCJQtdnN1P809//F7//h38wPA7HPIcuOjmCq2a4mWrTRDR6kDAxkZo1b01V02rNAA0GsPkCTxGBrVSrsKpeDWqt/ysNNmwi0dZvEoJBS4U7RAgkIVa0uKbzJLv4TJ1XksR+P4M6NTr/QgNzqJqwkKPB48JLqCw1gSPOmNZ5VrqfWYmZo5gZyJuwcUE4m6T6/IlnHK1hZcLEXtxrS6ciJiJns8UUwRe4nxb2VfPoIhCTdCIpEpNCYfogweb1bOJnx802Y7s5TL05rAgx8wKEgRuh0hSh5VnAOUjVCuI4dLFLHCWXzCyp62JMVWsUqOP9jz76xrMXX//6O1FS13WmGoRNdTwdhLmP6ThNZiZCIAYZcWBihkuIVTXnTGTTPG2GlVmNCSmmFAlWA/Hzz1788b/887/4tx+IgF0Od3erLoRgbZJ9wDY7d7YJzazufApeF0I/saz56fbT7f+t7cfvq3b3LZW/LbyVhmDZgzUMQM0Vwd1UnZgkRKI4nQoY0I6d/ub7x//9n//Z1Vvyq999h4TXcfdo+8Zoh+u7627Vj2PO05yiiGgfhZ2FpU5znqZIaejTqavCMYZkMAaN8/HVy5f742F74VlRqsUo8zyfTsdpmmMKXRfrYRbeudWS5wZzp7Bi5WpBodU9ROm6S+GV1jhl1zkXcOZihmHo1l1PjJonzbMllz52kWtCl44p7CVEJRd2wEotzJ6Y3AtczfYXV32141xi4n4cDz/7tbeef1GnaVxf7Lr1+s+//2EM6ApTrKWOShYTUhdD3ALY7FYhyPFwECqBAEBE+n5wp3mab69vUuqmaR76FCVsNpvj4QTI4YjpcOe+NxcYdD1876//ZN1d3tjcx+SACcpcCdJCAd1d3ck4MKSlW9ji1JvnE+kwjblbB3Obc96uu/FYibD4B54nA2ZGEmKvVa25l3iGi6q1lSMHiSnVWiWyB6+VWuo8cB7aloBcImLXez0OiJmJmdmg9EDMsiybFvEDHqxqgIUay34/S7aQE1tWmGACmJyEIry4UwwydH2KEpKw+uluf7q7C67DavU7/+FvvLl+49d+5W996xf+1ppTQBGeXEutI4vuxxt37fpOQgR8f7hLbLvN0Me+ZMtZGWHot0YzqMxTLq5O45BWQlLVVYm5Zxcm5tA5mNzYwOzZDhwYUDWDk3DMtU7TJIFY/GK7rTXDrUuhjx2HzpXUyIlqKVe7XVf66npzurVSu6EXCQSJQnOetWqtuLu7HQbk6fjWG48utqt135fq69UQw90wXAxD0mKruLnd42KAm7iSVg/CGeruicnYHcYsIswgJYgEEqhpqdr4xCTiVNtSiYJA3EjBcIc2LT8JoCi2n+7g6IKkLtRcKZDui0SJfU9a2dGlOGcfy7x6G59//vyK1sdD3p/waLV68eyWazfvLc8zBSBaQa0EhgKx66QYhQiqyJZdNQVxJ6uaQqpzCcxltoDEHp4+epJtytnmMZdRy8ibgW2sUJtrXT0Zxvkk0p9sinCNsMlhCH3q+iFINDPLCoVnQ3EK5MZWlex+dezNd+VwPDSQYsljM3c4NxCrEUcanV/dTK2oNwtlLGF7TYwLI+gDaANnNKe1UxfikNqZK/SwsvKz6RU1Xsa5GXEPUrwGOtrzRHTvfLS86/z3tjdriqgGf9/jVmYtAFHViWxZDNNrE6VWq9p9AqC9flq9meuwnPfvBm/tPpbWu3SYGS88fHfFWR9xrwh0PeNr96l59LozuMAyALQSmilXm+wIoIWzc4/2tP836SIvbdZz7X1G4Wn5Kgvfk++rOnOHqroqAGZpl8PtNWJvbmhDn7aRCszEzYSDGintdfeIzsSoxsN6fVHMnM4EMCIJAYDb0je4Pwl+pt81k/jWfq65/EjP1N2N7B6aPMNYdr8IOZ8rhGX0ddTFdRZEpGpoC3kFFGYGa1kNrWZnUujsKXRGrVHvcFNqsZRtEYHQQEqBlra2aEsWWqKFoYvL4vLYgJebhpgkptRy7sQlSOq7XmKw4mpWuRC7niEkOJYkYF8YjctKSmGzU/I66rSfb8ebMioE13bDjNT3QpRzVa2RU+LOqlo1VEcVKkyQc3CWqWl1hVsl8taMEmcmCQRygYAQSCQQi8DcZlPWQtqScU3dssYQq+WqldCllNwZGoPEboVqhcjNKzHmksn96tFjrR8hwovDPAZpIfBMZC1N3d29EjEzU3gAOTfcm8iW7jpSkvtnYwFnnWCuWdk5kIBgppYV1CjazrqYnh1Op5RiL6tjPSHikw8/vXxzuFxdfv/DzzjIbrctpeasxNYP7GpeXQ0eAHcmPs6T6Qz2LnUs9TifUt9vr3Yhpa522SzE2K8vwOXlq+k0vjic0Ke4cT0cpt3VlshP+xwExcbbgx8PetwfUuRHu0shqrnmqUzjdHM7lwIzKUq1Ut0XcOQAFiHxdhndLRflEpk7QilZrDAravHxUJHdMonHUrMxwZupObO4KeYpuxkF1IKUPHbS7AW0lHlWHZWcJU6Sw2rdbTZDTKyW63SYp3machcppX6eCnw/jiXnqgoBnBnOQ4f1ep3ziYhLqfOUYwxd119eXo6n248/fiUR73xltd6kxlw5jsfD4Q7GV0+2HGl/c/jh924QQcoEhpATkTACuVV3pyAQnoqReeojhfAXP/zobz786Ne/+dXv/sY3P/niozJOj3ZXX/v5X9wMT67eXm2+L9tPe1My1Y8//fTubk+oXtzgoWO41prdnDlyYDi53FOUGepQa95J6os6+6wTNwJZs/J2i7ue2FWLzQojjXW44N2jnoW2F+uf/6V3FfVmfw1xRFNY1VpcISF2G6uFINQs9Ay11FlLErtaXw2pP10fxuMRpjAEwXo1XGzXm2EgrYfb20Rcu45BtRYSZpGu64bVikWCSL9esSGXWqdCBgaXoqYeQuw73t+NLPF0mAy3w3rFkcd5HE8jgYLI2288raopxBUnAdWcT4djnnKgMKQ+xm7/as+ULp8+Xnc7LQA4pYFCt0La6/gP/9E/+V//1T9DwawH6gIzTfORCoUgVs6tm4VNLGASDozmNUvNnhIA2NxCEGZiBgvCYZrJCRXQJg0TMvOz9PjegtPcrAWRg4REgnCQyWa4u+LcJyeic8KH3w84Tt7gMG4v8+Z92ejTLQLVUWHczGCZ1e5Z1nQuXM7DOMgdEsSqw1zN2J1pIfMStW/qcDi5BGqWmGzkaHb0LeH2XEeZwxvry1VdW3kigLRlsEPIGU4LKAjci5Re12UPJ9RzG82WOVqImZkbS+Ee7mFma1VjrU5eJYUYgoi0gA43I6daSnbXUhPH/WH84z/701/5tV999+tvVRQOYZqmUmYhPu4PSWLzPlwgQBhYDK4Eh693WzJDKdxoWrC+T0XKbr1bp46NN932e3/0wb/4Z3/0xadFR7IYEVR9Ns/Nk/8sIcR5ZnA0jG9h9P0/9N386fbT7f+DrdXotMQeLQ8pnYkz7g6i5r3Q6m8BixCc2qADsUgdTtMf/PN/85Wf7X7l21/nnp5cvNOvuud3nz2fXphnzbXNaQtKTGDiEEKV2IW1K+228vjy6dDvqpvqOI7Hu/2r5y++uHj0znE8Hk+HFGPqYuqiCJnpYX8nwl2SaZzcC4QlpdV6SJYP46HmiYjmsY6n6aPTx4fbPB6NLE0ant9NANb9sFoNDCUvkfVi1737lUePH637/vHjp31YXY2rcMjH02meszJbTB0TVc3rdYxpiFHnec9hQ2Q156++9zPHw0ePH6eQdlN1iZCAijyrVxRlzJq9UN+HrktdEnNj9vVq6GpV881ms97sVO0Y9vOhzNWmCX0SEGu1nHPOc1ZkA2YHapfiaTpuV+vNZt1d3zDYA3RUZiYnP5v6wkDkrh5CEJKihRRx4BBoOp1gCER9NxTNbN5LYGJAKAhZixWj5eqLEYEYpvAKt0a0Akfuum61Xt/c3rEEZpIgpeRScy2F6tkH5rx+wUIhb/ioKeu9pobOfLGlTcx0pmzcEwTOYWhmrzkFIsRtzbjE/BUtBMROJEiKnFXLVGJUDuKz15o7snffffOr77zzm7/+re/8B9/+yvYtt6lXbJhLvTU/Mc/mRS0zYdUNYDZlYzZzrRWR1mlzfbiNse9WnVM+5bub2/1cT12fyGoX+8gdnLxlQCOxiSGQmSuczczdKjEN/XBxcZGp8iwUrEsRwbvVEDVCJAinNBAHi+xOWVU1X+0uBy1O7mKz5RDCkKKDTvv9NJ1u77JEIja4Aixkjy7Xl9sI8qHvPv1sv1p1gJdcbWWRUQu0Vq1ercXcwc3t3ocVtlDDA/vSkQJa0hiZt9QxMhGRGJpRmlYnoi72QUJTiri3NG2iQIHEmb2eoEAAFNxas+pMgOF0wnqzmaecNe9WyUBffH5DKj46qiEBHSBAgjaAxxVk5NXUiSz1oU/JstXZsSyouUyGzEMY9rd3fehu6qFOOJ1UD8p1QsacKyKsGIxhxiAi76XLQWtxVHgFiKCY8kwgb4K5hkO1G9fuOT4EsKtLZJEgzQK1qroiQkS60CnU3WuppVYzLaW4YqHRENjD0s9s0Iktj0O7txfky9wffPjSUWQ6K/m+VFXhHrW594pamqX24LXEtDjkLWvY9jmvOTFtXwsV6f6Vi0tpo3Y2ryVqwdhYHK8aWM1Ezbj3NTeFibnxoKpqLUUBMDgGMC8F5j2uhKXH0p7+82E1COmh+9WCOv3I1GbuZCBqWN+CGakpgeEPLKjO6dnLSW77sftPw6I4aEf2OiL7DAeaLqdnwV+EHIwFoYOR2TnIp7Ho2qf56wiLczPYAQQJILROwOsjErn/xEUEtnDIYA97pPfXsYEXzMy8BCb8+PYAvXp9PLinmAFAAFFblpjByINIy6ptsYPU+vkOFIeTBAkU4dBS3VXWHVd3diz+dG5w59bBgPg5dIBECCyhKUMbVlrttZ1hM41iEYZocRIPkoCqxbyaszGJNAKm1YKakiz3vhsRhRTqqsKBCg92T8qzyamzeczslLwjzk6opYYYoARmV3iGstasls1nF5NAQh7M6J79RzAycjhNYlAwSMHCbASGatGqIE8psaixVaiLyRBX/WBCSsbMUYIZp55TCsTGlAhRC+Yx51kvr1bdwIDnOWsuHOLTt56Ua31xd9NJhLqpuZmQGMGciLg5GgoTEZvZfWepcbWw5L3B9KzsajWfERFZdfXKyjFGJmq3d6NFGJm1E+KWUhdTtFxRgYAf/M0P/87bv7pd7XKGqJrVnKdpruaAoDKqOtRB8OA2T06CZBJQqZTT6EBchSmPL2/mx29sc+Xr22s5ZkfabDZXV26234/5OJUUMY0zE+YZKpjmarXe3qhq6vqNhEst+XDaz5ONJ9wdYB5i7MFC7NIHwjlAV4zIclaQP337cvdox5RyBlNgS26ZlZqS3GsgChhHdDGGCNR5HL2auyMB0YJwMRA7M/ouOLiMVuesE2BaSoGDRFMnxGKuqtVRY0TXhRDFDe4hBKjRNJpI7XuJMaxW3cXFbr+nEBnOp9OkqsQWu7TdrV+9miow6+nVddkfrh9dXdZq+9tjpH41bLYX/Wo9fPjJjQCl2CI2l+QMqwoYiIVZHV5MD3XWcrm9vHwsno/Pb179y3/7b377O9+M0ffjq3/1x3+QZHV19dZvfPcb/8mj/yik7vnz6//hv/8ff/+PXmLfAGJUM2RDBhTmxYbzwwtGBVp/NJG33Fl3cAsuNbAZgZldFh5tmWcMjtRmOZ/W83tvPf7GL7+X+mjuh/n6NE9gr1bzWGbNarUNLEH42WdjEBpWOqwiYKXMri6DWC0FdDoevOahBwFXV/iZ977y1htXqxROd6fj3e1bb7zhVku1Uoq5CQUwB2YCREKIEdVdazEldXMyYgop9j0pX+62xHF/Os6lmFGey/NXL69vbxzqbldXF+a6W2+4X1up83GuuQRI6mIfVxFxlTYxDEPcRgzqOo2aRFarzW0Z/+r992/u7lARhlQts0A6KtlcbbVKOQOQVu5jEe41aYO7uakv7SEC0+IMQk6ucHWfikNgDCcyZmY3wKvzPaNhMZcBQ0sTX7CIEBC6WGprPsEZLk0nTmi2IdYMZxbY6X6WPZOw3O4Bn0WuSEpno97z39G6Gq3Dt8An55UAA4txpd1XKkvh2u67B1byBMDg2sjg7WQ0yjv54sPrX6KpsyNS7ANHIUb1QvqAmn0mZNPD4gD3vxiIuGHjAmZyatdFiGyRXzclpjOYSEKMHTOrec1V3VxNyzTBTSsVvZvqv/6r9//z25EQDBRjOM17U00iz1++6LarBBFiIq5aQeROZqbkQWh7sXv14vlYTquYmjFdisFB29Vmk3abfne4KZ99cPfph3c2I8VVlFXlsehoWkL48sGde54PzpWe//6jVddPt59u/362M0gFnLGDZYxZpARnzNnBHkDa0Fd3MzQGJtdiUHUO/W796vr60w+v/+JP3v+dv/+bz482lzH4kI/WBwiFFClIi2utTBSFzZMr92kzHnKX4tDtOlm5Uc5TySdGZq7OxkzTNI3jYb1eP3nyuO928zzd3Fybu9ZSyhQCc4hOkdNul1K/raepgsJ/97/9T9MJzz+7e/bJ4fbaLYsyTZZrRWCOgU0B091G3n3v6rd+89vf/OWff+/dJ9vLJzxcPKXxjeTPPn/27IvP1+skwqVOTy8fMTuoms7jiFpN1Y6Hu69/7Wc//vjm+csXU95nxZOrlbFJhHlVMRIUrY6a0kAsIoHMhC2XU1GshuFic3FxeeXgzXr7we1NMWHioV8H6eY5H4+nucyPL5MZrp9lVEgvHNB1oRvidre9u9nXE9nkxOxAywdpnqve1sXuIlywoFqmZlofX3QX6w0LT/Ptqu/LZNC2xBVnVldVVVMScOBEUrXWUqvi3gpZgsQUu77DLd0vfViYlJeUQQfONgbLsnvBo5YB3Ny6FHyhebQ1mzExSxNjuJm1hWmbk92/PNGc28l0ZhkPXdcN8bg/llxjxwI7jaMT8ozTATHg6+9d/t3f+rXf/jvfvRq2hPl2+mSTEkWZNBPmvnPzKl47FvYBTFPOTLLebpn6QJ1BK2pKkRiGWg3mLKGPcJhpMSOkFFmCtWbTwlszdg4gBWrJ7sZRQuDVuu9zrNSnlXAkibILlxpK6uZ5zmoMBVxEJIADB3LuUrfdrLOOx0yx6/rtZp7LzasXp9OpVKyGze5iKzGAVLWomtZZa9F8GvrI5Le3B0LIl5YYJaNmr1ZV0ejYVSEsiN7o5O6upjCoKQsZzNqcJUbMRNyQrEbhsWIQSLOflFRzNQNcoADMq3tdjDFNhEU0a62F5uwepFsSot566ysfffGDwzi6x9NxBuAQSABZSAg9PGpT52gtNVcvKJpR3N0XgQtZtSbNiz4bHD6zIHz28cfrRyu4i2DV0TjCK2x0GCAI1Bl7RWFI5Bg8qqPWUmt1nTQYYNosNYggrc520ALcoN36ALU1t58FOgatCicTb9QUCJqQsN2xAaE9KUwkHCxXtAaCgbEYYuOMVbVC6zXbqNFV2i8P8J4vwRFtEAdwZipRS+Npg7qd93am25z3DNz3MfClvT38ob1RWmOWQM2kVRdjjHPJyrCGHL32T2+gn7slCaZ1cTTC4mNnZg1tWrolC+nSHpDIvjyFPSBv/qR/hquD0RzxFwzrAVlroTzB+MzxAi3GVGew/fXhL4X4Tzo1wOtCrp3hJfcJ5/++FLja/ugEEuFGW7uv8hvl7QG4hgfft0GJi7VYCyBkcGNh3d8qr/f2EAL7SafNf9Jt83AL4AWaoyU6URp2CG3XqFGlHAZybhcWClRz81OZsDTCvXUdSBAG0sgSpXU13J3AIhQoZi1NFEbVwyrBAHbhwInDEBAAd9OmApXAXLXWqdQ8H/OM6gRBcCe9XF+6AORMnPoUr5Kvkad5nqZaFYCIDEPfDR0xf/7Bp3U0GLAiDnBF6aoPFITynG0CzDADI5BRYWAK7A6qVnOZoQYCIiBwMQc1X8AiZtEDIivZpKpewygJLlACGJGwHjqDaZ6LV4ul64UZp3HM8xxDGvoNUQhBQmTi5qDm/dCfio6n02985zsf4NN//MN/IpHz6VSyMRBiYAJRYGGzhiJT8y30qgDAvPAAGsYpmOcJaNlZDWde3oVmONxuZTUOAMMBq8iobGbFhtUaxQDEFfdd9/yzl+NpFGE2lIppHEF+cTnkyWpFN7AW0kIlWx61xBqlPWq5Yu5S5CRXT9ZvvHWZdX9z+2KuByIKTuq5FJhnYV/3wkFOh/zyed6sw6rr8uSvnmWnYFgFEbfuNGkK/RtvXY6n8eXL6/3pVR6tTgXuKJUjmRY3gxsJYgxdSmmVuiGdxtMnn3zy6vpVqfl0m/OEZGLqdao2cYEHHtoi1Ny1KHiZdfohXVxtcz0hgMOiFc+N78EAI6SooYhABCGSGVGMxJa1nE6lltp3Q98xUbi6ehLSuN+f1MgcuczT/HIY+lKtWD5OJ/PCRCn1Bto9RgzgyLMWoNwclJwhmOs+H6Y+Dl1af+tX3zkexuub4+1xzhXgTJQohpAGFkJtnCnGmh16fbvvJA7Sv7w+/M2Hh9/+7q9+/vyzV88/Ew4X26upHj589pefP392mvZf/9ov/+5/+ff+6//mv7i7Pb7/Vz/86KNP/uYvf/ji+b7kNlD4dBIWZyEYlazzaFadgZrVs8PBBI4IiUncxSHmDBMoYb3m9TbsLtcXF+s333z6S7/0i9td/8WLzz/9/LPb29tcC5hOx2kuJaseDsfTZFnhQJDFIsmKNiNXMhtSvLrYuerxeGvltNnE7Xp9dfX4Yrtb973Op9N86GN4/M5bIpKnUmqpVilw6roQQp5nYSZzdydCWq3W6x2DB+nCsFKnca5mWPXrGDs6lVKyGhfnKVeHi0it5rW61zyPJQQrVa2EEBJFrX796vbR7unbT98xDXl0KIb+akipKN2OhzAM/9lv/+6Tv/3mk7ff3OfRjBzFqPnbQq2oETWar9q5HHhtWOAKGDHBzL0SGK1OzeNcJ0PBmXwVCEwVvsQguWOxuAKjGTLAzhiW01xLugpeqwtMjVrABbuZgtzgRkvcLFoV6Of50QB3Tp2quhkLhHkxXzRyIbggMKrBz2XUeT5rZqCqBiaWFEIAUal5yexrrlKAw4XYi6qakHAQARTELW24TR4eyNFCw91dBBJI3ZQWP9IYYz8MHGgupeSitb4uB/4dlKNmjcAtt9fbWtnU4GZkRjAipcAhdtGJWRgUVK1Yw5Sd3Gu7Bw3RcXcEZry6Pd7aKTBKreM0SuKh66wUK0pEkcNRea4mIhBRUyKXxBb45d1dPt2lq0cuXjVvN5vH/Q6Vtt3VrnvjH//Df/2P/uc//fQvgUmQozE5mCJSx5b1vsP2mkawVC8PfEl/Cl79dPv/dWuNNwJsMS0BsJDsiVpYHIwISiBhqvRgHdN03FXpcDw6sjt+7/f+8L/9vT989tF/ejG8GVOYy+yFp2Nxrh6llsm9EKswKwWiQCRwubudvQa9DILeSHUarYzrFcX+d6HoigAAIABJREFU0cuXX3RDf5pPL54/E2Yie/PNN1er3nVtVodVjHHt4IvLd0b1T7948eLF5+//4KM//fO//OjT53/xfwBxOUxmbCLM+XAwGBDOAxHj+oDvf3T6p//LJ1jhW9/uf+fv/t1f/OWfefTeVznkt9/aOfpnzz4xv9vshr6P4+n4xYtnRJa6rhScTtNxf/yFn/u1995554P3bz/4+JPd1eMnT58Yl7lO0zwlio7iSkMXQqAYcXWx6UI8Dit+460QU1U+jvMP3//kk8+/yC8wXEGoXF3uHm3f2GxWcYiEVKYvcn6p6tITlHPNfeRTnuLp9OTplVe8nPf9xWraj228X/oDBEEQsLlLkHUaiuU86ePd6p13v7LaBogdx2kIskn9J7evrHAu2XRptXKQYdMPm77vYvZ5HI95hDhSgCqpuptN89y4FfM8v86qIw8xcgz3RBVhEQ6lFDWlRnMBhISJxzK1lRwIIKEWPhNjw6/Yzq0bI9zTSRbWFtA69mbuBuYgoVqZ744hYp2wWYm5DqvkNbz5pv+Df/Aff+fXv/XVt94Z0CnKDtuD7cnG7Ho6HBKVTZ+mObtnYcTUB3RTnhLHlFZr2QqSOmvNldCnVF1rtVJMTVJ/kXxrmkmNakCIMSSKMIXVQmwkkTmSELHbqeY8azaPPNbpZn/z4acfvf/hX4cubC52X/+5r8UoterTR29u15etk8UcA1kIxd1h6GK83F1eyu7p20+3l5cffPzp3e3L+bDf7TCsBwmiWkicGvJUJjflEC632znT4fou9Vtz2Qy4rTBDrXBHTAkuMPNi5B5CaGHtRAyGmzJFDoEiK3nsxMhznhYRUFNMkIiIcBjSwMTTfir7GRWQntStaslZICn21dxKAy7Mqo2a0eOdX3rz6uuXQbof/OCTv/jgfa4Y0g4ZyBWVwF6rk6LvUuxDyWXMo80LwZwpBDYrNpZixbQ6ClbdyqlWOrLTdJyvr19Q9zSEsCgp7Ew1y4ChjMULd7K+WBN1+OyTz7SlDZpVc4ZQIGYmeIxBjVDUH9yN3tBZB8iDRMCsqsPMremV8pTrnKlF+tw3DAiuZ50TgdDS2giN52Xk6m4wuCxIRxAiBpmaurnTkopTKwig8JOH9wcQ1UMswx8WJa9BIGrfr/mo//iu6CwwBGBmtNgDtxbmkirKDnfzJZzRqFGdokBCE1E29wk1ZQ7gQIEdBiYHVzOQgZqerFnDnoVlAB4cgi3W3fcH8n8xvbXja1eifUUHNfc9Px8FETnxOV3H3c+W2A8AJwYTGRELO3D/L3Q+M9Yc5xvmro3tIHzPgiKC+48zoc6lLpnZEha3ZF8sHyAijUuVm4SrIWtO7nQOiKRF1NgWHcyLfgOtBaFnYdhPOjf/LvQKQIA7hM8QXbsdGcxq3nKuWksL7uRk1c6qAydnq+rN72Yhvbg7rKD54Tvg6uZGzCHEwMHNDapY0H93assBYSYl42ap4wYWMW8uzxCtjrGiwhvQKbCi1SuTgxFJUh+RzKRUYa8OUKAQu9RSM+vJAoKTU2U9VAwgoaAixFzVqrYjMHdXiApDiFiEHcI1uNYGUjh5L31d7GQcgBiTwWb1RuYsqBVI4ETmbnO1SStpzjPcwtXQsuq1VjOYedUaKT568mg4nQ6nm9OofS/ukmv95JPP3v3m19fbFRLyPLujFgSGBycndReQcFAtuBf4MJ2ZDI2z2WCshWfRXMVcQGeP4XbFtZyZnU2p0v5J0XD38XikSOvVerPdCPNYxjyVkCwIcoWbby+2u6ttiJEkQsVUasb+9vTqxe3Lm5dqExMx23aV3nn36ZOnu8dPdsNODsf84ua5e1Vt0ttgLilive6bGma0rIVh/XqzGyJPh1ycnSWluFn3wjae7u72L5iCWXEyuEIVNsNhGQuuFBAiuj5KIiJXLS7exUiwu+v9eNKeJYReFS2sBhYuHl2pZtU81wJ3YoSOjDwFiZGnbPNxNEKM0c21VDWAECVwCNJ536dh6Lo+qGLMEJK+J1ftUrce1uv1JmejYmEC0wywquc8qykRAxqTSGBXqjBHNvd+lYgqMWKABJ5LZsaQViYoczlNNk7HX/yFXzrsx83tYXVzvL453d3NXjIkF+s5BCESTiFwQVZ3okAcSSgyUj91w4pD4MghSuhwLC9zqbGHVPv087++u3359OmT3e5qdzn8fPfWm092ZhIkuSMXy45pync3hxfPr5999sXHn9+gQKdzDBxgDHOgWLsDQ0QaEAfy6N/4xrtZ51JPx/z885eH8MG0vbyY8nR7us1eT/PJSU7TfLc/leLTbFWZSGIIARzFch5roZqXukSL7m/uShJ261LYDMPlxcV2s9luNuQa2COwGtLQx+uX13muc64g6btNHLqYIpvXaXZ3rQiSQozCgZ2Jk1NQYmZhCnNRd6vG6pyrTZbnXKa5bFbDZhOJPTh7rdM0BpFhs1qlYQhDsOhVytFD6IxiycboUhyqirsG6eZS8AamcY6r2HVRq1oLXBAwIZfsxm5olpwgKFyYnMgMpu4KgKn5PDAxoKVqNs2OuogEmwslA75kTy9LP/gS8UcOowXDMtUCmGoftqAWPuwgcmk9CiWnpt5Y5kc606PvZ2NARBZwjKgBWA5iZhF291prZWtlJS91l4OECE5UW4HSdJBwa7VQi7+55140dZuDm80qqBlFYiGELbYm9yUN+FzW8Hl8DMQsTt6k8oua8rw8xrnyw9KHOhOXly6jE3lrGxis1rqSjUJBxCRsGpqrJdq0gjwXgyrcrHhL3dDqFXBUQDrS4J9+8dmnn3/+M195cibVet93F7uLbJqruTpABhEOIbLBmdGv+pfX18fx1IVV6iMY5r4a1imFqeTHF2+Or+zuVbl9dURNwpfqsdbKLOQOtur3YW5fvnhf+vFLDqk/3X66/Xve7ju7D1Y258f0bE7nralYnRh+Fn8wsbmbKhGFoZPgs05zwYUzPrE//97fvPnudrO72m2u3n33Zz59/gEJwa2UkussIQtHpijoilEyHk8lUhdkEKRaT3Oe4HkzBEpR73LXp5xjCBFuh8PeoY8uLy5225LnYeh46K5vD89evXp1p8+e3RyO+eaWD3fD6bBGdwwMILiKZbo7GUi5a+R6YRczE2ItgBu2dehwt09/8r2Pf/jZF7/7X/39H/71D7qOry7fJKKXrz6KIZjZOE2H/UlEWPq+H2LsY8hm9tZbb73z1uFPv/857vb9tidhGIPR9ZFZSs4hyLDqt9v15cU6hZSCfPzBZ6dx4rAqFeNxYmVEG28BQR/tcJwd/rh/cnl5ZUrTXE/ItIMb3R0OEgTww+Hw6FHPJDDUuUaJADkz67JcYGZ2MlU0V0UAwOXu4u2nb+yn62marUwRPO2Pp31NEGjTfAEdOLGI9KuhG6JO6sVDD3YWYlaIOnPqUt/3g0NqKaVmuJEQoK7I44h74QyxUKCzccyZd+oON633LWE+d1xM9bxU84UV0lCqdhBt1nHEFKkFLxG14p+s1JI94LjH8ZS/8lV852//3Le/9Y2nT3bvvPno8a4Tv91P482Lm/HyDbi75SQ6dFz09OIwtpj2KHIZnwy0othTSkBSN0PVCniIgaoVZ5GYArlVKl4FLOxgDUSMCG/q9+pe1EoQJaqNSLLZ9Cf1oqWyszozdX26uLg6lbFonXKuHmB2nOYUtOs6ItZqU87TKf/5n33v4tHF5mqdOqlup9tb1Tru9/l0Op3Gp08v+q4jb4FeWvKsbKVMsAoICU0nmue5XwVTbNY7mJeyt4VekWBcqZZSxWrgKCG0hpkBNWcIkbXIE3MXYgpdJymEyNQs1QcigDl0XQcldoYjpE4zhJnhWgzkKcRgtD+NgMSuq+aWCxS12m57+fL6Os8ZhtbEQyDUQEvss5qZqVomK64FMHAITLGxdMxci0KpBfBYdhICcPNq/+EPP+ovNzHEatCCPNVyRBBj6jh15vM8Vpurs+usXr2M5zGRSJhjCAgomt3dvSUxN60bQQ2L+cDSpmoWgi0HjtqdTWC/d9om4mUpSQ6wt2ZWC/WDuzs3CR8pk+vrjsIZtG36KrKmZztXDw/IQvdgxEJ09x+lWeH+ffd8q/vRf2HhNmjgR2GPRixiNMzOGlqTiO8f8oZ+GdwVizTSAYaL475aFAK5q8JNm/WJNJHauddnLWXIwE1r17B4XpguP+Er/d/hL8vhAmgBQP4amaPXbuXEP5KM/eN7dLSy9zUr+eEnLGf6S6+//+gfnWF/bPN7ev6XX9ROWGPL4PXYuRClm7/u2Qbtnh22vO6Bv/9P5KX9GGXvQXH+cAuL9o+5KYyN3APFGAnqapLggJuCW5oVVBfTDyI0g7f2M/h8HhZlR0Pc4AZTq6TCYblvrMkWqRXzVkxnMnKr5mIusMCVGrbOKESFUYmMmQTu6piPs0alaCxmYoggJho4xtQhCDEbd7HTouwMAgm7WZI4w+ImcJK+74lhWaspDKhE1b0AtaWbmZLp0tFvpjIM8uBpyYBqflvucBYKMSWPpl4hxAncy1TntpIXligdJ1iumZVIzdQMeVZ45i4mSimFLsfjpHe3J1eD2rP9F588+liFvvL2W7fPruukOKOIZq61BCZmMjMCOAQWweIUQ+cvBvhZPtiuFzORL08dMYsYmWqFg4Rc4QYPZw8xhzv6NMx1JueqPuV5vR26vl/v5L1335lruXqyXW1X0kmupVQfjxXgzcV2s73YXlx8tb53Go+lZEeRaE+e7p6+ceFcv3j2ea6Hkst606l5zllNa2UgpC52fc+I29XK1A7704vPT31au6ais0TPUxnNNhcCKof9rSETYbPututeuBOOIv8ne2/Wa0uSpQl9ay0zc/c9nOkOERlxY8ipssiiu6DokrolBDwg8cwTvw2pJV5A4rEk1KjVAqRGaiGKLkpF15BZVZkVGZERdzz3DHtwdzNba/Fgvs+9WZXZNA+0AIU9XF2dwfd2O77Nln3rG+Ld9V3LJSNxBKfgDmVBP4RqdZqOx8PRTAMQENi5VvNqBAkseTciuHTSS2eeq1Yzd0IptdSsmkXCZuhFuKpxrYGcTKJ0McWb8qrWMo7Hktm05Dm7GxP1qV+vNykkd8q55OxmJhKIRGvOsxLjcBiZnbgLMRCJmeaqTrZedzGl7XoQ8f39DlTNbHc8MgKDnbSW+euvvkl93FyuNxcXjw7lzfVuPOZpKsfjpNOoIQZmUiNp/BZ3uDEZswiub2+HVX/x6PL+7u2rt1+vh22/WkkVkKjOu+Or4UgXl6tu1cVOYr8RxC4NMSbiMKpPcznup+nwcZ2dayANrKHmOh/nu9u73d3ucNjv6/3kh+JFqXCEDETJzQ2skkzIKea748vKs8ShX/VpRW93d3kuefbj3oq24pZCCFGGGAMjk801q2anyBJCirxerS+3q82Q2DwJb1ZDEImC3f29hdQNqxDYTN2UmFLXdd2w2p6v1psYApmNx6mUGkLH1KhOZg4hzapSKpyEZS5qXtTMCaXWuUzuzgywR4nztN+shi4lM+PQpa43p3GaE9Eg3eZsm6sL5Hx7TpTIQpKUPf/sZ3/1v/3xH4NB4sc8VlTpJaW+5pGgIqgZkaODDGSuIEgITNxax24gZ6ZG9CGY17FoUS0OXRZjwhIn3AyfTqZGC2zFtHSNHrjZru6o0FakLO0qONQVDnN7cF5vO7cbLSv/omN0OBDIDQ5zEgihFUTMLMFMSZr0AEws1Nwil/QTJ0iAkisMpq3AcjJTWzjN5r5o8yiQsC+cc1PVoiemuhva7mkgb27yrq5eQYC0ioTU1apqrYBzZCunQHV6IHIvZVSbsPY110UjD2r2lGaOWrWFuWLJyzCHa3UO4rUazMhY2hNYQQ145bbSci+q+edfffE3f/PpJx9dtZdys77vHl1cvL69tWnUXMgpSkwppC60p2692bx8/SrX+cnV4/V2jarEthqGwOni8Qfr/uqf/Pf/w5c/u7O5R2WRtbnCKgmZw2qLzlk4LSdzl19TufyGkubb8e34tzT8VDn7e0V8A3RBS9UOeAjx1MFrJsK1McpL0RDiaZkDGeEM/+1/8wf/+X/xn/7o7z/r4+ZHP/xx8dFChuRKhzmPqgWALykWEiQEjpvhfDVsA6V9vje1vov9KlD0zFTMQL5a9yJyOB6v374ifPbhk6fCLCxwe3t9/eWL59d3frebxwlffn391Zf3r1+NqFwpMgWmIIGNqtlstQCAiDm5koKJOUQAMpbyzcv9fvxliNaf9aGfttt4tk0XV90nz76vdhynuzzXILGo3d6MXToX1Frrq9evVsOTzz7/6OrPcHOfb+/u+nUsllXrauglSGC/2J6drTdDTPv74+H2+u71uNvvsxb3mUICx/WwTWxaa5ny7u74i59/Q46PPztcXl1xkE8/+WTO+sUvvj7sZmEOMQ59GO/HnAsx+j7m28wxwriZTdGD2BsAw8yqVmVNPUIUuH318y+NdHXWCeLt2wMyKHGKobCpWRwiC4/HeThXrpjKXN26oU8h+ujH41xnI6+EAgohRW1J2wZvfNlKgZPIohE4nXYNgLnCFxkRk8WYaCFZeRPCcJM2nE7bzAwQ4unos+iT4OS1ZhBa6GFGzTUD+ell+uFn3/vB59/99LvfWZ3bR882z549Wg0ckKnOWg5aDqXcMG3mkt1mJ61z1bJzzYFIjGkic79YPwrSCaQq3KswAWyuRnWaK8fgxACFEBP3gkBGAg5ETMYw8uoC9+ytXUpKBHUT5ojIwolJYriyQlGki89fPz/m4+F4oMVIP6Ww6VfrRKJaYZOWst2eM1GeZi+aLVvtctG7m5t5HvOMp08edZ3EyKt1V8pY6hgDhEnNa6l/+dMvRPrdodueaZ7mPnV8HvfTBLKSmSjU3KoeiwwOzGBXr1BTZyEWpqYiJCdSajL/wO5epgwnScHViHJHkSFaDYxhtdod9tx3QQCrqjVIkC7EFEo2U4UZBwxn4fHTi2fPPtzd36vVQMgVc8mSOitMxsRQVxiZori5NfsCwFmrW1avsOKogC/NRKuaQoDi9nq6o+k//M9+uLnqXr15GwTcd7kzschgBWPG7u5gWYdO8zwtVs9OzTzU1LVWd881wwzqpICBW/4MPVBTlmXT1Z2wkG4WolBjCi1GTuTAyQbQT0nRcDD4pBmkhYTU3DIbWtFca0C+ADFNIgy0CnT5nP+68asY1uldvssEfB+5eWA3YgmPe/cbp+9ac58ydzV31S5Ffufk9N7K8871qZE2DAynIEwAqTtEGkKtzb6LgFMb9fSqTt5wtNYCbqZRrYu6mJQvnP4TjPWvq6eW1cNOakym0+S7u52CdU6LUOMK4QFZAp8U0PLgDvLuwm6LqUcTMjRzlCXpDXjHzHpvPk63CDt5XS1t64VPtZwa1Bqzj4jlRGxaUjHaNRvyT6esw3oyF2ksszZ9tfwGD6xf11z9WyPAQBCh2CTElThI8BBcQcHZKTra5xHBYG5utMRtnJI0CScNJwBAGEIGq1q13YSbV7hDVbWUhsUEj6bkRjQ6u6EQsZO4R+ZIkObMR3FmzECpcIiQECklmoBqVtxiRqwO4xQhAcyORbOr7CEFKxY3neXi7rUWJT0b1s5OcCgJB+FqRa0uUfTVahOFeOuVN/yVmSDEPI9qrC18qpk+ErGE0FAkMTZXDuyEGIMnrqbO4CRh4MN+LAdUo9gFCqzFnOCo+/1tc538zsU2j/WwG+2AuC2/+MVff++TH3z0/Sdv3rzWxOjIjckDo0YvqlCQwghea2FqOffUaA/NGK6h7BKjkzO3VHc4NSM7aoQOdgGcXBxwcjJn1Xac0YrQBYDLUY0063RxecadnD3afL//gbpWnSG8Pxxubu/mXPf7yZTPNtP27CL1yRiPn6xNy/Fwp+WY8/jy5XEuh2m6g5Suj1ZIhAOnaa7HQ66aQ+wkAtDtejvt8zTxcczzblcmneaxSa77NdZ3geHMkmKvVo0N0NBhve6HYRM7dle1UjWrFYM6eT9wP4Ra6ebmdZ4Wf1CrXvJUJkPlLsQU4t39XT/E1PUxBUOsCk6urLEnEer7PkQOgYnEtbipEMVO+tRJ4A1vrPrhfiLA1WpVNxNm7z2yy5rMtVRT19UmHeedwylYvw4hhFInc8xlohBiksTRSQGVkIdhWG+jaZXIWV3VpxlErZnJFWE/jz25UhQBwdabIMFJajf0tZQ8j1NtCHp0M9SSfSYiFx8LnLXb9Jvzp9uz7u3bV4Ht7Lzr+/U8n+VcVW292kqk/bi7u9u9fvk2z9Z13WZ91vUrXm3MAEfapvMn622/iZICx0jRar2/u9/v9jnPd7vr/bg7TPvjOB6mw5jHWcsvX3zZDbi82m63l0Z6nMtcdt2gRDKN8zzpdKzzrFUNjsDiaC27sRbqO0CsS7HvUpdk3YfNKj15fPnocttHKfOR4VHEqu1392/f3iSJ/Ihi1xOZcmThLnXDsO77gZnVlKyaF5AJu7DCKjMz2GqtOs2qFpNwCUOvPnvMKahEozIRjUQznOCy3my6riNwZxJLAnExn8YpicaLdUwxSoDHLvSH40RxZVAT+vL51//4v/7HMGSdLILYzb3R+txQDW4QoeruZIjOTAja1l8jdVdVDyAWFouqplPRyVFOK74TgcAMImuEYyJQ8HY6A0F9aa8sGDcRiCHGLbnQiBHA2vwRrYmnRcDupybLQucibw6ILV+qOaAGN1JlODtDnF1hDrVmNdGcBWHuAje0FZY4SGtpGZkCzgQWgkOrAWBhIjI1WFs9IiNoVm3ubI3yZObNLzAGcOskNtaYgcGRUicSGFbNqldDbe0rPm33S74hmq8Vlk77Q8+KiakZvMLVCfD5OOnJ5hKAOTnM2FrjjpYWJ9jJKZxKv4XxxQgd1S++/sXffPHlf/yP/oNSmjCgWMUHjx4/f/6Cqw8cOXaFnEh9rMl1tVk/Wl/88osvCMFJUupCKolUS+7T2SCXUS//2T/707Bf5SOgVuu9VyMqMGIQVFpi8kPl1Pzb3xVE76q031g6fDu+Hf9Pj2XJOh2kHtrGp344WjQhEcD6wIkBOXFTSxukwVnkKhLk9l5lwP/0P/7Lf/gf/f4Pfvz9IV4VlGff+Wz2+9nvp8pEJSsCUy+E6uRIEKo4X59fba+YApTHQx5WXRDKlo109jmuIiZS2PXdmygUu5WSbPqr52++saIvX97/5U+/PuQO3OeMu9e7t7e3OYOjsD9ociq7WmsnMrGQgxRoOUpEzAHsUrS8fruD4n/+F//r9z7/5NmnT7Xq7e2bH/zoo4vLp6VSSnm14v1+9/rN8WwD8jzr9OVXP3/2Wbc+p+9859FhurE6sUlwUysw6hMbsOridr2d7vMvfvri9Tf3d68hgouLrQeXnrptSmd8OB4uw/nu5rDbz29fV9Qyl1ePHpfLp9unT6/ioGO+3WUTZi1cSIIMtdbYU+p5Asw1IjElA1QNRg4LzKa2Xq+P80Gn8ujicd9t726nNzeHmvFZOJcYDscji3SrQdWnfKTYdd0WjDJNd6/uV5frYppiH0WSdxocKNUKqhXVw3h8dPmIXEmbCsaWg5/DgBa75KZmYAogIlmaN01j30vnZlVVazUzOJMwO6kaMbWEIJbgcGcIk7qaF8A9WAza4lQ2m/jBB48eXVz0fXzy6OzZs6c/+q3PP//sA6ZieZ/L6/1uFi4iykyc7Pyp3E/PzdRRrGS1kaFMRAquFDxF2ASjUuAHgEPoE3P1kms5jgetFBCjxBAig4WIwGAhCOHEtabkMJMCy9Y+YFarUZFAnNjN3Dr2i4GjrLT47u4+Mpc5b7YriSJBD9Pbj/EoYyIuw8qrym//8JPDeLy5v9sfxuJ6eX41dMN5v/7FQYeIPsr5+Yajs/gQQs4yzaNZ0ZJznl9eT1Wnvn881t3t4dXV4+2b6yORM4W+6+7vZjVmUohRSl03aNX5mLMWc5fElEgiEcFgyi3bEsZm5vm+xCFAMB0mAOs0cIzUvIwDQIkoms9ai1WNiYYurGq8e3NflQBHwPqsu3ps3//e6o/+/Muas+ZENdSZfKx0LOLOgZmqVbEKBGNQEM5z9arVqs+OClRAl4WMAIqzswfamKvdjR98+MFY35SySwksq3nwvFeGBWIzut/tqJokCet+3jUkj0jJzdy0coGBTIWFhFXVUN+jA+lCb2r1kZk/OJmDlhx7e0cwajiFQFopYCcpnzUvIKJFgadmD74LLSq6ZYKTNFxr0YYtNVFjdS0gyKnkPLHcT/ASLQlwMAOY/WQwd7qRUxJ2++H3BHQNRmv8R0ODoa3pG23hcMiyaZADTvJejSNg8Uanaf8sUBXLYjFrJ1GJ+7t6iEDkzC5Lh5cWYKZl87kTy4LtNUuadhenwEQ01dSyg/kpupBOdLZWi5q1uSIHsXkL9bO2yy0T66dGjjUDa3iuD1PVLuV+kkP4Q8+SmUUgJ2LUSa+6hFDD2qGhPatMC7Ql7I4Gepws5dsTAniDtJaJwcOpglrOo7EscZN8wraWXz7hU+/+HO9gzPcaqr/aW21T0kqC0PbHdvyAwoHqYHODLyINwWILxN7SPR6ioDguLDFw67LDAjyAAgzeyE/uDGvQLjm1IEoDEEhA5s6oTqP77MyOCAvw6B5PwVaZaDLKTc5ITkQGmkmU1OHkxpZ1RvX25DawMRBlmVdpZaT9JmIWUrLqYOXA6kW1LDBVw52ZXAyhobNm7mTc0vqsTbO0lrtRICYjIjdSqyByJjULzf7ea8PpnF3dSs5mTomphpRStswUonSU3DrrgjTt5rgbXWWzXh/yvJvGfISt/PmLb54+fRS2JBecDwWS3IK5sDVv3VqbxT/cvTbVzZJi6Quoau3z+nAwcYBg1sgTLQ+uERYXeziypuRc0iDU0XtfBXMtDUQPUQy126bvfuczB/7k//hXx+N4/ebmbnfnzsfDfDjqm7A7P7sd1htADeAQAAAgAElEQVTZ9FdXFymJxKDKc572hzGXO2b0ferSAEWpNlcpRWtzX8RsWlQtl2Mf1lePttsV3r7e3b+6RwZWAGCV5mOVSJt1zFmPY80ZIi2TuGWcZHWtVtRm9QouRDAj1SwxJA3r1Rp6LNlLqTZbkJRCYojafL5ZZSvzeESFkq7WXdpGhNoPKYbgbilJZDkcjuPhOO7NHdSRcgBin1KuJU9Vq2m1UtXVhEwLM+UQuhghIQxdSEO/H+/dkDrp+369Xr9+81I1A0riMXHqArOyUIicEkoZVU2ihBq0VukAF0Mw82J+dnGep7Lf781gZjlnVes6Ash67noZtCowz2XMC04B8uwAkMthvUpXjx49fnK+3sY8Hi4ur87PHu33x2magyThaE655lynt/ev7m73hNgPQ4jh4+//QBVm5tXhEEOSuFmtV93q8uzyg48vP+uuCBjzR7e722+ef/381avXb+bx+rg/4PIph9ivt2f9anWcpsO0Gw93WmW96eap3t1M44gpL80bb4G9DCYQ43AD9NhsS79Km1V3vh3WqzT0fWBRrS0NZc4lj2U6zDkXDxjnwodRVRNHCRJIiIM7Sim1zFZnYPEdoMWsHNBqtRavUGMHB4cUBA3RIwmJdtX6jmCSAvVDt92ct89MsJg0whjC/Squ+tUmnRmMoXk8pvUQmAWsoLc3t1+9+CprRg8PhkhgGCrM2qauFaZgbvkuFQwEdhQFkcHMySFwQRAIFFyZa2jmbG0bkKbSI3bituaDAGc/RcI4TlTeE3pDTgvpStVZmRhM7MHc2OC+KKzZGmF3oe+AW/QwWp6wQiHWFhnldnFyUNtVwNYCj21JKdGWxeHMHBoU1jwj7d0+945kzk3P73BhYeGF5O6AIQRWnAoJgMiIeWGhtbOwkARhaZ6D5tWgYH0gUbd04ZOT6KlaavQ0P9V84ssebaceGVmzZmude2J+cJPWZt31HqndnVuRtfS72GCVX7+9vX5zXa2KsE11zqMEGtI2gIaYuk4mpslrPuzyeGTBisMm9sEFwjCEEIZAwScrNaR+3tNXb96++hpnbnkG2E0PIAUROZOLO9gVD4DVA2z1f9Xv+nZ8O/7tD//V+hXvyyH81EtF8VMVTAufQBXW+KFmJBwIvlohDpbn+if/+09++8c//PiTS+2m87OrqdJoJtXMZ5qdvLArOTsksvSxO1+fr7s1gxjBncxonuuo46SjwTmAAkopw9lqu9n223V27yh89cs3eZ7fXO+PY8mVV9vtbrcfx4mBlFCLEZTpdDpiXQBvbr1+c7aqygw0txVh9qimGmx/xz/72XO39OyTy64PX/z81eWj4fHTs+9+/ujVq69fvfzjocd4HGMf+1V/GO/udq+V4uPH2zdvb4TjZkigMGWEhNRT3KzPN5fIuH5+9/zL++kONJN5yMwF8/rxKoWhYr6+3j37raflUEdYzeoa9vdEfKhU1SZJkKDn5ynvcZxqzdRHqqWIeD+QP8XutSlVQWKOFFwr1DKRIYlHFk8ox9T3Ct4fpy70Wie3SCSbTbrZZ+UKDqHvJXaEkGspqjZXHjPEhclIpzxbhblxAISY2B25jgalYGzkIC9mgCu0ZniGM8xYQlVztI34dFI1254PVuCmzkTCKSZ3HI5HmEEAJqijTkgRZMi1pdygAxLyG2ALPMYPvl/+0T/84e/97t+7OFv3KQ0xuM/Xtz+dxvsklVFCtM0mUmInn0qu8HGsACtmRTFSghJxRIxI6zhw13uImmFWiYS5ZvhkecxTrcYUk6dVWgUZ2mPf+lLLSk8Bi9DenapTaFuwgxxWraPWkncFvGenKBfD5eXqYrK0n3eBpe+SWx3H2xl3U92Lo+/6cJG6tN3tqdYpl8kK2KXmKo5HZ8PTOAxRGEqN5E1ublkVTkBQt/2MUhE6G+vhMF+vzgRvS62VOXSpv7/dGQrEEJrxulWYnrxcjM1IWRjizO4MiDqhQruU5KKLEq3a2bAOIn2IaKSYgsP9Drw2bYb3yhGIhTuPK8IAsCOAE4YzWW9rirvd/mWeMjSxdTa7HyaalVoRRO4iXmFo+ywYMFVq/TA7ge5uDGYYSwsl3iIIbAwUxmlvNorAjVSt1Bp7Dgg5EAVSMg0g8rFMAFwZFe0Rd13c64lP+X1LUt+yXHrzbT7RpRTurlhYKAu/8D3CTqO6U6us/F23wIUeOm8L93wBwniBg0/NhAZVNE1wmxprb84fKoyFT8vvIULvre+Eh9pveU/vkbh4qcSWYUteMtAs5JfDbkN3UNWkkaOAU/4pLSborWKTk0M0v6uAsNxEe8O+pCq6kuNkRQUSJ3Vw6xLD2tF7CcddnJWW3374Mi29SzppFh1OS671uztt1fi7uVpEm6Tu7ThPQHONf9gMW1wRsRtOwUZ0QshOJkMNN7MlBbxpQnF6LyeMbilyaQGJTvBle1N6Qg2pgT70/l+uTT6whN/5QpfxE7r4oIg8XbNN7onJ+p6JvL9/2V8//PRjAQ6oewtjb27zuVYncidisEOa9NtUjc1MF66aOYZOams8EyAsQUiAtKRmpRCdqMzFcjUyCIkICQASZqYYiKwtnRVqVVEpUOX60KIHwyqoQLV9IKoZuXiKCcwtCAQON3gulbx5G3vNmWEhdiExc+oSJ4kIUNQ6qFitVotqdSiMKKQIQq0FASlEMi+T6mK8TzCzCiODer9eEUgQyK2aulp2hZvVaimkVWIRr7ZwMUttXSbmpNm7LgViAYmRg4IQIDF2sZcyZVVjJopwJk6YZzvc5+fPr882Fz/+8d//oy/+CEZuXJVYmybIHc7kQlioe6pCDKbTEW5ZyxpFtD03zC1Di5alpC0T1h7FBXqltvIYBNjvJklREpNQLn443r25fv5h2Tx7/KGE9OU//epwn1+8vDdrxpmY95i9aLleTfPbn+37i/W6i0LWR1pvgoiID0zm5vNYORAYpXpVsCxrWq02Z/zujz+9v51ffnP94uv7ssfmchhWq1LzPI9F6zFDzBXT2bY/XwUYMccYV13sJIVfPH/Rqj8JiF3ouv6kAIUwD5uNSziOOedik0HRRUkxlmz74/359lK1jPOEAiRE5j6kYbOJSdwtITFxUcvZymwGcOPihhBCkL63w+6Y5+OYUZcTtbGz5Pt7m+YDs7MwRxm267u7XcMQ3GkYhvOzs6rFvUiQrgt9H4mrg2JKZnW/35t5jMMw9CFont0MpjzPxV3fvL22WkOQYbXuUl+KjON4OB7cve+HJ0+frFYDk1TlaSqHww6Wu8Rn665LdNgd3OYgCsuv39zs7t48f/WaWGq1flg9unq6Xp0xi/R0/mj7GX386tX127f3u8O9Av/8D/7wao3tFtsBfbfuOGjWMu8fXTy9uDg/W11s1pvNejjM4+3+br87MvN3f/DZ7/x7Pw5dyqq5linn/eF4t9vd3Y5qePJ4uLi8gPOwujseZ3io6lXd3ZkpBIkxOuwf/P7vC3GXAszmcad5JKrH40heYkAgGJmVWkpxQtd1IYTqdjgcxnFcDZsgnSmZUwyl4cAMixwhXEshUOwS3NWszAXqHrtAYKKAIIgxUAhkUA11narNZlnJCBXzPAeSVVxv1mfShdbkIvDBDvP1YXczzgd7/OiwPX88ExXu/uwnf/Hf/dN/8ub6GoxSVaJgiaqR075s7/5zYmG3bUCruULAfdezs1Wvc9YKd2cWiMOJ1EWkHYdAizdla9m1DsqyLjw0yXDSrqupu6kDjRhMRK3zQ7IUCA8qe3q/9GmbIf/tjccf9uBSK+ASmCTUXKGu5EwQYQKREAKbFX+vt3a6hNO7UgcOCEvji7W7YGYEELHwUridfN8XtO3hizHGENgB1ap6cqakdzTzvzuW8odOPbLTeXPxKPV3dRmfTAFAACqWuTtt2C1P8f2EaIcxXHmccX97GOd8cXl1HG/nOXd9UrVhWM3VKigKm3lxJ6ALqY+B3QIhdXHVSxclMvU+BKzOVo9efjn+4T//F3iFnUw+RiJxY2bjhVjwXnH77fh2/H99nArg910+2iMuII6h5gJw6JOZjuN0HFH18F/+V3/ww9/+3vbqd6njVbcGHd2SeZhEVBjKVj1A4EyQs/OzzdmGUyCwua9XK8M0TdNYR7WJojTRk1D47ue/1XWDQ25205T4i1++OOzGaSwcVnn2NYXXr+9fXL9aJCzuTubL8cKNbCn73ZqXC4RZYGau2lqUaH5Kjv2t7e+Mjy/G8e4HP/hot799/uL4O/RbTx5/9qPf+nfevHk5TfXtzavt5UePnjw6fvn85atfnp198Nl3PzxMx939tFp3qevUt+6aUui7LbR/8eLVL37+/PCmxbVFLTQfNZfJEvpN78nhiNI10YdXAxiVdrtxl+/v7tGv6PLiab86e/XLm9dfX2cKvhIKErt4+fj840+e/fHdX5tlqx4lSYwUzTSbFwnhbvcyrbrhPKUzfnP98s3uTb0HOhymY53q3S4jYc7H1MX12eCwabrNJbNQGGTMu+1Zp56nsYjCDQhIAmInKJwhs2YtVlWBxSMIFEGMwA53rcrk3SaGGCEwqFopbjBwjworlqtXBwyZA/UX6PquX/XEpFpFqFoOkS+fPHny4eOPP/nOp58/e/zB1YdPz0K0IBq4us3jYb87vHh7f4jMWibLuz5xN3RDH8Zx95Off3nYX3f9+snjDx4//s71/T1RMBRwRaDIJCwcZN0NfdoC0RTuzCRMzK3pZqXY6ET7465PA6BgWFolBEEgRPLgRGStwODWXwEa0agdzd2qhXY8lebPNjDzo7PHVfNuuq+vvvTKXnic9uR2ff1StayGfujiIPFmPMCbzZZ5KcfdvXmVSD/+8W8P6zTX437eRWaryD7XqbhT4BiEY1qXehsExJjn+f7+fhgGIs4Ffc/DKoUhFCuSiBXV9DjvvVIjNLs2C2ADEweWECmywarVIKGPfejS7naXuLNq85i72K83q/NLKJvNpLWWapCcOqSOSAIoDufdlgjw4oeux/Zq1ffD9eubF7/85uYa45iCSj0qsnpFBdhdGQio2VCLEC+whrlXXx45bTkU7TTdnMLVvMAIhnnSWj12g0ieJ5umI6qaC8GdbLVeZxMSLzmXPIMJMCKJIVJCRXZVCKlWuAOyOB7wr8JAWI57vBRNy6JJD75E7y2pDV6wE3tn+e2GhZ3WXDoVpViAiIeF+FRdLiDD33Zbf7jcrytEfjNu4b/+m/6A9Xg7sTdTKnImuNcWtscQZhCxEIMVtfmiLziPPABI7yZq4SmBzN34QWxGLIvKwI2sKQqEHwC1v3U37Ev5t7Rg303NwjLxkzywFYmtvhaSNvEPV6NTWuPfmqr3+GvLy7f2K1oV2pCxFmPwcCVmmD3ANu1um/SRJHADAxwnaKXp8eEEgQjBGvWNlrl+9zeQd+/3AfZ6+D6dxinQ0Mzfdajftz77lf/8G4wgITIzgRRkJO5Qd1INzdfe28eNWjcdClYlbe/PKMbgVt0JICEOkSJI3MllkXuIWl0yogKYQpvJwKLZyEBgZmm0QnLU+UFuujz29vAXcpjhpPWTBmwT4GauZFBmD8IulA3CkmKEkKmWWtnVCQHswkVzLqUUdXMmCSmIR2d1dRFOnFBMdbIG8DRmnxsUTTPYwDtyCNjB3hJdDbVorG5E6kpEFBgmMKcQggcUNzMSOKi4QtxJRSiKMHE/9Ac93u52zGFztr2rx+IVCbe7+xjXn33y+R9t/xT7HkW1qqpFDsQuVqUFtRMaJ6HFpxoWvximhtLysrgsZnMLEO4PgGdbkNxPfE72dvICT/e5P5OYQhCmymU+7Keb29311y+7IN2L129Wcs4eclZUBxASxchdFFdb99s66u1ux6SbdbfuL7suBg7mueT5OB9ClDR0CiGkmFhd2xPNrK9fvY2SLs63NuHWD25TLZJW/bDpzGuejwZPiSBOgdnlOE63dweR0K+GmKQJuEPg2EvfdyTiBhCrU2CBUy2Nywl35DlbdVUDe8ZMEamLFFw64kBFdQATQq1TiknVxnEEqOt6gjKFrlt1aZAYU+JpHmkB1d/REpnJXI9jIYIErGQVY39+dkkgM+v7LqWUcxZh5iQBzDCvUAVRLY0wGritv41/CAWI2VMKgXH/9th3iNIRNcmdxo7W3JWSJdQgHgTNNDNJ4Z5CHC4vtk+fXF2er9dDmvNhnvaH/d1udxhnE1UJFkNUt5evvnH/Jsb+fHu5PT/73g8//ejTD169fP3q1evDYVIaia0RXHI5KBCZn3745IMnj4PI3dvnuwM9efxkfXFxFjfV593+ON9Nk02r9UZB1byYUpCrJ4835+dAWa/CajWoou9jydalFYdIzftbFqNAgOZp1Kq3JdcyTdNYjgetuU94fLU9P992SWCV3EOX+j64gUEiQdXMkFJPxOpeS2XilBJLCECUYOZlzDBVVhHxUjVnd0QOgApz4sSQSCKgqjNbTNSxyjjmnPKMOc+ZQhf72HcJkNlzdZ2m3fWL158++VR9tz3bnl1uh9XgkgB5+frFv/zJHwbvui7NVtzMvEnvhZwIJEwkMHM8WJATncqGxTggUDDzmkvO1XVhW4FARieBPi279JJDs+Qo41SGnCjtoJMyvFUVpuoPLSVrHSSmE4zUdrVTc+5dQdRK35aYe1pzGtXT4G5eARPpiYiUHUoEFgGc0NYyaCnEwrS0dx6U+a0+OpVdftq7F2+SBhs1vSQvldnSxSMGYOQOBguHEJipuqqaqrp565T95h3z1JNrlPdW8i31xfItVQU97MPLzs0sbYWlpVI5McHe7eoOCEFErFaUatNcL64e39y8PBw7N+RSun6lU56nWV2Z0Imkfliv+k4kH/dk08Xm4mzTB6c6zcN6swqPOmzvXr39sz/5axSQI3pyUHVbXFv8W+zq2/H/w0GnhQs4NZObRzgv/E8WgZsQ96sQON/e4/mXbw/76YPV+Ti/ERcxieAEVmY4B0mRU83i7v2wCQu/G8V0vd0eZ9XqYA5ONRcd5/OLSwrdBx98ZzzWL796cTyOlxdPZqSjTsrdsFlPVo6jvb053uwQBXXplbMvzg+AMcTNwYC26AhqebRQaF30BtSsohkchG/uD/7NFEP47HuPwPLlL75mtn/37/3w9//BP/zJX/7FNO/MSEQkhPvd27Ozqw8/uDgeH//pn/5Ui1igGPpSmbyPWE+j3b/NxztHhZlrKcJ9kD7rlA/l7s2uu4xXF2e7u900TqVmkFAUF0P2wIiSGBQldhKHVRdTLKU4OwWi4N1Kzi9Xn37/8e52vr/Zl1KMYojEyWBatGJGfKJ9P2SfZp3MgR5pjbiOiUPqZX+4GycrXpola9YMRrdZc6Jj1s12UEt397eL9+OJrw1ATVfrldLsDb1q3XEHGVKHPkU3nw6Yi9k8UwUJKuCEmBBXmPhwiHmhXRAqAcEvLvDxh8OHHz1drYa+S+cXZ2fbTepT6qMLzCtwuB8Pb/5q10caeg5isJzHo3AdBp6mKbBfXA5J6HB4eziUGOnp08f04ZNSy3GafvbF38C3UHUyggUKiIklxDB03TqGjiDuQUgid0xM7tVmrRmkIUrdH7LaVEW0Y+sCc0BgdOQCZ3K2ViM06owEkC12RsxcvPkIiXOgAIAYKvXJ+Qfr1fputzdUL+7ZuyHm49HdC3AUZqH9fgcirROZpoghRbCsz4bt+UYS3e+hnhW1lGLuxCFJihJiCCHG1fA3Xbfpuq5W3x+O2+1GEqcOgIGM2UJkEWGiOvt8zMtnnuGOtEoQsECESYgDqyoxdzEJBao4jvNme/b440cMSqkPge9398f7cb8f4RVmxCQiMcRiNhftVrw6Xxct8/GOBx7OkoRwd3OoE7gIJpiqKGkBA+Ro3Wh2IqVa4LAgwpW16JKlo4ATnNnbmQBlVonMoTXCYIQurSXFeby3whJFs855JCdUEFNgBikRUp/yIRNzAMXEkgJctdZFdHPq5xHIyd7vBTYABbYAVktl2Lg4C3+pURfAgJur63uVUfP9kYWSdGLt4IGrdKpO2xeZFj+sBp/8BlTK39fkLVfz3/jTv/kS7T9N7miLuRKRg53d1bTRk9yIhRrRR5jIyY0cJLw0ct/dTiMSeUjRVAlCRss746WV7Gj9hxON6GEyTlZKTGgkR/Kl7mqp1QvsYwt456crvWfv+M79ftFI/V2AcXkxeq+Yex8vahCRnShY9MAsc7ibNY+hpgZcMA53cw/8HiGuKRbdm4ByUdAxM5Z3ze+9ZzwQ005FsZ+0oqdb+ZU/mTve01e8g/Pe9aD+jR+B0IV46u3zog03d1cPC4bnQNNAMFqMHRZmIdzRLPnJCS4NtXJiEFFD+ABrGRAkztKaS8s9lqm0Mz4LiTAjsVarRkJGLX0KACBNpBrAbg6owb1mO+lj4cGcYWSSTBIAyraoWAGvRY/TiOpCOXIAQy3XWl0BAgmLRDExQ+ggLhGhoHokVCKImy5nEHco8jhJIKsgJue2JjGBnQWmWpyJ1A1OQuTsIEhkrqxeZquxE45uARxAgmo2HscaSxdT16W3N/tH55f9ttsfplJyXOF+3Kf7+3yVP//+99/+8v4+36NWMDsYXgUQB2vjRTo7uBVtp2MTE6iFYTUUkpZkS3dvatfT6rZIkckJBhCTw10cHERcuYwVlt1t6GR71k16/Iu/+okW3h2wukyp8zJPpbrAY+Shi0x2HI8xXOlkPlkx3O5nH2822zRsJXYMilqLqTobx0QiDHEtVQsLpdS/fftqu76M3A9DqNtghdpMnp+fccTxcKtWQnS4x64TClntOJbA1K9SWm+tuds4iCmrelXVZl2gIjbPxVxjYHJktZq1uiJAuujkLu7snCgNMa0iEan6OM53t7vt2QqOea7e5N9O5lSLZa7BKYQEZ2aR0HS/aLi3JAmBqmYzmCMX1eoxdCGEWqqZjeO03++6XlIX2FFqLVVBLgz3ykIhhGYUOk55nnMtKhJS6rs+sKd13zG01LI73BZFDNhsVlfnq/HIJZfj4eZ4vFXVFOLQd48fnV+cn11cbM/OtutVd9zvxnHa7/bjmI1i6NaOOhU9HEs3WJ9CqXqcx3GeJptjJxxkcz5AHpnR9moq1WrOWpXBKQaBBTEKIwlvr6SLcdhCUhFyTlZ8Gsd51DxrcWZ1TEVLUZHQDb1IIsrzNKmBxYeVrFYxho45tKBW1Zpz0WrXL+/nOR8Ph1KPRBMbaql9p5t1fw7UqqXkwLLuhxQTU2g6N1RLvXZDb+ZwKm5CCCn1Epv4sVZFxgNAAwILEyhGWcwkEGBChaCuxbhw4n6dtlS5l9W226yT96nvUjeX+X4+HvPogOUy56lqZsbmbB37MJbjPM8vd/tffP3LeUa/jmDNmhsvBo5mIk5gNAGEuTUecEsWJfb2kWdnZ1PTYjUvLn7NmQrqMHKzxT0MixnT390YFgyKWtFDLNI2cCP390wuG0bEJxz8FCDya2y/23arp8LkYev11qBoFGNSAiBOTMIsssR9NGGgOsT95M182gsbs+lhn1saS2RmZEsRIMyNvP8QT2MwN206dTzMqDAxvLq2cHMAjQXxr90zFzLX+wwse0dkOlUx76oNYtDiq7nINrxVMET27nUcJFZBIAhy1eu3159+crFZb4/jJteplPrk8ZNjLuFud3u8d7bQdULdZt056d3Nm8h8dbY+Xw2kOh/m7dV3tt2T/XX9+U+eP/9i3zjfbuQFvKR3NLpyqxT+bxWK345vx/+rB52w4UVC4g/Ez9aMW+DswDGFdDjkEPCH/8sff/6j88v/5Pf6sAYdiSem2fsxBDXVJEMX1qQeQtpshpg6gBU2zfP2qodFY4qSotvN3T07tuuzfnM2TfrL56//9M9/drc7fvjBsVtdySQ6V5bNsLa//OnPd4cjAJJI1XyhAdByZFy6Egs+zosvRLMDJnNnYggcQAEQUuw1l9vX49ubF88++XB7fjnPt998c23Q3/v3f+fTzz6XkN7cvLi5uZXIjlLtuFqdfe/7T/7iL/58v7+Zs/a9j0cVhq/X8173b+e8AzKIQ0Bkiq5ABlIgF6vkFTkWEELg6iCBu6FiiN3Z2RnIxuOUZxPh7cX6fncPUY6Bk5rM1cfv/ejZq+dvSerd3aialREFgdEnjk/k7NEW7vu7fUF99Pis74bd8VDNrq6uPv3k2b/6sz+Mx3wc51lnMyA0493ioFUf1tu1Q4E67vLUcr69IRpOAZx4kK5fd3B2t1Kr5VrGUhWzzmrIBHQI3HKrERL6YdhcrNdn6eMPPnXxvk+rdd+tEzNqzRXz+aNufRZzmd3rdrtaD+eEVKzc73e3Nze7/X0px0dXm+vr3Xw8kOfVIE8fX5xvU9fx+vyc4FaOc66l5lrynEkkODiXMs0lz5ZCAZQFQiwsLFEkSugldMJdkC5JHyQFBJjXMs5lPI73WccQJQ5E0Io81VlCHxkRgTSSh9aootOnhQjOrXOmTf++1Jrq5M6BIpLDjTX2cTVs7i73xctcxghcXK3yPLpqmaa9Fkc9P1sX1eMxDClsu9WzZx+ROEdX1nEeiWw19GMeCU4SRcTMy5zzmHvjoVulfsUhmcLUPvrkw6uvrjebm/0+5zIxW+oEHiLHGt1Ma1bT5Xwc+qDWKAYui+kPLGux2q2G7WZTjjXnPN/lAKl0BHu2Mgx992x48ZcvII2IHqqRIR5rnQ77btUXLiVA1qG/6BHD/m5OtOoATOX/ZO/NeiVZtjShb61lZu4eETv2kJlnPneqW91FAd1FAUVDiZYQNBJIIPHAK+IZCYlnfgYChMQDtJCQmKRCzaRGJQSiUHdVdYua64517zknzzk57iEGdzeztRYP5hGZ595bqOGJpq89pPbeuXe4e4S72bJvWj4XsgiDCMNcrb1X0d21kqsjEhmhngEsgjEbt+KOXEwhCSzsUhQgCHEKxF1vtqaLC9s76pS9tv5daq6qLuQnySAAACAASURBVBzW6z7f5hBYXESI2NnBwq1jFwsHEhh7XcKqF2QfQNux61kstYRgLeWVL2wltx+aL4qrNyBRY+He5JRj4fPgDYlnbgDUoqex0zFbXOjPkmH5T333/6IkOYvEWrRDK9Xa9tbZVVrY9Kloa5tdXra85Cdf4RtiGE7NZOatZ7UTCZ06NnMLgqDlmpsdwc8KK5BzC+855ViBqIXDNh3QuWOSLwqon2YTHUysUCwE7ckn8RO/uTDQb1OiC3pzUrz5KQXD/XSRfvL3ucPMmbmhaGgdvZc1s13UEiLVTolwyuxfvl3ypd4+bcXJLvgGmmrXvqBpdlJ++YlGfVt7RYvH8KcQr//bEaJz66bkBAFa4ry6CbE7VBcBnbMbtTN04sXiqaZN39MkJ0ZKbuwQbh3ulIgNBgFJEzSaQdXMgeBwhZo5mUhrmd4iPZgCq1tVU6sKR2CRQITaeoB5LdlQFdVQgAgIEEFs0kLIiiqZxWhkpaqWggJFzRQIzmu2ZpqjlhpMZq6w1t7LimtLNm610PnGccBhpZqBihPDBUIwVgiY2Nxq0cBwkNbqTC4gRjQJxjUjSBALXrSUGhNJTwafxrmUghWnfiA5VNMUZL3t7h6yGWbN+2n3w0+/+8u/8o98x78/7nZFlY3ZmL0lM59i1to9bjhpVUEEZoCl6LLzolNWBL2FlNPpP+EAjJzhcBd4MCPhWHPVeoAWBHQdXWxXTv7jp58dHnKe6XAstTBT3wVxLWxGSmAIwv3rHYoTSxS2Wu9u5/1+3uzk6tEqrYJVdgYViTEArOpzrrnUEIg6IeJSMhjC6Lsw1aJkEFRUqBk5xHOtIhTZHR566TX23bC6WLVEfs1eSsm11mKqcEOKHbwwVzPE2IXO3a2GbAAYIUQSokgOK1ZLhRhB3aqRs9Z6++pIDBgd96MrzJrQreZgJXuIEtIljFJInkxV1Yo7hSQpRgls0Fw1T0g698M457nrkqqa1TlPx+PBvXNorXAUtGwgItVKRKmFpcHnOddqRBCREJiZver1o1XJ83jUUsEBm03Xdew+dx2JSCmFQH2KMWDd8+U2rddMnve718c9v759NU3TPI8EkpDAwWzKFfv9uIb0/cqpTDmXOtntbc6lgQN9v9pebaUftJqW2UyJXBjiDlfXTMTbbdenjqVOZb/PeizHytlFZz3k3WwaIDLmOs9VQkipg+fx+LrkOQRZDRdE/PBwLxJERFgcKDlP05hLffFizxTmudaCoeebbR9TiBwh5ETmXqs7W1aj4IncCMycJMYu3d7fw8nNAe66Xqutu2ElXey6LnWRk5snCZGCkwQKDOpikiAAmKIWV4XBVV0QU+rSNq27zfpifX1x1R6sw+F4//Dw+uGuoIYYV6m7uNwcp/16u0pDmOukFI4Vf+t3/tbv/N7vgqCuueTmVCYhafRRo3GsTceLDJTP66g73JmYnGptlZzBwb5Imps7BQaTZloXbzMF2ZLItMxoJwnTaSJorcIbCk5O1lqDg1tTGwYJSBfu4itLzELk0EmdtNREOK9R7gZubmeoVwJBvCnrhNjMtC0Ldl6038Q2tzNkbu174G5YLNB+agT4JveBT9WZu3uTtLERsTPOKj5D04QZAwC7w9TPsNfba/KJXCM66dj4LKh66x1o3NqpQeOivl7e16WueiuE4I10mwAu1QQAYRrz088+/9rHN8N6szpsDrf7XOpH3/imgVYvXvELKjZPbmyaWOYy72/vL4Zhux5WKfisXOWyf7ROj//skxe//zvfvX9eoSBNMNKiYTEguZ7Kmp9ZO/18/Hz8fTve8Mw4od7mDlVihsiSMSxdzRa5n/P027/ze9/6pcf/9K//6qrfEo1sM9Fs5Qgv6hq4H7oLdJak78LVqh8AKl53x93mUVe0ZNXU4SKuDw977ldDN3T9+o/+9M/+9Huf/PF3fnScy+2+/uo/9ldciiILd+uL4Q+++5vioetaNWzg1ojVwUte3wLzmzdVhxCc27YJgDIzU+vIUTyz10Tq4wQc8Oknr955d729GlzpO3/yZ6mP3/rmRx9/8PXDdHj1+u7qeptSOB5ejof47nsffvDe6tNPj2Was027+5LnPPU03pb750efAFCULqahllqKolYgEDEpF7eu61cbnXPZ2+yYWzpMCLGPffV6OOznef/o0TtXN5tsh1zMuCDCaJ7Kw+W2X12Ha+3DUOeptHYl3YB3nlzePLp++fJ2novGOXZh2MbtxWZ6MXNgiRHCqV+nbkWyv78/OIED4JhLjhyut1s1DyGsNpdW56o55xFeQ4jr9dANidgDORMzs5vPdfZKPqOWEjkM/bDu+83FZjWkNMTVqpOE2Mn6YrXa9psbMaoxxWHV90Ny11zmcSIRKObj3d3D7u7zOwuygcfDcby/u93d3895Ivj186HmMTiGhGlggZWpg1++//h9J/v0B3fTOKYYvMZatNZi1kqVzdCHuRxEQEFi13d936c+cgzcM6cgfZCOKFiGowmLRcBk5l4cdb0ZSoHWMteJ515EI6hzaeZBh5CjrVbMrdYwtwoiAkcJBFI1V3NyYYoenDoQOrb3rj4wsd3xftb46PHqh3/2g/GwJ7aURAJdXGz6JNvNKgQaVqv3bq4LckU5zuPDOOU6SpIlPaZPKXWHw3h3d7vb7VPqiDtz8WqqCIL33n/v5tFnFxfr+4fbuUwhkgSpxT1wME59QDPMGUygXqppQ3hjkx6pTlNddyEiWkWUdHj98IPPf3he82SFR48eP3r8+Ev/EgFOyEWVabW9ANHd/k6LVYxpjdV1H9bhcMyvP3+1f53rIWCnnqsSk4GDgFThAgokANxjLrl9LqgtN4jgRMYwMIhd2C0GISf3AjEQVP3u7niY9qAY0pB6kQmmbDA4grAZq1YCUhxS264om5mVUqm02omERCRSdDW1+hPZRoscRpetIN6o5k9f0Js0zFal+FdtYGdNEE5VTaP0zO0U5oA3+MSJ28PyMj9ZX/mpRnqrEPlZv/fnjAUEAr25QixZ5icekZzgcYmpt7Y98YUVWIRHWAptvLH3vdE1NYX+UgbSSShkp3bVC6ZzAqrerELLV2exEi06tDeHsFMVTW9dL731oeBURp5VJl95m9A+AQbeqJaWN+MMCeFckL95/SXMdcHRToDeCU+yqm8dfTmKnAI0ToV1s3K4n/jtBn2e2OmFE29HOV+HmcGhpmc4dWnfeD4c+RnDWmC5v7fyNMBb6om1VzF3VQVgohCUWuDggNYRY8miYwi4qY2IqPXcNLi7wjUSJLDDS83MTZS13OnurlZNq5l1sraqpRYyryByJSaJEojZWRDJs9UCweJFBQgGNQBsbAvDdgpDM0SKHaeKigp312TKqqUuugYApl7cVqcbholJ3MjVTC1yJJC6V6u6CK/w5l8HHIGjefVTa4PKgDrUODHMvVaLBOK2mSQKRtxLChKr1/VqDfFxOpSpWIdIwVwpkLvuj4d3Hz/ZbNbjtGdZX9wMx3mXH8AMlfK9T7//1/65f+HZ08/+7Eczxpk8kcMzyALMzYxJmtFqwR7BICV401S46nmWWkSk1NQBpyfqjD8vECwDZMbuosUlUtd1YY0SilPt+hT7wdzmXPooOZObmGngyKBSDgTte151qwmlmBKImL1WFNSAmTD1rqrHmkMXhlUv1Be41nI8lMNsfYTr+OTmps5mxc1NLe+PZaxZpnJ7e+dk642s1omExmke54kgtZqBqtX9ft9fIIBZIgfmOQDZHUWNObjzPJUQ4zAM1WqeJxHEPqUUzWnM49XlpfFQdCyaSeh4GPOM1aOLlPquf9huHk278fX+AMUinGV3MyYDEUNCSF0HZp7nSeficGaEKKt113tM4zHPc1bMOT/c77ouEUOEgFgKRDK4NrERB4+hqfVEbZ7GLEIhyHkEiSBM0zSOx2FFqkXEt5eJABYAGeDVegXQNM3C4XKzuRj6LgozzeNul0tVIxKRME35cMggiim5WS6qpiJgGfaHcpyOTMwSx9mOx9tca4rp8SPuVpvjdIjS7KUJMLcs7F2MZkFLPubdXHap66t1x7mO5RASdeuLqjbN5fXr53FY14JpLsRhnjO8lFmnEeu10irUWne7B1MwUQPvyN3MVL0LqRt65vn1YZ6zRTleXvT90JshF00xOLG651JDiJXNzLsQh9WqS8P3vv+7kSNAAgkplpyP3eZmtY2hW683Yb1eHmcQmVswBqIIE9yNnUrRBrGYUupSl1KU1KchdSlSNNhxOtzevXzx+uWxzv0wgNhJhyEdXu2v3rtxsv20u776sLD98ff+5Pe+/3sxipEV15AkJPEzqWWsZlpVq4pIe06ZzgsCaTUGyGDVXRfDhANQXfTqCjg8mvPS2eW8ohExTknnCw7TgJzW9J0JAHPTTJ+FzssU0Vbik/bIz8sPgHPxQyd26kRxveGROLCpubb2IFjwSSJTtLY2Le/L+cQctQ/+NMe36PflBZeWLAajM6Fz/t/TUutLYRcW7GuB1+xcmBGaelod4VSC/dQ400StKiKmpYfz6SxFmnDvDfXkCy3o56LkRNctr3mqSgzNNUQopdze3zmwXq/vu37KOZR0fXMtIRW1w/yQC+eHvc5ZA5uWPI6X22GIFAFzjp4GuVmHx+Ptq+/+yatyBFUES4JYaiERYbZzvP9btN3Px8/H/x/GIjY4WRhOgXRVNUoEs6qGEGq1w+v91/7Ch/n509s7fPHJ7Tpdsd9T7WDRi9RRa1FVowjuYiAwYt8PKXYEqmb74y7bdsrzlEeW0K37QNz3a6HI6H74o6c/+PHnrx7uSxULB8R+NskunfQXF1fHH2H1YYhB9lPBpFilZT4hd/EWgbU4IQwgNzi3dqmlAG7MxAwQXMhiLQxIjEOR8dNPXk7T4dvpg2HVlxr/+I++/+47714/ur68fvzFiy/ffe9dCf7w8OXQ89e+/v63vvXRw/139w8kEjTPx93Ec867Sp66TouhjHPVbCxp3et6EGDcHdfd8M4773R9KDpLIhzhMAQ0Ol7rojsoZe66wJHoruQ9pmorzE5Qmr548QlzWF1Jt1lP46GUUhXDOr779csn7zz5zo9/CMXqqnOnXKcxTyGE7dXVfjr+1m/97eubi/V6VQvf3x/cTuIFBycfVv14OEqQLqYu9SWF43QEe7eKV482V9fru/3dPI/7cTzmmgEQ+oirG6wT3rl+9OGHH7376PGjm6v33n/vYrtKPWedp3wkQur51e7Zcdwdjg/H+5fzi/nhsB/HcZzGOc8hSEp9LvOcs9XXjM7MpmnMdQZ5EPri2ZgE2x6RsMtm88uH3uqkX//g66thIOryNOXJpkOG02Z1tVltJfZE4lDAJXrXdcNqWK9WQ7eKCMFSH1dJhuBRJx3vDxfddjV0fVrFYB6Os5IMbAyQT1VzmZly0lrZHHK2fjXXKpEAxHD15quMRByEXb2qm1kUI4gQi0klFQ4X3Tp0nSCMtWwkPby6e3X3jBnby812u3n62acffvThzfXlY7lJXVpTvKtHEepDgNV5HBP3RFAzIk6p2++mh93x+fPXIYbt5Y2R1Gqqpr1uw0XoRCIVhXgJqYNzKWXKM5RdjBJJALOEIPvDvORMmQEeKFqBF2wuLyKHT3/0mc1uxVBAHSWJc81eGcrcgqjJYVAtKnyzvkhDfKj7wpN6lh5hLUa639cvPr99/aImQ9DkoC4MRx1B7Eu/95ZERgEhaxZhAqOCneHUgq7ITwpu5/WwOc7HWmZaEQJqsZfPDp88e/7BBzebdTzkhznPIEgUde26zouPc1arRhajRI7umPM85+x80kMRCUuQYFCjpmN4W52z4A+tDsI5VPu8CTyhV+0PTsIiwwI6LGqtN3tiWuJa0dhSFjrRezhxnCeG1P9ccZX/zC/xld8/Telvv4SfULmT3H/5DQJxQ6ka2MKnwAs36AkPEnnrhdti8ZWXbiWimrotjbWZm7OM3GypnZxOYBgvONXyUyy9nk8n5Ccu8w3YRG+OhQVaOr37X71OOsNxf/44vdGALeeIk8SOTvv99gLN07E0SWqlMhbwyQlajQnSzGunUrUlEZ1FL+Tnz3T5tp3wCUt8o/ZbQJ9GJTc3ovqyfC3yz0VgrKrUDGH/zzlVWr0ztGglABwkxgQhM9MGmkmLeapxHbljJvKiJWfNdTHLGiAIKUqXnKA1m5Xl7amAUIghxlhKqXMJKXVdB2KbXe+quMDda9VatVQzhMgXlxtJoVYj9jB0OVnmcmL1lwdVUSurewE5AjAgDDJsum7VGdlcc/Gaaxn6oe8HIh6P83gYGaEbuvVlZ2QA1arzVOZxQq4w6WMfwDqbFWVzzaTZdKqYFQYIM8tqndRqNVXUFhADAcXgQg3OICFJwaGKKikM6z7EULVM83FYr6cyh04oYSqTBV9dJCI67OfNTbq+uYJ7ClECqZZ5zNNxQiWb7fX9/C//+l+liZ9/8uJ7f/jD/auR9nGzWu2ePtTqj64va/FSSoydqRrMWI1cSbXpN+Sk3eQmUWcmgNFUG2CEFFLfaVFXJ0KT0BFFCp1OY/94nenWUylT/bf+3b/2g+c/enp7+50fvvSMOgFHwHt4AhAYgQ2YVYsq+ritk+d5hpbTnQ6KcAEIH337Og3p1d3tgXLssd6uhyG4WymTWslHPHm0jtyhYEjDfKjPXt3eToWZONjN9cVqnaZpNK+qdfdgU4YQ1qt+GNL1u/3D7m63y3mGGai1cnOq1c3w4QfvvPjyFSm/++SJEL9+eXecjhfbbT8Mh3Fcb9Z397fH/REGGZASgiRSMbVhGLpuNR/nu1cPZS6gBSNYphvD9Uc3pczmtlmvrm+21cv9/e2URyfLFU8eX2wuNve73d3dfj4AhM02dV2qtaqWEGm17lPiXKbjMecCIXQ9WlOCUrzrabvtUoq1VlVbrTZd1+WcHx4etOTr656JSs0pSWAfxxIlXay7y+2jcZy3F9skMQqO+92LF88edpM7hqFL/brrhoeHh8NxclAMHYhKLtM8RqGu7y+3F10/iDAR5Zzv7+7HaQTQdV3fhd3+/vGTzebiIgoTmdW51qlPsetimUcRkKuEjuLa0IFCmetuf7h/OB7HfHubUx9StwrSmWGas9aiZZbAq9W6C1JKJqDmkqdpvdmsVqvd/eHu7hA7VJVctcxwR7/Cu48uV+thNfRdCmQKeK11u7kY+vhwdycSHz96NB7nF89flJKD9Ku+N/VadFivbi4f9RJptuk4Xm623/7WtxiUWIZhSDF2ErVU0xaAtXpv8y3yLiaJMZhpzqO5iqDrYpR4v7999erF97//vfvD/eWj7bsfvN8NXS55Okx1rB/cfHi1ug5xc3nxLsvm9z/7/r//H/31/+p//p/Wq1XWTDCKYm5MzMLuXOaq1QQiIhUVqEQcmIWFnF2NTTrp9Fjvnj9gQoiBmKHU0hnhzvCFKRFy5qVqggPghkydaJAF0wEgYGYJwswQK2uVxC35RVXplOfZ1lqv1qofpqbNcrSI0qbkJ1hrUkggphgjCEWL+1eXqDOr1ATaLbJL3yzXfhoAmNndzS2G2KUEJSjEqEw1H2YrEDA7hxCapKvWWiwbA5HcHQH9JqVVJ4HMNJcyjhkKZkoSheWYp+VaBMRkZMTeJHLEHDomkJpqMSiomQOX0z6loJ44uqbIJ24L/0nBdaoJ7CulEmOOEiiG2nfT3XP8zt/+jz9//oNPPv2+c73bvf7g429I6kJK/SB5Ou5vH8bd/uWLLz//4sfPb1/98//Sr3XDsH+9T7b+6Mkv/PLHf+l/+I3f/Rv/5d/5X//mn6bIekxWgk8eAzMZaXFS99a+EvqzIKyfENb9fPx8/H9w/HQ57+4Sv8JSG516YJEQsZ22aYECAdVHjhYTJoI/w5f+N8b52XH68n7+5PpJdxhfH+d5tbrSyp/88Mt3Hn/jvSffYHT7Mn72xdPNRewuwqv7Z1+8/NHVdvP++qrv1tyvPvny1d/5w+/8J//N/xEDICKx+/TF8d/41/+1FJJWn/YZBX/9P/+Ndd/lyUoF3KGEGGKUQAAZmZp7rtaweQAUgkg45wACp+AVI6kXWgyoFFxirT6j4hu/uP3Ff/TxP/yXvvl3f+83Y49f+yf/mb/wy98E69OnPxjHh/Hwyq1M8/0/++v/yh/9wSe/9b//ybMXZZw6sgvkdHw1v3pxHymND5NwIif1SpFMFFLjJj5+/8mT969SIgn48otnr25fHx6MHDfvbq+ubmIXcx53u/vDuLu4WH3w8Tuhs2cvPnny5EoEpnWzvjjsc4zD/e3h4eH25tF2Oj5IotR3fTdMUz0eJrco3An3JWMcNc/l/v4w7k5dcYDVZn1xtY1JDoeHeZrWl8PmYhWD1Fpf371myMXFRdf1pU5q83oTYu+Hw+31O5eljutN/9HHH37w0XvX11dxCBebPoVg6vNhnKapzLO55jwejvfFc7Gy29/eP7xedTdwqVWnXFQ9xU2MCRLyrKX4arWOMe12e0ImziHErktW1WoNgkfbjc5HnY+stQuegsQQnzx+8vH7HzLw9JOn+4dDlD5wYiTmjjiBE1Ekqewvrh6trq6uJMQ85fE4I2Pbbd+7+mCbLrey7bGqU533U5LQbYTjXLB/tX/29OXTrHW9ubm4eEK+yVNYDTeX/Bi7cLG+HIbNPJd5zv0wxCggI5hjynrMZTStF+tNM1kBgJspKaqxOVn2qgskQxm3E26rzwYlUoMaqmDxrxjMzHa73eXl9cv9691xF7rw9MVTF15vLxDkUKbD/rg7HJ59+fL29QMYn36ODz5M24sbIj5O+S//5X/q+ubd7/7x8//2v//vXjzDdrsaR49dXwvPx3x/v2PimAROalZyrQUpcdcPWvW4m1Dx3qN33nn3nedfvPjyx8/6lCx7nstJb3OaKyp+8Ve//vL13X5/LMTderO63lDCmO9nHC3nX/kr3/7GNz98/smLP/y9P15pf//FNN6jD5tA/fF+bz6RICSWGJf0T3M3BRHMtbpXs6pQIoRIQYgZbOrmXuZ89cG20LSrB9zgX/xX/+rf+YO/ez/tNeByM/zSt38Jyq9f3L98+mI6TkYqndSqZaydpXpXQoms0mxPs2fDCcAKkqh3tZqrjtXMRIObe3VXgyJ2EQvO82YibZGjZ+k64KbVCBSYiKqbmsIMIq0QZZCpai7QpkJaEJ0m3jpNVacvnJ1cF3LyLBZadk/nkK4GZsDZFarN7AVmZiIRqbVaUTeAIAQWcWIzY2YWdvNaqtfTPElg4RgCAhU+m+ZsaSZ4OthydmZwp1MUFlNr+MpEdNgfWqOgptdhZqNGqXrVtrmGRAlddKBatuZ+OGuxTh4+FgkxMHGDcrSZBnTpRE2MFvR7XstU9SfWOHc3P4VjtKswajGKLfWj8bgGQ2Jw4ytbfwqYmqoRL+9lY3C5NkPd4mFoJzOs+1qqFm0ZOJGJhQ3k1qCFheKVpa14E7KRAM6UuYU6gexs6XRviUZ+1ma15RsxxpZP1YCtqpVOaWtvGxvOa/35zjx/a77sdMJZGmdmKKieickBaxxQU8+5W1Ung0iL9WBmJ3ddbkQz91KBJtQ6IW+tFbDZgpU0lY+1e8ZaI9XW9t5a9j0DQqUWo5baQlW18fLnazu7Q4hsAZ6bR0TJqnsFCGQcSMAkFBhCSpEiAoRSF1I+HFvCi5qbmlggDkwsYBhzOyMnUqBai/gCQYgCEVVfPLbMzsZMCESBnMmbyaSFzjAzhRgjOVmpVpUqmKnruthHiu6snCillEtBRJQuIFRVbUpTRkoxhNiHlDh+kEulfejC5ol87S8+vn+x//Hv3+6nw/BohUqz6n48JFlZVl8UOI1p56aKePOoki8uQ8Cs4vy8MlVVqxXgGAMgqm5arZpTmadD4TF0wDXAIcmg823nMGYGZxYUhhqI3PHG3+qAmltrbnlqMeiOlpsQfbrXPM7icQjsAKl4bVn+7EpOyNmKz1RZqHPmrh+u0pD6FCPHRGY5l5pzrhWlgBxd4qHvVher29evcyluiLJ0l1CCG8NMXWtWGLvieDxEiU7qhClnhc9zhjjgMYlWJQN7FAQ30lxnr4mcPQjH0jL9oKcJkcC+v9vHLm4uLvq+G4/jXEfAuz4RU+eVmOeSSymlAA5i1FqbGXC1Wo/TvlnEmCRGrFYxxphnPR5nNVxchNW6Y+b9Ph+Pc604HupqNRBY1UXYjB1WiwLGUdojYuZmziSmOIyjW815rhpEkgHqsSg9PL/L1cyDhOhItdRSyRGMIniYNY4P8zjODe+o1cwTM6Mkcw8StdI0lsoIgYSDSA/muVgptoo9yNWRj1Mu8zTXXEopbk7DMJhTVcrzfMhTKVaruZmIbGLPlOZ5nuc5ShTi1KXVsFoPK811HI8E7tZDqrXEam4xsgRmYjfPc1UrkcQBcyra2mX4XHIuuZqpgdmro+u61TqtVuvYd16sqlbTscy7wyHFiNT1RG0CcGY3ciJnki6iclVVUxbuhyFIqJrH+eGu3L549sVxOqy3fVhDOprKbraDqZs6GPf3r9b9RgiHOvYy/M3f/M0vXz0DYbYckjBJ09aCWgqUAQRnb3yGq7eOFeZGRgaom1mpuRYjghNMDdWh7q0p70kPvfTpIxgvFjhxYmI3NdO2mr5ZLE5cEBM5kamRiWnzZbZnG2em7owrmTugxCcSBgvV8JaSetFC00IAnheoExv1Zomir+xBz98srZsdTTW7cDoLmXmSaDdayLVWWwRaLQCiBXUC3ILc1ZwbFtdU3c1B8da8ZYt/81Q/LAZrP4mvTydF9PaVLCbDt8oOxjmBBycu87wsv7lIgnDLHhQWrJVAEjimkGtmZhF62N097Papo77jlQxdkiHFRzdXm6s0pJTnebPerulm2pnkqxdP9y+f7wDUycQjEyP64julhTV1uIN/Vlebn4+fj78vx8/kp5um/Ks/oSU5zlvK+AAAIABJREFUHcGtmPrFCg/ACo9G7Pr+hqSyznbcd9LpFKIMF8PNkDYtCsaKirtaMbhTAVnVmUNyive78dmL2xe3u1WPSiiKWpQD+r6DMQdkKnPJ8JagYRCBElKUICFyZCYyaonBZqVqrcWquZmituuTpVUUeBFCNPMIkZNrYK4WVCvd3+ZPf/zy5vqbpe4+e/o8rfon726fPHr/xfNSjtHFO9ncvXy5XvUfv//NZ8+/c3Vx8eyL4+HuIfn66upyd3eAKwWNXUrSGens1RnUmcmcbSJIrpo2ssUqDUVYuj5RJHMrqoBTAFgl1OvrteMqJjA7Yig6q5WAKNH7gVJCrpDEzp41O3vsk5vUotO4P+zm/S67Bjfu1ilwV4+uWkvR8XgQ6W8erYE+RgyroKjzmIeB+hRuHjHx8e7+Zc5YXeDjb7y/3n796994f64jyLs+pW4GPR/nOhUHUOd83E9ai4DMdC7jNB+NrLqO9ViB4/GePADOAIvADvM4qTFzIpNxPx5tHMdDiEV9KmViBjuYpQvpoq/kJabSs23X/eNH133sGDLPt5pLCOViw7Vkcic2ZiZpuyAjNyuaPA1hYIkGpzxDeYirdRwG6SNiBLMIxY4BK6VaoY7Ww8UH73z48v7WDHnMQ49V3wl8LockK5NaMSN4IDGyomBxJjNnIIj0QlprEW/OVgAtYom82dMcWYuRSWiENJdZi81gY3GIg7EoV2BmVnOumpOEVTdQ4nW/Geucc9bi2ZpmgtabjTmmeQZmgEIMw7BebZC6aKbdQB99/ME0vogpEAcglDwbVQhmtVqt60Kf0viihoGZA4AY02rFXszNXj17tb/dwxtM17JVAFvE4sTk4iFEMyu1UDdI5CkfVYuH2ZCxRTekUjVXJYdWIQRo1VLNR8sZicFuDCJvLqRlwTe4gY3MQW0jBuDMKcLJEVJ/uD/6arx4zNcfX3/62dNSiDwKebVyt7sl42meGq/ZEIM2iZlZye61ijkxO59YJwa1VpXEZn52hjUxEVoFwn4Sy7wpcYgWtVX79o2YqWXrtMYzS2f7pug5x2ARvkKD0ZuZ+CvVxSmE6ifqu1NFePqLNqH5G2shlvCkBna8DY6dJfTA+QKXyZ4bD9kit824Cc+JCOzcdvRfVTQtwqk3h1cimBG1QA8sl03Ujq++JAz5oiFiARk5Q5ZSk5aqD2cDYMsE55M8uNWUwi1E6qTM8sVA5/jK6S3nuHQ1opOVrSmYQEvTQHD7W/eTP7SV6GZubvjJcZKEnVRarWOjqoFIooi1EttNzdBkwS2AkUHc4mOXd8Ddm/CRTsm4p/j2NzfF6aIXA9gpCOwnpWVnfdqfN1oyPX8lTS00JZG7L13W1dquxxo0SIGECOwKsC+Ik6IBNqqKBlc6u7rZqWA/NepsrlpXh4HAMG4BJGZmvOBITgpyitSaBGevrI4mBNBS6yIqeHOvt7ZY7ZEWh0Oc2ciLe/HW/0Ba5la2WjMjeHXWEETEJFdviStqAFOiyMxWzbNbad1yjZ2suqmihcuAAjgQQ5d9FrOQMAVxcYrsTE4wNzCciQUhphiDm+UyW1WFTeOMQNIJe3v3GE55rlBY8XFf5ml2WEwuAQCLxC5w7FLo47Hc9ZLiBT/++GK97Z8+u/X7mmeWGBQuXZKULFtVo2YPPN0aTna2C9EbT4vj9DG17xqa2Z77luXeYOLuYl1tDkEeP97cvNdPY7l/fXz95WHaIQYhY3YGuHXRWCQeTuZwhYufVbMwhmK5ycjhONzNDltfrbuUlDRYhLY+QazV5xlHyTCGkntkCuocu7hZb7o+1Doex9nV8oy5wBUiEBFmccP9w9z4IwETpOkk3Mnc2VGmCnVTnecJyUMMQata9WLV64qHtNp47/M41pyTp14GADqr5mrRocQmkTo4qlU3hVvb9JdjJlC4lChyv3+Yy75fdad2asEJqkpM63XAioiozSxJ0nq9AXy12qQkR6CUEiT03TqKT6MVK0zCiFosTzaNGEfMo9Yy9n1P3HEwUDStquTwLlCMqe+Gruvc6bgb54Md9kdzq1bzXGp1B5gLsc/T2Mji6OxOZgLuAscQAkunKsdDvr075KkFSQkzMTu8wvXy2uVYS0FgTzF0XSRmOKkhz4hdCExqVtTmnI/HaZqLOYJ0KXVRYsllOs7jEbmAAGKkgDwbc2bY4u5mSiGtV8N6vXa1PM1Va7/ui1qtCpgE6bq+8TMN9hr6LgRJuTQsWd3HeR7nOddaSw2xB1Hqh+3F5TAMtdQy5VLzXLMdfXfcb4Z16jqKkSWZu1pb2EWNwAxBLTXPhYU4rNl9v99//vKzcTrc3b4A29XVZRek2DzVg2UnsLiIBw5ETBKDMTvCf/Eb/3XxHhHVaxcTM+bjHDgAMDVXuLaOKmx01iw5eMFrGiuQZ62TEQRspo76xh+2zPBv8WmLAZHaQshGdl4slzXmTeHRrPGt+c8CgZHReS94noeb/PgUMX+yE556keAM8SznTAxyp8aLYHEZnpa4VhssSnY9k3L+VmwkTjjRkmJ2qqHefpGFGVNfluUmaadlBm9xhyBrWZINVWLQEgeyhODjjLUtS9jS474d81QIvqlgfpImeks+thQxJ/oI1Lon+tsnThSkBYNW03boEON6s9L9CEbR/Oz5l598+ul6E57cbL/+3tf7vr+8vFy1hhgRVa2Pq4t4Ddt+//tf/skf/PjTHz0lh2UEkbYDIbipNUcS2ozsjJMR+ufj5+MfnOEnk4M5k1otDuB/+a3f/vCj7Ydfe9KlkPV26FS11urs3bq7vFxdJ+lNPTANfeJUhT0E7zpWr6EbgO7F3cP3fvzZDz/5wgjmUg21FgFSilY0hDACh8MBgFs1EDOZA2ZeoXAOLq0FT3OtuGLZdTjcyBffxbIBbLMfCrd0DrS84gjS3W7yp3V33P0Tv/YX73b+2WfP98fjR1978sv/0LcutzddCNN4e8BhHvP19tEH78nqO3Cv43Q4zujTdnOzORwOSLCuUM8kZFbclSLCingwD+Uwj7XmfgirEHuTKMPxkOc8Efg4TXOeikKRifOjR0+64Xq/v3dXIjocxlxUJAEuIVArjViqeamZiDfbG6F4eJisZic/TkCt7VNTMtbA5MQKy2ZTF9fdwBIIdCh5DHG83OJyG99/H5dX69X6nRh5cxm2N123IiN3xKI1l0nrIZcy5Xkuk4BqqdNh0lpS6LpuYFiXYohBUlR/rMX3r3euZlob+qClznWu1XK18WhzBjOYSYuD0UUZ+r4Fe8PLND7b9GHdhyFS3+dhmNd9sGLzcTeOxyCyuuhqAZkSB2Z1quqmSl71yfbmMm0760wtVr7oNpH67XCROIpDQELkjkiA2zzPleZA6NM6rnrVMI6FTCJJ36WaTW1EHz3OmRwSJCRXOy8H5uQWCGAJtexBxnBZooK4rbhEYFIrc7ViiRBN1XO2YsbBhIil4TampqbqbvPxOHUppqQSjShwKPPD/uEekT3JOM251NilNTZZa0xIXexW3dX1pUgwV3O9eXL54Ycffv7ZnSMMq4vDfjZo6sNWVnMpROiGfhhWt/fH1UXPHrxi1a+p53qcdbTd/e1xP7GTFrfSJOJorfYIi2dJS41R+tXKQ6BIyjnrjsSR8P47m/VqdXgYb5/v9nusYIQkRKxEToFDpboYBGEAFspxeXDfSug+LfqLNIUcRIG74zhJwGbT/cK3v/G//Z9/V6ijGOGW83S/e00mZW6oUSCqZ0Sg1IqMquZOIgtp5gt2w0svZqD9bAmBaGdBRLwg+IuSfqEjsewDT+zkGW5qpd0C2Jyupf1D3Bi7s/zqNL+e4p1wKtEAdvK3Cb+3XukrkJYvLKIDOGlHyE8GtHahZwnXW2pxd/clhB4Q4iXt1AF1Cm8OQsRO9tOWPF8mVaNz4yI/+fB8CZF6cz1n7IwWurc9IyA9dXEEEc5J2nTCZRqQ5M0DIUtvXLjzKfirXebpOn5inDG0VlefHk2cACw/AVjMS3jZCcBy9zPydyaeFy6kXSEvC4vCiZekXTP3WrW9H8xCp7fUyU59gNBETkTurmcu/K1dxXKupzAw+qof8q1P8O950PmuWWJRgoMd5sQwdV0es7ZUckAIwhScvUJbvBLUvDpsqfUDmCnQIp60JbzXccqbZHd/g1tVVNhyG7IbzM2a865FejmhwIjAQtTg/PYLy8s63FvLSW5RLiCCB2c4kzEpL7nDAhiK1WJKXtyInZUpZ49dhMKqixGLpBgBVp01W5mL59rC9K06qrddXCASMLu0qHsK5ARiphBIHOIkjBbASXABB+YoIpK1lly8OgTzcaZEnEhISilMzIWDiDATeJ7qcT9qVbBxaE9uHFd1XM9RdLMi71Mf+nQxxG793tc3+TXunh6O91m6EGIHdxL2bOTemi+AWvqLL4qyxeXaHmOIyKLBa/E3RC5iROrNY6LOBrbQ+TyOl9vtR9/4+KNvPvni2ctPf/zs4cVYR6SBqVJwOLmjhTM0hSOLB6A6mZMSOzl7y3lxwBSuYJl3arVuVpI2EUGjBLVqDfeC1KpzdoZD6TBV0jrNRbJ3MjOhlFyzRol9coZShEgUCXmqeSrteRSIG9Xqms0V5KzFyFHnIgQS0lprkBBCSDLn0jJtutSnGFEds9VaVR1kLMKKUjQju7NXYuXG6rgRGYPg5mGdylzmKUvgkovDQ2CDlVJcwMoODjGshj4EUfXxONVqXYopRff10K9jElWfxnkcZ1jp+n41DMyYJwXmlFIIKcWaZ68V84QgnLrIUPfgBHCAV0LsunS1veq7IU/l5YtXsG6aZiOqjpy9FriDuDLNq/XK1OasPOUQvOu7GFNITEIkUo2KwRGKZVWFq8PNYGZF0fUkxJakMJlxUw1pZOZk5qqpmcFjIOorPArnnIsZ5XkejyXPVSvI0UWkACeast7eHeJBnjzqh6GrdQYhhhgixYA+hYt1X9WRhFRiDMwUQuhTAvx4nB52+3GaCOj6bs6ZJTXX+jSXOZdGwoUYiUhCSEMvKY7jNOaZXJ2hXmctAzsHAVMxm8e5zJXMY0yRMdUpht4ctSoTJsuTj5+9fvrJ0x8zm/kcWbgDR9eslufqLhwis5Bf31xRYBZxkRn1+799t/mlrh+6qcxGDjM1RCE4mRpq68pMBJh5Q2FaZcLMC8ZiVotqtQBxFitqtqD6jTUQJhCrFWeCwdkaRXViSZrK9BS/sui0HIC2eZycEy8tslp8VGsfe6o1Wg660ULxNVSEiclx0kidFzE0Fo3ArY+JO7VcLiyCMWlYEpwXp+NPrd/nlbutA+ZGxnSKZjgtafB2/goQQjivlc6BJEijuVSthWedu7WYA1XfxpXopJrCEh4PM2tVU6tY3M/L9M+gy07ns5BpvrRNXLYL/jbx6BBhahyit/JPWZC6YHsVobv7V69evXx9+0x9SFGPV08uV9thWPUSVttwf3jZp84rQrd69/1f+M/+w//xh9959nCLxF1BPV2PncpqdXIHe6t59Ofw1c/HP3DDqZVpgJMa1UK4sv/g3/tP/+1/59/82tc/rDXncX/Rf3B3/yI65akG7TbDlhGz1S7E7XaTaSdUY/C+l1xr6Na7ff38y9sf/OjTp5/ft7JRrbU/ArmyaxcDox4O9xAALmBmKmpeiwHFmCxQILeqalMpwJm1bmXxIjRlkBngxHD3SkuXcDYnuAj1x6mOL+bPXuFX/vGY0qXuDl8+e/VwuLu+vvjmR+9ebbbPv7RxN9VJpZerq+Hb3/jmH3/3symjiyChOITuIlqaHT7bDHMF0CGs0V9y2nBY4eHlg1rpt5ddL8wRLrtjhYUYA4Sy1mwgcfVjiHW9kpwtlwKXWnKtNs9zKV7VStGSQWIKqrWkNAz9SjhOxwpkIeoTKDE712qqNefaD9QNlDqKvXXDvL5A1ymJxkDXj94JQYZV9+hm9e7jzeN3Hwtj0uPheJjm8cXrVzENqpSz/1/svVmvLUl2HvattSIiM/dwpjvU1GQ1m81m0ZaslgXagAcZEKA3wYAN60U/x/4VfveL/aYH2wLsF5uDDdkiZIpsspvdXV3TvVV1b90z7p2ZEbHW8kNk7nO7Scp6pVwBVN2DM+ydmTszYsW3vgEIoIgiUlPkMEjaRB3ryJU76Yhh8IAQEZTNY9lfdHmecy7u5BCLPgetii4OMQ3ucpyO43jcbQeJnPPBvYTAXR/6jqyO57swJLBNsHEebzuyLmwQ3bKaVgKlJFAQ1a5D7CKHnjiIhye834TOHXMuPXX9frPtdn3YUMWUpz4mxGClLJtkAMZUiWIQssvt0yEWNY7SJSIW1+Tc1cIHtYkQI21FErecKTSKDMMDsbu7sp2WQRAIRqQEEFWgmGWr3rjNMGYIkbAQM+b6YFa1ZtcqInPO03HehQ5KpRZy5Fzu7m+77VY4VVXVGqLEFFLfAUeDARqT9MNmziNLTP35u+8+v7r64mcfv97v4jSXUkrXx/1mM3h1IpZITDQg9QmVilkIIXKaM27H2/EwtWDiOlcyFoi5kzMIxGCDEW5v77a7fb/ju/E45sn7QmwCH3Z4791nfdd9+er1m6/udMQsHoyFpLkLSAiVChjGTYCijgXNWbCDtd8FanFubrC1j8hwCRyrFnB9/u4TfeO6zX06M6pqGKeDK3sReCRiM1doS7ezxYi18YGatC2YK1Z0wNVXKKTRFk78d+JGnmoKkqVfuNRozc17nXhaMiqDSBvM0fjjaxJ2w9XAjXe+kiNw+v9bXcflq7+iqMMK7vwKjPEWMPVYQD62SGmVUbszCRxmreNK5GvHsZWagOIUF3gKzqHlcNe6zdfScdEjLE1XOCAreLXiuE0n2vw5iJogYGmTLofWpu3GtaPl3ehUOy/3A4OJ2/vSwuTxE7T011yqt+pMomURW8rb9rPV/nx5txOC5WvduZLMTsfamigLKMAADC5EEG4MCxgtIk7m5vNlDR5AU8CtlDVb+Vx/6bAbakNggzUFJVaAqBm//iqo+a8dxG87+S7VfVjd5VZDK4UTeI2+InPSJr5khzVwA7X5mxAKiClAADLXFlZFRO7m683uWHcDSoYKd2EhosY4JabFbRNCtGjQTNiFQO6LnzQRsTA37Uwz3aW2tWt9KnOok1F7wt0BIwKRulatubKTUARQkIddhDsZk0N8ud/dWVVRwUYwJwM1FugibSRqQKxbc5dxJ5CgzSHkLO4CdjJuPXQiYYOa6TLdAOiahaKLcIjJyNwgHIhYPJZc6uRaDaHZ/gVT0zJrrhQyOLFUCR5DSnHYPdnGs+3lmf74J5+oqpcJcw6hZzdTUGsEuDoUbiJxvZnaJnOtiRq30Nc7QogcVdVRnJwDSHAo94g4f7K7vLrYX5z9+F/+yfWbe65dchUVLQo3uDXaWUsmdSKA2YNpddIWcyLOxuyAmUALsrsRKupR4z4kilFCzbmiskgKXZfGGDoiNmFzykWnqcKyW+3n5F4cpe/TbhO1a1G6YpWmKR/G8fxp326QXCzPtU5OTgzXaoGhuUYRZ8q1zvOknmqtVZXgTUpdxqJzne/nfJ+zoh4KJ5rGotUtHxjRKlzd3dkIzu5Opk7Wxe5wzOP9kdhUlYSYhZiP0+jmHIThIYQQWYTMldhjkthFkM9zPh7H3jpmCbE7HI7T+DAMWSQwh2ka3alLQ4pRE0o6zBk5K5M22bEIOASm6O5EIhxTGoY05KMe7sE8A8lc5mrTPOcCdwiDGf0m5ZrzNJcyh0DnZ5e8l8DkjlLqNM+51BBDTOpzqdVVXRXmMAN5IiR4MMU8oaq6apeo78WRrCYEZiJhDzFsKAapk0zjmEuuVgsBXUQfKcTUdQNxPIzz9c2dQzfb7vx8N48HLVMIbJrnmdRyTNRLPJRlBQkhhBhFRFXNdJ4155bHExxQNw5EytM85VJEAhF3m75p1N0t53yc5lzmXiT2gZxdXOHVvRrqPF9f387HKZDst/vNIN/c35ztzmKIaYgk5GQPx4ebh9u55s0+DHEg8eJTcDXOECV3MES66OHqyYXVlDgdi312/SnOISm5KIEUquYrR6exFB3OrcSB21JEtsDUhmrBTU2reXU3Z4ifKFLNK73NvExqK4DRVAKGxrLFGjbcGIKLuMy1reLq7gTxVgQQndR/9HiMvn51kncvrSUiZi5aT+q59vvcpIvu7IxlcV/X3SVbcCkzWn35l5fBtTlC1PjYS/ANtRMBPfZksBKVW8sOAAlJEGZyMyNrpgBwLPOfqbkRLwy1hZfaij1qmRxtnT41JRc8DacS4lR5AGur8JGZjhPZjU6lzqnkadljtPQtFYpaa5nnuZaSuvD5y5f3D7ep67ouqZf7h7sAIXedp7nWalN/vjVneNwMV//sf/pn080eBmKRGHR2XooZawTZti9p+CGcH/0nvh3fjv8fDIc/imiU3VEVgP3851+VHBMuKHiN9Unc18Gnw8HGA3PsMZSWKU4YUprGXGlSKzGxAo709c31J599/eLVV3cTUyIFOYwZ04xpOqbmq+d5Ot5vAthBLMRUzBC4qVuEOUoESfaZeXEmIG8pUe5tKiYiX/SDcCM4LdneZs4EEolkkrOi+ldf3T19ttufPX39Znz9+uEnP/74Yrt9//nl+e6JFz8e5qGb99v9b3/0W6+vDz/5xddCyD4p+vPn200N4/Fwd5zVgQ7bM/R7HrYxDoZQPVqggKChZ0DHY60o5CFyx0KQBSwv9eE4XgMak9dqpWoQZoG7a9VadJ5qLogdkzBA7qLqtZTDw3R4OOSsIgiBoaTu7JAOFNzIiyMBcajDFpsdLi7p/Q/e/63f/I0UU6SY8+ikWm7vx+P9w/2UM1H49OOXu91FipddvNifv7PdXrIKVbh6Fwfb2MPtQ54rkWip4zQd8zTnaZynqdTvvPOOaQmg1HfDMAzDICHELnVdf3a2j6krpdRaXr58Oc33bjaO9+pzP4Su93eenKWQYcd5vHY97rbpbHu+TZuS83XV169f3Gc1xcXZ+5tNYLJAHgJJDBHpKp4nDw7KXM08pa6Pm4Qu61TGoigIFVYJFGIg76Ttq8CKmjh0/d68BQm6MJXghY8P+WGezWbuwv5s86QPG3OPFIgYFFpUXrP64TUVBq6AEZtDHRqDK0yhoMDSpc6UAoJRcILd3h/ci9UchHebTYyhMQihqDn3adhvz4qrbDqKYQFhiILEi4vziyfXw9CVMt/d34zT/OLl6+3m8umz715cXXzvB7/5v//hi23/OiYutRobRSahkKK5H48PLChLrjllNZ3naZzmOQMkQaRSriVACEJoYBPBGvKnh8N48fQJd93DNJbDPcTRYb9PV8/Tk8t9Gevxdh7nAkZRsmpQt6JkqmS8IWMHY8Gn3JuPO9ruqmE7tLCPzJ1XBkFDs0KKNQFUzBQAVFgSxxZaqOauauxCzlo1W+FWKmjzPWKGiERws7swFmJmc9NatDn+0tqLc2v1lT2yrn7JRnw1RjhBOiecAUzkBGZuFlbUCIdNS0MEZlqMrdbqx99mYC3v0Fp5f2k+ppVTuvzSWlxRc4hof0vEprY0W7kJJhuXqVVT7exW1pK3hL/F6plAbub8lnHFcpRvgSe++BjBTt9ZizdbC7f2BtRKUG+TM2jFbht5v2UKvSWZWE7R8QjTnXquTTBIy5V/RK/++oaon3Sga/XdrnbbFKyYoS/Fubstnl9LGbpGeHvbQbxF3KN20SDcTtsW8qCTMBNxkIY3td52q4aXgwZaeJ8Dq59/e43VLqOV5u7cWFjrduDU/32spP8NBvOJR7Z+iyi0vD1mdnYKTit65e4waFl8qDwJArODHKxECCI8TRkCjgwjUVezVv1rBUg5kASQE7O4w2uFqYpL5BAlEzigyb7bPaPmDoQQXNgMZgXk6qaKQOJmZICZmjtpuzBtpdfmfSWiYmCQcTOfA8jUfc5mDCK1qqrTdAC7cJAgiI7qQgEVnp0qqPKqn3NxYAntcNKGeZ40sG/BzKQEB8SEGkbNIu5a1NR0gTwNoZPqSkAIAYSxjHmqAGKMVXWess4VBhgRBZFeyd2pKAR1nOc5H2/vbi629cl5StthF8/6px06e/P1zasv7wEvOrsQtwKiUdBbqlcw+Oo2vOxUvQnBhUMzr1EzXWJ1rUHzLvCAi/Ph6p2nH3z3gzmXTz757M/+/NW+61iTmHshnWdmIm5uxa0RxOSiTg4vWrwC5gJuwBkcTMEcNk8gAeRwN9qgYbvxyPOYK5Vh2w/DrhSXmNwDFudBgIJZnscMU0CJNYl0fWIgz9UdVslK1cm7MLR+nZZSZ0cFiLS2nAzUXLqhd+a51LFa9EkVXgE2iTHnXA7z/JDrXKnAih+nsvI0ME8zUAihbVGlGV36Ekk5HkcYquk0TdUrQ3MuJDSO3m2QUiJiCcFMax2nKWtF3w0EHI/Hl6/eDLc3u+12v9sFSe58f1fv72vXIQaAyIymsYQYiYJwguW5oOZpmjj2rqbDkOBkSqVYDDZNRZDmqZohSWcmlTsKFLpEoU33TsCUzZXVea46q3fTTKJjVRHKpdzfT25IqZMYh9AtxEcOwiGQMU1uMk+W8+xL2GxNKaWUQqQoexEupVkb1MaxFcRNH7xD121qdS3moCCh63uO3eXT8PTpWS7TftdvNnHot3mCWSnlvsy3WixwCH1kQ63VYWpO6sWqmtXqOZsqJHUhdQ7W4lFC8XrMk6r3qQ8cN8NmmuaiNk6zm5VSnEABKSQ4GWjK+e7h4fb24fbN7ZdffDUdxmHYPXv6/Or8qmab87gZtiGE2KXjw+FwvOs26Z33n+/Ok7s6MpFWHZmcqqnNqmLSxz7e3d2Tq23Hf/WTz//7f/o/wnF3OIZdkBjgBvIuSVssBcgNHScGSJ1cG47eaKVwc61WSvEKVKiag9wJYDqtgMscTyEEI5CgWasCjW60LJGNaN0W1yXWyVffJsCNXMmYWJZ18bEv1ubLAAAgAElEQVTHsrT1/LGxtv57Yj0t3bW1AQg4E9mpRCDAwSxEVN1wahHB5Zf7MqcXXk6JlyXwLdOGdsoOIISgtVY2FhKRFqoLgrCEEJysusNM1a0ujhjmBnVTyCCN6su09NUI7uTEjbi1rJpL0XRKdAWIyEwBWvedtJ7fI7z1dlGy7AvWy7ZcqWVWRvap1lzqDPbtrv/kkx+Pxbe7fewE7OM0RTwwSH3yebq43ByP4+XmmVX5V3/8Fz/9vXr+3WnXD9OoEob5bqa+M5ij0BI5sSoy/40Khm/Ht+Nv/PiVfjYRXAgrn9KcQLi7Gf/X/+X3nlztf/A7H0Q5fzXddPGcE4ddF1PXYzvmG2EWI2OapqmWg4c8DMJxyGqfvfj6489e3t4j9q6UBKw6pxDsph7uv+F+8EjQnKepS3AN5kTsqFViZ1AxFjSfF1uYts25xgCHKRjGxDgxKRZbE2c2ILiTm5EkgM0sRClSf/Qnf/HDf/+jYbcV7lKYfvznX+TD4e/9nX/3ex++92R/8bOf/4KIif3qfP8P/sF/cn3/T7/8Ql98dTfM8YMP3x+nh+vbmi5IEjb7YXe5QcSYj1MZcx5vH6bNEF5dH/seueDV14Cil3rMRYTPLvfVjpsdHHp7/VWMvNvtrWiZ591uF0VqJp2n7NW9RQynxkEVSape5jpPuZSiDSaxCoOAQsTz99J2S+eX6cmz7oNfO/ut33n25EnfBTOMU32Yx09evvoSys8vvh+wH4/TcZpKZuEzks0/+Yf/aKzyxdd3v/j49Y9/+vDpp3/y5S9e/exHX+LNYhWLB2ACApr3BAQIgDRawY/hQAUyUAAGEhBXBTYBPfAEv/vDD77/g+98+L3vXu7e32zD7ixtepmmr3edDJ3x+QibUkIitjy7p6uz/t2nH2663hTHY87VVMVM8mSei1TbvbelbOoeQmAOYGKDo3YhxcQEsKGLseQMshiiGTm5Vaiyu/dDEgKhMAChSnqf77/+5np8yMe7mmj34fvff3r+PPHAgQOFJmliLqBIXEBoYjByBymRV8tOmpIgyFxVQUQSQyJC9TzNY0X++qtXHEGuZ9tNd9nv9+cpDkPa1Kqqvt3vPXG/22jAqLkBSodxilGePn2nuseYbm/uX736shT70x/dXl5++t6Nvvfed3/7o4+evPN7VGU+OhHUyu1dCSmepcDCWbMqpmnapt0w9HWu169v/eiRAkKzRaYUExmxM1zMXUkXwrNDq+VaGFAvGChtmQf9te89u3q2cdgXn3z69csH1y6mWMZSq4lzy6UOQoUJZCA4myvEW3AzLzwVGBFaB8yx5OY0XIUpeHWFX55jv998+eUX6IBukNhzIubUDzSj1NncHq1mPDWWlFEMgaJYY3ks5CQRISIzK9m8VhiEWh5lmwfdAXewkJOt/JQVJVp4Jm0n7muzkgxw86VjvJZ2rW3I3LJr/ooe2KnkW79h7q1N+avjZKiw/iGaj5Cv+BedgDRaQbWGXpmDV0CkAStEcDd4dYgTA8QiIpNmGL1dgD2uDEQL5IQ1kose0ZQmr6O3DtEfyThtKSEsYnAzN1OCvXVBmg31ryw/6+UgJl+esEfo6nS+v5TasRyruy9YWOOd8OL0sbi4NgmhuVEz+rJFy/j2h7IIFf0k8ny8AZpkjUTUzE3hzkQsHJidqaq5G0yXrvSyHxAsQsJfLo1B7eqd9gorbrUAee3XrR382gP+/xyna6Sq/pZ/VuDs7oASucCd4cREC8zpXsya8y0IpsxxIS4yCxEse4VlJRE250ouDmeqcNfl0SVnaRfTlvMhBxAI7GioKlbyIrm1EIDaGvoAVXdTI2ciWySdxoGX3Z6hOeiTEwucjJiCSLDAItWKV6vKXt2bBNIMMxDg0aDsamBWFFPXuWqtzV+rQRLt8XRzb6QoMzrpcZywxHcZQHVZ9aj11gRE7kUVagxg4TgoAFU3dQaLippJDOQMs8CcZRFKa3aEauYMhgoQLQ+H8ZBrnc8OEg48eKYH8LT9TvLd7lW+x2x+mxFgxpSbLFvgMXDzLVP3hiITCEzMFCAuEpq2HyBYRQtFNniCCxDx/MOnv/4b391d7D799JNXn36FW+iVWzYtrsVr1hCiRCJwm6uZ24ZQaZmwm2iIiGydFsi9whRKRKST2tHm2zL0vQDF1ahIiEQVym5mlVTJXCl4pChMFBK7qZd5djdVrXmuZuSOWhUEgai1yAsKYBOgKZPdHQxKRj3InSuolIY1MzhSTGEJbFBlZ4nBQVYUdZl8rZiaOQqYwIzQHqGWwwE7Vh4khS4Ql1qKoUwK5jojJgROLCIiblXVtRR3hkvJNk0zZoyjYR4jYtd3rAl1gmIusIi+ZyeZDhY7jzF1UTLfz1YaDUdBMViKHCUVnavRPNs0Vq/5eLSq7HFbFOpi1AzrmgiBRKjmiZlSF0RIVZXqmNXyFEKoqtMEU2idgdldhGOXuhSEhM1MYqfu01SPB621EEDwrgfzLILzrYXg4zQrjk5HRmCRGFJKXYyx3wyl6DzXFnUiQsweEg1pO01U6qyFY+AQkyrlOs15hMPFyDM4OJGqNepPyyJRrUvrQc3VSq0U2VfEhwgxhBAC0LpHWuvMEAkAgnJwSapOIc6qmCcyPpb6MI/HebKYzsk84eb4KmxqkS1m4B7jw2GaJrMCUqUUI815JEEIJGGgILVAq0XzzsBhs++fD93T491P//j/+RHOAXYzlxDMVUAkjCbO9OWp4UVtp9qW8sbmddbinp2yoLpXa40RrPGh4mzQ9gqqHlI41QGCRT4DR2PfmBk7o30F45U41AI6TLVVQA1vWWjCdMovpxOPuk0gLaVlucW09R0Zi+zbTz0oxuJwZut8wItBPNB6hquBV+tNsQNoLUACk8GJTMm4bfga8aylg5MQSCQ4jNid3diJQEtXdMFvmr0XlgJprZQcHtwBEjjD2ASLjgLWZH+8kp5pBflsUWajGSf4Ysu4xE43znVD3GhZgOntPuTiiSVuIFgUjxXkVtWrMQnFaF28nrNVpFJq7YfNziNnzIFIRFOMQ9rcXU+b/RM/dn/0f/85tshHBIpaJmED1L1S48g1LvuK9BGgZPjLtdW349vxN3OcWv7N1pYXrW6b71QgLd4CTQy9NITZnYB0OObf//3/6z/7T//+3/7bTxn7r+7n8/NBU2+xxi66CUk0UiepqsJS1CR4FzkGvq/lm4fp+jgZSdcN2UVzZYoMT4zxYTxLPczM1akSg6Biom4u0FLgVllyzW1WqrXW4u3glmnKFlVIS0fHQp5gkNpy3s3EJKuRoabEINy/tuvXE2y7HS5jP3z8s89/8uObXXpxud//+gfvPH12Vc0eDjfq8v3vf/9v/TsfTuPPX7xC5QmxRkmSuy5ut2ebzWU/nKVjfbi/PRzrrPDLdzZd6KuWmNjnGTJFIKNotW2Xrp6fE0KIlW2ejkqbDhYDPImlyH3oxmMpBWbGsBRIRCuV0KU+CZEREJoRqlpWsIADho3vN/jhD7/Td3p+1T99ki6fxKeXlMJxLvd5msbDOI3zRp4+f/c7EZc19/1ZutqHcbTb23k60n/93/y3Q3h3PMo0umu6v8/TDZ7i6g73qhYl2WDUMZOoeWnmNZW8tB6+IQYIUTQK5uwiLMzoHORlLl6wOXQ//aM3X/9i/PGT1+6FWLe7FJP9F//lPxxKv3l2tukYyIQaUTkcj/m2WO5JBkqzTr3kPjSBtzgzcRQNjKhWSi1gitEih9aT7kKPPgWFu0mUbDxDXaeqhRksgZy0kLIzC5mQAG6KcjfeffPwJk/lzfVtoGF3tR/OBiMId0IJHskDwZgnogI4ucHVrYCAJX6tEJuIQStB2Tx7NtHi02G+e5gPt/MhGjO86wdQ2m4vREgCQSDCzLTtNmAaNVc3gcABs0A8DF0fY/NYz7lOU1HFXPDq9SuJ2/3FO3//P/7dTz794vOfX88FEnic1Su5i0gQTvCs1eIQt/1wf7zP49RpaNbNxap7FBaA3IilGV6w0UodD3FSB01ZRuno7Il3O1w87Tab7nivX3zx1eEGyS/IRLOYzs6gLTOgVN218Z7gMHV4c6NbeUUOgJjE2VWbbxAUIHanbMEqHc4unu/Ot6+uHxCBTpVnF03dEDuZpzuQGVc0Ko0RVWJjsrjywrXpuQJDOAqLw0nJTaFN3URE5NT4XVisgZbpsm3FVx2ar13JZZAxkS1tO1pkCw3fsVZGgQwCNnF3r+aNz0ME+GJO7m33T+RkJyvTt7CaExTWqCGPFKRWZ66/2XAi4JQ6Q0ayGnBhqWXBDDIYzB3mjfXWXIwUC9HglxeLVrs1JGpxRF2PkReLC3boikssDUkYOTfplYHgwhAGYLmaG9amJswhjce/XOeTgIDb2ZmfLrrSopFES8ylX27Ortdk1Sh400surhPW2E3UwgHc0cxCeHntZe1o5PvFo7t9MAt77S1sDiQs6oCrt4+ZxQmuRmquj2otgE6H1HDAVvCe+t/M3vSX5M1d3qCw5jl3grBOve9Tf9d/6TNatxYnXegCla3Qs7e9SsBYVyVII5xRO1IR4SWLygREBUwSJbTmc+tUc4SWeiw1hshCpK65sgQidnPpghczqLGYGczBIIGRQk2sVRJrWBQL+Sp34QZ2gRxs7NWWm0fN3RGbcA1oZphMruTm1YuONQRJMXk0MKGCCmgmL7awNAkSBQArk5EVLW7mJ1N3tFmggVPqaBH07qTWOAlkbG7mjRmhBAHA5jC3aCzCgYUMpuq5eFUiSAQiFUbjT3j1rktgLlaG2HPk6iV1yWBlrk5kqloKCxjBarTKk8e+f6djfbi//bR8+eT5hrcxC6V9+uDXrtJZOLyZb18e77451HvzakSNby0s4py1pTITE4NFGASFafXgpWYOUToJ4moWhzjP8+Y8WbSzJ2f9Zc8Dvbn55uXLL1++eC1bUA0BEdA8ZyipmdWG/cPYjaq7uZm5hZicwQAZSA1ubaIHKhhQFRGt7ke8evHm3Q+e1d3GrSodIJJrYa1e2Uyqo8La/tWbgVEKOZdcpuNhclVdqJvrjV+9HMs8FnJPKQCi1bNVBzmEJZkHECHoMtfUDAIHDoI6TU2OqsUQQpBExVDqMhM3i3youxGbcJBAIAkOhWdzFompk8CYplJ1FncoCsZ73NAxdZHY+77XQnUiAo21aJmmae4CzZPXWfOogSCInUwkweGmNh08RGMiK95fDJtdgrLpXSmlmsNonhUWQkeHoxPxlEsc5+noNzfj3R2RcVsGs2ctxc040jB0fUqjzcQuwsxStZRai7lDNDNL3O3hBi1UrS6Wn8IcGe5zyWf7fZnn+4Pe3uQmhiAjq8TiRef99r7vBFIpwomc3aiauSsMllInSXphq661mqqVqjoSUZ7mOU+bGN0wZ2ViJzYQB3jAmB+Ud9VRtMKMpUROrQERI5mi5pJBMO/CEGPsYio5w3zY9Cmm29ubLnUO5Bl9P/R9qtVLwXG2POV3ng1lKmPWMo/HPGvguOvDLmlHo+TLp33pHq7nuzev3ty9ue1C2m32MUgtdcq4uDw7jMfYpZyl63uKHXcy+3Q75vvbN++dfyRhW41vbh/evLnfbKNFscAAmaorAjd4iV2Nmp2VKWDspgQCswVyQWU7VBsJmalSW8BwwpUACBxU3QjETLV5KxJYuBmmGExrJV58J41aD6g1vpyJW2iOscHMXQ1M3mzPnRbSFtwbc5iw+kYRiFkay7sl/qxU6/ZDcnj2HEJg5oW9BLjpI+F8xbCMG+bPAK8ULnciDsHIqldv67BToGZGDm8ZQyxVjTmKqHrNqBw4CFGECJEvFukMAZu7NvV5W4qdgdCIqU7sTFDYsvy3KwxZml+L5YgTyVsQGK3r+VoEkZsSMU6pGUYgOFPrFYLInIiNQzUL7pE9EciteiRh8OxWXHPEpu/hngv2l88TYc5HDtgOcZPSJgzKHY/pxWd3v/+//RGehHzk8VDYeT5MCDCdhVaiGFqQDREZmsfoX9U+/XZ8O/7mDSKrC1K/dNF5ybKxRhRoGaQEbx4UYFBw4sbAOWb/4z/62TevJreNkiR6Nh/yvr8iMWc72CGG/r7cT2oP07zbXZT7+yhhCBDnP/nkizcPYzZzDubSpc10vCOjUupZj+kwhWfRHIoae2oTb+CaR4ubVO4zxdBysuY6CQNEsUEObYvjYAO4SVRgLROXqPlEaJux2NFspNs20wIUIdBXn1+Lx+cfXkp37NLLOukXX7z+yU/6s/32/PLsMN7cPrwBhzy/+Pf+1vtz1UN5YdBXt5/stk8hxKlHGoqLFn2o05HmOnhg8IHmXJlDtajGCFPJ4A2clbo5DgZ38pYo0ifZHe+qu/UhuSp4DqFcXYTLs8txznMGR5OAOR9jTOI2lVznYtV2Q3zvyW7Y98+eX7z/a8+urob3n1MMeb8N251X3B4Or+5vc8lTGXVIV1fpexfn7+7S5cODfv3V/YvP3tSxq5lv30x3b/I//4MZ4yc4AgwEoAAzhRLZmZ2qa1usiOHqngsxs4gZXA0dY65tzmZiBomICPto1ZQ9mPvhvhyCX38+fmJvlq1nBBzvxy8223h+vhm2vL+M3/ng3Xcud0/Pri53v1F9fBhfi2JIuZPspEbWDEvUyQsz+iJcctVSVCv1qYtRmN0LCbtj9img046L1XG6L/mw6WIft+IxyA41EsXAwbWqTSo2lrlSkYGsn41xwDc3ZZOtEPciW62CElMQThfwEa5u2a2wm6OCNQRy92IzUJkqk891qnX0jpR01MP18Y0mcCDNNhad1Hb97jDfz/kAsd1+M+a52wyD9J4hIvM0o9imH/a7HQNmOh6nlOJm2Jvm/W6Cp4eHN3d3F3/6p//iP/yP/m4abHwY/+KT6/6YiJhZpqn6WKZD6bvUebftNtE534+YEWKF1sBAEK1uqqYtRmbtqDWPJII6h20fuhpoKoT3PjzbnQ9xcHOrFXcHizTAhHLcUK/DPNGDLq6pBYoQOUr07LUu5psNSWi8GIYws7sbzF0BtJgvoHI/Q/Dk3Xcv37m4+fozdEA3awCCSOpEOpYSU60ZNRtLZCIUoCBRqprbPstVmTl1HQd2YnU1raTujWPSBMeyUNgXQtGSSex+suZssMLK+mk4CwmbkGqDsIyXRD5bQA8CxIMwiJqhj1mzkaGWSNf0UQ29auk89W14Yq3cAAJ4gbAapGEOU1pLKXecgufMV9bQQhShxmdZra9WZOXUMGz1Z9OpPkJzS1ejsZweGf3tp7Y0Z5mJnVRXqGS1doewL9kG4sEpMEWBQ6t7IyiJwAmuFIHV3WKhj7hzC5smqBpWEGnZuy6nC2Py1h62dUXDQnmD+xK5aH46qhMctHyQarQuEifTD6BxA80bf4WbAbm7N/+tpo9Cw3mNeH1MyE29arOgEBJHY+yQE0hPMBKYSZtfSZPnLny4tl9wEKnp8jZY5QuPd9uqpMNb5fPSa126rQvjr12etTHcjPcCg81PqYle4MIcU2yMRCVVVVMNbXAgUPP/dvckXa21Vi21iHB7Zsy1MbQCSYGbeS3VoG0TxdLuHoU2R5ZlXSChFh1gqla8cREWmlM1AC4MAzNFSdly0xazL9Zqbm6lEiiXapORLJYrVYtl9cYPZICQhs7JWpSVm6maQQkNG0fDphY+IcDCAczOzQtNTbVlBVh70gSrGzI5qlWAhUhVq5aq6kBgSBSKjOCzVSg0q8FQPYCTJAkiLi4WJFhnVl2rQ8CJWVjV6pzdYzdsKdB89EM59GeWtrtqlgaJAz76u9/96tNvJLxSzjr4fGeW3eaKUjPQHJoWJAlwg7JbhASm5G1rZly9qonRhvZXu7Mn+zSE93/tvalML16+fP31q1ev3wQhVraKLgVv9JXmh1zd2MAILb+U0BgPzNHa9KPqVb16gHBz3ne4u5mBMB0nT0gxbsLGvGY4MdUKqq6zqqoBCOSAVXVzYgJ1peR5LGWu7h4ChRCa+41aJQq12DhWJvQ9sYirESAhOESrM2nq+l76RqvjEBq3g2bfhn6mWqzWbFoqEXshr+ba8EwnIQrNdwLuLoFTis5erSZO1bXkosZwijF5iwdmgHB/e4Rg2EY411LnaW6Pt6qVGcMmhlBSTDHEdisySUrBHVoslzLXQmzMwY1T7Le7XS5zrQUV5WiumMZMRCWrVjPVUtQ0Hw/T8U6t3ptJiKKoc55hxokCc4yh0Zqr6bJS+ELPYZbWMwOzC+WJqldmdtUyZWYWllJ1LjVXzQXIUIHDhw3vdxtgmPI8TnNIxMkp6tDHEIITleK15FwQJEZJLGRGdc5VZ9W8XJBSj+PsbvM8xygSwByZQcQkPI+5VCq5uJowIYKJ292kilpyFGaioeu3w4YdZZpLrVFC33efffL52X7fdV1yDyEMwyAitZRxHLXWUrK5z8fxeDi44fzirOu6zXa32e44+JP3n9588+qzF59/8rOPD7cPz66ePX/y/OnVlYsZ4eVXLznwPkoKvSkmm8Y8H6epHMp8o2f/wSVcPv7Fp3/+k5+o+qylS6FWY1CDfFu/08zMFq3aUmEtiSoiJOziRtasr6qTSyCCNOKZGzUrunUwscg8z74uDLQWLiLiTagcAoBqhQiP+SytX2OGdNJQLI6na89sqSPwSEB6iwbs3ii8a1nkS9OIQPKYnnuiP7UG3y935shPi/LaMmyu7caPuROLX72TLcRtJ7PGslg4VeyNeMayiP9PjRlvOhxdbK3aNrZxbn0xO6RTJYe199XSY5YleimO6LTeUrsyy1fr2eGxk9hY9It7wKNhA4hgprnWKK2DEvo0BIrjcdye93PG06vthiJTYknH410eD2nfp7SNIbnKk8t3gvdfvvzkFz//HMdKPDRO3eNFPRUxfvrP3yrovh3fjn/bxkq4bF8vDNDWl1x5Bic7WwKoT914GH/y459++smLX//weYxDJGFSJgOpCFcU83wc73Odu12MIfWROqm16l/89OcPx8pB1HUcx62kEEIu2iZFEQHBzUUkpZQSanH1piJZHFSx8NUbxsyRoKpW16dWACxyQgItFn1MukZngIjZwcIMUpRSu15K0W9e337w3ntQFornZ1clHtz0xctX/+KP/uXv/u7vxBivrq7uHh6ur19LiB999J2s8Y//7Kfm9OLzr0NkOCqKj84j0WDDsO0kMdPtNzdWgoNTHEC82XRHn5mx3afdNqrnPB8jYwgIKRLTlHPJc4qyGbpXX70WicNm222SCNU8W3Eitlm78zDEeLT7PtbuSj744P3vfPe9YSvP3n3y7gdPh463sWg5QOeSHw7HcTxWoW47PO+H8zLz3TflcF3Ghy+vb+ePP37xh//nn3325WLpixG7HnNFJQiILWQtULiaNSfadhu4GamqQysQlr0Xc0ix1IqqbubEIUYyaC6++BwtdpJwhzKWJo65Fjj+u//hf0aj1p3ho99MP/w7f+/D986//+HVb3z4/mYXLp+8J7BCRxEzlLFMpRY3J5aAzozFYye9shBXc8taAJAznFk0kDMTnJ1AQQICSaNZeGASikwJbO5QIph1SYYk8zx/8J13AoUUPde7iEAyCVTEHE7ihAAK7tToV2ZuMCYIMYM1m7MFkqxTsVm91mqFm6iJzy/O4ShSOMZidqzl7vCgNl1dXDrTq5dvxnkazrfbYTOVOXLY9QMFDszz8VjzXGvt+nRxsdnt+Ob2LudgkDdvXh7G6bc/+v4PPvr1u+v7r765vrvJDpxvO7P58DBNWZ/tLy+3V9u4vX99lw95kLjvtq5+PBxbMVQNjEAcsMjPWouMmLl4Pk73Q8/P33u2veB33ztzqu5cKx7uj3CkkPJcqdA2DWHX+3We7m5AQAJ3aNHcq8+uEVjYa1nMSQXcsqmIiCjaEhBGiLDs2CBspNv2Zxfn6X4goaHrwiY93D9goN12f6xjtiMRhxBQvNaKAgpeq4oTqT2yUZrhmalbixlsxZW5ORFxM5IGEdPCFFpM3n2FTd5iPC1wDj1Opg3z4MVK6lThYCmZWu71wgDC4rnecl5bQcor+PVXjMb98VOJ4r9ambT2JR5hJvqVP7dm7dVIVczNxZXc1AzVuDHhsbZSF9JVQ7to7TG62VI7Mi1wGAjCYuamLcKnyT9XATdTDCJBWkyi01qXNlITt1dE82tvBCJbrvNKVFtp8UTk4iAj0AKC/Os7i0sLFY+n4mstSq0XvZzf4hG+ShyWH3BbMHyBWuGL3JFane7MjzivLw7lDKZIrbdNprVt3hsU5S29L6zFcPvbpkpQW3xpbY0gBC0Pi62e+MTV9W3OXatcH1GttoMwW+8lM8fi80sUcMJciUhoxWOW33W3WhvUY1q1HYO7NyGiiCyEMAcziwgTlAytyXvyVVk66Ax2IgY7sxhVU7Pi6kaw0NZzglU1VQeaw7Cb0gmaBQJzl5Jmaxy3RcniTkQi0cxgUBjXNQ6i7W+aItSBQF5P0t22u2EzVlV2gRu1S7turgym3viGj1uu5XMnpgXTb3bVlEs2iEMcVq20WRKBKLKkiACdUaqSTjq3c3QChS5Wq0p1nMbqSlEgviDd3B5LDUmub6+1TBLL7jyN05RflX5bQwh9P1QUSpp2PFxxTlZZy6jL46RA3xZXLD43rCCgogLVCO4WyzK3XGD3bLcZuoun5/0wbPe7mxf39zcPh7sxIYWU5ocpT9k3zVDFhAjezBnMKpwBbk8gFhatqauZactWUxhk3V82yzyGzgaGhNB1XfWOtDB4k+Acs5qptvgsJ3UlFJt45oCSSx4LCBSRYowxhsAt91dNiVkCVFFKRXYo2EUkMpibDClXrxVFmdCl2EUm81Lzdj+EWExUW39NJ7IgoX2gzewKi5ezo1ZNLiwMhrrFFPJU5jkHFSIOKzuzS5ECprkwkCQRiImGfi9CRKKqJdVSi4iE0No1pqa1KhzCgTkyea2FQFrqNAdhS1QAACAASURBVI5dl6w6gYmafyQqrFarpbkLSinz6CUKEzEU0zwH6rMasW/ihtidtE56l+9BDnb1qgZmdwacAqk2y7g2gzS7IXI4zzUXru16q6rBOFDqkWmdjlk5StdHq+NxmvMDpEO3RWQESQTSWk19HB/6rh86xNiZsVaYAc61LnW8qZt5KQVwCSnGHmRNlZynXNRzyWSOEKSXEIIBfZdhCJFDpChBhBiUgqSYtNacZyKapjHGSMxRorvP01SVxjHPeR66bp4nAc3joZS56/qu60KIKYWuj/0gL7/5+vr1l59//fKrN99YKdtyNtpMSRJHh375ze3F5QWn0KVunuv9w92Yx1IqtKmtY6Dwi08/+8N//n8cpkmBEjNIHPCqbjAhGFzVYS3zpXGiIO4URIRJUKGqVc1UyV2A5ozo3orMBRZhkIOYWFhcVwSI1p4IgLbqYJm9F3HtqTCgBpq5ii1BsutsB2CZimnt/rR21roX9IYIuVWtvAJROOE0a4GzoF3WhNordrV0q36lOlnN3rEu1aeyavVaJyzlWOOgN4NUUIsLdBIJgZ0aWuUkTEFEYarGi06cA9bS4/TijxXcukKfyq9fIXc/Hlgrs06Y13rhTid+AuVOeB+BrHWW3JsVGGJM3qibBQ8PIxNKMQ/cdV0f483h4XB/s+veEY7koc707OmTwzW9+vobJoHE+jAzxb+OWrV+Gv7YAft2fDv+LR3r5LOoG2idkNrD7SssDXhKaQz4gz/8gw9+/cl/9Y//86FP+27j9ZZQHF7rVGgym9TH43jfDUMTn9fqwv2b6xtgt9kMMcbjOM7zbIt9soEQYogpSYggYua+l1m4HisaiYpAre9rcNNSjAlLUY2V0LluZ9oTu5iOsjfFwCKvYAJRaOnYriBX9eM03d0ddiPFnrfdFjGlaOT6+tU3L1++eufdq2fP39vuxq++fn08HLbDxW9+99nr15+ph49/dOj3MMsb3gPBNUYwhwEhAS7h1rSqohqFrt+cd6EDOc7PN31ikqqeGQwWD8YdJQqgwoDWygK34rWGgbhLZRjGctAybwU6Hm9ur29vswT8zm99+Dsf/eD7v/2hdICosBPyz/5f9t6s17IkOw/71loRezjn3HNv5s2syqqeqgeOJmWLJgmKlkFYgiBPMmTBD37yP7IBvxsw4EfDerJhy9aDJIKQzKZJiRJ7qq7umqec7nSGvSNireWHiH1uVrMp89VSbVRlVd57hj1GrPjWN7zzNpv2vazHrpfLfv0IiJ2sV8Pl7TH/2b/8Fz/6wZ99+JO7eQqGMh0xJGgBOyRQSUxmUUiYQQgCFwrOMPA9E2RZr5CwcAhMxAywsCsXaFW4u3sNSaLmGQImgFmpBc6L1N4ulzwLwboWivX+B+nzz/75uvdf/ZVHf/U3fvHXfv2Xf/fRdwyT4JD1qJSG+HAVkDTPKZWpZLeOOHYrpzyXaUq77EqBJcYQI4Eck5bDmjcDR+kkxDEymCKoY2V3bytvcidixmbsjlPY37y8vHi960Yojx2Cp1zuNK6ZvNg8T3q2ClVQBQDMy1pR4Opq7OwuXpdFJM5c3MyNQwhdlD6UXDirA6lkh97t9sfpZr3ZcJTdfp+0jNN+PFs5g8wjB8DLcd4d92frjfmOhQTEMaz6XggchpR1t0+fffz++eXDr33jwefPzt979+blNY7HFDQTrGeMXbcZV5h9f3WY93klq0CDkpU8MQXhOGliFsuuJYOsipuaijBO19PnEWdvvPb4/LUxl91+v9ueXWjG7c0eMzxqzgWllNAF7mRgmICsi9WxpeosYO7mxHXMKV4xa0FwLV6MRVrrz5yICQrxy8crj3Z7e0OCi/OzY5m7ru/7cX97mA5zGNkVphopSB8VVlBMi5J4NqWmUuIqQFEuqJYir+BErUJaKDzEzFRq4HpDH1q6HoAlDw1LqiX+fDFmbrzYqC+jki+gutCCl9Ey3rY3NjJIQ1xOTb9liF4QMzRm3LLGvq+eaFF9YRESNjV4Re/ap9SGJpyJHMXdtcCIQvN6INyfChCxNdzDCWTVG6iNs77w84NINc/4YrmkbgZIkBAiAW6mRN6MplFFZqea9zT13MMseLXjezrOU8L4iQ72F2yNWkWvlKJ1yU3k5A1nbKgRCKQw1DKeQNVkG+7kXmM4UStfJbC5EphBVWxgLfK2fVML3ANqp7t+Xd1hV3Co3BS6L+krbmInheCpyAe5twXFckpOtw2ABjku59xbjnm1iazzdjtRZhZyzst33X9UfYO7l6I1kjNNGZwlsIRAgKqWonXJHWM87YrBiUS12Fz29UqTK7lzzX1wZkgQF+6Hdcm5UIHWW6QmBmbkaokPBHJyz+YFJJWEBzWzWEaKWh+X6rVvZuyaySt1GQC3JHkQwQjFm+di8alM98sIRs1ut2IgAjmstNtCAINnKw6QhsASA7Ewk7MRE3MIMVh0iEcJgLVccncIBYRixQkUGF2gIH2Imr0UTZqT5wrilEnDECDUj13kTthW55uMcjjeGJwoUwiyGvb729V2E4bhuNfr67R9gKErxXi2SUV/8NPvD2EYHnVPzi4tYxW2fRhKst3toUzl6bvPYZhTmlI2WBiYJRisH3tiin332uuvkUgq85M3nszHabe/Gzervu+vrm++990fQJrLUyD3BCtl2pV67oRrMhq0VK1bbXjV59gCc9ECBYqTQZjJ4UUBVEPS+nhV8zBVLblwIOZg6qYUOIyRmWzOWsU/TqXmhggL9wR3TQrznLOZuUbEGGP45KPncYxd15ekeS5w7UMnIXh2JidHmo+7uyPmhjvzpuvXIzFY8fTZp4KQ58IZZGZOZsXd6wANZkdp5nwEMyQtlJOTzyl5KiUXkHnfcWw+sX2MbmZJkWEFN/P+/AEPQxe7rrIus2cSmo8Tk7hRzhXYZKFgxZggkRjic1bXw/FwnA95mro+RA5vPHpttTnb5wJSJjOdNdNhl+7u8irm7VkXQgcDDiiUUBxw2lAXgxNlK+ZKgSkgF3cFAhBACpO6pracFQvvhhkiamZEGMdRCFmJmDfbzTCOaZ5VDWqHaUrPp4uLYbUK42b040xsgUNWKbuSU5qmKSVjR5A0jnm9GruuU2J1zimVnFVtmnAcMjMzS5QQwyhCKU1zyupOCEwe4cWLOwvzEGMch6Hv0nx8eH4RO4khBiKdE43j2HUlzdNhOt7tA0tJKYXQ98NU8ssXL3Y3u74bt+vtxcV2t7+NLKmOD7CUjnOa4tCNq/7Bo7O//7/9T1rK3fXueHfsJK7nXbyLZ8fzs/Uq53lXjpuwmTBNuzzdzoe878Z+vd2OvImP1/v5GPrz58/u/viHH27PZNXHoo5SiAgtPcHcnEESgnFLmiJyFsmuNaiu1Fs9FTJnFnERUO0raMkgVLd1oGFStdSufG5u/GqyZnlpBpRSQDA18+ZyKSxVBcjM1bWCXwFlXp1wm/6Ol4H/VH8Aqo68TOFcV1zkC//LzKOQEwrglfpHTTP46rxdTQGWb4cIs1SvAzEuQPVbXwznYQCZK9cQrDoDM1rGIpPCFa6mbW5msmo61rIniABdjuWe5wyYakOvKiu6FWD/+gLjVFScMl8ba712ehqIRA6QwTkSKSAUInKHyN0hKRmth81nL64264tnz6/689U3vv34bHP+/jxb1kBxiCvx8PrDbwxy8d0/+d7/8D/+H/NH6Nab1APT/zc49SV+9eX2b8m2NKobVn5apNQ+bP1dmhMK/uhf/um3f+Erf++/+jsh9NkKU1fy7DIfjreFD8bz0PtnT69YpgcPzwJbnmm9vvzo4w/i+PrhcAAQYhDhpNmgplYcEOYQap3cdd3FxSW4nya9uZvM5PN8PXZDDJFUc0o5Heu4HUIIwa0jU3OFFjVrShnnZRnQDk4XH3IUVSsKofnOEADCT3/y7rD56np84B7GIV5s+y6q++HtH793dX37rW9/4/LR5WuPY9ffmsEv8Hu/9auhX998/gelUFx1GRZXcfvoMqzjoRyv9lf7w+3mbD3JlHIJEcMq9H3v2LiWQE4oUSgqCyisqN+E7YP1EC8862G3293clkmsKMpOHMwBltfSn28vg/Bq1f/Ob//GV776xgr9zfzyZrpx++z65e3Hn314ffN5F9e/8tavl1lX4+by4jWRYXebnz/d/YN/8s//8R/86NlHwBFwQEBA5BisKymVVJgDum6eD5WcwWJGZgmupp7dW2A6Fg6tkbVJNed6VjsmAqKERiHOms1KyaizTrsi4iwAwG4O8cDcsaAuCwxK5EVxdZiudvjon378f/3jj7H7R3iE73wT/81//V/+h3/9N1fjRsIgImOgVaC4ojPL6XB3e3t1yHeJZoouA7PQbbrNk1KIHDtGKMnVuqHjLkQCubOwRI6mVIq6GxECd0PUx8DqAYmW9dAJI+V5f/Ps+e6zYJ+++ehbjy7eDDQW91y2gMOtKbOEiYVgKeVi1nWDkeZjLmYeycynNCdWhbLIx598XHIpc1l3YykaSfb7W7V0tbvdrNebs81hmnZ3u7vd7bhZrVerse+KqxaNIZbIED4e0+Gwi/360ePLonR9fUPw7ab78MMfvLw+e/zaG7/7u7/+C7+4+7N/+YOPPpmD+INNX2bvmA43t3fPDs8/eaF3OErO+1snMuPz7QNAjoeXecos7IGZwWzN8Rt+dhle/+bDr771Rhj9bnd9u7+KsYsPzkqhdCw44EB7TDx021yO8/Wt9PLa648hPh0O0+5gZqqm2U3NSrWdgReHk3BgiDjREqLjVNOkYcXP3ui/+cvf3DwYn96+9J4BpJLWYRMknK3P9nd3L55fBQ/kwsJjHJ3U9vmIUtkYLSgOUHc2My1mXrUuWNyyawUCL25uFa5wVlNfKhypzmQLj+aEHAEgFqAaKJu7FVXAiZqfZtU9mRu7EFcPW9cChxqs1l3Q6tNU3AGr5Jj7ykmW8QuL+4XbSUgILCWKL6LB5YcLkwRVkOmtI1F5TUsIdQWhqi1ujSVDbXnyqWgkAqMdCshIKiHA2c2qv64bpIcb+ckRG3DS2iXm4CzuUHMzL4CyVCTOBRACxVhbn1WGVAEWEalnfmnlstmCkLVX84KD/fwS7XQqiMmpigIbikgAAjk3V/f6czMnZiL2RrxDLa6B5k/WQPk6UVohksrFghkaHMlVX6pFzdV0qdNrNmXzIkZjqdUzy3Ta29Y30gXq+nnHVU9LQ/rqFW90EZwwFa842RfPAzMFLSd3LgeBpcKYbQmk1m74xlqyijtQVUYXVYlOgagSNtyIWWLjw4mLVUoAuHWWGGiZUOzuYCYR8vuCmomNDAQJIhKIUIq7QILAvWh1s0PVBwJkzkTWEriU1OFqDhATGxPXlktQUkUhsDBL4MoKMjWvKV8EAknVI8IAqq4Eza5fQe2uI2+USDCTMAcRMJyVzcxNwICbmksdO0BMEIYwCZNDnNnZVLFcCHJyRQyyWW2MzNg8AvCRVqWkUopahmVCUM1wc9LAKIbjjORW/AYuz69vz9faRwUhad6lXeBoCoNx5O/8e9+whON0vN3dTvPsgn7sV2drYt4fdlOeyzAdj/NqvcbKXl69APnsXTrkF89eAmAXGPtsWTUixiDFZsCdzBq/gwVCFLzpLwkOZyqTwtvA3e4CokYwYddijegvAGGe5lRmrNyJS8k3t74Os3hnClIPMTLDIiVPwgyHEA/94NHa5XYQ2AylGAcZ4hgkTDoVU1fPqnMpMO84dtxRcSrkM1AAdiVXGHcSOaYSOYTAUihVMNm82ocRuJpEL6MvgwOBKWs2t2LG5CxCLBKkix0JuWuxlEqRGFarUBfDeU4wz8HgVkpRU1QBLGkumRLHGCRIjN3u5pB0HkdnFg5SJyxLtt/tcoldF/puFUPMu1ktq05W5in50AEGCWIG5ogVZBadFQoY0t1UAoXYDauhG7vn1y/CEJHrqQAyPHnhAmF4DXCs8cpw9WKG6tOvWooeDoWJQ+xCCHW8ZAIxFZ0owMm6IW4ics6AzJOWMuc5lQJ3pAymYnaoiW81einGjllU7XCcUkYIHoBi1QWKpsl2+8mdDR1LiF0nKgS4WilFmGKUEIa+D1UITiAr6mp919toln2X84MHD4i467txHJlonubd3ZWN9vD84ny7+fTDz3jog0hByWV293G9Gdd90fThJx8+ffmpo8upQBidJNhtOr64fSk9z9OhPxu5j7OmeZ9L0tjJdr2OoRMNgeK639xO++fXV3BkdXbKc47ETM7Vmm8Z1ohYApuquxkJE8Gp9go1a6mQoi9zl1cLrSpQJ0Ebv0ytZvpS7XuhAsVNWFMx/hrCyMxgcGMvwbzKut3c6uB2T0+mynXyZh55mqGY8Upd0n61kKrqfFYnVyd4bemc4LA2ny0dqkZLaN2U5dPo9Fn3b6zoElQWWR9gxKJmXKsXImIDkzPZkiKoANy11SNAbXAwUesBtpqifhw1ESTaXL4wyX4ueOWtsDrZoreJf8G8lgkfcLcFv19+WLX9QhIDQnGQKfpuHPq176+DdJrQd+vVag2y/WEf4ASygo5iJ5uAtfiKMrqxS/tE1p16aj93P9ve/qUguC+3L7f/f2/u9/SrBcHCwoPEiTmqqt3YJU5p1h/98O2/+dd+7256ugqdQxwwy4Yji0YpUTQG7vuhj3FX6PaY1/25S2BmYeZQGfxmbiTUBQ+xc+IpJTMHc+v7BZjbPGciU1PKMLPFMw9FC1M1l2lMZBCIQc6N8VoLZmZA6wGZAuJQI4IEyUlFKATeH8r1i/3j186CRJjmpCBj4eNtlnB4dDs/etxfbDbZ7O76xSDT9slKwvr3/tq3n1/Nt3t7cb1noR41GyQMHuci41mAzyRgthBy13UgciVYdishUN+xMPpeJBKxERmLBfEIf/O18epqd9jjNu/WKzx88OhiffbNb3z1zTceh4DHjy6m47NPDzeK9OLl06urlyZQzQ/OHzx+9OR89RBD33Wr6cDvv/vxH//R2x9/cP3+ey+ffYaLzRpjt98pLHbo85QPuwNLF/sVzOfdTBKlestURU3NYKoRIwtNuM5xzFwXYksUB2kpVM2VmcmsGlsLsy9Z8uRUM7WcRbjGlRgRx9gLA5R90bmLgNlDZ0zWv0lDH2/v0v/6v//T7/4/P3jz9Ue/85u/9Su/9IuPzy8FgZCvrj4KTN2wDauhYEp0sKDZ883t9YvbawiP2+16OLN5KmW42K6CrBxwdeIqI/LA4tXOh6g4J+g6jl959HpKc9Gi8/Hmxd3udg7YrLpxPQ6b8SL0fQ1Jq1hB9WtyuFXDFzAzyNnMU8lZLJnujscZpbAddf7s82em6uq61qEbutAXc3Pb73Yi0nU9CU/z8ebulpjGfmCm6NR33TgON57HnOcpHw/7edbpqOq0u7s9HAoJckr73bw96197vB2Gi93dpeGTnCCwY8nBy93L3fXzvasPQ9fxSCSFNM3l6vaGCgw6nA8AVJOrZp1biWL41i8/kjVCnyUQie/3dyGsbm/20225vT7AQe59N643Qz6m/W4/yEg8EnkpCpCaW3Et1aKprpGdiNnFm6U4BEFNVQsFCiIgZE3obcpHzuGYjk50mPZayjzNBi+zekY6ZDDDUDRnnUqynDMKMmWcOFINpDAyMmgpreVMTlQ7eafEmgZaVHaoNyLM/T9Uw20cJ877q+06qm93wKuX8ZIT2KATZpg71BdpNr2SoEGLt8Kru01LBloFgE+VyT2+caoh/VUA6x79aeCNAP5qmdXqVPJG7DKtRlxkMDZqRqBowPViP2LsvDQHIAR1d/KcSzsXiy7P4AiQQCGwwVwracO44jzNPZ6IeaHet0EH3jQDP4eB1Uafdq594cnTX4hiNWpde6Mv2YdENUOpfrhjcacnIiYYNxlaY++AaoJSVW5UH0UIrLQi3YzdQeyEpsBzOEjVa/IeNwipWeu204rlP1+4Hsu0VaHGRSG4MNSsXln/8+9eJBmnm+30k7qZeZDATd9QT5w1S0iqEI42BDSEUMfwhpapK4yJhIScTL26pDtZo0U5RJgMRlZB2C4KCbedV6Q8G1AFSo0nBTA3AKt6DntxqHNFlwAyM4MVBbsRiBBqXCaTVQlpoWwZ5lXe527GCCG4khkFkUidu7ZjtaWQOT1SC0GRa2uegEgIJMwsQtSEo5WAQI1esKR4ujJg3nzvrDmweevwi8yHlFOxbChoKx0md9KkbqqpGCxZNnMe+Wy7geucpjQXLTR5ySUz+7gZ1mex66HIqeTjpC98//DRpRW93U1pUiIfx9CNveayu93lpFHXwmyivKLQMyKFXmRdiy3n4r4q2aaX827/2fWzF89/4a1fEpannzx/9tFzBKbEKCSIAJG6u5E0M7nFD45rJIVrle9UniJXxKT5zKFSLOAtXtP0tBQFvCBNU+5yHAMRl2RIKOrquWRXs0gxDlGGUL1Np90EBRFiFyuD181LUddiDgGXSdW1zNnV2bmjrusjzLVombJmraOzK1C8mB4s9UMIQULoRIJaISkk3HEw91JqB0ObzllAQhIodNWv3+EQZlOv96ypq2qU2NB9B4MDh5qtW+aSkwpnMwWh7/txvdpPxwA2taKFgnR9jBJpxt3dIc1FIkhBTBSI3AOHKIEJpupmt7udqeZ851YzM0gkBJFpyuTYrAf0cXezg4HUPaM90SaB+k6GTvqCnClLF9w9axEXJgFZoQzywIHro+QGuHAFYf04H83RdzmEYObdEFiEgr3++PWvfu3xnPYVEM4plaLH/TRNKWXAIYLcRh81FJA6zNkI1MXezPxmmpOroQQ1lH5QUdof027vBN0fj9uzuD5b9bFzV8BLKTFwHyVw1/WxlAQzIvdSLJVu7Iehz6mUUoZhzYFj13UxqqoIx9j3XVyN/Xa7+Yy17wJHnuaUcwbT2Xaz3qw+//zT7/7Jv7raI3QpBu66XmKXUOy4e3HTr85Wh8Nu+/BMepnmeXc4UHKnTkvuuOtj3I7nk5YfvPPeO++/C8Y029Arg2AO4hrQQm0Oohqv6018C6kG+GDLsOQoVgNNaxymO8GUYEKIobpsopg1tastNEeqRZV77bqAiLn6/wFeQy3c3UgrDbY1NFhIAKqsd68MrqquNtI61zgtBKZXKT3e+mt1PjZzIiPmOk22cRF0H/sCX4bf9qehKhvlNLW7W9UIutVukRsKEK32Zrj1eprvJbwSw+tMrn7ft9OWTl9DHRvIVAf1WmbhPqC3MaiqJWajef9FwM+pcQmv8BARM/MJCbOlYmtA2KmNRq5enIyESGpT0EXCalyHw9VmtdWiq1W/3Y5915npPB+H1RhEiDiGldj4ztsfvffOM5sxjH16eehGKSg/fyexlAJ/YV305fbl9m/c9iqGtdAW6uLgHkVmGrfn6frZT95597/7b//7v/W//I2xO4PNIh2HPnYCc5KSyrxdD9vtWUCMWOl8+OG77z7YPpwp7PZzNdkl9hCInCL3MdjmbCPCxym/ePHy00+evry6W51tJQzD0IeAq9u7pHNSQE1Yxq4n5nlO7q6qVhZohYhr6MN9h8CXIvKeN1HXae4EAQm7cRC6ur7Kx9dWD1aOaX/Yhez9QNKtp0SffHot/eePLy+62G3PRhpV1afp7q//zr/77Pnhxz/5/O7u+7c382ef3fEg40XfreLlZrtaZYbAcy45Te6aQQiMKBAonASlD2G96tZjgKXDbu9JRf1sHF4+fX4xrr/++uNHjy7Pz88uHpxt+nBx0XcdH6ddOT5/+tkHqRziEC3dWjkyD08u3zg7v+y69SDnt1f50/euPnr/9vv/6oM//bMfptSzjVxov4s5kdAQlGEkiGEYyUHq7qWnULzUsRVaY2wdfgoIawvFVquBRNjdndsYrqURGmqjvXnUGFe3oaaEYlR34dhHElJUl1xWVRIWiYUc5CRiYpNbkJhzmbUMXf/Ddz//yfufv3ZxdvMZv/vDm69/7cnXv/aVrzy5XK8uhLOIg+dsey/unAgWwBHkDs7JcJimLMU2qwEkFTVgClM+iPQiENQw2tp1cmbaxs1dts2wGmkQi2dDDrQ523SO41y44zWHrWs9VlMvhmKezbMEEoh5VeRAnQwo7innSWcVnzUdDntVZ5I8WHGPIAoSuHPhUt2GQX3X9f3ARGmezRTkMUSPkvRobiwUghDRPB+yGrN1PVarPnYY1+N2E7Rc52RfefP88aOLu5v55moqE988m67K8Tg5GbmiJCVRDRZX7KrTYa4uccWz+oyA9TY8eHD2+PGD8aKLjw4Hv5vylSnlkiR2Z+tt3w37cgdDt4qUqfMQhFQchHk67u5IQijZiUJd2lduVa0hAoNIQGTFXB2OLnQK05JCiBwYZDjia9/6+tXhxSRz0vmwm3c3+3jWwb2kcjwc+zD024GNMiafS0m5TMXVmHkI3YEmLJyS1mNrJJnFzoiXeqNCE+T1bkfbyzqM+MmaHK03aScIiV7ZKqUDFadYOBwVklmIRAxYI8tQdZKuA+tiKdVSX4GlpYoGjFFFrxaCOi0j2mn0rsVia2e+Uml6E1XRveVRW4lT8xWsb/eEWjGC3JmJ67lavoMXnk5xMmHh5uHMLo58LAhAWKrX2lllSCSJUC9WjNqyFizs1oKxmVtK4GkE5xMZfzmWdhKqD1FV1VVxHMG0oMb+nDrFr2wLiQxN2WDNXavWrFwJSI0VRARuXn312lSb6oYjFWBJ0G4qDXMzaINHuJoP3QceVW9ruBnMTqyvevIDs59mI28wlQPORgsKKTVVoCaUtIm4IbBo8/ErCOYCreIedWs39gkGdPdwAvzan6d/fWnVUntImNGc3VXhYKEqHrRlq19rpaWhW1aDu6ovjG1ydzdVVTPjBrjWO7B5lxEHieZa5mL1SqhXiZ95TdJDnvIwjgw1dbU6X8OZjcCQUNEVVdPqzwSrImGDqRcrHtsl4nuxbwXOQQSp9t8aYwAAIABJREFUkeuVc+iojy5zCBI40CEdIZWryFzpwsWqj3Jddjq5K4zdyV3AQgCZeVE1c3YWBLUMQ8v9Km4oJNHUDH48TCwyrLpxHGLk4yR3vgOhs1hvQQkSYxjGUDwc7/Q4aSpzkDGXYqCDF/fCYPaibNpBs/7o6fubDn0XOAhFIpGDT3e3z1ebDa1wvNmfdQP32O12N0/vzs+324vN8Tq9fH417SYkaKFggT0wGGygYhA1paoVtIps1MZPRUKpjVzqLbF+uRWx3N9YwG8SOLuzH4+zBAoSAOT5rgsgJ89kyTxDOXsQ7njsxsPhOM+por85FWk+qC0zzd2dKc97KKBtfBBiEdFckB0KUrdsUAKqibXpNCfNLNhcnGV3JSAGYgpdZKeUaJ7mhg7T8iAH4iAcWYjM1QzHPEEdqLekL7UNBUQyKnNRLbnUIBIyc2cPQdyhRQMFc4WRpWzmXdis16ugMk2TmllxNY0iblB1GrBaDbETZqjmnIuVYgYREvKSbRjWOdt0nIV0s95oxrxLOc+em22DF52PMxGtxk2IMmXKbkQhBIElL84spkbMIiRcQx5AIBEWFnfkKRsZsZha9uTuts8zCKz9Kg6rYdjEeT6UnIKJu5E4C5HAFMUQI0LAMHb9IBJcNZVcTJUg86wlA/BS3MyGbmTuSslptlLAhGkCU3GbVmPoe+liF0RiCF2ovE4TJgLMrHiZ0xxiCCxRBDVj1NyKJp3nlLoQz8625+vt48uHrhqYKy4rQma8OT978PBinucPPvzwnfc+CJcIhn7oh2EdiYuilDxr2U372IdxNVKgw83xdncjKiDLUxpl7Id+szlLan/2gx+9/d470qEafo1dLLO1XAJpvRb31m83wLnGaDE5uZrn6gfnrUZxMjVyEoBZ3F2YWdjMmrm5OwwkCNymcmvQTGVK45SMDKD6GjQzeSYhUdIKpVkdCLm2mIGTG1RY5pVlTq2PdrWJq0aSfJpu63NTU2RaqXWyUK5D/0lh6K19tvSIqC0czMy8aWXQxeiK2mTTkqEKkhqrwu1gjdwF7sxO3sjNzHg1AKWtRWjp7LQK4NXyoh4S2nuXTtDyf7XJWV/3CibVPqOm51DDsKxNEV+sRxyYdS4oXjTI0D/COz965+tPLiUaEx92hxBCv91uz9fD0KslERIhCdz34yCbLpy/86Pv/dE/+9P0Ahjm2Hem6oskxpcBFz+z/QUo3Jfbl9u/eZsvkLS1ZiLaog4AFi00XHOB4qOPP/rTP3g7YFDOIFcEB8a+Yw0J+77jGLAaenAQdGnyjz/4fBxWec5k3sTskTVzSd733ZPXHx/2O1w+BLA77F++fPHsCk/6eRX7GMOwingfzi1iSAj9MIQYnTlNM7tBWIu2zBu6H0VOR0Gtq306FlJ1QwFDS83EojLTj3744d/5u7/38uqTu8NtNqXQH4+TWr663r+8uXnjK5ffeuvJg+24Etnf7YWcfLrYxLe+einyaz/94On33vnw9gX2e2zON6uzMJx3FpwH0qrb9tndmMDOUXw7rktwITvru3UXxSylmbP1HAPzr/3CL51tN5ePHj68vNxuL4Qj4XA8Pr96+Wya7xi6P1yFGErO4jjbXJxtX794+ERd7m7m7//w+5988OKHP377vffx4iV6w9iJUdysRtPgmkwtu87zQbR2QYwAZnDPNikRQetqWdjZSetZraMjsYOoee9iaTxUL+NlTquDPYPMHFptZRoNwgEiA9W0dK1hhll9XK8MDqrmogSGi0AEMCUi7rKDpAfs8+d3f//D3x/+ye9/642L3/yrv/3r/84v/+I3X3v99fPLBxsmFE+mIh5WcX0R1/0GU5576aN0FIK4lKIp6Rg7kRARJpoNs3sBVSWQgSmgKymR0Ha4CByGUMZ+nZNrkRiG2HEIRq5mCSYgZVaQFzd3Fa7qSINbtqJwiUEDkYpIcJ0cPgwjkYRAUWLXdyxCUQYeSELsIgU53h5iF0IMq3GUIG6uNebNvGTsdX97nNKs/Ti4yXqzSkm7vhPhrg/nF5uuC/3Qi8RuoO1ZlzNvhvhwu14Nl5+8d2UHu3364rh3R5otwTCsifqoM7oLzMeiyDJg7GXcDOtNONt25w9k9YBf2I1JqrlTTnkYutefvLbpL+6ezTYD6jH0pOTF4HX9jTxnGAJJKql2dascGU3NSzC3mp7uRC5ZS9EybtZzOZSC0BHWOH/tPO/mKaVd2u93MwcQqJQycHj98vXpMFMgS1pAQjVBh4TZ2EyNT2jBUkh5TbVDYz3Ve9UbcOHVVKgOFCEEd6/Kr1b0EUytIUg4AU1LwfjK5pWkssATbQ+8jVEk7O7Q+yUfGouxdQ7qINWeONTRzKlxWFB5Tgvi88oA/oXh/BVW0jKUL5UVfXH/T4/norhEFVVphZMacF3BXWtksQryOkGqk1QEpNIvCexk7GIkCEEkcNHZF/UaFvCFQTXo0YragrVQ829qp/WeLVTd4Bd6Fy3Qoen9YZ4gsFO7op1dIl8QdFrKbXMXDjXyY0ElGkRYT0nz13JU2KXess02FijF2L0qEyqU0Zz/UM2vcNqBV9jMFZ5jNaMvXKx2RuuKuWVxNqDKf+bwfGlm15Red1+w1Wat7uY55wqrUSWZ1SxB92D2xTvkhISdbhgA7qUUwOtlUFVzq1Bs/ZSG3bZbdLl9zYlQlcZkXqW4zRvMrWLCLRvKAa5rZJLAcJSSFc7CJBzA5CBXYki16ga5iWsppag5E5iZQnA2qhGTiwk6nGrHwA1Vf+jkNTD+VSiv5SYsh09mXAOKXwWASbS+tT1+5gVe8UNvli0OswpsCwA4w0uNDivCTMIeYWruCnMncwBSvVooMMcuaJty6smoUkouJaO4ueVcDgfNmZR8mi1nEHh3zMwsQS4uH+SS73bX17tjjDyO67P1OaVnNcYtdpEDpZKzJSXLSH0MHrTQzL2XW58Nj994KML7m91+v4cwnAIFocjOTGDiuq7lNjABQI29EOfTs1DP4bLibc9I/cUJ+qYTeEgOQinKHggEo5LcDZZhxT0DGZaKRZXYj32kTNfH23pfqZnCAgKzBGJa1L9qZq7uCoebpZJ1Vk9G7sIR4qWCzGQQBpOTFzMoKIiqKrGzOIH6EIjBMJjBiVCgIGdhCnCux2fqru5d12sxdUKlsai2jgcTEwK33G4zs1LPmeXiWux4PDJzkOhuJZVcymo1MstqNa7X6/00qSqqjKw9XlaFVrlkP3jKM4qxUL2/AI4hlrlZd8UocBemTCABMUlkEOVUDIeVrJVg2TRpkMgCYVFSAtRgqkzByLWoulbLs4opF82vPXn9OE/zNKU5GUDsNUX4+ua263kY4zQdUjpqKexGJP3QM0tOcy4+djEEGsbY9yJipeSiSbMBNM0GQAQhEEGY2NTyXEydCSI8rozIS5lzzl0cmTkEBuw4ZWGMwxBDDcEzU5RSSikhBCYKxCXNZqYiBMop9yF2m3B+thnHgQlDP7h7KrNQWK3HzXo9pen5i6vbw+7isvOtQygOQ+w7KrAahMsSYjw/P+u6HlSKlqRTsKAlwIu4Rwl9PyTTTz///KNnnxgBHby5qtWmS3MzaISqeoGZGsubXIigKMW8Gvm5uRFVx8nKUK96OndXbd3A2gYjBGnOmdVMapkw7n0/qgNCHdUrUkNEFackVHJY2+oyqk3AWNApby2RNmfUgqgWPjiF8p2aBEtfZCEPnyZmat2LqnyvgVtLGsxprytft0HIRJX/1UoBBxlaeYmlneBO9upXY2k9NS5VW/2d2mJ/vnS6r9QW0MfvSyhv1I77AyScTLvQ5ml/pUdyX3i14wUApJLQEdgN1jF+8uOfPDlfdyvOab69uw4inXCIlHU+HneuqWhw00gxyLi7zZ9/dPPhB5/BYNkJnktiiq9O3V9uX27/Nm9eWd9EbsbOfh+iiuURNCdLWjiCWQDscRBwTUgxUmYSomDUSRz7vgtRDQbNWY+7ifuBPQeiQYL36LreSrHMXQhD399c30yXBy06DGM3juXFMc2Z+KBG6xgQQGhuLiCyZVFnZgDVhkSro06VONwBWVY7aG+lextkq941LUsnJ3zw2e04nm30vOC4O1xd3e2vXt4ep0xEL29up3IcVkK+6h92w3rMenzx/PPYnb/55OHXvva1N7/y1H36F28/++gzPH22e7jFm0+2Pc8hVPdSIhdVqqburIg2D8HW43rFJvOEnH1/4wnJcbfH3/uP/3YQCTEowSgf57vj9GK//+zm9sUw9FryOPYgXq3OL85X4+ZJ7M6vb/P7H3zy7NOb3/+HfzId5fYGZY8VIXYrYEiJACqazbO5EoN4ds2teUgMIjMCCkhQKfR1gebkyH4anqkVou5oniRtVCdz4za7eLsUhpoIUm8sBwAjqgVhcZAzVexAbVYy8yZXV1RfIc+uHIMLHXISM4QQQrcdC4p99uz29//v7/7g7R9/7euP/5P/9D/6Dx79+1tsEdFHQd5f3X6yofHyYjunI7OPwzp3nBMRQk4lUieBEqXZDjVe0Rs3IjIxWUC1de/I3AgYwhAJuZ4oM9Vsdlz35g6iAlalomUqfqyJhHWKNjYEDzFq5KAxdr1ocirC8ujhIxB1MW7XZ+v1OkgEsmnJWkSD1cqZGQQ1m/OcchKhGKIGurm9vZsmdx7HDXO/pb64931P5MR2ebllqXKGsEIQ7lV5v0llpnF4MO/n7SUfeyDDGDgDgIkcnABgBhxlg2+99fjsYtWP4p6yTTf56dXL+fF3zg6a1GcOcTuuWEoQBnmMQow0F6LiRmScc61CmV3ImAFVInVUlyWzJs1fUM/qI+PwZJmjy5pt8sR5dTaePz5HsOFs1IPbrCkZrUDkOaU+9MPQp2NKc0rHUo6zGFCoJgyqWskpcoADZqfmIBqKulQZ7gvigIZGNHqmM7OZth4nGk9mcfNenoUlmRNLGfOqU0R74wmHItQ6jCuHoTX8KkiC5iix1IT3pdOCGPgpk/kkOSS6H+/uv/EEnpz28lUY5ERCOr3ni59xoqoBtbiuL2kLVbt/ZQtxrL1bAcSdHcxgp+DEROIk7Xwtu972jp1P5mS+jMynP9vLFhDnfqde2cmlEP5CG7Vez1d1DovSs/2d7oV2qBKKljLpdup1vAJvAu5NSbkcQT2bzS2Ka/Hf8MVXTvjCamq5FE17WDe1Gj/VUMP7I6YmM2zMPL+/MKeXMNdRsmFh1hYR7dCohYNTXXv4fR6Lu3vAX3JzslIjDBoEwcQMIWd1ZYMtyZwN9GOpT3JNwvKCnFK1sa9rJBQ3Qg3xcPeW2schCCOgJIUZwF3XEVBKUSN4TdcKWjPh1Kq1iRKMTWD1tJq2RZSRVVticWneLqYIBHMjlbZ2IyxKTl+WQ/Xt7I3caNUFqZS2NlJ4hlFWBcQQjCgwo8ZP1tZNVc816+CiLhrGgSICBYfn2b1Yw8mJzPx4PIJJ3ab9NKkL27iKZiWK9N16PtzFrlIB83E/70wtMAcBEUnvNKijZJ3zDPI4nG9CYGa1cpjzcL4xtRDjarMKkXf7XTlkMhQ7WsIw4Hi8WY3rzarbjOnrbzy5eTHdPLvFEZGjAozA7ZoZuRPc1K3JZAJRtb1r60tCM4Mjcldb6Fd1iU1Cjfnh7YeLZYy350sLilrJrhk+medF5pndk8d1GOJQYkGBJkepHCuUUFgQhYkJTNU8kLK7nlbbbuQCDiJCQuTKnNlqjYqTlslhQkpU1Iw8CEvfsg2r0zzgasWZrTUarKhaJViabobzjOI5mZqWe/tzECjAJDi5FvPWMWlmDJoVBAy8XvVFS54LsSj8ME8dYjd22XOaVboYYzTTHGbpoFDTrDYjrplqeARxCyRxZu76LmcVFivuUOrAAzABVaXNMLeUsswc0JkrEYQoQJyMhWIMgUlVWJjIC0iMiRA4VPkSs/RhPR1KOpZcPEQSImNnAcymw/E47eZ5SmlW1b6Tzdn5euis+DzPKeXV2AMagxtbdkt+zAYQhBE66uExBuHOzIv71e1dSinnFELX96HrkkOJKIYoIs3eW3U+HB1FHDKOLOJuxdUKaJ569BLCdrt9+vmzekhmrkVXq9VqvXmwfbgaN2dn2757fjwcTbHaDOvthjh8/OGnnz773B1vvfXW83RtrJE7NdJcPGcqmYi32+12u4WXaZq1lFyyackiXkogHmK3GtY3e/v86vrzm4Mwh45d1cxdhLx2hygDDm9zCmldYjmxE3EmK0B2pILiOAlJHHBkcnInhi7pM/UpYGpu7LXCuAdy2uqo+qq0rfJqK1WWiTgED1AkuFETVTtVfSpwmgOplfsVTFqmZF8iOL641Xmcq0HHsv913mXcT/LVQgYgOH/h7SBzux8w3InAlQ8v1Py9zOo446eOEmqRsgzsSy+MaPFfoErhBojvjQl/duI7HQL5abr/maZPK+9+5qf0c/62TMtYOpiuRkHQcSrpuMOP3v7+r7715pOvXt5dXx32Nxxs1ffEeXf3cjfdlTKRC2BEvOpWH/30+Xs/+eTTT44o4ChmKmDyn92PL7cvty+3n7dRjfIquXSRI/fTMWPAP/g//+Fv/+ZvPHy4cZLiTKBIgaUrSOvVmsFa7QLhMcToNIZ+PQxzSSGVuBrI1UvpAlua7pLe3NxuN2eb9Wbou4LjNM/O3vdnm/OzMICUzYwdLFxUi3rOOVupw3NVOi+rwFMY9isHcFrqtEFU6noUcDCL8P5Y4JiSnV1ceqfP33358cdPwXJ7W8laJa6uxzO5ueGnm+473/zWsNr8yi+9dZjy8ZDHUX77r/zKb/2VX3t+c/vDt9/+/vd+/OGnn337tQfH3KVccsmllFmTFpfITNwHefjgYuj687PNo+35phs2w3o7rh+dnW+xIkBhDD768abc3B13V/vrw/Hlfno6T0elNZlsNw/Xm0fjcJFzmI6r9969+cM//N4f/vEPr24wXUHITGGZALZCBFXVnI+uTuIE95KqZKOVlKR1KcLSxlmuAiNiB6ver7KodnnIGU6L5W2bg8ibHSqcAbJTU3YZwAkgtybRaotSYjCgmpWXadEBURgDgIgIqRadc1Gg80wIYOnkkPTq+fVPX1z/s++9+z//o+/++reH/+xv/M2/9Xu/8wtvPBoDf/vhL852I6S7cnv98uW1v7h49GR1tp4n02zomCnM+bA7XBtlIwNLDKN0Y7SeHBQCtKRZg1CMsePOGZmRs+Y85+lgmS4ffxVBHUVxVNvv9WYuB7VE4hIphACGdSQSAyiG2PfDoGkqDtB33vpWcROWvhuIeDrMc045HYhQzOaUQozZdT9NRctxv5/S3HXxbLMJq+HFy2dHp77frKTr+hVgZc63d4c5HXM53O6vQgAz9vtJ3c82FzEMabbpUEw/evDaG3/7v/jd//zvru5u8ycfPX3vpx/f7W7R4bXXXr+8fLw/zNM8z8d8dfXSqPCgKR2n+c40meHNzcWo/e3dEaVcPrnsuwJKBN2shs043mmaU0pFo6i5QYWYXcmqfKeAjKCAVicn8MkClCuuUwEEDyNPdhfW6Fd8+bXNk2+9cTXfzJbQ87jZ7KaXlkArLymVOR13B51zmqY8qeXiuWjyMsFmVL9a7rlauNSiq4IpotzcexoCQg2l4mV4oGY4ZRQM2syw0JRatR+3tPq8whO+KK8X1OC+plnwlJP4jRY+TnDS6gjm9VdGQMXqAQC+hFx6JZP8nAHtCz9orz1BYQvs5dwqHfNacdIrYN4r+In+zCcCDruviNmbNqCgCKR+RktkDADDGSoehEkkBkZ0UPWYhQMkjeZVlXtu1TUJJD+nDDuFWZ8ALH8VclwwuvqBYv+aQu6Eu1fj8+W6AWVOOPGX6gklrpSz1uNFa/iedA/U8DxvbXM081ZvqoYv6AYqm87ceLn9GixofOL6tDunfje4auzcnav1FL7QKbYqH2E4qkCbGEziSyO8vY6ZdEG1vOEP9b76S2/eoCGvOO6CqNa2uy3oTzu3/y9779ZsyZGdh31rrcyq2pdz6z7dAAYzg6GHw6FHZJiWQxF+sF/tF7/7yb/H8v9QKMJ2OBThF4VthoOURHtIhUWaGnNEeW4YDAaN7sa57UtVZeZayw+Ztc/pAeigXilUNBBAn8veuy6Za33ru1S2bZucE1BQYGAwgwMLixUVrvgVyKCmTcsCIpL694ZmGK9aHVtgTRJY/9tNm1KGQFoMNSWhUlWaA7ER5DcS0uvi4xVndWNiCVUHWKmVtb+ozQrVp9nMna1BWw64avZqkswGYqMoVLuqOo1Be4oaodChWpiFhWMXARhXExsHw0wP494WvAOEeUxwI9Yu9l2MUJcQIHCj6kwGYw5BRGKIBDbTnHNOiYNsN+sYejhSzsfjuI5diCGuhjB0MciGjSO0ZMABlcj3D9P5Kr58PvS8Wsnw6u6L8f5ASgSwEVkNm3B1Vag7miC2NpuNr1pHU4L6Y3V10yX9ofZ8DhACB4VRXVWZSEjdwB5CZGJTNwW7RInJCxkxS/U7g8KSZU/lUETJnawYcn1WmIxdyZnANJcMN9L6opU4JjGERzkxkYSAQd19Ido3Rom7uylMzUqB5DKTCNwgVhMurI4izIpZFfIu9zznlBrxqvr1BfKmeoVnZCtugIICkVBrs3lBlwE4Ezj0Yb3eMPHDw70nDyxg7tZD13X90Oc8T5m6gUWg0BjC9mx9trc9QMjmVko1TUeQAPdi2Uomks12kEJHHW1GVmVqcGO2UlfmPsTAVG90ZnQdi3SVZ5tzTmlWFcCYm0+PQN589lZNOxm2q8DiReds83a7uX7+vB/i/f1NStkUMHKVPKly9gIzZuqYulKmMSfJLtL8bfs+dl1XiqXZ3didbS7zPE1TKhksiGsOoascUGHpQhyG2HUhsjgRVitTdYOqMgcnBrtTA9a72K1Xq9ev3nQswlK0WEmkRubCMgyrVT+kOR2P49nZ5dn5OYdwe3v79vbmOE5d14nEUsxgoFwMZUrBOQIdxyAd1HeH/TwdSkpqVTRQ4ytqSoU87PepFAQIB8C9eAnmEBNxgrb9x2tiYAvhQHOYsmLIhGQoaPZ5VpO7iaonHIGZTGHuVehWY2FqzKW1RbrWI7BTKUDEizK/rnttPMJMbouK78mbeRzf1PsdAIH9ydBlqdO/etc9LYqn77VGtGpfrVvH6QXeadWW6VnbHq2CfXUAwawNiCISMhgRiAlh2U3d2Woh1bwnmbmyctlbx/GbVdPTF22fvs2MGrdsmfydhm30jseBA8RMS+9SyV7cxJ/8yIar388iCs3FkPD61euSsxU7jnt4XvWyPRs4WM5zzlPXh67rYmRh6eLw13/9l69f3ULRDytXr1uqfemDfH18fXx9LMdXPOqWZsgQWMbjEY5/8k/+5+vrZ9fPf58g6pS1uuyxFo/cmWrk3kEh8tXVmc5g83mac87MKYaQJUbhKAw1zTnPaftys15vQgybDhwYTBJptepZmucssYTANYcjhFBKaZyCx8ngE3jcm7zncR1a5tL1v7A0rACRs6t9/vbmvW+chW5I7jcPuLgMcaAgJJ0fk39xf8e87oT/348/LSn9gz+4Oh+2PevN7e3t2zdEIcTh+9/64NvXVw+H+/P345gP4zgdx/EwHaYxmfvQRQZthuHDDz4MIh3LVtYDhV66dejOMHTgZLOhTD7d7W/f7m92836XDpMd5pIpxvtjeu/ltyVerNbvv307fvzLzz77bH93m3/287d5wvX55X2eNSPNmUSYujSXPI0gZg4ipOquimqWvvSv3qapTQIIL+7BcdquHom5lZQLAi2zl3eDLpoTc236CeDanVJ7CV+2Rq2a8rpvspd2+ZbC3mrjCAK5mZYCB0dRUM7FmIYY+23XAxzD7W66vOhn7f+Pf/n/3N3c/Jf/+d//vd/+lmyHUsSdNquLsU+iJXAQ5p7FhCN3BCqWsk0uyaBAUFMunjwF77oQOAqZCygQuFqZSC1/lZgUgI8wB6tTKpiLH5MfZk/s3qEzmMJIuFUATOthpVApwcW7vsuqcAd4Tul4PB7HXc67vu8IeNjvihYnH+c5l3RM8zxPxZWCBLIEL+qiltV8KvvdPB7nXNLhuD8e93M6rlahH7oQ+0hsVorOoYvn/SBh+NUvf/Li+Yfr1eXB5xRvzr+BVd7ePzyMdrtPtJvSNKW3b2+z5s127TFSoBg7QBDsi5svVtsOROqJ2SgoLIdoLN4aUBcv0GIM6qhzJ6t59+6U2d2gTmawakpzwjTRUAEBByqSbAJf4vLDi/MPNvGCP/vFq7GkZ5fXq+3qZbz+7LO3TLzqo1nZ3d+WycucA0tYrRzpOE415J4DRFhInOxEMK+snccb+uliRwuRvdm4cDV/c3rEo2rVcuIynX52WVJ8of+8w4DCY9F2amBqQYnahLen4iku1qCaWla5LwYMX/qdT5foBaBfKqnH/63aw0ca1/IK9XUXA6nKRH2nEgPe0Ra06+xg0sU9qy27EU5LYFeg1ruxG9xqRhLgDeiopCBA4VZjeRh4pxZ7CvfghFUtBk3UVm53d6l8mi+dnC+dLJzUD3V5cVSbv9OZo1ZgN+fZx3O6UNCITxICF3fzamdPVD3D/MlYt1W21EbMv/HRHjegJx/2ywS0rzieTIhPRvdurq6VaaWqeMIxWv5dh9H8twWwKo739FcscM+XnplGAiCqnEUsO4nVrRf15FhxFiMQUzCvKq4mu3IiSPMc0YoqWw3rYoOXZhHnLRQSix2jLYbhC4ZZHcZRnclgRASGCEq9pnWpcXCLmHwCYAFkFUGU6nyGZnlHjx2KVZ0iOYECWfGmq61NjjtqhDzXT0mlFA4mFMAUusCRDVa0qBeFwoAAFnau6fFkWVWTBY88TuMsrNQY7kQGLWoFkclR2WjmasICw/7+MO6OIoEZQWLKhbqYzaY5l5IJ3nd93KzNipXMTPvdJKDn55cBvc2a9xO56JzqAAAgAElEQVTUA4Jnh1WFIBmKe3EyX1ApYq7PrD6SN7XCfu2aEMOp0fFQLcaqRzUqZbPerOoO8fVqg2DuTuChX3tMyqORR4ksnDRZtnk/JZpTyitZhS4myokzEzMFkcgkTOxk6pmWpQDupm7QUvVHRIJALKGjEMgse2ou1xxYopQ8qxUr2cyslNlNA0MdBI7ijlwyubiZ1mCCugcwEXgeR1RwWYhERMTdTDNAIlJVbDXkzYBiWr01q2g+hGCm7j4Mq/VmXSyllNMhh0j9MNSpl0TmrueCEIkjqToE0smw6eac3EzIU7ZSrJRibtM8MgUY9f16s96uQi/CD/cHX1TqIJg1WRpcTeFW8jQRU2SKa14PGzMradacVavvWc2uhZurY7Nab7abYZCi+WE/5Qw2XnWrEKRkK3ONVZJ59vF4TLNr8S5IN4Qo/TRrLrOI9T1CRIyyXnddN6g6UynZc3aHm5WKj9bZKRFCZAaCSBeki6HvIhORy3pYmVmeZlM4O0nVHzOJEHOMcdWvNqv1ehiihDwlccSGHkFItNg4zgCt1+v1enN3//Dq89fTNDGHcU63+93Bj0YWKQQnLrbqulUcVl3vxfYP+7u7W9NccgYZiYQY+th1Euos4y//9Y/udjtEmBFU6zqR3ZzJIbDcVvLTCGmBehzm2ZEIxVAM1SQSXp3dqkwdhJYC423HriGpYCpa2m+slvFwcwfzyfmyPic1puDR/Fu1iihsUdo5luH/I8hOWESGdNqV/383KjptlP64w5IvCS8gAOxf8Rvo9BLulVi2lFK+LP7Vd8KDRPcCMmbiQMx8QjDhDqaaB4Kns7y6MDi+opjCAsm9817ah1nqKYfXzfVpZ/T0Fzz++DKeQmOtuTs5BSKuVvmIHea5iIhrcS+rdee9n5+tgnjSTPDt2Wa7Wfd9JCKR+M//6E8++9UNDCyUUnY1dIa/ReXz9fH18e/x8aWnlBgOqiTulf/ff/GjN6/fOiAIRKLFqwSMXUIIx1RWw/o4z8fjLga6DJtOMU/pOI1ZSxDuYzjfbFfdMHTRk+qco4Sz7dnl5eXzFwdmSdnG43G/3xFATCKt92OWEDh2oa7JZjDmZZLPj/Y2BAcxL03ho3rwySeqwh4jkuBaPv740279wepSnIMxzYWdRGGHKdnDtL2MZ2eb/cTTPB734/bf/vLqbHO+2QTWVMbd7rAa1ldXzy6frS42uLjusq+zasoplVTDRNx8Oo4C/uDyPLCw8zlvVtRH4gAeEAkOtT5KmtJ83KVpZ5hYCuCTURdXmezZy+8cHuwXn+5/8m8+/8VPbz799NYg+6OXst1nG1bPJk82HRwU+x4W8niAelxFJvactDghAMWpLN6rVEkwS9+LSrOtswZuBs6+zLNb4tJpNtEW0tOExb3yg087DhH5Yg1T22VdXhWVUkAEWJP0t2A2gBxaABdnF8QY3aFZ56SKFPvQ94P0q4H6ZHqzr/agxzV3rz+5/Q8+Ovutb768Ot+EIGE9c9bAnRjFbkWIQpLynPIsEcrqlBXZULwYWZAShtit+q4PQu7F0pyOakYUJMSu7zoIlOfpQYg9mks2npVS4aSYCwzsyVMuGkMM1BUzZl53axbudKohJNM8zznlnNM0z9M4HcekY4yhqD7sdurWDx0HiaHv3BVmjEmzT2rgrNmTHqdEji9uHo6Hyd3meR4ncMhqxhKZPec8jkcCbc9W5xfn3QouY5aHiTXH2Te7ELTH0F2ea/bd+Pann3w2zyjK7pihZ9yL0KT5cJz3R3z/qmMJ601IxY7T7nCYtgM5ktmcU0IBOVyZPYQQRKK65VTTwx1KcJASzBkOP5H6qhak0licOyg7Nrh40V18YyUXuEs3N8cRCXlTLjaX2/OLwzhGjut+ddwdDw8HTSi5bLt11/WatQ6/sZDIKzRjoOpXswApVJWxJ+Pq5lNRQQeqokJio98ccS1c+BNS9c4XlwqvEu2/BC5VpKdCxILGWWyG4DBnw4lIVCkATahlRk8KphOg9FUFYFvdHtlKywvSgmdVNOZUPtPSmS2PX/sYyzwSyyy0/Sqv5d8SuXYqBT00wSBXP2sBaKHqeBNd+klz2MxWqfq4f8WghOh0GtuqXVvptrDXFfzfoXg7leTvwHuPVlQEInZ2NGxrwQ9RN5F6azzeLbU/lUb4NaeT+Xs7gSdsA60cX6QMj5DcV101N7PFZrd9NzOdMNHloy/qhnorLg6ugFvdfolPRlr1heow+m8FYDkQWBYpI1VIbJnb2wlsWybeYGbhcMKvHq9lRS/UjRUZ5l49hhhQsMNUi3k1ixYjQi4VH+HQMTMzubuaxmZEV2GwFk3eLsRy7RbbfzIzVXP3JQjr9BAsrREsZ/NTt1LrBQPDXYwfb2dqE3wCMTcVr8MdWrzKyq0ClwTUVqnRAtjIvSIWlgksLDFEECiTF1UFBBSo0nYIzJAae5yzBomlpJITnEMfYycwhpmXYh0VW1K2TEtWMyeYi5hqtW6SjnWek5acu76LfWQRIoeAY4ymNkSwms6FIbGnIfZROujIKlWp46TuVh27nIAaTtbMlRfCGzUUa2kPXRAAcjM6rRpWAczmMFfrHoP1Adv1NoWUaBIO6/UmPxibmKlQYCbL5sWycxd7sRpXHZVBZOTCFKTqHCGAi1X4UVHt1tTMNCOLiIhAjCtRkUGEVV876CaHHY+jk1dRNIDi2QsMkMDBSc2yFcbyGNJyTzvcFcyNimo1Q6h+gzBBSKraDUSl0gnNygnGZhn6VbHkcGJSVXPv+4iiKVkwdfUxTxx5tem62HUdOcphLmUukLtSxEz7GLtOzA7McPdcUikahF0Btxiou9iwCAuP85imYgYw+j6IIKcyz9msMHMpag7To5kOfefuaUrTOKnCy5P1UhH6zhVlLseSiyY3xIAYAxNrUVcjJ1NziJvMc9kfiid0va2N84ZKhmqNuQh1A1a3rDlnS0VBTMKhixyiRMspq7oRVG0Tg1syq1JvYUYQYXBdE8igqmZgAUcJEgK34BRhvjg7G7q+41BC7iEsElfroRvSnFPKIcSz7cUwrI7H6bNfv3r1+evY9WA+7I9f7G5pK0YugUGxD/FsfbYd+vUwWLHpuD/uDkGoIuocaLUatpv1ZrXqQhTI//7Hf/Tq88/hXOPVA9gqlkQEqVIFA1X512lHAsiYKM+JS1jCkAGtWzdVCzZrpQyqeHdRCzrcyFmtBm42U3RvjpGLNQFgZn4iNjOYpKJaqk/WvS9vBgQATOzcvAXxZPvx3yCFt7V22SBoGc5Y2xF/8/tOpcwTuKi+V7eFvdg2zSqVQfud5tIxlLS6eAlzYIVBl+KAnRY7MF/8xBpR/m8AsN7BrpZp0ruNIrCQmZ9+lNrgPIJky96//LN8LjeKUrncIdJF53AKkdRL18mz7UXitN50UupgWlerfljHGOFe3O0Pf/jJcA+y4HV+o7Ve+xrB+vr4+vjbHx76TksRYeYQOe93h8PxmEpaBUJl0xK7s0gMHOZxvxq2u/395599ejg8nL/3kpPtuq5jCaDAsu7juu/6bggSoWRqcPRdv9mcXVycq1q6Ox6nw/1+B4IIIwialJwkRGJnYSvVPBzeJIQnBtYjk7XC8HjsHCrxgNDsZd3NYujNp08/++zlt85Xlxeh60MvkKjFVI0BUWS1VGzMbDnd3z68+hf/7L2r67/3ve999OH7zy/PznpJcyqHO8zimn3aMFmEEywKh16IJKcsOZc5T7uHAB5C32/WWw7RxVUJmYFgpsXyeMzTgaisBjGl/QjqN+vzF2Tdrz/ff/bpw8//+vXPf/rp3a2WNKxW58IxBD+MqRu62AeZdcpTStmqQ7JENzZjlAALIAYVeKndPahGgsHqbKa1qu4EBrMEb14xLQSsNVK1WF0a93aa+clJx6ndIF7a1XZdHOYiVdNOJAyvfAWuSgFCq0oLE5hi4eo/0cz5C7OZWymWNReesz5fx812Yyh/8i//+E//T/xHP/jOf/IHv/vhN65/93e+J6st90pknjV2oQurOed5TswsguIllTGpKkUOLt6bF50nw9BttgSkNB93h3meQbxab9fbcw7ihfN8cIkk7lIMc/ZUkJRSgRJQzFPJHa16p5IKAoYY+9AbK7MUFDfPU55SmlMyxYlS3mb5IhLjUBOhYuA+OIxFlN12ng1WyjgnU7t72B0eptjFGLkfiIlL1pzNPaWU9vvRHBRyHFB87LdcsC9lmizPvH8oo6fQ0VnsByq+PV/lh7GDuQeIKaEbuu2ql24yun/x3jeKjcTGWfeHh/0+bYe1e4oBwgRtOc8gEYqBA1SLKgzMUrSQgbz1OOzuhJpO1jLra3IRKQa8982rZx9uN8+7jONu2nNH3WqQVUfMxXSz3ljREESYtRRy9uyK4hA3ra4P7ijqJWs3NG+VOqOvU3T2xfW52U6jViQVN+WaqklsoEpFP9HLUe/Px/KyriWnG75ZRZyei6UQaisOqpc4yF2ZmEAs7JWk0vKGbFmoHgs8/xto73A8duhPvxvt7bSWu4FG7QcI1VW7OTs1TKieFyz1IeBPOFF0go/QwgNRF85KyyeAwAIKLFFYCFwH6l6jHiry40ze2C8UzOHNhvkEmj89Hs8aPVm/QU273Gy4/53Kt6XwbFwef1JxAuZgVLLI8uX2gvXMeNVBN8CKmkyazIjRHOKfyimeXpTTNVmgK7g/MQTzJ1yzVqkvoQFP0JdHRfzJQf2dH8Qi71IHkwQ0vOzJzUP8N0sIT2+tLeNMIk0c7u6m9sS4/fFcEhEad4kF4mQCVl+ot46aCGDqKHACAhhc7XipYkIle/DY90Skc4FYYCYJMQYRVtU0W4zR3TWTkbm2Z46EbNlKqrqkoldFDcXhsOACKlrdOcEAC4gEMNU2fPHlEzdRnLmLExmqqN1OjVjlueXagzi88nSwKOGrbtCpGpQxu0fmguIOdyUiCogxckA5zMiAwtlVDeIhSN8PMUACB+KLs2fjzsYymSkTYhCnAEsx8hADERm0LmZabcsTDArWlqYSh2mcmMEStn3fdVLKuNvvo1AUKqUwoKp3t3fb7nz9cnO2vQjy1swii0vF5Gp2PXulXhJRM7kkh5kuAdVoT8WiFmR49SXVhb158tN3NVBorpkcMKx7JipaIqGLckcP6sWsFA/sbKpI7j3FPrLwPM5zKemQdFYQmEMJWSQwMQlPh6kCVO4gqzQVEHOQrosdiauaqrEbs4c+MEt9JNSRR5OmXq1XH2gbQMtfrbCkw4rTApu3bnizOs/znFNyM1dzMxBRZHV3znBnUoOH2NXpAYM4SBwiR+6GvowZDi263+/7oV9vzsg4HfY5JyvwGb4q7JGF+hCSWprzbufj8V44plzO1hfr1aC5EDRKV6yIIMSQSpqnSYi2m/NhHbJ2dszGasUlhM12C/c8FU8osH7gECjNnkfb+7g9m5gkzamRUk+IGwEMnfOh+HF3cDPv7fn12fnF1fXLq7PN2ZiOMfRdLPOciGOIA5NamSaaY+xi7N2ZqI8BXY8YRVjN53GaiNI8a5q97/surkIMwtHMj8fj8Tiap1Jy7M7nUVOaSyYRNjPphMBa1B0igSCqWudPEqKA4ezu5hhWq0DchdiHGFj6EON6O2zO5mmepqnvh+vrawdev37z8ae/urm9efbyPXKac1ZY5F6YAscudOuuPz8/P18Nq9VAoDwnLYXARVMuU5RN6Pp+tR6GddcPEcO/+vGfl7SBGij0IRBKzrmtQSc3RlkqDmtTiZqLqtnElE7JHXUXYG/pKa0mb1u81bLB4cbkjlJlct7GSkRgYpZF9Q93dW168iAN62sI8OLW1na9RnddJmbtDwEtw8W8ecCD63PxjmPCUt6DvKYaowXn8gn5qh+hSnmJqP29nTb6eprqTN3hNcm3FlxucIaZRGnGe9Lsvdxdl4qHHQKS6nkPUBUB04K3ER5X/7/pWIoTNlhNcW7v6pQSvbzRNgT0dtFqSUXkZETczjCAFk1tAMUQVkOAC1FU8yDxbBtHHLqeiXM5jqkcN70EjnBxjaQRNyDBEEPk6FGzzct+3OjrRKeP9KQq+hrf+vr4O3o8VSt8iUzQjtOQf0nQsL4bDsdbYfaC7JhTKUbqoq6OxqVoOUzOx/20Obf94fj69u3+OL3o+qxFIOw18i4aOzP3XdfH3lOp0b055zlPwg6iKnkPgZ0gzAzS7FDzoCBTLSmlPGfUiRFzxT/qewc9iY8F3lmtWmlfk9DqOLcuzfKwe7CMGPou9LIQUZlDHCx06Tjq7f2RMEyHMefy+Sscdm+Hbtisu2+8//6HV9++39/uH3Yxdlebi8IjoHlO++NhTjOBQpChH9YxEIUe0Fw6ipJdwL10QBJ4DGKg+7LzolaUmOE8HXd3d/uLD37/Wx/+jqD7x//of3rz6/TJx7tVjEN3iX5wFQVttxfbbfjk4zerYQ2zMk7FJ3AMLBKizkUTYEFQOWl1H1UQCzlRNUYsy/lBNdwmZqHgBkJpkp/W5rVokPb9MDRVUb0CLrKccOaFflVPfk2jEnd2ZwZTnY1WR5E68G35yEpGjBhEtFhOxQGKXYiRRVKa5ofD/DBi6FHKyPHmoRyp9JCV6K9ud3d/+udd7//Nsxff//b3E8Yy3fM8iZRVYHgmn89Ww0PmMds0zmNKFONqNcQOIdB8OKaiQM8kShP1RuRpnoW6yDOMUlZCD6iADFqsqJfiJVsuMKaQrMw6IZKrTXMKGiRKsVxyCRHMbMXmaZ7nOWsBaYjsHCDEQfphtd6cdatumidn6khcOMTQ9R118oub18xF1XL2kvPxmI4zLrqwWm9YiiDncsizEzMosNSK3ffjmO4fVmebMY15tlTKmMa7nXrW8028uTnM0/zt7/3WR9S5BzXdHaZxOsSuW2+Ha6EPyrP3Xjx79foThwWh+yknjdKJRF6freLQCjKWejOwcDQDwORRIEUzvEKkekJTHIvsihXiCEApYHzjt99fPwuFDrv9F6MlWdPV5fl600/5cHd7H0WKl+NkxYuzDyGmWR0ufRTEzTlZb64oU5lVC1lVLVoNvq94CcO0rg9YzIyWJYLdCcRwt+qnUHWPOBHnqx1MNTP/qjWTluVyqf8W/Ae/wRtyImaws8PdudpxVxy4qWKWmgjuMG4eWMua/EjnoXffRsWuWvXn7aFksLlKy1eg4NKmtI+/j6zGGaABdrRgN+4LnISlYW/5ZE3nC6BaIXNgDmQws2qkbxWR5UrINGoeeUYNNVjMxr7iNC5Mt0XuDSJSIIC80lya7frfdDwienVnaBghsKic30XpatjEu/ugP+aDL6DiYtcGq60SiKqZl7fikXDSm9bK3AEj5YWOdXpT7u+MeBv9ihhc7U7sNDt/5+Ocrv3C0HIvlZZUM0ysOenXuEM9nUymysog/tIfEZbAIUgIHAiUNeeSS42iYApRWPj84hwENa2OQE5OhkChC52EWLMPS9bHc+oAC0sQjg6NQYSFnLU6nWdn8Gq97mOXj6NOKcRAMPfEZKY5p5TmUZP2fV9HLFypGhXcDyGGXoSrw1fgIBzgROAQQ+w6OOmkGECVEsNi5jqbpeq2DgKCkKDanQEBFNnIi2uN/pLI9blrpK7l8jf+Uc1pC0InIJiZSVgCWBCqCb0ws7tNaTqMD+M8hoh+JdIRs7NA1hxXsR+GGLuAmEe7vXmwYl0fSaCWnbKikKETEqMyp+mQvRQiGrrYd7Jax+122K5jFHLzbljnTKyUSr7Z3b25vz/sD28fEvv84bc/7PshiJh7zv767ZvL8+vAfXmgVx+/3V6e7R+OaqbF1LTSV5/KbVTdjGHtTBFFosgcWSIjklolv2kpbkZsMcZu6CphLK76PGcw8RVl8fe/9fInP/vJr159djzsx/GglKUnRE+eCjIN6M8iDzJbSZqzlSlN5gZ2kDuU2Di4UcrpsJZzKmIJNjsSpAgX1ll1yukwz8dZLUmooAYnRyH3QBziENeH22PIARN5AiuY0IV+6FaWLB8LMlGmciw2OSVQZsqETJSIMzgzCqGQl2brCGs4qBuKI5ur1a1EQe6kaqVYzpbiIMNm7Yb9cdf36939Lvrw/vNvPn/2PHj3jasXKEkU274bArvpnGZiSNRpRiecZ7OswmHdrdljmX09bDfr8zQl5pDS8eLsHEiE+YMPXry8vvbsu9tjHu3y4vl8zDkt5Z0amQhxpRb2UZjhnkvWPmBYBcDcWCiwBDjHEIhhrg50UWLX51I+/eRX+4fDxcXFMKy02O5wGOcRhNjJdrO+ujy7urqYxjFN83632+9SmqZOeqLgnJ2ciM/OzwF2QC3vx4eU98Oazi/D5pyHLX3j+r0+9qthvV1vtegQohUd4rBZbzqJgaNImOd03I95mk2dnISDK/KUV8Pq5cv3Hu4Pv/zVJ8+eXX/2+s3l5bNpTDkpCN/56Lubi4uPP/nsj/7kf73d7T/45rfDanUYp5v9nXT9wdWJu74XUB4nTVNwKzrt93cFeUzH3/nB9z767m/94Hd/8O0PvvXes/eeX73PYZVVZLX57/7h/xj6XGkyJSspMwUnJTjBpXKkrPquei9dF/ouxI5EVHxfWFGyuQKVSa5w8ygSiNnAJuIhxEiRhSMRmZGpWdZ+uyJhD2g77pK/ZHWzIyMhEmdBlXAXUyWVQBKoPx/abmUg4sidSCAjYSFiNlI1L2ZqxNR1oQpdaxkUY2SqoI5bDdtQK2YcA4IUNTULMYYYSWThcrYdyYoFFiYhFiIyb76PIXIMTFzIQQpl5y4GZx2TjW1EkV3V1cmUTwVTZftDGMLEgOcMdVKDsau5tgG8FkUlx4oAbbttzwWBRQBy1UAIwkFYAjcPQG1APeBgr0nAtSYkroJic7IFRHUPxgENhzOsrgaFchet+O0X03efvfz7v/8ff/Rb3xmuNl/sbmbfk42WD7v57eqy//zVm+98+Lsfvf+DWF7u33b/+B/+b+igSadx0qIkcCc1brBiXXpgjeitjfpWT/TT4dPXx9fH343jdFcbrK4oi1OtM7NRncTVsTdqIho7k7FIKGbFCgjd2fq//6f/9Pd/6/d+8IPf6Wn+/O2PSR/yeN+Hfvcwv//+d437H/3sFz/8yz+ZgPPth13YrFcbVZpTJqLrq+fvv3zP1HMuwpTKfPXs2dnlejfe/pt/+1OzDML55flhdxhib0XHugFpMcs5jXOZDbq4tHBdbOFcdUPExGQgaz6PfhqZovGC6hkItS4mzRPWFjS8/ODyfLNFhs45zbPm2ZFDdBdXx5zy7c3DZrO9vn4BngvhF7+++8knH//q8zdHcNxcnF2/328uU6AuhPtx93A8FKjCi6WipczJ58xFY4Ykfba5uty86GQ7kHRwyYXKLGQkrIGVh2TdF3elk+uPPvrPzrbf/9Mf/vS//Yf/w5//X+MnP0/fffG7Z2cvf/aT17/88c1+Oqap3N7d3d5+EUApTaqZhYmoMut1nKw6ELm7FfJMSOSJPFf4xbJqsg6BIYIgEHEmAxuTkam7uRV3NVO3om30uOgoCCQk1bm3Tm2tkbtcqWKRCH2IfaQgJlQtKp3c6gvX8PV2varhoxc3Is7mSXMlYsQuMrMCbhZC7FbrbtO57/vBgGzI64vNPhesN5/e57/45e0vbw9/+Gc//Fc//2z74sPr62sh4h6302chTCJTSfteQofV1ebF84uXwbr7u5vDw31Kx66jzbbLOO7zA4IdbDzq8d6ON9PdvR4ffLqbds8uLu/2NzmYsg6yebV7O+XCIUoff/7Jz01yofGQHg75kCy7qFImJgGVOU/7ab972O8epvkw6zSXaT89zOkwbFfdan12fgXpFR3L6jiVV2++eP7yPQOyFoP/9c8+Gfqz9ercC9/d7F/9Ot3fopTCxKvVZrM9j/2wO0zHcTyWYmAD3+3S6zfz7X0ex7Q7+DyG+Rge7vzNZ+X1a39zP1Owfr253d//+s2vf/32809ev35zfzPmfab7hPGY7x6Ob67XkTXlMpU8S/R+oMMh3d0exIfv//bf+9GPfoaDsfgwbAh0PE7H42TZhUInHbRm1VOULsbOAZah67fdapvNL188m8oRg26+dfZf/df/xX/4D76bZRfP9YPvvNAuXb7YHsr96/svdtM992ooSfP97pBS6vrB3Qu0uAp3BQRhj5S0JC9xFWdNSua1RGKAYOxOp1iqijOgBqpLx87m7KGn9fnqYZ6k424V+3XkrjKUjBxBWJqGoELkNVfLoOpqls2ScfNGogUygYNqunkjGaLmu5uh5fWwUBUckVkTvnAjNy1DzaZwdGqpitwYQU5uZE7uwSGO4CSOQAjGERSMuTjUqTiKkQHqtaKrT6E7YJ7zIpOiiu0JqJaDxNLSjrxCV2Aws8TY9XHVxXW33q4h5G5WrVnUYBCpjuhtlBlYhEKgwCIiQYJIDKGTXGZUQGqRHLmpmsKsEeOqd62pW4Er3KrUmAma1clRL259X3C3yopwERaRmsRVC7qqgagEnC52EoQD8wlsBJYPStKE8kSVOkpthONqMBMRdiJjaPNrJRAZkEFa4UI3Lb9BvKpb6mo1hCAhCgdmIV5OL9eyu45s6QR1of4oNfykza1dK78EVpE5a4Yo1VmtZNVitJDvtFjJ5asZWGZGS8h6FZhwdU6piHSTDlpKqclPFlCtIqymRihKWMzivLVeQo3hSO65uRcT1M2a95h7mRMT1/5fUwbV4XqTG9WyXFOur9XMLZsJFJjBHEIgdxcONZTNFuCWmSlUjxg0jhiDg5q5L2B0Ax1toQksTvhOdbRli09NffIFlfVVPWWYa4sIAlyqqrBK/QC4wsm5cRRrVH3PAhE4eY0kJiYVEDznbLNZKmlKJZft2TZEQYCzOttxPqYxk6LaugsQONQ7pWja71JkrPqwHlZn2/Pbfb64vBj6Ti3t9rcpJQN6QS64u9+tu37ORXMpxUgAIYmSJfQAACAASURBVBOnHthinCYvmaRjZgNcTQ3CYCG4q1dw+wmg7dXzCmbODEtZsJx2oiBMLGZe1AtM4BA427Aazl9ubm5v1BQFeS4OU3jSYgv6C4aSueYqMFY1aq1ZLdtIAouQOTkHTerqpKByKkIqkEwV7WevkipWJyMFWR3EakOPmRpUXHMkXbNacVVVKIGg9UqBIFQl5+buYGI1IwV7fVIrhr8sIerU8iLMgsNPURwAoeQCzJoye4wkpJLHfPP6Pk/z/d1Nuthozuuz9Vm3cba78X532BUyirzZ4HhfoFCUcT/OPAeJfRfnucxpGqep7yMHOc6HoSe18XDszi9evHz/OiV7+/bu1ZvXgYNIHEIsmuYxoWh7ljsUNcoppZIV5hAtRGFY9WY8j5ObzlOtwBB76rrOzB7uH8bp0JWw2vQcSOtDTaSqxbXkQu6mxkTD0Alvx+lYss1TiZ0M/UpNnbBebWfKh+NxnubxWAxwjCAMq66P/TSNOWvOWXNJOZ1vNkSUcnJzAsFomtLD/T6Vue+7oXdmdvM5p5zS9fV1iIEC55I/ffWrX/z84znnq2cvzs8vrs6fn19d3D7c7/Z7NUlZ9/vDQERB+n5dYJdnF8WLcDAt4zStmVmYQKqZJV5eXY1pTnc3X2RIoavNs7Ph+Tp2znFCHdNV/hM5c7NOgPsCkVBN/qgO4145qzBzV6sGog29Ajg0A3O4mRFqaoJZSVbImJ0YwkQcAbhqtf9rYzLi6ulYt72mDwbVsVOVIzKBuUbate0JNfobBgfX7cDMWtQs15ZKi1ndoM3gVHLxxqhd1lUCpO0frWR5VB82+rHDYRRIFtLV8qr1GQOUEJyc3BgiJCyutVE9RSPXbAQQk3ENDn1kucGbmeWJr9yMewlfRnMetTmPrOa60SjcIPxIT6O2/7bwlkd7hsVswr1x1RaKrjVyLuBgAkulN7OHBIqgmJMf91NKeUzHs2crU8p59CTbzcU8e0ldPuCn//onAMhg7YOc5ilLQ9tarWXM9TjuohNF6+vj6+Pv0kFPqvavGmS3dWZR5FUSLJmqQ1nEA8z1MI5Ih0ADo1Po2WalacciqP6oziAW6Yb1xbA9L1mZ1IHtenP97LkRpAtelSamRJRTKjltutV2s16tICGUY9ZShqF/8/lNntGcXxlS12euBoXs5MRMVvkR9UP54g+OhQ2xrFyOd0igtS5zB1NkqNvD/X6eSpSOwNvNJkTOlgCttH8QnHQ/zUMaLl+8rzm9eJ9eXL+4urh4KPrz12+Gh93ZZjN04fosSL89i2uDHqfd/v7erfRd5wpVH87W27herTbqni1nuGshzVamnMoYqevWHXuM/M1vvMzKuzH+2Q9//L/84Z/uXuNMsEt4uJn5mL106EYqoQtDF/v9bjfPCdWUoMDVoERaT0kV7ZRliVWg+BLBdAqLJ4e3AN+6e7ZFsMkHq+Jy4Q6ciOYAXBUL+QBNAl65tO0mcvMaOd+aHzQpihOd1thGPmkDhIUl0mBHaCmNldJGDSDT7UZCIICCRASZzWzSUnS16UIfb/aHv/jxx3H4F/Sf/sHvfHB5Plwfcfhif9exXW+unCinqUzmAX0Ynl88N6iRxSCNzCdsTBw5SrdehexKUYjNxI50GHnSYoGiijFRHzr1cnNz83B/L4O5FCMwlcjaSzDXlGdWChwmG7sYzs+3KxuOebq5f6uaiuVpTt1QmMKUdJpSKnoc9w/7w363p2ApjePD/N71dcqu2cRD3w2r4ZDmdvEaLYNIJBg5cSsYQnRzJZLj6DGCOolxuNgMfh0325RgXdeBhIhDR4Y8sKobM8CRJHRdGPpuPB6tTEwIITpiyUYciYUDJ50++vblXTzO92VOB/ZYvMALS7fadGfnF29fzYCXXMwQhUMMBp/LVA6Je7m7vcHarj94+b3f+86w7W5v3xyOu9vjq02OVxdnbx7G9SqamhUniCmRtQQB1ZSLewYKDhjhArVAwj333Efp8pSdn2TanRRzT/744gQMgJiM3EgLGdicTAE3qBU1hXs1V/bKJfPFVOFULdRaziFVrUJOxK07899cZ+s9vTCz8ETsV9WkBKCNzwjVwrUJDgiAvesp0YhfWY2Xz8WNgVUfwmVVZyYCk7RStplVVDhMWyhjsxwGMZNwU+4ufDAKESwhBoksUSg4MYo2PLtZxlZguy4R1fF6cTU9CegcjmpaIY9fBYGI0aRfy1a0lKFf4ZzKJwek5ZsBt2Zk5bVYb0RRc68mwG03q0Sc5VO9c4GWd9NWRDrtFFguTsU+QVYzCoydlJ1ccAKC6oVs5OUnb1xrHtqT0e8j0YwemXX05C0tXySzZedaJJHLRfSFs1a/+u7NQQAQvnISWwdWWLSLAERkcd3y9veKlBIWf3hbvNUN1QNIqxi4MdVoEVuZOXPtqqxY9faGOwwMglNJpWFBgVW1miPSu3d1Sqk6eC0Rf1WYWIWDi9HXk2q97TygCj86WfNjqa9iWorWW68SgRsMzY8xCq0/8JbfCFqsHB3VHp5aqheTkLubuwLuFU10N6fCJip1KCjMIhQQIjushily4BBDjAImyyXNU56L5VLM+5Ikdn3XcQzZE6XqdGXQpLo0thyEg1AIXSFCIGYTLtwHGfqu67vjIZXJrIBWHISmST/71e3L64vxMNeFgAQPh/vgq+EqXr3c3v96D4ADBYluXoMLhcHkVumFLbCV62VFhXKJKpvRsleQkOpj62JaReIMUtUCBwIuzs8++PC9n3z8UzU1R1b1rJfPn6U5TyGVudTATqEQWGAwq2Z5dXkGAGIwi0ggU2dSLW50ugHqGsVcMcwFbVNzYm/5NOTmDCsom/VWCnswtuKs3FPoAoiN3GCtlKk3mlUjMJBT5UUa1NXNXR+hNW9UPnY418yz4taExydmplOZ1Ypr0kgiEC+a0pjvsqbiUzniWDRzoSAPYS0c43Z9lSyNZU5j0oIoJMzzPKn6MPTEnjVN05gtS3Qnm8oUh5BVb3d30g/danv54hIhPNwecykpJXGCeL/qq3VdTil5UrdOumE9uM+5aLE23VF3z8YDuSMGWa36ftv3q65oejjussJDOo4HEp7m2RrRxErzIIcbusi88G6KIudcigMhhsgUYoiZLHDwiBKtOg64MQzstNvvGZRmTfOkVkSk73vhwFXmyQTyEEU9VPIjsRTTeZrG/T7N6VgjCOH742HO6YvbN2AZVr2zlZJub2/G6TCszubyMM+ZYyaRLg7s6hQ85Vys5DIfJx1WXde7+zzPJHh5dZ1yTof9/v7AhcqVX6yeDZfnbnjYH5BReah1VOULOuNL/8FEhCp6I6pBo+aqalmrF29VyFPF3oVgUDUY1WkKGuOm+knyacWzqt71Vh88tT2ouFWdbQiTwdS17Z0ioQvZHkM2/YlhgbtXPXvdYoUiVZ/BFsEJFrZ5cac6lUEMtKEeWuiLE+yJB2TbJohlSWBphKWGBymcnFRa28YhEhM1g/aaoyCl/p5qcc+tXfHmPAV3Vzdq2I3Xs/60imhVypNN8BS37FYFg/VZdzdjbkGNkNPJWSCik7TEn5y6x8plOaFEEK8bKIswjJcdNudyHMd5nuc0dd3FPM2aix7zZnhesrMPdw/jP//jH6JbMMbanj1u5f7kJb9if//6+Pr49/NozdJSRS/VrKprYApBimMeR7zFlI5jORClYVh/sU9Eibh3bb1LDN12fbE5uyIiN5VOLq8uhrMhaUmW55SEOQYBoJrnae677vnz6/Pt2ZxhPprh/PzsF5/cUIFZbbrYl0zYp2+4NhpVB0ILweq0ori/+5A/EeA09bBwjGHO0+s3bz86fnN73hPz0K+cgYyCqY4iWARG+8NBRN57+VJEri6fvXz/PQb9+K/+Kk/qTs8utxfn6w2t+r5cXK0vn5312yHGCy95EOkRqOTNcLEKvYOSJ1UjeK8mUCVPBqdOETIFonXstn/9o1/85JfjP/uzv/rZx3c2AU6rwG9vbkwtqaHI+DD/f+y9aZMtSXIddtw9Ipe71PKWft09gwFBUhgCMAIgRjKYTMsH/WSZyUBJlJkEEwUZAZoBmgHBGczS6O6Znu5+r15V3SUzI8Ld+SEi76s3GIrfgU6b6a6uukvevBke7sePn7PZ7OIY02xpKvXz1nSfnNZZP4cbA1XRZb0Uq2TPek1ahbR2Iy61zH+RiNomhi4CKYRqZ+Wt3Gp2ZA0Z9bVWoQu9pKo9Uqs412bGZcCeHH6pVogcUFLAxnEIsU7+C5HMS0nZTY3qELyPr1+/+bP/99/x6+Vnv/nyf/jjf/ny5XCz/TZ0PqpWCS0KHGPoOZpU68A6F8Ql51wKKHEgiiGSuptiUXKPtPBinRUpxFxsGfueI+Y8z4dTmuaHB10sQbAZdrsNs5C7paTiFHoxKyLccccuybPDVU2Nci4lF4k+nafXb94ez6fTdFLPN882u/2w5Pn+/u1udzshJ3fnsNvw7fUoNLFw1xFQFAtBObqpm5ozQpCeewlgia+/flBbVMkUEuJmM0rfF2dTOBFHhquXuVkdZi0ziqCjLkbcvb0P7NwLIptXgVqFlmLLKT1++598OHb3d5+f7++ODBV2BJAXxbTMSOURzNKDGYpsxYtbP47Sx9BHzeXD3/jW7/7Rv7j5eH96vPvs6x+jS9KRTapQKdKh3zAV9pJMF0VGz0H6GLmz4IssmkxLKSkTJDDHTkikk+6ItcNmQE0ojSpzcJ0ow4oeMaqMikMNpRS4myvcq/Q5EYOrWw/5k1yBLmunZReAg6v0M54QaahhTO/i1brknmBYgIOY/JL5eIu/TXzG3Z1bWFOzdaqwBrHGn/LWGazTZDULbS8CgMBECoN5K0gvf4nVDg4r2cXXimyd96sDXF0tv4WDcCDAnSyVVAEsYhALoK3p3CIRVQaT+xMVvcZ2cRZ5F8DXa8rEl5hTSVlrNvhezHn3jFbm1qQTa+O1guHtqA9mZndUF7P2jtzSWnc4vWvjtmtbJSzeC36/EgndqrgbUwjiQCnFHQ1kbTXGSvl1tPJhPdN29it6U9Vm19D85CarhgRq6xVYs/GWyNOTz/vrZyt/DQPLV8CRmVcAiyo/qGJD6+pBKUVELgAW1tOrjKaqJ7tSuJ9cIqtOHk8Q4rV688pXYu/7nplLKc5WeSv1/7VEK1lZTESEK5ZUS596E5lWuoyh73oWyqU0pMvc4cLS6Nl1KC4QG3gVo68S/u329wtmSUQMpnUpU3OlEfYaMmD85DalCwLt8Gor60oe3FVb1WJVVU9h6kVNq0IXwYOTFy9J07TkXJ3mcT6f1JLz0FEons2UBSLCIg5Vt8ASOHShEwnSs6tpyTqX4+kU9oOlZc55Ok9lKQAsixrK4g9LubkyUxChG2Oy/MXXv7gZX+yub1599PL0ekldpoDqp+IsgAvBvVS+p2vVsl/jZVU6q9rMXjFJsF1WHZM6dcwhCCyrgrC9GjZXfTfEw8MUNywCYhRgf7Vf5oVFZppL0jozVbRUkqEVdW3ueSBI9ZkDWaVsmlPNBFdiRbWiA1mr0hVWnMSdKyHKicDQYjyMIxeGetCiojS4CLszDG5eSr35V+B4DfE1LqtqlX9vGWhj/K81fHunNllIjZPubsQGTVadKPvYiRJmVYUvgLlQQKIy4/68HI/L5qZ7/q1n424TPC+H++WciNB1UVimKVnWGYua1snK0FHSQgRmLYAHZJvvHl8LnVzj5mrkGE/35/v7O12AgGEzhiFIIJeiCU5GjG4IoWM4z5Mej3OaZ4cgkvQ+Dpvd1W67H4n9dDqellNxDCOGsVMvOZfiqQW1ejc0+1lNi6qp5pyLMSObns4q0W5v9yJxOs7zNA/9uN/GsT+nPMUICSC3ktVy7kLnblpK2w3dzueTm4sEK55T7obQ9R2H0HVdLQmIiIJMaVLXrJmE07IMm85hIOuGIAFff/3l3Zs3LHjx8iWJADxPC4mUXBR+fjyVvCgRaYEhxI5DKFZy0cERQjycH6dpmuaFCj+eznPOHLuc+PXbhxrzbKVnOtXR7nVHoYarNsaww82tWCnqyXvpnOCUbeULwKmO4wMeIcwCaiRhoHKn3czgCKFCp00bXsAG0kt4a5DNutV55QcRCbMEs+VCErxsunSxHVkLJRFh52KFnOHGIIE0E4TWBGuJ1pofrc7iFeavMFXrZjHqYH9dLr7+CWhJGDWKkxOiCBG5VR5apcyv6ZHUMfg2QF83FwBqWlVO3rXOqA3TrX3C9zbBC/C3xrf2GAc1Shu1BgqzeO0fUk0GWwC4JIG123HhZTZMj9lX+cJGlHKoqrup6rLMRZVAQXh2gsc0p6t918mu766m0+v/+Nd/hw5mjXu+7tuXl//PHZVC8v/7kG+Ob45/qIe3hnANZYzWTHZTU5Yg3HIaff32y6/ffvXqGY9hDwqaUxaFxZr8daHf755dXz3rw+jGHGTsu41sp2U+zmdzG8cO6M+nU2Cap5Mbnj97eXvz7PWbxxqRdrs9BOSggnVggtxRB67dVnaqW+tJVO+NGv6qfOKqZqL+pFWAlfRe+9cSmVkNX755yJPGFz2xNKukEMzZCDHEvutMyzSdX9/dV57CZvMsI5yn6Se/+EU6m2nY3t/tN8MvP/niZo+PPv7o429/eH2z3fZdJ7jZ77bXVxFO6AsIZoEMSKV2sQFIlNAfiyUS6a/Y8s+/ePs//y//6/f/Fm/PeHa1yZ5Pd7Z/dj0f0mmat5u9QHWZy+KxF4Igv+OSwomr4Ze3gY51Ch3WxBVb4PZWNzlArWRfWzIrKwr/BQzL2p688imIiVZqyFqK1orm0qBphQM7iLAWikbNinttLtTdwOlCha17g69ZaaQ6r+FUzE8LItQdxYrEsN1tQfLwOP/J//1nf/Hn+Ort6z/+3u9973d/e+x30/m+CwMFlUBGWqDZ1dz6rnMnYQE4q6p7MVdPmVLyKdniYkL9vd5z6PqAGKNa3g6BmGFlDHE7jMfT8WF+pMjEYdxsUa22PcPZvGOhyoxfLOec4C4cajkPFzhyzofHx7uHh/Nchg3O5/Nm11fmOZWyiXGMnSqz5+urTddHZiaBepqmWYIXy1lLLiaBu64L0kUKErqun0qxaZ7mpYQYCeLoCOJqVbiKQaTBs1qxlHJZsmfyLN5LOs8xIObAnSj5tGQrxqrH5aCn4/Wz5247M53smGY3OHUu7Et+PJ/uMYA5ShCCm1KGMmCSHTbn+b/5r7/34bdf9dt49/r1V3ef/ejTT25exFffugmdnO/O5j2XENQtKWb3mUQphr6PY5BgURmY7Fy00p/UKjmC3CtTyyqcUn39CAbStWF2KfWZSARB3E0NpcBTRpXvJFRlIglcRThXtIhwyYUaVP4UnXryx7WkJ//VZIKeoFfwhiW3ZHJlvrb2/QUHa1JeBKKWXVVYyC84yarQ1WIdk3oVbLKGOMCpwgOOJ3wo4bBSd+p6gzdhJYdAGmwVuQskbfJuza/VvPJDHM6V7+KmlYqANc1bkSWSOoq5Amd1bum94HKBtt8Rg9YU+/0ItIaoJzZAT+jytWJtIuvtC7hks5exKEfNfxtbqkq0r1GG1rEBuuB49T/W2NiqWtRphib5f6l7ARB+xRNvxdnW3kH9MqXloxdDP36Se/rlqevZt33ZHCv36v1H/hoM69czsEQkhADUfPrSr2hv5BVPRT2hppXbsLj6/bei3t6dLK0zDmuhZi1ct7pIRIjIVhMtrqOAREWTV/u+ioUantw1tSyu7CdnbqmJajGrXIABIG6eDHWu3ZnZSRsSQQSuVRM30ZB6sgKg2toRqJpXMbMkK75aMda3rDovrZ2OtVC/XPJL/dMGO+rCLARREMFUXb2oVgysuJHO6kZlyTlbtSaTAHUkzVGrHCLFLnaRu9ixhLSkpFlYCMQQcbHsZVHNysaRu3SeKre2l36J25RLXpAtcfCr7aaLG3FSnat80OPpnqkbx93mZty86FPO6gXq0EZ+tDbs6Vw5hFWr7tIZbNGk3ght93aDGzODgogzBwIyAO7w8sOrfhtf37+BIheLI1Pwop6WVEfXtLipQskNWlRcBCFKJ9GJ3NXqrGvd8U3NShWfbjdrnaZ2d3YGmN2V0LgcTABZq6Krur5SycEDgSpm1ViFqq6O6hZQGmfTyOrAWq20yZ25tIIcawh/Ik/xdGNp5HNb0XsQSfXUoeiMZDiDSVglLwkETSU4KEAT5kO6++oQTosMQWS8uQ33bx54JV6CYRmLFgj6Dcaxn5Y5BIojF7Jugz5sT8f0eHf0IkO32W5vt1fbfuhzKikt8zLPhwMTSafdQCGi2JKXMg7juB1Yyvk85dnAih480Oa2v32+CzEcz8fD9Pa4eBcwjl2/7ZmdC3ddb1ZUlX3dVSoCYZ5zTos6EAmqviSU5HDOSe/fHlPK/fONUIyhE/auF2Y3z4B1PfVdB5S8wA2lKJBSSqfTGUSWVLVstvub2+cxdqEZEMqwGbu+u7q5rpPB2+Nuvpvipmei7dX29tn1dj/+7JNPp3SWLux3m1LKlMv9/SElnfMC5lTFHd3EfT/042aj7lZK6GI/DudlmtOy5FTcoDanXAzg8Hg8//Vf/xBdnYNvOIg7qrZ4ZT8xt1nXSi5kkJs14+TSaFVEwlyfW1Gbd0lG7W0Is1PlRrprA39CYHGq4pLkVGWw/P1NwAEzVzR+HXHlkpKZubyjN1+6Rms8f7K3EAmLSf1g5uZBpO6G5L4iM2vUXpMIf2+ar73me8qd3m5qr6EEBkABInHSACJr2qlEK0jaCOrELMSoKB4qLRfupXZ6WjdHpKJX66dbY/h7H5basAfWzW/932qYTSR1TB/rXAnglQnfmpeXB9LatUHrnRCxBCM3d5hBNReoqqszCOaReLPZuJnmLBSsePD+9uajyJvHu3k+ObBOUrdsQ9pFbO/xZH6wHbyWSfyruek3xzfHP6rDVyjLgaYxolV9N4qkq/xX3/+rf/rd25f//e9wiEHGeVlKcorMEAKC9Nvx+mr/LPB2ScVWcddcODIzYxzHcRwPj3d9jMfj48PDw8uPPnpx+8HxsAzdtuu6rgvbDoWC5aIGhYuDVoGOdbMwc5KVU1DJC5fMvsIf8Orivf6uJrVtFoGEubaW8wQvVfWL7h8fJIpEVEHDGLjrO0u80Hma7PPPX4cO+6uXi9PDw8MvvjixYBiuysm+vrvTCaczvn746kc/u0NADPTsuv+Xv/Od87fy7biZu9xzuOo3DHVRMFc9E0JA6Ie4Cbx5PE2ffv6TP//LH/zkJ5gWDMDhbomRtpuhjxtliuymzZwppyxTJbtKc95tEE+V7HSqDoG+xlpb/e3X+P2k3/KeurC/X13+Zw9aLyoujY/6n0+f/Y7YR87V6BZkQmQktFZoeBKOn8JYkVlbe93XvcbnZVETIoaLBMKCTACjH3rzeHicVFUgN5t9UfvLH3x2f5hTwff+8F/885vff8AbR07lfJreKo5Gap7T8UTE47AR6UKM7iQhJE4pL0auVAqlIPjbL36yjzfbbvN8vOZML3c3DLDb1XaTcTs/zCIBgY2seClWOmEK0Fym5Rh7nkpZ0nkuedEEgsToSszRKxKnupQ0p5IKthHTPOWylyD7/VWZdBz7rtum5Jps6IUFoeuWMp/maS6ZAzm8GEpBLS6dWc3NymZzNU1TyXOxXLyQBzMtJWkxgCT0OWuaUs7F1DwjwaGZdPFRPCNncCnSm7MVh1th2Gk5evaeex7s6mU4TOGLrxNOAME7hA7aARNMc0oZBSDUflI6l+45brbjb//OfxV6+erNl59+8ck5PSwnvC5Z/PTqW5vd/jo9LOLCi+NsPjktHCTuN1dd7EHIZRaH5lJWu0GtahFMCkWH5vBgDRslI7Z3A2qtSiYnYRKh1Vwwm1U09h35iNjrH63dm45mQLByZxqDpoIdZgaCXQghv7YV9t7KWFOpdR0AcOc6Z9A49tzsh2BV1o/dawbVkig1JawTUQSymmpVmSxrap/wBpcQVmkMIiBrQZtcaJH+AolRoBC62EkIgZiq55e5q2mpI2YX8Jvgzk0LidwZ3F7RKmxG7tqEJMCtNb2GofWSEEBrNEZj2pKTr3Y+Ty8g3iXH3pC3tcZekYbW9EYrAAAAinU8vsZDpnfv/Q55bK+G1a2CVu6+mjVuDi5RrhYIVk/e6xQhAVURkLDODa7RrBUE7We6XAeqYktt7rOK5V6cj9rXsc7P+btptwsw52vO/KuX6tcwsCp4FEJw95yzmTUyFGrZv1YLDhGpDCxbB0WFGF493q2VBmoNdiOvH7r6YlV/j/qFczXcA6lrcXX1shRSMlRZlebHirrknDSYo/IgrXabZJ12r8bwxCwiNRUoRWsH/nI71fKuSodU4Gwl44AIXB1QzZmJq8YwV1aCeB145EZPA1ehAmqjsQ4YtBZZtahqPX42IREuxDW2qGqtU5nb11qhn6I+dKMYK8JES87FCeYIAcyQEEIM6h6CEKQLHVFQdkpaihYg2dlU8ymVlAPCftxu9mNKhyhj14fi1HGPMMYQzQqQgnT3d6fNwBL6ZZlCTzFuTJev7r6Q0n34G8+Oh6OdNSdlY+EoCF5cszOFWn5VALxKirkXd2U31K5VRNM7MwIzSaAoLl4sa9Dtddjd9h//1quF9Kc//FHYwgxdFylQOs7H6ZRTyalosTocTuA+RqmXQYIFR3bPZmqqWtU3VbXk4goowVY/WyN2zyWTOGithSvKturBAa5uDDncP0bpIkcly1SsLHBwCR0LHFTYrdJUneBry8K9BmJ5Ug9WLMCpyfDU8cVKCiOCAcZgWwEsJ6YAjhyjic+GMxDcl+JzoSAGD13HxuzFJ7v/8oT+NN5ur19cb/a70+EBIFMjRreVCjkCEJZu22Usfd/FQQznMHQxBEw5GdKsp3TI2bs4jJvd7mqvRY/HwzwfEebd1bbrAomXXMppSTgPEq+eayIJ0wAAIABJREFUjwi7h82k6sT2/NXV9c1+GOR8Pj6e75z96jr0Q4ADZBxCYM8pB4Z4dJAhV4IaGc3LFEQ2G3ZXER/HcRx8uwlpysfj+XhMWvDIx7lfUk7M6tb3vRBzYArRh07I3DadG8UYU0pffv324X6+ue4/+uij7XZ7e/tsu9mpUSlFtcCUiYXo4XiMIcSuu37+LGm5fiae89XVRgJP8/TjH//t7vqZmqvpuBmj8/FwepyXwzlJBCJtxx5GfZAPP3z1watXKClbfvb85vbFszdvv1LL8zyfpmQLNp0Sdwb+9NOf/8mf/O/YwLC6bxrYm4Q2CwUJEHL1aqcNByi4Uc3OGbRMmTLX8O7urjBzphBChCOlhKxgiQ5mqy3m1n5HRch93Tub1yszXfZUMwMTvPlMVisWIy9VhnNNy90vdClfd1AAMLecVah2MSIzrGgpOg5D26fN61whUAhgGKFqaYJ8zZjQtjomc2KsE5SwOqwDZoaQEZxs3dzlaQu9fRY1REZtokntiLuREjGTuMOtuMIrFMZeASyidzgX1stST7zu4c2ltJR6lk3ivSUrVhvqwuSVr9gETgPcW1HZWFz0lBNaLypzVbsU89I2yrVFFEIQltjF7fVtSee8TJ2MTtLL/mbz6u6r+Qd/9ZP5XNZEpfYNwkrvfrfTvXe0b51W3sY3xzfHP7KjLvHVE5vXOotq5kdUM0YiplH+9f/xJzfP7b/9438WAsbhKs+zO4SiQAQUuB/7/Xa8hseUjyUnn536kHNW1ZJz38Xb/fZvDscudA9v737+yWff/vg3P/zgg7u7uwp3lTJ3MXh1OnSYepUaQeX7o3V/qXWM0WgLRG3cpnpr1doCzrU2qFkwm3AQghExcy65VoiM4MTG/Pr+fr/fbuNAwtUvK5I40UZGDvnxXMbNdp7SNL95c3cHlqvr57cvXp6n+auf/d3t9tZKyuJJS0lJGG9P8+e//P4Ht9/fd9iFftsN3/no4+/+1rc+vN6+3DyjGMzB6EK3n4z/7pev/7f/69//m3/7b5Ph9//wtyGbv/z+J198ct9ddR99/IFmWuQsrMtpQra4jUWX4+MkEgPF1v5RMzU3q0YdlbGMla1A78J4+/e7EpKsTn3XIKyX1sXlEettUnuQrfUsNXS/Twl4v0hvnRfzS2ithRyvhU+V1zcIvO1/T6tbIgpAqcbCqmoOLseDd31V9un6vvq/M1GAx2UyMxeOJPz1wzIf8k9/8fCnf/7ZD374o//xv/tXf/y9P/ijP/i9yCE5jjkZUr+Bazmc3sCRdDsOG6PgzMnL8Xw+LIdCyymfDvN9AX76k6+fXb286W6+ffVq4/HF5ipwHCReb69N6FFPYdsXUZBnS7POIUjoMKd0OB5fvfo4Zo4aLFvJEiQwF1JS56IolnLOWpQZfY/tdjNN59P5vNl1V1dXb053ZM7kfR+3u/G8LEiZA5RcsrmBxbX2xRXZMWdFnudzWbL23TYXcBgDExFl1bLoPJ3TYtpqejGt9vMeGJEgIHGIsVGvlkp2JsR+GHppggXJeJDXxy8oo9+M3/3et75zyl9++ebxPqVJvXBvXbmekUUTuSJEubm6efXig3/2T39rv9sV159//vkPf/wjYo99SFowQwvuvzjv4vDhzav75QtTt5Mv9+l8nlGEOimu0hcQmOV6ezX2w+N8Ps2zFo0xMNhSycXjJlCubX0jMDnJenM2EhA3MVAnBAnMbMLqJoEyLcRVCdVgZG0omi8MjGrWrNSGXImJmnocNOfaaXe6oBwA3vUd6Ulb7AlBsf7CnCvVof4NxEC1QmjK045GdQDX2FwplgByg9YutKCK3zjc15ZcZQzQCrvU9VtZj6Dqnlb96gjMIdSZY69WQ4rcpF+0oXmoqkTCbGTevIyqGDsYzu+oU27w99VElWoOjjoysDJ/sA7UrXSf1hnVX5Oqrb3UC0JYo89F9OsdbrhGrycovay72oVVUsPXe9/X2u1tEFh9QVOnxixqQAeYlaCulWMEkeK5bUNCAHHV5uKGmb538nWLugyJSrMHIILrBSIid4dUCUhae93V8MjgXm/VqssE+vtX6tcBWBfc6/LPeimfFjAXNhZdmEf1xmIiAzObA6p+uRAgZ69jflRHS7SNMtRzVdPaJ69vV0rxVjap0VNmQLUgKfVKNWJH7XlwHT3lnrqKE6tpKcVM64dn5hgitW2sYrkws2prwsyXHvw7Xpw5h9a2cndeV3U9+DKEQ4Q681I5ErQO57eUoxkv1EVGDerylU5HqBaRAjDGYewpLsvi7mZa1E0BAQPCIZAwY5kTE2k2EWejNBU4XEtO6sWwAAVOZbHCPnWbGF0ouWUrSwlhc3V1Y6aHx7v5NE/nw/PbzX7fG1G36cc4TI/p4fGuw+Z293y8Dotrym7FRJzIzKFZiAOISR3ehIubk72DwG7q5jSQmRsZhAFCx9yxcSklgb3bh2cf3myuh+V0IufYR1WLQ1fXuEhwIWMyKkTGBKEQOLALqZesnsyLCaQNb1ckyJycV/vPNnFKRmoOcxI4Q5oIGcOIGAGhca+qt+xiJRQEhniT51eYFqtcZuHixkLs7NaeVHsg7Y5q+chKO7cadbjFsxZ+VvnnxkchwFGqFL0IBdUKgTqyI0NEAGEVV1usIAIDUWRSyoux6NCPRK5uzBy77mrXn8+nlHNtm3SxiyEwU9/tQsBpSimXzRg7wXnKj8cj4zjIuR82m2G8urm67cZuSCGuAoGw7S6WUsaNbMZuGK+ubzZabCl5fzN2g6jnuUzmadiFcRxjDMu8eFMKgmrti4gzCZl50aIqZZmVB+67IDF0Xdjv9+OGuljO5/OyOMBF7XSu7gILoOZuHmNkZwcnDUKEvutFYtd1MfYvXwj89Xa72Wy3wzCmJRU9lGLzeZqXueSsZmReSt5tts+fPxMJYRhvr29crRvHx9PpeDp//stPPubIEpacu64f+s3+avd4WIAKlgO9M3y76V++eHF7e/3w9s4zj5tx2I7Hz08SJRUzo6UUCX0/bkX60zn/4vN7RFBt3LjD0PpLjZFWM9wWRKlqTRrIakNIdCl1CyS67JMOgHml6rrCrBiIvXp/sEiFlOY0eds1ml3x05hua0em3by1cS/sTKrWrPRWTRbVd3vHu0zeUazUDLyRUuFoYgwVmq2Jhq8GNO9Sj7ZxVB8VIWapfRate0ndts1JVhcTr7zPVe/RUVe3EDvZ+qIAnIVZuJnUelMnXfdqv5y5N57mRb3yvQ9Il8YRrRNHdZNgIYJV7a2mLEDrzkjrJW7vRpe3vfybVtdrujTmiUDmLkx6eXfm2MWYYt/zcnwwzUKyHa7gfSf7r15PP/qbT6ZTaSh544JTyyRdHb7aab9LU4gEzk70VAzhm+Ob4x/2Uddla6WvlYRfUjMQQKqlCjKAHEZuHgK//vTxzes7EBN1fXe1GZdpORELgRRgcCeDcEzZ1CwXLWbwYmalFC3ah1iyujoC8pKObx/LvNxs9pt+SEMpoGWeKm5VjWVXBSchUq62Yhd9hoalr2k31jx/RV8ausUkzJdAtOIz64sQCnTRZKSpQKHqGqr+EgqZB3BSut7sND88299GCg/H83Iulnnsr6KMeT6fT1yWM4B+DP3YeXCWMozy7GojsCkv7JTStDue3hzuh852/d4hIfTMW6PNJz//+Q8/+/KTT98ezuDQvX57Kjpvd8PVi66L4Wq/yak8fm1mBQbueLPribCkJQgvrmTsqlVfGAqDB16jqAMXJtr6Pa87ydNij57sBUAjm+ASvp2ePrgWO++OtvWtfYgnBAG6/ILBtYtBxLXjf6kxiahu/5WiVUeBagy3Wt02koLC3AqSGxFEjEnBQhyIeDknEI2bset6M9vdXu93CXoq6XxY7C/+vx/97U8/e/Hq1bPbTdcJ930pZxUzLzKYmxnPGUzcs8SBRh1tQQKFyBRUi+avHw9JzbalhzwLV84uCDF0wZbNMEaJHCVRnm3Otix5HvoYiRV5SidQkUgbHjrtME/n89mMihlXVRf3osUIzIidEHNRWxbd7gIoEGRJBZRjF7quH4ahmCpKDDJuBhcrNhVFLuj6uKSsipz0cEzns282M3GIXQgxMrumGTBmZ0JWmLlwiUFaC9DBzDFK17EwlKKWynyPIl0/jABKSmqZBVOZvYC7cNJ7HuJHv3nz8Xd46HZjvxMZf/ofPyUE8hh56Lqhj70X++yLn0+nabvZfPLZp4fT4Te+/Rvq5fF0TBP6Lbqwh27PD+ozabFy0HQo6ehkarLkg3axi6NcP7vab3bUc78ccXirqRBIc0HgXHIYxRmmikJO3izmxAEiLwVeDXNAToEoEnOI6gJIYHCTG/BchX191d5D475c7voWRy4iosjFQahivuA13Wktul8Ju5fw22bLKKxBiQBow9y4KkYxSaPqtyfWhoJTXdQIVX24QUXeRBwqHWB9Tp2x+tWTsH7T1/qLRSpGUqmy7moOd6vKEuYKN6vi4ZA6uVFHDRvtq746iZOC6uAeV9CD6nhyGx5rcfeCUF8+NtWKqj1gZXO+R/zHJbe//LWCIHUQjFpL+Uncr89obVECHEJ17qHBZO1P7whb9RlET9Cg2oZtiS4qFanK4tfSvrrSkxDaMKJ7NRJZmcEAWN79jLrlEnjlcLXNi1HBU1+hwHodoE6og8RkVg2627W4nHNDh/4eghXe7ysAgJmpatMTfnpcYvuTu7OUglUAiwB3c+PYBSFRM1jTZm+XDSsRkd7hprVGUi3VZ5OotTHqmCjzSp+iSngkEAUKgNfhT2IiBgdx8qy5C13oQs455+zwhkO7aQtbMWui+rRAWA26SEgk1Puv0hrJrOr1EJiZzD2nHPuoqGq5VUQOtTFDxI4mYk+tZ7bOcWCtx9S5WfFe1hcRODBBiALXecVlSmYla8mlgGgcumGM0zITl8hBKETpjvkMoqR57Lux2x59WVKy2TwbmHsOHtzU5tM0H21z1dlVGXcY4nD0nObFckklLfMCS5pwfFhgun0xRA4527TMBUVoOaT7YR9MS3H0JcA9TwmFiYlDcKclK4oGMEIwsGVvRWxl4xMMToFJ2N1d1IIqUthKGGVzsxlvN5NN53Tevdw8Pj6GTWQhc48dCQetk9BmrubORl6KsrnlUk7m2dhI63RoVdlkglNgSZXzumYrzVQVzZ2BmNkZCnEhYkehKtdWv5gAR8U0V2cxggSWGJjZS3F2BjHYQaWYq5FDSJip3lcr12KtHVsmxURc1cHq/HQjwxKDXRg5ZWcIa9/3TFVIu6p5FzcECUJSVKmwUyMxlbnkc2LBdrOdl5OwxCgc5ObZDTG6MquX08NZIoQQQycUNOfTcYLH5y+uYXz39enop7LgfD6f5/O82TwLt5uOzDSXArb9frvdbtwtpUREpuqs/RiZOWs8zct5mVNa5rRQcAlk0FSMK1qtbuoMdjcm6WJHVZ3ONKWZCcuSzcouboZx0w09kaa0lOKx6xx6PM4xUFFP2UpxpxnksSPXdDUquxOEXPrYh9DF0JfMr14JEeesXfTT+VhF0NNSFUtLKepmX375pg/jzc1hv9+lNF9dvdjuxmHo3rx588Mf/fhwwP3DfQhdN/RdjJvd8PG3XoFMflkOx6WYQ5d+7F48v3716vl2O05TKB6L6eF4fPP27vrmJsRI1Kfl3PejQ8yFKAYJlbTj5tX6oG4LVHselt3FzU3r3spcXVeVSEFGEgK5WIMTzSvV2kphZiYObDXtXce2n3R8qLKgVumoeu9zFYUCqgJ6dYBYw3tgDuJERQuH2pZruodcZWgvGlgNGSEiGLTU9jQ7B1KipJnXNjatc4gVWXN3qBGhhoXqAMtCEgO8+jUn5lDTFXhTuHMzdWdiNcAVwrBq5UBcNUy9aRGDQSIcxExZiDlY8bqVEDGLrYQ0rHp2vP5TL7s5ABGp3lLtYrYeB1fjRcEqUAO4W67mtHW5N3saI9A7X8LWT6t0yzU/bKh73c1NgmSCFq1etjHEGtzSvMCUKQTpyUIfd493hx/8zY/zxCBw7WqauJEatZFCd2JHCzRV/GVttFRTs28sCL85/qEfbemuPNILJI0V1aU2ZkIKiDAxO5mIUAAFIEIVp+NyO44ZXddtUy5ROgfUjUkYIS92OB6WklQ1L7mcXaIcHg+mmpB++XjoQg91Vz8+Hn752eff+Y3vTNP5F19++dXbt28eHoMQwYjBHccYWcLas6ZLYuymay3Q8s36odyz41KnVOBEiKmSbtWsDgqUUiBwAIpzOvZnGFnoQQHqOZCraRc6MusQTqn0/WYM/Rj7dLbHu0cGlQW7zS6dyv3beyZ36rMWdo4SSIhiUfHs1HVSsvX7vaWU4eeSDkt6fTxcRe65t5Kn/PbP/uI//Pv/8OOf/fKLYXutHqbFYh9jzx98eMPg0JnDpS84FDDGUcaNOCjrPC8nzQwLeOKNi0YZQJsiXL90e1e1tJ8udm1PWxkXaKp1ym3lIbSq+7KLrp2R1j0HKj+3FitUuVG1OmQmby0KA/jdhFQD0sgdSgBHAlBKdiDE4HBaWYFe6bQOOEpVEA2qZQHEkoIcaghhOacyl9jFSRcri5al78Jhyecvvrw/4bv/5v/5nd/9ze/+9se3V1c5Taf5relJOIfILOaU1Q0lZ5Rzme8fD6dlzq7Fg4vEDWZdMsrrx7tC+edf/vLl9YsYZJ5SGENOOXTdMMg8z4/TQZiDUEcMNrCdp4M6YtdH5kwWYgwhF/MQQuy6NJ3BFGPox+7qapc9xzAus6ri/u7weFhgqevKZmcSexBIiMB937Fi2MfDgYvp+ZzHcX93d3TjZbF58mWGWgniXXYzcMA0LfOcybEZQ98hLUUCj+MgEkrRnJcgFCO7l1wW9QAXpmBK07mAcj90ABthSTNHOIO6rGwhct+FwN3t9dV+c5Mzfnfzz8/HMp2KF/FCp8dpPk13X7/94utfOpkVHkJ/d/+QNVOMECwz4s2m664e7vPhYZmX+Xg/zYeiE1BcuTjKoUz9LgSPXKjf9WB4MWdiJjaOXQAgJgaz4pbdiys74CLERHB2LyRrHhKlJlrwamyDfhyIzYpnymVR89VIzVC0XDg/tQqnZsz2BDioKBJ764uizSM6UH3wHLjog7ebubJF6FdyjloXXzqqVNktF8SnhUAnZsrFZAWwfAVruNpVv8OVwasu6rqI3eHD0F28rN3hMDP1oqq1zwetix+GSkZF/diMOr8sTMRW4PBWO7Y+I6qvPDlBGgvB3NbFa61d/TQMVezD4ZXQ0NT0uAavlRJFNV7VLma9OAYjJ24KFF5pwlg3irUb3s6JeGWz1RfVdv3rFlgnKxlN/r9FQUaV1iCpVK8W2pjEyepwgTuKasMu3gGeuGB1LGsfl5qGT92V6mm07JOYWeAopertrEV2bU+7ugsAZgKz2bs43BA20Jq34xK/fw0DC0AFsN4L/b/uuKi8E1GIQVVb/s3MTCGEUlAVrFALL1pvzIq9XVBBBtBoeUwC1MLKGwzpddDVjZ2FiNnc2meu4mTFyNUZZpaR69gjMXcxwtuyJCIJgYPkcmZpk4NoOANRtQyo3wdbpWZ6pY7BTVVhqqWT6OvgSkVtuWKx/B6auV4dqqozwgJGAHMdJTM42tQIEQlHESZhI3Pz03zy5G6lmEvk2Muw7Te78Xg6zaeqwSXzIQnFCmrETXd79ez116/nZUYCossYoMglqZo4PdylTVGyuL3ZbIZtnk7n+ZiWWdPUD72mZTkrQeM2OruWUjSHECSIe9k9G6+vr/Xsx/vT8e1SZkVQWMie4YyIELs+dGZGZiKju7llIiAydSAoMcHUU3HLpkCv+w+v9y/Gbs+P8/HN6S50w2Yz5pKLl6JKTP04XO69oopsZgoryA4FEjADBQqEAINZMmLnIMKVIAqu5EVam1+X9UxgJwETsXAkkFqud2Cd5un215bdVN1ViDwQBY4IEphAHDlSFGLNau5EEBF2EIQZubRgQMwsdRK15ciOthirow2YyLgy+yggBBLVUkrOKXGoEqFaCilxQIwRBlev02fkTM5WrCxaUbyuD6fFWOI4DKpW5gLDEMecU8rTZtw9u77uh2helMw3w5ISu8TYPX8epukUQvDBVXXS8xdfTcweN9jtsN12wxiLRhYmAbMbNM9nVRMRDnxe7lliKbqkUgqYMocgqzeoqueS0pw8ucQQRbrdfrfZw0kkfH33FTOxkIOWJbOcRVzEHEKC2PddbwYsSefZ1IHZiVMoMLXbDVlJZgT0Q09dHMZhJzyklKZp+uVXXwKvLwp6zEIiUSREAtHjz74WOv3iq9NuCxBeffSbV9fPx+2e78+ffvb18YT+/tj1m4/2O2djtmfPr7a77tnz3Zs3d/O0bHfjOPQvnt2OY1TPYJcg5+Uc+zCM22IaQhdDvL0ZXzx/CWPNzhAYa4LU7R0EhphX2N0I5tVwHW7OFKs3HxmTKSlBLcTAFsxbEDR3N/JiTu7kJI3+KWvaYQSvnFNb3WnXxKLBGCzE1DbSqinYtqWaRTBVHUNVehLNWASrI+3ll1S7XgQjq7/jQBRCKasy5KVpUj2jYHWCreU85G2Hq1rKdfnWmQ0nFyJFmzcHUYW6CAo0wlajvnNZM5C23KhKfrm7MoQueiN1r0aT5oLTqvVJIEaNaesjmRmOYoUuRLcKT1V0vPqyV/lQd64lYlXytTpTvvYvWsOpft56aSvQ37o1tnbSmpnpmoukZZnnuTcyVbgLy+Hx8O1v/0GgcT766RfoJDLlVvaQgYWrymNDr9as6AkdY82o/Jspwm+Of4wHtZYurcJ5lSrTd3WdqbmSUEAgACPO0/KD7//ot/6nP0Z/zaalzyzMoEgUmE19Oi+Hx5MLkpZlmbOquuWcQEiWc8owhBDFA6ud3t599EffU0vzefr8F5/1ws9vd/AjUem67dBtl1nPp6kGbzgTtEYmuvQMWrlAtSJs67l2CqtHRF3kBAoc+y7GMJ9n9SKCQihacsm1plFXEGIUDths+0GCLLTf7A6PxxfPnpP74e789vXDZr+93m/d7Xw4Pzy8zRn97kqTU2AjgptUin1wBO63fb/t0KHfxgIqCLPyfrtzbF7fnf72pz//13/6f75+QCLZ3USRTs01LUuah76PIks+LnMOg2+uqWTf7Yb91TblMk28eAFJw3hqCgWg2bUDF14uLiH8vWMtG6lpthBVSQHg0vJxWu+OX33uSta7FGuXgqrdU7WiWa2kUCWDgdUg19t0Db1jQTfecX22g6z58q5fMQAECcWLG8gY4AA3ZjiZO4qZZTPNE4MZbCCbEvqA3Q4f3PZ/+u/+/Kc//+nD8Xt/+K/+ydX1/nB8EwhdzcwYp+mQsvXDBiSpeJ7nu6/v5qJx2PBArz74FhM2vMHBP//i55zC73/39z764EMKsWg2M1e14ssyneYTw4jKNg5D6DiieFb17MVcSimhi+M4hGHYbLfjOOayhCib7RAH2Ww3RpjnJZd0/3DSoj/95E3fYbff3SIMW05Fa2GcUlo0jTT0fSdW1HjYbIezns9lOtuygJke7zVG7fqy5MLi6rlkuKLbUeyZg4l0+90GwLIsMYQQRALysiwpn47ab0YOcjrPh3Mad9PN7VU/dGawSpUXUAdip1AKYcmzPeq0nM2k591clrvHx7vXh/u70+nxXIrCEEJw5Rh52PWPx8fk2vWCDPQI4xD6bYj8+vUbK5iOpZyABU0k1QDCUsrn5y93N90HHz+fQ0p5TqrD0I3bkcCxi4e3J4rEHXFhrYKnKK2eJkc10wkAoVieZtSqkyFm3g3B2aWhRVkLvFiVL2j38aqItEK4WO/Vdz+03IaAJhMDVEhkpc4DT7KuC5nmvQVWf7LmdUDkUF+HGZka96oyZLfbAQDMm5e8uTutrHjimrLWU3+X6rQF7yvDpjpIuavDi+VmJiio/PdQZUxr+DDA3dhXRuQlPhBJU0hCbQXXFLnJLsPtctWc7HJK7mg0LrMGeawOShc193dMTwBVN+ly/c1cGg9oRcRWvXNQtUd0ULNH9GINmAIqmuJe3eNaY4TWkPX3g10IlcHRrBLN6yQI3tFYq4JVdbSr4H97AwczeSWSXipuV2+dXTCYK863gluNZ0UASMjVS3aHi1AMAhI1rrrWrlYzbWqK4/VEqpY0/XoR9wYB/j1P3185nl76et+ySJDQLh5z80S/QIZe504vnfOWZNfUv25HIuJwU3VAhE3dXLWK1QUwKBBpVSSRdSEYwIBUjXszVZiHrmt6JfD6cQCoWRtdbDODtWW99mG4dXcuziBWJzDrBkRsLVgAMCKAm7HUapC7ukBdGve8XhmAlKh+yWyo2lBsVtQtuAsbDKqqY9xQpJRnnRctNk1LMf3g1Qd+mM7n5fy4uCPP1vdIeTljPo/z7e2LoCFI9OjqWpbiBlNnCkFojJyn/Hp6m5W763G/7WUIUFq8xLChoVuOqSQ8vp1CohDJjYisIDuZWdpvu9jJaU6TFQgQAXWbE4pDSWNY3KrCX4ihKlJBS7NuILgr2NEBI7oN+u1w9cG4fbZJPj2cjvfHw+32xgMrFKupQTFVVXNnCjG4mloyAktgMzMUMBAhiMKRzY1LZUyagdyk8twcRnBWL7QWj2AnMnIFCChGEGapE0DkMLP9MBQ2zcVQPJpEcgBKTuZGxkrCRExqJCZgV/A6qcMsK8OOeYWyjbymQO5wUzRk1BtzoobAqswFGMwIsQsIqLr+VYFtKYVWxqkQE0lSs5xdi1AVHcwhdiIyn5dFZivOLh1ijPJs/+xmd5XTcpxy6MJ+uAk+adZUipnHIDF2IQgcSylpWgzeRRBB1R4eDqfTRAQJ1HXisOPx8TyBGKHD1c31nJaSFQQJCAEhSNcNgQIhqCqMyqIIEjkwcQwBLBUqvLq+cnctqZRyPk+qOXbU9c1EUriXLqqWnGwpcAcHZHUIEdAvNL0fAAAgAElEQVR1PbuWDAezBHIxo2XR83k5nE73j4cYZLvdShB3qKmpmgFgkZASthvJqmrDlObzbKXIPJlaePXBR2Z/d/8wffjB89iHrOl8fgjd1f566Ibnu6tOlxQlEPEwxGU55TznPPd9FOGienV1Vd9G1QVyffVsHLYl2+kwLVNBxjrJQgEk3PqtBIeh4UyVM1NBElcYoO4FXgzVRGDdkkEEIVrRfEFwh7DAXVXhbl4M3hhFK7uqDgATVyFcWnk4NUOoHTTiICQVrVzbSivsYY1H/CSnqbuhVFWp5o9BHIJAp1RlbNsjnSvvumU89Ye6t9StUFq3gAKjWqQY8eqjzOoOsFFlL1bPPwZTbSpGKM2VeMTC1tYU3M2oUrzYK5XK/fKJ6r7jXjcjJlq5THXXqxnPE6Zx22l89UKsbiPNA8KCRIe1CUomauPkeuktvnuhehusm0JrhbSeVVP4UphXbdicQxhL0epK9vqrT1/84cux25IyErYvr/8Te2+yZEuSXIkdVTVz9ztFxBtzrKpEAdUYBGghQQq5QW+4ogj7Kyjkkqv+hP4B/gSkuegGVpQGSCFaCCFASgNkEY1GYShkFaqysvK9fEMMd3B3M1NVLsz8RmRWFoRrID0XGe+9iBv3+mCmevQM1/vP6YyntTDGL7Ho0aoE9xpoBbA7f0Xx8vXx9fGP5GgwwvKFOwdu3Q3ajB7ZIXj95u3/9u/+8J//V/9MaBDuYhyMskEbC1t9PM0gAZHmfBoTMavbarXZ7++u725WXYwStRQvKhLevnw1BHl6dfnO40frKFrmjn23GaI40NUBORMt+VR12FH9bms1WsOvvLID0FLv7ocJtblzBoQlCAeuczmAJaIocs5zGosmI5hnNVDgnuNq3UfEPOfifhynj548fv32zeF4TBnbQI+fPRnW8fra5gxnlDInzcjZZyhSMR+GvluHIB6s6mvSKe0lPiuI3G05bNPcffLik+/++fffee8XR7yaDof9NDGXEAITjuPtOMY+xs2wJvHQcRzEqdSOoJhmGLWQXQZRVbSgGtPU7HaCW7MEJtyfkfplraxqT9Wa23M/3igEfm7Lz436w/XR7wt6qPqZh3U+mklKs7qmFp7LvAwsG9mkksNE0GwXvW1TS8v3hQ4/cvBKoW6thhDDFeBQGfpFnUicHCHEYKolA+qxeH99m67vfhjievN4/au/+mFcPcnzxF4iBXO/3e9Tzk+7MKw3q1UPxuE46WEOiOT86OpyWPW99jno65/cvHjz5hfm/NwlDit1DxJcNR1nuLEgWx7nUyAP7GY561gKUtasUGdzlcAsIoGJzJkkSNfH+TAfx3G9Wceut9mnSU+nU8ooBuWZunFD5AR1Gsd5zKesab0d1C1lUyMzpFzmyUp2oq7rhrdv7pgYQ08QWGGxrjcrPqfsxu421Hz7nHNJMVA/xBBZOGdFEOtiJGYvSCOIbV4VApuRGRWHK8aUBNCQ+mHFItx5v4ub4fJ//b0/JB3GQzkd8zxDIgeEkousuOTkbrSCFLbjOM1AxPrRxXC1pS7Olo5zEUOdyVGQYBHF5zJzJw7z5MgcqBPTTsJxnwNcLkWLcSSOcHMLamIeHOomyy3f6j2nKMys2XSaYQSrnEvES8k5tWEqOQnYRVWb+XkLgcZ5+FlzEpZOf3lA/N5L1PULtYQvIahYKDO0yOy+YhVevrgHa9pzuOAlAByBm7knVU/oSiVviI4XLc1u9EF92saNRGkaqeldKnu1tn9URwQkocnc1NzOheKyNrRFw2r5TiAEIgoPNGhC7SMsDk/tWSbhGj0BIq5zTPWKKyzmYrVaI/Zm/NU+At0vTn5feLag2vsVh85Rs4uvX3WMPVOOvAFERACLOO5pqj/vqKjSPWQBMjrr1peCHwSmCuycpybmyoyKnhJa3qt7WxBrpMiy2p678Rq+Bl8gU1cA7uxEYSmSFzi0XhF7sHITaov91QwsAFUbeH8qv3z/AYScc9/3zFxUS05EHGIkCcWslGyqzBRFVGsfb6gO8UIizBAzPdPh6rU6I01Nk0jVBpGFHOISg3QhhKCkRFQL8ipfrZtP7KXruqof5ICiyczMVK1JTJyJwvKM0/3DaGa+wIPWyI2OwBwCt8YGQpinsf0kuTATs7Pbea7S9iSqSfYQuJs7mSkyzN2lTv1dYYoCgnew7DkWDkRCYJpsFhEwcSeaLRfNrq9evjH13frSkt7c3NqN51XJOQPI03y58kAdo3SbzhRpmuHORDnnMmJMQAB6sNGqC9fz0TINK95f4zTdBRMC5gnzpF3B0+eXJJZtLlayp/c+eK5j2Vzuvv2d3xzC6vWL1y9/fPPDH7y0tebiZOxmJR1BHsIq9hQslOyaSVG6iz7ZCEaMkMi7R/3V06vNo/UpTxNOidQiwhDfHm9KRhBsL3b9qk/znI7pVu9gYA9d7Jx9tgy4QEiBEIkhHoJLlE5ArmbuRUvOc5rLMHSmADszdGFlMhPcSWGVD1i82ERd4B4xxOym2czycTpU4Jwi4LBSExA5u7uC1Mlr108i4g4zr/iqOzguhlzt7iW3Uiqm2aCJ+sx7rWfcVLPDnA0FTkwcIB3HVYcelIAAVSQ75RnMLFGEWUSITGAGkJlpDiGsN9u+WwlEXTfD7mKgPKfj8ZjG/Ca9vf7pm7dv70bFsye7d957t+Pt7Xhzc/3mbp+fv79jYYmBGMFlWIc059M0ha6P3UXowjyfxvHI4pvtcPXo4tGzYRiPZqXrwpNnj29ubi3nKn4bpHez+XjyuBr62PXrTobtsLXsnm0a0/E4laxZ85TStz/6KGs6WplO85yt79CvaNCoauNYVkPWgpQywCxkcHCLCa6st4gYYxAetsOWSEry2+vjJz/98TiNRLTerLphtd5uDOXuZn93PM5jIuqGYfXmNcqV5oxifBhxGv2TT9/efn790xd/98u//J1+WP/4k7+b9bQ/hNhRPyDlvdpdKllt7ruu5JOqgTqWHPp+c7Hu+25O88c//FgkPH78uIvd/mY83N0MXf9odzXd2svPXp32CQVWITRmhou7e7XVchAkkJMAAeV+73SDZVC2Mpsgo4nSiatTb037JYRwVqUKHGAqpbRWhyh0FWlx1MxlVygiV+smYmIJAdyMEMAsIiw108ljCNU90NTrQl0n12hofiUTEQUx9nNVQIGYKajcp4XD2cnqGKPWPIEVbg1VQUVwrZFTwYHNKl7LzE7FVTXlologQAAYuQs0CJEzC4WYKVVUOrAoO7VqoNKy3NRKNjgWXwOr7l+t33Ope0wXOzyQTKqqP9iYKjcaAJnDybW6/rWzqym35odhABOcwaHN6utGbDU2hNsug4p9wagGv7iXJVmylJxLNnNh6rq+FHW1YdML8O6z9+/ejK9eXuMW13KLM64JJ5Tm2kr3fpoPd+sKnv39E6mvj6+PfySHG3ixPDIzhxNzZHJC0eJm/Sq++Pz1//y/fO9//Jf/0nwg6plisaQo5uRQd7PiT589z6qlvFHddyGkWS8urua5HPYvnn/00dXu6u2rV7679JzT8e7Z1cW7j548Gi734/X//n/8+3m8W8WdULi7Od3uJ1g08ELr9KWHowVs92Vu7kaoLUHrU6h5q6I6DnSRgiQ3m05CFrvgksFWPE/JppI2W4QoFBAi950MQ2D128N4c3M7FWTST1+9vJ11uEDchMtnF93Q97vIPWAYy4EE3TCstxHsq5UPKxyOby3gctX169VuePRk98hZPnlx8/zqO9fH/Bff/at/+3v/9s1Nfv6NXw6r9ZrFiHLOYxqFuRuiZlOYuocQLh5dEocb3Z+mNObbec7jVIQ77gIpuYONYebMiwN0A/bQ+LRfYYocQqgh5uROxCJCWNxDHjTPf9/dsrAMAHdrCqB7pkFNhKr+zIt1slf3aCwJbnX8xE3vX6EGA0yNmvP22QMLANKpZK2ZUAnMQoEo1KqUialKRFwlRurCqoshEuCmuD3o5fYiZf7Xv//d//O73/31f/qNf/E//PffuHj/oD9wO6qmiytKeX883ZzG2+3ucoj9o8tBS5lSSllnG1GcmEvxU9Fx3P/wxWfdbvvoakscLy8vFQmpSCEOBLgiKUUwEOzN9SummLKpcz/s1us153x3PEzzGIJM06yaSskppTSOXT+wRPNwd71/+fIoHU4zTrf5VN7s5rxZrymgOOdixcAcYUyYmKDFj4d5HMlAMa67uA3dyBKFe2LMac6jbrebi0fd3c0+lzIMvTq9eHUdBX3HIQxdFyQSI5Qyf/iNXz0cdL8/RBoDIY84XM9+QV0vq9U2hinlWQLBTKFTGs1omvM4ptXq7rNXDh9REIG+55TdpXQrevJ0t7vc3d3ejePkOw09O2y9u7i8uLS+fPr2xzc312VCsRYzTQpTZuMuxJKzW4LhME8fjz968tGjzePd2I/CFEVYyNU3V9t0LGaTlQIgDj0FMnGH910AoKpd7EvW093oOUEFyYsFdNhs1tfH0ZK6QlUJxIE5m7mbOSPUVpYaT6MVP7Qo+x7ocwEsoE17SNr/z9lYtPCwalXCX/hZf/D/Bti7E5NigVF8Ycju96eKQ1e2SkU1RELlCdlSoRHfJ+jVX08OTdrg6fO/LECOMQLUmWuV62dXiCXWmQSLnS+Inb1VjbZo39oMoTrraaX9E5zYkXPie4EkajyRMNdajRbWGUlweaBidnd4COwNNDwPWyq1v75e0xHUzL4HaDoB6LtQ7VOabA2oibRYiDjLWf/ShQQAM4UzzvF/IGYuasvpWtqOeiFrD1CXLoez3y+ny2uzUIW9qlGGmbdQDAacxcnVCZ6TE4O6GiLFVTpSdKH2EVFoW989Kkeoqd5fzcD60tG+52c/shMq06pGtzSIDqpqudST3CIliRbcrfoLc+i7UkrO+cF4o55EoyVP0UzvkWCHsiGrL6paN68rf2VjSZQQQoyxfn+NRxQRVebFossIFO3cqHgTraL6bANwBhmByAMgzBLqYIXgIEapCHcDzsTrfXUmX7azjRYLSnRmfzvlVBrli1G5iXW+RhW8aFwtSnNC4NiJt9cBCo53p2G13q0v0fl4l46nQ0aBI8TYSafJh26VpjydUv1QfYyhY6K5pOJKEqTkZKlE4auLtQV1s26LkpGzBhYqrmRDGLarS4qaykl1Vkun+cDg/VhSmrbD7vLq6tHjxx989P6nP/7sk598crxRAAiAoZTxYCMoEhxBnXxOIzpcPd4+e361uxxWF0wd357urg9v9/OEGMxJ3UulXxI3gzdhFlZVUxIvkTqACVyzDAkWAkcT9siGQDV7h+vDVU31mIXgrm7kXEsCaxzyugQTK0jdnNxDtcWDoZgXJMwBQViqAKmtKFC3Zb11dfcWWGvcPHzUYE4SHY6WL0eoRm91XFqZlXVwUJmPpk5wMiMowx1dFBYxciVDADm8lisNE4OahiD1Waz3EUw1pZTMYPM8WbaSte/6IXSJ5rs3++P+lA6Aw2aw4fbzKR9ecMcUbTNsr65i9tlgKY91zkIEMLsGzdG1E3Sa0+lgRa2U43az211sYohFc4yU0szk/dARZVdiCsKdUDCleU7zMaVU8qw2W8m5qIYYhmG1DVtzL6WwSBf7Wh8URQRTCKjAroQYQjaoKoQJBiYjchZBdncJLKHv4rrv19WamlhKdlPmSHCumEuL7nDkom6zG6NDmkHgoqSOq0fvnvY3b16cPv7B58+fvvv8vXcM+vr65YuXP7m62u0unodQJ9Wje1qt+tlhAhbLZeRAIp25iUhKebvtcyla6obCXejcKac8jpNW6Ss3erTAyUhh6qgqfiZxElTvVndyuFFlZlW7p2qG2FbXhoe4u5oxsVZQhgxwVtXi1eSKiZgD2NlqwoK7w5mWTboOgEjABmewNxtj5opZdRSIFmMtX3alh5sFETGZL0aXLYi5uBLk/G3nDqGZYLoD0hbGWhfUHzRTAhlBKNZyvwJiUENRUVgNNSagzp3NFC7cS6BEM5BACMy+sBrr61eUGdUYipoU/+E2viTDEHFNlD1zo2xRjzzAsGqnoraMOSonC9JimwG0tOhaC31xUF9PRZ1G1urFtZotkgBkpqhdzKLKJ+IgQXOJHFer1dXls3Xcfu/jH338tz/EFRhstoggzwKUtq/bmWyw7PpM91ePvJGW9av3+6+Pr49/qMfyXCzuHE4gVQUZhIXZCVqDJBjH4/zqYwh6RWDqgnTGM8HN1ayQI8bYdT2ZxtjF0MXQvXr95sn8hMG7ze7R1RM201weXVwhzS8++7sffv9v4rpfX25/85/+xu5y9z/9m9+JwjmrWdHsqolQrQfhtjjHeoO7qaUfM0Buje+5rKyLoANMgYnJCWqaNG9CqJ9ZGMTN2GazW7ursEqABCZko2iR0cfdhdyMx5OqRgwreEBYBWX3aAhwRUpYDbTexN3FAObVoOtVICW2icXNUgi9RHLIt3/xnwit//RP/8MP/+bTYfUu3d3cHI9JzYOgiTBgqvOsQgKz69sbct6udrHr1xuaxqLWgiJFOls6V2sx4GRMNXRtuZoVkPQl7YSw9JlMS+QVLSzbtgbeqyW+zKr60l3jjrrPch20V+YytRhy4vumrbX0RG7NfWyhybUS0peFeCnwGwerykXRhvFQl7YhESCBokQhYHFlMVcHuakieSZm7phFs46nMk/jqgsbbHX2v/vhyz/5s+//2jeff+eDb95MP725+XS9psuLq/Hk+/2b47GsN48eXa1hdHs7zS6xR8qliKnSerOlGG7H05jKM14JdHtxWfIh6RHZ1RVWUmIMq9iTa+xDxxQPU57GYmQwUyuqJZWSlMZpykVLyRAWx3qzI5Ipwe0gwnPx7A4gqMzFYzE3PxznlNUJpqTumt2V3T3nMk10OhF5cS3b9VUpyYxMUYqnhOMxqRmo3+x2fSdaSskWA/dDHIaOiEpKpRQH+tDdpf00nsxsiJTMNet0TEHWcT0MXVfKHDoq85zT0czMfFZLKR9Pp9ChJwhJ5F6ot0JAoU6lV+M06Tj7uL5a9yZm+vy9J323ylmncURwcO0JmGpVaAQTMkcGcyBxh+nRpn2SLT99/DwjadEwRASU0+ysxm5ila2CSC7qBF4HAHlSF4M5BBQCQSypuHQhrLerQ45ZMxie1dkZTCFYKtDKu8DZ+/NhyVfrGQHKgt22h+znHAvJCKgGxT+v2GjAxLk8WmCf88+iyh2XQofaE1RyXjpurr/DbREVn5EjR9d19dW1Mh2qdbY03qVbS5W3Ks2pr34OReQGQZNDCItkjBbFILsbtfL3TH4hVE/ls06w0Zbu68L2GupgOgc+Lvykeg7EzL3qnZcPUo1oK3hEC4BGixJvuUZ1yKzwe/irnjk6Q4VtFsI/e/EaV38BiZbvXN5DI2Hd/2o0dQG1kvJBidlmCnW95dryKqporWJYAIycjAxEJtwMY+sntWUmjjYDrgzcZey7nC/6eSmEbVL9pfvsZw4WMrOihYhCCKpqqjCYaeMXmhVvpKoH6zcIFLsIIjUzN9NF6AB4BbBEADdVbr+aHG5qagZCv+kMpm6N0xjarqRFEyUzc3Njb5LJ5arX2zOGaFTzB8wWC7t2NZjBZFxvRmZmlmCmZupmREpM93MXRZVmVvKgL2OgCqmEQNa8saiy0pv1nfB59gIHMkg4cGBid9eigIEZXoWmUomCQz9otjxlFOhsULCzqZLAZj3c7q+eP9ruLl6/fV1ZDkUBE448XK6mKYXYlZLmacolhRVbdDXdXq0Pt6d0gAeggWVcsgqDSByYU8kznjzZbvtVOpWb/ZsudpvH2yerq4LUb6LPQWfMpznnkucyn0ZXYxYWNrL3P/wWOlw93Vw9XbtMd8c3h/F4c3h9mFJ2sJuCiSVEAisz5Zxr3SgxDLKap2zJ3WpAC+CuOVs28sa61AKz5OqLoZ0DFCQyiZM7O6j+sJu7l+XyC7juHWZe1DJrNZfyKuGzYsVY2cjVTcx50TcBLkwACpVijRFklVxqALQoFmB8cfake+MGYnfD2QK7rbyQyupglyhwTGmiwACcG74pUbxXWKUZsrkiG2I1oNCUZpl9KmmekhcECYFZ1acxne6mcgILafEQaBX6POPmuEfEsIlyse0lZD8Y1FBIwF2MXQihs9KPx1nTvh/COJ2OowEgwTzqZs0w0ZTc7Hh9vV4N29V6pjxNOXJcrTZdGI778bAfT3en42EaT7DS6P3rtROiKWn2EH01dN0QKbjEW3MLkSV0zIhd6ftBJKakKRVzjwESuB/iat33on0XOwnMnVAH55I9pfnm+pCyqdI4J9O9FpNIMXIX+9XKplnHU0p5erQN46kM/Qou2bHdXn7yt5/8+Cc/0Yz/8Gd//V9e/CePnzxnoevbz7quE2FzLSVrSa7ZymxWqtHQOJ6O07TdXmwvwuk0HsbU9Xm6vtmuNpvhauDNMKxO41iKd7ETCjCQQ5atxN0M0DrQBZyqg2wVvUlFVMyJFK4QCag1c50QWa15asSnuoGIVLVmD7gq4M5woho964yaWFghIyYSEqp9WrWOqusR1zQMIoarm5tq/ffG8V04zvcbRF0yvcVoAXXCYlRjmR9uF5XwBeY2qMbCHCACkRNVQ8EFn4rmLt4GaHWVbvaJ1iIa2Zm0ygudmc9GWnUi1GTfIDufc2/aPiaulKn6Jlr7V8sJa4ONejCL4wGhvJZUFXnWloVDWKrQ1o80XI4WpkQ9dUR05tnXwVGzxwc5Q90IwRf7z2opQcLMBDcyaCnrfui74dHFczL5y7/43vf+/C/BHTUorHZSD0rAs1HLQ8FnO+qbWiaMXx9fH/+wjmVrffCVL9MjnEvQVlvX76kgsFrVWDfjUiPNatOUkABENXJQjB2oF5eTTWoKohi7w/4kXRckbtbbbujH0w9K0iePn73/3off+vDD0+H03nvf2PS9jse//t5qt7kwQU5ZiJ49ffL0yePThKJziGG3C3e3U0ounUCtjkCX6Wd954RFLdKwk3PuBNzJWhg3mUML4OQk7myqajB0kCghShBh8lzUvKgWLWVOE6A82C5suqG7Odw4c3YTgjLCqptSKihK4AjKiJGHPvR9KDrnnDB4DIyEwOhj9/jqybNH7z4Zvj2e5F//7h/8zV/8jfhqu9s9ev7sb3/yuQ8S1n2IwtnVkhbPiuOUhsib1QUU45TcyjyruQhHIoUVLZXV3iJKrLaChjqa0cUXDMCXhgbt/LQu0u5XZ7Q7wOqCuYzefVk87++oM8fB27waTMt82ryhYr7ccIvkxt3IA6QJBZdNkPHA0YxpyfRCY98uMfMEcl3slCGgCkvW62wG92Lk4ACYG/k8p5IVxqbQ4oCdCiKH42E+3qU//sPvHX/1Lsh3Pnz6Pl3I7eEHfe/D0Kv18zypjuvVZd5085SjdNeabt7eRSl5okw09MObu/314fDcUiRjkLAwS+y7UILOKWlR8i52suIog3CU48w0kUSnMGsSociiZilPuZgB2+0FQFePnuz3p9Px5u5uKsXH7GD0XRe6FSic5pxLent9ZEKISCmrpjSXaS6GLs047P3mxoWOu61I7E/jPGdabdgMwnAvqsPFxRUT3V5fpzmHQNz3LJ2Erug8jnPRmYDj8bg/3J0Ox5RKySiKks0shRD6Lkrn7i7GIqLSOaPvQmCBM6P75jdKlIGs08Q5EXsAF6VTEIakOCAMK+ncQe6y2kjReUrTlI4IhB5BpZYv7kJaDQiomZEENy4ccXd99HX56Fd+4TQePr99teUNBVbKzsYR0jFIoOTi2RVMFBluilIMquauzBIlZPIuxIvNVrMWLSBECRRh8EjRtCipGdzVSe4BkXt0ePkrAp3D9Gh5jB6st19Wai3Ix8+vNu4RMqAOMkELS4oXFKz9Km+aNRALUx0zUvMiXd4u4R5/qe/VawfHJDBofbnziM+tGsISLeas1DyDnNEghHMt5+AWu1NpRcssuOqq2pOMhg/UtQHNrau+u3M96TXvrA123WipwWsl3Ayv6pAXbRZ7jghEg64WgGpZc7wmKVZGhcMJUgv1hRyF839fdCSrp42Fq0yvWu6ecXYATn4u6uvZbQtjM/OqrcjD8h4AYHDRUBErYjIHMbCE8ZE72AnScU1iukfc6P7EwwEyoIJCJOYLN8v9KwGsdiq+/Fc/+01g4ZJVDF3XxRhnT6kUImMAUm8LPUs06zquZl5cixvPWlRbkNvifLj8dqu603Ynoc7JmZt1ZTf0xZSsGMxBHMDE5l5MNdWQyxrYValT98iZouxWl6mh705MAaLuWpSEWRY42CxIZGEYkyobWYG7MrOb1s0HAkAcisXeiwRCIiLmBoYwObmbojZPTqjxJUZW0c+aDq9m5jEGJ2hSGCMTE5EwwObmanEIsHzc7zVbTjM6CJHEoLlkzxotzjGs4nDRn8ZTDJ2eZnMTYWdYlwsDA5KkUzqGHMxVXYv7sN2k6ahFu3UXhVh8mo6eDVIcxYlPqfSnES6RQ+jDzeH25jh6kZxy3ETecOfcZcwn14ILXRMocOiicOzXF1dh6La7zml6e/v2ev/aReMQt/DsTtIbRAuyTcXd3Kc5UUl932/WWygRiqqSk0BQ0cpiZATTbAbNVMm3zszCVHmbQkx6bCxPLw5FSyFc1oL2dEjFf0xneLkHaq1YzQeAghQsoFhj20BgAbmRmZEWU4IW12pyVxtXbcM3cq98RAOL1Jt2MdSW1qBWgla1SiDE2MGIiEE0zQVdoKTcNXhXIunswgRyN3cxEnBgZ1ZIPpWsZpk9W4olxv54ezjtT/Mx2QzviDUwhPsQO0hcO2mZ8ufHa+j16nEMG15f7DhwsRx5GIZNz/pqSvu7u2OCKeoW2TFQKI/ZPGspZS7iwWY3KpoU6uY2j6kwMXdCdry7Pu5Rz6QpHLg75tN4awbL+NblBwoMnfQuY0Ifabe7MuU3Nzc52cwJyKYahQUWVr0AACAASURBVA2l79H33nXeRY3BicWMmYJIz9QdR7u9Pd7cHE/HomYp65TGEIf+VLwS67kE6ZgtzXm3jX2IpXgM9O3n762H/vrtzYvPb4YBL2/mj//mk1/79V+6uny62a5Xa2Gfx8OU8jTNp3XXvX71RoJQiMTRRbK6Tzmu/ebucHNzuFwPeZrAXYy4vHxsBiPfT9PhNMoA7Jv5N6DGBmkmrpWP3YAbbZsfKXsuyIASm6tWX+/G9KwlMsGp3o9mTsTMVtytgBw1ykDg4iAyMqo2Bu32D+4wVTDV0PViBQQWievIEQWlIFN0tVJHUTXVtuGwaN60dcxETMJECK5qbduqZbecR9u+GMU3jIXafKyauzQKwf1UGk6AkDu0mFtt5LRaXBncK09bQORmRXqUUigyOiAAwaKA3SoobQZolfyS1+hQ9zpAqNWBsxsHCuQMqxWHnyGe85yLK/OqbiHV486q90plVzIVq/x4I2uGnvVkS5NZEldksOoPWwglwM5E0vXmRM5a3EQnIHWYOHHwZ1cX+TRerK8EnE98tX5fk7/57O3N6xskUyr1DbSigVClReTMjXN35o6RL9gnFoPHxVjn6+Pr4x/Cwc1IA8tKcu56HIaKRy9hS/VvmxLEiGIIbuS05NDV57dgmjKACXBZlRzNqe8HJqyCCIU6UhqPubcQqHu8e5KtPLp4uts9/vDDD68ur/p+5XTLxDCz0r3/zV9774NfUaSXNy9evvrkp29efPD+N//2Rz/JWVMhjr3SVLU2oetyNisWRGpKFsDwADAhEARkZrkWrNWGD+7VYskFFANHuJMpFUelKSkhROm6OAzx7e0e7oGRpjmSz3MOUoKkzWa72W4//fPP1TAM/Wrot5vLn/705XrXF8shIgj6yNvNqo8diqF411F0RcoroSfbx88vv7EJ7zxd/fLG3vuTP/7Tf/Xb/89K8O77fWIddsPtdFhFiQBjICObpcxqxeEoav2wihzfvLw+Hg9FwR4ZVuYMM2Y4L6PCZWNpIw44oan6qGaYPGhe2mr+wNuGliF+839fOiVS9QXt9DaeARGhlAeG7SCjpq2oBITa1hIMdnarquUmE7lWsWelJ7SO2nm5Ue3sYtasjnnB2ojrUAq1Z2fmwuCi5qZetG6XXE1hDHWvU61vAcbVapdj0EKn1/h3f/B///QHn65ke/Fbzy8vP1Q7nk4/7eK8GtYEK2WisqJOqO9Ox7FQMcLL67eHUQNvdjJw8bfXN3f7x08vtgROBpVwnAt3QzesMecoa/OQtbiWPkYhDkFIhERWCNkkZYxz6VdDKGZIIQ7dsFKn05ze3h1e3xY1mGO96fquDyKBOzMvKWlCBliw30/MPs+qpTvcWZRtDHMpObtfiKV0SHliAwdiRtd3q/U6dmtGnI6nz1/sS8KTR5sZ5KV4AQct4Awu2R67MQHOllFmzwlGEAri0ZW86JxmVR6GnnjQkogl9B05NKWLK+okwsJ0cjmaW0Hgdb8LnYzTcdiSRFYtFYN59Gz36tXb/eHuMI0Xw5YIHEDNHTdrzgSuT7kxOxzOpoTJ93fzo92jeT4Vn0+TU4/QEQGRpIsrStFmKTmvXVbDYEmnNEaivgtzTsg6rHrJHGzgLPOc8puUJh2kQxAJlE4jczFVM+OKGxVjYjvHy1QvT2+gKrCgH41BvwQa04MnrtKP2h9pKV+/uF77F79c/mgNHbHqU13DDbQZTd8PIeqDVgNHGypUH70KIywItVdtTgumr2BwqCtIDf9zNJkkWQXCFgCc3AmmDq6gIiBs1Jq3+lvOBWvj37SgrlYFW9EF3yMncH37C75dOQ1ECEaLLy28KicYaEGAsAefxls2HlWZzz1Hzu8ragbMzcjAQKs6iWoyY9skzmW434ONjsYT8VbnL35buiyF9Zsb+RWAGyBVLdc+okjzuqf7hMMG6VcQxhmVA0xVPVf/UcDOFCq8566NQufNI6sJNWpLHySwsKm2vh4O/ioPrK9Ar754w50PoloqV2FgNVAp5pkWyaW313uA5MGLOtwsQSt3lsASRATuxZoO1W1BSAkgUED1oqriu9yaGz87xROzW73cLiJ1z6g2Z07N9NEI7LFSvlwNBApMRGaqpTDHhd3nVu/TwjAjr1N7qherqjY4EBOD2ZfoKfLKriNemsXGKiT3qhoUcZAzjKxpwKTubV5MRc3ZzcAubOzJweZeI8rK7COBTIiAEKEdDMpELo4A5XLM+91211/1J56LFhoARSpZhLBGoby67DZPViVomhOcDJZhQ99tr9ZsIUBiRL8KzDTpyQ3SxxVH5jkVv77bBw9D7Dvp0pyub07znLs+oHgXRJi3w2q16fuw6mIYun696vvV7tWbPJUp3R2Kn/bjnQt3q0h9cJExZzM2Z2Lnvu9CnDRrKXUtIfjpNKapaHGGkBsrm0tgcS1aPCdDURQwQVgCmJkczDC4TIcUib12/OqNC7jcfpV+VTPT6mJDSrVRdbLqpOMENkDBzShUqNH4yBVeQMqiMDWUZYVeng8iUKWV+lLfQBpU7iCCVrNVXwgSBhizs9VwNQrFgRjIQBFIVsykVqVULRbqskUu5IEhMs/ZHWJSzDAjz2l/s3/76q0W62IU4myq2UvJxh4ik3AIXQju7OMp9Ry7njoKTIwSESgEXm36pHMIYlJ2682wijEwEY+nGZ7VMzRfXV6dTqfTeMxFjZjJ3HMMuh4uhYJZp3lmgIREqK42DSqMtj+MjgLq1E2CrdfDdru+e5tP+yllIB9ALMyxI3DoggV28lRy8my2XqmBiMwkKx2P6fZ2vNvPp3GyxY+/KE3ZKBiDTAGISGQxTerOc8rb7erbv/ALn3/22e3tWwQYEcxffP72+ZubDz54frHakuTj6W2aNWebTxnqOp4kBKfE/XrYXoQQnWUulpOZemAGibizGqm5uUd6e33z4598epyPdWtpWDqpCRbSYFtV6R6tr/MY9gxShoOd3J0rmkIgYcCrX54D6rkSq5rBQJUiC0iIuNJzrQbhLlu6omV0VlDdYQ52CiIRHupSWECu0EqMxkLmrqs37kWIzk4RgR01ea+GYVErXlon8aCrNDAWAy4CoRUmD9AxnJfNqvJ145rsgvNYht2IjMXgWvmVSoEQgQBmQ2Uam9XyxK05MtRKh1rlj1ZcsBspGCxk0BpB7Gf8qVUzbfv3RbKHhWPvXgWf8BZ43NKxaNnsAebqeriY59WPqXUQAzJQFGkYozE4GJMKMhvEVxznaY68UlPxYd3tvNDx7jRPE0SocLNzxhJqRUbOUkl3S3m1nFRvY8Gvj6+Pf4iHgGxBJerwGTh3OzUgRsyaXKNNxkFGLTWiTb39TAGgQNGKAviLH33/vafrTRdhkQBDCYh97Id+Fdfb1zef990gCBKZNPzit37pGx9+6/LxY4DuDtPr60Pl4etpDrRxbIG5ICbFnPT9b3zz89v9y8+nw3joO6HQBUMphYS8xU5VexWuykGCVKIpiKCl8kkXb9s6AHcWoejckbuKwQp5gTHA4CixkyCAFmEEAcNrrjmzrVelH2i77iIjrnbSDcNmvd5sXr/9nGQ3jzMAIcSB+15CEIEz87qLvXgX8pPt5SoM71x9673H39nIe9/9o4//+Pf/8vZT2EUcH3GfBebdCrEns3k6ljRxPlkq5vCuC14rlIjiOE3FZ4IXyAx1gJhdeaENwOvYEAsqdL95wL9k8ld/omoyaNnGzAzNlgWgmg2y0NxoaWGXRvYhUaHdO+Y1sgw480tAVGX8OC/8C+uhsrXYKjBVXU9IHAt9hNose+FeLe/bgdbPu8NZoaTN1cabOn0Zlmjtouq+4ygO5DmT9iEw9Xy6of/4Vy8++uDvnr7z/Nd/7d2+f5Lmt32kIPOIU3YlLy6SvLy9u5EtiDB5OcG6ADELaje3++kwhotL4d5onMxHVSf0sWdnkd6cS/F5mrRHSnme59BZFbMGpsJG7OtVr8ZGYi4cwpxLgVN07uGK4OgiReHAElkKnFwIcIMpprkMQwyxB61yktUqbre03WVVrLfxcJhChATEGCRQ18UgsRQ73N3Mp5lNOiZNcsp6pHJa+2obQs/F6DiCiIYYh66fJoWVSi3ouOvCiimQe1HzbBK6olBFCDB3WEllfPU2b4dTL1v3IXbE1FEIceidip2MGDGC2FWLWrl8tL6+vjbOXRR3J1kKQlELWp9QGCC8kMUZBLBi8jJrnlMfQV0u7pe7jWtE7mla2Sz5EGxKohpYTvNhHYbVqjM3nWYM2F2sx5u5aPJCpk63rERx3TGJUtGkSWZXGFwCSYGWVnH6ean02sq0yIRayZ4ri/uHj5Z5LJ0Lrvs12P3+Ofr7DmrCSsfC+Wgv1jiStCTQeB3MnbMK7yvIc7EKAMQL7f8MT6ORkiqXzBaYBYvBly+v0c5AFV8LedPmNcysLgi102z8KHv4w203qkX0ogY8f8xa/YGdib19PqGaoVbLSCYiIbgxkxlXT5ovnqrzRnZGVwha6oJSm1ZbalJTmHOLKry/bAR485yoseYPy8YmE1vcY1FnJORABcW8LYBGXF1D2juprjm16veaeF4Nmmjxn21LY1VNGIu3Wh0ORsURqX7bg+W8Mn9aR1QBPeGfa+L+M/fVl84e3L2aTJ0t9CtNzAvUjRfVni8d/v1LtbNSew1iJhapiYGsWg107cGVZoGEQMzW9ief5pGYWIQFElpsOFCdXyrUBSw2K1b3jtrYME3zXEpxNwKzAwxhKVQq8QrMAmISL2ruZMXdXY3cBOc4gvphGUzSNGLG1BIJzBYyQo2Nr8RIAkvbG5nY4ETsZ2Sl6Hw4VROoIAHmOatrARp985THGGJYhy6GYT24Ha24qlMEdTCYWlHo5eOrbhVffv4yxk5ToQQi2j0enP3p+083jzdvj9dvjq/YZErah2DQIfarfqOzjfMp61xKvptGANSDBJcXgWvwlriRn/I8TuU4ztOUeZotgQWR8el4i3K+rpCAINitnr6+fg3C5gqXV9sn717EGPNcQgzRMc9eVM2wXvXCFFKapinnrClPinEcg8eOAxt70Vw0OImEkg1WKqsCBDOwuVpxivVkMqBjrp4yFdBtvMRmvgaGYPFQQ3Uq5AUq5QVRKHWoB4N79BrAVrFsWMWw3BRQkC2NIaO6H37pPjd3mDpDvTJX+dyrM7Wml4iqMpYZ7kaMGBgeyBQJnlDqTELgBCOv7p2B4EzEFD2YMeDQDMV0nPZv9+N1koAQRWfPs3GMFAEvJSucmDkEpsgmllLe3+6HNEjHlixPiSNCwMV26OKKmXfbzbAaSpmn4149sVAfeuIQwyrPh7vbMmdIUIeaoQtO3gnF9XpIU9KMdpIVgKOi3IH2b/aWezMN0SNvutB7kTTNeUIZcZgsROtj14UoHAJ5gHkpKasV6BUIROrznIr6zfXd6zfXr19dH2fEzmMHZhQ1Vc/qIjUokt0hLKf5lCewh+eP3/nP/9P/7Ld/+1+9/PxNu3Fc05w//vhHz589e/rsMpXbOeepJGJT9v3proeM+ykbhh2FYd2vBoDynHJJgd3MqrUfgP3dXdd1cLx68frPvvfnpz2Ev3BjnOceX75h6mDHvKad1qUjhM6rZ/+yfKA1X/f5VGZeQzBtqb2raVal+bn7fRZh3UW4spDgbGCnSBzgTTpd4zzN21joC4t/m6MthQoW76qzJkJY6OfRxRcbA1qmNiTypW9xwErV8y6+odQ0PQ8zWCoSU2DF3di9pqMyTIiZajegXx75ffEXeauympjvq78J5s4PPs3yRFctuwFown2qQs3Wt5zfdX3lmvRQucMPr7g1YXnfILb2SUHEQsLMpXi1iVSzzaPLi+GRGd1dHw53peuGkssySPt7PujXx9fHP/bj5ywE94+9WjMu0lIcKoFDEOaqyMa/+Z3f+ef/9W/9xq98EKln11mLSxy61dXVVdhc/vX3f3h1eVk9W/s+/tJ3vv3k2bO7/elP/9/v/l9/8qe//4d/fHoJTMAAdPgvfvNJ19OTp48/+sWPvvmL39pe7A5TOtzR2/3fqqaL3UWe9HQY0zwTU5CQU+Yz7I2lYXowHl0MzB3M4Co9lrqyiYh4UIJWw82A2LEIAx4i+hj6ntdr2WzCahWCFAEHiTEMV1fPKW6MQtdH4RhjnKZpmkcymIHZFaVYJjZ4gmuZ8ejy0Tfe/2BDFx+9808++9H+t3/3t3/3d/79+BbIyKt8c7OXteyePb+83MVBpintD8d5Qpl4LhYizHWe8Ca9ibE77mchYECUYTVs+9AHCTF0P/jh94W6+2z5c2Nz3qTan77iav/sSP7h3/CSceYPXnbhrn718mr2M1LF+z/6Aizd/0tr16pelds+UKeotLAeatlpbWpaO3U0K3hrlqoL7rZgcVRZXo7Gn2gcwyojSGl27YZ+bWppPP3eH/zRf/zrP/pnv/Wb/91/+988ffytz1//VbE92FTI2Q2z4YBw+uynNye106RFQ9FxPCXsZzqWj9559t47T0Lfkclpmg/7cbw7zKvtOsYnAwUOQ7958erTnNI0pTGl2A/D1oqqqla1UQwdOJLE01TM1LWEGB49ugJLUS3jHEMXulhJWGWe1RIAEZihpCTrfr0apikSapaROIkpLi93RMZ8kBDW28G8pDmdTsd5tLdvpih4+vhd1jAeTuN4yCUdb7HaYrUNzpYnzMcTkQWhUnSa4ISupxijAyklUJqm5PA5FWLvY5SlVyUOv/HrH1ji6aSH2zymglI865iyQ3NWc5qmMk0zB0wZMcabm7vjNAWRcTyGSK4EIVcHE8QRgAxU1rmLMHNgH7qM6fr6bcrzxfYibOg4719+dgwAciiHON0q9oxkrQUwXH6467YXh8OdK55cXDy5evTZ9cs5TaxibrhzrMDrSyFWz3W2RUTN7qYSLFqE2tlhulVs98zHLx20dDLL8RWPzFL7/Lxqq72Sg2mhyZ6xY2YQL5Dx8pCdn7YvPaT3bu1gghlVnL89gu17qdZydWYBa93fww/kAEKz4BIWb0NiN21he16FDWhawqYOq2WnAQX0YJVqp+0BGl7/WGwxpSdwCxavRukQEki1+4OpZXU4mzlgldV/HnkTHog54O3C1fTDBh02D47lV1e6Z5MBEqowAVItnKuFtzcOBppAuq1hyxe0LGhUr64sSJITvnAiz2AVGqrZdBmtTq4Z46jTYheCQ1q1LITFIKh+RxOcEDPXixJC+P8LYN2/o+UGJGp2s+7t16jqg4mv0yK//IpXcYQQ3Lz5VVXbTABoee2LGmsx23xwQmDouw4tjQvm1XJreV2uci0vlmtDUE21qKZ2ESbLy2V3h0nloNUMr6qlreYiql60Cma8khbu1YjtjVXaMlX3cWanRk2uGrH23CxXzghO1uSu7K5o4xeCFwKcA8c+MomSIRUYoXrBVRc7dy1aiJgl9J1ScTGtz7lAocf5tLb1ejfEOyb13bCRIGmcn1xdhS7Edcg+g1WESjJkxC4KBEriUtTIJcQhdOpC2bKLOelhXzbbsNus16tV4HjY74ubdKEDCfNYpv+PvTfrkS050sQ+M3M/S0RkZN6tdpLFapItdQsaaQYaPUiCXrRAmH8oCNCDAL0IEiBgtIygHo2AhqZnNCJ7Y5MscK0qVt09t1jOcXcz04P7icxbVWT3PAqqg4tbtzIjI09EuJubffZ9n1nG7IjC3AFKruoKGFLB+dsXKZdp2uVjeVV26vn8wSoMUTh0kUspKEXVSi7GZNr8fdQMqgEhSBAKMC7qnioo6JoLClCRPad61rtCoRUIJxfxwMaoXEolFAdAgQUsLsTNhoq45gVVQN0ECMv8TzgARSHArGLLTm4cYWZFrRicqbIo3MnJ1ClWOXCrRE9LZbHtI7SlAjCqvxpXkSlcTat5dpVsVU2kFaW+Gj20wWLWpNItE1I4zIbYpTk1OpiiTKpFEUHOOZWSwBxi7ELPBTnnrFmzlhyA5ON69GwllYMe6mzmfgz9EEyViDebDYCctORDmqbd7hbkq2GQVez6/vZ6TgmuUEXOdWAHrKQ+Tl3Hfd+t1qs85ZxNbZnXpmoKU0AsT5K6whCOkg6q81GTCqSYUiFiJhEUAUOqk5GLWdKSzWACcyTVebab3eF2Nx0Org6JYKEuVkp/k/YyM+CqaqamCAEPNo8fP3z8YPvw05++RASTuDGT9v3q2cvrq9e7h29tFZ6tZM/9wBEx3x6HfpXmfVbjlEvKElPrbZiFAC1adWkElFK6EAUxT3b9EiEsxIAaoQh3Af2rcbGOwDOtQ92ldmdad3g5Cer4CnFr7d0lJjuc2olh7tBlaOCCmbZljApgNW03GBxZIjvDYEoKNtydjV+Tbtz/mlc+cOX5NoEd69fK0+7dRr0aQ3aJ/AQ4kZXKT6KT6tGpfsGracBCcYSZa50eK1SnE9aF4szuZO09+5p0682Ep6Yz/Hs+kbvbrxv7Pq5H1WCsJW9LSwrNTLPefO3+o62XJZOonUSqTXVycjOvtDO4kTFzCIEzu3spJYb48OGjw+FQdZFG5qUCZ4qlhq1r4Jvrm+ubq141Tea/7WFmxkyNtb3s9GrMh7fww3/1w//4P/h3qAHeNaBSlC7GDgZNKaU5dsHhIfJqtZry/NkXn/7k45/86je/ZEV/jvAIQ4x9VA6ry5vb3fzcO86if/8f/MN3P/jgcPRjTq9e35ZCUTo4bm9vHW5W55cwWm3l9/8YyqKB8XZPNf1gh6srnEgkBAmF3WjmHhJAbIbMhNhJ14d+kNW6X62C61ySCkWRSCRudEzzYU4yQWIktqEPq5FTMo7kVIodvBjbUQtCxMX2bDs8fNx/QGn89U9/8fyXh+NnACOuCe43N9P2iV9sH+7my9BRztelgMAxxmJJi8/meYccyzBYnswSwF5oskIalUmYjszdG8HNFgJ7PacWwOleju53f7UE7G5VLF/EMoye6M7n4RTzmzLp69eMez282tnrTVZVGQqVdnV6oqoSdDioDU2rh2VVaZ1WVS0f6s1GYSPnpqKCu7V7rYQP03ZG0/L6l4KyPuE4rDSVeZ5DCJvthmhI83T9+vgXP/rF3/z4N3/8R+88evjRi0vPdhO66ig9hTE/fnv88cdPLaAwOWFO87Sb/BZdohdXl1NOQwhmPs3z7vr2i8uri/XNg835g+58O6yHbnCFluqwPqm7kat70pJKKWpEgSkQkRadS6ZgoLher4mDuefDXs1E4jB2RDzlA7P1Q3uV1ds3MFvRlExVibBejWYQ4dVqUMvM3EWZU57nlFOaj4Bj1Z+vuk0+WpkO6UCmnMnKhHIsZ2f9+SpOx6PEWGfBMYMDuq4LXXTgMCVwmjNUUVRDRB+dhUUCUVgN8eXLK0tcZi6JGF0/rkI/xj4aFSIjUfdStOQy3+6vzzfbcRjOht6AMisEBNYTUiCAEbQtWmIwgwUySC5IeXL4enMW11Q0PVhDM9LseVI6OmaICRO5UtYkRVhBTihG5JpL0dJJZAkpJTNFQp6SKrkpGF2MBldSN8teKR0MgjbNHt1BPqd0irCYedfgU+mFzF+XLt5tx7ZT7hLIhQTZNsm9xujy1UrpZz51PX0B09rGQBO7oEb6thuXkE+nGLFAcNQszd2rsg5UyTxt49yLHbUNzFVrRSBUkytSO8E4VhPTxQ8DizE8VSvkE5N/iSOLJOH+e9JazF5BqOKAh+gUKITA1arIAScmOZnrN0LOgsSA6gsmgilzq3zqq65UpiUo3qE37ZfX921517iOelogr9MdYsGdcM8OpKXNjQZbC5a2WE591TrUG40O1px4re7n9h7WH8bCJ6tt3EZGdWJ64/RuPf5FJ+Fu/3oA1n2EtUb8hjcBzNxc0esb5hBhAinuwKn7l7CoKxrQYGjSb64SPwBNblkHU3pTg1TocBxHXdTgqnoa28TSYDnAuWIThMq9IaLqDnM45Ko1B1DcqsNaEPH6zroRM9OiElmQNa/eJdK8uInQlIL1M6kGyOyoNRXUq9aTFv0ao9qmOOikvgdOalEHIMzRpWoVBaIAagRxDxzIUeZsZhKERLjz4KRFPYB7INhsx6vb1+vNisRnny82283Z5rDb1ynIt4fb11eXiiwcZuQYEVgCiannKWkq82EuaqGTRqY3sgpLM1F1XQiIvXSDT3Pqh67rOjPSrCieU66gMChWZ2GJfPti57Oxc06ks+/6eXu+WY0bdRfVUuaUPZsejkeCw8nUavmmXjQ7wKZgFVfAiNSZmSgqq7OiuKmzEYHNYKruMHM2C9RxO9MZDnNyNyp1Vj3qx1jxc3NtpEgATFI1z28s9yrxcziIK/roroBS82S7g6O1ccFbGKRKlqEmADagTTqTQC7ExCGIiDhcvcw5EQNWoOLOEomEqKOAUKAQsJJla/MyAygSBXF2gyM5ZvXZMAMKnVKZE7cQUT88ylkVZigV22UAyiDKUzZzZ5RicFBnUQgdC1OM3dB1+93x5dPXam6lzCkJIQ9IB+oixy4ZIYbRked810gopTBnYsQghVPfCWLU4qpuWk3GFI48l3xMfTf240CeNRk7j7HXMMEhJELsxZ2dvQtMImJEErW4i5MSTHVKPpectYAQBLGnfuilY63u/2DiECMxs6laUWHuQnzvnXe3m+0Xn32BPcID5hBNzWaUgjnh9eubhzdnw8pJSGEUOEjghM12m5MrTSKh5EzTRCxDCH2M63HUnOuejjFGjoFZKMAJjHHg/c5aTH+jO/HV6LoEVa3u6QRqI95bvG5KdagpmVYVYQ32dQJLBZKWyNmOaqLF6HspzOowijo/D4K6wZt0utZMxIu05l4P6Y2RvW2p24lmSlj4W/Y7s/7lBPnSV+5vOJRm5EQGsoVcjQVSW/KA2htQWO1VnQCsGodalfClltfvuhtiYnL9mrs+1SfL21whK5AtP8nEwqXqHJfDfqG81WBfCexLO4fJuToUtN6XWmar1BrChgAAIABJREFUI03doYAb1LwwU+DA0ia2CIft2cVf/ctfqRkiyqzLCcO1sfa7S61vrm+u/59e9ztJv/9aCkdqPclKvCZHj2dPX5oaQKpFBCxt5FwpmsuxlLS7vt5ebMfNarUeD8fd5Yvr33zyq2cvvrjev84ARygQRtk+OB8vzo+O28PLzz5/dX3rDx6/M4yr7373w1z8l7/69JNPPhMZ+iHOqUt5tlLThqbvWFqhjYTlXupoQWMHDCzEtTpzc7diASLCXcexi8494szBiEGkWr2TYDASImZodkbs4gDnq+ubKR12x+xsMuBb330/xhqW9PXl7WrdGwoHjeK9dBfb7uH67IPH3/ngyUcXeOdHf/rx//bf/4vffPw6BJhAhHRGLu4WNpvz9X7Lwa/pAGAYxoDB6VBKQS45+vZstd6sjzwfb4+MwAjmmlMCqKgJcx0kX+sX3IF3dB+1eqM+vKuT/V5xemJXtfrqjfOIamlbwziICar+uyLrXal29/R3FmtNCt+8ZWqZV1trFQttc5+9kUtaF2S5NxJInYLm8EoWMWImBcMVthxsvKSptRokgrPNJYxjHKTkMk2TsHRRxMLtzv+fH17/k//pR/P0R3/8x++O4wdir6jbFz+mcuQ4bzdj7OBRKHZBBj9aOoBHPebdy6vLfZq6cZOKuqOPo05XFi1P5eb6NiivxyHEXkIMUSUnh+WcintRSzlPueQMDpqK7faHw5Qo9KEbAA6BiWjVnx2PByZZrXt3l50K52HkEMRMQ8cgTynt9vn6WnM2rvohpsMxwwmuNWsRJglQJWZZr7quG4636fb1/ub1vqRSD9MMSMGwuXj34eOD/TZGHobubDt0PXHsKcRxtYJgOs5Eoe9XRWe4MjsLw6HFxYWcO+lk7KmPlrnMnpPnWdOkOSfAWSDRu3U42wzb7fb8/MEPvv/ROPRfPH12a4gS3BikWleCVBkzyMgdjNafrwOmnMCBuxj7KEPXR6ZjyvOx4ABKcCOyIAY1h+N4eXxVtGAulsohS+F5Ogj3TAA5C1nxckxQhMAxSIghl9xWLAAGSTWcO/FC6A7Eapnl3YpfaEh0yjB/V4S9A3PbePBTfrVkedQ8zVui3Bp+VMflnHJZZ4I51eHu3oYCLnBL3Y6L10OzznojOjSSQcPdvGmGK7pw0p7XW+Va11dXDDcztDmGy+v2Jd2uLBe/u5HAYUHP/ZREmy8/Yw0+ImeQ2Ym6BQBQcnYUM2aQNJhpkVe0xLbGNAKqPcgSdAAYuMJz1WGPHZVfRozqb1RV08vb4vDql2reAAe07upCMjvxttpHfo/9Zgu86XpC1E9J99JNr68cBGKuzILFggPuzlQBt4XiRrTAbk3wuXC1aAnLXplPMAf96wBYb1QaRNSmXzXWQP2bamNBnQiVaenwxY/w/nNBSzE1NyOHVPy2Pie8zST0xnQjcoUxiJmZSWLlzrm1qZl1jDkzsQSOMcYYzdTVStXsLugwuPHuIIRmbGbFSpAgQUwrP8QBd6qGW252b06vQQJXtze07dcmw50wvQoK1nLOK/hryzka7uHLJxRTm1gGBCL3pAorcHZIRXWrZbKQk2dXoQpgkQEcJJhJJ+iJxGUI6vny+tJcA/NsE89koked3D0jF8/qykyrTjT7YTehA5vMZZ6nvD/sUMC9GJQEfS9dHyR433VEPqdjLjPIYkfj0AXu+r53Ny0GI8tOYDfK2XIupupOz6+fM4xDO4EZJBTJJc/zlJJmgxIb5WKAB45MDVitcaHMCYXEO67KTGfmQJEiu0OLJytqxc20EZManMg6V0ouASRVye1AgTMZu3DlNzGgDjKvhpiVFAUt6f4i5aUnVklTxASrO1DJuRb5NeyTO4O0mTLUD7kq2JtkGOQQImESQCiwxBiYxVzNoJbE3Wo7JhB7BDN3IXQco/oMz573yYohQDqRIfAgiExMx+uDp2YJD4MmTUe1DGZhEiYxwzwXpAJRFpEglacKIE2zqSMg9OJwS5aQV+v+yaOHXT+S87Sfbm72LV4pTJGP8/HWRLA9F+kpdnGIkUWP88HMUd2jGXHoVC3lqROJMcLF1FMq85xzQjHVUuajrldx7Ld97HPyg+XUh+lAaVZIIRNyIjMhD8RRBCFaGEspTCIwLaUoVew+9OAgsQ+h70BIOeXSR1Nmroh2Ww9CcH14/jCQ/Ms/+1cY6kcvIEZK03GG48XLy/XT7sl7G2dWdhUPIYxn6zgM41qpei0wu6oQD10f1pi3m7w/VJ+0oR/GeGZm7kW1oG9oy127quL7Xw+stCOwglGoLRVv4R7NY/KO6bwwvJeocxIjLOANN+JSm15LDUt1lkU3K+BIkApqeqWQEZyFqeVS3lioS7UAvjsFvKXprWpwc0CZiMKXtYEN3Xwzubl/tLcdB0KrF4yMl1dDvnQy0BIAr9G1mAVmCk3Aa+yn6fLLg7/6Jr9xUzWZ+V2dw9OnRHSXwy2nePthZq6GnRWzWtr7zTi9ZmvcJjwyCSk7gZx9OeBbl+7US8fJwMcd7szcdUOMfdcN/8c//We31zccYbdZ4sZyWm5lWQ3fXN9c31z3rt+DYPuSmtHCAxWpGmhSrwQmtqy7233OhcDmDrBQSPBiRYsms77rDofbB4/PHz06X59vXly+/Nkvf/7LT35jnLcXZ5eHV2owhYxhuFgNF+vR5r3Ss8vrH378YvWg+/YH3/mDj773nW9/q5Ty8cc/IS+mXdeJKhdXEixTw+udVp6AElWSbZ2g7QwCGQtTIJCrqxqY3Z0h1kWE2KnMJMZCXSciYAGgpmZaXL2UEhBiHEqxFy/2hwlTRnWo+M53IURjH3wVd7cgKo5CjKGPD7bj+289efvs4ftvfXAWH7/4ZP8//Lf/+Ed/djWgH2O/KylnUhh6kAf30Hdr51QR/XFcCYYp5Ri7LqrwPI79elyLiWkJoY/UHw/HNBc3q4YrtPxp70dznKnfqVn0mx+1L9CW36FFrd5aWLhL2VKxIz/hWdTIAORa7pCw06Kq34Jzs09dyv9avH4JTVt+1ekrFSZYaP+1VlwYJrX7RKg1FKFOA6pn6+JFT2Bnbz7D5jDo4ulDIGKzMh9TCCHEmHPZ3VzDwD31HaPY//wnf/Xq5ouu+0d/9G+/U4pPeU7QZMl5BtPbbw2HHHZExCEA63PuR0qv9q9vrvbzYYt11tIP47tvv3s8Tm89ftixuOLzz59B9Vvf+oBD7EcYuzMR+ZyLmrsj55STG6UplcN+PqQMyZIzkYA5CJ9dbEreg63r3MwdyVH6LvZD57AYJTAfj4fDIR8Oeb9zEYyrPsagZiH2RCoUatW5GsdV3x9FDru0vz6Ww2F/PaXbDG3JixMsdKKbMZwdZjgpCzZnw8WDFYVxSiYhZC+qGphjFyWy6xRC7jgQGMYifYw9hL2EPHtKur+drq8Ph+n4an/tGRAAkIgnj8eHjx88eHDx7PNnFxcXu+v9r3/9K1WsYqjeIs4gZgRiImKQ+WLUYOamSeEYhl7cutANXXe+uXj2+YvjzXx7WewWSCQleNJpKizej4POeWfz9sE6itwcj9N0BMGgVtTd2AkZCCa9BInuU8mqqiAgAAYolB1GVG2AvBkSEU5MqHsA1iJLOoXQr7Y5W6w9aaoqrNR2312UJmr4SdsrfM8eoTUvCURWRUvsLR+kRj08bawFfamWG0aNCPXGnnToqQqnBceCNTf1U4LnUk20a1ugQolWM2U6cRcWMKt6mC/z56iBF0u+X9+Z6tKxWCFVdLrGsEWp1t4idnU1M3YUr6rwGhcCBQBVe+H3yEn3OFY1EtRYxIATU5OqUeu8MsgMzSKdFsvIezYj7Rn9Lj2tBSO1573/saHi5hWrr0N8HVgy6srfqOgVsbPBrEmN2k1XA7HTCqtgDarzzNdFXTPjZdY48HUm7r/nWtrO1b7nrn1xqkOWXoRjYeeeRIy+vOT6RuQ5NdoUEYcQY6xPyEyAl9L4BCEI2Fovg0mChBDmPKubmRk5EYUQhCRIqP1wdy+lpJS02qkEqCgTQxgCBJBUoxZ1da98J+HGGG9gIGrRASyc3hMdyQm0oIrkMAM5n8xcCIs/M3PdJbizuloAbF8oBSBzc4WBGXArWoqrsiOwcCSgeoIZG0kldAkHMXPVIjEOsY99SEgIvNqs3O3lsytEjCHkXbp6dssb3E5Xq/VqHMb1en087gNLv+r3N/Pr612PMm5WKDSnhA4UYa5QcMD2bL09X7++ebVeDbGTPE9pPpgl+GYYB4aESIHdAwjVNJ/cyeeiIAXMlKNYMrPmv0PmOZXbq931bnc4TOBALK4cKQYWEVHTrIBmN2zGs0mPeS5aJ2eZa1I/FoQQSeocGc2O+TR6U0AciJk4HY7KgYSlblyiKjI1NzgLQMwiAq4eNE2d13KKfJerMBMzmy0tsToP0a2YV/oSL7BlHT1KtVPg1Ty7/ojXmNyCCztJ81hjZhaJIaqRqkOrxwGZOpjMg5BL5CjRJXJAmXSeMhQgqLgEJmEIC9HxmDoPMXCI4eiFXazU3cnmsFyEu2Ho1WaghBA4sJOrFs2l7/rjPMERhkhCx/0x70FbefL47fV68/zpC806dB2MGaKMbMXqsOFAtukwq3Ds15FQ5jlNOXfRiNAN/aofYxT37FaiWNdFOM8zaFeKaSSoImUvZeoi1puhJIPZIbia6oxEFiXFTmowYIJIzRWlFA3BoVoM7gyufu9cIwMLq9mc55yHkggACwcRFhIhMN0eSuSuZPvrP/9ZN0o6KhWNZ6vSZzPuqHv+8mX3Ofo1hdHVwcL9KnaRPXGI3cjBmYoqMccg49ibyKEfbncHwIS47/vteltycUu5pBAw3y5N2YrC/D5QxRfU4u488hPQ46e+Dyg0CnGdC9MOAT+lFpVV5EsWXnGWetSgVDPHus4ZLm7cRmC200uYhesh7Iueu5KHl+4ItaPtlIS0cxjmbuTxqwBWU1g0xcSpWvjK63cytF7kve8uec39/2/nn3MjjwOALPnRlw6/Vsi0M/j+B7A0dr7UW3rjru/VH+1B5oY7kAzLOKjKkGuqQAOo8TvdwSTEgZ2tuh8ScyMUo2Wrp/NBmAhk5kXV3Jg5htj3vZD8r//sL891HKXf53kYhv2cacETqfZV7hDMb65vrm+uL1/+xlanE4BVm68SRERUi6p2oadI+RrHY57nue5OARtYveRS1JxJzi/OXr563vfx0eMHm/OzX376i08//fWzl0/X24vHZM+vXh0zNOFgh5u5p9fPr69u5gREWQ34+Oe/BMKH3/mD8/Pz7Xb96gbRj0La910IolmFyVI1K6+ZiizOug6qsZIAV4IwgZ2EWjzUWkYpUEgo9OwEFg8B/RCGEeMQxY1gjSGkllXhrOo3e6TUKoPjDIJaMSaLQlGw388GoMM6at+tH55dPLl4Zzs+OlzZT//8Nz/7i6sH3eb557swRjCZMjrmzolCThpC1OY8gxgiI8IphBgkppznKTEO6ZhS0iDOwkX1OB3JYWZ9HH05oGqv7vRPXsD/1t74avlsy/gesC8lJKg++A63uv83qM17Lw4iv3/80Om619GgU9vhywtuqfi80QoczlQnerhzNY+uxj/EzsRUnY3TXKS2PWpYr+zoUlpTXzgQk7CqqWdvi4LAbMD6Yru/uZmJV+t1fzYcbnYlZaZYCsYzn6f853/58t/7B9c/+OMf5Ly/3BUejDuBo5Tp/GyVrrOmeWYvxjzEcRz0FrfTbtZscHNfjevtuJnnw0ff+a6rvX7++sUXLy5fXb7/wbdIYhfFmSiSu/qckoFTZd4XJUxTUlMiV83OAAQsTNJ1BGQHMVeSxlwUMeYYO5LYxQggpQO0wD0liGAYnchNcxjHGEOMIsxKJMLDcCbgq+cvLl8dUBC0C6E3cysFxSDgIjpjf3040jEzl8LgMKwHp5h0zpbnkg77Y7+KQ+DKaogcJfSRxz4OZ+N2s7ogDa9eXL949fLZb19dv96nQzFzJ0hPZ6vxWA7zAccbfTq/0Mn3t4fv/eD7lulqj/MzkdyLIgshKNQZ0taxA0UbzQRWsqHDajUohdU4bNar1dg/++S5ZzeFMA3DJpbe3He7G1UdV3EunjN0rattN3XHro+aMZWkBcTQ5MiQUfrQx667LFelaHVlochkYl5MldCcpCuLtaGrrdNXWUlt5VfiUdtn3mR0S2Q9Xdy2Z9tCd/89NRHhdwbtOGUx1EopAEvdTTXtIrIGXC2CtnsxHkCjZn0VTKvdXjpVcASiKp3DXRRZnq8O3mvptRu5sy+7+IRpWIslcCeD1ccseVlLpN1bCHfwQtAB3MybxxQ1/w0SMHFBcXcv1eXQmNi5jmhq1nhqhSELzHc/3yXAaxirt0UgYnZYUzuewpD7iQ7nCxeutmBrOLUa09rb7MwLbLR8ACc0x2HC3KrfyhMCAJRS3N5I830xHDmBir7kva2RLBKYK8jlSz/49Kk29Km+W0zNju6r15fIVo1LtSCsulwnWheWVkZlC1TdYs5FVUWEiR1e7d55kbPWWzJzU9eiKeWUUy45z2rufd/1fRdiqBRnCajgFDODvR8Hdy9azNQJMYpIMDXVUu1jrNKzsLD9zM3MXE0VgQDzKlQVsHA1+u660MUIJq3TEdVcVWuaw+AAFjI3E4gEikRCEOLALKJWiqbmXKPePlxiGLw4MpDQnY9qdXyewYyJpVpngasRsCssN7isAjSu1XefNJuqgbxYSZq4kzgGiuxCk6bHTx4N4/DowUPLajRvulU9CN9++8n3P/r++YOLs+35ahgDRzKIETunfSolO0qa07DqzT1h7lfcD3R2Prz/3tvrsX/5/OnDszOUQkUD82oYzjZnm37FKvvd/vryNZQOh30fwjhGs7KbDnOeQycc4DkHSOiCgPtB1hfh3ffeUfXrq/3uZtfF4fbyeLhMZLQZNpFDysUVXewCR8u2PxxJeeiG7WYz9iuo55LcXSQEZlIPElbDKsbIzKbuWaG1UyDuCF0IwuZWrJhmqg76MLNSrJhp0eJszpWQFIQEDlOLIQQJgUOgwCBTczVopZKTJlfVxsXyZplB5qijKDupcKoElhC7LoYYWFgiS4yxixzY4CQMQk5pfzjs94fDcUpzevTkAgwnhChh6KoRdV9hoBDzVMhoe3b26MnDJ+88+eD9bz15962zi23sArPsn94SaC556Pp3nrxFHAR8vD16Np8UMVQSWeUT5jmnecpzqpZQMXQizCSa1HIhYun9WObPfvv5F198/vbDd14+fXl7fQyIWiwdC0xEeqbeC6a0TykdjpOaD+NqWHVEOMx5npJaIrhEevhoe3Exxt7mfJjSbc6H1Wp8/4O3ut67vmw29ODhejWy6jHnI6DDGM/OJNk89BhWvlqFh4+2Dx+v+wGxg/t0db3bno1XV6/hPYg//eSLeS5pzrEfNpvV/nh8dXVgykS27sePPvwOkT98cOFql69fHI8pSPjBR99/8taTVy+vfvmzT9XNSFiCmkI4SJhLKqzrMUK0X1Gxo/qcy/Gwu32wfuLKxBxiCDH2nQRiLfnR+fbdt5/85le/2G4eDH03xtW7b7//YPtYM37+40//+f/916zgwCyhRowKf9SDxNs54q4Opz705KzHYknJCArLSiFUOySJEhrYyyIcQwgcQqi+vQIWcOWh1vmoBELX9yLE0ljQROTkRrbMGoFE7obYDT0xqWsdNcDCDDa1O682bj9/al3Uu4BDiGOQ2EmIwp2ICBGFLizdFQcWwLYijMz3CwYQhNsYkKol9wwGhFhYAFQQTatrbj35mNzNXSlKHfsK8dAHHshBpQZ5dyxCezJi4trecPecDajE7HoAVdqtS6zlwmJI3xKMltRQFRkTVaywIoQk0qYdAyFICIGWLEQ6ZiGQS4h937Fw1tLo5sJmlktWMycPA0uQruv6ENzSe08e/lt//IMPvvVY9WA+//Xf/Gi93my3F3nm7eqt//K/+hPZlZtnChqhAi8MB7SZLXrjdN9lgfcO6Psn9dce+t9c31z/3734Tfi5lRYnHk1d84zW12rjEu6S+Qofm5lqdjeWIEFKUevKWlb/xT/6jz768D2BOtJuujEn6UYl/u3TZ7vp5sMPv/O9P/wIgs9ffP5P//RPpjKHMRznw9OXT19cJhG88/75W++/RUGurl4f03FO826fc8LL1/nnHz/95Ce/OXsw/mf/yX9+uH1a8jznnHNJOVuGKdwgLCJCoGofQgSJ7MGM3BkSOXTCkSA+rMfQSZqLC+LIm7M1SHPZgfN77z+5eDQWm25urvp+iDGshq7vo+Xp9vZmt8vvPflOiN1nn7/68U+vH1xQvxo44IMPzsZBSjn0HZ1vx/PzcLM7wvBHf/D+v/lvfOutB4/+8Ns/eLR69/OPL/+7/+Z/+Sf/45+9/oSid2w9d112ky52Y59RQker7Tjr4YunX3zyybPXN4Dmm6v9i9e7XFIf+6Eb0mFWNQKlY7q5OVguQz8IcZ6TiHizFeEqxajV9NI4dOFQgzNLDbw19rUas02aouYV0zTjdOd+BfhiHAPUsrJZHiiHcErSTzQQb0r/WmtUetjSPbpflVdZjHOlEFdfxtrSrJ4mVWWy2F9BqydLMctaj09TMzXY0jZvXC2GeclFUzY1WBv6VZ+ZnEy1HttaSppnIiIJms3mXLLFEKLE//1f/Phv/uKHm/PNP/x7f3+2w+3hVYi83+2345PV2fZYcHW8NaZ33nnX5ny4eXG+XpV0+N6HH11NV6plf9ztb3cEub68fvbF5YtXX5xvH7x4danmEsP5o4vYxWE1JDXNqmb9OHzx+fOnz3d128V+6MfhOM2vXt28vjxcX+1yeX1xsTnbrObpcHN7FSI/fLA+vzhjovVqJSGg+rEWZnBRBdAFPHiwff/993NKXTfMc5qn+cHFo2998OFmc/Hq6f6T374YIj5458PdzUQZZc6h64ZV56aHKW/G1TvferLnF1aNXotOuaQ5TVN6+fr1s5eXqnp9lQ+3x3feenx+trq9vB67Tc/jdnzEPjz9/NU//q//+c9//tnTp6/TIVv2nM0VJASiPg4Pzx8HosjRE6Zp/uVPXgiVD779zntvPXj1xeX161nQp31O10c4M8Sy9V23Glex6wyuXnKyMMKAD3/wbdX55vb65asXL1++nvd52ic/ImhglbTL8yGt+nG1Xk3psD5fT4f5/XffCaOMm/Fss50P0/GQV+sO5hJIejl/dL7erG9ud3OaQxCrrivqoOqMHRhcRwdUmVR1qBCStl+sWrWav9kqrN+9R3bytkHMa9TF3RqmZkDsgBOBCUKgSrdsFLQFYuLQNcmU1cahc+0OljrBwAG4NoCLGt2nZsFU7+KNo4JQEYkKPlhxK3WAbTOScuHT3D1uGfUysFu9SgSYqM5sYltoPY3zwFGCcBAJcHJvrkrCLBKE2M3crI2ZJIohsgSiJWahNUhhrW9cd71pHcrdkC4mZgnMTI5sSdXcjamB/gvpAoBbnRWBplkUYRCKFtXi5EE4BGGp5UJ1QkJVKJGgGhFzZArUVDvNkrvq/Wpa3JC+ruuYZeHotE+f63i+IIGWIoS5Jc7teZbDm6txeLX+dnN3qu+CayVtkRE3Wlh9PAiGv7OE8H7D/PSPGOOXvuv3yQNNyogQJSAsCFcVGzo3IesdAldLilNxVR3SSegk0uNKDRAqqo46cgWLZkTdqVrC19soVk7yvZarCIOBwAZdMF1aGiMopvXtBpOr+axmqEKPWr5AiOuTCLmwCUmV5DQn/zaDTCtw6eRqZgtzMsJztR5eYM5iLiRVbEzC3iafF6p+5sRG7qTewFIWCZGpI3RwWFLjSKv1eDFuh7E/HA46p/PN5ny1GfrBsl++vr5+dXP5/Gce8fCth2PXuelZt3XR42Hfh4CxTznHMUI8ruR8XA2rYKqlqOUSOFDmzgchDyJd1w1jP44DU3eIGqwv6wdnm83l5dXl9XWeJg5h3ccJrj6HIN35sPviAMbFxdnDR9vYhxiESa6n3XEHz8VnIGHW+dUhxz6sxrEb+iCSNE86dRxVreQ8GzNKgVKlyJGZEaDsXMkNRCSVtKHVA6g4qYO8YcBOJBUDJatG/HX4JivgZlQBbFtWry2L0Z2cgAC4VTpeNZtokdNPguEaGg0uYEbFealJd6nuMQDmRGAwS2UIuhGdJlpytahc8hrUX0+l5H0ynfJ0M/vsAq7ukre7HfVSpEyatJRuPQQwpukwHeNtWK03HBgMFISxL2pwJoGrubuAnDqHw9zIStIqRahdiEY8ZRdnZy/ZGbUvl10ZVWgJIYiTC3p2c/Vpn2M4ri+G1WpVLB8O+XY3MekGqxiMKM26cxSJcCL1/e6gq3W/Wm/HIa7Phq7nnCeHqhoz1pvu/ffXROJu7iXEUuzgmiQ4i44rqM0xdF0vwnG1GnLmkq2G5r6LuWSqZpzkmicRcc1EOgzRSlkPm36Ih2l/c3tjZCFEbR6E7FZ9Qj2CVT3NOdBGENiLq1v2X/z8047jaj32Qw9Ac3HmPsaScwBt1tu+i/VUhyOIZHJVgyF2KEqnfV/nSDa5GBMTtxaFNuWgloLiXpoAuTr6VUBG63RCM3cPwszs0Hoq3J3Op1OCeU4zs5PQMpeZwc7VUNYBqrCttQ5jGzfgyKykgSrYZqc2yF1XY2lU0Ykxpoz2tPdPgHvHx5LN3IdR/NSbWvQTjctMRAuleunTnHpcS/uduIonqlMN2ImoeHE3Ri0YjEiWDXp3fbkhd2qiO05WwDg18gl3M5gXXphXmjjq9McKZKsujStzIyJSENe5NGrERjWJIZFAUs1MiIhIKIiQs4BDgMcuxhiCECBSce+eWdwxdOPQr7oIKQFcQBIklpxARqjOjLjLJr65vrm+uep1nz3jb/5v3dNvUjtrKDJVLVrT6zDg6uo657IeerVj3/UmMR/305RCiOvNul/3Cr28vPqwz3GMAAAgAElEQVT1p786zsfQBRQNkR89vDimPOdino7TPlXFAEsI4p3BNVBJjmOanj199Yuf//LtJ++9erHb3ZaUbsex200JBRxAqAgJE8FN3d2KamjDZKsM3AUk1XfRqyGgkxfLIUIzONKw6kInc56Y/bPPbrYblFXse4msUWRY2ThGJ46he3iOEPup6HjWD8MQAsNI80QDHm4367Ngls83EhSrvtuEC/HV5YsXH//4s5sXKImzE1GoB1UrxtgdTsRmKFmJMATkbJohhD4Ofd8TZBjteJiO86yqkcnU0jy7IcZYSllKUV96PqjkD5wcFxuj7nfD829SpH53oLwrDX6HLntZQ7RQVJj+1ri7cMS4EeqsCuZrHminYbeLLOgODPNGTiHGnWyopmwAoOTUxj3VN8B5OThRH9TsTuAEiiB2C/PsK8hnn+7+9P/8q3//P/x7q/6d4/Fmd/NZHx/0YVDWoROg7Pflt+VT2hdzHOfj8birsj6zPCVH9ViNXT8O43gehnGapqR2TOUwZxJEFhCp+XScsqvDRZDzDKUABGEmxAinOuhG5/kIeMoJnlWzaREN5qSqcy5uJMxMJhLOzgxA1/UA9rvb9Xrz7Nmry9e3IcR9P4dwUA2H4xHAtMez/AyGft1LjDA1KyYGx810/enTT/ixWwBEAAbD3BSK6izEGAcMfSeg6OF8PH+8ffuwS59/8vx4k169vOU13MhnNzfi0IFc6ohECdZxZiQxJQdSns82IR/0cDV59p5Dvj1KN9ukKHC1gmxZC0kQdTO1TIQwoCiq5eU059v9ftajev7229/l8vp6d50O5jlrQWChSMf5mPbFV7eIQKTtw7N5npjD9uF2mtJxSmYYu4GImIRrLzYIs7CZs7ssiIQD7CLkpSn0WjOvrb22kX7/kr+nyrq3C2p4bT7TJ/j4LrektuIry0hdYbDV0BeqzBKqE+FrRGESg0cWMKOhG2DnBXpggqsZ6A2aDjXdDHtzz3MiJqfmo1HLQbgDEpoDqftJ5bDkhacX+JWtX6ODqjngBJbmLWGmhGqhaNVUsc4/JT/lb/U3EXG9GfW2KKsgvOXM3py9CXBjChCrjec64uF0N42ddqKP3oUyosXVghfbeyauIwjvRY7KxKnt3NNn6W880d2rrjXE6aO/d8bWYrg9lmt55k7M5l793qzSv07thAa5tXVHvvzer2u9/p0ArFON8eUfDgHLB3nyw1LTxi1cHsYsRFQZW6fbqKw3XwCikxKV63FQkdraPGNQ81NrETmXXFfGwgOGmsFQVN0UJ+fOuozF24R7JmcXFvVF3VnRK4LCTZWBLkQGG6kVO9mq1XYdGFKHVQRAhCqpB+xasHj01quBdGpV80VCIQYUE64k9KXMU1/0w3XTEpbp9s2wvkGpTMJmrrk6s3mIgSM7m5M70f5mt98fOoSH56OZT6/mPOl0lebrdCiTEyxRJ8LAw4vz1aofZFhth7mk55evjOyQDtJJ34dh7NMxTYejHop3gXOIpddc5qLJ8yQ4RAhKySgT1GnKWffeUdxszrqhm/N8s7/NaQ6hDr3jlNPDJw+2DzbHw+H5F69DDNOu2C3mObkChQCom04JE2y01dnYd4Ns483tjWsuubghkIDAkY3I1TMyg5ppnpAIqzBxNZtz9wK4kVZXKlSEqYLHDlhbQE5eudAnsR8azk0gl9On7osJQQtj5qiSw6V2x4J/ulcPf9ApoFH7i9xqi0FYhIm4cQQV8Ab6i4hAnNwI5krOMC+lzJOVo9rRqQBux1lJZhwPiOTBCyugm/5MSEop5ZD2825zttmcrcsuX726iV0suyPDUWkp5MzV14u0WSrUIOtEUCIRWCZzV7Y5WZoyTAKzq7k5FCSL25+5JRCzaUk5G+mw7ddnIwczu5qzOWUOCslFc/HsghhDRwMMRLTZjl0XxiFK8FImtdmhxM4iwzCu1h0RpzmVkodV7DpSUwkVgBfT0sU4xEAkfR8AInJzFfjQBS0guBBZSYebm/Pz80A4W/fvvfPWPOUgw/Zsvdvtnr16Xih3Eh1WabHVxw9ODClJ9zeHSE8KAhkjlzyVTz69fXgmj4hDCMIEoM7UyWnuRR4/fLQaV2S8Gsc+dn3siigRo0AZtXF1ikunUMqVcAto3fJvng0chATEZCA3c60nelurxY3ZGHCqaG7V6reziVmIybJ6bfbeS7GXgSUEruuBmtF4le67V1C+Hzpb+KxY9OBo05dOzDFv1GhSgOzeF7+MeZ0Qq+VaDks/nSDegh1QtxXuDi0iqpRZd5C2M8MNrmYGdhZiDpiPM7BMXXCSeyMU/i6n3Jf+9y49uUO17iURtVogb84GrdPXvlfDT2Ono76uOkWk5gokEFA1RnTAQFZpdhJkobmBiFgkhNB1Xd8Nrkh7ZDVA4GTqfBdqTkULfeWFfHN9c31z3V2LcqL6CX4N2l4fBTATVGGuP/nJzz7/d//w/HvvmFuQDuhyvjoeJxbpVl2/7pOl3/z21z/8ix8+f/XiyTtPiCHiT966gOBmv5tSmctU1N2tujI6u7MmQ3Rc725/8fEnfey/9wcf7r497Xb55fVNDOAAVzCTqxMZs1Ss3kzNgb5NdHGBiSOAhDy4mnsAd3BBIetDSJn6Pq7P1qGTm8OcSjo/67oOzMKtcUxMoWhOczkep/VK4mq9khBXDNKc5z4qbCbji7NziWOV8J/F/sn5W5bks09f/uQvP//pT8u6xC4KOJiauxGhinXgxc1VVaFzyg4IY55zmUkLbDZTiHDX9TdXu8M+sSMwl5w1lb7r+xg0lRpHvf1xuC32Ee20ICL9fQGQvt54kpZmzl2f4v637i2H++tnqTeXcusrbZElHtO9gm+piuqDKxLXOihQoLp0aVUYng6ehdDSjt1FbNNqaGqkDDQ6szfcrbaCzO/RYZiqZF1MJamqUc7l//qzT//TH/3mux9tVv17DoyDTTeXPeNiOzwu55kPOSdiNfIpH65vnmVMfZCZUUqCe9ECYulCXG2463XKh6S+P3gXul7O4xk4EnFRVbehH5IeptlKdpcs1hGTBA4wYQxdZHJYITIRDkpZS85FpFPRMmfmGEO3Xg8hUpgmMyNmN52maduv9rfH/Q3Gtd/ezsfDq5xxfXvNASY45uNm3Hax55jTMedD8ojNms8edf1GbsqBYwCjCfDhbb6Bg4HtqlutVpHFMw1huw7b1zdPn316+fLF9XSL1TCkOZdZjRADhRABcyV26FRmK3mv5g7xw2F6/Nb51YubF8PrrpfgEddIffLimGFUuUAwMe9g5lmVAInRtITBVd0M01QmnWMX5klLsqLWfHUig7lATQw9EBhR0QGBb68OgtCN/Xi2MhyH9ajZAZh7TkWzkjM5hMXMnC006ySqEhNmt8aDceBvmed6R3BBy57uAQ5+Ijgu1RQTVQLH3dYy88WICc0KzN3hQbj6lymRNUNUoJEYSCqQT9XZYQGwrEFjteK4vzXvJZcAGiG3Qb+NdQB3KDxWfGPh8t+xXpZtvGSBFWhuG7/eWlar6X2lC9SuM4NEmIlLUYJLHRPu99qkgMMZpxGLbeNX0aPW76q5MBxMYLjzQiy9V3o2U0ACGwGwxnlrzhdAY7fdRaY6D6piMgR2qsZVTi0A+QkDo1P8wv1Qecrk64cmqMtscS2k9o9aA6Oa855WiynuYmkDMCtw5ffAMMOyDu9df1cGFi9N/vslStWD0KIbp0UV0u7m3hcr90q1akGIvjrxDSAiEWlUGLNSCjMpucOI4bZ8BIashQJXN24nN1MzeIGZwp0DC0ujEoIglSFFBrgatQ+x+agt73t1rzMJXIEjEzoNEmzsMAJFAjELNQYdGG75zTe1oaAVfXUHIXIMEooXchJmMJlpKcXMURkJ5NRcz9qS4koikcBgkCurQ7Va9goqK88ExfQ4HfZXN1awknHvh/317ulvX5UDAKzD+GB8cKB8eL4/qEOQr+bHTx6st+N6M0ZPl/urg05Twigde9AStZjOlsn6/5e9d9uVJUmuxJaZuXtEZO7LuVVVN7vZPWRrOMRIECkJGEGCMC/SB+iHJEBfpJeZFwECdAEGGg1AdlMim+xmsS/Frtu57FtmRoS7m5ke3CP3PlXVHBJ6klhRVaf22Tszd2Skh7nZsmVrmUx+dXxdltN6PBweDkudAQUUiMAOILRG3wevnmHHVDFIup4u6jC22bv984lmokTzOr95+/btpw+7S7ZCMLCGslbWjXFqvsw5HzOMnr0ad5e7dV1hsGqqSgCFVvm5u1rVJnpgMGk/EBF2ZXQhAHJn87PFtDukodGt2G5Ga1C4n6UT0NubBmOQNyJDmyGmc8B177fxWeazDYG1gN97YuZO1oYL0RQ6G9Gqr0YCHN1m80lZHUIwdjIqXooaXMkYhrJWXwFDIBaKVhtvVy07EhAZgRs9DYEQEYY47MaL6QIrbt/em2nH0Gu1qk09DHxmsmwhqL1LIfZmaOQgR0aeC5wiR7WqjXtm6lDX6rU4O1eBMAzrqjnnqzBejRegXOpycbHbTYmAteharGbE6CmARZg5jSlGMfh8PJzmB/cqEsBCBGfTbCTSjFfCEKddNARmVV3XvAbCEGKKrGqBoERutRSvKcQYpilWLZFJ83x/++76ciIrF1PaDa9UoZWCTG9fv3l7+8YY6ta8Tc9QTEMga9aH+1MKg9YEZLOqGe7I1dacaxnCkHbjNKU4pgR3crx48WI37QRyka5iCHCklIYhAsgLpkv2TUjDt/yyrSNujQg6tyja/Q+JHBCFZSnaVu+57wzq/N7WDUCzRpENs99ShKazRps7Zg/CzWKCQeLNvIJZmqokGcjIgT5M4TjH7acZQG9ObOey5R/bDeJ+3u/7bXLGfdABrPNAuvsmgru9XDu3jQS56Q9uG08bv+wLlgGDqoo63JkDB2n3VDMGIRMC7EkG/3cf7o//815YdLMcPz+C0PnDj5gWzJrBOW85gLWmCMhZGMxN/ROAwc0VLnD3TTiv1tpu0qbiek4DatWcs5vFGPa7XYxpnlf8BuuVCQ8QKWvlfnmbKsQ3dJi+Pb49vj3eP3pVtCWrv+WuoT7jhQXLsvz4xz/+5X/1n/zo919a1SAEoKrmXNRNxihTOKzzr3/zyV/+/GOE+uzlpRGteb16cfXs+gLidDiV41GaYqGztR2+8rrShQyi4de//Oy4PPzwn/zw1atX3/nuw8e//NWy5iGxMjy7OqSnHI9oCaWuvOsC58Yks2paTV08DQEMiFOAs+8upt1uJOZ5Pj0cy/c/elmzCjANYUzCnrUs67q6J5DvphEpIYqhHA4Htzo8jzEYfCFfba7DxS6l4aPnH3z/2fc+/qsv/vTf/OLH/+dvsGLYXy5zJRG3qpQBAz9uJZv0SBf7q8VrdjSlkWJJyAyujuYpR960QWOwvl9Y0z7u/ept+AjY3DPQDVn/AfA9bRQqnDcy/+ojzmH16U98+ymaWkoDx76Gj1HfrfrB9qQObKkhutwzkVNjQBBxL4G8F35nWGqrUd9bs+Yb56oP+Jylf5rYTvttjL63NFcqOMOl1vrwt/jX/+P//l/+yz/4z/7zH31w9QfH06fHh1/RFC528aP4wqZ0c3PgFN0szmsuq6NOY1qyWC3udV5moqBwSQNYENKp1Id387Hki4sx7aaeHBDHEHZ7FNd5mc1ADBGOkUW4VDPDbr8LoYnpgJM4uJzKmi0lSWZEIhIYYRybmKe1AmoteV0srzenYw6CMe7KYu/ub9ai1T1G0hE2Ew9Qz2tZlryAfbzCsw+n61fj+Cx+fo/BIdQa080LjEPgaQALrvb73W6KzJ490nS4WW/fzIc3dbmjKU7lqFYYtXPPybzpl3n1Zck10HxazQxC/gC94ofbu+jj1fMxYsAJzYEKFfCNYmkMIzWrZizEwuZ+uXt+epiz13Ut1TEMQUIYhmGYdjkXV1eqxZydZGCKbMHBqFxP+fT29k4gL54/D0O8oHB9+ezuzTGXvKzrMS/H04MVC0kkCswbD6YxsIjIiIzsa4v6m4+nPcin33n8Qrf8dMMoHvXs0J3P3K0RCgEn4rCZ63g19jZV582tuaeb1hrPBG4WR42Oqb5JbjlcrXS8t9843Lk9vQpqVLDu24cteW4lX5TQDYwIQqwcXLqr2/bP+9j1GZ2GGxQE7hQnN2u1Bgt1A58+qNUe63hE1M6NUaDDRL4xhd3gpH2Ar5nOnkGYDdanHo46hs7tD0PrcDdlKW6/tQHxj9CZdyFVOIGEOiLWyCI9om2PfT8qUp+b2xR7rUv8nR/AGwDYR7H7IGSfm7TyBGpnAnBmkb6/P3/DSvz7AlitImpX9TwJeLYXfMS00Mlg7SktODfcqpnDY1siZ6gLj4uG268wQ9PRZOka2NSNN7kpgKk7N1FG7pJmbmRtPrYpe4m0a9AALPRF0FajMbbhXd8oT9vbrKbWahZhMLgrMG5sASJwv/moT6S+d3kfq0xiZnJyIerGNuadQ7YNErq7bk6l/eMjOIzchYQ5BA7CAuG1LjFwGMSSejR3b2o1oU/m0UUYPevr2zfHm7Xedt21glKPNry6XE6HwCGQHG9X5LdaL0WId7zb7U7z4gwPpmZlVUbcDy/I0noA1/GXP/2EXcyqGoRTjJGnkKbBBVULyOf1ePeb491nx3RFL7/7fNjFFELO6/H4kJ058KJzncvh+CAjxTDUYkOkSLGUatWb50b7gMxR5rKcVnOfhhHu1bTWCiMWcmGYVgWxg93cVCs1JwWyTj9hghuiIzjkMb9xsnbHUh+uhaPLPHf3h06BYz/TFr0HDjcYbfxuQiugmTfyH3cpbaOwYbpwh5vBGo7N1LYBJ3OrIJiadnPM1kFtDohC5CRVq7m6eRKOHIy0mMFg1RmVnLr5Bhlqh59yzs6ExCnEi6urNA0cOV0kDChlBbZOn7sbNUpue29wgnN3pwCgcIEZwwK4Ivs6V1MLzGBRLXA3VFJydVeFs6lLkBBjpVLXnNd1P6SLywkUd7shBM7rqqYlY1mx5MIogUMM/OLFi6quuhwOD/M8h4BxJCe4Wzn5MmeR2Cb6EChEAqmIV/VS6vX+chp2QcJSLQghShIupeRlmWQcYiDWKBLgdTkGWFlPQuOQYmGM05QzliXfr4UCiuqZ6gnuTRlXt2qnjF2arCYgGlSAy0swRM3ULQTeTcM0xCHEkqu7x5iYOUqKMWity7oI7YIIIqC9t+Dk6u7cKUW9y9CjJqgrsLQPqyFBZi2sbWQeMAPG1FYgA6ha4XDrrjdbIO5fBBFQ4+la0xVwVmwbWxBhFoBcDVsDuOfU7r6ZD26ZiVEXjjrHvC3U0db36YiPN0cC6hYKWx5jjjaUHfCYvXhHtc4h9PHV+kbXawMG3JriAIDGEnOrIHV2YqaYpAdhg7kHcxgeLYb/XodvmQ2849d+fsvnsLAVPFvkbuIATNSUDJyIyMWYvQl5acMYyaEGFpAZrLqxE1kb9kfhnDhw694CALTWWqu5hRB2+32wuCwZb6B7xDi4pbLWFt2IwL4B5f4PebvfHt8e/6iO827fbnBqDPevjBG2B5K5CQdAqtZPfvOz42HuAArcUFuMnuf5+auLkOLt27efv/709mF99Z1QreZqx/nhQ/pQ2CO7kHHrDkGtUMmUF6yz2aJ+ITA+3NbDcvvxx796+erFs+dXL19e/+2nNxcDCYdlXbsDFdCkv5lgBBliRQGDAyEw2Ey8eFUzCCSJwZ29aiXC9fXVMAwgzXldVxweTlAfhxRjvLzYBao1Dy+fP9tfvgzTqdrlu2N+c3eb7aCamUEsKbIjL8e7wTHsd6+un3/n2asJ05/825/8yf/xyS/+Zo5xyCsva+GROIEJ3CxyGt7g2naUNgtRrYlxc0qBIhEoxXS4f3CoBJhCzc1AQK3a5hFct0JOm4cGuof7k9qK3m9X/J2xcKtOzgV2i/NPMc3ef9m+/kqu/8jMfyzEv3L401Ga85ZxXnbeG6vNbcjdzhwEIjfdUNZ2ao8w2PZ+m0jOo/8gk59lNQlum33Qk22ht3fhFAgYYsg8/9mPP7m6Hv6jP/zn33/1nfUwl9PsIEpX+yld+nh7exPCEC+ZdF1nzMtxNwyoNeelWK6He6eoJhKEQsxWl1N5ON6Nx3j17OL6xTOBVVVh8U1L0wzMSDEO4+g5x7jmUhsFr9birsxdKxMEVagaQGmIQmnNejoeVSmENI5DKbrk++NxLmUOAfv9lcju8LAcj6u5TJdJuK4o9c6XYSYj5cwXuL6MLz66urhKCPVufcdJXEJV16pKiGAwpimlKOQ+xJCCkBqbCIW//dWXt18e8qGKxjTu13wYZJIBrtVd2UkgzFKLznNWoro4wBDAsB5KLXz/9j6QvXzxCvUzzmA0yRi0iUVX9+odjAW5EzikNHz+2Zcu9f60IqDw8i/+xT9J8tlyLHfvTliBAgAmcGF30wqMyCgwNXHTclpmdx7GkZjHiz3PodTVtQQJyhaibKNarSPfwtw5EXtCTvwtxzllegpgPf3Rxvvp3yO4m51vtKePsU2OkLqUBDFRWVZGx162mxTwpqnRIB31DUwyZ3fFhug0+ADotH069/t6w1KNwNscMjVW2CbwQA5uHnrb0COIoa1j7Fubk87SE0RPYgGRN42ncxLNbe9wR5erNzeCsrMCj8GHlInbnBa+cj2b5AdxqAoxgEkcnV3k7mZqjx2OR5DJ3dtjqNssbbj8Y/rtzRN1I/08gvv9jdGTbXIDVp4uCG5oSPt84F3G7Ak21r8wU3fijSjaABzbXv/8UAWaLNfXFtRXj3+AC+HTZdq+zjmf0Sh/MoTzpF//+Pb9ydlsOQQAPNFv8YZwtenXVgBtmmzNz3KLx4quKvIoYdTX6MY72PSDN2AMAG1CYO7E3Eobanop6k7CRqiuHZZlkY4Kds6MwZrov3vT8+/68P2D6X5TbbIDIiQhNiyUiMjgWs25Cc6ZG/oEWZdy2jCFxtuBsLODnclbGE0avUpxMmUwwUzJFDS4+S5dvLp+Xh/y4fAlFbsY4xAn1JDnktdy/+U9iGWIA2IkXx7yW31XyvLqBx9+8NHLfFcGLAq3Qqr8bHo27HYPrw/vPrstBwt0aZWQFUW1mmoB53nMFMiErz+4GJzm+Wa4TF75Vx9/gRkY8Op7+w+/++HnDze/+/3vw/DpJ5+uiv0ueiUo6VqZw0QTi2jWpcwSmQPUvSzl7u1Npfw7v/u7McakpSv3ubF16KqNmLpB3bRmz+51099st+7EHMDM6GwTdA0r7wCW2talM2x7v1P7VzbiB8isAQiNtirM7A1/aCfATcjZ239EqFUB6jiBNs9KcKNGcFshqlVRGcpEhBhEwIHApqpokoPWZ8MDS+JI0RDWMsOKm1vTTBCAlLTNRilMrDoPQ9qNF9fXV6b17m4xtatnF8f7o7BADUQsYu6u5xuza5r6E5hc2zIXAQRlOR1OeV5bfGb1oiCoiBMxCUKI6k6gmGIQ1FoOhwenyMGINRdV47xmB+IwEsMdWlozbliyTYNwHNKwN1gKkBBOc53nlVngYlrXpa65LMtyOASiMu2HYYwALi8vd8NkFksu4zDwNC1r5bAcTsc12zDEyDINcR9El8OQouacyZjHda3TPi3LWuYSGBhCngFx9wISkBMFOFwBo3XFFKcaRkcGYZAwRNRKcAQJKSUiWpc1+8wgmLNSXVcdbB+vzayseVXMpwUV0wgWscfLjL4XUFOrJG2mSB2mQgdKq+eaYRguLx/hLCNX7UAbnEABXTVKH3erhnv1Ps4Gw7Zo6A6HAI6wCSdqVXe4tF019C2W1LswXOfzmjVf5fcUOrfY3isH6lTcxj98/BGwmcF7A8i25OhJhXGe5XGhjTLWW/F4shEywAoAJoACgKtxs8k8G5JY381h/KRL8nh8pRjZ9s3us76VNOTuTE8f2RKW9uzGsjrneL2WOadp1BUbiRhFVRsKSSBVYu42hdSu+jl1IeEmqEnctFQlxBBDiCEkO/rZz1e1GWuEBoVvU/j/vq3+2+Pb4x/h8bX7/wmGhUeFkMdHEmDEbNXTEIjEVJcVzDJIMh4NpcBDEGa+vb393h9+pPA3b28+ff1phT579ooYbqaahyGeTn3cWsiUyKrWbHWxvHBeiatU4yXPIKDi3/27P/mDf/ajDz56+Yf/7D94uP1JzlkLzCmEbfigZawBHMCRnaMwSYychNmK12LZ3MHgKKWspu5aBbh8dh1SNHcRYfDr1/PL63E37oc41WpmCvg4jpeXl+lWX7x4gWG9uT09PORxwjRyDMRs7FXLcrG7enVx8dHVi3xYf/b65//qX/0sv8O6BDY5nHIa01yWIYEjqECkl0Ad6jFPMTGlqhkEkRDDwISaKwvf3N4lHodLvrt/sAo4JLDWWrLHKLkogZrJV1OHxHl6osfilsycUxzQV0Li12LkI5/gPRLW2WDrydJ5DxhzuKO1Tei8e/yda/Bx13ws5nxTFLBW5zYadisoqI+mU//+tjkSsZ+7K61WaBrwj3sQEW3GX96nEqhpWTohsBBBzNyqzfcLor/9HP/b//LXHz3/sf7Xf3x9NZH6cry3lML17uJiurjcRYumiwccFyyH+xSe1ZqX5ZTzelpOIkMaLtO4i8Puzc9/rh7vH9ZxWgv05v5hFyOIQwgVXmo1sxAgUYZh2O0miSEXrWZmZZnnWhczTNMQk4QQgpQkZlrcMQ27Wu3h4eHtmzswXVxcpXQ1TakWK4uuWT788Hvuw2d/+/bmzWFdIUmJ+fr58924+6v5l3FgIZ52L+LAz15M++uovhxOh+N8uvzOCwPm43LMK3uZIgeWYYjDbqe1uKvVDCUqY2D+6c8+2SHV4rrYyVbROAxTFM7rnNcTs8QQmFnd6lrcgWKgAEWaro5v74fLdDquu2G4/t3nUEglB5HBa1ODplrqmrOxxRAoipFdT1cX+6vPfv65XOHkfecAACAASURBVACMcZDry+tf/M0vLoaLP/qjPx7+aJzvl9e/fv3m7d2nb7+ISSgh7EDRC+UyuwxAlcN8jD4OYby7v3/92TuYb0MsIIYShB8zJbeWA5LZeVkTPbmXvopdvHe4P/Ygn9xQ8JBCE8V7wnB67+7bvvDzMFqrqZ1oOVY5B2nHxswhbXSi5s23YS9uaLIYW78CfY7G0edMWojvv2HjMGDTnHHVDXYX5vP7YYcxtzvJGGf87WlL9wwTA4CYkyu6SA1JuwVd20UIHVdopWEDUJpsUHs6wcRJsekYMYioi9urVYcA4MCO4ARAOxLyJKN+BKA2kMqtSdoS+nVonyWhi4BtzYDHtLYBak+T8DOMZedaBU9IWt5T/I5jbUNOtn12tbEFmBlC5DAn7vP8vnWT0McwNjbYxpX+xm7ENwNY3xiPz7jVuXQ5M6oen9WXykaMfXKgAq6+ibhvd8ZTcK69Wh9LbK/K3rS+AjGI3Kk9qAXtjlB0Pl1P/7mLUTu1FUkNUm7XmLvoYR94bkufnLyJvECrbT/gzfeqYVrurtrmr3wTF2tUvaZG38UlG0pATh44UrfcsuIGFXcoN91iwPt4KRGsQykNzCU4U6PdQJu3zjCm4kvOuU0R8pCEgyrWeUV1WWR6NimLHn25AUpZA0jZK8dhh9ub4eqCVtRc025M7KdjGa8hIQ7DMI1jDGFeV63m0GFIF2G32nr/5gEPGnQHo8YEN4hHcJLd9UVMwWFWq+fKHPVkQcKLi+dLOC1rufvieH97/OP/4j/+4e/9cDmuh3cHHXCYj7ZWqcwYyAXkkSMxiQdRBuC11GperAhYhY0DBw1ea+Yo1c0ani0EIydGM6GojupQgrZ7yWNIHIgCqVeYOdwIYBUEKFAgJjCo2bZ4iLo3EXPT9evl/jmUwp27Ih/cAYO1aSEDc5PRIsJmXQ03dm5nCTdmELGyqis5uxkbiIS7qDNDkNeCAGcjpkgJ7EJMbg0JRXA4iTEZd86pQ9TMvJKyMSskURwE4of5eDweI8WwD7RK61pECqSG0lqX3udgiUm9pUoOtbagyUg7qptPq1cHXItZm7okgDlwYAIHVC1mHJqZK7QW5Aw2M19q5WkaHTTuLqfdJAhuXFYjp2ma8rogDuMo6TpNecz1oVYvtc4LCDpOQViq1lKAk9danCAiKaYoVzGwCJgwjnx5kRTx8nIy03llVa1KLAgpDoMoR4ncBkK1QrP7wPOplFJSCFUJUuFkbiCSbgbQ/EcdijhEnok4uNdxSCWfHCCKMUqIodS6nI6a6zQk3sXEcV1XQRB4EhGW9aR5McxIL4faWG69SdEU9Tpm49ZsiUiAwMHZlRVsLEwGVWNqzTl411lsRFJD07IMCa4tIG0t5e41iDamzY5u6mvMpEQuDoIx2eYBC2qWxK31QEIAQtsShcTQ91A/d6K2yI8NPmu/nfouQwCjW8LAAWeQomcK2/3jWwz3rU/cNkQjeHsDbX9rC3SbN2fnNvAPNcAhcKcWGqi1OvUREnrSv2rlSMejiEDeN2A8Cjv4xkU8ayQAICY2NGJlD9dMZE6GbbNjAkFhbYDF2ACW1nqg7S0/IoFEzrIVJGzUQgsTc2RYZQHcSGsiTsSXwxUjuDJBjrcznoMrylKlLkJBKRuxI7k7XEG1ZxsEB9jEu1KB+2Pi8e3x7fH/w8OeckNxTsLRt/CNKnPuPPdBFbgD7HIelWntJnISELm3EiYXNKEeeFZzYmUDedW6pHF3Kqfb+8P9/Z0EpGniECjYdHkNkmG/w+HemVWDZ1jWskILwQKbSRg8mxUNMXKot18ePt1/+vzl9ctXzz/68NXP/vpTMg0kYOq5LzmYgOZrZCzGIXCiMIjEyCZ2MtXMiVwrO6zaqeKDa+yGlDiUWscwjfHkhOuryxfPngnhcLxbTkeGp/Rwd4x/8/EXcf9RCPsYBwaCYIgcWGLkQIP6enGVp6kmTp99nv/8T7+4/Sn2l2Os4oWiIKV0KLkqpQhmcocQsSOyEIhdUhgjDV4zASxwqK1YdMlzWZe621+EEBnHtvE1XWE2MIRtS7+e/rshQubeZZbd4W1ihdAMyrawzhuhgfsyeIzyTW4HT3sl54ZTr9073LRxVbrg8zaP1Nse9CgMc/YsbC/22GOgzVvqXK/RtsVSR6Lam6L2yn3gYyNG+Kbps6FYWy9loya3s/Ktz+KtPwtvnkUMBtxVUSuzBGFwuXmLv/izT3//R//09//lP/3sl8mLUdVB7CrF73z3WTnVpdY8I4zgwFNIuxiCi66ua7XICDUIh3G4ORQiWyqoYi1Yig+RhzhIrHlZ3SyKTCNLjLtBBBaZYuAhhFK0Zq8m7mpGaF7eSRAqu3CU6liyLauXGtSCO4hst0+73SThGhhevPjw9t1yPH72cF+HYdIyS5Fn+8uPPvjO8rC4KjGHUTiYhXLMa7E5Y6GEIQZzFGY4iiLIDB5SjBACKECqKmrTwljwAN5xYnHP5WERiFKG8DLPa16YhjQk5uiqXgUKsUAkDArGljmB10I1l8QBQFA2BztV9ca88GJIOqa4WI3sCh2nHfEAhgS6uAzXz3bXzy5TSPPd6c3Nu/W+6FrJ3ISev9xT4ulqTJdprfPD8WFdsoNSCLqUgRlOJWdYJRaJaRxSEDEogWC+lKWRLfqyoR4styVJTNzB4Z7ZgTbFp7Yam9hoX4VPKDX976HH1Y650tantDY82cSi3DZ6U795m65HhXbMCuiTsd4aDQQncAs159+57QPkYGsJ8RnD2ohdDbayJvu0QXfY2FnedI8oAk18jphcSMhNINrVOBh9FuuspdggkDbGS317cQJgGxCjhk14BkpgGBFM4dS4O+eQIUAjQGATyyMQda10JzOwuhMZMQmRGYxhTqEHqn4J0GGpNs4c+nhxv5i+oVDNILB20W7vuEkDBLvoDIi3YNY+3/Olat/0Pm/aCLNP4+hj5GyeZgQjExA7kRsbB5KGtfdLRUBXsoXLVkhsARrog+ntb38vBtbTigVbwxm9LU/vP/J81ujS6dvjRXwjDhIRmdrjm+zsLGpO574pFNTiMIMgJKPIkCY0bJTaHKl7n+EkAkmUFCMTQ93MwOJEoM72MzJnB1kuStvVRxviaNOYaiA0nKzRBJxIrQsCgx1EhSuhSed6B99aTS/df/2M6DGzQjtSBXd3rb7dy+dT7v8XQgPi3SHOMAFIHWZKUIeTugVLIbiIRXV3mEsIVCl4XI/z+rDYveeTUwYVYU+aUQuGMKRwPdCY59OprikNQQZfS+AhpbTMq6uHFIMUEmOv19f7VOKEiAeNLj5nAsAUmDkRi5iorodAIzHpusBtSoO5+tqsAVN018XKXMtbPe2P6poQh126eXsPQLNNYwqIx+ODuSVOAcGLk7G41VxJKU6hHnLR7AIiqlbHaciaYQxrzU3iPrLel0uTRmjBMcmASBzbPdBH/kHMwr56Y4xSl0EzN6cm0e9s5mFTXLa2UttdvzkPwhuy0z70JhPfVi0ROYTJrZkEubu0DFmdwrZe0EK8AAR1ZzJjNhah02lxBgWnZlnqJETCZNxHpq1R/BQEproR8x1EkAtYrh655OXO19N8XGqOSDEONLKdMjcmoKINMsC4h3Qja5P2De9FbfNaXgtACFiOp3Eal2XJq/YFrmgOroCbVrdSC7hwiCSBWSiGSKLLStk1RgSJpuRwr67Z8lG9UA2riqKsbmnaR0mD1sNSqiEYdJ4rpBJHJ6QhgGwYR61lGq+CDGQz3FQXER6nCPD9oV5cjc4onh9Op3mt404kMY/MMVQvECIOWrlWDhjnh7fH8iAMNQ2DcGQ4cq4cgrtD4OLEhIRxGu1GI5OqT9MocopRxjEGITObl+XwcMzLcjnu9uPl7mJy1SHFQAiEMcQVnnjACgmxrMVg5tXJyYhIiGBbr5i8TxYHYoNHEgpBWBBQxXJZiJqYO/XH8pYqEzOTOmlVAzVmoPSGFMFR68rC5I3q5cRtKZIMIlGqG6BdR9ydrRt+E9jhWpWIiIm4N31bliIirUXR1DHPRlAtSBCEiGCkpAbVXn8QO0k3Au18w7MzTEsEmqygi6t1m+KWbLdgaUpogzQkTOLqXtwBMiIXN6rVqbiE4FCrvqFi6GlEY7c5yImpSZQ+FjYgd7TehBqIu8W5uVLDmxpm1i56I7GxP5Yn7pBItbkXESAEIRdyUG2sbrUOLTrImJVAobO1tOdPrgA815XIzYrVnEBc8PLqJWsgT4GGv/jLX+AafodQwFzVVg0GGmAJRqBKyBvrgLxNDDefx14rPW7f+C09qm+Pb4//rx5P2qgtPaWtqYutFd8h737Xo8H85Dgn8h2pIPFikTkvq3k19S/vUCsVsFWuldMuMXGK9MHLq8urq9ef3Lx7d1uyTBOVSjJEinox7d/d37368MMv3r4hiWU91TXkEy/HCkOPtCEu8wnQlESImfyzzz77wQ++//LDFz/4ve/97C8/HXa8LMpOQYg5kHVf9uoWqXAUEgdbiBKGxC55KfAcAmnJu3GozlTLBy+vhhQZZFX3w/56fxzTsJ9GU5uX9fbmuKxrCIneLMtvPvvJn338+3+wozjs95cf4sNcv7RiQfhiH4Wi19PlM91fyvGw/uz/fvNv/qdfYwanyRZ1rTHx4XDHFNVlzcUJVqsQBeUppsRBNe3S1SAz7MENYK1FKVNZ/ObNO3FyRclVMxhCDisQYo5EzuxCTfDGOmXhDGMZuZoyDAA3MUenhvU8Cr1v6BSfy+oeGbuFLD3hC/dl1LJKYvTx+5YrUi9uiHuvpqegvSHiPd8nB0kb2/Ht+2DA0ett9zYK0Av5DYuiDqs5tBWeAM7IAjE9CduELuGDfubuIHezLiVMALhxScjbSCGpFrMKEAeOQdyKGpjwl3/18Xf/7fd/+Dsf/N73/tPP7n56QM5LLnr84MX1OtWF4xHpalzWXLXUxHGfLm58HoJUsvv7m9VIJR5XiBgJqXs1zsVjnFg1xOqnZRhTGpjZJMTdGA/He1DwnNm1rlYDMydnzVVpLTFJGtLuMpRia7Hbu7c1u9PIMSwHu39Yb+8eXryQD169evb8lfAQZDw93N89PKDg4uXl6WBBiRZnwwfPny1lKVpkILDN9bjMDxww7lIStqXGGPZD0l1aSyExo5JtrrYy+MMXz463h1L1cHd6+Ox2ALhyoOACIq1Zs88Aas3olR5rpdZyhbOQwCkSr7fHeBXGFA2rU4XXj55flJPlUsAiJAXOgRU+Duny+b7ePLy4vowpZglvbm/SJcdkw+CBaz09zKelLvTuy4f710cAV1dTHCIPzBPSVZQx5IPOXitKimPkMdEumuQlr6eVGIAxbEhxGIaaS4Mq5sMCJ5KQaxHAzUy1t8MIDGHmWhTUtJce0wk12/SmH+HfDfx9XKhKtWWwjM4FIjzmsk3au6FCtKWaZyH3hid0EKS144w2LyKCWlPioe1m6Gfi7gTXTZh9oyUwdw9EOLhrzfT9wUHtZm9AuYmdxwWcidkFzA420tZ+3jDiMydnQ7AeuQ/u7+df1EkQrc/bpsoU1m2kqWEjjjYOTA0bgDV0Da1Ya14eqNXEBUBoakredcUbSNhmxNrTuTOtwEzY5HgNbqbN1bH5C9WG53gTT3LeQpOaE0gSg+BqDd3qSE3rAMFhxmBD0xPbVsGjKvy2FhiQ/pbhRMogTzGZm7lWWFODa+BOwx3PQ9Ob7g96qe+O3wZgPdn7e/D9RgLXV4I+M7dPrEFX23t0VW3gjqm3Fhcz69PV3l/ta68PMMlGK2iXigCEFLTpcLUCACLMDGYnJrIOI5jBwe7SaHatdgQKnB0CaqUKGmTV7Ly2RMfdoAprPvcc2q3h5rldj8aZa/xcdyNuku8sgds2A4eqqpW2KFnEdDMAJgdBGE0ay90bbNKaOY3CRU1VThRGRo7qElmG4MkrQ6nUUgOHMKZRBkzl5t1N+VJpBUe0uBliJLPDzf3lq8s8r+u6QqiWSkKSMM/LMudhGtwoz9nhZaluth9261yW44oMDlRMk0SJQYJQ7ClgqfV0uKumIhzHFENcDnVe5qFUCDkhsowp/OlP/vyTT37xO9/7fvQEY5ywf7k/rsd5WapXNR3DIBKYijq3q8dOXlGX+nB7n6nwPiL2FhsJc2J1hxFq00I2MJMA4k1mpq9YRteJ4g7xeEN22Z29eacanJhEuEJbDmPumwJRw6ZawOF+/7WJ8GadwCQs1MJYgwqoL35YlwRvAVqMJQqA5nrZsh5XN68NRHcz9ijODCq11lxBCAMPQ0QkMIsEoKyLYXYWeFE3JQZL45TCGbWaM3JefDaubORhiG02MIyxxGxzMYLDhJ2aQ4cTjNBEJpyJmLt8OQCHNeYzQgzC4tW9gBKiSDG16tXMySRJg0PMrGYqKzgSC4cogFVdrVrVcnN3ezrhcIBlYAUqwHj14sWD2N0dT5c87MEBIUSLGFLRAqjDdRyCMIP84mKvOU/DmGJsc5gxSONpulNKMQ5p3O8MtdgqplfX0zgKWNc1PxwPbnSxu4oxkcRqKGq51GpVYozjxCRaLeuxehUQBMVMzaYRqupwNRWRSXavPsgxjsMwgOm0zOu8VDWW6KBcigPDOO52OxGxWs19GIZxN2JArkVkyzt7BFBqZqs9rzU3InNF9T46DbeWQ1SWgA4xORyu5nBVBcFFALaugGlu5tQa9s23te2S3g0nga4ARxxTCklO62pmzCzELRo2mSpTN7calAMJSbMBbqqBZg1TJYIwd1SLiAKzSGSE1gdWgnhVSBQ4ebFKcInM5gptQI/3Djy6uInZpt/Y4z3QBOjAYBb2umFojcUr3kTRyQ0u6s7VWpgFqQPVXfpoJrW2U4sDDXgigpDXLc9p/QB7T7JEmu3H1hnb6GXnLv0TuRURaWIMTg4mEuLQ4w8ao5MhLSlr7P1WqYCIUF3dobCqrmpEJMKBY+AQJSaJIY3TdHHzdv7k15/iLapjlAAytdr6a+iXC1vlszUUu4znN+7w3x7fHv8oj5ZNP+nRn7843/ztFnfvsiu1AoZc1UESk6E296vdOD5/fh1CfHg4fPn6rcQQ0nh7e/fBOOx2Fw+ng0iREMZxf3uXS7FavVbTCnKHVVVnCIs0Skwp6o7qePfm/vmrZy9fvrx8Bcvcpr+qaaTAzO4ECAvFQSjBNt1cZjJnSjReJXCd0nB9dXV6mC929uL55ZCCa4XpNAwvn7/YjfF4OH369maes6kyOdFoPtzdHu7u8Gf/1093lxf//D/80fXzjz778q1DmdWMhsgffPTRfppe7X/0Fz8//q//85/8/CdrGPfzUQW+6iIWOForymqtHDyIlFKKgZlSjKd1YZIUUwpRa4GrG6rBFIfDMYVUailHRXVvSgoE74M2narbKuVOLH0SrM8WSL41W/oH2dvhX/24AZxpeNvP3qfw0RY5rbfA21OscZCf9Ob7nwZ02RI4gZ+SEB5fq531V1r+j4X/mSyyPfjxi/YuXN8bifetQEWfeukkso7etnfnfYNgZq1QrYA0Dc3zCIsp3rzDT/70r/Ly+n/47/6bGk62vluX2zLnNd9dXb3gKemomunN7d2U9gIZxv3VZV5rvl/mZTksdqcc1xXDRIFFVU/HZZ6XUjQISYhpGig7IG3TJ3jOCxDMKhPHKCVbGhIRl5qxKHEbEfGcy2nOd7cPtUQWXhe5v19ffzkT5vlUQhiH8WJe51qXm7d3x1Nury7Ca57v7m8vLvdwY+a8rK6mlk/5pITLqzilKaV4vJ/jVZyGKQRZy7rUpeSSy5xkYBYySjGVY7579+Zwg7yArai7ZhcKeTmsXPouHGDqp3kxg1VrmXF1F1DOWq0MkkIKQ0oy4Lge9y/HGz2sWZndI5maWbVkPnrmVS7js9+5vnp++clvXj8cbiTZ1bMgYsvpaEF/+fGyl0EXIYpeyv3tDJmxx4v4zB05r6WUEMQtmhkxhinpsR6Pp/k0wwH14nk+ndybdo4wSUtummCLNaE0tzbYRUAj8huMcNYDx4bT/HsyjEblcVNtvc3m+GjepL29r8CmB2GmnZDQSQNGGw9rIwZ1xXO3DXeiTa3iCfHo8aQ2DdlN1op60X2OEr4BT+7be+k9TjZtQtneqAxu2jWKmJnZzdVUzfrpbaHAOvD9HpjXtbCYYO78eKobMN1uciIiYrbNtwnnDK5hB+dhCNo0OhxoRDSCEXXbuSZLhH65zifRYUd3crT5UOse4+bkyl2fviPhRFvkgIBAxIaeCneECZ2JQ755RflGbkV/jwx0zKqnvWBX5qavI8SCQMAmDtWuYP+0WFr+vSXl/uTPFlCJ4P4NANY3YlXf2LBt3/w7sK12jaoqmlObbyWc6Tc96WuvD2/bxXbObYDVW6ubaGPsurcxGq3aIFRTVzWz6nBPYAOn5ibPEG0rsHVT3GgTaKHmEd8rGu5LQIRYuDXISjWHuz3KKGFbE/5kBRPI2trQDqty+3ZDlB0I6PWrNi9nMNpYGpSsDRluvGA2AAHVal6yF7PoGM0JZjwvi1FNKeY5Z1QIqHLJxSrtp2E3jIdieVnXOsck4+VOGGuZIZjLfHf78PxCaq6zrw473VXN0MVuv7x9eH2PFVnrbrdjJycUrVqKmhERRXLyGEOMEaD1tBatRNBcXdwBFzb1Z1fT6e6EF3T5/IoQPvcvJYRp2pdTpkoiAqKqtarCz/gsuZlXzOvi0fYy8cCL5hCCBlNXEvPgFBjRyaQhmnzWSDbAkDU7Q4RcXIRAbGZOZhTAkBhEWBv/hdBksdu8E5GoldbD2yzjzrdOixfgJtfMbdoQG9bpBHdj794ADgO7MIUQYqOoMFljIZqpmzZomjgwO7OoZZg3LUYAzMENGYWciAShIqFB56oOhhEgICYE5wAeOCRxeFGliJgiQ6zQbp9E5fD2vubCDCdmb3wcb/7WW8OPyKiPsQYgAgYExBBDCN0nRVxiUCKt5lqdEMch0oBgILdaj0el4I0B1OS9hhSZJdwVKxkVg0jcj+JJRA73D6B6ONruhP31sLuQEOMQA6aJvGo1rzWlGIMAHrlNA1sQCjKUsrohSHXEoj4v2VHiMF5c7VbdLWWZdkxUq5ac67ouhFBViXVe87PnrG5rrWtFIBsjM4s7DUNyM2/8WcJS6vUFSllDCAQSYSdcXOwljCnGKKHWWkzNbRwSS2iICgmraff6cxvHYX85YYdai4TQ+FZ+biU9CZRMTkyBg661lOIZyIRKqHA1pnAOtu2Da1aU7XWamQAxe1c4VyMn2vRghbrhSPNJEFDkpmgCgImsN6L6Br5BmN7jFIPEm/9n+z7TWVizgbfOcGYOFNjIHa6u7kxsDiaOMVCkWGvV4nDnBiz37ogIN0TOFTBnGJjP5+bu3UXJt27XYwOAmPhM/27NOPUaJBQ2dILlZv4Hb0zhZvPUgDwYGW83P7fJHNoo8f1VWwrVjFrOw5Hb5Lf3cEXspGAWcHUDOYuzgANzdy/pesNtH3jcFtvt5whRzE21bZQAIAhCQtyEsIaYxiGOy+n46199igfIZQwxutXazrdFPWrBsOP134JW3x7fHv+vDmIW8XNEKE3gwolEXYvVqjUMciWXOefj8Xg43A9pb6SHw8NH/F0439/dcwhMMaVJ9abWYsYtP2goFNxSCh6Zydxyrgp4INze3r19e/P97/3gOx/+zmeffiERpjA1F6Wt30wkaB00pmqotUqpBg0xSGLmYTfFGEWCX++ny/3EsJJzzSsTpiF+56PvfPzwi9/85vD2Di+f40c/eJniVeDLq8vp1YuH37y5PZV3Zfnui+fheRmYTqCViXbTdH31coqv3r4NP//zw09/vs4LXlxezQ8zQaFGVEIkbkK9rBKDJFbSYYREyaW8fv3FsJuIaRhSrQUQc5eAGFFqvto/W04564KzluIW/x+HoJ9gQdSrrfcAoSdln/dOpL//iPZshz2+mG9PfPI637wq2hySE+jr5ryP7Y/WSP3Gsgg419v96V8Bzh7PwLY5nz4c5V/XgelzXme2QX+7jX9s528I03YdH8+QuOZsXiRREK+KTz/7/K/ffv7f6387Dd/jk+Xl7urZi8K+D7tP79588uvP813VA03js4tpp5DWahEJTKKGUmqtkIKWeJjZMtfTcUbEOh9zWQMDxOICkBmW+Wg8qEPSOHCoq5mi5Fq0qBpLKEWPp1KrAImgpZQ6r8siyzKvFUQ4nZa3b27gJDIeHua3b29sBRilLEVzVc3+btwPOZda7eb+FuwUnAOmKVyky8t4OQ7D/fwJX8QpjSMPo0UcFJoNBCtlWcqao+zEySoiM0ewS1k0n2pkJ4ktcRIBCwmClZprSWEYhlC01qJKBBgGxDEiuTCni6SDx5eMpZTVAEPalmjEHI6Vw+7FMLyafHAbZhnnZ9fhww+va84Ptweh3UVQ0qFWgjq5DCIWKlhTSIlTQaZG/gpYj8txPXiwOte1noaLYZ1XNDEWbpJIHd0MIRBAJO7Wm/kbJ4BxxhCs1zytZ+9s5MS/lezy9AtToKnSe2dX8WZIYA22aotWt1QU3b2ZO+UDRM0m29sUTL8tyIkeoeSv38WdwdAtOzZi4vsnDHSRuK0R2P85m9QBoMZmIRd0L3Vnt+petYWCMxzm7m5GEtpLOboAFW2uROcYxrSdifdT3d6FOc6KVNud3SRpzoUpoUOKXcCXwN3rDkSbL2lvo7qf1eR7N1zV1d212Qh5o7RKaNOZ/bTI+cyt6xwHcu7pcPPdZm+D2m5MvOFrTnR+aoOwSBy+9V6atDmDuWfdbMXaR0pEwoI2sLqN4z1m/+hvZusEAESPANbXl90Zm3z6zffWR0NPzXhTYieQkz+m6WZqOqSUUhKRWuuyLLWqk7/38fyWg4hqroCDCcEhTd0L5kZRYkwcxNVKUVPNtRBRgBCRG9xgXRwGRkRGAcIIURp4RHCYqVZ1t1Y1bQiWbFCVcgAAIABJREFUO0BDQGg8vL5puYOZbWMYtst4JtPZ5snYl2nbw/h8Jc1m69qTABRqJtwqTG8vws0oWJpAeK+sWg057oYVWaHq/VeEJJy4nqpFun72Ml3FIx8/P36h1aCwYh6dhMhIi8MphCHG5FLdkdIA4Isv32BHh2XOXmpxPcFPyCd99/rucDphQKJYq5JCvZRmzymAAzPQhntYVC2v/w9777YjW5Jkhy0zc/e9d2Rknktdumamu4czpDQjEiAkEJBA/oAgQI/SRwnQL+hFL3oXCPCBkABRICBCEudheBty2MPmdLGruqrOOXmJiL3d3cz0YL4jsy4jURKfpNoFZOXJjIzYF7+YLVu2VnUyYvSwhglpccZ2uaDh8/rl259un/30d1BwuT9DqW+NjL3a2c++OjoRS+JI2UYWTMbEPJUiU8rrWZxYCG401PAVmSQS54mwkTe1bgFZdnEScJJUBCUneOjNsUsI/8PY0XtTcwNBHQMgZZAJHM4ODfJ5BxEkB4hKRKBQ7hzzyi0YV8NhZ7TxMgmH6S/p1kxc2ToMDJgmAU8wYwLlJLlIyfzw9QZD6Pp3srWc05zzIRNRydNHHy3arG2t187ae8QnDIg7Ix+yTEkKK1Stm7pZbWu3hjfHN28+eTPN0/lx7U8btUZwN0IPlqe1ZsmchIfWIDMSUMihklLOOaeUs6zRbuV7vhyLrqKpW2ucnRe8OS7TItt5a826XnLmzOSw3tUUrGAWVbusJ91qnmY18+pdsel6OuPmML15c3OY8zy9Xk/n3htDhdjd3Lr21XpNNM+l/Px3/rBu1QyArLV3vX86nSnRzXGufXn66vH+oQnjMCcAaZ4Sl5Szql7Wi6TkQBti+lq3szjYJU8ZhHquMKSE2yN+/3d/nnM5HJbT6fHp/HQ5n+ebN6aOjDJPyfL948P7xwfvene4gftHr99MZVLXS91m6XBPOYkIHK2ZedOIJYPNG5wmKIOYKKXEEEZKlLLn87ZZVyaUaZZDWusWxZCg9cWay7uNCMXATFAij5CZXSmISZpm2RmBIECSpKXIkrZeW1cw51yczJp59PFdIU0mLqAMEge5qakrgVPKwhng5NYNcLemplW1andtqg1QYAaIJInPOS2ZmEDUSYefQopVUSk8RK9VYzhD4eyDiYVdZwvaDR0wdHhhZhYVmJiJD9cOdjNjYRIww+QZ27laNDtp3IpuY2FnBL1WIAFfRU8xODopiXzXxQrxAYAY4jvVaY929mgOQ5csC8gRMvhx/rGNp5SIKVx8w3/W1Y/LwaAEJxIARMLM5q7dVA0QpkRI29Y///wrAGSkbq3Vrk4JDmCUxn48fjx+PP7dHBHCm6kTtAP36NXr1osogCTy+vXd4e2xZfqjf/2v3O14vHk4vfvm/aMRMcu29qenc5km5iJSrLMpkzNRFJGYICgUbFlJ4mZ9I4Mz419/8cW5PX326U9///d+f7u0e346n7bWzd3Abl27gkF6qoUnElJztbrWLSeZlsLit7eHeZLHh3v381RuCK3XS++bta333tv2R//wH3zy0Wd/8z/+K+6+rvWrL758v+I/+Kt/3W17/PDPcA+8xuX8IaflZz97NWXJ3N7eHj95+5MlvVnw7/2dv/2//I9/+59dvkZO07uvP0xJRBwOde/qwDpKQSzm6oKPP/6IMn/++ed//qtfffTJmzLN0zQFs0Yb7pbDNOfT08UdpuH8CDUdteBR8DaE4cyeeNLeI/JvUQf/Cx6xD16+7wned5KcMBnnoWM7PpiJMARVomYd+2UQPLjva/4z0eOHB1f8b6eS/UWnGPyPPfv9/sWOEuqOwoULCTNib4GHPTe81/F5yBxFG5CqgYR5hqmhofvTN8CK/+q//m//i//yP/3DP/xbn9rPPmy/+ZM//6fvT+9nLlOe3q39j/7Zlzy/+g//2l+jMl8ul9N6bnDmrODLpTLw9Ggp1bevl9vjXZaltm51e3r8ALLXrw7MTIpAR7YK506Sp7JMM0+3y+l8utzXdYOa1n7JmSUtp6fz09Plq6/qNB1evXq7zMx0yeUx8Lh37z68e//hL//eH6zr1r2WGbXifH7oDcsN0kSK/v7xa+2Ay5zL4bDcHA85S2GxJ356bNimfoYXzweGcOIujCkj+UxZDtPNQe5Ol/7hC+Bk5MjcbHVUo8wwuHZERZpY9WyE6NcRFk3qXQMN4ERVal8rL35392p+O/9k/vjwW8vx63f3D4/qnKYZTN0aZRxfHX7+l3779du7d9989fZn8vqzw5TKUsr7r1q7OMHY5nqm7cFwMZjXGVzQa/+G3nXzfJugar2bGi5eW+NlFed5Obw5vvrw7p5ZkqQsieDb1rdtbbX2bsSSQGaqqs9TjaCIlCxaxfzF8BxK5teh/v0B/4zSfu/wF2/WtQMgJ9NoEBkDlgDYUPNmj5KdjYG+67p/Cw7+3iEsFnrZdvV9AL1wjntmb+2lv7gS7ESt/WxhHCs0hIj3yXid6RFpXklp0WF8ZXfRs5qVAeCxdlFwCcZyAjc2xvO5feuwaCcYOCIw7LZpKNqQM7mxMOHaTjOE/3yYNAK+u9tZZLg6WKvxW222x7b7NRNAGF1wzxRTQFCmTAkg66q96ZQTBosk0hySJMIMdQ+erbs5etsbPp3gRCFGH/dRnIQpsYR5+l9URHheDx2O9HIEXJfjl4pX4/n90FpM3z6w42O4IpHf5hhed4Ik0sPx8f/q4NHhd+1MBQhQUCJmTpwM5gYzmJl1a65EOSoWgdTCQyqFGJyYmw4UzN1N3XqHEyTeOUrkDL5W7zHMKZ0MYInN1G1XEQuKXbzVfk/GBnZtojQ3Ux8iNgIiIAUS6W429Jx5n64Bae+QKgQkvm2bFaNElMjZ3Vy1u5qRgUvTflyOF956BROmpRhzb7VftF+26ebgVJp2u3QpSEtKi5hYpUrIjLyUUls7tQvOoE6Xx3Vba0ps3UoqTmYq7DAyOHi4IaBtncGSaCqlta7an7XjCK6QBjc83j/OxyX/Trpbjg8PT9SAHvMY5EzkLkwk0eFDYbNL3nvnNmTwtFvvBmiaGB3krGt3MRWYGZtA4O4Kcw5dLHX3bu7ubOTemWWaCzQk3Qmh3B3q3g4QlIYTpPNAkcYwQ8xeJ3EeolOjxBUj28YYcgDDA2eUBsHjtSxA2NzHDDY2CIQ8hm/YbEZyHl+ZQcYGb9yZCakIs7O7EE8Cg2uLlJgSkRCJGGBq5tpd3TzQaxe71DVzAYPEKCl2Tiw4WgkZm3bqTORhmpYTxJtVLsLs67apqprGiqrqZs4kDDJth8PRzlirmTZz6J0ThAFtXc1ySmbetlovag1CJCTm5D3khoQoEbcEEiNv1qrVrR6WaZ6KuK6rSrQEmxdB57hWzyJffPm+t6429CC6WprKcljKJE43D2c5n1USzHrwWdy9azcTBz2dz2vd1BUCEVa49ZaQS05ERKwpgROm5fD67aunx/uml21r8aC1d1XiRr13UFQlhEQgom5GcMK61QWbz11SMkI3g4IL+pU35zAM195B6Rm+IwZXib7QPSZ1dkmiq8nuhhqLTnRXGJx50I8dToF3E5yC4u3OzkUMFvKKTk7ZKcX0tI6eODOTg224lzwXkM2cM8BuZERuoT8VVHMwOVV1rXB1NKXaVWEd3gADGciZE5OiW/OGfMicGSmEC2OVG9CvmzEROAT091nnTsQ0iNw7LQy7cEC8isfPY+dxRzfLCUTESdgR0rgxNa8YHoGIg0SF0R4eVWwFixDpHnMEvZfMdx1T4FrvcxJH34sb5gT1jngEKfxObTDL4r32LuPnXfKaEYV7KQ2mdpA2OYhpqtrdFG5kTiJT2xjHaFWGm+dClQI0N4AQRpR09cX98fjx+PH4f3gwEwu5cezQEdJJSjyo8i5JEqHDfvWrX57PT4fD4rB11cNtNrPew8QY21pbtRDMDHBj5wQ5w6pVBkBCAkqs1cAwx+l0OV8ut3d3bz9+c77fml4oSk/BpDEFSm+eujNgrXd0MFnmPFEpCd5NrbfzXPJchKGsVQgQ6rWfT6e5HAm0rlvdmrnPy4371DZ2FH3ickyWe29P7u1443c3E3u6XQ5LXgQ3H76UX/yTpz/75bn4lNLStgdZjkQqCSlRr05gEjbT7gpzVRyWGyb6zddface21VxKSsxMqsMvnZgBqnVT09EOAdqFarC3+0Qjj+/A1k42oBdZx8s8lgZl4AfToCspA3tS69+Gh15ylUaIH//fv49tJZJUCjJBYHgjBiZiGknBd+0Fvpty/zDUdT2hPZceu8S3XxjObiPsRvQP+ZBywTWljtMFWGkUPWhUiEYvZhYxEnTq//gfvf9P/tb5d//Kbe6vt28+//TmE5748XxJee528syP2/qwtZvlsCzHpt1cRawbq9Ky5MvW1hWmktPs4Nq6+tZ6TTn4L56yOBIb5qU4ZeNpPhxF8t3xbnooik4nN6h2U9Ps6iDhAqrarW5dLXdVM+RcCEzEpZR1a7UpCc9LAfW6GRwKUHGI1woi3N0cX796nUi287bVi2mv6/Z0Oh9eL+5MhKNkmYnQiZDEb1JJWO7m45xuuT3iDFKwE0NcHd0UUbAOTVsDOScZZhLeldzZUhZzl4nzjXjSp1al4Kafvvjw69slLZ/wR8dbeYfTZetoTpSFROjmbVrelsrnKue89DQxuq6Xy+W06YYO3k7dK00y4VC0bdY3zyZJeu2Xp1NHWq2uukIBHaloSimCxtY1M9Th3Ux13Vpvzc0H9T0Ghjvc6NoyFWSUsPcbo2yMviuB48WAfAZwXwxywuhCCnI9EbnvKBUo/BcCHyMyhEfCCLmI1ANu3se/M5FeSU/YA6ofwLAcJCPkGl/GFdk+TXdCz8tpfy08vkRzCFB3clU1d94dSK+mRt107/Abt3Dv0H1+R7r+Y2eEwV7ePBr38zts0/FUCAERxW0YkbIbnPcuhJGl/tAxYL8ISneN+hGXxoYUTI69hXnnOTnMEzMGmeB6PRAHOREkY28oDQfLXW8nvjo7OhSh+DECdlg0IQ5Rd20dQiSgFIlz7HY23BmvyyD2RY5GKwQIib53XIegv7j9PwhwhqDvtwCs6KEaho3jfbp2VIhIq0275ZIPh+W+Pvyfl0/cPXIYEH0rJndwEiamIAETCzElCEnXpr2DFLyDE8SDgBP7JLEbwqc8iGrBxNrzoMj9GYzm3UxHesnhMkpDKskG1Wicvu3IRgxAUEqJKBq1wmVscAFw/Yw963IfvGB6Ob73IWiw6CptWp+9GRiShDOHdrKavn9/fzvfJk4QRD+zrbatF7J0uFm22uSQQL7VNSfJxMHSSVNiEVNMU1EA9YKKOR+oU62NnbtpcnM4CydQ4CMwIkAIAGvt3nmkjzuZO+R7YMCGlJJ1t9Ue359IGUMB0IjErRMTEosnIna33VwNcPRurHANyf7w2oSZjomanDKSsIe4vhArQ2FKZsSZjaJnSqFoWoUzJSaFuaWcWNg8AWaiXZ0NNCwqHT3Q9UHAkGhG4rBLpuvQji0h/FCvVcHoaXInN4cCaqGJHjrYAkDVDAYL+mwmQ4jeOJCBGiA/2LlwcYN2UEkAde3Mcri96b01rd7JyFgo5yKZVVRNe+8GdRkMQ0rEKdXLdv/4oeRJZlYV33q0oEV0BaDcFMcQAIsl28k58bQUgNSU1CixZHazrh3uiYWIu6Xt3OA8TZMTqrfHp9Wzvp6WkKyechGhc+tbhSpDvZtahfUOg23NYZQJmZg4iZDrdllL4mUpU0luKUW7JWzK0lNiwLr1bl//5oODWtVazUFlSmmGWj3Scnt3/B395Ot3X6lrQmncU0qmcKapzG/zzbsP70+Xi5pxRp6LeOogMldrquauKUGBTz/6+Ce/9Untl61tzXSZCjM93p9JMhGt6wrhVMrx9qbXlqesQDc1s23bvKBM03yY3VJA1fMynbftudJqMBgLs7CHrpQ6G8FUXGBOHiqGbqZqPTyWiZgcRH4tz0Qxx6GjykLuFEubMwNMwowhv+7Rnuzi6qoNLJwpm8PUohKA0RpH7h7BI+2VKHYwMaUQJycCW4dVa1v3ZrwqNZghvEeEhRNHC62p9to7u6vzrUgRJ/PwFvQhIEkGxqhW0ahiBa0sFhQOBXVjC0tZt2A7W+z9g2AFcyfVLl5AxMKxOyr3wYnCkMtlIqhGncKFAwO17gbLUwoSNkARP9HY2YOvNWIdH/6KQyY4iFuqSmLMz9ugmXX1+IHL2AfNjZ33ws7QRrycq2QRESIwpyRJJMFH4SQ2cFMQpV4ZGd7JFGqW0lWxEQMhx18Uvfx4/Hj8ePzfO6J0DYzgzMKRBeiq4pFRWUf9V7/8xdq1ts3UcrHb2yUyAnKutT8+np+ezq2rarfOvZl2OHUED9Olu8JRGJzYOszgitb9iy+/+viTt7/909+u5/71+cEVziABCUFJhF2IQKZuwe7N3snYME+yXk7aPCe7OeSbQ1kmTkKJxJmsd4KdHs8hjGHqScTd1FiVe1NcML/Oq/acbComWJep3B5eTbgRzG+Ov/3f/Td//5d/+j43iGUQ0jJJkrpuTCCIW2cSkmRmIasI05wzJ/TeQFBVVRWRnFNKmxNAIbXhvSsxhwTjkB4fQNWeMvt3+EpjufVrNringDtKOLLB7z/cgG1wDbaDDfJDSY6OxgIfCUloQYQ5pceuyQFg+WBG+EjBaCQo7n6N7CMD+NaZfAe9ouuXAV09D0h3N/3O1UQabQPNC0ZzGKvTzrdwJY6mMTcPaxJmEiZTjoJaJCHM4NR/8YvT3/uf/vizjz/55Kdyed+brBtVn/OrV7fL3TfrB/vy4cO789PtJ68Py9x0btumejZPlPjjjz7e6rvTaWutn07bVEhrL7yqdgidLmciL1NhTiwspXQVM6hxyvl8OhlpKVlW6bXX5k5bbR3I0zyVcmm1ny5Pvaen82VdtwORSCaAJNXWzb3MUyrpRnutzd2nmW9fHW6Pd6f7mqV8+uYn87y8++r9v/nFF9uTpgQzbA+4nC+92lTkcExlEWFJ7JlhqltdG9vxOGUr6ECLuyQRwVl3NIUwZIA+RCKJwiONgJKzpfCJM2PrpkiYj8my/ebxi7Tcvrl9dfzo7u7jw+m0vX94vKwrJ5kP8+2bg/LpdHosC1Jn2nq39PBwfvxQLyduvbVTo+5ZOBUmUGcnGS7VptabCdNNPjS0mptXr5dmruzprJfWKkja3vqlvcM4iYiEgCnByXZHgp0YBDMneMhvv8CN8Ayy/BBy8oxhRbMZswDk7A4yd0bQSmw34AMFj4h3451h181Db2EvJsZvKdhYsKFSBxH+/gzeM5s9nMMII3coZawCL+bcfhmDRfUMZ42wXNVVQcTMkpKkyO2UPNh2ICYW0WbAQNyv4IuDYE57SwCGvPq4d0yhrbeLY7woKrNj7yX2SALsu2IRe9tjt8BLaK/5Xl8TLFbsSJNFl1eof0dUa4EZYqQgewoQcJQZk+8EK4c2G1k8URLRQRoZ74+h5q0Ynuk+yFwYjy+Wq7jz5oDGq9RdXdWTe3q2W3mxDNK3ntZVxP2lY+CVPPX9ysB1fMQLonnwJYZlbtoUoHBxiy2IWcxM1Uw1ZSkl5/wXuh8G+UtEmDnATjhcwEzRTuGClNgYBiNTIpZSoN69Ay0yv13WKq6PHMMgTruKiIhcxyUxhcpMXG/cBAvLN6gzwV3NjAFHWdJg6NgAa4jgNhSOo77P4Yfq8KG4SGYeCDORxCg283C3YogHg4xciEXYXEOHf0yu4SpSnN0FxGrJIAQBGU1lglPfei6JXrMcCStUVaEOkySciQhhGIfUAepqvhkmZCQ3eEddO5SAaAxkYk4T0Ilz6l1DDOq5u9/ddAQWDvjQYx4oKcnOYPL4BxFQL+3x/f2cpycZJHA341xcPdJTGuUguAXah8TcT3aUIxcy1VLy2mvkhLYREdIk2AyZok3SjUgZatgFcvIkJWcja2vX1taLCgkMLMSJqICUmVB8cCqsm3d300TClGBkaq7uHlioh7dN5KsBWw2IdkclAtBmEobD0OqwWktcmLk7mbnR/icJDjd0hxssJ7jBOqBwI2+u5F4oSRKR2isxlUPJnlBJNwdRyamUzFnO28XU+k4AdCFhCmq8ZGFng5qZs1FhYVa27iagUBplZnKz5mZuXiVxvsnTzQw4uR/meT1dzFUb1VU5rg8syR/fv8u3y3zInQy1g8OfjjklYkAYIGGUDI1fclZ1TaDE7WmVma25TTg/6et56q1Vsj43N5tLSQSHhqyYWT8sS0rSaj2ftvvHszk9Pj6+v6/dcDxiWXC8Oxhe5enVvMzLYT6fT24uzIk5l2WeDiKLlMPnn//ppa4kmPOcpmldzd1ZoKbLMj881ERoittXN28/etUr68PTRDkXzFy++POvynSTJSUWLrn1xjl5a2aecz6fz2IgopRSLqVI6iIijIwy5VPdXqzFIGbQiBJGlStcJAIZH8JVGKDhviqOPyWiUKUyUzVvBnEIwQywgF8hzETO5gw1dRgnlizENPAyGTUSxzArBmBqAYjFPqkKZnCMEWOmJEhkbFV7dT03r50M3h1tzHoCmMECJqFODkKDmTZ4ypmWxCIk6OrdfXcC3QOcWE4d7h0WAiVxY1LU7hwOIWGBISTwRcSTqls4rJtra40JKYmwuFtHtD5btGmPDYxk35jDwjkcTaBN4aML8xrFsCSz/Y5QZFLmFKJ7tu+sUa6M9kj4oH8CO8tqL2qG8NVzeDQWeXVLxOZh+uFw8y6JJeV5nu7PT5ODJWn3aS44gQ5i9aUPkIWJDdye1S4JBBqr6cjVfkS2fjz+v3xcA1d8G9H43uswgmAfuRjvnREjT3EEYK0hA6PDx9gUZtasR4sCE219TTl/+dW/yfPB3aa5zLPc3BzW9bJunYh714eHx8t5BZDksG3aNdIIEAOskoXMOJEkNhIksDN1EqRf/uqXn/zk7c3N/PYnt9Pn2DYQe9dm7iQiKfUOITE3c8slU7La1VXrumq/eOe3Hy3zxDkTrKlu83RQoPfemqr65bKaubDc3d011Vxy77VuGxL6utaOTHIodLukwjZJPqQ78WNfy3//d//hbS1WubUN0nNJrgqHKgln9qTNy2FOiSlVU19eTZQJ5G4efSTRmJlSmnLarDugqr1FOZCHUiANHyjsVT7fH9/o0tsLxmYOd+aIzCLxo/FPAxHBnjusr11LPv4LsgeP0O75Q/Z0DsC1LShiZNo7JYjAwe4gAKoWpc0RyjosyMX7mIvzHa1M+yhFjL0XRIErZhWZyPj38wv2t8Oe1DkBFIqsQUpgIJhfvre90/Pwpv1DzEi/xa8J9SFAZ/kf/t4/+vf/8l/6j/Kn73/9YeV3Zzp/+pd+9+0nb35P6Nf/4M++enh4OFX/tEtyScTVerett7nQvEzLoazbZgbh9Pj45GortpzscDw+PN0vy5Sm3LVvTVuz06XVxrU9Hu/c6xOJtd5IYG55KuvmiWnbqrrlwrkU7cHhgl5wOleRvswHlvJ0OvfeAWchTnI4TqlQmel4c0uQn3z28d3hjXh5+Obx/qvHp28UDeEhNmWx1erFLk/9/Lgp+bIce793Tx8+nGdavrj/+vjzTzNPcGRJvfa6NaKU09Sbw3kkO05wM3NyYwps2kqap1IgVL2i2No2dEzL9NGnHxG32r9Rm8u0TMuS54Sk85rMlBNg6/nporaVPKP7srz+/Mtvnu7t9IB+ph7ayn1l0sxZptprJ8ks5MLTNDXtIBymWXN50sd60q69G4RMpiQukbHGwOagvHQ3dyYK02S3cHmKRpmdh6WIdhK/qrjysGmPyMhpgMDXOl5MsqD8MLMFnBTerwG8hhfb0G0YIZnbTgwCdgzpmRrvYT1Pw1l7P/a/3fufruu9RpgWdM6dW+Th+hy0o5dzb5+o8Vip8EvuTlxJUGsdzuLEzM4pJWbubs0aRoYb+FFomu9p4lVGPRinAam5vYAA93u2fxwNmhgxExSqnZOUxI2s7lj2vljGwFDrnV6AUTxCTxcRAlSbW5R3A+xnB4bW64DU4lYGO8wCwuzVwoqc9sYRc2tNWTUUPFhotA6NCRErmyFc0yK+D9OnUFseYtFEYHaCOpggNFYid4eCCIkHbhnV2WAdvVgPAaTrZv/ym+vyej2ug5JGB/iIGIaA2TViGBDFtebgO6QXjWAByFitDT90XD/9+SfhWkg7JisgcRtsBDcyiUaaRNxBA7EdIpnj6QsJs5OrdVcm4tAriloQRjo5Ov5Cx8pgLgaEJlZYAhDgTEVjA2PfB1YaU4Jsv0tsLzalkIq3PQVijgVhb8pJbA6HjvmPazoJREHFAAYzQ9zZlQmjh5D39cGksBFo4sPdzcXOfa3IxDdCRpd24ikbQanDrFkrnIyN2FOeAv/VatQBBzIeHh4ocZqny2W7LTeXUyVwiPrtoV/MOngUfQZ+PHghpKGxF0o2EuSEXlvdtkSSiat3GHYiNgFsQRnde6Seq1U2rFvJScDozgkk3JK5ggAXMnNhNwXIlNxYYcZpElBOSYowSdHcqAuRq2q3uAaDIhkxkYGHajuUzFsgYEZgBPADHQ1URiOgIt/Xsn21C4xvb0WOiMHVzSwhQUM7bNAmA8KIbcCIhGDQPOWIAd1AOiLv4AyGHp+RGlmcWxiEOEyt92bah9SbA1Dy5ipEMBKSLGzcWqutMjCXUpapb/2Mi1Z3qFUdS+wEMEoRWVI65nJIxMTuNzcHSbT1rWuPIWpRVmQqtwfK1LR1b2A/Hqe718eb49Rtqy3iCaEk8zL1buZccoJIku5Gj6eVOVZub4YkuWtzVzdiosMy+5x7b4GrEclUFiE5P53ff3hAeqXdSPK81NbQGy5Ayuvjo4A0ZWakxLn3bs1760uRLMkBdry/f7+ua0TPnJJjc29AAlkqDAYnvDnieLekwr1bypTnhahr3eYy55QFnkK9AAAgAElEQVRLzlMpaSq1VhEh5q699346nSbOx2lmEbh1GAGhoR5A1YgeKdT3QeSjJ5cG7EGBpV4JR+TmzubEQmHK5GDaDVB2114zC0RswPG+s354JGIe/iACCEWEMRbpfVXf7VygUfqORZp23XEkIQERG8NJq/XNrFm/dDR1loJE0s3cRs8sQXcg23bXJCWrShVZMgdebeZOtu+ltPfbEmjETfspRvQzFkQm2v3KnQLpIwy5KpBT15ZESDKDVUa5KnKA8RUv9rghfRjVPd4FDGNZjXoEiAcrDQMIMiJysecdlAxwyZk4Yiog6GGO74ibfmszxXMJiUSShG+1qyFiEBYSppST9u57QpUyo4KPrHCK3mPfoTjs9Cu6fsKLZOxH9OrH4/8Hx0vQ6mXi8YPHyOmjzWFE7i97UmLFJoiEpJC5q5HAhVm9G6z1lTPcldmdbFnyoR3meaq9ns5PvXczv1wutTYz4ySg3RTezb0DnjL1HosziChPiYnNydy+vv/G0FRtvklv3izvP1xadbdmI2CFq5N7SYl4lswdtTm6revmIlgOvhxkSkiiRASoalvX7Xw+b2tNkglsbuSEML0i3erjum0mquogCGwufHecYat4meT2dJ8+//Nf4UucU9PmMBMCSYKDXNwSrDCReXcTMHVXBt589IoKndanrXc1qHnvjcjMu1vvClMzhpkShAgsuwDhzp8iAsKoOzaHAKquwE5srzvu80xaolFmpednumdpz2NgLOxX3sEYNrFHBcBFLxbPsdPszYN7yrkH/E7YBYAH9BRVpxfQmO+V3+eT+M7iPE6Qdg7aFdMa3YL72T5jY9iT3WFO5qYDe9gv/voRO3wbJjCBeg2eWHQUYlpuH58+/Nk//83Pf7b81kc//V//6R/L6+Xh6ZH45me/9/Of/PLPagVkc66cnNgkQxIxqExpvfRSUsmZBSBb17UkBhlgIsLC0zTnUs5rPa/b6bzeP9q6IZ3psrUsl1KIJaWUUknTMqtd3NGsmrZUSslZjbdKs6bH06bRpSdSSvn1F792cxGkLDlLmdK8lGlJZgbD27cfvTq8ff/lwxe/+urrL96xInFqW4ci5dxJteH8sNHUD+YfHW9zmrXatm6mW3v/7rPXZ20GQaasm/XaRYRZ4EoiodhA7LTbOkUCk8IBiQlE0zznG07OT/YwLanMaT7kh69/XevpsuacJnIcpinn1Fqtbd3OZ7VGAjHjDsuHb75p/R6XE7gRuUzztOnJaHMx5k4EYwV5ycvNzU21Vb3DTIBMqbJGL6Far7ZZ8+HjFECqEwHqxBGRKWmgn0qkL+fOPo72FMaB74QVAz19QWR8iReHPLibuWF0OYV+sBocHGN8Z0s9Z8AjJqPnE4gkyy3gqufpTM8ft5/NANFANL4+TzB6frf46Qu3vucrxQA9RgRIRM9qUrj2Y11/yyIGdXfXHupOIPqWPuko2NLuChSl2bEmBFmMMYL5gOdon+wOiu4xkiEKFuONRnch4u6GMAf203fXHcEe16Rxq5jCIC5ibxuPL2R0dsJrAB0GN1dzZmIJGWwPkthQiHWYOTggu4EJ+HW9Iorycegu7aH0i1HjBOf9r3Yc1MZyTPzSMxjfPwb5KB7Dzj8a5orXB4O9IHD9fqftPecD+01HkrS/30j11fS637h7a/WlvP/1ba+fGOcw3l8IZMZEAhKHAIko8WDEsCk05ItIiDORkXcfxpkCzpym5AJnMzPrmlJubqYW3UwgGCjlnEs2t3baYKAiIUS1AzOx84CZg72lptctlpl37TKEqMqQP9lt3oQYQiYWdLvnyRWyNTb2JXOP6hx8tySMOMqQOCssfkrWTB1MnKSruunNq9dP20mQbj8+mvbTw8oZZRGrXR+ammUulLgboObUGQyHZDHtgqS9RQ5bZvzqy39z++bIVS73v06H0k8nRqJQ2XFnyDUIeJEGRz/wTlAAuSPMn0O/rFnrvUumUlJtfTzlwb+g6yiJ9tyQErBmKOjeZpuON8cp5S2E0SUVsk0bGwsnKkKAKbmbqnVrbr7kRVs3NzUVkbmUkpK7b2sN0X4RUih46Ow4GYzd4IrdLTIeq7tQULHgIAG5RCf3QL7HRI8H5uQScAEckVSzs3fTuss6PKO6cAymt4kTIZXi1qxRb8Zh8uduzbGuJL7pKsrKnYW69QD8rNlWTWFtaOAJs7i5VgM6M03zJCwa/h6CqUzLfDgsB3a+vbReO9Ra66ZqrpJZEhNhtfZUz0jGwkK80EwLcSF0xwQ37+jsrrDj3fF8eWrrioxypNvXt7evbvPM1KwqXdZLmad5nm/AvW/ndgaV5TCXkrat5VcsLKoNhJLBQiUV4KKmqpiWJRep69raaq6Zyzzf9G7b/dPD02U53p0ua5Ly9qOby3q6vz/Vjstq/LSeL+dpysfjYVleNVtPl6d6WXuulaS1LRf/+psPbYMqSqGUUs7ecmraodjqhQWvXx9+//d++slnr3tvj6cHh785Hms/v3+4/8lHn8BJSsksidLh5gAHWt/Ol8cPHyxPd9MhzTcMVwsnGuNEYLTwi6Ox32CvwchzfuVk7AwGs4MSG5Oyu7q6cfhHRrmExjd+BUrhoanFyZGGPQoRXSGWQICvbhK299KPD44QL+azjebf4UDI4aRZshQY9ZP22m31Xrs2x2boYCZKROEpCoNR0L+NqGvT4FQz4Gi189kSRA5TEheizl01zENDbDZw5GjuNuxUXDMdFikEYQmOlJq5mWsbwgocPEmCjqns0SUuAlXsgVHASubXar6bGrGA2OmZrBSzVOIcxq7p4ChRRLexXVu+WRhE8zyrtWjNRtxheW57J3IJRGok2I5dEcLNWCSl5KagEK9XwBguEqKJe5XyGTIfdSC+JmfxmdAxtn48fjx+PP7fHQFGEEcBW8FY18v5fJYbcBJzNe7uetGneWZJRo6b45ImOdwsv/nmm/uHD10p5XI6ndZ13WqlcHDFNcAzEJzdGEpdKVHiOS9MvLa6ts1WnM4PaulwlJ/9/GPzz3/zGxMeRF2HQuBmU1mWPDdfoXQ7gcQZYMZPf/pa2JOYiImwE50u5w8fHj98eFxXO94djKibG6BgIyFqq75b6+qlLQWHjClJAR/y3C52yHeZ7r761cP//Hf/BBuMPGWCg4FE5M6m5JpUiTkhcQt1q24y589++7dZ8Itf/YtLRcpw194bYKpdDejR7uA+uuGY2V2fs4DIyuAeUeiIumIPjIRjlFZDaMxfYpjYGRr7q5+h/L0Q+e2H7kBwrMbqTkpX8ChyS9/NyccPr3EwYbB3R8ZrgYWNz3qJo/1bHi/h1/2SePfQ8eetZJzKFewzo5GQjobLq34mjQLr/ocBBUZdZ9+sWNbVsOIf/P3//eOP+n/2n/8N0jdbxZ/+y1/nj1/9jZ//3h/81b/+/qvfvL5jIWXpZfKbXO7WwtWXJZ1PenOzqKprv1yenh6fEuc8gcW60/H27ub2NqX0dG7r2h4f7f4DTmc4nT9M59sj7l7JYbkxuKkzJ2I/n+q6xmTsnJyZSKgrHw6oG5KICLq2h8cVwJSxQESSmtSKp6f7p6f7Kd/+9ONipw9/9ie/+vxffomKLCVR9sqttepKWVrVp8d1Jbs47j576zSbdxF7eLet39D5/lzXFkMi1GOCpEEyFEtDycRlVxqBO5FMRZutTxfJ6bYcmHg5lJSOhnb//kNrMpU7rzjdn1P2JKVIyQldMjn6eTs9dRBI1xnltNrXXwFPwCm0e/txnsxFvVeqzPCMDiPh5XZejotUutTz5els3eB+nJY05X6xy+O6nTfUvTPwRYUQ4MhEQuiWPFDHZ9r66DOzHRAgvw5PIn5GjZ9LaN+fXKOviIIdOebP/ld7zcAJzPsvKMRiOUSKX2qbO6DwF9TC737WtW5H+1y9lje+KyMXfxJ5+TMjCyAIv4B+rhgWoOShXx/Kw9g72BKggOoQw6IXSDVfb8/LT3DsVdW4czv4bePMr+uVAsSAQAkUmuxxF4mCUeQvhMtpp894UNfI4zUDrQjl92dvcYxFLBT5R4BK5AQWNgQJ7WpqSsRuAGnQ3YKFQI7hsDdu5hUfdHc3DzAv4Lvdztf3OjUx5fBiv2Ymz/cohg123uv3jwFgxZp4tYa9bgL04sC3a1zfoWtdf87MZiB6hsBGHT6QUPfePYwBr+/z8g3p5d4AgMJvM2zXMGz7wqEyQMoA+CmJEGcWS506dnYUJ6JExK4UqJVLyqw0nnVMCwYzSRJygAnmzHCh2KxeAKWOkGcJAeyxbxGDRvq060ru1EYwx3x1AJQiN3PaqSbu3s2GWSJAgqu3QbhTjoWG4A42MhsFnRjC4Z5phDLPj6enBJmWnG8LDqtt3rm7O2aA1L2BHBlIaGoQu5uP8zydzyftvW8NDiSUeX66PPzsd36Xe8IXv662IRqlbQdezAeLA/t0xIj19lVu/4mHNTwZdVZ01xwtP/s4JncYExhgv2rdRWzHsIrb14c8Sc7p9d2rsuTWq5FqU21h0shEJMJM4skNEId4hjl3a2a9tQZKSSJzJ0diRuaUdm84q3AzJgETXN2aWco8kCY4ObFw7EeI8BNDlW9AXPsUCsFB3ifrmHEc84K0KszGVhevDi15p1DjI4YzTKDJkRESP8Ygst6bqlr0xK4KCfUejp2TDGYEM5MIjtmhETohiyuMosmXlmVKkG69brWUMt/MPmnd6kefve1am9atbq3X7upmXm3zSk5sPodZ8MQzTUS9b2rN1A3A+fzQtKbC86uy3BbOfF7PqAoxdXR3UU+p0JIuU3+AVd2yJ2Jx728+uqt1o9pBnifqbjkxLKn5tm21Nsmibg5vrRk4p6HpZ4ba6ul0med5WsrOuESSMk+Hrm0913mSm+U430y2VjZobae1b9UPR9ou0BaGi0jM8zyRL+1yrl0fH6oUHG8Pn/3WJ0T+zbuvHu7fTTPZXQGBmW/nm1qbqlltlMvNtGTJ7DiRtPOFnDJLYnH3pqraPEGYQdDe/YqDx+BhpmCL7hE5yAiy40tEzETm7moNnhg+4M5RjIqBZrHYkggJUXJmZ94Fw8FBkxaRMDaFe3cP7k7MNvMootjomPBdvc4BQpIJIPbEyFBobe3SbHNvBgV1eAclaDNAOdraR/GaLISpzCEgZnNDg13M0ECJJ0kksCHKq2amobRFQGjS7xvHvpCO3ZyJjZRiZx5t3RisVRt1Jzc3DccMTiyRDZFD91jnSunev5fxcGioMuDFDnfdJwf46MRRVlKAiDlEIHPK3h27OqKwkBOT2fWJ72wCjJghKO3XgiKFrnxKSDnkIkyEOMXTHuLP1wtEAODPq/CVn/zj8ePx4/Hv4nAf5uyStFcs+PDh4f7D/c1yN3FpAx/wdT3Pc+Eptd6LcZrmlGirW++WclmWedtqrbX3TpyIOGXucFOHAYKurVuDUuvqTLmIQChBlM3t8XSvlu7Kzeu3t/ePN998eIyu5W7ae13mzARyI7irCluZM2ebioLx+vWh1jMDak099V5P5+3h4fGyNnVsWzenrfaUpXZ0QLgSP+VJP/00m1HKfZmLdVjFlI4T353v8as/e/jn/+QL5PD5Ju/erVfpPCJfVvMknrJ1q+AOx/xqub07tq1dnoCMeeaUJezRRwUnQiAE3GTuoTMblfiIgUcx+Kr9eM1ydiLUYF35swOgIzRMdvLs9eteFt6z0u8+85esPRroBMieE6rr/0YY/DLxASwaMl6+4Q8MrO8wsH5w9AGyI2z0fKnPb/fiEiIi9SFiGbH1XiZ5Pmh0eDiuqdmL/e0alwPtYUOefv1u+8U//80f/W9/+gd/8Df/5Kt/8c03/4r58sf/+Bc/eXt3XI7HaU4Mx4Woz0uaFzlrdWruLRc6HKbeoFbPFxxuLE/EJGaYj8eUS1ft5q351tAVaugKVaSEaXIiVdN10zxZ71yrqkURLsCCasaSdVrAwowEwuVyRkfY8qSSJZFaaxWuzl4KT/XSzpf704dT1NetQd29E1pqZlI5H5JIMWunUz099drDhfuGA9OJIp+hWXMH5aBfDTAjKtV7imoDMzTTZtr6tm0Ly7bVc3vyudHRof3Sz6cLfve3PqvbpV+U+JKzEhoxSWLhvMw358uldVhzJFF1XIAaJbzEEKO+3GQjr6arAgTJPB+X+bg4tNaLa9Nql7UVoWM5ZF5S9s6mTYfYru9p3A4beNS/VLGDPMEtC1w2yOwWis5hv0VOLDukM8DQH0Jdx4iP0FCEB08w7KS+NxGIfMR1g1MYKIft8dr1sB9Crr41zZ6HPmgf3WTPmf8PHd9CSQIOePEpAfeGG9NIid3UFMES4Ks2kdkwBsNOId3nF12vI5Y9C+nnoEIQMQtzUOa+dW+ikcIIRK77SsUMZiFQtGW7O+9rhr28Nw6SCD0pnIvMg3fpgMAdTrBwxdoXD4DhBKFoG4oqwOi7JYTcV/R/haptKLABFPTZFzjgfu2R8mIAe6MEbwRxd0lirgNyH1o9330uV9nB7zyxdMWknlf5vwDr+v4rnx/rFf+jK0v2xRiKOJ4HLHeVsseeI7wEyMK29oom+p7hD5NFAZJDRlnDAUDVABBzSlmICDWU2zykUkC7Enj0/Q24YTwsImYhCAzq5FLEkpEQ8RDgfnl6NmRSdv8AMw/RmJFi0T5bKJSyg2QFANCBhoSsYrSHjn5TeAASAhYQsYJ4GJbuRaYWBZ0QNmNJoXkSAzKD6VJXNvDhJi0yv0n1qfeqAOQIX8lcmSCFPLsxKOPT3/poupu/+PILAlrb0IkYyqqs+ZDwap7flMv9Cg5lFQ+wm4YC8b78+Xi0Q9A41rs4aWJHV3R3BzsnsBAJRNAZsPgT5iF4eF0lKEIjIXnz5s08TaZWchGRxPm0tstp67WzM7t3V0ILRB/szu7kTLBuvfW+dTgsgcAE5JRyyjkl7A+PneDOYHYBg9RiV2Kn4c0SPV2CRNdynceM3R0o+DpRKJiioeDuwdsYvE5rCiMIjzYwDzs6M0J8vBNldsqckJCIlMUYBGPVaMSKAaQeRNw0iBlg50yp6hbzxDSWSmZiQfLuXTvYJEvJybpf1vPp6TyXaZ5mNz+fnm7eLBC4orXtqZ+VkKZ8++ogksi9bqtSd2KZiVMhShttG5QUYGpeeaLj68Px7YGLV93Oj7XaOh+mnNmJ1bybS+LpkGRC3WpqnNNESe9e351OLsVrX6ep9N5STjlPJL7Wdv/4qBQC4NvT45Ntp95dZGotmM5Qx9o2OmHbVlXkjFKmeT5q7x/WD+cnvVn41Xzjt+vtzSuR8n+w9247lm1JltAwsznXWvviHu4RcS6ZpzIrr1WVXbRAtLqFeOIZ8YD4Cn6Ab+CdB74CHhAPILUQiEYqRDcoqymqq+uurMw8l7h5uO/LWnNOM+PB5trucTKzqlrwgjjzhOJ4uG/fl7XmxWzYsDEO9+ey1NvbgRwBmkYok0RoHAd2wnF57/tb3l9tqpVXb++0ndzOanR/EBG/2l/nsziatqal2UYHGYdhmCRdT9t6PEvz6/3VOAxuFpgjengJdWNeTxTqraHEoXvlHc5F7KAMs6Dc9mBTAaj3TR3wlUwUO2k0v4twYhIDG5P0875vwRAWSWLk4WnX+9HXjOGD/9a4mpgczp6JmT15RSvW5qazojk1Ts7qcFNSmJmRE3vqi6IvsH5S8hooOahBZ620kE/IdOGQuyHUysHEguA5xT7TrxkRMfRSSV4PlMuITAXhmuBQUyMRSE4ZxGYhvqL9/H08owjdkJY4/L2iq4Lwa07gy9YOu7QdkpAIE5NqgLphm8VYedl+8XRZT5BOC+fQj3d3gyuxkRtASRBv2WFdjL/bf1gH5uLj/pr8hxBA3G8IzL4Z34xvxr/RICI3pYAkBF++evXVq9cfvdzuNnmNbP1wOoA0ZVJztQomNS9lzlm2+83+6vru/bGUpVZlT3DOaRD2pajVBuGm1U0bi5m6usGUHOTDJlUq9w/vSLZjgQx883z3/O7h4R6ulIhrK1fj1smWMns14zpuKWfa7oerq+R+FtacDdFooNmW5Xg+n+alGtKQD6di8FJ9ctLA9qnIeN7T8Nl3n7/96t04pP1mM6Vkxa9ubtk3n//s/R//y79588UCh1aCmTcE5hTtDilRteZeZSDTxZLD8K1vf5tESj1igCRsdpOEpa4Tw0UY8uSgDL5V7bFll5lYd/21lOy9Uk+/kssEoOBmBmaLJDzOQl4j1RXwWQ/d35jGPgJVxF26OEbkRyu1yz/8PoCgkHl0S63g3NfSYv+1HJAPRgBQF5jK+99Pelz7FYhijMsFyfMPGqmePiEuibP1Ey7a+TtDrX8MGvfbibykP/+TLz//8uf/2X/+n24OD7tn9Ujz//7TP/4n//AnQ3NxhtZ5eajaMm+c9Dzfn5upZaK02Q7WaCkt3h6zpDw6iDiVpqfT6TyXpag2gJES1Lk1s4ayRAghsDGlnTCYTjm1nAej0H3TameDyhCnOLvZeTn3kltO02bMmc1ra7UuSsZe8eb+7fF9Obw7DTKYoZ2rqovnQQal6trGcbvbT0XOp1oOB12KCjE3hueUUJupVRhKbQDJkBli1YOE4+REoZALI2cE01LMnSldbZ9tdtNSzw/LCQXbAZtdzoOkBLc0z3Q+V7iCmzYz1/1+e327H6bdNB3tdCZigIUTEiSDPSfODGp62uwzJJezIfqNUhq342Y/tlbnNk/DuN0EJ0bqqZaqXtgrmAYLnSZ7BGqD5hRreVUmAjuT+9owhI6Heg+YPNoBLArqHQJ7ZAytK8t7qTC+uDBheOUKWo85LxO2oz39u76SAQJD/mDZXACt37yKcUFp++Igh3ddvF+74i4rhFbkyulSQ40/RHGFekNEUDXiNzkJPaqwr1fq0iYB9K/7N+O13K03b9H6y4GCBZqwZsXrJ2YoYmfxy2sJkYb8BCDcC7X0dHuklU8TkscBU65lWzjBHNR5Fb1OyhGlgojJ2EzJ1EKumghE7AG9rXmKk4Z0WRB2urV6vAKvPSO0QlS9c8mduO/D3i84OTj0sByysq7+NqAS6WuUq/VKP2JVv4pbXcY6Sz7EKD/8Ka082oDoHM7Su1Sevly8StgaXgCsDj8x4lO5gJjAYKFogV0rIERQI0k5cTIEcaOXqsOnyqIfkBnmoXtEzmxuAgKTQUs1Z6RBHOxm6iF95Y9LGFBtRJcqTm+A7byIvjYRNyiIEHE73J0dLpHDWHCenQJyYw8OdYgfM3sou6ydsQ5zaJubj133JKTfKWAjAhOVMhuZM4pVGWj/fFfGWg5Lm5UrvMUF6pNmt0+b2+nTzz5Om/zu7t0AWeYylxkJ51Knq7FqGfbTp9/+9PPTFwsKOkLbW1U7Z7DvWT03s7UYsc5NwBsyQxyMNKZxM7AgYMFI3UPdiSEOp87Qi22BiXzc5NtntwS8efva2YftUOZyPi7lXKEwU9QnLagZnMA5aHDJzNw13qa1QIowJhqHTEBYNYOMJYqsLGBXmDCzabVoaIIJqcPISVcW1uN2sIKt68SgYM5R90QN9TyzeEOx3TCt6GkLvh5A5uJmDobCkChJloEZIi6mNs8nU40HuMJ72zJgZopuB5lS4tzcPeTgGZyEhZjYtDkUmcms1BD3gsHmOtdWzaxWfXv/moSU2mxzEThDkruYs8LRrJ3rzA43SkJpTOYO1oScs+SJG7VhTE62tHnWpbk2cjFNIvBUVA/zebNhzjwMuD9jLktKPIwpjyk15jygtGE7zMsBkGHa5ky1ne8fjiQYBnanpbTToUoexxG1K9bxbrdVraUUAJttHnIGaD4VYmoL7s7HxHn38dWUh4+ev2DJbXldqz+/vXVHElB09Zq1atpaEtpsx6XN3/3uZy8/evH+7v3x8GZ/NVxfTaUc3r17u9tNH3/62XJ8SCSjACkxQhySNuN0NW742qjazXbvRUMjN2aKdWgIhCBqPp5GHY9aj5nYxsidKDE5MxmvLYckcdthbm4h9B6E20f7jL5w1ggfhBAbgIhISsngat1CNPg+6y69HjR+OS0hzCTEnsgFxq36clzaafHqUGKHkJB7i4UGrH18UYWk8BiGcJhSuTcATCQGW2yxQkQJmSSarxUWbgnMFL9uF6XzdZ2xc6edxrkhRMpdEjH4s9E+AnE4VFVJhSTnRMym1hBUVwDEzn0b6wzu8H4R97YW1XrdDGu14/Jm/FIZJBBDBJKIRZbzEmoXwuLr2RDBD1YKe5x9Zt09pldEzIVEhN0IMBIwR0ykRE5sIQ+2uuVivVXrxXnMZ2gNmP6u1Oib8c34Zvw9hhO5XQBofPnlqy+//PIH3/v42XVSM2Nvqofjw7Kcht3o0PN8BPMwDObLNE3b3bTbbb989eZ8nk+zj5LNQoOCVb20yBy7vYbDtZVqqqQTDZvNlJI+PBxubifzSsbPbq4++aS09rbOgpTrYXEzEpRSa2vDHkMemGy/3b14sW+aT6eHceLYrNWstrIspSoIEMlVqwNqcCQDNwNsoZS3Qx7S1d2rNznx9dX1zbNNq1+N415L+vJvDn/0Rz8r80CUyeCuSZxZMk9mYAIn0bqoL5JYRJ3IDT/44Q/nepj1/Px2u9RTHgeYhru0r3G9xj8NXYLZL2Z+PUkjOJNY8wvtIW7QE0ArAlByWnVxHJcj7jE5XkEvv7gZ/p2bZW+g+EDNcC1AXx6yFuY/TKY7TuZr2vr0GPj7TL/ID79GBeg/ArBWNvsVozhrAMDCpwSPhiHxMLvoy68VsK5E8OT5HZwmmHOrX706Hn6Gn/7hX+jNdPv8u+fDlw+HL/76L3/528+vuLq1WuusrgONZn48tbndTfnaHNO4zdthXux+exIxd5Y0OGBOZV4Ox/Myl1LVHUkEY1an0kqr1gqnlFKWlElkD6+1HtUgAhIRGYhs0dlN41qKRKau056JaRiHcRjzSGbwZvVcW9Xq5QkEvbkAACAASURBVPRQjvfzUsGaXBkKVI/8izmr1zxM0/bK1OucSuFSSYj0VOvc4Dyf5+YN+eJCSLCQyDEHAxo9QHFNzSHMkrJWS5SHcTT3UHzOCYllMwy7/ZimdF7s4aiHwzlszutS1b0Zxt2Gc1ZldQDicGbab0AyGCdxgVutRZ00pHnGhLRXURKM29FmM1jKwk6kDuVTKafDWVoSDIxkWta48xKWEoE5MBojcggzXWbqBWFeF0EnDawy4ERPtH2fAK5P1wsI3tXULxyl0Cn6laUQfXfR9RMID3V47FdWyG/EsFY0FkCHHbDCOEE+/FUM6xGz7nldZKIduHIP5fYe0Xm4Gz2ieusy7PgcswAt2u36anuMzD78KB1RWh3t3V1V15A+7lAImbtRjzyto1Eh3U7kRApXJQBByOo3BpevV0RmVdTitURL1mustkq4GqJ31NiZiDmFKZhHk2JX2YGvPlM9Ll2rzRePC3QssMvVc6Sxa54DIgqjgAvBC53cBwILQQjCWHXVP9ijPhzpImj1q3f0a7gVPZG7+hp69Uip7TWPy5PAg11GjzPDyZ3car+Toa51+YKZzVez2ECvAq4LjbyOlkTPd1inuUPNE8hYMpFY06bk6r52v/f2PyJJotaEMzFJ3D4mItKmXgyCtBuZpcytu2/2daoEYfT7va5udzOouXbiWKdRrWsZvn4RM1jQm1PXayci45TVmroRRXJO7mTrkwQ6CuJaasjNuLhACJI4eELk8HkpkkWYa1PiNF5vhmE4MhU7tgaE5jmACgD7/dXti5ub6+fDbtxuvxjHSUtrWhXmR8etH5fjdD2+/NaL1798s7wrPX5z4WjNWUUK44KmoKMZOvyK0LYihyM5koMgIw2b7KRg1WgF5RXGWy1VjQxUXRBa9Xmbttfb0/H0i1dfJObN7WZeSl0qiaSc9FSs+AVCzqAkOWXmjMTp4TQbO2TdMDygHx5SrqZLndWdE2mA8WzBgzGHGrxB3aHxD8BAoRvWcefLPneRs8HKzUNfAX2bdyfuEtOx8XGoosMANIc4DGSBJaCUFkiDpCTE7EKK7NmLmbbwz3ZHimhOqTaNwouIJx5cm7YKN+Qk4NSV7DTcaVo1nRsZSDjnrKql1jAHWEpRbmCjzLuJG1RrO941zuBEdXZ4SyxW1YRGSSmLEE/DdrOdrl7s3h/eHs7Hw+GwtGqCPGHaUhZOzOpeSnOdGSmgGyso5Lppm00GN2LPKSmGcRrOM4kM07SbJj4drdZD03GSKeUsIs51NbdLPAzH+ZxyhlGtdciy2+1EqMxlnt/nnJdzO88t8cPNhje57q+2OU1vX98LL/v91gwpIYlncbjVMp/nk1CbNoIB3//Bd25fXP3r/+vP748Pz25f3tzevHp1un84iMiz62df/eJ+GLLw4KOARFszVcp5u91vNomrDmk4nO9hKZhRgJMZDCT42nEpvSgT4h4geKzl2C2dhZOTsIvDPad1NzBHswaQARyhpxs5XN0tUSIn4t647RFguRN6b34/TPtyprVCzd0uVnsMxgRmYs7sIjQwqJTS5uazR/VHQElE4VWrGzACAo42RhAUbg7mnEShrSoqIEiUBShamnpNyilzPwoBZ3iLN01gDZNT6runkSfqm6dB2aI6ABHm1K1bhQVkgT+5wRzG7mzxIEZlg7HjsWczSKUWmDoTM7Pq10/ASI3WiMOjTHkpA0qcQcTCspRDSplzZmEHWmtubmw9aAJf4EEA5p4ej1enBMmsDrjCYWaqrdtjkZi7wYh9PYrgUA++J13YmR4lSrgwtD2K3vf9D9+Mb8b/P8blXP5bHvK0GuW9IeRJKuQgrKG1dy6lGw73Dw/3D+f5pJiaV4Oq13k+n+bD1q/U23k5ECVJbOZpkGEchmmopSxnnWfw2HqKkYUWjmyXJUlKeUjmrTV4hYpipHEzcK6nucggzmitPrt+dnN79csv3hq3zAzy2sqYkxUtDRsCpVaqDSlfXw+1lbdv3m531+RCHn7KaE17uYEzM4PYrLE4J8CbWQE0Zc3czmUeN9juNtf7m89/+dqXHdkzPT6cfolpezXbyasBgCQCl1q12TBOaaDSVNUdygmuDsV3f/DZn//Fnznr7e3N67vKBEUoGDo5m7s1uLsm87b2VYQZLSJzJ2YRJiEupYIAF3SBR49aYgiLrQAWnhQZcMktQ8yHrKuW94f9akqMns33/3kvZNCFtx9zxr1bGH3wa/EuopvxcX6hJ7bxz2hSsa8n3L9umNFqj4kn+dRjPvFB8m/x2v2ZQ3uZ/HIJ1v/bKtOBJ5kJ1kPCAUAP5zOzt/nZBjfP8U//+3/+7/1H/3hzdd3mL663+y9+cffZ9R6c3CszEkkeB5FWCk5njLczOYZhs9sOedwMG3BCM2OCOdStND0vSw0xF0YeElku6lzZ1JsywEQDgbTidND3d7UZprGOU8pJwCLIiuIOVU9CklJK+PiTj2qtw8DjlFngUDDPzqdTMT6YDXBmmJ4aKKe8adqs1gozUQljHGI4NW0MnobJzM7LcjwvmzbUZs6OBE5kZqFwZKsHXE8wgkjDEVswEddyLlYBr6el2Dw+k7xJ7rVWa0pQ1uans90fDWZ5gBmaYq7zaT6b1MN8nAs2W6/Whqw8gJlczbWamglOpTRzB2Q/Sh5LObj5uB0V1V3NvDWd55IxDMPAm8yatWE+zsG3jFRlhSNIuOMREYUGvyp8eSLV99X8s6NCq1RoX4V4zIb8CeXl8Yvel2IuDHZTbU1X5tcj8PsI9vAq6P61+OUxfvu7oprLkvn6961/xPXZ6cNHXZK8D44SX6kJK6mepJPqQ9Q9ZDi6eh87OxqFv+NlhT2+QN95CABEBCAzji4EVQVdHEjR9zSCc5fdWrH9tQoqoXgLMycicTbUgGMCBIt2ndbUvTd/oMtpGOjy0alf6Pj+iuoYu1CsnI5eESKbFoJ2wkngEMHTCazwkTlL4XbODheQdo3/kPyIGWTkFH2dl2lAwAVOYZh5kMvWDOnJW3aAXDabzVMSVs45IK2nGzSF3k7gRU+AmWHKLNyVm6g3zPW73uFPGoahCw+h1y4e0UD05Q+CezPTptqsKVlKwpkkceAdNHAe8jDmPKSUpWlVs6bqMBLKQ84ysHEr5TyfmjaQcwJlCqur9Vq6xUltcU7KCgAiDUkmyZMQk7FLFs6JOWcRIRESdmGwVa2lWVFWiJFVtQoCZEVeO3xnnbPYaq2l1dK0Kg3RGEKcJQ0sQuZaWiWOSRzsA1Kguak1h4OMmDghZVa2YRym7caZlvOplZazEFFZFmOq2pq2PA6L1u1ur263t7cff/JyezX99o+/9+yTm+ef3H77e9/61m9/K8v08O740z/66R//i3/99vW7w+H94fgwDZMkVlEkun2xn3Z5LrOM+e5v3gOEkqnw2PLNsNvQcDqc2MDwgViMxInUyBSBEbO7m6s+/+zqfF5uP9p89Nn1Q3l/1odnH18NmzSfFjPkKaWUJBGsuc6eq0+OndMVMOH3/9FP/tWf/6svH17tb68K1RnLs4+fbffb88MpkYhmVNAZOIMW8sV9UTIMedxMm+P5sN1spu2YOSfIlKaraZ9kaKpKjokwehFDIkrk4Nq0zGazo0Eg5ARiGXIamUeGgIK5R+wUQj1soWoFIoiwRALMSAwJuNn9slqIOY1pHIcxIbHDoCQNiSR1MSt3bKYNQUy11FpbUTMjW1oJzfvYj3JODCYXJnGHeqinkS/GEfS5ozWrtbXatIaFZVMn88QpzDdbCc9CkABMzT16L7ViWdwKwTOPm2HYwrM1a2eti7fi5VzneSaSIQ1m7e5why3/8t0Xp3OpMCPc3OTnt1dDztfbqxfPbhOl5XT2Zpu8GWV0I9UCArMubdlfD2r1/cP7u7t6d3cehFvxd6/v7t+9PZ/Ox4O+fLG7fXmt1tTaeVnM0nb3rCn/1V+9r7bMtTmbAcvSgCWPOaVUW2vFtVlrVkvVctju8mazdfDV9dVv/dZ3bp/f/nf/7KeffTTu9tPpfHr1+qB1IbLnz/b/7j/6t/7JP/7Ju/uv/vpnf1rs3c3NJg/U2jyktNtspzTevT1kk6UpUto/u9ru9/Nyun9/dz6fhDxlYcj9w/3heDqd28ND+eTFtyaZvvjZ6//lD/4gE2pwFoVyloHB1dydUw8kou7hiiRTliwY3dgV1gLRUHNVcmO4AAIZU5qyJXYBZ85DHqbMAtNWyqLWAjex5i8/felMTVupTUOcE0QQBjOYja0YqoeuZ+ziQhhzGqftNF3Xkx3vDsvd0Y8FKuKSNYkSVWRI5hQlbxeexilJduNWW9XWlqU2ZfA4jOMwDTKSeavVzJ2g1ar5uN1LzqUuZZmJPQ9MsFLOu7QTykwSxxsY6qa9fOcEJGIRctKmRoRxk5moFe0xpQIGVVu0Vncllcx5GFJOGtY7ZJw45AkJHoBRLWWYxuam0XRjGscxCdQUQBoyJTYHCWTgaTOO08hMVetpOUliYnJVawrV7hQzCLFEn7GaaWsetb9EwRIL6U3fcjVzXXjyqx2+9eLZP/zdH3168/w8n1rV2XR7ez1sr37xV/f/2//0J2++OgqDXeAsedtq8wD74OQuHkjZRQtmJSb0WszfnTV9M74Z/x8dT6uqT0dUqS/R7ErvwSV4D0M7W0WCAMAcrhCFQJcCp2e7/PMvfrHb4z/+T/7Dg72hwRY6vzu8+8u/+as//fwvkLh6BUNJTdLNi+cp51L8dKyvX9+fi2nBw32r6gab53NrLUJ5J2NByjyMOedUvaICaoflaGhG/vEnLz799scp89393Wff+fTHv/Pd2+e7Zu8ltaX4XHRZkBJevhx/98ff/Z0ffbS/aqfTq4eHOyhaLTnlTdpsxt1Xn79iTEPeEqYyG4yCvyy5qb4fhppFEhhtOZ+++PTb+OEPPr65zVbldv+DH3/2H/yX/8V/81//V/8r5aHdH6a0HSWPw5DHwUlKrUSmrMt8z5thezMC7GzXH21//9//nT/4P/7ncznmjcw6v3t/ykPw0EUNpRZtxgz38M8ha/AGODNJ4pQ5CQsUplZKnfKGu+/shZyMi8B7SNmCSCQlFncyo1UKuf9ZGc0f/ulM3vWJmSDkws4wuLFr1cdS5SUnokeCWGSbQswQM2g1iySJKKXEFMxhdVcKYkG0q5uTQ4gTi4B7gUp70ZQDpTNCVJSYqJspUdc6dAZAzitrAXBE6w4MvSM+Kv4hnxN6KN1rnZiFieAcyjQMFggTgzKaDMMooOOpzu/9bpnfvPvLNPh2i82E83z42ef3z24++uEPryYpX72+e/fQiiMN/uxm+PIX8/Nnttvy8Xj3+u2r7//ou89udts9cbJhO1Stdw/vz015GGkYm3oDScqAz6XUYnNpczkzY7ffLMXLwqWwllxLPh0qY9ht9q2K8P6v//KwGcbMe1cqS3n37m0t5/P5tCwPSSwlVisQ22yG57cfffE378qD+8yJMldgsUTM3sQrJedJPv6tj5j9zcNX4JYGn+cDOTLLKOPb16evXr353e/8gx99/0ef/8kXskvCTAwmGGHYTkoAIw/TME5QMgPl7AY4v7i9nk/n0mbOsOSb693++Q1tNoemh7MuC06nubW22Y6b3di0asN3vvPJD3/yHfVyrPcyYNpPeTNySuPVdJiPB10wMI2pxXTITNmAOm71+nbikb589fkvf/FVU/Nq86nM5zofq1WY0unhVE+nNGxscUFmEubUYyB4szCgURCcmsFCvdm7SJMGxCBDIgr+gfc0z/VCf2naAti9UFLiQR1uCT12CJMkSGYRkgtRAAaJbEqSM/WWk+B9cMp5EBZmCX2G8NwhWRcv/+Z1TWwG6xJCcBCDhURYCCScsmQO/SBTcw33uctidyMzmAJddjneRWRkritVx9n782ZiIRJnYSiYOXzbHeauwS16REu6FFhXr+rftS49BiA6yg2m4fRGxolTkmEc8zSknM2xNK2lmBqEZRhDS8QRqskAecoswilLEiF0F1fhPOSJ85A4MXEYtQkkD2MKhGUYUh6IBe6tFCKXJJxFWLjbAhIxupkkA2zj9Rjtc4HnhnaSd/shYmJnNidiTjkPUx6nPIw5ZZJMxJYGkUFSzjkNQonB7qbN2Hkcx5yHRAxTj9zb3OHEAHu63K2nI+cMwMxaa1hj36/Xcgm11tgRu/9C9JgiGp3gT6KHp7ytmOJ6KXkHOvsElYShsbITCxGRC4KxZ+bWlNSN1NYeMjerrRDA2rUJrHvErjzhQA2tq5sE3L5CcPGi7m5rr1fH1Lq+uPXDqr87C6mlzspbTRkCOlx1u3plqDe0rqtYAy90eFTaV+ZaQK2d0QVai+kEC+eFXl/i0NZJBhIGJ6AF4MnB8WEYYa5LXeayvSYmTuGb5T///OdtMbgPOeectflc56FtKlcmZBpZeDtux2ejZt1Mw7gbF1uMbX+zl08mueN6bsxILPN8VtL9zc7M3dVbBwdbc3VnAWVnIhG2kd8f79Meac8FtXqRQYbtuNnttPm7L+7Lw4KyoGKgJIOX9brxBuMuvb5/3WDCol2JceBE1lwk7AKVjdwkVG8Q+0ODLrqkCkKDssGjldC8mQqEmQiu3qqrx9U2oDVUoAEKNHKPeMpMw0jSoIDJ09xv1b7stYBHjL6tDNKAz7skXEQmLhebl26fYW5MBjJ24raYc+ALcfYBT576sXoXnaPB23EYwN7Icgi39wIjoxtxwlkY7gLhQMgB4kvPNkUA5Ea96T1qlGA28UawUNXx2EoCjja3qi02gofzwQg8QnIXeHIDgebTOYskybvNfplnb65oZDYOGDKGgUF2fb0jUK0NXluzVllnJbfNsGGq1du8lHletBlAzHCi0mwpanCWJDnlLHCrvIgkJk6c9rurVtr93d3xiOsrcqJS2ul0chemLJJB/u/8cPjok+9wGt/c3V/d3RGncTNc7TYifvfuzeH4HqQh1gaGuzUjc4cxRGWzVT231pZ54SRDytM01aWYmjYFp5wz7aid+fwwbzY7Yb6+Hn/83du//Nm7xChEsQs5XBgGaAMIEmICDGdUa25gJXczAmUmhmlwTmOyOcjVm5qKpJyGmGxVG9yYTRI3a60aJU4bKa2qa2CdBl0nkvXaQXNoLyshyMFMLCIpZ07H98dWTOeGYmFVRQ5XbQ1kTSGAq5sz4Gza9zliEgondjczrdrjGNJLt3tUrFSbVVE1wN28Westdz3PMCfqCii8+i/Fsc7aS4FR64zYAtFyh/ZYelvrI2TqbmySBXCrpmRM7AzmCAmSMGMINWSowqERlxh6eKRo7MQJEIZw1MridGawmRMUDnIBiNwNbkah1+K93dMQ5zjxBweimTEnkSwuyWI7AyCUQNTUaqullqW0pcaZ2tUkzQhIcI371z1HnEPf8Zvxzfhm/OpgPMpzAL0Ybiua9cG6WfGPxGxq04g8DOqK5BWlalVr7p5yAqOTXcMfprZSm3sWEUpZWJlDXBMUfQbZicLCVXLOeUjMDME4DBUNDk7sbGAstZzP59qWuS7H08Nms715Pg3j9+a5/fQP/2LKo7sNg3z86e3ts9006XmpApsS8iZP45TzmDknTjkPQDJNDWCyh4cHSRg2tJ3SdssiLpApj25LGvDZt58z16U83OxePn/26Z/+2c/LA6PBDcNmP7+6BwBOeRg4pWGTjQxk7oNyPT7MSNhdT5v9hjO/ePnSvL2/vz+cH0g0D7lWNTUCWCRlglktSkZuQV+6WO7KE4YLOHhkfnFI/6AL5NIV527xVJ3ceiEXrL1PnQ3la+tPD+tp/SlAdGE3hYp8Z6T87ei/x8yK+9uxrSdvDesJ/pt++wld5PJljwKD5UAXogQuDmsrheyDTkECOhLLUfgEuqbFyke7GMpc+sj6c5ADxCC3pqjInOtg3Px8DyzDfpiW+agtLHL5vLR5XowEJK1xMxbi6ytMU5oymfE4oNVa6tnbIaVA7XyupTZLecfiJBImLkHtHkZiggjcsRRtzZfS5rO/fXMkzjnjfNJhbM3YyVVRC4RaNEPUinGECIjQtEmj1qqqCYtIpz/nlBIPWpuzCdwZTdGqb6ZkbqYGawCGlIQos9TSSqnsmMacBsnEN5/tP//FKzCYJExnqlViTynlIRNB0eCax2F/tfOmOi+tVge2+2n/fCtX06JVkCkPp+Ph2TguSxvSOI6TtWW7HT/+dDPu5e7du+P5SI7NZkpJ8jAOaSpNpuupaW2znuYFcDSAMW1le7XZbAcIGxHRVOZSzlaswQAlVzd3VqOQKXXggpU8mXCrGjMABeFi1wU4caRFCkegQE83yUcq00p6xNOkaH1Mn5Gh960GDuQ0WDiX5q313USZ9VGjbgWfQrR07ae6LLx/0+Hr9mFmXbC7N2mtn2D9McBMYdi3NnEBl95CvmiNBweNAk13hbk5pUxGzEwGZZCxIWSKyeFC0sX8vCvVh1psKM1Y08eCygWdZwrF5mi9jhYMYVIXmIIoNtZQwaLoQOLV7Aih0eweakIwo54dR5obEuZu/WaESFlo8Yp0cqtQNDHCPRqIxMh6ew2xY+0Bv2woAbxc+Ked19Rbo9fppCBD4o6/d3Icg4xJEhPRKtnnDgNHKyeALn2LZKtJ92XyXYTEeoy+sk3iDa0ADUDwBicXka5cePEB6VF7n2ZP4/W4ecTUIqG6fLjHFpq18zZqDAIkoo4emrVm7nnDnUcXYJOLw0M8ee2vv5xC/Qt3oi583/sZP5ixcYHQW/EBFyS+CCejl7Y7rPHIk1ypeuiy8Vi5fMxIKV94Z+pkcbE6dNUhFFq5kJ1E15WSQN5pblFRH4aMhqCN5ZSaJ3WI9IsQ1yr4XzCQuRAcqLWeTue3r+9QAUNKknICWF1JekmqnWsz1UGHPPGO80BLrafjyWds5Oq7P/ju65/fFX2QRZJkL96KtaZuBICYOZMI+QIzN3aIGXsI7VvG1YvtcL0paAVtSkKJ91d7U5j6kWZuXM/upXDm22db2YuPsKwQenf3Vq1N05Z7fw+zspsGQdKK8SoTFlNG3UzNK6x0H5CwnLTm1FTJxGUQ6Xs1wELdtUwvfwjm0vlj6De097Z3fPESXviKyV6WTKynSzmOmQP5vWyXAW4GjRPwnhw7YA72WhXSGxPDnoyYhpR7vywTgUS40/vMTS1wBzWlFs2J7q5d7DAmdYdTeyts55yGzxqH+DSbqak5KMT0AUCMNLqw7LHrO/ZuIjOrKDBubno+MtE0DmH74uatKsxKm4np5up6Gic4tDUrCrLNJotQzhI7DBHlPOz34/lc796d2oztCLNeejme5ndv3xP5slRrgLXzeV6WwqSOTOilEGKklAgskjfbqVV99eVdaYAL3Eu143FpjZNklrw9nr7//R998u1vD9Pmq7dvpy+Gpeput91vp7nM7x/eP5ze58zTNA7DIMJm5E29aSNtWNL+hoaRc9qMozCHJ4QQuZrXhixCUcnn8/H+ardnk+cvb3/vd//Bzz//53MpcBh5YBgR/5h5eI6YsMGN4auQQhfPS2Bh1DUsfYzXAXPOnFKKmabaHC3OqQD2Jcu4G0otcReNwrRllXo1N3dT9aj6xgHHSCySMqdMKR/fv0UDSkNtcCRQYqGEqq2aMqx7UnQozDhQTCaG+JBZOv/Iu5gHHkMfh5vVUskjG2FAL33nCg1uQhxpT45EIHCap08FIpI1biIzgPuOTy5ucWq4uwpL2marUpdmLbZ6U2cmJUmc2SR8NZ7ETgzAKcUCcCdKuRfLPZah9c3CLQID924UQ/10ZayyCISOs8Xk7/ETyF3h5CmnaZQhu0cDABCtjeaqVksppSyt1d6DEgu7S0j4eoB+0yz4zfhm/L823Cy2RRYqpY4jkkiQ6NW1tdpaZaYkgztpc4CZxcxL1flcmEVEhJJIkuTMDY4WJl8cXAMet1sRlhx+hwSMKaXW1KFOJozTfDqcx9aWw+mB3+El4fb2xaff+tSdb68/SinXWkubU8Y0grAIIQsl5mkccx7D40m1FS1kydRL8aXo4YD9FXIaxmHMiTkpWe9Jnzbps9/65PhwLz5sprwZ83/7T/+HX/78F6jIknKadFtDgFbRmincnYwYxA7RYUzb3XT1fCcTH49HVT3P53dvH07abp6NDmhrZWn4MJGOdvcITVYr7rXsDYfFYdWArnZiH6BXAcVECO9mYZDUDcGjj6a3v/TsrZPwHiGptTdlhbkuicslUabH7//dPaqPhIA1X3oyqby/zBOE6zc9W0cEQkv7oufS35evT+cf4GWXd/v0hdfK+PpyXe2GIqCllU22ns497BmHUYiW8/nzz/F771OWW8aDKVRRih7Pc1lKM1JCWbQsZTNN19fjlMfEKbMPkhnQolpbTiNA2tTVEeErKIkIrKmqVlOnkYlYRGQY0zCRyFAbczscnFDGLWQ4y5iI3KC2BsYiabOZPn91vxVmdjOvVVMSIpbEbBJJFBE4CSkbUQhgg9nIoFDyUoswRJJwZZbINNXUdGEmSl70fP1s+sm//cPPX78S4mgQSym1WoiFklC8DhvMVRfkjXl9e3iLimFP17f7q+dXbfKmzchUrczH6frj3eZKmJiwFLt+tn354iULDvcPTkg0JeTl2NrprJtMLvv91ShWz3a+P/OeT8d5rjVtZHs1piTVVETI0zimci61RtXYyQnN3dDtfT7QSbhYE3gvDwb6SVjVUujJ/CXQJUbzy/JYO+p+Ze6uK7Qn2uicQF8pJtHNFjn/Bdp9fMQFYgBA3tVk8WThPAWg/37jgkNTBE+Ojgisi+Kpi3OXrcPlgqC3H8OdgvHJHnodXePIHbRaCpqrD5ndQi9pRWecLIypyf1RPYrcLTwnLh/e2fqmFNRRIRZJqcem1te3dlUlDWaDoyvhRb8QAh0zdwpcK7Ad4/h2q249J/FLkqfefQbjt81FQlarb8hM6w01sAMS8uTDjAAAIABJREFUnoNkvyYd9jUT/XB784jtL8gLkUfS0DfdXuXxDtytYvHUsTZ70j4ej0mqazvDZW4xByD1lJPVOc/rm4vJIIPwRTt4FWZbRewRzxbdiP3gic5EBgcNqi8VEJHT2mIZ1BgGMZEQJfLsJDB2ILTzkDk79YYQB8iFzFXNzfreTE82ZAcBEhPIEWZz3vGITsAN4phdPqEDATcCuJh0xEXsDYPcTzVQ70OMK9Ang7tBoqGbKAh1Do6ZHW+qt+UT4HgEEGk9vp07lZCh5HnMA2sa0pATZVHX5tQFj6uDIiDIPAhIiNm0lbrUUzk8HLD0tprWzKuxEJEIMbNZ1aLaap15OV6d2ZAGGNrxcCjnNvh8PX50/dH1lDanN/f1VEGKgXShjqG4MSBgH2xN++Bwl4aE6fkmPZts4GbGnHnkUz3ZwTjx7tlm4ITK87GUo41Tuvn2s6uPdi3Z2/u7t28e5rlmlqBDEYsR3GmS8WZ8XrWeMIskFzczYu8oi6FZEwsOtRHYzGpTKoA3VnEeUnTtS0JyU3cidCG5XjsTF4cxGHB1Whtz17jBLqjyijcDq+SVs9NlyfjTQOcC9gduH79mTmFuo73OCwYbiD0iOGamnAESEeYO+tRarFZV7/PF4SEpAe9i8T0i8WiMNldrcGomCom+deLAfiRJ4mUxuJs18m5TSnCvqoCHd5vBYUxMiSQwrEixoewYpzxtJoIvS9PmtSoDrlTmepLZrDXVVirBJfM05JRJOBFRa83dpmmb02bI5eF9adZA3NSYcHU1iuTTaXHTUmutENJChRzX+92xnJ3YmnHqsnNRkkhpGDLf3Ny0djcMwsyEQRsVtEoGehAWSRhG2T+bFt++PeTj24e5GEt7++7t+/fvjSrLxDJITsykpWmrWhTqaPX6R7+HyWTIaRoUPqNkSVMax5QyiVDfABlCQjtMhfz29tn3v/e9afzDV+cSe7IDITGVDKKIqooakTncggyESmoNCW6u2pLkPsVj42DGigBeQgRiNkc1g8MFeZJhkynRUouTWS+1usN7BGcIgPcxhgGIhCWJZA9S53GGC1RhlDmloCE79Y6+LokekJi5qfWdHESch0xrzZl69eSJEzKRu7VSCcYMysksDBAMAusGvyvrFRdF9T5C7akfHMzETMRAc3MwwaIPn9mJLAw/1UmZOCjKnEWXZtUKDKrNDUrK6sFTMwPMJdjRDncm6pefw5tjdU703iriUd2KM6SfJquyQ1eC72Y9vtaB4nLHqe3mMM1p2G4202BOaE0NRsKIRQy4d6Y5+un7NPS8oNMGhInjN+Ob8c34fzZ6lkSu6sJlxosXw3a37UUtt1KWeZnzmEVya1qWqgoW1mbn03J4OG224zgyszBnERM2VbeuHoUGb9qun98CALmqmnvoYEJqdBcL43g+zstWxNX1zfu3xBi309XNtYB+9/e/A+fTaX64v5vno+pB9QSyISUApN60MaO5mfnpCKLFneeC+dyIkESSZFUss+bs7NpQt1vZ7qaUnandXO8++9bHI8n/+M/+sLwBU/bqy8PRySAhgM3ODpDBrDU3IOPlZzcff/pid7V99/Du7v0bCJ2WZWktJ+x2u9Zq09ZadQN7CoMlJuilFH0JIjva5LBVOKqzBT4ohRA9qXAAvZTQ4/vHpj9ivoRkBApXwt9007EmyR0YWjOUp38/NVLvL7zq7eLJ615Kf5fHPGJPT3/x15GzyIBVdBmrOe7lo7H3EsmKa62PpJ5E/eYP16PZeIJ4l4G1BWKhbnA29ZBGmOczXuPhlc0PIrhiJGg7n+bjSbSomiv5edbTuQrz82c3iQnBMyjNStOlEfF2GKdxOtlZQialLETDNAw28QItC7FAzSkRSUrDsNmOboN6BR+aAg0tYaxaahvG5OrTiJwzEalqzsN+QyllCzSsaUQg7lSOrZlJBjKsmVlt3uBqLBcHmMje0pCv8vVJex7LFCjwhH0lo/vD25fPtz/+yW//n3/yL+aj6lGcW56gpEQwRoMSiLIjUeNyrg9tqTAML9PLl8+215uQZxm301HPp+WARADtt1fLfD4/nM6t7HbbMpuIn45lyNxmE9Oy1GpWlxObtKqb7fTiZuufQEt9//7+7v09iXuyCl1ayTQy0TCknIs2WPNEIiJeCY0SxM2tNVq9aGIq9Fm6zrMISphCiG6l5z8V0f7N7O7LVFyfeJ12DnQ6Csws0n7vrawcvMo1xHsCTBNdlnekYtFy1FtJfhUa+VvHBbvquk0Rw8WCJfgT+7h1byFymFuEb/1zdPAFfvk8hItaq6/8HY/sXsLKMDguTJ19FhtAYIGX8JuMLtg0AE+ZLdABJmcSZs7MOe6cmbpa635GFJL79IT+BmGOHkk3b6owXPYrXyPWjvRfjCDii/7hVmAvwDYBupSvARxwHCgAkvARBBN0td4Ank6wXzdNAAdZ3FqGh6sSmNbyelyTrhOPgK4UQO+Pw+MEc0dqrV3g0gsIFUZaH2zHRBerhUAHiTBN4+Xxamr2SO4jijTJ4/nRSWp9mBsLP54HvdYQil4IbkOSREIuBiYn67pzBBe02nobvPdPFQZd1M0lgqARMISadzlDCmcUQdBYgiQHYnf19XP1v31dtx/Cir52ifWMhPgplTcet+K0MDWFxqowN0pRUOp7BtFK5sUKV/fLTBLna0Ah0nvi05DykCVcPcCJU5bsbDo0DEnJiEirIfDIWtG81tpMoYAngkOhaixCCaKs/TUdDd5QzrOajjsZxmGcNq2dzuelHd794Ds/3v32/md/9le/+Jd/AUXajzxt0NwbuRZzMzSEHcfak5wmoS3L9VhYHc4jD2lMm9RM3z282eTtsEmjbL2SZNpeDylT2nPNraLMbZ7PdRjFjEqrifP1/vr6xbPr3X5oUvfl4d3x7fyGKs91gYAYLdTpGZyIMzPAxGSsbHC4AerqrWQgZxklWp45OmjdCUahZUjCJubRvcTEFISHbuz6lC93qWKFWSRA7kTiTxZSv7VE3qFbp9VPlQPGMnMFiMFOlPq6jubCcNSuphpGtWF64hqN2qp+2XcUj8U063iqODPYzRm9ddXJaTCXkOfiQNBcIZTMFnS7Z+r6ft4CiEZY7RAoegJJzKypGtzg4zCO4yAidVlqUWbP6mnIGWzNH+6Paq22Ru5JPA9jHhgwkOVhUKtNNcs45LEmkpSQWkqDpJwHfPTyZrPl2k7n+UhoFGBabVk2H73cLp//wl1rcVMGjJ1EjLW11rbT7ub2xsyFMA485IllBEFV53l+yIcvX31Jma/LcW6l6Pl0eneeh6ab83zvXIUhTCkld6+1tVLrXLU0MthyTiKq1mqtIaamnniMPrqyFGkNam2uSfLzZzeORpDdbvvixYuUUseqKSBtVocYoAjKrYW5oFrOlESQ4c5knTvkcHaxsGV54nRBXfsQICRhCzl2QEYatkIJzZtS6zj9I27ivjb79++sLQUikiQRs6qdy4zWC0UCIgMzODhH6P4J2hfFZce8lAUsWp59Jd6ambPRalxDLO7aahUhYUo5q1XV5v5/s/euvZIkyZXYMTN3j4h83FuvfpOc2dFSWAILgbsCvwnQfxSgD/pXEgSK5OxwyHn0zHRXV9V9ZGZEuLuZ6YN75L3VPUOK+1HswGC6qu7NzMhMd3OzY8fOcWJxNQcadNoBfmyNGaB3lfpfthYHGg2boCBuU6+tc0DmiubQSapmQSjEIMJejKTplZiTGXv2/PQqDDS1gq646wQQk0G3PmLn0va8YTsvWrbSn4K67khvAffA34YKn05ygOAWQ9ztdqMoEZupurU5QQKlEGJKKaUY4/XV0CQAGma94YIdvfo35HU/Xj9e/36vf6EGaruKuaVJjgUvX7x5/fqVk5lVEOZ5uX+84yAxxJzXZSlwl0iX83p/fz6diohhz8xBWJvBdK12zaBbHG1Ifa0152xmMQZJMXBEVauqsPOc3XnaD4d6eP/hw93ju/RuCFHM7LM3rxi05Fz1zFIkoirWZU2J3KXkCkOMXE2rW61orBQREsbtDU1TgtH5cTEq+30cE3ZjPBzGYayXxwety35MuzHef3v3/rcIwHGc6hrO6yNiAYMluLROOZjdGKhAwO5GDi+HNBAu+nh+mHY71QIBC3JeiUgkxsBWTK2NhAixaMshsTXCHWzbeddoEgTTTq/9mMHUmssbgcipiwq3X3umVHWFtP4oYPSsN0BPbKZ2fm3UjGcsp+8/nK4+X8+Qow0vw0ftzGc//VPL0rcU8YoroWN623vveNn1H576Iq1Qv3bhf7ion71ZXPtAfhXediOtIuIGVHcIVGD69nf30z+PL75MgXaMh5rXnKXkqgYXUkMpKGV98fIGpeZlfdQ5L355PK3zvDsMQ5qiBOjFarVqcI4xTkMiDww15apYs5MQ2By1WHPJLBL98BK1YkjxeHuc9mMMlFc/7FOKMa92d/8Qw+mwP7h7NjPTVp0Js0MclZnHccjZ57nAyGEQ7k0uEEU/3hyGMU27IRCV81KLVS9Nm5bYWFQL3n14+/ln+93tl1/95LO3375/YOXiklwIpqpQAzFBxhiEK9dZH1Ugr/DlF29evnq5lvUhn4lCGKKdaq7zuL853T2Sy3xaltMZAetcHt6fxymWi17qWTXLUQKlIe7Jh4f7D+fL48vjixdfHG5uj48f7tJ4Gya+XM4u1UEuVm1tE10hsJLBwBBGUFVUBLC5l3UFiT/lK21ddFCpO8Y9EaKMwO6VHN2Ola6ryK+b4HvLHk+L9brEiBzM1PAdU2MmkPQfbQysvgPJ4K0xTdsQd+8NUkd5nIn1T9vS/fGr5Uctqdp2n7lz6yo2AWt6Bi87nEhrZWbfusUN3nLuu4UAcPvF9gK27T9idt3Kqh6juqw5Ot+BtndMPZ9s2FKnUMXArQ3KBAYRIxASt7EhbaUj9a+RhbhbLVJDGppIBbUUFE0cvrHGQv++4K4N/m7f/1awXk2B+letuoEeoDbz28Ont0EicaKmnkuuRh+HF3f/YZBrSAy1BJ29Te9rE7JpD+mDBdeGAak2pAIAEeQqstGu8NG3TNRQbVXdlPB9g2yu5KFrJKRhGNZ1LaWUXAFwoPZJEshhtZHUzM0qtiDr7mrKTg0+cO5Lqx1KIYiD20AcMbs4B1KubapQQCIcmddL3Y4RaWue4F2gjChxCiFwEHNnLaob564BjeKdd9O7D60O2wwm2/klgDazxCui/FRHERELt3XfZnOux56ImBttnN+mBdP2XwxBjPWK8TLIAOnPb/AmbEJCTI0aaCRK7MxYysKRWUgbJ0UNguQ0jvs0DIhYlnleZ62KClPN65p1tWrOTkpBhIhUTbU25K6YKqqzchI4yDgvdbUcximEIJGzmWGd0vT3v/3Fq93L//Rf/8e/+V//y3/727/9p7//9eXDA5gomWy8RGcgIoyAIA5hf9hPt/tv82OmugvDuIvquXoNQWr2x8vjyMPAAwKPt5GJIZh5udy/m+tSK8aXIfn4yYvPbg6vzOzt+3f//H/9AvfAgN0wcaEy4+XhdjiM83oplrsaWkAcw3SYfHahAGHLXqN66TGplsqVBhqZoKVYAStMzQpQjKuIuhW1ZnnAAEN60CFsFMKn1Knv461udyMOALok33XBAIBb9/1tEUPd4LR575qhGqfQxqdN1dgJqLnUtbq7h2AhqNYehmv1eg18DcoGUz8xzNH0KNiciAwBbUKM0PGo6k5qRSuTkx+PR621IbwCbqirFVPTLjlEgEOEIolzQ73Umqy1SCDWXC6nJS8+TAQLUNHqDgsEALa6wXkAiwNWambiYYgxBrd5qav7PM/FlUNI426/P0wcdXd4EaIRgygQBiuXZa5alrCL++Nxv59yXmrJZYU5PBV2sGGlHDgx0zhFEUljCCkKRxYWsZTCNI1vv3s35/P+w27Y71j0eJOqQoIfbnZ7n5Z8qa5FteRS16y5uDZPUHbFuw/3Ys4xUAguxBwBrWuTgqg+DmOMIrw/7F+/uPlwencYX+6nF4fdwQtNQiqpNiUk81qVFvPZvfOOGorEKKhBY4xNKdwRPLidHKQtzrSTqsWaRsQ1al1iBxwJcWARUXbTXKw2GlE/GPti5CaC+HT4SbP6pSAphsEJ67rm84IKtmbva42IYF7Uuq8hBW4DgE3GwIUAuqpHMsSxeSi1tNi7cpOwkHB1haqX6rGpQkrRZpNOesXCnpLy55sJDhgpUWwnYf8V58Za9c36oosYendfL6WUWoQkhdQOdk5MQvDAJAhorMCe0jdxQeka+0QcQnC3kivcgebfzUzsbezT8CxDav/raUvfpw3i99bU7E6lCu+dN0eMcdrvEhcQVbdq2vp+wjwMw2HaHfaHcUrtvDCzdlYu9ZqDwp4aIj9eP14/Xv/61QU8/vhFDhJhgxERIr786rMvv/qShFUV0R7Oj3/49vfTi+M0Tedc85rNQMU/fLh79wG1Yje1tFzQxsbb4HDbogEgQFG1qmou6zzP5j6NwxRYIoO5GqnjlCFhSPtxZ7vT/MHclpyXctGy/ubr71zr5fFyPj0wyzRKTB6Du3ogHsIkSMSp+GpejBBiHNI+RRKpw7ADcJlP9/dZFZHqYZp2uzgd4jgIi7958/r2xfHbb7/9xd++Q0CoYFCkmI63le8RFOTV10b6hGC6lU8+fXm4mYZJPpy/Pb09PZ7OD2d/+TopXKEOen93fvliH2OKjOyl5uxaIyUKXFfTliM1KU8lYyFvzt/McJBV082C/AlgIrhS6xQ4Abb1SDoRwNzJiEiaPJJvbcitPMJWfm853fbdA3gGORmeAWZE1/rpGZmq9ylpw+AaarZVT0/WbN5O4ytF64fF//Ml+DGGdb3Da/3rV9WBp/v+V64rUwEfw3lPVZ3lkAKxas3sgTD4oL/++rs7efibw1+ShyEiDXBHzdDqHCUEb5Ip0BoCKEpigqGWbI4UY0zRzZbLXFcFAKtOSuxwF+ZpGkjCh/tHEjepxZa1cCm4rDrd8E93n5dsuZT9YQL5vF5KLiHFOA2a9TwroF/dHkperWt0R3NclmwVIuFwc5j297Zko0wiPAkrQ1FrjaMM+yGOodR1nlWl5lL2HpNE01pqXZeiFQRkvTzmdx+Wb15/dayyyH7JK+fVZwNT02hwCCA67OVwE28Ox5vjcZD0ySefmPk///rXIKMB5/x4qScMvD9O5/dzPhWrK4hQvFw0h5okRto93j9Ow0BzrLXE/cDTSDpc7h/r6c5zvrkZQ5RXr1+Nx1fffeDLshIFDlzXnNdcS3X3JoxZS0WhPFepkkIScxRDomeMi760iZkIVzZNB2YcXQz0Srv4F1faRo58Nqz6DLolZlJF7Y3TqE7M1khG9mSfCXOgD7I97XXD5oLYsKT/Hpp5H0rciIrNqq7/qOHfhu69tb0FmBGsCxi5w5u5T0/n/FoA4uk2mYgEIKlaCI2jQ9SydJiZEjcveSZiOHvjURr1T9xA5NTAPgLQ2DeNCtwcF5wExOxmzU1QBE12xrVp7XcZFnK4OiqaQ9RmSAi4w7wJG/fpMXfqjDJ3NPShBxmDF3egjTMYMzuBQivvWmnpV4m+/uR4+vY//vz7f1zIuc+UMoPcy+KgpnTWxJe9KSEyiVNnUzUxIVxNErenD8+WSf8usY3+PfvH/v9EzRySnv/aJpJFQcJ1WbgRM3W9YH/+3IC3BpQBfWyTiL1x04D+BbeXoO1FG42YiVlC4FVrg6yot8eFCC1HaL8jLEJibg4hkDW7RoeaBYi50nWvtU2BTvZjJme0vdy9FrYeR3OgbFurT4s4mqwVbYcWuhpVL/178whd/MQgcL32ZZqdhW9DH359QwyCG5uTM4MCqRWmBIKp1lprVheHIAyJg1jRutY6FzDiEITYHaUWr95U2ciJm82IUUPLjEy1IrrXdtIUrORkmi3nbKRqxQRvv/sGkh6y/PxX/5CYTw/v06v04vPXgcRNHx7vXTOzqykHxCk0PsQ4STqKfoBwpMDunmstpcYQatX5lFda9+OelKZhh0CVaiFdrSh4mOIYdjiHy8P8+Pa3eSlZMziFnccqsooVpeplzd4KU2E4wJAEjtIklsEC7fwMl+ux33TKAEDVXQlVtRoqSImMYFAldEJT07empnmBjWXdd2g78s2v6xkOFjYz79ylLWQ/bdyO/jbckppTpWMTtenOGgC5olIJaAbYXmEOVbWWxzSFtWtWBHHPrbfYFk4LKa1lSUzXvgmpm7Vy1wDuAoHhVpiYIYGEifsAtzrrZmLLm2gXwEB1b8PbIGitZqLVdDUoXEWrr6a1FCIfD5MIab1Uy9zsKuBm6mSGent7LNnmszUsbBx3Kek07Xf7HQfNua55FTLmEEJkFrO8Lgt5nKb1Zr87kV+q1WJmUPFaawiScw5hySU7PMY4pBgkOMjdmSkOw34/OTAvi7LeBBoOw5vPXs+XdbkUYhC8qtWqTDMTlzV7VSgFMIuz8FrqFIdpfzsdDhxkXpecVzImRSLUmtNh2KVxHIYhjqfTwxSOhxADh5o9hggKPbvV4llthV62KLwZedSaa9CWcIsIBkdAvmR4lxT0ja7cuqzMzExq6m4ePIw87AaYryWXKw4LYNMp6Ly/Z9kIgbYBVYkhEkhr1Vw9Gwy+Sbwr3FCpvzRTEA5MxFBVU9CWbrRoaUZBvHfPvJ+KRCQsvejAkxGy+rV5DQdInfoA/HOG2FZfOIiIgTb9D9i1D781IpoXOzr9u4sKtgeTwsXVVB2u5k5M4MBdNJjJfesndAiq32T/nJV8A4mJ5Ho2bjS07VV6zw2NJo8tctjGliLQdvy09+cAOHKIgppJuAmUwV1EGBIoJE4xhBhDz6OuVc9TktASFumt0X9Lb/LH68fr/6/XU/n0PMW97o/Oqsb1b88LM3K0waAUQkb57NPPP/nkEwLUDfB5vTyeHngKwzAyn91RitpqlzPWBTGwqedcRQJRy06JiY2VhSUI4KXhV6a1VqsOQ5Ey2BCoAR8IwrVJcDkZKIYEQKKz+DAMu5TWZV4u51zcrKrWoWIaGbApxWmIMexA6VJRchUGkUhIElIpy263zzlb9XVBVbhzlJBSE831m+Px1c3Lm8Px17+//+7b929e4f5b3D9cpChEEIGwdcEJGBBGfPnlF3/1n/+HN5+//sdf/t1vf/fuu7uTKtKAOKaJDVFLrllh6qFXeOoKr32SqKvBOMOoReZOfO0cd2oV5/OqeYNdqHMe+ph8rxrwbNLp+8SorZdNP6iyWuaNfj7+kRi6NbnBxL6lSNdw/JyZ5Zvs6fN16Ph43vHjZfl0f53/wd/72ffu1rfC+1rMUZ+23/75h5eDvvcUV44CHCCGKpypUDTNVWuVKAhDXcr927v7t+fhVWLCGEhAElK5lMGJhYYBKab58rgfRmFKUYYEZqIhTrsxxljqmtcVhhAjEWutuczn1asyUYgxEFcSDsFCjOC1QqtV57A/3JrSu7tlXh9US17mdfZxnGKQmiAJQtBa3Y24yzHXWnMuVe3F4UWMPEzpgWYwKLgEFg81F5gbuwdXlOV8iVU81tN6+fTLr8wzPK206FoKkBL2h4FHuju/pUF3L1Lcx3muD/fn949o0jpQVKCKrq7IuInDdAyR5ZwfT+fL6pcwBg82n+dsJY1jCCGwLMvDECfacVmzLqo7R+H9cAw3QdjWZbk8PNZlHnaSMN7G3cPl8vb3l9/94fIff3rAa4zjsJumYloLYkpa1XytarX0Je5N1sMa+KDiHCXl7nPjV7Y4EVgA6tNL2LAWZ/R1pE6tNXgtZp4tI++60ER9cGXbRM9ghufpG9z7atsq64b1buvfryVWhw6IOlaAbXP3jfMDKuRz5tf1hZ9F9e9tiStnxbeb7dZdtonkNVKMGVPTm34ii/mW3FJXOHVjbN5whA7KNeyJOjRPgPQcnrE9DESbLha8JYMtV3S0IQ2gFV595oz6lCczOzfZ1meDDu7BBQ43V9OW77uCQOS0USs2JL8NBW3Jcxt1dNvSeCd+GuCGo7MzmjCV28Y+u5KKgad64wnKx/X2+rdDfcju6sqEp5h7PZENIDMGtcnB9ptNUJYBbzVL+2yeXAivf+icoGfK7l1utq2lZ1H3dDq1tRtjaNLvfm199Lyhnz5Ay+Y3wpF5131v8oqwtkByqRIIYG+ytw7TbZQJZA6hjhwCTQ3FQB10EuEmDQOQqrm6mjZrz75MzdU0pECgPlDPBvZmoNsGPG0TrvJKbt4Ehrg/MTcDOYW5VQdUjTreaei/tjlNbtugbU8WLrVsC6OpezU+BQPkUDCYSUQU/cYMBoJEColDGjgwYCWb5qq5Nj2jJSySeM1z1jXEECQcb3ZDSr7bZcnLvLbxmVqrsBOYpE3vN9DXGWRFIRRTlBQ0qFZ9fDgZ10pwEkkhDIO5/e7hWywnYhzTDQ26O4wShhkPgYfdYQBMooRR1OtallyXeV73x0M2W8s6lyzkta5e1yQQoVw8lGrFa4XEULnOuGS3NIY0RFLaTbvT2/nx3Wm5LAAhkFDgyufT2dSjhItdhnEIQYx0jAMGhIk4cbFsUHLWomvNLCQhqFUQsXDgyEyGrSBuDQYHcaO1UDUNzSMMTcWx0hamgKu6uzdqhm8Z0wZqteq2s1bQi33eoqx3vJM2i85rCtgY4wRvDhtkAhFmZ9NqWszgBDJ1wIlJQhuPhZkReWlmCN5bDL3wbsZIBGohUduucWwaqURsMDIiI3YSMEPczas3AosQqnXXM3cjQhBRqy6CQIaKNmK9qhaHQDiU1dyrFoXbmDQdp/1+VypiwjAMzDBXZhdGKRnAupblnGsmz4BjmVcWDBPdf3hryLc347QLajXGGETv5zUvj+OYvvrq8/d3AlUtCwAzlFKJKIRYaq41g1QCpZSYoX0SkgBK48gCMKnRktd6sU+/+NQc51M+nR+JeJmVGbV4ipSzscFSftSsAAAgAElEQVSKE8cwhilMX/7ZT8c03Ny+SLtpXtf7r79+POfIvDu+eHVzePf7r3fTfkwJ2s59r7UwPLEIUVkzWECBgZphC5ABvc4iw7z55zlcKxcMzew3UKAccp9T7We+E3MDEImDB/JqBuORZWQSqm4Gb/EEfck1rhDMN3pgO2gqjND8MUUkkNSsy7LUnJkE5oI+kfDUWOu6kAYEECMw9ZMQRM58zWbadugHilGT5iMwG1SbizxttAQ1IrBIU5TSjUvcWgBtKzETGG3AFw4Ce3MJdqu1CkvfhW4NKXPvzjV9a8GZiQIJS0Mq1c3dAwmB2kRlPyKb+y8AJr+O0ltrbjlRY+pSO73bbVrrF3YmrhkgElqAoK2gaqP5JEy9tvGPukgMijD4ZTm/ub01dzUXojFNgYK4CHrat3V0YG61lqeEresPmMO+n9X9eP14/bu/en+RWjf8qf7yrbkFdMC6/9GcmPKysggBKPjJT376F3/x59dfOZ3P58uJz2m336WHByJa17yuqoYgmKbR4fd3jzGmrfLptaJIp3OqVlXttQizNSd7cwClVodNY6hmpdacZZ3X9vCqyzJfbj97/fj+92TmXpjBjGGIIbShGEACOJbq6nqZ9bt3l7yGmou7jiMvc54mXZa55MyEIBAiJo+BhP1yPu92nwcZ5lmXxVK8+a//019+/cv17W/O798ttVyQSj+MBvzZF3/2s//408PtSIMfX+xuX93s3x5evnq1anZrSog4HA87281rGXOZHy9WHcpaXDgoqBZlV2/NBHuarAQcqk5dh9QBeZZUo7d7sfXurgMSLTYzupWPX2uZH6wHdF0VPIORroX3n2ZFtYuFzak18Ft1zST0rMBxd3MX7vL8vZjqpxd9jzTw/Vd0OBCYNyev7afuV04zGrvjeVd1a0u5u4h4J/ten5To2r/tx8gTInbFAkHOYqWuiZljE2ilWomFqISf/93P/+Z/+ZINYj5KSMfjb7/5Tob9fgq76fNxCMv9u8g+xmGcwquXu6UQD2F/3A/jIJWqIQYKImC5XPLD43yakQtYhjQOIqBg0z7ujiJiSz5LcM2yrLSbjuOIy3wGWYzh8aHEVHNZ1C1Is+BWFo4kLO7wnMuaKwBzXcqyP07v4x0iQMYsgclFqlV1nfPl0+Orb9/fgcc40G4Y/sNf/OTtu2/N6s3hsB/Ge54HkVevD4eX493y7ryuskv7MA0F48305VcHALV6Xasbhinx6DTk8ThMwzSflt/97jeXc5EUgFUrkZAEVjdAa5n3u93+cDCxB635fp3TEhETjTe72w/fvn//zbmsmOXBwvnF632ydGQVhppeTvndt3fTcd/kjR7uLy9eHpnIYUSoFcxMBFMnJxKGoZbqkDBGg2sjEhF3mxoCBfLmIcfUBJqMzYlYiM2V0OEMe45cbfz3LSQS01aAf4QeNIjHSiUnaQkjSDd5FGIWZttEsp+ryzmM0IZ/faO09F4pCPqM93PdNx//0zU/6huTtqkAU+2bwKCqrZZBV6PepOrhHOAOVTfSJrjLQs7Qba8xEUsr5oGttwi4KVg+BvKIQODQPbxasHcHdT+1psZ2ZaJ1s0K+YljUR8aujWciELN51/5umKIwM5hqV6k2N2j/6LAROIjAkNbMbq/W5ii8DwlsB2Krd6+qU7TBTU5m6DOAG0jjhj/BZu7AVa21NRXcm866u241wrOvq6W26P/chbZBaFzcvpa4O+O1K7TgfjVQawDW9yJ+l6vduHtbuQ6tJoFDCFcJtCsQuAFYT41538ZNAfCTuWJ/j/bkNkVOIhx6bQ+qRl4VBBKnIMIByNfHOqw6NWkXakbl6Pjyxg/rgnHu7uo1Wu2rwsFMQiRXzX6nPt7RKTnX77437ltj3bePu30i3sEDIhEJIs2MpovjE0EkELFrezCISYi5aawQ2zb9T8wsYmQgJ3FhICBElhQoEknDLDTnjBVgKK2PsDSmNMgYJocykanXUmOM4ziltNzNd0WKqVmpnfFHbI2Aw13wMqRwfHGTjulip1M+aVlpgKSBQohvDrXAqx8Okw9hXR8f1oeHy8Mrv7m5OY4v0jiEYQiqRaKEQYp5nlG9LiUP6WY+rTnnIGARclHVFHfTzfD44fT4uJoCnk2QduBRqsKWGsn3w0gzc6VQZaI9EeWy5qXq4qzMRKXWtvBiTMOYDscDRlcqlYqSOcPdnCEhCphdTCIxxyhpHzmw24zG2Ox0QnQ8GRDmq/RMR9bBTC28bg6b3HnXz4W08dyys6fAf2w7t28ATmBGE3ujZrjW87Q2rycBoD42yAgcmMi5A2adL9rKfbNNbhHUoFcQtQbm1qGgLdSKdIFGEIFcwHnOWqpaM2uxnkl6U45vuXptUkdMlGIguIpKEAjiISzrsswLDGlMzLEsOc9rC8P3d+cU48uXt9VGEj3sR2IltlpXd3/3/pvT43r/WB8fUGY0l8z7R4RHjFNwqyGAKEs4DimO01BWJax5xf3Du7/+679Sy8vlUnJes1nFUtTVp3ECmXk1r07qZOCQUoqRmXkYBolpLdhFdmCZV2h+XYw5EcSdi+p8AUfE2ASQglutVYeB0ziMKb3+/DOvdsn19+9+/+13333z3Xd5nYcgX3zyehjSZ198eXtz0HVdzlUCYgxkyLoy48Xt7pvHDxKZAFPDaljdMgAOlEJgwKtr1Qp3KKyacgUFCLMIJybzZiLeVk83rmBXqu5GgcdhwOCV6lqzVnNCCCwibZ6VOmraQleXsepdjUbE4ygUrJpVI2NGSBwLV/INiNlKgS6GwNyPbWwd4I3/BGn8VWIW2lpkzOTUtK16o4fIQRSYhYmYwZAmIXc9Zq8byLlt0+39A88dT57OGm+NAGKQGW0Hb8s/KLReAbl66W2pZkXUiLlNU6CfbB2s6x65ZNVrVhJt2DATg8Q3pnlzvd22ddtzG2Vxexf+9IdnTcwre5MgCSa6lPNSZvcbg5uBRJiwT7uBBzbx6tr0OHk7yD/KJbuW6L9SeP14/Xj9e778o3P5I3eIj7kw7o7aTNS9gUev37x88+bVIOXClJHXki/reec3h5vj8CECKEVLhTBSQrOyLcW0FCJXLaVmR58QICJ3MFFec0yBt6xj270USCrMlbWirqpFoXB1Z7eqqlXr+vjwdkr7MaUXt2yuMRALqE1gsxgFdTmd1+/en7/7Ls8zYqims2lQ9ct5XteZRI+HRj4FQYdIQSiKwCTG/e9/c/f113cSX/7sLz9//QK/e/Pwh989nE7nl59PhmLmMobXn7z59LPXMdG7u3e//OU//f7br4+306dfvJGBTufZ3YkkxMDCCOxkDx+K5uIVkYbAiVhqzaUUAsmVS8vS8pBNTrZ3Jpxad5y2Hga+F/BaGO6pfpMa3LCpfxmQ2prof4wP1e8J2DTO21KhTQTx+7S9p9V0HS/64ev1svr5y1Fnmrlveol+/d1W0bazzLdjajMz2Tge11v9AS2lPw+eQwN4dnMdLtx6tDGFWmpRHWNIHM7ZdFUQYdHTnV8+XMZDGEgGSVnn+WJxyi9ev9kdRmb77d3XJVMKtD/sOKaHS81WwQ5xBlICs8Bda3XHkMZcdV7LXNYC/eLzT4yWmChFVCuqXgryWmNYCSO5MkFEYorz2VRLXhcHR0E27HajmZViZtmtuikAIlzmyzhcQkq7Qzo9FLOmtp4pETl8BQzDIdi7qrXc7g+f3L48Hg4Pj3en0xJTur29Oe52QhSDGGmVmrFYyQPZMO1fHG9THKv6uuScwUTHm+Owo2Lnaqae395/M5fHVXO9UEgxTFOIHBCU3LSs5+WTVy9jxP3dJd9nCMpSNXim8ni6//1vvrELAEBXRJyqOvzli5v9bcx1WS/zN79+++INdi+mfCl39/N+NwgxQ+AKchGhFGqoVkjbrFvTczOiyM4GpW5KZeYs1pYZe69GyZtEcCuShFkN7G5dReia4jQ6Bl9B2yte/By9Im6DYtgWLK6BeCNg0oZebcOE0mIvTBsV7LqK/0WZBP/BTncnfkKW3Z9BWlu8uSapG25iG+HL+8QDgDabzGhqxx3tFTATCztM3WiTkGp3EKJs5onbS29blwDnlpa7d9M7dIW/FsSYfbu3bjyBjjfRxmrCxg7iBq01AALkmWAOdddmMiYguHZ37I4ZgrstXrMicnV9gq4aPN7ybHIifYZzS+/d9tFl75JWTwHre1+Ib4w6oAuZobG9jGnrAV+/29Z11jZC6iB5Ul03NVgIUaSTPbwLfiH48/Hs7bPudoH9JhyA03PlrO1lGY141ThHTcldrcuYbJ0G6tAY+uCEuaMrEPvGGXtS5m3LmF1aD4aJA4sxAUpEaFaU0sJtG4gjmLq71tZGUBZmkFvXw+6qjq2fb4RK3JZKEyzBNv7agAyCKxmciaRPDbp3e8FGa3729vueQaNf9o/O3du22/BYdjczYW76ao2w23RYvHsJtI+BiEmat0sQsFEwBKfgS5kTDU1fjEHGjiA8pJTiNCYZQ9NSWpbL5XSpQx2n3TCEcRp2N4d7+oBgFAM5ucHd4AoGAiiSB0qHFIcQYuAsVosR0tBEEFFyzqux8xgCJTZLEmogxgBlVdZFdT5fLpcLRzocdxy4wDwQ83j//r5Ui0K7NIlQYlauu3ESCmZUCwBMw5imgSdWKXU9oXUoEb/7+jt9cD0rmzCTmHAh1gZMg1maF0MpJU1pOk6c/Fx0zjVbIaC6gSmNIeoQQnAFQUIgTlS9qrYh5ys038KTaV+JW3cK1qWhW8S9GhT03erCct0g1EGup+ckpmtr4vmOpg0302ssNhcK5mpQd3fr8TGIGIGIwzN0+GlXUlN7CNXLZtsGs6ak5t5eqSu7kTuBRdpKoy5U52SmRoYW/2AEczKHU9+LBIIIGQNCHGMAXAwxpZjC7EuMcdx5DsocarFSDEQSxKGmvi4l5xqSSJCYBhGrNauuVYsZWDgGDsEKb5ogDDWsuTIQIlgkxTgOY5RgavnVac0YJgh7SjwMIQTKGdwEBZu0VF3dKzNAFaTEEgMPwxBCSMMgEgkIKXEMRetynnMh4TCO05Kzr7n6wgo1NpcUJ46o9UwSdtPu5nA4vnz1j7/457//h5//8le/+e7d3bI6AfsJ9/en3/8h/c//+a+OThIHEndXs9qkMQPzGEMiYpJcTOfstbKCDOpEREIBZFbtek5Y0ZbeBmYi7I6T1VwKVNVaI4fc3TlChNyNmGQSZ4N61WqO0CIyMQwGI284LZGLkteWrAigfbB8GAZm0aLNP5uNhHlps3Idm+ogu236BI1ORQA5uUM3SIiIOIRaa5vnxhYDQdbnvIkYxAxuFKfqHBgMFiYIWsvoo6bMdqY22YJNGRfWdN7JXd0BV4brVh00xjtDtTU1rO2Pzee47WVpbSwya24JvZ/fUo2ndN8Bh1ewgEXQmry+QdXd6IBbOwRA65SwObjHGH46OTtY3k7HXoJFhJ1Q8mx5KZdLXh7P55LL7eGoVsgYmaIHdmoAFno3zntv5an6QHOz+RHE+vH68fq3XbR1ep6GSkiYmNjU8qoApmncTZNTaWd9I8OmFEgoBpbQFUaIMQzhcNiB+DKfwCHGEKO6LWZPhOzWP881cyCHuVrT/BWSwAFpYpXIWOt6OS3jRG4ukgjVzfK6Xs7nMU3DkMxEa+vmVCLEwdMwGkI2mCNXLAvmGesKV5QInzjGkQCtalaGAUOScQghuLAKx2mYDtOL4/jmv909/N3f/9PNgDfHTz/76vVnX4xDPN68uPl//uH/PN4eYoy5lss8v/vw3dtf/eHnv/g5pMqAP//JF+MuTeMhF13WtdSlWAFxKaWUIsLVrVQIGQIYzCa55hiEOVhVN2eSVodah4ecTOFNEIu84U24fl0f4VMOb2n/94Lg83L6h/+I63NeaQ7PLv7BA/qc3vPH9ynGJ62r773W03Ogh2t6er7+kB7Ct1Vk/qS+4gxy8itBgvqd0dZqfXa7f7Jx+kPhoI3S0XGKXt1ThKvDWcBEgJETh8FBerec3p/H4IMH8SAgr8jLmenNOCbTZX/YM9ypgisFOGut5bKe+WJwq46RCYYYU2sZjZ7WGqAUh5BSAA0xOrjWZbmc/f4Bpvj09TCMaf7m28cHHI/CsTDrMNA4sFUeBhTFfjeq6iqWc2WBiJDUUnGe8zQ8vLr59PBid393vii0GLEPKcYgmSsUaz2vGeyryM1uTHf393fv7x5PD7sxHY/Hm+MhMte6VGQlM/G1LnlVZexjWNcyz/PpfC6lTOOUjgLlb9/+7nw5C8dv/vC43w3TcXd3f6kljyl4ZCZS95rLtMOLm2l9tNP9BYrP//zz+bSgoiz18f3FHjHEECWsWuFOZ17qHHaD5OHy/mSJ7y/GuqQ0TnEf6aGumcBN2hsAIGBxNgoMQ9sWzUCvlALXtqhaHujc7ORA3WTcuYklmFsjSBGxizukDV6A2HxDW7Gxjzp0tVFNn63D5/7M2ACZLTdsM4sdQHCHXVEgx5OinXvbBGispTaT8BHfir5vSHrdEIRnm7XVaNdx5Gf9C3ZnJm0+cIARkVnpuAXQhCacyOHE5OzCzMLE1N3pqeNctIlm+BUWaCTcZ+AybXLtDd3rDCzvbchteKv3V9jhjZq0wdreY8UVDKSNUcGYdUMgDI7QC7neXvVnukbthbpehbl3oaXtZwB1h+/mig0UwK3L9ZK7OvOGYf3pnPMK4fUbN4ds3ItOLsM19PXgJmgfuLs0qKyNDbWZy+23vOXdQaTX4d/DTb93H0Qfxez2Je13u/bAUop1Copv3x+2ettDiI0jbdbc29Wtc0KoCaK3Vhe81NpKArUmAK9UGdI6/mRel5zhGA4B1FsgajAzqFM1EFh4DCMzm1tZirpRE9cikAHmgwy106aciMTZ3WupHZsgEBmDOFDodX1batZGzT6CJKTpS5obHF61WlVmVlV3iHTogUAwi5wKFTOrVV2NKzw4BzLeAG844HGIbTJOqTijaSLt9qM78lKWU7HsFIVDsGJhn4ZhJwL3AubpNoGpFdDnyynXqqTTqx0pmTbyhAOhqpWyYqTpOKVd4kCXeqnvH9YyZzMZYNV0nrMCiORR0gSQKYY0hijrms/zesmrlyIspZaimEZRyWBaS141mxMvwhCRoFlzLUI8DQfNdP/4CMTjYff4+Mg0pmFaNT/cn+EYpiA1qePhV4/kFErUqjAnQaTEyrlkYpIkxexyvsBxu79xeIVlq7nm3KzpDAMPwzgmH0KJKKhViVFKvSyXbKVtJruiV+zMYIEXtV6TWsMqhTpPpVfArRw1CBO32GSNeNuMZ9vJAKJWzMJdv9+ga2PL4pvKg4NbkOVWNKupZhIJIaTnmdCGjm6b0dtcK4DiG8gNtCHXJnREIAotvBDBzIo1touTtbcfhtCSp+7RoOTO5l7XAgICggiRhxAEZLnWUghOwchda4njOE2ieV7OF6EUJRlF09L29+P9Ca5xCsMoKck4BmaWEECelxmQYZS9MsPy2ufFzc0MMSFFSUMys3m+WEzH4/7N6/80pGEcxih4ebu3muu6lHJ2xzCmaZecvJSVIg1DZLHLfKprJMaOaqihWOHIpjAVZ15WXFY8PuQwhKrIWdfFlgUEsOUy1sgsxKWWmzc3P/vZz37yk5/+b//H//7u3cP9GbeHw82bT8Y1Pzw83p0X//o3pWCMYf0Pf/FnX3w2TGPJ9f7+fuQb2sPVlvPs2V1rOefyWAEMQuaubtVUlInMq0GdhTvAX6ywgsQdx+NUqnCptdbeGyAQUZAQYlDVUkrxYmqqTuAYREhgbu7sBKMNYyFucGXoNFoSChJjiETkRZfzss4zMmColMHRHEROYBAT1K6y7DBVJQDsDpib20YOEmEWL20mms3cTAEnkRbn28FEDBEupVariSAcKbIQ1NxYm0gbeTsq2zHYS8zm4WveUUtCU31qCnGNrkidBQ8ihxAzuKpZUXWTwIFFXbWlCI2OaHD37gWBjja5OgjCFDlAqOllwpiIjOhptz2lJNzzCLTPxfiPnOpPx2tX5iQPRxoOEREZpZA+Xh6//fab85//7KubT7JbPdcsJb5MiSNgYHCbAgbcvKdBBDg2icYfrx+vH6//rutZ6cVEDq+1MnEIVKtr0SXPFs/G5eHxblkvS76c5vO0G2KSm5tdXqucV63RKcYol0s5nR4phiCxHdxu3Qe+lXkiMk0jMZWaSQjkh/1+msYY026cVDOhrsslz/nxTotehE3Y5qWUZVnP7yIwxoUQL0u9zIUD0kTTsN/fHNe1fvP+MWd/POn9Yzk/0nnxFGC6SJhipP1+f77clQVM2O1tt+MQdF3PR0+76XDYvXYdHx58npOt5Ze/+L9/+U9/eP+HBzhwEDwqdoACGRAMR7k93KY4vr17D8aXXyLJVIuu62pe3XVe5pxVqzuYOYiowZalLFaCJ3KjjUHUegvq1CJ6r7I2TVHi1jjYsKofmAk2Hq5dKbEf/WxzaO6N4qcv+l8mZ/3Ry9yu7eqntdNX0EcY1p+4epukFUf+bBbl+nAA10JtY6v0arfTCYjQzLPxUfVof+oM+NfepfXpfFSNJMSotap6dmMm8RUGQub3v50HQljHfdjdHvAXn9/SNE1DGJJEmezNbc2r1nJZHx7mslZWRlX1uTIggmk3COK6+rvl9OFDLc7nlU6Lylmono/H4cXL3TROspNl/yES8uqXh4e8OGkYUzX1grrb4/b2dl10mTMI+x1uXxxKyXwy85WoEnMKIzHPl8s4xduX+yFEzfW7tx+WMxiUjilU8JBdqtmyf4Hjcffi1TEGfvv2m/PlvCzLupyWZdGSp3F0LzUsiDbuJ46xVjPWgvXb796ez+eHR1TFzeFBBrvlaRh5XgsIuwO9fHUkTsuqc1lLKe5s1VncVP/LX/9VNPnDeo8IJAwxvJ9nNZ3LcvrmhAs0eM1Z3eLIroaMtE5xGcsdf3h4RMA39/er6lc//Xwv8eHDHKJoMcYAX1Tds3pveDrYmkgTnEIKqk1IqDNLHErNmYe81koAJJhpEy2x4FEiEbkad28mANRcMv/oOm9PC6BRYRpKktoDfUO+4HCoV3ZiIe76O+JBzdQMqsog4RCYGwe2uXbzRnfpcMyzvUxMzwXqAcBbx+CJi9ObrNuW2zI5qmqqzbK9yco4yDlwJzw1ZEAIRNIy0w5cbAQdR9NeafIdBHixhtZtmuAAHEJXcKWjWe7u4I7t9c1uqq38bBryLQyEZ3v9in0DKL0dQuweQc2qC0qt9PQmYUTSzh03N5hu2vy+kW76DbV3CNBVaIacqCfm1QjVwJtLIJNbS3ub18QfDywfh8QGiDfs7ikuiW+9g64UTAA30d/23bUpJUUhfUL/262H61d7ZWABT+Sp64+20+IpBW+MtI5KNY2QZ3btVwyrnUHY0D5rRbijzSldZaPa+VW0qXZtL9fxYLTfNQBStZpI80uAO7mba7sdmBlt994+KHjzdyRvuGYGjNi3McAmVm3u6t6cp658MWtWtnbFgYnBkI46txf05oK4DVc2eRhT1P7cLU15OimNtHpbnUpAgE3eZe82CKRRjBiuxGBtZ5S5TtO03x3mIZ8+XPKc1RRDzLksy8wCwIiM4M5kbGpWTdWdPbz45IXOOl8uyzyXUpuGt4xBRpYkksjJcllzLuYWQwM+YRUwkHBLOsgp50JCnCJJKL56ds8mgVBFyMylFDJYVnJKkSSNUYuyoea8nGdiYMdEtK71sLs57I7r4uqcM5ZScXZExOOYwkBVwBhpFy1oUauVQAyqa625NgZaRQEQJlHovFxMLVt2conQBahwMWJy81KKFbdiLJxRlrKal0b5IYIzKECIAwURWdeCzV10ixDeJ4e5u7q2hU2bR6eaMnEIwaC+uTlv7E70ev95RAXIva9NRuNbmZqTNVsKwGqtZg6RqxPodW9+b5M+C85b0wKAeRNQo433AripG7u7kl0Xr7l6q/yvsYyu/BQHNwSeyAzrsiyLq9YQJTJVWEhSSqmrqhkjEgVA4NVyC4+ojJJtt08xBIKYo1ZdlqXW5j1C45hSTOPgjw/5suSSKxgxYdpxSuzuy7K41VWo1j0fbqKEdV32h6Oa7KbxeLMvtc65CLuZqtVqJSCG0FTIGFzXRYRRJdSqJDwkqDZpIycmpgQLVsuy1GUtrmCBg5iSw1UtBLy4PU77/bquf3j3cDlhzkijhaJrdsj46ec3XrOe7n71u9+x0DSOn968cPda8zJfasljTF9+8fnf/eO3+x1EqVRIwMQhuxUzM1tqjg5zI+rjz9UV5iheoUXLuBOliuAiDHdo84kgYZKBqSL7mks1dSKEEOCkqm6NP8xe1RUAewPHsJHrWv9HmKWZV1evTYm0rV+nGOBdX56IGGLuasXg1nXV1NXavEY7/7YjCwCYRUSIrIf7TWauRcnraQqHmrJJ11prTkKg7XRvC7vn8kRE3KylHNyrmtaTYQGDorgQmBjm2nA7c9emZthPTxLunDJ368fNtSH2/Ihr+QRJ650woAZQV+YkYiZ3uaZifZKDrg37fhTS1m9vfzVslhBbe+344oBoWVc25iBF693D3bIsmyGF2KooEIpBAgK42z3DTOlK4+rtvH5o4sfrx+vH6//zdYVCrrUFAFVHdokYhnRa1v+XvbfplSVJssOOmbl7RGTmve+rqnt6hjPkgBhAAIdaioD+tTbSRmsutBHEhQCCwgyn2T3dmqpX735lZoS7m5kW5pH3vuqaDw64EsurUK/evfkRGekfZseOnWNmTCQpd8svLy9bXd1sWy8LfWChlCQlLqVQWUimXMrlWllcJJl1tT6oNEFSYAhxiE10jcqExYbWuzKrgK0byGEcCh+Jy1ScuLduRCqYsxhczFk7WsehSErJIWC51PXx/GJW1upb5VYJ1Zujbq4d85SmaRKWyCdS4sOhzFNPYlNJh8OBefrNb7///ZD6m1kAACAASURBVN9+eXpsjPXp0XrzaZnKPB0Py4s+kWBtrbUOxmm+L2W+Xq7R+vH5u4d5OeRJ3t2/d+7n9arPvq5923pX/3h4R9aoNTVCh1hWawSoalDfmcWVRvzv4yvxPYpy8683t1eSu9+KeP6mmeWGDNlIVUfZIPJYjiOEdkrXoAr84ewYv33L2PoxekU7A2SnU/0U/ert03+U/N9yhNsT7daeEwlbSFsw7xInI8uhUb4ZL8V/D1R1I3N9dRkRB+y3LX6kXsSTY+2qZkpgIrHOxNmt1hesDyg4zDwTb3fHo5W8Xs7dt8NBpjmT196t6dZ7o3TIkpSUBERc5jTNxTrb1lq164oOe7ngh2eY6ftDhibBVLhwkdPBCNVVoVkrHr90Inz4NKfiqeD+/u77+oN5n+cyz9Oe/Sqg5pZZiNy8c4JTX+uqZqlQmdLl0mszv76YonUsRZza6Q6HU2aydVsfvnwB0fFwup4vz88X7fX+FP6/ZujwtGq7XmrvZ9DDPBWxfEB3YFqoo14207qGF/nxNLHQum5lEZmPROJJDCRZjtP07TcffO3PHy6/2KbLpa3rxatVbXp1MiahTBOLqzW05qrU0c7mptsT0HKZc20Xvejd/O7j+2++//Jdb0YuRAyX4CsMngoTwLg5rZEQUXjvmLt5Y2LJKQm7Gxm7OzN5yHneggtzVc0iow2JAHIzG9Lgt+m3a2C9nf/uwwvI30678ScFygURYs4icDHrvZv2UJsY7tWvQdTt6V+vsrFj/AHxxnV029AtYfqJtelM7KEQHfSrsMEjd9IAYSIVIg6ygxORc7Acdj2K8cHHttP7W7+80broFp2G+z0iWI+uqFDJ2HFw0C2HjKCOQYI9A907625yR6OMDDJy7Z1tp7nFTmWjpSDS1T0ppXFZhpEO3FqRR+jqIb7ERIIU4ERHD2VwkMF4NPkMUcmf2PFoAO03DGvs58TgKKvvPXhBDdlzBAagUYKm20Ui2h3fgFJwIP1I7mr/dm8AFn3d2vkVu2pbt9iyA6kZmJjZnhKPZ/XWsU9gvx0wNjTElIIuoOMQMh8dsMTuZsP5rHsiEhIWLoH8+UB9wgcwEgeDwTRUAprCKFPS0AUIC0p4r91CwgQOdmKOBpvAS29AkptFod7hw4ZKODGr2S4oxwwMcuDtYN3BWnfAoF2BIW63c2duxZpxwSFOxMIixOBxD8lBIA5ZLV63jUkE0M2I6N2799PxYJlrr22t7tq1at3CeQwT8iwcllVml+s5p3L/6f6jfISjtV577ValiJGtfTNo1PbFyYGQ4nEBCdBNe+u6OXO9bJ3Mgu1eDe4wMhfAXF0376oexr+lpJz708rux9NdOZYXPD8+Pp63F+Zk5lu/CnLKBcxJ8kRzXS4sYEmm3rYKwJr1rXs3GHTr7kYuhYuLV6tgYAIXMbfz+WxFO3dPnnLWS4MCxC7eWquXZs1hXqbJ2Vx7tItKJhLvGUyUVLKkZGl9AeGmxzw4jW6GaDaNXlDztHNJgnjJwklS7UNMPQB3vCJZX++UsfBigQRtlNFqI2EWCBgucFd1bXW0gu2IAzGByHUX5ApI+4Zk78x6RxgwMwaLZd/ZbTDM3c2ZQFzX6jywBXd3jVYxInJKqZQU7KDee+veKwAcDm45O3la8uX8Ykrv7u75XXl6uGzXTYTnw5KztLY5NUmJRYgFxMJgYaYkrO6WUprKktOpHgj+CCZaljLL/fvjcRbzCq8MlcyJhUG9bU3IRL58adfr9XqtIvTu/Z1cruu29d5SYVcJ9UIIdVWob3VlIaYk0hxEVNZV194MkCmzzMxQp3XbrivgmBIvZXJDN12m9OHdL3/xy2970//z//oPv/s7CMMI57VD1lymvMh0OFq7MvfPD8+OX98dj6cyH2lOSdwU3X7xzTf/87/7n/63/+U/HIsxGAQBJEi8RPDuiu4QFuEUtpHhHYJujg71l/MLCURYWKIDJbpTu3UKGUxGgDXCQ2mut8agkop1M4V3o2Agu4MMgr2Ze6DxZtZbtwCw9mKIMEe5OpjmNNiIpNaJ9uMvDA0idB8of9gDx3NoR3wx2pfd4AZVGoiPR6tjnHPdHK1TGmIEkQ8EekU+wFQPy4JwGra9c4MDEYVw3KO9/wJwM20RvjCNIADjA6lbGAAzgTgNTUD3vaGDEDKnhChqhQCWu5klGo4lBjONo/gWupCP7sKv9npHyJfuFaD9MD3en8718VpXkTJlYZGwwwaYOR2mIxP32hgoOQCs6D2HWpAX4s0ReZnv0cjP4+fx8/jxeK1h/9Qv6U2iAwixkt4sU5zczBLg5g+PD+t2BVE3I2Iz32q7XNdt08PhmEsBkZuXPElOT0/X9aJDoMBgcFaQsKQEwxBp5XCZ1+vlUq9bTmndVk6+bt2Pbk3NtZMBquo5g8DHZYKTKm3JCQ0Q5kKUu2Jd29ZNEnV3NQqqeZAGUkrLYWHhMsliOB1xfzefTsvh0N+/4/u70+lwcqO//uvf/PZvv7tcTPX65ak+nZ+hqK2uLy9ttZxI3alAkrycL8/PLx0djuWUHx+un76pTJOxbX3dtkrAcZlKyq0aM5uamuec81Rsc9vULGoDljgnFgAawjA0Sgi0b20+KhlvKwx7fOU7QPg2f4mvPLLE/de3hCVyK3d/w6j9e8dXjTC3H74hyI+3eoNhvZ1zX72Qf9Xn95NoV2Tjt3rpzj8en8F3+sKtkn6rQcbV/Og643l/mLbfUrFXPocjcbGuvVcxIrATu/NgyIPWMx4+Y7vwMt/R0krJTej8+LI+r6dj/pM//qjWe6/mIBaHq3cXOFmc863r+fnSNrhbmUm88LUFpLutVovW1VoxTrJMC/kijj6Jo7QtvVyubXODzod8Oh1a08TVXaZpfnp8cti6XVurKXMpmQVddcqnkiezBqKypPsPR/fr+VyFqZojYT6kb375casXkUIEVd22fjwcibCB+oZz7yW1w2nhSVQwYgmhhMKSzHrOkhIR4ITretk2F6ArAPv46Z3wtK2XnDM7SDKnDJFcyvvD4Te//m1yulyvbuyNcMD9h/v1oRK7FvJNbTVmKSn12vtmveP6vEnztoEpi2Yo0AgdwqmUCb25BjOCmAVJLIGIqYebvTFDiNumxh4dccwQLx5gjTCcoD3qa5LESE1DikRV3arTIWGonXroFI0+X8fritotC25I1tAsGUHRaPxzdxYh4cBkzIwZTsJETJKCTaXhit7BGJHvbbmFcvjAwHYAOehOb+f5iCTHdhBS1wCNyiVuDCw4hEjAfYS/gS65Yq8RGnkggZSGmLcz3fhLAU/dIJIdbR8UydtnRuiE7DHbIBnZ3mdwM94WcR+F6oiUGZDw+HI3B98kxSLzGzExOUjVYKPpEE5RJWYfzaEwxOYxdMkMg8xzA2sCR7t5lTsAYkmSExPgpFALc0KD27BNpMF5eA0+HcNpEQOHH9FvkAJlaDQPqsjAQhzhiERuofYULxY3eUcn9z/GvEO6bXZ0Iy8RomUvtkXVVxJW8FBuX1TrPQhDYUUer/AjRCwggF0z+O2GOiwrbypD8d0Hjc2aETksSt6mZqTEQhCAvZSiw54wCAGGISkF19A29t6UKSVmSdmadTOPNpCAIUiHLrAbg1MS5iEbhEDG4AZyJzWDGQQibKqhwxm+dWwMdnAGkZF17YF1DPVJgxMZqBvI9XiavRptw1gFABMLCakRQxJJNCV7cPxiXYsaecfd6eO6rg8vD74BjOlwoJJSSutahabLy1l41nNHVyRk4+TCSmBj8sfL4zzNcnh/eHdUt+vL2lt3wBNqbWurYZ8yGmEV2m/ZHjGhb1tPjpzEzFzX81XNYRrEMHfLJTtnYxBYm8K6d+qd29oLpLFyMjTJNmlX1YbmW2n5UMy7da/Qxg3JIa7Wru7ijAO2hyuAPBWxZBu8s5iASRLYzagikSNaTcnUu6p3RzesAU1Tc3X1zVbtyiyuTgYx7qowMDMYnAyhOpWcQJrBDlcKrWoh2mX9jRhJkqv3FtAwE4iU0OHO6CwuZg4jIWIK3zBX87Ae031RMEAUYSyia8ncsTkyMSUQmbfeG9RgjuzO7u7EnHKCu5qREflN+icYnRHfjHnpbqr6ipUywOQM54D69xjPUXsdVnAjRocgE3NU3thFWBLnZnWtKzYgwTrX1dGMqK9rP83HZc7TtHz5/MXrqimxJCPKh9S7d/Pn6+V+WpzntTbhfDycnh8fT8cDU56XpZTpKn0+cmcqZfr222+Op8XrulXW6q5IQkvJQizksM6Jvnz+rKoGMLNkpEJi1FoHqBTpvQul47z0tfVWn59fttqOh+M0yeXaus+1+vNl5cxFsFk9lMkM64rtCmGQlSlPcH18er4/3t+fTofjcr1u/+k//peqKEBK1Hr7/PRQSjku89JyInemvBwfns+///zwq29fDu8OlFF9XdvT6bj823/zF/g99KO5EhTdaROo+TJNLHQ5X3Mp1s1BSbK5p9jqAVO17uiipt7YONwehw9ESZmZu4bwPrzDOoXzbXIhgI27djICWMAMjl2Yzc0AxpSXnCYiUbNata9KhiREQFfXVsd5wEwMuam3sBAUiC4PJnMmck8eYhmERGTC5K6qgHNig5MAMqrKKSV4yNI7EkHJmxt1IiROg60wHHHiYOLgZ3lIzwQUBocAQkZu7iw0y9J1Y84EclbvilGI0OHYNPhgfWcYRoUgkDFR0xD9iLjE3JiIhENEDOwOMrK9sGU+AhVjJtM+WFURsbETM5G4h0eSWfQjMzu5RcOjUBJprFWtmndX6dt8mKbjrJQMeXM/5tNhOV4uL71d4TUnQBGFve7O3SVLWB07wtbDcEPobmHJyLJGcrXHVz+Pn8f//8cfTHV/o5NCb5bJCJX3onWEzkySgk4LANaA2vRSsTro4fmlGZPMXJbH8/p8vp7X3jafDjRxrtXqpkKTVa5X1OsQ0ROWIWRobEpFkukGs7nM01QM3Zr1bttl3VqlBDVct0qrzZOdL1vO0AYo2cyH6WBuXeXlrCIpzyeZJinpumk1IxJTM20KkTm1ru7ICWXiw7Go1HzHU8Hd/XK8S1PBktOU093puCyHa70+vjxe2mU63if+dH55vv/Adb2QbHUzYkAoFYmiRKvdzERonnNf9dMv7uu6ZeFrPz+eH67Xa8nTcjjMmcWUDOjat06ElEOAdicVEEbvA3Y9DXcP4Qtzd1innUcUpKP4v2G/uiMxt38j7dwJIW+QSx/ppdGouGOv0/tPboxv05kfIVZvUnR6feGd+0AEG21WGKI98F0ox19TIYLd1J7H5BzOKPEihLe0EQ/aBY13GWry48PTm+v00AzCoEBgvMsA+eKK37ih7C8Obxf06D3JRBSqSpTcewWrdXz/gG09UXqf50qTE+TlUp3yxgwnNWvVW83uYujdmitNJbmhd23uRY4dOklacto8zUt/rz1nJqrX69X0NE1T62vdKjyb9q3W43H69Mu7/ILL5Qyuavr+/XtV0nreNifP15ezs2kf+CWLT3mahAkkkgGijNPHo8xJFj6c07qupfvdcnr36Z4WztPsnbau8DTlu+u5mXlrcjmTweejbqpHiKrWrZKjJKJEKafLecsiLIWJem/rttYNwsiCaU7TnFOaD02vn7fzeXNqx9NpyVOiZEr/93/8m19+OG5X/u7LFYqTJCedj4sLHr88qDVj6ma5WTfv5kh4rs+Cwpn6ZbPZAZDi8/efr1TBSEWu1y1ngXfyxEkkhQ26EUxAzEgi13UjYQallHIW61rbpqoB8poaE3KRYDCEirSr2c7isZG1j9nub6plNPLXYWxGu6UeQ5jJet0B551ebzbaluAgYSWG5SREkphMSJtadzeVQoOhs8NTDJeBMTnBtQ+V+n3zvq1YYxk4iflgw7uTwcgiVLvpC5uhYiwmA9zcJAmI9gYsB5GLezYLtZMdXbnBYGPl7yqneAuMR4V3qIHvd8xBENx2KB6Ps53X/4ZGgRvFdL9/40ZEjVndoNDoyA6BGgx/VI9OG7hbLGYmEIGHOV/4tMeLlWRqu5q+A2BnYpHhjNfNFdBdrEtv7Dhiat0IbHG5URv4elMaH3P0RewfxgAHJ445Mw7jaJ980y0ef/CNqhVULgPgo4VwVN0l4Bm6uQrGHBskQR7co7cbfcyZUcreawLur3g/YQCRb51WbsDlzZMARMyc097SqK5m7hbptt26txwW90DJyNwNpBjl54H/uUcjIdgJDnZWt5G2CABztjDWCihKEksKHu5QrycHZdmVEODmSsrKBmcmaJwhBBiDkiRm6b233uFwJuxdNeCQ0IKbQRziJHFVztG1FsQIdQuOGtyzmxuI3MncSamZLUemlNM0N68wO2/Xa60sZZmPp+Xw9Df/r1mGKhKJkZCIQxR5SjLlZ8ZaVz8/92SK/nD+AY7lcGS2BlX2ROLmaoNKRg4GiwuIkoi1TkHwJhcHAGG2nTHtoMJJUoKwuW3mrQPdQHY33/drfflyeegv6CCzJCmnXHXjxPMktfVr387r1bpCYQXdKouD6NOff3z42x/0C4IWpE7ipNF9qq4wZEAYTGAppZiomjbrvRuQCNmdu4HIuwCiRlD30VPt4nAGd3QL/2aCkSscOVQEArUiKIPg7OYW0VXQ3MnhaqHUI0hkrNWY4U5s0U0+Wv+6teCbusLhu9XOvhlFRVGAPph/EIKKd0W3EC0aJTvsTEMfq4Cc3YzcyZiHTcfYj905lO/GZh5LXuD5thsQD6YJuTvMhyvS2ObcjMgpCC7jY9sQ+VSlbXNDc2hXXPVs2qaytr4iwdHr1rsjezbT67kWw3KirRZtW2Z36+dHPS0sIomJvJtdk7TTIU3HKWd33Yg8EXVVuAvYVc17ba6ttiolFZoYQmqGumUVRXJqOWdmqluFcpFFYT3IhtqnacpAb64mveu6QWDWautKyVNCFlwNJTMcmSRl3gqXxO/v7wB/fHh5emynGV2jAZdUvfaWVba2IYGIZBZ3PF9ffv/d9++m+0/3H6np2p4PKf/Zv/gjAELcSUjMyJq5w/IotDowImkzcjdodJ5DHN3BBjWom8KcIUzMnAo8CTz8gHeNQw1yDhMxOcKKEwCRC0t0yYUdjDsESVIWEeuk3bsizIGjKwEd7o04BdpKe8Ac5RkHOXYPctuDaycysIPhidNrQSZa9gQQgtlAft1J0dXMjZObGAlLIuSkWx2H4hCbHNpS2GMmGgGSO5GR2QjDmZm9xZYPs2AoRyP9EA5zd98jHqLwQKZxYBJI46+vFfwRaTmM3HkkJ8Cro8J+Qo816aPOFKdeONbcIjwKaa4IApnBhJTApZwvlwuahLlkljRlozDRFKEJ7r1WtVYy3d/PUJgQJ5bEUbsD28jEIwCyt2Uw7AUrx9c//Xn8PP47HCPX+IqKwvviQWQvAQC7kzsTwWyPMMmErVFXqwbfau0mRqUbX9Z23dpWvXaYuZrVTXtTU27VvbGZUiQ7Giqxot1b23LOrm7mwpwym0lvWqu2Hq5WfmPapIlBmCY0R5H5OJ0Oy9x6pybMklLJ0xEsanattbUeOzILWMDFIUiEUpCyy4Rzf6bZT8vh/sOyFIFt1l3o/TLP8zL/1V/9zePzA4TyPBdeTve0LMfL+YfWHom2TQMXYlPvGFVt7QbqutnhMMN8va6bqWvWujZDEmdya3Za7rZUN2qqXcmYMidKKVtQrZhgwTAwgpORu5E5RTLFwQDYAaw92RuDIusMBGw/e/bwJxE5QsZweBv6G2TK/R+C9X/y53uO8wbAej0QfJfmGajWVwQr2rfkG9iEH/kDYj8wXvkEtzfaux1vj/d9ivz0oJEBR1ZGO2A7PgPeNNN4HP5O3C8wNsjIWEAgYzbT7nDtuCq2NT9fKM/9ebs0z8+XmuRk6q2adahltwKXjtq9q/qUSwILTSJz4qknE6quypiPs5QpLXOpL7/Turba4WxGl/N5q/7wUM8Xf9dtXo7TIs3x7v5jLgDo+fHy/XcPbfPj8q5tRgInJhJzU+1GabBOrHXZZRNSX+5kWg7TSmR+Oi73Hw7/z9/+DVHxSolKSQfvcn25mFmkyZyRppKmYtbqtq7nzRTaYQaWy93pHVEYXplr9wrryAWl5HmataFtl+tl3bZtq7VrdUfvlvKE2YTB6QDvUKCglGJtI8ruRkeAi1hKxmQdvaGAS7ly87YKiLK5NRhg1rUrmUJHbUwMArLopxmsRTIDRRSnUpKkPBAkhoaWg3a3IfjLJMIyqOfkt74MpGjhGqniq9za4BhFz0f0/Y3eNvdQUCUG2ihIEoLfA9M9nHSA2IyYSA2RSMGZSSwap4aAemj1+g3A2LFdjJk9Xh43pWoC+RsHHTKABhhBzu5Ew3c+KGWuA/mmHSpL8bkoMnZiV3YXe225ui2nt/FWvDfTbvvmr1jWYJW+Lloyh8sN9NqlXBwIp0KQk5ETyF7lKd4A9bGjBGHTVc0lEVvM/cjl4obv6ztUXAFxwMjNolUPPFogAxUHeYgjjbICA1Czbmi7NMbYfoYCTYBd8bPRhvDmlryF8uiVrrVbGcIGVPNqCIsfbbw+9nYHwXiAXEbkSNhjdh7kIro1smLHrtxfi1XxyPHDOPAtyGvg8K8lur09EYGQOb8tDtggTu3x/34vhCjR3kOnBjPXQLCGixQHvkkYuluu5mrkxINjyEy298/TLtWmqqbq0ebKkYWYAxTqWymFApepNuvYde9IiOT19rmioUlOQ5RuZDpWKHNKKQnYpKErkpATdQkUOtqn3EBNm5FTQpJMRMIZgHlzd+vavbMRGZATEpIkYTG31pozHh9fjGC9Qw0KzjKVaZmOH+4/HKb5NylZs5InwKw27WYbpkOeyjynJf/q9LKtzLRMcypyOBwu66VeK4EEnCmTkptRo+jvCUJmfLfMImENZu5kTMjE7OJmCNiEqHAquRCzOlFDHMfiYNC0zNO0WO113daXtfVNkJxBRIVynnn2qTE2beptKmmep0SMavNpbi/bUz3b1omYZ0CYO1vvHRugSJQmKYcpHVhKgiBrhpkZo2RvAMzdACSBpmjWdWbKORPI3VygalAl4pSTGGvTXIQ6Dwa7jvRTmBMld9fmBCQePCxSY+JEyc23a12W5Np1GJC5C6m6dYdoYLpBcvO33HAelqxubqrogJm7odvNy3XwCt3AzswON9WB/44X4rfSc+Z7QAZ39z4s2/ZaZTjAyS67pxZ62UQwcnIYdRgBRAJnMurmZq4BQ8Ohauabqv/pv/omZVmv7Xw5997//M//lao+fv/4+PBkhu3cDu/ylHKZkEtq61bXy+YN3ntF22peMtS2uq7niziOp7syz5fnlxX28cPHw+kEbd5rZiZX68owN+7m0zyXZZKcW+8mMPfpUAj3KWVV7XWL/v219qdr9QYs1nvX1pt6W2u96HaBdJgBrYv5svD7+6muW8nS2+qqeU4f358myb/65a+s029+/dvt0tChBjcXgIhUvdV+uVx04jmRqeU8/fDl819X+8Xx/f/wL/91yanVxpn+5I//FICSObPMAmN3VXc2JXVimA5t/l67Qx0WunlM7GTW933XAYLCnY3QyeEiMCIX8WAT8delhV3kGzAYEUFAu/03MxcWGLatbmu12gAENRAGU5SSoxQ+1EPc3b1b3yPrAK4oikUM3GhGAETYKaRBnRkgKN9O268PYYNqMLSIWUhwA5sGdej2eHo93qNushuJmxmFtcIQjxusYfxUTZ1uelrYzyk3I2Yze6MiFSc/3WC6vy+9eb02vKYwcFdr3h0BWoXKocAZGu4QAkxJ5qks6cvTAyZgBiVhEYBaq7WrUDJYa63WK3p//+7dX/zFX/zvl//k93GsiHX7R6RWfh4/j5/HP3PQLTCPNZYSU2Jmams9n1/WdVW1Orw1rHWtFb1DO+qm69rc2cx7b2o9CalD3a0HMxq9d71u21y0NXNvrUmFw3vT67UN7ANAhmRZlul4YiiXnK60ztPh4zffnO7lcn6pak6ACMFNe+11a5tqS2lmzjU7R6Ozgzi6wrXW6/Pl8dO3xw8f7r59f+R+XR8+X3QV/maaloMc/v2//z9++AzgrpRExnen0zSVL5/tctFlmfQovVlrvTWjZq01AJRY1bDgdLoz618efrhsa1OtV6+09dVKyQw+frzb5nYt27b2qsZSiXOas6u62vCyjfB8JMpwG0V75tAzJpC9aqhgPyGiP9wxyEk+tDwJgCOlBIDDnxC3COkNbjUS3v+K3XQnXv3k7378g9c06p88Sin/dU/4x8aPmAc3JsHbv/7hk256O4FoXK8A8PBw/v7z0/3Bns/b1fqm1rU31afz1pqBk0hpPbRdXYF1rUtiKRMc17X+5jcPv/719t0DyvLDdLzL012b9F988yePD2R9cptPh8P2ni4vG7zPi7/78O0vf/nLtdXH5x/Mr9t2fnx8/v3v/+53v1ut4bBsTGmacyrMVNxq68To0Kqm6pZSAnPryiLzNJ1Oyz0md0/Maabf/peWckuEQ5mmjH5pa926NiYy8mWmaU4piaK1aBYSYeLkIix//Ks/M3WYddXr9Sr6tK7nLHy33E+HhZAv6/Xl+aKtCbBVPG2Xp+fLcTnSnX36+A0jQdp0BBO798NhsYrLWt998/7z7x76+dLBmdEJ5ZhP799tTc+Pz0bOhWvtAI6nw8dPH57qi6jVdvYkUJ8kkbJXs26sbKrQbmRQKOF4us+l9N6v58v5sqIrzAgIpekhS83hWs6qdRS/iAg0ZM7ttdltJN1DzSARAYPaFJVBuoE1N7M43Or32FcK76ADk4ay0ADFAAKLGDSYKBGywRPcoVFXAEwkpFFGyrYrV8SlvyFQxpNjr/CoZohHUZHoppYeLBx2MhKAhKIpOOA3CWRuX0r21edAgD/xZkN7Yy+PhApV3y9rfx6ZwenVDihUn3YOcKxRwxtK0w2ffzNCwd6RyAAAIABJREFUDSkCWxYOOUXtwYLz180tWETu7FBrsOgtgDOJMBN1a0NnkPfLQ3TXQU17bx6W8fJqzhqpKPGI/IE3WNU/MHaUy3e0wUZKGzt+2ksQ+wZlAGKegqHu5EaR0qaUeMyD3VnD3W+24rcjfP/yQ1qaw6jR++vUIB+y5WFR+cqzxehQxb6Px+2/OVnut4rMrfceDwuYaNz8nUhi8FFGCPxrN5LivQYtTOzk5uTMJADc3HrIBSO+CTOzKLIBw8MTUDPV0bc3KHs2vsW9OgG38NXatdkAZjjMXAGBEAmzeJqzA7BuBpLg37G4b3WNzC+6fMfnNVN6TRqFge5kwpzBRmrk7l2Xd4sDvbZaN+WeUjosS6H0+Pn7JxDOHcK1boGbtw4SZChmlyWxkm12ret23fKclcy0E7E3h7IovBuU0AjGMHew7l8SCYlyABoggoCN0FW7MnPI3xBr66uIOAl1Y4MwJefrtr5///6wHKDYLpcf7GE7P0M9Z2EQ3IsUcyvME5feO7vy5mpNVZ8+P2vvZWYn6NYAF2Fy8TqiFpo5n/JyP9ME9d57N7Vo/Qy4R93JKbFIEgKRgQxM4x8YjEE6iEdMQmAzFRE4u8Io5M2B0YnMMDPrDGJOFpGoOkkmIXe3plaKq7i5MRDWp26EfXKO3YX2+GrIanlgxWaDgkdkbuGsOXYsNt8FxzgRO2nw6j0KGzTIom/XyVuUYLhf4FUhMESoHUgMVRg5B2Y1CgZjMYfCWzTQusXTYwHFLvL0ZX336Y4sXdfWdPvw7bel5GkuSCgF9YLDobz7dJymlBOtl0tbN4bOU/7Fp5SIBQy1um51vea8lMQCZCZhWXKaitg81c0EIQCaEoOJSKjVLWVmlhCpI8Gc52me4G7d6+kEot5a780VZsP6CIDWDjOtDRsANIFt3VXnWd6/P9VV3aANvVVh5JJLTsf58OW7y9/97vemXuMoFxA4JUGCw8/r1S1TgaouhddrX+z89PzcezukyRvUNEGwoNVa1YgTM7mBPZkbujOLj/oIunaH0q6dH99kb3uLvI+j1d21Gkw9O0ME5CRfyYOM1m+FwaOVwPd6jKuNmg0HHFnXzdaKPog8g3Dg+5FA9LoN3koWsWywixl4+JsOzElhEk65USyIClLgtuNBgRqp09AuNDM289t2jNdtn16Pn31G+4hCbpSiuISA5lS7q5sPJfgRCnw9KFiSwlEq2feNEGLg8awdLvvxk39y7OWr/WIijGtwJofL3kFJ6uQQUCLJLHNKy4Q11j0RSE2vtaGuvYXEhO/uvfr+3Tf/47/9S7T/NYjwDlfVlNNXrjv/LfOdn8fP47/rsWcSo5kg5STCHVS1X67XrVeDq2nv3TSOWYjA3betbltlTkyuugHR0ADvPUzgOXD/DlWNau5Wq1MnwNXDyuPmPM/MpeRpzt5NovJEVKZS5vRyeWnauqqabbW22hQdrLmUkic4X85V2JkAgiSwQHV7fq7qWynvj4dDTtxqt95JWi4TIzHkv/wNEiOniSBd1c0IU0RDy7KgJO3em7au63V7eNy8Y1ryvCzH4wFOl/P68ny5XmvrcAUArc1mKkmsg1lyLq2rdjdzHl5LUSzwID4QDbKr2y2hxK7pGXo0tMvA+DgWd83YwfHdM8Do80m79PneQPpaYt9PrX38ASb196FUOz2K/oEzwv/QkfCfvEUz03Co35++Z07/zPH2SuJY/Oqv+8n69XE5CMSmFnceDRA8Pby8nO8+5XvOJ6stzfeJl8T+fK0MZi6SiphBEQyX3rRaR+dWcX7sLy/bekVdkYsQspv0Jr/7zcPT0/PnHx7W2t5/Opn51hNLmWeBpdrRNhMqra6XSz1OGkLS2wZvjaCuNCMjEbHAkgNO2qxqIG8szap2J9bjaSq59NbX7Xp9XHFFYprnwuB6ubZN3ZUY6u6MaeE8JU5Ekst0BHKiQpQS5ZLnz989W7feu3fV3mtVeGEW7yn7UsqsWdapCSbCdnm5QpGZExNUD+Xw/PCUhL/5+Onh4fGHz18+fPgIULP1cDjlbC18lnOibPPdfPx4omu9tEsWqc9nCD58OP7iV998+vSpP7Tsd9fNE9rLl6vWTpWwmndoJ+/q2gGz4OkvRswpCQCYJhFKSXuHGYskkZjZ5j5c1yIVj/X02pgGBFlnjAgHnYbyQ1D7XueVgyQncoR8zph6IQXFFCLRkCihB+4cLa4Ak8PdiZ323rHg3xDxwJ1t1FEjyzG6xYg/IjZGxAh7Q+hyZSMiJ2PGYBrtRCQP5Yphwz3AqODS3LAlvAFZXoGbCFBl17Pfl9gbSOS2yG7/Szvl30AuIgHF7yvXHd59WDTEGt2bkfG6Q8TtSgjROoIr+Q1iC47PwPVsECCAodA9NMdbeIvTeFcCzJUU5mpNbx+ZycUhNOjLjpBZ/NHNxqgC3YC4GwOK3jBYBxeKblvjrZ3/LXp1u+d+K0KMJ6RA+nfMyN7WCm43nIfV+Aj9RcSd3bvS1/Dm/lWNhDnuhbuqvgWwQoGavgawokykfT/A9puOt4Dl3ipuOg690eZtFFM2/CzVzNyExAfMZkAIGu3TyMfl2bB5H75dADgJEZurmrJRfFgmC30XYuKRusEBYYejWYPC4EgkzJQYYakZLn7CxOywvikLC6cAN8LjQ91ImEnMFebmDPVkwpRARsNyzL27pCRF6Mi1Bmmrc06JkFiQUZhVnaLXssMNWk1X66te1lpr3WrdtvWgyzRP8Nysa1N3oLs1cyN0ZuMQ06eRhKGhqxvETN3cPaGnTt17NWLlzAC5QtVYOE/ZzagrmIxommaDvTw/6dpVVTJPx+V0OKYi27aiu1mvvZGLBVs+gfKAP18e19MpT2Wul6bUjGC6matyBzuE05zm+ykfkgas17buHQwRVlWYuqnLqLExD4gfDjXVvTNwyJeDYTA17YpXise+IRFHo5/vZQfr5upQoGNfLQQn624Ks9C/ipZaSpRCeDvydmZWduylxFCFZg6xRDUbzUnAru0Q/qFqasSwYYKpI7UnImIeBt0790OjUWksQ78lx2MRGb0uKDcoiDFUR0P1jTD83QxkIEFwYpjIOYw5oouNnl/W4929pPkw3WlXUycyTvb+03y6mx8fHvLkh4NMKbVa18ulVS2CpUwf373rvU/TlEoWTuQkSQ5zWZZDfn8vwlmSa5tESJKASpIikoTdVa1v8TG1tlZ7b67dJWnvvTVmmZeJibX1nKSUtGlnpiQpEbP3meVFDYpMYIdura/r4YQP75ZM8v33D7ZB+0bOMHt/9w3Mrs/r+UXJJRMhJ9/JiQTW3pyskbJbV/OQRyf+8uXhd3/7u+mXf3Yo9xB0dPxrkJHWLswKYqIkbGpdNeXUtnG2RT8gJIovIZEZRQMQjxgBQdnTYeeak9BoD4SaWziuxsGjFhPUiMJ104IDzkjMQmJqfetaG5pil38NaIhTGAsIEdG+V7sPlvgNUroxvGI+RZhBo1rkQ7Jy1+KIh0R9PU5QEoApGLFmFskH9kN2fPY3HRIDhoslMpp0h1dK5IHCSXtXgw/Xpp8eg2XMHH6UARO/+XX4GH7FutpJ0D8BhwGA0OuGsRc8zJyGhY2NaIAdDBTQxDQJClMmhNJqOHHUdqXNt61rYNi8zPMk2bu+/3D6y7/8SwA5Az1kwegnTNN/xrB+Hj+P/wZjUJ+xezLlnKJWauZbreqNhcx1Xbdt21rtAJKgVVsv522zUk6A966tmRBRSiml2hsREYvANYGIUsrdFGRmJswsOSU0NZAyi4sSwYm6am81GV236n7Z2tptWVtdW1VXd1/btrYrxA6nqeS5pBJuvylzKd5mHJZ0OGZmu6yX07t5mTNIr9e1Xc5EuszH++OdIG+mcEw5l3xgWlaTS1/Xi9dtY5LMKfjaImlCSUnW9XrVPs/T3f3pdDw+PDw8fnk8XyqDpKF3h6E3eK1V8Hh6VrUyzU68btvWmnbdu9PNb2U5QpwgFh2eHFsyE0U4xsIjsw0DDY9Gn1HzoLeGXkEbHwznkZz5UFz4J/ObflQjuDX3cRiGvL7Yj18wkrDIlvETv/+Hhr1Jv3dY6a3i0D9nvG2OuRVp3maX42G3ax2HXjinWxiUA/jyw/P55Rfz9Ed5et/XR4hTOuRCl/p5lpSogDJxSy4k1F1erqvJSprRqXabltOHj5CMNC0ki1pJPn33u8/bFSDv68vLi05z3qqbsrvUbfv8/VUS3n04LvNd620qx6WcpqRXa1sDNiM0c0dSTi45l0nKTM6Atukwy5SVsW4binNhzuSmW7tczhUTDst0PBxccakX8y6JzOCKacbd/XI4zHkqamSeIui0prCWpK/PzapZV/jQGSVQv/Z6PnvN796XwvOH0zeXvMKeHvxqisSSiPq6zYf7Z7Xj8W46zbW27757mpYLG1OCFH/37T1/JBiY0b2X42m6Kxt1uhDgKMgzPv3qw7tP98T29PQkE5U0U0mP9dorsDWuSiro0N6ggEeVGlgvUpKARLhM03FZCPT89Kg9aCEe6qWRkLgNxIl8l2B/gxdjxzoG1j6KliMYDPGhAIoUntKwPXV3CrUDjBw+YAXb4yYe7PhdHA5BBAgFFdpNmIklzLDNo/M4mvyId8rg64KkUYglxyASgt3JwRo1U4OxOLPvRVsCyJnDuREh/RBAihNgfCP0DLVaAM5DZONVQMjgvJNwaC+78ldt7CMdo9dq8S40D4QBovsIZZ120OkGj9wW6oCLQETObnAWZnYP0VcG9PakIZED8lAc5DBb9MANbZeLBdyV4k3N4UbDkpwEnAiJw/Fy/+b3rWPf53jfJ1+TWd9FWDEAslundWzZe7Pl2C1HjmGvHNDxfd7AMncAiZn9pv30pnkV+967ux8GP5dEJKXRSaeDd3d7tVt9/AY53eCyN3c8HnnboL/ekinm8yALwm9b6+2/BK06XFVIDOrq0Tko8aWpwkCJXEfXbmBwAJnplJJZ9O8jULuwwYo3DrKxNw2eFouIiBMSORM1M4KHMVwsazI309qrAyxwIvNuoSO0E7wooOksIimREMRU1UzNmFkkGVmg3a5AN1MjZQugg1iYn79/4DmXXEAcL9JqvaqVlPOcUODmgdc4gAI4zFC3Tpf14fnJCgDnRAxepsUd7elJ1+4GVrJmMEpIUNYeLo5RuvLq6tJTFribwhSixo7eQgrIwGDTrpAETgmAmakaWj1+WGqtl8eX/nBFQpqXzDzNJZdU13U9r8K0rtv56WoVENCEaaY8ZUl0mCklAZxnHKeFiW3D5bIWyqmIk4NBBc1bs9q0mXVE4q6RpoeysSl36wqDsASAVWslUC6Z3QmUOAPoTdFhat4NOubwmE4gM4epuwsx3HtX6CB3uLmSESixmMGG4w9H5zKIWIJISsMwLPz+WMj35uqxVcSBsHs/4JYpUwgOugfBxIbnqoMCNwe79X0zDVx4bGR7xcB3sCysfBjYm+PZmdgjRCcCGRQQCqGesCAhkhDwJhK3bg4zEIPJCbxtOs+plNmz1q1NxJLpbplPdzOnSbERNya2tonbIUsSpPBimdMyz8fTiUUu63q5XljkNOeP7z/M09y27XI9ix2qsIAO8zyVAth6vV7Xy1Ryh7bWTE2EWDILequ9d0kmwlPOlpIjm+N6ft623nub85wES5kSXTPrYWJO5rW3y8UmPh3mj+/erZfnjKm3zuRbffmjX3zTt349r6RA55xSmmdzv9a1VSUzMz1MJWUhUkZfV/ujj3enu9PTy/mv/vN/viun5ZsTJVL0f/dv/vjXvz1f6mMYArh7TomdrLckqaEzM9z1dnoOSq11A6WI2zlkF8ODhADvYR4ayDxpwEDDZYLN1JvtrF73Yd3rTmCinEuSbGrWOsapyMIU8gbEKEm2dVBN3cPUcj99YvLYmDd+g20IDDATB/nVQfGkEEcItCV0siI7pP0UCEate6QEvgNYMHeOn7+eDuNXO4gIuBFxdM6a5ZLN3bXv8NrXaNNIcQb4G+SmAf+a01iPO/GRdzvRcRIHeMj2UxTpyGQicBnSKuMMvwHJA8pDBhfmSZDJxC0kxAzavCdXdQs5fjOFOnB/PL0cZriJ8J/96Z+MCwPA4JxiymA/KW8n7M/j5/Hz+EfHP4gF+I5hDd1gTgF7sJNFJ7UkAWGrrbXW1YQxlVOr9vj0ApunwkRozXqFiZZoC9+zPBGROSOsRgXuYEYuOXle1167wl0kcYqnWGu21vNUUlPj3qrWl4td1mvvSsKJSBlVleAslAsjHNNhxMRiJeN4TKfjzEkv5/ru/YfDcYLV58uDr+f7Se5Op9N0B02ff3iaE4QmoWmejuzpwc7XbbPec06ubq7burkhl3n6/9h7sx1JsiRL7IjIvapqi28RGVmZWftUdU83e4gmQPCrCBD8DfIX+BMECBB8J0CAbzPF6R72TBVrz6zIiPDwxcx0uVdE+CBXzT1yKdb0PA2YiirPCA8zUzXVu4gcOXJOl6+vLoZ+3u22ibmWcvvudjwUMqIsZI4aDuBQhTrefnm33W92+12/2fDpMD3eQ909/HnDEQtCDm7ULQp5G+IIpBqAxRR6NBFiwd21VfSDthCBj4uREVn41Qa/OJJDbnVxXc9xPr6JbPV197620BKBOSoV8G+BltaUHWe47MOSzJ85tOqa6H2Q5f6zj68wsL5KyFr/BIYBT5t95PsGU6dMMHfF7Zv7+7uJfK/W3T2cHkbkLNtNvxuEQE4JyiEbK4mtcFlQYeI1UZ+67f4imWuxsiwYHxcHdRe7h/s6L9CKQiMNjMN0f3+qmszr4S2wx8UGP/7xD65e9tNc+Ka72N/MV6LLw3TS2RYtmE6qWKhDv+0BYSHmSq6p7/vtZqmqsJQ7ThlMBhTVadLrnSSIBx1cOHUCeF0gHS4u5frF1Wa7AdE01ePj8ng/LZMuJ9MFBCwzUAFFz+hySlkIrrUS43SvD+/GfjPs9vtt3vmAh/74UCabdcE81uUH+0+3w5aIXO3q+urxdJqWU+au3+bTdNhcbLb9toyLuiZm6nihpabS7ZMAfb9lrsO+Z6HD4eGPX3y+2w9XFxdJEimRAorkjbzkTm5P8GQtZSmLiBiMhCQH54rdtFp1MgKqagDCRMQsDF9ln6IATtQUhwQgV0PjPQGIYvpaamyFdYVDRXBO4mOKcvTEoAny+OrS06qBDvJoIgBBYVFYxFpNbN1wzDBwYriTMxmay5xF+ZZWiVM0CqGE3p4DcHYWePQYUBTtA5wTInJiQ40A189z0CFRQz6DMo1D1F6xQkmB3a2tXmvg2pAptLboYKJFnLvWjx1Aa39pcMpKLsM3RXex7lgLaplJ3ViciUkoCVWBF3g1t1U7PbYzIeFYjNzQ+EPh54bQiPWoDZi3e84CeIJk4sxgmABMTivy1fwNnXAOkdvdRNNjZo/A37Hq1beXiZAZh5rtWp1e2RfxC8O5dPBUeHDC6kIYyQMBQXtzVTszUVr1gldoiVmSkJKqfsPi/yEh9wm7Wq+K4qYbUuJ2imccW17touKeRSM76MPPBGxRShzdnjCy6uqWJbOLwc2c1s4KbxYHYCYYoEhd0mrqHipyiO8syeDgNasJrg2DiSSFT5Uz83h8TJKYKR4+XMFgUNWmHUXwUkuTGyaYOnGYqFDf98KSOMEQTjIAUupSzkZmi6kWFAPDinkFOBgxxEI3rz6e5mmaZ62aRHjILFJcp+NcXCHgTkqAegkBty+EydTKUr0OaTC1ZVyOerTFui6LJ51nmLuSVxdIZFSktRQ0CzyDdCDqE7OLq86u7okNZKgwEMM1DMnAKVFK7mbFdTYAp8fDsN91Q1d3hQC1Uscqhm6b39/fC2HT97qomDDItPIcSashYzMM0zxPi3UDf/zxi/3V1Xwqb9/cptSlJMu8zMtYfLHiVau7syRhimkSObsZHFbVvBgUlIEuObzWysQd9UA8UvfgoFWngN7UTZtmdUwJrR4bQGI2g1Ull1ZwUFN4YpIkamwWDqZwuAu15cmwQvuwFatua3RzO2A85bhPq1KrKhJBta2yMagj8BJiUGIpXmKWPiHI6ymcjNdSoZ3JpGfnVAN3ZylURzQV2znndmWwEEUHBKwUeEMG3AkudHg8hbunJBwOj6DOUeZpWvREKLP6VdE8sOUu7XeJRMsM1bIsXZ+F5fLi4vLqcpymL7744nB8nI/IN9cXm75m2XSyDP10OAHYDZuuy1qLFx39ZFqLLkWrs/R9L31mllqtlELAvCzM3PdZxI+n02mCFp2vxt2wCU4WXBnYZIGYq9V51oL+Yvfq1Yvf/uZXDD4dZyZb5vrq5cvDfSlLzbydloKeO8nFzMyLqoAUyJKHzZDcxMrd6bDfX1+/uBrfvX99+/bu8PDyeu69KvT7P/7h3fEPr+/uTYG5NnQFHF3J3vCfFSZBe45msIqUJTY0AK6kbmLgLOr+BIuuG4IbnA2+dlinpxFFwex2iEjKOUuqWouxECuZECcnJasOZqQk6LNzyGEa1naDldX3LPCVJ6RmRYYgzLHoAQ4hSkISQ9mjQA4yctHGpG2bBAvnnD9Y6X2t9K37hj9jFp43FvdWa0kp1VIbdMtNrvL8QbSCXgjIqZWjn87WgKp1V2OKM9G5PhYb8tcq984stOJja6Xn/KGrzQsjzJCRiBJRhotVVFQ3dQA1A+ScE9XkiMDNNtvNpuuhWpdpe9HHyqZF3UCU2pR/njx96CL99cO/dvXfHd8d/z86/jIQoIWl5pAWjnPYUIEoonVmEmnpkIMIfd9tht3poPOkOSFJJ9KEVCNLiVabUPpg5m7ol2Vhbu5KzCQi4uJewi6EWUTaKZ3MzMHOGZwtdXyaj9MyqYn0mZEWUkwIu2SzWutSijktZjRXnxXMtRsI5KrYXQzbXV6muSwTtPS53/SbxL0t/P7NAYqqlEAy5F66UpfD4aBlFt6MywLo4fB+XrDdbK8ur6+uLi8uLKX8+HhcyjJOhUFJelcr8wIFc0qciFGtHm+Pm81mGLaSRdnS/FiLwV0Yqi0FNjgTQ9yV3EJCkUmasXOsoixNNJpa4GQameIKv4CdnMBOzOwUpsxuRsKQ1jAe24Q/MaT82wbHN6+Y66bgZ7+t9uKmc/JnxtYH//4t63GN9Cpkic/cAvpKLvQfB2l9M2j14WU0yCoKLk66SgjAnSFVFcDD+9Pj/VwU06hvb+9uj+g73e2H4dOhqLuzK6DOPVLKBnE7qkLhnFlyr5YhS9Hy7u393f0ydFeDXPTdhRZTrsOw225fjMt0mk5DGkRAckigx0d/+6eHL1/bqR6+9+KnLy4/znpF5e2bcqsdJe7caqnEcPbElKvOxVANzolTB0pucJeq5i6l2DL7PGPohvFQlnnph0GEAFY3cXDGxcX+8vKy62Scx+NxOR3qdKzL7DrDFnSccKoAMpEgiSYYmakWGPx0d/yyHIdd/vQHrz77wad51x22p+PDNB/NylIrDocDI93f3hWvH336Knfp8W7avdylnu++PNmmEtnd3cGhaSOMxVks8fbFtuNE8zweDkZerU5lWh6w1EksX1xsySkU2oWZnYwdBOXa8mgGJYQu9LIsppXgiYWYXd0NoTZFopyYRBKzMINcQarm0bzbSPZMzFgBlpVRH6hVIF7WaD3wOGUMwXPuw8SSJNpFrDUNG6+l98Al1plF7s4h+U5gJyNrl0AUgiQcMJiBzF0tLCDcXAucW4xKTC5k0NCvAINTA64a1ByNVq230V1XFb0oljY61hOssZY7n3rGaA3JWhP02gbcZteKJJ5fZga4GbXW8qiChlWhr/hVg66+MtdpRa+e/3U9mTESM4kTkbGVUJLRp0ons8cPjUY0hzs4nz2ZzEITKnhtLCJwgMQ5CyUyAksr8hDMTdbro2coHkVxGUzQ9WKdntk0th/MDeywFrCzexiUPatY27m38WmRApBOp/F8e1MiVccKJK0oIACYOgiufjqMwNgu8GvFhCbp/7UjluDoUCSCdFIXXf/pg8pH0MHOOUngcU95RYhOhQOhOBFVhMsoaqmkBII4a7F5XgI143PvDUN6frx7QAKlxF12eK2lzgsn3lxsiPlwPGKJXiCgYjrN4BmCvu+6rsspu3utNVKIGNiy3gdVJ1YWYSJzUziFYFhKiCYzU1UjhTtEhJymccQ0wgwE2eTNxZB2PYS9RjtNUp2XaXpYfCkTCqAoqaJyGpJsRLapiN189qoshfapHBe1utlsd9u9MJ+Op7uHB5Y0nabY1t1ciKGYTqOXKkgosClkDjisLDMY3EMGh2/7jXFVLVWX6FXklIglMVctDpCwdOIEZXpcJiGi3ElWNU19v0wzzLs+uxvUXfJic+f5J9//wWYYxuP45vN35TTFJmkCU69zVcLNx7IdtoT58Fh+q68/8ZLzkHbpeDjoqF3Xccdm0YZpVqrWM+RLHTqibOxa1IuiAI6qWo+nmLpG9nh/yDlnzhyeYtz4Du6eJHUi7OTqVqoFixPu5sUtnGxAlpLkYYCjLrVME2YgC4hIkkRjnBkIweSEYEXwo4GsrUwwdnIDsnRutfW6EklCaOuZAYwuS0zAqc7hk5aEg6JTtbCxh+NcwNSBFCcWcqLU2inVCEytmQvWhA69LtHMeI7MJQwrAoZw91oLOWmxYdO9eHGhXsdpLmrO2G4GYlnqUuuyHEcXzAu2u67fUtdT7rvL5NUPx4N9+uqzm4vL0+HoVafx+Mff/+5v/+Zv+9x/8bsv/uHxF/Ny+q/+/r++udodHh5/95tfPV5ff/bZZ0NOmdAzE2HTbZloPHotejyeaDAXTyk5ca11XGYAuRvqUkotF5uL+/u73fZit7v6yY9+dHO1EYbVejg8TMdlt3/5k599ejxNSymSBwCnadS7iQha69/+9d8ApMtyeDxe7gdT74dtPfDvPj+93O2ceRqLJ+67Lemy6JIF0zLXd/O2492m++zTm6mMf/y41FVDAAAgAElEQVRyvszdcR7/3S//6ZOXn332yXCww3/33/+3/+P/8D/90//9R0i5fHn18Pp+XuZMabfbTNPE4VwB5JxBRkSAwk0EnFqHXa3mIGJPIiTkIdrHnNVA7I5aY9sGXNjZCS7W9x0zuVspdamVBZIoSRpyb+aPjw92CNw+u1oxy5KGLcN8KcokAeA6yNayGhwswswk7uZqGpUVSqnPgxCr1nmZNmkriYgSwappWUaYgdF1W8nJ5qWUYjXkSUBZwuBmGqe5TF3KYadCJkwsnInIqgdFlUCSmZhdSN28VmJQIsDnpZipmQuTWVgEg8QlSex8jgqQMLOEHKkBnjKpu6lRGBTEtI0JQMSrqUjrRHeABUR8Lh5FF0m4FMbey5w6ARnY1N0EV9f7vOsmnSebqGMkdvdw5xhyznno+4Su5A3+dDu/uLT99uJ+fng4Pe63V0OXN0Pe95cvXr6c/Qhg2KBQZ9Wnw0wpt0ChVflBHA3KTxsqtaDGz7tw/P65Pfx3x3fHf+7HN/JT3P25JVH7VXt9JEoN+f/KG5lYUsodnx4n7mz/Eo6qqAtmSalodTYSvH339lW3ZUpdN9Ql39893N0tm2Hf97s3b96fxlFYUuYkmRjjacYM2WVinue5lpmZNjcXJJjnUYT7vmeVTnziGZm0lo5TcNJrnTe7bG6px+XV7vrF/vPPXw/73Xg/Pz4ccrdNfer7/jCeqtsn3/s0szw+npbp3ZHHH362/97LF0NKp9NhmsbLa3zyvZvj6d58vLjob19Pkny73W/3F3/8w+3/8j//74d7dDl1ki+Gq83N1SevPpvn+XQYyzyb6243/OEPv7u7f9htd8uyvH9/33X99eUVu/zmd7/pOM+1Ii+wtOl3Xt0NWpqizma3ffvF27LUzVV/e7it1a5fXWHB3bv7LMy9sJPOVoui0cyhDtWKWvvUaZjcsJKD2JkhIkHETswwswLVwKaa3I6ZqUOi3tzExWwtSPBXhs1a//9wndS6LqLPKxnk7qp6Br3CQwpY+V3xSz5nrxE3gvirA5UIIqtlbWTt5gBCpSh23kiI4hPWH23ICsl5hf8KJnUe/GvyZec1P/4a+UuodiPyWPWGlhIRCRGScNTFSKU+KAZkwrv7N1/+4dZrdzwuF7tXX96/uX14vKn+5u2bn/3wo89eXO83e/PxV7/9/fXLyXzzvY+vp0lff/F49/7uYp8uttddl/7DP3wORme9wX71j/8es9O+z92Q8+6HP/jZP/zyHyV1Y1ky+rTJMN9v5e27h0rYbvG//m//J0746OL6pz/8+d/8+F/9m3/9C4jPOiaB0vT23d37B6QekrBU/Ob3ry8u8dlnH11cfjzPy/v3x03fwzkPw9V1vv28DkM/bHoSmuax1FmSXOy6rutubm6Wsfz6l7/+4+dTTsGBTxvpXbCg6mi99FEgd5Jl9jLPRQ0OlFasOs3lV3ef//F3n+/3u5//9c+vLm5uX9/+/ssvE+OL333ugDMs+e//+Ltht7t5tXt7d4cZEBSavrybdpteujyW5XS8b013gk2/+buf/cvk/vb123/897+4fvkxGJhxdXHVdbmW21KRKm36np1PZSy1xnA2cghSTqfpAEeXO+o6rWWaRhikZzN3jQyC4J5BiUWrlrlaaOE7N+epQGe0WrP+dA/zKWv1cIKTi7S6a4yu6isMBGISVzXzElpOwR1xyY2NjxrzTARIYvU84skBCzlvNwAG4lqKuakFT4BCwtka0pRTvzK2hDgiuEB3HOHWjmbUF/0vpm5Ug6zTSv7OYUQLl4jG1zYBNHApZvWzGRr5njCFErea+VIca4uNr18nYvrzvEe4bK3TtwlykDCMG3Pp+Xuhz+I8haurazf0plZLifZtKJjQ9cxo2tNQN3MUD3ouE9hVq1f11MmqWgIm4szCSSgh1rWQh2cvtdR19fDo6mS2xdpC1BBHKLx6k+WJDxSAhLEyraJLOgzMVkwquBVODjYHxBEsOgdT6PcmTuYWzeMklM6oPEeX6TcDUM/wvw9ESZ5W4fOi+fW3Pq3gaA2GtqKKz2HFFbcDEYXhwxPtlp4QSHKQRT9NFDOAMClECPI6FKHbcj4vrTwUEVGbg9BAK/fK2ZlCPE7bF+TQ2PYV/6NQs2PmyJFC7pqFhAKyi8kUQjJMBHPiM1NAzRnm2iwxlaDmyl4VQXggQsCNBXqqnkkSS2YWypmNuqUurGxq0REqRq5Wiik4kTuT9YbEnDIhUcrakbovnaNnmxvRDIxOcui1CbgaWTWvCIjHXV3XG960xl0Xc4EzOYl6bdtnhhFHIgdhb6VKD32wgHdBhJZONzpP3EdJSURKrfXhOI2TuTKTuFi4tNnK5igsvXS5S12RxBZwZZKuy/WsG6cKc1IiF14LaAJiYzhgilUEv8G3T0sGiBhKgcLD3apBzY3I4BxEFkKwOpuVqT8FEASHObh6ZSdnpyQOjfUB7CSNiqkOc7VwjWuAuhnDca74eZseQX5cI2l3YhIHET2J47VXRCNYkAyJANTausPaPGzsqibZ+CHa/QFtBWcjhSZPZER07lAzBDLLJETmS124IHVpsx96N3NSr80zEdblrCggUqu1erYcyoAgM9NSllqKmRHQ5/7Vy++dTuPpdLq/Hx8O9wq9f3jfieg8lek4nWQej9vNbtN3JikmXQSdXdftNruSltmmWhVwMJOjmhHV6BvVqiFnxiBiSSxdJ/1uw9eyTHZz8+n72+OXb2/vHh6qlVLmlGpKqe87ETmNR63maqUugG02vdVN1/cAlkXBhsxkYgTmNHRMAmbVukxUt0PvnMAJhIVoNj+W8fZw93B63G+3lFitwMGM0+Nj7liruQRh+kn8DABREKsMWHV8Q45pfWQNK4ni7Dq7YrNVNVdrXYqtlua+6taixcop5QywayUNThaRx95P7ARtjhYkBiNQ8AT92Wh1M6ezPlcEFKoabR1ucBiZmRtFqOEE9kTgJiPZeOnSrGXQ6lQkIrlPtUwxOdrC4V8tZ8deb0buT2M7wu2UsqlFV294P/t5IgOhwE+0KqCcy3vPtyBaKV9rmTFmEBNFP+Nz0fTYhNF2vTUfWunDJEyuAGqtvmDRUkwBTZIAKMwZ7DTkPnG0jBsYS9GZl7ksxdThpSz77S4RVJdBOnyKLqX7aWI1pB6rVN7TfXj2uL87vju+O/55R0w9SQls/dD97K8+2u2H2J1P48ndmNmYOCWRRCAPKScwjIs6XM0CyyBVcy2pT5zIga7PqevMLCVWV1ONZa6UZVnSIJsoaVOXcpcl02bbXV1vnB18IjIrdbcfqCODL7UULdUMVk2hVHMfRehCpjnz1c0GzlAZTwdLzNCLy03eXty+e2s0iZQkuh1wcbl9cXXTy2Z8rJ1sPvnoZd+/cuxev35/d/vbN1/elqkQEzmVpQxDHnbdbr9jTofD3TiNl5dXqvr+/e0yF1chgUefuFv0VZMTjNgZSlk6IbYaXG9o9BYynFxhDo4trz0DRIZKDijcyYkgSSDODLCZNcORlmRQ6+ShIJsAOCvOREE+uu+DY/FnF0p/Lrq8JirPg7Hnf/gG6PQ8jkCRyHxrYoX1G6wn/uo/fe2kH/zV/9zp//LjqVXmKekygNyNyIU5kBkoqmI6oUxuM+psVn2/v+QOShhH3D1Mry463m1ODw/7CwBCzrUAxl3fuTNLPpyOd49TGK+JkBAVE88ikaY7jtN0PMynqZIzsxGJJCYiYWVUcdkTDpM+TMffT79/+7vbn/zgR/eHu9uHMhYzck5IREkkdUmSOhUmPh7GUhXuQ9fl3Lsa0wJ4PwicDZUJlLTbSM65y13Xde44PpyWk24SyJPNWEo1MBlpcfZkxaw4zJvhfQEroLACdOiyGLya+SgzlcP9JEJs0gNeMVZLmVKSruvSJg37LWBLXWaUOsMcJKhedKF5VhjQAR367fZyt3/99g3Vero/TkVv37/nju1k42HubvqXNzePy32EgWVa3FSEhDn8pDjxogsz55z73DNxXSpzqXO1qpGhxkhNKUvKzOLsLBJdu2VVulpRjpY5tiHoq651482f508Mr5alNDUoW9XegbWe3vzUHc6KJ8Ek/+ooD7Epj/AULSkDUyRvEOdm0+YI4lbMeAqiUwStgZeQk6E18cXgb2dcOS/rV2lnt2dzjlaywBmgeD6dortn/QgHmFeXvfaSrxdcngEg7W+0VrOjH8gbBa3dGiJaz/HszjjISeIurBdTqwkRWBjkK4bODuJEBHLhbGQ1pWyt7ZOcncASTTitecgN5uYGf44CAd9KOaUPfzpAqzph0wvx6AvlNjS8IYEUolBP3QUUzQ2ySiG2O2BIQKh5rQynf1b8ezYmwNeER4BG72AOy0hfI/xnr1zRAVpTADqrxcRH+gdV5Zhp59yGrDWneNUY7ausVUNVA/AjrNlLjOyGbrbOzJhWTOTBmxRyMlV1A9RVlZUlpyaq5QCTJEnEBLi6W3ULthdTgxkI1rZlV4MY3N3IjdzMq7tq3IxIMr1CF1U1XxhDEmfumBNDZBqPUEcFHEKg6i5eWcN0UVgoEWfBwO4gISV1hXVAz0FzDWRXhJ40ZgxaFDNQ4ermFWYwciLiJiZnReEwgTMZOFJiQti3y5qtkbtSE1qjGIpMILWQjwoGQ/CmichgpVYvXkoby+4WiH4YixijTrrZpkzScVG1eSpWw+Q1GRlquDIERESkzEHOiFVSiQDX4CiFNtDaQByDI5qTV7ySvIngNLdSxzoeAuBsSwKzuzmoLb/qteFfIMogSeYrgszq5CRwc4Xxuvqqr5am1sCm0PJ6miXEBAN5Exdq08MDIzU603GbgHebC7Up5q1qiOtNjS8TxcIWl7Qg74wms1D4UURL95rSR0O3gxIEYMopU3ISliypExZikfv7sdSlltLoWgxVr9VFAeIkHZFVNSdXq2Dv+iwufcovb15++eZPy7KcTtNpUsmYxtGTLMtpHo/3Wrucri9vrq+uh24wtXlRraWUQsR9Pzj5OE7zXIiFcwoLc7OSVvlGgbCTCEviLNRl7HZ93w/L4h+9vAbxcR7HMlr13CMNSGIOKlVDTIwTkgsBKedqycFQVIJOCylTEk/CnSTJlACQ1VILlqVo6T1RJSyuJ9XbR/3iyy9fvXzbDy92u23uEwZ0KU239cVHu7u7o7XaqsFiAYPDWc6LoT9bHW0VQqTVTpIi6DdqvCQ3N3Woxy4AoClbRr9nLHsMSSnn7O61VFeDrquBk4hwaFyoqULYo4PDWx3AW2ece7iYnBdt0EqbDVSIm42GkRqRMxEzMVHYsoSjhsQuakbRze0EiEjOXVnG5xtLW5fXGdIwLVuvCCsqDYgIE4U1LAhGbVeK3YeIPIwVeN0TsYYT68c/fZ8P/sfn+RKwYQDQKyWt3RiDn2v6cdaoNMJNzb2qmoYnh6t5FPBRp+ovty/C8kOx5IRxmrLIw+FxnE6+vy5lubm8LMvCQIc0XEKYADOi1EldVoDbG3j+bWIs3x3fHd8dXzn+zFThiDrNuwHDMPyXf//3H3/vo1gw7h7uihUFaq0g5K4DWM20mimZUllKLWwKM0os5GweZFVEP9iZLJNSXkoJ2cpSrZaKhCgfMYHFia3v02bXGxajOSVJ1PdDV3SixEvRpZZitZQ5WVWvKSNlMa9FkSTv91u2PB7LdDxAebft9/vtxc32T2//kDc8DC5d2l/g5Yuby4uL8bDcvnmEDiy78eBv3rx+uDu+u719eDcB4FBWPWF3tUkD3eyuu747LKdPPvr0r//qXz4+PP7q179xoFbrOtF61n4JHw+QEZx1Ucq0zEtxslpBqGWBEScwcV3ZU63fxxEuN7AQ7g3pHYqmCrB7yCEwovq7moa1xTDS6tWrawWxAI9EF/ps5V9HQ/x3TUtainDm6tGzn19/r39tMD2DvKi5bgH4Wqq3Fi3bPnuGj4Kn/3yMrsUR/+D//lW3tf+UozUHnK9yjVTX20CAV8wjsqeBslSwYb/dKtvrN3fTEW9uDz/+nkge5qIXl5fH49EiVoZ0w66alqrjaTxNMwZ0BFfzqlQLclLXnomYpnkZl1OI78+1wCDSBCuHvt/121pt1Pvlsfzp4TUU+2HXb/MnL191B7x9/JLItsNme7kx+FwmWUotdjyM81xSwpBzEgnVIDfrd31ZarWKasWU2FhAjFr0cH883I2H9wXGqKij6QL1Bc5k3Ino4lYcrsRg5sjRvAIKNkrI6kpOy0nnog9vHja7DQy7vGPmt+8ekSHClERSki6nRDd0c5DT8f7ATE14VD05+j51V9vN1X633+6223/zf/wCBnakDvNpevXxR/cPh83V/vLyZpcvMPpss09eq1pLvMRI3UHGxOi6vNluu9yFwI7DmXgeF4cmyUnE3TrpU0oxbyqDVM8+gOQWDV4RYHkotRPYVy3plmqF/ek6F+wJJECLTNEEygNNagpUkTY38kjDkaKW689c+ChgITdHiMM3aDpmhJBzeLvBxR2hCNMyqzX9arEbGiS3qkNEeM1k/hweA/CEpsR6FhfC1pgGz6bpmgsDpiCAjCzuiT5NLaImHvOVdaPhNeeya5t8Ed8BcDKKtJoRIBk//whSZosyJoEAgZvXWl1ajNpexnCE/xMYBKfkxCK+5r6Ik0Za3e5Qk/Rfl79nS5mt5KdYa9dUNcgfOFOYYhk0WgvFgZSEcvQzsMudfH0fIUrHcOdIJFqpWCIHSXgmCBJrBP9lKoPr2drw+zNhMzFLs2q0sE0jCsnorz45xkrfbVH6NxeUyfncLwUiKLXeqLilvD505rBUaMlVzAdaFZLJET1eRCzBl/IQcSemlg67a8gpmdVaOYWiwSqEFg3qITPnxObkzE4cHMOWmhkxzDUnRpujK3DBEricuZrDqtWpgMlFYGaVWZkzOEFHe9ogCeH0xwKogdXEicjFndzZK7FSdYJKxUDowQYWyl3uukx0VgEHFO0hOGCRDsPBURwzZlODkJO0+lUjZ1ozZGyO7t4ENEmbzZY7O0xjjru5+mrAWqnOy5I499LnLDMthuJuriu6XQFC6bSc1Bm2wAijzrOUfuiZyCtsMSKCwitg4cpHTezPQO6w6IUmUsAI5tAnnAgtcVVrYym+fgRJawnhTO7gQGcY6nCHkIl5Cciy9ROyEIlANdZyAzsJA86GIJbHOHZ280DFQrSvrUurwFAsnEDTqCJajQ/ROFstf8eaOJ+njYOYwmMbIZXITkKrg6J5tHPbepZ11nqQF89Td12UgZb3B4Wl2/bSE2VSr1prJ303pGERO5V5NhhI4ALiVZ6LE1EyW0rRLmezCqDvu8xpN+z2u/3t/fuiNXW+cUjGOI9lcZRJrZzG8vqLskzzZhh2272j1FrmaS5LVXOWBCVXaHGICrG61aJmQBJXiKRu2HS5Y4Cg5qUsXnqWhHFc5nIqNnsy6kgSD7sud53T6TTO82LbfrPdbnPiWnQ8jNNSppNPY4HCU646NShJlT2BEoMkSc691XkcpyGlzdBZ4spWHWOt7x7ev717/+LFlGV3/eLi+oqXE1AxdF3io5mvhFlf6Ve0FpCb1S/Ia2zVsdy1PZtj1hHBzZQ1WhCePzmwe/CNohoQMitCnJiFdda6FKt+XkUbIA1yq3E5IUng/gxijU3XEQYzDS0iePM4MaMUdOIgCLfRFTtdOCVbaMFEXrBe3ro9Ym1dPxeBV4nMp1FLT9gRwX31InQ4MbOudIZ4vZmFB4PElsNPO+4z/tX63286/NmjwbqfYk1Inr2uzeKnqn1sSGEdSbHDiJqBPFFq9Ew11ZI5VVQmro6UMS1zx7h/fLh/eMDLz4gx5D4RObOhTgVFauoYliNGOIckZ63R7+Cr747vjr/k+LaZ4gCzMKiWygx3/ulPf/LRRx9FXf/93d20LKWU0WvabFNO7r4ssxZSFa1YZnVfVvEiZpFoL4kVQ1WrNoX1TrplnlkodUKthLWmhTDVahbSu+pc1RYhyZskCafxIfX9NJ/MDYRSS6mFBHmAJDbUWtQcqlZ1qXV2W6TrhyFvN91mm07TvMtsJkSp77vdbtN1/f3r4/u3Ryvp9ee3j3f+hz/eqpsBqYt6sEDFenj1+/fj/ZuTbLHf9xc//RefffrpYX/5m9/8pk71fj4JSbFK5O4VrT5CcHKDVWXmMi1WjRJyJ7UqEbo+J061jMwMgYmSMzlgTN7QLJYoU7TStqquyU6Lm8hhvHoRBvXLVgwrnioBq0Z0BK5fHw1P63f7pX+AWz3Htr763q+NJj/vGm0H8bOg9PPj2d+ek4Kf/5kab+xMT1hJ/Ose+S0D+VuPJwbN1//JvOWVCAoBuYK5lV2FuJKhoEfep2HglMiTsFu9vy8MPDziOLq5gFI/bB8PD/NUqrJ0wpIcfhzHaeKu7z79ZDMfbbzVWhaHuhYnzXmT+6S+GMpm2y/FdapQLiisblY36eJiuKqqY14ONkYB/pf/+j/84K8+/uwnH+8uPrm4TqOdZCt501VTYjPXscy1WKlL1wGoRCZkQgZS83mxUmuN8dIlgK2Wcnw8odBy0nJEAulidTQYGOLV3dzYEnE1c2MGJWJnYXiBSRJh0cmdMGy2tZRpmd6/vi9XlYUuhquLm6u3f/p3tTpKsUSe4NM0DP3F5XWWPhHbrIaaiQtVSjZcd9ub/fbyMndZJCEjKXrpucNY5t3l5biUaZzv+TGZuHvucmK2xQDYUoI2Y9BFsBmGrs99n5m4WlWt0Z8aA4KZJSU35JyF2dQBYoc6VWsK7i30imUqtHVp5TRGFc+bWh2AVjslIwe3Ol/MWQ+ZcDDIidhJaE19ADcKVKzN4YB/VvYOHCF8fkaKPDRPYLZWEBvAQkjPLhdwsFFETnECYK38nZGW8/lJzsCKYw3p/IPp6daggPbGs0aqrzaiLVxdlbWfMizEDfmLAjZygjMZOdSDSGZnMa6WL8bZmUPLrOH1RGTszUGEyM4X42AnRQT4UW11Ylsl+N3hROxG575jR6xf566G5oLt7c6EeMV6wdFbGeGznysABPjaftdahJ6F0mfzwCCdWCz3K3K4cpgM5MQEJ3ZbAayzF+FfcDOfDhZubMA/Gw2kaBlhiRzDzDggzGfhtp/b71Yvqmfet9/8ueevjeg8X18p0vK8tfS+kmxUYcDArc824HFnidYXd1DD8s5qRI1dYnCDmdZaw64xgAkPhDVwDAu+uJOAmTmqPOpwqKq7YmiWXK0qRHB2GEJ/Eo6A2lyIxKuRVqdCnImSY273oTEMqkKIK8AMNlYoVF015i+DOKQMPVHq90TKYMq52UeqVbgFT8ylwTcCpOZif7at9OYvmALIdcCg2lCKxKAwhQGxAWAHuMYgdHP2kFPCWYgNhGKl1tqnTb8dUk4imdPi3qxqomUXDFKqoxbXUqoxvAA6+8aGzeDVtaqQWIUVp9Vc1NXMHcZqIeDnbu7KrE1T8IwPNH21tmKvoLuzwzrO7Zs319g2y4KTRSQh3qrRfFwj1HUnUFCHYyAE6soEJglomAlodoYxBngNbqNUoR5aVOfhblixKgABtgYE7uuc8vWFACiUfRAesuYBFrBDoo+Wowza6Idk3hah4IRgXWAAByQYhAC1DjbAlYwlOWEupeiyIU99Hnado1ZdlgVBNhVBSsi5J0q1WlWrqkhQraWWnLMzFAbCxcVFyiJZHFdgk8Q6T1oWYTL3ZZlUS9fnrk/BPLI2PYmZ2TilnJI63Mxr0VqrgGGqqoTUZ2IRMyWzsoyVjUWn6fju3bthfzUuRamamEEXr4CJoRxHYMrXKWi2pDaV5f3d3XjI0zjBgi0k7aG4GVzJklNPqeuSoS6LjnNV85TYRJizmI11vj/en6bjfrj+4Q8//dEn/+IX//RLCOqycDwPYiL1D1VaiJjIiCgsVZnZTcFtBkUZrG0F1BxYY0VibhKIFCRbrsFDBVHkUCklZjb1spRlKQ12MYg3jDqiVgJE2vWtHxewqzh5E+OMC2XyIA22NAJgEohT20CJ4ExtkkXv4aoyHtyzZg0DRE5SSoldITbQKKk0Ia5VZKBN39igWzTV1JZrrQ1JMra2+ljU8z7YRp6lH39m6zqjV89/tvvhT/WxoIRRw+Pae1fhdiFmROMLuXIllkTiEQArMYURhCKTuXWdLKPOjPvj4+3dnZunJEuZBOSuheaU4ORJvBq0Rk+3Pb/+79Cr747vjv/EgwA3MydVM0cpfnl5ud1tzGYw7h/ul2WZljqj7G8GkaSKaYKW4hUahtKqAIil60KLncBmMIa4e7Vq7jlxKTWEck0sdyJJzKqhIsOhagpQ9bKUCTIrZrUkaZCM8TimlBUO4dSlZaqqyAJOLCGxV4u7j1O5fzjW2fa93FxfXOx3XSdmxQwgI2KCikgSSinPU71993B4mH/764f5hDIBCaFloaXqbIml6zen+dTnbeVF53o/z+9v7x4fH5Okj15+dHd7f+cnd2di89pI9+BIlqKAQsylFrBf7PbU0Wk6FStD34sITmsipGBjCl2FALDciKNKCsDMVVfcCueKOxGxs4ega9RPzhX9WOZbnaGZXPlXF8uWLJyT2ADCzpyF8x9AH7BJ1ld/ffFdQauzPgCdi1QfvtW/ejHPeMdPZ2+1fcRmev7YDzamv+ygVlL9hn8yD3nsdRsO1DWM5oiYJeyq61KpWEecmODVrYI8JVTF/d3xeCz9ZlvtSwBarRSvXowwl3KcRvL9drP53vd3t188LLeHWhYA7gWkw+ai66XUiQXb/ZbGeporUKsyuyWAIOw5UUrI8FGcQD4+TJ//9nNK5Yc/++SnP/nRSQ/34/tTGXOSod/u9v3hdLh/OC4KFuSELsEJOWPo+f7xtFQAEEFiDNvUd/30WMex6oxOkzh5IT+BZwh3RKRFtWjlOgyDhzI8KAkRWIVcPXcdEU3jRIy8zZK4Vj3ejabaD5ubF/sX1y+xh3dQ8ZyEu+J28sAAACAASURBVBSNKWaWu247bJFJZYHaZrDNttvcXNKmtyzqNk0ndOg4wbw6JOdxWlT97e3d+7cP2RmjyYIeaX+56+bl9v3DMlcQ6KK/fLE3zJLEzFR1WUqtBY7w9XHxJIlZiMnhplqq16puQeYPXirMn6YV0ToaV+iGLPR96Gm6NViHow8YZ8kTXqcoB+2gwdArArTCM80OL+ZYg8UYgXC1F565Ss/ivFYcNmn5tUVHc6gyreAOnOPz2Tnk5ryBxQZeT9L6jePrPIcsztkYNL7NczSHEEru5y6w9ZfnOf7N0DM9Q8fiLB46jdqwlkgHI8ONzqMzy4ecJDWsEOTNSpIRSvweJLBwqXMoQKYrihS3jteGKUM0UTnEmdbebKygDa3qNr5G9/jKIrZ2m7a8BeeEe11nQuAZDoK1lIKfljJrBfp1LW6339xYeW2NIoelWLeZm3z7f8ThzW0KAosusPOjXZ/Es6cSt2l9QQgGrI8pZgQ7xMFt8Qx8gD4Iz9HoZIH3nkcrhXw9ORCNZmJmRUtwYZkZjtal5kgpVatYzc7jwkopwT3reoKj1tpAdeb2OAGrWHwJqkuI+Kuqq3FF66FyAsSN0BrwwmAgkjFfloUBdiZjGJESGdViqtXNQ/PP2cnJa1UFFFSdKrn4eSfmBFYwBbiuQjklMleyaiEy1NA5BWmSrs+SlsQFDifh6nWZlrIURmJhTgaiRBlsPBvDzULMzs3YnRaQCFGGtRqiosHw7mWpDBYCO4cSmK6qeBpstyCDrmjLOtxdfFmWE405DdLlHe+gOk+zluqK+KQhb6xgmotW401GqIPBkImUbSlEbNWsNLGbwJxhMK9Wz3I1cHXY6shGazBiaxs2nkKcGLMi4uahDxdFKtNqaxeVEImQwxMLMpuu1qQxuTI1ilOY93ErV5ynugX6oN4Eppi5NT62neA8TwEmVwoT2XXJsLXWprRuAAQm2NzMLKK7UYM6T9HpRHiiJZ6TeCaK6gN7XT8/pqu0f8caOioB8DIeU5W8yZSo6wbuc6W663KSoR9knudSi4MkSddJ1+dayzhOYOr63A8D2IsVEGqtj9PDMtfLy8vUyW6/7XohwcPhfiJdlI08c06p21/sN5tBROK7BHDjREa82ewpJcn9NE/HeVqWqmqJaV7qvBzLVYVTLbOw9xB3Myulkpq+u9NP5mMFcSIkzPN8ejzkyXeDwN3M3tjdXJcuZy319u2by+ET8utIEtTAzGAzbpC9VytxtyBCJAksHL7h8IrcATzX5f3D/et3ry9//P2/+1d/9//8w5tf/F+/3O95PB4TMUhYxMycSEQcbmqqxkxxkqYQGauN6TqGgVXuEYB6qCUYQGTUZCu8UU2D+RNbIrnnLExU5rIsi5b6VP0hMLHE7ggWIRZobRsbNT44R+HDg5QKZ2IR0SioGBRK5NKceMHMoNCacwdgqu6ksROSm2tVjQJKbldYS9GT5rROyBajh1hCu5hoU2ykv7BZOVOynGo1ZjSfwwACQa5u7CztMyOeoHNi4+cq0tf2N3c1jVOfg5WwFTsX5ANGq+3JPCUn7lBAoiXTlJSN3J1Y3as5WfBSGViWpaJwJoNvuu5wGB2Y5un2/Tu1KiKvP//j9e4y72723e6/+S8u7t/3X/z2+H4sJAn1fK3PakHfHd8d3x3fcvyFk6SadtwlSTlXZh+GfrvZFp8IOEyP1YoqQfjq5pqZVW08waoyxYbFoIRqVsucyFRTyiAWlrDwAjxL2mz6h8M9JESJre+2IrIsi3rdbHJxZcF2N0hCKRNhNtJqgJh07pPValWVmYehqzaXWrqB+75jIXd1V3cppVa1rsfHr159/PJlEpymx+P748UFXeyH7SDD0G2zb7dDJ939+8df//q3b17j/hY5YzPsIZjraT5VBrL0qHJ8XNICv+Trixec/P3t+3/7b395d//wVz//ORGrGQAzF05zXbgVG4wiBTQnMDnpYklwub+gjHmZp1ooc7T2hNVV1LAp3JHsXKaw5sjE4tSK7b722LWFl1eyhrUAqFV92uK98hIc+DoCtR4NGPoQUXpCr9p2+JceX8Wwvuk1a53yWbb2jR91vjY8ve7MpTqf6MNP/lYCwP/HsSbXZI1Ch+bIKSgFjulxmk+TMLJIPU2l1IuLBFcb/e27d+/fX33/s4sv3r0l6rqcp3meT9NiyzjWai4EiGw2XddJl1OlhRgLa+7zdjekzKfxOC64yJwrg0Fd14voMidiU1hxK66zYoarM2Gz5eNj/fUvv1Acf9x9//LVTjZXfIpkACmLczbLVcuwwX7XbXfZK7nmnPEwTmJE5CmDmTb9tpcNyjTkpVZDEV/UJlARUQ6qji2O4s5GmVDNXcFE6iRERAIWFyYIqFSbx0LCTFKmMpLaPG/7ucz685//9H56XOrcbfo85Kp6Oo7TcUokVP3jq4+ss4f3d9BK7vM8H473k1WWJJKGLl1tr+ZTeX94uLq4fvv2NnEi5nqsp9N0s7s8HB+OC+YHSMYPf/Sj3fXlYZ7e3t0+3j0MF+JeZpAWM3Vm6SXn1A8dVNVLMIdonkst1VQjsBEWEKlXNwijUV08JNKwjsNAlxpP6pxXRfoSHQLUgswoEqDFd00w5RmXvL3RW37WiEYxoc84csOF4p3MrG4GoxAdXyeNS1O5ioQwLpsdDG5JBaSlkGj9UO1CzEBNiivmfJPaPssQrZXWeHlEik2QCJ5Y3JrBvLdO5zMcAPGApJ65/zyb920psJbCBQNj1VQK/tR6H/0ZgI0n2oMDUftXDkUgEIVjWbSxW9g2BFB+XjxbF1f8aHhhYmGs+L+dbRS/YcU4X8Oz3/k6NtoCBW5YHsPMPXT9yVVXmCDes8rotCJ1W5Bc3c3/X/beZNmW5NgOW+4ekZl779PcWx2AAgE8AMZOpEnGCY0zmommT6D+Q2aacKBv0Uj/oIkkMw2kwRuoeSbSHh+IJz6ggGpu3eac3WRmhLtr4BG5971VMMo041NllVXde5rc2UR4s3z5ctUiKROnoG+kvhhaIyW1tXcbELcv+daCF7dzw8G9JcYSkbAArhrNXddqRycwBO2w80k6jGA9JWgKblHU/rCJ0B0uzGZuMUyTwcQSwzLM0Ki2AKCqIiySQrg+DLJwFoh68UjbgvuoUUV3ePJIZ8nFEzM5kXVH2EBiEiJ2J1X1aq5An75JANRILfrsrRXinYh8cWMAJt5G77qbaXX1RjsixPhCEKC9hQuh7dthbwMSw9vMEyoEYYaZSBbm6E4WImKhJCQZGaqqQUBCNbvMKyoNI4iZkjBxlkG9mlZTcnLTgMCadp4XY2JOsYTYG6MCFnoDMVUvCQX2QeZmcJCDJccaUXjvWAYkPLDOfrJBWSSNGUjYJS1FS43lyyPXpZgaKqQSE4pCjMXIK1hB7Khu1RhEzmRiDqjD2BVkPcE3hAwPgk/iaFCctypAIDnNBDlTYsA56JlNvJpRtYPvbs6tWykIKWEsnNyVIWqBJ8DFwBxhUBse25a5hsVr1qzxbq3HYNQmEzTSWNtfZm3fAzCKIA3cyJwhemVOMCIL2iHM2r7vej8U5E++2c+dQHfrZ2IXN8qYAhokIXOqq1L2+8Nhf78nAXxNfKFE4yRjGeaV4oNTFiKUUuriIjTkcUzjkCRJEmLASllP89vpo0cvKycahhHinChP2W2YT0dOsp+GMTO0WFlJlaNmYlAjM0opZ6a9JDXyy1o1lGKhptX8sl6ySC1rqi5DhrArgtGpFe4rs6SkWSphLcVgsIFF2NQva9GnU85C7k8nzHXdZZfMIFNdyZWZheDMRq7xmoqt0Dz4bjyQ5NVJy0xpWdJdpnF2HJf127fv/sGv6Sc/+fjzzz+FI48yH4kgRCmMhAhaTYiDX6vuzB4qHi4uCVRBAf9El/VWzhAitkYxDQ4ggcUlmg7BZuzEoDZ2IaFSXbXGENWr8SU3L9xQW2IwS+VGNW3OB71/gRqDlGIosRsar4rcQpYLzBuDi4BAekPfLqbRo7Uxe6i9OJE43KubVRpGMu7NwATSHr04KCT6qLf4o/1kqHw5t1743nfY2vEZ2/bZikA9pWG8N5Wk31yjjL3XdduxrjD3vYRHrW4V+HGTKgvX2xSpzBRaN9VGstKUy0Bk4tVKpTV5EmcUzkQ5ZYOdlpOiwOXt0+tR0v4eDP1n//Sf//mf/+Z3vz3CnSXpqgSm/i5Db4/0eqOb72Rc7+vabPrD8cPxt/poDvZ6bEJE6MGme/9bxzYYIJgJD5TMoNNBhp1wNmFTlHpZGA5SGml3t3OHG6miFiQ2N0KzUQQzXdVApoGnhOVzNgjTwAMUQx4qKtTg7O7LUigNOfN6PslgMhAJqlctxQnMqBW1QCvp4loIDkkyjYlJU0zpAcGNkxMXiE0Hut8dDi8e8mFf1+W8ru+Or/f3eTfKLsvdMO7zdDf9WPXuzbevvvwKlxPBiVzKUiSLVx8573ZTzuN8ruvrt48//fzdm9ff/v5r7MCEMadvXn394vBy/zAtlwICk7QoqAFSHOTUMEG1VK9GNIDEuFX/1NTJmWAKdk7hOCLKNtOoTvQKATOTiJuaaVENgx1z6CNDYaKICUz6y69ocRCs9TOi5aUtrY6eiq4I0heNYytxemsI3FgR14r8zde/s/yuxZjrF28qIs19QICukNrZYh+YaG+3H6Es+mBCv67wG9CAKfJodGzremkbjsZ0k1htVBaQm4ETAopttAqPshgUVgxGUDfbnc50tx8nLagnn2VHd8W00vw8P707v/s87Zc6ZR5EknkpZV1Nq0KYh5RUqxdyBk2kC8qKtMd0D96Zop6XhcBtPFFCYh6TVGI2J17VL6VoKTMq3Aic4DyJz/P66usnZP/V+GeHj3afPOLp+fl0mW11choGyoTdXoa9cy4GlyENIg+PtbgyMQtMlclFLAmPQ5aV50K2wgqPGJi8luJVvRgBwq51da1OMNOqYGczmHvVKhCWRF6Wy5LzEOkWO9e5Hp8vT6/fvvjpvjw920nNFq1+uSyn05mdM+f9sLdKMHZnykPe7YxR1tlh0y6P4/j4818edvdPr46lkNBo53Nl5wqcDQt4YlKminHnxP50elqoWuLpbr97sX/79muublGrJEkpk6TWc2O+1mKqAOlaa1EAKaZOMwdpAG3eGQcziahxmtDwgW3peu3rmFsxVdHDow2IikAqRhtGgbonSnTdNBHzoQdw1LKZQHdi53qLbFrzyA2aQkBCU6gK7a4W0VqIYnfbgga1h3QWAXBiMvPrJ0c+TgC3SYn9A+LTePMsRAQIJw9NppjhRdSi3sZU8oj5G5VoI/gwiFBV4wbj1sziUg1wt8bVQAjmtBiP4mF6G/LkrU8vbtmIhZ3NiYhIKABVQhfgiAuPXr0mZk8SeSrfYDva9b9vxfz6o3eQNEAN74FQLW/YqHHRgtY6Fak9duv2s2cl3SaDyAGJWD6wo9B+d4Q+D6WG2TncoXodqro9aPRLaM7o5q+1izVSt6DxnkUEgKq5O4uE4H10mbpTb30NkakbI00wNzPzbTwkAdQmPLQGl4AcydvcOIQ/SywxH1BVtfMJXasnoSHnePpElJIQJUat8VCJSMlJGeSERBIUG+oiwQSE1BMBLHA0NS+A0UAoctO4vijym1lZFxKWwBatk50Dt2qFOBKmMCKmbjUAF2mwGxkLEkdGy6jgRE1mHW4qVtnN4pTFVBeVUYbDUF3VlEli+KVVt2L1YnVZ8zhwTgHxMRGJpJRqXQBGZjdZS9N8BgFOUMCcx0SLe6mUkBKIyIWJYaTROwSFkYlFucyjiY/JGZwsm7lZUOYAGNiN1RlI7rmudCRhjHdpnEbOanmdF62FzGgSswtYAdi8ClNiiAGrolaJPV0N1ZyYHeTCCq2gJk3V7YKHFIIRcYw3NtfojYt3x4iAoM9a00DmGKFsRsYeTccwc9MQoCOFKRFL00CLfSsEqFc1mBupMAikqoAyMTgy7dZA5eTgBhKah3wXh6EOy90GzzXOp8NAqUnA9v4yBpyY6z6ABgc7M8UkD2cHw8VuN1cXtQaIOeTwpFFGm9GJaQ7CnNiMJCGNCWwKq+bCNE3psB9YAOJkT+512O2SklQx57VUNzM1dhzGHarvebfL+5yQOWdJY5JLtafTm+M7K3UZ95NpNtVpnA67vEwMt0QYotBWVsWpXOo6z2WuS9VVUdrbERawDGas6sRUTdMoUxqfT+9200CwVT07SHid1we5TxkimJcTS2byJDWze0ZOyEliqkUedyBSdyG4QAbJY0oDQwCdSUFkzEKSTECoxbw6qipY7u6GS6mylpFXtvPJmbPsMp+r/+6rP17q6XCQz378iAlgzsP09DTvh+TqtXrKuWghdghB2A3g5k7InVzIWbxWdydlIkrs5l6j/pDE2YpbCM05GJRIwK6gygqx0CudZCKVurrG6BxHc4SEkILQspo7MUREyEnYAXX17mdjh7fCQkyNgrk1bckYNaVoxj7GwMRqF+K2zokaOkvGCRxjP4mjcAWwusUklGDIhpdyIopJLJuz8OY8jKL/UqL5POXUk4CQYTAiQIgSoTO1eojTro4g/QtNliFOr9icak8P2r+21Vo2L+7suEkH2qwLN1MNA+NmnIldwho5sVBmSiy22qy8kg5JZH667MdpPw4kWG1ZfS3E4LosxyT+tL7+L/7Ff/5X//ab53czpsGCyRu1RLgRGQWU3XD5jsM1wjVA7qF9fC0d/XD8cPztOHqZuB1behFRZ/tipEvtW9SD805caak9QJR5Bx+I6/zsLz67v/9oqnYkWYFCplnS/k78YaCR15NGiGoGDUnCJqfDILdloZzNwDFlQ90dWpyVqtSBpoETDGtZ58tFlC9reXF4lImeluP+cfShrpit6mVe8oDDYVpWLPPJlY5PaynuZin53TSWzE5+2B2GxJx02o9V5716WcpS/M3T81KViJSwOzxOwxn1JOmQXPbDR5k+e/UV/vjF8uoVWCmEIlBtSGOSvVNFpaoVrvv7w/z2GbVM08CJlAoB64y6ailV3VMSZj7PcxrY1QJwimobETtorSFrTE/PJwyuZMiYy5yQkqS6VkZmIg+qK4d0Z3XzwQevgSMJh8yIg8miTLD2WsUAJoJwJGx9fi8DIfbwXj29lykI1IRwowzrRm3Ae3xey4J6nBSVjcjOGtEY+EAUcVtj21c7VsUcnTLNq1CvErVWePVGn+i0j9vTcU+GYKCmNGlN7QQtSya4s7DFnPt2yQS4a3TJeJypzQADYiBQB7bYq1OmFtnCzRThGhVgLsWYs/H6fKK/+De/+/k/+RnevHt3qV/+4cKWCZObznp+d3nzXB5keJzPCxtLylRWUjBjGHbsaT6X+bwa+/CC7vOkdcHkhxcD72y25bwuPNrxeJGUQE4J4yRDGnQpzkt1zFVXVySIJ7JUF4z7gcpKfnj9bXn88ny+XPLeTD35sJSicCakkfPoxPNqKMVXI+J092Jyt5SFgPPpvJzXteD8XHR1qzyfimsWz4NMqPVyWaysLEQJBCrLGhMYVF21onV3CFUTjQyRraqaqmkUU2spz2+ef5/W/+SXPx3Hcr7My4Ja63qpNpu55WGScfj9F19TVQYN97xjAsqyHp1gNS1af/Txn9kqakw2PL8+S03rsooSqpHRm2/eZidOrBXV/Pn8NLMO+4lS0uopjWVZVUtOQx4Gcq7VtFbXGEPRGPNOoUvStm0N0j0L3N0FZKGVAtMINiJuCoZPC696Lc+IhFkLNqkJ9HoBS1tpkay5ORGDkrs3eZSoqF5z//5RoI6MIVAUbZ/fTr+5Aa9R9Q02SQt9eusLxOP34H3cUUdliAyEpssVVsJCxQRsQSd1B8WYCXf30BcPmLmDaticT0vdErtZA4Iajszhkpr8KxExlXqJ6m9gW+bOjZ8Q6tRtncE3QgZTK+/CpEH0DSEPikXctSlC5ixfYQ6ixp4jwjKXjqa1eg5glTTm0kUb8U3XUgfsPNg/gwcIejNs0anVHNBprWbE5u4IlcPO0Qigrlvrbc4Jk3fGRkAlbVoCUK0E+JOItrfeHmIcsYZsC3XjgswC6YtfERELZfoNkIxbMGunbdrtV2IrUXRXETcxorivpl4dVpeuGGyrpm+eIP5ba22rsyOw7jDTzvAKJrOlxMxsbcUYETuz2qrt3cLdYU0NjYlZOFR3hcUR+kWcmFjaKK3S78udYxJc22kNqhSDxSMTJhGJEZ5W1dTHITn71QU5MVMmcoOleKVC5KYGAjNxEmEJpS1mIViFkhkUCrei5srGlIHsnqL+rhQ3aexqtda61nosrm7u0WgUpEZmTnlI1Vat1SoJhXRCp1I2glJmabTFajBzZmqtzoGDN36CQrkPKG4miriU2sSg4p0LuYONIU5MEAvGRi3VZB3zwEx5zCnFYAVHIkrACleU6hCksRGZaq0tl7bAbDkEO1nJa6vUxcYiCzaW88Y+asUnuJM1sxKq6kyJarFurwIAj7XH1OYv38QSaN1asfsNEGpRVd+0RETEya86oCFgFJGUauORuMKbJgOYvJUIvW3+qzX26OJiEMlmYIiYc79ZuEUizUSCxtZBw76JY4pHB/2ZmNisDc+IjdY0j2LtJrA4KAyS5RG7/ehmx+fnYUp3d+P94a6URYaBTCl7KbbWomqJ0jTtSGleTkIpk9iyzJhf7O/39we4n87PX3z5xeOLh+TDPM+SZDdNKfnIGCG6rjsZHu8epnGCYV3np+PTUtw4qfNS1x9/9Nnx+Hy5XIhZRNRM19V9nHYDE83zoqbjkCYCEaUhjX437PZZ+OOPjqrWozIzBQwEJkhVd4NIFiG1Wmsxw7oumRdFwQi6UM5iVrUaUAhESRhmakioRU+nxUxzzmlA1XpcL8N+r4M9nY5vL6+rzXeHx2lPyFhX4wZUq5m6Kg8Di3hrcGjlLgkdPSLzJtt2dfsglkajEU5wgLpIQeCq2MQTG9uVm52NQMA2B9MAJhECaVVtpR4VYuGkscG9HbEdwpyGuwD1qbuImlwryJDkrrNLBCJpYnARcbdiNnPO4hSqxgqQMCVJcZe00ayYmUgotPToOgS2wTMdr3JXbRuomwCk6DDsJaR+H87fO6ak1YjinC299V6c2SIiCd36rbyzEeI/ON7jDYep6EGYBYRF4WlKvVSAJMjtzCREQsA0TrPP1fPHn31cn+dvv/32o09+9Itf/Ozx5SMyQMGVZeqzUK7qD22lbH7zPatFuL75H1CsH46/NcfWaPAfOHwbe3BzRJi7udswEe7qBRmX9WIoY5ZLXQ5puL/bPx9PP/7Rj+jFrprWpbh5EngCQRY4zNr0qdDJcKiqccwDU3d2s6J15SWF9Y4W7KLuykhIbm7DPT28OMhOJXOt62XB4ZDuH+7d7HI5H3YPT89vTCXnlCSNw3AYDuZKJHkY7+52MvDx+e3x3ZvzxaycLufTND1M0/R4P3766f5yXk/P6068LL7/5AVs+vqrV7/7m2+ORwxiQYUwJ05CwPlyOddFCEkGZjkfT2kQyuzkunj1ioTT+SSTfPrJJ//+j79XV0otP6VOIohYaS3LuMvGsq5LeVeHQ7Ls037Y5aleyqWuiROsEwFiqBA5E7khe1KYupVa2Ki6AZZSNpjB2pyyTRfarNWn2Ul6eBMn60mdwhp+dF0aThS4VZPw+cC2X01sB0uD06FE5H9y6fn7JvgDoKvnNcAt6gpwBwLajwEd5yIA3CalBPZk3MPbmJ65oVfdT/Z85ztG/3tRN4DMrAWz2/NpbzQSnfzXf/PF//g/nP6rf/FPz/LR/R+OwnNKd2UtZoCh1rKsy1q0lDrwsL87HJdFWHNK03jnuuf9WM/nd5c3OcsnP38xjPmPr3+XBjIUEEtKwrmWWtYCdRloHAdPaTVYWasXV08CHYSraHFfrQ5GxFrdF/vyD9/QqzLs9fHl43TYCTmZMfk4jOPALImcTOuyLmaQQVKW3S7H2iuXk65qq9fFrBjUW53evczFysopDVNWq+VSeGzMj002GEwsbGpVq6sLi0jy6loqCXhMcNalvntTalmZSCRXXepyKRXh+t0wz8vTu7dYHMDOBj7wbgKxOHSZz6XUff7ozTfnt9+e51NBUaixExu5MZuRQdVjUIQBkht7pNg6r2sUNIkzk7ihqta1lnWFEcw64EB5HBjUBJOqmbqpTXlqVPg2/LMvzU4nipLApl9OxMQStXJnjnaUeFwOEHfRkjiNbfXC4ARwC7+8IdARdnXVJSJvkq/XFbwBwzeruc/L9g6s9GIGgK2SFz1Cfal3kwUSpmY8+jei3vsegdFjP7Yf6HCKq1lr+euG4v0w8SZec2pna/8J1ORK8Cdih1ndUJ5Wao3UwDhgvTBZpWgUbmOzcpDb4OQQsLVcOEa5kW9GJOJqdbReyujANmdQilaIjsl8EOxGamAgUO83ayyjhrB0kVuEMlf4xYhOo0rfkoaYPHjlv1Izd2yhb90aKpmoyV4bDObp1oLHawgSVqQKt4Zyc/z0/uEbehWJOhOaRld/JwEqEXlPfoiISfz6/K6WlN7/73s2dFulNz8fcnRELbe5QbJaEF9rjR8WAZjmZYlTx4RAySTMLIO6mpkVa04gYA0AAQozEYdfjKUZzaDxU6Hdb9RINcGfsc2jMRM4utIaG4IAM3I4MxM5E5nCXa2JOTVw04OS5jakjNBTClzaLIYjGrfuNqhqtdDeU9J4wapVVYPKWc1KVRLmFNUjUlcwcRYiYQ1StjuFalQLOYRZG6+tOnuQyqgNK262ygGFxr3ElgroRWvlpj4HJ4IRhJCEzciJjCHETKbQuS61kRc7CGZg4Sw6qlVAQQLJiVgorsi62zCo1UgJocIOV7NWFUPDLhHxC20wcCxWYSa/WhwAVbUHIoyNeELXICBup1kos0YgjW/3vPGDDbKBuW2ndEvp3JW2CGpORGEDvQnIRiDxXzqrkQAAIABJREFUfsZJbdzFdt0du24BWa/7OqiH8tyB4O5wiECEhieYhlHuHGG2JrqvgFVXruRU8phSImEy1TWCClvuxru1qlAx9FFLYLPCmXa7qcxrWQu5W9FS1kxCzsxJQedSni7nx08/SeMoTOOQRxldF/I07l/QaI+H+49evEwprWuFyFLX4zybDM5SSKdxrLUAWGsVYbiruhatua6lzrM5as4SpkY4TRMNwzSk9PLFo0sSyeJKnqz4WuCOcXR1V/VatfNvTRjruiS+KK13Ey4LSODG1YyN2MmNGyBEUMXlsqjpMOQ8MiElTkQZSdTLvD6dl6edjOOef/YxfveXZRhIRGotrgZXEAlLNQtKL92solbdMFMYRQtBxPZMZNEEGhpwrqYgh7R1EdEUcRv8EsaQmbQ58raOw5fELxAzXN1DI9dYvifYtY5kNc9l2BAseGNdOVyYaw01YyORJBzZTFAyzT2G0oqIE2prJ3S39gEdmqX+NJp3gTvHPL4IYNzhrV7i6gzknN1jpG+b2hAdl92LmVnIeH1PDrvdVL9Xv/FDfRPeaDBQuOcWs33PEU3fRAiTTsTqpmbEYAIEGv3iTGZeS5QH3B1CQixpHBTqlA53h3en5dW33xweL/cPBxHEKAmAjcr7vBOgt9B4w7DeT9Fu3+b3ffGH44fjP97j//uSfr/A6kD16lrSWLHi7oEv69ldJXgHsCzp4W60/fjutMIHIUkMjWDVDCGFSIAI58TCwu5EBpKU4EytnCqlVg7NTQMUTHBGjLvdTXmapvHOD3cCyZwuu10ecmYi10rstcJMU5JhyPv9jodsZpLSw/3D3d3hPD+vCwuPLx7cKyU5ADRfCtlpSKOZXi5Yp+Q7KStlOXzx+3/95u07CHIePBMsmevx7cmp5p3sxtGNlqUs58vhcL+sy3ycXQGH3FMe+PXbN3kaPv7kk7/+499UU6fuxKgDInAnI3jKYolqQeiwJ5H9uNtN+9NyJF9TGlkjTWRjZe7IE1iXmKuo5sqAscdMkp4I9Qp3aJ6Gn/KYDYdyVWm4IjZ0a7iplYCs917A+3Cq70I879Um2qTczWPcHk0pCFtJpJ/Arz+9XVPPsdqwwg9XaJxQOzPg/W+63+Tf71/zNVHy91a632T7NyBaDNC+XmQ7q1+jYXck5uPz8X/6X774V9M/P//hspZ1v78bp8e3X35pwQloiZ5LSgKutR6fbByFbDg+lZyZLLslMxiUGLtDui+HxVRtJRmmMVUdZl3WsyJDhGs1mDIzSNCnrrEIK1evnBMxmaOuxUW//faJMx5eyN3e6UDEVahIot24S1kEGUqmi+pcVY8XTLucMg9TnsbphKpmiVhcyRJFodt0rWspBeqUmFjItW1YhNZxS0ZCLBuruypC3wYCgJxhBgWDzSqesSzGNI4Zmc3Y7nZ7KD2/eyJmGKE6CCRYfL0sMw/CKYb0sFUk5tPzcT6tI41GVHVlozKv9AGQSgAjDWncDTJm00Jknc9BZgZCVyluTbQpAjMShgixQRvrPrrmeugYyEdDuq2FfRE/gdvsZQBEIXgR4VMf/uMdCOmcwQ8TfNtW420JcatOROR6rcxdU7MbfOrm6JJVgao0O9Ahqpsras/sGntHV+CNMDzhBl652c4I8Xe62heChjJ539qu14t8b1YeAw1maWVdwEU44OZ+SoKBjINQFPFygFlxJRE2h+yN1do5I8bOoafPwt76JgIWIeZkVC007M3aeKUe8256yeSIK3fGd8wOup2MVxB5dn/GAMzBJCCy7Xe/C6HfZtY9k0DLVloW31GiGypU+5IREoJndQWpvo8LC7Dw9mGRe8RIwe0H4v1Jc9e+vSctJb4nN9X7GCzeP+6G5/V9x+2FxZFS2j4iICqi4CrBHZsavarGFcYFi4gwF60U5WsFBBBJObFQLbWstZSasnBiMlbVahXRmBskZG7JPVwYDBZJiTyVZdVqEBUWUKpWWWFewipIzkOS83KhAHagIFBTuZJIAUnR5mwKIFCHq0GDfqEkWQMi5Z61MiM5sxuAAi1upVImh5fLQszCmVnGPFzohAQkgnCaBnFRNTVf54tXn4a9UCpL9Ta4uBGKG+7UIPPm7Ew9xmYRhZQNORhubLGwYhEH9QiZGDGwzWDuCjcyBLEig0YedkOeRAauXudlUagwswgzT+OUpyGlwQ6AOjsTPHqxSQgMU0CbVfQVXgwGYSdJ8aA28KixNTm+2LgsRCSJG0JsLQ3v+7FP/At+awOw4lfb9mo+PTCstj3Io0fg1ph2KR6AOPruOJmZ3oAU0btai4IjwgtMAVFpCLApYCkWApO7ElEFQoidKFGIXhMJuE0V5HDvges30Nsaq67RJ52ciQ21WQVmFhZhYnaCmlrD6l2STLvBUVV1f7e7G3ZFiy6X43k5Pj+D2VnSNOVxYmK45Zz3h8lE6ny6v9s/7u+g47SbhPnt89MXX/3xr37328f7Fy4pD7v9MOyG7MXXUiY5TDmNOX/88jHl9M2rV8fz5elyefX29Zevvz3VksZDyunTbz9OJMG3LWXRUhlEbMvlvCyohsnJnZ7Pl6WuY8oEvKPjkFIpfno+TbsdOA95f9gbLkup9fhchinXinfvTsw0Tmk/5IcHERG4Djv/9NPHV/W8nosZWJBESKS4uWoaMoRqLVrcDOulvFEXKfnh3oxrLTT44W747V//X+kX/+gf/OM/+y//5b/87/7b//7V12tOw1out/Wi28gyJq0XA4Bx2KmZQ2M9AjA3r3Agta5YL5EDMcTZiTRKXOQpZadS3VMSkQRjaPWq6OuWmITE3QnUTLpXuGutqmw9fOBtTmLMYN0sM7qpoBu/1b4VPQtwqImICDoDq/0i01or4BRkQGgtK1b4Y479G8aTiMzcTUNLJcYgEfp5orplBiJ1298d1Ipbm0iqABtzFnT0re3f7yNg9bfwoUru9cW0BxDVLUKv9xBB9TuSwN1lOMOFXEJNjkmQc+JBIOTmaprSaLoSJJLfWs2YnFCrllJo3C26UCJOuMxHo8ziuEMCJx7Ox0u7rBbOCKJQxuTu7K2Y38E39Jjnh+OH44fjevSN3HKVcC67+0Eyr2/Lv/pv/uu/+/d+9LS+2Q++4nx+PqaBS/X5aRakIe8yDWyoK0yrFgpmD8zh6k7uVs21VBBMKnnSqgSx6lBYNXMFYAXmoKyqyzjlcTcMI798eXj5yQ5SHpZ8Pr19enp++eLx/v7w5tt3j4/5eCzELsIpD/Nc1RxS3/72y9evX/3mb85Txj/8e5/vpt18Wky5FH16Oj/TxXT4yY8Pn34y3U0vP3rxk2VG8vvf/NUX/9tf/A6vcd6t7gOZk0tEQmUulSqxZJbp/v58Kqqeh106UNG19faLnu+Wn/7sgBUKELG5U4PqtnTDDX6aT0jIh7x7MaUBBh95TCpUiF0yyzYMgwjOSpKi1nl6urCTVodB2wT2qNuDzQt6QGgOY9KoBDYa1uaYouLgLTu9ugF3F6BNKEIEge1b30X/tyyZ+i9/f4lgA4k+zNjeS7nfL5xcC5bfOxH+1u9EwhYRtlPwn0ndCYjZIxuDaxtF8sG13f5h+1uU7W/LrkBL2bnTqAn09HzE/417fpny+Pi4e/kif/XN87zM83qRCVH0TpJ4zPPz+sc/Hr/80j77OJEMX3zx9qs/vkbF3/n8859+/vP58vbVt1+9fiq/+PWfvXl6d1mKuprVsq7rUinRNO3Z+enpxG6jpIRElqDFC7yqGbk5hFJK9/lh2HG6w1ffvsaKy1tlPk2H4eWP9pWp6LJclsuZyuTDKHCbMnjCuwtYitWlLpNr9iqnp/Lt74+nd4BecJTkiVRqcTMgD0qY15UItGckJndptHIHYMVtdTIiZHYhI5+Nc8oYixZbASE4w+zp6eK5LrOXBao0TEIk4oMXY0LOOTFL5jWVRdXnAuiQU5aceffqy9fP3zzjzD5mW6qfSqWuMc5dGgIAQQbwIAZd18tlvdi8CE+kcF0LKKU0yCSZGezmZNYFImBaLfTlDInZhXLQFSKXU4UanDQkmdp+CDEWCNi5LRuzGiJ2tsWHAlALKa21Y13XZNdUem+JfrA1tr9hK51+70aLgzsxrBccYxc1bsW2Lcw3lHmDtz4Apa+h1AdgdPBX3icr3A5EbJ/Qx//domwaSu+qjWPhBLhIDlltpjhzKNVEU6pt7RXCEtrG1CW3AYKFgoW7RsbdHxZvz980G2d2mBnMFNVbaNhjSetxonPIpDuBvLPMri/rBhwQuHvvFXEgOBlORDeDXKNty317t+894LD5DgDMtCUd5KSu3m/bb38/ri4YTNtbcXdVvQWhthXQPugKxr9XOogUKIAtd79ejru7a+PrNPe0rYP+HD5cGR8ct7e6/bnfJG2N6sD2CLABstFb6t54SyRCzPGSTE1VHWRmIabu5uTMwmYEGLcGeQcF0hd34RokohCnDGIAJzB5ta1mERy49ta3NA/NBxLAsMjpIlMkAkmgn659BgHAdQMKuXUMB0QJeAhPQR0KSkROZEDI6YBF0iVBxoGEIPGCpJS6LGu07QCubqrV1dxMVREq7CAwmSpc2S2ETaPtk4waUS+Sx5AHd5CRkrds0jCSWLu72CfOzBB2V5iD2JN4kpiO7IokwiShVTXPc0pJRDiUPq0RT1atVY0lsVYzBJ35SotQbxMjeUPjm1q0OUTgIHSNm8bC8MZ4inCHSQKSa2/MGxpHsNtEsBk465abCG5Krc8ZjdUSAupu1mbjUHMNAMyIqfXhEpMHByoOjgbcbmoBgAzSe2wbMysotAwy0yDPow+ZBjNR6wwOWSt3j/buvmvIiZlImwQYnDiKLAFgelXlRESmZlCqtTjVccg55f1uAk1mu90gS5qXWta1GGTaHXIeV56nPAjLbkr04uXD3e4wTKgp5VGQi1WFQHb7+wdIJsk5T+yuaoMPrGCWPEyMoSylrDqv67yuFWrMRlKpENGr16/3wzRNIxENOU9jdvaU0roSUFngQClVFUTOEIKdjqeZkqmdT7N7GnfDkPbj6MdnXZY1mOc1ZouzETmbDlku88kSG3yahAhFYdFXzCyciq4Augx+NMZbWb1Uz0PWIrV4qdUmmYZ0Ls/n5c2nD48//umPCVLPi4uLsHMTF7CQ92jmy/yqK7khqoCDKQZPuroTkSW6JQf1l2mtPpmIRcgrswslYTE1rdaGFVpkCLHi0NsSQ/nWiFB09e7l0SUqe6HtaoiBqwhyQK69FLd5MriZa29rR69BEUIPijm0/wjm0JtqSmeLE6BuWzgelvLqDGL5t37D2KluGxdZ+rU0LO5DPu920LXnrvXo4yaUeZ+K1bZm82F0/anrg2Gn3jJMDBKQkJMbrGjhaqGEstR1mO4IxhAyVK+mqEXXVJ6Pz199/fWv7h7NHUxpkOPp7bg/fPzJ42cfH77+w8mlDZ3upom2+whzE06FupnDdiPfG+f9cPxw/P/l8M4BQLcJQGzu/ge1otYi9p/98ieSK6BEVm02LWxS5rKIp/0kzgx2hVVoiSKfgNjMoNX7tCgkQODRwgYJMYnMqBpzWdQ1muecdAXI3Eqd8/CgVkud3WGG4+lEhGnI1cpuP1RVApnrPF/Ol0qUWeT0VC9HQgELhvT4yUcP7+jtmzdP59N6uazTgJx2Zjjc393v7188fLbPnywLo0y2QkYSGV0HhbOQmTa0xOFq1RhmTEndvboLsUc8ymZalrIuBQoSIsCqA04WzgQAjCxPudQVjsfH+09/+omjPp+OrliWpSzVqxWr7AIAZMYWU5ZSFpHkdnGiNrmc0Lgd7Qhtc7REqym/E8zJvXW9Xc1elPTog2Sjtd3FD2zB3p9IizcI6TZp+j72B7Yf8x5Sfve7vmUFN3nWnzjZ9VdufvGqstLUM3rPejyNuIstOb89z80jaX/oeZObOyO0VkMmDv1fN/chDcvhokCSNAzDOA05SylFFQkQAbET827a10Xm5c00QFUSJlor5iMWnI7lxaPX6sU0O+b5pHU1reAsJImJBeIpMVs1XStYFPBqTA5nEKpZMgdBvRBNwziMY5r26asvX2MlgC7H4tUeHu+d6NXby9Pb02XBfl/uHsfdznY7HnZSeVXFMi+oS6Y0ymEUTlTYVzExEDubaou8OYPMVSFIaUBT+gw94EBoCSv6BM2GxpjVJndrhgAbGc9PF02lFqhizLsh7xMJP0hdy24YadwJs7O/Ob67PM+Xgt2E/bS7O9xP+e7/+O1vcAIWU1t9NVRQ5FZmqGZXRAnsSEmIAGjKzPmuPJdWOlerXgUq0dHhbuamFpMFvTqZC6izqJgIpVQArnA1C8EJi4EInVNFjfzfO+ICTnX3mD4UF0XEMdbww6Q+wsMOIv+HwhRvK79DGrcG4XrSq7Z6D4a2BX+N5trj2n6y7RRV6ykbqM0ZpPeHTbf7RG+m2U4vNz8W2NZ7Gw39pNTVzqmfiBCTggB066m9Fzv6L6wNZWvNbh0SD6tF1xvcosLOckAEwAwSD6FncxKVgD68ieW0ID3CeAtRI1go8hJt7Vet3Qy9LupNkMt6tB3QRkMrGv4UYIBHw2CTA3FpLaIUDUP8JyrM7jHi9r21caUyBfa05Rje+U1RDQkrGBDj9vtXG9qZWZvmlHnrw7zNHtCTBAnNl5tk6HsAue0tX1OL9t0NceN+uLtquakWXElr2xnMzGsFwElE2JLWUt1jtAScPQTBopvKq2tVmLmQByUyBIbN4DXG+kWqZHAiSikNw6hmrqsDnFlEQKimRbW6cQpL0IyakwuxBNi39QdJDCttIz3j1kjYoY7W/u7uMd2ANGAL6t8BO7FTpkzBAnXyYrvDneSkYXJKVaDWykTMQkalVK3Fi7EbqTYRMgfchaC6AkSMxLzN+/Q2RZF5CwCDvhR3ZgC8QsfcEUSjpnGsaLAmMZR9serV11qleOI0DMM4uMDcLuXCLkHhKqpeLTMn0LLO5ipEIgxzUxdGyuQgVPPiXnVbNO3lXzHTEPCy5ofRJbw2RFUA50ito1W0u/xICB1oTK2+RrU9KwYcnNJtEtmWn1GbiRidkQ29i28ECBmtqkHQaGVH7h/DIXodIIn0mLs1uLZV3qZpcIgmeCCAktjJG4YGDxihz27r+lxNmMzinxrTGxlgQGiaJide1sXczcpuPz08Hna7zIxp2j083E0JzPR0fK6nI0BDGobDsB/Gjx5f7NKQQYdhuD8cXh4e9FIWM/Y0DsN+/3DY33/y6Y924zAOE5HMp4so7sbDbhgAZ9Dz02le56XUteq8LOo27gfm0Yhqtefn45KW3TolxjjINGZ1FZG0E4DOaylqddY8CNcYPOmLrrBVOL1+fblf5ZGm3f6wn9I7XsjPTKTqtZqkTKBa6kUdkMv5aIO45WEUCf04g5ppSE0xw7g9XXXOwm5lUWJYlWNad8O8H2jKFdXevPtm/snfSZnu76b9Qab9MM+W8+BAreauaipNuB2IBk8nluYSvGPKgYpavE4O9KlTTxt5D+oW6Ce3XoDWOA4nLVbXNQKtCDdib7Bw03p0ABCRlLhcVg4wLCDejc1H3RfGL/ANRamD9a3Q1OxFxG3BdmyFHesXQbSVudrajiHBbWhszx8iCXHA1byNhgiHhh6vAxQDVzsCFpOD+UYEyqNR9/u9Y6+mBEWzazFeb6wRL7uiQw8YvrdQDgCIVgAQYixsqOO7eq0aanUxEUWLuxJEAMDZndaiM9nz6fTvv/j9P/vV38/DuMrFUc+Xp48++fUvf/WLzz//ydd/+E30+YYSWXvQzSBHsRHOodreEiN0W/D9AN4Pxw/Hf+TH/zts9hrae5t0BIP2PrCIFSGJ1Cq8Apj2eRx9SnRavzFaAKurVVQfxarXalY9WvnJQSHhFOOkgZQkD0KMwlpIGUxGLQAE17qaqpNFLJUYniAJktxpJj6kzKfj6c3TN5JtN6WE/Ob12yz88uXjpc7DKEzZTE+n01qImZ6ezl99/U1ZkQU57ZcLieyZLstc57muq44JRDKNk/AwjjtV+fhHn//mL393eq4QJEnkg6nADMxtvBi1tMTjzgzkoqp1LrDCU0qDrEXNbb4s8JBnIrca4XHLdMgAcCKsADDthpcvH6rWWuv5ebk8z+tcakUpc1NTZadMzEyQJDLkDEFoPqhaTKDqURZ7yJGww500erbJrL2UaGlvwY/zVofv8H6XCSRqCsTbcgrv852smHpP+k3q+yeWWgfCvAVpvNUw3a/O9Bql3X7KB36qdxX0v/VlHMFjP1eEtnodg7VdRosQrm7u5uP89n/UJVDgTtJ8NDm2HDs8JBiE5/W4m+6Ar8u6TrsXKbERhgHjmHNOsDTtpuVMecTLl7u3r2uS6kWgQB7mc/nmm2/TsOZRWGwti2kFjENCyZyNiNyqkmIcpizJSl0uF2ki/gJShTp02t056bJoxTLcPQLgaaCcju9OX3/z9vN5HO5abuKGdXFdHRNy4mnkF3z//LS8e1ov9WkUWp5lOVVbCStBgZiNE40kkaRJSJiaqnZpAsCj7M3kTGBq4U+8G65lNbacRSOKYVfYtLs71lOpay3ObktZVnM917pUOfi0G5OkanV3t8tpKH5hqKmXRbkWVGAEjK0YaqvtuXqMiWoLkjFOeXc/7g67FXVeFodxSm2WJZOZutpa1ySSmE3dNSI0b0JXDf00RJ+g9RZCJVcz9Ztev7a6IgYx1cahbxmXO1xEtjUXRba2hd+viN4Axrdf/y4yFRK/EZ1uwc13iYYtbI3YqH2qt5zMCGzbdfMVxvJNBymIAu1cwUUIZv13diIouqNaNvleffOqmxQLZgPyCOhK6qF5FZ163uHSbiYAtKandq3krY+ztzy7hTC9N6wqTtp7AjsoDm8j6ZqMa5uM7a0kTBGwelsA/al1WaAtvcUGlLV4GdbwWuuAXswad2+z5q6AEaxbmD5z0EMdqcPj3crVWjfK57Y6zIKhg/48KeHGqAUwhI74BKMqzuVqG6JvakqKAJIAACxyBYk2QBTvlS+av+DGptkYYsHW4g4t3qRD8X3+Lqr1AdAGbPglutnvFeiO28Vtkzu6vjUTM1iLas/bSUiGnLOwcCmqtQE65sahc8BdhBjuHtrlIOIkKeWUWOAIpoNryHpTYphSrWUYU7Rue3sR3hB7IhF2d2aWnEDCZtU8IgBmTildVo1ZBb5pvTXb0oTRGMzRKIsGysZCY4JAoDH1jtRrYGCJZBhHqz6fFl0KGax6yIwynAhMwsRaqlMzFYGKMsGcOGaQhVWDgwEFtY5wALH+m4cO7ZsWwqjHToVCS+C76tkyJzay0kiWwgIiM69mVYs7SN3MSilu7kxwMBNLM04pC5OoeTG9oqV9D29u2/r2CgHlDRCkjnYFINBNt/fubo9XCTiThGlzd1zl+LcF14mXdl2UfcYGAWAhN1P0cgS7k1kT3u62oYXW6E3ikqipsDlAbgbr4DuZmwxxamYK1fqAOIImF6BVpM9uAYO2cA0gCJMqDGY3NUAWGoacRjb3gRML3d3vQPr4eJ+ySJJhGNz87u6uqqpjXutqy4uHx5ySqx2GaUw5g3h3v89DDn3bIY3T4YIq4DGN94cXQtiPdxPL87sL1KeH3WHcVy3DmP71X/4bY837XFVPy2WtNY0DiBR+uJveff20y2Ot6zgkwKdxrHV1kIFE2pRUyeM4DXlgAGWpdS0MjKPMC1Ja9msdJzBkGPJYR2HJw8A8LKXklNVwfD4L6T4D8HFKwyAOkwznUBb3GKgHFnVj4yTZDXA2VRir4nxanpJPScc0yERzOT8d3y4v5xcvH//+P/zVv/vrP9+NO2YutRJBSwUpUgoEqg16hREAhqqF0B4BplGodxAiIFBzbxiWEtgVcGNJnLh6rbU6N6bxupa6mlmX33MQ0zAkuETyBqvWVKzczF2dYrlHvGbG1AspYeA3ii2BA21PSbKwcJi15vEYzCzUeIZtV3nMBkXrmo8anTUAi5iSJHPt/XrMnb3u16UaS7uznAihB2+tJ1Ec2mY0MKmaAzEb97vepLu/dtoAD9Vs8ynYtkwkIYEdB9AGd7vWS95ztyCHM7XhzqpKCBiLI0HgJPthGNIQpsmVRHK0SC5VT/P85t27FTamgSXNugKFRX/9d3/+T/7T/+x//59/M3yS6rGL1Pe4C2jUTd98BbWd7ZtD7F/54fjh+Nt03KIAvuHpV8y9xe1oPV8BIrVtbaZhwACqGnqCpA4IPvv4I8Nrx1HL+ubpm91u9/bdmwWmMtR10aXUGsR8aJ9c6iCRZKYRLRODmaJPB+4pCRmr1ejSid+FYBqYd4SsKTmExkHgXld8/c3zx59MD/f74/N6OuFuT0ny+fxmN00EVtWcp7XYNO6PwPMzzhf8+pef7ff7abp78+0TAetamJBkMFuX5eI+jtNk5rVgNz38xf/5v3791WusqO7MYTnIanB0UUsNWyFErr7O1pqy1ZByClCGOxeYo1yBlggF8V6YwYpa5gIAglLX8/G41FJXFchlnl3VigmEFNVrqDuLMGWwolKlRCKJ4VQ1ZG2tKhGYJTGpagzMbaIvILh2UgQ1YlJUDq+kiS1risy8aS5zXz/sbdpsw6G2fyiMPjYuBoUW0O3Mq7bwbr2Nm0Z5uOdq0fi9iQW/55g+hM4Cz+pQ19XFbCDZxjQhoq55fQ3CtzPdgAhoqWhvgez5e0fVvOdXwW/od0pM5j5fVgy4nOdhGPbT/en8B7VDylSBwz4PI7mpCOcxSzIgCA3p9DxrZWDEbHXA6Xh58ZFMu32xp5ySJjWYKeuqdS51QSKrtTIoD4mJq1qtWrQ+/D/svVvPLMtxJbYiIrOquvu77SvPhTwiRRFDecbkSBAEDGAD40cbNgzID/4v/hn+HQbsJz/Ni4EZC/aAhmAPjMFYIiSLt3POvny37q6qzIjwQ2RV97f3IUd+HOkUNsjzdVdXZ1dlRkZ28YnfAAAgAElEQVSsWLHi4tl8MBzLVGq37dOQ5tBE526/P4DhFWBWS/v9+O7N2093z3bDpfCBgWfPXvQ9khzdS621T9v7OlrBuJ8LH+rYH/bH/XG0AhBbrTBjTuFHt06VZLC6iEm1RJqbY+G2w5f2c7w48ZK6nAuV6oWZtMduu3u8PxBx12023fbdV28wKgyYMe0Pm6ttnxMJ0VWWxF1iYSfTw8NhX8Yf/+CHX/3i/bvDnRfNlJg8CA51LjxIZOCcsNluhk0y9zLP0zi6o0rN1DfGmAWloKo5sYR3xSEgCkfjTgY8EYIlOLFviCR0bHwRYKIIVEitxgvMvjpgAeStog/NhWyR1xnsFDbEn0zUhi4tr5y93qj6EcQtVv1DBMtUY94GB0EaUbO18Qr9mGUt0en6C2rlrXnhcjDDJbCfZe2sXb6WjwAN7jwD5AKyaAQgYFndTsxYSKphXHyBvNd0r1LoGEkT5W76X+RqTm5RUyhRtN5Upui0+uO61qZi1CXCoroi9KTNo2AAFgWoDeEAzEOpGctDJ+Yl57w8QYCZhMWLr/bHl+8Ou1qjKgiNeXV6qicbFgbVeWn6FzjSKq+GJ1YL1ChQ7o50/rDbhFiilJCOAmBm1ZQjm23u8Fq9gbK02MKlBBTLLFqgpRV+gy8l1u6+YpyLTFGbV+fDIaK1JPvcvqeUVjmt5Xc+sf9niQ2cnUNMSlmWjDqYSQWEYHe3FXF26wgkgLuauhOvHKIAsWlFDd3d1JWquzNLigdrDftk5kw52t5jXXCtxEVPSKabVgU1oMfBcFi1ikoGb7pqS5BiHNqVEcIxiI3JsPT6ip6TZICXxr4JMjsJwaEwFpACxVDgBlKHs7jBicFEwoCCYVHLGA2DYY4oWnQiU7XA/ohI2hqgRadr6cBAC4ZMjbARopvxjQHnMay6zapmxqbkxK4gd6rFfK4AFRBVDQ+gwpMIt+6aIDBzYrhVQ9ElEdVwJlrq97y5L+CzObbaRGp9Rxfo1ZdFGh6AB89kgZfOsmfrbA/0aonum2k7iQfBAxxb+OwNyF/O9NNMjS8NsAAUxM6gBaqHFqqDCdIMYu5y44e3EkD1KGZc/Pk28MDsglrmLk4IPXw/La1AAUAumYiNDH2fN7th2KRx2hMcZgSuZR6Pj69uLjb9cH1xaWbH+Xh9cZlTFlAi7iV14GQkzlwlCedu6PsddByo23abeixd3yfKneSu29BcCSnnIaVOUb9+88bFrvFMemEW6RKLxJZ4sd1MfWEWg9U6AyrCRBnAXKpw2m466fvU9dshiyC4324UYncwmFot1UpVdV5IozlnSX21vSS22UuBKphJBF2Xuj51g9oelJyJwDBXB4gDbWpJAwEJsVYPSlUNABzgnGar7+9vD+Pjq9fP/5P/9J/9z//Dv8bWonMxc5OTC1iEyWC0UtM5lESIjd0JVs0anNxyJObNyoBg5OBodw0QXE2XlUtKamZmZO7aOABB4DIN0tPJTzdzaziZEzfXWUQCaFqyZs0HB9wYi1feDFTb1IPyGHtS0GQtpHtj/pNL3GRxt1prG7a3PQILOnbyS07pDQLCSQtq15qrcBb29rm247aTTyj2KYGDJ4cvOwc112phajYD5oty/OIPwU++zbpvLov4tCFFtaCqUcg6C1XXalEtaUmkFlGvi5lyUxjTNJfH41GBAnCXU6dW3am8fv3ik09eoYLl6fCXeOcE33/852lL/Pb49vh7dfhvm9pPFsDZWasBW19v5gaAR8fxTcb8KTJ4xOwo7vr4eCeJHaqmpTKx2VRrMa1cq2mJFq/eWim7RxFhSqgV5oAbDOrCLohW2ovEMLiVGabMkry6pSyH4/Hhftof8EyhStNU3CCc5rkSQYQdnog32800z8Rci6mBBZdXl4m7cZwKz9tBzEruEkkWmqsegUsRrrWomhn95V/+/PbuHoBaAOC+5MettfUDwdkdRR3CIsmNzCq5qzlVBXlmEZa4d2Hyo91ZEAsgIIcngyH1ULPb27uHw6NXStyBKOdutiMlYiZoBNiu1Wiuzm6KJBJqHc4erUvMTVxose9urdq++T7AGhs3n8xiR11ioSUD0pp4nVy39bE0MEzXjwQ119cEZcvH++IwnmYTloTHWR69eXZwEDEF5fYJerVuLlG50vImC70g/liHeTbDHRF88QK+PU1RfLjR/fsOAq0iOOejij+ZOeI2MI7HybbGkvaH98cxERkL+kFyz5xCEcdKKfOMOk9JNszCzBAhU1UrpQI5dQztp3GuxaIzABmzLU4QubnXubhYLZWcKpw4Yh4HmXc+laO57obd9nJbfIbBxwmU+mfd0LMTj1OFoN+kYnW3G4gLEbuxG79/97C/L1pj5RpDJKXdxfBQx2w8ScSe6kRRdwVexDg5lWgD5CtjhVoXaYuIOB62ceaUE2dyVfXad5vN9QBhADmlzP1m2HCwgpjBjuLzNJVxJBGfUTvfbvMwcE7EIDfa7jbb7bjvjlM5toCUqVU0JYaVnFLukmRWsJVaa8Ogyd2ru/qSsyYKY2dPfAac2uks5xAxQasFnnXOUgnVChCB2Bqhxx2uAHtjioBWtk3DV06e0rLW6OTnrb7TOtNPsO2Hkx9YgZOP0Stg7bW1oIlnH1twGG935mwDaWKIvEpyeewjHsUBJwvTRv6BM3leTPgE/4rzcRrpB589F8764JeGaDEJEzVtxQgDmN2Y3BwLl2u5r7TIvDchCwiEeGn0RM1JXWJcAO6LWF7TXSZaU6GtQCJs5em3rYbB2oN/8nPjfPj6gD5+ek/u0/pAfEXVTyb57KbhZAnTN1zr7EuCgdV6hwMUMN9i7nEmC79WFz7NQp/As/PLO6B6QsoW43wy9+tHQ1ZrQbsb2hUAVtSLrC+ej3xdAB98tZkP/WBLAzhnkpyiIVYts7taqVUNBIW4MbwSE5xcXYuxMFFw9ISYmRObmLpVLaUqMydhppR7EJlHkEwsxCkdHh6jrVa0A2iQjlGwFZjZ1LUUgjrnRCRCcNdSy+y5S24OCg03sAdlNRYSC4icm8H01hQg7hgpwzqP3izw1lGBnCAklRQ+AbNBCSAPZZwgOzsJpLVzgcHJqweZSp3A5kSqTW2H2N1JmJyIyRnMQlULgt4Z4BnaI26mSENrzgEFoaIYlJSMzcnBbImI4NVQaqwUrwAAgUg0MGNzBVNOiTU51MRNiINebi0A5oVo2uYziMEe+TZaSArLqtPWB3IRso+FRQ1f93gGusz5pyareMV5hEhAtDAJcxXwka/Vzm1QMflpgfN9EXEAhflvqRwhUXJzrTAmuDQFMidIx8vib/uOEUAGFloSdBGNK9AIkwSn6FK7KFsDIBiDGRAYWYWnjjebYbvtU2K1DOB4PNIIFtIyHR7uh2H45MWLZ9dXD4f99eYCTn3uO+ae00CJFF40i3By6bqMvAF2afusuzx8fXf5+lU2YZeh24KrOSF3zHjz9W8K4TjOW7OuG3aXV9R1k+lxmgzOyt/55Dvj4TiPh1oLw2GWE6eUHYB03WbHXW8QkJsrs2w2aegq1JiQGMEfNa9MJEJDlyiTL30eCERUu64ROYkpp3R9dfHZ56+/+vVX1IOl3WY1pMQpp1KKqnUSOTJ203UGkDCnnLph/3h8n+/uD/c/+vz3/+zP/qv/7r/974+fTzAwc+4GTgj5f1qpxwHtOtzByy5qepYdXoy7hbofAxWhjBa9y2NKuzuRMGcyUtVaK6uzgaPyDBTNlk0NxIIGPTViZWBELR5rwLhqFeGUskic7uY1uiObmVeYK5nmviOilJK5t3aDTAyvaO0eAt7iRCQsRG6tx4fyR9u9u4eaR1NbaCuMHUQUJKgP/BZmbhogHzkWH1z44xMoLKwzkX0wlAZaLZ/F2Wo/c7Pan22TZ4RYe8DE4g4E89fg0Nm0jFsevKqTgshMC2MmHzp6PIxf+wykYz3k1G23uL8r03R4/Z3vvHz1AkPUd6NVOy7eBQBj8IkGGxx+OEFiqGvF4bfHt8c/yGPdf1dejrkTsYfcddgEAzlePrv6J9/bCCBggo/jYZxGIkpd59NYqnVDKmpTtanYFOoAAaAII2T+CKmnrk9DlyhJ4qzqdQofh+9u76MpDQhIsCwkNgyp72Ue68XFxf3j/ZdfvXOFO9XZTanrmCnd3x8uL7cAAZK7YTMM9zzP83gYHzc9nl93u+12HOe3b9++ernlJNvtxlG5GoCpYLMTSU6l+Qs/+zc/54MkRq1VfSbzkAVHiLN6i4MiGOoodblTrzbOVmeFAUg955zNChTRjB1gokVinYO476nPTnp1c7XZDA8PD29vH5m4y7nve9dQH43UATc5oep1NFXTVJg7Y8DNQ6Gd4AQzY05OzOoc9lUJFaQUN+08ednsNbW83kr8WGKmVV8LwElk0bQpu8dOEYGQhvJrY8pH0rThAX4GmC4B0VlQ04aw5GGIV07Y2fwkoHEDzl/5Oxy+5nL+7scSyi6XCOVnl8XPYOYVbgAQfbrg2fWxvn9/u+tNBONof/O3X168zJIxDNz3kjsqo07T/u5xPxbojI59t0l2QGJVqGuxQExd4HJ7u3cnIAkTlMiY1AL9NMM4TUQEd2ZWtXme1c2FkGBcGytCPJoiIIOGbtj1ksr7u8NPn/2g6oGyXVxeqh8kqZM7MXEvPPSZXl4JrlIZ3bWrYxLf63i7fxy9GvfkTK5LsQtpE5MN5Y+xnhLbFARrksQ4waHu5CRw8dF0nmcI8i6/+OS5QR2eRLKkBLK5okCyuLih7vqdgEnIkpigF2xy2u7y0A9D3n75i3du3g+dzlqn2QjM2QkYOPUyHwuI+u1AiUspqsUV2ZNBUajMRTwFewpQN4KZQYMkukhJi0MrTNbgwM1BGpEg1nguoCoGkRNqNCOLJSZoSVaKm8bLIsLSR6FNKj7zqYjIWr1ZvLsiCRFNAQuBIMoT8VErhg8AktXT8Sh3WQhKHu0aGvjY/odwdinA3XPuyKypop5hzQsgE0DKGb68rqnfvtbO/1w+dVYsfAbSres/DDBzdFj1RgGKUiSAnBjMwbp0UMQfEc/Gp4MiRouWhYCJQ+XJOJB9RNq8sWraWMPen2Fx5g5rlCIACLKut5Jas1OxZQthCMLNQQ1lrY989ThExBbh+Fg1wTda7+qHuNDZZb4BwFrv9Rq3xEYXYBYLm7V31y6EccNXEf71CucTqmFbFrPvQyESWipizyfD2Q8gOsPFgj+2nr1Umqwj+TDnsECNrmS9RNeIxv+kJc0OhymI26YXeACxRCgDi/I7bh5K01InxG6mVmthouQ5dTlzcvJSQRYcGhaQz1DEvhlIATkFYAGIM8WGYe4i4MyJhcytGkwnRoqi3eBExDMMN4s5FNyXPp3sZPGnWnUtRuZwaQoNocrIzCRiBEWqXAp7bQErjMgI4GCYCSc1RODphBZlx/cQ3EjRYsqoV2Mni7UFtiXbBKwWnlgYiAAavgiqe/A8nBEEPnI3F2/BvNGCAEU3BCFJiYndW7cfZ3ZirVoJBifmJbd2jnI3kU5iXrIOtgJYbU00Ic8F214nE2jxDBrahDW5tlx+Pfdj58HbbIp56d8Arq5XXsizC93EwtgS2F2jmDySRMGdiQ9EYeBypwni3IbvH1kLooW/2hz3NUgngEmYkYzEARNJu91msxmIwEJ9n5Pw7eFxnqZh0+82/duvv3r96tX11dWWN6FSPY5Hnm13edkhZ+NeupSZavgUbnMVsysefHP99v27zpMYo7pQQhZO2ZmO8/jm7vb65sWgx2Gzzd1w3Xc71/3xmB734ziWw3jz6maeZlUjUxYmbnC6sHDOkrtZ/XG/H6cjwbZ9v910fT8kgIDrawFSEhahjrnuhqSYbK46m9VSihmDdLvhnEUVtVTvfXex++4Xm7/4375q+mdeYQQCS2Juc0m9OrPHeg+2o5mqm7M5q6MqHh4e9/v9j3d/CGA7pGkyIgaZN93MBu+GvTlBrksVv9pSrtum3DIJw8uLF3gtd8WSx4jqQ5gCFVZDOQ+La9LELgAn4ZBZg5uaS5TrA27xAJdoj5dLw9uC8baxEWEl2J4vjXB4CH7qiEtLEsvdgchGANQ68rrT2hDhY68Ei+PgDblZV5+qhnEGO4H0rG7//NO+SBLE9689yLBsUm2JrINclystUDFOS/5sjZ9ttAY4mMBOocgZELLXwBRTYtSqUJ+naS6zCgAyVppdiC9yX6re7+8F3WyHTFk6OI4P+9sX/Se7XYfX8Fk/+m3LSOnMvCzr25++/+3x7fEP8KDVatKC+ANwp6aqWSWlSNMS8Or56z/9k/9YThlDLXUmQR56tmpuLFIdpXqtrQdUxBmqupQSgZhYqNSJnSl5KTYXhVPuMhI4E7IYK5IjEwlJ4tyJVFxeXt0f9mrzxY5z2hBSlwdmB/jxYf/yxYtxnNw88IXjeLAqjnJ52e92l9O8PxzGh/3dyxc5Sfr081fv37959/4uJwwbpASi2vX9ZtNlSbdv8XoXhhpAdRO4omW44neE8RA4IaFpKEZUBMAx5K7vE0U9gcOqLdY5wl0NvLBOpb/odhe73OX57h4V1DsJScfzfgJgpmbheHM0sQ0FnWroO9BSNQQ0mlVEYWcaKy2mbjrW4W258Vo8Hp4YLQTmMPix/0UxSUQE3lgLTlDzFepa6GR+6vD3W2zpMs3WN0972AfxUfi752cE+BfKsucRL/12s73GVgZn4t9x5tNBnoVbdBIeaW7ncpwNdTkhCvMJ9w93/UvPHQ8DSkGtJXfoeskdidiMMhWvWkWgjCyecprvjWU2MWI3aCk2zShqx6OTu7B5IlXYBJ+h3NRWanUQskRlrs2u0rFvMBlcbNhsxmk81kPdV2d0XZ92Qz/0Y52OR3T58lDnzBh2/jjtPc1aK9RIU6eb/e0o1OXUWS3RuiyJS3IHCiplSimhcqmxOqJXfIOwPpgEBAK7u4GiJJWa3pI7oj85AwP6XR6u+sf5sXoRJpCWOqICFe4ayGGWtBk2XT+o0VxLOR7GOlKtsuO8G77+6g1bZ/Bu0+Uu+VyMYE4ddd2Q5zKq6ayFwaqqtbZ6IoOaobKhKdKsNSPh1gSMtSTNAYdGIhARhAAsiIgvaABOBPGljxrggIAVbSEhCGuhAc4soQNMQd84a4BwPo1j/TbHb03nt2Vx+m+HwxqrZi1u/aBOKx6Lt+g+wm3wusrOPEsCfKndw/JlcCMiYoYpOUDcqom88es+XkpPfsvTauIPjoCnHWTqC67jDR2AEwmWHHK4qGg6VL6IU0VCckE7lnXKxDRbyGM1Zz3sFYGZnJ3RKp8dIR0TexZAi27NaT4vsnfcOmbEa47Tgzvxl5r9fHoTwlr6GqyQhyhzLJbT3uvMjIV15WeEpKd3+Juh+W8AsFbLFZ59E2U3BSAi5++uABZW1NDdv2lqridFlOZuQaFcLuUIwt7ZGJd4YA2SToGMPz2wIGjnEcUHLnwDIEKKOSImU4Ram3qjUQZhJ4ClALBEEiclVFe0MIRimrm5uZKRFTVVVDe4sUISUmhO8dqz0JxQFlSEwImEJdLyS9EnAjAiJOKUOEVk6qzOib2JbTvMDcxwJrNol05krmo0V2QibvirK2l1K6CibSZzdF+ECEkSUnZ1UTFVq25+6sBK1OJRYQmc6fRoGwGJ2/T2pWLI0cp33aK4WJcOZhG7xZNmIQJFn3gSd3aSVovJzCwEEQhN5chEiUWYaiZXCDXdKmYCk5tXNTWNymsjr3AlhxCUFj35sx4xBlOAIMFRi7u50Mlpwchgq8T7OYCFs6m9ROag5fq0WMmzFfTx5Dtbfien5nR220DapeksQHbEPAqIHARicKIoBWVidV2HD3h0Xl1uebt8m7LNep+8NTSCmoOIWSQJpZqybbb9MHRXV1fbba9WqhainJimw3w4lq6Tob8s0xFaxC3Igmzus5poRu4oZ/C222z7TZ20ljrXoloHZtlebaVLBVd51yFb1Vo0991wddHttu8PD+8f7vtN36WeEqn7ZtiEcBAVUPHbw2OZy1xmtdqLdF2yYmUu1SA5U+4mrbf3+7fvHh/3oxBuLge9vpCry2HTdzm9fPFynGcWFkHO6YLQOdtB9w8HVToe565LXS+b7TYlqNo0ldKX3eX1xe4CWyRBdcDA3Ap8DSZMxORWa5TiJjhQCo7juD/I42PqGLLt3Wma57fv3o674z/5L1/OD/1f/81XcDILX0clyQKMxPP0BRde8CJqXFwisDAJe+QRiZnZFh5225Ba5WybA2bQqqYaAoDh4rMt7bdjDTQZSbCzu0FDDw4OD93cBp+5u7m6wmEwI7OTDiULM0nj1YYYe5uQraK3IUcNxXKE1rGrukZ9L8ydPbJhtHgrT8w5LbV9dMaWjlleq0b73cUlQ4Oyf/vxUThxWsN09nqAc4SWjftgq1oH9mTxO9iZo8SRIEJwYmfGkkJAVdVpmmpQWZkAr7UWhllnoHGeZrhzDps/DL3qXDFfP9/+0Y9/+Ff/9ldjaBp+MIxY4UvDrnPcCotL97t8q2+Pb4+/3wet/5qPThUSyssKwJnZKljx6vnLP/mnf2yI3mHODDOrrpQITLWaixjYnGoYUYG7RDESRxlPhmSShC51KaWcsru4kUjKff9Xf/OX3GfpWVld1DsgAWwi3Hfoui6lvNttht2QUkeUtttLszqPx3GESHYfI7lcynzY3wN913M/pL7n97dv5rmY1cN4v53rZ599V3W/P/rFDp9+umOp5lPuL3PHYz1ghA665GMNHOwQXeoHAVAIQIYLYVUNhchzSk5ezbaXm822Z6aLi97UD4fZzcnRZIjXMMnAwuY2z6XMTeO13/Sbvp/2Rwhg7lUJ0iI5BwjslCXD4WRBRA53rAW3vmyiEdhFHtQdxvDgv/uimUsLr5bc4Lo6dssgl39E4NZw6zysXcEmWhq8f/PO0vaK4AJH2ump77cGnOtxciybT0nrdc6BpI83nfNrRILlvPrv736sKIGfh1HLkNoOuPrB5g5Gj+Nhfzhayv7ixc3NzS0E2y22uzRscj+kafRazalutnCFCPqOc+8g84ztJhfzUswPWnQuExhAIgFZRS2GAgvaDK9jA6dU62zkaZPghgoARkqJmMjZ1czdtM6m9Oz55Se7q+MBX9/uX392fXGdH+c7zjbO0zwpjVKOm1/91TEn6/rZSYftcLHd7i7t8Dh22wed4KF0IMLcuu9FHxlm8qjGQuAQBCcykLtCAw9xcucz76PDsMu7m+3F8y0nLz4BlTkBtZYKQhpoSAOxjMdJixWu8JksoZiWWqn6wTCRzzJPRyEWSUO/ySJQrbXujyMR95teraqaE9Vqaup1kQlxJ0PEOM3/Uqwg9Zo991O9zjIH3AEyOIs0h4odZuSC1uKLnGBhMXgBuEOQt4FhgWUDa/Hg6mCdT+m2hE91IdEKo0Gqa+0aViYV4IEzLQVxT4rw1m9FWzoUBYW0uHNtrrcCmA/xl6Vctw0f4faF+7kGUb7i6eerKa759HonhAQhrQU0XWY/uYwEAJLJF6gtIrkGQLaBxWgtfPmmcLxi64EctDFz+1XkTkZN06MVd9AZIkhETGR1wfOWLyICc0OqnPjMKoOZg6DTniBzmPv2S1dgKyxZq25emHhx7eVZLfbt5Ogvwz5/GvSN5u+bGVjfaDdXM+zLZPoQ76Sm77W6/0S01KDiNLSzx7lecM2MfTDGWrVR4c4+Umtd6wfb956NDd+0s/jCrXUKCL3tqh4ybnrKOQBtBQPELCllBhzV3RZhJYRyl9YKBZUF43F4NZeq0VzYISAzmDbt5RgmCfPC+lOylMThtRQAKWdhgcHJYmBw56DfmbcWgUtvMbi3ekI1rQawgQOiiukfpfkoaCoxDGUyhrO4FDIiJyqQKq7WNL4NDlZyZjeg7zPQrFvUGYZIUohbxtomtHZ8K9+OAAQJnBa8NxYIL2gKAewkMG42kqKzYWCmAh9B5swL0g9ODeY0YgqfKVJ1hGTk7lZhLoQu+d6aGmeUpBMTUxDusJTEnhV4r3NmAYaXCNkBX0wYLahPaICFYv6yvJbQc12Z8ftpuVun0NHdIQsjZgW/sFRW+4L3CYmxG3sjqTVUIhp7uKSUcgopaNYQbg9ZbHI/qw+i9Vvi1zU042wVO0dGBSDilCSlxImGnTx/cSMpKjW5G4bp4JPGNmhJqOsyE714/mw79IBpcbjt+k2CdNxvuqGDDNzvhovM4lyoY2Yxr1mEGWPXX2223CVJ6VimuZS0GS5vrneXO7p9s5/H++N8ebXLSHOdRSRJoooh99778TA/3N0fjweCbzab7dDNByvzVOq8224458fH8fHxsD+O0wRmPDyOcGPCpsubq41fX/vd+6KqOicRTsjEdOS5TGak6qXMKW9z6pg1etrVqnDq++H1dzbj0R/2owPRCFm1gr1LibKUSbWWmNgG1ILjaPvH4/3ACTYQlZ2ZodSyx/1/81//2f/yL3727/76lz11CJ+nzS93d2mbe6vG9dl9cYIpNSawSPTXC5IskzAljk3NY77EQuLQ0nRVi9pGWqT81EBqFtp/IMDVrTFMm6fvLMJMBBKxUkrYdXeP/jsxp2NBg7w10Yw1LOy18VzdiWKyAsQkzARokE+jKZOucz+mpa0b4ZlBD8fmBGLxClsFjsXujCjyRcOa+HcANevGQU9CkbZAwsFZQWRaMOqA9rFwjder0dqQFdEUMCq6mUjiqZJQFDa6utXgzTYWQChA03Lttpc5w2UacT/tr1IKVu3F5bZorlo+/d4n//QnP/nV37y/t+M5/fzD3/ghjv7t8e3xD/2g1QM5w6jBHjXRWq3l0ghuuLq6/kc/+nFFdTNiJuJSy+F4KPCida6lVHXPaqEeBZCEPKXkbrPdbLZ91xuxgYyg4R2TG0uSxJwIOachS0/ErEyabMggNmbOeVNKMbXNZjcMvZZq2bfb7Xg8TGNRXXmHGZoAACAASURBVLMaQgTzUlWTeD8kre5eHx7vhTlxnub93f3x93/4/ecvL6V/dbWTZ8/E7bEqcmYWe3/7Boy5OLV8FrGhBmPkRFCPijuGc0pStahVEu9yqm4V1vddNNS+utiZ23GeUSDRkC2alQlAeP7J86Ll8eEAAksehlQw9V13eXM57sfjvnj1JbYlGEcjjj4P283mfrxHtIG2pd1HDDGa2qwIFNbwtBHE/OzRt6s3o04nwOY8ilwC2qDPtl1kTSMBiEgWT2Lv829pc2p1wHyhgXw4FU87yClsodPra7voaFV9nkD9+Dglef7/4FdLfLcAGU+H2bbXNSojAhrrTatgwDSPt7eP+Xr74uWzV6/s/Xi/3XWbbY4uhCJwr+Z1s8l1rmTWdcidA6CE3cUwFXEKMVCUGUJgEkgidyg3gRUHJ1Ci6O8ECjg5yrsUB7hirKOIpNyRSD1OtZRqpe/lxevnn//ed776+pd/+/VXV9c3zz7dbHe9JK2YD8e5zDRK/9c/v4UDHbZbfPbpi8vLy2E37K43m8t8ZJ1rE351XrQ2DcIsLCkzSglsF0QUNAtyJY2pFwsKbd1ge9W/+vTF1csrZ3+cHzTNkS3UueikYGw2/WW/S9I/0KMbxuO0fzjUCfNcTY8QoMdwQHd7m6V3g8GKVybeXW8IrO95niYS6jdDqQWGhXSSVKuVSh51PxHAOiKcDK3n5jaihU4BwCz+wwq8iCwVZRrNbhCKCCTiZEFWbFCFK7DU5PEpBIKveOhpCq7ITvuy9v8nD/AMuWoo2wIftdlLrRsfcG6zYjGcQwHeBtCiM0AaCRLr1XCK60irLbBBy3QQN0nTGN6qhffxylqX4/lLtgolB27lH51DwNJtzNfrUOvat+5YQYlZIWtzAK05XmY5R4IAi/ZpTuCWkaBILbQfHM3Zwh52AYm1eq0oWGJufr2dAuM2UmpYmcNcco6i7vbr/AzqgSPi8BPZwwkhfeIgtMKLb7qBCy60BOcf2b9vBrDcTwzSkz1Fi+dVFb7QhU+3fgkwvAk90dI/8sSGa0+IELXl0Udczdv2YEHwWg11TJKPh1fmYkv5Ey38k/NS8lgFTyKYwA8amBaN9hgNQ12A2QioDKYGJzAnTimJuZtns0JRJOfkZrWqF6CcrRGPaiLTWl2YiZnI4FqrVmMHnB3ODiHJlI2MwVlytTJNYQyck4O4zNqygeSAMYKERSu3jsgpCn7MneAFgLUaT8hCiio1uAwm6tVrA5yMTEkFRCRkAnM3RCHaMrMQrGyWFIvVYALUFr25M7f2DBZwVqM8UaMXCDMV14ZbxeJnAlk0t2iTCRBQDYKdOSvYhB1MggkQa7CQMRqv24k4ahjdzK3C4MJOEsASGJJE/cBOzQSEiW02OyaGEcl5wNwysWA/g6CI2NWWndujAnwx50/n4koIaes+1rUDTE+mZGhzO7OQOEHCKSEiZy7jBGpABhGBI/htdj2A85iyJBDh1EkSdlhRISKDIAppq0dz21AoWi2vc3CwHOyoWJMNlNisOsCkxMTJJfHV5eWLFy9Kmd69fas2Xl9fMsNdtVai2vUQoWk8fPbDH/RdRyTHuWbj51fX5MzO2ZMW66XrJM/jPM1FcmKWBN7mjglW7JPvvHo87iv7OM/TWIdLbDcXOfep6+aiv/r1Lz6xT1++uCllZj5mSaWULqXdZnscp//33ZvZ6rZPm+1mtxmsziGZ0eeBut5tdkUWyAYAqfnj49ylw4vrm67rptw5cS3TPE8cJf+ZfKkdBmAKr9aMA4NB5m6ozvbi5bO3bx8fx9ENTCgGmDFzHlKSRJgqOchZrKipwRxVda46lrof58NUnLjrO0X5kz/94z//l3+BAu+MmJmEo6GBOUDWWjGHZi3MYt36CY+g6Pkn6kbBZRdyZcBQDXAjY2FnFwicSJnUvDTvHdRqQ2rL4jT0zCzqRiy8AXNPRDkl5lavXWvVUJEnB0FYOIlDQYrmFbTNLaVkrrAmwkRtzwxULRoMaDUVYhICqLqba9tWw5J4y20240IrEuwNmooFGaW0RMYwIYI3uXgmgVkQUhdv4Bu8jNN6J6eW+1v2sSZBzI5Wa8xoFFVHOldeIBenlU7t8BSnE4OoScOyJM5F66xzMmdVEIpWLyYZCjCBmCEuTCLkTER0GPF4ON5c34B4LPOz3YXYMOv4+vX1F198kqQiyqhbLs2a6V6Wfrg+Hzh030Ja3x5/L49FlOXklfrZWwENtHepOe5RW9EMSZImiBnVLoxpQp/4O69eWN235ifCk/ndeJxEjnMd53mYZ/deXQPAclM4wapWB226IQ8bdi/mdTxM43gcD6oF0ZsUwPZmSDlxBtgUqmSUIuUHZjqOxzoX4SSQcTr2WZJ08HGaFIZIQCaRlFjVQOAMAmat7tCCbhuxpI/TQZLf3Gyur18NGyXf398+Eg/MOaVc5hk7aAh4EYTJ2UjPsJKGqMft05RT1Wp1lCyck1dFhaHM9eBGlFUgwRhlcSR3W55Nxevvvfz6N1+9fXfbyfDs5gbE9w+3PXXPr59P9/PduzsFOLN7dOAKyi9l7nab3dv7d0iAtiqBJU1KzoCG3Ba1sIyXmJkpesS2MMRhtBDdl0aUbaaco1dYsjKLlIYtOcz1lnzQbRCBjlET1qLIu4Z0KZScYma0wO+88Gb5/if/Tb7ga6BFyCWOtQPJbzt82SJ/92nLmIlW0a5l2VgTCorVwa320luCyt1V3UzROQaY6d397eU2bXebzU5+8wjmOUsVrkTq7rXUWqYkImyqlZNJRnVAsLkceEpzHQ1GkLloJ+RGADOBWUBGTD67CXruJputODKZusFZyDqGNL1pZzNWqKtVKCCgracez57f/Nuf/5vxgHJ0FkaIP7nV6vPsgOYulceKCYeK8qKIGAmIK3GJ1t1NqCv8HFbAPOeuSzl1h8OBATIjkAIR48HgIdC/QJlRSYd+vny5e/bJ9e3j3ftfvuML1FqNai1WxsLOzKxVUwYBpdZa63gcaU4wQgYcXDEfMB3LZtMpdJ5nn+tDlrx9eXV1c2H25u1xrtVg7l7mQkDOvRAgpLPCPEkHco06SHW4k7deMIwo0IWZxw08TaLwJhZtEke0/Fmq2UJXmLhq1Bs1yOE0sxve0bQwVojqfM6fwz0Lf+d0GjdErTHq25T1hbSzErZoSU2cDv4AQGiTnWP8ESa7h3TQKY5v57U2cUCrTgiXrhkLU/WGCHFqVeZkC8DxjZCWr0hHu4Yv8aNTYCZtCRqvUEUYMjR2yerPPQ1FHeDYhCAhLkNt2cZSPrn5DdoJbX1qoNYStXLiuNsB57E6EaL+OsTGfDWcvuyp7GRk8KgwMGApivT2BA2QyKn7UiVk7ItiV5t37RmdGcbf5aee41lCZ6UTq9GMF2ut8zy3fDs1ufFGk6El0Q2AKOWcUooCQ2vZKiIiFkkp5S6nnESElwpEtGZ/TgQR6brc97nrOmYJXlXf567LzBTUoZQ5d7nrEwur2c2za8kCgi1IJjFIGOQQSjlJn1JexM0bww1dl9M2Fx8JJiyZhUBe3IqTgZjhMHWHSRKhTE5lLtPxcS6Tw4l8s9sKhxJAq39xAjHnLklOlJiScGKHj2We5gkhEp+YQDaZAAgMxz1JEk4A1VpL1Whzp6bgBBYWrq6qlUA553GaCZQkDbkbct+nTpJ4pKDqEkJW1IOV0VC9jjoeaplAhnp0h4nHUwMryODq9eBaNEkOQTEOyEQd1b2aaqlW1bWqmpmF2HNpldxMHGgbERGllLKklKSTlIkZYFV3NQ9lLveIVIkjoRIon5uaqREzJ07EHOiXESouNjs2sbnarKSeSdiItImxGcAp537LuYejjLOOB0wVc/VaqDIjMUn8I7Bbw7MiJ6LqK4AVBXnkEQFDQlI1Nix3AoQ4IXNsfRFJszS0gyg8nGiIElE3L75pyEwvlsqdQCKSxEiLWp21VJ1V56rzNDtJYFdOMEBdFW0X5C47A255yMOul0TMLtkVc6mTo/bbYa6zkxOjunOiftsTeC6Fe3EQhNSslgI1kEtOqc9I7Ay3srkYbp5dXN9cXF7215fDMEhOdHmxHbq02fSXF7uh77WUu7t3b796++nrl3/4j370o+//4IvvfpGl3z+Mtdggw832+u7LW579ZnP16ubZ1WZ3sbtSt7u7u7nUIe2+/8X3O0qZU5bu9YtPbi6vt7uL3A2b7cVnn373k08/ZUnv727ffP3OqrnRZti6shpWnuU018N4KK5v94cy14f7+4eHu7v79y9fvnp3fw9Kx6nc349vv76HJvaekfeHmZ0vdlvhZFWJ6PL62TjOh+M4zWU2dZA5X13vNn3/cHccMnbbDjbpPJdpdHVhNtfHw/svv/rlH/7kj/eH+f3+XVKZ3T/57BM45jKnnEnIyTlZ6sjg1V0YkpG6LmUx+Pe/+J6QbPqNqf3yb3/5pz/503/9f/zs//x//irku1RNKLtzTh1DKPg2rUGkZc4Gq7GnJORt5iQKV0T5LeLRSxISoU5oEMqEjrhLl9tdTwMVrkfVsTLnPmU2ipq11HcsOTRHQMRC0dsz4A9VqPlcyjTPRY2Cjprzpu833SCcmJhB6qqkkqJngKuXUot5dTcRliyUKNKTbQEG+uxITHCzWrRq45Yum/Vmm4WkzEUIXe6EWIihLqDMmcEe/FtyykLCnih3ues7B8wAgxB3koQkelsEp8JbVeNTh6a5/Fa9KmZFddeFE2fuTuQcxfvRwNHBAZg5CCyUhIWcEc6MRsVDGGcTAsjVTdVMNchz0YlJwJ10XZ+nuXRDyn3POUEI4qrVVcnLy6tLLnp1cXVzcTN0z+4f9GH/mDJfb3f7/e3/+i//97fvpyRSCzt4e7GlbFqVac2OxabujU4aW370UWLQkqL6HY7Ct8e3x38oh4isAQwJkzilxQWQRoUAr4A6jJau9+6b7e74cOCcu02mBMdc9/jP/vk//i/+83/2Rz/9g01noMmp/vr+zb/6v//inda38yTD5ur6uZtMR//Nr7+6fzzmHtteupR3l7vPP//s+fPrUsa3799++es3t7ePj4dp3JtXJ04ltjbJZZoKCifb7uTyqrvc0XaL65tBOh+2m1/84q9T6utkX375m7u745BTLfM81f3+oRS8uNj4rHd3d7WOz18/v7je7Y8Hlrzfz7fvj0lQJ99tEgj7UV0fri741euuTG/v3/36k1cvdsPNpy/+4Mtf7f/H/+lfHPeHWuEFalB1Gy11USLQmEOcMouAFDrlTJSUklbT2Qpf+sUL5m313jaX+bMvPt9cD6VOh3nm8KQEFy/lhz/54k//+R/9+f/1s+M0dh1fXV/2Xa5TcTWqfP/2Hoof/N4Pcpa7433fZ8lcS4Viu9k+u3yWJX/+e9/Z7frMrLVq8Wg3JCSJkpC4ic82H4uqBkPHYGDPXR52g7mRkJ+RVcmJjcNbi3a5vEamwCKqRRUWChxPgu6mTn3i10QPODISSsJMztHZCUauMVQmgkBYmjALlq0HS8DVWvUufatX+tV6splFJtjdzTQSxk94xq2KX4hWlOx3mffFuVpVQmIhJQjFtsay1hNwosQkcBKwiHgy3+mzz7/+7o++M5rd7u33fvij/+gPXxLuhe8JxyF3t/eP2+HZ5fD88Fin8fDs2bPiKF5y78ejvX1/93h8fP7iZnc1HMfRp5o5b4ah73s3r1pSTjKlruuvnj1/+NVdP1wO/RXLhqljxsX1kAZTzLNa3iAPeeh7tzofat7is++/+OR7z0s9/u0vfr4/POxHLXjXZfz0pz/58quvtdKsXpXevzukw00dyVG2F+i64nhg1ouLHuZv30wdJ1h3fXEzXMpkj8Nlfv3dl5Lo/vFBcrq+vO7ykFOXc9/1fe6SdJCeeQBvsX3W33x2/eKLm+/9+PPv/ePPvvejz+WS3x3ffHn/q/syXl4Ol7sdGT+8H9X8+npzHMvd7f7u7v765ubZs+da63g8uhqqsUjXZytmMzabgSRdXl6mLhvb7nKj7m/fvTlMh67vW0FPNa1aSy3TNM+qxZmESNy4PM4oTDW0Vjg6LlBTfmamxCKSMoHJVt+HKaR11FslEFqakYgI5FZVtRXRNNgu0CEhYhhg5HPlKAxC00kNvWRyZ5BEqEWcJEmSBE4s0hKewhA3d20wDlEKOg85WCSnzCktNQHEjS9BQSgY+o7jUqFWg2iGFawgcZA5VH1p9h7kLA/hpAAZGtnT3bU2aksDloVIiIVjHVKj1Zu5q4oIN8+rhfzkDV3ic6/Lgy3CQJOfhiFxCsCHQ+DZGSCnBVpv+NhiIAjMYEa0A4EyWXO4Q8JIIyYxRHOmENBhJwIxYvASg+elY3hQeYjJCNWg7d4Hjkimrmo6FZ2rzqEv0u5aGEMIiIkTpyQhd0PugIFDAigQwtBOMYPVWls/EfPAT8Me+gLzucEXRRR3j47qAeykJ/y9M8MaGNZSPY5GMw26rbcnysxx4fUi63V8KfGwAHcXya42z0TKNK8fCTtKdCpL9Db2mHGNvmtN4hdrU8I1cbDAfZE0pxh24yxwy8EZIcV0alkZ9wqv7V2OFE7QjTzcGxIBp54yJBMSVStwLE0JmvwxEylA5goLqSZK0icx95SEhWo1M0spsSEUmonY3LT6VObgB0ZXLSwdeXVBTxvYa2pgcijIzUMZp2niBP9LwE4WxkgEcKoW+Fp0wwxD05LywcQSEHnwgeHOQVYgdgoRvrOHhdgymSVoWUJEWKado4KSMJs50UkXkBbFOWc3tyi6i6LIBT4OcNhQQUgU3BBidi9lDpWySKChKjOYUzN4RlbdpU1jRClh/KiTJts3HdSoYGaAE1mYq0CUm1nypwpuYWSXhRRFegSCEBs3bjcxgwyU0cgehoa1x69cVoS5Ls0znBGVCg6OjkQU6Y+Y7mBIG7C5R6NGg1UtZpXEo5FtZCIvbi6QeJqmeZotii0zu1YIlNxQyWUt3zTAvKornABL297IxmlfZgxd6rvtbhgudrvdZhCRYdPnnLqUhTAeHnyehciKlnHWue6Gyy4PcE6Uh7R59emLIfdMMj6ODHp7vCtlvr29Gw91tzkMfSeObdenJO7e5eHx4Xg8TFVcJJXZa5mOh8kdXR42w0USVq1TKVJ8TpXFmUlNS60wSqlDb7ljyZT7fnexgzFzb0j3d2Wa3VQdLJKISI1MUasdj9Pjw36eCwJZl1QNVGpn3e7i4uWreR7HWosFAQ4NH686F7VpnsG2veq3m+F2HDdDr9WYEhFP0+wu/ZDMaJqnaKwcE8gQIQHu7h+7y+s3798O2Hz3xfcrlZ/+8U9//u/e/Ks//5l0lJjd0eVOzbTJ5nlzTJ0W8m3QhKFqxBIko4agLl8WCUNEj4gozlO4mhX36jC4akWzNGDUYhQ6hCmBmShAZXNTrJa0pRs85A5FREFOzWiDYK1hPJbUh4h7g8GIPKogn+aLHGh9SVtdSmziizcPYhci4lZAYE1zvV0fhFDKY5LI6hkRlv06JHmDTtbYXPYkDRgG5pRtX4ME4oVMTwh7HMtxLdpfaknCXi/ZJDg7m6kvdmJJE1J4MpG3b7aPjMGuFkx0bwLFqMUh6kJKLghVQ8+pV/Ovvn53OI5O7M79sJPEquOxvHMcr296zLCBwIxqx3GSrCTRj3ItXPnmw1qa/xuY298e3x7/IR6+NoWgp6UB1N5dTzvxEpcXS63UddW9zDOx9Rugx4/+4Ae//4MvoDVa1xbWicxSZurd6qxK42Rm0zi766Kya32X+q7TOj/ejbcPt8d5BCFnEeGCqvUMP7eaLgfOtVo9jFMvuLgahm1KPTFIBEO/TUm0GgG5FVUzs/d9FpRMCcw5JCOoCnvKMh00mmgTMbHV6pJTYrhhf7g/PE5WxpxgNdQLcxJSl1evX48P79VLtPwuVuOeNeHqaPYnFpnKeT6mntMggBWGMijJcLnJfa5cD+VARFcvtim7Fa2o0qXhYgDpl29/hRl9R5u86UQ8cpyTP9w/MlP1Oo/leDwwA+LOkI6iWL6Uuep8sPeTjtNUSlEQmNF3fd8NCQnuZcbExmymxVwBhHB8QXFgJS7FJtIIFb70QDc7c/iWqUNN7OcbSkAWQnD7j2b0F9qFL4WA0RdsmWQNP/v3saMaZ+IMtzp3Sv2MlrIOZikUwDn/JOKD330snzv74dQ2Bm+O62msLZhoPbo9Ef4/9t6lZ5YkuRI7ZubuEZGZ3+u+6tlskgOOWtMDNsXhRloIGEEANSNIArTXbn6J/sb8hNlpo51EaKiRMJS0GBCCBJJDsqqruqvqPr5XZkaEu5lp4R6R+d1bTTS1kjgVqLqPvPlFeES4m5sdO3ZsHnF99fzx8RiuNy9fvtpdvfjml2/6RBIQGV2KXvB4OOS5M3eSyuAxJy+m6g6pOtIzKMbIdwWFMk9zbUkmQcRQoo95LHdAZDdmC4zoNh/nkR8yiTqX3Y1MR52nnDWXDADbfojCpUwG9ZbyBoFhfDxmoQjMzJI6vroa3nw9Qaq6CMxlHEE07bbdsLl4/qzokQ6Yp3LrUO9A/XwsD4c8IgBiF9cXEalPw7bfpJiEaLbxcbzb7x9r20QSqOnrN9/6rVHPHlSRJ59CRNd1ZFLICVDFcRqLGSUIGOLZitU2c8HRYi4hbolLm2vyTsjpsD+IiMOFeZ6nbF6yW9FmCJ1rCUtFLti9itm1KqnquS0ukAO12w5BvZiZM7Evk5FO04bWadn8G3il/Ri1xD98kWOufEQYOZH5ghNX/2rlqLW5TgTzpUiqgQmVIrX8oX7fQEStMk6trUJfQsqzmU+oWvoVATkt5AqvnUMf5rY0S1wqwE6o7ql4uEFHVisofVmRDsJ6ulZltIAhy4+eXK1znIQANDpS3Zngi8D0+cpsj7S9rhXaaPeyPJOzh9kAKDZ3Ieii9oiVutQYZ2ve+PRm1+HpSWaLYEbMqHIX3tB4+PIO3cwNvDQipMaOW07vS0rVF99Ymxo6oUrfnChpwEKNclpLCdbBPp2KAML5dFw/bfjJGWe1juUJhdWdmdfqxdOdPzG4aMVNZ9yuOrq83FoFowDU3MPKznUHc53nVmk7DU0jlFIWAMuX+/F1uYhI/WYl+VXtpPpGiVm1IoBG3tqjVj18dnZ3tbqwHKxNq7FirIEokGqu48ECH9R4qrY0BBuW8lIi1FLp+mDUXSoYZETUhI21Vu0sURQHocrpI1tyJ95SScWLKOBQh7BbW9S+sporwbMmiwoclQMBEITXbEwdjNbNTgLBoapwCIgCOa8FhHUaVR1Obw4fVbCsSbl5Db8qNAo31yol1yD6dYkugGO9R68/ZwvHm4ACMBRKrR8bgdFYX5WrDDI2Zq7iYMYwMnCAEABSQOG1CYdVy3W+MtEIFjXBsBQ/tyW8egOLxazz088AXBAcDeYiIyJyZmaupd8Vh68xbiuXWm7+3C6cFkybIKg1AixSY3mtVmIpBmpgY3OS2ooz0woYEoMrthA8ssc+7mTbTfFwOOwPY1FjzS5ABAVHAbFLZPEA0yrP41xtP4hgprNaYOs6HjbDxcV26HsRiTFKSF2MfUpJpIwjG11fXl5uL/quJ6c3370NEqDuqR+kf/HpyyDx4f7heBiHbjgcjswcJG22Xd8NDjZG6FKUEGJ48+7t69t3d4dH6WLaDTZOo43jvNe5pBCHvnfycS7TNBEbCbEgxFBKvn94nOcsInA29SpZEkIyQ+AgccPyjtiYyZxCiNzQDCulPD7uQ5BxHKdpNgBgDmaw1Kfdxe7q6vLWbZynXMBsHCimTkJw1/E43T7MRcvNs+uPbj66vfvr1MVpOkqMvfXH8UDku4uBiHMu5soECRBmYjI0WIiEX795vePL3/68e5wf/+APfv+7L47/8x/979w5EYqau1rxmj2um09Dl8AEZ1Q8p9qrqoaGmsyqxbHEtLS4NZAxAGI3U0VRVdWaeCmO6MTCotAKeEtgCSCCuqlTA6awysMTYGrFcwOm5aQNB2qbd/OWqLZOb0ZpQXD9tBCoYdYV4K4Z7Grkz8Amar5P86eaeh3VHqZcES7mWjgJrx04nKpkYBWON7Umq1fTTm3vW+AvW2QZ6bQl1Z10NQRtdSwM45N9eJo3aVbCGje87bZeydIObSrCMKqdm88yPUEqYn/ab6s9NWdyQCVEkL9+83bOhVlg2qUuxO7h4WHO4/X1xc/+g3/wr//7b+NFYMTis+e5UGus/DSA/xXtW344fjj+XTyobf58+kCLSUxqBVql9ICCn/x7P/npT38aAiJqg1bKc3b3lIJMNI6zeyFonkKeMoBNn4ZuI9y743g8Ho7Hh8c9AsDgQDGJmWlRiFMUdwd76AXBjcoxm2dcBUp9FLEUYwipZIsxTscpZxBjmqaYOASOsSPL7oW8MLkwkaOLqUvd491xnouDHQFsU3YJRkzzND/cTbuhpKgppRZhsBjK3ePDJ5//zjdfHYvnBIpJvJRa0MLsDDJmM7esFAgx5LkgRaEWo1AABeYYQgqAH8ZDCHHY9gRM+5EM3a7fXGxAuH13B8J2sxnC1iaMj8dpX8pYoDaVosXK9F0hj1FSjMziscq3J4OO08jB1RSgIKywgCBSa7TbPsPCMYbiplpOb9uslAlNbZsYECaYnILmxZxzo9XWMqAleDl3JdtPLEnGs0/OFFH/xpnXDPPT1MLC7zgFYqghxSnMbkn8Fl2dpjG1ptIL5tU++54GI796SICfaU4SWpBJlV5z9lVrqXtzMzUx4A7Pn73S/N0mdJurG1AIki62O3Du4tCnoWR9++bWbDtrrpw1YhLhEDkmsGIuAJTAIQAB5iiwAmOmmAI5e5l1Un3Y95stEwUiYYxQ81JUo/jV1fbZs2d/+n98CUUSutptw6VcbLddH3Me1a2ouVMMEJGi+vDwGFMCHpm877tNGF6nX0ZDIg4xzJnfvC5dJ+nTbrfrnr/yMpbU++GwQTpvJwAAIABJREFUv96+3F1cD5veMmwEIwpFBuVRNVseM00gCq5eZiWVIQ4pde425lFnzTlrmT0oRYQUQyLNtckdcWKYhRigZozI0QMK5owMdjAQ4Lwm8VBKKVqO+8hCnlXnolQkCCdY0VK0cjJaNQdqcAYYahhd02orT6RNAj53RPz0utusXRCu5uA0p2KJ6GpzweYQAlbznkvesoKhtPz0cooFNKi/1eDczcBsDjnFj8vXzuiKbUKuHtcpH/n+GmxY1CnSO0V2vjyF6nrV79hJXK89hKXe7zSUBSxeaxq9uuBN6cta1tV58XIrr+Ec8muP+nzM9P6Y37c6TuZNsWwBG6kGBv4EFadmz1p+dQ1jT+c/B7mfHufoeDNKTVW53nu9D2c0/kV12U2tAkP1qs2fxqntw3vv5On9PrGENT5nCNbE89m31mlzfjTq3cmxXqfOr3d8EKM/eQT1tdXsPa3l3DifhljqTGuE0G65Yl4NITC0Xl2LBNQZgHVm0E8A7HqFFoMpcCobs7o2QQ4UcvUKJjC41vdVkqDDPNR+lu6upORuXEvt3Z1Qi0nqjbYmKA3cMsvmBBYqYBDMjdhLLjA4Q7hSmdzhIUjN/lBo5L2KjzvBzcEV2GvvT7H0kgC5Lh2Fq6IUt67HTZrd60hrYqE+coaDGmusFj6KE2wucIcEAFWJGbW1IBHIlg53dWpXeRiDORGDfBVSdlICG6ySu1qd31NDY27UlvzTeaNNws3c1BTmzhRCsApiG1sVAYITqTMgRCIUjIyJyBWuZMZkRKsM1RpCn6Y8URUOYva1ecSS1KKWRziZyNM0ZrC3OJOr79vYJd406Sqpirgq29d5e7r6ulqJTndNrSkkLYS7WgZt1QxVvg05NdPokDqApsUQhSiIuTqBIk3zsd8Mu8vNLm8fHh7vbx9mLXWozgYGRwodByI3IkUVwizuqlTKTOQikFCrdDlEAZDnqXLnihN3/cVmZzfPN7G7vrl58fwmhUBOX33xTRc6L8oDylaFA7lYtmnKm+Fis9nttlu9sfGY3UXhbpCYhu3mYrv9n/7lv5x1nkxDn5IVZ1YpLhZYQgjCPOuc56JmLATTKpQ2jsc3725H49RFaFE4UMyMWUyLukeWKU8l1y6iEA5M6tZwyXnOqsXdpymP86yqu6sLYs5aiqoDIFcrXtXKRFKfYteVnA/Hac64vbsdhqvrZ1fxlyia51EvLkNKcTxSrromIhIkBhVBiImJWZqsXkydO/b7/XQ1Q/zh8f7jj3/8G59/Cq5ye9ACp2o1QCSV7l1JoZ69gVqNksW11BTVRlXU1gEIUSWDnjI+BDQkWG2dfkQsQYhMswIcKMDJTLEIVlbOUat0E6keChm8wN2UylkTvrYj1yqduvpQm0JVUhVT1auEuVQHBSeMaN29mNjJau6DCLwkq5f0BlrPC6G1kSZLk8l1RVlVEytgCRBUHcxSRUlPtmilXL3nDy3sqtNWcjrWGo3FtXHU/OVant4kVtawxBovrA6lvbjG23J3uMAJQgKi2AWOAoY2XpvXYkyAat5VQmQEM1Wai+Vp3gunjz9+8Y//8X/8z//bPyKCBNEYPReYVokx96V38Q8cqx+OH44nB8HbxustgGcUQ4A7QhdBxdSQcXl1cX1zMx3fKEzdDvPx4fGx5Bw2iZhKmd29iwlEZiyC6+vr3fZq/zDe3z3uD8d5mgEMQ6coFBiBEYECRCBQ1Q4xNkkkwlab5rE7zLT0u2Gz2RGEXB5u5zwjRYzHUQTDkITFJeQ8wrMwKowjTDGknA/zDOFgxkSxFJ2Ocwqej/Mx5JLj0IUUmCikOGTkh+lw97D/+7/zrBu+Rn7IWWGwDHeDIrBIYHOarbgWh2V2pKBwVTU4EvqB0yZQoNAlgk9zyXMhsJEr6agzCkdLBM5zefHs4mp7hcy37x4eb/fzPnfUp9jBQZUxI6DILJxSCiHU4qMyl2zzVnqWTsSEVNVYBcA8TWxcnScmcIxuplywOKbVWKPtO7QkJZxQE0MEakmEWj5ADudlR23TZU2LYkm6Yumf5YvYTE1fvh8/LxHKk4jnzCldTrl8+YxMgDW6rigBWgmLn3aZ04w+YVqry/m3WhDtHLRs4I2e4/CqMYYmrVp9YDe3Yllwj+uLm3kzbYfdPJavvv5idxW3/Y6DBQld6Esut3ezk8QAZ5grREKSzabbXRZXPk4lRGMpLIUS2ACBs1vLQVdZTkDRpa6MhVRBxKJdCF1Hqcfl1fblR88/+9GDoN/1V0PaHB/3D/f7h4c9D14nKkvoeY6xM+P7+32/3Yg8kJQY07DZXr1INgogoHgcy/3tA3xm37786DrEcH3dP38VhZ/16WrYPBdPD3d7ndwyT/uyv93v7493b+/v7x/m8YgZcCDiYrvZbrf9kDmQk3exSzF5NA9WJBfPavr4uO+7PsVuc9HFSFF6cEbxFBIHzNOUMUPajFOq4qMOoGiOIR0fDwDMas/DKiOkZkoKbzpxXrncVZTEl09cfSXS1NnYcqQN0GnREC3ZvVWADY3OQuu0dl9IdfAFCoZDqeLFZMS8OlVGpwl9vhywABONDEHsJ1GrFi/V4lm0dOOTJYPWhfB0ofeWxjmgce4KNZTIzohZZ/QadhivxZINv6kAFZZoGgs4502gBi2ItIW08cEV11+frr+nA/9eqbtaW7SwHxpUjaVn1wKot5byOFkBaupc3urgKlcMZ/mbp0d9XM1tbqAn6MzOwVuIKqs4RXtdy50tRSP4AIb7VUcQAeDm1fNnFyc3bWjdCvR9rycbRAS1tcRT7Ol9oGkxn8tzgZ8lB07P+Skx7wR2emNmrZKEHxra8/FVIEBEmNhXz57bi1ItFeU8XRTnz2oBVuEiwsLurmXpTbdeS4lspRAwuxDV2UcLNgZnN65MRUWxOAQALkxWX6A7kWvLyJBwRbKrfg07iUsN60KQWUs1RkEIIuZlbUnQbIIZ3CBCUrE3dQez135idf91cnWvQRwbkZO6c0OCyYFgIiZGxE6w4lz7FC7Fkda07xeh/NOkqG1RWdxX5jOxu/rCVajRcKW1VV03IrCgMZFglUK0BHOtNd/ppXi7Baxvqv5V2yduMDESGKGXviCzCZubOoq3Nq+CmpVjdzCEyBQoxMpkVfSAnCu4WC/T4tlzNPNkHVqse6Km4mRlsIKqizQ7mMlqYXCbRq069iwn8R44h5YWq5xQLOB983ZaUkKbS2LVIFBje7pXth5AjCqlZOwUELrIkUq2XCw77P7dJfJ2twspbK8HZ98f9uMhgyDJDZCEEEmI4MJqDrGaCzZ3Qkq06ULXxWFIRJbzNI8TAV0IOefAIv7xs+vrq+3F9ebi+vp6s9m4uxV9cf2KDOR0fXF5c/k8Z52Px7dvbvM8E4V+GFLfF/W50DzrcZrI7DjPaegK07uH+67vJURmUXUij5Lipkshupsr8pTnaWKRFGXKrq61Xd6cJ/XkQZjAIjHFLvWbIc9ScgGA+4fHnNkh4EiBzcmRifsQIpDdPcYYQ3w8zDnPXepin4zsOI3TPEmQru9oHusb5CAhBodLCilNv/z2Fy+fU+jpxc3Vu7f3ufg8z4TGZJ7nKRi5WwiIMUgQB9dsJUDF/P7hsWhWlMfjw/Xwwlljjxef4u4d8mgkZFqcYs3JgR1MzgpHybrkXZiZXRjsRqj1vhV3a/NsmdQLKlqBI7fqfdoyxZiEhYgNQc0AWFWUqu48yYKCUfP2ibgm28hbu+UFfPJaw0frNlEXOavN1Eo01nUGuEnjYPrJHpy5R+5uBnEs2bo1XAALS6iNC2q1IJpIfFtURkRGNfSg1sF6KUt8b6d5L0njjWkPeAXRfPlOW8BYke4nblBT3FzH+SHsVV0yIkDANQt3UvoyZ8AFjj4NiG4Co1ydATAcnIt6CN3Qq1qBQcthfCh5PB4PMfSXV9e//49+F0AuM1RADA61JJNW3KrmdIhOY/zh+OH4d/towG6zK9UX4rag3VKKc9EQ8PFPsN2m2kO02ERMD/eP7+5uj/Nh4ETs7sosm6F/JE6p225K3w8sYRzHx8f9OM0wyIa3F9sxT0Zq7CqGCE+ttQQEhWeJIfSBqbCYUZmzhWBDn3bbznLJBUIgQAJ09jxPfYopiREXnaKULiEmZvPZlAxl8lIQUprnOcbkhjwbK0wLGUeJXRBQBrjrt4fx8O133z2OiH13cXWx2d0e3s1FrTajZamK3eZVGT20PjxxtymezScIeIPd5cWw60ISicJMWW2cjzlr4hi6FKhk08fjQUIA6MXz50mGw7vjPOZ5yiiVA26aNQ6pTGNtpDXnLCEkScVL1lz3zTkXlsrDFV/76wDuagbT2gaDOSJZqhF47c6kWry2h6++PRFQC2AIVQ1jMfenmJqa3weg5rDfA7CefO9XQ0bnABaWOOW8lOn8azjDsLBGQ8uustA3ztIpy7a7Bmvn1/r1j/d+dhFwX36pWVStSiNNnwRwLQpG4ri7eekcv/jyl3/6b7742e//Rups0w8xRIGU2ecMFuoHImU1Y7IY03bXaQFz9/j4sNlICJjFnGvi0JXUFVayZZtzgQMMy/N8HJNH2jCLc0SIxKzmeZ6Ov/f7/9BLt+uvxdN3v/z2y/Ll41iOh4MTzC0NQSTBeZ717vbx2YvPY3gHHwnEQp98+nJ8LONEOfM4T7CAUg5jeTwc+74MFzFGvry8fHH5Y8GzN9/dvvvu7bu394+3x7ff3j2+OULJC5FTpKSsNin2OEzH+X7mRMN2c3lzASKHhRhqWF6m8ZDH0LMnpBRt6N3cVI1UYohddEIes7MhAbLk+M2reKUzbq6v3717N885spCZFjcyFIKDK7hq7loleAnqFcZqoYw1C/g0y27n4CgBTQjp3EMDuNF5lpLVGsafcnqL7wlzWosD2grjFpID72ELa9S0JgPP3C06C8qWkgQ6rThvUBFLA20+nP/LcnsKHNECXXn7r0V89ez1ZhcQCljWvQNVRPSkdwGrwjJo/9Rwn6plfsJO3hvSk9X3IRRSGT9PF2mVrwEDrQSnFewYWsv75rCr2YnU1T6uVuMMy/kbYe7GMrGliNLO6SDLI3W41Ne3DGRB/2iBGfHrOp0eU6q0l9oZkFo+AIQnDSu/17aF5d+eVD+uQoOnqVZ1RqyZywrNqlbt6Tax6pdNdb2UP731iqE0gaolL/4etEbLimgY1irP5jBrC6yo/U0vwNxRNfmXckI2rWFJbbWyauSbw4OAxRbxstpyC1qqWm9giYwqdecOWaZ306l3KBG7KkAUkgiL1bSFw6UiR87MIcY5FBgg5AJi9+Kq2qYSEaxAqo6agCv7DoA7kwsQsHahbFZBiZ3NvL4WBpFwXTykRMSkRkbwAKkTojVORQEcFkBFCWCWGvOYu0KZsGjuAEyWlwLLivNQrVKuWlOnhgjOZxW2QrUlYL2FWhN3erkN6lvXNjXE2uDsbtCiBsyU1UoVj2+xd50t2gSmTEFc/QfHpK4ONXJXMHPN/9kCQtVCT6Iam7PDjWT1Ivy0yhzuNVVxBmAZtLpCRAUNua7JjLpoaglh7SBR8wGOJqND3OSUGgXDvXFpGoblCncz5OwxAA5Xb9Dfsm7J3SDCMYViCrhEids+RME82XxkxrBNj9P9t/f3Q8DVzfXlzWa47PaPh3meur6HEgmTg8y5YWykRWWaaJo2Q9puht3FZtOnrpdhGAJknkpgZqd3r9/A7KPr59EpdZsh9X3q81ju7+6O++PNxbMy5+uL608+/vji4uLtt9893N7fPx5E+OFxf/X8edpsyuEQ+yQddtutZZW+y2r3j4erZ89ZyAkQJhZzY0OE9JsNoCmmKY9d17k4Mw7jcS5zN/TDbntxdfXt63stkQP13eZiF2+ur4XlOM73D0eH397D1SSYcw4pkTuTAhJjcse7d7eXl7vNZnOcxhBCTGkYhqzz/f3dNI0XV1dEeHiwUopaOcyTEkDGkbaX3S9/8fXhcXr54uOPP361fzxqKfv9nhldl2IKZnYcJ1WXABICUHIxNTYnyGE6PuwPL3dXox7/6su/+s1P/54j/+jHr/7wP/3D//GP/vjrL/acGE7a3MXGnHIonMpsXHvFBBYRisFFZy9wdQOkCTyIE4EU5ijkULC4uLvlojl7UbRiW/dgBmNhEXZHKaW5I3Xhu9esp3MtyltSoQxITVuseFMTgbQqgFkTV27e6pArR9FrhsyrOiNqPxAQEfNp467s2rUdrdriYDlchNxEQojCwrmUUjvoaG0hcdpbarLQWol0hevqFvjBBrEQQlGL4rlCSrY0qDptWeZVP/MsorAa71bbXOkcCPXGlwtVI+puCvdatAJqnVZsqdcwhi8eYOOqA84kZFBXGef5CPJL/u7N7f3j4brvjofHad4zU7HRMD2/+BSfYZvi3W0mj8TiViqWuZq0NRxabutvn5//4fjh+Dt18OLOq9egyImiMBMMaqUc9NVvb//r//I/+72f/QSuQl6KdrG7e3h4/fbNfr/v/BJwIhu67ubm6hd/df/i5tU2HY77/M1XX769fWQS5mAoIlWhChIk9MEi6WAQKUXdFIFMjCLHXigk4lnZi45p6LZD6Ltwb4UM5NZHXG668TgLKErsU3Qdo5SujxIldNFRyrHM02wKLaDE+9G2zExsBc4IoD52Q78NwQ/Ho3J80Q0P94eff/WVGojo1atX5Uf+Zf75PM0iCAhwlFyswEmZKXQCpmJm4uYG5rgNm4te+uSCuZTx4Q7u81ymwziPueu6Yeg3u+1hHO8eHhjc99tNxDjO+7v9dJgTUkjRM+neStYuda1/zVxm9RAkdOE4j9NxJAcnHud94MQc3FyLWlZCEA6qqrmYEzOLBzC5OC3Z7jLXPkKLS7fg+kxEQYgohFDzuqpqtOYqUEnHFdF5Iv9+drT8fTWwJ5/2/82xglBrPdAawDvO9YZAvA7mg/CpffDrjuM96KpBA1XVBMIAnMkZ5lbctUrIVzjTc3FcYZrKTb99fTj8xV/85XffPvz8r8Pldem6XYr9PBedSxJ0u35zmRSW8xyCUNBuky4QNt1u2EgIBJ8npdqtDBGU2HOeDhMZM3NKToGmw5jHEnYEL6VMIqUoKZwO/vAw/Om/+b+PR7B2pOF4t8cjsMXwIhKT1jyT0GOYXfThmH/8W78xTbZ/HEf2KdhHzz5/k2/3h/00zQaNFxGISuO37+5F5v2EecKL6/T3ftQFH7/64hd/8ed/+ctfHLEHxqazRiSRAyGo+ZBiv+21lGmajg/5+Pbu7Td3aRfCIPGC4yZ4rF0TRSBWoIZidphHzVYy+ugWjJ2UlRIPXQ91y2We1RVRpAsxSDQzFGODgCxDjAJI1Qww8+oF1gCD3NmoOnd1knptKLpEOK1pT4VmzhDcBQXBigmsSNY5zFohEraKsC0METcQXABbPME10GrJNJcz4HgdzNk6fTpTF6rA07m94Czk3gq2vmedvie09eSktUytYW4oBIYzLxbA19G2q1W96aXBw3r2E4RNqBVKbRmfvrYszGVRv7cOP+Bb4QMtZ2unqY+zJo4XZLtqSVHDU8yV7ITlVWyGA7Umhu2GtBadPHlSCCG05+oLqaPK8qwuccWzxBbFZiJwIBRiELGcsKDvpUtV/N3oSQm2A7XKDl5fZbs8NwHo9Sl9v10LK27VOlI8FbHGikw1U+oLexbLbAaAyqvypwKETy69onKr0XzyhbP7WR6WN1qitSFVgICezKrlxCeLv5zEzZXB7qjQFICTnB9Qm8U3zaGzPLq3cmAmcRfiSKF2IoCXpX/Cekc18mE0HTyp4squErg19MWyC9FSCShERAbXNR3fNkki4rV4hODCtZ0UwRCCLF88LQ0YMdibIB/IiB1kNZFhUFBlXxk7qdcGi2dGp6ZzWFrG3lAfGQkRSWPJFdITY87dBVR7pFFb5fWMTeiPzrBsaummCowTL++YTth/XXMAgEogrOQtAzBiWs7equgIJNwWn5WaS1PiqrNdxe2Z0Z7tkharZncxam1wa3HNOXGwHWaG9ePFLplabcdQl2zDp6rWGRrZq979yfzTmpqj01RdQXNUTbt1iDWAVhAgYCKHk6Ci6yEwCBRInOdSRKjrU+pS6GOnA5PfvBjubt8dHg7HAzbbY/f8svPE5KpRJFrtw6BmpeEMDi45m+dSsB2GzabfbYbddtju+iGllHqdPRBbKTpOKH5zcdlxzFmJAOHxYbx/83A8HOWms2IpdEO/6bthHOc55+1202+GmOKrTz/e7nbh/v54PHLonl1euftu2ESEwLK7vlItx+moOZMYiGxSi+hifzFc7DYbM40hTDoX5NqmE8T9kG5unn359a1QJiMGdtsds8SY5mzMktXrjlnV0wO4lInZCSQibvH+/na323YpDsNATKamczHXnOdSMrnHGIIEteJu43F0s9TFGAOID+Ok9ubZ9cvtdri42B7HOy9wRtzElEJK8XBUs2LuZsVBqlqKSqAeUkox027oFPr1N1+Fjp3Kb/z4s5/93k//9Z/8CWQfIjTXicXN5rFDXa3VCIPQWrLQAqwCVLtOey36q9CIYXHU3d2KmsLVWvdxrW6NOQwkAipojQcqbM1w92LuVkCdVdiFmuV0wGsv0UbLAlB1t5aF3KIDgDmgNl6iuumfyWcu38XitdOyBRMa7Nx0IQlELExw4Von07o21h4acDhXKjcBYPGliTlqgxtUZ7udbTlosUnnmwWsjotb+skXC4AFqK6bquNURF4dGVsZ2w0fXrY5MDGqql+tN3Q81QoGAHIqcwbYI7m3lsZmpDAtnkmP0/zd23eHx+nFdhuCPO7H7XYDn+b8SF353X843H4zHB6ORJSLCbGV7CJ1wMvufCrM/wG9+uH4O34Q1YzbKW/rHyILa31MdcsQJAEKslIUhK5LP/u9n37+2cd5Gs2yUzboOI6Hw76455zNjQghhk0/uD90cZhQ9o8Pb797RAFtmAObmsGL6VymPvYhSB8ADsXNptEUCCCBSe3rBmLALEYeusgM8jyOBzcCSkoIwiIemAJDmIJIHDhEi12SGMx8mmZXhbnUGq+WR2jF1zF0QWLgQGTzVGLUELp5yncP95c7OhyP/ZC6PrGIGpChKC3LywjMCABbtbtlPiIYpxC7ThIXK2U2d53zmOdSCorCMnKe1Hy73ShcC01qao/btJsf9fFuX+bcoQ8UaxBJJG7ETjX8BiGbbgiobWNhKSZMkUhqjFiKltnYi7JZUdcFlxKjJaxrei0rxlRj45UJz0tMjtU1pdbfY3FPa7uOAH4qebUcZ2GIn/3uy9aGDxCi5efOJWvOzudL3vpXmOmTv7y26AIan+X7wsW/4fgwGDxhWE3dGVhzVg5vBWx1V6nZW4Fr62Nz0MN+v9vu3r69lYAydT5QzmbFUoeuC0EqVigEN1N3jUlCkl5TiG5uQ0kI2QWcOHRkEA5gJwQWUHC+exwBSJRiuWjRGRI8diBiM7u+vPF8PB6KZ2dE3kISl0OGsBMVJoo8HQqo4FA083go+zsFJqb55ea3xgmPh/E4Tmoee0pJthuZJzIgT5hm5Dnd3z36qO/e3B7uJ2RwQHeZpoOiAJlKVrixY87leHcLgjD3qatKrfO+zLlEQyoxbVLqU4xpypOxlSmbGoxKAQxqOmtmV2NPfcfObmqRjaeSLabYpz5QuH19V4oysZnZ7CwkHCBVasfcQL70nDHAnRuPs8ZHuSW5iOhp1NzoWNWJWjKB5/Mzpog1pKnBlDot6lpLvrBxU4zBq5Dv4hv62dnOmDrr/D8RCvyM+0L8ZLpSZdkbqMbg64T9/pW1DAFnv68h6An8rXWQq5pTHTCd/1xbfA0nWJYialMgb1pM5ARTNDXnJ0djUGFhngFnMeN733zvPghgb+5x7Q3qq5mqb7I+TCYtmaRGqV4zx8zcRKyrQvUS/n9oMlYn+YTr1Re7IDeLzQEIahUtcCKSGq/SisKvDu4H7KQFZ1t/obOr1/lbnerz4bUb/L5HFUopK8iKFa46m9lVOagpvxkWMY/lOwuTaskSnM7QfsX3mmuwNEHcxq9a4cQ21LYNzDkTkYgYWa27B6FyB86WQ3sSLBJCaF0PQKqFhd0Fy2MHiJnb2uVW0+GAmnlRdlBoq4UYziRCIuyts706xBqNplL5hKW2JHczy1aq4FntSsnEIKpY5aQzChAAsuIEA0nr7E4MIrKl7GXhYRITsQjMXbXC520/bjIzgLoI154gFKQaiIrZ1Qi++jHSk/miPWytfpUXPNWLgoVEmNxaZNoYWA6YatXjW1yB+gTbumaQUdUN86otDaAZLYKILKthEVevwm+1XWbdD82YA5MsYGWddJ7nuV6IFv+zLmAwt2lRxV5qd1IlmDNIWETkkA+nzmELXlaRKXMVqdWYTgw8XcFEMD0HR9dJs7YUBOBeDIHqW4fU9n4OtPCUqHJnjRqiVzsYVCF4ZpGqsQZaEnZURa0a6seMEMnYK2zo5Jxoztb3HQnrQWMfu66LXQqciDmIbwYIXdisx/3Ud8lLGY+Tm19d7ESimbXKUQWR9CEGiQwuuZSpTHm/22y2m2E7dBebjWkZ+k7ZA3Pi7YvLm+DUS6dzGR+OljRJb7Oh0PXlsxR6SdwPQwypS/3zFy8vLi8B317snPD1L7+Z81fjPB6PY0r9t30fQ3j54tmnLz/ZDbtXn7w6HA7TN9P94RBTevb8ZQjKVKLzdrN5df2ii/F+fz/fTXCYmauZagjx6vpKgOk4WQH8are7fHh4PBwP01yK2n5/7CNMkAvFGPu+uzuOKUE4sEjRfH19c3FxKUySYl1jx/FI7JuuY7f9/T3HWqcWi+o4TmqaujhshmQI4b5k3N/fXd/cfPLZx4/3Y3Y9HGdzm+bx5csbx0SYpjKbuQiIGKTMHGIwoNv0IcUxT69/8e1YjlTCzfDyd37yW//+P/jJn335r5jJRcTYlo4B1X9NL3DNAAAgAElEQVQgr/qzRIEkCgcyWHEFatfftutzxdMXnMi9idYuMnlVyA1guLoVEBzk6urmjRFUC6cJAAmEWDkGq1p8ZuZWcRAWqlBzS6IYnMyXCu5K2GIRg9ZWFtUOmxEqJts2MDJzMyVZdOK5LhU3dxKiAFPzqoe1NPQtRb2Cg7WawWoXB6BBXW5VOK6ueCUsjZEVrafrmWzi+56Tu3OsvT1aUTwt4Uj1/Nb4B0uzV4eTVHttQULDxc7OStVIoKqmWnV5GjezXrK4QhU5hq7h7OZwIhF1nYtOwNt3D19+/fWbt/e/+fGrZ8+effPtF/0QipHqlHH4p//kv/jj/+H//OUv/iIGmUuWLtpobi5RqqB9jYgcS3b9iV90tnv+bXR/fzh+OP4/ePiC0S6Y+AlSPznTa+jekklrMtYB2243TodDp8+eXX72+SsORfMYO+aQHnArEnLRmNKcS54LgChht93N41fvXu+/+ebb/f2h6oNrVoWDSUJ02GxlK8LCAucQ3AtrLUw26aKhMEcRCSFCy3bori63MTAzDoc7t+Cu2yHm+QiHCMdIIuj6MAwh68Gpgt06TYcYNsMg/ZFLmaKQRIJbn+JmsIuLK5GciwX1w358/vxmM2wtP4zH48uXH/38y59L3mafu10c81ENgVhYYORkFYdXNXNAkIYQt32360IP45zLZKrEXszHGexIQRw2F3/cz8U0pBCiSEDibjvsptt3OStBzFCKala1EmPIU+HARuoMFhQtKaWpTCnH4zxqMTMjNXJSddOlu4daCpFDFRlp+WymqnVhMAgIUXKtRLM1kibATbVtn0SoLIBVjvfJjPp+SMnhTuRmLQp2Jyd1XW2puUWJWPYXNFZ1S82/h229tx+9N1HfB8K8yrJWp3zhDfx6x/nlfNEjOh/AKvhFXlupsKsxAhFMs2UlhitiF/I3evPsWYqzqoPCzbOL4/FRjdUQQqxefUppLqPup5LHLnVlLvNcSs4pbMfpkG2GEwtCHzaXwQGJtRqe+j5BkN3YW8veJGHOk5IyUVHPBcOG+76TINNR88HyvhACExe1Mk412kKKbhIp2nw8+ngEbGadKB9QVA8HPOse3353uL/bZ1jq0O9os6EuZmJzx7ynm6td4OHbrx+Ot3evv337+GBCSJKQxca8bPJEVb2JnYJU8jc5wYUBVvfJlTGbep5tDojAlsYyMSh0MVV3FJxLPsz7PFsvQ9cnm1XhJMwmTOi23WbYofg45RQZRmUyd0gIIUSJXsqczVrPmjU/XkdYS9CsqT4snJonPKEKxKzwxQeVrrCip4nqbqpsICM1c7jQSeEBZxhRm10nEMQdUHMmiJwwniZF16b1smrcAUiQWvG3tIOryc2T9vx7a+f8YDpThF8CzOXvKwzlsLYErBKoiFCb8awPhxpEU7EPN3B1u5nUtFJQmNnZyWp1An24LJcIu90pFgbX+4ctfJfmz7a/aQaAwMTERYvWOiiAGczUWiiWBmobHFQFVet14F7Z/QvCtA5v2Q3X0kUigizTw5vjSmhO/YrREFDDWhc396b3fgaB0VpgWm9l5UE1/LR5zd5i1BpqODn7wjbCml9YIKH3HlU4f+XfC3I9hbfaozhZ0gU5I6I6Aiwwljfm1IenBIAG3yzz28yJIMK16E/VVEspJrECaLyMBESoul2ohDP3SocjphhjjJGIcs5A65heSimlwMCBRZg5NJpC6+zRZFkU5kSRyRhmtlSghdrPT63AoaZuVaxKGFJDR2YyNSeYajUBAmaw8rLaa/O7DTUdcGEWCUFqmMrEgFUxGhIQk8NrtoscxCwslgtqHZu5V7ljsMNLKarKUUKIbrWnYY1aYe5q6o4oEQpUwjxzw6dAxbRogSMIgUhCIGGYoWn8weDQqkdscFc3BtGS+SEiI0JrnIpmOlZUyCEibT6gUSekEWEq5tXk8bgV2mHpNSaAWylrm8L66ttCMieqzRBAcHd1dVdAtelF1aV63iqz/l/Vk61KvfuvMBuoiMD5B08qkOT0MRrFbLGDQKUn1gUKR7Mgpx9Au5+6jp2rfam2g4UoRDBInBgxCgtRdA58nObYhavnl2CmnjgKgHE6FtOaKLm+fJZ2QyDSYt2mnw7Hh4cHBl9fXgxDV+Z5nIrlLBJDDEM3DMOmj4kAqL397tvLq4uUoup89+723es3/bC5vLj67NPPXj57sY09Zs3H/M3X3+TDvIkbVkrcXe2uL64uU98T0e7yot8Mw2Z49vK5lvLNt9/84rtvwPS//m9/Muc5duk4HkOIkSWG+OMf/cZPfufvv3r56vNPP3t3/26ax3Ecp2lKUTZdJ6zjdJjNX14/2+02/K3f3t+qQiBunufi6pthmwKOBwihi93Q9ePx+O7tbTEapzLOWhTMCIn7fiCiomBFKVqyznN+/uK6H3omyhWUIVKaRTwOF1HC7d071RxTZE6O0UfkueSca4HlxQXubnF3f391c/nRq1dvXr/96uffAFBVhs3z5A4WYoWIhBgAN4eajfN0PE6IuHt80P389u0vfv71F5/f/Naumz/7/JP//L/6w//uX/yrfGEVtgFLCIGY1c3cmCnDrGn9q7Vy9AWgqjOoKj8RQah1cK1Cao6qs6i06FFZYwya1ZOdbS+GAiUgCMUYWfqZmwlGLeaXllyo1r71kzBwJGJyNTAv7SbIjYjJrTEW130CzYmn5TZOu50vQLV05Oxa85IOc66L0K02J63RQk00OIFadw9zMhMRtKbEgAJChjNq8WKnVq/9yXEit75vGtbYuD1bkLtVoJGcWjWif3C2JYPpK3d4MR1uIHUnh1LqEwfxFWASESGdy5zLYc4PhR4fD5NmBw8yuPvd3bubZ8+HTcw4/pN/+p/81Z+//uP/5U9tUpRi4qELyFaDsZML2Pwx+vDW1nDrBwzrh+Pv5NGyoYtn+3SNtxgrlykFAYPF8Ro//d3fHDbBfQpcwErQympygrCQiJszhb4bdpvLv/zLv54f0+Ptfp7Nc5VIYaiHIMNm41Q2Q99tu37ocsnZjIlCkGzkXLpuGPMooO2QIoc8H5OEq4vds+tr5hQlGGToWSRO07R/PEahTR+HbZ+Lh17yOM2mmKFFVY0JfQpMU56KFTediHzYDNeXYXd16XY/TdmtHI82pI1IXGQScXd7+/j2dSrDy0+eD5t+2pf7d3d6MI7s7KqubhSx26Vh11+9+GTWPNuUbTTNiIgSimc4gqALKUiYkfM+W0RKAzPlMgaRq4uLacpFrcqdaCllUpsLu0BItRiUhhpgEDOratX0M8N0yKi4DZFpE3IFQQKnFKNEVS251HJ450ZLWnIjlKmgJQQJi6ZDKUW4NZPG6iQuFTOORmKx74lDcZo8S/O1NZDBGvucAU8tHltSIsAZV/dvPr4fPfu1jja5f7Vhd5xQP1TdGMI8FSYQpGZT3MiVSGOtO7OsHLg1Dga2m+3uMrG8PR5n99wNG7ODqjNzEOEQg8VxHJU8EB0eRzMAwYnVVT1nna2QwLLmjz65fthPOs7TPCKbBI4SxG22wqDUw4tPeXIGBelSGXpOKYFY1X759h7HWhNW1BgODgyCmbEyq9iMXDz0PBcrB6LSbdPFOM/HPH39xeuHh30phh79Bs9fpN1Ff3yYtBSmGKx7fvP54d30Z//Xvx0P8AkwdClG6ZwI+ehQtdb2C+YECDELg1CqahgTjN3UjzC1Mtt8zIXx+YtP3jy8Pu7nZK5FJbKEOO1zVY5SlNpxqJhKIA8SRbqhT0Nfiwti15VJzTUOfHm1k0SHPFptWq8r8YpYiJR9Ed/XdTo1aswyP0/o5SKd+aHMNzUAq5YGEVyo1qAs02zRjDm5S+fw2JMzna68Qkvn/3rCcJ0cLiK1Mm/xaloDx19nFVTOhFW826yahqpitKIn7Zpn0umrVwQsWnjLTS1gX0UKsUq9+lNPk38F9HHGJare2ffRO2m9FBGImeDqeR1ehUEY1Ag9dZ3aUvboaxFB9aHJpQHhYGcQdPnS8ribXZIowBObQwJnc/UKiIgQszyBvlhAxExayofu5Ye35evgmuFkEFS1oVcr0LQAREuA4r/KED7RwHoP6X9q+H7F4KipeLfLE7D0dvWlVpaXTeL8qDCEO5ZNpA2gHsxU0cAz7IwWX6RWLKJiOuudr/0S/Oyo/1SFTojJzNE0+AlOYKIAq0/QzUAW2NitOBhr5ORkTYapwlrE7IymZ04MsvZ+l0aH7Xl55UmAAWfuO2n5dzRxhFobUzsEKNydKzhubkXhLiAmCcTZqE3NihctFbKVPs0dBxFbETQ3wJiq82FNEW2pWmuPsdUlMbszMZM44GpurdYYDrihwN21ivO4K4iDMAcsUDq5oAqvgWtF3TpRz+ZV3cnXSv4zGPVsUiwbra9T1U9u54qZt6gXqG014EuNlS9eQtVkPZ9t7aVU16JJL38/i5sa5evcmC4oFVcb3WDkml9Z74GWEZ6f9vSz55dg5rVtZeWfMIwsROFIgLGg6yICJh+d3cW7IYQucAgX4aKYHY6P++Nhzrkay2cXdHmxubrYEhjEOk2BihvDzHOB2sWwGZ5tHETOKQ2bru9TJyByF/UuheO4f/vu9ePj3c+/vksDfvtHv/XZZ58x8bg/iBIpBZM+dJvQ9dJzF1MYhmHz5v7N82fPr6+vnz9/3qVYLN/e3v7FX/3ln/3bPw99GEvpL4bj8TjqtOuCsR3z/ue/+OJweCTHP/tv/lnoIogeHu/fvX37ox/9aOj7eX+v4zzuD/1u2MS+l24ISUsh88CRAFeDIcZ+lrHvwna7Tak7Ho/TOGntFSmRBOYoRXsATikCjuPx+PgA9zKN8/3dg5kextHhLEJe+o77EPqY+pic6fLy8jgfbV9yzGrQkud5dtDNzXWebvfH/X7/+OL5q4uLC07fJKNSZhhyzkRwY1WkjkVE1ZjYTA/H/O721rfdPVAOs+r8xVdffHT1qUSEgX/2j36G71A2Bp0RErNocRZr0mru4FohjEKtmg/UcN62Firrs3UGaJsRKk9TtVLw4BAEkBMZrDaQcF/4jMsOBkIVdmr/UftDM7nCXOsNK9lyBbLrJtTs/ZJl8kXccoXIznJfCxTk7zsuYFDHhUqBLjXXgJPWHqVZvaUqqjWrPVMNVr2I2jBpSQwZWTaXloVso3qqcHdmIk5/PPeoKoPpbHznHyyQ04foVRtGW/4tmmkCFMu/W+WFElEwVWOWKBQHsJlqlVF2wnGcj9Ms6ARRkQ+HPSjvdlsiY+hHHz/vBhZBmTICNM8SmGgF2hvIXgluy47p5/+EHzCsH47/vx2/VuR/+uZS7dt8yKbpuyx6c+IupnHcz+BhY9jjP/yP/mC3jcSFSM0nRXYYGCEGLmGeihq2/bZP/ThOX78+dLlMs8EAYeZALKY5hjhs+sfxPqYkQeCucznmKaQgRDHwTDFGYU5dL5F5PhwYliQO/RAkABRD4Nh1iUyNEEwlJWZ2JpNASv8Pe+/WK0t2nIl9EbFWZtZlX845fWM3h2xSFKXRhSPNGJiHASwYMGQYfhwDhv1DDPjRf8oP82LAfpFtDMcySUsjUaJ47cu57b1rV1VmrhURfoiVVXW6D2naMGDZ6CTR2GfvrEtmrhWXL774ApOFBKKXMpdZu6wiltgA9D2GjojRDV3qxAmTlnH2YBgQCYzqrLVg6EiLPTy+/vD25oP33rtfP1gRzunzTz9HUdQFc09Iax2u8pOn2/vHh8P9cXe8A9u2XxNzGWdfioslpk4I+pQYUrWWST3BjR72Dw9392WnMKTcuZFVS8SpSzpXACIchZqkvj/sTQ3sKaMqui41y+bkEmUQiDC3fjpGFDLYyBB8jpNLgkUkj4hsyRxE5mpsbdLuknece+TCm1q0ozeVGSNj55jTBiKHhWgk3uD5neWBTj+7+3mEVFPz+eJ6Pke4l9yV/1tHs+cX7/9G1L0cHLWv5URzY2OvMHIOKWpzVHcLhRvAWWsRIs5S3QGsNuthNavT4xHE5frpWnEYS5m1cnZ1zV3qlR8fd8M61erMIsJqrqZqCOjHHCa0WndztWOZpmnWCQNT33Upyb4cQ7jYYdM8ShqQpGmIqE/jXGcaEmydXZKOZocZelK4RE6deKfTPI/m5iBsh2c9P++kGKd1l4/7kVy7HnmFrockTUlJICmJ5dsn7+qUHl8djkdkggvU4UqlaD0qhGkRhSEsEqBQYnJnnSvAAk4sTuwoVuEOVcCxzpsxj4f5cLCJkyFx1ZIzw4miVOdA47QgJmYakZqZ1u31ZpVXBxynOm+222HdH8dxnEY4OZNkuBGcSAORTQHN2DkNXJbFxRJrOOxZNpsu10/8oGqA20k9ydu+IIISmrZEYA3Bv28x5Hk5nzCB+NeXp+1d5H/tVRw9ehfkpUXx6UuQwlKk/MIvzd6IeU5B71JgPIenFy8DItC8/P2yMWMzL5SLhlov7DAsswv5yyS2BcS4uKt23u+Xd7zZHKJAR5jIqETAHmKyLdEHgjjhhIXasdxtX8CpELMNouCJYentRraTAQAnZdgT+M5MEDZSVwXAIszibSfFY24rZZHE/z85mu5Sa4EMLVqYIsoSdFqizAjUBQuk8cbaPR8NwOILMt6lPT1DQW8zp8FooiVtIqIkKaWmq6UtfXJzM7XLBecANx1shAsJCCwoRe0cd2a4+WUPSPyp1kLUXkVMIsJwMJvZNE2qqqZMDWOKLwlmd5/nKZBidgrTI1nIUQMJTVBxJ7OEnIQTGqABZ27xSQoagrKp1Vqa4HCkUzllZpYQJVc4QKYAg0kcZEg5gDc1G+cDHMTcJeYG/wULjwiQ1noqZAQl16U52GDuUDhbYN4Na4oORHf1Kioswp3AQEalVjNAI9XV5MncqlYGdyycmFmIuZS5WPDUJBS3HNEi5DhBc6HLnJO3DRo6DwxccK/iITPNQYJbdkNicfg8z00GarFuy3xBszP8pzHpgVpVozGZnJydEK2cAKAcH0sNXQ4EUxaR5S8c0SB1siBftp0OSBsvcLZNOKNXIPZl6qBjwQMbmgwI+AsQ8FuMafv9GdpycjC7mnsI8bMkTn1Gsklp1Dmv0rAd7u7vh6EnoeN4fNg9zLMCkAROOD483q6G1ZDLrKr1qltdff2bq2Hd96tSaki5bzab1K+BxE695FXusyQh3PTrcTrMx4Oo315d569Tv14/fXpD5lrmq27Fioe7h17S5mq9GbbrfrNZSTGdXf/0n/2LZ+89u7m6edzff/8v/93/9D//xa8+/6RfrSadX33yanv7ZNrP4zx1OfXrfH11XWvRop/fff74sP9v/tv/+j/+sz//kz/5Zx+89+7f/s3fvPjs04cX9P7N9aZbPe53NhXKvB3Wt1c3s5aOU9d1fTfUUh/vH77+wdfneVytus1ms98/7nYPpRRI7vpNn1abjRwOVKY6jlNKsl5vynw8HA+Mull3pRaeXYS7rlPTuRTXCdUTLPf99WbLwqtVv1p1q9Vwd/fyYb+HGpmK+Ycfvk9IP/nxi7//yS9z7r71rW/f3j79qx/+zfNXd7HXN9stYzzMx2gLN3djEHiq1WIoHpyZN1dPf/CjH7x7/d7N+slme/tN+vjr/2k/362evzhs+3WZdDzsiJEHiPisnq/IQBDmLNKJMRymZMzurq5gRqghVHhgfFgITcfjEVOT+WQiSckJdTqaVTNI6omF4K4KWDQ1k6FOpfqYrnoIOmnGHOYO48ykYCaXtpNiNA5Rc+rkvBASW+tcw6WgOAUAS3ErykBmxhGRMMONMgoVI0ePxCKcoKRFTc1rhATkRGrmaimJYClruFtpkTsxFuzMKJ+LdUFffWvcBBdcwFdfVicgiqIDvI1Sximi+nWHUJDQmQiIvskFw3K0jMbUjmWCps2wlXV3nA5aynrVr/qhm+vu/uGzzz9//fjASIycUs9JDof985efPbtd3fbv/94//Z1//r1f/G8/+nGX+t2rfVVL4KXrM6jK4hr0kXOxEXGX8BV09dXx//PjzTTMl7helz8wXDmhX2XuKPczgD//T/6jZythnYjKPO0tqydz+LBZJTuMZc6pf/b0vb7vP/nFJyE2mjgxSySZROTMxOyOYnMyGcfjUXX/cJhVV7dr6VmI1x1n4ic3t6uO9/f3Lz+fvvYur1InzMf9wZ0Tp74bpml+fffg8M06r1adeylzdcHuiN04rfucharVefac/MnttfDq9lD7YcU5MRNRnWy83z3O8+Nq2HaZtGK93sJpHu24B9soSKu+r1xeH15//ur5u7fv/87vffP3//C7XcoixOLHsj/Oe8C6rv/Vp8+F+fp2023oOB0OhwMRutxJTsZ+2M2m2nerr733jpo97h+meVbzbpvd8e67784HLY/3bDnlVGsFOfXigpg+q6rOuFpv+nU3l9nNk6RudV1SmaYaVRVmocQpMxGFHmKZi8cwjcza2gZMNagoQTmOqm5L/gSpxecx87iRjyiEG5zA3iRTQHAzp5h6CJDHjKb2TwSHIBjEYG91+uYUTuWZS8vqbapQi/4u3MdSev9/YM37l8SA6M1v0ZZ+XHWbLW7mzk5QOIV8LpuJ10ikhYnZDVAm4aAXrSA5GyZVA0M67oZBNR+n4/3uwbkzWCa+WnWHh53V2neQJKoyjlNRrSYOz4bUsaldX2U4r3I69sdxd0iQvktTVXNoLbMiCRELWNwwzzDXUjQlME/jA8CakVmSiZGQZKrzJKnbDpshb/YHp8LH0ZFw1T8pj3b36V6Nu6F/KC+7jNUmrbbESadD9fpYCxLWzMNmffNXP/iHF5/eJU9kVMaCgsJQxOqKBREKASYOI/MYlW7V2WDmLm6hTU2IDEIA4Bd/96vutkMVtfnpk/fQ+f3+XvoUSjSNPgF3J3U2VauV6TBNZT5O17fXVtVHH7Z9vx3GaXq5vyPilKTnzg06q07aliIBIQ1McDcm2FvX2Bl4pVYLPGFcS9IUxKXW6dVIXmBaxD2pYb4EGEEYLmTnEOkcaVwCu785goq/Va1NTyI6sUKl6ksr+q2XNc9l0W0NzrzA3UwXqO0E5cgC9MaFgyPQRCvvurch17Ul26doFizCi4wGAJA0jdovD3/w882MYMytulvTQT5hiheSQWZGIkAMnVA1Vzvl44i81Kh9JahCWJiY2EgbIGXBxIqmSxAgRCZLBdaXJ0SwYpeQFjG12y4swmFDzvzXANOCc9w03X/Dk4wLggg5cTA4zKLVDOIhPvjGI2RiW8aC/4YjRSJy0uo+AVZfuu9vefFSt6AoMMCd6UyJOv1wWqyXrz3RUE8dgssjO9X2IUJmMPMYY7UUNqJjzN2bcFrLpURiMKLWCoASEXOAaPER7iFgBHeYOUOZSY0cBqGUMxKUqxOQIImESaM9kUFwCV1eNLtiqrBzl1jsEWYSZrjaIvdPsUsjXyEL1oM1uMYdbgontJTD22gtYSHhVuUpBgdZeBqPWS0AIREnMoqpLMXNDeoeopjOTExicK3Vzv0rZKrW5jm6N/k5wMl1oWUpbNH9jRk9jTbRVuhJVAVAUDGpOXCKrduMi8ccUXcWAItpOK2BhgThVAtd8qmTpNoXF9tiLhp/wrG0JRMh4H8ib1Nk37ZWF37fr98SzkyR2xIvrApyZgp1usizfVlwbbLAxcJ9owq3kGLevISFJ9MsRrtKCv2FapRJAK0FQt0woDAl7ob+MB6L1pw7jxmr2rygFrCDqulY5nGc59L3/TCshpTFKaW87Yeu6xzIksBZp2Kqzp6zDJI9JdeZDZ3kzXbTp5xW/e2Tm2dPn95sr8v9cT6UoeuTMlFiZy3ar7quWw3k4zTuHh8Px/3zF89/+sufT7WY22E6IHEe+vV2JTlhIqulWFEr1Yq5ORkJOhk+ffHJT392sx026816v3tUNXa63VxBnQehToh9f9zv9ruhX+dV4izFigM5p9Vws173BDw8PM5zYZa51n6glHOSnmg2xzyXWsvVdisiBBZO6816NWxSoq5PYCpafH9waCK1atxTzt2s5fC4315f502u81SrEktOuR86Nbt9cvXBB/ri5esXL58/uX1PhK42V89f3aHgeDx2XRIR4ab+ZmZEnBMxtMy1DjqVOcG366tPPvv07vFu1vmG8h3u/uxf/flf/A9/+eLlkZkR9N5izkBGZlhsKXawW9NKi/l3cAc16czYOc0cESFGqtoMFEeFGcSaOisTaYxFiG44IieLYrYwoKZqWl3cm8hfSARaBRETg82NaeFkVXdvfYVuMTyFQlbLTsalOeaT8GS0PTYvft46FB42sdnsCTklJmEjU1g1GDHE4YgBOUaE2JNGjctF7nrSNCEFhatNwfNtNfn2kV/a+wH5xY/tv/FWJ8rSaTAHEU5k4V9jSuCLqXD4UnVqPf9LqbNh48ykcDNVZWsDXGvVyppZUmZA5qnez483HW23V+BJdap1Ni8jHb773e/8/u9/8r98/6/7nJHAhIgZzxkLXfyvXelioy5Cycuq1VfHV8c/5uOt2+4tC5ea2TkhBcsLL8J0NyIep2OXmQA14ANwsrnOHSmTOkq0L5tVVZWUhsw6UVBld7sDJqgbnFgk5AvcnCQZfBzHlHKpsx4qqs0HBYCqJu6wDCH3xFLGsr8/kuPJ9qbjPI/FTFPquq5PWXa7ehxLzuiH9TBkSa00PGsqagpJ5O5Qg7t2ma83g9sRbOPx0eGpE/c6ay1aqrbM9J133oFTGatOGO1Yx84Nr+/vjtNxd9iVWbf9VeY+dXm97m9uVkZqrtUmnSuTqepUxnE6znUkQri90DzXauSpz6syeSmlS8N6valeq+rr3WOizkzBsFImdZ0tETtsLtUF5HAFBNvr7eZ6c/f69TzNbsTEQqmMRwgxczQYMjMTVbUaA8NZmAWt1fNswk8zrOP/DjQBltOCabLNYGlN8rqY6iVUq+28QKWWQHZZQktO8kb3xdmcfjGfomWx0qtn1xwAACAASURBVFtOjhOCWPFbswzfcvhSxzm//6+z7C1JdrOQFQvfxEzCyIj4AkRgjx6j1CchczWvWKN6nR53k06rDVbbTe5y5rX6/W6/29w87YaVVRXQesjVy7rvFDRN1R1VzZwhVN21qrvVUgku3OSgiYiJU/K+Z2WejxVEeejAUgFTaDhnA7N2Q2LKCYMRvILMsxBJyZw6zl6hxQlZXHWuqOn+1eHl632m7przdsW5x9X1cHXdm6jaVGcrk3XDsOpu7l483L+6Q6EuDyhUwG6VwMQpIRV3CnIUGYHJEUiCui6QSEsYW/E9wE+Fih1eH2VIw7rPkuCYp2rqXU7ETlKpkpvZqRypilJmFlWfpsPt9W2tlbOknJxs9sIiTU6UGA71ahaAS9TenYiMnJjdlE6rgk6rAGhzaUJwoP2NLo44s5FIlsV01mJpzH00TiKHiPmpdngZaWAhVDWR1jcLgQtT8rw1mhjFuSe3paRvDeK+/EsOe3CiL7SwdEkl2+W8Ld+kEzXn9PYtzlxiKyKikHJtcWVD+kh+Qyh1+lNLnM3BZ+gw0Jh2n82caGF2tftypjq1J9MeenRaRKsQMVGbNhmL8nS97TqFGzpHp+43JitvPtxgijCsPbXWQRXWs+kwwWM+HOE82vvXxcVEMW7bTxpNzS+3x+uXQPtlR+HpiXz5mae4X9Eu3lbGoml1Ap781wkZLh9gHo0PVBHaYueDiUMx5QtFgJSTmZ1WdhyXgXc8vsUVebtX5y3XALITAJdE4jpUzd2EQ2TKvTZxqHivLDEgpm0e0wLAM0sWzyi1gpwTcwrtSqvuYLCABQzSqlrVakjkMqVFCrRRmAE4MTFLayps8mnusGoK03hoKSUHAOXQIlZrypTkwkgcop/kala1Ne2EMYu5D3DOxCk5FXevtfqy48yUndxZzbQqSei2ExOHcwecmU3dSiV2Z0/JmSlRNjMCRa+SmQsnABHARSJmBisW+XHMBSRCo1RR+LvYFV7nOebFu3qIyBNzkoy2Zdue4sWmRG9nrDSrIfMV+DIap8Nc6RLygrdrNgIvwxUQO2OJExamxLKcYtDa2ygYAFqi7WeKlBMxJ8Z5eiVOP5z3wxvbbMHjlqDkjUAlTlgousSxNEyyqBVXhxAcdSrm2Gy3Qz+M05SHfLvugtg4z1NKwqQ555SSW/3gva89vbkahtU8zXMpOXVDP/RDfzgcj8cjQPuH4343FbwMRG27Gt59+rR/+ow3fUqdD5snt7erVf/02ZO7+5eW5eb6BoBWHceRK262T2hA4syUzZFzd339JK+7m6/dPh4f/+EffvKjH/3w7/7u7yTzsFntx/Hh4f76ydVhPmTupzrN06Hr+DAlrUoW3tG7If3q01+s++G7v/Odb33zG/cvXpfdjhziTO63Vzfci0K73A252wy9dKlAmbnvh3V/nXIehqw2PzzMIrTZrNac1tvb1G3W65WaGOZabDyWvp8SuMu8Xq+vrq6ePXu2P+yOx9FcQd51XUqMckjMicXN53GadTbHsO7XwwCCmiZmLbUCXdfdPtuqz7XYOO6Hfv3ue7f3j88Pj9M0HWoZWDglsMSkdgvdMWElVjDPRY/HY0fd58+P9/v73WF3tT3Uefwv//P/Yn9Xf/rLT+dpqtVy19c61Woi6FZ55BiGDLBHIOJEwuTu7K5uMGI+T5wNZmkiyZTGcHUG1yg1MxmIuDUhkzfP6yev8yZN10/xijsRL6hLw7OdNBTuoqSl6uamFabd0J/LKRHj4RweLRuNlspW4zsFxiJ9ogIyFmY2VnNXM3cBgTkoqK4uTAxiF2+gvFkUroIlSgDBQvfBjMGGRf6u0Z/9jKovhsJPHnLxNy39XcQcifjUdoeLwOtt7trN0KTIWtuyEZMQK9WQI4gbnnLqqJvJ53muB7NMnNI8zw9FKechSfXy4u7158+fX3/w/s3Nk4fd81rdzB8e7oen5Q//6Ds//qtPkZFTY+lKilGR7K6Lf4wn90Xn/wUM620h1xec9lfHV8c/7sNPJbZTWtJaCFsxvf1hkcIiMrObq5v73f3A+PY33v/4u7e3+Wq3+/nQkWSRxM4KeCl6//Cg4uvr7eNh2u32nWRTxwFFamKhxCxM5gojdoMdx+P6ti/jPI5zT0QGS0QEVZ29JOuFaB7naTfVCe9c48MPPnA63t/vVkMe+s0wdCKJCKsVDUPfDdINQuzzNB/Gw3D9DsbUsmNjd02SNut1Fuz3x/14ePl6Vx2rjfQ9p7SGdcwkkoYBT66f3b06HA+jO6A+jVOtNtYpdTSsu1cvH+7vH2DYrNZX11dT3ajXcTxUKyzMnGqtx+kwTpMTuj6JUBlLHec6Q48u7FB3q14VgFWK4bFd7g6H/apf5af5eD+O+xECyuJqtdZuk524aO26zCI5ZUR3eFFkV1VOiRDVcTUYsRNRnWsMH+qiPV5DTJqa06Km9qzR10AUolrsZBxMFL/0Z0yhvBJslSWP/q2BJGqLbamULKrtFy5vUb3g0+J86wr+v3BcvscyBOz0RmcdrhN8d5ldxmijc6Upgnk0xDDa2JvfIIE7UUqZJcFUvSgI+8PhYC8Ox33OqeuZkw/DupT9PNUs3Xaz3T8cUOnJzfbxeMj96vE4q87Bggm3XxVa1b1MPNdZp3Ha3R8PO1v32rE5SR7WkrB/fLR6yvs5S5JkKTkLwakbhLwTT+Zec4IqMYXY8TzPeiz7/Z6SpS7rvh4f54dXjxhRSB/vDx9+40b5sFrnftWb6eOx6kxeOdF6s77+dz/8UdelDoyJ3IWcHUQkwuLsjdQT1SxrAgogdwUMLMzMXg3EMcqSIn2L0EddD/X6+ko2cr9/PdqBuxSQRoRFZtCq3gK2gEUoJbbc7XYPdSpWjRxlnNRNEtWi7lBosEslJ6++PNpFEYItkKpWQb+EjVoYQK3rhryFKCcAiyLQ8tYx22QcqEFQUZ2nhuwGHuG8RJVYIsCWnC3AQjs7Qqzzcj4hQXE0dAKENjHMLjCuE5rzdpCWYtxa249t4FBjPNEiAtuMwcUbRCycJL7YKe/EBXp1Iv20sW9LWhiRoll5CwnDF7bNGQ7z0x9OwVi8swfNhZZOQTU6CZcRMTfFWabYp84x283MLVR0CEruTQ3XmzQ8XbBQzgug/SBgNOGPM0THZOautoBdfHHLFywU5F5Pr6CTLfliAEmmZsuapEVPDQC76SVyuUA9fvqktwSwAJC86e4vWQQR4OpLLR3ugDa9MiBwBrT7H33vYZhjLTAxs1wu0DCe8bX4tEYJIin4aKqn5Cse6ZvIwJJkMNFCF6NSastGDCDPOVFqfDN3AzuBwM7EKXF4vGUcPZpafIITjEAMkiSdOJupBfWJmZjFXau5OWKoIDvbrEE/DCCIBdHkFwJP1FYVE4gMHu11CzNOArHylqo1GS8L3pMLZeJaavR95JQ6ApWqpiGE7ABIwE7EoqpwJ1DinDqZ56pV2yQvgohYNYuyIFoHbCw9AI5G8gpUj1wdDbn1BkU1RqhTG3ECwJkIKYyWQ2Fhn4UC9iSKq20I99J1GAMPT1A7zIlIq7k7EoSi57ZJmbv7AkQDgMOaouDJXqAJ5tHyz7YuLFLRALlibJmf3gTmwXtq2WtFawd/g93Zlpxp9Ilf8rjM1ZYRYU4ANSpHMMdBgIXtUbWTB2sDT51PUlmxYjSk1QK4i3Yocld3SBb1WlTdTDoi4VJmh8PrXOZh1U3TeDgcDfXqetPlvLlaE/H9/cvNzY0RSzdsupXtHvth9c6776n564f96/3xxatX0zy9fLU7HoPriXc3q48//CfrnN95+nS/u5uO4/Xm+sP3P+AspZbDNOlU717cPT989t1vfGu2CYau67rUd93KnaTv16tudb297reffvarn/z9T/7+H/7+/rDr1p2TPYy7Q3nMs8DgXKvORmXGeCykc4VBi+0eHjfX3zgc5xevX75398672yd/9O3f/fu//dvXdzuidH37tKpmpJy71TA8ub1d36zvHu8ej4+Ad0nef+dDZi467naTm26v1kREklKXnOzdZ7cij0n4sB9ZMR0nJFkNqes6opRE3Gw8HObpKCltNmtiqDolslJBEBCKjo87K9Ow6q5XgwOHw+H+9YPKMKxXXcL1ttPqV2t79mx1WNPDbvU5JkkgqiDOwdu0yqQpSz8Q0dAJcSdmrjK/eHw4gj5/+dlhfih2eNzNf/ydP/yDf/qdn/3o59//tz/c3Fypk0G0GnW5CqEXpiZa6bRUSJSAGAJKDlhjsBocQpKQElLyBD27j5BJjImAeejMXWvDTEMNndsGchJJibWqc6A+LR2kYDC3Zgy46zL1j0hjyE14C3jxlg8060AEBrSVhWLLNWPSmiuD8GQAEaWc2ZksVPksetC9uSAnAhjO5EwKggVrkgAnJz/JfXgTSFy6eqg2kcYUqDE1l7XwPtMyBscXuYiI0JZJJPHWxMTCZrqcujRZ4xzShQltuRERlhIaaIlGmhCfw51Zcpe1ljrPlpC75AJKrlrHUEI0/vnLn/308yff/uCD7e17L17vpqKHgx/3r77+3rS9Gd55Hx++j3qoGGW4GorOBIcbi0e3+fLlHE1QDeRkUEIQxZaQAydH3b4sQE5vlKPaWV8Rtb46/t87LpffZQh+Asyjc9fJsVBW4xQATNbiHGKDEBHEVSgPPM728dc/+q/+9X92hcG6oRNVr1Odcu4NswNUic2ooB5LGTXnXucMgyQHedVCzkgMckpurkJ0td2M42HTDcw2zfPVbfIhiJzEQ9KqYLE9oeKD996PQcuH3ZQpyTXdXK0O4z510/oam41IZ8WPOWVyOdzXd1aruxevZvN+kwUb6IOpMHcpE7Ec53lSTBUm2q/UaBpWCWRwv97cdkjj4wxzBo4HBSVH7VdDP+RK83aNzFk8MXVe/f7+eJgOu/G+GCB4dr3SauaWU2ZhNzdjn2ncz15idIbVaV5ve9UiIlbqNI3X1zdDHkgp9d3usHucFOTdpofCZuVEWjVvc6n1+uo65Xz3+v5xd0g557XMZZ7KzCyn0qcjwDE0jgoc0ODYsjHcrLgr3BBVMYMxEYiJIyAPJGlJXmKZmNlcnYgTh6qWurouLVDN1vuyjr6Ql0UnVXyVkyOEamM9N2NKYqQnBUdqFZSThw2PeBpsdV7vp/V70cewJP+L/6EFBwBOErd0rkcxiATO5zKNA+6hzgJzspbLozok5H5DuiCDxMGqlrNAZrURSVMa6jwS08PudfGXz97xvt+v+iuhrpYn0+j1mG8314e7/TRNt+vrJ8M7j/sjeRJ2eJVM5Dyb66zKzhig3bjbH/Z1GqnMmDxPuRN0xqSoELLJqhVmN1Nm73KXOnE3U0tdsqJmxRhqY9cPdSoQIUlHHefHo5GysZl//O1v/vInv8yaMaETLpgI16t8JZynYzHSadTHh+P18A6jF+8fj/VpP6Se7+4ONorVmkSYDDon5kI1bn2bXRZrs3Xfwd3NnQih3Ml+Lr+bAQfUwcbd1HG6vb796c93/ROqpfR9r12nqsxsalIkeVb14sVqRZLtZvX6k9cAoK0dFT1yzn3qBaTq1UokGMRMygSmRY6UILV1T9PZLi5GlbxJ9PpCU3QEAeeM5zqTu8RU6wC33JyEFry4yYrToi+Exv471Q3Pn0nEQjBTd4gkokC6lzaDyKa9TR5sXDS04XruywjZhXBPLW91PzGrHHBPwmjkISzNRCen4Quw1p5e2yweLCdfftlQD4smhoZRGILy6WiqRwv5JiCiE1b2hpVwuFn05BHDVH3Z1QvWAgBuMciQwIvZIeKUop8N5KGLdbHb/STFx8ghqL3YFAHZ6eJNLbRlnf2EMQV/xN0zJzpfbkTHrNUW9kzAPSHucwJUmo3hYB9jsa/NuDEc1HSAmj9WeKJEDeRkd0hikEmjETcxJXvT0f+6kDNmpavZwtPhNsLwTTw0wnpcvp8DOScWJiIzWvDEQJXaR3+hQE0L9SR4ee4wc1V1x6Lj/qUvSMQnFHiBD2Ah3rW0wTBHE5aGjCN5lMpjxgYznQr9IZnGTJDYIUSJmAkcQvsmOTUqMtjIwp2JCIFg0FqJOXGTF2MRktA6AMUjbH6E3ZyNYty7uxuppE7JOAaEEdGyskwN7szMkERuIIDdyBYRsQUXA9B0na06qXFIqFGCVz/3oDag2oPqxWJeT4pLxJS4AU4QArkQmImJ6lKJQXj5mP/SnF3rpqFFdSuKBOYugZnBmkZl4FXu7i4uQrxsEo6OQq01WMrCROwJxBaLWCk2DJHFjAmcJgK2AKB1FPtiGM4NxtHnGGbAmOlMJvEwI21TcoOVHJFmL6jqEmFwMEreWH7uDuPI8bwxX1t9YCmkBSJtVV3iSRLQjD4t4VWoBxqQjIjImRxoC4BRS8ldFpaiVuFd33HGPM/jsZJge1PU5OHh7vXdYVjh9unNk2c3777/bs75/m6rLsfjVG1PwMP9w+1tvql4PBxf7Q6vdo/P73YkQtJjmNnZTae5HA6H4ziWMu8fxzIe1usVkxwP83533O33x8fjahimw3Hze9+jqRFuzV2SiCTOmYWYcL+7+/nPfv7zn/2s1Hrz7LbYvBsfCxXuxcSGPqcEVZ3qPKkkJbj3qe+77EwFtrpeU8d3d3c/1Z/96Xd+/+n1kxevXhyO45N3n406ZkKSdHNzLT0Xrv1D3hxWh3EP4qv1RlXn+aC1SMLVZm0c0k9a1TbrXqsK2GpVLWU0eIV3DjK14+GopVpRnYvXajkhS5e7nLJWNdfEcn11Bfhcp3G/39J2vRlk6LWWn3zy6rpu+65LbP3AfaerXgX0wXtb4Xm3H4mKGwmB4cYlZU8ZksEiImxEzPCUH8dHlXS3vzvs78u8Px6P++397/3Ot3/xh599/9/+sNYpdUNxghBWXeWqSQM7aa7fHEDM8HUHIBGZhEsNB8qU2IVdYGAXb6K0QTx0IZGc2L2Woj5LyPrBwxYt/RSstUK4DSo2a2z08Fi8sKfI2YhcPPSeGnADmPMCRgfwRjCQRm9/YFiXJaBWjSUGoKbRqQhEVqERr1uMWlmyB/ek4d69helCoTy7GLtF4ImdyAkWVpCI2d0AbrG8RZuEiZOesLowO4szWnhYZ2OE5sFPNqhZmPD7LT5it8s8pHG8loCk1RdQq3mQcM3hChcE3VUQNcxC9unu0+e7j44+e+qL96paVIR0d/zkdlXffZe+98cf/eD7zyEgEjVvMSgvvHYg8vpljCucjGB+4ZlPl7mYVG7PyLnBpl8dXx3/OI7L8vBlrb4Vk04IbfzuzUb+pf4cqrbiJKA6lpqIyhrbzep7v/8HE8ZEDFJzVzjDJisOH3JnroeHx3F3kH5t0P1jQYJIMjK1YmA2NvHM7OQuZFC1qetW0ktn6G9TTajuSVl6QaHxMI5lvNl26/WqWGGvUCInNyVW56lb1UxYbTDXOh4nTxsWoQ5C5lasDlCGd15Qjrrfj2Z0nOthqiFlTgxOMJ9ylzJDiIZ+C+fpUOaxmGKeNckg4v26YwGxbq+ko1xHWIUppqns51o85YFW6+7hcR+UhS5nIrGqWq2M1WfAl/FnDtNpLIcV8mq9XfUDg4/3+8S9os7jVHxGgkJNK2cCoGqJPHV5tV7Bfff4OJay7TJlgsIICXTSwL0AbZqxrmbsxIAYeXUurgFggTz8EygEMZrfiSrySbjGHAT14kTMHS+1ktrUaKIRHI2l0pLOk5+JZeXGYG9zQpa1t3yat3Xb6rvLuvQWTV+sT5wW8+WvF7dE50wuTji1MJ5OPL1syQjQJHIlHGlLjcgbBY2Nzcy1KSh7hZGGszITcSZOZHEL3d2rT0zG/RqK9Wo9P+5Xm/170r26u8+80UL1mOvs086zi5CbjtM4rLcdEQtLEs+dJ+TJyOaqzIKcpGfN9ejj0bUmgAwr9R6Uqs/qSjl7P0tPzF7n+TRTSRWl6LAaVItrqeaqk0lfyRMJJSllqjZzL2a6kv7Zsyf7+33iLuZTAb7fzdf9xgzH8Zh70Yr9Ee9uN0PezKNuEzKBjKBK6r2wMGstVkEsYCUn0ghNGlXh5C1DXKUFO3AjOT3faNspkz683m3T+p2vP0NCEohw16WSq03kDlOTwqJk7FCvXHpjFgGQwWBScsuW16mTnDyxsVX1aqYWfAQGUTQ4KtyI3pRdu1x1YVSXtRxollsrty8ZFRPZ0iSIhlG4hIA746S8dsEzWoKec1x1sWcirKKLSQIX9bPIN1tSuIzfgTXwxZtC+tKzBpw3R0yTWFDatitahw69+T1On0khud6QiaYTdkpAAxSz0M52Cbr/0lNgDmuoHQFwboJWX/iYi03sJ5Qv7hGfLvn03+WSiABzc2InBsXUiAUo9/OXJG9pMHR5ngRmtmbLoufp/CgC3Tu3xTngkOV7NiDGgogXLJc4P2SxiAFTWmTMdUEeogk5vrZ5U/KilrI7B4BOy/VGcErmxOLNJgdY4PrrEasvHCneCI7g2WowufyNu9/oW8syixQd7l3fxe1W1dZEYm6qIBCDqclahyG/3DkEqAX9SpfH8LZv13bC5fdY3FYQM4Px1YSlNKBQSZmIzCyIY8QsFF+s3e+m68+AEEsiwqwzcUjeAu6kiKa5lFPoXmkc1VIWFk4pEZGIUOLY+7owmXxZ76bxqU3zDjm1+Iq58fBO22vp2UwpObED0zT5cphp3w8BY4W8DhFVqqDgg1r0KEIdKXSYobF+oXBvUvcUXAiCAO5kiGGvTXaSmRrpAKd9Q8z2ZjdoQIwWChIGDsVmIfeWjUkDamDmOaV29a7Nc5uquaQG3cGJWNzcgwrWsCUAHDwFp5YE64mq2L6jLJboizQqd9YaD32xad4sQDvFIpdegiFuxCqKQQ8x+PISOacgrBGANrPtwmq0vM8Xy3TahadFGlQvWoKJIP0RKObXXLQwNcBdwILE0vWpuI77GlAtRYtUQlU83N8DqF4B3L+6zyb3d6+KohTUIz58fzOO42q72e/3L1+8fHiY1lcJmRIJqtUZh1JfvX79s1/8wkr5+tc+IldJeZrKbvcwTgWAmZfZMnerYc1blP1MRIkl1ienBJCq/eVf/+UP/+oHP/3VT/vN+tmTm0M57sseRH3Xd0PvZNVqhRWrXGYGkkmf+zz029xNc7m9uQXzZy+ePzx/9Ycff+ujjz5wUhBpmXIiAWdJUPdq0tGz26e3T24Px+P+OAqlcZ6nsQC83Vz3fT+Wab9/nIqai5l3/TBUDMOaKM8yuisxmdk8z7vdI5H1fU9Qd2XmvutWfZeTHA77x+NxvV5dXV+Z6f1DGaeJCFfb7ZPb6+vbm7/96d10PFAtwtytVplR5ykxf/TR15698+5f/vAH0zSVYizghMyJnSmB2JxcUvZqIUE6TkTVXr9+tX/Yl3Guc/ns+S//+Z9+b7qv/+Z//Dcv/2HvK4djPazTOoddcIJxiE96U1ZrdejGmY2SQ1uECzrk4XKDFykRxwtiUhazmZFwG08TQzFr+GKA0bY9n4YrOGK8M71hxc1CzbLxHrF0wmMxs+Gjg8JEy4ynFg+1THKBubAEUOoBexOxoRGwlt3ddgu1d6NAgH2pWgeKH6VpVzSuVVR/iNFkONsdi11KvDA2lpDjy/SiU5K8lO+IiIPM/oZX8+Xu+wU09JsOItDxeMxDEuFKDK2uiYVEkJmGLBtONo/PX372cH8/4ZjRRTEFsNzJ/d3LVV5/93e/8R/+2b/63//X/25zNc/z3KwmB5/NY6DAcosdZMRt4Sx3M1DALwmOfnV8dfx/6jA4sZ19cLMzp5q7O4V4L5b/tFyTieqsf/q9j3/3u7/zra99vNt9vupg7gpjTtXtOE3qzl1HOv/qZz9/cf/w7J2rnPD8+QseQj0i0jA3LXB4StRBBLUq58S9DKuce86brojDijt1XYL6Z58/fnh19dE/eZJzJvJ5GvvsnFF13h8eDHW1ziwdhKb9cX+oLPX2ZvvRhx/N8+wIqVMWcQJKrfv9QZUOh3GetVb0a+l7N7W5OkuSnHIatuuNI7189fDZ53e1gAksOXVCnFU1Sd5srpPLfT2OU9Fix6lOZYQYDV3KqVQIyNhVYVrKWEoBKuBIzFWNSPquv7na3N7eHA/HxF3f90T80ddu//1f/9iqAnj27q079vtjhXYpYwARSUpjmY7TaKPN8yji6uqzq1lKiSsI4gbX4A2FeyKckqug15txKxu3dM0vw7JWm3ACifBpbJc77NSpo9oKzMQM0otRYm/Y+1PSfV5RLXeLSq67h8ZGVM1bfOtLWnfhU96KKbz9WJzTl53U5RFDQ/Cmt27Mm5MTbZI2C+gQUF9rzSCFEWqQESRaKeAad9/ZTQ0V99hcreqvStd11/3q+asXajpN9XE3acX9/f32xtfrbh7L4/5OMq/77G7qlPJQjP2oWmHMDs4k7l5KPY4zk6Qkfd+lLKaqVqoWScA69UOnrlYdZOoGQ61lLvOqW+lcy6w2OWaQOTsJJXa2Ev1uBNPt5urJk6e713eolki0qs142O2vn23ccTjub/qbyJS22+1qtf30p5+wZ5ZUxgogpSQxgk2tVIO0MOyN9PQt2MiXfgTcfehX43FfFN371197573P7381bDon0qoMz5wScQmaAPlJDUtVC2aMZI2vDlIqXilTdBGWUkpRK8rGpCLurA6jYOsb9EuQ6W9abTihrovoZ/RCxhrjiOtc3vbK8zI7gyZfOKcxrQCQu0VOHNLdXz65IWhv3sbT8n7LJroAxN5I2X79sSBHgbH8xj153oVt/jVOpRT6DTu65ZG0RKsA6LIj4eKKcBGmCkkQT9uwI5ITNuC+dHpGhyBxrd4oVQwKZSNpWBua1iwAMg20FQsS7lhITw1ia/G4OnjJUxMinXXACWZwW5r1XETcKl3cP48+EXcPaW93MmNpd9bNTd1UocaZvXEYHcGk+y1XaHynLz6XN4z95f0P+5w27wAAIABJREFUwIhoqcXXWoMcpDHEIrxDkz5qU8KBkwZZC/DjPHU9V1R+3fJqbJ4FFD6RBZfXRJtxAFtmBm3WipquljFLEtbwbmdMEx59kQ4NVDGE0whuVrUivjV7zpmaMLxqNShi8u65/TWwYLP4dAcoiD6t1WYhNVRYV0AewxAFtDCOlt1lTgxmBktVLbXAlgLKwqI8KdYDIFBVQwPjiCR5o2XEYl2Y1vA+57ZQA1Q1g5003ReuwXmwBBZ55wVGXp4EnTBhM2Z2h1WjyInJ4EbMcRWNOQG2wDWtLoAzJaYkiZhMq5oFHHahSBXEv/Dx5zV4+vILYnQBtfkShHgjPdW50PJwqCnPhVZaNAYuUN6CRp9KtNZ6hE/+vBlNeiOCQTPOROd/Au7OHS84IRr775THXkRQjqUPMQQZ3N0huVNTVpMsIhyAZ9fnYZtrLYfDWNW6Pj+RTSml2uzmq364vr7+4J33f/j9H5VJpph4rTDjaarS1Vp1HGsWGrpc1BnFmbsEMXf3Mpf9/ni13erQE2Gcp+M4uWG12qaU2JEcAHWp44yExCxmrmpIpqrV6r//8d/sx8P6aiN9Nqhk7tfDUY85C8RrKWRwt67r+mHoUyYjzgnsUAOZkU82i2od7WG/++DZex9/8xu73b1kMUKdS63zdBzn46gFecipz+uembrjYSxzYdCqH6TDcdrvHh8fdg9T8S6vJPUdfKTSd33freuwnucxCeCYphle1+t+vRlWg6jVruv6Lq+GgeBd16+sCkuZJtVKoKurq9ubm+1mA3IQf+P9rZHUOpMZapn2jzbN/Wq9vb7dbjbb1WqeDnPxrgPEWFBrVQOpu/F6WBWrXUqSUq3UMe4fXrPlRKJlVpqHnL75ja//iz/5k//+F39RMKlXyWsSVgO3Hlm0di9gcZcgJsFCLz1bxYsCRNvQnETAJJTczRdQfdlypw7ypTDELClVKm0xL/FEW+2Lj43PUQNgZM1FhkbjsuL9wtyegpU3nPQXj+ViOOYIGkF9GToT37aZEnC8Z/N5cFDg3ss0dyfj6O42b8h3VNfMHZDmZwMGJ3KOjomTG7rwR3Tpfc7EMUPAhixRkXuDD/L2kO3yQh3xRGutbCxJhCRKOilzl3qBcaL1ZmUjlXI8TGPR0nfrYbPSOqdEXZeqzWPZXz/74OOPP7q6yZ99/liUE+cWEYKjEfuM7kWeEjzX1ifdEpj4vZ+KqKfv+RX96qvjH/3h4cUvsGTEfqSTDVry2JOGb5zFDhigdcIf/8Ef/ct/+R+wsEOJhaQbj4djnaTrjNiY5lqO8/Ti9d2h1Pe6gYTvH44xuxTmzDHDho1NXd3QcepXw9P+XUBzpsxc2RXF2Yac+j69fnWHgqfXT25vb832RJkZxEpc5mLHsk+JueOqWqd6PJa5ACSrzdX2avOTn/8YgAjlPgnnYUjEorWOk9Za3djMEvecrOhYiwNiBjMMw5WavH55+OyzV1pB1HHquZZ5rklckginMvtc6vFxKpWLN3GSeZ4fd9Z37DHfzDmagMCuUKuu3Ho0VF2Lr/Jwt3/45O6lCG6ubj/82tf7vj+UPYFyl1PKkkSrwoxJOPE8V9Lx/vE14E4snKJorGZuJJY8xtdE55Q1LX5vMtdwVxhqaDt40K9aWMiXdcVWMQk/0iCHVnIIT+Iec59aUqDhcN/is5YMvEWaSyrYHAa1dpYTeoUFw4rg8gt1kfNHnB3slz/x4nNPweeXz6AFwLr4qliKvi1gbtLWl5/eMKxMJARzUriRMKjEFZo5zInF3MwVhqur/vrm+vB4Z4p3nr1XS52m8XF/YPDj4+Oz929un1x7pecv71yn1MnQQY2J4dWFjDxwGVItSKqloADJJKecSRJMzb3OOpEWJi42q5sTjFxhEWozMB7HMhat8OrQkAGylFPi5NUAsuqoGLrhanv1q5//Qi0G6hG8alVzS8SJuyx9Eb/uB6E0H+qnv3w5H0pGrsWSpIQUDUNajRw55zLVqKE1zHAppP02x/KwkTltN5un17fDtq+qn3/+fDqOm3yb0FUpllhYhKQG88l81vm9D5+ghpWphUplhfo0zl7dqkM1WOdurqZQhlk0qeDXYCtvKdohYr32V1q0mU60vsiZgQZvXAZOl8HPArX4W2/MJdZzuZsAfPn8MzpxQprefKvTO/hS5z3n12+J6750wb8FaPKF9yI670ksOeUJtcBbNjWIF1n7hU6zZJrnc/QN4kgEae1d2rjD6CU8p6MRw7mBzIy8jRsLPTsyt0hszRb2XBBNPCDIuJTz/QMiNnZbeBcnplbE0W3bWiOfNWHt1sBAADVN+gW9QXsSbbQmt6FProZqMJgYqi2DAE8w5W8FYqXzXbpIMNrMvrPlbX+9nBgYOaFwu0WhV0itf/zilQZKi+dYnr0DIb4Y0tTu0Uj4lt0V1vYEY9Al9EKxHhju6g1/OSUhF/uBSbVxexKCkaRt9IY5qSTOQ4qHVEttHiYRN7Ktq2qUHMCwNoOzEQo46j0aOsJOIOaGZJKzhaMNJZqqrSvOrC5LQZbZWGwOsJ+8SjvBwUTMIT5Xaz1heWZu7hotS0nI2czAFPwKs+hGJrgxCWAwN3czg56E8U+AMBBWuN0xX5Zf9Ky2J9Yw3oBm2qMxjcnBbg4j98bvMreqp0x5iRhADJHEcReMyGHupmfj5k1HwKnJqLV13L7PeZ/GD+Tm7gaL4fbLdU1wcg9COYMjNY0bQuDoBiSA2aKfupUAzm+PuCkxdNK9IQengOEURJyal90JSDmdVoU5SN0JjYFLp9gGQVeJvRREV7il1E1ajDz/H+y9S7MlSZImpA8zdz+v+4gbEZkZUZWZXV2v7qrqpzQjLQwDwsjIIMxmQIQNAj8BERYg/AlW7BD4IzAiM8KwoGHBAD3dXd1F13RVZ2ZkxuO+zsPdzUxVWai5n3MjI6tKmk0t0iQz4sa55/jxh5ma6qeffoqBEbVoGkvDzaJbiIRhGBHx8upRbMLQ97t+27RNYO7auOhWN7tDKIEMgUwZDKgfxtBEMyjJuCEklCHlJEzUNiECrhaLi7Ozp0+etG2LbSsi99vdze1dLmUBmIa8arsQmjzkxmi1WkMxAzQxJcNi2XLp9cWrz7rN8tHTR0nyUAYlCw2HljEQB3YfFdCQcbFcNhSgWMMNEysUspK1aCmb2EGWN3fXjy8u33vymMhSydnKYejHPF6cXazP1zfbOzGRZGZAhnkURF50KwoL4/L65vX9/TanLAIWjIkUrRQ1hW7RrZbLcYimhRhSGlShaXjRReKGZIprDAlw2S1Wq6WZ7A73JZc2xvX5ZrPZxMDjOIyH4VsfftQP4263Gw4HKXl/f4dI52br9Spy++z9901fpXxDDMyqqKKiAKyIITRtlJTapjVghNumpUPfU6bIAQGY8Wb7+tH7Z3/0937/X/1ff/rZ/RtgECzFUAmYpnQBgiliLbB1SAaZsWaPp0VteEw91xxd5Rcigbvj5WifnYA4daH1pcgcuAmlKBEjoJI4RxIQEBUMphbjiDgloOZyNARAUBPP1iEQqgnWEt/qWMwr+51blFFtOesSVlYXkMHsHlSCKE7UbjMhJI9Na0gDAOzrEFDmJJPVeuHTgKEKs+Npyf1DL8c8gLEKHNa+E7Vt7BT01BQc1Lf90s138hygmk8AQhIDEEPvmSiaSwaw0MRc+pxTLplbWi47TSNaQdL9frtebc4W+uwbT//4H/zoz378L53v6TqHvuNN2TPXmDU0mWyRlwkAOsHbg09RL0LXI2qP735MX4+vx6/TmBRmXGd5eqVG5YDHKpX5VzbVcqimESJ8/3vf+93f+eFgh/VyhTgWS0NOd/1uudgIwSHnN9v7237f5xLbVbdaF5W+FzVwHRdGYiatC049vdotunW7PvR7KQO3IZVDgoSRYhNCpO12XGygOyMEHccxtIYBBIYspESIEppgBCWVXAqgFwNaLiIqqRwAIURsm4BNXCw7KTzkfNinlIop5ARp0KajIlDExKAfx45jjAuw5vYuvb4eTKIBRmUFySURsinuD+OwG3fbw+GgYMBdx22EoEI5idCopsBM2HLbdMgmxUYY+jwiYgiMiCVLv03lUMY7wQTAONylz/76heclxzzKXtuu67puGWIZ89D3peRccmwaM0glMZMhiJQaVxQ0YRBEQW+8DV4Ybp7mx5q0lbrpTYnZKaSZYyjAB/z6yduuBtv9NFVFBARGdiSIppqpKS9ej/AgWplAqzlyPT0HPG4704kc95T6Un3j9Il3B9qzOz5vVe96DxEe96z5+mfk1sUfp8B18i286pYAAwADCIIaFqNsznJDElAzDciAQlz0m8Bsl5ebT2/5bnd4dPXNl5+8GMfc97lrQ87p7OxsvWkairkciAQgMWMbNYuQIUFhNAJIpZSsYww5J++BXigVGQ2a2FBsMSWRBKI65tFC3c093gAEIu4Po2ZoscGAfTM2HASg5bZpmp3e+hIFhchhvVxvd3sRQQiEJqzI2h8OoV227QIV8iCr7mwc8v2uP7waEgJZQoPAEQRLyaUUNYiBu649bHvzsiiYb/OvtFciYjoMECvJXVOxIoEIDIbdOPa6WUNgIkQDJMTArNwgCwHkXELD6oCZESpZES1qo5qiqRIyMgKguJaQClaF0hru2RTqTKd8EnUeZxF8GWM9Pf8aNxG6/lKdbFOS7HS2mpmauvjv2/cBfIXWNVVl7LwH38niOjJd6mTFL9/rt2rGHCuwKcQ6PZ93jhPY7QipvfONp+iD2dvVzDi5i3WJ2YRPnYDacGyx57SQt79Ip4Ro/UasWHvFpauRM6KpIg0nmETNdbMMzNQmKQ5Er3EiAqdnIZLJBHPPuD3Mffz8chSBDUnRm5D6861aQe6W21QbpPP+W28PegWATc/Wk8qkBqQTq7DecwUVNy3TU6hZ1F8RwDpSa+pwlMrMvMTPd5BTvNONuNMaHQg/nRnHHLVPGJqm+wm0hAhaNIQQY4RK4Hq7aeJxPPjq6ZWTBIKaiYqB+961OkxNA9bqOZtiJ/b+p4DOcvGZYGRS1NhUVYsBAgXvxMGkpKZWKmjDgbwIVIsCgIlh8J6XYsWcuGFVL9HZOGSzvpp3aNCp1aOqV/V4Y2A1ATnK8wcOYsXUEDGG6FLGNmF8FUOdjAhxqOSpKRCdtmIDQMkyGSlARYOJrTbRX42AiAGrp0dE3lHY3jGggmcBAaxKLFd+gsMb6FimFnX9y4nObATOqsCSnQVOUKUzpx6p9QbBBBhV7j9U8KyiQac4k/qk98I/nSaH78KGbIwGBKSoULvZKsokaEhmDAwISMwMiEBYSqorococ6HQrwT9v058wF25PU1pM0QmhvvrYxbjcYujsblQNf3Ryp+/FKCLecMBtd2QOHKQoMQVu1Mts1VQFCc/Wm9V6FWNMKSEE3UHC4g3OGDWn3O8Pm81quViEwApFRQEkBuhC1xCTagzxfHP2jWfPu6Zr20ZEXr+52e0OfT+MQ2LEq+cXj84vyBAUu64TK6UosKs5Ycp5yPvDeMAFAREEQKacx1ESMhFTbJqWYte1ZppEkAMSW1Ek4hgjUlEAgqxFI2QZ7/e7JMlAEU1NzDSnJCJnm3PB8vrNm6RCkZGgDIUwYAAkUswCZb89HPYHNciiSGNRG/p8c3ObC8RmuV51gUkkqaRxkCaGUsrQ90zgXweiEUPbNKvl4uzyAtG22/Vh2ClkCpXWPgzjbre9evxeF5tF4F3g3XbbDz0RoRZJYw7hWx9/s5TSj9uxFApWu30yNG3TdYvNag1Z16u1RQn8smtbO2RRjYGXXTcOu3TI7z/96Ld++9vf+cFHn/3vb2ITCmUV4oYBZfZxEZ0vCo4m1xSxGsjbLoidGNvatVZNixlUESRDICYHNZgDMRHWLhjO5Q7IVJtAoxgDqqsRikmt6SNAQmScq/zAUVlmlQLABOb6gGBe6a7HukZfVPTAtvvwwnNTUDnpNjO9zSahKcAKVrkAQX2L1mUFBqReamimjl07M9lmn+wkZqkLGafdjeZdzGoINHkOU017zaHXt1k92lQqPIclv2QggMUYPU2CTKjeWLJmw3O2oqkhEoOhpEPuC5TQNk3bpGFM45jSoeiwL7eXT1b/9D/5J//jf/cvu3NL/RQFVbFTPzdvtFOFTqdb6v+wSlapt+A4kY6tLL4eX49f7+HLdXairbKtsVo8PKIZ0/yeiJ0mTWzff774+MPnT86u9uMrbmnMqVhGJjHNVpRxKPn13fWrux3Gxfr8arHe3N7e98MRgEY09PJeUyMIMcSmAQAmLlnGMiyXnUFBghi5aYkJoMDzjy6bBWzv7wxzfxibrggexgxtaBbLxWK9GNKovSJS1yEGUCu3d3fbw05NiSAECA0xhhiDCuaUDodBiobQmKVxzCtpAciMwXAYx4EChcjQpYHvd9AxjllMUwYpqpJLQUKwPGQxJQLFEGLXdA02VnBUycOhZ+YY2jZ2gWLOWUSRuOu6pomgmFIGg+3ddrvdg0K3CKawPRz+4s9+8uiDsyY2Krrf91nGbhFD05YMferdaV+vN6pW9gKEpipFwBCZAFWzoQIJmiIYuQyDxyCuyuE7nU3RebXTNvmM1b+srnhN88y+3aRD4w64d5CtvibhLBhdo4hpI5ixqmkTwRmWmmfbg6ja5ReP4FGVUn04jV1D56sn+YNEy5f2GQMAQ3QH3uPoaU3UFWJ1T9Yp6p1P1ggQzQIIAhRzkX8sNbJHMhNEQAqK1LW0+qbs+9sQCGG5u/9iucw5a86SCyy7AACPLh8xa9c0pYzb3f1u6IkDkSFkBAyMXWQQlFHGlLOMatUlkGK59ACr5WoBtgIt92WPBkigNJEufDErgKAMEBnWi2UT2yYcNos1pEPbdKvV4oZDETYRQGDG5bLrx57UNXcQENfrza7fbS6Wy24xjuPuZvjgvat+N77+/E6yQKBysKYlMBApKWUzIIbYhBjjvPGDs7lr1PJVYewJVwZAknAAVUjD2B8Oh92eGxKwnAoIlDGJqaSiBYshMMTA1DCKadL7u3sQIiUgVLIsSbNBqvOD0ExAkoAe8Vp0Dwin+fpgyuA7z1jrjD6GO95Bbna3an8umP1MqxhW1QKdyBb+P37paxweqOH5EbIxsyNLxs/kLT9wKqWbIIYv42unb3+AXv0CDOt4W2qJ2bvSkFNl0wQ5TzjaZAqm9OW06Gg+5BFhgQnYmRAod0rh1GxMmAxUlAvBq5LrTXaTd3qLzEwNTZkieNdx9XpPdLvoGxVUGG3iW04I2PRMyRyTq5dgBORQhqscqaiKt0zyEBbNCCoiBTBnsRHJan7BL1UFkKzKCbl+vM03DUymkrX5on8l8AoAIPhtOC2LmwEsQKiAm1WPfoaZ1NEWAmaqrBOppVw1W39S8ubaUg8CKlMzIKpiUohYSnlInIP6EQJ820hP6NW0DVSRKQRgRKRZVwsjOTzkrCliF1QOfr0GZlD8nTkXVlJTECDGSJHZEzBo4n0HAQhCDBU3mRYrGgQOICY6goCpCQgzGVFt1AAEYGLCgLU01KlyxcNIQ0YPC0WVnbXDzMyqaiaIyIFBwJzipTA9JAwUsM5jFEQz4KknJYAHKQYIKY3oTWXrIiJAA9MJN50oSIQE7HeGvX/EhASfrHxzZrEDsk5JM6kcbg1KDg+pmvPOyJC9v0Q1Xl6JaWpNJKJgiqKlHhsBVIHIKmNv7rhW2d5wXGnT3052MquUcqgRLFNgJqJABEjsboUpiBYVMy2ial4PHpCZAjGFQMz3Y49EXuaJjjuj8kO3F9zgnKD0/pOkAowMzIxAwMAAikxuvAXmrg2gYESztw1gUHKKi6brOgMZU79aLpu2vdnfShEOjGjj2I/9F4tV263aq8eX5+fnyHY4HLZ3vVtaIiawglCKlKJN01FgbvKQodWhbcKT1eNFt8Si/f19RFx2i6ePn7Qxnp+dqerLl69Kyve7O1PZLFdXl1fP3vtg2S6H/aDi2t/QcOi6FpCGMY1lNNLXt28AbPPoYr1e764Pu35HjARIgdvIIcRcct/vh5SjEYhtliuOLXPAKNzEMpaU026/ExNg2O7vD4dDkkKBRSSEcHd7e7u///nPP1msFpdXVzFElTHEoKYiJZeklIZ+KKWEGCRLGsbD0O/24/3dThQ2mzOAVdNGU0yjmGnbtWrSDwOBEnvVsEYLkSOF9mxzsd4sHz9+vN3fvrl7c3d3vd8fuq4dh7Q/7M6Gi8BhvViCah76YZ+JFoFQS0o9fPOb33z58mUbOOUSoHbFaxlWi8XZ2cX55kxH2SzWStIwtdymss0ldV27OVv/zU9+3rXrnA+Xl6unz86BoVmyGGbQrulSydXLnYThPDDz5CkxAoJM/PDJbIJneKuFVChSrCj0mZhDF90sE9XGOCEG56VOGQvVokRUq5F98fiORaRFZ7gKXUhPVUqpHQQ5hBjGVI4tWOqOa0oTfDb95kG12vSPgFTqpxStoitoWPlOBoreFHhKKJtNqSz3H/0/dNPm7EsXxmGkSejk5Btt8i1shqJOvBxHdSomhbN5xVMR3+meQ/Ve3jFswq7fetkAmtgN0psBITJhMTf7wUtHfY/ICklLtpIgA5irEw7jft2GEPB2+zrw4z/+vT+AHbQf2HBQJifqwVw1Mp24AdX9HE7Aw2Pl4OSOPfz91+Pr8Ws+7PSHE6lemyd/DXgfTG0DUBBYrtoPn39wdX4mliNjv98e0i52uFyvG9lDICTWAPf9/tVdf351vj6/aJeL9OZ+6IEYVMAUFAHB+0Obpy4CcxozEI5DGjWtsOMAwNy2oW0QJYPBk8cXDcbXr3623qx2fb+ORgRJUkRabc7WZxu9B1VQhGbRUYFc7H6/S2VYrT2qM8Sa+FFDNSlZkaDtYjikYuLK5UwAKCkNY2giBYJgwrsBYoPDtqiMwFBMxmFkgvNl04S2WS4jailMoXGvkTEYytXjpwTMgRlw6Ie72631AgTdomuaZjzkoT9YkYiMGdtFQIHxkNtNi43lJFdPzmPTHvqhqIYmEGFKKZWxbboYYtM2h91QVCIHL3qggMQMFqCy/A1sEvkz8NwloZFxdQZdonWGlE5RJJw3jYp24RQzT3nuSTh2cu9h+uAJtdbj8/mXBoAugIbwgPQEcCQU4OxDTjLwX2Vc5/OZfOKvnvFfEePZtJudbrW+S9IE5pnN+de3jkmQzQKaNzcxUDTEYgYAYWrDxmq4vuiefysXOXSL5vLy7LPX9/vdqEpSqBQgJAQ+W101AA014zCOaZTtFknBELQwYRMjGoFQIkkqQEYIGIEQxEAtBYbVqolBVdKY9pYhRCqEKYtLyZqCFMlJQKBr2/PN2Wq5WsRF2yzLXhvmRdc1MWbpS/Z+aNIt2iKpoUXNOJNsztafXm8D83LZDPvDfmvhvdgf5PZ2i02z5DgethAbKTqmpAIhUGAOIcwyxtPG+YvGCbGkvjNGJobRRItYLmnoD3sSVbDSMqQxlf5QClghZgmRAmEkMrPIYfdqZMCGQ2gbImwoCquyERATBQjFRCGbqRlRBZP8298lCIAnp+l/TcVfBlO9q9vKuVcXHL3LShuY3ApfREi1Sbu+PcXgrS878ozgwUp8cEv1iCYdEwa/mn8yLYRfil5NXE0kP3tE1PILcJQpAn37y+wU+TKbFMMfmhqojQsdyPJaaASYYKwJvcJJjMvPaurQZ3SkqgA4wGfidiUwqtVm1yBobGhQ0Sw5dppzCusRpnPAJEwOo1Z9dzQIDpzhlKhWhyanSibwJuaAWs8fwbOhVS3Na5+8nV19EB784oT+EWhx93nCgucff4XhmAUCgoqKKjM3MYYQcs5pTJWRxJXENlea+EZAXHslmMx7hBdQ13mDU+ls0zQxRt8XFovlo0dXQz+aWUqp7/ucs00qcRV7QnR4a378E1oH4EQXX46upGVTtKYACF3bOi7m5c1ekcFc5dJSzl5an0UmWXeKIYQQCEmKl+MIUE3hMYcYmxADB14sFjmXNCTNBgQxNoSU+tzvBi21yA4NrYBkLak46MRAHIJoiSF2bds1XeBgLjAPmFMRs6ZpmDmnomCzSDwgNjF2XVdKkSJW1FW9vL1oHrP0QxmTGpqp5CJSRMR9tAnBoa5pGMkRWjVjoIn45lsrELoCFyGht9BTkZJzzjnGyESBnUoNKgXNHOhiohAYGVTVCzSjm3VGU6vSiUzERICmIKmUJFrMmyeqmBUjA3RNaaIYInODCKBWVCWLiSIxc6CK/5sZEHEgRoM8ihUBhMgxxECBXL24oTZSIGAtOqaU+lFK7aRQsuRhVDGm0MTA6KJRTk4pKY1ttwD0honiktVMyIjOFMEpgq1mijCEwESmqlmpY0RV8DkFHBADE4L5K74+aqMIEK9K9aiYyUy1lLEfU0pAUEoehh6JQgimmnIxNTFlwpLH/WEvUpweIyIvPn+zbDeBaLlYLLvmw+ffaFv+/R/87h/+/u998N4Hy4a/9fG318vVqlusu85yPluufvj93/rh93/waHN+2B1ub25v39wS8fNnz6+unl5dPv7D3/mDH/32jy43l8Ho4uwy90lzefz4ydAPd3f3GGi33/+L//V/yTEXLBSCIfTjwIEvry7ff/b+k8ePm6Y57A6vX7+6ub52EXItOvTDm1dvPnvx2eeff/7kyQcAyMgkuAxdSdmKLpvu0eXjbtH2Qw+EKeciOozDX/z4x//mZ3+z3e6Xq8V777338tUNMTdt6PvdX/7VX7x49bNchJhWm7O2a4k4p3x/f9j19vKTux/87m9u7+8O+21O43LZffTRh5IFzDgEBDw7O3t89fTq8v2z88un7z1ru+7m9vbV9ZufffK32/tdlqKmHPjq8dVvfOtblo2BWw4X52ePr642qyWYvn79oj+M69VmvVxfnJ+vlovIYKo5ZZ+0kgXUbl5dX24uuthqyvevblr827KHAAAgAElEQVTu/vP/+D/9wfe+++b19XLR3Vy/SSmtz5cfffzhP/33/6P/9n/475sGm2UbF+0wjhwQUGs+YcJxi2oIzAGHMXm5mZrUqmcBRiIkSZrH5DJSqEhMXbdsuqaStgCYOcYYgvfxME9O1AQG87g/SM6lKAIhobkOoAqyazKAJy0UzRiICGJNFogWZyJMuR9VE8fa1DXvHCUPXPPhniYB31FNg6WUJBXNIlm9G7qJEWIItGy7JsbqHhEEwiZyiF5OqCRT0Aou/YSEyN6j1qSoIFIIHGMkJhEpUkwV0Qtkj5siPhyn++UsHxZC8E2hXoTb6/l9hK5Fz0REyEx+n4kQg2coPGNEAooMopLHUcGWq2a5bDlYE7GNJlLWq65rw/XLz/76x//63/3jf9TG7u7N3e3tF08fXy473B22bbfg2HFcfjr+5Pa673vEogoGBDKmGBtAKCrgYB4aIRCBy1m7m+K0OKsZwJr0qxmar1Gsr8ev65hDAnCQBr23cvX9a+4TcQqjzAAWyy60jN56VQTBoIEPri7/m//qv/yH//DvI4xEedE0TQdFxld3r3odlsvVz64/+fOf/PTPfvrjpFAQMCxCXL55c3d9+/pw56lTIAYMhIxGdrbZrM7Wj64evbl+88nPP9nf7rFF0cEQLh6tuwWTGaT8g+++3xItWnr8+LLpaJTD3f1QANZnFAI0TdztD2MaRWC3H6+vU5HStG1sOoXym99+fnnRXlxsNqs1IWnRIlLEcsmHA9zc54tHy/OLdYzYNHpxwReb0EV9fH7x/IMPH7cf/smf/NlP//JlSRziqiQFb//qrRwKdW0ng97d7gI1oenSMO5vX6fUt0139+pmGIukIllLLiBWQEC0jPmQDutueXZ23jaNFkCAYUxlUCAoIqUIsPX90Hbt+mw19un65V0qQ4iulo7jOPaHQ38YtLj7V0u2NYupcUJSAqtbCyigmakQkKtSVEadAkh1xVVMikk2JDQwdfFTIiR00Mu/F7xs4BjCAAKAqmTJKS/XS1EVVZiCSVUFMyBkDkS1WAGmypr6DcSIKCo+EWfaSs391BOheX+ZeQP+qVKKZ/31mC1/OwL3Of72f0CIWKTKlnmTK/frPSMNat4k3URRAIHAGAC18gkagjbEEIJxA9xoCIgETdPFGEtJ2ASOLDx+5wdP/ov/+j+T7rP/+y//j5+9+LRbvL9cXf3Zn/4bLXa+6Z4++eA3Pv7umIfP33zxV3/115988tlyvTk7XxoYkrWLaGBpEKIGIOTRcrJAzdMnT8/WCyTlAJePLoexf/n6ixevXqfxEIhXm6UJ9KmERQPZQqDz9uzp1XvfePKsvz/sb/o3n9x98fPXN1/cbvf3FxePfvjDH5nIz3720ywFBP7w9370wz/4/vXNq5/89V/c3hxMoFksaBE++u573OTVsjOzF59eL0L44PE3Qokv/uYzK0GG4ez8oglRizUxmmkeNITQNE3f91WsU1wIxWZC3kw88fw6IbGrNRPjTNFCcyeqWzXdJkIE1dwf0mFIkfDwUjiGIFy2mQKtzherzXKzWYPZ9mavg4FASZpSTjkhIFNoqSVkExvHnFM2s0iROXC1iZ6qU9ejOGGT2MTJqZPW3T9iokDMoZ451uoQQgoc6DihRLTM6NUE61SBHnPVPXO8mStcM9ntOttr9RUAWBHBiYTlh8CK3QC6aPzRJ5to5idjfgaIU5oXMXDASSj2rV3jwWdrCZt341YRFXE6htXTq+R78gbNcwoVCZCpSlGfEEgA6G2WFABOzeX8dGqLIjUrjsqZG4HFYjHXwPl3E1Ig7wAIAKbgXChRcFLklLk1gAxEGGIMTQiRXSK8ClqbNyxyC4iAYB6dKphWEXjJYkUMAIEQkAxZDQRdcBANHEdBAxMsxUANDXFq4W1WG2horRpzgwqnhWFgUKUMS/3BSSZzhteqLL3Nj+nUVL41QogMR/FdAK8N9Gw6e9nzlESvXD478mDgFFjy7zYrjmMBYH1MIpJzZmZv5eeg1TyfKtvrS05J1dtCRBdDmemLp2nuKWiw+e5MRzOzwMzMwesFHQtFLFMjGpx55uDwpXp1i//Spsv2OpYatxgwUWgCqCETmJkYAbqUFRoUX64KgBA4sM8sM8kKDJpLAVQsYqquRYUwUexmaSpT1VKKTh0MRYSIiElNESfNZgEoCorAyIaIjAxT0Qy4spoTNwqoSHaOGjECIxiIU689NWRmBlKKKTJz3e6QkKDkMgPdCMDEYIZgQOQtiBEcTDPA+X7VHZo41Glnlcfn+c46WXS60QJGZgiqhq7DMle0zMg/HCedqSma6ITse3X39C+v2ZyJEAQkCGAgRWye2PWJ+01SNAJQYzRQFSUA5KDItTRJVU2RDKse1mT6AdAFEn1phsl419NWNSTv3+YwLs6r0cHvukLq2YYAZgbizVxRyRSkuDZ2BeQJYRxHIFgR5pTSmNoutE3zw+9/v9+l65vXVqRIIYRVtzItkkvHzftP3jMz2lg6pPVivXjywYLjk4tHMqbPP33RcCTCZbfgGARss7ksKXWxu7+5J8WooLFIKl276Nquj30RQaBSiqkJKnHwbt5FNFI0hTxKhtz3h+39Lo0ZgQmZMAZECoQtc5Gsst/vYbmOwK6ZF2MTQgSiIecxj2Mqte7RFIDWm7UhBsbD/nB9fV1KiRa9lBdU8whIKTYkqbHYISAzdC33oxSC/eFuGPbD0Jc0yF05P1sT8zCUu7uXlxdXjy7bnIBWXbtY3253hxf7fX93c3dzc/vSQNWEgnVd8/kXr2ITv/fxt5WFEAKRKZ2fP2JuAHB/6F998QIRl6uzNjTvXT1puLHychiLyxnJfnx0+dQGGccDFN10y/cePV60ixAa7DBpHstgYn2636cbaeSP/vAbn3x2e73rkVtEb+pXddZrYmoudpsXxswEVt9Favrs7XH8VYWzpyKCiZdQt4ipeqIWXRjqlG/zevV5r65VdHVJTE46mCs3QHWowXgu/fW/Tk/OahsNQEIFChRr4sYBFDtq7plhMSFD9zR8KxCblAPdXfRWDjaVjqCBgol6lcls0t1UEs3lfu/YGr8Kupl9LD8pv4H17dNlqZq3D1bfkbRKAvg1TSj4VHyvk5H1jhamDBiIKBhoFhBVaUIz5sEAhjJyy4vFspQs4wEZb+5eM8vZ8vkf/zt/74u/HX76lz8GBaIofebQKBQRneolPe811c5Ml+6n81ZCHh+yCb4eX49fq3GCXvm/9cGKra4DnrRbR0AbczIwd3WaRUNo/S791m9/e7VoRQbkwohoYqbFipoAaMLEDTWLCAFiC6Frl8uliPaHoSRrF00ZpagYA0XEQKDSxtAE3t7f7+53kZqcEyucr867cxaR21evl8vm2eOnm27FAqiScz+kbZaRGlgsgBgMWQzVIBcTQAohdoUbBibXbt3utozKxr1SSQamTeS2DctVO8q4TZBS5mihiYEtokYubaT1OraRhjLmXvIIDbIUEzVDUPO4AxhFWEoSE5CsOCYpxePNEAIIGEqypCJgUEqBSWMkYkA0MzHRuSID+FgqrtmaLppYGpKIEENOmSkgYN/3XBOFznitIU3dyNwb89yBmZlWz2ly/6dtZ3ITXTPC7TTBXLMHMzH4bcM2WcWH88umvZFmv/HkXfMW4DDpKe2i8gjU1MW0j5GETfSK4+x9a6vGIx3k7zDsZOpbVehx3q1U9gRM+YkZFaisCCSvX0Ez5Eq8RwLEoGB5HLGNsY3jcIAoIcrd/RerR9sQWoLl/W3i/f43Pvx4tVhcrC8fP/rg8urKcL8/lHEIjGst3HbL5QrssC3jSChNy1pACjQtbTbLu1dDQ20R1SKgggAxhiKhDZk5yljGMQFYDFjGEpiXYcEY8m48mA73exuBEDCiFNNRb2+uP3/xiVhBBhBYXMHqKu4Otzf3d/seKAIhNR02m6WSAJZSRgIAMS2Sh1wSgAAhobIVKK5nLaZaO72YGRjBLC6DX55RcHx9JtFMIZOqEUJgBtRh7PtDb9G65SIXTGXXNQxdMVUlhAaKlnEcuUM95H53kKzMwEb+zWoAUp0gVDMFMgQMAAbmctlTkl5BTZjDL97W3T9UE8UTJ3KWEYfZV6iverng/McvGQ9vlD0kCtKxDc6E2NZ3vePIv4SBNZ2jazHblP+dV9aDJeZpvBN2LuEx5HSkAOZq3Hdc0lecwoymufM6O1TVkz/exuqPTQBY5eRMBCyqi/TocOLkok9OeNXoBwJF8QMRVGXaY3u/+mXuIxto1YKvaUvzmkI0qDqCDg6oegkbqIqpoVW0S81OiR1iBnP4AAa1Sefk16pvxFMvcL+at+sDftHN/KoRYowiokXmaTmhRUbEamBeLVgBR7+vNbt9hGBOvh3RhZTq2gEFRS2lmNUODmZpfroPQNP5MBN6xcRAcwE6TEjtVwysGYf5sMTsrIDTg5tVFTMEJ2chGqiI1frPCq+YiIGCglGdUipSUja1QFN1oUeAiowMiODx01TORkxMDIYiTiZCEy2WfMPAudm8Q1xVgR7BzDWPfONR1ZSS5+uZeY6/0BAUKyFeFYUCcQ1KTfxhKYCRIZIqmNRiZd/OCRCJJ6TTa5vF1JAUXTqqXrXUswIg70xYS3SwtrIHQyBD9f66aOpuJBLEpqnhrXgMCeAHU3AxfEAEJUMz8HqXWl7kaBb4adqkhFW9GXX9MZvzBoAqR+EbV0CvYK2ZmSGAmrpm2Wx51YAUCKiqXBua3xwRZAqBgUDBxftr0S5iNa8uwG+VICsUnOBHWEvMzTmHbu68PpwQbELonbgOR94mgvdidUNgrnWlVszTY5WOWQNdiIGY2URSPwA0FuE73/nO53/7cre93vf3KQGqnq9Wlsubz7/Y328fn12o6QdPnmiG89XZ5dlFx6HFCKrpMBy2h6ZpKCBjjCE0DaAhie3v9mkYGuPNYrlZrderzaJdHJretTxLllJKn0ZojJDFLGtmDkzBxA59f3N9ff3mhtFWqxVZUAUzJAyBUTWL4nZ7iNxxIEUEZg4ROYhiP+TDOKSsxlTFtQmvrh63i060DENvd9b3mQIghzSOuWQzYAYzLZIZSZUAtGmpa2VIUMqIZGaSUtpuy6efvHj27L0mNpFXZ+uLy8unhJFie327f/HFp7c310jaj4ch9YYl5ywAHKBrgRiev/ecgGIgAGxCuFyvLy8vl8vlmzc32/2u9CO0cr5aL2PXQbsK6yGXwzDeb3f9YWyN0v3BIJ8vN9/58Fvf+eg3P3j6PnHIKe2HHiMgq9gw5i034Z/8B//4n/3z/+2Lf/XnWuz87HyXbskxK3MshxGnDdcVniZE32adAQMz9dbmp/6CgRfbVmQc0Xe3imu9lZLyRBMCkQIwmKt/upkiwICIQb3QAE4BEWfCVhya3NLUST/7crMDfQI2A1TKJjJ4g5PaOroet1YQeolI3WNx6ivhi2j2NwAcFfJVWD9gxAQAJirehhQUJ7syI8xf2lLeHl+1/1QPacr0eSdgj7msCg67nOZ0GKzYkTfDrTUpCqqiQmYcIjdNq1IjQEN4c5cCNALatQs6u0DdEwUD6fsdIN8Nr//g3/rdP/0/f/aTf/3ys0+v2wX2GbyKWophTTNgnSVYTdBMePfYzAjQmd4w+Ulfj6/Hr994C71CrPKe88qqhrCmrKv+ESK4hIc3aWEiAoF7+A//8T/6+MNvRGZCDEhuaUWyaQEWgUzBiEEB4oK5aZbrVRrzzc1dKQXCQosCAjUUWuYQUCzEEEPY94e8zRiIkVpqHm0eYZtevn6zu7ezBZytFueLzlJJfe6lH8sBWRcNLFeMxI5/p6zDmEQRkTkqczBz+rb2/X61aNRKP+zLqEjYdmGhUIoW033KsbWmo+WSG+KGMxOsV3x51nVNPOx2Y59hBEEANhFxNV73o8SsYJbRoIBYMR3FChAECpEZBMxyKUVcONW79BGggZdLmEqW4tUHiGTVoBgAWDb2toi7XrMGwrGXRaDQkvY9dQaKVoyI0chcOWXK6jvAVrV/p9RGxX8AYNrrcCofPdquSVoVquM2b4vV5KM9MPSnSj0IoEXQjKcMDlYBwZqBrPLSc/q/RqrHWPeIds1xGh4ZKL7t0qyU83B6/92HVpUPL2ytipyGU/mP23esUe8RmkAEU0toU98+APBYQERT4uUyNjSmAgEuHnXLNd7dXo9jYm426yviy/e/+URLBsE00Iuf393dXV/fvtmOt5ePVhveXF1tiu3tlSUtIQoHQ4RGsetiIP7scB/DoIYp5SyGoCE484fbpjkMecy5a5qWQt4O7WKxpEUotL/Z2QjjFiADIxKzqpah3Or9ixefhhWrKUX44PnVxdNV0dSnO1DgJYCpBW2WYbVuB1kQgWWNEVBZs5TBy1dJFdVbq4h7TdW9cqGF6ckeZ8s7RyUDGU2uCTCjWVHPVpmJKofQLbpxUJdiaFrOBwkcmkXn5AYE1CIq0jWsGUnJENRDRPHeyuphWBXqnhAXMxPVGsWrAh8nKkzAyjEnN03cB4yD46yccI45WTknTx+AJO+6Ce/+5XHhHF+qxQAGgOakjYfSDPaVR6tnebzAWfZuegq1TKAiY/NN8uk/2wl0Aj8I1nwjTgtnOo7hkeqLk5fqB6k+VdXZmK3QUep+AkCtXs0M+1Q3mkqZkst4ZB7N8k0zZuLnIPNBEIHA0BQEUKsJ1COx6Yi9GxjWdC/U0LnyeRxv94sjRFMVMaxEDqiwRCU0V0PothBlPn/HttCOhtbtG6HLl4FOiYSpVrRSZv8uI7jc0hSRH2WPHDRBkflJn2JVPhUmqur8ovO22MslSilaJqYNHCeKI1m118DJ0eAEp5zui/8a5rv01REEAAASMRFWPm/FeuoadyQCEZFmT8eRDzN0WXyrdh3IUAuoKVlxipHLbPX9gIDEFAIjkpmAmhV1Vp6YgIADDbWezRC8N0qxuGADsWKCRohI7B0xGc3DPAAMjKLFxFz9ConMLOfsNB8mkglbZOAYPEcnWhRBkF0SzuemNxlGEKFmwaoFptSBzuXQiISnHEclmwtr/Vu8RyTM4Zm7E1QfCsBE75ykAsWUkYCQAALzpJ9WbILyEbwAkaiqbxGYihiSy1RNuHe1kFaD6GNkyqpqUiaosWJBXpvvc1QkT1XMdd+utspPoHLClDCiF88SAPmyVS3iyB0hAZiiICGZERJODRqC08mceIkgaoEAkXSigU2m0ZtS+vp1rjpO1qpiczDxsrQUAAAG8BaQBgCMBiYAqEoGBpYgthAjN02DCGMaDUWlrBbt5fnyo2cflPGq3++fPrq4PDsb9ruXn3+Wcv7o4w+7tjs/O+9id7Y6Wy+WmKX0ueRCaqTeZoKgGJiGJhLiMPZlFFTMWUZITy661WLpZMa2bbM59gGH/QEVm9gImrgGnSEoHnbDzevbu9vdZtnxOqKxJAUBBkQjUgLRUsCAwFDFyXwRMWSFkvKQiiFSYBTVbKp2fnHerbp+2A9pzCmpaRoHA+oPB5XSttAt29hFQNWSxqQiKTawWGECixFXq1Yll9SLwP6wH8e0aBdXV3G5Om+bVRMXd9vDX/3kJ1+8/Cw2YbGMHHixOkvSD6XkbMWAAkSCF6/etLFZtG3DuGhj07Rd215dPV4tN8MwqgIyMzIDx2XcdBd9Gl+9vkm7LGjpvu+3Q1yeXT29+M7H3/qtb3/v4vxye7e9v7/VPHbLJjAC5T7tmsXij//tP/qbT178+Y//35tt4sA2qgBMnbQm1wQ9I1TrkE+tYl1Cc45nNt3gXfmqVdSJiDpbZpytMICBMTNM3fEA6/ZWvIc5ItTcgCp6sa0BYG3YAC5sBzC5BFjZPHMP2UqtnGwLgC8xosAOh1OlwyqAWpVr96aloDijMNUBgdq/xC0TntgmZDM0Lw5BJAI1VFWQ2m0BERFnbA3mGzKPd/hkk1N49PmqYXv4bjv5fBUUqLbF7LjrG4CC4CxwauAJDBUjats25iIUOBASWB4SQRMYeKmsw3A4xLY5HLaAFtpws71+79Fv//D3vvfJX95+9vM/YbZmSZANGbwYBx0BRDtGSxOGhbNog9WmSj6nDI/Zo6/H1+PXZHwZvbJZOIOO6BXMCxunQAPBqyIc2S4pud/97/2Dv//kah2YfANXEAMVySIZgwEIBRC1VGC9asR0uehutsPNzUtTHEsyNoxEXQxN5IBQmMgAtI0RFKzXs8vNebdax8X1/fbNi/vVEh5tzkikIchQVAYpA1JeLMNiwYsumkkpJgop2zAUQFIFAFa1XIqIFlEDJCYzSWmUjA23SMQJgHLT4sUjjG3bLbuzRewCNG2PULpmtV6Glux2fyijgAACmhJIvW/IXp1iEswKgICpFhFDwYbYZTU8WahmUtxPwsliIIFXxEgeRR19OolKDFAJjSRJOmQAwEiQJEAIgUkRFKwYZICI6JopCqaVukqILhk8bW8VEpoyBSfsKyOXmzWomVY/iVmIvf45AUkTiv/A1E+RBxQpc158jiHxWFfwjnjEzDNLtUETehLeatWjgeIvLIqZXv9Fkc4vHfP2b4amgAao042o98qlcG1K9Ro4rwIKVhjTVxRLAQOE0ErJuRi2YAHaJT9+ev63P3ud8nB+9hsXl98ZxtXtmze7u/vt7Xa/zbf3u89efrId4NmTxYff4ma5fM7Ltg3n+WCkRW93u2SgIWCIoAVVYOyzKOZso0IphV3AJAQOrAAigESRm2BjowxZ80FvX93rHji7GhqaAhgqEYjcbq+jYs7l7Ak9/eCyWVHaJeUEBBqAwCBa01G3iitpJRUVWy0boBbMypihADGqmHpFqlltdO9JsdoobCKCw+x0/AJopb7Bf8iiOqo2cLbaLDfrxIMhQABgKKa+tMGQA+tUjucJ8aaNZQBSVIEJgUAEkMllwtonwAMjMIVazaU1MJ6mx+SwWCWtH5ERM3v7OmaPTWvId/Qvf6Xxzgltdgp8zTja8fen7/zlX/Hl1fTOj+GEbuMDYtT0cTzCTh7zTnpNFW1BcIqOOpA1fQZOPvPlE/slkDTCbBMAIOd8vAKsANCscnFic8yD2WouCNzYGCiw5w2m0jSYLKUbLv9wnTgVJ6vGUmsKkwAcxhSZhLC9GHR+5pPlrYhKDUn8tEjnEok5STptD1XcerLgAN42Sh/CTL/qvAp2MnERK/3KcajjPcd6iea8Mr8ZEyoxvwcAiCjG6FyhUopfV6CARyUzcMFgb3VXyhTqeDAx6bC4jUBAw0oYmP1+xNqV4O05gOQ8JZCKX3l5LamJqogBgLAxxinkc2l9Q3BSncMGnpybW9vpEcsWkCJAgF5nxqDqlUbgE6WSIabzkaLmMJiamUXiIqpmbIBcuQkKhp62AnSIyoBEBNT1xRkASimlFK+mnB68EYbAAaRYUcmCDmO6YanNAdWXGiMZEXNtTerF/gbgkvk8iZpRQOQa2mjl4GnTNLOxnlZMjaGP/yQkZH9IZKDg1ToElS+hdZufACzPfjpUzeayyh5XU702PeLtE/5kMJfFKlboCGmyqWYVXGZEPFmeNU/GE4fOpvYWqlIBZmC3ZGJCioomIpjNgI0AEQIzA89xKMytN/wmTA97itJnjhfIZPKBEIlcABEAgOo7ECs3FBAlmTMuEahq3wEgUK2hVwACU0gJmHPbFaQ6N0IIb1593oT43W9/tFmtt7d368WaGT7/7IvXb16u1uv9dks7GvfDxeaCMrSKpJD7MQ8jFF11Xdt1yDGlvE37IqIKkuTy7Pzy0ZPU95CFiAMzIzFRGxp1uToKoJqTAgDHEEMgIBErJff7w9CPBNDEbhEXRrEMOY2ZkVw+lgCWzbKLCzSQIkJkBmqYBRBUAENoiLGUtD8Mt/c3oeNu2QBLklFM2hgJUU2IITbcNbFpQ9OEJCJiRYpqjg2vmbgZY0vMzThwt2hjTJeXFykVAmEM/T69fnXTdOmTT1/++K/+WiF/4xvPqGljxKYlSMRpKJqAwIAAw+ub2/VymXKJaHvClPJmsVgulpv15vGjxwo4jqkkSSpiOEjaHWS4P+TDGAHH7aH0Y7d69Gi1+eiD508urvb7w+cvv7i9fSNl/M7H3+jaUMpwc/NSzC4uHn/zw2fP33928/Jv7t7c0pKmqjifNLXCos75GXSHCRiauhS+bZ+nelWri9tmYKmuTF9gBgBGhlQxWQADMgQC9X3G62KRiNhZYEB+UohekAAg6QQLMjNwFcnK4Z624SOANq8IYnQxStNqOuqpgZsTUFXXu3LkiSp3Sd11I5zXIqBXSAM6bXeOCUxNRREqpuwY+pS+eXt8OT6Z3zb/yoG5uk+fOhdwdIQ8AzDDXvOBEBFMEQMgA+gcYqkKmBIjCiBhE9sOqS1yrds1LTm0ZphTRsiH4UDctl2TLQWmH/3Ob//0/3n5P/+zPxlzDkzjWAKbZ/rne3D0044XU890huPq6R2v5Ovx9fg1GqfoVf0TJ4RiRq9mFGDephEotgqAoCCSkjy+Wj1/rt989sz0IJIIpYAgSCQGzSUPFkCM3NkTgaZp7g8Sm4gl3+xgGYJphqaJTQiRjQ2ImrbhwCYSPA7IsOqWq3ad9+n68zeHAT58dv7k4hwss+lYxpJ7gNR2vDxfdsuAav1hUNWiUIrmrIZgs3gKiCFysBAI0YrkUjJzGwhz1pKHnAbisFzF2MW2C8sFrbu2CbEJuWtxuWAmHQ8HTQICRKxCnpXwQALNQKyqk3hDZwWIRGQolvuRmqhikN1vP4aebrXM1FTMCtTG1lNY794amhYpqbiGbPWUTLgQRjDFmhfMZkCgQIrqZCsxYJhg9eOGZVNaxF3MmRcB1eI6ggSiOpmyyZbhMaqs0M0RxT+ZZoClSIhzZuf42aku0E5ehulLqmElIg8LwfxfqF5sjsd5+2BTeDC3/3+Y3QmXqM6zghqgTuLFc7IEzCpZy5z3olCQM/IboeAAACAASURBVAKCZ/mREaMBBm4xUE7bMfXYArQgNrYdG6Qmtuvzx223/Pknt//if/rnVhAVAi7HLLs7OIzwShLwm/vdfbuyq/faxXp1GXHI5fb2WpKIFU9RXWxWJUEZi8+snEpNixGpaRa/LUhKi9BAtuGwz/eatgoDRGaPswAMCYijEWYdLAMwPPvw0eXjTYFhN9xk6V31K0Zerrt23Q35oJCLJBNdLBumjg01CShYVfGE073d03mT93W6X74LQJnmg4Mgk2tf8VMtAB0s16vVejUc+n4YFHS9CmNfQA0iqFpKSbJohsOhR1QpBYRMSbVmwMwV1RRd7MQjBgcKwElZzvD2//CB3+I/eO+y07OFIyJzAgEAODLw1hH8ucA0mU+P/Etn6Ql29cBa2AkzEE7cqLc+/uXx1ukZQCDyIjCAB7vGKVr3VYd7sDztwcdx1napsXs9xNG/w+M7Z2RqvmMnYbXNbztemTwohxcndODbt8LjgHpY90HRjGfEygyoVvEhuHmf9ZoeIijVdXcaE9aWhUYGpRY+e4w+md6arnV+jtUsqGsJTRNcZ3TqmGgAQECtscv8gACAGeZF9P+x92a9kmRJepgt5/gWceMumVmVWVXdXV3dPT37TPdIhLiBEgkBhAQB2kEK4ov06whBkB4kPUgQCAkERAEkMMMZTjenp7fqri23u8Tm7ueYmR7sHI/I6mr1ENBQfCgvIOveyEgPD/ezmH322ff59dTY9FcPpOC6VCcRD1eL4oKMehbkVB0840mVWsQvnN9hI1gmLWIM0clWpRuLqKizY9AsUJEUPxbpsuVPV2kvvBiXOSSUaf7FDwYkYiZCzeaZfxYBAHKzEi2pDUUGd6eyRWcFPP9AdLTBlfoV0AJV/XJQdQKEmqkmmZS5/EUyQgQ1yQICgQkYVU2SZU2AQICMRAYFul5Gn48jWmCagsKqirmkIrMrkKWUYogFBLRSPyFgBim+BC5G5RNDxNSAkAgUMaWkBoiBCaCAgyCqOZuZGQERezeoLaJPfih44+cyxokIENTF5AHQ0RhAICSgKjiHjMgUskpxmzQ1MyT0HnICI6h8wcJlNhM0BKqdsbUoVJXpkACAiMHzWgUECExgKGpm2cQMOZCLNiNFWAYqVLHAnLNn0a5zn1NmIEFjQlPIkEWVEDVnUSClEBgjMTGD+RzJpsUSgpk9J0c4Z1W8OQ/KQ15e9R3WUXIjBTj1t0pgJOQAVDgsKmpKqiqASjEQgaKqQUpwPBxM47AehmH16OrmcH9L/UV7fXl9tYkEq2aIxOk4N4GfPH379cs7gzwfk0057w4wpsisx0wKQ9tvt/uG2xh41nn/sH11+2Cql5c3TdNfXFxaM0hKXdc1ofV+CwqEOUsWFdlsLh/mvRm2TR+aBpnm43w8Ho67AwE9vry+urrq2t4wSqJdmhQhtBRDQApXm+uLi828P855TogmbjFHCoAUKZJY3u12nz1//tmLjy+uLy4u14CWJWdRF/EfVkM34CT3WXcZc0rJAJkpNqyqhLEZhqTStmGyZGBt2282YwhNmtXy2HeDKT3/5OXd7qcf/vzl64cEAdb3h0tm5NhyjO3Q9qMRZpmTqszz7jghMSJmhKPm6Xh8CLHv2ovV5vLy8ury5ubqURu7VbiwxNvD/n67e/bknYf9DoBMcNodnj5+61vvf+O3v/nrHfYvX7789MWL42GnMimagh3G3arftJEvuv7f/Vt/M0/h7vjfPX9+LxVlQGduVsnVAsKXDRCAgBCJCc76ZqrmhaP+tsSpb8TxgFxXgGWmY7XmEBBiMmD1XYBK3c9XCFEoAlReirJzOjRAcT8BA1MDKtx1r7ecz5VCqHLx0Oz+BlkW5vypJFNI7WZWmy7KpoqwlJzL+xgIiz4WgSogKUEgrdRJLHp/gOYQOn3hXvnmi6VQWQt3ZysM11e0rmxeHIOKm9XtdcHtlvp/WRKqfmEhgxdHyGmeDLUJgSgYrf/ZP/vD3//2bz9ZX4CRqiFi0zRJZBz37TA8yP37X/3K7/zut3/3O09++L1btWyIKlAVYUrLjBWqXG3ZxnIjfb1adqK/aBj65fHl8f/TcUIBFr7A6Qc4n70eoTvWoXNGBgSDAL/327/7X/39/7SJcZoNLQOI6oSokclEDvsHVRg21LQhYiCGpuN0N7axaVhBYX2xPsy7blg1gVXmWVII3Pf9xWp93B239w8gsLpgIiKFl5+92N5OH7wXn7590YXYtV0beUQ1yNxAXDfrTRubZj6klI5mIhlFMGcBIiPIWUUNSJs2tk1LhDmnPCuo9UNoKIrMCBIiYERJiiRNi0Q6dHyxGmK436yb9RAZdR4nSRkEwHwJIChq44gmlsFETSBCBAjEhMxGmnNKu30TmwRJrIRw5guwGigQilnmgACNERvZjAaqRByZnYmUppym5Os4ZGgCz/OkIm1sxnE2NTQ0b/MUKk0yhu6MArAkU3XhRQR0E/dSViRkAlqwhtIsCrVVxq8YFQBtKaoDeJv7F44xE4MIROhxsZrWZAi9vaMOtvp+34i07hWngk0RnERCF8A+w7Cg4kmfB7N+ZRL3hXWX+mVt+bkQc5xMxCeojdALqmhgiN6Eh1REQgiQASNABCQVpaZRSmjw7Alsrpqcx9WwmeYxpenDP/vp//6//dFHP5wBYD3AZj2IxSwABinRZy/Tz1+Nof/Bs7vhW9/+yvpydXl1td2mV68O+8OU5iaEq7fffvrqxf14ePBHnHKW4veOx2PSEWKDIqKWV92wf71POx3vMio0McCMaGgizm1DYLFkCKHltpFf/41vxpa2xzuBtL5aNY9v+waapm37mHV8/vK5ymhJWmhX7aYNFzoGf7LoGuSqGNGzFkBgKlhDLRPq+QNCRNM3BlIZJ0Wft26sBl3Xj/kIAZgo57w/7CeY+9Vw/ej60w9fZYOu79IhSc4xNsQwzWNgJMNpyjABJ4TMCgZkBgjMZOQRV87gtDv3fkNgAACiLxxJvwg5lcDmLKJaBtrZK6fXsQ5mO2Mz/UWChzPOZPncJTIsWsZLIPmvEoqcg1Ow5K1v0ieXN2sNZbE+NIRTh6FbIpi94YvnkxagkH1rAFX+6oTB4BlkgYhEHnsvt6helS+FBeYqXxbPkbDlIS3IFACA0S/ges4MCVLBNIBCDbG6ZAFBoZ94wuUhLSKxfy0DMu9nQiT0f718q0WxqtR+xcETFChdk6d3Ls+rRpOngBmMTl2Nv2Ttcqj1L4bgBxFVK/WQUyfn6aYZFKcOIHRPOV+4Lau6Li7U8rXXJXJ219XytJZAv35fRCrdY4U4hnW1LSPPx5kZYFEpUnAEBB0JIk46w1n7g8cvZoCAgUJCJeSKGJouFRt2kaxlOAAgFrmW8g4rMx8RSwEJF6pvyStE68MwLfLGoFI6bb0rsAKUWvBRQkLIJxX6orPuhAIsIlsGiBTYM1NCDsAMhGaRYs4Z1R0E0Mw5BSaWy8W46QmRmtP8UM1QyyBIsyEDEVHt8AEyAyAyNYBQwNckIpJrT6UPOpBZzZQQiRjAkIlRnYhRGk8MTBWJXBLZB6wgADFoBnG+BjAET55JEdV7MwHQ5bCcd+Tdu2UzJwN3FXKyW30QRRqLid1ZwUqJBP2feCbMMSzeo3WS1KXEiqWsoQFQMjNRY0RXBxDghkDEa3lKysAA6PILUgzUDBGYAAlC8OjNHJZbSn8lSdUlhq4Fm6UhkiqCXzJZa9rWIxtXFHIhNRMAMwhEDMjlcXEEJEO0JnLftm0Tbh4/0STjYfdwFyXn1c2Tzfry4vJyt9turi8jUzbt+9Xj6ychNI8314eHXaJjUFp1w09/+FNTvLrh0PTri6tjgjQmNgZFBFK11TCsVwOSISkiECMTIpqIdBfrA2UwjG3X9d00z9N43O8O85RiDOuLi67vQwhm1DJPMZoChhDaFgCabojcCmZJdoTZOEBgDGQizvUax3QYD7v99n73kDlTSxRxlEnUJONFE9qu4xivppuXLz+dplksh7ZrmibJnBhDE1fDwEQNh0mOpsLMl5ur7cN+vbpADE1c3Vw9+dmHP3v12cPty0MTaT7oi8+2CES47obGCGLfZpI8wSxqWdbGSSwbcCBCnDXN87TbP9zf3d/d3us78Ozt7mK1XrcX2IbNavPWdX56/eTu4WE6JkKaD/NmWF8PV43FaZ7G+4McRzIlAFWd0pzMjmmeZL7bv37r5vE33n/3vUdXrz68g07NUSmv4REXtqcBmLm3CxoEwDK80ZgUjQ0AMqAhKwMSGmjpIjtthyWCLjssWV0sjVAtK6srkUkxCgdn4iogeA+LOnnJqNrCmnqvB/qoV6wlEEAwogK0g4KKSinCI1Dx7DMzkKxaNCN9csCyt5yiKANbaMpW6siIIFp0TZDq3glAyGYKamSkpKBUAbhSQ7Nl632TNm8Lx3nZbL2apUZUtflcBoVDAdmIypJES5xTdxfzZ7iQ78tHokZSAsxAgMGdjD3KceFIzSCJ0oyqevzhj37wzadfe2f9qA+rxKsujLGBu93Dw+71BXfN/tWTzdvvv3/zO7/zzZ/95J+OI8QWZTRTAqAq5J78Shds/RQcVuzx9J3LpdfI5c13fv74Eu/68vjLO/D0P1zG7sLqdAmnJRIlPC1wJWxGUGAmyRoppnwwgHVHH3z9q3/7b/1NgtwEJGRAzBlQVRlFYUyTkHTWE1AI2jbAKJFJJeVx7ghiiMPQtB0ApJwm0QkZu3bdxHBUOxwOmLC7bgHHac7396/7hr/y9O2LoTdJfRebPoV5omlETUyBsWVs0AQRRMQgm2VEBiAEUhERCdEahhhRxNAgpYwKgZECGGSO0vaIRClPqCmCsIol2vRdDNrFNliIGDUnUAUFwwTEIMn57yAuN8Mq5HyOwECMSEDMCjqNKa6QkNTIBX2rTgOCmQgkMSB2ZyEwNSZBIwIKHCIx8Hg8JMvOKM+mkYIkSVNu2sZ5BkSoWcXVz0tMqGCo6pGrmUHVcvIh4WoPC4dWgVyABtFJB2wgttRBSmRYTeRhifvr+ZzQtYw7QtdDBc+BqKguei7zue3hjWXRvMZpBkDey1UCa/NC9impW+q1p6ybvF/H/wEUKsXpgxwj8KtlA0Vza5Oa2p6XtswF8D1EB6tbaSG8YCllEPJSWPHLR0RFQzAjMDWRHCKGPs45vfvOe+9/80m2fROvo9rrW/nhD168+OkIEQJg26y6dkPYaKbtYaumMFImub+buz7c383DxUXXXa5W+e61TuM+pTkO1q8bvqeSgRKkDKSISGqaEhBFBNYcEJqW+2OedTfxyExtQ/1xPhIhQzDLIAqaQHNL7dA1F61cXK330/1oh+4qUKC334OUCVQzH8Y5tcdDQEABQ227tsfhKOZZiWFCMgRhYMOQRUg1cHRf9YBuaYVGVgFS31grzWl5CAZYHencbE7MQhuAoO0aMRWB3cNR0PqGh6ZveJfySJGISBrltmk6Zo2ERmBIekiTqIFlTznBiF0PdSG1mJaU2EpJCq1gEo7VLhQY/9M7SctgqJmd1vDrfNT52CjoiJm7faGBglERoLMiD3YeRlhpXVnciMrSXS+vTB8HR8wM3PQGKpN+Qd+w8EJBC3J0PgMrFOC/4MIysjoX/FrUgNDM8VEo2WKVbCrLiJ260BHxFIiimQ9SclENexMBqUrW7niGsHQKn5UzTwwsc7087yaq4iD16hE95odlyVuAEqhOgFW+tCIUhCiqy6faCV4tOfTyG5Hz6fw3l/omKMLcrsVcN9oF2tN6D6HWWssNNSuiOEu8K678XGsETuUtt1frVS8Ppy44UKsIvDyzX3mEpAmJqLSPFXsPRZgl1UuFQqL0BjJ/UFZZYw6X+IWIGYCKaZ7rbgDeJFhuJYICZFVFqVLlqialJq515GNd/uEEb6PDgWZoFmJwq0t/nZmASABAgAKpmAPlSgpmpRuQEQOHENxcw036iEih6n8xGkDOCoQcqYhiqXIIRKyI2TSEIJjLbC9dx4iGKioiIQQIkLO4jHqZzgjOALMZgKoXr9tTmaGC0wBUy3gBNUbiEBjZMgBAQAYCNEQBAgJgUBHNIlmzggE1hET+IBxnASQDzKIwGfcRCIiYKnKoKmIZA7IZBTSDrOowJji7qYjooyY1VebAjCKSbcKAwIDkEv4KAOLeHIwQgksI+kQkv8tqZExAlgWUGEizWFZ1TWVTiIYIzG60AGYnzSmn41lWRCRGBNMsaBBCAHOOm5iIxyI1QTREFFelNzAwVGdvIWMg4lLTQQYkEFURQIoUkBnM0Ih8WSviipbBSSsgVgqNoACUiYEZRS17qIVg4ssVELoTopiaAbKvwaoEhAxGoKV3qRTnDIAYy6JQeCwlZIBAyEgBKQAgD01oO2pbamPYXKxWfaNpfvz0WZ7m7XZ/f3+/2Vx2w3p/HPe73YsXr376s4+n/TxO8+bqYpoMLFz/zmMMsWkx78f7uwfmmJOC0Wq1aYYVxEFn3XTry8vLy831wW43m3XbNQDatBHIsuS2jeuLVYwx9aHFDAb9atW27XScx+OUphnN1qv1arUKIcQmgmBz0XdDe5hSiE3XrQwJOaoACEq2SVK/vujXq6YN05Q4EKKldJScmDEEyjlTJGCESAiU9prNRI2Ahn4TQkvTJDa1MbZtN84KNMcYImHfdjrl+TCCiiGu16s0yXp9gRoCNYHbTz96uXsxReFuCJbT+CDP9VZNJjtwK9SYMFgIGcwsjKOgTcwEEMwSQ45MpPCwe7h/ddtqSxPrTvf97mK9eeutt9t4/Wh9uV1fHvcTKs7HWZK2FmXWaTd11KyIHw7znI8vnr/oV91qsx5TPszTNN73zfDu08u/+t3f3t0+/OD+BTGq+92WOWJeETWFQGxioBIggIJaAgRiI1FVgQysFCAgu9BZAlQiL8YVSipXKdmyyppXHSCjhgaZEYykENa9Rhu8yxwAXDTV+U4Gls0ITYmJA5i56qOXIRCYgBGRsITaCKYqQICExFjsyNFEwLw8XrU5HKKm6lFjKqAlxpCqM+dYlErxFlwOQGSC4ojlWzyV5TubonrkgIhgoHSWtzh3rfKSK00JDBTI9dsArbK31ErAZiV5Rv+/i1LkChSVmi2WRdYvO1qHihnFgjU9cOt8KVNJ8yzcRmopRxPI1Mr99nUeUwttbK7Cxfzq7gerR2F10R1lN453j2/emeDVe19f/7W/8bs//MGH/+T//mjdcdKYRt9VCDCBKWAWAOIasxmckw8QnGBWIz6sGMApaYIvRrC+ZGx9efxlHCdcoRbPl9IzLrCDpyU16LVF1BbBSvE9MDGTAWGMm/5qmvd/5Tvf/YPv/tbVpp9lTzgDJLHs/V4JNJlYgKRJ8GgAoTteXQLjfHO5ur99/cmL10NzOU/StwE5ZZlEEwAQJ2JNacySiMg4xwjDGsd0a1G+8fW3Hj+6yTqiZLCZOwvrKUiaD5olp72RgirEyGbIwYi0bWLOCBBQBLK0fVwNXYigmhRAFdlMNGeZIOh60xnaPKWuIUQLmppg8/71xfD1zTCQynE7XV2HgMIIYKA6IzGAmApzAEXJGEIUCMmSsmEkQxXVgVqkNo2zZAExNAIpFNzlhmuG3WEmTswcIbBhGzgbElNoQtPEGJvDfBAUimAJmLHpomQd88hNg0hZ54rCGHgTlBcEAC1D0YKBBSxaEnE4pX5k5mpAvuJ6zcWkFFhKQR2xdA+c5ecLVdYXxZqkMzMaaBL3RAck863N31ztg7DoE2Mx8KgNAAZmlh1HciNrNGVmQMtzMoMYAwAUXUo/j/dxoi0nh0ohKyl6QR98BqChmzt5AGmgisT+8d426CElEp1Tn/1iHPRA9t0BzRXB0YANTAxEDQgYIMS+z/kBUSHBd37/t777V55CvCW+ZIof/uTnP/jBJ3PIMEFoI2FHGkLTBhxQp3E62Jypg+OBpiPf3+bYjkAQcNW1E9EoSVKaVoO2A1KnwZCaBqzxNDen2ZSbrmFrAjQhYz4qHuO828PUMHfZotutxQYjpSRHtQkMhqZ/fHPdbcI4z68eXh/yro1xvz82m1bnjChMoUVuA/exSZPOhxSbtovDw+1dxgwEAhMFMsgBGwCecgJBCsFEU0ren2Eln6zFLq0Ulzq4zAyMCN3d1O2kzNggGhjcPLq5uNzMU371YgcMDfR01TRtt7fjYTxgJgCbbCbrGaMlybMQBLBJ6yxwUcuiCSoiJgRky45dcyP0rArw1GFzwlxdxuZ06BnR4nNrsftonfAgYO+QLXBwwXWJHH1dRJGsiOe5naOn+Yg+Cl3HtTQYuHvDOTxlp3rF0krn0LFUTKkEWGQ1iPTHYWpeCXA/xbJUIBGCwsLHAu805gpMO9znE+d8wpDPagEqj9rrxYAOSJYenJrWOYZ00rmrrJDTrwWydhiKFBDNqji8ISiCOWHF6y+l2mxqQFQVIcjfC4jeJUdIoglrum8O1xU0tbSmISIHWu6pQ/EOZGhWL0t4Ny77sMhlgfTL9/GxwPHLSnlGPMTy3OjNzmswcCG+MzrsMuKwtDX46eQLg8k6bM+GI2KA0rvB3uiXcy7ec58LUs0MTESWErLjdBXErRdY6hQF/3MEdbGxhFqyVoOcclUxWmBRWH49u0TH+LwDRlQt5TQMq3me1ZLr84L3ziCoyDxN8zgSscfhdYgCMcUQQgjzPC+3r/AOapsbFEcvDCGIiYISBaZIRKZilgI3zjkyRzKMvIMNzEIIIQTfh3LWsvEggPdFkkpWDMB84jSWO0+O1JDTVrncOzApK42qMvMpMqvdarZAsnVKOI6GlTZmRmophmB44hCCb5CK6uiJGgBIcRskoIoYOlmuqiMvzYCqqAaA5ilxTRLrE0MqXoNOT/PiqFXbAu//ExM1Mt8gQdlvZMGwGZ3n6HgwloGBTh5BREAiNBTVnERFEEruWsZwwJST1aQUagtSIY2ZqUp2b0F3rFfAsn6RA1JOyjMqXqE+JtTAoNZZsGaqaMCFtkkM2XlzkSo1NKl46yais0/AiCCjuUJ/fZwAgJoTYFmP/HRkpiaA7FwSZopd03bsxE1iatvYxEhAt3evH18/cbPoYbV+efv6+9///v3d3cef/vxhf7+fQASuL2Fz8cwSSp6//s5XroYLVuTGHj9+0q/Xq9UFIRKEp0+erYZh3Q2a0pym4WK1Wg+EkHOiGIhonufhYn1z/Whzsdnm16YWmGKIMQQDFc0hhn64Xq9XzJwkB8k3m+uhXynQfpymrBxaDmF3t2+VZRY0jKHt2r7vh7bvTDMzHsfj4bhnovV63e1aCNSvhtBGJTXkticT3R+PrSEzb9YXgHq/TXnKIeRV1xESEDchkuFxGudpMjVkyJIQcRynq9UqhPjy+csf/vgFCLRNNCEACmQ5293D/QTEvcaBKQYRShlklucPd49vhqaN4zxO4+5i1d1sNm0fUULGPKbps+efvHrxYtWvb65vRPOTR4/bpr9crzerzfF+fz/lOc2SkopwoKvLzbO3nr1+/fLu4YF+/vEHv/bBer3ePuw/+eTjZ4/f/fjjnz959PT3fu+3fvjhT/7kH79oOkAEJlbnKXn3czZwgVEsDvKF6MdgXhJQI4IAxOaNtcAghsBAcLavIKJkcVeNs8DGSnTjwYWBaiaOjiE5mZGIkUDckLUQrUucUo2iyuIcQkAg35VU1NAMi4VooTA6A5iRAlFxSHfDdC1VJCsAf4l1cMldfEYWzUlX+a3N4r5l2cnTVQ2Yln8B3kryeQOoN2qOp9DpbDOskxcq/nx2YFn4GYEQFQgQCdTqLodLGbAENMAYmBBCYyFTkNgwgahCyomlKUak5lanMYuIKhH3/boN6e6BmWhouxuiLM00Pmwl3gxPv/ud33z5/O6f/I//UN/XQhhTLEQzPN2bNy788yrGS8Xx8/fni48vwasvj7+84xy9+iWHRxA1LTtHuCqXAMHMmjYet4f2qpvu0x989zt//W/8O0qT5BmiGqacp6wTBTRIGqVbt5qnedwT0WZFz274YZSLdX97e7cbd9Tw8TCtHvWiIyg0HRACIRzHfRdwtRpE9OYKVusGYSbN77578cE3PwDAh1f3KyakOOURKMSm5WmeE263U1bgAIgUG+6bZm4mlUKRYAKM3HX90K+7vjmO25QOIbQt8zQnQem7AfugYiqHaRZkC4xgIhnahm5uNul4kKOqGiFVOQhDyaDAEJiCaz6rgBJQYFMUU8nJTFPgpuUQo4ipGIhHRlRbbxCJkAFQRUWzIgESM3OkAExIqGCxa9quFRVQBdDYxNhEhUTCRJVj5LSRkrVilX9UrBSh5fiCHKekGFYpJAYqlqvqn52NiyLq+8Y6eJ6Q1TSnvOot9p41LsTc8jPWE3rngLtYltegJj51IbXTFlAi1DM4qhb9f2HZLR9RULpKJgMAWro6aopJwN4EceIIn3+781+Xr/HGDWUkRCAx50cbOdm7CayK6SDwAF99/9l7X3l6p8em05cfvXjxyfb5yxHAS+k8Hqf58AoxTrMcVYjJDCKCZpxnvb/bHcZd0/Nmc311fXM82gt4nedRccYg7UAYkUIbu1ZVpukIoJZVFJEDEaUpH+4Ph/sRNIJFSWBg6/5inPdpnihIcSMWaLvmyduP4kD32+3zF68sptvtbjuNBtAOzfpiveovmobm/Seb1Xp7N4/7yRAUdJzHOU1AEAKnUSwDNcGTHlDKSTVLTlkzhOCyCK4uVkpBJstzopJiIKqKJocSEBFNTEQA4ery6tFbN9/70+9Dhq5rj+MYx241rMOTcDweD3Y0ATOd0xyASVBLi6A/fAAADEzIJY11n7dCQLWS0lbSupoikFaDnXPaDr5JJjQEUfl8iADgTMaapJxDGpVRWAavp2pLyyEuQxZrAFkH4flH+KWqVt6QlcmPS5C2QIPnCEH9gRZT0jOwARxutjJNDBC1JG8FaDBAM+XqZ1aQIYsf7gAAIABJREFUlNqcvExWg8JfXEDls3nj8LeeZjComqAplhwYCkpSMS63EK8RcoHaT4hS/armD6NiI+X9boxHpe936QoE7+WrGH0F1vG86aL84CXUCkMu0H1KGQyw2jtRlSqBOqKXgbM8cTMH3M+hJTv7cwnT/Y79fx9NBjArolREIpJ9enxBqFCwp1P4Xpt7z0eTneRgl2yoIL71zpoZgGandTEzokl5JrAkUTX3qSrjaqJqANlRHmYOwcwEZRnrJ2X3DBYVF/iXEKtEFEARdFyg0AIWuVtnDYKKi6fTZ8HRJUlJu5YQOAQ3ORYzNciIWr8anG4cutqfK60QMEyH2bjcNzsRCFFVa6MsqPrU0eojWu5FZRMsN7kulxW8Ki+qghlWONLMEhouWuEAVp0WnXZR5rSKqQLzsmKAmpGZCAOqi5q5tJYBAAipb80EZFQLTwYABZn3NQPKZfsLLrtTflsIiGW0EIAjWj7n1JDDOVAN3iq8nKvclKI/tTRC+dLTNI2rVqqqVQ+GIpiHbnzpy4JLqgOUxlFDJEL1LlVGcAkxQBNVJGQMYslLCQbu24NIxgyAQEgRw8L9AFfsAi2o1DJnyG1CHGwuF6/1Z4dFSykQAQNzDECqlswwBBaRLMdA0LVBVc2UOOz3h3V/jE0XQpNN/8X3/vR7f/q9+7vjcU5NC6t1DG1Y9YOK7Y67H/34z22av/3+N5/evDWEZuhX24f99uGhyUM3DDEERCSGQDHN43qzbroW1AQUiNquF2KgGOPw6Prxv/jhD7DjphnaENibwIjathtWXd+3h8Nxnueua0PgrgkYGsRAc2Ju+tXF8w8/6zFAFjKMFLumW/WrrmmPu60qztM87ses0nXdo+vHk81E3A89kD3sDhcXq/E4K2hKGUA4cNf0e9oe9lsAWm2umlWHHFf9WkXuHrZZsj+WLPnly1fbZnfx/g019PLuNRyh6UGSznNW0X7dYwsxmuQss3JjyGgGljXN89UQm7YTg91+3D1MKrDqLi9vNn0LNueh6S2rgWSY9sftZy8+mebDZnW5Xl0O7TrJzIFWq35YDUM/NEO8vFqP09g13dXmMoa47lea1czmaZzm8eF+v1lfPXpy88E334f/449yNkLgYITkpZ15zmDg0pRYWvSh7KSn7a9uiYguX4VAvtAiLtuPLRv8ssQU+hBWqL229qoqVDSIAE0VAZnBEJEQ1NVIwLAwoxb4R9UFRV3MsqDkqqVU5k4ZCEjEkXjUGYtrr4LL+S0xOp7HQjWQf/NvAUrNvkZLoHVjsFoVPA/wzvQOAGsBaNmBF5NWWz6RTsqZZ7tejQ+WO28IXGpyAUwRDdCVRH0dNO/0KMubs3ILmRyBEcT1GJkb1TQejkMYiINkcNcRJlbEp0+fJdrt8wOaqebj/j6DdtivLrq/9tf/AOAfhiDHnQC2xFiYdUhmCGq49P8Xu5pTVnT6Xm9saV8eXx7/2o8a2J+HnV/4RqqFpTIVqfSzIIK56SCCIjCosW63W0B457233n3v6SralMdAIJaTjKKpCWGGSUOixvI0TkfrYvfW1fDOk3fuf/izR29dbbe7o05ClBgUMIuIaWipjTFQcDUhQlytm0fXl9O0v79/fvPk7WfPnq7X1w/bB6SIxA/b4zrCnDBlSsKSgWNACMU+nSgEbBoQBUNQQbMWiWLowFoTRmyaSAFBcxqP47rrEBkA2q7d7Y7HIzDn1ZCMMjfQtg0zYRPAGiJMaSrAivOcAACxGJ0hqqln1x6dqhiYzmkGCqAq5sqcZgJorilPFBjrnUffTxAUAcBEVVVQMmXq+h6Zm7ZVEcSkWGRGeCmoUDFLLXsU1Cj+l6Ykv5DqYDmJn2bxpPr8u2q+teRdv5iulzywRqGnEVg2CiiQWPnpnJVQzkbVIgnqDoLFB/tcarr2t5QPrT997nJK9FsurOZZZ4ZWWNutqirNSbbnlxyIp42sRA1mRAzOTCYDV+hFAMR5PCrkOECaYJrHnGZuw5TSq9vXd/dbQOCWSAJjMIHjdDSYQ+y72KVkYDMYzLPkZPv9KIdj23Fs2qHfPHnyOAu8eHE7pa3R2K9DVFJFsUlVAXNkM5Q5iyZTyX3u8qgyCnFPHPKkCmLgOGsCmwoXqIV+w7GnOY239y9vb++GzUoYTAEDBKbAjGSq2cCSZGTgCNM8sRwBgJiAgTkkUBGbxrkwgzy5AQP0lI3w7OYVyAABvPvVxWMCgJH3GyEREYOBmM3bGR5Ds44GOh4mZm77ZsrzOI6Xl5d903Hg0MQ8a57EsiBaIKYYFWgk73DyzBbBYWSr3CpHgupcOPkTeN5zYpacj/M35hcCnDx83nh5kategi5DpDOw1+r4tOXMDmwt0eY5/vuLY9IAlBQVnVxgy8lwmUAKRi6hXp4IVrWgBRDCkluiW/twyaQ99ipXukBcCAYuglVuis9PAFL34iqECHBEAOvNO60Y/sjLhCzrRi2llAlmZwh1WXt9vzpDDu2UgKshlsYDK0tLhQCh/KqwOH65cpF6W5yDRnXRKyiCKhAtiIILHi7Zgd8MNUXnbWCpA32hV97nHhy+qX32xqO0z5/BDH7xbW/cyX/1I2DdPIr1XHnMn3+f6AlDwApzOva2FG/PB6SVojmURr+zr+yzPLbsqJmr1YoIYjHLq4ZxiEjMDEygWlAfVTWdcjI0jMxM4LbjOYOZc6xSm538lkWwJgk55yySThjtG3KJRBRiBICUkmVN4wwIQKAkGRlR85xhhvEwMnOMgZjNVPNEGLBBSXmxUzQ7ibotzSyAAFzalb2kJlL6TkwFjEIIAGwmIrLAW35hhDiPKcYYgsM6klKGBUJFKJPb6jeh4sZoZoYKOSuqu8DYgi4jILoUuxmKw4yniQEAVrx+RUFdIFHcHtCMCsKM3uiDpAvkjeS8b0RUUydUWUlHhS24Th0hcxBANDIkVjQDNBEzdM/GIZYCmtU25XM8y0SJqIkR1FQFPGRSNRMg60In5c6aOg5upS/V1woiguDlQgBR8Jues4LFPi6LsMdtamruyMnk/miI1VURjZkICchUte3bnDXn2YcWM1aksn4omGbRKhZdF18BNIrNgj8qAJgY+TIhgO6YRkS0Wg8hboauHbqmb1sibtu2a5uXr1+99fa7BPCjn/zwf/lH/9flGuK6HSBwDNQGQbmddmmfBx5ebV/PP54ebW7eun58d3cns8YQh3U/rDfIMYHu9vd3d8+fvPVktWpHnbZ3D2Qw9P2YE8Z21Qxzyk3T/f7v/8E//dkfri7Xq1UfOR7HMY0zqRKRpDwzAeLm8vLd994bt7tPPvmk71YY2khNG5pN01+0Q1BOKTGEi2Hz7Mk711c387idx4mZQ+Cu71lIjJv+2XbajuPU9I2qPf/suULDkS/XAxMS4dCv18PQd+3t7R0g9dzEpuuGFTfd4TASUYxRDVVgHKcYQ86TiR32x49+/jFMoB0AY55NRt3DzDOMU44DtIRMbeSGmQKHobdVA0nS8X7c7sb9DlKecnp12Mv1xapByzkxwOXFRTNEJt0dXx+nh1f8om+Gob2I1Ky6zWZ90XdxTAeKq4jxenP1rW99a3u4//6ff//FixdOEd1cXt5t7wj54+c/f/fd9/7e3/8v/od/9D8dtu2r20NOAnh0TmikkAlMBRGdK0x1X9QyEdEIRIBUEXwOoxUTBCMnz1aU3NdZ5BqsEiMCBxfOAsf3FQFNJZWGazFBd8zAbGiEUJFh8C5nIEKmMgmTgAFS5ECl3TuLiRYNLAZnPyMAEsqcCixVJFRPhg8LQxGwKIeamZtYlLe5m4mCoBpy8JC8kLRBQB2MK1kRgjvBeGMIMyCAlHb40tTuvIAlfDIwqjCfwVl/+wm3OlWsyrqM4O6o6MqE5q5AxaYV3YdXQEUt65ygyTkGity0bTMMXde3maeUg0kgalSNmALEFsgoMjXHLKY49MOAwVJDGiLni279/tV3f/3vwLQb8nRUAclOiUWkYAaqZy4oVAE/35uruOSXx5fHvyHHr0SvwGEFNQBSrh2xHi8TlfyG1AgP210zwAfvf+0f/Nf/5X/4d/+9IeJuvg00JZAxbXeHe0DNGCbaWpiS7XeH2yHwsKYnl+uvvf32Jx999vbNo9s7iO123s2rm8vduDURJuLAsWs7jg13EZuXn7589frh9etPry7b7/zBv/2Vr3317n73+nYX2/jVr3+APH/2+ie4s8M4b/fzPAnHi27YNF2cjrdeWA8R244wWpuCJE5tY8Yq+PBqzJo2j1ZXm2uZxxevPp3GFJGYD13XDUM3rrsXr3aiKpqury8e31xeXHZ325cd8rpZ74/b+/vtNE1ggEaGSEyMPM8jYQguRpHEFJmBGJBYwSDLrCm7GZyhqqELZhmaWU4ZXDcjulgHIoKqzpKd3c8xUgx32wdG6ofe1KZxnI/H/dGoYGeKgDFEQEspgxVhxooaKLrGx/lRSxcVi6p/nMoO9gYEj6f12Qs3sOTVAGAlXP/C0bUk5EiIhqpyoqw6nCUmJt5uslyVM03Oc7yldAS1Wn92mctohy8gxNaPOgnZLIXjs+/oL1VekEuqwpt34ZcfniYTGmHVkiyFHtBsOkNrqw6atwB5PEyTduHPf/TjH/3o5z97fYwdIrSgGJvG0LKoKTQxGpOmJBnmGcat4bMYQ7+9n16+Otxvf/Ts6bvXjx4/ffoWMasYxW6deU54e7u/f7U1hb4N7brtmibtNE0wjfM44XwUmBQiIjKhosn9y095aFbrntomwYFaW98068dNkt1u3CnC5eXjzGKWmKKLEBz3h+P+kGX31pOLw3zsV5c3YZi2o+V9t25jG8BAFSJ3BDxPwkwUmkBFgoYYCYMZgBGpq3EqODqpIFnAxUcChhhqLocU2GkikGx41n3j1z5YbVY/+vFPtMuyk+PxCIivXr2c5mPgZr/fk1LDDRmMY0ZVIGYKCNQ00SESKxiygakn8OCKPICg5oV4hzQKuq/QxHjWRAiwVPffHApIHD1FOhuWOdppxKoBQNYsJp+biSHw5/gHAJBSOh/q6LgJvYmyYkFeC1RVRrxpFiiiy7Dw3vFE8gLXZ1XABdVCLJSIthT7bQHAYDGOK2uBfzBU3QiE0oOpVshI5/0KSgt6dZq8JUjEEyzkTgknKMCgpoJFbdbI1BYyVbGSJAcFKtxoRdzhi4B6WK613BFDMxODLEYqCxhXbvZC7/KxoUD+PYowtt+evu81iyUTlUpO+tcdCH4hFvb/coSmaQBcM9JcFPyLVzosK/JJ0l8NqbZMWF3vzioMxXZjOczMixJEiC7HjlgfJ3jVaUENy4OmAo/VR4CIpDim2TtMy5imIidMSIE5cnDTEARZ7oiZgZgqYFMBO3d2r3dtOf8yeABBRDBnABRRUEg5uyp5CA6eKGgppKuZqHiaUiEKEK2AEHpyVSEYX3sQ/M5jPYrRCYh/XLEtZDd9FgAoy9/nkico4C0U8WI7kQ7UcsqAWrToa5HMJc8QALAoOOGyDiBgeUy+2/pUPtNJqTuioqIiiaFfJ5AWqpWV6U1IRFI6ikwL2lQeIxblZgK12uhTlasMDDw19cfr7b2e1arIqX3IGUw+7b1ndBzHwsDyUqbW+q2VjNFZFMxFQVpFtNBlTVMWdM3NquLHBg0DBmY2ANFEFLxuox7MMBpYNmsri0pFsLT/khUrg0IvlarFUzLtMi2AmFUFARzzJUJFUxMzYMDYcNPGGENKScRWXdM0bYyNP5q26V4cX9/fP5jBTz78GcyAXZcMjOAwTyRjaCOCcRP6oZ8kTbcvtvttbOOmW6djDhgNYZzmScb15ebqyVvbw8Mx7cdp95Mf/vlHH32UxrRerZ48efzOO++/8+zdGNv1JrabdReboJiPsyWRnAPGrukUbJ7mJDnGaGbTODYcKbYM2DUtcWeGh4f9RbeWKUO2Rxc3X3v3K4+unjCEPCUmRoDAYTUMcyKBVijPMI+Hefuwu98/fPr8s7vtdHGxlqdPbq4vNqv2YnURAvXdsB4uVHWacsoCSQTmnBMBxhDMcNQ0z3PftSadqkzjfPd6yz2YAbprRwZLJoSGuApN3zVtaHKS4zgrSIxBI47TOE8piQJDyni/n4n2xDQ0gUJsgkGjxrMQKDEgjHKQKc9pJg2yFsn57v5OZo2x3Wwu265995137rbdH/3xH7747Pn19fXVcNk0zaf752D06vXrftX//le/8bf/xn/wJ3/8Z/vtvzxMwIECBwpRMiCiufcfERZEnkwBCYDQqOg0lqlolUENC656WqhOKLtvZKpGyCE6yKJaQPkaztYKQM5CCMHqsu9LECD6nLPSFb8UN7B6vmjdLWpWwFy3FVGVxMhevsEKXUEtGbl9nnkysog+Wi1++kUsYTfViILLtuQltQW/BwDQUsGjwGDGp6jLrVio1M/qIovuFqylJnaegZwvyAZgVdVwqRXiUuaxEjahl8scdlQwAREIAZlDjG0TuyaEto3Iq3x/SFO+3+5u7+7242HoBuKoB7TMMbQhRgUc55zzNE3HPl4GsL/77/+df/x//ulHHx8IFRkh+6qEorVM6JvcclUI53baXx5fHv8GHB6B1IarWuh2LGCJAt4c0L42wglnLmRDALPY0nzUb3zwlV/71levbvrDeJdk367AbJ7zQWyMMSLpJGOmGYMgZVSFPHVD8+z60Qfvfd3MUppE80FGgg4RYtMSK2BWFW56Q3h5+/L+sD8m6Ft49uzpB998Twx//OGHr16/+tr778bhIqf9NE804m4/7Q+zCHWMKYPtp+39nuPUDRojtcaUICEmgJxBsu2208P9/jAdvkINW0JTySQCx+MExR7ZAGQYIMTQ9bFdxbbnpPM47Yfhsu9bnON2d5/nCczbvd0Gm1zJARFN0XJCCgaoikTAyKpZUyXrePypQFqL+CU7NCj216SiRioA6O5BgSmEcRz7rjMM/pAUvU6IquYJCHMoKZb3Ni1EEVtqC6fji/Ocwm6tVYqSan7BG+tfltMsCekXoqU1LSqkMDgfkrBsjbAUks8v7fN7hNVk95QonWX6S9D9JurkrxWZLSuve9sAnCzky05fOw1/xbFMpeWKtUTINYMxMDUCASRsQ4b5sINv//blzeMhds2D2CcvX97vjlmhiXE1XN59dq9qJqKasxLKzBDLDRGYjkDWNHG1Xs8G824nr27vumHdNN36ov/5Rx/mHAg7Bc4yiYIINElDxyEisgHonOd8nMFcbxc4cMOtJmk2T6Zpf5z3Os/QwdtvXVw+6bmRpJMxdLFvsL/bbtOcBAKaaUBjQ/RkDpLaKjAITfNeJbQYiB1RAEBCY39azAyAScSjmGzZWQJQ0hgseIwqFW9mA1XJ2WtvAGggYgpkEODJ0yfDZjjs9p988mm7ju0qBo7NEGF/FFVJU5pnVGJGEoqIaqBJADHgaaxYEW6HWlB7Awyq/oCuymYAYLSkdKeRCV8wlQzfHP9+UPV2t2JmDQTo+sxQNYyWs+mJzHP2cfW3Eiu+MUgdYnCwT+ug94JjSWcrTKseDNr52UpgWk9V4Qg4f8knrj+zmvLbKSmvtlolULNCpyNFACvMOp+AlfVV0ZI3kASo/y3zqKwuZoWyWTCBgoVBnXP+CWbAJ00yUwA7I8lDxaOwhGyOWauBwxEARSrfv7+Ve+jtprjcBr9472/zX9W0+JzheQEIfvE4Hzb2S+hX8AWD6i/64hvr0q86QtM0RfpKVFRKi8Qv/OPAzA2HEJjZnLRSaFNY8IYCoBCf8Wa9JW6BbPyJMjMzyzgBBPccMNdK9NVci8OWZwgiUlZVLPX2AmPU7+qYGjNbFneABVUvKy9N4D4D9LR9wCn9MABECnSalgjEXISxBMQBHgUwIGDJpnlOlM1MRUAMoQh4oZOewIW7K3xMBI7LGWidY0SA7G09JCoLtiMqQASAhVBg4ERKoMKPO83QKjZlCz5cJgCIZPW4w0AhByAgRTOsTZRobpDoIk9IsPTlE5gBOe5ETo4jqlZjZahVQkShJIiZUWAXAPB56E4T4PHGiccIqmrZ1aCJ3N4FqibOWTYNYOorbtkEXMEHmR2/UxMVEVXfJcoSjuW8mI7zubsZcakGoJ0WXzMolrsl/MCqPFY2bzLU0r5rIJ4Tl03AoPI+S6gFCmAGKeWixE9cigMuxODJPxU43cwQyOwUJlRFPFWXsmMkZmIDRCMlxhiZmdREU1JNxzZcrNeINM952t99/Te+Nu7Hh/3h+evbjz9+BR2Mo0yWYh+SKYr1YITYdQ1FSHm0LNv9fpynR48eQ6PTYZ7mGdC6NvRds14PD4fbP//xn6V5/pN//s8/++xTSRI4vvfs3c9e3j5/+fJrX/n6W28/CzE+e/R0N2732wNH5hgaikqSReZxDjGuujUBbx/271zf0DoyxptHbzfdcNjPh+1xrwxmm83Nb/7ab3z7G9+4ubze72/RcNUPKc3H8WDZcsrduj9mNYOmbe+29598/MnDbnuckljuutg1fNG3AJyT5CldDGtmfvH89cPD/TwmjM0hZxFxtrGpzPPUxYFjjwgp5XTEYR33h0SIyCyUQRmzAaJlAiHJcBin++0RidcXwwElpVmNkBhRZgEZFWFCxLSKXb8htF3aE2qL8zSPiKHhdtVT1+K4PW6PD9M05yRpkq4dpjyuh/Ww6t9+++3f/I3fEMuH/aFtIxKthv7u7uE47X/w4395eXPz9/6j//y/p//5xYuXz1++yooi6h4fZboIFKyFyBvgodYQChRtZVL5Msjk2YVYLQsv1sWnBRDQAEJL6j4atcGQiaE4JCzd/p6JlJ3RCw2+AWQVkNKlS00gJFACs5QSEACa4/IGQOySk2hgJgoCQFJ22nPRWWdgmS0Xm89ry+QRG5pp+dZWUG1iMCajSlOlmoqcqltoiMzF4sqdGknVyfkndrqdvnSxvTU4z6neCPcMqk4eLLmIecxm4B2GCGiGvhsac/byIQIxcQhImJNMo7YU+q7VFaqk7afb27vbh8PDVdcGbPtuMx+mZCMDo1lEBI6MaJa3cP+f/Sf/sczdJx/9r69epxLJeteDa9WgkesDlQjRt8Jyh9/IFf9CgcSXx5fHX8KBtvhBedq/pA1WwQpEtCoSsuyqp8yp1OkNEASkZUh38N/+N//gG++/qzYpziGK2Jx1nNI229RExIApjYqp75thaCLOehyx79999Jh+c/XHP3m5e7hFlKGPc55WfddGRszztJ+madUMTctENE0CBB986+1/66/+LoX8ve/92ff+7PvM8Oy99avbXdb9cNHOeZdSzhkAWbLdP9ylaf5/2HuzHlmyI03sM7Nz3D0iMjJv3q0WVhVZJKvY7IVDNJtsdnM2NTR60KN+gB4F6DfoQU/6A3rWuwABEtCCIECCgMbM9HQL0GDU02xwNM2tWCzWduve3CLCl3PMTA/nuEfcW0U2WwLnqZyFZOaNSE8P97OYffbZ991eXZ9t6X6RMvRsljVjHOmwT2PPV1fDs2dDPyCEq0+e3D64XG1Wa3gyHYmQdVIbDenR4/XFvfub9Wq7htrdlIbYBmnYYJFpHEdTA4EqDwAewByK8IOpwxBi8LnkUG8tuQTJgxaJZTIqNcpS5SDmwvJHdlPz6MaQYiXtrllLbW9KSVUtqak6iJhcbampCFfR0efkk1GC5xdqtp+RYKNCnIzSVlNWsiLdikrTWH651iaAF3KleVt88czmIEagJYnEc8lb7S7HvOee5Bo1/q05uxN8lg3x4wZ2DH9PU98jPjajelQBqpMuQswMgDkXFzzHnfk7jvmjloDbuPSyz1WWkvlodspgvbhYfevb33jzq19IOvz0F+8d+hTa5nLNh8Rn2+0nP/9wBNuYp3EEB0PL7q4OFybX0WCBqQ3chig26H433e125xcS27g9vzf02T2WglYMiIwmxFXsjNwoZydSTpMKNWCyYdIoLKSeWMQwGaduFbvLZvtw25z5YHvN+TBMPkSKTT/mQ58Mxmyu7AomTBljUuKojnEanVwiQ40jYwVh6Q8TqQVpLWUjJyNN5moozty6EDhKca1kz+AoFElhamaWY9tAYGqqGYAERoM3vvRGovHpzTNEjH169c2XhmkE0HSxNLWwCNzzmMVDIHFG6RRxcBozE1U/cnbYjJ7xMfCY3Q/KqCiizA6nXHK5EouUZpxCqD9CJijQ2Av8k/lFR82YakmwOurUuYAaSKL8evkZR6yKaqJKnzHHvP7do9awV8j4hQHrdTaUz1BRG8xTvLaO1zer5kpQOJ3+VS+sJqdux7Bx0Y4yVHswUIV1ZwCrhoPHtHjOIonIC7WpOMnTbE45Z52o7UllcSu2dlzNQee7604cZIGa3N2da4JYjopCEjvIZ75pYXuYLYXheXLT8Vb7nJMfMfDjNwRKKVnNr22G5uZnc9Ky5ieIPD6bwYfTd/7mDncPSwdfaRKb1+fjU3F3mJc2iBBCjLFctKre3d2WuLw+R4JzSaa4gFxER1krm++hZYW6mlry2fCRTorzjoIdlS4umLvTwttiJhFVFWZ3mKl56UwjhWZVylRhtRl0nhf+WjufN4qKu9VU5+j76cdCvxEMnmqyB1Ax2QOgNnsXoqZMhUVg7ouK+bwZVYwN4wiuP823HwafZdylzvZSfWGYlZYXOCFwLD6BWDZLomIgCFRfh/KdkfNsQcLEUaLZRGV4e2mapoqY1fyt3g/hAJCrotqCCYGyqapVcXFTEEQEBHUl5iLfVDzE3GCuVgMIYkCJdXbvI+LSEVgeiAgBlpLCQFL83amasFLtRrZK06j+GKVXsHz62naa1eYEmSuQDHfnwM7OdXGmQBEEMzs6RTDRzLN1ODMYMkcADqD0W9UEulxyVhVm4iDBqsUkFahRAXcGQ/N8S4EyQZgYZShRXdKJyIEyyxZ9PAeI530hEBf9Z3IWsnIeCe7qxkSUVUWkYH/jOA67fZDwyiuEem1pAAAgAElEQVRf2P/4p+9/8MHkGYJhTOigZs6IMSphP41nmy6umjNeJZqaGB0Q4QxTtylNDx8/cqbze5cf3330k1/88N98/1+nlM20Pevg6JrOIz29e7b/Sa+ObrW+//j+V9748nsf/qy/6xlomjhkwuSmGhDuby83m2323EnLJqsQczY2dByTpbN2Pbbjbrh989UvfuO3vv7649eeXj0JzEoioOS4vrre93ujxIHGNLRt50pw6odhSqldtaa22+/udu2qkbNNd3e986wmdrbaHvbv5aTjtKcmj46cssOJuewSOevZ+UbVbq7vQuTp1pommkOnTNIwB9UMsmlU7IbQraZBYSgCnBYVxCE0Lpzy1A+JTFV7iRab9e1w6BzJ2XJqKUaJgWMbFcxmdu/iQb/r+zyu28355VlOdru72R/2D/Hw5YuXfud3fuf27uZmd7Pf75u2cUOMAtj+cPvXf/NX/+y7/9kf/sE33/vxL9752b8i1ovzdZ9MmKeU4U4hevE9KnJ7LmbZhUWkCIGUBhEhNnYGY6YxLyke8RIgU0XJS22IQzXkLIGMF2IWBQlOdfLOu/3cX2+AFAMjzH07AIpWsC9h/Ex+n4MMd2EJIZjrOI1tDLP457LtL8gxFgpWdU1dQpdlS5uBtApLCyBWughrjkGlPM/VkLRoeMLMxecKtntRpHeo+lKPrkFAQbhp/jCYF1uaDarnfLvEHEWnQoSYXD17Zi8qVHByhzWRQyAPzMTGBmESASHlTPAppWEi8/W27aSR9Vnz5OmHdzd3cv9VyyZ+tm6QqCeYkUpUMLeybqQ7DPvf/upv/cN/ePPuj+/+9H/+F80qnW/vjYOGIOMwxqbVcajJEpPPVTfnebtHDdQ+I0f8/Pj8+M0cn4YNTvDfk++Wt80LF6rHFXnF7Qsg66tVZ9kS5e1mfXu3365Xzn33Jfzjf/Td4Jm8H21oW1MfDsPN7e6qn/rziy9mT8xORE1oHlze2119pOMUDZvVJrTnP/jxRxddG3nfNXy1O5zfv9Rp7PtRdTpbdyEKsQvHboWziN//1jfalTx58tFP3/kJkV7eXzn3EJIwOWxMIws3TWMu5vnutk99tgl58v4AJgkc99PQ90lTc3U1woJmwGAJh8Poe+savnd+r21Z060IzLQ/TEb55ZcePHh02cTI6MlCP/Zt8GHqJe/vr4Jm06w1/9OSbQLFnT4rQBAxLU0pVThizrTKil96ywnuUK8iSQC8CNTAzFwcBgQpWntm5skgknPK5q5a0ce5YqlAkFA2hRhbIgouRbH0mIP56aIL1J5oBlHRaS0xmy/rNM09BWVL4LnaUla559K858CxJd2tO0E5RxUrBqhoyBqwXE0JenkGl4453rx7PXdulO1Un/v1OpCrMqHP5Ipjl6DDzYrp3HIucKnquFf+xbxXo6arRyrNzHum068LAEeV+UWmGfUs9Y+YKVxDcE0Ia/ry22+88vqjn1z/4P2PnhjCZrva9dPdszENGYZpmMicWQxmqg44MVhMkxH6Pk+TQwVo+v3klA6HvForMb388qPDfrq9mYbDwdWK20rTNm3TJlOv6U9p+59ABraUPOfRzdJh7zptH64fv/Gg3crkQ5/7Tmwy3/eHYSKnkA1Tsimn7bYdhzEnLvS/nAnAzdUuj9Y2qy52nJvNvW6zDnmfjEwERuZuOSeazN05CLO4Q5OVwtnMb6nEGCIXkZLLSuQCMzC7AiCszlebe6vQ8v4wWdDtxeru0Dt7spRzDqEhUEqTMJvbNKVotmpacMjZpiHHYDAYA25gKXZ1x6nh4BrlFKx0Xlcr1lnx0SOxYBnE8zCbF+G5OucLe6Hqb86zsXxZkKojdrus1MvAp1MsY168S6xV0nNhKYTLGXdAyfextOHMZ+fjbKX5tDUMPYGDj8ivJp0xNdB8SUSnDtOAH3UqalxcZoYta1udyjaXIamileU+LWyyIhQB1M6qk79gM1TEi8fRfKXzp6t2YkCRdfJKqSOYE9irq+AJ/Efzlbm7WYW0Z+R+eRBMFESI2MxSqVEc78RzR865qMDzUTALVLmHKOpGJzLlfz9wik6H3POHnyxNmEGn02Dg9LcWPK58E6Y0eWHwLorsZaSU9k+pQnXlbAU4mFd2Px3smFfOZImtthmCyNwKo8dLDmSmZuoIkdUMhkUJq8BWvjxyd6rueHWCMVfcN6VUbweAIkLP7DyrR+H5e3S8uDr0ljtR8LGT21RH2QLfzbOiTgzPiuJ0WV4FMD9wACnnsqX4LN8oIjQ3+GAeCjSXm1QNhCJuVXhtRGbVLMuNKyFwNhA8jhzmqrtWcdhZacvcaMZ3amNdSaAc1U/XqjBc+ZzMRCxlnQvEcM41UinNmZTVioMbEYOMpPpumM9kB6u+8lWJhgwEYXG4kGRXGDGJCGVUThkxEbOppuRcvf2ISCDL2sSzMepczDKzqs1SRyJVMqSfDujyiKUJ5rrMw+PMmZ8yEzkve7TP/zffWHMr5mdFCIAcTqpKmWnmaBSj2Go8XCKcRRR/Aafdvfgjns7becWTWWmmaPYX5LdwOJnLxRVelxu0bRqOxAEODyKrVde0rYi4m6qO47RenZHL7e6aJWzOV/uhh0PNIMRR2qYJLG0TV223abeTDav1WkSyeYgN8aimEuPZxSZbeu/Dn//tO//+pr8lorPNBtHJad2t27Ylo8Owf/rs44+fPpAGX3j86jAcrp7c7g/7zOrJIiIzN12z7bZtszK3i812220icJiG/mavB58mbUP3+PzylYuHX/7iFy/OzgNxGkYXYziHuN/t9rd32bORjuOk5rFtEzK4Mmfark15ypb6ob87NOfbM+YobQQFqj5KpDlDcjLklEHOkZg4xpAmDSx5zFfPrtx8HG2z6jxn1cShYxKDO2wacybbXDTkHgQpYRyG9bYjQoyNQ9SRcjJHaELsWuliP42T2ZRFU+4kdLGJocuOpL6n/t79h5k028SZKWMa8zCM5IKIsJLzzapdPQxNuLm9btt2v+sZJEJ50p/+5Ef8Xf0Hv/vb7/7kvb/4t//q+gPYNqcph1jY24GIzKyYDDqDjJ2JmCA8N9EsM4nmkY454KgzCoWeebJilhK71zWzLmDqVpvQuPTzKnGx94QwmbkW2wqSpBlz2OSAqaJYNxR/0Vo9+9Se5MiaA3GJ3pdd8jjVy+QiOt3+Txf759b9Ej5QkROuEcYcHNUQrkzTYsmiWtbHuuJbhdjo+RyaZt/4etk1QwEKidOcZr8IKIq2YFlnjWu5vOod+Lz3hEBFwYsjeQOJ7PCUJvJArlPa02AsuhLZdM36/naycUyjIDiREdrQio/JBrcROpGyu5A1wWCGt7/69td/6yd/+r/8i2nC2RlGNofBlGOj88roftzuliVyHhl4zqfx+eLe58fnx2/8qIHAr8BR562/RrV15pZXCgQTyLNN59v27tB/6dXLP/72N9soKe3dD2qHlJPxuD9c3+6vxjwovWqsHFkgQoFXZ+lwZ3nSKVuTA8vFut2uIsZko29CXkUek2eyVbc6W3erpt3vD/10/frrL73xxisQ+8UH73308XtG++09NKskod+eb0ByGA9RAA8WWTMlNZ1GzWgbCMEVTbNi9h0Nw2FSTbsbC5HcOAZarz0ndrehz9OUz89bhC7rYUqTk4WAtgtNK646jgNzHlMmU3gOcaIVMUuxLWYSuLul2ihe7qQDmMvAleXuRz3yqrd4JAiUW72s0rS4oXup1dEMlIBYXLX6qM9aq6CquFDIXEREwgSaU8pjuF7sjRYOSPlaVUeK+HuB46kS5J8fQVQdTir7oNQ0KtnKilvT3LjjBQGqVe1KLSlrnxfLsSqx/Hcshr8ixyvr/3PjuOal8y+ebt/Lc3H3o/LJEZOoeNzSu3KCI3xqk6znXzavFy+1tMXVrBzFqclAHIEBYT1x54j59nB3sztk57bpYsPu4+3VDRxuKsTObKaqmZEIiByMjDjnZHkyI3GVScEZ/ZAOwyAs9y42kTNcp2lMKbmBDF61eKrDlaZMDInVABNZCS5EGam9iPdfvTi7300YcxopJATONg0pjdkVk3DHLCI5hJjTZFrRnKtPBrDn0QS4t4mb4BKoXUu3iTd9jyBBAjmnSaHunkChjE81iyzLTSaglteYLSeDqbt5JpBTqsOHETdy/+V7r7zxygdPPjC2ZhU7b3vr+/EwTL1wWG9WIDrsD/DTJtoCigAKLTkaaiZUQgwQoMfHftzJUWZjzYC49jIeH3eNsbyCNsfRiOfhhhIFWaW+MmYaD2pUcAI+PT+cTmHZ50cgjlDM/CFPEusjzqU1AivvEhRoB3OUCJ71b4pmjBfR5gXzmlUm6nRdyJ0OL0x6qi7eqNHaAkWyudaPNUebhQVaMlCuFmAEPkX5KiPJchWbrp/CqFZtjRxu6l4WnAXGADHPAkw0B7w4WWoX151yqcsUXkLQcpaqJFRvPVVAfQ6HyypmXuL206GCk8WN50r3jLb7Z379ZRjT3/dYFvPTc376hKeDdsn6Q5oSlnyg6KgX1z9XwEt33vLuSfOY03FPmt+PWQMe6qqVexVjoMUcdx5JpaWeCiJilfpU/oTpUZhFpGCQlcdIKFa8RTSckUznW1sAHhGhGDUrgaBOAmZ2loqLLaAWY8H2ypbMsZLF3N3V4MuO6Xh+g8Hyzy/cWGYq+MWUSTg2sXyccn5TzTmnnAu6SmACmZllhZVUgef/llWKTrK2ukgtvKrlYcKsuA1SqIRhre6YcC8uX6ZG69XKNFtBOwqKTE4MEnLi2lVS3Ot1gfPc3EAQczNQICYyATGLBIdrNgIZBbdsqrkQWVGzVDcjhgdG4SQVASnJSoZZlj6bIwNcGFoFsmJIiZiMSiJc7OfdE7m4i1eImZjJjPjFbMrdza1pWzW4WuHVMcspcMnMMyBp5iaoatZkDjOOMRVgEYVLIvCAlB2UkUXYuYCC5R4ZSEC19OtaYLEZU6vLxHMxSImYSgQ4/1Olznntc4ZR8Y9Qd6hZ6HB+cR5aTHkyE4m02WxWq46qIJ1oSvFMSOXqDl2bX3r9Zbt+ljU7I2tip03TdefnawpdXK3aVXvWFMDr5vrmfLXd94d9v3t2++TVR4/+5ff/4m/+3V//6J0frjarpm2MzdzTODahlZU03IyH8Wb/9Gc///H1zSff+973Ls8vz7t77/z8Z3d3d6ON67aBoFu13WYdY+xW3b3thaXp6pOnh8Owu3162A+X5/e36+0f/sF3vvDKq/e2F+S23123In1/kGgxiqkx8dn6LNnk5kWFnYwBkhBi6NbrLltTCgQ55xjazWZrmt09qce24zHB1YygOk0JZA2RMDdtO/VjCHK4S0+eHJDBwm7E4MCBUPlGcNO+NPRSGxuJwTSNU85TilGapgmxYWHn7GpdE9p1gyCjJu9zP4wHRidhs163ITeSGk6B5NndDRGFVYD4hAnRA0lK+uz2kz7tXn/1C5eXF48eXK67NmW7eXY7DgOyec5Tf/izP//ffv8bf/jNr3/tP/qj7/75n/9VWLVMfL3bc2hFWNUBRdEZITIhUp6RbV5WA1NXdydVNy5my8x6Ep2oal3n5+JPCeJrDa8sRe5eZAKIWgnOwsJKGZRBJEJS8Wmy5MSA1OqwLRjQEv3Di81NERGmI/kLWQ3Os8Iu7KRgaEzCwals0yX5OVmQ54yqiGC5mVutk9cPSU4sxeYcRLDaZl7qGKbmhY2wxBwnX08n8RxBHKV54xKqWHU3XSykDQCrubEKBZQ2TDicDFYLQeNwSDSFta83MUQyqIKDCCwNB3NG1/XjOt67151xG5nMlRCY21buTZbH1LvuXfvgQ+BgmZBXTWzGUb/8+tvf+cNPvv3tf/433//Zod+5S3ZnIrhW1UCqQr+orARU96lPpT70y+1mPj8+P36DB2FBnl+cjjOzwOHGQqWtjalY4BEh5ckILSHd2vnL3X4c/9Ef/fF/+V/85xEuxBNsu15lpN2wu909vb55wk3c513XdjE0bhvG2DSE7aNpuJn6oVttG8bvvPXW09vxvZ/3d7/4MHTNx+/85Hx7seIw9NfvfXL38uNRpHnrzbe++Obrb37ltb/4y/8j5363+/jeZZdzkphjN603HQf2PYuI7tWVTJGTmoEhoVRjaQq0cRDTIJiARngfEIQFXVxvwsfPrplxd3vY7+KDBw+F25u7O8Aev3TetW23akzzMIy7u7s25obhnKZsTZf0DOv1WQgBJYQgN3dTHBPHuYesrl/kVAKWUk8FZvbCMV2tlbsSr7s7ORRgmGpN29xhHpjUyFAiOyvpFQGxaYgYOrucFxymBH+VMlwS5qNuzhHAYnY4l6dOZFQZWCV4r5fDR81Rd6++6MdkiQKfVknK16qRWEM4Qqm2Yt4JUUkZxzwcPpc0/j+tkLXOOicgvwweewHKrW7mWhyPapG4ZOZ1QyqF+pO0cP5Dn3F6B0Lk0l5VSSNqzJGFEgYo3v7ma829eDVdX+1ubm/2N1c7jg05ifEwjkgg9xAJImawrMkndjRRjMVJGdE1OAd4GwM0o+/H3T60TYR2QaiLYd3GQyuWcs5QzU5Tt1rxxdb9MOxHcidVM3MFBMXo7PU3H28u1pvLVW/7T26fhI4uzloKOvVTMufIwkE4SIiqbSA4NSVrzWa7awe5ZpjBxis22bYW2nj/8bmZX6WBGhOXlBWkCACjXIFbltC5E9tMFIIBMNdkSswsDoYHR6gG97TC+nK1frBuz5u//f6P7l9ctF3rgmyYckpqEhBjCCGGEHPOxY0LuhAMHYBlRCGCgKR0TjPBzdRn/IKLRAyKajusOHRBqqyXn2IQv3Q0eonWnntjhVW9iF8f3duWoXU6wF4Y2L/2QSjioVoA67IEQY5ViYrbZUMpiZbrJOcS88GlOgp5aRGaQ8STPaSuO6VVqN4rEMAkVIBDYidIYIWpaYWIZEnH4XDDTFtdpCEqGDjPnrkToC43AIis1E0VKIy2WQsEVeUHxSUCAJycrIoIWcW05jJNCcjm217kkqxi6oXwRycK4zOhxdjIFhy+pAbw2RwbZs4nCJrm+kCXnjbM8Nyy/C7fLC52n/1Qf+UY+DUBrBeO8oZQMQsCiAoVqPLHEnQupC/ibQuLrLxtebV8EnNzWlTXISIsrGY5ayECMnMIIcQYQhjudj7fy3pgxkqXHjutOC0XOIBAxfyudGY5tEAcSQGGo2g2EaFcoapVisyxDQSk7uxL+lGROPcqjv4rbxoLe+FbL1OiaCeZsYhsVvUZcLlSdzPVrGbu3jRNGWq6OOsJAVDVaZoWINrrX6jkJsBrM9rzzw7zxTOzlTeZOeG5d1YtgEAEN3XTggcagxxC7OSWzZiEybJZKmZ8hf3IIEgI6l6QQ8wNfkWUvTaKshDgdZVR1HoYaiOSA8WOzNlYlJ1Qu2nqLCxxiVWyKIgUruQtiUOpLLjFCnB5gAVSLqfgmYK6jKKiV4iZtOWmri9MjAXcJix0lIV+SgyyOV4WFsDVQe5iJAIHE6BuMPZZHaeAquq5LPeYG7m5ahMs0oAAEdMCi9bQB0SKrGURYl6MOZyc2WOU9XoVWqYRORMbmMXUCBAJm83GDY3EKA0yBkITwqrtIDylcRhMFI2Es3YdDUwiEGZi4ilpTntNdnN7s9vf4go9+n/zb/+vdz58NyNTJOXszNLylO0w7ruuXW9XRDH30yfXH+33t9fXN2fri6+++XaQ5mfvvPOLd9/nM3780uPz823btQC6tjtrziYfDqGPZ2vJDae7Vx6+/Oj+w8eXD8/aFVI69P1hf3e+PWvbJuexP/RN7B5cPoAgIe2nvXqKIfIURLhp2rbrpnGSKDEImItJnZP0Y2+mRtR0XUyTB07FHs/MXC0qCzcxmA0xBDLgAG7YCZqV2YOIgZCXGhBAaGJEjAqbRhuHPBwmrJrNBjGQtrRBdBiTZ5+SUhMaUDBN/TRayJwVoYCtTsBNfxcRVs06ShMbicyN8zTl3d1+zMPT60/udjdfePnVy8vL6+sbqEUOrpbHfL45u3n6dDzs3njj1e999w8/fP/JX/6fP5YNmijZck5GTCFKnfRcbLgKSF7rs5Vk5GrFqKbI3hXsHsvGapVqyFy4VGXOLchvLeDNSQ0V9uXM1MmG0iBeNFCs/BGemTsz+LXoV82TcW4AlqP+oFtBv7VOylr7YmIydxBZsRWuG0AVUMRJ/3d9gmUWngIxqA6Cs4DIAqoRsEhyzisSltz4xaMS0kqButQey8Su5wFQo7oSYNCc5rgbu9T8hIireaunPE52oNabtms7ocYDfB3bVWzyaHAEQiCapn2ylcTI9U4SeWzoPrMhTLBD8J4kMZA9CdamsYutIH7lS1/5Z3/ynwz9//79//vHvM5tu6Eghey5BLMVnKrB4QIIzqpmR2efzzGsz4//wMc84Wr6UmffaZxWZtvc1lbQK63BVIkrzNX0w4/vvvet3/3j737761//2jDu22AOdc/CbJ6GNIx53KziOPVtuxLEhjrLbqpN7AJ5ymPKeRh3L5298vWvvHH1bLq+/vDpzSSKLoiIDHukCa88fvT6G28+ePhIXZ89ffbs6pMQ0XSrKFh37WqDNlhO+1a67Xp1NU5pnMaDmoq7RG5N3BRMEY5+n8cpTQOYVjGuN2sX7qbBk05ENiW0DVSRUnZXESJK6/Xmtde+sF6vrm/u9vvb/X7o9wdtfNUEC96oq8Ed27OLGCIMEBam7AyzRS+hLtmFnVCoRlbAm/llqpjhnM9VXkb13SF44W1aJTFhLuMRSJhBbrASOJXYSUqHi5q7M7FTscudnUbKmmNOFZmpVjyYyQVMdTEGM6hKEFeWfSlb1vVtDhOPXRdVBXLOxJZ9oQ6wBU4qhkaY40SfUYDloHl5LD/Mbfc+j1kcv/l0SeT57K5kwaUP7AQ7mCPVhadCAMjMMLvKHfMXf36K1BmCCkz9CgyLSt/MfAYHzMCzu2KDP/on3z1/vP3k7unt4W4cdbcbSQ5pjAwKTEkBOFXZWphlUmIKcLekRCQcgzTKEB67Jo6WhimtJlt1Mg27KM3F+coUOavb7dDDMRlNoe2woaZH6DCMRhnmgCBEhIjJ8YUvv5RsHHx/M1wdtF9RnFzcXOHSoGkbBzNLDFGVx34kkiiBqcE0rdZbJ2ie0jRoHm9vb7XRzWp7fv8sZ7t6NiQfsidFBhMCz6iNYRYRdofbXIQu+szsEqo/nAucHBFn56vVtmu6uEu3h/d3TcDt/iZOrYuDERppTdz99vY2xkgEbtjHguBS0lz0ZCSQqxOYvOTC8JJpOrvVih6pk1cMp2g/kzujsn3sefTql23l/jx6dfL+MrytBD+nRMHlxP4pbItmStHfdVCZt5Uy5oA6dIZ0K1nFGVKQwvIbfIIYk8E1z07TcC0fv14e1RlNxDNePNPhC62g5JUMIhcUgodlh1XzLZ/FkE8Ip6idyj4DVXX6Fu76rOB4BLqPIVYJ4soPXjq3vBBByrWVRbLgKlR4HZhvK1XEvKxm7kZW0S1TM6LCnDxdWOpaWl6hgpss17JcZT23l45rmnvynh8np+jVgmHhU+vY3+so963cQ2b+1e9cbjURhQXwZ2bm2uNWbSYdRXdOmKvhQrnu+eqfI6vOiybV+zU7G7qbmWVDABGJSIwxxnhwIyY3rxQed4BEhAIRSKshYplzwKyIXeSRQkHZiviTIqdEsyxXqX8sIKK7M9Nx86I5+qnWdY6ZilU/BsML/vLpie0QYTOzmQ1IAAch4myZhLv1CsAwDGNKmEv/TMRBQhPZoTrzguY/6vXmZAAkQswhMBFqN3v54OZciN6l2LKMHSaUT22lIVFJ5o45AjMXgJkNZmUyz4O87usEp5SUyE1AyXRSyw6CsZO4u7fdSg1MMqPetUpv6hxIeGHJFamCas1Z5qapgrC0JokwNZGsqrCCai2PIUShLn1FqLMmUzWfcsgRFZofSmlj8tLnbRVJKi+qao1QigS+aX2+c+uyuS2+qks1jxavbZIo7ARnZmKDogj0swixU1lbycxRDTLAYCZWT3P8V/LgpddonhNEJWAqem3HhYhL0FAtllEUAGHMLExt05Y+1BACkZM6gJQTg0TCZrtppQkSV6vm8hz7EeMwBYohBs85OUWS4MzZGRxI2tiRe4wtEavmYeh3/S5pgvgeux++8//0OnnrQxqgODvbtF1n0DROh2nX9CIuKU1muZX43rvvvfLyF157+Y3L8/sPLx/1d0OMYXu+PdtsYhOHsbchTz6o2brZnG/v0QPOU3r1pVdefvSS5XT15JMSAezvbtZt7FbNIY9DP67W3Xa73fU7chIJkTzEGGNcrTZnm7PR0odPPuhWnUqYePKUb2/v0pR2dzu1vEqZYoxdixhtzKIuxIAFCSEGghDfLbFvkDBNZlk5gCW44jlGD5UZigLHsGOaEKPlPIm6+yQhi5CaTlOGadici0RyUbJEOYEjOBMFZmU2obv9/vrmppG43Zydby+a2Di5tOi6VjG9/8HHXdudrTaR+PL8njRx7Mf93S5Ik6fh/fd/9rWv/d43f+d3r2/v/vKvfny2ahMsDdmzUhskhFL/m3GmEsmUpa3w8M0c6paRQVBwXR8wC0OW6UUkxf9Y1dTU5wWYUGa3W90xGSicVmOzSuYBCFyoiGbVLWlZh8m8bt7HvaoujkRSqBNWCbhYiK9LtM9AaQARsgK8mZeaJpUuj2MERXVhcdTgoCBlBK9w+BxAzKFWSXl97jw6FhKk0qMKEGWVdu4zeZKWDG++yheCAGYWmPoSCcKt2EFQFUxhgcOIXCJ1m3a1aaUFBY2BmxDJ3TQHQddR20iMgCTAmEwtJ2iHFlgLYsdOYVTuY1Ry1ZiEJBm6eL6fhkcvvfxP/vE/3fXp+//8x3xGRESRbS6XlaspkqZHiLF+qBKa1RXyiGE9Dx98fnx+/AaPuo6U72vKccwdTtU1EgsAACAASURBVLInK0vELAhYRmjhoFryszVuP8F//Cd/8r3v/pEwHw5D3HLKw6S7ZmXTNGpOIcr6bJ0tO5wRCN2YUt9nmMYudut4u7t5cn3zxc3lFx49+M7v4XD9yQ/+9hdPd5L2twn5cnPxW19+/Hvf+MYrr76+P/Q/+umPfv6Ld7JBmMAypf7y4t7Dl1ZjupuGvTCdbTcf9Pv93bS7U5EVcwwkENdpYhOd8t3tcOj7u9up77VrOUgXQ2c5hTSV2EkEIcJdp2loGz8721zcW5+fb1ar7ur6+vrmahxVU3bz/mBhzRK6GFqAz8/vxdCVHJyIUI188OmuuLKvYJ7yVPV2anUE7oVCXjbVsszWogCA8mJN7uDElpVAQlRYQQwKLJBZwLQAYWXbqXIjs3C7E7md1BlRKoFFf8IrsgMyhxxL6DP5ohKBa4piPnt013SSyErN/pgF0DHlLpIyJdlbYC2rfjzH6giORfJj6lB/ayZi/Ios/oWEf44ZCUuRoZyvjPoFwipFEl8S6boVkgJVo6JG05UIMAedz33Y5w/TTOxld6uRRGHTRcDxrT/61hQ/+OjqvafXV9OYBWJgz/AMnQzEVHVFTAgJJIQgMEtpyo0EpuAu0+TjZDGsx/FmGtJhn9erNPih2WxX3ZmeNePQuY19m8dRJUzqh9F00D5h8gA3NBusO96enW3WG4niYdof7u7SXea8umiU0m1/WEFULTQcm5CSOimxkWPoewJFakSCTrrZnjuco3o35engeRymA4HON5ebe6u4RToocsllpHaZqjsU5GoZBii5ovIYy9ZORIJk2QEI0GK9aR68erm52Jjrze722c2T88vLZ8+u9v0YV+CI1bojoanPt7c7EWIPzGLuIHamlIzUBRJDMKirMTGV2h0X12fnap+Fok0Mw8LDKuaiBaAxz0f49nkw61PHi+jV6fAuYQDNBb86aefg+Ygo0fHrr3V4GcRc4Gk3qq2RdchXAIJBobLEnIyqP1bxNzIQFyaHq1uRM1ow2TlOm3OtGb4puXFFpgwu5kXdCEYQJvVZwb1K5KNOOQfIZrysLDFV/YVw5C3NkRUTgQlVgrlQRiv2XJZac2dnIvMKvLnPuDrNtQLg9HZSAStmTWVTJ34RXl+OavZdB8qCxtdVpgBTJ1k2ux+x+IXGtABYp6Pk/w96tbC6yqlOHdJ/9eHu4TgyUGGAiqqYlY/mBbW10qxee/AKFgNA3VydiCqxqKAADHfkrFCtvQlUR7GZpWlSVWZhppK2aJoCS2kXCiG4++Fw8GzFm7R2qy9d+lrEzhjsLgJXLy6KBYkkcq96YzNfTKQypyrrLxd6n7vpvFHMKF6RaKm5zQtHRRYWBSQWEZbgYNfCZK7JWcVhZodEIiJmnRKOuBWqOHKZRxLqdmNWgURmJV1E30Uk51wYCgBohm8KzqhV9tHLPr2k6BWWUXeFq6O0SvOSUDKMSnclUek4PIYpM0gJorkvl2u1bPEsLDtyYScSQML17CXeUKXAIgFGaiYsoWEoxmGkOTUuKdIc4ZRLdgPlrM5GvCSFPst3YX5Yi84cLaDDEcCiUsdz98LCNCoLeFFzr5W92rJHTOyFKEN5ShJCCAEsXhwwzSBgp0DELFboV5jB/JIAl+X2GLZgwfznRQHHKy98ltq6wwCIYeYulRoyl0lcmNuuaZo256xwYmrbhpVijAWPizGuV2siyim36/jK41fe+/DJzdUttWFKU0pTJFo3XQRP+55CI5uwWZ+FNqxXmza2aUKaxrvbOwq23q6yTc/uPlyfX3brFYgoIjSBAiDgyBn5MN01aMxyDNSu4ofvf8TerNuzi+299Vubu2e3zDSlqYyoQ7+7vr6SGC/uXz588NIrL718fnYuzkJyeX7xt//uBwS0TWgaCUzDYe+eVXNkiRKAgrlYkCCRm6Zd+erczu/19yakm11n8N3+zrINTXt9/5Gb3h0OKU9jnrb37mkZGEQMYiZGaNum7TpVj+FZaaWFoPR5K0zEGQEEU63TX0uBzTRZssld24jAILjmNI4pa3LJEoIEZE3DmDSjCV1gIRFjz05DVkeGs7IPeRrS0O/3OqbbXZddN+t1lOjwfuzbzZaF9rvd3d2uCfHRw4cs0u/6aZyur29Di48//uDlh688fPjoj7/7na989X/o93R1t5OAbCg4t/tSn1726aMWjDusWEKUjn8+kjdnLKmugQuvVj1rxS+W5cABmDrYKnGdKZA4jAiLZV+N13l2QSinZXZiK3AzkReWVpFy4KNYp9tJRrAAzsf1qKK/y9JTtAbdZoKtO7NUHasZl/YKv1X+aBH3m2N+WuIiL60q5Mw4guc0v+E0S0EtjJSPWqs1akUXo4Yn5VaUMxS8zZxACiUjYgrMwgIhEGKg2HWr7apZyeAHaGqaBqRDPw7DGCPubVebdbPe8nrdSHJN+fr66vrq5pV7L1mOLGeBgvOo1DWsDE3WAwgxZCOhZrNq33rr7f9U4n/7X/93q/V6HFMprinNKU6lktV7htOAdb4VS9Wr/NvnCNbnx3+44xigHqP4+fCZPVk1GKoT6/IuMwKmhJfun7315Yd/8M1vvv3WWynvm9BIYXMyC/n11bNxGpsYNmcbNTO4QARNstDvpn643WzD2UVrZqY5TYeNbL72pdc95S++9qX//k//rO26R49fe+NLr33pzS9TbNM0/vzdd9/92bvvffDe6gISKWc0ZDGErmnUKGu2nIbDdHd12F1PwxBXXUAQIhHxGEnVsuk4er9P11fjoR/Ot2tTcJQQrO2a0DRtvI0BMcJd94f9vXubywcPmxb7/W3Kw6E/7HZ3jshGU8p3wddN12xWTbty5/PteQgRCmeDMMAE47qYF2LHkjxZzViXVLbsKRW9Aso6KyCQLVDj8uhmuBEgMGlKIURhJhYzl4rzS6leLNY5vuQhc0JBYLN0mhmX3he12hFyTIGKE2JZzJgJs/qxmfnsd+3zxynhGLlZierlBBsCVcmb51Izr7yJeoXlvTWznBfP+ZV6C0+aImZg74UBXne5I14wJ9MneZx/9qJbx/lCHMaM5p2cqt6PZbursXfVmz89FgST50JPLppDQu2mG314/OrLP/zgp7fD3f6wzzk3MY5Kacp5SsjchmjT5NlKbBGIYwgxhCGlonTrwNBP1/vb3XS33kQg5OS73dA0+fzS3XpXZsZ6LW17P5sd+kMbWzcxTe2ZPaQmJOHEBJytNtuz7Wq1ZgkfffLhkPfZR25DWMVRXTWpSnFOdtikI8M7boSon7I4VsJmPI109WRP5OtN3Gya2EEnd9cxjfvDLjTd5cPt3dVhPFg1HAM8u5MSAUI5ZQKRobIUDc4OQghSwNzYhYuH5+uLVWglnIXseciDUo6rjkOxIiYWqnklMwtDQMJ5yEKQIHEVMaIf954gwZnFyTQbyJi8bMxV/bTW+CuZnArl3ovrMlEpF2JGVf/+6NUy3ufXl9F7HKFL9be+WpO6ZeT/OgfBhR1VIqZyL0pbIbxo03MlPtgc3NIc9BUMi0ASClJhXDkpFXEraA2UZvwKVTCrWgq6GZzh6s4uHFBt/uZI0h1zg3WNLJ+DclDy/7m0MmuFOVA/QXkOKLLozOyuqkUuFTVVNSoqS3VGLryvAhMtKfrxIVWgn+vuuODmFckpoX5pA+SZdIKiKTLjHm4zRDUzbIAiZl1gCVugjII5nIJN8zD4jEdMv9ZIO/4unWDrv+L9py+F+d9QFnlVnT8kQJAQYgjlvOYuzA6Y6qQK1YoIFCBjBn1CZGFx95QygOIHB6bicDRNU7mCrusCSI2nabLkHj2G0LZt27aqOgwDXKsiS90JqkWhOZoIghRSmLPVlOI405BzJqKcjRmlbxEF2tCytsJKwyBq1/3x3pcRoseO2+X+wJFzIU9BJMQYm6ZllmzOmdVt6gdzN9NV03GQssupak7ZdHK3EAoThNTyOFhRAZAQQ2SCmGnOWj0JmUVkGTchBDMjUMW8AKCqBbubMTHVps5CgXRYAcmcyb1ojbk7wMJUp+pCcCKSIOKKRAoAMju7k1uGmxckgIk5hCCBLKeCyoHds2UlouI++Vyip6CmVsEsK5NwEIOpZstOVUYKBnNmcpAQMzmD2XMeITP/tixgcHAtqM0mCmqW67JcCVUOh1pmYWKSqoAGFFovXJgJYijkYgfIuaiVERwMyslYjDlKkGyW3UwzHGiIEITYzCw7hCAOI2eXGjy8KMh1LBo8N0VpXt3Jvcg5F5H9jLq0lTeKuUE4dm1sYlZ1aNOEEFuJoW1bAZkZg9sY0zT1+4MQn2/OYR/cPNutztphmoJgs1ltV+uWw35345zpwlZtG61Zt20TomKapvHq6kpaarrWyO8OT5vtNpCDsVqttudnBa/vDz07KMiqW2nI7AK2EGTcHe6ur89W61fbV77+9m8L87s/e+fq6moYh5un1z9/9x0O4evd2f0v3n/p8vHDy4dwf//DD66urp88++TR44ftWReYOPKh39/2u1XXnZ1tOLCqxqaFsYl69FXbORTww+b8sNu99uprN7fXTw593x+oMFyAcZpSmgy+UU2qmosoFoFEInVd2606MxJBzpqLAZNT2THMLKLuSgzSebLDqXgssVAT2ygIgeCUpzSkxAEhoo0NMh+G8fZq3zRpu9msz4LB+2lKqlMYc2hbCk+ePV233er8TIeBQM7GDccm7m53H3z8fvelty7un5P4frjbPHgJsGnSi/Mz05cPu7sgcB3vhqv73aO3Xv/S197+2g///XvvP71brwJg2Ryms/QaSuuxW4X7QSgiEcXhtUaxboARcYnd3WqphxkciAt1U6mg0gu7uIa26ioOAQcR4tAEh+ecoZAws3fNZKawlkHPQQCu1f65pA4zhAqPwLnG3V7bHJY5VHc1QoFdcCz+EC1mErPvMjNZcVqcu8PLZZPXhKyqWdZkoFToi+ICQ3MxiCEnZyJatHJnhleNJKwAUzOmAwIURkc2Z53kRUhwDgPn/3FhHgACCULsZqltYrdunfPQ7xO8CeIk/TCOvT24F84vNqtN2JzLatWyYkj9R08/+ujZR4/OviwgtsDSSCmUmTLb1PcQnHXd0+snD+8/HlLebNZ/8AffLh9kyqNIKxwMAxNgpWZQ9QVPSNSEmn+aQWp2RYvBzRKflp8YpJ+DWp8fv6nDZ9z0SGp+4TUQuI5NciA4GQOjWSRAIUzf+fbvv/zSw4bCaCOxWlZFXnWBgU9unu7HfbvpYtcO4wQYgxuEEXHq89Wz25Q7jkLUdO0mjUl9d+98/bUvvv7G62/8V//Nn/3JPx3/5I+/8+aXvyRd9y//8l/f3h3e+cUHT58+NbPdXYKIiDadZOh+miZz8Dpl2R92h/3UH+BgJiHnNE2hazfr9Tjt0oSAFWEY9rc3NyA/5BFwyVnNtOu4CSjspayp71PTXDx8dL8f7j7++IPYtEOf04S2FWKMA/o99BxNaJrQuqFpO+YIq9EdKFfJCGeDB1BRGC3mMqVLCWU7OCERLYIrNbwvGlS1llDEaVAcoKg0CzLGPpFAWJgpkwEcOIrImCfLpZWKimMt3CveBMCZCdmWB1wcbwCDZ1g4aaDj4oRLczf8TMXINch3nIivz3WMWeEaHI8oUdlh+NOJ9wxSnWRRXpsan1sAnxuii6zykvh91lH225qgEi02v5+eDV6kQgpgV8zmFj4w++yEdXLW+TfnhtwZVPyMg5mklqPMTJjUc+gsNxPeA4Dr/X40eOw4jqB+PIz725Qn33Zr82nMyd3VDSSBKIiEyDw3m6r57tBf39yNultvH4XY5kGHYbzbDavXHoi4+WTuqxVvthcxxv3+wBJsQhvCZtNFWksSH2wcMkOiBMU05D6sEIR91CHnqBK70DgHCkSw4jSYrSFtmwDnrMgOOBMFcrl672Mw8v1Nw9tuxRQiEY/9dL17dnn+8PxyNerQJwVBkcrGDQOzCCQjuXnxNPCKV8ANUwlIMnibX3vzlfsvXQ65f//JL548ezYk5cZWm3h9/UwT2i7ESON+ujscXD2G5v69e0Ly5Papqq6267hulKzfHVB4AgHV6ay6STvgs51OcesqbHn4KeJZYX0HkylQKSXH4uUvOXxhs784aGeUas6d58ih/LdI5FUGd/H60c8cyQXipTowibxO88qTKiecGYVO7lzjPhYqWj7VQ8yIUCRyQEJC7OxsgRZ7wSOyVjHsE7i8BMVeRV/MiyIRIlBORgxXc6vAwFwl8VKsrGuIzbemhrJzHaBUOou0KC2tVzMxBUfxosI5VYqIXvsoZ8prne0v7HwlPqs02bqUUZFpg6PKuy4ST5gZWD774xGYnciL2jSYmdSPOs4FTpjB8YKi1NvnTifCtcuZT48agf8aXKpTAGs5z6/ziwCoKJNVQqJ7GSuxa7qua5oGqI1vaZpSSkV0illiCBzCNI4zzqfmtVuVsNxwYIn+T76pf7hSlgwGCDWxKdyrMU025Tr6CWTEn9JSZ6oqv9W+hFndi/VVqaWcFkPKr4QQQggcRAJlM9Wiw3eED2kmTJlZmpIEIXJVt6wAYtvEJhBYNWtWNSNy5ijC7p5zVjMpdILiRsnczncvZ7XSL73MohnNkBBi0xBRmpKZFqCquDdyqU4RM5EQ55RSIWG5k0EBbiTGNsTgBrXs5jklgwlHFnL3nBXZMFlsGyJKKblaXDdN15pldWu7ToT7cfBiwav1dhAzCZOQcMiWc1Zz58ChaUOg4jBduktVNakW2YamiyEEAiksu2afls8buGmlERJSDPs+DROq9CBZEqLAxE5KDI7ghoY0gAEGBAggAQsLFVtlhBC62MUYmDhNaZoSO1LK4zg5vGu7uezkpmXVp1Llcy8IPogoE5kDalAjIDox87CbSt2tPB1mmABBQte061Vs2NgUmnLKrCESRzJ4suyeYVJzZRypigCEF8IaSBgipUhoDLCD4ezElJFBjsAUiFggHhsm8ZTHzbp95eXHDx7cg+VhGC62Zw/uPxj7aRyHB9t7Xzx7JC6T+gcfP/vRz37+1z/4gTqDKEY2T03E5YPt40ePHj14lA7T7779e2+/8dU1t0j06uNXfvjDH/7k3Z/8g299M541/9P/+j/2Oj7bfXJ2r3v00sMQZbffm5kIr9frQJEyubq4BGk6ai6n8+b/Ze9NYm5LkvOwLyIzz3CHf3hjvZq7eqjqLrE52hZFEqJIeYQpmTZsEF7ZWhjaeeedAQPaeGd4ZXjllReGvDEgwIDhAZLhQbLa4mCym81mdXd1d72uN/zDnc6QGRFeZJ5z73tV1Wxa4sJA5Sv8qPe/e8+YGRnxxRdfUPPo0aN79x6q4p23vxyqalmtGMygfdqe+bUgGXR32H189Xxz2I4ahS1punP/zma/MahzOBz2Q9+TCKtUPqQ4VpUTFWJjj+3upusOvnJj7Iehozp8PGx//OzJ97/34eGwOztff+Gdt53jGNP1zXUSefDgwTiMz66ei7IPlSHuD9uYutV6df/uw/1t3FwNT7/f//4ffZf3gPhmVbMboiRDYFcbabRROaHGz/3qu5tuc7vd7cehqoKlPQx1y8tVndN67JxzfohyOMRhGMeIIaKt8Npri3feedU7dPtbHUcy3Dm/75UdfPDcVH65rJuqDdZITI6ogvfkLOHB5b2H9x98+bUvbna3N1c3Xde3TfON/+N/3x0O73/9X/j6L/5iL4A7+8//i//yf/jv/9cnN4e2xrAhkDVNlWCRk7KHWuMbr05uhsOT3kcggoyNXCKQCYmqgRneeXKcyaKWu3AU+jV779Khc9479jnrkoaUC7ghBqIQAgwxRTjjkBuT52QAuIjBE4FERFQAeA4+VPBs0EEGkMBZWDRV7bniFNMwjHmyiSroExZ/2uBQ+lU5Ymc54Vb2Y4VBkjgqguqZrKqUEACG844CsWe4rM2iSBCxzNQ2gByMjdlADEdKli2vQrWIfBpAWUasSA3mcEPUUSjZQpjLgdvE37RMjivCZFq0FhwQ0Cyapm28RwpR69Teq9f3l8YxHroGPsD2t7u6wZtvXqzOa67s4nzt9/T8g+cXcu83f+Ff/5d/8d84c284XcEWcNmLjkAEBkVMFg0QKIjEeARvbvv/5O/8p//13/3vdDAGLVuVOPbDCFjd1Kkf4159xb4KMSYZhTK7TSc4ziy3gJ73ctLJAUV2Tz9HsD4fP+14KWyaoWq85Cge6wcBTB0xX0iU5Z/Grgp1JUCSCGaowOLDR/fN4pNvXf3t/+jf+nd/59/5mfffVdmt22rQW8W+jze9bp9sH1/1V672dds2vq4pLGixCosaITh/SNvHT34gTgY7PN9cJSTnEapQ1dVqvWqb1X3c76HfffLRN7/1wXcf//j7P7p+fHXzbLvfx6ETJMb6Tnj02v12La7qLy/WlffjoMOQSN3/8wc/iB1SxLLx6+UZMzO3sberm6ePHt2tGhy6zTDsXAjOB0eeXR2qpuvGH3/8dHX3outvz878vbuuXfTvv//mcoGqJphdXd3+6EfXYNd3JqMGh7feXJwv+dV7Dy7rR3ear+Dw7n/2d/7bv/d3/3FYrs/vXOy76+5m59cuuEo0pwXdpD9rZKrIregVAIXiKpsVL9Cm6vXT96lO4QAiduxyey0HFUzCLXnPYYiRgnMhOZMkS2OSmGBmxkWS3IzNbCh8jpzpK9PF5U7QUBWzrFCqIPNV5bLuhqgmo2zTc04haYwJptmE00TDN5TaB6Pj7wGIjM55IkopiSh5OOeyWAcyqgcQlAWU6zqUgKm0nZxZblNUTpeDWTPLGVbMza8mIa7Sc0oQlpVpVuMuSvQ5k8QFDii7TyZZZCUR5LpwRQhBzcQE+dZ9jgcEs0TzZwSWRjCfY0DniQlKPqGSMemv/82f+Vd/59e//AtvfeOP/q8//OCPHl/9eN8NH357U4mXzukYum4YYwTANQXv4pA8hWZRG6Tb9Uns4s3la2+9RoRvf/TtMeIrX3sFnJhtjEPX7/7ar7z17OkPDwcJHiFUznEV2gcPHq5WZ2lE7dsUdXN7sJGGzbjbxnGw65vt1c1NQtwexos7tavD/tDvDsl7nJ2tz9YLU+m6w253aOrq4vycqdrvhrPVHYlufzN8+MOP9rc9OsChXrqzi0W7dMqj6rBcLaoqjMNweXb3lYevsoVnj7fPP94++cHzw82QOtUECEFUYoSZDwgVnEMkqlZNaPjRo4d//V/8za7fP3v+8faw6VIfafzo6cdPbm/WF+2qXTSyTEO62Ww2/S7UoV2tCNRt+9Sl2CUvoaJQuWrox0N30EEZ7JRTL9YV4SmalGA4KxQXSpbqVB2VRTAIOiX82Eh0BgtK6J4BGSt96ucVQQ4AG5fefgrAkijNDHXOwdSsRqymUBObiuEc+4yympqRanoh/s36Es455zyBbNK/E5O8+E0yCaOkXN1U7weF8+yCR9HXTrm4mEEqR1bo5Iw4G+SUA5lvnalAB8h2rbQ2ylrYMUvMwEr4GSrvvadsP0gGpIwceWYGY84Wl8wxci+Fxi0guUgIampF13UieyFl0Cp3EgdTqU5wZFAfPLggJGoiKhCFCphBHIo9zdQHs5QjcVUxaKEkEWW9MMqtlUTEpopsYmLiynkYUooiCoJzwTGP4+idfwmZypVvfyac9KnCVaUpx0tGZjrUT7BFPyV6BcCjCPsV1DC/f0kSY8xHSSmpKcRICzhnWXEJsEwLmhDTeRd76ZqnzBgmwJZAZCqZOWRkNoltEYiNjCknEWxKkrz8XDDrj+VqFDp5KJ9+n5lcljP1kmfUDDROI2vYZ3B0or3JLN3lXRjHcVI3LuB0/pj33iMjqZZhMMzdNHO1Wh6TamV+Q5lJWNoAm2oWkp8w4lzTZ6REpGAREZEc/uQaNBMS1iK0prmulUt8R0wwx4AjDVM3VkeWAznKVLs0DB2IJStwWVaNy9V2Gb3lFJPkRra5MkgVygZTE1E1SK4bJcd5My6Vm6piCdX87DlfIBNZ1tuqmIvFyXxLVcp3WppUBlcbYukQli2XmnGafFnKXQOTWpKUl1qORM2OnkcGnPPyizGWS+Gi/lx8YcolhMh2L1QFNT0KGBLUM3vHTEpQtWQiJllb0ZRKcGs0sROmJGEmaOBFVz1vGbnRq5ZcoBk1IQBTqCxmEBMZFNywdkhe1eT58+dx7M/Pzrz3m+2Gya1WSyLEGEWScVgtlq8+eHRzvd11/fXVZrcZ8uIe+3HsujSMZ6v13YszB4zDIL08ffp0HAbHLhP0Fsv19ce3BkpJtttdu2hEZRxH59jUHPlAwcGDmFnV7PLyPFho6spUNVlKkdmJj8YuQT/+6PFV9czUHGEcxt1hFzWpUzUI6ZPrZ7vDBo6aukoSB40kUitQ5UoQhLpqmyqlfm/EBq8w45gwjIdXXnlQharx9TD0oXLnq/PdYaeqTd2MaRyGfrfbj+OYlKIIkYkmA1RtGDpf1Zd3Lg7PNlCE1iPVIkmRsnqbmRLBOTYuXWMw1TgYkWmWiHWmzgggz+RDqMAmMiQhb6qWTK3vhsP+sFwG5xkCJEtpVHOsKQnUPAUx04RECoEzVmPvnRt13HXbm/6WGcv1wjmWFN97/yuHvj+/0272V0l93YZf+vmvP/7Bx//gH/0uEi7vN/1+iGmMCVYRREzhKle5egjiA9iIBGa5e++kYY6c2tFpUpYUFAjEILaii26mpjQRGPOHs1SfAcTkK29s5MuiY2MAzrkYY449it6fI2YGOWRZOlOwkXdGJsiCkrl67yeM2esqtCBobgltZgYt6lwzRQtTrpuIp3S7sXFG/0HTKieU9ntkZLnWjwpjmEtyszDQSpf2EkMU9VYq2fDCWyIzgxDciVDhTBqAZe4uwASX2HG2Y/vYVXUIbSDPScU71zTted0GM5IR1gPiHQyaYlQxJVGWKMM+7c5cMghBpgw8ADZzgJKKkeS0VE3+0O3bDGi5NwAAIABJREFUpv2ln//F73/7R//gf/nfHr795uMP/xihJEtVtK4roiRRrJRIl8d4EpnSMSM7b+iZTXZM5H6OYX0+fqqRYdFPANWf/ekCo55MyCN6BYBMpYh9JoFHaAKRu765Dj4B+M2//lfv3FlVFSRhtH3X3Va1ukAe5EauqEqkQxqhJhJBGiqqa0dsjny7OPOtE5J6sRYIBzM2cuYcM2yLZwH1+aJ65f7lzXb7rf0H18+utx1GAjwWLZ8tlstFu1oDwYvSdhfjICYcvGOgqrBswtly3TSLrhvHfhgHOPZ1vVitK2YSkf2hY4o+VFUFM0oxMrSuMyOMm9o3tTQ1ew9NUURFUmZNeWJRzdtftvqiMsa48EFEEcCet5vNIDvUICW4ycPK/PRiVJhyd6ZcoXky9GjdZrYqz2nrvJ9mfhATSEkk2UlwYpZYySkbIWu/ZA+I54KduVyZqFSBT2bmqGo71V9MFwIYVGSqnCLn2JKUa7RSR/cJwK3cgKlNLL95ch79yReDi6NlpxeYLGaT1HNG6qbNFC/S9E8MK5WMjyErGlHBDQxkE7vajmednwGsCLhTiWWmu5wIJjYRCn7KgNBM6qodDr0nx+zj0DNr29AYQNV4fm/hW6ds5Ly5SlnAsJFSbxaFlJxzYsLsFGRCoyRiAmsig8cwxqqpiDgX5riQox9VSyFgGCUqJxMIDCMLzKjr9jAa+pE19MO42x5Sp+MhjQPM6j7FaCmZtC3144A0gOhs3Tb1sq4DE4MpuFAH5wpnWlRlPAzjiMNhzEEBe4KaRU0xqrILjn2lpv3Yq8mh3z15/pjhfLV+/a1X33j9rf1meP7RzfPHV/vbg4mJYyJbLqqzy3Z91ro2tOdr732o/fXNs8cff/Ts6mOFUGBqKdRuvW7I4TD0y2oFF+qqriVGkW53UCMdRJKSEYmJymBDkkS5646wKZjIAjQWwlN+3QIlMJeqm4IuA1O1b5ljZhAlFCkZQ2mANy2wF+ZBDjBn7aVjAI/iBhBKf2ibfYW8qjjT4Qlc6ALTkvjErJ9+YRNAUO4oe2xT69Psm51O0emmaHZJ7fjzxXsAkFWYPwkKGE60lrSANPk4lBkwOSjMPIo5PVnYMRO938oXkKH13MKuIONmWV7ecqtBK52PDGDOtIoJ2yCgNB88XvixGDuDlMRHg2SwUkdVarDK68k3WnB5TBIWBcoEMtBZsA9JuckZ5YYAuUbD1DQDDqql++sn8JSfklQ1f/gn/OtkvT/9iz/lWUp5YEGvJuuolgXRS1GhmjpQCUisiCIJZWBBPx1kevli5ysrqicpCnty5IxMRDQKJAuLKM0z8jMALLOpCCQbbdEj4nDyaPKYgSQAMAW5ebZOVSnHkaEr7/3cb7GcZaojzdhkBlJ1KhwNIeSTTgWJJCrzAyxXRchFeJmlVYr22R33uSLENhdEGrS00FPLLwGUC+nKPWoGvOZOmZjvBSX0BqAilrNKWVHL5aptFaikLBmmMCLNGSQDc+n1YpZSLLErESlDzNiIUHTQIflfgvfsGC7n40scVd7frFWnqkQMOJdVzx1gloyKYlhJNjkiIqpCUCM1EQjIoFAuvOhMj1UrGFIu9GMiIWTpBklSvOPpqdvR0ZkWB5Ejyg3ZiIrPxPnpZkkezmC8GBkcyBGcMbOoqYhBJ6WIQt+eqKIvzNXppJRFFvK5cz0kNDOP8zWpmFjZSJSY2LMBvmbf+N6GdlGxo8Nuu99vlm3THbrNZtO2TfvotaqqqiqQsK8Xi/Xl6vKuOL7d7r77/e/h6rF3Vd04F1yo6vt37779+he+8PYXnPD+ar87bK+fXDPTomnapglN9fDuvR89/mHlQj/06TY5dr4KiZJjn4N473xwlScfXOXhOXg27sZDN4xxlOV63dTNeHa2aBbe++c3z+sqhBCc5yRiLC4QOw+IGLngdad913U7OxwOu+1GY7qzWL795uvtaq2aksSUkqlVvqKFheBC9GZGaUxR2qq5f+eumhopiCwpGerKGySlmNKommCOCKFyzi8EKeckPbuqbaqqQ65xcBQlkSE4D3JqZNBMoxRnOT/KDk4JUEkgDzMWMVVl75i4aZoazOxAHEdxfT/0Y3+Qbt8tGhfIgThZSuOYcQaCpOSYBgtj5RaBg2dHpp7Z+aofDlc3sqyX9y7vrtbr4Kvt5vbh648A+GqRVEz0ydMfvfP2G3/1137l8eOn3/ngRwRSI4iTJD5QEoWAwN6HyH7KoefE1IzM5iwwlDIGD53MKY5bcbEwZlCjGcAiopyO1mwep7zYhBZNJlcUVAQ1wYDPu2Tpy5qlg5137DiD6aqT/N4nZYTzsjldUBO/EhMud7K5FOs3qZJk4zN9wQArdS653oImyWFCLh4sldVzJmfS5TLM6FoOmHJwMKtEZjWGyV1TUi4gWXY7ZmeTsyoCphZTquqrytVMFYxNoSDygdtFs/CObRgH8c557ykwsRFZCK4yD1KRmLdtKpicTU+QzBzgJ4lmAGoxtcvwa7/8l589fv5/fuOfQCIc2rohojGOMUZ2gYmn5hKzsZySvDYrTHCBP8t8yODVp1a6fD4+H//Ug06ijxInnaSFTtzfEFwuqHEe5K3y5hw2+/Ht11699zPtb/zar0Y9wKJzEIxdv2UfjJJojHGoKh/HTpMow2DEChaQGpQcqrYOdRWRWgc1GVLfj103dimNEG2dP1ue+ap99Mar1K5GNHfuP/n2977/w2fXA3B57u+c105HpMJSlWEc9uPQialzRawiJzVJRKJEgfnKumG7f6LjMEQZxxFmQBwbHc+Crc/b1flDIXPeV0GAaBolxQgxSyIiMaqA8uaYJbgZLnc+YoKpcwgV0ACWhsOAQFzxacCQ4SL6qRa1lZd0gi8eX0uOTo1MjZimfh+Tf2sQg0nmyLNzZHM54LQRzFYmi1bkXOF0kLx76dwri5Rylw1Lksicc0yOHaeYACkxeanPmKv6MJeKlxiBTorYf2IANsUmE0FhyokXbMlKBnQ+hGqxpi+NsmtlDKtso3OIY9NjPX5tSq7PfykLojyg42uZ6DLT9v5TDGIrBDeS3EsKknB5iTv3z+/ev3h+8/GzzZNNdx3TaEpQxChjZyQwqA/BjByH0qdIVJISm3NOWOKYQggM1gQAziN4B8IYiQnDaClBFUlR3AdN+30fox32vUQ6HPq+G9IQ496AyntLIilJEqkaTsnYcVO3dbsOvlHVoY8Mk8SmToliNJikKMKWkqSUzIQ9sbCIjNHCOLYW6srDkciYYvLeJ0rbblv7ehEWLnDbNo68jurJjZfqzakkkFQVhZqYTAkYKUXpbvs/fvrB9c11RL+6bNu2AaGtk7EdxiENth97j0DsvA8qnERSHHU0SyDNTpTpWKhARd9KwWD2bhiG+SUfZ+Ik0AwUrfkXEIAMLk25JitCB6S5FdWnlPeV79uUlp+OWJDj2eU7roPpUk4D6gkWAk7zkxO8Ug5VQmCjqUcZlw58KJqpR7D4dPnY8Q4n9GJ+JvOnuEBK8xWWRmRmxbvLatQ5HEeJVoloUlTIZmFyiIynKJsZOl/A0R2CA2dUUaW4ZIwsvW2ZKgYDjNzkaRdcvvQYQia2ZvS7uG5S0rZM88PP58wsnOyAzWwylD6GL1jvDJDneyElVU2SaNY2BWBFjcVeGBltOH16P2n89MDWP6svAvAn4Cfg6Niybe6RlwkudoLjT/rof75zz6LmzI45FRlflApMNTXNMnkoxZtH/vhnjZKFKGKLmK9nwnBegPFUFSDJgEfZNqbjmCFTqCYcSjU3NMy8OyPCSJRSwvwsZv2saQDH1z8fp1QpUkGQ8n/56szMkggpYGyThGSW09USV5JZhsNKh4UplKBp9amBPdGUgGc6PjRGJrSpmBCgJAAJVE2FjINjMsr8jNEsR2FzuiaHuCKYJkNeU5xzRJZr5JgdFY0zlJodypJScCIy7by59AiSD8NU6NOkRioGiFmW1WeYgzEyrAQjVkpQtilKJRAgppQTNYqkkuvtwQRHDBr7sRSEH6E8CiHk9zK/pnzVWjDQYhh1ahAJheYCRGcgUUrGXIqAzHJ5pzmA862zMSE3BLB5OtnJvKBi+82mdzatCYCAKNEYmQVnRM4Frhx5c0x3Ltd37q7qOpAuFnUVgjvst9dXzzYcls3iwdt3+mGoufFVaBarla8R/BDT5Z2Lp89fJ6fOqfN49PD+F9548503vvDgwf24jxh08/TmBz/88O6de+2qrUNYLpZvv/Hm7/3B75Grko4pmhraqjGz4IMjx+xb3wbnPZyn4NULkmfqYtcdxtini5sLx2633969e/fe3btRYyDmEIzVOBUxa1JNcUyjjIfb2+vtbpti3O93h/1e+gF37r375S9eXl4eDrvtbpPF+EJdyyDDOI7jQOxW67MfXT8j75DKEjO2lCTDqTHGqgpV5ceRk5J33DQVuyAmME2aqgoiQk5RIw7J6RCCT6bkHJiRMse0ZIFBahBicw5JLSmcOSinZJISB/E+mLH3PoSwWJBUQhAbRwjikCwZh5NtPAPSUBVJYpGZiV3O7xCzs1Bx7Ma+67y5uqqW7bKqK1f5buzaZVs1vkYQ+B999P2HD9/8mfe/8u2f/9rzq+unTw911dYL1+92bA6qMFKBsIFYRmgyFjByEQfDgKQgaC7Kpzl3kY1mEVXIWQpkicPJjc5yhsw5kZF19diyVzRZvFJbN4sgTJN8stWlrRQROcfOk2EutcvoTl4qL1r9DFpbtuFFJT1XPdIEZE0XiKNfYFOs+2KuTtWOIcbkXVGmn9qUoC97xyRqcIyWp0Wd9xsqyfdinVihE5436eAWL6iwxI8blxpERKK88tqD6LrIA7GBnYh2MW7Bzfl6tWyl1uWyXSxb4wQkA0LlK6p8xXCqSIQ0SzZO6QIPM5gjOFKDg6TxYrVMZu+984Xf+NVf/YP/+3f/x//579d1XdVNJoIdDoc+Re88s5syb1Cbjjrlkab91EqMZ9PLKfDW5yDW5+MvYhCdrsEZAjjJSMEsVCGlCNXcgiWNfSJ4j7/09S/9jb/5L102y432Me2DN9MoOhCzWBzTYCalcQXM+aoJofUhMAtFyvAzI0EP43B72A4St912u93su4OkBMhZW98uD8v1RbM4u//wzi+0zetffHT324sPfvjhvj8sLhau8kM8BPVscCATHIZ4uD3s9zCDJJDGMQ5mNgzdOEZXudVq4Sp79uRpVYX7Dx4AmlLPAW1bn50tVqvVYtE+fvJ8GJzZ3rvoSMlE05jSIKowcQRy5pxzK++8rtbLtg11HTyzY1IdF6uKAvQwAmBXkSpIZwd/ioB+athjkkmY8ZrTRIRNNAf6ZF49azRms2I5ppqzJxMWlkPc+bin3zY7RslW0sAALMFIYXDeOVA0RZHWMZjhRcHWl45mJV4lfPITL30eE5BkxS3HbCvnjkOYN44/D45UDjJ94TQWnS7VcvrGSoUPTXt4Mcinn56vqySUXjziyWCg2++bZmWJhn7wwTFrdxvf/fm3v/b195aX7e//4T++3j3ZxdsxSRw5RmDUNIJVzRCCd2zeBcecgpJq8EEh7I0d1Ca5nQQ4MCtxjqXHGDFGS8Iwb2QqOZcu+z6O0brDEKP23aApGaAMgsKZkebpE0f1IVRVW7lGR97tYkxjss4xVCWmFDyTDWY09HFR6fzyKNdsyvSemHzwFFiG0TRxCEKatPccurTf3vTdZkydslY1L5Zn7diN3jwxG3S7313fXh0OHZMjxqYf0AGMi3thcdY4Coe+68coRrFPmnC1uVk0C2MiZV8UGExSzFgSMRsjN61n4tJI0kBgz36ggWcKYnm9ptAp/1g4JjYT52nKtL00jXKbrzyLc8uaFxChk9U6h/4n0lGTY6vHqArTJGR2J5R6IspRD02Az6esrjzji1jUCTQ3zV0qAf4c6c/hNoCJNDr5fEf8/WQhThdTZKAzucRmF9isKClh8iHzgRVKuVY4lyjB5QRkfvwzRsGlPVAGqUWkQEOAkRJ41kn9JIZtMLgSSBPb5MjlZnBazlywAct5iVzbXUASmuT6cjXRhILM72t2Wk9gCszVATjBKrME08y6sakj3585/mlAqH+a4R2z6FG7x3tHxPNmQzO2NyVPgDkW0Rf2js8eJe1AdJQTm81w6V1ozJhiPVDuCv+TDvjCRpjxiONcnq7n9DP5RohZNJak1wnkhGlBFtWSXBmX/yoKIFoqQsgv7b8TSW06GgpXamo4KCeXUToDT9ukqab8xYzqsGMuTc0pq4q7OXqylPNML21JagqBc5iMjYrN9AIAgBYAuGxeljQSMbF574yNmdk4WiSDM0o5vFQzMiUh4Nj9T03ZSIQcT0Yyg8aUayeVUrk6LhD29E2amImUQAoxAjsjIuSSvRxq5jIgNrU0Ed0yhFfsWhZrMyrVoGZGSrnOMjd7yOI7yUazLAp9FM6cocpscYxBpgTmiYMNg8JSgnOZk52froEAZyBVUoEYK7wxQ5nIIfdJJAKb0zm7eDpRTxw5yq3tzKgwSmnWwMptdyXnBsgA9S6Q1xD47t2LO3dXnri+e+Edx5R2t5umaQ67zW63dcz/5He/cef8/qPX3rz/0J3dWVxcXDSrxetvv3519Rwk3sM5Ol8vX7l3/9HdB5VV2msVKh/cMPaHw6FdtGmMwfk3Hr0ucayadtWeJSQmZ0KAS0nAYGOwTlYCMHMVh8qrIEoiDvDWdfth7OvG3793yU4V2o8HOBPIqEkNYtqNQx/Hjx5/9Oz51X6/V5UYo3cuBF9V3jmnmlQ1iy+1TcU9b/a3V9c3KQ3L5fKiXrdVo0xxjGM/JBmrtqlcNQLDGGM/NsFXVajqoKMCopqyGllMcRzjxeqeRa7acLZGJwQhX4cUs2gYgciMRAuWml0oYyMHSyIKA6tS6tM4Rvb59bqqCqrifeUq7kDBwwEyqiQxJjI03ldVlecTQYK3UHnvAVKlaMQcAnmCMyUZY//02ZOz9Xq1XNa+ccE9/vjpclyciZwtz1tfnZ83Ke732/1bb7z2xhuvPP72B/VDcrWvB2+iMIIPMQlLcuyRYJp/nfvvZfA576llsr5UxWNmWcfAO5dhqjJ/S3ken7jVUBEAEIhJmelcakZAgMcUi0BUqLQGUXAWg8taHmpmUgiKxIAYH92oCfqdAoUS19As/5A/M8FU5WR4IaKZDzTvD7kLeumnblxAGZuKAq2AyXSMmWnSdyR+IYae0jzzw2MjIlaefQY4JuYi75rhsaL9qKqkScRrF4c+dY6h1QiRcSuD61vI+apZrtrFslksmm7c9/2gvZgZvBqJIhpEWVh1ymsIweVuKWyau9gy6HZ7s1yth26/OHvwC19/77f/xr/y3e9++/f+6JuZEQxjxxWROudMNEoiAudGPKf4FCbnbLJq8y6cA7TP4avPx1/AOGYZi4uVF93Jv5efZplow96bSEyqO3zp/bt/6We+9Bu//iuPt9/3DLNBYYqeWNhDU1Qb69p1bjRWNvhAVeVYLemgEquqMfLG1Gu63u++/4OPtt2+Gw/90IskH3xdhZvbx3VVNc3z1dnl+uJyuT7/8p23v/KlL+y1e3bz/I//9Fs//OjDjRzO2ktztt8d+t1tt5WuwzCg6xECiG0Yt8OI3QHP94CLX73D68tLcud37tx/443XmqZx3lbrpl04tXGMHYhAMo5NkuC4r0I4Wy3FXIoM8KI1pp5dDQrEzrFe3mkaLy44E1GLqkOoiAGV6ELrPI9j7/yETpdH+lkoxyfeEECnb+nFf50DXUyemBblQpSfBhhUSh97E8NEV5/fe+bFzkHD8eBTDFs2iRxB6nRMUhM1YjXjk4xFht+PsfpJ4D1fJGjqSP4ZT2Hajl4KOiZpbJzeMqh0eMyRymc+1xduTT/lfifGRrmAQhA+Acby2abGWicrpeRZ5uf+mW83uLBYLC0RE1VtcPVwtYtf/dp7X/36V0br/uTDb236m0G2Q/J977oeIUIFrKQilrLGNoHZceCAECpBTBZB1LSO2DSlLAFZmNwpxXHsBsREZrVxZEA1qgkJD4MkxjBGESQx5ysfjBAh7JjYO+c9YKriufaoYm/doT8cJFk0jsQCUzVUQU0HGGJKKiYiMaYUQaoWAQJ7hCp470EQUziQkUJSSiKJ2dfkbjf7D797iwPqqlpWq0D11Q+eO8dUcWi88xjTQOwb3wbnar+4leukiKM+e3oVLR3iIJTas3ZZr8/unH37xx94qohZSIUMwiWtXVAcJg8KhMikDMkqarlyhQOFaaJpCUpL9DkvvhLonMLIwAnB3YrsNRGXz54MmuCheQbSdMR83pcQq5cGFWGsF+GSCcZFwbtPAtkMg5nmFOYpDWhGY+b/cgxoJ6GwopA2PvVqPoVJajP9Y0a/qJC0qFizfA352VjuDljwb4Ur7Ig0FRzrC25m9ky5wKxzrpSkwOI4PpnjM8ykT7bio8NyXFkwMtJTyE+zzN5LNzVROIsdRXn/ppY1cmxiugET4GUzCHhqtefX/ucbnzoZ6OXd4J/9d33TNDHGlJJq5h/lAxYQZ66km/CsfD7QKS7zE9Ery8pMlMP02a8v+iUppUysDcHnJlZZK3Genp/6MIlzmXgBOMs60Zcv43RnYmbvHAef9nHmv9jJAIwoX2nB7PKlZpKzqaZTmdoXX/jUWhFZTRJAltPKB8nP0AwqiJqhrpLKntpUGbzP1UCEQiTOoE2+tcZXiVKilBkMOmE2eQIWt0BVRSwvqvk5k7J3WtqQAgRRYRIwCaBJvfcc2CmbKo7VlblJAVvKkTxMxVhFRITZODerJi7RrnO5T/FEkzCAKXCdqXUgY+IMP4mlpGJk5RkXp4RzKZEkUYgaNBLMSrMJcgDgTP2sYMCa8TSw5H3eUe704ojdqprfS66EhcHSNBdLiSa5rLmeP6ilpyhcIXUwmJi8I22MaoYnoaSWC7RKN7ecFcm+ShE5PNE4KKaWJ7xn8lood2zMb4eJKLNJjRiOTQB2CE1YLOr1xWqxbLynsR+5rpg9EbVNtWpeWbWLm9vNarkehvEv//Jf8VSd37l3dnkJFz569vjxd775jd//Rjd269XqS1/84t27F0+f0jf/4PcXoWXxZ/Xq7uquZ//6629I1LquJUntqjuvvNmwr0OjLStEku62OzNJMZqYdyE2YxPqNjQIII9oqfYVMXzrqtpxsGHXQ3AYdgZNiEPfHXa759urUQcwkffMPkmKIo8ff7TbH0Strur1ev3KK6+8+ejhV7/0xQfL+wOGZMmgScfrq2d9HKJI1dQLv3CeD0O/bFdq1m0Ph+1ujMPdul63S1ed7bptTAM79t7Blj6kJEgpxqRGaiaSJFRhcXa5u1bv0bYsiZJFoQRh8uSq2pmJxvyqFFmAPAtpCRRQp8rjaIcd4BHTcNgPdR2c4zt3L0JVmeR+iUhDjF1kBTu0bQslZnYeTOS8eZ9bZmnUEYIQgpIMaSBPXIXN1ebZ9bPFcnl5fsmV2x22ycYhjrfXV44r75ZE6b0vvfPOO19558vvfvjRf7zdjrubEcliFA6+qhoR3afu7uIiL7o878xl4GRKZ2FqWTI5u44IRGqatWO5LrX/VvZ1YyLKMn3EITgzFhWFgnN3UwKQW6tEjRzYV56IJEmSBAEzzNHUJyVbOlY1ETFVnlzu3H00u2QTTezEns9LeNrAj2ASTm6t/DVb0eJFFT1iRpbRtSxOWNrRlkyTaVYvBQAmVtLSCtlleuyEwmXzQlADiKaYCQCMTLgAPRmOdq60xRBTISNnkx8mYDy7fhqrRBUMGMfRBCliFOm6blFx5Wwc0XU2SNd1+3HfhTGIGxVRMCgiISqPZEZgQMyYzJddN9+WpvuXa1PUZ/Vu99Rx/e4XX/sr//zXf+/b3xzj0A995WvnnKeamZNFMwFlBbDci4zmrZ+4+E7FBioVeMuOudbPx+fjL2JQKazAaTyS4/P8cxwM8N6HrEixWqBb4N//937n3/6df+2V9Z293dRMBr8Zng7pVt0o1G/2V5vhSirr4qHv994FQAxxTHFUYvISENCMKtuue/zjZ4cxUWjY2KMmE+ccPM6WFTsjcrt42D7pqu0VM/VxePDg3r3Ltvna2+998X7VhPXZ2ajpdrPdbnfdMMRoqhjEVF0SE2VyrqkXoXX1wi9Xa4CfP7txHExst7/1nu7eWy4Wbrvr9vurvu81pcq7RVNVFQdfNXU9DJFcYO+8a4ha4sAuKDRpT2xjGvqBoVzxvvHjbn8jI3wFVdOBKCPek+kkOjWr/5/e12R/CAQB5WaGeY9QLsIaU2qkdJGXye+1k7PPeI2bwJgjc9ZIc65y2tUy6GMFrmGQkuYu9UZHE03kTwN9ItKTSAFFqJZBBGaR44W8UMhXrgUATCFmjkp+0hjZnc5HI5fZ/iVN8smR8/Ulep9y+kdf+oWnOiMC9ikYBQqJw3LxeEkNA6rHA/xZQwe5evwYvmaybj+6O8Al3vv622eXyw9++IcfPf1ODNU+pih6ODA6WCQHwMgSNGqyRGAfLI6R4VVhhKEfUOkrbz3wnkaN7QrGWCyqlOIwSJIUE8bRkjBxraXpOCVFN4yO3TioqCYR5yvnLHJMSczEiENVBe9DqIYh3jzfdoeUomM0XAU4VhlFYu5ryaRN01S+JqKUJA4RQ9m42KNd1u1iwZXvhz5aDxdB6NOoAucw6mjpMKY+p+USxpvDle5RXSyGfrBRuhFgIMEbR5dYiSsaO5Bh38nlxfLOxUPabXaH23Gbnt9c7dthWS2d+RQlieY2pGyO4VUSVFETewqNN5AOkiSxZmljkqTee0JuRygZW5GZ6VCSfVN9U3ntdvSTJk7ONNsnJ8nKJM8I0eRJTVyQeZJNzs+ELxwhoOMUUi2gAXJ/QDVT9mxHCtKnwRMT5zAfceL+H0874dIzi8mMSq8+A4Qm9IvKHduRJSUvnSfNR6SNAAAgAElEQVQLr2bPNtNHHDFNyFnRcJ+I5uVKcks+JSpIIouKiVkW8DHzmMC5bOV88URp+mNmqkKlQHfKBU7004w9GAA203zBXBD5KZs6mwUr104EHI93ktcxFGUQnSD7nI1mJQOY2bMztRhjkVY60SY6Mt3+/zB87v03g5Hz7MmYSK6AyygBUSllLwK3c+25vWAYX8TzSgddnjSzgNy4nTDBLxmXJaIsoA6ACG7Gbj9xxS/9bl4Jc57nUwdRoWDBHSk5810Tcv9dsGPnXE5uoCxU5Lr64sVPtzcfJD+umVqZV818OzpPEBwnX/lJBU0BilAXTVKO+QMZRQPg6kpVMnxrMKbSy10LQH2SlIGZihJloTGQsS+CkOSJmY2K2DsAMkomQcvTZyWFlOLkmcY5PVFVYzYTlQg4ZmZMKDYHz8wMkiRaioTgncv0Kcv6dXkjnTwLgRoTzNSByByT5tBIFWoC5gxTlvdGIIMjg4HImcOEHbncDafE42Rq7aI1UVUVFSRY6X96nBhWyJ4Gk9y2FAQHstwphjCpWZsPnoKZh3Hpn5ptn8KgoCxTiCILTeSArF14AuR9YsZmAwJYlmvIgvujRhEQw3uiQHXt20WzXi/Pzpbb3e2PP3pyfrHcbRiwu5cXr73yKoOaZln5CoY//eB7TajuDcNh6IXoOx/8yb7vVus1tuaYYxqur6/6fn9Wte15zUzkOLTNw/P7b7z6xgff+d5qtaxCFbw/w/ruxb2B05iUiMaUmM2g45g0pkTRKVzLrV9470Oorvc3FODJi4pn6sc+ygClcewjokKU9Lbb3h5uu9h57+u2bduWHBzh+uZ5TOq9b5frN15/8713371/eVFXfovtdrdRs74/XN8832w3Qxzg4BdVu2hFZb/bmYgZp5TiGIcxarRqUZ2dnVV1NYw9SNiBYd7XQ4qHQVNKYDjn6yb0/fjwwVnb9LuIs0UTB9ze7hHgmFTEV2RiRGQM9hjjmFMXYikvfgMkWRoMCUQYe5gHLFZ1cBQmYhCZmSRJKYXgQwihbva3+xACO4f8r3mdmuS1kkwFMipX5NmTMQ7DYX/YL1fLZdMSUYyjd26/3/74x88uV/cv7jxYry7a5f3333/3F3/2n/vDb37nR8PT1KNGFVXZoGA1ZefgAS30dCIYqUnOhU1oC4yJzSa5KJS0DCS78ZbZmrOBz6p/BOOpDROIyBW2KaZGTtmUOXYFrpVs9JGbqcMxecacXzo145qxqeJAsRZ8uGQqTvZnypgNzWwBIOemTlNbRcmlWHiikhq0Y/A0WYSjV3Si1VDEeOmo0om8WU1Zk4zjZKeJS9oOKNdNnEufGUTIjDPkYE5BRVnP2ERlvVz6FVsYQ7AAmJcQhUlVYjeMcdMJAlca05iSBDiwCEXlJLntoEZHRc2spFMNxBxj8kEN0o1d1+3WqzORQxVWX/ryK3/rb/3Of/X3/pv+oFAkic6FbD+Pj2J6aCg7Hs1AZnn+OEEKy9M5+rufj8/HX8SYcsgnpWrF3SZV8r4JHmqDUqy9/6Wf/eLPfv1rbz58tbetZx1SjLHr4360vWNRk32/f765ckt33W+jjW3TjtqC2mQRBnYUSA/SjZDr/ebZ5lYA51tyFKMc+j6lPZFs90+Wq7ptFiA203rv66Ym0mfPu9sNV7UbY58iTPejphQFOlQewXES3Fmd7brh9mY/jH3g5uLyvF01ow67/dPtZr+57eIgm9vNdretG7e5PW+X3PW3m82Trh/j0NRVu15Wnm3UJFG7bui7zgXfNHboRlBiNyRT1d4BAYNLCeyC21+EdOhuAXiPcbTUx7CsyY0mE/Bh2cLRJNrywlq3kkuYTeanwSJ26j+a6WQ5SoxYkJci90LzV8rvLZOGKWf/8mmOPnTZj0rE9oLFYWNkxzSDQaI0Z7iRi2hAZDShRfnENN9kmWcv3NHRps0u/8w/nZy96dcnfysNeY+5ljxtpzDheCorlJIphzMd6oV5P31jQiimTewEzZ1pL8fnc+KEIt/4jFlMdITToWbnZ+e31zerpqaA7c1YVfjyV+8/eGVt1N/un7u63Y0D2KsijgYFhBw5MpeiQEBqGiXCRJIZSUpihgh4LJcLFwwyLlqQh8FyqJWB0xRVhEmNCQRnBoVazGIeFAeJEd4Zm0lCSmakar4Kizq0PoT99unmeug6sJf18jxUTn1KyaAKJFWQhUWzzFAE5uI4AgBfVU3ThCoQZIyxl9EHkIcaguO6DsGF8TAOwwCPyqOiIAP1EsehBwiB4QxEqBSJdMAwxmCOHDgQBdscdlfPbqNGGQhkLoVK637sLbtEwoCrfFV520eMphBVEXYOrvC18+x0jp05SeqcMzWQEpgZYkI2yZuWT5fd+GQST+jPJGVgZWZNs3J+HJgXQ5k+c0JxWg6FO/HC8qCjXzTDQMeJiqPvUJbRJPpbYNhSC0wzDHFyJaerBQU64MlfpenWXyoZzN8mNcqynUfzg8nSzE5hKd0rQmMKQF7wEIsVsvL8pmQt8dSNmlCUpCdUgUC+EPbzmVlZTbNcjhWkanoNsySDFRIe8fR/80XQS7DKbMpOcEQDMoY+PT6bCpjmgiZMBNsMNDCzmZ6YNxwfzouv9y9ofNbBPwXf/IzhM7BTYBuAOcuiGBE758AsqibqSm0VCAWaSRM0Y0fDPunsF7tcHjGmLSenF3IfP7Lc1SsHRZiAzzLDchAkap/kVeF0VUxn/9TbniGt44pSYT72mJvxMhCbipnmAEyLxoumVEhPGTGp6nqWHD6ZPEXkv5SkMmluJ1+Oo6pFvIqyQHQ5tWaG0TTpVUWJGMwTmmiCDIrAKhPVXLDDjslQOvoZkGXaiVSk3G+RWs+PXZl8uU3HLnhVQd45MpCkklIikHcOABJxaQ2iEqML02wuC+IYRhqQ26XmW8gSoZHiOIwEYnYgm4qCJ6md3FPeEztin7mrBFOQGjMR2EiFwZYpkw402QiGl2zcaIaTRahUuLKVOWUi0tZ1lrsjMHtAyRyTaH7yWeI9Y+lmBmesIEImy2VwkAm5t7MFUCBB1hSyEsjlsqeCmxtlVTAqTU9zx2fNGADm9m0T5apMOwUbsXOOXGBzePPhG5vdrZJUbXCBfBXqtlbVbt/tbw8//N6tvp5IaEg7mL3z9heHQYIziXLYH1QkrGrn3dXN1ZPr6+9850/WF+cxDrnn2/X1ddfv27oOF7QfDkvPT54/Gw+xouqt195696vvmcrZ2Tq4kJDef/f9b37wxzHuwZBDbM+XoQ6kW3WK3OaWXd3UTduGEJ5fPeGKAwWLtl5wkrFdLGCAJwCjjGA+DIfdYdfFvl20iEyes0/55ltvHQ7dcrl6460333rrbfbu6vb6O08+3mxvu74D2RD72+1t1NExVXV9fXN9cefy7t3L5aqhITX1wtfe1+HmZlM3rfeeybV1u2hX49gZUnDeCINISmkco6981bShap49v/7C277y7RjhWlfk6Rx87frNgf0qDh0FchWaFjebG98GqMUY2TmLliqNMcU+UUConarkbm8Mz+RlTE0dPFqT6IhhpVtFTBJVWTNqzGYKgZoykRmRWlKJoqpJVNhosV4Oabzd357Fs3O/ury4/Pjjx46JmK5unnz44Yevv/GVaO7VR3r3/NXf/q3feuOV3//7/9M//OA7323bQCmNh745WwdHUSIqePN5dfjAAosizCBiVVNRykJciiPUnhuDaunOwTy1ndOMGWdsHGUN5P0CRdaNUEqwwWXXRMmF5CWtIICJg3OBwSSSksTiu+SwQo2YZ1B+tvG5O+C85VvWtpyaIR93mRP93bzgtNCjipmaO9KUXCDDlHKHwdxzOrstLzDSiRikKF0yHByRc8wGA6fM9tZcWK2TGlU+RbFkMADOcnZENFlSCuCamUlNFs3q7OzML9Dr3vu0rkNYohJrCEzWd3sZjKumDYHImjaseLFoal8TkUb0qh7mmByZp9ybVQTQEHg49ORJ9dDFTVi4Ll1HDGncL9bLX/q59//D/+Bv/+7vfesf/cNvHPb9+eXZ1eObZuFElIp8Rk46Tsb+GCZNLQGASeoMmX/6UlHAJ3ftz8fn4yePgqSfohNZOYeOHyg+KBWUXEuEZewqZq8aRQSMB3cf/Ju//Vtvf+nhvrsmRHMaKr/p+kH7SMOqrZS0T+PV7TUGfPD4e8vz1cP796Ms2ZE6GCHa2JLtx56q5vnm5vnmto9SNa0x90Pf9Z2qOEfiwn6UbX+bxsFM6saH4CRF7xwQ333vzSQDDRbTVpHYhe6wG5ONUYdB2sNZvajWF54PfOi2Tz7+Pl0513g1ubne3l7vrp5dD/2YYrdcVld+t+h90/D5atnWqw/+9OPRj4GXBE6yF7nbHdJu1xvpeo3Nbg/4KDbIIVSWoq0qUIpcVY43bi0Xd8KDB9g+h3dhTCn4ijz2h11V18w8DKN3FRHh6H5P0WzOcMNytFkwbhyNdX5RU6vuyULMnzlN783WdjoEcuYQmhPAzEw5olQoEooWmhlAavNFHds/58glm3uU0E2sBDVUXH0qEtdS7mhSRTxKN9rUiuyIt02V9Hkuqql3DnBJtBThF1HG6dZyAOP4RbgORMTgOR6ZcirHOn6iYnan3efkjyFfh2mOZaYPWdFZtqKkkjU8MC2V6e3lRVMu3yyTV16ImHI21sh7YmNv1RkePFz+8q/+3MWjcHt48vTqYx+q3e2NESdxIgqGJgtgE5ioJydZMid3vcx91U05mHqcn6+c56hd08DX2O+2TbsYxzSOCA7DEFMSQJ0j7xwzaUr9MHj2i7bd7YZxRF1ZFJOEOGifRlNuq6ZpluP4/7L3Zr+eZdmZ0Br2PsNvukPEjciIHKKysqpcdg0e2nPTbXXbD25APLQYGlrCSP3CAzwb8QBCSEi80P2E+AOQeADDQyMEqNXYMlILbFpNu92WKVdVOrMyMmO69/6mM+y911o87H3O70ZmurBRg2iUR5GpiDv8zrSHtb71re8b+y70HYBBXdWLReNqvx+2NinWhmTnrlkslzHG7jikKOhhuWkBMGqqm8o3NTElTTHGlMAMPAAhEGfpUK68r2tatYNHR+aiqtUEjFOiTAba9YekQgCuYmOwCBJttVqen92XCCIQunjY7xjdGMPtq0NdOfYOmV2FzaL1deXQb4OFsU8hqCNSNDFAYu9QyhZLjGiklmQaVGUazcENzUN1rkDBzJUoChKiBgqIZNP8vDPB50KWTbJ4OduZx9s84U5TYgaDJ4hVJ1yrYEw4gU8zPjyrUKlB9sjLy4RNtKXptMiZB5HpDNk+pyR584fnzlmbcKy7nVvzMDcDyW7bNKHWJVqzzJ1ELAJXd6VfJzgaLHfaKGhSImJgI0g5XM66O4jZ9lo1+crnl1JwMTRQQCE1NRVEyilxrpJKfrn5DSIwz61QMyA3w4zTv6fILDf/aP4PQaW8TAIsXQV5Gk7LY/51lc+qIc1PqaAidufnPxdRev3N/6mOT/3wCcn5oR8+XdLnXIMbx1Fz95ZqhlnyLxChcw4RRSTjOGUdnp/saxdyQj7xzqqoVlZrQgRmQlLVOdCfpX7NIMaURMsdAaiUyQn0+mDMJ8v621D2malL5POfQtlxC7CqKjYHSmVO0gSFKqQYJ9BJT+YEhEgMCG3bppRijHNXYM6dZt6BJBGVgtNNiuBEDACW7VG1ECCywygCTWsFwjzpS14FM0aWYvapQyLOGvgGliwRoGo2xlQVoUyNQ0BEh4SECsBIqZCFEMpcIwISFTERUXbEzIxshXEx7dwAVV2pWpKU221mUeOc784PXVVFlAmIyHmHTM65GEYiymWfSb7LkAghk0GwkBYyPJR3YMp69mSolNNTYpdZQ0yKKdMiRZKKWhIAROJ8XoSyIacUYZqNRMRMZoAVMDEgSkqiMocsQoKaW49zmqq+8uyc5V2YwJxSVhi7M5nuVjg4Q15WSGBT2A0F3p/XfLNiJGH5bRMzOc/sSFmqZYUjakxAXDVNJs2BwatXr56/eAYIN7dHiRAULs/7FFLlqjhGMENy6/PNxcV53Va3L14+e/70o2c/uIJYN42hHvtDsgSozMzeK9j17vbm+c0HkdNobbv8iR/78ZvrG2YcQ+z6F+8+effps0+2Lw+LVTtoBwkW69YaTSnGEIlQzMYUOYxOk2vrPoVjGEipqmoBrbx35MgRAz17+TypvLq5vr7dogf2uU/ORGW339+/ulqtlm9/6cmjx4/Rud/9+7/76sWzP/zD/70/HnbH7Xp9tj7bjONIzGoiaPv97cOHj98ID+9dnD+5erQ5X1/wpa9rZDbApl049gyOwcUhGkrTVuS4C2nsxz70S1637fLy3v399sNhDIni+TmEFNnX7arqY4g2GkBIAxIgG3kAgBBihBRNiByiAx6yuwMQeF85RykiiFrCOEoYU+X5YnPRdV0IXVUTEqekKYXjsb937wFZnrpG5NkpM9euYecqrrzzqgSmMUnj67qtJeoYx5giE9euvticJ0tdfzS2V4dXL/7gf3l12N52hy+9GX/6p751dXnv5untH/wf34fbYfPw7MVhZ6be142vShXHmYkpqCEQZzYpAki2zhWVylWAIDElEZgapUW04D95hWM0NeKyvpfSE0LSVGICPXm65vPOeoIAkGuJZgpI7JCYDDRJUhETmDAogswWnShiuUyHluvqn94ETMwoFwFK5lAKCdMupWZAxkx5ry7dkVgCfCz+owVVPClvlR4WICJ0mG0O57ALOR8OwEgxczvHvs9WIqAADgDB0JQVAM1UDAkVKe85AgzGmFXPIIGvaksoowIYO14vV+uqqs1qNNRws79NCsjgPXqqfcWttY4p6XgM+40bamiQgcCoGLkCctmN69Yp9kPaJzs6dFappF6iQOrB2a/+8780SviHv/+7YjwchqqmuqnGcchvYhKryD0A5bHAVCC9GxxOa920yr2+7X5xfHH8mQ4EfH2A3fmW5bLUNBPL/3N+xiaCldekYxchwF/5t/6Zn/6Zb7391gPVvg87BlKhMR0CDG5BynY9Xh9jpx67oRti9JqwctWiBrQgQaIEs6ppXeO6FA/98dnLl7f7o28aqipEAIK2aeplE/qhD/1xfxi6A5CsYlNX2HX7oe8R4Z0nl+2iBtPDYTumY9W0h8Pu0IWb7e2xB1X40pef3H/40Gx4+fLp7fY6AWwu7q02y/4w3FzfHA7REZyfLzbLZtH6tublom5qIva//3vPpEpd15s60TCMOo4aoomKr9VVTRQdx2GISh58zewQsroQiWH/rW9/9en39Lc/+tBhatcbiQGnkptlmoBNTXAlEL8znUueOK+XNoWGhdMAkOPb3AhTsIwScL++MiACIpeWwdyNAYjsEJHZZd93RDMqzRp5R7FJjPbU9GC5TQJUjAycYyJSs6QiSalmxIl1UQStcao16hzW5XvJ0hj5XoBItZQ7ci6g2ctn+plyz1CSQ8IiQo+T78CJ7Xx6ep8d8/lXZqjJTtwpm3MkuPsSEIte4wTLTXmpKr42e+ZQFafiz5wK0vSXOxglUkjJ174fB88SCB6+3X7txx5fXDX/+MM/+t77f3SUzrm6DwrqmBhsADUVYMPKe1JQFURCRgQ0lZQM0FxDIcj5xTrCAUmaFrhyqjIOQ0q5ooYpicQEZJ58/n1TsqT1sm7rRVMFNPGurZhJYtCURk1BZBhBjsfuMMYANXiCquaqYWAYx0EtalAjSNmsEsF7vxuP19fbpl7ee3iOxsNiLObyguBAxUIAp+AIkAESIhM7N3RRki7airGW0RJGJFhuln0/ANJiuSDH0WIcB0VANvbOeWrq5uGjh1VT9123vz12hz6MCjH0GsBgDAkpkeNmgdao97yqlrEeJUbRpFE1AQG6isiRjBrCmIQdOqLstmmqmbBQinplZMBkaWdZPjynhBnGwSQTOGVQANGcyuSBdIq+7DUVts9u5yeU7DTiCh6hJ+TFJs8yoqljBUwVsuGoqKIWNpdhzrqskPNhmoR3uJ55ocj22bkzUV8HznEyLbwzB4rSfDlJDl4nckkOE4sJTkaQYJpucEeVCHFOAbP5MzMjISE6IMHcVHG66fIroGpaBPil4CZWVK7z93HCpMEIwRRLWwEjZkl+kDt389orKKuhzQ4+GezLt5Dhwlx5JSAgmB9+vgwxAAWdbjBvo85lWO2HwEp3zv+nJkn93z7+NPGkG/redB4AUCBJKjxAIspyTikEFUWGHL9nO8bPflwezDTRiJiRnTM1yArmpUJv01i0rI9lmaWUS9xMBmZFab0giZ86SfmEGYN8Tbb8s5dUwh08pSjT/eK0/Ux/ETPLy9mszFsAKpxJNPOEJKbcgDOf2qZRWqYHAJyexlTOtrtbb6n2ZJALcr5wp3SSLzjFVAwH7KRvn38OrfRyQkGJCpg9YWpkRQUmm+pZwbRzz23mDwExOUOQbKJFyEQIgMqurkwUE2Yyrk0rSL6NcnEESVJ+63nA5LmVVAiFSkiTux3BstOeGokpTXCQZYUCALTsUgmChMgFEYdccM19dypSaCyaGdrIzAQIDKRIlt0fCksyl9ryuyvJLRdvRkEFTYia9RfyvGdG8ugqUiislFIhM0w5czM71SSpYOJEREBip6Ald9bPBYR50EFZFwyZMG9CiEx0/erVELqE0Rs7T+2iratmtVyZGl/fUDX2Pdy/qE1HU9ve7hh9CmJGFXHeZxQUCarGA8IYx8V6US9Ww9AToaiNcXh5/aKrGg++TyF2cnPYhRSNWUxT0GEcb25ePnr8+P7l/Ze769a3z4dIq9X+9oBsTGzOiMjQhjAmNVN58OgKDGIKcQy746GmquLI5NabtYA9ffaUmPfHIwBKssVitV6t68rtdtsU4+FwePe9L7/95J0hxX/8B7/3W3/vfz7sbwlD3fLCb9rVEmq6vt4eu4Or3YNHb5yvrtyyera//uTm2bqtFGS9PqOKlmer435wzjmuyOGiXfXdUS22zUK5GpO1i5Wv68VyuVpuNqvLs7NjSooO3nj49icfvXSO62WVxsBOkoMwHoEBCeu6chXGOMYE4IidI6RmWSNgSAEKDESSlAxUQKL1+0EbV23WTd0ApgTh0PUuCICohs3mEoC9942rfEXEQsjElZpp3gTRLI94x8wOUdBj1NANR+nDmw8eQ2Xf/eB7XezdpgLzn9w857pVoa8//MaX33zry0/eBILxRs6/utqP/fH2tl1u3nrj8dPvfh8AABXAgg5IlBlTCMjsBASh0JgMprLtFNAS6KlGMO8l2ZvPsgJhWadOi+O0Qub9ckL5jZmJyVgNFRxw7YgxpKQqOUQwJcPCfp4XllNZ/XVK8zydKIvhlclWtv5cVZjJvIZZN89Ui0MiTgUWJKTikFp8VLEsy5hTIlCYgD9DB8wOCXPG4/LPl65IBIKqbVQkDREY0FFxjZnKgkJIDs3UWMEDeFOvSAYO0qj7VwfhIDTWCz3zfrEmAUPPi7ZW3HRxiyxg4jy3deUjqcRDt3v24uOHT94THQXGiOyAszWsIYiJgrKDUfogx1EPkpSZoE7oVb0G4B959wm56Ou4fzWe1dhW9e7FFiucNj3CbOKBOX/LhZapmbKgWHdSq8+EuF9gWF8cf9bjFMIV/PQuzX3+Ar0mKDmFFakfqk2FiG4NieGf+xd++a137g3xxle2aFkgHkMv2AlFAZEU+rEfZEhgxri6d+5rz3Xtq1pAr7e3olrV1S7sqWqf3xxuDrvbw64LcVFXq6ZCxpjiYTwewhGcdCEOKQ2aICUACQmJYLGqNIX9YR/i2LZ+TMOQBhZGAmasaweYlmeXzHZz/fzmdtcdr2vva4d1xQ517HfHYwSFuoHVktcbv2wqIk3DuN2N/SjLJUqCEFRlFJGhTzGAJBY0pOriYhMlcbXzwVZrvrhYsCUYA6AaSdT+vffefvdJ/9vjhwmH5dnDQz8STWIXUxJGhZfx+vKbp/uJSJVTUrv7phDp1GM0UTLuvsQp3YRMcylC0khFq2Q6qU7q0TYpwefVm4iKpqsBTObXZiWlKKuUTX8UMscpZ+dwQpRO7A/Tk1m8zYG7KlIpwuZT4Cl0z+6zd9x2ZyCobDAlR5j2sxz56Zwbf2rcn3CledGcnlG59+kpvgYlzoyWOeUuz4rBZsXYHJDKKb++M91wesXlK4RqUC+bFEHwCD+Ab//Uly6vavbD7vC8Dwf2DaM77vZpnJkBAGLM7IjBjA0AkZEALVkwEUAwVejh/GL1crdFUsqezxJjUBEj8qhKgEbIiMzos/oKYV01jr3zVVMvHKWKfeNWxOkgnYQwdFG1G/rYNJVztFxJ7SvnOVlvCQFkHAP0AC2AAzWNIZrZOPbdqAixbbXy3teVjEOSOCTxBMyubSTXwx27s/aM0R33Xd+NCHVbN2g8hMDMy2V7eXZ5OByP/RBiREnk2W9qGmzcBVrI4zffrnxF7G5vtzfX2+GwhwREjhBUk2M0sRRBBhlS79DJmFzlF751567vDkMcBLR0uTCigIwCAOzrQgxRBdI7OUYu2mct5wyl6pzzSlb3BSByWqzmDAoqMy+kZR6VhhEqJByYGe70GeZKIYPc7QecmxVhrhRm9R4FBTDLuEmWedI5JwIAU1Oi0zpS4k6axvnr+X0GeoFKRwwBAsGMuqOWSyIm0wl2mPS4ccrrTucuyTsQkeV0sHQTwpS5TghwsqQC3rhyhMQIekJC7DRvp72pNCUooJIZgsxQWsbDJjxELa+FQFM7A5XAS5ULz+rOvc9T2HCWeJpHQcFNzGAKesEAFSbRJwWZpH7sTmvipLBRkL0TcPKZw6b16v+hGO+zH/snwTvOAE42TvNgQzTLEl+afeInPUDIzF4RySSlz5wYoOgloXfE3vmqyr14KcUyIoiIWVMCInIu83slJVUFRPKOABNGE/0cB4H59qb0Bk4L86fvMD8F59x8R4Aomu6AVhVGOvcAACAASURBVIiI3jnnfXYfmx9TLteXwYclkhqGITvgIWJ+LPlRxJjprza7FppZSgmnfmCbw4I7L2bCuoyZM0poZiEEU5mrL2CGgKop/9NUTcREjfIVlscJAMan2TjnnGiWJBveA8zQi0GKybe1c1WxsFCMGkMMAODIE3kkdMjZc4wcOmIABjM1iyanGAQBEE0tpZRZkJYT3FQwSqPc8KsFprIiK5dMiXIwgUxuUp5BQiOagHYzgCyqlWzaLfN4cMTihDIbXKfkV0RVmL2W0VCW4hJjSVIRUc2ed+xIC8SeWQvIiGMI6myEYGaCgI6YmMCZCiliNiyZbTsUEQgBQRAICylwev5zQFLcbOfIAzEHaiqCYsJqKa2b5fn9JTAapMWqWa2XlasZeTj2+5uxoZobe/jg6ktP3tqszzar86Zux26MIYFpS5r1lS7u32svlh98/INu6Pvx2PLC1947v9/tX96+2m1v2qpaNZsKmrqpwfMxjt//4IOx65ZNYyaHw9E59/Wv/cjFxcXv/cHv7V/dfPnJO6+2137Z+NoTo6HLhbsQU5Bx2x0qXxtYNw79cSDBi/XF4zfuXz18OMDw7NmLs4sLdOSs9t7/7E/9/G57++EHH2y3h0eP3vorv/Krzw4v/u5v/eb/+Jv/w8evPnzvKz/enLfOezDtjzG4RI2nTdUNMYVuhZeLdtlRvN1uw/HwD/7QVlV7dfX4YnOxXG36IR26MSStvfdYX5xdqqa2bQeJlavvXT4AVAPruvjJJ89X67NjPwja5cXlB99/pmkAJw/fvKyq9nqxu32158rVrbu8fwG17roXw6CY1NWqOi6a1pIlRjV0zpFSTBxThAjjoBBvAVJ33m0u1oZ4OB5Fta5h0ZKvmt//g+87hsVifXl5ttksHUNM4bA7Hg+7xtdXF/fWy+XCt/fOLpjdOI6eXV37MQ3vf/C9n/zSjx0P+4T68NEb7/RP4tMPDBjNP335wff+6PtLWP7c13/xb/xL//KDs4v//L/4b77/8Uco4muHbGPs2/MFjSZg6kxEEYEcsznMzqG5+9gshtz2S5XzgJZERIw4dzJk7cmUy2OmprmUxCMYqAF5nrRKYIaJMxVrTg+QCBnVgyF675xzgDb9KUuSqpqYJal8aXmeMyD8nO0MwHKDMTGUmjjkjGRifllmDqmmbI7qAMkIiZlk2j+mxfOUluSzmk7rhoKqKBlzxuQshQTMOaOIKYgqE/mqurg4B4TtbjdqWLWtqQxjx5wthBQJqUZDquqqXjUKMUp0Dttm1W9t6FK0DgDGW3iaXvqHwst63wWJiJWQh5DiGJTqtmr8ql2c8eZsufQNGaQEaQgdqTj0y7pVEoExahilB+p34zboftTt9nDAUZpF4ys/6Db015um+Q9+/d/9+Z/7uV//d3596OjF9473Hp/fvNrNRAAsESjkPhjkyTgFc+HOThvv1EXzmZf0xfHF8Wc8pmQJJ/LnnfAaCYsZApwKkwCApnH15lXfH1zd/4Wf/fY3vvnmz/+5b3Twcgg3H3/8A9V4cXWvqmqPKQLcjn3sDsN4/O4HH374/H2sCVsX0oDOrxdtqprjeACATroedb2Gp8+ebg+HIKmPwVlCzwC2Ox4++eSj65vbe48uK+8rT65uYxwOoa8VFi0DQBIYooxh//xFf4w3yvrWo4brtgY/JgFKb7zxcLc9HnYHTbZYrI/Hw9hbs4hjn0zi1T3f1NzU1HheLrj2TkXjGMYu7bbHx4+e3GyPKYa+70KEY6/HTo/DQI6OY1wARgNBWG4WZ+e82Cxx7JMKA9aVA4xnl2dXVxewBB4AAAmdaMJsmWolyMfC0zGCO/nTPO9tTlkBJkWbedU2s7tygjBVauFuDGxzx2iBbhARDETVVHGSQszqk6RySmIQnXNgpklO0BWimRE7VLAEAmKgCABZorFodsytF68BQa8dBiY6J3iuomLdkUO6XCZAmFKDE/xkE/A31UgQHUPB4LJju+Dcx/CpUT8PdESczlXif0SzTDopxIqSShdJ2KyOg4amUkRn51QWCp0WCBlNzGRepSfN5tewSUMnKmOKVRubmoLqv/lv//WX/QdPn31nu3+GaN0x7Q96cy1OgoQS16KpQ6x81cuBidAhOwSRBMCE4MnXFCEtl80h8sJ4O0Du6kiRTb2jZhgPm+VyDEdQq7x3hCEYAVVchT4c5WjJyLjbhW13M+zt9rYbBh0GsQSA/Tf/3JeVYmOxrmpD6LvOjJpF3Y8DOLi455eLtq2bcRx2+72onK/rvh+fv3hxfnbx6sUNsyGZE2pa1yz9pl0uFg2IaUwQEdEteL25/zAl3N0cdtt9tx8cuvPN8v0P/3jVLgmxH3sFvbx3uWjr3e3tWF2f379YXS63N/tPPnohUVCIuTE1iKrJTBDYQMAEQEB62R5utw6WF6sHj6/OFqtXKmoDN1UcNISAWKNHromEqoUfjr2SGE964zCHMFjEjUABsKlrJFRNUw6aEVsiRBWxbCxQhu4UsOXxrEaZ32BFpNwmhfNpSr4GO316Ik2GN3Np87QSvL5MIAEaTvBDBh9m9AoBM89g0oyaRna+10wMYQPNZTsF1dlIGhQhz3Vi0Kl/ErF0+EkuzuKkOYWACmwwwWeWGe0KChkURCq5W35nCknMKSFRJjoUnWwgLapYWfMZTLJZkBVATRAUQA2MshE26LR+ZDtDUiNUU8i6zzkEyzgWvf6YDZAREFAMeMb68LOYDAAg0YRLTEg3FFDuLi6UwdAJyvy8svH8gdN69ekl/f/1w50YJWWM5Po852x/dpskIufY7KTX+ydds02d2PY6HIYqWU8qf5Ga2jJYzGwAQKgiWSIfmT1RlGQxGXyGgpVHxlT4nXGoz0JdE+ZaJlLGYZlQprvFLLUOkFKa5+QMGWe59xm4RaTMKcBCOijPQUQynJdPJNnfQFUk5Z0v62nlFprX7qPMxtOIM5spXNNER0TM4sQ0PV0QTQUywalbGIEIRWx6QDAtWSqmxR4vf3MqNBFglsIBVaWpTx9LHwwiGmGQlIWdCrKZn72UfpVT7StvqBM1rGyiNSADM2W6tYiWbwGAnWpXNLVun9JVyC/WisEEClpRajfR7LEIAAyoIhYBUQWKUQMBquksjwB3SrWqWqjCAMIIZorRDChT3ImMEB0aioClcjWMiM641Cny/gCcl/qyjivmjmljnFaI0/vN4QWRFjx7DndURRAU0BgcJUkhgkZhj1VVKerN9c3utuu77v79zbtfesc79t6rQtcNKdw8uF8DkPc1gm0WHglCjFGTr327bEaN4ziEGJar5f17931VOc/98XAc+v6Yztqzizfur842Q4o3+22FBIQpSNMu9rvDm4/evDi7fPrRR2+98bZEbXxDuZpnEFPQiW2rlrCqBU1SGmOgCKrgnG/aVkR2+72v66QCzKtmxchhjFVVP3705qPHjx+99egHL5++/4P3v/Od715vb9mto8ZX1y99JWaqJtZAGFIfuxHikKC3sfVLYUik5unjl0839fLQ97dnVw/vP2bXyJCGPnSHTjQsFwuRqFH7cRyGMUoEhP3+cLvfjSF99WvfqL1rF6uziwsTFBCwtFgtLi8vl8tVTE+d56rmuvHKAgaagDyYQhwFnBGjc1yWFPDso5QmdpNkYwTvhmZZg0tJLAn4CpCZiaPgGCxIz77humornxL0Xdzvxg4HMk/ozh6cI1OIYeyOntkxiibrowXRYGKiYK6pAsbj2HlctKvlumpePX/+8urjdx+890s//+evrw//4X/0n8EalvdWdVs/ffZ0uWyP4SCWEBFAU4KKHHvOpQiJSVVygRomuMIoUx5LgH8n2chDuvxddR7IRbCcpsWw5JmIpqqZHpXFYwnZEXsyyDNRbIJByolUQczcicwzTbNPL+z5mzOflrLnMEJWCfxUmRnUgAqjck4M1JSsiLnObdd2R8zXLO9NxKCIxkCmmkRMDLM4vZqqgKiYkvOGIKoxxdy4rWjAQBWqEUUFRlc7YKCKyOVmTkSH7Hm/P0CMbuH8ktCli2V7eX6xafxwuFUZCZQd+obQEYCIJEMhT2p66HYIiKRmmmIQ0IqZK0/cck6xTIZwSDii0yC9pACWFOqEMSAm6Q52/dY7V//Gr/3a3/xP/tPllT8ejlOcR1NH6Kce5bS5fB5YZXfKP/D/gcjmi+OfumOKiKYcHQuAdbcyR0SmRcpk/j1A9BUeXvRfee/tn/mFb/3lv/xTvd3cHD70PixWOWfcmboIaUwS4tDHYQjDmGJUBQNSE0BkSmb9MIpB01RBEzHVTTPEQA4XmyVUvqqbIGEYh5v9zb479BG2u916vXGuNcNklgUP6rZdr9rhuE+mEhM4r6EBG9rl2XK1iiH5qknJlu3ZOGiMUFcEAJVb9GHYrFbOAaMs26qqMI5RU0Id4yASzZRqajaLJlGDGFRSjNb3cDyE/WFMio7gcOj4ZnsYuhiHs3OOkVNyziSLMiBZ1x3QVt4hEDjnhn4QFUUh4hw0wsQ5KtSAu8friMcJ/M8vYoa0TqSE0xLw6dVgColgWurnyiPk0q5O/XiAmlWS7+ROJZ89WUwAATkkQ0gSJVNXCDiv7WDw2vpkOdXPpFqkad2HqdI4kS9O0BKcNkGDfHmaOSZ36aeIUDKfcnVl3GZhL/tslvKZo2zGk8CgTYLxczw5/9iEcsEJwgPI+hxTESifnQAV7a4v3fR2Xz+vgtTLS7FxGMLyDL/+07Bp/ceH3bG/3u1fhqE/HCQMtcOVpJAkEZV2A1NRTZrU1ZQFdlUSgKqhmSwWy+UVdd1uHPoQY0YWkmgMRlgT+SRQVU4FFY1AwShm82vyIhqjoJAahCHtXsXxgBrYY8M1RB9HG1JUcsjEyBpiGmUw5RiMGayGtmm8cyJRxCQJAHlfqfA4pGEYdZ+0BqyBjbPoiEZLgyyaNiYOw1DX7vziUoSHoItq8+gKxiGkIaHh1b2HzaIJKb54+erm9kZEQgpC8eJqc37/Ykjjy9uXEiOaQyBGznbYoABGmKKp8dwfp6ABUhfTECJZGEZNWlXMC68GklLlKqy9BosSBVJWqQE0pAmMNcqRHE5de6JaYCkrkZSaudw+BSBzi2AuVs2+BDNOCjjPrDzmy0S464g1xU6lcgl31208zR2yLK1TKF3TAKQ7ZX8EnOlCkKPCzO3CImL32sIzfQJSjoByjFf8vGAK82wKS3IXVPncKXc7XWp23NFiHKETrodljqDRNFmQMrllvos/KcIxLYojpsWpG5SywbcpQsa8FCbt/SxagZDtnVWAClsMMz0LsvfAafktyMe89mbYZbp1hNKnqKZoeNLwg/IhCBPgeSdOy0n6/IDvIOqfubvPQBn/xCO9z8aTn3sKN0GeOCMRlJV9cbazNZE0IRhlcVRVSUo8rcd373FS/zJTEpGUspgxEwFzHvJmVtdNzNX8LKk4Zf9J1TG5yplgArNUUoy7J0GmuZ8T5xjHFEu3+p1rofIS1ExERMWKXxPAlAOdZpplceXCGwaYqVc4o2BQXh4CQO4TzCJiRFRVPj9hSQny4l0E1hQEkOdNpQDJmbCnoiqS6zmSUhKB1wkINg9WRAM0M0ZC5qyUDGWq30VeSwOxmYrKJLaFiqVfGB0657KPZgoxr0xGkHFcyKTEklHqPPTLTIaiVp57ZCb0MD9GYubcs5Y0sgNgQyYENIUsHoiFj2QIpTCEZOXR5+wSDRBFIk49QYAADslAU9HhEhBCxNzgk3UJEDw7x548d+PRZvvCqWmImIiRCEUE0FQTGBiZEkJWT0CwLLVQWqpUTSfdBDXLDs1ERIxk0zJY1L1kmllokyXhvG6iGapRbo/Nd2OmILmZkh2T844d7be7vhvO7q8rX43j8OzjFzc3+9WiOT8/QyQilqSjpjjas+3L7ctDvx2ZPDv8xV/4JloahmF72K7P1hfrs9Vy/eLVi2cvXo5jONtcxhjzW5KUxm64t7586+233n7ydsMNEnhfIVEMsa6q6xfXZ+v1ZrH88z/3C9/85jd+47/9Ddd4ZDSAMMZuHEOMgFjXdVVXfdePwxD2AwzpfHH+4P6DN64erRcrE1gtVu8+eff9D/54d9i/9eaT+/ce3ry4rWq3Xm0ePLy6vLz/X/7t/+rD5x9954++t9v17WbRhcEIgkmMg/deyUYJCZVqH8d4u98CU93Uo4blqrVjl0x/8NGz97/34vGj2x//9k8uVisUuLm5jiFsVgtJcbfbdRKPXbfvjiHF6+vbl9fXXdD16v7V1aMH9y/bdqFBtcEQUgq6WLaLxeb5y2sAch7HEEbp+0Ehgm98XTeEyTlicmZgFlTVUlQ1Jqcp5VUTQRBcTIIE3tfsU90wO58Ulqtmv++HQfaHoWoqWIKKqJEZd0P6eNjG0RbVgoHIdAzjfhz7vr88OzurVy+fX69XS/MMqd+cn59d3jt88kkfh9VyU5G73b5UGUDjg/sX/9pf/Vd/5x/9w+++/+F3nn1IjvowXFxc9dujojlCMpRoSRJoOOWHlCk2hQyZy84IRAwpE2ABcYLvS2RgKmg0ReiF7ThVLXBKKQARiNAUpkq6gTI5JBKRkJIkAYGMl5eiFyLQXMEH+/Qu+dphBmKAOC2yoAiUZXHn4IYALDPMc6ivYFqMFCf0uSywuc2wsDlOq2iurWU5SA9gSQUIHDvvXRLBREYKZPWiFdNh6EViXbeuonFUoGyNjqhATN47XzuBNIYBHLBDYAg6kkQ1aerFauOQw3q1rnwTxhEJvffoFD03rfeevBESsnNtU9cNgyqBMTF7SslMYoxBwCMzsgJIsnF7uB3htl7qmPoIvY0hUsVMbbs57l+NkN778tvuV38FYvXv/3t/y7nIUE/x0Pycs9hwzthgUm3OL33aGaYYfI45Pjfo+eL44rh7/ImTG1/722uRK005BYBZcZDIK85huPFvwi/98s/+hV/66W/+6LvP9+87P0Q7GgfAAA7E4qvtq+sumK9DDNvDPkJqFk2vQVTrum3bhYhe73b94dgu27r2hjameH17nRTWm9Vyw1HtenfzyfOX19fbEBMxbNbn7aJ13oWQEGm1XLeNM0xdPx67w5Plk2XTioZlbMViVS9itP0x7A8BEXeH3szVzSLXE5vFylA2l8uURoTQ1Fx5JJWQ9TVUQpA4WgpwHExCdexHTSkkHUY4HMfDYSCP4Cwe+0h6OI7soW5hHKq4aBwQIkmSwfqKjhetq2oHBnVTdftJ6I7y+g6UxTpn5eW5EggAp267E0QyT3ibaFlGp1ZEmIsQn58LTQXHIuOSubVQzMpPgThBXp2z6GuOtqB0L2E2TCziIjBDPWZgRf26ZOmFpDQlpwSkqHNkdjetnRKZchMZBUADMELC1yvPBUICgBkmQwTNCQ4ogGru4dLPgP92en4nANdO3/pUvWC6sPmZnR76nZ8qujilsjPxsGCCF6mgHHd/IX8emSkxisBXvvb2X/pnv3ETXwgO++P+xfWL7Q5CNFOWKCYElgVoxUxjiiqSNLnaEzkxkWighTayuTi7/+Z6d9gdun1Io3OIvoqdxJgqB0xsRlaUmIURDERiiKNFSIBsBJo0Rhn7MHQSekfoXdUYo0aANBrKctmQt37sx+4ICE3TLJuqvaoRrV1WIYRh6Oq6XsFqe30IY/C+ahauP4zQAhC4ihbLerVqkVQkDt0IETz6pd9Aguc/uA4jxACVVpWvFTSOKaV4tqmHMAzDEI6jQ659U1VstDBErjjEMOroqgqNZdAUI0YkZQIAQwIxFRBAKHJkgKZBdjc7PNhtf3AVEFGzXKpitz+QQzI3DH0fNHcV6KkrqiQwOYizMj/VJBN8bCopkkPHRgggUGhNOHfJTYGb2clAp1gxTPjXlGhPQJTm3IrpToKMiCqqn/G4LL26p2FcRuNpVuZ/TiaJd44SU5aAI69GJw8EKN6FNpE5cn5dBPUmSZl8YaZTTwDmiiac1qashZ35UiC5u4yndc+yaHKWteFkaRLLsnyzr19wRgHUFLL2VvEczNNWEUxRnRlYWXjyUpXpKAQGSRQYMMNyVoCCE9IyVQ3s9K4MpkXhBBvY9IU7PZ4FAsvKPqUhu7j2AbwmifXDI7h5vTK7A5f/kz7+NPGkWzUrM5Pc1ASaTAxMTEpRyjMQKWYPEFBTSVmkXJ1nVc198jOOlb3PYCqcJDOQlGvdReZcJF+ZiGhKVnSGJoxQxMyAmT2DgQAaKBJ6ZrvTG8KOVdU0y46jYwJEU81efWUHZG6cz/YAYqn4CoI657MXQX5rImJg7DizpvOLR8SkkjtrM1AhYCKyaJqUMSZVEZUEKqpJgBmJVaFoZ9mUCZXsrozd02vOM0fFpnkcY0TE0nuaq0kTXpYn6rwiKIAjcj6bi9GkNJ+zSTAwIBDQMqcRQQrSlDNRIMjsMZ0eZ2FMWUFdCaCsbGSSEiFglqsrTosAopVnMxyjgIEj0qzGhzkMY8fITEIp573T6kfZ5lfJQA1Qi4472GxZY6YCIMmIXM6kNSNvQIigufMbLMcFZT5mB83M8gMSMTECKZuzgjEREAMiECKbRQQzzRSKsrqTISkhIMq0CiAxA4maJVUCg0l1UE3NmPOFn9BPABBLmeiq+b9c3EMzUyNkZgUQFbMZ+ANG8ES19wwIqo4ARLfXt2MYx74HgbGPr+KNSXr08I3NeiNR1PR73/sjFbh5NSrCg8v1V57caxuHpk5s3B7fvv8GOFpXrXXajYf9y5cxxbZqL6pFW0O9an7kva995cmTq8tzGQUthW6Pw8ACFLQVTtd9tajvLS+W1eInv/aTu/HQxX6Io4lZ36Gqc54SAOjt020KwmLn7frR2RtvrB/cW16s3LL1i8Ytvv7O17vr3gasecnULtwGhnC+WZ+7Tbc//Mbf/q97levhVtHJ0NPLm9VFXTctIDjnnKsQoW1zC68Oh+FIx9rXZ4sNmBjyPsSX2+H5i90nN5+8+c5XvvzkqnbV7ngESNvDTtJ4u98GtGiSPyFFGwbdH+H6xXXTrO+dCzsm4j4O4OCw77fbI7FXkBAHR6ydjKkfRyAG771jFyERsXPOKoxRQgigRI4IaFRNKYEKEatxjMaEQBUhIVaqHFNsmuXtdjwO6vxQ95UBOCRVEkURGMYY06u6dkMYz5bL881Z/+LVfghUJ7R4O3aLizMBdW7x5PFX//jjFys/XO9uAsd7m/OzVft892HV4Gb11v377/7rf/2v/Xd/5+9s/+5xH7rzzWJIvXp1tSPFZbW+6Q8qJiB125iqKHDFoIqIBNmXMNvIogGYzwLqWUEPXQnxkR3SBGoTAAFIdrjIgTWCgYLLxqMZ8chhtBkjV0gESRREHHJu0QYAzOUlJHSURAkI0GiGlApErDBTK6ls+UlNQdEAs8ZC3u+nvQ3hTtOIQK7gGyCzJzQDVSxXkC2FszdP4UpmnFoUicVE1ZqmqdtFTCFpinEkT4tla6ACut60wDAGBQZAURM1QSTnK0KuuOb8zMbUNGwOk0vtpiUPh/1B69TWtDxzbVOZ4HDUF7ZlCE1rtHSA4KtKs58EU0XtslmvV826cU0kBCVAR0CVqiAhZ+OZpCOT3nQvbo/XkY4r70axaKJDMJK6ZUVaLpfHw8uxd1f3l7/2N/6V//hv/q0GL4ZOYhjZO/IWhtG0eBLjbMIFhgiSdy0iMwbLVWBFSlC2/fn547S/Acx14j9zGPPF8U/VQfh//Y5xMjGFKaQuEPadH8kAtLFqpkYqoIqpGQiYWlou1sfD3tW1qYFqHPRX/tK3/+Iv/8TXfuyt5A9Jj1Vr+24f07jd799ZfWnf9YchXO8OkYfz88V1d7sdb5ViHDu2mthTwuE4fvLxMwd6iffVKI6p2djHz59WzdrVbVNV3RDicNhvX+52wARNA6umvdhcgOk+BgReLVaEcRiGPu6JYb1ul6sFYl31FlJ/HA/DGG+2h+1ul9RWEk2N2dVVxUy1874lqoSd+sZC6Nq69QQCqAoxpCAQDA8h3O6PMIgAxDACgPeQUhJVMJdiqhb1LJ1jSimQRY/eAZCoButxEVYbapYIFWgKq6Xv+pCIGRgUs0iNgYIjRNAMDZVuHyidL3NekWuE0xwvbw4xy8kCTBnVidnxqUNzdlUqyrkMbTCZpdG0ZBgDT/bPJb8qKFOJMCXnyAkSWjm3IRDDZDeSITBDtFydVsxuSZMG8qTzgDD36iAiqNkdl0MzK7qJgDDZB1rOL4socEk2FQxUUy4GZ/ELVCBE4hnYwynxpIlAMPFlcr0T8K6jQXmeU+I9HSU/tqx5U3rAbFLbKgRjQwRGEDQDzhRihax8CRl/Q1MwMx77xHUCB+cP67/4qz/zyeEHwet1Ly/2AL4+3Eq7cUtnN1vAvjXFqsYUxiChca0FB8lJByHnkQ6AgGo0B/feuH8cXyhZn4ZkyMrEDsD6YWRW54VIDWwcI6g1VXs8Rkngua6YJFgK6lzlHXXjbUywaFuo2jj0Qz+AGvjYLonYiL2llaOVaKorX9feOQYyMZM+UNV65vAq9SGtayJP8RjdGmoHdWNVrciRkSqsUDH1YgnDKMddv73Z7XqFCJCgVN0YwAHo+3MwX9fN0q+QXMPtvfv3v/ojX/uffvs311V7DGPlUC1JTAQOzFJUFW0cImSLuiwFBYgiKMfdMZE+eOvq+e0LESDP1cIfB4iSnHOu9cN+zHpPJ+Z8ljLPTa84fxxklRNkJi6+7GBoUbK4MDFK0ZAAAMnaUGYwmVAne60TyBhZp95tzOOGAQCQEQGAbGL4GZDNRMHCbzcTkZOQ2zygC5hc4joBYcqGPVncxcCQAE+VRiiDGqDY74AW/VjELAedmYY2K8mrKpPL1Co0lMzqVMTSbDllnmo2WduamWbEJ9sagk4MF874QCZGpKTEhIRsJKpmUrYtImAUK+FQybmNJh2uwi+ZZm8WdLe5NoNZfN1yt6ICATOTYwUTikpsNAAAIABJREFUFTDDbAo3tW5O6NOd/bRg+Hc6uMu30BUHcQUt1YlpbcvV3hNaNCW2U+/UxGLLqMEPQZR+ePHyNdD8zwh74bQ83v2i88RqBoKChmpkJposgZF59uQR0FIS08x/LO8gm8Tp9PDvlCJO1RoFI7BMLrp73ZmxpzGJSu4lI2aYIhmYWE6Iub8QmCi7BgCUonkWGc9PP/PFEFERkuqphEIATAQgkEozZHaqcgjgpm1CVVTVyNAmElO+Q7HpsicmJSAImhQnPwOwJEmLQy6qWjTJnoB39pwCHUPee18/ym4MGfuUU8vGRB4+8R6LdvL0i9PHI05AckZTCRDQeF5IwKZ3kjOLvHMWExcBRGRPpaSZ3y8CqKISEmQPTmDMytaYN1kxBsxyXShYBOczo0HBBBQt8+1UExQA7oTsAmbF6Exlx+wqmDnPWQw5qagqOw+lJRsJnBKSZoYGAgiU0hgw+UmrHsEwSbaYZLCcNpe6BFlOcNEAjQgAiHOQk/FFUkRCEoAiUFBKGGiapRDU8sDP3zNVy5xCmM28iTCJTqESKE0xVvZczHTQ/C6xbH7sII9tA3v8+PHtbbPrtgBw2B1VNafjoqIihFTX9bJtj9Lf3t52/QjRMcGmPXtwefX8408uz1frs03Dvh8HZq7r6mpzFt64evEKSJURW8dvXDxoH1fnZ5ePH795vl5K7MMY+mNsqG4Xm1W1sFGXdcXBtvsbY/Bt/VPf+sltt//4xScffvIRCNKSVFVBxjB2u533m5r9sm7vL+9dLS9rrH1EGo3QmOHJ1TvxK+ntR4cBEJ1b1uuL8/atBw/2h/3/+o9+5/rm1VFBa7c4a80kjDGN6FvvvV8sFnXdmFlKwkgOYehV6giiVe1SsDHv1J6U4NktfPT8xb37jx4/WK/PNkNv290rjaNYQs+eeIELF0JTj4vGm8Td7X6zOXT3O2Rav9H0PxioguOxe/78FSB2Qx/SwOqAUVVAQAE0aQwSU3RuQUTeo/ecUkIEz56QYowimEQduCQ2jMqguc5iBimZqNWVM2BAHVM6HjtVW1RN49u6HkWSJDOAV7c3uWH74t59t1yNfdj3yVL/st1Xh0WzWvh6geQ39b3LRepeDcPu2PvF+fny490HXdy/95aLCt/6ia/2Nrx8tf3v/95vNVAJpmrh+tjFIziyxi+CJefMOU7JkLN8LqiYmhiyYSYMmRlNrhB3GFEla7lTEjYAQy4kTDMDNVXUAt3mInyuFJVuYkQCC4oG2ZXBMGcmQEU4CynmynjZWRR1+hR7LfqZsoA8jV1eQe4seNNaCVampYIxGEHGwwkASDFabihnsCxWcGetxOya6iiJqplmzQECE0kgy2pZt3XS1HVHQMlhERiIBDUiRqa6qpri+awQx8Ce6kXjahMvy/WSakwS1pfDatksGgcGYdBtfzzstGrsqlqsHGPF5tRQ1YSAySpLNg79YFtWB4AxRBNwjFXjXfKCCCimIdFwffv80N9aLU6aIaUooihemBN01iNgFO4YmurqXv3wr/2Lf/Uf/G/f+fu/83vr5bmoDUPH+WWJcUneyt4NU+dOxjANEMABJjA8jYrTKypfIpiYD19gWP+/P35o8fZzfgxf++drDWkKCgjERKSk2dgM0OpmYaS+9gYABNDDe99qfvEXvvXVrz72dejlulpC1P6muzbTfTgKcK86JAgKoyWoKGIK1oEJotSOF76BpGM3hBCo9V1KOVQQsJgGp02KlmQchmBpXNSoG/MVNG3dVk3rK5U0MlsiR6waTBTBvIeYhq4TYuiHwyB9TBoVRxkjWkS8Oe5STOxc5Z1namq/gMqIzTTpOA7HhadxjDEqkgSFBCzM4lxiiuHgfRVTJITFAkSkbVtyBkxNU6nTyoKrSBPGHsYO2pVnNOKECOQTwAgcwUE4pqZWZkZypiCimikLzKBoaFNbzollBVaa0O+QJV4vw+OMV5ff+KGHTT0bGbSasTDOGewJAtMJ50QEVJw4VYBQOO7ZbC4LXBggATIQUQm+cyiuebeagsjJFxHnUThzR3IuTJjxn0IUs3n3w8mYDBCBDNE4939goVpN3BWcTMeyItap+XXC/SAnRVNeCrnScvLFPT2pwrW68/WMH06PrFCyaCatAIBY0Yikkt3mtgczUDRVJM7lbgUwE+8hiv3o1x986Ucf/J/svUnMbVl2JrSavfc553Z/89oIR9gZ4XBXaWcm7lRl46yqtFxVLqo8YQIFEiAxAsEIISEhZggJMUYgJMSEgRkAE2a2UBUFlpyFy4UznZmVdkRG++I1f3eb0+y911oM9jnn3vci0rjsmuDKk5l//u/+997T7L3XXutb3/qWVt2Tq0/cqj5kut5Bvayz3GnOCAoRLTozRI/oojAAU+WrnFWyCRdfQoHB1V6DqZP9YZ8g77uUBLzPBiyKQ4xI0RQAc9GWNAVTzAkIwbsKjSShKps6FY0GSiiEhJA0KySoIOcDucZ7dq6u3CLw2W63y9rlLGakCIi5ajyQqmRlAISMMXh2a33tsnZshCSiKj1QYGpMsN/1w76Nd6nfJUsQzIMxIJAfhfnNLMbBe++9V7Nh173on60uFm++/cabj3/4rTe+8O17j4bbfpf3YqoiJWNdmG+MDKYAjDhN7NJ2TkySAcNis/LDi0GTG1pDdd4NXVQ1JMSAkA245OQnzqGOPdBO15uhIaKCjmGmmhlyBkAmKmp3ZpS1hLNlQc2AMUzRCow7vqKCTD6gHZcLHsvQCtJ9Mqth+rLPViLPTsVxkhfqgCmNxKL5RRrZlscauekkNqpXlBQsqiAgoKrqqMZMOM5+HMEFHI3MiLMfMeFRNwEBC3lifoonXk0h3yhM6hmIQI5O/BwolwIIIlNga6ilNPbEEI62dHZYS9w/algYALCNCNo0LFMmsNRbIU00odmQzFZ3xJ6mHmMwFTwiFouNUCxo4X+dfP4lxtMEYOHMrP8c4/OZY/74NHivvvn0Ty/vGX/Gw8WcCx8qS1aQscyMgCpix0SUc5aYNStoGdsxdqCZ8nNynIA3ABNnqlz3iHqMWCjKBHzARIg1AGAGxCL6jojOOXbjjDQbAcj58RZplbH4FsdMwviYiHBWKbSX2E/EVCCpUgAoJYABEBGdeFkGo4444kSLJEKA1A8jsQkQqQBMRWpcTEa4dZ75Mw14nn6fc9iUyyJkYsSRZWiTNPv0rnmbK/WbpVOKza8AACB45xExj+LFx9riaTBKsZwhoqqoqXfeBz+2FM3jJi8iRMjI8wWUfovlCRMTTuBYCF5FVVURyCEwGpiamCoyqIiB2dSuDOZ1xQwj6jQGjQzGziFRCeBVBSYMudw2FbPIUKTwQKBQQ9gREmFpJqomKoX/BrORMlFCNGeEpbi4gHtYupfinD4pSUUwLRDW1EVe9Yi+TXAgGGg2BQMGx8DMAKAI2cDND9sK8M6IOJbZIpkpAQsJOAu1d0zOk4Kh6He/+92ub/sMdQWr9WK9WW825294L6IAtlkvl+uVa6r26uY73/1OzGCS2Qf02Mb+3Q/fP6TLdzaratkY49327sHjR1/5ypdzlg8+eH972HsfCJGNzlbr+/ceKuDN7W3X9iZQY3BLx8E772LshtRTcIBwOBzyYQ+M5xfnDx8++tKXv/zpi2f/5Pf/ycefPnHEjx48Pr+8jMmWzepivb63PL9cnd1bnRNAd2g9OrdcPXr4KFT1rt0/ubsB7x9vzn7o3oN4aH/vD/7x//F//cOz9f3b2xfOUah9jmqSAJxICpVv6iCSdIKWVWwQ6GPs+9Z7Dt7tcpZsFLCq6PZGv/HNP0BF/tKX1ouFasryrOt7I26ahScQsbbt6rpbLJZVZR99squWzy8vH1TN6ks/9+Xf+u7fxyUchmF4+hSxiB5RHJIRTXpvEIccgCoOjK6YRuec92oCxMAlhYkGCGqScpQD2KBmWQ36rm/qipzVPgbnNCRNdnPVdVUHZ+ery8vz87OcE0Lf1KHv0/N8Ywbnl/dD1aSMd4e2a/uVfbLvdl9450fvbR7e3u3eePC6Rt2+2F4/f35LNxeLpbBrb3aiLvCTX/iFf/kXfvFL2fQ2Xn/zG9+uQ7PebPapenZzs7PdurmMkgws5zw1Wi00BxMwMiImJcRspoZIY1ZaJ1HDYmGtuBQAIyxBZqCooKBYWhKXUpSp2IQQHQATMiuAiqphVkAoalk81iaX5i9WKhVpTuDry/vLlHkHIC4bPMCYYiCiLPlVAjoCkJUyxVlsfmJX2/QGAMKYjl6LgXkyJCZPSBiYASHLkLIlSVlyMV/ee8xgql3bgSMVBQQkZnTMDgCstxwl9UOOElMyA7i+wxq4gfO+dwu/2+0v758tqobBHbZdO/QSezEIEdbnXrSpnFdJqkKcggdh2e12eb/LdX/pGN/QdjhoD8s6rN2GXKkoQsEctX3y/JOr3VW9ZqjSkLuUW0X2udJBLMUhx/XiPrgd+YXC9t//D/7e//o//9Zhe/fd9z5gI8eUsrEBgUMgMwFTeMXfwEKCJyjJxtnlxPGPJ4OGY6IR/twOyw+Ov9DHKx4wgIEJAhM6RhMYuTaMHPft8mLZxQ4Q5Ab+i//8P/vpL3/hwcXZTp6KHu5un7fD9b696+IQsyYQJRpyUrPFokFTzwiaVVIVeFGFs/Uix6E7ROepcq47HEKFoWniMKyWa19V+0N76IeYRE3vX95//fW6bpoQajJyjH3KoBlBcuxFh37YVxVXlRMREYwpt+1h3+9S1gQ0JE1Zs+Jh34kA4VDAkOXCX6algSdQTQKAKUkW7YfIRMgVhwrA1yAroGfPbxiiGbCD84t1jN39hxdGJpZdxRmjt+Aci+T9oW/CofK0CoREKgZEGRKF+Ogcrm6hzwlKMkBEcgYlY4/4kimdPPTR/X55jF5d2H/6NY4AdJLaNRspAWA2EjzK34qyqU0UBkBgE0QEJjQkRHTMgKCWtVROlG2C2RFTtuNni2ogFqGMqfDgGKt/9vpeytvA579x+vwxki9B++SZUwlVaYK8jI6o7Vx6OMuhlCjgqEfzJz/BlwapBPhFRHssy8KpHGhkfxRFaAQ1EzBEVRCCUswCkLmOKRz+xt/99a/9nR/r83Ml2Xe7w6FvD1BVTOD7rWgGtiSWER2QIzYASEkXvu72HXsO3mnpAFbD+sJfXDZZ+hj7TEkyxAQI4Lz3AZkYQVLOIlpXtSpItj4nR1A3Z3W1aA9DFpBsKQ/73aAZwNKQ9il3aejBw2IDjtiSHbpu6FLl1hRkaFNMfbOoqXJm2Ywq32RNoFrXMCQAlFCHpmnWq5rRsljXDrGP0SACamd3z/f7G4UdgIJ3DFqEksE7R4QpJe2FKsoqWNqeRxq6frjrr753/e4ffe/Ddz9cbzaVCyCQegEBQmZzaMhEjli0L4xSFFQAZGI0KWBTBkI8W1/uut319V3l2fugUVOfGNh5pyI4K8iczlWbFxViUWoeAdrChDcw1WRAhs4h0Ri8iEoelYVf/apptb2ypOctHj+DVnyWIzMeAjYrpk8GpESp85mJUCeygx2XpTHziPyeVDIZIBmyWZEqHXsLnnKIDA2mWiQd12OJ8cc4/YS59BJtaLrfU0NXmBrH02OpAyj/UkCZPlZ6CB4j/gnm+Dw0Z16kZd1OWVo79lgAs9Lvi5ABlLAgnYhqPF/z/OSL74wjXwNnpH2eKeO3TyBGeXFGaU5xhgnAOqHRTO/Elx7W5xx/mvfgP6fyQyeSVVVEs+YxQ8olpAAzk5SL9PURTyiM2FFfcbzck8saYwx46W8GQMe7QkREK2JPczq3yCGXiaWaYiJCx0zs8FiLOy6nuUE7TEiNzSMPgDyy3T67opCo0FsKoFb4O1YkvUQMrAhgGUxFhqV6xQxFAUFTRiiVLly+AQzzSWeRUreP03Ue+wb8iTDWuGsVME5NaZphL5uGWQ7fTEV07PdFJJLLNkVUwGabay0BAJlsxgqnNViQ79IAcV6lRIV8YSIChI5oXrAnKwQR0ESR0DuvrCllNSkl1i8NuI2F7eNlTBXSM2epUF7LfY7INVL5Q8lAHcFQHFNxRAiKwDhWK9HolJTRxwLDj1zw6dGrKgmImZT2ATiOhamazCBdIcdOgl/lbDjeSAG5JnWeYq9gTk6UQ0rBI4zElUnmU6YOBFO5pgECFfoZsRqYqkQ9uzxzzi8sA4GKHg6dCHgnakaMXR/vtruU0q7dH64Bl0AOiLCNbf/scHnh4A5+SGWxqGvvXtzdtn233x/Oz8+rqq66vvFVqXtVsKSy2++vXlyD4WZ5VjWVgHSpc4BqyYy95Wa1cE1o++56e1el5b0HZ74Oy2Zzub7ftm2KsUi2DarBh9r7Cpyppn5wRIzE7FQUySrnkg8P7l9i7S9Xm4br73707f/7D34vU9pcni3zdmBtu3Zo+00TmmXjKkSGrHJ7d+ecM9CYhpyVEJxHA82SkNB5F+PAntfn6/3u7snTFwh/WFfNT/7kO7725B16rkPj64CmzBhjxDH5YVmk69vDoQ118847P/pb8PfLppOjAsFy1bDjvuujJkRCYiJgYu+qqgp9P4goIpoamIoIYxE4k0IANjARETPNigZioMlIU2hc6rLjsGxo6IdDlzNC3/cpxcWiDiGoxqppEHno2xe3d83Hnz569BoSZ+AU43ZoY+7vda+dKwyHtGnO7y3bu/Vte7Xt9u3t/u7ibBUWIbpD1Syebz92vPnRd374r//SL7949/rpzcfnzSqwAwcgYt5EesmqFpAMDLLkqRUDIU0oRGFClR4D46TXsV/LbBBGVAJGYmZRTLRJ96TA+MWRcsiegaGIqU2fNrOpaL9ATNPCKnWANhGj1WSErEoGDo8741zYb1aw+THKmt+BiIgKIDBiYwRsOikpGJihjm1oGCyPXwoMyCPuhg4QjcipacyDiJU+JKq63x0MzTn27FMSZ8aOl4uavWNiE7Ns3dAP3SC9ggAAOMeaStEi5hYq785X97p271yQlHf7fY4phIpNmVPXDzd324erhQLlpEiQIQtIH6OKNOIWVQejd6VD6t3A5DdI3gAdQwZt+51AGiRhzFEHsyjqYgaFbCmBqXFP3Ge4eZHjW2+++bW/8ZVuv/uv/sv/UVHXC6cHsFx036bhHH01OJpClOJ4zb7SbLRxHqFRN2u06K943T84/gU9Ps/BfQUZKX5iUS0SEVQu7diBrN0fmMAwZ0iP7997/WfPf/4Xf0Jgdxs/AtdWtQ1opGpkUaKRj5ANEcg57xaLCi2HQIQgmkK9cB5CYJEYh7ZZVCH4lCK5XCGmlM7Pzon5sD+0+13bRzVYLtfLpq6qmpC6buj7Q98f+qE1jftDAshIeHZ+dn6xENUs2SAbIKimrEBYYhExyxEUQABEARScwyFp30ZHxkSELmaJKecsEJDZATgDRk++qusKqiqASVP79Wbx7HlXNwEZkyRhtVwYPVRc1y4OQ6wCOck5RUmr1KehWsAbb8D2CQz9gMg5l+TfSI1VFSYCMkCdIrayuumVMYLTNOoUR/3pl7mdOo1jGAejzzd9IxQlDZvfOOvKCBCwjQlRQhZCACkVGiPNhNGS2By8oZIVBgkCwkg1LlyDwm6YOVYFdBrRqyNpYvLWcQpZy3ZYHP/jXduEXo3B7BQXzGq/c6q8VEEWEzsGT+gU5TSQKr9+fgwMo/729Mr0iI4O9PSkS3ZWzYxQSmkBKk1VLYSGmPjw5tvw+J2mPofrdssBrp5d79vdcgGaaNiqY1QFVARLAGql8EFxiOLAwMiHyihbNAxwflFfPmoWZy5bhwyMzFQRJuba+9o7I1KwFONWVKu6CmK9phy1WWw2m3PG6rDNkrMkU4UhZgAAVNGucJ7rGlbLetHUltP25rC9TaulNYG7PjGHxq/rRRNT1w+tgaAYMazXNfEAaN5DE0IaugwAxozsqWr3uevbYZu7O4MOCsvJYSUxW0pMDkyBKKDH2iNj3w8xRmZmIPbO1d4Atp9uf7f/+t/+tb99tri40puhHxCBjSEbZIAMNjZ8GvGYIgUsoyISSdJ23yKTZz8cYjRxNXjn2atlsKwApYcYjG3WYJrq0/woqTpmhyWmG8NBBIBsSc20sCgRGbiEgoXTNLVtn5fe/BPxs4RAmGz0ydoHm4SnX56mc/COJ6vp6Mvh0WuAozWYz04TrlsQ9HHZAYCWXvJq89Ip98AFVQVIkgsWPz2C0v8MJ/dyqrX9vGOEEU4znniywI6LcQy7R9gJX4GVwaz0ajw9DWJxj09eHb3hadkWCKlkmi0b8CjpXgoMR4gGkaaGE+NjNjUAHdsYfg44NHrg9qqFPsWw7AR/KMSjVz7+WXzqlVc+78zHd9rEaLE/N4blCkMErfRyGmsCigy2ZDNLZfsaK7vxpSubVN1PLp2AmCaelk13W5SKGKZIvrCfyhTEwgtSA1UAZMdmlnMyQHA2ag2+fIeS83HulO65SOMGxOjYI8FMU5KpzHfsEpjF0JS0/LMMzygIB+icwyL2VuQWrEBro3jkiLcoqBuZX6WUbHTuDWAkXBcA+KXt408YonkU7ZgpevUoeFmZ0OWdqlaq58bts3xTgWxLZSMimDnnRMR0AhzxOIFs5FuVqjpCchnGsYGcpxOP/z8N2Ui4dOgcIiIjK4oVOF+nclEsOltHEpyNHXDGKXuc4AhoBjkrabHngEglYzCaKCyJKwMyUJjKdImAVLXEt4YGDEUKK4qMT3+cf2JjGWvhkSAgjnVHBApa8MoZMVQojTLpePvFqTtCXQZkADiWRBUTA1oK/meDXyoPCXTuRFmsbNlNJBuAjCrTDO22FxUISIgxxkPXt91AzES0WDb1oslmGYyd80vqRMlAMZuaoR5yoh7u+nZpa2QQtF17ePbihfOeEJtQV847wN5syPF2e9MOAzAuF+vLy3v76207tDlG2Nxbh2ZVL0IIMSVfVQ/PNmf37pN3mi122WF4eP6IL7BUVhnYJ9dPCVFT1iFZVqzAsfPo0Wi3PRCTr8JmvW4quBv2xLiF7YfXH77/9H23afbDjhwwWkpDm2Czsqqpq5UbYpdVtrur5ercOU5ZMkDd4GIR2FHWjBmqRYgxE4XgFzHaRx9vv/fJp8vmn67OFm994Q1wnqvKcZm3xT0EQ8iShyFXAVT10B0Ww3KzWsEDYCIpdeZEzMzEREyiYOhKaYcjRu9ddXV9k5N474L3oGamosmyiWZmIE9aOKViJdOKZqKQIy6akAYNFfvgGUjzHskkx0Pbeu+YKYv0QwQEY3fo47sffprBbzYXyj5jgoZSll13aNvOoa+huVzcH+4N3d3+6dUnL66fZ+wuL89jlw+xVbbH995+tHnrb/61v/rOG2//R//Jf5y7fuii96jOReuBBASziSfvCHNSQeNiws2sKH7ACGCB4agFYMc80igwgFNTlCnrNSm+l17mEw2bofCRzGHpwSJFXQUQgEq1gJkDADA1RLZCeMQxarLJvM3+Do3VvacWpCxfETlN/eCYFjgCKsiANAsAj1ESQClfBPATWk0ABbpiAAYFIwcgJlnKGcmhqqUuda7bnG2Wq9W+3QNgcC6EwN6lYUgxa4R8yNIrJCj7GgFZziCgCPEuVx4291fPr56HZZWi7NqBDEJNCIYEu0MUig9/aOW4Vo1MRkBmQEiegYlLMrGqgprGYX9o73ixCfXawAySQRZMvibleBh6cxICJ0i7Q0eUHRi6cHd4YY1413cHq87xnR+/+OrX/tI3v/VT/88/fvfJB0MdXDIyY1M0c7PePoEJyLQvaZGBNUCbSlRoXHjj1Jn9qKJA9ifuhD84/gU6XnGBR5d2/uuEjDChiKqAERJ49mwgCry8qLthpwQ//eW3/81/+zeahWz7m5TbOOx2/VWyPXugYF4Du2UvKSlwVVUAy6Ya+kNg8g7jEL1bLhrHbABY16GpKnIISXNOQ9d1nTZNBUh15RnBNKvknHyKwVSyyGF/6IfBLDmHIbBqbBb+8vL+g0fndU03t1eIBqiifcxiClUVPAaBIQ8ppaQz9Etg6EWobQfPtmwqVehj7NqcM4AzVehT7FLskw1DrJoQHAeHq9WiXrh6gUhCzqFZTnlIMRUqkhkqSNaUciSjnDDpoT1429UL9+abb733rQ+vDxHRmQkxElGpkFEVmkLFOUcIoIj82TGafx6joP+PBPyrh8356XEqTBD5fMj4vvGbdRS+MEBF41FhGkrCAdEA0bAw9lFPJJANxlq6KabGqQqPJrXamYwyCsHDSV8/nFAlnA3ZuDWiER4z2WY2xabTdmOjBKPoKRplE1ECUe1Y8jGeYcbR0D4f+j++iPMuCVOEevxAOV8JYHDsk16cXbTSr3ESVDp/DX72r/zk8lH64Nm3E11nr0+ef3p913petQfdX0vTmAlIFACQJEkEMiF4AN93kZ1n56L1hrI+48evn20eBfZ9NwxAmkUlYxwQwUSSYwgVECkAZJGSDRNRNVuuz9eb89hrFo1RJYGKiVmocA6/fQ2rdX22XnT7HiGz8WYZmmqTIpA5BqfZxVaGmLIK+xKu4GIRQkUqpdFbNhA0ZmRmr5hzlw63OW0BBgBzhF4z5IysbukdIIpkzUpEzjvNRkJoxCWXLkVfmEAAttBv+8Y3F+vzZ91TVKaMGhUTs4CogC+AZskL4sQ4MDIEg/127xeOicewQ805h0AC0g8DITExApplAzUkZufZqZmdtGctdTNoZhOTghCzTzCGOQgF5CY0pokDMk43mJHo4n7Z5wBYdoKp2hS3lh3/swDHDP0cyQEw4VljdnIyAKe40HHdTnI1OgpsIZaSRZgDdYcOp8QZApVqTeUTvAJQJ0ErMJgrrj67rF5aXKfvmUFhBBwZaAA4CttAgZKLMw1zBGvzuebrKAVNBvhSqfX8lIqfSSPpx9RMAAVLYRRYqXA41lTiiD8gIqjOBYljD8oyHAbTANlonI6DdzpKM91sQkUgtaLXAAAgAElEQVTmy5j/dKzu+mc/Xkl4/DnRKwBwxfk0nHIapddHMe1F1hdmZM4QkJkAgJEJKec8cmHm6ysp91mM0ExEHDtyxDRCRScQoMHU4HbaBKDANDlny5otYQF0R0iyREWn9XEThjfNdEeOPZuaahrjrtJai7DAVUlEQCAX34jLIp/rEEeULc2N5WAiPIKhVRxSzioqSYwUcQSspplawrJxitPpuHy/7XzC5myS+AIbu7LMM2a+sHJtpeKvPEPm0v6rQLGjHtsIIRXV/OmO8hTtFRJDkdZT1Rijc658OSITmOScs0pW1VQ69xXuVKnqsokjoaBZc6EQWem5PiLEQIzsCMhPCQYrXRrnO1I9WqqyKEqnPKMRZDSdRAtKlswUuOywha3FRTGnMCNQxsCT581/NIeaTWVS8pGSqQCzognIgDCRoUbZw7FsdBouBDg2mpmt3liONOGJMC5pI2YrbtOUFUEAYDoS06yo/JCqSs4iSA4YPTuOWbqhZWEf3DBIymaW0Rk7qtVEZIgRGLhy99+8+PC958agIIpQ1Swe1Lvb4eDubmLX7/a7YYjtoY3D4AA9ceqHMiXavjt0HTkX6tpQX9y+0CjSRzJd1pVjarjxnmKM3WGfQb2vEXHo+sOhAyPPznOoQ93UdRUCC5JDUJCsZqBiyMiIMfZt24W6uqwr53mQvm3vVk1474N3v/3BP73ublK63fVbcuAZGel+TRf3L0MTSrKZHKtBaYsnJkRQN65Z1D44FTFA9nW9rAkqUH9+CR8/3Q4HePeDDy4enD14fH/fdSp5SNlVBGxmRI6Dd8SYVZwHEWnb/b5dDjm+9fYbL55cx6Elz4A4DMl7cM4rQJIECg6ZDCXmHoZ+iBCBgKgiHwIzIuCQB2IIPjjHMeaYkmUAQ+c9gSVJlpHM5yE7MvKuCWS1xNRptv1hj2SIQEz7tnXOi0IyuH2xN3ryONNqvQZmCYSsV9ub5YvrxxevYbSzsM7r+8OjvUG+6j69bW815PV6dWh3i+WiHS76/uLi7Ow3vvprv/M3/863/vC7f3j1HS5VckMLtcdMYLOIJQVARDYzTaOLgMhYosUJS7cpn4tlLSGMqASO7gOOjUhHh5v9WO5bmsqTI2PUYitUwQio2HyaclVj1t2QVNNMdyzbpk0RERPaVFY87n8nVqW0Byl7ytHsIo6sSARkLKq9o19CUzqG0AgoIBShhoJnsQHPscl8gSMQVvijVVXVdV2A+yFGUKx95evqkHRIaTj0sU0gI54NiFL4SwSWrN11vgpnl2skqJoaIQPtRS3lrJqDhwzAAzBX7ESs9o4YzESZQmBk9jlnAPCezUgEchqytg4qAR3k0MF+sM43mCAP0i3qZrle9N3ubnsHNixrD7ne7Xe7anvv8iG7epc/OQuPf+wvPfzX/t6/sln/n7/53/4ONUzJiZZyUJ7UJhTJTGVyRufD5iBx3GmKBUQzGTl1o2H9szs/Pzj+4hyfk8I98ZJmN7f4C8WfAmAALsrb1aIOFW17+Gtf/fLXfv3n//ov/+yT2993oRfrtt3VvrtyNSpwn/vQNIvlpku5i2pEIbjK8/6uZRRGUO3MlpuzFSFUVRPYm2iSwXsHCLvDruv64gKdn58Zwqbt+773PoS6QYSYIDqMUaq6Xq3rZln1w3azWf3QG49CzcNwuLp67jwbqHPQp0zE7Dw6zymrDsMAhkAOXGB2DlwtBikpKkDNqtR1XdeBCChGELfrczvYkCFJWnllJ8vl4uxigYj3LtdZI2aJKXV91/ZREJiJQB1CriyL5WwO0Dk+tAdL1+DPLh6ch8XHgNEAC3xQfP2SIZwoQwAAkzwgIr86RvByHHKSRLCTn/CZ36d/jzDS/Pu05Zy2dLcTVZppAyjOPxiCoo6eYYGDjlQUMQPVMcqAMdEyVn3gqPMMYwUATNSRKe06PoCMJ3vUGIiUiP5lfGhuxQtlJzQwQjCBuV9huSgBO8b95eNjhzZEAisCiiX7gsevx++DYRVfmsZbmNLnNkVLR35WuTI0ICM0BCMFKIr0UKI/Rsj2k195+LO/8va9N+uPXvxxr3fr+xd9jtt9uz9Qv0eIENUsF1UksAiSwYELYYEc2ruegh+kS9bCCl774dVrP7KRZrjdX7V9rJdLEAAgUYxRYxy8VyJmHw0gphhz7mMeYgag1WbTLFbdYdcNsR9yTkhKxG61JoNExkxU1361WjRNuLl+BgDL+twvmxzp+uZK1SHmYZ+MRW0gr9XCuQoADRnqOiBCkpRTcsyBKjQ/tNpuh911lh1AAogEGCCzRU2iVR0CkUjWBHGIBU6tmgoVHTMqpphSTrGP4MAHn2L64I/eb1aNA8fgEMkSaLQA7NAlS6KF90ZURNjFkICUTBQYNEkegAL4yjnvGMiyIaJzvqoJBnXOERImBANH4LxjJhzlZUbZo6lhGiCWcImYOFRhTPdptkkAnYiKX4RmpbmrgY1NCaaym2J4JxM9L/YTgWMAmKRvPgeVoKNfZhNdYG4TP85zHAsccGoNUbplqijaWIelqjitFjBDxCLfg4CKCgCEPBoFIAAgxxPgADBKr464wfgqftYsHa/zJfQKT34WZg0hEUoxOYXISSN0dfIt01cd8wHT3ZY4dfZYJwBas83I0REtUSNmMioOLGLphDIC1SdGcQTZ53TySxcyf9sJJDGDj6eYwxy2f/5ofuZ4NYFx8uJn32n2Ukrgz4NhOZEsqnmUQCp+pwGPbVYNUfPcVxAAjYjYsSfPRCKCgKdy98jITDbiFCoiZd04dgV5wVHF6RU31sAMBMChc46IhmFQVUBLORXgCRERqUgNjin8k4dT8DUzQELHTkBUClSrkAEmcISZs6GqmhgYCAkrFwSnPEoiEpGcpbB9AAGJGJCIDKzyFQBEjZpMR1FxxAKwHQtiX0WrCjILUwHm9NLpHg9laZbpXACscknlKOhP+VkqOhHxRM/eVItgwMh1slG4ipl55BYRWc4jng6FYUGqKknNjKgMUDm/Wi4dEIwbZmYsbCqjnKEAWMQICLkUn6qW9oJEOHb1owJgOcCJtzU923I7x86mAISkKpbMDIDBghFRzmmC8wvkVnzI0Yco9NkCYIGBsalZUUIorTRGyNmMNOcMUvpq2ISXG4CMdAwmYiYARC0KeqM2FuGx7hdOh3TKHRTgi2kkFRKBTsH1aBGnAJuIDQCpkL2K/kDB1RSRyJDJs+NDt7c+l/3AE5Nxv49Y4Wq1Yu9d8FVVZc73H93/8P3nYQmcQruLPYi/gLBaDpCf316/+PRZ6vp13aTlxhNdnl8sVpuh6xGQAg19Nwxxtd6Ax+vt7ScffvzzX/n5xMzOdzLk7fNuaC/P7jVhGXxQxKvbqyyWYjJFZl+7Wsm013wYyDtNmdA5ZHMORCRrxExoKUsf26qpDOXuZvv08KLF/vH9R3/w3W/+3rd//0V728rATakQzMZwcV5d3D93wd2+uBbLdVOV6r2CPDoHvqKqDkSUTIiBPdaLBtTnwXwVmEEItmm4vtsa4X7oPJlaAmM2AhTvKNTeVY47EoWYhn7o+qGNcXj9tdfvru4AwXknWcqDWqyWChDjILmIcEFKCbveqSsSS94HIIWMZtYPnQ9Q1eScF1WNRaCt1KcjCKgAmss55whQk/PO+9APrQiIRlW5uH9ZL5bd7Q7NsgIgHQa169tQb7heBKZWh8r06vZ64TZvP3r7sD00VRPIX55dJhy4zQfdJUoDdIfD4d7lo6fPPlzAimoalod/69/41//r/+a/+/offocQMiSIxo0nwtRJygM7BwDBe0BKORsUTg8W4IgIJ67kSRQzWSRRIwJCVBMVQ0JkAAMlAwBkwpKUILMx6kQrNFDVUbEdJsXJYhxKoggISm/WOQ8ASDB1g5mSdWUTRqSxdWxBje24Lc8hx/zLuJ9jCbD0pOgNgAyI2KGVanQ0JAQmG9sqK9lUeEgAGVQMCOo6rDfr5XLZD8NqtU43NyqK5Dw7QkdqkJUBXeUd+JSzAYmJIbpQg5MsSYasosTQLBtH2dUkSZKmvgM0qAIwg/e1aGcZ2LGpDDFV3pEPprDdbgkIAcEBOWQzhWSWs8lh2Le2jdJVVS0pI8PyfLHebLJ13VVn0vuwZtT2sL/e3q42iweXS837Xq/Pzx598Ytvffrk9jd/83cO3YCJiFDUAKx4tUVcwU53sKORPAJYp385CSf/7G7KD46/QMcMh7/s57/sxY4OsapaBvPECIQKppKBog/44sUOIvz6b/zVr/7ql2N9i9a5JveHbdRtteIo/YsXd0J0sdrUq2XfaxeHkh51BP3QqiYzTdFi3J2drbo2L5fNarm+u932+0O1XCPXu8P1dret69pX/v5isdqs2q7bH1oAcM4DQM7p7Gxxd7utm3pzvqhqf30L681ysar7/nC3v7vZpfNzIoJkJgIyMoMgpnzYx5QhK3iA0HhfLV2owWVUD2g+1DmpGGSFQw+DJRe6LsqQUMi7wPs2GcDZplqtm65tL+9vnl9fgWLK0g+xG9QIiQxVPYMs0JQNCQkqF/pDJ2mLuAgNUYnqSRAZ1EwEwJCdcwyzqLqeBEmfGaPp53F7sFFg9LPr/dVX0ApZ+Qh/nYSJdrQoNkWT03nHOQRTjtSKQyzIPDZTO0mTI7vj9yOWEqxX+SR49Emna0MgQBk3xMmDn6fqyefnGo2TP+NYg8Elyi+PcnQMT9GrgtUhgCKQ2lhWVAr6Xw4lXo60j58GKD3FJgmR8RpsZCSQASAaKUzPYyz3hxHzy4AIpEYACc5ft8dfWDQbsV3//OmT6t7SVVXOtL3rndVVWKUeTRHZmwhksAzkq9ovGUO7azMMKXaGsboHD99oLh76Z+3u9nDoI5zdZ8FQNzJkh8gimRl9RaHyTGmIKcbY97mPyRE1TVPVdcq3fRyGqHEAZq6cXywDAJFaqMJqvVzUNSIF/9p+2y3rMzC/vbl9+tGWCcm5ZrGoFo4DAWOOGoLLmtUi+8ZX3pKm2FehbrgBDf2263ZJOkB1YM7EwFiFoShC9kmkA4TgfbOqVTSllFNGK3q6pkkI2LM3tjREiHD97PqtzVsePQKxcZKsAuzZUzC1pAMSzv3zRDISMNCQE9QAACJZB6jq4OtKkw79oJIrrptV3WoffKApt4cEzjnAwm8fvZgCYKkqADEiMJegpq6rnHJUzVnKpCJgnpbw7D6N2LAVSRb8zIZ/nIg6cXzmNTTrxry8vF7654xBza9P6M2U0hxhBUJCidlgBLCgfLdB6Uhf2pcREc248yR3NdH0QhHULTdrdvQJjysIZ/WLl+7vs8Lzx5UIJf1qIw0Njhcz4QEnq/wEw5ohgMn5Pd4+jTA0KmQiKh642cgwmz4++bA4sfZGzGj8QTj9pzDsmAuaeYJjWakPmt3jGUI6hatK2D5zZU4Btc9/Jv8sx58TtDo92FABjKa+aePGIYBgkkWyOceL5SLUgZhUVAoulaUfhrquCcepU+4tq8ZhSCklyQBARAWQKrrsOecseVLFnw4zRCBi8hyCL5iL5FyghPLNKqIiMBGRlps1AIgqiMGRtlO2WkMi51yoAiL64Jvlgj0XJMXMmkUzikmhzUhHSinnnFOOOeacrewjzDW7oq2eYspdjhILfwsAyhwFBJUpvQzARIx0JPDA8RdjIh7BsrJRFkx8fPOkKofTRmp2LH6cdb5mMMjMRDRnMZMQqqqq2HEpFSzBmZllkZRz6gdiqqtqsVzWi0UVPDGX4kEAcMEVBoGomCkSMjMxlmKoalkRkYLGIeYoSOA8c+BROGy88jFULz0ZFUBUYxqy5hyj5DwJqI3XX4gDk3ygSJIiIFV43WagogjE5JicI0dYiBBa0C5HnokQ0BRTzKmPfdsNbYz7OOyHftcPKQ7D0HfD0A9q2jSLRVN7F6rKl4Iwz+yDK+LRr2CpMeVpIpdrLqWQJWNhJb0hYkUBzSY6ISEio6ApToasLNIy7qo2JhBAVXRWHSICJFNLMR7uDiN8JqYKmjRnodrVdQ1gbXfY7e5eXD0PPjx+/OjHf+otdA6cvfn26z/xM++89eM/ZgyfPPnkex/8cRwyqLWH/WZ1vjlbe3YfffChmR269snV823fKkLUeLu9ffr82fOrq3rZnJ1tcs677XbfHi7vXXz69OnVzU07dEni02fPn754sdvt7ra729vbdn8AtcAejfq+B6eq0u4Pd7e3OeXValk3YYjDbr+9//B+N3T/6B99/ermanN/ff+1iz9871v/++/8gz9491utDYcs9br2lX/w8PJHfuTNs4vzp8+evv/hB13fpiQ55bPLB+wcgBiYaN5u5cX1btduDQQI3vvjT+7fu2ByV1d3d7udRy86AMDd/vq3f/frf+trX/3o44/eff/du9ur1x492PeHLBpz7rthd2iXi+bs/OJwGK6ur9//8L2//Eu/tN+1nz5/Jq2Qh6oO/dCbgXPOsdOsMWXJqmI59pbs7HKzWi1i3y+a6vxiww43m1Xb9n1OWQZkfHD/niNvSs65stjN4OZu+/prr8Wcuu6Qc66rerlsXGCB2A+227ev/9CDy/uXOWvOecgiCrs9XN3dEeCjh5f79umyrrtDvH12097tH18+vru5Xa8Wq7PV/dcuf/sf/m/P7p41q5VCUhXprXZLzDS03ZOPPvrKF7/0M1/+4huPH7370R+JQq9SNw0mVNCz8zNCFE1ZdRTRIxrLv5Ac89B3aMbFOSBy3gUfHLOBOeblclHIR4iArkjWHQnV6AzJkIEdlkbmqlgKbUEATEAUBKh0OSidEFVVALKYjiA0zPs+ACIxk5pqFBNl75z3xYbM+ysiHk2ZjhkesVziCPKMaEmEiMgRjmiY2dTHCcisMLwQjAyJHLMLTs1ElMCYUdWAgTz6EIDg0B5ub6+HQ/f0yXMVPdy2t09us6SzzTkKHe62nvzQpWyWRU3VeUeeFUVyggCX9y8ePrp3/60HQNZUoar8/rbtD7aoYbGC1x6fvfHmQ9NkoItFZWl48v7+rdfffHB+/+qTbXd7+Fu/+nfPwhdSNE05BHAec6ZBM1f+42ff+we/81tPtu9nF6mBCMNdu93utznHLGkYhr7rQ1i+uLvb7rc325s+dot1w567ONy/9/pf/blf+/rvfv3B5ePb620f02K9QEbTwTch59Qsmph6mHr7jP8lgLkWpti9krc5iT1Ht5PoNO79wfH/3wM/73g1fXfyzikPN2qPvvLBOcFJU48XADA0VwV2zsBk6OtNHSqAMAxd/y/9yg//q//OL//q137uweP6/U+/OeRPbw5Pdv1dtK7Lh/2wS5Y//Pjpx0+eP3z06DvffR/QDzFJ7OOwXyydwuBDvry3Ojs/W63PFssVIPVDQkZy3A3x+fXV1e0NM7ng2vaw3e9u726vrl5c314fDrv9Yfv8xacffvR+qIORAolaVpCqqaIMTz795Hvv//GzF9t6iYiY1NqU0cNiuVCkrhu6ro+iFxfVw8fnm7O1CLZtl01NsuWoKrd325SiGQ3RskJS6LMIAnoHzhHDss6blV8sHJC5CofYOkei+uKqfXalbQ9gZMZV8KtlNRyGLNGxqypOw9DtO1XvcP3008M3vvFJNwAi2TCl6sgK9b4Q1HHMH4+9nl1wR/tc1BlENJeCxbK6iadWP3gapuEEch2hHkAoMstgBiNZFedqDAKDic2AzpjRUeE8TLtGsd8GiCZMXPkKmLQYfCb2DpmBZoUpm05Z5tbpBJ7lZcdUyMijV8Gi6IhYZFJD8CEEdiP7XqAELzjHQceFULqDjEEVj86yARiUqiYqnC0DAgQFMINsJmBikjNXPCXIC5I7Z8fnswAgsXfkxoZLJioiIjoWB2ABEc0AGIGUUrI6hED1EFPOSoRp6NaPN0ASVg4D6lv63/8P/2lsnn304t13P/5mot44PHt+ePJR++KFOagrWtd+mbqICszBjE0oRwRg9p4CuUaTHi7ewLPX4Bd/5W1xh0O+4qDZLOVcVQug4H1ThVpVt/u7/S42VXrt9XtVXV/fbO92HTEtVss4pLu77ZBSjHJoWyL2wYtJ1x9CBZf3z+vGmUZEqevm7R95J3Xw3h99/K1vfnT98Q4MKr+o/LLv0tAPMfbbXXdzO8TYnV9uqios18uiWVNVjc/+J9/5ac7NN77xne0nRkIWHSUPWkM0GAQEEBAkoeax8CSnEqQQMhipqAkSIKMDUGQ0MG5IB/uxL/74EpbvvffecrGwpOkQA3vvQowDBDAAFTVRJAjBI7M644pE5Od+6eeqxruKm2UTqoqAJUm/7w437f72MNwN7a497A5D7MsmKypIUC2qqqlAJMZBREoTdhNVUREDMTXpYi+WAIEdETMRA1hOOacsUVTARDUrKKEiGpmVFVDoPLN0wPc9ZloNnlByYJTlenm9jVOYoPRbL7AXzg24QA1NTUVI0URNDfJoOnDMsAIAMDAYiIiKSVaJMv43i2QpGll4wp9Q1ZTzqMFdzBPhmAucDdVUsEU0hfPzdRMCAQeq68o5J1A6VCN6BEI1U81q2WTKuJbv1MKrIAIEQxAQGTtTvEJMK36yiuYkOYmaEmKpVZjbEJ0amRlUYmZ2LH02tbEIaHK9xpSvGgAQs/POO890REVGeSV5dXxxoiKZmffeOTeHvafHZz/1/Y7549Mg0lz9ht/fIfx+JwIAN2Gu48ahNlHaCg0LlKxoBlm5TwZEJgZCwJxz2WNOTjBp98L4cItTUi4DxrzEuFGegILT/1RV9Mi0s1FEERBGaKXoQBVkZ0RNx9smZp1ITCPio2qGGfLEpTQzK9yugg2VaVrIuVgSHwXSomkq4URwAgACRlI7JoJOhhh0xER13iRPNkow0EWzElNRkVza5SlSUZLnOQVFzKjHcZpH9POmCBCNGRUpSPuk1PcSt83AVwELb8sMzBRETWfx5rm4r/yuOQOAqpQueykmdjzJosOECttEhZiEfUdkGHHiLiqcOBjT7CpnKWGncw4AlFmLDqHqlOUzUxv7XxacCGxMURUg3WRqqAFoqKaoo4J0ud+Kg4GoWlaVKJEGEVdQWUNFZERDQmanND2TMb4ymqoPx4c8DwMe8WkkUxtVmQsKWRiBxlpaGU7fMVK5Z3FNGMVNEcxwTNmpGQMCGsKYsxwXjqJoEiERIiZGRscupqHr2uVm/eDhvfPzdQghVNWTp5+23aFru76DBG0kYIQoKUrOKp0kO+z6vo9s3ARPlsGymav9+YOLLnVX26uG/GpVLVzT65Awe3RUcZcHtwiNIwRGQ00a0ANh0qhDHnIkRmR0td+4M8/say9kCcWvQoL84uZ5tMTkDSTm4er2SgjCegkYGmZfMZEZ2O3dTZbc58EHj6aiFqNwNwDoELuUEwBUFQBCKIgQ+xCgbdvKQ1MHwuA0qeHti61lPm/yp58+dd4vF2ei2+cvntfLZUxDloSMziE7att9P0hdL+qq6fs+1P78/Oz27k5MF873eUgpIoKoZMkEBFw0bZkCt4e+PbTJ8mpVL5YVYL67uzMQLP6nypAGYKgaD4aSNWVNKUGG/aEbhmgggMgu+YCG6Lwfpd5F2JAY2XMwWy6E0bJCe9h+/PGHb//wsu27oY1nuCFPBqKQs+bgfDR76wtffH54UYxwHTwB9f1hD7ehCcuwvj58KtY/fP38J378ncM3vnX7kalLiEyIKcYU+1JmDGpEpaDPxEjVpPhqMPY6NQNSNS4Kn6BgKScEzFqqHtHMkMAIkNDIiElRsZT7ECqMqqWjSdIxLFFRKsnj4sRjAYJPrNznpOwBpkYWL2cEDeat3Y55PZzEbQmQkNwYRo1vkfECi2L9pO1rVujgCoBa1BVFpfTAHe+AiZhIdWzfy0yqSozKFmO+vbpOfQYEU+DAzvmYxQdPjgQFqZRtwBAP28N1k2vBhOaIYbnhdcOrlQ8VOSZTs4yD9Gi4IHAEpmzKIfiFbxw3BuhcAMgpt2aRXEOeAZQDmdMU87bb7gnQg4DFPNTeO+ea1dIhDUoUGjLNBLvhsO22juqKqqj7LV/9e//hv/u//E+//e4ff7C73cZo3ntuQr2ovKd2vz1mDuec4vjLS8NlsxWdylqOges/px40Pzj+whwGUFXVnLTD0o1a1SEvV4thiAcSrgRZUoqwhb/81Z/5+b/yU7I8fO/5p8szuNvtDIf/l703a7YkSc7DPnePyMyz3Huruqp6umfrGcyCZUDMEMRAIEiAlEyEQBPNZJBkkl5lpgfJTP+MoiQ+SCYzmaAHmUwSKVF6IABim6Wnt6rurrucJTMjwt31EJHnnKrpGYIAzaSHyTarqr43z8nMyAgP988//3wuoyLHLnjBmOZsOXbrXLSYzmlyZSMLQsHRdXG9XhVjCeEw7kNSs+jGLMHhlWteTHPSpHma51yKV654baaORq8xmJM7kZElyz55tuk4p4RgXIwDdV0QRpm5Y+4GJmHnfoPH/SolLyVP83w8pinl4maFrNPend1NTZgoYBAUx1RQzB0ZASK06vsgFflPqhVKdieXSH0HZLiJ5TiaRkIX+q4bYuwJyGXsVt10OKjer67k29/96u//998PgpxqnKQ1XPXKG1q8uPM6PfnqF9UGzq2Cwd2JqphtIwVc8qjwWg0Nzt26XmMb+cU51d1UtcU3ax5nxYho0YHx5gE3/KkyrU732QLjFu20EnV69XLVStFCMV3k5Bdyw1Ia2RB5XKThm++5UCwWroTX8qrFX60li1yJx5ej5xc3gYasubc+YfVai9D76+wvXyJVctQyEZxPOA+1OZFbYORSDCIhgJQFYJLeN4/i7fH45a88+pu/84u3+tEx32dMcd0xB2VODmWmoKmUebeP6ETYLLo6GylxiCIdc+chlON4wIAnX+y//q0n3abcPdxz9M1Vn2yeRp3z5LRm5mJO7KGy5RwpTe7BGSTIpYzjER4C6ZyUWFlwOOaieRjCdrtar7gMtXoAACAASURBVDsObqbZk6Vi6j/44XufvHiYRg1EJdSlKYzIpg63VMWdMYShk8FRvFBKdhxnU42H+OmLu92nOY9gA1vvhalEdnaQUoY5TAGjZSc70bdzqSJKddrzsjCsSttH9nka55JBGOejmfOKjc2QQi+FcxVyISF3O8wTvHDPrg5GzrOZFU1mTkQlkWXzSl4n9nAO8lok6xR6CSFIkBxLKAVCmtVMK0oQYz/0XdfHT3efEDPMcVLkbbfN5wnjIGN2qtTz11qz/AWPv9DO/ipmQS2veJr1tXLGiANV7XKunl4DcmqfoaWiaFlH3Kj09X5dzWrnLm5J0YpPOLPbQkpsbdheMULuXhOilw/itU82oQX7FbDwxVS0C1QMwVrt++tu7PK/Cy7244PqdHnC8tMmMXq2pu1hGjTf4AtIGx6++N4GKrj7woa5IIy+Nv4/8bjEnv7qx2mXP33hX+6bg18Q+Za5XKdQjRUqiOsQuHtjpzEHDnBM80S13qMiMK+z8l65s1Nyo/5wyX/XaeOtxay5q3q1776Yb6rgSaNfMXMpZdkkXus51YCY+hNtbKRzIVvVcbrIZiyYi7fJ7fULqarTNvU7AjGRcZO1MpxvvK6GSp3yRaetznC7mJnmkBBciy38zvq7ylCrWlQApO5AP6aRdom2vjbJ3NvzqtvptDNeCK+8uTZiDiNdzO8pFKxCcVZFauoGTUQUqGR1eOsKRhARZlJrMPjCO0Td2p2dqpClV0VLsdMgVWvjricG2SI1xyLkrFCQnw2KVn5j/W4UbZu/qTWmRhvnmuYiXoQpYQAY5m4KgwN5TqVYrXkkRu08CSKqYu11uzevrgYv0VZztBbjUvH+CmAtoHVbJkRuZE2xc+nI1vD+dj910tQ9lIi91n/Wae9UnJtztRiiCnMR1DXnBBXu+n4Y+gHu+/1D1gSiYTWshpXDVbObq3kuUMKm71axC0NvQqPlu+OeHeM4eqCY+4QSup7ATh6GeH/YHfeHx5ur+MaTnrt3P3h3PqQnj95c2Xp/HNfrDfckEiJHS0pKHjX55MWneQSJRFmvhtXVOjDNyHOeRx2jhLGM9+M9RUBMPafEP3j/R6MmDEFEhu0aJWvJ0zyN0zjlhMBBJLiAa+c7csecFPAQOxIGWc3sMgdT3N3erlc6xO0Qgw5yQ4LEczqu+tX7Hz5//Phqe31zd3f/4YsP33nnq/M8Fc0xyrDqxln3h2kejTiGeXr56SfrzeqLX3hrnHfzg8k1gUFkBKMaGrixixPBnIyypgqal5RTmnOenXVYi6qmgpx9f9iLBaZAFIzdCSxiRFktm5uZT8nZV+goOERCR0XTNKe+p9VmPaxX8zjvHw5e5jLiuN99jN0vfuPbNs+qqlLmMu6m+ymNIfOmX6158+vf/c3vvf/9dz/60f7hE3RdH5FZk6Zj2qc5fXz7wc3Nk29/5xd241FC/49/8L9YcYKHEAA3eFi0wB0UiJigRIA1najT/LVaxGfM1BB81WZpudrMcysnEFgItcKQKyrsMLgCVjMkjEY4NDNnCm3JoObjTiolF3va5WZPNbnguDCwdYNZAoxaItEa6sBbUQhXiIqqqrKDiZ2sVWHXxMGSBXI2BZExEYNBXkqBnW8jxigslsuUS87KQJkLEQWR6TjpXKLE2A3TOBuc2AzJRQprtgmE0CN06FcUB0zzvqBEBLhtt8M6xMc3VzFSyWMfgpBOUyJF7BQOmJCFoV9vwzqG3uCBo7FO42yerjYUgkzIs6ZjHkn8mMe0nzhyypkMN+vN9Xq1CmIk+8NsFBDjMR/mT184ML9RnlwRxzXj9ru/8S0J/Wq9/of/1X99fEjgHHjI6Rhj1626cRzP7tXJ7WBvFpWapooTnEB2Dh4Xv+zsu/wMw/rZ0Q73mgRWU2Gp8YYEMfJpnovn1VXkrkx2/OI714++O/zb/+5vfPErj8f5k/c//YCv1g/znkWneTIuV6uYgdvdfj8en62fzHOe5tEtRO44iBoRS78aOF4bZg7h3R9+FGQuhd0lhj7EmE134zjlGUSG4OyhC9Up4hirFzHkHPueo4CbbsacSy4p6TSlOZsZMKtDnWHFXdzFzLSkuRCo7/u+jw+HY8pzLtkcJee5ehLGQbgX72M3rIWAWYsf5zIjuwPJjDiszMqUJkfqVJjJQTW+MEPJ8AJmD4wSRUBuEQggOFPXxf1unufd6vqNv/4b3/r9f/x9WcFY4GRmRFKVpSv41ORI/ZSJO1f8Ne/x1cBn8fabZtarWMqlwT5Fd80TqwB4+3OxFKd/mBpoMeBLDoLp1KwHRlBtVUYw8yZLA5hRVdJol6YawdIJHfMztl4rPG0B25aIcQkxqpPplc1wNlvehHy95itPsJTbEik4mohFjRmWHvatzLAOqJ/c9kVyefGSL77z1B27XfwU7CxbU6M5eLvaouhszgCL5Nkc2sUejFmnMCBhR4TuBn/tu1/53X/vbz/sP9jP+91h7wRIGKc8lwIRid5xz2sO3h31GELv4IxJfVbLs2qej+vY9Y/o61/+wje/8+wrP399P71/TFn60Hd9cZrzsXhyBKMqiDmzeBfRdSwiYyoSOXacZ5tSIjlEUSPqV3LzeCCeiLDdrrbbTQykyKop65yVCuH5++8eHuywz2okHNQKjGqqtsDBxVqTFnHjrKDg02j73Vxmo4f8YnU3fYrjAyiDTXwGobbnMxAZFXMjqDZRqPoqDKBi2jyeSgmslSG+1M0EO4y7VAoGJC3MCH0oJR9SERGDKYyFiZldWM0KQB67IGub5uM4H8fxWGqcWyjNWUttMLUApWjavWpOUIPUDdeZJAQhoUhatGQ1NTK4wopJECd3YmgFelul6VklwgFfoKFTQ9EFOapXvRR5Ij+v/1N8egm2AvCLzggXhqKO5vk/AK1w0BzW4OjFf2uIGxps3bSslub0ALiuDkdlsbQLW31v7FUSol4pVD1u0Km26ceQYSx25ZWf1Ddd9ZXUFQo7qcpXJI3dF3B9oXOcivXojK6csfRTJWgdaII7y2VVNQCACULEsGaDFrwE1prmNAttIq3vXfWjGzJzeg53B1SV6XQz53eHHzvODvip89u/irf2Lz35gt70lzzC2cKioQdYhtjNyJkMrg3vaUyV1vKpyZXAFuKZn8oIGlz3SlHlSfP/8qlOm0cVzV/Mcc3kVLsPQqVEmRm1DpgNUbwcqeWHKLlUDNLUsLzEelFTjTE6NSixZvku2WsLANQ2r/Y0BGmS6ERmeK2fUuXNvPqqqqTtScfdQTkl9VaLW3sdVpijcsocDRqBw81eQ6ZPw0inZoXLQdSKMgjSSIp0uigAmFqrhbaWMwwSKDTM0Ujra3J4lf8DQEwizIFTTqfxoaVUU73UZeYn0JvIW3PSEyRoJ9DqvEIuJnQl16BGrAt1omp3U5Xtsrog3dWsNNDRzBeErdlSXp6YUJE/02TLFkLEUAW5mnEVgDchYyMG3JXPhMlTCed50M/uRL3GWTbh7JcQiHxRz29hOS3ziUBm2tDv5ue1Zh7VA6oGzQlVDR0ESAX4WWphZilm1gURktWwctLDcf/y9lMWfuONN+BWzJ7cPH6Q/bw/zMNx6PpnT59drTZvvPlEuu44zS/39+xUtJQ5I/GmTNur625YObyUEozyODP8arMC/Ifv/9ALun7VT6v73Q6BRGIvIa6iBVh2I51ds5Ypjw7mBIjHPhT14/Ho0JxzYA4i1Mu63xIsaaIsP3z/h7vpMMOSFlghK2kap/0x5awEJ1XzYtR1kblniWZgDiAOMUhkR3uhbuaG/W6yxHLdM5gI62Hl17jflSDhxYuPr7br7dVmHIf7+w/nPKeSmbnru9Vm8/LuxZyQCw77fdbxhz9693Nvfu7tL3zu+ccfffxwr5aGVez6ToRLsZKTKpr8kXlJSYKwIFs5jsf9PszpWLPZQJBZmTVnm3NiTp0MEOZALB2YcylqUHVzrdNPQEMXJJDNPk2TMF9fX8UYphBhCq0luRiPgHoMUTbcQY7p8DDeqirP6KfoAV9962sI3XHUh5d3KeMYy4DiayTMu+O9vjf9/OZbz5584Vvf+nop9Cd/9L13f/DxYZ4CRwqhsa/Mci7M5CetIgJALBAiAVTdqhujdV05CAY/FdoTNbPvizlnYbCDAabqicCYlLyWENoCBVlb4mg5TYI3VNrPoc8r1qzCu2ZWBZmoCQdcbAEVI1sk7BZGLIkLO7tZm0VkRGRVAre6TIsD1YB+h5tptsCkbjo174J6hMAhxsBSalJEDUQ+AwFEsGJOtNoMoRO7vRvnhOhwKJXWDCiANxi2uHoSrt/ovv/yOZgCSaQQA6/X3WrVdYFHn5mczKzoXHJUuCFKT+j6OKy6jTubwYly1nGaiFONFw/j/uOXL8Y0xW2HzlLOBj8cD+WY0zi5Pta+g2FM0g0xdp3acRxHuXvBoCh93KwJXefhN37zFwT2g/f/6P/43//Z4Z42N1RGpDyVnJftETg71GgvkFq+1qk5uk4XZy1uql/k336GYf3sAEBEpRQtxc0MrbiAYiDQYf+AgVah2415+8h/8Ttf+Lu/+92337kZ7eWE2/4KH37yQUF2zXPOsSMFppRu7/bThNjFaZ7yNLGFYdszkxqKlRBcusjkHPgwHZlRMmmRvreus6RlN+6nMocQGOy1xgcg8djHEEOQoKrDpi8k1cqVkqeU5jRlywVkzOaeDZaUBEoq6p7yPM95zp3wWmi7WR9HIlMGuliraTypEbszApExd0MvgaIqdxyTTkWzu5uJMDm5WVEVI4mBOYo5S3ZSNRBH4VUMIKJ5PhyPZd7E7ToMw2BqjpJ87Dt/49ljjChrr93TaOlrUzvQnqhX3gwln3O35zeH15ewL8gTfvzsz3r1Z3T7LBV7kYXFcgcn+wGqTQPPjKzqHS6frpGDMQCoiUjNd9SwgrwSt5pJP+1HC3Me5+84fXnb205wWQsN632dwbCTk1t/bziHPBWadD+XKjnV2NwqS8BsyX1iiaovG5KcQqUT1LCE3N7k5tEi5RbUnBpbnYeZaxMTAzVSS9jCA44z/tbf/Llf+ztf/9rX3/6D5//iMI+73WF2U6eUZ6fQ9aSYjHS1XfcU5uNDSuqQkid4cjaN5IKDH77ylc9/9VtfWD3m3Ti+9/yjQmVYr0Vi12vX55J9TpOa5eIpT0xYr2SzXa/X63G+7/rIJCPPOSugJCbMwhSH9bCNbrRabbq41lSO4y7nEVBBKO7PP93bhJIjU18DNTPTXLyYu7oAAYGRk49HTZbVaZ58OlqaECaMu5T2jBFeQB5Q9EQZEHZ4Mag1rXI9h7hUOQq1GrrJwhiZQV0ABnX+MO5MrV9zGqtGullWLR45uJCrmpnWSCWyMcIQt9fr4aa739/vjg+HeaxyI8EoZ0MBCpxbcrEhOwu7uaimNHHhNM9uHmOMMRauIhg6ZS0pk4CvRb0AS+EJ3PxctXfCas1Rq40qmloLaInx6qT6jIaDZ9Dq4h91s3991Z/CbG9/npAdPy8mwGFl6a/Y+psZmho7oU39MzJeM461qqk+iZOru7szM7yRGOr/VhygCsOTtx70l/dPJ2gPTS2HmSENF65xdVv/tDB4CKiCx7asR7IleKzYWs2iNmjr9Px04oQsN3a6LnEtA65q5LVYiarYH06i7uTOIOHmqfoCg/uJG7q8WrS+F5dv7acDSfTZ2uX/yscJBfvX5fUFagh9/XYAIG7CucslqSIrhRTqDexYXlxDGnG50dXX4b4AbBeD+JnPVIGOehtmVrv7XWyKDpgr1BsudqEldopezKtdrjRd1/orB6hKhjcP2lpzSryqT9bslTQAa1HpIjevgFDlHLZ3LJUl1nQ/zjWsbXs9T3y7gIzHaWpQyKm2doH5VLXmnUzttGOeh8crYwLnQV6gRnfwUqwLPkUF53EFMM8THNA2XCGIBKmtGawR0tz9BBK3b2BmYYFAhElaH81WWt+q55b+Jrg06ZVCdInP02m0K4eOLuS96l578naYueJEggZiV64cAVYbYnobT26t/dBg75qbA4lImhPquzl3ADRUBJbdvHjT5jcT46XJYgUBcymEzzDB7d1W4tirU7cZhtMegMr0QO3oY1pToi1BRwS25ljY0n7CTm+nphXFiQCpmUBuHNWirlldi+aSk3iwoinNh+Pxna98NUpALqt+WK/Xbz191vf9ar1x1WOebw8PQhJEkibNucA8yFbY4MdxXHEopah7qYy1AGHOXsY0zja/3N2G0G09h64Wl2l2Eqek81jGvlunYjFPkiTntNvviDznlOeJQG9//m2CpZRySdH7D1988OA65vnouRx808VpSnPKROg60cB50nlW5qDF5rlKQRBxcLBbS2GYUS4WGRkoJad5ilGC9DAOkZlpmqY5Ha+vt++88/b11U3OD8fjAZC+jyyhGEAYVoBjnLVA33v/R9fbqydPnrz55tPjdD/N83q9GoaOOcxTEhYt2paiAwaY1x7i5rnrpB82xFerzTrldH//wJyAVBLAoOgoagAIImH3sHMGSEGuZLGLwyCh64QRNBOxuZmWuRTVfLUZ1l2/WY27h91hxHQcV5v1cLXqjLNOkx762Lvo/f4hW7l+8uyNq6df/9I3ONt+v3t4+XCv+6vNPPQRoXz4ybvP3n7jrZu3vvGVr15vnv0//+QP3//wf8DRyzSDnBse2DLWLmXhzICJYwhSVRtRTFs0UknsWACnuhcoGdHCcA5wRis25JrMdmvbLtPFEm4GAyCAzVEdeNjSgIas7aleS/9bGpq54sfujtYw91K+xMy1WtVTB0NQDTAJSq41PeBOCz4OaE2acQ1ECc5wdTVqFdMgQy2Ibmed9RsWb08rxcydnQBhIeHQh/XVqkiqUijKuTXa6MEDuEfB8TDxNOfad5tC7PqOgTQf81RKngDugkHVXRUWAoZuQ2CmGELnxhAx0znlXErX17yp397d/fBH76acOgYFdkWlFGa1MaVpnsVQSt7NWHm/HtjhhexYDg/T7RfjOy5j5vvH8anT/S/96tv/wX/091Oefv8f/eGdHAKxSHQy8AK9N9t9SVe/+CfjxLS9cE/blnuJYeFnx88OoPLQaXG0mNkBVY2bAZ2OOqPgF3/lnd/8N7/zu3//t/b+4sXLd7ve19vuxd2u67vjNJqjC4Ma7w/z4TD23aPYddM4CkuMcei7oe+ZFJSdqkYSSDj0HXE0JwcrU1HPWoqpupnmlFNKKYaopmolhDB0fYydu+VcVtc32X1OeUzTYR5Tmg0OIZJQ77+AhMg4ECG7FXetniHcUQBj8igAA4HMoUZTqcleOCZi22x6iXzdr1eEWT0X06I+1dKhKh7BZkrOZlRlNrWQhEjUxyBgm44P+/103Iabaxn6+PDwiZNIcCYnSVjDCcJUs4PcGoaf7GxLjIJOuf4Fx/lJOfkTpEUXMNRPXuVn9OriZ68lMIhPfaVOIWYLUmt0cUm7OH9d/X1F0k+Cy9XrspZXX4K8mg+hc5BWc+dLJLv4AUs+vD3+Kd5p91Sv4n5xG972J7iQ6+Vztnynt0/h9EFymLc6lNPh8EWZfYmuXyMDnAKvBd6i85UaqyYEqKsricFR3AuANb7z699455tPX87v3T3czV6OU0lkWTUVjt162FjB/XR42MJktYHkXLlflkBADxk8RFCHd77x5Xe+/sWX9+9//0fvf/TJ4epxlLVzcAi6XgywKRW1XNS99ANtrlbr9SbGaG5DN/QdS+B5SgISsVKKmsfYbWLn7l0nApnnfJgmuMYIJdfmngSAK488EJzIStUfpyq0HTiUgnnUuajDcqaSQ0llEzrhnlv1TC/cMWUyAteG6wWsXJ30Oi9oiWQNYKmlmwCDqTmJBAgQ0W3icT5yoGE7zPmIDIVTdCJ4cBcAcLOSk1Y8tsOw7vpV7Fbx+e2HuVip7pY4cRSxIqU213ptKTGRArmUcZqYqBQlkFmZcslzLnOxZACsRsROtTiliVSetmc/TRSHEzvc6Ny+jZz5XKh2OeNe28FfswYnWOBMrHj1aKZ+wXdOq6t9PQCC2cIhOpuJJWp1X2Dl9oGqb2pkJ0pTvYFL/ehGiKKK9mpNtMLB3nK6l/dWQ10GEbOxEzW48uSCUq25pmYvKqS0oOFNnmhBrZd0H12M/cVY/bhFJSJhoYAqR1atWAOAKlx+SuASEWDujEY1emUYT8/uy7XwigP2k9wwr8DfhRL3Z572kz77U35FC3D007Gzn36E0MO1KpGDGcwVOIBWUUYAbjBSW/oUwmqXV6+lKN42klfKI5d304amZsUvcJ7zY1z+RaedAae8+vlkc/NS9bFi7H5szSyTldrGU+eeL/N6CWb8pFt2vj13XoQhm968F2idAaUpxDvg3ndda0zq2mI5wmmyL+gXuS897y6Oky54xVnNzM30Qs8Mwl4n36sfpAsb8drLpgURI15oiBe7vi/j1oaxinIuc7EGh6dmBMRkbkxSiVA1SOv6GEIA40RYI6IFFbpohAlUVuUJvaoNLxxNE8zhDDZDHWU039SFRc30gnZXV1boOlMzVctqWqozBaUFQSQy8sU1MTduiUNxIZRcrYMwM8TcTW3RNgNQW0qSa6l97RmN1UcLmuunmyFSdzXlxWSi6qpdTMtWj8h1WIgBtoWH5iDj2hmkuYGNLgo0uWw4IICXtp2YEzs4sJqXUpgdQqq62+1SOYYosQ9djP2qH9ZdH4P2/XQcyf366upqux2GYeiHlNLucDAth2ncz0cYiQSCEhuntD/sZk3EDLPisu56iq6k2cujJ4/YxcWP6WhkHz7/AMyPbx7dPdyZece8WW3W/Vo6iIdhM4zTZKRJ05SmVLIE2h8Pn3zy8Tju3/zCm5ZTMaWEDdOL2w9GWe3LRL0kt1iKmquCFyIs1USP0TjOu+Oeifo+MKiMBVJEOMbg2joADB1gnuc50KqPXSnWDd3Q9R9//GDAn//Jn7355NHV9XXsP//8xcdvPHq62aym2czozWdPHHJ3O9LDbhi6l/fjh8/fW22GL3/lS8Om/7/+1z/0VXFXIWFo1Tqh6u4yiIPDJfBV37/x5OrJk6dEKr3ELt7e3pVSzM1BofMYKERRK8UzlBXwUhCFmB2aFcVMlcd5hhcWPH32TBjj4eF4OED1anN1dXW9Xa2v1uvxuCdzgvR9Hxw65WM+WFTh4Erm/OLjl+vN9p0v/NyTm6d3Lz/9oz/84/v7u3E8bNYdOp/p+E/+7//t7nb/S9/4tXfe/Np/+V/859/8+q/8w//mv/uzP/te1pS0ILtEktiE7UwNRiAGIYZIcHOvhYCtbnrpN+tqWumE7MQggQSWIBKFAhkZuCV4DK5qpGDjCgKiJfNYqiaVGtxN4aoGC92Az0p2nKw7Ko7sgBsWMd0TgAX11hOKl3XKgAkbiNxKMTgznB1yDniIvKrNszCZVS3LQBxDMDNi6Vfs7gYrnM1hmopJKcV1aS8VAYeqM4vmst/v19dP3/nal4/TNKakpBwZrMZTt+H1msFZbc5lDAIiCCEECoHN8mF3KPMhBD/sbLXC9mYdwtAHrCmu+q3NxQqi9F3sA3eaPKcM96FbM1NBeXl7+6P33qWt3+0fVOdEGZGdWboAZgMZkFQL8DDtJ7VICZ4pl7u9//l7f/Slp3OHO7zB+cA9P/q93/ud3/6tv/ufzv/Ze+9++t4H+xVyrSslYncCcU0W1bYvbcNphZ7AQk0+MxTqXvQz4tXPjp9wdH0nEkxrF2kAlOFX69Ux79/6/Oadbz759//j3/2FX/ni3fTBy+OHu+nTdNgdxjsjPHv0+Xw4iMR+vUkl3e+OxdKXnj3tYn88Hh7fPLraPoqhB5FaTsdRyhT7EjpnyGazJV6lwHNyh5RsSU3JnMkJ0zzuDzsmXq03MYTQh2HVD8PATGr06e6QVI+H/WF/GPNoBIosLqELABdVV2VnY+eqGACEABGqohPC3kVyuJMQSSYqxbTkCJbILYMDFfIQIgdiVafiblkLuRsZqaeUVN1MppnmSXNGTu5mWZAFIaMkm5NPcz5OsJLGOXeh2/T9dnXdcXz214GPu0/vlJyr+1dF/eAwENeyOAKBiLkJOZ9d/cWRbqB+CwuXEB84e6Sfvdj5s9Gtk5fr1ZiwhLajnOqYAFcirsJd1Qmr9r7pIza87dQG9ZWQYaGXVSZK5dSznEgfLeXIvjz9GaDCCR66uNtLr/0Ub9dqAqb6BzdGVfMGW+y7RCzeaqDa15C50YVsVx3YWqZyikvdHRcFF14rwnDC9ZZbOyWEzGLslD2VOQgPN8KDPXur+1u/+/Vf/e2fu3nWf/Die+/+6EfDVRgPuUQbNY+GQFerTf/25954oPTygwfYTKFc3wzZbJ4RIrZXcXO14Sjf+Ru/ysLvvvfhn/zgD475brWWYmG/n0OMVZPHvDgpyFkwrORqu7rabpnpeDymNHd91w2rtfQilHMx0zmNaXbJx/rKQwwsK4UXL4HBzDnZ/u64HrqkURPDyJk5ChdmJQlC5MUUrm7UcRTuTXPJpJlLCSUXjp1QT8hwJmNmDpDFfXDyzGRgGC+yQb4kzmuJFsFQ+7DXTuYKAQJkwLDpUzn0cbV9tCleDppcPQzcuVRGPiITk8/m5tyH9TDEoTtMUwrzeGe4Ajp0kWPoB15psommjGzZEbxGntUJskofV2QtIYbYd14s51ySVj3xettVrY9M2+xuTtQCg9a/FrzJ3QVwZ3U71bkuLtgyEBcz8zNBkJ+OjACvx7pEZOZqTl7J+Kg4X8XRmjlZkodmtd8XjEGgikDSBerELuZa6Rf1nZmbkJgbSmlmaqEknJCdE68FDopUxSj4JDrPzmzMQszFlIylCr+CbMHempPDlTVT6wq8yqwuK3KxkzhBdqfAsgKj7T0QQYRZhIKXoI055AbUrvfsflYccjZQMC3NQvrZKLVbh7cG39YK3nAy138xT8zMYqXa4wAAIABJREFUXocn/grH6aJ/JQArhkFRew84EUQiEalV2p0B5ES62Gta8JRavFFKTalrRRZPfDhUOdzWk90bV8fgfMEsXt7exQNV0KsiK8u1cK7DbV9YA/0zY++VhEZ7Qw0poiqrREsPSHMtWk5uNNG5CDaGWNMv7o3V4+q1R6q7S606Q+NiVYlLtPs6bxRUmyMYaatkaXiNm1ektgJ/Jx3/lnshEgleI7iLY3mIOlI1Y9RCShCIyc0VreOAW8OY7bSjtYV0asJCILhVcqixw3DuzkBEVPXVybnutmSxE1o681YsytzdKp1NydlJUVurtAzZ8m6dvGoit+XZgGf14iQAFEbsrVlwsz1tvbELjF1Ns1lSVa8V0Own+SoytyUhAnapZSsnMlYNoNgEBjJi50qWI+FAIiwAaTFXAcGYIE2pR0Ksb8XQ3i/ITk024W0yXFLu2t/exAT5JIXoFbJsCnKtrKaOHgiCRY2nSXzyIiNYG3+QuWhtQ2OkGI95znmzicMwmLlm9+xxHa9X8fn7L7quk9pasfjd4fa4P6zXa4khmxaHqUPzquuiBEaYDimNpeu61TB4URaYWs7zZBp7DhRZYV4cZRzvS1HyHFhMse6HAGyHvouDkPQxkruwVH5Z6DpiN0fO+nB3KEnH3dQPfRiG4pQnTZZCJ+RhFVYlJ2MxkZRVjhoH6jjQEIiQU845hyhdYCMyy4oSQwgQMFGBG2LXaeGcVUKRqGDu10M/rTiG475Mkx738/Xj7WZzDf+YmUW4C1YC3nzyaEw5zSkXdH0Xj+n24ZP5+MUnX3pMDOQ/TCkLd0xFq7ilLW2EDCEqka1Xm6ub9bOnTwPicUzp/hD7/uHhOO8TnDsEQNkiCrMHcVUYXLkPCEv+Q2COokpjgZfVOq6HGCLmUUuZTDHOY993fbfe3lyvN6ur1SYyERTshumo98WPTmW7eRzjZtyPmvjp0+2bj760iTe724k9kFme5hBpHYfbh/u725fj4WFa367X+PI7b37rl75xe/vJi48/0uQwcGAJtRqFjWvPTK/YkAO1+WfTNqcqONckPxqgW38oQAR1xIEpUC5K1QiAoU7qKITmLBB5aBAvMXvLhVfzZeY8NG57LQRoiaxlm2ciW9Zarcg7Z5kcVTG+GXBb1iGIWcjFDLAaGJAvQoXNMLa+IxRAzq3wBIaSixV1QifBq7cjTkzOMCFXZuqiaLZMAq+FzqzZdd7j7vZ+dbMubsUzB0ZwCs5C3cDdmnMp8+EwG7gDUycGohh5FYB5tjwphIoiCgXm7brvyANIWMdp5sysm8FvgpMSTHMIXeiisxWkfTrejw83j1fHNM564HXVbnSOwiwWUMQ9YrMOU57VMjmYeqPO0O0O0/RoosB3+x88Wj/pyD54+c/eevpLv/ef/L3/9h/9j+8+35NE7kCFS1FharuXU+z6lCc4TnmbmoTE8u4ujKVgUScDtL7S5SM1KWRLUPez4/9Px1/AyWx18p/x2XMAtPz2VErVSlgAkATiQMxuVlhiiAiC2aZ51kP+ws+989t/79d++de+tnqkHz98b3WDR9fDj97/+INPf/iVr30zA4nQh2gcCpVUrO+2m/UQSDyn7ba7GYaS7f54OKRD0j3J3K3QrTgEQYwSohCRZy2lkBdScwWDmUIfex0IIHKQMnVgato18PF4LEWncTyO45yBHlHAxAp2t6loMSMFMcRDRSnIEQjuJTJ6oVUgOJfquTk7kTFMQhhWq3W/GSSIw1POxYvmkj3NlnSIWzMHSxADmXkxeL3nIIgdMbuVnMbSGTEP5KqFprmkNEIgA7qO1msJzt/99tf/+J9+8jHdgWIMRAQGscSUlQgMrdgbYERi5otTdxHELulqvlCEeD3TWd1Z99d1sRZRLV8kieHELRSs6A8RnFgq96BuSi3/14gzvgQl4ijUesm2K1SkwWvnnOqLkgPUWvdUDwx1t/emnY7q2RsMiPXz8EoEr2yLtpMxY0lgnOJgP4+I49yf96SgeFISQu16SwQXOFnzk3kpo49wO5172mnrWjL3WqDkWhsHL1gBOSpyx8tqawPvHBxKKMRYuc7s5kUPGY9X+st/46ubJ/bp4QfvvvjT5y+f39CNgoryOPusM/qpXw9vf2kTg93ucJ9nKOAHGDDg0SO89dYbT9/83Pb62oJ/ev/J/rCfi+Ysu5d6P41f/spTlkekZZ5nKwLLRB7FQifbTRcDNM9zOmqGFiOjKL0HsZKy5pKpZE8J5BRjV4oTsmlmsHB043lOD3t9tF7nlBESWIyMYSYCcWeDG9gNblZCjDHEGDoy1jnbDGSQsCa1YlDzOaNPFQ51B1DqKwe89ph0J7MqDA0QW176OVhp/r5kECiiX0WKnkvuu1W37gbtDvvkCcaAIefG+SYhitJJJ51wkELlOI0yUmA2ttiF2HUhDF1YeXBxTjYXFIdZMatkLF+EogIChz725MhmWkoIAhF1LVBkeDIAfGPqtSsWqK6T2sGsqtBVrrrAWyO9MxZKDgJjOauiSBex0L90a/BzMd4CXXndMUBtQTs1RanmRjQsvKHTixmpcJJZNQNGxlicy1eRZHd3ZvFFwM+pyRXX8KyROpt4jMLNnBzmjWAOYzr3o68rj2FcI82qatwC/Oola0WvWs+zut8RoQoig9BI+u5wMVRUEN40904a+gwlr7i+Exk7S6WdLpJ2dAJELuHtOn5ao1Sqb7ThDsRE8AbGVXNU8e6/EHJ0qjPwhrgQPmuL/9d9nDLTP/20INw7F6UMqghFJSJBydxqCgKqTcy7SonVdSfC0zjR8jQt40F0If3UdpbagPZ0ZkM69TM91GW0lu88gcQXI70ozFV18RMWRgvRpQpgAaGyjYpWcMbrLHevkGotZyulmBoThxiIaJomVRURkGtFfgmgxscq9UGYiUBKS5awwa5OIBFiIeZatUtMEsRsyemb22nJN9YOm1nVpjd301foocxVtl5U1Rrn2d1dHcQM5lqhU8wAV23Spw00qodd6O3VEpviteGvFgMjDjGEYLUP6GLCHOZm2Wy9WTWqGDFApfYIzdaYZuQsTWyVwcxkbqoGAodgrvUd1aqkCsaAYJXtR01kBlZFPEHEQhI4EkmZi6ZS5oJitEwKrzR3ImISYj912j55Tw4U60Jfs2pajNSJRVhQNbUAYrJsrfUhGOTETgIXdwavRNHqoR1ksMpvc1NVPYHirx3V+XKtxqYBcWc9/wpcMbwVljerzyLLW/HF5wPqEjGHUeTg7loyhIrpeuhiP6y3Vx9+9CHTGLQLHJjCRz94vl5vuz6uNl3fh4f93f3D3c31zeMnb/R9v1mtK1FwPXSBueQyjlPJxXrrNLB71mnqD3vCg5YYw9VwFWkVRRy2WseSEUVharlkWEljSrOrz2PayLCSDkQ5ayQZ1oMDYz9db27KWHTyMvn1ZrXaXu/GuWSZpuMQH5fZwjrcjXuATTiPmgvYdbXpu3VIaTb1KBKDEMizFlUtcFHWzEYcZdUPwmGedX+Yj/PdDfdDt2ZCt+nf/tKb7/3ggzHh7nb39K2h72Wz3mopaRqZJYpvNoGDp5sedDXOedji9l4fbh+evv346maz+RxUeU4TyELstpvt3g4ORAnBXfoSIjab+PjR9ubq+vlHz+9ud8f9FKI4zEsgAkOChjK7QokgxMQWeqTRvRQThIAwhNAFhncUr662Xc+H3V0/SN/z9c1mnlPK48ORtxSHoYsifezZi5VsyAXjcS5Ybah4tD5gcPPDw7iKucO24+1Xv/i1m/XVw/0nOR+CQhEeXz/SPL18+dEbj95YXw2/9MtfHqdfz/PxT/7F6p//wfdCB0suEZVmRubkhmKWSloxE5zYiSkQQCwOgpMRKagR541gAo5AgLKpz1Yc4CaZaUQqlOEKtxM7k6QmZGvrZDOYkdmSijcnXxTda2Osth9UZIuJSNjgzuSL1mft48lElarerKBSbRcqUWqnEWIhg5oRedXPc0btFu+qgJkLUy0MaGohMLjaVJVdqXWRV6+1hLWzsOU5NeCaQJFWw4qESrTnz18oEDqmwmXK0jmiSk+ddUWzMboB5ivmLh8nz/lRH4YgRlnBlk0Eq0G6KCHw1WpF2W5vn9MYng2fv+qeRdu65z50Qt53KwmdId9Pu08On47IWxnK7NlL5zGnlFUZUtgOeUw2C1nHRlLcvRgJxVxol6yP8aNPPt50YftFPL//4Gb1eBjeelnoH/yHv3X9xqNnT/7p//Q//5/CYnsLXWAzLUlC0FxYIit8qbglwAyNaY8Ta71Fp+Ryjl4v93biBQJ7Fev42fH/+fGqB1aP10tZ2pn8WT8kX1JwgFe1gEVmm88uCpMyshWzAhIX7rrQDTz5/tnPP/q3/p2//W/89jeHx/7B7Z/MdO9GY97djR+FtTjpp7u7TGDH3e4g5KFbvfnsOoZOIOvQDyQ0p/3dw4uH273NitmRpPPYswhdPdrWHp9lnKdcnIQEzmRqquZkEjmnzEYAWynT4Wg5u2Gc8nH3oCAtyiQhWO1SzjE4QwnGYkS1MZZlIoaIROGqIh7gwTQCJkKgvfqY85jZCuaUGJ1IiKELMcDGPD8QSifWR1biaSZv1cyqpk7EEmJPcdYYS69sWsbjbVKTzXq77RjFXbKamj59sgqMOe/GfLcN19/+zjc+/NN7GdA7EYXA0YoFlsIVVzFiNi1qArB5AZbs6JIKxqlFfcOEICc/iZoQaouX+CS1eArEqOZfl8CvVevV5AnQgiaFLhntJc4ld8JSQ1B1YGuM59yqHPTk0jZBn5Y3Rg3rsEBc9WYM3uoVTvPawSKo/YUIEHAQJsaiklSj8iqx4k6kzR2stQ655FZn3TzcKjjCqDqM6gSScGYCL2ESA0QQr/tsi2ThFdkyN1tUKWq6vj431dC8yk6c6hhbatdhLhiGIe2c0PfrFcdj4TFs8Tv/4LuP3uQZL1/sf/B8927GuJtiv+ncQu0IqrbrVrRerR5dPf7ml7/Y2cZGSpayJQjFtUBqAGnf/+H39se9kbqEudA4YVfwhXwF3JR53N0hhpjH4qbMut0O19dDEB+Pk+oUg2jSzHkYYh9XZUYq7hpLTqp+td2sNxtVmo73h8NBCwKHlDGNzNDYR4pzt6E+RFNLU1Yr5gR1txTW4obQSehYmIauV9U8Jc+GDHQwNQ4EAagAqdjMLsxiXpwhEtQKNeSw8hG4zR8nBxE3BgHI0NSvsLrpNSjEaeXdVdyGK3NOxzwdUhoz9xQFtfRgvd0+evyYSHbH/d3DXZHSxVX/tMspCQQuxT2Zxio9Lg2LUKLaRqcGmS4Gsc16s1oNOSe4BxZNRZPBjbTyoInJhURryYMDBKsbtFS+BRqyRJU1ZH5Ru+eE0JSGGvhFzK/C2D/t8KaI2ZY0mTQuzEIUqgE2VRj3AhgnQM2FhZhrmpNJqEZTBl+kgmBuZsKM0GqM/AS4MC+36G5OBheYGpz62DGzkxoTW226zd7Kqlxr6vYiPHN2C2ReYFahtHqTDSmy2o+8WRoiOBs1W8+u7q6oFBZqDRYX2ujlXgkv3tTNmIjZ0HR+Wi9vbgaj2rHGwawo+Qmcqn3MmpEirnPVnJnVz2+s4VmnK38mnnUKZulsKz/jPPuJs+AvCEW99pHLi/yUz4ZSVNXO3Le6Z7trKfBKjqQTll9rpIiquB6bQvg8fS/kzs6T+tXs61/m+PHPnotUq5JUZX69JjDmHkJwd2ORIJVdJCxTGomIhU96TACISFXrP6pAVS24L0XbbHCHQYPyojjlpJ60zuyLXbDdLBFBuF60Dj7zIj5/wkHodKdet1MWrkBJhVoqPYqZF/ilwu1tUIgbCavkQsISJMZIl3IwZk6kpSzXQ+UVnTwFFokxMjM5V26RVZoUvJbolZzUXN1gzLUxkJM31M45UPVE6/M2/TJAQpAQUqm5oSbuzlWV3HXZzhdHoQ5C5SoxmCRyvN3fQYGCprfFFXtyUyOiSsUibtVDVaK+4mxmtl5tK2/fXWsfNCZmIa1Vk+6mVtS4Fg7WqeTuVpzBUYyWoqkWaDug1T+rmYHWRKDO9pNyAcGygR0ClsW3WUhYROe6cfOavnCHVlaio5LSWjxgNf2jjuQcmZjISQgxhK4b5pRe3s5wrGnsNxK4O4wPh+Megqvt5mq7nnUcx6MgXD26WsfV4zceARxCZPd5nvI055xLKq5e5hyEtqvVerUSoVwmdkxDHmTNhKHvV9tV5Kuui569zJmpB9OU0mRp3E83q+s+OAKrqqpCKMTIoC7Gz3/+85rLerMaun6a0mTT/jgLx8Bi7ofdIaVEzATuh+i5lOzTMYsQUYhdVZazkhWVxG+a1eFZWGKIm/V2ntM8z4dDka5cuYL9OB1MS9/HYQOK2M871Tf6fjN00VTTOMbYxSjH43G92sRuiF3/8vZ+mqcouNvdHg9vPH508+3v/LU///M/v315XHO4utrwlons7uFoZv2as8ICYgxd35na3e3uk08+HWfUKKwLWK27INzHyOQpTcQcYyAW7sJ02COAGRyIyYsVqPdCfd/Fjvb73Thhs+nX6361HmDRjFWx34+kdke86cXdVKc0HxlDH3sK5KqmmWAl6bjb9Rwk8KZf9W9+7vHN+rC/nccDba7hHGkQCYfj/nrbv/nsyXe+3R32u0fXq3/+Z9+7Hvrdbp5ShYkFSnBIFO67kkZmqWk2wJmbFl5jrFfZh0DELkwUiKsMX5PWWix364RygiRAaNl1J5gqtMFaNWHPgGr22tGHznqFbfu+pD5S9YioJZsdVHsm1Oy7LT4XHA51ZRcnr3zTykcnSMWvWvBDDWN2MgIJBSc3NTXXopWLB0ZEgCHNGVRYmIJIJEQOMYQgaiWXHFby9uffNvM//tM/XTxaurresHLoeNVtonDJMzsCRR5WWTEVKylnTf32OvJ66MwsdZ09efPR6qob/1/23qXXliU5D/siIrOq1mPvfd7n3tu8bD6abJItUnx0k5BIt0RKkCU/ODHgmeGJB4LH/iGGf4IBDwQY0sBTG/CMgAETsEzJpJv9Ynffe889r733elRVZkaEB5m11jq3L6luygRouGuwz2OvWpVVlRkZ8cUXX8yHIP2D7dXt928/fPLzzx6998X3f7aifF5KH0OxxMypTN/49je++b1vxlU8pvGYjtsnVyppPByyGjmXEKxYH0UIoQ/EHLrgRpZtP0/ICeaHHV2v4uNHa9KUdscPnl7f33/3as3/4A9+J8qDN3eHf/3Hf35rxyBdtiJCXd8XkvFwbNWEDhKAmFri0087YLPz1Ezniaq1cCiWJOLl539y/H/t+EtfnV8kfwgV3qldVBr9BoBwQ7QCiBQyFc/din/2iw9/+/d+9ff/6W/I5nh7+Khgrxi//9Gr3fE2xPj48fP9Ybo7zDF2prq7n8V9vdo+e/CIDONhutpeE3h3PLx+++bl7ae5o9hR8bmME4mGSP1mKDampMdpnFOphPt+6MxzKa5aUk5uJVk2K4WmSgYtOY1TnjJJF0RCjB3Ba+ExwGpayFg4EDswF59TTpmHFYVezDhNWqJDOXJPEgVyKJNrtqS7fSEA+c41wbamUZCFLITQh0AoFuQ4ci6OYsSqMAkUg4QYY6/9mkEyj6Rqli3lqRQM264fhhC1JBquhjKW3eHW5zerx8+vHw7Xj7ZKL6Wn+ZC6YZW9MLFIV3Sk8/sz9UWk9ezrXyBZF4ed2hYuHm/lZ/nF4m/alo0j1AwBoWlG0TmKcG8J6zOw1OgNVcbYrcqNmhoF9VOm/CIMoQr9oEXop+OMrOEEsF7+erkeVfSsBvbvfqqhbX6axrSUB8Fxiv+x6AF6y1IuIVUlAZ9CiPNTXYgPhAbtkzfB2BZT1zimaj9Vhc56f15UFx2V+mRJRCwriOOqH3dzXA/FCg3jF7+I//y/+Gf/5tt/9IOXL1/d3u3G3bB9oO7jnAsZRASkblM6Xq/i9cOrm+HR1foBCo9p2s+Haco54e3b40cfv/z09cvDfVltV9sH22I2TWaOyJinsruf0pg1MZt4kZTnPvJ62Dy6edh1tI90t6cQbTym/WHvoL4btMpZgufZAYQQCTxPaXd/KDmJdFpQkhFotVqPxxHkq1W/Xq0Bnw6c9iVpUVc3OBtqXKuayzxNyd1NVQAVqObVqpsmRQIIJGbQIAJ2L3A3c/barwy1B9zFtJKlpIgWEFKAFYZt4A7oqONe2cY0hb579oUn928Pubxx0OPrh8fbl+v1eru9vrq56Ybu9n7vs8c+era+61brVeJ5znN2s5SLFSlOySgpGVwtECOgmKopC5FQ6CTGELrIQUCwoqOW5KXGUBJ46IY4hMyT2Jkq22ahL9Wqp+lXsWJ6Z0Wc4uXTKsQFgPWXoQxtibUYallP3Lw+NEpJE/Nr3sAZwDpZBVqw8UVpSN1rUrRqGld4y52WGkA/gdGLATqN0tXcDUrKhbyurcYEI+ZGL6vKqd6qfCv50ulk+JrOFBaLQl7ras5L14FTuU61Du2uGuZWOS8/ZDoX2B5SHWymGhGpXoBprWFaxQ582Vu5SQS2SJUX6pifrdDf7HFy0U+T4RIS+VEwrB/xY6cjpJROfB3UohkiZq7QbAVQDDBbCt6q7ngDHZu21SUiR5fCiO/ew199fO64P/dcXwjJLevCf9XiWcpXCbWdn6OiV61gbkGsKghSP1O/lhnMLRSrW1trDnfhcp33GXdUrpm169ZHV39XP3LWj3dv7OC2ZzV5qVP3gdPOX8WqTkvST2vHze2igpKXYRMRnXUozy+ggqBoGFYNxhpUR41hZJV8VMEkBgylqC3p86p1B126GXIbn6ovb+HUz5EAhBC80isAIgrMtQlb81nOzklFuRA4MgV2cgUyqhAPsQFV6IbNzvWeDhduQmz11qw2UTTknCuc1SzzQtJjJneiJuBysoe1qrVaFMupgB2BBU0Q7cTsrjDimTK7NBxs1NTmlXx2rtan0bDLukGcAnKr0jvNE3Pz1qSstut0AzvCcmtVGl7NFJs1TKFUTKlf9UV9ntQUbvchunPuegwbBnSajjGKSJAYYJRLznnOWogZTAabi9M0rcexX3Uig1sZU571noCVriCusTPYEIZuverCalht+m4wA4j3+50NawqSck4ld7kbNmsRZuE+drGLUQIHDp0ElWPB9ZpFAMX+sKdIMA8SQmTuvExz0bzbGxNz5aVB3VWEWUCAKgoAD323Ns1Moe+71Tqrcykp5zRNR7fCq67vMQwgmk1zCGHou939/jjN69Xq+ubaVbsgElgIWjITbq4gfdrv7169jj/14XuH8R76CoTYUeCw2nS7wxGkw3rIh2wGM5+nbLqfUx6GzXYTmfg4jnMeTZG9bDbr2IVhiGY2p2nOiUwfPd5kL+ZmXrRoKVoI7Hj58m0/UOwtgvf7IhKutjdPnj0nxPu78dWru/3tflUcjzYkQ55LmlMX40PurjZX4mxFY/AuUBSwa5mnOc0s2gfur29su52neQhr4YHQpaQ5aRzw+NH1r/zyl/qOr/+nf7Ue4v4wI8MF4JqOYJNaB11B/Eq1bnkcXzZiB8wgxbknEqqdq5zOy62VZyzeSc3PcHP2qJqOiv9W8faWJGmprnd2webc4Ow5oKXKsOTQ0S6kxsSo3ZFbSHxS3Fz06tsJ3LJz1RYQmMSsVPY1E3OMVNvNJJiaVwhfBE6qlkxBELBIgPP6ZuPkq3VvprdvbzMy9+yjYQIeAsC6X6+6Yb1drbfd9abve+455rgJq/AmJ7ALUTFYmdxXIWLo1iIDBe3XUUQI/ObN/ZOffv/Js5tVvL7aPHz08HGw0HHMuYjQNGUBrJSPPvqL77/47vrRkG1OZQYPWXVKOWclRJjEEIh6DkjVvJfiRuRkRCxySFNKxRCPeVr30d1vjy+vVu8/GIYC/dVf+9Lv/8Fv/8m//T9xV8pNAaFkdp+YuF+t8jzWR8oITbjGvaYgzhlVRuttv6RNq/GjVlFoROxV/OUnINbf+uOUkX33f/8dzl6LqVG8RePM4Frltd6sj4cdZkVPzmRjxhEf/sL1P/lPfu33fv+3nr6Hb/7g2zPuCo5juX/5+uX+cHj8+GkX+ru7+1KCuGTyNE5CuH58PazW4+5YHBy627e7kvWYJ4VK6PpV6InVAolypP1+LyGkXMZpzNmJIjERu6oSQUS6GMMwdCGGEAisKatZkWiU7g/HwK3RVW1aG8xZyAzmDmbVnIrmhFIwTjYllJXSEIlovXq44gemXFxGcxrKZs6vb+/L/IYcgR2ehItpcc/GrmrjQbWUYrQ/dFmdWUN0CASgKCxCghjhGoqCJcPNUIpn585FDGbOt7cTmc85ix3ncgjD1aOn/ZOH/OrljAJJI6wW6bipu9S4joCqhujAKdy9gKE/85bt5O1cEPWW2IpOM8GbEWamJiWBxtjC0rfDHA4j4cVqnH4ugFON2QhoCoifM+VayLDsKXRR6HoOMc7leov9qXXmbnAQk3BNSLdsStue4L7cKC3fdrrBBZhaYun2OJoAl1ZpZvelaqkJfRgqxMCLMIvBKzt6UaNYou2G+9eBVB7CUpENBxEzAlhiECIcdkeJ3m87l33S+1/9lWdf/4++Akk3T2++/fLlWHS9eaYWi1rh4jq7USGNEvq+i30UIgpQz/NcuBt06v7io4/v3u73u7Tfj3PyrBgQcqY55ZRse9X36wBzy+ZKZUaZcpo0J/BgsCgeuiDrYV1K2o1HYjVV92JeSplTnswhAcKoOrDH41xy7rs49JucSkqp5NLF7n6/Z0gnfa1l0ZRL0NBJiJLLJAFz8aQ+zUcZaX84kHNOcy0L3FwN3SqU2dABigwNvZBxJY2eIq8W8jWkwsBSi0haWpsMpCAgIK643/bKIHjsgrrd7Xer9frp9ZMrkzyraHj6+NF3jy+3DzaPHj8YhvU4z/vpfpz3IiIW3ByVQ5ZMFepwVS4uBWIIoUTvAAAgAElEQVQuxgCBObJQFIWZsccCwVyST3C3XLLmwlFWm07ZoR5cAgtLLQlpNbPe3LMF3HnHoNe6wssQ93ycdmf31urzc493wItTpe5yJi3EHDdY7VX1QyyeRtxYWigsr8Kw5LtOg6kMDHwGKiKIQ5voxeKCtuwnnBr/nJcwy5mq8k+Fz5l4oTi2x0PAQiHBeUDVOLYcDZ14FU2JaDFSFWpALZEkarWErp+TrwsgoRBCC8/dF0WFS7xhEeg5vT7U+zsRV099J2hhJ53O+lExmR/98OWFng3ju/jPX+HRfeZXP9bYQk6pnlQBlxMviZhdq2S5W61EI4KjEi5owR2xeCzVLYkhxq6zpbleZcf86KP5EY8K9lzgMp+PfE3TVNckl8KnHoLUsJ5LYfKKHF2eW0dPRFKXPZGadbEz01LqfSlVR9tO13fX2pOLz93d6yUJAE6PV1VTyss5tQtYZSLU4bg7vKCQlqK8YNVEJFU9BnCgmMGdY1ivVkRUgZv6NNy88WIuoOxz1TEzSd0eucLeKSetKryVWFGVbhjuCMIUGC5aLOeMYgBIqFbAmblpqY9UIosIExXTPOWuC1BDhdUJpVTA2Yyo8cuFQOSTw7zr+l56gZTsc5pxBIITUU34FfMQKEgsRc1MteZmgFDhOq5/dXEI8jSDKx9EiAC1UkqarRZ01WwME6u2IkIwUaiCOJVWWl0EEaq6QBerkMQX94uaxGCrYwbAsWsvid8xo/W/cF6l1X5VytkZVwRO+CJgqA3LzMxhUFZCSmll/bofPnj+hdu3t3f3b7s+Xl89+ML77x2OexJ//vzp8+fP+nUsJY3TYZymt7evu67rukDCOZfs6TDPc0YfEUMEi8757e5wmNI4p+1mPad5OhzzPK+H1fXV9d39sBpW11fXQ5+ixO0qBFeGBQlx6N9+/EZL7oYBTCFyP8RO6PHDa2g57PerVX/Y72Wih4+fcogIoICc5+JFc/LCgGVIH7uOxZ010/FYwBCGCERAjGkyEJigCglYDZ5mXw+du3Uduk73x+n29q3f+Grdb9fX6+3w+EF/d/f2sH97d3f75PFWIK46jTuCrtf9w5ubEMPd/X5/d5um4/Vm4BiKpk9fff/F6+9+7Tf//pe//HMPr6///Fv/9+7wKnKMPT151ncSHzx62L1ViXG9Xk1T+uijl5++2MWIPq43240ZpR0SJxDS8XZY91dXV9yzmc45qRaRQQ1mWpl0MYYgRlZSyiGE7XYlgcwLUzSj27f7adL9fdIi280DBbrhQb8eCHDTGNaBOzhpLkPn2z4WcHCddnellBBp1XexiyXNx2n+4PkXdnfHu9tDmo9Dp8Jr4XGzvv7KL/3Me88f/LN/9PXDYf7zb/7FR598nFWyViBc4GyOrtJQa4dMc3hbCzF0Eqr4h8LNuRXAVkhKYeYmXJt7uDtMjWpDEPdTcNuaxjbvnMzd4exQr2pTy4JoGL4vO2JdiBXxrzGStw3TnEBmrWbXrPYhdIkiXaDQXArz0nJq4Lr8rUlkOMXo5q3WW8SY2b2UUlL2bFAYm4m5GZhE4MJgcrbM7ihmedsP2+0VD96HKB07+S/+5pfef//93f1hnKbbN7ff/rPvwdBf4cmTqwcPt+v14MRA3qyG+MAmuQOl2/sXKOnBzfX1eqXm9/e71XolPJDGeex6jf/Xn3/np9e/HDEE7twsMK62637gLQ+fHH5wd7gtMk9WXOexHL/38W62ORdPhdxSJ3k82mFtMYJjAVSowshCLOaW5hE2z4bvvPj+8ycPt0Mvupvv0pzA9vTm0c/9l//Vf/Zf//N//vz5r/3Mh88Pd/Px7eQSxmNeDT0NUvccQCoDmJhAEdBKEAA5O5AcZxjRLhy/6hou9IufHH/7jx//LTUgnN2VsFSTgsWZCZTSHHrmDSAWon34xcfv/Uz43X/85d/6ez//4HnZ5W+O9oOPXn3XWLOllLK7vHq1e4mjqj16+NSLuVvfDUMfh26tTuubG+nmt/v7P/vGn4r0KeX7vKOCOPGw6rpeiM3nEjRwkZJNVWuP6Jzz61cvc55j7GFeig3D+upqE0OcpnScj+M4zvM8zW6EXKqKjikh9uIhhFA1eakkPc5lf4QWDD1W2xACE6ClcwnQTZTo4DIVz3rV9zcbeXzz5O3N9TzfZ93D0+7+Tf/4ehiCqo2HtN+n+Qg13B8KMfpV6NckzgEG0dhF4iAdi4eOsNHO5sLkGfNcZD9xRklFca+b1dANV4F5LHc3N+vf+O1fksN7/+O/+F9XW0mHeTNcM0lKRdWZEISZwUQsKOWETp3Wrv+QKErlKrTk//mn4sRFp0ZaIaqdZ6nBRoamTFi5DH5mRdmF4M6S6vNKZwA3sVZ2cjupqlnV2IbUEXFrFwN8XsBQ09vnWbpUUV1UabTW4XYOzxpwdTrrND53ACJS85Pm1uBaBxxKVXCn9rsFV/H4ChcQUQUKqVG9Ts/Jqr9akwK1GJGoqJIpCG6lRbnuHBne5F6IiCBahDmESCUdH73Xv7y7+9rXv/gP/vBXfvef/J1//a0/Hml/uz++eLXr15uc0Q2rvqOS9mk8ZLes8939uO6PgftDHAMPx/v523/x4rsvDuMeMWDVrUNYXa0eOO3UZbcb52lCQuoUbJp0PuZ5zK9e7soRKEDBuMZ2eMuqV9dd7ExAgG+3mxhjCJ0WYzFmxEjPnt0E6e7u9rdvR3f0UYZ+OwyrksaSPRcHshYY6ZzGOHHfd+5FNZkbMRU3Yb657h88uqnzS21246Iq7jCM4y6X+ekHD/7uV3/++9/+5PX3D8QEYVJWUjQ1JCZUWc8L6XYCx1A16Z1BEkicow8PhrgelDLEPIpbcbJ5nt/c3bEzBUx5fvHqxfrBVaHy8u7T8tocePTk8dNnT1988jJMKc/zy7f3JcENKG231Kr6q4Dpah3Uyuaqf/bsyebmKqvtx7u3h7fFShorH0VdjSFCPKwClHy2Oc3TmIYH0dSt1QF7LXxskw9gCMjNDcZO3rosLR3YKmWCrTl3DUHyf3fSAoBq7SbeVi95k9AhQ8UKGgS8fBNhEbLDiVDJcHNVIxKWEEIpxU8+onrlZFQ6hZGRtAXLrYJqQVhQ6U1VrcWIiEUkBJDVG6yQnFHDpWuyuXon5t50DppNstYyiBq3oQ2V2726e+v15k7EHKSaALeuyiF7rRT+zOGNXUlLKbQBzMFPZqf1RqtjOJ1GBoMtWQM3EAD2Kqx4iR7+zRwnC7nc+BnOw48AY/31jiAhnPLVdQREVGfGORHhVWm/jewE3tbhUUtjV/2lStuxZVL6jzXiz/3wDwNyTcybuWZh/C85kVmY6ZKaRETFEi57DQCtulCkwkBLdqXedaPioIrNmqmaqS31hqBF0LE+pfrTydydRJbOnSDhyy2eiERa5V2bkI1ppZVS5H5e62Z1kI0pVgdfeREOBJEQAgBVrT3aTnfXvvwEDjfZUYgIR3G3E/Lc4LNW2e3MAC8yeszCQghupTkuS8fDmtCicxFviy/dvKj6VGoNdTX/xmCubUGqtHrdzhkwFokchYJnL1OZxwQm4SjM5kWtQOFMFVg+GSwAXsoJ9G0VgZVsLBXfdDMtpjBnblBkfWciolQlo0FMHJiFnClpAlENjB1q5iZuYrzAf+31Xjgr7u9oE9bXe5Fwq/4InUZeHS6jpoWKE82bLswigYiF2c0MJs1yIeW8348ANFtRmFIM8YMPPrjf3RrKMPTjeNgdknmZp3l33B/G+5/+8OdW64GIc945jKMENwkRIkRBUbLBsx1m7daE0Bun4pMxFdghzUoUho5D5BAQ2JgUbrDAvN6uJYTFONs0jcfxSEQ5JzV99fb1cbcvrhu94aHmLW2a5sxORhDAuNZdFq4JR4ZZTQ44yMhr3oOJYmQPEKEgHUw225t5ntSYJRsm1ZxL8lFN0+s3Lx8/WoFsvV07OYjX23UpOee577q+6/p+Nc8pzVOaRwb6GKQLc9FUZtW827/drDebq/js2aP9/jiPswQJCrNc0hhCDCGuVqtpzNM44YCyQSfkVnc8EhJTnfZ5yjkEubrebrfrrpfiRYTAQlbBHQQhYYFbiBy7mLMV1b7vVXHYT3sru/tpd59hoY99/+yBIYIHyCpE67sVKJRsVIw6X/UxmVmehm4VQGaqcw6QwLLdbEuyUlw4hsAp5RcvXu3vjj/1/P31evPgZvid3/n1b3zz24d5v5/vP317KBNAkKGXyGQ+z7l1e7JljzQCM0iEAwUwGE6GKrTuBmg1TLbo3Tbx26Y7UBs2MDchXvdFMbduPWg4P1XX/CLhhjN39byi4FUCBcvpVJPTlS1Wm9U2qyAE1BR2uehvTASvcqZKROyx6vItNHYmNmpb2Dnv5RVTBpMADnIDmWNY90Vh4sYmHTvbnGZyUi3f++73bl/fzXOadklKIGBO5dNpN97PwxBVyqOff7i+7rY3MomzJ0+HrEhlVAsGEEVQLBlRh+999/UPvvGx3t1+/Zf+w5wsjfvOaRg6CTT0XUb6zl986+74ZtLx9ev7sPZCpZSiJKGLBqTJZnVYKWUOEXGlIfJqiBIHEtaUrFiBWcnq6eXubX8VlLObXg8PH9/0xznP+mqekvb5v/3v/pv/4b//l9/5xovNNogFsIcgmltrJlRdsfa+fOmqAZAzqs4onewjYC0js0CRdQ9ZXuxPjr+9x+dlSi9CkIvjnB2ktvi4acYJIaB2UWEqaQ4rgDwdPDGePB+++ve+9NXf/bnrp570008++sFY9iQpa8pmEkNAGMeihbrYw1ETgYG7IP326iZE0ay39/tPPvnk1d1t160kBukFnccuUCAnKzmnMq1WKzIrxVVNQpVypdj17hRjp0U9J4CKg9RL0bloUQ5htYq0e3NgIoMXrTRpJzPLWhXDczbNYAcYIYTt5qbrOss5TRkFf/J/fEcsaMJxLsktbK6GdVxfxRikX205BsM0p0PJU2IpGYdR9wdogUg0BrEbsYEqPuIlGXHgngN0mtUMnDk6CNwTd6SusyoQnGRKPgQ20v34Zru5evD0+fWjDiuMB4VTsQKASIgC+YIyu7qB2HHp8Hx+6LoUsqCu7FYYVDPfvpxHzNQUy6sv2fKpS4qWgBbkAVVF9dIitNiQ6qZ0UfF0sta4vBgu1Pj+kml8CWDVs4hYl1OYuZZBNSyqWbe2xRExtS0OXtEpsxhjBeDq9du46g5Dp/qASvwgoBUqOrkvABpoESuqIVgD5CrNor2XZWOsTYzcASFxMJHAa8Nd1ow+Sr9alXI4zK8w4Jd/6/1f+vXntBrX1/Knf/Yt9GsK24Lu1dvX1zfbtQygQBKhGiKvVkOUFSmr53lMr+7ulej6eu12VKUxJzZagcGkWopmh3JPUSSShxDmYzoc5nIAppad3XR9x5vpkLSMq4G5txC467sYOgeZ5RCo62QaCzNAllOaE1Y9x9hLCACbNdwkpVznSykppVDbaxuKC7Q4RpRo3RCHVe9w1cIsagpHVkNCXuU3d6+cNHniHggAwVSJbWFXVXqHUKsBrS+oihmVlp4RIJJE5p65F4oUpVM2NculFLWUx5x1kJWTG9lkOVLKaQIwl1wUFOLN9c3jJw/3t4e7+c5mcAY5WSGYeOPtNP+klJINkLEfx7Dqkua5JBbWrHOeQWAiVxdikFa9PRdAKEKsmC75I67aVwSAiWuHHnZzapUpdBIk/8zabiu7gVh0dsw+u7Ra3NRojJd7euNNmZm7LlSh+oH2mbOPQJVqf9EfsL2a5Zvaf7ZiyDPiTERQc/NKz6rNe85Fn1opUEwMU1NSJxjjJETBiyNyYjm1CoN6o0sbxyp3RThTkM7Dp9PavDQ1C0pdmWfu7O0T9YkHkYqc2iLa3c5obfXOVIdlcC2WPAf7WGx2bafnVtUy6i1cvpp33uy/n8t1wlgqnvCjf9vpfZ2+50e/aOi6rpSi9lmwiYggXGlsJlaKuhsaXgWqOvetlvZ8mHua58uY/t8TePvhmzkV3LXB1BaJF7y+87k44QNtYp03ITMt6uY1RSEiIQQ1ndNcpc54oVC5u6pW0IoWWpWI+DKhW9TVhgag1mFW/nmdJswirObuOee6cZ+oWAAqhRINeALOz67BdGYuVa+KSCu1zWotHpna8XjEgijRUviJixgRy40ws0iQIGBaPt6Yd8QMgROIlVopEIiwoFtGTQifvLi7WVFikhgkNDqbeZtC9Tt1rtpbEELFiDg0qd+8sPrMNUpgC2Rs5pbNkmLOBIkcmLiQqRMcpmaefZkS9YU2TXzCIssJd1xdXdXKcNWMxZ0hJhGuDRlpIXO2Dszk1T5SrRquj9/coW5Um8ha9ZMWTH1pLelne0DQUtAe5TugFTWgFUv9Y83InZw6oGlOnye8V3eepTYJ6GIUgkhIU5rGKcRgZjGEPOdPP3k19F2eCweUoinNx3lfwXbm0MV13/c5pZTy7d3d8TiZOwemICAujt1+qnvV3W4qRsKUU9bsNM5g7j0onA/iEAW6fsYcUjGQcMGHjx6TtmZudWJnLWYW+/hg3X/zm9/Mc3qSR77p1nydFGplyu6BABcW5+aplayu6rUFant4sKKt2ZEQN8eMpmNxPd7cbLWAJca+l+PRgClN5joUevVmvrl5Vqx0QYrmXCyErl8NfT9E4UBIeR6neRzHSrSZp8SuEr1kjR3e3r0sOl1vr3/mZ3/q1etXd2/uAezpmKYRGIahK8U0F1OtKakoYsXmUUu2Yb1erdZpno/jwSe9e3UPYL0ZmLgqMhI81vnGcCvm0GRpNiKPYc3E7mASd5mmst/Nt2/meYJhZ6nE2GV1hkYSpwgEdZr3B518LVcMEUTh3t3zlKYymXWrVd93Qz+sSia4wstxTsfxCNOcrmXb9QN+82t/xyg729XDq49evP72tz85jBNFUjItJW5YapGzc21HUfPk3oAbbZ2NuWmt153yJOVY9/DWDsEqZxp8Uiep1kkbK59aRwsSkKqdNpVTzXU9odVxMxPIK7R0gvsrVNJ+ywRdVhOWdrEVKCFaGsfUMTTRTQY5yIiUUOnDrlz1HX3Z6Jf9AAqDoqB2U3RyisSRM5IeU5qSBAgHSnS8nY7jVEopR2UKwgxC5Iip7EuaJB0JV+8XfkhD7MJ6iBKEYp6m9dDFIRCF7faGOH780cv7T16lO/zp//7y93/ny1fr6y4Md9OrBzePhTHrMcQwY3p9+yoModuGN2+Ph8PU3zCLkHrJPs82juZqKSBliPg2hDnnOR1jzCLCMFhKc9aUNj0mKyVgRr4b5+l4ZF6XefPkivqOjbv/9A//4fvvPf6XP/M//4t/9b/gsP/g+fNPPn7b910tM19AQq4AIWhBo6sbSbVJ9OU+5zW4q7bx5I/95Phbfvjno1U//LHFJtBCMgdCjOxVs0DU2cxVdfvgaj/esviHP3f9i1/54n/8h//Br3ztyeb9u930Wjm92b1wMQooOSe1abJxMkLXdT0Tz8epi9GKT2UW5qurm1U/fPTi4+/+4AefvnxBfTyWqY9DP4S45u16MOg4HveHw5RmEnFHzqrFRUoQdfeqMxEkqqKoF/WcTUnH2Y6j5mQxBI7iEowrqFPUPalpLgFNLFTVRORqE0LoWUQLj0nTVPJ+1kOWyfVgZYIRqBMLs1HabsMXfvrxo8fDg4cPYm93+1f7/e04oahMSbNCZNWvtje9Z00k6iimVRucYi+bzTBkZL2f8uSsJJCA9VW8ulkNq8hsxL0hT/PUd11cD9P+uE+vel8/eC5/91ef/un/9rq7CmUs8+gSg8NqZyA1MzXYokP17iL9zCxoiShbGsGeXNDL4LSmFapg+ZK+qJ7dEmsum8kSiX1mWtU9CUvMWDObNa1xAsibzWZqjcsXVke9OE7X/vx5TE0ax9AYFlSppDVkXRRV0BIeNfdZzZyZQeHBT70OKwcENVY4x9swN6l0jZbLqeyLutXVRBAcVgUaSeAAbKkbdAVJhd2oCrYuWBwRu53U8J0oQAJkRo/1Q//aV59+9esfPvogfOujPznYPJvfvT4q86ffv5/LIRlu4HGgvltDQVwfbTFlM5qzHqa0m8pcLPaxM1EFi/Sr7jjuzUxzBrzb8uNHV8MQuxj29+N+d4ADETBcbYenTx8/eXSd5vtx/3bcJaXyhS89zJpLKe7Q4o4igSTQ8bgnCiy83Xjfr9ar9TCsYSTCMYaSdZ7MC8Aohlxy52LWZJ1NEG7w4Rffv7m5JoaaOtnmOLlZ4BlE8zw9fvrg5mobuyBHfvL+490+TbvsWhp0SDg1tWfUNp++TCBHYKCiVwiDxD548LnMZDysBgLG8ThNoyuzgzpNOXmCZyNBt14fx/uiMJCS3023oQurMKR5TsdECiGy4mIRLqbmDfx1ACIhexlTeru7zZwRWFHMXd0AsEhV0SUic5umjOwwCIlEMbMqmda0iUWM4AqixtaoS80qWaGCQbUVaK3UvVDrXmCXc/LpM+uIlkQ/EbXvW4wFO/uJXb/YBaILcvYJflmKZivYi4rgmBudOShE1HpSX/x/1QuCg+sCtFOeswZmtQ4A7OrCS31uZZswhAAqqI3Izg5gewRYIKql9URDPLhBAfVj1ec9VT43pM3dHbKotCqsUusuj3LukEoNxQC5LqgcTmShqtpu7R0BAtJ6ecICk9RgvrFGlyoGNObF+WHjHYv5GTOI0wd/JGjpM1DUjwUB/VjoFWoVVo0TahFpg10WjKY+ghACMau1WlUHKq+pWm/mhnPBLGmpLv9lruOvgV6dqEafPbfCmXRGBOBem0/Vbiloi9wBskbdXaQbq1tNjfokQdy8yoq7e0qpdW1nqou8XdDMgEpxjCT1KS0ISCXS2IINiamV0moDRcTMXE2C9H0/H8f28AjM4bT/VXxKizVwnz6jm+cnbpGZYdHqsgpggYpn5HZ7LEKLPn0IoT6l43hseyKfVblOVzdzZh5WA4gMVqyKCDgzs9A8qrkJvGbJcEKBWw8Ud7HKUmZmcz3VMALoIp9bvrQdvLZrqZj10r8RFCRG6cpU0pTKnJkECiikE4qdqmpRqNV+pudSUAcM5k1rYTFOUFOvPWG0EpgqDlfTEJi1wCm4Ny1phbOTa+0QEVadwVxrN1UCG58ZUgQzuAta1+f6nqrIutfyw1MiogFc9Y5PIVlF9yqfnZb+z+fZTiddBgaB3AxEwlyyVtGoXLR4NnNhJpfjYZzHySWr5q4fttuh66OTuWsI0g9DP/RpLtM83d3tbu93c1HNEOYCVSczqLspoFpwmHU2U6gJkHVOltbaqxkJGyirFuUuHlb9ZhjWwRmBsmZy6ro+iIBhsMiBmB/c3Lz54zeHw8EC4uvtF59dw1HUiaHqoeNSLMTIEixrKcWKtpSG1uJBcUMp6rU/uDsx5+xpth3v1ttY2wMD3MVu1lxKDoGZ5eFNmHOu9mae0ycvXjx/+tQBZila5qJE2O/34zhqsZwAT30XwExsfT+ozuNIm9Xq+ma7Xn/wrTQT0TzneRr7gUshKx6DlNm0qHTIk3adwHw+TNurm8idsgWRXDQn393vckqh49BxmicKkMggbjJzxGay2xtIt1s4KCeNUYQDAVqQEjSDAl6+vr9+cGMOtjkgX2/WoA4IxzHdHXfvP/6pu7u7XgYv1oUYpZKFTbXMM7ZXNzHGeVKHhSAcontK6b549/LN21/86S++eP3x/byXjTz44OHr6bXe5rkgdjIfihUPAUECSwDYCtxqjW2DV7ltn3VLPfGjAAcLo+omGnyxVGfQyJ2a8Oypn83yLcCidXthAls+nOScbXO4L2Kbp/iHajuHFh9Q44qiNquqCnm0rKw24nPiQZMCFogDixHI3VRbRqF5V0zCDPLaMZGNGBRAkbOl2Af1knKeSvn5D37mxfc+3r+dMQMF7IwEBxTubhQAhsSATvqY06EcbscHHzziDl3Iab7t+y4Qs0g/rLZXj3e76XAXvvmNjyXHzYBf+cXf+KkPf1qLXm+uQhdyOqorgX7w8iPqebjqn/WPj7x7fX+Yk7KEVNTg7myGnFMpau6x5y5R0tnsKBy6Lq5XMQbPhjlhnvClX9jE9SpGPrx+dXv74nAs7z35BQ27BB6nw6P1B1/9vS9P5fDm9pM/+qN/45JWWy855VLgfHX1aNyPIfYpe4uyzJxqreYievtZD+GzPz8vQfhXEbT/2hmy/18dP653eHksmZoWl3hzyT/7MbloM9f+PK9SIqocRheOoLDerO93exBCFwnFRan3p+/3X/v6V/7BH3ztq7/9lXCzezt98unr14e0T8XNbNas4FTy/e4wJY8BquyGQhyur3MpquXx48ehiyQ8zunN7jZ0fRy6/W5fSDthiUyRNeUpzWMac7GUM7MUtZyzqCu5mqZiKedSkFLOuYTo86Tbq+3rt680IyXbH4+x741CF3uwl3lMOXdOTMQiMXZzKofjvNlcx65fDZsQuo9fvEhJ79/MVdFmsD6Nc5lMYuxCr4WzahI73o8x6vtf+GB7E4sd53Sc5lQUFDqwFWdIH3vzbCCwODwjgMUlQoKL8MOH6xDw6tXeMvoBq03s1jF0wiRd7I+HXUrmLhyCk93ev3wcHz774NmXfun5t7/5ukzmBBcm4hAii7qVhUN3rug7cyXenVO+fJB0CWNOCe1TA6IaX9VQlJpCOpYdpMVaxCzi5O52mlHLVrBExae6kGV6t5Bg0Y6CgwErZz3nM/T27tQ9ucS4XCbuxsDic15osJ57Rp1MWYt0a0qSuVEn6ofbngU0tP783Byonbtra6JavuTmRAz3WhXETSWw3s8STXvF0rR2j6tYW3swLDlphSe0mBtJBHWuOQH6S7/+7B/+069sn/ont9/5+PY7n9zeTiW8PU5jou+/3K16KKZuGLjrtFAMw2HcAaTBrYC9pGxzmc3R91E2ER60MLkEQSpTEBrWLsxhZe+9/2i/39VUVU5j1RTpJTsVjT0AACAASURBVD58cHV1telCSBMf92WeizG+4MhZSyluBhdm7joumVIqcBLhrudh6LquizGmKVUrpMm8YYqIHbpO3HVOc1YwcHXdbTar6webbog5p/EwumNYRTNjAYi22zis+jBISqkgURcfPLs5xBEzHw+jWgGh1p2YkbdcntPSG3n7cEsCDozgygUwFyjjOB+NnAJyziU7VNWRi45lwgwoIOiGLYfgVpK5MIZhcMb9bvf21W0ajWbA3BWhopClgrNGwhJI1UGIvUjHiuJGxTWl5KjCLA6AQ1VKdi2KGTAomUT2ANQSPKp0QiczBrEIE8NZrcC9NewyqyyGav+Z+IRaLzgKTsFOnbc/bBDqLOdahPQZRNuaksTF+q8Ho0HWtWWng7zibaY4xb9ncOcEjPuisb8EnFhcuDpSOZEoDY2Qs6TWIC5VF4JgBDC8LGJb9R68xpmthrANrwLuS0augm3mDol1eKd7codrqRHl2XaAyN9xdXwpMFq+sT1PcuITmd1bUUItTQQt4BjQx9gIuZcm7tw56SLMrOyKhQ4CAIKTDVz+bNbs5GVdYjLv4FPvFH6dv+SHpsL/y0e4vEYFsJhO6E3TZmoHU5NZPEGSREu/OyMitxO79vyFP9ZoTjjuXwXdNUTkXB1/2r3qUZ8jtwaXy9Jati6IV1KliEDAxqj1d1oagNW+ZEErL6/bUFu/fIXn3ZQqj5iAU1wHGBaoqCkRsxAqVOx1nARCBY6Il3lTFwq3ssETP64+6pNfWDfb+uk2qtPmuEzKIKGWvZxCTVxgwaAGxuFCZq8hNkzO4LZh1x26QeonCXZvGaQKyrT5rW6mKn0Ub2tbKmxIULXa96vlNwACU+Ca5dFSzC1SMFitEGYmrr2JAbjX3pfM1PrWtmgWlVlZJ08u+WS8qmb8OQMG1NdaC5+rQig7g2Cupgatls+cnIRF4QG+wN56MUXPFhPgJQtYbZp5VU44Bex2cuMJjSbWKCfEFE5OGc6vp04cNTBgnlNmIiPzWgitKOqAk3lx555zRtFZRCSwE1IqqtOQTYJM49tS9H53nCbNBi8w9loYpQWr1TrnYmYcGCzM5KTkSoGNkHIOIXelSE4gLoWEw3ZjDu453h7u8zgz89Y3wzBk06yFnUq2ta4LLLvOlpMXCnJ1DTEUhRVA3cyVjVxdzZquP8EqsYckUAgBqD1A3Z1hhEr69PjJJ6+316thvTJ3SCAv7lYRwBhDSrObMvGU8ss3r6+2VzBnDtm0FI+xqf6fWr0T+Xq13mzWwzDkrMfj4T72IfL7778/HsfXr191PfUJb2/v16uNMK9XgxV3cwUwI/Rxu73Kk+aUd3mf0txSdIw0WS7j9VV/c/Poze0uckdGYGe4SGDiZCkljEfsdscQAELfe98REEMIMc6qCMJZcRhzKffj4WXAfHM1PNzeDLFXEEssbqnknEqMIdRKWDN4tYH5cDgW1RBlsxlKR9NcUErx8fbu5ctXn663q2fPH3z8avvy/lW3podPt4X18OYuSggbK+YOVSIjd6vemdfsBTtFEic38wquVw3m06KoO+rizjcj3mCu9q/qsRMWRtVpz7ALpOtk/6txPcXFrcWVA5fYOioDbLHOfN6qW9dxLPxrR2VVn86Ce5kTC0kIzOS1D4YtNK+Tq0Tn1jMLKRxOpe/XENdiRLLq+Wq7feWCDFJ4hs2GBfCHu2ejwHB2FiKbdnkcRn5PhqEL0dLsQThICDH03TrG7d3t7ZuX8+0deM6/8fNf+vD9L2622/k4derECJ0Y5D7tvvXRdw8+Jyro/NkXnsRrevHyB/tjcYd7MRdmhBDcrVi22VdFzFH1ztQ9m3nWcc6lgAndqucuIrARPGIs+9vjy3g/XK3S0N0c9eNn3Ye//ps/++rV3y+e/uiPvjFlsGPYxHnM4+G+gCnPlZ9d8wcXu9IZpiL67B6Lcwz4k+Nv3dFC9Pr3z3t3p+Dmsn6AAGI+ObTVG05zspJUoaoyyGobpQ+vv/MSD/DV3/m1r//j3/mNr3757fHTQMc38/3tbrzd3RUuFN0lOiFrTmZmlEvRMrq6c5We8q7v+qE/jse3Jb96+7rr+/XV2swyEjNxZGef0jzNUyq5pvpyNhE2q25YKW5ZvWQrpqpUigPBTXJxt7DbHZiGnDEnLyANUiqwLZFNwQxnU/JQS5xj1682wyZQV2Z//fLONezuS48oBdNxxmxk7BBnshAcQkBOtruf97spDpDQd/0mF8oGlkhctHA2X3WdIdXEHMDMZtBUpi4zQYi9H2i9Jis+dLFbRQ6WtTDAPMyzqknJmOeSzYHJh2l1ZQ+fD88+9D//tyUQYt+TslrD8ImottRessY4r1RvPtISiS5adi02bK5j2x+Wk4jQqgVbzHCeWG5Gi69p1VC7X2zZZwDonQnYNKcXA714VWjAE3nljCzjWWbs2ZM/x9XnyMJqq1tqudvF87+AutoWU9tnLrcG+hz8fVkkC2FkeRTqjTbhzNTE3L0qc7g5oBAHaEnqwyovTAmV+WcgsgbYVeUsV44kLO4EoyBBOngYLU5gfOW3vvD8Z7e78ukn99+RtXz/G7dXj56w9MdxfPTk5sXHd0RlniwOPiftyXNSZqmCs3CSwKuNSBeYhlr8ayaqBLNhXQsVgwjAZbPl3T7l7CAl2GoNgqxXw9XNEKJN83gcD/OU5gmlIkQKK1A1IheJRFU4BW5VedlUS8ozGPOUzBKzg8EdTABD6KjrhBhdDxBiiA8fXvdDP83Tfr87juM8JZGwWg3EFLvoAJmFQfbH/YuPb1+/mR9c9Y8fPO+H4f71YYirMUw2ZhQHYJO3kk0BgkMAw5P3HpMwgied5jRlnSkwix+ncZzHoMGVQBQiw8lTUV32Nsf9/T50pApTkABB1Ow4zslMIunsZhQhDDYlqiR+qg1zqNGjBCSu0KJmZnNJrrZgMWDiWkYCQR2toy4sh5/aLlfZf4Nzc3JOvIK2fpqXU0khROReS98aUFUD3jNsUSkJF6u5/aqVal2urfoYLkEWuF0umgsYwcwZgLTQv2paVcLY2S7URdrEH3CBVZ/aHlzKSV8iye5emxqCxFsg4uT1vk5DdZz6l9Wvvegdet75FotYmxqdb7P92WqwT0aMlgi+PfOTbbwwlWjNRZs0h7XeR6dnfjZHDoeAjJwutLmXMLxdkZiZULmqJzrI5csyqwzTxV1/x5C9u7e/88tLYOTyC/E3eQQtxd7F1Wr7lNNlqxC7E5uBnGtBhoG4aSqRqWXXUowMCv9LLvRjHKe9of7znUdGBKqI9gW0CRBBJLTSOQCfqcW7/PJizl75ZZU7ZmZzmundPacGG/jMgjvBYRdb3QlaqpwsYVFo1dUCAIKazvNc0asT+qaudYaRSBekltBV1OXkHdQnzIua8qmytAVozJVmVUoxs0q/oiVTtExotBLRKuhu7uSmvsBwILiRQYmqmt671qWLldZ0mpdERBKCmrpqa9RXO3o6qFGNG9dhnHNdzMJQIq7WQwi1yo5DMVVrOlxFS9bibuRgJvVa41kgVPsFwB0kTCFIAMjITIvric1aVZYAGBW7dK7JQQKCW1EHUMB8sjl+aaEBSvPMRCAXIZALS+vNvPSvdD+v2JN5OjGvANSF1FJiqEpndEobEnOrGq/KYVwROSqmqNbnFL3X4VWcrvY3UcQukCNnda/9YkGAOM8JYCdPZk7CpWSzUpQcXudGMbgzOwzuSmpk5makQZyrdHUpsBg4BAns/WogwpSOTtT1nYQIzYRoQCp5zpkCPnr9UlMKErLrDTsTK9k056wlHKKsu4AhkRf4OJev/ML/w96bNVuSJOdhn7tHZObZ7lJLV3VXT09Pz4ZFmAXAiIQoAAQk0WgQn/Qgk0lP+gF6lclk+g161hPN8MpfQONmNMpIkEMjaSAH+2Bmeq297nKWzIwId9dDZJ57q6axA+ILwqxu97n3nJNbhIf7559//hOPnz57dbntU4a5CJOpWnEHRwRn5uiKPGbLJZtzDXgyHMhF6/YjEiTQ1cviGMCx1q4ysREMXsxdtQkRTua8OyT3fPfusF4vmvXae3YSkrBabUqBOTntASYJpyfnbz28H5v4gx/8YOzHw2G/Xi9F5O23H4gQEXLqf/hpevhg27Wr5aoDKEYBFAGxa87OzoTjs2ev+kOPksHOgZioJPMDBs7lzIQ7EREGhJm9bVuRQBrTeE3saTRVlwDhzBSitMvVchyNOFnh4jbkfLjGkyejBHTxo7cfPFp2a2rae3fvXO23HliTKplSsaJqKsZ1SZerVyJN26xWq5UpvXp5WVD2w/V+uNr317/1+//xS1/9+jd+9ieu0tXTV6++9LVH9w93lh89+eTpE2R0G9JUSXYZFLQ26BWCE9iVFEQ2C25TZa4SfOo6R17zZDphywAmsSyqvGuzY6X2nAA4mtzb2YvPGzS3T8C0apjIp66CqPLB5jXkcvGKXh0jEp96Fwvz0YbDHZ5BkwCgVDtsRm4Vn54AeJ/VueYTmYysBMklpTGLo4vN4WJvA2EPL0ABMsgnq+Og2nvbzErOpnrxYk9U0qOyXkToSOy5aFFzNKtVB2sff3r90Y+eNd5cvUy/8r/+N+9/8QNTh6nBnr54fHp3c7Dhdz/+/r/5T//uOu/2saSVn98/ef/ueydn3WefPXnxYp+KC/vJZhXjgpgcxV1zTnUv0aIlDf1OiSGE03W4c940i1VWKzkhSLfZkDXXw8X1p4c7m4t3Hry3LS96vTjZvP33/odf/IVf+s7f/3/+wb/9je998v3Lvs/LTcgHbQjQ4My5KJzADFhViHGmGhNO945u7bCTna/m7494+G9Ohc9zEv56/BWMG9zgZmG+CTZ+7oqd0Wczs7rkQ4hdtzLzruukHEoeLi+uMeC/+h9/8ms/8YW/+/f+9ld+8l2n/W9//Ie4HgZs94PmwqOTF/XgY85jKnB2dtWS1bQUipKvx9V6fb45V8Lj50+vt9tnr56uz9ab09X19qq1SOQkNuSUhuEwDG4aQ9MtuquryxgaGFQBWC6l5GLGABkpXECSla138PDywoCDK8zREYy4jBoih9gu2+iUa++OYgaX9WJ9tjrv2uW4S5dPX3zyESKViZ960MOFd4Tgpj5kGqhD00JCw9fJdwOkvLU9OTnrmBcUnB3sxA0qfdvhWc1KJsmOEgxuGFE6KaZjGjNR2CwjUbtYLJeb1pGvt7syjotuudv2XdOlhP02mXnbBKe+WfXvvLf45s+9//1//8MiaCORoBTLo5KoRAkMtUqZmlbq9MwrAjVhTlItPs+gFc2SNJgjLJpAmvq7uj9YzedNbk+t15sUqQREMFBgn5ggwOS8+Rvzj44e2vzbI9MBADlN0A9q49M/lcWo+dZjnFfPsAoSzblraMXIapx+a7wZz025bZ++VyYZqwn2mj4CZwOM3WrJS3UwWYSZiMnY3VgBg8G56r0TdM4hwQEO3jYtgJyKMDeRFcOBdo++GN/96ua//rvfRHf58cvLbbq+//C9fcJZs3D37eHlgwePtoerJpS+LyFynxJztAQSjosWjCEZnFeLdRNRMooWeAA8lzL0w507ixBC2wUiM+ewhEveXe9LVmdbncli0Z6tV01EGnYXl7vD/mAGFvZipg2QmFGzi1UKIEQRoVRKLhhHEPqShzzKOBY4t13YnAY3iqG1Ym1s2qZx02UbiDm2XdO045Aurq7SMGhxIQE0pRxDCBIcBvbv/+Czt+6fntxbhUUomZ5dPhHrHrz3VqTWRtpdbi1ZkNBEYvYQGtTe2DW7L1JQUhqSmnqusY+qe3aFUiE3axAWbUsk6tnYKFKVXBhy0uKlaPVIkhbNPqQRgAgrlIwAdicGOZM7OTOYnRURYEgbOAYKzApiWUHGlHJKKI4CYyNmIemCWOfgqYZOWGqBmtVWlw64uNZiHGeXWrPi7kc/anKZQCRMBKg5g4ikypy+GaG/Nv/pNXgLszD6tBped6eO64OnV0cRd4W7Kyk5e+1ZfaugmIgY7OzHnn3EU8GdH+VT53C4ItHE7FNADjV3VQhuL/D5/OBvHKp+iYMx58Jnb4Un+hWRg520usqY5ACPX2KT3bAjks4I9fZVX1rhoYqNOAA3THCVmdMUsR9P53gbpwoeAt1m2NxG2+lGb5mZyY8YH+NoCdWUQC5zxWH9frv5ptvmdrKI9Xb8kWj9X/kIeuwUegSwJunxSs6jOf6egX7cvC3GSECtsAMgr0+sP8c4QlfHO/0mqlcJeKrz9J6xAZAIVwyFpvYjn5MhnI5irrgRbIJDeNJHn8gppnjtsU17GOb1MGv11KULdyOSiv663IB/zGyAVyzGptlab51j4jrd6CbZ1Hd8EkKudCFoBdowp5JmlNThfkPtq2dibjCa6+yqjNcR954vpu69E1JflemrIdFJ5NgAVCSSmSdR4+kf3UiN801RIhGBq0TUBCCaKXSqHtTKcTR3gVBlfPFko9ydXKGupWgyUzjMlEjNXJ0n+0GY00vzKp1pbXDHLbWymT9WcwM1MVrzRhMDbjKaXpEmEMFqVwl3KOAwduJZWRgOdSo2qd+DbkxH1Wgg0KyleTTN7rVz28Snw5SL5CO8OMFlPhHWjuZjcn8mpwhENHWicXgBFC5wtpxrsTYIZA4dTVgc3vc5pdwumxglxgYgU81jUQNYYohVYtkcrlAiER/6HtVJIjgstIs2Sts0y65zN7cyYbIS2rZdNssYmuVi1bZNELm6ujLVJgSJwlG62BhcYcVKn8bYtaJ50LQ9HC6urr/2lZ8cs/VDTlaapoFwNTv1GTGxK+loysUK1FVJa7riBqUgqneqXTAzl1KSwaywxChgIS2akgYpkYVik9UOfb/rx5PTs6ZduLupOnHTLhZrP4ylKQpI00gIEmOzWi4369PVQk2VwE+ePOma9uT01My3V/uT9cvd1t16wJomLBdNySN5kAbjmIhotVo3sR2GXvNIpEwE0aI6HOzl04vlJgaOQQjsDiVwkGa1bsAO5Ngwi4pMSm2xkYVLWmlOts+jxCWHRqKBoYbrHa73h7PNKM1idX7+6umzLnaxa6mJGZ7HIecUYzR2YYlEUIDapiGRxn059O6eVDXpeHn1Yv3y9M79+1/9+vv9b/fbtF+d3wkLKWH38tludzklugTEseYrAKdJInAuW3AF5l0ZBAaZzETOKhZikMq+Miee0nRHazQZFRwtzJvo1R+TwHEH8ZwUIDjBj3oDTGCmwAh20/wGsxm5dQifCjOqkZpMWDG3Usy9pj2ZhWTqqz2FC2xgghCEEGwcR2ZnsGUz9ccfPjtc7CsDiwoBJAgySTFUiXPzqsMI02vsmrG/zn7ejiVpsVxGVS9ZTjecMw97GhSb2ADpp3/yG/fv3M3jKKUsumDkwpxHfbW/uhy2l2l3SHlMOdnh4dt333333fV61bWPnzy+GnMah33OI0uo5ZFWFJVmRiCWyE2MfHbW3r+3OTvt+kNKY98KVgEkEohz0f3hZZ8OWfff/OrPjfl6r3QS+fyt5S//nZ9/9O6j3/in/+kf/aN/3wqWJ+vDdYqRDZSLTTk8AmBOVaGMZpyqxmA2a2nYHNXhj37sb46j9/zXGNZf1vi8RXeTwgIwJ9l/zHP9PPfvmEo86kKUUlLOHKgRFrG9DtgAj/Ar/+23Pvj6O2cPcLH/0SFfnN6Vl7t+3+/UFUJaLKVcchnzkFRBgeEVNgAzAhHTYrns1oukeXv5anfYjTlBsN1eX11fgo2FXD1r7oc+p0zMkZhIht41lhiCSFQ1LVkLsQTm4A5HEIlu1I/ZfLy4gDAkUIgg7sYylFyaIuvNYtl1qpLLmFMeh7Fp2vVqzRyHoRwu+/1F3ykM4Bi1sFlkz0Sc1cZh0lJZLlqJ7WEY+wyKe0SmKNKKenA3B0kQBxHbq8vrod+75di4BCAiAIwAC6akpTCDIMwSQoxRSklmSa2Yay65DYuSMKgK3JtYypD5cnPefPErb6H7IRRZxxgWxGxm1ZGsza3JGTfqKTaVg7sbUS07AvFUAVSDG5/4p0dqxjFQvGEe4NaP6iYRcW1mXzOjTMzwG+XzmsqtM/H1Meuwz3+i+XvfmNhTuvomMnsj0JhO0idfbD6O2ZHYcPzCOTyf9y+fcTqb6iO5Fq9MkS5Vm1dJyDe4lU1SrDMIpkYwt0IEskoNIa4+JbvPksxgmbqmTDfQYBYXHQvlpNmLiBQqyYbVCd7+8upXf+3n13f5wxfPLodXGXj69PKtB+c5Y384wPHi+cWq4SgNXEq2MmppRAsik3A0dy0DIERiKZUhlQJCMON8GPb7cu/eWqFa4MhOqcbBKQ9mJA02Z7JexZO1WCn9sD0M+6LoumUMy4Lc92pEzFEELLWCklQhISDnyvsrWohAnIshcmwaYW7Jw2qx1uKLtg0sfd/nYQwxkshuv9vt9uNYJMTFoiNHSmm/74NI17UhMFzv3ttIlP1uvLjYa0EILDQ8v3jRSWcjDhcHJt6s18YCcRMl8lFzHvJY8tmd86vt5XZ3nUoCmVPR7EmdQV3sYJ6SuvmYcqBCQKTQxMhMY87LdlW8uI+mhSnkbEzSLRbjNqVekeHuaoWtzlJ1tqo+YQSQc+DYxdg1zqZe2JljW8v5MoqrQiFgCbEJ0QFTV1NTY5JaJHgjVD1Xsphh0oUy97lypE7qY5xNFVl2O/ISb+O0x5Uw4dS3MKwJP3sD0K1p0Xmt+i30Cje/vul3UHlPVajL6aY4bF7z08tJLgpkldToM+hD8xdPMNZ0rmYzcOVWW7DVWOPGDtBsIiZK0uRATgd2e3PLJCLwbQzCp7LmY6g6ucHssy893TYnB4WpfswnxXzHxJdD7aVYTe98OUTAsVcdTxabrdaBYs4c2K0KBqthaV1lM0PF6w5zK4zFbJdnc3/L6N2MP4oq9P/PCMe67vls5lOZHJZZaoqmbOn8wUk+ieZMi91QjP4SLuYWPPQGCW3ekPz46ubtf7qvrmfvalqpmEQUQqicKataldMlzlsq38hz3/4WqlSAukPXpTX3MVGrpBcWEVXVUiZMZT46GMcOice9s56J1QaOVlkASqRN0/iN4p3XcKvqnlJFoNzMaGpOTwSgdjlk5pzz1EtrWqFWzcBEWKoNGsRdrXhVN6uoS1WWsxvwymEwMofCYVPJfb1PFQo8Kmwxgah4JqqdTGsPRzjVdoIA5mjTWcnJrWiu6BWAoipE5mauRAFMmJu7wJzUAHhtKqsTt7KikO6VYnQzhbiu0UouU4NDAjGTuatqpS3x1BFpZmn4bKEM5uoEUpAaEVdOXS1WtKNRw5wHrKyCivAe/+THrvA3TlS9Y5NOn4EYJIwJpZ8hLqD2hK7QUj01M3O3Cq4FZnI2oBSXrgF7HpOOBi5BgilrNjXPmUpBtZFciSrqfuQvqlfbF6MsVt3qZNU1EtmbwO5om9DEuF6uosQqeKemVQyOhLfDITAZFPvronnRLRoJJGyCQcfQRR+wPeybq6vw9Pl7X/zSh59+9vTZqyaOTdNyoFwKCG2IIYiq5tEsuwQmgkhkEbjnnG2Ga6n2FGVIVHPv+1GhxFiuV23biPBB9ylZ76UI4GUc7XKPy+3+rfvUdW0xHg47p0BEWX0sRc2bJobYjKm8fHGpam60XK6s6H7fX15d3btzp23be/fuLdpFE7//B3/wNCfN4xhCXC5bt0AecxqffPIZkcRmuV6thHhXtGR1RmgiLzjnsr9MEiBBYoxmRU2TjabE0jSxdXDtGC2BqmSBw0Q4RpFw7IFCcRnO7sTLbe5W8fJ6v2gvN93iYrvtsxJbs1x6DMV1tJw1u1B0dcOiEZibJ/PUhnB6ulgupWh+8fJFX3qO9MnjDwcf7z+48/Dy3odPPyRrTu90X5X3zs+vfus/fqpAGlDMBcbC5pM+1TQFfe4NPmOulTfHABMb1GbFuwkzmomIU+66Xm7NLNJEWfSJJv4noFeOGRMhQoWS5+jhuHzBRCFQUCN1NtQe5PC56H/CUMirHAIJvDb0cqp9WQ0OkomYS0TE5EQ1r+YRFkBCJEwiptbGtusEgobi4x885UQNh6qVikJkxE6qZlz1lh0gZnDkrLbfY9yVPGrfjxZKzrnUdoCZXu53wwFsC6L48NH60TvvrrtFvrwYh0PguD7prnX7o2cf//6Hf/jqsD1Q7i0Vz/lydMqG3DTh3XffPj+90/faH3KfhmE89ON2TLABIoiRlovV+vTkZLNqWm476loyHX/0oyddS2/dO9VAlsZFs4jSKOVtf3A6vOjvB1qS9oexz337jW9/+Zs/+a1Hd9+V4P/h3/7O5Xa3XK9zzn1fMHEd5nngxojzzlkTZKj8WeCY/uKj6/a5T//2eBOLPIKhfz3+cgfVZzXHMdPvXhMyA+ZN8c3hVkvd6iaiWkoOsQ1tSGXY++7+w+6nv/2lr/0XD3/11751yJeJn2vuiw/Pr570pc/W7/vd7rDty+BiJtBJSVScahaKY6S2C92iXZ8upZF+OFxuL4ehH8Zht78uXlLarjfrRppUdMhpzNmByGJOQypmUPUmhhhbeDZ1MwoxxtCUos5NCO0wlGFM6nl7QBOxZGmlbdrVxW4/ahozhSa0iwhmc/SpWDbmMI7l8mI7HNJ4MfbbdGfZDUagNiukDYlfmbPDOXrowubeen3axo4Og45l7BNd77XbameSjWqXHGJQMON89XKXcmbGGtyE2DDFwK00rtGys7dCklX7PsEOTdcBObJLJ+vVcncxukKzs5Kal2iJ+4Ffxfbszr3VF38C14/54mUK3mLqwV1NefXxjxALvEabc/Q65QGqPKjXmhubCa5TvuHoNhLAkyrOrUKd2ymNahB44lU5jq6VT07qG+HwdBI4SuJMvBHcoDuvwVe35u5N+HP7K+cUy4S73cBUx3TjzT411SlNUfcxsK071fQNfnOnqvWvqozT+UydLupeA3adfMwps2IOsiNITljx/wAAIABJREFUzwAx1+TDjNlNt8fNpOGSc7YMUnUlRliXr33j7k//7Ns/9XPvffLiB588/ehquDhk+/gPP3r0pS8/fXYYhn65WDx7djg7PematpHGTXOyPBZLQGQYw8DUaPGUNA/ZUiHEIOLMRWIrRSiYjjnnYgMxDE5MoREiSNA79xeLRWhjKanEIYcWRKFtlm08Afurl5/FzruuadqASevDiKhpghZvWxUGETURIZK7CqNtuYkhhq5ruqFPk9yKWi5J4eM+73aHXEojnUg0J1cfhnK4TCHCT3yxbIksOI05j6VU9e9CBvJRh5zGtB+H3loJoQViw0RF1RxpzEOfDv2wWHe73fZydx2Fl8sOHHIugDVt2zVt6tMwDpZQioIRGE2IsmSD77f7sFiaVFY6C8fQtE1suaH+eswpORkHoUKmSjBQrSuoDx5ArWQkJy+ljDlREZmcMREhdXJVU5B7gXmGJbOs6hYswOHFFU5EbEzEPvM5MHG7fRZRmgnRt0Aiu0k4zZypI5JzhKve3I6P4umvpabqnnB78dLsxk2/8WOgPQdaRMwBZLUI7AhgTXHxbVrlBO3QzNiYoBqaI1AwzQ6tz6xSm+Gc6mTy0Yz40fb4lI5jv3Vr5mPPSHyViZmRaQeo9h4Fw2utpM8hJ/ktM1mPTj5fG7wK008JAXWAWVBlvKrufCWroGaYbzqGMc/2sRJPqNK47HWFpTfh+zd9p5lVegQobh7V7Tf+5/O4gs/KXrh57tN1H6ViJkYQ5Eibrddj6nNnP9eqleZvKPD++ccbGNYbKO/xKEQ8y8jVKnSfthzcQiVuD5ku8taV3iy24y2guSClHrECWBVXqvSdCez0SW7t+IArAjopcItUq2pm5M5C7lOrQSGuf8JcpEk0KV6xCIEKFcytA44gl7n7RCOaCsRoNhCTWrgD8+nVD6WU6l0SJmK2Iw4yI4B1hk5FzVQlKqa4w8yJq9vBMPhcCz1dslqp0SwAgMN0/rXeuYy5bt31nIoZiFigbtVgGBzMRGxqIAITpDK/nFlMiwNMPglbOrxYJfoBsKrWPKPEx//CoaVUUR2r/KxbEQ5TFVeCljJFwDRh8SAmN5Gj1TDUqugCFrCC5UgYrVzMaXpUQit8EpLEPDNZ+DgHJxBiDvNR+15P0xe44dj7bHTnV7eX0gyRwysdJkCrqDab1dpuAZkbp+Q+jFkLCZuRFldSOAdhuKtZKQYATIHFYCHQYrU4OdlsTlYi7ppcCzOvV5uu7RoJJVs/DFe7XSl6sjl7cP/h2dmZRGm6RohLLle7q5TH1Wq9jMsgAYy4bLDnbOXq+tpD861vfTvEqMVTSsTShkiAMMcmBqFSUkk5J4V5DNK2jchkl2rbYz/eL7OUC4PArnAR5FKCBWLW7DkhQEsxMyTXPOB6t+tT6hbtkNLF9Q4ShWV/GLa7fkxD264khL4fd7t+HMenT1+cnW1O1ptxSNfbq5P1CUB3790/Pz1nwn63u7ra55xEpGlibslUhoNuL64h6BYaYwwxNLHxorkkrugGkxc/bFNoQrdomaVoGkvOBcTK4ubJxxQbAOJwMxdJTG3ThuWyVaXLXToMQ1wvlqv15fXF/YcPdv3w7OXFPu4vLq4ePXiUHcZi1bsW5iZKGyBkpkUznFL2Q09uRViIqWlD2zXLZXcYh6GMT54/+eJm+c4XHp78YPX84qUz33/r/Oz8jHT18vn22ZNX++2oMJ+YlFPbz0oBtTmNNwFQk5fP1S1xn8prCXPuDkQg46kH6rT1YHZDpp3l2EDwNWwCry0FTGoh01+htex9IkrWdcYkTOJMALHNa3BiszqEjwoCjLra4cY+sQgkkrnWLhE1M1iV6yet3CnVRxN/290oclxt1ptu/fh3n5IRG5MRjKjUshsjd3bUytmJlCkSITnnfLCcdBhStxYiGQaNoZTijz99fjjkvtd3H9z7xZ/7+bPFeUDJ7ikPxGEVFp8NV49fPfnk+ae9lxJoTNmhBnv58tVud3my2Zyenq5Wy/U6MjckNIz7l6+eXrx8KboUltg2i+VyuVqtNgvAS9kP/cH18OLF4XSDzXJZ2MbD9uyENutIDRPA0T978YNWNpv23rqNzaLx0C/WJ3/jb30zNvLWg3u//vf/8eLMUICSwQLQNA9qgoF46hh0JJ7WR1Y39TmzArI/pR9x9A1uOwl/Pf4i4/OA43k3uo1e+U0MP3/y8+//a3WixABCy6HFMO7efXf1N3/xZ/7Wr/zMF796lxeH7e7TPO6Ms7N++OR7Tbcwpuvd5dXhysllEcmFmJkESmZe1BhBRLp1t1i0HCVrzjqOadztd4dDX2ysqSfVZIaimlNKCiaII5eSkkqorkETQiy5pIScnRlByGqfNwpmqkooPuQKsgfiVkLr4JRhyUPTS8ttRC5WijWBCXx5cQXsUeBby/txtT6jTI4G2dpmeY29qppRs2hXZ8vN2WlovB/3Q1I1jBlXV0NsmzNauLDVBJKbmpnq4ZBLRtdBeNE2XdcGCa7FhsM4DkMX27hoPI9DPwBY9gixkFiAhMBd25VeM1wC5VEPZK1ow4U4hth957/8yd/99y+3V89yTnARESeY6yRR41XAaWJUVdLAZKpnOMrc2abS7RoJ33jiNGUcJ/2aCeuq8ePMbpp0c27hTcBRe4tm0tPnTtRJFPpIY39zfh63GfxYEPY5wPfEJDmae7/xfye/+fjFzAQSxxwEkR8T+pPbePvLq59dCVo0heYsdAxF4ZYTAxwmyoeb1xqBuuYcAISJDPONmJ4BJISkKZcEBgV4Lsv16TtfPvnOL33wUz/70OP+s4/+MNkh6XgYfEgYBtVCADEhRqyXqyCNCFvp82g5FsuAumZjCm27SCj73T71oxh1XRPjAiSBuxi7xXKVS6Oek5JTCSFKkKZtQkS3orN7yxDMy+go3dKXGww7NvNcnIQvt+PqREQ8RtLipeS5p62zcNNAhOBoGu+6wAL20ERhNMvlyhINQ78btwQ+7HuYSmNjHpMWZgFRztm0wDD0GSMQQERuPpSxYQGDBGHtEdI0C1IuY6FMsYviGlwc5TAmy8WMVD3lPCZHwvXhOmuOwjHEKgbiBoIHDlCUUW0AtFacwQrUnZ0DkbjkMUvXMkd1AjiE6ERDSt1i0Vi72+1YhRjGhSaPhDnAA5xtcbJwNoenNKacxjyyRtZpLtWEHEFMzXMyq3sxyIgpqELVTJUmOcJarcuo2uFqajMP4MZkTwnICeLyIyh1A+y+afF9MvrzCp3CILpZwjfL8Q3SDPmbi5pIavgLEJMEEaeJP3QMjY/juJAdXrlas/MBAOZWi6kqIDY3pHZiMIMmpQebyuLox43EjSHBvJfVSpyj+hWma+R50/SbSwMcUIAn4+iVS3ZUyq5VD0YO96rOc1uqq17EkUmjZYbbbj4MmdOB89lMezTdnAJoJtNUy2STXTvejfl9APRGZmt6qrOpuRW2/ud0ugLm20xzN4E5JpnL0+xotavc3PF5uKqFUN9GqPsb+ec4P3/2QTcW+RZ0dXtuu9dGoGCaNA3NAgGAgMrt8nh/fRbermolBBYHSi7CPKGXx+urmWOaquVEeEypFpo5O93q4nkcPPd9dzeCVJmq6duEUMk/c6NQDiIik3p80RClMrbc3YUFcmRM3yDcczeVCjpOqOGMyk9NGOtcNpsenxqEhCd9YnUH3HS+M9NGTsRgMNiZUEkUxKRaBBAWAhtVJbQJJIbB3TSb6uQpRA5TiHijojeDW27mJuBZpt5KVSivD0FYhBDcgiHXW0NT01MWQtUyn9TRS73nxxQf3gT1VUst0Z60uNwCBSaYgQNE2Kda5anxsQhPj8VZWKYpD65caJ4qWm7J1pM7YBM2V+/eBBvenldExETmelzgk/Ig33oPMwmRUNFSwTpMbSYcTlPHykk5xgGQcZ11TEzOZmZFwU1JBYwQRJoIspLV1HLR0HIbY5X0tmJFnYjU3FThTMImbqUYhcDctjEIAZ5zGYd9CGG9XocYaiHoOKTHj59st7v7dx4u2tV6vb5753SxbMix3+6G/WCuTBYCx9gYfG3LyxgD8TgMu6vr5WJZcul3/bhHzn0IZKqCUB3hnMowDGMPApomeuNatBQrWeuNcoeV2sJSqfEQhFnI1IoO++yGELkfUs5oGxbnog5yFIwp1Y7Kueju0J+cnLpjTHkYsrrHtmmadrvf933vRr///YuHd4f3vxSXq+X+8WMz3SzPLeXR7Z133n7x/NmQ/qBoMg+GAihAITIEYIz9kNe57drlakXkeTumcQRXlg3KATinIIE5qGTNo6m6Q4AxDbnYcoWmad1NDW4c2iDLyE5N015ePdsf9qtFS4GRcf/BvVdPn+z7w2G/K8PwwQdfISMXKkAjEtoYPLRNDEI5pe1uGyRqiEX1cNizMDMvN+vzt86lk9/8re81ywU3PKTtg7fvvPfeg4vt8xeXL07OuvVm852/+Y3f+90f7sbL3QBkOBmLVMAmkBCRqyHAirqbkxBDpjrCm/TBBFzwjCBPE3/yt73WjFUeajXmRDlr/QqnOUz58bCCcEw9OzBTuRxSjzA3SA8+2cbZiZrQKVRmNvkEejsBpcDhzhaYmKVlKWw5DzPDy5ggAndzUvMan4GMGVZy0aQIfrY8vXPnDhyWbRySODEkIjIziGO3BOvoqciolcetuV0scs4pezEelRZxLRydroKsFs2qv37VUsCYvvjgwX/3K7+8Rsh+IDJhOt/cvUxXV7vddb/fHfaj5l0aLg775Vq4aAgwK2kcXr683KxP79y98+UPvvr2o3eY7dnzJ5999ukyLrWgqA0pp5R3u20uo2tSHVfrZtFRDO2hHxdLsShFgjcBGgJjfX72e3/4/Q/e+8r987djMC/D41d/uJbdW5sPfuEXv/X1n/rKr//f//giH7CANKxjhsz7k9U66EkMaw7LeAI2p43tqIFFXruXHV1DmtzDqTSJKkWrhtTVyDL+ksYbXutf5OWf68jz3fgLvfxjxmtvvn2ncXTBZw/Iycj5SIeb5Ukwew+vHcgArvTMqTxjLugimpoUk3OQEHksaRgVI97/+r1f/jvf/umffe/i8OnTy48WdzgfhhcvHicr5w9O931/vb0efWg6aVZLiKRSAPHaqdZKKhqFAyG0QsGSDk5GAkc59LtdX0iwWZC7p6KUzAA1lKkbrxhIi7Zx5VaYgkh0H1LCMIJEWXxMOTZNBJvXiE9MUWoOjgBmia2N/ZAQ9iU2ByyaUiwQVsvTwOHF0+em+XS1NuMx9R21AqPYlpxCkLt3z4fdYci7sJBuFTkgax5Kb2QxBDiNY86F1QIomVPSolaKFU2UE1ThxsKNSBskEuyw211d9odDvn9H2siaiCFUc4ouUFbN49Av2+bieps9NNyOY2am9ZqHMjr2rt0HX3/02Y92xYE0ELeRZCKkw6JwrlSg23Ei+Faqu4oHz7nWmVxQZ8q06LnmK6vs1VxYXSGq6t0R3MDsXjGxepya5sSRpn6T83h9YsNvgoQbjtT8ZyKvQQOMnZx9Jv7/0WGY3TIsU6RYMSSaj1TrHImInAlqOicfDWAnshovTmWic2gMZnKd9CBq+CWY5RK5FCchgTC4SsJWiVwQVeovEQF8bPFL5CRgCCikwx7ucbVQKz5Y37588KX3v/bNtz/46bd/5w9+s1e98/bD8Vl7Obx68Oj08dNn4Hboy8vrBCCERkhAZqa1ilAVVsyKxqZr4oJK9rT3jK49Pdvca7oVUVCnbCZBso7F02HcDflauGVypz5IXLbNerkwT0MezVw4tk3MwVKfSjlICCXDVZg65gDKRXUcxqIQhim7M4HVlVliG0BuihARhdfrxe4677b9q5d7MqhivZDNInTCRaHqKRVV72IHIhG21tplu1iuvJTDNknsDKbmgZvQxBgaHW1IB7G4aLvQNciWUi5Fi6acoXk2nBEXLy4oSIiNuw/9OM1GRc4pqfe7AQlNG2tdj2Y4vOWmW3S5OMc2dl328XrYW1YfS8756uXF+eb+Yt3uZJfSCAUIJCAhiFvVTWOc3DtLeTTXoppzgaGRKNKWUkpJVnQyzKWS5A1GQhxijE1Imr0Ypr5ePCO9cBA7zPWmgd0xUmEGUWCa+o65zxDzDcDrt35zRHiPGJajqshPe8cxBUK3jzPjvXU/mtYe+VSJ53OkV9lJtWr5uK7nMZ3MLb3pGeKZTRDXU7nhX1a/QphYiJh9FlD3Oe764/EMIgKzm9GM77j7TWGa10LG2nC7SlJUi0FUG1paDfbcfarchENzoRAmsbS6d2LuLEhgFiLciM+Y2yR4xICb87FQq95yqpDObFqrrhALE1cm3aRdbeYi/Np1Ac7IWuYwvv7h9v853Gfk7k8efxUpxirMNmNxR7rI5x1m1ty/mRo/9rY/g/MWY6zFiccaxltJ+M8/geNomiaIcBA4itaypspgCoDnlCtVh2iqoq9rpXpjzKxuE7mJKEoAwUy1TFyi0IYoAiJTc7Mq1lMhiSDBbvbZ6SRphqMr+lF3GQDM1DRN0zRVan273aaU4YhNCG3UrCmnujnWSkxzd3UQgohMiuxglhDC1YtrhJu7y0IxRmYehtHdF4uOiNKYSpkC/tceiIGFjtCYYSIRghFj4ChuWuu5wODIHIgC124XJY/MUnE9h7sqIQaO7jArxVRNp+iVSYLUcLGGFGUSSqgtHYwwA3cCCUSh4SBVw1zHMl7ukaiNnbj028P5+nQcU0opWwYz4AJmJ88Kpq5p1a2kDABMMM9qUBABAR6rMgamLtANTw1iyY0caqnSt3xW0WOKIcQYQwiHw+HWJDR3aCge4ARqsFw1HpCtqBuOaf9qDEBkk/TPdKuqdB9N3dBwBIePH8OEQhp54Ka4gUiCSAhEpKrFEtghTAISI564eyRwYsYkRUECQ5keOhOLEZMw20R4uKUfCAAwY3ioFg+5tJs2NAxPTUvrdRvatlst7t65E4RzSo/efmfY9x/+4Icff/yZjSgpNK2//+7XvvEzX+vCwKxNiDA/HIZHb38hiMTYhRBXy+XLFxeqNoz5sh9+9PjT/+l//l9++3d+61/+s+/+i3/93W4NI3RdaNpWTffDoBmBg3iEQ1XHfYKhXXUsYjes13rrjFurhZ8kEIEzVE0dJ+eL0PDhcFDzthUhbwLSEH7lV3+enb//g9+5c+fOi+cvNpsTGH326eNhGA89VqsoTZfSeLJZf/Lpq82a752fn56sF114+uzjtx++dX5+sjlZXLx48f77Xx6G4bBPT5+8atv1b/zGf+zisr/Ey1eH0AihaWK3OTk1yVfbV14shFj6lMYkrZycrK53148ePjx/uJRWiEvS8urp/tNnrx598ZQELJKGbF7aLgTGerW6c3oy9P2PfvSxxfsEPjlZkCf48FNf/yAfdhcvng2HcXe9//bPfPPb3/j2vfO7u5eX1xcX73/h4elJl9P+xdNnprZenAZpu8Vis9nENr66fP7s2WcxxvVmHZtW3VIph7Efc3l28fIXf+mXv/e7v/0v/t/f+OjjDx++82hxcn7v3jvu4Uc/+Oz3vvejD394iR5t0wEyHsZGWsDtkFU4LBdWVIchhKZtWk1ZKOR+TGNmdTjBNIBjmMDQmqJ3IlNVL4CDvZKrDQgxzjH03L/T3YvVbSeEAHfNVeJhzpiRWy1PDsFKAYE7CW0DePKEioALVaMKJytqZlWsEpiNat3uvRaMQyIbkUG1nkwDbiXEBmQklj0bozlt4yYmTTklYlovVmfrM6g//fhp+rSEkVnJ1IlCjF3bdSmnRAnihbMHjYsQFrS+3/a2/fJXv9qcymD71elyv708XOY1y73N+qtvffDdf/Evv/MTv/Rrv/rL3/zytwLh5fPnDHrw1v2CcTdu//V/+jf/6jd/44fPP9yW64FzidGEx5yEsYgSmLo2whTIp6fnDx8+PL97x2DjePjX3/0P3QLuuPfWI5B8+PFHzFgt113XMNTKAFjb0mLjq01cNAvPDqPTbn335Ez7RMXXzeLh3Ydv3b3fxSXGle7WZycPT+L9H3387J//s3/3D379H/7eH3xartGdnO6ueyS0yzUBub8AXAGWKBzh0YppUbCQcMVR3I2swDIDOrG+HQwrOvt/b6irfu54Dc9ytR9/x+dQjWqSc/ZjaI5f/9wv/9T+Gs8//5KOzJ9zvZ8/fgwHE5l8W1Sf39mq8v58MX7rc7cSvlDH+s6mP4w6OtAwRRhJTYZJ8TKGNYOUAkvX33uE//3/+N+++lOP2jP97NXve3tYnYVPn3/8yWefvLp8lcYCkgLvSwoxAnxxsRtHX63WZ+d3m65NOT1/9vLlqy0zNif46tfuL5ddlG57fXj2/Pl2l8BoWyyXqxiaMUN4cXXZb3cXRDQOEDR3z+8GCc9ePF+vwr17Z90i9vv99np3OAy7g17vcX5n/YV33w0xXl/vP/n42eX1DgQJjRnlbGnMfYF1yAVdIydn8cGD+1cXz/e7Yd2u7927c/H88umT67YJZHK40rG3ohaCZFXNgAEBb905efTo7bv375iXTz795NnF48I4PVuEEEpRiDv367PmrXdOY1uMcoh82A+HXXr+IUWmIHZ6tn707v2u6fb7/fNnl69eXgujXWC9aUV8c7ah1lK/JZTVsm0C53HkAlNeLlYS4vXV9fV1CgEffPHBW3fPWjnL22a8XPzbf/rZP/kn36OXCN0ZMqLYcin73a64m9/ErpjCktemMQGkxpPkhalNaqUh0u1PTXPJHYCwIDLVBB0BNeybHW8i0lzenLa34oXjz7lSHRU7o6mdUc1OE8DQ6kaZo8ABhlSahk5UFHKoTjsPCyE4CbMQg921OtD4sToT92Agca6uH5sDqM2KMedbjzHucaVxdRdrNqcmV6YIV6znwFUF1ZicZOKpOYggxIE4EHFhN6TQFIlUhuKJ4upuurbmzsmwf3H6zni17v+v//O/P3sbssrPL15eXO+++x9+rwAP3j0x0sH2D95+79nT6+11ZqyFl+PWiG254uvrlynv7t0JboUA8W4RT89XD5mW40EPe/v002ff+92PcAAcCEAL7AHB3bdP3v2pez//N3723fcf/t5vf/fDj7+7Xi6ZohYhNMyLsbfdtr++3OVS4EgpDQlmYX26KNo3ra03LQdtmth1zTiWwz5fXQ6ucbM+WW06DqWN5l7GfrDCy8Xdf/nPP4Kh5Y6IUxpAttp0q3VHxDnp0Pd5LFYsD0DB5nR9fnpORPvtIeX+etivlnG1XsQm9ikd+oGI16tNw+1hN4z77Ir+ukcyIBDczarmEQRNDA4zNzUFQAFBmbPE2Lja0I9uFptgB9egJ6encFf11Wp5786d5x896Ycha26W7ep03axbd9te766314QQrNms1ovlakxl2/eH/hAaaRcR5GMe1IvXGNZsao5i4iqTDm8ltjvcHAoUWCm10QAcFEGoNILqORkR1YkFh5uTuYPmpny1Q5dXGlfsYuVG3F6DP76fTDDWrRUKwF2Pb2UHnH1K2E4QGt2qoSMXVI4BEUOmJGRFWczNYF4mioZ/zjncGARHR9WfdD/6k5jL7qSiWYCpNwURFIIT1G2GlV83OA4YwSZVHHN3VagdM3A0ccjhcG7FqJJIJpIYnOfgexJcBkAKVHGLmsAFOXkTmqKqpXilH8aGRIyg6qpFi03ywDZRYqeKYiInhEZsavJRhxFIKExVzOam6jOmIQyaRX4AEKQKE9VHXPuDa6lzaRJHw+QpvJ4ZuMEn/4Tx+RPmL4Bqhfr5Y3bT7fP9ntl38Vs/P+dM/vQHrkS4qjf24xfwx2N1E6Jag1tV05mpcYsVRfOUOn7A50iFZyaXVHCDyIgYqjNN2dynhihux4SOu4cg5lxQV9FU4DfpwznmJpc3J1n1SutsiG1j8FLKRMfkSe7qhmtW20DMQllTeU7dAo+Vz7OjeZRP17lg8IZo8MYDqXLGIdRKxqMeFmpbw2kmY+oVRrM8OJETTWyzSbhqKqEjImA6bWY2UuaJdSVTXmg2E6hrau6556bz9k0+ac8w6qqQqrNASjCUMknXN9KAyQBxEvXC0y0XYhepnoQDXFmcBCJWrasaxg7TYlNzY6sGp2bH/Ca6mZrwEbl7ToXm5qzThczifzQ3IZxm2i3WK5mDqLpBmBfSRNya/018k3kVzRRWqt8gImbkDjcqEy9UK2wPUkAcDDOapitPtHJidzPoUUKIiSuuXopO/Rd4ooXOan2BMUH/7h5XS4JpLiF4I5GJteS+9/2+3Ww2i8VC54yfCF8drBM92dxdbZZjSg0ly4ndY4hRZBgPYz8GjjG2VyFulpvFZtkP6eTu3be/8O71y5dtCHdOz0AIhKIIzF50GMaSIQI3y6lwrbuLYllVjVgwpTl5AheIvSjqjKSa6zcmEiEoctKU3QBRC8JkELI0DHBOKe13e2bu+96K5zISg4A0ljxsmWEKN+TBt9c9O0zbKI0WHfaHwAbQixfPRJrYtPfu3xVuFwuUlNS40grz2OdixByXDFZ1RZmgeXG5eHYdOnr54uV1/+rkfPXWg3uH/a5YQURKZT8eANICc1uWePdsHWNgYSJrYnhx9SqE5mzdnJysF9363p3zK5QrBgGxg7Achr4fU2ya8/M7zFSsmJXQxDQkB4yoGIaSM5WkBcLF8u6wbUraDX236NwtRrl3fvbs2ePAePedB+OwzWm3aU8vtk9gYb0O73/5Yb8dnz3uRxtQ0ISmlCHGrt2s0jiq5dg2RG3kCPecx6YJZS7nlspgmpy8ylqcivjqjkN1fR7pNDB3vmVDbqw4HYs4QDOV6rWcSRBKFfcPHAI7IVrIlmpmW6EwmuJ8ItysbYdPO7BXfaqa2qrlkrW6pcpPiBEZ2OfESNUlVIq1IyuxUNO27apNi+LZrZYmuydPedTaV4JaCKww3FFKodjstqDAq/OTdG1qgcKy7y/lzw1CAAAgAElEQVTI8prk7gebL9y/95VHdx+dn1Hpc7Y2CJxzyU3ofvjxb724vN4PqU9ptJIDUsqDwwknq0W37DSl7fXgpk3LcTc8fvz8entYrTerk+6tt1ZJU1Ea0oFje3Z+zx1NE+FqThyXgUFsKdtwObLvFnG5WSyGws9ebu+uTooNSXW0cdS9+Yh0gPUX25HO0p0Hm+/8wk8c9vvmH/6r3/+Dj64+vApdJ8vOjPPl1ek7JyXtx6RaSinuKIzIMVaJaJ+zrJiyttMmhuPDrr+hm5+EP5Pf8SeP2zPK/2Iv/yzjuCfd+Pl/gZd/6kGvf44ATLIAx/O3uXmJz6vx5u2v91Ajxu56C2JwgJoRFouWmbJnNshZOwxXUOAMv/QLX/72dz74mZ/90q48u7p8jma4+3D9O9//zd24TdaHRsBiEDeFpd1hgDPHuG7brl2Baej7y932MPYSIQGl4OxsnfO43V/vDj0xrTcN2B0F4tyIjuWwPxwO2S02bUst94dycZmWHXXNRgIA0eL/H3Nv8nvLlp0JfWvtvSPidL/mNu/ed1+fmXamn51ZzkrbZZtKyi4kCiEZUSrhEQPEAMFfgBgyQkJMmcAAMUBijISEkGywSpSxhSHtdNnOdPMy83W3/TWniWbvvdZisCPinHvzpf0st3vw3rnnFxEndsRu1vrWt76VxEStCGv5ypxzSXJUTZJ9zaFmIu98xexzFiKkLm0j1puqqQM56vu4qNdsgZWuXtxevdh3B7BqXVXLZe1ZU0pWrBAYGE0FX5tSPLTXMcac21DBe7DLADnnjCWpGwlDDECJQM58cOu1h3CWbojddrvrfey7FAfrO4SAunGOaiIpZRNMfEyZNdMiBKrJqZJ6T3Ud0nI5JFGVIVEfzS/ENXDLVJ9HLGANmJW9H7ohMC2axW23n9U/QSiu5isIqE0LtBWY62hDl0E1HzwarSWHhmc/U21cjz9HNscrboIVI2EcrVoo/9Of+PQfM2FkNNKK0abGJy6OjfnwmHtsY037V9FzA4y4iHXCpBzDsxL06ZwZe08AxjTpIqtTYjHFvDcyJphjspkzQiVgAzYlyWAydkSam03tvB/622axdKtmv+3dZsNQ1Nlf5q9/+Wx9T8LGnt4+e3Z7+/jpdhCoQ9YqrMBJ+jTE3NfNxtOqayGGYd/utl2o4nIRUkpQVM43frkIq9Rbu9vdXnXb2+HF1Q4RYLALIdRVXelC2uEgkHY/fOcPvrvbXd3unty7cxbjEIcM3TB8jBh65OiBipmJcoAzkr6nnNAPENOqkYphZsOQ+35ISYDiLVpJjhtrBngwsfMOAWgxxAgQRMPKee9FNaUhJymOmsiYuwXldjekIcUUiehyuYYziIf4ynFiHYa0i3vmIXYpR/PkQQwlCAPwLrAHueKBapZsYmD4hpumCRaCOEdOVR1xjFHVwroKQN/1IYQQgog+f3q1v94zkXdsQ+5u93mIFNiiBgoG7mJLTJkA51xTNU7FpJMBpmp5Ugwt+kpG6ooG21hvawSYGQJSVZ1MnNHNxOwPFxgJk/llViIVNs8qMhRePAjqPndE5GRqzM44nYx7myb+6KOfcCZtlEkRGEhJiUDi4EeSiM47f6lR9mqK8Gkbobcs43JQOjzPa8aElRcOE8HMFwZ4uc15b/tR1wdGNZmTdW2iMIwY9yzMRApAyIqAzLRoTf81gDDRK4GMLDITOS2zlCqDRftn7gqmVzMbQcWZt7mbo3UL0TyBDMXLNMa8uJqNmZ7j3bwMO2LU7Jr6fCS1Ts+Gp2pbf61W2Odtfnxspc3SPH/zreBWBcPSH4Ga/ahmk6J5QWSOtflOQjGvHD9/dkfgw2boEZgF2D9DCHYcDWRFW5p1MukKFlIcIibv3Yg9TThrub1S/WG1WUuWIoNpZsRESkU5fmZgzvjk5BspiriVe2mAzEUG2bHJMVuwJJiddLv0C8yjFNeRN1Y8RVXSmeQ/n0M0AWbztUoYzEZdEgIRlcRCoyJDyUVxfLw/AmDZiuFCR4iOGAY6goqYHseICWUxJWeIQzRVEJxzcMwEViPVebTwJBhvAEr0o+QUOZask1kEVYUwuGSYyrGAzLyI2rjG6Ahmz8/t9PUDRf3L7KjcPltqkyvOJffTjsv/6IFNWU3Hh1lWvvGJl6WJCtdAVUchrWnxoYLv85ibSQQmNzK7UNb3Y594TN4onRlRrnFslNTJMiTEjEiBqgrD0GaN3rmqrquK+xgPu70jbpo6uOb6+jr1g0HPzjaH3e2yCZcXl5vztahElTQMCg51Y162+/3jx080Y7lYhRDeevTWkDN7X/l6uVj07eHO2fl7X3zzi+/cf/L0uWOqQpOypN5UgAqsllNi1kJXBEFVVAuAVfblaS5O+CTG6mUGMmISEQKaEELll8umdsSaeE3Be1Pz3ndd++jRG3035KxMHkQvnu0VWDp2TMvlwjuI2OHQMiV260VTM7OI9X0S0Zub2/V641y1Xq9CWN6/d/+wyzpE10fnocLM8B5MSqXgiKpBnfPehZRifdZo0pubgRy+9KUf75PseKgCUjYR5zyHioe+TzEdDi1BCRoc7t27/PDJs4Aublpee0/V0B52t1tVW62XD1cPzi/OD4cDybPL1WazWg6xNTNo9MFLlpIIbGYpZQWDuG4azUlEYkyffvL44uISjkJdrVarZ0+ers82X3jnHcnp06ePd9stsQ+uaer1G2/dWy+W++v4/MP9n37vewKiLZllSZpiB+ZsCjVXVGTcOrcRlseYm1kJCYwCwHP8Ziz9W4DcoxN8YgkYgFG/kkYSNOS4Q03imtMpBhQaLLPzbpRmZEsSx9lQNnabitzZbKIcJxFKnHw0AQsCbMJTHQ8iYiZvIorCJIOqmivcAZiRVsGt16u0Hvohs4HHpBUyWBqiJYUnsEAtJ0BBnuoFwiJUVW1mtzc3JhkaU0w3V7uHrz2g97/2pS++d3l2aVkt22KxKuxjgf7rP/6jJzfP2jgko0whIQ+iUcAMhTcLOaeuF2aA6Wbbvbg9eB/Oz87PLlcXd+5c315Zxm7fuiCLxVnXxb4X56jyNUjbru/aPps6T3Vwe463Li8qVzs0bzUkWgUklS7HzIqUkQZD2rXUVPLGO5f/zq/80o996f3v/MFH/9V//t9l7dlzqJjOQoqDJLVsDHaB4SqAJauJYoxLlg34JMyLk/aKwfo3YK/8ndhh0y//df34PDn+4p/8vI909kFetjHGX7Jp11VwcOycEqCZKBGR45RzF1NeXuKdd978x9/82Z/6xqO3v7C5+3CVrmx/GKLsn724eX79JJuIJrCRI0ip4Yw4iKrUi7pZVHVwpvnQHW5ubySjrmm5qr1TJu4O3dVNO/SZ2TWLmh1S7L13TV0fdqnvDzkBqFSbFPX25hCHuF43q3XYXF6AfZQ4pBxzzmYGeA8X2KB91w0xk6PFsvGuaharqmpiTEw3XUqB6OLOZlEHJqvq6mKz7tuu27XPn920nbIrZkmhElBdBxDiQE1KAFar5vJiVdc0DPv9bp9iGzzcAoELsdspkAcjNUcUHAnIMdWB3KLeWiaCgnKSvhsia98NfScAvAsEL5k0m+8tEEmmvkUexIHDshGJBMdc1c2KXCOZUsreNUaBXdgsV1pXX/zKg5/84yffx237rF/WS599FowSxrDJ6p0toFdGT4mnjlm+xiOUpbP3eTLqyKA2JoSPDvhINS+Djkft6h8eunY0CiaTzQhu/ponfahJ4dVm9xUoRYXKAs0GLRYakRnY1IpPZgRmh2mbMCXTSXrxZQfhdNuavSlMVp5NcuxQmoCEl8C84kCe4nWTATcqV8+4F4iEVJMaCzk0i1pyikMPcpIlo+dKkqWUuy9/5Z2v/dLbP/lzD1zVPb+6/ujZ9Yvr248+uW57KCNmv6rqKNruc9emzaJxHNr9bWzjYd/uD/1bbyzOVquu23rytWugdbe33fXVi8f76xdd18UYDcMIpFDwwTdR+vt371CVXzx9/vjZx3DvXd5xl5f3bq6vu0NHCjHdbfeHfRSBanF5HKDM3LUGkixSwzkOqjklYda+TzGaCEykHwY+GLGwlxCMIIGD8/5sg94QexBgDs6Tq5k9mWihWRcXs6p98MEzD13ftT2M6jqwMdQ0Sizp7EoQ6/seFNErBOqJiWmqjluFUHIYc47NYrU7IOYeBs++8pUTF9sETaoqKqaIMdfVwjBSGVR16A/Dvs8HDR4cyIQsRjd0HCpm8q7yruoPfWwHGNXLdV3XdXB97NouquWqcjlnFA0DHeujlGlDhSMjZIVRriAl2KxjRDTXZDPAjKZhDrOCYam95EFiGsGzw/U52+yPT970EfgYDS4bnZNxsB9/dcKD7ARmszzeygkO7NjNU3/+xeMNYDTgZLIYp+c0+YYmJesXE/BHs9dVOCbMOmku/0WdnZza2U8hiCrxZO6edMzmWx7XIry8ehpAWVTFIEARhc5iAEbN1mImAVZE8E6vVS7gjgtG2bQVM0QwG9ojj2R6BcVznYSdR3XvmfNzvEH6rMIZf6fNj/8/voTx89/ZHX2OZpPGU0GIME2z02zEH0XgKokkMwRWGElHnHgsUjWG+ufZMU3zI3BmxaueJmBhORVAKucsOR+rkBYPbtrmCi1r5lHPs46IHDMmQrFZcZPK4MPowo1iyeNZ5efmLvOoSzx3CJjQrvnnRjNzElYqizYxTfRHd8xQnriJBVlD0aUzUtNxy2aiSSTKZsN2NJzJVAwgUszlV8hoktCwaXkiVTZ45mwwEVMCkPoBADHBwGZwpDIWBxNVS6ngcaVXMi2DJU1yTIcs4SpmnpSBi5qUTjOYpoyN+Y0DCHWYX8j4loFpMQWmMMXUm9Il2NG+Or5KQqE86fz10Z+YWfSjMUeaRySPeSyjZmTMDDYuhWDLWlicfYwqqGZwx5oYIJDpKFNducISGe26UamfFFoinSjJ8SIxp2QCWlG9aJqFE8Oh37d917YtmVy9uG73h/VidefeHUch+OrsfL1aLxZNpblPqhUB3lHmw6F/fn3Vd/HunTtnZ2dPr5/3ff/wwRsrs2fPnr755tuVD288uv/1r331//iN/2vQAcqaxQQoGeIKJtYsWcesAQaVnPCRJFhWUposOkwL9MhvVVN1PjSLsFgt1qsFS0LCaw/uv/7gde+Y2fb73TvvvLXd7kQQYxKY8sciRuwtqw/OGMwIgWPMbdtenN9vmsVqURFrSjYMQ9/3w5BXy7Pzs/qNNx4NvTXVdRsPOZa9UFUjBKWUdZn+BUcxhkQrqWzX2wh1i2bj3C0Td31yVVguFuxpsagMkqTf7bdVwP07F3fv3PnOHz3LA1J3yD1paNpD2O9vHNNr9+89vP9wsdxsr3fdYaid3yyaLnZ9lMrbsmm88ybeew9CylmIfBXW/oxhqppiur29laxc+Tt3766W69vbbeWqy/Pw+msPYorf+eiDxWqjXkxltbJ33rvLX6g+unxi1eGwzd/fXbPBKlShIkeaJUmM0UgDg02TWS67rZZJUPS7xxlTxrIU44vmbXME70/w48nhKEtsuYgZptpUr/reOuYOTxBnGSU8Xpomc2d0oEb7agp7zFs+AEAMbKBSM5qmgjcgdiA30hmnhQwGY2I1SWmQZlEvfLXx/ZAtWlZhKwqDREUWsWEreDoZAm7a3Z37F652bduK5P1ul9uhNtTs+3169NrDt88fPtjca3dtbdV6tfGhqn29k/bTm8d/+MffTcF6NQ1BVJLqkDUbCNR1ghzJqFleeEaW2McB5FXtyfMX3/vk+S988z0OgYB9N8j+sMnhZttq1M3ZarWoRGR32++3gyE0i0VTs0mv6dBU2DRYL5aX6+XZWZVg265dhEXj3WLt2Nrrw8fusL/cvPHmm2/fv3Pvx3/ix771rd998WT/wZ98tN23qCzlwWSCqcwsZSuVj4h5rOsjJ/P75XaM78zf/F0CTn+Pm2FSGvsL2g8bej/C9ONjVHd2Rcq2P1GPQYCSn0TtPJlo3+990GoFc5JMf/mXv/7ln/rCz/3iT9996IWuPn76HbeQZk37bffixVNzqlmS5i7GFCHZspGpeY8pzKqKNMQ8DAcREGO5ru7du7w4W15d3W5vD+0ugnxoqqJhLIoKripBEUNVN6aLfnA3V7vnL6TdY7Xcry/x3hfeBOcY+35IQ5KsZDB2FCrHjnJOMQ45RzUlZ3UTFovGBdf2dd1zl1QsJbGmrpxnXwXq+yw69BmEZgFiE0k5RTIsF3VdN6qVSGbHztFqFZzL7WHfdTtRqWquKkfkQOy8N3CKDqIM8sWThHpnYVFt920TUBiMfYqQ1LVJMi2Xi816Y5b6PmXJWbsmBTKSDMtIleVQlLOYyDNXlTdfLYahu90OkpGjVfeqKvAb7579zL/xhfXy09/6Xx4nj6resPm2PXBghRzr0h+ZSHMczVAid4QiUGuFzHp07o6BjHkhoCnGNxqvY+lzKuFiM+LPGss2+38nlAODuQnrGX1WIgIKw2sU8dHReivZYAawTdFfGrOZCIRSip6mu4Idb/oYLy+9UoyZzZPZf+JdY5wep0jUmGw0oVdHl4tGF5qMp8NHvnEJ5MwK22RQFRm6g2paXiwNkrQNS19VQ3MPX/3mo5//p19+9N7mX/3O//79px+2hkMbty0N2QRI2YHqnA9DP7R7qZCA9vr5TRyy5JwEwTdNtdHBGl+z+d1Vv7t+8exxd/MsxR6+AjM8cVY1YkdV8PV2e3X3tQci8cmLKzQITs9WZ1XIVbXyzpJQGmR7ezgchuDrplmF4NSE8gCy7maXVY2saZjIw6SI8hAIalrSMrSPaRDNzmOxwHLpmnW9XC025wtHGmpWRYyDQobUB3YcqPZhsGSMunbrZu05DIecYzIxB2fJ+l3frBojDN1gbM77ytWZDFqU3rwrKh6ulHlBEdxRtZTS3bt3YxzSMIz2jViOebfbaoQVvWgCFH3b1U0435zBrO/77tBpb84hJ5AYgiEgD8Zp8FU4O1svFstu1/X9oIfece19VVVeyDkQgwKHlAcyggJSCsKX2B7MqOQAYsKVTY10lBEeDZsjq3lET2Ynl46fT5wVe4mS8/nbyxiW/ZCxNk6BOefOpsHPIKXjdCYiS+NqAIDGwOdLFzudbi9NvdnrPgWVx1Wi1NS2mcxvU07ARGv6S3V27tL4T5pSCY6+nh1d4fm/JeFnPLf45wQR4aLxaWArcQCbfVBM8YBpUWOb0HfAJqG9EdCYUK0jyH8CXR0f4+n6Vvzu8UfNzKYUyAlq/1HQyt9J88cOzTf3t4JezblsM9zyCob657QCVBWXsXxT5tgpmPVKm5HgU4CnSDiVUT7G2E+QZhuRbYON6YExRiset07AhI15DkpHKM3mLZN5RGGIU0wz12xeFMpvzZ9PKut9RjvNtSy/VcC4nHO5SDlAR+mBQnnAXOiQiEzNsStyTSoTEFOWJyqTiYvha2am5frTsxijY6XDo9tJRPM0mZeMctFympXSESXBn6aFo8Tkymw3cyAQZ0DF2MwRq2U1qBohm7EJwUBiqkVz02BizopA/hQiIMfOOYdiNhU4kPlYpOKUXDhZUvMbL09v1rCbB9h8bDmLxqjibLiUoBkXH2xalMraMSkV0/EyhJdGJ80hNRnl+9imMQOjsc6aEUZ+MNSUtERn56Rf41FZqPjqauq8886VFHmzYqMBamBDITQpxAC1IWZTg4Pz7ByHUFe1LPKKHKeUk+fdbnd13fFdf3F5/sZbD1M0wESSr1edmHlG5bjykAzvzLOyuaaqN6t9f9jt93fuvxaG7vHHH15s1mrgEB49eHDv3vmTq5vu0A0pCwBmwDnnYBpTVFG4KeBjY1WO48NTKI/Es6mUiBHx+HxM2UizDv1gfcfWvnb3/Tdef/3sbH1+efb06eO333nr+vZWBF0fh5j6mOOQ+q4fuqFt2+4anUPwulggVEPTNE1dLxZL1cTMgOWcbm5e7Kq9Ge7cOXfceK5utjc317uuM+QU+7S8CMzGDppKqU/JKQHctwM5wAEHvHh6w7Vbrc+GbPt+X/k6VBXIFCaSzZQAVRHNxMaEqJDUywCplW1Te1/V9aKpzaxr27bral8PMXZDqwTNEUCDumlqSY7ZDVG6oQPrYllVlV+u1o5d27fLxVqhlvJhv9/vdkych9gsmrcevbHcrH/7D/91VvHeLZpFqKUdcuDm7oPqp1dfevH88P1n12mb2WfPzsg5B1d5qKSopAV8PFEAOpofIzqPefE4zqvxGDWdcgxnvHe0KMxgcnpicRhgGIuBigo5MlIxMVE2mrOfyu8W2Hcyz8Z7mfDvscpWGWpqx9V9TIEm0jKd3Tgmj2G3bG5BZtIPbVNX5NSvXSUcD4oOKhmWxQieSuWoUlgADAgevvHwvR97t1k2L66fV1VAtpvnw9JQLwNlnC/PLs436POLJ8/vLC4vL+4Qo9fh4+cf/e4fffsHjz+u7qxbSV2WwdCpdQmqIAfTlD2W9eL87Fw1p/2tGZo6cPD7w+Hpdb/bd+Bg0Jhou8+3u5vDQUgxJN8tYKZpYEWQXN9cq+S2rnS18Ez5eY+7d9vNZkO+6rMNacgLV62Xoaabq6vr6+588To5b0aNv/vuW2//R//JP//tf/WtHzz+o+FPBEB9B3AjyUpEJCdkgIi8Zy6xpUKQ/lGb+Mv7498jU+qv2P6aja5pkvx5lx0N4s9ztVc2rrHxvImV743YREXF2Dw7dpYxREPcAwcA+MYvfPkXv/mzb3/hQZsf3xzSp88+XF7WN+2z2+4qWSZmgcaU2kPfdTAFHHxVLRYLVc2KnKNKHlISTU2DUOHsbHFxcXb/3sUf/f7HaQBZ5X3NVMU+x9QpclNzTpqiMoVQLYa0bNt4dZ0OHYYEiuAOzWIT8z5l62OOoloKxfNYpUtUhtQPMcZoRYzbByJfneUVBWyfPju0uxSsaR644A77w9XN7fZ61/UKwAeG2RBj47CoqovzxXLVGKAqIfhnz55lQcoW00FNqgqVZ0+OiBVMylmzJqSYNGVSV4wwVgqelkusmiVI2FmoQmyjigHsXM2uSn3OYlkRc6u0XC2q4AUaVbjv4ma9dM4R+xRliPmw725uDzkeFgs+O6th6Xyxunvx+jd+4UuX55e/9b89HmKsgjpf+SADhgntP0WTXxlm0549FxMssQsdU1NPhgww4UNT6GK0SsfL6OSPsMMPt9NQbTkdWlSJS8T3FGkqN2uqMKOJc1FM38mVMJpjvCV/HOycF8sEGolhU1LBZOjNvbUT1YhRd3pUyi59h4HGfItXJt00s6Y9qdwZjxeap12xsUsyIYdRFb7b7kIT6vVmiJ1SEg+5yriHr3/ttZ/5J+8+end9tX/80eNPnt7c9qiSwojETBlJtG1lv8uaTTPats+x69o+ZQSPyw0qX1v2Fa2R3X4bn3y0e/Gk214DEaF2y7rxgVKkQzcQeceBiLPZfruNw+AZ777bOLIYB+dRhWUVdL89HHb9dtu3ra6XulqGEKqUBskxJkPDJi5HzSsEv1iu1uwk5ySNA2JKQ4qjCEjMCIq6BnNdhSZUgUh9RewYRrrH0FraRRexWFbrZQODii1puWyWOuh+aPtucPAEDO1A0KYmYopdUrL1qmKihoMZqfdGjpRIYBmqaqK9CkdS1Zz6OCRNCiGDSdRIyZtb1qte+lSq9DA4UEq5qauzzUZE+n5QM64QcogpaQIxXF14D2KUmDj4ynOADioa247YoEFzckYGYjFWhZFlKyUOIUURyahkFEqZYRN6q0fwl2j64zxx5z8dpx3Nq7qZqSnZCQHic7R5utkJlYTo5YlffpSp5O5hYiTS6DgfDTMiEsjpDvTD6NUppPIKgAWMkFT5eSYCrAjmFFPQaIKSacLjx5Xk87bTTMaTyToZkyPsRkVHYyZAHJ885sc7nlSUdwoWXsi7RmOiCQBV1uIGj4ijjmXsRmD7JQRhpFK8glrS7JaOT2zCJYTZjUsUkahMun3Hy8H+fmFYfkL9PgPR/BttMcb5818W3y1P/BT9GYv9TW/ilUdc4ImyOQ3DAMw+DFAGNsM5ds6P8mx6VF+dUWomSimNcZDi0bgANUWGwQQRiXNShRuLccLMGExMRhRjLKmLmLa+MvEKb2i+yeKyz1O3fFYx9jSrhk13iCLlPj+N+eZVVVVQhLQmnpqRseORkSHJZhXz0h2GMVBkI5XNVGA+uFKYsezexasWU+axaqHBjI1AZiZQMoKAXHk4rtDNeV5MbAKAZ+CMGWJE5JxjUJH9YqJqsZCU80SOG2uLlsS4oh0DgwqTp8J1ZFKAHVXOAWArhWGLCUOlQgQzl9DcdM2yeB2RRCJKKZV/ThhnWTegNgJEMHt1YRMQKROLCSZAauR8ERE58HF486iuh4KxWRFkMwIV/jzzSLCafgswMc1phOMZZSwRlYALGUx9KXFRnrU6x6IyetZjojMBxuwKRbSIUI6yPxm+IhfgXBCRlDOBmnpBDKg456qqCqFL0rd9f/f1e1dXt8+unm73+12/XVQwyMJoUOvVqHKLszWFEJZNn4arm9vNen29u3J08fDB/Y8/+v7DR29U1erhwwf/3q/8yq/9+r/88JPHu3ZwHETUslLw7FzpeKHEqeokozTuJ+NjzGo8GZ8jNgpykAwjMe3athcZnKDyaEJV+RB8IFDb9v/D//jfZ8FyeVHVzXJzYUp3Ly4fvPZg6Pq+a6+un3sK0LRsFucXq4cPX4+xSymlPCwWVdJgqtt2T4fBHL/+4G1fUXNWPXrntcv7l598/Oxw6Bhus66YOHap63IezBJJyt75smCYaKL4ycfPwqo6u7dZb86zGsCxz4IcY5fSwAAvEeOw2+9S3/7qv/+L2xfXzaKu68qgr92/+2TRbHf7/X5/9fxmuTxzLnj2u27PJPfvrKOg67uUhkWzunv5eop2u98/ffakT/3mfMjx3zYAACAASURBVLWo63t3L5eLpUEfvfl237dt1/V9+ujDTy8uz25ubu7w3Qev3X/wxuuvv3a22lzkPAz94fb6kz2TZNusH/z4F772D77+1ffff/8Pvv3Hf/D7f/r0yY0mGfN92Xnna9+0u5bIcWEHkgMDEOemET0tu3PSMdOkwYfJgijzE6VWC2COiM0UUsKijCmTf1zMT5Z6Ii6rYC6zgo9/MoD4iDuVJWDyHLgMNwBaarUAJ9ELUjMuuYVHJbsiBgpTeOdMtBva0LtFVVdrv1ms2kOfO0lJERmDIppCQUTB6sCrZYMmf/WrP3X58M5+uyezi8WmrW/2tJMWm4vNu2+89vr5w9z2fd+TqGl2nhTy6fNPf+fb/8+3vvsHBxuShp0Mt0PfQ9R5I0RVZ1xxDaqGRDe3A6nm7A3u0Jl1SZQ3K7y4infuXeTUi1LX4fpWuOjTaU6xWdZLzSHFoT2kPg5MFkJYrJaX55V3cnHn/ursjm/ORExS4hjqwTxigsKZhXy9e7zbH+6ct8+uP/3qN9762V/41V/5F9/8jf/zX/7Gr/3Wr/+vHyyCM5F56xNXYhWsWXmEGenz25BHU/Ez/jC9+s9zoVdP+ltufzkVhc93xc/y+U9byZr4oafzWeDhD0EUNB6nUwB5VMNgcq5IMYrzuLxYAXL3wfI/+A//2T//1X93fdd//OSDP/v428sLq87s6nuPX/TyfPtEgwx5ELaULYsTeLjsXOW8Y0/sKKUiApX7mEXNOVs1brPZnJ+fhcB9F802ZV9PkftOD90hS16tvWzCbi83N1vTRQjcHuzmVg6dGLm60dWqvnNn6Ztl7PqYJaYUkxEbOaoqVuRBhiEfYhz6AQY4p74hDsZK67O63lRb7A5Df7a6vHf/YtGsP/n+J+1+iDEtFo6g5+uLRdNozrXXukJT185RjANEfCB2Q0wp5yyKqkEoOg9CREEydTEOqd8fkir6vdW1RVV2AlKGvfXWg7paZe01R+fcgStDbLdye7Nt98l51LVjZhGQ1J4aXzuTHpZjTETOuaCK/aE/HPrrm/3NTcqR29YOh17TbXD4sbf7dx5+6ad/9p0v/iPcfowXnx6WCOyDZR3T4cyMZGI7ySTUOoKiTJNqQuEdvcxImnEZKvF+RdFtLrt9MS4L0nRUY/uhBKaj43qCYc3r/YhCATafOoa7UDIEyRypWokcA9Ci1srjpmAolX+ImMCFjF/wNFdG/qnLDBxXjrGnREaShXlcoJRpDKbwq3PJjlkPRT6MYSA37m/HyUhQmKiwc1XwgKUUjVJdnVVV3fVdhjZn6M/xX/7Xv/rovbPqjP7wg//329/5g2hudfbw+vlu33fsnLLVi3rI+fnV4fa6PVutF/WlZWjMm7VXMihdbjZQ7re5ssXtdfvko+unH3XDAVAQQqAlZRhMBSpgUErD4ZBXy8WL2+tmgffe2bz79r0njz8gumN2vlqdM8Xrq09ur7G9xdCB0V9eOphPMbb7tG/bzfIii+aUvKvrar1eB9V4kF0IlWRAo6kVwMPDHIPJ50S3uzblF8ZGAYvGORfAkrRTRVYoSb1qFvWSsXPi1VSKNnbSYklon51j7dSguc3qbLDeiESUzLGxZk0xWzYkgsFynhQCAUO7O5iody4LUhSTCFdXoa4bIh5mp0wtgZxILpwy70YCFwhwMCBnYSYCabTYpYF7iRnZAAxtl1JMtaNi81juhgQwiZEQZHRJyIwFY+lPHeFThqOpkOdY9tNGV/8kNgiMFk0po3kck6PdrWaThoN3Hp+vzT7s/GH+wdJKBcEywcCAjHbYCdWAgOLGTVryAOOo2j4DVWpFNdiKE4d5KpXVwI3/xgTMGIxsPAdETAy2Ii43u+1/rhkw79QGks+OAE2O4HxLPwSxzA9q9GCAk2AqXKGRjDdNbMg8JUcxF+kKUpmQsEkDg5jKFD35ATCBPb8k1HRCv5oXUS2YOazAKmNC4eSHHnv29wm9QkkhnCFAFKzms4SwbIrCvTJ6/lpu4pVRPrfT3/pR3x/BqRNQ8ZUL0knTOKo1FJ3ukkl7yr3SSW+/vFrmaTASxEBE7IpqOQwENiK26eCCdJQZ9coNqI3C/jN6ddqRGbGiiWZVYJ1yuuBICJrhlfnElxcImzrKRZXFOSciIkVRqxQNmuHe8Z0W1s8oWGBHRRjH3grnAcyMPBVwUR0FMNmNPmE5XlXL7guYc6XUXWGDFrdRT1bIsTHgQMrk2ClyeeJNVQ+F71Vy3sAy+ZuzBHNBqEZwcQoYjIqFRd5vTO4psxqlWKABZiomZXU7fZjMHHNyY1GGEddlHnPxSOfl/Wi7jCnZE5Vt/BKTul4xxsrfSl4T2EqgbxqSmDTWx9iagcTIoAS1cTQBVqQVvSNjNRKiSVmaoIJxZyoruQEOuSR4F1OpKNKLgUlVuRCxyuNxVFU+VI6I4pBBZCZWSLyqqlZV4Wy9KOhwhqUcd/v2Rbxph8P9+5tQcbVYcN/BLJv6uuIsXRy2h/2uO4S6SrfX/W73xoOHT558uliv4J3j6uFrD95++63r292z7bYycj7Efa8QQskbJFeeP3jULJvVMMp4kfltlxB9CSiwqpmaZ4hK1yEYlmuo0mF7SJI//fjxn/3ZBxob0bTbtXo7VLepXlRMrKLBubpu3n7zPQbIZNk0602zXq/2uzz0MaVEpD64YTAYx9S3h0Pb7c2MWS4v1mcbLJt6uzt45wAMwzBUnl3sLEUREKmq96HwPX1dHXYH7fd+FTiw5CyCHjlJR4SS/yoZqglWM/t333q0XS5Tjm3fHvb7T9Ow2x/M6PZm17U9cVitfDbphi44FVoaoU9DOsTdrr137w0l6VO63beH7nZIfVWHrHK2OXeOm+XShWpIUjZ1BscUh74fhsEz/tE//EW3cE+fPv7Od3/v8ZO0XqKp0HZXf/yn36rDB+88ev/L7797eefi29/67h9+8KE+BZwsKuXgzaz4sOqYQGYztWnkIpd3R0wgmkQp53Vy/MwFuRrpUtM2qzbqvE1BNRB05FQRCOTADuQBKtpxGEUe5uuP+Bim5fRos01U9jFCMR5Ytgl2BTgWGBdJK8cQJWLnfYDmlJnJQJqRc5Tac0NNVfGCh0N8tLwnnXa7od93rBacb5pqs1leXJw3542IXV/dbq9ucpeF5MHZveqBbZ89e/u113/p535xbcueFS43F77xwZAMdHW4+vDph9f9lVWWncYsvYgQOFTk2JkGDuyCwlvSq3bvmQM7MxvyIBJd5au6GSKrVmaas48xIoGCV+M0sFTerdZpOGxvt0MeQqDLi2axcMvl4rWHr92/e3Z5tlw2FXzNjpwn7+qkSTlc3L9bLwZJGGLPIT+9+ag7xEcPL3s9+PXNT//8o6+8/y9+/X/6b/JDMYMkCY5E4bx3IEkWfNXHyMWFg0y77iug0ishQbzabFoqcLotvnreNABebZ/55Y+yQP4qR/6NNpv1oV9tP/Qt8eTmn3756mGvoldjT4v/X8LCClU4VE1FgPOUUhpiziH+W//kH/7yP/uFr/zEO/cennd2defh5vbQb/vHw+H22dVzcSoODn6737q6EnWgRbNYNA0THEiydjHGGKUwc8c9lVBVYb1erVYrM7vd7atwmfohpZiG3PW57QUOdVOlxFmla0FEOeXtTvpeohAZueCX69X55QUzqUiSnHUkKDCz8wxSyVE1j0IBDr4iZs3Sx5hzFvO8XFbk8drdu3cu75C5YYgMXi/PPHvH/ny92azXjk3SHtKJxr4b+q4VTTHVq3WTkhABEDNzjmFOsldwjuja3PVy6FE1GFrV80oy1BExKaNpanaWB8mSQOoDV1XoGbudwg6bc1fXmyoERWDy3lU5JrLiTluKJdJuMUrbxyy8WGyWd5bBm/NdqDO0y9bdHj5+cLn6x9/8if/v//7k+ZPbtt9VYQFmgsyF6h0zEYkcJ11Bt2hKzcPEqDKbBTfoOKQKtX9cq0fXcYy5nU6lSVhjHn4nF5j/N83yk9ylYgdbKTlfjhwFMErtkEnTAkcLfLoZs7FiPY26XycVuOZsm9n9gwET22wKzYxO6djfUjP65Zk1L280BhqPB5ga8YmBSuPfigcRageoGjk0Xd8mS+wJwGtvnn39F7/w3lceWXO42j/56NmHT6+vXFhm17CvY96Xat1V3QCub1NODAuV56wpePWblZGkITd1g0w5g+Haq3zzpB/2wABiB/jcwUSAmLKaicKGKIPqYuXI47XXNg9ev2CSoUXsoyTLCaq826MfoBkAmL3j4F3tOANexcchGwyMqmpgvNu2Il3MqbgSKZsIPLP3HpYYMAlDa+1+f8tdXVWmMQRUlQMqQRSlbFY3IXiu6kaitrd9ShE6muIqygoYHLm+SyoqyRCQkLOIK/qMIKeUollMZL68YSs6jUwgc3Dka88+ppRykiiRkjE0qympkqkoaRUqmO62+6I7HrwfhiQZznFwpKU23VgxBkPfQ23oE7REndVSyqTOHDGZSEoaAkNmBXfAQEoiRmqTOHPR3TQDRti0KBizkRa/YZpCNvNXaHZ0acznPZZEG0e5G484nZt2BGBf3iNGWefjUJ+mqh35RpPdpcX/KZ90+nbsCDuecoJPd/55ahhspCqOXtXsQZPBpoJjOOJIE9XqpMcFXT7ebmFbjMlYJ6yFAgQe+WKM8cSxlQxTIzV+6amM/mRZW2YlqjGpeYQL6ASzshGWKg9HUZA3BhWUSUcYsvBTx7JeABHyZ9lEUy9nx/X0lmnyrCYorIzvsnJOFLn5qR7DBieXenW5/lts/hQEOYE/X20jMOjcKcrzlxVff+mCr0yD6emc8oxeOWZufILyzP8t34/wEzBnAtKEcBWIKsY4T46ibk5TKh+m12NmIoLpZso2CCLLmZhpVhAf40XjBkfT/scjQYuPqOCkTzTOnXmCnQDGY3NQUVV1zhW9eREpLKYxDXB+7IYY4ziN1UqFTQOOt8xcXpmZOTeWPs45g5BVaJTHmiBYMyNomUwO8yMpLCh2xOzIxCzDiDwBRZ8e5AkUgKO6AOlYshhH62V8C3Cl8Os0BkAg0+lFJJSEejjnCCRaiqaSkUz88mkg0ih1MxaJLDagah8Hx85NsHfJ0xkfOhWleYzQsoqxnb7HshSOBf1oNBSMoSTE4CLkSFAysrF+BWGqYGbmeI786QikmamKKYg5EHNRYi+RDQJAXIo2EnIssnymBmQp0GPSTMBYkGusL2BkAJvMrt1YeRAFoTLNE2Ku3jstjBJSBbG3UcWEXEH4rFSxKY9OZH84uOiZjci8c+yo7/qqDpeXl8xutV7HFLPqkOOha4fckovL1YLYx5wvzs63h9aIs+n19qau69V6uT3cNlWd1eoXztf+Bz/43sOc79598OTFizffeHR1s42DPHn2NNRr7ysYYh68d2VgE8bIrMoM3U7mX6H4EamIZVgFJhiTwVIU7x0ZQ7Fc+LfefBB8/eTpc7H8Zx988PTpi0PbO899jPsW2br795ek8PCXF+cGvPHoUYwDmVbeOYcXL66ampfLRVW7oT/U9XK7uyGCKrLEtt3mHJ2rxGLM+f6Dy8Uq+ODXq1XO6A9pe3V4/PGLp0+ukmYIes0wwCFwlTXHFPOQFnXdVOHQd2A7X5yHirt2D6TLs/W9O+vLy/X5qpE4bFZNP0A12qK+3e0ky9DH29sbEd21e/YhBN8PXR2wa/dsacix7drYxfedMzL2LtR1ZYtkmofodwcjrypE5L3PajFrFdyh66oQ4jA8efKEQ/jil77Yxs5E/Ve+/qV34X18cf302dNPnj1LhGer5bmj5Y995c2f+PJPXD3e/e5v/v73Pv7B8+fPTK3XQ04EYygsmkpWcp69yMBMppRVmdjT7BoQaCz+VNyHslkX06uUgbWxCLQBRFwGsJXynyWhFI7AykxgMI8k0LH+0Ml+PukSFCZ5ibHPdEsQFcm8Qi5RLQsCMTsmRxgrSFg5awz7GJEyCHnIHKiuKyFNlpx39bpanK2unl6d3d3EfaqqKnhXmQveB+8Ds4kS6M9+7wfqpc/tcuEOV9c/8e6XHr57vnznK++/96Vv/szP9+ngDCG49WZJjH3c3rb77z/94Dbe8BL5kKJ0beqSiDrHSYZeiIkabtvBclyESrJlk55STslMyBGrDkN6/c27Q2+qIQ58aEGOvK+IfNcPrh3uXlbOS12vmhUMw737y9VycXG2DnUdI77/p9scowmaulo1C++80+HOyt+53HjPm9XaLZf90Ktl8fnj7Z+wcViFt++sVu7hf/s//xe/960/+83f/O3f+/YH5I0J3nMeVMnYewyJnCOCpFQKws4+8KlhOm2awCydgyIMcYJ1nwaQ7JWI0vT9Z6JL9tKY+VHth8+1z4rD/bD27d+GqVd2jr+4vwSUqUevHPfqmSdCsGMRdrOqrrIIqcIReyKAHBvE1zBgtWzqmv/T/+w//to3vvTWe/fW59WL/ZMBt83GH+LhB5/84PGLDx8/e0aBVpdrKAQVoxYVMC+qOvgaRlm6fTfEFGNST0RkzErsiLFcrdbrtfdhv9/vtgPkzm43bHdpGNJ+fzBYs4Za3ffo4jAkVJWPg9zu2iTeoClp0zRnF6vzy41YirlXjb5yzhORJ1JyBlK1HJpQSwZAHtUigLTrDre7XYpCwSfEJoTlomJgv+/6LkI5uIqNald79pJETVQSkLLElDpiWzarZlFLllD5FHTokwiCr4kXfWeHQ+w6Oexy2yclpIg4cHCbmHqomGZquI8tiA77fd93y1WzCOtmWQ89scMQQQw1ca4OTFANPuxvO8Lgl86zzzlWVmfR7fbw4vqQE4ea2VehgVlW0rrx7XCz75mvvveP/+k/UFn019//7h++QPCcTRUgeOfYl6J4RpPfNfI4AOLCA8Fo7BRD5KVJWLQlZt+tuK6GUj1wrqkzzRWehqXZiWyPzSI3U+Mxc6okH3hyXHjtBtOpOMdR9wawSdZ6dn+ZxRQgds4HZzZWO1fTUTDLLInSyZyZAGC1Uq+7fDNm5UyQOjONmRmG4xJ16r+c+rvIJmGEFWyUBQWFOhh0GDo1KV5l0lgtaqHBL+yn3//Kz//bP/mNf/MLg90+ffrhh08/fHJzlSlfXXW+Ds0mNH3TDf3l5cVys5asKWbP4bDvHVNwVNeOmHyoBp+DYxOnA9/etlefdrtrocwmsOTIuVI8R9lq11SV9hI1d6jQbBZ31pvX3zw/v1jEdHj4YE2o9vt+u30a/FIVdYVUAQzHXgQiBQoKjkOXBZBQh7pZiOjV7fP20JvJ+cXi3r0H11etIzCFpvaZPABvlaqmvo25PTtbphgZqGoXKlquFmY2SPLsYkyL1Wq1WnTbLktEJjP1gW3i7DBzfxhMDB4OrArKDCNXMSmcc55dZmMlk0l3xZHzjpglKshA5MxlFRuymJCbaiUpDCQmi7qBYei6UFXe+6apGXyIAztPDjRVgmfnXHB9HNp9i4Qxtl1MdmIunpIAhhyVbVy5i0Q71MbKA1PcrbgpCnM2gTqEYhCNkUQCADdqt2MCUEfFUCaVk9l3nG7TcC3kAB1LpU9fzp7U8ZwJ9HU8YVQARtkPU3NMUIi9HGq0I2gkIoyxPFopBvSK4zwjGDP5Zj6ACPMkHGWaC+TDNDsVVogXmKD3kz6fTEyb+z4KzcxHMRWvC5N0TXHjjUegqpx4SmohsqLIXqgOxsDMCANgKD9BE/xXPoxCMSMQQ0UP5iTxs9z7KUPEJmdwvv3jkQWkmDrFY/hAGBNZFgA7ZwxI0XJRAKVA7MuoxVgrQz6fUTOf+xIw+ldoY+ZdCYPYn4sZzUjQZxpqf9l2OgpL+/ydOVWDmq/zyumnIFHJVSiti+0IIdE8nsbTZ/Wo8eEqFFoQrnKVApiqjBCSGkbqiyoMPrjCmZp+GihSXzrBxDM4SKN81XyrI3LHrDmbKTPNdQOpZOMYREaboAzinIXKqBIDpnrBVla745XHlMmpaoNOd0OFRUZmZjknYjaCuSL2XXTlKGfJWQBjFKEq4gKUFKSngD9qsFKbxcafVBMzN9FNj0jvBEKMr2wGxZkgMAYxyqqrMIGKqAhAdizCOE40mJmYeOfHBL152SGQsklRbraJ1wTn3fgKacxNMjIlnQGsnLOIMNEUDhzNGsUIiNpUyZiZWCmf8r7BZCRSjLhi5Y/LgHNOUWDQ0j0ldkdVriwF7TRVqBUO0bQu2ZgdN3rjBh6FTaE6bY4GmOMKgtGOK9EYT+x8SZrWAqEBVmIDMONSrNUUuqwWapaSIBk7BDgiS6kvhPmmcRcXZ6tlVde196Ef0na/37dtTvAeHELMsu96cr5pkpopQc2yac3cLBbGaNt+FVwv/c32ltmvu/O6X/Wxu7y8/5M/9ZWKm49vnuab/eX9y6EbJMdxgpiJmVkeEysLWkjGpZiTc448zLSomZbMVRIwiBFjzD3AONusHz56a7nefPzpx8+fP39+9YLgGAxzZGAoDKnLe+oqd+PZh+C8CzmJpMhNlVLudLBNc362WiwXi2XohzY4v2gCI9fBkeUUu17aNGSQI+qbxurG10u35OrOnYvLi/Oqrppl3fdiyR3aQ0ySNfWxKwIr3WHnqvzWW4++9e3fR4V333h098H5fnedh/39uxd375x7D0v9t7/9+w9fu7s+O6uaRRbzvu/7vG8PADnnJKcYuyxVFmXkuuGmgsLYOfLcDXGICczrzdrXrhsOSXKEJZAL1fXVi/1+x0RNU/vgQl07xzFL12/FpJJBSIMPr79+33k4R+cvmuDDp588XS/vXm8/bdu8OV/+5Ffeff+rX3z9nbPf+a3Vb/za7v/n7c16LcmuM7E17L1jOMOdcqismUUWWRxEihQlmNWC1JRttdWyG2qg0TbgN8MPDT/5D/jJP8GPbr/IgH+ABVj95nYblg3NgiyKKlKsKlZlVWbezDudc2LYe6+1/LAjzr05FFVqEQ4Usm7ePCdOnIg9rPWtb33fkyf9yXqxjUMWEgT2wTFHEdMMe14nkCnkrMwOiZEMqUi2yVQG2EcHhXJVHn8JsaxAYwglTEQFxMIend9WSKJYbCCfQyKeAjUArgORsjQ5Lpi+Fi4GKKio5oyIyGxkSXKOUwSTs0ofYz9CAJHoa6oaR47HMaqYW/pFUx+fHDeLkPtsKiklx4zIQzc+urgQSc266ULeaOfNVlULWc+rR9946+13v/1Lb965VxFXSKcPH7Z1XTcrQPjk6v6fv/eXf/3hD7d6GXnwC9qkrotdFmOC2Es/aKjZRoh91AhQgycnaiaWsoplYmAtIqkco8ZRCDl4jNEkZSQAEZFkkBdtqMIa2ETHV149OTm+JVE+vf9oc775+P7jOIJGqAKsl7BsjxymlYdbJyf37t39+te+Unvuhr6uXMrD6dV9zWnRtge0TKa//S/fffsbb73y1vrw3/y7v/nh3zz8GECjqlZtHWMPTskHjRnUDE1kknNGxtKv+dQzg7kGMjmOzUjWi4/PhUtNdYxnIpHnoh2E5190c+BeHy8s8r0ofPq5oloTdvWMjvsLvr593kBudp8r4R9NvRhl1SVPxbcCSEKb0dmrd1//2jffevMLr/6X//Xv1At48PjDj84/4jol3H745MlH999/dPbT3XgVRQRUd2O9bFfrkyQy5H4YIoHWFYSqVkAzqSpfV+jqAADjMDof6qZeHx5VVbPb9mdnm+1VlBgePt5cXW5ELKu4AJQgGwlS16cxQ7PwMdqui32f8mjA0Czo4KC+dbKM4xYp1Y1z3AIgYaUoSLmEc1XlmWmxREB03sXcDePQD90wQDYIS0DUq8uL7eVuc9F3FztPjTFp0sxqGQhsjDvmvllQU/tQV6pSBdcs6u1mV0ytgZiQnavZtSp2fjZuLvuuFxAAB5rBUeV9TdGnnBW0Ur24PEfHY59FIORBfU3MdcP1AkvhKuahGxRBvXeMagbDkBzlxdL3Q/QhitL5RXf6OCHA8gCbhQiwiOiul0oPWiOHUbZ33lj/6j/+puyqnzz4v8ezrllwSiSqyGgIMmQVpYrBSn+STfpYJQpCm01XSsz6zKwpmeeM8BrMPKk5nntm8NrfPUuuo835vCU7tZLbFwQLwWbcao+RKRoxaRFpIOTiicRoajAZC5fZhPvi5U1exgvmC+7dD0umUWJrg3mrwtnD8QVnMKiqSlLKqkyOvSuBnANFAnaoFkWSrwJ6wpDTNr3+9q1f/89+8du/+uXqMP/Jez/48OEHj84+MVe1BydDHvpxIKXlIqwPwuqgUYPzzVaSxDEPXQqejg7qdtkET4ISEkrOrV+kHh/89JMnj7Yue4kAmRDZsuU05jH6g+BXLtkIkn2AVMEXv3o3VHZ41IaA1mMdDgTx4/sPRe3NN750dLC4vNg1DZuS9z5n6bp+HKIqeF8zR0BM0g19NwyyudqdX0DlYbkC76tbJ7e6XYqj5pjGXphdcN4zm0cE2lx1YwSEFNIAQISggCCmqhmjihByXVWXm03qs2ZVKC6aCAzDMIICOXKBDCHFDAm4dmAmORkoMoTgLZuqALOpIhIBMXK32QIRMQKAqpGxqmXNAIw4Kc0wkmQp4i2FMOCIsKr5oAZD0Zw0eUIXPHsGAMkCUFZulVFL1TNTcuCK5hFO0T8UTNYMUBBLjFT2wAnqmDJFw5uNd3NiCDQNQ5vgCSxCSlYkG/CZTRD3YMnTv8Hn2FeIk90Z4DUXEmbKy5ykGxkVS/VyvciTEjntifl2DS6bwSQXoWpiSLhP3PaEFbtJxLlx8T74gkBP03XWOZ5ht4l8VoqSpc23tKA8P6UB9rs+Xv/VigBGOWheGwpA+pmNZXvwAq6f1f4cMDUSlY4UJoKnCKIAk/wVTU/2BigAgETF6mi/shVI0/Z/mU60x/hw9k2dhDPMwCar7sImm0CvvQLS9YOG66Lh3+v4Odbw3PUZf+ZJb0Z/+8bOlNK/9wd/CokFQwAAIABJREFUFgS2R21+xpd8Hr27+ZubZ96/ZoIMVJl4mkgGeyEtMxORQnea8E6bGLzX5zFTmZjHU2kE52YzmzCpcvEiAmCIZGaiYhlAoFpXIlJU3JCQmUtnloiISEpJRIjIZE89u3YqZHYqqiYmUEJGxJkhUMSSS7SAMH+XqfcKDFQyTGrlAICKWlr/CPerXVnYSkgqc6Q6wVwAMFk+CgIAsoPJEmFWZiaEQri67hWaYKyC6u6XOJtULQvKa1PdYMaw9nhmFhERQCRHgpPuVZm2E199soAsmubTvConRMPC78LS0YtmUjgVRkpEgFzuGiCjY4cz/6IslBOqeJ0nTbC6mpExlKVSDXSa1IW/uY/tyx2fqwE6KeSUnYzY5qUBAadNzwAAzSCNaYImdf5URHA4p/M2OU9cr0qlsmklpZ9EwsrWZsYASIzl1IYAHguZCRSn4BIUURGYg1kqRrMIDMBglmVqNs2i45j7fmD2iNL3fdcNKQERkKtKQyYRex/YeaTIzrWLNlTBORdT7IdhGHar5ggDKRqQKkPVhjurxXYbb98+7t8YX37/6JP+3DTlPPobDfaoqmpMbAACYmqlc5eZcX5MiKiUkaAgyynlUHNVVZvc+QDrg8P14UnMevrk/OHD0yEN3jl2lWPnGD3nmJOnKvZyf/dou+kWbXvr1q2y1fngU5Ku77zX9bpiF4rdT/D+6HAtsgqhYqY4ZkmjmnkXREazLAKbbqiqxd1b66Ojw+OTky9/BYJvLs62j05Pzy8unlycvX//Y9gAEJz3V51dvXzv7usv3160i9defenO3eOUbqW08wyax/PTJ09OHx0t64NxtSJXB2dAw5j6IRNx0zSEWDVNVYWprgAQ88jOkSNfB0K+f/8+UzBwoa6NQSyDOnQhlTjIhwTQXV2tZFlWi2XbBu9cVYmZCt66czfG4f0Pfvzk7OGtW0frg6OvffXk1Ve2i8Xiww8/hrPLqBdDOj08rt7+2j3n88XV4//rD37w6NNdu4S4FYhoaMSViWZNzJM8ZBGhEjVB4GKvWbZIM1HhaTklMCwspcLbKsEVWEGg0cgAYQajy1SbjAOneYCzdOXPPq6x7+s627TZEQLDbEmFRsjOK6FaAgEwMDF23lWQZbQIEbRqkJmHNG6z1cNY19X6YH28OrIeN6fbbrfdDlsWdI5MVXIeTi/h0N86PljUVep29x918d7VksMrJ3cOmmXcdHUANF34GtE66E67Rx+ff/i4e7TT3eW445WnzvyIC0TisM2RsXgmAcNUz/DOx27s+yEnNQBXgWN03rxzoOYQV4tFjHp2sUljBEvgrGmq4BOYoPXrA39w+MrJyUEax9MHVz/5yf3NebQIMYJmsAQeK0fg2TPwZmQ+690HHx+tF3dODox1tx2cEqFW6HrZxWjH6yfvfP3u3Zd+/eBW+De/j7//P/4wQYZDIBzzKBAhqfkqAHvNgoVFq2pqOVtVVbMHhZlq6Z4mh6UiNWesL44cEOeqzt85Hm78DwDghWHoC1AuwBcGNfrZkNqzV/i5Xvb5zqU2hXbPnPS5RBlf8MHPf41Sv7PyOOY3GhmaZjOIAlEhAtTQDQA9fO8//8Zv/7PfeOdrX1J3+bcf/fRid7o4covj9r33H/z1j//y4vJx1bp6ueS2jpKVQIGRQ9dd7fpxt9uBQd3EhURmcczeN85RaU9mJmK3XC4Xy3WOtt32V5ddHLHbdZfbftOn4H3V1L5CqnICGSWbA65I2YQ0AygbtbCo4fDQL5fYtLbbXYkOSOI8EjjnHLtgnFNOKSazzA4dEwIZqJgiWdMwkgwJHOGiahza9mp38fhy7DTByChtaJnduB2yRMljaHO1DKFusqTdbjPstrsYUS0mGAdJUQF9IldVUYRUQRGdD+pUMSEBey+FekCICFmSgDnMHMAZ+ABAGYTNhD1QgiwKo4okBKgrUD1ypAnL40u7nbVtNAxJdIhQBXCBfcO+4ryjflBTGJONOfZjT258+dWDL3/9zmt/DO/3MvRmqICQJRtAqAOiT1kmxAoAYLLsoTk/gykMnGhUz4xHnBlYIKZFRu2pf51h6SkuehGqdXNA2z6gvZ6kpgbTxjCBazhLGZarkblsoiQGpW2cjEGpFDCv57rN4f/TQNykszVF7DYnBTb34hATkhIBic1b1vQFXzTtDcSHGs1EkoKhSAYrrGGRLKaQTEYwzUkUdnDwNnz/t7/zrXdfC0f9RXz8g/d/MKRxEAKAwHJ4axH63HXd7duHFGi7u+qHCCqhquOYNjtd1QoH4Jyxs81m48xLFG5PYtaLs40OjsVDUlAix4aqAgVyHce+1zGs4eSl4Jfx5TdWm+3ZmC/J1y642MV+GGJMBkzM3oe61qauzJwk6PvOFE2nnpL1ajWmvtvCbrdt10gEIUDTArPr+0GyxZTHIfWXMfZj8DXE7LwiQVVVaoMGYGdmSRU1oRg5cJI1aUohBwrOOQDMkITAiuBvNhAIIRASOXLeCeSUMzCENjh2/dCVbIHImSqIopmAkSogKoipUQn4iTyhebNkKaZSxi61aSQYx8SMBiQiAIoIRK5qF6pAUnoRraoqYoxjpkBSVEJlFm+bLG20TCfCSanGFECLhgKy3cgPnsqCZ47ODJrsaTkTygIFFLOyNFwP9GdcP2d+IsxQkd2EzPYMrP0Jnh7U+9/Z/mwAEwQDCAjEpAglN0XZy/LMBSrRyUu6hIAzBrP/8yZ6BTcnvllwQU0UpxZgu0byJlkwRFRCRGOa+S42OV79zGOCd8Amf9w5HytB5ERMewaRKPhAoYdOuF4pw+9vTfmTp7SyYKWKE//h+mHAfjWcgf2JIwNU/LtsMlqdM9XpSeO+yDZ1Xl7DIwCARYllSvjngyYVayukgZnjdr0A/n3gqGdeu398n/sEzx43AKyfeaiWlXeCaW669f28jhcCTy887Maxv8/P35qb2ISqppTAAGb8qvxSRFTEJu1zm8BNBO8cwiTRosUdUPJkBU+zNhsi07UGxN5hcN94CABkbKwiuaqqlFK0OAtm2X4hKChyQdBKGi+Sc85E5L333pfLZTBl2yfwRaZdJhb2zbs3z3xEMwuVL2fOAoTogiMmw+njAIyZvffErAiipFiQPVOzqq4EQITUBEQYiR2RQcwJRICRnGNGIAIwcmxGe2xr9kspi0u5LJAMQMXXi0QU0RA4g7IROibvRNSybYeeiFwVCFTAsikBMvF0Y0UKRUhsj6xPPZWmRsiaDVBKp6eKgIFmBQZ2joQAQCBVbUWeCvFKVZmInZttAWb83AwZkU1AAFBNLWuSpHitKLovSxDi7PAKAIbgSrmuCE+U5wIAOQsTeXZlQ5WUVATi9RJf1lRzDhwranE4LIvHRHCd271LJZGARFRFwRTIgEA0S0rIBA4nGWsmICowYTG4ITRE6odeQUXF0LIzioEdEVRiRZnJekpEA6GvahizGjlXkQqY0Scff1I3oakbJBTTGKNz7vj4mBm3281PP/hws9nUdTXKuI3Ua5Ro8OATRTw4PDo5vlNV9RtfvPfu8Cs/PPybH/3oA8lUB5eTFn5/cTN4JrYrCz9kUBUkACykRTADU3WMKUmMXV37d77y9pe/8qV2vXzvxz/+yQf3h6ETlZQkeKyqOoSq8jVhSCnFmDfDeHbWLxpwrj44WLTNYrfbXl09SXEbqgORhRkhWddvqxCOjtbeV96HGONms9vuLkU0VNQP5zlnGEmQgC8vL6804W4zqtCiOTTBMceTlw7eeuf1X8Jv1YtqvVqkvgMwI/zVf/TLp48fP3r48MH9T46OlgfNYug256dPnpydbi67L37hDQqhT7lhV7XLQ2DwAZ2Pw5hTCsET6NXlWVVVFgJexTiyIwNDzZAen66Wh217oEBDkmxIzvdZPvnpR5eXZ6/ee+Wll19+fHp6cf7k0ZNHmsajw8NXXr53fHjoq+pHH94fhlw3lecFaPsXf/aegb711puHR8vNZkPevvTO6yG4BxfvPdl+4KBaHB3+2j/5xte++frF2fA//+t/2xyCNAaJJEYUQGLHDgGK6qBMPRlQmmGL/5MqqoHjsnKV9nvwSIWaBQU7Biz9/6qGNFf55nDJO6esQEVmGJgmkdPPgyAwkYiIxBJ5kEciEDAgMJoUAYp8JnGomhqmbAiYCRBzHhgp+LqqGBgg75qqWtSVxPQnf/SHp492C6lJeRzHcaPAkzs3eq5d018Op+9f3Fk1v/SVl//b/+q/+cK9l33W8eJS+uESd7cODpqFO8tP3n/8/g/f/+EOtn5N0GV2+vjizIjbBbuAuTdWdQDDkB1nUdAMY99jLI3UpjLdqRB81aJpBrSmbZrl0eqoWZy6zdWuH2IVoF1EoHPJPVI8OXrt29/+5umj7V/+yZ/95IfnlxcACaqG5jZ27AYzjIR6Bunh5QVjXv4tvHTn7i/+wjtHB81uN4SqBdO06c53nY6PDxb3xs2PF4vD3/rn3/3N3/4P/sk//T//9I/e+4P/488+/eTy4HAB5nZXQ9/tIAKic96Dc6pa2KYqel1ipuLvWzqO/o7D5rXz7zyu2ctPrzzPve5FZ3vRMLu2tv2ZJ/x5olflI/AF1/M5i6UvuE9EBIQKgqJoamIK3gEQKYIPAZ1677dp8z/97n/38itHX/rCF7dxm/Sst3QVP7YqPrq8/PB899GDD7bpfIDdbpt98FXb1m1rjgwhSj6/ejKmnC0F7ygo+QyQVYTMci5eSoaI3gdCN/Rxc9k/enh5cbFjbi+2mygjOuDa1as6VAaMUTvK49Gdw3a9SEldxV9drNkIgZhdU1dNK31/KvlSc5djn1NGq6pgamya+qEfxzEZMAGznzQaAas6VI2vY4wxxkwHy6XDZoCcBk0jxC6vq7BcrZzjRw8+3m5jVYFLIJzbxZKdp1DlcVCw7XYYI4wdpAiqQpgdd86xEixXTRypG3aa4KW7L7/0yh1fjR45sBMzkYgM5KANQAzMCBoFFBy0SyQ2InAOHEJw5FlDkOXahQoAYIy2PnDrgxVSvdnmi8srJMp53GyfOH9Q140nG7vLh6e7OKRlRZfb08NF89Vvv/wvhu//8C8f/t7v/mB1skDCfjukLscqhhDmtXAGcgCgOMXcjOoR2NzTYxJRCWa1QmNANROcK3tQEkQHqLSvpj41QIsA0FP0hafhYhO7fo/O3UZggFjUnQ3NAAlLPVChMO2hiB6Cmprm64QB4GeV+RHBSuI3LQ/oiIiZ/KR6gMUwLO7vCb54HQEEiHFEQo8+Z8kivvI+BGIYhpEIuMJkVrX6+hdXr3zl6J/9i3/8yhcPd/rJn//tDz69ePCTj89Wh8FXy0HG3ebCeah889Kdg/W6zhDzGKmGVbtUDagUd5EZVNOuT7IZFwdtzY2wy/14+un5+ARITE1hNLCkahyIAktJYAnaJdx5bXnvC4vmACOeJrjIUZK2JH53NfR9R4h1u4hjHoZuuVwz1ZJxczVcXV0R+So0Ztj3w3IdiBUqCBUzQ1UF4ljVhAhnT87GAS/Or64uIWRwBjHm/vJKIK3W7dHt+s1XXx/zlVoUwWHQZFmS5GhjzAjAdhUo9JuBHS6XKw1q2UQsJ9Go2CMZISIxMQcjM5PlskXDYdOnlBBQNYMgqiGAK9QFBTCUpEYg2QBl5q0gIEMx+xZV0DKsRAAQ1CALEAJTdN6QGBmLoErSWEryvgoIHGlEAcfskAquAlRaYBFNJc1cGDObeYuFy7SvwF0v9Ta9EJERSiwFMFf35o6U2e7DZpNovAY4nsKG5sz6JoZFM7hCSPvu35sAU8lBss0MMivbN5haUYkv6mAKZlmnKTarKwKCiBZVHiA20D3+YGZIuG9semqeAsBcbjEEmJpbSpvvlJ4TojEREaMhSfnW++/5PKSw/5SnE5OnBIiuke5ZFP16siOWzj+DSbkCACCUNYBgjyCiotHU62wwKZGRAvJcHzC7AfPPqOX0t7DvTrP9a2+oB84Xr9PyXG7MdGImnt+yfyUy8z6HJ6JJIOeZe/IZAdH/D8fUQvh5XroHg+BFY+XncuynymeNnhdeFTz9FZ6ZbPu2RxExM556Iaf3igpMXWNlwkxDmKbLmES1ymRmT0hEbmZazVOnIEqFS3Wt4WXzVU3wzVMjQ1VzzuUiZ9wEAYCdw+lW5/LKosKOxWlxGmkTRoWITCam16N1mvvliyMi13WdUkopFdWbcnlSuvrFAID3su4wUc/sxniHMsR17y6EhkQkhkzsiAknxuJeK704FM+QMBjfmOxqUEQEZ0wXBKTIHRWmGTGaSswxuMDOIaJpBgMict4TYsGGy5PSYqhXFp75D0IHlBVoDzJO7bkIe2E1ADSdILyJg1o6KuehAjPNqQyISbqgiF8pPhMlFZGCazy3rC+l882sFGJmjbw9d3MCLkVURK8XgDL2DMxg6vQrQSECgCLRpPuzb7RSJCSddp2J4g57AqoRggEjYTHenS9gGkNogkDMRGWtUikjyptOabv3VRVaQBJRx6Gp26FKfT/0cXQAoTIiVwTLnHPBezNj9gA4jnEco3Nu0+2MDR1VlVO2PvWhD4bS9zsAPDk+ePWVlx4++LRHG4YxRwAFCuDYUfGXLJUhK+CVqanmKUYERiQAUlMlR1xxjpkJjg+OX3v99eX64MnZ47/4f//yYtMftg0CqsggpppUmIlFNY0ppxyQomo3wNXlBk1wvRiHIcZUVZ4djmOfc5dy7LqtSts0TQjoHJs578k5NhMiTUmYgRxXVW3kcozdGDfdkKMOw9j3Y8726MlDciSajGARKgYlxN2w+7Vf+3VJEVRyGi03COCI16v1atHga4DIQ5K82Q5jXi5aF8LhwVFTtcPQ77ZbyVlyTin1fV/VFR403lfOs0MC5yCjmolqVkkpRknEwdi5ulnY4erwqF6s8Oyi0EEl55TzMAzDOCjyYrESQUkY3GK1OMzp4/OLs5w+fPX1287Z+mhJLE/OPskyhMpJtNXiRAb2TXPrTvuv/tU//fM/fu8P/p8fw+MINYQmkDIKmRSZENrrA+IkiDvFYYh8XSLcr+vXBSoCmd6BqgamIFjMeYr1AFEpf08S7HNX9ec55ioITkW6YoFR+K1u2hVE1QIvFoujoyMz67t+TJEYq2a16a98QCTcdF3fD+YATcd+cFZZEjfibjOAABu7ymmW3Bt6Wi0WZ6dXQHCwoO9+51vf++637xzflW60nNN2G5CYabVoo6Ynl6cffPr+hw/exwU3R/VqsfQW3n+0q2vxnkm5RwnI6hQARIwU2CMK5pQZGYGY1RCYAEzBoNudG+lqdbBYHqycN1s0Lfb9BkBNUsxn3sHRwapdhLZav/+jv374yWa7JU8hm41bBDQgARXVmHKsm9C0VZRYh2DsHl+c/+C9v33rzVcqT+TrNI7bPjEiE+7GhwrC1uM4rqo73/zlL735hTfefOP1/+1//d8/+PCjxx9BFXixqEbNplQoDAWnZqau7yYvpaKySFaSzGnds3mN+6zn+9wvXxxjvJD2/8wbX4hWPf0R02v02Ze+8EPxZuz8Dz3mNvgXnPG53yA+/32fv1VlAS7xAwEIWlYTFSQbRxsfZrgNv/WfvPsf/db3ju745iAlODvffHK1u8w2uhYvLh9d9eeX3dmDs4/GPI4yEHEdmmZRu6pKqt04jDFebK4QgB2yI+ZsiKpZLROwmaqIc847X1UVAPa7YXPVd11MEcxrlAxOyQA4KyVFM0iISclxDR5RUOumroI5AO8a750jNIjDGBFGs6SWcwLNoyo6dcY554yIlXfOuUkT0wyJnCMkZFexwwO/WC/XaURGF1xoXBZNYBj7nCF2mxh3YBkWLQBSzOIREdmHmpnHNKQIKUMWUAWVjJirCoJvzFM/jNkSVHB4sjw+WXW515QQMpCIJB/AOfAOiEqclUsS3i6c98YOg2dHUIcAOTuHPoApiIAo+GBIRoRNUx0ceoMQGq5arJpQcYXSnke5vNhYHNwx3//0p3bHL5o7X/7aK8v25Pd+9wf9OJKhgTbLmp0zMJUIU4x0cxQ+PdrsBXpwiAQ0hUMweQIWWbvpRCWGc581N55Jm+aupfkDp0TOVCdt2Osxv0/wC9nhZjxnhYxeZB3IdI5m92nhC69kTtdt/jsCMxF6Ii70iRJaI6FNH4jFzecGceX6bDElz56ImNjInPPEJJokqyIoKiAcnSxf/+LLv/DLr739C3ceXr33aPvxgKcZhuO70A+yvdq6wMuDxXJFDM6GtN08Tjp4B8TUdR2ia9tKj9emmThLjlkASRxju2yvNnlzuQMEM9GBQBkUDUYtuAtDPO9A4J137r7znZf9anx4+dM+RqyUCYduN3agIyfhrNIApZxKMjIONgxjjKOIMIV9PDzGwUgO1+3R8dp5syjeF+s0TSnX1UFdiYaUY8wJ4pBBgLwLVLXVyiEYc1LKOZuoimoySWoZ1IqabE4x55xNUUVNzASLE0EeMhpyYGAL7JwnUzA1IrQpsDDI4PSGndyUYCHj5AkzJXcTWDCvvSbTUy1qwrlIioOWSpwXQiyIj5maTKdx5H3FiBUaOHIOCNW0kJC1kH3mvWIaPQSGarqfWkXl6ZrsNOcdBmB7bHX+p2k2AM1ULACYHWavVdefpYnsMaznZwQCTuaC+9tV5te+rcpmZqaVPNfmqv2MLNP+tDfQpPKpaHhDy2ieQrC/zmd+KEmflbMW3ZDymEop4oY6toEW/HqmaV5/9lM/TxDV9SKDM5ELAEx1SoYBFdRm64XrImu5D4AzC7TELsVXQmFiySk7xj3rqTwX3CNLUyF/Us3an3f/aIhABG4k8fDc6jJTuG4gX2YGIKJ4gwpTAFktJMnyuA0AZwWnG3f78yNB+/Ez3z186nn9/Q93DRXND+ozwCMsDL6JsXJDwunf73jhRdONXeZnHOUOPiP0/sytgRm9unnOydiNCruzMLB0/8rpj7n1bQ8IYTFmRwghEDM5BoCcc06iKui4CKUXPMgxIaGKJsmw980tkGcR8EHcz5z97rU/VKWM7iJIn7Mw55Sy30dRZrMh6ySoTyRZMhbLvOsDJqLr9dIDZpZSRoSssn/ce2hPsZQ4Ye9/kFNSVRCZsB/nEbHIHxB575yCZcnXDca4x3qnmwig+/h4zxzCMs1KN55aEfdDQmQyUkVw3qNjoKKWXlYfwoIKqaqIFZobgJta88q9M0B1jrMZGDAhMYmqYTG0Kk+ZEYEAc8oFC7NpoShP0u2/hcEEnaCaoJKVTmRCVJt69wABpnoCTIhSKcPoLKhoSshKRmVPADPvPCGKWErJTDWrqsLe7EIBrOhzik2Nkwo8r32I1ybMNsH2TCQAoDC5C9q0S5WbrgpopjxzGBipKF8bAphkIc+ABAaaddRIZERGDFUVnGdEjDEhE7DzTN67qgoppZiyC4BIOefddpfGWPR9mJiZF4vFSy+9tFgs1YQ8UQh1G9arlRkq2MX2sr04m/ZdjbdvH3/n29/cXsXLi/7yYnN5dRVTkpwlGTMBgiMyuvb9YeKC75kaAljxKmbMKXOAd95+++VXXq6q6uL84pNPHpw/7tulq9tm7KPpKAKac+q70s6WYhI19OyZFPTxwyeXZ+cnJ6umIe/9wUG9WFQKMnS7Yei7bpQMOeecVSdDBmJ2Xd+NY+z6oanrOlRZJGdJ0XKWJKkfUt9nMBWFYdcPqWzXQAqtAyboEnzw4U+8C4umOT5aEVvf7ca+I7Sqqgng8dV5VVVERLjrh369OvDeN6VzkKnbXGaCWkPK1Db1ar1qa2eaxjHnMS0X7RCjwYBF6EBUsghjqKq6rsT07PzcwLwPjmmxaLzjUfLldstjahZH4yhgOYT65PClw/WDnOzx6eluN64O+ZsnX95sLg0lynboxrHLWSKkysPKcnX75Td/4zff/e63fuWv/vRv/+iP/+TqItauKSVJEWX2iGgK7BwSlHylMJyYQNJwXWhSQBWzSVh0n5DAJIqpe7gdp1BoWgd0BngB9tHHDBKXyYv7UsA0l0olklypmk3gOyAgE7MjT8CkUDxxPIMb0zj2ER2u1weKacmLZuFdgMtdxqIpb8iGTJhGRcOmChCt7yNldhywRhDtL2NY0u3bR7/xvV9/93vf+oXXv9Ttnoz9DuJwslqu2uZ4uUaG88snHz/86P7px0+2T2puQl0ba7ftb93ygMxWQe0b1grGXoRl7PoinmNsREKoho7bxvvKhZpC7VwQdjHpIFoB1s7xYsVVXceoCDnFWAVYNOHeS3ePVi/lEf7wD39kI6yaA83+qhvAGEDRomQFMkxgHJVT2zSLgwViOr/oDM5SzqtFfXx818SG3UjAi5r+6r0/vX18dPv4XrYeRU5eOnjjlddundx6++23P/no7F//D//L4/MzVKeZSH2KMcUEZuwI0VWhmtZqnVjRAGA07zj6TOz5FJpkT//bZx02h6g3fgVzZPnUcaMlEWe0FeypYiTC3nbzuXc/NSaLnsgLPuQfdtjNnz6L7XHjBdcXdt2wNaVAarGPvvLMjGwGwASGGFVfe+3ku//8O9/8zte//q1vfPWbr23sz+taPj59L+t4fvVwcdCeX56fb8/PNk+6uD3fnPYxhQba6tBXLtRBEHbb3cVmM6SBHRsIsilI1piHwbKQAXjHzGpmhuxCTHkcYtflzeXYd2kcIeZctwEYxzEDpGzgEBRScOQr6sfN5mpE8MLiEQI7ooiWU8wxjsM4HB0RojgGYTAByUlBjFVVgMA7noUmQE01S1LhKX7Tw4M1I+8ux7EbLatnZkyS05PH5whah7BqPDoLrXmHMWrK0cycdxxCTCAKCoDkCFnUACM58rUXgSh90/Dtu6t6aVUNccgASS35CkJVVY3TIm5nOYuWJNz7UFek2dhxqJxn8ORSP7QLD8iEnglDcGbJLMfUZ4lEKApEUFU8dP1ocd0s28XKk5GOY0wffvRx4BqHwFHOAAAgAElEQVQP6eBkdbR+43f+i+//6Aef/NXf/A0gLFpP5tKYkBCM1RRxKuhP8wHJpnQRwVBsjxRNc7bQwmFOuXGKP20ad5PbzTUia8+M4c9CqwEAsXAX1IpbphoA2TVa9FxWB0QTHaZUWCbJ6FnUFAw+qyl9ysZpzrongjxgicTmBi1RBdKyMc1ObCUbnkuY826EBnXtTcDMyBEY5pRzjAamYE1NoeU7t2+9+/3vfOvXXjt6E7K/THS1iY/Odx93GUPjlYKv67rxoQWDzdh3GH1dBR8WghKTgqacR4JqsVgQqXPJ+cxsChkM22axxU1OAgSWABSD9wAWVdSySoaqOrx9/MVv3Hv5nbWrh81wqW6sG+52sR/AMiBWMWmMyh5yzlUVVsslO+y6q/PzTrIxO+ZScFLnqWl9BmsbV7dOtGOCtm1ElMnlKIeHB221Tod69XC7ebyLmx0IIEOKudvs0GWgUSGLGAE5cuDAE4sDZj5YHRIxmUtDlqyDRNEsKqWvooyHEpukDAqSc0Zj77lItiOhgokoC+KEAaGVXiozKPW0Mn6LqNpUc7uhSm4ABiK2T3/UAIkUTCUXLjpSyapIRDz7uqnMzJKaGhCqmEwF8euVHHEO9MsvbDIhB7yOdSYECbGMfQSYDHCmYVsMXbGIWdmNBV9v7IMTyjD//NSONpOWCl5VLg9h7+UwvwVAVfa2DmqIqFj6lgwQkGgSj6ZZXHwK7mbAyOx6YZg+eU7P92yOp+bkPM0VdOI+AYOKXesLoxFMOf9U6ZxYWiUj1BmhKyneTXH0/a49QTpExY1QSwG1xLPzDmp71XMDUZnPMV2tmgjKHlK6gXjOD3qSsCijC2FyMzIrHI355sO88BBMSl5TxoQ3BiHc+HlCOuY1FwEBJAtNqkj7gFoN8gsDE9y7QN44/ec89pDo3+dNLz74+tNvAHY3VuKpBgJPI0TXMMk/+NiDu08x8Z7+89mLvqGVvj/Jzca9chT06im5dDBjJGZ2jgptSieYnBCZ2DuHiCqFnjTtwhOKglhV1XR/bK9pOt2QQmhCwpL2Q0mxAEodxjnGGV3aX9X+++4vUkREpnVxSsVKtC5a6DUTF6VgLBPpENlx8J4cMxESoUz4LJipmmeWLKKiUujRpQH3OpJHYAQCQi3qXapmSojMZCKmOoFQRbTLgTE4T65yzKSgWdLkjbFfKqEwh8wR8uRHWJp90Myc80ylaqdgNgslTKQyRQXCUFeAZAomRgphcjkUFdEskqQYcDByaaIu2S+SAyLPXJ4LMzl2npmJRJXIUWl2Z0Jm3ZPviLz3gJMuqRaaj6lY6VQURQNGDm7SF5ysDsghETAqEjhGptLsJ6pZTWYeLEyancTTtyRghx4UJUkes6oykEqJ5IAY2IFjRkZjQIRSoWQkh84BMaAzYiAyZAMyCLUzK631Oi30ZjOld/LULeDpRCS7fvZGk1xiCdSy5iySM0jxPUQmK04GaI7RB0ZS1QSYvMcQPCIDYs6y221jSgbQNPVqtUZmZiZiMwl1WCzbxWoZqsCEpjqMQ1vXcez7rktxILTlsmmXrW99s6zaZXjw+LHzpTUczAwZmLEQ5ZDIREANGNijoYECOWBnninU9r1febepmyePHj989ODs6izpWDcVM0vOOUvsTQQkm2TVqJJNi6ZSydCS5JQRMztsFtXR0SpUzlDMBBDTiGAuJ1Vg52ukaky63cZ+tCHKZpfUgkEYoqYRQUkFh37cdbt+jM5xUi27FxFgIckpqSGSgVnTVrfvnlQ177qrTx98cnb+eIjDEIfzq8tCtsuS+r4bxp4IiAxJkXS725ydPxGTUPnlql4ftquDBXuXs/Rj6sdYVU2SrKrsyHkHZllhSJpyruv6Jz95XyHXTTDQTx89PL5z7IITg24YxhSdr5AwxgRmR0eHdWhyik8eDZ8+vAIaEEgBVusDH+osKuYNnQL1KV5uN4MMxydHRy8dLI7CwUltmPp8OQw5Q14fLZR1HEfniZhVRLMREBmTMoOLIgpoUlyoYQ7KwLRA8kYE7MDYgKSsX8BGntk7JVNQKc21NwAsgtJqBmhQgHAzQyx0UJ2cqE2JgErqAjrBx4wUHCAAUaiqRbsIFCxav+l3202SwTkkZ6EBYDFMOY9iidm8t/WiadsgMVdQdVdbyQRota8sA6vTXiVbTPHrv/jm99799m98/92vvv2FgHZx9nDsNwhpfdC268o5PB0e/vT0wx8++OFFvugtDjDu8njVby+uLhSZiDyxI3IMbeXqNjjPwWFT8bIJVQXIKbTULGlx5FZHYbF2VYvm4mLtfeXYc7acNbGDENB7aupQeT4+OGiq+mR95+TgHkH7+7/3586grQIIWMo5J0ABFCNRhNJcVdXNcr0kx+M4bPoolmLeiuW6rpBAJI1xzHnYbB9kGZDJBQawJKNAbhf1q6+/8tobryjK7bu305gur7ZE5GpHjjKoaqoXS5mlYHXaTYrpZNluZ2kTKwpgDspjB0QjQADUiTlb/qMpgMfy01TZRgAjs33AWvh8Zc4WIuyUhNB8nonxp3PeagiANOUqkxEHzkXn6x8AEJAMCJGL9ZMZ4uf6j66H9/XPT/+1XDqiIuq8XACiGgGSIRlQ6TdXBKXrdsNydgYgz7X3NRjrmEEBkNt2YQDGEhqsWzdabtf20mvV7/zL3/y13/yld//xd9546675Tb0YFIb7Dz96+ORBFzsOdNFdbrvt6fmjLg392ANTu1o3i4YqJ4a7brzcdNtdv+sHHypCDCE4H7JoN0iOBlklqwqsD07IhW5IF1f95W686vLlduwG6yN2o7SLgChIQgTstAoaKvABCUmSdts49ppjbFyoHTk2sDzGrut2XS9HR4QIzFieL6AZqhGT866qvQ9ApACiZoRInFWiJAUlpkXVpj5dne8uL6+GPmFRukHpYyLOy1XdLBf1YtE0DSj2Q4xjiRpJDHddTAqiKOaykFkAcnW9YF9lSet17ev+lVcOX7rXsOtzOhfdOSdNjW1bee+CZyIz1eIDyETeuyows7aNWy0rIkXIlTfPSJiCw/UyHB+13imTAiQwzZLiMJqoQ5QxyTgs69AEamuqKjTISUYXqF74ds3Norl769WUex3k0dllVYdxhBjRuVaEyHvVBCTI0wAzKFOVTNmM1ciMDciQykieVXSKeIdO9BTb48BlvqAiIM/o01wanRkvZeBOW0FBF/byW9d16DL75hfRrP5R4qKZYQJIQIX1NMWtaDLVy6ZqdBFctClvLLEZ4VwwNERksNIihOQYCAyymRgkxAjX2t7Ihe6PCqUmioBYAmI0tIP1YrPtW98QMGMYtiMjpThWKxjU/tF//KXv/vqXf/FX37rzlr/M99//9CdXYx+NB/FdzEMe20VYrnwVSEbpLlK8MpK6rQ4YF9vLvD3PcWCHTRplfbjKuSendetX63bX9W19GGi5eRw/ef8SRmUhJvQOXYA4RsiwOF584Usv3XpjdevNZTjULTzu9JJrQuTYaxoQsjOlmDUmcb5tmgYZjo4OUhofPDrddaqqTeVdcGMcchrbBbsFJuuPT+rFijbbDTs4OmoCEwOO26F2CxJCcZyDJt6OPYCiV8G0HbrD203KKSVVZXZt26zbZuW4ZnJEHoEdV2nMKWtV1c77LGoAQGDJLAIQGAAzhDqowhAjAGXRHLNJwU4RBbFYhStASaBKtA9FVVhnwGAGsGYZ8uu0ujgsaemUAyScVFy0bFREQAhkoiZYelvMLItklTSVTQ0AHLImKVmAQ2IoaSRKMfO6zuKxiHIjUJleRb13klAuzKE9CDbnaDq9FIpW1/zfRDEi5wquoeUGIhESmZYhbKrTrnydX04JOVJRiMdCx4IJyJq7gvea5oSGRea0NLDoNf8IABGZiJlKu13pLSidLlawuD3cNe1nBa/Da6evAr6VZadgevP+byww6SdPuWyRW0YDVCMt+lzlGmBCMAEmqX4mIANDM1HQ4tpGYFREWW16b0E8dSJHTc2TiDq3I8zXWO7JZKBdWB/TeENEMFUVKyXaIkSJeE1qECAAkynzw9JYBGRqhMRIc0JZLOkAJrH68tBQ5dqjcfK1LMTYqV6o87OYzl4G2XSJP+/q2+c83FOf/Aya9hxAdhMe+geiV8+//SZABs9jvTeOvfUA7qmFE8noGla7Sb/a/xMSCcieJjeHmVagBypLiyqomGnh/c762LMo+yQdNUHOVDpYygNGMLCiXVUUXsp+WxSuIM/XUHbAGwJYROScK/8qKsUwbloRVdV08qcwVZnwL0AU05yzqQRw4BgACmureAaDwdw8vX940wMlpCkOmKBywtJ7Y4ozCE1GJa0rWpxEAMSTu8XUuFGm5ARdFR54+TAiBGA0Kf7Fe3UwmHFnRICsIDpNPzRDMyqtOgSkMQsIQDISdEBsRARKBVA3moRQinMhTsav5dsCi80Trgi4GxS7ejAAJUBQwhlqIwMo0lpqpgAyPUQFAFFRnKS1yg0v8dOc6CAZl3WmxI5qAGWOl1hnr78ooKSqM6ikAIYkZmJFsB8Y5m+AN5IlQyo4KYIaEiIYFQcBm/AlADBGNEUyYp1E/a080rJGT7NjsmPDaWjsdfwKZqyqcwY07SSiJjmXLYuAcs4pj5U6pOwraZnAuKJF1w/9MMQxZsl17c1gtVynnLOocz5UVZJaLY8xGmK/64rTeoxp111plpySJDEFz65erF45uvXw4emQNwfHfLYTuAJwBg5UDEwhAwiYqm+qFEcAkASQAAhETBTuvbx6+d6rta/6vh/6brO93I1bX7nJUMg55wLzQEhQLDMVTHWqaakhAyggg6hlMTVUtZQE2dg7ZG5qrwpxTDmhCLJzhLWv1xyh3/W7oUuSuthpzgjYNC0RE7NzziwnHbOYWomPAQzMkSknEctwdn62XNVdtyG2zeb8anM29EOVax5c3w+3Tg6IGUC7fic5IWbRg7apVfXJk0dPzh7V9aJt26pdkzdFIQ4Y6lqdDzqkqKpmGsy1bevYwZi6TRdT7rru/v2fAt5znmIeTy9PT8bjtl0QUxdj7DrydVu3KcrQ93UIt46PEL54eb7tx4thAx98cP/OvdsutM2qBlqSi8YOiMZxvBguXnnjtQ9Pf+SgfvXeG//hl7/3xpfu/cUfvffv/u0PoYPLzRVkAlbwyM4jcRqyJlUxJueagFAZqM6Ku4bFQ0oNFEhhopADOjWEaaI5KIowuWi3P71tYcl3aF9vmHyLbRaLnw4perszlXwGsJBRqbBjVCRZQhONmhKO5nKMMm4u3rzzxrDpN5vNkMA7qAI4hJQGkFD76ujVw9Sn998/cwJpaxKlVvaVj8MIH8J/+t9//40v3H3p1mJ7cdpdXHjTk+P1etU0jWfmx/Dkyfj4SXpykS4yCQY3pLHfdVHF14vHD3ZNlagC76ipqkCVkj8U6PuYUiZgVR1iTJLBhB2zE4CccxzycOiPzGjMMQ5bA63rqq6bZd1UPmjS2vkUI2kdex27C1+BJZBhIPPLhU/aF+PIYtQas2UAHhW3A+yyI0EH4F1G2AzjTz/95OXbx8um8Z7R0bI+2P5/tL1Js2XJcSb2uUfEGe69b8yhMlEjCgAxECTRIMWhyQZotG6TaGqpW03J1DKTqTdtrYWkrSSz3rQWMmmvv6GFFlqpW1OrJVGkOGAgCAIgUKjMqszKzPfefXc4Q0S4uxZxzn0vqwogQFJn8aryvXPPPSdOhIf7559/3m+/9853F+3T0+XZg/tvLJuRZXPniF6/88Y//Ef/9ne+9UNf//M//saf4zkAnL55tDxZba53++udBSttWQEGGzl2pJpHgzOz8rYwJ9iAQypaJt3bIkBhfCsbadN+ZMUHBc9UT2D+7ywyMn/k8LeDcyK3zj4Y0fk3jJf+eitVacUXJJpTpT/x8ROcS3P+rPw0UgB86HZNM11E5+5SRhPkp9wsF2NMIkLMHBpm8oFXR03Kw9W6j08BAA/x5mfbr3zlK//RP/575K3vL9b9+vx8te43692L7X633e/qtrrab4c8bvp9FzNXtDg6dRW3qxYeWXW33e33abcfh5hyNkMmJxw8w8WsMTNnYwqVr1yowHXXDS8uN1ebUZUFVT9YN2pMpYuvEKUQQA4hoGnhvQM5S2Qgb5WZOXhnjpSdY0VmiHNwjBCcKqkoNcIsKlCEzIGcd57ZeYOZKpywI2NYYklRyBwwjkMeMI5jzslgzpuvQYCr4Dy4chyCc1Uc4zCmIY0IqNvgo5kTuCZjTDA1SmokmUBK3kDkcXremObzc9e2WdKWMbROKaD2HDypSXF3SgtWNTVkRmTKTKmoAphG0uQDq6mDBc/L2i8brn0Y05gyM3vRSmOWbAWnEMsmo6u5cuxdE0eNcbfp11e7xi9EqvyFL/4K9DPepW++9+7m+Q6o6uURu5qNzbILQTSLKk+kq4IgKUon6QPaRIpCpDaAxFDOUT2E/WVNuKlUi4l0XlZTwfAhQXiY8DSnlmfeBKbL2IFBYiSzR0yFPlH6qPG8HXARk8Bh7ZKCphKfskZows2KlZmekiZlhwN3AqVtGpFZNlI6NNgtAjXkqLygqUZ9tkKYwBQCrl9sjxdHy8Uy9jJ2qa0q73D2yskHm2tE/I2/+da/9tWfW5zz0+0PH73/3R88epLh6+NlJt4PODpd9P1+v+t1IKQKcRmsqbmNQxiGdHmFMbqqro3qPMqiasbx2mBJbMx6uR4qluAsJ5JERMyVD+xUkpiADUd4+Pr9T3zyPi27qNeSxB3Dox5jlwfI4BBVEotCRLMhRYAQ09gsHNzQLpEEaQT5FCpvJhEjBakXoDpXS1UejMYqOO/EBR6TSsrdepNHN/aWu9Dvk1GGgxJGGBSLo2W3h8ZIxt5XddUEv8i1bdb7btdv+y5W1u3GXbdfLVfBB3YeKiakZnBgTABqqWSDIeciemswmKCk5OnQHsSmuUyAm1tZYp6O+jF0kFmy6BbJJqeMgpYyMbkpQhGCwiDRIgBVzaVllZZkP3v2RMyKIhBPKOEB2bwepoVzQ7wp/g9Kfb2Bgp/lrg43eIvKRDRBcfOHp/h4AkiKhspcPUZEzuAKElNK2iYqTxGppJlyRhAr9MZJSf0GXpqGY2Z7lGoWgxGcTvl3mvKMVhhzoHK+YIaDyrqZpGtuHQQQqSkXnll50BL7EsGBmIpemRQhGsLN1Q7gY4nZrTiMMFYjVgimsGEaHhBKFfhkwbRw8KdBs/kn6NZmOw/DjL3bgbp6cDzK2ylAARd/14wmitc8mjpfQ9TUAEeGCdac6WxC5pwjJpUJcjLDdCGQUskHYoL/ZrV7zKwTPeQUDvWDhxH+6RyXD0+8v+xHbw7/F58CYAaJDl/5UR2vv/TxUSbXS2P0ccfh229zrGwuLSjXPNQ5HmhZzFzS+CaaLROR6QwlGtQgIqmAWeWOPtJ+KKVUyvfKl5bbL3CJmbEnGCSrzDp2mMkdBiilG+tVAF5MkNbh/s0KNVWLKtS8V6Ne1LcxuzIXoSQiJhIlOnFEFHxgZjh3W529cHvYJv4XZqWqspYKEYxKp84p10CYcmdKIHaFY8nGRDBTwYS9pInPSuTZz/ZhfjJAaWoLNZnfMoWYzUgEwMxTo8nmTdXI5NlTf7GBMLKqMaFwPCmQM5jApOB8UiBuwBEcEVzR50hDb6omElVAiRVGIEczD0lLp0SjWdGjiHkSmDjnDJpi2ps04K0pUOaGTqHR3NGwPKMxlOiQqcO8aTGgVCBulFonkTxGkVz6jKiq81OSY06OEAhlCpSXrqUcVJWKvBrAzlXs2DshMWeAI1YynYI7nt2x+UmNVQukRWQAF0+r0OtL8WWZFw6WTMXASJIJUEIUgJJz5DzIcVu1wdc1L8aYrq+vx1H6iFWLGFMVQkqjmdUhwKyqqqwkktfrK82yrJu2bUNwm+01gyTn2Bcl8tqlcb3r19fXY4xf/c3faNtlHPM3v/atp0+exl6JHIxUwEQq5OvG2MhZ3fh79++d3zl7/bXXlqsVgb729a89ee/p0/cv+Rgc4Bh11YrTGHPfD227MCUTlWSiolkKf6f0PjKDCCRrzjnG2O37IKgbapoQAj/81MPNpt92eyZerY4Wy6UoyHHKsR96E8sYUxr7TiWjbXeLxcI5btqqbgKBhyGOYyr2hh3IsQkElgXGyJaHNDqjbCisiSiah369ieyuTk6Pgw/9OO673pz5KoTK7/b79eZ6TNmFtOt38iJv99VquayrhsmRwpSaqh36YdSxykOLqmqqhoj3e4nx+eby2cXWyIxkGIbtPj599uL+K+7k+MRV9dj1z68uIC+Cr4ILXb974/U3Hjy8/zfoi+2S/+zPvw8jSVmiQpld64KffCRO9WrxP/5P//IXfvZzn337VUX87g//VAP/7b/7lb//O3//m1/70z/6w69/789+AA3jJnfdBoD3FXtnWQFREleV/oJT2gBSBCS0KJIUhNymBBrgQQxyYAfiwqazW/7XwY8k07LlF/xWD3b4cJAv4cvsQzgQg725AO98qB2cDeMuZyM4Y1GNSBgRMeD07BQsVeXMtK7qdtGyE2Jhqhlekt49P5F93F3GKOLqkHfx3vn57/zab3/1t371819+JTjr+/2TJ0+2V9evv/LK8fGxDxRVohv+6JvfuNxcPfrgvXXc8JIFSKP1Kbu6OjpePXm6Zw7MwfnKcxV8Zb5m8uSz5KKPTyuzMY5ZoqiYJVVhOA/uuygmKcuYkhlSzDmBzTkEyZb6fui7o6bfXz9/9/vPTpfoNtj1uQnc1u2iOVZo1jzKCFGNUMHWxuv9CMHyGIsFFuRA3A/94/ffl5gf3r9/78750fFyf3kxpDGPed/12802xnR6vDte3Hvx4vl35Ftvvvazf+vXvvgrv/zFf/bP/otvf+ud/+a//m/f+f7Tiw/Wq9MFnfuL9699qAhBEpUtTua2ucW/L1v9XNIuDCkpxomOZ/NUmOfGXP1dchOHuPlW9PFXc9F+5DFf8UMOxk96/ASOH83B9PQIdtDLKGH47KJMeFthq7ERGcEH33d7QOpl632IeUgyrPdrX2F1B7/x9372059769d+45c++TOv1Q1TGNTynfttzPGH733nenyy2V1dXl1ETagom+26/bbvBFq37VF76msHh02/3Q39+mq/3vR9p6oAY8wINdhH7wwqlAVq5OrV6k7VtJur/QcvNs+eD9dbuCChHseI3V6zogogUhe49lTVvq5DXQcQxpTjGCWrKjlytW9zwiBZhM00ZzOFc3DcMBkcO1bvADhjl4yySRYZxi6LZjH25IMHU6kTF5XR0pKO84g4miQis7ZdqHZEtFos4pjHXswGaOy6fR+7lMEVqiH5JhiTDx6ZmJ3zZBJHESj6MRpRVdFyuajro3YZNEcmIV9oQyC4FBMZw5RhrqhGEwiZjIk8mWmKmaA5s+Yis2KlNx6bI/jaj2lQFceuqVwdOIK8Z9U8jsNub+yb9qhtmuB9w5yiDBebC67gjv3jy2+88fbrdx/+yuqu/4Pf/+7v/d6j2kXJyqZj34eFc+RK8fWtEiQ1JJTWrdPkLxZYZ7CJQQw1ZlIFXIkYHXPhXDhmHmIkTGI6AIypaAgAt/L/hJtvPUSg83Kbos150dmt8+fE6k2wMHnLNlNVrJTuoEQFxTucOkMDAJQ+Zk0a6czPBE3SqQZW4tldnp3FA6qGaeCsOTnVqNur/W6zheLVT93pu+2DT7zy7/3Hv/7rf+fLr33m9P2rd/6fr//Benh22a/fv7y82oIrHJ23y5M2Sdr36K4VCd6IIneb/tmzx2PEvgN6wAEB9x4smmNeLk8o0G5/td+ut9f7D54i5IFXOiaSjCxqKY1jVmh7jM//4puvvvnayfnxdX95sV6/GJ/wZX7w9p3juwsora+uc6exMxNSQz9gGJF4f3JeV7Vfb54G7159fdVe9pu1qOR6Ie2qGqOmFE+OzxbLcyDt99d1bYuWCcSOc44iWO823U42O5xUq8VqcXL/ExSShRhaqluqa6fwcAJlH+ADObJRpNt3m+12uxuCC9qpZDHD2fHpcrX0o++pcwqIeLiUBSARU0Fxy9h5hldkhoNMjBjMDvmPYVfc2N8f83cCSnv0UqRaSrbpJsoexsGyTlNi9ltKYEIg5ypCoRTzXPxX9NRvIBh8aNuiCTCRnD90X4cJfzMTaaJH3ZrUDJBlLQpbk77yjAKXGg5SGGEuh5vYxoWDCYJ3zAYi1lt1uDZRrOYwCjbVNzLB+ACfHU4zltJ1waYmhTiMculp9tGt2sRkDuTtBnhj7xw7R85h0jZ+GYWYDZV9qA6sNDi7PQ3KqNkcv9/Cdg6G5SPvAS9d80Pf+tI/p9umWxu4Hohrc07AVElNFapwPJXd3K5Im+u9SEmmKBIyPZoqgcvDM/gQz86PU0TK5hsyzDXVP/Xx8jT7azt+CgDrgAX+9d7BR4+/EB07zB7MwMfh9nBrjOxlnaxCy4GhiChRQXBnymTZlXIWlPc0U5Ax81oApJQMVoR+DtcUEzMwU/DBzDLyXH04y2rjsJEeHgBTIZ8CH3qpBNyCOQ9L4lAIOT2ImKiYWVlDIgIgOA9mx6zOEUlB2bIWfjRPYp9lrIqxmOEMsqkzK8PRZHgIhYKmE9HaDKqiZmAt+vUmJXR0vpBDTe1ARyXKqjQb3bKMSj+ND79cu8lnEbFzTMRwBCMwo1gfTc7YlAxmWae7JVIREyoyYDPUX2oJD4vPQFNYM9FXUTaMwnviqUVoceGZUhJydKusfHojByKbWaGoGblJx25KMDq2nAuFjctbPURDViIDFPid1CSmHNO0QwCqVlVhBvhgsELhPKw0m4s+MVuWyZARExUlXWJXxEYZgCucWJoIaCjeEtmcHzn4VDCd0ikHsXnLZCRlALIYszhHyCpGxBRqLhlpsA0xjmMcR8kZbCjO3DCO292OAG0aMy2UVjPkmPukI+8AACAASURBVFREQu29r6uq3+/ZO2JTpKwjKzxXy6O6G1wWe/ToncVymaIS5zt3ThyFtl0EXxGxc97XISeLKaaUmGm1Wi2Xq34YX1xcri/Xjx8/TmM+PlvEMQ8pWs0MyWQpZhnBjZ+cAlJiI/alKQvNyx/FTRXKSfsxZlO10gnG74dhu99tt1uiaQE479hRqFzduNUq1E1joOCHvo9ZkNLI3DRNcC7cuXNnu91tt7u+71XFDGSkAh+IHZ2erpartqzvEMJisQKcqeVkBOy6tFjlECoXgg89u+B8cFVVpdSulnAcvE8pXazXfueHLrVt632AQlL+mU/9jIikMcU49sPgXcoZPnCouOulbdEP3eXVVRyjMV6sryk0xlUI1fLoPA773W69bOBD1Q39kw+ehMCvv/4JcsIeHMxX7Jn6LkZSYh9zlJzJ++Ozs7/11QdXL9bf+LOvL6u28e3J0ZmEfXbhzc/eS3hLXdfv84v3L64uYCOyxFL/bJozW1FkA5dUN7EDyv+U1i2YSmALqZAZ7AvlU1Vm7VG6qYkqy2l65zM4RRP9ZCYslr87wE2WngjkQZ7YM5xx0Lpt2TOz6TDk1JsAHlyTC5RULy8vAVrUKyt9EBJVrmkaT8C4H589e1yhXrb1w7fvrJ9f/dm3N1/5pU9/5W/+5hc/+4X7d8849UO3319vEePxol20tQuBg0sWs6V3n7243m/X/bgXFSSFxmwizpL1fbpz58S74OBFsBviTmK2XZ81ZRMRZudDCMEbNGtSEUUuVSrOh91+73wg5uArNXUcJNPmuus3Y065rWpNsR/G2A3f/d47UHiPPFqKomkgXzGYQR5qEKpADCUlUcsASBVDlEXbuIAxjRfrPeHKcdM2zfV+WDbt8XFrin7XPf7g8QcvXrz2yidPj+9VNYRePM/dgo93Y37t9fYf/6e/s77c/qv/9ff/4A9/7wdfAzwyEpIiO+bGBGTkQl22xNkVNsDYFJRudlQ7sN4PGM68E0+/1wnJ+pBzRvNJf2kQ60d/kObkK/3lr/4xR9l5uHTEKuHInBu3EuOQ3WTYzU0QPs33yhjHjir1jg1xP+yQFDWkwZ0z3H0Ff/ff+c03P/Xq4ii4alidrVTydt+9WF8RlEN+9vhZN266sfd1IO/MUjZlz8dnJ4ujNpMly922u9xtumHY9TEmLc25NMN5EOCYPBMFduQc6sYtXFiq+YvLq81G+oFVldSZNQwl6r1D3XpXM5OrKt+2TV3q6FTHqJIpjppiZvaVtyHnbFIlZm8Ae++dy6o0IS5WnAUPx0aQpCml3X43RmRBVcNVzM6rWUqSBJqgrcvZcqYYocoh1E3NRLpoF5L2fX/NJDnaMI6i0JJAZFbAHLIIwHUdvGdmSVk0QyQzo6rgvASPrtv0XapqcLAk4gNBKWn0TQUDq3ky8yjqTYTsCexEc8waTVXMssIjK0HNaUYWtFUlaRw6A4SM60DEXNWIUWLCbj86H5vaQM4zFotGLaumfb/f+CsHf7Uf2urOz3/pE8tl+JNvP7r+YFsFbwCQYTWAqqpVNIveuNBUGhbpbc9qVqNhLgvAlc5iNDklNlHli8/DB99+Yj3YwSubMSXg5YV9cLqL4urtNTZH/DdFQwaQWUlp2lzkQXO+t7jOwEHP5kNXs3ndTdx7o5cSKVTSmGUHIwBSfI2JEjyfRaDyoGRht0uI6ex4eVQfbbvte93F5z9X/Vv/wa/+3C9/6vy16o+/+7tPrh5f7J5dDVd9jtR4GvMg8FEb5YvnW+fCctVQDP0W64vd7jqnHqRoPOwIAqji4rJrIlQ4+NZzH0d0XUwj7TssvUYhMyjgAjVHVduG87snr3/q1ap1P3zve1e7y4j+2ZB1h+Z0WKwWhCb223Erw6605EM/ah9ReZggVKEb+6pZLtrahVy3GHtUgZzjJjdZ/HJRnZ0dd/vt5jq1lWubmkAqGIdkhigaEzTjathl7e4e3Q0NWaBQU72sdv0mSjQTokpVkgwx62YzbnfbcRwgKBrBAOI45pzruhYR793R8Unf7zwF0xhT1FgceMfkPHzRVYeZZSvx/kHfrRS6fKxxpymfYjOQ8yO2gJscm+UiZkHkg3fsQJYnU1xgomnp0FSVMQW/E3h0g8vc2s1maONjjw/96Xb4eQvA1Zu4FwffeKIsFDmSglwdyvhEpm1FDpjyVLRLBnOBZ9B2+iIcPLDpO8oPwq0ziIkNyqIwy0WVWK3QiT80jAfs7eXDJmbVNESFo+Eck2PnHWiyNnbr3g43gzkGn6O/Yl5exiZfugECT6/+I03Ub86+jXMVg/aha90CSaeHMpv83hI73AAgM7xQBDZMUVrDTUg8cyncOSAkB1xKzW4YbgcHpxi6aTDmEcOkqzwZ2EJG+2kclsNA/P+BYf2kANaHkci/8vHRh/nY3/yob7y1ednh3m5DVwCKNvkBd1NVEUHp8qdzwXBxbBmOmAgiNtkmmzbJW+vLVIvI3ES/ylluXvR8OOdgotMMm+6UQDZBJQe8rGA2t4zRfCq76fqlXLF86oCilKfIOasoPJNzhQlYpJucQ6lGTPNQiBxgGKZpjRUAZ6a1GomUyjdhxwwuAIrBHBOYATY1NRVRtUwMYittG0hBRYfxFho99WaUQrA0xlQdR0xaAk2DUam+nOMJM4UqkSMCzDe1plICLSYiKmYlQccwI4UDGQrPrQQspAY2UjMqYvZEJmqsDo5LaShNUJYxTdKFRVy/iAETsXNT9FoWvJFACn2JbpyM6YXPkP1ki8xMRQBMbCdMWqbEoKLlXMYUpGqa1cSY4BwbWZ5n4hxdgObCVRy+YE6sTNsKmYpmEs0mnMk5nigGxkxwZLOSRDF6mEJ6swm9KoaRJBdhQCrMdTI2kzJTJhmHbDlJaUDtA4GdgpVUzCxKlOQ9mjowu+WiOjo+Xh0f1SHklPph6PtONIfaE1tOoiIpxRjHohNPbGTGAd7IBSMni6o9OVk2bXj33Xfu2H2Gb1q3XFSr1XFdtSqqYj5UYtAGtTjiZV017ALMri7X7z567/Gj9+HgJLiKo0aqUPmKiU2NjImcRC0MXNgB0i2AHTGTWi6mXc1ELKacLSucC2TGm8vL9dWu6wfvOUYZUwwhqAko141bWbNarYh40VZ9N3bd6Bx7T3Xtq6o+Oz9mNtVsyClObY28JyJX1b5dVGb5enM9kYKNCM5gVdUeHTFohGMKrmobJeMQxiT7fiRyVdMmlZTyvh9TzD5wcJlIgiczxHHohj5JFpOY4zD2dajgQlW5uvGh54cPHlxvr7qhV8PZ+d0XL16M+fm2z2dn53WomqZGx8rma2+edvvNsxdhdbQ4Pzv5wuc/kyU9e/Hs2bPnnRkvGu9DN3Y5j6uj5d17x/vtMFgMwbsFG+cX26fPLz5Y1Sdvvvb657/8xvG9Ztin/VV6/vTqg/cv3vn+e7vLjAh41HWdo5TmmYWJWPjxky11BCWYzXzsqYU8cVFgsClVjildNRtuKpXQpjR3Sp3XB2aPicH+RkuIGRTgguPgjAgeHChU3pyNEk0AwC94cbwItRPNsU+OOWXN+yxRfUihoXrFJydHgULuU99tTxdHjtLbbz78h7/9D9566+GrDx6erE4Wvnr6/DvjsBuH3Di3Wh03TWNE3Tg+uXj6wfrFH337u8kE3sRJHIZsGiWOmqNIvuiPjpcZCok5ShqSRE2qvSQzUlXmUDdN0zZGmjWZipGUhg0q2XFwrq7q2mCSpzKJlGSz28ZeHtxzlQ9mHGNcX4sm1CFooDhIP+6bpQfICMyenAuBEUChSDbK0aoG5Zj6bhRHZtFi3O+2abNNF5frz751TpQGwdDtN9driNWhe75pXI2TlQhf9fHZ6JfcLE6PH/7Cr7xG6h+8dvTrX/3F7sr/03/6363aPGxz5qoJROpyFCJSJRDphMfLnJfBzf5SEFFz81Y48fon722uVy1/tXknmylLpi/DXZMD8uMy7LcO+pGhxMFF+CkBsr/4VNLiSgNzzbti6mQEMipy0xMa7AxhHiwDKcGiJu+NnMUkYDx8++jNt175+S998gs//+bRSfPlX/yiq6gbr9fbx4OE+3fvnp42+yE/u7q6uHpxcfVs1AjAcRCyJNnI6rauV62r/G531Q3den19tb1OYjmBvauImdMwYnXEVU3LZWiqygDPTRVWlquUue/iet1Jrjx75hHwRNVy5atlTWTt0rdNMmTvHTtvxClbThJHyxFpkH5QpuwpN57Anp0PAb6qQiDnSRSlCC/n0m8ZppxJs5jM3QKYoQBUicHsfGBiVbJxxDha1+lup1DkI2YXGCaCnItSdFYjU1I1IzIhSV7BcGZRq4rDwrWtDy6RRTUcH+Pu3VXbVG3r6uBy7Hfdvk7eB4o5N4vau0qNNWnxZYJzDkykPDXCIXEUFWbCDEcIAU1FZOxKXxzJJ0dnu12bYkfg2jc1uyhsjrnPoQc7ZLNh7M1osahWy4WqS2Psh/2VaaiGQO1iQZ/+3Ouvvn7v0Q/f/9Yfvvja9554wdFpI0I5m2WY+uKoGDJBcMNLn6Ag2FSpdwCryDMANlYtJeNmBlUwrCRoMWOxhzRDAQhKCd9LGBYdOE1QQnBTKQBKbDkZ/mn1H3CukgCdBCXUTLWINtCc+bUC1NOcCDRVvrnCtHdMwZ7ZrWVaErtGjkhKyDw/DZVSq6kkyCZUwoicJw71Pu9diK++Vf+jf/Lv3nu9ufdmnerL7z35wZ8+/sNEUTw6zRddv+vNte60XijR84vrtj2rfe2sGvq833ZX113cB+SV6OzkF4c1pk5xebEB5zGJ52a5aGBXQ4++EhC7BTvfVFbdO7tz78F5aGjbbfqr4XJ9tRm2rtXlAtVJCL4eB6iYjmHstNuKqYD9mDFGcI2UFKZtW4fafJ1PzkO7CmNPKs6U1TyhJShByMQzquB98Jo5RR2G5FzlmX2QpjHL6mvHlbiayRN7VaT1/qrMCM9QQ1ZYshhjjImJwUpK5ImUbLC+633wQz+M43h8vBrhPXlnYhl5FOed58DkHBw0q8DULBepKzpQt2/g/h9lm8t0fBnruHXcEggHmWqp7TZWI2Xm4LyVcowJBCo/+BBoHLC1OUaYhZFLG6dbCMOcrJuuwo4/FFITqLS5x61QVMVu4xQFjVKdo1lMHXRUjMrgoLAQp3CpyC3PQHVZfBNtalq8+LjQvozZtCUSSkUKEXujrMJTgbHNTPpbb6GERZi108sQg+wGACwhNHMJEIl5LhAiA98EWreH5QBGGG6N4Muv/RCY36SjjMhwi+d9+4MTgq128D1mkO/l6TGBVlRabhcUaVbHsNnuGVnR3SlQPJnR3EmwCGwXshjZgRCjpQcalYITo0O+eMY8ysuesRSjIjOKCTjVSQ4cH5lCf8FxGKK/XvQKPy2A9aEb+qvfzW3s5oAR/oUMrNty7wWlws2wvwRj3XSaMytgUFXVpdKw1BWXKcHMznsiMhSw/QZZuZm4Bu+dWYFyZII1CkOPmYhudlk68DnAXCSt3ZjjROq6tU5o3oxv3znN/QRL52botNqLkF8BsExvOb3lgwQzBeCcF1USKWemnA8jzETm5pafMAZk6tCqMCVSIuJQKvZMgCpUOqm5mamJSlGIcZVj5lza5VkpRzByjolMVVRFs2fPRTm22F2gIGemYqpwbkpuAZhkmMqqVwJz5QARLbJHKCo4EHBhk5kpipo6ofg8iqlC0GAqdPMWOHhPzKVl3awhWKyBTWL9KoByqb6cbBxPbS5LCdOEX8/6YBMmNG8dxQNTsywlPnZEWhgiDBTJFuKi0Qg2mEAFgHfsgxdYlqSmCpCScmkFzxMyp1ZU1m9MJM/ThSCmklWcBE/meNJ0IoB52ipu2dyb6VLMZuGzpESOHPvyW8tFoB5cyHJFWiOXHpHlOs4IWSUPcrq4u2gXUtV1XXvv2zosFotF24bge9hut3vx4jKm4ehouVi23jkzG1Pa7fdj6j2Ry2DASHzNzrGRDKkTSmBZrZZ142GknhZtc35yFGO6eLEehqFp2yFKygKj5fLIe7fbd5vN9vkHF08vnxM7cnClaZTAhCxbNpGsJkZGOZXqTzIt6splNJUmqUUYIIIUNUVJiViNWIYxAe79Jxe73T5lNDUNqdmN26au60XtvatrL8JVVSZKXdfV0fEKEwBtRNp1m2HcpzyYZefhQMyOyUAWApPTbujiJoZQ1VWtRqJQhffhuK6HvFZQFiXnQt2IYb3djVmOj1YcgijGFGNKKqxmWx1StrqqHLGKPHr8vveuqYJzLJa5anxVCceuF9V87/4dsbjru7pq791/5fHTF+vdbrPL232qav/agxNl6uIolxd1CLXz6/XVu+/y8fHi4SuvxDRurtf76+GD/c6vlnDUj50gn2bhUD998sOzk7Oj4wV5HeK47a7GfrjeN8Kb+/cfNqdaLdzRef3qJ+/sr998651X33v3+XuPnl9f7xiqOU0S2YUeZc6mSVngcjIxg4ENDHaOvCMiEoXmeYUfvIWC3ToQTEFuhrfIcJPEmhaqcVHXI4WRg3eevHNVAEhgooacUxI1RYWmretl07SBHZuFcUhjN+w2+7wFMhBAHssVxvvD+enJ3dM7O7t8eO/e/bPjz7396X/zX/91RNlfb9aXVxtYt30Rgj9u6qpuqqZ23hPzsxeXX/v2t//sh9//8/ceUxVCU8OrWhJYthRVhpRjQtevHTlSaLI0qkQogwLYmRnnnECOfSWakkSQwBk5mIlmOz1ahKr2vlYz0axqZKySul6HHcbjzMbjmLMgVHy51sW9uvaUKBOnOAqV5t1sVPTrHQequCJ2VjdVTF2KdL3pCRbICNiM48X6g3cfffDw/pfYRC3vt/v9rmsrXy9armndXVx3l8+v3ifwvfP7bX28T88g/nhx/oUvP/zCL3xSx/CN73zZyfLxO5fv/vmT7TbmkZRU0iRfNdVJzaEDmQNumu2SVTa1rNHZIZ14F7Bb/uakv3zjbNgMMX2oHOAndX0+rrZo/tOc/PwpEpqEgyP7I48ypf1N1cHch3sSup1iokKHYZ3pxSAFxEjYqZG5Gg9ead946xO//MtfevPTZ5/+/J3Pfu7tqvb77vrpiycGqVruUz9SQ8rX2+unTx5dd5urzaV5qpq6IouSoiYhVUfZdIzjEKMYsmkyE4UR+VB5rshyE8ejVfBem+Cqipncsl017dl2I+tn6+1u3Hexqo/MJOURKVV1dXy2qluvNpIT713OEQoRE5EU8ziM45hNIEJxBJG2tbimCRVCxb7muuamdlXj9/utATlrypJE2bI61tKhynGoiDycc0X4hJjZOXbM3szx0Oe+036vmz0YuC9chZpZ+2Hoh1Gs4J+OmJ2RsQNYC7VDyEiJVCQxoV1QFdh5vXP36MEr9x27NMS2arVqoaGqgkGSbElq1qXDSLp3zhyROQFlMnZElfdVCCYSmdSk8oFIfEBdt1A21eDJEdoqLJtaUgTVjEbbehT0OTH7MVFw5hxE05jgkwrqstizasyagno/7uLjkGhx/Ilf++rbR6e1VeN3v3vZ1ry5ilAHdVmJKBAyZgf3wMmYAj0DmzMiYgPUCvm8+Fhz8s1mnhJAxDSBXWo0Xc7AILXZ1AMEU9NCOgf0AJvxFAfaXGRFt/x6HJb2XMNFk360MUH00EwOjksb60k4EzZ1j54hhiknPaUHi02amO9TbhpTNruI5ZS8CmNmlx1ywAQzN1QrH6r4mc++/vZnz/6Nf/9Lka8fP//en77zjccvfohF7dtq03XrYb+NOhhWTbU4OYa57a66d/fV/aa/vtitn+93l0POtXcNccVqBiUmMyWfjE0173ej2aiIZmB2Yrrr9quqa6rm6P7yOJx4VMt2WR+1u/319x9992oYVw2yEAY7PfWnZ0dNvcyR4ygyhrFL/Q5k7GoHA1t2wDikbjcc32mJh5i6qm7ayocq5MQ5UYymSVJOu80657EKzrEnY89B0hAjal8nhxAqAlRG5y1JDqUdVKDCuRYrmIsA5pgYJFnjKARChKq6ysET4tQ2Pac8xujYFeFqE0gCQTx7Z674GJpEo5aUeUFOcMOYuan4eck6z0jklEc7TI2XLbgCNsUyJbPPArHSpwoCB8fOiGUiN03Th4ASAJhJuRcULo2YYdJVNpQ9efqiw1fTDCXlnD8KOBw2iunkQ2R7U0NEMILkQncvA2FZIEb5MBqOytsomuPGU46kjIHoHJGUragEbxP2OyF5OIgwT1Spks5l58SMdAojS0rIbG6lggnO+xA3crrATCOZGg66qSldGa+p71W5CX3pPZkZ3/xjWucT+emAe5jN631G1ctzMG6dBNwkwybIgWbjVszD9PcDKUfntNcEF2HG/emGAnPbJZk4FyA2yTf+xAyM6AwmlLaPdvNKAZS6KZgBTG5i0+lBsws0E2RhWlLsH3VobgC+jxyHNUJ0MK5/nRjWTwpgYR6O23jTAbL5Sx/lOgWQoplhdBuE+thjUkmfTzuUZd7+IN2qebxtaOpQpbmf3VzsZYe2gAWf+tBUnvFO897nnHMWEXHOee+ZHauWD6aYYTg4yQWDNlLm4JyzNCEP82K4IUsaJnBN5VASf7BBpKbOu5xyjFGkNM6jqb0SATlbAggUuOSJ2LFTB0BVopCKlFF27Ap6RZMBmIdLBMWl4mn5HVJMVVVlU1EpvfiICjICZue9A5GKoOjfF2SbeJJcztosamIHM1VNJuXFlPzS5NHMy4YmrKasDAXIwwupFQWTOcflwEyu4A8oqk0zej2DwwQCUkLRPjMttdrOOTEqzJsp4wUDa4liS6m58jSFmPggcKZik+DVBHzfzK+XrBgAmCocTTsYmynIGVCaWZTmZoUbTuoMAnjnQgjIGYCp6QwIF11PKm1vUUz9ZBdLtazdgjuLtrVCZ9nBqfTZbubZrWCnvPTbe1WecE0mp2Ii2QzOOw/PZW8wgRgYDuxcVYUaHqIpxuH89XMTpJyqqmLmxrsqhKqqmqY22GZNMfZJsog4dstlm1KKaUw5qVmfk3MUHPvgQnAcYJD19VXX92NMrzy4T+T6fuj3+9WqOTqux4H2ew51e//+/R8+em+IQz+MvgpLHO267fvvP714vobi7P755XvPdeUBc/CaVYDCVwRz8LUdpDTNRLU0LQArkVMxE5R5lJLkrCoERyKaM7K3rCbKTOp8DeKcUnLUUN00VRYaYw+SkjYOVXW6XDK7/a7fbjdZhmH0WUbiXNfee1/XNWBj7EXEOSKGiKRUBj+o0DDEGFPbLtpFY8RjzKBY+9pxFVMaU3Jc8VnlyYE3IFe1bewlRUtpSElSo01de6anz56dnZxU4RgztbNufNKcUt/1mwdnD6um4nHwtT8+O4kZ3YAsCW6bZLx7d1k19e56+/zZs+PV6o2HDwXy6PE7r37iwafefks0n5+dnRyfPL667LecJUZR8iDXG12IeSG62m3Gvl+29Z0H57X3V88uv/v46x+s369DU7vl0fL07unDB2984ku/9HNP37v83f/rD/7V7/7+7lHCCASFQ+kDWEQxjcBwZLAs5gxmxgYHeHYhEMhMoFaabR7y4wdTM/lhNzRWm32wWYSFAOeNy+YuRmTkwZ45gNlUU5Yx5jiOifLqeHV8fspE4zj0Q6+SK9d0mzFvAUPbNs44arffYbdf78/Wb7127+wkfPFzb//qL//ip1593fJ+fflit15DLY3j9fMXn3r7U688uG/kuigueLjw/rMX33nn3W+/8yi7JotdbToi9Z68ZyGXTQm+qRgKlOBSkmTNAimqbgo1jRExD0bOSEUzBXjPzGAQWErNZCkIJwrM5L1jCsF1I4+qLglyUgK3C68xe1855yqX/LLdbXtiNggoQ6DqSMhANVXMDhRyppgMUdWwqHlRVxZ0fx0f7/D1b7776sM7Dz9xv2rOFe/vt8/j5bWxu3d+zEx//oNvq/Jnf+bT5yd3Fu3pa3dfF2wICdzV1dF/+V/9k6tn/f/5v//B//DfP/rB/7JFBwCoiqUqhedsxmpgnToMGVBkdZR8AaynklKbtDInpcGSXCmV8zdskUm++cNxyk2y8scehzTYjz1+cvTqxqAfXPzDn176DQEM9UZlhsxhO5mZGCmZGTJR2ROn/iWAwjJUodARAPoKn/v5+iu/9Yu//du/9YlPHpO/vrr+oLYQc08uLo/axaq9uLpoXLVLu4v188dP3lVgzInZVUzGljQpRJlSzLHPg6RMulgtxhwHTTFJGi143zR15RqgAobJbUlGrvKOmqbad0M37PfDmNUqpjjqMCQxNMfj8igcn7Zdn/u+a5ercXCpTzmpiPbdOAwpx+h8UEPOBS1UIgWLEKBgcR6VJ7jAEDGybCmLwpjgQBWT8x7E3rOwZ80mKjZz2sXMhExIMkmEJYiHc+1i0Thvu+1+GFMW5Kik6lzwvgJ7BbKpSiYAjJgkjb2K1BWahqvajk+a8zsnJHwxrBfNcXDV0fKVRdPuu+6FPXfkAlqVbWD2PhKZSVYobHTEbV23tXPwI6sqLRetaCQnTVWpckqJDA46DL2kCMuu6ItrJAWQmLWurAqAImfECOLcDHtHzlRDVbVtlWS7aGw3PHPet83y8z/76nJ5NPb44z+53I8dLtEsq9BUaSj4j5+wJhIrTRQAlHQROZgjgLisRNUMUSm9jwgw8FRvR6VR4LykZrL5fK15od3iXti0BRySdjcnTUgWTbeBG3W8KbqZdLjMTG1mHgCYNWWmLCfNMJjZ1KrHbjCs+SHFpvZtRCDyhNJOhwACxObxmNpBmzA5kBnUECG2fz9/+e+8/g/+w9/8wi+8Ru3m0ZM/+dY733qxf7LJQzDbXmwuN6kT+BZ3z1bEtQCnp+dvv/2F/TZuXjy7+KBfv+ggvq5aget3UlVN0wTHnCX2qUsawajrRsTGlPa7ftfFnBGHfltd+eOT9owf3rvb+tXY99iu1gAAIABJREFU5efPL569eHbVj8RQj9OzFiRgBbmUkMekEZqqPAxDB2ZtvHPBByNHPPay3Qx3HqxiHlPM7DM7Ajw754xlGNebTRNCGnsfuK5qU9OMuqogSTI4hBKrO+Y4DkOMvUThxVm7ci4Y5cXydBjG0ZKZJwret85VzqWChcJARE3TMLutbRftYrVayZj3CU3bSFIlUzFkKAuZI2hOyUzTmCwrg8jYXg7cPxa9OhjfWxyVj98n2EiTwYwCHLEx2EFUNStEEeA9K2BJkihAc4P5MgGLkbbCHihd4g1GPHX0nG5jmqPzP+e/MPPLaBVsgo0PM5yI5iZi0wPN11GUjLqjWW9aSp9RLe20ufTTBcgc3YpdFASd8b95yztQsQ43zMySYSooiA5Pg+ycU1FjxcRmmAIiUMHTcKPT9PI7UQM7xlyXw46d94WsDUPhDXz8K3rpXU8haglPb+FHE9mz8M9u5gOBiwaRzUARppMnqF3tFpR+gxDi9osxexnTmowVFWKZTTxUIljpYmgTuimHeifmAyvm4OiWf0+3On/v7QDxBhqYJAjowBaCceFe/FSHzWpcLw3RX99xM3s+9D+4AfB+pLMWQpjYTLdgo8NI/fjPHqCrSb2bWVVTSj/JZ8uYfmhcCpp2WCG3XyFuNS68QYGnh7w1DEXJFISy87z8pWZWKlBeshFM7Cd+cnlVzrupnrlQuswK4uWCLw+rMwGsUDdTTACqWbXhpmHfDKWZmQ+eDz0QRUHwPlRtXb5CYhrHMcWEBDjUwTnnJ4Kq433XVW3tQyAmFUk5W2lEeGulgKApmwkY3rHzbLCosloulEwBNc2aNOnk3tPkJLNDCB6ASBYFAcwwgyiWq3pePihC8gZMJZFQMBVlOU83XVFNVY2g1oaFJslDzDFZVGSwwKWp3RORK68+VA17Z0TRNKoWopDut4c3y0QMUlVyXLeNEY0xmqO6qeFULBV3gtxk3sSyqYnlYovZu6LlrGTOs69ZzVIeS9GfszlHIESGhhpVFRUtjZcZRFA2ZlRt3S5qU+37YdwnEkzVhQ7Oew5ONFvp2cFGjomJQciipSFAmQxl2B055wyFpkVgooWBQX7C67PFmyl92zI53JjDoigEIis0IPLki71NltWSmIAAj1Ax10xOOWCAHh9XZ3dOfOXbtl1fXC0WR01bB/ZExAzJslmvYxyOVkenp6cpxevrtUjyzleVC1UANMcY4+6tt966Xl9td5ucxxBcVdWAi2Zk8D4sl8u6ajz7zXb77Omzbj+cnp4u2hXUmPHOo/fOTu68/cnPpih/8q1vP/re9fSkZWZ6N/MpeMrfMDGXCeNUtCjHMU1rU5HBZiYhODgyZGYzRrPAvVeOqobuv3LHV/bo8bsvnuvJcWiqoCpqsly2zhMR3b176jxvt9u+34lkVQq+rarKe+9cSCntdrvN9a5u6rqqnXNZZBwGkeS8a9t2uVhVVbPZ7B4/er7vsFzgzvkdVVpfXceYlqvFYJ33aJumbVYhVGysKu2ivnf37nJZmeXr6/X7j590+wi4ruuY6PT46Pho6cgev/uUGCdHywev3Dk7O/3C5z8nqt3Q9f2wvl5frq/GnPs+KjgJmmb5/gfPL5+Pu2FYLgP79Oar91ftYnN1mfvdp998O42DpNRU7pX79z/zmZ9p2/Z733/nT37w+On1TlSrNmy7/eXmGoQQEGqsWgremeTlqjldLpoQTNX76tVXXpVou20X9xkWjus7p8f3T47utdUihOW/+Of/x3uPnv7w+4+3V71IFjFSeO80WRz15GjV78acs3kzdlVoABOxgg9Xodltd0gR5MBM5CmAnFKpiVZTTSaZvS/EaZUMQl1VYVGNlCenywAmXzkQvAvtUZtyjjn1+x1U0DJSRoWzO2dVFZar5Ruvv/6//c//EiNIUPmalCwqOyxO6bU37rzx5iv/+X/yny0Qdvrig8fv7q4uZIwVswMkZR3TZz/9ubGPy6OT5dnZef3gX3z9//7eo0ff+M53fvD0vfXYdSaurc1MJamKanJV5StW0SHG87OjlARKnh2BNeUxR3haLBa+DlVosun19npMo1pSsqrluvFqMnRyflwT+ZhkGKMUtGtAINw5WRwfLXMcSfP52bmn5cXz/df/38dksAHtcgEL/X4EEUqCIYA9kSdzpGxALr+sPHwg78mxK7VYTNR43l7Josbrr67efvu189OlaTfGDXRsgv1/tL1ps23JcR22MrNqD2e4976ph9eNRgNoAhxACYJIijRJyRooh8MOWxG2FdYn/wJ/89/RT3D4kxwOhywFHWKIEk2RhEiZICYB6OlNdzrD3ruqMtMfau9zbw8gITK8O+L1fe+es+eqyly51kqiEkXGcQfLXdt37dmji8cX5w8fbB8+2D7ari5YO/Fu2z3c0sPr8fB//LN//rv/6k///e9/+OrFrbB8/P6xb1vhOB6yG5EGwSzdUjNuWndnrmxpsmLmSnfqwFqjNvXRPNc5kwQhhhBkSBMtAea9oGQuMNz9ea8Od68KavctO+Y9/zTI1t2ucEJemQOBK+f3VMOrwQYAVVUtRBS4C7qtDUQAgHSaBstjv+0lhqmM600/HIecC8Rrx/aiuV81Zxer2OCXf+0X/tavffMf/MPf/PLrTw/YXe9fKO2oPbQhZCTzknK+vHr58uXL9z/68M2nT996+vaPf/Tx7/7u77y8erF97aLbtA8fPXzw6AF3zc3+5nq/2w37/XhIJQ15MNh6ve43G3U67kdV3qzXfRtKOexunz96tF2vGiFhbvJk+6H8+KPLj18cQpDdjZozKBBx2zfdiiUqhdx03Lbti+dXquHB2aOLBw+HIT17/+Pd7SHKqutoOB7Xmy7GcHG2dgw3h5sm4ulb52fna9VsXqZpbNuOqRmHtN+P01iMJWWY+ZinL3zhjdvdzsiK6jilcQIIIQaWENC9+I97pPb2Mt/cpM2qT5rfePIEpi+vn5cMS2gahjeRW1cMWUMM3XplKLvdVeyxPZfVGhKmvvenbz187cmT7fbs5mq/ux2irW+vjt/+9g8+eAGMQELzAG+/sX305GG39mZ7rX7bd+2Di9V2011sQxtI0yFPAzQ/unjQd+1hf9yP19nUMjh0q26jrtfXV0/fetx1DcD73TQOZdVcdGcXJfLNzfU47gnKrEUzYCISWHLOKaWcMxW8ecYNh7bdRN4IbR4/fO/Jg68Mt+EH37n8f//9R//0n/7vK1kf9igDus3FYX8LKubaRJKIaVcgXjsCEySnopY8FDCIaicgApGrmRr7Yp9KTCwpHWuj59NonbO2JdPmSnCiUB0kbR4gBqAWnivlkEUA+Cw7WMZj7eZDDJ/LeHOyAEJyVDP52YekANWNw5lmxVQd+6eIuv7f4GfddrffwVlIypQpyPbsgRfc3lxT03jO6/MLIkjDx9ur89cudreX2U1CabrwS3/njf/yv/2Nb/zyzye9+ejld18efjzZ/tn1ix8+u0wMjqFZbZ3DsYxooqrvdwOsjbw2Db//Rz/CAExgDZYUSuIde2PmmgdZ9V0btmdtuw673aumpXe/9JRZX10+y64fvxreeuvxz/7MV7741jvlkH//d771p//h+7vngANRECANNtumicqhvPXlt7gPyXR3u0+D719N022O3K7WG460m26nlNar9vFrfbeZ1ufp8et9u+bd7nB7M5bChHa3y8dj6dr2Yt2Ox2PKZbPqHj161MXueEgvnt2+enFLvkpD1CQlqcG25/3DJxcF4+54NdleWvSrdYiNO+2uh2cfHc7O2uk4SWEvGA/mIyAIMXRdD1BJuZgyyFTLULZ5fbw+qNZGT97Evm06zVqmrFlZgVJVGlJJDG5VqI6ZrHBKNU8Agd7BGT8pY3dyZ5sBAmISZpATrMzYzeyVTifeDs9vuQGOKAGVcaZWDZ1P/s68lOHvnJJq/y7Ufs5ESxPC+2yP+7n2os+lmZ5+YjIBbWhqElpS0axwCAVx0VJq9s0xVAcbtdnrnIiEGUKFUi0ngaiyRWgh43zizzuCg3v1inDU1Y1oYWWB3Tzn8onbS7Ovy/2bT27b1Tnci+kstzGtWQGY6CTkAsyK+QwgzLMKEPmuIrTMFSeED2ZeStGyINJLAan+aUYhRCLSWkHHDGOzfxLfsGUKOu2YKvZ4yp6xQJGzatnV6l1dnu/s5jxjebh7pp+CUO6/k0VVTefPGk4/EFd36OqiA3fPWjkWp/P8/LeaIacj3oeDPvvJ/6TtL8SCQiWbfOpV/ikPfDKZ+sudq98zWceCav8553r/i0TV5oNP3/3cndPC6lr+ESHe4U1+4qd47d22LEKBZq6ez5peYSGmMr+IWKYsApA1Vzun2fexatzvfWZ2bjotdSeWWZ0pmGoweuqoeIKuyCsZE6Z2ciKuEbgEqXfAAVc1q+gRSBBCrMAWAAhzqOoBs+KmukA2s1R6HlUARao8VBEiIQDBOGn22u6XAHYOlaVKLGzu1dLdzFmYJdSeMvVyHGqzG/48trlq9mZ3qFoDr89IfbZ8WqhphGyFoBTAxuqnZ7cMbFR4ArlM5NEJhRwEkSDC04xyn/wN5m/lXJzgZmAuOcPc2Vlmozs3TyW3fTStXSVnT1QiYqoiQFLVWZi3vDN0l79wKmXm11UftABhcXYnFxY413kzBKnzOHH1S4CpkfDMTnVXVQFXiaC7VYXTIntc1hUCEerK51ACzb1U3cSDnXr2zi+rA5WyNt8OntsWwYuag4mN54LBfO0EZwTiICEwU4BEJp/YQpksjUMe8s3NXiS2XaOmpSjBTPVwPB4Ph5xL0zZd256fn2vJqlm15JQlMDOH0F1f36SUmIQ5mvo0FfDsfxtYSlGmHPt4tt26+WF/JOJSUhBZrTbvPH17vTl31ZvLW81AAJToxHj1ufNirZAy1RR1Lk+cpprF/6UuIQ53s6W1NSEEiiEAXEopxUMjTexjPBCxERmxqU5TCiYx8vE4xCa0TdPEi5Rzzmpau6qXdoFwz843IhIkznMCSC0C6vBcSowI0rRtV/LIxCkpkTAHs3x7e3z4xrqUTIhacDzs05BFeD2sBA3sLDackxOJSDBjkaBajsPk7gTfnq+tpBCjKsZx2u2PipKmYZymKQ0itAqNhEAUsgLUtDE2oQSCl0IBw5hXna/XW+lXqZRxGNm92axz0f3+QBTeeOPp4N3wne//wZ98Z7MJ6+1m2292x70VHrKV0dumxIi+i2MiM41R0jT88P0fkVHbdBSEDKPtrg92nG6FGjP5ys+9+fjN7TvvPbm+vH7+7MV3v/PhcIVSFAy0OEx7DeAGfdc7cS5FixtMKEiMh/EIqDRtjI2DtBRzU80EEhEWgNk4mhaoVyUnEVQ174fmYpWshCBN17LIMA55SrTiNCb1mjeHCsEDCBKCSGARJ6jiBojwjOlqguHt9x6/9zPvfPVn3/7qV9/t+rDfX72a9mm4ubl5VcaD5mzEfdOut6v2QTPkvL24ePDwyaj2vesf/8mffeeHH3380ctXY3Zwm8ajaiJhy+aqThwNZuQOV1w+O4YobWw8BnJ2BdSz6URaMmmTSYgRvKRUXOscTiaRYoO2X0/jlLMB0oSevEAnKziMqe/7KEGtpJQhZb1ZQxFXREGEJY2Fme84ynX6VieiyLVxoxM7M5lagZMQKLCgkRBDe3Gh43H38lI32yRxc7Y+kyhpvDmmiaicbxvpNpqn7GJTKq+e3xx2N9ur/cPb8+35o/PHXnh/+/Fl3Hah/+ZvfunLP/fuD/72ze/9mz/6sz/9s48Px0EnDBMAVGtICCQyBSZJ4wiCuZILG5kVdyfiuaY69wa32JJUfjfmUPRU3f3z4pJacnfHEsDQiS3y2bDIP10o/gu2RTXg7mZppibepU5k7qo6B7Ec69GnKVWGKQcKQqGN1sEC0njQY0o9KSaJZEGLATdAjy985ezXf/3XvvZzX37n3deevH7ebfRF/uHN/uVwvA29tY0Un0qepmnaHfdXl5f74TDnBOoiYb0+S1lXm5Yikqb9YY+JjuMx5bGU4u4koZP+MBxfvrrk6725DcdChGl7tu4b8/HiwSY2Uus0NTBRmAskwqAuiJGbyA4SKaENsWUJAVyKJrWmazaq/OLZzX4/Hm5zyUxezJrVum8ir1Zt01JWXa1qr0MLDbWhNQ1X11dmINJxKNOoRV2z3e7yMHlWvPZaJhFhVjcWArk5cikoNhUTis5CMCQcaWSqCxDDTpmMu2kjIGHWkvKIUZtO+q2cnXWGI6E8ON88fm394LwrKX/8wQstdHs17l/t9rc6XEscVDMMwICr59O4v6KgD74wnp03F2dnbVzBNE/aMndNw2XKJbuOAaGNVowDLDNh6WQQo4zjJMJN0677rgtom7U0kslXbcyjH/bXzNx1kQOLcIxBmNy8JM3ZDH0pkMBtlCaS2u1xfAbePHm9acK7//nf/tl//0ffvrpxCX0bLTPFriX1aRqGMV08fJhSKtm0uAi6vleEMe+YlxTQ3e+oH/Xln8Msm7OvBViiJbQ5BfDAHOFgoXYsXC0/JYF33nj3iQdLRDV/685tmjBH4KcDLYTdu5QWM649D/fTiTPo5uoaoH7VNU07SiqppDFbRhdXTd/d5huHeSn7Yd/03HU0DjTt8xff2/7qb3z9V//hO29+cTP4+x+9/NHHl+/vy3XydDNO2cEhxG4FDsOUjtOIPJERmQcmMi+j4QBMQCYzp8LsDmQQkThgTaPgMoxjduz3h6bgcLg6v1i//vrj9Xb95I19v+5Ixo+ff/f25c3Lmx85Q9bQAVCFQJq2Wbd9a8wTxHOehinf3u7ywaeDeyEEuJbJ8jgNRQ3WEnEb+9W6Y6ZpTDlBFZqDUXCnECQ0fUo5FS0FU9LhmApjOObjPh/3Hkm9BC/Q5BQCrJkGTVqOQymECIEnEmMKVqiJLNRFohA5lQkEREiQGCrZwpn5YrNp27aUlPfT8YOxzt6uDqBoES1cWS00h8tVlnfnvUTLa7kQge58qpbXy2ct4efP6ASC0SL2W7x7l8Sioien9m9GoPpzdWuslrS15l+FOwtSMX8dM7dn5tLUbPSUid1bUH7iueF0aZ/Yqv5sgZgArwJe4/nmgdSq+BbuNDdurPoYh9y7QbXr7DLo6N6S+EnEZeEkzblc3aHP6bTw/PvFMqKmlctQJRC5c1Gt521mOl8AFqDsNNPY/Rtyumxm+hTdBct0AlStzN3v7qNXmC/89EjmhPRzb3f9c34ms8XrHaaxACz3DPt9BrLk1JuC4GZqcDiHiud87sHuHZaWzN/hdz2Nlhvuy3/u9x/Pybb6U7snfML36a+OW/302x2AdZ9I9VNuJ/jptOEeWvTnb6djnWyq7v/jT7nVp3u/Z9+nwL/PwJAeJM5ppVXb/rvfLzZv7EDVqVRcueIyIYRq1QTcYVgOR/FTfImFCEZ+d131DGyRW6qqlrmZ5WIXXptG1Z444u6+7LMaM5Vc6mUCqNJFCeJV0WrmJyEnQ1hkIbXVuxBjqD3NKgK9aOTqOHElMIGZGOwuBCdmlqpTQ7LMjllfW8NmA0PqrUiWfAb9BfCThxTYebleBxa7PME8IyyxvpM55mxswWXqGHGr/aUotMIMF6fkhnrGdVwVclIHuVqFHZlYuHaZXjCbOufVtQCGNPcbUy1wVKk8BwkCWFFVK0ytYQbqnUmMSWYjDIdpUXXDQltlX9Td7nBLRRmEaphHEJLaEbEqOIqqL9Puyb7eYG5WzNsYUa3XKiBp7rMm0G3WTsLZqT7basRWq39MNPuvUyWo8xJu1bFFEJChalSxPMv5bs+ArBNAunSpnEFdIrBw5S4xkbCEYmxsk6dcEuf9Pq9WY9/3HkLKqaSplHIYhv3RUjl0q9sH5+ervivsaT8ej0ciik1gpqI6jplZmjaIRnUlEJjdfRxTyUrAdrtdrTd91xJxbOI0TMNxdOK+71bddru+ePni+qMPPj7cHNlgikqTAwDj6pFWp1jik5DAcTdRo669lZMDNzgoLMMaXN/ScUzqY99PCknFJZATG8gAI0qlqKspqWrXt48fPui7LucyjONxOB6PO+YQQiVdou9XmAFGckeMgQrGlFIuOZtIRxxi07JMKYOGqetWsW1D1uOQ4JKmKTAZcHs53l6lJtCuycM+w3FxvrGCtu0dUjLMfRzHYZpySTDfbla5KI3TIR6csD8O7jmXYZzGnEeHx9BwiMQSFUH68fxMJ1Ib3AHz3e3hYn22XW/WXTPubnPRyGKOFy8vicL5+fDm07e+8qUvKcL3v/ud4VAiKTewjLPV2XHYp6FoggjKOLZtenDRP3iwirFXTeM0ZNVQeZgdF7imMY12OI6vv/kldPns9Wb7+MmTt8/e/MKTcWf5qLvd/ur69oMfX6MBRYCIjZy0aThwq6qaE0U4XJilEa+5EBlTJbAbeR2e1Y3VUVGtSoktWTWbZ0IbY5AYxvEIz6DGTJmpbSORusemRS4TBSLNxUtC2V+3EMQWb7724Euvv/vlL37pF37+a4+enIcz3a6bcdp/9P4Pj4frNO1KGgJREAYLBZHYUGia7bY7u8iQ73/wwX/43vf/7R9+69XucD0cVSK3MU2YNJGI5VJLBW4EI+JA5tev8mYDWblnKzmnKRcrJO4TkRSjiQOzoIm9SBzLoEVT0ugMQghhxOTwEEPb9O7TiFTUSylEJEFKrq1q/OziDAVwIoEWLSkLt0S1NcISIWulhBILOzmRM1jV1XVuHQEWiEo0D8dx3A+D06tJ8cW3H223Z6ttu7t9sd8diDWESEwKFNX9uKPd9fXt5eXtq1Xfv/3G07Zp27jq8nrVbfsH27cfP37y9PW3fubR7vLXn324/+jHL//kD/7s3/0/37q5VbCy9l7Us6kmtIq5qu3MDEMVCs2SbPPa2wFMTmRLcyL1cipFf0KLjaV6cVKLzLT8+edTNY7YPw1inVaovyi6uV/PuwvP3JaQa6nYmqspG9UJx8y0FIRATlGEBeopl8xkzIJGQ4umxzEZDGcX+NIX3/rVX/nVr/zMu29/4ckX3nnj8VsXfUOIyTAexuupvMrYm7Hm4EmLlsN+f31zdXt7PY5TKmkYx2Ec1bTt+rY/EpEI4HYcDkOaLm9udtOUbeRGQteqa846Tcg5qQKOtgVBmZ1ZSHzMUzZuQsvM45iHlBFcWmhB06FpsV5HgAwWGjQts3hW5FSmRI20u9ty+eL2sJ9cAUeIKQY5e7xpQj47a0M0FGvWDYur51SmADkeJ5aGuJ0VtbURLerMMGqB+mxbQLMlgVcLXDWznJruHBKbxsCw4iJEJAbNCiisOjSYTSkRoWhSKEhD0zYBEnPf0ONHD54+fbjdNofDzeXl7rDPbexvXg0f/ei4v8V4C6Ram+Q0Ik3p6jqBkCOmCeRjGXWzobM3t+vVqpE8oRztGNib4OTkIgoaBSm5WlF3BX38bHdxUc621sY2Nm3XhtDGTriLJD6VaefQtolt01QhQoJLzdINgk0pWUogFo4+5aur23y+fvPJG29s1+0//h9/62/89V/81u9+73f+9b/TPI6Dt/1aQpOz9LG34nU+AKG4QVO1rF4ULeTuBK0DrIbatbGNk8240tIy6BOJLYFmc8s5CvKlU8ucbvFick1LcGO+wFBUeR11n5+Tf5xgBQccJ0MsXyAvx9x60BbZ4lIcs3670qLErGolF0150BEm27Nt07e4uYrBYx86CtfH8f1nH7735f7Xfu03/9ovv/fln3vcPr0c7eqDF89//OLHt8PeGZPrISVpuV2vOXZGxJlDECJKZXQFLOfRr1+mLXplRhAQFZncEhHFWN3lZbXmXEbVlDNI8OCife218wcPz0Ogfr1ana9THnK6HdJxd7xRLqFDKICwcCstI5Zkx14kRDBbtqIlay6u7NmgVItkxqVtsA7tahVjZGK46mGfh+mYck6Z0gi1MgwlZUxperANxSirS/Zx0uRp2KVhl9MAiHoqmlSzk3IebQhlTOPhMCoMnb359NwdgWKz6iN1fbfd+U2ZEjGLKIQZ86yo7pt+1XVd3/c5S1De+Z6YIQqAmDlIhVycluYey/xPID/ZNtFdpAziua3MXZhZl4KfPMnXLtg2ez+52+yiMycUs4nNfB50B6hWfLfMHcF8ka5UOeFCsVnA3PlMcXJ38tkL8V66+gmc4v47Twy/21MFUMyUwKSgulzOerr56F4PVF0MTurBukgu9IT5NCo/gPkO4Vv+X4VxyznMqI9CcRqss5M+V5rF6eunjK+mRfPewKXGMY5q9uzLwCcHz7yPenLmfv88ZsjvhE2elveazc/41Iml9kn0qhr76XIH72KEe5f5mUvH3UNZYKM7pNGrKHFx4HEYudQ3kwDz2QX0zjn/L9iIIDz7/Vf3fRC0+FICsLrkzRHHHfK5IGmfnCgdQAU0Pqnk+1w857P/+FcBvMJiV3+HIv0nbRXHERFaZICnjgY/zXZ6YKev3Eeg/pzzuf+rnwSZ3UevTj/wvBADzJjxqROPpq6AxESVTow7Ty6YWYwz+GULWaa+vBVBWy7BKznGF4P5OfTkOahV1WIFVluE3nW4nG2wqr18bZi4YGdYnjERgSAiRKxuWopVAAhz6aiibydvMieESAZX05rpC9XmrFYJP0xgFmYQscFhRuKQGQYKejI+t3nEzcphrxQgArHMQO48g85zEmvJJ2hzxo2Xx1pPbckAMCskZpsoApElnblg5hB4gbOPnqoOEZVm604M5hlyd4Np1kpYovvy70rFmUcdVbTr9DIsF6/uzKKqpWhVSrp4EY0Lc87MVdUcFGaaLjFjMcQjUG2ti4oVLV2SjcEMIzGYYxZdE/kdfLL0wyQHzzZgPpMBAPcZc6uaQpYgQZxrM4jqM6nsTADZTKSD3cVjBmZQ5buReTWGmKfvuhBXWhbN3UWq4IYCiEBMqJb8lalAZMVdCCrskdxUdWb9AAAgAElEQVSjYErpOAx911kVph2naSrVS+Zw2AeRGNm0aElakkhwBHc3dbUqt2EQEcdGgjShaL66uhqOQ9/3fdH97lBaI6a+XTFCyS7MIqELq81q+3y4ef/DKxSIwo2JuGq2pVazvIbCXqmL9eV1mIjMvhbz3GBwg859QcydwO5wIzUfh3xM3neTB56mIktkw8yAwKFmJasPOef86OJh162axohZTVliLfeEIDG2XdepmhYz1xPmHmM3TVPOpRQPEvpuvbtJwzBoSTH0bdvThiUcA8VGur7ZxhAZxzSmBEdJY0qrrg1E5tY1K+YmRZXILDQcjzkrOaYpTaNpTiLMEnJSsGVNRZNaNoNZDaCiEK/75tHFmSWfhtvDITHieEzDsWxWtO43nrOmIiRqdHOzc/B+mGK7euOt8y994Qu//Nd/6Ts/+NH7z5+DxBntgz6TMRe4lyG9vMrMSBPB2wcPthfnZ8K7adipZiFOKhKMEDKK8viDj741pmIFq269XZ+99qUzggyHdHMp6xuJ53q2uRDiV692l1eXZQeJEY0iaRrzetuMh6JFyTIAbiiIG5GaqZkDQVgkmlou2Wypzc/voTVCIQJIVjJTkQZA0pxJCE1PlINwFCJyCdRFj4HXq7Bd89/7Oz/vrk9ff/2v/fzX3/vyVx6eXZjq88sP/uP3fgBP+8NVGndmZdU2sWskRpYoTYfQTk7nD984Wnr/gx/969/7vT/59nd/+OxDlz4VKmbCMKWSgTHDaqAcTYKzMLuQYMrWkiYqrsMwHPcFjqYHr11ND8fEgv68PXuwpcDBtfikxYU5RE4pu3uIsWn62HTjWOoICqH6WIElhBBClM12jRWSmpihwLwIRVo69FYTPhCcFMZs7nWJdQQJxEKQYmpFvSRVGXdFnd3D81c3wzSB/N13Xn/y5EEqZX887o7aNBSFY2Ai4iiwNJR8vHymai551W+3m/Mujs10iPFy1R4fbt9+7+uvNdhM6s8/uHz63tnP/c0v3l4N3/v2D3/0gw8uXx3csI582JNmWDEHecUQFaaLc+JcWnQnZ3YBfLEuJaKsi9H5XVzDfleK/9zE925hOHndzCvgQuv4i7c5WXf3uwJuDdyJULN2R206Vb1Q6pxnmrXpGzOjoMTwMoGzBG/X0YEpI27SV7/wxje+8fXX39g+ffviV37ll7/wzlvrVauexrK3oMN0sx+upnSrPnHMyjyMWkox9/3+6urmchgHN4QIRVbLoeGHjy649cFuKaDkfNwdL29vXl7djgWrrWz7rbvf3OwPg9aFmwhtwHrTb9ZtbBhE0ziqpyDiHRHzYZjGrCzSdjGlLBGh4X4TiLhoIQIHqp7oOblrMwx+e3188WLSac7fuMHjR3J+toohbbdRbTKRpovmlvN4uzsAuL0eLi4uJKzgUaQIN04kLOtV4RjHaQjcpjSZFxBYODQmBgezurq3HMFNu1JuYQlgkiAwz1rX+LqeU0J2U4O3Ha223HRlyjnE8bXXn3zh7dfOtv1hf/Pso2fX1znEhl01uyvESODVBocQUNTdQEBAyXT5SvO4Gw546+m2a8/ONmuh4yp6pNwK2oaIOWdmolygZRpzSdmHSYcjDINqWbd91xqMGy1N3wXC2XpN9qRYilGCSDEd9uM0TSjed/2mbUx7LTy3BPNSbJimW6Hct0gmX/uFrz19etZ1k7S7mxfDv/zd9y0fHIcgsV2vr673ddSQsJOqFicPYYn8zU8kC18UUEZO4Dl1mxWx7jOdug5PkFeBF055IgiV1YK7mGdBvOoPvPyFTn9+/vir+VwVP50mgLuMboGx7oZ8PY3KpBC4esrJnc0pdusYWy22O94OmWPn4ClnFDNf2f/wX3/9q7/w5te+/s7Ttx41Z+V7V9++HF+9eHF1PeyLcda4n/Jx0KZfscRxGsAgsnbuK+XCYdU0Rl1u4749FoqkEXD2nN2cEthCixBotUFKmBLaBhcN3n334Tvvvta04XjYp3TY3wzXN69yuT3byPmDvkzuOl0f0XS23sTNWQPORkPTWBRIdEyqprVJUmDOpilNRRHXfnbebbbbrmmkMdVhf0hEOuaJpQUFYtZiw6iHo00pb7dnqUjKRkRTdlFLk5VkAWDj437MExEIAVNsYhMsuxYrDjjaEKeUyS1Glr5d9810DHmcmLlpgjuX7GXMpkZNaJoGwDAMWjIRcr6zL3OuJXElg1lRU7EZqqqG4XfPmmojJ6tv6wy5LJ217uf7/rlp/EIonFeP2SEKC+OBZktgB6piHDT3BHCCk87OudXE1wEiBy9cpHlbeFnL0SvctkASn+WLfAqR8LvLqAzDGVQ+Xf9CGKoaB54JV17vSR1ky+hYjrPI0GY/4oWT8ZnNP/1XX6BnzCZyBK9c15pb3ocK7iFKRIBqBk6KvLk5YkWHrJoVz+f3qTUaoHvAwn18b5FmYe5sP5/xAppVTOvEY8IsV6zM0kpdWERFhOU2z8jQfBE1i6YFRnOd287cET8dcFco0XIXFh7pJx7cT95qIcCXEKemtOrq81mQL9KVTz0MWmiIn7v5PanZ5wI4fwmI6c/fwl9lpyf0qr6I9wGjn+a797/iywD+1Gf+/B1+6rufhas++9c7qKge+v7zqDX7ClPzLChaztNUvWmaUwfDGZaiU0BJy+xT1725yeEMdxmkk/qxWib97LkR0clQ7KRGBECgEMPdh2ve5a6l1IAy0mytVd9vVb0TMxLaNXsVxhKYQQIWYqkgiBGYyJkJXFuvmzMxUeXwszBATn5yMwehNmGsfLG55L4QWity6z5bL7O7M8yMmUjNhWye1MhZcHfhy+1bHOP8RCkXIjA3MIC1MTVQQQYU7pUixCAyd7Wq8Ct378O916z2l7bT3V5G+swpJggzxThN06xvJ4BQuWzMrLWzoi+sy3sPbgboiMByR/0tbmZggN2CEMMgIF3euyqorJWWeeI6bfNc6cuqOnP9aHZyrK8ZdJ5GDWLkDAfP77GdhKe0cKrqRBgYzvOHASOwQxg1LqQZvSc52VqTmRZ1crDCzSYtTAENN9SGJnBHCAgxdl1PhGkajj6ljDaia4WJK2OXiJoYeb1hkdBEdxeRru+rN7ezB+bYtKEJAWU1lRjarutLsY8+ehZjs1r1D87O27ZLXbGiKWkv0oZWtCtHCCOGlsCqMx3OzZlmwKouSwQCuzvICEEIJyzV59dofpokBq2orrM4mZMZzNzBEgJUzR2qIhXDItVc1EuGW9nvxtVKQxBiadtmvVpP01QfYNu2EqQuWydEm5hCjGkqOefDfmwileLuUMWo2rajiMQYY3O2XvVN7NbrbeBmu512u6ObkPu27+E8Drltw2q1CjlhGlnAwkQ0HI+mmkoZR2QocFC165tdbDy2zowYpFoal2LVUbAV3q7aadVeiuyKN30oOR8Ph0PD02q96tc8Wz9YbHsOjTnf7vb48MPVevP1n/9ZorDf7Z9dHmPHNy+PxS2EJoTg3ni5ndSfPxuHQ97tcni3DaFtYnGeVNN+fz0cd1GaILHpeZiOKY+TpTTuMu/Xft636+2jzebB47f09a/+wle62A3H6eZm9+MPPvrDP/zhdJknyYiAAE3SAXDXksBoBS5U1IvPzn1eH3olirppUVcQM4hBhQPAaRwnVXUCGGNKKAAwpNEzYo/rayADD/BOP56fPXztydnDR9u/++u/kae0afvz7ZnQ9OLl94ZhuLp6dXX5crvtSz6M46HrmtWqjyGaIQPS9Juzh87BefWjZx/+4R//yR98+9svL2/azUOEsL+8nZIKsqmxwTIAQQhMkSG1T3PFq12hhchJLEQuRQGFZwbgCQpoT4fdCDYT9Rm7Dm3bHA4HZhIJIDJ1Yg5NjAFt25esDI9NBFXVc/jiew9ffnh52IO9SIxuVUrvS5ToVTDF7lCbc0qipuskijso5aSezTSVcRqbftXENk3Hl7dj++GL6t+16rvzi8fuKefjYRyjUAzctjHGBlbGaT+lESFeHw63w9S3x83q4tGjJ+Ljs9sfblYXfbtZy4On71w8euOXBP31y/3v/Pa/+e1/8X//i3/zI3wbYzJsZ6dyRHcySAFXk/daK5A5KHQ3XeyjK9ZP94wlPrERsKBX9+OW+0VIAhifUZL8RAPgzx5hjnFrRaJSeGXphORzZZ0IVK3/XNWh5gBiWw77oYxAAgzokBn5RcYjoKB7t/zSf/a1/+Yf/dZ77721XfO6WzlpwrUhOY2Tpd3x+fXN8+LDets0bRhtOh6GaZocuB1udscbmK1Wm67ru7btVrHtYtPGB4fzZzfvH4fD5dXly5evrnbH4qhZYk45jeWwUwjWK6xWHZG10jddT4Sik2KKtVoTgoSoBVMu41RMJITGzLp1x8wSIUysrG6lFFPLyUxFuDsebLcrqkBAJKhj2+PB+Wa7XcUQOGQtmR21bkVsaco5l2lCSlSylozjoUyjMxoIlZyFY4yZKBQ31AWdXALX2EiLG4iOBnZpqOkwWvVhqT3KIaHWnyJMau9oEEhcQlH3y4P99W8+fXBxtlm3x8Pu5YsXh9tMBoGXKadUhBBjKAHKBS5mNJuVREBwOHjtEN+1OO7Lfj8eNny+oe3ZthW1coyNAIzQWBBmpMKTZvNsjs0ZYoRaHnNQPQ6HkRGkka5rmzZuVh1JL0xa9DAcpymVKYfQbNebdXdx80yrm6+q5ZKDJA4+5eeHUbrNw5av5VH793/rF7/6pbd+/3f/+F/+2/d3e0gLzflwtVs9bqaiWQuIYqAQyI1SLnSSpsytj3BKnfw0ngQwP1EQTkqIe1nfQmA5fe0USOEEXc3V0pr13nEYZyT4k0lsnQN82fO9uOEutV/2XQGJ+78iouNwhBNTE0QCB5Coa2hldbZRTftxf/PjCQKs8Td/Bf/z//KPV1u92n1A8sE2dlfHH+3zIVOWGKYRl9fHw5C5WUnsySmNO2k4xNqqD1nhZhzUtaCUVz88sk8kwpGA7AwKCE1ZbULfN2fnfSnkiG3DIfLFw5ZkGsb97f5aC33vO88PhyG06Lv24eNNpEZ4At0Og4hYs9LYGgXqQyvEsWUdUxrSYQ9P1oFzAYojoItYb9vzixijFMtZU0pHCSQhtM2Kwyo3gY7TNNlxHKAYJx2TThMAXU0GDkAIEgKDFWnQMoIDkZNnJacmxK5tsiduEUUmH1LKbgYj73uCwS2EIBRyVvdsahxD3/cxxmmaUkpw65seESGEIgpHjJFJtOjcdt1NZyXEvSn93uTsi/TllIfS6c28n3V+Tl7szgw3IrKab55AqrvQFadBcYdNOQCqNuf3VqVlnfJ7x/ZTHlQTWNQ88ARy3U+WPyfLJtAn/nYPv3Wvgg8sspw6sBZGlKMuenznI62fWiJnnOWOZnDH3Pl0LaiO5qUNSfWeOSViFVu8G5czWjjnzTVadVvYVOC5e4PTMjnQDBXeS0XvndDJPeATyODppDBPIfeqSzN1YFmu6yOsbl92b1fz+c1qxzv92TwF1RwZJ9IX7maW+2+CLaySehp80kf/dBsthbfT/Im7WW4+efO7Zz8/6dqW8DObkS6XPwcqPwm6+ey///SEp89uoaKMfwn94OnYvlhZ1fTspzyb08f+Esf93Fvwk8CsT30up0SLbZnffy9rkgNTwCE0Dzo66ROxYEOVHnV65xbElxaB7Wmiwd0PBi3KkU8wTd3cvcq4qnKw5KxmFbAQiScCExB8cXCvXyGmlBPUQOAYKnHSzUvVuTngiEE4Sh23Mt83sBCzuytgIKsCN2e4a4Fq7TTOysRE1QvJT/OS1SKEhZrexSYCMLOixcxhS9DvDjOp67o7zExroxZyIT+hs3W/+glsUd1BMChZdakCAwJBkLgWzVrEnRWlTt/mAmGBsXuVSNp9IviCSXu9wwTklACiIHCzUjJgphKYRUII43QkIoRZp9l0LQTmWrQULRxQezkv3mrzhVTpDFXxt+pckKnQVO3XGAPgxaonjMNpNvYSsMygYMU7T3Z6tXCLOROckT1zhfrcWosJRMJsta8UzbFdtdJH5f/qgt/NbDkANJuOkVnx2AZzdzaWuSbhp0WPnMEzxAYuxdOgojk3pWvahpvMY2hltVr1q97NmrZpmhhjJkZom/Pz87ZtatPpvu8XR8c6R9N2cz5OKZdM7kRSFGXMJH5+9gCw3e3x5ub2sD+oou1Axg8ePIixHcrxcDh0tHGlSC0c7KiWPqq5gsYcMBuH2Wkg+nxHiUB24l/Oc8XpjZ1fP2WjUkwiR5GmyW3brlerEML17lpVs+aIEKR2EpEY2EuaJlxeXomErutIXEJzdna+292WXMy0aVrLULVSSs4l55xzrjWccczDUNK4a1sjSIxN26Rx1Nvb4zRN63W/Xq8/eP8DAl/JLSMOQ4YGzdqGwOCrl9e3N68ePnzABGqlLiFd2woIbjklUoycUgENUBt2t4d+jdg3TRc5cG/ujpSyFgcQBH0Tz7f9w4u1lTKot7Ebh/GylEj09ltvzr1gwI8eP2nbniQcp2l69qyRV1/7ua9/4xe/frZ5+Ht/9IfPnl3dXO3NuYkWoqsqWR/YxGk46EfTpRCfbePZNrSxASylfUplApiCAo+/+GafmmnM05D3x+uPn380DjhbrR4/fL2N3euvvdU2HPpeVnj09Ow3/t4vrdqVFxxuDofd4Xd++1/nC89TMUVOViYFoQsOEJxUPSctJcNZhInFVE2NLXB0IIugiS4SJIQQAzGlsagZM7UtE/HjJw+/8dd+9snjB09ef/zw8XnVuZ5xtyvXQmDHuN+/ePZ8d3U9TUoID863xNrF2J6fi1DTNYB4No7tavvw7OKJh/i//fY/+9b/+6ff+fYPn19etW2fbBonHVOZrHTW56ks/hgMRILA2WoHOUZkePEy5CY2XbOK0mYtUxrHIYUmdH1TrHixPCk3JBLUvOQ8cWEGSRKRoiXlMYZV1/UPzh+ZFs/5+vr6bNtdnK0Oh/3IuurPvvk3vvHH/u0f//g5jNRIi87rEjvN3shgh5uW4lTrDyRmJiYSggeYQpM6PHRtNvWC2MaguLzdH/5sf7u7/PKX3nxwvt5sL3I67nbXZThOk+Yydl1oWmlW69h1P/jhh7e7MU3oWnnw8LWvfInferPpW/8P3/13H3z4kXjz4Pz1d5++9+ThG5vHm3/0T/72f/dP/i4AgZzhyTf+1n/12sUbaUrDcToc0u4qk7qs4UamKFnrkugZXlCJiUus6PPy+cm45o53dfppWdruxePkFQH9K2ynigKBHKbVo7BObgSvS6TQYqbpEsEN4kpXDVarfr1ppA2PHm3f/sIbv/Jr3/zGN37x8ZOL1588NijBp3yV0tX7r94fhmMIFNvgyJttQzJ1G47NZrOJUxqub/b7w+44Dm3bkqBbNat+tVqvu65HgQQjkrOwomC3x3gcbDgeb26Oxwnrbeg3AZFTTlnz66+vzx9etF0b2UwnK8wSppxyKQSEGARouw4hHPbDq+vrw4TYrwA48/nFAy0pl6l6i+bJxiFNk7pBuNcS9ochZ2vblon7KE1Lr7129sabj2J04LjfXZmNLjKV3LZdDG3JyMmYyDQeDnr1and9dUwTttuHTRtTGbKPTiWbErE53NTcCM4cQOTsSiDL5CEEWa16s2QDUkk6FgCbzbqPfSmUk5Y0JckQNC2aDt2Kpbdf/MbXbi5fvnr50auXl9NxalvpezaX8TDt92W/r/WvENYbuDisVC6CqAefjthchL4PpuX5y+G73/t+Hs/ee/fJ4+2D7vxsGqyJDM8Seum7thPwwCHFoTRpWq97piJEbFKSHveHaUpE6Lqu69qub9eb9epsI23HRGnIAhGWQGzFt9uHMAMfpun2OF51fdqu+7Zz41dK/v3nV567s+7NX/j6V37zF/+nf/gPfvNf/c63/q9//gd/9p2PSdqb28xCTQwk5lKKw7Q6AChoQXqXENrvMmZgLij7IqSp+f7MSpkTvbksseSmdz4CdD8lWX4mwJ2JeQGrP51W0F0k7wD7HGAtm9+zt7ufYvpMHwMcq753Zy2wDHc1K15yXDfDqONw/MrPvHb2zfiP/vvf+vv/xS8Vf7E+G4yvVmf7H/zHP/5f/88/fuebF0OaspGiKUZqjcSu6VomdksiHhs1VzIOEAFysePt7nh7+/xDnD+kMgX3QGTmDOe20ydvtOcXm65vur4xk9hIEJSSnNLNzcs8jSmNsdne3gxtDF3UPE7H3c359snZ9tHjR2988MHVbn/keCRJYJc2Sq3FCwAnBjGi0Pm5rPtue953WwnnLlFBSWKBeDaoerXwBaodqjRdsznL0pRUUApyRiMgapu44jZPQfd5Qpq7kSO5asr9qKWBWBul72K7iau+LXk8lkNOGcZMZ0EQQmAKWkwVTaTmjGJsQwhpmoZxLKW0TSDQw4cPmMI0TTlrCAHFayoBWphEvKR5dnqbfhK1xE+A6/1stIJJn/08LfShu899JvNfavE+V9bru6angXGfwUR3e7oHO9S9VK0/aGbonBLfn5R901zjvkNmMJerGMRMxchk1lDYom85Yceo6d1cY3MwOYF12dmc1t6DgbDgBr5ckgEnn01fEOkTDuZANXh3uM30tTsmii/dVsyJmeacs96vJRGqjCmvwRUtyNFcF6Rl5ri7G6ftxMo6rfan27is1Hz/+dEsZ2E3Pe2IlzeiurrPD91n2gJJ9WUnmv1FK9EPXB1yZgeM2pfrNO+4luJEItXw/rNv3Ce2BTC79x7ch0IcqL6gtHz63lz3WYSHABa50xxWB6FPTrz/P20zgPX5KOxPsZ0QqxNv6CfQAj+90eIT8dMf66+CeWEOAaF2Rwe8A4ArslsLnuYOy2qyILnzf0Q5Z/jM7jzt0GviX1dMAy1kyuoQXCl5zg5FoQJAmFlkHsMVmSAKMRZTLwWofiFy52PlYJFSFKhqDZgblMjAFGaU20mIq6eSLVxFYmKBKc19hlhrT2vUYMzdAWGCwMTVPDuc4UKV9gSSqp4kBohp1hsyFTY1FpdAADSp1/pk7ZNX762hdruol2C++EVZPVe5B/C5+dwCBETkXOc+h5q7mgsY87UEEBMHY9KsKG6liuAcPLeEwR27aa7A0ZJR1IPNg762m3RYKQa4NAECrpwpiFQf/MDCzu5q7urVvb6quWfko14fO80gJsNn/h4ZmCHgIBwlzDRvdSebGckgInIWYmI2NbgATmRLWX2G5+eGzuQgUjODionXnhNU1QGJZklG1b95BcKIDLQAW0TC1cXCee5G64AJBaAsxFaaNVX1Ha5cDRDN33U4StY85ohQsl6N1xus26ZjIlU9Ho/uut2sooSmDX3fNU3Ds/hRiqbiWeemmqYuKVtOdV6eOxFwdDSkarvd4XiYmGJWGw56nEo3KYHNeVKMow6TWnEAnkmzh0DBhVAbTmZUT4y6vhFO97s+/znvoznrhs103/pUT3UTNTNnMELTxNibIUpf8qTFSQXC7kqEJpI0blPeH9PqkIlaFuqpDdwGqOqIEjk0OSVzt+KqmnOe0uhKcNYqVmUwgWOI5iE1PA1TQkrqlkVMlYMENZDg7Hy93nbjMLh77FiLUSBpEVehYGIawWAJIaKJogVtG4umnNC12Kw3oeUmBvHgJTf4/0h7kx5bkuxM7Axm5tO9N4Y35lyZNRermsVqsMmmgIagZosLrSRA0EoL/Qj9EEFr7aSNhIYEaNGU1ERTjQaBpsBmsQmyKos1sXJ4+fK9FxF3cncbzjlamN+IyMpks9Dli3yRd/Brbm5mbuc73/k+5xsPAKNOMSci9giND9DZo7NLhuanH3zUtL0Wnct02I3xYSkZ6wa06zdEnErJOXfsY8kl5acPHnZhuHr18vrTj6MSo8U5TvukThlcv2n7zjsPgOVwmEUThzWyR9eEgUtJcZ7iNKcCz//6Zxyg69o2dG3fANKwtlW/8q0ejldyHYnIsztbb0II5GzKe0kCZMMZ/5f/9T+dxyJZc8xXr26eP/90PEzzNBNxjOl6d9jtACaAouAVGEAAEijMUCCdgyGcD/bw4my1WofghqF78uRRcM45evDgQQj+weW5IxVJw9CGxjRe7+KL2XOcRkZgoDzHPN5I3Eu2Yf3AezdNueEmeO/IOfUpShf6y7MnF5vXvd/s4vSn//4HP/vggxdXR3aNG4bpOB/iXDIAQs5ZRZdEpylpRlEwUqoAFgVqtKgWFTX24CCAYdYiIgLgQ0OOi0jLIbQBnSbhlCHNIpKHlUNALSZJQQ5924TgNNOYchQrCmPU46ioY+Ovv/7VNx8+eXjz6rg7HIFQUfhk1my41P2gg4UTJIpADJA1izcfsBJ0K9rlPcs0i4pzDXtOMd/M0Lfp5dlBgTYXl41biTWzbdO0neMul7nX0A9t1w8325Q1oHPcnVF7dpD00YvnEpNmWZ2dW5H99Oqjl3Zz+LjxTd8MjM6R77vhrH/+P/4P/70Vt90dPvzFs+9//6/+n3/zg/gB5AOAN2CADAhEgoKCDTr0YA6MasFW1gwoUP8Ha/kCVgFM1dutwOL7sqw1dasJWjVMlkImu/sD0FRtMeStzy5EUENFqjVTREWzYdVhBDPjuq0EALlNm4IjZMdIICpZDA5QKZc3Pp0/ge98563f+M43X3/jyaMnF13v295b2H786tkI510XDMrQM3Ypx+0oOzQYQtf34dX2FTlrBj90jQfc5+3xOM5z9Oyb0DKxc/5ss2HniF2KaS5zUVXRYxzffOutzf68a/p+tTpOx2Zou3UHTNvDfk7z+ePL84szVT3ud9MEknPBXLKiEvmGwAMjQJMzHaZyHOEYoYPEHr2vexgnmqv0igiImEhBACSIMeWUDcR7ABDyNqzDg0ftsCK1Y5zH43hw7AKhqIAYM6NiTgWMg1vv03G315cvISVIc15tAEgFgbzPGQB90VI0nwJGpbplITFi5ui8hVbcLF8LSvUAACAASURBVLODlEYp6h10Xde2wzzlbBIa6x0CGjWwOfcPn6zbloKHGKeb65vpEBmhawJ7XwQlg0ExBhNrVoiAqiDFGA3IEE0ILNBwsQ49oY1oNO3zzctpeihQHLvQhcGRgpMJzcwDmxEYCbqCYqFhAnbIDGRseUpxSqKYsGixmBIArvr1qh8IfU7GNOZU5int04s3n56jUREcJ5nnrGqoBYpCWwR3au78om3pmMsHe5ouLvWf/mffee9Lb/zx//v9P/rjfzu9BDiHrmsAfc5WooBAZXGQQyYWqCwRNFkixWpRTVwZ/reZSahqZWB2kvoAJFBQ1CW3WYXsTgx0BNJFGZUUDYAJjJZIHhemOiHVwgyoynV1P0QMRKcQWE7YmjGAGcjCpTA0NQRmRHCqWMNrEG/VuJAE0TxS8ap+PyeAc/hv/7v/9PJx8+5XLn3zjGmLNJd8fbP9GHT66nvr5y9u9glSBkVw3KzWHLOlMqXZDAtWCk4Gi7HlfoONuIRqyNAhjMXYx7ONu3x4Pmy874uYiGjTBSJgJ1qyWTEjYgWoSXQJDQWPF+ehbYNvZuc0l2gY2XehldXa6va4SpZIiYaSs2Oz4GDVA3fQkARH5+fN5YM1t5x0ziWWkgjIOR+nKEJqrCJASU1TFjBqfRO4NSBg9l69Z+ehCejVHdikQJmFmMGxzIrIGjFNEV0BlsBu6Fp2SqyAIgoALuYEhOQZZFkvnXeePJGTXMZxTDkToyGkknzTQUFCRTApYlmLCgEAEpLWQnEkMFNYhgmC0Ql/QbIlFX9CBO7Fs3ZCUG/3n3fvVFn4+ji4h4goANr9+FlhGZv15GZV/gpud7R4il9v7QnufgxvN712K9BWLwP+3iB6iZ6Wp1t9ri3ayWTGANWOC0BrpvsEIShWXRcEQiS+v9+uQNyJ0HjCn60m+mGhGmCltS2lxidwRk+YXM3OV1zslrF0izPdxvNwh0ThCc06Bey1h06g822fLS/VCHbRsrkLUxf0zE58KANb+Ge3zKXl4vCE8VRjrmVtWNp5y1mv992qQLEt13My32LnsEq5Wx10rsadlb3Fy8IFp5FnyzJnVbQGbqHTW2D9XooN7y7AThjeApwhOboHQy59cX+U1I6m072xe6/rMglOIdTn9M1uA+ZfgnH+48Cc28NV0dZf5aO/9DE7lTtWqKX66FWC0q9ytnu0vV/+9S+8sNs85Offum3M58/2S3g2IircAxRPs/8uY1r/UQU1BSTme9aWECe5hbzv8qyVOHR6iCKAESIAE1ayUy0LBAQTK5KViVnNGyAWlQr5GYKoFhUDYSR0vJhiqoqqRyqac8kAQM6JqakxLr5matnUqo2mSN0W1yVNzaAUQiYkM1CpemG0gLe8+HChmhZSw7ogkyEp8LJMgy4bdzJCQz1hQwRIizqeVT/1ezO5ilXhCe6pS08VI6r48anGUgFK3czb4kLOyyRbioxNQTIogbIpMjIhIhup0hIDqBUQrMpjYOicA1UTAzUC4IpkIxZQQ+DgjcBqD1S02zE6NNJcyUuE6AgZjTRrUhWxBGSLtYMCIVd+sS5Lgy25cU0AeOorRIdAiLyMEULghdK2LKAISEYI9dFJSGSootVm8Y71ZgBZBWuigM3ACoBn5pMfkkgxYrfQVpFrMSdILf8xBsRqD4mgVBdpWlZfRF04cgAIjEuShxiYoRZd6UIGVlFGKkWOhwkVC+aplIJHMz64AwDc3BwD88V5v9msSs6L+LuhZCtRkwKSN9OUY8opffhinCZQdewJuG27tm/B8m43pZTmSUSImYghF1Gj/WEiopyFDPcSb7bjOCVQsBmzZu4CKzIzAsUiqgJkFaFctDVtIU/nknGZGkBgwKAAJlWfTqs5LaAgkpmWLIJAyAA8J0EMOcZ5RofIzOyQ2YQMiRVzTIIUnB/mcdakUsphl0sx9SZjUi1tF/qm8d4DWMpRVVGY0bcNIHG2gkWBuemCKMKc55jn2fyhTLP4QEzGntu1Z/YhakrzNG85QOjcDMdDcs6JDyLFJCdCHtaNDwzFwoPgkLu+WW961yCA5mNJ00SEvEIkxKKQi2s8CjjHbWguzy/6bv3s+fO+DSlls8Y5f311Y1b17RXd3Pf9OM613sMB/uxnv3jrLVuv19/7zrceXVz+T//LH27WYKIodHFxvtsdETHH2bFvel9UpiRjVHDmHfX9qiUtO5fnkqzEBFSQCWuZiqFxQ9Emk6ShTDqXXBrf4zz7TJNzjjybA0NN9vpr5/2Kgm8ch8N48drVgzzngG7oVyKYJkAMpL4qD+aY0zQ7ckPb+cbt4SZpbHp3fjY4zyoJUS8uVl3bSMlPnzxGRBMhyCmVVA46atEsUNB70Hwc5+PuMO5GzTlw8C4ACZF/eP5A5mLJVt1ZmkVyfPdL33r45Okxyvs/+viHP//JX/z4/cOcj0V6JstRULtVY4q5SMkF6nbVAKFAKbmAVGtZYkUmJSmaS5ZJinOOvACgsUdnBYqJMQBBGYuauY7IcRM6IEA2zYUBG4+excykzILZDMzyetO6pvvk5bUJsFKen52fPVmdrS4uLl68umlCB9EEF/oCAmbLdeVQBREABCyaswEAOAm+1AocckiOxml0nhFdKSmaoAIQZMGPP9k+/3QX2rN+aL07O7tY5a7f7WCOV8dxrwYm4Xi0nEPTrrr1g7Dunl29mG4mHXnVdo+ebIbOpXT42+fvdyGcn226dshTYfSXDx4KPnntrbPALfvNt77z5Du/9fY/+4Pft9Rdvzr++Ic//+EPfvxnf/a+YwUFSWBsxdAhm3lUANHgySAbKhAYkiihCVZDbjK89ZxCIyCogibLU8/QVYcN4qoPX591dUdr1XoYBFVxUQ1hclR1VRUCtxlUT1pKSIYADqBrGodunqcpaSlWJTVhgK++96Vvfuub3/zWt9544xGFHTTj+cPVa68/HFZt0kktGeYsB0ci/sVBrEgaDUMgabK2x3maTdomXB5vbiwJzrg/OCOdjoeUSxva1bAygpLFsRe1UormjET7NKpVzT8A5K4ZHl4+YufGeESH3FCxzFSycNd6b5JKknEux1RyQcdMRK4lx0NzZsxzTrvjYXfIrg29g67zgBDaME6plHI4ZjUlRlRBgCY4QvBM8zQ6Qm6JsADZalUuLptulRR2anF/uDbFru98450Wx44MCZjRlwJxEhECCwA5R7kqaYxxvU5nl5v15aDGhn5KxwLqAzITVpM+xIgJC3rivsPgcGh9jqBmCWTlGyBIJU5pVMznl7Rat0gYWvfo8dnrbzw8P1/99V/9leSZSYfWmZXKJGeitm2HvpCVEjk0VHJRUQZ1jnwIzFBItV+dPdhIPHhzF5uudeW4m64/Ta82hy7IwwcbsxmxMBtiKDodp/0Up7pfYl4REBp0oe3WLQrEuYzHVEpxzrxAbgQMHQdq3fkZeBcOu+N23o3j9cubn7dtcASAwr5vXBc4kDm2tg0NBjPbhgZLijfjyz48eHj2ztuvfePJ0we/8a1v/8m/+fHPP/joBz/76bjXdX8e1m3OU0xbQDRmIAJVIyR2xohqjGRZRAvW3O2CABMAGDqAWiCkC6CLhgjOtCanENVOBUcK+S4YNV0UYKCS/QHNTA1FF80FRTZEpOrtA8xGjLTIG5OBKhACOZAaf9KSJgOreTNAZURHzo/TDGTMhg4LCXBuPHzv26//1m994+Hj1e//F18OfYn5BfoEcDgcx2yz2dx13dubrzRj2cZ0nKeoaSolH/Yxx5QAEUyBFPIRCKCD9cP+7OKyZ1bHNM/w6kkx2RxSVq9uIOF5TDFnKJEO+2POZXMeRFKOyTew2Qx904uKOTDDmI6vv74SyezcasNd54qMh+M+TdR03PaN47VoSTnlFKWU6XBjxRzlzQqaAA8f9kjatjIM2XlKkcfoIGrORTPEGZm9Ks9jLJoAHJKrqcFuNUxpRhNhCx4AIqFzgYaeN+twk5MKmbI6RiSJMO9nbIr55DpvKtM8GggxFTEzvLregbhpyiWVkgSNWt9659KcjsdjHDMQOOdEy2HcrbXJU0kplVJEBYrU/HTFIgkXUwHRYpAXoV8zUEJAggop16060AKOLlv3u//CL0e4Vavj9OcJggW4g7PuEV5OJYanUrWaY4YFYKogxCmDgnfg1wnoqvred4zELwrPvwABwFsRyKWVAAZVfhdVqVb5VFNHAqu59yoLsgjQkyFbrZ8jRBUrAKf21UFsgNVaGYEcV0lhhWXa4sJcAgCwsngnECAaEqJWKsAC4GGdy3ACtO5zf5aIajnRCciiE952S3q6Ky9GRKBaEHnLZ7sDzutD3RaSQF2SqqLwidlQNwKL2r+ZFbUFR0XTumuihZymJiKV+XELjYEBe1qE/A0AkREBQVWtqIEyuVq3aLpo0JjZCRZDNRM4lVYub1Rt36qkuGhkk9Gyki6QE5gqM5lVxsYC+y8w2AngqyE+3v7c3fBY2n4LeZoZ0kJFOYEjCAh80t6/JTzddvPfPya/6HD/cejV7StfxM79tY77wNavCc7B57pmaeHt0oF4yxm6HavLakBUZWhqcZ+IiEhlFd3yFe+guruigdOYqQiO3b27lBciiKqIYilIaIxVEj3FBACARkxUUY+TgcGJqgWnUSt1ZCtzVXGrZXqAQETABLrkHYoqiRGQEYFqAZU6FgnAASxCeiJ1nnEN+esOe4FpmUhvOUdohrpQfZbht2h2ASgQklsgFVWFSgRbUKiTYQMRLhoRVuv/AIzYIcI9ZyVERNFcv1tX6Lo0ieqyciCSIyREj1a0zAUqjEYV9UexurUBQyCuQHpVK7+tPoZFDJUBGQysSFEVYCCPHCpf3kSKnBpGxKclpm5mVERMDQkcO2KKYlSXUQJgYmZgPA0YM81aZHGirB2+FKgYGlW3PDPUEwHrtNJC9YJfBgJXfStekgtSQUCAyqOt2ohSRYrZAO6XbpeSAR2QVbF8IkKyKuukYFCBWTNEIj5ZEJSqrIBVfV4WAkK18yAmUC05JikAaNMs6iXGMk2x5FyyAhxVtMwFFPv1arUZAOE4x+vr8erVFRB4AjYgpMcPH/sQhtXQNP1+v3v16noai3dUk6w5lVoBKSoMNM7jnGKUBFpdUKyIECCIAFR/E1MzQDSCW0tsEwUADnia9Qtrl/CkJFBDTjRAzFmMgE2jVOUr1SLTGOcpT3MOTMEzIjGrmU2THA7QBjSzInLYj3FO4+54OEQwazwj2sXFqmm6vl0Va1POJrtSwIE6z84HRZiLpDk6bpBo6PuugRIVjZqmMZIikRh9w8TYr5phE3a7bZLRe/QNZ4mHcXd5Pnjno+WcxLMb+nXzqHv2wcdt2/Z913ctgO33+22MLfs2OOd5fzgCIjM53xhinFN2CIo+ND60rz95uj0cSkkhBOeolCIiXdcVKR9//NFrr71Wtc+0aJrT1fYqNI4dvvbaw7ffffMP/+gPiRo65IkFSDCoasqSbUyCITSMCOMUY4mA0o++ax0otsPQDvjAubq3yDnN81HVQghd1xIhsWNyZYqH8cU0vmh8uxk2fRhQMM0pTrn9JMQo3jVDvw7tcPl4E9gNTTcMKwNMUYlDcC2zY2NQQ7XO+zY0CoIDHae9qBBASimORyJbr/t5Ph4O2w/SWEqRkgJD3zIQFCtt17DDm931uu/naby+vh73x8aH9eWmG86MG89BRR0xtyHO0Yfh0frizTff3qX5hz/5m//rj/7o/Q9/osZNT+w0zvE4HofVuhuGNBeKyaryIhgSOmQA0yx17TdSQUADKaLFBKQUAc1ATN4B2rLygAHgYTxCgkZD27e+deRILXsOYKLFDJAIPDMRlZIr+zY0jffN9niEDKOlDz58NnTr9qx7/PTh7uYADIRESAQMNVGiJVvNPoAJWAXxCa2cmgxGDjgI4akk/7Q6eQKxfH0Td1MB98MnTx599cvvrjdnJUCRY9EpxiKHY5y1784TG5KLc5TrtB9f7a/2188TG3xpfPyNr7/XrVeGKlZ243F/GFW1a1q9SbvdFWx1aDbr9eUwXDx+7+Lr33u995evXo1/84PX3v3h69/83ldAaDqmV1cvnj//9Oc//XA6xIYb35JZyYUQFKoHVFWyB+EGiKpoI4mISDYhJGImqjKRSBw45kVrt/YLKrBzFCimaGZEqARabcwIPblgDguISilKjQMTALFFbQW9p7733jOY9av2tSevv/fel53nXHK7bl9787Vvfvsbv/Htb7/5xqMEv5jkqkgukg7j1e74SjT5lprOeU8CKeeYNUlGAUJEFySo5HJ4+Wo+u1xfXV1dX12lHJ3zrQ/snRZ5cfU8xkjknHepxOM8m2nb96EJLnhy5Ly/vtlXtmzTdC4wN8wBj/Px6url9fZ6ndN6M+RS8hxNJTj2bYvsFFAIzs8uplz2+/jqxc319bRah9Xgut4XESBQlZTycZxzLs5R4xwRU+XSmDvu5qFtvGcFDcFef/3pwwcbxJxSnqcpJSD0pXgzMnMlmmgqYkwNONgf9sTh7KyLUVTGJMkIBInbpu2H0LpZFNARiIGqGjv0TCoiuQRCgBwa533oBjceS44WI49jzrLPExSVoSfnjFDPLsLl5ebx0wfnF+u2ce//6NO332guLs6018NuH8cIRfrVZd+1cZLn5bDetDmaWmZPPoQQnPdAbII6ORh67/pNC13niuVtnO35x1frNj5+vHr84Exr1gwMwNIU53HMsbDnNrg4z55DF5q+79bDKsd0s92PY1KFLOIAkcFMcp7Zu/WwakPw7NCMyKbjS9DesVex4PyDi4uh7XKMbWj6viWQnOZx3PrSrMJlaGDUl2T6ta+89p2v/NZrb/z5hx9u//zf/egv/v37z19tQRKYmAI5JKRcpcAVFloykiEbAogUVed7UFs2hUBoXJ/ZWouNVCsJwBRJUQ0BtdZ+GYAWXaIrsBMKZgARyDlmqAUXWpBCtaxdtlMKixCDmhowVTVmMqyZlaqejIgOEG35oqu7ZdViKtRlQCGn/QCPn/Zf+eqbZxf8jW+99ju/++3HT1Y3h49305Xivgd+dfP8evtytd5cXl52bpMFWzo050PSs910vDnsxVm3Wl1kJmLLlGNGYU+uc+7ybHW+aQwTkYG6i4cQU3e9S7spTznt9+PV/nkpgOrHYxaFfrUiJANUNUIfukEkH4+HeZriNK9Wr4tk9qXtib3lecqlzCW1YTP03TCsATSleDwcpnmm2TDJsCLnqOvD2+88iWlUVSaqe1MiMsBxzjmWmIxYSpY4Z0NCdGJoaqvVWbdpmY0hRkhopeQ5kbWuu3i4Zmp8Mz77aF+ScNs2PgCIYJZcDGFF1vVhu79mZuaAKDEmU7Wc4yRQQLJIFmTkQjmXkqt6IxiYmiDybnewZKUkq8alUhkOZLXKkbCyjGpRQvXgWcgyBo48mGFVU1ZQFSOsHu6/FHV+QWgs92pf7+JVuMebuRdcntAB1CUsuK0vuReA0ud/xE7VHmZLbe19OfK/+zCEX240LiI5J67VcuZTqxfG8WdKIE/EoNvrsVPwZXfkBjgxhipsQnAbo/0SRFLTP4i4MKHsNsQ5eaLYPQ6U3alu3a+DrG2+i4tuX79HE7p9T1QW0OqELi3h8An0qdgj3mMb4V3l81LxuPCbYNGFMTI1dABqp9que2jlqePsDoyzE46nBgv0bgudDqGSRk/EMtR79+OEQQGYaXX8BVwEe1RrjH+nAYhGxEuFjN327md6aGkMwiIVfu9dA6jsx9uhAl94VAkjXGg9t0Pl76Il/SqH+xU/90s8ptsXK4iD95Swfp3j83jTr4lh3VGrTmQxcgtl7w5fxhN36Lbo9rMyq3fIClU6972aW1hG2IkwBaaGZKpW9ZLgNN/JncYKAJgVUzNgZA5eRUtOAMjeVXD29pML7VNP9dgLvmOgoFgAeSGccgVaEeDWLxCMARiyFFICNq2PWAJkALcsFPWqEYCA1Cq8zVXqHaAKVBkAAEF162MkcphzhW/y0qqq5IT1fgEgIpHlkydHParTF6CZikpF3KAiVwSLc9Vyh8hAa8JLl7w+0CIRbwhgCOQcGxFgYQHRJauAVgPLus7UvktWGBEAtCI1JwmF6ggNCIq1CkQAIXQBkJDAUIqoqQrIMskBwWgB3wRMrUYWsOySdEl9LPfoREEFqOjnid20fOZ0YxGBEUlECKgmPRYO6O2ydn/xvTcoK34oRW4nIdXuKopYKyUNqhwNGiAZgkIhIzCrV0RIySLcLR8V0AOoi65aRULNzIgW804idAQOBe3y4nJMB2Zq2qYNTZ5Lnsr1i0OOBQzYzTHGOGXNEBwoYdt3oQmqsNvN7KANDozSWOai+91EzjvP/aonijmXohAYunaFWBP+5oNDRBWxao3IxQ1gAJLATA1QzMDEQBQNCatfLti9BJmB3qawbic/Ibo64a3avdSeZwcKqgUQsGnCerX64ONPUjIwInQIqKKlFOcQoaKIBmgqMk/x+SdX25vsHZjATnLbAjsCJFFgDzmCFCsFigmKBlDfNIhQSh6PmQj7ZtM1rXoEJe+5X59tD9cVVhBJAKHvO9U8zdu+b0Lj9vvt/rDve+dd531T0jIDvfebzRkzNm3DzNM0Ho5biVlCC9C0riNySKBACgqixxghFkJmapwPD58+jB/FlKXrPTsyENEiWorkT18+PzvfnF9swFA9hDZ0vnFNyFbAwdnZ5h/85jdffHqV03VOJTh5562nzvH1zafM6NgxkamOU9YpF4kvxZpAfecfPLh47cnj6bgXzTkXZmJmEfHeD0MfY4zzPAzNenXpnKvJ9cZ5puCD69s1bKhfrZhiynqYj5QmQjf0XdfzLPuYyn47mWHb9pVcsOn6VddhA1MZd/utHEhNVUVKVpXWOTX4+Nmzw367222bJrRNE5wTFDAXmqCIRYwYiegH7//YREou7H3T9dy0/bAC9GkuOaWcDa2owHBx+ejJ4xnS3376wQ9+9sO/eP8vf/ps+5V/+LqwxZjsBuI8V/J6zlmq3g4AoeO6cpIBiOlpl8umWcAqD4oQ2UDFLMeMRMhADgBQTZvQgEOopgzRZJQ4zxePB9UMoOwwBIfEpiaiiLU4qyAhErB3Ku7Fq5u8xtUwbC7Xh+OhytVY3YgagQYzQFTPHhCz5kqoRaopF1mSMQqSxcCMuOZjqm+xd4xEBhoYttsbNTtbrZ2Vhsz5wYd1TFFFFezp649urg/TPM/j0QkwUT8M8NBblqvt7vt/+cPHjy6/9M6bTePG/f7q1aeE4LsmQz6Ox4fnl8r5GHaHaRyvP4AP3n/86K133/raP/i9L//27/6mCh6n+dOPP/3pT378/g/f/9f/6uYv//IQP4zx81uKAHgGDjAfDQqAAAhAAHAAqmJa05pqoFlLVj7Hau+r1UdCsVjRZGYGDtQt21JAgyI5Sk4RDJiBA0+fHu7/cgJLIEcQgAwA3/wd+P1/+jt/8Af/+Ve/9jX2zlABTVkL5GP86FB+WuxQnwWuiRtGMTjOu5vdFNOIbKtVv1qvu6apBeA5T1miiMakolMsKXSOQ7XvmHIsu+O03x+KlPOzB307AEBMk6gAoaI5EyQ0S5cPns7HOR2LoJFz67OV85RkNtCUphIdwWpoO1pjborzTdN2AjDnkopJ0TjN26vD1YvxeIS+AeE8TxEIiZyIF5HgOWVNSVGAURGAEZWKCZAmh+wbt950jy4enG+GGMfd9uZ4yJKdIt1cR1NwRFNOKcW2C8NZz0wGLAK+kdUZkg9IDTOBQ3A0pmgZgX0ThlQANBMmVNBcTDOTta2zYszQNs0ZteMh7nbj/HInADFDUXAeXANM0Hp4542nZ+cXofWH7dXz4+HNp7AehuCpGIS2YfRlUW3BtvPj0RAmU2oCAxGTGcRc1IGx53ic0uC7VXu+HpxO19ujRLAzjTHtbnbp6WXbtJ5VMRugUwqA6rBpe982H37w8nzd9U1DhEToWz+sezPMJRdJ3pNo3h+2ucS+Hy43F11YNRdhaLpH6fJw2BJTSWU6jmjgiBvvA4FjJABGFNWSc3ANMCaJoooAonaQ8Xu/9d5vf3f93e9841/8iz/+P/7Pf/6z/w/gDB682UxzGg8JFKnzvutFtcRsKoIIhsAtETOQVbEbq/ecUU1EGJY0/1LfJ1AZ7AtrZdmS3XqN4aKxQwURnSOu+spkhmhWlo2nggiIAghQsMWUSLBiGlazBMRgqmZM3gCqjIVBMVNwxq5QyGkHkEEBtufw29/G/+q/+d2vf/2NrpFDfvHJ/OHN/GxY+e3h02l/mOJRzGLG7VU2ZVGacgn9ELpmdb7uLs/eahpEVwREEApCYQeOkUjm4IrpuN8fjtMxJUiZP/jo2X5nx4QFKZl5OqegJWYfgDV7VxFpzw5U6fpqP8/TNE+lJBNDmg21ZVNAMY0pG0I/rKTgcR7FlJkNpNu03bovGUpBUwzeN50DFgWLJYJlRJ8FcrGYLGctAjkpYskJYqz5aJ1GyxngctysVoUjmjAKmkmJyalzrm1Ct/Er7cLNPmZ1jTY9pizznICh66Bb+W7VfHpV2oaDC65zATTNAuAGcnFKSeaMgmJpTMzc+TZDVroTGj6mCAXBBBCQ2DFLUc1VPpZqBlTBTv4nIGa3UrF2izIA1E/L5ww7lu36F4axSwUYnGClWxDFEKkGZngPybo96MScueN7VTDoTpPnLlQ4oVcn5OhXYpngL/3oEjLpIvpxe+F30NW9n4C7VtmpdUpk96SoTh87uTiaao2gCO4rVv1SG+7Oh4SqX9Cln7m6hUvyeebNqdGIqrrUM+pnr/iWEGW3d9nAFiPy0xWaKiLdI9AB3N6w0wnu3SE44Y7L5dsi9/O544QiLW+dcBUzW54Odq+XcRGJt7s+upMXu9cMgyWRBgY1D4eoukgYUcUb5DPold2PQ++1rZLvPt/39/8kJLgnXX/v+59DvZaTAQAAIABJREFUDz83RD/fIf+B44uw4c9CYn/XGX9N/OwLpbI+f5LbV/Ae4esLkbLPX8jtT9DJvg0RT4B5jfurAe0SKS2lfrh8sT4Hq9p6dVocxyMi3QJYpybeB7BunYGWt05TH1y3mNohIphJHY6OQxPAYIqzqTnvqnqdc0zMUIXbVRGxlFJEmYgYVVSKQQFwzJ6rYAYSnC7IzLQ6TBHTNM21Sg4YjMScoUNkrKknETM1PjFPK4DF4Gp8MU1x4YIxsAMOnohMLc4ppQRgVSyq9maRyjAyRCIAmRQZFiSHibyj+oumpfoyLizKAmZIREzMTB6REMmksqrqw0IVFVHRtMLvNfwhQkYhU5WiKlqnX/ViJFsgVStaVZZutzUV03G9UweEgEzM7DyjI0JKJZeSi2S7W3EYiKoXiYmYKBRd+KOLwTOaqfNYf90Itd5kAmBc7jos5pKL0cFC4GRGx0gxRnKMXC0wqwgKAYCaFihABg7Rk5EZGIFbMLYsWjKgp1u1xWpXXxegaj3jCB0vxmVL8X7tPkBC0YREVl3NoNqxgaAQkoHJUowKJ68RAELviYMnR+sH7fX1VeB2OO/PN2fPnj0b97NT3jxcNU3w5Hf7/fG4zwcoCsM5PHr09OLybIzzs0+e77ZzCI6UJZsWYGTw5cHl5snTR7nk7Xbbtk3Xd8wY07zb7rourFYrRDgeDw+GJ30zHLbzB3/70fbVcdxGRx6hzl8jMmIkpqJFrADWqkCoZC50dZ+xPEjMlMhXBFlRAJQcAGtoHHsskMYM3/7qe+989Y3gm3/+v/9LD+i5bdseEHI6+GBPXj/zzqZpD0avv/aWp+bDX7z46Y9fpK1cPA2aYLtPjy+aq20Ehq6HBw9X5w/Ph74XjTe7V9vdAQjOLjcIvN0fjodsBp3vGVwcJcUCYBdPVje7KxEIDTDDejNcXJwh2X5/vVoPzPDy5atxgibAZo3r4axkFTFHgZDeevvtkkvrPTHt99url59qLmgAKv16eHT5UEx3N9t5nsiFoVuFpmtC14bBheA9iYpjZ2avXr366c9+Ok3TZn2Wc/rk+fXbbz158623COkXv/j4xdWnVlLXrh5ePPjye+995StffvOtd374/o/+/Pt/9fNf/Hy/n56/mrrgzx8N5BiJlAzIlORmOyZJTQNE4BkePXj45huPUUcp0cy89967GNOiv+N9COHhw0dmpiKKalIA0CM1HNrQBQ6d7wCoFJnm+XAYr65vDvubOe7avvNuIOJVv764fNSGVqRMu72WuB76B2fnTd9pIQ4uxrTdbnNOF5vzYTUYKIiFEByxdw7RAgFDYcfAdpgOU5rbrvn4o2er1Wrohya0jhyiI6X99RGNVqt1Hzoz6vv1O29/OXv4n/+3//VP/t2ffvhymxNQD+/+5je3+/3xcIxzAkHNWOYyjanmHEBQi5mq5LryLHaKlbADZYFciQiAVQTEgLFC0ewcsKlTEwEE8MC9cy0baMq5XTuxQgRd57qu8Y1DFO8dAM5zRMScswjFA8wzlpTOzzZPHz3uQpPG6S//9G/AAHL1ZGs9BGUFZ8ykhilnkQKg7AgcEBs5MyiqWk0SgaHqAzpPzMiMACZaiFUVpgx9B7/x3pfeefvRW288lHJ49uxvX3z6bJ5y6wOy74dhvenZ2/54fbU9vLrSNEPwcLEZ2qYhwgcX52+8+fjp47PD4eblq4+lTIH54uIcAJqmb9sVU9OEFYqfj9lja0KXm0cXq4tVMzQ+OHQBG+8Cq5eUS0w/+dGPP/nk+Q9/+NMf/eAXz58dS3QitNtNZiBSdyOCaG1o4zy/eLkjgKH33vtsciMRELGmVBTNgBDZUQiBPI1pVIHNes3gIBMLBiMH5JiN7PV3XxMqw3n33ntv/vY//M4/+cf/6OnDS7eI5qHWpAxgthR1ThoFi5EqmMB+r3+Tyi7mNKdpnI8K0rYNBzqM+5Rm3zjfOEQkI0k6jpOqImN9HLx69dK3gYmz5OM4Hg4HBGqaVooSUdt15LxW6gsykwcmNShiKni4zofjdHPzchxvkKVfNV3vm9Y3rQ/BtW1DjlJMSARG7Dwyj1O62R3HuXDTvby6/slPr5+9mNnDO+9s0GXuJud9EbjZ5WkC0xq/ESoDAAN65zrffPK310TQ9f7x4wdPnj5uO5fSfHO9vbm5KSW3qw0iHvbHHAsBTfOcFB486J688WBYdzFPh8N0OI5ZAIFFIUNTMBymUUo6v9h0q5DzxChNwK4FT0ogbeNXfZ+PkmZRg7YZunYAo1xku919/PGnu11sW9ism2Foe0qPLrvf/b3fQ+devHj1ox//6ONnz7/0pXdevtjutkdGbkMPgnHOxKHxLVL7/T/78e4AjXfrlQ9NsxoaI8lpVo1KMlw+mafZUXnryaPz3o27TyTuHj948OCC9tsXX3nvzbffeY1QC2Ru3GGaPvn0+TFN7BpD2u+O680m+OCd36w3bdvmBPMUtzfbly8/PRzGpqGhb4euXw2ry4vLrh0YeYlWzVR1msbj/ohql+vNehgYrcTJMTSOiI3RgTQlhZzUuWbVPmzdmahv6EFK3LqLh/TGBPB///Ef/8t/9W//9Z/8Rcx6vdvPRSi4our8oIqqGEKD6EAQCcp8QEM1RIFla6VWSmFiogpKKZjlIneRbSVGgSGSLv7YFc8CJCFSAFEzFDRRU7AEYMiIZBW6ICSUmtdWMCFTMkNC8iEgQ9KkJhQICLUQoqcGgSagufFEgb71j/rv/va7//if/OZ77z5lkOv0/Hr/8S+e/2XKu8M0XlxuLh5ehNYfpv1xnF5dH+aoptAP5+dnj467436/e7U9RIFmgPX5BaLf7fZpjozNef+oDwMbkG0NrkUmJPCBmftSmuute/EyPn8Rr67HVzs4zNAEePTINQ2L5s1m0zSemQFtHI83Nwc1qBWcS8LE0WrjLy66pucKbUmhcZxTMu8gBM+e53lOEWIELdC24exs3Q+NaJznMZeJsGH2Wvw42X6XER0BHbejGprYPCVJFmdIB4AEw0V48s5le5HJJwYkUEZbdR0hj4eYo5XMr67ibjs17RDHfDjO/cDnD1rfY87TFKXvWIsRNoEGy+5wM0+7lA45x+zZn5+f993gmPeH/RSnWWIsCQDAQ/AhfWqQEbQAIzry7FCkJHHAzpiUQc20BmIlF9VioEjqAFCT1GDnlOO2ummHz8bOFRO4hwmZAQQIy1sGsJjl1W17LUqlWrJlJ06Pmd2qmuNnuQE10qzJfarVGZ+Nhe8oUWb3HPP+Q0fVarkTlTIEQBUzqxlkqDEVGtBnw//KigSAkwr5qQ30mV9epGnFbmuiiBCR1KPSZz4GAFZKhZzuHMUqXPx3XOZnDv08gPUZZ7b6RZTPwH+1xq8q7QJU/7IasYMq3gOPsBpV2e15FpQCa7GNmi42ZbaQ2pYzLzUtcpLFhDtgzMB5vn81lWBTlzWiWgwEqgInZOP2KsSM/BdDN7q4wxGAiVQx7YXTg5UneXLhA7H7AMcpGXDXGNMv6GgkwtPAu22SiNw2o5JAqnzXLTJzn/8EJ+Tu3lX/PRgU/OoMrPsXACdS0v32/fpHbf0vUZ9+nfPfn7e3zbYT9wqREY3Mbg0Bl+KMe+rpIiqi3rkKYFXU8t7Aqv8AgJ0gtbsqZDuhVwgAtPg82kk4DKt0q5nKYjFQ07QnHlUVqTM1E5WmaUSlykwtzUMTMA6L1ruh1a3naYkjIDJCIwSP5AgdGhsgGd/pjwNVIisgEaqBIhmAgppUuTgsiyk0MoAggABbLQ5hdmAnbhqR1rLok3o6IAErO3TOVbsHRbjNXDCh1lcBzdxSXLuA0gRYVYD1pHKIhkJIVcsdKpCkqmpIBmzOeRcQzCrikmJc5pKZCRqaLE43UNmgiFYpZ+wX+TYkQCbvffU9BIGaEkEmADIjsFOdpiECn1B5WMAQQDAipEojX7hjlWm6sMqY8cSxPH33zjIAUdXYFlFAREAirjNcch1IeMpyLFj6koww0GotDAttquYJZCk8RAQlYDVArHSzeystVMsqQkNcEHsCvP25JSdEgARAtRwPgAkc1zlgio69d8GjRyPvQj9w65vVsCKikmQ+lmkHbePaACqy2+0AUUxzlKbxnhsTNFFkLDFrznkt81xEpGm6ruskl932GNN0fbVbb9qm6dbrIfgAale7azJen63Gw2igxEaLpqORQ8eMTGaL34GRLWAuLRmvShOsDwsFMTExBa14KzFD03qFEtj1A/oGwCQ0jgNQcUU0pQwAIoUZ0bBtApOWrAB22B9TLl3XaJxNGBA6zyVjIJeTHLKhHZmaIZx1Q1PlOrLmpgmA2CQuJYsAiKQiOauJOu9EUgheVZHMByaicRoBCjOL5JTEDJhBCqRoyRdTM0M1MdN5GkXEMXp2qlpEADB4VkVkV9BSytvjmHNuArEXI1HIWUaM48PL867zABhjbFp+/fUnx+Nxt9vOcep7uL65ch6Z3dX2Zn9IhOCDJIn7cXt988J7enAxfOPr74zj9ThdrTs4vwzVHx0Ju7ZxTShWFCjGKaYpJhAHKUHOcLZq0byZVQNPx8EUGRswkyzjIS24txXFErgxdoaUSymlMDvPDlCL5ijTFA9TmcFxKgqUneOEZdYJzZhAXT6OuwJju+Kh6a4OW85+nqZpOjrngFS0qKpj55uwu9nO85xibBAQpe2aYd0XyylnBTi7uHTeG/FxSjEe45wsAyUgoOkYnzx5+sabbz18+OTF9tWPPvj5X//0/Qye22ABEqTDuL/Z3UzHiZC9azWVosLMaAyK1clCiloBWLD508PHqvOfWbX7BgE5ZTURAatpWQXVqYrxkSIUYHZtoBijGfhQt5Ywj7Oo9H3nHMU5IiIAqVQrAzbTrCmV49lZePz4yc9+8jc6c9pLSWIm5IicEy25CogYEpBWpUYB9AYGRKgFoAD4+gChwME59o0jAimF2amVOSY0GPfwk598lFPuu/5s3a2HR1OfS9xNYxI95lSIbFgHBkIIRRMwKkDMfpzlsD/84oNXL16OX//GW+sNd5uLeaTd8ZUcxXsaQkkl5yJ6g0yhdT0oxH08lmcvtqF1XR+6zrXn68uhWzUcHKHr8Cu/sX793fbdrz36vf/ke9PkGzoHamIUQFTVcTxOh3GepvE4ffThR9//8z//5JPncc77OR9mgB5OxeIAlYbLACLHfYYA5+fwta9+/bvf/e43v/zts+ZiCG1PjTNUlSy5v+gSzMC5H+jB5Wrdi+irKDPi/8/am/TYsqzXYV8TEdnspk7Vae673ev4/B5NUzQNEwIMUdbIEOBf4YEHnnimkT3wT7HnhgGPNLFhGzLcCKRtkBDFvn+3O11V7SYzI+JrPIjcVXUbPlGUclCnzq7cGZEZkRHxrVjfWhAwRgrqMi1zF1MXwTmDLFmWuU6T3PNwUD+YZ4AcoozbzTB0RbMYYMCuC6GLRFjmDKTDyIDsCFVqlvriw+sq9Xg+35/uz/MEjImDc+1S4JgQTa0aAIVEiGZWRVRMxdVoquocht1VHILa4r5M82Qeu24XmN2NnIaU1F3UVDMY11JKziU3x8zq1RhgiDDEQRFVFnEXURdwbV7HiAhESACBuEvcJ3x+DWMX91e7ly/3m6twf3949+79eZocoR+GTd8boBucdCpLcYc+AgdAV2ZPEFLnvWEPaODnaZZqi/tcc8kLHtFgBJCx44AckRIrAfYp7Te7br/Nc11yNsOUwjCM7m4+j/c2Z+gH2O91O9qW+Xobng9RwKcIY4fX+/F4dzgf7/IMQ88OXnMpOUdWDGlI/INPn//1X73LWeazBKpd6kLgBWApim42z7pMXc9DwsAAbl2Xnt/sxx7Ox8P5PN/fna6v9xExAG+j7dLg4rXqUvOL6+uu60rVZZoYqeu6oetSigB2Ot2dzpOZuUrOs6uY1KHbdLFjjA7w6fOPFWSI6WrYgnkijkwuVUpdynwvGU0CR6dN1z0b+g14PefXudyhRe9OCfZo5V7O4N2v/+zDj27+03/4D/7Bb/9/v/s//a//9A//BKAIONBwRAD3DgkBNGc1k9SZqa7bl0BkrG6iFZzd0PxhvXyJk9dPwEHHzdbaaqmBcGTm6IIOEc1N1JVdrU+JMZKDiGkRc3VA7ppmdJNNBTM0hOar7VCNKgUgJqdOVOFwhgE+/in85n/8a7/+93/S75fdcx6uTp8ffu+43N3fvxGYeOBxv9MzavI359tOUy5ydzrfTkaUUtfPHpa7067vw7DZMyu4EZ6W7N4U0dArzPPs1Ri9CxNSJYZuCN3Qc0ju/blKv6XNEnMdi0yIECIM/bDZ9LlkBFYFd5vO8+3dKWcYBgwpYEsTQFIwMRDH6AgcMLiKATMGU7RFqtWaEvUBFKwChC52Y9+P/Zt3d6JZDYhUqi9znc5wnjxyczwkcDBBq1QXLWcABYqQOEHBnhMGZEBTYTCmFEJE1uILBhqeRU/e9wPh9jovwLLZdhR8WdSpbjbDdCh50iKLFTq9X8pZMSNkzljPdZJOiUhRiTlxcvOiFRQMpUujWhVzUHNyCARMyGZqxS2YNrmrFtQQtNiBiJiAShFYUxcaE+YpjrP+vKALXyeeOFqLuVb5X7gk1a32Sw2uQYeL5Do8/fYDMOTwyIRqHd+gyWc/rOphDXtbqYjfBnS++3Aw8Ac7PX+IGtuPpk9lj9d6ZHgBthCYaGXvIIDiSld4GpKDP3xx/X2N2xAez/l6lZ7ydNZg6NI2D3X4GnnqybN6cqyh0tPKf+Os9e/u0HJ5LjVcg6PLwyC6RPjfgihas7R8P7g4SD5gM3BR3/8u9tA3GVgXdOIpZLniOk15fOVkubsbGDfeafvGOhyuWUHQ1L+wsUwfir8UtT4FgotS+FqfbzyZ74BjHPiisfMUUPv2iU1a6BunPeBZ/i0Xzn/l8bcFsB4AoAd85wHA+rd1PDTDN2C8v/Px0Anaz1Vj/gF7vNzLk1fCL+TSh3vU9ZmuEDg8WEQ80GQuPadNjeuV175zwd1XxKpBkitm0nIFoZRiZqvrZMv9xzaygYOZu5htE6uRNmXyVnNH6Fo6Dq6QP1jjXzZ+p4G6mxhyChQYCQXELvfRbgXXxCtHBAIiAzc0MRdrsvSBg1p1U0NQBhe1EDgGJuYU3JvglSERAHIkYnRzNTVXIODAIYXWrNXUzS4oNF2wEqcQCEhQH15JN6xSkb3xxAERsSnKN+ErMG3zq2lVInLypttEkckBA7m5m7k1ZS5iv3BcL+0OBJUFA4bYVPAdEMxVVMy9Jc6sovDAauzuIA29QiYwQmiUAjcCJKZADN5atr0kQKsrDTFzCIzm6tZYQmDg5o5rWrKjE3Jrbwd3dUS7gFsPfaj10tW9o3WntScDNMmKdXHWmG184Uy1qdEffcAQHxPcTX31fWyywwjMSBSAwMBc1hTSJx3ZrTWi+fR+amz9+bjIovlQkcnQyyxIJFJVnSkwEyGYeylSSkVm4qiTWAIX1yJuqxHmcsr38agmm80IQIfD6fbuDZLnMzguu3HZbIbNuJlPy/39+/32Ztx2ISEEoLaVpe7gxIyRianhVSrV3BuxEJnCKiDYMn3dzLQ1BgAyxi50PcfEFLwsdTP2+6tNiDgvJyT46MWrw+10PC0mCwdqguzYVIpMA7ObHo/nWvz5ixcE94fb+6Ebx2Fzup+6PhIRi5wPVut7reHZyyGOnlIKGIlITACcA5lZqbVmkwwBQ2R2135IZqoqKUVEXJYlBBzHTlWWZY4xpIRdiCmxuedcCTkMMcQwz1POudTSp3Q+T9JMrANvuk3XdUuux+M5VylZRTNQUqMgxiyE0CVwH82sVtntNs+f30zz9Jd/8de3t+9fvdp8/vnnp9N91w3mJoDoriBLnW7v3sWExH797PqDV1f/4a//vR98/5P/7Z/97yIZGcpSgWnYDF3XWYYYOlVXhbFL/ZD6cVur9d3QR1TVZckmykj7zY736XQ63d7e3r57Z+rEASM4KmOOHBJxJCLEods6iEgVkxjD1fUudHQ4nZeSFxFYMh2md7fn/a7bbQd0m+oyZUk9d0PgGPNynqajO/T9COhLnkuuInp7f/jis88BoEupzsdAttvvruHmxfObYdweTwdRy9VVbD4vx+PpdJqp+g9eff/m+XPmcPXs5vnLV4d5+r0/+aP/+7d+5+evv+r3V9ESB3hx/fLNuzfnJdcCDGqK5EzEbRzQalbc1NEYmvRhm1x8JYFTc/fx1TEEI7iuubPrTqg5OGBCikyB0N3FATBQVK8VjBCZIjrn5bxkQM/DmAjjdrtlCqfTRNsUKt7Np1rz7fv3ppNb/tVf+6X3r+/ffHZ7f6smxTEidO4uVcwtxp6YxauDg6sUQUdiJwcCMEHwZkDUCJOo4LVa7NnNdIHQASC8f1/L8pmK//DTV9dXw831R2N/tUyH97fv5ikT3zlsEJ0gcKgqOM9Qq4JzzvF81He3X3zx+t1Hnzz7+NOrq6vNtsPD8Yt9t/MAxedTXsgpYZJ61mzzeeFUz7NqFgKKGHfDdr/Z7ze7/TiOsQOF/Xj9oxcvEt647QI+A+wcWno21JpLXqTUcsp39/f/yT/+zTxVhkAQ1KyAtF0JBOTGYl29ZpWZPWq36T/++OMffvxLm+7ZlroOI0DbAJGCi2JWmA0m9Iw2g0vgolqrE0Jwh8BW9GiuRuogxCXgknhxXLrkIQZfcpnyNFWFDpk4YsBQpC6awYEdAUxN1VRcGoC166+M1FiNFZPFlDZ938UOzNVU1aXJXqqrYa2Wq1YxVVfnUlPzM0ohiWguk0jORZaZwSUw1xAJSUCriAMgxVxVTQDtcHff9ZvvfXAVu4OjMVKuWsXVxBy6mJipVlEzptCFwOyEENkQ5x/+oP/wxc318+cxdee5vHv9dpnu3HC32XFIOc9Lrubed0xIaeBx7LohAAqClDqJFNVyUXA2DgpqSFQq3B+nlPjm2W47REYJ4BHJzSXLMpfP/vo9EYoLko3bfhjHzWYM6XtXz3aSy9DRZhO7CBuqPckA9r6eJE+gmQFvb2+J6Oqqi6EDx4oeQ0hMAWE5Hz98dUPu796ec8mbgROrWQVbumCp7+8Od2AQ+y6AEsBmGHabq91+S16fPbsGh9df3W2G7W7TJ8DIYd8vaCwqM1cy7GPqEtSUQoin40HVh34Yh/jqg+dEZlLBTUrxWtkxYhxin1JgCm8OrxkpxTR2fYcJwdGVAsfRLXbLfKplIgjAiThQUDAPrAkNvUqt294DaK33aMMHz1989PyTn/7yT375xx/+5m/8e2/fnr/46s0f/tGf/slf/enr9+/uDplKIYpdjBzDfT05QRM2BQfHiIzd0Ky+3U2tFlFnXMkdl5ixbQxnW1n/FzaEB8KOkYlQwcWquFpp8TOagBmBMzNVKYSEQEgEAGjmqE5GQRmzONQEQPbBC/rh9z/91b/30xcf7jcv9NOfbH/8s+99dfenFaZDeTedDlOeqs65TtVL7DB1PTA6wPv7XKouOXV9RI65+Pk413z/wfVNzjmLOpI17pd5rRUAXOUw3ZfQbYcUgkWm1A3InkvRIsQ2lUmB0sBX133qxhtNzDhsOKWAR1S3+ZzP01Sr5gLI0PWp6/sYOHbpOJ0dq4GXWql4KSJqFBirEiEHjjEggbsyRWbOiwWO8zIfz/fm2WzVthax8yTThLnQLFNgluyEJIu6gAqAQAzU92lIIwlBdVXPNU/T4urLzsfNWAocj0W8lOKlOqZlv9/GTXIHYClSDW3cMHlA13rOy2GqE9ZJqTAbk0EVON2fT3iGBMNu7DZdGhIgaFEFM7WbZ7t8yucFTSVE7roOwbOZg6mpmBIGpnCRrm4LcSKkwKEQQdv0d0CzZlJ1sZKDS++DS+LYIwMLnVY5cL8AG41dCACEDyjJijo9oEgI6xY50QrfPBSEayltqsHLOuHrWMDfGFZ/GzJoklQXQ3RoSjV4YWc00ScnAvuaWhI+RXeQnqBaX8PvHkDm9igB0M0u4itNrATcnZ6K+D48jgcUyFejsEak+NptPiAyT5/6Y/Gm5hdQbz3o0kiPHwCo2YX40CrSRPBWeXx6hCmeIlh4qd5Dy17u2R3Uldc8LGB2IruIuMOTSzwBLgDxQfmk/XPBeszdvdXlEcFQh4DwNAdwRTkbFncxWrTHVoIHMNGdmFuQfgGU0P8GwOq7D1wjzUss7197MLAyh76B0Ll7CAH+TugVAIRvfwEvGYnfBpKefvhvCDD9goo+bZJvfPiLv/UL/vSQi+dguGqvAlwguYdH6daUjpy5+c6twl7NbyEkXmXLHcDA0HHVAoGVmbxiC3RpQwBssAYhoamuW0SXjMZGy7qwATmEgIQKJqrN2wQZAnLjkJCJqoNr4MhMaOigdmH4WXM2Cu2VxsZSAvBx2ImruzrYmnO8UhiaWBACoKmDOFRoUZOLu4O5JUxqhA9K325maoBETswNhGtwLhFiCAjNoxpUpOsS0ipa8EAMa9Mb2sUktcVf7ekwPujFN2V5BGJq8ihMiAFZ1dQczUEd1MxBpapriCGE6EgNpAFEDoS4bl60dMiGpYM3P2aDEDASh+CtcV1V107PvEYmiO5AACxVHyYia+AieKMWN3VHWDlMjkj+NUxztSFUMzUFuFBnL4LyrZebKjiRN3F9XGGR1UzRiRGgCYk6EQZmRHJ1IqIUiQKsZoIAABcLDzAHdFjTF9cx6hICXyDiFSJ1a7CbqxuseBZA68Zm3tRMfZ0yydoejoqYuOAZgmFAK2Dg1gNiaKpeZu7BxLwuaghjSCkmI0KishRxDdghspigIhCc5tnYn988X5aFmQmpDdbdqA5wOJ7SEFM33J/uKOEi07bfbvabt1+cpShGp4RaVF1DSEAEpGjmZL7OVe5g3ojRQG7asgYAwQlixyESoDkSJ1Sp1Z3YhzEBaV7OQ9c/2++sYD7XpeZh2KDL0Het8QDMkKTMAAAgAElEQVQxUAB3L3g+548++uD23VENwLhmVwO3Vd8fROaDvcP7InN/BRwBIwIUJOj6BIAAFbJpI76BKsg2jZhwPs/zLO7ggwJ6CEMIcZrKMls/cIwh9j0SaM5iim5ciRin5Xw6ncIUUoq1lFxqCCFEdiIMwcwNqJpn0SyizoPBOFDHkQin+USofd8PY+r6hlr3H3/yarvrpun80UcfbHdbABr2ZXuejncHQkdGtXx//7Yu52fPnn380Sc//PFHrz66OZ/v/8Uf/ovzJPOcIcC+7kupd3cHA1iWAoi7zXbc9u56f3t3vbWw61TscH/IS97trzbjJnAcuuEe729v78wECCEwBovEjMSIHUdG/OSjjzfb4XjUaT6JiIEaAHJQq4B4PizH09IPR7EdsHdEuWa0oiZmGkNXpADjZjOmPlatOef7u+PpNJ3nqSxlf/Us9d3+5ga1xpSQeHd1ba6n8/T69edEQQ2m83J/fxDFfdrs9jeffvqj93fvP/3Bj25Ppz/8kz/7Z//X//kXX3xOqa9goQ+YAsew1EzOjKoCpiV6AsGSKwhZdVACI3Rosi+XdSW08QdCADICR256U+DABrayrqj1dEWn5pfUhPPQFREocs/YxcBIbccBFGoWdIgxXG33Odcu9RE66YBgl/PxXAWmCd8ff/rDn6ZEXQox3r17uyxlJq3uZKbEBGBNFaWR/swbp5VWb3kFqGYIOYI7glZzq1pVVd0CYlNHJPLTAn/1l1/Kop9+8up7L6+eP7+auuQA9fWX81y7XhFhWUyle/d+QoTNEEwQYR9jd5ru//rzMtXXcz3+0k8+/slPvz/nWze/vz9WqVXqkDrqjJFzzXO5/+L1HbpbrUwdYzzMw2He7s6bMcVAhOKvXnz8wU3uk6AvEZVCZwjgjgQp8hgJgdLN/hPY/8qv/iBgiNAxxGbMSEAEjKtHMTmgQpuOsUCtUAkIwNnP6NU9oIGbilfuACC7TwYnsaOVI4KEYIEDUwAvUrVIUTdF9SAVi3quXtXn5r+CACklBKyuCGyKRCml+Obtuzkv7paYuhSZsGpdagb00IVqxUA44bjrqCISAqOjAjpGVhMnUjWpIoY5y5KlBbqqHPgZISOZqRbLVYqqIIlD7x5KlmWekVhcDCyEHsibNkKKFAOOQ3KAOdN51nk+xy508dl5WRQQgfqU0IuDEYNrdfAQfBi4j/rJB9sXz8Juj1Xy8XRndug7MECiUmqd5wUwjP0mRiIK/dCnjoFspaozILqq1Apt1RY49aG7v1+qwhBhSHS964cuWp0DQ4os1U+H4/G+/s5v348jxA5CgGEI07J874OX1zeb6+stk3TsKWIkgGne9DzLfUAodVrmg4h2iWIchnFHmKYp53lhxpQCg2YpfUgvXuwJLC+42Y2BcSllt+nGzVWILGUpGcbYodUU07Pdi4+/93LTB9Pcd/F4eL8scvv+nICG/SBFX+1f9uFUpJ7m6f50XI7zZrfthu48z7mUGKNK6eL44voaTe5u39aszAgOecl9KvFZHIfR1T778stIvN3uOoqQPEAIGJElcaDOdt1Q66JmGkZMY2BzrW7VoAaOrvmUNdimo6thYNT3i8wx3PzKT25+9pNnpcrb97d//Mcf/Mvf/+DP//Kz3/v9P/vq9V2pJQQMPb+9hRCAHdDJFFQkYAoxalF3N3NHjF0AMVe9xKaESIa4zGW1h4aWnACMyJyogcUuzc26qAEqry4TzETICE7qGkJgxloKkXIETgWTzw7/6B/+yLncvNi9+ujqxQfbn/3KJy8/3EOYq93fLn+c4Z2gzHo6LEdx64d9t31uoE2S5HA6c4y7MVaxoTMxF0V0lbBAnfNMp7Oe80kROBEGMHWpHgk6SqmjgJ4Sc0AOyIENNNelSHX0otKNKQ3dlW/QR5Ve1dVtmefUhaWUVZ0aIXUQY+SYiJt3brDTEQMioZjlWquI1LZ2JiDvx14kb7abEPh8mhn5atyWrKfT2b0OY++6qGgtWoubA3EAgHmpaBKImGLfDXGI2ttXh1sM1MVuiH0gWk6Tk01TPRyqCch8nrcAxNPkU6mxi1OVejgVm4eBNtvBTdWquaGxqsnidfYymUwAJUBFUAQAkgd1DfdqoBAoAmLBolYa+Smk2EMnSiERkmtRQ6OAgRKG5h1O0OJCastoMHcRaaIol4iqEfy+FvA/hrGPWBM8hELo+IBBIa4auy3wAMAWWnjLalmD/xVBakU0+tMFHmnfuEgsrY5ccNHWeoQ0GMPDFR7BoO+iKQHCKmm/5uFA4MfsPvc1OPg2QnRBvaylO7UqENPXEI0LuGLqF9VIpyd8J1ytXxwAHkhZD1iR+2rVBA+Ekq/xk9afDt6c9eAJKvQIrzwAPM3w3h9gDWoRO1FYy28EgFWf5hGdbASYCx/ssQjEVSTqocQVimvntth7hSupJSM9ucKTdrk8a1jhAndckRnmR83xC4zgLdLzR9TuSW90d2jBSgMrCB64XS1WfajBkxTYh0p8G5D5Rmd5sBR8bI+VyuNPyn/oyd+81Lffmr/l8R0MrKdQ0QNc9Xh3ZqtE1L8mVPbtUv425zy9madV+jsUt5ZI8FB7/zp77XLOE0JWy/u7QMItrhaQtbH8a2m9K4wFXwdkAR5fLkRiskeF+PUaDeUiJiTGQAji4uqO0OjSYGZAToGBmqwPPGCq69iE7s15au2erRAyMGdvG6cOq4h7++mrJSw5uKmDAAqYiAmYAjqSo1S9DL5rgeamUJGISENgCrSaX5A74ArZIwIRM5toVWmPnYiQkIFVVU39krlpoIgeMF6Q4ksnd0JgAiYnMYUKpmZV1XR9wbRpgLi5iRu4g6OpcUBCAlrHhdZhkMPlFpqRlNcqZh5Uob3/AEhOTAYtHdRXtfcVZiIHRwRXc3V8BLDXEkzdrcn3PrAk1k4Bl7dmHb4fuwt5G6nxAqoZkgIGcKfmOeG+ZmN7q2TbYiF6dJggJCZvSZEKTa2MYK05XNxagcDJGsrWnBPRGeBCgUXHVbse3FbgE1sO/sUhuknEP8zSQEDMFNa5ydWI1hdLRZFcVWNKMmnOMvTUlPtVm9CvQQ+RQ2AGJkT06sauoEy02Q6nk5oLIDIzIlhQUch1XuZtyfnd+9ebzbZWQYA0MG+gnpRIAzMGEBeUSswOa553s71Yb649Q3dVMTVsWw2pYYCK6A41L1XcQ4DUcQgIIG21MPRps+1O93GpmRjANAQCMFUwV8dmvEbH6XS4P7g5Rao126pMXBpsTQBqsJyrU1Wk7dXIQKLCKXR9h0DuGHY+DFizS3EkXnINwMScEpvJkhURA2sMDsDukLO6A6GEyBRS36OrOVipJYVobioihFVFVAGg1ppzZg7EAZEJA4CYWS5CVEOoMaZmzlylBOUQOed8PB4RcbMZ3NVdt9vNbrcjDrtqw+ncBZaa+xhiZAc9nu+JfXM3dGNiCr/yqz/LVv/f3/n9qYBluJEyvS9fffW2S0ldIpNtBIqK5Hm6f9stVreIeDwc5vnUgNRhYJFaSxN3BwSoIoTASM0zVQyB8Hg6hsAlL9N0VlVzn+b5dKq5SEqh9dsYqe/Hsd/2id0UtMTYOdD79+/meQ6xC5EdXFRERdwU3Nz6cbPd73fXV30Mkhdzq1VrVXerRU7HcwydO+Upm8KrFx/85NOffPLBx6c5Xz1/xaE/zO/+/Odf3J2ncbObp/MyLUboatNSUaObuYILuLqYgLKK47rjgO5tIwMBG6vfVgJTG698FWpk5svCiB3IyZlbiG7mCnKZ8cBMrYhsX/ZIykzgDUQCQjCFkoubT+d8Pk2latqErov9cKUlmC59onHogDV0Nuz5+oPBcHn3XnQWcKQQQ0RTUXGKXRvOmQJRSzhwNFuhGwcwExOPDmjaiFqIzMjGDXpz1elsX35+R0oRY4pdCP1mHIdxPM8nqQpAJgGdRKZASSSoYN/1z2723ZCm+c2ywLv38/fO1vdX0/3dwqmUIgqBEbZo6gwEakCQ5xMTI1LVAq5qBgTALh4ZcRPTrOd3y1ucssk4dqfNZrcZNj1EBMgwTVLJIXFkDAkTQkeQDMjBQ1sgAyGwA1xs1MBdxKsjMDkAqQe0vnpAiMEZEZmkSJGwAC4MM3H2VNUWQAUIDmzO6qouYmLkBgIojsW9gitRAEM3jRi4GwIYEKnDUpYl5/d359P5DIDbMW033vWdAVFIIfFmO7x5/07RqhRxcVA1N63VkTDGLlVVA8tFcxEzFrWqJt7WLHB/vmdkhGo2qc/omaN1fVxzDYuIKBAVU0MPwRzZHatCNb++uQKiw6nMy1wK9GPu+z0GNqNc5XA+9SMOfRITldlAEGEY4fqm32+GD7+3h5Jv7z4/HubD4UwEYw/nxWKA1IUUtqJGwW9udrvtMI5jiGTu6gZI9c1Xkkx6Z6pVpFTPOZ+rDQn7ZyAV6jxrPcdhCxGJCYCW2d68WQ53ggZWwBCKgqi8e3dAwHk6DAPHYMEXJmeXzhe6GvthWIrWPF1tr/fPuq++fMcxpa6L3JlDnScDZQQCT0zodex72/e27fphdK9hqUPf7fbbEPj27esAsN92+/32+c3VOKTnL553iebzIQYOHKb59P7uGNzGEBFh6EboqCZBw+P9IR/PLhZSOE3nfjPe7K+6mHIpyHC93ZHK+XxWURVvPm4iWkotuYxdr6qgblUqVPOqFCNh4hgRlckFzLIbgVOEYGziuZoA1G2/q8tynE6TnwD0enhFjKrvGCZwGyP/4FX/fPeD/+g3fvrXP//yf/gf/+n//L/89m/9AcApQ8z8EUgFEABvsGMQsXI4A0PqupBSLiClgAIYRIYu9CF2ISTmMM+zNl9lK6LFCpjmqg4xEjMBcgxD36uIiEqtJhXUDLkChN51kbkIFIATwCvon8HxDPD7AC/hH/3jX/7Jv/vD6+djv1fniVgNX9+f394e3pzL6aNPPxzCtt9vxvwCMfb9GGEk6BzAwe42J44hdL2qLbWezlOtJuJ5W2stf/yHv7u7evn8xQ+M7f589+bt51VhHKiqMUqkwBFDz03eBDCKllJlLrVapoghESMiEmOQCnnG01mWPIkWJIsh4IAddLYqC2GutYjgBNVqR0SB2uRi4OqG3hw5zBFKA7QYRUUFQuxLlSVnZlBTB0JGBhIyBwGElionCoTeMQ9jn7ADxdvt7bYbxmEIMbjbfCwYfDn5+T1UBai6zLnfjGiRvaYUq9WQOHaU+sCBShFCDpyIwvluySfRxaBCsGRKwSkANnMjR0RCR9CikqXTjhACsTog8rws7OTeJkpQ8VqrmgQOBC5qroaGqIgGyBSQXF3FRZWI0NYx/XFd/12kn+8IR9cYHxrWdFlbr0wIfxT2uMQY+Bj6rsF4W+Q/xOaPFVhzCREfAtFLSNsmoScR/ZPqfP24RP6+Cm+sMcgTCKmFNhdm1Hff4iUgxgth4SEMv4Sq6hdq9lOY7xLUwnehBI/BMzYJFnz89LH4y9NBAFh1r7/7TgHaRj62gJ7oQn97lMQCREDyNSh7RCEaQ+rpFZ+AYw0JWFP51kRJbKUYXGTvaX0Qj7QhABDVR8Tu20/1kpHTsIvWUS4JmavW1YNQ0tewCAdf+8XKern0HG/AmqrC6rD48I1vsdj+Btjm8cE+JgxdPrhYMbZEHv/WJVaS0Nfb6G+J83x3CuF3wmMPV/w3hK5+wfEUOHvK9vqFUPG/ZhFNm/Gh7Z9iW3Ah7F0YWw9ej+1oguXEZJfj0jAXHPcJtmrNL8rBac2/ushXtS1qMFsJR4iAzNTIlIRIiamqmbu2F7maACE36WA00AbicEPEi1R35xiQGoTkDrBK/wCby2r6+vgIVtcjAABzagbE6lbdFEEBdRUTyLWskHjDLxqu4u5oygCQIiMTIyGAFRV3MzAiDEQICIz4mGPaUJKmQQXgTSTcgAkIDBUdwKEp6QeKhMgYyBAUPGsthhVMzVfaTKMhtKEUzF1cwdxEkYM1iS1agXtBRygISADutkqzgAGDBmkvMxIgcy3VQS6yeo0uioFDSOyKeRE3A1M3XFM5CQBNWvK5KAUkRCRsWvv+hCp5Ee9/GP7beMYA5N5icG84FGrb8IEHrB384QVsfcz8MiwSkaERrX0QiYK2SxATORk0bi41Zv3aGO6opggYYng6+6w4ra1EM7/gd+6+imGtoBiCOjmGFBGw1ipFiDGlCGY5L+2Xq6stCR6Oh83N/pSPRUqAtL3aAvj5MBlXUW+G9E5gaoCQOu76SLwxU61SpbhBKWAKhFCrTlM+Z6E4J07H+W4/Pvv+j1795V+8tgJFFBnBsOYZOEIyCBpTJG5y+OrWYjF3cTUAhL4LNDIN4KBFNEWKXcilAMLVVXd1tQW0XIoq3x3ehxT7noae749QlzMRIhgCqpRSCo+BOKTeq8JfffbzD25eXOHVdDu5OTrURdydAoUYAqup5zMQQZ8QOsxSuBOH7mIJ1zHGPOl0XIrIm9dlt+Wrq+1u+2yaznd3C4Av02mZ67jpmYZ5mvNsedFhiLvdrhs7d5WSRRYnAjAIbcwBVUWAUrKZl6JMUdUD90wudamliLgZqFiXaPdqZya1FiJU1dvbW1Xd7Xa1VmZChJKXq+vrYddzl0BlOh3AxVxEfDtu1OTt7ZsiZXe1/8EPfry//s3v/+hH//y3fvuP//j29vYtYHh5s5+mUhcztfP97RB9N3QdDPfv3ncMXdcRYKBQl2UJ58Sc57OUOQVIKTRWDzEGRgQgBSJn5ru3b9hdxBgQiKQULSKlmEBxAYBtD1fbzWbcdN0wpshbKMtcst3dHt6+ftOlYR8HB6pq01zMfX/1bNzupEoV4xDU/e3tLZkQEaKXUlNM6Lyca9puhn7sw/bVi+7HP/53Xt68Ot6eN/vdL//41//b//6/+/mXX7x5934xqI7zSSsCBSpST9OU+s6rWQaroALVlFxRCBVdwc3R1i0wdiRoecDQAPu2C4vNWJYBmcjB3YjWxG0nDMyiUqVAXdXT3RwyDEPvIIAmIo0C3NjEpjTV+tnPX5+nigi76uPYbbZdHIZAXZ+oT1HBFKTfhM321c2rZ8Nf/PzNl3U5ukGpJm23VttQixBDZA6IbgomBXTd/fNqVsRYkAkZHcDRhIkYiDCl6OzLebq9z+X8FSjUUj/8sA+x213t1HVexIyMtkPXXW1qLa65gjNEG/puGK7TuZ6mu8MR7u7z/e28Gz4xy6gFpLiZKrt2ISVmQu8KjYlCCMHcihgoZGNYZFrEJF9tN6cq+ec//+Lz91989vk8wzDsb54/u7m++eDFq1fPr7fjMKaBnQPGbdp1PAaKYMHFfvj8BTkAUttvx8tqQbUWqwpOESgE91idvQYx7iDFEDHQ8XwnODvPHAtTRZ1qndVrDH3gDjyIeW0EWjJHMARnckDyULKDE2AKkZE5AIrJvEy1RqL4/PoHL19yP3TEgl6WvBxO93NeKNel2pKLNFkjzWpmoAzMxIG5SD2cT6XIUnReijkHTshRARTMwM7HO3dXXRAldbDfp3EYuhREihQNFIBpybJIrabuM4VEzGpeiuIOMcTQ6XYfaBLkXPWM3lKW6nSyWqf9VY+sSDIm2G7h5vn46sXuet9/+flfXG+eDeM2xpFomJczE796MQ7jLg3bwANyYKaSz0Ta9wNzVLel1Fr1Jz/6NTHIRe7vD2/fvPvq9esI8GK37fqIWHJ+N3b84qqLodZSXXGpeHs/ffVavvgSfvwicYghBgURWQ73s5vlJV3tUhckcR37yAHV7IvPPxvG/b/8gz97e5vHbd9tKcbBHEGEOCZGZnQwtEoBAjqBRPbnN7v97nq336YQxCozAkBelg///qtSy2Y7DpveXY+nuz/50z8/Hm9znq5225c316XiF5+/peIfPnu+318xhE0KCEhGf/j2D8TggPeL2FTg2c37gdPw/PnAHENQjujed50piGgp2ndj6nuOqQMcQijzQkBmVotMS3aBsev34yZ00dRVqooVNUKtBKpeFnWTxAhpYQ791RCxd65fzZ/L4kPcKw6mam6JEqM7pF/68fjf/JP//L/+J//FKZfb2+Op0H/2X/5XFJ8vk9TqtcjhsCgj33Ql1xRjF7vIQUKIQOwo4q3cAos5ldNEXeqGuBnGrgvECERmUGrNeVnmk6hUg2HYJDfIuSSLBNtNN2ySSE5d2mz7YaD9s+FXf+0nP/uVH376o1cffHI1bkOF/Pb0JfDh3fTZub7hgMNm4JFfbK5f0su//PIz83g85rdvj7e3x9vb94c7+OJzeHcAZtj20HdwnOAwQ1WoCs8GuL6Gq902BPoP/v1fc9ByKnM9Zwm7zSuDfDwdaoYMBtuSEjhExwQeasFSYylDrp41U1A0cVpAtfpSF8qZp3M9HO5rlW7oYx8DhBiiISxZcs7TknMppcKLGwoU+pBSYLNaBVDaYpgQo2Z1AcmV3FzMquVzlqWCGgDVpTJTDJFTx2B1mrJKUUeGSBAjcnAzUcau6672m+246boBDGqtqRvMDES9Zs9wViiLSZa46TfDMHSpS10a0jASB621yqKu4I5m8O6rRSaQE1CJKIwaXExW0swlqGOUoqFYcKYUgIE1EFI9ZEcSrQaGxAqmKBxWtyMSr25eHQQAIXHHzA6rwxEiOvkq23IBW/hbIedl7f70aIvpp15kl4BijdTEHa05slwAmwcsYl0RwIXChV8zOX96rPGyr8rECN992t90NKjDwZEJW6bOkz81MOU7ROEfzmq5QIAGzuZf+9PjdaBlAV/AhRYxg0OLxB+AsEcUBX21XMe1hoAAD4mXayEXzGC1dPhbQRaN3kYt9HpoUGgRMzq1DX2EBzgMLuyHJ9dffyGmVvnm2HzR0AIHB0S6MD0eMDa4gB6ACKLfhq4QkQiai9oDK+oBvMOWXUZATuDNBPBrrK4HnI1a9E8NR1uZU3iBNRs68Vjo3+KpPVQPvn4vrehH9KYhYd+FlD5Qyf4OyNK/QgPr63DjY22+wY36t3KslLMHmfNL83zjrr4BHv/iC37zI18T/db/PfBkvgXYramC6/9WNhas3YianFb7XESeft/9Iq3fFqsIzRmQgR+zghHM1BqBq3WvC4sSVL0ZkIODE4AzoboxIQVqjS3WNuAhAGpjYa7g2cqhQVxd+hDR3bxtS7k3+tUDOoru6ORmYGZiaAT2QCkEMATzi3jliiBfKD2+vsQGZsbU9pZNrNFYiIhNHQkDrlJZzcijITjMBABurqtfhTkYAl4cFDXGSIBohIYqoot5NqjWEBikpmIOAOsUQIgBodkvSRVEAAYM3ChcBI2TAromfAI6AjEgMpB5E7cCQLcq7bmsrKVmKwnKSIDI2PwZLkmABC22dAQHNwEHR/IVG0cwdPUmqgGEiES4+lc6AjTXkXXkaNl9K+PqMtiQtWzpxzkHL3CSu/uKwzq4oUEzfPSWZkTgQAGMQGoztL+kTl/6e5vI1m2Rp6+Aropgl/2glSOMDm6Aa/9pYwLJYuBWtUmZoKlJ1X5IIdCyFGaIiVtzl6wWYOj6Z892saO/+vPP3U2sqDQdanCFboTUIZGmxLWag9UKogCl4WgMQEvOz653pcwYkBE5wsvvPTe111+8nw9N/afdoYI7IFBHgYKbgbiTq1Q3sGblFoGZmRmDOyHD6qrSdRQS7Habro+lLKUsymwmKewpCEcDgLkCu6sKAJZaSql9J11Mw4hDgvk9xBRiSHbWbFnBOYS8LCauLk4QAqODLDrdV0rgwYKrWImROMQQ2Q2K1mwZMECB6ah9ssBsRloBEc4V5ilfC6YUTUjUajWRzCHtmGMKgVGEA2HvXQiRKZh5EA1MAFhKyUsFiEyBKIYQRbTkuRbVqjnnGPzZLhC6qolIGxJKqZ9//hkR73Z7AJ/nOXZdcgIVQkPXUrK5I/rL589FdF7m87y8u70dN3tO/c2L65/98k+vnr/+nd/9o/NZZMkh+hihFihTwVo2z8ZttznN89APfd8FDqX0SBgju1tgGIZE5CGEnCtxCB1HTqSO7IzUhTjPs9Tapf7m2Y2Dn89nFVAFqVZNCKHrhuv9PjJbFWfuQqSoUpbj/ZEwDMN2s9mFEGtVNQPEmCJpwBDy6TydDqfpKLnsxhHBhoHUYLvZ8vc+/r3f+f1EcYxjTH3fjwGjKr766JNhs72V4//xz/8fUTjn2ZHEXRSAgorL4jJDQnIhrObFQQAUGsMKzM0QL9m/dMkOQARwp5WgD47aktSJHRzNzNE5MKCrKaA1eSxAXJH5NvaCIbTTTaSqKjPFSG6AQAZ+vKtQgBKej+d5OU3nLkVKiTdjJwPkRdF96PvdfrPzrUAO3eHdl/PpoJYNAIBBPbsBYCQKxMHNwRXAUUoIhIBiYGrg7TUMZqJA60yFTsSAHrwzNK349s1hWc7j+EnotevGcaP3xwmA+27kMEjVw+G8TKVtTM7THUUndCYIBDnXn//8q9/41V9HL9VgnufzMuW6EFGIwUQpdvurEGNCBzGpVSR7wBgwuFbDeKo1jBRT7G+GeN7OIJnkzfHL++X1YfnS4vc/GT9IYZfS0AXrQh9pYVdwJoUKt8HxoniCYKjuqlJdK6ihuiI4pDBS6AgCKoMlhYAWYldNS/UFNINnq6cic1VVsA6RiaFhye7GDmRGIGgO5kiu0MjKpOSMorKoHM/1NE1Z5f7+3olCCv3AFKTWquax2+12w3Y//tXPFxB3dwSKgYgjUUQM4FBKvT/cTXPNoiU7Mvb9ltwQSM1VPSV2N8BExP2A+30ahg4R5rO4OqVAylWXlrJvZtxWdGCK8tXb17tn237oP/hwMy2LiBNblbws2QH6AYis1KljHof0bBe3+7jbRWYsSx3Hl6XS/L66dyFc//D7nyJ3Knx3P73+7HB3+0Wu4u7IFgJ2/UDEopZLzVmd/mR/db3bX4WY+u75Dz99oY7H8+lw/2apt32XN6kPcB5R7HMAACAASURBVEZH8DrPPk24LEpMQ2/bzRUAcWQFyQJqOucagw89Mlofeez7TR8TDCWmly8/CX/6lugQ0xh5ADStMltWtVpLyWfJyhwDODrUYky03z+L7IFwuxkdfJ6n+7v7+/u7u3d3McbNbtw+23ZdVK85z6dpYWLkhCFw1++ubkLsENImXGXPDMBIYxg/uPlQQRfJt4fDdC7L2d+9fodVX716OVA3lTM6DN0mxiT6/9P2Jj+zbdmd0Gr23qeL5mtu9xpnJi/tlLFwTaBoZKkkBkyQGPJfMGWCGPG/ICSEmBUIWUiMTMlIYFNVVlFu0pn5mtt+TUScZjdrLQb7RNzv3XxOGxc+T0/3ShH3NPucs2Ov3/o1mpOG0PXdxlODHqDMDlEFmJmAAViKCIFkFHYIFDx7Z40n9N4DJXQaRDID0bSU4J2v3TRMs2YFaNumkBADmSlEBfXcEpWsWpTUrO3ENc1/81/9F6lgShqTPtydfvnL7375zdt//md/+vM3Jd7FIwDwuc96TuwJREytR/Q33gAM8hLjHNVAs+UKSawwAoEyjPNYG6LgIW+gvZpCM/3n/9l/2vb+5ma3Gbxr9fZm2F+31kyTnmKCx+mh64JiCTsHsB3H8fXd+4f7w3GcgdyHD5GczxnjIqUAwFVo8HovTGXo2+ubHWF49/aBykMUmbPkDI8JlrsFSeX0F7ur/vbV1f7587bN7w9fH6bHLKYC7IEJgDWWGbEIuCwuJliSzRmTEpIYZCYVWUxmiRSjm6OO05wyAEODRsxSYW+UNQsNmUgAlJmcI1otJWrRhwhIxClPoJBTrhx2U0s5q4H3rWNyzsxEiimICQbft02Zl6lpAQG8cwgQywTYeuKCeZFFozIxMoYQShaHjoBA1RJkBSbzgZuhbbxvnDcoZUnJ8rJEKeLIm2KZ8jIBRoCCKMzgRVBEtKR1rX6pK4nZueADBzZZ8Q5lObN1DAg9OccOAXIsBNjthpJ0Ok4yFTSo3rqr6YlzqE+kNHDGWX6t6nxaxl4qRYILNAVro3glNtmZ+HLRWXwsS+su1h/xlf+zVuifAEmrIu+J09Na5OAPUKZ+vaDGJ8Sb2t8HRCurnTBceFW/uRSvn51PbaV0wEW5hNUe98nX1xLTzhSmC3r1N+38QglYL/UyXJfKvjKezsf9m8+1uiSjmRnaJ0OEZ82dgpl9JLWcj/Hpbg3AAdmTAMnLWH2PzPQElHyKePxN28Wbez3VjwSJJ2NYkZkzwrU+MmsAEKxHwJVlddH92RnZuIzd+VlbgcK/dXsKYOH3H9p6h86I5w9c4d8Dt7psf7uJ+6dn8w/JwIJfG4hPkLJ/U9SsTgvfyzKwy11cN1u1Fk83q2i+yAXAupj/X5CsS3yvqiEC82ooqapaLHR8/o59hAURTPUylemaVMeOqoWTIiE7Frm8f/VIFdOoDN/qpmQmqlhzTeFMgzTAylqqLEaoWEalc6IhahXiqckKSgAigCLQOoMQWt1VZU9Vrqer+Lhh5f4JImKVLK9wCBqAxZyYCIkATRWKiomBgXPE7BBBQECg0jKppiECEBiaOWIQMAUVlaywKCbFsuqK2a3lmopW7K7GhJCCCliu0BIAKCEBoxGh8/UV/eiaaAqgBKCyqvOAqy+gfZwUCcFECyoAITKAEYKtRSWqGtXJAA0NSsUuDdVAFbhGXVgl8dU+g3zk9K4P4/k5szqdAKzyxGqXUvH4+njh2TTQnj4+TKKpJh8iPUltFNFqE8n1M1vDB/TjWwCwZmfayr0Crb+IFbg6d2tW9LzinnKZHI2CyyWXUhCVHTOxqeZU+j44gqIppZmCUg9LnHUBGKBoTnlRzf0VtL6typPgPCgmibv9sNn1BkUNiqQiqQnUoUtOVaVtO8c+xXLz7Or93YwM3nsgbTr/6rMXqnCHh3FJoAQOgQlIkIFd9SAjIgOArHkd79UIwzGhohCjDzgtakve7/3+atu2XiSLJEQlInZMmNuGNlu/24EoaAYiUNGScy7AgG3T2MYNA82jphRb17JDQCNGD5QBJJsUAwIgcugs2fQQubHNbdt4SrqogmNATyVpgQwMwTfgogiMp2TAKhS8N9MUJSU4HpfdzjG1WEMIs53GE5JtqWtb3/QBcmHHwXtCp2ai5onILC5pmWPJMYS27dhzMA+ZJUnKKZvljHB//+gI2Dnn2DnXtm3f8TzPsJJG0cxKLq7JiNoEnzynqCknBD0eD1XAmbOkkoevr10IN8+f/daPvvjqd367LP7+4WGaxmVOKSbvIHhAXfLpIJKuX+7bpiEkx0RNc14hym43+IDTOBfJRCoIHIInB6QoyuCY2RF5dn3bDT0bIiGnXOr6O+YMRpvd7vb6mokRoPW+bTqQbpmmFHO46jebfdu0YiqS2Pucyv3DYY6LqOacVLVp283VbrfZPt7dx1Qe7w/Prm4/f/H5H/z7f+BdA0BMoes2bT+EdrO9ev7t27d//L/8b3/8Z999cdupcC4imNuuF9MlphRTKtDWgNeCmA1lBXmgeu1pXX8hGCjqJeSozkBYCy8DAzEAVVrTCSqqxVhxcLE1twSoOvIhEBhCSjM5Na0pBOZC8N7nLATOEY/6AICIjgyh2JTijBaCl4SSSaw0gQ3ZLbMPbrgeXPB9P7397uF0yKBQMuRkUBsziCqmYqrE6HNJWH8gL03jAmtLAddlFCLmWEAFjYNviGA8zG8+5FdfPmx2uN13/WZbzBd1TbNRkaHjHAFUvPOhUSknyZJlQYBN7zd9a0WRViaYGpzmeDyVYkpI85REZL/tu5ZSzNMYSypguOmG3dA5HxxyKids/Xa3cduuvdqNJ5CcSh6dA7Tx7cNfcZh9+4XHgaHJbACNmkcM3vEikbW2PwgMTVHBBEQZgNRAahQGWmQIjA1yQyRIHsl7E3UGaoYFoPgA6AOpOQ5IDsmhOaoBtigFcjKJxYqZqVHmnHIpRRGK6rTMxzjfPTyMcUbmJUV0jAQ8omCOSzSUrvXTlB+PS9tuIAKgIWpo2HtWo3kpIlo0jfM8L+cfKXJqAKZQpcWm213PBOyAvfigQ8vOk5rmxKVGZ5gWNQMmZhfYBUIiyVGLNkNQjAXAtXQzdMNm03Th7sPjN99GztD2HEIHyIDW9uH2qh8Gx1TiPM0x64n7phuGK8f9PJe7uziO+XgoDw/j3cPhND9Wq1wFAAKmByBQhZQhZvAB+n7p2oP3bdu3Lz67vdoPw1Vz24eUhyxvfRM3rZHHCe3xMB9GWVLjmuH6Gh8fFwTgQOStWAEtaua5IDVd1+4H37VOSiqAod0gtuRbsceYTLF0ba8ylVJSlJSjihACY/G+JXTjaUwRCHZD33ZNALVxnO7u7h7uH5d5Gg8Te3x4vPcfws2zq+evnocWdg6bxjetfzjNyzQCkAktizhokuWaFtP5/seff7Xk+eH0GBfo3CNbdby208MxtSl42nTDOe9PlMEA55QWNEbYeAyNNyOP3mPD5hMUUCwFS8bAjfMtEU6WYk7HFKfxOE3HnJNq2Qwbwsw8t6HbDhtuXIby+vBNiVlL6dtm2w+t8wqJYEGLYJ646bcBEf7Jf/BFFhMlU5qm/Pbdq7v78f7u3x3HlAuq6LjEFOPD4WEax8PhdHd3/HB3PBxOyzKNCcxADRoHTYCmgW5zdfvsWb/p97vtbrcbhrZpfNcFF8g7JAbnIQRiop/+26/YQT+4tkHFJadR7FDcDIQJ8s+/+XnjtkuUGSb1pZTl8XB89/ZhnI6+6d69m713ampG3jfeN8Tsenq+HYLrjo95GafjY1lOnKOVRcQgTXDEogL3b193Db347NkXP3327MvtfngRmjAu75zXxuumg7YhMBFdRHBeeF5oWmxOacl5swcuBA7AkIBcaFRR9VTXfmpZFAy9itVmrvdM3IbW1DLhUju/Nf4WAZzzJWP1JLFiRJhTWlUeqiKC5hrfOMdIUkpKMadUTCn4Ybtp2Lt5nuc5I4r3ngN5Yt+wcj7ODybchXbYtAYEWqo5KQhIARJdIBNC8MROfIcpz/MyipSUtAmhG3pEFlkkAxdAZTRGIRJQReLVowkq/IbIjhyTKWhRySaiAMaOQYGNEdA5ZscAAAYxZgANfReClSxzEhQUVbECQATOnc2V6gL6I1sHf41mgoDnoKSPq/1LIhjWtuulsrZzjXAm2lzISfgRa6gd7BVe/Njhxu8f4Mny/fskpk+3Tz74Pmq0NswNqgnUBb5asYkf3NtZW3ep1y8sm4/fqjWFfs/bGtf9PiUtXXyuPoHeVlx1DWmv1et55M76kY/+y/DpXfmB7cwDUzWC1d4YKjfuQmZTPQNGl/OsV/NkKC5MsLPl8VpqUS1EzvgTVH3mWS961mP98F3Cc7icrfXgimBU+6tP0M7LflagQ9fLOI/x9655HbELtYXwssL/hJD199jwLDz6TVjkv8H2NwJYn0BIn+B8/xDbUwCy/v2ijfzeI/7/BcP69S+v6rgzkvSU5/UE37Dvnw5YJVbpSrqrAFY1enfO6frRxVPNkNA5x8xmlnPWUrz3pRQRqUIe9g6JxLRahzMzImrNR4Cz7yBUPMqIyUCKlnriaqudhpTqRA1gIKKAYATOATNRZbqCfYxpRYAKYH2E1ivAVlHWShuqfkurkz0xr2Z6lYlbjZEAqpysgsqqamKGRkxQ+8CgpkVBUVbDb0RgOqMhaAaCCmhKeFa1oWLlExkBARuJqBXVIpYVskKNYDdABFImZETIUlQEGQjIoTM0QFE1rASDYopqRLB6MNaCD63SntTQTMxUdIUeCSh4gLPtF5qZgqFghiLMRMB+tTADrfIYWB8UJi6lQNWGqpqeOyD8BK28/NQYmF6CLdfpD9a/VjmiwsqqRSAEuQic8Qy6AtpKshPJ68/zx+e1HkoNED1y/YGsn3w0YUQErOd8mbi4asUR6s21NcrHGKoJvsEZoDQDyYpIjljsXJSAgkIpKSZVlWmatrvh+bOrFFMzUL9rp3RMr0eFstv2wXstgoabYfDkpzgOQ0+O53mUojmLSOn73nufkojoZtg2TbekU9YcmqakyEzmLKXo2+aLL17ttldv396/e38PQOgYPbE3qupKFUBj5grQoQMArPmIVKVapYTGBRFCuL65efZsvyyn4+nBQIkMQR1DExxzACDRIkWnaQotiZQiIALsXNd2aLrZ7ETS6XiETtEpgBJxnJMBgFsdxFQVjcB8WiKrErB3wUyLxmXJYjMgoyPXeGIiByAYU8aJ2zY0AWOMiNK2DgFygrbtQ6Bic5ZjKTZPS/DUtOxdACTSEnxDyG6JzjlPTGgpliIYkyFpa8COvQ9dp94zruBpWZYFLCOS977v+7ZtfPDb7Xae53mevffe+1yKL8U76tuQY4gzSRQxfffuPRL7pkPiJZYPH+6S5DGOr774ct9f/+P/6B+9fXP37a++e/P6jeTWo267pg1IlhOaJ05LijHFGImQPSEA7za7Z1dXV8P9/eM4HYk0GxB7JkIhK0pGDuH57YvNZhN8g0AC5oibENo2+BBSKWY0bDZDtzEwSSkwbrrOEUbPcUnD5hm7ppQcl5RyBkURHafxNI3M7IJnJvLsQkPepZQi83ev39zub17dvvjys89NcVmyCW6HzW5/4/vtNx8e/uc//MN/+j/9Yc9QFA7H05yhbxBRS5ZpiqUYEeSxSKWiKoAiVUGxGRjV/lf99Tm3Ic6BNPUlJTU1QzCpzlJQzQWLFYfOeS4KuWTRAmjgYCWPE6ODUrJ3dDaFBWLy3oMRQsPsgI8EjMQMDGBmrGaSeZ5ASiG2uKQ5puPp1Pa+73xo/dVtR6zLLMsojw+zHYtkIEBVUxUVNSWPjORBxEzAgAhNQZKYGDKCYyICRQOTnM0yU6cIVlTNoMDbNx/mhdjf9LtdM7CX1rNb5kNg8SzYWtcxseZckLGIicDz2/2rF7fPb/d//uf/mtmylMfT6f74eJomRUCCaQRVuL7q+7ZPKU3HQ1kgEFztXpYra5pgEg3j3fGQMbPH9tqGZ57ReQyNd9PUPb57N+V3h5niElrf4b4MzQ6wJSxqbs7ChoyEyIgMQIombBXGEhRFAwDR2SlZaRQ6xN773mEXy6gkBjnnBWBunAXvHDoDZ0BqoEiArApFbRGbJU95jhK1lEFDmmNMSUBTKYfxdJxPj+OYpLR9a0imUEoZj9Oc57hMwNa3vj14cvJ7v/dTdgFrUJJTlbKkNM2lmto6F9oOQmgMWIEASLQmJRkzqabALnhkD0SaS5HaxrEiajFOqUBOlozI+6ar6XrZ0lJEnt0OS14MIznX9O31s37YBHJTVjBrFRvvBu/7nJWZN0MTHKgsJosqv3kz7zebHE0tfXg//uVf/Ortu+lwBDUIjjebq+C8qhYQLRLrDx8RAASA42Gc52nJk0wAHj7/0esff/bqtz67fvVy12+Gu8d5SUsX1LVkQMRQiooSUEuO5+WdiWAEDljXIAogigjgHQ1D0zZ0uDs23f722fNTLGqYcrLZb8Ow6fsiBsuiksGsaV1oeef77bB1zr8VKEUa7zd93zTNNC7v37z5+utvjsdHJiYIjG6JNsUje/fs5bOilsScQcqyjNM0nkitF3i4P+rnRBAQJC3JB77Z7ZfSuEBI0HWsDLvN0DVhmec4Tze3t33fFdVkxQxMLZuUqGrROw5ADTsCQiN23iOT5TilnJVQfNsisBRB4lzk/u5hPJ1SSkWKaH54iG3f9n2n7EgzSJJSAOxxfjgd7j3A9f7qdnd9vbshC1YSYU+sAAX06PUey0LmiJurbdgO7quf9M4/EwOiUMAOp9M0TadlHOfl4f509+H44cPp8WGZ5yJKNfwCCZxHH8h3m/3ty2Gz2V9td9u+G0IIPGza0LBjRVCFggBE+PD43iBFSFKyUZzLw5JP6AgoPEzTX/71nyo1H+4fjzOAA++anO10TCLQ9orgAbyKpBRTkqYVoLbZtkh+meNfv/7m+ACaoSTQDJbqGg+wksQZZtLH09v3h3dfPj7/7d///PbZ7a3ryC1aTmCzd9XMVUuRXCgVJ+JFnKjkDL7U1HNjNM8+eGgbtxlyEvMNOyZ0Zz0AIDMAIRoxqDfwDAgiJWnJjrxjtxQrxZgQjTxzBca9Uy2YoxCRJyajHKOBSbZ5LJLB+tBtmt2uR9JcMoGFFhnYMw9Dt9kPh/vTFAV5HrgBEABFU4coZCakajqnGQqyzMmunvVAZgVy0rhAAOLeo7GWCBksgyUlMRGohBt0hNUDZl2Ar7yTlKIWW9KcNBETiDpi512NTRcTVQVDFSlQYoxgoKbIRIprblOFmZDWjj3VPK8n6rzvF51rJbmiIWcECp4kFlY6ApzX+fjxhD+iVx+lF3BhR50rVvz1g8IZNFkX++seP0EvLuf7yRmf93Auh+XiX35OSDzXCD+ECeAZnIKPFfjKzfiBb63/X4718SrtPCZr6/6Ty3ty3Suy96Tex3Vcn8gyfuNmVp2g6oFWRSjiZaCrJ855aj/jPnWE64N1xgwuB8eVbbJapBMi13qk2ntdUMvzVdf/nijEvj9c520FsC6cfDuzEPAjTgSXgYUL3+3puJ8rUfv40F4QMbCP9/1vH7fL+MFanV6eCnzCGDkfAJ+AbE/H/nv37mIt/3c57g8DWE/Bm/9fLNv/Ltuvo4+XG/CDn/6t2w9+v96gs/03VPDo6T+pQDmdzbNhHcrVM0tVtRYcDMF7Zr6MDxGtEZIITBxC8N5XpnyOJYRgUInzhkSeHTomFTsDWLAasBkhMZFIkZqDTuY9m1rN4FsnTwWys8qxCr7KatBO5LxzwFTnnQJPntH1hScEwlW+u8q3ERwiIwEDV0dxg4LMJmCaAMwICBkMNGdih3zmRqiJCXClVmHNkxXRrmlqLhEYEFHb9gAQYzTVksUMCD4qwY0AkRCrbJhrv0KSQlHIBoImAGImgNWNAwiQBJVAHLnGtcE7My1IcZkQwRQEwEghFTAz50wBCLXOg6Ymst62qrCkFS9XQzgzTuFsP6Ug5qQJDpBNa14gqpaKcyEjOYalVPKZqWgxAyMmYl4nKGRD0Up9Qqou+wDrDEY15fHiVIZgq8kWnoXZAGCIDOv8pdU7n6jaklHFlmi1/Qc4J1Z455FBtK5VzsS69ctUstTDIxAjGWLldeDlymF1cSRDXMNzAQCUMJ1is+mcdzFamYo6hQbIw1JKHgsQLCk9a6+vr4fHx3HPV93QjOPp7sN7H9h7b6pgxo66PgTvjTI7FMuPhztTZHKAisTM7D05pr4fQuPF4v39++22Gw+Luth1/Wk+DO32+ctXV7eQrbx7+wFErQHn0XkCMikiVgixRsYgr3w9rtAUqAlMpQybhtiI5LPPXtw82337zXI4TY7BMZQcQXW/uQ6hZfAVXQOcnIPTMq86R6AQGjAdho5985fv3hAdO9czETPPD9F5aluPhjllJGZ0CoBQVLVkkwIGsKSyZADOm96z80ga00yA5JyUYiLee8l4H4+B/NV+X6SYaOP77aZXmpYI43wspeQYJQcIykxE7J2z6pqgBoyEbIhFLAs0COwdMbNB0zRt1zpHgAianEvzNIkCMhGzmDnCCmAdDvddt9ntdiIlxhjMIyOTM0NRBYOkalbQNZ6dip2mUbSMUxgPjznmf/zv/YfffP0diZElT9QQ7LeDZ0CTpvX/zy//Yk7p8eE4zhA8tD0yWdd1Q993XVtSLjmBmDdDYkJnKKKZjAjh88+/JOTqN6xFpAgD7Pe77X4rYikX7xtTK0VSiTFjaVsfAhMjkHeNCkzj8ng8iBQFyEXN0LEfhg16vr+7f//h7nqX8Dka8DBsZUklSeObb371Xd8MpoAUmk6b0An7P/mTf/G///EfH++gv6W7+5kcElpRzEspuUCxDn1o/LhM57mZGFYPDBEDuETBAwKaqqwa9vPMgeDUKjeX1OS8VCBCMHOI5L0VSCmBGnh0ztXX2jnmJjCYQ0bCgmaQGL3jRrEguRCatVsBllIiRkeeCVV0GvPhNL98cTvPp4fjyTkYdv7mdtswWU7DVbi63T58mE7xWCKAgECq7XQQRPJEvunaEpeUlQiInKKJqpoiOhYUNdUMJqZKLphBztFUXCPDDt+9jUuGYaftJqxh2yhMQqyIib26UMSEXNlsN8zbnOebm82zm9ub2/1f/8Wvcp4fDseH4zhnDa1j75MUIDHQJEgCaq7pt56jJEpihzHiFJflQC5+d/edYiEH/dbd3t7ut9tN06QY2eOLL1+h6VTm9/fvN82mbzZN2zE7MBCQmJIzInKEjMBIToEEJJukkpUEPVHt2hTNUmLOhaQFZABiJiIlZ4JSrHGgyBlWST6YATJzKyBJISaYYjkuacqTpETNdpnSkrMBZNNxTlOUoiTAEDqHFkueUjyMeS5FBDoM1RQaKQM5QEZ2hmWO5fHhYZwWIN/1WyTvu64BP2x2hixiMaWUSyrFBIjp4c1d33aNsHMClMxSXXCYgRSICaWgmitG3jsKjp0rsWTVUiDGiISbzdAPDaBN00GUzJZnz7b9sB9HTQmdJ8KOyDlgUyNwfTNw4x793eHevvnV2/GYT8f8+Bjj4hskZNd03W7YsyORsqS4xFlSUUPnmRyjQ8lz32xCA8fpVB717S+PbqHO4Nmu3z3fETx/mBbHCloQhNiIARBEbUnL82e3cTpmLegBSIAVEXKRcTw2PO17GdrBO0EqbRceH++kJCTo+82XX3w5jmNovWmKCxCab/zWdzfD1dV277ybxmU8nvo2NMF7h0yQ4vJw//D4KE2jXZu3V8/N8WmZp7i8fzwseXaBk5bOu5LLaY55mvrd1TQvAOygyTJO49hrUyy7wLf726HfXl1fL3FRyVbKptkUyyWVXAoSOfLBMYIBulRMgdrAcTk2vUdiU0AFxw4b7zSQcRu6vtkCYMyLljSP8fBwXJaFvHOuZWuK0yz2cBiXVIpg33fMPjTclRxLXE6Ph/k4bIZDHEVGhLZtrWU2RJNp7x/BL2oowIABoTFwYli0FCVFbFvpe3cNlKBD24p+oeoNGjPvsKkCZgURUABJQkth5x0zqBWDDJCBF3GGoAZFIVXrWG1nBRWJEReAFGlZUADgeDx89/bD++PSb3ZJOyFNGY+z5pKmCUoGnuOz53vXtORMYAJQ9oHDMEZ9++bdfCpqsNn55WiSy9pVrmU7AiCUgptdEJQ3vypvDm/DoPurrz7//LNU7u4fx2WcQNmRqYmYKQr70LiGWwzSGC5EriqVBRStGHDTNYNqZ8DOAxGxi8ly0VK0iOSiIiqSb3YO2QM6USmCTeh8GHLOuRRDjxSIWeaU8+K4VYMlLkzinCnashTvGZCkwDgBwoQOHToka1pEdYgQ48Kta/pwtd+rQion17hu2+XxKKJZUrH6o2Y17qM4WZZZF9jtm9314F1zOE7zeJRsJapmGx8jLKAJIJpoYWMTAyhwXsybrnwkdGQCVkysSC71t3KZFu467wN5MrR5PC5JmVjFQOBQHsFQs4CZoQMGXJNVTERqAwZhXbuvtIMz/rEu5QGqGxIQqJ2ZAaByIdEAAFpVdqgZUe0nrQDQ+Rvf4w8R1ECus3zjguV8Wut+759VoISNvv+Vj8ybpxsi6rn8VVNU0iqdA1DA1bvePmoYv/dvn6AnZzwHPjnHmq1odOnIXZhS+PGCET6udT45hBlUVcnKsIFPRgDPpRVAgU8BnDOW+JFHdT6hj/+vVIsVibv8Uc0bzjwEuJDEnpxAhR1RK4GkwnEKpghMuKaBwTnW3uCJvtHOmpfv3SJYgS2sD1Klaa0yVjNl4AJSeWiEVIrhU3FqRTkrJQJrlb0+Vyseeb4CABMVMACpndLzNf1m0OVy8y8MqxWE/UhFsicUsx/cxye8JTgjLX8XwAd3u52I1LzUT1hOfw8c7u++XU6u7t97X4EkM1PVCvRcDl0JSgCVBaUhhKe6v4s71W8+n2P8qwAAIABJREFU50rAqzeJHLVt471PKZWc7Ykc9EytWs2cKj5VmVOSCxL6EJqmqTZYOedSInzyMqxnsjY4aMVNlYgRUFUFFAicd84xrO9OfRmoWrESgbEBmRGI5uvbm7jMaUklCSB4FwI7NEg5m5pzrGo5Z+cdBSKPhiogSmtClWpRrRMCMvnqT1jLNhBLKeVUIAIIgxIIgJBDZiaH5BoGtCXPMc/goWtbF3wuWarWxRE5RE8FVaysJlUEANBwX82vVuLASsVCJkRELSs+Y6xWYSWF9TVXtCy7YadRxoeTpLrksOC48Q0izlPMqVQgznvvAxuYlKQmhNj7VqwU04ymhMoGDOB96AIRllzAjJ1zRFrKsiyWBRA4eOdcjTdmR6pWpJSSqyO/iCJi0wTnnCGmnFLR6moACFXrCAWIAKvNnkOsFiyEBdV737StWInLYjGjgBWr6yk0YsOSBBnZIXlHDMSEBOCgutGrMyNUNEXV6u70tNXj+TxnEBGyI3bERAZVrrHSBouo6sUBDhEAjUyN6iyrYFp9Z6B6YwKx9x7BTKS6vDFXktfKB0Hf1LAwcKAoBQoQQABqAD0og3OI3pCxb7bBh1fPX96/vf/lL75Fhu2GmKlt/bBpt7t2sx0I6eHuME0nYgTSuJQUtWl3zD1aENFpmZZljHnZ7waRiKDI4B03DffdcHPzrO+2Xbc9nZZvvn79zdevD6cjErQtE3BaMiIN/fZw95AnaDoXWo5zbFt/8/IKPJzGA3n44sef7a+GYuXxcBfnA5o2wQXnHbIn53nviNQSQPYNN20LxqXA/d1RRH701Ven4/HN27fHKU5LBHOBGyh0vBvv3p5kBFAggEABEdOcBTTsOyPJOYGDq+fh+vkwLtPbh/jv/P5tjGWMs4qllPM9LbMSw2YYur4LPvgmHO+mb799e/N8L1nHZf7sxTMOGeDIDF0Xnr24cg7v7t+ZSUr55url9c3Oh+b+/b0LbRGpXfGU5XSMh0Mxg/2u3e/2y5Kneeq7/vpmvxnypg+eeRynw/FICF3X397cdH1XSpEiy7I0TSOKSyqqQmA554fH+/v7Q+Op73vvXS4lxiRSnG92V/u+G1T1enf1o9/68U9/+tUyjr/4q7/6l//3n/Rdv90MJaW3718vENFz27SIOE7jdExE8OUXn798+WK/34+ncRxH5x2YBR+apgshMFYzL4pzrn0xZPDON01gx4fx9KuvfykiIYTpeLy6vnn27FnjQknldJyWeUEjMPzdn/3uz//q52/evufgu6GflmUc52K6xDjFuesGJBq6HorlJe62u/1m07K7HbY/+ezLw7vHr378laEr5Jur6/eHw3/73/+P//R//SMo0HYMzEtO5LwPnsygIImiqImCWSqrM+oZW66rIXq6cCBETWJnji2cFyDEYAzVuKC2DxERkFSNiH3DQCgqwGAMSECM6AiIEGFZxto8AAby4Lzz3nd965wzKEsq83zK2UwAGLx3RDVxwgRE5rx7PrS9T3GZ49INdH1FL16GNvhpnIbm+nr//PCQvvvl+3dvDuOjsnVphjjl4EI+jHjpjgKgMRAZIjEh4JmKhsFtyHmjJDIViXVINvtNLLHr3Ref3Xz+5VXfI/iiWO4fP4iW4/GIBN6BCuz3w89+9ruvXn6O4D58eHi8u/urf/WnRAAM7D0wJSlLklQAq1yo69q+a9umccBgKojqmVofGu/cPD2KLimfchnVxDlgBg9QPQKCg75pd22/H7bbrrvd3e63+20/DE3fcZPvTkO3YQpMTeu3UfU4Tg+n4/v79+ZAscxpbLs2tBvP3RVvbdJyzNeb25/86KusZSlLLrPIDBo7T9y4TKDm0ZqYArvheMwGvOT4/uE1cO53AZ3EOL/97l3X9MXwcDo9HA+pCAZHwReTMS2Hw/1pGVNJimBoqkpgbYNdB86Xr7563nSQJH748P54Wgi9AZ6myVRvb1/e3j4Ho7dvP7x+8/p4HJcZmgaGoQO0ZV407Y6nxSC1HbgAv/M7N0iacnLsm7Z78/oDQRCFUxzB8dX1zdBv45KPj48pLS9fPZeUiKXvfdtQkbSk0ySx7XzXdnPMYE4yHQ/LNErXfPbq+U/ywv/X//mv/tkfvXYNDARdAE+DJDoe47QkSQARoIOvfu/Vv/XTH5+Oj99994sS52KAzOiCGSnww/0RzUM1gsPAyGB5nO/aFg4n+C//6z94+Vvdoh8E093h8c//8s3x5B4eQttupzGzLNM0TXNWA/aOnSDb81v64iXfXvnf/tHLtJw0zteb4asf//S/+x/+KGVwYXv9bKvoDsf7cTyWDMHB0HbPb55t26EBGtrOed80rUc3TcsyLQjY+LaU8u23r3/19beHx9ht3c2rV7evXlAb7qbjN+/eznHsum6/2/RNaFA1xdPdg4vzlzdX/8k/+Y9vu108Hef06LtQLGNg5xwCmWZJOZfy8Ph4/3i/229vXtxmzcC0xOWvf/X1/cPjfv8cyRH5Vy9flPkY2LW+bV3r0bMGMmb0aM5z6NoNUzCwBcZZD9Myq0rOZRzHw+HQhNb7sN/th37LSAjOLMf5yI6QtGmc51AkAyFhEHBqTpQKMEvcL1+3kJE8kgNkI1BDIGDvAaFAUS0CkMhnCGZE2BC0oF7MpajI3tgrspolFcGSQUSLahLNy3Kal/H+4f3j4/vHw5tcTs4BkhMr7falIpvCnMrpND8ej3MEg6brbny7db4nbtg10IA6UT2O04fT4S7OMxQ83Ns8wTwCIOx27fOXt22zmxc53I+Hx9Pdu9PpJIMPJVoaCywIAOeoDnPoFc21sL0Nzz8fXn7ZhSE+e+GevwhXN+H1Nz9PMTsMoWdFleKWaONcUrZi1nVbUVUpOWcVYwDknrA9jfPx8XSaRASwFhpIzK4YVISqFPjt33m5jNM8L6WoWWWuIVMIviGiIiXnbGoxlXHO02St503fhhCQ7c//+uH5FfQ9EUIWJYTQNv0wEDEiEDZguIwxRZWsMZWStGSRYlqW6y1ohDhDmiBOECNrQULyLSumfuc++9GtkT08HovhdDpphudXtw11d6+P9796gIVIHANqbdggcghqVnJuu05VkeD6ak9M4zLO05RiAQLnsWQDD4BAHdy+uL16dpVTfP32dY7FAKhAyZUuwGgMBcpSICtiCNyAGqqpmmqRc3qJY2bnHDusDDDRc78ZzXQ1FRWDDFBNuRHBxM6G5RWxWgUU1XACEKqr6zm5qunChc5k5yr61zV63yvnL/V2WrlBAEiE9dZcEslWrAHxzA773rYeAomgRnsjAqiJiNrFlfyjEuks7VtVPQRIoHphVNFZjUgfqVqm1VntktClAAbeufMKqdLprEpO7IyJYKU/OGeAWbLqqhkCBKDzIDyBBM4A1pkZUxPCV0eYFUMxxBwj2BOUigGM68GrGVUdq+qXDlKbjKpqptAPA9QCrEp8zmhGHbfLmRStI/IU8wMt8uRc8aL3Uq1DXbMJgKr3dEWdav1HhGpYBWYfzbBwpciYpZz1bCPjPFf1WCmFiLz387ggo/eOmfV8NbaK1p7c0+/hTeufkpR4NVb6BMChNZvAzOyC5DyFd54+qJc9XnhYT5/MXwd5XEVm7Lydn6R/8O0p2QwARASekMeenuhTqOty6nV76mr264f45CP7eEcBzERkpdKtrx3UE6jSPwAUtacPNABUzEJEUkpIWB9Pu0CYZ6zmAo3XTc0AjPh8F6tEkNaJCSpt5xwKiIBkpmJmArwWJWmZKx+rGoSw0Ur0g7M9OIFjWz3YBIS0TofMXEAVz3h0VQgCEjIaIaApVlN1dYhIWtbCQk2rmTAKIJmCAlYhmYmcYw0RLjLkFZqHj8UVEIISoFQlWo1sAyStNAA0MjCk+lieJTFWd4hIIiKVwAVGsJqF5ZKr5hmIoB5YQYpWtSUhM2HK2cAEqyPYuZ8FYFJVDqaqlEVZVRUBjbFa90l1IwGuJSQqEjDWG0UCKyeBEJDIORYAVZWV+2pYXRTrBITn1kSdoFemDxoyAROaWO2hIGCtILn6ieDKsDRTMKq6PwQyLJc3fFUDap1GDQ1kdTWr99cMVGwNyrgg7Ocfl1r+0rof8OwvrxQQIJIhyJqQCCqGoqVGq9amAZ35pQbkzmOrRoy1nAYHagACvqF2aJvOD0NPyMuc2bntdv/iWWSE1/cfAmvJBVGcA3bsyIXQGCiiKuRSihMEk5yWnDMAGigxkuB0nAGFnXokRCIGsXz38P79hw9dO2w217v9tkh293acT2MSQiEEEzmeHgQAPPiW2s4DJaSypMkBX9/sQteAyTSPTee3295707R4cmimRTJiH4KWXEpCyi6EkqMql8IGZEBf//K7nGPKKeUl5RktOKLGd8O2RcG303FlFZsiOCaW9TatbR3JJhmC8/suQgbJYjkBUmA33GxLtJRyfTBEShlzlrjZNd6F8fRg2ZYYA5bgkYnMNC6LODS1lHIpMM+zO0AIbUxRAAHRBZ9VluMUc0GCxhMSzHGZpmWeYylWrATfLR7FrIABkaoWkSUm1XXmlCKLJmJHSAYgKqLmfLPbbx/uj0CxBSOipm2IOkOOS8np2PedmX377dclx1cvnn/22UuGf/TN19+8efMaAXe7m+stxZzMTEW7xjyFJjTX17d9v0HgnGyZC0xZrATHbVP6rm9bMkeEcDie+r7bbIam8YCmRWKMyzg7ZOe475qG6fbm6nq3A8AIeaKlFBVRB9SE0IYmBA9MzBxCE0sBKc485cxMzE5KgQLeeUZCw74bttt97Ri8e3+3v362f3GLbfen/+z/+O679z1RYSy1jUROAVMWBGAxUmOxutS4tDuexGlfuJlQVyrVIPC8xFE797kq5bNyJM/WFICKDMTAFaFWMxQAIiZi75DqmtAgn0l5AmakhmIaMYrLxlZKZkbnV5sPBROJKljnHWoplyKnnFLOAuh0mnWcjJmQXTFJEtnDcNWIbrrOrPjxEBWKabFu5ULU3yHHDgxzUUAgj4wsRSRmhQxIxELeKIABGAI3DSnMY/ru27uU588+a7e3bbP1O9yIJrWZHW82XdO0wTdLXL755ruS7HSa59NI1EvJJQkuCh4NGIAYTdVytCxliTNzDJ6ZBMUhBkfqnRC7TTeokJSSU1ITEMBA5hmIgvdtCE1oKQTlZsn09uFwnOL1bn97C9z64XbvwY9TPD2OxKMLGwWCpuVhG0vMYNgNGlwizgqWI0ZlxUKUAIy5FDjFOE0HtHQ1NMF35ILHziCUqFLM2OWiRYxdI2jzktXmGGcBnsVENIoVcOYcMheFKeXDeLofp5hT9SVQgsY5dJSkzA+neb7/yVc305KWNM2plJXsJYaA7OYYf/GLX+Wih4dpHMc19QTZVhvGlpo+FAKk0IILC4VByxzTHEFi1izKaCJqBOQEqABmH2Cz7cF6SQXUmIiM0Lwz9a5pWJmciC7jDBYQ/X77fNOGxwf5s3/+8zffTu/eHa730AUnSXKiOaUSYTzlaubNPXGr82l5vH8QTZ4RA7CREQNCFjMRQgdKpqQZEqg3BAAsgbT4Tv/lv/jlwzj8+GfPTGkz+M8/D7/45YPZYxG8vrrqw/bDh7tSjksWZt7uWudS15kPhCRSopSkmpkMIDUeggPfNcGFOZebq2sRPczjkiDg7ND1oQnEoQlqVkWboNC2npA8M6L0nb/Zd20wDC1COR3u80SnlErJojrH6CdClWpVvdttfe5C18WYU8jIxOwJKC7JY8tEjhwhk2sKlBIEt7jZbjpu0QCQCkpLjQNX5phKNAXM+rPf/gmqeWRG54wZHYNDcwjVMQMqpwdIPLpN6IpKwgRFYZBXLz8zseCawAGkgvHWNF1oWEFEsmJG1KKmBEny/WE6HGf23dWmb8grEDvP7IC5xtdkE0OBtX+oCpDMMogCS57nsRyOy+kUvRuy4pJ0Suk4T+M4Z1LynHMUUYOiKqJriIaZJ7oRJMdMDn/x3SMwmXFKOk7lcPJL0pyN3ASYUrnXgoZgjQ5X7vPPr7b9Vfu8hyIe3Z/c/2vvEXpibnzT58JFo2QLTbi+vrKCUh7GMZlC04PfkohIWkk3v/97P0s5Z83ghEwO93OIc3ABIYI2rd+0VFL6f3l7ux5LkiQ77JiZu0fE/cjM6uqenh3u7C53l5QgiQAJgXok9KIHPehB+qMCBIh6FyABpD6GS0IgsFrujGa6e6aruj4y770R4R9mpgePezOre3q5WBEKFKoqb8aNcI8Pd7djx84prqTg0lpppt7AJBDirpXRFf+aAUwOcQkchhCqNkNtcIDFmpU+CcXEabCSFZyGKXHVdSnzmlttIj4MSCm5ozaYoTYyFbdWm825NSNih6MptLkLiCARMbAQXFUBQ9Hm58tyOa3aCE6maM1ac614/Vkg0rH76jAM1gSmlmuBwFiaW13K0+WiELiLsLnWkmte07TrFWrsRIFdlUJIQ6qttVxyK0NMx+OhawLkNWtr4gx1bU5EzORkyDQ/zn1RPcQhciy5KmtMbOrWQGYGAxu4x/TNFNdiJ99W5wxjJ5iiuaIjDh2j6hVUzn3m2TxVQD30uxWhvYhetz9bkMh9pe8bovIcsm6R2EYa+rHYvQM/3Xfqyt3qKid2XVlcE2Bd+/fql/vJQTqbBoZNM76X/n3aUHpBosKNCtQXG9cIEQ5sawn0FrzoNG3RSWdc9NCFt196J4b1/tv1s2251APtjS7ynP/7hM50g7HohYwU0Dlw15WXX1dYG5Z3pbgRkROD+83qOssOaFegMSeiLrsAcWttO9QWYl1RCPjtUtmVtYetF1ehnyAvyoA6Fc5xQ2l+jHC3HajDZb1O8HZbNs2kT3f0m52i+zNqeIODfgiJYntyHA7irvJMGwOH8L2v3KCo6639O8JKL5/pl7BX30Jr7QaY/d1O8P9l6zymW8te+im+bM+P/UhXYbPehdsOL6Gx733IQtbcrgDW9XN6+cISkdn2aN+QPyKKKXWsutZK12KuK3j14kw/vJBdH6gLUF3Huk8YlbfH2uHups0ZUKcIClRL6eFuZCEiYaZuTdq1qDgIdSjdnUzNzNXImYmZoUqdgOhdGfyKL21d7f5Wgfp9IEVH2J3coa606b91sQsYXd0HGd6Fzbe16zYI92MCMN/EkbYK4I5bA0TsDoPZpibcAUvHdVB0cmLuiFInE4cQtKmpmVYAQGRma5sZRC/SJLgEJubaCgAj8l4YSgxsEbYbvKmbKbkb0Yb+baqN3is0zZ1NROgqmNWNYAGYKRlYmBnc5fKJiMicN/ovdRV6A3O3eETXV4e6NzBEyCL1S2C2jeTuRgFbroDN+ojZuaXMuFUMXa8ksA35Hckz0m2cZZB1CIttG//cYDfqJjFxH+KvOBt6CandhvXusLKN6WYK28bY7h975RTSDULe2IVMTOxkHV2TyENKzFxzmz0H5vWS9UH3055/8lMB/+Tup7VlpZom2h3TOEYza2UJHM1zKbXW1sybrWVdz7MLU4hsrrXWrvIWYhzGMI4xDQHA09PT44fFlb/4yXJ//+r+/v5wPOa1tNq6ydbT4+l8uZR1BkMC7Q/Tq1d345DiGCqKemW2GFOMway1Vt3602W1tLpWbXoYXy95qW2dJpYgTfVyXs6ntmZjiU9PpxBpfxz7tGFaVCPJME1DkvHN1yc4XKFkYHdmMremQYIQs3jJ1RsN0+C7agZyRBlCikMc8ylMKV0u87quRBxCzGtW02k3uNc8VzI6n+f74LKTYTekJCGlGPkuPHz19bdq8Mu5tGUYRlUTbSJJJAiLSBgHpEgxRBExcxGapnFI4ziEdVlFgJEAFgkNramta66lmeo4jq2Z6joOE4ihptrgPg3jftqtOYOQa2MmFia31uqy1Fr1eNi7eqv1w4ePrv7lF5//+T/8j1OcCPFy/rjb7TwixBhCjBJaVVUNIRyPd8yxNiORkFJZy7KsC2wtaiCSaOZM/PjxPeEhxUAwd2s5V2t1zWXJec15joHJjg+0ST6FFGOMIUY5Tgdzr9pyWY2IozizRDJmcQI1CRiHUGsNIezTbhyHJHKYdvtpV2sJaXDwbv/AMX317bf//H/8n/7y330FJQnByU2NhcyuiTiDGGBgx3Xi+T3btvC5mkAzQk/cbbqlfWICoQ8ztDkp9e9sSUGzbprT/Z+ZJUhwgllzNdSX86nptnfAENhZIBK67DmI0MxLLjk336Q/UGsxuBlEIKBScPrQ8W0xQeBmCgoyHoc4gDykHY0HQqPQdjXruuZlXXMr6g0OuBpAFNIQeCBK1MoMz+SN2CBgAgjz5eTiJO1xLe27RVL09PAw7faHMaWDsMYo9/f3RJzX9u7d++VSy2K5qJY6yVBWLFmbKQUPMSIG27inbtwJ9iai0tVY4EIeSIV4nQZHMVMzBgWOBFOoI3IKkZDMpFRYzTMhiVwkX5b84XT5bXrzD/7gD+/39x45U2u5RScKgwnxOJRzXk3TEHvUTq3kpfDie94ZUSPPtcy1PC6X8+UpBj3cpSiUW1EO7j4vubVSG+fSNksweF7XXM5NK3GqDbnUZa1NnUOQkFigeV7zer6cci1EJoklSozsrutyWZen0wWlLqUuS77UUoiECbVps8YkS5kfP55rsWVBKWBAhAy8li4m6+fLqVaVYDxQCGNIg7JJydbUzIPEXsPb4wC32YxjGIZjSpJKrm6N4eSwqnAmCcKBOTAPQYgwwGOQfZ7t22/e/fabxw/v4Ypxl46H6fK0LmueZ22554dYYkijgPXyNH98/5gGhpNwEA5Ook5s3nNQBjNzqw3WmhGgTu2yWJjwF//6N799hzj948//3v5wnJ4uSOn88HCsTSTAHSJpmqYweBw4DdegjMDCJMQcQpzGcU8IQ0BIUxgHd17ndYW3tQZBirwbd2NK4zjuh2FIqbWW59XMYuzdl8CBmO7v75ikqWXNa63LcllMM1zcBhYBU1PLFRTSlMbDcIxpL1JLdfMhJNgEt0GmKEOioRs0o1lwupsOYxqm3chM6o0hELqbDmVs7uzWqmpe1n06NqvUk4ZdWoAokDBFYSE2VTOt5J6ESYaKymSS0sR3D+POmwlJJDGQuIC8GQKjNm1lrt6qalGthqykLofdEOMUENZht7Sac13zeck519bFikqrTavCidzg1ZoShIVcarbLeT3P1R2KUNTWUi95nte12FIquixPjFOMSTgOY4pxcrWcaycOE9PbD4sI3FEa1hWXBWtBLgoUNeSGaoCDAx4eOBTWz+4O++m4m+4O+9d3H+fLcmqLWTPVWjQEd2+5tbxq1RwHROZjerWbdofdzs3bqgQwyR/+7Gcl1yXnuVyW+nR6d8bTXHO+nMzb3R/9/BWjtfKuFWuOUjXn1hqcmEVyrgCpemtmCmJ3V/NKwYYpOHsqUKWq1peFPQEbgsQY3Z1FiNCqtdbmWWtBjI1oo/o2Ldq0NusrWDNvLYOaMA+h4yBbVVfgJNLt1HuCXlvVZVlOF72tOU2pqbtiKS5gDiFMaSTqD1JrWlUhniahAKvN4cTKBIY5VWOEgVBlza5q6qDIEAVbQzPyuB+Ox7s+M+Z5vcyzVet9cYM3QLwrmFjz2ZamLY5h2k88iOnZHTFELZq7CMfGKQLg6mrX8sQNVthclJ7V0/tEwsTgq7x6jzrsGjH9flfATxcCV4l4usVWnRdzxW76gryf/yaxfltD9KKJDQXop7sGrVu12MbSAbN/et7fs11JIX0l8gKh2ALAHoM84z/P200L/IrXdQJYh1U+OXNHsPyadb99r/eRrvImtKFD3XGgX5fuAPPMXOno2lUF65ngfit3277o3n/54nwO3yTXO35EXUyZ+qILt9WWbxrq8Jt5GhFxrRUvrsD30ItP4IYf7Mci/SV6boxt1UwbePQCF7yZ/OGKRFwxqY3UtiU6/dnAq3/q7vaCJ2VqErnH7Na2keF2I14+EX69oT1o324p+HuAF73YcL3UP0Sgfmz73p5XvOX73w03l/S/zUH/A2636jy86Btweyi+Dxa+/LGTyj5lsv0ev8KX1C3coChsD0/HvDq4S51AQ3hBftsKx7oQez/pMAylFHd7cateFjvfzv0DsLGPMH4rnNhe0WfAjra8ei+y3XZzwEDqYOeNfMiBhEmu5b/kbgJiYgncqyMd2imG3E/bH0Und3AvXqZuNAB3RwMZMZOZmlY0u+LdHXfZxMZBSgHEcDLvUu9kJIxN9t1BRs/oHADUmm+qeMC1NWS24TcOcutaXJu6et+B4CYhdJyrf1FE4GjNeiEkSydpMYu4e2sKdxYwHEBzsBCY+9/GWwTofaxWI9/Aeme66ZddZfhdlYTFgdCV0fpL3l/ASuYqzgYybyC7UmkDwbPm3kdiOPuWbGEAZNAGIiKEzV2wt6VrK5O5CAGAkHO3pnJcuVO0gY3eWXHYQlbqfDACGyoJrskCwMndutrWbfxzQK43of983dOtqqpv5DLbfGl6nXvna/G1cLCTRLpGlsPVrJPT+osmIsZwOHU5f0KrtdT8+Hg5jANrWE65kdW1CfE0DurVnGDiTayIOgGBxFq2eZ5LBQC3dalYFwBIE7rySIyIicdRxjHGJCykVUvJteHyaPP5m1efzZ+9/uzu4W5/3MUQhjTW0vaH3brmshbAxjEeDlNM4q4syNXffPcBa9sfv4yRLpflspxdNcUQRLr+sDZT06aNGOO02+0Pl8syr/M3377PK6bdcJnz/f0UQhpHKGyd11IzKw9xSsOEBBR4RTNz668mzFxIAAmEpZZE4ziwRGq5EThJCiwpTN++/3DY37Vipeg00ThOzKFPrjmvEITo6rlWas3gMYQ4pDROScTfvP0WgKqVamYthGTFMJAIi/DhsDODGVrdHv+Y0i6kadpPuzifvi5FmAMzscTgBKCUxqzuHtXMvLWmwZjQARBykigxxi+//Om6rss6t1qL9iptmEIV9cOlPolVAAAgAElEQVQpBpmGcc352zdvWm376fD5T74Yp+m7N2+eTh9P6zlEikOaxhEjAWCWGCOcCHx/93A83F3OMz+xWothSOOYhkFYoA6iWsvp8eN5Q29aCDFRiJDzupRlTimcnh5lI2VHN4sxpjS9/ux1znlZ19P53OAuGPZ7EnJzJyPxEDgmZpfEaT9NSWJgjixu9ng6DzQdHz6b7u5+++bdv/w//s9/84uvwoQYYghRrZkrbbrABmzyfGTYKJt/Q15qe3v9uubrK1Nxd5BSf6F7jYdh0+V0qEECuXuXNOhOtWjUwWrqKbaqPfO6naMrxAAIHCSFKO4GAjOlATERcyylzEsuuTr8kpUdQZCmkIaUUi9ZxnwWZvAol6XWUkou2xwawnCP4S4lmeoc82I0AxeTwmYeKDLzfJlrbZW0O3mkUQBUmBMoQCJCwPyxHO/H/f5A3phrGpPDtdXddH887OC1J2Geni6PH8/vvjvNl2YKgpCHOKaSbZ3rUgxsaXCK7tSzAGRXi1egASA3coU1ciXzcSxDpJQkpl0MQyJyr7WVGKKqrBm1NKYqzLshpmGiIJfa3n/7Js8XaPnTn//J/f6z6WG/ruqO5k2dPXCBZyOwdIYTqtlSU+X9LvCQFD63ktEqWiWNiWVKEJrPcy0L81RVDCjNni5zM4tJIFZKWXN2t8Pd5/Na2lqbwcEcIodQvPZ5U0JgqwYfxjDtAgPzPOd8IdLPXmFZ5tLmUldmHobJPHqhta3VVBs7hEQkGKo6ARLUQuulNM4fLhd3DIAoDzQaUesGMQJTpJjWtdbaaAATTGsrsyQfhl0MNg2j1tpaM21QkyAxTSkOBkppR2ol8+XcHt+t7767fPPNY1lxd5iGYZfSALRSmoRC7CJIwxRlFGLzmltba11OMyy2qiTOwkzcE+fcFyKGTVO0NVNiIRlC1XI3Dh8f86lgt/vmn4x/8nm8d0/TtKew+/D+VG3+5tdnU4BcUhSh1hanMjoADWEXY/RaI6UhTYJw2CEO987DXICGr755lxKOx/RwONzt9rthiiEOQxiGGFRaWTWrgVOUGLqTrMVhmI5mTYdKuNQ1V9IWWUhEiVur0ngIfIzT58f713d3Uwq+rrWYG4UUrWmrOfI08Jgo9fUuNbB4GqRpE+JaalCOIaU4+MOXoxzVvDU3g6RoIHOGOhsRWJiJRIIwiZA4vFOAyCyYGJyrB0UMKYyTzjM7xWHcdQMVZ+JQPdRWyrq4ZrPWce1iMB6m/T3FcD6dP3yYZ59La2vJ61qWkkvLDjjpWpdSV/V2Ixg4erU+WBg2NAuqRpKcxIR0FEmj6CDFhITALLGbfhaPpdIy1w8f1vfvT+vaQLg7CLE5pKmXqrmhNiwFqlADCEEQAqxhfbRvfvnh49f5sD988ZqWz+TP/+Q/efP2G/hvn86nkskhzF5tWZd1no2BV692YzxMaZfisIsTgb25mbHL6f2jO6maV7IarQ51ru+WuS2YpPzZz+9iqE841TIX85zruqIqSFSSGBqB4WAiDhIlUBQjEyARc0i2Z0DMumRtUzPAWSjFYTnBDXkt5/N6uRRViCBGCkGY2Vy3VDAQwqaKKkwpSozx/t5DYBa4KzZ7OeIexmwT2FaHYF3hSrEJtxBOswpR4CYgEo57TiRO4ggkCANzRETc3yUDWi5aUG0NgQ8P01PJLs1JddOiZ4cXW+G+3x2/+IPPl/Py5pvf5bUQECVCzaqTUQBbJTfrwlBuyFTJiSaOKUQJtRbqFlGN2lbURxCC4pqbxwYfbLBRn6y1O/4GYTCxMJ7DPdvCQO75c+CZgv3pvH/9v7/g6fS9rYsJfLLThiP0QouXyJFfS51uxKQNBXFccY0b6CMbLPMj65Hv8UI6K+EKXV2rpviaW/PvdeVTRhdvDdkIQlcQDISrHv61D4Qbx+WmtoMbKAX0jF0HDcgMvFWf9ZRhB842FOdamUi3K3Prrl9JaVf4ja4RFbwzGDfs7Frz91ye1avsQDeDeAeg6i/widsVBHUl4ivAuH326WWSfszn24Rufvh778XGtKJtr5eln+7O3INDumImL7GyTwhTZiYhmPa6wS65JXi2j9ze0+/BWDce4NaAayN/jAr4PZTmx7bvQVfbdX5RiXnbwo249Lc57n/A7SWA1dtwU+16iWcBv/+F+h7a9ftMOumHPKwrUL4xf1T1ClM8X9ZeU9nHBL6iV/0Uvc1EnYnZj/i99xJEv/9Kuvpt+IDDzEF2+2p/7joLh8iDsLOBYQRTyLDBP4GYu3w3EeDGbgpTdTNmdjeFEiNQMDIyqDo5Edi7YAdAPdJRU4Opwzrk0l9N7QMrhw36IoeLg2x7/wXOTgJ00xIB5MY56oe+uiBsxggObNj8dmfh1F36rmCHeW/QBi2CrI/77ATqdYuds4lnVqg7EccYmFhNVZ+vv5pRIO8qZtIpXwaA1MkMPd3S6+HMjbrRMG2IvHf1SG/swtTh96amWojYCDBnJ4c4kbmC4Cxhc/Jijn2KJien7j9IgHRiqilUnDshxTvRybccjRPoNoOQWx8PqYNNxhw2xcI+7VlvqzCRkNiW7rjWo1OHzIFuatIl/7YbA4LL1fqCnXvWrQHuxiRE7NZjXoPwdu+4r1Cvp3fbKLpMDY2d3dm77Bd5CAEBFUVLq4w4hN2w40j3x/sy6+XpMj+ul8czGXs2D8qJ9sfh+HC8f3WMo0gMIYp5FUFihJCaknFrTXOFAUPCMFK9OLNLAHcT59xKbmZ2dxej1I8f8Obtx3lZj6enEMNxvz8cjuM4ffnTL++OBwkiRCFAAnJef/ft1+8+fPf49LjmS4ycy8UR8rpoKQyENKQwpilNYWIKa86lFJLmgBNX9VxarTjNcM8scFAziikdBMK4nPJ5OdXajlPYH1EvVKqjQTf9RoEbO5q6QDxjF3avX99xsHfvv4WQupeaL3V+/925Fje1XNcU0/29DIlO56aG5isiqgCOZj4vzfxMZOOYJJA2Ox4OEqTkVlsGkFJqaiGEmBLVRsQEqdWEzQwi5o4Uh3EchyHOc1D1WqtIAMAUVFszlSDXLCvcuedhTY29pzXRWjsejjHGECXXsuZc6rkp1MCMy4ynp0t6nZjDb3/39ttv37ran//pn/3xH//JcX/41f/z1z6jtZKXUtYG8hhTDEk4xhiZOcZERCBRMSKEEMdxmtIoEFX96ZdfJolwLXktLUsI4qS1HYZJHl4ze22tLuujfWTh3f4uhUSTDON0vDvmOTMzMeCmvcKMukRBY3ERI29p4CmkcQgJIULEUZdyepx/8vd//sUf/OF5Lf/bL/7if/lf/wVm7F8P6myb4SnMGm7Zi+vreeW5/+i0ex0zb+uGjrb3FRmDVNWJiXu+gzYIi53Y3KHWCZg9RaZqtbZOo+zlxXSVzuplCQZQt3ONUUKuRVsVhyUjjrt9HCaRyMvCbljaJQpSiuM0pHEMAgJ587xUIidoKbqWxawACoAasUhKA41pnosPaRjG3ev9kMZxGL3pd9+9jSdb17OQj1OKMZqFUmwppTnigDAgBBwedrvdfj9OMfKY5P5uikMjWanPpybrWr57+/jxw+l8Lo8fYYoYOEgihPOTlko5S85NzdfcODr13DgTCAp3M2IlBhsRzLWiuWq7m3Y10TSxJfJEpEwpxF0kSWZ0WoubpUDjkIiJSwtqrdU1l1br249vX332kHY7pJg4qUpbNbfSZZi8STNyYqiTwoxDGPaH47Q7gAhCUWLcpZGmaaImntfzb9++OT0t03h3f/xJGhIr1EvRCosiVrWUWoj5kvO8lnnN81qK1uDqBUVLtUKB98fdqBGsYdAQrOTZbUmp7Xfj8T4u+WJeHZAUYoqtRVBT4tIqcXCKEDGqzdWVtS+FiODBidJu5+QsDcJKnJteLus6L0Jk1WMcam2qPjBiBJNpy0rcmGCN00CEwNTL6/fjEI+DJl6zmoZlnh8/5O/ezB8/5GVurikwicRhHF893L357lswUSCJTuAhTEPawfwyl7YqGFbVCpo2cu3So2oO5R4hQXu1rIIAYTBziEOkcToE4dyWX/3q/fRq/INT+8nPXj+8wtu332W9RB4/fJjhYMF08GEcd7uRxfb7OowxxkBArY2Y3QDI/fFz592c2VobhukmoLYfpzENUZIQ1Vr6enNZlnmeRWIIYUgDgdS0Wqu1lrKe3r3JNde6qkMZDWCZjmk3BDmkYZQwIAwh7cexGNYlazVEIqOWbWlVkIadBEosGGRgadlPDeJqXhWeog8sIR2Gu/G+04admYUXbeSRCMIQColjoEAQomvERQjCgSK7qZujgYIIDTHO+ZE5JFAECYHRcQOa1yVfTirgQN10dNgd7j7/qSJ8++bdX/71L3/59Tf/9tcLosSEaTcdjsfj3b0Eyi1j3PnQzLJ6I/aWF60Fikoy8GEYD4PEqRNsgWqWS/WSuZkEJkhrdp5bKbm1Qh7dJGc7n/yyjHBJQ1jXmcRBrGalUWtNHTGACOLgIDHGIBKssQHzeDmF8tHLx8vbbz7+V//1P13Xp/M5XGY8nXJ7VI5t2GGc4sP9w348RB41u1BiI1NlIhLSpnlZ/vrf/CbGkSUSS1cebwSJEKO3vFw++u5AASN5I1NrxSpUQeZm7XB/v9GE3JmQpC/MlFivlrAGaxIHZgZC62lMWDOAhpLb5bKcTjlnCGMcw243hSDEbq0SgQWpyzchuDtRSCkNadwCHdMe3JiRqpk2BrHDXGEmQsOAZmSrb8Z0xBBblcmM0SJbEIoSQuBhCCkNHGipq7KGUXY+Na2rlVpRrI1cp7spL7ouWYu5AcTGYOZIVEtFdAoE8lr7KD0IQlcjgXMKoVZt1TkwIrQpiqt4mVsXNjJXVaVuIKeu0mWomODebgFJr767poKuKAZtK2XeOJnXGi4id0ZXoux5aOvo0jUF9UnYuEVNtyUBAPJrLd7vRZpewFXXCLpP8x2veV5V9KgWzJv4zPXgN6rFjyxIvo9h9dCveyORX5WPedvhuR/PKx26oRIvjoNrnu5KHer4DNOzPvVVan2LY7fPDMbGxL0zBGamDRB4SWLy28lfXN4rl2prYyez3+ChvtLdcK0ttjXTa+3hc5UcMXfVFnuxxvMrL+rFqbc78Az08Kd79Paob4Sp2xe7tv+nuM5zr663dDPzunbxSkd7hn6oF8y+gFZu8JDjOaFKzzdo+7qZdSgBz7fsk2fjGU17IQD1wwfm5Y9/M+J0+/rtQXnpTng7yLML4f/PANbLk/5YD/ED0PflJzfc6vZ8v+zzD8+14cI3jHV7Hjb8Tlg4CIAbBgmiEEJKiZk7Lev5Ofh+N3rD/j0XceMn9nne3LC95XRFoB1wMxGkkDjCYFWbqQfmrfrEDOTdbQ4EKLx61uoOEXIYAkIILKzQ5g2lMYUNG4G4O3ddRjVTJ3M3YmZnsAhF7k7DCCCCNpNIV6qAO2ErS0y8qa4QnN1oq4W7IlDb7UrjAOvqgOpufh3fdTPQAKibzxKBlEyw9crRyUC3Ic/UatPWrfIcbs1JKAwJRFocxoBB2ACoehBi9qtQHhs5GRO5GhGIWJgBd2sdipdORgMD3lzRcyTsJHD1bqorYuy95saJQUGIaBNs6iQyou5ST3QNDHvZS1ecYXdrRpJouxtk5LJhn66QsA0bRua0FQoaIBuiJ+6AMTpUZ0Q9ZwIWNheCu5AzdQ8EGOiKB7JflbmYTPzKCO1eg0AUITZiYopCrOQGMw5EffG5cb5oY4DZpgPfrVfcN2o4gdhFyODmxtwxAHWTmOI4jsfh7s27N+fz0/oxawETh90gFFz1/bvL+3cXDL/77NXhD/7oi7tXUxzGcbd31xCTUzgcZLerj49Ppdpun7744tU3v/42DSENMabo7rUWcw0SQxxiGInXy7me5zWGCFrfvX1nXokwTrv7u/uc591uOB53n79+uH91TCOHSMWWbNaqzfPJfNBaNbdmTrp6ohiGKR3u7u7evH3X1Fur57mE1NZFayMWBMaScbwbLuc5xLi/C2mUNNy7nj7Ms9ZFKLx69XBGbmXZpjdiOMHcFFq8RUXBlHaff/ZFnOR0OskQamtPj6fHj2c0XC4LQFb8XX0cxuFnP/vpf/af/qNua/h0ep/Lqlrm5el0+rjmWk2b65yXvM4cwjCOJNVXU9UwhHxe4DwOU0ZZl7MIiDgNA4FV3cyZQndWncajellyE9rcdsxUWEaJBKihKXrGq6t5MQsYtbV1XatqTOnh4TODnS9ndVPPZYWbC9tlrlq/oy/5sBtbbb/4V//qm6+++uM/+uOf//zn//if/Offvvn68fT09PHp6enp8elUW2OWz19/8frzz6vWr776bS2tqX04vwP7OIxjmpJEISFgknQ8TEOM5N5yPj3OSdLr11+8untgod1+XNZlXs7znKtqAB8PB+IQQ9pNg4DuH46fza9XrWmXACVyCWzeYmT3ti7l7nC3G9MgYReG43A4jnsyGYb69//Bf1Qh//u/+Iv//p//D7/5+j0S3EREHs8nFiZmrwbuAJ+Tg68JVP9kOfXpNHddh2yZQOVtcby5PDscJBvFlok6GQubmAWpqquBgUjEDLg29U3vwwOJehOIw60Peg4HWm0l52plyatpDYkbjATjFJhiDGQpOOjBBhCByc3zMhcipsAstSmRt1mJlcVjihSiaiu5WrXsdbX2WKGVSqu1NK2AYkq4PxziwdPdOI3Dfj9N4yAyVLV13XmwmEKMIYRwPq21qFkO437cTxxSzW1elqd3l5CiEBn5+7frx8eSV8wzyOFBCsiafVwfAwV1r5Vqcy8GNiIiEQpMzGrWXEEqgrStK4FGppTJci6XUw2iY5L9IY136ThO7sNa6ocPFzM97Me12eOS5fGRCBIQQxyDPOX58fJ+f9zvxvsQglfVllEdJGNMrasFBGF3MpcQ78fD5/ev7naHAIFaSLKfppR0GlHr+uHj+2/f/e7jh8fD8XOKwzEGY0yHQMUdam615nmZKYTvfvtLkKjpWstay/IhGymCUXAIYuRpP8bETU9rPpnm+4fp/u6LcSTifJrfhsgk5E5rKfNlPa15Xr1WEkEr5M61RkCa+nyp5krEBG6uvCdmZ2ENBGHnoI4Gdqc1L5NTbTUE2e3itJNA3GqFes25+OXyqPvdfhyGJExEQRyGOmM+28cPT3/9f//u9KhlDSUL03Q/HYiR85rP83etNm0gpBRr0tpYFSU3LS0vxc1DIjLy1mnEUFUzq8VM2RHQFE4MbKgM2JyDxMP9qwaNIZqldVn+9S9+/Ve/+vV/+9/9N19+ef/0OGtbW9Np4rygVovVJIT7h9202+2nephUBOta5sviEbUqIewP908nfPju6emypGn66ZevhiSH3TDGgQFSc23FyjyfSi0fv/t4Ps8i8Xy+7HeHGMdlXuZ5WZdyenr3z/6LfzqkmHYT4pDVl2ZNm1Zl0CCBzQR8N+wDkN1LzjCwRfEmHlALGwePkWIgmngiZPc1sThZgzQzgXijUaLF2ACHN3gxlZ5SZARQ6Mkgki2h6q21BiKSgA2ecoqBBeZtqXnc77yZQ9WKqScEFdRqrVCupKC0m47T8TgM78/n//lf/uKvfvnv3rxDKWiOcPdqKXae87tTlfeP45jH/fDw6jiMyaieZ8u1EoF9cIuRg/vgdcgtwOXth3NryFqWvJ6Wy2XOrW78qVpwuWBdoYYhgCm06rVCFUHiIG13CB20cOOiVArIJSQJkUJIwzAAcG3t1Mpc1kdb5oDG8AWL/Zf/7B9ZXrSWsqIVpMGn3X5/F/a7XQoTLCzn+vG7p2++evc0IxEGBgynM3ACzgCWniEGARIgbRjQzv7+d/73fvL2i58N0xTHsBNpraKFVd0M5O67aaeKprXWUpvW1lDNuSnc2J28aW3KwTXGGIcYATZUVTMnxCQyxtSGFlnHYTeOu5SieVMtTS2wCyF0CyqOvUpRYhh3w/v379zRtDkgERHs5poLx6Rq67qWBjeNITCEmUP10qDqbq6t9Vw6i3MgJJXglICBOQWYKhUnCYkGHscB425mx34I+zERhaZW7ISKjVUDm8bh+NmBnT6e3p2ezjIGItOqaO5KgSKD2cIkw7zOcIQQBFrWtXqd6aI6uGhTNC3TlDiJmUJBwkziZk4N0iGfKyvEtxoHI7+ReWwrLXF33yRLAjO4aO2Za7gTb8j5C2RoK17pwRXsGsY70AkfP4gze5DX2Q1bMPpcQvgS1lCjm/gVQO50czzvZza7rvx/JI59xr/4CnW4O4Roqwq6rlB6yG14GRlvHbmpV9PG5LqBZvyCW3QjXG0IyzOu9oKLQ+hGiSC4cyCANrlmbIHUtdkvahXpBRxEDjLq/dkaz7dvwK9Gib05wgH4FHnwK1q87d8b/Mk1u0FGnyIEG7mePq2Paz3fiWcog0CyIWjPbbabceMVXHtJxNnw0w2aJHd0wYcNY3oBnG1EIodqLxHpwOHzQW5A1qdQzLaC3fqxoWNMn1KlvgdjvUSvXrb2h9v3+oIXt/zl3+HWyttBf+yIf7ftx45540y9JE99D7r6sVa97LZft+/t9kOcz7fYHdjCg08uKK5uCGD2zrVjCSGEEIjIzYmobWVsL5tyhaVwvZmbr9v284bCEkmQrbGGa/ku6Db6XZvVGyzcJa2omcKcqNcVujV1ImIikU580Ka1NhCZSZfYokTEBLgqNfUY+7ACAGxwd1dH8x4/d3YWO4UQmdG4uVtXqXI2jtGgV6YjAV3qm7raOuhak0bbK9s9EBhuZEmSwggKRz/trYPbVQLQJaLcCOykcAHcyZtbxEYYc6Jm1m1AmdnhLsLMnbXEImh0BdDdOnGKNmJcF6ljQi/X6aRdRge0uWsydqjH0Sd/dJNTN7eqALZa/Y60WVdcp8DcSMnReU49Y8Fxo7QSsTHA/RnaBoL+pLuTMyAOAQvZtdTTe/V517DfDvJCfJCItoGy/xEikHEv2sYmhXNVcfaeHrp2ZRuP0cW0+sN2fdb4KglJ8O6VAXJm6geW67rNO+vLnmErXD1v3cm3slB3d9OmcZAQxVgZVJaiFx1a+vjufSsM8G43DeP44e3bOIwQYgSjNlJs1S6XJY3MwWIaS5nVNUjgEA4Sl2Ux5DSM4zSlCbvddNjv05BMbVkXQlwtazOCDMMgnNalzeu5qpshBYQQXP18Ov3pn/2xWa26XpancR9YbNjLfTu29tgaHEaOQLw0yWudT+sg6+H4ML46kKf97p5Imo5D3ImkFGmMRlit5drQRlejvNYw2XS8c9M0BolcszUr43AXJ0tLW7VCgV6/36ClkXk3bAbI1fLccqni1lpblvL4CAR42wrwfbXT6bIuBQ8UoxyPuzU/uTNSnHb3w0BPT0/TNI3Djgglt9aqWYeayX0juram2pRJmEUVzNKLzNxdmxubNAtq0+6wLE8lr82cGUzi5hRgjiDBnc1BxD3nTgQRcYJbbbU+PdX7h/vdfseBSy1ExIQUpbU2jmBwzpZzvT8e9rv9wuEyL7/85S/dPAj/5PWXh/FwnO6m9F4rvv32dznnQON+d1dK/s2vvjpfLkRkAWGK8OhWGnviGIKsteymKU5DJDHVkos71jlrtRBFgmhrrTZt1c3gKsIpRpHA7iIYh3Q87IIWBF5rbqrdFKGrrWutbBhiHGQ4DrvP9ve7sDfl9PldGva/+s1X/9e//eVf/vp9cp4eyNSZnJW3l9OIuAvQbdJX25B0nZ/8mvvaBjJs7/J1Buwj93W+om1kcdsyqkbexe6IACY365gUGOQkXbbKHM1cmISEZODYJTyEGESKBoM1zbl685wrHGDjhlKxLLNwbM2ZREJsyQCvTUst5updbHsciDwEAqnDY0ppEAijFtJew0hrsel4MKepJ1HMvLppm8s5Bh5ToGTVZ8urSDI4oklkimahVWoqeakzjELkA+1+9+07L3m5nHKeU5LXn3++3++iHITUtVg1U7JKplayotYYlWVbwZoBBoUHVyaKTMTCTmogN2wuQz19LlUNpnBVgbC6ixmtxThaaXqeVzdITApyqkQGcgkyDgBhLmUpS20Z3oSsaEPJrBQJIDGORQ1GriaOgcJO0j4OE4vDrWRzJ+gQOArQnIXSFOnCSrliqVgoxLQnJC6l1VrUilq10h7Pj2mcQghhYIK3ZSltRQNHhFGGQUQEpOYrkKcpvnp1/OzhTsRysfPS9VTI3PKSn071PNfqgSiaSskIYexOoNpqqedSmrvCTanVbMMBY2II7sJEEuM4sDi5t9LUnQgxhSHto0SBG63m6q2rILYQ1pRCCsLMtZZc/HGmx8fy9s3p69/kVmSIQ6DJjGPYTVMa4vL23Zs3X394/ZMjiIgCM5hYq5vWuhZVE2ZXtWabhgTEza1Cq7fW3LrNjTN17biO9zoxiDt91dQR0nj5yG8u6+PHfP/q/u7uYRp23z3OBOnvda/F7om2EBKoEKGW1rQhdtyZxmn/5u37t28vj+fLtC8//dlnY5T9OE5DCmCmjkFbKTmveV3XZbmIDCmNDkgI424nIcVUhOnD+/d3x30aJyGwAVUjaIhjX5+wGptT17VTSxJFJHEIMfnQWHg3TELsTc24IXNokcUJjDDEVFtT9WYK4xDQXJtqUy2mPIzu3VGMCczC2wgDV1VSN3LtvBVQSCI0NMJSclnn168eTHWupUITh6Y+8Gg8UnJRirsUdiOQvr68++tv33831/3nf/IP//BQKh6fSqOHaqxqBB6mYbffh8AUPER2r8fdvOZ5XS/zeXUibQ4Ny9qWpSxLaVWNSE3XVtZac+6x3KaFMYCmqfOSRzea5zL7Ukytada6xwM2GSdjSORgrgSZ0jiOY4zB3Utep91UWljUUBmVoIQztJa2zjVf3LDf4YvPX++PD042z8v7x4/Lpa7n/PF9WS9gICYJSKaeUEowDiCDGlD7QpkhQ14dteSAX//VhygP48kI+jIAACAASURBVB9OYUQMMdcWSpVmIQzNFS5mtZS2zqWU1aEQUAQYLDIMU5BxXsrVe85CZHYhUWtogkiRIEFSrc4cQggEcr1qqnBgggiJEIsDZMwsgHltTRuaggRdPNEBUyvW1Ly11qprc+cgIhKSROaiuWhtilIQmBgUJY4Sg4OMxJzUnSgwHOrG1Fc+d6aD1hw4TEPIS017iZdQV4Vq99/mQIfP9vth/6u//PVS5imM1KjkYs0CEpOIcyuahtTX8mwMMigBXrhK5LiPcGyMeXISjrG7AfYXgLAFVgRzvwq/0LUSRU2vzJFnwk4XJiZmorZBOB39wDW5+SKU3JCRFwFs/4nQbate+LdcuTbXmOET+OOTyGtjffvVq+nagFulIYiJ7Sqm9Xti6it61SEN8mt057eI98X5n6sM6Ro1bKue58bSdf1DINui5Od+YKuD2xDA7TdmvRf9KvGGcN3O/8Ptx5CSbleILa55ARTe0JPr7eiA3TNjrq+fXlhHd+DQ+fmE1/DruQGf4BJXwteLTxzYFEGvSvad6ggGXT3jn2XgX3Rv++6ttTfY6eVJOxyxxcg3jOz6FdUXdYq+lcR13tPtlvnGRbshUNgYgvZ8xn8vOPV88X8ADX0P4brZ9PVfvRRJ7//ZAKyXYkCfvgl/0/a33+2HDb2qDv3+jW/st5fw0wusqn/4Q1PGF7dq2zPGSFe17y7cbr14uY9B2wMBtV5HfztRVx5ybc2vRY5rzjd4+Hb/u/sdQKbqcAKDwAwiuc4QIHgaorltWfRuZcTEAttUZAFBCNy5UADsVvUq8Cu/yWGm2oXXW7PWtJWGTabRWh9LMiIHDiwsZtblsjYylLqqo/9xIidm6iqOBMQQJHBrrWhxB0VQJHK+QWy9PFldiW6I/jZkAJu6U7cmIKAs5fbyMglzf3VwxUO2oUf6shEMh9H2MpkqhcSBN06TbUFYt20TicyiGzJ1TTb0XAhcRLSPK5sucZ92EQJ3MzUnIoGbm5mactwWYa5OTpsVKEhrtzUw65WYcn35iYm6ZjmczNwIIPY+TXV0jwlG3A06urp5f6TUtNMhmJmCw1QdcDRr1IlOtBWHb/8CbghC4KBaHcTMcCHqmh3uruD+RNnG6iBy7VgYETqJqteB6ybxCCLiQERAa63vkVt1QyDpSiBMPcvK6KhHl+vk7W10R7diQS/t357pfl1F1QIFAg/DuJ5KXWYd7vOKxIGIW22EwpTc+0I/gNnM81rXpZ7Pc4gt7qWZWqtNnciGuOPgkYQD19pef/bTKcVhTN0C1p2DKDwu80oktS5Bhv+XtzdZtmVHssOWuwOIiN2dc277Xr5sqhGLRaOZTMahzPQzmvBrNNVYXyEOJJPGkkxWHVmZVawm8+Xrbn/PbqIB4O4aIPa55zVFFU00YXCbvXcgEIgIwH358uWHm+S6Ew7tvS6aq5Y5n6fzpCjjcpozdbvUJcqaOeLwJGmtXZeiBHDok3kxs7jf3D27u7u5ve26YV58t42Ahkhe46bf/uzzJyk8/VpfnS8jTIX9cl4oytMX4f7DMcSwPwzHj5dclpTK9tDDSfVcJgOMPbT7zomIgIDj5XR/HE7jx8tpXOoiUaLE7aZeLubZQki84WWea6nzNLm7Vs15eff+DUH7IYJMRLquIwiaZLMkuMM5RjFVVVuWLBzGcS75w26377rN6XiZ53PNZLpWf2DhYSjLHJ9/tq8nn6dcq4pQkkSMUgtcwi7NudZikcVBa1kDEXdvmWJTzbXUeZ7BVJZKakISUpdCB/jQdVANQYQlhhD3++P9x/P59Oq7V4HDn/zxH3bSv3y6udvd7YcDm7z/8FFLvX//Mefy9rv342jdQJ4QSvHCIy3k1IeUUvrVz75gijH23cC73XboN33s4bzkWQKt8K85M7kj56UssxCXuYyn8+FwAFmMwdgKuarO84QmjVNNnFMcIgnUh82wHw596DdxSJvt7YvPTpf5L//9r//ib/+SGCIUKORcCB6GaGrqTtKUQD6tlte1Ew/2wYOJtdpkV0Sr7VyPYocP207zTxuEeIXwG7vU17gvQG5mFWByMlelwGKi5CnFnCvMQwocxShWq4pSalnH4qvuqinmaXabVSnGzSb042VhYlU1aIgB7I661KqqQ4iBxdzUVD1CkRfUKkE6kZCLVqx1aK0N1BXs3W7YdF0UmJUpq/nMDIld13cGKsW8GgsZivGy7fe73fDs2bP/8Ff/nnM/HWd3bHd2s08YtvthINtZvf/w4W1dPAQhTiJmWolB5EwkYY1WJyEzI3gzNxqa3wwwM9VaoSA3Iw/sMXJKkMROnmtZznValiZsZoTTOPUWUo8+RTCqleN0fz7b827IeZqXyxD6ECiAI9SKSmQxlhCpC+aWPTM8OnXkCRaguVSd53kcVXK3oRh4SPHp05saDRHTVKZyxET77W1KHQJyXeZ8MRQJVGupeqZSwB2HEKQwZ1BmRgjcdTz07KRVF6a8P3R3+9th2AaBu8YUur43aNOpyaWcz+NlDhCplZZ5Gfp93x+0AlSr2rxAK6mZVnU22iF17PCcXZhzLQ4uRVOUkIQMMW76bkhx48rVq1vUWomMhe9ub1MnwgIiVXv/5vL+iONFXr85H++zLqyFp8X6LnTd8OT2Rc6X8Xy8HMdAdD5dgJAXWCXhaE4515YTVdTYUHOpST2qE0WwAa5el1prJSPAmzgYyIpXd1lqLvcfmKTUSqzDvkuxD6H+zX/4cprGu+fdy6dfzOcvj6+yKRFIqx/vZwk+Xuxyyk9vfXi2K1pS6kKkXMo0z7vdfpy//XB/OY+4vywvPlOS0PXdfrftQyIl1WUax3mZ3BFCjLFvsoIGUvPUDftDb0bz+TRQJWJTi0YCdBypyek7WD1KSDGQqZIK03a3DQRhk8jmcdj0McYWyYjcicDhwlQrHB44ENGiOULcoUVNq1qpbsw8zaVZjkTOBIf4ypz3AHEmddeiag4Wdzb3S17uT6fLfJ6ssoFVB+6e3z45L/M+dpdMBZ0m57T55uPx9enVP77+5vWH0zdvxlL6ECtasciS3aKpu/vM5cxnJ3dUteKowz6B8P59OR0X4nC5z0HCPC451/GUL/MlxACBNasQgCDGpghDKcau77vUxZSaiEwky6HWWksLLIFggIHcAgUnDhyGrhcWW5rIRLFR81j6MPS7Ic9Viy0yQnXTd58/f3l3A+cA2xQN47i8fXN++/a+THCFZfTSC8gzxqolFysObXVkIU7gQJ5ck7pYqcsJcZO//LvpF1886WQPuvQ7GZc5hVCV4jBc5tkdpeiy5HmZtXoIkciZlMCB0m57MJOy3C91VtW8mK3FSpxBm76zEpg8cMgZ81TynNFK+hB1MYkAZDFFwFWNg4CCO2mdUwqLVzhCoNhFiexqS66qlQUxdmqmVgDjVXsQEljM3LlKC/Y6t1Lr5Na8UdWsXkudtaz8Ggu77T72/bK0HU0V0+YmMT/Jk+WlTuNcy0wb6vbdF7/44td/8ZtuSOVSTA2C0MVggZTUVa2qpha91mKmDiYGTJ0RupRkgQHqykBMERLcshtI2B2WlYRBcL3KFgPkrfYSXTGNNblfTamxD1bJkIYBE5yaptWKoviqcruGu2hVLXrk4V6NgAcp9qsLv5J1Hrn63/fQH1ClB8987fvxj9v+12ykT0d+37n+5GLDoc05pAcJoEddrYYJO8jZGrfLr9SHFiV6xA1bcb6rU3nFR1YMxbHW06KVXqZrrsoDRseMRhOq6o9BF+D6Gl9/bFftLV+drNbV6hKvGGTzuNczrGr95uqr8PkDZ4zoU8cP01vrJ7DvMT3Fr0yO9nA86P3To4M/wYF8/T89iOAT8w8m+RNg1LCFx8N5uCltVI1dJcKAqzsMYPpUiMDXITyAKo2q3IoGCAtW0TTiRwQub4+sEx6xkR56+AGG84AFPX6WHv/g8YcPeFT772O86OGQTymE/6Xaj7Gqf2b7AXR3fZH44UoeAKyH942IWsKLmTXZ/8e9NQCvsajMLOfcAKxP8PNVg8+x5p22m9fMWQClFFVt0lcppSUv7bS+IpBwGBM3fZZSqpk+HnaThFdVN1yf9vWFcPiK+DTwRCyIxBgCBTR6QKlODkZMXErxxq6Nodn+NZclVygaocMdcGvkr7pUkIVeOHDXdcir22ZqVtWqo66xfaLgikZISBYpAkIQDhLBoABtedvetpWGNJl7pXXpudZhJAIIui5p5k5KeVqYRUQkSKPagq1lWK/T4VfM/pGS3prkTFdrUmDVA3FMEhDWQgxODUVWVa366dEhhzWHkKGmqGhMhBUINBNqFCNQU1l3rUpAQCAgSDDTIEFEQGSquWQ3F2a71hht5133H1Ajna3IzmNknYjI/LoKEkS9MDE3nA6Oxm5qh0lTwlon5FOFwZWcu1K5hEObZ25hjTXSQBREWQ3uruTcNkigqSGgcenM7KrZBiJneCUnMga156KxowsqQGAYuzRZfrjB2uJJjc5BxCBtnB4Brjw3c7ARmGo1zlUikSN2IfnWqlGLKpjnrHleumHjcGLnAArBrC6aL+dpfzdwpGU5py6eTss0z0Sz3Az7/RN3lyip23SiNZf7+4ubSQhDP2yGDVMqWcdxNi+l+n7/rOs6ZmaReZrv78s41Trz3/zuH2IEC5482ZRawJzzUjQ7mVrtu+5uf3P8cNZSvOrTu2e/+PmvgvTn8zidLm/ffWQhtVJ16br0+ee/ev7kxe3+Z5vu7tXr7z7evys6ibhpPR5PbrTdb1LsTMv9h5zLvNv0WwyXy1LGGW5OCvLYxVozCEg4XY6n81BNL+N4Gsftrk99HLbd5X4CIcQQYtCqZnY8ncbLCAofv3r99Te/ZcZ+t+mGXtXmZZlzMYcEnuc5pRAicxCWRJxzXtw8z14YMfR9vzGj0/FyOudaUSvgSAm77b5f4pPn26o2L1rKEoTRiQinEECSi+Wl5GUSDofDtktkBqvqcArS77Y73rl7WUrVWmvZ9rsuei6qauTYbnqvRViWedJl6VO6O9zGKET47puv/uDl5zHEzWF/d3d3u73Z9bv3Hz5+++rVV19/latuun2ZL5dj3T/bD6mD4ePxNJ6WQCF19Zef/SKEbrs9bIdE7BJil3o1O59P1l5ACcN2l2qZ50mrzuNk6nnO5/N56BOrdpEpJDJlIphX1Ugh9B0b74ZNolhn3T7b7YcDptql+PzZy2c3P//ffvPnf/HXv/7td1+HFJiFqvddXCqu4LpdrTLiB0NqbWb+iZ/6EKz7BGY9mBXrztH+vMbYrj9u+xk7fmgVeMu5NjAgYGaGMIiJ5mWGgQPHGNOQIF6sXCarRUGgSO6uFTkjJUiXwGwKGJv5/XERghlCRIzouq4iZ81gSKQQxYwkJHdapnI6zqbcdSTCS84zxhYWcIUDPXMIYbPdP316I/DXr78puux2u35oCSgoZVGrFDyKHG43KfFhONxsb1KX3nxEvJ+1IjIixfmM/bY7HA59r8si3+BDVRMRGCwrR4BcfZ1xEZJAxFQqzCwvWaQt1rZyjwBHVUeteHKbAnuMiJEk8OLFi1WzUi1E7HeBYONsi+adYHtI3SbVKtN8mY64eXIjSdRKrbNyGOKQdv0iVhWLlYgoQcylJK+1mC5iNYlHoELzfDauRErOZraUPPssiZ6+uDmeLvcfPhTL232PSPN4fvfxzbJUAnEAqqbeIIt6VSWHxt48OLP3myjJrF4o+NBxv9mmDpuhTzG6eanuqo3pjFZ1ofhSoBaDpMt5GsdZaxeDxdC5+7LkaZoAjoEpIit++Ys7SVrKJFSYqZS8zNM0XbSGovOm33UpdqkzJa1gEqcgoWM2CdZv+y51kZNWH8fleMzv3uird2WaQpdun3/+UksYL8WUutQzyzjOp9O51Np1dDkbU9UirmIFml3zamo0PTtnU4eZBY4pdm4GUzdqzBMDiD0mkRB0HosaWS2zSuxqqdAiIdxst0utf/Z//uZ4fP7f/nf/zctnP/v4/vT383fNwNClzrmM05gG/PzzeLtL4yVTrPuhE+Hj6eNucwjpdtgMd8+7XWYwdvvdYTfcPbm52W4DcR3LvJRa67JkwIkQY3SSUrWexvFS9vubYXvYDdv9sKnnjzXPHz+e46whJIpdoAgyUyXmIIGIvBpUhS2IO4p6DkRdCkbqqM4KdohIFHfPmt2MIGpKoCRJHequVq1o9eoMpkDqzCJgaQzu0nKVkUIUorpKcyOkZERjzUtd5jqXIGGz/frdu8gszjedD6oKjh4Qo5MJ+gv0H1+//T/+6q+/fPUtOrlkefX27Zv3iIKbHbpyyIvN02Wc/LJgWgAgRXQBIWB/QN/DLOYiudB3302xJUkZygWcKARQYCZAgsTI5maFmSWIhEgWvMJQAQ/s3EnfCXPPEr97OwHcop1mldyIOBLKJU9V67LUqiXX5WQRuNnekkdiU/OFcHvYP33xB5JszuXN28vf/ua7b757fX+aS7FlRp0QOA1xk6SziqXMWgpVoBQUt4pWMblVVFSKqMIe3ah8KMvgKP02PYmHiG5KgTddghjHkGv8+OF+yXmaq1ZnMeaYIoUuhiAS+iRDMetCqllrqW5mqiFCogtHFlumeRrzsngtmKdai8aY+qFPXTIrIJXArgZo4Ogkpl5KWXINkWuFADEhJQGTVXdHwwdBop5jtKI+L7kshYRZIoMkoKqDrT1TWt1AQqLZNKtqXXJdqqth38cuBMsVshZf7zouPnPc9Ieu34RSPZyS6fDk9mZ3szWqSFDXagoGC5lrNYcSE4UuzPNCREHYzKoWTixM5sXUvLqE4F7NlSUwsZkTgwSrtMpsRquQIhraAobCCDGEptdpZqp19QHN3dSJIl0TPVYXwYmYyLCmDn4CQ3wlF63QArXCE9SCXlcKxQrK4CETsOVf+A99cXIYNxPkwZ5okbQrwrIGz4EfyOQ84A4/0WiNlT0AJ63b7xX+AwDnKxSMlhEAa/kpn/RzVmivOfTtrHjgXD20RyOh1Z0mImJiBqD2kFrHFAirRuP1Ep2wapgB5OzmV/E+u2YCwp0MRs7O7W48QsmaiLvDr2X9vhd8/P7EXC8NePDmVmRj/XC9kT8xsQ/BzEZlaLrK1+tf/+YVkVtTRBsbr0Gr7UffT257BFyuXz98A8LKj7sCIPxAfdKVl/NpFj5hqVeD1X+SFPZPtAfp80dj+4kZeFDufzxp3wdkASA8QGXtz0cB4f+/28N5H0N0/qi1bx+uhK/t4fMH1PVxnz/o4VM/K3MKK0uqeeIAC4i41TVo6KPIquS/CvI94IgNXgddb7YDTUBcHsZDRC0JsdaKK2hNoKaB8/BMN3lvFhEWNS+lFqsk4EQxRrUMEFhEAoHmcS61ruJdAlgDlMgbvmNQ8+AQYiZeLMPI3GDednR4y0GMkQNAXrWo5VIIFBAoMAeiQBRIc76C6EQgoQDShsKaG+oVgBImZnKGOTcIxhG50cCkDczMqrp7dbTiy7RWKLniv1jfVgKcQ8eBJQXhoFaNLYQgLKioVVdqmpuqVq2wNX2chTkEB5MbnJrkE1bImZiFiY2ucNuKSa2LbXtYpPGv2t10a0FGFiaFw6u3il7U2MNM7KzOvk5+rT96ktf9GGvGn63X6E4QghMHElhLJ1sjLd40zthJIACoZVSu9XHbbtV4yCuVubKCyMwJIGty7I3rQWwthGUwrPUC2qUTnBs7VACwAM7eZMeoTRc4tBq3SkamDVFzMF+z3uHCDUizlrBpbsxECAQ300q12G67NdLxPLqChDiIGGlVs8Y1N2EWIXV1Q9MLf/J0fxnNUC6XmnOFIzyLN7eHWuplGqv66f0xT/PlMtVqXRd2+13f9SLiTinFm8PN8XyMSYS91rkqNRFuhLIAf/Szp+MyXi7TNE+Xy2mDPmud5ouwEMMdZt6l/nb3RDvc3b4MPHz8cP7699+N0/zh3fvUdWZ1Xop0XqaIX21ffvbzP/zlvgvDxw9vPx4vfeBOfBzn3bBh4eDeD6mWfL6fY5xY+s2uK7WWc7VFYeRgu6aaGszJ09Bt99tZZwkSYyzF4WgJpyISYjCv4zy6OoDT6egGiZAQQGQOM9JqtZxbwSAiidFF4GB3rlpNmSkxBaIQYxr6bUrz0KNWbQWzy4JFqlrp0iaGHjiV0nbIlXHXIDGt87JUR5YktW0i5sycutgPfWJStVIrA4mZUl8M53Fc5gxTYRSznJf5VMn9sN2H20OftoGlUNn3m2XK0/0Fhbque373/O7m2c3+7s2r11999Q/Hj4gJd4eh7/sUezNzHecRRJUd//CPv/vVL3/x2cvPY7cxy9Ncx+WcS5nnMQj1feQgu01XlsVMp3EZx9HUASRhdk9BNn2fCNHqlHM11aIdh+DBlnLT3wgI1KWQBAFOiftIEeC/+Ot//7tvv7lo2Q5bqHmpn4i6aBi0wZ0fNrhPf7nbQwr6Y9XVa3CwLScrd9KBT9oVj7dOXnUdV2WERrRfDT9vnFCmdQ1slR2szBWCKNHJnZ0DsQsXQTP0A6k5HEwIHPq0MyNACYGRYgAMqqgErQ399qpopQwawG7mZlaLm7JVZC1mdcpT3Bmo7VoQQtcnIVmWfH9/7lLc7+/oQDHKdhclkFYdp2nKs4iFRF3PMIkJbnWeZpxRF4rCVjGe69tvjynu7m6fi3jfb7fDTusI0qpWyygEI6x5DASwO9zUarVawWKUOMYAkUa7c3iIoe85hrC/2bpVpsrsIFvKUrJTAgdwgJFL8F0CCyRiKpMtOSU53A53h/PP/+jnodSpzn7+YDH3++f77X6XZJqWi5oy4DXXSrWIaIqeIpjMUbUuMQkHcBdCcvN8vpyOy32O2g9D2gpf1HkyGp2o2DjnU6kqEs1NLZuPaAW+tbGeK1GtWs00cRQBR0rJU6IQHa61Lu5mXuC2LLMzG9gMbgKC1jpepmWuy4zxfD9d6u3dXSnlfDmeJ6RoqbPtpoud9AkkFCmkrksp1ryUmmOKxE7CHGBUc500R1MJwZldYugiBeF+uEmht8LLtBw/5rdv6njuh/Sc3FMc+u62O+xevuhV9XK5jOM4zVM/xKJpHEuTYPRsddE6eR0FrVBnA4xDK6viaqDqlYyIYoyurBXFK5EzOVHLcGQCtFqtNUhghxkCwnhcuJOacfx4Hj/WmyfDYbi7u307jj6NmquDkFIQGKNPYSOi7qXU2SqRetGyv9nsbveff4EQhq5Lt08OQYwZ8zKGazhTQjC3mtWMStVcFqLkMHjtNntQMAT1crpMmpelXpgv3WZzd/cs9NCiOWcEVmZzK8vstKRgfeqZrNaJmEWYgNP8YZrmAEG3jbwxLWplLdBR1J3RJNAaqCsUPJiAAg+SiBqABTas1fgczEFITMmMUxCXoAybLRdVkZS2JO4xWq7LeRoNkxGxLM7OQqEzz9+++ebbd++/fXv66g3SoMNNf/Ospzjf3+d3H7DR0QscnAIzdJ+4BelCIHerM1yG/W7H+20ulI9fl2K51ECBpAZOcPbSZCCIIMyIEkUoxNC1ekAOzVW1LsukWkQkdTH2crw/sgdvXivW2np1rExUS/VqxHBFHwY3/3h/EjqzWAgLZvzJv/wT4qXo9N2rd69LLrPmSy0jC/c9e6YaECO6uiDPOV8qOQIiEypla3Ks1ZUrqXllaC/SmRlcvNj5Q4m0eXqbRv3WLbNAHMxIQc73H6fsSwYRhhQ3w64fgkTXaqiRhMkkcr8bOic3z6Ai0bsu9H3/3VcfjqdyvK+1wJWW2UtG33uIiQWlFKAOmxQEbkSAMBnxWuJWpKrWoiwgIYdzoH67jyIssVYnlr7vbcpkZVZgAUtOKUoMiIi9DF1iIs15nEsXQgxs1YsaO+9Tn7rIrfKSAepMFBOnPjx5cphGns6m5F3f7w57cxVYpfL2/i2ASooOJKDiZlq9wiAIfZSKTMJNKwDNqjdHQe5KV0IIIYWgrnA4WXVVGBOtUalALG1LNbNWto2pKYgTsTARqavBiTnGqKqNA0hagqwicQ0N+aRTjsfu/cNGT48/ehTJWi2FlhzzA7vgccoeHmwBYnsALX7Y4yekpkXoH1NmfowdtGMf3HJ8OvB7I74OyukhaaZZNQ64GWEN57dv6Couc3VZ/DomeoSYrN19CvdRozS5O2hFnZpr3WpsPcYW6MEysgdOyRXKw8OvwFd7jK5nXbGmB57S1aVa9Wq+P9nM9OP5f3Tlbbb9J/Grx/gF0BIb7Qc//AQMPu7WHT8F4FBTmbc2MDRz/eEMTX/CP6FX3yMSNVYXCNcMqE/aW1dE5dNQ/1/bTz9FP9UeBvCT/31o4fFQ/ou0x4jYf257fFRjS9VHuMBDzymlx+S09vI/1qh/aGa2LEvO+XtfEZgphCAiImJmVdW01vopwZLoe/3XWt29IVP+CMMigrm1/mtREmplDfFQzRAIIcQYp2miB3Ie0Gg9tSp4BanblVqAm5Za2vNK5tWdY4ATr9R6V3ezpuDbpoVX1BrkpNKF0AcJ5G6llGUqAeyAq1tjfoACBaEgxGSigJCXVX1z1fxui4ekcMXMuX0QRJis5JxzNnMSEpFEqZGN1K+adg4mYbCYNGTYXBkABSNbSw1Sq4PX1lEGyA1uRAYGE5EEkSS6VDOoGrxWtaoFzVVie3h1YDCBCHd9fz5ODGoVFclXXlrLFTWz6l69rnuEIwSJkgKHWtULQgwwWFsIiKN0aMtEqx/s1StKVoriTGvhrisGpvppncVDQrsasRFRKxdo7JBrRYmVX0XsRCFYW0gYaCVUwNHF3avqUqu2S2UnorW6IjODwFK4WiOtXQWp1FBzaWQuN0ABAyIQ14iA4WqatlqK0hT9WEBuXt2cr0LTjzdFdmcndgcZOQtwZZ9h5UhqoNh1vTPmsszj/NmLz6vnt9++gaNYjY2OByjMUSHggJBEWMhs9lKK3t487bf4cP9mv+84D3qpUwAAIABJREFUcK28290wp/uP0z/8/ss848mmt6o5ayl+vuTX799HwXZgd+v7Yb/fxSA5T5ubA5gv5zMRHw6b3aFfSqlWqy7VsFSfS+5p6DZ91pmJun6Ypkmn+rMXP3959zlpOt7nv//bL1+/en9/PF8uZbfZ5slKtnl0KP78/d/9+Z//HdLuX//hHz978eRP/6t/9eL+9TfffHl/nMc6hs9kWRa1EkN4/vlz4M1lus/TvdD25tn+0uXpOFN2I00dS2JMur/ZL3mZz9NlGpdisXNJ6abf9unm+PF8uVyWZapqXZfyou9efxgzv3//bp7BgnGcQq21oBQtpaoaM0R4t70xlVJQq+ZcpxG1ZNTKEmpByeTuIjHFjVtxvdSC6jCbC7y6ETNBqkIEjal0X0dANpuBRCSEnPN5nKdCgJJ5jHGLIQS5P576ruv7ru835KildJFvD4dxHOG+3+/LvNRlicLslOf53evvvp5OXTd0In1M+ZjH02U55c1mwylZ1aeHJ//2v/+37z98+J//3b/76ptviIT7jUia60xVvMIMC+Grr17vdzeXKe/2cIg6itb7y7mUpe+jLgaooX/x7NkXP/8ZAVa0Zq1FSy63h62wyyyTVs0WWPrQOVPi2FEg0qe7J4GipN6yf7z/+MXNyxd3L7u4A+R/+B//p7AFCi71Qo6NtdTi0PYQMWe/0kAfb3ZtpbhGCL1Zxlcs36+Vg9p33hIG/Jot2DIQoCtc9GDV4RoJbVbI1eAzM1SoGbQZYZDU4kCmVksBHBBKm4DBITACAyK874eh60zDMuXzZZxzraY3h1t3y3GpWqz4wrnCRwUTRDyXsiyLkAypF5ab3d4qlrkU1SFEiUrsppiLjjPG85wEIeDDh1NKdNgfUorm87T4ZhMlJXAQicSFGdN4Ygix5zx7yQigjvKJAK8Vb/S+uqnr8xdPul4+e/kkJrqMM4jT7d27Nx84IkSJzETEQYhIVYMVWxNAGuaspZSpwh3bHvvb3f7mMGy7nKdlmXJdFBUpRVGKSuwSMezS/tD3g6RItc7zeIJpn4anzw5Pbj7/6u0rm5ctd3f9XruyS/02diHGwUWkByeSMC35kjzGfut9z70HnerpnEeKnG2axxlZwUXrVMUs6KJjMd0cYuo23FXp6s2Trtrt5bJM45JLNkybnbas01qtqKKULkkaNhJps4v7w4YYOS9zPS9TWbCsm7QrqMW+hRGAViozafF376ZxxnaDuyebvJSvv/5KAiSEX/y8GwYJCTFyv+nefXwXO+x3m5vdtg9S8liWmWGU2Mk4rBnH1RYn8igSOASOXerCZrd/MR7L629PX391/+3v3/72H8ubtwX1tFrr+vfY4osXT//0T/7057/42W7f/dmfnf7jl98sJe92Uorm7GUynbnOIGcOEaaKSqwxIiZIgoNLrVamLm23m30iHc9TGALHwIJqSy4LB0qdnJcMg2kJIgqJQWotITIyfve76e/uvv3jf/3yVz/7F7//7RtgHC/jfAEMruaG03358G7aDUPoQs6nLnHf75VMYUZWXUuejPSJHJZlHPMErR1JH5KQaDVXUgWRxNCp8avv3k5zHnZ3HLbur0vVy/Fo82mTOnPU6sMmp24fQleKLvPisRVQzlrmEMtu0213KbDnMuaajVRC+Orbr0/n05PDk/j8BdfF1ISDkIgwOZVimjOIEIQTD9Sza2V3UMd9U88kg8PIBGyBJZC4gV26ELu+z16zK5kt43TMl1GX43j51a/+oN9sAg9cncMmT/NEtR/6QPHtu+/+1//9f3l1el+cnn8mBTJnnYuqGhNz4MviWhqOr6U4ucXEDoxTHWegoOsvh9vlxcs4bLb7J5vxOC/nXDw7Q7WAWN3UrOlIRGJnWDEuMucWxtZpnoh9u9nFuMm1fjyezvPJZ6gVoJXoIXa2bDkXEKCIwl2XQMRhYxCji9plN/DzZ8MfbOnP/q+/yDW/efv27//hd199c5xGEAWiNJbsxVxpqcupTigVxeAIMQUJZPCK/u62WjWdrbT6HQqY5lqXMuwP+fL+L//vL//Vn/7y8z+8rYE2m7jl7jiVKau73tzc4Tw6Zua43e73h9sg+Hj/7nQ8mcluC6a+ZkYzJtu+wUrGAr69OaAel7HWGXn2ywnjhEA5j++6HsTY7rqwjU9v96rl4/E4zyOH1PWb/eEwLjMFSsvEMXRdFBGvmi/1cpmnpahCQgiSUt91/WavdjnNl6kw+a6LQN1uNoftgZw+vvtw/yGfS7GKrsN2M+z229RHEbFaPeflkq1UkqJ9SnG+TMd37y6vXgEXICAMHYAEvzkc+m7Tv0hYfD6V7TCQSpGlsmoxdjg7VyZDtUqMlDpnr7qAYKaqSF0InSw1m7OQ1KwgsDCBnTUM6SHVhl0BCAIxSrZaS/P9cy7CHFMMIbY8IVU10ygR3uBf06pefwBItKpzV7DnoeZL82qrfuJhA9S0QqhJyzD/0w74GigDQI9wmH+6PQAZ/yl3/oED5gCRXd0Fv4YPnGCEUNB4PEyPxv4AmF27MjMyf0h5aaILshJ/4G6t30fZTOs4iUlVHcSRm5xFY5/w6pW13MI1ZmjeAljugK3u03WKzNeCfOzs4qvaGFbCCj4RmVg+qQn9FImqFVD8BAzh+5SodhzxT9yBH0Mo7q76A8GlFcJqMMUnUpR5C18+qDBdz/tjaPGHrZGBzNxRAaA+Su770RV+D736Z7eflI36SWTqMTMJj/hJP2jhxwf/80GynxzKA5D0YzjpP7f94PAH0Ooxncyv6PXDjWxfteRJf6T7BYBADbFq42wSWq27xuG8PtVot4avWXJuBgeFpnL3CcNCi2aXCoCFifCD0z2Q7qrWNfds9VLcrzgx3BtHptaq2qpCAAwEGBNgwkJgaoEOGAvHjkmpFcRtAzZzicLCHKIwEaGaalWyq4a6EQyuAFDdoMXoKnFlTqFlmIjDVbWFM2OKbSUhU7iYK9wDuZvRKuRJDHYQKbTlork1TkEe65VSxiQgJmGRIAo1qFOjM5krXQuutlRkJkP1XCDiFKKURL54NW1l8dZsNqDNP4UAh1kF3My0KlS9MT9trTjfEB8hVgbBGAImr9YIay3N00xzLaFlaK6wd3s/G8BOYGG0EsRei3vwxqhqjN8mkU4rjvSIOkGgltnjV0k+grkKAoG5JdALWa0E8qazEMFgcmFIkwGoxdwNgVv4oK151ESzqLmkAGPVrtdG5cFKUm5JmeSrV9oIdcRN9U41rznohFWfXcBGAKopoOutYQeaOMF1PuDUxHKZiOFt4aMro5AoSMglwyBBbGGQenXV2sA+M21QnTUBeEEMqU8dCPM0cS8EGjab2LF7OtzcXs6LVsAiSpnnKk7CQbrGr4SqXS7WdZJzfv36jQgTY1mmWjXn7I5oGlLqUqqW9/vDsK0SICFWVSYetpuyZCJxM2IZ0qaLw/EyfvXlN7/73VenEYIYLFpuymCWOqvZbAI49ERff/nt6eP9F798ftjuz5vbOr//OOd5yUQY+v6w326GXZ30zavj6Vxhl+22gEIIwqBSFy3oEiPA2Z19qfOUL9lwWca+9k9u9i+e3H5Lr/KSL/MExeIZjHmZeQkhpCUv/bAqKajWZcm1IGcACNHy0tD/YA4zLwU1EwO5aC1jCH2XBqYAKJo0UFBmjiFFrvcfT2rW9WmrJcQAkLmGsNaOAEDEpdRKxga3KsxOFHOZeLpcLuSeYpDYReFIXFTncczzDIf1PbkG4e2wSUFKitDCoC7FTYqD9N67IFStecmeVWJws1//1a8V/m/+63/zL/7oX/6HX//NN+9fL+fxfDqfzhcCUgoxyuWSj8fz+/dHCSKBslrR+ubj++kyBnEhDuIvnj6tNR8222e3dyKBo1hd6rJs+mS1q251AaMwkarXpbJQF9N+uxOkLvS7m6deoWXaDrvnT56fs335+ve4R7jtPbnm0mTAVbVRebHmmv/EdrZ+pp9ilHa1+tb18CHud91OVkOivdjQT7bIQziwWWa0xl+a+jwHIiYlW+ExIgCpiwYDwaDFXFpwIgYAyuamwrLdbGA8XYrWnEupxYq6VfiOh02/2W5Lmd0rR8pql+VsRDm7ViwLhHWeLuLYDn3gaKVYziQUQczBiSnWCA8SJYSqlVXLUl6P9ywIESlit8P+5k5EVJUFatW9sjC5aa21TBhh2UkBlk0XnfPldPr6qzLOx8Pd/sXL282h+/bbV6/ffDgdL60az5VIobyKXYgwYqhFzdRLsb5PIcRU1QmpT12/iUP/D7/9x8ZUdvfQ4eZ2P2zJeC5LJkK/jdt9HwNKntTysAmbbXd7u7u73e62/d/+5j+K47PDyydD5CQe4KxmjY4KRTVT91JtgavFzqEFuVS95IuncDrOb+9fz+XkVMlz4blKbkHlzWbfb3sKNuezKoZNijFtN9tpm6cy/GJzcKpmvixlWXIuBcIiUnSJXdgfNkVzKWdYBTcdRVKzXHKpizd0lJlYSDgmGTZ2OIwhFHd8eD8S4eXLm8PNECLvdikmnubL+XzU+mHoAjOShMikZSnL4m4SJUYGcdWmbEhBJEUWAUidRE2K2em4vPl2/P0/fnjz7Xy634hJL3lx226GLqVSC1C02rfffT1sYz+8rFYcmiJ1XZrPU11g1WFEIKYQQrSVHuQQUCSJFFNf1G32lRAcQNTQ+ODiVsjIhQCDKURazWN0XYI7A8s0kyMojh9Olw93v/ri9jJ9qFWIIMJqpDVocbdYi9QK6pmFAVOz4+l088S2h/327B+PR1Iep7NZZtcoLCHE1AVqBlOYl2yKXKp5fvHyIBw3+9vNZl9qPR1P9/cnLBMdYpBQrUnvCkDmru5VMZesZSFyXeZlqW5bIgliJOTgMZ+zXpwLd0ahVjI4iwR1Za/CSZiN/brmkDX9QFIHCVYnmYVESAKTObxVQHFmYZGEqGpRfNsNY5oXr3OtWuxv//bvvvjsi8Owj7GT2IM1pb6L6ctXX/3db//j+Xze7e/KMs1TBYcUpaoKaNPH/abPG5suuYWqfa5wiSnVosASoDVCGVO2+9ORxLtNZEYupS7qRmVSRyPF0BpjZlu0aq0GRIE5aoUpQKjLyBwAUxM2UcttoRWKAq7VUIDqzWAjT07R1M85h92u327m+VLU0iBf/OLzN6/eq+L923J+zzoKV1W3eZk0OwzEkRTIpaUsMJjM3LNXhYNEiJyMjWolJZSATliMQhfjJePV15hPHCUIrE+BUpyqXubFoc+evgQFczdrEiuBCEmGbR/IA6PL2bWSmZFQjIEDmDWFmGJfk2023WFfyFWYoRTZa9ZSYTO6npgDczifJ6Bst7u7u05CVEcxz8csQptNDyYJ5OxkYrDLbMcTmDH0JuyqmqL0m8G9gYOtPmiBlsiUQr/E4WiXaKHv02bT7W/3+/2WmLRm5eIQkcxkqrqM56Pb5TzWihSRt4gcRIQJQ5ec6HQ5SqC8VAhMHFaKq4sJ2FTnOkpIAKNgjb1jrcDn7jkvRBa5K7WmbsPSXEYXBGZydXaWFSZoIIaTe5NI0mra1CEa1YCImFalXiYGWW1uZSuf9Mhl/KfaI8QKD8iPX8EXRku+IXL/ROH6kWsPAn9Pp6CZA/6jAx4yGR+TcX5iUI84Xw9e+fchqdUsAYyI8Oj3P5Brv56S1nGufoZ//8xXFIO+j+98uhy/Uq9wde0fGAXAIxbVY9oQPSx1194aVrambj6c60d4xurL2/cv5Hu/+Ik7+shBvCYufv/OirD7VSy9zVXjrHyvr0du5vewpMa4wA/QwWt+Z+v108PU8pEYpOsj/Oha2rPVRuGPq4oBDyLu145+8vr/v0BJP27/JID1gDT9p7Guf84JHovG/6dP/OP2Ce1z/8EnD59fb9WnfzzgVo9RrYfDf3wtIkKr6pI3kpeqNv2sxz9sp9DHDwY/ep8fPT7tEw6cYgRQS621sEgMwQWqVmutteJRluj1TSZmCLHB1RXttWlOfgRHImFnV7cAYWEHmbrCQ4oM9grNaqV4Aw4Y13xKb6aMAyBOHTcDxNSsmpK5m6sXbxylVhKDYwgILVvO3KFaoeZBalvP1bGqgZuS0ZptJ0xMzFa8NmzHzNW8aRBerLJWKSRMARKEBGrqLb+EQSs6ZA+vqhvcDMYoCqNekoQQY8i1wFYlY5Jrzt41h1Qk1FpKyVrqVHToN24OM9MWj3e419pKBZI3+VFia3BUsYJictU6N20KsgBatKRJtINJYqBGeSB2dzVtTLMVw4QzMa8VYeFNln/N+AOtiT+gVrbQsWJG1MQSudTFWhpeW/HWAgKkBmsSE4wrZ9XNtbq7GRGZm4XrMeCWq9liCG2nIKdG09UGNhKuABYRkyCsP1p1rJxJKIQmb399glYoDOwPUOP17WqRelqz24mIUEt1ppTikktZSiAmZQ7qCnKQUExpWi4soEAOr6YRIOZ+6Jz8919/lTY+jici2u3u+mHLCKfjh/Nx9Owo2D+7Kcu8LFmLuYGFGTxs0pMnt4767eu3h11H7B8/Ht2NGQ7kkiHcx257uAXZUpd5Hi+XcV6m2IlEzFOeynQz7J49edGlXou9/u7t73777ZIxxM6NIWGaSmJmgbi4wMxQ6nKel2n5+OZ1Xs6/+KOXz17cymz3X73JuXQpHnaHYejG6fLzX/7scLi5uTldjktV5MXIgmd3DmWs3dDdPktxw2paSiGm7Vaq1zkvBttshmcvngzDZp6W8/ny7t370or9QDbbTX51Io67w67vt5cxO06TLz7rksEL3vL9/tDz7S6mkGIX42wVdcY0KZFuhhIkTeMyTXPOpRR1A3NoyWbf/P7b7b4jkr7bEHOZ83gpwuHMS0meUmBOIfZKVU3dmElAYk7LXN18WbLggupD13VdJyGEFETYzYa+sxqYsOm6FNLm9snPf/YzKyWXpU5lnmZT4/UVka4fYpc+fPj44d2HYbO9e/rs5ubJs2efvbs/f/3q9V//+jd5/trKVLOVhTc7khBYxEGl6jjNLohd9/7D+3E8WclDl7abQRikFlk2w2bTDduh91LqUsjRx+QsxjQXdeXFyxD6Xdp+fveZ/z+0vU2zLEmSJXRU1cz8IyLux3svs6oys6q6qruanhZEEDYwyCDsQQQEYcW/ZMkCRGaBgPQw0AuYQWboz6rKqsz3ee+NG+EfZqaqLMzjvptZmd3VPYMvXsaN9HA3N3c3Uzt69JxSu9Dv0q7bjSx6fbgNof/yb//qf/if/6dXf9DlELNXJKHVrG6vCVETjnsWMj3Tt/BLJvR5+Pi009Ns4S0K/sZE+PTfj5EXAa3Q0C5cgaaE0c7kjb9FTtJMbBuc3sjgzhIiJxKuprkWg5l4o3hqtXxep2lpMwVAqDg/nGMKw65311zU1Zkkxl5hQQZhR6TALCRWlIxCDNJLoQBWuDburBiIeRwGCenheCyT5dU9UiKp2axajBiKm6JWJS5mlgIva5Y6CeLVbty9TF3ZH99NtdSqCvNcUG2p/nW1OUQCtB/o5csxeP/23T2TmFmpFeQCihRiDDFGczM1Fokxdl0IMUgQkDg5EeYpk0cI3DCXHAijYwgy9OnqaiC2XPPjo+13wSwz6TjGw77rEq/z+Xw+pt3hfHw8Lsvd6aH4xNnYcOgOgmgEc5YQO4mHbg+Ge83FuUpd7d39+/7FdYVyJ8ypqE7n9bTemSyvXr0YhjGlCDbVYoaqriSSUkwxROFFb14l9TWvZZqcRKOSM6lqAyOnyXPJ5/PxNM8UaEgjsZRal2md1nnOGHbSjYHDuN/HFEO5kevr8ng8l6IP94vq/OLF2PUhl2VdixOzlH4kq+nVJ9fLvIRAVvNaZrWVhUQ4puBohcUKwn7fsbB5tYqsvBKixF+/+errX09f/s1pPvvQvTzsX6VQp2WSIPvD2HXhdD4+nt5/+ZtjiM5czqfHGJiIa3Eokbl4AAnUtdRWGA7bFCe3daY5HFp9WpdJa551Pa/EEjqWjjmiC9HJ1D1FCSGWUpi4SwlmgOdc+6Fby/r29YcXt1fxPxpj6JgrAFdACcbrauvsudjx4TxGvbnu61ruH06Pj9MPv/ijq+v96aR39x9y8buHo5WFrCaRfZ8EwqmPqd9R7AaDU60Yd4U5ptgNu4M7v3v3fl1mmIlElkAikWUYd13XAaSqptqMFUspXZQ+pS5GITY1cwiTw8dhfHl7W9yu9wcJpLkwJRIqpVj1IYYQI7NUdSNSK7mW1UoVI+GSjwQWksQxsTAnZiZtozWFEFoMqrWwUJDYdd1Alt36efnt669++PJH6OAwIbnaX42xr17NitZcdB1k33Vx8PCY81omkeH6ag8PZvy+zpUbVOcFVQKooxijCwYWZpnmJZfl7nSkuAZJaezGQ5yozGcggNnRdKlZERqSYE2wqwVwFyEK1CoEcgrExCyKbehkBDhsqcjOEsgZDrJomda1cBxBvJbshOvb7rMvPvvZH/3h//LP/0Wg8Xyu50e3EtZZSzFrqQeAACHmmFyVnahF7db0wmmelyZyw4GIHNWtFjETllJUK9DhMO524/A46cPpTq378LBmoxiHXHRZ6unBSvV1nst6H5hca5BAFO/fz+/eLHl1EoQkwx6hQ+p8XTSv+vh4NKNht9+NA9MoPpai9/eP03Sel4mlwn2ezjOqm8eAEAEqaylLKUrnfhiHYc+RDLWoMkXvI4eVRB2o6vNcTCs5utgNfYKNpazwDIdrDUyHccQN+SR1NS1VZzrntdwrCRyaayYphxe8v06pExLvhr5L8BEwK8XdOJsRUexCjBHmh8PV2U4oi9ZaSjWDiIQQrXiu2a12aQhAXtaSnRMTxFkjBXKYkwQh6VhoU4hyMBETE8jUL1rkzbnLoVx03cq9DBRIOtlqCdVKLVWVBBJSmRYAptjUdRnuRL9LT/mmFtW2umNuCwm6YBKEhl5tvsNPgM63fwh2sqcSwufolQMNYLsU47XhEhcY4/uX8A0naen7j0ymZw0gwGFw2XZ4CnM2V8GPl+gblwpmjalFTxm9ZwjShaXyMRDaVKCaj6vZBvYQhSBQbbYxW969MaK2IphLF3/z8jbwCNtJLlJXW2mRXxgq31MgeGnSR5Whj7jKFqptlJMLze57kC9cII7LAb/zLM9RDndvAu1b77a2XiCRb6Epm7LF5YaDmZqexmXvSyLVt1v8EWPZbssmhUQb9ev32p4YPM+37wSIvqUH/31b+F1jwt/98H3b8x3oYmVIRDFGAOu6Pjcm+Hu33wV6n3/zDcD1WQuft7+Jv9FFvv13298O2BTYVLffNgKXsHDAk1Q8nu4ctvfz6bzPQa2G3hI3hztyghObuTnYm/dEO0tTTaJWFdKMCSVIlFC1fqyVrY33hSRBonhghboV4qYTpKZGIEopUHAmYQPzmmd3ZyYWODdnJ3e4uqtq3/VWzTedAnBkOJNRLbp1HZMLRAjiIHOvBCUzJ9dSCEROpt7saRtpKqQQiN2ahRN040fBzDcfLAcgKIbqHpw8qLmzoRoiiZA7cRAJ4uzmzfl2A4xJzBdTlAqJEtPQFzVk52aqI6HrIzmVWhpiz5DAAg6qZFpDIDPXug0Ml3toevHscCboRRHMAYIAgSUl8aocpfW2WtVqMICYIE0ZkEIk5g0dEnIyp1Z+3p4qXMb67TV1b9WYTZ0RbgRq96g2YhiEmLzOFcDFBFPAAFOFQ2C+ZSNaJXSbW7wdiQEmmJNAmNDEwRxtscrcJK7I1F1ruHTFNlGRO4Eie9Pe3zppY5s1qXpH8zLbCHxMIAJvUxyh0nbVaLbyBmmYr0WJWmsXREsxhfScz02nkgOHLiQtmSKcTbH5MILK9YBF59dvPlzfXs3TCsea5z/+xR/cf3h8+HB/ujuWqWIBgmlV42rkRHDVGHjo5DAkSHr3Af0QTPHu/gzCOHAITMTBKktHjKJWal1rXeuKFTGTCJel5Ak//vRWICXrdFzffP3+eK/DGIioaO363k+TGps2zQIKJk7k1cglhv7r37wrU/mD/+Dzl4dX+qrenz/kXOdhJtJSzwXx6mXoD1fTY358WO/eTeSkhmKGAVcv969+cAu293dvP9w9vvzsZloWKIv0TvL2zRtXj52EbqDkUz6WYy2W12qutSrMqbgPgQ8343E6ho5ldS9mhKXUrqhWS12MsUsx1qyruxqtqz8cT+aa66KoEkkCSoFE4kh5rafTlBIHSVoZCPNc5jky8Xl67Lr04y8+3x0Gc5mWidzPj8fudheQNDsLwYMZLWtVPdeiLDENsYtxPIym5maBuYuxT12SsN/td+PIwDxNj/enN+/eBImlatU6DLvr4ZZjTH1/e/NCDfcf7nfj7keff/6jz774wQ8/vd7vvvzy069fv3777t2H+4dxHF69vLm52ZvX1+9ez9Ox34/7w37JN7nmRXMaR4hkM53O8zyPKd0crvqY1mV1u9XqMOqkQx+nqIUtxu56PFyPV0PYqeWXV5+8Gn60G2+Oeky7VzPSX3799T//sz8jjwLah2DEpXjlSmAGrFZv/hcMGH0jieZPycDtTzzNNtQiMtsCi8a1dDzlRD9GRaRP5YN08aYxaqcENlFXMdMtuSlgawYcXB4rRUgUYSHAcqkKpVq8uoAEANZllprgQTTUWp+m2hzXaZm9+aiqWjUlMGzou6Hv8rJ4RTf0KQZlFZYksdRKbq7ExXvpWlU+TC0XKJCxzjWGWEoBiXOE1DJjFoqJzQLgpMg2w413dHMdLcxf/OLq/F7nqnqs61IpIjDlySPLWfJDOqZdGHYxjAZgrtGUy1q8uAIcIZEkkURhjg4T5hBjChEuqpSzllrVDWzjfsfJionM1szJ8krjrhuGVMq0zIsWDH2333Gfut2QmH09nbUU1dwfDkPXl7q8ffdmlhTMGE6veOiG03nqu2GuFGO/63YAptOpDz0j53yq5QHUOdYYQxqvV+3Py1qK5zyjc8xDAAAgAElEQVSva+77sVYr2bQsZm4KIgnBFFQ9V3vMGbkuy7Iuay4116oKX9c6r5MzneYHAMu6nOfZgdxpiLFWf1zz4wk5wyhx2g3dXroQkrl2gftlXojt9hWZx27HxdapPAjEbHB4dQJjd+iZa6kl1zXXFWQBZNCqXNTrqjGlcRxCtFKWZYJr73Xw2gXu//z//LfnRxzvmnrkcnN96HdDWo2IxjEFkVyZJ6+qb9/95hd/+OPIMVBfC5ZJrXRQI0QCOVVgNXMKFJLXjC5BLB7Gg7E/nk7TtJYFllEWIIMD+Snvb3cdxRhhsGmahQdGYIpWtc4aY3RVFECAwm/ezl/8KKPG692LWs5HkFmB1cqhljU7F/dVy1JdTdSwrq5FX79+e3P7CZGt69E01KXWXF01BZ76Wqpc77nvhEVA7I4uhq7vNVc3lbJ2sYtXY8y7D76A+xRjSiGldLjq+2QxVKHCVEOMUOScYeG6H2+62126Zq2oJS/T3f3xpz/9yQ+ud04UROBeaCWQEGcvsKpqEohIJLCbaylmYAmRQMTvlodGJ+9DHLvO0pAohsBmgJMEU2dVW3zJS067nUaQxBTGUfMfpJ8meDTthG099f1gtpjrYd//k3/yh//jn/1LuZ3GmzEQZHZ6VBglFhjXjCDXvYTz+THXwj1irLt9JZdl0S4FgF/cHh6PsiWe1ZGk26VpXTPp4TY15AEgZmku8vO8WFlZOIiYVmvLOUbqk3Co6iWXUgo0MosQXE21whUBTpVJOAqpqhqHqlhE8lpOh2v89A9+9uqHXxzP9f/51fuR3muN4sktac62goPIJfMqJJuckmopxck2sySWsgLsxE5Na4zAElwrCEueWn1G6oOJPi6Px3mZp3qeI4f9YffJ/d38cF/v78uyIsXTMp+at/bV1Uu4/c2Xr3/7NWwFAnZ7fGJ93zPNVc45dqkUHvp9lCSQJJw6CcFrwW7siGIp07Q85hWlgsATbF7eP85QBwUcDoLgYWACm5qCJAxdj9ifY85NJ6uU6oaoRixdFFAJZVWrn+5HociMWjLUGF7XevxwzMeCCkSAEQQVQMBnuktyuHpxJeLrefnix5+/fXcfUoXHdakf7o7zbEyy20ns083NFVXMD7Or7rv98f7EEjkMIJAxrHjL9zh5NbAQkxNg6NNw9ekND3ReJ66wtdpUfXHzasqe3dQskIkhkCSy5l3rMHPw5tEd0QweW6qoOAOBODZmI2/sIIc3XQ9ngNkBZ26Wex+1wh2XpBeF4A6YwQhbVZ2KkwOb93rDNFqszls6jAAjaHPgewpDtsXFRQ6kBSHm7s6NHO4fc256cTn7CB4RnjCNrc7xWbUj+YYNCQG86dK0bBqeAVDUxDYv2JS34Mmxub6j6QhRc89y983zEU1uBdyMIBsPh4zQQOfGeYPDWvC0MdZo68ym476t9VvE9SSg75vxV5MDat44Fz2Hy2U/YWfNgs83/S08YWEb24k+dpKjLQyb5lnjwXwH8OPYvCcv+MVlSfk7e259DGADM5s97HMGFdzRkJnL+vryMyMjsD+VN26Pw4aIXfgIm4j79svWXd+AffCsZb8f0vP785kaXLOxcr7nV+E7gaHfc/s+rtY/Wgn+OyGn79ztiTj21PtP1oR/96lVN2vIpzvnF1Li5eDP9v7mLfmO5j1Bw2qZLpwbInfUBoa12kMmV/cGPbiZQwAXxvanPdEfQWBpMDQ1ZQ6izUnP3KzdUbRaOwETBQkWiBBEwDBykBu1ql0YSEmVzc0d1pyPQR/1y53MWJhhVOCtlPoC7TjYbHtD1FEdbVRmgATEntWqUysyNCe9QDbNzhSkpPAKJSeDk7MBIKa2MnNv5YcwNEeqzba9jQJNmCyEwBJi7NSy17ZrdUogb7T8TSy4jSAgEa61qJXLt99YE26kjosesrVLMXe95CwcIN1up+klt9Dsfd1a2oUIjQTGjiBOTcsSH9/rJ+bEBfXEJcfg7k3wRuGAbpWALM7+hPM3bMrRbuVFnfBpRGo4+7YUbjwVCIFbatlaVmPzRcRGxFBmYgfMIU31CoCbu3Cwp1SDE7G3kY2EeLsQ33SjCdtNJRATSEpWQJwcBiNDcCfzy5hoZlEC4LU4R34a1tkZiijR4ZWqY7t3bjBWozqrd9nn7FYcKO7yeHws84Kq+yhV9OF07+Sh43HoEsdgTG5CblXhNnYhhVhMOWCp8Mn6HrsxjrvxxYub4+k0L/N5mbIWJTK3vGhwdIGY3I3O56WXw3xe5/MCgkjz5YVZ5WAw1U1TjMhaCRKraZAQjY4Pp3df3b/iw6ub67xO07w8fDgRd6HT33z1ty9fXe/6/e7AIh3cH2T57fkMACOuXva3n+6XZdaHPAPdGCtMlCSGeSlv3rxtAu4k4m6pD6MyB3LytZzhqG7LulKY+iGpVg4UOg7VmNB1IYTEEpjEOYgk5pVFJTgUa1lTcYmUmLWaRDjQOB1zXfeRJbAbcjbTukxeM0ngafZ5WX7wAz9IH+LAU4X5fNaxt9VrEMRBNmU7ZlBwDtXBjkikIGJyZw7CMaohmy1rTcm7lEIaxhFv7t+N42jmtaoSdmVJTCIyjKNICiEQi6uj+qvrFy//46s/+cXPf/mrX/6rf/Ov/vVf/l+/+KOfff7Fj65udo/T43l6uL+/u4K9+OTlYX+1znOMMh72ClpzdS0o6yzBVK+vDpFFV6+rVzWKwuDkXY+q7NG65P3Y7WMnr64/eTV+ehhe+hK5292t+dcfPrx5PC51iXHsOCjUg2SrZMxKBnVTu3i2Po0LAED+TEP0W7NMexvhzW/VW7aMn3bzyyCzfbiAVU+DTzO23+Kmp5wZtZHMyYjgulh0FiFxcbVccmHlhNBx6AMCDFZLZe9i6HjgPE8lV2vjgaB4Ta4hSMedqwYYOwu14sBkXtZz5l4IwV3cRatqEWbkPHfeEUuwEIX72JHIQhkMDoyZSw0sUkotq9V17XsldhEnxFIIxMIW0jzlOR5KKEVOJQWsJ7BR5Ni5LKfsPr/69NWLmxvvytv711+/+XC42etKa1AubEBIHAI3V0ESuIMZIcBdy1rPpzrNORcHuwQPpVxd9/tDN45xLRnutejjfcnLksuZGcMAonK1v9qNKTCWaV7PMxwpxi6m4K5LLiVnouz5w3Kfpv7g+7d370WSOW5vX10FIqN1mfueKVAIfrjuzQtR4UAUE6nDkyPN0/zhw0PJMKXUnUyRUmpFcMPQdV3ixPsUp/lD0byuJZey1pJzrqY512mdSbhW4yClqBkUqMsaTN1pUZsKhmHgdCvpNnWjdKI2LWc/nx+XZaq6mtdK+XE6/uiLH7345Hqtq5o9PJ5PSxYvVYshW0tekbFAAhGjaHVFCKlLI1PIyzTNJc8p0KDr7nin6zy9eQ0yMIECFSxrfpQoaouqm2dmXtezsPcda60xdYzAFi37fHJXmHGQGPoE5IVWpULFnSocL65vb64Pt1f7RZd1La6TVWgFm7gwe6jZdKHmWr3OJ61CIazVYVRW9zWHfSIlys1kDFDMj/XtV+9/8tnPHF/evzfwCgJCW7EBiUPXVZ8f55wIIlwWmx5P19c3gVW4lsXWM2ohgpRI1V06I8nFEEMkhxC7qxctywo1iXMaxpHlh4duzy/OShxiSrEf0jj0UUxsFSpDJ8PQ5aUuxIFkjFdjuOnooMjmqxYrU0jYM3dwkJHCwT1RZUIgZxbhBBKCCIKTd2IkyQXGpuKVrLi6VS0ZXBxrH7sh9E4gEYIbSGEImvMCpBUFQcZuB6auIj+ee6Z9DKxLRIqcinqI+PTw6kefYeV5WlYadvur2O/7vKDMVtecglzfvBxDnHeSy1zKGewxlVpKH9F3WNcyDF3kfs4159oEB2OXul1/JUsXO1XX6uYEIhYGJCUyc2JjYhcOrEYIAkitptXMyBFDsF44wFVtdVeKLagyBrSqM4euY5PA56UACb/4+R/98Z/+6byu//Jf/LkZThnQOoRmD5EUVSi0dTdDmtgr2NXMNxMpoJV+GLE7mTO1+AvMpE0wl2uLw+d8Ok75cV1cOoq7aL36UHW0akAv4TGoSwDQMQdJTKFXY3XEDplwvYu76/FwNYZEjqXovGa/v7NhMPI5Twu79TGNQ7ra96mL4z5pSa/fnU9nWzOIjElJqB98WbFkPJxUec5GJGTkMUVETxL7XW9h9qpmsIqygEMkZhb0PXeDOHToDmWhvMyPH07T/fr4YdGFUQkZaLYikBCEqJa1nt5lwuyWwkAP5/Mf3vxw6DQGA+R4POOuGlDdVFVYiKjvu07CudZdLyJJZNDCmol4dJocDAdxiAwAVR2EMQ3X1zfd0FuwUKOt2RbzudrsaiCFF3eDJ0JyFghHDlbduBKc2UCsZM7qQkQg28SzzL3lUEDYVCwvCxXaksvbMoJaYQq767aQ2KZz34CRsC2FzcmF3Bo+Y80dq8URDWBgAj89WwChGdY/3y5FQRvWRo7NiXf739vKY4sxWr57izgIdFnh8FO80VAwcrUWkKBpKeOCc7VzXuhXfIldWiPb9TZxcQIMRsTmF41Q2TTIm7EQk4OoURIaFEZoi0k3YoJudKpv4RyX1eq2yGFunux0UYGhJ53rj11EvhWKfuw2vtgtAvKs+u55x16obu3qG3DROCvfKOX6uH1L/f3jPfie7Ztksm9ylp4YT98DjGyUqKcuwXZHnxG7vnFy/65rbAf6vuZ9s6nf3Ybv2/+JsfV90FD4fc76d2y/Cxi5u6r+4wCs33N73olPHf0t4tjv8rkAEKhJu23v9+ZG2gicjZz18bqeH+3v2trTZgY2iDCTExM28hUAIg5ETaXpaUhw2/wpG7OnObO6G1MUJpDXquZu5E5ea2Vm2UrzSdfsUPbIDsBCCMwkwkWLqYLQxIlYWAD1i/UgORpCoa52oZ+yOxlY1MyLurg1ghEDQAhR1fRiNEPMQZhjJxC418YAKQZ7IgVtw6xxYHMxMrA33rcCsQ3R5oALmMhJrQHXzk1EYetywM2q1+oSKHQhGSTbuUHkdZ2JWK2pPlhtrFFVQER4Xdetl5/dtzZob5pczI2pV6vXNZuaqXEjNTRwy1Thpq0TiAIxA0QiTpGaGz3YNvPXjYbEl+jj6cFpYv5PlmGNKIwn2pcReJPeuzRU2lDqaraN6k8PJF0uo9G50BB/g3lMzM5uBrUWPDbQ2pXcIWYN/thYeUbc1rfuZhZF2Lcsy8YfA9OTKjRdKh9ZiJoSll+opChmrGjOjhSIhU3g7goo0HpZVdWNhBFBCoUWL6TEKaivTgb2VrKpBFdPKSbi8+NpXQwZwZf7Dx/evX4zn05l1cTc93GpGlIY0rAPYxShomXJeVnvytFQQ9fnYk409F09rWtGirTbXX/+2U9+/JPP/tc/+9/meZnm2cmpCwBqhRv2fRf6WrIh24nm48OpFIWjZG1hJTOlrvNSPJuaQxt/m5uRQik1pc7Mfvmr3y519/nPXr188Sk/PEzr8Xy2XXM7ktD3KQzjzVX3+We7yP0yl3fv356n48tXtxLrw+MxJn1xixhpGDpCWNdyf/fu/evT5dYjRoz7PnVpdxgP14P5OM2/GcZAxOfzqWpy964bCBakCIcQQt/3QaJwcBQRDkFEauoQIsywLvn6Zh9CmOeViAAuxZZ5BeH6arffj1opZ12rGmrV6jCoV8X9/X03BBBERF2r4nQ+zyt1nYBdawlCA4/7/W6327HIeVrv33w9L7Mwvbi63Q2DEOtarGrfpdvD9fXhipitlGU5Obs71iXPS+Ygh/21G8XA4zjEGE0hhDLPj9P0eDpJoF/87A//i//8n70Ybl9PX90f73/71W/e/uZ1nfIn16/6oT/fPcLsendzNV4zYZ3zUmsfJHJPEEBi6Pb9FVsfjUwNHJKE6y6EqyEvGlyGdPj8Bz/b9eNhPOz5et/dcuy8l7/49S//4i//5jytKs7FmINITB0FiqZuGeRu1bilLPwpWdnGf97w5u/cnqAtdyIyN7oErd/cLrnUb8909pTzu2QAt5xmIyiTN5IFw8ndTM3c4BDI2A1pTMa61NUZQYUBCqwiJrUlNPu+DxwIEkIXCaJWrbKpVpXIV4erTrq7u/uvfv1uY6wwoEABHByw9McQAwcadl0fx9h1TB1CcJfdnkJMpapWcVNHrWoMkhiJ4/7qJZFWLe8+3BNbjKnfD69+ONZMy3E+vjvlNXchXb3qzeovf/Xr9+fffPKjFzevrj794au3v37QzuMgfa2AgwIRiwjH4G7LWmrJBtNi66LH81rOGQoISgBVDEMV2o9jGiyZKjEf9ikmOA2HK+oHv7lKuzEFVq2lFgAhdeNhv3OpMvQUI3IRo9mKlJJh3MXDy5t5zporOATqifnVy0N06in13fUV2UO1eLi2EJzlvExd3H1mPzhOX8AthDjPkxmKl7xW1YWFcg67fT8MXepCrtUdLA2sxlprVc3m6uRGWV2awQl3Ztpcj8FcFQB+9Zt5GPLVMd/cXndDNJSavSpS1w3dIIHU87gb3r1/f3//fi1gRnUE4X6/K2UxrYEcgQMTsackMUqtykJDN0oI87xO81Iy2JNaPN7lL3/5/quvlzIhRqRIiZM4n6eZmczr+TSpIXFgIQkSmIzWvNR5LtNUlrOfz6vnDA6HfT8Ou6HfP8rjuk51mgFgj5vrm+vrvQjrPNdVtaBkoALmofEcnaZpFvbx0H14Nw/7wdXyeQYxSilqGnsWsuJzriSA493X9//H//7n/+V/90+XMn395SMIiBj6vnp1JpaUxmTI57nGXRjHRHUVUvE69Cykx7uaS7bKxDF1IWuUWIFF19KlKCzRic3zPAVQF1Jws2U2Cbs+3VzfvDkVl5gi9yl0KYp7yRWlHobxMO7OOlHfH4bdq6ubQz8I2I3cpQv91f4mYnBjswpCCBRjAMyhUbpAIclBIEbkzqG9e+wKy17MymF3Va241ghKLJEZasUWJhaPmyaxWxIJHM1Ml0pdGNOwO/Tzh6NBIkmXUpc6Aj+u93/xV3/7/nT30z/5+X/9X/03v/rw9f/729/89sObwONhOKyuD9PkpaJStlPXyeHmOsabtSzn00NRy1X7uO/78e7uHIL0noqXtRRzQDR28UrGvQ33H07FalF1I5bAoRehxGQk5g5SZu9SN/QdGMtSci5MCH1I0sV60Ox5ndVAJClEabpHjvm81KywXEoNFG5f6H/6T/+z8TB+9evXf/nXf/nVb1/XCVgA9bUriNJobuyNqGNeFSIi4mpaqxVtar5mMKvg4C05udUJBSVXmAQmAiW8eAXqdK1O6GLYWepzDctcprsPaRzCGHc+DppDCCLBQeZcVBUYdvsXwQhh3O1TFym4s6rStOg05WWhZT3OU50fgIzQr4nhwNWIzz//4ic//tFPfvyTL77Qx/Pp/d3D/cNDH9PLYcxVT/P5y1/dz3kNDysxKOKwv/LeeeivD8PNTcjrOedqGsrKmkPJhUjGcd+P+xDo/kNd13L//vHuw1om9Ah930HYi5elwImZhNmYCmGey/Hrh1qsv+WlLF/95i0H7rrRjay6FQQPQuQGUjs+HEU4dcP5/rFqTmPsY7fcLeta+v0hNw1QWIzc9Ba9VBiurm5e3Lx68/hWuTrbuixlLnk1FJgWMrPVGsWZmxCMS5ROo1FVRyV3r1Xzaqam1MRWhKJQraalFPmIW13m/BaEN0bVM7QFTzwXRxPUvQA+1r5srJ4nl5iLeCbRpSLqSb3mY1Hg9udHec5WPgjHVmXRvv7diKPxy2hT1AFArQylHZ0am+2Cy7TVdSviviA9H68K34vJtJ5xs20BsqUArTHUAIAVADGYtvJlXPZ7toiEmzf+GYhaM8Bw+xg00YVowMyt2AjPlvy/i2x865vfB7N5Ytt8B0zz3fjVPxjl+Xsb8Bwt+e59vv/n30J4iMjtO9r3j2zcP2T7zm75dwKwvhO9agAWvgdC+veyPZGt8M2r+r4n7+MOcN48CpyImLjpX7Sj0bMn6unSnuDJ7z4sAc2g8vJLAugiY08bH5iZNwbMdoBW+2reXu5Ga241qSKBiI3VoGYXQXezxqAECK5ezUEG3ewXm3KUkWpVU+cLqM3NZazJPgHkUCMlgtfqJHiCYMC+SbipN8vBdiUcxAE2UyYQgkhKKUhwMyvGRqRkFb45Wz1VuDDMrCgJN9AaFUhoyuJWt1ridlVP/hpPpgMAOSmcoKhaiUgkBoFJhGstVdUBBVGIkYit2kXizt0hLGwbbH5hcH7kIjZkrzGx4BVo0l7bztaOLE34HmgCBNKUs1xCU9IHoO5O3nhjbXQwuIMEcDf/OII/59q2B/DpIp9Q7jbCXuSliNqyF6EN27TVYxNRs4L8CLN6gyVlK/PcvOvBxMxi5qYVLswugd3IvNXzsjtgTI0Y17A0EG3GJt7AXLRS+i1t0zwUdZtwHUDj67mZt05pvPeLNr87kbsvedVqJAiJ62quWg1WLYWotOGkFBC70CfiQIFDF+N5WqHb6mKdlvl08mps7KZeaHd9MDhWzMu6FNO1aK1EUKskfvPJrRU4WeQ+BbDXvtt1aYyhi7F/OD6wxBSTQuHkQYQoOIG468fD/np9zPd3x7sPR0JIsaq6WSWJRNIMtJ+mfwLMVYs6XNVEUogxqb9+e65U/+RP/zim/v4xreWuVuuGtCxzLdmqCA231z+kwdVnDquEcl4+hMpOy9XVmFJkeCCo2bpM03GFUZQAQKsWtUVK7LhP3fX19TBEJ41Jcl6PpyO41lpTRAwxjKlL3bIs7aGoWpuHCQtSH1LnDp/OZkBK3A0R8JQiczifllrLGCABIRIzdZ2AaF1XsALeDZyrnafT6bEbhk5SkJR2uy6mUGtd1rXrQm2lGSlxkND1Xq1UX1Y9nZYUY92j1X+qk7pxrnPJXa1dlygG6ZIHuHmFruspHaOZBUkxpHnG+eTsvNvth3HPLF4tlzyfzu9fv89XS9+n6+Fq99Phix9+/ubdm9e//epxPnl2OLEKC7nadC4MUEh9NySmGMa+u7q+euEPIXpkNkiglIZAV6OpkiBe724+efnZEIeeE9UAxzhcTVi//urNX//N35iaOqgoizGJkHBkJTNVtjbF1As/yj9O9HRRXrDvmvyfRTZb8cGz6O8bg8jTv5dQ9eNg03bepqHtoO2FVvOh6wDAUItCQMKBPXAgkFWvZOScQiRIWUuZFis5sMRAyj4Mo8JLVtJFiVnN1LJWIlKYJOllSD5FnYsa2cbm3/wfFj4vChRO0MwhDOMhhBD7lHLVYT+GLi3zejquyzKXtbSkbuyQTvjTP/0TZpvn0939uq7rMCDF1F8NupoIa7XTwzTnfH7MANKIWmnNpVYbJITkBFcyErTB21zVq5aqqst6rtVoFbJQMlQLhCAt74vDAcR1zffEKaU07oYu9cNuEHHienMThbNrmabFLXtVMwppF1KvJB/evb252d8eroYQURRrnau+uX/gOHRpsMKn07He3Z/Ozhp+/OoH5/OCcoaTAkctp1KqsAHnebLswxgCrtcyB2kODM47ELtacazuWbUcH2c86lozwcFkRBDhEAXUil0M8Do7B2JiOIqCzYjgAnKw3b7YEUVQNy221HUt5+mU796ftOq47w/XY+wYRH2XQkgPjzkGcADDrBSzSIQUgkQyg0NjpBQ4CplREDa1shSqUZCgw3Syd6+n92/X+YjdQMxgD3BppZYA3KGKda3Zqwj1fRTxXHB/d7p/f3p8mFw7qMAEaiVrrbYZMAEIJFFub/dm9vj4aF4ep+n4cFpWoAIFKFahIuIgrLDkVhwreE+mhlzBhGqo8GpEggoroA4AHu4e/+9//fDf/vf/LIiLeAioTl1qdhFe1RzknKquufp16tJOrnZdH3k/hLHbVT2tK0yNxV3IK88FafVoWZyq56VqH0IKaUgpcYiMwCKEmte1lKKD1uImXYgMrjnnaULOqR+SKYCu717d3tyOu176ACayJIIhDtIJgriaGhhkEkTMrVoREuEk6MiFgVrVAQRhgqG6eik1SCQm4dixJOFEBFXNmdydrIoxcSSBxF7ckIILnNmZDHWpEbHOdaV801+f8vmv/+avf/3ll+9PHyasf/Kf/Ic35ewZy6n4/PDwPtdMeanLlOuCJT/s98Mn/c1+OFCg01lLXbWaxZ4FqRO4rWWe8nlRZSejIkzESsxzXlRRK8w9UE4UjKBuIQEsatUdEsARxOhIKJopmvPPbuiXcy11AbsQhRRjEDhqKbELpazlVJDw2Y9f/PznP7k9vHj97u0v//bLr96+QUmouUUyRlZNXZ2cXPXidUQu6iyqZrXSZoe21X65wpnY+KKdzIArWQhkqiHhi5/cvPjRrURQ6Kvn43k9Pi7n2Vb1T7pPjDX0AuqaMGstmosZREKX9mk49BJ6OKnXapnZwQ5CUewOY85uWpsRWSAJJDXXx3v/ZXmYpu7Vq1evPn05DLux4n6aH6f1NFcJEdJDgIqaAQcSMpfFkcj6fuxStBpWz24qxEXLdJ66HIUHCYEQ3rx+rUUeH9cyIzCu9odAfT6Vru9V3ZeqTvDiyfshDmM4LXNdrGYC4te/edsN/ThojAmVe+4XaF2rUVXQ+fFxlwYOQET2YsYuxoHAlVhDIC3mrkECCbUaFARICqb1w9t3RhZ30ddaSoFugIe3pZsBBq+oZGGtItuaylqeV70UU4dKiRSCCLM0OwR29qbi7v5dKNGzQICeLRyeUKgWSBBwKfTyZ2uCZx+cmP1b8YXztpoAAS16b5V+5G5E0r4E7IlQgItv4Mf8WxuXn8o82kKLLwoj3Kz/DNYCH7fnqFg75DNi0zdCFsZTPdIWBRkkNBupC5PJmeDwS/nbpQIGBGa2Jwiv1b60/tnW8q3VeBKkpied9G93Ey6EkydCzLc6+O/ZPqIHzzCsf9Bvn2+/L5BCaNjL9pPnl/otTOM7f72Fiam4okcAACAASURBVPSNVtCztWo7IFN7xL/Z6N+rgf8u27dwtPbh3xsD66lrngCs//+2vwvU/Pu25jzo7ptil318whqViy6eBLRVjj2zA/hO5JEvCPD2Jl8YYe1VZmK+gNUfkW8ADcDyTXGXAzO5g5m9xfrPTrhxp8xJndVxqVauqlorNWCiDUGNUINqEGY2KI/J2UlBF20Ug0swZtKmWsXu0mCLi5gdtZ2bABSHEMgdTqEZLTtXNVewMhub6Tasb487EwsRmVYRYuaqzZiQowgRilfTVsrtbuZMDUeHy7MBykgJZlXdgT4KM2KMzAx4WZoGpjMzM6Fexng3cxpjZ99Eyp/D3E2WDETY5AUAAqPlKtwULu0FFtCFMyWwZo4okQP8YrqzSUa5XyQOqVnZEpFbK8fDM9zqMiZf5KmZCA2RuqB3RO1YTXUdBmJmdhZhgzMzyZZLsQZHtplMvVGEW27GtqcKbm7VASM0ngXMXZgbeuhO7gS9IDJNt7bRPWSbrQzWSvPZP9KcN+Le1oWNDdYkt5moqUuamYEZ7usyA0QRsY+qqyvM1UypgjswU5PI77o07PsYghtFSeQrORBxtT8MXdeF1HVdFdWcOQR4WtZ1mbItFVWbqoAENrgk1wWxT9nN1boU+mTC4fFx+frr9yxyd7/eXEnsEqEWzW7cxdhJ9KIise8PWJcPD8vr1x8ip6vDVVVa1rKUMp8nFjdT4IK7tWJcIsC12rqWjlgC04r3v13Xn9fd1VVM3YeTCuXb2xfExd0Wq/N6luN7syUlTn3NWqb5DiQGGoYhhLAummI3n/V8nEoBQ4J0zFQkl5qt0mp1OZdaLF6l/bgD2bostVQQckYKlZiFJISY84lAAjdnIgM4BGEmCQIYaFYFiTJbPzBzgjORs4DZm62Qg2PnMUWzPq95zdZ3TAKzopqZO+lS1/WqL1lwejzlUhQuMTYQNldb1rLOy+N8XlbLFXC/P55Pj0tstD7XJKECRb3vusC0H2MDfqRjJ3Myg5pVM5we5+lxjiERvAtdINl1vQBayunD/fzw8OOf/iSfV4fv49i9+vy2O6ylLLXeP9x/uLs7LSd1DehYmDzO5zLV6hZe3HJKBwPFmCSJDF0YuhCjkzAnQYzcH/obcnYIgdeqFCUXff31+3/7V/9mWQsNoVbDWsQ8BHZvbndGDBFS5aZM9ZQx+MZk4PjW3P+NRMrzOacJztE3d3+GXm1jHT1X2nLAm54OyLaAbTOfYNVaizqZB0hiEKnaMmUsa2WVKGGIMNW8zOeVHX3vUQITYKSmWetcldS5upsRc5fivMyURZh1Nq+Olr0AKBIBtdpVfztPc86LZT2Wpda7/nTuDqlYnvPS7zt3rjo7KhMH2cJ+FkTm92/ux11XzbXCDTlr1YXIrHg3dC8+u+l3Kc9ZVGqtd3l+OGqlB+5otx/B6lyIKgtadryq5dpq5M0BEXJ4qWUtbvDQxZRiSgDlm5cioQw99aP0vcRAIVBsote21AWICvFa85onK5UpRKF5ne3+fJqXvuvoOsV+dNI5T2tZj+8epsy3Vy9roQ8PM1tJvnaevnj10zWX5TS7oTrenI5vjw/nUtSxzDOD94f9vKzTdH7x4vpwtRt3abfrDtd9jE5ScjkdH98dj+dpOT8ua0sqUAhgVodDnAOCu/lSjc2IuRo5B0kDiFQd7DFJmYNZqIufpqnYuiynXGpeoQqVWTrs4+DsWjXn6orh/yPuzXYtWZLssGVm7h4RezhTDjdv3VvF7mqSJTbVfJAAUe/6EAECpO+QAH2HAEES9KifICAS0NDg2F2NLjZ5646ZefKcPcTg7mamB4998tyhCk2qKQUSB5k7T0R4xI5wN1u21rLtcH29S13qopTlbRep62LXBzOqmpkQAzGFWrwupRStuZDuocP50d99O37329Ppg7PBK7QtpKwhSJJA7lVro67U6lrda5aIseDw4XR4OM6jx8BMIWy6vMy12jiOcCzzVLXELm336ebm5nw+q2ZizEueziYGZhiRwsnJSiFmImWmPOfUg8zXXvXV4ARmVzPAFTCwkZnn0fIM1xyl9h2GhHHxWrNSNfCc8zhL2AbhOGYfvGzY90PqBNjE1y/vpin86Z8+gMHmyqgEGp2scKjo4Wbs6Pfdbn/Nbrrk4hRDYqH5fL4/nE9+tVQfOia/SUKkilLELKhG1SiS+v6T3dWu2woSwaW9t3DuezJmC+ytdskwuLNrAEfyBARyYeeiS+vlYmYVqrVardO4gL0L4rH5VBiZSVM8q5kZS5QoQtJxIu43YaPGtPgyLy93Lzzn08PjOZ/p9rUV/e2XX/3bL3+zubl++/brN+8/Dcy/+uUv9tfX94/jN989ui6Jk8Qum1YdSSbiniRSXSrOWTFPqPYYuxCSmHmu5TxrLkjRG3iRLdfqm12s1Usx00afh0GdNKYggc7neSkwWooXEWZhJzeYatE639y+ork6F2MVAOwQaK7jeBYOsZPYp08//eRnb17f3dy9/fL+i99+ff/+scOueqEKJriQVSqlMkCOJhdYDS6YnGrrr00Ebo2O2dSoWvMYFbd1kje4RHapbpq2ePPzN2nbP5w+nGc7jvnd/fnx6MUIQcZyLr54MBYHvCwlm2VT1JCEJZIwudeqmkvROseOU6LYh77m/X5/OsyjLIjKALOoRtNQq43LMp/fnz/4eMLmhaOTV69fHw/j8XhS8xjDdjeoWS3FzEQogGCac8mLAkE1m+ZSiMxrreepzPNsWsdRiHganUHkAlJhqtXUMhGnLtVS57kWraUChqHvJETYZBVWqaiNY57POqU69JsU+/1wQ3p+eDxSJhq8al4Kh4Gu7nrLdjrmrBMSY5DsRdjNq5MjuJIaGSLv9lsQHh4fp+MIh4iQkzWaAoPBUFJyZm7mMKq2oLKLCauamkLNqnpFs8Qi1hBAYe08LkTF68d07Wklb72Q1ijzo4E5NbPZ7wFYF5sBahkMVkFHA6dozSsBUPP0oJWJRYYLe4qISNZctRXsubmWNCqS/YghREwXetdl/3YxTfjYACxasykAKy2MmwjwiS6+ip8uh38Kd9pFMYjI3M1c2iCchKhR0wAnJxeQs5k3nzAng9tF9rGyt9ZE9tnwm5LPL4jOmue3lA3PzLR/KOH6PoD1I7L7791+cJBnLI3/UJt/LIheAk36HobV/u4/CDrX/35CrxrS5+2z7wsTLxjWD877Ewjgf5BtfaovVdn/twysj1/7M4Tsx4y1v1lF4Q9wq+f/bEP6PSZczzHIJ/StkaSeo6QNW3b/XouCnziiO9RWoLfhXE0naLYelhju2oa0EsfATM9YeLRSbYiBi933KoXmRhASDnCCupuLk4iwhGqoVFrXV+f2qAHtENrglDa+1qChXQ+BHeLSNa0jSi4gILQnW1Y4pkmLhWspTCzMHLnpDdy8qmpRq+bVyYiUoH5xF2SQMISJMy1JIgeGWTYTR2ThQF5MTZkIlRyOwITm03Zp2+pUtJLB1b20MqaBOUaRwCArRaFggnrVpllu87XDHSFGM5jpkx//2pv1ewikswiEgomvJS53d7ROjiIEuFMrmaGZIBGE7bJ4eHNyb3TUdfK3p+kYQLNjfKpb0Eq0uOD+aEQluJG5exAhrBLCJjeCW/MgJIIEJm9oFq8L11ORAWS5ShBmCUQEKl7dyMytrgUEotYU0T9Si73ROi429o6LzNSbZeh6q6xVMZyp9SThJ8IciIwv98LNzEhb60RSMxASMwFZNYikLjFxLaWotTNWq70kStSQCRHZbXdkfjwf2ZkNrth28Wq77WIMIWyGrYmWEGPqJicuqtOcx4q6GjZmNQrghAeML950Dl6WEvsuRlnm+fDwfj5PIOQRpSscmYSJ2eBucKZakeHjealZLdPxHrsru74eWL1UR9FalkCyNneU1nLWBdKYbhTM3fOSWYiZlPyLv/r2k5+9evHm5hc3f1RxAE3uSmTC5K7jdAbV67T1UKVzXbJWIo8aCiOmkDabGz+P0wldiLVYdhMmNbhxhbn7dFoOj0dhO5/HmKTW2h4YYTCHtlabYhxH0wRTRwiRiTkECSGkLqpW96JqjlwVXd+nmFSdpd9sB2KDT8xeraYUhuGq7wZX/+79o5OZQ4QkAOSGKoGG3cCEeZ5zdSfE2NVa1HyaFlM+nc/jPFY34g4c7h9OyzwPXdoOQ5+ChLSo+jgW1b4PyVGqCQslihJDJxI5CkO15HlZzq71fJBIsev326HfDF3JOedcasnj8vjdh8Px0KWw2W732+3Lq00YhuP5dP/w4eHweDwdHg+PuSzCWOalFrMigiHJbnuz3YRN2qTYB4qBOYBYwabQDEJrvkAhdCUXAtR8OpW33y3dRphC0brULMU1ElMwVzNjIhIWUa0fp+fLDNAi1CcC6PcWtAsT3n2tnrh/xL+e/d5ae/y4nK1n+MFCtXL813plC3jzUtyttnJng70AgqE4BVAUhxcUhgAUIzSjZndUD4Q5GxOBS6k+LVgAQpdiNZuWZT7lYRjKVMRFWKpWmAUE4UAo7D1VIzhBreTxcZ7mee8D977UbLZU06xj0WrmLk4dsXCTg3z51be3L65CZHWWMFStOY/VJ3J70b/c7DdpYFQXEje9GadxmiqWaS737x9jEvfF15Y5rlTggKIUZ0bXM1Fzbq4FDiB2fHWz2e9TSnZ7xyK56zx1TIR5znlZpvGY86w6Sdh0HYVkMZGZLrnWWoHCxEJ4+fJNDOl0ttPxOJ/nZZyXKY+Hw9V2/OwNWeXHhxMpdT7vaQBvqs7TTACK2bTg/f14WqYQkxYnqGl9+/b44eH9+Wh3L3S3729uNYTA+7Ad+hitaj9OTNlzye3BktD6xUUTz3Mp5rnUh/PS8BoQxxT7fnC3otUcHLvf/Mu3Qx8lxMYnkBhjCs4Lqjuhas21zPMEeEpytbPtlkJwWHX18zjxNobQD0NyR54VZEIGh1W3alYcla2k8cRvvzy+/fb8+E51BgXMrTNa1BgDmWdWJ626aDWCEFSrZ8MgBHVVqBJc3MSNRAKLOprgz9SMhLo+pRRDkPu3j+Zlv79mBGlVHWYnInKGeKlhkBhil7ppHF+9fPlwOC5LATkqiKhL0auXXLyCicm49bQBEMk2fbjex+EDphlLPjsZM5NwUXMIp62Xcj6dUo8YXHVOsfvZp69evPz0H/3v/6RLIDclzVYrZSqEVEpFYN50XUWci+dpytPYS/A9D12fleZsH8bDtOim423X+24biTnEKNIzb5g222Ho0nUMEbKalxM7KtwCMxyh8evJm4bY3QAhEqAhJszMQcTgasVQQRVugZi92ZpxhIg5aXVTNgvCzT+YvVIVgotJh34jQwWRScnl9u6q0MyDqReDifB2u33x6uX2bvfh9Hh//56H7vNPXr/+5PW7x8er3TfffftuPGfehxA3BUPxnDpIyMHrdhdZKrETjLi0vtjE3hJvIziZkStM3WIfWCHRq8LNzd1MHd4FJmF1aAW4dZWxlg3XimpARfVFbTFkp2JECnitWlQLNNRPXr18+eLly7sXVOyLv/ryz3/9r+Zcd8Pe4efDDIfEyCK1as01SAgibgYnacm9ujb1gINlNW03g1drNc01/1j7PhnEKxbE+vrz609/8cms5d1vvzr5eDrr8VwOZ7ggklIkChQ5NLCerZKzELMQdxzca8nTlJcll1Jr1V7ZkUg8Jg7CIpx6DsyRUh51mTMyt6D0PD2cl4evp6/vHrubl/HV61cvXl91Qzodx1J1OyRtwK9XCTwMFMWAeZqKmiShoesCOUxgtMxqSkup07wss5KnLkiQru9roLAsiy7zfrgaNj0TUYMTq1n1kus4USlIoQ8sj4/n+YwsesZ4lrzb7zf9ppMB9TgdZiHa7a9qWYjl5vWVLnZ6967UhUPkHrpMLOKiJPCgZq5cJcTN1VZdH+8ficSLRotO2qRzLMRgl5YshCBBVWu1spQo0aMbUJsdkzmw9tlzY3eGr2yntSsLPpavVpUFc2spf+kH+LTer53AL77f9Gw3NKatO63FZkET17WopSUMq33TUwByCQaeRQ7NLr5Niqta5un0dHG8esZUWA3U17I6E8mTS+4T/wkflY3PXbc+EjqIvpenN50JIOSNztY4HsRmTtw6LbY0hCHr6K11i7yAGrJqRS737qm9lq9F9+fR0co++F690J9+fp8lswZjf83tOXT178qz+ffg5Tzb+SNh6ulQ7qsDxcfP7SdO8QOTCr88YmtLymeAyQ/Rlaen9T/k9hy6+psBsAA0O6Ef6Ph+P1Htb2r7ftSOC4PKn2DO5+LPp615YD3dgsbmlSjMTAT3Fc0A8eUquJkNAU/v/rPrWl/Ty/Pv3rhnrX+lr8mHV62BuOLStZKY4QojukBfTS3mZCuG3uz+FEQwFxaoublXJ6YogWN0M+RLrtLc1RlmWIXDDaFguDZAuwGn3tDTwMJBSDUrgYwkrBiS6fo+MxFzXUrsEgsTiRFQoao2qxczdTZAnYwa0kEkDCYwQ4goSIoxNld1KKhCEIKIVnWzS92v9aRtOwINlyGg+Nq7z9BuCRFxpABSU9ACgJhKUVu/MFxqI+uKASdvSeT6XT/xZhuiDGISJkdgc7i3plgsIGYOgQiqFaWunCOHE4wKSBxOQkwEWSdgNQioXpBvR/vaW6LqzyeFhkq2t8VbJMWr+G59gq0xmM2pFTZAxM2/mXhl+jXeFz1NtRVgYZFm9EzWOFhYc164uzfO+oqSO4FWaJaIGM1hvRk3NpPTjy9U63V2IeXaZb0DiMTF3AzmBqhD3A1Nidpa5LCIqZJw6IKEMI7nlui2ooqEQIF8ycgodYkSXX08jV3ftcRSSAhel7pMeRchFCig77aD9FyDns0ctWTNYFldTpUxP2r4rI/M94cTOIbQLXMdH5fIgZ3gqFqlhiihC111q1pQi1dkK+/fPQSLBIHCnbX6stRlKUwsw9ZtBlGjCboC1Y0cZtW163siWpZRq3OH7ab79s/vxzx//vlnf+uXb+b64c/+8v9YdKo6W/VadZMCJHKEOCXEPg/jKee5uHmKkkL/8uZ1vr/HDNnGrgvmUrR4bUFDMhQHlqkc+DSO4/a6D9KIUBtU2e52pqzFAMyLMtUgHFVCBEMgnnrabNKyWFVx53kuXnS7HfpBlrmEkGLs3HUai2qdpzmEISUWSdt97M+YZuQFmy0RW87nXD0EqbUyeyklV9/4SvupakuuZnPOdZrKXPIwbBDldMqnU7YrdP0gse+3myhCMAQOXafQqjkidiE5ULw4aUz9Mi7qNcXA5ON4nM55GK5evnq52237zRabLRO//ebbh3fvT4cDE5+H03J1tdnv93f86vbVZ29+Pk3z199+/W9++28eHh9iCHzFpuVmf3V3+8kQdzfxdhP7NAQXqNeK4g5Xmk7LMtsmbLu4ZeJEqbgxeOh2fT+Asd9fzV6sQLWamlsUgXnrVxVFRKniKST6OBsQ/SgMeLaQ8VPAZP5E+P/p7fvr4Mc49bLDpUtOO8qKYVHJi0jriNUULo4CJw9MKXSxS0amRd1rDCHtNvNxnM6OrNTDpcTdpk+xUBgLrCxkYBcqKFOlSqFjhawl4pYdrw6JfHx/rItST12/KeBqky8oU5FgdUGpM4HHacwZ0Fbyhao3G6Kuiw4h4hASM/JZx9kpOjGqFKXZg/d96lOfUuzSJyCczuf379796y+++Y//+FNzATec3tnBBjKUAnZ0ZE55Ljj5WgGaaPlkc/Pi5fVuz2/ebFQP7pNbXfJSl8N4MnXEyJstbzbRvEzzVBXMMGCaoarXV+n65vYf/P3/5HA4vn339uuvvn7//pBnJSc2Zwmc7kqpuRTLakpElsK1Y8r5BKLiFtOOqItRbq5vAwuZh7Cbz/3jh6UsaTx6Xs6lFBYqNYXUh7DSOJioelNAO9QiEFjMqToVYFI9TzCrEgFgB95so5mq1eIuJMcRwpa4he9IfUg9BVDNC7FLagllTSnudlsfjJnH02mc5hgARxcVhBjYW1sZYzOrS62zuXdCQWCl9MuBPrwtp0etGShwhVfwwIFT4GiGeZpVF0c1hzBcm3AETA5Gl/oU+8wGsNUyT9WshBCIEYi71LMgRgJQark/lCjYbUhEmILA1JpLKRyO6szYdENK8eF4/4e//IPHDwcsxpFMnQKiBCuWc4FBYiAjU2MR5RoiNj1tttJ3YAbYjBC6uNkNsSeO3G8Gz3M+nc0hASWPqeOb62HXffrd6Z+8uUIQc9NSoDN3zJ0wsnVd7MMwFjwe7rUsrLWPySUWF1OYpPN0PJ8nzaG8eEEkXSALsWfvhTcx3W63QwxJKNui5sIiFIgDOUIQrRVMwgSGopa6AODAoBZMtW4/kroItaU4w5w8BoLJ4BtmjsKRiE295lqqkHcSYhAzqFbVwm5cg0A6pMhCJM51fpjI7fXtC+m48d7ffPaadv7+8cNxfD88bH0M3dC9ePF60w+kvJzO+XTa7/ZvPv9EJb8/vBvHkWgOie5uNvWa9udSCsUUx3NRrc5VWgdVAthFKMbAQg/3J6bQbEnNXWs1NTOLKQn5ogCQOu63vbsueZkr0CxQO5R6zjYXm1oanFWh0GX1OH31+tUvfvHz0+H0zdfffPjuQ6DB8/k0TiT84ubu7df3ISSRoDajlFaM9MY0YmdzMzNf62JrAVfNqmtBGHDJOhlu6pXIQGY2Y4eXn19/8ouXFfrV2+9oMHdRpzk7GEoGNnJQAAubmTFxoD7EGLrNZpi5zNMynov7ZA4t0GBwSRJjv2e3yNjvhl66nof7d4/35REBtSISnFAdVZfvvp0eZvQD3nzys+3mukt8/+F+mqbISAHMJMFCzMzu5rXUwLXb7EOItYK8y4OHkPLiJfv5vOSiOlZsApNs+m4zDPVcHusx19JtUuyCpNbiWiGopnU0VAybbT90798eUCoxecGcK3TavLjqJe767enxbFWvrq7u799mq7dXt25AeFdyplQlRluKBSAYmE1cS4FAQ6FIxerp8djt+7mMwaU2V1y71KiJwM6RiZnM4ObNQDPIR3IKMQkHYTial/xTdtbUeT8GAZiIee3AshKTvNEjcMk/n+/zMaIgWuvHzWnTWqpw0RM1x92nfT4Sadaw4PuFMaILcaKVy9uMAADNI6z9ckNJGteBCCTkTI2y4e6tFu58Kd8DH1Gty9mfXcLHz56GQ43Y0X5ffQXgPkIYlwyrpU2ES+5CT4yhSxwqALk7/8jL6WP2frE7fi7tekISnvNyVih5ZUOs4/xd3JwfKAd/jIf8e9N6fg/AIrImwa3JVPtQVen724Wd8BGg9DXN/ek48wdX8cOB/0hQ+JMbff8r+HfdngJdvlwaEZHI2nr26aY8XfZPg21/Q9vvgree36knItXTqH7XkH4SNSOiEEKMUUTMLOecc6YA/3HNG7g4IYG4kaTi5UQkwimlEML5fIa7url9PJdV/Z3fHuHptWRtzT4vqDatLffQcUwxxLROI8JOMK+5ZmhpE8TualdzqblaUXIIRQ6MtPZnRzUzM1WtRuSpG0JKzshLmcs4vNhULVbVq5lCWvs6hhmEQ+gSmKopkxCxQyvUYAZrfmGmGjkIRStq1TvuUXA+HgnkZ1sZoyTSrHqZiUWCiMg0Hs1KNQvCEjmmSIGJYW5Zc67aIHwE4hS6PoHh7urVzEIMVt2Ko4KJAwcmN6rCJCExUS01L7mWWtU9rw0FSZBCsIxLYPBUvQAIIQgRtfmXmUOKLCwsVlVrdTWHqZle8JeQYuyiR1Oq5pWEu75nYXctWszNG1PpArxZDgRmxsUnfq0umBWtVc0bytJ4DjEEDuJ0abYol+f7giyTomatqu6rVaE7sTxfHamdJJcqCETwtTvBCstqqXAnEmI202ZzwClwEBA7wZlqmdtKweTsLmATd6GqFQTuhAnq5uSQteXHE71jiBsmQiAPZqIVtbHrazU4JFIjsoUgRLBiV9trofj49qHkQsIVutsPHnHy03/+D/8zN5vP89t3b7/67VuwXd10P//sF/vtLo/Lv/zn/3Lb7T98fUwSxg/1F3//Dzb99vDd4asvv0DBbrM5PY6cGMHNnXsYY7japP3muJzvrq/zPB0Oj30f715fbfbbb7770thuX16HTk7jeZrm282tmz3cP/7dz391fH/84jdf5QO6Xra7fTXMSzEyjqS6uJoVh4KVAyI5GsO/lBkiKcVaqyTf3+3effsBCf/pP/wHf/DHnx2mbzmNHw7fZJ2EZV7KdC5EUGBe4MDPP73e73cP744P94fjAX/yx39SMr/9q+Of/8VvkMLN9kUpCndJ4vBpOtZ53uy77orvXuze3b+9vu7VbS45dJKkP53GafZdt7m7e/Hrf/YFCNTh7jbe3m67PoCWfoAEZqa7u7v7+w/LMhNRzjWGvu+3cI6xu7291TLNy/zwcDifJpE49Lv2vhxPp2+/fTf0Yb/fp9SJdEsuuSxRmIXG8/n+w+nTT+6OxyOc95urEOTh4XgYz86dm6YYNpt+nM4Mv9pv+i5uhu76an9zs08hzPkUUIQtStz1+5v99Yvb2223pUK2aJ7mv/hXv4YjcFKL2+31i5vb6+vrT16/fvPmzc3u6v7Dh+++/fabr7+ZxkmCJIkUUuq3nEK/2Xz+859JimB6PBy++Oq3v/n1X5xOp+v9/pe//OUf/eIP+bFebbfbXU+ih+nh7dtvpnlO3Xa3vQ08bPsXN/sXgXpHBMUpl//hf/kf/6f/7X99OJ0elnO/22UrrXUJs4REJKhetSgcIQQmYac6VzODwo2psa8Asx/K7deFwAFAhJ+qLI5L1Chrja02+vOlY2grhEhgAA6vpTbQ+XuxKdCaqjLc9BKPR3AChDiys6tbGlKuGY7Ndhi6rpOgc57HaSllAV5//jMlX2qdxrGeZlSFIiC4mY4Wtrzd7/b7fcnl8XjIhwWBtlcbJwLb6AAAIABJREFUZpweT1yvg3TGJevkPiMBCekKN2+23T6CnAKccHpYjse5ziBGTAlEJZeuS5tN13XRvFZbRIgHoU60lrJMQ9eRNjU8dWm42V8LJwfFGPsuDF2JgQDPNZfavI1FHaVoVQcCUyAEli50m67bmFotC3wKkruhpK4G0VqWaZo1W2Nan06n8zj1G2w2ePX6xc3N7nQ+3b8/pLC5urqNcXAN//gf/bOuG8ZlmiYwIwoRaDqiZtsk/Nf/5X/zf//jPz18ePyTP/qP/viXf/vF9rpOc5nyNM3nZdLIX759d398vNpfffLq9fhw+O7tkWS33W33V5vD8e2r13vD9OXXvzacc31PYby52W62ac6jdXI6j6fzmTht91eFeJyX94/jkrOBjEKpXtXvrq9is7Gfl+NxOh7rMuF8gjuZibuFSLt9N+xS6P14PqrZ9fVwfbXrU3K38/n8/v2hZDADhmXCH/+9bS7nly9uf/Hz17Hzd999eX48l4wk/X77cjnR4XF5/935/rv0zW/zF395hnO/3bpSPpycLGw59YlItLoqQJWl1MVVEVKA1xd3t7urvu/TMtb3bx8/vDuhDBI6lZngzI1n4u7Wd6nfdKfz45SzEDaD3L247tLmdJrfffsujwCQKMI5xli1Dn1KXaw2726uzsfT+4cjVTiwiX0fO0CWeZmXWd0ga3UKs/+3//N/sfjhL3/z+H/+s1/fH3Eo4ITrO3z6s35/hf2Aq123EX+V9DbQZht2u32/2Q3D7cAv/68/+zf/9J9/+af/9N254OXPrnb7Xc1T9LLfbFOUTepe3Fy/uruznM+Hx3yeNl1/d3t7c33V9/04Wmju6nWO5K+v+m2Q3v3lzX6fUgIHOJwfz2rUMbgWG2K/GbZE3EvvKIsv4zLOeaqeIUhdZGJXJKRN2gRIKaW5hhtXRVEUBT9MtBm2Ae5eAlmCMhReaq2RyR0556omvJO459QBnUEUDrMeYlaYSTk/1kMl/erx628P3xSt/bav7L/9+uu/+u1fjou9+OTVr371D0Lq//VfffEv/sWvf/vV/Hf+REKfUurV/DQup+OUK9RRKmtxtZCzzbNPC0olVTcjVc0zphklg4AgEkJy53nMWiz18eb2Zr/fOWyapmme1Eo3xP1+T+JLybVmdp4ezttuOx/18fDowPV2fz7nN69ff/7Z513q33717t/+9t/ef/OIE0KivuvzXPOpAIh9XPUYRowLcwHWXi1c6t7cag7e1IVwgA0GkPT9duNuyzQ6q6RgVJxt/zoeqfx3//1/dZy/eTi+/c23/7SgLEUMqSiNy3I4l7/z9z4Zx4PZ1PVDCPF0nMZzKRmmuL4arm/uTofx/dsPdaHNJt3c3gjLfJ6Op8M4KSuEY+QQKAhJkgTyWhZ1Vc1KLpEkkCR30mmy0xkiePPm5Wef/XxeRrV8Ph8Op4e8aNdj6JgIy2Ix4Pb2JsUu56JKS9YP76fD43J8xHgClnWB2g6bvuvyvHTUHR6OferJ4NW9AkAM0YF5Warr/mobh3SextPDsZU8iQkGn136+Oknn8Q+vPvw7fFx+uxXd2FI1bKr3Vxdi3XfffH+/uv7MrtYWJELc9XKEq5vrvb7q/k8f/v1N10/WNEy5defvtpf7fK0HA6HZSxazKp5hS1KEoMIhIVls9vyEDNqrWV6/8Gzcgi+qFdPvWyurkG81LxohbsdpycBBHw1K4cTW6MwEVaHEQOZoiWPWBsRtuDA13ZLq2Wxf3TCMnKHETMJIEyNnOBqIJHUyvRrQq3Nj61ZMjf5hxPBXJ1B/GSffEmwm6CFKEgIzAhk4g0pA1qtylkkpSSgZZmtajPEyufSoC6mQA0HWtUxcHP2Sz+1NWmT1QkODJCrEojtaRgfUZfmGL9m4i0DIhBIsHrYK4xWP3g0FiOaSdl6NnJ3WpOz5wga4aL4ew5gXW5as9JmgLx6KcXdyOU5Y+YJjmiRRvuklPID3OOJ/fM8//s9Fkwtu3wCQ9ruz2VwHJ4TetYLdDfge/JPfgZvPW0hBDOrVW0VkLWIcr2T7UQrF+KytZIHEflPDfk5mtSG+vwTfN/N/Hdtz7lsz4+8jvnpl37wH/9/bc9Ruh/85Qlo+7GU9CeH/XTH8fRw46lB0/f2JSJndzRnost9b8pgNzPUWp8eF3d3MyL64YF+8mrWS3peQW+gLYOcuBm4yyVpcVJrHCIBKQeQQaDVVNdHxx3cMppq7eDRwEQSo5C5OwxeFcLCHKWzbADYpT2FLIBDrTZbIzNzkJsrGRgOc/K1PSqRiJCDmdvMAYeZujrUwQTGOn3YBa83A7u51Vrbgy/c+M8ws8ZpaNIZuvw6sUPdrDHAjSl4Iymxs8DR6hVrjcPBgKpz0x4yQhQrpN5MuBhKus5dxG5NL91QZWrtX6CN+NU0ncZqzc3XfNW3rxUDhrFVVyZQYPJATO1hcLtYxDvTk/ynNbm/ZJ5mBjBxI6uvfKunqoETWgIE+ig1fVaJcHdCq6T7SqRztBqPrlLNi+jSiSJHJm7Q2GV294+0WLbGCGt27Y1eCAYxXVy08ITCt52ZOXD0FmwBJLTK6cWdqZk/ubOZOa/8sRAohKBUqiox3KDmahUGEek2XehCignKXd9ths0wDEaeNrFyjXNYxjnncjyc8lJESIE2h/b9sO23Dhw+nFTBIaZrO9wfl1TyuBCJQ10BgbQ74LW5vjRCXxdja/QJhrlb0TzNWtUI87jQ4nNeaoF1YKGhGySEEGKSPvusaqVoNTMrCvfG518Zae7E5k7eHCMdEGkNTd0JLC6hj9XKu2/vr15t9i+3Yz41AVq1hmgISIThVqfJPnw4uTJTSGkTZJzPWYuYKhysOJ/Oak7wYJGFzA2MEKMw5aU+HhHjQkJqQLW6LMvk8wzRfIyn/jrkuVrFeC5dN6du23Vp2ISYpE10Itz3PRG5ZzevtbiTmR+Pp+3QEQWmAKCUpZQC0NV+PwzxxYtdSmEY+mEY1Mih85JPcyGYmXYdtpuulbe6EExRa11GzHVhBja03crQDV0K223XRMFLmadZfOjguL67JtckYUibkEIpdbaJlHRRmO+urzWXaS65TDQxsauXfuiur683Qy9Efepurq63/UZEBGwuoRua/HiZajnNSym11m28+tt/+Hen86iqwWMe699682kgkFixTKZdJ2ZSlvNJDTXpFh2llFyEwJwt51oJXF0DS63FfX3RQN4sDIku7g9qDq+GZhdILrS+UnJZ2n5UivU1Unxast2fAldvcuSnuMd/sPxdiFsfyVgf1x4BQKvRhq61SgI7kXML49p0mTiBkUvOc7ZqSuKl1lzhFBjLNC9Wq5uQyGbI5xHVmMmJNMJg0zR3qbu6ubp6cbWcp8fTYV5mq84xkFv1qZQZVhCAHt0Gu5uUEpvVarMWU/NqECH0CBJj7IgkhjQMfYgCNi1esmYyVNhsZuYVgRdyM3CM0Sg/jIc81/G01GJw/eUvXsXgIZKTmtfWzMPd1VDVSwbARIEkpW6z3exDkJKncXqYpg+ffX61de6HYO5LrafjWGshQhDsr8KwZdX8+PhQ6xxCev3iTUybmvHdNx8+vD3XJc1nnzIR0zAMZsi5LFnFo5se3uc8grWLNNzsXo7HMXhws7z4eawZBor7ze2237IFQdqkfdreSZBpWkzleMwkpUs7I1Iba615wXYbb67v3p7vRSh2kTlwoo6TEqepzqXk4iQIKQ2pCynWXKtlEmx2nVaquTBDq6vW9uCY5WVZTrOWiq7H0Ie+jzFQKSrB+w2ljoTEDBILRHrZhCRzWXItSylGcKAWjOdqua8lnY/j8b7UM+BAoTqqGbkThFyhxZipCeHhTkwcAEYUyaXWkoU2VnWeTssysQgAsxmoIFd3NUQKfZ9C5Hk+51wYGPqw3+92u+sYO1DMi53pvEw55wJFKSVECmEInZSF3E0vbg/CCCzubq2fDIuqtVFJiHWbzYv5wqF2W6QKAjhhs4u3d7sulYfDY17mn73cGYWMEkzHPEGYJVLqXt7tPv/s5v7D8cvvljwdjigM5y4UGIx0mtSRiwZiLxUWpuoPp6kaUly0YtP3mz72KQ2B+q7rY9gIi4ijCXa41koMCdCqS57yvLj7ZrtbsFQr6pVT6GM/ZpuW82F+3PbbyIngYyZRakStAEY0gxq5A0M/MEKpc11yEsROCFBVKMyZAUaIQozARq6rw6lAGMjTyGSU2NljiBU27IebdD3XIkkAvH51J4Fy1WG33fTMAa9ebn/1q5999vlp8vvQUYjUUP0UOBfLFeZhyX4+ZRDFFOLCuQZTM8WyVLdcq5cMVRC06zAMw9VuZ2YiMYRQS8k5z8tca4lJYohE8Kq6LHMevdZldnE1pmEHOK5vdne38frqzqq+/fD2q6++Ph9HEJBgRtO4uIFTIIcWsK+qgIsnT8svqBVr6eLV8zT785oNggD1kvPirg4lAUeHmAbIUDY9jvnd6KcZ01yW6ijK1aqaCMtu61BPEjlGYdFF86FMR8wzYoBG0qih8nW3p44CR0w+53k6z2VUz3j58jUZMSgwCZEQuxdLkSXkaqd5ckWK6EIf0/aq8w2P41zyYfzA32z3A7Ht+5CkV51CQoyJWUpuDomMpsVgE0E3YMihLJZnq9N6F6yaRw1RUkph4lxzABORwV3JvJiZuXZdl2LHJGJClTx7HFIIscy5WuGC44fj1e3Vzf4u5+8eH48D9RwRe9GgrJp2sr0Zyli9wsznc4Hg9uXN9npv7sfz8eH4iIQQmaLEFGJMt1d3tPcudqd4Hs/zPE1ZCyeyWkopcOZhQDASTzFSwZzEZzVTsIdOYkpMpDAzdb3IXNqfS19yXJpgPbGtnvhLBDxDbX7X9hG9ao+RrwmWA0YEEHMzP2FGcyVxAzU7m2a4fhnHiqC1PS8U7qehtW/KzECupjAwWISIIExACEGCNBESVr/15ktDdBH0fZTyrWSmj1e38sGebsjl89XMh56aWP3E3fgIl7izrd3L1rv4kTX1vfv8cUf/IYzw1Izu6Wdj/7T0raUCrj+BqvyAe/X04e8hA/3kLj/YfhJ1wu9mNvlKlFvZas8crn56u4Ak30NdtPklP52YLl/AR2f39rE8XeMToNb0T79rhH9NatTzM/+YZRV+gIH9GOv6/2xbgaTvqxGfw43PB/bXGaG7q+qTyPEJQb6c7ukLoO/fmvbUs7uzUbMPqrWaWWNyqeqa7dtH2dhPX9Gzn5dtxRBATsTSFOeX797s0q7BwWAnZxEWrrVqYwcZ4FD2NhO28zKFEEIQcZKGc2kFNwviGJdWfmry7QarNHwIq2YSBjj7BeNwJqG1afsFpHs+vTQ09/JPcjiZG63HJFizf0JI1DxDjRSmpZI3pz9hIhYK6uq+ruNmRg3MYiIhh7OTrX58pnB3Uy8uoV2vC4g5xODmHopWdXU0KyfX9WWVy6pARExr+hfXzI8FEBCtwrgQiYguzDo4E4m7uDFToGZ/rG5qhLV4gCd5OZ6Z0/hqsgJ3v3iWeyusYQWS1+Z+pk5kT5Nqg/VWzTecQBxIiKEGp9Xys148Htdro5aGPRUKnijD3i7X/EkS2CBaiLkQmplXq0+s89DatoladUbIHcWzwYXFudUI1woFiKT1sGzfOhoMSyCvqi3qwWXRdVhgiSGVXMtY53EZur6cCiWqIkpqGe++ep+1zqXEwMO2P8/n87k+3B/22/3LuxddHB7miQRZK1xOh+OISUB96Jcy55IDt7CQyGHwFk9TKSFyKYsI96lTW5a8OLtWOCPn6mRFvbH6Q2Dq2wLGzXu0qi/L4oz21pkxyxPSTeTkdqkGGZjEHVBmiKmVXDf9cJ79u2/fpmv5g+GNdKnrBiNVrSE4gQxk4JjqtEzHk0ZZrrZXQ8dLrCUvrhFQCLxq8QkAWKi054IQ0Pcp9YHZYAic0hB8nhsYqwYCSq2n07jfb0cel6m4Q9UIwsxalZk4RjOLITZvNVVa5kIgInGnWuzDdKyqy1zNVrafmRH79c2+6zjn7KilzgC7L265ltkdKfH1btCao6yEci2KalahC5RQQmmd2fsudV0CmZZlmkqIkECBbFnmwBy5OWz5knP1CiVWihKub280lzDO59PoqHMZZcJpOo7zabsM4zI5fBiG7bCNIQq4gpg7kuDsqD6P8zhNxNx13cs3PwdonuYocr294dDVuuR5mvPjOB3zPLqVwGIl16XWuLgqdJ3kliUfT4fz+eBmzDyXTLzS6UEOc4MaX1bx5j6qqxcFY51eCc3ZiX4cVqxFrrVCuOLeHyOwFaYGieBZ7e4y76xs/Ut111cSFvHzEI3ADLXLGkWtzbW1+hACRYPlmmtVZTUw1MmagE+WOc9WWSh1IYTgS85zzqUQYdj1XZ+O43HM5z3tNttt18fFl7Gcweg3Q1gQQwjpJkSWjmhwi0XjwhEV1ayqwxwxpRgFzsSBKbqRhiAxmteaS16W5vFEAtY1Gm6LS2CS6IaSSz2Ny+lkSwY5lj//ejNgs8WwiV0nHBjw0pZyo6wNsnHTRHJM8bFLgbkuZRyng3T5tnY3tJMQlJJSrfDAplB3FIVVEGlKu81m08tumf3h7eN3Xz28fzvnKY1jWar3m9T1nbnX6u6I0onT+DiLx5thuBpuX95++mdf/PPrzY6QSsF4XDZ3t692NyElBmnOtmA1xCScj+NuP7gXKJiiqqhSzn6mpe/77X4zjgcQ4I1bUDlEJhJmVSsFgb1LabvZBqapVjOLIjF2MHHnaVxMQUAM2G54uxGKHuCD22aXbm42XRdUa85LLkuIIn2MMQLUlwzm1G8khnGZtYyl1Bbz1Mpe3bPUmY/3/u67cz7GYFTV61hBaH1KTFVzRSDmKI5qVasxU4ixizEEbLb9bjuoZdPFTZkZ0GqVgwEITCnG1HUhBlOdlxFADJxSiqljDk4SUtruNlbU1JZaYCA2lkDiTqpeHMZCfYqoa8+fWmpZqoRATGROzBCQEBwS4Wqh891+yJTPrmkDcDkejzroMMj1ZthsNtIBJJVsrouOdSk58PnV3R9WfVWKdZv3H47nOU8GEA8hcd8nr6qoSy0KDuCYOJcyf3h4eDhEls2wHYWT0JD4bj/cbl93fRpSEqBaJTMjMXYlU51L1bnM5NLp0LMJxAgFql5LXcYyj2U0r730gUnVUUtVlJyZ2Di6e70wsIbu1iFurNUd5M4AWSUrBG4KFiIOhNgmMgJYSBACs2IOwk5mriAby1nZPDGHwMLCfH1zlfpYqzojiqZkb17tr65C9Xp/uBun8XA6nM7zPCMXd9AQmUPXd2DQaZxrLV2XUsdwqbW5nVVy3XRhmqopolgQI4e6e63TmGuupQX3rgyvkbQ42ImqcFX2Ny+2BO3SMHTbmr1P+y5tXPnh/cO3X719++6DK4IIAtW5ooBZgvw/zL3ZjiRJsiV2REQXM3P3iMilqqu7b/fcmTsEyBeC7/x4AgT4wieCT8MBQd7LXmrJLRZ3W1RVRPig5pGRWVU9fYcDkoZEINLDzNwWNTWRI0fOiVCvWntX044G9OAZ1MHZXUnCoeivlB7X7bkH0CkhFTBiYyZQNcF4wqvvpvxqedo+PG3v758elgIQmmlt7vCY4jQO8+Ms4sSi7mVu5RG2QBqmMB34JtuU2A8HCohu3GqrbkN89fqGmPZpggB2o16Y5QYyUOXD+N0rcfaqm5EP4zHF8ZHnDx+etFh5qHfDMQwSxqBDKFWKzd4MEg5TFInadKtr0yJBEvF0IHhyg6vNsG0paFBr5sxEKbFEanVrHkhJjWCAKshFKIQAkDU3A0lwqikMZFRrFQricn44vz7cHe9uLsvTx/kx3QYW4cyNG4PyQaCTjaYNj0+Pb1+/Ot4c8zSo+8ePn87tSUY+3d1mTrq41lZLef/DT260LstWttqaAxRYQvDSvBlnSYcYBlFWdyN2iWIMwImRYgghAOam1g96z0qwc5AYXS3m1xLJnTjUh8UV1briXs+ZJfVq/Wf7KeqhghHYe0cZEaRrtfuebLh38hWe/4erofu1om870uTPX7vDFIC6mTkBzs69Wa/Lz8Hg5h0KJXZTBBBT14/3Z3LBDpbt3LEXJsren5qu0eedB+HeqWXSewbxGY7yfqS006ncr5XmnpV2uZSe/vMz96rvf/+FPyc3n8kxrTdXvQDaQH5N5qCq8P4c+86Z6C5YP2MVvcQu/jaG9Wt/ernDr/b8FS72PCa+QMR+Gbf6+uvsCpS8YGP0k/M9Su1DYJdX+wyeAHjJwOrf+3xUfYXndjr/zzLfe7mrl5uHX/vD/x+WnQR0BbB6J+ffBjK/Wl5u9cJmYE/b92/B53Mnuj7oHbm+7sTdm+o0jqqNiJq2Dr/8+pTzi0vn6eyJCBERS39g3KHqZsbmpExsfe4jghBvWs2e26+vxut7mR0NykQGEhIHmrp7Y4OEwMLe3Mnp6qZocCYIBd+ROuq6eN4nACZiYu5FedLazNRICJ31xkLBa4WAiZTxkggKOHPfAzqy1TWs3MkcikZEEoRIWIgJ7E3hztYBfm3N2To9yHYVqQ4HuekO6rTui2iNiHpDExwuxE21qZn2phynz/5+V4Cpz8gOwf67wMWdDdZ79Hini5F7FyYT9HWMCJ2CpvvchZ1c0bNE2lvO/WoU2y90J2d557Q592IA8S6nbta3IEJ4nl3cdqf5TuQR7gJf7gB1gK5jhsLEtHcWcmtVYugYFEN290ODBGpm1OdWJicYG4SdHegmaX30OxGRkBALqEuTMdj5M7q104s7OuQdC9vpXG6uTZXATE66uyVeEWFn7zZG2vTyeNkeSz23Nray1HCQNGUEd7L7+V6YHXL3+mY8HRDo8dP54eHh1Zu7t998c3v36v7jEiB1bW7E4FbnKR9iDlq5zJWkZ/I7PQWOrVYyHKfTtszTmNns03mbL6u6looY9xlApDsrNDNx98vl0ppx4K6mb9ZYAgu5OwsMxiASdgBKXRevy6921UpXIyFVu1wu43HKKc3b/ONff+Js/+6/fjvkg6KtyyxCwnGr2pqBJQSUBaUUG5QIMYhZEZBEnRLmJ4f00AaqHUoiZnTX0u7LIiIppCLV3cDU+1xNvZQSQmShceQQJaUsIRL5PJ9548NhUA0OwKnWVrZaShPOzGzmW6mXxwu6IrIiZYkxqNUQeZoyqK3lsswLgCDBjXMAD8HcQpAceFvnGAcCe2umGphiwFrgBm3QZhLcvF++ptpUtRRpLYUknz59GnPy0cgF6lFiQBAElkgSjjcHazqd7ObV1sysOTNTpGLlaTlfzk9amjZLkohIQhAIKBGH5kbGZMwudat1rdH45ngzTCnH/Or0ai1qhlJtXXVZluVyMbccBmvEzllylhwodOSnK/Gv5UKSRYCt09AhvbbuXX3oGjrsTkEkEDjYyJTcenhlV7efL95a1MsEBLhfoXd8EaT4rwYl3dDqSsTsJdA+PXfEbH+dEgAwPXtWG5xAjQC3Ht8ak3KXIGzmUGdHnyFbrSGwhMBMMI3CGEKtzRsQPYyRG1dv5+3si4HgwY83xxhDznE5X2LCcKBhDHEQStbc19bUmrmFwG7GBgkQEUJQpVZbLdaatda01aZVrfQzg4E9gJxFY4wSPAixkKtraU6WMg1jHkNaHx/doE1USQ3WmmrbqhkggpSObm2et7WUojDDOOAwRQkEweN54aScYsqsiDzcDKkJlXU+Py1rrkgB43BM4RAwbTN9eH/+4S/3n96vZcW2eFmhhlXUzysRkSGnYQwpNLRlvcnj29vXr25eDelwflwGHnNMhNCan053w2ka8rDOy/unH9endVk3mVYylLodj69ru5RWVKk1xHAATPVyOdfp0NyKC1M3PbNiGtxZgjDvfjC1tWXdphyYERgEI2jO8vrVablsrZKpD0M+3gzHQ0B0ZXOrMcUUyWxbt+WyzqU2EZKYQg4OokDqTszVrCxbq4uAWIITDBEttS1cLvr0SI+fQLWyM5zRHAwEpi4nTgjgwIEjo2rVCneCerQY5XiYxjGo2nRIl8taNjOr8D1YmqZ4e3uTcrpclvO2EuM4DSEIQOuymT31ckRr1lwhCJk8+HE6mreG1krd6gZGzHFCqFsTkDfbylY2HQgOC8II5ORmFRtuX5/a+eFwk7797dtj43D8cLo7xBHr8i4k+offvjmMMbg5Q4VMWvFatnVeL9bqH775x2+/mcDf3bwaf/r46a8//HT/2Jg1SBmGzJXrVrRiyOMUc+K0WrtctrXWSHL//t00DKdDptPBjznEICESUYM1rdxajjnEoLWu21o29cAxCKIXKyZe0eYyP10eLsu5eg2Zb25vczoKBBuZMdzVA4k4klrb6ra11txBNUUJIfOIBCeQam0V1kiEmAKImIURnvt12D0QM3gImUULNnNV0vcf3+kRq1QjdzKRmHIAp9ZqbbW1JSZLUTiKgofp9ad70bKu54V08wZzNI/iCCHd3eVxpHVtW2MFC6RUTZFjCHmwMR3nZSubkYuhLJdtWZt3pcO6YwcsWFZ0ElMa4zjRgSeG3h3iNtvt8XBzej0/1cf7Wtfl8X754S8fPn54ckeWCJAyOAR3wNm6gLeL+5Vo0ifk/Sd1uaJrgQLoyfVzBkIEIO4VHJCTwtQA4HiD3/z+8OaP3z5u7x+Wnx62tTqEYO6mChAZBZIoAd5s07a1tmDUQ5YkacjDdOIRG+pSulS/VS+Ll021EpwYet4qOdCjdhiZghTkTi1NfLgd0yBACimP8e6QTxwWjXG1jZ2fPmzjMUwnCTE5cqtL0RJHvzl9k9Lw8PhY2zpmRnBtNSjlQfwUieM4Up235bKYm4QOeoLFRaBN1dyNu2VjCsyM2oov1hGgYRw5Hchpm5e2teN4SCGcz+obAsnt6Wadz+MweGzGutZFrYI5DsIhCsJFn97+4dXtq7ulbO8+vP+4foDj9PrmOBx987qtTdt2Xt7oK4SkAAAgAElEQVQ/vDMFBBxJJEiUMMhWK0bAwJGQUXzbturgFGMaIp0U6uKdhGRaazOFG3N3sebd/raHCfwryja/nGA+EwpeCpCTk+0ehHsegs9xAHnXWW8w4t4vx+iSy11xhfemkD2Q3gtyvMM8dm1Psc/HY1eKt/dCie0H0jrpSk1dhVmE2EIVI+4SJAQD9oZA7CHOlZcC6v/ZuyXRc7FdsYd3NOp5I75u9Ly1vzi4q2T7FTUBaJ+SXkJX+/Un7gDgy6u863m95KjsHxB6+9sLAOA566GrftZXeMVzD90XN/Jfw0t63vYLcOrlX33f/hkz2SeVXwoWf/49vcPrSlW4Mp5832snjz7jVs+n3JdtLS+tCX++zvNFeAnw/fws/sbyi/BUeD7Jl9rnf+ce/8suXyF2O4z0JQOr//Ky5/N5+TX07evrdR3vz4Ogt7893+nec/YSNezPp6mFEACYOemvKrf92skB/OUn5E5uvYnP3cnNWlOxLsDm1r+Z2XgnLtk12SBisBHDzaFQ94oGcyNzNa36jAt76wKR5mpXBEJFJKYgxNatCvvU1gdcN6vZXVb3R9R3Z1aIiDBbIARmYq3q1/nTgdANCzvgSLS1bcdy95HrV4Sng3K9GuUuaqLuqv0QASHynWlEIDe6TvIMCBTW3BkU+5QDBERjgTRSNjOttm/cKwwdRetzLe/Sm3CoN9i1Qc9cmBg+DIOROghMRuaMXXJxV7OyTpAieb6VfczwPqm9sLjoJ01fmD/0jvK+UnP33dvvOku6q13fCOQ7E3i/Ld1SQAFcFZ37tOso2lLv1QSBnYS896cBZGamILB0d1reRZHdTA1uEOwsO4J1ahFg3R2HIE4G/pLx6wD1AdrtV9Sa1uZmBEJwkv2B1a7f1WsnvYmsFG0KwAxosOr1UhFdRvEz2mhgU8PNdLp7dTeNH4eUjjenEMKrN6//+v2P9WxwZ4kCstaihBBjzqmcq3fxWd4pcU6AthjH169Pnz60aRq8OgxVHWtBhQcIM3qu7D7Piwj5Bl8legpBOMAr3BGCWO/A7y/Cqx2jE7qxI7vBwb3HxCxKcOdtKXnQmMKE6ek8X/7lT7/940ky3Lk1E4lMAhiLEOF4OmC0GJjYVQuxuhYSDlGnSeZVod1yuJsngSLFEFJOIly1AGAODCEWqAMUQhDmumnZtvv785A45xCjiHAfvWYMQBXrOrsbgdd1O59XUzIVplZKdafDcATQRWXLpttWgHY6HVorrRX3orq5OWkQDuOYhiGomjVtWnIahhi10boVqMcYxqxb1a2gq/wC0KalFBHdnwFy86rq4ziOOaeY4Fa15TCGmANFgZhDUhKxzHIMJ4Wt2+bNJHPR8jg/umnVpk1bba22KAGSQmCQttZCilZVWNa6PH66f3z/8ObV65vDkU4nPSjJICGNgTmoo2jbtmWeLwt7DhxTyEEGcjFHRGBBq60oYsA1AgII3ie55yoFX0MBJ4YECa7OEFjzq/oE8RXsfvFq6FMf9k5DMid7DtOe66+41m/98+usV1t6z/c+072savY5af9Jz86jZHDSbkTWcTgtZs3cnTg5ADeyBsAUBiWlkAIzaSm1tQAMQ5TEy0NZHrbqrakyK8RXXWqtYJ/uxpgivCWvRstqBE3mKTFL4HGI89aCCjlZKcVdS5WgwrkWX+a6LerVOUerFQBlDAkhiDsIgcmILUoEVxJHdx+z5gBHTiHGlCJuyKsExBBTCkSqspFosxbCcDhMbXCWoPfn4pAuEwlV9VL95nUw4qelYDW3QEiRKDjVRrUiCJTFfbg8thab+GAlsx4SI2SZPz3B4IZ1bfPWRDDmMB4iA162Mp9vxvT7b765O90ucymbrpeSb4chHYY8ubo3t+hWtV7KNi9uKuwhx3HMErBuVkoxc3IZx9NE+bJILWVZ9NXd26LLVqpCJGewuLLsi6rpZV6enpbXt1MSEKG1YubCOQ3xN9+8UgWRpCTDKHlgkG5orUFVL0+PVWvVZu4skAhjLVbUvNWaD5O6rVtrthBqkuhOpZlrSDQsK99/upwfaylIDa7g3t9COwclMHNnpRMzcUiBDGZoTdd1DQJtm1mKETe34zyft9W2zRGRAjjicMp3rw8hhHk+Ny2HQz5MRwDrWtZ1O5/namrkQlFY8jTGAwtxjPEyn0vbvPmmqN6cKUSppam7mZWmMKg2Y2cmDmTkpgZDiFytuNjt6+OrfNOkTafReRvS4eY2pMytrMS0ObmZogVSQRM4MS76wW24vQkx3h6ODJ+13f/4rngtVC5JUl2LQiiNNBwoZl1L22ZvDTHOl/dvX//TP/6bP/72u29f3xwOUzTBbJW11bKSqjIl8sZWUSpsGMaYopLOZU3ZjLxamet8aXMcOB8OOR8IQY3JiV3MlCXGlPM4FCukndtAl3nlQx5j5MQRDi+m5MowYYnCAwCGMMNA3J1q3A2VwEJk7qpVRYnx4eF9jBPdJkC70wMz4A3e3Ku2trUKp62uRe3+w6Oqjyn94fe/I47q8vA0/+mv/1JK1RUUkzuD6jQdOXCrBtq0NcsqgaNoCGJTUKVtK9tSAaiBBQHYHA2IhMggUWYdEk/HnIYYA03CJfHr29NxOpAtP/7l3TbT+x8fP33YvCAPkVhaaWZEQZjIFK0aG18ZBx3Hc5CB4E5qVwMwIjB29YdrxrjHy7TTbplI3dzBCfkWr74dXv9m+s3vb97Nf1VeaWgyA3rNRd3drNUqztaKF0eVEVMcx3H45nj6TSnVYW1b63JupX7/w4enhyfdrGymFa2QNYvg3nXS2SUwd7KUETM1uDpOt/mb37z6w7/5LqaTWdQn1adBV9Lg7z/95XCTb96kw10YxnyIr25v7fV3N4ebkym1VpuujgpWk9aFLELKo+VAMt3e3n/6eL6cw44CNBaXQK6uBGZ0JQgidm/bNpNLjCmElEOaDofHj/dlXgmUWBLHIQyXy3max9vb2zatPPCGupVFtUkT0SCVs2XJPBzyZuv7x/dbrY1LPMXK1UUX3dpSS9m8almrG5jAIXQCj5GxwNyOpwMRN21KrZltrTBLBA3jMEjQrVJz3arWol09mYklBA5Wr/ogvKcn9DP34GuG8fP/f12/6nRu7LUpuqYJz0Lnn8OKTgvgPeowN3K2Th0AvYCCmEBCvEvEoHfJMPfM8rl1xAkku1i78z4KVZt7TzktcJAgMEe3KQXc4E7EMPuF072GN3sEtGfNXbvDOnyyE6z6+6IP+693spsLdlvFL5TJiX6mn98jqN3y/QuXva4Pvsdz18/3QKvT0Kx3UuGaQNPzCs8IzvUYe2D2q9pHL7/315ZnDAg/g0F2+ILJfLeOe4lh/Rwb+UUa0FXaG0A3DQPwWVitB5vEn7W0PiMz/XpclcG/gm5+7Uuf8b6/ccpfLV9hQXjJwHp5wv+fY1h8XfDlbftXne1X+9y3fQE9vRiU/YkAuBdTrAf619dvp/t6a011VzjbAZL/Jydr3lolBBExb6aG1tRAIBV3cufO+9CYs5F1O8R+eQAzK88Tnpk3a82aKXolhsxa3dxNctCubNL5PAR3N3JEcoaaOgBmMJuA3Ey71I+7uYioeUf9fOfgdJ6ksQgFBCZXmLkwmHt7jHmHBbXTL33/aQBc1Z1cYaDOWqJORwSwN6kRiL0pmFyYiUmI9hd0IDAb3K05MbsQjMEQJyGWQI2gGm9EQJ0GpqZdWbnzPQCEENxdVQ3Y4Rt3JhKREAQBDALtHqO2H73gORaBgq/Gr9c29mvwYERyNbtw7LPtZ2yUhfnq8qMqcNv5aszV67VUci1i2H79iDoTgQTQay2h8zXN3ZjhVlHZGAQYyEkELAGdb+Fdz0CugRQR93pfL6pIv7Wqzd21M94Z6gbhGHYBaRIw855CMzEzy37bTM1c4fvbiwkUdl8IswaASVS1Lk1LkyCUIS7j3RBzaNpM7OZ0+H77aToe11Iul4tk+WZ8fby7uT0cRfj+0/3hcLg53H64/whwjLEsC7gPWEyH6elyYUCCIDhVQEiitNaE6eZmenq6H4Zotd7ehdub2x/efQAjpjCOBw5SailarBWBMMm2rdxTYtrvRAjsRM0A131wCpPDdtZzR2j395aZA5RSqKWYmSiFFL1CH/Dx4/3xVWxNq5pEYmEyEXO1llI63Y0E062oFRZ1LBJkOvC330xDXv/8p8pCRNAKOEKkcRzHaSTSUikFnE6nw3FoD9aWcy2NWUKIjAhn5paiMKHVdrlUZh8tECMNQ0rDjz/8pIqUpFYtBUHYzJZ1eXxay4a3d0gpE7NwNK9bWc1wuZxBdV1nd085upk3g1eCxCiIYo1abTlKjjLXWtcNLmMemIc8+tPTBaQ5RKIm5G4NgmlMIVBMAvdSljJrS8OTn9d5cfdv7t6+ff2bN3dv1m3V1k7HWwc3U2211HVZVut4SbMAeX37pkOorrbWdduIueUhqNq6bZKim8eYXp1eoWGbl97JmSWd8s0/v/uYpjSOeUqv85iOh3Gbz/N59hZEp5vp7jCcyobNTUAUxMyqIcBbU4mdm7i/THaCZkAI0ouX/dHqL3i3PpTAEIfteogvlmsY1NOavUlwbywHvggB9hLo3oLS9/7Fn54BLu92PFdbVHJV7exbt50+BgecXABF2Yo2ZQ9dmhQG5gAHoG5utSkDFdAGwxgkjtPhdDrctsvlnIchDfHm9mZd14+PH+ZzAeNwzGC6XNbvfkNkThGUOY1BciCGNXVoiIFdSqmuXtVBGoOHyCIg8T53gUGMw5SPxxxCMCN4EHbnMo3Jqbg0YQpB4eJkZaNaazvbXZ7KqkYGD2M+ponVS6tF3VThjpTS27fT6zc3zdWcCOKwUte1nMfjpF6f5mVZWilGNI1BpuBw5xDzMAYmwrguvDyVupaHD+v8qBG3h9PNNr+7LOuma4VuzVSh2lxrtarzvJ7v37757pvb09u7u/npMuXJzMc8TsMBMTyus9PqCqseOR7GKbLd3E03d7ePj/F8fnp6ugc36toAzjnHUrdSyE2+ffPmfv7gZ5hLiNKctlKWZS5FVcGB3Em1lrJx4m5IAajr1htIpmFIeQgBLBqkkjBT2KCP6/np3AyIGTHBCc7sZNW22rRUexNOmzbdFrcyZBhZ2XS+GKvmnC/n8tcfHu4ftwC4oVUjohDFQWqFQBJCjMEB1QYLHChPh9battVOQ9/qqpaypJvb0e31kJd11nVraaA0xtub4zRlNRvGeIcpp5GIW/NhGITDw3IupgAabWPOwzQd8hBCOJ/P3eOGBcwo21o2Fw/n85kAcQEhTAJ2aw5yZggjRFlEq9en+WHeiMJJEs7reS7ny/Jwe8LtzenyuNVlfnN7R1EKWvKapR4ChpzGOMyXh5x9jIch59vb4dWr9O//af344en+w2MtrSzNF9Ni02G6HeWQkg/hzSFHiSkO3/3hv3/7+s23r19livCt+VJarWVp60pmx+mwAh8+fWRSeJOQOZKzO5tEqWhGZpHSabg5cBgkhGFtWp3FMYYDe2jbBiPQEOlE0loKjgzGZWsOqLvBQZ4gzIEksoSUcwz5mpMow+Ci7m7azFWRY/CmRauRAfz+w7sx3RKnrW5odneYcozrfNG2qVcIRFXNtzLX2sYcW3UzEokushW/PU2v/tv/rqmXZsu6zeu6bVs1bW7bWlWrDy3nEMNQVg9hAGLZ2vlJ3XA6hGGcchrN7Onp3ExTyhyJyDhYyiFlismD2OPHdznksp3fPc0/fv/pf/uPj17RNpghZmJI3bR32qk1KNNOce01XemSss+6x9dy7l6WJKLnzm0A+pz+XOkjxC6CMOIf/t2r3/zx+Jt/PE5vKR9wfv/+8OYwJdFadU3SCCkIRYBh9b/6x3+qy2YFVKMX1jV++lD/h//pf/74/gMWgIEGbEAAHOjSBIhQoFKrFd7Bjes/55UI0eBCxufcvv/nd//r//gDDBiACBrw6nQaTuN0vF0eirYK5cPvbr59/Z3G+a9/+d/rnwohpHwchkTMRkVaV58mre5Qc4xjfnok0604w62lrFZJOESSIKy5Ft/WrZTFHKaQuGtYbHW7Pd6ZEWLMFGtVrWskni+X+Wn69o9/cG8/Xr7foOetgJDMuFa9QOplzCMGfirn9bI2K8ebu9ffvtoutVzK49NDe6w4AwWoYIKwOKBq3rw71U5305tvXoPp46dP67qCgEgE6sxw4e5M2Bxm3kp1AziwiHe9SPSus2sQ+TeSbsczznJlEP1shRef6c5i4p3vcF3DAaNwFTqgvfWOjIS4345rlRpM4n10gjoDANatYHfgieBX1AzExCJgJqaOf7q7m9LeuMhgl+5A5QC6DsvL5OnnSzct3mtsu74Sg3yHPJ45W894xWeIyvy5hsgO+xxb/S3oYIef9mz3C8ALX1cK0UWH9doU1VOhHQF7wZV52TT3azf3pU/d8zq/uPKXcd/fXhMvMax/xdJP5wX6RkTMnTb1+Ru9t2by3izZR/HLE3/+3uer588C8D9jjf39WNPLPT9vFX7+0WeU8f/15eWF6MtLlNGvy9+zq6+O//niXp/Ql196/UkdbjSz3uKxw6wdvYKjlmLmaurWXSI6ovy3oNPrRb+W2Z26yp51WEcBUnf3rrhnIO0+hbRbvwHmLrETTPdmR2YCxCxcCUqdJdXrJZ8vVcdbusEDsLcGEvMuqaTqTk33dm7y0DEaoo7Lwx0pBmtKnYzVpQfh0EYONw1dC7wLhXfdKBKFu0K9s9VshwCfUVqtDnNjk13AhJ06rENgImMmYa6qnS6E/v7fOaUCZ/jOSGkwQIWsr8dwFwM8SqSe6gCkxMbPQ6iPgV12UBjscGYYEcUQREJtGxH1bgrD3hreJzMGjIls7zpz986Q2zur9x7qjnteSaTE1zmaRIT5c5p4bbnud4W9dk7rlTfh8Aa3rsSKvTwNAsyuys7qymByZenNEzDHFWkVwIjIdu4czMjJjZS5KxzswqLCAWbe3FpzhaqzEMduU04cAxEUCiIhJ3EQIZAImNHUFObsX5DhHW5OghiCCETEFabeSjUFGUx9a1urVVYxNZPGBFnEBw2g7Wn9UFfWEhNH18sjYDgdbscpIQKbGRrMUgjNNUhKeeCB2ZkTN29IRHztsGVtVkLU5nMY9Zvx7ub29uPDBxIMMeaYOAJGrghxGtJghKVuamqkCkCAAHMHgVnUTaRDhJ3H5xB3VzcjZ6OrcS85Z4kSFdrUmFkESpjn5XAbaIf+YohRl7KsxVzhQcdBiNZamq8hBmdTbmEIN2/H8fbw559+QHQAJBAKcRDJrFYNddnmEDgkHqc81ngpLuKqpVsiRsksBzdttaxrKVVj2FhUYh081q0uC7SBqbMNbMiHYThYXaAFaj9+/3RzY4fjMAxJYmLQWs6t+DbXZS0pRGIOHIxca9msInPOMeXMmcvWatFaamuVSHNKccgjQkxkphLIjc3QmhNhGm8dNSV2N4dYa1VMmz7NF6s6pHw8Htctb/PqDhalwPNlfXx8uMwPl/NKhHK6NauB43SaDC5ZyFlLtWpBQiRrZkUrqhKoWL2U5Wl5qqWVT3Utq6RwWy/3nz7kLVvNh0liyPHw9pjv7k5mhb3G0+mVcBRBIHJE9uQWqiMaNSMeUrPmbooddObuUkMMJ/TXicHMyRju7OzkwuRE7tbn+Rcvo87MFPQuORCAQGJkZG4viNpqV7WLK4zlu2YwgN1h4plP23vIr/XIPtXw59BYr29eIiJ4cRiE2LqzkHl36PZOkC0KbaDu2EsQn9fL6ut0GsebTEyc4aJxkBu+yeMG8nEcAASmtpWcZBqnm9vTdBgQUFq9rPetgUVDGkLO1BZhpCzDmGEhUhxjb8pspYGFpknGKTIzIDEMITIz0iDqlbgXTm2ItEW7XLZtqbbZ3e2bJWb1EmMEQpCsm5d1bWZNtdU1xuH27mYYc8PmjmVZVI2kDaOoWVNbN51XWwvI5xaIc0yhu55LTuMQjoHSed7+j//w5/t3Z9vCm1e/ux3v7m6d5D4UVtEDa6uNvDIqmxOhrU9D+PY48M0YPi7z6ZRhnnIYxoMxtnclQEQRJRyn0bdj4W3MdjpSq/b+4/uqc4wMNvO61KpMRZuLKJEzmbXWilIQDGq6btvlsiwLlJASBxZmj0HEDfAgHJlbs1bXy1odlaUyM5FrVZEUU6xqgc0dHejpGiAuztJlXywTJEmrXhrI2Sw0Iq3WqlFzSnL+ONcnKjOyxa4tSuIsDphqE05RgjA3tVY2oCWJWQ7sGwIoOlCZEYRDJGI+vRol0nwp8+Ihh+PpNI2jaStbPRym4+m2bHW+bOqUQlQjEUEDGmBQMh20ubm2eZtLq8KScg7BW9FtNnH1BS7CUZgRYoRbRWFmc2NCzmk5as5jiCNodahZXZaHplQrImNdEHI2rdsGDxGUmq9QiGjiFGX457/+5ea4HMaTSCCRKWMa8qtTurye6lYTIjVkxGM6jHEcQxYQO5IEjml881Yd8/bTD4/3y3wR+DDkMQ9uLXJADM39aduotixhzIIUiIKEFDh/Wj4ZaSNFDEwo1EpZyFpiC57GxJEGTVzX2hqpEXGKbBbEqMVhq9RUHdoiAzFwEPLAjl7GZMDdFV29pjnIvZlBm6bprnajH5KK4s3n82Vp9/N20Wbr7d3tcarrilYEljJLhQSjAIrp//rnH1sDyGM+5PFwHAYldrLhdOSUlm1ZljKv5X7eluoSV465NQvEEoM3CSExxXneJBZJUXjIeQwhrVuRITLlkKLEYK6lLoA6t+ZORkOOh3zIOX16XJ4et61ggFhTZpCEYlVJhzFbsbIomjqxcKRIrTTntFNK+EUK0Itf4IDQCSW97cPIiOBG5mRGLILWklA8+HiH3/xu+uO/ffvmDzdVni7nx1qQBGbImU2glRKlJAfSqCuy3uiyPH24PHz4dP/u8u77e10Gqpk/RSsVmaIIgmt1b+QFMIYL1FGNZCLzXSm2QxUMMGlrkmU6jHCv56W6qxhmgIA1zJvZXMtDK7hQ3B5+CpcPm9Txd//46t9/9998/+5Py9ZYiUzUkaYhDm6karYV1+3SmNYtz+e6nMFsIrJtqirkwkFcISFW3VxgLlatF+MZnces63qh4ONhIEVdG9bmKZFza12DK5XuHKhwBzNFktZsnk3rkjEe85RTfFzObanjcRynvOp2frRLqT4jNPIVurlBKcCvZtwphQiJEhSmtdat5JRjiD1R37aVK7WtWNnVf0kIZu5m0I7PklKP0HcUg/b88FrYB+BGvtsS4pmdtEcKIAMxvIcERteo/gVHgzr5gK61djiSSMNuAc8kauZdAdexWzNdUxDhvTvEYA7rDzbECWTdlGrfCMROgpgSERncVN2tCUHMWT1xq0Z8BXtoDz9eMM72XJ0AcnZyvrK5rh9fs7c9t+qWjbQXlfeVenMV+XMufgW16AUacAXz9qjn2qkIkHV/+p44fy7p4fMGji4n8/keXL/dAXbotTf4utneb7NfT1wV7vbcvLeyEH/2jrwmqj8HE74ic71c5/m/1C9oP6Ar4Pbysx03fyZQ/WyRIHvw+RX4Q5+BJr9WRnvhk4h6B1vvTvvqkJ5/+cps8eWafw+G9ZKr9dXK4SVI9rzTvx8n+i+1+JdUt2frQPzs5v3agT1/3nlbXXX45+v8Sqdx/3OHlNFUibTH/TtqBCKmWurz1/ShQETdzOirY/jqrhD1Mgscu/Hcdb+EZga9PsOdisdwp+4X6IC5SjOo94RBiNDVBpKbKZmpusG7ZhbM+Yq59/rJauwEcRbiwELSiFWbQ029m60CxFAmQLifVs/O3d1cAwXAa2tmLcTArgGwakHI3RtgzxA/4M5qBrXhkM2aq1FXCu4q4e5m2ktNO6rmAUo7N5FcOIQQsc3O0OvAJ4KQMESbOboSF8BwMgW5ty7OwuQi1LwQCXpPn+xGYO4eUwSwbZu6UkevdmdZ67RkMqumQUS6J6CxqVqvZFxRf2KS3tAFF7uihObmSkO4sq6B7hJ4ZUwwc5dyq602NCcD76rp+wvGeveE9LHUtMF2i1x3dMfEnffUK599GLnCPQTp6GpvV3cnVTPvQxPCQoAbrKcpbgwwOFBgIVe4sqtZJVInDuxMjZg4REosnShn2PsQIQQmsLP4XFbCVQqMiVlEmNhMtXXZyG5SRuxVmSQG6KbCEkLoPo4sTBSX8zaMiRqMTABuKPMcZZif7pdlYWbTOh7k9dvD48eL2iZJUo7zdhlkDFN8/c3bpq1q3eZZDuzw1lo6kGT/cP8DJ3w6/3B3d3p99wYgyRBPEqQsmy+t1tJKS3Ec8mTRPXOryhkcYQInX9smEliCq4UkzbQ/vh4MCRCQ9lb/ag4iUlgj0MBrMzfnhjAIRTU1ocAB2QYiMvenx8uyaYihbJX5cjqMDg4pB2ZybD5zGg83UwjTq+/v4bHWZmYSJOcUozRsTdfLtuQDN182FZJmrcbE5awVa8yect7W2mrVVuFKBHISphxF2/owP3IfrMZdnDinacoHLRTDrK1czohc2ZksDVOAklZYBRKjMXGopSAEETJr2twZCJzyOI6jH/j8dBkS4xjWdYW3IDEkxOHoZu/efTAjKVxrISm//4c/1rqEGNd1ZgppDEykBpagaqWuj+dPrrVtJcdY25zSsK5P6+V+ebo/P50lpo4tkgh9EoBvDjdJ4qwzQKc4uHgYgzV3aBryw8NjrU1E4iE9PT4lZE983i7wUi5l9i1gQpQggRGDcDqM4vmQT605k4xxKmD2EUgAagPlqELeRSwJtIsJClE0JVNzJVcyc6iTe/BngPwzWf7zi28Xo8I+OfhnXib3It/L95V9UYrt9Qcj/uId59d3izv2hnEGdYz6Wuak7ggLc2JnYUaDgA1G1ghqjuYgJpLAFKxpD5g5UgjMToq2Ug3M4zjGEMy86Ebgw2G6vT3VWlS1bJUal5kQmSuoWYs5ZxMAACAASURBVJkb2BvapkQ8SAh5zCFnTtGsSJDIgT1mipYN1phr1d3pk6gwZzBcCiSZ86d3l7pp4NDZonBWQ1uhjSSE+byW0hx2QSllS/mtNnKk+08/ifAwHFvTp8dLWDWN5bvf/nZZw2XZHp/mZfVNt1pRG4h4HMSdxdUJISdYK6WexiORwMQr/8f/cA4rrHh7mLE+HH7L3K02iIYh8kRWLWqNhOEARjlO4e5mDFQCLadTUHWlmsf4Kt7NyyXGWFsVYjkdalmSeObN66daPgLnw0kqtuY1Tvjp46f1YSHYN9++Ptyd5u0viorAMaQ8DtwoVT0eh2pbUU1JnDkiZwE1baWGGGIUITSrxwnCG6HCE4HdvJa2GZpqymmaqoSoxtZMXc2qE3LCIQtLyNOIpbqTuDHBW9VWczgIcqL0L//nn+1ywswgQTMonMy9EkEEQrsTstWqtTIJNbECaxQ53txmcB2ShNB9mj1kZEdD1VBiiuNRRLBe1qJ6ONymOH14fz+v1YFG9vh0rmVjY/e9Rq+qRWsg2VptbsQcY0pj+vT+vm1dqpIkDylERSUQWAGkkauaEw434z/929eXuS2r3X+aG23TrSVJZno8xBD56WyZY9N8/9ho2SRJTi7ka8VcGutDcuFSQ6rRSzmfiT3laTzcvLo5trWewmFAzp6mkDKHTCGCGHDTav79+c8eeNvWZb6/XC6Bk9sYxG+ON8yi7ELpePdq/XD2whJHoXFIRxBv1n549/54dwxTrKbnbd10CcSHdAiStrLN2xLHcZhGRg4UXSUwZx6IeNbFAhVfuyJdYnbKWZiTsKOoEtXEUV0LVK2qVQbYWd2r2eLjbA0piXjT7du3v9uGNaRFBNVtrWsoTNqCY0zpkIMwnHwMkWM4pMEzJAiHCG4idcgDiUg0xap1ToFr8JwHk6AeDOLbVrayLtvtaaSIaQwc6bIoR7q5PUyHm21tHz48etBxHABat1VbqShADUwpDzmmKU2n4VUtcv/xx48ft0CUcgSlbdMCj1nkIDGJrtRMd2WGbv0srtSeawJuDHOwUYCrk4HQpUm7hbY59Sm1pyEx5mMtc57a3e/l7i29/R3fvOFp4o8X/dNf/6IENo9sIRuPLehRLHIVaALnP/8vl+Vp/fDu8f27Tx/vH7cZqBXlLB4EkZZuoyTS3BtcAQUUruYuVvwqaL3XJomNzGENWmtVEWaQOO1ZC7Ebr6WtDwXRQ7I4hfpoTz9+PMnbu/H4D//0m9vfv/3+p+9/On84z5tHribGUAQZaWJC3CS0D3/6cDkvrUICgfjhYXNjEVGnZV2nMTRqeUokUtdm86pNK7YYQwj88fJxGKeQ4va0NVVvupY5TfGyXf70179M32aYrO0SI8oGd45psNCKrtUYrd4MJBJoxXq5ZMtjZLoYLk4LZKFDHADairpTcFZphZqzhSwBUtZaammlBQkpRSbu/XOttjJXbyCDu4uIRHZ1U1dVY808kBPbjsP1/itjYwf3IhY6zknXjtPP+FXvZwGB3HfYaudevEA3dqmmXbwc3TFLPR6DanUzcGAJIDIiF0EHrXonQU+zmLgruJuTQ5hbbcKCanBIDEJUqCGYM1HkNAQ4tdpSSuYaolMgI5OBtqfamgUKva/MOuawnxb3TKejOR0ZeYa0XsYxzxhfd0xk75ynq9yCk3dJnM8g1TPG9VkfqVuGdast4r3cCJB56wDLS3TBn8Go/af1JpMdjum0it5sS6qwLtFC5CJuhL0jSU2twSG8t+CYmakSEfXAFTsC8wzF/CKm00/h5TpfEZr8etevLIjnq9ATc2fuh7RzbnAtjj5vH4Ls+N0VBNrbAJ+vPT53CfVfHN47T5OE5+H3vHQbx/3KE/3ieT07Ff7i8pLV9YvKUeHnH/2raF3/2ctze+BLTGrXnPIvH8UvqWj/yT0/392/80hejIlrtxf/8gW9Erj+03jh85E8H/9XeNbL7sgvhtGzSagD/bE0YxLfhRoNCnALFAKH/vB0WKWf8kvqYKeRYYMzSN2hDW7uSq72fxP3Zj22JUua0Gdm7r6GvXdEnDnvzTtWqRoEqOkWvPDn+A1IPCPxxF/gDSEhXlogxNAgpC5udd28mXnyDDHsvdfg7mbGg68dJ05OlWpR1HoIxbBibV+Tu9lnn31fbdYLkNY+JywEvnT/uTe3V4QYOAYJDAhXqLkjxKi1mHkxd4PbNlQHnKxxoZrqh6lbNbgxSxcCMYoqrPql+5JZNnIimzMYJCwxJvgEoCn4gyEUmBiGqlrdlJyZJbCpmmtLxOBoFYmSFWxM1AhnIHCgIFFE1NTI1Q3tMj4+IGQNrYxDB6KG/uBCvm33xtzdjMwrTHhTq99KHQIBKj06XXyyO30KRbu7NaFD9seW6TaXtudBmqi4e/Om3WZPhwvcYeYhRDQ+r5k1l3FSVd04Wn6pUBCxXGhj2MxE2mBN4TAQxUBR4vF0FAiMCMJMIQQQFVUnND0jb+qqxM5tbm8wCMEpitSqXms74cASQ5RIZuriUFcQQ2AuHCTBy1pRHaAkXI0eaztktVQGkxAMQuhSz5B1XVtFxuH9rn/2+qaaPrxfJFrW7OxTPvc+PH/z/Dwdz7Pe7G6q51LWGMP+euz25JRP08kcJDDSvNb9/oqQ3Gldl/N0VAM5ejEJ1MeOhafzXDJ5BDIMHlMksKpCiIQZqmrVmhoXoU0y7pvQNpFq0cUtKIcUQpDAJNpwRlMLUVJMtdYyL1p0XqrP1RzCNQoTUQwpBIK1tk12oFp5/mK3Fp/OdV1M3cxJYUtec1mr49AzC87Tw1pmYkpRfCThyETm5XQ+uiMFGsfEAYHB5ON+CEFiSaUcS7GUYkq9G4UYHHBY63MdD6xWH04163xFPXMlRql5WdVhIUUnrOsag7Bwn5IEqbVmzjGG65vnMYQ85vNpBmxdlrr69a4fhlHN3779+ni0wLxkCxHz+czsefH5PKvVxDEESUFubp4xuZjP86K57vqRY1pyrgqREELsY2c7piBENM9TLsWNhr4PQRbn4/2RjGz1dDPsdgeeYYZh7Jd1OZ1Pfd+bmgQh5mmZvvnmm+PxNHbDbpdERIF1mq1WMumCDglXHQcRF67kWzzkDoVFhJhqXWDaCJUSOBAbC2irWW4MJnVUh3pxJr+YZ8MlSiOuf7Zk+GcLE7ZF51ET+PNl5vEX2yEvwNhndbZtQmtFoqbc1irJG4a+Wbh76w1ukxtf4uJtpts8NS6SroArjBR9il2IA8F9niYahjyXrhuePXvGTJqrZ5wf5oe7+3yEJJy93vHC7+8QkBksuL7pnr06jPs9i1m1fuxrJdWS1wVWxIMQE/vV1a6oVNVqW5poVdc11zrNy/pwP2MB9NIj40CEBAxdv5Ph29tvtVb3GjrEiP5ZR2QIjiQVlqmYeynlquv67uqwf9Z12enh4Xg7zyX0WGcUQ+rDMIwSopVMmkHEItOyWLnVa7DG9axVUVZ41rUc397f/3V8bjKXuq66xizX16HvUlBzza5+dXV9ff186HciFDvuR5nOOdfZqOz2/dVV5456zKWWXGbCGhMFwTJPruXZ9RUC3U8P6zpJCrnMHz6877r0h7968/s/fPHnb/4+xR47BaXArOJDl66vDYJ5yUXdUFNMgdRVAWitcCNCinyJUNgdtZgZ6rqu5v1w6Pudj0rcMcesuZi6Z05IPaeeJAQrEAnSUYBbLct5qmu56q52++dB09tbxOORvC+VrCpEHG5mMTX9OapFQUYkXRfdPZeS76uZdj0kjCxurkvOEGn+qRJj7JLBqtn9/X2QLqZhfxg142E+TdO6rmvTASilqrUWFBChap2WydgG6UOKy1I01xRXBpkZqhocQjGmrusKCaBqgJG6ccCi2O2Gf/4v/qNvv3v78fbD+/sHY0EXOEgfOKUuRV7n6c7PAb4s06rgiN2APuGwgw2RrVw/f6NqS86UiMTX9WEtZ5CTluAc424kHhDZHSgCAnwt8/l0Oq/5z/e3oevJOS8rTEMIgV1AKURmgToHvxp3aQFl7Pt9n8bAouZQtapwCFEB3JRAIiGmwITV6rlMXRh38TolCQhBmBpP14icztPZg5M7TCt8tcocE4kzsztxIAg3UT2zdVlhGpmFU6sggmDuwXmQfuzHEI2l7naBorz9eHu6Pybi1PcxpnEcOCH7Ottc8vrmy9eqANhARRUhcOyaz9nxfPq7P/95WXKuNutYkYjgqKWs83KaF++7EsLeEUAFXMBZxPtBQJXF5vWsrs2we82rOWKkcTceDodd13c1PNu9+Oar0/uPpyWjH1ErSYowlxi6XppHESfu9ilz1mJqNSLEFJa5MPPGaeEnkhOtLI1KxjBlVkUTtjHIZvLlse5f9eM+X78Oz17zl398ORzSeXn4yzdfEdHQD+us3U5uDi9T3Ecbj7fz3Ydpup1Fd//jf/u/AcAKtOiMQM7u5J8YYM2tuVklEQi+OdSwzsUavLC5tTm7k2zBrnnTqjUX36Jjp1ZtdSIx0TWrVnfA8H/x391+/OZfTn/91//h767HXz2cTZK9vX+/3N97YCTp0ni4OgzjIcl0/uZuPCQKtq51XgoMzEhtqRRbddXgQxeZO+JqIKgKUE1rzhQigAYH1FrFETnkNeuDhoPEa2aWLiZjBZQITK0dEKWYr3Y6nilyzlmipBAZPJ+W092CFQFuxVk5sIA5xVglVJ1qtum89tfDw9190ZJSSEO/LMtyXlIK2BZ9wOAKEBggJgYbdEvuqPF1LvfispZ7C+TJG0f6H0pi/XsLPV0MBNsntJ/MrNmnGrxmdmYAOZeSCwdm5sYlICFuni/mpuZm9WLxBHNVRSCHGzsCEIw4MDNFYSFh0VIbLSx1UZWEQYE5UON1wdzY5XHcW2Xu0+gv+u3+WToM4AfUJL+4Mj9KVjWE5hIUPebcZI3QRZ/U0/2SbfnlOC0iqvWTR9XjAFhky+DbaIldvWnYPQZl7XsHNgfErR7p1gzagUv7EQAiaTpuZC2WujhTP57djwq9P/71KYzwc0jIlg5/op49xRm2xNOfOAg8uc7fw14++5RHIPWpBaQDBOZPxK6nR/iRoT1hKf1ylOmnrgmaiPsvPMo/xvZDVTN8fgme3rZfONQfxYx+fnu8rI9ff7lO/D/4Kb/kcfx85yeoaoM4mcSje2lNYqgoqMbadtiga2x0MNjj6Sg7tR7grbdNzWBbjtIePXNXNSbXxv5qAo7mptCLxrm7uRO7C0SiEHM1aNX6pE+eQI0s5caAgWpRc3NzcoKQOxrvwC96WhfvP3a2i/krg8jgnCSIMMsjQNS6jomIXY3aqgs0cw3fTq5NiiIB38MfiRyupmoKbJws0AW8bWhagwv5IqLpbmYNP9lsvdC8+zYwm6gJcF58Dxr59AfMzDYFEEgbdNT6KS/0ivaYqVqM0Tdku+F67EybSyvg6sZbntl0EBvURUQgW9elxR+PKjnEjYKG5hOAC5OQNnAOTrBqZuYVvs2gl8kd5ObOZmqlOnHr1ySHW3UKcHJXN1Th6OSVCO0JNLBBEND4WJHAGIZBa63VyqJNWllrXXSjCgNuUFcrFQEiHEJMsYvMoarmUmMSAMs6hRD7obu62ee6LHfOpqGTWaesy814dc7WjXF3GJcyLxN2V7ur6510tupxWWEK1bou8zTl169fnY55mlci6mIyZDgkuESLPZXqajmX1Q1gdEM8jOO61nwuIQga6Mxu0iDX5ofNXs3JwYxq1ko0zMISOBDM1AyYjgusybV6FxNEWO5jQIoBMGHRakGomItxF4fmBVqyrmUlLubFMLvADOe1YEXfIUZcX2McA7Gp1lIq4IfDVUpV1dlFmG9uRiKOQYit1uymaqYqEliExn1HCCEkoKneqnkmsRBJIvrUT+elVGNB6mTcdaXINJ+nuUiARKS+jx0LsRAHZzXLOa/LOp1PIYSG7LFQ6qQaSZBh6A6Hvbvf3Ny4f8yrxYCUsK6LBFT1XFYm/ts/fb0bw4vnN69fv7q+2ot7XVdXk9Cr0u39OdBCoN3+ajcM+1pytXVdT+fpeDy/fPFaJAgRuYv7NJ+p0ph2ImAv6sh5Nqut5/bu4RaKsRumab6dbsU4hSAiMUVmYuhiviwFupKFZVwjRXgwLmAHGi4JwGKSdaogBowgTXwajmrqRhdbYsVlLkWLEow21N/A+EQj/9EiDfOl5Rh4Gt09re7gEophg5f0Qo/c9m0rSws+2KHyuNhhk8VDawtoyP9l/ycse3fAbBNqaUJ66g4k8m7ou+u05nU5TxpsmiaxsMh0Os7zaYJjXUpZEQN0AQEKWAV1CAFa8XC7SiJjSPTq1cnBRcu8nGGKSCmSwPXly71ndTiLqPHdcX44rcXIAdUaRcIhMCjPpZiCsRu46xIR3DPYwFYU8wybkN69K2pERmwK1PN5HMOLV8/++Me/PoxDl7rj8dvzqQTZf/nrNM2zUF7yCmIzJzUzryULc5dkzXXRU5cGcWX0KWEJiJQIcT1N72/fXb/oJYoqvKgqcYoB0di8lqubl7vDM4rRmJysuq51zlqmaWA6FJ1V67zel7LWujrmGPoQ0rRkd+rSWKjWaiXX0BOTSshX1/vrZzEmJXAXehEqWefzdM6lVCdQigREzmUpNS953O/CmEBLKVA1EYSQTEm49RQGYhYJEjpIJA6pGzpRR3DQTddJZJJqyGs9n6a7h+n+2c0Xuq6lZDE1zZqrG4iEKSw544TilFLy1TgkFql11VpYLHoIqSvzpLXG1IUUa6las3lRRV6wn04xEdWaFnEKjsiB3cAUgqRcas6ZGVcyUuTzdD4+zOtqpaoZCYOIOUTXTcTF4ZWqQtW0em0vSdGyVnE4pDEkxdmchdlNWzsvb9SG1Yns9RfPF/3QjcOz5yjOMSYnU8eSSy6+nlavdUiize3YKVfvInfd/vrmqk8hcdB1dSaOEgfpxuiqIiBXMofmxR0onXQgVpDCzmW+nx9O80RuVlYtWkuNkq52uy70rBqJOonVzUsxo13qUxeHNIQoTX1XmJ4frojYi3YphqtnS13cqqmey7ScSnLbpcMQNISOEZ6G6AI2NYrELJtXs0Rmcd80gsypkJl6i/eajiyYAotIShxXlFpKIShrzVlzLnou5PtnN4PHkmdK4mbFNMPZ/az1VHNWO4QdpDmMwjRXZSZMyzLlcpym43nN1XKpbz98rMDVPu4O434/jLtUtXpZ+j50fXJH3wcRgPR0fljmZZqP5xlrXlJc+jFJTLWWGFPfd10XUopWLWs9neu7B5xXvHlxWM5UMihw18dxPyx5OZ9mBkmUMCbKFRVCoY9pWZYngMU2H2+2QnByJUaLfoMwsSt5dTQZ+zzaH/74q27McTjToM/e7Ne6fPPNX+5OH16+eb17PmSbTX3XvWDqp4fy8dv83Venu+8WPd9fPYu2cHErXq24GWCGgssyREpcG4XKiZrEiAHNm47cHy224YCpm2njlUjqJIQogZe8ZlubSrZfciVJzaHTnKzAHt5nrdn9/+6H57/5qy9Dne7P7+oUHpaS3Zyxv6Egu3G3f/Xy4L+Rh9v5/l7DVDlCC1xhrH3fdWNXVtWSM2onXeiimZGaa9WstXjsw+aSxwxuQq4Eg846naZD3SUOCP1SM1hDkBgjel6HtazVVhQv7EGiDLtht98Hj6c0QU+RCZDpvEhhy2AJFLfGCRhQAKY1r8Vz340SxWfXqhqEbLvSLd3gC3Igze1n8yE3dmpexOaXBKaRoUENXfx324g2TNL90g/4iBhQ+xUxEQmqVbXC3jIZafGBuzq5Nc0Q3nRBQIDAK3RzBYPSRjlvrRdmfp4mGIkwzIvW/fUIuJBUK+4Wu0guZqbWHDOBz1Pd9pp8DrjgkQ30GPB8+tNTNjptlfpLrtNylkcOO/yizkKP6dtnUdbWWfcEoyHA24xm24W0C2r1adCtzca0MQxAZE1Vh1mKGvlTksp2IvSIK/1UqfIntu+BOD8aKOKSzm4nQp92BmBuLWOldrq+aSDhwoB4Sph6vP4X7O0T5cguBK6ta2zTWv5+/+NPDO8z4fafOeXvwSY/db4/wsD6/2fzJ1r9LSE3s1LK93b7xP27KPz/ElhqAw5+mpn2/+32OKTHQbYf+clWSvHPt58ZXoPrHhWtGjLNzHCB6WYNuD1s5A23amhIayppr7KRKTgwOTm0Fdbx2KFLT55ub/mWskhLv53Y2fOywLxcijF9ChwEzhwiR2uiXdvhNr+HBpuAgZIzM2+iCNWzlcb9KQ4Jjb25qb4TkTPTps7El9ov1aJazWuFc5CQYmQCCwNerVopTdNrM0Awa7SlNMaqbqZq24zT8KhHxhSJUCB5ggS3zcwE5DAzb/aLRIA5tG6a4Q6A5PE13koAGwZP8jgNPgFbfTNwdLs8utuCIAC7w5xUPXXBal1XBWmDI5ld8Wk2aUfLeSViDiIiMUYRgWC1pfHvhNk3/0ZseBT5pqSF5oMWhNHSzlLqarULiZzdXdVMzYp6q7a6u1kpJgzpyN2tNBMyF4ETVCs8A2AJXYohRhDVXKbTSUvZKgCMOMzjvlfX5bTCkIYORlpU1wJQY6iAiUKrt4Wh60OSdZ6VCgdeSjUrnLOqX19dv/ny1Ze/+/J/+Vf/K3kAmc2Y9TTVIeusroidMBJRNyL2Ps3HuT6woAuQgJjkILur/dW7t3//l28/9EH6ITFJLrr6cs4wqdWUgvZ7ycZC4frmRR+H03HOau5WShEhShKIlKorMQkLihSBMIVaqqmHJCRODlVnEBNHQZ6wHwcKON7f9odDP+4iJbciLCBSVTPvd7sUQ2RhkKoSmAJTqFeguOLqOu32+67r53k5HU8AXV2NOee7+w/v3i8EzDOK4c1LctdlmbuYhv5QKnUpBOFlzWteU+AQg1lR5VrVXVlYtZRSa61wCTGZe0weFWMSA3WOq5vhcDP0QyTq0iQPxwcmqNf9fnclezIqS845kxOM1mU5niyEtzF2MaYQw4sXz96EVwqEEKJAJP7xd7958/L5xw/3x9PHEJisJklaq+WyZI2Buu7Q91d9tx/6qy7FKCEy39/eQ+3Z8y92405I6nxc51OdJveVJR4O19fXz0SYYML07Nn1F69ezqdpPi3H47ucT/2wC1Hm+SFG+c2v3xDJdDxRkP1uf72/mjmyYuz7i/+Ag2Ucx/0QAwJVVi3uHpiasYYjE1UARMat/emSo7hRhTeCKtzhtpn0NCyYGJUIINn0SeFmm2Tppzf9cRF5UrD6QbT3ZHbAk9mM4IA+yUBayOREcmH3buIFfhFZbW4624cxnFss5i12o0u54FJ4dIqBGWBXVxdIELjP58VMySVSfH3zej9eHT+ePnxza6fLAuGgIUajphJis0GABAxQwvtvl+OyvPrienfYUfAQzbXPyUp2UrATk8/r+uzZtbu/e3/77rsPt/dWDNT3MQawCHMK4qoSCjOud7ubw4GBeZqn+fTqza8UZlaK5mm9H3YD8omDmAsD3d444P39u6//h3c76X/329+ezsfvvrt/9zBLwn/yL/4YU0nrOp2m6TizsDChWpZC7BVwx5zzzbjbXz1/8frPt150EYFkE3Xd3+zGXd+dZM4nEi4KVxME4fL85ReHq5cch/vz8duPH04PD+40DGJci89qswQaRh8hrqkqSd+v7kQSJS21HKdpOk3FKp2LltOLZ/H3vz88u8Hx4Zur3TNnmOnZl3mZvNSu63ddwr2GQOM+1mqmNYqROjyk0MCNyBLPx9U9QZJbFE5d7OHdu68fvv7m23kp0zxXRSmowG6PL3/7m9/9/os3v/7tH371z1Inbz+8/ejvb+fbh+N5Pq9joCHFmv1hPp/uZiwIA+elwihKkCAOtaJmVtzE3Ay5qllR9VyLlRo7jNcx9XHcDS4qEtZ1Xcs6LRyiEDdxBoHmQBI41lXn08OHt3f3D0spTaO6aSMwmCh444yHgYZdLzEUL8uaEcABIK+1IErYqRtp1lJX8uhKMDDHftgLZ5KKvnQjgfNX3/65xmzkRNyyuxQ7Uz8+zFoQA07nHAN2V3sWlHo6Lb5fUTR06EtF13fDEIjKw/nj+fS2k/Rsd6hcWaJbVquZld1y8cIShGefs1QZ01jqbncY+lFIoGB0SVKjWUWnXRiaX03opZGsVRXQwBIlkFkfh+z53bff3Z3vx914uNlX1vNpztn7cc9Rqmtga4IJbeYR4ou+Apmq5sqOLliiKCSCCKg5tNayFvUM9k46YhOmQCyMvBy1VDUVkUG6l8+e55r0u2ldjt1Bfvvy18vzF8Tepdj3Ikyzn7O6BpGYQhzJA0DnZbk9L+dpppCmXN++e1fdSQJFmifb7TzEEGOI7GQZXtjru9sVdNuYfYernXAYx13f7ZZcn7145uos0SHLvM7T9DCdzBRep+l0Oj58cfWrh+m02rI7oGRI9OuXh7IyPZwgQiKhS8n6NS9EFvtOiuhc3ayS0sBkbluTEYiQJESTmrXqxkdp9G0wPDoLhiTDOIQxfPHPXt68Cm467ofDDVs/3X9472k93BwkRtDuav+8mn/45vT266/+/k/vlwdwRj2F830Jq6DAKnuNW2mWgFBbRt28ZslaaE7Q5oTeqP3NzxpPOLxMG6PfHJiXlWjlpka7VXU/JTz5/gwCRUgEO8qCuyPuvpr/z//+v8MV/ov/+j+/W27/p//jf57OfzedbjMv5Pnh41fd0P32yy9/+1evv/7qa+66FxjXUu/en5YZKcW+H4P0p+Pcax8k5sWKqpMFAZOIp+Le933JCucYY9/3mrOroQIZ54dpOp5KzDVksCZC44ynQa6eHUjp/vgRibKWKddKi+vH4GE9V8ywTTycQuhq1Q19YOdAANChaGZhtnCezqflDAMxdM3kDG9W1yTEUICcDd5qRQAZVFVVzN3VYE2lw/HoSOmPWZx/AqCwpRstMeBH88rPI4MNSniEaAgQ9jh+cQAAIABJREFUNGlIYYzDWE2JEVMAY17npSzEsIAQmEJzaldWDzGkGLVaLcrgFFJVZeIgAqDWWkohlyjRDfOy2MlgsKSWVc3efPFmXWcr1ap1Imm/L0td17WWDGusHbKfCGk+AU9PyRzfy/2bb2mDfuzpjhcEi+jTb30r1bfDbuZsF/ObjRL1eWnQ4fL4IjweiQjS2p62YKr1vUABghmYN6+0Fr21D2htVQa4qtAmcOTeSKufcICGgfwM88bMGh7y8+1lDcN6PB26NGxePMQa9oLNqp74kbWTc3nEpD5dyouf4FYdNWtSyzGFFi3XWi/azE8y35/Ynu7zNMr9mX/5+e2fjIH1eA6PdKcW1j7u8D1K1A//9xd+xC/c039A9frlSNnT3zwe5HHkdGkY/IXDo4tMXdsJDitq7M2HGK3R1sD+RI+tfTF3NfNmCEhubuZbcb/JyTXWDsNB7Bt/ibjZGzfXhkZ03ST0FMQCNydzYe5SRxx0MRKRmIJWbf1i2JyCedMLZIByO79PM9GlSkOtfGe6tUS6SkEKvInMN3iatznDAd860Wp7uwjGBgLcmOQTYugbCm5m5qaqm7kUcOFxwom4EbuYHrXvH+/RY+7ajCbb/NIgIPCWurV7+dn71woS5pujyIW/9Xj7+TJ9PJmJL2rscDSUzUyrWq1weGBhAZyJPn9G3LVBXk6E1jhMDIkANzCIHvl7hqbDuVUeCAjODCZ3M3gzUlFvBSU3IjTiHbbUmi7FGgeRCLGhQo0bCNgsr1dAEIS6kFLXqZmvZnmBMgjEHCWNaYB5KbmWAqfAwZo7obeeTN0KO2j6XhEuJdtaC1i7MRAzSTQtx+nB3NV87HdvvnwB59NpIlkKlq/ffTVnHRLTsToZoWajtTiCD2nYiTF71/UxiocYY2i0vlxUJLO4O9TWXEs0phRG7g+HMOx3ULbKS15ZZBzHaTrnZaUuMstWqmFycqvu7E6oXowUApLWNE7krT2cAiEwdTHFTh5YlmlmT0LkhofjCmA/gkhijH3Xqdrd7d10WmOIh/1VP3TAPbiIcEq+24WuH7qOq1YRWnKp1eGQIDG6V2vwBRGJcOxk8Nj3KQYJySToftfvr8aQiIjO50lVibzUdVlXrUbExC4SUselInY+OIcQDtd910vqOMYowVRnEjJkkHbDoKsqEwtHjkFCYNFqdw934zDGFFPoxnFMIZC7iDuKahW2/b7TOhDvRchdQ5C8lrv747dv8e//za9ubl68efPqsB9rze/+/N3Dw52WOqSOIR9ul+v91e9+87tfvbkZxjH2Jzo+TNPc3tZx3JE5zLSUEKA1a13M1vN5AdeUhlIRY6dW3OurVy+Zwm4cAaSYYicgO57up/lYayXCOO5fv3jTSYdMarXmighINKB5gSOCmcwqmhzg1jvcbMhr69fdMKztoSEAJK1Rb4Osfi4UcbS6BV2w98+WCaDpAz6ujsRbXe+xNHH52sI5e1Lo+zQzOi6+y2jlAwAwN9NLXoM2tXBT4HGgQd6wrehZaq4rq9YUe3I+30/Prp8vx3z/9mgTeKPQBgJ8avU3YYKygcCRILDqMKwzajWJabfvmFa3mNjzXGtWYUlRYpT94SrnMp2+++69oYI6CswhJi0ZZgRi4jGM7OgpoXCt6gsFHYOlJrIfQB0dYEnXwMTPnu85Uq7rsuZpqvkEEiol9v2zwx4P53ldcPvxyCwOIooCZychotQbeVGTGEiw1uX24YFpTEM3HOSo5ubpEA3F2SGgQAmJgFJKXbVTsYIYdyR9NakWjIKH2IfUdZ27zvPJvRAxiwFmXswq00aBkxi9lpxXNSXArIjg+mbcHcj8tM45L2IGc53WvJyXUjNLdFGray2ZJDZpbjK3Bi6HSAi1ohaM45VrzNnnOZc8C8+M4cO7+c//9rhkrxWydevY+hHz3duP35xevD5cPxtjR3/4974c0x57INvykHP1XUyH/RXKsBwrGG0KhWl1dzcOnEIHgrvlUhQGoJZSa0FrhDfELvRj1w2j+ZrrUtZabSUGR04p9V2XOsm59v0upaTFp2k6z0vJgLYiM1+66AEmiIdAw67rhmiOUirHLfgxoHplCiGKmZm6lZytCiVyWtecxjDnezc8fy5XL/rbhw+IAmEvOuclEytImPOaq1UWSOpVs8FBCcwk6tB5pY8fpzucEsmrm6uhH0IUD8GlK1Uf7j4kCeOwvxn3ROJECtRaKnGipKzccZQw6BhDCOREHmIcYp+ks0rr6bgq7YdD7HYRgcFMrKSkDkCEAuTm6mou07rOidPL65fNFdfhxDL0cbffNzjT4K3rX5ogD3FgijFWaM55OU8w7zklhBDFRQjsXtXZHK4Q4hQ7gQHGTlAPLH0S0upkEXIYd1V5Hq9Jwq4/pP04kjmpMAS2+nJe5uN8zqxd398d72LoQoi11sB0tT9wjPn2IUqIEjhIUU8hF1cmc6vuTpAo7DG8eEFDnxrxPiURDrXmD+fJ3B3MnEyrk23RtpublaJ1qetaXxxeV6M4+PNX4q5rnZVSNV7KpKtWZGFSQhx7CRIooDgR66qqOh4GLbWWYmZgREYAIVP7jKq5Pd4UIQF9n+Ig4yFdPd/vnnVzd3w3n/c7/eLXL2+u0+304eP5fRj6L57/CtytK69zvL+f/vKnh2++fv/uL0hOV8N+GPrOfF4WJ9aWDTR8hFp/wWOA6BsL7EJv2cjA1LR36eny4bBm79OqtnRp9bJtaSPAyAVORInI2UDFmZoRuVBPdKj5Af/Vf/nf/Mv/7D/+53/zn14dXvzb7/70ze1X9x/vZsWXv94fdrtXrw/Ho5zOa64au/T6yxtTnqbMEBLwii4NKXZ3H051LUYF4BRCFyT0yQnVKsBM4vDqRUAipO4BgLqzOXuIgSUIhVqqFw9BurF7/wDRquogMHFR1axaKrjZpKqrawvtnIoWK16sIgIBXdcpKSlbtpqVBBCqiwuMrJXlSUic23rqW8OYM4Am37vF//6YyNFF0AmbPdKGJG6r9aXMtZWkLvjVhlF6c++7SIcTwcmJibiRFxlCxOTV1AwMiUzsJC0NhAeQeIN3LLiJFaosmxeVkYXAAHEQZvLiHl08kIpm3WSVGFGimWFBpDBXr2Ylq1ZHh1YXx4WB+KPg1WdcpEe1ph/+6TFE+kH2jQunCI+ZX8vdsIm64WJ2dTnChmE9/vhIPnB2u5CkLnQjJ2JcfumP94e3iKpRtYgN5ETC3EC67ehuW3vUdtMaMeoCS/3UOf7M+f7U9ohDtQMyk13+cXMDbILftOFzl9zx0xi+Pxh3uhgmPuayT9GP733/Dw3v00f86M5t5N874I/u+U/GwKLNe94eldqfXoJHctb3LtA/Btz2OUjwGTT477Y9hdseITlVfYptPcKZP3EIe4p5lFKaUykLC1rLuqPa9nZeetzcN1t2IiLbxNjtQgnCVogHM8cQQK7w2uhGFdbMBFrrNl9gf22ly1aeIdMGOQEsHKhZ2OFxgmiS8MSNdkROcDfXFjkyCzUompyDqLNrqbU2CAOAN5GJUhSmRZtAIQwECRIAWC1maurErZuBsVm/Xq5Zs4lrYAw2dP2C7Fxu7TYu33oD3QFsIusXyM/U2rxprRwi3Ny2Gs5vZiLCaLZeTXQZbSXXJ8/oo7LVRjFryWCbutpgNtEDB6BV3bZqBDka9PZJDG1D8EFCALxZ81arSl6cu+AN0YPDPzGXPytVNB381qNi5uoMZuFSlIkvnFaiptFOaMHcBT2kECJATplFWMQcbtmD4zEzMHJ1VyIXV8WFE4iVDA7n1A3SRCMlBg7v338nLNpwR+GQJEgSCjlr1bV4keRSWJg4BWEuNS951of68e5doOH6Zkxj6OJrEH/7zV+IrZjdnWZn7AYkXYpRSE0hhYNQjKJa1yXvhjru0s3VcDrPS9bdHvs99wMPY+x6NqPKCBye7w7rXP/+T18vR91fXUkImisUWtTgqurqnEASBR5iz8SlFoc1L0sGuYk7uWuttVbsrrTmcrgaDvvDt9++1YpxSM+xuz+ewbg5HLoU53nJS86lfHj7/uEeXcTyrI77fjjEimVZzh9v12k5jkPfDzvm8O7dh/v7hxBpHDsRKRnnaSUSYu762HVRxMddJ0JBAA6OVjkz5thwWgJCEDcXJgQS5pQkphAiAHs4TqbGITgVbR2qQtVq6ELfd/N8dhgLKowDjWlgFi3adV2M8d23PoxDQzvMdVlnMxvHMZKUXG7vPsYQiWwcOnfTkvvUdbELwn08v37962Up3/z5/bcE1Xw+PSzzrFoDusC03y/v5OHjh/O3L59d7/ubl1fD7to5PtzfT8ejO6Ug5J4Cy7jruxSAsUs551zXUok55TKfzqeh3//NX/8HXUjrXObzHES+eP26lLWa5rJWr0xSTXMpu7gLKcGslsrsTmau6oXIQgAz1CoTQO1xE2YmcyJYqS00hV8U97bJkt0V3mS0HlUYPgtcvreuE7VC/g8Wi0dzosvXH61ktRDt8afHckcTnG8qV+7elMbbX1u3aUOYW7V0C9PIHDr2u6rZoBBIIpZWAOh2/Whq331z+2yP5X453p2FGBmWXQKHEGqu66oSBYE5JocFFpC7aNwJ9bbMy+nhmJIIK6yaUs65Zu1SJyG9ePViWdfv3n54OE77LhTGWqrVAhPX7Gqx64Z+kJ4taz2X44fFFnVz6sLD13M1JTHpKYQ08NWi5fThwXIIHY3XXR8CrXM54z7P3+5vr68PQfoY4jyX7769jSmmPoYYh34EyFGdHKRZy65LfYzrvH68+9ilIQxhvAp3D3frvCJgCFAva0HRkmLY9T07SUJUKqejxI4oEfVFz9Wk6w5D30VmJgF0tx+YYb7mXLKWNa8xBHUxryQS+xhmSVWKI/Xyev/82fMQQm5q5UP6TVmtWC3FVQGXWuqS50C863dVdc1rLUixFwrGLNy5Scnr8WE93hqQS7Z5LrXWIEG43r6r9x9gyms2kImgZMBx91COd3cfvrsbh85Iq5Vx110fruSa14dpPk9u6FI/7G7W87r1YQSGkVutho5T7KJqWdeMgBCJOJS1wiEp9p0Mo0hCzsuyinmd5rlqLQYzSLTdrqTUh5ByrQOheSq2vKKt/DFGOJk1aRhXd0oYDjH1yYlqKcXqeOjX86qrO5Q4uJu7AsYMa17CxKow5nHcLfMHGJ6/uHnxxdVcjjNWBDegaK3rsszVLLtjGPe15NiNIul0On78OIXIXefchWX1dTrPpznAPl6djsfz8+ddijbsDwN5qiqOoes4oObsWqUblaqTQOAGDyRROo/CIaCRYeC1mDMjpMAcQmRxzQVVKHGjanCbjMxhh2EAm8E7dIgMkuxl1qXvxhSGmJK6kVehitZSBiaAhYT4ahgXW3TNWioU7kwupoCwgJ0ZXiFuoCjoIzPUrRKYJM5LFokEK7VIJHYiChzS9X7cX91Mng2IEg3FodVKWYotGjsZuJvyXHJZDNO6znMO/dgNQ2J/cX2IqT/OM3t5fjUsa6iuzCSBGsxqjqt9p+rLeS3V3GEKM26FTIBLXd0opXie59P5nHMhhkRW1ZoxTVMXD+PV8PzV892e3357muf5uKySaDfs+2EoNeuSTd2zVSte4dXcDLXuhoOTkyt0k8V2h5oqzBgSQQwDrAIDnv3qZn/dcTLmstj8bvp4/QZf/PH3z7/cr/P9w8MHZQdMXY8fz3/56qzGp+Ny9+G8nojcvdJ69FKKLTxPVYxd4WqbolKrkhKImJudvTp5BdodBAA0fWfTx3T7U/zo5uAWknNTqNgcQVpFg1ooSCQMQI2qg0ycjKmjXT7lfkf/+7/6NwNfc003X7y8/publ+9f/Ou//dc8v2fzt3//8fpQhxFvfnVzOi3naY7SE6U5z0Q1xkRRjcu8luIZwbxUM0LkGFLieHd7VLiwV60lZ1dQAjmUkZJEESUmDhIDmFw9z8s61Y76NHSQLQFhRkyBTarW6oYEKqxeQ4zCYurVDDD1amSSZNj3EmMt6nAJYnArRtpWU3IjM4MxsQsJNc8sskfQoLllYQvcGXS5UxdZko2VfSEG0ZPF/cLXpk1zCVvvh236tCCCkUsIaILp5GC4mBPFEAHkmkspRtIPQyd9hTaxqmpFa62KbggVmtfSRe773hTrvPZ9X0txuAQ2VE4iHsqp1qxaKwgkHGK0olqVwALp+27BmiVO57MpdCuSt2QJP0MrfxoCbVwqf4JrOLZC3eOzuqUjjwjLppjgZt+LivyCFD5+gwvT4EKGaFjUpkF+Gejlkm+V6c2UbeM3MJrkDhmIm0gogVuTGZx8Y04RtSJgU7tqJl30uWDRTyEP/stayn4ICW2mdviEbLSPeyyOPrnOP0IbaheBiJqEzuZTSailtnTWHcRbJvs9yOmHA34Edh4H8zNIy0/BW0+3f8oWQvxDXLgfReD+MTCsx0/Zbu0/9BE/xLyeILif/Yk2bfWfBFaf3iQR2cR0XS63tqUTgKMhTK3ID/dq2h5GfbyGG1QMU6MtLdlowcQEd1MDUSRiZnO15udgrqQgIKBCyQybkC/D3Zu9emvRU4ULkQgHFpYo7latYuuoBRxGxoS2TlzmCiMQg0EIgUOKxDSXhQzE3LAmZhJmMKqqaYE6zJtmFlNobeTWrLAcbjB2JnNsRmqXKQcGhKb93mT0AFwk1VW1YUbMmxsD1FTVmw8siEkUlZ6+UbYlf03Uv01YJLR5I7bZlzfOi6lekPrPaJiPbqPMl7Gae7MhRJMuZxgFDgbfVMOIBES8zdOfPWlEMNjFx9ZgcQgtDTa6YOkbdaOVRKgVYtiZC6nBquHSDlDW1VuY7xcgsgmkmUMQkoiQqdWqTk5GDjQ9i5Bk9klYYgjM7GY1q67ViqE6nM3Kmt2MWMnDhezGJEwgG4bOHW7a5lAOkTmYWllyRYlDx8FrrRUWXPpOhmEkuGotJVeug8UXr55fX93Mea14Xqsu83yejsQYxm4c024/EqHqqjVvtSkXdz6fTjGFYUzTMgthvxv6HcY9D2MPF+G+FORJhUGC08OMCbQDRXI3rNBqm4oYbRJDFAiEmEKiWEox1UBCxkowNdNavZpiOde8rgwjIK9r34+Hw176FCIx0f6wS128v32oNbtjWbFkmCIcl1xzf9jFxEBXik7TcV3Kq1cSQh+Ea0WMHkIc+mFlr5WPx5O7MsOs1rq2F7BWL6W13aBo7nJnZsu6CNgqw03YiRCFY6QoBKOUqFaLATEiRUkpCJGWqrWmEIRlHAZyq7U4EUtMMTJLQdFamfn5y+cpRjdTU2FunWiqxYyn+Xh394E5juMAUOpSJY4xptSP4/Dylfzt//Pu4f50d/deHWPHQz8SkJfVdI0i53MB8TTndx++GyK/fvPm5cvn+/047K+H4fDh/XcCq2PuQrw+XD2/eSag48Mx57WaPxwXiJdS8pKHbvfy+U3i/h7HdVoN9eowzivWUiVxGGLJ5kTVrJgSLLEguIgUaCB2L8RWHQKrZR2udkW1WbK5O2/BTVsXgEvhr8WR/GjO0Biw/iO6A23hIG7VMxYRqOulveDpjnTJILzJgsLZ8TjzUnMNbSTxR6Z662Lg6NxiiOaKC3Oj2iI0bzLpoK3Ebt6myEfNUqcAJgYruFnHOdxLqa724uaGQLXUDSsztqqmZlW1WAw9CRlVN0WFV0d0ZnRDoJ6qLu4+T4vpTF7JYyk2L3nNWlX/8Fe//9t/86e//OUbrTwMg9UKqjEhioFdSPogSWS6m8935/l+zRMwAwrE/5e6N9uVJTuyxJaZ7cE9Is5wb05MkkkWoWJLzVK3WlB1NSAB+gM96UEP+iP9gv5DHyBAELob/SAI1aUWilVFZlblcIdzTkzuvvc2Mz1sj7jnJpNksqAWIccd4sTx8HD37XuwZcvWAhLgQEDahs1Nju3sIJvDq6dD3mA3/EBiTJQIpRrevnmMQcZN2oybw/7pdNKtUwhR3dyNRZy0oamqqt7vJI+JAauqWH7wo5f7sTy8PR72DY4f//SDNHhIvOVhHFIOoZ4WZtS5Pe7nz37805Ty6TS9ebt/+3Aia/wiDHcbZjL1nAbzGlKqWpwZQYqWRbG0tsnjq1ffPOzfnObHvMEmp/sXNyEVQ4NVdycagpAjUopAeDo+HJ7mam2zHe5e7Gpz2CFIDjFbczOB81L1vG8Pr+e3bybvRYIVBAyDjymIBjRAQY3hXK0FCYhIjKDezr6fluL42//71y8/uEk//skwjjfbW6vFzXMcxmFkLjDU1nLecJYyz1onVScNTkbBmA2XwA6EPKa7+00aMM/nZnqcTm4+d5qWgwgc10ecuBu/GQnYSaJwgEQSDiEEImnVWmvq5nCJCDk4qTkM2qzutjstWpfqzZwsQMz6FIyiCjazllKOQx5uM/bADvcf3eab8Hh6e0xHKJuLmrdSiF2bEsdxGH0YS1UClSrzNBvw8YcJKZdCy/lQJ0eD6wlWznO8u5OXL/Jum25vo5dKjvMyi4MoVitd19LIKTApL0vJKeQQmURrX+i4wWPgLDnTCPA8z8tSWoPEtNvsUkgEqLeqysLbPAwpz62eyrzUZmwp5KZG3dYMXtsCIgRi6uL+JD2FCsoSbRx9UasWOSYZhpDhZL6m+7pdaRIE9lVIvGPmaiBvpc02I7pweLN/PGkTD9NhH25zsxIVkS2gBacMzsbUkIpJDGUpVlvQllmhE4qPQpJEIsjDUYs44iY3d3PrPqtqTVuNQc7naTpXd4QQp6maoTXwao8DgNXInWutS0XomgwSxmRNlblWxXY3pEGWpvQwF3Uz3tyEzSZNkxZgmmongMINZkQSh6HLw3YXG3fUWrRRF8iEaSuIER998kIkDdvh409fxKRzeVjaqfJp8wKf/ezlR5/dKtrhfDKXcbOZTu3LL1+9eTV/8ffFDa5p2leo71JuzU7Hk50chRkJDoYbeQBAXdww9dWo23Vpe1k1d0yhT0x0iSJ6zAH0uoxeEUEMg5leeD++ioeQqzszuIck6PLYEGWqJ3XrTuX0b/71v/u//uav/tV/+199+p989Cef/jQE/uLrz798/au/+/Wb3YuX4ya8eHmbsqiXw9NhHI3YDFWSLXomK1a9Ql1gXA2sYAURqNosKbtrLZUGpQZzlwARpEEouKoSPJAY+dLqPM3z2SQLM+1uh2le+jRHxDFGisQDl1itKEcWISEh695WZjAZZLwZx82wzEu1pq6rsUm3dGxrWSVpjygdrp2A7Su/ignk1g0Kaf3bb5hf6k5WAybQ2ior/LD2o47dXNqvm4X7ig6gQ4vE1OdrYoCJhVkYRCK8LCtlpLaaEfOYBaramreY8zyXwOLsBI+JN8P2fnfvirftAQZTKFkXehm3m9vxbq+Hh/kxp6Fa3Yxj57KFjUzHc4qJCMIcPPTyY3Hprk2m+sxE6xkKdbnA70Q33iEA/h620eGWZ5E4rcWFZMzS/RN6/eA1pn6+XYhuK61tXVQ9Q3OuCM8aJfXSJSOHQy5rootwnBoILjl2eX5iIu92T2vwtwLCvrJJcOV8XW7Gb2JVdKkQeu8mfNf2nNjW91G1b1VHrj3XYRfZU0KnWF3KCUFX5tr12bsqZHUw4d0zCfQQ+FtwzfOT/9br59AkvyN2/WO2PzKA9Tt+e30cn8N1f/Szwu98gH7zze/c+fnVXd9cCTtdKtQ63bFzQbvoHUG79p4ypNei9lrei2EFCOTkAmmmHXhCIJHIQiBv1twdXeBJYa5uqw4fLqEOenmceS9g6zFPL4LvOReDE4xhYOEo7Cbuip53gFFXYTIipl5VYzA4Exk5wQ3kBHVtrl2hyRlgFuYQgjN6jVvTvughJhHi4IJVt73busIr1DwGd+6oy8XL4/nYd7355uAua9XRKGZiMvMLnL/u/gzX70mMlR9N6HQu7l4s3B0m+iKJAEi3Ju1Hf7/l11ZezVnXr1mR7o50XYaqtSNfSVzMK1cMz8bbXmb8rBq1T1fXkBdrsuIyihG6dysMpD0iZmHpBZKqSgJzWylh60Nk61cSOHCIAu4GJOpmECg5BTALUxBhWUuyoT3rYuQQMAGxo5ZevZmZG6x6NNem2iIHhSeCwonJnVxNq5k5RIjYTWtTr6aqIaQQg/TiLPj9B3c5x2GTOICb3728jSEIy7LMpS6lnPOYPvroQ7hP03kpB7Vm1mptpbSUtiHwuEm3mmKUFy93ITWJOgy5lwKKRGulaWMHEgCIgBkcg3pdUUEHGGauVYl7CWQMMZprB4XdzRQGAzt3tW4GEbRV1RIi5xxCEE4jsbk7MYSRoixLMycJGEcI4KBlqfv9ISZsxg3v+HQ67vdz07INu3EcUlrxESJWa2a2zCcWFgGRhODzfB43KYXQvZLN0EohtVprbZ6SpBCYmEI0MxHOzFGYjTXw/S1Slu12t92OIYRSSq1LqyoBrVZmIuIYcmRu7qrWWqm1uSkRbbZbEXHVWgsRXM2Mai3uVkrphLh5OhPzZjPktNtstiKhlpCH/Dd/92/LjHlCCGB4iiAiA4OpGT8dnphSHnegVJZyXr5683j48MOXH3/84Ycv71+/fn2aJpjf3dyqKocwpkSuTYcQYgj7ZnSixV1SDK1VCSEIDykrUwpJrTqcwYJIoq3q3MpSFzAi505EJTKBgCymsEuQIRVyFmF3bapWV/koa+gYd0eO+NKR187Vh6oVyOoLVbpY6lyA5HfaBOuA8R3zzTrur5PFFd96tkjzy1hznWWAnvLtjFK/Bi2u1syE2dysrQPOeqi+nunfI+F8PFEABC5As6VBIiKLL5NVvd3eu/kyz0SAOuAxJ6qsTQlEIs5gEvc+pnsXk9OmqECCEGtrh8eT6SIytIrTcVaDh9M/dzof58MJYwiBUxCGLlars4trQizn8+FwOD1Unc1noDBmg8Xog7YCUvNWjk0fbX4scRNkCLtAY0y8CIFf3NxB58fH83me9oc4kHVEAAAgAElEQVQn8K6PsdOMlDS1ZtWqNiGmCB7Z0QhIKUqgJhoHVJ82w2Zzy/cfx+JtUfziP//54+G1aQGGzTh4qeeHx/mp1EN9/Yjd7dYmf/P61Vdfvn77+IS2tKV5bbsxiyBGN9SmrsRG1ADV1tyrzael/eqL//BweJzq48c/eDne36nHcj41PYaoRGEc7qy187meS11qnU7lPJd5QVnOQ7q5fXGX820KAxCPh/n1q7fTeZ5n3T+V+eRd0c17Dl3imG8ij/BqGszAYBBpaxxiYI5Qak0CNrvNuAs67Z/e7N/Ep48+udukG99V1zZPC9nxfD5gB5gVL2KkvsCs1dJQ1ol4owCpKwRgjJswbJIEX1QEog51VQcRQkBM/U8gInVNI0ImCu5qTioRqdtqwQEXuK0YLWKCRDY3U+0hek9bci/o6QG9Echd4Qr1SsySBoo2twME+SXCnS00PZ2fZqipOlpTV0OA+OpQTEI81SIiLMIMIozjmFLWqq2KMIZtJq7HqTWttSEmS2xijd0DyNQjicGYKYUcgvQ7L2xKbRy25Dwv87LUHMe0uR2wCQgTFtWTG59Op+P5bJCQhsVqDoE5BGbmIAjCgSkMcSQK1iZAWSQyMYkZqldX4tCUqoNsJUqsPI9A2MREu60tGOIYOSUemramlUFCxByJAnPDyuEE3KGWUiKJUkuP6Ih4UV2Yia3UdheG2nxZpuBtYB9FMig0XaZlf5xud7vgJpG3w4ZDlJiU6HF/1FLaXBme2FmwmJvD1ViIiSWkwElVmWgzDsQSQq7tsRa0ar3FCRAmay4hbMaUMsGN2EMQTlJKqdW1uRFzSLvbAEoU7HCcm++rqmIBz3EjkEwVhZsBwUPgFEjAzk2YyN1n8lYrTooMDMCAuEO8kz/7xZ/d3N2QVLX9eV7ePj48POIX//TFzYc3TjpP1T0Jx1Lk4e3hzevp+IQ6A56sSa01EyQIhGq3CXc2bWzcF9crbLIKy/p1jnlucLdCVrwudNe0SPeyez7t0LsP0Iq3rI1LFxKWO6gvXhwAxLlWc8DnSlGC0XKY/9f/5X//8Z99+N//j//dv/oX//KHX378v/3b+deff+HWatWmi3sLgVhqTDRu4+m8VD0VK0NEHNmFrKE4qJr7UlRNF0Sn4DDjkQLHWYst4ASJCBsOWUIFhN1bWeo8L7U6GiqXZZ7HzTDXmZlEUh7yTb4pXKvX5WlZzjOCW1NldQHc1asDklkGQaDz8dzX5NbdBtf89GrUy8bdBEXbGmetFCtyp+7p6dx1Jr1DBtdZ+1ur/gvbY81R0dqAuCSp+k5EvQYFgLMzE8iMnQjcK/gFIuF4Op5Pk5OTwMzODErMkVtrSk5N3eBBUxpFJHMY43aMG3XdpO28zLGT9YmdfTtsbm9u9KiPx6cQQ4wx56HOpZkj4rDfxyE7tGvexRS7v7bD3HukY9AecF3CzC7D8jwkexYmvx9KdxzpuxlJFxRmBfW+m5f+/ubPkv5rqdAlvvOr3eH1OOuhcYkfv907DAjXpRMIILMV/VG/FIYyekQGf2f/9/vP8/fCIO//su9/XQG+91l/9xT1FyLyHce5oFl4h8Zcj/Luef1t6NV1+x2N9VvBuO/BWPqjAVh/6Pb8+v8/QLJ+95n8JvyEf9RZufu3yl/XSl0iXoug3+FZAAzuzbo6ERH1RD91bUAghMiyeuV2ugwZxyE6uZmuQLJDteNNHXx1JgJBknQJKmWom/sqO8jU9dXROVgOcyIjFyiEQhYJrKFZMysKNbcesxhLgMF1hZV6RqGhWYP1/RjOHlNAoiDhIvnEDII2rAQXYhcogZwRADgU2jOnYDPqQVTvWiKEi7/es35uUG8O7WIu7uTOBuv2x9bLIFXNqDEx1HjlRxFFNqyTPoFCkLXRAL8A0kQE6ZZ0a0NeSHz2joy1wh59hXAp21npFOTu1Ct0HP19IvKLX+F7Dx6vIz2u0lrkZN3sHuyEy6qEnEHgnjEF3N3U2EVkZWKoNVPEFPqtMr1WensHaIiIWUSEQ2ha1hW+wq1VdWKWKMZQluDcNfObXgsheX2c3cchc94AFoi24zCMGWz/8OvPJUhf1Zt7UTVVVorEIG+Leq0Og0Adi1QBy5jGlHnMMUJRHw5vng6P5DIMY8p5zMMwjvunp+PjwWtpW43DGISQuLZpmg6nw/nNY3txTy5y/2K7vQkxYbMNLKh1SSGlNOwfT0OOSHj1zaOp3I3DudbDYe9H2KQsgUAOtV7GD1ducCCSRSttqVrNVbVp60RilsBRuLl+/Ol2czsqFGz3L3abzXicp8W0laLWaq263cYUNpvNstSZCgtCCBKDmT8+lrt7/uDl7d39zTRNrf2KOaSUhmEYxwFGRKE1a7XWVlsDmZmBYEK+FN9uebvdisRaq5ZK1m0hzWuDuDgTgSUaKbELeRASEvZ0e3eT05BSIvDpfD48Ph1PExwpBWJPMUbOWpQ5NqvzvLiZqzlMDcOwYRKwN+r1ClA31TaXCcDLD1/UWt+82UMtxnxzezdsdo9vj7/+/PPHp/Myo1SI8DBKHgdDKMty2C9CEOalYFnKNH++GYbNON7e3i6YJ31zmJZvXj/c3Wy5anM/ztP+cBhztjyQaZCYYrq9va0VjLQbOYR8eNq3waLE27sdub96+9X5fJ6WxQKTiBkAGeLYaa7rmsUrUQDAzJvNcH87eNos8EmrmTrU3cjdFXDl1cwaqwcrkVX41RnILmgoXQhZ+O7Z+rqY++4p5BnZe/3Z/Z04qnfZ114buL7TdzK9JusItKokmKl1sZyeemdCj/x7fsA7huzDdqPUEJyih0gcydz04sqy2Wy2aXN4M3E8C5Er9UJqb0SghsYsYGIhThzHKAmNS63V3QKxqlJDq2gLyFspOs0r4bE5jTe7ly8mndmNtsPtbreVXIeUUohJ0unp/OWXr+qjQREQSWOtBsspbU6PX6Vx4Dio1joVPdV5rON9ePHxzS5ufAYRfXj70Wacib/6+pvzNJ/GLTFrSrjf0u3N7WazI+JSzZoqtYYzCYWM7W5MkZgWYZ6n01Jxc//Bf/bPfviTPynLUm5u8pdfn47H42473O6GqlqXZT63ekZwjJxOPj08vHl4fJinxVt5+9a8LvjoxScfvzicH4ldyZzJAjfFXMvcpmoLFjvV15zK/d3w6WcvPvn0ZrMNp5Mej5XYh3Rzd/vxPO+nZf/wMJ2XEygwsdtUFjIdX9z+NIShVjuf2nJ6/eu/e3zzZu5E71YBEFOIMXAKMeYhbwIPR2kxwI0pRKbUYmImJ6vzrNAY4icvP/mTP/3019/8zWk6PHyz3415HNPL25faFhYtdV6W089/cXs+5GlPx8dDYvHR4QbujlcYNqKmnBg7xBjzToyaNmOSELPDScWdWBCz5CGExCEyBWnedrdjHgOgxealHSggRQ4i2rzWqs3ARuIhIo9pGFJt2rR1aGOZl1bNHAxhl77AIGd2kBmRmhXzk6pOj/vhI/zs5x9sPgrHut8vBw9uDdozhoSUOIbEEl29tFKLyRBDCJttykk+/uCjVst+OpVqmzAEydYwldpmMOPmtgyRhVQICdzIgjcx16a7DY9hKxAmSBQEcgQQhxg4eA5ZgYeyf/X6zdPjIcX86Q8+3dxsdts0lbaoL/VoU4sSNzlv0iZ6grUgMcVhCKPs4tSaguKQzG06L7W1EKKzG1oFM7mzNzWYMZq7B+Nd3HBMmcfMA7tQUzRmliC96lLh1GdK9l5w01gyGBxFuqw0CBKqiDMX0mNdSjk/vPmSlunD3faHH7zc5FzToEtZppOlGIi6xiQzMbGpeW1oLRDlNGYJpSnNaui0chZiCQLih/1TjsMw3EiItenbN0+mKgImuPXcXQjEQcaUk3CsrVYtBA4izSvQQOCgBNpsIUE4CkWolhCgpFw9kIKKWZOIABLzJPb4xeNqpyHgKAwe7rbph8O4kY9/+OKHP3qZxsQcgfDq8avPP//raXnzwQf4yc9u/8mff/LZP/tPv379cDoskcebzc2bb14/vd0/PdTzHmWBgIhjA0cJOUqSVIsSVTj6WOne+np6TZKCoPC1tE3fm03IV9tuAgh0KUG54ibfGdbQhSPUUxC8ru8VJLS6Xzs5yBGIFF3ytlUHFXD2X/6br/6n/+N//vlfvPwXf/5f/Pk//Yt//ot/8tXp/wwCGA3D+HEcmR9bdSIlrsTh/p5jEDOkDG9UJbSpldmXubYG2jDQiMKAEDZBaykKi8i3CFuRDGFS9rkt53NZzkADBKp6OB5298OK7VKIIQYhRLHYZCAkeEM1dZ4dbqtEryOTB2/eylRWVzcInMmFzBzap11TY4c7dezCuzTHqnCF2OEtZ3aoGTvbyqtab+275ulJqssrAFgd0kFEZARmuF0MswCCs3fWAuAQODvEOTIL9m+PqJfkE7CUsm0mQVyRc57nOcUowsthqWoD4kTl6+mb+VyhwAQAXf8LhPkw8Y8DJ551GmQch0Fb7XoRZlrOC01HJ9zstvf396/evoVzL+R5V3dl65258IB+Z8kYfRud+X9te0+AnC6Jwyuaw9/xxfSMNXJhIb2DdAmNtKcxjNZE3YXl5wSYAAQhZsi1+O53lKP5MwLU78YZrtT79ylRK7Tcz3Nd9l0C58vXI8i3wT6/sDqef3W/P+soQiAmYbL67XD1cp/o+tnfhmF95/X+XkSsb39MDaw/dLfn9+I/yjl9j+05EvmcGnY9pd8BKP7mdj3OtXXd/VpigsslhxDMHJ3C6rza1l715Wj1F2DmnsgnMFyZmYS9EyBU7UoVvny5UK9V63ypPgfBzXqhsqk7vJOf+mRmHZ9w76XBwp1yyEKBQiN219UjsT/0XdH9yui54DbNySkxC5Nwz/qRuVXtLBI3R7vQk9zdtUtggog8BMDYOkrnDWboUE3XGF4xvX5532q4tfd2t8KOirtfhLB6Lw7h0pJ8cZAE1NFau7bFO3RsZYFeDA75nYjb9f/r89DLSPvtWp+iZ0+JXzIGdE2v+DqLXTIuAHopEK3kOBDRRX75XUoA3POluKaD3N21Napws04+YxJrDhgHcTPoM6dnWiXhRdzhZk7GRBxZDGiq1hTNjSmF4F0/ja2XZFLXUuiNBXeQWVvOhOLeGsFqPqcUQIA522qGo2bWlBrYhQXazFEtuKTIyY3Mis0o7BS3MUY5TwdntKrWfMhbM1vm8mpppdTz8bg/7EPg437O4yhRho3ERIToENMGMrcCtpQRMyTWIBEeg8RhGCZZtuMmwOZdI6QUtm9fPTw9ncwwbIfT6zmA3XnVfmDuVblk7B0RNbNedytqdqlrEUfBz/70s/v7m9omCXx7u0spPRweno6PvWNNE2KU4fZ2G0YiPD2hNjB7Ig4hOlSbtEqEGAMIsSx6OpXaTDiABJBavNfHECEISVgNx29u8mazHccts8SYPRm7eWkllCVPMYack7lrq80BaABnEo4xEH/wg085iDU/n6Zu+a0VBEFgYhnzNoV8Ps7zcmrVQ4zjMCD4PJ3P50mbjnlgQq2lr2bcvWfXRCTEyCLjprSqJOJOrfk0l4e3h3/48mkcxpQoRhmGFKPUZVmW1hSIkkIa2M3rtKh5KzY3l7m2qehpWoS/+W/+5V+kEDITE7193FvTD25ut8MYxFuFE8M9pSQyuNF+f2jVbnc3OY5MmPanVkopCzzmGDgO6HSMvk6U7sREBOrID4uIxOpurqWWPsZSt+zrOgl2yT88zyM9S7GCrgrpl3Hg/fTas8HkinV9e/549+9l5dW1XfpyqR/BHD03//wsjK6TRbeZYXYzkJvBuxo6MbgnSTt6xw6AmHleZpBBuzkuuFekMJgBRojMUUIkdYQo5CjzMqZNGobzNDmziToDYsTmZAYvbYkRfdKBmXAc0zjXMM21Loq2yky05uOwvburZ6rL2ZkCe6j76tQ8SdwQzSKLRKoAUEEKgZhaOxcsbqSBAseBoxQsXnQ5tHLbTE0V1MDs2228e5GWet6MYbMVNdoVaaq11mVe3LksbSnFqCAWB/KAVpcgHKOTY1lQdUpju9ncthfjstgXf/+rz7/4cp7w4YtTFk8IQwiemm2xi0gIR2/uuh1iTkFrYDdCDcFvbjaPx2+6MDAHYo5mS1NtqBSMo23vYhrz7n4Y73xux2Xvx/3TYX90ayLLbpz3h2WadVp8mj0PadwMw/gi583N7kOt4+nQXr9+fHw7vfr64dWX8zxTDAHwUtrt7Q2TMAsRSwgxCMyqzlWrVjA0Rg8xAF5rMdcUsd3kcUwp5oGHxZYyt3Kqkfz2fkCOMcjDm6evvv4yxuRU4Ch1uk5SICADjJ9+8qKpsjAzO2hZlvN0rE1DjEFCF2IzdyKXGPI4xgRmJ4aTbm6HELlVU6rK7gESwOIUpZFOS4UjBgyDpBQlBF/TRUZgLc3W9ZGwkzb3hkjM3XqA3dpUluJuqLj7QfrwR/f5Jr49vpphm5Cstb5IEWFBDBIJXForSzE15iGGwCENg8QoWmFNySSE4XSowi4sElsUBBk4Dp5kXuaplGC+4TBwYK1J1LMbTCgIRwI3JZEcuw+U2sO0P53m43Q+LGdphR7TOJ5AEocd5QBl0UAOY1SvgWLTWquZypAly8jki6orWTVtvZ+TkzU0wDr+DHaCQtWaukkgziEmSQKBUkDsLoWho96Awsiug5M3N5gSMzFCCGAWkXHcDLwsrESylPm8nN/un3x5SmyffHCbh3Rzt6WI1rbNTGJQwzQv9TxV9dJsUXNwHoZxd6vu5/PSXNnJzJq2pq1MtZlZ6zIQgSkJOzwS8ZgDiBnamjMlBLbms1ZiBxFLFhYCbcbgZG5UtdVa1UyipaHeCxOlGIeytDzMh6WVWt2QGGHw6B6ZTvdQhRlS4Dxsc85BhphyHIHBH+bX5djO53n/MLHQi/vhg81Hu5uyvbFhNFKQRq6uLc4Tvfr7un+cVdkqAjgwm5ErhIVDYAiREzNIr4tBv5B3OnGuu/R01u1VzvpCJOmRSLcGfzYTrUaDvwXBury91j+QKDV2OAkxyMkvdVPoCWhjVHf4dju0UM/ntv9i+Ye7N17i9sPho/sfVjqqeYw57QZTevXm0azGQOOYchZ1lKWWpbqQuFaCO1TRHGnsJ2NMECDdojhCwnjPYQsL1U2b19a8VqBBAkIMgSSQRJYhpxBylzs3t6atlNnQJIMYNqN1HZWIHpZRgrMvpYBBEIKQETnBACXzriVM1G1ObCUvrwqWBDDcjFwuDpXehcP6r5+vEt7bns3fdNmlZ9b9kjpaSVgkTEZCq7UhgwMogAI4cIdTEYgCnHyIQ5ScQ7KEYcyuGIYcYijz3EplC15Rjoojchqc3GEAuVnzJk20NmcwSNFCkqlMpRWspbNwAgQhyma70devyNFaM10ZBiBAuqT9+oB+O5TG9yJPXe/PMynyNU///YPx5/F7j9GIcGFNPT/CBcR0gK5GjwC6hNx6hGsx0DU9iQvH7nIMIuqelP3FKuXuz0zt/pFbV3u4bNb5F1cuDFZ2X9/n3cVfJ+Lfen/6pV0u8D1uphPxdUTB5SZc/312kD8Mt/k++/+RRdz/WN/+j9vef8rXktFV1f8Pv5Z+hOe+mP0guk4ePbwFAF/l09BL+9fxilf86pnJpV+DlnU0Y67azAzWwB2bIOJ+5p3qbhc8dY2l3g0uDFymPn9+7XD1pqrRWST0dDqxEDmpk10U4EvvmVfBJ2JxgBVOQiEnFkHnxJq7t2qqbq4XEpGvJCQ1IyNjrFSxnl+A90USAsiYXAgCkMHYu9LUhT56edKud9VVm7t0CH19D+vs8n5v6BduV4BcFUSmfRnwbjByuHlPtrw3BPtzyLkHoKtFHcztekeJyFWJedXF6l6qnUrhqxLt2qDSP30FrNATAdS53rwy+PhSIe6GXrfvzdzQzBjCzE6gQOxMQkyuWB0RsToZdj9IM7UGM1cSJ2YBFGZGbg62ZuJwhxJpX7cGC6UpFIBxL0QyiDEptdKsVa2lRlKzlIO11iV31Myb8eqq6QY1UhaJEiWQopWyqBr7IhQAlh2DrVbvsMh0Ok+nej5Oy1xaRYwEpVfHvfs+DOHDj+9evNykPNzeGhGm6VyWAvZhIDaogWlkjwJmoxzHMY+BUG8MHl/e5ExDoofzecphc/pq7kaTMAITOwsxBecgwoHIY+eVMLjWgkbkFNbg/ic//XHK/vR0DpFjTBII3EUhICIhKmjV7GfmmEJsjRlqqtbu73atlse3Z+bosP1+XmYz7eEcMydtVkqtpQEIQXKOMVEUipG3uzHGWJZW61yrCvEY4jaO27x13AaRkISAZZ6XWtxbzmkYsghXtdvtrqk9HQ/7h8PxPGlxcUoxjTGT8G7YDWnYP+3fvn5Qow8++HAYtsxUazudzvv94Wa3DRJqrWrKpg6PQ0opNNPzPImEzW7LFOOQnvbHpeA0zeP25rOf7B73izsBBqJmRszb3W63Q61N1ah5zM5BCHEquj+/yTHe7jbbTYLPc6m32+2L3UitTqf96TRvYt4NO20+LzNLbAqi2J/xeVqEpcYcORJTbWWaT6fzmVJ2oZijqh3OpwCJGYgDETFRL5J0N7i3ViYtC1nVuupTdcZ+51fh0kcN78Cr69qT1szj2revMYNds9v9I/3t9473rVkEl7HO0amgfZwU81WLS7XbWlx9XQEHxB3rOkaI2ZmZzVxNzXyts175XXpdm/SHdhw2iuJikjkkJvFq2tAMiCJLLVpt8QUETjBzU3CkMIotmraDkSupWnNrXhsDGpCIJbpEDkGCSAx5cZqnRYuDICnw2M7n+e3bx+PjgSwzhcPDEbMGo6XWOWrbGdyEOBLmBXaugU0QCbZM5cXLD8/zcZomUQmDhCAVasBSFrVhSInYlnqSgHFDn3w65JzHIbVmTJtpqinGwKwKBgeKDW5aiOGKaTqaeU6eB9o2oLmExehoqzF2SwFpg8A+n455c7Pbjry0mJPOZ8VyPu7dS8pEzbSUpkttorZzWkJUBFggMIjci6sYJWKhNMa7j4Y4UkhmPE1Fu3GfedaatA1/+Zd/c57rtBxO52mel1uE3c3Nyw8+HIYdEP7hi8OXX7769a++eno7L1OrjXMakmQzW/RpO9y9q60zV22AS9CYYYb53BZruyFL4Dxgs73ZbPO4kdP58Mu//uv9YV+1hOCnwwznjz+5yZmZ+fB0FvG7l7vNuNEP0o8+/USIy7JY93TPEhLHXVcvYDCVpZS3p6pzaxIjEwdVXRatrXFEUOm9wqwxnEjTJjMDgryRTRUO3evKyEnM8whTSETMQZi60CR3DW2HmcOoj8HuZErUlIhDDGAy9gpv2sDAC3zy2YvxLjQus89IDg8wUi3anMwQjcyZCWqkJoQYRJiX6Tyd5+Nh72rCiJLIRXXRqkzKgCpCSOB4WMp8ntt5zg4fxzQmjjnGzBC0LkYt6pxkPJfyuH97Pp8dFIK4k8cQtlt3f1xOj+UMltxaGsbNMOQYYFDDojX2TtkMNrPTZhwSJ5hPy9yqCkLXdmzamuoCCCGyCBHDeTXA8SSSOSTJbMENxCIiJIAbrMHZHGbO7FGuKxh3ohBjCmTszvlGdjehtmmfYpj1WGoBO4eAYJW0sXqiSDlxOJ/mcdw2cztPXnXxWmxRZyOZmmNpJOIUQ4jsbOZnPS/TtD+epnmOOTeDtnxzm3Le7HYvtGmQIBxLadNSTcmMTvO8LHMz5CHvdruURgnebE8MCd3XW5vUJJSGaB7dSCSIDB/ZTi2UxctZyTh4hLIV/uFHH7Viy1xrc1sruYYwbOPohuPXh9eH0/F4bOXUx9nb3V36wY9uP/1R3N3Ev/3V58PwcUL64ouHL375dn845JRCQEAkobMtrdS6mJm6ajVrixuYYiTjzoZY42xCTy7A0V26VynWS770An0Aa4KiB9+0yvS4+3MCSp8QLslRvAsU+kp5rTcFsZv3PDO59QjBEftq//RU0jYNQb7+9en4+j+8/fn5T37x6c/+6/uz+ps3j09lurm7GdNmtykiYVpmFoCCuaWUWiZXozHWyaao59xKI8pRnVrV2mbhsH2Z007HId3cjw1qrDCDdiFYUMSQQ45jROykpRSCiLRqrVZFUKtFZ6eWd2GUVOc2n4sZYo7NrLbGmSmg1cZBxAUmBIbCFW59VFpvTvfFYgcR6ZUC0+1czMkI3ptjFSPq99c70nyJ5+gZP2jFQGxdDPRGXrVGLhAWdUodoyMkECcBAoFXsOjKYxAWEXF1ax45s0owEZPsKQQpWttS61l9chQwCTmpNXj3UUQ72/HxiA2FFECUNrFpG3RYzos/Kx8ptZ6mKaesrXtZGQHEvD572iGeFe3EykV/Rgd599Pv23pK/yL4jhU0+kMC8+s65/fQay4Hpq41TSu/6WoK3YkUl/CTOrba1eT5HY60vri222X/K9nquy7x98Eml8D/WjJssFVQ6P293vv5goc+v/bfQBSvIOplGXk92MVr4HoV33mqfyhI8n0woj9mCeHve0q+Y+crC+Y/1jl975PpTwneb7Prb79PU12fsytJx9w7TQlGuFBriKjWC0dm3ZjgDFk75zpbkSt6jbtr34eFpHaExgDGyr2+TFr9WVy/lpydbXXaZWLqQc310piIhAiGFcNBM3VykbXSBB1K6+qqCNXaWn1PQWhlfoOg2ihwHJIR1Va9GrmbX6rPuqNBxeUqTFwCWEHtwouEm2sXAO92eT1m5M7ANVPALiM+riAg4TLC41IE2Lvmlby0Kh+u73e4qseAfZ6orb1rPF/l23Hhia3uDJeW7V/Zm1hNL5muixSf9Wd4zZy01kIIvAL/nQ/R713PI+Dd33cX1Ft+Haq9t8w7ucGVnce9lIuDcYf81NSoN6+wyzMm2MoWIW9O5OZurVkX9VBjAXG4TMw96hXVatq4dfafxAioVapEJMzQBpi2Ro27G05kzmxZMdwAACAASURBVFH6+lfN1GAO7aBbR4I76tZFsJspQaGmYEartsyLqt/dJHRNIaaY4nKsD2+f5vM6iXSZEG9YKhZrw3EexighpZTv7vl42C/LHAKHKKzuCxpUbEe6TKfSilultti8KFPb3Gx3u808LaUVIR4kMwK0djyBsYqNrY3gEOmuzsSFbL0hAnZUu7m/naa3S1uMzEjFRULPlSFnEeIQSK0RQkxhs8mmrgoz0+aEOJ3mupwlhBB4nqGtpFRzTsKZKMzTfDwsapXYUgwph5xDEApCKQ2ttuPpeDicS6ljyj5ub17kXd5KZBHOQ8op1FqWumgtIYWUAoCl6hjzqU3nw+nNN2/O02INTT0Ls4e21OW85JyFQgjZGtyZiEMIMaYQAua1Y6jqssze1OEjIcZg5tNyHodxu729u30xDNvHh79/8/arp8fJDTc393f3G+Hg3tPdTdhDiICfTtPheFyW4g6m0BTNQnMjw3EuS1vmNr15eErC8uJuHMcgRE2bYpkrnM7LMuSxqIVAgKSUQwgirKq1VidKKRKhtWYA1wyp2kxdZ8kjBct9mII6NDjARFJrm6s2WZHfS99fuxIz8Gyify6od+1sPar79sTg7732K8fyu6aQ5wPOZUyn6/LPrav2rimId2fT65u77CETuwQIrfkLg13KmckhxJBeSX0d0yRI67XrDGJ3cmIXpiCU89CszfPMScZd0lLVgIxGdWkwUQ/Wx2mHgaAwCCSAyGKQcTeMY1a1VtEqtBA4xpx2t8N4E2vRUts0L2xo87J/nHAwaMbSQPVhDJsUInOiaFQrIbALzMFJZNwkRfZyqdMQsMAjmhcnk8TVl+MyBzKO7W4YJAQmlyjDePvlF1+7h1KLK7lRlMBsFHNInrIHYfc5hpQT5EYChyD1PL2tc4uye/Hyg2X5SGDkrmVJgXPcZvWEoZyaoy7LGTDzej4fHh9eQWfcbFrdqZ5ZTMkUbkRGrXipXgyV2IZtfPnxDUc9Tm9PczEz8siUmMUIMex++csvmnpryzyXpVqI9UPK2+3LIMObt/u/+9uvPv/8689//fZ8BANDjkwhSCQ24S08OJp7U12VXWKkzW34yMZa8Pb1RITNmIecUoq3d2NMXtt0PDxMyzTPCAEx43SYzJ3wiZuel7NaGTdAozFvIt9Mx8VbqwoWpBxjEon85u0rVV1M3dFac7KYokiWENVwPs1zmavpQKG0WqpUU0MJQpKtNGdx5jDskjPzqdbFymK1NU78YnsDR6lVSMy8ltJd6JhYmzPFFWZWgjGZkhKxsDIpiE0YGjDu8IOf3fz4p5+0cNqfn4xL2iQtZI2sUtcd9V5+yOCL2c2Qs5mWyeepHY+P2+F2M462YDrN1rrwnDNQK7RqVVtQqpszMkUKERxizDFGKFk1DhwkuPmXr189HY5ffv318XS8ubv97LPPtnc3AzyVpWibpvk0nZtqMI263PvNmGJ2DgppCBQDRZEIhTbTZjFy4qDkxlBRZzfoUpfWilqNwjnlFGNiDtoiSwg58BA5MHpCjPkaFvtaPWYOVSM4BD0l1pdjTMLkBgVJCik6L6dJKJ7rNJcpD2ncxfFm45EWL4tVY4uRTFLIW4ZXZw0qWLx6Lw1dTuXhWJhF1VsFUSCiuczn0zyd51JwnpZpxnZ3CiHvdi93u/taCoNSyimp+TxPVau16stSl7lO51oW3W1bHsNSn6j707GXWoks5zyMAxPPS61NxyGlPBiwzHU+GRkHBJ1pOXvLbCq5yDzXaVqWZZ7K7GXeIhofTuWxMdKWYqY22eKHtPn4g49v716YoZSp6Dy//mr+63//5a/+Zr8Z5ZOP7vIQUyIWms5vrLUgNKtNs2Gp7EGQRKKzg4yYydfF4YqArFOBma1C/Z3SSJ0mR2vLscSe1OVuWLMqrL4/NxFcnS9O6R1WIay54I5vKXfOkbsziJgFZr3UoS2taaMNJ0nL5H/173/5V3/51//Dn/6X6Y5aob//4sv4zeNPfvrjIQ/jZnuczkuZOATAU0pu6k2p8nwqp1TSoIuScmyg6ThNdRavLz54OeS83W2GTXrYPz4dDxS6fRDFrMTIKeU4BAQhru1UlsW1LpMSudwSuu42XBLvbjZaFGLmnIZxKaVOres/mmuvSWEDGtDI25oOX2+aAY7O5yMQcQ8DOjOJyIys+2StvATrpFCswd8ltus3f5UxwRqyfIvY8mwp0D/UwzhhJgN31XhaTe/CWvzphBBCDLGV1prmnM/TssxlPpUy1O1mGyxNx/PxacbiGRtaGOatqUShzIJYTvogT8kiRbZuzk1+Nam8LmPmMj3tH3MeKlRVjRlsHVHtiQS/qoWuD9B7sfPvB6EuZMJ3cRI9C5u+H2Zyzf+tOcZrUIRvH+US3V/Pa8Wfro2xAj50yVbShVXXY8xr9AlHrx/ytXwKz4CF38RG/JoFpUvg990XAmYSkQ5gdajETJ+d5DuY8BKoruywLoh8RUuvTkSXD61fbVd6zeV3ZmBiPLsPzzGQ6wG/V0tcPt4/cpV4/20f//+NBhbeX6b/cU/jOXnqW3f2e6JXfc/rc0YX4GTNaFzbvh/e+NpPVrzMLzB87wi9+wvhMkcBxIGZOHKovW7OOXSgYMVdekrGTN0c0glM3fKvywyIMLN1Zcc+rhAzqRO7qqm6QbkxyCHeRXfE+jkygQoxeK2/EQoh9l5ZGhETx4Cu7e3GDhjYQZfCvXlaHay8k0xCNOHQzQMdpqqAaVunzrXbrJNoX3O/w5J7VhWAgpmF5f/h7c2abEmS8zBfIiK3c04td+ttZno0wBCbIDNCkImUmUwPfKaZHsgX/TX9AumV0ptkksloMo1BBAlAImYwS/f03O6+W1WdJZdY3F0Pkefc6p4BJBFDZrfVvbcqKzNPZmSE++effx8iKq6e9Lgu8LUNGQhZERDEFJQqdQHMwDk2s9VLxOEZScJVILnaW+hvcI5YhwqSghoYIrJzNbG/jBNErO6PSJVjVnG2OkGcucE1CqkjYhVsrv9CqOKO9cPjukd1M6xxAzGhOSOz2jZQdcwcAwKthec1AyekGtEqVRmddebQBBnVB1WrVwQAzOSLCIhkKsDkkZDBNawgVGMjYzBztU8wiyZIJioqZrtdI0VMtAr8E3tSsFxVdMABS9E0R5sNGCgAOyK0nFMssCkOWMWKd13f9JiSlT1kGHaNFIsxgTPvWgBNKnGUk18QzLdURdZUqxIBSNY4A2ppXZcp7R+OmiznN3HKOZsBfPqJxCXv3z18/eZdA9x31yJguXpiixkUUU0FBcSUPJLnwME3ARCLIDM4T2ITMLDH5bjMacmaJBdzdoYmrQuBO2bnAJnZS4HDYZyTlAJ9Q13fjuM8jbFtyIC8b5qmJgDs2CsjERfJ0ykCGTlwLhO1zjkmYAIVzTnP8zKOUQUaRgMyQ3ae2Tm0LvS73QYQUlpyWhSUGVSLWXr27FnYn96+fjAFEyP0aLnGPEuM0xSvb/nq+ka5HecFEHPORMTOd+3GlDabLaKJ6jJPSxYAaEDJIShCMUAMITRN03dd2/RvXt9//eWdKugLfPbio2HYBO+naXzYP8zLlEtkcs5RE4LEKl2TirqsBnPOBnmXfvDsow9f/HCapiUOati2fSCWeVGReY7OeVNwIWhRHxoDJOfbDpoQEABARa3renZBAUS1SMEcwaBpBucIHZpJUTG1gqzOqkF7qgk+vy9p1uhdFAiAGEARDJVU6yu61kyxvmx1LJ5f5nNd6/1msAYT55gIv7WsXGCtb6BXKmcDbjNRsVUvgytr7MxvhTV4rOEtARLjWf5ERIGoth06uuhnVWtoJETRUlSMhNRIWTSnWuR2pWswp7zEeWi3TPzuq3vL4DZURJYxoecYJ3BoZIAGDQ29cx0WyFnVqQx927fdw/5wOp7Gk0LM2LZN0/f9sOldCO6TD19sQ/Orz17vv4ok3LS7fAAFb+ZoFlVwnRNQoCweVBU1EWHowpu3b6AF3jgKVDAnSwAABLNBoSTkYp7ysjRonWf2CFakaAj9brf5839VAp5EARSJyHsCp97UNeYDA+YitU6u7GTTbyTjIT7kBN32qu+v5jE33qPKfDzstlebpllc64SPlnsIzoFzBpSW9PD2/qUzGHp2zkJLdIyCYqqKIJJKHlOekAqYoA+h5yTLm/v9FNV76DqGYqexxAWHFgrAUnKMy2mCGOHqtrAbmrAtgvt9fPPmOJ5yyUBGhD4nmyFLsaZlxz5nMS0K2awgqvMMoEh5u23QWErMxbab9vrqqm0bZpuXwzzNota1G9AqJpBjFMMUYymq3gfvm6btX331oDmhPsynRVWdw+1u6IILHSHC/nC/zGmaiymwB+c5NB1oA8B5icd5hAzg1yGaUhKIRcV7CADHU3KeunbrQ0DwKZVcohIsCZpGnj17Rhzu3u3nJZesoto0ntgjJFDxHAqWGgLYhUIuvgAkUXCiDsCDG+DDT588+ejqy3eH47LH4Jrg45LWuosCIDA2jlpC59gRKjvXd7tSUm5HzdFR2A4dGh/u79++WxjROwt+1aPJ0YpwO1x3TWHVAV0DRgZFJKV80pGLa/zG04aJ/uWf/c+uHVKKiDZ4dpvO901MSQw5+M4zBBbVpKCgUWeIWYy5mj3iMjS+awIVFsUC5gCJXGhbUr+UMUsC0BKXmGaR2rRVPHbGFJfJt9vGeU9sChazITB7KwIqaKtOhZkVLaqCrIYISMaaVQhEAAUka0wlC+U8zqe3bwfbxnm/lH0/+G03DJveYSiQU+0UYDem0phTszHDtMj+NO9PE7J3wWWz/WlcYh5PMUXzjtrWA6GosWv7hn75y+kwwpJP2+vOwBA1l5Ji6Y1L1tOUj4fpNC7OtchdLHK6T/o69f1p2PDmOqtZ8MgORC00TAg+uL7rQ4z7w1gkYtFxnI+nKc/qsPHYxNmWMX39ZW4CseNc9DTm/UFUgLZDdC3QGBMQA5gtCSDADz5uP/zkanfdmR2Ph/H7H/7eX/6rl//Xn3328mXu0e/o2uW+p23femD1dDJNyNi0TV4sL0nVaoQsqkAVPVn5IIiIICuZ90zegbV1w8zOUWTNN7hK7MIaItOZMfR+0alpOOhFVKeuTbgWio0QAExXGS28rE2rwS0icF6kb9qUFwrkBbKlz/761e//w083Xg97mJf55vpd0/X9Zrtp++A9N04lt21DQFZUoqCOKRYvRcWcR2c2L5IT7B18ssXr2812N7jGHfJexmSoiOQcNZ4MwLGvaQMzG7QgKU5xOgo3EJ4Edm7GsSiwJmo8MOJCiA5apxLBoPIENKslFcuqgoVRyMTMZEX1qohk7cRHrgE8QfVCWhVsAQCs+rB/g/tCVt+iX9v0G4ml2Xugpi7c58yk/odEpIy1wnQGtbAZWgYWUQBoGt+1naoiYNd2p1Nh4NM8enA8MLGVLGVODXVtaEpSAEMh9hx8KJQVTVL26tyG4zgvEqc8q5giAgOIIdecDlJZ2rY3KgaqWlTUTNGoCrhg7VI2Qqpaabp+jF9rqLRv3ZXKUMCVmva+PggA1e7LyEDq4DuHTyu49BiSNYM19/rN2xqYXa4GEW3NuhQAkOgMKJ1doS+lyzO2C1jNXBEQsDo8KwCqvVcnfd9K5ZxHvEBV63RatXcNDeTbkeI3rxXO4MR7Gj+iPNbaVlPTFdd+nF1WyOo9gnEGJB4/BEMAtbVMe9bPUjVHaxT6GMP6O6hk37jm3ySPVQ/1+Ee/EVf5LYBBFyDmAusws4gsy6KqzHwRt3/EVVlVgS5XeTnUv1s73m/lU9Q7denpu/C8Ls/+78P8evxc6zHtkTDb5ftYARc1BGTH3nvn3DzP37oqZj4PxAvDzwCQmJiZkFRVREop7N064M0AdQXIAKCAG3zTtqXkOC+u99SgCIgkYkbHItK0IeYEKkDgnUciFS3FkMw7dk3DngCwSEoli67qFVptExd2yGtHC6hJ9RTkOqerakopxwQZgCA0wbMD1ZxyKrLWDGp7uYGZEnrHAQGVtJRSNIkWQIMAFBjJFGthH5ipMnlqZnYBkejsBMbM3nsRyblIquTuKiVAcYlYsTtids47ZwhLjLlkAAghAMBqAQurbQasaJM6T+c29/dbfVh4Vr+qTTpnXNxWR0TE+qqLFFVABOccMyMjmBITEwNCMa0zTu1pri5lhpY0rqJXBMDA3sEq1AUOAJFMpBSDBdCA2RETQHUGlL7rdA1cTKraDyAoyHmYIUH1TyqmtcmUHDdNQ40fKYND9o4dMCGCIAKCaS5s2PhgWadxTrmogQkgATtgcrX6l0VFz0FQvQV6FgogdJ7RAXpWksKFAobOhz64BoZbbhofKJDytt/97G9+7qC9f72fFyUGELe52pUs03TsukZRY4qbXfvik+vtjY/pbtiGec4geTt0bTOU7O5ez1/+6k6k3O5uDm9P9w/ZOSgZQgt//Ad//N3vf++rr7768//tL6JS6zpDS3FWjX7btn1TUprT7AfnGmqaBgDmyUxdikcA+eg719//3Q9vn/U+FGJRy4DaNo2ATafp6y9f57T0XfNwP7Wtv77ZMgXvG9/0KevDYXr3bn86jWTN23cTIrx40d/cbnOJKS7O+evrm5vb6//pf/2LD592Odp4XK424fbJLToVSU3fXl1fff3qa1AA0ekU9w9p0+AHLz766MXzm6urrmlO+8O7N28P+4fddtN2gVB/+Hs/mObx/uHtaZ5f3z+wa4vY4XA6HkcT7ro+NG0phRyOh9NxSc+eXmfR43La7XYvnj0NoYlLSUtG9K9fv56W/dPb7ZMnvcI8zaMKmMg8axv8k6dPg++2/c3HH33ykx9/9ubV/Re/ejmeZF7AM9xehw8/+uj29rZpmqZpvA85l2maDofTmzdvH+4fliiCeXNz9Z3vfHy12zERlIJmP/7LP3dQ/uHv/+f/1X/5X3z8wQeHt+9O93d5OhjaOMeHcXzy/Pnu6kYUHLrb3XXngywJim773eE4H+f5OJ6iSRjaq6dPurYL7HpubJE/+fSPS1kckDAE7H95evXf/w//4l/8j//Lj375E4dYznKfCIBWDYtAVuFzswtspGf8GWqYQ2AQbNWSW7vIz8epcPvKz0V4FOe8Xywua+Wl7GdqoAWBK0AqoiBVVRZ41RYiVSum5jMEJvaeCNGkqJkUKQzEhN67SlWNkrMZOQAmIARnCvrB916c5nFJs5pxA83QEhpodWu20DUpFe8aUEg5p6mkJWtSVCJ0UgoQuUC+YWTJWUzMb/X5p7cff+95s+kO48P9/j4e03TM928zRAAG6AAY/tP/5INPv/vRtu2/+Omrv/jRZ69/niHB4DoiWpap6dp5npH5+uluuB3a6+64nO4e7paUAG2z3Z4ejshAnjSp66h/Gq5uut1Nh66c5rslFQNoe9jsYLd1wQEZBNf3zc3Ll4fxWE5jiiUVszDAMMB21/Z9cMGurvxmcNPpiGZDv/HYgnVd2LV+UyR8/tnD02cfSErz8UCmrz7/4le/+DIe4I9/56N/9l//0+9/8r3ltPzql198/vXPpnJ4fvPx4d1+4OYHn37ygx98+OOf/p9NRwr5tKQ5KTe7bjuEHU9l+vLtF599/eNos9/0BeFhXKaZmXdSQk6+de1Xf/PzsgABDX3f9/5P/+QfTaf4V3/+s//9X//0h9+5/f73fueLz77YP4xv342IwbGoJnLQd77rQxvCPM9E4rwaSFFggq7tu3ZrQgpu2FyPx/T23V2KOXRt37fLPJ2mg+cmTvbVm0PbwIuPw/Wz8OKjq+cf3Nw+vV3m9NOffP7q5T7OhODu748A8vzZ9dAPyzgdDve26sdDypALmAPJIJlaGkQs53x1c5VyfDjui0Lbwu52u9kMPjAgmOWmLzEvp9OSi17t+g8/fNpvwjTPb968FgWQgNDlhFPmlGA8ntK8QAYuxAplAl0UMgIExwHBu+Kd+ZhPiU/QL24DH/1w+/3/+IPts7DA+PLNy8Och51/eruJ48Mym3fUNU+ur56/fnWYTpKinMb51csDMADD06fhH/yDT+fl8Pqrr5/cwh/9wX/Ub9xxPr59dw9IT588+/j504B4fPt6zlPGUvKEksoIf/A7t9//+JnFedo//N73fn/AJ8d9+fyzr37+xdc/+tmbfgfbHT19ev2dj59/8OJJ8Nh479gtMaJy3w0AtMS4LLMm8UYOvEPfhG539dwUH+7383G5Ga5v+6uSbNfeDl1fNDbEKc3zeDwd7uMyljQPfXv75Hq7HRxjAEYgBy3CANZBZC1MvgFmcGYWFbKhAICCCqRiSyxjLEuUSJ4QMedcUq6eZcXSw/Tubn93mB78xm2e9k0X9uP9/XifSg5D320GJByjDO0HD8fj23dv9vtjMWu73oc2ZZuX+LAfP/vs65iBGUQhllp0BHLQtq4fuu1uK1pSSTkvRRcAUm1T8iI8TvHN2/E4gQqUAjmDJACDwNB3zgd68QmaxJwhziAZHAE7QAL24ANsr7th097dn05TtkxxAkZkcmuWirlkSwlihFKgZIjosmsV1DE0rYHOmx6e3dIw6O9++vEf/d4Pp/345vXXLJv/7r/9v4+vYR6hJTChnKGIcmg/+cGH18933W2bIH/96ksETjHv7x5YPQrnseRZGmhRAItBsVJqxa1IKTXhNDFAQF7JwkyMBHC20g5tk0oqpUof4vtWuGyAELwHsxKLao0V7RHQAJAvotyXMizjqvZeWcmXNEv1XBivwrjwEQwfwn/zz//J7Xf5R//6X0Y59Zurw9GO0/Knf/qPdk82dw+v7969Drxrw7YNDXtclml/2M8pAqFrfMzLHGPwYbPdMdu0HI778XhcTvdzmgy1ybMtUywFhmEz9EMpeT7Nh1czGDAzmeVFQWEYmq5tl2UBJjV49vxZyfry3StAakPryaXjEk9TwJDHaAKYgZRU1QqgABqhUQVowAwNEXnNvwzUTCtHOgMDYjWhA0M1QQBbneDqyk5IBrAaYJmhnjvBVvv4KteGAKCk6gAcIIIxuOC4YQUpKMyMAQGtWLEMMCNxcI6bpmmaIFJKyaplPEw1gwABZGAPzCEeEszQhc5zsxyXwOE0HgCx3bYUUBmKm7unwW9JkZ8++0iN3r18uz/uQQSyVtnR3dA/fXp7d5iWmFNcJItVad2CmotzjtFZFhEhIKgxkwCYodXBQ6UUW5vyDM7gHl6ipXNOW1WcK4EBrCoj41q3tiq2WcuEZtWIiaDxjoiqTqus6Gxt7TQ0YBfWsuJZfkHB1C5EurUfsEq/AJKpqNVGXUBanQ3wEp6tkmcVulpJ+tWzC8+J6gWughUMW6PFNU8EMDjbBkBV1SgXPbvqCD/0Q84551yK1HQYACQrvP9luLT7fSukfAx0mFkVz7nMEvWn8kiD/zHP7jGkVg914X9dkI3HkerjzTl32flyhL8DbHkMk/12GFj1si5nxW+ykCpW9XhnePSpLjfuW5/h14/z72l7fGfrGSsGx8yPpan+nttjQt3jG/Wbdq1fVqSjqru9x1MfPT9cDS7fDyJTM7RViKiyB00JcKXnGJ2RY6CAjjjnXHKuMoxiWFU3kYmZqmUrISoBEp1nECQGMFSzUooaGaiqqF54T8ZEaGiuoi1VzgnJUWUEAFYz81yyvNcwVtOqmYzsCBD4zP6xquKEkpIVJoJqlICITIYKDExciVMKAgRSzm8XrKKnqoamyIyAKpJzybGYqhmwcw2uolRaDGytLFUeMIIiIjOpkqqJiKlqPlt82VmlHgAMhO19vevM12R2dn7Lz3AyVAkzuFBV8VIoo1WK5swgNUBdzQrP4GnV31mnssthYMX7DURKPTtVjqgpAHClTxivzLtzG42qnkmi1edSVymQ87fRyKrKc5WoAiBkMDRDEAMkRUVAYEUyQkNTkWIArrCpQF1KFADBe+e9Q8RSRKtlLphifQuIDMyK2Wq0WJuTVn0ABBVLJUOigminFGPxkNHQMh4e5oDZFNAAhJFpPM5qwOi0rAtGzpajEPSbzVXXkXMLSssYSqSHu/l4iJ4DGZ/u03jIziohHMoMn/3sV8fD5Bv30e9+/PM//8XcWdM17bYT5RinHCN21Ox8N3QiCUhKXsc9iIBCTEsui5l/2N+xR7ECIG3b+iYAQt93EkLfNwTIxI3z7Bwi5pxyFgAdNk3XNW/fvGsaYIYQqIq9NY0fhqHrwjSe2GA8zWDgGJzzvnEAusT5+Pbdu3fviDG4hoGDa25v2l2/GfptE4auu3IAKR08dx+9uNpuh6Z1OS9mrmmGp0/9JidudoBuWRKoT4selllk8UlTioiwLJILHPepGcJuc9MFfziM4+ntNEVT+/53f6drNlp0mhI73V75zXabY5qnmRjUbBynzEIQ9vvj/uFhGmfJAgposOmxaRowXeYpLbMMm64zkVJyZNJnT2+ePrkS1WzZNW7oXF4O98fxdDimZWmbgbTEkvb7Q9+2JoBM6BCRQhuCFgGb05SzeufbJaAIigZm9kCOkUhMU44lmhsPKjk7r5QwlgUWK8mQc5bFZ8f8wx/84Ps/+MVfv/2JUZcuhSkzkrUZAGsZtjKx39OvAOxsvWyAZiSEaELvowdEJOZ1DiGskNc6lNd1ZLXxeLymvF887Lwo2MoSJ89ggIpWQHSVCETvjBCpvvm14l7DNFXFopmRVpWT9zW4SlKBr79+RQF91/S9J0eqKiVR7cJCpSI5JxXz1R+0GebTMj1MUoqQYCKzUjIQ+s2ufXLbcjAKyEhvX93r67fKxs7ttm3DonneHybIChmgQNc10+m+jAfJy3YX9tsc9zDFmQBEwaYIROTdcZnGh7RxOWzDk92zaKloTuPsbqjr+rYPSWLTuu1V3/WuHVgAWbjl4oNrO246ZKdqWcQQ5sQdI4bGb8i1GBRz6LRtqe28b0g1LbME6jz1jlyggXFIE7x5Nx0f7u/fncBvplGCF8SHDwAAIABJREFU94N322G3+53hO88+nB72Hz191nZdjNM4HYxiM0BaLNtsJBwQWGOevDOEyCR9R6FtkIJAOY2naBHRun4nibPYVGRZLKljwlRkXPKEJWNBhyIFeHjy7MMY5cuXb+7u7j+4ciXCL3/+0nF4ejs4mu/u9qUsXR/EspQcXOd9UBUi80ENoloBIM/EhGIQp1mK7ffz4bA3QUNEwHmO05gILS+EBk2DLjSIHLOMS9oUJReevfjgl59/JeAlRWBxDgQkSzJU5wOYtSEUEYVcPf2UgQSRjRBANKapiAAAETB7R16yxCWlXFJJ3/3eDZqhalqWuzQBvBp2Ppc8LZkJSi6gWrIr5ouCagEBKKZZLUPvN6KQVCRpyRlXJ0+FgOxYe2hv4OaDbbtzGZbjslfIw0B91wCgahVawFJkntJ4LOMx5wQ5YXX2hAJlps9+9to38sHz26stprhkKQVjswlFLFs+LUsDFKOkpELC5M2sC8X7xgDROWCn6Pa6vLqffvnq/vV+abeAHSlzNpm0zHlJBlnLth9cCFhQRFOKIgKADilwcBic86EbfvHVL9m182mOp5hSWuYU0HdhEAgIggCN43bYDEQ59yVOoXFD0wYkU631JwVjE9BSAzjTiMSgIJYK5nM2Uw1iTBCVEQBjXkITXCDHnogIjFUH8Nj0W8/UIQHkJE5p02xkQxS8IIzLcpyW1/dfTuNyOBxO82wGUwLv1YwV2DAUhVygADRd08Fqui2qS7Z8Wm6ffVziVLREgZTBTFUnyS2Ad97vrrfGy36fs0AsoBGAoG3cZnO9ux4O+7eigKqEEAKhmol6dsG7puGh3ZScgm+utkEU+87iLCmqqiAV75Echo66wiVzLK5Fyo5MWbKWnIeuG3r1ITHD8w+acXwHEOYTn94uPMOOfBtMMuQIXJDIS9JXn785HY8f8wfdddOFICoq1DQBhCwDefTmsCggCihoURS1jEgcHEIN1tdGploUMVAxBCt1VaJARaWKmAACM6+tRGQIQDUwRDgDCLRmsReW1krDqgQSQ7PqblRjWDPEKiRaQ+1V4gMNkRPTsfz433z2R82HP/zuD/7qJ//GAw8NjEf5t3/113/yn/3Jw5vx5eevJZ+c67rGh9aVEud4yhKHTec7j4yOAFAeju+ypCUd0pJzMmQfAlvyAsUMc7QZFiYMbdhe7U7vkkaULGIGAoggWTMLOY/OgeRiBp4YSUSyKJsyc9P0AbxOpZq515S9kIIiKKGtfWGX5flMVTMwRIPqvm0XMewzTeiylJ9ZXPrIAm/1Uvm7tpoTnE9WEcQqtQKEDE5ZlckAcimI6H31AkcRIr+oKimoQu0BNNCmCxlKLtmKmlPz5tQrSqFsBghWnDXbZnPbi6AiGOHw/Gq2nE5HUGB2reOmDUaInkgRC1Y9JlMxAm55ZTewGlY3xjMJCABMERgAsDp1QfVCf9S7t37sGjhVWHQdne8bAete9S+XMAnXppMVT6lyBnBWSVjH7yqxv+Y9gAbVzhNWvtWaoiHyOR+vfbJEUBG6R0/mLJmFCFbl3msTBlJtrqLzZb7nSJ4TPFAAU2WkisCV8zW/J30BAFbzS8w5i8iaaV5Ov8q6A6wUGXg/IM/bt1AaWFuM193qT1dUy+qtu9z189j7Jlb173W7MLN+mwBW/ZAX0OdSHP7WnpeveO72XBkYj0hP/4G3b6GDiFgpTnUoVDbTbwXGujza/y9Hu5z6W0e4AFi/fpMvIOD7H8naloi1b6Vyi4lD45k5xsWyuNYhoZqaCRCSo6oUaqZIAEaGtsoMIhKCiKqaFsPalXLmKzMRG5ExEIhbwacK0RBxhVsYqZRctMBZoZyMQWHlkp2ZSStwDWAGVFv+clLHNbuD2spShc+5ahVWyRYAsdWysCLWa9q1du6qSpFVb4uYHbqK/loxEbmMzssoJEKF1b+RDG1F+QHqOc+8UwNV1ccEV7wsRzWDPWNYK1p/htnXzPHc//ytEVIvp5iCmqqcRZ9XDf+qOou2ikbDGeqqIv3r5GYEKqhrWFFrDxeo8RGAZWa6rqEG53BlvYh18q3vKpNR7cQTwJXUZwBk61wvpmZQSGvmzKIG6pjbtgkhlCIi1UnXzM4GN+tFoQGYKdeGirpwoIIAMGixkgug2qwiWTA4cqXIMoNSYWZmNMOu7U77U3DBNSHlWKQAQlzisixEV4gEgMzOO4/KxE2Kp+m4aEETPD2MZQbHqGaeGQHfvrk7jsePP/74k+9+8u7LuxhTlsWFpms9kNesfdtdPblynYvLhIzTaY5lUSBwEAJcXQ3D0LLDw/GhaZ2hVsWlDW6Da4fNVUk5BAcDmAkgV0/GeYlLElFs2jaE0LddnjMShAbVipQEqlrKdDqdjuP1BpgcO9f4EJxPMcW4TMtoCKHphr5vQ9ACwenQba63Nx49W8izoXfX2+faVkwtOM/H0/LTn34JKKFzopqFdrurZ0+3n3wId3eHX33x5ngcl3gSMETb9H6e8/5+umG/G7qG/XE8PNw9zDN4BhPo2w0ojtO7434c+ifbTR9xGseZGJgw52RGPE0PDw93d3fLJGDV4UARSdWmaZmmRbVsNuPV1ZVzbvU7a0IIHhC9Z/JoBuN4MiuiqZTkd60mHePp9d1rwHKzvUKPWMjMmNgLI2mSnEox0CVPoMUDctMpmgvBp0zMkEFKiXEBgEJZsbgCoqUGkqXIcTqpc59++v1PP/0UfwTehVr6ADRUw4pL1YofA5jVyh+aEVY+qWkVVX/EiOcKZxEAIDNXKBNg9XqwtTPhXJNQu8wu7xcLeE+hf68niIiIjtkMci2dKTIROyTnlN5b3xZVqDFprSQUM1rDpHNAfA5WECqNS0WkkAKoiVq1sVADVawiWgKWPA/DMLS+acinOanY9sV1nJeYFkBFIVLCDClnjTnKMsXFOQ5dMwwdEm43u+vheeeGzdC0HblwN8VpLCLoNre76yOdOE/7RQowuTKX0DWucQVLsbKkxYFr2mAKspR+14bMbRNccJYKMSAaEpwJ986g+BC6vvEBEJJINgFBFFEO6JFcx+gao8KNNA0E54gwZbACJQWHLhXKR4jjfLxf9vfz/m7eH6Zul165QxfCrmsfNsMmhJax67bb3fX19S4wspdh6150t+3oWrfpfbgdrm6ebIPjFx8+N0pZ05LztOgSlymVUcZsOUshDCXPx+M8F4nFKtBjuci8iExtIAUNXX993d/cXL/66vXP/ubzu7v74PppjL/6+u6T73x4e7u7ve7ykvfHU617Z4FSxPvaAEPsGAjUlDB4bpq2EaV5TjHO0zzHWAhRpOScckoxqUrMCzoHw6YfNj25Ms0z3JW2ba5vbr776cc/+tGfczBV6zpPRCXLVGYTqalB13cxpSSSRYzAGSiI98TsFPOSppjUDJqGQ/AmMMc4zUtMKSscricARXAMblnKNKW+bxvm5BIxq0ARzSWKJMsGKUGG+r8WFjEtgIpoBAaAYk7NgVISNz152j/73vaTTz/ornAf5xhH57gdurZrAMwzN9w4biSHkvS4Hw8PS8mVjkwgAgLjIT7sl9sn8Luf/nA7mOkU50wejclMYyqH4xgAltO4LKORBE9kZbcLfd8hsWRUYID2/nD6xa/e/vyLX40LDM96bMAHJCYVGacJrATvCMBRcOjYeed8LiXFiNmASRDHOepxfnO3D01XYpmPy7Q/Lc2ybTZPh2vuu9r9w0g+tK1nK00pLTN5z4hQJBM0YiYCBuqwgGNENSlgjApgGVBqKICoVVQMQdGU0CQn9Ow8Y2WXmnmgvh22IahTczLZdEhHT54ap4ET6Bzn0zyP8zyNaZ7i6XSappgLAEZAB8BtPwBRE1ozURAVKmYE6tu29733XdM2cSm5mAoTtl3bheDBcB6nGEW1NJ6HzoHh0LOq00QI4Jhd8KVY19ycxuM8LwzQhKbxHkysqIkrCXKkd/eT89Bu0AXlxnnPkpnJe++P01tCh+jBgonPpUkW9+mhFI9Gmml3c71p89AeNrt0e7tZDrJM8urr6YsfH1PiNvQIdlqWZUoqQJ7QwzKmxU7+ZbrOG8eaRVPKtnJITEHRudAEzaapFMRah8ba9fO+7anm8AhoVuXJ1iYnKCJVhrx2GBDWaV2JkM4ZMRHaY8TKHgFY38xffj2TtYtGIynAOclGLEmP7+DP/o+fkpfv/d7tBzefNpvm7cO9QxpPbzTb/evx5efz6TCjQd/xsG1CQ+zRN/7+3cl33nc+dAFBj/NpiaOBWAEAbkID4JIaca0SSS6lSOlcN3RbhbegBsUAgZhMNebcd33oWwU9jcs0jeyY2SEwm1kWy4rFVDMDAWD1KV4hEnwfRF+WzQpBoPEqEGa1tmVwLmmtRdta6KIV61sDfYPLja70CoBqXgfvf/2bN7hGAGhUYcLKAqhpByEbA2gVoSUwY3a1Z7H2XtSz4apiY5vdkHzOYylJuHHowXlXABRFSbEBaAEbpuBLLqfToQg48pumM2wkF9GCWorqEmNMMeWsplDTE7ZamChZTIAdoJlmUDV+35yGq15YVWmormb1C7y/BZXJXtObczFuBX/O+M96Q9c+QjzXEy8pDnwDG8RztqYr0w14HfZ0plmcd8cz2fCcblbbMlub/eDSW3h5cc7KuZdf5cs565WoaVVDhsrrWMG61dvtUpgEg5Vnf2lfAwSDkrNWFQiD82FWHtYFN7hs53iy5oSPhhBc2lxxvYYV4Fmxs8uNgjMopt/0Kv3b8I3fOrb19wWwvpVv13t0+fvjH8Hfwqi67PYfALf727Zfv7DH2uq/cYf/v9tjYbbLDfn17Vvf/xYF7FsA369DhL8OYMFaMlnfsarf6NhVUaqa6jjnjKBgBtMV/yBcjdcRaJXA0hUbQVQ1EcVViBzqq8LErEhQXQkBWAUqTFHnZUZCR4RICogIVpknxqgIiqu7qpiqhuCwMkIRjRQcK5k4rp5ZRnBBxVeeZoVmwC6UrlWtHsHO/XUV21YBBmbv19XjEVORiIzZvrnVXJEBFZEqtsYEAIbAK5i1BgYGqJV6oZd6y6NnU+F2RFybe+rUU8lepipwfl5a/cJML/EGqEAFhuokzEirBSWhoSOuEJtWGzvjqqtaESpAAlM4w/HrqMC1mf4xgIVnSXqolaFz3aL6l9VVB5mQUNHMBMTWZLfSuciEKiccAAEYGRjJGQAVcc674MlxLcaVUrCSwx5VEuAcWhlWXxUgQAdUyNa4yxRFUwQD4wCO2YdQbw9XUVKm4D0QeeeZMeUKfwIYSFERMZS4qKE45wHo+ub21Vcn0CUtyQTKAkRohprNEYamUYU45eN+PO7HP/jD33358uVXb78qok3b99sgKu3g286hRwDHnnOKIlkR+i0+ebr74KPbpqXj8XAOBc+ds1mCIxdYRGPMgCxFRDKi5FKO4zynwswdbQPxsxcbLQUBi6bjIYllMUt5Wg5lf0iffPyM0Ito45qSyv3hYRxH9nT79OnzF88ZUYqe9iOYNNyB8jzlwzib3QfnurYz1bgsCuoDPRzvv3r9BToYtoNoeXL74emgfbe0bee4/d6n31PVh/uHL798+XC4IyLPWlIZ93Pbhd2Tbjdclaggh7jIcX9qm6FreilRDAg8YfULUGYITUBwwQVmrFgme7fdXplxt6Q4H+McSyoxlhjLdjvGZbm+vgohENgyHXN0SNj2DWvlfue+C024BYASEwTOFt8e3mZd2tY3DOBQSgFG1zgOhIwOyDsCtqIJAIv5pMU3g0/ZN8FrLiimWkomAmNXgeoqDWgI0zQvqt2Tm6Hd7A+w3eQMZkBU5zkDsjpnIgCYAsMqKFc1AWsIstKdDFQE7b2kHSJordKeeVpa4S6qrK61HF4PcqkDrpP/ugCsTR/1narMWVNTE0BDduyZHRmvtlPrJI2r8MSZhXWOqM8I/TkyRlBod20sKaecS0ZP6AjIqGZBbA0jOgTAImVJ89AOw9A1zscp5SVbUUZ0QKXIcoolJYNSIA+7wYWAKR8ngcP0LkybAW6vP+m3m74fug23g52mLDmZFAYMQ/Pko6fDRu/fHOc5qoposaDKWiArKqiykOYiIMnmXduQB2IRKNkiGi0F8jhvXN8NoenaZVEDKgVUxTSnbCbguUR/NPW1sIOMhtmwiJGoaa23Y1hGlgXyXJbT/Pbr0/7dNB9BChDCEh+WDB6gYUCDgeF62N5ctdf9jpgbT83A3DS+DIKxIdc5vr3ebK9aYrtqrwSWWed4Oi6n8WGaI5TCMuUopqXYNOaHfc4CBSG0QGCUC6QoRa637XRcPnjx9MnN01zy3/zkZ6/e3DW4seJSLPf34PhOS7i5vtptBpHNkk8lA3uYplkUcs4uEKDnBpCYkJHIOefAAZGYIJoPxOSZaV18AUQhRdtecbfpmrbJkMfj4bRYP/Q3T66ePr8ZtkDgExfVVgrOp1GLOsLgGkRquh6JRQHZkXeEJIqbbte03cO9f/P2Lqu2IYS2QYRljvOY4pINgDwcHqau67a7q6GzaTld7ZqnT64Nc9akhtS5zFhSjMsiCSwDFEABUscQ4jGpGBkFFzhQKaXgYg0WV3gLn/zesw8/vdk8aTJPkpJvfCDnW0dkIDD0Vw13CM14lJIxntJ4TJqxaRrPIaYFxPJswBAn0AgamMlLtiRlNlGDUgAVG7AlLnHOAJBZ2wDb3RDaoAZzlGIuAb/ej798tb87ge8IHflAXRe6vvM+pJhzmmeCvGQ03Pbb25snbeiXmFJSTcW1rUG5fzi8vXvYXD8VUyVMko+HCVoNG9K0MIhD8gBgQmCmQoDkPLMjRDUBc0s2LWJqjgAdMlcPOkFkQCJTtsrPFgWF1WQHGdGACA1AanDBSA7BIXviIqROCpVcCLN6JgQYUzzG6TCNS45gwKigarlIKilqziCKCrTJtr3a3F4PS47zsozLjACbYXt1c9WEzgDJuR//5N8Sh0q66Tbtphscw+DtOM6H01JKaoMLoUFqARpTLgXSktOSxsPp6mYLbIIlLVKy8UbZAaCKlKKFR7m/H7c732wM0QzBt9xvfdu0RJzfBlUqGaSoZFVVg4wyWXIk/VW/3ba9g4fd0H304Y7Qmrb98vPTy5cPv/hFbKB1oVMpOS1SasV0pVGgwOH+gHza3G4l6bwspQgYKaAxODb0QNXTaNWXBU0GRbBSfmhloCCtLrTVUKbm0GnlBq99DogIVEXhCR8l499IiC5I1toyheccH9d/4SUQrvya9/QROGuLM3hTGd+Uv/zRy69fvfqn/+yfCM1psbGdh93T+6/v3365j3uIewCBxUmep+22211v+0336n6a5hO3vtu1vnMpZ1EJ3gERZIfijEg1I4JzjE5quRvAkKhS0YDJO++9KzGmUrx3bRuWOBfJ5XQiRkcNkysplyXJIhbVoraOVR9phOm5YL5Whep9qOupwaUsjhd5MLtIA+AFDKBLZlfD6UvnjZ2xr/UOXihD8Pgv5wp0ZWCxQRFFAK4C5WaghsjAxJ7JITKq6KMMHYCAHStqzsI3oXOeLB1kz8EtaQFvSqqg4MB6gB5gwOJEimTL8zgz+k2z7bdbVBjHcZlGQwJ2p+kIiqAGRMTIxKAouSgpVA0sQCCDDChrJx2sDIQz1kQXxz9cL/TcrrHeu7V6WNFBq45cwPgNfiCulT1an9gKtl8QrPc4F5yxI0N9j0yeYYoLWHFGwR69CgiVUlVFpirjHuBCgrKLy/T5WJcHt8oHubrbe7HjGjPCGpCtImeXHO2SRiFiETnzJepvnf128fEJV+5ZbZ+8vMuIa4AJZ8TgfURY66YI+B5zhsv2GKRbh/7fDpj8dnGevxeA9fhSLmDKpah7+f5vBLPWdP0MH/z9EaK/z/YtROnvAJj+nbeVvkR0Rkb+36W+6g4XFtgFGbxgYd86yEW799dPDOtrg845wIsClwICMhKzkT7GVtcGRlQiQsBaY6+Y71n6CWDlQpoBMAAbsyAqkiI4wCrTi6tCoYKgoaoBipog1aVMAVZmFhiYmIpCAfNaQfbaDGeI7GBtDodq/aGACkxABgiKaGegGmgVa18J/CtkUyXjzcyY2bEDQgWTUt5DTIi1afQyJlXVExNz1TNe70GlVFSKwbnIImC+92tiahfa1/vsEvGMYL6fsgAAbdXEehQXAIApWV35reJ0dQqvupiq66p/JtQCAVXfXauCzOe5n+rkbYi6+u+aPf7j/Cc+zoLfT3TvJeHrgsKIjoBwrTDoZUkAo1rUMDFlAGQGomoO6cwzMyKrWcpZRKHm6HAuI1zuVT1ZHapr71LFUg1IoSKGALmoIDhQ9VjPqwqliAig5ZQTMxqoFEAAJDIy8oCIp9P04sOt2JKzxpJVy8cvBscNY2MqBAwwe++hgMSUpCB6ZleK3r3bH6bTP/7Hf3L1ZFB+mksChFzEe2xaLDKDYtaE5JEKBugDPHuxffJk13Y0zadXb756/nzHjirTOKUUl8wYmVxKaZmntmlKkeo4mFOel3lJQA7AITq9vWoZlR25Qrkj0YDgidh07Hr46MMPYizTaQEAU/TBddY0bbsZNk3TfvXFV/Mc45x27U56nI7L6W4+3c/zcbq/P8Y9QLGCJWx4c+M3V92rtwkY4E1JUZ0kMyOvN0+GTz/9/h/+wR/e3t6ebk8l2/3DuyTHttndXuNxXJZx6j/6oLluWu9LLHfvjp9//uV2GLq+QRL2vmRbpihSarZDRN6xIzZVkSIqCOy8ZwxMbjweCXKGHCNMMxhE749D322G3jnLeS5FnKPTfsqWS1Ek8N63bdc0IToGU1Y4Tcclnp4+vd22DjWnEtl7bpA8AIlD88GRJ8kKZoKaNTtUJSAmYgS1lLOKugDoO0QSU5Ns4OuMexxH2mxACI4wwSy2ynvUjKDKR8GKXxsYVYdxQUOtE0s1SjU1w3Kub5nBSimXksulxFh3c4TA7/dcX58zFevy/pp9Q3O3zn8FBKzOP+CYnfPoKWN+PzlVKjQAGRQ7i3c9OizgJV4xBFCVNREiNFQrCgDq1z0Va3GjgAFpzjk6ZEQTyTEtd18cnKu+tWaocYauaW+eXLVtSw0yBh9j0RRzTpMuISJOKaaHfTIe2c3si6vcU6Du9ubq6ebJxx8cHo7Hw/HL8EXOOZdcP37W/LDcr0BegXE/AwGEVZa478EDD/22adurqyuA3XHc6//D3Jt1S7IkV0PbzNw9IjLzTDXdsW9PavUHre9DIIYFb3x/lx/AAy88wOIFFtInIakltWh136luVZ0hhxjc3cx48MhT596+rSWQQMSqdapOVmZEZISHu9m2bXtbdVMtRZVrgRtqsVxm4ZKrQ5grnEzUOmMLTAhkMWfPp2U5esS2jGG+T/XkNhU2CjGcjlNVmKMYvCIz8uEwHQ4//vS0zCUGzMsRWOAZujhxCBJ75oiKrCjZ5jFPi2VP3m0F7iXnrEtR5MXy5JqRC8yRiIgcuVJRdqToOuDFy+tNP/yfv/r6q69vA3XbzeV01DprYLx5s9jyDsU22/js6vJuP8FVBO52msacPRQYNBmH5CZGXkqpTJ5LzqWCLMQ2aqwUrapEYMLuGlfPLy+vLmMnJZ+quxWMy7zo7Kgff/rR8TAeoXVhUypFa0EYYuo6YQHAwiGFLlLfd5Jird56tVLmbmQD+hSZqRSfTss8VSg4SBfi6TC7xd02dl2cqbgHpqTwZisaQiBIkEoKruACV5ASWyQLZgprcgFGwdln02wGXOHlZ+kHP3+xuYn387uKqfqSEnEQJ2tNMJu4DTKUheZxKdlLMauAOlkIIS1aQM2B15bJ794dCN0lc14w1bkG9sCAZdaYJHad1dlL84XExcW25HKqpRQDdW8O49dv9m/2D9Zx2A3zsnDqRKTvuphSLeOcs9ZyOoxeq17r0G8JgZy7uKHgm83OzekwLqoXQSBMDoWfpuki9iFwACI0AOTqVtWhtQLadPPU2czVeJ7VqpHVKIpkXayNig4O4MDQMwBvRgoyhgvQtAGSSCQnV3gz/gmBOBE7zKpy8kRhk3r3uZRpPO33x4dJFxdOqa+2UJ29LqQWCSIo5FNWzaNrHDrEAK/1WMARz27iB6+uQXJ7t3+4fRfgZJkgXmw5lId57nsMA226CgMRlmIKr1pKtVI8Zy/F3J2kFt2nDXXDsIzzMuXTlLuE/qojcpJKyH2HFDH0iRPm0aZ5HKe8p+M8jy9ffjxNS5nm03FZZtYiJDMFx1JQp2c3r8iWOh9vLp5//MGNK9cqb79Z7h58KYhBLFBxFFN0SLEjhpbqBRRxuQ1DTOxgdg4g9cAiXTQl9lBzAamyKhdrbEqDma84UlMw59ZGCGJ/WlwP5gq4WVsUHsMzYsIqImTfyljpSYM80znHJ2ofQWPinfvfV7upJ3hNewvIRwu7DSe9+3J++6v87/+9dVt5cfmi5Hl3ef1n/+FvX39xr3PoApvVstiyJ1YVqlG8w8V+ephzVkaPZEJMCU6RUzYtS7HCuZRmgkgEFoA8az6dDuAYUiTXTmKMgdxzrdSKnrUI81QzO3oKANtcmnYeVXgFpPXN05OY/8wve1JbepoLv0ec2BrKwUTnHgYjEK9FrtYrI6D3rREranVe7+m7uMmTQOCsnd/wNXODO8kKCHFjGwiTkJlWrWd9ErjQ6ruVQl00dGHYDX3KC3LfdQ+HO/SMYCBgQNwS9WKdT7Y4W4ycBeJ+PDx4qX3fAx66NGw2F5cXX7z+siVrIHOmJrGmoZ75TmgRBTnMnJhccW7ae1Kla1jQ2kfk7680ViwUTWGqgVtnCPFbbzoPUCZ6DKeYn1zBpwDWY+Z8RhSd0UDPJ5AUmTVlmKfQh0NA56xrhRofATI8gnL+5LvhEYfkJqny9JQaQf58xHb+9juaS+s3fj8OzljStyGmpwDS+ycRDc/CUynn97gNwA2+OMNx3/pp34Wl/hFw4/9HANbj9r3oz6NyRfZKAAAgAElEQVSy1e/7Mn7WeGq//msxsJ5CGI+v1FpxPvmGE/0zIbbvoHj/mAbWk49854jn9MVBUD+3FtKZ0PO7p+cIIbbLDDgLc2BmLrXO87w+zOcKKgGuQCMhmWutFM/ack30rhH9GU2jiNuYpmAKAQlFmJuZNlWkaIomkWBGIC0QchKomSkHOMEUpRZRadJWqyw5r3PNWdXYXQls1KSZWt+cOBgsLIE5NIdmprN4VQOj4ATVWtVVAQ0scJCbVnezBuHVUs2NiEIIDTMn5zMK3dAibbJgbt7YYTgf4zHBW6vPRIzQTr7ZkT7esvONfrzX35rpngy/938c0Ma9B4EDNazvzOE2h7mJmzhB2+zb+o8ExNJ0wpoeugOrJcCKf/njlPfUhGI9gUY0wblTcZ1tG5gkIiTiBDIzNTKsdjWt4zMQiKSR95irm5pptQBiJjWbp8VURUJKaca8Xmxf0U34I9V3LUqRE1kr2gqDQd44cNuLpFbdYc4iXeghKl7gpgQf98cudVp1qRMHERYlG7qeWN7dvvvpzz6ZZiq5nsZ8Opx+8KEeD8uy6NXuRYrp+O7X67G4oPhynLhPDNE564xf/f1fX17vPvvxRwQcxsPDw8OUp7v7WxJIwN0JUSCMZ8/Chx89f/nhM7M65+OST0CuVc0tpAgPtSxzPi1L6VNXlrzk8WI3wHmuFSCQh4iIRpyZci4Pd7XkuU2UuVSG9AN3KWw/ePG81E3fLdOSIle1ftttdoOqT8ty/3D4+vW7r754OB3x4fXwyc9udt3VN1+/efvN/f6b6fBwOu0rHGHAZkiqOk1y/fIqDXPxPGc14rEskaEjHm4ffv2Xf/o//g9/ylf4T372h//u3/7H/8Wf/Jcxyeef/+ZP//c/3e3un7283m06icG36cWzyzKXX//DfH+ftwOun3U3z7e11tOphsG7TTfNc86zu89W8qTjUu/vZsIceBejWbUYgzQTr6BdV7ueUwoAmJkpbDabEAjAskw2L0ueile1jgNJxLDtRLgsedJp2h8/On5UNYVac1226YKJWqOaAhI5kiiMOFpAZSWrcCdhEEqteTkJ2IfdEAaGHU/H5TAGihRC6BJPAiDFCAFVgwLkTqRAE88Vak24bSqls2MsnRlYqxAIzJkD1LyZnAPQNd9o02sr5gFQODUb+pXjSMAqrHt+etGg4XMP9XkBcBgqiCSEFAKLCJGTqen6oJGxgCk2GiuRubbq/Tm2fLKqWKN0qcUUpes5ipJPywLNj2mMETmgblGo6zqJVHQe9+P+bj+dDAqDtkZRB4KQoty/3hs/LF6sfZHA6IwMh/tjni1EUSrFHtJgwwaSpJRJ62m3oW1vaTv0XQzPLz/5oz8xq4AveaxeuiEOmwTB8XS4u7t98epZF2NMnSnyUkOMwnI6HbVimSqJlxmlWlvIunDZD1sSZTZnPx4PSnA1IpA0vTmkjsh5OuS3Xx3mByS6yIf94TYvh+oL6uLs0ERXL65cmiWqhxh2Xe9W5+NbL5Gp05rvH+7neb/k47t3b7b9LklKAvdRbdnsuq+++fJuf8td2F5e7G42vozTeDqNx1xpHE0r9/GCyVV1kCGRVHjPcELX++Xls2EXbt/c/f2v/kErhn5rJVjG7ddToFTH/C4f8zK+ennx459+/OzFxes3X53m/fX1zdu7OzhyAS2lgDpwFyHB5prNcDzuc/aqMCN25KKlFFUQgxN+8IPPhk3fbWO1ubpxCCx1XKbXb98Mm81P/vAnr7/8OpfX42kqVUQohnh9fX25vYDTX/3N3zGjKJyw2UIigzz1W3vw8TTFvgP1pRSdcl6sVgtBJIg762wZqPMouE9997B/OB5JAnPQ03GJXbJaq+mSK1WEyqUaFiBHVTYFu4Qucajqk3mJW2yu8PLn28/+8ONnr65evLpcfCQvZT6N+WSukQMTMxAkauE66t3t+OUXXwtdeKFO0lIKGUeKUIpxYKFaTrqgLF5n1Z7K4kUppKjupWqWcrFJ2+ud9QFlDsFurvsQ5es3X2/77W5zCRv++tdf/vqLh2Mtm91uNu86IYI5SrV5zuPpdHo4aM0phKHv+90udGnJizlvt7s+dYF4/3Awwu7qqroRnIWJ3Ek3Q//8erftJMBRs7TeI3ISIwiY4VSrV7NaPFBfuTqqkRtpwSxouH8gyMozdyY2ogpyggU4sTOQyQVMcCclc2ddqi1t/LCJhCi8k02rIcWKwSlSYAkSQuyKpVKjDQNCGEIcKERnlsCb3eAoFDalXFCKsRsuLq66tHl4OCwP48P8LhR0g2+3vNkO3dCHGMymabolRUp4vknqac58Gss4T3nRWmpRCEJI+Pzr6foKz6+HZx9fBw46V1P1agTvho6Yri67UpaAm5urC7sKx+MMSl3Xu/vpdHJKQCdsU4IurJlhJYiTlI9fysPD4eKyf3l1neQiUv/nf/l3n395b5Y21zFYRKQylxoVkY2oLhVkGPjqugspVvPoKfYerai5CEVmq2SqyzIB5KJrjkAAIzAz2Mxqay8SmDY0wHilBMHchn7bjH4fS57nMnkrrZp+R+aF1ioyfO3aIjA9lmLpET54FH62lf7yxFSXQJalTjGEjo31dPjv/7v/+Q9/8eKnv/jwo5sPT3P56ot3forTKWxTV3TGMufseczz8fDw7vjxjz/wPClrHr3apMGJEEk2nS1LXU4auAtBDF5yMaDFq0a2lOlisxWTWgq1gjAzCUjIVHNZUhcLiilqza6m84IZgUgCmyq3vItbHEsayIvamc1DaCKwfKYuN8Fch/MarnNj7T3h4eBRZrup17rre0NCp7MbDAecq1furVcQMDTrbzIQyN0FLESlwAlmTtoYZ2ZW3UmVtDatZIW0eAPEZGrFSt/3mFFRu4u+H/pDOYUULrY30qNK1mjdRddv42Jlqap58aypBrWSAm8vN5HDPE/7/WGuFfdv8BukXVe0rAJYaDZ4CDEIsbvXWkwBhlWEJrt8LsWdMdMz9PP+WvATXKuFQS3501bgYxCBrUFmdC4omhNWrzl311wAchfHWuR3gGzFDHn1H1jbVAwgA4c2hs/n8X6Er6EYkbdUzRuG2IBJx5mD58AqecYgfpqzE8FXrzNbb/8ZfGhUwTOA9e2g7LydCfN0/q39XLkvcCb+PhxjfWr9bCDgv4OL4czAeO8wYOar4d73nsrv3R7P/3fO/f8htPIvwMD63WM/XqNvYc/fbhV8fMPTC7qm00++4b/st/19m5+bHx8P99Tg6ek3+ucc4nea+75nWwGjJ+95PDecvQtXud+GenJ7w7fgwt95KM7ngPZZMjOtCnjDOkzVV3ScWmHfyJlCIFm5iU2KvU3AzRaZwCTCQiAytKY2c4c6yL0oEpoqTDuLlom1zkQQtSelKlxhbiTEzgxqGnwrjdG98RTUFAo4iEFCTUnP2TkQCfxxrmBmcF1K41uRw9RcFRVwV1FmdoOZqStxm1KoEWO8SVG1ptHHtrqWfrqStMXb116wdb05L/HklRxGftaUEZKnt6N16q2LzZn/2dLQ9vNRLe8xF22tg1i1w7DeesDP+FObrc0bftZmRmIyorULcm32tvOsh8ZoPU9M557oMwzX3oFVqhBoXVMtn3RfXSHb9zU383W8nOf2JtCJMzcbpqaqNVeEGJhr9VKLq7erLQxmaausmSmssdnasRnEj17mTjiTa2FeoS+uX5xOey1gie54dv1sPE7VNESYKhkJM6qjwtm9HYjY1E9zrdVrsZJ9OpWHh8WMS1a49MPQxQRhqxUsEqORtq8KckSB6Jev38aeXry62e22m9qnTXg43OvtzIJ+01fMzEgdXr28ePXB5faiG8dSVPsh9ZuXyzKxCiiA2EzyUlznwMRsXUwxiivHIEQkQix9CDVrdbhbudhuJ8KyzForDBDXWirxxe7Ku36ZR9McY4wpEEuQqIZpLnfvDl9+M99sYBFXu2eX22dRuv39adxn0qiLoCp3gNL+NiMh2jzcjsdTQWRiHjZp2e89IgXWwTUhCKT6b379VT7qL//qV5989sHLF8//5E/+89N0By6n072WYrZcXPYxvrp7+M04oRpYPHUckjs7B+lCP8+5aAWhZM3Z3IM6NKMgmzI5b4YdATEKCxFcAqdOWKSquhcHWATAZrOJUQDKWiUGZlYzjiIsalaWZSl1P52iIFqttfZWJaVpGcdpEolzCpGDKywKhIiFWSRJrBIWwYJaalELkKWbY9wseZ6WmVG6zcZBm82mCzFGubzCMnJ1A4hWS2xtGH/T3GutgG30rlgtyN30HMDTipSDfaU6ruC5E5yYGWeyra2x0ePM/ri0nKcDb6zzcyR3/u+GKccYOQgAdTVTg9JqHt3Q9fa8rRVgOs9CbUdM7f+ICUbe9Z0xCQsxO7SLEUkQLZfs4o2qaQUxdV0fJYblNJ/GcVpMCB7ARk2jQRiRIxPX4tVdKMUuSAwQFExFS11qEBVmkJmCuVO1sui82FLyou8Oy9Slztxyma/oItfFrKQudkn6y7DZMjM4BubdbrNhEnPM07x/OM7LLJzIeV6m27Rn8XkZSym7brMZ0nbXd8MQI3M0CTrnBUHNjQOFGLpBho6Gni2jip9O8IIobMVrNp0hLn0nSULXd6dx4hiXk06nuQsbT8XKsh2GLl5uu2dOtzXT6Ti71QAWQtfHEJkFFNLd4fj63f3rd9/EPjxnHbbDKY9TnsZlyoXGGe4SwsBM6pYkRPY+iHdwQtfFFy+emdnr12+nY01hYE/TqNOx6B6yESgixemk++6B+YfXl4NZCXseNpthnNVrrapmYuIIRE0FBqZazUttRWw4TM2qQiTElMx1s9uCfc7zoqe5Li4uLEup9/eHL8JXv/ijX4zj2L29MzqaR4k8dN2wHUIXXX3oYRArKgFpSDGFXMs4nUr1JeNqg2Gb6FTHuTRt8hijUCiLLTlzIiuex6oV46EQyXQqISlzD0N2zbkuyyLak8Xg6g5VssqoDjJJBK5zLai4+hhXn3Uf/fz6gx9dSLC3p6/ncpp1zF5KaYpD3neJQxQOy2jLabp9e3x3632c3MDMKaYQAuCwwtKL0DIBGVeXl0Fqra7qJCyS1KtabcxBSn3fp9SFvsP1VSeEvIzsaRhkt7v5/M/+4W6/KG2QunlZLvohJTGj0zhrzeNpOhznTlLfdX23ff7s+abfzfOs2QxOwjnXpZRSq5k5N9ccC0Ls5epqd7kbhkCMsqp3t/KkkFOLl0jhxa247WJgETiDjdjBauwOgitBDCszU6GNdN+kxYTBLlxdogVikACoZck5T9OUS5Yog/RhSG4WiIfQP+u2PXH1CoIzQqc0RMmx9ogp9f0GJEvJTjXyaFb7LoVtVECxcL53HZPWZzuSl7tX1yYsQcQJVae6LIYSBS7k7iGQB+6H2PVhWGIMmaXiiGWpdcRPf3Rdy2JKy2gKXcZKJkO3C6EfwsW8ZBvH0/Hw0HPsQlV88eV+fxg5kBOGnmstedEycl3IKgXyD5591PfSxfrBB6Hq+PHHn+y22zqGOFx/9dv57i4bQn8Rm7SYbSq2wGK1zDCgD9vL7eZql30+3d++6AaOTbsWRKautWotlqIouypJs+FhCLOQwIjMpRmpPGYF5vpYknXIVsyaOVOLu95zOR7Lw48fpnPC1lhIdG4axGOWBxg5EbnROVhsvmt85l61IxO458o1U9ftdIff/OVdFP3445cf//iD0+HLq253nHk/l2quFdDAYFfLVZfJXr4EsnDXQ5GXpczmhCFREsADwZk59p0WXXKBKAkkUIwM5hCZjUv1asVNFdp1wpHAIEF1JcFKFSDXpg4m5+8m3jTcWyzMBGeGKs5tDHi8Zk+XbcKq3k6gJiuwLtl0nlQb7YpoZd74+/X+DBS+vwPtJp3rWNx260QGKMhZXNudpKbIIqs9XC215MwiLMTE3KRc3OEw8lwLDIf5sKsX4lyo5nnZXG88urFSpDhItxvyqF4r4MwE8RBDiMGsHufleJhyVpZAqeNIRkrizh5YGpLiaswtz0BVtOKQMZxb4mLkAClBVpZb8x88d408Ntf5qqTg7OQNhqS1ydL5HICt4/t8zc5ZGLG0iuIjNPYEgKBz8gNfLQeaETw9Xv8WObUU+6kJD0AwPj81Z7ypUUzWOA0g0ib1/3RwvE/X1yjukWHweNCGba2P0Xkk0pMjP4kLH5/dBsCtNdX3uz2zFx5hh/MAPdPE1rPiRximscMA9t8Bub53+w6u8vsoO9+Bkr4XIfleXCj87h7/7yI1v++cHqGU77zhH0ep/ik8rH9xAOvpbtvlfqSGPX3xn3PcRyzjH39PE49/+n76vs3dycBCAFRXUHk9bbUzRxE4a1+tXCH3JglvzRzE1qa3XAqcXAAiYnZ1Ig8hhhDMalWFEZMIsZsWr+QIFJgFDlNnW3nCWlSrETUSeZMyhqNlPq2FZU30xGjlLZ3JAo2HCwcFql5WdKchZRAna/OjNNts8iahpWReqzV1dRYmZq7k5Krq5A0PY4c2zN/Ihc6wz7lDjd+bYDpU3WytJfkZG6J6ftb9fVJH53mo3TtTNdeGZj9C3e/9BFcwzIjc+Uz0bMcxJ34/5q0VJwgkzEIk4EY9g7L4ozTOeVYDExnOZK7HnZgxETn0kQu5thyeSwS8Fo7OyFW7F7yqcrXAhdYIRdY3W1NoX5cWa2zTdvK8Cs1jbfk2JasV1c01s5GTMDsDjFLLKgdPTS6DVm2vM4q29qUqELxptlnDIuEKMLhkgzEc9/uH3dXV4TCCPSQpk4XIUFOtRG1oMxPnUnQ0Y7x7ezdNh2laDvfH2wekMMQ0xKTTNM3jlFKXraAUqJIwhQBaFy0wGfn96Tjc30onu8ut9NTv0uXl1WbTX17v7u5vLy4uYpQl782nd+/2uZQYRSTUqkyhVi9aCbLMGEcj0iGmq8uh73tSLNV2wwXgVTWHLKH47ArEEA77yYq25hQC+m4bQhj6LgorbJmni21PLEu1cZyOdQTkdBrzXDaM7eZq14XNsNs/jHf5+ObL/fyQywIn4kSrv0JkYimlHseZpQPDvJZRL55f5LnMuUKVCbk4gZZ6eHd3QMIfz7ku/uOffvrhx89KPf3Zn3899N0yj/NSxtF+9KMXDw+zuV1dd10vITqFIIHdlAASkhgYQWs5jceux/2EUjIQt5v+5avrZZlLrcKQyELk0DkXjCfA21BkRhACh9QNAicREHI1ybULFEKXs0rqT6fp5mInKZpXU+XAh3f7/X7fdQMTxMiNzNB3my6aRInoduIQFNQlT6UUghNhsx3UtHqNwiL8sD9cP38RN8PFzfaP/uAX/+HP/26xhQITyI3gJBIEcK3m3PAkWgHwR/C54UUO0KMpM4HeezwJ0bkn8RycrGjq++imBbLn+GhFsegxJ2h7JCJaLXUDU0tHtRZTQ+XmCQ8ywLSe42BnofeTCa1xNjFRU81g9F0/lVxLtWrq1vVdt00ePeSJGIkDB6rIBFa1aZqmcZyWDAcHUvVqzkBgYWZTU/UVUBcSCuRiuXog6UKKfZQA82qWi29NyuIVqAoARdXqyUImhoU6uVaqkBrTEHZ96C3rSXORQK8+vLKa8qjTOJ8O43hYDvuplL0aqgKGEEFArZhwGIbu4tK6bewGSVuPvV9e3DgX9WwwJhYJQsZE1TR1qeTpckhUyVzPFFpLKQRB0WUZSxqYnCJ3UZJVHKfpB68+u7l+GWi4e5gP9/N4rKazmmnQFKN6Gec5dt2b271SV9Hd3t6+G0/Xzy/jIEZQ13mu9/eFZZsSyIXMXZUjbzddHy3bKCFc3ly//XL8+utvRBgcYEkXfPn1LcSRDc6BAieepuXt21vI5dX1Vej54XC4ur6Jcz6NU9ZMhBi6lGKKyd1Va99HJmchlmiK/XGOHe92F3035FqrWc5LrmPx2dhcPDjZsTjx3f5v/90f/6e7y6vnL54dH/JDnUy964OIay0ANruLXIqTS6SUopO5Wcski+Jwmm6u0+XVZYrlcH86HZZmO2PkKcWcl81miNLVUhOnIfWEkGLqhjQt47gsZmAWVUbpiJzFEcFCFuvVRTeX01Snj34wfPDBzR/88Yu6m/TaPJ3Gko/zqKQkMFh1XzLctYtIklJIbw7T4X65vTuYQrlI6OHcd6nvB1PrN0O/CVor2GF49uK65r1jdHOJsdZq5FZtXCpKDs82V11aWeaoqUs3N9duiSheX7z4q7/dh4Cu3xnH0KFaZU5mmKZsyjl7yRg2se82HLrxlGve51rGMS/j8uzq+dD3w3bTL/Pd6aR5ilKR1WuZx3fPLnd9EPeqee5SBJm5KbxWXWqtBpJAobPIDFnKnGKSEIBqXkAm3Pp+1GwxhSscZOwukDX3WfWWAzEpJLAQV6ua65SXfRmJORBN49SbxSjMcSuxvxrUatVqpgUllofIMsSuVCMKIQVmmZc6zhMrOfnQzObI1cm9WrVe8OpyuOrTvFQ3U0PVWrVW6YpL5jl1lFVPy6J14biNITqDKMTYX26FPAbpwXE6DWUpUrsgMXWxFlqOehh173ke8+1hqoEkcuxdnW5v6ze3Rycsip/95Lpkn2cdj8syIgAdDznFbQr9QEz3F5fzyxfdph/mKf3N37/bv433dzZsQVR4iFZy/yJJjHZkX8QrZVVjOk2VEp8O3m81RWfG5eU2SCyzQr0PfVUrubhWXVvJQEwkZG7ECBLcXKu5KdRdAW/KG4Kw1o6JqHmNEJyIDFZ1jbKJmijrmi7zurYBK8UDbmcK0prKNdILnQEIMm+Si9SALIeTETe1NOPpWEkYA//yL/Y//Pjhw48+uBpefvTy8KvDW4m5lMWrk0uIEeZtKXv9m3dhS11MbG5qsMUJlaxkxJBkE2HSxc6TV7elFAOcjQKlvr+rd8FTxbLUGYphiLvLnXKt6nEIh4djCJx6DxZZRUqpVQ1WDGpI1OQBTBsVhVo4D3djBnN0di/aYmtfDcWppQSrrBKtWikAiNCyvzVTwDmBWq/mk7W/ISlYi86+dsas/B4GkROUrTHtGp3Jqbk8kZOZgVCtTphTl/rQcWTuJBEVNTenSJUqLrDM8+27dwRoyXOZOvTryamVUlKK9aGeTkdxSRzcwYGz1U2/CUI8E1U3LSyB+lSmGRGSuEsphqiqZS55LtkqEyw3TBvMLElIqVlENdzN9Nt1u3bFGvhjq70NiBBAaI7mK57DTA0Bfw/mtKvfaB8g5rNoDLWa4ft4jYi0+ln3rZHfydAgsveckhZs4dvAUNuDreSxFRY6Mw5WpHg9pxVt8JYjPuqlNw7CCqE8InDfgz+8P2jLqlQLvg2wvP+UP80Q/Uwf5EdAppRyTsHYzFQNTbyaGU8FuN9rXnzP9p2X6WyI93vO/3s+/vve9r3QUPh/CQz63s3PfKt/Ckr1r7h9V1vq/6uzfbw4jyhVw7Aac+/bQCYkisFWTiaDhB7hKno8fUcI4amXomZtwhVt8Doc1hIrhjuFICQBzQiWvDYfLPDaOyhwzkWFQcJ0JiTz2gIMN1U3bs94duNVDBLu2oRTGlRBgAgTBTJz9+pVtQmgg4kjqCl8ayMMnb1mV44rmMnYwaxQNbU1EWQiwF1iYmc3I7gzGAKBh3XabVMEQYghwk3EzlRbmtf6RvkMtalBSIQp5+ruKbE7alG3x2m0XUUYIzTVp2+9DAJJ89tptWuta93yvDHgzE+fiEd61tpsZG581t4660A2Vw5e5x7ipjFAMDi7goUDc9s5was5NUPI96B6+xw9egCfF1E0DekzC8MIjXq6cjSa/pi7sNRiIKxrBoiZwGRWGWhrOMxhKLVCEENcjdUM8BVfa8RW2MqxJlvPw53Wtk11kFNo7apNvhrTuLDEmCIJl2ohQEKY52K5ifuTVRW4CXmkGKILARZEhs32/n6vupRsywwUzIsGTvvxKCZurrB+O+iYy6TeRNbYvVXfDB6wnya5uzXx3bK5vNxePbv69IfbFy9vWPgv/+q4u+6FfL4t+/vbu4eJSHe7XYzdtCw3V88Oh3EualamMd/vl1qwjfWjl7uby+vTYRp9YaRaasmqzsx9YixlLpPuj4cYkkg/pI7Ft9s+xSQSTGst2nfdMPTu2J/ub+9uj6eFEGrxzbC5utz0cdvHLRV89fmbN1+9uXt7wgIJ0SrcGd7QWZAA7jF1m00qdXn78BoFH/3wk+k0+WnKC6zWlXppJAx2/9Nf/vIffvubOf/xD3/0aruTz37w42k6vL19ezw+LMWur15022jwIAgdSXQELEtelokCUfGYIiLPi6YUut6Fl7GAt/Hq6ubVhx+9ffN6un03lSKBg7BaddfNtt/udrurXUgxL9PxNGnN1S2EENroEr6/u93tLnbDJoSYOZdqAA+bngXONC/zNE7Hw/50PHqtwYMbz8hmpJXS1YWENMSNknXTicxMNYgMm14iT8tcVa8uBgrouth1sYvdjz/9wc9//rO/+eVvjnlpGuvrY6ctVuXHcpq7n4U7/cxncjTi59qB7H6ueXELTB8Zsef4h5oVxZO1iInPhhGPgp/nGgmdGaJERHBYtQoQYIY2Ba0Ts4PPPeZYzUfXpKcVQt3ZG+YoUSRKYDIzzSXXomaABRIL4mZkREDNamrMBEJRg9cQw/ZiGLGUk5GsOqrWtOVhqqvcBwS5ZjDBrX+2SZtusxlUyziOuc7Evr+fJTKlQILQkKTI213v7AYZhlQtE8Jmk8zzl2+/tFoD02boan/58Pp+mex0GsfDPM9WMpLEvgvFaq2lHZaBRTGfltt3S+ywueJnL7e7mzjstkbaxdRcF7wicoLhanc1j1bqQxWNqLGj3WVfuOSxLLksczFC9kLVoeRwEe0lRe7/4Cef/eCTT1R1OuS3X+/n6ZBSlYih2w7DNoREEij2h1M17qW7nPcPx7d3E+bnz69bl+uSy8MBMSyXlx0LqVU1J04xBSapGUq24/EAACAASURBVFcXF0GS21wyjkejXFMKQgwVAtd5AbFateLLCbd3+48+fZW6/jAeSilXN5cOXpaSy6KlknmUGFM8nY7zskjgRFbVAVcYMTZ9f3V92Xfbovbl66+MvPrirBQtJJSqVSnEuj/hq6+/6br+g48+Qg2/tS+/+nI/lylmCZQkBGogsLlWklxImiABmNAFdEFCCMy02Q5uvhRf5twaDkUYjq7vhGjJysLMMo+ZRC6uut3FpeGQl5OacoiS0lKLcVWp5ArWYj6l6eoVfvKfPfvZLz5+9dH16/Gre98f5sPhOBavMXXC4iwskbm4wxQAiaQl76e5zAuKIoRGFKRhl1KSZanb696s1roMl7T7uJuXU/OPcVImMSLAa9HppAthG6Z+Vxv9eJrisNmkTobu8mL7XCH397i8RNdLrlbKIlaj8ND3m343bJLQqEXVFOhS3P7yb//u+upamF9/8/bh4fjxqw8+/fiT7W6b62JeyVZbevXcMxJqCgCrre2ba4WqUC5UCwhkxAQKCOzLEh1EQkxNo6fNX836s5ZSazU1ZzBTkBAkRBZhYUInKYqwk5Vaa2XE1KGLYoRaCyMuFU4xsBBTFxrnz90sU80Ti/R9WsydmCkEdz2OlDo207lqkj5xil3nznmpFU4cB2HtiYhNydydnABVzYwJehhPp3neus21nKZRUtyEUHu/2HamEA4pbn7764fnl7sYLsh4GfP+djw+lHffzO8e9ssJqAjb4cNPPiiFXn/1oIZpNNeQa0UFOIUklwkXg9cJ86nUMX7x+f6LLx62NxYifvTTy+tniMJVtv/L//S/fvHVXroUYpiXQ9XqRhxCvOx509OS6kIy13ma7+eF1ABkVZ2UYu27rVWvuRB4d7E9PYztusFWISAmSalDIFUruaiaq0HPjX1MLBwlSpBayrnQ3vATtCp3Mypao7BHLab37I9zCtNqMecljVoVBtYkIPzpJx/VetxXmrCzA+SkCluABX/9Z7+5fL79r//b/8bp5nT83w773xzrDANB2ANzYCODHd+NWxrShpHQmC8GzMW9LH3v224bYmBiEtps+1LzUgvEjAzBpaNOWGKoxlosbWTYdaq6P+5JKPbMMQQW1khFpIaqCgUpkFC8ORmtZsErMEEAYESBAWeLBFW35lO8VpzaMr/+ITyu1O1XQtMsszOa+JRMA+BRVOnbL/uZluRoNEo4nMEUsAYhZu5WHaC1p6R64ezsASKdxK7jmmdZXDztogSBYr88eDZ2IeLT/TFuBAHuzhnR44aH0cckSYjneipHRwE9YwrMAzORFrda86nGy0iBuhRjCHCqWgEn9i5EIRrn3GQTmLBy0oxhbmpVXYQeoQNt3wvfhpZwNnD094yr1iQSWZo92Jo7ubtDzXglRK0lQD/v9v3lfAzIcKZNPb6OBjuec+zH23Jm0jUhej9DPe1vYNXfXB8BAjU1YPP3GxqrxPF47Cfo0yPS1P6xdvB9awjADef88clT+X0Axrnw+f4A5sbgR/yh7aPFadT6oh5BujOi9rgvwntW2iN48ohbPX3xdxGuf0pr2u/bwvce4192+zY2+f6V3/fOf5Xt6RX418XXHpk7qvod5NIfJdnQLCrcGSCIUCu2O62qKOvgJjSAuSFhDao2NmJqZT6sJYNGe5GAKGAGu5NXlcAwXg3wiM4+GOJKauqyzr4KR2vQJndx9ZWw2FCnNtzVzA2N+iPC3nQTiErVag47i7mwGyOQaDNTsMdJBgAMWt3IyZpVcuMycwPf4GBuPTDaShtORCJMRNowfKeG5cGNV7EmVtVaCjEnZuG1Jb1df9Y1RguiDmcWAG7WyKGrKQxzq6qE1MFrK0w9nWIaeIiz2RfwBH3/zn3H+5nmrJ+Ddt+afW4jRbVEeEWvmrmx0TkQaTLqJBLa3Knk3oTvWzSyVibOOGcbI2uwsc6/yo2CvGbGDekSYRCqmtcnymsNUlyFr8ihTbSHVwTPLRgqwGgcEG/N02YiYWWpthnbG89plWBcV2d2UwM5u1Dz0XAHvNYqIaTUEYm5hr7f7S6WUzbNAiJCLUXWce3MbEwSZBi67WUXgrkZcW44w93tvpRaraqbVg0iw67LRMUWELnoui4SIAgRSqigwzI/TPvbQ/r0Bx//4Q9/9uqD51rzn//V8ubudc1TyeNpPJaKvpOUUojJPACp1mWZiirywjVjnDHvbTnpRLVmSrRJNKRIqHPNM7knSYwBwMP92+vr3W5zmTphRj9EIszLVJc8z7P32vcRkGUe94f9PGMzyDDs0CdBH6gPlA77w5vXbx/uTtsuFXJ3aTWXqmaa0bwwM4jp4vKi1HQqx2KlevUA6UNkaBFTg3lDsoZh++JiO532f/bn/8ftw5sffvbq5//mp06IcZjyvGTo3d324tKZTstUCBepZ+B4WHJZnj+/1FCHoaurTLlLkEa+diNwCF1f3PbjaZrGEKMwA85CixlCd3WTjMJSx+NxzmV2Qur7bexjSiLy8tUnpkYsMXDfc9fvQuxi6lnYXR0VhFqWGDs3U1PhwJBadZzmUz/10QGbpinn0iYHFgkhuKNodQLHSAIKmOZxUbu82X32yaddiNLyOJCwEFG1amZBWnt+G/Xe7J6AlTm19hAQeS3fmgEArMSr94HCGaP3pzNHK/G10AEA+fcwnVsHYjuambrruoKseQnMDG0aaLvlMzTfvK4JBHUCReEoHISCCPP9/b02cJnhgC3VoggLG9VclGpK8WJ72Q99YIF6LebKZan1ZOjggBeY2ePhQKDACHAnTiF2KW26lCJIal1MTSik1E1LgZOQEEnLoE1tHGcJQDBH5EBB4lLzNI3zrIEwJCwLdDl88+VkReYp5wWmiBIEwSYmCxGxZzczrTVwNPi8LMXJhwG1ZwvjcVKchk0KMXm1eXGvGqjfdRcXm/T88nPxeP/2OPBFN1A+5WxWSIcB2wHzCbMXZGDGAx42V7tN5z/80YefffoBao0SLZNYPySJXX1+8/LFs+cU+LTkcSqHk1GKHHb99vkClRA4Rjfr0tBvKMaRCJLgpmY5V52XWtXNsxouLm9K1uM+zxO0wDOpiFeCcgrdMs9934FsGWd02GwunXhallyqe+seVLOqpQZClNClKCGAkGuepqJK5l61Nh2C1sBbainqY55AZKQUPHggYooe++AkJS+ff/7mxfPnL58/m6/m38p+P0HrHNhfPv/wo48+fXi450rqrkU71yH1IqGqC4dNZ1GGruu1IudKTNtdJ8LTuGhVF1w/2wphOk3TOBnMPIdRh1nmZegvIrOEmCA2TaOPi1UzNbhCHITjafnhf0X/5o/+4JMfPX/+4Za6zCj1MB7G/WHOXeqI2cHMIcQ+paYDEMzFwQ4q1XKBKYp54MLkEq3a6Tgd+i6VvKiUD18+++yzD+Z8Sn0sVauONqPvryLYE7kiOQIXhkRhorosp2kuTBGdA4hIVxfY7i5z1ikfgHl3tTFlQJxYKwXpdtsbWA2xr9WXuZzixKBxWR5O0+6wP03XVeu723f74/3PP/2PdClYiuYQn7242XS7IQ3SNRapolZkM5MQuxCylmLZTKszKl0YqaqgFwoEVJDDFVWt5FqKzmrV3VCUiFLoyKNIFEtEHBEF5OplqeaIMWqMNvthnGqxTz56JZCcK3NkZiIByExN1agMQ0hU4ebUvC4nIntx+UGFMWKBM7oFxSqlMMiuc0iF18bh4yAsDnJXdxDLAr2dDzfPVGHGNpV5XMZpnorVnMsyL8u8lFytTj/+5HmQztQebh/e3H/129/WwxHTgqUCPdIGNxdyce3H8fDumzsFpT6FmDIbkqkxYCJh2PbehSilcjrlonZwWHHc3Oy0TlNddruLv/j7d1tJ15cdE9UC93ke4QsGQS9JAFUtNUvkTepdypJ2lc1t3qUw9Gk6ZtUiSIFCXdQW08W8OoPgEGKOnLrODZNPpzKu4koijd4vLuRCRq11wd35/UJD1Loqni5U35eofSdNpRa20jmHXxOZp7JB7xe9WoowcVNJMYcGSH775vDXf/H5R59+/Ud/8m9/+9WXt/dvJXqefRkLYKTm2nQkE9XoWUQ5dkIsS5kW1XGqMBvi4OzzMgMg9jREL561LmUm5n4n277XEhX1eJql47SNy+THqcQETgFCCKyuEONexKMtxTLgqKZgNOW3tp6yMDP9X9S9Sa9tS3Ie9kVE5up2c5rbvL5IVpGSKAmyJRi2YcACPPbAA/8DDz3xj/HMcwM27KEmGhgQPLJAy7KkEkWqWN2r19z+nLOb1WRmRHiQa5973ytWySZMUFyDcy/Obs7aa+fKzPjia6D0GLVY+8FEsNpQpkuBafVRE8gjTqKmQcKFWQXnCyL24dX2R1zgEYJY4UUCiKFgriqJussXZuIadW5WJAitQhICoOqalsLS9E0YGlcsYZEgiXLfSiPNorNnmCkWmBTKwiSsIWrcy8570ylzEALcStYZigc7cQKYqSUR0mwo6PaNkQZmh+clzWkhpzY2bWiZeOTERgI2d3MlCAJVw3BNGiVe0A0VQB/LQazwHzEANy7uF5uwevUIEiKrlqzlcWTWNt8ak3UBvz68vo++KKD34/QyrB9jId9jFb7ij481FC6sqVrgvId73rcVL+9/aTj6hfEIg6peal//EBT5HoZV8coPYaNHAsX/m6Oejl/O3wFTJ/mAXUSXXPhHSE29xnrgw9N6fPp3EZ7HMvMCiOM7r/rgmR/+/rdAQH/uQ6Gye/BdAOy3K93+Yof/NaFf1evw79VJPrrIrxeQqXbuERCCiAg+wEdR2+eXtWRZlgqErO9Vx15xSL3DqUZpBIkchClUlNvVzIyZ1cS1gl+uxVgQuUk5KZRKLWeCk6obGAi8mnK5UajR2wxA1VwLOVhIOKzmGebuaIe225DXmEM1U3Uw1FkYcWUwhSAgM89BIoTUamyGv5/cV/zczZ21ztSXx8ngMAUzsTA7FytW1EmsWmIVR4azFzJmdrMKpNAqyczqRiEykVZErO3kAk5/UEza4wGAmGqmkqpaZS0BzLW8dUN5ZIXWGccBUMWXqp5vZQ0buUOrNdgKOIIuycd04clSdazQVVlpRLR6SlVsn1T//P0GTN+rkohBBK88hPdEPzJ4FAkxVBYHLnYAoY1OTgESpGZRwasrIcg9snAjcFI4MTFFU1UzM3XzvmnMgOJmVSKwriSok5QZiGvwY/0P1Q0Bg4Dj8cxRclQi0VK2m72EEJumLIUMrlqy12hjI8xYrJAECg3FxOrldD7mpMsCZPzxH/+b03nquuggDVTmYtA4hEF6cyslF3UAHEEN4mZwdmnb4n44jYfpfrbpNB8++uTpfj9MaXz55hVZ2Q9t24bYknCTlnI8Ljn76V7v7k+H0zwtQAEI+x4fP312NXx8vbm5/fxZ4JhSebg/vNI3d6++Kl42+/3t7c31zb58corMuSyn08Pd4e00n9o23DzZquaSFhOG5RARIrEAQAyhiTHNNM7z9Xbz6uWbt7+8e3hzQkEetGRIZIiLBM9u5hRE2liWuaRlmc65pGk6AziODyQS2sCxKbnoom50/fRJ17fj6XR3uDPNxezH//rP/uj//LM/+IM//oMf/d4f/M2/87s/+hsv37z+yU9+GtqNkc0ljfO82W+HvumWoqfJHQYFkzBJ06g7z9x2MZzy2/u7KS03z3Z3Dw/H87RkbyyLCEht9nzAki3Evm3beU7uQSmO4+hjPpyXtuuYadMNX339q9NhEiAKfuezL7ho/7sf9w0JEUvcbzbntpcQYVZSefLso+vr5yG0Xuh8PmvnOafT+Rgj/+AHP4Cjb7v9bk8FEkJK85u71yKcrSw5Ocft1ZNnT26ub/qXD1WPq+TExEIXjlM1/MzJnS7OhQ7i2o51dybAL94JWOXJDCaSil45VQVGvde/Z5iAUkoFp94j5pVKWSW6Aag7u9XYsFwadquu5NJlvByX3RozEztJVUELiZMwhIzgqqpqpTpYsYAdHsFRSZRCaI3ClEZdlDxPxbq+Y8g8zzkVCqHdA0eGmAPi7Ga5ZFNiIopck02bLg77DTW8zOlw/5B1YbIgITsFjmX2nIBYPICiOeUQSRpwqFRR44ic8rQoA6GDcMcUg7VvvzoxqSs8AwUa3ElLWsA89H3fDbmk0+GQdKnzIBYc8nQYz/gl/sv/+u8dx1dN5KZpC8eXr19Ooz653sUfPtvvt8INo9lsvaSlLBmdP71qn1zf3t7cbjabu8M7YfKiuhg7WvB4PG4G77p0OJxa4qt+O8Gvhk1sShc3Tdwk17d3d9++fpcyPxzOCTm7zIlPb+6M+aNn17tdiN12HL85nss4H3R1ai75BACbAZv9bn91+83Xdy9ePJzOgGGZ7JBGPwDZpWcJsYmiWtptv3uyfXt/fPPPXzz/6Orps6u+7xnUiAxt1wi1fXhyc7XZDBJDjJGZ5+W1Fm8it52wBAm9KT88PEzT66Lm7KWSfc0UVAhcMC8TsRfFL7568fbtYfgPNn/49/7wsy+e/uAHf/Lzn3zz8pvl9etffvmrX/7g8x8uy7LZjVlz7KIEgglcDg+n02ECpv3uuh92YJUmbJsYusSRmGm3vfp49+TLn3+V8gwBkqelXN1cdYO8ePXO3uDjj7cxNn2H8KSUnU5zZsOmx/6qRbP8t//df2M0T+nhMN8dcffTn/zJwzgO22ZeEhNYJC0lLTMQmELb7thBEFUqxSV2HFM7LI2jHdA3fSn+ML4txccJm2t/cjt0XXv75PqTT568/Ppnw7ZXi9zcZi+JrIlhu7nqn3Mn1sFEEzyJGIsHsqbhrgsxNhFd1yJwm2xycmbf7a/bKAC/eX04HR+GJt5cX33y/DmRv3r5tms2d+9O5/EQm7Zt0W5aJ6S8EGO/38VA6TBFxdUw3P7+7WdPbjbSZvfs6lbAuXgurnO6n3M6ZzcWiR1CK4TBL3Q/6Qy0eEmlJM2GbLY4K0djeCdtJGFnNoZ5KVmr+1IhM/fCxNyELsQuxGef7EIBUoE7b9reSdSRqgLOSEAEPpQ3ztkpL/rw7nD/6vXXr9++/sWv7nNGpW/GiPs76IKh24XQjuN4fxxzQgj46Zd4co2+Q3E4cHvdPvv40y9+/3eeffxse90nnRZHiM3Tm6cSiFc3VlJVGL76xZdtbAhYruiLT5r/6O+DSZasb+9PFNrN7snDYfzq6xenlw+xxW7T3H70jCQex/Nclmy6zLMnaygH9DqxTZ6ydkPbtHp91Wy3N01o7t6ch1t5doNtv+e2PU3H88EpIE2ILtxEUp7uz+NxTmlxU5SEDb744WcffXqb7MhRI0XPpzY0OuP07nD34oAMpLWLzMDiBTzv9vvNsNkOuyiNJtVsXkxz0eKVKZPdqX1PyiCq9g4QZhK34mvdTG6K33S83x37Y2J4pVmtlbyv+SQMglNV2MFJQRnkUCVXLcrG4wN+/H988+M/+p/++//1D3/0w0+y3//Zz7+6e71M5zQvU3BxFVdQwPwwJ1uuwvbJzfXV7mbM0zifl3kihjupai6zO9o2DtueF87n07iknHLOHiJCDM0Wuwbbfd9uY9KEgExgKnBL2YRC7NpuMwxm+ZzKuHAhXdb0F82q6lqMwRLFyd0MEthRw0rMIVQVmfweuwAAVypMVbfgMICdQCQQYgE826rk9Eu+8COccQFDnBiu0LpbQI0RRd2LMFdtihtc3YtDiYTXDjk5oEbmZoElU0Jrfdtzwzc3+81m8MWHpueMVnoxrmnXRUs+p3lMp/7kKFdhc57Gc55mzdxzv+0rCd0LuDhlp+JmKpFy0UkNRsucSJ3BKSe2EOCYoObKykYOD+DAIk0IbEJZTLx68VX9aU0+d7WVy0Y1RiA2TY0gMziYhSFEnMmYiSBZTdcIzcfhTSBIcABWvI5Px2W4fpdb+PgS4e9VU5Ua8ggtrb/070I8vpblkEo+qTfmqoG5gFDr3ZFzWRt7/t3KjeDsAL8Hvb6LFwMQ+f4uEb8Zz6n4GC4nAEeVDV4+SwVniaqmy76DMdl3KYcfHo92YN8jVf0mUOUvxr2qR/g+nPaXSYP6d/K8/goZWI9//a8cunoELB+/1+/Bk25rStQKPawN9kueIz1CphU0tUs7n4gJAgArDnF5OXEgMBmb++oMToC7JjVTV3NzZ2KAqs9URWbEQSAhM3IH2FmYRAherJDwqqKrp7TeEkLCTKRF3SuhqxqEr8382v7d7jauqsWsmHrJuQRB2wQWXhGpx8rLLz38enngORd2fuSGrrQz87oK1zndQy0gdS0MheCupTiz6aoNqNQtd5hr5V7ZJVr4wjhdvxoiUtcofW1puDsTMwvgqtUOjLE2spigtE4cl9N/j3dTncxwUfPhsswxoRrIV8pV3SO4u3oBsZFDQPCqCTWyUrkURE7mBGY4k9t730M8YpqPc1D9Xd1bVMZH/cqcavyEgL1YoYoPOUd2dgiYeQUtVzKVU02M5BUzhFRm4Pv7y6w22fw9CfYyxFdDLjMnJ2arwk9jclQDSnPKOcOIRdQ95Zxy5iBNjDolUo8MUyAA4XJtnXLW8Tzur/vKVY9iHnE6zixC4m4ltiEt8zif2xhDG9yVgqMkBySCAkHYgDEttJjCm9g6cH98cCl3D3z77GYuY14WMyU3CZFJcnF3aZvu4W5SJdOApUCxf3rzdD9s2mf7/qOh2Xnuv33x5k//9M+++erlOC1znmIXu2FuumPbRMX59mb39NnN1dXT65ubeT7M6ZDTXDTlnLWNpaSUkwTa7bZW5lJKzqPlIDSMh/Hh3eHhdICgbdvADLdUFhBRYJCDEdtQM2iWNB0PDrYoUEdBDkwucHXLpVhB1ukczPU8TULCwvOybNqt8/z29Qj/Knb9zbPr5x/94N/+5FfnMRUr45KWNFKU0N5sd51bP89T5dpx4N1uyI0kCYycpsP922m8H+8OD1NOxjWWXUJsACyWs+ZxLu8ejn1X6qgq6sXYydmoZCdxkdYK5QRzuMBNLNvx4eibhsj7Ljax2W52yzyfT2dBR89pMwzu4ZRmhzMTMdwtBBmGXkT6pgvMWZc4RHReUmYBE7q+NUiMoR+6zz/7+F//2dd9U9FiqzpsMxQDr4td3T96hZPWDurlBnOUR2IkA7bO0/zIIF8XAbrM199ZKS5TCK0TUXVjJSZiBjtw8RaE2WNhQXj/fo+TTyVD8cVC69I8hwgCSAS0hkjAPcaQUtFsmgyETpSdG25jE8EG8nE+n47j1dW+aRpyGX1WNSKiIM8+fz4dx+PhOM0LFCC0beiG1omylWLK0UEKkKqllOBKkcx0mfJ2e+3qBiN1Z7dsTuRgc5iWZXJn5eT90MYmWlYBYLGVzdX+CejNRvoCS1nV1LNIaPtuxywxxAhxR8M9GMTiIXLDFLz4eZ7G6ZhK8ZKXspCrUInHe0Uut1c5kN3fJfbUd0NsAHemEoSS5XfH+7vj3e2zbpnPKc8lFzGEpgnx1HTJ9HB4eHiyvbq52rvmvt3E1gN3plhSHs/pdMqLxXE0FTKRVFwZWnwaF1UjbrqhP6fj4VjcEAJq5D0BG2mHYbPd3/rXh5xUCCSNSpuzjYcz1NM8E0xLMtcQWkd4d//aBU9uyd2XZYmxBXnXNDJ0w9AMTccgLVpZOfv9JmdlEpJAFCT0abHxnEyNiQsZ1t0tWXEXkLqBcjYWvHn58MreRW7Px1e31+3v/M5nVkD27f3dfD5hd7XRdzot6XQ+t4v0264LQ5R2GBC4NXdiyTnFGNouFtU5LYuOjbRtJ6Ylz1M6lwrz1ljhklQImyH03ZCSjdMy56yM7gpPr/HpJ08//cHzJ893P//mxxmjS5ltin20jjexIdBmiMzRqZvn4i5m5MRClLJCkybNs3/8yccxdsPmYV6WZV6STiBydgM2e3SbcHXT933nSC/ffnsYD7fWtC1uhv2YllOeWaSJoQnMnvI85TzFPnaddAO6PogIwWFOIssMKxMF2vQ9SI6Hs/Vd17Ra/DxmFOw2DpemiaHpglCQvNlcZ1tY0PZd08W+67pNa7AmiLZxF5rb0H48XDVMxVLSKthUCuqsRqpWEtJixRDYIYAzhxiEFJ7Ng1LIiqX4omYoDhUxihChtMwlo6OGuBGKMQh7IINX3UxkEkRpHG3KxNxvZX/nY4xboD2V5eE8/vLrV7/86ptvX714ODycU9IooZdusNCl7IfT+CYbiJEcqujb693NZ9t9Mx9lOdOrl69fvk6He6QEIhxG2MIhcilq6oc9Xr+9f/HOPv5s3F335+VhTg/cmCMT22Yr1/vt9fX1dju0Ev/m7/1tTTpN5xMdxCVLypqL5i8+vy2gt3dvxuWh39jv/ejmnPQ8K2g0tP027tr+2xcv0pTzuSDPXGYsgbTVZEbLGX59/emyUBRhzqk83FwDsDkv01TKoj26ALTS9TSUye5evsUxowEJqMHVrv342WbT8yk5RfHicGfinPPDdMAMFEDBRmCSumMOnlNJITGCFStJqYrOjEzdtZYVFrrVToJq+HhdsD7US31As/jOYlTXobpn/F4d92EHfa0uHmlFa69WApgMng1FTV3hGiAiG9Hz+M033+5vutunffNCY1cXNJgrG7t54Nah6Tzfv/FmCFvuU8mH01lLFkETmr5v+35wWGyb2EYOXKwYTTBqWmTMpZCxhYaUy6ILgm/2jREqYc/UkxUnCbElY2UrZG0MbDUf21xNkyPB3GpBTURBWFjIUbJWk6xKx6nSfNBqh1JX7QoiVKcPX9k0xMLuIFXwqpbwtWvvDiZQlZ9V/K/COpUHBCeoO7lyzZ5Sq6rncpF0VPYWudWYPiaFkoMCSRQOfFpOczpFdG3bAJgO5+lhERMtVmvCRee7cLeU0aJSS9urzabfn8p41pmo1iguzI1QIAaYh5AXhaKk4sl9QWg4xjZ4YOfI1fGXcslW21pigZyN1K0JTS2IzR1ahXgXxX+svQAAIABJREFU1lNNIySC1Jxmt7rhIXcmMCM7EwVhBwpU4V7LOAgTVZonADWo6cqWcgKvNdBliBKI4EZMwvy9qhzM+PWQukdCYg0QZFzcdB7vKCJcysmVfVE5VNDyAd5EH9x079ldHwApH/C/sIZvfe/m+3eAKt97/JGE8TiSsQ6577wh+fdf+P7J36VifUCsoT+XHvT96/kbz/PPeUL43t/4y+Be/fU6/gphrMev9kMA67G7jg++QhYiITUrptDKibQ1LONRl+G130941MQRe1iJSXWyhFc/dDY1LxcLbwKEiGiZU2VKAc41qgvshhqpySxYR6S5qQsxEwcCSFSKPdqdV3c8BsGqadIjzZFI3VSLr+/iDiepoXRVKyJrIB1Q4PESt0GMmlKv9P7aweEwqBmIwMwEd7NKcmAApmC4SAghrqQ2QEgksNbdGxO8YlAKsASmwE4ha3b3ECOAUor7xfu8RoQRoWrKgVUJvM59JBKCwC/uZGD36nBj1X6gzmFUitXP5QDxyvB9X7ISgYnIWaR6ENZmjFW7eawtiUqmrT+dVnooy2pO6Hp550s+67o7uajunVZvnkd2qz/CSZUHx+KhJOaittJbDdV+nqoFosEMVN+eMjMzzJgQuBESMFhqxZlShjkUpuaPClH/8ANXIy1bcS81CBNDiESaZImcmMVVU0rnaRKCBE7m7NQ0oSyqcKq+agEk7m4pKcs2hMgMXTJgVqzf9EWXKaVNF2OMZclBuOoigwQOMC8OM3jOakwpJ2iiQAQxTWkqaUmn0/Ef/hf/4MnT2/PpdH73NifTaQnihCZyP2yuv/zlK+FewFXn//zpRz/84tMffvpRG5ovf/LN25fH+7uHb759+fLdu6q4RJcg5xp+8+S2PbydHt5OT59vb57thmFo2kZtPhzelpJjDObl/uFg0u2vdzH2y6iHh+QmV1e7P/0XP10OGUUAZxLLHttQsgPGTKWyeohBDoGbzeMonTCzJQdXZCCrWtYCV5aw6DK+O4Jov9st01IKJs05odzl0+F1DMOnc/7si8+/+Pz37+7vljKplfuH86tXxxBwvW9jE3VKu9111/Ula43J6dpWNyE2E3gCYZkntVLvBWdIiMxizmrmTqfTtCyla1sWyzkVNRE28yUXncu2zyJh23WadZry+TTO06K6KVmLzkKtMG/6XlMe0zxNy3ie7u8epjm/e3fQZB999FETg5qKs5kGkb7rNem8pKVZrGgphUPImgETkSbIR0+f/qf/2X/yj//xP6MGRFBXd4+xF5c8L8QVur10BAioTu0g5zWd8HHJrwTLOk3XX62Gfevq/D2i++U+ofc/V3w7rNkUtkaqftDfo0vMYV0EfFUlOxEzLs6H75leBqeKaAtTvdUd7prnwkDTxijR3YJEcrbFUlnUNOdiGQyaD4sggHk6zakUIcopT5idcXN7E1g0l/N4ViuVcBZr95CQy1LmeckFRUkAhbsjI0s2EEWRSIBlVVd3I3NiD64CEMRj6EMU5ZKmcTxntrSJWGu4UjwpMrFIE9o+Dkxclnx8d9CiFLhSQLmlpu2kQQlWmvGbr19Ku6hn9nMXd/DG83z/av4SryNt2rgtKR8O4247dH2jIZak4zKaU9vGolOxUWkCFweYte3t9knbtkQou93mi8++6GILViJzD8ts05zMqO93x7uRODatnOb54ZD7DZPQ+TyZWb8LT55ed9vN/rScTmOxzCBmDoF3+0232eRF56nkxbRATIK0bM1iRwiXJUnjRUsTxVznlHICGG9fnknydtullEw1Btluhu2uD1GS5XE8H88nhz179hREp/NUiuXs8zzlhFJUzYncQFoX19rrZmeBNMLJc7KUrBT/05/82TRt//bf+vyTjz69fbovuWy30+sXx3fv3qrppu9CaAqW8/k8FmtJS4EXUkIpSy4a2tBvurbvm75pU9e03e5qe/z2vu1j2y3L7HHA/rqPkYuPTYfYkbmFlj7//Ha/7Te7ePO03980wzZI4xzx8y9/qoJ+081lgvPDeNp2beRALYl0uTAzNkM0ZXdKS56meTpNBDQhLptmSbkbumE75FzcrGliKXlJaRhakDatLGlalvl0Oov5+XyMYTcMQ3bKp1Pb1yhlitxsdl2k1Lfl5raRMBedDseHN8n22/ZHn/7watuPE6bzxKHrOn7x4v76anh6e80hMIVp1tO43B2On3z87Prm+uc/+SkTb3ZNDI3EXT/0XdfstkNKfDqe5uOZ4de77W0crrt9reHa0CRNtbyrBjMcWEy4qBFW2S44IpDB2ZzMYTBb63J3hxoVM1eiliXGEKkN3AgaQYRJbJri5qZSBYIcCT07BxqmRP/kn/zfxboCOc56XtKvvn3x1asXL+9ePoz3s6IQmgG7K+yv47AnaVbCJnNIie6POZtHbg5v7PXXx1/87PXhdHaO5mxLQcB8hkKrVcXr+9y1d9sX01e/Olw9HUJXIMl5yTqqoY24ue6fPz09ub3a9btffsMhqjQ5ttQ0V33rHIkiFehcEiAhysP5NGaNoK3140zjsuSCdKbTefIMVaAQZbfkVDKs5HNxx6ef/W5Or++Why7upulODct8SN6CAoeOklAGmMmoobgftgsms6JSQo9h4CD57YuHt+eHdtsFCuMxlcWswNMl/qhK2kGuDlYiznM+K4IEL5ZzIXMYa9FqocpEXhef+q/7e9iqbs5tZflcFA+CDyrr7xI/aPUc4tobqU3Zi5bqOxDYunM1KyAQct2WkwhRY1WucYX/7R/97//5f/WH1ze73aYdB0cLAcTYk1s2S8ohSAn5Pr3r33L7RIMKhNjN8jiOgA19K1GIQIwQpe9baYSIx/tjSWrJiNAPbT9EYVKTqyc7NYzjRCHmrGVesqUpCxfM0xnJEKnrIishIERvolmrVAiZ7ALg1y3+mth9aRVXRyESXBKkKoJU+8cVpTIzq54wEDBQSxqAYPVi0XvWDFA9uOjRecZXSUc1h7FLVQdzGImLm8PWDlUQgYBkPVuh2qdODcl5nht16RiZx8N0eHNyBQqCBLBrsnflfkozdui23PRdd9M5MYpM05g1k7kVWCJOcPXYei65jU3XdbQhbmhoBzb2TOzcbTpBICcSXlI2lPpxmEhM1qYeOVUOm1/gq8dCi6t5LtxhXoXdVBWafLF2cGJ2K+pY7YNBxHIp4byYQWsa1aMIEVbpcr4+x/jDPdiHJIZ1i/XB+Ac+0MrSJZ9n3Qq+v2lW9xX31bO9flFsa+31viqi7yISv0ZZWk9gdei/nN9vPX4dfuJ1Lq93sAi/B6MvlAszX5li33vtB9DV9wAsXMgf3yPifO85f7EjiMijTdKjVO1DWtZvf/cP0TW6yBI+RMR+0/P/PT8+/Ah/Sef8PViKmUN4b0n2+F187wQu13nVb7m7ZfW1FLl4+NUbiEHCbOuQksoqYjIzAswqUFPRJ60ZdVY9pKq/ElGpvutWyx3jGioDCLmbk1ZQhIMIMdSVmIJUtidF5lKKmRKziBhgprjI39TMzYhICO5uWuOziAiqPk9L4BBDlBgAmKmZOVRrzB2cWZhQ1FZyVb2jHGviIMzhquuaICxMbOrwGvNRCbRatKjqYwyhldJ1XfJcLLlWGioRc82bN3dnEmYyU80gMNhXCywnojRPphWPIRdoxdqYV7CtxqmReLUpY3JXV4eZFyDQxdrPgVrFkq+cjGrzvLZWVi+yijvCnbD20ehiPn8ZH6sasX6TBi/mXgEsWpe3x2nuEbe6qKrrAKp0vTrYSinFixYFi0hF+RTE4uxaZ1NmCDu51u8TRiuNGSqFQcQwQMnNy2IEggIXoKJmJhZTIqyXKBAYBnd1yi6MIA0I5AxEONgQYhzP5yWNncSmC1Sa810SNgqwDDBCUDAMnJOVVLp2Y0rn03leRnOQed9fW5bj8YRIgAgRENwgHJhc4ZqLKpRhljhKE4R5Y6rTaZ6sICA8gATffvX25nYbqKRFdUZawEwiMUgkxzKDLKFQIKjgetg+3T/Nk//4j//VT3/2829/dYeMfths415Fs2ZLbqLEkMhv3yyg5fWbw4sX/Oyjpz/60RfPPr7e3zSBG8BjDKrLkmY0xA31u+rD6pri0A3nNxMKUWYnLDa7mljgwEyRnZlMJJZcqrKiqMcmFvNU3IvzhJKKkVkxWsVnDvdAgUjymMuSq+dqjOROSf3rb14fptNX37z4B//xf9j2cn//rpSHbctB9PDmGKzsrzb7XTd0TSBRt1VJQMpkITgLLIF5CZy7QNlh6qYeQ2jbFWdNJc1ldBr6JgiJk87z7LM3jXRdJ2JPn96c5Hi4PwbGeJqZmN3TPBOrltx3TWlCiCF2sdm0D+NxNjwc5sPDUXNe9Pz82fO+7810nGahACO4aMH5fGbwfB7H2ZshFl1CkJyX/dX2b/3h38Br0J5jEyxpXlSCRQmmXqxYVriFKKtkujbJvLKhiAAj0xWFJhJnFrpQ4uFVU2BroqvzZZ/i9fb0x53V2hFQ4tXWnarby4p01y3IIxztdbWpyJozgdyr+Vw1DQwVaYOs3nrO1byjBn6YE0mIEmIMIcLMDPNYNKeiOmuCFhDQUOFlOi0kYImbzaZozuf85vBqd7W9+eij3W47juP0ckqzuSVmcSIzNxQyL1OxomCCspJBHYZMkxOTCpwpOFXzXKg5AN60W2OdyziOJUZzzTllz3mCH/mAhBEzQwLHrFmTuhUicyvz+XQ+H3jt/JiyY5pUp9ajbG0b2zJraNqSfJqn0g0kbdsPD8v05uF+ePXq8x/8zquX355fLmnx66fX4yllT8tZpQ/7zf7d3TexRdvsmTWYP7w5/f4PPr7Z3XZxu9+Wod3ahvTKH4734/n09Nk+L/PpVJiatuUlv4lNk302m+cpbXeSloQW5qXR5vbJ7TXx23f3bW9qjTlMM7OEgV1wf3g4Hc/jeckJVkrP3TiXqmWnGKVxZkXrTiXlMwBkvH03dVv56Pn1NN27ZWIO0kQhdkfxaZzmaezq0XcGPx5HkKvlKZUpLWNSIkAGczIvTirwSCRMQRhRcrKm7d0XhzyM+uLtqR0OaPKTT9vrp3L93HMq5O08Ne/uDofXlgo05Yc5n6cSpRuPM5iIRWLeX4WrWw5xs78JoREP1GwFx4IOTYcEfPGjq3E5JddNy7vrbrsFRTStXD9ru20YNtz1TjTPy3mepu6qmVPOVtpmOM9nFJhSymqFNJQQ2k3bqTIknM8Tu+TFUwaBzeknv/iya2W/3Q6brum4G9rNZljmdH9fSLDd3N7f3x/uzqnM5Hqz2SBtbN48TPZwzscTn5o8DHS16Zpt126H3aBNOy46EoKV7d39+XQ8HY+Hm6v73/vd3/vZz14dj4svJTuWjLkso45EZI2XYkcbn/fPU3Qj+vLtw5PrNp1z29IwNKZF09x4NzTBxfMyb/rNNjTbdtvKQC5iHJzZohEBmsHZHGbsTWQRYkEn1EUKFjt1FyKCBpSBUytFoaVkgxACeRDjXdNEMNCbd6lItsCxP1pRJgQWagrs29cv3ty/O07FnN7c3f/P/+h/efUOBXiYkFFZwGBBbBAFQ9dzAHMDlmLmPpNoUbXk51O53f/uqxfL8e50/2q8f3M6vJ2bGPquVcO4FEqiWsAemhibAPdlTG/Kcr/M8ubuH/7Dv3s4v7NCKFSW2Ul+9WZ6+Pb+/mm63uT/8X/4px/f4ukTPHt+8/EnTz79/Lbfx81Ne/V0t9/q06f7t3fhZ796682xCKhcb7rNw72/Oo+n08iKQpCWEaLODCOWEJ2F27Mtz54/+eXPfw5f2rZZ7KyMxcuinrmVNkxvZ5sKY7FBh3Y7POnbvUzjOKcCxm5/A20O9/ffvJ3jMO/aQZOncy6TcQlRIjNXCUW1mCWCFVdam88koCiai1qBF4BYhPDYgjRao0YqbuXk5ASStZ9IDoIIpFbc7k7VppV9Zfi4v6/f7UOeyGW7aZc+jTPXDiZDUaPQndi9cIhE6st0pi3+2R/98fPPd3/nH/z+H/zgb7/65p/+8Pee/Ownb8ngQgBrAU1ODI48vSnySWDR6yFm92UpJJrKSFk7aaMI4KY5RmnaaGonU3KAIQIODlH1xVFiIzqXvpWmbZclsSlA+83wcDg20iaasiZiEUgIIYjEgCyLziXnYtXOKFzi26rfC5nbB+3mwLWW8bXYCgBMs5o53MUh7jX0kSMbw+DkVtFGApkxcQVYvK7/K4uHRAROahfFl12s4J0A1poIHtjZHAaCmUcPTHDVbTvMJc/THGLzdHj25S9fTD7xIssxNRYcZHBL6goYJswcgIT5aC9/9eaTXZSBrrZD14ZlmefThGJEQSSS8HE89pumaYMVo845AME0aXZj58S6GTpTs0jUC2b1DFPz1Y2eyIWcYQwX9irLVGYGE6lT/UgkBiVodb8RCg2LhbQ2/9zXFb64QanGbmL1WQGbrMXkpYS+mDuQcwWWKpRk6hVPCqsnsqsr4GyPuDEcgBAI9Run9RWAgyGPZqYEfGCRVat7ZqCs0DFd7pgVjXl8XmWYrEIWqsS7ai3DThWxxGM1WMGED9EGh/MFcH5EDOpnubw/kcEqbYXYK6GFv4PqED5A7N6rIL+DV6zu2///wVW/foQKV/0WyOm3HL/+ql8nLn0IvP01On79nP8yPgVdHPjxAQL44d/y32QtbxdajrsqCF5TSB9HIzFzIGbWuRr3OjO5k6ubmV0UfBe3QDcYMWKIJAxZfaxCQ3AppVR5orqLURABgbhO+yvuZDBxlnq/VTgFBCU3Y/Ajsls965hZ3QGXqjH0mqPOzOJmtc1jZiUV5SqpEV8di4kA4pUTXWEauQA/5hBQkRpmv47MWvNVxWCVLrnDTN1AxpaLs3vlhBrrSqXm9VY2dnMXkhBQVHNR4eqwBcDI4aQXWwCkbLXeFJAzXBWAVR0RuxeiSs9alxMmcYFagRtI6kNAxbzIK1RIBCJTAoyYdPW9Wi1PAALjkX5VKRgXFBnVGeexL+DMztVpmogu/5hfwlAqQYyZ7NIl8EcJqJmmZGsqitftB1YYlIhUyIiIARZTdXUD/ALUC8i9QKUO5+pHXdwvsFll2a4aQzPImssmRA4oHAYoWAF1DpymTJGdvFBpJKipRAJ5DBK5n6dUV24J4AgJUIa7FTcA19c3LGEeUykgQmjQtoHbuBt3KZU8J4GouhmBPBJrJiuuCmJQ0NpNdQExNxggFoMbspB9++Wrvu0skc7QGWUhd2YSDsgpC7qU55JxPfT3efr4yW2Zll+9efcv/8WfzOexj70RoKIKcyGYU+YKnzq1zA7zGW9GOx5ftTJE6a52V1e7p0A5z2/VlhBLwlKcxY1FNptOuS1LhgIulXJX55mSi3jgGC27FiNw4KBkUCvFyMwZkIDeUYqr1oBSUmcFoG5WFaGmGiiA3d2qwbGQzGle3sxfvXr7+e9+Ogxht+u0bDyfzHxZ7HxcdptN00TLli0TIMJ51mUZ1bjtqO0xLRDOgVVETanqiDVY3WGzUM45aVoyd3HTxSDi8zJNSxGJXcvuqYkk7IQMBzwHIQlsJRE859T3ITTSbVtq4267z4bDeL47nQ/nUxf9YbzfLH3TCdTPJTNoaDZt7GKIVjSXNC0TFcSOsxbWknXuuvb502e4AcjcISGkrMuS0YQg0c3UCtbdPFYaJOpGk7mSq/gCMKHyJlfLqzp/2SUSw/GeuF7BpnV2qwhwddAjWM11hT1yu9bV5DuLF+NSbVy2T1xjZi483boeOdUcRV89EM3d1FWNhBykDlJ383lZqARWyckJDA5OxhZW0ph54BAlhhDzkBsjIpvnM7PPcypazMyImhCDSCnQXHLJnp2MyYlrjpYrzDmbVfdwB0WqYbK+brW8zCUhnZeJFwqRBMautSNULKOHJWcniixRStGyLLkyX5fSUiBQSjlEtEG4JaJMqsEDNcLEbuzOqpyKsjTdpl+ylZJe3b2+fXbVbNrtVd9KK003z+My+Xiy0/3p/m7aPNX9VRPaxkoJhGnkJ9efXO+eBO+F5uNh0UJN2AinIBTjLiXkRKn4krK7kljJs+kisC62cHLPYMtlLLknaYJg6COIitu8WMr5PNtUct8+zcVUK4kvCEtJC4rBnRqRAImIg7gXy3NoagfEIw99uw1cpuku59PxkE1TI0Ny1aIxtm3bllIqDTmXnJItuaRcUtZSwJeVs26o2bwaY0ZhRAMhhsYaJ/LQbMaMwzRtBjSDu1rs5Xc++5svvz3+7Gev7r5++Po1pEOLkhaUBPSpWsC4Wik6NVOfGxYyWgpo1JyW+9fzVAi7a+x6bK7BxRCb3c2wv+03m4YiKOA4HR8eZj6V2HqMtWFmfXfNVoMFRZN7hoqakSkF19gIOGbHOC2HhwdGm7NKaJnFQWZpWfQB51TGfojtsJPQEWux+XQ+uoW3bx+mMY+zXQ/Y9deRrk/v7OWLd1+/fNfsuVDqBrm+6tOT65vNM2pM+Xyeshu7xiUP4zhZXl69e/fJp0/fvX24v8+Rm+v9/jx/Kw0ZKQnLIAxH40Vs9gzkTFg8l2Qu3LmQF0+Ljqehb5/1nbXt0Gz23dCGBk5LolA0lAJTF+UOEjhQU4gDhygFEEYjJoSg0jk5wYAiSIKZySjAiOFBuQHFEFpPORWLceB4xWHIFApiYhR4hhbgPp3+1ZcP//Lf/Mk///GPp2Sm5bQIdmFejIJGIqibmgImMEZTxQPEkOjkzsSiWuZ5STlj6PZvvnn4+hd392+PlAAHitlUXCmo5KSoJtowsK3BM8KuvuS83z85nk9pXogGJBmnZTyhvR2WZnj34HiN0xnLS7z+6d2vdne3H++efXb9d//+j7ZtL4Nxmz+6+uyT55/+7NW//fruJ1FjwK73cnj98Is36eopz0ZGwU2cXKGiHjwwMRJCtGwTU1l0BBoXIELJzJVaMStgEFvmnGiURjhiaLveGoeTNOdzWWZnAN4S+sikmM2zgIumOoWDcNGIoRofiUjTRDAhF3OFVboKnCpwosbsNX0a1US7at/W2nyt44kFTHZBr9YN+EXd5O9b73X7uD6+Hk5ORI/bv4vVo7gDKHxpvbppBtxdkRAMf/J/ffmjH/zh86tPP//s2auXJzQoauQBQqRCCWAnIpzhs4mg2fKSoeIkKPCiS/FAkSmyZ0BrO8h3/VBizjmroViaZncjzR5joyXBmNH2TYjETLTb71TLmKakcOdlHGFEHltEUeQll5SdnDsYAIe6woFmLdlgRgZZ4ST2lb/ogS557cTOal799aFsprWeeGQCMcjcai1zQVsu6XtWKrdbaicaTI810AWyMOkaFkDIGL5aGzkZyKBZBRzMOwnRY+sBE3JSmpUynAFFgBiRkVm0IMFFNRsAOyESu8KWcrvfYXe1NJPOxIlZI+ANBY4OQyqplFwK8pLySF3XxLZZzjNTCEP0AisGJ9WiSakQGUVEuLg5uVBNAlvJ6Wsbn03YhETYiJzEnSEBQUgKLTUEEwxU9kKBa9VOKlUcR43JndfBfqmK1/G+Du7aP7TV4KUWfURkZHypMhmXhOVLqlaNHXQiep99RQDE+UKEXzHgRxDAK6Puotql1R7CH/OmcZEfrgS0Ry97IpgT0WO3ed3JXWrADwGEyo+4IAaPCNb7p7kDBltxg/en9/59vov02EXZ837P+Ws0oL8YyvTbj+AfWMT/fz0+PJu/jijVX+3x68Dk4/EoIfxNr70wbQgAM68QzeOdUHk8zBIk5QyqA7boCqqYFV8prER1EWFyrjHVIlXWV1Q3fadaAWp/VOk6QUIM1AAGImeYGxtZJeNUR2FzwED2aKpS8Qj3WmBpIAKJVPqkEhzCzEQmTKabbkgpp5StGACOoTpvEbGwwOFuWgxeDZsAPHKYPXIAyLSiSRU1rzowgLgWhF71jeQQd81a8ZzI8/n0/usAUpnJOLZN0zSZ8jSOWNL6sKEGGMFq+8jK43kQUE93Lfwq99Wg8FKzdJ2ZqwAzkDgh54xa465ouhIHFrnMOFYVyeZGdV3ii4M7Q0sG1q8H9ji1vR9UVjXfQkTkBne+pH+Bu/eTIVGFzCqFrQ68aqKDOgawJrxeZjx1SJ3YjVlATuRkgDHM4QxyELuZk4kErOszAJSCVfgEkBNAdhGjro6stVzGReEY4O5qZsWXOYXt/8Pem/VYkiVnYp+ZnePLXWLJyKWyqrKrqxf2wmZzNCRHMxQ58zLSz5pn/QZBb3yQIAjQgyBA0IM0A41AUBTXZrM3dldVdlXlHsvd3P2cY2Z6OH4jo6t7OKQwIwgCHYVCRsSNuH7vdT/H7LNvCWAqKacUukXTdZ2AmtCuz1Ydxf1mm0YtWowwjXAgLnH/wcXp/fOLexfMtN/uQgQ5AnMIdH561sX407/5CHvT1jWXEFoyA7GZemGBEogp5JJVVQmhafvFggOF4GBNef/i8+HhgyGKaKZp9O3W3bPalnls205VmYVYz85Oz3H64Qcf/OWf/dVf//kPNp8d0KDrQCRatKg7DGQeHCAXMnMyI2EDMNk04GdPn2Ybl+v24bsnj9dPfvrRlXtsuhWRZAppyNNhbHgdoxyuNrh1s593RACg4DA3VU0pNG3XtQb3SYtmzSzCfdO0fXt1fSlHOIQr+mzEFfx1lZq7zQS3oqpqJKheY0j4yz///peePP7gw3ffe/eDZde+fvl519rqZPml9590XdxtbxwQCV0sA6VJ4F27bM9W3dn23qbkUkqeMxgcpWSaQCKoRGwvmpBo9L6LsWtDKGUqpbjmcdiv+hBImharZRt8evTw9PRssVwtxkMex32eUoggQtu1i1XT9yfD5GZKxCWn9fkZs6U85pzYGWrjNBzGXRND20cd0iGNU5raLpq7Fhs9GcbYrC7uXfzO73349OmrV9e7xWLZdEiHafLUxpYlwC1Pk6uxCCG4Oc9eGPNqOlc0VFfs4z17nFxVTqeYo3WCAAAgAElEQVTPlT65H+sghxPqBPEtJf12+nUkbB5rlF+xj7j5TLfUIxWMKxJmrFSDYtXMUJmb7gQzK6VUW15FQYNm0UiM7ihWPBVLE8hIGGTmCQRphEE+FT+Uru/i4nQaxsPusN0eFl0XQkSBkIAYRkWtFCvJzBQKKN/xeYQ5vMDq2qtAcQ9e7QsRoQe/fnOZvABAxCTggEWLdtHEtpUYHrxzur8q024yZ0RgKmMqWkrDAfAYIgCQc6SmD9SGAk0la85RSSFlHBUlNGRIqiDhIDxku7wettub1Wq5XvSH7X4Y989fXQcXUBjLsH9RdgAzoUje7hfMrvH9d7/WL09fX26uX19/dPnZ/Yv7i37VL+6tTqkYbfbp+uawTfubwybGxg1efBwymZNRYA5ETdsV8zdv3kjsOMSu6yQEZ5HDwXa7aUo+jeOYCBSCiIBNSinjMCAXiADIru7WQIigCjZIoOxeNAcJJ+t7r14fttvL3XYchmG9upA2dn0vMTSN5FL2+yFNOo1lGNIwWpq0lBq4RVZGquMMhzNsouw+TaO5KeH6ctu0UbU8ffr61RvkdPWNb7z/pQ/ee3C+7riZEh6+8963f+O7v7+ZfvI3H794+WY4HA6bzTSOzM2wG8bRd3ufJvTrw9k73iwipHCDRuKTb37929d7h188uP/+l55cXV83i8CRY8s3+6tnr54dLne7/e5mP6ghRHQ9Fku0XRNCSPtdtfpc9EVgbUQjDBEVD0xm5pZS8c12+/r1GMNIxIvVWiSmUU9W3TCM2+3+eoPY5FKmnHLKZbc97PaAviDQxcXyy8tzm+zjn738o1efIaHvsFw3L1/m7I5SPsG2X28P17tf+/rpu+8SoxnTyI7AbIWut68/e/r0m9/4zn5/yGmapuHe6eJmj76XvoshhBgIpG3TxMhqmaBtB3VrYlwuu3XfLWMjZMN+28LPT9cxtpGaHm0AmWUviTMBrJayZ0oOCEdEhgIdhblgMHdTFhFA6hfGbGROQhxiSMWTTgRnRGlWxnHEgrBO6HaTDWYvt5d/+r2/+Nf/x//6lz98/nqH7RaxxYcfhFzKOCHGmFUNslyuITSlJDkVUwg1gcdpjDE0RdtkCA4lFnHj6YDpgOvL7fZqt3u90y1EEIks224/koUgQsZgBrRkLaZNJ2hCmRyHghWmvW2v0mY7trHZboYXzzJGnLfdvg0vnr7EFrshAg6zFzD8aAva/k9/8HP04Cf4z//5V776jS+/8+TBkye//+D0NzdXz7abN7bcfedb3bd+4/SPv/d5a1Ig7jJ5zhgoqU0RXtBhKhNzUC3jpA4rDgoQio6gAAU0TYT5VIaUxyY2jcSuabu2zym/eP5qSuM4qU2wNA2ZWm4FUvcCLaquMEjgEINX149AxNR2sV20Ts6BtKaISiVJWXWjDSGoK9VRZa377DgfBuBv7ZnpF1tYuu2Wv3DURpvufHl3G5pnNzCe2+9js81WSmwYFvN1lnX4mz9+9vmvv/zwH9//5//in//BH/w39y+6/ZUOO3DX2E4LSBVUHILN9f5i2fddSyIUorol15RHohgkCgdTpCkJCxM9fPBOKnkcDvv9YRyH/ZhNIURwmqYy7j1Ntlj0bRPbtmlaaho6REMEVJvznjOHQsGYkrFx8OBCi+WSggzDkHJmkqpZICXY7InBkDFNsz2lQb1WaWCh4FJJRLfp4PXfRxtdJ6aSFbfB5DiSamhmGBlA5Ldm4X6k/xCxg9umUpdVrRgVUgc7g9mIicukxXS1OBWT3W7AAEsgBSmZko0lhCAhSPSCAgeUZtYOI2goOVv255fPhzTkg1MC50Y0qOr9D09KyQw6aU7Om9NpHMdDLjQkLdWyd5wOjMAhShNLIoQE8UCh67vpZiTn2o8oucE4YE7JdDM3mLkaU5hxH3aQKYqbJi1ODvYgwiJtDKamSdmFXaA+056s6pF5FslZhV597kRuJ4rzFevmLseenW4LuDugDZEdmQUVeTzm19VwyJlKT0dQ57a/nt/MWyrUsbarreEXbixirhfOrzpuUanas33hdv1Vxxf80CsKcZe9hS9gWHeOSkzxI+HmFsD6wmP+fafw9z7CXWDsl0/rbz/46Gd2++VdStE/HH+v47Zv+eXv//J33o443l5SMwpRTOtjKlxVzdHhMJ83H5+pU2+xjtrM3GJn5laKetZS9O6nyUyVe8U1LZbqg4+ivWrLLUdbqhbMLJDqBmduIYQZGT4idNW63RTmzmSomjFDjNHMTb14cYVV3gsIaspKzkYzH4t1FsYd20CS44LhTmY2xzWCGAyf+8I6LiKAve7dgECIS1FIVd3B3S0XEDgI3NlrC3XcgMmJqltyJQ/BhWY6cBQKgYlq5t5MaDiaheHISZxXLTIQIrNCfW7XiGacBzP4TtW6wXG7TBw/d5qzcuvKSqhw/6wIfHsvOyDCNI/U/O0KdIf0dxws4M505xj5SpWuZbdOfvOaaG4wcqhDiGtiGsxnMhkduYOVI17F5uaAzPOpmScmIHA9KyMwsZvNyR5vYf66nbA6FFQ/sgQvRRsOzGpu4v2iixcSOOQxHQ7DmHMdY66X6wf3Hz5+8lhzJqKujSfr1lTTZFPat+FRc+9ssezHN1mYdVQjtVqPGcNFIMSc84R5HxE3z2MRARruFxGhS8PeMok0hGVOwzioaVE3YicKptrFuGgkinz9a7+WxvTi81evnl/LgtuuPWwHaGi7rm2CwUFW9YNgg1id0YkwLbkU227sk6fPLy7uhQ4PHq2aZu1ASoZATRN1spT2QEspbLcT9JZ/yARE9tnnTBXuUSITaSoGc/cosW1abpgEDIRqalZj0v1WtlphE4bDixWQuRIMTGrqTKHleBZePtu5fXa6Xr/77r1Hj94fdkMuQyddJ62AS9JSUpCoChFpY9hNZdinkkuQUMpQirvVfFV2I3fXnNwVELiJIAQCzKy0TXt6tpbgwzjsduPZKnJs+g4L6adWv/Lld+6dL2PLOZFaGcdDN8YQpNr1wA9O3WLRnxTabDZn52d52gOaNQmkkSYELpb3hy0pYohgdRgzAdCiOY+mMAsdt7//u7//v+z+zYtXOxQLxMnJs6orN6GJLc9L8XyDubk51XwmR6Wtvr1PUd9pc6+r1VwUzRjvXIcy1TwKc31rHHf8A7its25v7V8GsNwhCiPcLoU2bxVuFUgTgqHKQeDzsNHMra72AMCgpmnarg0hZJ5SHgrX0s1hVZgCNdWEIORSzKY0paw5jwaFQptVE2KXStZSUkopZRQDEccIM1OFBXWd0XUAxflI5nWrCm+pDLacLQ0FgbplY+LZkhmKkYNJgjNO75+4bVM+5LGQEIX6Kqy4CshAQhxjo1xGLZy8iHkwN7dsqZBaii36plPnYRjH4sk0CrJhKsNS4vpsSWyH7ZAIgIVoDSSRuVnJNMF22yEBTx689+id983k889f7q43Lz593jbLrjtpF4tu2X72/KPPXj5/s73MVMYptetFgRII5m3DrkbFQyd920+5XF9vnHK3WMamrRRjU4KKcJTQHg4TcajwIuCGkjyjYZEQoqglq3s7E6pX4Lw5OQcyV8BFhNzbdrVen8W+TVB1NdNpzAAN4zSNeRzKOHrJmLUekBiVq4Wvw4xKchRknacRljWcR6IglGPAMOqby5tH75zeO18fbBxHff7s6XarasFF3//wwaIP03CVx8mVSvHddry63GfLsfPFWbc66WIfIObFL0L34GFf1EKMsdenP/zp2b17Td+GFF6+unz+6rKYT5NtbsidT04j98JEVZzy7Pl1qPYIhH4R1usuhAYIaSpmrppz9mEo45jGER7Rdty1rYQIt/315BYJkT1rwTjYvj2U4rkAjq5v247b2KeD7q7ybpMxIior/FrT6aN1Rk45T3sdtnj1cne6wmrZdj0RBSGhhll4d8g//+zHX/vq1x4/uufZnv78J+N01TdoGA0jBiISNReBWkqTCXvfwwFnbwSRwV5YK0WzMHszexeXmsIDdgpMtTDRXNShBUzGzphlTO5wVy+OxlEbRGNSYkR3TeYMmlTHbEEc7sEXRdZE64Lu8+vdX//kZx9/9tmPn350ub18dZ1Pz9dnF3GY9GYzvrqa2JELHjw+iRAQSxAzC6HmKSgHbiLvNXEQMBeDTkXJ1JAmm0aMA158/vrmKk3usRFxQiEziMONsnkMHQc4a9bJTdUpSgQhl4LJr15vD5vkJXJYkhIOl0hg7dJBXvx8h+VphyXcVHMpow9FGueW8qD2tPzwj65ff/z04Xv7+18+f/jB+htf/3a4f/Py8mefvf74Jt1crHEoOpVs5kGnVGCe1JSpPFrBvYiIqZQMDhQF5kzqxUpR69ax4SaNWTcF6uCR2bITZcopbXb7MiEIL9ZN7OJ6uV7Enlw0uScv06eaNeesswyKzQuYF4u+W7SAqykLcSAIEAjFK4GESZjZreJV83DzLkXjzgbi8xY1zyH/XZ3jsTD34yDiFwasR6YGGUFAb/csAgFixVH5xCMw4Ed/8Tfdw/JPf/23QteexIWnseQsQabB2EVVAAVh3I1NuLdaLCXtV4GGnIY8ptHyUIbDRJR22/14OLRt1/edOTGFtl24C0CHPBJcmFMuKXk+IKdcii4XLWDqNqV99oEjiElLglFWpFFt9DKCFF2Ill1gkRsKwswVByEyqpYJBICY2VD7J4Oxe2YmDsI1Ux7Vknwufd9WwTxL3m7pOPMkmJxAkLfvLhHBKp/A58BCAs/DfC9etOb+OQVmiSJCHHo4T0NaNEzGu5stCtgROIAZCWSBVeAVtjIwqcwsATfYwQqrBe+xiNIlykYeJDbcokG5Kc7ULRbn69Oubfe73QYbK2V7SCUpWriYegIRKHAgi4GcIpoutNubrZAQYFLLHZ+Tlat0bTa3Uze4HK9aeI0t1NpSOmVY5CAShM2d2Ji0ZtsQ+dGq9EitYgaBVG22VPG31+p8hd7pwavxyrHbOTaiR34TjtBTPS2ajXKcZsth1Ive5xvJ4eBjkuBtl2akAOhOIUeoPnWGO9x8+sU7663fsfutuXu9pX8FHnbsTO/emLe/jmMbePvl7XcwQ2n8y7949w/+RzrCXdDk/wGAdVcBd/sa/uH4Ox5feOe/gP0duXxfvC7rjyqWMSMLBHeIiDvqyNDdtbiq8cwvreV+xVLsaA0/X47V987KrJU1wKwAmKZpflLUrIcaAojK/zWQGSoBw9VgUFerEXRksW35CJMRUQU4KnSlaqZOREqqZjBUQyIKXi30xjG5u0RhmQFWmEPN1IqVih1VR3PQTE0AMCsi1WZvKfXagmH+YW2tuBLI69Ln1TuZwVUC17AI376rpRSDe9GSirsHjiA3uJlWfpuIgBgwJzUGyKqTGYnUZYrgwkJMzuRqAFXUB7WNreiZeddFcqnRkLcgmdsciTEHmFQbaCInuwV84NVp7850oLKacBe8r5IkmsXZfufbRyzLjyKjGTbyI0rnBjhzuL0+mY9FC8GdjyR0typ/qg4K5tVmch78WH1zb88ENX3siCoeL0U4qi8CCVBo5mbVEMS5uzCDNMLMc+Tw0Q/e1dh4GMfIoV8tosQQm6VasgymdtHmKb96/oqCqya3fLLqHfb69WYYtimNy9X64Tv3L59vREiBSs4jg6tQ/aiNSholEktgDm5IQzIvi74Lwhzi6XpBFhlt4JXmnCcFGM7cSNu204Q2NKtV27bx3cfv/tmf/Plnn36ODG4IzvAgJF4MUSoJDu7VIs3Uzs5Pt7ttKUpMLDDFbotPPn6GmMd0sVidOfxqe9jvD8vz0Hetrk5sCtub4c2rGxhQ42wcAo4EEjYiLcZEIUQjTMOoMAvWhq5rGgiypemQG4rJFKo4YqSmgFUOpMBhRYsWUwutdH2fNU9pMhAEkfjV68Nnn7xYLvrH71zcv3h82N8sFqGRjsjW/bpeyf1i3TbLNNLrV9su7E+XIOKnL34YAhOhbXrmmIvnoodhKrkQi0TqBX0b3UvRCWhWq75pcXOtN9dTTodIedktl+s2L/jDL93vFyHlsbiBnSODoKrDOHC2nKemPVmfdG3bElHJU85pBEyNEc5Wq1XfFZ1e3twI8cXphZOCFWRpSiVvWRoHU5h4Onz7W9/83l/+4Ac//SSnxCEIB5jnaWJC00RIMLXjHNvcuboK1rLpdoxKVAH8mYyIOu0+Oi8cBxTzusOBmWmY9Ahy11Wa8ItVyW3N8oXv12zCo1tp/ft1FZlbVZrPpmIblR5GBK6mKO2iNzeJwd1LLiUX1VwJrQSIwAjGgIMr0uTEBaplvzl4qOZ3AIictVgZS8oJTmzkerTaKg6lmUVbV3YmmHMg59nWQ5RZEIgdrmqs4Cb07YIajCqlJFcdh0wYU7KT5fnyXpNzu7XR3Cmi7gGaiqoThEESpailUiCZF9LGGDuiME0pLU/j6qSTJpTixbQkY9GmoY5cgiY9OMKDR2d4cG+7O2wuD4d9TiCLfv/eWmJwYkLcT/m7v/mdhw/f2W6Gp59+6sk2+2HKmtUZhBB//vzZZy+fm0zNqomdCLs7+rZZ9k0Ma8IIVfHATuyY9yejFJViUcVmf9jvJxZaLJqbsgMaETEHyJo29n2b3FqJTRNBzKxdHwsXhZp528SmCfcuzhfL/urq0mB93wVp1+t7Z6fn1Iabw/awH8ZxGqaRiHb7cb+bhgGHEW7QQnBxoq4PzHBwKUhZc66renDLEJA4VJbrlnjd95zz9tnnr9frjgluuW36z14+v9kMRI0aBeku7i2WCwutkNFyuU4p39914zROmpxyu9R2QQqdhqnQIXZtSXqz322n/fPX14ek3aoh4teXb95sbkKI8Ga16JumX5/FrnfipDnlVA57dB0AS6ksV23TNDXOhai6jJQq1SCq+n6oaso5OrnxNCUi6fuFSCbJXcfCoSDFgLjCxcXFMEy7zbi5nPaXZX/lomj60C0XHMP+MEgbYiTrhjRhu8kvnu9Wy/TgYR8iGZlatfbHZoNPf/7ROw8fP3lyTvTgzdWrSKCSyzgQipmqJlPas/JqGfv24aPzw2EYtuP1ZY5pOIG2fd+vVqtFI+QMJ5R6d1bubDaU4g5VlAKtUj2v0z8XAnGVl5N7KcShipth7NxyMHY4ByLrmhhiOzluEl5d7158/vzyqnz8/NX3f/zjj18+/dmzz2MLUIihbxfCIXankfJyOKSsY3aGYRgOEmpgdLVb5sDMzP1i0XSxXfQcuTLiihqM18vVab/avrYyjjAWBEtmyZhiI9GANGXzAgpETCROLhwDRRCyMMz2N5NmCtR7ilw6ls548tzoFBgnKNUmIsCYXRRZJ3U1EvaBPvmrq0++f3nvvcsPPnz30ZMzvE5PPgwP7r9z8ZWTQ0nj+MfXB9sOSEkHxmiwwLyIIfrFRW6DxYAyOYC2aU+X2Kd21OQlmyOu+obZmdQROSz6BYGnQ8pTdqWm6QKja5omRhBsrwcaSLlMpYx6fn4+DMNhGHIp1YoUgDQUekHEOI45lyABgWIbqiKM1CqNzr2WfVRDmzy4Qa1U6tBcQFbzplvDoH9f20jHJv3t9jM368cW12DHHNxj40NgsKXi5CSkB2sW8Uc//PHiff7qP/rK+4+/tN2lcZfbbJiQAlB1ZMwqVEbrmr7rltlKbJusO2HzEt682hwOY4g8jqMWwEvb0KsXb5glNiGEuFisoZJTIoeqhoDcmBng1cOk7LZDziXG0LcBJvvrvYTABhchQduTqHhhTaVkNyc1r34ZsNnWUpyZmMhFxMmgFWUqULgxMdXd3dzVjfi2Zp8r7jsF/Fy7O44jYiKpHiOG2u45QR2oEsF52zcjchgzhFkkcEMUpUabRxGhkJLraO4+XI51p2YXUtLiXWy9MsIczkTCAjIvROxmNsHcIXDAk9vGdHQvBQARy4LglNsyjBOtCcotui89/HLbd9v9blt2yTKIp1zGUV2ASABp0UFHRJjrcdpWSxV249vmCARjcyImsARm9upW41Z9fMEEISfS2VAYs4iuEtmqymiW6r0tnY6NEs1DxNvL9zgdPBIRjhf6Ec5hVLf9WR87s99qF1Z94rjmhc0MfHfCrSgSTsLHv3YUMN06qc0nN4OgdDzhYwP4FuxEHV4f8aa7FKX5Vf/ScRds+luwpy9AWnQkl92uAzM95VYf9qvYWP+hjvDLL+/v9WT/L2Bs/78/boEq3PnU64/+LtdQ/VclyzBToHCEpcxub8ea6TBTBCtLbuYj3Z6Fu2upKxZYhCOXnHG7rczIRv1tqqBKycWKaSnVDN7V4cpELk4rc3G5fWm1xzK3UkfrM3DhRhVpOqLWTi7jMInM5oiOumKaqqEGbFhlNHuFj3wGsCpyQ5atKqRqPM7xzGtcnwNOIiEyiEopxIjMxAy4qbI4M0RmpoOAqpdXmiYHYowSJOXJVGvgR2WXAShwiFUzKQ/kDFV1GDFIZjiqYl81gqRuSHZEyZkZfgx4qSRjoIoeAVTDM3eQzLOF4/rrDkQmB91+0Lf5HDiC9FYpxKiezO5+fLeIvLxF6IEqvfbbkcCRn0VmFTyb1ZDMRM6Gqmj0GmHj1ZjaACMyciNip1kvVWvgeskQ3GFc5xx0ZJUcx3jERMbHwQW5M0REArEw2BXadS3Ik2bIzH7PKTsjpelms1nEfhFbbzwYCFbciVGSvn75Zvx0PDlbqBcW6/rQ9Yubm415Phw2/bJ7/PjBD7//M4dKYOGaUUyq5tmtzkfmV+lgB1iczQRKwzZRtIf3T/Po3opQl5MgAyGAQ9u0q+X6sHtdfFqv7j9590kI4f/847/ABBbKk6omcpIYvNg4ThQIBJOCGUKzput4f8il4EgRh+HVm2uP6WZ3/U9/97uSJs3tbn+FZlh3q/Vq7U0cLm/GIdfJXCUPus9m/ywVyqUaVgk1J/XiVlRzgXkqU9HctUvxVFTrqgJncdMaOTVfasQmlcUx+307W7bhkNYnyzLunz1/uV4tl01/fvpw0XbCWSdVL+LMwilN4+4wURkP5soP7l8wd8XK86ufNhrcaNH3InGcMo82Du4GJl12nUGiMBNU1SwD1DRysu5j0K6RNtDJqjs/XeUh3L84Gaacp+yE2LUxsEQZDkOaUtPFw35MhWOzdgRh/vTzT5vI68VqHEZXNEInqxNTfXP9puGwXC4KCoJLI6XkYdj3/SrExq2UNF3cP3/06MHFyeL19SE6Igcj16I5pzrDrjaaPDOa5kX4yC6fxc9EM2J168IAJq5OBkcM0Y/cKyKAaTYdoeNv1fv6VlX9Cz3DL/YY9IVv0u00sAJtAjZ36Gy9wMLVLYIY2UrXNWbORKXkojmlyUoxzghH69/jWQRmNyKCFTOwFdJslWmahkI+qmqaMoAoDREVKp7VtMws0rpaERERO4pCZizc3AxCLCRGIA9eoIzkZShNiJ20KqxWiuZhLLnoslutTnsmgGx7lWwee7vV998KlAK7VYG1oMZRiFUHV3n06MHpveVuGIZhOo/tyZL75jCOWxFvWgzTzXYsJ2ePT09Pvzw+un61ef1yt90dYDg5W5RxErK+j6+m/Nu/858s1t1Pn376808/WXVLZpp03Bw265YX0l9u3uyn3fpeH3uexmJEzLbqJYQVSXt1/YIJpj4epiFN1VQlTQnZPJQ82fXmsNsjNnBLoUl924cQkoJtih11XdA8Vc6NxEjMFASeY8dCoeu6k/Xy9GytVsyySOgXyyBdCDFnMyvDOI3jNI7TlDIxpVTGCcOINNxeS+KEIM4Ch8xOiMkBcxG4ACrcDbvpdHXSLTtHnkZMqfzNTz/eHa5OThYny9Nnr16OA3fdlErebtPVBou2izFa1vsXj8wtpwzyMecx7zaHXWjZxVzL1XDTSJeLH4ZhGK3t11f7Z5KiO485E8HcmfN6edL3y6ZxIJVcSknmuuikbWLKI1QYos5aCmBFU1ETJpbYNHG5wHpVmGkcbbfbN7EAsV1EAgUBsRkKGE4uTKtF37bt/XsPX726fn0YttfTtJttyUXaEBoEaqnjhpqWV4uFpilGH6dpuy2n59S0jfvkntseZ2coEz7++BOCffClx1/92nvnl/EHf/WjXEzHwXRyNq/UeBRhA8rDh2fT2L3yy7Kd2uCnq8W6bc5OlyfLJdySDgQqnoqLFGoKczEUj1EokAgs2Ayz1/aQghCFEMDkeXSJ1UDInIQjQgDYwRAOWAyanr54+fTVm588vfnDP/zTH3/80asNwGi7ZVwtIDSk6dVui2F7//Ss6bu25+5sMY7jixdXmosFtE1oRZpOQh3owAAupgHRibN6SkVtEtaT5fr09Ox8/fjn+fpNyNCkxctonj0GlhiZSBmlZBcXJhIhgpmnlM0VZDBo1obbcSib/WY6FFgDp3FXYuwfP3p3+7MfZVLMgTTUEIRFQhzHobivTk5SSbtnhz/79K8g+KN/i3/03Xd++3e/9vXfeHhxQd/56reeX798eb3Z7XRP2E+uTKHxxZLee3exoNKLVY+q065/eHF+s6NhKqraB4hqCIFEutVy1a8biofNtL3Z5oM2oWtip+6BGlLK47jZb1TNFWVSDHjwpYfE3PateDRyiEehEBlkQxrGNJqRwUKMbehcSuZCapFDaOL+sDc3ODFBmCmwgosVcqn5He42s7JuqRa3tJRfddS561sG1i9uRn48mDDbk8+RcgDIlWaSxCSxjfub/NnHz//s//re17/+jb/56OPX11dt4dEKork6CYkICSgrQ9JQtttDm/UwJmcikumASdNyCWHmSARots1mY8ZNDKv1smkjEddxfxNj27CX/Thp13XLRRcibTa7Urxr113fuNHmcheOhgAAhBBDiLEn8FTyYT9MJRNQRSIEBBKuQ1tG6MWKcjUFr467bqpGgRlc3zUmriHxbxvBys2e9YQAiJwg1ROuluaovlskXBWKrqQzkqGY9b5OTGDYjG5HIw0AACAASURBVFxBVS15G5kQ2MEcxBgjEysKeQEKsTGRzENvJyYRZoiVgiqeWcjCR9/v9odpyFPOe8UIFMyU7W6eW79avjg5OV2e9LGL9x7dO3l4kp/9/PrqxoJRICaWohYpUGChMuR0mNBSfem1T6hj/wrFzb5TRCQ1N4ljiFLbxqJu2bvOqACAsJJX5hnUBSzO89jObk0b7G1DPCNRt8woMNPdlvmWWVIbm9mP5y0tya1S13nuO2f2YW2Ea2NEgNZhJmYeV3V2niWEM1RJVWjjcw1Y1aKoI0WiqvObO7hbLO0XUa27d+jfjkz9wp17567+AvcKXywvISJ335b6yMoFwRHS+o+BFIVfedJ/x2f6guTtC2rJfzj+Lscvv2O3uCb+3R/8Lex496ryOUGSmIO7q6m5adbby/fOc3nNkwJBKrDFrm6u9c5AiKFpml3KwNvtpj6TuYMUxqZaSrHiVgzqUKDMxm8IKEXnjmwm+AgRXM2KIR8TEond4FZV3sRe8w6OIpgqbjYrpp6djZikIanZKKoWOFSGLHzO3gKQpgIcdfs4/r9uuQaQU5BwDDckuIQgIqZmqmVyC8V8VvOamYSGRdKU3LTv+xillFQpRu4NMPsnAgAZyG9tL9X1trUkIpibaVVLzpFhPGPsziCuEsWaePgLFwFQMyio2lhXT+Mq56ovTo55xxWS5Ko3PEbq1j+FWr7Xz7vyK2Y48Ui8qlxTPQ51qC63XmsJLcUBcLXuYiEG0Sy9tmrmPr/VZOxmMIY7GRF5ZffeDg9M1c2YZ+LVUV5Jczdecy9guJVBMihWA284gQxtaMcymhYJLI2knBkhdEJEYxrEsOx6jnLY7HbXu8Muc6RmGYl9TINrSZpjhxhPmyaGCHccpt06rx4/fg+GbN4EZgHU3M3UtNSxI0mAF5RSiCAxxNhF8RhC3k97G+TRg3GfFwsnNCUDCgRhkdjE5aJPqjbqeXPxjW/8WhoLPodcMIsECVasjJOBQdyEQIER4CwUyMmc7bA/FDeKTMSVF8kBU/Grq/3lYf97/2IBOri1RI0m3ab96aLpmrbv+66nCV5TMs3U1GpjziTC4o6SC4AYhYlHzWmcjDIFUtdCWC9CRp6ZlyAGqbObuXlxZRAzN4GF2c2G/WCASNN0MfbRPDccNtv88vPL1XL5nW99Y9lEs2k43Gz3N8RK5NfXN89fXF9f5XG0L3/p3d/87m+dnj282W0dBlKWGFtmBk3qnplMHU3AomvMtZRUa6iUBrNJgjUNLxdr8tRSWK8X9+6dTfvm5HSVL7eh7cRi47GkA6Db7U61LFanRqnkpCWH2HRd89HPPnn48NFyuTC1lJK6kSBPOeWRYls8GVloZbHsd9vhcNgR84pOQJ50CkL9om07YcDMgjgTS3DNOVfTimLz1MsBKHyGoPwtHxJ2pJPWcraasqNyESpsdTTIrqmtOGbP+rHauTsJ/JWby93qRkB6XAzq+kLgY3nKRMLQGqMgALvUmAclEKikTFKxeWfmvu81pptt8gYGIAMFygAhRAohpJSnpCyQRrQYC1lxU3PzKC03oY5wSyk2aR3G+zw+Bo70K3K2rAhUNdRFvULYXOAgcbLCU8opbZe2jKvQLRbOal6YOTZhKuP98/OujzmNuyFhQNVHIaAW/Zi8eKGWqQ3MopbTbkoKJCxP8e47753fP/n0889ytvP1vS72b9rLT35+wwwJNuwOPBwur73t/OyenJzeP71Y7nYHQrh6vpvSvmkXoaFtwleevM/wVPa7w+u+4+VqLVKmtF3xslkH5VFa61aCUHb71+vTE2bq+0Xb912/HIeXdQ3Yp2kck8KIg+lcyytIjc2qjiLG2PR9H5r9IcOKnfXJKRVLatk9ihGgU/apZMTcxBKUQ7N2tsvL123biKkrk1OayjRsnDFRNhPhUCMjmQUOrf0JMziAojAc41y9oxpkGoxYooFAoe/W1zev2NrAy5eXLw3p5Ly9vpk47C4ePNpPZbvPw8DFJyIpSuqNWu8Tri630/BmHNM0jecX92JLWiRPmVLpl4v1+vzTFy8Ig6oDthvwzW8++OjjT7eHAYSmiauudUBiw5RL2RbL7gmUYhO6uICPbdvDWUSaph9HdVMSNyuqRojCCIGXq/70vLiGadoNw2CqTbs4pD1MYzAJCAES2+Vi2cSmiX2UdtGfa9ntL213NcEjR2F4KelwMGoIfdBsoY2LZdOsYyfUtUPTSNedLFfNlG6I7fQ0Lrs1GX//L5617c8ePTz90gf3Ly7i05/+aL/HmEAwbtC0aDrpW5gO25vr8/Ozk3U77qPT9OGT97/+5APP00nsl9ztdLvZboglUGg8RIiZRJJu0cU2cuAJyaFK7mZ1/MFwYQ4kzCFNhyDt7H/J4tIUdAVcPGSXyItn21d/+oNP/+QHn3z0bPvTj59d3/CgJm2LyMbadEwi0EKC/uxktVpPaSya22XnjbdtY+6quQRtqZVAwpWa469vxpWqwsC+O2y1oIkIbH1rzMHMTQ1jcYpRojmYxartA6jtFxyIxAuz+1hSQUkIaFpHg5PlMkoYtq9h6LtlH8N2szvsD00f+9UCnZLvfJaPy8w+Nu46SplJC6uOOTW9SBfHF9Of/G/Prz/3q+f65e+efec/+yfNz79X0k9tvCkoycwVlNJihbOOeowdJ6VEaNYt3V+1BLu5cVNQ5GGfEGOI0oX2dL3SwfabPVwLsIptJ/1YMiA6lmk3jpsMQwgUSUqnl68uwyK2i7ZrWonSdCE2rCXd3Gz2h0PV4hdHF7soUSUwJS/eSmib5np7U/12iISJRQKBTUFGswVq5YmYv+0l7gqUfnFSctRb/cJ37u5KFVo5Zj9RnUHXUa1Z9SMnHzKFkDZlvVoeNumvv/eD3/pnv/Pps2cISTovm9FqOgo52EkgmUsuV6+HV1ev++VS3Vanq65t0Wy7FsvFum2bknNO4zhOMfa73WGcioO7Ug7bfUpltejbpg0x7jeTFQ0cF92K2NLgxdCHAEQ3Cww2cfOciw7VuVSbjpq2ddBN2vhQPFTqFBEFZ0AgYCdQICYhd4o1WwkwaFFpZK6l6xi5oh4AuCZ/m/uxIwDVxoeIQEYMljkGkqiqZaTabnl1/q2cA0vCs4uuuyV1LmzCOWduuOeFCTVN21IUFo5iRVGInIK045BYAHZn1znRFsys2eBYL09NcfN6e7geSQkZZExGXtyzsQSHubteY7PbD9eHft3fO7/Imj/68dMd78/fOeUIqEHAgdqmDS4T05jy7STLj6QEV3ilh9mRzCdOARI5NjGKmFkhKubUkVL9AKCm7qX2qkYkbK6V7+1uNhMt7kBHc2U0/1eZ6XdUU3eufwLMrLbSVD2PyRl0lCbeZUbR7Z+vIJeaHp9ontXN3dKR2fSW2lIt4d3vPJbAbnbEeW8xrOMT2ux7g7suWJUG8csQzxdYWncLyLtngjsYxd3jzj0+f3lLxGHm6mj0H/z4B7zp/4vHfBv8kr/+7bVya7d2fMCcKdi1Xbto3X2apqIZROWg8/zDa1gsi0j16IVDVdXM1CjA6bjTCCpfC+LzfcJgYWIy9kJVtk0CWDHP7kowRwEKQOhiyx2Xc1fOOILcpLMnFHCrXCEC4pHrycIiouZJc9d1x5uzEiydFTpZSaWUAiFmxiyilNA1wgxAVXMu91cnVkrOuZRccklm8wtnhBDm9+24COAO/wiEtFNqEKPwnLZrqqp1aMpSUae6YcQmxBiLaiqZCNJI6aiguHlgOeL6pkXdTSR0TevuOaei5ahqRB2Gg9FEmTVFVdKIujeR3ZkJOLwmszI5MYO5ZgTmodQfo9phNJGZqodUNR6p61BgDsREUl9yXQeHzaFunG+7Xz+WGMwilZmMIwvPiMmZaxD2tM9MPA/XrAZvuKnDuZ415jy0ConOykwc33PglvIBACbVFN8pcNu2LpZskkYokAfnQBxJgpDQarHslm3StNlvMps0goA2hmE7RJbzk/O+aS+fbV49u5wvM67XM9yxXAdpKJc8Ag8u+MkH7/f9ou+X6+X66mrz+sWb/c1w+WKz340BkT3mmmutzOKQyQB3cCAOLbGoFyeAzVNe3I/3H9z79q//+vb68L3v/XDz/Jq7Jiy6rg3LdXz04MQt/+Y3f9OK/Xf//f+YNohoxKNmdXOWAHdVVTcIxS5QIBcvVlzT8t7aGdMwzRdBKWERQO6Ss2CxwH/xL//TYunp5z/a7A8P75998N6Hee9Pf/J8uPEf/OELkIgJFWdoIIRGpIk5l/0+tW3o+m4c05iSLBBivHhydtin681NdxqtZrWYaanyNxJicvLicOfKUXE3UpAZB1SOTiWOCYJQ34eUpynj9/7Jt3/7t797fhpzHljsevPmxcvPX76+fP36zeef4eEjbDYglq999Vvf+Y3fuLx5/uLl5z/4/s8+f5kf3MNy2Y3juFqdMttut330zv3nz17D5exev16vHr/7zv37Zyeniyayuy76RsdpOgzDzW6/2aRxDO2qX58ZNE/7Lz15h9y0JFXX4hKXMSyBZpgs5fSTH/2JWbl/8fC9x4+bEMqkbWy7tidFI/Gddx67+n63D9Qs+hW5f/785WazffDg8Ve+9s2cMU76P/8P//a/+q//2+Uph2YxDKmYx7Yh8pyzaXafiVZu5EbQGs/kWBLJLJpAFTAyS5C3aJO7WSXIO5zrylAfrUdOud/dxu1uZeLukGMcxN06I5d8O5WrC4yISBNqpSIiIFNXZnJCKapWbk+pWbUOdzJhijHE2FBDLjDYzHtVLUm7uAghlEn3u30+jHCEpimaQtO0bR9Z3CyNqeSSazjG3VXI3no0iFOVXZDMiu9KNDMCRKVB6GQqhXvqz/rCui8DNeCeq9gBAWCcn4dxKHAsu24RFzYh7cvuzXS4mdoQbYKrQ1FQEIDQMBEHLE7j6kx+7TtPhnKzG292w+YwImc0ERdn65PTZddzCNZ01C+CRCFmNxwOeRoLUVy0q93zw4tP30zb7TKKq/6X/+pf/eR7P/jhX31/3Azn63sffvkrq8X6ZH2Cpnl5/fL19WfX+xeHdN0u5Pz+ebYizCxgUvPRPOWcbjaHm/3erHSLFccwpOzcGORmO11d7w+TN7FbrpcpD48fvL+9TD/90Uc3r8Bpef1qH2kB5SDSNGFzczOlggZw/ON/9o3T9cm4H15ffXJy0n39a+8Pw/bq8mp7c2jD8uL8sTTN6JmZANuPh81mO0zTMJRhKNt9yplDWMa4ZFKnl6tFF5vFlLDdjMM+wwAJ/cmKA/bjzcOH983t9c0WzF0/tot8/pA//MqDJx88fPjw4b/51//79XV6+PBcVXe7bRf6abCu6d57752XL543sVl07WZ7M+WBI3XLhiMfxmGzyYcdTpY4v9efnp83bbffT2OazHyxWjRdo5b3+/1+3KO4MBNrzskMbRtWy5P9rmxu/m/23mxXkyRJD/vMzN0j/u1smSeX6uqq6mXYC7uHM+SAI/BCutACPobeQ+/AC0EXegABgu50QwkgIFAUBWrEGWEG5Czd013dtXQtuZ/zbxHh7mamC4//ZNbS0wNe9UUHUJmok3H+NcLd7LNv2ZVCpZoT/vEfvnccb/qVTOOkClOaJtsf8zQpPLomA4NSDF1MyTCFCJiWaVQtKUThUEdb9VfLxeXzT7d/+7OP9jdDkp6U6ph1UADdAums2+UJS0jE2Tp+4+H9q4uNl93h8Nn9+9396/Deu/emcd+Fvgy0ezkO+3J2vnz44Oz6werqbL3ms2evXv7yow8//PjJ7qDdErHDar3oFjKM02a9WC76R/ev37u4vwAiaAkh2OGw2+5vjZlZhCQ6i1FUdNJtVhtmIoGROUHhTqwKRt+FpWlwo0XqjjfPAksXzjj0HJf7Aavlg7HK7Vhv9tO/+B/++xe3N588wUdbUEIfYMzVKJt6xepBpz4RIYSYuq6XlQSulo+H/TBMBE4iMbCbE9UUKEYKgQM7c3i2HRar9Wq9Xq4WIv7y1ZPDfugTrjaXZ8vL4w19/Itnzz/d9rYUCtMhj8eRKcXQM8swDaELJFBMbtU7ir2EhOol9nj3vW+sz9afP3n55MkL2EIn15z7Zf+97373xz/6wf/0P/7Pix7ksAl1gmUklq6LNWvRUg3CYGGjoAYqoubABDgK/sl/2/8X//yPv/2DR8dx/9mnn5djvnn5zPXF9XX3ne9efeubZ6UeYEHCxe7Y/fTntz/78PmL/XSs9XY3Zt6MozKwXqw76Y630+F2OLw6JlqRxU8+eIqDAkCZ5Wl3vH0QEAAAC95cni3Ol85mNZPpMAxZNYaemb1YHkrJFdnayKEtvxIDAQIGURtVw+E6s8/JyN1hZFm96l0t96UO9vVeRI3NNYs/zMxbw8LNGnf+ocEQAQBKZMQmpCzKVt2qWnVhiTFKT8fuYKn+i//lv/vk5Ud/+4uf/cVf/vnhxnTXD7fme1XStBb1/MN/+h1V/Ozpzx48vPr4o5eP3r2MXdweb25v8o9//9sEWq2W29vb29123NlhPwzHAkNa4frqMsaopQRJwzh+/qvbZh6bODLxNJZqtlj2Xdd78cjduM15O+lR7Vh9aoQj61OsbnVQKBCAEGCGanAiFnao1cc/fDRpHm+G425YrlbH2wMHDpB+uZQQhulYa2FhU1etnr19QUIcWepU3WHW1NnMHCiAGKVkh6eYiGj2L6bG1zGcCDqLdRpyFgEJqoI76tZRyZUV0Rer1f0H95no5snN/uk277VHTwPpSMu47GK3290iIq6jsrpUD36chnuXV7//j378r//VvwGji910nBqVm43JmYyc3ImtFLizgAMpuQOb61W6H9cPljdle3uzv7p/iTUddgMpCQIydKxciYDpMNWpMiACVTCERVrGlxtMjTBbutRqbhYkEHis0/13Ho2ea6m1FFOFuxhQvRwLsrELV9RJZ4MTazwjOplvCM2BWe3i9zvW1QxaNcJUQw3dYC1IGkbgQCytbpkfs0lVGjdCzeEuLZOaZvniXTf6ppn6fGc5yGzOTGxkNKNqde68gDtMgAPZrD8CEUkLtX+dJXrS57q8+Yxv3rN3P3/zYd/84d3xJsilqszcWmw7HV9dEL6WGvW1kNlXX8ybL/UOCQlffbjfHb89B/16vh++cDUQyIXZ3UspZqaqDarv+oTTd/8GVtouFn+tVTzlGOKNVodOnMhm+i4sxOpscCIRMrjD6l1o3QyWGNHpnmm2V6fX2e7EU8AsAIDNmrrX4Q41b6bgRedblRsFiZqOixgceEbc3eFurqYqs78XdxSncZx/am6zcdT8npoH1fw6Tq/MTls/ORBnH3mYzazOwAwwsZHxvNdCAquBjazRxoiJCVa50SYb8OzuRExspsyzs7wDxCC0gDAQiGQ2yAbNZDLMTCOcSJgy4+XN3bmxyNxNZ2f7GGhWirZ3ZKYOOyVaEFFje6gb4ASjlt2r5oaTa3x7zvay4Ubk5DOqOLMz2qzAHM3LvbinFOBkbl7h7qYVzicH0BNvHPMUadbv+ymxROZefv4uABI3cWdwoKbbacCZshG78TyHIudpnPKUlXW5Xq0uNofpcHu4mWBFzd1yKSGGJjPidrHNHo4AgT2SOplGslrseJyIY1pY9Roi+lUHUM6l1prHagZi6foOKuaFgpqpOREHJrH2+rzCDAFEHFK8ub057IbFIm0TLFgSD8ndMrx2UaZpyMe6QJ+n0diaxybcayntFqSZwacgbq5zAI15DDGSUJd6EnFoSGGaBvUSCauuf/Vyt1yn1fKqFIMJgfM07fa7MoTNvcW4r2WoXUqBQx6GMmARmJi7TmKMDZidbQvcQRQ6QWqrAbftFcJg8Jyi0PjyTc0/I9sOl1M5NRNmzEEo2XRiVNveHm9ebh/eeztImPJhtz1OY1WtwiGkqgoSMNJ+v//oo4/eeudeqZdX985vd89LhaOkFFKSLkWrZRoOQXDv3tnDR9eXV1dvvfUodaHU6TgMbrZerZVdxCnU6sepyLFmSri6upSz80W/Ni2hX4qwKqqJqYxTHY7DdrePsSvFay27/V6IoqSUOhEGUzXdHfdCHPsYKDbgbrHqKFBchGHa1UK7Q57siA0OBzvv3VDNbSoVDKHmTtHQ+FN3yOzO7hqTOPmcBnva8mefubuQGncjF4DktHLg9azstPCe1nG3u9EhaA7eeHPPaDc03QFk8z8THGhD9hkgC+IEc4M2UuZctQHURCYEg6saUTEiO8nEW5nlgQuKGSDESaARtVQrqe+YBXA19buA1EBumFMyZnCf2qul+Y24A4JTKTmrKs0hgZhdhCHE4hHgUEr1qs3/IoDBVs0qSUP8q+7qQUeDkqx4FReLtMz77JXIaZqmWrXr+8VyFYIsVvHqcnH75DjpNJQ6ZalF3UkzBs5JoiCiMwlECEwK1KJadcy1gIRRNqvF6r1Ly+tN31+uVkxjSGW1lkXoN0sp5XZ/GGKqfXeWFr72IKv1BTgsaH22ePbsmYG0mnllqsRKQjGlME05VxAkhEVMueJwrMNUKHTLEIjSMFlgcbKzy9X19cP9q2d1Ot5/eJb39Pzz29WqtzFPtSJguZaJVbXcbm/G/Xgcjka7t976oydPfXuzhVPO+uzpy+I+eSXy1IXYJYBVfRzzcSjT1DZkLWXMZbp3b+mEorWqkyAtEjhICCxk8OVicxxKySWgixL7IO6H/bbsdznIcpq869er1RCkJ+hmJavFui4qABEOIbjVcVS4psAkgJurMayLuPrGUs2r8X4/pexKYBEOKDXn3ZDrUGqF1RApBgeUGQ70KfRd9+Tzl6XAFN7WIkoxLgjmPqk2VjCJSErBjZTYilYb3azq0K/dUM20+qRWxRbk0Oq73T7x5fOnW/EEK3ByNGIXhCGCFtMJIApSYmc9HvYlH1SpKGVzCuzsQxnziLGUXOs0jbuD881+GJ/98NGPNqvunbcfnl8shmmsXkmwXC1WyyU5OLhI6EQmHSPFnpMDtZZi1Zm3h32/6LuuJzTrbmiwiQtmP4rmgMRFy/GYy7CLsujjuk/rlHyYhvVmM6DUjIt4T5b9QeNnL/d/9bOPPnt2e1s3k/ShP/Z5WwMyoG61zcAiwoLFA2DMTEzglhc0qbXkIVNyVoqBmVmCS6Cuk66LKXU/+WQ4t33Volr6Rc8cuj6kSE4au3jvenXcTTfPtsfDGD0YLCxjih1DylhjEmIQgyhUIaCUXIohdlj2IsGnaRiGY84GP8AEoiGa0bA/vvi9Hz169Wz7/MkRI4QodYkUY85wBoUgd+VTxyTEJDDiZLGU1fjpT+P/zR+R3fvmtx8+vOSffvbv18kuNg+uLrFkZ913KE7KmC6Wy7Oeh+3zw21BjGT6/NWLrl/2qR/zNOaxjhoknm/Op30tY0UFLICETMW0JaG11tvnjbjZt+ZcGOTuFaZFq6q5ZQJ5aaMph6LlTtOJ/gGiWf10Wo2piZp89iWBvc5Jfz0GhvPXBBG23eVOmnXqL06FX/vZiU/kzerUYQRpnhUsgWDsDHPNTokA/PynHyzv8/nZarNJQejDZ9vFYo3YlTIClSM1BTw7xkNO/WyfEqWjlEMIqnUch3Ecay4hdCkl1Vqqw3E4HGIIQTjFrktdtwAcTMIWyITgQi7cpdBz5LwrtWgeMg6KyjH2LK7TNBfkiWd2NOE0J3bAiASMUoqRQoAOEgUCZjFFLkXUTpI0oiZCY23sGwDVTZsAg+YPr8LEQAQWmflaTCGJFigqzRWDA2TunBAAiiRCpsYJ3MncoIhnzfthF0SqlUo2c79T8GpqOuShwohMtU41Ixkxbc420stHn/wKAQLRonBQJXYi41Y5GKAlz9eSs4CZkKmWY9GbatDNo820yFOZcASzL/qFUMz7XHMxQXDiyDQvS0JhtvOoXonQhZ5AVgxOplA0pWAlEFxzGYtVq2paW6hyc89gAYKgwOBguJ2o8NTaklNF9Hceb/ILCa8rLToV1E53vCfHG2UaTpwuMN2tIH5qTmm2Njv1/l9J/GwHExs3Q+QZ3zlVjHcduc/t3ZfeSKsS8XdhC/8Jxx2095/263ev/2sxrK89GSes/nfHb9HxtaOMdtzBol/9UgnUwA49HSTEzImT4wv5hm0buhPr3g3/ZzkJzaI/VQ0nXSsRWs3RnKQJRAxSciV94xW0lttbH+vu86rQvFruYiOaU9JMUlKdxwNu7tQcR2DauFrmRGBuL2MuQQAi6Mzxae9GDSIMEWFDPRZyskaUkmb33XRQ5LM7d3sV5JjttV7bx0QAUDdDY+ES2go+f3BQN7SgODKFOjmJg8yZZN6AwT4nvM4iCqKTMbITg51B5g1DnKXNcD61pW3FaXvOm1rSZmE+U43dTiRStbmBu0MI3R0Om2EkcnKmliN0sjt0NM4dZjd+n4czxMLcsk/cm4MyjPwENsFahkljkrinELxZtrOpqcMJNqsj77yuZmBt5iv7bMXkkNhc5cHtQ2Anp0AkzIERAXaBmLiLIxiElMkIQnY8VNVCiReb5XK5KJZNC1FsAcM6xwO/vjvcTp7xDKtN4UkG5AnHQ+Y4hikUzdOYqxUSkw79KsL9uCtiaAbyWpXRklfaB2/qDnYHKACBtBoI291NLXr/evPk5mlQEzdCHqcBvFqvL9Ty7e0Oc/4myJ2JjAlV0SYnbrVFo7Vvj2fPI7BbtWq1VakBlLruOGR4ddAnnz57771vnK/vWVUYhFKdple3B0zxrXfffv7p9mW9VdcQgixJi7doZwfUtNRiZiLEMqOJMYUYoaqhzXNOjkrsDINaWxwa6uH0+vpRJnZzb4gz2MxqUa2GgudPX/7y/Q/f/cbD64cXufY/e/+nxyFrRUip62u7e1Xry9ubqZZHb1+cn5995zvfjIF3h10tg1lg+GqV1uuryOmtB/zWNx4/eHhNwlXLyxfb7f621hJj+PSjmxiwWi4Wqd9cpHA7QwAAIABJREFUvHV2Fqo7CauFcTgsksbIXRdTDLVUay1ruyBhV1f3jsddDCnnaqrrJYOgcFPNY3Zg2S/OLy662LEHuK1okWpKXXIu964f9Kv6e//w3X/2wT/8qz//+eXFWeoWhzxWVScVYoKpNiRV2A0i7uQGAyQGJ+WW2jZj1d6oVW1FMMxrA2F2DmzdBprwrYltncjJWqviJ/D/TkSMO2bTXM/MCFhbdfzEvSVvpM35uwUBMhO/W/F9VzQ3jiU54LXCXdWpqLfUjubOBW8yZo8psixYuEys1SRFN1ebx/ckzJAQopmZ6jxlAbWFaA7+mJmvmEXvLX/DyZvrWoOq4Vahk1qwQBJYFOqgmCIHnvLglYRCC3itZhVVJHZ9WqRVF5eHV3srjope+3IsgPTcaa7HMkbmMd+M5TDWSR0QgGLhasNUJ5/O0uZcmMKUSi5qXoqWKZdcq4M9Zxun67OzfrO6f3n1/W9/K+fbFOtbj84TpWW3bNrM84uOOhrdF86RUiVDUA4KsVp1ypNZFfauY5oF1cGJqxmpucgw5pvd8dXN5IghRYMN0/jwerE/bM+X984ulmcXYSR5+8Gj7bNp3B6Wq3Q4jFdnm37V0aJONhSth+P+uMvDpNmxOV89f87zDN98fzjc7A7HXCTi4nL5+BtvrZZxygqMTOiSMEcQO9BTFCHVXMacs6k7xxAixS66k7otlpv9/lAqutgzwBSIgtbixv3ybLs/xLRIPZViZaohBJHAHZlV89J37GpuZbEQliABEDf2FBd98vXm/HAs4zhOU3Fvrk1kpmXK4zgUzcRIERwCvALGDCYOEpmkC0vpRauPGB217xYsCik1VvfqRqpN9q5qKNVKNXWnAGZyUkcFK0klR9VJzcqEgJBi/OjTz5ayYYoSAgwQloAUiQMq63IFdFis0+Z8nbo4DYdhGIj4MNa4r8pQslzLcaDD0croRFWiIaBWU4xOpe9D6DaGVakFQn2f+tgnyKHugojlcjiMsVunjo/DeNje5pw50GQlysITq5OqERMFcxQHzGrRanBmyVMt2YU7wKGKUjDS+cV1SGmY4NQX658cxl9+9Omf/8cP/+pnH27HaadydJTFKvgonKsLg8XZyQ1VIrzVRCC4qVZ3rXnSorDWejszsdAb8gOKEruue/fRioWJOYiEIAteMjshKxSii2Xc3Os3191BJp1yMURm6RWGOh0ZwWABRECAZXgf5eGj67e+eb06T4e82+63XR826+4wTvPKRHkor57dpN//gz/8+U8+zMOHOzuIUKSg2adBAzVfT5ipq8c+UohMhRzNoBXeP/us29+8pOEXP/zjB4/fwY+//+M+6LL39ark+vl0uA2xEnjK3i2Wj66v7l1cvrx9NmYl4HBAjO7u4zhO+5GUztJliPGYx+FQMCkswOBKZjyv6pilVkKsMLiXmn1yYndTmFU1U5gVADCCOpROWbQkEKYT1NGGV618sxnJIofOLPu2bRq8GVbMDcjXddnzttOq/1OZ+gVp0mlqy07zZgYiZ2+BS3OtZF7NPMNGwPAf/+yv/vi//vGDR1ePXz04DvrLv97WMLJIKZMbzs+YgzILEXa7fYiipYYU+q679NKlNE02jMdxOI7Hw6LvY4xmiTi7ey7Zvcaw7PuOOQ6H4zhOtWieCqqpKZhMDY6UulfHW6vN/1XAYoVgCiKdbTxOTpB+2oAdTasGwjgdKbEzQmBpMkOHw3POzCyzUt7n7BTV2UP4ZNjhczRXq8RMHQwOIRDDrDo8iDiodWCnfRsAKkwFQWACB4xhrE7ubBxIUdRzkA7BjR1AJUsRHLnkEilwIllG71wsq8DFH37jYVyEzz7+rIkcUUhcYE6ny6Zdk62iCMKNUtl6lHGXoThO0/23rtfdavLs5iKkVsysukqkbrHY3e4VFUzMIiEIscIVniIRKITAYJVai6k2fA9oHxQBZvyakz4T17jR0p1q1TsLqjcaWTqNz77+ev7qBX5Cj+F3cQXzl36yafETzIUZG7sji+BEEqA7Svx8qZxuG3pdqn3p+PItNyNTdxDB3eV3d6PNbf7d3fgb8aY3T/g7+DRv3tFf+vM3Hndo1B2G9ff/3d8BWL+Nx9cyct9EoPBFnKut/O0nDatqeBMTW2Mr3k3ybYZnX0dG+puPifl2McBd9U2xqxERuHUpzm3TDMYCa209MRSt1VU+vaz293wjNXslt0bRbK+rGQs2WI1OVqTWmjAmQF7rg93IwU3PBPgsbZsT44gbYIcQCWB3c1EzamOm9hzcECY4gYmamlh9XsGaWbKZQ+cVhxk0l1MzKh6bqBLWjIqb2WJrMyOJENwNZm7eujEAjTYK1YaIEbG1/FMCgUFoMUNG8zdxYjFA+G64dfqSZlHcDH+BXAS12Px/bWDD7ADU2iXBLDSXJc0di1vwyXzcUR78JLjGydcQSgZvTLLT19dmAa3XrV7nBxETP30iM9kJTaMIB6GN5drO4W3q4C2n0OcESSKCOCJx4GYC1fIlwQZ2BPIAEndSc6qDikCL7W53HGlCbkQwCCQEp3na0p5yRq8MICKWOhiCtYi0MmI8Kqdc6KW51akyKFCEaFoGU93v1bQ0moipUm0dvFM0apx9N7BLkCpei1YtU7HNenF5ef7ps264mazman4cTXXabJZw2766ZRZwJGc3ZyF2amb4QtLuE3N1t3k7I499MDerZVIFM0CSOHaBII6qRp8/ffbwwcOr5fpyfb3d3TKSVd4d0KNQ4H7dL8Z8vN3pWGLPEsgmc7eqVopyreYWFkkiZS0OsLDEME61JSQwUXMWP8UsGMgaQHtHnj5lgDYnUgJTYKmqbh4DUfDDfvjZ3/70e9/59je++fjq/lXfLcex5KLCvFzRlBG76MWP0zDkw/Pnzy8vzx49frTerF6+fPHZJ7/a3u5gx9Xi8u233+pjB/a+72Pg569effjBB7vhWGtWc4BKAZOvF2dny/NFWi67FYcQOyql7Hd7gi06Me0XXVdyHiY1J3hY9F0IAs/CBDAcU5m6rGpeqh73h8PhaPCQoppKkiQh52KTZhutGCZ/vHk7rRb/4Iff/ujjT97/8INqGdGjiGVTdec5rQGAkLuzO5ERrHlZuBMZXicSvi63vlBU4TQYPDUBDc967dow33NzUfTG4adnn0/D3I3gzlq3zRfMzee8BsgJ8apmbn7Hq2x/mhO10gzezKwqoG7MaONzghB7IDBTQAxCfWSiWmrV2vahNn0UihwQSLySzkN/ApGpz3MEO9VaNNuDzWJKJyW4ObmSB2cXVuJiYmmVJIXCVVn70HHgMmUrYGZqAWfi6JicOEp/1vdxoa5QqsciVaTSYT8d8nE6jEMeD6/2IelUp0khidOij3FlPh2G7bDLh00mWwiL2aiYjDKzG4OITDXX+upXQ3iQz1bx4cX68nx1++Kp67Raxk7SsktkHCVuVl1lplHVsvpUMJYyYoK6lTqN01hrEYFzEiYDSUzRrZpNx2MxOgx1N5T9gFwLiUnoiNxgNzfPAy3OzpfffPfxZ798zlKl0+u3N31a+fO63qxCjJMfk8dSyjAep5JFkCKmMh3HYZxGNTA453zYl8OIuMB6TTHEEIVpR+QphdhFM8lZmWW1WQ/jtpSSx2IZYFBXjDWFwBwZkrrOj2NKPYPqOBQZ+6SLJZbLRZ/Sxx9/BLCAp2HKufSxy3EiGNzyOMbAFIIriE0ChUAU4Nx2XFa4CMUYiUgkuKNWL6VpR6o7xS71sWNy1dKYUBwiPJWCzeaqFtSi5jWXihY2MxVVbyMsZiJS84YnWs4AIUgQiVoLBQ2BE8fKWo82jpNXnJ/fPztfYoQupr7rmATFWGJgj5FZrELv3T8vov0qrTerIDTsay4aUxpzfbVDsVrJims2G0qdRq8KCNKSl8s0Ydhut9vdtmgNXej62ElHXqdxV+E3r14sl0t2kIuSD3m8efXi9sWLmOLV9f0UPCx79LGW6q7CgQNMnIhKtf04lJIBduVFWq/XF9BYJ0xmVHzZL9V6sBwH/PLzj/7D3376k/c//7O//Jtt9rg+75ab3XjU4GHJxF0wUSdDcDIn0VKbCA2m5K5GQG3SXWlMtJiiBHIzq2oO8yJeoku2q8tVUat15hoROUubuLBi3A4vK4bLh6vlujtsx+lJ1uwVBVSdvegkwsYCh8f64OL87HLz4K3rB4+unMvtk5tcSreIK4NSOWaDolId6vbVDt9++3uX9+/tdoeYUh5qHWpxa/plItd5LgulAlKXclq5CAqitHt18//+u794sl396A/u/1f/5Q83682jexeLOL04DLW8Mldhrzr6eLy4ePzOt9755Jl/9skz6WnRszmNY65DqblEDwU5j2V/ux/3hgoyQgWU4EynlG2QwomZFADDrVqFs5nZTLM6mVgRiTMxw9mbP32AMHNjtRD41IHPTJHWUTfHPdgsG3jdQfzamfvplC+0o2/06XONbESRXuNbcDIwnOZ8E8+zuMCLwMoHP/3ox//0Ww8ebN765oOXr3bhPjDUPJkDWOLqkUiyMoAQxrEuE7RWdlquV/0yxhThOo0ArCh4mlxPRTUggpTSarVarhYxdsfDCvBdHspQUWubg2YecuS+S44SQkCSko2dVLOWGhKlEAw05QwzSDP/PQ34GYCBMUxjkAhqGjWCwckAsloNRBICQnvrxCBmJ5uJPSeuEPOs2HBwc+DlyIDXamhDdqE5yPYOEnBkr20yTYJGEWpWpw5wZCZIQreMZSzUwfeoWsiZRZyBSG7OHctGqmfVDGB9uYqLMH0wgeDmwdnRdBk0u8jDySGRhUMAM5icrZqQeIFPqhVlX/uwTGkx0n4ox+M0CEukFFOMIUkI4uLNIJiYORipRMTQubqruYMCUE1d4SCer3MwEgu3vHuCKBk7qmlVotlY1O4ALG8AzUmh8/fHr06nvolhOTATLE5/uQM0B0v7XaNHJ5Tqyw9oOAUMtv8EX6U34vTvOH29fpooo8kXT6ecrhS87srfPP7+5Klfh2HduR79xkf42uOrGNZXqVhfe/wOwPrtOt6Eru4uiDtm3ZcwrNeXyxv4J2hOBHByc7NykqU01UYLPWDCXXAAnVyQZjZWE7MoHKbWfsg4cbXcaAaMQMwSyGLDnwkmYIezMTe/pLuHc4BIQD77Uc1MIgKarSFba0WYCMKB3J3JwczSCLGMGXtzcwMTN9SHG/GM2nZqZg6EZt3URjiqbVc4rU9u9PpXAHLmtnw1vK85N80xhwJvWc7sM5OWSJgcrlrNYQ3RmyF1ZZfZud3N4NpOIjgTi3tDDJmcHURopKi2kcwL1fxdzjAR3emE7r5u89OXzDxbZTGjDk4M5pMgr7FjmB3z2+S2Up/SLwhQ1xax63XeVrmpfswBsDevHWlv0QkueH1FkjkILLnWGWUCUSQRgZLW4nA2ApPBT0hZW4levx9vJcNJ2MdQZ0CIWk8iaDMtMJwNQhIIQs7e8h1DEnMcbo+Tjd3ZkkNUq40vU7W2CJIWPNuKtrbnkZMVVwMFdmgpmEajIR9tMlSv2veLEEK3TLBSi6QFskNLBRGl4EOZSxASsHC7mNmVHOyIbqhOvljF9Xn36PHFM3qVs4aIOkFIzzarcWdPnnxeSmUjN7Ka3cTd2sxErToDjBPcQExCzTChfY4EDhxjH2NSqw02yrkeRrx6uV2tF5v1xXZ3UCWrNCmS4NnzF33aXD64F1O83b7MZpFYgpAzqanCmnsVEwd2dTOXQCTccOEGXBI1jaqh6fyJIC1Kp33Bzg5rpBgyh2COCmBz7WLq+6Rl+vR5/eX7v3r7W4++d/mdy3v3u89+dbN/mvrl2fnm2YstBYF60ZGZ/+YnP33r8fWDhw/ON6uL882D+5e3N68O++17737z+9//fp7G3W736ubVL9//5aefff7y5lW/WnAIN9vhs2f1P/9nP/j8s5cffPh0PHzuhj4tri4vfviD7z5+fL1Zr1OoedzlSQNrnurxOLpTjIsQ+9ingF4CM7GriUgMkVncMYzT8Xhcr9fmnmspWhW6229fvHy+2+1YQpcWl/fvRVmfX6y//b1vfeuvv/knf/qTxSIihopipDglB/rrCZk7NStWFK10yg00tzejkv20rn+5wqHTPdWgw5nxOZ/Jd+GeX7f9v94yWr1zd8rMkTUnEKhVeI0iq2aYjRZa6A+qGmAuLcXLyQFDCMzEcFRXcopBoKaWs4KJoAZTkJZa5n0KLdyb0bajwIGZuQ1YqOVQm1tjrDZtbQrB794n4LPi2d1ImNlJK8y85sqBDVa9VBEOokeb1EDgYLELHBnCqjratECNXNImRkpHPuyf7PN+2t9OZELGEQmZ81TVmQmBepFN4pXxolYdxsM4Yr20Rc8EKKCsIVHsEocAqOepS16mvayv1ss+CrvmQBhzLuyDaqSOopUyVeY8DsfDrvJReco2FtecdSxlzLVWJSL1LMGZUkipE9RxHKfhMLqCQwr9sh5vMQ26XNDlxdmLF0+7iBRx/fDqfH35/NNnv/rs43V/9uDx/UVcBhGJcT8cx/FIATlPZhqjLpdxueHD4ZDL1FKMHVZKqQoOSBFtzVGzcZpKLe5wsJnnnMG6WHZAIARIQQcwuAOCKk3Cbh7HWgAu5nU61mmrpGmN87PVZtOXcnj+4nOhzlRVlUmYeBwK3IQJdQpMIGVYEIBMYpdi4sQOy+ovbnfmFKIIByLKk5dcp6zuQt6JcJQuSm+mXqeikyizR1fOo5rFWqxWq9VywTDu94ftYdiquQh33aJtyDEKEdWaS4E6qk1FTaQhAS2jWIfpCCDGuNksYvLuCslc3MtQSjZRqDl59WATsFytBxtZWM21lDJV88ixc8FQqjE1k2RJEnvRPDqhGHI1M62ah+nw6ubFfhhTos3FerNZu/euteZpOu56odQvhOOQ883t7sXT53k4Xl5eUQz98gyRstViE7mFwBIZJA6boAfNRQuz9GkZVz3FNGWt1ZdJ0nJzGMO91SPm8LOPf/Gv/s2f/vlPPnxxzLtqYXMRzpYHrXuZQh98ENRi7m6k3oaI1bRRoBstguEQdmYEgAQhdAKBs1YzI6ZIQC0+TQbU3fHW4WYU+0VMAQyQSSDpKNdxv73JE1bn68Wq44j9mMeXPrSlRtAtqWbLo8HQdbh+eHX/wQNJ8ZNPn2yPr8ZygIAkpL7bEIU4wPNq1Z2dL5d93B1fSYeL++eq+nR6PmxHFKCDtR60zd4EJgdQYyedluiAggO8hoW83I6/+PnH/09v/+j3vxulf3AdYreRdMZ8YKFFXN0ecljS+uJqub652T+jyRfr1ZhrnrJVC0QMLtN0fFUOu4oRzcB6RqNAADc6fysg3Z2EKLiIEDvE52xZhgPVACLhSEJwQJwMQo2BxdWUZpZv6yFOpXezkGgL8UwfmWeed3vSrz3ebGtpLirojn7igENAeuoNGqI2D9tbMi/Ps9HIqQDbF/sPf/HBxTvfeXB9dbu7ee+ds+ef7m6yYYGrS9x/tC467A8GryEhSBtfUkyBHVpL6sJq2WtdjON4PIwwmKmaiyCmsFmvN5sVM8yKCMckwgKaexcAVatqBurF+VpHPxwORQsgHMTUWSQtOicUq1a0qUY83HFuZnmZuodZhcDA3T46ox5alYkdd/6zgJzmiDxDVm1eDSJtY2KZx+nOBvWiliScnu41hsKRHM5d5EhWi4uHjo2oUqUEghtXRabkcRXyvtpo1VUIHlAcEzLIIwcnRwAEE4Y8UfXarGDugqFkLlOMWql8St+yWlHg7hK5T1JIVfOrJzdn1+d9F8aym3I1w3qZ+rjSyYdpODs700nLmGuuWtRdaygSyUMEOUiE2NydC8iR0IXo1fNUcbK4EYDBxjB3k1azQmcWAeMNt6YZe5oZdH9PAtEbRZSfZC1zFg1mVUyb5lP71xMFvrWap9//QuPf+AYn8sLXkhvn85n89cxzbuJodoGY55fw14XfDCmcNLx3RBYiKqV8qWj8Oq7M10Ndb57zGi/9O0978/w7iOPNB//qs3/1+B2A9dt4/Lr2ox1fArNOvwLVqiAO3GRf1WqtlSroDhxtnBScLu32LO7M5E4kFEIgZnVTd1c7TetPYxL3ZnUCh5o2KSEFFiK4uIkWg5ERyCE851wRMazZk8+7++xiRcJzm06BSV0dziIxhWEchSXEwEJO0BZeSmaYx/HEoMgiQtIWcW/YERtZEZnbmRm68Obd1GAzbor2WU5o1goBYiEWgYPdtEknGEJzCgrYmnzRaOabwN0ZaNbKDmqEq6ra/IGAqgA1j3YHVE2dhJwBMpoDUOcvs+1ZM/NphiDndasxh05ManVt0mWzmelkb9Qx7u6N4c08zwXNQVzVACQmMKiRJGQer6m4NEN4sJubwtTmODQ6sTzM2O80inMzzoKqrk3BzQgIxAwBcYTCtCma4AZUzFBcE/PPLJEZVCQhFhA3MYiGwAhsqM7OApCDQQEcBQEgjy4ZxTGbBQWSvusrJNesWs1MzVJM8TLVKZddnbISc5QEl1IqUyCq5MzmmutwHL0T4hwihxSZqerkBZLC+b2z1WJz++KwfXWo2WPgXAASIiEOxKJW2pfiWcF+/eAiRCLWXA85p2++c3123o3jMA2j+u764eXDh/efHncff7bHBGQhZlfUWgCESMyzupJbtkq7x8iYuZQ8f7YiJGxWay3VqwFqpEMG8OzF8/W6v764IqU6qdZZRbYbthK6zeqyX/X9WXr69PNyMDgkiHSxeiaAQ1A3c3L3YhWIIcS0MK8NvQbUTc3qPNppTEcAjcc1A8DzwoQGGeqEdnFmyn2fUkrLWv7yb/7awgDShw8f3+5uplqGvF+t158/27J7LRgnX/T+9NmN6TjlYbx3/8GD67feevzuO99ws3fefvvx48f/7v/6t+//4v1PPn3y4uZVKUhdXC5WRU14ujyj588PL18NL16N4x7IgORPf3X787/98N33rt96ePXjH/3e+dnlcilMhlKZ2U4IChsWq6VIWCwWMYT9fq+59P3C3VPfx1yYQ1Ebi9JxP47jy+dPbrY3JU9gcaOL+/dTOHv44J3v/fAf/Ddj/pM/+wmxKyOk5DCr1dyIqZnVtsLImWHsDrVKzm+UEXPq8t0CjZlteTdYg598q4QZIDvJPNGCEN6Im8EXy4jTjO60ZeC0mJ0EHu1Mc9SGaHvjVmFmozcuHsOy4dRXkM0AN7uJMwikJCKdRHevteZxq6fwIGuPI+3J3c1LmQoozJoJBgWYkSnYZ99g9bsX6uxtJt1WDyYYEZiIICwEsqouPuwHc1fRWspExL1YVlVAHWJ1bWmVKFBWrSXznscy9HHh0bfH7YunL3kPOwKVum7Tpa6OZZhGkQDhWsiyYSLuItOacvGcb57rcu39atWnNJlozcQiLmaomd5558IO+7cfvf2td9/rJJ2tN4VHKhYo6Fhuh20fU4x95XDYjdNUIObiRXWoeRimalwqVRV3HXMOrF1nISXmSJwrUAwcQ9+nSS0ej0MGSCTG+/fuMfLnT35183L77lvf+Sd/9I9/8h9++cv3P3n5/MaM82TjqLmCAhbrRvj11PXnF4vVJg7jSMRd1+exlNGLwgwxQoTzVG5ebRerxEzCchxUPYcgzCh5url5tVidSVquFp1EIylKEzHBpykXp94srTZn/vJ23N9yMmEIY7mMXYfd/uWz57erPmlGnkoXuiHn40FduU/RrYTA7DkI1arqvl7j7OK8X3RFyyEfVEq1prnp3GScPE+1FHeHKYg5JyqdADRNPuXCQjEqMOVcU1yZKshqzeRgryXnw6HkCgKWvYaU3CmllJKIhJjKVNTNSp7SYu3upsQhhC5gaSI1UmcYX7767Pvffbh9Mbx4ujsOoNypm2shABEqgFHJNZtrrq5Zi7NI6haLlRQfu2VvPpTJru5d3TtbokbhKrJbrfPFWdzud061W8bsuRbbb3d5PFxeXJytlhL47Pp+FF50C+f0+bNXH77/YZ1w73LZb9aVkV3H4zgMg2ldptQvUiDKPo2l7Pa7w3EXYzxbnQun4rYdR1P0/bpfnSVaI61/9tHz//Pf/vv//V//ycfP8OhbV/3marFYlchZ/NlnH4x10gMWhM6jg8xg5qXW6mWRqCqgDbp2IWEnIZ1r3Uo5Vy2upsQeI6cUtMSJSLUcdpNExJSCcBAyInef8ujIJQQnksSc9PL+1YPH964fHW5e7MqxdrRMsvjw/Y839zcX52fLVW+mtze3P/mbnx5z3eU9HNSBAxS42KwW68WDx49Wq5iSu4/k+F//5f+x7nGxuby8On/46Dv2Q9/fHD/9/DOtlnNRdWpGe9FB4AKyPnAnQTxquqB4dnZ+2cPzfnvzv/3Lj//i//v4j/6zd/7gDx9/45uyWIZpzE5mRk9ebo/Yctq8/Z33Hj998cHHr0Ku45DLaAmIEYGEHNa0lgAM5ARrmwHN85GTe4e5CnMMEjr26EZGrgAFCaqmpXh1F4NzY1TDzZUdMJ6tl9tMwl+HLwHaikY69b9faKl/M1fiDfbHF052d58ndHJK1G2TcqWWYYpZFBUAZ/II1fEw/umf/vl7v//g7R9cv/8x/+BHv/f0cjsdbLkMaVHvP+h/8Ysnx+GwWm7ub/rjdAQwDEP1nOs0DvsHD+4vl4sgPB0nV9PqOTfLFKyWy/VmKYG325txnKYhi0i/FKuFKs3J2+6p89U6QMUFdSnlgGjijlzRHJ4kxvUGU62mUFOQEwmBxB3qZt4tYtcnUq5sMUQI3H0e/gFmVmulU+RUK8h9hj9A3Mw3pPkfMaGlhTaWVghRuRKhmrZ9syUIEzsB3MUKTYsudoHKwdi6ZQ/2/VgBM0Hx6ZCVQ1qsexv3VWBjZSerxsIpRE486VSoLK7T9fX9dB5ffPaSe4BAkYqWUNoF2bzb571eTR1wNSpu1RNFdg4cTJ2ED58el6sVyJxrEqzErn90AAAgAElEQVTO+/PNJUwOOuVJmdnI3VmL51yhQCgFGOtEzNdn95f94rA91lI9eeS4TIsy5JL3rti9fMXMHIQDzcEBJCRUtKpqizQzA/QOw5rVLDiN2N+8zH/91f2a+tQAJ/a7znmufAhO0Fb9OBSgFl7oMLozjzvdG4STzMjvEPEvPuMXX5a9Zrq85uB/4eW9cQu6u/CMAdyd+RsBh7/7nDcoNF+DW/3G46sY1pe4O7/uF38HYP1WHy2z4M7P/00q1pv8LAA+G/NYbI5CRFBHwTzon+HfZlWB14/WFkdu3uJAm34QkdCb54HESYhlTrPgGZMwJkSBEBm7gsCoRHA0I19qoXrMxM5wJ2Zr4MtM05wZl5hZYNRG6+4MJ3d2Z2oNi8GtvnFbMAlzC0aceyE3mJuh1BooiAgLG8NmhigTMbmaWUtsgbTgem50J+KT2ZXNpFewM4mznTjXr/2VT+B8Q6LaZASl1BbyeiKVt7EPg6mZTRlOZmCzraKfoKf2qQMz7MBs7UGciGesXJioibt9BiFPPSFCQ5xmEaI5yGf/b8BhRgwolHjmmmMWfzX6U9OZtgGTu0HhLjTT7chcMRuCgVnbZ83sRFxxxwwhhQsMxBzZhcTMTkM/Ha3eydFxtwEzESBM0hSaAqkk5mxo1kBkDcFqsFd7mQ6DU+q6mou6pXW33pyzkaTAFCjYlIdA3PddWIjvy/a4n0hpduMid4QYs1mbWKLCsqFKQIos4f/n7t16bUmS87AvIjKzqtZl386lT3fPpYczpoYSIRsGDAuG9CALsCUBevCrH/zsB/8t/wILlg0INizbEmldKIoyyeFwTM6we7rPdV/WqlVVmRkRfsha+5yeGdKUNBIEF3DO3mfvtWrlqarMjPjii++LUrSM05xnvbm82m472nVKMi212pJ9QQTUnY1QzR1e0dJ8dwj6PnBwUK06Hme9urh89mKb53h3q9MJT26eXF7e3HLFCShY5S25c7NVEYScV2E3x6OGUbOrbqoUBPeitWiFeZYo7jUI1BEDTvPp+DCRpGq8FFQlELKTM095EglD6mOSFLkSqrpXlSAphax1tbnUtcTq5iIhuJc6NzDDrZVdVyGkNllwdhlw8NrXeu4ddZDVyiLsqBnLXPbbzabHl+/G9KM/vn765L/823/92eH+1e3t8iaTSD9scilF4QR1u9h1knqtfn9/p3VeTrtN3xFwtd/u99tXt2/nWiXF/eVVUWOJCp6WLCF98vFHt+/GsljknnpayGyuRMoh/uRPXr+7e/302VO1q3kJF/uBZNt3YZkXJoGbqVupUBNwlzpPNvsSJALour70RaHVilGdsz8c7t7c3brX2Cciybm8ev2K+aHf7G+uXnzne99EgocKEhhT8LJUaYsvt0YBXwWdGo1SuTXOPfK9sRbuzg11Z+oWgPclgHa+lUD6uLsTuVNDQHGecuu//LwLnOOYR+U8gNae1XMU4uZa17tPTgAbjL9W9oeADGAQEyqc4MKEQAxXJTCptCCpqnpRNadGOkttSjc7VHO4q5uphXUfM1/dS9cQELTi3w6ttA6XXNuLeWWymSkZFVZYBaFogRAEcGIjEdFqXhyABbfeAPdqcMw5azUS5k7ybcURwmJwLlEQUWW+v0dgi0rBlAwzeZI4BEoUEYuXeax51ED90A1QPk2HZdIQ4IhaKiOY+3ZzsdvuCORGUfou1iRdhT68ewtFKTyzZ5fTZBeX+0WPZVmmRZfCCmhrpTbSwgp1Q0eMgFyhLhQVgYwcq484FGXJ09s37z756Nlu14unGLsYd5vdPsX0+l2eZu2YlpG6nipZKajFEJ2YY5JhSCUXB0mIXSfs4phSEmMy86XanHO37Xb73VzKcTl6RYgiMfiY65RPPkqU2AkHdg8GbV14ORfyOW363QXb4vlozkgd+g12O9kMNI9HFCxe6xKtbrzIPJ4e7iuZDB3MapeESKI4ETs0BjYVhpAVnTRTWCq0rO67OaMUatK9pbgZQspDqoGDl1qKOjtTUUfOuLp0dwoxdOkibXgI131UoQVazKkUdgAiRMGZOQ4R0UW1uDkFuShlgRp5DAxPVZgDy5JP033eXW2Xxez1gxucmureOdQJIBVWMatFS625TwGiEuYugQxXm4/KVNz8NBfSvOu7ru+I1Jiy4256IDIeOFHwUy6KutiQ58uLLiXZDT07B6JCtvjpQRF7xKfbcLOrXXgYH07jOJ2mCBl4x7Y366ZlOU2nw8NoWrbDtg99nSlb6LhPGHb95Yb2Abt/9sMvf/TDr/7xb3/x7oAXn+6fPP/41d3D669e8hDjNm2CDP32gcegQSzA2Zm5GptINVLn4l7bFeAYQ2SBF0E0d1VvCapWJ3ZKFBCMghpb1u2wgyhzEESyVIrNJy4VS7TLq2G722gpVetsx77rL5/3IVI+OtcYafvNb31rPuX7++n+fiSieVlOp7Jk3+0u40C5zkueRTAeR2a/utimwG7LNE/LPP3qr38UuXNDnstpfFty3u0v/uIn3394ONzd3R0OB3dwoNCBBWwR6AJ3sYvc+cXTPuN0+3B/HI9dpE++czOejv/Xb//EAgp/9O3vfPL2bs71uJTpze3Dp7sj9ZsX3332K4dv/cnb07jMtcAdSkEtKqXAknpIPGkBBG7UlFoBeNNzIAfMqTp7SjENiSM71eqEpvf8mCe7WzUxeHVXQL31DlCjzBgauZqaZ6A6FKt3y9oGQM217T2zY2Vrr3vNI2eE3stdUWuspJWMf67SrW92Nl8rZK2BqAF27oCLUOtuF4E7I7ufwqsfVzkNV93Fs8v9l1+97feL9BQ74uQHPZ3sJAM4yGY/VPi0LMthoRHLMi1DvtrthwsOZCng5moz5zqeCi+ICf2A2Fmt02G8G8fZjYZ+F7t0cR3YoealFFXrhhS7sNRTkBD31FuwGbMXUmiwEjT0qR96LPl0WlCNufmxw52UFRVpm0IfPRubUzDpoYt/uGkrjJqlxPnCMBNC2zMZ56t4roQbWuAsHGMILmpaS2k7tbOzkAhTcE8OhnemoZjDpRn/QAWFnANVdtMcOHEf4kVntphb8QUG6STtIieqdYHg+snmk8+ebzabu7vbtEtLqqLRhbySiDi5o4KsyX41TNIIwhyCCEUiNmenIF5daRqXECJdBUnY3uxaezEl4oUO4xEL6qR1qlwAI5SI4uY17fpuPyT0RWzmrOSbtE8hGcA1eqmlOMQ4etcliZFWdRIrVVFBRIGouuoqkmG09hagZZ5fB07OPlvrNfczy+BcxG2p9rko2O4Nr1T6x5M0CZw2VXT9KD+HOSv8tZ7gnGGtUlq2pswfaqsBdBb4b6DPyotYkW0///CRcvU4dFpzzPUNaxp+Htl7Nth53B8CYh9887UusQ/Rq2ZH+P49fzqq9QvwqT+N/vb+hWss/MsHsH5+NP8agNwvayQ/R1P6GdDn38rA/jSa3J/zlY8vflThVdWfQUAfSXrreVb1InNzLdqUTAASCqbmWFmLRCSyKqwXK27eSCsxBoDUVDUzeNVRahOIhYOEEFikiXHXNjeJ3MiYhAPMTRtnkii0HjRzdatrXkO85izEUlo2461+ztw2J9d6zn1zYUnB2Cu0wcTFzU1bVzywpm+82pV4++qN6GwwrZXdoAzBmb3FUVgClKwWg7O0/u+Vj3YGDty9evNBZBChyUo2nU7ARQS0IgoG4IzNAW7wYpCGsfsqCkZCEAGREMBsBIeB9EwqwLpaELna2uoOCszssOYm7CBA1WAGbixUIfH4iDbCa6lnQlNzOG60bzDBCc1FlYjUVMkCCzNTg5BMDe6uLSxp1oUAN7jukbfaGpV4bTK15sl4DkLIQeoAzAAmJxYI3MEBDTPipozmjPfaPiYSQc3nrlUOhURF4NDVmWxtVqJGemIK4mymWkxSzFMGoUvbKMObty+fvXgeODiqUY3MVipFHvp+olMXxIxzLhwYgTiK5taWQVBECttu23UBosQopS6qlXHSmTR0TNZ7vErcp56Ht69fIRuqGSkoIBoYoWOJFAYfT/fDLqbOQ9dN+Z09HK6uriXRsI2ffvNpkC5Qp4VAQEUIMc/OHIWZYFqqU+UQwArXsKbkzUnBaGA3pD7FGGMI5gp3Mw0ikmRZZmZaFr8/HHPRXMk8mUdULPC+F5AvZVzmUatut1sLfHg31TlXWBeElFRNApicEzMhL4vC6Dz/DasQJ/GZ0CsCkJpbW5SYV+672yOTmbm1WjKZlbnUZBJSF6ecw9/73/7Pv/E3/0bf726unh6O90G6Fx8/++KLl+rz0FNMSZ1Pc9kOblbn8fDF4eXN1cXFxeX93evrJ5dznovjYZ4220tuxDEFUE1rnvX59Uevyu14e5snhQem6J5PU0aFFfzL//vH++1X3/z0o48+ukmJry+2k9XgDHUi1znnnE/GqFaKMkQ4mBsRQWTOsyQa0M/zcj8eX799vbvY9rtNDNGZlprh+jDedsNw8+ziP/4Pv/HFT2/fjJlMowQYuD8TUA1nXXJ3Mqb3xk2PLhv+foV/H+P7OVw9RxkreRZo6mPt5ezuqH6uRvhaKHd/jE8e/0Y4d6uuTY3tLjsTu8NU10LiiqSt09fsHDVZE/Pj9jFgJw5MCYDpYhWtNckhwsm4uBUGn8mk1GI9Zxi3rcLgbEZas6oSCGqkYAcZwZu4L1kTrW/wKXwN8t1dUBs3lh1AHGLadrFPasVcvSJQ2FCnoWZdNFfPtQaz1rJSDQItBuLIcb26yjF0nCVwSKVPPTLmrBmuEJeasFT1Sk3DBN4Qv2WxXGyezACkEEJiw3LKz65fPH36hBF01ldfvdnGzf27o2AJlO4P+epybz44kwz19AV98vFHGOMMJ62xo1pzqcWdGDERm1tVosJadamg0PU9qpOBY0/bi0ihmi7TnPs+TUcti1nWV3J/tUs3z148eaKvXv4QGRYohcAsXpclWwiZqxfN2508S5dv393e3x1Pk6a02W33d/dLN/CUy7zMSynTPPc57a82F1d7dX13PxW1rqdhlwwJwupe5lKyQUAdU2QWgJHzvI9zCIfNZZWwRbGb5+HFt7qPXlxshvjFT99dbrrTKXhJgq4udLhfjodqqgdoCLjcb7bbvmrVeiJW8yScmMS01EXvDzIvtExeSzMLbuJYpKCiXg2SkIflIoaIJIpSczZTZTWfAFWNSW6ebZ5cXkTeiZ9QurqUGJgp1WqEZgNiuaK6OAeKxE5Wo+bCgSxRJW1s4qJFXZcybYch7VLYCZ80Kbqwg9EyL9WrRLPCyVIhr1pzKfuLQfVBeIEHMmzidR5fvXtdlmmONM/bvNt2KWkHjp0s9gDPIEPnMXDIxoTYG0Vl4bnMkeIhnx6WcdTjxYuQNrvwZH/q3Gx6N97naabq224/hCvUCzXWjNPhtkz1+nJ3s7tEZVvEc3999WIXL7jSV+/ujuPt//z3f//z129ePkw0XEyF37w5uFASyfNyynMUqjXvzmsU1EwV6myeSGwxFOMm20Tcd2nT983gIuearbiSqruqVyvVWZWKqnj15ep5l2evVU/HKQ1YljIvJN02z3m36WTfT0u5P9yNJQ99eP7kebeN7Di9K8vpeLidavVl1qWUWhWASDcMoSxFixoYzhCDQ5cyHu/zQuYZojElNZh6netxPgiH3ZNdNwwG8kgW2CO61O9229BR64FTdyfEDnFInuTwoMelLA5VeXXIQeLbt8v4mz/5/OX0X/ytX5+Wy9NS53K8nyD3t9Tr5bOPn3572D71+Q0GZq+Ra+eWigkzxY1LfyoLqCfPAg/MRFqqFZCygAMze7dL/b5LQ1dM86JGAkepk8LdnMEKs1ysggyiQsZmalrNmxf5CjN508yy5r6Dc3bceh7O+Yivu5XDmWQlojxm4W3rElmZVufOrHNX0zndbRYwAMC2YjLB2SFGBBFxZF8KAQQjBCmGu+q3ZA/1erv54/y7YYgj5mOxbX9xquiuNluveVnNOkrO01GJUCbWrkxPp10ny3IUyZthHxZOaXBoiNhsmcKy5GUuc3UI85zrkIaLmy4lnk/1cDhZRUxd0XI4jV0UHiSITEcF3DuAJGxC2ERm8tk50bIspeZaFSBmiTQ4OQ8iiao7qlrQbhtOuVIHX1UvQCEQSyB2NTJVtnOc72i0BjgTmJlbJ6IrvMJYUgKJV7gr3MHuoVlWggLVUKQT6glNKz6yDMnFI2eI9Zcdky9LzrkISLacQFUcPSJinhfZdUZarMoe1092w166bdg+HV69esuD+IEkdlCGwrmCAtgbg48CXMEEYY4eYc2CVL0jXcyfxbvj/Weffrb5xuWXU9k92b95c8cqFjj28f6nr7AwJlCBeODKTjBxLDVARp7msDBzPekyLc8utlQIuXDtrFDYwFBhbJUDi1AgkqqFarFK3Cy1VrGXNfZia8VD5jUSXrlVLqve8lpQa1Gcr4QPs/fc9lYiXwkZq4zbmqJhpU/41xha7ZGntYrpa5/UB/yvVccDgnOhUVblH8Lao/hYpnxEBmy1w2wGrO8Z/e6tZruC0TgTyJjpTHX5WqyJ98cjk+vnv2mntQ+xi9ZY8P8Js/xiGGQlwbVPfcR2v4aiufv/PxlYj1fkQwzr5y/TzyNcv6zPxS8DHfuzz/DIrAshNJtYVV0JwOfbzETq2gZGRCIC8fMTD3czWxlHWB87EllhhepOzfQlxSChPevqsOqwCmJIZBaDWzXoalgmK5uZq2a1CoNyDTFGjiTs2hCJx2y3hpiIUIu3yuSqjxBIAYerKYisVoZJivBHr9GGj7RG/HOORQTmbNVQzQFj8LnbxgCCoYnSozndqDk3WR83NXNAayEhCcLCvnZUnfF0AohaZ6KZMa0ssjZp9SyaDiJqCvT8XuKdmF2afJ+AzM54E94j2NRu1kpIImZmJeaWetpagXFf4TWciVQrL6P9552afnKjUzTfyEABDT0kNvbQGuXZTdwhKpnR1NHNVK2iLWq2SnaDiAKHBoyCVrsad4ersLQWs3VJZW7p+XlNXhf32CcGmzUT8RazGBGvAjitiOFq5mh9bADJekOJSbh1CNFKxnAqtcRhiF3susGKklGAEMvr12/7LvZdvxzn0FPNxdxCkKIAzL3CfKkLXLV1owq6IW22234jUx5rVSbebBKFQE7TMh3maTkpiexu9pfbqxS5LuV0mud5Vi8cIweWhM0uhd4Nk4E3u51aJjZiHk9jl7rLq6shbu/ePhyOp9w6UgQSonDTQnUiV/PWLS/EEKymBuel2qpLCKnr+r6LLLUUM4ULMXFi01q91hmB+ne39yKx6weSERlIYCFmqqVM46TVnl5epv1GM5bATFBTZ09dsNk96c3zm8ubq9u7u+P0wIHdrLlPo905uBM4yMr6WTd2I3+kdNKqJAvwGZhpdOV5ziFxYDqOp1Hxu7/3B88/ut7vr0q13X7Y7C6WRZf8csklBF5yzdWXTbnYbfbbNB6n03iqRWNMzz/+5M2bN+/up3lRw2nJBeDNZpNSV6sfx8OnH332cHeCQ0tuhjVOzkJGdVn0hz/6vEs4HA7j+OLmyX439BIlxCSMEGQZx9PpOB6Ph65nls1m13VdlBAkxBCChBSTVys1z8t0PB0pYrPZhBRiCiHJZtiPp6Pcvv3e977/n/+Nv/53/4e///L2y9RFU0UGDWTVdWU9NnASvJqee2O9Pi7rwBnsXQGnx4Vi/XtdCUAhhDUtMGvtfoSmcbYmB43t2s704V5CwKMP+lrf/SBYoTPnaY26Hs/wqE7qrR6/6q40SK5mZVZmMnX35qbUsTARM0sITkQcBLxaR7ctoNUARSIRzFSruq4pEJ99PlozS1uG15ok+7ns2UqqeATxwcZBhqHfbDe55pyzO8RC1BiSLDzNMptV1QkABOqmqJbsVMft800Uuv/yXTWkPmgpc67D9SbroQ0LDGJzztXJtKhlD/bk6fX1zeU4TvP9YcmjwobNpqoXzwF0mOe/9Nn3nl49JeU3b9/evn2YwpIovnz5RhU18ye7/eX1E94Nfvf6xy7LlBlhv9lLHyYqmA7LsVStkULqEocw13w8napX7kgCZa8OIZa+j2bsmPOsruTOD/fTeJjn0R/u7cWV7oann37r04e70xfllZqzcF6qwUDQPqVO3PO8uGoYD/f396cy17Ab+r67ut4VJRyOtdKyYJ6nJfNQqE90ddkLoxZ3VwlkO86ntiI44MVNp4JZWNyjS4LidJwUbqHTJx/tPv7G7vpJ6Dp5uDvmScmSFVpG1byUYqdDsRkkpNkVqL1rhVZbZh021IUteVxmWyZopuXgp9EPhzrns9lJSwlCaIFe4JBsYznORZcll+rWPCuCjIflNM8pod9BtS+Wq80kSuyhq7uLjZE4ebUF6kGYQWpUqln1r76amGrX85IBqgyPgfquc6bYx/3VDpT7fTw96EDpyZMbmNy9vbt/OGjxu9ujenYuLrW2wYoQqBbb7TZfvnw3Hv3+voyHiW28j4eYuOvp6moopYs89sn7LnZdB9caZiHebLuUUscdnOd5ef3uze04IeHpR8+3Fzci6bRM02l8e/u2D+lyuLjYXXbdoOqo6lq15KHvri4vgoRp0qG7WnLYDFeCze3b+9/+nd///KtX//3/+MPPvrHf7rddpIfjePvmp2nYDvsNVVo811qY0YdkkJKx5KUUJadEMUqclpMryCmwxJi6vuv7weHjccy55Kyl1FrM3My8Zq1Z51MGUzUN27LkWhUpRSOa5lKrRg5z1jdyX32uvij8YRznCX3c2ilMd/Xtl4fju+XwVYZQlK1wdATVqmIxWc0VwVlW3qobcijLPKuTeQ6BOdLd8eHtmwkT0p6fXF8Vq59/9cXr1w8oQIF0GHbbfjvELpjlOZe8TMWMK4caD9Oxmqm7I0xZp/EAwnbDp9H/9994TfLP/sKvfbK//sgRAfrRH/047a++vdmEaL/y/evP/9eXN704xVqEKTELwTl4t0lac3lwWAHYhR0KNzAghOgm2F3tKLCalVxrNQqRyVelCHKDCxxM1nq011JHI2xAqz1yf92d/UwHXpGq938+zGxb79J5lX6fnqxFGFuFPgFvccWHO9E5wG4hLbGf7aIIIH4kLINgpsIeUgAyFA93x/Fh61lLmUFmKLlmmiXEDcfQ70TEU+gOtw/lVOqhxBihTu7LlHPOanXOeZ4PInEY+s0mxUSA57IspwWGwBAStyZNSlp8WUqeqzszSi1VBNXVq6tR2IT95U1UKdPi5pOdrDgTsOHNdjBNy5LdPYWYuk5iGPODE6NpoTBxYISVtgNC8zfhwEDz3iSrRbOumAGtu7M3HjeDAW6eempq4MBgjilBmtSJO+kqUdWqTRGSApxFJG2Sk2dEDxpTIrZidcpLF2i36b2XnGada4BI7rqhB1nYcNoxmO/u7/fEksJ8XCgGE+VSmz83t/I1J2d2LuQmgiAcIWJs2d21qKK6wwJ7rXpzdbm/GU5vH3Zxrz3dj4fp/jTIFiNQDAu8EtxZyWAenBHG20PW3O86KzblCXCHGci0VqsOQzNzhFWtVDnEtYgvgYOyq7tbS0f8gyCpccC/Rvc5wyhrWPRzkMvaz+TrHRRha/rLhDOF7jG+As4R35lTf06GfhGS8xgKNgLWY2/Uh3DZI6/qcTSPX93hBmOnDxv0zM849XkW+r8CredcPH3/zwZdtYOIzOwRL/u3evwbAVj/Dsb3r3p8OKQ/g4H1C3/7y/rcX9b5/3xP0ppyNNijPUCNsfX4OD6+puWVzFxrdYPpCtA2x9bHlIYAZomBW8blZopKj3rnIDOAPXBwwIuhrgjYGd2l1e6dAG4LMIjXrAtCIYTq1dwJLJ0QQam1jwMCJF4LMq3gAmulLebWSkZE1EysHgGs99eCnGLrrFk7dJjYpS0hCnJQ2z7tkQ5E7y+itQ7l1int7uRuqOt99cfVp13Z1tZHjfmFcxq4kroeM09eAbN12K31c+0PbG5dABBCOK9pZAATDFZVzwUv4qY676tOorZOBAcMEoJA3i9MtA6lscbhxNZAIBICGzfUreWEsVFezdxd2+op4DUWsTZWPr8ABGaQws1VnfpA/jPzDY8cnMcftnGt5huykngeo5n1t0QONNdGb9uzs7S75WbqSmoGM/XqprTphn7omTzPWSjUuZjW0+1EW00ueZlly3WpGaUpS0PZCVhq1QVk5goAHdKulyDLUg+nuVqRhBBjjFFi1KzL8biU7IXh5FV3F71mpuTlOOsMkyJ93G63sSeXDKIm6TbPuhlCjD05ovRd2rjJq7evb+/uT6e5NWHBmeBu5tw4k+YwGFYbQiKYO5+Ry+zqtVJdlGbVZVrYKXSSuhhCEI4EUi7TMr9+/ebp06dGqKW2rSwvJWyCdCHmUGse55Ns++tn16fTNC+n+e2MB+RYscf11W5zse02iY5UvKAQmTNcpBl2upq2at9640BtQfhZlQAAgJlT60QmAryUXCqK62bLFwP+6Id/fHW1h4lWVVWohCCboVf1UsucKzlKKczebwfXTck5lzKOpx//5PPf+hefbwbZ7HdLrofDoc28FPoQRDjO81SrikjsIoG1FivFqLbHrmZ0gUqt85JrrczM1Ix+KAhrZCJbylJrTanv+k61AiLEQ9cNXb/Z9iIM864PITIB5o136ilx1eV4nJjCdBq///1f/Yf/6J/iJ19qrcJMkZgFYlZ1ZZmvOQO3Gl67ZI+z5X1osOLfRETQM8HtfSphbfs+r2C0EqY+CMTokdf99RvUTvTBwnnuKzxvIuuEpQ+qYB8eK6/LjdbFBU5nOwJpmU9V1a+vYMzCInVVwfM1XVnJhmzawNj3AZ2fe61WlnpD7x7jPmpFgoZk+VooYJDIshQ5TF5RtZqbcABQ72radtvNXihOdgpcQYWJkXyas/sBihfXL3ZPN9PD/cxlxGizY8qZUpUMASI4AWKLLjswKlwAACAASURBVKgVcGyAAfvr/fZi/+7hzTiOU9Yo3AeatMxLGdivB3u2f7ENu/lwOt7NNxfP4a7FclUz7rfD/uZqd3VhMezm4XK/t1xrydTTfrObxrdECMwuxkCzdgJTKaV4iSHkWh/mHFKiUB1h9fVVdQWhL7WYS9X66uXd+K4+u9HPvvndb372rTfv3t3/cCrbev3kusIO8z1cum7L1Gml+/tiVerCefEllLmbpvlQlcwWltpFdBGJLbFdXl3NSyrz/f1sTLjaXm7767dfTURBOpZeKpXb8e0hz0aQiGFAtXw/5k2Hm8vdN7719PImpV5d9XA3e4l3b8Z55PGImlGL5pMx1n5lACUv08lLzoTKFGFxmQjk44jTgd+9qq7gig5QQ60gZ0oCdQdJCMgxOxmxVpxmL8VBkKiSDO4lQwKMp4rTUh+yPhQ/OcMZ1Ud1Alk39ErOpVRzqGVTc7y89asBsRuIwzJPhwePAU+ecOAwDMP+cuug7T7l63nwEAe2SpwExLX64WEmMoQCMRWIB0fSqkG2T29e/D8/+mI+TYf7pZamKMOqXkoOLCni5pJdi1YjKJERrdTqasTkTAQJ/bD3UclKigOZHE+n8TS615o99XG/313s9x0lHdWsiuiwiX3fpdTlbO5hXmq/e3IjH78uD//yD//oH/2T3/3pl8e//JduXr09vv3p2A/9/nLXOcZ5uns4DLvNxeay2DItUy4Z1ooX3qCVBhSKBDMjIxYREWJSt3ma7+4fpmlpbS5gDkzmNWdXg5qtQaefqyOr1w8XnMbTkit4WIZKHJH60FNK3AtvjuPx4W45nSo87q62qOJKahCnwNGgZVmKLV2IMQp7qphL8WLo0hATT4WmPJ3ygeLw4uNrMx+P45dv3kVH3w1Pn13XuSzzYuZzLbcP95uhd7PjcTzNU1WDgAOG/XYtoTa2S3BXIyVi36fyB79/P0/0V/7qr237XuL2i7d/skxLmSdh/d53P/0Hf+9l3AaXZCSBUuTAXiki9qmrjkqFBB5MDdURHAyL7hGtyOmqVesyL2oWGgbSkH4nITMS0BrjuRP8w1z9/QpPxI/VtFawekxqWgzsP6dkgjMl44PA8LEHDo0K8vMBA1YOFx5BMLPW4MAwczi3ddCo62POdckL9nj5+tWLN/3+o+vt9qkFFMpOmUPnFBxuVBE4pVgXp8xQDqETCZGzV3cDMReDF4/OPbq+2222yU0Px8Myv4EhihCSGRMCo3M1XXJVFg7MAW6bTTcvy3iyqthtwpPnTzZdP949HO4fjuNYvIDh1S92F4HFYoR7CjFGkSRlLlxZi1qtNUrsJG5RMji11CKs9BgCCRuZm4MdAuGoZsxErSOG1qpOyaVWuANWBEESYpdoxcXMvKrX4sY9KttcJrZsQOo6UoK4s+daJS8hEoT73bBJw6ZLXjQF9oWD9/v+WiRxYOpckhkv4+E0nl65Eg2whwpAI8jEneEtZWOGODHT1EQq1NSVzCxrRWAS0IA+heMhB+FB0o52G9rG3bC1i3flbrw9IaXosNLqR0RKIAQWD2wwhy91CSn0Mc6zKsqSl3k5GapsUGrGqiRmyiYWemHpJHlyd50Wb0V7WvGj5lhA1qzmHx/plcT+ATlpnQL23tMdK8RE5GQUSCAfBl9nauK5DNkCvQ9Bq3Ol8udnBzk+nDjnc/4MuHE+58+//bHD9xGGa100H05G+QVK6v6LzvgYLvo5HGPGL+wW/PcdwPr39mi504c340M48PH7Pz/i+Of/XHwAXT3mD/8ap/pwb/gzPqsFrKr6yNZ7ZPG1bOTDZ6htpmam2oSbAYCZQggkRJVyKaYaiCSQCAemqlrqAneRkFJiIVA0CEWJIdWqSynIFS6uVaupnftMEhog5UzqXpYRjiiRWSSJMwRgYkR2ImbnSIAFkZBiraW5SzFJIDiJKmqtgYVCICISWYXh3UldW9HfHe6xE27axmbuRlGY1vYcVW2llOreRPtWiRVmEjCzdkyrnLYSUYjiYIOaGlFz5IOZMTMxs7A7XNWZEMiKozVLttuwEtmYhb2hRrTeg7W6pU3Wz919GIZ210wNumrBK9qW70zcFNtDl6JErHrfzfWeQhVuTrxEflaQWZ+56g6vru4OCWB2PqeO7m7Wxd7dILDgHVZCeM5m6qrqpo2i1xY+actW62xjUDVnanAnnS0C6GfmFHmpC8yZV6Sgzcuclc+8sHb5QSjW9o8V6oK1DtdiTM0YR1VhwITZRoc52SnP++329uW7aTxhwfiQx5j7xHSiuElx6N2YWLr9niWM01TdJRGogm2367aXu6L65t2bOc8s6Cw2QISzmVmIYbNlXayW+dXD8Ru/9hc3XZ9Sp4ZcVYIQ0zgf7x7eTrmQ9Or21as3QSC8xd1MzEwbr6fD3Wk8zseHcZmX9zNxfUKBBoK4A2SOhgVbcDSxFEe37YhYTEoueVlsMiiWUHRrWs3MYt8586vPb1+Nt3/nO999eDg8HB+aBZgx1FWCpE1yt/FUxvElKFxu9s9fPPuV737WD+nJ0ycphXf3d7/7g997c/f6OE5gcCSzVYurLSNGhFYZNyNiYRaSlRrjfOY8rN9YdbhJYKJW/jMi7yK5+XTEb/7Gbz55fv38xdNf+/5ffv3mq3/xL/754YCUsN3uQkwxHQkWkxetVTOIJIaPP/rm1fX1u4eHl7f49SeXNzdPxmkCiRuCyDhOp9PBDBebGyeNSbSGWsxcQQAF10pCrpaz//TLd9NxHI83Ty4vNkPq0oaIcp5TJ5tdz5FhLMRW9XQ8Mgu5C0kfu176qsXUQwh934mg6jIvBKf7h3e37w5d3D998vz1m58+e/7sP/ur/+nhQX/n934Qek4bWIUqmjMqiNmZmjKEezO6fr/lM9OZHvW1TeoMXOkHhcHpuADvUw4ABpOzz3ZTPGFmVdOmQ/d+c2nu3l+r1D1+FrCy6eiRcPX1o01YcHNqJhCxBIQVqA8hmKm7rYRgbisSN3B9yYuQ0FrU4OZ2WktVrf5Iwn9PIQa1oQjBwUzmbq25mB2B1mCKCOzMLMIceNf3IH94d1+mshrszujKrm4wXCfasQQmYw/YDtu4k7t6yFa6FE96+s5H3/jk+tnnly915vHJrEW1VmJWqkZVCUZgKIj7/bC72ZC4it0fj/f3p1dvtBQ8uRQVOR2X27fLfMR/89/97W8/+Szf6cufvjs8HD755BNXG/Nxd/l0u9sP2/3F05vQ9V+9elmm5Ve//T3X5cuvfvzwcNdR9+bLV9oxC3d91KXeH2/nOU8Z1dDvOHBUdWaolTK5OuACc2Fike1mP1MhV82n8WF5eTh+/vIH41399b/8l/7WJ3/zn/6T33r3xbu3r2/DZRd3Gw7p/mE+zYfnV9ff+PT6Bz/8nWWZtfjxWA/j6fOfHoIgBsSAzQX1vQj5Mp3enMaL/fVf+0/+2rNnL/KiP/6jn/zoD3/ya5999+EwHZfRXYdONvuPFx+ncpCON/uw2GxWr6/233rx8TdffERUpmm8vz198eP7w8My3UlZBAt5cVSKimpeFannEDlwCExpSH039H0qmR/uihAvSz+P9vD2lNY2DCEnbvLtxZErItLlpkesi2dHdSqVGziq1dX84ild9vjok+tPv31xfRM//nRz8/xTl29O05hrfjgcxnkKXer7YdFa6lhrzQU5Iy/41ifJLA7dMAyb1O0It+Mx/+TzOQZshmPsNimlTz+7/uj5zemuPLw75AwPvtlvXcM0TcyAwgmICMbGKcV0dXGz3Vz95m/85jLhNCIKuuRXe6GOLPv9Q3aff+UbT7TcaVXTGmPsu00QJkpLtrGMy1yYQ0zdxcXeHK5yfz++fXc7T2PXd8+fPbna7S72+8Cwkqu7eWafL3cxdbFkqyXsts+33Sc9nv8vv/eP/+E/+K3f+uc/YMJmP3z+1TuKYbiIBry+v5tyrgoRHKejObKBGCkxWdUKVWvubaUUU0upd19gRMzV9DSOOedlqeNxUdMu9cyUorhrVQxDASME6roQI337W59Ny1KrOpGBba+lbh9O98Xm7b6nIKd5XDIuN33Xp7rwu7fH289P872xRJ8NFqgSQYRYOBpy1iPILaBWVy/FfX/Rp10o1aZlmuusBg+eWOdlIkI/DJvttmT1asWrB8RNgpK5jcs0TZOWOi/FmrNzaLc1l9X5eHWRC4iV43LIXQpffVW/+sFdPv7oP/or337y6cc3V36/vL2/fdPt+Tvf/O63vom9XM9HDpnZewHXpUzjYZpOIvzkkyeR94mH+TQteYSZ0dp7WWvOWhzQataodaclw61W4GxmVIC6ejS3EG5NzwGs9kBYqSZ0Lg4A9jW6yLpfrEnWeQN7NKFbcxBmanQMPjt5P9J+v3YiqKqjRT3cpBcdLXYwmAtRlzo4pmUkjhdX++yH/+nv/vZd+el//d/+V6485TzNcwUz0VzqMp+gFjHEkMq4SOa+DvWQS1n0CfQGcJYuDtvND39nRBnB2F7g+nrY7foQwsX2SaDFqiyzlazsejeP0+l09/qIEYi47QFguESMtLtiuDC643SvuiCZD54kbGVTcjmO45vju+Ye2HeRInmgwK5e5lnLZKZg5n7o9xJMTSSKJDMvVWvVdldN1dmolxRjDN04jiKBAFdTczrfFyLE1GRKKoMpCEU2qS4gEgE5Ie5YSWPqJYSstbq5LTHEEEOe82madmHYbjfLshRaLHDfpf1+09Nmly5+4x/99nKYMQMR2KHbgiMjdlfby1/9tf/g93/7h4P3icPp9kQi0OTOcHFldzJMWoDi7DWQRYlJAoK3SNWpYIMgfnj18MUffPEv/48/xIyPPn3Wd/3x1QNP1TJ5BkwYHJjdbT5NSBw3AeT5Lj/9lRtP9u7eNldRktecyykzsxZQIBaRIDHEEASBhMhdoguMtZhVp0QiHBDIiFS8mCvmUz5HRO36WisggT6gEK4NTHhEgYnQJD7fB29ndNZWL8rV03ItUPq5gchpNaRe6/x4bI16H+H9ooNaNdl/IdwEWoWDzrP1Q6uEr43wPej8Z0MWX0O4HHwmRfzMr/7dHL98Bta/y9H/zPF4S34eSPqZ1/zMu/4Nx/wzn/uIJf0bwlh/xru+/gw5gMbZe/zt4wtE5PFlZmbVW0lkxZPpMYchOou5A3BzhQ79hmoxuJs9bkDuxiRu5EVdlUAUeri7qTfaL0UiuKixCbNIABEbVK2qJuYVC3EmafupszCLkQuLsDRtuzO3eVUyXhMpMxMRnE18zR2mqtq+bROUpQFJXs3EqgcGNeM6a6XMdio/9x625cjgIfBKAjI/Iyw4U0noZ2ijq4KYqruLBAuFhFqDlXHr3xNuFCa4UUPgnfwsTdmGQYA3OJxhZgSD2Wpmz612VbW2T6x1AkMau5iZQAKqi4XWtklrwdPOt/trB6mfV8rGXzB3aG198sQQEQmBmGMkE2d1q2RWYWYfVgVaHUHbFTBQk3J+/O0ZLG6PVAuHyB266qCBSeDQs8lsU2cmAO9Vsgyma196I6o5AAaD3UDB3RRqIXAv6XJ3effmDgtYyBZnQ+RAheY5Z8ox9u5O7P22C0O4PdyHJFXBQpTClOdlnqZxbjVSLa6atUpILiytMlvYqigL3tx9OaShS72DzcHCsevAcDInCjESWzWTKHmx4+GBGLVQDOlwNw7hwpzdG0MG7/mJcJgDuk5Cdzu3ExJWMhYpizCD3EgsGCnIUUwXmyy7K3OAUUihzvXq+nrOSxNxg6LbRlMseSGFMyigsagmnW8Pt/ene4a/evvqk08+nfPpNB85xNSlgmpNFGCNbs+L2PqAtalL9DX21XuiDBr+0Jrq1/8mu1ktloQFfriVH/3BH19eXd5cPf3q5avlBK8Uh8Qs7pAojOZN6UECus5K3u32IabjYbncIHadKU1TrkV3u32QULJp5VytMbeZUbWUYiwhpM4VmRCilDyRYJnwtiwhvnx7+40Yn8QuwuppnJhj6kTCACV3rrmY2m7Ydv0AQpBAgKrWWkDedRHspS5BOaVE5CGxeh5Ph1rrZrv/7ve+89lnn//O7/1gGUvsGmVA1Mwd3JwfzhB0iNx6ZgCnlWD69XXGV6sAt/c/aXPtazvCOt+82lrqXq1G2+z/2e1jtQfBz22Oj7Wfxv36hRW9xzW0gVxrpUSI1snc6GCsVUHaspumJiYqXq2SobVLP/pmnCM8IlnJXW7nxYoIJGA00h/MvTo5hBDOivKtpYIRSIQlSlAzW4B5pXQi+zIvy1IW6jeh82F1hKxThodIPMR0eXE5hOH+9jYWOsy3efbKLn2Yp6nryFHNUR0cMOy6zX5zcXPRb4eqS8754WGcTpmdtlESpXr05c7qA/AS3//sL9K8jNMU0d9cvLjYPgE5h4HiZn95QTFk8tcPb2/v7nTJvfDpdJzHSUvhfXe8v6XthrtATFVLKblWUqOilrypOHOQgMBq1RwhRE/GZFE6CSEEW0gh1A2BXIV9qse3dy+3w+Zb33l+edWFP9HjNKU+wXE8zJ30zz/69Nuf/YUf/OCPujgsOi1zhs/LBO5BAX2KQx+ZkU95OsxWUcZ60V/ZJHnOb3769vD2+PYPf1AJCMY90UDeaQ1Zw5JEHLTf9/0Qr652w54Xu08Sc8n3707Tg5/exeDJrUlqVpgFCSqojCAEt5KXxo0e+ssQUq2+LEUQ3KPWTR+zV6qlOIyJpbm2Q02avVlVc9UyzhluEHCHbkAaKHakbts9bp6kiwsBT2qsWkuhaZrmZXq4u18q76hH16Gy1+Iam7BMtnxxeXF3O97e3Y+nJcj/y92b9cqyJedhX0SstTKzqnbtvc/ZZ7jdzW6STTZJ0RoISYAsA7bfDBh69N/xT/CTf4gBPwjWgwHLDxYMSxBJm2Ozh9vddzjjHmrIzLVWRPhhZdXZ99zLoU1KApwP5+yhdlZm1hoivvji+wJh6IcUk5rWOc+vXn++vVxfXV6tBzGb7nYPdaIKrk6mUsY9REjUpfUMUdcNq9WKOe4eplqgitUgpk7wrhuGVQDNXUebNWmxWr2qETmRWYCLZHU1VeXizE6BgsTeq8GEzK0iT9Ws/savfTtJYOA4HeroyEJemMauT7Wwo+/6q657UtG/Ohz+/R/8+eev9t36OiUZS+Xkxes011znqhCRmBgEtbbTuhUdi5GDubEiiUAwqlWb3mkLEsztOKnkWooVNRYx1zyrMBG7s8cAidR1YbXquq4TSZ0wWR3LnMsYhtgPXcFKqocukZsqVfWS1YKn9Wqz2U4rmnY7ywVqDBJJTVyvTGPlqa3BpeSiGQGxC33fhxSYPERJJGOexqNKRK7VqmeqSTpmcmJTM/PGfqql1llRGzkdCBSESUjdvDqdtDxd3YuaM/pgh7I/FBRgwKc/ef3k2ZUCz7/3THnWcgjcDaLPr9bvP3t496pY7oNYFzq451ynYuzGMnYxONg7C4JS1Kzq0oPtQk3hQoiaB2TxE2EE1oxZFskOanHw4m8HAGjKgKcMBt7C4LPO9CkNbm3g7Ye+kHVVH7NRvkLF8uYNRISThfRHhy6JzJLyNLqxmpK7qzYGH8w9EonludDAUCVdEXrSWKbxuJ9mZwqoxlk1sAuUmefDhEPCKKKxlBI1dHEAJFczls2QCmGuWTNqBqMLHHLNrjRN+f52nEekND+5eNLHdeot2/F8xX2fYhIW1iY2JUyRO0mpS151movaAzMJs7MLswQhIjOd50ISYN5gTYVCiHux0uqZ2YBKquwMNzcVjzFJCAx2GCVwIHKqRa1WINBS+gSEWnXcyBXqWmebUR0RMQonmm0OXUirmLqe5/kwHmu11tBv2Yjh6jVXDkzSHOJhqrvDw937w9x6CGKQjgmOWUUGpgCjftWtNgAVHU3ZQudUBVVgAmNXj3Fgy3AKJElSjFHN9tMD1EpBOZbLl2kuxy71F/3FrY9wdNR3koKLdIO5qjoVuFlxN289RnCvwhGOrkvdk4BQL2+203HKc97VnY4KgZNzoNVmWG3WKXS11P39Tk2NPfaBGIp6YiYBgLkuTjJQXwzLTiwqLM2uj3NtN7OTGvo5gqpWH6NXS/nxhEct/7ZQ+RR/nfRuHoV0H8ArohMLEmd0+GtocutN+lq09pWrtZNYl5s/RioatrWk/2f2zJkS+ejgE22+zf5GQWg9Te3ezxya/wjH/w8ZWI/RK/8qj+lDxeDR139Xz/qjEfwV9KDxR37J4zE+9fVffT3xaO/V9LA+elk7SSNeMTM3UxJeUlJrdCQnaVpX7KqqVVebNRFJIDdeGs+UTs5RXtydSWgpKCg7zEkocpBIk40A3GEwEeYgAGqt3uItVzN1iBHABCag9SObVeLAqg5Vc3Vr8ngcY2hYki1GcmiaX161idW1ZNkcDiNm96a93sIKalwiJm8wnHmjiCrBF5M1dxL2U9ZkDtOKtr+0hyx0np+NIqFVzYyYQODILNKgbiZICCBSs9M+3kI3Y1dynN5wAYbquX0YeCzHv9TBsPRRd9KJ8MJbYgIRE98f751jw9r8A//utGC2b5qAdMPPFnFBByGXDK+AgwlRkiM0wX64GFuoquRVa9GmlEYnnGWBlGhhieGr0+3xnODW7EOO1nIFg4IDAAd5U5w3d2djppbUo1Xi1CkwcwBcuFFhHIByhrkAKaWI7vLicnf7AAC1uRqSF3igWcvU1TRwLmpqF/3lZn1xe7zjAAAuzsyHcTzs75kDw8k5z+pmNdmKRCLUVdWc0A+p317M+12es9uDO4GpG7owJ2JUK04+TzNHDjGm1EHNoGQ4Hmat0+7++CsvnpzFH6FQqi3SOxVDnJr+fXuajZLGxEIsyMcpdjFKhBIqo7QqkEBJawWB10LEWFF9XUEYhqEbOnSIHFqzZOP+OSEk8UCatc4ZXolZiEH8o5/8RanFHWlIBs81n/Czlmm4f7Dq5qoV5w5eNbZWM2p6bI2kCA4MgBbfnRbfcmBhArjmuf7wR3/ym9//rZfffdrFYbvZHMMowgzu+p60utfFNyeGMnup1dxfv37/i8++SILxONfKea651mnMw8BBpOu7ZHR3936e1UkBNXPhypzMqAt91ydyXw8Rnc7zcX+wN2/ed1149vx66HtH0XIU4RAimZjBy5xzLjGthjUzE9zVrGrVYq4GKzkfx1q1XlxsuA9Pnl69+vL9pz/7ydOnz57cPL95/uwf/qPf/cM/+8NXP3s/1bIeOi1WDQAxhMC2ICsEsEN9Aar81G38le3DfVnXAHz417HU+ZafEFo73SnO0RbLeGM6fUPZ5iOk7LxfLLP4LLj7td3Hlkxj2fKYidzJF/WrtuoQwbRZRC9CgUQw1lNM5ka2lDNbCAQHOZO0DalFc2ccl4iZyJjZ3Np6Bl/sKhaCGhGBmIJIzRWORGl0RW0MUh8u+7EcKWFzue6v0tr7SrVY3r2/36wvfHJ3VK7I81Tqw3gIMSpIgqROnl5edV0kpjEfD3lEJ2FFlfL9bjRTB2quedbIKXGY7vVhN5LZs81mF/ffufm1X/zoh57D1eaFkt6+P4xlur3b3e3uN5e7NHTr7S7nUnczV31yeREpXG+uy918/+4heJfnMtXS3GglxiGGoPT+7piL9e4hJBEupo5K4CDBWItVsO3HPTuJ+GrVpdjv7qbpUB6mtz/9VDebzfNn18+/vVldfvcXn392GOfbd9WhT589SX33808/DzKUOlvN82y1AoqYZOhTn7oYgtZc51JmDN0qYLW/Lcf3bx9uj2/evLu73x9vJ47ECZ7cQp0D0CFusQ7Wqz/Z3FzfXK5WqZbj29v3vaxv34y/+NmuHNFR1DkhQ6disxJ51wfqQmVUy7WqBO5TJ5HneWJhobjfZa0lhh4epqmCYmgIhFvWGQYIug1STynNqQsxpqehL27FDs6aOvSDp+TPn71IPW5ebC62fJj2+91ums3R392O01zmzMwcqPMSrHAAr1NwcOTCOq6H9XwseSoPDzszdGnV992wGgJbLvui4/1uTr1fb7eXz4Tl+njvt2+muzpOdQSDg6YITugG3Nxsu3WXVmmeD+9u36Y+sFQhgiFKl7oYAoGl62W9SaojU0oRRBCmUl29BqEgIYYuUMxTvr3bu7qr13JkjpHj0HUpUd8lcit5GvfjvC+Crg/URZ0mA2y7fbrqbyr6N692f/LHX/yf/9efvHk3DsN2jaQIxrlUKu7ZyMmXvsWii1BCoFqsZneDEIjBfNoDHFOdalXhwGwON/VqUCWW0PUdXDXnhcpLCG1pFKfgEuX1z2/NYW5Tzrnk9VPvhovNen0YldzNiIj7qClEIgkcLjYX5QbHecz31cGk6jXDAKKYOARRkmJLr/1q6G9e3oROpjIeDxPIIcQUewnzsXIgYdZih2k09iSJnRs30xwwI3BbzEMMMcWQxIGiFSCzAjcwS6QQVxGpl74OXdd1D7vb7PO8s7/40y/uDu9/5fv/+HJ9sav7Mj988eWP/9Hv/Na/ef2T+4c95llQ+7TpehGJItCKh+N95LoadLVOJjbXsWiFOxNLDPOc2dkNrmAjR2i136UQ3CJEWzaRVp9q1Q+iJvMHYnArOba0tHmTL1WGhn2BCN6CzlOdwx9vF0vQ0ZyFTuIkRItjyNePxvbyD/+1ZN/dobr4kpO7165bzTp5VUQkWd+9G7frp0etprv9IWcvsesQAFhgY9A0aZprmAJJQOWIuOo2IcTRR5G4H/fJ+kjB1eaxjsfJLdVaS67zNM8TkMEx1OqR0sX6KsvKVA0llzFP4ICYApGX6kULjjAKq9VgoPH+YdplNIWlpr5rTEZM5M6pSfpy0apgqqxwKqi1zrWaW+s6jaqubsScui7EWHOZD5N0zEKuMG3ipNWa6ChBUkwxGfn6chP6mK1wJfVKHfq+Dys+6E6p5jKbWykV5sSs6iXPmJ1XzC7TfjaC9LxOab1eRY+7fNzd7uFMzE7iIJ3mydef6QAAIABJREFUyq6eew4Tze/evPvkk2+R+u7L/X7OtTpbhQQmhzOZAPGkkybVobmY1eq+6oYQlFZ49uzZYTq+u39/++6BHGEDwKzWy4vNl6/esrkRsZAwL9b20lHEPM+ycaxhVKr7VKf9dF/VqLftzVoseLVpnHPNuWSeZPaspR7no1ULoJgSCKVRIBa5tVMBTW2J0Jfx+dGg/RA9faVd9nSYOtEZuDpNiJZBOXCuDNLXcKtH4dhXpsdXEa2PZ89CbaQT8+N0igUvs/MZP4SUQOs0ap8KHBTpTEE4wQ6n5t+P3+6juJBwqmW2h2HfiFL/Bzj+VgDWY2AIfwuq0d/V8Tj+pqZZDpxpMudrO1/h40vlE9n1r7j+xxH/45f5I92yBiF9dFUf/e1fexdfv8LzrX30q/OTf/zv45HULmzBelqSZK60WFoECSCoKeDEJCION1dmDl3IeTZTP210tZZTKOKq6nCOKSRhUNVaVWEKloWzBKbF228BZ9v716KtoiO8iE6d0nhqp9WKEATkxKQNCgeEAVpITwCaGJaZVVWomS1hHBOquppDjUU6dlVtrJaF2rUgR2c5mYUs0pA2F6NFXuWssbVYwoEXxad28WbW0rPmyqqmHIgYvrh2wRoVmxZ/w0XhDubmi5DLyaUCi8jfhwWjBZ1uLkJm7hUcqO/6mGL7UB2tLmPqjgKF4aSRRS7WWFyNBuFMZDg19xmI5EzvATOpS7tZqFuFura3BiEKJARncctWq6EpGCzlR1nW42XEtTF5ogF+GI04Zc520gqDgSP8hOwRg0ibea0IExbMz5UgzVUgoBkFEAQcUufFiFobElup4oQCg0dhcq6lAtCg7rj5/vP3796XatM0pj5dXGzm6VhLTiGCUGrVGRyQ+t7hZS7WBDt6YRFzbyJNnAIE9w9j40uJIHbBxVgzFh1Nc/h4PK6GtQp5webiCdzrnI+H23GEmU/TOB0nGDhGnXMMg8NrrRKDlgJvsCycGoJKDjT1V3AjiptXdnNSdncCmZIZcYSpc6Q6KS7x+S8+e3Lz5OmTaySshuH+dhdZgghzUKjV4orWe5VrWfZRMoeZGUWBn5StTnUYg5HBzU/ac+2zRGtx9HrqM2yvdfJm57v4F6h6IzESCGaekOZSLzbrV28O5ejDarvqLy4uru7v90JpuBo4SL/ZljIF8tR1Dj8eDu4253I4jD/72TtizHPlSERBONVqx+PoajFEd4zHsQn6SWgCU2ZeKXZBggTebi+6JKZZxIZBvvjidUp4+eLJZvN8c3Gxe38MwjFEQOapGhkIOeeieYhD0ZpSp2bjPM06d1339t2r1WrtXh8eHvq+JzYiur170/Xdw+725Sff/Y0ffO8Hv/nr7968HSaxubkFObG4wrwSCxNXq65Mbuy+lOnU0HwYiAhQszY7T5nGeStqD31ZMh5983Fs4YDwB0Ts/MLH+9fjjePRtnJGLx+dGfgAap02tCZ5xnoibbUF1cx1IV618KhJ1uPk9bOsh2RM0uQ8GsvMgebsd3oiy11Yk/E9S040zK/VP7DQAXyhxToRx5g0ap4nmCGwDhXJsDHvzIKhQiBapL63vMsx9GOdJ59EKie/2l5OViYf1TUELqhitBr67mLbabfLh8mOh/2eWWJI5KEUaBGuKOa7N5MYmPCd6/W/+C//q4v+SqgLjHmy43z8d3/w74/5+O7+3fvd6zSsnr14LlHc7Mlw+f1Pvlvn8uTmejN0h2n39vW7y/WTPWZYmetUtCaRNPQoHtLksJzNI2IIcLPqVT2wwY0ctRSwRYmSBEwxcSmBSGvmd4e39/Pbw/z2B7/13RffW2la397m46zjEZB8mN6/effmYXef5wqz6oGU1pvgWgMPHPoY0vFwl+KVQIVlPsrP7t/v7vd392OewIbNqnOigjyNBQJsAAIHrFfp8vpqs1nVMlcFeRnH3ev3d+++zO9fa9QwhK4cdSHsWjVXBofATlZUxxE3Ly8269U4zne7w1yUKY3HuRak6CF2T188V7VcJ7UMt57BjK6X1LvBLrcgsfWKXRzBN+ttTCRsHJzIf+3XnxN57EhCCWGotmPUWrQPtYzFKyS4TVnCmqvXo4XAKQ0hrXteu5fVqoNR5DrPapXmYw5ESGRqEKhjLodsFPvw5EVarzlEYq8PUvsEB9b90K39yc12c9FLJyY2l2meDyyOilJrF7lfJQo+zkfVKaROYgyxh7sEcdecZ8BTCu6oWuZiT66f7Xav37y+JePEvl77sA6rbkiJh44YyPOxTrmUUq2aQ5iRVbhjSev03PXi3Rv9V//rv/mjP/7JL17NzJyP037y1eXmYToS88IcKai5tnq8FiWAhd2oqYorQOzaSnIAgFzgjtBziNHdqxdTN4ckIYYubgQNafHQcYhEArBJlD//xWcCOFAqYFAZ15uuW3fTHGrJ7DSETQihCylAxuORCKmX1bqzUkspKlgKkcbSBQrkZKiAoV/Fy+tt6lNVHQ/T7f6BA8cUmJmDuMPKUgckYqpWSgXg1ZgkMTtDG+ceJBK7lEJKjiZKVKAwdQ7UdV2IHSvEvbqVuaS0mnbFgNt3h7fj7j9/v798sYl4+vruz6b93W9+97/5xSf3P/rz22mElnHWYCrrdXxx8+Ldu/fTVBSF2MBGYrELVbVmJUJM3XF/YAQyJgM7WQu/tIVh5uqwJXRz9wZYtbsDgcRa4Pah/gksuhTwpS39mzKRdnZ8Nfp7tF354y8//MnywhOlt0XCvlC4yZ3QtGLJ3N2teI4eSHjKAOHt24ef//TLJ0+fP8z7vu/D5O935WadduN+NTAFmqZpk4KBa86wglprDpq9ZFehzfYJ6H3LiYi8OTgRs7qrGRGnziojdklCgEuIASzm5sjR8XDYhxRqZKYQJOQpH4/Hepg7TiRhnqdpzFZarQoqhpkoUZe61KXRjhJDlOiz1aqwWSRo8FJqi9c5xNCRKhQV1VVi6ihIyCZ5mlg4hJAkFnEtpsU4oOti7EKTeGg27srubG4qEkLHIfLlenO3u5unSXrpQm91LHNl0BAHXsPEbLSaa3brHFitqaLrUknV1eHmBSQcU6qqmktFCZvgFe8Pt0+2m/WQ0mVYTShH6FETwbJrzSAuYyEOzFRKncYjRKQTFx4uVvuH/cXVarO9nHP+/ItPjeGE0MlR9/3q6le+/531ejPup93Dfj5MXlUNUHcjEaaO8lgw4FAP/qChD4dy2N3vY0gXzzZlLCtsd/c7jERC1co4ziXPJ7q4qJvDRYgXnTiBwqsTM0fSoqf6PM7lZl/mzIf4qUUup6jkbDQDfxSzfbWsv7SfnIa/LIkoLYLObh9mzIl8cKKzAH4yF2wa8YKlgdDMzZyF3U+uNwThk1LzEpXBT1yzMzPrPN9ZWNVM9RwEMnNrDVrCsVNegFOceb6Lj+CIcyH2XL/8pXChD5f16PBH73d+r78bAOvr9/CfEMZqx0ew0UdYG752hY8f9192zrNK+l/2do+RrPNn1v7kbwhg/RXv/jd5pOd3eQxgna9hOc+p9WeRvQXU1bTyogXe2BYsDLOqpobGWuJGm4aRnZ+Su7s62N0ABTXrATN45FCdHJDW10sMdvdGTqEm4QnTNs3ICexCpCA3q1plmZPwZp1ObtoMAw1YqkPn3W7hYhJRoEBqtHCQSJpi+pJutbs2d7f2gHxpEiS3pmRJJzrRwjJqEAsxkTA3ptXpGcJhOA0YN0dgJ19cU5ckb1EHaHzUpcVxMXw5oWd87swyYHE0dPOzPEGDmQIHdqICd8+lNCaduZELFnGbDysJObk5MRZiW7OHNQdcmFxpCTKa0j2REzdmkMGgMKrmSsQcYwhMTBJYl85GNJAOfwm8flponRzNRhWPljw/u6udcA4iyOPR62gWzfBFfp6EAHarqtYebAqhDUg311ryPLs7AlCh6kTWHGMhBMLQdUzkXo/HfeqS1myuLMTEqtooMa4Eg6vpBGaEFMQCCquVmmuppWSvterC5EOzhK61eM1q7uQcEGM0hRsRRZKwWV+669GPhjuDNx2iahUBRI5sFJuPm7GIltPn52fBVG4Yq6k1rYO2AcGlDTcyImeQkXutKkTu1q3w+tUXT55cXVytn20vSjEKgJlWcq+mUAdw0uMAoGCCqpKww8SjVYsh9fBpnlsfLwyLUZ6jzROctkJg6fGkpsq/TDJ2aGObEoGMGiMUhkqWDJ7JVo4Z797e7e/G6+ubMmsIUYSIqOayfXpZVMRtGAYJQd0YZGogGsfCDCcOIQLsQMll1NlbHdI9UCQiEQoBEtpKpxJAbOZOIHXquo7Zgvj+cP/2fXj9+u32cr1ep67vgrCwmKFV+ziguk55lhhqrUPTFDNTMxEx0xgDER3HwzRNZhQjdV2apuM07Q/7+2GdfuP7v/rll1/80R/9NFQNQ2BhgNRU1WJs5G24LQ3CS+TfrAOX/RRLaesDPPV4tjz64vTbZZo9fhXBzE/17DN61QTkP+wO58IPPmwW37AVnhtNlsWGTouPN1ncRwtB6z19nKucFurlFEuUdlppHTDW5vlEZIt5EBh80g6D1VYzcGp1BULrSzGA2FnQxAmJnDmwiUYtsZK6dCGnEQFTnN6N70LhWisZ++z6DrsyDmLIMLdhi7Al2UqI0klXtZr551+86wJunl5ePr2KfQwIbhZZQCIe3FKUSF2apimPWRSR0DN+5eZb//yf/DPxsOovHvbTz7/47M3dmz/+sz/NbhTEuD+O+fMv34zzLEz23L719GUCxRC7obvaPnlz/75bi9ejlbHMbnNpS3gInFJ0JnPWAjDMGSbmqqpWHQ4Sj6lVplS9FaqMOyXSJIiCh3k/+8NFJzef9N1mXWwaD7jovebdw+6wuxtB1K+6PgYmDuK1OocksVcSR5LQdymWorvdYdxNjrTdrkqn43EctUhgD5AIHzBc83CVrp4P66vUd3Gcj9N8qL5+fn1R0nB79+buFloQPLKkPN6llISc2L1Ca2ZnjhTgwxbb7QZEx+N0d7A0z8yzKdxQs2re/Wd/7x8cjsf9w93DfpqqckTscHGpwyoIY3MR7x+mt7v762tcbfHy5cvLq82wSqtuSCleXT6Z5jwe9/vDu3l3uL07GHBxhe2ACPQJKV30/cX+OM670nG62m6HYWPu1fWHP/2RcFj1fQo8Hst+NxedVEMEsSA2LULUOT9YlEEuu3W8LILapw4BXZ7mruvWF+n58+sQ6zgfDvt5no9mM1hT38oNLKKO2SgTFxBXnaYSSS24ADTPSkQiWCq1VuiJzLns9hWK7YDrq3ixXptqLhA2hpUy5zKaAUJkbu7ri6dX22e7HXp5/npf/+CPf/qHf/Tn72+9Ophkzl51LBRjXDfVBmFF0FrhTswcQtMF5mqKFtcsZIZWHAQIMcIdwg3MdxZ2kNfqhlysloLqiqb3H1frjtnAFS0DUpCxwhoO5epWDNUTRSaBgQiJYkeRDKVkN3Dw1EscpBRlhyVgBopNmsFIKx7WSSikPoHp4f7hOI7HeQqc+m4gQsm5zBo6IRjc1czNyRYka/nfyc1dwc6tCKfFmGrTCBBi5+jVqZoVVyt5LuNYylS1WOjXZj6TS+Zjtc9+/ubiyc326uLhkNRyF/T5TfedZ+FnYy3F6jTWwuvuQjgKswRS1ZxHjoVYsUhKkDnBgAprG6SBDGxu6o00xc6qBneixaeoGfm0/HmpGZzW9PN+QYuYwEIDWZLSr1A9Hm1JtLSSc9tN2tJP9PWM9PEf2vmFS6jzoXCCJjkPGIGF1JuDKADc3u5/8enr3/n297qu74c0zHM3I6ZY92aVlO2Yj+0qjJyIIJAQxmPOd2WMx62k1WpdR62qQghRuj7FFOYyN3faFu46WVWFlVLMrdGKFYzNKgijzNm0MJIq+WxlX2fNXepDCME0Z+OGI1iw0eYpI7GvnCJYnMCsUrxwcBaYmckpW0ngXqzdK7lHp4TYxYvE93c5xsAiVLwSQ83JqWfpo3QJQDU9zMc6ZoW6KhzFsnHlgqcvrjerDSOEEGvRaJEcZppSJKJas7miWhAkC2Vf73VXujo95IeH9zgCsNj3627ITFWcApO1HknJOvXEYUXWo2Qg+qQj1dmNKQ1eAnkTxWKEwF1I6849POx3eczPty+q4zjOGdhs05Fzt0oSIR1Lx//iv/tvX3326tMff/qzn/7i1eev53cZjjBwPhoiukvpr3oNdbVZ9ZtuPk4mdTZHBtTj6qrre2OSIDGGmLpxPx4f9iBSIiElIIhUc1Cb6G4t+2sMAD6N4Q9GhO7N3v6DQ84HAOs8cT4a7B8RqOj8An88bc5fL5yKRwFYw48+iM0tljmMcOI0YEmpPu45a6d2O533HMU1gsGiTHeyUHT3k8eZSJvr+PoJsYAh9gEG+Gqz1zme/BviHr/scT7p300L4deRrL8aCfoPcTwuMj8OxP+GuM8vi7v9ZfAQgFrrL3/5fwfH4zG0aI0T6QlP/cbXtx2rvd4cRMTS9h0D+AQOORETO5Obs5qioboE92qGalCtYGMmkYXLyk6sVM2cnaMQMVFL341oUWih09QXCQCatF1tKlcNZrbTBmiLv94JCjH3BUxsXJ5GtyBH33fZSjVzUyFhkYb/qp+cBwmQNiuZpe3KofXAmHmj9Swep0vbDjUG15l/rWZu1gpXyybe9jV24mXhY4cxCFBaUrnlWPLUBWNummFQXVBuM6hDwcQMuHkXu83FRohLLjmXUmue5iZkJkGCSDU9n96pQUTOWMxJFhMcIzUjcmi7byKGG9QAbvqa1CBCIwMqHGAVkFDiEPpemPk4TwYn9gUWIztlpB/AzA/lihOYBffT0g+cYPvza3BeFR3NHNjZ3JzYyZmdYdQoFW0AKKEFwMSUa5lyjkPngVYX6+nhaNUzeReCB2Y2BHhxKsiHmRhTfMg5py72XQdYnvJ8nDHDE8qxaK0o4EhSQz2qoU55rlor4FzmsYg2zBIVMNdaTd2LggVdzyGQkIjEEBLAzFEVqq7qQaBmY54KzRiA2UCgRUz1xMU7byKnuui5UNJk3oxUSJgIxNZkKsCE4NA8V6reXXCueP/69fTdb19cb7/zrW/98M9+3Als4UASkaQYja3WAveml9pmTRSW2Nei81i215ddP2i+LTZ+GKtEcHyoopziWLBTc9WEnBceoqi5cdOaWYC6G3Mg4zK5VdzdH+H4kz/94erJ8M/+i3/6P//L/+nJ9bNSp/kwZi/fWX3bvOsDXVxuugAJ4k4SQ0qxX4lTSilJDOZA5nGc5+nYTCPMsF25SGRGNwjIa3EnV0wtwdNaEoXnN0+GYYhszPlwOHz+5avLq3WXnm+GCyYvaqUUuEsMFCjnepiORm7wzjruJHXJ5lyJtpvLIfUg11LevX6z2VxuNlfxSX9/e8jz/KMf/fA73/n+7/3e73Zd+L//7U9rzFycSay6uzfeW1s/WtPlSXvgw6RoqA77SRiuJSTfvIx/9YuvBQytTHD+eUslvr5lf/3E3/x+59f7+Q3P7Cc6GWj4Kbihj87DJ3mVVpfgpRFlMak9+YNDOEgbZ75Ypjq8lCqRhIhZSKj5jjtT9QoiEYkphhTaAuFKWoPV5OqWLDyNPLBV2097KYjW1eNso+MAHDDX0iEGhDzNh73xIffP15snG5YA9WwHzKYH7PngHbRTI5+Ox3myPINKEO2oiI9ap7qidLzP//Dv/fY//6f/5Pd+9+9/8eWnuyn/8Mef/uv/43/74v3dcUK3jr/+g2c3L69zmV6//8LmGqXbHfc/++zn33n6rNivXG+vn87Tm/uHA+fJKagzlFBLNpqckxB1JHDiWou5GkGVvKCqa1U3iilIbIqBYCI4D5vYrwe4z/MxCqUubK6HgjFjN2z9B7/zzGoyTXdvjsdRneDKXRIY9V26vrx0RxnLmA8l16sn11rtcJjfvH2/PxxxJMAhBASCeTQMoVvH9WboLmTzZBguw8WT5Jxn3d/fPpiXq8s1cZxHfrhHnSl4ZAvzWPsuheBOJhHFESNRqnHTbbrLm2fPAOwe9mOdYlwAkbRmYcpV5wlf3v44CMcNnqwjh3BxkYYh9YmrlRDo13/1e09vrreX204oBO0iV83TfKxz0dlDGXrtVsPVd65/NXZsNma7B48hhcMxv351e7877o95E7i/7KuiTO8+f/2T29vjbkJaIcQhxfUQV/1FGmLKuuo65qBVCycDCgNmlnN1vxfv05Befnv1rW9tIw+7hz05XWw3l9fbzz///PZhd7u/cwIzNmvarIcUk1Vzg3sJol0f+hWKzff7wqa9MTOm7EzOoqpmWpmkzLnMtczoBSliverWQ5fzXKsTKrmWeZqOO0IK3IckXth15b4NcfXp2+l//9d/+L/8y99/fWeph4HVxYWr+tuH3dPrSyJPAjUtZYZOVR3wFFMIoVZ3I2UEpsCAs7WaHECE9XqTc0aTknBzLBbVtRYChyQeyWGb7WpYpa4nR1WtRetxHn1CVQMDEWAEBChFD6m/rLCHh/08Ze+C9E3TOpvD3WIvYfbf/JVvCZgdZc7TOOZpzjOqUd8PRGJmh3msRedpNqPURapcq5XsakbKH4ioDmv1R2oSAF7I3Myrm3sgdrVJ52maY5DQRVSHexMjqFQpGlctc6ZKbFx3h3R5QYE0T4j44R//ol/ZD/7Bzc3Fr756/Rcl3718mX7nN7/36tWPbEQ9ZCTMx8hsDI4cPOvx/uG4ByUkiVAgq1ZMo6NIg6OorZzN4FkXLgaUaSkYAOBT1ObkJETlmzaY1qF9Tuta0UG+oaayVDDO25m29J/5nHv/tRnWsjWcULOW13u7G3cSJzJXBwTF37y+//3f/8N//F//9mZYXeTVqPmanAKlEOa5Sp1R9s5uUj0ASgjYXG3343H+bDqmfSn05Obi9s19ruCIYRvX246ExkwGzQojcADEpGfNmue5lAbZmlHZroKZlqkcDoBmGDARjgsBmRIHSyQkHFkY1eYy57FkKojYfK8DGZg4sTC7wBjUOgPVHe5szsWDUx8is0SxCAnSDWlD2tBKZRbjWkHCEiLHFIdh6OKYp/1h54FCiNXN2VebtLlcdX3385+9IoNnYAIqwiZcXV5vt5uu61qHakqJCN2qT10Eakrh+uqyj/38u/aLn7853s/3t7s3b77cv3qAgtaIsTAFYWGGuVNHT1+s7alRSdPeHl6N9Tivh4u9Vi9OBI5iwUzncc5Ycb8Kn3z/ZnO1eXf77s3Dq+5CwhBFs/SBILvjTs3+h//+f2yjCgOut9uX3/k2DHdvb4uVuJbrl9e8wqjj/eH+s9tMhiGF1MW+Xz15+eSP/u2fcMEiI9wCWsOSo4JMndyr1mZ02gZtK8cSnXhabVTiHAwvVs9NvsBPhbmvjeOvTQ48isFO/zuaQ9ejN1hyuNMLHs2Xj+fOKWb8Rojoq+BRI2k1TAogNA8xYnqsOGSPGPcnWpYvnmFfg+S+9pOvfHOCvz8c33SNv/xB9NEXf8caWP8fkKD/EMdjRLDlXX81oPaYr/RXv+z8wbQ/+br33zf+1d/ydv7mx0f4HfAh7Vx+2MakObgts+oOc3t8hoYJuZmzNbYxyBoJCW5Wm7JRCyKpmcUBBgakUYwNDitBK0zN2awiBBC3lvhWUHc/ocgCsBCDzU9pG0e3ak1kUtqj5sfASNsimdjdjcy9aSu5mqchQKsbKQgwloA2M9EWiUU6qn3gTZce1Bjxbl6W+czkCxHTHUthf+HfqS5Iw4kkeerNpNYV6AzmD1DE2XL0TI+obfbRouPenrm5myrUycCtV44ChLvYBQ8wYjXPBRVBQ+NyC4JA2PN5zNIiEA80k9RzJrxUv4wpgBfmhBO5V4IsTl/mVf1MpYHA2JQVRKmLoUvRq8NJGOSIH/LqE7nqQyZ9WgM/4Fbw0/aAJlL+YZaZQ4hPP1miFzIQGGCoN2wPS0LsU84SROAGzDU7wDEIHJ2AKxzZq1VVcwDzYfRqJRcmHB4O3aoTMDULSlXMhgJHNZA36SR35WrZq9dZ1QncrPQcQaiR41xdDbVRA9sqryAXUBCOpjQdJyIrdT7uR1VcbtcPh10f3k8lrzpMo4G4GeQ180gwN62QRzBD03uwtn+puVAL98XZydhOJU6DW1W4bcNAxCWPx/3D9dOLq+3GtImnhBC7yCtXqdlyLlWtPV9iB9zMtGqgqKVqcWwphY79RJ1rVgtNqNJ0kb44tWM0R4TGfVx2UmKQa0O8qE3T1njGDKpV3Z0qccKnrz7/1mcvtxfXKfSX28t373V/uC3Ix+MxREGMy1JCTA4W6fvu4qKrHtR9GqdxnPM016pEQcRNtRpUi6MJ8EtgrtXUaco2TzUEBKJa63EcU1xzDBf9Vuv08HD/6vWbYQhX3/5EwGbFrIApBDHwXOohT5VV3eIcUoocOFoXcr6+fhoj55zhvNsfmOPl5U3f9fe3h2ma3ry5226vnzx9/oPf+g1c4pKH29sxMgjyGMFtBE2cKNGPNxc8WuywMNY/3kc+2nH+2n2mjbX2XtbIwm7nEK3V5M+n/Zts4A2zbkFP412cQdcl68MjFQm0Sjx/AL6wFBIWrmgjqC6DikHkRgszXgkwocBA4MVc19wdpieBNrTR7MbEZppLKVaNqzuqVaHGnFQAm34rGg77Q93PVOAVUjmGLgU5Hq1MMxzaTbxO26uLzbB5d/facsmHeb8/aqzxJvUXqY8D1crF1cSLWGbLhskrHAf8zq//5t//7d+2kvd53M2HN3f3X7y/q46blxcF9TDl1VSmedbqwtHUxzx/+fbNENOb27vNek0cu/7i1dvPR9OqLN6RlWkaZ51c8lTn1PUwzMVA7oR5tKquUkydCW5BzZg5dX1PiahjC8LJ3e8fblOk5y+ut5fr16++mPP+6snmyfMbRppH7xKnHrdv9sf9XPJhGqHcOrziMU/3+7tc7MX26d3t4e372/1hSn2ec8EpAAAgAElEQVTkTZjmjKzgwn0/rKhbx9V2GDYpDhLXhFhG3TFUdRIpQ0rPnz897vKrL+/nIwLHEFaY2dRWm1jKUW3ihHXHLKmG2q/o6bOrT7798qd/8en9w8EZF9ddKRWkwzqEQEnRF5U4DX1KKTACE1LHF8Pw7Obm6ZOnNzfPt5ttKXU8HG8Pe9hMpLkcx+Nxnmar+Def/UQQNxcXn7x8/uLF0/Vmna1km9brZOh6D4i5G+phOh7nyeuU5xF5WidsL+TNvVadqEI6Tt0qbnqDhUSKPE0cJBp5IIKRqY51Zi99GFLHQ4pDEgldqc7Bq9c3b1/NBTnDCTGh69N6syYQRRKmWkutGiOG1bDedOUwuhGrROKqDGjvrGp5LkyzqcYoV5dxiD70orUeDg/znF1zv45uVTWXqlFUBKmL3bAdhqeKzc361/7Vv/uDP/iDn9/tc5AIJ4S2G3PqJFicxxJFQpRAZKyBgqLAISIiYganysRBJEoQkeaRTc0Ji+BwrVpqdTMWCZElsFPoUkp915QGJAB0UntvcaszDGjlohRDpBQSKTw7CaPS8d30sDumMOeLrmm1N53QaprdHg67GEMKgTuwN0F/Io+F1LTmXMhYJKSus+q1WDketSqIRaRqPRXjTnHcsm5hwVjUYWZszgZYLcVMvUsSpOZCQuxk7q4qgUPgft2ZsprsDmU1XJjrIeeri837L/f/z+//+OnN9Sff/dbYTfvd68366uXL9cUA3aMSgoQ6532d2zblsyEDBK9AVwNFQqxqtShK05yCt+KXwW3R2gGYXHGqE/ipir3EwW0tfcyadT9vLMuu/pVd46P95RsoWWerJPzllIITx3iJIthb8fiU2S/pXMOzzBohWwKAsp8//8kIZwksgpjoYrs6Vk99yvuqczXo8xc3exrfjQ81AwEXl6v38zwe5lxw6OeXz7a7naEgDEgDSw+QO1clM4YkBJaUQr+KJdZDNtfaejLJLc9TSiEgdNC5OEagLHfRdjQRCSwMMbOstYmhmRpGL6V44MBMgUDcHCM5slBgJ621Zh3niVNM65hidPO55FJmhkgSzVmrujtHSutAGhL34EApcCeCQDNrmbXiVBTyQIhMKyCP0Bkdx7TuLq+vnl7dbC8285jv727f3+3m6ThNU0xDTMFsjim+eHFz8/RGOL28/uR9ua/7egjDoY9TLYExPxxKEekAErCnPnik6h64BpAfKibsj29BgiBgdodjRnAwXjx78fI3Xlw/v/rpZz9+d/921a3DlkOX5jmLhDrr7uH+bX6//iSWUetoXmm3m+bpbQwyXKxurtZpEyuXSUcDQkrbKHAyNTMcj8d8yJECMYG1JcHSunxThILMWa2W6gptanZNfRfWRDkboclPxCWcNRK+IfT6kNG0L/ib0B366rctCXwcTi1fPBIy/pBenZur8PFZznPqEbzzMfWpdfWdL894keJp2MX5PI9xDPelZRJfm9qP6Dv++CcfXc9Hz+RveXwjkPK3BbDOd/KNbLH/JDDWh9z4pB3Yvv0rgKQlIv5lzt/Qq7Ny1tffDl99OP/RVM3w1RToq+LxRGcrXGu/NWAxT2mT0NTMlRZZ3QVjptYNRoAQYiMaucGJwYGVlpY3sDubOlwdyl68ub6rqFcndmq6V0wUWitf80aDLPgGsQtBBVydYQ4ilib+TLBFoxinvKfdIweoNogDcJi2fsCmWtXqNmRnbtDyiTEzsSyGeace40a/BAk3uJpIVA2P+nmxSOz4+WTt50pOws6+jCPyhbS5SD2dBTMX6uZpRC6fCjN7i38cjW8cKQR0RALzw/2h5mratPaJbGErVCvVC0c5E9XauvFNA9lbEQvcOuycSUBk1PSdmZxMjcygDZuDO6y0or6xEASxj+rqcGJmkXnO5xt4RKA9rWgnOuqiKsgNcTy/9ERYXaJAaoaLi8Ant7+Amyns5EcmDaucj8qpxgUarC5wg6nLECiRFvVsRR0KIhzu9joXFLBgPuYUQ5OjdziIosRKxbPbIiYNVMwHBbRx6ykIizAFEU4k1QpQmpjEwhkjuKEWy3OtXks2ITtOU9ac532dLARcXm5ff/HqgTrysF4N891ozRFqabJsH8CjrWD5uBYBoJMsowk5CUO8eXS2LlG02UuAWx8RBfvdbZ2errouMI0FUbhPQxc3bpK9uo5VskPNdWEwNiE5F6tw0zqVwJHB4KVUJcRErOofxqoDJ+QF3hg0bW1pXWEkzOcBzzihz8Rm+v9y9yY91ixJdtgxM3ePiDtl5je9oeq9mrqbre5mN0hJLYIgNW200UYL/QIB+ifaakFAK0ELaUFpoRYgQQNEQBQBgaI4qUn2wGZV1/CqXr3pG3K4Q0S4u5lp4XEz8w1VXRRbosTAhw+ZN++NGzeuu7n5sWPnNK8eEZqnfP367vrNzXvvfJMj1ezHY6aITz56OWw6222iiEXSqgIydYnSD91caDzMOU+nY9ZqIHQppChqlec5xGCmahYoxi6kjqvDpaiVGCI7T+M8zePtbS0lPX+6LsXeXN8xM3l97/nzPiZmYZIg4sJzrWMZj9NptnCcDzPNF7ut1coUmMN2szMvqhZCnKZcq+acCbHv+/E0juPp+ubleru+utr+G3/+169fn6bjT+a5ijwU7c71ldYQd55K7v4zRT2/Ynn93LK18Bu/uOYuGietW/ocylTLUtfBfbHHH534q97/q67F3JfeWnNy8ubjaudARF+6HD8zwNpFoX361tH4MJJgi7boIsmnMPeYuBVTUBvabUYOQgji7Ko651lJ1YOrTdNcZ20iYjDYaM1raN1tdusLzjDRuc5emu2pznXi1AXnATJmrXs9vD6GMGy7y08++HSggR2zWoVnmgHEyOIhEmsxOxWf2Itjtmz21lvx1379O++98/bt9ZuffvrRjz/+6Qcff3I7ot9AAxPFudbPXr2e55OwwbmUeWZ6U66fTlcffvxRYE4pxtS/eXN7Qq3iSm6Vp0nn4zQDJNhwIueSzUFGPk2mCnRNOx8lV4niYIlRpDcVUHSIufXDptbx7vaUSz6Ok0g4nQrhbrfZDetOTaasqetMuy72ZfZpmjSP1zfX+7n2W2ySFL49+bWv8yrCqTjXi8v1kFZENNt08byPvfSbLvbCwRWjIlO01HHHkWnbdfzkan18U9+8nu6u0Zsnsug8pBhjzTUXIAbEnmIvKrS6SJvLnsT24+H6cEuI3GxlgkrvkjywpoCruFp13bAa1sNms1pvN5ddN8CJPJ5e4tPf/+x0yKfTtL+7qXUCuZaspWhWGP/D7368YuzWV2+9KC9ejNvN2imb5BBr8Wpc1hdxfbHuZBAuQzcOfBCVWY4hyV5GJRYGk5qNebaitetDSOi7uN4Muc5NUx4uQTgQEXyaD/N45EslIXLMVW3Ep69yvyKJJAwJLiEyi1UT5q7vJFMpbuYSwmq1fnU3W9VQHIRcIff+8s04xrRP8e0Xl+6z13meD6XMqnU9dFe7Ta0nuDKDhSRySKGLW0V/OuB1fv0//vf/x6cvxxC3Dla42qxuIGeRoR/uXt5ajBadA1pftjS5QdV6b4VGALFIiDEyK7MyU0rxze2NllpbcUkRkksIkoScYhdDlKaSqaZQDZRCiMSBWBP328udzp46Xm16ESPRMubrU2ZwnvX25eF0LHOseazSEYRD4m7oqpMaPr3brwdshvXQJXTEFnnyqqQtP6kopYi5F4fBFFZcTEDsek4rz0UaR+tQbvVL19p0LgBWP6fQMGitpRRhCiEwkc/qWmohAmy2Bh4FSa6sqqqSZDufyh9/b/7ON6cXz99++9kvjePvrTa7J8/i195N9VhPe++75OrjOIaAUoCmz8MQQkdROCoRuRZVq0otEjdGhZ1rmUsEhntblH0RhjjnpWglJ5xzD19S4zMKhVYbWJDFP2GFaCEaDjAL872Vx1e9rim4njE2c5fzOuafOx8W9jKYISSirritWs1Uc8mlTKlf3UxznyTEBKck8d333roOd/Ox3tYTDMNu4Fc3WYsgQmFc4sq3gtWKOJn6ZHDnIgkdICTM3dAPEKslKyZjDRKEmVzcfEhd7GMnOnKdVIuV1rehVLO6OwlztVpKLVpSDLFPZlbKnKuRU4rCga1QmSZTZWMJIcZABe7q7hQ8JJEYSinTONmcYdhutlOe6lwChy7FEBmeogxMAuG5Lt0DRGAhZ2LxFKXr4qrrTnuI4WI9XF0+idLlU7376e3M0zzO+/3+dDwUmxpLUkLQkmE4fnx4ffWGJb7zZCyuFPD2k2dPVqvDYX/M4+vTm7nUsAaFSNG6Tb9a9SWX7TBsh+23vmGH10c/0R/+vR+Tq7UC/hrPXlzsnuzeef+d7dPtcd5/+PrDKnh61fMqEAXhkYy9eBmtjt5V8ZlQQAApvCJLRZySdYGiwuY6n+qplhr7KJFVPcZOiMe70WeHERm1anRKKUhkcENwmUjIjdSoiY82gyI/p69nZscj3s/CN19mzLIbXZRhHnDfR0P3nnfxVQP/LFTz8Bx3d7U2/7D0RwHUGPiERwqn9+d7BHGcy6Pn4zH68VAWfeS7YGeClZmL8D28fC5itmZKenxyP9N37h/HeUv++fn/RQzrF8dYft7x+ZTyT4GBRWfJri9IRP1zQa/u35o+J1v7OefBLzz5F7+tX0AZ6UvHl9Er/L97H74Mlz7+7Hj81dP536OrU7VW+yABMZk1DRK0TSoxCZjBBixiJYIQGezGCgXO/FczdCTnnYg1UJzUIOQwCMvZd0qc2Zl1EXJnIHIw9SY6j8BCgYTJTL36fV+Vk7fOE2ZJTVurgcdWq7qzCDeXdnNvHwhN+miBnMAM5gdj+kWkDnSPKXhTpQYzyX2soLMzAFHbeS4UPGJ4ZLCfg0TboLl/ebwJGox/tlcmgotIE40EuRBHCQFRPLh6nsv+cFj84AVCAoCczNyqQpGepEag+wIGf9aYwfk7bmFwkdVGY2O0YleT6TdiWzBDZiFCNbVcm/4D9yH1kYCsBewhRMznkHwP/z8Kry3tOW+KmzIY4VxxcG8qVws0unRHGS36B9SYtWRNwZ+bPD+bkXkFwQy1mrPDUKxkzQoNfQQkj1nd4AiEwHy825daURGiuGqdcuwSAaVUJzBIREz1Xm3IKll1MDhAYnBzLe5wjhRT59RsFyNHCpFApl5LLVq9TGVW7SQLhVIqSKqWmt0daLit6WbYXFxe3r6atZ5pbnCmeyYf6CzF/7kipS+PUGh2nQyysyT+8vWGgFJLl4zdj4e7OpfV0K1XMs2AuZZavZKTKTNxDEHhgAvY2oQvVWFEwVGm00wURALbYj3U5lKTgiWmxSeuGgzuMHda2mmXqdl4jefGBFtaAAwsrf5u0ndWKgynw/gHv/+Pv/2tX/rgwx+Mp1krYsTrNzdbG5LI0AXpIyFIYGLiEFJKzXZ0mnPOVWvbTyCl0HVdCLQehuPxMM+FuAaSGAK7GTjFtTt09lq45FpKrTo+vRrMdZr85vbuyeVwd7eX7QXHEEJiRzXXMp+m8TiP4vLq5tWxjLPO27jZxCHGtNmsxumgqsOwGsfJ3W9vb7tUt5snd3eHEOLpdLi7vX7+dPjL//pf+t2//4evPzn89NOXj9qeDc7UlEQ+V4R7vNX4k48vhPfH+c398Rh/v//hHiDFeVn8GSnWzzrOr16K5+1LNjI6o3D3W5z7DG7ZCMLQEGpqtWpQE/56BL5Rc6ZuhMflf6gzm5mqIYDNIVA24tDFaGzHaSwVERXcVa1zKYtUX4NinQVxNax2m90QBs1l6Id5yOM0pj4yYzrlaCGSEJIi56LlkG/jXagJmcydwQJWqB5x5Hm1kb7bxNAVzKVWUiFVL7bp01/+C3/pl3/pm2w2j4fv/+RHP/roJ9enN+tdTOvhbjoNQy9u82Gu5dR3UYsyIddSi1XXl29eR5Lnz5+vhk2ebTadWSEo2fJUTgUz0PVw4sCJUABorTm7G1Z9iIFrKXPWzW6l5nOuVsfTUa0KQUKIm+0wzePt7csQqOsYKNfXh/X61p7X3XZT6kn9TiL3q/T0KgWJ8xzfvL4ZtW4Ju4tuvd0ej+PuKV0+v6zqh8NpymW37S6udu60P2K4CBQMMWuEiVabiYr0IfaUgkRhCSDSoeuTbOt+fzT1VCUIYOalGygwXCBJh10X11EGqj6/evOyWw3b3UUuNWtV9tVmtb5kDnM3xKe7zZ956/1IIcYk1JlSPtW7/d31y+Nnn9x99NPXf/x7LzGfC0n39ik4V5eAU6FXev2DP7gGgNZv0gERcMQrfPP9qxfvPrl80vdb2j6JQ7+j3k/kxr5d0WwOZ4bWuR72h2nW1POwisMmxbBioFRuTdyRHKiqcy6zFXPXFAf35B7F6fUtnor3q7TZdiym6lMuAVy0CkvNdZ4zkdRac62H01RzNefBZJxrnwjELKGtaDkXU9usVzVbwSTcIDbq+rhK/fXpWgRdYgksgSQKx1Sm8NHHt//oH/zh3/n918+32364ULc5H82do8y1uHqX+pqVlb0aiYPP2uCwOc9EbI0UvyRdy/as+T87aDrlh3iw/G9ODrdas2oBXIRCCKmT1WqIkc3LPI/jOPXDUGDDKu22A1CmfKxTmec8T2U66Xg0VJjKaIpkEE99Ct0q9Wm19dv9nTpVWCWnQIgO9arVnAIFElKrmhW5BcPEzkEiDHmaKDzQJpqCeXPGYRfAVRd3P2u6YCLCrG5w11wkiYgQoWQupVYvVmEngxcnlnhxOszGkLQ6HZVSnPL8g3/y8smzi9/8rbdoCF2sFxfpV37p/buXH9++OQ2pK1M9ZhDBZwThkBikTM5KMDRvSJsVjkWntiXKBvdmw3Lf4tcSz2Wx8RZ56SGB9MfVdl92vAReyi9nsc6vXBju91wLIrXUjB/4xV+9mizLTyNeEfkDsPZA3HLnhTnepq0QsRtMzbRO43w4zr3I8Thv0xAlKWm12m/6zRN78u402zzdaRqSmrtTksTGpZyGTdhchBCdg031ROQUvV9T6gQegZj6aGaGUjmDidmZqfWHMDGLBKYkbMkEMufRDQW1lmoKDtwiTOxCIAFBwOhCldJ1cb1ZSdfNOSswz7OpMTsJBbCrSAhggTT9E6MA8ihgczWrzoiJQxIttZYq4jFFEJ0Op3EezQoxnNwIwhCmwByZn683Q1htN9sQusPt4bOffHq6m5EBBRSUMHQxkpRJqURx5Cnvc9nfvobix8dPwjN5+8XbV1fbvg/PX+x22tun9tn+RjNKqTbVQTcpgmBI3u0kXEjcRJrDe2+eoEgp2dwk8vN3nj158XS9W53y/u70iiOuViKDEzN5yKO6jXZUGz15nI8FSrAQEMhCLVSkTDQWLmts04oUpm6VbM5HPpFX8kCBpVW+UM3cm+6AULBqx+NRiBkUwc1m3QXOy7j/fA7W6JxLiZHB3DLfppN+r4OOe2LI4wp+m13nXx4P/AcQ6jzuFzzJ75Oxh6c9/P+FHO3RJD7/3tK4x3AVPo9n+SOalT9ML8CbbfTjidwq4+1jnxH8r4I47t/iC7P6MQKDf+bjIXd9dBl/agAWM4tIM7zDP1f0qh1fwNHcF4fyr7ywr7z7P/9oL7mnbn35tI8f+Tno45chp3+q4wvv8pV//eK7ExYyoXjkqK5txfV7rpaAOQSRajMtBnZCxMIMAjGrtxao0vhRAnfnarb07hpgSDFYcNXWB2RFiy+oBpjQ5I4I1qTRvRWSAQaDqFa1qo26w4EDxFqeYOfONQIBZhSCMDehK3c1NZ1qliYPFQREtdRmXEUMkQVvMjcwfOk68ZZymddFpp3BzOoON2Jq3SmPviZqEJZ5PQNeTCAP9zvRRdP6QQmeHgIYEy8pES9hBoAQg0ShcAiFjjtBZ9nLrHkqXGHN96VCoUQiRImFu9Ss6M/JxFLyahkIFucfbi3VtuQxYDFydiw3vCWaDf1r359EEQlgL0XhDkWulVG7VSLAqrq7cGzj66E9yOGLxjgatNJi34JsKWiRG6PPEREdvnh40EIrAmBO5gJyNZhKkCBRmNS0uFG0c/8qoCiljPMUQoghsMiYRwgg6GQQwzSOpoAiSDA4zLuUAOSpzGPhuPTua20KZiCDKwKxcARz1Wq5anTtbNdt2EkgzOhi7IdEgUst43ya82QKz7BqWitUBYEJpsgVx+M0DKuuS+v1WmdK3atSDA2MPStSn6Fkb0YAD4kclgnl0pAhcm6DymDqBgiIQwpSi4ZsGnUa94D1Q5BUQ4BqPc7TBI+8FoiQRO4MSgv7kNAMM00lBnPKZZZZYhKqwbh4A7BAkLZZJha4kdJShuXWTbAsm4vc28LWOoNYIIIbURI3VRMK8zzCUXL+/ve+92/923/5hz/83jieYEgpnkwdi/6dMHex67vUdwNL7GLnxGmsYSIJoWrJRzUtIXBIfR/79XaV5+l0KqYaQgmBQb5ad323nqayv97HJORwNxbEvlfKcdauS7vd1emUdytIihLAQNWisOq1ooL87rCfa+6GtL1a96sOZJvtFtBWlbq+uQHR/m4/pfLi7Xc++fTjZ89fFJuOx9vnT5/9+q//6ve++8NuCPClrLrE6XOF5WctlfcJw3J/3QB+yHjooWS3JFE4094+P8W++ICfhUVwRpnPf/hK9ubPPO7zqnPtspnFspPB3IxI2tXeXwLBG1/D0VrfCO2lupQQuH0wArTROQz2oIRYp2qsEFCFREhq7a2cUuewo40oMDEamEjg5SEKAlDp0O+GXR/7eZpO+6O7hV4AoDdEwghPNhe1Wo0cwnDLh3w9X8duyNdzmR29Y40YYIrppKvUaBiAknAglqLHQ81/7jf/7PNnz25evyKxP/juH3706lU1Hy5W0vWvP7lLfV/aly6plDJPdbsbzGzOM0k4TvP1/njx7Ol2s40xUbaai5HnYloY1UQQJQxhCDGV6hVGddIyu0M4ppBcUeY8DNvDcZxG3d+drt/MZSIJdHXxNMTOPQz9ZS7j/jCKlO1m/eLp8y7J9c1+PN5WzbsnmzIdZqPYr59erp699c7u2erTV4dS9XI3yICn8QKIBj6e5mkqTsQhE3izksn21YtnY3cRSDC3alnAApLQRYNN+bTa7LbbFWgfo4QUq/opj2M5bi4Re4wFx4pBbNitnevhuD8epnff+cawTm9e33386pVEXFxsLy4TSdhsu/ff/vpvfus3IwIo3F0fv/tPvv93/uY//PjDabrhfDIEwchddwGVPCnMvVZQBircUInCwJC2GXBU59mVKCfxULWUj+YfXt/99PtHh3W7+su//uL9b7/YXD657C65w6F8qqfDaTp42ySSCsOqTeOsOq+GGJLE0Keu0+LH4z7PE1Bi4K4LN9fjemUhWkyBk5xOSANCovX2kkkPh2thi+tVmWbXUnKeRgSxUnR/ON7up5xhmIxkyhpEuNWemFxRyziN+yEJEVLoLze7EMM0HgObo2o1oYjIwpEgTBR5nWv3/R988Pf+/j/ZDelwstVmS2LldKDIXddVtdM0a++MAOXqStWI3UVI3J1KVnULreO+KZS23t+qpZQlwS6AgCMLUTGNEpillLm6l6LVNQW+2F2uN8Ow6jfrAVz3+7v9frq7nu022ezqfVwZuR32t0G6rhuOdyVPBgUjRAStzZqlKJDQ7dbb1Wo4nu6YohnlqgTMc80ZXniecqHCxk3YkgIzgs1utVIUgFGaM0Vjr4KMmMhB7Bwg7rClFZvd4GTEEphbjcerFrUuJGEOYAPYKRBZsDqhqvUrOZ7mNPSp745vrtOFd8I/+eEn2/X6V779DlZSbApp+9a7T9PwiQbn5E2higIDxiwxdiESswFM3lx7rGneLQuIs3ljczA9mBDRUkM9VzJa4G9FzBau6UuFkJatOqzlfG2h54V5AmoK62dka+Fu3e/Siah1Lra/03np+sJqsojFujucDItAJD1e1ai1b7i6GYwgAchgq17HUU8n8FD3dzpsa6iiWY/1dswjgm2fr+7mftKjpzzVI8yJTVWneb+7Wm02A0hLmYsWYYlJhqEHYi1SCyRQ5JRLFw4o1Y3UNNcMAGka2fJ0nOtEbIOzcyda1R2ugMGqISANad33ea6n44mMPKHv0A9xs13FfpjynOusqLUaCzlrqVlZJQYnzzCxrFBJNKxSF9PNmxsVD0KxTxwkl3mcplpJhiQiBdnshMCUGtbmISAmCSmIhN/6jT/rmcbT9NlHLz/+8Wen27kxMRdd30JOcDO7U4oa1xFRJRoRTW79k6SKTz/49LMff3b5vPuXfu2Xnz1/kat/drjxGdPkqOiGSdaY6jQfjgVjgFstHYbv/Plv1GMrP1mtlQij7W9evlaqu6vt1+vVVKaxvLmM7/Vp82nFdMx20FDDqt/M5ZqdFpHchjBQ8YTAjKrHMVP03WYH8TdvrvO+Qvw0nQLCk82TuJaJylwmYQ7Mza+pdQQICYGIIeIgJ4PCmvYywQiyQFdELMQiRNRkos651zLSG3EHC63hIZm6H9f80G1ynxDxoynwubng/qihxR/93ZZtLxZm1lcna+YuC9n+K5TXAZib6tlziVtNuukgnZvEHl3Oebd9P5EXZhbOhqTL9X4J3/gC/PKncnwBxMBjmPHnvOAeoPnypdyrf90/4f4lf4rA2/93jsa+uT/uywK/yGu/EqK6V1AzszZ8Ukr3d1VVGyD45be4x1NFJITQfm7P90dNrT/vYho78DxYuWMXOvMnz4M4AEKNAnUeKto0gEiwWnUxJWKuqlmLqRETiKqpTbUrg2gwV7VaNRNTkBCaDAxLCFTNSs4WEGIQFvU65WpmTGCOMSVmrqWWUiQIiahWLRm15UCBhSUEMJ2NQlFqKdOU1is0IKRVkaRtE9VhJNQwLCNUmJMtLSxoT3YRIfZGq1q+LYdVs9ZUDYiERrMEsMiutL5LQqa5UayDBBY2NTOtVRciFEFCCP2G+DwAACAASURBVCKmC8JLDBJu8u/soZeUOLFymeu8H/NUdERD0yS0nsaHuWpmauoKOHhF7QlE7G5tyCxwiDuziJz1u5bvdYECQSiltJh4nrbBSJVAxA6FOwQU4IzQodsOoRcjn8pc5jp00bRZQ5oDDbpyvb9IPmcybco8ci4kFCsEYvZGi1tGr1W6j8pE5i4sJOBGUmoNSUR5PNU2GwToGSlJZAipawjh6cWleQngwdPp9vDZm9dm6HrmxOqmMBEIR4Bq1ZKVFEwghTsWhXviRZUoEITaWueoIagwhAIzO8hJ1a24kQCMzeWmX/e5zHmajqfyta892277+UY/fvWxdHhx+exwe/tbv/LbAP/Nv/53x3nCCVSWhY0X1hsWKINbyYycyAQWaoMZRKJIJA/ubnOtpXSrwb3keVzvttWq9HX3LDx5u/v2n/na07eeFPW/+p//b9su5iPPd4U8+JxRsN5ePX37uXs5HA+OPI3jNOUFMnCsd+vVeshVb+drSpFAVivUCCIgq+rqXpuIFhp3khWmqHC7L623FgtnaTUloJkgwWpreJREMRLEpp/iP/md/+iv/y9/7R//8R+c8uGz64yNrbb45tvvvv/Oi0FkHeOPf/STb3z9V1YX2+/+8Cf/w//0uxiw3ewcONze7Z5emuYucQxgqs+fXrrVWuY8ZwFdXF5uL65SWo+nPE/17u54/fp2GmcW6mKQYEwaou8uVleb9SW697/23rvf+Hq/6Q/z4eNXn91Neycvtapb3/VEOJ1OXvIQ4/Nnzy82O3a+vb29ff1ms9nsT8fj6ZS1cJCLy4sUUx/7FFZ5tt/4tX85hov/9X/+W3/1d35nvEWfgikzqJpHYdd6root0gcLHdAc3JYDcTPLla3ZQS46deYIRLpoLfCypJMRPyQTDaK0aur+aG4BgDf1RnxR5qApvocoRKRqDRazRtL0cyiTh3V/CZNE987S1EBodyYGOy9qoW0DiFLOyYe7uQtAxNK8Ns1KraZKQPBIoHZvTM/oewggBxsJRMCMEt0HhF5CEmfKVd0MbhB0qU+xi626QI7AkxajEldhvRu6Ianr4e447sdyLGKMgnIyGGhgYot99/T5MxA++/GnNdcoQvDi5oT1Ll29s0PAhx+9euv5i9tPRj0RF9Gp1N87/Kd/7T/+1W+9a/nuH/7u3/rRJx/cJvnpmzcff/rpzd3+lOc55zGbOdYr2m1WXWQtOeeZlVz9L/5rf+7pxe50OuXp7pvffr9Y/dEHH9weDt2wUrMf/+Sjm0PtNkirEFKUFD1IM+AkIYmL8UctuWg95VwVpyNu74AJCFj1SaKs16tf/dVf/r0/+Ltd15eShco7b+2ePn1+c3O9379ZreLFRXz6fGDK21232azmPN/c3LmvQtxVxTjm/SmPx3Ic5+NpnovNM6wtEAkcxaNKgiqmEQ48f05PLzdmdjgcL7bdZrMOQs+fvEi6/uiHN//df/PHuMWTi+cQvPnw5a/+9teIj9zV2IvExNJBWFVZbNWH6+ufbDer7bofUr8dNk+v3n1+9e5m9USQyLr/7K/8l4fb+bs/+RgvgRnowRGkpLnZrSY4u4GrintorjKAGppJxnmENQNgUPM2dwKzUahucEUicBuHwA5fe2voL/3f/w//vc8OH+/3d9M85jIe50P1qZhe340c8fzZJnXdnHOdRq06zT5OUEPXyaZPlvNuGy8uNqHrjvP8ar8fT0YWquq626Q0jIfj4e7WzYceTy6H9Vpi1JA0RS5mtdaSjRy7FZ5eplXHkS1FiYzV0PVdyuM0n6pATGcRe+ut5xe7zTznwPH6ei+hT12X+n4l649ey+/+7dN//d/+n4drHN8Mw/pqLBVJRUaJs5tbZcvBZ+1S52qqqt58eQ0ARZFIqgriEIKqtv1ZjIFZ8jTXWlMXcymtX55ZOHBDXJxgqgZ78eJF18VXn76+uzkg4RvvvXX15Or29vqjjz6dT+AV7AQEbJ+sLnfbzbAWo88+enX92a2OQKZAUU/GUeIQT2Vi0qdvP+k38dX1Z9lMFTAgIPTo+15M6j7XYrWq1YahwwuA1qEqAGBQ86ZyTo1kwdQgm1bq8zNp1WEgd3ai+xi5tOLZsqSfGejmrtbU/hROHJ2URDiQUgYhdNhsww3V/+K/+ndeHz5SvTrs449+ePf7/+jjn354vd8XNzndZD86pZ4pGul2JYHj8fY4H0YUMGBTS2wFTu7m6jCHces7WPi4vnhWsn+ufp8CezVVVWuyQUu128wdkFb0VQDkzmfR1aXyuOwdHvrAz/3inz/umQTL3skMDm7IWLundv8Sfrg2IhAUCibhoOYGQ9fD7/6Dv/Jv3ujHP/7k9vs//uQ04b33XlCh45vrKD0jbda7m9c3x/FmWHUs5Wvvf/2jj3+63xdVXL1Yv/udizkfmj+S1uoKN9ZCefZSoJnMOHI/bLbEVIrOUzG1wCHFGJz62AXIfMqH28PpMLaOzPE0EXkz9R42HQvnOatpij1AWq1SvXqWVuu0Wq1ZYil1zlldq9XqNSRJq86oub7HPDemX615JrNVn55ePb15fT0fcwo9Q25e342HCqdhvenXw/F0G6LUU86lrC9THnNIuNo+vbzaDDyMH+abT28++uQNTk3fAajwCUxNwVioyaap15Zn8DlvZ0AQ+0RCJc+uwAovnu6+8Z13PdHm+e5v/O9/m3aIq4DL+vzF0ydPL3KdiIzMjofT4fUY0AVKnST2YLmMp1E4pCGC8Y1vvf+9H3z36eXbm7T7+Puvf/S9D/2u8iwYGRNWaQCsWMk6uwMCBCCiu+ievH3FG5r0hLTYE91+MqNiF9ddil5ACKpea621mJkpwU1VH+yNQEwkEDiao6jbomau+bzpeowo+SPFh591EDw3wKmlXQ0Oa2J4aMhsI983KM2c4M2/yh2eJLVFydWaARkxtZ0sEzelUa+LMwZwT4Ro5cAv5WYOMyNATdvsizE2slEttWptD4pILbXtJRuY4I+kw8+hYBHSekTkb81S2rCRPxH2+UoY5B6veDTZl8/2uRM2aO8RnRP/VAysn88S+r9BYvr/3fH/BB73eLNBRPealws3R0RE5nn+ORdzXgUeQKufRTT7/BufV1kAcFOgNQVRGyJo3V0OoKlKNeJ02ww05kapuemnO9S9mi5YCFGIvU7GTQAeIGI3c2pKv+4wN+YmJ9BO37Rgzsi2VmUqCAKHcAgchFmJinkznHKn5YKJjJofM8wAllp02Za1YGMwApE6AW6L5HurM/HDfo4WzaVKYCJzoH3QFtQaHZ6W3/BojvF5lTZhcSyaMg1gMmu7fJx50O0WPIDiTCCIkUSQqZdcqUBnQwnBiZMR2NysuqK26iqWUEIMcYa5hpB8EVjTBZMmVtMl6QLaHb9n150R9HsA+1EMJF/UwZgdDKtLquUwhValAm36X9IKd81R+HMKC+ciwQP67cZol4zFyrVFwaXo540P1taTM5rm3jwGoETN8+cspsgkgd0ILmfDWINEdjU3rbWoVRCHYb3erHdlmktW6DhXZMQLLAT0VuSwZci7YdFyssb/YNCCIIi39nmQwR3qtbHynIlI+hAokgvIYWYhBFmtGKMQu0PV1eAFYI7d6jSPKfXDthv3ExgkRIazN8EXp+tC5zcDAtD04lsF1dxNScFeSiZ2CUnVOYgIN5fvUrNBt7stEuZS8gQ4kyFKdHDO9c1nrwE1MWI1M+LmTu1QqNaca64zFmPQJXF0dXVvrZ339qTuRtZ6P4HWV99ajttIu281cF6qqMTwRtFxqx6FsTZyEHMuNp4mVQSCO6rmeR5jTMYSg7gbzJNERIgjz5lioCir1Yo8xkhdxyEgpeQmBNdaXTXn+bQ/7m26vT1OYy3ZVT2ljplD4t1uWK1S11NMlIh0tDmX43FEWr7vqiXrXEplFu8iO0dmD+KM0/EEQxdSCOHqybOXLz9TV45hPaTQRQmklk9jyVR22yc3t29SqC/evfpXfvM3f+/3vnvz6dRvEwN1ylWoF6Fm6brMmTao4Y213txuvKVMxOqNpwqADRzDOb8iLKr/eBxhWhu0P+QDX1zEG/X9c+tFq3n7fe3vUfZ2H1G+dDTxQCwUMAeYF4InLRppTdmrWTjYci1yX+jTMxu02lJdBMicFwU99kVbywGCMznI0Np4Kpxd2KUqsbuBvZEKC6vWNuTMVY0qFQRzNxKvnp3dRLmnIXW99KRSi07jFFPqU8/Mq66vpYTIdURZVjdQhxQ7K+ZkX//aiyHtbvwIcw48+4T38c1vff12/+rNyx/nOuY8v9zP1/v9aZyrqrD0wyBRSy3uGMdiKg43J61tJ5kUrO7ZdH88rHebvu+mMrcoNwwr4xOCwVGzTfOsoOrGKQxDF1NHsFKmUtzBjAFqXmcqcAeD1GBZ0dPxeLq9VcYx9fj6WxerYV2yaWGvcTxZ1XEYiOMckpF4LTWXUnT00cZJp1xBIXRp1/frHRXV4zSpFiNzuEIvrra5zvOUux4xYjVEJ61aUkKIXDWXXG/3N1edbLbyK7/M158Z1RHE8RliFyVeIJRcTzkfYpwlUhDrU3KaViusV/7Ws/W622y6y6fbZ57lgw9++sH3P339yemTH540YztvTnFUUlJiC4RADoOTsruTgc3ZnYpxMwxujf4sDqNG714CPwStdAE4iYlDUImik2j1IkfcvfTThL/x1/721779/Nnzt+785qdv9sVySHEuJQmIoTVXAZEyW0uojGHu6lJMXjy9sjqVuYQurdZ9KuM4n6qaGRXToKYGVWHUENIwrNYr4VDcp6olRGHmIB7Y+w4xhhhICO6mro7o0NhxoBQpwYJZditlnq3q7EhxHeMKiJG2cw03b04/+uHrMoOQIJ2pwCvVqppdlYlIiTQ4Us0FrkuTYKM4kpMxlOEQEENABBjB3dxcfUkhXFjOlVfyRjhvHkBmRjZPM3xxcEfFYT+mricK282mH/T2ONKK+iHGPhWz0zxGRCcprfuples6YQqanbKlVR89+gzMEgVQMwcUyLEawYDKVJUqRBf15mWNgjtpW0rb/nYxiACo9XubnzUHqAlBuqMlMY+YEU4u5s0M5UGq+WyZvbwcXglEVR0QXpZ5zNLF+sEPbtZXq6o2Toenb63fHD9EkrAK0BRrqIIurvo0wCtTtWIOCAeSZtCkS8kAdL6ElvSeP4rjcwH/HOUbO6TlRA8UkntewjnaN6J4EwNa1o4lxJ+XmYfF4086zm/DjubGdH8iAIAC4u7LhYMWnY4lewO8hfdiKKWaKghgk8C87le1OAG11m7dzS7S+2a7Gra4LP16lxwhDWI6ms/uhUBRIjjCpZhlm2EukKagUuaJhIuaeim1TAYahdRT6AOxzjVPs2omTpxCJ8nd53GCAWKciNxtRkVmChyZQe+//x5I3ZHnqrnW06ywxd4qGDlJCCTmBjfLdXKttWRXn0seulgsK9VqlQndqkNItWDWuYw5JqZgtAJNOJaMgmEdd7tt3w062vWb/XQqwVDp3FKt51Fwn2y0qNcG+LKFcziIRYuSUZCEBFK/ebNfra/f+dZbfey/9Z13rue7sAuW6lTm29Odw8yqqWopGigGiSkFTiiWFRYIZFOZDfrq+o3EQOL7u8P1m2s/1iidBDE4E437KQibODMjGCUGo5rVKR/v9n3sJHIpxd0YtNslHa2c5nKYtPh2d6VqWs0q1JxboGiT1XEmH7nj3hi8qeQuKe79FDnvZ9idz+D1zxnVwBIG29yRlhkv/YTEUGtD+rx1UpwhbwKpKoHYqJW2F86jOQHcaInN39Mf5u89e/4rL+w+97vHg87w8eef/FXZHS32o/cf7AFXuj85EYnIY7Dpy6DE8vp/Smzri8d5c3H/WX5RAOvebu/nX82/2BjWL863+kWOx5Df/fdx357KZ/LMzwKwvnBJ/2zXRnBbJhGTMDMLpJmdeIuhi6ITgQgtDXGjqqquQWJrM6qqgHGKXeqOb/YciGgRi3TA4IYGFVA1JSISdtezQ6CfWWVYpOQrmkLK+RKXhj3g3rb9zCpiooXGSV51wWhanyCBCBTOlTI1Jnc0BYP7k1LbKWpZhI3PJoL3dDRvG3R3b2Dz2b7wrMFHEBZ1vae/aW00q7Na+f1kdvhim8UsTQ/UE6JmL1PRUa04ZWpPEQnkWmshUAhCTfbJCLBlV+guImre8DI6N/PeUyoexawHoff7sbP82qA0IiISYibhRVQdiupNoUZRc3EYIpwRWPzBuuIh7hHRuUPUP/fY+cf2aJAA90Unw6G+3Jm2c24IKRyEZUNOZEvJDk5GFEgCQ1gZbm61gs3MSDyXqZRSiQdOruqBCQQjcjgjpAgwGZuat9akxr2yZUTRgg0sgOW5u8tApnqGumDcmLeBOAQR8YBqilpiF1PsuF2xu5GRoChUNaVuzvNqWL/97ttvfnLLoRFlqG3U/QFWXMaItyKNn8n9Lbu+n+nkJLA6cUixi6aVI1XXXKxUPhxPl7O++87Vt9+7vPlkvrub1clyJRHiYMBhv4cgrRKbE3MMQkzmta2uZl7MQxeNnNyJqXGr/MwPIyZf3BJggJw7CJdZClpwwZbgYiEZMxoKxwSDkbqJOASq6Pohhr4oQgAT3FBymaYpuK5TJPa5nnobNtthWMMKrFQRIuYY3AytGSIGiTHChUBarFjRimmsd3fHl59en44mgtR3XZdiIGZZrdZXT7fdwO7FSs7H/d10SIdrWnlaJQ5Uaz6e9nDvUmcliIQoBEmq9e7u7ng4bYb1drPd7HafvXwZQuqihC5AaMpjmTKpCU2bze71q1dXl/L19979C3/xt2u1v/Xp74NMQt/3pF5N72UXPhe929hwc4Mtt5HavQa1jZA4i7Qheq812tKyJeG431d8Cb1azrbg3XS/Rbl/5kOgOJ/t5y8tRM1LdAku1jCq1l7a8DigJchm+MI7Leq+DjdzdSzzUhe3ahAxteFTvbY9lreyhMHN4eQGb4i9N/FCBqBuIKqqpnruOwAiqlVHVY0UlypOCDHEJBAWHVaDxKDZvVrVGrr49tfe+oQ/61Iy9Vwy2CUIjL04czjd7LtAsg15nN772pN/9d/9s+8+f/ZHNx98+MlPbm5e3RzvXt7u707j4XCcczYmCVFYPHjNeapKkBDYFVqQImIKDqtaTtPx1Rt68vxivRnmOs+5wnS9HkIvU53Hkqd5HgvmimroV1VCXCFqzadjmXMWkf3BREIKq90G01RzKXWqSjanvL/d1wpx7J70z58/6Tu+uzucjqdpLjai3OHttytDxzFXNa1WZs9ax7He7nPOiCn0PYdOQgggjqEyk5M5ubrutrtpPiUJpjUmrPohBEArCQcGvNQ6H/bXnXVdv/3Or751/fQ03pnVcPXkqQiT0zyWw1hmH1ebcduFqydDirWU8dnVi6vt1ddevHu5e5JP/uonp09//OrDP37zwx98+NOXb8rtMhTZqfkcV1UChCIRmbqbkpMZ2KHuxo1d4+7OzDj7YIKcsYxbtAKUuzuZOzGYpNnR6mj7MmHCH/2DH5VbLt8Om6fpGy9+6eb0ctSblKKMN8Vz7LjrqRRjgxNVcDLNlVgAWEzh9jiNo5qg361EmAXVYY5SiudpHqsZRMDiXR/6IRJbLVRVhSgESJIYaIih62MM5OpmFc1bmklCjAl9ZNM0j1ZKOdjB1GPoQ9h0cQC2nTz/3g8+/qN/9OqP/vDj410TN2bVCi1uGVTN0ISzqTortJbF/7PNaW7zUV3RtEOXghUtfJpz+Q+11pjiObZYq6j5YoHtEPdqLhZEQuBabH+7F5auT13suw53x7FLqe/6JImdyqze2gIIiICiWg0hatGaK9yYuMxVp1JOKunMDTcmIy9UYdToLhXLxlXPvkZuTdyrkaQCc8uslg7T5oy3wGxL3HY0TRycO3fOIdTul+9zUcGdbCmutkQQrQCoLRR5rZhOeRb8/u9+8Fu//R0KAp+++e23TwVdr1UT1WgJYy6mVcu0SCscs2VjYoqEagalc3WamdQWL5VzcXFZVdqCcEbnPh/228+PH/X7RaSVK5iI7EFi+v7/h9hO+JmrxsNuZbkRj+vx9xhbe6CVO85Aw5Ka+3lFMhCqZmLEKKmDBKQuRAtKZZpuTes0lvW2jzGkLuwuNuaFxbeX25RS1Wx+cFVXI0+BO6YOKlmnMnstVQjuVGzMdeLAFAKROddaa6m+TptKWmrNJeda4Bq9BLPG0Q+BnD1EiknMmYDVar1arbo0pBQZrEWnMZ+O8zRNptWZwGSGYhZYRUNVnadSs5vWWrNlB2AC4ZiiWaFpnr1kJpHIHGQaSy1z7PtSa5fi0Heu6tGvdpfrfq1Tff3pzauPX2Gmms/olcF1SdmXpMCbvTwYfr/BaQBsYC61khEHYaJaqp785Ue33IVJy2/82m98cvfxnd4c9TT6aRpHh+e5lKwCQDlr0dlPOkFBre3VkUtRLW+ur4d15+yHw2F/t0cB9wRHzrmnbsGOwOxifi4pByBwdYsxhYHzaR7HTIbL1U7Nyqh30xiJSylVzVRrrWfYvVWvl1kLoPGhFrriUkk/V7hbknJWEaVGyDyrP7TjK0GPZbYtbTpgX2bEOd3ic070CIU6Hw3AEggIZ4cn1FrdHxLtZZI9JqG4E50LAF++GICZ743m7nGG+4v/BdGD+8/7GKh6YCt8/pm/yAm/8EK/vyGPNpHLTWt7/1ZQbxsk+C8KYD2+xJ+Dlfysr/NfjONPEb36E4/zqklfeT8fD6N2/EyDj1/sIIcT2MHEgYKIcJB5bvuJ2iw3wQ5mAgUREgYxrJKRcCARotbqYeTMELgZjHlhzsDgaL1t5Kb8f5H3Zs2WJMeZ2OfuEZl5zrlrVfWC7iY2Do3kcNPQNCOZSTLRxJFpnvUuM9m8jH6fHqRH2dBsjCOS4AaAC9AAgQbQSy13O0tmRoS76yEizz1VXQOBpEwmzWR3Vd26dW6ePJkRvnzu/n21kZiJDHV4coGS2N1kGYr0lrsVs9oEUriOHFOtlJpbIx53YWKGO4Nr5IBltr+2V1Ui6joZxw73NtJGS8PZ4oVrur1YloV+pd309oqq5UinG4KYsPR+nfhmUNODWV4Kb3dZSKg5jsCdW7LZ8lg8ga2yGDgCOxwKEYmhB2BVO/ckcGBQWVZBvcwKep5aWDOrYRYtqBUWQ0AtU6blHjA5cy1UgB1S15XDNbnXrDIICdUqbA0+qaaO9WTLIFy7niOHIbX3daB2q8GcADvBIR9LCq2npzoarVfYbKULURUHJJCX2owFil0MgbsQVTPcbu5f5VyyFwAsFLuANfr12tQ9u2txY2gFScG+QADkhPp5H7NuX4CsCnWh1Z7dyKEKY7jnlAoFihwlsEhKKUZy0W4AzSCioV+BPIT44Ucf/tW//1tUrHgRtm1yQacLjdwcIGeQ4fFlFR6qvBwo7jAE8uTqqlao2JT4Ybsf9yMh/No/+dUf6Kd6e7OdRmR3mJNREJIQAtxdzUIQFwaZCCsgUTgIG5MwwcicmUwIgBeFekMVWm9eK4NWmQRvz62q0vmypY7/VQXMuh/MHVocQCplc3F5eXV9P91Et0mSMMy8lJwJatlJx2m70fXV1dk7T7r9jg6zhaCmGZhVE9y70DOttaq3GAOBQEwdvDNNeUbZowhyntNcuiFwIHWbcioAsQUyJT/k8dXuTs7k6dmTftWLUElT7CJB53FnHM7OL2LXjdN8v73L03aeEkhiP6w2GzBJIBLKmqd5TuMYhY39YXcnni8ungxD/MY3fun29v4P/+I7030Jg4ZInlC0orSPdsZbtkDu0ArZNMpzwrICSFALpdayxIZj+Yksc12y9IhhPRZLsEQ+x/jjuPxOo5PTL36+b2Gvje2tfMloTO3NjtY39IpO2vHvXtWmDarGILcjzN62nFemwCbyTtCGjdbtaQYzkBKUjFpe41iCRSd3t2JaFGrkVGccfUIhdTh3wpEB95r4uxfT0HVONOZDmqZZ4/nZ+bDuz5+cX11ewOju7m6ap67rYohFy7yd717cD730HZFPv/PP/rP/6X/+H794+OFo96MdXjy8ymT7/T5nLblMU8kGDiXGKB2DCO5Ewsxq5qT9Ct3QGXIueZpHf5iZf3m17tdpUDsUtdU6iknaW5lSzsgJc4ECUd2M3DgnP+zLNGkIOo8425yt1xsfeCf7m5u7qto57vf3t/T0Igz98OFHz9brPo377f3DPE6tjqDo4srB85TGcXQDcXAPuZR5RimQoLkkBYCci45zAkEid33Xhy5ykNV61XUlT0QWWLpAgfpSHKYihgDVabd/8MjP3h3WG5v2JU+iafjR91/kjGmenPPZFT54b3N+ibMzEzb3+Ctf/+oQL4Ktx3v96Y9e/fs/+PZf/83d/ArILcCgljBUWkGrG8MFMHJTFHNmrz0+TKReO2rca2W8uSvUOnfdYwAep5ngTgSWIAIzm+FAwf7GvvXy47/78ce/8dv/9Jd/9avvXH1wSKv7/fOHTGY4G7qLq/V+wv4+qTkLkbgXFCvJyn4MUyqqoN2Digr7ZjV0RCXZPB1uHw45YdVhtUK/CsLmlAkq4hIk59xFGmLou9j3XdcLE4pBTcGmcIOLcN/TEFiNtEiasmaFOZMwFaZ+1b3b48Pv/Ol3/+xbn33+adIEA1BUKQGKOkBvYIMXpwxYvX0LyWXdqQQUd1cRIVBlQJQgDi+loEq5iZSSmbhy3cEfK7UgiLBIEAiTrFdrcuz3+zTp9n6XUy9M5rSSFRQ2OzFCH4tpyqaw7jxG7vY3ez+4kRlb6LquX0vg/W7MeS7FTGEgFoncBQRCMMtFi2lL4OGPkV5j8KyoJdwDgKaIemoRjyWnFhVyWzveWleA2q7fAprjGqIjc4dXG0VUGToYIBS4W3ZkfO/bt1/7Bp68N2zW5elZv9pADDHBIX0fLHGe51xSUk9zsd2EghC7hRUTAAAAIABJREFUwEJAIToyXtU4rlHZnvhi1N6Q10oTvuBECwZ3hN0eQa5GfMNMcK46T4+e4ghxnfz25ZTp9Rx4CbNAx5DvjTzLHVWDvL65V8dSrRUZCPO8p7X3K9lsoip3MfhMefbb29nKzCTSUYzhbLNarcN+vt8ddldhHWI1Btm9kEPAQpG8K8mmfZn2aophKO6kxWs/TYwkfQwmpXRabLPZkIsmpz05ey61tqRWDISwBggUTYIF0LDqLq/Or66uVsNmNQx/+ed/ToZ5rhRw6OIgMUAhdc4skKrPY5nT3Per9bCZRt5jDAHrIa435yKd226c8jRnACHKarVed/3hoMVLnstmvTk/W/ccV906UrBJX31x+/yTV/nOl/ifKx/oEaMiwEyp4bC1WLZkMw5tJG7iZpqKZiJyDrwfp08+/rR88bNf/+e/zhuXHTAqUp40F7VxzGlGZARgTlMe4SPgWG3C2XojIpZmdYzjuDpf5VzGcXR1MMzUJkXSeNaziZAYLPvshYuqR9AZrc5Wm8vVerO2oLZFHoEM7SpBM/ciq2E9zskMpmq14noMflqfYdugpsZV8LsaKHsDfiWAGFxdgzfc2h8X8JfDI3rc+YS3/GttYHwrylsHlYxMSN5g7q753PHsb5zZ/S1NT0cY4fQkp1N7fjIq+OXjjYAQJ5v0NKQ83blv3cWnP/vWt3jjhSeR7OufYrmr1Y7+/UYIT/Pkt8JY/xGjV/+PH0d8ASc383Sp/d8SWp2uvH8kuFaTIRawgbk19MIg1Eh1DcTuZM5BmAKD3EkgVEGIog5ngzqp2jzN4Kp3S163/iJ+B3JzM4UAQQRLz1Xlwwfc3EIIjfyr8VLowvTuTCTMxGQA1Zk8Wma54UQuxGYmrbTUJnOkCso6qbYqw+n2qKo5aEFEhbOsXdjRvjy6ZjdTd2Om45ieQkOMQN133hq1l/issrwv+ae5OzOxMJGQgt3zXMpkltxTDccdcDMrmqudYybx1iTE5mqoEYlVsaKTlVM/UW3CqiwBC71aC7hON6hw43Q7bdQisNWZToCIQgjqpahCYcWrRWWiRRTyxIK22mNdyUdBUl5CDVS4w4FAYXEdx0T6kSELeM0qNzCRFhyJiAxeoHBXd2ndfUIQYarSQA4XB/EqrMAgYYlBRFxJHIXVyeAMJ5izNZCNHZB6me7sFbCtQI0TatG8xe7uALl5KYpCRJ7NFblb5UzkZinNfS8csNmsD3QAQ0ScKKX07PpdAKZ15dZePHrM2xce9BYXGwS8yA22B+TQyp/oUqf5zMWNzMWJkYseDvN2e7i/ufvgK+8/vBx3q/H+bo+CbujGpIB0XQTpnDLBQEJMwoGJXFQkSGBR0QoneFsDcDchh9FikSpA1WgfqVVFFwyzXawdu/McZEa0MDYROxovyX43bc7Onz579uLh+WSH6CVGjjEwk0PNk0MP48M4b969fnJxviYy7ix0BEndQMQUOPRDF7uw2+4IbMXSVOA8dH3fba423Xxp5HeHbGaYJzWodHK73e7mHYl2g5xvhk6wS4fpbg5rPnt21q/iatUNfWRmsjxNSUO8OD8bYqdqBJpSmlNxcFENIhKDVLi5ZCJh4Tovd3P38uqMUz48bF+thydf//pH/+K3fuOPvvXd/TiuJDq03aLFeL+BN5m1R2BHjJ2P2CCKWet2X2aTW8BEx1O99sXx6wpZn7qP5al5LTlUKlPmt5zhrQfB2WrgB2qaIE4V60SrpnnFLq3pj1YIu/VYmjmx1ZTR2ti1watF4WYm6tkbUuXHVLqgKh+ClppdJTF1JjMUQwEKhIhNnGCkzu5sdYCAWJiFiIk59rLb7919c7Y5vzwvmg7jYbt/EAmhjwSEPYtyCCFwTxa7qPdlO9lc8vxPf+Wrv/XPvvaN95/+b//2f10PKws62SR9n4vCiTkSiibLxd1KX/nsxEQiE6kWEazXFxLDNO6nNOU8maWiOUYZVt00z8WKgkTZQUVdq5I8Iwj6bsXockKaSYuUBM24ungnyMAuakbOgTm3IpLutvcffvTk/Hzz5PpsHrc3N6+2DyOArqNhFWOnIgPgcyqHg7pjWDGHyEzMabWW8/NLp2DuZg5Srp4CUovGNucQhSXORbOOOiejEEMgEdPkbCGQqWebDun+4jz2m5lDyZEsM3dbzciOIeL8AtfXdv20e/pks+7Wm/X119/99XHCJz948Tff/tHHf/P59799N78ADN1q6MKQUzLTmqcsCq0MJy81lgLoaFupdhW1RK3iPdWhtqIUt4qCkxPZsuXgZqolC4hYxEkBSOryPt2N+El8cbG6+tXf/tqT80tYzvmwK3MvFMQYGtlDLyqcIc5KRB3zXKbYIxgAV5uHzWaz6TRj3E/3d9P9HUBYrXH9dLNZd8QlJWXJXdC+4zIjAEEQAossXlGtmJGwuxc1YTiLUlZESCdCzB5YSslCCFgFnM9p9Zd/8tnffX8/7iEcSyHk7MFEvJaZyKuiApDrLPsxgQAIUDRn1IBpNlUisIgRkcHgMUTAtZSqZAt305olOgASFkgkqTpoXehpICta0n4+ZM1KQC6+Xq/ypGUcUXCG4I40JTU9uziPIaaUMmelslqdX6yvV1233d4/PBxyLvBKLsGRuyEMIUQ4ZyDbfFo2WBws3MmtZoat+e6kfgW8Ae4ff/wYpBMcxCAjgnK7O6Bj3Nlqe1aNJuBgFtTvUoSbFwX85af++Y/H6yfXl8/OJ9x+7ZfwxedIN5OOAWUjQdjY3UCBioydB/FVNwiF7PNMufmCWiJGi6Bq1gxbgjKq1ShaYjYimC8E8GgTghU/Wj7b4g2qrFMLwv3Re538Saffec1ZvJYtH2HBNpd5ensfs+sarzuBnVFbwMCkBgNhGrdxDRGEAACqOU2eJh/3gIKCbreHZ++cn12cxY6kSC7IZS4FgLrN5GAGQ8gljTYddDpkTc6MEISgTOAeYYh9FzmEnsSJiMI4TiIdReqFECUWRGPkMk6qhj5CBOqFhzAQdaE7u+q6NWcb02Gaxjl4j8JikZl7GfrYxy4W06yZXfKUx5tD6OPZ1bDZrPcSmDxIGFaxEVqydH1wFDeAVXparVc80GH3gBUQAeJh2Lz/7P3Dzf75qy9effpqvlekuk0Z4Ib7u3Mt4tY0iGrhiMF1BICNDFZJMVxYjDinDPcQu67rLGDOB9z4T370SX/Fqz5M1hn3edKUSl1sWeHqAUHEChsyplzW6i5UsxcFclbTVOosPaNocXNE9OtuPxcwMUQsmLsxOQqY+nW3vtg4cBjHnDMCQEhTsdmsgIWZuGT1Gmu6LUFFzeJ8WfWtfHHshW+z0b7YugVghTnIdMGujuvX3wJQwd2I+DHEcvCXGpcel/+bP9zAZoebGS+dRwtgUDdgC+Ue9wv87Wc7yQ1PTvJ4GT8nuvsy8nW6f0+v7djb9fOBiLe+19uKpgQ4vR641oNPEA8i+nsAWKdQyz8SLvn/6fHWu/+PuRVHcOoo3UivKxseVR1/zhmOL/7HoIfuy4yfmHr22v/lCmKhzpvace21ZoDVTNWKKxFZMYM7cxAWgZqlfEAkkC29Sr5QrRuAKnjhKLSMCdeLF2HA2WjZZuZLxAOu7SouIiFGIjL3jBIRVYypzc1VsjrhBT2plXtbSl2OXC1qqM0AdVZsmR9zcJA2O0DkbkTk5sfqFU6cLcz1FLxxSJXRgjNYWEjIzYuW2gL6SAvvpgRhYWKBkJMb7l/eIwETkEBOQpGZDQuRFlBMR52EpdYK6kYWEQq0n3ckJFUjA3D3Uxq1x916jDvpmCU7hcoc3uoJQC2xNvl68xI6CVKHLd1qLmkEbfGDu3obCGIs4VlTFXRdipaPLaqVx8qOsOBJ8YGavBpqut5+b90b7dbXzxG7QdVKKkgGcXQGhpHNjpxnKyFNs8Tg7oWdo5hrTrNNBsP67MKze/HKXgoSkJHW7o1KrMNgANYYd7whNbVE1nAbI3dVL2AjgplyQ73g7jlnmI/TvNFV18dVXKvadvtgMza96WQfffA1XCHOIe8LCEYc6np73fl4rWf6Ma2qtled3CutJhH14ma5zBwFQtIJd5hTwdZfvbj/W//ef/3Pf2/34nB7vv3ZZy8hWK9W++lOLBAkpQwtsu7NlQ2I4q5mpJVUFyWlAivEEiVQlWGvT3iZviSCM5yhjwWhhquiYlXtEzhVfu8FJiYKJBQ4Orui7La7YbW6uLwgoXE/ry66oedhiF0XGblAnUoq437cZZ+AFGLYSHzn/Sdzunj65ElKyVVd1Z22d/dATJOWpDH2Q3/J6Ner4epcAeH9bp5nEEKQXPLzlzccLHa0PuvnnK+HYDnpPqHD0/eenJ2tzs42Wq62D3d5GksuAtOcCAiho9CpY54Ocy73u90H731lFaWPUU2VICJhtdIyqZf7h+3V5Tsvbj4/DNN7z8L19fm/+u9/L5J89y//9mE391GyKLCk0gTyOq/TZvatAO4k4mbHyhtRq4kr2mwnTjooK7aPR6zqsex0/E7bdG8rvi3Z+9HYkbuTvKUQ94b/qNwp7OZOVGsvrXEquFdgExVYhhHqwKBXj0LCQg529gqcLQ2QjeyEjKpbqNdT37EifwoUr0uu0vGAyMhlaT9gY1d2g+6NIqgDKawK07plA8S0WOmOaL7v9/vt83swENGv49XVVVEd0yFN8+3Dg6rCQTpRkX4ggq97IOL3f+93f/d3v/7J9jufvvy479aHQ57Jtg/3D9u9dCsiZmKu2gcEIelDLJotqTKVXIZN1606FozTeDhMc57YMM57Zo6RY0fZuKSci7q7qjOhC2JsIQ5Bhjzb/TyWXDQxW8i59NcrVUtpziVbTp1AeoQOFxdxyvmdZ+vVOli5396/GvcHGELE0HdXF+dPnp4fdq/6FalymuGOwEzGuVBRdH3XD4MaUilMHpz7PmZTuM7jYV/yania02Ra1Iu72lzm0darbrUOhShN6HoXAQczPyj3Y7qzIiTcB/qX/8NveQ6q6pi6wS6vZbUK7EToxzv93//4//jxx8//7Fvz7guEiKv+7Oy9VU407tJ4N4Z152aeK+ExB+6ISOsztqrWIqjSwqi1CQK4NnVkU+aWijgRk7NRHaarO6tSfxKTmc/zTIGIhUlgnr7w62dPnfRHf/ziR3/84q//q+/85u/+yvtff3L9tc39dHE/fbq92Tm07wCG8CpuZKMsHIcu3j3/Wd+FwFWVpBD72fnqbH2+vd+u1uH6aupC/+TyMgSBppJ3OR80FWMSCn1EFykKMQxmpRTA5lJcPcQARirZQLp1cmMdxPuez4bIqyFsb2833bqPqxdf7H78w8Mf/rtXIOq6NXUR8wwidhNSqBLgBVzgiTwTjGIv6vaYK1UY0Or+I3ctakLkAc4oqRAxB2Zitkza9jMbudcmTW+QIvu0n0vSYRgADxR7jrkUT17UbcZhHomg7ja7JeaIVDIRxXWQEC6eXvIzGfcjFV5fD4GlzOYrjqsh59THnjnE0AXpiChnVW8aqY7SXFcF6ys91pGr1LnGPoTHrAmPWNbRSDbTeUR4GmuTy2LD6CSS0UZS3gpysNbaXFVRiMAwvfvMv/tnn3/zlz/8ylfPv/j8+//iv/zV//MPf3jzKu/utmlfonVWRljSGZY7zKk4j2WGTeWQpFaGmVt/fCuSaI1666QCYSn6tukLLEzsFZg7pri1Ltlqk6deg3zJJ9/0IDh1QG9Jqq0RCxBqK9hxMfHxXdwXLftausDSFGbStmNzYgqABRKcoao5Z4zjeHjAOFW0kFjk9lV699lACPvxsF6fxXiTdL/dKbGFCHIIonBXEo8P82FfSGMffRjC+dnAnM3VmE3I3XKejYijBCmrc1qtQt/35KuSi6kGi1Qkp5zyxExdF2KMaU4ppa4f1us+5/GLFy9uXzzsPwOQcCRfw75CpqvNarXp33n/vWHTr7jfjndcjNVXsYsXTwhk0OefvSglOaHruvXZysyKJbBmPxjN3ap7dnGZDuVh+9ChR5Hd7eH+s/3hpQpECUCAeRuXU2+kt6YwNGEXAjc5Soc7GxzOBFMXkIDByOZkopncELsuY/qLP/nT97/57vUHZ5DSSYgku2RB+q7r01yCYeg6dDjQYRqTCBVyszJlzarnIRwO86pfr1abs/Oy3R08OXoQxzGN2TPBSQRCgihkORoP0q16ieH2/uZud9Ov+uuLiwDavhptLlyEQPvdvklNtAFhOhIfVzUOLE0GZsZL1zcWyLfB2JW5tY46m7n5Y6fAUjX8cuK9EGzgmHc1MfgFJm+bC/w2+AsOwFxdmclMqRLvLtvziEcd9+MRvfoyCPDlQuaXp7V+cfTgDTCrYlhHAOuNl/0DEInl/L4A6K+Fsm/81f0XHiE8Ra+OP/wL/uzJ4/5PEfb6+ccb97MCEKd4BL6EUB6P0++/sbD+/tcBqkmBusPZav3ciR3iVQfOYEQE55p6FC1ay31mRsYRxCKVT10hNTxonoZaUXzx2Vi0ceu1BgnMDBAzhRBr01CFiIgIxCIIQm3qqn7q1l21QFvHz04nq7RhTFbFU20BT5Y6LKjKyrQeLA8Sl3tnXrncF/SKqNbr4V7BmVPwBV4JS1uBDUTEwk5eI5WFYKrmnVKtJDkTGArPhh3ggBK5s7NwEGYjM7PWbWFerCBUqLtOMnDTPy3tHauuhJmZmntl0+Z6uyoc1qAQWtCRFpk/1hOsDnkZm6s7iBjWKJjbLLeBjMjATtmOI3a0pKdtNTYkz1stwxd26pZ0upvWjiOqTXc12yVdPMbSTd5u3XLN9aGHEN0KTGGVfBUUK9GVKbyohhBCFxBkHbth05naYRynaSpaSi5e3LObksPBAoKTcSVo4ppjt8fptRhpdVwLqFU6AGzutRpTFcOVibtAxko43gDkVGIfq2zH7UPSbiyDD5xV7asffHT72V3e7pw9MDcl7sYgf7ovlt+WZdxiam5lsuZQvYot1BnOkFMh0+3dfjpsz39v8/TJ5eXlps5HMEEAh5qz5UyyoCQwt0eeWbVStMBybXoxssB1GdTOcoZS4w6otfdHhcnmYYTFj60yR2NV38C8XgTVvQfsD4fr84vYxXE+bLdlcxlgEJYQmUEpTWBVL3M+7PYPMXTTlKNEMtWSD9ttznlO87g/jIcDNGpJ86wlWckyrcsgRSgQS+DIHESUA3PHipzmOTqFri/q+8N0PlzMWtI8bab5YXfYnA3D0OtmM+62h6yxjqya5pwdLMJd3x/GybPNafvOO+92BicGt2dIgcm4zDMHMku7XWaXadqvV/LBh+/95m/+6u1n93cvflxcQ4AZWEhETLWS63mxKkwhtSe8VaGX3Qqv9Pm1K5CoJSPutTB+DG3aryOCXeFkf5207tFf+NFTP4YdpxFIfbr++LLF5Fb7YY3Srg0HOaRWDdpsl8OYQBXZrnBv1XwjwmI72kqvHHRon6h9HxVAh9ZXtuFaI9KqDEbNW3AFHaxFogookRKldopakoDAyc2MIix7TpOTM3GZM5Ktnpw9eXJFgmkes5V33313Gsfd9jDtZwB38xYTBYsSUx/iaoVf/ubTX/naV55erX/wyccSbHu4f9iW3ZQ/f/lqHOdY6lAbEYGp9p+ycGQOadqVoqbgwBeXV7vDqKbFVR0xIOW57/oYpevClJNbVlPVwkQSOnX03EvooJRmTXMyVairsmYc7nZUB9VhzuZSCuN8Lc+eDGrx6pyTjvv9Hn7oAzSCBUEkSAgiJRciKVqlsllNvHgpMKec8zglc0s5L2GzMjyXknNJCex+2B2K5hCCCBWHTg6z1SoGQZoPOTsLcfAaUaQCy7rq+yeXm/vbH16cXayHzr2ASuDLVTgPvhn3tr/bfe/br24+10G5RI4U8tQd5pSTsdNqsxmng3p1V6EOEtbV2ZYZtd0gVNtqWvZCBGYpqmZNRZOAyrLSaiZYliFBQnCYucFaIdgMQVbzvSssxI6Gcvuz8Xvyk374xle+cfbs4r2b2x+L+eq8y5oVKuIBZBKCdF3fQ8hQO+sQGGbzNO00T9uHXcl5tV5tVqvVOnTCrjyRL8Crq2kfEKgSJbIZmdYrDhIDEWJYpfkA45IszTMVOuuC9Exd38uwp/1muOx48+qL3V9861O8BF1GolDHJ4WZUMjNzNxABa5gbXIP5kzVcDfPv9wgoM6TsRGYLKvREgBkszo1Xnd9xaZrNOYEhqtZQkbRYtAmoyPUObOpsRvIfI+4igzPY55p4i4orOuju2ctXdf1Qw+y/e4w4eCKCYf+PIoEfSjdZiAHN5lmzZaKKYiIaVEgISImXqbj3QBa4r1FQaZhWAun1esYFrV6TrWwAAjaIr4a8yzqYN6ii5NRVVf3CpsRO9f6BNvh7JOPX5R9EOp3+/3Xf+mjH/zgxfWnt4dbn6ykZFTUFUJ9iB2FvqMYRazozGMZs9PRemL5FMvYXVP7aTmvLyTeLT41LKgUFo6g+gGZHhm+akyMVh1eEsvFlTwmmb5EL3S8Ve3XaxlNZa7A4p4e+/H96HRa28lCulCr2i3CWA2RQ5FgIQR3cdeSUTIjMfV94KDj1grmrF40RHJHTq4lE9t5ZGaHixXkpDmrKYLEGLvVKmzWnYRSNE+5ZPOSdT+NagiDdGvu+wh1chV2hGyWHYPRQBGBeBi61XoQ4Ziky4GZJSJpSZr3D4BXqhC4wdWZRJgBk0Jc2OYyanl4dT+WbRfhXV+0MIcYO4d/dvd5BoLQ+QWHEKvKSc55P+1zQh+71aYvBztM8xzn/cN+dz+ODzMSRIIC5AEwKNy00f2hos+VUXRZwu0ptuIyAWpOZMIhhE7MzV2zuRITgXl/Z7vbXXdGvIYHDRB2DnEl3eB56oIE56LGHoTKZnUmwm6mc1V9JU1KAbHrLq+vti8PMLCxFd2nB5aYA0lluK9hZSc8MPfijN2404S4iUM3kLHbCGOhAEdWh6IJzNb1ZKgfpy7DxrTk4Mbg3mx9M2iPq/boClp8T8ea7Ul0dHzZaz+4xFFeVcu81XTflqe3wIrEj+eonFbMbdcdYzV3tJ7KtoOWEri/BU77cp3yy8eRs+j0UlqWyGynjZZfAhlOz/8IcL+JaxMWLvXjGd7AuU5xND8xLEuMS6/fZKJfvAPrraOVX74jR+zgjVe+8Zpf8E3/v3a8FVD8x3yc03t4+vUpRPrlpXD8Zn1NbdF6AwT9RUDD42rwxSw0vKHAubZNkbspvPrV2kpvSytmW9IVyOcq3OsOJ3YJLKA63VZRCjetiIeaByER0opSASwcYvDG3O5EVIqaavN8jcveiauiFNRKZX5RU4MLSyUmWuhC/bVd7qiXWO+NSD1nE3kTWhASN4Uxsy9QSR1nIaJqO0AIkYGKKj2WDisK06qJFacxN7IKQTYuqqURtO5eroFBFXWdNB8yqEpUEGrtz80MqgoDoSqXUp1nqMJ5BnN1K+bJsHr8sPWeoLZvEE5b+YDGRAjAdQnNj2qwNdmrzoxJlJzALLWJ3tydrTbowahx5lO9VzW8o3p2B9yLHaV5DA3b4IV7E76sWK9sam3cUrVic740mhxXP9NrqxlGJ34BMHL1khRkiPAoXR/AZOpKqknVVLO6OgzOTfMIYCYGgwLYwZWZoi5nN4eZ1jvWmu2JkacEF6qEFbT0Iivc3COkZ7DXXMTduxj204Eix8BzKjGAg97f38+cfvDxD775zW/+1f1fb8NOKAAQCa7FGsi3lCMXZ1VqbybXySojchbmwOZupQoveHGDqrto8ZTAHaZDurnLt69erlfdVz548uQC+4yiSQJTZIkMi8nUrfIIqasjgAJYSEsxz5WenZxcdTbtuI8xciQtRUsBOzO7eh26bAuM2nZikcbgtZC419lcK+YGhhqH0BJ67A+7d+PVauhS3sGgpUxaYFchSuD48OqLruuK5lLK4bD/yle+Mv3dp/txun1pxcq0G7uuM3OYDPHs/rCDcyk+z0hp6u4PZNJJnFPKmlULEYhhpupFgejsTiUjzXO6sGlWM0rFnz9/+cH77/TdSs6Qp3naT5EZIFPfbrfc9e64vLpKWYPEh91uSrMfKPax70LrWkchVxZ5+s7TOU3kseisNqUUwPRrv/bNh1cP9/ubm5f7VIwiEbMVZHNmDRycXGsQIITKTEFSO9Lb2ne4Ox8B1xpR1fCzEpadbJGahniFq2vMc9yOr7mDZkaarVywrEev13DvYzgBAGZm7qpVn+OxJtFgptoD0H4DHJozgWvy2swOWp/rElNCHcxEXC0UUW3JIkAbGFbhOvPK2E0obgZmJ2l3Ak6mFQtqDYOrPjazb0WL+QxvrV4MIc8OdmOrTSIMJhKYWfGCEmJI93lKqcWJE3hmCC7X17/01cvry/gv/9XvXH2lf/7yJ/d3z2/unpsNdw/zi9v7u+0BYC2mDivuiqIIDM3GqyCRp/0uZyVC6OTZs3c++fQnl+criSwBXdftdztsLIQYowQhc8vzPI6HLnb9sJ6SdQiOkLN7tnRI85xcHeZmuC13w7pbrbsYKLBJJxD74L0n7394wbFcnMf77f7g28uLTR4oPhSAV6shCu33e6YwjpOjdH1PiGZBizvQD52ZbXd3RFxMTZUYHAIz9Z0MfUcgYaR5yhlxEyWIFYVZTra9T6u1DMOaxJkdrNzxNOU5Q6w7P7t4+uy6l3y2tq7PfVgR4qq/Kunsxc/sh99//vyz7bf+6KAjziOxRbPOlGAs5FrKPo21yZlCIGNz16xu7lp7hWtfoFej714pt6sqJoFB2rDThv1y+6dKduDgem5zJfLWTO3u7uIRiQ0gkRBXKGV/O/50vFnHfh7Pv/ZrT5+dfUTdHPqyT9vM2eE5pTHlGD1KuLp+Mu93eR4jo+ujBHFPpaQYEEPsRJhLSgcIhK0fQhfXpsmR3G3oOndPyTwnlhC7SASisBqC5vn87OKL7QMkzAm3905l8ou+I1jH5N2mfzbEy4ctPLdWAAAgAElEQVTb9PFf//Tf/ds/4+uwGS72c7ZpQi8ipPXhupsCBV4AtQAQoxZMHqlIuJUMm6SoQZhBNKdchRYcfjiM1Tlk18q74E14oVkJK+rstdU7W1ZdoHB1LdqiS0fPUU3NCiuTsrlSJ26Y5gnQVPpSinF5yLclaZG8Pl8RGHujjtyslLkULaVoKWwiCFTD1mpTmJnEzFFsgcKFmYrlN5K6hr8/2s36xxEzffzusXkc4AWTaVKxqAhZRc1MfWF4MkUNtSPOXnxye/PZ+OJzTVMRlidPL6+v8EV3s1qFMWVmhim5k3PHQYgtmc7FU60AUovcGlhGR86jFtN4E4/xOvFYw0Vm01pbqi3lOG6MJZhspzXV5ZO/loIejxNXdeItWnrYIp3lbrYi5SPGV5kM3R0u3PAUg0v1Bd6C0gqtGGGzHjROw0BXV+clC2k/yqzFYFG4I+HzJxfd2YpJpBtu727HEabarwKRd3MrjaecxzFrAXPo4hA7YdZSCuAp52nMSTklnRLMYVBAn12fdx2vIpg9W9mn3TSmeZ7dOXZy/eTq/Pxsniez2cymaZ4oi4Szzbpc2c3PZisOkIC1KByIVKCks0Cm9UgBpjrN0GTzmO7utiR8fnHBIWyGi3Ee1bNqNgtdL0xc6rZhKPQwHopnMOWUX7263d3vH3ZbOPKUoF1Dbljq86Q6Ci1iQDEDECq/cF2hFbgEAUgpsbOHxmleKSK8Ms/Pzhe4fblbnQ/r2O12o6x7GERCjFGj6TZZUQp8NmyGvj87P98fdsTcdV2IvB7WNf5nkfc+eHLz/KYc1PeAWdys8kHBnlXVCjFJIOsMHXNkF0+eJbKZ51nzOHp2t6ZNHEM3lxlewWVHU+lANWAtZjWj2h61lMxRK7ME1xa2HBv+GozUeDiBytbS9teSTWMRgzpWEZcFTu2nQSdb5Lh9HluxaEGIG+D9JneTmj+W9o/x0FJJPKlEti+Og1w/BxZw9yN1Mk4QBmY+HQI7AlunP3h6bacve+OoKfAp7FA7LmKMx69PQO2WwFprF6XHitJJUPr3GCH8Bx+nuNp/sscRejweb4B9R6Dqy4vsDWTq9PiHwWen66wt0xZW1OoYKvowrLr6WoOpqmare7NCFaZHV1znqd1c28upDo04LQzpVjtkHCQIfSBiS0nNSIiJ69otpag6HMS8WBcWYREBabHMICzRUxsDB7FwlVsnW0qtXjd5czTE4MhgZyLzVmKo3jqwOBORGBujitZWn3tEz6jKKBLVtlrAiUSITk0AEcHcjhnhG7jkUkciAqm6UIgcUVAmtVlZBcbkAkdl72DTVrdjwNu9dfdSRZdDZROEmmopIQZlLaVUK1mnFyvmB6CU0lBCah0KfsxOqWGR9FhwcdQOhYrok3OzjY1jvEGm7mYmIZgWd3JTB7lLQ3+staL70qKF5umWWGXpBmk5dsVPDW5E6lWMHdWbUNWUAkkrhzBES3JzJnaWRZLGKLsLiGHqKZkzypyNfJ47g5VSqtMoKbk6nAJLY9EXJ2Fyd60Zb1PdrK7BDFRTZoPNBWTEfMQBW6sfw4t7IAaTskK7vhvWq1zGUrIqsubrJ1dnw/ln++f7w+7bf/WX/91/+/uXl9fPf/bCFfM+dU83MBIWg2fN7TkcrYW2SVcAxGAhCZBItcUu1SFbJulCYHFFQOhCH8DR8l9957tf/+ir7394+c1/8uEP9YtxPxt8GCREcYRSDDArxaEugZndQWwIvnS2u7u2SHVA33UxxHEcaZ6JQcyuWqHLupjcvbX0VU5uf9wjDRknpkAgISI1hxomCBuhMOXNAFxjvyvDUBHyRqpJQqD+MM5fO7+cpj2B72/3Oe/Xa5ydnY85MXOQCME8g+Ale0W/U87TnKzzaR6nPAPmbLlUUiInQc5q+6nrY9fLq9tdmaehDw8PhyjECO5+efG0TGW72d/evOr77mF34KCSXWLou/7y6ioXwzjdbXdnbueX5+fDAMb+sN8fDkC5OLvYbNbzwUrSEGiat+M0Xa/9/fc/+s//i9+4e3jxB3/wF4FRAFMLEtZ9r2qqxlw3GdyNmUmiqdcKHloAAQJpXuQhnRzE7gqvkhtvHLRgTs3aE0pr5ngsmmHBsOomf4vDflsd6lj/KI5luq/a/mOTCxFV60tElGc0IS46OW8VA6XWnkBeGVMZS9RXIzX1pcDI7U2bmSa4uom5tli0dXhpExWCucSeiZSMjKi00xCgqbTqDQOxItvBit28ujkcdlDnDX3yk59YsWEYOsT9wx4GdCxMZ+f9/f7m3/wv//rDD8/ndPvTn37y4uXzwziyxKKelJJSmp25mHlWUwUJclEJQdX2+13FWWKI6/XFXMputycUQGO3ynkqRQ+HMYTkoCA0T9N+O1pGiD7EjshTRkpuyVxBhXwyyyCCCKXJ3Ce3MvTcrXizGbrB3333/OmTzd3Dy1LKapC0CqolBLm87EQGkeiwkuf9dDAvsY8inZvkpNlM2TkIGatls2SGECFCRBaqjmPXhShCddgEORcQ1wFfkMwzmTkHH9bd2WqIayUpZt3m7LKn2HXd4ZDee/9K064LuL64XA9Pf/aT3U9++PIv/uiLb//5Z7s9dI+z9caLlMkqXOteXIt6dpQhntsiV1JFy53I0WSZWvNM5TPyBT1tsT3ATGQkfrL+q6qcU3My5iAvCnYsyXztb6vEwOQMZRYWx2G//9H3P39IXxym+//m93/n1cNPH8bnsQsebJrzbp/v99YPysQXQw9LIkmEY9etN+sQgxDmad7t9vf3uy5gs47S98ws7MKkwjB2tevrd/Ksu/GwPRyKHmLXc2Ahhbp4cSVBLHO5f7BXN8aKlcwXq+JGpmHTv4Ny9cnHL//0T777xU9BI8kGTGzEsGKFKzVSHXqtsZA7siUy8q51tC1mgxqb91L5W2rry5dL5ufkFTKqDwZeyzLmqQ2ZUyB2gpAlUzMiUnXTpi4dCUhmVWBeGUpetHCJIZh6SnMphcidDKII5gaFBuGw6cY8wsy1NpUpKpkqgxjs5EuDXoNzHg2c1U93ynO+OLMvm0ait3yTlxLOwqLmQC2ONYMMbpSp7MdxcAOBD/cTovzgez9df3hx+dGzlzd3l5dX10/A8ebiorcDRFGyp0l7AfcyT2nc7ZBLF3qYH+OHJaMFYWGh9SPx1WLGKyEXlppSbYaqTITVUjr50roCEDmrn3B1nviRR8fwHzzepNRpoQHk9ZoKAdbGOmuxtSoqFjOSUAvpdaaD0MU48bRcD/oQAudtOtAmmiVHt7nacKDDOFKZcipmyAqfipn2PbwTBqWkh1HHgxFiiFFCFOGk05ymlKeU+DAedgdwwPk5r1d9FMZee+rPh3UnNIE0PViiyOeg4Gbj7ax7M7OUSlHVDA48bM42T67eH2in+vBid3t/m3IGuYCcPM9IWdO8PZTt+fWmH+QqdrnsP/9iPx3QD1LUDtP4zjvvFs2u2dXMiqsTW+yoLxTMuz7OaTb4xcVFKP14GMfDhIKASE7ZrLnkBtG2x2cEEqZKm+vNeC6oC+A1OGR1t1KYrA6AdBLMacwpdCGCDrcpPQUNZZzzKvQELiVT4b4Pn988j94Pq4EuYhe6QJKmnOdEgWBesvZ9l+e02Zz3Q3z23tNpNx/CuCt7SwW9G7mZgaxfr9frVZEyyzzpVObi5BKiSBj307SfdFbRwKhqHnCv6l0LK0JNYG2RIgIvkgrVQfBJTEHZytEjEHPjtCqK0wJhBdt5GTapPCNsYF52HFB7VlvW40s4zG/akeVvlcS97iYmqu/bktMG4LwRjJ3anKra3HqgjhvtH4zAnG7wX/CVRxzjDYDiDbgDS0TKi9LrIyTyWvuF1crpEbV6vAn/7wBY/9Ec/zC06Oef8PRB4sQHfBnLPAWtaImijg/+P/QWb124XwbOajGfqntvex0hiJsXMzMvanVfAaDq447/1wTWzMzaxFoA3HlRH3UnNa0E1SIkIrXoY+RSEeXaq0UkreOgnZMqWEBw9wJlJyJBlQZqLpmaerODmNnIirfiUkPDW5jAJBX4WTxtLTuhylDVE2kpVsO1OgZIrRHgGJIBMHi987Tcxsqk/Iie115ctyMqD34UQ2UwG6sasnsGlyDgKY1ODCVzh3shC8QSxJtwamUN0xgiHfVciQAU59pH6nh8x4p2nAgRGktw9tciLDqtCxwXGINIBM6178gN5uZaiQqWqNUZ5to6q6qV8fqvvkBhhKWuVv/WQEBu1Vec2jRbVnupqeZyox1ESwq7kIY7kEv2tjAYFNwL7LEd3xXmpm5EFCWKB5AywVlB5HNt6yMji3yccmO4Q8C5Iq81eW/VJSgIcAaTt6aQNkNSLxDCzCpsxELs7AwRiX1HYswkwiEEdol9PDs/v813+5upqJ5dbDbrs/3zHULruapTi7SMbC53sYWPWCjVQXXuhZiEicgEIBYehk4CSrEu9mfDZughrj/+ux+9++TJ1cXV03eufvaTL24ecieY02TI5h4qoTUMcPPiSs4m3drdkQGhIAKgWKnSAzWOjDF2XZcsm5lTzf2qKqiRGioR0ZLF0IlglR+FRyEtP1TFjLN114kz6XrNIdpnL8GCECTG0PfSb4bV0LvJYZzV7OzsQjPf79ERyFcl8zQeRCQEmefkBjUvBa4Aw6BGWhzZk5Fy52YoyQxNs8IMBmcyZp7dcnZh3Iy7aXyQMKSsjHB+cX3xsP27H/5gszlnyd1glMr6/MKFpeunfJhzggNM4zw/DeFydZWmWS3v9/dzmoN0VSo1lekwPpDJgbpcxifPLr75yx9+7+Pv/OCHNStG1dirPaSL2QQgRMwsxVXNjyoJtUrt1kad2phKhYnflkhVBp/lxAQiNz2Nn472bAm5Hut4P8e5+CIhurBj19J/Nd5c0z84SMFtITCOlfvHbKVBlfBGggLUTk9rPbcEtI/V3sS9ZlMO1NFjd4K1emmbQjlaomMuXXlcW/cHEFgkCLkaKq8VUHHXgdfDhgIVLWkeAYohTvPUd0OMkTIX1j50btk57+aH3/7133j+6uObly9vXr18uN/Ok0m0adJ5tpwxjR6DGkDE61Xf9b2aJS373f6wG/ue9pM/effy4vLqbrt92O1Xq0iOKafADmotow5y95QOKYMcViXbJWhGHkctYI8RXSZNlgIkiKD3rHl3X3KHc8L/xd6bNNuSJOdhn7tHZObJc86d3lRDD6hGdTemJgEQAAnRaNpoTVEyLbilUab/oZ1kMi200E4b/QOYFjKTZCaRkoEgIYLoFoBGT9WoruqqevWGO54hMyPcXYuIPPe8V9WNbgHigkRaDfeem5knhwgP988///zRxYPlSRTGfrvd3N20sY9tWC0WLy+HPI2LxWqxiBLalJNPSTWDECRGafcpbza7yV360LRRImUrfDdIYEDdjchAOaub0zQOxFgsQMw5mamYwbUR6tV8t904x7Oz07Yzp2EaKQiEmmFv189f2L7pG1+cPRQ7sd3yg+9+8J0/vf7Onz2/uUEEKSEnkLGquilMiQyWi4yRCKDspaex1wS13c+pKjs0a0WXiiQHtPZvoUo4ITafw/lqgUnLculuUIDJCKzkTARr2+jGTjBzTVClZtFKaO5ejn/+Jx/9zu/8+mn3RuBwix+Ds1lWtazAOGz2wt6IWqXemLm5CLVRUhpSGsfBZVGuXrwuuuqeCMaMGLo0JrPk1iblaadACmQ2aiQll0XTjz5IAImbZQqITZHTb21YtvGN8TZ98uNJQKpp2O8DRSvDTRMJ4AxIyaHVpCZluJMJ4DWLWSt3iwtoMwmgosezjbj/oUgFVNq3MdzISgEdnNw0q8ILUbc0ujGCgSBMiOSesqUMdtIidkY25TRkkEWWSEICRECABPU8jWMm1aw65tmqVAnz4t4cPKlqVSvtFTj6CK82CP4JW1mgX09R38e5Fb3yQ7PDkhYkN3YGFVkoKqs7HKCgY170ix9/8Mk7V/273/jyn37wb9bnj1f9KhsWDTmSyJJjk3Z7EgocEB3tIix4uew/ffqJWJiRx+rM2wFEq1qe90ay/t+cyAKFOX93yE7Xfw5N3DDDfYetpEtrMuOnrxp0aM6I+t2A21GzTxT/W+dXUxz2I3fShYjLO3Y1AMI8DcNul8fdfhqJm9bhMZoOyVLCmjjoy8tnHIduAafMjBAhJO7a9St3THvdbsf93ozRhmCUxzwGJyJTg7kAvOxP+wVcpxDkfHF6cX62vb1d+8mDcH5+sl48CHjbdkN4uSVy3g3bu7vrcRjc7HRxITFACST9ou/7ZTjvwrK7fnbz9NNPnz795MOn7++vFRHLi+iiu2QpYz/t0DbNgtt21QTL027caNoPBqQxa1bNmDh3LRCCkwdBYCLyvms2t/t+cbaMq/FGh/0wTRmCRoJmB2fiMvIrklIWTAAg4kBqbkUGjsPcvYKLFW27ztW05pGcOYgQEy3QULRIjmmykfNAaUSPJoQ2abJk0VuMSNOouzzsdtRRfBIENHmyiZJqkLBq+0XfA7rbb/v1IjaRGBlp2E7YzAldQVpkW1ekddBJPJeJNExJpwxnYREnVrJsmkxcak1HHcxHcG1lgpfheu+OEF5NxeF+PM/J9xnWmwtx/OhB1nQipO5P9199Xxs75yE/66yV6zoAVO6YO0fdG9VDPPrZ6L6Y14O2+k+bia8d+JNhhGNk6icdfoxz/ex4WUEL5kDVD5dRnN5inW1uVfQKvP1vk4H1Nxs+rwbzGKI6RiUwVwVifp1t2x7217nr3F9lOx6sMxbG7gTKVcEOgEMVWkIHZgpeM+cVvaKSCQeDBGCwQBqWEEMIEmm42+AAm7oXaQMC3CmXmmQmYWEir/xGOhiFEGPhwhTcx82N3Ll0hivoFR10IGuflUrfqd1wnFFRDQGISJiCzCmlihB7ViMrwgdFefxA9HZzCAcpVZHZrDQBYzNTNbgXTWvM+k3uXsrxKt6GoqrlBztSebhAI03epd3lDhPggDKSY4Jxrs23yJ2UJEhkn7lp7gp40gmHqFMQQ0Rg1ezBS8ViZYo6XI9twQwCUo3mKnolcs+4III7EzGJSHCHWa79nJIiWCEpOIOEiZBdbVQJQYQDBzcv38skTDBSeKh9TqpVYr5vyENzuV7FZ0odWy0oKFpTJe/AhWBfIDyzUtjHUy0qZS6etR6SGU6kZIA5RRYxwmRUwL3y50huKOuxIrvVXiSlMpBdQEokReO9ZmioyOggcJVas2yl5yYYLg6FqrJzaEPORh3tp3E37p10uVrGJrDx9cuX0y4Hb8Yhg/HDH/7wfPHg3a+8+63Lb168cbG5vTMzUjJ3ibPI9bx+EQf3PI9KZ4KZp+QSwcyxYXMWCao2jSlN2jd9Ch5B4jHnNAyb7smDN956+OLF1c3dx323mMZMUqmFzpyiZs9Gbp4hWJ/2Lpp9l+4QJbi7i6nZuN+ncVq03WKxaNs2JXU4kbgRQVhhGdAyEckOXcCodHKclY5IZtwYZt52PK70y194s13hZEVfevPJZtzvp+v1qo+BC17eti2YV2frfnWm2Z48fmvR/BD60hR3V+OGR1U7OYmRo6bpdL2eUt5hGk0dMM3DsHU2NUNwJolgaVg15xIKEdhgyXZparqYkqa9pgmXEYQICzlhtTo7PduDeLvPzL7Z305peJPFiEhC07Un52cvnz/PnuUZxxiePHpwsj4BIbu+vLy8ududr08Ycre50nZaNMvt7uUHPxofXjz5rd/8W7/xd37zP/+n/+WbX3i434zXz+5SY4u+sewOsBTnkOYuohAABrVaD6t6jxb5XKlXE3uvbcWkM7TEpAZm+7wMHs1igv5TUnz3Zz2YvlJ8LPNZwAwuSU4yRnZTU3UzhREJ13xnjXQrQjWP9+LUuau5k5FV3cFSH0YCuLFXQb6S4JzDZS513IebQaVFlEVor2PhGVd5P2PNbrvMgZnFTa2ElxGATbvULdtF27OQuepk2822W3ars4v2otvf7Bd9o779lV9597/4J/94N26eP3/x6dOXH37w0TD59Yutkn/6Ynx+ud3cle5OcEBY2rZrmi5byrt8e72FIQTBHhdnFyG077//g2E3PXnEu9304oVenGGaMncxkLghSPvGo7e7fvPsxc1uh2m/beI6QsRQlNMCcTTWzJZ1mkx3DgYCYierbnW2vlitg6fxkw9fDNP2tF+M+51qXnbkXWyahgNMc85TSmPbRSJaLvvQtLtdzgojuGrDLUeOxoCESMwwB0iEWUjMPOcJwHq9SAnb7ThNvlo9jKHdbHcffXInUR48fMjUPX060PXeeNjd3PqIR+uL08UiDbS9Xjx6+0vr+Nblj8fv/fkHv/d7333xMRDQkDBJSmnY78ACL1+sRZCdGCwoQJ9qLikRKgXspm5FurEMLgNJwRmotjUzr6xkghnY3ay2oC25JyarEkI1NnC4WzaCG6trW9qxubuTKtSZpnjzqU40YcT/fPF//oP/8LfOHj+ccKnNpploscA26W6wzbO7k1943DadkKRpv9nstrtdiOgaakJ7erJ4/CBq1purzbCblj0uTtaLZdfIguBC8aNProdBh3HK7lP2m5vsioszeNKGEBBO+xNt+kHT9R5sd/2aFku0LQXuzs9+6eaye/876bvfxbJBt2RLKTQexZImUxciZ87ZS50mERCsSFypZbCQEbEX8ZuZaom6nH4OAXTeVEH38DyZwWfdaIdm15QAdTUQlNmd4V7wdiK3rG6AQCczdYFn02m4hni3aLKb7pXYjeETcracByQgA23NYgoRCyBGRtAC/BsJ1fyM06z6NKPmNVT9rCn8HA+cKjhVs6IA6F58h+YUJxGHUjtN6u6u2WqwWy0nEYkRB0Ha5z/71ubxLyy/+rffubv2R09Ozi6o65CGzXSbs+85N4IWjv12n1NK0+RZd9s9gQtpoZrZGTqbvdujSm/c325Rxooyk24AHEWhn815H37+7KM43pmPzHv51I52ONqTZ2fr+FsqlsBSjL0TRaIIV1gAJbhjwunp6dXVpzllN1e1aZqaBT95vPzkk5eLM3zlK08k2tXNndqYDdxgsZIgnUhPTC8vn8UQCSxtWLILd5GbaczPr55NE05Xbd/3bdsHVpGw7JdCwbIhY/fMxzv+4Q9e/Otnf/biKfAcuAMYWKG0w6v9/hbzD4L7ATLh7K3Tr73z9a99/Wu/8Y2/vd3dvry+vL67/PEnH0w0hP3NSPn80er80VmMbG7TYBTC9eV+2GYoXr68DAIENIxVv1iftMnSdtyTkynSlKaUTrqw3w83Vxu782EYMGHyrLsU2vbwNsw0uxGK3lt56LUBq0MA0ZmNXZDEGIMiO3KV2XWkaSJHaJthO2YAgrR37MQtsoqQICB73u4HTBQ0ap7SqBDgoZ2u120Trq+vln1/0p9Ejmfr03GaXly9GIZhc3MbqLv44sVyuX706BGL3N7evLx6mUzdLGdvtVE1g0uIpj7sBowGZc6syjlln9STBunIhazmyalKXB0g6jo5yyirs3BWWGhCrPGLkZu751qxQvdDt5T0HApsQVqD1lzyIrWW58AiPI67f1IgH4LAHVZFgUyd6upTjzjQ6T/38L/GzY+2n37Zh2DzGL06RtCO//valeecj7HvUh1VQlp3FH7W8RfhyAT9DYD1c2x/FeTop6Cb5WV8tsawbIcXdtj58LIPP/+U7/0cjPaI5HU0Og/Jprk6mDFqctTKudJr3IrLyiXP7ZW/Um5EihaLGTKMiw7OPX5c+Ujklc1ZohIuJcQ5z12lABhi5IJ9MAnV6ym8La/KmnUtrFJWxUrMMtNU1V4KbFT4K2RgYiGgGAU3Nbe560rRUiQPbRHoLozechrLWlKLhagDAObm5kWaCgfmwqvvtL4peFVS53rRgYMz4PvamjobJkCo3KmhlFBWRpWj8nxB0Hlpn/NXxTtRzAXYdUp7FcnKORcTUDhrzCVLXLrHFc3S1yxReaIo7mR5gkU/hpm9VG0ysZBLYbnf3/HBmhxIZ0d8z/sBzHMHkHovs2vlcKrcp+Jn0vFDIyI1rdpYVa+hKN84Ecxr/yh1mIKEnImcLRvUWQiCyKJAdmu6xgvVz9nVSp8sENenIwRnFOTkkGOcyYBmueqrZrVkACggSKmGUzJiY1NnZ3fbjxMTuoWamakyNdOYjepydnV9Ha1zteakS1OaptTEyIFrNQpm9Kosk1acYIM5RxSKYnav9ECAXZhZc06TesJoacdDQOz6GEK+vrncDw/7k/bBGxe7P/44xNSvumnKql6YjmBnMAWHEYI3ixi6Ti1fD3eESvAkhmdY1tHGslSHEJhZtfR+K+0IrFCrhSlbbSF8lDABiRxPEyKYKggn6347vQzB3nxycTdsbzbGItvt3TBcx8bStG9jOD151C/WRMEyn19cnDSf3t7sNbubE2McjMmYYtf1IglgojFNeRyncRxVfLlqQmAzFaa+WQCcc05jzppVLU+aFdM0xiC7SduIIWO3mXTM436IW97vx0ePv3x5dXlze8fC2bKqjWOKkZ2o67pm0QF0e3v3MX0C6OPzB8t+uepPtre7OrjM0jTtNptlt3rr4RezjuO4W3Ttk0dv/KP/5D/653/wf1/f3K0f9eMwpSE1izalCV5oNyhDyIvgq1dFJ2TAIFKNIB0SfEyfV/vnRz6rFaCn9LL8CXHIYRa/aiIOpzlaPg5vsywEtelsIRRYqfNyV7VslmDuoYmleeIrHI35tHOVC6GILR5SoW5whtSvqr3ivAqpHKKjIkdRLwnEPmdNCNkcYrOYhUihg6pxFT4El9a40jjxfjcmzdIihEgxXj+/QoK2npLmSWG022/fffetX/7Vrz45e/Ltv/iD999//+7uJTRamkDRPZomWNMEhyVhKQXyaZymSVXVzcnAkTS7dGgXranf3I1tEHBo2tB3JOJnZ2ci7KbjNInIxcXFYrVkCiJwbZwAACAASURBVHebkTikZAzqmpjHNO2G3XbcbxMGFF08xBgXvOibk3W77BZuIU8gxri3ccRuk8ZpUBtDBAjTeAPsVTGpm+XFunVGiMGdUspl8U95TGkgDgxlAbE3bQNSVSU4XLOm/aBf+OLjcUjTzR6Qvl/2i3VSMuiia4c0/fjHl+SOqLGf+jW3IbatxhZEGMb09W/83byN3/uTzXvf+fC9736QbpplQJIpT+ZqzSJ6QaOLNm+pM61wqaRhdJd75ow5bK5Gr+tRGRdGEKrJXDrwfWvJNO6ZIIejSpb8kPSe7XIx5p50JGcHGwlRCMxMDktth5Hxo+9tv/DmR+/wYzsXIl+tVts8Xe22WXWckFXRxCawaSJMZe1LyeBDRHuyXgXiPORpHNRwc3uXpruT9dn5+cnF2cO/+P63VeOQPJulbGpwx5TQlM4r2aXGT8SBu4BuidjlEDlyR3n5J//6/W/90Q8xQZr1OG3MptC4EIxRsg+q8FwIQUyltEacyG0CmaFqac9Egkqkvp/U1Qk49i8K9YYPwZ97aRFUCsWtshMcZZ0ULgp1xb0BNI0HcD5PEwWhIAE05QxzpckS5VRVCprYLCWklJMqMzMFqkI4JStljiJLXG3ZXJ5Tuu6U+rqZLjH3fn1le/UD8rnOrQ4cO7JJ8+3We8HsfdemZOTgeoDOg0qojF3LEAw7v73WJpxoZoetVrjZpgLewhuCay5qGR6Indy1VIDVZO3RRdUC7frrgUziswUmwBVhZh/O8cVxFIp7d47pWEbj1b/eh7KfC/4dhbJz8HBIu9AROFgXBmYWpuK0EzGMTTPIQ2APQQddLHp7YVOaiCOTunlK+zGNGrBeh0XvWcfYaiSwwAnE5lC1xAi3t1j2vljEro+WbL8bb4fdtFdmevz45MH5AyKehtw0nsfp6sVV5NhKnwcfN7vh5ZDudHfVyO3EkO40OIdJLY0JbO4O9TAWPjgLsam7sxtsSsP19N53f3D57EW/7GPHF4/OHj95+MV337wZbp5fP73avaRoztlMhmHcbgYiWfRdHnd5VOxAK4rsbZA2SCQygEFCFoWHYQ/HOI3TNqec2tBGCZNnUy1yrvX1e9V/YxAzqVY5fjB7WW2LfgfqODEgTZO7l/pCh6c8MohZzDNMNQcAUbrVYi1omtBw2i9Pegv58uklJuJIIbQKTZTb2LIQ3E9Pzrsmwny32QQSbiV5Wp2uYRinNPhoo+2f7k4vzkaMW98NeTCzBm27WNhusGriCUrI1SQRCTN5YKeIVH2V4irMg7MGHuVXf3WUHgZtBVCrsfIS5tHxjvPBNAcMXJy2eZ4DmKvVX5lER5PFXzGS8+c+y84U7KZGWDT7Q/TqhRxPLivdcl/vM/izbD8Fo/hL9/lsuPea3Sjba1Lxr5iCo1PR3N8Q9QX5/QM8ujH62UXc/2b7/287XhsOQ/YAVRJRSulQEXr40//nMUqfEWYD5hSUYZ7NVKkxBMXs/RGIRISYycjMyElrXRh5Yc04NGl2pSYEy1m1JsW91OUWBncptXZ3MyEu3atAkMCzcpNWD5FBUv7nJrURCebwCaXfVFXhrM+Qo1AxOuQEr+zXkmSQWZIADjX4rNd0WIUblMY+8IPJKFLu5RaKmB9VdhUAJq7qAD4zCQDcY/sHaIlLbEU07UbdG7E4aWVDCTXSMAng2ZHN3T1b1lyAJA4iBIaU7y3ZPa8BXgYtZn8LbsXl4lrGWCBCAGqK2t6mvsfCicqqdET/BuCWq/UtbXtKyCgVqSQhEioq9E3bFrOeU21EXfAOMzcFkR1GrLnNiu/HzNJaTli08p2cZ3eq+MLmpf5jfqKzp1U8J5QldX7I9S06mTgxgwrHyJkBoeIhZrWu6UytDHIj06x1CWMCGLl00y1qHvP7rBXyJVgyJjEueVImKb16iAqgEAnueVTQrKSm5kWGP3DXRSifnq2vb++ypecvn3/h4dtf+/pXv/cn3yUhFnYDMavZvQtXVsWUAIcYAphDjOwE10mEWNiyqZo7XI0M7qSj7nWI4os+ppSfPv/kjbfeODk5/+ovvfud73zQ0GK7uTNkVXVyopZF8pgocGzC6MnNQoir9XLoVScrHVFFxAWW1VyHYSCmpmkDh2E/mLkQM5HXloRl6BzNqfKEqaJ3VlBuAjFUAUcIMtxsROytNx7dDct29eZuP97dPb+9u9JhmyYEsaxJFSHEm+ubt99+++rj4ZvX3y4opLtvN4O798tuHCYQYgwAiLDfZTM0EX2/iDFsd3cAmrZZ9ktm1qx3t5vbm02elAiSQ7dq97o9WXcyDNdX1zoNQN7t78zyO+98hUO4uUvX1zs15Lezp0lCZKK+75umtZy2291+uzVPrYTFol8s+gcXD0Q4sO+2O3dfdMsgopZVU8rjZnMT4/I//c/+0Vtvffn/+N//+Xsf/IUwx9Dud0OIoppzLuIKpaEekaG0Ja0+E89L+Yw8+2wcX/XHvIDHQFUrmyGeGqW9lsqjubTgcwKPQxEHHRpy1UUKmBXLCk/VCVYqOAu07FCUxtWW88GRBBE7qr09WIV7WihqSWLFUAukVYp7japUXTnZ3E+sULOsmAU/oNDuoFhAe3ZDkfiRUgdlBBgcTCQxqLqpQy1P7kRNiMKxX6zakyZwc/3yan+5a2ITlvm3f/M3/v7f+60d337/+9+9ub68fPliu92pw5SJA3tg1hBgOTMLFCkrJ8056zQiUL9YOOVhnx5cLEl8v9/nbF2kcZzWfds8vpjG66w+DvthGKY0dV23WrWnq5NFt9ruht1++tGHz3bbvVkUNvcpTYkdbS9t00oIp48eZVdHck/b28F0iK13HWe13QZ3t0kC3MiFIKUHb64hjLgwK1zVxnF3fb3d7jT2cYSTTFzUxNvQNELkKSedsoTYxCZKFyUv++V2c6U5nZ8/PD1/uN/h5tnNNHmMTU7p6fMtFE2PR3HJzp6GUS11qV89OHnjUR6X3/uzp3/6h+9/+BefjpuhaVvnZOiYPeccAqekmhJQybxMEGYRCRzvtjspTBaaM1KHIc2gIrJdYkgYsxQ9XyrjqdTwEoHYuSjQ1SYWxkRFsns+YyX1MRMxgx3Znb10vXGDsSWXhtk6oWG4tT//5kd9vzjtyBqcnKy3aRev912nqz6mKVsbsiEln0YPLcVIzAgSApMwBxZhFkHbxNPletE1MWIcp5cvbqfJiNgUw5Cz2WoVuxi6yOfLGLA/Wa6R9iP2TaP9SlZtt1o2i4Zb4RYtbPGv/sV3/vhbPzhdnIuEpslBOPk2RCkajPMqTKVvCaCVR1gaNRwU3O8d0tmNOgDcdmhNe7/gV4YkFchrXteLYmoNTLhO8AOwUr1HTxlcPBCHTQZAiFQrZpYnOLkQkAGgbZo2dvs0Kgah0HFXQSZoST7el8TXtf4QJVUiKw6ygMeL2f2tfB6k9QokX8QPHJjLvkubmBJhFqtVpNMP5ypujxk8m2NxIpPlBnjx6d2P3vu0fdK5Uez44uFqe7lBhG+L3qiBrBGxAj85EZFarsaZ5tpsB+5Fpl5Zm8sDqHht9XU/S7Koi0WFtmZtH8x3VJ5gEWM+oFdHT+P1x/UaelV9rPpFXIQ6Kk+NwEwhiJlqBtxVVVOWhmMTEeN+Gpu4sAzPFkNjrUAZwVYP5OLJ+WrdxTYhDeuAtl04dDdOOXnOg2oiNKenbYyx7/uuXzDJfjvst+Od7E09hLjfTsN22u0GAYLYsj3pZJF2evNss3mx3zzfYQrYM409J5kshMhRLO0zWNoQ3A0DQKi92rMxS+CQM2Prl7eXL59dosG6X7z5xpu3l5v1o+XiYXjnnXfeXX7l6vbyg48+uLq+8owQOoJM477tu7PTxWbcrE+6GD3ERETDfphsIqcg0rXN7XbXLxfEnjxJDB132tjkA5wRXGtn8aKVBPMSP5Gbm5oIg5lQ9cvvk2HkIE/jSMKBmUQcbopAgYnGcaAowkHHqY3d2cl5sJh8vx+GJXUcJe+NA0hRJl8ho2XNAjlZnOw2m9unW1Md1qldt7u7oX+zZxbHNIz7u92tA81JE5oYF0FDMDhndrWUsk5Z9wlgKukKhys8GzI8l9afsztRbPrse9D9IJz9J8xTf77pGeMmRm0p47U/e9nR1TH3rqnoe63PdRTeQEWaSgT7OsD/ml2ZAWVAZzfPMUsllBVnRt1mcPlVCzuHgW6v0FzwV95+Emh1vB0qAQ+/Yo74Dh8e4KrjXoQ+i8cffrUqW0kHoKNgggcgkean8ZcAWMdYmh9tx3/96Ycf43CvHfuzPJR/T7bjJ/maFH/5a6HY1Z73R7jV8SM9bK99ckzAI6IQwmG4lNMWRhKRMEiL33/wLUCOAtszBZIYiuNGTEKl6584WQWwxFlqLOKwSdXcqzhhnbtEcDDbwXSoWZFed3CQECIFcoIXgggRgoMdUiZlxfUMADlLWfrdPZdgSggUOKXMxE6lkWJBrwEhhZaSODOHluspy29xI5iIkAmw4icJUWGAB3A2FybhUNsZlrytW8meleTbWPhkBCpFjlZFsAEyNWFh8DSmtJls1OCBYtCU1D3GECWUW2Njgahlg8O1SOFXR654XEzCZfGwgsREiigtogEhIi6tGImFvfiR8NpukcFO6mRFfN9NyM1c1Q6pCfFIlefqxSGqikb1Vr008mZiETHNWU3NmViYmcjgrga10j3M3b0KgBocdqgTlVq0We149spfr/FzkfRBdYnLO0JdQWg+YaHmzYIb81o0qThJI06us0aHK9xJnKBEVhsrQq3I2hcuULkrDzBzSF2PCHM3AnImOJkWcZ4iuF8WKicqjed8NPFIBHbKgIAysbMjsGQEqJuK0in2uhvydnn2i2vp3/umTItkRE7sCKZaRDqYyQFXBWUKTEFAbuZmAnbhJsbG3JuWiWkcJiM1VFWNMVvKwdFxCNe317d3m7e++NbZxfJ3/8FvPvvk5Xvf3Wz2uesDcTumFGPbdf3d9a312kS+vrkeNZyen4VWxjGbawhRQABMaBqnlNNyvQgLGcZRo4FcVU3h5CQ1UAdJdfL54AMpvBq2MnhK/y+0kNjcbjZKQ7eIbdt1xsaUfOmcYZHYV92i6/q+W4Lybnv1+NHbDx/1aECJ4d5LLxx2m5vz8/Ob2+dNF0WkOL4uEMGiaSNHMtYJ7p6ioqOmjdRFtWmYKvZIZm1jXYzrk/j4cffBR+9/6UtvbDf7q7vny+WCoz14dLLZ3g7jbhxweXn56PGDRXsqEsw5MhLgbsO0u7zk0/X61HII8eTs1NXILU+IaLtm0UgEsaoOw7aJQXX/5ttnv/U7v5rTdve/XD17fg0hToByGxsn313uQh8tZXKwWnDxCruXBhUlHiykxAq4VkpoddsKJCF1Fa541ywsfE+ZP2gM1/lUpV21SJM6+L6e19Tc1c2hdW4WV8JCRX1NHeZuhAxSeHIoYGBQYEp+30QCqLoxJfUxO3VefQev1r7YZhLKOuu4FEzUYdWRcCo628VUlLnjDnc7QHzF5JBzgeDZtLSKr8J37sylXY8lBwdxJo4YiUCavOnbJsZnH123LQybv/93/u47X37UNxTJnn/6yZSG3W7aTSlnGibKOo2TTkPKRp7hrpatb3qiOE47eFw0LblPowamh4/OKNj+7jYP1pw2rhrjKjC226vbzbC5uU3TFEMkt65B6Jv1SXtydnZ1ebvf7fernJNvd0O7oG4BV8TYNE0jErs1X99s97ud04QopDTsp9shu/uU8fJ21/ccooiYRBBYEDlIIBjU4LFtzOzmZv/ypTYNxl1CRLAQvV11p23XqE7DMKbkrsFy8JFjaM765fZl9iFCY9vGB4/Pv/2dD++m3Wavvp1SyswIDdZ96AKftScvnt0FQnf64OH6zZPu4b/4Z3/44fcv3/v+i82LDA2x6QxoezSNBFHLSuoBsfj3pTUgO0Gp5MBqsF71L8lREuKVCeT35aRFs88dVgQkGTOwW10KECBFzs9c5zqwOpvKWCxxPky5MHoCqpgTFzOvE0yx3+D9/fbJwxfe81fe+Or1eHfSxbN1M2lqo/bLlrlJo407nkYYPIquV23XhhBjmpJEbtvezbqu61frRRPV8jCO27w7O30zK5xvnZKE0HbciC87XkY67U/6hkUCe1602xNsV9yt0a2w6NH0WH7ve88/+fj2ZtifnpLySOQksOw5G+ARcIObOgnI6jO9X4+rj+gOMkdB+6hoWxa4ueQAMc/wI7ikQjcFwSKam+WUOGVeTMtybkqltKfuYFKAkMJLB9Sz5dLigwyxbYQoW1ZXCQAha3bSIG6amBt4LTEtKTYrlPvSsqZibVxhrHLZM55SefBHHnWF1l/zulEUNgjHsXCexTtnw3aAbWriFcBc6HekfWnmPlFSIhv85uXwR//yz/7jf/L3NuMN9X7y+IF8lDEO0ZnTOFom8ezBa3tlgzuTeHVTy3sQVF+wjNqafijW291hNGeeajgAuAQm8pRzmQ8zuliyd9V5Lq69c/3NMAOK5HOexeEEA8iJuZD6Ua14hfbmh5LgpWhUqggQKZERVSHtmRg4to3s1Zquh3i2AQmr5otBH5BtiJ1bmlRjDOtl9+B8HRuk/U1KWbN3bTQLTDyKp8wpe7bUC0lI3OzRULNYhlUftzGRbq6G66u7afMSk6cBecDDi/Mvf+lNzvTps6ebD+/STrGZZVZAxs6wnClnLU/dZkI9EapaBYoTlByGIXKO5okId9f7u09/iAic4UtffvjOr/zC2199e9mdvfHIu+b08uqKBVOeZEVNi34tMnZBQhBq25Yj7e722/0UuhBayZ6X533Xr7a3IxbaSPStITpFssmJQulBXvreMMOczNTNODixO7QuvVSS9FSaC1SAF15IXjEGEGdVVrIMUlIodw6DmZmgWy7u9jfbcdvvu8BkXvv3JM3Zfdm1aZfdXbN5Si8+uZ62GRN2L6YQKcODhmTJBRzdVBuKvsvSSUwgcEIa9yMl081kSSWLJkUiNhYTyvBRdVJXJ2ew1HFYhj5qG006oEmlpUHxSvxo9lZQ1wsgVO+/5NzrJK6J2MP+NDeWofov16KNOaKa5VfniV78mNm0HrTIih050DXnOeQz2FzgRJ89n+IOvRL4//WiKwfA4YAIHfCm4z8V8s0xFHUMXb2Gchxf5/FRh51ri+35kc7F3TigdOWl/kQA67P41AGK+ty//pTzvIbD/bWAgv/ObMcAH2YAC0dP6fiBH3Z77dfP7vnZA8vPx+puh93MIFKjnoJaFX8wwDOVZcU9CAeURtRFx4AhDlLAYcReFPG46NcJjYNWhpQDXjkyPgcjYFAQVxOJzsGQRISDgOHk1khRfTKGi9WuCl6pMaazYSg1bnOirGBrEmsmry6FgFdtF/LitZR1pE5/oLhNXBGe0pyCwTwXLDMklD0OxZVlMydolWhxLvdaI0lCqWYo1oUdjAB3n+CTeXLzIoVaqV5milq/6cAsoVANJszN3LVq00qtGCw7mdZ8cJWlrpmGmdMKdSNAmNzN1SpXokR2BGYGWaWrgmzGgop51+rjAfB7wX4QyLm2xZhjYRzlJGmmnZWfGaUScNaWcAAy18hVxp8dnkQ12X5EkZ3PP68mag5AZrcXs2GjkgwxiLGJBlNSN6GD2YGkbSpnLbjt3INoxgRKJ3Cymqq0ct/lHszrxaozDEBJOZcGQsIgEHtgYmdSy9mRkSebhpzyFLomq2XNk++9x2ijOfbpbtn2zVu8v/bkibitqm0gstKI092tSs4RYJ6TTUOmCBEydaXcxBCbmD1TSswwmZdfAcfYLHC7x9XtTbLx9PzhL33j3QcPz4Twzf/nT3LKq/VZvvVF1zmRB7TtYpy2u92GI09Dy8LqqqaSpRTTRhHE4DmFhrnllJN5BsSKHHhBAmsWlwAYAzTrclc/oCzOZAJzaxuWtWWzzXY35Ot+4kT2vfc+DrGNLa3W6649axqKEslIwGqjCMUmn17I249Wzz7ek4Qia6ATxn0aRgVbiGJKzLxcnERBEJt205TTNEyA7GjPJCnH2AWQdgvhQESAoe85xEXfhW4RrjbPvhQfUuMu2UU3u6sQ6K23Ltyny6urNG0tn8IU4DwOXWgiCZnu2c39dnvnjPVytVwsQtN0HMll2k0EIZIgMUokopymq6vnX/tqfOvR2W//5q9cPX/6f/3B7z99b1qctm3bDMMkTSQhcYEaEcgKRlygGNxzHkowWKMh49mwUWEklak4Z1MP2mpOVbUPFe+iYoL4PgNZtX9qfEEAlyymkzLMYaUzBIlDoxexszrPDapgA5xdHVoaXxW3xI7yunDUOmGvmZM63bkMoOre2QxCHLmZTl5tXXGGGFbVU2tcVMwn4eh+UEENRiFaMh8KzwGYzu4pWWZtOJNPyOrjzfblXW5FdDHcfhvf+Idf+PVf//q7v/DW/uby8sV2t9ulnCY3ozBoThnDlKfJcspJmdyRLWdv29IuN0iAkKhNebLTh7Jcd4DmvOsaP1kthEXVVH07WJAOtCMYecgTDbvMktt+EWLol92bbz1yYJymKWtKeb8bcnZzcnMDff+9HwIqDZqu6zoJgdV9mCZzhAYZSA4mTwZLVZiOmVmEhSVybOKUdEqaElYrmFMM0jf9sl8vmmVWvb2Zttsds3TN0pRvN4Ppftuhi03bL5etwLHdbV5eP7u6m/YDwWJhCLcNnZ51Ty7OT7pui3a1WDw8ebIIF+NW/+UffpsHuIPb4KnLFoMEcRcX05SGDGdyJleASIulLE5Q1UqDH5wiOqAF8yJMCjDxDK+UWeCHJWYeJ1JcICInsFtxMbw6PYW1N7tPCnMqZTnOKCKcDEc2hyqV5WjEy0+2yycNDYs2TNbo2QlPDiILkuGNZ8CDcGwjBTY4AssidkRh1a+7qHR+QUTb7ebq8i5EOTs7efT4yUvkcZi40S5nCamLcdqnu+u7k0fNor3IaReCNjGv+nHAGLZBN0qBm77taPU//d7/9unzawh2accCKGcPSUFqImCGm5s5s3ttgFU8Ap65UqhWobTlIjp+fDPD8+B20gGkqIaE5lfjIOeKYjkd8KOysc++RPWjSAnw+fQ+95xmIiehECWQk7FBkHXKmlQNZGBTG720HzSflfvq97Lz7EITDpd1b2RAxSs4igk/NzZ0x1Hn4MOHM0ViNqqzxT0YZfgx3WmG9Q22t33J/+jeP/rxZb/sL7cf2yI0qwVihA1MFGDmquS5iJSWWgQFeVl33cxnXNZKMhFEUgVfZ2jJZE7/gapqqdfrE0LpI0QV+S0OJO7nS/WhvRjimi+dPdf7fR2HUgg/uNGzZ1d/U/f5GhFRiznr9LV5ZglpiISBnNk1JYxwLMJFK+eBPx5pdGFji03szxaLs9jIlBrNk017EyTyEGNDQhEhm2se4VsRGE37NCaehPvMBJFxGkkbGslH6jTGbrWw092z7Nu0/2SfL0edCIoKTXlSlJwKKRhCgOeS/yXnkqVhY4a5KQxGXXPKOqUkbjkyLKhl9wkfjS8uX9y+/+HHX/jFL37hK19s5LRfnP3g/e88v3phjtU5UqDYdDkpQIumD5FD27EmBJj4pNN6tWhXYTvueWGhdU7GEdyI70nA5qlAAnOPFC2tDZgBcTMqSR8SdxgXu2kVo0YDmJtqYjCzeZ2ai36RkDUY1pAlEDM3Jhld2zrAFM7O13fNbQtZNSdh0UgTdbScNY823O2nuxwsejZKbDunaHoHNLzs22YpyzxdP7/ZvridJIxp1ywjiey2Gx+NE7ORZ9U9SD2SsDMpTJOrQwEu+lG4n18l73xoSlg+I6fC4TpMweJHl598pjscISh+CIYAAMzEM+ODADCx8TwhC0w+N4Pwe3NQ/ZjZtNy3sT/y0zBfwuHgA5pIdL8LZvkFPfxeTdDPB9d87vZTDj9Gpl7DIo6RrM+e5zXE6rUdDkmCGlrSUecHP7xHws+ugXU4daGKHcMiP+OxB47Zz3Xsv/Pb4RW+hlu9tsPxdsBBf9IOmNvD0VyQeNhKZelnDnnlA5/FeoqmNwsQCJFZRFgCk6qCKMZQaABaYJayhjGJMAceeapsrSI7JeylNr80/HMRsJeLKVBCCSqYslsIkk0dIAEFAKWt4IGcCS9EmFeCOIAMyGGxcKLSaKNEYwUCouIBBRCBLOTs6pVLZXB3BWEZltlyEWEqM6h8aYiRiLIlVSWuMof3CbNDIq2Yq/vwrA50gGDmuSQA3RVaWCsJyEhIJb7zmWzKYFBB6/kea6MqyFEk7qg8EavKHXrojDz3s645NTIiArlprWfDbLjVjRuuNPcSXDK5ehHUB7uTE5mzgxli0oiESrMi4pS1JrsrKFkuzSUy2MhDhdCZXNwLFe9A3K1SNAR3U6tLQe2oVhRKSq0ZUFU9DwlRmBo5l5tzBkG40nrdSihqcK1A3txjpDxY2m32RXaNiYlJIARKVrssAuSlgm/+xwkKJzLAhcAMYVYmL6OzKMGZEaTtWinaJzahdjvDsB+yTfvB3nyryzCJ1HMf4rS9Thjw6YunD+js137rl37/f/0jh4IyfKbEOFVxM6/56KKYAbiqEpPD814p6mLZxhC6GDNPFh3CmomI276NXej72G3j1fX18+cv3377K9/4tXf3vzB8+a0vxzb+8b/59t3tJoQmpaTmy9X69HT5yad7sRCpHXeTmTAznKdpEqJWOgmRm1DLLYEmtnszYpCYmUKdhBjOzlbJOffzo7AfHM4iEhpT96z9cvXo7ZPb3e122F7dXXV7a9bdd77/0eNH3eMnj87Wp/2yC8ymeb8fpmHDiIu43GwvL95YvvvuF18+/QHIh3EI1DDH6+uNE/I0r9kIXSMxBpje3t5sdwoHRzXdD8O+7cLypO+6uOgXC7SAq9py2bMQs6acxmG/3w9tjDDfb3diiCE+uLjol6tnz54/f/5yHMerF5cSIhwioVt0fd8NY59ycvc0dEYFvAAAIABJREFUTWMYo0js4+nZWdsuhs2oU4IhxNh3/SK2MJuG4Q9+/59dXDz5tV/+5Xffefd3f/c/+K/+6//m6nJKdyNL40MmI3LOpswipWsB00xDcufDKn9wI+jAaiCakXm8vqYALiJAgcHqugCg9Nm8TzjNeafP819ewfNJS2Wzoagj11xDEcMqLgezs5tLkBmoqpNuhuNxjzYUqOqQVayhGFdXr2LHNJf3FDbDDGO5z6r1RyFSLRADsaEUEsLL4khSAjPYLNlIAFEAWLNNeQA8hraNIQ3b3/5b37h958V//9/+dwvhcbz84MOX3/7Ot6+vbqc8KqBO05jHCSmTWRGm0RgDFEDWrC71cU5TgmQkPHnjjfXqZD/spzQ9frI6P7/IadzttjmP2x2apmlia1OapimlnHMe8zTmBIKqxhhjjGq0G26zJhF2mE5pGKchTcJ+erZerZZONIz7YdzlnNURWsQGbYu2lbaLISiQ3JhFQmhiG0Nkig5Xy95E6jqslgtwCJH7ftW2nWa7url9+unL7c5O10334DQnu77cX10NU7759V/+Urvo2HBzvXlx+6P9brjbOSYAGoIsezk5iafr5TQML7a7t9/88jtf+NKD9fmPfvDjf/X7f/DiQ8QAziDALMMzCQuzu+ecU1YujSHmFGzpmOxmcBPMqfBXXRuex+7sef4crvzczpAAWFmZX5sDJG4OKv1KBHBASxorpwxGjJgm/Oj96+5R++Ljzdu/+oT8xcVJopjvNuNwd5t09IGnKYGMIMwBCJud3txej+Ow6E7yRMNwt16tHj66ePTkQbdoWDgbOejk9PxrX/vFi9V6xPbm9oVrPl8tFszD5kXSUTgn1xBDDHG/H7cWdR0jrQT9//g/fPPsDXQhjimRoyE2M+GqUnmfF/RKgSIvBCsG3OaejEdZqs8vp5g/fCXrB3czO3SLwOe+s8/biML8HgAcdaSp+TgHKIRGs5nllGrPFyZnhGmf6+UUw+AzMlYv0d18zrPWS57XYg8sXgGaozjy5wxe6PiHY7+diD73VARG8Anc8ssXIyawi2ewy6rvu7YF3xFgqlwtPR2LDxbc0VylZo5z+eqSvjyQGjDf7GGt1vmJHnBJZjbX46jkLwuGZ3TqflR8ZgH5S174fex+GI1Uc3sIcSkS4WNWNWRZQB/AaWpaxGhIe3Nq29Vy3Z2edbF1EcTQpUHNch7V3EPoJESKjRGZhv3Ntu9XSrwd03a7S+NgGoet3+38YYxN2zL4Yv1Q0F1+evutb38LO0iCT3D1qjtfzIK5qcOrUvcMUrgVJG5+aqGAGkGur+/ImcFNWIjAyBQ502SDbz6aNs8//tF7H5+/8b2v/dLXzx6fvPuFr33ly18abH99d/3Rhy9XD+TudgfLSaeTk44btBwUmpC5QWjJRT3k2HGjgRYsC5LO82isnHONlRxmVnqCGYiYhTgwkbupmoGrUqAD5MTuaiGElDVlw2gQJhYxD+SLVcNiN3l//kZ/8qQLbdrlHWhc9g2TIqHvun27s+zdyeL04nyY0tNPn1l2zrK52sAo7xODhQnuebLb61u0OFmvFk3fSP707ub57U1hEJ49oriQNLhtp4YjnKdhwgQDjEpX04MH+BNGWTXpr0/ie+D91dFqVbSlno0+cxRX74Jgs0gDi1aieZ0C9xJ5h7zKjADXPXwGxj5/c+g9Rx3zIVSBtntT/Jo00L+d7TDZj5/pofbrGJY6xqru/czP2177/LDna/bn5wCwjo//uSC9v8qx/z5sP2U5PPzpGHiimUhVskmfHQQ1SCcqA/owVnCElL2GJJbV1A+4dJnIgYUJgRCqxlWZijZPaiu5HFL4wWqUPLsw0QHAqixKBjmVYj0ymLnDs2dzy6TCAVKQKuUgVOBosRJsODtZFXLR0mKPUcGXGTAnwJldqNasVQ4moXwVrIgXV1CADFTL7csjLcRahhgZvCybpZyzdGkkVzc3kQCAZmqCF/ICk8JnOfsaK7nDzdWVOJhqnnKaEgHEVNTDy2pXojNHYY0RA1R1yUutb0XHSk1ZcUCYwMJmbFTbQbrVIuHXYU0qkM7M7jqgM7h3EKoBZGKwuVuuAwYCZwaXNKbEpuGI0qWSmdRzcYRKd5gKTbkzEyG4HdIDs1b+kaKruxdF/ftxyzPQdDQgac7hzZdMQAG0ig471aJSMFVFEy9l/VCrHFy7F+xwclKGFylZeG1iRmRExkVPonCAnQjsuH9OXjh9xMxS6TpFiBpz7rm01lN1q8WwnDUz/l/y3qzntiS5DlsRmbmHc84337Grqqvn6ubUBpqDRUkQLIq2ZIgwCMuS/Wb7gQDhNz8Y8IMN+F/4Zwi2YYC2JdqiBYoWRUvsbqK7WV1dc926937jGfaQGRF+yNz7O3eo6upq2y/cF7jfdM4+e+fOjIxYsWKFy4kgUfHeL+tl7athGDE+2aZ0ufmYquHLX3kdSwRhU02DwpiNyBxliSpiyfsjk4HIW/CePY8yJBU2SFL1qmogOA8GsUfwvl2EUHmRWNftMGw+/vjJk8dPXr37Za3D6dnJG298Y7Me/uh//X5zmPrupm4aV3k6WC2rpfMWtCLhNI7ZzqRB1czXoqLknOMgAkR1xJ6DUiQ2Iis0tfJYpv35NsooTBoER4BSAqFa1Pfu3z+/vhg1CWxQWVTVvTt8eLhqqgqGvhslShzj2HfjEKsQKu/PLz9aLA4OjkLVUt+PlsCuJl+NQ/ShUjVSMlWzqAqVwpMvfaEMKpk8lNh3jsFNIDIRYRcMFGNSHVRHxihJ2QcRiX2qXRi7ITi/Ojy8e+eeCF1dXp2fn1d1e3x8QmbBeVfXPniR2C4WTVMzUdf14zgetqvFYnlycKJJx10vg3jvq1DlmfXgzuluuz1//MErD770m7/6nb/7W//e//m///FbPzqvTziOEeoNDAowKGWxtmnaudv9dC8uytj1bV00aF5De9sKcjg2RXG3PMrJGBah0xd3pE88SImz+6iELAQnRErQLPOfU+s8cSqQkwNk2YJQ8ccMRmAj2WtxWOCqnP+YA74pITqJCROYssDM3AUMZsSU+8yWHaKA7ZhUGCbl2sndtRzHChtISUSTidSLqgkOka+fPv2H/+h3d9fXH1099kEvr64+/OjRENN6t2sWKwWNUcdoapr3YFFjODCBjdkBBElaAIEIxp07d9pFO45RVU6O7zZttYld33cxDjFCTYlZDWOMBGLmvh9GiTElkVRVDTHW211Mo/POu8DMoXbEgSNe+9IqhJqZxzhiTDGNSeArhArtgprWN22o6wCwSA6eDKTsjZ2xqqqw48XCHx5itVqSczndsNvs+rG/vN6sbzIY4FPEsEt9ZxqJ1foB6em2j31nG3FyuDoV3W3WA5FbLtqjVaiCShorVznnj1YnccCH1+dvv/nh+cdoG+iINEKSEHmzUYXGgZ138/6VdyiYpWkOz8nYF2ZkmSbz3zLW8RkxrL0cVdlJbWqgl3NW0+KoJrAD04yyeX0BjKj9GjcX+uHbF9/8zhu7frsITbR6ez04JFITZbKsOqApeanqJEISmubw7O6d4Fzfd6pyedU9ebwGaahQ+wb94oP3HoH04Rfu3rlzdu/szsnhsaO67zfn513XbA5XEJMINWEzctw24RhYXo4D1hhPHPvQVpxsgFjwgUOlljtCZ3tAlpVYJv0Jm5HeybOi2bd/0VKUZNl+fJZHkQDMClgvDTFpdummxziNtj1nyfLWqKZxjLM0pgGiSXJhIBN7lpQsu6ZT9Rxywz8r3Syp1MBNZshuZwv5kgpUnTkAn5hU/qRf7sE/twBWPo+9+GIiIoao0+BcsF7URCPGPvmmbprm6HAFfWpqJEaOSad04NwJJ5eBTzbSJsAft7tEhrEIuSUILAMvbu/ubFLLnb+fb+WnQZa3dzTDjD/LYVNzhdxjlEwzTEBEDsjNMA0wZb1zevDaLx2tN0+j3BgNBnNsVa1VULG+G8bKa8UxWUwifRQVMrAnz3lfZSb2oao98W6QYTts1goVr/50sajRwFPFtSc/ruP26RofARFUofJMtdvtYukiQVk9RKehyunQCQPO6G9RlaW8MwuI4IiZwKYmUQSqzDYKaqBmbHD5k8vvX33vzmtnf/1v/8ZmuH7zL998cnXxxS+9cnl1HaOmwRI20frFynHQZIk9qrZCZX0c4CTUzkWYV1eDW0IvMozZHmawRsgMEMARgxzYOULUEpslyl1Q8sooMqZCBM8gwOWuUEgqHTolqRa498rh2YNmdOO4uY6ybhoPpq7bYWB42vYddiye+n7oUn+yOHXqbp5cMQWVkcmzDww1MxkECul13A7b9RZD9iVgZrFKjkKQEAVxNEsjYpksCgA64c15fCmZTO75NCeNhG6JShOGPSt8vmQ+fvqvZ/wIgM31J/yMdcvgN2ZG++0ZbNYKvMV7X/phL/v9/u42C0t9boBlHxCYv/mMZ7PpwPOm7CXgz/wbm5rRfZareu5l+SSfFcB67q5ePN1nP8nne+9fkePFSbM/8nNuZP/Zf/p47k+RjF499+Iyw/LWDSneAsEIzjk44sDmIASBlNYpgBFMoxVRJJr/5VOa5bYbGcBiUK6TB1NWDyI1UWTahplTMDiAA4HY1MhblsYigrDk3YrYyGXl9GyfrCQMM/pSLAQpqZBabjVvxlqgJKhBiCTrpmQVXyIADgRyKDIxKCV02VdWVSn9qQp6SCCQI2ipQc6CXJhLC6hEl5zdIYOqAM7U0igalVIGdQBFjjoIFPtRy7AVbC7/x6XXj2Z8aaK/J8tVkWzIvQLnTOT0RIufbqW0sdg5yuJKk7a6FjVjAGUbhpJlKAjEZsTEmh8cMXzlwYYkCiVymjfmUt1pakzInm9WFJnqEbPuNKabyW5k7myECVnLHB1XRChyQ6DJ/y3zUSdPKH/l0ocwb0i5MyazKZSM2BRIBkellDJHy2ZFayyTvjOyB5S26oKMA7HLDfQm19tKiYMDiNmxhyND4uwCUs7Kk4nGrNDM5qpQBWbPwXvzCtfDqK7rw9VBU9XjONgoi/oG0gvW4Pjw4Sr12F2NqR8ZznEgzQWqTMRSdmKGM/JUVTU5RBkhUCAOkQgpJWJjhmcLFBZts1zVVcVX1zc5LHry+OLHb/3k9Ve/MnTxow8/3mw23/zWG//yX32/3yQMiDQO6/4meCaqKFBiUwzD4H2gukLUFFWTJRLPjtmPMSZTqnK7SCISw6zBakQv2WmLyQAbkWRN7wbtQXN67+jJxWN1VrW1Edj5B1+4433NbH0/FgqcoQpt8LX3ZE667tqGSAF3H4a33xnJw1ThA4zSMORAU0FJE0VLMXnP3ju34hR10llRGDTpOESDmiVJY3t4PCaJcZTUe9aDRdu2bRUCk+vGbe3PosXNzbqqWu9cu1hs1juRnalVVa2qwXswE8ixX7TtarUSSVcXlzdX28NmVYXqeHXUVu3YDpvrjUZJkgggg9NYs3Tr83R05+Do5Hf//t+7f3r/D//pH//p9/4CPZYnB7tdHziYh+hYiv6YYQLN9nCvYodAYCurGNngTobx5V7YBHMDE6u9oDgG/Vm2adK8ypjETEAFwMppAi6TIpe5TLFihqtKjPXsnLGcyMiqJxl9yhmQUm046UbkCZc5GZStajHiueaImJjB7IyRq4Bz2J2paZg+WDXXETIRODM3FZbNRO5MqOPQjb/8jW/9jb/+a7/5a9+JY0ekN+ubDz788N133ydf+aoVQT/Erkt9b8zeNFs6i0Mk9gRyzhG5Ip8nBkZ9gsPDw2z2mKlt6xSjqMSYUopVhd1uJ6JEjtk5JmYPsCpJshh1HHZjGje7nZn6ELz3kzkyI/jA224rkrznxbKuWz/Gfkx9qBEChQpEEtU0qUQdBpWUvIuhdz7Q0UmtFkPdrFbV0QHaZSAKorbr+81ue3W96wYwoamd5yp2NnTmuDlcLZzzH757aYjNQVidHaCy1eExKATeEfPBqj1sQ4rbrrteLe8drY4Ol8c3TzfnH9ycP+7uHb5+8cE7HCGRKlezr8ZRUhphHFAZzGWwVbNIlyFj+phIVs9JhpfZ8QwK+0mr4CXrAprb4WGaTgXkJABKed80kDmYz2JZgIIEJKrCxuQAhUmesri+iD/8/kd/5z9oOfnKuda7QHp6tpTRS+8kkZolxFC3q4PTzLaTUbdbjUO6ue5iHLbdUwB1FdqFW9R4/HZ//nRbVxR8P2yvHv1k17jlgzuH9x80oTpONj65egLa8KKt/DKsmsPlnao6ubiUH//gR3iAmIRU/SL3dAM7qCKJSmZfEDE7lczEKogdUVFFyIkl0qnQzLJfuDfqZQz3kKDn/mpzJeFLLEzBGG3KDwG0L5syuUkGsCs1ySopjjlNlfVjGFL8CMt6pBkqt/l8ZpMWFqQ4x5O26dRhseA89vwN/KzHZJ8A5ITifMKXID5lonFK0ZFzGsgGDNKth6EbsayCr+7fvwt7WzVhMnhZzK9kEHMXnekT2WhqajF9Sv7RblHFjNlRKeLGfpRRugCJYAKk5kD0ZaPyzAP9PEHeLTBsgOXi+PygnGcipKggAzv2AKeze3d+4699++Lq/THdsOvrGtSgapjd2A+DyaA1U00i0UwAqJogqnQuirCKSN20qtj1w/VVt12rRHgzz365WFjnxpjMcH5+sX60Gy4HdqgyJS+Spazt5aA+11w6ZpiJlm6SUxaPoJm2rqS5mROUtFkemFIOgEQkRWVyi2VLgSLJsN3RwGj85kk/pvfe+hcPqlNeNavX7n2x7+Pp0Z2YcIWraHrTJ1qkZe2DZ1fx4mChRP22q+rKOW87Tl6phl85iRInv9aILAtlEENKny4mzu6RcSnZ0lx9QCVTrWbmCI7JERwZTFNixuBjWOILrx0/+Orp8YP2Zhy8RLa0WLVgH6/jZtyiDjZgPWy3l0OUtFocrU4PKVJ9cBB3CUXigKvgHTDyEE01arcZLh5fI8KTc+TGMQ5rqSoKaOEsjr31OQCdlG1LcqwENI4ZSXJynabkg6GI9D3DEfzEWbyfq3j+VZj8LiVjhcHUcvtXoFgqIDN5NbfF1fKmuaLEMKtxlRDnk3apfUR/77Ln/55r8Pc5jv1FPRuBz/je5yq98rFf7DWDFRPEe4thfYp93UevXvqyn6EL4T7GhpdlIX7qGz/He/+KHLcI7rMj89KB2p+m83Pdf+Uzc4JKUvn5c1KBhadf523tmdyXd149yHOWwpZShmbBO2MaUwSUHZNjztViVHpjWZGcz4LvPPsfOUtmSiA2MlYjR5aRhAAEAijbgExjBxRF7LsQpmhe50UFZSrMR86nqasdjETNVLLDUsRbU0FHiI0si2RTbrTHIM+eiTWX5ZkgawZAkhpIJaUshFyoWAAxmxQxlzJuJc+Viw+tuCpMpjZR10rFIlnuUwvnXAjB1KwKWjSlFKxEsNLdlkEwURA555RIU5Ik0xTIaL8VpdXy5EpoZqpTNgCqOk8AZnLOWfEAi+goZfoCkxrgDTBjg9NC3FYYzHmnUJgJtOjeTowJAZyKGlTNO6BIuRmAoqlDmemURe4pRsnEPL2tBmIqMxWQCTkq83We9wDg2JUkFhil7mceeQczkhw5KgCXFUehIgpV5oKrWYl/5jlJpqZJ8oSFA6DGYtNMK1+JyTPApOpURIxIHTtmSjFKkqQGD6hzXIE8O+TOAzlkjilKTJJkedAeHobKKRGLdV/7+utPHl3G3QUYjsRZlhTP6mF+NIF5m3ZDMxCmGQWkZDQIiHxg5zU4V1X14eHBarVwwXZdT5AUE9v6vbff+fBrH5jRO+++/fbb733ja7/4N3/z19/9yaMPPni82fQYsbm6IeLFvbOKw/X6OsW0XCy5cqw87AYIJFnd+OBd7FPX955C9sUm+ZLCXrm1H8YFFzGAHGBgJkciEc6WR9XqpD08PXhy9SQ0SsF3/eZ6u3GeYux3Y2dCzlVNaOtQVU0TvKXUd+OG/DikCN987Zuvvvvoh4HQbwYvgYwtseQcrYlZZoYaVOu6CnVIzsZxSJqQO5cr4hjVhEkVSKLEEqOYah38wcHh6uDQM4IPu+3GO79crHLA0+12Y9e3dVPdve99E5xPbAROMfVdr6argyXMgnOeHQxd111fXZHQ0fLIE9d1nWwcun4chtQP91bLJtRm48364812/fUvv3pydHp2cmez3v7gR+8EF2xYo25gALHlikAVMAFsk+5CdssmdyE3LygLdIZ0pt2grCRVnUArFCWZGW0uO8oE5X+Gg4xIACMTY7UM0JNYjkEmlJcMRspWIstpJRImZtmtY2Y6ZUpyMiXrOAen2APjrARtZTFoIXIV9mX2VG2WuSqtK0oyoBQhcXY6yYzZMZGSM4NFNROQEoMZjQv37h391t/6zb/z238zxS512zrw1To9efLk0ZOnp/eOwaEf06Ybdr30PVWV5r2KmVQcWxE9Ji6VjwYJFX3tS19ZrZbb3c2YBu88yK6vbwil89HBKjx9cl6HiplCqJhI1YbdUKBC4xjHMQqTz43Pd7vNGNWAqkKo66hp221hWFWHi9WCnfUDtl0kEmNl7+A0SUzR4sjDKGkEcfIJzuPwOKQUq7quKlc1vgpEzKI0Rqci2x1UcXTUrFYr51qLjsBN3cigQz8+/XANxhsnD09OVr1uxy6S6XJZVd43tYcMFsfGhUXTnqxOhl360Q/eefdHHwQ9uH/3RNYQhoN37AGDJWgyDiY5lyTFT6F5A5zov7dUn2enZfasJgfp1uF/7kUvOcyyaN8kHoe5TqSgyFQSM+YAB6SMbRWG8MQScS4k7xi6vdKLa01bRxJc5WrwosLxYSVDpU0QdTHpptuJ0q6zcdBhTLvtzl1ub66H683GM0LAcsmhDlXd+Kp9/+MPjpf16fFR4NX5x/1bf/mTJ5f4ygP827/+i9/45t3lcrXuH7PDgqqmXtXHxwfNXeDg/fcu/o8//C48GDwkkR3IkydOMaVYUCjOqg1KppSp9nnW5ogPmHmgKAgT0XODaCjsmWxK6AWZp4KFYfaactymc+g3QSnzs8jVKLdAe0naERHIEycrRG81I87ZMFJTU06qs1LmNAWIJjOEyVyS0S09wsBWREUnP+YZH/szxnW3Xvo0zSgDBJPjPblhJdGWDRQTg+CM2JEMqjAw1td9jOJjDIFee/ULMJCpI5ebKhNcHsUcDKtI6TKAPe/Y9rpHat4nUKxpYbvf3lSu2suVHMhtrJ9Bpj6JgTU9k/meX5bN+uSjDPmtCmz5rFza6cgsGTycC4EcADk4bt74xdcf7f4N+75donLsFo0i9Cntdh1sdFzVPpiRc75tQnTUjaqWUpKEJDEtmlMV9P0wdgpBGxyrk07MzKtTIO7S+mK7ebxFh8DklHSwYRSFhDYIWDXDoWADGTKMBViR9M8JfsvikZPMEizazpTJyJPznqvVMo0xdrF2TQissbZRvfOaEm35j//Zn+AEX/7Kq/e+dPdwUW9T39bLXodetgJYTe1xw0GTjK5hEiKypm7qphlEzQ3VIrhTTzDRUXPPcCb2TOxUFERRBBlCz1IfPnde1bkxQ3HvctmKI3iGN5jCWXvY8lKP7qy++kuv1kcuhi5KhyqSKIKwr6pFVQ26Qc8Nx6SiCQGu9QmJyDWrZtytUVcSwSKSTSwzrLT7ZnGahOCIPI2SVLQlh5BX6ZC5VEVDIBcCOyYyUiZix4gC2G0leV5stJfaKLHk7Z9tD3s1wxzl5SUz/1h45JkCkdGpPE7ZSvI+1vHczmOlhAmYWqljftUz8Nl8WbM1pAnnBpnYnGm33NQGLwewPgveso8o/dQX/9Qz0HTso2D7KMc+hvVJZ3sO5XgOJMn//3QAa/9t+8jIZzTi84d9jvf+FTnmnEb+8ZNm0jyAz73+pXNu9taeAQMIe94/9r/JhdDl56nuhDwcE4iUTcXEFJLAMPbGSDECCIGdyxWLyHxYmME4mhJTjgqm85aLJwaDSSDKmjsCwpQ1QdRUZOSKVS3XaRdMumzwOXM+uzrTop+arKvqYlFFlTEBYiABwEWZkrPcLxsTXAm1mQkUOAQOjt126HPopSZTXR9AllJizNhc/jSAUBSTiIhUAZe7gU3GxhE75gR4DqzMGAHUVctGfdypQJIIJREJVa0qSUwNylnHKivqOgBJn+Fym5jy1Kdydh1p8hQnMSxM93wbvBoyZLffmPL5eUgKl88EI8s6zNCiQGkltpwm4WRVLUuglesnAolqqdnm6dTMLjtEjmMccSs8DcCIjeaExWzuZ/Bo9ogyikQuBxFqDAjNbA6UqBSZHWWlMaQKxARikyKvmhXJEQLn7BkpQYkM5EAGzR677qExeX4zEzFJ7oSAjEISkajKhLsBzpMngHI6TmFi4xj7vh+6jmAPHzw4OT2+c7Zk4xTx6usPtpudYIDCfB5yQyYI5muAmkJU2TR551CkYBxgAvPsHcGJ8/Cem0U4PGqWy1ZkbJp2s77ebkE2XFbnT8+fVKHudrtuWL/z3pvf+dVff/iFV/7FP/nXP3r8E9SA6Xij1f1qtVw+efIU0CqENjScALHYCRFXvvGN3w4dBhE3KRujVCKYkMGBXKlAgaPiDhisJMXMGURACC21B355VD/6ycVxswLTetttx23ThqEf+2GUxJVH7ZcGHscIs83mZttdHB7VZslV9Ze/8DD+0Q+rGrhRFYURhZpIUxpy+h0BU+sHg7lQsaoO2yQKBDgvwkwMF3wdQoyJmDMzwAfvvGubhmCqOL9AVLl3dNQ2zc1u+/T84uLi/OT4zsOze2LYbLZxGAmUUhyGQUyGPsZFrLyv6xrLJROtr29215ur+vLo4Oju0RkFv1unm+ubfrO5WraLqq7bgzTsun5z/87DL73ycPh2+u53vv2D775zdfkEFGISAAiUrY3mUediq4vd5oI3TeV40zYxZfie23FVhahoyc2vzD25irne4FSVAAAgAElEQVS226W3H2Ldrs/Z5ZpWCLTI5BTLrUVAp1A48oWVYmeozpDCHiZ1e7byIdnRzBpYOSoz8ETSLAG13ZojKnVBZnNXMQYb5+ajNoVV05gxq0ruoQEih8DkFUDcwQQEBIBwcRF/5+/9W7/+a99e1P7RxeVHH34AT52mBAG7zXZMpmochcRIzYic964KEgk+1KrW9Z2IigpSNEdw4Mpefe2V5aK9WZ/3w46IVNNmc71ctI5Z1ZaL5cePnpydHq8WLTObWtd1m90umS0Wy6qqTNlx1S6bdtGKxOv1pWyu1VDXzWK1hGMXApFVTaVI/a4b0+AcRQEDVR1CxSmmPm+9YrBIBO9AnJidWjJNcM6QHAtzjgCbuqpgAwxNXa1WR4wmkpFoVL3YXV++d4UKGHG8Ols09eZy8/TmY1/xclE3lfMYNutrNjk9Ol3Vi4PFSXeT1k+HJ+9b47bBuqZdenKSLI6jxGQmlLlnRJKSxZQV/zknk2YNo9LDaMKZXoZkTfMVz//1E/xQ2zvRHvQyvXxywIrOCQhgQ3omRlEA8L4xr2Mc0CueIGjrpNZRQVIBFnsTISMHHkTGcdyN42bH63W/3W7TOK6Wy5Qogy/ExBREuRvSOA6rA5yd3Gma5XYTLy/G2Ls6yc0V//CHH4Zav/pGO2pIKVXqW67rpq3rQ9jB+fnT733vKRKWZ8eus931ZVhUofbboQNT8JVz3sxSSikJCmbEeT0yuYKYYwa2C2/n+XGc/ogZotp3QcpbJotCU4w32Z09cGc+ZOb9z65sdgtzjpQE2VW1mFQRPLPzYqnk0VJ5/qaGqYig9J6caGCZZaKAK4QIghmDZvLRyyfKy6ZN+bCXMZCsVFADJadrz8Sr2ZknEJFjx8TDZuSWhdHvkjmCiWM7u3sCAojJkUWbsaiMRllO3bKBkIXhmDlTzYoVnsFBmwLjyQxbaVhjc7g4RaEza/WzDEW+95e8bEqm7D3a+ftnHrfmMsiMGKtm/RIHqBmc96DI3jDAV3J2d/HR+7tQy5LhmiYsjnaDizfbsR8ZQIBVDPEevqpXyTMw7FKnqRdYTFAyZt827dGKmyCSnJMF15VssAhL4v7pzcXmfFf7mhrIZugHkYiFd8vjg22MpfmjmIlFgyf44LM7zKW0hacbzfJkuWk7RtlBAKXEvvYV2FWN98rrm40m8QehbWuoiXPDZV8dBOrt4qPz4+OTr3/jW3/2/e+Sch0a83F048npwZ37J7vh5uJq58beoSKx4N0iLNmPo4t1wwaLPeumqEQmVvbmcokgKVQUqvC50QVgcKl8b4CzUmrq571fClZPaE4XyzvV/S+evfLGKx9fvne5vtylzQ7dIGPsNqEyZQqLZtjuUAEVYIAPXeqGy7islurMpEdokSRJlDQ6LjJODK6q0LbN+mqbVNRgvaAiHTlXgTT1wgRj3JI+60HQJOfnpuJu21NDpNKg6XbWFVZasfmTz1os/n7e4xlwafJ/Zogjly0TgUxKr1ubq9xfXA7zhvLsEnjGINx+2hz/5P855473gP58Fc+oC75wvAgU7C/nGSf6HBjW/JYZvdo/50s/aP7xpfLfz73+pRePT9zAP9sxV13uH/Pl5qg7R8sppc8N7P1Mx4tg0Gf8XHr2wDSs+wDcJ33Ei2fbf3F+5WKxSCmJSNYY2D/VPqD4uQHUT74xOM9c2K0F+ChIgnPzE4wpxpTyBeQ6PTBcRRS8qzwFNkYyUTJiJSJi48xlMgBQlTFFJIDADCZql6u+7+MQYTOKkevs2TuX09Cqme5kt39lgFAvalFTE9VcPwi2LCWCOe+a8wKZ824G5yj4QMFtY5evAIyc8XYODLKkmuCFCJBkzI4ImpAlt6FkhsaHqKKaEqQ0XHeZfgR4qtpAzGomJgAIWnoQwczg21ZUVCUbFucrUsR+9PCBKgza7wZNRok0Git5H4KrYKSiXbfN7Z/AqqRq5sAESlEgAJc+yHVVZUpXjFGTAYADmuITTuk2IiJzrCoEct7DkCRmYIGQG52CqCAvZSynaaaCJClUQTPvzHO1qOtFZWxj7JOlnIGhokxmWVEt02NLEi+reOUSAYJAFbcWLe8rKcVsG7IzpyI50H122poZcvPkEuEqALR1m1lhlrX0IaWr0CR2g4z3OINjXyAnynuWplTS6JSzS3ljcUQQk6Qphx0UkPM97JwRDAJARyVQFaqmCUTU932M0Qx5i03JdrudJAUDlauXjaucsZJXZlscNUy022xvbgbvUAVEw+kJXvvCw2W7atyCLVx+fP3BOx+//4Ob5So0/oB3/vHl49O7Zze2ViQwfHC+chScWDI2JU2aQu1BODw6aI+caDeOo2PXVNUYh4uLYdjgja+fkfFu+6Rq8V/8/u9fXFz86z/58R/+yZ9++ZXj44N73/7lX62b1f/9p3/+ox/+5fs/OQeharFcVIuj5c24OTo56q6H8w/XUAQf4hABLI4P2lWzjbs+baum8a5CROw0daMN5sRVruIIYp/MYoyiiWvPnpKNsJEXDmv92q+/8qWvPFwd1Zv+QnSA1zF2qvHgoHny9P3VwcH6ery+Ho4Pz1bN0c36+tHj8/t3lt/8hdfPLz8MlUqKi3B2dPBgt/E/+O4Hb/7w0e5a2S019tWiZo8YO0kpVFnlx4ZxhGVImKumWrSVr50PLo59P2z7OIrBmNq28h5Nze992P3ef/rb3XZ9enzYBCdx+PFf/rip67quDw4P67r2vur74Wa93e36Icrrr3/5J2//+K23PlhvbtoWv/RLvxgqP3bdom2bpibjVbt04O3Njoy+cPbg3r37lfNxGCFy4AxiIhSj+Wr52mvfun//iyb1tpcPH1/9/f/wH94//EI/jL0NKqMj1/fdol2IijpVZG841zNpicn2Yu9MGb0NbKYWtzC42tMk8mN2q+ae20YUvotONpkn+2wEkIfPQugQaBIbU0pA8hAzUwgxsSOXlUxY2TImnw+fmbK5JV05RMRgjp0PgQARSbE4DMRwHs45eDcMIzyIsw77HBhMLPSCJ5TOp+Sc9+wcO+fAJDQYyfyROUpk5tscBDOY1Ggc0/Hx4ebifHXWOornP+7/1Zv/eOFCF68/+ujdR4/e7zYbDfTdH/34n/9f/0zM9SLkqkGsH8SRd64eurjb9JLgOcACszOzse+RxCozwr2Tk9e/+cqDh3evb5744NbbK8XYj7vddjcM0TscHtQHB8uby4ujg+PKVymKJHEcyDsFXV5dd93uzun9drm4uLza9WtfueVy4Tx1w67v+2Q4ubcKdTCzGKP3HGoPMnIaaq5r9jXlUvRuR9t1vLrajgPqCodH9XLlX33trtpADBX0/bjbJlEPrsckdd2++8EHzlV1tWrag4PFGbR6+8cfvvXWT2ynYO/NlvdXB0fL47sHvdwcntab7iJ47DaDo6G7xv2z1a/8wq+smrO/+Dc//ud//BfDU6DHarlqq4P+ekhjGsYRKsQKBzKG5nLt2dJbThx5clzo3QBhHMeCpGerbjR9kzm2pfuxRdmvtZjKxW7z3/lsRCUlkgGFvLHtp8MnDNdDliACKVMEDRksgSIzHapwQHAxJpU+HKT6NfzH/9l3fuVvPbzo3rnpHn3vz58Eh0Vz0LRH2zG9+e6jjx6DGMtllSSeHp4dHx+u15uriwtiDQHLtj46XgF2dXnd4Mxjcfno5uOPnjZ09Oj96wAHo9CmxRG+9cv4yhuroxNfe/zKV3+RY7gbvnL+lv4vf/Bnf/A/vvnu4x1pJVrByJE62oFp1Ckno1kKCYF9TgWZGRMzMTv0ssM0Mi/GJMUhsEJuRiFbZQdXfahedKcZBRkBYNN2r2auYOvlHLBgapLLGnPN3AyTOWRpSgVK7iTHo6XwgE0yC6ZcIgCQzNwgmqByN8HaZpY5SkaA49uJMVnL5xPJ00DkrzyHBmkSVJ7A+tL1eA8LnUfyNgIEYEqKxq8crwbdRln/g//m146/KptwGdX/6i/81n/97/739RL1dmGELimyRQRMNYlwygqwRUW0XMJk4ed5bDKH/UVLQmBhVaeJ2E6lZRDBULS9TQlEnOUs9DmU6iXhsZqb1Gjn3+VXqpbXs3NMBlGAVF1uH06sgLAT5wlEJo6pdq4aB0lkdx+ePjl/Sxv8+//oV37vv/qdP/7eP65PpdPtux9+PET/9GlKoCGOMF61frVoaw51tZJEFxc3j84vH7x21h6Gm2799PJmdwkIVECERb1aVCcY/XitPNQtVn/yP/0ZMgA6ku8dJ/ViHuw4ILirrod35hyBSMFSRFRvLQSAItRa8qYAsqpHWDkxy3WIbM7l9Dc5AqkmVVE251jYEgFexCf1AANr/Ef/7X+yHm4+vH7/any8k/PX33hQLy1a55hTxO5qPKhPKrSVtZT8xaPLcRsP26PUj++++f7m8Xi4PExJdruOyTnvU0wxiojGfoDBN633TmSIaWSCJ7ZIpMyBnTljpRrtqj4+O7r38G5YNDsZz2+efnz5ztYUNe7cQQJfjfrNr57VzWFdLfshXj/dDOf92MswDkTsXcXmSBxr1VrT3Qzrj661FxLIMKY0osLqbn10digJV+c38TxpZ6YO7FxwZ/dPlqvVerO+ub4Zx4EVmpIndsSW1JKxWSZZm1oU7GFXEwM9M0D19tEw+4Io7Zm1DF7PBqv8lYnUmNg5NoNJFko23uucBqbdMGSUuehvZbnopPlDCS7vaJjop0RTlt/xsBnhcJtpsyxAKfvwBIMkiUwCLdMyxst6oeb4iGdAZr5HEZl1tAGklPYt0v43+xjFS5GQTxGPp4l+Mffxe+4F3vvZO92Hj+bPelH46Pa9n/SpP+dhe4wvvIDD/f8DZu1/yvzoP2Wgn3s8+0d+70t5Kz/1GmY4zKbjZz3Jz3lYLk+bM95l8aoBbBmNIjCz97mhj6GIBLGxSTKxjFcpVJwClqk0JQmGPPMkt4sjhvfBe5cp3+ToNjmqBgGRkSfvnAKslAxqgpn9WCrOmEgolwbk5W2ZS0MgsHIpiFMCiJUVCoHCCOI4FAh9oidYkTMBcorZyFEuLgPDUu5+l6tbVHNPF2espDCCKjPUAUQqhZplM4Bvt1g+W1Z/sYK2qxYHwAhGklRHs1T6fMFQ6vDMYBZCRURwmv3EoitvYCYly0V/ZfpNbcMLUuTAnjPsX55jNoSUNaeo+HmW3c8yH4oXkkcm3U5pIqgjDh6OyhbsYaRGqkXFjAp5n3J1JEo+z6YtOwvJw7IXWFJ+cz477xvF6s0JSgOewezzwZm4TAydsr7lw40geVJM8l9TQ8DiRZaTcsn9Fqno21TwreZbuaN84QzSEtZkCklR/7LS2qx40zaNVb5eSTIOoxmjdBV2xKwKUjEyZyDm9fXWe459gsAFNFXbuhg87XZ9GtUd10fL1cnd034X04iPPrgxbOu2PXCr6921WzLyOjATNY5RoeQzGsOBQ9SUYho6TZxEU464vAtNGA/v1kxZ4x03W3TdetFWi0VgwuXV1djLo4/fe/jw1Yev3vE1L5Zvvf/+o90Vko3VMgzbGBcjsVULOPWBGyY39H2/6YyUahD7OA6jCosjcQxnZABLMoZPSUdRTUrkkFiR4EaqSCW1pzDrxbrr9fX1+sK8nJ2drJqD65urDz86ryrq+15Uq4rNtO+7GGMVkJJ8/OipYgRIRNfjjaPW4eToeHnn7skT3XS7Ds5ER0sGVTLEMcYYHaOpGx/CMI6SFErMIXfE8z401BqsG6ImykJ1u2iIYLjV6jCOcez7OvjF6oBhSXQYBsCInHOuCnUKZhovLy6Z3MFqsdvdXF7inXfeOzxcHqyWSaTr+oPFSkQYVIdao/TDsN1sJNSSkqUkMh4fHJ4cnTBXQ7Su3zx69P7x8YM7xw/a9uC//L3f/8N/+kff/+Ffjtthdffg+Oz44slFWRZJqCpCvVoCtwysM6hg/bf2f4oM6Vbx8CXbBFEOsCxj3MbPxB1E2eggjckR5w0imwLPFDPrbSK8qakZ3KSPk81AMQTlUAO44ARTmDqt0sz3zLsM5SpAs8IFKSyGUiWoEBBjEkSaIHTkbUNLf1c1zOHa7bCISCm0BpEzKLWLles7z2DG1ZP1N9548J//d7/tQdfb893u8urqfBh2QmnXx5iisU9JY4Kk1I2atynNZMzSzMC899tdB9PFsgkVb7ZriWgPQwhkiOPYJUGMI1gAM0vMcB4+uKqqmmbRLha1r+IQxyGmZJLEiJl88Asib+rMnGkN9WSBiRkJNhJ0HGPKuR0YcWAxhbApOSNWMc35IbWGnfPOqRd2mTHN4ziKDrnddLfr1jd93xu5tl021DTOc97jFu3CTC8vLra7Te3rwSWLUUCiA6waxz7KMPYiaawDHyyp3+DssL5/+uBoeefycffRexfDRQF8Ui+bbn28OB14dOAogxXGbJE8soJTKuzWl7vdMmzv/5cctveVZhffZmu+n+ieOTQT+DIRT/Jv931KgDQLIoCVoCDab36Q/T4rGosUBzyoa9bgtK6olc5IEIKvQsXOKwkzqgpJsNuNSXDvxFVVRcRqwkYiGkVV4Dw59mbVMFjXq0nlQuOph5CKediy4SHpk8vES26bRVK0FED+Zts9eTxIJorl0TNPlohhMOQmAyhlyhmzgEFzoj8X48pEUnhZNDH9qVCinwMtFASZmBI5FpjSUrn1R44OAZhNrQaLM2WwopCJwprK5zTkumSdjYJNj5Cm8/P+08UcuxbjsffrZx9/Ac3myPWZ2TTTP4s5pdn9ya4ffaJ2DD2HXU0nnG6tMJfyzWjuFEe5hID72I80uMobR5yCNcNhmVziCq2s0PDzuGD/Hp/BZ28n6FTdMN2/3d72dBe3T2wa2L1B/vRjIrV86mH7I2IAZi2msiOoAa4wdj2bxfX2khq4E/hWBP2DV+5s5enVVYyDMrUNc1LXVLZY1Mum5QQoNVjBeVuuGCsZ4s3FVl26d3L4tN+Og5nnwA0pb693PFYu1nEXd9cXAIjYFGxFaqI8flKAq8qpc+ao9MXmUjSyR90voiLlJuZRZ4OTcuO5aXXuKpRnPhlIObd4VnbEKubgKPvhC/z5H3/31Te+0FJzPaonVOBxs6EaUTRwUymntZCmod+lTrYXnamNiJWvXnv9i//y3e8dnx23Low27LqtE8/sqVJEQWUAxA0paeVRB4DBpDVXh6uzs9Ozo8OjlMYxDlFHOJNhTCYDKYgDL1g2tfPHB3dQiVtf3tzEi3d/Elx1fHRysDrUraSU0hhFKJDVvvHec9L1+iamtDhtOdLuemdMFQXUEpaBG5+GKJDmuB04ypAnUzq/vuhTF0IFVmLLCvkFfs/VNTkeUM3W+XkE+tkFMW8de3tAIbLbi0sVmMMdfeGvM8RRQp+Mm5X0iOUozMAGODg1VQXnUhGURScmppp1mfNVTe+dq2msAOC5x3oxReUCVPEip+g5BKqI+UwFPfOVzyZr33bt//7zARfzp9Mny109h1590kleevy8ANbLzPv8FMuQvYjnvfSN/18c8wOYocd9EGr/GvafZf5m/2pnAOtzX//+E3oO3fv0g56l2/3MB+FWzdJyMzVY7uspSgbnHBszs4ENkgVS8z5aHGBSKMETObZckVOwklx/oaJSBJ4AIvbBhyr0u8J6sEz8tRlrMHIgTw6klnVSQHsQDFGOP7PkbtkAGcTKDg6AYw+2LFmlJgYTy+34XC4gKbryGeyZtF2yJ5RFsyxjX6ZTtg+5/nCyG2CaoOISCJplIQAiM80tmbBXumYwVTGY5OJmhSLBOCdkSE3FTIBUjFqxStn7ECUicPEnZrxvxn/mqZu5ezMOmR8oceG+ZkjFCjyGst1mo0GlmK5MvFKVX6biHK+WQtBMkSBFAAdin9ETnYLC+YOyBNXkNhbIq7T50QLwmBWt9cKsLZkGLpt0vo48Ia1gUHuoN27xLs19DdlsQsYweavloTFAQpSbSOpkNguQVW7y1tjP9w+D5B0hJ/QnZSCaxCrKdUOhRSkyK+OXznYmapJV9ic1RkPWhQObQURUkpJBoiFBRiRvUFAvkjYMIg2Ba2Z/eu+sWaw+evK97ThU1LrWIerkSMNUNUFIBerJ06SgbmJDnxKT+hyii0+JwS54idhsxuWiXi6Ph+urzebm8PCwaXm1AAH9sH7/g7dF42J59NrrD+4/PH313UfvvvXBZrepVu4OHTZ1FUnGUPfdqP1gBh9CSnEcrVk0gWgcDSrMzk3FwwBYOW4GBSmxC4G858BgRLOc8v2l3/jyyd1le+Aur7fdcOGsSro0Cd1ufPK0++JrzTj0RGHR1jDbDtuk42q5MNKPnzw9PmnhSJNJ3JHeLJq6XdZ375/EqP34lIwMCQrvPHufEpmJYzh2ZDQM0cTqSochxtHYG7GJJomqCY513EYmIw9uIGIq6fLiaRy6g4PlzXoNIDgfQvA+aO7a7nzwAXCa0tHhUfAVQd9///H5+U2MY1PXdaUpxrPjU1Iwu9BUvXR91++qbVg5JhKzpl25qjZ2mgM+St5TFYgwHtXLf/C7v/Otr3/9f/4f/rc/+Cd/ENR11+tV0+6G3ThKaLwWPd4JTc9fcnfu7KComUreeeZ1lV2c/eDk1g4UFYm9DadcFW5tDJFYMqiBbBLSmugFU/NOK76VFjnbnGVEWcnZMSPDLJUzNWfKEoggy7qKzK7sVniGsTXDDhNUoGAUIS+a7AhnAT613Hws70L5WosGxYSNAESOYGBL/dCctrqLo6bf/mt/42/93V/9d/72bzDL5eXjzeby4uqpyOCrcHX59MnT8+0uueCVKAmGCHbOQCSQhHw3DhjHvvJsIE0pgVcH9Wq5vPfgpG7cGHeb7Y0PNKZIzlKKmV7CRN55733TNMF7zuRSckAyhTGHUAOe4FXZ1Ks4SWwaVChFGnqMgoQBDsQIFRM7sZQ0AsI92iUfHNTOhWIeeUY4iYjYsYjEODpSg9MU02jjCHDPASFWhwcrIu9cY5CbzfXHj57eXG9VQQxTNCe2Wvm6ZbXRkGKMjsbl4qAN/jL2r99//Xh5d7iRd3700fs/foI1QgN2joHKBefYO1JHMCeGlNvgiRZUqPgwxjmtnZuBKGVbXmbgFGnve0xmWQpaM7hSNrK8k+keHEMZ/M0RvWYshfYLdfNGMi2H7LiQpQnAyoGPz62m5vAblFX2CCOGjV48Xm+vRwQ/diBD8FUIrZJLokLgAM8YRwCoate0VdtWTdMAAtLMmveBq6btrnV7PVxd7WKv8A5wIkhjVK3IVVc3Nx31y9Plg5NVP8ZF5ZLS48fbN9981PVlcU5WgGehoim1lB0bVtFMqCTA8tAxMWMSIn4WGLoNAstjmnjhsGkIdY/RgLn+JY95YYLfotjz/k0GM3WEXEE4h3aYNLRmxaS9/CxNGNnka1vhjU3eA1tuPGGwTDECLJshLfdKQC6vsv36nxnznDAs7McO2UQWdfsXuBDzED3rzufZm81y6YzMgJqoJFV1DA8R9MMwcL9sF9F6/wr8xywQRW7lw4bSJ5HASimrWdjMz7XSKpOwF9NbVgNzc6xeRBz2NoUyLX6+YC2DhmX4Pjmcyes0H6V/bs62EKtARYnUN44978Y1VnjjS3e/8MVTUBxjf7Ne31xtYkchNKlDGllV06UNIS6Cd+xHSwbj0H7x3oP1eLGJl4lvFstmXUuK0XHV1stxI5ubziVdct2vh6fvXULAcJJMDcTKbOYAg7EZiQtMjook3BQr2PTki98GZS6YylTBbsYKLzMKYqYqpR5+0inRrMuaBefIYEZkDDGQvvnnb6Y03v3S8atnDx+vx3izDStvgmHTM2l3Pm6fdOg2cStxG1PUtq1x7O7eu/vqa18Yvm192t1cbDSBaq6bSpOMY+8r71qfV7VEE8PRCl96+PXDxYlEUcWqPVhfb8xUkqSU1FLaxeQpegbT2erBw2XYpOu0gZAi1u3icMVmBk7EgqatUhxpgGhkQzQ2goA6HeDo9Piooto3od86Q9IQ/WHFS8csfum2F1uowbl2saraipyy895zqB3Im1gap/zc7fphTSb6jI16+eScnsue1uGEau25SPbM67MpKtFH/pUClGdHNjGOSv4Dk3J5SYEXJ4Ut7xA6szTKKTKan7eZQihWzKq3KG3dbS+XYi/Yk09aXyKlxbz3/jlEaR/c2EcnXmTt0AuKVJ+CZsx/fSlYls+WA9v9i/ns8MjPBWB9CrAyQ27PDcrPC8d8rmPO15WqpU+97Od+/OxD+ekXoEUhXH/qQ/p/5ROnc4H2udaT00JEIpq9N6Wc7jbQ1COBck9VSlnWR6z0tuIpI8YAF37UbWxCACPrYTnnUtIcR4kZ8hpgwMOFwI6Ri8s0y/xSgcwLZZI0ZQ0VYnK5SsCb9xacsZK5vP0a2NSUocq5ujBDHGJwoEkQPG8ZbCwmqki5kbIaQ8kEMuulTLslbtP7MIgYZbOEvN8DzOQdEYGkeEXFiVElTIJfpgIyZQMos7sJAOXzSOZdlShP1ZQ1I2ilIpFAMNL9JhnZEQMRQdVowgN1DjaLQ54fhVrxypJmzuqMIBZmRIb7vXeEqTMG58aHppby1bngQ+Vd1iCeogfMYPRk2Euac+I1TnpVkwuJct3lPjJwxDRhWmUzmJy9SRt+ckqziI6VdosGM53cw5KGKJmtXCuS8/U6o2mT61SUr7JyvBUX4dZZM81eZ65CzK4psZXEGjKzBYSsbbC3dWS/k5kZzpFXEpgQqPK+qitz2qeu7/u6qb33woCOKaLbjsZqxrzwCrra7Jy/Wtarqm5aplf/H+LerNeWJTkP+yIis6rWsIez95nv2LebQxOSKFEiKdmGTckEIUiWH/3iv2LAgO0Hv/k/GPCjAEPQiyHZBmyaBATLMEmxydvdt7vvfM+4p7VWDZkR4YfMWnudc4e+LQ6uPt29zz61alVVZkZGfPHFF++ev/ji6md2jqsAACAASURBVOrqhpWaddSs+zftZtkNhJyMHRTYlDSrGZjJGytRQuTUhCbG9smTTd+k8ODs7GxtuDTLKQ8s+c4JABGJl5tn/Ufbk+Pzu/cf3Lt//51febS622y3Wxb6wZ/9aWijO6Rx9G46MUcWAiDCwuSFHYMQwNCaP0IgATLl2DRtDMyS4cmS59EJ3RqLY/zNX/9l4+Hy5pmhXy4bxLDdbabRttuhiWibpSVjiU27SMn7fgNYu+imadru7Ew6EBHHEJFSvknXjPXR6eLudDxNw4uLDRLc0TYWYxtEclbHlLNRpev40I8pJwkUIqtNakribcNuvtv58bK9c744PV4J8c12u9lud9ub7bB59uyibcOjBw84BHLSlM2haiIhBNlst4vYLO+tYhNClBcvn5EbzMndshY1YA4SJeaYkNzcQwhd22UJJyd3yC27a06uWARuF9F9urh+Sta+9ca97775ewtunl9+/vHHX3z0s8/PH5+uF4ut+c2u71aN7uma2AeUpeipLA+ruYrZsNcY/TaoeMVvKAn9PVLEXP0or1sJlaItipEAUnO4FdknL/07Z8kbm7ebClVVngJQLe5+e5oj3eJzli83Iqda4FzMgrm72qypRzPfgirPAFTqmrmqzNIM3zOc94UuNXCuUYVhxrIOrBN4d3O9Prl/Pb188+3j3/nHv/mf/t5/uFjI5dXTJ88+G4bNbtw0i0iR+qF/cXWdDYuuMyUbDNw7ghpBDeAgEWQwJE2r5VKzDtcDBN996+Fbbz1eH7X9uN31N8N4Hb3JmpE95Ul1juqpvH9OOU8pjX2CgzgIk3NoGnHPZkijmbJmdtA0Eqvtdrq9sSGhcUhEbCDC7pyzjVNKaiAw4+z8NLbS7ygrTG3MPiYwm7mTsKpOaSJXpgDn5aJtO+on3W37acx3H95r2uU0+cXLFy+fb16+2Aw92JkZ1uH+G8dHJ4vQNn0aI5By3zTeRF4v23Dn9Hvvfm+64Z/+8OmP//yjm0uNLS+6btyOQrReLcZ+m6ekmmtdg7NXEaOZCuMzBkCVYG0+15jPBnm/z+xn2AxbwF8revKSSJpL2Oq+RqjJ89nz3pMDb3e3uoKI4DzWWrmqkc3uVDIoRA5SQIm9bZtJfXOTfvLjj976tZPTx8zeLRdtE9eEmJKN45SBECENmghVgDKQF108OVm7q1uKIbRdGwNrx5/85Hp7ka8uh5CRWy1693kyzWxoLm8civfyOjZrzR4WYpmuXqYPPrzi6ci97rcMvt29vSZyyhqhElG574sxQe5g8KHo1WsQFsEL48xLhFZBCFTKU1a9/cB+HGcztPd8X6HtVN8HRZKU9qGdlx7KVInPXgsIK7ZYyeEVEuEC3hR8iWjfX3UGmuAgMpptZr0J83qJ2bzO13jtuQ9nHuZEXAHW6MsQ1lcdxWczZ64pPncQw9TMazuIZGYp5SYb0m64+d47d15s+qvnIywAEcSzkw0IucHoFj67Ha5q5FASr5WFdnjeHNPWTaFEcH8p6NXPD2pusbNadlWxHGMmENRM2NVy29LQZ2R89713v/tL74y5f/rk86v+YhyUdDVNzdNPLjdX07Db5oTAOF2uhGK/S6vl8f1HD95588Gd07NNev708idXL69g4paIJUrjnEkHJAL7uBlvnvcwghEUgKp42dnMHWwguJCVbt3l1kmdGDWPXmKUshvBCaU3UHlSJzPA6qwkm6U6QRzm2jf3XDv2FqDRyR2k5AK9Hj/4ox+eHf+dN9++v1rai92Hy5Oz7ZQ2L/s+6cUn2+cfGy6BBIwAoT+apq1Gak+Pz97+1bc+e/L58+uLa9q0XdCoShY6aSKrmcPatu2a9Vl7cro+vnvnbuD26vnN5fObF5uXH/z4gyDBTNUm84kY3C3b9RE3YXm8Wh0f24iLZ5fcCLxFE7gXCR4mt91E7hDEyA5W6JAH1pGMKXCQmCXHEBZnDZo2ZUpi3sE7DxK61ImLL5gy2qYJbVQbcx41TdkTxAgAmyUDBeaSoGO3uWL4q2ae+60Pgm+IxL/qVw58eT3sCZ1WNxurSXqvPWJAtXZlzh64w8nctLpbJZSg2gRsjrXq+UVr9gBvmqXfsZ9qh4/29cf+CgWuOgSVfiGs47Uzfy6k83W4SvnfQ7EmfI0y1dcdf1UAFvau8cE7+vIv/5qPuq/MpZhfBrNeG5jDv3rtrIfXnuhbjvoeZfzm02gGCP5yjrJLFftaIQEUIM+9rHGUktjb3CVQfymCnGvMwASWmuiGm9fOy5W9LVLgAwLtM/9UquHI3cyYAWPm0AYWYiaFmZla9iqvUm6xeoZqVv9exE4YkWKL1tWyas4p50IrsFoaM982EXFkF3ipKZFS/lxmXo3n4AbzouVeATMhBhNTxYxu85PFc8ac2XciAu+3FZ+zfGVylIpB4cKHdHcrb46ZAlMmRqBARupVR9Rsrg3zSuDaa83s4S0A7lUgvKDmKGyv2ciZVY/LxWEHPjcAUBWkIJhXuobNPn7NrnENZImo5oJKgBnRtFGKIGU9e197S9WYzoBoiRWr0S0JSL/1Rl/JY8wLcJ6e8xfvPb95HOdG5XPeu5jz/eogoFSGAoXGUfyJ2x2kTp5iH33mWZRS1fq9qN7ibaaRmJC91JPOfwBjghXGmQHmxkWXmgCCMHFpSekQEWcQG6ogPOCuasQkIjGGMU5wduOcbIQ1DbPQrp+EN75ikQnq7373ncXq+Rc/e35zsWOGmZY03f7FupcpAbhxDK5FVCiQc2kMLikzNzG0kE2/1c3lcHrSPnr49tHx0TTtUtqt1zIlOzo+ur7amqfNcJGeD5vxcn18ev+N86PjdxeL7t/+4P+N+sIMDkwZyIAkZMCQQ55GU3EQmDPgMHKy+oYtn5wtiKMC45jGcbQ8wa09w6/96juP37nXtXj64vmzZ58q+sWqBcLlTX+9GYI05+dnMSy8LRAAm6kE5KzD2E+TMiE0Szgkog1iYxp6NU8xNmfnRxL8ZthMgA+YJmPKTMGyj1MKjS9Xy+P1cT/04ziCQtO0IqI2mXnXxTun608/vsgJJw+O3nx87+HDu2nK11dXZdrdbHefPx2Pj8bTO0ndUk6qpupqFKRpYjSzaZq61fLBgwer1fLzz9c5j00MQYKy9n0vkECxodCECEIXm+VyuVwsUtMMKcfQNKERtqRpu91afsrn0rXr7eZ6RW9M3v+j3/kHw9j/6//1//zZ7/+LZ1eX9947vXv3Dl1h0OTiRLPd2C8zVKJxiUHxKm7FpdVDBelvSQSzZ3MbRTDBuOLEZdEREzNLE2BmyKrZ3KCAOVVjUhlXrqgYg5O5kYMKJl8uto9/qZZdkXBtEgo3rkXM5gV5NyuAExe6FhU7XPeN0myIqHTvMq+8fDCcjIiNKnyJW2ZGtTYlHr4lWDiwkKd/+hSn+I9+6x/8xt/9m4subLcvP/zwJ8+efT7ZoJ6FuE9DRg6BlkterZfW25hGIqn19+YNiYgAOWtetq1qHtKIDqd35N69O8cnCxZPu2EYdymNxK5eOzWU17d3M1S1n4axH6cxNaFZLNcFKnc3U9v0A1Hu+zwOxuKBM4mOvaaErFg1kIgYhVlghSbARMaCEBuSxsymZGkyVSvAGQBiMHPOWbNqVoKR02Jx1LSLm914s7243qQHDxED9/1wfXV5fTNkBTMCrItLbuzs7qpZsBNNmkOU3ZRzQhon7+K9e/ePVyefPb364uOXL59fC2i5PGLHNO1EUs7jdnNj6pbNb0WRaog9wxtzMq4UlM9Tt8JYdVuYB/Mgdrn12Q7CkkNnrJ5Z9peyt+59w4NE7AHKUs60MvWpqHSC3RhOcKXartAABVsb15wxTeknP7v5/mebk/t3Ttb3NjtzhH6wzTT000iC2KEhYtA4WT9sNpsgHJarBnCduPTEdDdTffry2nZICjKM45RSgjHMsmKcfAOwgOioWxwzxgYNOKQpbK9xvGjhNzNJmW43YptDs7pAnP3gFRUYZx82za4abg+qi2q/sR8A6mWcsG/Ctj/rFRys2gafR3l/CSY2s5mVwzWqr+u/ukrVlDndwk0z/WFOpdfbZyIjK0icV5HtMloHLgFm7jfkyxHrXOp46NS8OuG+Ksr9ucft256ZpCWPBoc6iN3Zh7y7uH7x+K0H/UdfPONBstVuNFrD9VD3gy8VT9GrL5X230i8H9U6CPOd/MUjtZm6ezBVCK8uvcPfzwJdJddYijyMwIQABxGrjUm1gHMPHtw9u3fn6bMPIYG4EQ55oouX25/8+GK4wEpwfn7Mzi8+ud7dDDkpeHv5bDg7u/fmd89PTk7TdHe72fT9Vh2SNY8aQ7NoFpowbKfd9ZYmwAgJwSiTQWAMK72zSY1NASc2JriTOcHgAnABLioKS15wc8fcJss9wzTPSVqQg42odElQEiJXcgdbSZBbIRZVbWIHQ937dPnZyzuPw+Pv3l2sJhVSCzw107X6To6IJjJVMjdTpBu76Dc6fr7bDd//+7+2urM+eXD6Ml2OOXPMzjKM6p1Ki+UiPrx/7/zs/N7yXuudDXbxYvPZZ08+/tFn47NMS7BnuKvlAvs7D7uXk5rDuLvzdHFn/ca7bw95eHr1hQVQTx7yNO22dhWOF1OawBSaANNxzJrBxF3bebar/uUoTaCYRSfPmbOTBw7SMi9w9+17GJC3Og5T0n5Iu2mckEiztU0bgzAji7kCJcpxL/wCJ37VRtXDfd+VfU5OfPugmw7xbGC/KXgNr6gGml7nNNWMiANFxuB2KyrGzuY1OcfmZlr3ISJ381rcQKVriFe3at9V7DB2/2pM5jUWEQ74Voe42P5fDy+y//kQl3gN/PrmF7a/+JcvVV/+KxtxPb6l5fmr0sA6PHwuvMRXEdL+em5gP0ivgVD74xAR/PJAVp22A2jwF7Xs36C99Vd7UAVRvHQaLo67EBPDrQi7lcR6kdsvyYAS1hcwhQJzFBIYxFghDrLsyTwQEZgCBSYu5BgG3G2aprZpir4JWSbLxCEE4UbcTWFu2VGQISoiEVRILwWGFqBSu5zM4ZzdkCbLllVTmlLS14js1bchmCkxShc4Joa6V/obgUpFukBdOFPBslCSve5mgRsvonzFKyWwEAVICEakMLe5ZM5rw+xqg7y4/sQFF1NoAgHMMXAQZ7i7wty4tFd3sDkTzN3cRIQchqrKXEj9ZHs/DoAXrfRaO0FU85tyQJGYzywjjNKAo/TQOZi3VMVlbg3KK7OavJiE2MSma4gwZbWKtB3MKSLVjL1tmlEwm6EkcBEhnHlSX3Mcov4zHEjFYVQG++1HiWrb8mLEC5JTIvQC/DkzFUZ8Bb5m1LG+vrIQ/JXtzGuAvQd2vehLKxUnsIBnZnA3tF6HofLxCEBwkCOnaRiUnJfLZdshYdr1/ZjH0ArYu7Z1hbSBGu5aEARq2Txn3dyMIHO1aUzTpMvFoglxeXT84PHdEMPHn3y6uRyhYEdp5lmWWy5AlnqtkWUWEQrR2U2zTZjgXSQO8vj+w6sXV2nKEsIvffe9s7OT9//8s6ub56vlyjab9boLgUPsdv308ur5h599vF4v33nnvfPpbp6m/+G//28vnl89//zig/c/+uP/588//uBpoIYitmNPESGwI00ZyS2yNQwRWIArzPH8cgyMrMAEbnD+4OzO3eWb7975pV9++96Dkz/90f99cf3kenPVLdkh7m6uBDBL+f+m6XLK0zQVxFVNN1eaFXfutNOYh2EMEsPxul10Qtjt0jht227x+OgsSH7x/OLFk02/g1p2KDHFGJiZvPBDJcaw6Lq2bUgc1IRIXRPLCeen+O57bz96dG+5ik8vnjx79lwix4bIuCT4r7ebq+u240AkbkQSupYbchEZh6G/3izWi9VqeX5+HgLg1sTYTWnX94umSzlNkCbEtm0Xi0XXtk1s3OjZxQXzIMSW8zRNkeOiXfS78fzOfc/0MT7IyR6cvflf/rP/4p/87j87Pz35/T/4w4+++FCnwABMnWbBmDnUg5KVhvAz1UlECLfypRXEPVjNPnOufM+cmlcdE+0hb1jdKUIMlrNr2Tys9o12dRgzqxFmXgQABm4tWYk651QKqOrOuzsCOUHd3I2E1ZVMiprUTNYkMNXuHCJWGWHg4MRE5X2Y1xo8OBGMjalE3hV0r7C/z2Eve+1WiOAALMeW3vwHj/6b//q/+tXvvOu5/4P/6//4+OMfH58tNtvL7bCJy1bFdsOQPMcuskg27IZpO6ZksGyenIibSMKsipyzCA95Ojlavvn2w0eP7knjl5cv1cekA6BZ4dMUYhMi2KN7JkLXxhiiiKi6Tqnvh2lUdGjNiNihKelm099c7UBNyhinzCzu1HaBKa6WOG5sfbZwaJpyP0yTWtsGAjdNOD5eHR11aczDtOt3O3PJirZFbNB1TWwiERFTCJHgeTIzX7bNerWOXWuUXlxs2kV0V8C6ZVgnRjYYR2nW3Xp93MVmcEogIU5HR0d2cwFCG8Ky6x6cP/rkw8/e/3efP3/ysuUjJR/7BLNWJMZwc3WRk5nCHEXL0pxpJojMGMQ+21F5hWZW8xhhnmCzaT/cZfZw1D52d9/DM74v9tqjWACZ7Xsc1IscZmL22ZSKE5fTndwLekpMTlRoFUaErFNJ5F2+wObCgXh8dPdqk643u+ub6+upn8jaZejcI6IQ42YY+91GbNmuQmgAZFVNeUdQzZeXu36LjqVbQkbOqnlMTAHuWXUYdCIs76CJ66ZZIY0OWHZXRoZ6qPAcWeVTVdNR4aAKVvte6tMLdPyKmtS3DvfqyYfDMQPXeyOzH5GZnHBLL6g1QeCUDUQs9bOGWuW3jwaLtyhAVXUoJq1ax9uEqM9invvqItt7kQQQl7LnWfjyVXrDPD1KAnj2oOjV6bafQr/A+zkEVcvjswDCzGLkbijCBSKhH3cvL5/df3T/i9Nr0KWaQbiIVZTeQoVSWhBDPSCf7sfs1tvjmqXb+5n7sOfgpf41HT77rbXSClYr6YqDWlLgwhR42GzjKbp7OD5rzdPHn3589OD4Zre5uRo/+XDz5HMMT4GE9vj4pHuQk37x/HK4BhiY8OnVxb+8/Fff//W3f+VvvXn+aPXOW9/9wUd/2HXdNCXk/mTZrlfr7TC8fLG7fDGAIAicmUkyJjBcoBXhhHFp/lRJhXWGwVB62s5wevVqQSwVTrVSeJ/KimMgYHZhtTQoYSisVM3CnEty3Imd2ZkdeUzN6fJHP/5w61+Yvf23//73nu2uNk+eT9f56cd9eo7OAgbhkQOJw3POmvJ1urm+urni60dvPXr01sOzByf9sL26uhiG7ePTs3v37t67e358unbTfjN88pNPP/7hp5/8+SWuAQcCutVyuNjV6eMGgoQiz2HLo4VLGJ9Omw8+efYnn+DOAo2vuWulZafU7653A0/DxOCIEGMMoq6ZAGCy0dWExDTbpJrdyCyYqJCSOPW6bbhddsucfdptxzxyy4HDkFPThsWyCRKxm9yn0nXGk6lXfeRvwfs7mIAHaH4d0wOk/ZVTaWY4Uv2e/R5RzyAU6iRKMSyDnJgr+FTbkxApl6aBr+FFRjTDMs7MAQJDIWMWw8KlxqhYIRaaORA//yEPkQ0zew3QKBfc/xWzOcLB/ru/yCHy9W2O1zCyr/yZZpl5fGvA5C8TwPoynHaIHP3/crw2YHtsb3+rh/e8Fxs6PP+1+/+6Z/kGyNAPVMD+Eh+sXPtgbzp0E24hzgL/MwscBNdqXsEs5AV1AgghiDvIPOWsBV+CEQvYRUSESUhJITCpEDSTMxjEQSSwuMNMTbObgUWaCBJyI2U2ESIRJkDd3RVVZ9jd3amQzkuUYk6lP7CX3rSu7k7Ilsbs2dWyFpErBwUCQ1iKVEpBwTUpiVfaOAsxgeHz4nd2ZmMmUkYGsiMTsudsUIvLUuBu7jAuYBORcO1i4Vx0ZMmKpKMUJL8kUViI2Ikr6uIEIhYRpqDquegfwZgERmaZhEopYUZeN4tkk+nclbvca3WRQSyAEbsDuWhACbi0wRDOmKowKBXNRSo6kMzshEChaMrwrdNYNBPAzKqzVhQAJ/eqIi8isWmYyep2WxvG2L7Ln5NVtj4XBZKSgSiLp/rDPqeXXj+8jFT1/hw18enzfCi3On9ynxEs/+E5q0hFGbOiWqX3IR98oiibAnCaZffZqcozHqxF339NraCYU2yupRbLzQCFBZCxCSkTCxeqPpsTciniIwdbYFF3aEoZlrlpmxDCol203E2UBFOhjksUDkFVsxoJpqw3/bbp4tF6Neo2WT46b97i85+Onw07GANkVJqcoLjes2q1FgXtSBTMc0nCIwPZSPTkZGnTAJvW6/b+/fNxnC5vLjbTNTfcLKM03jJLIG7bzEujJJG2w1X/xe768vJ/+9dN5HC8PHnnnfv3zk42f2+32w0ff/zpk+dPt9MmdGHM07MbYIvEoAhxqGJSQIEFMoAMLPDw8eK3fvtvvfHWfemUWXu9vhmeQ7RbIrRBs46qRLZYNDnbxeXVnTuRSNXTlBMq0sqqBqBtlpvr6ea6F9GGFuF4IW3gIQ15IyEt2/U77511CyeML56nNCn7QIjRY+FwFYZLt2pjw47scGYHKOV0c20nJ3jv3Xfeeuf+YhmzjjltHNNul1fcrVfNvTPqFoHZNrttlhiCSIiBPGMckjtSysPl9XizizGGrKlt10erhTCP4zQNI0opCwFMTdPENjqRupm7UbjZ9NdXL4d+J0z3795bHq1c8m64bpvVpr9+/OgtxfQyPWu7o//8n/2Th48f/s//8l/8yY/fN0WzDJElwRSqbhzYDVT7s88Mq7nuuXKjSn2CVcGoOXql21itrLxaxkx7U0ZMUuntM5u4hD9MFpxAyEBtSjoXDDq8WN5S41O+R26XHsoWAIBgKHW8heRrDjJKszEs0LNDCvZPxlYMOwgI7DW8rqajcilgRXurPDY73Kn04BAuyLMSuHbe0AwxjPiVX3vvn/7Tf/irv/z29dXz6+vnw7T56NMPv7d8e0jjmEZKGAfb7bZJVRnbKW0vNmPKacrsUqocyUzNMjy7TgQME5a4+/DknffeOD1bP3/+2dX2ec5ju2hCLI4aYiw0MhPpRKiJQYQBNzMWZhGwYq9CwDyOutml7U5JsplPU5aQsqKlpulcRDjGrl2lnEbbDoNiVHfnSG2M3WrVLNrdcLUbeid2B7F3CyGmpmEJrpYWITB3HtoJeRpTdnWn1epImna13q1Xy20/xIbOz49jDKqXnn3RyaqV0JpKD8nMHJZDu4xrkKsfr9dnR/dP1w9+8G/+9KOfPr2+UrYIHYdxiCyrroshpCF7lYQBk8CZPbhrZbLCxW/D8cq6KSLvRZbTilrVgdxaORX78rEK6vJc3nMbbcDLpiSAQ8kFtRvBPrNeCq8A8tJhF+RGLlSjWTeQkd1up0ZEJHOjApY0DqoaE8DIm+BTG06EI4+aNuPUT9lbLNqOyaHQ7CREjKSafCI3Yhp1B4MPNE263SoEIYYQxIE8GEjcCRQcNOymo7tr+CYQollIOaIdNu6jAfC0rSAuZcdgdaHMXiPBta74Ur9f0ziEUmP3lU4u0cy29KrXA7iSs5OT054lvy+2qrA2M9UKLJ8/Xvb/OU9XPRsiIrY9Bj974fO/otbRcAF45wrqKjnkAMlhJGpFvqww5+CVpY9DOYjqE8yuAr32sAfOPBV/pvqMxXTOt/2KofN6xVd89nrBWaB+BlQdc0tVdhJzQ6K0iCwx5l2/Sdt3j89C/KxMS1DycqdG7s4ipf1QkXknwMu8ngeuQC0zYx4gBapiW/XiCqoFRyFn1filUiAPsFy6Be/8lSc6eO46sQ5exB4hmN1dciIqcIbUcbvdeZjJ3YyyRAdP1DgmCq08frwKy6kfX6huhm03bhZPPx4/+xmuLwBgdRxjEzY3fb/ZDVuQUaDITUg6jR/k9+2jLnDXvHn21lkp4TCHpmwjVmG1GYZ0lbBFcObMMGER8uDZ6uwTz8UqBSqhRVFzLRPRKB9stX4wt4vkAotDwElLgQbXqVo23iI34ADrzD9G0XckJ3JmJ3aaUpbMi9TcfDK+3/zoN3/r7715+ihvP79Z24X9dHClBtLS7moiaho0cIQgZJ52E1t3fbk1t/XR4uFb9++9ccfUmxDfePzGo/sP3OyD99//03/7Zy8/2vQvEkbmQACQMPZTExampRuslUIWd+dMu82Q3UPbhNBKaPTFlH3cNNvQebsIq8XZck0/uviUOsQlkwgFapqGxKDIO/XssZGO45g1WxYOUMLEtiMjpJFHTBIkUR49jZqX3XFLPNilsqk5yJJO4zQJhOasAhvg5OCE5LUtFhdztJ+JXvaCav7tcMICtXEMcNsaYj91i+YcZhOzp0AdwAREVHWDvaoBzrSDOZXmpa7UQURmtRLHHEYVVyo7CFBctRKGELlLiTHnRH5NMM5UUv8SjHWIPOx1wA/Bij128WWs5tszof49jj2kdXiHv+jXfTWA9WW05Suv+xoMdAgG7a9w2Bnx517wG44vo2PfcM9f941mFmPEq8ji/hH2ANb+X18D4Pb0scOXTnOTyFLRdvj7/Qe/DsDyg/3yEGvbf2QfMLzymGXxHK6s+uFXdosyJu7sxp6JmWtHN69nunvOymSRY7GvzEHFa69189BFBLCQBIYYQC5kVLIiLsz7FumFHzJZTjk5WWBwZK97E5OamUMzO5krkbPUEjGFUSnxICpgdXkyZJjBEjwB2UwJCZZM1ed9E25OwghU3knxG7kwbEHIKNBddU+L1WFzUhAjESa2lGFECld4hiW3QsGCgVgkUCNoYLUPcwFACoZVDBHP9Gvj4ERurnOtXhkDgYQ8TXM0Xra4ohteXAOHg1vGRG51Ty+PplYRVbAQy76gOiN54dAJQWiGZYrnTxCukSk7MZXmPaYmEgRFrnxGq9xF2My0RJlUaNseQohdG2JMaVJTi0ZiQQAAIABJREFUh7mbuRY4p4iHWYWmeHZpa6BaXMnykPNfDwzl/oe5nX2NOlEUuGY2bNk2iu9UYNcitw8HuZQswVzWWGC5qpdDDIKW8F2JrLY4Q0VGXUiswLTlG8jNyObuZKqG2rqQAMLcwqt4IpTJS9AsgZiL3I5TroT9aM4+2C4kEKOJ0CL+lAcH7ixPI+I4jX2/M0ZoIggAqxuJNItAkfvcD7lr1/cC+W68enj3/oOHD8nTD7bPoiBnJLNQJ4cXQS8mzoNKiEbkQ9aY3CAMIUAnyx55cXRMq8XpnbO1RP6TH/zgyfOXm2krgtgtNsOVG9uwa5qu7Wi5bsaUn798kmzSjD/64z+4s777+MGbjx88Pr+3Pj6SXR9O77793u7eMKQpp2ymWXRgz+yaLGc2amLs2hgbbpuWgDFPFseHj5fHZ9TrdL29HLfXZw/OhmG7pmW2tNsNlrxrW5aw2QwXl+Ou3xCrqmadiKVpoyOYTU3szk7u/uQnH11djm5jsCaNdHp2FNrgw3jTX0O268Xy+A6vl28Mb9L15XhxcbPdTZvtWEXdakGqJs0wC8QSpAmBOeQ8/KP/5Hfe+94b6/Xy+ubiZrtdLuTkuH3+Ypum/OD+w3xvzczCMqVePXWhW7UxtGw2bsdt0hy6qJp3221KueuWgblrhUIEvGkaAjdNjCGEIO2yjV0zWUrDpMpJeVTeTrbZ7oS96Vojv3N8mpZ5oXr/fH25ebloj1Ztm9D/7b/7Nx+99fjNd978V//L//77v/+HL8ZnbVgwqUvkKBNSmkZmcrWyoou0vjCx1LxWYf+7l3LjSrpggt6GE6jEWEJBeQpMzSJzP3Ufp5Eqg4k8FBFoCg1QhAYJxELgQm+d3byCIygCATobA9/vWV6cOpaia1Qll2eGafnDzfxXnqUYCcp7aN2L9nblWRWbhmplTUkklF0zSGNAUVcZ844DzOzBw/Pf/o2/9x/8x3/j7/z6L7ttv3j64Reff3yzvVydrKQRTN52TYysOQm86eLx3ePwpNtuUmyaLkmfchoVxIiSLas5B151zSLG77z39vd+5Z07Z8fDuGl2cnp2dH1joQlEHhtOicwwjlOI1DSxbZsmCgupJTddrY9CiHTTB5YppSGZgXfbabvNjtg2i5yTeZaA2FjbabdgFkuu45BULU0+DZgyKORFEIkhxOBMk+bs1sSGwG4emIiVGEpDP2nbrt1dOMZWUrJ+6On6eqFrCJ/eOXVy9cziy6PGWHcTpZFWq9AG3exenh8v2y4wZyDEsFksoo6+XiyOl3cX8eynP/ri6lm6fD50TcdubWyCBBBNyUITTWGFdWFCxF5auajV3i6OMmPLmGouHWVmb0dv528Nkx373iM1kjCDYxYSP9iQym5lVEMNRo0uqq9VFKHmWt3yhxxwLdiIwZ3MGM6lAyixUzAWhkUHERgxgy1NBLabF+nmQhenPORhO21u+nFQJ7PVcUtsbjSliUS4KZ4WQQzk/TQ2IUApZ8mJm6ihoeCSJ++nhCg+EoTc6eZ6++7feOvp9Sb1O4xNkzWO3YunfX+5BcPzFlYeeTRK5oAJ3Eh83i/dSzYerwiYe6mXtBmBpnnt4rY1TQXCy/olrxKdVR0MRVSC9tZ4bgF/6y7t6/qwV4OpJ4iUaqpDyTOf2Tpz42YUB5JuhZ2oglR+G2cWpKhGrDzLk9ZE3G2LnOqBf2Vt0Z7MR/NsK15J7Yrs82cPAKk9y8nnzNytO1Si1D0u5M4EcUxJuVFvAUPyYdQJ2Tzz1c3lg7ffCPwjMLhlS4MZCRqAoZmD85zmKm9unq+vhLZW5/38Jomq4qwylR7kXkQQy/Q3Kp1h66Fzj4qaWpwhmNfFa746a1/Ry9n8U+2wRlRyEiXuN/PSgDuM06RAbKLaVo2a82ZxLL/0/e+c3JPkl4sVffH55e7q6MVnw/OnW0wal75YB6hfXF1M2xE9BBxMCAHGIzb9E3z0589OTo7WJyenx8vkzsLBZbjp183x9vm2v9lhBIORiEBQCt5mSySgCGczzsRgKe2qISQlTe4VaiImcoWZwxzmVGRfiQRMJMSEQVF6SFQVfiMpPrAZjEIBiQCGW5FzB9TciNg7CtHFxG+eQ1v87E8vv/O9u2f0+OF6d3W8XfINEbxjH1n7wFMTNbolyxmC6aqosKRx2E15RyRHJ+vYLCIvWZfXz14+//D65tPxxYeD5NhAzMxGQyZxDhKnNFl2EZEQsyaeJFgMjkhuo0GBnNkphvbmk5tmEW3ZNafd8t4S/RNmkkbEhUAeapEzolq2KDHGwN6IiDsPo+adq0vTxKVIE9thGsZhzKqekLfOQstu3bQxBJlyMkKp2pFiZIykuBSMRNMeuTWq65Dg8EKr95KJp4pXFdcIDnWvGnaleBdz8RKXUuYyeLWux7VK2cw1y8Xmu7lXk1oz58IlQ+BQwCkITIowo8Pc1AEYPNTPOO9TCfvOEiQs7kU8y0oasTBlv5kh4zNH5xDAuk0SUKlB+goS1/6E/cmH8MhXnvxzsZ1DUMXdRcRfPb4SLfnK4y/EwPo6TOoQi/n2t/LXc5RCuddGovysqvsh/AbA7rWrhRD2H99/8BDG+oVQzMMp9ZXfOG+K87/sT/jSWJQ5xiE4XE2rxAazCIlISlPOCoYzpZyrVmImNXUycICQNAHiFFADEK+BgQRppG0oqmrKk7qDlUiSJs0GQkKCKTNLYQQRQOaFeFrtO7S0lpuFsyv2wSQkrl5wJc6uCZacsuuYq+gWo6bxFW6WYVoUPatwMgAgFK9EOBMIRYmcqHDwbJYvhldspG7DWbNacjcEhCjdsqOWEykMrqVD1Gz/igvGRMSBhQPUB3eYuuk8RA41z1AzKwL2LMLKRVfYzHLW4kapFYRvL558CObXN4Yi8AgkLUJVmrLDULaDGrMRqVc33KuUOdzdXJkiEbEfioahKMhXzF4QG+EYJAbhop5bpM9NrbaKdC7VqETEatXu1kJRltKPsqjRyOyAGgyu89ftn+mAnH4byR7U9xUCxf5fea4XdBS9mDn5ihIdG4EZtRSVSympV4+ZIOAiviMiDFdn1EJRVBCs5FWcAbaqZVulMWb/m5ANTF5katVdSjkTUdGsYQMDQlSae2T3os5IxEzbzbYzc7iEaDblNMLZzb3stMylK/MwDS8vXh4v2+OT9fm9O10XLeuzJzewZtf305hKUWXdVU3NFAwjEiGz7JpCtMAQhpkOUw7iD+/fe/z40dm99cXF5YcffXKzvei6k9hGN+83m5w9Smwit23jHqarq77vIVgulpSx2Vx/nH96dfm8aztN5o7T07PHb96PTfvi4iKZrtfHsGiTp2n0nNsYjtaro/Xi+ubq+Oh4uWgmTZfXFy9evPz86XM0JIGW647GrD4YKCAAnHTQ7Ea0Xh+vVqddR+4pIzN1UombFlhjXJ6c3FH9yB3jZF88faZmx6fHMUQinsbthsZnT549vH/v4f3HbXM0Dra5GocelxfDF188e3n5Mk0ZRA7LakQWm7Ber87O79y9e7ZcNt//W790erTOOsUhdG23PlolPTZTIm1CWC0XIkJEwzgRS2xEAlFJ84knHRbLbiEdnIbL681mk9LYDzdRoogEDrFbFp0qZiGSNOU0qmnOysvVXWlWbddtj9bXVy+fPX/+/Pnz++f3Ht57eH4axqlXcYIIN0Ai57v3z373d//R+uQorOR/+hf/fCHipnlUCaSmIkGTliAuSlWTFY5U5q0XDqMws+V5FRURKiJADuoMKx2j1FeD9gthrvFxFHiguEVBJLYMNbIqt05OTuSzra0xK+Zlvo/hKoTlRT2vwlyEIFUtmmYxOgParvGK87sVEA4zUcALZAVyd3UATFTDomIBM0IIpVbb1Eo0lnNaLtqdjW+8ef6bv/Ub//Q/+91f/eW3hMYPPvzhn/3wT/p+sz5aPXr7oQRpl8sp9UmnKQ8OMIXj0/Wv/dovj0P+oz/+AaEh2NG6E4kGG9PIQvfvnT24f+/4tH30+MGds+Nx7K83l2ppddRJpGHozbxpOuaKqLiruYpwU6rvzbJ7aJrV6ni5TOOYtje7KU3DZOOYAYttE2JpM4IY0S2kW8TFikWCC3365FJiQ1TwR7SNLJZdCDyMQzbKWWGc1RgQ4rZtYiNE5ppynqZpMLU2WoxxsZBxSLv++vLmuu26Yz8d81jIMNt+58DpyXkaLUjThjbEcOdkvVxDguZ047YTBxpp2HVMl9PlD3/6AheASs7ehNDECJiqlg4oTOxkRASDOUzVXKFqtQZ0zm3U/aN6SA4iYvKDioM9LjKTtm73Gp9TJgXNeN2/coDcqoCAveK+FliiYKWVUMmgIkcJImKBC0AkTkRqyZjaGBWcJ3MYxwAAOl283Lx4cX3+7v1hSFOmlKQfeiXvVrnrpGvbtpVpzDoNJYPVts00jaowpijRVYc+F96GKzRrzgnKgMAsJ8MCx8vl5HEYdkPfnrCMo15ejpvNjvZ+YtlPS9MDD2VL9oNt2WfY+VaMkuSAgVVhoGIuvpqXVV8yzSj1fOWZ84CCoLhWp7f+D7u5uR3kn2ab5LPr9SU3G7dfsQe8b39dXJxbifp5vVXP3PckmP0dzuN+ECAcPNSXIhpCaZxtByd/Xezz5TdV3Kyw9/mZQYiCNLmrgQQtwDT0O4o9SXCi5XrpKKNjILipuhYTrWoH33prYb/5TmbWl3MpbqiE2DrKhVTn7geI8L//QXsR3hlOrGEXOcgcMmMFVNv9gKVInQM+Zj8BcXzvV988e3Tn2c0PLcjnT66uL9J2mNjAXTg6FgLnUft+yKNyRECwCXmausUiLk830+UXn23Pfvrk9OHqeH1y3d/kUZkQWXbbPqe897pr4yMUveAKcla8kczJiZiFxMXUshX6Xan3A6F2b1I3N+cZBYeXOhMBeamLAYjq483wJlW/GjPPtCjUlWTuctUOu4EXFBvevbB/84d/ZCm88513juL67v3jAZc6clyFxRlvPk9Zc9sscsppGLGm6+trBq6SyTaverq8chG8ff727s0Rb/FP3v/g459+vrm8icLInEezMSM5U2SRnHKhZzLx/ukcEJHSmHuyaUpjs1iAkLZDuhq3cdtfTe1N9+CtB1M7MDs8a06TTgCHEJq24YYbi5oNEmIreVJVhTIbRY5oRISud/3uasAEgMZ+h9CcnJ2sVit3e/n8xZQmEIIEMlh2y2qZxHmOEbDHWKsFccc8+3Dr08xnzuFbgYqIeL9t7NkqwK0hMiuh4byOCECt/+DZQGIGieqXFcDXyzSgWq3I7CXnJ1IWoZerF85XxchnOIlpT/qir7IqX3fsQY/XrNPXATV7Otj+tD3M9HVf8QshHgBE5FbSerachyDSN3w2fEuA6RtOe+2bvg7V+us/vvzV+1f/ZQyyHPvf78tBDy/y5Zdw+PHXQMp9xeJ+yL/NPb/2Mr9uFyz+0yvTtngFr2KI9RmrOS4/WoF/hMUjVTqHWS6sXWJjrxFBlNgGZ0NwiBVZdGERCUwhQMgImZBJsxkBZNmyO0oOPGtmBDARGcjcS/8jciulEQRAiNQNIGGp6RsnOCw5JUeCK7maqDhcJBor3FikICNF4V1EWFCYU06uKZWEU0FQhMm5cJG9CLVXc8KOADfzwh8PDoJyriVpkTlQKVHE/IrcSmTINaXn7uZk5FxgCjIteklAoaSJgLx64YT5rsDCEIZbASDAxcFyotJLi4yciUMIXMppqPavlBCJQLWSkbzg+LEMax1oKkNP5AcV3CUILKjWrbWmItgOCCRARJqmocBg0rljpppWAdY6KeHmRiRA4EC43dALwsRALQUsrGeuVn8/Q2/n9hyFlKPEufslOU/7W6d09ry5TKQ6wYkYXKJZArRk9ZhI5yqCeSlQvdMS95b9q/hO5cTyh90dVsCvWeqgPnxl8LqxZctUBoq4QhIaPBMTC4tI4c+pmimKBuswDBxDaORotRgyq+ukaimVZiIpjKoO+NVVP06f3T1dPrh/Poy95jG7Hp0s+j4jpVTqwiYgAQEQoEEbGydSTOYZ7CGibRAIkdwdR0fru3fvPXz0kFg/e/ph30+Lxcli1aWcdsMupxBDbGILhCCL09MThSR9mV0XbXd99XIhQkKdtWxiqmq26a/jBcfFop+GMU27fnd+fvf4znq5PFm2TSNSJEhcdhLT6NM4Dep9u3RCTKoO63f9k+df3GyvWeTeg/tN5KzbcZwWi+WdO/dP75w++/yTbJJz70ZR2hg6IU1jT4jEYZzG5WLVNdCcUtLNzbZtyUExLoPQw0dnJ8fHTdc0MRwfr7//K/dFlp98/PT99z94/0e7jz7ZYOvQhACs0K317OzOd77z7tvvPjo/Oz1eraahf3lxeXV1oZaIebVaAdYP25RzGW0itF3DwiyedVIbyeBeKJIUI7dds1h2ntxh11fXBAoxnKxPu9ar/wnOqqpmSdngFN56440h5XHa7ZbLNsZnptMwpJRvrm/IZdmu1ytvQnu9uVwuTk5X5wR38d/6zb/723//t//H/+6fP//1y5OTdewaajn1lnV0cyIKQaIEotLGAQXwVjUqjSZ4X6FbVwgzl3X8SuKEHE5KB2mYAhSVeKOUR1FNErIzhEOJxoolzyU4q1JylcwYbL+obn/wvT5dhbeiiBS6Rg1ISeGhCQancjWbHdCDRM7tM9Xdjx0uEGYKreRkpgbhpmEPBdHGzkZ8iO//3nu/949/553vPJ60n4bLIW3u3D89ykvNaUi9kplr0jRMwzSOElma5sH53XfeObq83Py7P//Bi+sJWwxjD+kRgIDjO/Lgwfm777753V96+9mzJ198/rkErNcr93SzuZqmabPZiEjTCDOllOEmIl3bNU0dNVNTM5C07YIRp/FmHLObCxuQiY3FzFPWKSmiQ8SbJsRAxNnYd8PU0ARCbMprUSGPgfq+t21WZPfsI9y8CbJoGyHmwOqZyOBEpEF8tWr4qLu+vN5sp2FKyuDd1dOXl8vliki2fU+IgVpCZDRRll0X2thGcaY+6SZPmchaWXZNOw3jzz58HzfgKF231kHdISQp6dCPMGtivI0hGCh7U5XtrNE0URXdd3dCLe1nIsA9/4J+plfex+0vDv5bEdtDr51IRIi9EBtJCqGaPCWqm3rhpLgiu00OZUcuJUIR6pDQmBGEXlxevbw8bprvDGPWLK4hjTyZ5jFoYBUIBwkcpUSzTBxixHrVucZxTLs+mWHcwGUMlmziyCEFciWfJodjifXRIoeTYdrudstw94zD8vrm8uL6igkSGuThYOtFkQPw2T2mGZIi+FxcR/MeyfsalW/v2P+8AKMkkW7PqnFlacs8e9RciwMPJIfxiut+cLk9xF43f7PiC9nBbc94+j4kq9jW7M/4fjrM/VO/6QlAfttSABXx+0WAnvrC51jX3RWMykAsQBUREYU0pdgej3mMR0zH0EtH1VIt6bJCj5+HpiBQ++c4xPu+iitRPduSTC0uXSHq0h7L28t+fdVr+Kop8RUAIDO8lI/Ob9ydQ5X5LGL1hUBs9badADIwGRhpzOvzUZo02e5mHG7G6YuX17ttpq5pVxSlOVov+5sxJZsmhSFEDhRUWdNgjS+aRcfDkIfN5e7i2VX3sBkSS8NrXjdpcXG1mfLocAhAMLFC2zezoq9mUCKwCIhK84uCYzORiGQoF+XwAjGUN0BFfaQWUaBAYvB9w4FiXkpA4bXPSbkuzCuC7GWEraQ+kVI+Wq2l1WT9px89OV7/6M3Hb9w9u/ti8+TlD/vTZbdcLvgI08X1ZpvZRiNFQBHfFRJhPjk6Pn9wCvvo8hK+dSjGPv/sxx9uX+42G0SdKTlFQYSdao2Ccy17hLtn1amfmqYJbQghBA8IpFNSqHOVCxjHqX85PnrjIfsiBkBSD7ue1FR5SYtlayOmQQWiWT1lz8ZESjalEQNEaLVcVSpURAytjTRO2g99jAFAygmE2IZA7MnVs3pRPakTag8i7W0C5vzHPCAHgIvfYliFcs57mZIv4UTVFjmI9mM7g+wlUpvxrNvl5nsIidydiSQEK7R4I/WSGi/cgPkLHTN8vOcb/wII0eHCP8QHfiEDdfh13/zVh+jVVwImX3n+a9f89k/3F9XA2r+IQ/DsL3jNv9Kj0KzK3YpI6exmc8SOA+To27xE+/+Ie7deWbLkPOyLiLXyUlX7ds7pc2Z6eoZDcniVSPFi0bpQkmEItl9syIBlG7IN6cGA4Vf7yf9DD4b8A/zoB8MPhG1BsAQBImURpDTDy5Az7J7p7nPb96rKzLVWRPhhZdauc053c2ZI24m+7F27Kitz5VqxIr744guzUsq8xTITUQjBzHLO9Q11fH5w6frPY/G9ezHzLD/AcCD32nKOaMGJiaigBAkSGiI3WCmeNAlC13dNoGkaU8oI4FgbJcwLkQUanDsykLFTrQgGCzGMNemQkxfXpEhLTR8WHVCGG7QUhxEWyMotiIiIalFVAnEIIqLFtZTYdiEEGLSoljJdJRiQgUxQcl3yf1UkVWFsbhpDUzU+3arGoakZBFTTyiIijMDMgNQ0vtWNhR0U6r4uKs6QKhlZPVESAsPIh7J1ZTAVK6hVbzM8R3VjgcNKcaia911bkIShVS+eWCA8K2eARFy1mAZuQmRQk3JGVQsPgTAncuqTlPpFc8E0GOxuHFC0VLSeGOwMIicjWbAqJmKIVJlTB7G5A8ZMgFilVNXwsiarmUCQyDEGCcLC7lD3kovV3mU1B1UpGwR3Vbibu6lBN816KWYzNTNVABxDnZAKzHx/OrbD8zQ5qDDMM3nOeCwomTuI3sz0HRpS0+wgYgEia15erUABEuJaTy5V9Q3uoGQ2d4YsIAIdFB7rbHWGM4G45t71gZJLVCn0boCXjMC1mXWtJCFBYCFhdwQEEJilKq6p+7yJAqV4wSgxhGbddQ0pnHAaZEppt92pmaqZI3Zww5Qta1az2+2dlbS/3/+FX/m5+/thmjIBqeSb29v7293N7d7dXDwEJRFXKkzc0vlJe3rSnW7609W6a/pI3enpqapdXr7+o29/NKUhtOGjjy/3+5xGnG2k7zCMd23TnZ6fXTw5O9mcxaYbc2KmV59ejaPe3N/f7+4fnT862WzM/fsvvv/H3/u2GpqmK/CUh3HKJyv8+Ne+8fTxe20Iw7Db3t588NWvhCC55Mur1y9ef7rd3kmzPj29iDGa6TDuCViv1zkZIB+8/+NNXLvH++3w0Xef/87vfFcIqmhbPH1y/vTZCXNrWsaiN9fbYcB7jzoRubq6e/H6Zre7uXh0drJpmrhqoj9/8XIa97vtlkzgtF6fPnn85afvvf/X3vulf/dv/40YNqWwecylqJai+yltt/ubFy8//t6Hf3z1+ipPY8pD04THj8+ffelRf/YIgLlO01RyNjNmCo046TDtVFWIm6aNTQxC47ibhokQ1+t15eTmMeec4R6kCdIIB+YA55xLXcGxadtmFWKHNJYM5vbxoy89ffwkpWF/t3PT7fb++ub19v5e+JVrMONnT7/8wVd/LEirho2c/e7un/1vv/Eb/8dv/JP/87f+KRTnT0+563fDHnMowlqslBI4AFQ7zdHCFwEcrn607niOn/zgqhETwH7ERzBb9sfanxJW14mTK0qVt6Dq+4MCmEDmcxNQdzeYzPpCwCK1Vc1I3T1pfhGsOhN2K3ZWMSzPC0nEwS7ArOU8h78CBzlZlf4lUlV3iHAIMVCzS1u10vd9bMKQhlzyyXn8uZ/9xl/+b375P/t7//Gw337nw29dXX2y397c3t1mTfv99vLq9YvX3/8P/v3/8G7aT9Ngrh7YSMjt7u6KgLPT9f/w3/33KfvLF5e317t+tdms106+3223d3dDGv7xP/7fpzSM067v+6dP3+v7GELQUnLOIYTYhKJjdcGbNmxOejO/u7vLJTPz+++/37YrZx6m9Ory+urqnkMjjWYfi4ORRKRdQwq6Hv1J066ERM00a/rZn31GwiIsQZxdVbPmYRz2w07du7aR0Ggxcg1Emsrk5kgpDdOE0zMwwZAcE0uUUChobIN5urwevvcxHl/cS6CbW09pEtue9Ovzk6bxEKjd39BwPwTes+QY+fHp6Wl/8fT8x158OPzr3/wmCD2F3f0QpWWLafJxTGlILNTEtpTRjGoPZAjE3A4iJQtaQVw7KFWyw5yhmUu/33Q868b7rjc17xpE9BCY1M3dDw7VEoocn9SZmaocIRMxWESYbZ8FDA5O4mBUCUr2GIXEc8mmWaShyGg7ZEOLT3bXH1yeKMVPX1zd7/3myq7udVB03TRN6Nehj52QeOgAK5Pe5m3Xdc+efPnVi5tPX97e31gTOviYBje1XprQtdOkY54gwSUToZSRyHa725dX8SeeflDQffzi9rsfPdctpr62ta0+zAy+1FyOz7r1RAB0blLtc/pvDqvePQ69ZfDDBB7LcyDiuSbRl+PQZ2n5lQ4oTHWPZ3/4sy7G1TCTK9zh5Acx/ppCPKISYAZXFgB8NkQPwJYvnRrfvCf63Fl1uIg/HbQ7Pmr7mdrzscLyBGCAcHRwSRMUgbhvuvs9v7q+f//R+fOr5z/581/zgX7r//o3s5tjChYhcXtL/NgPF3Sw5F8Qo83ZB4e5EYsviqcLreuHhIk/+zsq940O7eAdaEUAeFWIAjtY3WEgdSZmteqft32ZGvyD//o/GcPLnd5Rt/oXv/l79wkc4/pxn1V9IqYuTdPd/a42Tc7JQJk0cIg5q93uLDgcH31n+9Ht7/2d//YXpFE5aVZ0Wrb0h7/zndutkgMRCignE0KBs0oMABweREIT3DWN7upmZuwhSOxCLHEapwO+4z6rrta0ttOcBwXoAHfAQKicYTc3sDnVsrBa7Ew0M6BRnV43B6TrNknddkaBxiv97X/y+1+/+LG/+Ovf+Mmv/tjv/+G//OoHX6XS3lvu6PQV397d3rlY6EPR3Kxt5DuaAAAgAElEQVQaowzypomNSB7BjsfPLkjlt//l7373n38UnogoqYEACaI2J3vNlJgZs1tdihbNwkFOGsALckm5VN2NGoS6OAzZyjTC8HH8dPW4vXj/5PTpan3S9Cu+G3ZgOT3rr15tx1w2/SPLtNveB7a+W5WMcRjzbg9B15CjUAMvUC2EGIM40T4NgEvkftUGCqxUtEBmbQGHVYd8JvQd1jVAVcKmWvq6xO0dEpZjbl/sTr70AFkW/8E6mVnFueZTL9gl22ECYFHmm9vce02T13pscsJSQ8eVJeLZEzkAxqzyDnjVEXIQMYmbqSn96cj6w3EMRPhCcTqgN19gEN5CJA425FgAHktbw+Oz/eB7wQEtOXy2XuoPAiV9NgPrM+CSz+YBPQwBjsblLbju/y9I63MSAm+Uelas54BhHa728z777ouqeniiXDuCER2qET+TyXX46s9Ept76rsOo4s0Brx3rZp+CADjLQ7AxR/cPfBsFqLbrgVdRJ2UKxExRCE5LpTwRiGtNiKhU7qo5zTK67MIWrLhO7qlAqfaJnq9BgFpvWEVOyA1e719kKeWtQ46553mVbidzUocTGdgFBbWEkFTY5sRmVaOn2jQdsLnEa+Yc+aL4aJhvxMgY7K5VTH3W7ONagugk1S6QKAWSqtdu2SgQMRmZeclFQcYkc1CF6tQYhJf6FqC6SwbM5QqL9N/chNrNCkAxSjG3ZNlypEBBBEUzanUQFjilPs0ZaSrKwiLMwiwM4lJKUWUhEB3oCbNQZ50Kh0dfcchli6TKPLaFS0+zbmmIQYKEGFi4lgoWV3U3GC9t6WsUCQDOXItzqqtfyWZzm8iH+YxZ/nYWf60ClLQsODpM6c+e9Mdvgj/wQZaZD6pamIc1tIhpUZVhU68aAlVg4eAH21I+texiyz5UpTEBYmIGtGrVqnnVw6+tCMGzFKPXPrhaoERNnYBcwwBwZcSrzgJhM4ZQg+mCcdiHhiLFYqlpm9WqE6FhP6gZKrIAYnFmqPtuv1NNcHXzT19+z505BCKadHSezp50j56t7+7v9+MQJXZ938RIDUKDzbpZdWHVN+t21cZ1Q6smNrf3208+efn8+U3SyRkSIqELwVg6ptYNt3e7Ycr7aVpvNk0Xm7Ai8feenUI1kKz6ftW3jKjTBHF17MbpejtVaowwsmE/3Q25i826XQnLJtmQs4/TtE9bRWlWKxFRzW0bJbAE3g/ZbndtZzGuQgxAmEa7vdldXt3sdlg30c0nK9ttWa8tRnaNqrrbDo0Q4MMwaCklI0cRaVbrk7YxIt2sh75fdV1bBcc364ZlfH314fY+pVGmvUwTzJtcjIhCU0A56f0w3e53dz/9E39xv90NY0hpeH15aUinZ2sJoetWVXnC3JyQNGtKOWd3bWLDoVutumE7pDxZmQARbltrRULTtm3bmbmrp5SnUBppFZ6zCYmIMDNIppRLtpxKGrOI9avVZr159uQZVLWULnbjkNI0CHW7++GF2abvN5tTQBLJWdv9lV/65S7GQtO3vv3717d3J6dnMQZTczNVtVI0FQlMzIHD0QJ8SDhVvPhATX0I8KrqENddBVj0YbxSMGdfHHCHiMK9wsDktDRPmA1x9QsPwlRSNaMJqI4hz94cuZEJ2NwW4te8Ug850coYPXieRzZlthPzNxExc+DApKUonNyIIjVtW4xKTsO4R0C7wi/+8s/89b/1l3/iJ792df3pbn+3H6534032MfSsE5S1dk/fTdtiCYHgAmcOQWIgInhJw/bVq0/32+n+bv/q1ZVZHUvSUsY0TNOw292rFwL3fbfZrAFDRtf3fRrbth3HoZRsaqFBjFFEtIzTNI5TZkL7lbYOsAIKb9umXbezaBUXNxBrE+n0rOtXcbVqQaaazQsRxvHOCSFw07YsvB/2WRVEMDChiU2IjUrRNLlaStmdYoO+79drn9IYO2L2UkZQ4VBCJ5u2M6erm92q165vY9OUnAYz8aZvTsnb/VbH3XD70Y1huzlJT5/J+19aPzp79Gj9XkS8fP7J/Y2eNKGVlReDBxCVrG7EIQhTLcSoZLG5OLxqOc67m9MBgKh7OdMhLAdq74B3NhRa7PDx7rLoiiwqS2SmD6c62qJqsVt9Dy38CatdceoOW8HaSkAEW5UygUGA6IbaDwvFJigm66A5rLvSsgPtqgOgilJcM5BRRkxiwspWhGNFy6YpuecgcfXopImZbCpl3zdtKxnGgSRQhMKLijO1RE0x8tub6yRbUJqKI653E15e3l9eX6Fu/8Y1rCMHHZSMQeruDmZUZsgBy3sIxO0gUokDRQnA3NBhxomWBfp5xzH1+ug4+Mn1+RyKIRzgGs/gwTShEvDeiSxmjuhRfLmYBX4TiPKH9vXLy4cPHSYPww3vfMU7HrtXzWemo5rTB7BvZqB+0YhUD22BU2esQoQkm3kxBDQxxCZyKsxQ+P3+7vTJ2aPHZwBY4MVcnWmh3B5f8uz42DGhsPqKNX/xcAXVb3WdB9GryV8c3QeGyecenzkyR/9bvqqe8eCsOsFn0TIDnFhnN4+dHF6YApNCM7GtVjJd6ld/8mlqw3de/NHv/OG3t5N/91Ocr29bHkmoX21sACPCaqvuOlGYhEMMWqwUizFCiquWLYb9PqfJjTwaQMOkEpAZ3JI7kGlOwWqhuQTYODQhRi28Oe1SynlKWkrOJWsBEEOgB67onOepaHkFR+ukZnro+DbHMPM0qGM9j/iiJuIQoG6JxGPOgUWzO5N4Z6xW0uXz17evn0ggK7i+uhy2lu6Zps4oQZyFqGE4YhMseL8ObRtL0ci4ePxo06/zNl+9uAEjeAO3sRSptEdmY1QflZfJabX5Kwg8y+kqDO61SXHt9WlaYFX3hCnCbzX5uGcKXHqE/qLF2hIKKDmlbEhFjYOEhmwkohCZJ7ZkIFxfXwqw7gNrIwjsPVeMXXPKOU3JzY1cjnQwIXWWM0xnnpvPLs0SKM3Wap6fc9nHEcxFblpFY8jcyMncQIQjYOXBZL3JwMJcyzW/hby2dzhYmOr9OIFVFz4B1Uuc84E4gJbHy2qxx8vPPwSafIjOjhfpD47MfAGk83kQ2DE09EN94wEVeTCJn3/86AysY2Dlra956wr+vI4/l7PN1ddH7vtbx498SYe2lO/imj/4ad9Ctdz9INpFb8rMm+nBmai75RGbbCbb1NykWvFcSYmoOiMOn6apaIaQRAG5qsLNBSTMgTiytKJeaguZut6ZGYXKVDQpsqEQnKAzx7gK+nBgDmxc+ZsVvgAzAoRAmguDOQizGKwUJSBALFmRwmByDiSgoTqwBILWmjpzmLtLBXXIzYOamSmb+FKnD4c0bLPcNkOqb0m0lIQteN8BXnECmFkkEFH25GwONzInC80syWrE7mSk8Cr6pzNiggWJqb5qLdBzwKFmVQQVxkwkUdzMimkqYApyqM12VDUjt+oZu1WOVK2Grt2TwcYgUjcn89qqZa6udrfaNMjrTgIrDAaTLUrORF5nZZUZmxVDGCCKTUAVMtSibqrqcBKQzaKeDpgrKS8JjCqzz0SeU67T1QlCBBGrZ6hzvgplEVWNsYNtmEfL52DD8XZ6c34Vfry/0NHBzkqLF1CXCYGCzFmvxXtTs1nWrT5ColnBap4plSNfwxOq9Cv2mS2y1FvWpVhX9Ly5oNYjFHcpxmwOYQabmhpcjGyWga/y2VpjdopUiuWUPFjW3MYQI8NDjFSAIDBCCE3XxyZyEzGkKWtatU3XtR9+9Pz8/GTdrHPKt7ttE2Vz1sGRPHgMXduu133bNk4Woq+60EZiLrkMmrU/Xe/2u08+fv3hhx9fX2YEZMXmNHR9V4bpZihpwxJibDYl51cvr25uduuT/uTibL3pTk5PSx7cwJE5CBPEWRqhRNJg1XckbKaOiQPGstul+7aXrmna0Jycnuy2d1OZjGx1so6xZWI4t21rVoSDO6VU1pu+7zfu4eZ6e3W1u765G0eNGdyIwcoeNzlpumwaabogwiJ6enrWNHG72xJTLXsqatOU3SFB15sTYpqmSVVZWBjuebcbvvfR68vXW009vGdeTUkdFlsPsSBMoCHncnN7k5OWUra7YbcfhiklLRcXG4lN62sznabJTM3U4Mxs7mASJmYBS2hEyYb9NE07QWyabrM5O12fCsuw3+dSStYkRdULrAlVCXbyXRa5BgKzNE1LUOHQts3pZt2IpGksU3HDZrVJ26TCOm4//pM/Pju7ePr0/X51Zkw/8ZX3n54+OmvX3//0k3/4j/7hdne7BxqK7i4kwkGaoFlRVDgIM2pHBlOwLykbf7ARD9W7h/3owfFDRbHMRVhrowqb5bGsxsFw4ipS6rPc8pFnV2OVJSadfSk7AApQAMWrKp+zL8JHi0NpjpqonC1sTQ/M6x+Gii4Z4GpzQbSZAamKBGkqsZPAPNwlEH7p137qF/7Sz/7CX/qZp185PznvL69e3NxdXt1c7vbXHFm9XO9urm+vh2lvjNv9HTGHEL2UKSUJQWIIRGkagPDH3/5Qi5txzjrsp+vr2/1+cNemlbZri/s4Daql61tVA2ya0jROKSURzjmplthgfdL3fVMJUyEGKRmOq5srQoyx2w/DfpdT8tBb29JqzU0b3Vwk9n0fI0uAWdltp6yTMKSlftOBKQQRgZP3XRPNp5QCk8MZ7EaavRRzzdOUQ+B+JZtNbLqwH8YQhIRTyeoZ4rGhtl0Th+04nj/SzUnXxE0jltfe8mmgfnszvnhxOWynre5yyU/ew/m6b7ltqWm4/fS7r3/n//59Uh23aFe06df7fdLimgtBYuxgJQ9ZOLhVFMjgpFqgc2cyOIgU4FleplptqgmUGhN8ljrPGxSq6snM8BURzZ2LCXoc8r8Bji5Bfw34zQ2msOoTgcmIvEoh8sw1NhjEOXDhQoyujeRcCkTa0K+3d7uTi9XIJfuUbTp79Cj50N6OXXLmEkIjUHbWAkVpQwOinJ3cpv2UkxOavlkFSW5SButi14SIydMulSm5EUCBuKje397yOslJw3HlcXNzlS6vd7uk3IA5ohQ4wbzCcvWHA6OJvNKzCO51U/MHvKfugjNL6MitpXko51yWHWufHwZzzhmSL3gF3N0rrnoQW2GeM5R1K19iOrVFKgsAIAtv650nXoPQhZtXf5ubQhzHfO61WBIzl+/Y+6+YPtxRu+C98yVv+fPVMwLTXPc6+0VkvozSQY3gs+KAyhmvRpC99h2iTlotpEURDB3aJpRcprLt+zCmkaMEIshcju1W4Owzx0eJeW5q8HCBBNJKPqHZsFLtQ/PwHqJZftUPSG4Nv5fn/XnHEQj47lHjkzfuF6hFwZj7xTo73IqTmEFpCflnhJrAgLtBgbw+XT/5edqche/d3Hz/k8s//t5rac4ena5ipP399Xm76SjcXE55NPGgJaECWMyWqhK6MwncUcCC2KKROAAl5Ukn0sYcq3XYF2VtyMNIYApeXAdQsLk5XRAJ0YnKkN2MiaVtuLrC6tCFVgzAYe4VB611Gw7UjDeFlhe8g4mqshSBdM7/2py0oWUInWZdFJCq+ejUcOz7PI0UAzXpw48+OvlW/Llf/cbXv/L17z//9PJy8hHTlqJtVqddyuOUR/TYTftVDF3buNv9zS0Zvvzk2apdffgnn25f3qENGJm8li/A5ibkVj3/uU/6ohIQQoAjl1TDQ1oy8Yt7Xlt/MhmRuYS23I335b7Y8CisT8/a/uxkxDjm3HZSVjKmctKetuda7pOWzNI2TTPCAT1ZbWLghiNZowk6BSta8lRKGfdjGTMYTROt5heISCrjgmtcSgdcaUHk56pIB7vPIn2+ZMLqKiU42FxnfO4o3PAlm44jO/AQblPdZxZ9vcpnhDMCaEnKe7WsBJCqqhqLY9mUyL0at5oxNDe41fx8XbeHBXywZ/72CvusNXrECnz39WPM4a3jLT7swVTigNw94LAPp/qCE757VL/ujZTq0fGWR/rWEX5AQO74Kg9H5RkdHudbpLJ3P/sjH4dv/IJTHY/su7DaMSR0+IjVNPUycMclhD/4jRy+4gAtHYYFCwGvglCfeba3LuwY+XoX6axHfd61ngKYDR8AMxehpmncPedSSj5aYFVEGLU9c70wK1bhCBCc3ed+fUaMgmJJqYuO2p2QiVCz+jqZZXcFrKpmhRrWkEBEJIqIqCg3TbJsakIkLGRODgbX3g1WTF01KwQcSSRUdIGJowRkALUJEMzhuZgoyXLxblb/0WpcK8LiDle3vmms3o7UFIi7am0jcVjCgHsxdYWDmZ3Na65m7lJVmxL53FvHnIVsIZrNL8KFmVmcZrDQilZYhA9V7NUDggtzlekqSR1upgXuZIiAw0wdUpsBLk4DgUChQi+o8NbMBKpAIcgXLMnJbWleKEwVxCyWKyGIedYaWIQrcOgja+4hhqpPOUeyVVZMBIsthXuoXg8qYc7crBrRkjMxcXU3Zw0wKq5wJ+YQ4wKzzor3ZuZLc6BAodKXUOskASNXd1/oGnB3nXPsREsFEchRuyPVnPtMAasELSwZj2rOfVG8OHLNveaGH5DD5Q3VcBUtqibM5pVe9uAHcxWGVodZFVR0M1cnpsq/ZBZzLVrEApgBRm1U6A5DDDFNaYY4zeAeREw0NtSfnNze3ddAtFvFENhtSnlC1fYi2+VMu1ulHIKEzovu77ZqZkVzbNCtKDYGzlomYoc3avXiM7lmy9c398+fv3z58nYYEVqQNONE47hnYU9lN+wfXZy1XaNuOWOcpjFPHOPFxdku3U85l5RyGgE73Wy6VePUN23MtuYYq4ZayZMI1pt107YOTympamzbIeVclEiaRpqmIyCnktKYc0lT6tpeQts2/WZ9fr8tu/vp9evr3W5S4zyiaGZhtzClNOTUdXJ6etKvGtXt2cXJuB/NU8lcDFTyftiv1qFp2pxz7Jqiya1oSaVM03jX950WndJdUajtNJcp7XNxd4sT2s6alTettS2GcZzGVHTaj8Ptdp9tH1o/Pds0Ie73tyzs4KLmzMyRGKYKtykV2g8hiEgs7Cmpj1PxTEVyTsM0tSH2fW/qIUQHmRqgyaHqAoKH+/u71WqzWneN9HANZFKLedVCiH2z2qwdCurMTsyKCscmiI+73d2rJq5OVquLx483f+Ovvnj1en97/a+//Yff+u53vvvik3UTS1EHC3MuKkQhimXNObsjtjFZecCVjv4hYFGE8LlhQ+3uvHR6rhsVVSHrakzMwO4yCxpW7+yNjMHccIoAB/OC+lcXua7Q6hkf0vyLVvCcFF18T1uat6IaaKoWwopB3UlZEEMIQrkUtWxmsQkwy5oCUVKEht/74OTLHzz5m//Ov/0Xfumnnz47G/L9dvf6+u7li5efTGkfWpGGi9qYh7vdzTQlFk45NV0H4ZItaaFMGBnk4zjt99N3P/wjU9HiqiiljIOlBOJag2Xb/VTMQ/RpnMZxqNVx+2HMucSod7eDOU5PQ9eGGEIIDA9dF3JBztjt74EQw7QfpqmkST2kjCAOj5103bptuyY2OeeipT4wM3b3gIa95iapYvRBmNiLzkSLJsYx6TCMVFmMwk6q7qkoRosNmyMVZVKIwK24k+U85WLW9REg4bBZd+tH57ubfHc1XD6/ffXiMg8FLSCEycuYd3dj/5W1jnT3Uj/+aBqvQcZpKswTnKx4zoUrB7nmauYkBLkumpM4wAm0BH+Vrwei4P7gWB+KzI99KugDbWQWUzv6sx8klvyIX0Lz1GQmEq6lskxicFUl9hBk3s5ycTUi5KQcSlw1EiSnEVRMIBESoZMzO7XUdi1HXsWVUnYZjfnV5ScgbTterZsxORNbMWqJKQiEiNxZc0pDcS9Bym47mkLNLdM4FS8hJzU1VqBQkOgEhpes6jjZnGrwGENoN0kFoRsmuxvRhmiqzGJ1aCoJC2zuvrQGXqTI5x4NNm+qTtCKEi9whS/5owXxOAj6HI0kEbHMYmMl6RLefm6wdHDj675/6EX4VpziS9/wg79QfzCz2i7Il2AVi0mBOzNzzWfi4BLVPy5w/JLknYNYn1/9zOM4xqgXKSwPtHE8eJyY04tGlZizDPDhh+VX2IJ+KHlKGSFKgCqeXJw/15daBlWTQNvh/uT8pN1ErIBrxCZogReDVAUNewNVmiGoAzZLB6bJIaSqI8/MxQod1kB9VP7wybfu/Y3Y3p1E3nmwM5IzZyKW1Tr/iWYCFjmMapmAG7yKgEA9MDuppj2Cc9AJiGv+O//pv7ebdt/6gz/45MXzJq5Sad97em6aopcW8ujk8Xe++Z1QWnbRBHeLLK6m6qaAs8NL0eLeRM7FxEPXrsCh7G17c991IRcKrXghy8YtE7mJiUSHuyo5GyznbOYpKzNIRKTqr7gXmM0dfH15ovPjpYMIVs3A2FLVMaMc9c6xvHeZs4eHWDPmBMCLGpMEcSVTMc1E4cOPXnUb+vGf/uCrX/na66vbIU9B4eTFlKwo1MUhoAAza7o2NnR9ed2E7vzkPO/y809e3N/eoDQUasYgL1MbANxMgYUqPU+lGa1dkGT3uVs4gUGoIYPX7sKGNnNOKNmnLn/63Zuf+eVfwVm+2t7u9s+fPn36rVcv2Zuu6fo2bMt4e3PPwl232pxsACUUEXbzaRinfdFJanAWJHRtu50yDEwcRAClzG7FCWw1J+2zHTqa+rNO3MPOwADxskMszTTJitZZL/UmqQrkFjp4SMeAAOGghwA8ODMzSl77OhtVkiGcaxbdzWHQmjAXqqoxEkJtwumuh/M92Lo3kaN5A+MHQ/LW8RZycmxOD/890F0/73gLV3nrDMdfVI+3sJSDYX/rJO+e/DMv460Xj0GS8Hkn/bxTHC7x+E+Hk3zxKPxZDv+s+sQvPj7zpt56VG8U1f+oF4aj0T+AYl/wPN767Be8cvzrMdQ1dxp3AyAsdcaoldoFjWgOPUwcAAmYQcwkVXGccpUVr/Y8MjMJw8kgzFEQKFvRrGEWEZ+VnCozSK2i8g5U+WJydyHiJkokDiRS4eaq/WgzvcXYTC2bFTfX6oHWUKhm4MHmNmuKzfs9qjV0WzJFRARxqrqCBGJITfwtcIgzqaoFBzEzg2H80Mymdvpzr9DXXGvooFpkAqr4hisOb3O4uy2NJ3gmpS57/5xuIAITcjY65O0wV6WFIDAwiXg0NRLy4F7VeTFHjO5+aOflqMKDDDKWCqzUFveHpshwcxeuDrlxfb/A4ezMxBU3MQKI2UMQIq57ozlqXu6wcdbCn/oEUBU+KrPM36JjLOvO6/ZsJOxYtKuwUPmZAkjrcqizVKsANKPibYu1dSPC3JaF5kycWRWrnE29Y6F70aFeG+TweSiWtrIPS+PBF3xwjx982HpV/uCsLhlWHBxR91kfaC6kpdkzX1AsuIHImBlOZkBxCmBVsJAwwUzJpDLUmJidK/caWvtFKmYwsjjMmCiE0PXtbr+vVQbDkEDmlrRMfStgn3Q6O4eqJt1z7JuOVDmncb8vEtBFlmDOWS2BVJiJzWGac85sZXzy+Kv7/XB3vx1HACBG2zYIzTRNXdsZ53GfU1KQl1JyxjRiTHh0gb5fDSOHEAhoRJo2Nm0TY+z6bkpZXVnEGcWspJFhfdeCaLcf0zDsd/chyDTluTdLcbCFwDmn/bBPU56m3LRr5ghE93B7e/3yxfXl5S2cQREEV4KIBLJsWmyatGRzB8hXfZemQRVKxgGgiv+CQwjocxpBJgwJAoQQQ9s1DJoulCmN+zAOXMxyKeoZGRTAiuAQxnZ7N+wn9VwzikRQtXFMuZTb212MgYjHcYotxUZqklxLHj0VtVXb18K6ruvapi3ZcrL77fbm5q5tug++9OWu7UIbowRX94xSSq3lrFRUFg0BbcNMIuRuhVnapo0iQswUIst4cx8EF6ePTjabnPL93W68v9nqzfnF426dz9v+9IOv/pd/9+9+8zvf/p//1//lux9+srvO6HGyidN92nRdobK/3TNz27VURf2Wib/skv6QozwCqQ6x1UO4hdoX6RCh0cPOVMGrGfSdc++z/8g1+bi8eMjzA1Wq2Y/WJnwmmB7OWkvIZlW5oz8sS9udAXYJgYR0VNuVrW3h2KxX3UrO27OXVze4RH5qf+1Xf+5v/M1f+/Gf+rG2x3a4ut9fv75+WXQap/tsGd5Z8f00DMOQciKmvt+gSvaaV55sNqWUXHVKab/fm1rORQunZABCBAvqDjlN4zR5MUgt33SexqSmmj0n1dYkeN+0Z+enIpXjoyHIer12omEYZpaPeGy4W7sEtCtqVzPXOzYUG5JAoBA8xBhBGIcx5xQij/uJg4cYpCMJQYTYLecsTOSIIoU0MERi14YQA0hDkLYJzhqDqGspWYIIBYUbCYGyFhIwxZo4ijG0XXc53L969erq5W2eCgKx9P3G+34QjmnMbVgP13b3KqUd9vdom+BmKU+OUAmA6g64MCQEK4kMMPJqYOskMXrL1DtqiFeV3StFoJJt33Sf/M1fgVrbUj/ly967+GlvB+gP62H5m5uLUGgC3LPmmoo3R1FjKTHAG3hVylsxB3KzjFKzcU2cFEW6zjyRJA79dn+jPkiM3Sp0Q3H3UlKaEIJLv4qxcUDNStZS0EQd9mPJwYzcOCfzQmmXkK0JsQ+dNKEUTXnKSeFoYlukhaFkjEn70KFWEJOYVaCQbIYn5js+dNBboqQaKi2w3oLxEb1dq+lH/2Jx1I/GfOZwzj7B8mAO2+6bVujwjBd/7/D6Eg4+1Oa98fZD3LiUOuPogfobX1R9CaNFDuaAIOHNOfBOiPr2QQ/egx/APHq4mYNhXdCyA4b64LH4kZyCH27da6NVBCZjh2LVt80oUeKQpuJ2dX355OSx9JANcA2Syoiz6vovbLmDOu3RaH/+LVWfZwHbjq50Cf7fGPKjMx4Gn4F3Hs4bvz9MtwOIVX0+AMQOglF1/pa2ogZ2i85hcsKjc/qpX/z6177x/nBWQc0AACAASURBVKevP375+m4YLXin1nli8XDan5/3my9ffDmlb5bRURgcGEREJZUKD5g/OJcAidrl5V3YeMtB1XbbIYTOGm1N0mS5FI9G7LFlaKDs05CcUVS1kJo9Ojs3U7WsJac8laJUiBwyb34MJhIs/SV89nSZ3MjcaFZ6rWK6tjwDO5qOD+4nVeeXaFYVt1lplUlMjWACbG923/vok2ffeNJ1fddepwIDVMdsWYI3nVBP7enpXb4qXpyCmUtkd9/ebq+uL6EcmyZKdK1OvTOxMS9tiI9SvwQAZjqHMMvcfZjyS4xBRAwmhg6lDU3SyQdk9z5s7veXQezx2amzIyfzKaepCRCuDUVC23Zd35H41etPs8GSTfuUBnBpgrRtDObO4NjEWn5upl7cTGHuiqV1w7wRvGs1DhZhAQ6XzMjym9VW5otADR5CniNZdMy5k9kyHfylZcXQwq2awSxiR+3eVPvFV5WsWXCmNgjBAQSfl8ZhhdYEz2xq5mjF/aDBVScZPfhFf8qxOGD2YD//bMcBoqEj+s7hT29tDW9dxo92/CglhA/I3ztX8/8qhlWPz2QzHV/AD3Ilh9H8vDH9YQ8/ktb6s5zzLeTrLXhx4YsRMdzdFRwQAhNRzurqRnPLLMBEqm65h0AxhtBEMBtMrXiFdpmaJkpkZq5C6NIGRDE3z8iqxUtNPwoxQK4EAzFM5pS5sxtZCMKBKLJEpgAwSMjMyYhc2AgFcCKlMuSc4AqOHoI0IZjCXIsVDkSOXNI+FwC1gI7IIVrNT1U0d2aqZTu1Ed7ckmrOFAqQVEFgcWJiEQ48U7mAWajI5ounWQpgHm0vprkYXEnnHIMADqirKYu0MQBQn/lQvuhaVgQJpT50DiIOuNUmSUQLxU0CN20sVmpbwtoCvpq0gwcmFBhVfnxucecAkbMTeBYThxARRIiInJwEDiMisLAs9FJ2YQAsATM5cpYLC4BXujKAonlB4JwITEJUIa4jKYe6GZtD4eZe3GFWTCIZz05PFSerROiaJpgLvs0Dh7mRGM/cWwGGNNFcjj6b/JloUbFXkvpg4HCzSvmelX0dBQle3Z1qx312+0BLG2ua62QP++miSzpXHNU9pNamkDghWSGCBIJDixq0Cv1jyTkBc0cYB0GN4JVYVj1sYlQJoeqmO5sIRwmFyDLDVccMoOSC0bLZwNNuu499bJq2Cd3F+eMxJ1Ua95PaWJ9dDFTUc5kuHp9vh11d8lGk66KvrW1Hs8LMAo9kTh5j6Lq2bQiwolrIHNS27TiV27udDUCAuxiJhMAOuADFwLthP2YW8YofThn7/XBzeXtyeprbxrVECat+tVl1JDwNo8OmNDlAwk4ILMLBjaeppGHc3d7d3t0/evxekNC2K+KsmkliFPamG4aJGX3fdN1ajZvYN7Ezo5vru+2tN70Kh35zYgaWWi6NaRpKRiklRnn85Ozi0QY07cdY1AmcUgJrStM0haaV15evYohdG9pGQoyr1brve3I/PbUY+pL6acR2l/f7lEtxzxK17anpKISwu73b7sdqe4gQAhFJzqpqVaKrFNvvp9BQ7MO6bUNsm7bv2qbvu+vrq5z2wuH84tF6tR72abq5u75+dXc3BsHppm+bZyLUtI2rZU+Wjcgg4Iay3l1eXb167V3TrFfrTdcHiW1sVv2qbTqoCUIb4uP+NO2G69evPv30eyHE89PzZ1+6gIe+3RBC9qzAs8dnT578lV/95V/5+3/vm//qX/32P/of/yfT5vGX29vr/TSmro0cmBhubqrEfgjclp1cqxvjs0IHzIxY7FB+g9neLdEa1VwlMcHNFlBsNh10/Imj/y6w01K/WN9ytFfXOJQefLGFyIBjlk19p8PdlWVmVahpyaUJsTkLJyfdfjdMadDB78r+J37+6V//+7/267/+Vy8en95vr/bTZXZ/ff3i6vrl89effu1rXymuOedsqo7Xr1+/vrrKOZ9dPHn67KmZpZzMPaVUSjEGuVix3X4qxbvVmpPud4mDhyDCsWiZxjwMyFsvS/dF4UgkOVtKJSff74tIPjs7Ozs7u7g4y2XYD7thGNbr9fn5ab/u7u5up5JFYtd1KyNqqOTc902IllIqWYkLSEW41uSKNCXZsB9vrodSspbMEW2L1bpZn3Sr01YabkLTxJRUi+5Lzm45tA0CKxzOQYJzMKfHj5+Nw27K+xCo6XuQll2qze9AQhxrVxAmSml6/erVi5ev0xZB0PfrFOLpaVyfxC6GhsJp//T7v//hd779YtyBFFHWaqYYrZiZBBazAjUCxRjSlAGy2rLYlxla59rMhq4oiM/iK/XvNU1Oy85zsPvH8Mwy9WjGUPGW90pHMUD9eYEYfAZf4SCEGFf9CoSUJ3Vromy1AEBDHhXiaN1IpRUnngY9O1+lncICMTlZgEFcBFqG7d11iAhqEojYS5nKpFOCuTVNxxTZdVLPWbVg2OetbMlXZMxoVMX3AyaDzhSnwNGJrYxeAMf2bqTOpMVunKZiPXMIodLfVY0DzYVcM3xQN0tbqFOzanqNpOcQyitZxtz9TfxqHsy6HucFu8RxRLWzkMwO1Yx38/EHieXYChzAygN2ji+QbH/zmG3CcnlHBmixPkeGps6eQ2xY7+utiOFPU/M6GgHzJZ05N0Oixa8Th9dSslqT9Zl3AvBMk1owALbQRmorPwPCiCwBEMhuO0yXzz948n678a8+jZ9eqmUFoWavRYKWh/zEGzfzgKDxPEB+gEt4biL9g90vjkZyGXl7YOMc39cDBlkTE4eKybrM6nJzkgAjJiETuEDNYWaZW+1aHwvQ4ed+9Wf/rb/9i3JKf/LNTy8vp+3W73c5l/2L73+0WrdfenJx/uOPnp1/adPS9nak1Paxk4BpP5SsjQQP5OqQJbJyKPDi1fWz1ZNNfzrwmHUbmq5rVlR4vx1ZdjlNLNw2jRdM+0yZXM1KzXFTHUYmM8lzBTM7GdXMHelcZ195/1xLlJjYnMWLL5Or4hAPQO2SIXevHz3kiZVAMHcPMZSUVbNoEGaz2qMSd3f7f/Gb//y/+rV/EJpOAmYksxhHjiH268BrOn32KN3kbGUYi5KKsEN1KrgD3DarDsZqukTRlfcAOMTZtEajWLJXNR8we9efN3eULACey3q18eLT3QTC6+/f3vrl06+fbs5Wn756RQTfpdt8NUFtHNKohSemQUi6vjnfXOx32/tpOw1AgpaixaZabSwUQuOkViylbMWQYQVUwDXXPkcKb6MBbxWL1fvgAz5VDcOBpEluMHbxinrzAwBCR8/uGFIgJ5kt3oOAC8+QlIdacE5AYMhikWrCnqoRs6WZ1IyoHQJVWrSkZ/7FPH/qn0AiWLI8x4v0/7Pjz/iNb2Eyf+rZfjgA661BxJtW7DMhrT/fo1LRDrrpx8fxrfKRosdb4OLDBvYDj9EPePjCxPuzwJlf8NkDXAo8aDsQLWqmi9FTLcyCyq8GzJSIOAiHwAx1uITgTDPtksFscDcTcjOHWXFVGAJmHeu69ryW4SFEIoYyvGjdmjkGCswRLsW5dr9FyQYDqjU3Yi1wkAXRUgrIicEMURSFIRTmhnkWYZ+RI8xeIxOD6vVYVYPnMGPUs6pR5RKB5sqtQBKFRCBY5K5mtKSiDSCCYW7eN28KqmAzn4WsKq5ySDw5iCC1gZYa5sa2cPOl2o4lgqhWaXLNjrhaUhUSIhAZEUITyEDJsmVg2R6YTR/s/xF+/jBR66OvhZzg2g6JmdnJnLxS8CpcVkEuYsB5MWTuAIUwr06iig4Q893ujphpqUhc5JoBwHz5vNWRIjeYGnTeDqyhObnAWCqNZuRLamRLiBK8EGrrjdr13l2JylhkWaFcJzUTZqEAUpQZPKvdFcjqJRrceWFiYxEOqCIeWtNas64PiLyyyGb6x9yfczb3dS4ssbeTuRmcXJjqBCBaSPhSG5AQkWtlFM5hUVWw9uJWyYM8lzkagQEWAjPm1gmSpxEBam5JzTBRvr/btRqdyRx9vzIOU5rcKsJoLB5iE5sIlGIuLCLSNpHBhsLEq1VXciJ4iERk7q4FKWUGMZmwdJt1lE3bdlq0lFJrY0thSqacc8luWWAigcjSpCF6vwqhcRCZ2fMXz78SLkpJ5E4BOeSSG1KbUso577a7u+01S7PZrLuuEYaHEElioPW6F6accrdpu75rtJmmSeExhGYTY2xK0dvb0ZxL8ZzNjc5OL/rVC9wmOMz10cVpSkv5M3HRqnOcm5ZPz/oQvV/F9947TTmrkWlHRDGImZpi2HsOSUs2bXo0LFE4TMOo6iLcbdqTk+7k3IchlZKJIcElOigD2N1fg5AzQOg79KtutV71/VokuoVXry632/04pOmuxEamjW1OuvPz9cnm7OLR2X63N4UW3e8GLZamPI2jAU0TmfJut2vidQjSxkZI2jZ6w+xERKqJhe53t/f3WzZarzfnm9Mm9iUlz35xfnFxci6I2+3ue69eaklU1N1pKvtXw/NXzwG+uHi8Xp+wtLFpm2ZNbun+7hvvf+Xrz77cgn733/zeP/unv3X9ByO+hCfvdUX9brc1Q9s1Pou/POwvRFRrswHUkmozI7AtVIHZFs12eSnrnUtyaM7HPtgwmiNZOo4fcdinjja2z4kSiZbrO+Q230mYAeCAQ3lKJeTnXAzaJyGS3nmDpsN//l/8R4+fXJycdbFVTvr644+3w+3t/dX13eXV9euvff39IKGwTqlks5yUnNt2s16vN+v13f29WilazExE2IM7GQVzkSZsTs5TLhKGlAoxk7FOMOSimAr6FZi4b1cijRbabadx3O92034H5uHxk/OTk9PVelMKpzRux13TNOt1W2Wt2MHiIbpIUDRmsW2DaTIvarnuEWYKcJ5sGO639+Pl69vrm4yMpp1FXoZ9Skn/H+rerdeyJDkP+yIic1323udWVV3dPT09Nw6HI85FFCxINi3CliUbth98e7DgJz/4Nxjwi1/9C/wf/GRAgF4kGDAhmRJMmhYt0RKp4XCGMz1d3dVVdS77ttbKzIjwQ661z6nqC2dICrazG6hzzl57XTJzZUZ88cUXYO7XgQMFYTNomlLOqlBXLaWkaqOviMVJnj272Q+HYRhig7PLicjGlIgbMOfi0sxWey6Tjnpz9wIF3Rqrtg2NhNhWgTi3ILKKtH7xbP/BT17YyG4SQm96FGdXiBCqtqWqEZnxskXUyBjI63ZmjrkMSP2oyqvNHqOTmcNqatunnOrXmwPCfApdg5ZAsZfXpmANlTl80ceY3xQiYQkheK2U5wSizXmbSoEItcheILm6PSzoWrz11ltDO2kRzWXKk6srKRkcmvO46vtS1C1P43Q8alL0LbABQwAUVXerVYXhmKZJqAGIORAIRZu2bziIk2Wb0mTFSStCjZtXu/7S1xdrRgghRIrMDIPpUoh3aTa7R/cUrIVRuThNJzjK3eFk9BkIVkWnTkGdOlSVjwkmLLBN9fdOy0Ttar6X/sADA9gfrAuf6VbcH+mzQEGVoQAeLCnLI9Ey5qdnewOs+sxLUI1a/Rw+TRUwnX8+gVDLgzyE5O6BuS90PQo8MFWBVBgcxed8a3HF9vY47Pabrnv69O1XP/p4SMVP1IvT6Prr6+VrD/jmlR8MwaIb/sXthAJ94ePQKWLx8G+v/6mepOYMwJmdSYnNIVAyRzLKaIG38P5337l6b3033V3fDdPQ3L447G4VlPESw266nXbX7f7JamD3hqGlpmK6JoWBgqGmmZA5KcicOQZMSTn03epif+tTNnVpYyTiEHPXR+LsrqF1F04JJg4hFIc7WPaHQRgi4CBRorTwDB8JBlU1d9OlwtV9lIiIYSD2OfXnHr16zfV7OIiLIzADXsYhIhnM4FrnvBg3TV9S+viPtW36EIMZ8kL7E+YYghADiF3XrlojG9KY1ZsmrtersmYIYABDc1EtaoWIuKJpywpwuk9a1H9Pbw0tL/zrY13TJNlhsQlwgAKb2S7/+I8+vHw/TMeUx2MfYzAUTZa8sOikPkEtH22UEEX4rSdPXxnGXZpoAggKTIrJvWV0UU0d5maa3QtIwTXmZhUKecCxfLhBfB7eVpe5OVezHllTDmGw6tuevvzmokH3rw6f4iV1sbGFcl7PPws3euRAi/IS0awdXFznW60OzoNepSXS/2kcYw6f+6xzfF8E4y8aw/qC1fgEDX0ejvHz/HF5T+6RrC94hJ8XwHrYZVjgqoe3/q8JunoImdVfP09p63SHtLSHiA8+p99re3OK/OKjfjr5F7DD/szts+DC+gEAqFa2/Wx1qRpm1SoicBBdounZwVY1D0Tcq83qMDU3FDUCwU2h7MaOGJhrZrewM0PmEr8RtdiEybwKIwJixu5szuZk7oA2BIa5ZvVspM5eZQ5BBoLbZJ5hZCYIROwQYoTghDEleCW9ALW6DzEFR625zLWEkbuZ1oUB5guSUgvWk4gLGUFNrXq3xMQks0E2Lw21wiCAuVhsta5OI+/LDkyzBe3w2auqAL17LbInxMKVyAR3cjMt6jpXkGfGrNLI5CIcnHTGUyqzaBFbv9/ZHa6mVX28GmezYkd97loiyZUwKyowM8it6nHVUAI7UAVSnWSuPV5zrOFyr23opjA4MbPUeIXPCpJWz1jLaVPVqZpHBDTH83yWwqkWoluxEALhRHGSYq7FVc1UfS7JAk+mS07oHKRiug/l+GzycQhgYmJduHJOBlhNC62xztpjTAtqh9mIrWPE5nPK+elVqlsLZtou3K3yFIm8MnvnKgeg+iHNwRiedXqtjvtMq3CYGriKjdVTO5jATubMRCEAlKdRmgBCDY1qwW47THmIfatO6/W5Fk+TqcKImKgUK+oOabu4294Qo18FZnGzaZi0qGvu++7sbL1eb9xsHIdpSnlKUI+R1v3q4uLiYvPUTHPORpAuwqXKfSnULCfzvmn7VUcouks5l6aUbtWuN+t+3YeGPvn4ec3/jSFsxhFZu64RllXXp5R3hy2TtF0XIwE5CLVBAjfet3bWb7fbrgl91wThxNApDVqaEJumE7ZhuNvvp3Hy/S5Po4dmtVqvNt1hP2RYiY+4VijIORO5CNRRNJtls3RzuxvHHUhD400Iq3YlodFiViyQbDYb0wJoyZZFS6mC4y1RMVeHMmcRxMZCI00rIYiT5kyl5H7Vqpl6UkVs0fV9369CbNwJJDc3+5vbgynGBAk2Hu+GsVipelhBpOu6ME3TcBy3d7ucc85FYrjoOwYXLXfbuya0gaWN7Xm/ibFxtXGYDsfDo55Ck2NjmmwYdjolOG+vt9fnN+++/d7qm2dNDC9vbj+5ftUEbkKAq5acxykN4zRNZ7cvz84uVuvz9eb8/OyqDd1FvwI8tu1/8Df/5ve/871f/6v/9v/2W7/9z/7VP/vhz15A0fYxdKFSayvovNCj7i1mX/bQ2TOkpbrfaS+yxaMFqmmO6n7MqwIB9zbWjGXNLt1M7H/wlr/hZc0236KwPHvQi+n86a1xflFBVYGRAkMCDVMaUiLFr3zjG7/2a9/93ve//Wt/7TuH4+12f/fso7vb7auPnv90f7zbHbbXt692h7vtdufusenAJqrnm8sg0YEu9pp1HKdpGqc81fy+yALnXLQYhRg4NAHcr5lkMvM8qTnA3K286eny4oJJ+tUqhHg4DC9fXh+P4zjmcYIEiESRGCQKt23T7A8+Tcf9vu4h5Xg8EIu5xiZOJTOReuOe1JMTQiCHD9OUp3Q85Nub8bjPx0OGUhMbMsCteBncQ/D1mcaGBRZjkNCxcFtyEAoNJ9MpGxitUzE20Ha3HaY0ZbQmYeQYGjUJQcxdVbMaeQmklicbx5yx7nl1HtvQ5cKhj1l3WUvWYirbbfrgT64/fp5tamxCKVA1YuNQZbesCgKYUdFiNmeKutX6laicHyLcy34bFt7MgkfMc5PulR7vnWp6bdJ4jbUsdTnogdM/B77vwdJKEOEqklCFZsnNbZomM8slGRwZj95ac0lKbAzNihqDYEhDkYObl6mkMZesuWSf1Ntp1aHlNpDEvkmpRGHhYd6wGIGpCiaXkt2tjUKNwqFqZsUyobgr4KFt+1VsdczD4TjsBgGDIZ0U0mlMG5yt+vO65fNctQswF+Z7lxQ16FJNkKUjzH3G9mZEw0+6TVWv6LNbjRzdM+AW1Mpn7ad785vmN91P0NI9i+Pe0H1t3D67PUx6WPzDGe+7d1odtXDzKQmoGjh8WvuW5/bPKY78eU/8Olz0ptfgb4b5lzn50Lz8vFYxEFaAHIqAEIkmIicYt7HZTof9fvfo6frJ46umfbG/K9WchftcUtP5VKK5nrBS8++763V36ORp/+LNH/77mttUs+Pc6nZSB6j68J96L+EkDqq5E8FqcUwrsII0Fpx/hb7+a0/e+c7VGIZnL5599Pzu9pXePC+W7GLT6wowSjflkz+5vogvhgMiiStKyoWtAormRmTEFV7OYIQmND0VZUdjHsbR77bDeFPGWHxyLZnIHAoqIg4hGogj4KEuQURx068NBpQCNTPVSkudp2JlaFW73JfOoJor6MQ8LzILfryMy/zTksP8+iyZsWMyzD6FVdpxpMAcixUMmoqvN5vN+mw47Gbh47qkqKVJi6s0jXvKSUdDiNK1TVo71uAjpjxZVi/mpTiT+cJJesBsPQH682Iwr70PloYZHl5EvmDqLpFzThRCiKuku5fP7t7+2lfzwe7S7ftfe7/nT5IAyjEwFcnVIHcyRSlespkCTlJTGsEgj520fScN55RSmVBTK91rbB/mIJ9TaU5gVH2Ez3HtaZ6b94Kc9+/DfAZ3f4279cYidf8f4GbVWZ0XHIO7wZzs9BbA3VXuuTg1s5uJ5zsAAbZQZe/3OqmVcGkRYngdS7PPQY7+tbZPAxRv/P3062fCI5+Gj2iBez99zjfaL8DAenjS03kfhkH+NWFYp8udkKnPO+B0n7gf0Nc6kZkre+sNvOnPc+dvXA5/Wo//Gc788NEW4wwgcIADec57cRa4wwxkRlwtMm2aYGSqqm4s7MK0lMCrrHBzV9MqluWA1fgmg2uhd62QAExN1dWKkzkcUhUxhZhEGAxndYazKQAHF6rJX66mWZFQHXwyCLE4ubIVVa5rMWHOWKG2iWNI1cRiBzszVcYQlnXTZhiKrMp+M0ECSwgk4qJVg8gIWmX6XectE7QIci6oi4OWFDlTFRF1MNWVZu5w5llQrJRco5LMZA9WiUqGInWuYl+AADXPkISkqp66o7K1GCREIrXybHUSWQQwLDE8r0udLzYQHrpyy4JVQzo1gVmogiqz/po7yVzKHgQmEhaT5fvm5qqmUNRCXe5lhnq97oiziASBTOcihyCC0WvmFwCq+mjwefGFiAizm2vJZlaILZGVWqVPqxY0AOi9lnz1Thd+FuagZ/UmzJzJMRPymchIEdRpJr6JVGk31LBhJV+hLvlMgKEq2C+RFObFuvXZiDNTY1AA4GrF6/6g83a1mPDEtQJaxfXIeR4dLFYbrBLT3CkwzZuIERGzEHHbdbGNuWSdCgTsrMksspsfDkdCM6Q8jKPDOLAZipY45vWmb2KXsoZaJ3uec+RuTNy13ebs/PL8zFTHJh7H5HBhC8FXfb9Zr88vzm9eqqoRIcbWlJxIRJSUA5uqBG7aUKYi0RrhEERY2rbdbNaxk1ef3Jqb5jIOY5kmz9r1bds0Tde0TXN5dcUkq1UvrEzeRmlEyDyPuZQ8Dtuxb7u+bdomCAYvaSzJJYRumvLLVy/Ho4Hj4ZBvb49Pnr676lePHz9KnzxPCcdhF6SppajNECFOasAwHI/Dbn+4TnlvDrC0XZSzvok8ahmnkQxt22nJcK0SbdXuCaEJkpTcrJRSxpxmpgy3RA1JLbthZ2ebrmtXq2GaphhD369CCMfjsL07HI/jq1eHlBAEbRNCiMw0jvry1XYYx5cvXq1Xsevbvl8llmlKh+NOC9q2Q5AQJTQC02E8BCZdrS7Xm7aNJase9sfj7uxczAbzMeVkhTJaRkMm7CHyy1eX1+cXV2kqSmxdRGxgRYxdUEi7PmTTXTpolDLx6NpR7NA0IUbwL3/5K++9+6Vf/uY3v/HLX/ud3/uVv/8P/tcfffAThRuRTX6fwvtgo6m26elnPCjBg2Wy47RIYfZXzIwIzEtWLxwOmyPM927kDPqrnRYzJl4MS399G2UjtsW8X4IIyzkf7pEVbqfZbJVQC7xq3+MrX37vradvfe/73/nL3/vu977z7Re3z+52r37y0x999MmHw7RLZZrScRh2qrlrm3GcUIvSEQvzer1p27ZocbfhODJJKSVPSbgLITRNVOeUJnVixzDlklMIDUusm6QThabtVyGE5nxzEUJomu54HPe7w/X1dhwhjBBqXreUXErOoeG2bdu2m6bj3TaxgMWGwR1Fbdd0XNQkhBCteqlBpO2akrA/HG9v0m6b91u3AhhYmthudDTXVLLlpCS2PsuxoXWMbRckAGSljOpA8KrlRyQgmrIOU769yzWe486KGKkRYeIq466qE0PYYqBAoBggoCZSZIBxzMNUjhfn0eCq/urF7vrFvhwBCxjyOGSIxgbu7llNs8NFiKqbN+OaBAdZnX6z/0kngGAJ81SDADWc/cDoeoBefUZboITFgngw54B7PIWZQKRuVfXb3Jg5xACyYRxMTV3rBRTFxcDsBCggDEFBZmVXf/7Ri/E2l0OpKqQQQc7dGWCsBUEpSrvZdJeXksodHXcAtJhqUWXTQoS2C8JSsqfRpnE6HnwYtKQaF8lDNp+05GJa3AMRSSREwKNwY8q73f6wP1yttIZuJEAo5DxWz3Z+X2v25dwrD2OkC3xcHepKPvisYo/g+3WhOuoPHO/ZaXSfa6i93ttz788Z+q8P4gkD+kzr/KHrMV/wwWUfjv9DdOa0RtVvPlx2iD4Dqvr5CFgVH5v9fJ8hV0gID54F8/2envG1q7zZ1K2iihxh5zg/0IAVYgAAIABJREFUO1tpJ2MwS21szbaH46GJ4fziLIS6ZKO+Q1YK8Wfd8hs+zuv43ac/f/Pb9a1ajjn5fgDBl8DkGy9dTdA4lWLEXPe21t448WLq8Kk7nIPP2tuNz2s7BYyGd79x9lf+re8+en/z4c0Hf/ijH/7hDz8ZX3rZha7l1nl3BLInzSOncT/CwDAvXin69+kc5F6r/ImCEdvQbzqJTNQU5THp4ZCm2/FII0YDEDsK4hLAApEQG40xMDdFPRdzUL9a5zKVYl68lJLNWTUizAaqOYSYaSbLzr3+2o4KR2XsLbIWAOieGO1zrPWNKahaqvdHBNMESxxaOJesaPH8kxdN25+fXb56tTOeg9BW1BhacnEzhhdXdxGAME1TytOqQxpoHI9iSzDZ58qYXhc3zPQf3INxtCBDNVlxCRnUez+9TOROUCvkbAUeGG1ftsft7WEVvOu7SNwwSk1cKFYqc4wEoJzK0YdDE1MuTNKEpihldg4cOUaOBCKGs1spCjBzcCHA2c2M3XQ290/czM/3zeuT3b+tdZriJKk/j84c+TjN8Df2nfkoc7D5kpfirnNdZvKZjVX/LwtvnZkgNX3JlpXU8GAqLEWq5h+WRe/+caonpUXvh+CNe3vQ/vyIx6fbyYp7fYr/XO1TFuBrRKI3gLCH7c+igfX/VquP9HkMrIfHvLktfc74/UUhTZXuhE8pxP952mtOxesoJoC6tjGRuWtxECSAazLajO6aE7tbaLpsVc/KzYk4zpX8yGqCtQFwc2YR4SjMLlBjYhCc3Ss900hJtZRSHDXaIzGQBGZhCgR2nalJAV5gIGaBgODQqmDtgLMzUZAQJJhZLQdG1ZNRqCtFEg5zKv0pRC/Vs6i1imoPW0VNDEYEcJBGYmxCE/bDTiiA4QSvsmBgbgOdNgO3qq5FFclzwGdMJ0ThOYWMZkuZXEIQZndPOREgoRayqUS3GQ0REgkSODCLEcwsSJkVl4zczFPxaohVHg/TokLgTibMmKvU+FyprqbBVUXL2rEMqT1KREwsXDMKxyGF2jkggxfz094jAieQSGgaakTJTa1oqZ2Yi56t1lnVtdbHda83N9d4RA2On0IK9wYv0UmwwWc7lwAIS6juo+VpKilppe/B5PRkNbHPbI4o3Ecz5ntmuBMCzREYJ62Pz/OiLG7JIXDxKnC/ZD/W2Mu88dAi8PHaCu+gMH9S4TqAzCr7LIBcc6kkaiwh6mXbdnOOgM/ZAV5n8v2dm6Ne22ZXy2ZpACZ2Fm66LjbB4dM0v8QgdH3X9DHtj9OUcpq8FIrSxAbIY0LRIiSr1aprI+C1SDdJkL4Nm77rWoKblWEcazXM1WoFAlMR0iDiaiVNTYhMxgx3TbmARRAAEDOsEKsZjsdRxM4uVquuBzsIOam5X1xcDcNhN+2O+7y36XBIfRc2m9XmbNWtV48urkDEUmNxEkSIPOdpf9jtdnshJ6gI2raRwGo62DSNmtK4PwxpNObYrdbDsdzc3q02Z5eXT5q2yyWN47Tb311enjVdFBV35MwcNBeM07GUc2aKTZemst+XlLVtpxx4e3O4fnVXkj55fAE3EQgxc3ASNVFDVnIKxKRWsuasEwxcwIFFGoltQ0GkEZHzlI7HvQFd34Dp7mb37NmzafJxwtlmtVlvun4Vm4bIUh6mdNzvp+PhcOyap+88Pj87X/UrLXq3vRknlDIOw3i+Xl1dXgUSMz0MRxGuWacOzSWP6Wi8HvLh+vZ6e7NvpH/y+Evrfv3o4nHfrI341d0txZ6aru3X3Sqer3tmNG1g0XEcmhinnFjCen3OiPv9cP3qGrt8fnZ+RumyfXw4bt3pu9/91te/+dWvfO3L//Pf/bv/4O//Nm6Bd4EI0BygfRAcmt8hImEmc8AMsGpNnrafOWV7XgHqKgkmZiwUxRPU7fPCYYvh53ZSmCDAqRY1rxGGZc8D8RzXZarHLSFQqwjbbCwT1RC0g8y15DKNwAGY0PwK/rP//D/+9V//N7/87peHYX9M23/xr35vSPuX15/sjtcpDbvDdpj2IYbVpr+8eNT3Xcp2HKZpymreNG1s2mAhlTSV1HXtfs9uIApN7Ju4mtRLORAEiMOQpmnarKNINGPiQkQSKDShbQJQ2rZvmjgOQy7TmJENXYfYIAQ4fBiPIfJF7JomdG08HPN4SF0vm7NVjGNRYDFURGJoOjIT9hBC126GUtI0DEOaJpjO1rYZlexMjTtZyUZaJqRJTRFj0/UhRillcrMpgayW0wQFZNXDeNxup+3WYoMQIQWleIkwR5pySulwLJFLCBKlDTF0XdN1SDs9DIpGQtu9evYSAc07ZwJY4TSJaQvnSCGX0V2FuG3WU0mTlVwmJg4SgMoPIve5ujEAkM9KkaibG2Nm1lR6UIUJZnPg5FDU/voMTIAAgmHWh69kZPd5fzHM6MP9Al0NLSEWMXUQ9X2vKNMhF9eZEQzb54MShM04WDSRwALVxBSF+XZ7RALAGAEwAgOOCeXox9uspM79atVdXuEwDscRY8Y4mapWX5+pmmUwzWplGvS49+loSBHm4+1uzCCWlps2rtXUsumkEBBiLvTq1UHVdvv91BwNEwgSm4Buyml+R+dWZRNOgNaMVjDd7/h+6tJPde19ZG0uNrq43CeokJwwQ+O0nByLq1s1bU+gzxvti+Pis23y4JYWj/r+CKBSk+5PblWK4LNO9+nGvgg4V768L3FGBwjsi1lEhBMNAV5rSkt44F7SAzDsNfxidodPDzF/WBMHBWiBNTaPzlZ6LruXWoa2j+aYxkPTxK5rjmlawgOs5q5GjBqrnT3vSr5eUhv/NM/1Xvr68w+lxd2vaY335Mc3jqikRXYs4qjuDqJTr81JZj6XtHN3A4Qr8sRO5AjAHqtLe/+b73YX8eMffvzhxy9uPpxg/Hj9dN0H5P00IDqYQ9f2q2ZDCpvcCpoYY4wpH2a0uapLeamPKIFCpLOzq77bBI5CUvcTqKEABg3OADOYuYmh6TSPxhptKnBEknGYzHKx4oDE2EUhgw01ly0buaurLyUMHL5UGLjvrRma94o6z/0+C2As6MOnel/ViCESZkqLQqKwsRbDCh9/+MKinQr/ekGBpmgEgF3ZkiXo6FSaBsXz7fZmezsRCE6WVSpd8+RAM4OM2Nm5aK0Bdh+7WkCf16fF8vP8uRPIS7Gua9JQUDI/Wtn28OMfffSXVu88eesyHQcCjhPakD17LgZw07ZN7Ik4jYnATex8BfZCphbMk437MckUmth3sREZUyIzocAMAleOwwKsAieMe77jN+iHOGGpC+BU95eTMN0CGNXFhOgUUHkzvOfzO+RLsAWoDrR/GjI+jX2laHBd7EVSTpiLWZ3EEUC2rKrOcK27FQMGWrJEqrqKf8aM+VT74nX1z9weYlivPegveK0T7vF5QM3phOF04c887tP39wWf/gVmz83WNM9llH2p7qeqKaUvuJP6d1V942x4gHy5+xsH3Bsuy3V9EWWvH53u5OFh9ed6Y38RD/3mDZ+u+AaGNf/RoIuoHhyaqxIQpOFaxwGAcGWDEMAkRjHGyIhU3FSzFeee264xgycnqmrtpOYwZqKS5+I+uaScEgqEQuC+1vHLZqkUiFMgD4A4xMHzDV1uNuN+Go5HnwoMCGQKyzXIUlxAgbjhnhoXd7OkhQJxCES4fHReTItmLVnVSrU4Q4yxATzlRIQYo0gINGveq1vxZMNx1XWl6DhO2RVEHAMR6YzELJqIjjktjkEMhaubO0ZbTAECR4lNE5gJXkoppVBNzEQlg7FIpSgQG1Omu+tt9fXu6Z+1Be5jIyIkVFQlxja2savKIznnguzZcy1x6Kg4H4jBzEyVhMxWleMFzOSBmEnJi6upn19duepcCkUX8ilDzblrzjY9EY8ljcedPdBtrf8Us7loMZN7jVk5g4QbDqRqpgUFqCZQ8BAjAapuXs4en6npwok1cvFctsNBR4OCAwvEsnpRgkLhBW4ghgSxbCCQ0ELldzigBDUwOIIgpnNJZdSdiGAMAE1gLWYZmRxUiOCMtolN17BwMtWS3YmFK6XYyqztQQGa79/fIAwgIKA4ihM5cbVhqgaILVTfuhHZ5MbMIKo7+mLe+RxtqZmKRJoLHMYWQhMCiwRmGqakqWRNVWjASUOLTAlKm/Ozru22W0/TIA4tQ9Pwk0fnbRuY5XgYJbaq093heLM7Ng02KxGR43Q3JfWCb37z6wGRiFfr3jyPh6QpiRJ3aOGPHp89fbz+0Q+hnL/xy18ekn706hrufd/ElQQ24fHqCd55+u7l1dU0lA8//Pj6ZrdeX23OeqVd14XV2bn57nBM2V0cL653z57fnZ21V1ePck7b/avQ0MXF5u1Hj9smjMey207b29I1vO7zzYvr6xe3F1eXP/zDH7z99lf7/uLubj+Nut3j0WM+Pz9fb0BMt3evAF+v1+++e7Xb7YDjlLbFECJSwvEAYjx+Er785bdXq+74an97OzLRZrV2l9sXlqb99u6givOLzfOXd02Dd999cn653u8P3K0Pk/ehf+vp45QGDtw04eX1tbl1fde2a6JQKnfBfRpTKWnK2q83TnpxdZ5y2e7GFzepZHzpS2/fbafrmzHsS7/qNpsVU+ua94djscS3+dXN/vrt7Xvvfenxk3cePXkyDMe7262IxBggzXa3g9pmtWlSe7u7zpqiCImb0Kthv7Np/fYjWW8++JNnh49+9v6X4ubi8YsXH59vHr296j/a3Qj4S0+fvvfoyYv989vj3e/+wb/8x7/7Wx++/PHL3e2YsD0CwNffxV//tX/3W1/9S7/y/rfsgnZ8mFL2aEFCttS08h/+rb/27/+tv/ZHP/7xb/7mb/7WP/mdP/jxB+Pk+8MUxFerfhjStC/SMrHEJhJEVc0Y5tzEQDGlAY4gwd2tjE0To4iZ5jSZaR9XzSoej4cpFSJQqOQpJ4bzqUosiBADz+Upa+YtNcIB4JKSw9v1JqWkqtIJl4KUSZiiCEtkmQYr42AFq7PV5mxzPOz31+nisuO1b/fTL73/+J13n/wn/+l/9P3vf6dtpe3anMbf/8Pf+cEf/eAnP/vjl/ufPnr6qO/bsNajDaPdHtNIhfp+RcFfvXrVdaubl7eHaXr/K1+5vrl++erlMB6IcXO7/9rX3ju/fPzkrS9NU9neZTU7P798753zn37ws2cffLjZnAWK2+1BzcHetLFvVsOwp1AuHl+98/Tpxx9+9Ccf/CinzBS+/F5XSokxXF1dXl6emZf9/vbm9vmT48XV1cWjR1ePnzxKefr4+Yu7u7vhCBYkR9OcXZ1f7A/DBz956QZVxBDPz1Zpwt3Wbu9gI2CgKHD2PE1DwsDctySAoiguLi7efufR2UUrDe32t9v99NWvfrtt+93NcDhMH9+8OKYJXQPo9nZs20o2jE3DBdNEU9N1jXWHXZomrK+adbfqYru72f/4k48ahPfef+esu7h+fvPDHz7r+t6lUMGTq6ff/dZ3/49/9Mfbm8RElg7obHp5jYbSXSsthxCa7qyUknMhs8ARgBCz8D0hixxWAQ6zyqQGajyjCgyyEAsRS0mpMq8DsQuhbsU+R2BAtYgwmzm5LmqVDvh8GAECVCIhz1GLZW8kCSEGcWc1wBhVMksABl+sjJIzl5Jci7T9o8vHftTnz56vaYNbYCAUa+nSCywUL832g7Q99+abTzq37Gk7fHKz/eStd57E9eV0HKZ9fv7i7svvP3XhJoiIjMNhtV6zWuvBDhMSxlRIIH20CE+Uk1s2NwudeEOYpuNoXeLDq6lt1//XP/8X3/0vvv31X3v6vZ8ef/+3Xq7imZVRaBSpRHR2SmZe821mA8adTgbw4ljPCLbhoS/iqN4XYa6VMqNKNXg2f22RKzgFfU4/mHnJGXRfAhEnN7IakgsrvcpZLF5iBdkRObiZYSZwz0Ccnc5ERCAiz455/BlAZHZCtrxkiy5GvvAbgk3sgJeTDM1cefuBcXfqGAPmkvfuYAoSiCmVsgS8sMxDR2WMO/iUvn0PptVwJciFbJ3L6O3xyVfxq7/x7s+2H368vR4LutWaKH/ta+tVR7e7T9YXj/7r/+a/+h//h/+Jbe1ozlcXg++cjkAmwI0JPXzlpOA96CTRazZL9FfkjZgMbp7l5Nz4rFPLxF7ZiA5IHQxzKLkXsgWDq2t7hTJsKZqjUIYTZgUhgIhD4DkNrmJqPIekXZRA6j5aKS4Ni0sZkL/+lafvv5v+u//+v/2/f/K7f+/v/S+//4MXNsZ+0+gW29vru+dmVohQDK7pbti+erVttT8eirtocTBi20urRT1PyYuHi1VJRxAuL85+6Vtf+5cf/uHTx4/e/fKjt85Xlyv5eALHxkbvVheRwv7u48lw1XHW9PzDm4vVuuXgZiUlcNhfb8HWruLm7MxCvr67tqM2BCjVAnbz7OU5XwxVsNgZ/oYDSyetrDpVlkj2A0yZiKjKX0CLOVGeSqFajrZLmlxZ4pna8Nv/+J//jX/v+9/8pfc//uSDw+DWNOBuypZk8lW5aPKTx+di/f7VtR4P6/Xm4vKRXw+HFw71ECSPWYgE5OaACgLF4ELsDKibu6qZVYx2niuL9m4Nu1f45vRgQkxMJdjtOMFb4pZHQbeyPzx+6ze+efEW/fjFH3GPR1+RcRQ/oLGSB7cxH7aTl4K+e/bR82OZ3rl4cn55dvDD8cPnzC0RlzGVaRyPYMG6bwxsmkCtExmhgNQohHhahjBLRLmWch+uMINDmLmG5QmosOCin08EgTg5g2cfaikXNS95D0C7uWYXBWQnZyt1+eQQ5ut6Bfprcod6/ZVFWKruoZUphRBQ5m4mgggTpGoQuzsYTGLmMjMt6U8Fbpbw5GuoAh4AcA8//cz2ECD6zKs95BVVMO7h8WZWd5MvoB+9AXH4pzhZn75t/P+CgXXK+/tT8bUvaA/xvJ+nvTFUtXD16VR/5tv4hdpr3PbPQCJf323nXClaSqDMBCOWKFWyvKr8eJVQqumEJsJVnttUaZ5qamrELEGYqabsnkjCWoqq1k2PI6imjgT2CIiToMpsS+DxMOZUfKkOW1lRFEEEllpiz52cmIWl3jiESZiY56TCeiwbqysRhJTNYRQJECNXS+6V7T+v9c5UzCoti4m8Vq6rgIM7Zn7ca++qnZDySvtikMzC7FrUSRlVcwpEwl4NOCIT1VplxAhWoGwyn8tPJB/UExdSq4i5wUlZQEwcQgCB2YJqXnavGiLwE0+1imyhdoUzVFzYjc3J1ZzZj8NxTq2BExO1wiIcSGEQJFVHyTkbHAu5f46JOMzUKsHYrFIjUA0P1Zo9TgTEJdRQrLCLSNMEDq2lMvPhzGAsbq4EraEJZxcyNyMynyMWXCOfzFbFtpbo4BKNq7qQFVojrdw/ejOaQCAicSKH+ayTw0RmllPhwEwQEsND1Z77ruVAAJEToxZxXCIzcDix19LVyzCeYmA1XiO13i2clhTH03kXwggAFIK7ixVoLdLJzFOZ2GjmCQQAIEaQ2DZtjDHGWG26IBSjNE0MwkIEQ845sggCRTcvlTrp5mAXJo9erDAxEY/TAdAmMHMXSKbh+DKbPO1iwHqNV7ty/ep5QQiE0LduZRzHSJl7dH0MkUuZ9odD0RIlMokWFFASeNWvM2Qjn2wajQA6JrUdM4TPzjbder0K7TpEaU3Ozj2KuHto2qbtY9O0Xb9ZXVWPcbXuixYO1+M4DcOhbfvVuqeQi067vcYQHz++DLHsdjfjBHd0K1xcSdOEVb/uulhD4E0MzIEQHBRDFyVYCYfDfhpVDRIpNIFYABrGYglhve77i8urJ7thd9hvi7o7cnbn6nBQCG3XdvD9ZrPp+lYtDcNezQCESFkxjdgdDmaBOZai43EkQghshiCNWX776aMpHaYxXb+8GYejCAHW9F1gFpEQWKKAmZiKlsPh4OZ917PQ5mxFwhxbpia0WK3WjAiGQjfnG4NNZbx69HTdr0jLH3/449/6nX/06nB39KO14b1f+la8faFaDsNxPAwJ/i//5I8/eXX3k5/+7GJ93sb47uN3nj5++vbjt85XFwxWjFn10dXqN37jr//q93/1937/R3/wgx//9v/5T64/GLfTgAZg6KSxa4WkJCupBGcPwRRFUzSwsAO55BCC5qIpR+EutiCo6X6bHBqYneBmNa6ISoRfIvoOWDamubK0GayoWREKHMSJ1ExLqjnb3DSha0MQqA2Hw7QfVlcbkZYdpumTF5+gAB3yauwafOtbT/7O3/kv33vv6aPH56tNMCsvXj57/vyjDz/82UcfPbvb3Tz98ruxIdV8HA9D2qsniTg7O3909eTJW09vXt1u7+5YqO2a4zDcbrc3t9ucS7/itsHl1VXJPgwJHlbdxao7D9IBdnn5WLgpxY7D8fGjTdu26mUqQ0ojqHfYze311UVvPsVIIoFI0pQd6PvQtMzieZqKTuZZS07jOIxawQNmWq/OpryPoXVQmuw67Q5DmiYwkAsmz5YHuLhx28io6hkEghAQXCmcRSJXKAW0KyjKkKaQHNkPwzROeT/kXHgctUxwCywu0nDM3YrGo3dNs1mt+rPgXZmwSxmdyHrTclC4Hw6HzHkYizAIAWiIWgmrEJpsiOTVuWWOH/7JR+OxsMm8LRLYA1usYY85SdsJNFfVXQL3c5TJZyf7tQ1i1hsnVA+DQBWAqnvmPNkWA+61DaAaUsQ8U3prwUPMmATPsew6/Sr/y+HqRkIsUryklEpJIJZG3N2ypZSp5RgbiTHHsmp6Bmf1ntd6VEyIEpliKBFOxeElaQZ7bGXViA7pMAzHcSyQ7TRmVXVY2woRzG0q1sD7db9uV2UYpqJpyHmAF9Ok7kIIzEECzzBccLCjhxONuazPewfvD4fsh6YHCyBxzIXAZEykROSkRktkC5iFJOfSWQsoNHcuAJDd047udcvfMMxnjecHgBZA7rWsch1anlEMeyC8/hntdIVZSeHhhj5/657qcU+GcuA++2bmBZg7L5oMbv7Qej55SG9QJIxqKuty2PJAp6645yDVYqP35sxsy8w3R/ffqmSk06MtNWke3C6gQIMgUUqD/iw+evfxfjhCpFtvUj420p4/WXVCYzoE7x9fBgzoHgfsKKWxpCRdJfyAZqODATXUtGB6Ezx5rTNPHzz8gd4wpZanIAd4KRE5O/vu5Pd4JD38x3HqIZqrLtJiprmwuylR4BCZgwVTL5q0veTf+Nt/46fPPvjZs4/LJDYiHclGoBAbe62DjlkEQ81KKZqJXAhi7qSWTR1uMI/cX/RGKIqLq74/az558XHWKU8TQTeb5q0nly8u9733k1IMHTN7AQrGY+qarokSRLyYQcEGL7VwnbkXdUVx04UxTAuAWt2SN/r6zc7/rPaaUPeDVp3QOetw9gpRSVHFjKAklZ9qWsqcQgFnMEhAjJSHdDTxkkuCAcwOpJTrGKk6DByYw7xh13pUcFG3Ofhf1WJP71n1JR6M9oMbJTjfc2kq9c5A2UkUjONu6HaCEt555+2bo6lN4+EI8iDUcizwCXBTEeHsx+E4IaVxAkEkQGdvgwhM0JKrj+ZubmTGTgKGm88sjnmK1ySP12byvfU+j8+b3V7lXWypSuivfff+58rkciI5qVgRqlJvPf9yG07EOPHwiCBcC6YBkCDV7eEFAJhr2TjNBaWWQXB/jTb7xq09bL8Q9PHnbw8v95D08wVfOX36eYd9Hvjz/2kAy2u1l09BOV9A9frM53/IlvqFrv7w11qB6ARY/vzn+XO2zyPRfc7R8BmimhH8OYpVa5WZqcLgzs5BSCgEAZGrmaK4lmJmBgOLAZBYc/iXgp6zXNi84XpNLjFY0WoskhNkzi9L02TJ6r6JB6ARYRYhrzfGzCRcvZxaI7uYtk0kQ3BTwCriMxsSCkAqDx/uZsS4F6kiwFGsONS5WmHutTCbG8xgDq2sKyKeQwWnTiYhU2NmCTM1V7WYeyXlCKTWR4aTZ1c1LVUj5aSyR7PVfWJqu9cEl2KF5iWHLELgIQSJIkFERc2mcapRPJ+jUbOt4VRDpJWCDydAXLma/U7kZoBlZ4KDmSSwhMhV5kwzYEWzu6uVBat/wN8n8qJuDq0FTXyJOLxGl6VKf9b5E2Fumqbpmv2wNagpTOc6UjCYuivEmZTcHAWmACOAlmUYOPGnfdnefdnuadm2T0bjaX0+2UDGM5+2WqkMAAVWyiQxNE0rDBjUlWaxHa+xJNQqAZgJwJW7Pac2VG63+RzLxb35SUTOYCJlP1nJ5HXz8dlCAWBExKBZWN/n6akQOHOIoYKkMaLUPEMmEYkSAgs7RLhtY5QgRGSWh6yJyjTi4GeXTeAgTeXGaQwiQkxQmFsZD7tEgZlF0EZp+1XbBFJM07Df7p6+/d7mYnX56Hw7bsc0UOhi20ggLSaONsari/XTp4/6ttnvD3d3t9M4OeJx2B8Gkq5MRQhIGWZUiphRLkqADZTS2DTNZrOaEmE7qHobgrgRSb85KyWDJbbterNp+25zcS4hqOcQpO3iaoWUMAzHEEPTisLHYUrpsNmcXXRnv/TW129vL8dxIiJmxEZqfQQRqfLJFQkuWlSNYuzapu/DcdDDkK6u4nrdNE0UlhCart0oYCrXL/Ys/smLlzfXW/Uc2xCbRDLkya140zbrzVon69bklEHZ3c/OLmJshoO99ep2aFVEctLD4YgZ1Zq6NjZRWBgFLMxMRct2tx1HabvY9V2/6oIEAkAWosRG2hhBejzsS0lEfrbaXF5eXg+3jCAkbWw3m7VnFmEiW626aSzEvlrFcTr+4Ed//OMf/eA3/+E/PFrqr9qwCt1FZyIS4zq2QfrhOL662+9uxpuP787X51Hix49fPr64ujy7fOvirfOzs6snV/160531Xzv/2i9x+943fuWvPr/+23/z3/n4Zy9++Ec//t9/93c++vgFGNknn8yKiQhzsFIsF+GGmEWYGMGDmWZKsWtwAAAgAElEQVRTzUbCFImJTT2XEpogwrWSIQGm5oo5ury8v+uzpuRcslcpt9gEgjjIHZqLloI0Utu23JmWPEygKA2t2sgh7sctVIgtq8Pxy9/80re//a3v/eXvvP324/V5991f/bbFfHf3KuUxl+H27uXL6+e3u2sO9NbTJz979pPNedc0EkJ8dPnk4uyxanE3VR+HcRyn3fbY9ZumiWMahuEwToM7iFYX549X7Wb0XAqIIhB2t8ebV7s86TBOKeVhmA7b4fzRGmfBoFNSdeubDTHt97cEKzqmPAK0XjVnZxsiFiFmTOk4jPuUBwA5p3E4DDmZW4ji7l3XN8PUd6uifrc77Hb7KUMYTUDJmEaMx7uuXYfQdA1rmlIuQI1DOOAcg2o2tvWGrp6uVuc9WHeHfda0PxzHVGJ3CCGPuzwOeXs8anAd2BwScLHp+zaEmiGszmJwVU0h8lq64/6QsxXTaYQVTEftaIh+ZhrdAxGaJnCExLhabf7pH3x0lhs4narGu8HIYKCF4DPvvzXQQXio/l3dW59zr+aM/5NH+CBhcCGz4EH430+eyAmYcAYtVZ9O9FonqbgHcdXarBI9VNOHnOcSLZXNW2CgWMUVyRgNIjlE2eCiooOmPLGFLra78Q4K6UQKmam5sFTOMGo6/WbV3ww6jmkaQDx6gRCHntebddNE1VwsGZiIzefk55QzvGnb7rjfG1uoyJtTFVhxuLkictay2x82l6273d58Usp0eXl2drZC2GIca35a7Q6HgN1PhRYBIp9p9ESVcISlZssMRC2W3PwXrue539UxJ38+iABVl4xwsr9tBrVnbS2/H0wH3Y/m0mgxGR/8aR5heoBdzUaE4z56Tw8yE+twg+8zg+6bn4547RqymEInRPTeHT3ha/6a1bSwnD4HkXuAZS1XdqoRs/lkDqBo8qCIODvbvPvOOx+9/OlIycFFQebnF2syvdvtu/Xm8nHAU7S9psFyQegioOwRKE5OXMhHWwLRn3drDzO+P3XD9JkfOPGbGIvTg66us/GBBVfNumqWnQBRrzxARU7ugb0lbpRgnCYev/GXHn3733jvr/z1X/mdP/inP/rg2Ytn4/YGlBINQbJAXYtpVmrmi6iWaSqTZqLILOa5mLIWsBmBhOJKDsMRPc4enVGH5y8/GVbT4bBTLZvz1dO3r35y9jMMJfSBBSIkXa/T4NLkAi1WVHUqU07mau4QIrghFFP1Mkdc/xyuIc0FiO7LkX32LJq9nQeReDJ4zZXQknMQcQ+mlTO4aAmLc4DmlCyLF81ajUgzy1Xe1+HFMIuBsLlpqequc1mHBXJ0Y/zptJ/TpMAcHZhlfeFasueMBne3+2bX5mxXV28pjZZGHC03Y8nqpGAABjOIE0FzUi+llBkufQ3ycDdwYAKVAi1W+WHMbCXhntPpS2GDeXGAPUSK/gJaPZMtSoEn6tP/w9yb9tqWHNlhKyIy93CmO72hXr2a2GSTzWarB6PV6gGWBQhC24AE+6N/j/1z/Mk24E+GJAO2u9WGZEg9kGyyyZqL9aY7nGEPmRHhD7n3ubfeKz5WkZDBLODWPffts4fM3JkRK1asODKSjqLbJYLnk0Myrb0gYrDpLNFQOnByLI8h/5eqQ/wy7St+8Wsxfo5Ixau39/q7fYlp9bUQj19rAAvzO/x1J9jdHnmpE796K8n5X3rm/x8a3Wm4xW5f9xQzHu9aCgsSzJ2jWGHaQM2g7mbgQBxAR+ddHQozx1wAgYoICsAgJwiLsZkYGVwxJejP9uixeVFBcGLnEui0aV3EZGC5Ac5cRJwAkBVOKpG5GZyMKFvwMIki0MTsZCKFloImIAa7m5MQkZOQTOl2BPI0DFaq46HoGdlEiHLMQMmdG547s6iYmRlLSaMkkKu5W9mlmJmpQODmebCckmd4vq3Kh3g8Oc8lLIqeVcmEm8pXlyTGCZgSLupXwdgAV7fCw1Wfj8RU1a5YkAywU5hY+wDYvObaS04OOdhFxNlyTmZqKNiLs0xACxVbfgL0i9qIuwMlzDit8ThujUUedyLaiYhIDIFJ4MhDhqNQictjkpUTEo6lDHVWyykBSoM7jIjBt14IbgdlNjenMGZ51WZvZD7GeJbTQtHN9RLvcGTLgSMLk9H0pDxR8Urcb94JuOjmADSReadQ8zEkUoQPSm46mBhCnozm3prw3MkKZYCoFMokv60TAHIiZ885n16cDcPBRZmRfFRNBYQy1T5nYWXDZrWuYiBBGvtDv4NDIzl7qKyquaqEJQhpVUmMJAw1tRyG7uAAEeoqBG+8KXgPe4JaVktVFVbrpl3cdAkcyVhNUwhYtIvz0/bRw/P33nl8dXn57OmT3b5XBVEaRh1VQ6YQg5RypQgwsqnmfXJIDA2oUqtutp15Fy53lVBTyXpRL9s6axqSSqjrdgHh5ckmZ+12BweZptPTxfX1Qa0bUmASgB1Jre86urrGG2/+hqFd5ChBzCyNI4qeHhBCqOvGzHLOwzj0Q7aGmqZtFmE51k7jxb11rNhch2GMsTk5Oc8d3Tzb/+gHP7y6fvbsZswdpMXZGeo6JMs3W/QHIGCzRBOwXLVMXNehXcp777376NGj05N7w6AfvP/psyeHUpyCCFnV+tEsMDcSmIiuLq8Xy7hYNO7a9V3Kg8MlMNWAOxNCkEW9aGJUVe3GlAazHALVbfv05gUpmToZtc3C2AjIeRT2k83y3v2Ttgk/ef9H/+Yv//Xf/+SHHz7/pF4u5IbGm0Gf5NX6tG6apm5EqmpRwRAziGtIVOLnu+tnz5+N4+hqF+cX3/n2dx7cf2O5Wi1Xy8Vyc3J2enK++fZ337u+2v7gB48XZ/z5Z89d8cknn3740cfdoFGIMWZ4IIN2phgzQgghVDklIWIRNx+HVFJrY6iCBCJ3dSJhosAouK1PSg5waACpuo6AGsRYjIk0u+asOTV1LTFUMWDMlhNlVcuEIIE1ewCWq/rxo0dvvHF/s1n85ne+9Y1vvvub3/2NNy/e2Nt2f3P95NlnLy6flCrpXdcl60mMIzhyN+5qlUqqZbNs2ioESSldvri+vtna1c2hG6+3W3C1btsujU3bnJ5uACyXy836hCjEGOF6OIw319cvXlzvdocXV1fdAAOQgR3Wb9QnF0si9EMXKnr05oMHDy7unZ+6H9TGlC0ELJbx3r2Lqop91z9/8Xy/3aU0AhYCqaYxcdcdVDVUQUSapikBPAGZ4tDBgXoRq6o2S4MNw4gotFotmbI6SEBEqpZcAYzWwRwV2rUsT5tqEYy1G7r9cOi7UY33fSb23faw2/XXfUJEzDkIE6FtqkCkSccukys3xELkSrAQxN2IkLNrdoJcPU/j9jkuVuyBqJagVeNN2zSLdrVa4WOMJ0VG64gRQHVS2C0xG5AfeVHTSu9+ezQcmNRwMft4d22OaXsngCZYBMcUj+MRt3HgW4Frv3USpnq2RLeIhMMliAgkMJGbZxCFELy27FlzFuHQyELaZCkf0phSTjoYjZxOVydNrHdW4j/IOeUE99AIcWQw1HQch/X6nF84LBNAbgKJVVXXcblcMpPDs+YKFRGpas55BgFZgqCBILAxCFlzVgUcgZytqqPDDv1QAjHDANPh4nx1cXEC+ZgLz6JEI52deCpNXDArxyzLM1kBBBzjZ+SAzH2MGZliAt2mwRUwx2ZrY4Ii5/MUP+x2P6eZgXRnlF7K4ytbqQNstwPvk3lwLMp8PGuJsN6Fp2jGQucjSqXmLzPkX7at59Pc5fP5fLuzb4LJtDj69K93wBxfBDnoeOJpGjsBnm0A8nqFs7OTzcnm7374YiDLLH2ft8MYqAowDP0qXA7p2e/9wfrv/3Y7IJgOJ8t7h33CtPRmIDN1k767T48+XXb6Hx2dY3tZyup4n3NF8GK5lWCkz2b2PFvKI9udXuSSROBWErgIkzgtORXxbRiVMt2sIwFCbm7ZktcdzvAn//J3v/uP39zps7/5/t/cbO35ZwO2cAMG90SeyJJjNGqCw4gFxMmzmlUcXASmRk5kEHcBife505yqc1Cj+7S96Q/UYn/Ydv3udL3enLWhwv7QOXN2IW64rZSzSzX0WXvvJOc+W1YIyLNLwXbN1FS0gHIFuSvL0QRPfNHWfVkH7YsdXgzgnwtdlYNKEe7jKd2Jld2MXAkwbZvGTErFhCnzgozZQ4CwpLEDKYAxo+v7lDOYEEG5+HosHFjIbRJesqnyKxeW4VRIj46z+e48+bmt5JOUqL7lhGBwbK/2iz0lhVfqA7XVUk58r37d7ftx9MFdHREgj5VEiaxMiQbqLGdygRkEEkQIIizMBnfXkq/mHhlkZjabH/DJkZ7wgXkR+fnD8ZXbnIqL2VUnvy3xfGxFmwhzsISmMtBT5Yfj8nbbu/NHYNqqXoKHfmkA6yu2r4W9vIRhHf/40i9f+sWve61j+7UGsF4aql84WneiLre/FNTz6w52mWovrSOvjsp/7nZ8lq9y0TnKOO1DZdoPw2DuU0BMplRrl9KnbNknQjOK315MBbCwhFAygZlY2F3EiLhkr5UAlzgFJiEEQNzEKRAJAS5gCqxZLUyQs+mEeDGDhEWEA5EgeVY3uOgEdTAcfRox3XJ5dQvRfdKz1VKZaGawzivsjKgzbknp5JM0QjGT5qgPzVZOaTw3M+MjajJlYoLAcDIFm5vB1LVXG4EjegWAGAwmFDPcyQisrl5KzqvDUchiZq6myAXn48IbrdvGfJqnatkNTgU8mxWPyUFgERdiYQ5MzAYjo0qim6laQayM1M2GPGAyRJ2IhQU6ZcXZzBoqgZmjLXUbK/Mph+IYsSNhCRJjFURAlNX0kDHCS4itiAdrMQ2PhmQxl9gn4HKav1PslhiTKTRdowRUCgo5Ves4OhpfjP9ZKZNZkDByKoy3KWqJ3GeJDMClFIIB35L0MQvvF6ExL7jlVKgQReFMS/GRopo+xeOZMbF6HZM0wBEMPVpwTMUfMAKBLBCBzF2RMa43S9tm41TVHAw5kwhXVXD37nBwYxHeLNZVHQHPqUsDjvZwv++Zm7aOUYSZA1EQFkFFgWpcXV+ySBRhV9XR8uhVFGFUobKYc14smwcP7vXZr3d98kDCBWdYLZu2BsHSOIz90PV7N7RtJArUZxI65GzI0YuuZHAzVR+TjwOaWtumJorD6EZsCCmlAZbSpDWvmgGiEJ15t99TYJhmS2kYU9aT05VqztnMkiGZiwRnoX449M8P3/Y3x7RPKYtGnjw3VfW6aiTEtm3MFEDXp3GE0GA+1E17frE+OatX62hmfd8DY12tTXm3G5787PqT9y+3uxERAMRRh9WiqYwpcr8PBzUPjPVqk7Ndbnd1g0f16cnJ6Wq9yWl7fn5x2I+ffPZTJLhxqIgJqp5SVrPILIFzHhbt5vRsM/bd4XDo+97MJHCMUuh6wsLMIgx3lylFCQTA6tiMljVnMqpDrZY1jXkcRPDw4fnJZsnI++7mxe758/31yYPT9mS5H/r+5jBkvLi+ahppm6ap2ibWbV1XUi9WG+KoaRzUxzQe9vu6ql5sr//9X//Huv7++fn5e7/xG++8+85FG02pDs3D09OzP/qD3/7ON1+8uPrB93/4V3/xVz/45H18hm6ZYYAAYfpJjtznKDmNaJogVTC1nE1YWMQJk9Fmpb4eMaalmCarEQ4a9iM52ggENoN2g0JCkIqlaULbNl23t3EUkVVVeZDr7mbcJwzAJZDw+J/5f/Nf/9P/6p/9l28+elRVFQeA7GZ8/tnPPkl6GMdDP2wPwz5EqSpZbppBm/Gyu7q++Rf/4s/7sd9ub/b7XdeNZd1hiZvNqUh1OLzY7Xd1fbKCqo6bzXK1Wqg6nNpm3Xd5HPzm5vD0yeWzpy92N4ekUIMNgAARiIBJGjDm7vK6C4LlYv/W47feee/hD3/0Fyy6WmO5WJ2ebRbLKkgwT2rj/tC7oa4hcXK5mdlc3U0Vqu5GWQ2QojIkgdqmrULrOh5YTbM7MwcJaJumbRpVO3T7ZBmGds1OuljIycVisYlcwcmNkFQzQWLlLKp0GHU7pM4QAc3euC6qhWar62pZ182SaaEWB4hrNjMIixWb27ypF6Gtno1Xh34cmtws2hDbJDsSb5qqbdumapGhGaYEK3Jo5gpw8TJUWAAU4u0xrFIWUJ/3homxNJs3RLcpKy+Ho2Y76fbn7Z+P/tbkP5Sfty4DjgBI+YM5KTMTFQ3jUu6DReCRdYSphSBNXbMRsqcuFW1WOAZTk1WUyCBid1XVZGBnMhGpGAJnHXWs2roES5oadVWxI8ZY1RULd13XD8OYUhVDvamFgoQh1BIk7XLKqnVbkYKSm2qGmisRUQihic2yydU4WirBvhigeTg5Xd2/fwrbI5xi1IluTeUBGaQledC/iB/dIhTzRxKe9vEjNedW5OrumBDI5wpwZWQndOqIYWEyCqYB8hkZmpl4RyhzOvBl+3cerNvbnUeU5od4ySPyO4bIq4lCX9r8lbl29EtnBwGA446nMJk0X8Pxu+2H2eQFV7CQHj588OCNeyKi6leHfaaKKVxf7ylzFWhdS5dunrz48I/+9Hc+/+QvPt9ndKjrerc9sE33yJwd6kReAECfxhi3jzX1RVkRAboj43p8hFefhelWl/8L3eWYFnwAMJ4tOZ3OQkfAsmCf4i4wb0IsZnrvybmvH/J73zn9xu8/jKf0l//vv/vg46cVnfV7gQqyexIbnXKJ60JETCxECXVwGKAIxBC4QIgroWgcTIExj2jQnrdD6NI4UoOmxb47XF1frZbVclOvT5GzaWf7w3UYu0wEwpDNSVDHWC3G7oYEkNmlYDib0VSyyRmeiz07u2MlnVZ/8WQr3obPyYOv8ft4CrzemfglwWxau3jRLs1zjAiCsdTSY6eAUKFp2p0egrAw527ohz5rDlVABA3EHAILgaywHUrqJRERrMjsl4GjO7f0FV4jcmY3mDE7yDyl8kxDl8fOjeLHH36eEJerTdM2eVnF7WEwsx6FGUCwECnEyEastAuAOrIDDuYgIUhJp/SZoTtBqTY5Ol+Yn/MtTX3uhYL1VdeDn/+MNEPnJY/DbYqb31mE5tuyeeMrEMfEzJrEf47+yB3k0ydY9AsY1q+CQnzp6vSr8HWOd3WXNvQqevX6e/5SsOX17dcawMKdjvi6CvE00/Ywq2h9rYve1SE73sMRQMUvGolfvR0x2rsfX1/l0MyZ7+C+BBByP0UGEGbrgBGEmVjdTY1ZQggajVxiCLPcGqkWPIKISSBE5OIcJDRxggPZSl5d9uxkE5pgBJA7VaGikDy7BjYtL7OV7AkJgkBOrm7K5sHKoxpAIiRhHBJ84oIJHCRKDhgFdrhnB0CB5oiHOpfIEjlbCV3i9t03GAEEFtwS4Yu3BXUjIqPiInAIAaUCgIOAKAFlQzK4WRqzK5DdM0FBCe4QD0wBBFeDQJiZpGD7QmKY6huiCGISTaL/ZppHCIq+8Wa9kTm1wSky2EitqPiZqRsYDoQYKZTkxwmuN9N938kkCjIZQm5esq6YKBfVAS9qAQ6fVDjngKmTOynNKYSMklNXqgKVohgT9UqqGIkpZx2GIQ0DaeCSQOpFCgDucC08YzczAjMVNpuTkxuJl2KNIaU0HVcsGvdpFynUrVsv44thqOJiZLjBbjUxJs4uMdw8d8kSSxWI2NUnXt4caVfX4xYMR4FVVQp2BhSmD5MdJePYi2S7EVFEYRIC8CkFo4StaVb9La4VYaoeeUwqsJRSP+4RPC4aqYXhTWyX9XLohpubdOi1EizbBpFZKLAEAjEq4WTW1HHVLjaLJQvURoayk2eNVQiRyCyK1IHNMjx7Tm5KIZYxG8f+4uJssT5pV8sPP3tyfdM5QSILo5Hc7w/7q8/H/bWba9a2odV6qcpmQ8Ws406ChMAiAiANZq4gN2BU67pD3zPIJZJEqkJFrKa2P/TjMKyWlYFDrNKYP/vss1hFYWYhQzLT1XrRDzWccjY1zU7EGAY3hymePPn4ydNnhz1YQMAsWd2cn5+v1+sY67pyd14t3W1vZuPQCVsMvGoqtYEJMDWlIY8fffDJRz959vzzrtuNEoQjuec61t1Bcx7rRS1cx5hTN2x3sLQ9PV08fnS/WYTDYfc//y//K4EfPXprtTh99713nz692V72zy/3ARJCINIiGxeCkDSnq4vVelFXleUkwn2PYRzNvKnaGCPBc0p931lODBIyESFytfHQ6cX5vd1Nt7+5KZhXVh+7MUY5P9vcf3D20Sf/0Pe9+u7hW/fef/5Rs2irttmPI0QiYO7jYP1+D9sHcF3VjYRnbdM2bVNV77z19vnpo/vML549H/LAgcY0PHv/J//x+3/dp+7RG2+EIG8+evsb3/jWG/ffON+cf+Pdh7//zW//9//yX/2P/0N39eLm008//fsf/OBv//r7P/3JBx9/9MxzBGzMnbv3lAlK5kLCgc1Us5qbm4FZpiKLKfsxF9iPZJfQQAILR4KoY0w5pdE5SAhONAyd5tw2TcNRnHPSt9b3/+hP/uC//e/+1T/5kz/ccJswKJIhd+Pu2dMPL7cvLnfPnjz92fXNZWxkzN2TZ59v9zftqnn8+NHp+fmDRxenF5tD1z99/iJp7ruDqjftYtEucs4vXlyBLCXUzSJW6zHlvu/2+5uLiwd13XSH8eZq16F7+uSq6/L11eHq6qY7QBOIqWmbcFIRc4yxrw/MZInI47IZ1fTy2fXnnz69d29d12G9bheLdtGulsvWLB3Goe/7GMOilWFQB4SFiCRIK0uz7OQpq7vHGEs6pgSpKkgQkcpM3MWdcsY4jvv9fr1en51tFouFWb66ut7tbsDOrVc1L1axaUOooZScXMWTGwVwiM5hGHWEe8Cq5WZdm5pnq+tFvhkkhia0yyaGxjWO2cdD2i2aRV3Xz56+IK5CK4GXTVijvsKIwJVIBaJk4yH1RA9CFABYIo+AEjvBpZQGhylMYZY4F0uFGaWO/Mx/msIaRdP6GI+mwjzgO0I+PntQxW++JeLc+Yk5mjdZBbfRzWkXLGEHh5FxSYcjSGAnH9IgJnXbQEg1WTYzY4YIBQF5TvsxJ9UuI4MrdiVPmkPmerSkLGxqJBKXIambZERDhVgHETLXnEciaxrUMdpoQkxOQ0pXNzeqyQAiVrOU+5yySAwxwA66A04YBOZSGIWoFncXoKqrWAlVQopkmahaLqqU+1V7cn6xRo8YTT3RVDBXQOKkRKaGOeW+uN9Fs3MGG2h6iYVvXQafo4gvMYp83qwxj2j5OAkgk/Md93sWpPAZFLoljB/BkPkMX8RKChjifhxQ90lc5g43CkRkL6ne3L2xuyd8xbR2gP0L5ZsmX8BoCg/67GjR8YAvQ9ZeaY67vVbM0lt5Y3eNLY0Bbzx6cO+N80O/D3HRHa4S6mbJu53buK0qiWfr0exy9+QP/tE/ff5k+x/+j4/f768H7S2ze4ATk7vlUsmBiMRL8WxM/TK9TpOXT5N5QzPfqphKMkNaRzyrvEU0cf5L/iPmpM1yGsCnao8sJk4oJH866vfPjz7HlkNwSZ4s9h5TcyF/8s+/970/evfGrv/9X/7wP/2nn+6uITZyqjnBUkZvnojBIbBVrGRgklpQUeYMh4qWV0NClNYQizgvjHHxYF21pJQQ86JCu1p3/fbZ82fn9xZn56tv/da7Vy+2l0/Thx9t86FDCAg1t01Tr+q4XlQh9SnrDoCNCBWYwMwgIXAQddWilIoZH5nenOO6xi+XQXhpTh4TYH+Oo3c72++8IwDgBivjZlzXC/MUA2JsRpFCWIAwRBeLts7VqpbIrqUSEFOsY5EAZmbxoFmzj4k0fFHJrYzq/Gx3oM7XTvPb0fYCZRnYiOEVSIIlkar+6EcfYIF79+jkvJaKz+6dpc5ueN93iSsYa9Y8pF6MaqmWq5ZTNWiCsAiFUhfAb22M+eKT5PntjUyB5mlmM5X6BFzGi+6cwfz2tiedxfms9hVwlWL427x+gpBNC6SQTafXxycaRUkpgM6phfwycuMzgfWlq3wpxPMVcYlfguv0C9tLGNYvfUtf695+fQGs42O8HrV59Vt3n9/ndjzhLzwVzQ3zpnj8+10w63j+r/5EX6u9etuvw1zvQLxUJKFApZJFyYwGAAMHCAuEisXMbjqtrkwCgRRn1ebCimRAQKBQ3p0Sqiu8VDPLmpHhbFa4PezOjinsCEjNTBImA8dNJwCAxNhBZkWRq5rYxGAWJmIhIito41xBSOFGDiYYMQNOBWYpAN+kuFrC/+5O+bjuTJxsomlUhcPMyLtdWkAFtgEgIjnnUsFauKR5kQGmmpNqciRAQUbBhTmQUrlPJ2diJzCkCMS6G0GIvdCwaKqcNEc5ywKpgBgIfd9ReXRhmWlWRERu5i4FgCFIEBKAydzV1NUcloYx8V1DxJkpBJkWwinUbaRwd3PF7XSmadEuSrYzgR2EibpmHoLUVSUhlBVek+WUc8qqiBlSRn3OX3RzU51Yxs5MLEzMEWykZCiBHGIQSniQib2Yy1R2/emlu93tQUw4vv0zgFU+EAHGxGSmZeH3UoIgO4tBSjBWCE5M7NmOscdbr2bag51hBhYymvR8bS64TiWqZu5ijtn+cgYXYp0XyTe65c073F28YGpwBvPhcDiMXXCuVAKDK67qUFUxpcRFzgoYxr5qJMTY1sHWtbuGgGB2dnq2XLVtWztMld0GUzVXC+JOZkhZmR3msRbiiEnnCyDqxn61oWVbLRaxidjS0Hdpe31gVHnTLBpW0zwmAiKYagnEqu6azWjR1kmVYMIOx+gZbnXFBLPsh+5gDgY4UqjI66quyoKifc7LRVVVFTP6od/ttjFWTRMDswhbMMCYwMKxCu48pLRLg8NDRF0TiVdVSCm7wQ0pQTOEiRBjaJnZTUSquqqY+OZmm9O4y0OsmEMDzywSgjhX0Oqzj549e3Ld34BDDIGJxJEZQSjEEOq6EabiYeacTLG9GZf6KAUAACAASURBVLrDuFhVxMpc7w/7Tz/+/PHjKsZ2sWg0edJR1UtVaTcQUVVFkJyebdy1H0ZVq6qoOTupO1d1HWO0rDnlvu+VJUioGGEugD0O4+OLNz1Bu/4wHEBwzcy+aOvVqlm29b/5t/8hm25OT85O1+tNWwrCR+HIQQ3Nsk59HnIaBh1V067bMw71tmkWTVOBuW3bqqoiswvv+sEsE9Fic3ZSnWUfzManl5+Mef/xx/+wXp6sF6v7F/fPT8+W9Wpzulgt335wb/Wtb753fbPPQ8pqH3/06f/5f/3f/+7f/hRrYO/oFUHRAhnIQAUQQjQIwZSLx0BGEJBZoW04uXrOlvMwZti8N1mVk2Y47t1/Y7lYPH70xu//7m+/987b5/fOmHB6vnn77bfWHEbszMYhd4duf3V1+dMP/uHZ1ROuabmoF6v7293Vvu9JjIKrj/t+71sy8/1hPwzjs6ttiJFJqqp2BEcAMVG8unpu7jGE5Wrl5kNOKQ855xBMsw99Jk8fffRJGqTfa05gEEu0bOPeeEXEpEAafBzyOOaqlvViPWrfD/3nnz9ZvS9vvH0K5DFpEdBUtXFMOeUY4nK5VN2aOSEIR1M07cKhakaUiKhpWjVPSQEUtUrV7NmGIeWs2dD3A035zt62ddYxpS7lgdgkMy9jVTFHZO1NlSOZ2ji6GZqzKqmpGnMIMS42y6qtxjFlHThzpAqJu5teUx9XLCtX0qHLdeQYm1W7BsU8uCUPgbiFERDMJStSsn6WPJsStdjZjNwAIhih6ACYw124eM0+YUjCbnfVv6e1mujoEZYfR5GjO37GrZfkt57VXXOJZmRs2v+mXbCYM8fFe4LQCEyFLg2HhZw5sJnnnN3BDGFhKlXUBEk9EZxEQ84ZCTnlsqEPo7FZVVcU2A1ZOnbnCGmlWsSSMQryGAKI3Cln5RjcLWdIiEwpxNAPQ7c7bDttKRADDISyzZq5C1OIYhDL2aEGye4AAlM/9Cnx6WrVDwduTYKD4Zonck7hJ5RNjafA/7QRT9LcJUp0a3TS3PlH2PDWnSumw+1Hnj1eAmaC1q1YPDCBJneG6UhYuJOO6NNhzF/qOd6ik0BxNf2lIf/CFV+dDa9rfvvNoyNwy4vBF2Tgj2csxuYMxM65jV+8FAFETDiKwZYbn2ZnCYQZZVSo11Fq3h/2LDwmVXgaAA9DykTU9TouZN/vnO07v/PNpz/K7//wajdcEi3NApd0RDLCSBMxpHRvAYxvPeVbfodPvPfCJbnzgMcUwuIW3WqeTYzJl8/jBSCYX6Y5kW6C/CYfweEhMozHZEOvFrVL2pzi4bv2e3/2jTfeu/83f/f9v/vBT7eX0AGp02AWjdIIGydchZibNu59C1KpRBoafYTAREEmYghqwUODosu6WvLpg82gB01JGM2iosA2cN8nNa/a5p1vPNqcLOHPPn2+ZYEaqrpum6YNrUpNnjgGIyADCqvBIkRixu5MECJVH9187kB8yeD/vKnnfvfl+DkTcvJTJkB+8g1hVoLEE+fRARKSasFTmN8hLDHGKgSRyFxXVR2xr4UzkRDJNF2ns2VkNwiK0T4DWMc6o198e+5Ql+j2BTmmQh4fzgs4U6RGyr/XsW3i8nK4QgcQhuvDYZEp5OVmRYtAzn61dbZs2cyG3FOGMLeLRUjBB8tKM++JSiV5s4KkMnPREyZimS5f0KkZPSyFbGesfVJGxzx1vzAI8+Se/jCDAwWWOAZBbr9SBn5K1JjBd3L3WbzbYWYlt+fYbyA6lp008/LuFMbM5PffubXXwA6vQp+v4kEvgSS/SqO7a8gve+QRbMGX3e3xmC+9xK8XgHUE8I4Pc6y/eDwAP6ez7nZQOU/O+Uv/9TVXv4tbvQpXvUrjeh2o9BXaa6aR3yGdfSn77O6GWgAclNwvmcsal1pQR+UfgjuEGcSF5UhS9HetwBDFUnF3VXW18gYyk0N94tSUF2xKDaFSgAUUhGdbqEAULMKWMgUIhGDTAgtzeAak8ISKSh85AEUWiSzs7lkTjouLw50EIBEjJgPcC25F8FCKnxZRKTgAg+m0Ns720XHPJWJmYSlF91TL1Ys0MYGQ3SoJBLhNl4A7jNjY1Hyc0CtowfElckVAAUaslNzjGR5RK3UzmdnN3EwkMLG7w3yKWvK83jNSGomJTMTJXckYSkpKTBMTkApCYpNRwSAQF4DlFt48TgwuEZ8Sv6Yp2l1msrmDC02COZebnxyFaUpOtYVoKkrOHJjEzIZ+TGnMmmHOEEsWJQhLhppmze7uppNNGgsC51O1J3IyN1OHGlzdQMRSZPsZTmSlmvnEoeVb29bnbX1+Opu0iDBl5R8rFYCImEQBqLoonCDuEBIi4kCmWiTW6Ysw1iRkQEZOQDJjmSagkQOZfIpNFsMLTFPBSgJyIRxiUq31UqUXBQIsk5CcDt1eiIms7/acuWIZNNBIScdYkwwIAscINKrG7KtVA1diIvbNyYqFxzHlnCRwFSq1ZFmJAhwiyNk0mzCaOjAHU2hAiLFyWq9XXbe72R76w3azrA5bbC8Phz36fhQfHz94PHSRHMR0vjlJCfsu5ZQC8WjjerG62V3DETmAkCiP7u66WrCr5GRwqNqo3nWe+37RcFsjspkiEO6fnxPs+uoyjcMwdIR1vVrUdcVMw9jnPAC83myqqq40jmmMQ1rV4ex0IyIsVMJUTd1WoUrJ23YZQpMzhxBSIiA2lciaA1d1HXf7m5y61FusGOZRGgltXZ391f/z0zWteh2NaFBdnrTMRfA+BKmCNEQqHFgiUzp0zkNuGsSKF8u674ZxwKKRYRg+//zze/fuLZrezPb7A7GnpCIIQUIMIRCAsmYSoWlaM+37fr8brq+2VVU1VQUnVSfLcC9BAiIy03EYGFg2TXV+cekgQ+ferOqT9RKuOQ3/+7/+nx4//q1vfOs3T85Xv/Wb3/z4k0933bBu20ByOIx9l4ILBY6Njyn1uyEpTJE1pYzD/tOmaS7OT6vIgAcKIXAVIwnEaT9sl8u21+7mZ5dDN7CHplqcb+49vP/gZHna1u35yembbz363h98O0pToU5Znz+9/J3f+d6f//OfEZAHyyMcPur40QeffPj+R3/3k7/ed8iGTIqik+glcj9vmowmet8BjMB4ePLg7cdvf/e733305qP7F/dN1TS/9fabRL5ul48en7754N7p8vSAXT/uTbXbX3/2/FPzUT0nHW9uLnc3Lw7763TIzVCDLHsimFtu6krqqKSH4dB1w26/z6anZ/ez2jB0h67PhnGAmnZjrttlVde7m91yvVHN7ilWdUoJPhLFGFrNdHPlnvPQwQxBKIigRBs8uNqYx5zzZrVsFxGiqsNwyMmRxv7Z08+/93u/l1I3XN4cDkManagUqg+qoxkR2FRz9tFtd3395jsrKwIjxCnlGBtPyWx006oSc5ilrN4PBwBVLBK8KaW+64lurO+6m+0251Eqv7xyhLBaRaGoZuaJEdx9HNGNePRmfXM9uHPd1EZeVZUr2NgzhnFY8iIfdPt0N+YxrGl5EVHrYH0ayE3W65MQ4vXloU+D+tC22PdIvgvuFIZFHalOiObkQxpxhXDCydlViWeRzeAgIFCsAhx5zDCDqwjlkmFIrsXhYXI1oFS0nIjGmOGnaRGedvkioGVl6T1uH7i7ueEoEA+f6hcTE5nzBHvdaaoKIQ7k7odhkAw4iDmWvOaUg8SqrlbtKvXXmq2E0MgY7MM4MNPqdEV8SF2PGlx5FeI+ASEt1mhP6vZkcX24KZcIzl2Xht7HPLZKzSJWMSAgJ3VHiGFiGczscjQUa1GYOxU2mCUzgJhz1pBSpgGR9of95ZWeLNtnL549PHmosl8/wvDRYaJNKczcoRxn85EA5ynKRpj42KQoeqS3bg8dc8wmY2HaVSdQsGBcs2I7AVxYKapOMy/ZAbdZz/uOMwx3o1sGymzVGH8ZDDVhJbMlTHR7qrsG/+wHArc8IXpNytAtPnfnkJfi4q98B2C6xbz87n/H2TjpjIEgIjDVbMRMYEyBRMxKUW6VxRN4OyYaunGfNYOQcpd2zsxp8Mi064Z+aCjZx08+ffP+e+/89r2zH+LwrB+2Qsbg6HDPYyRwjOPgKBLqpRtmZUkzcz067iYIQBEVoxLOm0fYZtoKHcto0QzV3VEgAzvBoa4TiwvORCC2WZjOAREhR8pZKHLNgb1PuliE+xv+9h+/8dY/On34zvIfPvzx3//4g2G3QMKwHTFmz52EiNGQNVQVAWCPDQdQJrQndd1W/W6HBk4ZotKwsWXk2FK9CIsosa2osopj6g9EiMt6dzMwx92he/r5pabh/v3lg/qkP4zPr58w1VeXxoI0bL3LlGIa+9gKY4nsFYer3U0dAnlwBbkIs3Myz6YqjWTNNBNI5/lc3CQipkIeeGkGHQvTfelUPzqnIqI6dSaV6hLqBEdgVNas6+w5BGuX9X43QAwSQxvqRWiXpJqESQKHgFhLFAYrBaqbkG7M3TVlZHP4lFuMKYoPJ2QDFffDJ+CqOJJ0nAw0FZyaq3zeol8GCcziCvXoEIdiudisNucf/uRzCOA05vFwSFSPi+WiXlSLzaLPo7oNeRAR1ZyyDd5vqlMGh0pknGq0u5km1aJG41TKJZeaWBKjm5e8lwnDOk5bP6rtYFKld58dpfIQPsF382Kh7gRikXJRYOoP4IgYzF3Bd4D/GeJ1d2IGuZuqgUmEiIhYBOxHfNDUXG43uRLfgR53rpdhrGOq2V3I8O6EuTuRXvrj6xGM1//r3VO9etjxuy8d9qWA2t1v4Q4Uczztz7vKrxeA9Wq7+wClMXNK6TXH/zys7ite6+7XfyE+9Utf6/X38Mt8EQjCRGSlcAMmpcTbfbokNGcDg4Vd1R0u4CDCklWnJDMvYVKoeSUBTmZwdVczdyPncEsW5gnrdj4CS6Ai153yUPhRXFEVI9WUzcY8lgQ6EBDBkSWSsdO0iZtmd1VkAzFBIoUYQlWkl2AFVPc8Aemk7ATTSRWJmAxeraoMIwfBhFypmAPmcDdXMofNcgxULELzKVhkJVcsxkIqtaw2qHVu6pYNCpTkPGdyMlMoyEkkxIoPtiv2gd9pBX49GseT5JU5IEQQYRImIbXkgJuOyZAAgIQ4MHFRQy6d6hyYnBjsXILGJCLKqZhNpaouE00VFotpp+ZeTFBXR1F2EhGRwMyqqdgyJchJpSgkI+cszE3ThBDcbMzZzDRnNys7WiB2M4BNHeZIXkLV5M4FdJthNRQhW2KGqxUv1aq6nqW9vFhU5IW7V6YV5k3wjhbvVD8QAjHTqVijOQsXDWCUy2PacTTbBNEGkSJKKWFMpVDL7Tm/gGfRHL2nid8FwiQtzBOmx8TFUWFhKCkStDgVTswACZMzT7q2DrMMWIwCD8ZZ1ZIbVZ7DmImaRcVhlf2aHVUb2mV019SNJNY01aKtJIoD+67f3WyHfmjb6v7FaaxbCTFWMQTUzVpyLsV1s9L19hB5WK9xctKsN8vN5uTDDz/89KNPWcK9i4t189bJYvX02c049CJpuDmslktVZRKpKrWwbHwsCg5MaHXZ1KpZQjDNkrNVWCyWTR3hNvZ9SmlIg1qdlYa+K9WqQ4QItldZyJsYauFlVe0O3XAYeL2om9rMbvbb/WGMMYypj1VsF/XJyQKkTV1vTlfL5WK/65vG16t7pycXQ+9XL3b7/fB82JpuWTilVDf1ahngODk5qyoJkbe7PIxDrGNVN1VooywXzRkMhzxKFRyw7DllKZUpIIAUsoE7VVV1ekovnu5jhAg5GC4SQowDCNvtDqCLdy82m3XXdSkPw5DMsVo1i2VT/LHu0C2Wdd3UltO2SHaBDofd++8PJ5vN4zffyMmIJEQWorZpF8sVEaWUiXh3fbVebS42m1VTW7b9dtvWzaNH95nx/sc//uhTEH2w2mzeOq0fv3n/008/2V5dnmwePHr48PLFdkf9ft8dtPfsrFO9sFGRh9TnlDKYd9eHm2W7KDbcoqpXy2VbNyK+OpMMFyapKsq+3++vD9sPP/up/11eNKvAcu/i/u9873cf3n/cVqv1ctNWy/Vq84d/+vt/+GdMLnnUcTRXOxz6H//oJx9//Mkfff57V88vU85t3ZQAO6PQXQGAikI3EQcpRY1Wi/U777zz+7/7Xzx+/Pj85IwIaulMNlu7hloVcwUb9Gq3v+zHLuWhG7uPPvgHpWxQkJsnqfjkZA3BkPtDf8jITVM/WjySWkbT5JlDkKqhKvb9UC+qtOuvb/YvXlypqkiEY7FYXty7UMNyfSKBr64uh9HadhVjA5cY2rqiy8vtYY82Uh0kjZYHc04UQruMdV1pHg+H3jTHyHUbD13//PnWBA8fVA8fnC03sWkWVWxN9/v9QVibesks4zjutkM/9KbkTkOn226n2U7O+6w6pr6sMD7uCgpe1SKR1YhAOVhK7LBYgxl1FQHr+pvd/nlKZoaqkhjD47PF8qRaL5exJoy5H0cdk6suWxAD5ppGM5aqBqg/9ExEYDEhld1Nl3bp5no/jpBTXEiSWm5G09QHOTSLZrlo713U++bARpsNkEF1R1FD0w3qTUS7CnUdhqHDCDhFiWbkZDqttI4iOW9GVOIBpGaYiwmTiJkTChWIMLNy5wojX2L/qGGmz/oxWW1yqX3aVoq2FsxcqMj9lOY26ShOAVRM5N1SA4QBYZYgpkrkwhxECBRjDBKZAzkjw7PlYAgRhVgs0q5bqfnqMvfdGBOIElh5heasCotgYspGIkwxpXw4pJtr70ZkpGa1iNWiT4cxGxGFGOq2rqrRsyoyRYTALGQ8VQYrk4QIQiTEpp7H0RxeSc566MdkuR/7emVvvIGPfibjQWd1DFChShVCnAgF9lLi1ot2wZwmV9AsmnLQbnuZJod8IhHxrN1g7l5K+BRKnZcoDxyYygIfSQW3wzlXXKEpBjRTQmh6vpdbySY9Kg4c40i3VvFdJ7I41AC9Fr06nvrOIfzFf/M7B5Vp5f5Sosjdr9MXPhSqhamXci9EXLLMmEu9lNJDwBKyQlgY1zaMnUI3m5Phsk+jjaOm0QLnOsbrbaJV9fTqxdnJ+Vu/tfrdP37rr/63j8N6pL5xBRBAVbaRFExc0kbnrCoq8qRmEwUSR0AEmKo7T573hHnd6Qc6Ou7us+48yHMqhatBIGczZSi4WGVeNFcJFCVwCEGYwjiMeySKddBRxzr94z/7zj/582+dvt3+4Md/+9MPnj/7fJcPy5ArHq7z4aCaXczHqWIOMZRyphQaRkRYEVeGZKgAUQ85BaOQqxod/OSkPrlYZ3MjcJBlc8KcQ1N9/tmzuo43u/0Pf/zjxSL/6R//4b3z1eYc3/jWWrVqFkMa7PmTy67bpw5wtHUNljxkrgQ7jGqk2TIT8VTonGdmzRFDn2GNybClsvC8hMj+XEfyOG/nWPWdiTgF6uHOIsSA7m113hr3XGOxCfb8GkQQ5rqplmG5qbtuL+yqY2+ZWGNdJR3iYvnuu29/8PSTISdO4mOmanIYGXAjKgot01wtORYGlAottzdDdx6kAHZliXH3WNWaRzM18SktNcAD9X0mCegQRMDejQOL92lwk0PfjePojFhFFoYDSZFpHBMGGvpeNccYAMrZ0jDCj5w/B1CkPUpJ2ZJlBC+r3STMCyuSH5hrBs4gtx/PcXyZ7/zmEw9gei3KuL40dlP6f3EGp9xAzAlBNo+bwyBTFpEblST6GfSeDimru7+iB487wNBR7Oj1cMTxgJfYPL8iYOJ3KEev3t6rv3/1M7/6+6vt1x3Aohki+VI08UvbLzEYL4FWv/CY/3ztpRn2Nb44L2eqNq2QTCAI8yRZRSDMNUmLZpU7EzPYvFQTnbo7xugmRFP2lpV12UsAVLN72aRsCspBNWdXjsGYb5FtSkwsFDiEyAJwAILKkFLSEeyxibGJRRrdmIuNUyRJEUKUWHFVcwwQ8hKgzWaqqpqLpeDZdcLZ5zCXuscYiEqih7hQEHH30TPmABEYVOysWSbc555XVWEWFnLklHLONgIjwYk9AKUmFHtRky/WFUGKDcOY+mput1gy2MzpKBUALrEvBjMYjljVBlM3M1VoqQuprsyAEheCG7kbQ0CZiBlTpUQSCTStklTCZQXPMXXXsvgVk3F60jIrivWpauX9YmZ3lMxNFq6lirGKMRaqWkrpaJ0VqIichYW9ZJtO8vE+p9EdtdvM3MxkuiS5IafkhiABRM6Yck6ZiWTGocDE7nO+wB3PhRkOcGBXRyk0yyABRIpT5EBJJATczeGePbM5QqAYWCjGyk1V8+32Q7O8Ax+7sHjbR8Sx6CeT5gyHuc/V3tnFIexuljNsfmpGqQVJgSgUvV4zsyJUkhyawe6xrtpVwywI1gwR6lVbORvBQ00M5uAsqJr4/OZqfxhevNh3Hc5O+sWyXTKV2pXMFGNbN940Td+N45DGLrEnDs16E5p2mca0qJqT9TKPQ4Tee3By72T1YfOzm+0up25/c8k6pHRYtA+kDoCVRKqTzfnmdPPi8GJ3uB7H5K7D0C9iVM0hhLat3dzrIEIkYd+lQ5/HjjT35BYIABbNHprZbVHFNsoA19z1Q1PXDdyLnqu7pnEcQ1cHjlVYrVqRyEwppdVqc3ry4HRzz6z6+PrJ1WX32c/+P/LerNmWKzkP+zLXUFV7OOOdcIELdLPZ3WRzpiiatGUp/CyFX/wH7He/O/yf7CfLEbYiFA7qQbYoiuIgtsQeiAbQAO50hj3VsNbKTD+s2uceXKBJsCXbjHAF4uKcfXbVrr2qaq3ML7/8vleauUzqGgJovV50C3auPHv/XRHyPjZNBFEIXMrUNWer5dr7Fgeo0xidiaWqw6GqSmnKapJtYtbZqHF1NuwH53wpst+NJQugoqSq4zjlklJKy2Vsu9C0YUyDc1gsIjvkPMUYiLlt27ZtDoecUhqGpOJjw4fDaKqX55chOCIweLlarLsFMznngnMoiWHLrj1dr6BiRQJZ2y7apiki+93u8hREuL555T7l1cPzrm1Uey3ZgUjw8MFl0/TM2/32kPJkrmK3R5kKAghZMAlIKU35cJiur3eslGT8rd/9zqRTJ7xaLC8eXzyNTX/of/SDH0wynK5W5+fnN5vNP/3n/8yZuzy7fP/ZN9558vT9Zx9849kHl93DgqQs7KlZNJfnp+8+eZRzylPxLjI7kUJGi7jKkkWLd6FxnsBFS0rJLxoYRKSCestuGbw3GwGw5uwMNgDqQECaxs3U36Y0TWU69Psnjy93w367u931u5SnKY/O82qxPmtOxrS+2V/BWbde+CZkVnKOvB8l9YdBjf7p//K/MYW+H4d+rFofaZIQNn0/AfiFb33QtovFIoOkaYL3rRZyHM3S1atb9EiNOVKq+l0ciGwahzQN1SCpiNy8vtnvuZcMh2ePw7vvPz67WILKbnMgxMXipCSXUjnsk1qSYloCw8gZq+WUpGQVTKOknIoW50lVk0xzQxez987XyoBCDaFB8DGEzruw2x76cdr18IRFh7Z1xPKd73yTyGLDRlORMRnBrA0Oy87z0IW4Z+vHUURlytz6WkqSQij04q82jkgEHLGOzSKu1UsU0eI2m0EETQhtF51TYzm9CCnnZLckrF5TxuMLtCsWKlBBh9kXBoAZWy0u1V42LSL+OG2KaDW6cjAiT8w40jzeNE/MDUtfER0xEWYLWJsX4y8AB28yg/nnO2yV34InatpAJjNzwrF33sUm5nFSEfaeyZjYO89wKSW5W/TJ1WCnmGTL6tr2pF1Ym3ivUSwYvJw8XJ4+7MIyqLMpZWWCc0VKTpYSxgntZCrsQ7f0DihGmKaUpjGJeCuxtZOT1rLLkozITEVnmU2IcQjBeSI4io6VwUTewKGJgrw+b9557+knf/ISDJMaMREYzGSmbI7MmZi5muwxWI/1oDn6I/uSnJQdwRqaC1GzsLkdu+vny0DOUFQAgr7JEd80leHI3qhJr725Fscr8jboVEORu9eNvgBx3Y/nmdnwhd2/FoY17/7Fu+h4gHv/Ht9G1XBgRieYWW0WwpwBHJq77czqYM7RoMHM1OBnehoAgwY8/ebq9OlKvIyHQckWXWfXY8mmyoGiiZnQVAi+2+dp4v2D91bf/pXLP/2Tnw7/JmPR05hz1pOzBXva7DbON2a1xEZV21REZsLJHQnOjtRxq88dfekr17cRHf9a04Tjy2wqWuZDknPEZirEVS7VwRhEAs5jSs7igrzjaVAZMwLWz/CLv/HsyTceop0221srjlJjI8qeyl6ocGCTKdsE8o7IjM2cJht9S76BX6JZeLh49RooSk0Wr2ayvIBkxJUPS5eGKSVdLJfLbik6ZZF+X8g5MoxDud3Yzc3m9CRcPFh0q0fb7X5/uBoTrncAEgAIuqUSTPIE31DD3jWaTXI2UYZjsjcDVbVU7fiMEAi1HEqOWO/ZoX75pn37bntzZ7/pNoXZEQAmY3bRKwkOeP+bjymO2Y3tqaCrIHIvzqhdxnW43m5i59LUlzQSSexc1vHi7PG777mf/tFzSMIcmpsVBcNqqmDExkeHLFAFrSt2RjPgUqHP+1/KbG71Npj3wcyMCpzOaOmArlm6EHMSeEBNRUyNATHNOQ3jMEwJHm1oj+ASiSGlrKNN06gFyiKiIlrE3J0ICVXfMQPXzvXq+85GRkzVT8zqQzjjf8fb3+b/jsP+FY+9opqz3yNIvZmsjg+RwbEDSFRA7jg4dTYkutOaVzW+e4yMqkPUHVB8hCfrmvaVd8Xd9tffP3eQws8Cue6O8LcCWO7Aip+119fEMb4+rvLlA/5dB7DudLXrGvb1pdx/PhjoraGcF87/Fzf+UjiFr2pd/MpNisKq7Dng6iIEXwEOKBhwYMeYqfjkPBOTiKaUoICLIYPv+taY+t3Bgcgwm0yLCYxq4EdQNTBUmBw7F47SWwCgQCKAlDgTWzEjcmBiTyE6sgA28gxf7TrMLw3/0AAAIABJREFUo54YC1jgNVvk0DjvhEoqeZhylpJNiljJ1UhxninnLzVXwQD0GLS+GMg30TXg4BvHYmKwak7Hs+w43rJRsdozTWwqpioJVuDUkZGqsZGZFqsd5QwieFPRZBOyuc4p5D4HuJI9qvR+hd7ImB2TOShXMFFLVqi3KBCQqOkxejhW4mYhAxisoMwIiwPzLLHeNI2JaRGt87gqVE0EFSiYK3qghsyZEQQmYiTZCKrqQmAXmEhMmaCiwXy36EIIOec0pVIKKvMJx5IAoGqBPeUZI6NKc6N7c3+1kCQ1cypwhJnUqwSxcUhGyt65QLVJkYkVcq9+QsTkyKqBeU0o6tJS+wtdtU10zI7hcITpFJj1O2oQaTL3w6oKiJtFLKUAKnKMubi6ARATkzOtsTaZkRE5qpU+x8ycp1yZ9kpExM4yOx9jVC7quVKmyZGaGCqsVmn6ZI6GYeAI7yg4CmzLdrVaLkLr9rv9frfPlhddEzr2EatuuVo/MClFpjaGk7OzH37yUcqYMtiDvB8mGdOhpHF9smwbdzj0y1XXLZrFahmiDP3AADiqwpRDDO+9+/TR+cnV61eH/V7G3eni/Fe/+11m/9577wbyxA5KcJE5qHlywYVFDC3HmHRIZQLgGDmlXKacx2nsGXZzc/3TTz+5vbnth4EiInsJMAtd5JNlEyP9w3/w+y9ePB8OB5vG0g8NoVmvJKt49d4/ePBwsRhKKapWRKQ/eO/btlXVYRxurjYX549PTy5KoQ9//PG/+/5Pxh7RuZzUBCRBpnQ97EFol3jvqe9WnQ/Nagmj0VA+/+z1MlLXtioeA9yZI1LyFNmF4EREVVKSfky6T0TCDmdnJ2dn/uzsEsBuu9v3I3OK0YvY4ZBXq4ZAt5sbZn705MFytXj9+nXfH5jddrNLeVwsm/jgYhiGcRz2u23fH3JGSgUUGH6zSTc3m3ceP3YxBk8X5w9a5zebm65drFanO9kWyWO/y2O/ub7t2taxg8p2e5ulbLa3v/zdbyeRm90N37qy4G9+6xtCfH21/fCTn1y9um6b8/XJ6eXDB8uTk+ub6xevr7y6bslTEjVTgWY7lDQk6Zq25a7kfDgMmoUc/uBf/mCGbhssWywCum758PKyO1vtku5evFqvT9799sMuRFL77Pb5X33+4b/+8z86OzltQvuP/rN/6MmfLNerxTo1XetDiHHVdR5RYfv9WEox5uA4CJjNsTlnkeJi4T+//ik7VkVORYrud+zATNRE5z1J13rHRBAxNZV8SNN+3++zZpD2w5jyKJpBFhq/OrmMISi0H3sx6ZrlYdw/f/580uzbxrXxZrP78U8+/Ozlp6J4dPlMhYy8GOek41SmJFeb/sV1v1ji13/7N00ldp2iODbHoVsu+n25udm9+GyDBlIgosG56CMzZ8tSRjWwQ7toY0MG6xb25Hz9zrsXy5NWdNpuXu4O10/efex4GZyNw+7Vq+ubm8kUl5dn52fn0dOhP0iZ0uQ8dYbxsE+5TN2yiY0vZXLOp5xKyXDwwZN30VGz4LPgYHG5OGubFSFM0/k05nGc2PkQoqmVUl588jLn0VhCMHOJuPiGffCL4JzGi9MTEntZbq9vtqngdHUB0NiX25dbGqEbIBCY1bTfW3lx4Ib9cjEO+ebm0C4P+/3m5Kx9+s6jh4/OfvV7z169eLHfbNnY2I9u/eDhifU3H/7kR2d2gRamqrmUXIhr+z3IE9iMwWw0Bw1KoJKKioLYkzJrMZulM+2uyoS51+3t0O6IXlTZwS9FibN0IY4ivkQGiErFsNjXHvb6FwDknHedV4NITkVTzv0wBiYm1qxwZAzKqpKhgONm2eU8S3+JmWo5DBNaPFyfPzp79Mg9EkaSPOnQnYSwMvEiTtkrOafGRUyVDKaCaSy3t9umiacXS5/bzWa7XDhnIEbbhPhoNXXu9maw3oGpOHXOw5zBiqmWokJOOYZoTkl1s+mTaVLJWi6fPPzu977z4Z8cPvnBhgEzYufYOdChFlvUoEXEiAJ5741N73JSLVoMCnb3Rn7mIFht6a89dHSnnm5Hxe6798p8Ee5gxJkrYW/kfGZO3Jtc8Bjcin5FZIwjRwu4o7a8+dMbJkjlH+mcQH5t9Orrb3dZHPMsy8pMpcic5eGIYdUH4MhNwxtYlW2WeZhrwKeP/K///i8/+YUHz28/2aXNmNIkIfowSK5N/cNhtJIJy5e345BfLNb77psffO93H/yP3/7H/8N/9792QZU5b2R79RIRvglV5UxU1dREicgx15KHgmfcqnJrjuNavxMR3wMU+Q6lfMNa4ZlVslgta6irRUQVompKXIFlVnJkzkBUlfH9mFWLoTsHn+C//e//m1/45Wfrc/53f/lv/89/8398//sIhnzjDy8LBsaorqkuwkStWzRtiF5ZpVFtpD2N2ed4Gk7PF/zwZD/udtupaxu/1P1UHn/zwjfsnVcTTeLbEGIUseub/fPXN9/+te/2u+n555/LbcGEP/2zH0z9za//5vvf+OBd7/0/+P3fDmG5uUl/8Wcf/eivPru5PiD7m1fjdqe3+5sQQ9NES9Ccc5mWi5PAbn97ULALXoqiyj35ygSqdu/MdQ76Ei5K+Orb8h5AUOV55+KUEamomjE5Mio5YwGc4nf+y19N8cWr7SeP32e/WH9yIv1Ak+Rdei1Xm0mU2BedSsF6idg5aGnbgDMXTjxu4R0jVPxKTdlmkVomYzJ3JFEq3yHWdBTQfcPFm7G1I63CFK6IGTmOFDwbqwYzh2e/8H5z2f7xX/wxn0BNlosgjc8oBRocN4tuCW7aeP3qGgwkYEQRKmORQUwBQc7CrgCIsan6iQR/Bw3WBaS22tBxbuGqx3KPbEU4SlYp7jdxzpow+iZFnHGneb75wmW6m7HqpnZ0Sz+eyUwjmU+CTRVmIgI9shYrTUDNeaYjVFkfuTpnfOWN8fVBovsY1le+52seqmIUbzGK/rYme3/j9jUBnL/TANZ9qO8tMayvs9fPhz3d3+v+CfzcB/xbbffX77/tx9U1xfhNbarqpTKREjPDqmQUoCJmADvPMDNIda8o2ZljpkqCLwYlUYNiborSihoo3LHGNvdfgdQUWrvdwTOMJZXrY6IAWTEhYlauPTpQFD2qYDHV5jM4ZrDF6Fg9CkqWMqY8Js3QDIhBGAZydZSqMZpBa8xARqbJyBnqAh2YEciq9YXNkqNUxfEqU3pu078b+crFFJGciwlIqoQXkVWRQKuIHYGIsllVACeYOg4wq1NQ7TyrKAxmsXKFoQbrVOnZRlATmEIgxkQ6E3jqsFbBgrkV+26empcvgzkjNjZm4yrNXulOKLXAR1R5/zNVttZNYHS01DGDGYdgdaqtKYH30cE5B7Oc0jhN4ziqiPfhuIDezfsGIxGRIoo3rir1bZVwVFsOIFrFMKoeW537tAgYyoXE+2pITHTMSuaaL91xrKkGyPUCmdS6IdUe09paSMQm1YeSubYR1HE2E1SRelUQ2jYQwOwqFDczxux4C9/NljzTsIiIXO2I9OQbUpsb61ULzFmlx5vVKv6sQw8jUgiMRFWzQGAMFJggeO88efYiJQ/Dtt/uDsJAjApSJaWAGL2IWoLz5KN/8s6T/WH0YU/gtmv7fjj0/TjZaT9cXKy7xWq9WjXNoh9KP0zjJBAZhjwM0/XV9W/92q/e3F73+1tJ0+Xp8unjx94vXr7upej26iZwVLEQ27ZZhcYt18vYdsMkn/30s08/e44AYmrbJgZWLYABxTs6O129++idR+cX9ak7DMNu2G9vbvf7G8tjG7lrw2cffzxOhwcPHrz/9PGibT76+Cdq6n0LI1EJTey6bppSyjnnrFJU1fugqikXIm9G05g3t7vnz1+PA5xyGgUGUIhhlWSUMmDE6Gx7269XXbdsnLVTTm3XhgiAmPlkdYoFvPeacyVkgIQqpwAouToRgBh93x8Oh5yL98FAIlCtNTwE7yqj83azKUXeffruYrFomma73YzDfhyVGU2jOef9fpdyLmkMIa7XtNvkwyE7okOPw37AI6zXJ10Tm9iRKpM3RSmVyWkpJTIj6Gq1Cs4753yIuc/DMLz//gdZpb1eji5vdtvl8uTd999dLE/Lh58Og3342c3Jft82S/Io0LMH52wkUzaMAhWlXAqUtVhhQ+OIDBSI2BOnaYIDew7mLFNfMEwpy+bs/IRIi5RRORkv2tE7Aik33jeBPIH0+z/8iyY058vTk+WqaxcPzy9Plqd94TQmgBw7x26aaLVYOu9Kyv1hr0W9D6H1y7U7DPvtfr/fHaRI62KMzbLrIjXOhZTGRJrGyVJetYv16UnbPXx9616+fr3rd0WLoFQsXERSzsTkHXdNOyS7ur7aDFuKBHLjmKfD8Or2ZrPtS2HnmpxLTtL3w9AngL0LiDwexkMPJbTt4ub66rDfM1k/jI6xeHCW07S93QGIgUXqVFJJfKomYIQIZjjHXbd+8PAkNLxcxydPzsjlXT8UwYk/ub7ex6bdbcebq93tzSSZAJPMTE2a0m43qFgu4qFFLA5ZtMSmMYUUIe+OZIiK9QCUnOe2C841TQjeuZyk7XyMwTl3OAxX26vD/jD2+aRb9v1BCe0CsUPTQQSJp6btSC0Suia00TchOEeL2Kogq6UR2MG37DmqomiBOtK25GIDwbtpBHscDjlEe331qej22dMHLqSmK8zWdO3hJhXJBGnb0LYNVggTTzPCcUwXXCVoMDtnZiUXm2njdWWs6leOpOCOsnI/QmJ6q9KPOVWqaMGxZaNO7W+iQVTqyMyTeQOizFwku/eqliKDkqMjbcbR7ESgJonZOUfGZEbBBRd845hdmVIuWkCAY7CmMt7sb1uJzSIWsmRZOReyBPXt6YPHj17dfJTUhlSGqRRjU4KpD4GpJWKCB7jym2PbdJ0ySJIaWc5jVQIg750FApsTK1qKWp+5qCew50nK+rwF9T7EKY8dWdvFZhFnpWeu4aIp4KrTiehdr41VJvecvR3jJAX8neHeG1SxIlCzdjXBzBxQKQUzEnLEwei4Hx1BSTuuwDW0UVMmfisGNoAVb3G/jpf1Hv/hGEF8Yd9jA9tMfzqe8lcc66s2O+bh9167SxrfBCjE99K/uTWhZsr3dq/3pOqslUVsEFV17B2oVFEkAjtXFO9843J90Q1p3OyvXSRWblx7drrIw541Kk9lHKE0Jsu7fbeyodzsctOE6fKdb/7mP8Sf/MsJu6k7vbQcZDr4GINvRKQUEZGjNgOByFTuspwvwIv3vuwMmtx72cBzO9YMKRuB+t2GfAzOO+9JVa2oCWh++GFkcDDH5H3XGtswDAh4573u2XcvPvjeeTzPrzbbH3740fVLXgbFyId9CQgUHATB/DQqWvMdAZZKMieqqlbgPIIp50y5Cbw677gJCKFdctTiF9y0vpTiqDk5WzN1TG673e13vR6wud2n0YhDPKGUJkn24vnVy89j25ytT5o2rKQkWLl4zL8YLm+uutvrlPJ4dYCOSH0W3WCCJIFCcPDofHAGOO+YZ+EJ0zt6Xo1EDfZlr7l5WN/a6Ivac7Ov0/0MV9WYXWBlVSvI8K3s8rW424t3wuKsWy7jzUZeXN1s+jSVLIacBYwY4ANUSpJxKmOMiw++9ezPPvw+OXKO0pRxB0XVZhFjB8BMZdZ2d46VrPajv5kKjkkKzTfSDHLv+x4OjsxMNFq3iOG0HWTc3/S76ggU0S07d4qDjJ69cyEECkGJ3FyMz4DARKVwVdQqqnwsVzvvpEjtTa72E5VhparzhGD3xrT+e3zfF5ObL97+d0/5/W1u2pjpom/ef+8HKYKjIO4X0rc7NPuY6RPmdPEubyd6s1rWN+uXboy3b5zj9rP+Svdau+5DaceP+AIa9ddvX97x/g/3z+ErX/zK0/vKT7kbvbeOdn/7Owdg3T/LilvdBy/vXvxZu/8nwZjurvd//KF+jo+uP9Tv+Lc6B+cdER2bfq2ooECC1IVK5xVoFqsrIgRlDgSAQeRrlEZGBFIVLdLGppRiRRyYQBUOEAUT4I5qSt6bmWiBQliJmY3NH2sMVB3tdK7J0byQmanOqtlHQSplA6yYiTFcmVKaxCbVXFtiHBvUuMpkeOecd0wkKqVkFYU5550LPGE0hYFQYNnMK1GVzbOqfkWAQUHuOC+8mSlqF5iqlSIlW6V6MRxRDWSrgZ6aWdY0x3NM5L0PXk1EVVRMMVs5Q0nJOUdVy5HgnROBVeWmGsMY1c5tw0ygr2E2IDXEZNVZFpPUsTOYmpqRM8fmmV2ZiompmClIqk48QaqeCNfxpdkXqoKZhNobqhpikFJKyTCwd12ziM6TWZqmNE2lFC0CgVYn5lnWtV5IVtUikkshMueczvgpCVShDq6yl9TU2SzJBpBjJscpaRW7mO/wN9Hd3CJSoSWtCCWAWW2NiFxKZSbZ1gtpwtUes+7NFagzg/FcGX6zIpVS6qPNjoEZbyIm49qmc6SQ1UYG0llRjImJ2zhnlUUyTEGsUDMlJvJHHXdDFR0DW93TszeGoMz2KCAiLrmMgyEKEbxHSUi5FEkN/Jim69uc01DKtOhaIXRd20/JRxdjd7I+zUMWYbMplwyO65Pzpuv6w3B9u90dxqHvNZU8ZQc0AauuRR4DaRtcmvTq9eumOX148WS5OFG1dXc6DOnQjxB+9fnVp3/447G3Mclmv73e3OasHLnrYgisRczMB1607clZ27ZusQ4PH11cXF48fPiIHKZx6Hebw+42TwezMhx2MYQmNs6589O1vPN0NEzkFNjttmUqBnPO+epNRzPQ65jbpt3c3Nxcbw+7ctiX/jCRIYaGOZQiRr6NrRUVzWgUKj/96LmPFtvLbtkqpsPulhCGYdrt9hfnDTymQ+JQUCDFODqAoveiUnIhQ2jBHmaWchr6frla1d5XUytFcwZz2W0HMzHTNE4PLh6cnZ33q/WLF58OozKj6yh4irEpJeWcvQ9nZ6eqyrTHZuj3GYBnT+Dzs7PVYpHTmFPqFp2obja3gV2/3bKUGCIzdV2bUx6nsWVKJW93+9X6pGNSzy92V9fD/sOffPL03fcePLpMRQtwezgMY9pubxcLf3J2ulyuUOyw2atpUXMGA0uFXtSmMVtRAhE7hcM0wTs1Lkom5KMD02ab9turZhE54PX1nsLzVefWq2bZLNg4sLsNMTj/8sXLxsd1t1zErm2ap0/efXB26cwHDgQ69ENJpWu61XK1WCyX7cLMrJj3odGQ/N6orE+b5SqqCrIRUfRwQQRlGHtmTMOoWaHqo49Nc3q+pkhn6fQHH/4wxABHRUXGsYhyLqbMjoKPbbfIpK71rgsvb64//eST6+2miCyXq6ZZHLZ7UypFHBO76DlKMKh3br+dkNM0TWNOaRqHF89fORe9X1y/3H7+/IUU5MGYyDk21VKyZ2LWbBDByQLvP3tnuWwXJ3G5apqGY2e55CawIRo1P/3ks5OT8/2+32yG/oAmWgxt0yzNeLcfbq/3PgaCpZIJIHApOgyToUxlUpiouoBFGxfrzgWnOvnQt10HcEr9bjfst4nQOoRpkv2u3++HItmzz5OlEeRALQdynsFEIcaz09Npmtou5BJWi2YY0mHIaZoIzhF1HolRsrlAjj2HwI5JnWWh6L2PjU/Ra5rkcCjsCjBdnHty0/osNNEt1qs//8lfTun0rOGz9dOiBT0Q4AObshFX4R9T6bouLpoYQ5rSIENR9exsDlXAjmFW5J4O7rG/m44rwRfDJipyZz74BvOqe7wpjhtMbE7EXV106Gj1ciQP1H0NlgsQ2LMRVce+WhlRVaYCYXOsMM0TR18XEePaHUmoeHFwu2m/6dVtEdqAwHAmxGOxs0dd13XDZ2Pfj9td3w8gkPME1hDiar1yHpUaH0MM3q+6k8by1NuQs4pzjvshQ5jVo35XFSI0Pkx5kpw1chNjrbTsD0hFUi5u5S8ennzwi09/9KevjGAKY4OKGKDGpCByzGCq7GybV6x5vVUG7C4EOA7V3W/HvKtm3Kb6ho1us/QZ34FdR2EAO6JK9gZOhB2JW29hWG8zVmoedQcufbG99A69uoM36xvnO2eGtL7m9hZgSl/8YSZP6MwCJNLqXIw79OcNucbmxiXHsyOnqTnvlOZfiEGeUfAbf+97COnzV692/aY5aadpcr5rYqhlGB+8j9S2TYhxksKBlbRZGMX9bvrpP/6v/9GvfCB//Ac//dF/eO448sJrkVSyqokUqx5wNEtfzWnvrGdWq6tVswUAuJpO1CjSjO5/Z6qqFrUQaGp6cf5gmqZxnKQIKhDp7locqPr1gChbUVH205P3l7/6m9/4nd/7pXe+dREe81/+1X/48AcvfvKTl2Rdf33QQXVEZGLPxdSRb5uVBjGnRsiSi2UHFICCxMYb5yHtzaRdNKuzU/MMKi6EcdrsDhmgGJbeLZqgUy6H3aGkHFqUYfAUFjGaJ+Lx9GTZNiqJogsni5V38fp6e9j3JeflKrTN6fkpPTx98N1njnP7L/6vf+WFJ8tMaH0I0VUHQlOyChLW4ndNcpRUFEowE6XoA93d8cAxQ7mDO/nNbQ2rInM2x8pmd4+dAbN0IJSxPu92cVif+U8/u9n2r1osigR1KxfRrag7W108PLu+HZyHD+KDEUkZy1SGw7B90Cy+9Z0P/uyffZ+MyHPRet52DKlBxGRSQR96g0zda+ie2yC+4vEz0/X6RK0kGrMWGOIifPDBB4h2u71+/4N3P/r8R8Sl5MQSIBhLciHWA4lIt2pVUKzA4F1kYbWCIgZ455krs15nO3WYzTJTlStFM6hlR6j8eBsTzUXneu53g/s3bEfkfdboqYb2dFxyjruL1vR2nnCqnVdROaI/tWR/nJFofllFmNmOTY53mNpfQxi9myTvgyRf+Yb7GNYdknUfjfrK3b/yE2dY8564U/35/ifSUf3p54NT7g7y15/V3y0A6/6XvBum+//W7xNCuP/X+2/4j//cr3zl/yEw68uHfQub+2s+9/5FncegMpfBVBUlVExQXIWMaPYmVKBaLRjIlB2cYzKnFaCwoymdGNRW3aK4LCwll1rqICJ3ZDOyY2bv2KmpChcppES+znTMNZqpvnlkxkf2NgCrtRhPhCJaoMGTI7KiMikpTeMgWfKkSIDBOecA5gDTujQCIKYYQoETVRMVNmZwNaL2RDDNkk0MEikG50GklShGs5YlMRhsJlbF2wlNbDSLZJEMKmxFLcMMnhwA0QKwc97M1EQ0mwFm5pRjzKqqR2tqM9UqdkX1BzfbTRCxFAiMq249wVhqo8QsMEgkqKFQjZwxFzbZOZOjUV8dygKDcvCCMrfyYVbQhxEZVwuZahppRmRMzFaFw8jg1EUSU0gGkfPsAzyxTJonTX2eL7NCs0LhOcw0NzMGpz6RMsOpqKgZz9OxDwEEtTpWjkBaTLXGrbPrMLHcpRpE1WFdjaRGo0oQKBHNRpizShfNUrFuZhrOKmA8LwbVpf4No45galTXsOMaUAbhwC4477xCtZIMydgxOYgZcW35FDGdgRVmES0ykg8GgzPvmEDFSgXktH6qEdjYsyaomgtujq3nQizZ3H3qgveqNByKN4q8SNRPRaxYTrn4TMDUp77vVUvOVGTrFnEYDylPZydn52enU5PUqnJZ2+8TPwz7XeoPw831vh9HzZMIcoIHYLi5fR3ITpfLovb6ZrPd7R9fxg+enT9754Nxkuvr3djnVy+GH//oLz/8ySd//pc/uLoGgLlbNCA4+AjHUIXU7mSH1RKxQRvx+OG7T997+uz9Z0+ePL68PAt8fn56SiQqaVrd3m6vrq9vRK8dGwhd06qQiHZNV6OJKQ3kHRFMhIPzPjCxC/4lvUx5l3NJEzEkEByBApGASWXqyaZ1GxSqzt9upk8/f3F2uWwWXZpsuy0l++vtjefV+88Ue7hlMSXnPUHLlCtRpdI9qnpd8K4J0YG71UJN4NC23jkaByFyw6EMSCJoI0yZiu/i4tHlw88/+1jzhhy6xjtWmACo6jPTlAD1zrpAxVOezJEtmtjEABMtSa1E70nR9+PNfn8Sm3G/b9vl2dnZdru73W1D02CcNvv9LqU89quTdVyvFlSuXhyub6/Xq9P1ih3QBH54vhymOKRM3nkPdkpMfsEJxKKePQcaR8tTTmU0zdGH2LAUKSX7LhSz2k0rZkaBldR0MjmUXoEmurVfTEnkdrvF3lQI2vlFEyMTGheaEDwHz/zDz358ujq/PL28PH/gvd/c3JqaFCFD9OH05PTk5CT6BoBaWZ0vmjYuukUT2qaNcd0wMA6DWmGyyWTY9dMw2pinZeFFdJaKFHh3ur5c3bxmT1POSiygKaVcSiWquOCePHrC168yKTF78of9UIp479tFByDn3nMMjtizwTwj+MBmKt7Hsru9HYdeS9nv90rYXG1/4ZvOkt9fmw/eUOZ8XJQ92qVzAevAlxeXZ+er80frtvPkzPmssGkqRXJKMg1FgO3tZrFY5tE22xwD0oS2QRu9Y8ppqmqI0ySlQIH1+ixOwShP0zQmJarlInLEjtBGGLEiErucbHMzHfYy7HS/22oBzJkxlAAuJu0yxmCpDGnUtuuIgmoxcz60q7Ozq82mlMyNxSXv09QsLiVZkcSe4AAP4WIevvVNG0AoAMyi97RYpLIBo0yYerTRNttd05BFOMJY+rPzOI1bpke58Mc/veIHOFyNXQieOe0VPhDRMi6cAzNFH7zzDJ6GUYoQ1byOmBwI0bFWbxgg5yJanHNzBe5NVjyHP1VvqfIBYLPm8L3YvOaBMKje27MuFCZ2xCjI1MhgjuA8wCZzc5XWHj+oiRkZCFxLS5IdyIUQnNPgkwKkIFosWh95ux1Za+sc0iZhYeOIhw/Dipc6IG01HUxGQOCcxpZaQrNGs4JnGvph2a661jNgY9u6tY8kcdiPw/pkdX3zmoWdmClp0jxlCLynRdtkgYhYIWZ/2PdEM4bGAAAgAElEQVQTsNtggZwWh7N3/C/+xoN//j9BHYMbGLOVQCCnWpUqmJipiNRiFwwwqYlZbWOE3QOt6gAe0+76slbK94wT3tlj1b3q0M0MCDZS0BujljdcKnxB+KVSV2hWFz8mxQAANuJZx74u13eZ0jHForuEze7dLnXXtwLqu0PTm8/GHbrz1psxp61UdzyaEIMYKrP+kXN+DhFnXpqBCtgggKnnRtXEkCGXDy6fv/yUlt6iScjI+OB773x88/39tNsNh9WDxWYznp3tzEby+2GYWBmtL44gYqL9TnJqh4kWDZHbP/rWycPHl/HE9vr8kz/fomkDdZaliKyWi1yGIqNjUoXkKqjPTN7M2ax0OnPvaj+oAbXzluCpzDQRJoDEtBjMzbmzAgWmpEBxQON8JCuwg4HYLfIkzXmXdSw8xdN89g7/ym8/+Pv/+ftPnzVhlX70/PWffP+HP/7+xzZ2S3eKUfqrqeXGwYmoBRNXABJiYw9fipp5aINuieDRdY2D5cNgTprQxtaRd1nAHPI43G764Jcjm3fJQaJz5TC15E8W9Oz99WG/9+y72KZEv/SdD7Tsz1frlX+EIWwO/dWL/uOPP3911S9XD58+fufkJFwuFE8RQkfNs/0m3VxN+00+HDSP0BTSRJ48CIrCbARVUTI4wCkg5uCda8e55Ktz9zMJSEFHPHrWI+cZFSGzaj/lFAQOAiXLROwcd0yu2LhYyuLCvfN+yBgO07TpcT32TItXr19pDlA7704en11YeWVOlZW8kefCWSjv6GbpVhfP3oFHLkUmBnniQEoiCOwIKGkiJ0ZqZlZVZ10EqNpYz125tRTJDDWdjQgdMXPlBph35OBiDsmv/PpRl+nQ5+v1eXycL/a7XdoP2ZJfto33aRod3GLRlCzFyJOLwZOSJhgbPBtq+naUFbK7GUsMZiQGA5PVwtAR0Zrlq2YYHY49jE0FsGoPOC8ex5o63Z+X5iefZpkfZTObdVoIZI7oOHdVElhNoMhVezEDyLm5YOt4btZhtqOTGI6z5pyz6B0AiLfVxY5T01uY0Vdud0DS3a93779Pbrrb/kY45V4e/zYy89ZZ3dc++jqn+nNsf7cArLvtLdTwrdfvxv0/eePl/+fbz311CVWdDkw8YxTKBjWtLW5gmetCBpDAMZwxFyI1JwRnpkI228fByBGbCKoWeDEtYoVq9aNKXzu+c4chYJbEcnUKUGM4g4KtspbuJgICSInnCXqWrjIjUrJimtWbm/pMApRjKYKY2JkRKQOlsodITYqa3slGWanm2/OcChhU1ETJvKNjfGGqJHM1d2aCVWqWinIXO00qBVoIwiiKYgY1NgaRORhmpz4iwAoVOJiDsUKqcGw1s3ZHIyRS1bsoyqAGAYlAXG1Owx2cT0RVKsAdeSl3ehA1lODjvAg2piqZYcot29zQCYLRsYv7WN7ROWqsuh11+KvKMyNbEioIcMTBs0FKyXlSSQol1CXWUHsYKz5YFUgYNI4SHFfHQ1UhRs0hKnAzP75ExKRss+UsgxWAMrPAQEpVfIpZSaxWJwmYjbTnR73yxmbjAJj3xwLQXIAlQj3DY6SrhtloR+l++cIgRYgJ7ii8D7urElcQkUDeMYhMlWgWKxDVkjNjdnNnz86xmaulHhM1mHKtmWloQyQvMBUVqYq31LRNKtPssUWspjkVo9A0zpsLJExERillVdVShqGogVCmsnv/8p2mITNadDEGn8YiBdOQidBPw+XZg6qVb0YwJYLzcIxFxHqBx08eDIeDmiWRYrxq1rFdqMD7hZfy4U9+9Ed/+Bf/9l//8Op2U7SUgnUTXHCiJeVyso6AMLNznj3XmkHKSTRPe91O+vz5pz/88cuu+/ff+uYHv/33fuvJk8ePHl6en69jQ3/wL/73od/tDnuzYdG53X7nGtknrJbL1WKZSxLNQCySRaSoUvX5Yh98ePT4UZogmXto2+bcFoZLQ1ItjkiKebamaYQjIg/9dLWbttt+dRLGbLAIuL6/vbnZ7nYbKNQZS/UomCVCRYqZOk/E5hwH54IP3jlEm7KGGD0HGPX9LcNJMTLkDGuRc9pvB32EVbe6OD2NoZQyEZmZTlPvXHTO55xub29EE6sj4+hQAvI0EpkjkzxImaZx6PelbYJoOfT7TgHRQI33Iav2aVp2XSrp5eZ2M4258V3wHMNJuLiYEoRYIGnyLBfrbjjsYnQLicbOmKRMWUqfx6GMZrqKK2aSYlSgaqBCzjtmQ9GSnA+QY1u+QkoBnA+OfQCZknVtbJtl9KoyjeOQUyFAmyxErQ/wqiZWiopc91v3+vn5ycU7hyfrk5NF1y0Xy8bFm+ubz69ffnLz6Xq5apsFzNRs+vdjbOJyuby8uHz23ru/8M1vnuD0NNKAYbu/6UUn0D6VZdtwEw9lQpmmlKYpjXn6lV/69WRpe9i9evVqTOX2dseQsOq2u13S0i66UswcDftpGCYTWzQL9YgxmEkMDqqp5H7QkhHDFEILUBN9pLLd3u53Wx9c2zbEkIm89+wZLdrY7qc9BXhYVqjgdi+PHjW//GvffPjw/OR8HVsWnfrhcOg346GfUs4lp5RVLbYdUJiNwSHgZB23m8QM0aJSTLVypkVFFHBYLBdN69SmfqBSJBVRhRVLU3a+eOe5ISPK2YZB+4P2e0wHlqnNk6mIIyIgF+t7O1kHUEoZSYCYlVm5RNG2H/2i2e63LpiyLU66wrh8cHn98nYc82EyJCCg+MwRvnVwYiaGJOaA4Bxpggvws1MvhiGrmhoptM/pwcPV9dVexHKBmPu93/3l7//hh4dXE5EzZzEsiCn4lkiljOM0Buej9+p9SaWuS2a1lsBztFALGKpqXIveOptI4a7wrKpce9HfsERm/gId84t5DZg75I7rAr0BLI4OYUBlQytDjxLklURj1VddZ2pvBU1qfws5CsquWvk6Jm6WjYMhAYquw9Rn3SJ0WAc8vXjwwZP3Hp0+/JO96mhWaioF15E4mMvkJg5NU3zkLvqo2SxXg0N/ul4sGw2x+eij10rKxMTGzpQKCkqmGCI5OAqeY6FcJKGgP9iG+8PZpj1fP/3WEh5wTC6wMpM4hpFNVbeIieABrU2rR4McmbWGGfqzIlQ6Bh06ayO/LX9+h3zRPNJH+lVlL1gtcx0vyfEK2TG6ZaL7nz2r7oDfyGfd+6h72dr9XOvu/7Uo+OUv8TO+21eVt2dWlc0I3l1/3TE6UZCbB+WukVJw1HIWNQeDMStJqdVXWFAEbc668DiO1g/5MJVxHJGnvFxg0emUxsXSFEkKSLyYkWU2SYOlwV29TnmYnKWW+l//9u/9Vw++V7T8z/lf9T8cs4ijcH65BumwS92iZaKx7wtQwWllz2AyNZR55EBs1aDT6vUgVihXLewZSCYyKCBG8ITdza0RMTVN2xKiKllRImrazneLabodhmvEAtHe4+lTfPfvP/r27zw5DJvvf/SXP/i4v36d0+h0sDz1mBAQoms9h+LExazQXKasHtqADUGxwOoS68tmedLE1qvVlKCANaVRR5uKmPGw0zK1DS2ib6dD//rm6nTZprEPjEi4iGA6nKwv33/32enpyXvvvtsfDuPQl93q+fP97dXUD2G6XS3o0do/6PgkomTbAyPp8E/+yX/x8UcvP/7o+pNPNn/10fPXVwM2A/QMvqYAppLrhOMIrDUyhjdyjgU4amcY2BhmdBS7VaLa1DvzsMwgBhjJHNaziECNQZ7ZsTmFNku3PMfjp5efv/joarPZj6C4dGFxM7yilJxgGdq8n5wWYxMpBZkcaRAiTra/Ta8Xfo13QbeSbwQUnQsGhyIwBzKFcBXhxazNWy3GYSDiuUOX5uYFPkK7BEfMjtz2+RWWHp2aV2R0p41b2PX+5dXu+dnZ2el6Oe77XDiiiXHBzEPqiRG8I9E8jsEaLg7ZNEnOgmKmpGomSkIMB9M7CpRBj0QMmBmUK0eQ1KrWYKXi6nGeOcJVBIBcVXe+pzl1TwMLc75LbLObSpVcNJs9oI+5Bpmju7lGFfeXITsarFrdjSotuL40t58QMMOXPxsQ+JpYwZfmQLz1693P96lYX+fIXz6ZLx/z5zvnr7/9HQWw7rav/MI/R3vd/x+2+1Zx9wZnnhuhZllUZ36PYw+zNCYC2FXCD+hIA63I1H43qIqpmhwjmVpOZIAgIpXvNVfRyFDhDlUzq5QjPaoXofLIUREtM5g3I6LgAilThkBkUptEYNZjrntRpeSzGUQKVOfaBJuZ5FxURaFw9aBFhFyoa8Kbqp5WdqlqNfcTwGxW8apiJtDKbhbXuazFimgSy1oxKDUTtTcCSWbeuQpGmFbMj5SM+f9m7812bNmuK7Ex51ormt1md/pzW16SIkVSJZXKksouWFUqwHDpxQ/+AdtP9Qv+CH+AYdhA2bBgw0AZsAG/GJZLkESLEmVJJMXmXt7u3NPkOdns3E10a805/bBiZ+ZtKEpluFwCFA+JzJ17R8SOiLXWnGOOOQarKZvLZKF8iqoG05SMs+i6v5kIs1b++Pu+SOiI1Cx7AmWcCIaxPw4gg7PMQc5HJhg5YVXZA/jj9MlGrMLMusdoCET7nvzcDAi22A3OuaIogg8EkkFiF+NOUxTIKDyVkTgbaw3A2E+ekbX8eib1gRxlAbXramsmxLKnbDunCWrR1JwLDgRycKbOvANd36/rJcCwp/mOk/51nYAdYS/mJaYwMN+soMQ3877d9IcABBVNKYGN2RkbQMw5LlYdtT7IzMDMjtzoWyeS+ygpASDvCWDmgig3bma0rKxKMxu6QSwBLudUxK4oQlEWrmAXWXWw0UczRumjClHpvasr9s7McoejauxTgipadNLjQeqK0pXVcjKdEULX7nabfrVqoeh2ODs8m0zqui6rMiT4NEQGioDj5fTu8XKz226v1gWFe8f3Xn/84OH9R49O3vRS/87v/C//8n/93z7+MeCAgIJzJETJWBOJOjW5XMUkBhUghhJVxWVVAbzdJmUUIQyD7C4jED9+8oPf/b0fwOMbX737m//+v/fNb339W7/0q1dXr549//jps/dPz84/eXJa1Fgc3rtzdFxPytXV5TB0eY5KKQ2iSM45z84rY7lcNq0MnQ39wEUoKiYt+r6Hc2aaVKAqnZWzeV1NdtPVEHF1uV4cBmKu60nwtl712932/PwV7iForn2NNKMkKTWRPTvnQuGCd2OtXEmSkeqkmLg6xCSvTleSBApmaERnsC1ePV+dnGyOjxdHBwd1RZvt5Wa7bnbQ1EwqrieTqii6jtsuETsY15VOa5dHX4xD1+xM42p1uVlfHSwX0+kUhtRLGcJ0OjlYLsu67vphNptfrK8uL88vV2dtHMpJVVX1bDF/dO/uvK6qULFzpQ8Hy4PTly8IHELhy1KZLlfrvtmmIabBHCN4z+Qs2qDUaxIxA7kiKCDNwAwCZ8IEDJqMoOZZ1dhxYOeoIGLH3kT6Lu12gCFNelHjmc+KgJpS0253275pQOnFdPqX06l/542vLJfLN19/o55WZVc0F92ri3PnV3VZlnXdpXaynEwXkza13/7jb/93/8N/u9us3n7zK//ur//D1157vDw+KHwY+v7y5dnLy4vuWTudThcHS18VhcPvf+f3F4vFcrk8OTp++OBBWZVD33340/eePn86rK/SIPfu3hOWH/7kxx+//+HHH55ySU1vBoQCD+4ugvOLqZclUgSRdy6kQXftVoTn9QSSROPqcvPhx2eFCx//9P31Rao9icSpm8yO5w8e3nnw4Pjo+GA5n3bD7vnpx23qu/O2nhSh4CRJQUOSi9XVtm1TRFn4hQtFPSEi53F0UBwcHMfhpZntto0kSTGOJHzAexQlyiKojZIpatpebokggq4VMYBTzQWF0HWy28Sm6dsGuw2GFinBGcqi9N4Fh6qUoZcULUZEAdxgFuGtT3CXBG/D0JZcqNj5+elqjTsHut22/dDVZQgPivWrnSt8WRW+YLGhl36gRNH5nnwxLiNF4eqKmW1oU64SmaRB+zuvvTH0uHqx0m3wk8U/+q3fuPxk+8OnT8gTal9U3pjIcYr9utnALPgQXIhDjE0kB1OQkWcjJs5cZEcgEIMdEecQ5KaWq59BVGhERvBF8MT+LTfg1g3KRbnwZUxjA5uJEFFO0XP13mWFAYyJT85GkqmpSurVAwHTKrAjIixndQmv25bFCl8sDu+l1zBduEjr5XzqGeurC3I2hgpQVbjgfZBQZDV3TZKGZojd5vmTs80K6ACHusDR7ODg8GQ2ncZWJKbcg+a9T5RSTOgNgaqyDqFQNRVGr6vVJnXd/aPFyb17R794B8coOhu6JPBIxoHI8b5a7kBgvuWId0OugimUMs/tsxc1K7jnPZjaF2gOj7vaZ3Ej8ETMo4KWjVHr7ft5rSIKvYacaO8XfIvTj+tU1G59/pp7tWd5fZ4F8IUw1s/dbjMX8JkHaf896dZRrpNb3UOeSBADoSBidrzdtCg9OIHx4NHRr/7WN58/vdjsrNul2OHli9Vrb9xXaDFEF8IyWt/p0ClTsAjppC4BDesr3aya1O1evz/97p/9xZ3lm7/527/8j/7pb/yL/+pffv//eoKWhv7MlOBUyZmwYcakigEKmJADsQoPuXL3mQuzh3bHgNS0gnkDETlkhygQexGDqDJFwGJMQEThhrhD2t392lyoWz7Q3/jH3/yN3/qlB4/vrnbrn7z/5Omzs6T+27//w4krtXXr02646NCDwZ20RaHMbB5GohCYoADXVs7K2aE/fjA7vD9Vjr30bdvlFKMZ+tjo0KcUU0raNNExh0p86jfrVWjwlXceP7x753CxWM6WD+8+Xl9tJMkwpPe/98F/8Z//N9gAD3A0xbbDsAMSsAVaoAbu4d4xDpdYLCZVhasXvihnX/vS3/v1v//g7GL3x3/8/VefnLWX7fNnL2KvYcpEE1JKXco8oOz9LkRmvXOaS9JMY4spGeX8BpYbkgOBQJFMYWpZUjhbuiZoNFVxxKAhwWBDUdfH9w4evPHgySdP1tuVOHjniDwYxl7FuijbXd916kpWdlGjmUQdnPlt36w3T2lRfOuX3j7/4OpSt82mN0fQgthUQcTB15oaI9k3NxLD7YfSLcEmG5VLspFplpZVourBItQOhfESK7v80je+Mj2cvPfBu6eXZ8VkCqU2icDXk1rN2qZp2y44713SaLnnWPdkR1NRgeXCisAS1CwTmWhEqkYGAEBIudqgGVkm8J5hRQSIjE0fN62E2Cv1cs5uxrszFkyICEwYaZ9Zvz6nZDcol5GZOUYOqfLJ5cuUKaJgIjUyQGCWQATsbVKz4eO4vBBohMZu1rxb085fEwD5DLT0+anv88yp26//9WfIn0vd+v9i+7cdwMLnrmC+QNfcq7+DsW5vZiYit5/v7GScs5QMqRgbOWZzJhpTNCAEzp54ewJTtl/A0MtYwcwSUEzGgIPRKJ4tppoSuRFLvsF6YWBSUux9V0cwxpCluBygRJ44IJhCehEVGdQGA/a0zMxhYogl3tOnzCT3EaiKahIz8uwcZ+q7krHj7HA0troRmSG7dWTJdQc1IiaXKZqmI1CFPNEKWYRFRcoTE8GyPj0c3HX7ghHMZeklUzISZTATKYgo616pqqmmjKXkJkVVvvW40k34xXxTEgYwMu9pL2qrt5qp8emqphGRAxmTVyPOUJBkMu0ezQGbgsG0vyz7IqepOs/BheC8Ruv7LjUi/Uis29fdyMRgoJxaEQBTUVPdezsZAFJjN6qFGZSMjNQsAR5M5HKxQjUTrVjFJNeeCCSW9JbayQ3mdDPwiW8HVLmWkVUBxmaRDKpltxe6htw+u0PNGJYxg3x+JkdK1HhTmUyNgyNmBzIziTcdiBjl48aWUwDQkaZlyYzMO6e9iopj9hTYu6Ioi7JIMhBBzfp+AClgIgAnSa6oS+85pialVJYhc8qcM+fgPZna5eochLqaM7um6S4vNuurru8AAxIc+7Io6roQ6wvzTJ5IygLVJFSzOrbRh2JWHxyfPD48uL9e4/mTn3z87ukf/eGfnr7A/IhNXUqurqbG3HV93/dqykTswnRWiiRJZmZGloS1VygG4bII1WTq/LCVLQOhIoO1EZ98cv77v//dH/zwx//8n/8nh0e+mkyXy4Pz8xf9kEx1VtUFM6nBTJP0qe9j3/b9ECWZJSCoek2qLkaJiWJKcRiGZIFDURVBYaIxDSkNsRdzvS/L+WzZ9ldRYt/HeuKSGDE5F3bb5uXpy9fvH16e79o0iJiI5VxIkoqKLwLDqZgkUelENGWkclJUddAESYAQu9zWq2wkg7W74eL8oiiUGVVddINXQz+g79NQbZz3BweLelJULaWou1Uk0GIxn83m00m53ay3m6u6qmgv7Jj5X9OqLpyfVpPCB1Ml5rIszDDEQVSfv3geSe7cOXEMib0DGFoX1aSskuidw6N2iN0QyTEcT0ovUohIYnEe3pMDDZy9xiwigdmF0swB7egbMdp45MFpQx/BzA7MXkRjTENgIJn64DJkZUNUciGKDjGmlKICjqvaPKBq56tUVy9enJ2Z8ZfefnN5cnx4fLLdbterK3Juvly0fbtrt0kjQH3qDg6PFsvl4nC5brY/ef/dzdVmvpi//ebby5OjoixWl6uY0uVmbaZDP8zn8+yOulqtmKiqqmldv/H4jeV82QztkOTgzkEbu66LSkgi5uni8rIZtlU9efFsfXhYLheHZVVFb7EXSbLb7U5fXQrBVGCyXV8N3ZUmHJ9Uh4fLw3lxfHwSB1suDlPSGLvzy9WLl88lRbD4UshpWYf75UngSgQxqZjzRV2Z6ykqsOvSdDolOFAKoXDeS7ZP0W4Y4hCj905EvCfvXSioaZu+b0GJHbwPnLUnmVRtGBAHFMIheMtOIRpUUow29GDmup4UITgmdpgveLPdau4nzFm/9+TMNPV93zZNlzqwDgOKYrGY6/Jg+eSDZ7tGkMRKc1MmAoKpS1H6gcQIphJ1qIqJDzUwlEU1qQOHBB1MSMUjkSb0fT+d1X1lm5eXca2/+NYvuwmhgpkFz8ICoz52AzqoQRElRopQyugUxpZsZeMcuzMxs2MeDVJUsvxBXvA5S25i7yI1wgm8l739XGx4s6LQzc8R3YCRkY6rx0hAAWjsALS8WNGezDWGWJpYBmUikLoCvnRFcKZKpHVVPLr/MDVxt+5efXyeiC7rNIRVNXkcY7/broPnogy+8NYOQzSWKAznyEw1pdSndtu3V3HoUBKDkXrre+sJNnPL2bKxZrvbdW1bWMHMFJjgVOHYFaFwLkCiCsEQo17F9eXV5uHd4WhRfeWbuPygfNVE6ykmtcSBvfcus6SJPHEmm7GZIK+Nmc+QRwo+Y4pNxAzdyyblNOa6D+fW5rz71N975gP2qWJeX2lftbqOeq5pWvmvjDGa2TUD+wuzgFv/xfV7bidy14XevyJJ+7n/2j8RRLdEzvfkC7sOW3I45kC6T6g1wcFnpuGubcOisFLTTI/uT9565/Hv/eXv95aaVjUWV5fDO1+Z7tpNEXwovBK6VvohBQoyIHY2qcJ0Ngesbbpuh+bQhYnvrLlsn5j6f/BP7r3+9vTP//DjH3x3C8BPqNluoRWJN3XkKmIlSkyJnaT8mN+Kt26l5jeviArUjSEUc47BQhVS34sOgsTBucIEAKeswP0rv/Xaa28v7r9RHz+s3eLqj77/g6bzmw1/ctq8/GjTnoM4pRayA7pcV8Jgg1BWFFUOoFLJkZ9IvawmyzA7DJPDupgUu6HvuqHp+6SiKkOvaYDGbMeKFFEUWrBMQvCzenEw+9ZbX17Us9j2uop/8MffPT29PH95HgeFI1xgdryYYFqk0mnsKXLlktO+bKMOYSObPvVndlk07HDx5L0wKR6/sXnzS3GxPPrm136hf3Pz/JMPlM6fPr2ITbZjB7QAnJgxiB2ckbEyD9eKYjmdGlU+ciisbp8dkEGzD+D4VhjDwwYC4CRZZCIUcBP2tQ9VcbXZcSiLgg1Mzs9mC6el9kqwppe21QIOIZA3qJBATYfWOFrTrx+9fVcHGZrYDL1ab6QGFvPMLri6GyKzAwlbRqhI6VqrywCQ6U2QPEaOGZdL1XTaxib23dRPlgfLy91qpetGByqrs6tVuxm6OJRFKcyDDE23y32AJrnc7BjOwUNBntQZxESE8tDOvRwZ+iawMe9rEERe03DdDbNvRyEzy9yxfKbIHltjDrAvhO+R8lykRi6L6Kh6AmTMkXNTIpsbJyojHj8GUkGmVmWyFiGzHUz3yry6Z3Bm4Conk2YOtIfMMhsDDEhmfX4aOv8boR+357rPo1dfOL/9rP3/3Nd/1rz6M3iv//oYzt8CAAufu9x/h1594Tam9HskdYQwroncRgRiNpWxx8xgOozZvZkljGQaunZJHQlUWUI7u7GBHITGca+mkJTZW5nr75wbhzyNqp4ZTdaxfIBsWMEgYkcUmAInHboIMSSzBAJljaax1CrQpDpKqdr4NchUJUFB2R6DyedeNOR+NAbMgR2zczCIaNYFZ87oNrGNFJ4cOjlywQcdVAbVBCRAMoCVaT5Ce1Ys1ER1FBFnJlMzFVXHNyPzU0/lePk/P93Yvl36CwqauYBBChDtyUFZeGAU9iAiJjbktgrOdklMZAxzLjNHOJcK8uPgiJwRsRGxjR6MvgyOHQwWTXuJXZReWRyBQWQmRMTklGQMFvODYgqhDMsR5dRhZNQTYKawfPYEjGsv3DVQp6pQSH7OQCIwA5sp7Ts7PjWkiTJMSGMZHinrld2edmkE2vaX1W7z7/ZVZBpLyrnxUoU096PQODTy2ACrmlO4se3TNCvEkxHvy0xGUAiJqYLg2RtMYwKzd6GelUzO1JKqpBS7IaVEbOyJjPs+EscQnGNWMhH13jH7JK2ZOufYQSKcg3Ps2Kkk0346Xc7qOsV4drY+O11tN63FMa6sJnVVFURgh4w92WcAACAASURBVLLyk3rinHkWFyAad01z/+TRg7uvL2Z31hv70V+8/+GPX7z/3pPLTeO5SqLWEnnfDZpUYlICO3bkmFhlIIPP3bhqKlEl5dK7Vw1tm4YuSgTYx0RwQtDVWv7sRx9B8Atf+c7J3cWdewdHx49O7jxsOzS7FVEf+zj0nSNXFWUf+5RSTHGQ3FFpHAfXuaKcqjI7z47FtO2HSCAUjjJ3w3smpGEQabvu8KAuKzOWpmmn0+Wu6xhOkrZ9evL0yZ079/s2pSSxVxB88M57M8iQxCkUmQ+XemubwYiGwTj1kkgVSPDOZ/gbFmEME43Wtl0/dOxQVTW7JSDB7z74KA2DhGJb12UoyKBM5gNcUR0fH945OZlM67NXZ9vtpiqL6XSqKpPJpK4qt8Dx7JgNRQhd223b3fnVerqcD33sh8GH0HQvz86pKIvCkbTtbtcG549PTg6WB2Uovv61r15ttpdXV9um7eJQBra6JDNPPYg8TCQlSaICAojFGM5TcOQCYGDnRuJJbssWTQKIMsAaYyJCGXzhORRVUZNlFUEoUdENbd93osIMX9eOuHYFEee6xOXV5ftPPiym5cP7Dx7cu+ercLVdr9ZXAtk1DTHKSTWdTmc8m83avu/Wu6vvfu9PAe26vgjl6ctX9+/cnZT1bDKp6lJTGvqBmH3wBAxd37Vtiqkoin46WyzmxwfH96ui6XtXuqLfPbz7IBTFfH7kSnd2fnG12xDZ+Z1XdV0WRaWCtkuxTyK0rA8enjzyBX/57Xe2u7WJxEGuLhtfuOOT+80unb5cbdZd33R9P2ybza5bt/22GzYxAcDygO/eP06mTddfrlZ93yrgw2QSalDXNG2/3d69exKCJ4pJYte2XYcQoCxDG1W1KEJKiZnLsvCBrlZX683KezdbliEURSiIzDkir+CkCknmlB27EFwoonPENBQFV9V0Wk1SkrbpzCwEt153xSQ4Fyik4MlxYC/GKfOMkqQhUR/R7ND3qoohpnri61DP54uLi8uUkisslA7iIArHSkreqklZFGWKTVkF7zPLOpkQEguxJN82/dHRHX+vftWtust2FzflgVs+Dv2VOPOxG1RgCRKEg2fnTM3EmMCepJeRUZWbLvZd9MzsnBNRVZXRDoPgRhZzDg77Ie6jRCLAmG/UDz8TJI1L054LQzS+M1fYrpdxHrWubxaST6XyeRmBisFIzYhkb7YmotLsUm0uaCWdrZ9v1lsLddlfrlAjfD1Magcdds06ibFjZiTdL3IAqYmIDCn1ljpDD2cAkYrGLZq2P4uryWFZF1Uq0mYdB4mBgi88QAJjdiBWzRUoMg/nynan55fr1fpyUWz+4T/69e/KR1eXZ0YkyqYBFHyAEdQ0myXn2ltee8csMS/On26o2a+zer0Aj+uv4bMX3zCWz259DNflSttTAHJ0eE24vr4buFUc3R8K+/7BW7u8ReIygLKo5W062BiQZbiM6LN7+ILti/5/jVrd/vuz31gV1+EaRuIFGRw7RQ6yPcyJJZCRN65w7/7i4H4VsXv2/CXYdbF3pcGhbWLbduyMnLFnJvFeCk/KINN64qu6Vkl9dF3E6dna7gQqVj1f9d326M3lnQf33nzjrW986/y9Hz9594dPW4+0AYYEYi78KLxkkiub+/o056pGDrBu3bcRAshKD2CG0YhTmIiLcIBXLTSUcAHvvPXGN375qwd3pt/6tROar9v+YiuX26a/6s9VD84u5f2PTp+9v/UdukZiByQuaw8lMgpFUJJeOwR1tfchWGF+yvOjMFkUYcLR9etu2Ha7pt0lEcAn0V0bhy6zRMkFCw6H8+rO4XxRTorDo4WbLcN0e7p9/uGrZqV/+b2PNrtmdbXTATT16F2BWdCFttTt0LbmfeGIqWUkjpYi+4bNe7Cz7YtBy8vtqds854O7B0d3DqYHdO+1WTX/2uNPLr//Fx9tVkNsEBtFTEaQvVGTQvZtFSO7Z1QaM8Ko0MujWNzY/QYYkXlQTrYCUYLTzNlyhdWHqO8GKfRsfTEY1PtBxJA4mA9lQdUgsd21cdg1266o1ZXwE4Rp4YnMrChsWkxdwGTq5/fLXRNWLdIGloPRsU/XwTypMbuMLpsxGWH0eL4GozEWGcZZ1ZRgZA1tpU5HRwdHbx8uHy4u+tVutXOlmxXz7Wa33WxR+LoulSmJclFUoWAjUlSuXF+8AjEUJKRZ9yArpQgh0/JU1ciNLmTZvX10Uh3pbHmuMKK9Kt9oOJ8xppw441oBhfauf9dznpkh92TkOWjsVrK80tBe6GS8ny47y5uZjlSwkUw1glBGBoyiihmet+uHIQ/B8ZGw8XC39fpuaCJ/bfTjGhO4/tT1n7dnv1HS5tPI/ueP8nOP+zeCZf4KmOyvs/2tAbCu0Rn8HW71M7b8/F0Lp400yb3ZWu4bI2NHpKKS2wITwEDaJ+e6Hy2G3BuIHATlEJIdnOoerVLIGK2ogY2YnSP212iMjvydcRdAHvycjTkckWPnnThE1k5IwUpOXWA/iCAbJ9ueyO7UmPbjHxnctmyRQTc6t+bGFZhg7Jizjglz1rnKFbHsf2cCGFnK+svEznn41CeNgqRQZHXvsWEhU9AdcoBIWVcMIz54g7aNHLccLe1NaECZCAbs2bZjnXK0HVERCu469tmHX1mCKtuXwGDCxsQgpr04LTlmIuio8Gj73r1RdhPX2gujVsc+AsS++8Gmk6lEsahDjKlP0isSIMZkSpkqBEdE7EBZBYwMamqjpnemydnYFDrSZSmjigCRkqmJETh3/RHMOTLVuJ9MGZrt4fcBZ7YN3Hch3sytuSiIT1ceiMixw74KateIpI3Ku7c+vr8g+Tap8TXspoYsFcwsMEuSQAYE581yz7zZSGUjl3FcdoTRhZDBRrknkcjIs2f2IslEUjJDNlNzoSgB9DGmZGXp2PteUkoCcAjeDQWTlmUJktRTZjsyQ5NNJpP5YupdWK/as9Pzq03D6j1RkghCGQpm9H0zDC15TGd1WbLJIDKsN5vl4ujho9fm9Z3nn1z96C8//O53/uzsVCpfh2LC5DbrBp2U84kZxyzW4AvnSVXTEOMQ4TLLYV9To+yhozGmlEiSwgU4MyhzmNRBJfWxs4T/+r//H998fP+dd177xi9+9atfe+f+g7e69nK9erbZrKL0s+WsKItBUp9iCJoosmOBDTHCBjVXhLosQ1Wb8zQkROkhkdmbGntXVlVdFkaIMrCb+aLqu2a93h0dLyb1dBgGFxwzzi433/jGL/VdMrpoNm1LQ1k6H4KpypBoxPCd95RiHLJz6QAJGl0UMRi8LwgkSSEJYKiQkWMwqXM2n9bLRbmY1btdE7sPCWE2rZls6HpTrar65GB+uDg8PFxMpxMRSbFngBmzeuII3rm6ro/nB/emx844VJWYtk3X971zDkZNu63mi+XBgTnebrclWzAziV3ftdtqMal9KKelL8KyKsPL84vuvJXUM9m09B5IqpA49Cn2MUaDMZjHWc0xvIcmZpfd30XFRMYSZZ5mlU3EDEMCFYVzzMETaWbtb7d9M3RD7MlRWYYQCs/OeV/XVXC+bVpfln1Knzx/liTV07oqq/nBcts0r87P1RKXNLGJOnOOlTSabLrd+cVFzpZSiqfnL+bV/Pjg+J2333l0//6kmjgCmFar1XQyDc7DkIZh6PvYdH3THR4cTueqptvdJpEupouyqkJZmsOkrrvYq8mdOzPHXoT6NnZ9grAo1HQ2rX3J9++enF1YVfgkcnKnP3u5mU3K7bo9ffH04nLzw3c/gUPpUVU+lL6oaye9iJrTmPpd27L3XR/X60ZMi7Jmx0ktGQ1Jp9MpMzENXderUEyYTouyKDebXV4jUpI8YTqPfmjbVoqCp2a5uVtVnWdfZAqtxEHgtCzKsiiL0HtnzkUKjohSkqGPbdfGbjQ1p4kvqwAnPoAAVZBj5713jgkgY+ZN06xX2O2aTbsJRVVMfZj4BWZd14YqTBeTqKntd0YWkwyxNagPQVLW+GNPTAhQkcQMBw0pRhWZLSbF61U88q1sDu7O5s/roV8jaeqi84VjpyrZrs85Npgm0SRMrKTjestZfYdEhY1ARg6cp92sZgAdV6Qc2twUlgkAMeutZsNPLQS3uFd0vcTQ7dVmvxJnmSaMCZqqXsMUI82IAASwJ6/syVxKJpAoUU38Nm2Gi023GjYvG2hlniBAhcV0Mp2UQ2xOX75yVa0K5z2ZY2aEWJfes+u6uFk3zVUcVkgdlMjFghUsqVm3Tdce2/FiPvMLb41tN01GddQkl/uTJRaXY0JlFEW9Xfv1tlltrw4mF7/0D7764Y/P/E+eawya2HpWOCLhceEnzpWmDF6ojmk0cmj1Rb2Bt7C+G+jqM9DSHpO6FcPTDdZ0jV4BWdERsNsaC/nGEd06Tq6T7m2qbtb7W7lZ/lyO+LKqwwiM6o3SDPY52xd8r59BGfjMvwg0Yjj7gtl4MpqLxsSWNScyZQOOnYFsPycbkyucYWeFPnr93vGDyfOLj7ddo8Ld0B/frZbLumt7ExvSoBS9c3sJHSZixxIChzLEXpNKUnTarbpLK5saTlIbm+2isEffuLt8VJX3+96v2ws++7i9Oh2gzpFA1WLaXzdnFIyyVw6UMouEbx76sWoo4EjkjDVn4EbiAlFp5uBKLI/x4OHR4d35O99446tffzg/LGCbi+3zT05/tO1fVpPFZuMA/+yT3fNXF/P5cvVssAY6IBQcyqBqzFTOioQhCVHB5Sy4kjUMbiLl0nxt6oc+DrFPyWJUCUUZfNk2Q7QIgAuECQWmku3u8fzR/ZOjycINbv10/ZM/f/ejnzz/8P0X56dAC1chBKgn6WV5fCgxXg0XVTXxDqHEEPsuCUcubAKYimjsKSqcokC/xbsvn737w2eY46037p48nNx9PHv46OGb78yj4uJ8++KT1dnpGj2BgEgGl4RMLRBxFqfNsIY5aLbgGO0pR0CEQMSiSuoyG9WUJMHMEydjg1iY4/BhffzaAdfy5PTp7OFkkL6NUUiTNOtNW3CKrQ5t582326ibXtnqmZsfV6EkNQnsXMVd36y6i2JJ84fFUePWL6RNAAwJKekgKXdwYD9wMQp0ZHxTbw8MG5veRhDdHCyk5aPq/uvHh68dpJB0O7SbrSVazJaVn2y2GyanHr3GQWJZFnU91SSpjxwcegxuMIMTtmz1bkTX41yBTEmmvTutqtEIn5Eygdh4TINzskbOEZtZUjUY83WuNzqJjuWMrEGWD2Uq++a+PDmNC8OeO3XTWL1PvEkJBkdMYOKsVavXbFIaM6fRyDHPa+PzoHvL1P3FJvvsXPTzYffPbbdZUZ+BUMamyT2Adf3+28jX3+goP2v71zjtv3r72wFg5e0axvr/+0T+bdzMxvX+WgkLANm+GQ1mORklAygPpfGBNoJmfcaMlYzBHHP2IdnHDUTsSEGqAtqrHI1zWAavldjvjWBg+JQBAdtokpi9Ypk9c3DkyZgiYcioE3k4ZwGpp+upEYw8QalBAYdrAvl1TTQTvMwRMWcUCQRix947JmNSE2TEIUmG3J1m2XjJ3E6wEkNjomSkRPA0Fh4JMOg1MD5aQ1AGM4zhALru0xg5PqqqlmhspibnxqlNTW/G777kKCqse7QbN1GCCbKiVEbPrpmfhixhlvFC2NgLrpQ5tyBTFTNvZJo7vlUMLhtYsSPQaMRkmNSTXvuu6YZ2SIMgAgIeITRVMeeJzAV2yjqOvlxbGUN54Br35DGpMMvF8ywElgXyQWTsmZRYwcaDDvkjYLixQEIYPwi6cf0ZA2HOF5wAQ+Yu7euzRG585rGHOs3yGd7aAfbBNF/bIt28lsuwIHLEuZSjQ9TRItJUR0IZwRFpBnK99yAoa0pRVIMPdV2Zoe+7q4t1LmQqkSvCdDqvp8WmWVdFyWS7dpcE3jvyro0xisLgnHfOeeerqlKkbrcGkCXkIPDeheAl6fpqfX6+g1JVVRAkiVBkO4E49E27CaXzfjKdVEOPzVW3aS4f3/vSwfLebm3f+95P/+/v/Gi3selklnrptr05nkyXWltKoiKQHjFqGdgXYDNWdp4IYEbuqQE5DkRIsVcZsgwGiEQBFUehLENR1j6W0Xck9uOfvvjokxery91ktlwuD6qiiM16o1cqXIaaSxd22yKUQoB4sEtJkkWRtFpdLeYIvgZpsn6ckTzEBCJc+HpSl1VJjNXlucKYKPU0xK0aFvPlxeqSHBuw2+H4ZLm+2uzaXUpDUoTSB++GYSyeAZRzec8hxSbG7MbkmDhJAjj4AIOmAYasUsqOCarSmw3eTeeLej6rm6ZzXKiw92VKw9XVxaxaHh8cPn746PHD13zgzXr34tlTib3zeTYg7xhmwYe79+7NrS58UU7qtu/CZVlVcbk8ODvb7tr14uTk7v27bTesVpfWNcfz+XQy6Zqu79rV5SU79+r07OD42BXBscZu2zaXzk2KsjSFDikmDH0cIoYIRzJq8gLkiAJxdOwy7z0DCAmSm6nHVimQgwhAktB1Qn0CK5jYUTOsRSKc1WVVVNNQFmQmhpR0GPqXL595LqvKzs7Pm3Y3X8zeefudh48fAXj69ElVzYmxaXZd7A3ou67vh6SpnE0uV5eXF5cZln3+4lXhnq53u6jpS2++NalqDeGHP/jL1x49Ojk8LssyDUO73XWWCi6vbLXeblwRzlfn5bRaHB0wu37bXG43m2ZbT6uyCk/Pr6rppPBVEYLngigAlNv3VCXFYb26PE+DpljX1U/f/aGJvnx29d4HP2x3flqij+g7DCkVmooC7DBb4Pjo8OTe3cOjk7Zto2jTDSmltjfvvYjCOBR1WVeOzTnuB6h0ACaTqizL3XaXTM0wRCUgiRQUmOE9vA8+eO+C8wFJRvDQkaGPUYRiVcxCCM6lTEHqY+xa8XDe+7KsmGLfDxCURT2d1kbJOCn6JObYiMgFzzFPYlwUAwBmahIOCyaWYdgtDqbc6GQ+PTheJo2rDYnobtuum7btd85VXdua+qKcFaEI3hFJNmEoiCR2l5eXhzM6ufto9uhoezoUc7eN6zbCSadi9aQuqwl16FKnguAdBx5SN/SpKAvI2G+R525Vg0RnTETOsRKcOU0J+V2qzhzGfOMG7MhACGcjtZv1dlxcbuZ/ZKNzMI+1k9vx1JjC3Hpxj7CMzPKx64QdO++DIig4iRlEzRC8j/3w4vnO7ziEiURfcDUY4BECJelfXD5fbTGhqObhyJtHGEVSXBYjADv2RUFtM0grkqTgKhRhEGdtt3mxOVkeTg6XaRv7ZqcxwpDUAIgipegYHJDXwRBKpTBE7VPfobn/2mso2yYiuN7Ya3LJMbOwZ1UdazQjmJivQ05sNAtS43MY1nWWc01P+ALyW4YI93yHm0U4z8bXn7ebVVtVs8kLRo/mT+/vVi60r9SNNcLr+7Yv2d3AXiNmRtfFvf0NHcPYv/GWcSn7gucLubQ7yhsgR1YQI4ajUR4HBiM2X7s+KgYc3lnM75YfPP8wFGi2Q9ejqsq794+N2tl03sfdkMbv4ok8V0xEgcoy1BMPGuAlMl575+Hq8vJ0dVGXcufuncFig/bp6iPW+sGXlt+SNz549/TF5gqvgCgDSx50yMQr0eyVyOyMsFfipzGZz5eJFC6CkpEANrYjAGJAAghyiK/+yt3/4D/8zcdv3RPq2u6q16sPPvlLcrEdWpViu+7PzmQ2naaN9RtMJyQ7kBBgMSURUxLvWGMUJ4nEF6BaXEXmFZVY6JM3o9SnvhsGLhx5rifTupqYbY12CPALhBJOlQjVxB8czGd+2nb9B+998vS9y4uPBxngBBaQW+ZNTXu5c/dgvdtFScm2bd+nblAHeE9ae60ILg2D9C4mA7GbFaQILgmibvTpe69OX9np2UylvP/gwbd+6Rt9H7/z7T89O18jGQqAsiwuEEFFgVFPPCs7ORo9E8hUyIBcrh6Ntb3uq/5Ebhg6IwNbFvGIJSZH5fLevKPm9L3d0ZdOtk1vJl3Xd/3m1atY+J4UAWUo6vlisb5c9ds2pRRKMXXDMEBNpzJsh6ZuTg6Pq2M3WfldI7gCoLkJdIgClkRwbH7/dMtepxcgQHJ6k53BxxA8a1cBYjh6OD14PJGi/fDJExxY4q69QijC4Z2jIR5cXax3aYudIGkIgRxJL23XUo7FmTz5wE5gUBZoXiXUDN4gYHOkN2Z+uahuZp4YxrdhE6IRrRkRMMozHN1MdNfIUc6Px9mFx1RmnMhuuJeq+x7za2qCWVaKxFhlZwBGSCqj/5cBRqbjR3i/01xSyZqLhE9Nitjn+NeZ4F8Bhnzm9S982zWedXuH+Zfb7/8rwP2fe9x/A9uNkvTtk7i+UrcYJTcp9PV7/g2f6/X217yg/2/O8DN38fruXu/5C//7GWLep8tNP/MMr/f8s952Gxm9PtZtyfbrVz7/PTw8kGlVxOCMWKaUiBlkKglExFCzEYvZxxkwoNj/QoBHEQKFDGPpqIqZ+6C9IwZ7R3u2pkKMFB7siPLEoknyuBSDguAJzsG7hqyVvu3QWfa4CI5hcOTNoIqUsmWeqtsrcifAgT3AgIML4IIRmD0TEbMHNGlSKJyrJyUHFyVGiQlCI9RunMgSJAkA8lyEIgQfuOi3XbfutFcyX/oShC71iAnBV0VNIEc8xDikDgwu2AUnEE1xb94CMDvnQ9hXA6AikiQRyHlmx7n1UlSvvZDq+TRPaXp9/w2ZYmWwqJJ0GEn5Dlyw954cZUjfO5aYZDBNMIEnzm2SsY9mcCX5wpMjOBI1UTGoZ++9885Lnxy8RY1Nim1kc6SkfXTklExNAWJHRuqd91VhJkOMquqMdWeWTAVwcB7kkQ00fCBfOHZMjnzw0aTTAQKAPRwZwTDEId8Iyrq82YQvS6rZvvvRZbdHdiCXg1xRM0mIeytuI5CONRKi7B6YR4RjElWVkSOYmdaAL52RGZmSgsbauXPkgodjNUvZLH2PbOWVkA0KmcxmoqoimTmX8bmiKOq6ds61u916u0WvwRWiqn0CAx5wgGJ2d3H34YlaWm3Pp7PyanPliqKY1lUZcuIfAnmnIKnqYl5XbdddXKyY6fBw/vhLx82uYUy7xn384flH759xorIqisrfuTd/+GB5dv6sT5tq4uaLeVH69dW674bjw6N7J3f+6W/+9r/63//o//zdP3jxBBAiLS1lhBKcu1KQDZAzYCqwBGgGZMuqFpHsfYB8FQiA7i0FFEzELj8jYO+YGWTQZOlkuUgytG3brwcw/t6vvf33v/nO64/ngHz48Udw0RzuPb7Xp+69D9//6NnzalqwcwJM6/rj9y8Wc7z26KuLxXHb2B/8wR+vLpMJw3zsEyVa3jkuipAkVtNCLV6uXqranZPq6Hj22msPCTR08fmzly9enM3n8zfffMcEH33w8Yfvny8PCqRQlmXsI4ELH8qyHOKwubpquoEJoWBm57hwLqQh7nbNopr70l1drBNkWhevv3H/0RvLxSEfHtdAarutqgRfdJ1O6kVZTIoisLfN+mq33iyms3v37qlq6iNg00k9ndQwI4VnjqnfbZt+175+8HBSTibz6a5rn52+qJbze48e7vr2T/78z977+IOirkNdShzidlezPzw4nE+nZVmWRVFO6o8+fpJUklooSwT39NmzT56diuDO3TvT2ezly9WL5y/FClUeBts0PSNUk5mB26tN4QqoxJRMBMQuzxtjmTA/DHkhY2KDY6IsmC051Qmz4AuXNBHTyfHh8cFR7b1jqqtSJW03mycfPL9cNwPwxp3wa//Ob3z5nXdWFxff//6f331wzweuq7osSyKKMXZ9f7VarVarIQ6maNu2bZvUqWd/MF/cPb7z9ptvfeOrv/DOm28/+fDDOpQk2jddGoYqFIvpYj5biAh7LurSVwFMEXK1vXry4pPTVy9fnr/abLeKVM5DksQUqnISQhUHbdt26PtqUh0fL1Nq54vZxx8/+ZM/+eO6wsHhw9nscL48OX11+Uff+dHleggBcHAO1ZTu3rs/nRdEkYlTkvVmw84NvazXWxc8wa1WfewxPXD37x5+5St31+uVJO3a9PL0sm3FMQCq61kIfrdr+r6f1FU1CWax6ztf4OBwPp/PTenJs6eMMgQup76swS4mS4OZ46IKU6Ty/Gz78tnVbg1E1JMwX8yhGIaBnJsfnnRtN8S2S02n3WzGk4WfLYrl8YR8Ii/sre37oQ9EdR1mzvH56fnVejWZzJ6+3AZGUWNxOJ/OZ6IS4xCHtFm3Q5I7JxVBgyMiNUQdEAWTCY4OppOZ5+XwzpffKnz9wU8+efXs9EuPf+X+4Rt//ns//cNv/4WtUWgtA1ehFpGYIoGnk0kZQt/12/Wma1sARAjOEdHQJxDCvCDmvuvYubIq05CSJBCKogghxCEmSWVZDrsIQE1NYGpQzWyh3NjOcGPmAFFIyi9y9jd2w5D2a3fGI7IaAdNY2lcbudNGY2fKWIAHEU3mVJNxa0VfLBAmkITDybRQ9+r97XCm6QJBKlfPunZdPYwnX7Z/9h//5t2vzF7unv+Xv/NdML7+5TeWJ9NXr16KDLN5Oal8FSY+VL/3uz8oEnmpSswo+t1l36wHErME7TuUUk78w3sPjw+OurZ9+vTpZrv1ZTDGkKJNCAR4u3P/6OGbx7OF7nbPnW++9pWH3/z61+7WDzcv6ff+53f/p3/xbbS4d/Sly9OLNKxdVUpMCviysL3yOY2IEKCWhfI+H6B6x857g8Uh2mcFsm5+Osf7aPJmux0hZ6CJ91jVdZhtsIxUfuF2OzH59A5tLK2CPv36uLwT0V59FACY+NOnBgDj19n3ON4+4s17YBxGeWgVg2TtVGLm8ZliAoGhWZ41RbAVJJUZi0YNfTii2Wv6q//4q1/+1Ucvtx+dbU7fff9MDaGg+byezEpD7IcuaWpbmOGttx6qUNO0pnG5nBwdz1JqFH1Z82Tq2mnGNQAAIABJREFUX56+8CE4DkSeKfiqLFG55CE2tH1q47ScH83vTMPBsMFHP3r57veefPTT8+aKGX7X9qGsmDn1Qxo65UChIDOTEVVm5xwzuIVLlEUWyLnKNW74T/+z/yhMcXBSzJcOvt9sz7rYmsp2dzVfVD/6yQ+M8Pj146Ki3S5uVtQ2k6c/jd///ivswBdOoxZ1OZnX5KEUXUW+JnFxsLaaF8vjZVG76NuITmEuOPLBYFFSCNXx0bElOn3x8tXLqztHh+JtuiwWi7r2/tGd+/eWJ3HVf/CDD9/93k/f/6OIhHmYS+faXWvUA4ADF1ROqqLyHFggUeMgUUyRfatacl0hCUgMZQhnQiG8MCt5NZfUJLviIAH38M9++9erKS2W1XRaP33y9F/9H3+OodicDrByUk83pwMimQrlODcJVIkpMFdV9f9w927NkiTJeZhf4pKZdTuXvs91d2d3sbsACQokJJFmepD4QBkND9SbHvQD9Av0E/Q39DskM5rMRMpAowmEAQKBBYa72zM9M305fW5VlZeIcHc9RFb1me7e2X2gIAphM2fO1KnKzIrM8HD//PPPCXCaJjUxJEVmCCJQspVcQDIv3ebxugy7wV9mhn/23/3jgW4uy6svL16e3etW5+ur3fXVbkSGpvWO49hrGc3UQXHbV/t7Z+emedtfKMGHH54TKqLut9uUNDhsWte65sStbU8vnu1efrHbf5VB4+nm3tXXL0CtKgFLEcfB+VCKlJwRZ56TD54dFs1FRlDABtbrOLrpf/qf/8cXN1//8tkXz15/cZt3PUzCqASrxXqzPEEJ++0oowFiLmXY7vthkJwJnAc33aZVXFGm/eU+XyfPLvo2DUmyWgEuiEYgWNFU1FomompFtUYyYKKCtSk6YS1cqRpdlRZhlYJgcMBiK3PCpDYuxDcEKAOUmizBikZKMVNBREd+DsNF1YqBzCouNWqd1R0BDnKNNUs4W5Q3SFo9EQAg3smo2FxU+m3TdDCPdw1glcD+9Sbxu1ARNxcTf+tt74Itdylax5/v4kjHz/7G834HnvObr/ndv731yrs43989DhQeBhweC0Q8tJP7FloE75uft6A9OMCWv3H23zr1Wyd69531aFVD+i3I7L2fQrAq6T0TKN9+G9ohN0UEZm/KtiqVFYkOpEcAQiVgPC4vVDMEFTDUgkim88IGq+ByQQEFQkNDVFVAwlpvaOTYV6OjxbBUo2OI4JCYWLICAwMZaFVTMiSwuYnsrEpEQAzGAFxLik1EERFQRFVUiiqpDpMFC8iIRpWohUoHhcHDEq18IUDLRUXeLFyDiv4rwoFRrWKGZo4Y5qykEQE5JzWFVaWVDmyg422dKaIzO+z4J0OseZdZdlyPJkmNgAQVcOaaK8icLrY7GcuaEquZAwI0kKpGYQAOwcxopmaZooFWkUJidOwC+4SgScsokqR6XSgACrVrRj1Qle+fyWDIRGJgYIQoigeDX+15pd8yCJhaQSUrlk3EFASYEAgI6ZBiNYBacVgTlIhU9eVxTqSqztgRUS0ARTUAEzU4yFEdLdNhh5l9TDLjmsvAar4OzMN6FjSrPYgJEahqCc9nr7MJNSGCWNt3AoDNbXoR56SkFDEwEEUB57wU8OCzpUph07n/SA2CBA3SOBXNqsrskSjnNFyXMXpCcQERHCKIZECLjgHMeQbTXLIWzhNIGcvkYuDHD08JQwguRj45bc1yiOxCQwxd06aUNNtJd+/jx58+vP/k3/yrP//iF6/SrgEdATwIgUntDzUv9UOxP4IZlsODDwamMh7v1NwlmQ4zjoeHzwpoLe5U04pTKyje3PSrVbte+Z1th3569c31X4cvQB7ef3DywZNPn1981U/7p798RgGJ+MMPnyDB9XabpxEAH9wPpjZN/ThFFb9adCUNaUIwh0DmIQTPzIqScy5lQsDgLOfy8uLiR599dvH6Ynuzyzl1XWxiRJDTeyfXV93J+eXQp0BQinkfCMnExnGYxpRTqaClcxxjdBwIcJemJrjFJoJp6KBBaBpYreNq2XQttE0kZqS02+52+62pt6gIJiVXXbNuEZHs5uYqpbRsl7FxRFDl6qTk/TikNJlIbCKHaEipyJjSOE1lh8v9voA5x8uuw+Cd42LONW3rfOP9DDPNeK6BgUqZkjnwq9Xqg8ew3e+nqc8pq0m7aIZRNAuReUcimsuoCqBJCe8ILdtsnHReJVjljQCZGcDU1EAZGIjMmZQiWU1ruS1ueW+DMoBjapsIAGjqnVtE4AFur/Kr568/ePTByeb0J7/zu7f7K+ccEamZlDIMQ98Pu76fUr7ZbXfbHRJsVifrddTJbvv9MIxmcLrenJ2dNV037PbDdmdFuxDbZRdjdM61bUuOikmekhFmK9M05ZTSNPX7/fXlZT/uP/nRRylnyanvJ+8jU0SE1Wa1OVkvl+3N7TTlAUkXC2dWUh7Ulin3Usb1Bi934D24iM6Tb7xqLgWjJwRkdoQuJ93v0nYHMZS2427hpZXT05OTk41aCZ7NOQBqWjeOQoyIvN9viSH4sF4vmibG6ACj81BkKjlP0+Q4iFQis8KoAMhelETRmAQJQxvWmy4NJYRJCnShXXRtTiKaRGW33Q3jkDWh0+AIAHPOYpFd8G1Um5KOUyrjOCFKcAjqyQk7UMubBSBB03bLxTLGZkpTGnOekmdkBMmiWiiE2DgizphkUhUYk2ivq4W9fvW6CQtVQebb3eW6O41dSAgPHixff7nz0gmUNE41XTMKFOYipaKQqlYFBAHBGA4+2PyLVXhVDRBUdBYitCrraUdrfTBjb4ZZFW/CmpufM0dHwas7IMvxhaMcENrbmMwdBwFNBIXQETkmmvVfpKAaq5AWBQPHHkAhABQ8PVtBKP20N+DFAvY97G5GjggATeu9P9B+C3gABrRsRYolLKNqVhIERRALrplux13YffDg8eNHj7qu++bFNy+vnycB8ABiMEHzIG7Olqv1slvYMF6m0k9FxeTLF08/OPv+ww9XcA/cS7i8eUGBPUc1bbqYBXJO7BzRUcAYDt6G0UF/8s401BVvcPfluxP1ZrbxW7N8+MCbG3H4pXpQ+PYxvmu863IfCBZHqsTbl3f3ETEzBcX3XB6917V+zwXcjfoAAec5UQSqjUVr9YMZkQPDNO671bppmr1Oue9/5/d/z6355fb5Tb65zZfNCnIBRBPsx5K0aBJldqtV08Q2T2G77S9f7xBTToUZuiWFximOV7e3ypC1pIJayABoB8Fp5zUwQEDTqbdRh9tdXpI17SP3/fDg8Q8fWmmasP63f/Kni8USiXa73YuLcXidTbI5AAEoAAbaAi66+ydd10LbtbFrFuvFyem627Sl2Rqnm2TTHsGnJPucLQ/Q93nM0+n5usjtYoGhcY7YMqfB6yCwB0jcnm3yOBrIaIOWpF7ZwCmQA7eEk4ddtw7FUs7TKJMpOHLRMQCB8dXrm2lXHDs0XHcNI4zDmBysH95fL1dpn37+5ecXX17dPt+l3jcbGy9hez0ALP3qXt69guBc9D4weSwqmoqCaIVS6y2s5oASESgTGBE5UGYkU0YgLGoCBFTMU+iMRtvufvGXz1Zn+NH3zof+mr3+/X/wab/Tp/7Vi4vhdkyeNspQC0CEsO1aZpKUSkq3+xuTwoxt2xpxFhynQZIAEEZHPnBjl9sXYNPJR8uTD1bd/eU47fvrYXHiuWn7Ufb7AgrMmFPOkhFCt1gRxDLBlgcRlaSSwHloadU2HiBDhrYpq/UCEXa77avda19i3MTzjzaIu92r8Wr7FTQIZuyIiUuykgUwmQNkZCZEzkWyZTMrlgABGjh/0v3kx7/z4fcfjlOfSuaA5w/OTv3mtuz7MvXjMI7bMuVAUTNK1iYskVxxLhAnUFMVK1Z0gokLV5pFVtE8WLVNhOAdClYNNnyz/tCM0JSQAUHJ6ou1mkMRjA8hIB5USwCODentoOd7CEgAYG5lCAZWlQYN1ARq5eIBmJ/Fq46bzEG9pcZxlWt3xx7doa8dL+E77MtvS4T6LgbWr0OLfhuw4j/B8R4Aq44jiKOH6Ppv98L+Vkf9sm8BlkQ0u9qqpRQRees5eC/OBe+jp9l30vDuQmBH+OzuZ+vFHBHWu+Do8SPv/14z90qxNjQCM60tjI5nmJkVBELHzd4AEQTMESnNnTyRiYgPixEAZ+jBTGvtl6ERVujrANMoVD29ufmo1SkCAPTkQSGXoqlgropUQIhMjsmJ9IA0F8WBGjAAABIBARlQFW5HcggOkFHJdO5bYiaq1QVUUDQRUzVmAkQ8SFcBkNlhGrFi4YaIqWTRqipey7gVDJhACWt/PS2iaoDATEagVlQKA7GvRDd944l9+yYivqlHOEAGUFsF0lF6X00qhKVKSjPERbOMwpFSWnOBYGZoCuqo9raZrawpCCgiAQMiGmOpTS4MK/TviJnJOee9n/ZTnkrpsyZjI9Iq+XVQNDw8QogEtfwUEIgRjIAyFeSZ13cQeACjGkQYWKV7oR5YZpXNdNC2qiipzVWPCsBgdAdQrAiVmoLV7i1zSXslqd3RkZ3jb4O5blXrgZWoFsDRIbGBiCRQ5sNXGu9hsRkgKlaJxyP76nidCEBYGzvqzFcq2YqBagaVDNErMaMhiM1FKwZgCDI/YKVInlKWnKUaklLEkkopGRA6Q+dqrzERBUQI0bUllpIRcXc77reTFYeAbRPi/ca7AAht45bLeHF5ZVAccxP9qltc7MeA8dH5h/dOP7IU/7f/9V/2V+XmcgQh7xw4V7KY5YpW1K0daWYY4BuPHxBB84xtzdJzCFThO7TjPT1EMlK3XlEAMZDcLM/SKIRGSJ7p5fPL7eXV9vL6Rz/5+Ac//HSxOM8KX718GlrnGj7ZrIrJdruXlNPQn56sbm92Y7+NLviwOjtZmXK/LymZmeWkRXORXLSI5jRN7CF2DaK8vILYxJzzvt/nkudWpZZXJ83jD+5xwD/50y/IUh5T5NoHgMxsmqaSlWheujH49XLpXWCE/X5LOGXJIcr5ZhUbd37WrjcxthY8I6ljLCVtb28ddV1cZnZSimh2HhnROSol5Typ9yYIpo7JMQ859fvdOIxNCE27QGZBRNUsmtXS0N9sb32M0ftl24D33XLhmG3KnmgRm1nJBUBEfQgkImhiZgibzWq5Xl7dbF+9ej2OY4ytWZfyjh1j6zhqmnKRAgbiUa32+aniSog0WyOou9gs6YeKBRBE1ODQfcMACTWrTgYCgLYt/cQTaQm+ys1bEyMqePRDzlOBaT9O+xGL7q/3Ly5e+hhjG0MIADaM0zAN230/5Rxie69ZjdMwppwnJSAF66f+2ddfeXavL17/0T/7b1+nPBKhw9A2bdt5HxBnZmvJJZdUTIuJSonOd23bhugIRHPldYoVlWzIi27RNKHtmqZrFWzX79XyVIb1ZjUOg/euW0QXsF34Tz55rPbcB18lYpExBs+AkkspIgpjn4tomlSl8heJCZiAAVWk5MLOvI8hRpHi3IBAJcsehxjj2dkZEw7jkEv2gbquVXPOkXOuiU0TOhEpJeXesmBsjCP6lh1zbKj1XkUXS28maVJmYGdgEAKKIjIn5lKjaoMiYgVqvSYHJ1A7cJDzRg5Ch8FxLm6cMI1TE7GIWZE8TKCQi+QhYVGPWAAkiahlEi61ZR6KwSTgkinJCYTUJ1ZXqcdj3nPABx+sP3occQyiwKol59TnqkIyTgPMRVjqnBcQsXKozkN0s7BJTaCoSq3pBgTVIlKZ4Cpz2snsuMset5LjpnPYLiqz9rg5zxmjO5trzVLALERiR62XGcrAN7lyRLSSQD0TsvNYTbiACBZByaAFwICZwCM34Fr68NPHi3W43d/elmm5hJQgF00i5DAEQ9SSFUoCdpZBMpSxlJQsaRoyjAnMgREUIEHIsLvdXbx4yQCrVbdYf/pkfPDNi+e341bBbGEPP3pw/+GJj9iP/ZgyIEyi23FI4/bj9qMnP+z+8A82f/Gvd/vLfes7yaVocY4AASwTOUCcN6Q32zeQ4XGnAAAirA4U6Nz2WeBu4eZhngCq2/AtT/XoYhxexTngO0pTzDcO32RNvj1szqm8m+q/m9l9r+/9FnoF7/PbAedOy3ffg1XG4c5j9utcezv235nzvmrIaliJ52Ajxg4jac6wgo9+9EhX/U1+PuDkVjHqEAyY0HuHyGnKjgKh875jt3j58nYc8jDwMMKYBvLwMCxD50Rhu0ulinyYSQFTRHCZQENpG3YezUPRNEBK0gdaxnsn987WVjqUzlH8w7PPvGcDyFNJ40eamNHHEBEZAaVIyilJUprIm/cOGXx03bJtl/FmeD3BsB8nFkXOY+rTnvtrmqYhl5sf//S+pNuCyQOyQ2Y0NUkG0G6604QjmIoVixZa6jbBNQQs5lK3bk4eLtDhcDuNeap0Sa4ghIJMWia77reeYL3YdI2/d7q5TyftYnESTzjj5Tfbb54+f/n0crgxykTYLE8WvOokcwHKsqTgXQzs2UBynqyW56HaXNNXoyjQKsiiUomdhEZmtaTAFMAYADF51AaYbEq/+vlX7dKG3e7Rxyebs9XZ/ZP1GpumO3+5u3i2fbkfYtMweTMS1ZSTA+LA3gU0ztNUJGXN7JkcMZpSMSlGKA5cWHUb98kPPj773gkt7XK62kuvTpyPWXV30/dDaTq36iIylCII3juvhTUrWNn3e5iKJGDAvFcvqqYNLdGbiWVNilREc5Em6vrhYrFclifKhS6/ed3vt7tJUWp5BhSTGdZ0yOTZKRMnTdDCjz797Ic//t6DD8/ahSNvn3/+q+10s5e9X/Jys8bscNgiwLifhtyjM8hYJhkTmlIaxjIVKIpVPI7QVM3IB8cd5Uk0m9XCvTkGxtmVreHpwTUVtDB3isfZhlTGwKHo9eDlV6VhmykfFYNShVlSAWaLXw3ArINYm4kcNHaA5gR7xamrUvH8qfqBw7ZyQLjmIGRmX7zHsN1B4+bPvGWcvgO6Of5y1zC+l5Z1x4i9jTncTQm8d+A7tvfXHfD/veHee5pDbGe1HP6oC/53eFTs6S4edES1vuMOVQDr7ivvgly/8dTHx+vuc3Z3MHM90d2N9oidiUjlZL3/4HXpMCBCrQ5RUyQ8yKFX+U0EqwSLowC4gQEzE4CAIQEyMbORGgjMLHs7CkGYKRpVQ3EwIYAGdITjqnKVAiI6ZIcsppJVc8GCpACIhEgEiCoGIFK116toOhI5DrWdtoEAGjGQI2AwNuS5D4SCSW38wIgMTOS8Z3YVycPZgB3cLzxU788N/2xugTTTedRACZGsNgcxK6JFRJSpssLRdIZV0DMxgYGaHu6gHbzdN7d43grtSHvBylrXA5/VZnEyqGlYUwMC9g7tANfPpKJ6UJ1dPCLyQAiKKrVDJAEiI6GSzmAQKAIwATtiZmQkQMm5ZNHJoEBF0MxMoTYpxIPLiFWuypAMzAgBGICrcBUiIAM6qsJm7IAdA5sBAwITFRWrmtg642JqAEp1wklnrl+dq0rPOsi118ADtRaDmDGgoTFWRPbgE1YH+fDvkZlms9ZGfbpr5oW0cvRmXBdA6r2gemF3ghysKbf5p9XTVc0xUCAFBS310lWLADE6MgJBMwUkOFTSAhgQlCHrykxhHPN+txsHQwfsmBDURAqoqgoQ176I5Dy3rY6jmcHV660IBMfOE7vaX1IQoOu8jwqaAteHCMuYNcG6u3e6fjTe4t/81edf/ftdnRYXgicvpshgOpdoINXIAw+Q6IwcVhmAIjVldac+v67j4wxWJhcB1mwUAKFVBWbv3e66F8uLtmkb2u33tzv7+fB8P4yvr3e/9/u/s1qdn+apH6/HIant2INncoxDP5ytImrKWXLsgm9O1l0ppqWfxrGUUrKO/U4FBE2gaMkueO8reTurGbNDxCnlNIkh7vqbnM7vPzo5u3/y+S++0AF2e0gwMsKya4LzypRRRMBHMBE07ZqwWC5K3o+jjuNgJosOPvx4E5t4ehacV9EyDIVcKSUjmnMMYiJ5GPrdbjeNgwvUOD7ZrJeLpWPKkmSfg3dmishmMo1j3/eOGalyLFGZOfjYNkMe0zSRc0yESAywbNvVcsmGjtiTzzmNw5jzlKZp0XUKEKSMJRXTEIJvY1i0Lvj9fkCi/X5MJYsCmDPMqCgl12C/mvFD2F7tNiKCiYHVUtkKBhgykkNEMjURUQFHTqQiYAAIMFmBwjXqB1BVT0bAWBAEzjbNk/tP7p/ev7m+evbFl4mzIYYQPQcffWiWJ2CPHnwwTGOInthfvH751bOvNZVluwjspn5I4/j8xTevX3/9L/7oj07OzjbrtRUhA3TOELLktEtVMKRIHsqkoGC2XC05OHbctPG0v22aloLPsUgBIhdi8CEY2G6/TXm4vr1GLIh2ev+83+9jaNdnazAnBqvNRkFFbZxSKkoMXdN4z30/9Lv9MKb9PrFzjqhrmJklWy5FTXrqifP9B6fEGCMjeqKT5WIFQOOY9rveB39+flpy7oddP9x22J2eLZ3rRHNdi6enZ30/bLfbcUy5GBJED+wwBI7ReQfOKXtDKmolJQuBEYk9OKQhF2QkxSIiRX3HXRfZ0zQmtSSUDUQUKFBsoF1wFwNim8Y+p2m5aLa3U7+fprGEEA1JpHhmU9UMVGvoipUsCCQAWQENnAgU02wOnCNnouMIm4UQ6/nj1Wefff/P/viXoGAgOSkJkqkBFCmGgIxzH2EjrY3IEYERmIDADGatw9r4GGDeNKFWj+MhcXgAQ+o/d7Icb/ZfPCqVHHLrd4jndzbrWULlwDk9QFzz2467CooUKEDmCJxJUXWmIpmS4KFXrANCxSwuLe6Hhx/eb1bNl988e7nbIYd2Re16GYPPZVKYchIorIDowpTBJ82jaiJLqlOBLAZzLW8es3NOiz795bMXz18++fThow/uP/zg/OTx4mp3vZtuJ03n9xdt53b765evX2bZnZ5GVby4vHxyf/P88suTx/f/8J/87tOf//F+b3kYVYSYpmk0AHKkUMAIqTZmqeFcdeaODWuq/gjV5JyZminoQZf6HW90diaOLvHhP9/+81t34T1vfOe4b3Tcj29++7O/xXg/znXgur8FjdVN825AaHAHt6v75CwDVMkgNVFqajPjHj1BgGQ7HA268rv/+SeZe45FRZRttd5MaQgxxBCZvIjBniWTqUtF+2H/7KvXnqKPrELDoNvdsNg1PjgxHAccBvMOHFXNeEKz0co05GniEIEInPPgSFSKTRn2zCq6nSaden3wwZmUSUUD8kmITdsx1w4D7HwQke3N7upyysLErFrG1F+P+7If9SI/fHQ+5V5swqwK0ve7ccdpzyWVMdvPumV02ZC3w5QnHcaYixPO0Cp2MLy+AjJwQAtozuPpw0Voqeg0ibZL9ksoJRebzIwRvPdtWDgOY0qpL21oSsp51JtpH0NZPHz05NHHq8Xp86+ev3j+8ubVdn+ZrXfWyzCqN1iuFovFaUp6c72L1NZ7JVoUjMmBkUkpOUtRUAcASAhaZlVfBJgr1rDWSVQYo1YJkKqUkSKQ8+NVGbe2768AQp7It46Yzh+vlqcxdJCyjVvNu4IFzCl7b6JTGqP3IUZwIEMZJYEkc0wBgRSKARl4a+4NqyfLRz89jafhcnj9+dO/adbEgQAwT3kYRhMgIwaOkanlaZKUc8maBQE1jTvIAIyBupuXt7dmCuXkbNVtYtY8FhNDQZtwB6a+bVarZfMkNi4sH8u079IgqYfd7bTfFchq4yQF2GPTNE23WCwXq8WSA63OF6cfbuLa3eyvX33z8umXXw5ldAu/vN+oYwhcJgscN4sNCGKhlKoa/6AZJCfLNQ4CQHVMpEhEFBgJEXO2bFmqq6qmc9On2hITjr2kqoabwSGNPjeMQoSaaK9gPCDQTLyofVhRreq+3q3hq8u6himzu1zfX6NIA8MqtjEr4hkCzdhWDWNQD+KJ8yFq4HOoPbo7dDY9eDyD4bcQ8/8o411z924C4Neh/+8e5Le3tP9xx68FsOAOgvMddW1/l8YRwzqO2rHTKppwh/d0/OWt2Tu+p6Javw0GeYQ53z3+3XEXCzu+4a2uAb9uIBmg2axGJ7Pa6YFOXxcnARwEI+paA0BgYCElJEADwoOTqHMoe4SZZ/ihVnMDEILKfDSdFyvivEyRvMOABlBUc4FitcIL5zysHgEcm3v+mKExkWOPXHXZiqHAAc5WM6t1dQdh6QorIoJzzodAzFLDcZjRiRqHH1UpK19doBABktkcr1caKJqBiYoCEmqRYymzKRkpApiITIau0Xfug1ntkKGqc9uMqtEBcJASetdjq/iAIRqqGJiBqxMxF00j8gG4qQ01DJnmThdsmOcyIOJqnvPx8AzgfXDsmBgVxGQYMuaD86VgAnI4T233azSHtQCgh/5DhqjHnLgpOgKuUo5FDgHxwfWz2de32e8TNZuJvrOuIYPJnHFFQ8CaRpmfNDh8SUWblfKJal3nnPbEo4YFEsD8kMPRl7UZfDOrZaxKVVyxHlsPq0PtmGklOChrAhzxGqzzWXc5BMSZHwc0I8E1YwKAoFDhTbGqMolApkUAKgANuSTNQIzes2NSBSIFgyrKj2hSSohch4q9+OZ60S2g5VJqaWwmguhdbJYwuRAIEXPKBjDs9ifL03vnH7Vh/cUvL/78T/4DCKCPzgVHqCJSkpkwu/lbG0FFLuqcmcJcLoyoCKLzLDOCHmaWgIigNqkCNFViQwaqc0wIjArh9uKKHK8WKyacppEQ4orU4BdfXv/Ns+vFZvHgyfnjxx++eIkvXn1xdX2xWDZNF0+Wy/2wlSkRmGIBzSLjctWVDMMu3WjJqWiG7BIYCiIH9t6RUxHxntZLEDXvQ9M0u+2wH4Q4Xd++vLzcfPDh4/PN6ePHy9vLPKaJBBxD18bgGwZMUxmLBQeAWsqU86jqiQWxFIFuCScbePBw4xy9KbZpAAAgAElEQVQQT2nKRdMwKjtF0hDDCbNkz86lKfX9fhh3ti+eAEy6tvXeD2kaUlouFjlPDABmIqWG2aIw5uScR3MuhsVmzaMPMXhmJipTmkZZdF3jfOxWMcRKWkEb81QmmdrlwjmO1Lo07cehmDqDpmnO7p93y3GaMjHnVFLRUmrmQnLBlA3ort4eGJiYktXO12izjHvtjWfkwfvA5EytlJJz0aKH0A0BjMyBiYkCEjkiAG8OzALHk85O1qvNch3Il7Fcvn7xe//oH6KntmnbrvU+qBl5bmIcplFEs8hiufjk4+9N+z6N4+7m9gqUCU5Wm5P15uL66my9OVs/ANH9djv2Q1ZxAv3QqxaOXqzsp15MwFFsms3J2kdeLJs+9xe7a2+WveQsOcu+3+/225TGIjnlvpTBeei6pm2jobbNIkafkyJaiG61WgzDlFJiUGYfGxdDZ8ZX17tpnMYBQlDnmQysqJiJCgIgmlpuWo8ViTQNgR0HJu66lhByyaVMBuo8NU1smtC2DaCM26EfRsJhtb5fsjgOiEkVVEDVSikxaCVDGJQQoO2cimgWgwxGZgkwXLx6TUwGYqrgoGu7B/fvLU+aqQxZ9qoZAM1QJadSphKa1i+XQc+XaNaELo029GNOApIQHYBRy4aIlh04QzArRIG8R8uGUgRyKexh6iftGiuSU84FSslX168ena7uPzzv+5+DAICSOUREMUA1mE2lipoaMDJ5qZkUBqjQOBjxocPyIXNeN1NiRCIpSrNbcxe3ejuBNAPvx4f+wJemSjP/1sZteMDCCKFUIIJmXOawJdB8Z7VYQStY0IRRIag5KKRiwJ6YBUVKBoJPfnhveRoLltt++/ryeiro46JZLENDkG5FxzIVpy0zoAEpmAIZqCgIggioIRhXsnExckSMqvmmz/jVl7f96+//8OPf/8O/1266r55/+cXzLw11nG6url+9vt51LRD7fipfv/j6pz/5+Jc///xHZ+cff3L/ez9evvjVTSnSxOA897vJVDk4FZmDvTmOBADDit0ceMaHaSA100MaFeEwme+4sbMnMSdM3tyU49wfKL3fuhHvff3uEe8yBe46w98dg80u55s3H+7st8e7WNg7aea6hWr9Skfojuo84Exgnh1tM2BWFbLili5rAgcPP+p+9gefvdg/a5Y8QB4xQ1GMEBofggfjosUIiMmQp6nc3o7DCJlyA9J22i0ohEW/01J6gzROdYad+WCKOaecBs0quWwdOY9Ni82iWSwCgAoklC3iVtUGGfZ5PIk/GXNJORUx25tegKhqMUAKIToOwzDe3NykjM6FEBGdks+8gLbxA+6SDarC5BQwC4+SJ83gwEcoEDCe7oZhvTppO4cmuVi3uQWeroev/XmgSOwsNrg8a7rzgE7SkKxkcVhsEig+amsOMTah9b4pBUpKaSiI2jWRnJY0LCKcnWxWfjm9yE//3ddff/UNZdJsNjnO7MTMcLe/FRB2vlkZetECIkVmvo8jw6JGBXEiK0yIRKg1cf7m6TEGBVQwJiMwIEU1QhCQUUfDoISeG5N9+fIXt9t9+eh7D1zMK6+LBh/R4ur1DTXjyBkGAIWsGcxAbZhSlgSKimweQ2sYJRewCcABdAAdPPyswyXwOmsrStPlVJYDLD0H9swuhIUUySnfXO9WFto2pJT6Xs065xqM3iS1selC58Bdv7zQSSqvlvn+yaNTl4dXl69ut2PJUOIU23HVtt2S111cnz/qmq7xy35bfvH5N3/6Z3/VX6XYQYOw2Zw8efzxw0eP791/8NHHH4GHZ1//8vNf/PU3f/rlVPoQwvXl1E+pW9lkejuOH/3wA5YADKs2OuDci/WgYOyDOWQksilnEa3de7BIMUVX/VFCcADhgPQUrRJRaKCKRFiTHAY1z1FMwUAVq++KxKCHrCwSHpsAggKIGdVmBFbXcK0prK1x58ZOFdmak9OGhkhzyAZmNTFvUAVhKzcLq5N0LG+aIXA8ZI/tW6btW1sUwIygw5umi7/leMvo3UWafiOx5rsTAHePfPz9fQLcfxskrPeXEB6/4W8PxPz/d7xFsEJEntszQSnlCC29y6566zhHnOtuUeHx4FVc7a3zHqfXDuPdw9a/1srBu7mmOQOIv4HnhQxAZliLBgyrmA/WV3BeZXXnrVVEM3eqLvr6fWxuX0XFyNB0VvxFJUQAFhUiIGYiqm3ukLDkUjkoCEZW24UBEXsOjL5kzSlDLpWEPgMyaqKmIPO3I6K5Qm3W8ibiyvuYQUVRIwUPBlSrDJWAD55lBdZmblqFwefWEGigRGiIxQwMSkXoBaKPmjSjQq0fRKsonxUQUIBsaoSoaqKGRdABOVCFMmhYqNYefIDMd1e1ieixehrmBo4zu0FBjwy+6ghWO0XIqFQ1ZOubTZUdIxsxHdLIB0Cf0CEjuKr5qKoAhEzluOdWOgeR98GzMwXJpZQMezAEqrJQxYoIMiDjocKUERGZ7EDcswpzzew9QgJDNELkN+kLLTqjSAYCig6t1rAizfWSSKUUYztgQ8BERnN/j/pQz7lvPEJNAIAGwLUhChwn8PC3wyvHtag6yzKa1RY7XPludV3aG393hkFhtuzfdpPnCwRCsrlDjKmozi08DVSZHBKjEQF5dkULWFXfR7VcLw6dJ3YI1jVuuVwM+UbFpiHzIiDUjvLgvWcHBqUc/rfe86ubLWNNzu3GZITgPJxuYmh0TLBerXLOu90utC2I/finP4nu7PmX27/8888vX+4A20CRiU1F8gQgNeaqE0QGUInygGjMNaIzqNxFKBmYsKa0aFZHKqjsgAmRXE0xmxVQrcZszjyhlX0Ki3ZOPRf1HIgQySQJ9PJ//vG//enPPvudn/5gszkdptvx1W3JBS12TRM8YCmLtskZEIrmabM5d9yC+X4/9uNuynM/ypxTbJfLVZdyn1NeLBbn9zfr1Xro+zGNpyqAN6plGPT11eVyE0IITx4/PtvIenG9vR4km3OOCJ13MTqVjATBE6Pthxvi3DX85MnJvXsnH3700Hs7v3dSyjhOwzhmzSSaSxoR1TkXYzQfK3LedV23iCpZSwKAYezVYt0B0jTtd3vooKKowTlEyCntoHccC2jwYbFYdF3nggOEwE5yGYb9vm1BZdj1Pi7aGEVkGMf9OEzTRC5whNCw957SlESKaRubVfQ+ujbr+mRzfv/B9nZ3c72Nvu/aHMMuuH0ukBOroMic5/ToKoZpatUdB0TDao2rjC0igmNiDPtxzzxXGJkBIRFgzilrAVFH7LGAlP1uz07vnT34wSff/0d/8A/bf9z8N//0n/6r/+tfA2PtKjtNOac8pelmtx2GkZhWJ5v1er3ZbFaPnjBintI0jpCli81qufr5X/38+5980vrYxkjOzdwch+xYUt73+zENu7EXE/K8NO24894vFl2A8GJ/XUyzylTKMIzX19uKNjaNJwaAlPtpystKxyTHU0m7fX+762m/jzGIaNfG7B0zu9rstqhlASNTnQaZBlED8tC0btm2bRdXq2W3YBEhFsmjFFBBAJcUcxLRPI49gLRds14vFosWwMZxTHm8vr4dJwnBF7lUASIMwRmWI9VbLQ/DTvNQMvjAi0WjIpaxiU6KjqOkcQ9ghsie0RE4dd4TsRmmlETNNcHActJcICkg3BDY6er09GzdhPbFs2tUjQyGHtRNk+SSPMXlqnVEila0ABKzc86rGvNkCBxD2zmRUYrmJCH4e/ddlvTl188aPPPBPXi8ePrFVsC8EamSmhEFZkXNKlJUSuEYXHCMkFXU5MD9OWjE2mzuce6HC+SIiGTeKI/Fbm8YWEdEwczgmOs+IiaHWrDqIByAmiNocteVP0JnhysABNRAlK1ozpqsiEEg8hEw5KIq5lwkDyUVjQVW8E/+6/8Cu/7y5uJmt51Ebm6zc+OmS7ELTRPGSfsEquIbA4BSwGeoW+OceDRFMiRDNDYqUwZl3zJRGYZ8Od3s819gaz/4yfeA5Pr69fOL53EBwHTvrGu6ULS8vrxhLoLCTl9un56vPvzv/4d/8cf/x/+yipRvpRQhbypQSkLiCh7OeznoTERDnEO82kSn+lpmh6CvBpJvbaN3frHDz8MdOMzzvN/aO9Wd3xVqHbzhdz3nd/Gst8c7lAbE93n188/viOjs3V8Ox0EAoEr/hkOwig7J1PJy3d0O209+fO+z339inCCU1zdXl3Kti7y9sAcroCkXBVVUQXLRh0jgU+6nnJYnoMVc8A8e3Ds7W0Yfrq4uv352oVqI4IMPH4SAnrlIStPt0KdpBEmz4MOia9fCBoG9TaJit66x2Bi3eb2if/lv/jIaeA9t2znnhmHs9yllaGNwzhlQreL13o8mabufcjaDpoWmhU8/faBZBYDZexcbiYW21gxgsF6tn1/2gZrLi/Tq1TfM8OTB+fc++v7f/y835x/4XML//dcvF6sTFwBdbpfMHRYrJsUH9BGLjrlk55GwZesch2mS29v++mq73+tqgecnp9G7NvD9s5NV7J7+5dOn/+71z//6S0gQmTXbMm4ig2ka05TGvdp+cbLgSGW4IOe8c+bRksgIJZlmJOGohMYgqGYSfG3qAKC1Bk0VsCYqDLAiGQAMhaEUNU1cine8ZMSbp7ubr1+nyZbnQrEY7S+vX/3D/+o/Y4vjUF59c/Plr56/etZ7iei4v+zzNAF6cuy8U0hAsLnHiwWvT7r7j85PHqzWDzZPX/7qavzqZnuLrT/7gE42CyvgsOtvswoyOUQIrA5ZSp6GMU8QY9t1rbmXcdPcX96PFNPtOA3iBEzg6mJUeA3sKCJBWKxb4BLQi5PL/cXN/nnjadzfLLv1ZnEv+NOzD0/++ff/+YPl2cb5y5eXr15ePXv2zZ/9xZ9sx/718y0kgAVAA8sVPHy0vv/w4TdfPE0jpnHQXoXKT3/v75nS1c3rnPJYJh1VBnXiA3sDYA8BuQQFRST/8tlVjaLElMCZGjtyPkgWK7OMc62SATJVNTKohFCAXGS2OoyAQuyAgRwZWG3oBIiKxnDIT8hs8OaDzhndepdrgECz+OiMLx0CcFUlPcibCBjjt5tC1Ijtjn07sjoOtuVb4c67Rua3BWHuIg9wB144WrDv5lX99vTVuyjH/1dVeu8BsO5+t++oTftPc7yFRv32nzqiVES1zwYdAal6v5m5lPLrjvDWY4GHcbwYZr77GAFUzgXDHeWsX3fk42XAnYemQjF3Nk87+gf1mTp8N7NZeaqWiNWoHGyuRqtsHzyotoNWkAUQ0LIKoM5On9lMlWE1qHLoVU+8lu9ZTdjPYtlWQx4wBXNgYMSV9UFEDoDMqmLIQSObELVKHlU6DAJX0Op4gwDBVATQSjVlZIpqqiAIqAfGjFpEOYhxKiCoVLeLmEDRVKuI9VHyqNoMqSF9dOgEqFRGV9W0mtOJAkKGQAqVvEDoKiBioAqqCnIA/ec5qc9E1b6ig1Dg0fAdHgLAqhMGaEcFJgQUsgJ4qGNDxFrAhket9Ip8GilUhfpZ82lWophPVtlzOnudWGNNAkXLahPAABzJo1OEAkVBCR0xi6lVzIkZCURBQAiKEQIYmigooNYGdEBanyJGA2Kk2gKkCogBCxwCAgUkI0QCVakNK4nIGBARGWH28hDmosWZFKyoSPNWI3Dk5B4iFJ0Bv0rgrTmZmUl0yGVYZYiDETPOiXfCWZkX1RBV5wcaqgr+fCSy2rUQAaFAVlAwFTA51BECgFFdXgUdUGRUA4GCZlxPrECA0ZSK87QMyxBc9JAS6mQFFb364AmQkL2v6IYymg9ETAAUW/BdMLN9tn6CVQfAwE2kEIKjxWYx7HoiVuHN6aP14l7q6er57ee//AJGBhElRUDVYqrokJmskkmrNVFQBUaudIxKvGZjNAQoBLV3gYmi1sZeB+YbIpEZAqkQmKIZ1U6maqYW1qHktN1KCI48O2TJUkohj+Tg4hU8+/rVyb2zR09Ozs4eqsk07fMwQeDgGT0hEVEpWfI0MtvpekXmLi+utre7aV/75CFkKJLbxksGRfDMpydni8UqhCvHbr1exxCvb25yGVSk349XcBGDa31kA1Ppd/uUt1lYFciJa2Aaoe0gNGiQssDp6fl5s7h37+SDD+/nPOa8T2mapp4oeOeDwVg0p1SSeF+IWAqqSts2i2XrHMk0WSpYoFiOPnBAEEnTFNkhYoyeTBFNJCeZUsmKERnQqOvaEP04TVKk8UFSQYVpzP0++ZjzYkEAY56mkqaS+jx6LMaVKW2MkNPUXwwiOqVJBNq2IXLMGAKHQA4ZNWIp0zhl56VgziJiZOQ4IpCIShYzcExqWrQYaFKVaSJKRA6BwUzn1VXra0EIAVAQxAoqFU26E1GJDZyfna/PVvs8PP36yyZ4RXn21XMFnepI05RSKWW73V3f3iyXix/88LPcp69/9RWqnq7Wjx4/WrStgux2/eXFFRR5dXHRxfbe6ankyTlCMIc+RhPUdLvrp3HKY5bizAdpXMqqc0HeOPWj5DyKCKiJaBEpiNy2i9jwMNymPBWRaUpEKKop55RTzpNBWq42C/Kx4SKSi+Q8pT7d7sciRQoYQjp0ZgsOmgY3m7hYtm3nQoRxt/XBGXDFpYuWPJVhTCqqtaUCgm+c5ZLzNPTD0I/DKEhE7C+vrrz3zmGMBOTYKZEyoRmknMs0mKLjCGTIhdDFztKoyMUI7j3sihAxuxCACRQuLvb66mqSPUdbn7fEWkTJzaVOar2h86FdrOhmuysjmHiGgOZ34y4LgATHHaAvVkxHNdHa4r6AFGS2GLr1crlwO5FiUFbrpluGb755nabdfrhysPi9n/3s6f/+xxhQStFszgAQj/KJIKCqjoSYgarOjKGBieHBnTlkuupWBrMeYrXBd1ATO6SuKzSlZlXAoFILFQ6xwCFjonZQejrm3N7apWuZh1a/aW4rg0QAzOBKGZwSKaoVJOxCCBaTKNMClZgtY/LLEh/Bpz/64OnL/3BzOyoGYFFISfa7/nU7rtv1oqEnPVylaYioQAAZ2AjVmSIUMlUkT4ioENGjIhpZgdSLOnIdblbeRfr3P/+bPg9PvncfUVMCctAu9f79B2I4pH7XF4UylaHbxHT7guLJj7//s3/w+803vxifXwJk4NACoTNij2pJoSAbAKA6hQAKgAIGCArfVqWq/tTRjz3IvMDBnZyJ2HOKbsYZ4c2tnY9Sb9zRp8U3L/46j/5NRPjm9s9Jv2PU9+aI/w91b9Zzy5ZdCY05VxMRu/ua094m89rpTJdNGcp2WQIJIQQPoCqpeOGFn8KP4IEnfgASL0i84QdUQEkYiRKyjV24ynY6s5z35u1O83V77+jWWnNOHlbsfb7bZDptVyE5ztF3zrd3tGtFrFhzzDHH4PNx+BEmZe9O8Ctncko2LnfNoxn+coMwEUgWfYxlw1qcVIgc+9oSy71MzoM4MEmCkCiy3+DlR08uXu7eDm+x8+OE/VhI6O29XUZCFgvOkWeitunapiVzaZjbCBj5zq4vV89fblerzoqBLM1lmgHgB20MnhrPIrDUzEhFoUYqpgTVrDabOa0yWcUsqQ/sXfCxudhM3lpicj6oWSlOjIP3TbduYpOzppSNijkCFYJ4jxix24XNrq2kMylZOMTYrFaNa0pbplJsu15NvY45v3495RTaJjBdmIuzHm8OX7x+o+pdpt55xy0kaGImj1WzEUnOkZoVmQkxEAK7aZS5z/3bcegFI977pebp1l/uNhfd1eXq2Q//5cc/+oPP3/6wxy2TIyFWgwuRPEyTKUITu3UXoy+iWird2cFIxCRlS2TZGMTGfAqfWCDqAEAqAdIqGbLUmg3TU3FtDdPYEWsx7Qsmc62XyT18dmzdJpYdN6tA+Pizj9fby7ZZr5+131m9/8H3nWX68rNXB9rjBpCsISvj6ru4fs8/eXrddoG9+TZP3T7r6J+6jdsND/l+6lPhrOVyt7Ks+9thGqaL9XrVdpe7dWhoTH1LZq7EgKYVBHVBw8a5QkUEgiZsGocxjw9vh5Q/3T7ZXrzYTo72+VZA5jg613iPNorM7eXl9vJa5/jFpzevP/skJm4FZSw5yzSWfhiVaHexmdMMsvWqa1u/v5m+/ORf+nyh/ayUbQYyLsJFkmTH23SYNUmalLI68tnMlEEhuHYVo181oWlf/+QOBoMWzlABsydyDiAIGUwAb1CDIddAp+JSdQThCr3XegxTOM9gNhNjVjKtifo6SvA5/WGAwS8mpKfYrVbt1BD1FGUs/Aig1vnVMYAZZ9WX0zijVdXqUUhrlVZxxuvrh+9grHcD41+h7/4YFjj9ev7/1/g3Pwch+datfv5xf0Em199g+fko23nxP+uL2iI558dYzDfX+dpZnlf725z6X7l8686/SRb7Bc/hMa5Ur/Rx2z1Gph5f7/nDb4WfvvZr3e0ZhzpjZFUh/kywerzy4/1U8KvWMwIwNXLEDmoC1KjzfKTl79ke+Ayc1RRlpcEAKEmJUQlZS8TOBqKqb1epJyKZPJ1sgAkwQS0ertpXIir1qavQFcGoelibVu1nqcCFh+NKiQKx2UlpHUQwVVXvg/NcipaiNc9P7OA8nVhUbAYTKSIQNTP3jiMKrWNXtTsEvOmJ4u7Yw0FIoVVVBvM4FRFiUrZa+FYrD9QgEArORecjlyIoqHZHRqDARmByjtzSjwQOzI6UDBCiQgDs5GJjAnOo8FQFmNwJuzrnBQ1EzHDO+5LzqYqy6hLpO4FzhjGRY+cYzozFzM6aCkSukmbEdBGT8iZqWIS2iR0vaKWnoiWXFCk4ZZcdJcEM73zgIDB1BmIXAjsnJZmRd469gzMlUafmlD0v0z1VXdwAQYDqqQoUUqseGIu6pVtKDGo+PTlyFBzBToblWCIYB3YwmJma8TK5XJTpl/BEATOtzB9bRF5RbUJqBvicxYWBq/xqbRM6Rz1qJ2i1flYltUoWmDZtBBtEzZYCVSGpaWaQMpmxMDvHTIyyVAsQeVKSEEOInjKDWWd1DohcxAzqVwGNmdfV5Ya57fsHx4hNIHLjYWy2frNZOy5aClnwjghiNgOBqRQpF1fN9npXMmX1TYtnz3fgvFrzetduN5HVyPn1Zrvyu++8//0y0Sd/+cVnP3qFPWKMKWdSgUAki2TPgRzMUsXoiBywWD+akYiDEsBG7IlhyouyHMiURMzAjqnKVC5dY4AZwxzq+CQiVmDBk4NoGXOJiG3buMaxIOWZDGhwv08f//RVsfLyvcsXz96/v3/95vUneSwlxu2uY3bRUxrHYmWe+67dxIAn19txTEN/Y2YMYqY8zWSFya52lxe77dXu6vWXr+9u7t++ud1s1tuLnRFgqyeXu1XTHfeHh/s7hgsxfvjhE+izedL+MA791AfJh9R4XF9fXF5tCdI0/uV7T3e7brfpQkNFZex7My0iZEkKuq4VsSzo+wMs9dNDNUlbrVZdF9rNjlwQzDCoqodr1ysTCeyg6ry/vtyVlFNOIjbMxyyapfWex3F09LSNUbP2+37dbZhjcE3OpZ+mKOScY89JSlZJVoLkksosMxGDQWRSbOin47FPpaScutUqhDgOo4lGTwZ2q7j2LHJ5d5jmWfd5nuZqL+igJMXmNLvgQtMEdoFcITKZSgY79jEQuBSjWNgFmFOnpqbso+POY5wn82yko6SuC09fPPvud96/fv9pX4Y//fGfTf0YQ/PxTz81o5xTzvn86tTs1v5a5vTFx6+6bm9mkua7ePPw9rDq1t5zCK6NfurHJtwEctEzJD+5vMqWq8YXO5dU4MjFULKSZ1NM06y5qKh63N29EU+MEHzbudbAbdemlJomeGeDYbNZm+k0p832gtmrqAtutelSmotMIYami0W0H8Z+GoYxPxwm8qSkT67W0zDBSfBNu3Lbi7DZxhDV7DiNs6TcrVbsvCkTcy4Y5zzNuZSskLlIkrJedVVlstrA+ibCcBymfrK1S8GH2HjvnfeMIIYiAmbjWlDBSqQhW2C+uFpLAjsWsYdjoaIw9uzZNcM09w9TsRlOxGXXcLOipgs+hBDo4oK6lRL3YlNsN7HB3GMazaO0sUVBcHAuAkHV2q4BkVhRwTyX/aGfC9Ybz9RsNhcrrw8Pnzcbt+rW5Gj+qUTP++HVs+aj3/7t3/if8z/3a0V2YhhFPJGHSdGi9Z1hpmKWDQQqla9rRQESEUfsmOGciDrAOSfQkosAwbkqv7cgI6fBaQkezljF2V4ZAMFxzVdykcqkOM3urIptVdt1kFUNhQrQL56/bGTETM5yYCuNc85bTomLNvCuuGDBN9vU38foPdPT9/Eb/9GHsx7vD4e3N8dpQlHdXgDAjLfDqKvmJZUn3uww9pSnlnZIYLAJueLzVCxpcJEMJuKJJaXovRIVq7ZZXJKzAfs07/OPw4ZWq+7505XaWLJBaBrFx5Xj9Pp+EpjS5Lo589ubw1/8F//l7/zu//j/3t082NikEiOtrOQYfC4qOjMDRmBPZQVlo8Mi3U5EMK11oLYkBGv4dwYDCSdedU0oFrGvca4McLRM5E6B27kW5XHM8VVE8SvLmQtBAN45kdXpMJ0Pdc6PwapQQaWO2QLIM58Kg04nBsCIrboPcT1HW9QQ6gQOSkqAkth5k+UYClJyVTeAZXEwZs/esTOAWzfI9PQD31zxUQ8j0jSlDBZtb28GKMbezKHdNE1stajNJpJD0C7g+sLd3uVnL9YvX15sL7u+Hw/7A7l5s228m6WgcRIYXYgcmqCEwYIhN75oLjZ6X9iNznMMjXOOrSsl556QQaFhFhUuSYchiYpIMXAWO/ZTLhpjy96lKWlKREKm0WHV+C620TfjcZqGeZ5z8gkq69WqjQxEMktTMnF3t/dDn7W4kvRhn9/e9FIG8p1Q365E6aC+i21TUEQRyHvnDTqX7AE12nbrIMFLc/dwnxPbzM9WK2mHX/nOlc6HjY9uzGkof/LPfjp8WqYHNLKSLGLio4PWJNsAACAASURBVJtT8uwdexeEGHkWUPEhOltrQslFs2gxksDVqaaYlMRiBGZmLvaoewlVnCI4MWRRNTmRO6sqFpPAEThPyCZJ2Eu5kQcaPqbbD3/l5Q+++w9/fPvn+zJPZG27Xm1W0XVNiB/8vWf/gTbrsBoPx7mM5Cz7B17NsXPKWiwbA8G/frhp1tt+nI9ZpmzXT67WK2foVcTztG6w7cK6WWGiYZ/6lI1cZGsD77YeAYnmqfRSmjnPUDS+8yHMt0lnyZOVqXj4brce0ngcxkmkodhRIDZpw6EUPBzTnr/4/OaTn7zCABRgXJ5DBq/bNRE7DUaC2Yn5ubCOnYqywAdPTBOyn/j4+YMd1E/BUzff3B73A0uk4gFnjmLXbq9ic32xibtnTz7s+0OSmaKpquRcqsiNgxbAmdXuUUAJyq4GEAIGEbNKVW0mESO3RLO6sCOXySSdao+IoWxCJx8bBgRQsioUWuPNd4/6aWiTioAZETPVym7DV1zd9BR1LH+qSAvIsMTgFe0CLfbQj5CtioJ9Q6HmDEo8XpYh8Rv4w/nnu2HzG/DItyI5f2Ou1t8Svfoa3ednLf6xBvk3T+uvRb/6m7Gf/k0t9tXazr/WaZw3PGNJX8OVzhpYj3d7/upbz+RrDKzHFCo+LY8/fLzh2XOwfhhjPJO/lm8rL7ke/du66NwaIfglsKw8n9NxhXVhbCn0/M5fJIQWeks9b60s6ArtOcCZDx5AyklrgE8oCq9SZYjq4auYkGNIzVtU0Ic8jCogU7UhFsStOhVW2Irc0nQn/SViVjXNyUylzlDsxP03wAFMTK6aPxVLizR7HYyqlIWKFVGBlGKqBEdUPVJRUSYmUoNj54MLTUCGmEhR0kX4CK4CdQRj712FRRTVUsapI4YZ3NKbINI6TgLnCRbBYEVLzfcxEzvnnGf2hISzSpkacDq32svLPBqnXdNJfRC2cI+UiM4EmZoIOmUgTx1bxdwVJavOpqlQJm7BIBEVUSOEJrBzUsWZyap2OsgqVYp5kXQFjNy79IAuFQ72mIG/MPtqDWQt+DzFFArzwS+p1/OYy1DIgo7VCSKdodXTnUBEYLN8To/bcrcurfKOdEgn+Q68m0EDp2d8SesuX+uipoh3OwWWG6OuTQRQKYU9k6s1E6SqAgNMtQhb16x945WRcyZi8rV0X+BhEeTVRQ6Nc56KNHEKYs7g0GC1brebtdoMTSklUIZhmllNVHLO6tiYrOuaEJ4BvNttpvmQ5kNKOg0JWmB2udtdrV4wBSb/ycef/ujjH0Lh2ScqtX0ZJOcU8/kvFhhVT047p0HNRKU6KjJgjk8ZdHAFv81UxLSqfCkcKs587o+SBAR2ROxEdRinpvWhDcUyGby3aR5/8vFP57l3zn7pu89LnuTyxTg8HPuDQbt1F0KzWq+kWMpTP+zZh6fPr3xo7u4f3twWb8YeChz7vfdus9tsNmsi+sP/54/643DopxcvJDZhs9lE79rGWdGc89s3r1PC8+dPnj95slnv2nadZjk+DHd3+9vb+/efPetWjfNMpNtt9/LFs7YNWuZxGOeUQog5p2UAMYaxKZnRPOWHh36a82rlQogwuw/eeb9ysW1XMQQzMyvOBeeD9w5MPoaui0w8TeMwps//8guDK0HI/DhOnkLJOg7z0CdRTZNKSXNO98dDWM0cuePWCEYmIqtV1/fHw2EUFe+d8x7kxmE8HvepSCllnuecZOyntgnb9dZEJOUudtvd5eYS+8PRVOepH2dBGZCBAlSlIUjbxM127WLbWsxjVjICJEs1lyAProqEqpEdMaRIDFRdba+udh999N0P3nux3qz6aXx7+/ZwOLx9/eWUJ8crw5Ii8s5774nQdL5t25Lz25u3t/e3625Dprdvb//sh38xJ2xW4cP3P3jx4lnrQ4xhs14P47xbt0VsmmcUc96xZ/bs2DUUg3kDcplTrqgEMfD25s368mLdtSF4WNhswmq1yjmPw/F4fAih2V2s7u7u5jk9f7Zu4uru/o6YQ4j39/dzPjRN07SN855YV6vGuajiq+rTk+unldXZto0PpDqrzaVMRWYzTcNMYPZRhETnNGOY51xyiEFU5zKKrZtmtWpbkcTOh9iY0TSlcVTH8N6FEL0n79F2Ad5m7euE1vvovQs+WCAVCtx13aY4C/0sQ07zmDPlzKDM3CixmXkfFCY57++nlXCMbejCxUX38mUnejz2N6q5jetnzyKkaFZkU0tzLixVbd2cp3mepnHisIwEpaAUlFzynKdxXm3RtmvnGCS+CVdPUMbsIy6uV93W4z3YDGOFI1aCmWYRFRBcXArT1FCKiBXygdgBpKJmBkfeBd9wnpOZMjkjcSQAmL1YPvF6TgCEPc5hn18N78hcRCcC2PLdeQzkE7kQWjmHpwTIwie2ms5XgLIleEVgc6pkRjaksfOdkhVOpkNCzD49/6j5T//x7/z4439187C/v5++uL9tLjartWVJbGAuogOZFxQ1KsLDKFBMSVymUEDgqmsTvffMJeeSzcGqt6YZSrHczxgKOqQZn3/+5vnL3XazScnf3u1vXu3nTLFt201sHRiR2KmUeT746/xrf/8703/e5Ls//+M/+NQ3TnNBERVPYE8MVVNTMVs0JpQYZ+1JNTsz+43M3mlALY386OdXhcaqEd+3Sbt8e8jxbdP5XyA4Od8E9Hj1hUNzmiKcAiZ8HSgzWaYBy/G+cv44TTMfq3a+W8WYlyxdtbcwM8sQiFmDIvLed3bPPtr5DR3T/ohjZhk0p5xA4AhI630T/UVwzTiNDzcPUNntNkUyKZ5ct8+e7kLUknspo1oi0hitKtDOU0+tFyOi4Byv1iuOTiiwR5J+SgciNmUgwkiLK8WVbDkLU9ls1sfDMEzDsYcpvAMRisBLFh3FxDsXomM4ggANO/WOYV4z9vtjyqIKx5bnuTcjp+SYARHtx2M/9qJlmtFEfPH6y+Nw/8H7Vx9+93lc3b++GdUcE6U5TZKU1Hvu1l10bhonFIkcvGsb1+WBpmlOM8jpat342DZutbq4aKj7+MdfvPnkk0//9DWK9xLJwI4Vmuc5y3TdPAvOpzylKWUpIWXvckmAQotoVitKUm166GSdTgao2tn84XwnGhBjFFGjQvIuvjtVrCwZViYigXcUuTneTrd3nzI3v/bv/saN3twOt7d3DyndNm17cbGLPqyb7vs/ePL+By+Hw+GwfyBSDruMoR8Ox/FYUs4qKE5J+3l46MfDuAfF1Xq1asPdq3sU+eiDX047IPG4T6++eDuNUzalgLjiVYgdbbsAKdAiMAnBw2POY86zSIEnYuSUb2/vvWNqwqbxOUs/jNMwy1y85X44fDl/no44HAAHrIAEeDAzMuskfeode9c4F+J+HsohwaFpmsP9gRhOmcxwgVefvdXMyGHaD5pLf5P7PWxOkFQfWddNeVbNlGd5//kHN/u3h/6BvVLgcTqOw+SMTGDOoJBzFFyzD3BKWn3YNdWCgyWurkGxVJ/OhXtBIDAzwWqKAoTqFgrNSzGQVt0NJsBEjUCitmDaNdcBI4MjMlB139GvVWudQ8FT0FJjnBqUnOSYF47xY4wM5+n6zx7jfgFZq79byy9+Od/CwKJzSPwLNM3XeEN/1xuxDkPfKkj2sy7tsZL61+Czb2Jej5czIetrGvln8OuxOpJz7qwxX8EEq8LlC7mkbvjVEwZAVBlYy55PzC8RJQcAXLvsRHis5JnFnMyRyeKrwFh4QMzEzkIIqqozIKCTI2m9kGqIxs4pCzERGxOEYaogAwtMCOwcO+IMVIRbVAlLzRgRSaV7VFrVElObPKabEZEjcgRnxlRro9i5OjOGN2bH5LgScYoULTAWERWBwdwZUrITPE6mxQU2DRCDknGWqVheqKkAV3KqQhyHBRojAkyXCjR3zh0unbKwg85YSW1UbyRVUqyal2gRhjuhzVb5Y6TERPAERtWlgoNRtYxcMsXn/j7fQsxMzMTkvjF3V1FSqrJFZS55SpyYGAoxVYEaE1UDliwLK5qsVk2AiTzB1ZhdQQYwmneJynfIj9pXjksV/qpVFzCAXRU0c3q61c/Z2VwlthbIFFh65kT/Yzrd/O9sJPFO6uRd9LEMRDjX19opqFla7CtP4xnNqdWsSmRMZrpUp9BSAWCoL0I7KVgQk2+cqUkFayIoEhsQoE5MVUqCAzzEctuuBGUYeyLLZQ5tCOazoFuF9boLwY/jUMqMIt6rI5c4q5BpmebM7E1y017sNhcl0/7u4fbm5v7+zXbtL3Z8ebHebbrdate1q6fXzz/95Mv9fo9gMXgtch7PbLnZTY1Uai+d6lHtRExbOowW/JTftZ3hNDnT6kdsVURseTaWnjpBBQxLBg9lkFUQU6dJUzGFhuB9ICMdx/zq1dsY+b0XT7t2h52ZSBHt+943cb2KXetSsiJpGPZNu9ts12Z2/XQLvnvYaxoAxlzG6+uXV1cX3SrOafri9a0nSEF/HO4ir1dbtH7sp5Jng24263meh+Fw5yiEcHl5ud1sri53773/IqW8Xa2D45zTnGYfGKRzGofjwaw0bWDHJcuqWw/DeDxMbWyb2EqF7Cxf7DrvfW2ZeU7jODWd7y5WF5sNQMN4hJlnL1oM5EOMzYoJKjInOI5mQZVzNhUmhJxsv+/nMRfVw/4opsM0jTps/RZA0zRAVJWU0nazTvMMHUyEnfPEcH61WhXRWPIwDGJQlWmaYfO6XdUhnIBS8vPnz9nT0A/j3PuIMkMEJsgZUKQsxHPMLjg2y0DWYpI1ZSsZMbBzVCmxliU7VaacMwRIgoAnv/zsH/zmb3744fvH/vBHf/j7H//kL4dhzCm1bTvkvsLrBGLvgvMxxrajYRjW2833v/+r9w8Pn/30s8P+6IhAcJ7GXH7y2eeffvH5P/yt3xzmdJzmqcizzc7EsoirpeUOHNjDCcBGWco8jDD2ITpySmhiS+CcMsx5R4BnplLyw8O+7+/Xm5WKMrMZqVJK+XjoXfAh+JTyF69u1quw3m7btvOBAeu6uN1epVRKKZvN9vRWLaWUaS4pEZELviGm1CdV5zkGH6ZZ+v7m4ZhD8DEG55wz8tw4F2A89Ontm/tSqImRyLdNSDljibQZpDln02JOzSz4EEIMPjCcMZq4YmunUfb78e52SHMqM0qxnER0AqvzkbxrfDQPmeepV4JcbM1EanLDqjKtWS6p27QvX8Zn16s84bgf3twcVDDnqUgDxn5/P8wltri42romjGlMgiIYhv3NrT65uGy6FcjE0AR6/vJ66kujwa9UaPjO93H3iR2nAoOrFCgQCMFTbJu5TN4FkLMyQ0DOSJ0otMaHxEpM5GrOCuaq4QARAd50NpAt9uYn4OKbANZ54K8Na/gKY+fxe+G0+SmFcXrlOjJebETIGToxKhqYG3bMSU1JNitXZG52GHpkpPUW7/3ykxcfXv5v//z/GEvX9+nhAT5N6+sORj4QBxaMOaesmbgzxDkpInQyV0v0maAkpZD3TE4kkavGyWauhlcGT/AUG2NXPv3kQVV3F21wHcnU3+c58RinEJtAKBNYA3HMaR7Gh6cXu3/w299786/tj//4U/ihTLLeXksuRZR9NJlMag7DnFcxqYYxSyWV6lIVWF+3/C7cepTQWv5dVN5PvIHaHYut5F+1fCtW9c2p9bd2Zk2DPtoHVT2q0+zvNIk4J8Qeb1kFKuomWPKI9G66sVzmV87ECGAjakNXSklZrCiYXdO41qmmkid4fPiD725fuETH0Q5oirCmMqZUoGCPbXfdctAU+xH9Xm9eTzml6QLrjdtcXRnSNEzDsN9su1KK6kwwQqmVErnMrug8Y7RUJsticBQb8o2L1vEoIlpKSHuZM9JsomxWFEVkfv70ol2TkfexzAkm8AExBBgzh7ZtmqaLoWHylnWehyKjqUyjzHMyOMfwjoL3zJEpqJZpHqrSohnHSNi4rkPXNtM89EMustpun7jg5rTvx3QYhjHlQuYabDbrdbtV0ZInT8G5OIyq0DxKytOxF1E0USLyxeZl57vpIb3+7JO/+LM3IN9t2vFmYHbRRU++FFXknJOpoRihauwJHEqBCUwERVDMBNX2vI5OC2vfTsUAj++95fazBQhZmIcV5YWR1iFOYRwCSPIshQDBq0/f/NHv/0n7XWcZU5/uD3vv3P740HXt1fXF9BfDlzdfXFxsVcWxpWHIMoqk4zi+url583a4O+LD7/nQdkTUNU1W6g+9Tq4kXDRXL55+8Hq8H/fp7tPxzashOg9yBTn32ljydni5fW+chgYhWnCdjwHzdCwJLgAeeSyCEi86nonB3gWynCWZppQG3zXRxaZrsYnej7fW5xEgwEGLghUNlE1DotCFxjWbjhLnaZrnGRs20WIaYvjOey/f3j0Q+PgwvfnyoQxFDsbgGCJHEpGUk/TpId8Oh8EifvN3frvlZn39fLXtZhn3hzjFYZpGGCnNAkMBHBCWMaGYkjM1eDKIW7wwuGblxVSV4ZgU5uoTbapWYyNVwIjYk4PLUqoPLutJzkpOloJMVK09qmqmKWp1Aiq75Dwg0CkQp1N6HvgmTvJ48Ki0L3tXOXIaU34GsP/XEWX/OZ/84tt+6/LXojr9jU/mm4v/VrAGp3Z5/J+fs3yTcPT4q/9/UC37KpXpr3XQn7Nyva4zePSL7Pb8in68/8e/ysmx5Xyqj0/+8U4qhiUipZQzNYzZvdvzKd5fBJnOiaSTumWV2Trvrf4qMtEZCyNj79WT1nnJwvoBHE2Hvh5EYI4JzhaTweUUAQYRKha2SBbRgpHNUoxooSmdIpbK3YDzHk68855KYqBW4jMJVFG4EKqRBC+gTtV3cnW2yVZrCRyZM7BpnSct5Qfq22AennylhUIgAOSkjVQXtarDC8WiywhAYc44skOMxMqkgDmDJ4h5OHbOmVNDKRlKzrNzULMiapIpeICr+P1y2kSm9vUnh+Dg1MigJZdS1EhC01DttIUpBDCRc0xEDifsBjUlVPllRoZFZt7BYFK17cU5EPjrgx2hZGNlH6JTHqc09okyLMNImJkcwLViTi1YvTEUpiRMIIeaCMe7t7i5NvAZuXyEH2FRMH1HoasK8nUAZmZybprnU2xA532oyjmRWUGRZSJ4gk6YWdWaJp5YagssA4OInPyhlsVU8ykVT8tsA97T2S339PgAajBic6RLplT1LCd3grGcITIBLFZIiKlZt0w0p6Tegg/wlK1klPV1x0zjNBn7zcWuXTdTHhWllPT67r5kCwFXV5er1drAptuujcN4eP3mLic8vY5d1zTxVJ8BMivBMZmsYrvuLvZ5/ORHrx4eXjFzf5vmJ3i63V6udxe7yycXz16+98F/89/+d/efwjEkYb3qICqlKFOtNRYRgKqdZAVCawimYnaq8V8m9aQ+Bq5qcTVIqZJ20FOnVpqkM4DIKlJMTNWPOHOCwrKBF7lNOLhAPniFjNOYSwGQRtwNr58//eR7v/RB9FvJNybOEcgckWua1ns99lM/PBz6w8X2aS7ya//OR5e73/rss1d9ShfXVzE0RHw47D/55OOffvaFJDQrhIBjn479bRNvnz+9vL7atG2rKteXl0T48su3h8MDQQ6H+3lOeRbnPHN47/nLFy9eXjzZzlN4+/rVn//wJ8fjXRPaZ0+fPn1yNU1jPxw2m03TrveHORsuNxtRCiE+f/4eM6eUADRNs9vsrnZXq6YNMYS2NTPOMc1zLpNzrvHeeZ+LpHmepikXefH8/ZxNS1l3K3T08vn7MUZHMScV0xDaVEo7T8dyaLdxvVvvLneOakE0zWNi8Ga1jjGu1+u2jXORVze3l9tdyinPM0QbH54/vYwxbte7dbdyoHmcj/tD94HfbpqnTy9Wq+hcJPPTlO4f9sf9ME0JtaTGzSUbSJoYG8DapZ6ZLOQs85wLiWcwENntdpe7y80PfvUH3/veL0/j+OMf//if/q//y8Pw5u4GIFxsOYSGmvaLz9/UR947eI8YPMhykTEBjE0DM8w9isJ5Y4KZlQJIguB3//f/+6Nn2+999F1Tev7ivU3bUgyH+5th6JUkc/ExJEnTPM05lznFpnHsjCCmu8tLJTgKbdt4185zmef5eDwO4+BjnObp5i5vNpvt7kqNxqmwa0oparK7uCLHPnrnnZmO42F/7Esuu+2z995779mzD+quchIzY1dq8f653h/WptmaNl5ePE1Z7+/GeX5IqYBGZoZ3Zm7oc9+P9w/3X74VT1iv0DSN803rPTkDu9DEGJHylNLEzUIjco5VbRznh4chJwsk43B/82YYRlyuw/2d1DIKqIFm5RkMzU1YO6fwDo1D68PVbtVEmqchBDy5emqix0NuOnd5cbEKT8Ze37y5vTu8HQbsx7kdj6tVFCvEYAezQoD3aBqwQ0plf7i/vffEs3DfTlgXv9t2wVSGw8P0quXVf/KP/uM/+8OP/+wPPj58YW727NkxQ2CmWtB1Gw5equQgiokViBYiOGY2pSw6aYaaIyZnKlABEQrsrIbw8xfDuxdVJdmzEZ0dDL9WuHEyS6lAhgOUYQ7siRyxJzhtNmFIU3bimxi7TRqzgdzaNSFsPA/z22aNf/yP/v3v/nr7B3/0x59/cdvP7TGtvF2Pt9Ozlx8dhjdTOkoajnxfMkriNAavZcK8abfH20OeZ4IjwDtH1d3FyLH3TUwqUvUknOfgKEA1p+m4Wa+mfrh9M2/Wu5KAqT08pHE2KbNM7RRx+8VR5eDt6Ivct19cv3f58oPNP/mvfr3ZHP+n/+GP5uiHu/td+1Ri3Pd3bIGMHDl2YGeSzAjKQiA1VMBweaMyHEhgpDiZQi4cpZ/bIz8zNvu3ubyTo/kK7+rk0F1/EnjxjHkHjOlXU2UnmvYyg6zfMcBsNA1zdcWgqlLKiuCsC9urp88+3L73qy++3P/lw/jKbVQZQkWq7qnHptkM97mwM0lzPx8eDg+3CQPydb/99Rff/+hXH/rPX7/9fLWO3mUpYxu4YY4u5pTNxDVOyaY851ydhyOcFk05MTsyojnTfj8OvebimIOPnphUJavdH29j4G7nu10jCjbPrvEu5lmmJFJsyrManJHMNs3JDM4778Hg/aFnB2bMcwlB2taIbN/naUII42rVdCt2LI7JuxK7QDDR8djv1+vd06sL0of7u/3haLHFeteuuh1z1x8OOdHzFy/b0OzvDnf9MB5GhZLHs133wcuX333/A5LLP/kXP/7Jn39+9+WeLMLlcegpkooUpKq0wez7/mCw6s8EgrAKZw4RgmrxueSq1UxJjVB9aWpffwMbJWAeJ5wTpHXaSYAtDgdKBhMHV5KoM9MCAjq8/XL/e//97/9n//V/uG2v8tbmSWab+mm87cfP7+9mxfUOf//Xvk+glMbIrJKLpHEeHw5DNlxdwzufp7w/TncPEEA3ElZXF92zYM2//uGXf/z7P3raXOseeosUXAwR2aUyf/nl3Zc/vLv+jQvl5Hx0nAKFdRNHSYvsKyGuw+768uriyre+n4/3h4ciiZiaJkbnnj2/KmmCmCZsnrbtxZYpZjFTWLFATeva6OJ0nIZ+OB77uR8KzVi76Ns4BlKsd+tnL59tNpu/+IsfQejtZ2+wL/AN1FmmJMScgAwFFMiahwGE3/+n/ycUz773wp5ffvnmi/3NPl5zu2vZucZRDoWUIYSMMhZ4Q7ZFyplcdCHNZgR2rCqiilI1YRZJH0dORBZFrXprELFnJvgu1EIbKJmCCcSsAKtByYi0nNK3J/dzAwnrmY9wRq/shG9+bRiycwYdj9bnJcbD449/rkr6O5LK3wJI+ru4/EwNLHwVw/rFYaxaoXbe6t/guf4iy9/4iOer+xoZCo8wzq+1QP31WxHAM3nqvLfHzXLe6nEV4Xn9M80BQPUurHIhj0Aus2quXPdjFTlaIMTFIa3iS+TGaTpvaMuzAapgccUK3pHpsVTJOSImcoaa7KxER1jVgqDT7JwZRqhIERbpK+PzSXpvVouMACyOdkwgFdXsiJwj7x0CSykmj3kiqEWEVYmPmJjZqJrgVZispsnJTFUMnngRKSAiCjEK64JsWM2pmfdczdOSZBNUgfNTYdTif2dkKeelds/DRefVqTObzcikFBUVLELexoRqlVr9HM8088dQuurZWPodT+4MnSzdJADQnDz4lg4yGLEn5xwICtVaAcZGXPNDX5/x0TkFhKVI286nQ4AxGTtz3pxmk1kwV9oRjE2g7Fx1q1Qy5xwzKcRUlHRxA6RFFqROWAnmAqB8vqiqT1+96mrpmZ5CgMrXqRL9bMqwc9L1HR5WTQ7fBRi29M6p2WDnMl5+dMnnR2YZ8Pmc7jhPT22BLe1UDPqVdjuhZTCFeHJKeurEJb9yQryyqjcjNYA8QN4cmZemjSGEqYypn0V04zfeO+HE3rWb2G3aMmYpmtWKWRE4D3ZGrGlOTGRwIgWG4MGOQmhC8AZhMnPkKI19chgkpbEc3r7qH17fBW14TbNNlDEeUr4qm+ebTbt+/erm/nMEI8ckrKrVmaC6+1ZGVbVkrGPOojFr9bmCLXNx1AIvC+zOnMDlYXy02EkgxqpLQP2ovnwB8owTu1SUnRkpmRLBSSl5KkTEnkQUI7789ObpxZOry83l7qUpuyAgSikxcyWe+EA+RFAiLm3XrLd+vXHjfWbIPPXEPA4DjFZNdzeO1aShPm0iSFnMEGOYJnl4eGC2UmZ2DNIic5EZBHbsvaql+4c3+8PNPE7H436ep5wJmlNKx36YpknEYM6MmB2D0pxyyc754IMPnolBaGPjvWeQ996MjsdjynkchpxTTimnFELYbTYxRu99DL5bbYa+rwEqAT5wDCGGsF53T66v2Pno/VzKlKajrKijGCMAZmqbxrZbU22bJgRPoDKnwzwlUTa0IcYYp3Gac0pZVKSybosUMyq55JJvbl8Pw5Tz5D01rSdjcg5YeW/zzKoANARvMCYP43Ecpx8N5QAAIABJREFU+96OM6BoPUwRXPPk6mq72TXNKjA7g5k93D38qz/502Hsb25v7h96kUDIMPSTlmHc92NsCUpWS4+UUhbnmIxYDQbHDbPjdZ7nnAF27ODYmeRigGV6OKaPP/t8u9n82q//+pOLbUozCGMakswWqAt1QCtKwoGpis5DQRZ8EJDj4H3wjqdJVdU5Xq3bpvHjNBCjabu2WUmxUtQ5l3MuJTdtaLvWheA9iZaUnVllCJcs43F4+OLzN0QIMa5Xa7CnBBEdxzRNY0r67OrFPOR5sqEvKed5zoSF0TDPxRlELKUyTsM4pnXrmKp6V3bMV9c7YokRlVnbNIFjKzapQdVEUHI5HKaSKPiONE5jPh4AgXS+jSLZFutiYlWBAKJWlEhjQHCQlAJvo9M0zzB0bUcOoFmsjPM+Z0uzCo2rLVwLN4GduIZcgCMURT+PKxec47ZVYqSMYQTgFB4I7Gmcpt1lGxuacxrT/f345sNf+aXPf/old0YBKJZLEiY1FVUM5WpzVQ17QY441FkBrHq/EIFVClIByDyrLHKFRgZSRwv5h/ks7v7zkZN3b4DToEanRAydtRSW9w/BiIhrW8IYlRltjshpLRhP2bRqCwBJ5tCi5CMafPBh/PBXri6fdn/+l6+Bzf6QsjqIwyyMlaSYMqmQxtg1HDkMh2xmBHry7Gl/P5kIiamocxxDtKI5F++9sVc1USFXk4puUcYU0gTvaOxTf5/Wzepi9ezzzz+XTCTNw82kG6za6+PhRsRIcyrHbPtMPrTtB99t/t6/t/29371ZrWOSKU+m4mshFROoFlByTRbaMsGnU1hW/WGY2dRYYUTfeN0y8SPaeG3rn0WB+0Y/fbMr3zGxH6327dt+nYFlJwLNMvuuBDJaDkN00iwAk57LJb9yHme95pPQhZ4SaoRqiU2+zAPH4IMDkxHMckp7PGk//LXvffSrL5I/HOTGmrkEZCkF7F1cr5j96nJztf/k1jckxcZjno6CQlBreLVu157ZSiJkqHljQVGlXEySpgQDgnelpCnnnFUlmBazDFgITBLmSff7dNzLPDMQfKSW0LTUdk2EXF37KtKVU6FsZo6Ic5G5lGGYjsdRKsimHTIZpG39ahWJCMTTiLYjx56MpJBkcsHHsCplCoGbptEgjouZMMm6W7Wx9cxE5hw5TquWtxsvlijAgaZxmqd5vx9gwhQdx9VqI1Oe5sGcNS2ePN08fXrx9MnLH/2LT95+MR7uTHPHBaEDvOpsMouI6slq2S+iulRNxR05xz4LoFXw6AwlLDlV1Wq4zXS6U79+A74TX6jBFL+7SUireH/NCTowOKqKZoEQxO6+OGyfrzbNbtX2ZCwul3kKrdt2FlpfPMxk9+xKxrS/HUXFx2a7o1gSRTCYCYHjqhEQB2o0IwuklP3NgB5zKjYSZlghzUzF+2qgfUi3P33YPG2ay9h434Xm8sk6NO7mZpQZANquiTGOw1wOxylNUtQ3jXHp5/7+bbq6bsDqvVOVTALP5oqqqiBJGqfhYGyZ8pA27eq9j16qyP7h4X7/ME3Ds5cfDMdhc9XFdbg/3L29+XLVXK669TD0pN5mZfEhxMqDIqiavqs4zoBjlxmTRfEheGc8pbnpWh+dETlzUJa5nkwBqskEmJmFnLJWAoQC+dQ/fMqwOyY159hYpeii7gwxothGKyZZ1KRWm4OtRrIENSWwmthZ0QSA1j+Gr0UbdJLleTfCnEaR5Y47+ZCdhXO+OpjZN0fAdyDZOcD/GejH3waH+QW3/aYU1S++7d+KgfWtGliPm+bn4FaPYb/HCx5lIH8Ww+vfxvIYcfsbbP4Yw6Kvek/W5Wt4U/21cprOBz1ve/7wMWK10ENO3/4c+ttj/8fHAlinPaA+OhXAWiqxKqsbj/ZJmFICwTE754igMCKqrjy6gAK1fIps4V5xpVUZFqo+AJAJpD5aClMpMDjHRiBmwyJSYTBisFV4x4lK5ZeDQAxXVQ9MTdRYiMGOOEAyVV3t6uxggCwa5IrK7KgzUpMzsnACxapNmnPehei9DxrMnBPKZlrUUCWzYN47T95YVUrBCUZUoKo7OSJHRpjSVKEsAqkzChUW5DKbmpkUmBAAx8S1/hNGtcTvNA2jUzbPzuNadadYJPu0tjhOK5/SeadW4mXuzGDv2LGxmphCub5H60waZkvtHZ0iFMZiC2t0nkotIBUIFhAiRSqcppSnDIEPrqicDq1wnmsYzsRMZoRiwGmGahVVe/dAqNZbCYTTJROxW+aBdbXlVtHqJABVqTcxM9dNzk1Epu/a79RyJ0jlHaRVxZfMTqit2XIB9mjFyuMmEFGtSHzniLR0x9eetXo9dmLPWWVAVU+DWhRHZCbwPlTZfnNirOxdF9rVZh1CuL+9G7PCMKZj66NSmeb0cLyfaToeDyGwIvtIREYOKSeDDeMENdW1iDCDAFGVYha4SCZWmKakOcGakue0P96+/uwBg+UuoB/bBiy4v314+eTq5bP3NIff+2f/V4WbdQZXJSNakBFiMnJUKYxK9e45N9p50K6IdgUXgDMRutYsV5Rr6ZrqtqOKqnm0TONkeXo8OWGtDAeVkpIB8OYBSiXD2HlHjqwUz/rpx7dt+Olv/eZvfPje92Jsv7ztVXLfT7loiL6aleY8l5zbtiNOx/5taOT6ehPb+NNPfjoM0/3dQRXTMHcNabZ5Rtcitg4GKWX/sJ9G17YxBJ/z5INpUbPSduv1qnXsmJ2IrdbN/uHh9vZumsbQhDYErKyI7I99P4whuvVqBVApZbfd7XYX0zi2Tfvi2cucU9/3McS2ab1zVfc3sM+l7A/j4XDI82SGlOZqtLDf7zfrzdXlVQjRcUhpDK7xjv4/6t6tZ5IkyQ47ZubuccnM71JVXdXdMzs7w12C5K64FAmKooClAAKSCAgQBL7rjwnQX+CroHdJoCiCBLj3WXJvMz19q6rvmpkR4e5mpgePzO/ry8z2ktBi6N2oysprhIeHu/mxY+ekyDFIjIjBL7YDwfpxSB0fp/k4H3tPRYpbPR72KUYi6lJKKZlaLWWejtPxOB2PSixdF0S6YXD3w3R8eNjP8xRCEOHj4ZjnRcD90F/uLroUx753kphSyTVMEPE08DzHh8fHnDMJDakbumHoRnfWQuQxhu5wPJaixGG7vej7oRSdj9NyWNzs+DAdjl9M5VhqrdVN+GzIw+ptL+gAxIVDSiHFjpm0epdgqByaD7bELqaVGcOm7qa1lhCtZn/77vEvhp+9u73fbDchRkHkPS1LnuepYOHA1dSgBrWiVSuDjbAZxuOyTNP0eL9fHcEcxEgpgKjr+3HsRYKqCSeIlVIMrqbHSauXgYW7JFEGs1LzcZkp+DE/1vv8yed/PvT9bndNAq1+mKbjMk9LycWsIs84HnWaj3mBw4d+8zoN5kbMj4+Py1L6rDFGre7GXQpunHNxt9B3XdezOGg5Hg7HYx03IW2CelqWrFpL0bzoNC9eB4GoQY1ZYAKO4eoyHA7TvFQDEYlVg7m51goEDB1thzR0qZQjZ2W2acoi1KcUQySa98d70yO7cAphAHXEncfEF1dj7BgQM4t92OyGaqXWJdfl7u4wL6pguEhIIdHjcZmWeej6fjsc389f3n5y9b0P0eerjwbMOr/1fFRJMsaeOBBRqVXJjJ2EJaSqFe3wGxxOBjJIq3hWZ4crTgyZ5zkL8q9P8ufW+HGO0/K7Es7Lyfb26RWc3ui8whkn1GZlajXov5bKRG48HbKBKXUcaTo8aLJS7/7m3978o3/4N7mbf/rJ7X7v88ymgzBP08yMw/6xLEvLu2nVbAQXZoORsFy/uL757P1hPrhp1ZIopi4uZZmX5aK7PtRa1xpmgpFXq1Y5EVM/PeRu12dd3n75uP34xdXupU5/EWnkxMu8YITmMB+rsIcoGeVufndzeCfT+L1fu/4f//l/9X/+X/+HdFQfp7k40GrBDDD3omYibK7m2jZkRI3q4MRC0mQy2c3o29zLSfgUDntbcv0sgvGXNfomfODfVjD43fgH9CTw8OwL1y9d6VfrH88Azuf5SToprQJrrhUAmgUSqLE0Ll6+rFaKZvVKAamLuO6+91sfvv71rVyVz29/SqMiEPdM5pH7yOM4DDFuL8bL9JI6pIfb/XKYy1xSFOnr649evLi6KMuBqH784YtiB6LaHHtS7FKIV5K6LnUbOR4P1UHagjbJtda6bMLAoOOcD8c8Z7ixm5rPLNz1oesl9clcYxCRBHApOediarWiFl8WnWfUCoYnKFcmhiktSzlOpZSSC0QoBnaQVV9cozFJ6hPFxETMXLuB4QgiKYUg1IUowtN0SNFevhr7Tbw/Hg9LfZiXw+GhZJtn7yLu7m7mmDZ93w8xJNp1ceyGH/7gwzGMZcp/8G//zPeMo4jxPB/g2Q1mgMEDKHgACzeWmXmFF4ARYxz68ebwsHKvzE+D4JT+NoeDmZrC7Tc3ldRICe1/c0Ah9BT+urc8deySloKM0CXVqrXgAn/y7/781//B39hebS6316OMMx1tts3FyB1N5XB7fJjnY7GXu66v7vNSd5fjbtN1ZVHyx8cHUIIjBcTQdd02Wir7cv/l/XJXA0ueih6MQx8pYYEVZw5E0FwGSq8uXn1w/YpgQtptoqK+jptu2JpjqmVZMhWNFCSHnKubebDIIXZqFd0QQpRa8rQ85IzUX0iIudbDcdJct9227wcqvJ/u8Zb6vhvGLsUXZdlO8z7L8eLVr4zb9MmnP0GFcuHKhNBJqlTJOSAQq0Esuyu4aaoLPLuJv/vk7ePtQ7eJo4yP8wMSEjsxu3rWsibjgzk72FokzMKesRIaArOLusEhkVOXqlUW6vqu5BIigxTLshQ7hbg1xKF4tWrmlcBgkWYkSES8GsyvtN+GOmDdS7cNyDcmp7araZvB0w7nNFLWQnUwneq9njNTv8us9tfPFvplaOEXnDZ9tRTua0QhnBCcb77tefvuh3LeR52RoL/qyfxHfwrPzqid1LdCS+fDO5/1WQDra6jW88N43j9nrPT8z6bX3tgl5z58jl6dv+Qs/d5iqVUZu1U4BYkxEpGq4sTbEhERWcM5AgmTsBPMrGpdeScEMLQR8YlcATdnwMkZiHJajkEM8wZlY3Wxbp6i7t70s5nWig9VJXcOJ10EEHOUIETeIHKnQEJMEsXNfUAhQBW6IkqW7cSpcudW77TCW2u24xk8LUIxhhijhGDBF61GBjVTg6qrC4jjCZKDOyFwA3kIDGma+CFAUEp2YrJVL51iE6BEgBS4F8BAxGviDpVAIm2XdbLibmlgcjg/4SrNhZsBNMmIJizV4B9yWMtv0proJGrRkZg2HPjkgCzOcHeCu/opd+xsWD1yiBzQVSFLzY3BgYnYDUFixwOKWZndnASAb/pxyouaujULITP1JvCEJvdNAAzMIJivYhdooVyrFsc6obdQ9is0wwZ+BHZv6JSvHrRu1DDflR53QgKfwXrne3Id+zinJvjEGEI7PFpvumeZM2tVpU9zQXuJTnSq8zZlvTgggzXTBEYTnmuGAwJqOx4BOQcBt1IKcGQJgYQkSOpS6tJ2t4Ozao1JKLhahaPogtlzmSX11uwNCSTItRStWrQWEz42HetaoBWlaI0GopJVNbt7IKSQSl7u7+vtl+8gkSFA6oKTF60WZbzaXf/0z+9+/Md/igNqcM8OB0dOofXx6qjlcHhDhOHuroYTnuDupwJbJ3JGUwFbJ7Kn3OMpvFu3d80Q09olopWM15BY52YbAHNzg6BWM1ucwJwIgLkrUujuHpY//dOffu/NDz548frV9Zubx794d/fFZrjou8FJHx/3m+1wczOplh/9cPtwfBxJuz5wCEb6/ubznGmaS0rp5avru7vbrABBJGw323k+xhCYqNYKSsPQqS2bzZiiwOtm011eXNZS53mJMe0PD2/ff/n+/R0zdryZrWrVtTLZ/bA/bjc7sIB4HMcQBYuTIURZFkshdF3Xdx0zBwmbzdCllHOupczHaVlmYWGSECIBLAzjmrUsWkPtAoXofUpDz0nEbWaiGGwzckx+fb0ZhoC7siyTgViEmLRWEAmzVY0pxhDgnnOhEFdDCyK4931fSiWirh/6vhMErRVwDtIN/TBECdYPKYYUYrx/2Od6RKmkGhKGTReSCNNm6PrUtXtiHLvd7mocd4/30zSVw35e5nn/sJ/meTnmx/vH4/S4zI4TBQEOBIDBgmZ5UOqK3jNDEjM1FwsOoVGKqBR1h4QgUYgFYDNUOMdCDs01my/NSJYlptQRK81ObjA1rbWkGCWQVahqqxRRrUXrbndZ6u37/d3d/QMR9f0oEtTteDyq6zgOJKyAcCAKhCoSUkwLvGg1dW3TDhEJcwhSpZSFFpRad7utCJe6vHu/lGLLnHOups6cYh9v3u+ZglqZ5/tu6DebYZNi0Xo4HEggRDFKS1uoW8sKFHUAHNJxyl3PpdbD8VjUP+5qsA7EqghCJRczCtI9HqbjMQt1Dkgky/44HV5++KFCXRgQVW0mWl1i7ix2GDc8bsLFZc+yEOxwmAklUJ8CYurBR4kWE2KIJVscUY4wgiROfUxDbAWEIYWui/3YP+5vHx8R00MuyDmrl00nqq5KN7f56kK6AAoy6eH2ePPy4+uHu3n/7rMwx3GIgUWrxUAvrl/+7PMviMjcXZv1OZNQS1yd5Du9EprMlYNAzqHtOyv8HFYx81rZYf5kK/eVeMrbIt3STQasopj+hHsxvK77kurEjUW8ajm7mpG7OhGsuAIG6/vduNu9f7yzUovWTUd39/jtf/4b/8Vv/vDu7uZ3f/zjfaalPnDolbXfqQrfP34iMV9u4zD0NdfD48GcxEhVK02pl8028Wz30x4Ms5pLVjeWmEs1aoIDAnOr6iBIi8rIzawDuVjmMmN8s8NUvXdrTJMFX375dp7nYePjpk/b4Xa6O97tr+TNhx+8/FsvPv6n/+yjP/g3b98/UBy4C/18nGKMlvM0HYdNV9aYkdcgqHl4NatrcyMDYNpYcc/SyU8LyFNsfw5xiRpl5StSsN9o3/LSdyyXWRcxPOXDfJVscHfnp2KdZ2DauiJqYHk6+Gcpn3XD6YyGbJrBjSis8RuIwBwFpXQpWqBjOaaL8NFvvPnV//K1xeWz209KPIRERcExdjw8PNbtZlMWBlKZ/MPXL6fHw80X8/5wgOHV68uulw/ebDfbuCwPVy82/VjnXI8HXybAKaXYpU0/jtvtdj89mlHOps7EsRZaZssGR0kRMXQhatcRPOSlGnKMkjqVAAm0P0y19iFYKTbPdZnNzdwCPPR9T245VzhFSKIgQma11ulwnB8eMYywhhy1BLFVNU59x8SmNk/ZfIF5imAyNRXmXLIt2c0vt1t1HYhkGMeK/MX7h4MCiAHTAWPvD3dfkl0MMVzu5Opy8+rq5YcfvDzclB//zr//7MdvIcw2pCD92HnVSbUfOx5lKvPV5aUu5TBNqGguyQyKIcYQiRhWyfn5EG1cfbd1gJtZk8Kibxuc5xF8HllPz64UCDPVtShiXf6YZr//fP/2k5vLi+sXu5efP366u9rJVhBqobrbXBzmw5JzvX13kL5junncZ9PtRQ9yMGq1UmatFMMYuY8UkySHlWl5fFhIUacpUTfuRio05YWgkRnAQs5OfexikGXJh3k/l9lY40bSIP24lcNyPOZSNMS42Wxc7/bH+24M26txvAq7cSCpZsYkV5evapFS6zxPdS4RdL293g3bxB1t6HB/uLt5jLCr8Yq74RAOt49fSECMnAYOwWBY5gNNIAQrue/7CqtlYqpN9kWcHc4QgJZcpKd6qHWqQtuLlxdCXDqVyNNxkhCarbwt5lYBcBJh9mISpJSKQEwskQ3EZIE59JEDJ0QWBpMkCUEAEq2hpbwZBuXIXs2aKTmbtfwsZMUH3Fe2/7lSZN1v2BPHYh0MhDZRtmy7+5o5IT7t5NsE1VTm2cye4vLzJrJxIP4TsJH/X9u3Ft59C+b7jL5zBkb+U07nFwFY39r85JR3XoT8xDD6GtT1S9jLP699s1t/XvtWVO67QHXfvE5nTArPeu85jHXuxgZandErOkG1jZJEJ5M4AMxk+qT+7idCizloFVmnBmCtMy1TK/T2ZtvmDldvopXuMqQ1aOOzlKk1Jj2IzgpSjTzuhCbHpWZelaMA3qp5W3liwylA6sQNMnA2F0InQq4KVG1QGJ1QszY1ODOgrewPOL0kAENCCCFIEDA3VCUvRXEuaHeoGZGSVnI3J+IYjIXZyUASmj46gx3NR9n1ZDlCQuzCHM/7i9NP19Plbg59Qid60WkPj5XWRvIMjVnThb4SqXgVJveGkFBjPzXbRBDD2bTRgprQdivkJHJf6c7nSeK0XILOeSR1s3bVnJr6P4OBqtBScc5qs5M5FC4gA5hacpWZmjZwm2MZBDgZGew0SECBcPLhaFMz2ux8WsLPY30d2DhN9I4Qg7k3mvBa2X0u3PvqjdXGIegb0qlfuZFOsObaH2cG1glu42erzPkj50fkZDBqoj/MRuYnihIxtatEpKpBiMEcGNGNnAGHzfNEoN3FbujGw+NBPZtnMu+EhphSP/R9KiUrVBWmEGlMCKsFpSBVjTGmLqXgKSWCELWKOTPNRL7bYjMMtdiyLGTG3SgMNxF2QIc07LZXy6Sff34zHzIKKBALzM55hdYb5ufh4c8JbX72Xz0DWKeuP/mu4kQ8aK/xk76J45R/92a3Q20buS7HZ0sDENQN1UVCCKBm4enOFS6Bsd/jZz/54vXLD16/2fX9NsWH7Xa3u9hN076WYtrlBeZLtfzwcGNWQkhFk3l42NfADV9FCLHvtsxLiCVGiVFy5hhDCMxiRFRrrTV3XZ9iLEUBY4EtOs8TgJvbm7v7+8MRmwEpxWEcYHD1IKHZLXZdLxJqrea+LPNxmkrOJZf7+7sPXn7QxNGpUZodbpZi3Gy2pRTNxc1TF1JMIkFEoggTm0JL7YYQg4x96IIzVa1TqZaXpRQl1C5JCHEpaUbkxv4MwcxLKVbVApVcVHVelqoqIu1K11pB5EKxi9vdzt1FxI06B4uQkQPv379zVxIehi0zEVvOyxdffpJSn9LQ9aHv4zD0qKh5maZlnqcUx8Nh6tL9m9ffK9lKWd69v727uz3sFzJxU60tCdRGT+M5tJv7BNa7bzebBqeICJFUdS85l7YvtvPNbHBiI4iZaDGtMCU2IiEwhn7s+77ruuiukxN5CNxzP459GjqD5VKYSZpOoUJqtVyCBGGJImA281KnJS9LWYioepdLFTP2ZJRV1eHEQhzYrDZ18Opw6EqhJYPnXJm0HzoQL/Py+DDlXGpFq5ZlZqIwHZe+63KtS566XEWQ2CVIiNT13EsIyUEmiSVzKU2BDwTOOecyjdtgqo9H19XHDN5KXkhrye7BDa28ru/7cZskhtu7hzJbfxGzddSxO5uKFFPTcSNh4NjV3UWfeuaoRMXdlrkwo1YCYoyx63uW2iZc1RoH9EQcKSRfdKm1JQg4ajCzbuwBIlCM6LpGHq/wTqu743hEF6oFkEo1HJZ9txs21/3V966Podzd7B2EQlnzY94rGTWBgLWOEGAnrqfMNJwUZMxObPC2hrclRx18Kr44zTrmX18tvhGDtS0qIbRF47yQEOAtJPJ1SWkVcb7WJzbU3knd2RMlUAiIXezFOTDBly7Gj38Ff/vvfLS7wOGQi90dCiii1vlRoQIwrq4QGMOmjD37wH2/KwvePu5zrtPe5pfvhw3ZnkFIPXSyKU+Ru9QNuVZrqak2KEyDCwxe2iQtPrGCiSVnBRgJlpy4IAADiqoyuUQP0UJ4uLs/TNOhfJ62F9fb69/+H/5+Lr/7xcNPMclm3NlcqrlaDsklolR7tkqc+5X8WdGAmUO1SWQ+S9z6iZhyirR5JXCvV61F0WfBhf+o9oxN/LT6rOKP59IEp5NxwdO73J9HBWscfjqe9szP+Ulvw6TBVk0L2gCG+P37L91dhuCjY8bFh+mDX91evBEN8qClaJlrdWFwJISaa2Y93M9BJHfzB9+/cDo4FnRIjI9+5Xq36V68HGKqc12IjQgxBmpJWBB5MOW82MTlcMzTsSxLURUiWWaUXKrjsK+lq5cXL7dbqh1cfZLq8N2ON6MR55JRCxaUnLVkOx51niCU+l5EuhiHKLQs2Q3BkZiIrNZKKiMFRx0G9H0QCaoKWC0oOefi3MJzLkQGd1OUYr2BErvWnKu7jX0Ak5GpOliuroaQ6LDPx0PpI7YbiTz2gYYu7PpXv/r97w1x3N8sf/7Hn/zh7/60v0yjXJJHqMVQ3ShKZk/uQI4XlxdLq6bPxR0QSBBJkUVUle0ZW9OfD9engNK+ZSr5xphY06y+ZlLXLzA4VauttkVr+wHxXHWxT//ii49ef7R50/XczfN+vOpnzLACwlTqPJe9Fkv1zatrBCxaYkZMaew293hgSAgxSg8NtjCEIockAoVXAAhJxrGzxZblqKjOYKLY0byfj4/7h8jzfDhOe/dqsFIrly7Bm3PxPC0uin5L8Ithu7kaEIst0/tP34Ze+qHb9hex3+4fs7Fx9+Kz42fjOHzv1fcDR88ICLJ7k36YREKe55vbu4fj3a989NHd/ubu8f1+vttPb1ERO3ggFM12SMTEzkJu7ubNIYKdGYyKQBSRKteiddrvd5cXw9U4XqKyzjy3UJjFgwg5nG3gQQrVSQO4BGa4iIQY1VRJwUzCjbyhblYU3th6CiMh8UAA1ElVVRXenM3gZmrO3goQVsUbECAO43VtWDPqT5PNeWCtsnt+2oqsimlP09AJRmhFL/jGJPtz5p9fjnaa+U+7hu8A/pyRjf+U3/1FGlhfa2fA7JucrNb1XzuU/4wArNbOXf8LKvuen9S3nuB3AbNao1NrF1J/vkgbPWvPfqKJQ3kDtU5ov68gQisPVFJXM4ejqK3F/H6aXhmNpdX8h/SELp3P8gFZAAAgAElEQVTvnBiCo6EnDriRETOk7egbrGWMZqu8gswKaxvaWisLibTCJa+1toxnq5NzMVWq7BadSWKX3B3VrKq1jlgngkZrquTkBl5BqyhBmLlJuTOzMaFl4FV1XsC+riGORiVTd7UizDHGlSLHQsxO2vQsjN1RjW1NvKxbLhdhlkCRwKkIqCKAla1WW/GshiW1krhzGgberLiJV+QFTyX0jQ6DJouwBj0BK0rFIGIQjJS44QMOM2cHQUkIBqwrbqOwnvJC1DA7UnOHK4ia9n6r44XDq+uy5JzzWrAJabYAp5HsALdav4aUJrA3H2iQu51+jeBq8Bi7Nbb/6jzwNWjbz5eSViMPb3pobQVYNwN+Bpie3zrnIOL8tUQr8+sccxiew2bPbxkADWFr50pPWbLnn234rBi3NzEIJxCQjITW0JTJpuwhMXMIwVhLzVUdC+6Wx6Hr3rz4yAvmuznXg5Gaeexjou6i36Yhff7+c1FhgylUQURgMVNzuCtzGPrUp47IiQFIEBGBaZmW/PqDF32/ef9Fubu7KVr6caelgkwkEMv15Qdv3nz/7RcPv/87f3x3c4BAhF1BgFddTc6h7tY2b60Y51wLSvRcgeTZzHYyh3I/o9ntfnzaXZyurZPDmdwau5pXNf12o7fhQQSYmzqzmTHFhnF1sc+LRuqmw/Ljf/8fujCK/M2X19+LKY1jnzpZpplIcq61ZnN7uN8vy+yOEFKuUgtPR1xsMHRdCB3MX754oVqXec5lcTWChcib7RCjEMNqIaIYYkopRum6Ac61+jwv0zT/7LP3xyNgSH0ct5uriwt31FrdbJmnixe73dVGS41JdrsxMjfWLMyHLo5dJxKiiEhIIZBXq6VL/cvLqzEmUVqWpe+6FJJIiDEGDsIsFK3YxXYTgwypI6KaSz7uNc/7w/44zf1ms91tu3Hc7obsy/uH+8fHo4iAKc95WpZ+6I/HaX+cSilBZBjHkALMlmWZl6Ubh34Yhu1uWuacsxulPrl5nnLO8x/+wR/FxDH2F5e7q6tLYxrG8Bu/8bdC7Jal/uQnn37+7o6BXR/7mPp+vLp+8fLFB7uLq77b/q//278AAxkoZ1ZsbaW23Nxg4aaqepokn/SwURfVqmZWSYsUrIkVEwlriatbbUQUJqbgHl1Jq6O6FavWCjWkT/2YetRyUCXi1CXxkFIKQZaqZqaqcAiYwTGE/ftbofDyxfVmM9Za7x/3yzGrli6l1KXUdeawYpoPMKrwE3ThrVrZHIs6mdVsWmHGrm5kEiTGALBprtWXBXmBqTMpkZGhZCLXpdrjo/nDXOq8vRquX15utsGZ+81YawFss00Qv3n/uBTEkIjC4+HgZE6RGAZwAIfQdZ1ZqRGElC3DmQPHLmqFIUuU7Ysk/W5Z8s3+3WE55AysgBekQ7zw1Fu/DZevB+JSfdL50BHCWpDOQGKKqd9QWNxdDcjUj5s0xFoxTcv++HA4TITALCLS911IvOTF3ERC31diJ3etlhfkiVRxIKqBLOt8KJs4pyDpIr76wcVxW22s00POe1uOWI6LOQEt50MOIgOhuUI1lLy2dE4LeLCyGdYp/PkyhBWZ+mbzJxoOnuu18wlxP5N02qvrTkLcyc3YzZ1aTX4jnyo5vBs6kmRKdVoS1S6aR1y/oN/+J3/vRz98eXf/OafHf/JP/x6GflnqfpmnXIwdEcM23d7fP9zvHx+Wh5upLOj78fX3utv3+f49KNx//P2LfZL58KAT6gw1i4mZklU1BqBwUFOMqcTUmNkGqIvDyIimw7HotPvgutZlqvNwiY9/dYibOB/DbPVuqd1cbveTqz7c3P7F23/18uLTf/bf/S+7F6+h//L//n9+fLAvjFEletBtP8zTwsLkpjD3ddFsbjlupxxdOwQjWwsU1ri1UXLWi+AOoiYU0cBQh8OYfJVb+Eaz77jNMf1mLPCX5KTXQ/rqW84jwxsegBP/DicDpbVGYH1bYGaKDjZty21F1d3HL+KGpnKIm2l8Jf/9//TbdXN4v3wCcwQ3E3XP2cFMJF7lcH94uD8mXjDG97cPeb4PY/noDWLE93+wefnqUnV+2L/L5f7h0/1mlwx+eJjzAqthmbJa85HgFx+87LqLHQ3LYrWQC8nQK0rOM4oKMKTgEcIy9gQOu62kvuZK0+JDEA4DE7NblWWxkkuuiwpriqYV81JcjVEiK5GyeEppN8RhpM1mIKKci5maeSk6z76UJQSEiJQQI4RhDCEEDpXFap2OJRcdNg+b7SgxapnV6qtX1x/FV599+v6xe3+1213uZPvBS1JDsYvtBz/6/t/49M/e/dG/+rP/91/+FAcg5xLuyajWBUAQREl9RyWrUfMBDKGLCmMxJmYRDlCvXp3AqyLuadysAdGKLzwBUt9Fqu0ZIoqVsduoijjn3omcnISOuvxk+fLl2zfp5Ys3L/71H//Ra3ntnYFtPpSOuykvxz0uP+A4pLGZmwiFmHa7izKbVtRMefbjobgad9xziByZsKark/HgYJfZTKzYDEcJ2F5J7KGel5oNHoaR3Q/TlCQc5vnzt5+XozLzXA/T/kYpvHp1vdtuFj28u/v8H/3jf3Dz7u3+9rF2/vKDq+9/+KbMy5/96Z/Mn+Z93n/5e2+PXwBHhJfoIg4PwCPAuPy4/+gHH5Rl/t7rj37rN35rM+xufvR3/sX7/11mdlg1JCa12WASkxc71eStsz6IeulantyMy8EO+8PF5U7AZSnRwzzPIhJimJZJD4ojljhx5vkhY8bFi52axBiDhFKzkTIzBzK1qlpzNTO3VS8kBAkpURAHxOxwmKAGAguDYNW8upcqTnCwE5gZZNo4W+sOzsCnvc3zkeH+bB56euRA0y9Zl7C25JxG4n8+EMpfp1TU8/ZXALDwDEnBeYP6DbbYd4dv/ko//dfTvvtZfCtVCn+V83qOlP2lLoetq5+BXOuE2vCFs+LY177T4RLF0OINXyfSFsUxSJiYmxMhExhmOFE1yB0eWAzaFnM78b5wypsBOPF+DO5NO0tapRxBnZp6BJO7q5u5gRkgdnaDO5vxWp5GTOLkSpQdatDT1rqpIDFcnZiEmALFEEWYpJX3kTFgrmZVtQnbU9MKJQKt4BsZqhqAjjtmrroice7mZIbWe3rGNFb6JtSciVWEQyfCHYyCkwblAq3aJixt805Y+QOtW9BE/Nyw6gX6GsyxsymIwSvZzIkoQFHXY+ZKFIjJ3Yy8VXR6Oxdqad9vgvMtSexk6/Vd6XRChsYEAzOpWS0LzMFo8lpCwcwBdSdo4xrxahULApy91auuiNFJJJ0JLrQylRrF70x4fbojTv+tiS3CGf8o675qLfFoR0tPXKszdeoUSgD4qiydf/3Uz+Px6cHTMH2OuX/t7iRfg2cyF/fGWVvJhk7c9rEG4hAjcTPaVVWtWg3OoGAhH+vnxy+QMR/nlq6hAHFdHucDS8kleKioDecNgtQlIREsy1yIYqNMCidiA2ljWzrgMK2QGJlDqfNhKiAw1awTkQLiKNcv32y311/+9P0f/fEfTUeiwIxQrZKj5CIcvPVO4x63CtQWULnjKSX0tUYEqJ2Sz2f0qsHPDXM/d745CKZOTCe2TVvWISC0Cmsmb7zwFtg6SRTmwETzskgUAR7v8ZM/+7Qb6B/+t7+OUJk853lZatdtQuCur/M8T1Puu00zoyQndwih67oubZgiQLvdzsymGB73tVouNTNhHMfUhVKX6pq6LsTAIsIhxmgGVVX1ZZkBXOzidtO/eHG1222r6jIv5ibExLi+vur79JiX4/EA6NB1VWuMMXLE5XbTD8wsJ0K4anGDQFKI23HLrznnLEHYmYlT6kQCg4iYqF5djswaOWrVupRcM6tNh+n29ibsD9M0X19fh5QEonO+e/fOiUKMpdZlXh72ctgfDscJzNvttt+MEK5aj9M0l5zKPNquG8aqmmtx4xSjpICquuDlizdCcPIgkYhT1/C30PXjdhuJ0/WLA4EjIzKnNMSQ3Pmzz764ff8nAKJDCS7thiIGcdsGmDepOyJi8KnqmNZpmX0+zCfMyyBoo0WCkANgmDe+BzFcXKg4QMak0jirVhUZXi0AgdmJo0gKyYG5TGUpc1mm6XCc52XJQUKX+kBioHlaQkpDP/T9oKZNi98JEgTCAKmbqU3LXHOp1rwp2VxbuX3J2u6IUkqppkZMgSXAqWQXoRiHcYTZNE95WUBwpoYXJ1MyNXJ4xZIRywRsJDJJTZ1Xy8KhGztnv7+HE1o5gy3od0FCiAkJFpLGlGJKphiGLUFKBSGydCHqPOfDtJ/yMXXp4mocNhefff4l9QgRDpAiRoSItEM3UD/4cMlmfjzmvCAEXGw3xF0MQ1mgJR/micVDCuxCwQzaLmypxYxyMUYV8Zyzu5VSmzChMFOUEMhApqYLWSFU6JwWlumQy3FZNs7slMj6nD6QF/Hi5vP7SRcoGNBZ4d6oT0x0knlcy/JVmzEEWkF0SzP4SYKGv55A/cXx23na+xpb51mzlX5La96GyUxIjQBzUiKQsaUkDrdaFs0IZamPDLx+gR/92tXf/s2Pit1N9X2/sxBstru5zFotSKIQDL4bt0LYjZv60qfXZZ60ZP7kJ++XI2yDaX4Pn9VxcYWHAlNQQCWrtRoLrWZnRgCZc4s0ArG7gakQDCa+lCXr8dXr7e39Mk3YXePjH7yqvCyupVpdMGa5OSqK3M+hk5gf3/3+X/zO9sOP/pv/+TeO/PDv/vVnKIhbGFF1K4v1G1GgrU8OhFUZwelEn2oCZeeV4nmOvVXGnBN95xj6q+Vb33rpnPzkFvKLryvTV4EGwikZ8+zLvv03vuXbnjYCfqJbnF95ekwO5pV5utalQkH+ON8lksx5vIof/eiDu/z57eHtLA+H5ZgdFHtXno5LmSsJyElr7kLtU7m4CJ998el2w5srubruYVm6BTyVcnh4fJf1OC+Yy6QV8wQiEo9qZEosQYxj2AQZ+uRzqMe5RhESsHiuU87HWusyzUI07nZ9HIhTiuZm4th04ug4JGaO7Fa9zGVS5EWLHWY+1AXHGeRICUNCTAiCfqCuS44gwqragvG2CzFDzmg1A80fCgwKBCHCEHhQrvBairrzUoyjp65nJ3fPuQy9bPpXYxcvN0nzVJY8cHfVb+4+ffj9f/unP/mdd3iP0CV3D80hgIOZptDHELW6mgHY7/cikoZOQsiltNLy5m/RYvB2zZ6JaD+lv+mZVOh3GjArSuHeoqi29p3VMZxPvwZBrJ7v3953L/mHH3//4Qaevhxf9GGQ4nq5u6o9dHmQyCGFbuyZXEQcmOdlHLbHQ15KmR7z/m6u1dEjbLZDHHfbZeKSZ12s7Je9q2HjYZCaPS8OIG68+DTvj+/v9nPBMBxj6FMaOCatXmZFAXUgp9k8SDlb7l10V+9/dpskvd5+HDAcPst/8tPf3d8/uBaaSEo6PmYsCAmDDonisOXa1VxK3dvbP7mtV0euUY8YttsffXz9q68+enj3eDguSy6pY6/qYkpF6eSlwM1lHXA307JUjkKBoXY8zrinFAIiutDNcwZRiolHWXSWSBfdRShhDkudCwIRcWjK7wKSVqxES15KLVUrFHBoARw8eErEHEBQNhyPABGzsOBcGWirX0NLjjdwnkFE5OvuBcZuqqf0+1cWlpOn/GlKpHVzdRpl7k9g1tNzpznnl7qdkYe/TtztrwZgtXYGsL75JJ7hOL/4NL75hl8SSOsXUKj81PCN4z9z0L77xTt/2zepbV9rjZt9hqgAeLP/Onk+NubeE4J2omGbWUw9WdV64trouqFt6FXjXjVkhYmoqRihEfnZTVeYjNHUw9vs8pyz4XBTa6pYgZ/CTlUinHw62j25Lvqubk5qRC5oekN2HjsJpDLEgJYEPc8SjuBYFe+aoLuaKjkTdIXtqmrVGkOCA42ZROZYU6awZgTTaGZ+cgF0M1MyoHojTMGJT0GWQ7WawSUEkQAhFyFmURZXJTM1MjNoQ0DWrD2tRnyt60AQMDELE0g8NBSwSRSiVSeuRVfWVI5FvAlZnMGZVnTlQIvh/BkQQytc52fK0fqrQiarQaQ3eFKtmoIgMQQKpBCStk6Ye6NluYCkZUtphThOGNR51DYuj6o2w+ATGgI8n2L9hAI+/RPNzw5A1XaFwIQAPBVaNvKe4av30OkG8dV+8efeYIQWJbV+8ZaNakABEYHsNHKf8iN0kmAUgFerPuJVLOtkvumAdV2nXtXUSjM/UDhJCin2Ounx5oCMKIkZsMogFD/eHA6PC3d89WbHzkGie4kxpJhiCIEDYWIEMyhg5imGlLpxZOK6FIVrjCjZ4DXn2nBno2K+MKN6YbcXL14BYX9b7r4EzIWDqZubUKi1hI6+ktD2czXqiZ34FfyKnjrxxOL009O0LsTPr/C6gVzFWNo80q4cn3SPeSW+GXlzMIDCsBB3gaOZefUCY2Zxv715+L3fu/u7//WvCifzusy1ZBuHCwm0q85UTe3i4lpVc9YUhxC579F1fQoJEDMSkRDEPM2LVC0ggKyVU2utzNylzt1yLl1KJdtic8kKZ1O+vNiO43h5ebHdbFT1/e3Nw8OjMI1jt91uttvRrJa6TNM0HecYY9N2FTDgr15cBQmBuOayzLPWSkJuakW7vn/18oWbmyGGlEIUDrQGOkxsF1ed6uLmBSVJdYoxJC3+8HCsxY77ueuWy9TvxvG42d11t6VWNzBR16dPPvu81Jqrckyx1lzNlnKcjnePD4+HPUIYHvepH1rZOMApxiihVi2qr1+/KfOyP+73j8d5zhzFCTHFIFM/bkXibrcFcRLuggz9LqV+nsrbt/c/+fQTOVVLt4iQEMRACoNVrSjrDRVZuGUR2xzGIBdOSa2uqx7B1NzcijVXyxPZF3CwAXAmw3oNKcakJS/QxNxJCHAFpRC7lECe61Jynsu0nw5znkvWGCK7gF1B4zBWs1wK4LFLL1+92O42S8nVtKiWUq1a0TrN0zxNJRcJklIiJjUzQlGlDAfUaq3uThK7EHozzSVHIIQUI5irWjaHMIeYAvdloZK1qoYEDtjuuO8FXIhZQnWaQqwxctdTNeo6NvUYyZQoekpdjDIOgUNInQGkVbWacBSJIsWcRGgYU+wFYvvDoj47C4XYX3TJOneYWa01RPSjXL/ahKQh1fEyVJVZ3RcI4/r6yrxfFt8/LFmn/XSXhrDZjSEJEatTKXVZ6pKrSCACixC4FGUutWipNeeSi4LMPZMrXMhDxLBoyUepBfNRYVFdnDh0obsMVT0xXfJ2c3Hx+G65+fwBjLYuk7M78Xk6bqmLqm0cqa/usU9z0YoyPQVmf0kU9pTHeB5xPXHPmxUDObddSVvbGW4tpsDqyAd3BCiKVixWxKMRuhHf/9HuB79+EXfz28MXladx21e2+XGajo85d123C7xRp4cvXZFC6odN3HZWaiXI5bZ/8+J9nVCO0+H9MQzx8joujwUBRKzVTAs4tJqXluZjB1p/sawPjamaFwcs+7x9mUqIoeKDj3fXH47vH97OZb+92IahQ9q+e5jZkvRx8UCM3/2TP/rNX4u//lsf5+Xvl7n83t27kKxkuNmwTYRVDoxOS8Ua7rTwBa1a3WnV4qNnqMBJH/asEPNV0nW7as0r+2uLvH897/Rz20nM4Nk1JbLyNQLXql/19P0//wtPelkrCH969M3xs0a5LfUFcrBud7u9Pv7df/Brf+cf/4DG5fP3f25cE48akjh/eXN/mD07OBSist0mkrq5lLHH9Qu+3WN70V1e9F0MmrPicHO/z6Ucl6MZOJDIUIrmsqSQWDbmEJEu9V2f3r19iEEAyYvmRc1EEnddjFGEfV4etCyp71IUJgEYtVTlEPpxOx7mwgJhNoJZ0qxCtQQzI3cu5MJKhM1Iw+AphZhk6LsQQlWd59kdREoMISZ4Ss3FkZmEwK7c0qxVYdrBOwYTgimc43Gu0WPqB1fc3+/neX519WI7Jisze729vUWpm4vraPI7/+Y//OG/+eTms8zYUAmeJzc7ieSSa4DEqgtAzLw/7Luu74eeWYxRZ1Wtpwow5tOFZSInsPNqRE5nJOqv0NYPnUfwyqZpoXQrXKU2Q1lGHLuHh3v+rL7+4YvLDaYJffa4iQEpIW070q6amaKGJEEYTvNhno7TJl7cvjs+3i3L0eZJSwYdD11NXRovL8B8NHssVcu8h2MYU993lBnLkgkf/8oH1NHhsHRz4sipH8y9GCQkjrLZjBMdtRoCtjva7i4uL7cpBXIZdpfBgmc/7ku+LQ83yxc/uzke9ohIKZaiyfsxxZpLvrdKOcYYYkwk85zf3+6TyU3e/1n82fGNbrebUS7irufp/nh7IyJFixGcqgLgptxM1HYMhmqluAs5OkHgnHO+XV5vXo5jv1jZ9Zu5zmQeiJU5BI4SRKULIQ7yOB8hxF7IQeSpTzFGuDt70YLCYGcir952PXAWZ29mRCGZO4NkVW7BGd5s600bHufFqCkROxncXb42hbU0yCnLsoLdTgAx60q8QBMKOpU8tw+eNr2/FOjIz23/GTCwnscHdKp4PD+PEwL1NVvDXxBK/JIgVs/bcy7VX/rO58d//uB3P6mzphVOtaPP8azn7WvPmDWjeBJa5a5UVXV1ZhN5+tqTwjxwyoUZN1FGZ2mFXK6qZhRCW6jX5Dla2VStxuscf4IAnqFX7k1Ru91czSSvce7dLXFyuJmqO6ByCnqcoHA1Q5NOB9y1AuTGRCSQk57XGg4BAIsjNP1581pqrcWq+emOf+oWp4jobmshoK+wFU7oTrXmE8JqqjAQjPQZoOGr0TOdaqLNQZWlyXcTmaNJcsXAwiAz1For1CmJtk5vs1QrIWzfRX4SkjrJmYFXvIwIjJLnU/gDo5WqsOKUwBlkOONjXx9FAGkrvaCTqDYEzMRlZUjQat1kCgILMwRqVlvJJJkbVaz9T9JgyCZEcoYfn+FZTnAt1b+aEW3D7vld4O5G7n6qKsNaOd6qjc7BLbUq06/OJGeu1XnCaW9otLrnNwSd/2qQLloChxxOzOfh2iwG8By9ah/jU6+Kk4CsEYjcVp3apr9JvpIbXYIAYJACMCKHZcMCVBGJsfn0GXmxYy1GBSMuX26FJIUAUmHxFusTNYNyEDNLDGkc+92u3+1SLnt9OKZOYhxz0VJzLhUCKEAVDBEYZWJcv7iepzodCmYgCoFrUTIJKeisDUJiW8Xy2h+rssczAPTZYnl6TO6+Bv0rHvrVKei8z2vXzB3Ep+Ia4P/j7l2aZsuO67CVuR/nUY/vdZ99G+huPJpokSJpygxZnsg0QwpHOELSxBMPPfBE9t/SUGENHOGJwiGFKNshM0SFBYIABHSju3G7773fs6rOc+/M9GCf+r7baAQJSST8OIjGRV9UnVNVJ8/emStXriUiR1W+BSujRf9yActVLeesKhxCThMTgiNBev3Svnz15vzRKsbgXPS+Wa9qtbxaq3NuGHrnY5pHgq+q2mWOHmTQsvTBac4+uOjdqqlVHWyOwYlmnWWa5lVbear74SApO+KZkmRVpapqYT5WGmMEqB+GYRju7m4Ph8k78h4xnsbK393dzmkUTTfXl2baNqtpGCWl9bp95+nFqm4oVgYRzUQWvW9j5Zk9UfTBgUW1qproA5MHwHDBB1859mkGsiQyjaGtY9U0TVNvVXmY5zllRgy+aSOZieS077phmuac4d2huyWOSVSyJBUBVVVIadofDruuywrfdex93TQuOIBhcMTOh2B0sj3t6dD1Q98NSQZ2TDH44HMWDrXjCuSY3bqpmljljPWaFEzMZkweVAxBDCoGMzNyS/cCWTIVN46liUKkRWO6uAcs1ewyQW1msuikLkKPy6ixLst2AZDNmJhMHRA92rqqq0hmeZqnadYsTOTYp5zKJLmKkZFj79kXHuJ2e9L13TiNKWf2LrYVO5JO5imLSCHwTvM8TmM/9OOYQnBqWlUVE/djvyxoS9rJIPbeEVxRMlRBNpumPM9JBUxcxbqqaka1Pl1fvbkc59zU1K79ehXiipw3Ymkax07a6LxnckrOqtozs4lLitWqZSYzBB/rNlaNTWnXdQrTum4cOxFJKalYqKPzXDWLWTiFsR/T9tFajJgo5zRO2Xus1uH08Yp9Vhtjy6xcJyZBU3Hbroaepmm6uzl0qVeyMaWMvl2xkeNQOWSac1kbmItzH88TiaRhHOd5mMaUsoDRxd4Fqqo6hoasmrrh0MnhMDmiug7zpNCRCQiiLvs1Hm3OVu7s+ufdNHxyd9svi0vpNYkakcItbl8ZMAOzFc9jOpJ8qCzt6X7Tecjifkm7w5bB8oeVjI6r3P2UP5ExafmaYFtEEqz8TalPbOlvZBPvyjScsOeTMzx/Lzz5ZhXX883hs9iaq0DBiWRJMhzybs9siZ0qws3tTbYh1lhtQtvG9bpp13RxUa+bMxa++uLqBtLfiI44u4jTYd7tLLD3rk39bGaLCGX5NKIo0pkocjtANmUxo11/4xvdnIdn26fbx9HccLe7EsrrcOHqFXx7N0BzXtWxcpDgP7/6Sc7DR+//3vsfPv3bf+f3+5t/cftFlzo1+LZtpr4rRip0bFUsfnxU5tKJQaKAO/bUFAbT++3d6EHvctmO2e6170oOdN82edilf1UcQeUXXilHVIF+8Zxvn/5radVDfNjRr/CtTfMrLyirlVjRhwVAzOYAEr/yzx89+sZHz5+8d/H67tPke8cVxAeKCnf95othgN+s2Fu2cbPxPshm46qQnOu/+V775Mmj6GCSUJMjvbm5zkmMMCecrDZ1tZ7TQGTsVhzaNE3TmIdh8N30+vKqrn3wDGMT51zraw/OzotI8mRt4063m3XbzlOeRiHzjDbCBYTVaiSGc4HIN02sQpjGNM8Gc0R+HvMwzmayajTW4p0j5hCMKEMTs/hYOeeYcs6mZFXF7DzMWWlQmIMWTxVLE2tdOjKLQEIAACAASURBVJjegDlhzlp8l8Y57+66lOfTlZqoJ+7udp7TZrs525w45X/1Rz968ynQrRhtGpOrqnnqyCszS8YgLArLApK6beacwK7IHmXNguJlsCwRDjiqExXOfRFfVKNjNr/MC/9K4beIQCx1x2Jvs0AQD6dQgFjAGdMh317dffrxp++9eP/N8Mp53q62IJ6G5Mx7q+bpRiBVGzz5aUjTPEmyaX93+arr94g+1r6RYe66YU2r6nwdQxsr+DprShBRFa3IbWJjfk3talu1p1XSyUZFVE8BzGnMeU5NNVcx1k1TxZjHEWFen6/W61UVgmlWlXWzSl1/+2b3xcc3/StghseK0JAMmtSMXKw8opnL05RM85Q5GDE0KwTOwtXr3b/87I8RcbrZfPP5e08fPYravHp1DWIpzkuLeodyGUFYhGgBIHonpJIEEYBhQE115avd3eHkfIsBkhKMimJ+3x3sYKnLwfkxTyAkl3zwzG5VraqmKtzwOaUysuPZK7LNymDNEK8EBlHbrFNOktMRfidic1zUWlC4GaSKouRedButKHUsTKu3lpG3GsW8cEysRBk9uOEdWSxHvGoJnf/Xw1e/GmbyV3H8+zGwfgFheVu2qeAI95yg8n1+RVjuFyCw/28dfw5jC1+7r/SQJcE5F2MEoKKqmlMur/jK29UM5pw7ng3luTYyR8RFwarIZ5Yl2YEcueAKksSEYRwWzSPH8OyomFGXQUDKIlChgjwsCPHx2TMTMaipZyZiV568I6P6yEXTRZbiXl3ezDSJNrWTLCYQzcTwDszFmAwKM8uOPHmAyZQlZzNh4uAcM8/DiKKAUZwICV5JBVj6yZLSwvwEwRw5dsRc9H9wlDhXVVEpBrllZBJMIspM7DhrVs2LiAEVpS0zgytJsTfLJvl+6bCFzFPI8lhOwo4JTIF1nuOqEVrgPVvs+Zb/qBlpEYE3XUA+RZmxJwOTkVoRdyof5wi6vR07b03YvR0fRU+qSNw+2CCqLd0AkKgqiFXVRFGmexhUbLHTbGqyuBMpAUzsnaOjILdaobjafZAvMuCwgoVR6SAs4t1cAtWsiImoWXENLIOZCqOiz+tjKKflh2fkHulYxJ6P3w/lt1oucBR4fICljqlneW6K7jyBFg0TPequ3fNDcc8seqhcsKS3yxayTLyX76tqmmE8yyiqjpeHTsw5g4OfhzSPCQYGUzaZ1VQ4sgWCgis0TSQlcrRw5cy0gDezWM7kXSBX+bpt25PNyfmjzXZT77vLrr+TGFbt+urNoJpEpcSq8+wCHEHNHGG1Wk/dLIsDNJOy5RTIRxczp4LpGZgBgS5f862dsRC0HmY66Bi890IQ9/1Jgy0ejsvCYvdrW3kMtehfEQGSxdyCVBYymxaPA4ZzbOTNLKUZsFWz6sZRFbFuyNswDddvbk+3m3q1Qo15nJqqHqau8tGvaBp7S2nse+crJgMkZeQ0CYzgnYuqSuaC96tVS6TEqalrAmnOaZ7q05Pg3dgPKpnZk5EqQoxtG+Yq3d3t05z7fsgp5TyP4yRSFmCtYvTe9/0gWeoqwlgUIcY0SrZ0sj67vb7jM3bkcxIR8ezrWLftmsBMLifNMCY/9mlCZuc8x7rydVXXVXPor8dR50lyUiZXVSfrzdaHcZy0nqa7ux1TDK71jpqYt+s5Z+rHNCdxxOwC+yjI0zROeQZRIy0RZZGyds1TxpwBC+JVaJ4nVVmttpu2KTKCWKaniwR+G5uqH6c565gmIq6rahptGvq7u0NT7Qj+9evX12/6LAAJEy2zRKbFaj24hcNiAhF1kZfFoBQADBiGfixAs2PvHHsmXdYwfXudOQYOYAZTNiZYPwyR1DFCCI5Jc+77fr/bD8MARzAjJrATNcliSihmDMSs4phjrNsm55SYXRrnMY0pz3meswiBmclUU87TlPoBUSU0VnnnvZ8Pc4H/QGWBMSJWhaoxcwjRTMZxGoZhGGdVeF+8BVklPX/38X5/izsMbC3EODgOMcQQ0Lb1JFPTRoCSEMxiDN65cRByWG3iMAxqcL6t21A31F0lUytS9C5EmJvmKQuSmpqM00Qe7aauKj+nkV1m7xwzZqOctGAsNBkkSSdgF6yqORgarp3neRr63XA4HOYk9doPfVZLBAmxamvWEJEsTcmUABURM80i7MFcNKSJDY5w2Ol6y4FjG9tBVfJ42Keb2/l026qFm13HpnUbrg43vraL88fbuF7x2gRnr5u7T3sQwGaWoVD1xZcJRqZAAuDgHEShCi7jIMTkCJYsl4WN7vfIsgKVjosZqJgTFsyHsTTUjiuf4V4ZkK2gLCVLosVm1UBgM28qpb9Vtvh5MteAHGHCXKWLczz9ZtWc6+34Ot/Yty++TXDZ3L5P+yHc7fiLn/eHO8mpV4vjNB/6m6z9doMnT0/e+9Y7F+ehqnNbNwwemkDnq2F/OSu25+u+s911ik2IdbPv+sxSOv+kREokBiHmAKhAkcVETUw0X99+GbJePFk/f/dRXOn14QsXXZpzFoxJJnWzwfkqMWfVnDNi/MEnL03qv/Xb//lv/80Pf/j9n/7Rmx+OBsbMM8gVhdD7omoRNS3tzCPO40rqYFrw3aMYIzNUlw7SIjT5lmMp6IGq//WD8Nb/UUDke82GY8KFJQOzh/c8tLfeejuV+0kgIyUjI3sbw1p6NsdeFx1H6alcZPmIZZc0xtLFN1NjNThlAyUI0A7/2X/xN5sL/tEn378dr84fP7t8dTvcTYd+pqoa9gA8CRtlFXVQouQ8JZ33h+nDjz5cr7eHw67f9XXj6xBudlKFKpqN09i26yqse9O2duv2NIb1dLi5urvp+l2a8jBb06S6QgiuiquSlU3jJBg1D+tNWNXV2faiis1+7LvBah+bpgqekWXTNsLqnfc+QrnxU5qF4ImYyR+67m53mOfRxxziESNmz855OCPf1ivJMBq0HwRGyp6CqYM5E0fERE41AwoLxBWQmL333A+TQQEdpn7f9SmNMbjD/oa1eny6enNz8+33vvn84unj5l3tN29+BBiiNabRyDUBQ0pMidgpYFngiZkN2jSNqDrHpjqmSVS0EJgLpSabEvhI+SeYcSk8SgoJI3qrR/+Vo8Tc14O0NIzpflThlzb+gDrENE8smA/4yQ+//Lu/87ewo4PebpsNOff59csqrNm8ZNSxirE11ZQygCpWfZfnCZrRtm30Tbe/tVHnylSh4KQyIsfGq5COMtG0cU1VVaen2xffeHx1+3FKYz/0w5DBOueEMYPc1fWVd45Vnj66COFkkJ2PmHM3Db1lC/D15uTq+rB/0w/XwIi62kRrxjwllRjq1vnDrhvHrtmsnXqCBefynEfNMYST0+1hd9OEZrSJEt1+tv/w/fbJ4+cRNb7/p2aWj6UYFqCbjq7tUFXvqtjGMU0yTAAoOoO0zbqK/tDdvf/tb4bK3+zuSGEOBE2Tjrtp7nJTxawZisw5BYm1p9U6huicSymFGFXEgMhBzRWfcFbizEzesfkYB9isuUBUHt5IiXUhWQEqDyMcODINSkbE3t/3UR5aKVYWFqIHg4hlGkdLdcB4Szf5Hr36/+fxl4L2HNf3tw58lVr1HwytLdUgH2lAX+Uolf9xz0JiZlWdpuk//iv9+ccD4nP8ePef517T+s9/79tJ9i+9B/d/ef8FmXmYhgJcHF8EAMxwzrFzBCq6s4vHkQGEEHwIIYQwjqPdIzJ6vAR/DRvj4xxiYT0SEdE8J+8DE2vWPAtUvY8hBFExiK+j925K8zxNS7XPzI6N1URXpytRESsdcoXz5ow8LWVB+ccVkYpSLyg5YseOfNcnLmM2xTwUYhBRYceKQvwBGPAgB+c8E5MSxCRbFWoT06x5zjkp5owMCMihnEyKYlV5zstPWohNoFV7KqqiWUxBSs6IoSSSZjBCE3xwAjVvmaXwQtmR8945JyIQyWImdt8nZCAET0wyFYepJaFZmnJLJxjq2YqwLfP9dy73Wc0KXMhEWURVSE3pIQxSzsTL3BrIzIp0qBWzxQc+XfE3k6O7W9HKyrIQXlEUxxiAmBgsU84wY3jHlTXS23AzYlJkLL+nFrtDmC/CBIWvtDyMyLkEfbkYvxXMRuoblyVLFlUDlNkfe02mprCiRUHBByLSYvOBBTpiLk3cYuhkhKJihoXwdCw//DL6h8WvEWRk2eVf7M4SmMDOgdkRiRbMSdX9QpECAN477/09bzFbomDsQeyIDcQusJgaBMuplqTaO4IjQJVRVTFUMXBMt3m/2wXz+U7qKlKGFljOKQXVaOotMdZn4cX7T2MbxrG/2d123dRWVLE3JVOu21NVfvnzV/kgIPzB3/u9rr++eNTGGj/5yY+DP7m9HQ+Xdrnrm1jnSU2yC/bs7IJ4/of/3T/8Z//0n//rf/VvP//s1s2VZHVEjgC1LCmEgKJEx8jQgocfE6yHlepoHWLLFmuAol03di86c5z7XxiB9HAOgSmE7C3bFYMvotCOzJFzDGKBZZuJYEqQMtfpy2gbqTGYmMnIMIaV+/v/4A++++H743i72YRhvL28+jk5JQdy9pOf/UTUYtVuTs+Zq+4w//yzy8vXt1XcPnr89Ic/+nFTVz5YSnPKePy4vjg/NUmb9frp0yeXl1fXN5dts6rr6uXLz9/75vtNs7q97n/22Y9PT0+fP/vGZ59/aqrs8MXL7unT+M1vvChBsmqay8vXxd6463dqUrnYNuvNettUjWf/8b/72bOnTx+dXlycnx0O+2ePHjHHzfbRyfasDA8yu3mSAooRfAjVer05PzvfbragwRMTIaVZcg4ueB+YKOUyEi3TPPX9ICqhcr6O0zy/ubn89MvPX19ffvnmi37s+3HIaR6mcZ4TsYOLxCR5msZDyjDAebSNW59s4Vzfj3e7w80t/sEf/ie1j/0w3d7eHPo+m15eXU0Jq3W9PT2p6yplTdOck8xjXjXrJxdPJNknP/38448vT07acZBhTnMGETtfeSbM8zzM07gEAhG8CwxYmbg99l44eCxgQUktSu/RmMkgpsqOQnCx4jmlflDHHENk8pZVptmDU5r/m7//h//j//Df724vLy8//8nHf2rIF08eiWnS+WZ/I5KbpmnbtvK1JOkO/W63f/Ht71xe3bx69eX17WXWtD7ZNpuVmKQ53+x3TO765u7qen95c1vX7uRsU1WVqnR91/WDKkKgcbZhQAxYrVoinvp5nOZvvHjqnHv55UvH/OjRo9Vq9dnnP9/fzJJdbMwUN3vd1Dg9PTs9PfXej2M/zaMhjdM45/npk42ZnpydjPN81+3aZlM37fX1/ouXt+OEkxOEgJPTerOtfYT3zMy7XbfbDUwwBHJxnLJCzx6dxwp33V2s3GbbGBLCPosSEGOIIRIh50Q8P336aLutDFO78mkc06Ays0wkOUgOn/zkil3zs5/dnD9ateu6Wof1ec1+7vbD3evDOCVwGJOdnl34EPaHQ5pmIl01kUzyPDHp1Y2en/Gz54/W27OhT1++ue278eZ63M96dortycZH9+z547jSL19/dnM5nzftk5Nnm7hp/ep//Z//5XCF/SVq8RWt8xTnvpfpELyLsU4zpjHBHDvvHAdPWFjEGZSPgn6mR1+To34WFEbGUrS1ls2F3+pyIwQujhpMxM6xwZAMWYv+vUKMTIlddCGEEAQmJsxkQc8+2E64o3o4ecrvfKf91m+ers/s7nDtOJ+fnL7z+Bv9Lv3oz179+OUXtwO+fAWZ4FFpqoYRlXnLcrKuVk2YxsPVzV1T44MP8PzF2aPHp89fPEppPOwPtzfD4Tp3l3z7Or/85HD55ezVa5djDDZSmrh16+DqnERNjYUrq09cPx9m7vMZXnwXv/P7Hz5+fhJbHKbrl5efqc/mXKa0OX3n4vGTH/7Zj0IdZ53ynFdVg0Eb+CC+1vDt59/73W/9/ic/fP2v/+lP/8n/9M/bOvSvEzE5sGZVQfC158BGpiyimoqRkJgXZeECM5XWh5EDQaAK08Kbc8YiNh0NrOlXq9YIZMyu7EKqCrLgg5nlLFbU7Y9AggJQC1UEIPdAU2FNcRkKUDraWZY0EqZLlmmAGVpXIgBCUBB8ZM/MOSeAqsobIeeZqMTIylxQlu0L//jb1d/7b//Tu/nlZ29+9vpyb/rozWu+vRoju2mafO0vHp/e7q9v9lcAeIXHz3F6tl5tq9OL1cXptru6DZ6d53keb/fXSeYY4TxWTVPFVX+nwW+iXweq2MI/+sf/R0tsXRxSRmXbjVOaV+u6aZthzK9e7jEBW3zrg+13v/uuJ8iccjK2Smce7sbu0N3dXU/TCIfeo/DnijagNxjQNLTebNfb9fZ0c3d3c7276VJOTp8/e8pGTDz03W6/j6HquuHkZLVarZ1zIJpHteQOt+OrV9cqTU40zYosiMA81Wd4793z1cZf3b7+3ve+EaLvhnx1c92N3bvfeMdxHg53lKeTZvXO2dPWrb755MPPv9/9k3/0zz753weqiELUiRxHIoDFKBsJOTUuOZDJLGCsNitmnuZ5nqdjLx/kAMAUwWpNoiIMeHIOzsSmceYyyiBLCaCLZu2xwgKIKOX0dQzrmPc/FCfHUbOvvGbDq67r3cZba7nOf+O//t32STXY/vPrn3z5Zvrd3/vuzz592d/l1XbaPkVY11lGYl/7NlD7+Y++3H2JtMfmdPPo2fMxTTevb8fLDshg/MEf/pen55uXL3/+6vLnZ4/Pt9vV3d3tbr+fpvHQ3Xz0G8/6vtvtxjkTh2ac5HCYxjFhxvrJ6oP33v35y8/OT07XFzHn7vNP3jy7WG/iat7l/nr88b/oQEACSXQWXMmZsRjkQvk4UnecVyj/rQozip48XGTJWZNii3eevvMb3/1wGMY/+aM/Ma+YdZ6VnTcly+SE2TiQd2Ai7LqdIXNLFtlYEPHiN148+ebjd959fjfsuqGb57k/DN3d/vWPLqGg7BpuUz/LIC6wmopkBHDrY+TTszMfw9XlpYPfbDfMtL/Z7XYHGuGVJZOKwesHH76fkMbU7/eHqUsMji5AIbNIzovwzdLHd7wwygter4U7ttjpHmMGi/DvQ9fckSvzHaIwLfXGMhVBy/iLLYKDb40VLkH0VRTibSzibejm/up/IZ5zj9V8/b1ff9kvvPKXnvbXQMvy+Cp6Rf8+Kk6/4vEVJPKrf38vXo5fy7d9+2N8HVD71c/wH3ZFYCGaLP2gMiyGMid9fM0R+aBCWxAhopTScl+OxHl2TK5ot9s9SEuOio4wyAzkiMFFRF1FTbNClYyhJlnIkQE5JzUxzczFWkGO/SaA7gcbS4i4Y2vqrV/BzBSW1UyVj/AJ7kdMzYCsWgYBS+qgpMuLyomKLp5lsC9WgzCbprkoqqsAsvwc7BbyCBn4+PZlpExLbgEDTdNkILr3RjQq8vVA4ecU6A3FLbE07SAwyYmyZyeGhcX11mNrpHTMhxchLcO92mCxrsfby8RbIaJFn0v1gfRz7MMUuJ4KFev+w1hRmTiGyVG6HViwq2W0D0RkCrAuOfvC7SI2WMZyhtKEJiZSZjZyZaR7aXf46I1MGeYNjrUMf4PZyBaTIFt2YlrulZmYmkEpP0z5LfOjx+jl0kvgRbvk2JYgYBHlvxe5UhQgz8BY1JqoVLwAlcKjkHpk4dwer/fVB2xJE1hVj0LvhcBt9w/aEjiGt+iKplbyVTs6NbIHW9mTi539QwM2m7EWeSwSVZ/BgZ1znpwnL8jlRpSYsKMKO8iYMfUyDiM5EDi6MPHk4GOITGHo8+6mU4UzJ42Y4fb2cDjchaCnvj45Obm8HNarLSZ5c9X18+B9BRCJwaiMoQ7DPBwmzJCkECO3bGeOfGF7liFOKuItwOIuACPiQty+h7Me+tnOjuhVeWrt+LCV1y214vGdpWRgekDBCv8WICgZeGmsExikxgv8ezRYKDSwwvhjEvr04y9ePHu+2mz6/c4gUDp0O/Z2/vjkZL2aNDvHwZkLrHXVtJWPfpqHu9vbnKDBfB3qKhLrelXXVZgH6bvu5uZmnqcq1iFE72NdrwGe53maU8roDsN+f4DRPEvOvQFtU4cQgg/TOBJRDHXOCWIMDsFvVttVu67jKnBg8qcnj6qwdlwHvzo/ay8ePTPywbXsaqHyS7is077r5znlWdUohN0XX961qyZQDiF47x1z8H69XrdVqJu6CsGCdl1XhWZz8TTlCR4UmFwX+2m1Ojs1GqbZxyrWdc5plSZVIVeBK5h13d3lMFgWH+CAPMt46OrVuqlibuquG80KZ8OquuLgQ1XHqt7te9EsSayCd0x19A6OpPKBib2n05PNO8/mYUjEirIOMREpOw61B9RYLJkq2dEagxbqoZqZmPEyLYxjlckLlQEGkJhJsqw6pYWxEYJn5yXLOA/bZjWO3W9864NvffdbPjowBOni8fmUxljHfurHaej77tAd6rq+wAWvHUBZZUzzOCYzCrFq6nbKk6imeTayOc0AQojb7VYEiszOsQsFcgsxrj3f3nVg57yxk6xIWYpUuRnGeQrBs4PzTjSnnLz3VSuSOUYP8DkPpjqMB9xZjBURw3xKMvaaMu5uUt34m+suW8qiEyeiyXs6OY1xnE/PKyarau88lfaPCI9jTjPYYc7JoPNs5HmcEriQHsm40MTgGCrIKTl267bxbQNSmeVw28eo2flpsN3NLnC1XZ92+1SF6nTT/vSn12frRmeeegsVZJqzDGyyblvVvhuSd14k+eBidCJkYiLiGTFWVaScD1XlRDANKWdtmlUM9TTe7YeuG7A+VfZh33cndTw52Y6HSyV045Cn/KZ7/Tu/9+Hrn918jrurz+exu2W3rjxTdlMn09i19bqOjQgky5zmWWeokEddUazCmOdSQRwXPS4KfwYj4yMaUagV90JryxZdtoZlN1PNZipIOZSuknMuEJkjSVPS0SgTGxH5EEIV+/7QPKGn33z8+Btx8wzC826cfO3b+rRZXfzxH/9sPtDQK+MUOleuH4nTDJ0FiadpCuSd1BVqAm15pjzcvsLY33R7q5pVqOCbpprynJTJuxgVZLi9uco6wcgQKIBFlSTBMZPNeU55ToNNMrXnePKOe/wsrtfkfDLKZkPpy3BAFXwdwZxjdIJ0ZMpHRLVMWbRP/avbzz/+YhvW23c+2rz/cfXJn01oYNmyCHsXYmQEyzSlXCQXIEpEjiFkRKUas5LgUtGYJF0y33K3inTRfWb0Kx3LnnY/pcPklpSMiI5MrCXfwC9QYO4PwuKHU2xzufjtvPVBjtTkMmVCABuRo5KBGdQEZnMWYlMydVqvQ3fbI8aL5xcvvnf25AP/g0/+TdxmJSVXjwOl0aeBks1mqjrf3dwOY+cI1Rqupk17+uLFs5NH667f/+jfffKkbdmCYwdyYG8yJ0VOAM3TbOPAtatmG2TsoR4zxEiH5FyoY/TeREVF06x5loXmJpiGtLubAszESELq58PdtL88jMOY5gwDB5w82e76XlP2ddM0tYrM83Dopb/Z7VZz/3hWyMn68Srwfhrmnrp+T4bCsz/ZngDkfW3KyZBTPuzGNOg8ihm1zUo8kc2ZUog85IkMpuy8P9muvfcg9sGdnGzbtq5qL3NiaBUrz27dnNa0ev3zmx/9X6/muwg3uMAMJFUjYXNmBGJyAlUiHF1EARTkkhhgsN5bT+tyh2HH7QikRTijcFWxdNixDJCaWlEItrdi6JfFFr39Bx8j9qtkA4Nj532AsmVFxrBLVkln+3GYoJjT7L13oXgcxeiCwURyEnHOPELwKTGyaD92c85ZE5wBDr382Q//7dn5aZapbRsPXL56dXl9nVJ2zgfUb37+po71Kq4bz0remaJhJspe0tx9+vKTeZ4SNUnUe1qv4Qg5TWM3HW4SPCgD6kmZFGYZZmbFxephzPdIOaJi974syal0Ow0AFJx57Mebm1tVXV+0l29uaxeJsompgZkJTOZUIZLrGL3ntHDejAgKnKxPT07Orq5uXl29UsiqbdertSaFu2Q4IpdV05RWcZ3SrJLAIHIsJEm6vmvQxrqa+kk1m1E2KYUSU/DkOBA8ukNnQcUykZGHV0fERaNxGQ5dxlGIoGWehI4j0HIEqu4RhoWI8FYg3CtQK2BYcvGH8vAX6py/BLrSX+bxH0lv+ss6/NvEq7+649jkB772nQsZ6uvw1q/h+AsRxL/sywE4oldHQ/p7FO8eKQIvmgEFwDIzzUfJgWVoa8GwAJiJWRFNhvceBCl2SYUMT+w9mRYEawGDyxVDCGaUsriiWu3YtAx9PTxlaqoP2d6io/TgiI5S+ZtmNVO4UplQYXmYKMBFAcFIS4pYqGFMMF7ox0Wxu0gWkRHEYJBphjlW55QYztjBylx7IW4aH5urZkX6qrihqcHSODEXi7PyixeU75iF0JEoYsRGTK5krsXx3UVa1iMDYExcvrIqFqX542Jzfx/tCBthQSKXJHi54VYuv3i6w8D+4VlbLMBpafeVhX6RdzIq8KMZeFEFLEiDFXHyUhgaTLIta2eZnii2vbBl5GVBcKgIabJz4nP5BArjGApUZc50eSsMBbvRRTO/0LTY9MiYVlODMsig5S30NvvvLUCcmTQXQbIHAQAiiB51x473CCgEtEUi1o6CVwt+dPQOKBH8C4IEJQFR0TLGaveAZUEweUFomEnECvq2oInH3IWEylbLWgDlUn7fw39lvEhQmg9EKpY5mzciEpPAgRhqEFX4xe8AvNhGLvdVDcaOOfi68sk5xxyZ/DxP19cDF7TVEdReffnlod+FgGZNq9X66mperzc2zyBAwAw1RBdjDFWogov9frzaDdClQFtC8L4VcdQOu8eWjvkFHa2dl+fiHskqf9jRQA4PP9WyGR/PSkd22v2xPDiqyw0nKh4KWDzHCQQ2UiJesG7giCouys0p5R/88Pu/81u/+eTJ6WF36QKZWd8NxtPjZxdNU9vUZ5Wu71br6uz8DAhpspcv37x6QJxGqAAAIABJREFU/UYEKc0g167aELmq2KBTSuPYzXlS1bpufAg++KquFJbTnNIsim6YzPT09Lzv+v0+X5zZ06dPNuuVYy6pSF2F7GiCrf3ae1dVlRmlWdgH9v7J4xen2/NHpxcn242aElWSbddNX7y8vXxzvb8b0mxDP/fdmLPkuXQdKIQQK++UfXDeO8cueF83dVvVm82mrisVHcexbqtHJ+enj1br82Z9sg2h3W4vyFcX+uz84uJmf313d33o9ofDbp5nctG5CqpsktYnqzrVdfDBJxF2vF6v67Y9Pcknq313GKXScZyHaSrqv+v1Cbvq0HVGlBNA5H1d1S6weGKAfAhnZ2ch1D/5ySfMy1PPTl0wx2Cwj15BwopMklSyAmAKzDBAVZabXYLHGAWDL+HpiNn5hRljpRe5ZHNMIYYQwmG/U4ff/b2//pt//a+BNEQnUHMKlX4+jGk69Ifb/V3Xd93Yz6L7wxBcpaLk3c3tnaiGEFebbdTJCHCY81ws7URzrPxmuyJPCqiKSM6qTIjeeYdYBeeR8zTPalDnyHsaCMM0KYQdeR8UliTXbUPOSzZmT+Rj4GGchm6epl3T1E29YuY0a9dlUcAmH/w4pll7VxEwmVEM4eRkHas+Bg8SolItK4HYsfOBfTLyKec5Sc6wpL7bK8U5z+R0nMgoeadV5dq6YvIApRHqQET9PIjmWPFFCszB84qgwUXT0Xk+PVvBdo7lME4Uqrqu6spPquTZr+OU035IdYU5dSAxIqIsllIWjj7E6IJr1s57n0WHcRR1q1XrfRimfLnv5gwgE/th3K/zpqkaMhq6JN1Ycerv9u/91ncqt2mbw5fb3ZvPbw+XhymHENz2tCXn5zlbElJiMvYuuhrIikRQyaV1vVQPRqBFax1LSoKHkXxe9u2HDUTJlFVVlUhIYaZWw2oSv+zN3gwp1NFiQphBKjANQ444PV+//9E7H3z0vD7RFPbNCfkWh8P+8qq7enX7J//mdR5Qx9YCTWnWBJk1TwnCwXnng2YZ+9HmaR76eZw5oJsgb9CPt+3JZnMaTs9Xvm6iWBXj6qRebdvmxN+8Hr784UFmM8mWZOxmbyHEQAbRIVepWWPl8ez9k2ffa05f+NVJcDELDebm0FgVHAfHwdXRWIe2QjcnS2JK2WUnEME0Ti5h3999+uqTbz7+znsfPf+v+O988sHV//KP/7dCY/ExxFD1u8SzxqqWlEXmZcejQrWy4yZzzPxpGccqeQmTLLbGv8pxJHiXfpgRFoeWY9dwoQyU6fbj5nJPwf5Kdn9sZz1EwP3EvBYS1lsvlqM4M5XdTUSUAJAYQ1nJAUwWkKuMc/veR+9++6NvhUd2mF8f+skB+4Ncvh72d/n2DajPcVuDRXQ+DP2syTdYr9tHzy7efe8JR7x6eb073MqcX3XXm7ZabdbGEIEooGBH02xjTsMdDzzIlIa70TJjxARBxmrdnl9sh/mmmMFKzmRUV5UEgc8qPs/MTHnOqZ93l/3NZXfzutMEJkQHH+FbGvaigghvrpqHsR8tiw2DURju9nPdVC++cbZqW6PKJN9OV0OfmNE0SPNsYvM4D4eUkqVZ93fDMGix6zk/qx1FH4a+79jpQJgzTFHX9eakPnQHJQOIfahcPQ/j0HfItm4qZ/F0/cSl6qefv/7j//P7d28AD8dsmc3EaRHsVGMBlMpI4LHZCSCLeCpOkUsPj4vOxDGUoLagVUqqanr0lPracU+o+XPitNQ1f0Esg1JKZiYqpeTZ73Zu2/rGBRdDNRPgHfkA8mD2IdTKVhyl2Ht2LlTwMeU8dV0nptkSojkmydj1N8pzjMFnN/bD7fX+cDhUdeVXTub5Gxe/qToPae7nMSUh8Cq2TdMoZdHpMB3alTceu25c1VVbN9HXmGns+8NdBoHUwRzE1JIDVDWbENGC99JDY1IXa6pjP1mk6LCUkWEd9fb6to3N5nT7/MU7l59d28aMDUfrKl1qL4A0K9QZMZEvciuAoK2auqo/+/zTjz//OIb46OwiVLHvehic92RMsnRXVcXU4GAmIkKgvuu997H2d7u7RiKTVy9ckc6WckJOmg3OpBfXEAKZI/bFFopJZGEc2P3IglrJektxQgxQyXaA0is2YBEo+Xq8KJZqnbBIpXyVygL95UDpX8lx/9TcM5m+Dox8Hcn5fxDG8l8nnv06j6/WRb+Oq38FQX9LkP7XeRAT36MYbyF3hDIFCzEp5aOIqCl7KpAWlnrfhNTy8sZlDJPL1PcvlJQIIeSUlQzERaK7dL8dM8zNKjAr44BGxTp6qWaNoMWHlkteqAu3wpZit3yawr0nV3AcMlNLBlOACzZfcKvCfmIiR0yERe+OCkLG3hwbF18dVeiYCQYow5kVSSiGipnClIwW6aeCgdhx4lUIUGIjEhIjg7EJ5XItOJSlQVUMSo4IzoELfd0Mokq6oFcEGJEDa+G8lysV5qQtDLIFFMKC3GQVU144RMd2rhUSrdkiQEQ4aoIDBFpWQtAiv2pYfkEjYl6ag7a0HNQWNz0jWjhsIFgqBu33PCMuqvd4q+1T5DsIDHOApyOipUqK0uogaMnyTU2P/CVHC7emnHopJ48sKF6AzaOULogePIAWvIyYiReZLRUrbttAYVbrgnEcF+/CsCrn5KLodaQGHXcConvu3cNhx/RUi7Ssfb1ZYYXqeEx2VeS44BRFDwYpaWHySUlpitIHsaFINYdAgDnHAmRJnB1qwKAZ2WthCxd1HOUjOA0QmZqyZxPkKTvvvAttbGOMVaynIU2jYII6BRMTG8tud5gyhmEax2m1atfrtS9TnAHee8ByytVq3bTt+fa0jnWeFXPxBXNHo82F4raQAbWwDReE66u/J443eAnpBcI6OkWY3d/x40/5VQzriOPSMd4IMJWiJFzU3xwWHt2S3RCYiRyTatHmv6fZi5kQws3L1N0mGBN5B4HSNGmWbhh75iUL6YcxVKvVug2h6frxdnfYd/32hH2guqnade09iJfZD6N86PbTjHNmg4IQYxRVM+Ng7crnlKuqOTs57dpD9GiacHF+rpJymkg1pRS89855xzFWIBu6eRgHx+LWdVM17734YL06bapm6IerN5dv3rzpuuHq9u7Vq8tPP//ki0uooHQggePsM4AARGAP+KMBWjri4x7wRfQHjy7w/NmL7334nSfPLp6983x9uq7X1epktTrZGlu9as4vLqapu729vr25zdlESVJyZKsYiTV4R6xTmqZ5JucduIkxnG/3+7tp9PvD2A+DD16Mxzll0SwgokM/E9F209ZNa8GQi9C6eu/X67aqfFZzKQUHFxCjmeo0qagZkTKhyBiLlEUfC2nPULL1I8xvixmPHddEdszAQtxQMxhyzmoUfAiBmza+ePHot/7GRxfPLj774vOcuuvbNze7L8WSOXIh9GmYZJo1dcN4t9t7H1ftZt2um2b9/T/907ptm6aOTQxVFatopOiNvTfC6zdXzjnDvaSAqhEXgqBq3VRNXZdQ7/uxqkJdN47znCfRrEY+Rh8dMYlJXTc+xHkSEXXsnF8DbhxknCQELVPmME650DsI6k3FjMtmp2Jc+RCcczSnEaRiEC3VfsCibsvMTiQPCWZwjCxpzpZEdZyVM0HXK8Q2rJsV4LtuurvtcjYiEHJKOiWkPjx9ehIdj93NXE8wTWlQRd3a7naeFdtT3mya9dYf5n4eM7LF2jUr1FW42Q/DmGLNBkFhoADZgMQGErOURTQZoXEu1tV6U19c8DipQYAEU5VMCAy/26fDPLSVl4m+fHNTu+rixcV6e7Y6W//oBz+e3yRDpEhMbp4nmXqQI+ej8zF6YspJplGHPrs19C045L52MLyFwxuwWB7bcdUCyASa73ehwtxh8rFIZpmQgsUwc8WIJE4FBoe4Qq7wu3/7W9WWmw3WZ61WsZ/33e18fSM//fHV7dWcJx4OWvtcr72CNEEm6KyBqfIxts3YDdMwddOQ9jMTXItEQMCh9y+/7JqDJbN2E+CRbfIVtqu6vjh93p3vxx/kzsmkeaDkzDRTPWiGZKzP8fhFw7U+edE8/2DbXJCvRWkS9C6mzZpCE0EE53xQlvl0W8tN7lKaJ92NXTCO5OZpaohnHe+G659fffL0Au9+9Ojxu0++/4MfXn126F/PWVKoY6jYwOydiRgX+QN5oLu9JYFbEkhb/JRL3mBfkZ76C4579AqwRXpgUbI6ap6omV+K6WMeUjKX+4rwuFHR/SZ43BAXFjwx4WiKvczvHFMRg6mYkJgSwwXAFYl4mDPeIp/Yb/+1b3/ne++dP93eDZfj9V7JHe6my6vh+mqWTJ5Conmek4vexIzk5KQ+vzh75xvP6k2cpunm9dWbm9c5T3UMDpnYuArOe1UWZYIjQ0oydTL0VjH6/bS/OqQByChyE7HmuvFZTYpP9Jxydo48eQfHpo4shFCnYdhd31y9OuyvBr0FAPVQh5Rx/eWQjSrf0FRPSv3BpuQMJEMC4c6kC0Plh404rrA+2a6a3XTYS06uxTz2DFjW3c246yTApcxVCCpqZD56x85nrhCc1/0EcjA29r6qwyef/xTMMVRt27Bz+5vboUurAI7eoQq2SiN2r+z1x0CCcwRjzQYjT27OGYu+7hFTWLAP4EGpeWn6l05l6Z8plb6+UdF6hZoA8mA6dIy4Y4jakgLdV15/Tqg+/NvXC1uieZzBbGKWM4D93a597GODyvtNOwMaPNeNj7GpfF3HhsSlZCZchDVj5VJl8yzTPAgZOCES2HCKk8dbTbnr+v2uywpLqNi1fl1ZdRilsnZ3m3a3Yzf2QurbKq6qqo4W8phVHZoNZ5nmIUem7Xq7cusxSRp2eWRkhXoSVi1jC1q4d8dBB6WFXFnamHT/U5EB4ohLsqdwZGJ60MPNYX2yvnj8FAaRRA7mAIHlLKJm6slxcOM8KgkHIk/3Jg3MrFnHYYRgTvN1uuaKSRkBMFPLgV2zaabbXlV9cOaX4RF4U5hYqmLgCA5wDlTGRT2MwMwcVIlGGQN8cIGjYxiESUp7eiER4J6qZ/83dW/WLE2SXIcdd4+IXGq5y7f23rNgEwiCi5FmpElPfNCDRMr0IOOj/qiMRgk0SaAAkRDAGQwwA/Te33a3WjMzwt31EFn3u71gAMiwmNK6Z8qq61ZlZUZFeJxz/Jy52DbMniffGAn3XMr3DZV500MATtz8g6nu/m3oe/Y1f8PHtwbqXwSMfAuu+fsVYYVvncTf0tnc8yTffebvXor28Ms+BBq/iz7+bRw0A1XzImk2NytV66R5B1mTDgAApt40qQp5/L6zyax4hQxYqus2k7n7HObwjS9YH1eUK1CwkyPJPfZQFSo+OxO8ZZyKae3wqG82Qyyoal2qy4SbkdToQwGheO1NAfjk1kkV7gAxCbPMqiJzmg2yyJmdK1RuNdruAOdqSObuJA44hIhd7juCMStAZg1nLYsAinwCxdW15pMxEAAC1+2vuUEjR55xHTgoEKo0hMEVpKuhujWUcBYVExPPiniew+5YKNTLmGfFzoxdVXctm590VPCJMXdmnYQG95VW5W3uWUF2nwmE2qNI7F6N/gh+n6cHwGtrtFU75WodeRpFIDh0vi5ExmZMYEdgM4CkuDMZ1YTwKpSba/5qv0Wnt6rlG8/qOke1PXuLY6LaJFVpFebRQ0REKTTMYveNurWQnV9Tz5GN73cOxFVAhVN/ZoWYZ+QUTg7+pgx3vgqn//UTU3uCVt5eXtRb6aZwd57tEuvCIkRgrxmXVrW/DiapwIsAJAQ9QWtuoMASIonCYLOBihFLJX64RsDzzEmVbPv9OOXcNE1MIpz6dt21i+l4Y1pfGVFUorR9JJSuMYMOh0k4LBb9NGguuUkgpTxkGFjQxPj0yVOCaAGqLWnNxVSt1ds8iRlcMI+MU1FHc7FOD68OVTgZMxI9N6p+8ypXEfc9hjX/vE939vR2PCszZ+i0otnzzwcOYSaApc45sLm/mOogEgrI+asvXj5+d9m0XZNERFQtZ725uupWXYxBYqTgqU1qWkxTE548Pe/7vut6s5JSaPvIrKWMkVnWfTPFw2E/TKPDzVVVQ4x1lLZdc3n5aDgMBG5iq01ZLherVc/EV7fXOk1ENI1j1y6IKEjc7/aH4aiTi6TF6tHlxfPHF+907eVyeR4lvfx686c///I//K+/s9sRAsYxDxOCzmZ/WkMFGGZzH7RYwIJiCFEEQClaxuxADEIEJBCzZvr6q7svv/hdiVif9WePVs8/fP6DX/3BO+8//c1/9BsX4VEfW0N+8frzn//8F8Nx7GI3jEOZRsBgxXxMMY45v7p+s9lu9vsdmIKIO8xQ1IbxgBHOYb8fjsME4pSaIRszt+2ZcBMjlXEquUx5dIcqzi/OOOycNJtzDEQ0TjaW0ZRc4cTOBgYS18A+A9zInSCwClzTaeqmuvSRG3T2cTczhZsLQhB3z3nM4wT35++f/fhXfnT57Hw3bL549Xnf8N1h89WrzyFwpsvHj1wsttHHQw0YEpAPgzkXx7/7nZ8+eZTOLvqLR+uzy+XFxXlMsem6VpgYN3/yppoZOAQiIZAErjirC4EQUwgSq214CLHtEgvHIZoV8xBjDEGIWVWbRogoTzpNk4j2zTKlpm1G+NSkpmlaP8lDHRDmPIFEmrAI4iHEkCIREzg1jaOY+xxga8ilEGQs7s4htU1XIBqbSAFNF2MjlHcKVzVhLJctEx0PU57GYV+Go+nk5iYS8phvbj1a6ZIuujJNOUa+vDifRhv2u4tzffUKfY9FT21DTcOTIaOMObP4o8sFcdwNx2Gy4BYCQgQTmGEoh0lRnNhTEglEoGEYnRATP3v+eLffZjuqIkTRUkrW5fLy9vXLu90wHAKDXl3ftSmtF6t+vXj2owtNP7j57PbFz2+mu4ldkLh5vAgk5ahQm/LorqaFgaZB9lDJazopcLxO2OCZ2nhAddzPaHU61BOG4jUWluFU1PcgghALLBiJTjaiOKKjQeyxOO9zc/jtf/4bh/EGkUIKo+N2U168uv3kk682d9PdFd57/viIPaQPTAHj4Ds21QKFFs1mBLXEkdiKZituANpmcdGllDbbfHfYIvJTWTir2uBl27Z9e9a2F4vf/Ge/vrud3rx689VXGzvA7lAykIAVuvfxg3/4eHnWnD1axLWaHAqV7IPZYDSlhkIEqvU2Gaw8PltORz/GoMehZEvStItF4rS92Zpuls/Xr/dfq/iPPv61jz/4wb/9n//NH/zuH/8f/+H3d1/m/WEbpaMkwzhA1U3JrTJi91zSw4NO+rhTzfDX35PR3Jle76UBXAUd1cy0rkZVHXp6Od07OswsDWbg61SazsjlyVKZAPE5LJHBAq+ynlqAVQKXBQjk7FbJhhY2gi7xr/6n/6Zb0J9/+otPrn/aLRb7bdnuynaLnCupVSBuwY0nOJ5cLj786OMPPnpfAr25e/P5V19vtjfFC7Hsc373uaQ2SUqAqE7FxDKZWh4tH2HWcFwSZbW8348QF4ESjPLxuGm7pD4NY8lTzmMuWSiQcu5Sa4UsYzzku+vD7e3BD0ABCXNhK0bFc55C2wo3euRplw+HnLNTEDJzMdJU3G9eH3fHMa1o0XeL1A/tOOScovR9A0iemFDEtG1Wsfp8qpZKt7OFBBIJUboBIuBARcv+MA4jQrSmIWLAynDIOgJEgZqI/u7NcPP1/sWn15gQiIlER7dCgkDEswCrDi0D8cMS00tRMxep3gpU/QxIHSBysnuP9lq0K8hq8uCDnrjZkv20K/yLt4YPd5G/9HA4p5CYdNQCw+5q111ydEw8kiCPA5H3fZNSG4IIp8gQipOWkr0UI6QY3UgpEIhMAHJ1oEW7Snc3w3a7J8fZomtDHz11zULVQsn/6X/76TgMLrQ6X108Wp89PuMGB925+JB1sUjNIhyGIXKIIhfri1W6uNru9ttPvAhKhIbaKQx2v++6nctvu5+A3augvu6siZygJJUQqiWQqxumYTQ1YcYZjMzKSf5YAFd3p8Ah0DBMLMQiYIMCArTYj/vyJk/D2KZGxzLsxgZp0bVTnPI44QATJE6lFBGOMVhwy9nJJRHETYqLocEubzxDUsMkdizgKpYAyBHBSSSJmVcxwozLP2TrfaaGYXXL7rUJZF6CThqCb+1H7qczvwdIHU73Nfl9bf3Nqe9v+Tjtku7R/+9vjPsuevX3IgOqR/jW+fkpzfFv8DO+993un/z7BfD+ts/h7a310zC+R6mIZvSq/v5n4Q15xUcEpz2ks8wZf24uXDeGrlARCSFgNqeCFVUozTvQin9bmY3hXVi46nzc3b2oGipGAlU91RbGLMQEIgNUC+4lGUC1u5S33WJaMa+aMQMhJgTnTFp/z/VbV2I9hBqy7uZm2cycBS6BIQKBA0qW2adiasi1UjGHkZGpEzFCwP3QdDe1aoIwT4oAnGtrm6GYwWHEs0k5BCEKh0BUI3TEiruCyGtoXV0IBcKzB3ndaN2Lj3Cv/qkIiboJAoiVnEiIWDDNdxmoKhizB9xiFRic8nv5BARy1bbVDn6bY7EZs9n/bJLmDHeuWJU5Eb8dMHiLMji9/Tiakbb5XMzU7k0piSpg5G4CUmaRqotjc3PR2bKUQKFaqlVOAah2N7NS2F31ZFHp5m/TCe5Jq1mao7U79Z4QcyYuVRJEVEPMGCAWw6mDsSJQVQXudTmb616HC9G3fqt++nmdvjyITuYDVfGjqHohZiGz6oJvBpl9YIm5FjeWi6EUJwc5B2IIEYmLg0op2XJEcCIoQop93xfNiACRMwpMSGYVFNfqqLpaujOyqg5qCi1SsgkSeToeSx4VEJboRsShbZts+xiCFr272w/j8N67P/KSF4t2teg2NyPIu56G8VDKdL5a73fHYchQFBi7Es8pE0Q0G83O0r4TS+ZgCadBMs9CPsMG94uSubvck0j317miDvPM8mCdm5O9qHaj1h5XB2jWsJxoKtL7VK/Zwy+4w6HVxhtWPbOUEfCHP/0JtdN//S9/u180i+1y2afDmG5urtYXH0tcprYlaTl0ZRoOuyN5efr4snmvS6k9HHY5j+ZTLjmIV2SBBe4NES4uzlIKDpUALc7Mfd+3bbePRxSMw5jHKYm0Ucp0vH1z7Vbarh2Po1AAEEJzdvbo2bP+8cWzR5fPV4vLyD2j+cWffvbv/pff/b3/+H99/gd7LAFC6jEVcERILCRq4CAgI2cGm8PUHGQgy9OURxCYTjkUzAa2ou5O5KVoGXWxiFry69cD/vga//FTnP0uzoA9nn6Mf/6P//Fv/dZvPnv+5IP3PrSSt5vNetWR6TSNmie1XDQP43HYbm7evNkeD2owx6/+8Edd36dm0Xb98XhUp8NhuL4puaCJQ3YQCdNNcFr2XWQxdSEKQUTw7jvP2j7FlodpUvJpmqbiJvA5StUrIFz/cXUzBTl4bgo89XdQ7UpnBjFbyW7mdXFk8gJyuMypDiFRcf/X/8N/9+OPP4gtfvanf/TyxRfC/uVXP8+2ZSaDrR6tEMCdnKWLtTM5CyV2qcEnO0U6TEedtsPt+X65P+z7ZX92vu4Xi7bvWXga824/jRNA6Hv0i67p2hiFhc0yubKkrmnqMGWGmhbzaTJJGkN0IYVNZWrcJs2H43S92SSJuTGW6CIUhWMq5jmXoSiUzD0bvXxzd3F+3nRxHMYQJHLK43g8HhbLXs0qb5DN1QsySIIjcghtv3KSVnWxWnCkEAHWYdSiRwpg9lXXb+62d7fHaYAw2rRumzgc82F70OxUMOz16883T5/au++dvff8HSE2Rxevnjy+yOMny7OuW7XwoUwZPqkOu31JTXj6/PmUi3HX3B1ZuG0TiEspxGxqWUs2WNasYwzu4OOY22PbdOHsbB2Sv7k+Fi0ktt/f5UHfe/ajYcvYH95c3YFx3R2aeCxcvLHmvHnWrB8/XX/wwbMvPvnq9atNGXQc8rhHiIGZhsl10gBqU2ra5mY3mwxWhqeqjt2NyM09VF9huIP94cRWXR+16rKIhAVCTIpifkQABXgAJXJBswgelJOcP1n96Nd++I/+yT/81f/q45vNz2S1en11+59+/6d/9PPPru4AxrLp4EvQeHtrQE/oBGTFoveJRoeXyQY74LhJqe+6RYhpEi5F4Wja5dnF49j6NF6NWr78+kpFzy5TaGSchsPwKiEFWl7+8KMP04dt+s0udevl2Wqx0DyO077pufigNNxs3uyOt7vDbc7HEBlSso6ljCAsKtshgYyncezbNUbWg0w7sUy27JtwAZ6GVLaHHaXw6vXXn3791S++/rOOl//9v/y37fo3zt9t/vD3f/Znf/JiujmwidU1VIh8rjPgNrdyfWPrxjCdm/N5LoSqDvtEQf1FkNa8S6wc1X2BwQ6p0qnqRMF1VaqUWy0L7Jubj1NmmM+l4/2ztT7hyvTwSYYP9xxwEpCyiAQ20sKFAgoDAavLbv1k9eE/+pge689f/qxZlHTh77aXd3fH7evhMGGcfDwaaIgRUbBctu/94Nnzd589f/58d9i/ev3V/rA7TMPmdrvZTWpYLdrled82LOIlcy66O5Ypu0RSxTQgH9HHLsSVcA7iNN6kFm3XMFvXS552q7PznFPJquplgpkCjIS+62JK+/3h+s319m7vNXAjBEJwUzcIeLFYKDzvddB9KerFoMZR0HZecqKVxDAdy2E82na/bLu2x3rRrsQvLle3m7vxqLu7cvPKpwneTIdxrKFP8LLb75omqJZchmLqjqZF2wWC7w9biWh6Wq8WMUguExn6BhfL7qw9a3zx2Z+8+NM/+uoXP/kaEazJphohzlEEOpMBAOTE+QqgTEJkVV3JtSx1VzNzqrHjYBQjAozgRi7ucFM2AvOpoj3xoQ/EVvc03vcN1L/SQSBTYyJxhoEp+q6UYYoltG1jsRx3u1G9a/soLZmXyZ3ElIYh+3jc748JxMxdF0LbWNAJVKYyjNlDa6ToAAAgAElEQVQdox7Bdvls3VDbyXK4G69f3X29uypjwd5wBTgQeRNff8mvscDynfTj3/pwsWi97/rHy6Mdih9ibHT0lLq+W9/odPcGGAkleBYvXv2tmOeg1pmudPJTKwKq6v4ksoQ5FY/cqmpxZUJoQ5ZSvOz3+5u76/c/en57e7fbHS3PWkICiVfzDsQQIU5GmuGMpgvtWbc9br56vTvmg5GTcLsIqWmWy9VFfxkQ797cHTbDdBjWZ6vhcLSKtYkjQM1dMXXjo+XFP/jw16tx7mZ3eH11XYbiIzDV7HpP6y4uoiRBLqRwNTNyqJODISfr12r/V2Y3BJgbE4RryFqle+sL/SS/fztyfJ5yZi9kPzkF4cS4/H0dvwQCusc0/u61R989vg1g/Y0f94jYt4Rn98ffqtzpr3J8C2X8S8G776rJvvuG9y/71rvdr8+n/wqevY/9wZnMfygU4K4+N9PybK5d9Q5OxMIcYyQhVSslm1Ypl5+iHcndrRS1GmDg94e5a1GDOs8i+9kmHFA4o7K+DMVJ4AiqEFfdqgKzXAyWNZtB4azmwkQURBwoWWdhdt3HMBMTXIu5atXtAmRCsTIm7nA1K4YCEgrOzAybcSx4VXUxM81+arONFt7yfFRz+soD0g0sREIuFGPkGMwLVw2bAfACna/UrA8hzG6jTkbm5qfdOXxWmRNmJ0InVF+oGmEzG3gDVVT7VsH8YKjogyFDdOr5q8XSN/KfHcZUuy7v0wp99qaSk6Cmdvvdj6+qFaqiqZOm4eSmNueozD6quB9lgZhAUiVD8wWDk3KBgwTMZKa1rpttV2f+gU11piW96prur86DsQ6UUqjM45kEJAwhqUXt/HaOquW+5ypmjy+vpvHwU9dRvdn0ALO7v/MnSdo91vawjwAPplp/UP7WXxXNpybFjd1Vra6gs3CtOoGpZSsCdoNBQWBhCkLRTj6fM4Zc+w5r0171hXVCTBJDBJyIS/HhcITKNPpus5/prDoOmN28lEIMOsK9FIWW0qTkK+m6dPXqeLZMDD7uh1LGftEfdgcrXnvTvCp77GSR/5AjeXCB3jbU3/+o7TRE3e+v1Jxu/uCgewyrMpszrPvtBn2asd4TteSoMsdZkod5mIC8/o5oFofNWjgtxiwvr2+vXtyocgyhbfrlYu2Y7o6TEKcYQgzgABaQMjnDWdB1oYnBLcKnaSqmBV6UYOZasrutV8v1agmnacpwYkBYAgsJU8+i0VRhVifVKR/dTI3YyZ2sOEAksQ3L9eLR86cfr5fn+3359PPPXr+6+39+76evXl4dNiRPcLZc7TajmUlUkHjhQQEgijiEQMSRq9EbiIB2EVTziWN4S1SompqKSGpi2yWRIJSwHicrs8fsHssz+Bh+8fPPt5vDet2vV93l+foHH72/6nstBVYc0ZzUZBiObYqLLnFwc0wlB4lds2qSizQxHna7XR0J04hSoApzbeKmDWxaVl1HIBFJKdaJqi/tpC2NGMs0FXUyltmHDWZQSBQicSWF1oL/XlB54jYc0Nqy417N3Uw4xhiAkPPkKChmjtDg4nwRO/nwg+dNF67vXr+6egHWYToWyxKFBcfDccyjpAQGgV1J3UvOqpNmc6d/8luXDqipCFKbjHzIE7abbNq1i7OzS5HjMF7tj26OMIFlIiaiFCAxNKrqWliiiJRiplpKVq29FKWO3spbqGYtOec8TYDkfNynlMzcjVV1mqZpylbUzeFk2XXvpakpErlr+hJsHPKkRxEey+gwdQ4uszbSSRUOcSN3Nlci9F0DKeYaXVACs1b1k2WfjhhHLBpEDkwJrjrRNCESJQnDzspZuTx7ulo00zCmpqGna1W5ubpanl0W90nHMk0phihRtbiWGFyYcx+FwBJCCqXYMFW7fjRdmoYJoHHSXIoEZoK6SVy4O4HaLpkWLbYbEOWu/ai/vHyar+/eXN3B+dXdzfm6bTwOOJjniScEw8qf/Wi9eBRffHm1uwFa6FAj4AARh2QEUgYx3Xsi1T5GzLkyc/hdtW7iYOamb5ua1V2ESeZ1c14+iMECNk6Ro2fOIIw594/xT//Zr3784w9WF4vQbj97+UfD4e719fVnn7388ss3wwaNJZLQ0KoUTx72t8fFYgWFjtCBdEBEw5GOeSzDhOzGOZeJyiyUBqHpU9u2zqNN5N7sNuP2Ttte+vXaQIeR9sNAtP/8659dnj/u275v2sflcpG7PA4itm479WG7v9rsr3eHzXEYQdyRsKMUjCNKQd9GRgzWEBgTxk3eXB9uvp4222wGZF1GMEf4QoRHJQ8BzXQo4yEPv/eT33nv8Xu/+c8/6s8CxfLTP3hje4WDC5jFSVxhxZyFIOZOYILM3AcEXmAFXg0lhYhnKaaDmGtFcWoDO60UlW5zw9un3tLfDysBqj7MJ/PO+wy4E632oFiq6Yg1UXregcwenxUCsxqsBoLPG1EWliCQufoslWtc4eKdy2cfP9vb4FPpvOyGzbi9zTkTNbvpOE58yBkKNHj0Di4vHj158my5XgO02V7vD4ft9na72x8Ow83dQRVNCxaxjGmyXAzDOGU9HrUA0cASydlheWItUormAe4Qjn3XpgYSUbKm2DbRNIhJLqG4hdhJs5CLi9XlxdmffP318bhTUzA4EnGgQrUBlBjPnjx6fXW93x3MlEnYSN3giCQGF5fE6ThMgOWC26vN03S2PltT0/Z9cuK9jF5KXufDToOkVmkY9ogMw+Zux2xaRiekFnCIoG0kJhoLYqip68TsPk1B0AUsuybFGEt78+bNq6+2d9dgg6mREdyJyQGzLFzDRueNEnlNFTop9asxhlb5dfU2OZU7BmF2OEPqH+qMZdYV61QDft9W79s7u7/mHlZHy6nMWyNnYk7UPFqfWztNYbjZbJz9cDx2bdM0zTSUgjKNiiLDNE4TgBI4ppjavtVQGDZ1wJC9oOv7s+581a2WssLIX+xelv11uZ1QBJPEvmUnimRQtezI5TDdvd60q/PLR5dI4zAci8Kz6r4c9vm8YdKI2qZqoTaPkL2lAU51tp+oypO15X1BDycncYYCIDYidjIKEsxtnI6747a/WOzKDiOQMW89QKRwV2MOMRiZelY1RHRtvz5fI2A8DEVK2zZd07VNA+dFu3j+6J3HZ4+3N9svP/vq9Rev1PI05mJ59maugoYIThhtHPOw3e+GaQQzCVKXQgpsEcWz5dCEEEWCmGk9aSczshrDCq87ITIFoGJUhQ8A1BHrmDyF1D2QNX3PgJnr8Lf6K8d9c8hfDcd6yEb/tcbh/+fjW+jVdz/670aiFL71O6yHmX33yb/icf9NHn637z7/9wVaPUSX/GSg/vA8f8mJffeW/PJvQQ+O754Gzc1ZuNcwmc7RLUxcewPVVLPWLu6Hb0VEzM4szCxBgKJaPeDcq+iJmZkBPx4mZiZmV5SS542pe84TyBHImIOIkZuZgcjU6/6fZ0025nnciUhERARAYI5R1J0za93eATAjoRiFG95tjw8wBSciJlI/AdDzSkMQro7e1bDczFGh6qp9cnKjaqEEo5jE1UsuBoQQKsAkInDUrQQxjGYP9mriGoU4iguHGFlkymXWpwi7uZmpWsWvmMldH9witpprei+R05NX36nnm0C168VcS1Z88y6fyECne99YqjzvCb3B6enaJFeFMhXqPV1yBtfg1TpQua52NEtP3a3ST3OzGpFIALk5RMTIUQqd8i+ITUTUbAbFzCHkXvMy7o29TjNmbcNgZ6JqiwWb1XgMZmfhcMJEQVCqeFqpAkN3J3eHQkVn53tGIJHIIqw26/gdp6LS3VyBqofDbFwv1YnN/R75uwcs741N7lfJE7h2+n1943HFiGdjxbcLKxgkMvtmuJHVQBUjEJnqXHYzgSyFKIlBlLUgkJsfDnvLBkcpWlMUzU2Lgs0DgcBMLHAW02rwIyxSShnyFILq7nAYjqGNZcxwZ+EYQ1GDS87ZCSwE9nHYn50/aZru6ePL21eb9Vncbw/rZVot+0XfffXl1zDHLD1gVENSMyJSKE64q7uD67zBp7jA01XCqXp3P9VrJwXcdye0E1ZXvQ9Qb1iV6Z12HRWIsXkqrT3NQHXnq9k/1TTVTVWLWvXBu694TIkKwXDcj7vt/snTR4vF6vzscsy7lCOzgOjudjNOdzEtF92yS2mQ8XjYwz2sEQVoAnl1UyAmNiY2F5H1YhWDTGOu1g1tapuuE2KCnC0bGzANw6Lr2jY0Se5uXi/6HiAGusjrxQVRWJ9dPnnyXtetI7o3L7e/+Nnnf/xfPrl+sf3PP/1ZLTWa1I4TUpMm00Li5gYSiQCpV3UScXUGs1r+QEid1MnrVBfqdtuKs8HdYOpKsxNLMFaQETmJm0CNx8mvbm7vtm9E8OTy8ePzs2k3rReLXMYP33++6Fe5TKlNKbXuvj5/lC1v99s3V6+ZojvnacxTSbFpkq4Way37FEdQMJOclcyHwzGwk5YYBDG5qwiZG5G2XeDYSDY1cUQmH8YcjKAhD3riWWb1Aoxqtqs4z4UA1U702lxOxCFnc2hVj0JNqzI24tHF+kc//uijjz/ol3G3v97eXW2215H9zesX6rlrW4NRmMZc+qaJqcnqCpvGcTgULc7EIaT15bmbOZkIVa/4POXD4fDyxXVq4vriou3WIk3THvJUchlLzsfDUFRF8P77793c3eUpN01oQihlHMdxHAaoBQbMdZpSYDhFCdNxKMVKGQKBgN2+yLGkFEKQcRzzVERCCIFbgVHOBYGGMvFe25ZgfNgNx+GYrez218/fuxymQdV0tKLGgSXQOJhpsbIrOqnnrmvIPU+jY0qBmQTwNqXI0rdtXgylkb7tBXEYR9fSJRaQmVycr0x10Y1nq0UMNPkoRI8e9ePoH3z4uF9e7I/jzaaMeerbZpryagk4yrhvuiaKSi/EUkGFoDRqIablqs9DMKX9/jiM0yL0EsKUx2L9cRiLlouz81IOu90wHUpW7HaH1Wo9PZP+9noaptiYomyPm4IhRBYmMU8dxSadrZrl4w/GG9y83F69vM1HIAipUBFT5FG98nxMp2nQ3FUqnQN2NyYOIuowMzawcFXO0pxHXD39akORKQFBIEytUNKuDR//4L1n7z06fz/98Def92dpP2y2h1s/4hd/ePvVF1effPZ6OkI6NG20LJvj2MYmeZqOB8jIMeadjvu83x1jbGNKHv3AZpSLjtNEbWrOn5zlYxm8QHSaduN0GKZj7IKWsrtWosP5xWUTz1XD1eaQp+No4frwejvKou00HM9oCSv5MNxllmhX168nPYzjNI0lpRRC7yWPk+YKT0/BKWZjV+SBNtebm5e72xd8PBI57GbQzW2/SrGLbR9u7oYQ+0RSSuYkf/7yvxynzQfPP/7g1y7b/p8+vfzi5ae3X3/68nBTyFh3Ts4UA4oajCW4khuJxJhSzsokTgFezLRaTjlgNbuQhLgma39n93GiA2dZ8NzqV9XlMJuNFGo9gweb6TrFWG1HogpruMKr45Gq1s5fmDOxO2DOgfz0CUTiFZ0W4iQcJXvJZUICItDggx+/9+j5BbVegm6HbT+2gfJ+1M12t+jw4iqvWvnwg3fOuuVyIeePkdok3MXU3N1tXr+5Hqe82W42u904ghxtS/2iXXSdBKQQpjLs9sPxODkJiRwnTSm4BVfdbPcpDGW0u+1GQmibtu9bDiWXIcTIHgM1Ql6TZYJwFAlCgC4XzecvXpzF1PXSIKDIuPeSJ2ZtmxiSLFbt9Y3V1LYYY+BgHoikaVI28VyUScc85iN62OTnq4v1RbMb32y3+91udKd+0cHa4XB3POxT6tq2V9Y8juP2yA2Ci5JSg4uz0C9kuUgp+TjaatlKYGZrUhCT/vkygtbNokupT8u720/LBDissJUSKEoIMC8lm3rfN8XL3JZNYPZqx1bU3KtZAbToHKnjmJNlzCsbzXPR6WanlMI5QYSMDIbaB4LvKYjqYPtL9rPf3f0RqOkiGTyQkJTNGBZhvzmyPoY7Wb67nRZnzX537GN3fnb26vrldtwrPIVuHKecoTq1DfdJYissXltoEqJnbRdda424DNvxeDO9+ezqeD1gYkZkCGdxdZuME4cY85SHG1x9fd2dybMPP/p6/zlxdMXxMB1u8Wn5qrF1zgqgSd24r0S/E81JR/6g19LdZs31vDXyUxlJRMwkOhUSTjFlnzRr3aFMZSyUmy72l82I4xTVdkAGCzz7NJXohOAOSEiLNjWrtj9vpePdtD/QMTJClK5rhYNOvr3apqHhA+VjHu4OZdSiFkIgggd3ykVMEvWrJq2isV1tr1TzWIqZuUvqYrQmoXHFmMfJJ3PFzCZaXVRIiEXM3Yt71ZoTnIXgJGYG18px0wkx//au8J5NrsP17e7FZ4ZXq1PoiSa+r8y/O64ejrq6yzs5vn17fP6S0fi9xy8X6HyvDun+r+4xCvpOE+LfOKoV/kbe5f9Hx8P797240i/527dxgX8ZboUHsOv8Kd9EXh/e2plzAkBQNQASae7ZdsCRc5lVNcQnl9m6h/fq8u7uNYIwa1Y1VSMhZhYJLEVY4BWYgqlW2MuqUsOdiSQITI3nmbsu5HBwnJ0OwSDhECWISLU0AgEUREQ4FzZT9bdTPAEpzfkzRBBhltm080RrgILEpoWRmlVBuXptglRMMBT1GrPnVlF5mBYlmu2l1QoIIhxirLKYOUqQH0wIAgrCQSQGEGkpuaiZMRMFZiHgpOeCm1Eec71uVcIWhE2oUKmaKyGuW/aZqPMZRnE/JbadUBOqxTBRdd16MDSEyE7epV5RISdXraDjPPEzM4xrCeVURV6z9sXI5jUEPvdcvx3DjBmMAHiuxIlmERzNzmaAn4T9YY4XpxNYiIojGWo/U+AAIoefVD3VaAKVaWBnVNNyh1efJQAMrr72RtnKCfmb74jB2cyMDEoO9bcy2VlvPPO0J3nPKbOonn9FVMzwjZmcTl/9QZWLqmc6va7CgbO66PSWDIoiLEFEfMZI83z1Tv6uc7SlkUEXXctBKnozqY/jGFhqQz4xPM/Rhk46Y2LCxA6YuiYRZ5IYATuORwN1fe8Fvt+KJDQsgqZpJAgYKUQSYlE3Gwfsd4d+cXz65L2ubcfxcP3mzTD5B89W7777VNi+/PKLogqGZ8ym6YR5BItoKaep4u3Vogfz3vx/6n4yL/vLEfl51N+TRXCrV6oeRg6X+8Qoqm3DfvqdoHp3kxnUzdztmydYs1cLAGEZh7Ft+uPYLBer7WHhXM7OzscyHffj/u42RIsU2mbRp+a4PVy//mrVt00Tu9RFsSiQACLebfccZH227tvF4Ti2IbGVYrZousViSSSmRpDCnqd8+ezR4yfnm83VcX9omibGuN8em9SvFhfM6enlu+erZ9vt+H//5Cd//mdf/OnP//yrF7c8cdemks2c3MjmoFISCVWiVnuu3X32i6WZ2a80r5Yy53G4OzOpVeqhto+bmqllQjB3iQ4QB4gRG9hCiDFyikHYSxlvb3aefXN7Ox7vmP1f/7f/4343NakB0Kblu+98fBwPx/Gw2W369mzYIyAZWXB28y7G9aKJgczXDtntjodD7pq27xoRTHnIk1tsik7udnZ+tm4Wj7pLEtoddy9fvbzbjpu7PJapiVSKh5jyoOM0cs1MYphBi7rOYHTlQuHurkTkMq86qjZkdXcv6JZ4/s5Fv2zPL85+/Csf/Oqv//jm5sU0Hre7683uuoshRGpiP47TZr9ZrFbE4ThOEhOLI1sdXsyUYpNS8u1daEKQKMLZ8ngYxpKnKe93ByYxxK5bLJbrtlmMw3Rz8+YwTCUjBCfmtu3Tftgf9jFY1/VFcdxvpmGMAg4sldVQYxYDtJQ8KcwCzT5gRAL1YtmKhhCYqG1Syfl4HOtsplklgSm5kaqPQ9mNagUf/3ChhiEP42Eai6aW24Z19JvNpnbHh4i22TNPIWF9ntpWHE2ItFr2yGWQKYoLeQpE7kEsBvUyta1LsCZpjHa2jk0MrmOedsDRUwOPjx8vmrYV8f0Rw6TH7SGPw3oZiTgFSkzLJm12h8P+SELStjGye1AQmJquGY7KITRCsemICKWominDWThwavsFpnE3HvHqxevLi7Q8Xz59/uSzz79A8El12E7huI8tlm1cNq0Ib7dXbVw9+/h9ej8tn/eLrxa7m+PVq33ZaslGHgDQUKjCGQpU5TWRu53oH5+pQkJsUiBk01KKK1zQ95y1AKWyL1MhBPCKPCIu9OJyuXrc/eN/8Ws/+JV34oJd8svrF1+8+HSzv0lh+e///Se1A60NTaBkR4Jz5EDqpgW7aco+FjU0NjKmqEUD2Xqxenz56HgYtnd3RUvq49l6rVPeTwNaHg7bzW4jgjb1MNrdHjabw6Jdvvvh404Cl00e9v26mSadxjzpmDFMtoqRD/s7uzvGgKJTCCwBNkAVbuwWbMowShJRWnMZJgzHaRwyTDw3OpbhoELxOOzvjvn8bHnxuNntjuvL8Ojx0kWybmOTfJp+8eUfv7l9/eOPfvXJB89+u/1o82tP/+wny//8f/5sd5s9uTsxBAyfg17IwWrg4qrECAQBC7kyzNwAZ6K3GmH3WjXVmmoukh08B0ISUKNwCDPtO9dRtT0xCAOsqu6FqVqYMSpbwDRr82uVM6NYswibiWYeZ2aBa5nuSKEWT4WLUi48QTyt48V76+WTvnuUNtPN8e747EfvXzx+frP/7Pqrl5Jwft6mFH78g8tlf3a+vlwt28i55Ltx3OfpmItt7u6ubzc5u7kSECM4IQilhlLk1MY2dTn7dBh3WyXW2DbEPJlCfRryZu9N3PiO4IhtSH2E+DgO0zTEGG+vd8dDHkedjmrZ2Esei1EZh3a7ux0zPJW2C9L0496Gw4EbdE3XRAHZcdrGjpYXoUymJTvQtk3TdgYfD0OeNFkShkgUpr5brlfnbSfX29dXm+3nXxz6Dhfr85j6fhm3d7syebtOq34dziOZDzqO0/7R8mx5kc7PQmi160h90LLnhuHF8sjBV33oL7oE6Xl11q6Trv7sky+GTSBqKNT0yZnuqne1WLFaLNLcTOInG1AikqoEdHM9kZ92XwgbE1fCciZKZ3Ju3nmdQtL9m0Xnt6qiv5JG5uHhqOA5zOcqnwrlYy5Ho8g56/EA93HIOHaZEF68vJkMi1WXTZmjj4M6iqh6cS9Zx2EajBE47of84usXbWnXafXyz99cfbHDG0ABE5gLhzxNUJirGAk4tCnrNG7KcZs318esGKBegik2mzLtbi4W1+UAhNqISnX7QzNzCfKq3yc/ed5VDrNKsU6CinrB2c1JICzgMNhg6kEodhFBBy9hLR89e5+GcPX5zavPrrU4Grj4mAfRoF5WF+v3f+WDy2eXd7vbF9cvrndXlND2HciL5sAhj+PNq5svrr8AUMNCAFlSX4qlRewvFqHniQY06C4abni0cXvYZs1ZLXIwt2maQkgiUuelcRzUGQydTAfFhAAWqfoIONd/QZHZ3BhQQjEjIkYpOrfsnPQReIt14uSD8rZufjuO5s0HvX1Ab8eNPxhq36uM+cbA/DsXZN0//q6MCd/BXv5Gzu3vAsD6Xgjw70uB9a0L9xAR/CVyuPvjr3LaJ3XV/NjM/iKk7DRfzsMamDUmZqaqoPt8vdk3hOj0boQKtQDQogA4MDHNU/BsH+RmFX5mzBhPVQEo8BZY8WqBWTvQ6ixUeXEhEWgVJTGqglpYqNJg7qpGNfS0YkBVuuFm6lpKSNHNqmzTmQxzDcEkdTfHQmBS80weiWtHAoXsAIJRbYV0dnJ2M62oP5zAIgYlJomBKlLgIDIhMYIHq9ZVTgghIDEHIRGz2vSh9Lb/cXZCqMsT8xx8dS9xI6oNgn7Sizk53ct5TgIqIoc8zNshgFC5X34oCjrd9vtZqIIy9PDBPQLIM8o5Y6BgJpjZjGrhtDzLvZ12fXeYGTFTrfEYhEAzXWlwm60dKmrFp8SemUPxWShVGxG5XsQqu64l3+ljmNzhpX551H5TNwQK9Qu7mRuCs7HrTGkBgLkVreF+XkMo66Wch6GfvFdrcYoZc7qf/eu1MZxw0gfXlfibMyPA1R/tNNU43IW0+PyBBGEWFg4iQmo173PuMgHN5Afc3OZV2oqTgKW25VPRcpxGdqLEieI4jPWdUwpGUC3I7vAgTGKp6ySG2CZm7PZ7YuFEZbQ85SYlEMwLUVLNbpZabppWAkAll0O3bIhLSkixO3+0/OTLl3vF+qw5v1i2XXrx4qtpGtllzmysKul52NSMv/sHJ9DVHi6as2rzhDJ+YxH61pT1Fvai2dS0cm4z7FqvnIMIprV3cg7OnOc5m1M6vYb91E7bGnlJdF/+GBBS4zE78OLFyyC/USUVSRL162W7jjroGtPRtaAcpqwhsazadjrsUbJEiUGcg4LHw6GiIk2IbUpJQpFsBKgIc5tSlOhGpmpetnf7cRyChBjClKfDfscsKXar5UXXrvr+PEnXpzPS9u5m+9OffvqLn39y9WpTBjBb1zeAmoKZ6y/N4Vb5XxCkFnXuZvPKUhVIDhDVUNTZxM/MQO6uelqOCMxggjHAVh2mrbqjFmTVYEwUKwExTWVzt+9SWrSPzeyP/ujPmeiDDz74+IeXlxePm0W83dy+eP1iLHwhy+vhjgp0LDZpt2yfP318GC6+fPF1tT0ho0YsxNh2QaJVh2a1vN8Pu93dxeW6aZvV2TK1aVkWMfFqN10vdqvVUtX/+OevFgmpCeMw1dxvIqpxkHDYybCkDlYmrpZzTmrVbUYcQNfh3Sf9r//GDx89uez61C+78Xh3HG7LOObpoNOQEYisSd24z268WK61wIqplaJF1Yil6wO7AKxkHIyCOflkNo55PxwO+3G/H2IQc/rqyxdn5xdPHj/rm6ZNI8yJ6DjtKhAJ4hACgasZsHCA26LvYMrCcHXAcpFI5GZ5crXI4BaEpgmdFpQ8jd5fI+YAACAASURBVHkw1xqgReRNE/I0FgDkeZoiNzWlWziGGBvVIzAM+XjIhzFnVQiTd1aiZoXjRAMjT4VcmhjPFovFspHgEtCk6FOZjnmLzXicLN8uFqtlH5uAQxpTiMyZ+E4Ch5DMJjNzH6Yhj0e48XL1nHwcjtvt5mazG1OiKety1bVdR+aYJqmtjKYpxSg8OiYUK+4u44TjMALc9YvUNKUUIlZFnsxgUy5mWrLFEEIvb95cEXXL/vHZ2WK1TXfXWwQ0HdpW1mers7M1uW7vXsWz3py+vnmRpDt78uS9jz/Y3w5/+pNPP/n0c1zDh5IzsAQmYJrJDK2FDEABAWwGzTaqwYmK5WqTCUdC7LAbHGzzyshAdMj8m+Q1/sW/+gdPnj05f3IWujDkvN0cbm6mzS1f31IedzBEZyYh53I0V26b2IRmPB6pFAzQnPdD6SNFaTruC7IXZ6K+b569+/TLLz6/ubmBmHEZfXSxrmmOx5HVArfBWzKxyce8f/nJbRf7syf9WfvENdxt77Z7wNE2GPMooZydLyVJ5K7vopaJoKqGDkwtnOAcQ5NCG0MU7qzQNOj2bhynfLZ4vOrDsj1sbjeSWNozkJCn3SYrDW3X5+zFbNLsk+OYY9MULl9efbo73n74+MMf/OgH73/8ZD9e/f7//gafAZ3bmcqO7GAFBRxZEjtlU3FScysZbjFQitHZcxnsxNW/XXtm9MruyV0rBNCcEkpSayWdX2CAkzOM/bTwgYSAWq+ZGgVU+kwEwmAK5FwyUWAnmLpCJQQRIXJ1q74VigIyEEhrpLahBwKaC376w1V70by8ffFmf/fRD9+Jy1F1fPHi5fUW7z3Hxfni/yXvzXosSbIzse+cY2bufpeIyMilll6rm002V5EiOTPQiBIwmAEE6EUPkn6E/oB+mAA9CAIEDkYagRoNQQ2bYu+srq7KyqzKjOXe64uZnXP0YH4js6ubHErcBIwXkBlR6eHXw93c3M53vmW7efR7v/2rtzfj6W5c8jjVaRo/n0/LeLR28oY852ZkjsCQmAAnUvMZTtMpLydfRs8TQuSUmipYCbzpIu1sSHFCDhH9JqROqi7Hw2mcy2ZwL1hmVYWvKL4S826771NH5okAmLrVuixFjS2lIEmq6zhNV+Gi2zHHoUx1Os6qC1EAyjTO8zhBHJ0kiRy7ylWzlWK88Gmup1HHBUTYbXW3i4+fXZYy3x+qsDy6vLi6ekTgcZzH8fD4yeV2T9udZ7tlWko5BSnLDDAWL5Fit0kBCGx9ohQQgM9+BAqVKbo4hbZcbQUF4KhaHO6kRoam9xeQNOBAyJmseeAZnMi8AS5tEW3saDGT5mt6s6/2t27rouhvWKn+gprRfR5bKG2iICwIHANhN1z0l1FqjPK5VYZa4LDbXIwHQBAvE5F3/QbpgAI1q7UWzYtN8zKFkIxRMihK4GgFZJSIakcDb+xE0zQrlU3qaq2lmpu5UoSQBNX66rN7/T7Fa/LkMV4hWAg3Wmiac+r63ZPh+P0RoUdlWs1CmmUnNXd+2Jtfcs2o9ge2kZtZ33dzGWspLkBEiFTN4T5cdHErN+UmdvL4K+/rhPv5Djewo8McCRigpQKQa9l+ab97tr99fjsf5jrYrusudntSYgtlqTXXxJ1sQkC07MUzaTieFsClE6KQujTsNtaZR6WIOo2LLhVAgLsSeYxD5OBmeZnLsljV3PohCtRm8tycXcmFADMzOCcRAlDhrEythUlQa6XVG05oW/UAK4DZysyzycvPNOWJfS1kDO5ggraKD3+F+drPA0b4a/Ot/ha3t9GPn9/+1sGfvz8G1tvMo7+3D/35jZn9rByk8wbgzMT5q7Z/L/fqC3u+DV0RvzWUfXVW+sVHI2g1rbnhFszsomeKz8MDAYp4YGM1pWGL2wBDmACUUrR613frUdsqoaE0qmBQIAi525KVyJseW4QpEIuwkLkyuQFEjYC9Gsg3FaFWLVbVKgmxcJLAwgZd0TfAVpYSHN6MJIWEhVNMquruSy4OMnIXR2Dh2BEJwinfEjO5kDFcVfycEWKrz1WTpZGBqNZaXc2NWCiuBYsTsQQWEREjqC2mpqrkCCEIi7vXlunOK1WKhVHA3FRWaFwnN0O1lcjJrfp3WKOHyip3YybAOdpb5Dtgba387J11uEKdGKDVtxmACPkbG/QzmMDN5bnFHTYyBwB3MtCKpK3OQuxQb/imGxHIZR2CfPbRbk0lITqbbTSh5uppyo4VgnNq+BUcVqxWbW/1BlCeqWnMzJRN6MGnsJ2jE7FWNVUQRwkcgwYrXB3alp8krdMphtaRgT+wxlaIjRozo3HMHGDyVRgDOKBNh/n2Rf3ZRoS7E1Cby8wbmhDg5+iv1ZEtiEQiNAWCn6G21tQjAgQsILgRnGQax2BJooCdiBoP0d2Hfggcy1xpMXLKSwZAHQmt/mvE6IfEAmejIKGTueZcF82GDLNMbGa25NGJnKpTEonM7CAzfv7xxy8F85i/8uUv/d7v/OY/+8/+8f3d3Yuffsastcx/8t3v+D05JMTga0TpSmXx6g8u9e3+tIujeoZL118XZoTV8upnkMAvzmnnZtAKv7gDcqbuNU9cW5EsU6VzGBUcD4Si89YyFlZ2XVss8uqCttn0ecl6v/zoBx9+9PrD//a/+S+eXj9Z8v28XB6mm1ev7m4Pd7lkgaTUqZlX3V/sd8N2SH2e8+LgTTf0fRS+vzeHv/foGREvOddl7kKcpiUwJU6RQ2QBsUQmojzoo8vtdkh5GgPo0eW1SCSXy+2j7XD15PGXu7T9+KPP/vAP/5d//ad/jo+BiLgPm20Kko7T0kB8r2sid0NhGzjXnklv62Qmai3LhydPQOCH13B7KK06A0wQIREh5mJevYpI8ze182UsqmYQ6VPiMi+E2Mer8X65O5z+7b/9P4NgOf4b3AMDvv17j/7gP/3P/9E//f3f+Z0/CCI/+NPval1efPb85WefzPV0ur+PffrlD7728SfP7w9j3KSccDqd7g8L2LxUeE2SiGjJ8/F4d3e8+fz2Rb8ZNvvd1dXV42fD+1/SZSwla2BZZj3ezGOYQlNygqOwBXGFgLU0iMnJ4WSBSQIxy66nzaYfhtR3cQh0uRvee+fiy1995+Lqolo5nQ6Pry/KPHbJrBxqLsfD6I4g3dOnu77bHceTkx/HwzTP6loXhVNAhJPDPnn90wcfXuIYQ9rshourS69y8/ruw5+cfvT9CfGTLz3dPnvy5Nm7T68fP7m/f30YD6Xkl5985lC4eIUWI5Jh2LraPI5wdKlrYvQgIYjbYs4aUjD1nL3f7HPW0dzmRd1itBZwHwIPm46lmiLnkkvmyUEryqMKOE7HPE46F4/dZrvdS+jKUpexosBhVQFBAPabfrfrUgimueay5Gmej1//ygdPri93w/D685v7+wNj2Q4xXqVatyki9RvVabvrHl1u+o7Zcwzr9BtiDJLnXO/v729eTacJl9eAIUp4fLlf5uVwf89M28RJIqfkLKc8nQ7LUsAx395hntF3XU80zfn+/p7Am82uqplazWTupmJK5Hw/zvbqhVm4enz1++//9h//8f8OeNaqptM8x9j3Q+r21zc3r7Wctv2lbKBbfVVfoKdf/v33f+OffFNISlYr+p0/+nfLscxjaS+keSp1gZioWlaDg3q4YYgM8mLWR0qdQEzd9xtwCBw5dri62n/la1969N726ZcuYhemed5eXDrok5c/ffXdu08/e/3DD5/fHmdgQGUsBZlLNiYnMqgFpOCx3J/uPr9pLSEnlOJ3adzs0G17uJ7m8TTdv7jl3/ytX0OHsJUZU16WnGtdyul0glM52aJzvrNSiwTvt/3NJyeqH3+LvnLx6GKy0yZduE/M3vcsAuaoxUvOXRRYyNPotYYQH19emfn9/UGrBQ4gniftBLXo8bA8f343TaD3xxA2VxfyyUf3uS6x71H05vlnCLp9IkS8LDl1fLXfu+HPf7BorsCyHe6uLz45nF68uPvxu4++9N/99/81cv9H/+o7f/YnP/7en3x8eLUE7XSieVZbFtUaQgd1AQk3OoxVm40IQc6iYpg5tddhY6Y0V24CAJHovhKzmuacmUWiqqJ5dDIzUV2Ku0kXUkohcHPvFqEQpNSSs0EQY4STKUEIzI5GvKKGfENWCRS3juojr6gOlw6bfbp8ejFchbSXUW+O87J7L27j5vLauu4k5N/+peurR7vUJ5FkFP+n//l/gHXiKZBYzTe34zgiMIYeFxddCBKipp73u03XdanrTLWahRh3/e4vfviiZiwnqwvcmMkMVWtJPZ4+vn7v6eOL7fXr7SHbLHDD4jWXWtjRye7TF3coDAexe/OLmtS38IpacLFB3+0O41hKVmLugxotXoksbOSQTznPDA6buAmDL0Tg4/F4vMtwdBfM1dRzoTpTubu7u7m5TzW+vpnuj1UCFMhaJNFXnr3z9W98SWccb6eb18eP/uJDM3n86OnXvvzNJR+Pt/ePH+8HGeJAKWO3Hz7+ZOojbfp4ue0vtjGKBcduJxEo8wJGP8hszGoUFGbk5N4UABSDgGAITs2TFMbWaP4wY7CruTlTkzWc6fru3pQp58K/vaPR2n5rm+/BIP5vs2hV98urBAsmsqDaXKabPGWMr3PcJ+i6/N4PF/1wYUZYgA5a3V1jh6urR2Wa3Z0CcQh96DgGVS5TthH9fsM1vH5+/PzlASfQCAvqGVwoJebgRCoMB4g9cJLEC/j+s3w/f/aN3/maosBIFbHLp9vjjz/86Fc/+JVv//q3/uz4vfGz2YUcQgaHnJdw9pA3uvKqwW5o5pZm3vxGa60OiIQYxQTZnAagx93pxi/2u6cb7+zF8flms3//d97/4Pe+oYvdvz5NdyOcTc3gcZOWy+klXo678eIr2yvbudogQx3rdDu/+ultPlQUYAQyoAA4ig9xqFanOZ8+/RR39fq96/5Rx8xstNScHSkxHHm03nGx2yVLp1fT4fZgVs+ChbVOCogsbKQNQ1AXmJl5ZWMniLuvUTYgCAdyNEG0u6vq2dXnF29tFlobzq1fTwTntlZeQ7l+juWEt3Crh2///kGrh1N6G0R7W2SGny3T6C+3RP9/u/0Hx8Bq6rmHa/cwpL5w13/hxf3/cM5v7h/eYkkDPzsW3/7gs07H3Q0GZ/YHJHvlUPsaVV/Ojk5qameODBGxCMhNHfVM2zk7bomcXQTYid2IVoSitR+hys4ujdYjkd+kC3NTk600jYZS1SYLUTBD1UQY7I3Aaw1xOie8EBxGJBBuGUFQreZrUaxwgRNBIgcOkDY/ulGjJzQOqjUPLeamODRqvDJ3bQafzbK1E20PvwhLAMFMa61tij0LM12hD+7451vvLHTGBBsZCw83rJHOuFkyeeP+NroWkzsaMQfnm3um1v0cgLUe0N9yaFr9jc+Qgp8/sSFSb4m9Go/m7EH01lABzhF9jsYa8gqHKVkLzSN1c2dzERJZWx+Ac0PHVu7V2tdyb5iS55wbxRlEZxuvxihjIVnf++ulcm8KVdfGx4tCLYze18SW9bK4VgAUpeF168BffxugKUx9/X3ap8o68ZO3G31mlOHh77V/+9ax8IBDnaeasxyhoVci0sw7zRxWjaw58bflDTMRO/HKF2yJarOaVjMYMXmEEDdTN4khMMcQ4OYVIYAFnJgTKWsu1RdIYI5StOSSF1cIsRANHHaISRQWQwKompbqyzK751wCkc3Vnl53qQexljIfTzdB7ObV5+N4FxE3237OSOe72XBiPDSvzUNsdrZ+ZmQBzX3pLSbyw3A9s87oCxPXm80fghMeCKQPYY9nH4Q2OazlyMoKg/lZYtqaST9z1MZSbLC+OeZxkiBxiDH5/YtKJGZgEoBqxXia7+8OpdbE6WLb74ZtjOlitxcRdnz44YdaC8xkt+lTFx49Vs1CVEudT2Pg2G9ikpC1ulWYsUNEIgdh2b53QVARV12Gfnj69BlzhHLf7WIYasY8Tt/50+9/+ONPuhyWTQ0xMIdprFrGOAznq2eAgX1NWDaAnJlBYHNrZE6P7t6kcwaG+hrvCaCVcEAQXomADldyb6bCWs1JqEGoDkgMbl6qLrW2xnJe6GYpp/s5Z+iIvk9LzpvHodunu1f4l3/4x3/xk8++8a0PHj+++i//2R/cvHopDHi9O746jXdlHpn82dPHEuT73/vR/SGnLu6vtpy4EkpW98oiKclpPKY+pbAhonEcD4dDMcxzceXNZvtLv/SBVrx8fkPM47gs8zzOBXm9NrFH0fXrNvgK3KCxw2bYPn58sb/YXuy3nevFdnjn6dV2k+bp/tMXzz/6+KNvfPDVkmeGRWFJYWJyg4RIiONxBrOZHY/j7f3NPI3zhCC43F1e7K+2m23+FCGtEucQeLMZYhhq8eNpdqdnT4Zlqctc7+5OgeXJ0yf7/Z4Ip3G8eX1vVh0uQYDudDo5WMBFKxMaZU9Vqxk5mFmYjBjCRWtecpAKlxhSl1K1WUTcfZpOIBIOKYWSa9fFPg0xBIfWUmrRtfePIKELSqahFDYjrQgkS4U6JKCL2A5D3/VD18Ug83i6P9xM0zRNeHp1CBxN1azkotshdANi8uSkNsfEgZbtLj59ut9s03g81DqlRCmm7XYzToUoCEGa4ovEoFCHuasu80hgczJVOKl4XXLz/k8UTnPNGV0CCLUUrR6Ea/GWNOHGQAhBCmstam6n4x00GMqjR1e/9K0P7g93Nze347jk2ZZgEKrg+8nnjGm+O4zTaTzutrsAHssNlBiUovRx+P1//pvTYZrHMS+6TOVwe5rGeR7H40HHO2BaJ7wpKxzY4+I6Xl7u4iAGffbuo2GXNvsudsKBQickfsr5/evrNOy++/3vncZlnMvnr+9fvT7e3syJu67fGodScsGdA1FCF5IWZSNRt1kxIgYmJoY4I8+2sHYdpZScdTErx5rrEnvZUFpKrqUoVXeUxZgSGbBgmQzVTGoXN7rgdDuOt8tuGzuO6GK36eFKpCDTWg93eZmmEKjMJU+jQDbbbj7Nc86n00Ekhj4EEZgScUqp6yiIuGqzeRSxOKBWCEAhFEsxaQrBzWEmTE5YZn10dbFMVe0QBSaoPFW+vV/sh8+nZNt3P9i//9Xf+9avfu3/+tc/+MG/+/D+J0DCZj/YgvmzexQgcJ+6JJFhblTdy5k0rWbuvpqWre/2hy4Kx5BaNahaXR1aSSLJ2hppfTV3lxiJSZIwkarVnIuVFONDIVorjAssMMHcGGsMM4M5CRGZV1Xzxsh2r7raXXVb8C7P+LzmmAoVyXHA4y/th6uu74OYzscTVYOW+9vleJzUeT6i6z1EYY7uYehjoGo69n0UFhMbBu/6JIGIrDllEBkRmZdOenf3OusMzbXWlv0GImheFjmV2JMX0+l+qocTCCgZgeAuyIzCACMauNaKyog0DN0+cE/EZcFxtKHbJGYzq6WAaLPtN9uOqC4ZuWR1WHHLTmuGCUKCmORpcXbrmnlCC1DmWkyNttsoAgiPyymOvO16rzQeT3kaoaUu/uLjl/cv7ymqdPPXP7jcbnuOdVkyfCaAyYU8sMVIkZxMYwBVfXXzOXYgJncz0kAw0pZ17MRgtmpr5B098MsNjBUIha613hqjTedFDz1IuB6UAHQedeel41ohNj+LL66I/prbz/9cI1eTAcyNf14dM6gKTOa5liMADPvt0O9OpxE9hm1yb1JIKqWqObnXoqUuEhFCIBcngh8jdX1IsxXMiC2CJqt42HRdDHFcbtAUFmdlA4y1OhjosB2uX59uxuO4LLVk58SLFSsmwpSa367Z2ULXwOQrK7xZe6wcViIHzJv1XEsnkuk0CTjFGGNcSElhDjD6TYrbkG1ZliUGmevMiJt04WYnWuqgfRqWaQFTlnyYDsiO4GkfUpVEg3jIU1YoM1AAQ9d3HMQLvDo7CwWFuxZkBWHOJWhgNS+etYoQR9GlekFVIDo5WVErlVnU9EGQkSh0HI2hZC5NaQwvDqYWs6wPFW/b3tIztCW52TqEHuq2vwxparX6mWjAUCNiEYJhrVnwBiF6QCoeVuxvY1h/b2DLXxMteTjbh5P/G57ef4geWA+jp33R8NQv7PM3uaZfGJc/cyj/wt+/YGMmCcHNGovEzpl2wErcxJleaNWyGgs32VYDwBsU4udismqVtehZVYeNQbMiOO06MIPJyYjh3F6TDriEyE5OfMZhyN1UXasW1ZqLASxNNATV2lw5QowxhqzZqEXTCa2iLDhcTcHUGD1RgsIqTK0UdRixg13DdgguYuTqxhXExurqYICdRFrF6wwKDXJiACyAsCVqeDkHBq8uGOZGIBZukE2t5mLeBJpr70DbpNH2fMCS2EkotGwJXr2yW48BZ5MGsyZGFG41eLN1b1gJMT8YKgGAOUljufgZLFqBgPVJbgSkhrY3ZkxjjTb6nTzoDxs/dx0RrislrHGi3UmrmemaxuNwgyA0VrUw6fq+VuIId1p5IqBGRqpOZGaG3DA/XlE/OIHIuXlw52kRSOuJmj0YZEECQoyBQ4vXfBiHZxKdOSDWni/38x7n0d0+4g0fmehBzAlfFyOrtdqZkrZiSasQrgExfua/rVQ4GHmrmYmpPQANcFCthqVZyTKf/cKa1lWImViYmEHoh07danOfVWJZo/XWE2WwcK2VBURkRRVA75tNkk5EZNgMx+l0GI9zzn2KoZe8ZA4ouVpxTmQKZhEJuZQMA1cRh2NeltSneTzc3YZS5j7J65uXx8PxcnMdouAEltAW61BDrSBajSVXWAqtK/bAuaIHENrXSFFXXwOZ8HDJviB9XScte4A4zxDYgxzxDH2tt9PJiVsHppkdNcYrmoW3PfwItSUcyJyZ2lk0cXFIwKfISx7HMcVOOPRdv99v57zMy8wWtpv9ZjPAESV0XZf7ZTMMwszuZV6YbLfdMg93h7vj/b2ZcZeWcXZDFwJL2PT9dhiEo5kzi1Z/9erGvPSdpE5EZLvZRR62w7WW8P3v/vjTT26++50PX3x678acIrHU4u7Y7i7GeT6/iB3wc4TlOmLRHIZXDi2I1X31WgHcKhOTPsyPbZLj85MPbrYtTSFuvGKTD7NKqWWaZiJEIlPvuCsT376erNim3+el9v1OzcoS56U8//TDH3740Y9/9Mk77zy5wtZ53F6kD77+zVze+8nHP3j+8uPT6bi72G+3m2fP3klxzGU8HZfUox9ijL2rmeqSNcYo0iR1MLVqtiz5dDiF0JWcr69iF7unTy83fZ8XW6as1YVCCiml7v7lMaXU912MiZlArlayjWYl9STRAWWuV/vte0+fPHv6qHq9ef3y9u4zhp6Od6a63WwuLi9SSH3sjVIxGZelWnnn/XdP8/E05WE2rz157bt0eXl5sb/ohvj06ZUkJlApVdv7xlQ4gdgMOXvJ5iD2cLovP/3w01LLdj9cXV3XAuP5NB6R2Z2XpbqxCAWWtN2lmMy1lpMblmkBUEp1oxjE2M3x+rO7NPQhkAS2yrUqsYcgueS+7wKnEuvQbVLqYD4to1oWI2KPglqqiBCF8Tgvk6XNNjC5ERTc8W4fUzIJOB6PXWebzWaZl8PdZIYu4rOXry92wzAM+93Wa+0SCZcUmMTHMW+GcHFx+e477zy6vAwEXdgtBHGtyzwdRDbbIT2+3kzLcDiVfrub5jEEMi2wyg5bzYsQO95sNhx66YqB+mGPcDqecp/6GMPxMOalUuJ5XsyKo4iQowoTUVR3YTDxvBxevBxvbj/9td/4FrMSrEuLW0yxJ0pqztL1XQwcFCXDMuZsejreTkcE4NHlxeNHV6+nGvsw7OKAzqo/1itS0kyeQcoBAUZaqyC4+1JPi80k3m1iGkK/SSQ+bNLucrvZ9iQE7W5fLX/8Rz8B7Hs/+HjRKdd6d5xKBTskgDyjzJxLICoFDuXgzBwoRJZcFxCEyGdyBwVmgxVz9SQpddJznG26vbmtVlrWppo7jCiyB1vcJkMRcvLCEM6HUjLMcfP8brvx/dXu/vhKNhFmahYTWcU8z9PJu+iXm7Tpo9dal8pMwtgMG2JmITOD4/Xru93ukqJIFBIFw91Ch/feuzocys3rI4cuJQk9T8fl85el2+z7IeYy54KhezewURj6rnQxF8z38zgv02G8u9w8fTTwfrf91u7dL7/7/vRP8ePvfvx//+kP/uIvfroUHp4kqUGz1lxyqUJIkYNzMePWQ3ODO4GCrH4xD0ZYcLdSmo8GWWsIEJOQNd62E9GagUoNcFm7NATuOC5zTn3susiEEARCtcJcuLHZ14lbmRgCInhoZBJBqE/f7bbXw7vvP3763nW/S6dyHJdjdyX7Z10NE2/NubK4VC1UBH77+W1RmmbNlVIMkaOazfOsmVm67T4OXXd5sZUgp/G05MndW/hwLrktVbWizPnJk6/cvJrubieUBQLpKUaEzmOAw07Hu2236Tfy5PHV3e3pcJyI0XdIYej7AWlaG43BQNW5GmGz2V4/erLf7ZiDVe/7nolLNXeIhJiiSCQERVVgqY5lKTOg6EXIKSXu+65WXSaPA4ugslXTZclwLKWC6OLR5dDHrmPyenv7+WfjVEcfb+oyimAwxeH+8Oq0hI3wVu/unpHUYKdSptTL1eUa8ANoFO9jsKKqlbx8/uolNtDZOTZQqjl92NmMlhQtnKp1tL21i4jobBNr5GcxhJ9jl5tgcO0M4+1VKM47UhMNEFa+udubf/6ZZdHPLZTw0Av8S+o8oloLXAABEziAMlouJ7jmCgMSHj15stn093evhgGbTVL3loazlCWAiUmtTpMGkEM63sU+HeS+LDWSsDAE0jEK+egAhFmtUiCKDe2Fu1etBmhbtFSwd/Okc1aRAFRJMUFOd2Ps+J33nvzo+SfgCrI1XdudvSmL2tVu8l4w2BxFK9QIzXKZJbKpVS061xqqbCXumHpDJGdXVCd1EXR8qqebu3uBiATqQxY+nA7mPiYHVAAAIABJREFUZGpKuYpK5R2Gob/a7y7qVO9u7+ZXRbOhpYGJkBO0uRUwFFbMeeWGlTGf7lxcPPmyFEoEsBWgoBSMPnEQYo4hhRBKHpnAgiQpcZekr9BslZhWVhQTFKq62quZr8bPIDMlP4M1ABoMamuvfu3rr2IGrG5Z/rAqbqXdGdw5i6faP/JbzivUjBh+fqz5ipP94uH3d7O9DXT8PMHqbeDlbQzrb/ih4Qs8tL/h4R4OQme5eoOH3maX/UNxrx5O7wuX1Rs4+hYc+Ldykl84whts9ucO3MhZbybLxl91MKHp81MMfi4C0XZkcm89JDc9a6oYTKv3NrkLw5P3/aCmWlVNoa7sEHDg5jTc8ozdwQIPRAwSApuJtxK0PQXsjflvrubF3Ly0QLfG4LG1VPYGxK8ksIFX3bk5Vosb1RUfAxoxwWEEF3erucLRYoGo4xZy7Oou4Mheyao5QEIeAzG5kQanABEmaUCVuiuFSNrM6Feo2h1uRGGFvcwBJ6vt9M9P+EOkGs5so/Vm8Yq+ADBmEaxl+aqYb9ozqpaogzcr0fOnAmQr8dOalJpcCCTw5tG0WgO5Vid2EEjWkMHVtdzQ7Gfd1xNfiUXnTpE7tOjKbyJzf8C61t2hzK29I3AiEemSQMuSKwBrocGOZgaG1q5xQ3E3p+aF5i7GTGQtxMWM2GGk2d2qA4ElgHOuUCDCGK5WuBARBW7nxCLtkjUAVVXpHKR4Jp6tcSXAugR5mO+cSZuJ1/rWCGsI5BsYxRou0gQG3vKGhOHt0VY8yNcEHDjEIBIAb/xBa/mXTBwYBCcDO1ga2uItVsXRRarqcKqAM1UYg0m4wphkf3XBirqU5ThZKQoiwjBsH7/35Pqdxy9ef5q6jsexlMUr3vnyBZFb1Eww1DqDqHCKcHJra3c4IKnrgm52RIxxHknYpU55iB2lIYSErBkZ2sOIW4wfxciAu4LQ9Z1ZcTQh/QqhACvbCfSg/GzXnx7YVGcqkYEI/vCO8VUS629eRA1rbV25MxrpACSyYLWaa955FqmE2qwlWJjJTQ3NwZp8dcZr+xu51dTLkjMiXj7//Nk7j09EU38cuh7B9sOOQCEMhSn0QynLUisIwnyx3/Upmqm7daljR86lZFtmBXAqo0iSGGKQlLr91Y45wKnWnOeRHeZ5nI650KOw32/3BOnTZuh2p2z/6l/+0Xi0Fy/uI3WFzYopnJhiCMzsWhuvE25EZyu5tRoCjNpNID+j2A/IbuO3Gh4AKSI6f23uMLdWm5F5Mww9a4kJUIQu54KsTMWYmSylZJD5MG63Qy214SZVteSsriDUaj/4yY9/8OMf/6//2//xW7/+1X/yj3/3t/7jbz97992Fpu319vb29TSPCnn27lXahJp3P33+E3fv0iZImKdl0aXbbFO/n6aputZj6fr+yZP38jJ1fHDHNM23rz8TCX3fDztJPXW7hvR539HFftNfIMW022yGYSNC7CCy8XS4u3uluhAqsV1fbb/23jv77aA+H4+HnMftdnj85FHqeoakmAQixBJ2ufopq/SmaloD2fZy96XEj/M+u0NEUowxBIAeP/qKep3nZdFxWRZ3gi85n3IpCp997veDVjsdlvupvP7w45vp+JWvvfv02fUvP3vy3e/9WT9cEImbH04nN7q43A7bgYBuMxyPR0l7p3o43Jeiqt71HVN04X7jN69GizVCSi3q2rMzUwhh6LuuS2Yuwl1HXUeqpjCFIRgJJDBoFCShCluq+cY2XerihRTkwtPl420/QO005nz86Hjx6KuE2HdXqpYiaR7J0n7oL4fuovN5OuwS+uhV8zDgg3ffvX58eXmx7RLnZUzB4AmBfMl3dzdPHsculcfXBNkvKpXTdEquKmyg2uTcHBEACiYdtl3kgdWIo7zPj07HYurLXN1yrQ5fUiCHzUsO5OqlT5vY74SGzaY3nx0FlGfFUm8olM0+hiS1iFZXywJc7PbESIlZOAilxFpmn6PFkg2Heu+n+7Lg+vG+511pffhu26ehj11i2W03wiQgLYXNzXU+0ulEJSuLx8gxRHPXEk53Ot6POWue+JOf3H73hz+almMuNTLcUQEwmn0CeU3Cvo+ngyLARVyYBQxWWKYMQVZtkQ4Mdoar5on6YddxgtVlwuHl0WDNx1PQaWaqJEalOAqwOCmRCgWxg7oj3+H25Xh9vX/0+Oru/kfJNiJGZFSZ4UCIoaYQhmHXJTodXzucRBEkhVjUl6Kl5GWx8ZQXiBsvTNjgvk5RKFwMV32aPn6FSSXOsJCL1VJpRi5eNagm1WqSQ6TUp82mk7BMlY6nJRLter6vrz95fdhvP310cf3Vb3/1q7++f/brX37yq3jnT/rnf3E33+P5D19ziBLDfFyS9HlZWFi9gpyFnSzG+IZAXsHBYgTgpaAWZ2MQN3zfRQhk1awo3CjEKMHMaq21KJhEKCRpuoHNMKhW1LZoM2nG3pMk6WOXDsdXFEGdFJkpIfbYb7G/6C+vLvodfukfPYkb7C63w6aH0FhitcETQ6TSMC5TyTTPYznd+7zkmk5HXRZfCi8ZV4+uHZxznk6npSzbzWa721xc7TdDb7BQaVHAXWIgolK41FKKE0GAvncm6jsZOxRg22MYpOu566O7Vy2lnC4vri6e7Cp74VyywoVjNPjuIkyHojUHBsiDwCI8aNpKv0tPnjy5vztNU7Y616xWWChRiY6+IJRYM1KphkXhiBxcXYglipkTQwIktN6aXV5ezsuc53ycjt2+J6HtxT4wTrd300nn+5IPqCPmUWs5WgkoCkLNyhE//fBjDv31hmPfOS2Xl0PkyKidIDjYnBRsxI7tZgsDpcBVtJgzo67IJrETmROIm+MdcfOgNKGCpp70VnwZzL01t4kIZCTAagqMB9tcdoBJzlnaDS0jZhgRQluonrvI6wroXNStUMW6TCJ/+09HW4WdV6LmFthrQ9cC2qJBa0ycBsKxgICA/fU2bnF380oSYl+De16smkuswh2BHabFmR3MltRrlcj39/fp6rELwVHd4FDzPopBl3H2gbsuBQlaaq6VzEwQkxhDcw0iwZkNIt4LSqY85ju9e/b00de//v6P/uQTkEIVhBAHL8lscZQ2TuBsyoGjV2On4GKk1bU9tKFLc54nz21ClI7RO3VekhXSOAx9t7Fg07Hk4qUUY3M45bosi+QuUeLAysupHDLKQosRoaOg4ebFie7hB6AievDFNLvWlTTRhaDzKJElDWWZy81SrGzDRRd6qVW1kHSkhDIjYyrZaCSl1G9SiEBw1zU/nYPD1cyKQeEgr+YKmMHOeVPW6tnW4Tm3dNc/1kX3+u1qB9vGzipufeCmlFoeBDltMe5EFlpR7KbWhEutDUrODG/iGLhrcxTFAzwGPKwuz6hqK6b+drd/LwPrF4IqKzXyjBE9/P+3+VkPe/5CPO7vhIFF5211Xz5/8D8sdNW2n/e6+vkr+zc8z1/84/4LvqWHae8MY61z4prj0AJ9z0oykrPX8YPCDf4wKzJgMG06t9V83d1CDDCYWdOHOysLKVdzc9iZA9NWWQYBArvA2RyujYwCJrCZaVFTeIXbGo33wBpwB6SVbcEMUGeJ1qCRZgEDNLNeaqEvq580tdnN1N2tsTCzWWBRdjJiATmzEhlRdTMzBlIw10ZAhcCjQeDuXg2moQ3pBlW1lgWhkcqseVc2CqyvKAnLOYQGKMX4TDB+uC3urHC4KTmbs2CdB4Rh3gz73F1LIayKOQI14KvFBaqrqQNO7G7s/BBP8bZgsI0Gx5tZhh64p+vsSABxg7/OekGoGTfo4S0V4opeOaghVA1CFDAxC6row0e5w52ahRaab6Xaag7GUVgYzXHHmMhIsQbxKRE1kItJmDkKCioAGIopmbIC3JYVazer4UwrLIUmSj3/1g2bZTjO7QVZlQVGb54Wp3UMrdw+B3tbL2irHNZ+LbfFDJn+jF6NA1hoTSMCvNmoMRk1K7TmO0ZgdnYlYoa6uTm5CTGTCpOTmLCtAQvmxF2K282O1ObDGFnIuGqugn4zDMNuu78oL35qam5GDDAePdqZuqrGI2oBOigQJa5vHqsgZZHQxb4PbguMnZBrXrLMy0kSbTYdxEvNCHCAQmiPEAcRZi1uZk3buvKh0F6C6/qLGhRIK6B1pqm96QI1ftvausSbYQlfsxSwcvGpodfc0NOVcYSHMCB4Q3Jofb22OY3WVE2sUT8PpNEWweyOShLKDDCef/LyvWePd93lId1KpYqpC2mRxaMs7pl8ynlZlsRipV4/uu5TcFMQ+r4vdTl8Nj1//lnJJcY4TZOEsL3YhRCDKwi55FLq8XA8no7vPXtnfzGAcq05hLQdhpJZKN3fTh99+Nl3f3T7qOtzxmYjbNBSSCSEAPJpPMkK3qP5zRM157Tzf4AbHqaVN2EITar78My2G0GNAdpMA30FubgFuDq7gNiasZ0zxy7EksvCWSUhxAg3U0MER1+Oc+pENZtXY8SUYhqIPWuuajjie3/+/PXdH374/KN/8p/8xpe/9vRrv/SV4+nuo49+cnPzeqkvn75zXYs7t9hWdiAm4tD1fb/dXjklVdRlMtWxz0KxD8PxeK85V9PZyv29NtujYrYsJS81xbS/2H/w1W/m5e7V4YYPxO67YRMC53nUelqW04sXn3z7V77xu//Rrz178vTzzz/7+JNPstZu6BL3IN7trppBIxlDkaiPLLuUarVlLuO4hKAbpqFHM2xe5eeN2YspBQ6DEUbNt7f3t058cXn57uWVav3On/8ZRC/2ezMpGK3g88Ndeh27XRf6yzTsKJeaay61VnLzcVxCJyHGYiRpy+5F5yljWVoEMDiAmNPQY5hSr4C5VubV1KxxgZk5CExIBKDCQRMBQsnJ4CBLfRNVk1vP3G+GDiEWkkF2HajbiqRS85J6LEs+jiM47ba9qYRAgT/vkwxJtn3kizCNsh2ScNVKMQ7vXl/vt9vAJL44LV1gp2jElaqWqmXijvcbdkmFu6nGEJDH0bQQaz+gFFRFjCQ9SzC4i5miZQL2MZIHItBuG0quMLBok+1qVSJh7gQbhMA8GsRwdKrqKHrgKH1IEmQ6lXE6luKSui6GlGLa9F2fYowOnSYaynbY2ZBiHyUIvbp5gcFmPx6WKS9V5o6JyXGx3T6mS9LMMKuVvVguZbEYNnGzWaby+acv/8U//69O98v93fT557eff/r58+cvD3fL4S6XMVc3klDEYwx9INWiRUuuSCYxEDMhUAKJGJNpVVchQk9YYBVMTVvjMIDMfMoLG/JclsNxurCNEyDgTohBufriKEbVSd0LWJmbyngBBFgw3dXDq/r6cmIe5mUKkftemvWkawgcYurNQy7zVGYRc4/sqMWmqeRsuWCZrRjRNIHEIqe4QZe0TRxuJSzYICQrOdcCCPotmKQW5IXmqZyWT1LXWexJO6Fg6J0Dp5BjrE7wZV5ezaf5bvz4yX7/wdd+5Q9++dd/7Xe//p1/8+GP/+z5j//HF0DBBiDUHayF1WZrfqxE4uR1qYAhAAw1sEEiEmMubRXIzGvogxNJDBJTy6txMhJE4pY62VJvqmp1lS7oUqwCQC6QgG161O22r2/vZ1vQsW/M84IMH5Cf4d338bWv7775zS8/+8rVr/z2+1O+O4zH27vb++NhqVN2O9ws1Zykm+bKnNRimToschr1dMI0WilUjXIfipdSs5oOG94/itttANs4j6Uu43wwIKVIRKqu6vOieVZ3BKr1+BpGEn27Z3Xrk3e9b4bQdbGU6hVqU7aOosdd7Oq23I/LrGpzKbfVK6cSIpi8VmWBJBjn4hli188eEfvt3V1ZECN13JWZx+NMqdsOuwWVg3MkCzl4CApr8mhVRe2GgRIZeQuJe/bO9WTLcToobNh2qU8ioUzL/c083k06wuYgLmzq1aAERBK4l0A+nu6ALqVkloouLB4TRQpBVctSCyyrbFgohBBhUHYLRI2B5gWlugFu1rxN3uTvgIzIQCprmhWsNY3cWnSQt4dudeg506rW7hKBGc4EombK4gDB3mBV/jbb5U1FfaaT0HnJ9ObPVmo0PqCvxRLUtTbn0NbQD4wA6TDsuJ+BDv1VRGeVcpUTJZCUGBgoWpDd4BUmzBQg4qzmOc9WjdjnOut64qiN9J0o9kEQxmpOYiTGrExKxuQkwpHO8Z7NXaF6NbJqJZdq6iVK6If47jeQD7j9DKagADJRJVu75gZjL25MpKHR/8iKusHczLIXSx5itK5aUt2YDha2KKFmKpu04UCH8TiOuVY4w6hWrTazj0wzd5LSECUh26RSjOrCdZYsVTCDjUydK6gSnNjIV8BQRRCKszCZkJJXQCVa3IRtET1MR4QgTkoKWFWqdYkIHXcAs4utMiCq5qBSTL3CyAgMA/s5Rrt5nfq5ljk3fR+oeGdWz1vVyHkXXn3DaOVMvbU6b3WygVrAta+Zrs215Y0witFCLZpfW8VfvsnDEPYv2tv8XW9/BajyC4WEb6ss/zL0Cn+nEkI/u5g/nNn/DwGsZjf+D7YRfmZIn1VRDwBkkyipqog0JZe7l1KsOdk8IG8PR3Go6sqkdYBQURTqYhThAQSsT2ULNsBKFoD4Goy6Jur4Cq8QNdN3rVqLQgE9G4sT0AK0CCSQGCVI4xVp0dS+cjcQrHllNvaRWdWWlEdoGYJugWs1d4dW94b0OIOcm7E8CcVEYi0Pb9WfrbbwzZ6qtSxQ4V7ZrbHNwSvfIYZGL/JaK/RNClvTzAdaaa5zHs/OSbTaWZO7KVqunrlxBoElsDAF5oj2ooNSnhdiWTmHxESG9op8g36vgGO7qg83uzHcVgCBHvZdbW685f+1W7WGuD3ICB0GXglZb2HE7RVpDSCwN6MCIoGEhdmYi5qTOpqrfwOwzM7zLyCIEgILOao2fLGhpV4JgTw0lWtbIII4SGQqVqg5ESiMADX2lheM/4e7N+uRLMnSw75zjtldfIstl8rK2nqZnhn2cDjkkBApiCIGIkE+UCAgQb9A/0FPeuOz/oF+hR4EbZCeSIqafXrYy7C3qq7ONVYPd7/3mtk5Rw92PTKrZ0iAgnpE8aIQFZnp4e5hbtfMzne+hfDgg1SVlVWyN4tJ6zPPLNn6u/rckfhK0iycuYYiV1Dg+Pg51LY+2/zQ6p/4YM0OIIT4wLhEdd9ngahVrcKMqs0SNgBm2fBOEiqRpIkcJMOt1HyQSlH2PJbpMNy8uWa1KJFZMut2vL/ZXn/+sy+ko9gEM4tECd5I7NeL0LTTmC+vtsuztSm1oQsxppR8NLXRTN2dSFLR5WpJzKWMu/2QUo4xdKEX4WEYwChmjbAFFLeaReAm7m5FA4uhWi/N8jbUkPKHs958fqrw8kO/iOuOWfnqdT160Ao+LJ4GN4fUw0vtOD3MXquwIuHoXjlrjhhEJCLMrCgV46l2DA6oqVeLLvVxVM0KxRdffPHrv/qNJ09Pb/dvbcybTX/+5Oz+cH+5P4zJQowATdPkITYiqjok9eohVfLd9n532MfYOjg2zfXtdry7N6coHSDTlHNKw+5weXV1fX396YfPmLsmiqutlsvl4lSou367/6M//tM//IPv4wY3/cioOKGjel2HkHMuQ5ZGHg6m73pHs37wHUhbb97jjVrXn3nE39un343xDCpX9S4RMWZBK7MdWwdN06KUcZpW7aptmjGPu/0YAsZxDJHhnFJu2iiRQxD1eiI1OD7+9Y/G8XB9s/2Xv/t7b65+2q3o2bOLb3/71z/55KNv/5Xf/M53vqvqd/eHk/XFNE7TlNzhRCE0Xd//4R/+8dnpGYiXyw2zkMvp6YawZMZi0bfLPufx6upqGA9mEg1CVOm74zhc37wZhuGw3++325JxcbL84OkHj87P18tHy8VH//k/+ocnJxst+Wdffnl5eXm33a5PN2cXF22/cKJxTMOQbq/vLy+vL19fXr59e7e/v9pil6AH4AAUQIEekPdsthwwPPoVOTk5Oz877/t+1Z8G6qY8bS+3N6+3m7OTb3/rN93txZevxmHsuFPWsi9f/PTy6u0lCf723/qtu7ubq/3ucNi7e052uxuL6nITx/Hw9MmHzJxzJkZRM8OUR4i3TdsvuvUKbdeYam10hMDMzE7TNFY5pEjj5uOUibRppWmXTk3WXFTHNKlN4+glIwgfhvukmjxJRGzVPbWRH50/WS5aEfr8x1+cbB63zTKGhlwfX5wT7ReL5tnTi5PV4rC9DlKItAkgLos+qo1kxORButWy4ZxTKRat6xfDbrdomrZbbhZxRLTJrIlIMpXStWHZn2fNh3FScw5UNJXiaUyHKaeC/SHG0DdN1zZyetbHwFrMjcahBIE7iQQ3L6WAEEQ4ROIexOoHBrVNE2OXRpsOw253d3ePXICAVY/N2cliuQgxasnDsE3Dvm1iZE8uQynE6/0+lKzjKEWJYNAs5Mt2mZJOuyGN+zwOh1u01D57+vjp44/PTp6yt6ryT//b/x4MjEAGMpAAAXrAq9mooQAsMTZknKfB3MuEpqEYBUDDLMKqpllJSxMbCRK6XDLcAYW7+3G/G6ZRx5LUoRgOByeSJjQgCHuGTTYO2SaySVEiECQE01LU6jTe3eqLLy5vxptHv3H+8u4+Bl73fQxxTAOAru+Xy55YUqkqdwKgRcehHPalaG2CMTPGaTQjZl50XWiDG1xHNut7SwlNQBPRNLFrwuZk2XdtTtNht9sNSZquGE+jOywEVlBO9nq4FIIb2LBc4HS1arx8UcYf/fSLb378K9/85Fv/8L/8a/xP/uZ/90//m3/+J3/0f/zP/+fv/os/PWz17ioLN8j9sE/FTGLsFytd2XBITWyFeJomLVqKaxljq8ROpCCYoijMETDFJjJLSlNyF+Gms0CwquY55rK0iwWxgIMqcjFV3Y5DaHZn31irTk3bPf7Vk7/9O7/1G7/9jeUZSXeY9DbpXeh0tVr8qz/9PQOmabrf7ba77f1hcmKnUIzN0/Z+JOmFY7ROJ9/dHe53ZRygpgrw3V0qE6T0K1ouu7ZBLodpdCZ2VyIOTESsBaX4eEjjkMfBSoFgNx12fdO3vSw2vSPFYKEJTd+EGFQ8IlKUVJKLdKvGzIqmlMo0pskTJoQutF1Pbpy5jbFZRgR+e3OlliWGxXq12vQHGiwj7Q9Z4Y5CnL1ddoumxKJNpkyT25islKylJguHhYNJqSjjyfPlxZOTH37xw+3hquulCWGzPCnJ7q8Pd2/3u60hYUHctE2MRmAXUdOcplp5iIQY27ZbkE1S1JS7vo1EZdgP05gdVApTMOBuu4XB3BpueQEPYx5dYa7Vyt2PHheAQ4933HHpn403KrN+3qFnuj6A49kb8zHnuDdr7aCCKhwgx5xuHE+seDhqPvShZ5+L9wUceHjC41eujSskB5MRl2rLgQisgJD7JZ2Ubn2O558+o5h3+y1zCFKYuev7KN39dnKgaLGsMUYJfQgoaRqmg5BIoNgK8XvHZkYIsWm6QLHv7IBJydxcTY2chSjAXJUKIm5vrqZxb2RlnLSkoggRiNjn/avr8p/9o3/w4x/85M/+5KdXL0v2gRtGDZRWFBJmKVwja0SYKIhpMUcxheZuFczMgqJRLHD24XrzdOOd3Q43h2Hfjg0l3F5vh73Op1AGKXw0jIa73dCmVVmFpWdkJSj51u9jaCgBNaOPoYAhS2W1c+1Hs2sWNoehBlIBDSOKtCJ9CPdFdRxZJEiAqBa4m6omJCevgVSmVk1FDFDPNX0nwAkM8+O8mCEWc/VadByhq/mTfwd6fuWihx81qw7DRBSO6Uv1kFddN9T0yF6ZT+VeI0LcC5SPveR3c26uX/+CF/0P6fplAVgPmNmxbnoooP4/HtFau+IdZP6XdP3b5agPFAe8AyPmusXdS7EHSWYF4GwezOOTV8whiggTk7m5lfqMYxrnu4grbYjBZOo1HQpVyitEUtVSIGEIMTlxlZjBANRgwTLHMdRVmvDuLmXmICGIgKr9pQfi2dlBVWefeJ+haDIwSQ009tmrO7JU1AXqJQ2AENV4w+BMkUxCYJZihd2NSRDIVKkuLjNHtzpU1TcMIjd201pQsrtXEgpRlS7PcmVzJXV1Y0PGjLhUUy2IU5WXWsVLjkuSHzP7anehRixXf0OCu5Ed2S9UDSbq+zmWre/Pivopg7jaD1W1IGYiGB0Zcv4XzKH6TyFEOhpi1WzHeWc9Lp11Ky/uriVYFIk1CZ7M8lTmllH9ibrmcbUi5lBjFonIoMft3gggN3hoG7OidWEFEZOTixAJGaPyW/EOkXtYyDGj/z7brs+MniOr58h7q5/kfJnbkYyCOUrGKqvLq082OdfEg4fGgr9/b2AGbEII8+1jxxuKZxf+OsxMDiYSJoFVDox51bcnQUsUA1MQd8vFoEZOgQTu+/0+7QdkYwg3oevaRmiyPE7jdNg2Z13TCYs3oTmM0/ZuG2LsF/1yudhu75d9n5JHjiFGd5MkKbsn53ESlpozE5swjlZ0UrWmaQIHd8tlwgayMy+5ntmdfcZNzIpb28Y5hOGIiMyg1RH6o3d+bA+zCg89o/em0YNk9Ssw1gNMenzVeagrYafu+hWsREWuGEFCCOLuTBWsnk39KrLjBM/uEEsFDgS8evn29nbb9Hjz9vLq9tXJo351stwe9rv9voDXvpYmNlE2y9XJejPsdwCYPDZtiDyV3AypXN9f39wIh+12PyUQ3TZNxySqqkVTSuMwDPu7YThoKevlarE+EQoxtJvVxYsv7r/7p9//yY/vwwpeRJpQVBXGIbh7ycXMpAn+XsaiP4j/H6b3e9vf8THHrw4Js1bz3c8f0auHvzAcAXU/amuZHJgOQ9vUHHgYs4SQxrwfDnCUjMBU/eNDbDiwmSUt5hpibJbtz372ksU4+Pn5Zr26GPPtq5eXJX/vsE+73fTo4lkI7cn+8OLLl7f5dlSklMz1YIe7m/3J+vzs7ELVmCVoV5wYAAAgAElEQVTlMg05L7OEEqOEgBhZOJ6dncg955wBaZrOnA6H3TDmYVwSY9F3UB2GfdOGpgl913z04XNyPH3yYZqmq+ub6+ttv1p++PGnLvbm8vJ7P/zR3d1BJKZJD4dpd7/f7faH3WClXUUPWqZouqwzm3PyrM4gCpVjSyAMN5p3N3ev90xC5EbSNPL46aNnz5+vVovLtzdvrl6Jt08ungKU0jiM92oZjt0OgbHou6Frp+GgquZII9JYnFIu5ezsfLVY932z6NuSs6oxeRonBq9Xq9iASN0N5CLMzHDPuex2k0iGMZGoFvMs0Vn6vmmkYVZCGi82J9NUQphy4cCNulgqKY2aq/dv6dvl+fnZom9ilD/6gy/c7rpGmSbV8dNPn+TRmbRvw3rd2yQlpyBYLruch+3dbS7Tar2M61WQGAOiCVFpRJZNfP3zz/M0MYfimiylwVPK7iUEiLQSJGTEIKloNreiVANVFCUh5cykOWei0EThTZuTp7HMgVXmOeuUDvAMkthS23nbe9OFNqxyTiISJJB4aLzvUQoOB6SCUtC2YbXqwayZmFeNCKMQiJlDv7p7O5TipRQDicRGGKzkyt5E6mIbuT2bwvjNJ49Olmfkcv1m+93f/5Oby71lxojqlgIQt8ItADXXapsNghs0qVZvxhzgYBd4Uwpl24cmwMm1mBa4ERUh5ljx+zlvBwoScAwKK8WZID3n0cBOUGNjc6Ti2cpkSEAGGbGwgN1oProwbML9VbpO+PRvrflWUIwgRGRKpq7q05hDoKaNLCu3MWtR1ZQ1FxChbRtqxUn2hyGnzCIx5sYbDi4t0AezFjhYATlOT1br5arromnRyUgtAIvFKqtr8WkoozCgudg4omRYQd9htWm61eKkXZbDuDvc/OjFn43p9vHZ6SJ214sfju34W7/z6Jt//T+dBvrud3785sX+R3/2xf0b4AaqJTUDtIcVByI1LsRNdHM9pCLKR46Bh+rHTQpykIRALF6KEwoXDgpAFQ6QILRxd7gDGLEDM8oe6ljh4lv4+OuLj7/+q7/xN76daLwZrr7zxb+0F6O0mcNU/FB8hPt493azvlit1uePNt2663bD7pDudxMomPE0abGBPHU41VF2d9gfLKd6TMJ+N5jYqqPT09VqE7Lux32CYrFYdF1HxOM47fcHU9JCw5in0XKGFhSHOSYbgndNDBQCU+HIFMmFoARBQbHsxcnAEq1bcM6SRKHsjLaPTR9jiMzSxxg6DguZpunN1eWi7aQN50/O235/d73b3hUQsCQ06VCuF3rG5gxiJ3MrpeSSCEyBnDxpUbe+65aP5OnzM4q5+Nh00i5ayxlFD3eH3d0BmRaIRMQkbtLEPgpb5pSmYskDYqzd1EgcyaO7VNsHBqlqTkVikNBwjGnwu7sdDCRMXF15tYbVWMoVqwoSYO5OPmsOapu4ZiIbQKCHhHBUKQbNbiVfoaEcuTTH2x4+78yzFubIsSIc6QXv6CEzhvUVQsJXrofOVq3chMBExFAYPJGod8i2L9bHhs/Pu7Pz5ajj9v5W1WIgkdDEVuFMpW+Dq6RcjjH3rqrDpI3oql1uVpvTfnN9dYuIRhouVEYbh6lhirEhL0Zubgo1qooSd9Xa8y7TwIQuyphp0vl9TyVd3l39PI3/0d/5rYvd2eO7u8kud1u3cU8I8OipGBGJVLxFixqTMwxmFdUWWKtGiqDcsGzo5MnJ6ZOTCeOAIU35+uaGGKUYK1cBMRzsEGeOccREDjWb05cVEIxhOujBk6MDytx7cId6ptmmgsgt22iizlWy5BzRdU0TKOdJcwpw5GJZSYGqxQMzYKWMuRCx15bUTE8zc6+UgUrCOgoJGHBo9WdjN8Ox+IM/VCBVhEBH+ek78c3831xdVmxX3js6zi7HmGOyjh3ldz3nh3P7v8P1l0y/+uVdv1wG1p+HsX55L/fvdP1bVI1/IZ/t/4VX/HNz7AGOeP+l3q9b3i97SpkN1+dRPf788XuAEGMIMcycHXV3J0ZJhggwqCJWR/0UVcqSEzGY2avFNx9FL7WiqhRXexD8vP8bzCQLgpMwV60Z4GAii8yscIWrWzHTolb9NmdwHUIQsBixk4CJiWeyjgOmqBuPE4xUKFhNaXFyaKkRqcIOncGPh35LFSeZkz/4ItWhoBqsSo6aLCciIFLVOUMPTgQUODmYMFOpxKCz0Kx2Vmo9XqlEZg7Tmr+nc9/luARBq0eYf4W1OX98eMDrMTNeeHaMPK5182box3VtjoCcZbkAMY6hhHwU6tZ7reKzVeBZfxAVW3M3IKiHAGIRCeRWJq2pkQzmSorjWhpxNd52m3V8VRZpVD3+yRwxEDVBAM2luFUbao71kzTjKh57uM1mg0Kq+snK0LGZPe0VWKH5F5whZqp2hUfXTn+4iwh1LDEjMu5u5jOl793N9d4KTail4y+gCZU1U8GXSjxiJhIi9moJRRV1rZioAAEuTgJWENxNySk0DPM0TCWrtAHZLVtCcSGwCwUE1ykP+2G9Xiz7RZoqgNX0m2WI0veLXFLOZuS5GnioopLhzBySs6tJQ/WoV5yEmAEzNffyyZPmMqfDlGAMwFQrhAo8GOH7u50U8//mFELi+Z+8RjkZzQR4d3Ka/e0eYPWjZPkXlzLC+wNPAIEqEXPmDdXAUxImYo4hBglq6m7GBe94Ww4yGHGzZOcy7YVVg7/4+eXtdnv6aFGK7ff7di0rWqrbm8vLw+R50pIyO/aLaRzy1es7YusX4ez85OTs5PTiSdufgDrzqKUQd2YWhQVBSNrQkHmF3ZvY5nEoufBys+7XDvYSDvv88surL352rxM2m2Z7k6Diph4QQjC1XJKwtH07DcM8Rn50CJvR6ocV8y9Cr1B/e/pKx/ZIBTwyuuYj9HwDA67wWZGEMkwyE1lrACVCbLt2sc07Cm7qMCWnMhUYS2SRKC4gcvW2bbTkkos7d91KIsyn16+utneHH//wxd//B3+/iW0X5Wsfb4ZHw8+++PLlq5e3d7e7/W532JN2aX9dioZWFqv2yeNHjy/OiafVuktpzDkXdonLtm1UDRRKseVitb3fFdVx3McQAXcUCVit+pOT9Wefffbhk2dd09xcbVerVdduzs75frz7+cvr/T6/fPPqxeXnY86lZC1UMjS5KYN6ZvZkmpGnVArgUDf2uugSAdVVjRnpFgOp+YB6Lmc0XaAx0q7r1vfSyjqerE7JQUXL/nAfiUDatpEY0zAwY73q3JbTNMCTO7qOzTAOuL+9iUxC1nfRravr1TBOsNJGadtAgBd1QYzSSKWB5JKQ3eA7pgA4qITiTcttJ5ElEqtT24qqAm5mSsldiVLbEMjXa5xu+iayl1ySayYi3G/Tnm4CN6pTGpZpvE/TOucpTcP9djsctlHgusxlGIZ7J1suloyGPLgWV4kiTb+IvBpuL9sYxB2llGSawOZRmEOIIaSUrKTKL8tFd1MJpTALYXJo0zYSJU05p7FtF0EawN1IQtd3fHNzP415Gj3nEYLYYrkUcBObJsa4398XzTknCdL2ePrsdHOql1f3+wMkIgi5aU5JVRlom2jqcBemvl9MaRyGMk2JyKOwNhSF+9AIGrE+hrBousI53+Lt63R7fXjz+ur1mzfX9wPSLDxxF+bALG42k3Qd3iBGqAHFxpzgDGWwwKVkAdStFHXiUuNHRcjhEIQ2OJe6Hpg5MiJHiUFTNgUIElCFgUZmVMCkk5bRKcMVsLmMrhspjFhFohc1PQCGTX9yfvK45L0X6ORQT1M67BLBLx6tHj1eaA0py2ZqU/KUq3eDE2nTRBhcUUxzOqBr+67tF0IkXR8C8247WiFY9pKh4tnYqY9dECUOKadpSuagGCQIcds0QSQTtO+JWhktt8VDjP3Zpml551fT3Ws2ujjdLOLp2WfPnobzGNabT5r9Df7O1d8cd1om391O93fDmy+vfvrjn10dtroFDOjb0DRgbWJfiuacao3ZNA1xULWSjeZWKKlAzWCKZt6JIECT0QJqJ6fl+UfPnj//q88++qA9LXx+u7lYUJT2fJqGfcb2dnt9e3s3pPsQ0PaRQ/RSnq6XoXUXLWYppcMwTUmJhTyKBOYeaiXT9XY/7uh+O2h2MBBqt8+Wy/Dk6frph6f9ku53DrcyGgtAVoqXoqaYppInq0RL8hCY3GlxwkWTtNT0AUIMhC5IFGbyYmPOnquWyYgZFGJHG+p0CVMK3DahDTGKhKZpGg7F8n7ai4DZ266Fe7/qwC5N6Lppd3/Y7VVlWC6bu6tLQdBUbDIYimYAHJhbLp6VSuya86dnH3xtuXocku5i549PTqWVlLVM5f5qO96OrXexbRxUipUCZs5jsQwRWSx7BGk7ZQkEduOSMSVrQm3VWFFVIITQSisiqFFEBm7EqqWBOAWQEiu7G4xqV8CMvBoS1VKg6rDrtkzvgIOqx682CuaoAM7xcfVk/q5tN4v/aJYJvAOq3guAe//rv4lo8/5VJRdMEGZndi2wQoJFi1G32x1ZTOcXaxY9bHe7/ZYFbReb2BLYXUXCYhGsiKdhKklVTWCmcCRFCLzeLNf98rAcYkuttZYs79N+GotQ0zVgNzL32uyk2rCfOR0B52enTYrZc9/GZr+/uzuUyXc5NS044scvf+xSzj/ZFPGr1/u7q8EnFo2F4IrCBpC5O7uRGqtTgigFkY4Tj/15f/ropFk1iaYi5WZ/k5Ek0kL6+/0uF3Qxdl3ribUkL1nAbezaZrHzycGhD9y4aihejJE8T5YN1p03HsyBpAU8MyQqWlXMiQ2tIsAYEDRLWa76ppX9YT+OQyQCvORMFqtkoPa01TSX3HJ0M6+lHFHto8MMs3rPq40OucFquAqxYRa1PJyH34FTBLw3Eev5z4/zC0dX2vcO1TTbUTx04cnpXeU4e8nPteLxIV8FLh6AqlqAGf5Du365ANbDDf/vD3QFzD3sOg8eCFm/7Mv/PLEU+MW6EJVFMv+NH2ttErijaE3KIxHBkRBhx0JnbjrMkDxma6dARScISOZKVevJSMDV1xRSiTfGAM8A1pwC5y4icDhxBbmU9UhBAo63JDMzC4HMHGpEJCwslKfi6qZqqmY6S5AYoNmVyk0tE8Q4OAVhlwq0mFmM8YgyVITMrfquE6lr0UIOYnEco0QcIKvjwA6vq8mxJCZ11flTrsARMQhCyqY2a4Lq+JeK+FRzLGYIyEOlrfORvukzvjGLATG3Rt1qU7BiPRSoRu0d9XEV/6991Pc+fSIHqNo6vN+8Ob4lJxCkIopGzLN9/1F76OSqBTwzqInAfDTd8OMyWClWTu5V4eIEqsZVk0+wGdXkGRU6mgGaaykAJAhQocwZYvP5QSSBI4EZpZiVgtlnaXY7AtWzR310HS/G7CVQ8cHjMl2nprnMtXz9DKrJv5sf1UAPb+H4hDO3qNqLw0FzoCJANGN872ZpDbCvYzuXJ+4g1VoiCGROMKD5vqtDzLMdHTfwAGcozMiFocy1Uemmaco6phqKlFyRJzC4jdyIhKg6HfbD+WqzXneBzaio5nE8tF08Odm8/vJyGl2QCAIiJ2chFhcOLJJKPgxZ1YsqByEORPV2K+725MmTw+3lYTtStQUxA1dymQhm97S5+VP5fajceQIgmA2x6k3H4OOUpnmvnQcaREQuTu/rYSt90b/SxHx38vN5FauOTl6RMuHK7Kb5CSoZjnhmgTkAco5N8FCmA4kIl+u30/39bko5NLHt+8ViuVytDynt97vL7dZ0moZxGrZk1jWL4XAQwXp99vTps6fp6enJWQjNkw+erdenw3B4/epNTsnUlovler3ZrDbjNOiU+64du27RNMvTR5uTs83ypF+cvHx5+70f/OiP/+gHhxESkQtxbEzhrkThKFiY5b2zhV69747jXNkXx2QZeiB+HxHbd423d7vAu57c8dHHlVZnc0OFwbW63nkMTW0tC1NKSU3Xq7Vu6Ha3jTHmKXsEiaQ0oUC8lTaAkbXkaURsYhCCm2OadBhHszyM5eryxU9/+kUMyw+fffSNb3zz6eMPVstSxtnHar/blym9ev1izJUUg+cfnT19fFJ0go1pGkrJIsISixZqqRQ1YyZeLHsWJuLrqxyCuFvgrgmrTz/7+OPnHz//6NmmX5PzD//sJ5YpJT0M0+cvXv3Zv/7e/X5vxBwgsRuTm3pJpKUa9BKRuMMUlSMLAxKqsyLqdkp1Q7Q+ti3c4IVKLu4FaSpf3r758vtvsMDXv/lZ28bYNJuz9WqzXC/7u62Mad91cbFq765vSRAir1ddE0FU2g6x5ZRstcQw7oaxjTGweNcFkcbNzC3GuFguzk5OSikjk6q3sQvSpKnkKbetqLpngqBtew4GLtUkhYlExCjEgJojpgbi3DYLYj8kb1qs12HRBXhO4yEnjOP07Mny1Yv9fvAYJ2FcXV4LhnJa8pQP+8Pd7XYadjEAqsTe9qumkTas2FvNnFJR5RhixzGSPjq/aJpIxCHDoCBXF1Vj5hhFiAm+WCzaxWLKSfZpKqVtTSi437f9AlF294f9rvQtmBmkTBR4AW/u7w5TTT0pBiAa4OZqXswyhKLmMto+BokxnGy69Sau1stxspRzytPby91+PzFR34bVsmtibISY4ZodWkqaUiGCB21CXPTLx2cXj04eBQtXL68u0z4f8s9/9PrLF1vcAAQ0YAs2FGkW1c+wZipXT6XA5OSMgFyl5I56/nEiAdTc8xw6ReoAGHEhgUlNHcKRRcQMEsQVFDlSQwBygQMF+ViXUG2QmXlyTzXmiwFiZzJXV6pGnkpsLGaqAKFMWC82w4A0HDwTnCzj9iarY7UuufhhmIBCYHNxN1cokCw5UNN7YoAa8gTT3MS+aUWzrhZteHJOfr+93t3d7PJe6ZSEuPEuhiaVYtIcPKUpJzUp3i9jGyUsogESuG89RBo1TePbBjhZNBIFZsmya9q9Htt4v9zeMS9PNk9Si/UnZ0++tvECpri/z/c3w88/lyffDuTh/np/e31Xuy33N3TWfnR3u7u+ud3d3xdT6l3EbSqYShGFA2Jh0bWL5WrdXjw6Dw2XMhonbmy16vfj7fqs/+zrHz57/sHjJxdhlcdAIP/y1evf/d1/mR3c9FnLbjgcpmnR9+eLzXK17kJZ9XdNKIDmZMULS+i6NrqkxFokNhnkyX1M4zAasXWrtuvb2DDE2yWvT5rzJ8vVqiNJErhphR1MntI4DqbFmRomdhQmbmJgaoUDYAUDM5o+LDa9IeVUnMzImMVgU0lmJMwSxZHdNMTYtg0sqHrbrNq4MLNxTGMeRvdxnG6ub9o2cvC2a9yUySE4vVg/+eBie3f/+sXbMeXlhq5+fgcwsqMgECMYHBTNg7t56LE5XTz9+NHF805luxv2q00T245FgMZVxt20v53Oul6oS1NOUzGGtEhTmQ6pW7TScNe1TVtAZOaqlovnVIRIVUVADBGwMIjgtFgtLy4u4C+Jg6nnUtiLkRoZ5poFwmK1h2oghXt18LDZQPB4Nql526BqmzA7wxL77KAwnx8Z/i4Trqad193kCIwdIYIKeteN+3jerkbxf+56D86Ye4fkCp8NWRUOCWh7qA23dyWexYtHpzf7YXu/G6cSAvp+0TSNmaeURCQEcgrCCeo5TUGiw0Oo2J3Wc3u3aLq29cHVDcIsrKZTGm0xuyHXQ4rWAl2AAPT47LNP316/vbq7XPStSJimMnoCYbGJF49WL25erPrOe24fxbUsuG91lDLw4RY2JmhGJvOCiGOtaYjeLUO7arqzs8X54uzJWezl7rC9uns7DcnZYyssLCzZlJ1a6SS2WQe1icwDoog8unh0SJOyOSUhCYRCmMWJ5GePT63ViaZUdsywclRtmxqBGyJhiIMdAd1p35/03HDaT7lMtXRFrfbUi5qbs3PgUAsIOMH5PXKCu9HceK/Ip8PcyeBuULgTO9tRr/Oue3xUl/hXZwVbPSxXNeDx+FcDtIjqAZrdAee5w1/ZCnNVfOQX4MHPFvqeGALz6/3CnKSHL///v36JABa+imH9e3VVAOsXCGJ/yVct2HBEsB7+aA+MoiO2FkJQrawFcIAEYWZVNauZB3B3GKaUglVuEYhJRDgAARKPbUB1r67WASIM4UiimKGfOWqUzGcYzUMQEJOzkzOJM8wUD7VXXbqrhw2RmZlbEGGJMcTd/Z6MTNWPds4kHFioFh1GZkVNfeY2qQncUIoWRb8IWrugbjAw4FL5UDCoaSYnnf2erYZ81XqZwTVdpJ4r2VlNzZweguyLK0PEzYyyW/GiOkPcdcWZ7b+IIQQSFpC4V3XekRohjPfQKxYIwrQvxlZpJiQVP5xXj+KmXnDs9Lgf8YFZuuf0boME3tsEZ9yBZ7gK9ckr4AiAwEQlqYuF2VulgptW2abgGqZHAKu5l7mbIMQz0FXN3/HAY3OHopLo1LQQiwikhjMyYDRLBSv5S0QaYWUhypOrw2swQE1hqzO8OnTNzQSfHS4DC4iYqz01zb8zytGVqUJsdOQCvj/fZvSK5klV8cKjAzw5G9yJ/GHQ4D4L2UTYHoycAIebqaubYB7aOtnpqNusb63+mcCREFBmBMGIwOSWiyIFSN83mbnkrIOCENooMTpBc9GhyDqUMUfE9WrV9jKlQ7uI2W21WsfQ/vzzl5rJYcQxRAkSWAxcg+1Y1feHPEyZkPqlVPYcA9mKWTk9WS8WuxhGN1aGF6t4KDOIoZboaCo65+HUdaDS96wCfFwtwN61f0CV16BOmPMp5/EF0zHnsfIfj5shs9dxZ3aa4xgAwFDg1TGA589rxg9VzWZWZp0a9TOBFTUJUOUQOCAPTiLr9Way80Hvu+XCgd1+uNteDgfkRSbm2PRWCnHYbE7HlHbDYXrxxeX9zdnZ+Xp5+uT8gw8+/DiltN/lnJMwL9tus15tNpuwo7HdNyKBQYYPP3hG1LjyenH65XT7h7///f/rj3+yio3Cpr32J5sylSlZhaSJwCJmNo5jDOF4Bx1v2Af3pSPURUeUap6BRzCrNuVmmPv4gPf3Iz+uCVA4jrYuToD3JwstyZSdQsrZnLrlIvfABN4wbM5Hd2sVrjByktgIpISQp4m7Ljr2u+Hy7dUwbrs+htAcdtY2/Y9++LO720En7n5zsVwuP3z6vGnak/Vm2XfMfnl7uR0Ax+GAi8NNSvdXl8PucHsYDstl/8lnn7RtdzgcLq+u7+7305jdyZyEY9s2TWwXfWjbVhjLvv/s048+/ejjyDwcDm/f3Hz7r/zV73/3X//h73/n+5//QBZ0fnF28fT5mMbXl2/fXN2dbNZF85TSOGhJQGFG8MzjoClDKLAEirCirjOnlUACYoYnNzIzt+xVtElAbCI1SDl/+dMXecibzfrRR2cffvzk2bOny7a9unkLKovYf/GTf23Ayeny/HzdNBImA7N6dpSTk4VqITYJ5J6dtO16oibl3DTNyenKbJrSJMxavI0dcyTkkjywq5KmItJuVqsQPftBxIPEIIFD7RuZsDlQFEHQ9ryQZuMGKuu+JStj2gdesODu5uaTj7/+5tWPDxN6R9fg7uaw6AAlK14mT5OZMkscD9o28fyDZ13fxihMnZPDTDiE0AiJ47BanjSBmUMs7pS5iEJSKu7e9d2yX+acV6tF1y8P49DE/VDKlEuQBiJTzjE2KXKK6HuJMbgrubVNJGodxWEhSnRIQN9x17ZBgjulyS4uzqZ0SHnMaQQiCxHbctmdXixyshev3tzcjmOCJU9T6ltZbPo2SpmG3f7OfT+qgdA36FtcnJ6erc4vTp4+e/z8cD1898ufXr+6GW+n8TZJBjcBzihsSsxtoFatWNG6uwQKrpqtNF0XEHNK0NJ3HTFlVVWDarXKNKhLgDmKIqCGY6qWUlQaccy5t84IFCNFM5MgFOaloCY5NqFppAFgtFd3L0ezB4epmlsIoQqjWFkrf1lw8+ZWTtgS73bDYtn0iz5GN80G9IuVSJNSbtpGmAnUBLF2dGcmMfOcUmCR1tOow4RpOJgtzOhw2C3b0+Vy08X8Zn9zew1fDJvuUdN0kUVNx2l38cF5znpv99OUG6hqdBKD1/2oJXY2IiennPxqux/y4mS9WHYnTSM/+9kXyzbEuB2Ht4v1TZDmbH3TUMxTiaFd9acffOvps29+k43PTi4aaW4ur4f9YXe/f/3y5vpn+vJnb25/8EXZAwdMPiAAuZ6PC0agAT7Iv/Ktb37y6Ye/8uvfPD1dO2WzTFGHvNvtbpbr9uLJWbbh1evv3765ux3vY9+lojf3ownfvdnd3meFtQuEtkWQpmuXizZPrwNRbJquaRDb2FIxOYwomqaxpFRKxjiW2CCcRpZ2uVytT9ZtF4k09NJ1HFukNB2G7Xa305SDCDHYxazk4sLeNovAPIkxNTG0TC3YfvLlVYiQQP0yluJTKiUpsbct2UwdkrZrY8M5jzkX5th0AuOUi3oK7TJn3x3ub2+3eTSCabLDbgLh5PTQNnG56BxOgn7TdKtz6ezq8iqn28pWqzTVErQejIsYFCiwM2wuukfP1u1Cb4Z98anpg0Pd+dH5ado7ZdI9iruQ7m6GYRy7TR+WXddi2u3HfcG+LPpNCKyWkqqaq0OdSslwYxIJ7BmqhZyK6sXp6smTp/A/ra3YVFLgol6ThpSqboRRyWgOL+5kxXkOGfQqRZglV0di9IO+xI3ANB9C/MjEOlJfHjxa6z48s7T8Yac+tlAfCrhZIvgL2MAvtKNAIOdSTDiCQ82Mloa7TkC232+Xq/7JyYevb+6Gca9z659jjNM0pZQCd15tv0BQlFLM2FGEERyqZbe73zSb0LILdtOOEsfYhNDYZNM0OvvR2Isrw8yOfwLhs48+9pJvby5ZwiIuLk49rZKjrE+68w/WTUdpHLb7211K0rXnn556ardvxl3ZwTImgPEgRkE5NugWU1iH3/6dv34/3WfTVCYN2q7bNvRqZb/fpyGVSVFqBeI3MNQAACAASURBVEqUqdGYUtFUsqQ0lg/PLyZLU0luuaSkBRaBWs2ZnlycWNRd3m+3u0purZb+c59g7dwC7OZARNx0cdMWUwuuyZyY4BJj41GLjXkSZeEQSGLTpKlwLQ5ARF5bh6pzKx6gOQVN3X1Om2KrYBPX0OevdiGPvD56r9ir4dLvGacRYKrk5MTzLAQAZyajCrPOrAQD3I6tusoVJPuKh/vDG6D3mSf/nl7/z5Cid/qjh6/vi3uBf2dw5+F9PHg2vS/nedDv/IVv9yvCn3/zSzdN845McfzmL4FL1fe9Ha/3f5FfeNj7vz5mM2njMBujPBQ11czYTN1RfY61WAgiQdq2JSIznaaUpiyBH5hWzPyQ7ViZSilNHKRf9AZLKU1jggMRXdvGXu79AAEq7YhZiKstVdM0IQYmVtVScoFxkBACRzLXokVV2amJbeQWamkqZSzmStFriFJVGgtLhdJwjMM0My+eDyogM59BqIDQNMw8jiMU3FKMwckLijOahpoYOQrA7silqFkpZqpzKcj1LChBgro7ipnHEEnYoVkVagCYyAdvWFD3JqsLPbSomZdigUWE85SRgiCYWsmJYwhRDFZKxmzoDqrrBRsFY2F3q01jYtTxlFlxSRU9DBaro2T9aGoKoZrhyPkkprlJJP6gyKc5kvGIxtSLyN1Vy4zhVCynfsMzjjSb7pizfUU6V1/dzEpWr8EsXCWK4u5eFEAjXdf0fWxef/4aVIdWjkQoczICmXqZjiMfiSOHJnpwhZlngHBbdUyhDRJDFBFidjcTd1EjM1KDVX8yVTV3YmIhIpZI/iCWIjczJhaahd9EpKop5+PSjTq1KjLbxxWZq2rJOadJpxmQBR37SCIkRDBhDiEwz2AhM+/290wPbDUCYKwlmgQwk8JRY2ikOtDPwtvQBArIQT37o/PzbtNpKi9/+qYJEiiEEBuJ05T2h4EcTYiaLWd1rmGThkDSQKmEHh98cPLs40ebs2W2vD3s05gX/env/bPvwSEUXU1iWK6XTmXMB460WnchQoQPw27Rx6dPTi7Ou0fnJ5tFH6nt6PR//R/++faN/fiH1zgAFIIEN7OSyEBAt2jMrJjqvHYQEbEdV16tWZYuzjNfrraS4A4PoXWoz3i6g9RRRYdHFPA4M/H+Qk0AEPoIt+NB0FHDFcQoiJd6XIsGqxHFTRuJKU3Z4av1SRratB+ZvBUbhv2zR/0//se/85/83d+OHe4Pb7/7oz85Od9sh/uf/OzLz798cX+bP/7o/PmHz9jpfru7v9ve3l4/efrxZ1//iIP8wR/83suXY+T4a7/6jW9961f/xl/7G2z4/Cc/1Zw//OAD8URkX3zxk7dvXgjz3/3b//EP/+zzTz/5ladPPnmy+ezXvvFPcIEAxKZJyVUVHInIrYBsNlnATCKz/NUkEK/g8vuH1q/cokTvdg2iMLcu6o+SHc9Cx+2Mj6QuAYcIFmdxuMMk8GLREmxKg7t2jURuo3T73Xh/c09KIo0VI2IR4SCAF2hRhWcwxUV0eN/J848+OOxuYsMx8DBMn//k/tNPTn7jN37z9tXhn/3z3++e4L/+r/6Lv/pbv6med7vtkw/Ot/c3V3dv7+6ux/Fwc3fz6sWLbKlp26vbq1dvsFri7/29397vxxcvv1z06yfPPrrf7u9u9sM4NDE8fXJ2sll0bXzy+PGji9NvfetbN5e3129v00Fvrnf/0//4v7x6dTUMaJeSSL/2tefNslOy7f1N1tK0PVGEhsMu3d5sr94ebABSHSaBMhzQOSr9+EE44GQWfI6nqHxeeO3oAAyEapZyzK9o0TzG1z/+9NPPPvrg+eOzi/X3fvBHN7eXN3dXq1X/5Nm5u97d74dUplSXSCXy5WrZdYtxmFLKZjTs834/FsNv/rVfv7+7P+wPpagWTEOZxgwEMp7Gsug3i35xdnbKQVPeGees+/v9Tezw4fOzx8/OLy8vp5yZm1xsmrRrm6999tGjx6evX738+csvQpTT05O2bQgoxVLK27v97e1ht7Nlg4+f42ufPP/2r/8aO968+PnJavn40UXftID9yb/6zu3d3cuXd7s9mg79CShivcY3vv7Jr/3Kxz7cnmxWWRXSbQ/lze1wud2PauenpyKcpsHMVMtytTw7v7i8vTNnSLjb3n/nez+IS5ly6rvFZrNS8Ha7H0Zv47okHg4e4mlO8sWPX724fNW2zAEhcN83LNgPh+fPz7tOJOiU9ubp5GSz3JwShavru/vdfr15HELz+uXlq9e304SuxdPH7ePztRDGcfjhD/cfPT8hC7v7/ccffe2bn/0qlf5Hf/rT/+1//xd4DQxABoRRy2WHg+HMYHKGc22EONy9AIBHd5kBaTYKAFkQgjhI57nCTiTp/ybu3Xoty7L0oG+MMedca+3buURERlZlVlVXd5e7qy0bGYOEECCQEAKEBL+BF3jjGQkhfgjyIw+8IeCNB4SwZTd22e6Lu11d1c7Ka2REnOu+rLXmnGMMHubaJ6Kys1sW7mrWQyrynB1779h7rjnH+MZ3GbWdOyQAwyMQECIothcJEsTNpUiiIbDUUo4PhzpVBFxfXsQQaq7j6VRqcQNV+EQ1t8Od2SWFREQKBRmgECO2mfDs39ltX/YXl735dJwfcpklhM12HaK8vb39a7/zvXk+SPBOOjeM4zyeppyLmRHxw4Ou14gBRIhJVuteAt09zA+PZbfCb//G3/75H392fCzrdHm5vl51W5trnSsBnOj3P/1HuxfXz148J+E392/jOu1Pe0iR5KUetlfd9bOd5fl4f+h4iNZNp/rqF+XzT06IWCdiuESkhK5H6sGMKEgMZgSgS92m3/XdKojsVsPF9uLiYrfdrlfd+sOLj4lSTCHP09vbm2meNpt1TPH24SbF1Pfd4+N+f3io0GrlOJ6maSy1VLVq9bd+53dq1Zvb2z/95OeffPbF4QABglw4heIl22xUOHG/pt11fPndq/Umus9aR7d5G82KjlMFWML65u3+y69wOmE1oO8vmNPxkPeHE7SwIIW4Wq/X280wDCnFr1+/EuFqdZqOORcQgjSLBtSK3HIqOZqJVrbCpiQhDv1utUmz3kJyLfM0z2CsV1it1l2XACpFH+5POetqWK3XsTlh1FrhHGOf4mq93oyn8vlnr77+6gBBDCgndCJgn0e7+mC1XvWbzVoSTeXEXLsuAZYiXe+ut3Q17uf728f7u4f9/X4cK4g2F8PV1fX2clNLnWuJq6DpeNK7aZ66bn11dR1DPx7q4+vTV//i7eNXJSKt4tYyTXkuPqNkSFzvdnk+lDrLChrw7/2HP/jg4w0kf33/Jwb8zl97uX+42Q1DBHZDd7XdHB9PL69/I/jVq6/ov/8f/ncc8Hz7Axv87uErn2sfhwixsdZZ8zGLMVMKIsTiaqWWUuZWvjbvlGX8TDinVrXpcePT/9IRvVBgALjBeZk1nc8UOh/erUx9KrkX4Quau+65P3QH8M5j/qkAcA6+mg9ztxososiR+vnqN3HxMV9+L/34b//1k+Of/fyTt2/Htzen7Q4vXl4x4Xg8nI6lFuQJm9VOs+0fD874zoe7YZtO4/hwdxRFF/pN3H387GOf6bOfffHZn7ziylwFhSXJLCdKTMQNOGSi1Kdh133/1z764Lsf/N4f/WOteTrp/m7GJV6+fJ6GFIbQbzgMqpjuH96UzA8Pth26w75+cPGdZ7uXu+1F5DDvT1Csu77muc5ZhIahT10oOR/m4yd3r/rNKvWxWj1Ox8PxWDTDEURqMVSPMQXE+aHcf/WAOweDKrwCCfwdXD//QJI8HG+vLy/FMVOZTNXxox/++v7t/ZsvXoeMoFKPdZ3W+7eHOhs7ipltw1zn2Kfd88s0yJvbN/WUMSxhfZGTG+pc8Oio6EIUCCppVq9uufGfnFqh1zp44wXsbCQ/QCgQEXvz52WAmPxQTqDml9UiAlsLzn42TfamnypGuvCv6Py4GEJbWjHGJhxRcgrSosyf1lXLWn9XVDZ9BJv7eQGe/WQYsCVO/alD/BZw5c9CGfhXI/e8D/K0Fuzpzf9lvcSvloHVriei0zeuv4D9tGwHzH8WlvL3tob23786GeB717/MgwEQkYjEGLPOWAbnywOssRzNibBkeBHU1GtzVyZr1umA2pKDsOj1mBoTo0EVzGJqx+NRgtgTL33JAPTUd8Wz6zJJkBgCkAvUVGeldxohNqgCajhDU8Quwo1cwEJBUnBWF6UnXpAvX67Icpc2xpOrsnMTtDWVI4ysqJGSAYECBxiZmQlChIioWR2Ng6TUFVNujnrETYO0zDta5ghcnQXuzcGKnNTcCURN3SAQq+7a3ORdmFnEzUWdnRjMJkQSECpVsJxdzAkKBANAElrWubM7VVq0afZEAmrEqRa32xpaN1tkovRuBbzP1TSzNvJqorfztAZnBeiTSM7dGXBmOdOYn7il33I1Htf7D2h7VwN02obo7iA7i8OYGCBVWHfRWbE611IUQBTmQEzBzf0pnfN9hOJp1IRzwhfMlLTZzLiB3dlBBGF/TwjOLI3HhIaRqTTxRdOUe7uzmkiTvIk4Fmn304DLXKEEJnarbmpejZxJbBmJtUGEAuQUJDC3pHp3bzJRbojSeb0/3aRkEAjgUDh5EDrLxRdWJIzcPHXdTJORt1YiRQxdSqFLMQWJLjRrrlXHeYaCAhHgWgEKMRKrM7okHFldc5mqV9Vs5qfpAAUczRDKlKsWamI+aweQAFQrjsf5/vFxvRZzz6VM04wUn109G2/vIJCOyWMAO+ASWIiZG5m8LUptNDhbkhkaTRkAL9k8y2l35nP6eUtyPmuznlbcmQu3cId+iZ/MAKBasICvfi7uiCgQ2BhNjwxA/Rx16oQWo2LWD8nNSAtQQZizllJAUNfDND0+HivZmE+11iDU9wgiDI4hrNfr0+G42V4Mq65U1Zxjt/ng5RB5w9I/3B9+9vNPIwuMV6uNSESpwuhTjMzzPArC5ebqcn1NFv7JH/4+nmMTmShx6AxqpTI/LWlCc8x/uhnOHLenT6gROv/8kdfTPUvv1vi7+rmN3c7/aXNSB8xNlQzWdL/uICpzdVQzi1FCTG40zRPIYgplquql3Zi1akv1oMAxBg7BxXMZYeBh4+7zXExlrL4/7FFwuXt+Osyn6RQC5jv843/8Bxe7q+//8HtXF1dWdP/wgKowOx0e9w+3IYQ86ng6btdb+uB4OtntzW2KHVxOp/GrL78WDl03ALJ/vH92+fzu7ZvSh++8fAlt9FQtpfzxT3/+6ou3b98+vnmLvpOeVquBuuFqvRmqlf3xMB6Od4/Tqhu6sAKIOQif24rmrIcn6IrecTbJFxGrGjk1nwmGAWxsBpgqJgeBUwh94M4Upe791aev2EiIIofXX9yGTp5dfrDd9etuVWseQ3k8HGvNQ9+xcNWZYMwaItwFLjVriBDDaX9SdTc+HcfTadZsQfoY4+k4HR7nPOG4nw6Pp9hR9WlYoV/LeliDp8Nx/4FdAR6Euz51jq7zPsYuRDGCgowsWx4LOUQ4xBiDdCleXG2szvn0cHW1Xm82IaYuxO9+9/uX2wthPjwcbm5vSu5g674rqaurbZ82q6yj6nh3e/zFJ1/8+Ne/22zLOXAXBoENHetcvvrq9rDf7x8ecylEuLq+vH7xWObqMcRuZcD11fWb+7fTrHXeC1PquxRopjpNR+auqh1Ot/DUDfzyg0sJlGuGI6UhpZBix961wHC4uPk8z2E8hdQHQYgBrnCLKey2EVte97zbpBjAbGuW3/7hauhiDKv44uXL5997+Orx5qtXP//Dz9IxZmgjfsEIVtl9EZcvtFNntnYcEdxh1BJxNREYZASlasQLxkmsIGduG4ECgBMZETmxm4ObM7uRupO5Nmp6getoKTFRN6QYQ0qp5EKGWsyqkzE7g9zI+UmhYmqoDKJmSNk2GRKw+kyoAVUcJIhdcGd2pTj0F5eXQboqs7uW6q4wJaIQwpKZ0/djaAA8zE1Ni4Q+cme5zIRIq9/4tR//6R99/urzt6/1SDNqtjLNgtCtJF5tcPSS5rhOu37gwCcUFgfKdrsekuRxZlCKw264enybj48+7kug1NnKT3CClVqrQtVKjZE5SQYTUSXSGl35NGZhPx3L3f403L5JfUxBkv2z1Wq13W37PhXNh8PD/ov7OY9X1xddl9x1zvPD/u4wnqZax2ma82wGYijwnXp1PE23493BH70DGVxlnus0z7lOcYXLZ/32qr+8HtZbGTZCNJXyqDgBOM3E3nY7iDuoG4aZADXkOg1dGlbJqU5TMcCoZNwn0+iVPbGYms1zHk+aZ7CQJ0oJDmi1eUIpIC9aSq0oM9TQpQRnjj24OCqLr9ZRBCGQaj0es0gqRY/H4sabdXDnnOd5ysQUQ9JS9+Pts6srK7rq07CCG6Jw7E2ca9FeQie9FcpTHaTrwgqUay3mxRy3Dzfe5RTT8+8O1x+uptOzw+G0eJx6fjzdqBsJR+kh7h7UaZrn/f7QJavZu66LKSIUVC8l19mrKUVxjyQUoquitB06gdhARuIxJfM8jSM7ypSHoRPm+XQiNfIaAl482+GE9ZpHO/lsMQVnydNclHoJw7qDmhWtdVIVciZnD0qtcMHCLXqyoXgvl83PNek3zubzr/HL5p5PP/ZWJZ3P/eXUbs+4dAZ494Bvqd4NLtL1m34uRblePd/dlzcGXFzsPvroMpfxlEvfBV6KAxA8xtAPUasSzKpIADmnTtQ15xOfFGZdZBLSqqXmqUwBMQySdqInq6cCRy2ALFNqCFJK281uu930facZb754Pd7NIkSFAMSM6XGep9LXFLpVWqfjvOeUUuS+TkZw4HF+HG+meBfJPJ9mmwsbYN5Fubq42Pk2ljjP03Eebx5u4nyIKXAQNS0116rC0lBEr1A1s5KnQkYQTxzJfbbqAJmQUOikK51N1QskxFU/DJvVRbrwWB/ofn+8p+J1wtANuxe73WqbQjqV/Krsvc7umqU6PKw7ShJCKONci1YDiqE0PAhucG+aboKBfLFpX9oLh4LeK9yeaAgLzelMxFoaxTOF5VzsOcx/CalYIqQW3MqfnrcJZQikbk2/6t76OnN3tadxKX1jXTkg4DPjsHnRtgXXXIbPzeb/T5K4X8Xrhvef9K9A7vcEWv15ZKsn6Orpz9/Ap95Hvr/x5v/ss/3lXn8WO/vW12ofY6OeiUgIIcQ4H+enTXDZ4M5shnPWBSDk5mqmJdOTd1LrhFo73rD8Rtg5fy4xRnMrWqrWpZlf9k1y8xCCNg91dxC4cWBUtWprZTlIiEICJdSmSWRiYZFQxupAi0Vxo4BATE4Nd3BpXbZ5kCDMRGJqMLWsWizY4kzO4OZ1Y+0tPzn9mFtdtgd3gkMVTExGLdSPncil8XuVDO6uusiVz0KkdiiRUyN8gMAm7uQKq6QVMCNmSUxqXpufFJExOVGTAZzbUXdbfMcbtYpJhA2mzmejqIjGdzoPXMzOdvoOV3tahA6Q2tnP2WGwZRNya5wWPi8EX/rXBcRBw5uUibiFejwhLQt8dO75l67XWai99DfA1UbaYoY71NAYam0bNpi6Zs3r7apMZXIrpjBUdiaSNiwQokhPEL6c8Yg2JSBfcnYAq05QXSZTzbX9XOurGzkYQmDAyJsZmjE3/ac/DcYWBgTwbu2egZSFN9EwHRiMXNWqWTW3c4IBgLP+Fg4mlsDCS+KBVm1Rie1/nzYKMzNyWiKlHFrRPnZ3smZff9ZDtGVrmOdMDsvKDldzqlUYQk7qbBY8cCAQC7sij83nSc2sKX9J3Lzq4r1KEqC1IIIM5DCDorp5iBIQqpdSy/py7VbVeRyVH8arq97MpjE/3jzWITx/8fzzn903trarqambozH8GhWZiXgxdmuGM6YLjNeUq62is8VIEu7Ntolc/QxUEWA4n+TLEOdp9vOkMMR5p6L2+u7iberCZ/VrIxOdLca8+WGZO7mBiZkMaqig6lQdCobD5zKN8yTww/HweDgUUo50sbsSTqfTeLndbVabPnXY4O7mXiQKyzRlVQshXl1fBFoXtVev7/b386offv373++2K1erucZehtjFEMfDYT7O634zxM3dzfF/+1/+D0zIGRQcXKvD3bSFObyXc2nLOfDnIMt/QdDLUhp7Q8F9GQXAF/O4d2jW+bnaeoWzA8Yk7gAxzOqczSqJSwoOcqjEsN6s+qF7vDvqXNtX595CbLwNJ0JgT8gKCFabIXUdsaTUz7OdTnsAu83F669uvv7y9S5t1PWTP3j1u/4Ht6/3P/zRd7/3gw8/evkxRL9+8+X+8bZMUxfW1PcmmRirYV0Lx9CLxD5tSq23r2+6fvPs+ebq+sWLqw97WomFi9XVy2cfrleJHW/fvPn5zz/9vd//g7dvH4w6CXDi47F0SKdj7QaSlFbDbhrnu4dH2OSJyRMAXkbptAwEWkVo/Ev7CAhwAUP9HNtD1PYzJyKwcIvIUHWbtEnSDTj6/OrLN/OUv/rsdQW7uxZ/1MmVrq63z67S/nQE6Xo9hEDj5MMQuxTgHpiBULNOIxvw+utbZq7FxmM5HswNq466IK5sM8YyjT7twyElNqvby9QPu93lhaQ1h/z4uD8dRyeSIMziMEK0avc3+9s3D6fHmZhq3veDdH1cb1Zdn9bruIuDyDrRejWk7W4jkbu+e7a92q0vHh8e7x/efPLJ1zHEWiJjw6H2q+2wWWEM+0O+uXso+eZv/ei3qk+BITwQdePh4e7+9OXt4/3jg9bTeMI4IkaM4/3jfiZmJebQpb4HhXV3yTgRVc3lVGstlkfNtXadqaEW7bp0db0dcprzPN/neaplmmIK7grPWkPq3V1Mw3zK7ofQ5ZzNVHOezSCBNpshdfFi0wVRaHbPgf3lB5frbnex+1BLP+7pJ//X77/97Hj39oQspMnnwhzIXe0M/ra5mDfE6ukGM6KGEzlcnhwVsRxSbWlYg66Xna9VKWZEREbcztmy2O0YQAI3t2KqziBJMYUIoRjjw2GCsRYtxeCehIjE2URaF6Tqpl6bB3VDY5dNVjAd86asvbKBmprfYOaIsbscOlBwjqpWq3olrd70gyIsQvEyEFoNpCQ+9H3sBi36wYsElVdf3lysP1j1Fzrf3r2+yfcKLCFfSLj87jAdpukhr6769bNutY3rJIiefd6sViI4HPZDt9oOl893L19/8snD63p4QNArlNV0qkzGUiVmiVkiRCjGyOctVERjmEMgEQthChEhQAKEoQce+q4f+t3F6uK6T70fpmma95nyOB9LmfohOPvsmNSOtWYFGCGCBQ/5Zj8d9vqA4bT7kHdgKp0dpczsSN0urS9ivw5poJhcuJhlcg1gEpxOFgIZSJ0FPAxrYCgbOo3FFJIocUj9ei5W6mgGEUBmA6vbOJ9MaTzV8WS1okvBA8GJmYWdkU1NK8qMktHmWCrZPIPCOB+JPUYaVqnrI7e2tqoZmMJ6WI3T9Hg/jiIxaQhRq87zvBrC1e6aqkXii2FlO61FhYMlP+7Hki2mQJmncT7dTsO2C4MQq1GOPRHoYTysrslDTDJITEloFVMpkouhVDO4wlDHeQK5gVRpKtn8tOpIkKxk1QpH0aLqBGEBEUwAVtXZUEIj320QEsCqXprbap0zG+c8h/UqMk2HQ+RodYoJu+cXOKK7CqfTmKfarwIxH0+TOHPHTNhcreaxTKepVgWUhBsdZYELCM1kpJ28zK3J9WZhxYv04Awzkfg7shY/zepwHgS/O+4dLOdq/x2U0IpabxTPpYjl95yzlhfmkgtxR+7QKrGjimGFq+vh6tn6drqfisZIEj0kxEQhSEwB1PjUNUgYukQ9S/CcTw7LOTcTcTOyUrPm/Wk/pFUYePtsPffz3JUyW2Bc7q6iRA4CI2Lu+6HvOlN9uHk4Ho8PN+N6E0VEFD5i0kmD11qlF044TRMnIWGJMU81m3qZQyhUDNXrnMsML4Bh16O3wBN89HEcx3nenybMUwo8rIaQIsDkTsbu0Ow6VYXDqGR1eKO9wogAN1xc77ZXm/XFarUe8sPpeLevtUrX0X78av/VOJ06T9tnH2nR/d2hQkvRwVcxEge5enYl82maTsVU3UIXYxdRYcG0wIuhGEpL4ICbmRFVQFsU2JmytNRm9ARWLmuqmb8sTV1YsnUI8LOxTitOzs1M61J9cU0lODxQs/B4aoNApIvNh1c3MWq2IFgCBc5iV6A549Ay81xqHX0q+Fqj6mh6HVJvMVxYivQ/vzr9q73+FUGnbzKwvpUq9Zd1vf/kjRr3DTDo/YfRe9c3nmeJWnvv5+9TKn4173153ffIoY4//+Mietctc8vo+zNdydKcM56eo6EE7o3+cG4UGQuZ5Cz2dDM1L2ZoaR1d53BnL6WYeetKRXjhxKvROaKNQVYBUlciF2YQJIgwiQcDw2t1mDWbbjfNVa2iNr4ltx25egWcmSk0sz6jJmwEm6tW02pQ+KKFZjjQECmj5lel1eFGLU3PTSsADSnFLpL7nIups6NZJhHg7W/B3dzIIzE71JWcicgdqgZ1b8lUBUwCBymxERzsDCWvsIbveUv5MW8Cx4Y0Ksw09BHsdG5pqtXW2BCB2AMFFixQNrm5wdWWLEKIgpfipO26yza3HJX2tD8tNKZlf2kN/9PZdv7a3x/unBfGAnK920jPq/3bt4CzZZaZtTe0vDq5oRb1qjWtN+wSPBpDq7q5mpqDmEMMImKqtdTA0mYJLdiQiEnIkkObCNyqVVdnNPjLwe6k5mpuLcqv/cMM8Gbnn5jOvKmmWKe20JulGrM7iMRdz+y01r0TN1zOyWtDZdtX03i7C2erObHzOQGxjSxMHeYUvkFWO/+NZfDSVOTs5OTGxGBnZzJebL2c8pSRrc6ZDFAt3j4hmWoupJQQAps2JwbiTqyYWlmwHYaTF+QCMJMIRQl5xvV1p0XK0U7z1N5S6hKra665zv3QpSO3NAAAIABJREFUVy0xhVxLLsilGpCLPjw81CP/6KN/nehPUWDedJXa8BBvPvwObgwUaudmI6wuIJQsVlZEaLhu+9jPC8oWm/aWuLBkofi7eu78hzNu1W4LgjOaSwsxs5BIC6ZsClNvqmIzNdeQAjGpV3dvlE+HjdNea4UpSaUACOY6jdMYQadxmnOREjfr9brv+q479ocA8WoQkxB22+04TVot5xpCTLELsZ9ne7jbn/anPM7bYb1O6+16Hcnn05QkAc5urtWLv7j8MEj69JNP/u7/+U+RYVGIRI3AkCDGRkSu3ixC29r61s3/X+Y6u7a7nAGrd/Xt2X2t3dvLp03tx8IswoGZneGoqmrVADdrKZa5i33sQ+qTFT36qY616HnTIjKrdTKdychACFvEFEDEErtupaeZ0OTn6/ubL96+2m/7oevjl18/fvn5P/jJP/nJv/Fv/c2//jd/69/99/9N4jJP88X6+vrisN2tjHCY5uPxlFJI3dB1Xa51u93E2JveqpogXl88331nM9/e/fpHv/Gd77744PJF14fxePziiy/++I9++tXXb9Xw/PlHqdeHm9OrNzfDpEavj+N89WLTp/X1M7S0zpyz1VqyBRZEqupEZLpQLJm5AdnkwGKBQkJe1YjOfCxv9bO7ewhBopi5zXOdDRlISANHCuNj3t99WWb8+G99b55ytqnotN50MaTN1Wp3sTuNvF73MYlEHYZORFoKIlymJCwE0JvX+yACh6oJkbrPUyYPzCH2sdSK2YWkzGYz9sjbi7y7Wq1WvcQyzve1FiPMswNSVTvqplN+uL3/4vO35kjJS85mcK8hOFAcoQsxMD9/eQHX1KPUk3mI/a66PuwPt/ePDw+H62cfAB4CVc7OiUMfO09lFp7cpgLAJMUO3M8zffqLV5++2n9+s+eAy12fEqxO680gQvPoFPl0mo7zPsR+vek//v6HTk5ST9PDm9vbcTJzcCD3EmLYrFOMCZRyzbWWcRwPB9M6t41k9RjX27DdhW4AsahimmaupRrybONYmWP7olOS9TqZTdNxrvXkQJ+uXwzPLoZnn756+OkffvEn//ANTkBFTBshmWyfhAle3m1fBBAT4zwaOmfjLrFQhLoMi7zCW3PjgDdz6aV2o3OynxOZuzocbtCWq9vymTnAQQszBGQwNS1Ws5Zc4WTVtFqzLBAQMxmjpcDD3dt4qm0QbQkDIJSTwpggXpdZlrkVUhANw+o0HqtZVdXZUVFLhXtYDEolha7qxOQiTmzDkGI3mNN6HcuEP/rJz67X+4v186vNs+NNyafDcsRW9eL3n45xB+lP/QW/rBcvX174dnesJ53BJjXbuLdgqe+ve7k+3P7s8fVo+z6FUCezyYhgzDSLCVdhIh+h51IZRCCGBGLxEBGicwCzMcnd20zuU0UX8NH3ht/80Q8urncxDW9v38x5ctFTLhKjc1eRQtd3G1mtu81utVp3++k+Y+TBdqsYgkhiqcFGNgWIOfUtL2+apzl7DEJMsJWbEiooswRyJwM4hpQGphVi6ss0FXePATEN4FCty7moWguQUat3d5kJJSNnqIKAEIT7GEOKgaxmtzlDoTUIM0NEUheHVeo7OY3VHQgSOKQYCai1OkOrN8bfdLTD/TyscXWZwirmUxnHKpafXYg4DTH1188uVxd5nOESKD3enX7xi8+Ph3navy0TEHD/cOSE1GG17V6sroYYjvlu0nGyPXKAB1M2ZXd2ZxIh4XmexnEkRnex8k6AVGsdxxq4DrGTIN0QwipXh6EKg0BBhKJo1ZpHhW23sr3k4cJTR+pz0bGYThPYSZxrBTmEyOsMYc1z2PhmlSAIbGzFrBAL4BCEGCjQOM3Xl5fGqFR0ri3vabk/l3MTBIiynzOvqPX0vmSutOHo09j0qbIhdtfmBdA40Of03yfuwtN4+c+c77RsEk8Zw+8V6e4A5vkYg3EkcH58KGGH7//g+sOPd5IKyuimEA59ubigoR9SSiHAnLouBInHY2XxwASKxCHPs1ZHpXk2NwSmSvXx9FByVljYEPexu4wC7kInKkMYRGItPo1lPI7TcSpz3j/uT8cTFBSFAofCVr3mquwjwB1nmzS5MJGaGs3FOHRg4URBAlU4lFjjIGSeJM6lTPP9PJZ5LsVUBJpR1TRYCOTVtShAZl6mgowQJHBwySW4AyUX0tZbAoTjdPDoAWLVy6mMj3PODyB85ZRW8fp6NzzboEPN2dTePtzt98f1diVDv7t6EcBUUEuB+pCSEJdSUJ2La3a0KA5bZsBmzkpuCymqeeICpMD5p1g6l8ajOGNBhpZ6ufR6v8SnaV+6/xLTHm3e1qBV8ichDhHMlpXVDHhERIiaHI2ZsUziqGlf/cmxDQSgqi75SYsuZVnSLYjz3bz/20RxfzXMrL9ciCl8A4j5lQJY33ihpoB7+tW3cprsW8Wa3/acvyQL+tVQyb6BXuHP+crfB+AAeFMCfmsKIaNBtedvgcGNvfC0pS4W1Gje3r4wj9rd1d5A06aZmpvDQUwShIWZGYRSzRrxCgRHLXWZCrAwR15e3VqXKwJzNkDNFrojE6QVT0zglugNghA1DaOe34a7WVUt2kZJbmdA4Qn4bZl0Bpira2vEnNirVVhILEG06DwVqC/UDmpTz1baLKzKFgLmvrR0rmoGUneDs5XZG9XDHQBHjkTQCivw6tUWNgUplNXo7JjvgCEksYa/wAxNb8xmIJCAJDATG5bCshlRuy0WjWYAGzEcsljzuzmoIXgLF6uhUrSgS8u16GQXcKgBO9aeseVONMX9GWt/Qnzfgb9nGtN57Z1xGTr/hJZg+SabdrhZNfdckwuFIXEIc851zshwhTMgFELyWuFgZiHylohERoGEhTux6prVtLprNQic2dpre7BG1mJQM5eyZUzx3gBjoUQt4Iot5LIFEWkDCjwhekzEzCRW1Zr/tzp7WxrExA4XZggjCEB6jhk0s6ePp0HA78HfFEjIYWqgtjyFlg2JmQm+TKnh6MLgnZOam2n1dYpJAkkzjDRn54SYklYrc21+KyyBOTGhWuYIiFfNU1bkklI0b0irX19d1iJ7nU7HCQ4zExaHMLGdNaSxk4EgjDaFN/Na9f549/JvfafvejACEoEbDVGe7khXWiBvd6AhSwsEddYYP5EQscSuLAvRdNEXN4qaN69TnGeT5xXpTGdKIAFAo7awUvtWhFucEDGRw8yF2eFutlApuXV9HkQkBFUzymhpDQwRGLTUrG5QjNM85WxH6lfDbtv1kkhtPJyO+z1Uuy49u7i69Xs170PqVsPjfl+rTrONcz4cx/3D4XR4fPv25sMPnlHtdJ5LB83KoBTkg2cvP7j++ObN6U/+6GeHhzz0MfW7UuGuCI4AN0VTDDXcbrnv/j9eTwfHU+lh59vCFh7W07CscSmpZRMsRFwRZq4GF5ipu9Za3SkXhc9Vy9ANu4t1EJlCnk6TectOswpTrVDgAqtVvxpWTjgcDg8PD1pUTwtUKxI5sPQ4ZY2y2W0uch5Pp/qTn/zh7/7Tf/Q3/rXfGYZwsX32wx/8aL1az/NoAauSj+tTraWqjePELC+evYypH0e7eXt3PIzTKT/bJonrX/v4o+tnW1LqQv/pp/9iOs3H0zF0WMWrooYYtRJGFPFXX9zu94+qH3748bPd+qK+qPvHw8N0mE6TVhCRCFnDwMnQDjoAxEZ27kXOUVF+FpB4Iyei9fy1upmCKcaA4NRSxqvlWgFXAgivPn/brST0bMYP9/vPfvHqRbnsth2opC52XZCwCm3bUXKThn633WyeMZsyoetSSjyVaZzUa+n6PqakRkZZWGLXZR4LdBpLHstqLQj07NmL2EnRQsKlFObQpSge8mR18tQhCBNZoCTEgFedLIMkSQi5opSZpcpkQagLcTy+/eKr16fxOKxWISZzcY7CiSRVBIn9envRx/Uq2XEqCeCYplEf9vXTT778eo/i6FIy79QycUhhSF2acyYKzigzjeNEJPPJrp9frDbx9h43N/darR+w3sSqwhQQRWs5HufD8XEcZwB9Fyp7nlUND6/LOJZSZHcZVusQozArB/JS3W0ec7Xshn6IWkU1ECmxgmEFHz37eIWLu8/2f/D3f/r7/+Rz3FJYrauzWB+YAkIgEMyWXYxbbd/0G3YmGrs1j1w3KLgsPe6SaWMLHuqCBdtHg5yo8S7MqW2wCrfmnSMIwhbcIF6FSJjJvMxlGmd3grqStlEBFtV4a3qJhR1OulgSolUd7eByQoVXREqBYnaqVVHLZIUr8lT7jd+8veEEkKK4F8o5w9HFGCUSUS21lCzSDtmi2Vl6IB73pzr7q6/zI3358QvebZ69fI7D20/wUJdj2Qgnr5TKlKdsw+qO6vdXqZ/ySTSMD1MplE/xkOsBvlauYzjsC43E8VROTnWJIXZWYJFuNicIwInFGXBPXZIEN7aWZSJOEMu9mZf5VOb602mUcP+babvadF+//nTMp35gCbbeJhc2kmEYNhfr3eV6d7Hu12mdL4rPatmxaBeRs8asxYp60bkqctFcwU6qxAha1aqr2u6iF+FcrWi1rFqmUlwkuROx1lLYtWMOKYqthWtVVdWaa5lLjBAiBrd/oiq0sGkwEYIwIwSHewwQkZSCBBJhCcRiq9XarIgQ2oqCatWaTTjmUu/vj4cThjWeX12w8HgYtdZVQiDa3z8+214Hiqv1QMbH48kLBUmU+dnl5Woud4/7QgUnIMEMs2G9CmSRkfpuzXGkGEPsCbEWzJOaCnmw6nmqh9M0jlOIoZ5KROec1EvNpQs1sa2GbrVbldlPNE6P0LHNvV2IzC0XQBAj7S767XUg0qpqUkJsE/cgOouA4ey2GVYMZmgUF7Lv/TVIpSNqCFTdqFpIIkyGOpY8WzZRSixMau56Fgza+QBtJGdzMhCagyy1IL6lPH5XNTcUazniz0YpZyZWiy/0J2XMN2kT7zfPT20g03s2KK13dJMuMmu36WCc7+df/xv48V//4Ye/vr6ZP78c+vJ4mjynoca0Grpt6qTWqdbCgq7r5/nkbkzoh+gQrTBDrcgTzCEdXDDncZrH9o9KQ1p3aej7VdrYnbJFLeZWc8n3D/d1VjYuuWBG6hJlLpN6dRJutZ9mm0+lSukvgxXPWswESNvtlUFDpzEEqu61GluSEFzIMM11PI2nk7uDA1qLYw4tnsdSpjLNWVpMarUB/Squu75LaWZmK9nVWGTdB6xJhO7v7+8fHhKHcpPLXaY5rOPWzacygvztZzcPX+6pQ/H5+YfPh3WnBunT5nJz/3A/65ynWXN2uILgNB9mKo5cw0wwprOLiVd3c6/ETmRyFvyR+9JrvAdAGb1nnw6HtS73/A2D3gW0uS2NzDfQFXdfQq6a09q7cT0W2NThZh4ahWBpXuic5N1q9WWZPUnWan3Cy+ButCCv7RjhJxSCfXFd+Lai9Fd3/aXjSwsDa+lk/kroV+0PvARXfRNpeh8b+gs+0PdBq3dQ0a/4C/gGevUXPKw1Ge1d1aqmFe/gh/NFQMu7bwN0b/lq/N7zL6it+rl1PP8tIRZZHjnPs7nVVpLTYnfdACwnZyOW8A09S/tt+/BNTU2N1b0l/zC7qzZAqEnqAgCvsHY4tB2/yRlBRqSmIJhaKUWLwkHCNhs9ZcyhzS3oPLSg1hYbE0IAKzGbU56rFtMCV+PF0Aq8xKNRm5WCncGCJtJsVqrC5mZOIIGUqVhQQNo55AwQm6oWQ4axmTMqKgy8hNy3t3nWxLVdaMlAJCehYAZrcBZ8gayaGOE91VtT6AR6WoVtoTSssKEsHBjK5uSgxdFsYXu5A8QLq6vtTG6qIJAQnwe9zRj7/bumATRPqv73b4oFFAOhdXXtU6OFlNsSLaeaYwghBg4RgZTM2ZDRnJKMjZg5BgbcrRYtVomRmAMxYqxQNzUwHG01eGPJqRODIidhtkhEtRZaJhmAtNVuoLNLlrO7MyocLrKw4mr9JbtwkBALy3wcoYA1QqEHXlL3qruQxC554FpyyUXZl00GZ3cyIl9AaDBTEGmK2lqLwWOMFMjcWrwyOZEzO7GRExOYSaDwqnUGRzczuHtkjhwpOBBSgjoL1eIw8uJM3HWpY0kDcbK5TvnRTxVD13kl8jCNdjFcD/2qHoAIFCpzzjm3HKAu9A+PjywkQtvtRriGGM10nmc1f3x8uLy6HFZrSfC5YahntpXBqsYoBm/S+aYqJDRp6rJPtWW6lHl+Nndom4222/y8lPFEVn63fS1lHuj81O1WakHyoMXezBisqlZc3WIKLCwQCImIk6LC0ehaqKopRZfq6pHBwWMgJ6taatbDYT+ejsfpJIFT4CA0j9P93a1Wu9herlar589frnIxQ79ecZTTON/d3715O5ZcpkM97nHj+Ok//3SzHr7z/KqPtl0FEbm42F5fXqbYjVP+vd/76f/0P/+vxwnjA/Qik8RaKzFa0BbgrWN1t/Zp/3IB8P71zeLg/avhtu0LEFrmv0xLjg1Tw7D8vWeixutc7muvbkosxAjEJqyL4R8AkOg8nwJR161iSDGMKSWtNeeiRkFSlyJFfvnDF/3QlZz3D49q5Xiqx+O92PItl7nstjt7Tl98end3M4VAtRgFeTtNKPgv/+v/7j/4t3/8X/zn/+lv/Oi3v/fRD/6ff/j3q+cU+aEcXr++2R8P0zTG2HX9G5BsVpfXly+I46tXX//sp3/y3/5X/806iFF5+/DV16f93/k7/+Pu6vkw9JcXzy6vvvv3/sHvW+l0Zgyh77eHx7vjQz09lPod28QhSRRauIVmMHVTM0P7NlrryYA3Wzw1WoY91iLnW1j1+2UiOVStqkVhSSl2gQWqNedcFSQUYwod3309xi3Wu06iq+GW99Lzs2HddX2XuvU6Mg/TfFJVEdHzq7SrzGCGRA4hCScNrGEOwg3FDeDsUFWh1PUDS4ZjHKd4NC7zD3/042EfpzyO03Qwi33cDOte1pfb6/Fqqjq7VUotfpYBdVNoGznYcZ7qPA09V6U589v7+tVnrx/vRkH34UffnUbtJUYHd6JcS1FDZQ4SgkgVSWRWst3d7vcnN8flxeUgiQKbKTmlrq8WUehwzMMqCfUh8DxW0/Cnf/qZmX8YnwXphj4q6rBKq3V3ONactdb5eBhvb8eH/ckMQYbtZqeFDvtxzvk0j3nC/b2CNKWw2236FRB0zpm4imgpLdLU8jwfTzb0NAy8DqnL+hvf/e1//o8+/92/98d/9//+vD6CrbdpkELzqfIQE5hqdi9w+FnOD2/TQiJfuO0tlcscIGWez5znxfSSlukPmZ4dHWmZFqAND82fxtxUqLF/24FT5pwEKa6IyKtbcZCjwsTJW14aVyMxZ3eQswBErDBf3NuXraAtXAO5xNil2J9mKbMWy6eC0E2H4yGs4hdfPu4uERNHRCsYT8UM2tUQJMZI0Fzm4CRCWrNmSOGppNu3xzopBFPWz7/84gcfxOuLS/q1X/v8T7+Y9qOwEDimSzc1O3ipt1/bV598JRvTUN14f3Osltzj7e1kdw/y8upy+OC230+nyaY7GHyGEpwgFFr6llOmllwmQFAycfecjwDGeBaqO6BY7z4009UQtRvn+fT1ze0H+6vV7nJ7uc4P41jyxYaGLV2/eCb9oGbzXF6/ff3zX+zHebq9O6436/V6m7qemNWMzWMTsJU6VQVRCDGEADJkJavuaqpap2G7LdnzbLW6qU2znk4nd+GlyvJcpnHcAz1xCkLEZMbTZPOcry43ZpIng1W4wgKc58mmccq5TmMhUIih6/qUYghEbGa5lFqqscPMNdfsTq4xBXaCes2Vna8vLq4vuO/Wp/14OJwi8XZ7fXV1cbEeooiPqjA1IeXp/ghjWcl2WP/WD3+zW22Oh1LN7h4PX37x5f70WGq+e3u6uT0OK2wv+UWfyKoUtcrTXI/7mrNroWmsJaPOQAakdnXaiKQQtco8FbaJnC1bTOHFh9dlpw83h4fbIzJFZiKXQN0gLrracL8KsaNp3vd9WO269cXzdX8fmIrWTTdAVYifv3hR5jlxioEY9p/9x3/7J7/7+c3N1yn2xYzJQ2AzLbmCsT/eM4n0KYVU3XLOWg2VvA2YDaaLQwWdS2D2Zna3xCidj3I/u3s8yfjPUfXy7kBm4mXUdGap05O00H8pjolaBjQtKNjyK4NDUzAJwlLJAMd/9J/8Bz/88YWu9o9UPny2ecz7LXPWBF13cWM+H47T4XDoUtqsdyGyVSOmlAJx5zbpLFkD+jqX0oALY6iamzFBxWkIPMAor9ebm69uX3399X6vVoEJKCARcm6+ivlU5zGHAAruAUjUyTCkIXYYp0dUHkvt+46ZN+uLsZyyHW2uUKeQhOAKd9Lq02Tz7EsxWYEAYupS10nn5poNGU6IMZBwkiFIYmeIhz5YZ8jWUT9se94G2lCdqxrIfNpnPIAmHevRULlPlxe7/XGf6xwTrVbDhx9+p+9Xr99+/ebuzddv32D3zvZMEFRny14PNTi4EpUWrNWMcaAGr+BGBLGl5oUtbBGyNuVeijt3a3NZN/j/y9y79MqWZGlC31rLzPbe7n5e9xXPzMis6qpSPboaNagHLTFiBAKJCYIJM6T+D/wDJP4AQkhICAla9AAhMUE1KJoWNF2t7up6ZmZUZmR0RkbEfZx7jj/2w8zWWgxs+7k3IiMh6c5s8AhFnOvXz97bt5ubLfvW92geyasvKtCG20rXa/h8y7v8ek3ob/37VvF4HpMP7KLmgngGH6zpnh4ANiaDEpEDIivO1XafKyzy0GylFiLBrnD7OqfGf45Z+f+fHyuA9YAB/csjQW//7teO8zaG9bPUqq+Q7n4xitPXjvnwK78iJOv/8bBvA2rt4W0lNEUgPPD2aG25M1FgaWO/2bYJU6O52orQrKzVdYD7ikT4Gv26jtTa6Iu0MqMaWYiIQR4CK8zOFkghhGZKY2amdlZFaq0GcfEoTNTYH6Z1Li7mXJuVczWDAmElTZqpAwptMEEjxqykMYi5slFzN/c1xbQpKoW43Yhmms7EEkW8WAviEUit6uTGTquxqpu4t+4di7k7QYnWJQgAs4SIBmBpcXeDNvKukXJruGjDTLyBUwwSa0plae48WZWUiVa9DUMcYMhZu9mQAFXTdckyX6VrTARWW5q3Phvbqtdy4+YWuzaBzpPfwwg5CxDQMJYzXteq4zZvEjjw6t3S0pNWpsx6HDMj5reYHA04MGcytCmTORALmmsrzuwwIwebQtfDBAuDeGAl96VWraDcwnrdvHEV1tAuaoCO0xoOCGAVSLjDGoWJRZiJg3CEOjWUrZHiuCWtNRBqnVyp2XyA3dTY3Z1bKrI7nxk8LWN3KnnlDK0cHxEhZxKHBATm1oFzbepGOxsYgpiYyB2maE2JRupyI6vkBASmRhV0NW8qUndvFv+wefZSuCKPhbIvszqZkkWEEIIFmJOLX1wMkba1+mk/7u9OBmxS2G23LtWoFOVc1RxsamqmS168C12f4CHHHspQ13mZmEHgSHEeJwmUIncxilCMbG5FF/U6L6hWQyd915+Oc8sUDxIcpLVa8ZDCuuzB0DiCaJMSzgjKWnv5uZ/ja0FGYFuzDeAtwxe+2ga1EUS21mdnA4hVPghyXecqa6dQJxi36UZBZIxAHMnhzs3dbAW/3IyigShICOLspeuEY8hWXJecp/F0CInLOAhu+tRjqPPQ11L7IV1cbmvNLBKHTrpuznl/HPfHaZkrLMAtBmXF8TQ/f/Gyi/T0qq9mIaarq6dX2+t3Hv3a/r68fpGfv8TTqyGFOKq51RicGBAyEcBImzy4GavTGmlEq+h75U7B2QnEDjrHStsqwG3LCPCGZXvu/PrbX2Fa/9hopiAwE878P/NKRM6IMVIkicwejQwwhrtjWbJWv9wJOxXNCjXXWotq7XkYUtfvhoCOqbNa1SmFbnfZTYfFFClIrapGQilSgleJ0g0dZWOYEmQjPs2ffvLlX/zZj2KX3v/g6fvvfculvtq/eP7i83k51lpSkmk5jct0OMx99+rq6vrq4hIIriOVcSkaBxHSV69fff4C0uV+w3FIu0cXFjAdFpKIxBzAHQwwLVYq4NM01WpExBK0enVXc1tvEju7aVUK3sZcQ8jNCXBzDq0vQeeCDi0qBQ0Al+BEpSiyESGGISWom6pOp4WZyuQnFBIH0HeBSrfB9cV2WJb9zfBe1QlFpjwG59XXzwhADAk6GwAlU08JwyYSGRO5KXEJiXJF1UKTMYEHIqW85NNRuVvgEiQFqmxzNPJZZQOyuunizfXlF1/+FAwxaLVSNRQQCgkCNDF3UiWaoEamFOLp9TjvZ19ss+mvh91+OXqTVna0AMfDXLSkjsG81DLE7ZKPpcxzncDx6c2TCenlrCLijK7rYgruPk1jzmaSzbkYisuYfTkut9vj0CdJpU/JMBGr6UJuKQ73t9M4ocyWF1L1MHCQBANoMtPhostlKRUlQxUhdDGw8SxSQqJt6J16QpqnxXwsmnvifps2QzeUy+V+++M/33/8T2/rS8QOHDstFQqvWYsyNferRv/EGVz286TnKyF4VRA2KEtXtkVrIAFORgRAzmoMOheaDuIWWGbkWE21ODQxu7O5eaFitVbjtpjLA8+jvZbPRyNnAqQ5EFIrAfxheWdyJnCzcwiUmDqzYBanZZ4rtjEt1cdpOUyIHZhjigyfmwe5GquTwjgYdUBAZmSmSB0UU56NvKLGBFTMc/3i9sW3nm6fvfvucqw/yZ+5OgmFXqpXomTwZbLPPrvrrsLlk8HYzbiaqmFcZp9f3+yuLx9dDBcp3+dSTETMiCAMbvtDstqc6+EAOwzM7nAOgYSNztFZbqheC2pGlJgiOzxSmselS+m3f/u37o67ZbnluIjQ6/tP630ERzfORfOyePZNN/S8ldrl4tNpOowTVJPIyl9ghhCzpo6JjWGhqR44pJTmE4skzQoziUMImHZgAAAgAElEQVSgSh60qHrzkPScl1xKySbim22fEjtsWTAvVbYbNZSi87IsxQIjUCgF8zhP05IXiFDfQ9iaj5xbKXUxK0ResoOVOaqDYwKJkLjlw/6YQvrg/W/D6Hgcr979QDjWUso8j6+m42cvyXy5X5iQJFmxw92dW9hurkFS1UQCSffOO+8+2VxdfXuotrw+vfjnL350v4dEPLnYPLq8XHRcljrnMs3LtKAWViVDih1FsdqVJmPwAiZigxVkqjkuUL3aXF1dXJOHi6vN9uaok9liXUpOenHZGy8cq4Uym8HROfUpxqFLAl1KdTImIzL4ZrtZCAIK4m7z7//ub/7o+68AuNmQuuk0CbMVWJUgvmRLg6Q+SB/IVUv1xZHZKnk2kLG1nVPbdHhz13B2cyNpDrJv9TTW/U2r4VemLlYIm6hpWbCu0uvX//wwstZEWdvHIPIWrX5+pa9UhqwZwXVWDxUb/NbvfZsv7p6fXoQwdymlWI3iRR9r4SA2zTVPeZmQGCKyzDNTqBJEyZTVQ1WQxOFyiEXH09EQIgmJIsCtqBfzAsq5lu98668dDot9KeTaCcsgLtClKUqgi5ICGe7CLF4rhAKFTdqkPhwPI4p7FjcksFTjxaZ5AsCgDoEUtdg8q2bVxepCyA6FG27evwmRQ5dE2ExVzGgSlkG6Bl2R2TLl03KcS+aZJAtDOSpircdSSC8utwO6kvJoSxe6GIY65elwGtNScuUUzelYJp1AFpIMBZZrwZ0TU4ghxhg4WNE6F56peYOgNmN2IoCs1RPNF2XtICqa8aivVdp5J05v/ttqrvOK0rZ4581u225hncwbr/YsVzyPoQf4dD3pw7EI5zEHh1dTf0sBttJB1mG3tpOJIFHMlStZS8gCmnECN282Oi91OOtfzzXoCrT+C+NXPx8a+RrN6Jf7CPQzD1+THv9lMaAHeeAD2eftY9Zav/b6n/cOf/ZKvhHqwhm6+hWhV994JV+7pPbfpu94+3rWnDtqXlStbAHBmDgwg6iQtt57lNCY6GpmZGZr5vPDnNnAfHJXV6sOnIshB0WmyBwCi6wmcuxVs0GrVncFsyShAFNdllmzEiGs83r70nkT2IsKK4Ga4SQRsUdTUwZJFI5MBIW6uQQGyNQMxsKS2KpBvcmvxMicDNxy/MBo8pdGT3W4w5hDJKlWNTucOQRYcXJ1bTADGGCnyCJBRCrcqrquhnjn5uTZDIlBzm7e9B8KW0kppkQIBF+NriHS3ls7gVcD6mos7Y0z5dJmkBAEQFnKOmjprOrBOj2wk1kACVlDhK0Vv6uiRajFFfoZ0GdgTUBqU4/BG7VqnfsaSNRcOVa0RvWhhdT8Y4mZQKjmBDoHXrSmr5sZS2Be51bmBwIHrd7TQQQuQdS01qwwYg5JWITNFcGrV9h6PWYNrQvtYgqrmrG2GytBiNlgzaieSVxIWNyh1Yl89UmHETH5A+ro5+nUV9dlI3JACWzCTCxqqlAhkKzc7VX5E2h10AMoEoSJKAoxk2lRtwaQqWINy2WIsDC8KlYxJcPcK6qqERuE2E0JAJjdzFDNjZglCBjE7iUH9RDDOFscZClOgSgEl2jMEoPlE2AULHaSXMwEnmKIu9126LpxOS0FVqAVKXCgiKRmGsT34+s5Hxd46MDRGVzrZIYudkIMSofjPfpu6CREDsLuKsFTxyR4fXh18+zm3WfP/urVpwEMkiDBDQaSgFxwVp81xNzMvQ3+NR3U0Eh/RAAb1n2au5PQSl47ty0ZvEYKOgBv/Dw560KVcA6WBEmLVuG2L0OtCtNG0zItBk9Dx4GzLsxCEa5wMhaOKeRcutQFBrxW4OLRjnsZ8wRktfL6Fo9urMxlHk/tpF0XRBAiceTTeByX0oeg1V7vx1f3h3n0eSow0kyEYFrvT4effvGFcLm5/GhalsthuN49enbzfpn7v/jzH/3jf/ynwfHy5fThh1d3X34RYx9ScFIthcXMLXCAEJyrAWBAiKSJ0mAGV3JvbjYOtrWjS00Gs65N9JV+m1pFk7URHIwWlUnnnRVbE44yBxjUSuOAtuolcxWJIQVmcm0NOSUXM5/K2KfBih4OxzIXNwija6+Fu9rzn9zGbV/yvJQx9pK6vhbVtsItqNV325t8cHihyBXGkbSaE5HzMFw9f77/3//wj4/H0+/99d/46Nfei72T6Oeb4WK3Xcrt7mLgGVWtWoTlaX5p9Xh1efPhe1ePH/d1nuY63t5+/r/9gz/88P1weXNpbPPiYzl9+J33Pksvx7uCjGNWFja3sRz2+46Dvnr1Eh6IY0xRtVquzorQSgdBdtfaxrO7rVJaIjIYu4YHHv2KNNKZdwgJHKI7qqq1ZPHVIasZtjkHInM2dvc86h1y4unZlTx65x2PT2INh7sxpcvq7DaLcGAMaRlSJ9ztrnOZbZ4Vcrq47NMwMNvxdDT3NPRCzCFoNqqqCzhxSh2BctYuxpcv7kJEWZDHEpzduCOw5S7SRx++9+r2y93llgMZFlCGWZK4G8LlttsNoYulwriMm8tn15uLw+evLofrqZZd2knGTb+xohwx+QjPt/t7d+7TzS4NuZige338yavbl4IUZPvOk4sff/HaSzaLMYSh62IMqjaZxxSmpZzmMpcKDuPikbr9/cTh+dWNDJtAglwVNoaQdrvdx9//FL4hxG0fprkwpxgSk2+Goeti36dx3C95ilGJWKuXguo2lyX7MgyXXbfJS+RCrsX8BGLm2IXh0eZb/8cf/OBP/tGXn/5ohAPKjilwpE44QHWszQFB2B/W17doF97W1rXgP//vPPM9kCnPKoxGdF17ANXOUGhDr829LWjCIQQBkzfngVIVp2kSDg6SEKwYZNW1Qhhm7qzr7ApTI3OiRpdt/Fk618htYnWY12x5dvO0P4ESUrdNw3bONQWYSRd2Xa/ZptjBlELqEKSglnyfBqlUc/Zi2HRDiJ3lyUPhGPvtUhwidFpOr493u3cu3/nonXEZX33xXGKv3RFEMCcRCbzf8wDpLhISxZ5V9f5+nwHo6+d38usf/drT966x4Pb5HSFRClwjirsqrMItUKSQwHA3lELiJGDjVnJUdQILRxCXSZkJLkKSYtLFP/vnz7/z0bsffvR42D3hMNztPxvnuU7zrPMyI+fm2khMKSh8KSWzKpUp26lWo9mpFI1Rdhc9KeYy10lZLAXyJFpL1SoU8qTDxuCkSil5rZwnYYoi0apN0zyOmCaaJ0Uo14+63U5YKJeSC/mhAMhaspkCfSf9MGihqkuugEHNJyqK45a2w+6CKZhbzkXNqoWuG2KIDgdvDvuZrGqx5UT70+ndRzVJevf6KYV+v5+PL+Y6lmWfT3djPS13X5aLDcSlzGoVVvNn9nwt8hVXm4v6TJ++/2i4DJc36en773/05LqadZe6eRZ++OqzwrTkWpdMIOa2BwjSJeawjNO271gA4o66AO5j8rSwIJDDCwd3rlpqRXE2dB46uX58BdbdxaA0z8txzkfSOsRNrrksM4GjiFJR5qnUTR9yLgYPQbwavJpO3/7O0+989PTj73358ZfTsNu6GiGQe5Sw2WwOp6PE6EEqWaZcUoXDqoUk7EABCxQuRGB2J4IQ2NlhrrLSqNYvvLU68wweNykWrypDWvf4zY8WjWBz3hh6qytXONpgBe5EEhpT/4x5EOBgdCkp1Vrq0w+6D37zMffL7eGz/fLj/kaWeb+JrNU2MUxFrUyaR9csAMzLkksumyFU1eU4waHaqbkTx5BIUI+jmDgHM9puErOWMkWRLgUInt/e3t7tp1xYwJV0UhSKrexwt6yQwMLMgYRbH5hJYDwfS9RuLrNln09jF7rD+KKKqWeJkUC51JqVCiiDjZP3gxBFOEG1XsRtiGTNf9cQaoiWaq65FOqEyBBpPo2n4wiDTozMs9pip1LyxWVf6KQatDIqcISZeUSKQy263FfECDKC6Ijj6/E0j7a4FkVFcDF1iTxsuhS78TjOp4U1uJOqQYnbauAMRXA3wJq1vrtD8VAprNsn0JmJ0J5ayXd+bktipeeh6hmPemMd66v+dKX1USP1tl586/c+mF+7gQAhYjY3r4oHt5qWcrhys1ontV2dGyFGNq3OzaajrVwsxCsRwd3c1a3FKa0SxzNudt5/fhXZ+Bnvo29GQX4ONPLL4kX9vEd4yPv7VcBj7fErBZUeTrHyOb+J1fWrPvs3Xs/baNrD3X1zkwn8kODla5wBn7EtEAURBeDNeKh5uPMDwuhwrdoo7Sv6xDAzqjBUBbxVPoTZx9CFlCK4c5iaem3b2FVO4QIOoLCSZ/1saMeQ4SLR+py3HEEWSV108qpFqzmZw6w6nFJILKzFshdtybtUzcndrXEymNAI+yshiB0OgbmVoqYNsaYHS4izy1dDoMDSBA7S/lLNubVI1KAKECRIA6PMH/JD8HD3K0CQKMxUW4yd+xpNCocRg60qmCRIY0c1koS5WzW4mRo1whXI0LIV14/SG1GUXM0YpFCHOZzMwEJEJAxqzVQlh6s7zGXNljQzEJ0F076WyrYOjRZn6e1NtcZto4CBAISQ6LwstqxJdxeOQQIxw6y92ebXfQbA2lhsYjmwyBslhLvEkDpxxTLNZV5Q2mCgGCNjnQe94SCNxdRsHoiIubW4Gw+kCb+LFwK7OzVLNneH15zbQOaGvTHBUFTPf2RmJiE74ydngrabAwESJCRplF1qewzhM0Lupqpm/gATEBFBSAJjLCUIhRCJ2dRrVTc3FhJiDszkbnWpjVUMhpObK7l79WHYASoUx81sUISWAuelVPTh4nKbPDlpLiUvJ/YQRK6fXERJ0paP7LXWxm0nB1NMXfLVzWqvplq9KrqEzdDNs+73Gb5sMWz64f7+fj8vXaLdbpuiANp3Ubdbpml/eH19vb15dAkB2QoJuzdrKtZamtckHnyoVvcRrF8xvN3HOT931gq+3VOiddzZuvI28XPrn5/d+daMTUXsg8Fojfkkb2YC1oY9KHFKiQNZ1VwLBH2fmGBmF7ttGe3q5jpP0/74fMzoN0NVW5al6zj1fTEsC2qpc14oSQoShxSRUteR8DRPh+N4nHPoN8dxWUo+TqiKxJESQ2nJVYu9vr+fp+d//be/M8/z48vrJ0/eeXT17NUX+3/4D//JP/mnf14XhIC7+/suJHWrOVcrEI8dxxCaoleZmNyANkQemmWNHnkWEZGgjWFjonbvfFUlrbfVsWqPnBvvrZW6TCTtFUwBRCAXESKYloo3zT4KAkBV24095z0GETalw+G4TDkfDRVgcGrFEKZpHud8ezohClBBGvu43Xa7y83i5TBNIHzx5U9/73f+RifpL//qTwsWrxJCSn2sVadpDGGXj/jjP/2rl3c/+eEP//Lv/J3/5J1n76jWD57ellyYSb30XVhqJs5RNi9f7u/v8s3l49/5nd/ZbTYnq8/vvziOxy+ef/nue+9sH13fHadDPt4d7yXysOujDOEy1rFMy/6yj5tNr1rm+TTPi4i5B3eCm2olkASx1Z23Kayx7iH0bK/HIADCTg/YOZ3ND8HERFRXWiZCFAea7dq59QSok6NmY+EYuIz1009eWS4E/Lv/3r/9lx//iXhf5iWGwQPAoCCXlxc555xtt0tLsO1ONptNTLEuxeFEbKZaa+hSt4novZ4KuYYeHMRhSyk644svX93cbK3qspQ8HX/zr/2WZrU69/32+uZi6AMzpcRLJTWzagROKQ5dFwNiCHWZu27Y9luYaLU+DWHbk4uptUASEFytlqXMOXVDJ6kPHVOfUWrR42Esyz7weLG7fPKEZdGqDthmsxHmcZy6FBU4zeOyzEsBR2IKIaR5KYdDubjaXV5cbykueSYJh2MtpQqh1NpSbVgaN05DDNuLnohY4NzRnIm11nI8HZfCimxUTaBq87yMx2UcZ9C8G+KmG4In1uF68+w/+6//+3QkOLpEZqiaU+CQAhxwrlqKOSkovGVrgCaaQPtqPjxz/mY+zH6tPbjOimZKq6PN2613PDyzFmlqRRddQ6hDox21NZ0IQcSJ81IFDCKzJuho9czK05cWQUNwImnbHjPFqk6pWsbxJL2Y+7xkzPCIkMJmO0zLCQRhJmFmirHvOnWLIUQAalrU2SoJ1GGGagiIBINbiPHqKubo+VgL9MX+x5uBv/XBh7+1+eBH31te3t7nItWcU5AQSWw+FUTLiwvz6XTqL7dd2Cw2AfT89uWT6+sPvvVOH9L98W65LRRg6q6OUsgV4nzu+6+RuI1E0DwrvLBYqwichUirac/MEcs4Hfc5KJ6/fP7OGEKvOS/HcZyWDE6BuRZlKtXgLgYID1qpqqmyLqiTZQWYVQHDIhZTIOuF2c3yUstky1JOp2MpmBbc3IQUY60qkuCkatvtRZc2h/Fw2Odaadx7noG0lG2KV7vNNiwLueXb1+NmQAzx8rJT9Sih6wJimOduzrOWFatkjjHELvUsVmrWitNk/c4b38fVxtN83B8YlMdSZluO2PVXAkmx/+lPX/74Jz999elrZIDQVxIVVOhEtXiZQY4gnACtgLsVv9sf7l4dfvjJj5++Ozx+9+rbv/neB995fP10Y5Rfz7ev716EoVdXODG5BIlKjiQyBJK0C1eXm5j4dJxq1vE05nmxCiHUJd9cPxLIMud5nPf7w2kscAjJcYwSnTuLHSiCsXa+Sp2WmQnCXRjCQMESmbi4kqsJCyc5jYdH108uhu53f//XP/t0/Pj5nx3uD9uLoS46TTlIpMjcB2dfyqK1GlcIgoR+6Eh5qVOdHAYOZAUEjymoopTiII/UOh0sIBI4uZKrPmz+CVjNi20tjxv8sEIZa7lFeOCzrLXWyghunfAz1rX+UgM0XNzN0eHm2fY/+o//nZe3H7+cPovXiCnNlkuxobvWSstYSy1lXmAU2aE6nk6bvoPROJ2msYSQLi6ud5f9dFqOh5OZ1aWAUELpu9QNXTdIWTglogCAP/nRD29vD3V0ccA5kriDlUWCc5nnydWIyVx1UbDGbdcPnWq9u713qsUKzIUYbiVPnng79HVRa5R/k4hATHAEl67r0iaRUanLcpy1k6p6mkYQpaHfDRfH/eH0ajzxeHG5CTtZ2eoAzEopoghRGNzFFIeLnPN0P8cQh0uans+uEvqARJJCtsWWjAJUHI/H+8NdzsXNIGCSuuScl447ca1ztWyBo1bXYlDXJoRCXN3UHzZ1OPu6rp/sW5/jw87yDVfq4bfooRw8l9lnSArWUDH4mQJBTdPw9glolTgQfwWZWdWCjrfPd94V4WFFI6hWczN4QxNoDSFnd4ABPSNWD7Dam6N+7cfzw37mmV8YKHp7VX0byfolPsLPnuOXjjf9gkf7xpf9Czz5ZkC8MUf/Vw1j+WojdT47wdwerufhVS1d9oGe5u6N48MidEblrDoJ+Bxo+HD8RkJZ32brLKt70eKm7lQrAGeDgEExBRE2eDEzqKm5AE1V0YwGDFCYuZGREzfl1uqB7WZV4UReUXSpIFeoqhHBmcydiSiQkDCzuQNUp6zSOpWrORcECOSBRNjj6pwDBkxzyWTEJOSmquc+uYOAsBrJN6hiBbCsuerZGdteSZvVWqj02mdduyPkzrQq9EJg5tC68sztDru5Esyc3dtbBtBmFoKjaSzNYEbM0iYdW+mcOPdz0agRTRa3YtuNQNWcXrEqtZgJao1sZWdOlhv52zZl5zdF/JWhu85168/rp39mu7bFFdWYOYhIS1crjRnsIPYVr/c17o9IHdzI8iCHNacA9cpMIqGntBCUsxUQ0KLnG6tfrYaQgHNR3bB9Agd2gqs3p3+g9fDCAwWs0UfgTbp2lnC0KjbQ+paFW+ehxU+2id5h6s5uoY/hbGK9joTzcmFmqqpVW9b02twQhEbhElrbcELMYlAr7tqMzFpob4vRLGCcPe/XgVRVY2LmGCT227QfTyBoy70uaktVLxxo1dVBAoU+dVFiLXo8Hm9ubkCkalVbpHQjLbJIiEly51YVXVnmQoTUiQQyz2oAKrsmplndSmG3GCSw9F3HSlFefvH5P9/1715st6hQs+ZwD2eDU3sLbu1mnFETw9vj7LxPe3gQncehf2UibQOPuAn5VxGin0u6ph32876PGmP5PHCJSISIKXub3EhEzK0WA3mSxGAzJcAMz549iyGeqqWwGafx9ev9o5srlkBC3TCkiNCBk1BMkIAQ1lxQpqXMkkSS5FrqdMq59DGWWIqCIFoarbghqPbFbb3YXc2nfZRut90Rhdv7w6c/+fyz29vNgNT398cppS6IOJroVKEAu50lSMR8lgwyrM1Fdk4lOJc6fjbW8yYygrc0q4c73O6QQb0Byy2Wps0c7g6Yy4oCrpvo9mM7QoqJmJtSzt7yOxAOJmSl1sVAoAQ3lMU1lxAtioD55urxWBazpVouY5kFF5cbiF9cDHLNlEw6SOeXjzdltul2tpg325hSUtXTNA4pRo7zoX78gx9//y8+GdLm3fc/so8ohc0y/qNZp3E5wHU6Fu8oRfLON9vtd7/73deHW7Ua++7i0c37H3375eHV/RdfGgc1HA770wlk/OTJo43s5vspl23qCVwl0MXFxWbTmfE012WpuXiM4BBQudRq9rbL49rR4Ta9NloN+3pv211kuJK5sYDgVSs5BWZnmFv1ijf8cSGYhGBmMEspTcuMjONhfvVy/8XnL5dRD4dxs0tulTmkXhzOjBDhRP2wEba+H4ZhOI2n+/1etRJCyVqpAh5Egki/6bj37rJLfcg2TzlrQXh9O5fp5nLX9dvnz48ObnL/vEw155JPS1liZhI1VmGYkzCBsExLn2STLrq4qQWLlnkqMXQx9mU2ci2u7kgiMfV90O2wiV3fN6Nf4VotheFqd7Ovh9Npurl6/K333/8gDXMu4+lUtVqTssKdeX+ayaEGLQXw7fZynicaNfCzZ08+JJlv9y+neUmhaqXLXff6bimm44j7kzHyNC4pJWIOQcxKLpMjD1sO0UsZcyYEbrEtpZRSjve3ecnLxZZT7DvZbMIWU/rik1vcwnsfBiImnc0Bc8s5N4sEIg58nvDOJpJfK3ffQFc47z8cb3RC68h6aKzhXHi8+VObENuq1+YNRfNhVNBqWmKwxo5vPqTM1GxPVx7yarDpK/nDDNY6E9ZmlwfDaWfkWswLC8wqgK5Hv+UYeX+cQ4AEV11qIT9bI8JJq5uXbjcMPYtAKC9zYZiraWW3FLnrhySobHmZ99TjkL+8PdqjJ5cfht308f3dTxUJF5dbYz/pZLUqoNXYeP96krT1HBINKfJxOt4f948fX28u4uWj+BLFf1LhOH+gHuBOri1CxWACcoaunjHa7IvgcIPSsL2ZTsdpnmfzOmW+wYfvY/tIxnyaj6+P86tpHjlIBWeLxciIJQRGYopXu6fTWOaxuDlRcOhymu/u7ylQ14XIcZOG1IWSl2WZy1RKWZZc4JRSzMhwrtXnWU3HrutT6ojCNOfTKedc14SiiG7AxW7YblPq2JziwkOPoY8p9URSSxtxClBMvNl0M2UAXdddXV72m86szvN8Op6WXNRwel3KrnbXKUa2knPJQ4hdkkT87Hr79NF7d7eHH/zpJ198+XIeF2Qk5oS1TSpolrXuBmEWTuRuXJmjBPKugEgC7l4tx+kLF91sh6vraw6hTHcX28fc81Lmk46mEAeHFPttoL4UG6esi0XiSGIoZTrtT9UdlwCJdDIk6WPsYt/Lrt/EorWO0/H29nlV3Z66R0+2oYMIxxj7IcIiCO4Ko8vtdnCOZNskiVTAfRShcNiPjuJUPvrOu9/57qt3v/dn9y89BLjSsOtqttf7Vx5FXKSpL9RbvsfQ9xExOr2e7qtD4AoE4Spu1KwzWvbPWgh547w4OxGliBZcfW7nn+tu/urueAW13wIfWnpVc6735u7aervmBij5GpOSlwWGmw/T0w+vPvz20//57/+P3U3uYkxddzyWUnnoNuRWNedlWaYZihSRYgwgadIYg1YweeCQYjeVJY+TSIChaoGi7wMLOFCZtSxlsRmF6mztGqxA3ZFBKkKJlEmNPbZ60WAOQ0S3jf3QISCATtMEgEVSiF2IiZOx1qV6rp5VlAJcWhtOiaoqLQuqVSs1W7RkqZQ6HkdjPBm2wzBY1vluQoFWM3UY9TEwx2AdCUkRT17jskyFxZe5oMqT6yuy8MpvT/eHYgG1lsAgQ0La9tmX7cVwmO99XlWjLRnWHKpaSnG3GEIIoW2V26fmQLVCymcDgFbkfTNc8HUYwfGzr3zonj/85Rm3wvpPo6TQm6Wk7TVphb/WyKo2QFfY9MGC4qtX82bJWmGE8/KF1hRYMaw329XzhvHtt3NGEr7p8G8AubegvJ+9kG+8Wd9wvb8oCPMLQl3hQejX3v/bEMnbz/+CZ/3/9vEA8j0Qyr6RlvWrfjyc9G3c0Sqc3aBtE2LWyCNviGMPH1hTfr15GwSvXkjNXUSA1c7NyNYK7GEPLwSiEEKrkBo4ZYqqlTKpsLFXODFRoBCi9WpVTWEO1GalqYoHYFlU26nUCYGZAhSWdYkxphAtmrXI0GDs7GwKJaHQc4isITQlkbV4QAExOzX4gCDtm2ns5MWJjEUCyJsXbbEWE8QBHCV0kYSImCUQUdulq2oLmBYWJzYzqKrWuEuMh1nD2QgGrRURcJgokZu5xAB3UyfiRtmBQi6S1lo0G1xYRAhCgGutDaTjdQvUZjdtarxmV4RmxrjOD1gDTlrsXWNGmZtpSoklMHxVLIO/6q/v570vkcgqDCRDY+cRHE6rysCdIJAy5vOMsppjMDEpaVs2ioJADXbDClaSvuFDG5O03TiIzA1mZCWPkWOXuiEOdQna0r6LVQPcjMzYWUuDD6nF8BEAqLMEAbyhlsRhvWXiQGMymZtxCoCd631XcyKmIO5qqOZExgA4SeRu7R+4t4CZ6MG9JZWbiHAgN6+1+ur8Xk1b3XsW3pKv6i0DIjLNqlQAACAASURBVIih7maq7iQCIld4Ua+ay9k1tt0lBknTmSIyH46n1MXNlndXGw8+bIas2QVGNubp9evXlWoMwUyHGIbLHVGYp5yXXEsVka7rN9vCwShyP/SmPM01Rd5uh03yypUhpViTB14/unz67Hpe5lp0f3+32wyDFi3ldDiUm+Q9CbiPfPMo7e9v3/+N7z59do2E6KEUE5b2bQshLsvSJqTVxr0tdnSGlr42K656mdXWis+7uzezKRELObXDmaubqzX+AhPBzybu7a/NzCVQY91Zs9kmuEBERMSKWqkXV7uu706nA4FE4ngY6/7F6XDqUxgu0s22P92PglCrjeM4LsUZoQvF6lyLKxfXkhe4BY7MnGK/2WzK4XQ47Q+nKSXe7TaW4ulUx+NUZrOK2CUWvDohdJEmCSEQxSnn/+7v/r2//N4neYZG7LrB7+ZFS+jBzKRkiqKWARalQCSBiIUFLg5YM7Y4RzyuPdl1x4kzbNJi8pocAVjtXNGsCpqTE7ODAjV6UFOviYDALkVz4xY6QCLM5EwpdBKIiNSslKXWFrIKk5Z/xhMWACGwVrfFtX0xI0iQD2POCwcHOwpK0mVZhqtuu9ukEG8ur3785Q+s6MXN7v7VHgOacrwstY7L7uqS3Ezrq58WOP6r/+K/+Zu//6/9B//hv//Rr390c3Hzl3/+J90QUwBFG08jue0218tQLy8uH988fX77aujTcR6//8Pvp028/cmriqgUXt2Nx4NdXT17dHMTpdfZSSRxtyyn13cv08Z3F0PqOm+Odk7M1U3YUp1cofbQycDD/AwjEEMggDvUAV9tWJsPEbETCdzNtTrISNasDgEFAqjNWzohDIRKZVGULM5dlHLCH/3hD/7oD37wn/+X/+nnzz/9/sd/8ennP3j07Ppb33kvRA6BmuP7O49vbl+dlnmq81JVd7stM+/3xxjX62WRbhguN0OXgiQuVMqUa8GYce30yU/uHv3ue5fX4fPPXv/VX/3ko/c/ePL4puRc6vzo5pmicnQOblhi0G0fNn0fQ5jH8Wr7pO+7+1fTTz75/NnjkNIOlggpRDDLsizmdTtc7DbDJe+GsCGJ28326ZPrm5steDzczVTkvWcflAU//PFP05Cfvtf3Q7TJXt7dZrVcai1Wa3UoM4KgOnKut/Uwj2WTsRRO6YKlL6fb2xd79xDj9te/++Enn3z++m5Rdw9eirOoQ+Feq03ToZrtdnjy5PrR4+2Sj69fj/vXc+wpbhGDEMAEVgwhdBYwQpf02Sev//gf/DP00IpanNkJiCHCKefSyq2Hh7q2ue9tDOubHz9TMzYyK4HaD62sbFTTc//IffVkcwZIml2Cm1YiRApoXcYmxQUJhBsLmUibYyCTChrpzxVWWkgrnekgbetDEEiS1IXYBaqQJPEK77xzff14S6xVl2dPNzGKm01T0Vrz4oAKq1QCL5fXl0IkjCgobEs+5pl16kkTcRLSsEm73e7d9x/3iQPVFOnyym6+ffn42+GP/8+Xx3sjQT+kTtL98SURhLjvh77b2MTLvY5TkV1/udvmvLx4+fmjy93f/jd//2J3/Xf/2z/oNcynWhewIwo7MYp7NQeII4jcQBwpokscIpyKeamq/Y5KkBALi4YL/MZvX337154NlziW/VKWxTB7ysd6mOdcqxV350DUhRhD/8/+5OPpuBwPKBkowAgAGAD3WctJJhR2tfk4z/N03FccAMPuUbz49g26F2o2zzqOCiAlF46H+9MXL16Xgiioihjo6jLsLofdZWe+3N2fxumwLHm7DUTmyIQYIgECUzXvOmJOXScAdf1wsdsS+bIsh+P+eByXvCrYTL2LYbNL82gC5Kns0u7dD59t0tX/8Pf+pzoBE3ACCqQjYprnWmfvQDpBW/tP3Z2yrSEu5i2HyQAvQL8L896/97+++N4fvfjw93b/+r/xN77129+il5+4uytZcSK/2O0YQ565ZsvH5fazl4fnstnG7a4bdt2j99831WVZYB5jKketxxm2WIUrRYmbvr+43N7e3RZd1LKZlVqrzWomtKEQArPWMpdymO8jh912sx1Sz3p1cSVUl3GBFV0O6A7Prp797u+8+2fff+9PppdEFnahozjOealSa/W4ZlE3Ij3U9FQuH11cbncXm8vxcBgPU61Fqy26IIASO+BVt7ukRUsxLavdcAgiLDA2M/fqzbFDyW31FVqre4itLerWtGIBOQKoadoh1ADo1kUhqaq2ag8N2L3XHcvyt/723/xb/9avP9//+LOXLz64TkvxuwMfRp3nUFSPJ3v14uhWHl8+SpuulHr3ev/iywMBqesCSaS6TOXVF68Dn3SuwWXTDZbLXLXtnpxsyuP9uDeg21DUKEKX2xQ0l4PrQfPeQk011DwvgMeOYowIrtGx5esn19urC4p0OB6n+2PsUi3FTnqy6URTZDCDiUsxq2CgoC5l2XTDkDpCWMZ8Ot7XYsQwRryY3dhGIGI6zkICY+4Cuee53pe9Fq+oKVEn29glhc86Tcc57mQaFzB2lHLNrOhvNt1NV2ue8xJTrFZImBNnpdh3sUtlqVUrM8pY4ODERr7UgiB96mCopZKcJ//VbtpWO5rz5N+sD9/uV3wjXPXzlg9+Uw+eu5jN19jPaZZrD3TdyK91igPuxM2F19C2XPhqH+X/5qTC8DYymyLCyZjl4QUrz6Ft3b7SuTmntH/1eHB6CG1/wwT6BRGVt1vgeAOx/TLRmPDmWt3xlYz5r1zHvxoM6Bc8yze+7GsUtQd20v+rI/9SHm+f+g2D5gGsf4N6AlhlXGtr3V0eYAusMC0CalYAWm1Vk7XfJLC0zY+jufzyCtudG/zuZhwg0jy33eHC1DATEWZwWTsC61AlJ4aQQdXUFUrtK8XkFpgrnJ2bS2FjnLubW2AhUNVCruwPjUVrUEuTuzWhmcNXZRaZuTmZL1VLdYO6OszVXSFJnAwMCSRBUgzMogSATLXWWmuxqg+lqfuqVIQC3TkezIkM1oASdg4E91JVYQ4jsKsDoIek4tCqi8aigsFaQKB5c6sHM7G8wcwfQGsiZmGFneEPoqYwbg4CcDW1lT3BZg3wCi0B0dyhLYPnre8drbat3ESXZxjhzE59uAI4HHmdYpvBFLNgzUw006YeIlojgwFd+4UE87Offut1rngrgxharPgikMCMgMDBjZQKFVeYG9gpn7RV1CwgpuZ53rSEoBaSgSBk3NSObR50Ijg3lJxhBm+gWbN+t/N3ZMW/xKCkAmnu9ZXMzAK7VWvflHYDGvHK1xiBNzfnDAa2DHQzoyCwNlCa7EuIWRqGvML4514aHC39kWll4sYuVehcFmZytm7b6azqxsK2uC615T+zSaSuSz0ZlHS72W43G1NPsfOthxSczeDznMukC1VCFGGYmHrXCYFD5L4PMYWup1o1UhdjmqbjtOw7SV2MXYjCIOF3nj45vTq5LkIOhfNqQQ+YuzQPr3Uq8PY1WFWpb5OwHialN32cdQyeX3NGR8/PrACVn6mHzbPPCeQgc+MzOAm0PMp2YGZKXXRBTGnohyAyLVOULoUuh+ymXi0f8zguOKHbBU/OgVPc7LZXKQ5LnlLqux5p2DrTKWd0wSNVd6+KwJFps92SzPvTNC/TMk9tInJmVasFVgEgBKlaXXE6jSGkEHs114z/5e//AfJ16kFOtTqIyUkggQODVNts2mYCF1jrn1ljvZ+hK/c3IImv1a6vkz89VEKtdQE0nh+T+vnzWMMK3uhhoe4wBFJT05bXCOI1ZdarGgRkZqbVrTqzhNgzhRBDYimLnU6nWt3V8X+x9ya9tiXLedgXEZmr23uf7nbVvHpVfCo+gp1E0jIJyaIFEdDAmuoneOCBB/4FnvgXeGR76oEnNgxo4pEBa2BbgCSTtkmRIF/fVHeb0+69V5OZEeFBrn3uLfLpiW5IwIYXCoWDc8/Z3cmVGfHF1whYWITVrCyl65pQmaEMa5zFc5l7blOe1XJcwpdffDa0u27XqW6nvOQp5aICaTbD8W500t1m2O7azWZ4eHP8o//9e7/86Q+eXDx78uLqk/e/9fn1D9jciz2/2j3sJyG6uPrwW9/8hbbp75Z52LXZ9bOXX+7nQwZBOCUd+k3XRlPp2i5Qd393n6YFVOZlmpNTwHgcl2lqu74fehGb5iUnRSat7MKKjwrVvJF1AlTvZlrh/pW2vw5C6xlRKbhVqIWaG7HOHqoPojngEiVA6kiUCrFwzkaO7Vl3+OH81RfXxzG3YTsdy6uvrkPky6e7to/bsrkrx5dfvs6JUlrMQEQhRC3qrqEhN6p2sRIYAmNz8jkvc56zYnGwBHPs93PTdE+fPX/5xee77n4bGyI83NwNQ1c0IVjbi3Mgn1HTWhwE6tstFRzv7vf79N6TdjOENHvJbk4SYoSrSdN3RIupCTgSB/cI3oXhq7s3nXSlDaasppHFyvJw83p3tmvYu8hVbPWwH6dp1lQACFWQ1zVS5dVqJi3BcykL8lRSTiT56YuPmkhMWuF0ZjiSmpVSloTL813RseskRiYqpcxu1rVbSIGlXMwNpiYMgbcSOgz6QLc/mV9/r257j+Niyjm7sQR5HIDXWF4nB4NO4WKPpdpbQtbj6Py0SvBYfJ8KjtPGSFjv3HdqS1uPm7WKq9YW5ixUc0Z9HWUVsyqOc2Z+7CjWyfwaY2kMoRMi9ohfETOELGeKbtAlTYrcdjRse2bsj/fzcnz+/EpLLsUAdpOSkypC8IaEgmnhogtYzRXmZAZ1L7SMKYu5Wt/1IcYgnj1JhzjIQ74u86Ebzp9/8yL/+O7N/W23xK7rubGx2OF4L10ZulYkCsgL9vtp08t0PI7TPfzJ9jw0ffm7f+9bDzfLq8/vr18epgNKMfiMAhgQQG1smtbBJWU3TaYpa/YJ5lDMPKHFZsvbs3h2GT75xRcffvxMWlzfvV5mnTJlbabs04Ilw5TIKVQjGPNpLGlhZGMFM8IZ1/AQJiLnwMGS7e8Oh8NkCVgQmGMXLndXT7ZPbnFYMIr4bsshhGGzYeJSijhiEyXAlIahG3ax6ZhZ53kep0POiQgffPhsGqd5TlqKGUyz6pJm5OSleEqJSULgUhpmUs1ECIHMvBg2m7CUAlgj5IHFEQSbrokUyKR8gdD2cDFk8yWoIJGPJoq2a7POBIGBiEHB3F1JSMyMahILgwjzsYSW5BIcfL6zP/vjn3726tXu25c5jJYLg01LIAoi85JvX9/mxTAhH/WQdJrmK4tPzj/u2248Tg93h/F22V8fzKDZAO67/mJ37g4BLs4v+2370y9/fBhTsZnFmhZpLl0nAdHUtNie5l03cGwk1JzlzDqncfQlH69fbZ5ehTh9+xtPfu3TT26ulx9/ecPOk9JYdHt2MY5ubnNOKN4Am0YkNuxhnuZRFebDdjg7P7+/f3jY73Up8BpAamD026EsmeecUEwBkLmXtFQuJNEpQzywKz3aKFZJCLlU3nllpQuxEROCO9XoIadirqsHRnV8tSAgYk1pQY/3f+Hyg0+e/PCLP+g2aIcutO045Sbsmo6OR1oWEopNEzb9lgRpzlY8UGV7g0CBReHLmJYyo3gbOy+qRSVAIkRgpKksydA03HZd42H3/jC3eZ7LkgoKQt8G79gkl+JeCjlhqXZJtWhXz2Uq83iwxfqGvaAkQGvtzARoKSgQgjDBoMnnNHmDJiIvRRdzAyLBXJMTDAwSuPoyJivaha4JMh6nMmd3WEHKuchCBs2e8lKshJnBaLrQhNZdYh+bvjEpas3GN7GJ43jMJbVdF4rENsQmcMNIFcWpTQoLs5kRCwmXkisjqZLlXZ1XYUHtyf8cVvA1hsHXgYTTgvgLl7+DXq0/6KgtZ4UwjdQJ0kTI29+qlKu12XuXQvT1Q+b0D/Vsqi0/ofaAOIEPp16muqr4arPgbx/hLQrx7gv++pvxx0rq7RzokfP05z+If831fwH8+to5+3Ov8Jf8uf871898ir8iROldAG6Vm/11QVdva6C/IPd7JPbRYx+4ck5Xxg4JvWtx9fhG1vfCj0+BRw6FBBIRODJrdW+u7AkRWZEjd4CzQ6oWZU1TMBhBaB1EukHAImT1LGcYQz3nrEljaE5ab6DSc9xNHEXNtFTjKBEnVCUeGbEbEQuk0v6rAM/gFNiZ1Ixk9URa6blsIQgRuznUaqR100ZzNRgzMROxOzQnq3e1mTExBxZmAKqgqq5hQeNKWmMBK9l/DQQ0l8Cm0GS6+uxly+AankwwODMv88KBRUIVvNXnMrM6mWHh6jxflXSnv04FtlbyCRERV02cVCdmX5nwzCwS2NW8QATV9sbNihUJUhNZa5FsazhrDV5cnbe5opVv187pWteH1w6MiVw9axFiRljDYGscJAErjFl/3UBh1TPVOn7NZ1UOBHjWpMRV6QAFN+ziUoJVwdS86pgMWFHQVaem7nVuDCWFmzGMjYmEIIHEQ7XyADPcyXmVQdIJPyLmsN4+xOAoq12aEZTzUtytoqgG0+JaihVdb7IVLDn1M1jpLabmJ9RgfauAg6Q6BwnDjAKMT6ZQj1s9GcDuSkRpXtK0SMNjmZ+1QZTdHYwYmAM5g4WEOUrMky7HJY25bWNDbYHGJgRuPNhcpv3xuBzVZzYzoXaz66kyapxiw00Tc1mWNIr40G+vdlfjYZ6Oe3bbDEPfdkyV4azPnj9J++sQ0fYBXs2SoVC4wLSY1A+xHnNMfDKqwrsYaP3/GtR4UqhWzA61xzstSwCqCn5LVGZUiuFqPbmWCwY0dOobiX31FhBmEcmmec4VsxYOaVmCSBe7eZrm41QWx1w5Vmr3ZbH86S99EEOnCjMOoVEgF1NTmkPctA23BhQzL8Xc2q6dlyUteZ7nnAtLnKakyVIpj7I7OFjocouU8m53GWKTFlum5eX3sLkYiZgoTFNiEa53cs2wt0r0ZHe1EwLoJyraqTx5BKZWSHylZVBVwp4+7rfGCeQnSKWuSQYzkYgwnSYTtY12XzGy+qlW4z5CTonyuiUWN6mpUNmSZuHYDkPTzMfDsU4bKshovPJtRQTk6sUV3DCRFcWcJlt0s+kfjpo0peP1k+3z4ax54pf7m+N0WByQ2A5PL/a3DzlBKEYepKTlFr//P/0rIfqbv/2L/+B3/+G/+MN/+vmr790fb55effidww+DxN/41d/89V/9W7ev77qhn5bl1es385Le3NyyNHMpuVBOGpuuWuTc396/+epN0ewwCqXfYBiaJaUYWuEAIvfVNAjCNagD5tUpf13n9dOu8xcC2DnA1wzVagqHeuhkLaZ1kgwzJwEYlUCICnM7NSG4ETk1IlqKLkrEIjGNBR3+x//+X/6NX/3G0O8+fO+TN/eff/c7P/pgevrRL7y3222mKeV0JDQll3kusZXK/41BAgd3muZ5yanTvBQYMwsXS8bWdHQBV7fzXfPV669yPvuFb370cLO/fvPmg6unV1ebeRkvz3eH8ajIm03nnpYllTSlpd0MXRPaSN00jk3sP/7wo298+M1XLw9HS4Dlol3fBRnMy7AdIjeaRafctrHvYh9Di5iOKVL38HA9p6VpuqdPn765vh7vb7a9dA2d7zZLsSVnIQRhYmYwO2BWMs52vRCJJC2UZg9uKCCVcT8Wn7/5cXhyuY0xbkdJFmPohVtCTIuN49z0ZD6HWNrGVRNRatoW1CqRe3YHkYSow9APHW2afhM3n391+Or7Bx0RGBShJ7uC03an9YyGS+0iIdV93R8xLDyW+74epxVx9lPdRSfwfgWVeWV41+OSUQ1K3E+jwPVEdFVVrwMQZge5VdtTg4GU4WZZUSmQdeZA7FzV2XWUGEAgrpmGXtVHxquoSZqw2Q3t0OBeuz42fbM9G9TyPB/V0HftNGkIwZgXlHlSd63JTGwMSJpNbWma2Hcd90GX7v5g+/tjzgVOw7DEICHQsAsURae5aVy6OOXp4sVVM7Tbr+4/f3V9t8/vf9Sdn591Q3BY37dWmmXYmPI0zfOyaMHFJUtjx/l6enlz/uwi9qHt4/nT7bLXlHS1WkuWTVnUqai6ciLStuV+E4bNk37TNE0sDmmIYup3/vS9zcWznUmZpvnm/u4wjscxu8uSaEmcDa4kYOdIHEUaVWeSqq8TDkPfhYZdlIgYfL49g9F8P1kCZsAQWmpCTPvy1fevn/7GlovJJvT9ICFo9nlOTUfvf/jUnUouzNK0DUdzT4f9pJocpWmI2JsQF5pRt2d3M8/Z5gXLgrQgJ/RdLXHh7mrFzCTwJjAF7rq23D8waDN0u67xcenCsBzLmy/eLPt7OEmz0aPasqCgJGcnZCL1AgsUyMmKmwPiRmRqaroGXnIgr3WZIHMxqKc5jbrchtf8K9/60JmgZBmlIMkoXSdO+1dHCELkMpsu6Dtyy8s0ilOey/gw3t3s99cgQmQOTOMylaNasP6qe++jF5vh/P5uLAUUETuECffniw0ySGNKOZUlIHatR0YTLHExawzbrgsJy+F+81Rpun9x9uwf/YPfPbt48V/+N/9EYtuYjA+HOR2brmGIWEOlcFFxg3ouKS1JTWMIHMkd24uhO2vH6ThN85yzMBpu3J2YJHCwUNgsOxOFpjFVX3PV/VQb0Uplw6lasrVYFDhT/UMil1wLahaBmZYsdSroYARmiSwWFu2WX/r2xfOP2/381U9f/uDiiVw82WXY3d2+350tE33x+f1hr5Rye972befkR5vg1gTMMyxrTuaKNjZ9aElJtBLktQux37ZhCNVFT9XcIRyYYyne7MLQ9iH2mzg9vJqON4stxCQeCyJz603bbs67sJHJl0mPy8PMxOw4GzbzYUJ2JMBAAnaCwZcaWYXQkDmQPTu0LCmoqhtzDbaAwMtKtggcUJB00WxCHGOMVIobgdyMFMmXlNQVCuVAy31CDy02Y45cB4TmpGpFgvRdGxDFJQRZxsXJSKhpo0QmEvW8jCkE6frW1MqigK3lFBELu5kXFwlEq8OJ89vp4yrH+PORfT/vqngSv5Wdrq1EtYg4EaDW77wFox6hA9SwK38XAaBTR/LYvJxKyBNlxRkEIldVwKk63vJaptZv1gdfX+LbN/EWxjL9GcgUHvtF+je+9b/wqyeG118dBSr8FT3uu9dfP3vrXQzorw3AijG++6RfY0u5s9Dpy7dgZV3kROuEcEU3v6ZRrSSHt6vHK17A6/BPgggHd9eiFIhFiKjqKYSlaQJpFde5w0yqF7hzHcu4MYe1X3VydVNndyixsZtbVolM1SuqGIlR4CjBYG5WBVZ1pK9Vz8i16yJFqUKPOvAE12Q4L268Ohyzi5GBBAKSEMgI5qY1Jc9P6jk4LKXkjqwrnZ6FgoQQQrU/Z7dqjVfz5k2yv23EKyktOLklNV3N3d2Qzeq8XtXqmeTmMDc1EQkciCilWdeBNph4zQ2kkzqNiAR1LI+TarFiBDX3DQTz6rHP1fGC6m6oZm4cmJnUYOpE6hXBrOI1mFf9vT5C6XVyW/e86vi+riBmtgyYxxhCbOBeVElXl3eqzvzqXtNXTsuunruuBoMygazCp6AKQwKOYoWcAgUKxMIowmzO5GpkHLZMa1ypqvtJEgut4FQ1KPQTvdDNnLGm1pOp1sac6XHmAHUjJhJmEKTO55kEEqUCB7U5KVpYmAPXx89azNY64hG0etuNCFhQp2Hrtr6eLOt/rq5ZiZ14PRdWcli9JWFMgYSYZJzncUo1T1ECZS3t0AVTsBfP435puijMZcz7aby34zQmzIDg5u76+fMXzKJmD8fDxZOLz189YAHN5objw9S1HQeUZOoWgpSSlzQt89J0JBKenXXTfiwpr7uHWskGM3EMQzcM/XY33PYFZ5B7cqbQxTwXZ+q6dpnTCVEhAFxTVep244ZKKlxVf15gpkZMFCSwwB71Naehjbmarhnxp++QsBDRGg+5Yn8iAW5aKUQn7T0alFIUHkTu3tyRMJim/WwZZ+dbcSmzksFdPENVc1EjzGNi5nlOKec2BnPc3h5CS5LCUDTGaKrj4bCoxxiaplG1UnSZF+FmmpIaLwX1/uRIlt0cxNx32Gx2NSxgHOecGjwgbdUdbmqqRBIkMEmakpbMoVJ7KjYNZ6tT1/oprBgU1VRHEJyqeHsFUuiR8kM12fNEaHOsPn71UHAzN3FzDizETgFk1XXM2VG9shxwMFEQycW0aCmlTvZMAFghZeaF0r7s85KJA4FcdJXOOpGQdGylmGnxVAs+L06ElBIFUEDs4tnl7u5mf5zHbbfdXW5EBLKf9vOURg4U2tiElgz394f9NO33x7vf/5df3n/2oy+/9x//J//Rt37hF9uOv/fjf9U3/UV/MU/lvYsXH1x98N3vfnez4yVND/eHosWdEAClYri5H5swb7tnaZ7vbm7vH+4QgAk4w/vn5+cXHTO67VbVxmlc5lmz1vyIpgk5GjzDmMmFyYwVNW/AKoGShQrZIxu7gv4VcggxuLgWdQeR15QhCcHJvRgMTKxZYcRecQgmczUQAzGizf/8f/2Dh+Pd7/7eb3/701+mH9ndj+5ffnV3cfb8/EUUka5vPPNBcZyxJW0aBlFsY2zjOM5FESOypWgukCBtE1tXFC+KYurmnOdyPKbnz9778Q9+RBZhvhmGadn2287I5kXJXITRtDmXJnSRowQe70ah8I33Pnr25BtPzl98/pPbzWbbdxjHaTqOz9+/is3QRN60TR7NdkMj3PfNEEML1tnGYzo+LGD3iM0w4NXLPO9Rztu2TUJzVoeJcAyxa8XQlJI0Jy9wE7iQd8u8jA/T0GqesqZSrWa7Vq6uts8/eDGX8DD561cPfdcHHkqhJ6DD4WHY7MBLsftiE7FKIF98Tkma0nhs2wYbHoIH0a5pW+r0mL76bMIcVTP7Ogiu3pIklfl+mlETUbUUwTt1/Dsl1mrL+M5ImtZGYG0tsLJK7TQeJgZMta4px2OHUaPVQURu5EyktSY4QWB2mmq5e1ar5mE5jwAAIABJREFU7ldM9YUbQMakRIY6VlwZY3Cr5xQRRKlFv4m78/487e7HcnG1LZrmNKnpZoiPE9MQggVpmpzzaOZE1PdnrmJFTANiiNI0bSRp06Bm5ThmEFJOIQiLHlM7LxJb32ybtnDRdNbp07OtS7ldrlOPb37r6eXVuUNfvXwNt8jNZghBzua+NZTtgMtnvDkPLqWo3h5eaYnUx23sNpdcipachyNMhbwxb5e5HPYzuJOIpsP2rNldxH6QEIJpUFWOdPGkv3q2pag3d7fXt28O4zEVPxxU3fNSPV6r8T3Bycy06HbYlORsuVAWoraJTS8Uitdwi8hWPEZqAjRCHEykOd8ejmnEJ//ux5Tnru03m23fb1++fJ2LDZumib0bjdOcswJaci6aHJkIQWIIROz7/ThNyzTNbmjbFmIiJEwlF3PEiBil67p+6Jdlmed5WRYiDw0TO2CX58N225BZF5tPPvr44eYw3Yxf/ODVPAJHFFayhrSJznUtMUQ4sAe3pEBlyJe6bms2GhERBZJqDMcShMjIncSS3V4f8MbfvNqGM2WRNsg863xMu44icwVfSYgiDU0cBu97htt+f5gOaTqmeQQJuhB45dmwUDRN93fHYTN2w66LZ28OD5xBgq7BPFlDMjfWSEiLS6OTLTPyQqHvwrQs203baOk2QzcMMS951MY3v/jhJ7LZ/Rf/1T/55L3uzcNyedaOOQMqzGebDUpJ+0OZynxc1Ja2b5zJyQ/THoSL84t2aOJG+qVbltndW4kPr4+BorlrUVvMBRyDkFDlVWdfR8mVlhsglX4NYYjpSQtT59oOggKZAC3QGQCEuYlNTqVkC6Eh4lJ8yfrRR+Hf/nufbi795c0PpJvf+/ADZ5+mPC00a3p4kC+/uHnzBuct2Jb3X3wYhfumZ9xpQRNlnIoWtLEX7sxjRAwmqnlO42bTnV9uY9/Macol6VLYYArNxIC3mPJEWw5P6KzfLWYDDX23BXzOY8bcDRJ65pYaBJo1zbkUEwqNSB6NFKJEYCiyZqsGYcTCrAo1M4CFDZSLCce2a+toQ3VGdndIDJFbKrTkpZTSN71ls2xkDIMYQX1JCbkIBQjYSTMAV7bRJqI02Wys0pLDwZRz5igiMi2zqr5+9TqlxMKhiVFCMcklV/YbBUHWoqqqEpiZ3EgdFMzJiZkYVNtM1LqtEniJH5sKgp2I3XW3p0dZ3GkYbCslZR1M0ulUqt3sOus8HT5muoJQVB1qQExaCf84NU+oCW/sJzuOx3ML66FTB60EgupqUrS2futRdtK+Pv7qidi10tPXShb/umtlJjw62PwsttbPuf5PgTDv0q/+jb8Yfv4//7/6+plUt7+iq1KuHldz/aJiUlirn/XH3nL83lk6qAQ/WsnttRuvxcq67t+51jrJrbLQmcVKUVNLysHW9DwiiiQQCeJc869oTSFwsjU3zIHK8CFPigLAHIGdoeTupsbMpz6rMEA158/XytDNDVrrMYZXAGaFedY0WqsPCq+pwTCAnZ2sAkYth0AhUCAXMtdipmZmxFTJQuZaSnYnc6odBUBOXL867R2n9wIYrcNOBpycTvyTVdX0iF47ai6frgUoqRY0gtrAsglzrTVp9Z1YN4t1FFt71irMfMwPXKks9f9M6zMQ18lq/Rvr6k1gWoihXlDchNicxCuHzteef80frPbr9UWbV59B91PZTRWwXPdZqtAXDKtzBt4Kl/zxK5w4Nub2yAQEqib81G2fCFZVRcNVZrOi6aQn5NMJHmpsDIGroYzVoXJ99sguXmMCK8cEIKb4uJTXJ2Mwsa04qlYNmhOzc9ZSkTJVNTNw3c4Bgpd6mpzuIjo9af2CK3R1+uGThVzNzvQVqzDCGjZgBGZQIBevM3swQUACEslLro9pCoUfDg/9diAhM9NcymhCCvXpUCip2wklK5j3PnaTqRvsOB6fPH2GDLZqMIll1nnKTWTNVrwmFJpDczZnHKc5LUvJSz2OSi7LshALwWuQZ2yb2DTS8NUFHkbyAg5MDK+yKDrBVevy9Prdt/j42qCRm5+GPKvRy7tbW92csFqLvcs6dj/RsPnEJzI4OxRCKITq7AJ3qJqasoh0YZwmYuIgupSMZIO5Yn33IpoLwWtS/LifTDWGsJGBG20jxtlFHYYVSDPPKaUlBRZVNWPhQIjMsZQkHEJooWAuqgoDMQ1DL7hvuz5QIIr3+/HNV6/RIQRxsBWreYGlFEJVba/5qVjlaHg0al/PWl+LFHdiOJmsn8zjx3za+N9+TqebDo8kdF9PATIjI3KE2m8TTrmh6woXYeK3ffUqna7UDliNmjRbCpKZxRo9RqQlwVF9A42d6/JGMDEKkAhuKTRkVFLOsWSDO2FMIxNvh7PhvCfiEMK4T8e7Bxis1bbtqJGnz5+JyPG4//6PP/vpw2f/6H/7+x998lQtffnyszwlzhysEQ2Nhm3YpPGOW2li24S26/osrrToMc0LSrZt56jNvYACXNB3uLq6evL0rJTU9+00jdO45FTULHDgFYmtu9bKlWFhwFblMhxMLo/y69VA0E6xPszkBC1wdzqZUNSTV9f9iVNO4jWnlckhFCBOECgIMnD/2U8+//Knrz769MWn3/r2T7/6U0Bevb6mrn969fzmi5QYbUubjOq3TURGpAb1BK4TmklYpYldaGPbiHO2VCBQLUtqOrSRUkpnm52HsCzzPM5tiLvN1kwd2bQQGTk3od30u6HrAvvnP/nJh+9/dPHi8mJ3HiCa0mY44xhKWvaHQ1qGEKKbwCI0t4GiUCsQV8CDcZmyuEgIUCN430emJkZiNvfsVpjBwkTehKhqIxtZJvXxuLgBktOUA9N0PJQ0C1MbsDhU02bTnz95irh5eXP83ve//3A/Rtl2/e7i/CrltJNNNwzFUiqzUTVEVC3ZBSUrtRxDAGVzdbVi7oukEZQ7mBnpY4H0WP0/4lKPZ9/jPJn8nZ2wrpXHH1v3zJV5tX7LTj0K1TvY69n72KKso3Va1fBYM1rhqLC/rOCV+knNvb7UGmxczQ4IZHAGVw8EVKXhSiWvaxAAtmeNIecys3gICG1IaRrnwzynpgUAkaBF3cAsQVgEdb7OzJpB3jIxDJaJGosNbbZhs+OlwApUwcYSo5pkayKLmqQCluCiU75XObz4oB02w9PnG1A5HvepPACxodB1sWvbq+aCxJs4N12WkJwNjOvra2hD3gXpY9vHPnYSr97bEYipMw/TWA7HaUmzw5vWuoGbHk5zMr+5m7quPR8GDpjL5KbTvBwPy5I8ZZqPZiRmwYnq2IuJTW3JqUDhgKlrsWLgpJpUQ4geRZjIKQPednJ+1lpxVxITggx9N549NA2XwEFgyEWnaX5Q87YZgOxERZclzWZt08UmNEwNCNVaE2RpMTdmihSobQeHMxfTMuSa54kY6t/mlIxJJiLMAhiL9X3XDsFKKU697GzSw/U87xFDzBHskRAUUstkLe4KAhRA5bULrYeH1f3RiJiJ3Qq8slSpsnGtUg2dIfnuen/VDbEPgXnTOscYGxyRqUdLAhchVihH4UBZs2bkUop6WeAFBU4Ky4U6Dl0g5mO+v709IDbnF08elmNSbSL6rhVu3EyzBIl9NNpkxFJQFMWBh+PDhrfEfh77y3bHCwVCRD4cr6/OL3/nV84+f307HbEZWjMUKyVZ5uApVy8nZ4ClUM7ZkhLItptd8VSWpW3bqydnMV5Nx3F/fwiB5nFeJq1Jhe6Ul6SkEoWFoQCRhGBOp9uWwDWNAasFcD3qSWFwVOM6AlxCqAFCWgygpmkBy2m2VDD77/w7v/5rf/ubJPnNeH31bPjgmy9+8uVXt7eHZQpzSdevvRQEQQgwjQ93x9gInHbbsxBSSprySAht08BlTlaL5JzzMs/dEBjUxbAklGWxJYshWpDSsNBUlof5rkw8LsumfXr2/ubZ5QfPnz5vRPbj/tXNF4fpYT/vdSwxtDGGxmhJaZ7SshQ2kNYBeu2YyKp5nZATmxFRFYpUkj87sws7YERiIsTqRmAoOcwLkN3ICpslZYeqkxEUrk6nxsqKSxBNWmNY4JYpu2tJkChQn9IcPMBczQg4jEdhDiE0MTYhxl7Sks1gblp0SYupFzN2EmJiQYCuHZWvMphTunmddNApGvAE+6D2V4/j3RMH6tS4V506n3hbtaA4eQXVu7NmKdGp+vP1POIa1W61nqNTs1Zp5KdK/u2J9VjYn8Jp6HTm+TqifnyIE+3/hLid4LhHkOwtUPezrtMH4CuGhcd39k478Fd3/RwY6//LANZfz/XnwMI1HO0d1pyvTPXTTIxDRbv8pFCr8VhYB4UATqGtdUnRX3hGXsWutasHqk6vKtLMhAAiZlPLicIQtGI8RqhOoQYUr/2in1p50jUio/JmTJ2qdjsXdSKu42kng5e1IDQD1CFv7b2sepc+DjxBVuN0XGsIIwsqvLQWcCtOUW/B9dNQ1aZpABiZVVeqql0sXj32LLtCnRGI3b2UqvIzAsBv7X3sJJdbMRWcJDt1YMKrM9NbWhxoaNqUkmZVc4hU4yxjkpUOtrqpGKF2d05OFZAhO8k8K3LhxFU/z49wsrubKVn1evScc4X91m2sYoJ+aq8eZ7nvcC8dXrWNKyp3WnUs7qsgptTUIpCekKvT79oqmjl1elzrbnZfrQWV10OnjgKwYluVIaVaTXQqy46YSa2wg+kRIopETsxupq78KOBrBAGV67M+P8hUAXI7oSruTgDbytl2Xy38hcGedUGppwBY2MTAtcuHyQp6ramODGZZZ+bsVlMBHQ6tfFwRrHFthso+Y6AKRr1yq4KEyCYOUhOnyAiMIMy+zIkjE8PUkDFOE0dpusaKNdzoxtu2sQQsyReQI3YNEaWSPdvDzWE+Lmi4aTYoDIcrsRHMSyrH+2PuIxjFUKw4haaN0oi7Tcdlv38olpo+uHdEtCSV6MyBQApqusFZmm3z7Pn7y/3N8WFRFARCwbJMJx08VuIBTq6V60G8HnYrOaEmB9a1esp089O9Yyh1Nf65vUjLallc//rMLLzuKhVKiEQayIqpFhKISNu0WmxZJi2GAmObDnNekqeKp4liDQKG+zynnPJuu0XoDvPtbnfOtFczgbMVSznPS57KNB7huL0+pKUAkakzRVoAUAzRzEHkCgCxaXbnZzEkgmy3522/+fwnr//Z//zPwbAMFhbAkUsNhFVvmlgT6MydpH6AmYkr9OHkENRJAjkRV1kB4CfzVlSAFbS6t3tlVAHGYEe1GUSNrzRnXq16qpiQCMHV1dVYiV0iMwuLCAhqNTmIjLwKDAXmZpYAB0vTivCaRRECF0HJxWod5Si+sHCMMbaBO6EIEhRflrksy7LMRmRwlGIHOwLcNX0cwhZD0zabb2xfv3wzj4ua2pT3CrQNE8nA44P9p//Zf/6P//G/92u//jd+82/+3VdffImpfXL+4tP3PnnRPdt9PPzRD/5F32zOh4ttf3aYZgqqJMPAoUniIPYYZXvWJ11CE8umXF7unj17dnF19vBwt91uTCH+YIlKcoquVtJsplq3tdOglZhFtY5SKpLFxFV8ZWQE9+LOqOW2wx1VRFzZoCAoWWXm1n05Q6EODzUnpUIIblAPFDzTfl7+4Pf/MHS/+Wu/9e1PP/6Nu/H65fVPKT79lb//W3ev5/3d0XwOUY+TgTy24vBcln7ohi2llM1VkXJRok1ohAnIxZLtzs8e/OZieznE5sc//P7z58/yw4Pl6f52/+y9Z1dXT5smhkjH8SHl4zIvMaANXddsBfnly/vL3VNxCsyG3IVIVWyvi6CM+9dW2ouznZK6lSFK38W2iQ0TkC43l6++ukWRduiSTyHQ0+eXJfch8pSTwSDVrNIBMYOreGYUYsPt6+PQcSZbxunybPvHf/SHadm3US+vLl1CiDId049++pPPv7oe55zGvB124+HwnT/97t01vvHRmZer5+9t2l4oSGIUshAKi5khF1VCbFs2JyupZDsejw8LJvESa0o84KeJzWNtXeGlU83thurFWcdNb1l5fuoV3oW0zM2JTtFjtlZpjwMkc29YzNfMUHuLRq8wlpOv9dDJ/crhMDwWh0QEXfFp4kqHoeq2TaUaOwDKRDCUOnmsb213ud3Pd6M+FORh22lJx+NhP80p11m8BMF8WEzhzsVL3X5KycfjFNHG0INby/PiSxOadsDQ88VlLLY83CEnFJQ0ZydM0zQc236Q0DBz4StlpsunZx99/H7btIfxPs3Hw/GNWnm4yzmNQ3fWtWedCwHZLc8z0kisxHAORX3Jky9FeGJmJhNoFQTPix7HcRoBhkR0CU1GnEEMd+QcNueddPwwHr+6OSxpYpFSfJpRik8HjzEGCRBnRnAx87LkeSkl63woNXatHgEpJaMUCbwZhEPOOedirJvzgQw5ackI4L7tL/u2adg8qurxcLgvD/v93i0si6Ylz1N52EMVmz7FWEW0CqzKY1X80rff5xACd8IcYlBVZWliiJcdwPOU3ImJrbhZddJoQxAWcniI3jQIhEASPN5dH26+Orz5/IEdm7hdBmZqrSCB1Ymc7WQFCi5R2Ndcbn9sKmgFY62WxXSqEuuihzvUQLh5+fDkxZaMrdjl1QUHiYH6HT+5ijevMsz6vu267vxJ6zwfxr1rS9JyMFCGQpmhbtVIgoyFKcnD/eH6cPNbv/1v3ezvfLnvu+1227YCXcYsRdrhYnsmZ6PRHCRrxmGZl9s36b552m+6J+9Zh7aJfegCiTU4o/4//A/+/f/6v/3v+h/85JB4NwzXN+OoeToe8lIs+26I1ICkkSDTNKecVVGQ1bmJshnas74LzK1aa8QphJCEp5zVnZHNi2su6oWZzZyrWQXB2R3u2WBmpjBefVhqRvkq1ChkUHNhhNiQSk5aUmr7ttvGaTyY5YsX7eXH4Xd/71eef9Le3r/eJIpD7077h/zZT+bjCCe7uU27zdPLs8haeuEvvrjuhnj15OLps/dU8xdfvur7kjNJjFZoOYzLfrGFcs6ecNgsISA2tInNEK6WzswQm00TOyMd/Ua6wc3R6H65K0bLq/HPfvxHH3/zm9uzDQY4iCSGIoxQlddQwgwdjRleHufdXg1BUad8SghcHRBcMxwQqtHhZuZFo0uUyG4pl2SZmAksGtKUPbtlBYlrDQ1c8Z2aR2rmgUAkRmoMZwdpdVtouAnCINZieco559DQZnPWtQ3L6lEaQpAQUHLWkpZlmdJanhkg3DXRnZO75uJsxIFq5eXMxPO41KrCT9MQIz2hNqfu6rThn0aZdb687vq1twYAFwBmvrpS1AqiHkrrfLKKa0Bf41m8vWg9UiAnUteJKVYHpOvvCMv6Dysy5vCKNtQXeQIa9Gc9xV8o79/9Pr/TyX4dUfo6rPaXvv7yNKufc/3/ANb/M5e7qyqdrne/f/pinRADxMzVn6uUgtOCeOwYHwugx++QnFhXqMO/upi9QmA44WQsUpsjIqIK5ZqKtGJeXIXYCVIH9Ybqok1GICOjwIGYTI1q8qu7qT9azEMgTF6txkt9WevN9Hg3WvWdqs5Plf5m8GrMDq8MBkaNXViJTJUn48Z1SAlbo7dKLsR0OoPJ/Wvkxkfke9XnoBKReHWXXyftdZ/hNQdXwWCqGTf1IZjdV63l+mEzC1c3rlLtHN/CT/XzZHJSrxbBRFihG3JaY7rtxARi5hOyg0deXi0wIpirm6bR+sG0FU9grJw293c4Mv5I73QnflxXteCltRMWqTyaGm6+goP0uIVVsFyxYl+PxkhVm24nnoi5V+2302pEf9LcWTVlr1Y+xGASohjgJzFGtVxbXxWqLVglAJ2GNKtret2sNSudeFPrn4NUtVhluhKqKwEHAmBGVifaDCFCXNOg6pqvWDDcK8OdIRVvVHKH0vquqNIbS1FfjaDqa63+JNVkjcA1vY9ImMmNASEIOdeQBIG6FXeCdNw2HROLc4yyGzZ0RULycH2YaTESBoJFTeqzkUAXz9A28Pn2spE2ErK6FZA7GXlxKy5R2EI2tcLctcwousxTWnJyWNs2xCvjRJ2yuVmZ5qxO94djdj+/uHg1HI/75STPdM9G0ryzRdE7p8zj16sOjmj9gzlOzD0/wapeWT5WgcrT0YzHZVmPr7rrMQi0qlVrNioxByYNYBdijrFpQ7PwUt3PK60vT0nzSrvTlYsFZ8BgauwURaZ0uL1+MzQdbW2ajihFU9Elk3nk0ErnwM2b25SRZkvJUvHxCJA2Ma/pPww06DddkABgyakfNn23Xaby3e/8EIxSspwSIJogzqQoaualsAihOqkZiGE1eLEuVai7kFXA6WsH+6nwcV+dMP1x+zqpgJlIUR136gCCTkA2CwkI6mZqpoaAVX7tcPiqzXTQaUmjOEQrCZSEhYSITIsRQoxNE9U050WLOpA1RwohCIXqpc1Fy3FeKkDhlpsY2TlEiEguaZomVwoc2q7tt01/bABT90RABjiZo21ba9KffO/l7n/4px9++OEvfvoJ54an9hsvPnq6eypKZ83uyeZpu43n/U0nLYzSXJw8Rt5toQmH/cGii8SLy13bdSEEZiwp31zf3dy8mY7LPE3zVEpGziglQ60sXqrX0KmO5IpkVQuxlYpjlV9KzitUsf5l1kEiE1cqAwFQqvYb5CCjSmyo90mVeJEXkJBpMSUmOEPx8tWb7/7pD5sh/q1f/+0/++Ef397sy0LTYX7+9Ck5nEoITHRQeNtHcywpD0Ns+24cx3lZSnIzzSVLEWMzLUXnzfbZMoWz7SYSv/z8s1/+9NMjzEYKHM82F0Pb5Zwuzs5DpIe97/d3uuTpuPRtw1Y+/saHRP7wcD/0Z5tezs82Oet4OKRpz57TOJNPpYPLht3aTrZDbGOITAI8ubjcdn0qhVnYabPtzppuno63d3dzWkLbRhL1Yy6W1ecJ06hpyshgCsf7LLBthy6GoQsPt1/GFn3XnV9suGmP0/wwzi/f3C9LYZYlLYxxnojQ7nb47KcPjhyay6tnUQJiDAbKap15AZwJqEnEIhwUyGmZlwwV4uhGp7rf8fW7sN6KX9v5Tj3C1xhYP+OiWsCcarGvPfBp9CN8mnjzyvZ6+8B1L3Ui0soqf4uUoW5+p9Glk0N9tYM2MqsemdW60k8jdXeuYQVQ5MN07ND2u07acH+4uduPBjQBBExTtmLjMZWSAHJfiKrzpmsuZiLeAKpp0qJ9b6rZQN0mbJY4jTklELkLwIixiTHEEGJgFto/HDbbYeg2bdvnlG5vrkPgftiw6Hg83t55Wh6i5JyvpcHuTJpOIUslZbT9xrKradbiqkQemdoQRJgCNRKoGYZzcyNDFRQ4AU0jUcKLF0+7bsNM9w/T7c3DOOYmtm0b8xxKtjwSN04BFIgUxMxOKKZzzkuZ9mgDggg3BEAVKE6Fl7moMLnnJadUohABc1lyMQF58FBsKUNxS0nH4zyNyZQJPB7Tfq/HAzBDGsim77rWTOd5yik7wAIGlhnMgYXMfDzkcZpyVlDs2p5ZFqiq5axES86ZiEIIITBIc84htmqLa9kO59tw9id/9p1Xn93lGT03wYOB1M2KworCmeGBiRgGJlqHw4/CdnaytUB0OHG9HZSZKPCJs+8AwNBRoFUuzX3XTcsxOQ+7zdXT8/31m0W96eXq+UWz9XGZldB2rWBYJqY4eSkQJnJxYUHSbGqai0fH6G3X1mEPmFlYLaVpZsVF3+12TYPCARsx0WU6PsxjXgS+2XlsS+BkAIKZm5fb8sUHTy///t/529Dwz/6XPzkuY9e0FQs0ZhdVISO0rbRdIx3nnOd5Jra2j7u+74Ic7u7SOLUh7rbnaUPb7cW8W27e3N7f7lEgMXBDRYvpasLr7uBqrFH9lwpcqu1ibVGwTp2cDMJgsGWquR0wwNlJS0mp5PYJfvPvfPg7v/fLHm6+fPMQGn/2fDvl+bvf+f48wlL/1ZfTkyfxbLsbtudMvBwndj8ebor7ZqNtp1lL1uJMEkIIpERmeV4KZiDXGTRUVXMJTQNjzlZmX/bL7GUpMz9xl6brYvditzxM1+PD8TB1zOpLRmNuzohtFzpBsuV+Xg5J5xLA3Aab9UTdqwl7tjZmTqhFi+CkVjMGcXVKd4NaSRTaCIcldTaJgUXIXUtSJTcEITJUt1JfbWzdzZFR6UxM7GJe5RcM4SCFyfj/YO/Nem3JkvOwLyLWymHvfeY7dfVIdjfZzVY3B5GgRxAyIMOGAQEG/GLAsAE/WJD/ht/07h/gRxsw4BcblmTaEiETMgRIpNgUm2I3m91dVbfqDmfYU2autSLCDytz31NVFNUUDRiGmbg4OPfsPPvkzlxDxBdffJ8LiUsBM0QgUaofiasZE+12+3EY3YzEcs4giAg7adaah5uauxtVEanZfpsB4QAfqJY7fImVvVqQzUx8epRhzVHd0pjncKssljn1n42jKrT3LhBkBy9sLsIiIP+nY1j1lxZiwyMC8SkRAxikj5os6kVWTGBh0mBJf/6U4zNQkp/+7omYcgKw3P+UX3h8fBYRO+Ehp5foEUXjX+P4SwDrL3qc7n4FsCo49amncsKnlv/5SWx+zsBh78bEzLGahcTNLFQKgM42AkvqiMotgTBV6kKUxYqOK1nAah8vZKGBsWDm6oCWBjsnOEWOYMx0MINrpdCwm7m68EwhgJMbk1eNdHObezJOWW39EARWXcI+p7plEhMZE5ljbvcVZlKGk5qpg8oMUY9jksAceAk3ly6amjIKydJCU6UOKs7ExCSEE/HBycxpMb4gFnd3VZ+bj7hWvxb6pKHmuEv0a4+2p5qHQ2heymqnEBMJwF7p/yQzvESoyluLt8Qj0JoqBm9qPjMhFhylKr5jns7LzysSSWQzVlU/fl2R5iWP3I1DEBEzK6VUoKE2A9a0dh6HVn97LlDXspybLSuUE+BmZk4KwMA8Q1eoYj421/BIuPo4zXH7Uj6Gu5sWJdT9IhXxAAAgAElEQVQlnomZGcVVyUD1M1ol6OWS577M2udGBJCIzNL18Fl5Xw1k7/q3DQqTKPPQmzkSlUlES79cHRkM6Nxh9miqVriYZsoRCfOMdLrX3bjClCQM4oqwKdWrQRO7NE1eClr0q369WkNqJCZtbGNsSHH0AUW4BAERBR0zClb9eiiTMSKas/4MSuKSTV2dqmUls5AISzHzkrWQFgYjJ87JUsklTwYPIuo+FRVlh7ki8FDG+PGr2zKGrl+1fQRDF+qTFasIM07jbMY2aAacHm1LqCbxTA5o3Xr9lDmdQKq5qPSOh7Usc7UkNN9ImwHkBUIF1OBWe2phpOolGwooVsM9smIEEmGdFvi1KsJUjb8gOee3b96+/yc/JnhgCsRWik2jp1WErLs+ciTIcTekTIf9dDyUYjgOIJQUj0LR3UITFEWCVJw05RJCA/BhGD96+YAGgXhmijPFGADOhCnlXLTy+lTV2CBwB1UMq8LU5s70TqrQaJF6rRjgQv+uy+2MAdYBdlojZs6iKeo0caLaDe1qrlZfVzVyJXYiwfwsucqy+7u03CvUK8JwS1qyOwfquzVcmD1zJvKiKsHBWsynCWpuptkKQGAJEEEMgeGlaUII7fFwPIyHCTDWjW+6iyZuBM7ioUWrjIMebz++9eDrNX704Y9evn/39Z/52pfe+9p75198fvFsE1aNxU7i86vntMKm+biVRhDISF2JeL1eaaTb14cylbPVRdd3Tdu0bTsMx1evX43HcbvdXV6ewzANY0luBapmxWBkVuVRzWrSLVQ1/1QXX2yDyIkaQ3X/qe3M1dApkPhpBBuqI+68qqlzYAKxVaUkgxlR3QvVnbWUJjTk9qM/ef9u//Y7f/VvXpzfnJ9fKU0/+MGffP2rP2OaQkDTSGw4qzVdZ6Apt03TcohZJSkqcprTxBNCJ00jIayn4eglW84IzDS8ePbk3l3bvmu7tm1h7Oqr1SY2QRjjcT8cd17IVZz8O7/47TcfvZzGcRwOm9X5s2c397cP2/tbTcc2IJfBklhuPUZ2RJE2UheJCQF+1q1ubp4mU/XSNs3Z+dop5zKMJWW38/WqiCnuimrJGIc8HDWNqsVJRDxD8fz6+vmza9ikGes1Vj33fZB+9fEHb3MhkKiaLlam7nAjcsaE7XbYbuP51Xm3itL0IbuZO0t2TMYgMoeZB3YAJZdSFCQsQU0I9m4lWjqnP3nwZ+Ctz5zxSSvxGRpeCkb+CVozAMzhhM8AG5Zlc3m5luoqeaOWZ3hpfgZT7e+aF0yqw5EMxm6wou5cIVmHz0sEgZhcXH0Cabc+32xWyjq+GVJC14bNpnHHcMwll2kyM+MqR9TUgCWSRygXg5qmVEjK2BHL0cEh0mrdnp1TEwgeyKII95vY9RIbZy7mIny2fxg+mN6sNl1suBQwo+3aftUQdcLjfpe222F6ANboV2100UKlwICppFxY1ecKImky06l0TeQABG+bEJpAglKmcUpZwcJtt+r71fpiU5LuhzROmbhrY+vGu/uiSlZ42LuGJKIhUgjigZnZMqMIa2iDdW3TxAZOOaVpKpNqMD8eLMZCRCVpTqnvCPAhTyWDgQTVpF/Ml0l9HOx4TIe99n0n1KiY0BileIf1Zn19dd11fUrJdeslmVsQDkFevdy2fexXLeCHw36/H1TRNAYLzDaOqRQjGlJKqlnNYiQWMoOarVYRaiLett2qObt/vX2495ZCoHYacs5w5DwVeHFmYyYBNDAgQK6BDoxm7w8CmSs5k1enPa4OLFWh3LjS7XkOLstktKG+W8cgr293isPlZXP15Ow45JzgRBlp3I3Z95uz64vNE8/tcLijLiJVEqISmTEdx33KpkDXi3WQoG0rfZGsxzEV9TQNGgpyTmTU69gFXIqEwN1qnYmfPbm6vr4Kfb/VfHh449O2oU3Xjqby4snP/uov/BXWxpL/znd/+HY3ilJoyYSz6aSlmBXyTAXwdtU2fehj10r0XHb7YxlGT9nBdsxF14asZmdnm6vNtViYcro73OnR3JUYIRBoFkWdpSEYsEpek3k94apsAnIWDcFjdk4JzCG0EVzAh6Om9hLf+IX2V/+dz/+bv/Gl7735rbvdh89fvLday/F+evP69vLqyxfrTnzo4vn6/FLhx+Mhp1JMFCFnv7172B132fI4HlhCaCQ2gQtxIARwIyYaI11etn3fsjsXmLkebHrIJWXNNE1pmrI0tGn767OL/jxGl/t4Z0qlTIcHH6YyaYlNo8XycRwOUzkUmkDKZBTQ+tJLpwSGmi0OeT6D/VADmTCLVtsvI5iAdbJCBQCKY9HycycYAfBsNZX0uda4dPjX1VqJDV6ZsOweAIdOnrQAoCqJa9TFToTTMQ2HkZn6db85X33445fIAINEXUGB2q5l5yy51hsM5tVwh04yGhWT1HdlCBDByfnRx51PXXLx2fLoFCfrjGz5cqbP6SufghAAwKzksPC65nwGn96kPpkTzuEkL8QO+uSpn9rfHpdqlp3pT0XI3nm4f+pwB8HYyImIbMYlH1/bv5S99anjMY72+Ou/9vGXANb/A8enmHV1iJ0UuE5FNiyA1KxttBzMUs+vCu4gBAmVbqOqph5CqEaYlbPjvtTvlzFZE+kKdgMOktr1Rm65JvoGhwuBhGt2VcNxcocRO0zVFZorCQpQhxmJmM1JGVc1LCfXWWIdXJzc+F0GW5lSXBnJ2UFOPPMIEBggEphrqaVLBkOs6JSLF3hxmuGURVOKiGewwmdUmwFAWIgrWoFFJZwIC4BVMY2KR/mMhBOkEtBmva4ZaSeWQEQz8QFUSqlGDHNib26YXRVpoS7Vy3N2YYJg1gI+Qd4zFASnKp2z0MVq2YKDZ5RS3B0CCkzCBpXav7UwXAg+i2iBZ3xzXhnfodfLdwBAQhwqYGE1lWZ55HbhiypXDZ7n1bRKTlbobuEhuENhDMAFcLd62dW9iIjgswGYw80KmE7yU0vmrnXLsVqlcDi5M8hhpNXRb2ZoLXgTFu2keXxxRWl9bgslEGOWYXOYerMWKyeqmUMdXolDNm+jRsRWyGYSRcULiITcDOyL4P6c41iFrnTZmKyCtPP25JXeYoaGmijNNF+SADM/KI0pD6kNbROjZYuIauwOCTGyOlOUbkrJC2DMJHnMgZq+qo0X02ILwkHMwtK4cU5uVM22UUwPw8EcXdeCgxRLmUpxTYpy8NSPh7eNnMemjW2DALhXHfbi0DJjv/NgmZGTGZuaH9uSmzEzmOa77zYjk+8WtTqMP7HvEWpxjACFw+ueb4iNAGRmjgpNu7lLEMBVS06plIJ5dJCqgkLXtAYZjqOzc9XEg8IhTE0T4D4c9vd3txeXXUkjXEndckHRIKGNjSCCJE9cUhqHPI3Zqa09zuolBjGhpmm8lGkcq315JXCPUzoO43HnTUDkimgY3FRLhXDrzDZTny2KvdYdjYxtKdgtwCvcYaiCC49ubx1a9O6u0ePvlocxk4PMiZyqwwUAuNrcawygKnuzBaEQwgJky1xMOO01VvUfrUr0l5xLIa+Pw9XJQmRnInEjLarJis9m9kwiQQKBYQySXLKIrdeBeeWuKY3F0/10++z6aYgxpdJ1fdv2ScvGzq6en8VArz/6ETj+8z/8o+dPbn71F37p2bNnvTd5l+Bjt+HrzVWi1IS2i/3ZakMeDj6NWYmla84u1zkP5spZ7f7hvm3aaRqnId9vd6pYrQqM0uQ5uynMyBxkPpOKa8wYKpvVKj64BMILe5+YiSmQ1K3P3Kz2dzJqX7Kzm1uZga9lH5nVW6t/oXu1CVImMrKStFk1wnLcD7vd+M9+57vtRj734gtv7l/d3u7iN+LmbFWsGDS2Qd1JQohR3Yp6KlnRMXMep1JKTpOJruJq1XVNt3r18gMttn3Ynq3C9eXN9eW57gejVoSP+yMJHfaHzUW/Wq1jlCCy393dXN88eXLVdXJ11eXhAGsCk5V8tb4k9eN+l8dt28iuKJuSZtNEJJXuSFChwIAxnj95NkzT2/2bvu+7Nt7vt4fhmK1IF0PTUk7EQhycvDbNkrllRdFNF0H5K1/40s98+UmeDjGiX6HteLVuz66v//BHH93f59dvjllTjGRaZWnJzbQAEdOI8ZismIiQS5Dcdk4xFhI/kKqVMlkauCnFNauq2sxPeqe2wKB5E38co9V/7xKB0+45V1A+EU+fsOdPRNsL3L/UGp2FS67Eq1Nq8om/cPrBotVw+psg+FzHg53Om5eKuq8Z14tmJpDA8+lyncGBu1VzfnEeAg/jMaUighDCer3Jqa6cbQxeSiHWEDSESiwWaFTzNI7jeDSbmrYMjZVSKDAhxiCX5+vSB7cASIhhtQpNC8dYypRzgbUPd+PL43GziRdX681ZrLumGver1dWTnmhI08HXw9lZ0/c9s07JpwQwvFR6rQCmJeWiwXjdBXUqRVPKzNxobnphQbfa9BLapl+v1+v1evtwezgc97sxj+aFPXNOdtinwA2DygRMhbgIcwiswUXEndyCOAcq5NFUTD1NmEY12DQaGBwzOVQBRkespmMBHCEgQdOIrj0ro5se0+TjgDYGkkBAEO/aQIht0zN1rmzFrcCKmVlRIOB2e7i66CO3LMijTQPUoVqIJgD7w2CKnDUGBjw01DRNCKLqLGj70HBsqTkeBj/sHh6GjhGxEsR9SrN0JRsCocrvVt78rGzxrqJRh5aTQ6lqjAqDCLOX8YmNCoCsRr3H3Xj1ZH1xdd30lgsoWDFtWu/O41r6u7cPtw/3CVPT4fKyjX2bjEPbPXnyYkvbPEylHEMMTd9YSpMaBKtVePHsBigXF73TMZdjyiWIhYBVj80qnK+aqyDR8znRZr2y9dk0HS8vLziGN4ftw/3w4Y+34xGX6yc37bVk+tyTL66b/tvf/DpTfPHsvf/uf/jNIF69EIqjVOJOykfLQdCdtY00UcSmPBwOeT+0zg3Ypvz29ja1w1hUJJ6tz9uzllx0sCY1vEJKqeRUihG7y9LwxUvTidcwkEHONQQFxRI4N+RNcCEONVFyHszt7Aw/963Nv/UbX/vWrzxpzra4e1ifkdr9bodpnNqmTZPGEF88eRa4Yw9TOR72e+QApb7bFB9v77fFvO0AwuYs9H0XY1sK+lU3Hj2pA9pv+rOLtUAP++NR91Z8+2bY3yNPqF20iAy2xImfcB/D+XotatMxb3fbMVlWOEKMhYE8JZsKFDBods1pHdaVauZE4LnuT1arsHXNM1ej2u2iVkyrYBaLqdGijEIVQLViptWjhr34nDFVOrnCxedEgUGFyAlsrDOSCIMnyww3pcChCSCLHGE0TmNKCQwm1tXqxHuYgzBCEImhYWIt6uZelaSrPDnBF/NJJp07+moi4wSYsz1aqAGceoNORd53ITXmlO3df1Fz0nm6VaLDIpN9eot/lXD3wmAAMzv74/N9MclG3Y9m4tXc14PqDvZ46/v0O/9ZR0VvTxBHHQUnGOtThZ/THfmzf/jZ3/rzHn8JYP1Fj09ptzNzfSonVAtL9IMlH5wRLYLMB8+dTaf3FA5BKtCpbiGEJZBacNqag1ZJQakYGJdSimYiFg5MLCxqWt1g1ZydQFVEiU216kOxA+4MKlMp2bUoOag6KRiIK0ke7BQgIGAGGAgOQXCqTcpzvD+Hd+aK4g6AGSQs1TbOmUGuSjA19yoOXhuMtWilv9YdgjnUjtuqaA6d2VHLakBUG0aq5MkSMtYCpswUTqq9h3VTJhKhYObFzU0B8oAqmlf7xwAzrcbXVeunGiqauUHcnJQQCDOHtIa8UvEldzICW/1FoMopwUyEiNge4dVM4mJa4ORBYmgFUrsbQTxrNzmcnQ0z62oxQcKM180aOpVKA9RbIkRCVYoQNak99WrO1YQZ5QewoFkzI6y+7r7E7AbkGlNbffjVzWsedZidwo1gZQILlpSwNk2G2MHcrajpOyrwsnrX6yXithVgLrb4TBQ2VyUhMJiCQ4lg6iCPMYDZzUpRM+cgZq60WA9WgLNCt07mmcmIqIi62GzNUZE34sDqfirSz5/LyE6SXebOdRsgh+sMYlldvLumacA+5eFw2DaNEJMpHbaHNE592z65uYkxxhBSmax4kGhGOpXdw75Zh2yDlmwl5Tx2MbrE0ceiyTJ200gRTehCiMQEISY2La5VIZMqzyC27M7mQQ1qnlMhT6whHR82XUAUiYQGyBDmGFqh9pjHeSBXGhnZSQoGqEKV77TEaWbCERc4qFipU+1PLcqckkNmmRFLn3EcAMRCReHwYrUKDIACpBJXzJgodr0VzVOCg4KLgFwARxAJAWLZgAQQJIS2bZoYidE28X6bKqJLajAnwcKCotBEDFqKa7HQhHl6KFi44aaJIU84HI6rNdpQrcA85aLmxFwMTfUHUORiZTRmiLCEQA7V4oUqrdV9RpTmyVXDKT5xzuba3SKKN6NUC1pb4WJbbve7qf0Obq7z25Y42YjgLMHZrMzyqCISORZk86o7Cn/0DigwFO0sRJEgktjMSslZ8zgORBwb1uzkTgIibkiyVLl9YogXzu5KpgFmmqGlT0FkvembFIuV88vz977yeXd/8/pNiNSseDok8/yFr7334sWz3/vH+uLm5gfv//D5925+/Zd//ZwvShnScIxhFYP01DiKGHWxvTq/aKVvdbrbbnPR6+vLzXuXx4fx9avbj1+/ffXxHbM1sSETVXRdODu7zGNJo6rCDEFCAFIu8LqEzMWWGYLAEizWqW1GLsREDJFQ9RNTLidQQ8AKZ6p6J46TdKvBtTrSLehG7VY0Z2EQ5SmbgZ1hDNj/8ff+4V//j37jc8+/uNvvovA0HYgKkTL7atWZ+5RLCNS3/WE/TKms+tgGGgTHYz4OKtAY4R03EobRAmG7e2i4e/bivTZwIC8E1Xx7d+f8ZPfwQGzrzZPV6uJs1R3O19dXV8+fPb3uVx+9+m4TwmZ1FkKYxuNlc3G2ap9cXhy2b2Kk7UNRuJdCWhxakmtulEXgxEjTcLnq16vm7Ta3sY2I+4fjbrdjoqZtWYLZGALHKG2kvmctZTqqG1LJ3Sq8HvD0ydXnX1wPxx83DbqW2uglj+N4+Pjl67dbbI8IEcLuCobEwG3biLiBCcaOJlArkoqQlzaIRC4uw1hSKWnSNAzBrWTNRUoB8mg+1TrIUqXmuXf8HVZstSiznIBThPbum8WqBUtJ7GQk/Ygp/w69cncGl6IKqWXzetbpnE8cvlT36gilum1XOSJeTMzqmbyY3ywBD1XzEHNWEMAKAktp29g2mNK4294fR7QdRDgEVrXAUUgYdBwOZumRfJeppwgbxuNuuxNWJhmPOk5GAW3rQbq2lbYNpnD3GGm1lhCQM4+DTuN0/3bImTTJ69f5bnv/9a/drFabzWa13e5z9hDC2fkmhNU4HNvO+1UzpkMuZoamkXFSFgkhkMCM1YaUrDwMfSssPiXjCGrQUt+07Wq1CaFhamLsg3SNtBMXWJrGNBzKtIMXODlFCiHCUBwoyGpga0OJoRWOxMIsh/0xBicUM9OsbqDAFCi2sYkxpeQoN5c3TRv2h737SABHAjsSzi4vy30Z9sWdc7JSqjSehNAEYbcI5+mYjzrkPB2HNE255Dw/fwF7aEPPgRhH98kcqpZLKdnSAChKKlMAC1YsxNI0wY3VAoE3mwsM4c2Ht5Knwx5PVtdUOkGceCttjEGGiHFM1UwRZualmnQY6bwVzeVT0CMufi1kilBOUH/EVVzG7H63D/zs+vqcuyQBm/NVv44P94ePX725uLg8jPvDYE0LERQdd4eH8QDq4udvPgfB/du3pVjubHXRa6HpCCWEjT19vgYfVhveDX4sAJm0aBibK7l6tn7ybHMjKQ0P0bxvmtj1250503YYXr+5e/3m4Scv9ynJV9o+Z335h3/4y3/11+H6pH/681/48jd+/q/87f/2N88u0ctUDOaosrws6Bq0TbNq+jyl++29GAVw0/Q2puOQdPJiAFmIjRZ9/ebt61d3Tduvuv7y6lqCjOPx5Uc/KaMjLLjVUvWrANZMTAFVV6lqaozCOcNBFIKqpuMRskfM3OHnf/HFv/HXfv7ZF5rXDz8cyv2LLz7fboePXn9YvG/75g//xftt8/zJ06u3t+PDfiuR3C1ILOpnm6v9cDvs9JiO6zWmjKZpVptWOKTkbRdii2nIIDSdrNZ9Oh4P+4NO7on2d5juAUXg6OS+J+paIfDEbn5xeR4Kf7R9Ne0tFfSbNjYriS05sk972rqbkMTYRJYyzaW5Gu24OlS9OIkEDtXq2aBURVcNUEAhgiBMkQMFdTUwQcTITC2XIIGdZ5VbqakFZphLmGtdtRABZAxisVqbA2q/aOV8MJyQpyIuwpFJLeluu9dSVmfrcRyp9rxUmQoQhyAGB+WpmLtEQZnTXqtpX1kkfbAQs+YpNDPpZ7Tq8cRx1MTYqhY6z4RcnHaEWoQ/hXxzXUSIyOePtCRpn9k96LQR+Fz+cDgzw2E0A9FeczvzWW31UfQ5U0Bqu+fsOnJCq+bI8XTJ+CR3+dSiccIuKjdGKkkCMw/is0SqxySezx60BMB/QQbWvCufOEEn/KXm3fXd6/c/7Ts+Am5++t/6f/043dB6PL71p08U4+ye9q6t5hNcuvmlT73t45/TjKYwEVXsqnZ+pVRQt5tFH/bxOzx6z3dZEQcEiRyIIcXKogRfSS4zpcKZtKnuGVr7KGKsqnbipmbVgl1N3TN5qkQbSJAYIwfp+y6XnPKUSlJzIohQbGOMYkDSBKbQBREurqpavDATBwkSp+MUYyuhSgBoKTlbYUbbtBJZTXNJVqCjeyaozREbA1I758DCEkRiCKFKU/E8Hs1TyiklSwkkQaTGg8wsQsfxwMKBBSAv0FS8wJUCCVMQDxVyUyocqWs7EVEt0zSmNDaxWZ5VZbLCCByImygCZoEQNzJNKWsikeqyqm5uRVbi7EzsTjDTXNUOJUisxcBSiuaMpPVjEhMF4iAs1LSNeilWzHXpguMTVud1wAhVsljWXLT6cjtDOBMUZmp2gslYgtQB/IgS+NmBihlyFVSQkZiUrSBXhhzN6mZciWEGwlyHcsCgaaa/ChOLMIOMid0dtFyNWpU5wqMVG07J7dOLFoOYDGAGs7iZqlWEl4WrybFXwi4LM/tkPmh1gkEB1OFg5hgjkZdihcs8V2bLwjqvUDtQwwxjuTsbmAQIRMGNrEARQQ0hAgEmTsIxyPTxIG28XF3cfOHJ9ZPLf/R3/tF733qRc3776q0p0M3JUec9RnFnmOSU1XJoPbaeOX/zqz/7lZ97sTvuXr9+sz+Mb18d9jmB8a3vfHO9Wd/fP/zwJ39CMIV2Ua4uL2Lk7e7uxfPrXMb9Pu2OEwd845vP+q7bPuymYUhD0ol+9stfu7p6+uaj7Z98/4Mf/fCtTMyTTAdQYfHgZgZ1ZPBituCQSnZzcncmD9IQuxvMVYupzrgPZlyyUtaWjh95V6khIYgs4W+17SbAmrZd6F4zrlWoVBu3EGIIAYY0JXO9vrq+fXsLwVe/9DOxCz/8Fz/yJlgpsY9maZry1c3qP/sv/sbzz1/+7nf/8as37796/fHFVWT2tusvLy6Ow2RmXbMhCa9f3379a9/+/e/+0Y/ff5kn3h3t6c2NFkaRnEpO05R3JePzLzafe2/tdvxb/+Xfut483d/lv/s///3/6b//B/uH6ZTs1gAEsxbV4sVhBLgHm9sypdK/l1KYOZRgTEqVCa+lRgIFqEi+ExGJE9nJ7cW8OgvwaTOZZwpzhZjneMZ9fnx1e5Z5r+q6bu49r844cHNkBzOZadYCUwjX3gYImjZKCAb3nJrZ9gyKuc/EiUmCAczCHBVQzYwpRquMQ2Ja92erTf/By4+zoW/RtFR1e7rV6urpk6vryzEd0zAydNodMY2v3k6/+z/+rzzaSkUP06rrfGOJpx+/ef+3/ulv/+73v9s9O9/lYZsScezaDXv34Y8/+oPv/tHr2+PFqunWKwdJiGCZpunJ1dPt3XZ7vx12oyWFVrxviSaBEGKMUUROWyoz3F1VmbnydgF3hWu1NiGp/fVms89bcjdQjXMrGFuBDBC9i/mI4YHh7lP20MTQNkVL1uni+fnDT7Z4gf/kP/4PfvnXv304vjb5OPZ4/eruJz95f38Ynj55b0zTbrefUrp5chOi/PEP/9iNX3zxhYTw6qNXt7f3N0/Pnr935WL/9PfevzzDKkooigl/8z/9z/fbY875OA4OHcvYr/umExLru+YL7z2fpoFcc0qB8vXGvUwizWZzvVldgBgmQcJut9tuHyQQMw+HnZbj+aZ/9vRFL/0scj8jKJy8HKc8jrofpsTHA3av714bxCSMxV9+fPej91/f3R3uHjBOUEUpGCc8vYn//l//tV//tW8cHj74vd/9+/2qfP4Lz/bHcVIZvfkn//zD/uwppHs4HECd4Ok0+vb+dhqPTez/8Hsf3Fx3l1f8hS833/nlr7784OOi/LAbjJqb5y9++NFHH7/6WAQ5lbOWvvOlX9y+rz/4h/e//0/eRF3pNLzr/6/BxAwWvwvVUG1rPhOUipye7JKYEBGjKicKi8PtUYjyOFCkIz82LP+zDjJydjKckNWFn/0o4RC4wIUVUkDF3TRGOY7HZz978+rhbX/VKzSdp7/xX31r728Px2EsiZs4Jd0eDyTN+fll163SkI6HYynaiHRdaDqxktOUXC2G9nvfuztrYFmOO2WOL54/785o9LfqSUSvLs8k+GazWa828HD/9vjB+6/f3h6tMJE07XoYhiDUrxpQKTbMNogi7ro/IAhurp9cXm2aRlhILbtryeU4HKfJmIU5OLEbSilkaKQD0eGw31z2N8/Op7xP+ZDS8WxzebZ+ct7fPNyOLz98/dHtj0GNGZXJpqFMg5Ohbdu+P2vbtkYP7CTJubgxHMil7A/73W4PRJQMCFPrBh8TuPC53NxcA3w8jL+JeWEAACAASURBVDc3T9KQ7g53almpkLixXV73733xyeYcKU/jcdzthsO+lOS1zb4UwOHeMELfrxzY7ff5OIKEMrwYon/u+bOzi3W3CkqqmJLnUspxP6SkTGF7ONZaj6q54+I8Xpz3qpOXKfbNz33nW9NRN3x+96Pt7/329/Z/kpDQxZW7O9PFzUVBetjfm1lcb7woXEVIU4qBh32Z1S5sKYooQysib2bOQOBZHd99nvPMKIL2WfPVX/zc8y92h/Lq9nD35a9fvf/R3ZRgHk0lJ5LgIVLXaQjO3LpF85aoIwpdXEXhtqEmeAgWGe6ppCGr7cbdfjyErt+cr5qOg9j5Sq420gnyeEiHt9eO5zfnL957cXl1CebteDwcx49e3d5v96HZfPTRHah59XIot/jm555+86vf+MLzr7z39EtXq2eM1QD6u7/1f/4vf+f/+oOXPyktf/Fnv3a4uxvfPrx8/+36rLl+/mz7sH/1+l4YbYzBSSfVZAJvG3qzw8X5WYzdNOpxP6iib7qu79Ry28pXvvx5Fp+m8bhLwz7vh3EaU8paSkHO0qxcs5fCmhleCta8Fmu67nx7t80sIYbix+Zsuvy8/zd/+7++eU/vxu+/uf+D+/0Hzeqi6drDIb968+owAtSfnT//4IPxe3/00XHAl7701R/84INX9+PzzcXl2SUZf/jy4+3b48XT8MWvPe83vD/eh4DL6+sQmpcv37z56G4a0be87vuW2zLZtEvbV+mwLb4n1gYpWgrqevGsfzi+hWq3ZhP7xV/65g9/9IPtMalVFxdAEdqWvfHB8j5RAufAk3tCpHBCeZRU4QyTCh8R+eKMzNV50M3U1LWqIUttLqJHJaaaooKqQ7ybm3vVuWWR2ojianBPqVRZYRZiqczx4ICZ6Rz6O4QouESSGB2qbuoKpjY2C0skUDVsL8g5D0MCsO5XAMZh1HEird2MREZk7kY6GaFWsAAHAzE0zJxSUjWqn/yUqi/KwrUKIk2jZlZKvcCZZeGEbACq6ou7a51/c+GD5h6fqglheqIX1NInLQkQKtPKq9hwqORfMytuVIlulZ/gs+8Z1eurO191taki2Z8Ekqr2NKGG/bUm48WymzMTS6gfrZTyKWTK4W3oKhhyMqb7qfbEuun9aRjWT4kdhRNO9llyl7vP7U5/YZzs/1vHn33v/uxX/2U3ainyAXAzq8P3dG+ZYbbE4o8IDu+SxRlLrQdXq2V3dyWtueWMXxAtGj9VYMYMqM5uoFmFvBasa9ReFtzDQGA3AwFqykpE4ziqabWfF2JmqdI0tVOICozcWF3cyKrgu8FdzbxIEx2kpupeZYhhbiC1giKVC7XAymSnj1gncCU38azFWxSoEWQVMXaoqhWdSZhcp9/8j6uSuzps7ot0W3herlVYGuYIcJhqchd3J0aIUbUqns6JI3utqcOLAUHdyAFnzVldQcoQ1KY6zML4VslX79ryKryFan3FLBYcZuB65SfxdX03y2aWZiUDgcjBbNVjsaJQi0Pc0oBAc8Y7m2bNnCTMzCSbGacLqn9iJzBT1fkiqjy8RcujnubLV6IZ768udajRN3kIYMOi/K1e3AHT2gs5V6MDk86FKloOZ6Jkj+mqy9o+468LrWWWAToVxyuFlYWZxAg+22MTzGoqa26K4mSuS9GMHqHCPPfb15Z3rhVJd3d15zmzCVaJt+4Oc1d1ZyZzZQSo6nE6yu0twXGO437IOZHUnhuwgIl1Sm4MDxyEXTSnUhIaKsCQD4fhIeskEf2qWV+WkGmyaZpGZx+nQZGjUGRy0qLHIKGJbl6IKUTpeoBg5imXlG23HzXjfLVJmkqZQovQo+tR1HR0Jm6azhM5MwjqBi4zgKVQMzCiMM0aY0o+94bOTVJLsobHT6k+sopHnnJCmxUqa3m/jh1VrWXeWUZuXnpmBnKVfwrCanBTCWCBk3Hks6eb7X4sJZWp1Mfar0Psm7br+r5frdcXpV+fdcTeNV3X99lA4L5bEceLS8+5Ej9hBlJo0pxUp6JqWo0ZbJZ3IwoAicRSxvE41klB8xWfBnn9pgrXV770UrBeoEB6t+DPbUFOPie0tZHNpApk1KHo78Tc5zoXz2SLTxa9ag6NeczDAZv1wsgZdjI8Pm1F83QlqqZo9VqWPzlHQGQFMAOgetL4XYqL9VwzB5TYpTjIzYzdFijYjXLWPBUCGgIUeZpdg9SPEm/dc9Fsrn0bpWXh1eV6+nu//Zu/9DPf+tqLL3Uhrtv+rrxRlLZtzs7WLLTbb0crWdWh47HkEcfj4eLibNOt3WhMSU2ZIxOR8TilrlvJZWz4cNju0pgYxAIzVManmrJytcuY7U0WcGEhyQktN2pm0LktvcxOTnW59OXxvys/nhbPdze8GuvOj6GWHMYhY4NG8OH7Hz773PXzz51/dHf7rL18cnM1HI9pfLV7uF9tzvumP+y2w36/3vR9bPaH7Tgcmr5vO76+bM7XbRRKrm2EBHDgRgJjmqZjzkPOJeep6ly7lZK14dA2zflmlRqG5hKl4V5o367O2rZvm5ZY2Wut0vo2+GoFUGziWb8OlGMAmUwwmrvVXFHqU42R4HE8lje3uw+3P+zXq/Pzi/1xOtxvt7f3ZRiEebOyJsow+TBamfArv/KVm5uW6di05ebmHL6Fl65rLMvt3cgOzZbGlKdqTcOmVooeh+Nhf3z+5LrtqOtK10aGlVSmTG5Q6Ha7YyezMiU0AUxeklmpsgLJEUD6eIsDvCoOnORKThXzPzOSpWWmzgwuWvBrOk02fxcB/vQx8bv9zedCutNsgYM5MalvzjMQbVzRDWLiSIFkzMP6uhltOL/efOPbn+96AgWjUA5jtilbdkJshNiH8bi726VUmhiNKaVsVsyKluxmWux8gwDOTk0X2ftSYk6QZtU0HUkx95LGmJjIYHGsJFXlkrmo3zy5XK/WbRvbTopOw7R1KyATIbMikt2Ryz5lEAd2qsZ8asU9ExUiAZRdACYmEgoC1UJS3FPJQ8mD+cgoZHk87Mpe71+Pd6+2Zi1Apg6jJsRmTTB251IyE8XYmlFJxY5JFCRkhFLUDLFt88MEAAwWYhZrxXziYsPDSCR9s7IRZXLOgZlDCMkHYQhLzrlpLmNsmmYVZAxyHA7JFFAOBWbkharthjORCMemCQ23ROYh8C9885sPD/dv718d814aoeha1LKRudGswcCxEvE0xkY4EFRdA8Uf/ejDKD26Zr8by+AwCHMaJnd0fbu7f6AWTdsYYG7leASDeiZxlho7gbiKX8Ocl4x0DtAd0GX46YLa2iz/4bELbd+oNTddVM/X15vdwXMODw/H+11edXiy2cTIblPOCewSQ4weorz66H0JaJhi9DZSEyiwB4JZKTaZ51TKcUpZKUbrYqvecRPXTezbzdP1+uLsDH13NxwOx+MwDu7Sdav3Vjfq8uGP34zj0MeYN/nt8PD9938yFZA0LLGLxbz5pW99gyhc/84/++73v//6hz+kjLM+PL3pd/vp1fuvnJgZF2eXbd8xXHMej4fhMB1HBzClIecyjaY5AaFYyVZMSxnGDz96H1DT0jcXTRtXRByC5FLUyYjAJU1KEwvDLboe8sGnw34YwqopeSzIWJd/969959/7D391dSN7ux1t8rY5a9/bnJ+xhOIPYFFXd02awbbagGO4374tni/WUXV6uHuTEqZpaNbUrfvq6iAMkJpNzHx+0TN5ngqMYJRS0mIgiV0MhzJm16xQEXcmsaHIBAWCRYnuGZF7sqTTkn8RUNxNrdii0u4SQwhBh/KO5DqviHMbqhPY54RuNjp2n82RbQ6ZuIZMRBU6gRMpzWwhr/tvlRKbMS53zDS35U/WdZQs8GLHxWCjWUjetVb1a1f5TGHV4q7qAuW6qgPmpl4Nd0ou9TqZePaaVxjU9JFcz2nroKoUQeQ8R1dOCyvrUVxQ6S5zXs3LTVrEdGukVqsY7kww5vpWc0fEsmd9an+Zw0aa/wjmyJMeBXBgxxLZobZYnYhki5gKTpuZuVeQ55O7Xw0/KwMd8xOcJaHNHim4f+rwR0e9tp8SgfoLHqF+hkdFKlQZcmZW1Sq99Jg7/f+341M888c36s91Q2Yzi+WooOHjATR3KLwj9P2rj4p3nlDP03XOzxQOp1J0kS0i82pM6q68/NYs5O1a5YTgdQFSLYAVm8cGg5lEqrOho7jDVV3JPc/Ko0Yn2XNys6brTE21qJrrjEKTQ82ddM58QcQgYYOhtrAzgT3EgFmlakbAAQcTzHnZmyWwe1115sljbmS1tRCq9WO6VwFx4lkdrN4iZiHAraiSzi+wSMppSbhn8PqEjbkvNVg3IzDNfXMLvsNuSgBTXdfqQg4CvKhCmUJl3rnUpmrUJu1KtDKzWXFjBo60SrHUVYcrZuULgFUXFyYiJmcJ7AZo7TCcl32tK6WfYveaY6HCCjXrnvVoF5THedHj/8SxpPZUI/B6AhuIYnTSeel2n0FScyzgI1ChMTPymRMoDGJhIi7vgIK6nC7w7FwQYK7mX3i8fTADaENLzoVzIlswYebqfsckvDgNBDMxJxgt3Rl1q1lER5atx7za8FRok+H1/lSMt05UBpOxsE0+0OgPRkwvnj/b7fbHaYgxmrqN7g1xYIMVZAKiaIiRSpuKNit0QS3kw3TMpeSiDlqt28ZizHEYdlM5HPajOSRAxEtBSpNIYTZ1ZUFs2YMYqYOLei62P0Azbi7bcUpJtevj2Xl3dhEG1XF0EwuBczHyagtavWN8Ts7qyA7CTFbUVKtk0Ak9J/4sgFUnDs3YiJ9SQn83BmhO5TUXWuYvnQYtLeRKMmIGBy8lWaaGiZFsihTWl/1gOZHMKC7h8tmZNFKsGExiaLuubXtmhBgdokVDYGaREJvYTSnloqowRVFMpeTRyuhq5hVgrfETi6ABmCkc99Obt3c6D7bPfN5Fe30e+jQ7AL6bG8tpS2jwKD+e8b4l652T1uVmLDCgP0KhTrv+8hUVl63vNkPF9Q3mW74k2TWWITI4SX1lqRsuQQ85SL3WF1Rdl3lX36LOlLkVlIujpkHm7kozjUwIJenI2RS1iY8cWrH6hONhBFxdOXCMUkX82tD8b//7P5B/G+vQtSY2ZV8ldB660K+7MY2v7u+4j4WlKE2DTYPB4s31FXvc3h8fHl5OqcTkJJLGnA6pa3rhwCChEFjxOJzyT4RRM8XUFkh8kRd89Hgd8E9AVHPsVcO/GRP0ZTJ4lZhZgrsZ+6vtnmbOIJFpnJpetOj3//iPnnzu5ue/+aXf/6M3Qfzpk+cvnj6HyZvXtxebTRva4bhvQgOnGCIBJSWJ0rdx1ZyvNl0IUoybFhxA4sISiI9pUFPARTgIG0gCa5kKF6F+terahlylJG4jj7tBQhtjA/KigxgThCR2TRD0pmiatpGGPKV02O8GM4oxhFaY3GVSL0WVKIR2dXa5KvHK4xjbGNr2uBs5W3RaNw2sTEezrOer+JUvPttsNr/269/e9MxsTcPPnj/JOcZG2qbPe729vU0aSsKQ9DgpkAIlU6SpHA7TfvCf+/ILIMdm5IbV827YDqMVp+I8lBRWfde1+TC1DQKjlMmdiRSuVtIntUMcjx5iHcnz4/3sNP9sxOXL7K2p1amD3h/hzDRvKH8ODGsBQU8A+Ol93imaVtbYvDUxRCr0H/tmSEOzDu0aX/rai2/+4le4e9nFNqEcE+dSWKRtJcSQczkepoftACPZxMKeVXm0OtfJvbj2XZPTvOfmMj1s70Py9SVfrPoYQZSKqnuTS406hKThYFRA5sPxGAKbSS5WSio5u5fQgDlKCL0Z4G0XRByUzWCmxAAVUCqqgRCFRWTmqrszJUOJjXLIakfTScRCRBt5Ohz22+PHL7evX+nqsilFTc2t+hUFFnEwjKBWLOeUpuOkQyFHiGzueuoiaajSNogQQpDI5hJahsON1u0mTZmUOumkZUQdssdWzvrzNvS3b3axCcwB3jEs55wnc61eKcENqoqcIWRaiDwEjhyEODYNHE3ThNhOD3flcDw7XzVNiyAZpWp0gGdPaCIWCWAmYyJ2pg8//Pjp1c0Zb9I0lFRYsGoaLZjS2Dfxdv/QWIjraObMJhLbvoktT8chJ216BrgSgc0MCbO3DzERCUktnlYbCpgr5ggQBO5xfrU6u1rrMRDa++1wdnnWmrBIN/lqZTHOSIM6qTnNQthZC3bDfZAQhfoisEgUGeRsSxYMIhKiUM07PMOF4MRKXNbXZ+1640R3d9u3/zd579prS5Jch62IyMyq2nufc+67H9M9PWoOh0NSpCwLkiVYNCAbNuBv+g3+G4Z/kwF9tgkIhmALImmIFkWOxBlOz0w/7+M89qOqMjMi/CGr9jm3uymOxhRhQHXRjfPYp3btqnxErFhrxavXlsumv7jYPH786AVperm9PllJu81NuDue9l/efskxDtsdmIewff7k/XefXl78vd997+mTH374wb/4P//g85ev59MpBqRE1SAxpO5SYjDXag6hsB36kOKkh9uTW6le3MGCmEQCEVWiWnUaJ1Odzeo0V+YEYhcS4kAxhnTz8k5rJVCKfRDxUEOeu4suADIAAe+8/94/+W/+4W/8g/d/4+9+8NMv/u0nv/jx9f41xXzxKDx6uolRUsogMdM5V47F3IfNRb9Jn3zyOldshwGz17HmWiWSBFItX3716nc+/G445mKjap5GmFoI7BZqNnOPMfYhhV3XyVwmna4zrCIQHJGTQYk5NMG149WXr8f9zCriys5BUpBOKMou6kYnnqf9qLWimlkNC+sCC7BBaEnlGlS3mHpx4VgYEu5QB84lt7Vs3NxYm78E3S+H7moEdvH1xb4MXVuAIZCZr4nW/T93pyag1XMi49DWeIdMHagtRWptM1rRXqfaEmOBCJOAjV0V5u51oS/BVybjgkEtrjRYub3futibOpygLTlaycFnBy1dXFJJQL52rH/bY3F5ZwIc/PbG1fKxB6jZGq0sLcAe1mv+Q8e5lVz79uxI1VbNJbxcQ6P1kS6OyG+dyL9Fpfc3g2GFb32PMwiycAIfgFz/WR1/XejV+ST+9qg7c9/O/Kx1vPwVxxqcO903BXh7PLubGbN48SVlxzLOoNRAa2vZ+9tTCw43qJqtKfw6XZcp1pICdzQcRtUZDlmM/JqMVt2CSHG36qb1nIMt3IJFu0REwrHxpoKZOoGZiCnEsCYJvmaOS6oAOJO0No3wVmIi12a+7mbQCvIm1G6oFzEJt45xDsLqjCMNZ7PlFhBA4LWToC8thUBEHJil0XKWhYG5lbcWSEWInLxY66y35jRuS6JvDnNjBBFhoRCxoCbu8KVr6kqTcNialXozn4fDoeQMo8YivV/wmxtZEJgzOYybp9RyI+Dgc+Dw4P7TyvM695tfyiEOdyM71wmWG9Cs05aFdendSg5iNve2f63tpNDos4SFA7b2FFi5I0QQciIKS3O8Bbpa8Lj1hq+orrvzed+jBmlykiTgIgCbs7MJkYNdms5ShIlJoFIVVcl1gTHd2g0BznZztLQeWO3fDb7cQyZfRcStTNnIX05waNVpmj763kfz+PPjeGqgpasLhb7fUNKSpnlyiFIIoWOvlK1uOjbJx/kIZ2e4GzG6mDjx/nCgKtOUmRATiYhaLepRayMLE4eQmNA7eYydN4zBoIbqGKdSct3sUr/l3UVkZc/Vs1Wd1AmQZWMhXlR+vKRQLk3f6QpbVWQgb6S61RXsrfVrQWr8rZ+dv70fNLDFga31clxmXKOFtjg6kEjwrLNOCEYih7LXY6EQKFlHIaVAZErj4+ePis43h3qcj2rqTmZgFlM7ncbj8dR32xgtuNbqtc45N8Io4NCKWrXWxexsneOBWgcmAyD7/ekXn31eteIbxzoeW977FnSF82davm9tA+//qPnpLpHdGbxqjqYrYnUO2R6u+Ocd55v7i69/Rgs/btk+7pmGRITmF+cOO6NvzEuvTwbDSJS80kK4bE+UqQVJ2q5HHWREtFh96UKwMyatXrKSiZuScJLICSKEYAzTUiuMYeM0e7Fg/uji0Y/+4kePd7vdZvd4uHz9xRdP37vYPhkevfOIY8hlfv3my92TpxTjONU8O6MfutSHTZ49z+Xu9lQLQqoQqrNCceJRWMjJzYSDmVUtK8INZmktgJtPhqm66oqRu/tbGP050sMZ7bqPEleotwEOq/i53TF2tF4RDmMmg5srkUgItUwx9iXrV6/G61d3IjFP81/8+Cc68bN3nn704YfzcU4hqujzJ8/6obvd3wWWbX8hRLASAqcQU2QiT4FTBydUrxz6Lm0ny30Xo4XYiUQhcQ50u59LPpXSw2tgayWhPkWqWyaqtQqDqSEJDotdugwpeiWhGBEP42l/dzocJhYZtoMBjpz1jhM5FAhdkO3mot88317yeByr4bK7qFtM+3K6HXvydx730sXdo93TF08vry4+eH5V/Fjq3m3aXQ6qZo40XN6eDtfXejwa15otTJOXMkeamam25rfqc5kcpfPiRIoy59OYocQOymV6djlcXG7c5yGF6E7wQGvNvM5EYTHshK2L1PqEfZ1nWIo4X5/n35hqa5D37YDXw4Dq2/78W46HnTTa1S32o+v+e//KwFYBdQMa2dphErmQl3353d/++G/91ruXz+I1JnDlAI6IFBCYK5nz6TQd9lNRRGEzmrPWWqGFmYJIYAHQdYPqzOIklscyHm/9ZM673dVFZClac6EpezRndpCEFGNX1QyEaTqx8DQdDOpeSQoLnCgIdV1KXc/E290mJgJKraUxVUAKsnFE3xcRCEStllLgJuIgdANiNK2j+RzhQx8e7XZ3eZxq4aq7iOg9THMutWS4VjaRkFLXPAqn02k8jfVUoYAgN+aILZYU/cVAxjUrqrJ4lxIsdiGYeclqM063I4u0XmZe3AqkD5EiKX/yi8+2u4vNsGWWabZp0nHMC6Afoiu5qqqCUOdMThabBJ9E+bNPPxs2fZIYOU2nqYzah7jt+ynnaopwWtgoTaZPqNp0+qzuU27lg6YUggR0IVqiPE+JhQ3IrihZa9p0m02/2QzudSxjVt9sQnOe1qa+ICVmZhEOIBcHE4cg2jRepu7WejO7qGwRNyS9o6hZvd1rf2Gp2+RSu03/7m7jlksZp1wpECcBS7Y5H8Y8e+qbzoCcyMDmXKtVy+p1LlkVCR6FLnZdCjqkKlSgxa1Wne7ySH0MzKcyzWXuQupTv439QCmG/teef3hIozq7aaUsCEXKZ28+vb69jki/80Pbpd2j4dnf/eFHP/joxc7HH33y85+9uv781Wu4K1GFOcucp2mezbkfhn7Txy28FtUTKWqFAAgUOmIyM1UUl9oN26p+OtX9dFBDCELO7sIITAFC4s4mIYTAbGaF3UORHadt+b1/8nc/+sHzv/+Pfn3zmP/8sz/8s7/4k3/34z97+aZsL/H46abfxMePt8wSwobZ51zsMI0zxdiFtDtOrx0IURhUFFSLVa+jTUWL4veuNiHlecY05+Npv7/L84w8e84WxZ4/fr7tdsGiV8SB0QMR5NXNITCl2IcQUurEuX72i5eluDMkgoRgxCGG0BG8qKoVWIWbgrzFbmvJzd2ZlvLQusA64E1x3zKDlumdid5v7bxGDZ1ZgSBa12Jr+cDZE8pha3bQXMTbP76HxNagk84XxgAJO5t7g7xtsfMFjMidwUQMh5Xs7kIcJDCLNK9gB6lh7WHs5+yYuRGXWpJiqOtbf3MPIG+eQOaLq1er7hsWCcOaawNYO3kTAb40o3egOU14i6Idi4MiAG+UDW7RHZ192ZdNz+6v5ZdEKM7owUNLdTs/Wlr2TjMDwezsvfzW8RDA+ptEisI3zZ4a66qR8FUVbxtC/WdyPFQCnjWi33xCv/yj+hrAxMyAt9u7AA5rjPXLn/AMlH7t5/cNECuoGTk0N9KmUqSlt66vNJRFML+ium3Gto3zwWnbMGh2SG1xYoK7NjdoMEtgboUfR1OOvZ3n0QJdrewzYRZprfpIm86Plm5oaLpCX2CQZk/C7s2pTZu9+mK5Su4wuGq73rxW1ZdG6fdqPYYA4u2TmPvSQBBrmOBBlg/M53hzKY+1C2qKu6WE4DBa+o4SsS2mVU1styZKC+rpgC6Cx7aeL1Ns8X13Icbq4XqGItcW282WzxbfdsaSrdIKgAUYNThwQdkI3vx31r7dywMEVqxqUaq6LWupt12krfFfG4Ps3q4b7rKOlkoGhS3i9eXhEoi4YWKLerGNN+KmTlmuWgGWBcA68x/obJAMYlkArLZiNgiBz8VDdzYiJRiRQYxUFdVdyIlVFWICERJnXd/FF6HbA9oX2ojj1peQvHkMNY9Kc3IPYMUqi1UFDIERIFHMNaYUUwJzLQomdJK6/uLyklCmCdWnPB2LZbC71s0TbC96inxz3DOxGQkkSAoiYB7nqaPOoCFARGIirSBAGNxwugbdUQABIgBJ6lKHStgfTkLyaM6pN6NT6HH1ZEiwV/Ph+HqGM3lct0dpckJQ6/pMDiq+NBhwQqPTrUjIX74S0UohwJnavSIlWCsz30gS2xNmkhYCObtEFuJptK4PEiVbPe3fpNTFvpc+XuyGkEj44v0P36Pop/FQq4JQq85T4YEBKiVPY4nB3cmU1H0ap3kuRReqBREbUVMsghhsDhcWg8DVKgA+HfNPP39l/mCZenjRK/LWPjI1SNiWkXz2wqQF8Lvnci+q3jaczvXAdRd4GO+0BeGblZL7ksnXim3mi3dJszNZEOmV0SUNI2xFvbacSuBm/iTtQqoZFIoAoNX+yAnC7k6wh+9IALXGowZmdiKrVN2aNphIYkipCymJU53LUWtVM3MazWvWSHzRg4L86Oc/+d73vv/Dj3sd5NM3XzyWy+7pELq0vdrSS6gVLz5PGQibfogUpmm6fnl4/fJNPQGNj6oQCs5e51K1tCJHkmTQ4oWprc3EjdzBZMbUTB11tsQz6gAAIABJREFUDegarEH3lKuGSa4o4/3CcNZ4Aqu8ofFJ11uy3Or2H1NbqQTMgaG8ICYVN9e3P/3xJx9/+IM//dEf3by5e/bs6ZOnT55cPSGWuzlvN5uLi4vjfr/phhSiB1UUAUTY3Ugt9BwiHETiaYi7rqvIsR8SosNTktCJRCp2Go+j2VznI6EGoSAQoqvt42KTlplZYwATWa1QY8oBgULPHr0CmcW7bdf122HYDi461/2rl59edbuuS2pkXjJOA9J73fM73qsBGo7Xh/3Lr47Xc7fF83ev3v3gvefvP3/05NEm9Pv60i1P420p+z46B4IzSyqVpozj0VAyxwSPVms2jTGEkDbbFNP08vXrrrPdZWQJrdV6CHDAiTzXXHKXYpciw9ktSkCMUUIrvxHrAyLVN8Hfh1/8MoDTUsZZgc11hJxXNlr0yN8Gcf1V514xrDMkfT43hNpm3so1dvYTYO13Mql++OvvPf3O5d30curuSFC1EiOm6JVq9TKX6VRK8SAikkrxqtW0mjnDoyAljiGN4zxPRSupa83mIxBRK2rFOJbTeJzzsVbr+phiD2eHgQ1sSgqOcIzzPI7FGdsNYodSvOuqSAohMiMmZjY1q1qtWWPAzNAP6DtOKTFJKTXnolpSQtdL6pK75TK1JDmF9OhiZyee43g5XF3G4c2xBjM1UoVqLV6LVw3W9UpE82msU4UDAVjJRM2jkAUOY2GQqxUgCdzN58MM53mqp5tXp+Op65JDDcXJNGgt2VT5mo+jExUh7foYQtd3GxhPyHBqLYzgWtWW4iO5Q0vVOpdpHKfjsVmFgPzpxYt+k5gDgdidiTaxd0YIwVyZYa45K2DC4pChhzvyXMw0RFRgnjMqu6KMtQNbVSsAA9GdapVSteRa+05qNV/bWjgcAVFS3/cEWoMZkIiXajAjtlaMZgLw9N2LuCOKFoaQtLt6NsW+I0o4Kgvtdhv3eHc3l1Iip7RJ5qjTNJf5MOG9571XcnM3nUsutUTyQVp/5Uiimz5t+yGRs6nWrMWVAVY37Mc7F48sc5k40HbYXO622zSwVlJ9fvUozPz69TWTpU2KIXmwz2+/ON4cPY/f/8H3uOSLPvaMJ9vN7/293/zgg2f/+x/84edf/uK0R7+ZuxS3j67U6JTdiTgGEI/TfJymi6ttmUZMZoCpz3lqc71WD8lDz6jiM5zhDGtrKUcovOpm19nsdc6lzlndanXRnHCzBwJ+73/4re//8IPidz/96sf/x7/6l7OdxsrV6TCivspfvXqz2XQkMfabEM1cxzGfJjiEgjkhREiQIXUZMs2nfXYAV5e4eAyzKYaG8oR5nOa5zDOwNGBfNnyzaqgIig3YgeyWayYl477vh8ttPwQhe/PqhLAEbl5tyrNmmqWkXaheSh3BjsgixO3JOt2vW82A0tB6MPI50/AFkVrZAN+2FK8J9HlRPJfgCAB0zVe/BpcsmQGcCbEVRWXpHI1F2WeEpX+9O7Q5qGCdDNBF9Ohu5ODaQij3wCBecpraWGOE6ksmad7SpIbhcJOxONCcWL6N2+OqTXnSiBJLXdCJmbgpddWZ4AaqrQHiqnFhOLHDHnALVk3Pw5Cb6EFZ5HwX78vLfyWY8E3o4Bxz3hNiHgShS5TJuGdUPjjU9HyGv8kjnLG389WbWSmF1vYr+JtF1P7/dpzRq/NPfjWg8R4nbSVxYsBrrQtV775I+B+BiD0cgQ9L935m+qkyxJZ804Gl3z2Wb93tHJA9mB++0DE4rVAH4O6lLhKYhVgTmIic4eogyHmAAwDMSGHGjrD6ewEwtcpYBJVNpM9gcFPMcWvkwaUULLC1LVfjzf5gWTOWN1hVSq12LgQhya6MZlPdTNzMzIgUjdnt0Kq1tixIOcVWmWJ3VataFz+UZnvM3BpaN2Stui0l/KYGNTM/57hA1+4dE4EM4tIQpuaUzM3PxkiLVWrgfGOkcKv4EC1tzeC0+AoxLzGykbe6f/PoISPAra2bWmtdCES0CvdaH7OlUrHmo1bPq46tX5xxuvOKxAbI14YgkbXGzE1oRgC4NfDilvtyqx00okfL07nJKtmNYbTgfmbmRM2/beHEOBYdIEgES65IbXk3bzsSvBEGmVmYx+MUXMpU6lS8kGu14loskhaYOZghUULPLmbCEAJTYDEmkLYLPCfoBAiBiFvIq6RuWGpHzEHEoGYwsxAiRQbQDf2c5+s31+o2pO2433OXYoy1eJ7r1ZOuv2BJ8c3NwQ0h8KT4tR9+3PVUcv3ZLz5xBzn3YdvFUGrNVsdbSKgkYEA4xiDoLQoNfQQbxQCGqhmRA7k6M4fUXVxezaf5y6/Gy03YX+7TkBRTP+Dq+WN7lLx8ddrf+GgOBQstLQ5YCSqtdz2WXm7agGBveWDDZN7eoJoUdpn6WFcTavIHYj+/ekUhH3RhXVak6s1bzqsZa0PeIQNDMVymfujqaK/ezNmnq22EO0XEIWyG/r0P3+136frNXqJA4lxKUQVzP/TmUCcWiTESCbMcj6cpZ1MCcSN2CUWThmE0dGnpLsPECpCIZtSX6HZhxreQsFpA1SpdLSYTh7Yp70t1ipx5IZ81KMqJ/V5vtjK4Hp4UZ1bIOSLx+7uHt6Xl7TJ8bQVKvBjhOaHUStSQQWJuPEkjZnIQkwQwUWBhb11um9rDvcJLczwhIiYBt+aqBAZ7W2edmq2ei7suRVcBKXmtFvuuZHOwKZtyye0j0zRrrkiDSx+DUJDwxetXj7eXf/Dvfvr86Z/1V9v3Xjx/9YtP603e7Lehk+9+9N2fv/p0LKWUuZbS7AyOx8Orr25ef7Hf742JQmKA3BAk5ZoDRyczdS/ubqlP235TVXMutVaAlirL+Wijk7HScZblpa1UvpocLVXGRlamZVdsFR4itHDWF4L+0oGiDQERdiMzbb0NKHCeqxsg+Pyzz//Xf/bP/pf/+X8q+VhmLXPd3+63w2Z7sQsUQNjtdvPjZyA6HPd3+c3sMwtHYbhatYi+DzAKqafLx7vLfsg6OW9FRFWNLCbZXnS1bo6hboZOfXbNgYSFg0eQBAmEojqVXPuITtjJa53ceBO3Af2sqjN77VIIMQzudDoebw7XKW2EAwlLIHKYltvxkA/Hod88vnrx4p13fvOd3/jHf/8fKrxCjzhOGCc9jvnVV6djrrbd9urHw+F1DthsBgqbKdc5a4qYZ9S59BsNMVXiUlWYUiIJ0UGf/mLcRKTtEAdRKtVWQTcFZt7fnS4fXwYapuMdAZFj7DYpniDgxKjfaAyyDIAVb1+43L8c4uRrfmJgIgKZk60nWIbVMkH1ARfgrzrneUI7aCE8vnU5Zmqu5IGDND82JZeeMuUX7+2+950+PcvH+uqr46fxeaFqWbU1X6zVjod5GitUutC5hVrqXHUh6VdoxeQ29LrZ+M2bEYa+SymmucuVLA7YbmMgGg+n6/3BHSmpBBeRkLrYI1V2UZlp2o9Dn5gBRgzoesREMXnqQghMZLlmOxZmUq05T+7UdQkgrb7dJJEknODCJFGYiYDcOPLjeMoFlxeRXYOnxFupdd4fykGF5fbzawkdswy0AZvCzUxLnsqpsfzIAYHzosKhyByEGe4wrV1KZJKrmpVxOpSj5aN6haliLLyJ5TRxpApFsovHu81lb2QllygCLDSHGON2O4RAMYV2Y2uttSI0FfCcA0LXxTyWkrVUnTS3CC5taZM2Q9y52+vXb6aaUx9TSiEJB5rz5LI0yBaGSC8Sd9uLUnCsU8meun7W8XA9dyENYRj32Z0M5OSpZ5vzaQKDQwx9iEM/FDM1U1Uis5ZuiGCVf6kbO5mbijcNX+Pmgtmt/tZ/+RuXz7nKKbsey/z0+dObmxKjdsOQTMxqLqNZiTGkIfV9MDMm6bv+3RexzBUCr2QVWqxWYxbZDsPQxy4wu0QMPdeyrzVTqEpg4S4Fj3XbJZQ85VLGUyBN4oE8sAd4JO+uhjKOhxM94qGUWs005JOfbvUYBP/8j35/F7fvP37ng2fvfvTivQ+++/QH3/34v/r7/+CP/t2//eM/+dMf/fnPP/vi9fXdzVQcEmMaUtelvrsYBrvaHV6/ZgFJCUmrYs6qiiAkyUlQWVWMewhBK0Sw3Q3b7Y6N61wPN7dgpVCDYDek58+eSW/f+/V3/tv/8R/9zu/+cLLbf/2Tf/VH/+aPbo5fOsWvXpVukLTtgaCeiZhZrLJWqLJpyJnKbFMZx5FTQIwphHSx29VY1SrLPiZ6971H775/td9fS7AYJG46Mi6TnYJw3GgFA2qY5zkghEDDJj5/F5HT8ZBvb4qTezC6sOFJvLzaDX38i1dfPN6k8VTJXaj74Nl7jx+9YA7X+9ev7l6GEOEeOrbJcilJHOCle/iSrhKxtDzDffVLwNJyBg/F0ffL4Nq9bvkN0cP1s0HPzUS0eYDer7T3f3Omry41p+blak5uTggI1KC1ipg6a42MDK5OTqRO6m7uBnaIw80L5coGgAxq5toMd9bIwVZ300hwX31yl7X8mzk7Aa2vYosCydmroTEpScjZzOC2MDfU0PxbGM5sbhRa56nGWjjvDyuLaA0TmVZ5gxuRLL+xX2qDO0tlsJZLv/Z/LMyJtYjXEkwi5pXv8W3HGTLCtwFk/ymO0N6pAVhn4OOM2pzdr37JS6EVUPiVr/4hZPaXneQ/Baz2HzgbrRXue2bTr/rWTUDT6FcAzHBOVX4F7PJcGnyIXq2IWMsS5f7Ey4t99cUGNRO6dQlAA4weXAaTLJ7mD1sbGC1+E2Qu3PJeKFy9dZRtV6OmcDDIWn+KlgDb8hYGvjcFXzyOueFTzt4QMSJg6amwEBXa/cM6uVp6iAWtJhBEBKYSSEjg1My8XM0BZYNXdmu29F7V2TkYnyUnwlbh53cCoObcwPslf29JKpOAsLjfrwNB1itu86YhM0RsvJiDwd3aCgpgbffZKGjj8cTMWJt42xrgEogoOND4VrRMzAY4LBL0Yq3dIQjNXIgXJMuX0dBafDtJs1P9+gi6r23clz/WFXnx3FmGroFaKOe+IEDLJG2b0HlK+sMxSQ/YJb6MsLVY4/cMLH57HC4oyjLG39ogSilwt2JWDAVFCdUXi2aDFiihqHasCHBTuKyN2JanQk0WiYWi5QoWInZd8cNWbRASsDe0wABmCRLQ7r7j9ua2mgpxK8EihlzGw8Gfvffuo6ePuv60vbqqasTOXB892TmXeleMwYLEXZ86OM1zPowjFDkrC0uIZnCXGIcknFJMKZ50dDdzmLkB85yDRHcSSSF5nqc5eM65VItJSsTVo53stnfX82e/uKkz4AprOljmVqwCg2BurrY4lxED3FwGFpBKCViax69FGF8FWO1xLw3x2r62tAugRlNaN48FDHcHyJw8MFittr2ZzJNI6Ch0sd8Mk+fW3W88ji6Mu71RnAs2mx5oHVdIFblayTlIl5ItV9dANMDd55JbO92WHaF1bBGgWQQyucHU3YlYVJ0pMAIMzAJ6C8D6GuZ0Pggs3iIrJ1+80tCYm+RMjYBDaOLMVXG7glNnF7n7oMfPo+6+zLYQgeDLstYmXPuFmy9a1ubPJgzA3M2ZbcUiFzymrUAt/GqKQYcZNdxdaVGzNoVwcW/mWeYgX/TgC62lYWdkaCV8xAo3V1iZiqoye0wggRfAMKSdBA4h9F1/+3o/Fd8f8O9/8umzD56/eP9FhR3m083hjjp+9vyZhOAla1U4BUmn03g65NNhGieDcwgiJLXUqkqx6rFy4iBCMDOrWhNi13UJiLEej8dSqlY1NmZe1q0mBef7zfIc26ziMl+eArXiUmMonotUD+DHpVzhyyrVpMaNrMjkBHNjpuoVQBA6nI6v/jXcw+PL58fjaTzMx/1k7h9+97tXl49ub292Fxc5zyLBvB6VxLQL/dDFWmtWhXoQBtOQYpdCSsG8Vp1cyF1z1q4AHmLk7SZt+kRuTGC4AES2P95uhp6Zaq5TOZERUmSVPI8C2QhEJIAvd4+3cJHAKRibs88+ceoM02mciKiPQwpp0yfi3p3m4+EmX8d+CF3MOs92slBiUBedMGnda0UIKaoRSq0+TtwNqU6Tuw+bzrSomqXCQYSt9VghFBEF2cUFdjvZbiRGL+VkjmkCBRLhks3cxGPgNGYow9SDxNR1EEiVcySzPCS/j7mX8JXoYS70YKq7SFjKPcssW9axt9EuWsUd6/drgembCcw3F49WTud7BGxZVtc/9lXkS+ss974LBq8+ixjE0wV//29/Tzby2c3PNY2JxZ0MTQGGMnk+VS2cYu8c5rnW4iUriJME5lA1V3WBCRkZUkzbfhtEmMbEERHDpjcruUxeIAkpSYySkqRB4MG8Sqg10s3LnKJ0HXddz0H7DWKkGKkfuhhjtWzZclUQa0XJy37AxIR+HlsuWIlACExJQiKayNk1zPPoJoJe3F0Tajzty+Fa37w6JJbj9RwiYgwppdR1XSCKVEo+nA51NhLEACLUxrkkMFMKgXnpLtT1nbFpLmoK9XlSn9yrA4AhUCD4PE8wICJFiSKneT5Ne99S1VLKHCIHEbPiMJHWTQMxiScOEtgkIwQOXepQTyMmq5AIFUCh1e9uDlAR4Xksuc6mLhtKIibOASRwctVKHCUIhxhJpmmerADcdcOdjTBE6VLqjvujmphRSMxAmTOLbLpt7KI7hKTbxKy1lFJNtcXbVo5TZicyQIgpEIyEhdmbdSqbi2PG03ceT3h9ON3e7g/Xh6l6vLmdNkO63D1jDrc3r46HO6059CEFGzoq2Tly32+vdpd//uMfJxpAAmYLZO7sRDWKDsk7gQdQZ9SJkHRDXy822HQWY3XLT4bL8TQep8nnYg4MtdRTDanrk7AlxsXzocbHoYzTm+nV3R0kxYF2j2MKSa7CKU8vp6/kYJyqp7INs/vw6x++83jb/+2Pf/CjT372b/703//s00+PuaplGn0+HYqRtQ2REFPs+oGIc665FHdzhsMU1cW3FxvigrEAKGWeR4J6OY1zVgNmIAg+ei//4//6B9/7/vvvf/wkbHlfv/x/fvTHX11/qQi3e95dbl/f3AyTdv0sQSPlYRhiivNcT6dpmoqbAJHgNddRj2ZwkzbSUW0YuhAQO/RDFFkE8sxJpNtuhmPnrl40wV1LLV6csBvS0G8ur2wYSghR+tFkb8B0VNo67UAbyIZfvH/Rp7AtfndzOh2mm9vbqp5rncs0n6Y65hBCDMGS2aRGTg3UaL7sfl/XWcM9EFblM87RYHM1wVqix1IbakWilvM1Xf4Sbi5hz1KVX9KIr/1bSlPLr93ZF0sFJhgv6RqUyCBODG6NzJb+NQooyBr9fOlZpLUuV+ZwJ2r9dc7axkZ6elC4IJwdzWnxmKUHK7/5QuX21VSzXbPRPfrVSpG08EgcIJgvINQSZhCoWfTe7yotRmuSHz9jMyuIQA+iy78EpWgvPed+D7lKWNEef/Ax6UwVafupLbnSWxve2xDE3wx6BSA0z4gzgHX+AOerOb/0mxf0UDPZjnaqB9ZO/9Ef42vg1H/gDPcl/r8mMOvhSVYqAZ/j3VZv+ZVPzsvspYYwuLvqaiz6AGRawuUH+dM6th4EU0sZ+Vuu/2v3wd2Y5J6DuGKpLfoiWoh/IBIWB5mXhRXAi68LQETmLettoLC3GrRBl6CfiB1eqzKMXIRFRLQqyIWEhU1VVZvUDwCYIgkZaa3qEGqOnr7Yu7MHCXAYzMxoJYQIt04RcMeqxHUmwKl6UQW11n0EMmnICYMCAxBz1FLqnEmEqI1Ph8PUjFSYaJWo0cIxuvdAWZrEEkiYiEQgHAAUMnNdOoKFpnzkNmDMmn4ZwmyuZsor8gkCSUOyW5xtbgzDKgViwLmxXc1aLwUjmDVbdiKAWcBrWM5eTR3uC1jP5xzN3d1tSYN52R6+MWDemmht+3iwVi6tABpOxyJNHQiDw4j5rfLAAubRClm0T9t8u5fTt7ScQcRkZ5ZPWxkZBGVp+5X7ag7i7lgdzYzMKaQUubIHp8BejAksUqsyM9gBIyKJIo1Opb4adDkaM7cN44UH1vTwC3ulDSrmFoAR8+oQ5AS4VnNViZxLEZFxGolJVRHgbmBjZiG62x8uHm/GaQyhkyQglcDH4yHbeHN3RwG73daK7HY7FD4dp/1+CluYUoxdStHMa6EYYik1Cq6utrc3e2aGk1Yrqjd1H2NKqRMOfeLY3YWgqrUaPX766Pr1p3OZL7qrZ+88efri9svjDTnQGsWt2Rs7t+7G8FbqctMVcYGTNR7WIh9ug+LBsrjkXLzuZwtKAixbrsPJqxpzG+HrugREFgSutXAkZihqdZcEJycmQ5UAAHmufd+Xw1x6//SL4+ZiuLt9czjsD6fDNI/jlF+/MeEqceqSVK2l6pynUvx2f1BVX9tBMPN4OnHzyXGYlZDEFLnmWiuTT9MEQogJ6a3qwTJ6fSVhrDnneSNojW94kcnCSYFwhq+p4UFtuMG99dGkpXRFIGDthbrcz/vJ0t7gfin3M6TbHsNSRIC7M5rwtf2hmZkpkQUXkJu5qjXHMG5uE77M7VaeYmZlWiLKJp9u6zl7WwfbUstMMFVUggDULKCYZJxmmLv4OE2YLMQASNezkBhpF/s8Z4fw0D1+Evc3N/0O//cvfvzkL65+5+/8FsWgPr+5vel33eMnT0qZdptdmY/k1vXDzctTVTIL1WYCmbpp1aJubq5YyElGzCJMzKd50lvd7HYhBGZWrWaeYmq3lJlNBM26LwjcuYmc4aZL25O2NrSyAAktFhxtaW67hKEpnhsNw1eVqLOTs6qDiIQNCvN1B3ERYSJQ+ee//y9fvNhe7J589dUX8zxKSk8ePwlRqpYnTx6Z1RAj2KocJ+NN7IcUp9NIZF1M225XrQyx36Tu0cWuA5tlkZ5cb/d3xGXYcEosCCmw19qnKHBxuBWvs1AHeM5Tyac+bMSjcIRw4kEkRXShC8QlqzqoVjcGS3d58fhu/KoCZs5Ace2IIsWQkjiraReCMbSO4tnrUXUCwSgzlaGP5TSWejLNImDiNzdvrkxCFzZD9+6LZz/7dJ5mJlHTEznDxapamCTMRPru893uMl1dxS76eNynhLs7CAWOoUw5pY4tRAopRLY6HscrebIdtmCYadvzWu1hqR8bmIhZVKsrOCwALb5xsEjTf9niOoTmCbfCx8sEPJuC3i+HDK9n4OzBCfnrW20jJdi6oi6r5bIyYy1rssM5CJynaSYxImWuBQU9fv23Pr54Pry6ufmLLz79wW+/B5i550n316VknUfPJ6Q09GFbFFOtUHhFVY1dEGZyEgd7LKNt+qsYQ5LIREOyp08ez2VC9OPx1nQSas5RbRVSd3WqLIWCsfuTq02I4fJq2F32QM3lYF5YVp9cdYCqmlvzyyMzK7mmxCn1t3d3pqq1EIUu9cOm61JgiGXPlbSkLonVNJY83Z2eDGU8oY7p+g16GmUONutMVbnUPg3bTiIzaBOGQXqHOisxKbM5GTkHhCAhRGYarobdbne8OR1u70quIj1VDxKWkmevRedKRox0GR69uOx20bipJjEMUTrqOhep5qXoWEvRqkFiZJFGRTMLFJhjTN0wdFAd+9PkSoJ3Hz2Lkvb7QznVl+MrCaEfOoGM47HjIMndFagsUl1L1aZqIq2qmMbJFZ0P/XYAAwlGVMyqed9v8pyXKuKEdBUudxdOOB5PeS4grrVoVYd5IzwvrtvBFkE4EZFalRiIYTaHJBdXuzDs3ty+eXP6dK532U4OXN/smfu724nqMYh41S6mylnEyXPNgR0X/ZCkK/v5KjwREnggFhKxQKhE2XNFvh2J/OJyGJ4Mw9CneHm5o6td6Dt1zzkfnqSnGePGN0dKp+OxjzEIczTj+Wg5Y+6fbh5vt7zn4o9O0ylr2W7C5uKSmO/y7XazlYs4d/PPT5/uv7h7xI9f9O9uNhffeefy+9/56N13nn783gfjia9vj3/+ySefv3r51atX14eXRZF2j0PspA8SAphqqbnmUrLCq1a3qevSsBmutltSKqXkadZy1Gpzwffei7/9wx/+9m/+YDcMaZs/+v6ziyfDUe8+e/PVp6/LT376s6+ur28P82EfbvaHX/tb37m721e9C5yfPr3M81xLmcZ8uDvMI8g7prTYnUAu+q6YEXwc5+lwOh5OEmiQsN32T55c7Y+TWiVny26Fy+g68fEwz8eSp3nTpyg11DD0XeBIiUio28jGQzGTXWemJxzyYdzn+PzDxzVXr80RIB3v9uVYAT4dTzZmVHCACJFwS1ucmmZwDVvW/GCJYHytm6+mVlgjJzVfui6tFdG26KkqEbEIAc04ixhNktLWxPaF3x9LQmJuZ0VIUw60ls3EAl34E+bemtOSETfeU3U3kK3eMEv2TboGXa3U13Ix4yUURGteBHZvqm5f8xSoGgmoiVGWQHjlnbWtZHk5MzW7xgoQL6oGU29JR7sda13UxdsNEsES+LmvGEKpykwxhBa7qS+fvlXoSfDwcaz3G60gfQ5u1ZUehLUPiUq+koeaGuYeWjw/zPvvHmyF58f6oFPht6Wcf82o1sLAenh9/1/ewx8Yk//KZ/jWr7/1NX9dl/3N42v35Fue2K94PIQI20QBlubmKxniPnECvikneesi15M+AFC/7XVfw2N9metY4Zr7q2vO/Q0kan/SyBYLEuvw6nWtGgLmbS9E85lTIyIDiElrCYFFmEjAUlBczd2FmFiE2FS1KCBLr2hiN7ipkUcWU1U1tbpgHsxMFCgwk6k7rKUKQAORzLz1TrUUoheyxtgU6VLHRLVaQa21Gbop1n6Jlq1otiAcRUIQl4ZhLyZfZ5CF0LR+jTLVbrV4Ez5a84n3xWmwsVC4+SuRkJgsnw3NjwvGC5bo3ppVPCBGtWjWF0KVO7k1fRvrAlsyoeE81JSFNY/nvrSNi0sLcdIAmLW7ZQso92CQEFDNVuhhWW5WAHUdJlgy3FZ9WJz6HcIylwwTgqnhAAAgAElEQVShZdnFMm4fgh10HiXNAXqFXRUIHBbLCCKsnj5gLBZra726XZOvMnaAFNql3ta2mo3f6+wQuICJRSDCIUWHajN+ezC+RcSaubibmaFZHwVaMMrGrRJyJjDbCsi0tblWY3aHhMghxpjEzA85IwCKMk8o8KjH6XC776/3N7Xa7mLX9fH13ZsLZaeqVmMHSTKOZc7TEAYJJMJVTQQpxeaXYepjLlZmKO0uVBCJoOqllGme3YvI/PgqXmy3eZ5TRN/LnEd47PuNmv78s8/ff9ZvdlfvfvfFl3924x04MBkMys5MLZIANepDI+aY3ZuEMRoKamYrfE8EJ7ZWCzqP0/MutSZ9q9kQwbU1GGilGPAyqJsYD6BFVWrL0+PI6XIbOu5T6F9dX6cupMASrN8d+67bA+PpdHN7o1an2a4PuNzOl4+EWCRICCJCU65znkotOdecAWStDg9sQHEwcwwi5B1crFoJxupqTVYXYIsvgi0S4GX8vnW0qcFtcCyN6Ywaw/TcRHQ1wVoNUexsU/BgV3u76nPvlvfgZ/ehhvuZOtTYsQ3gIsAhLb4hMoebOXtVbb1/TN0rjBqbTuEgCry8uQuRGi9nwdJcuvkJo3lDuLPTYg8H8caOa0pi8qU42TA0N4AYkmJSo9NxPNyNJELwHBUOkhj6mKh8+fr1//WHf/jf/cPfnU7XOVfO/OLFc9OaQicySWA32uwuXcP+Wk2P0MVVYW155CEslHBzM6hIYOFcs5+OBFLVIKFJ2c9CQl7iLZcQ3Fbx9ArcE7ewc2nnsH6uVdbFeGs5ZGpUX184p2Irr645W5gbOTGLedViboSE3//f/sU//af//Xfef3F9vd8fx8ttOh6P5vry5Velzs+fPxuGjURoOE7aUbU6Z5hd9NunT58R8zGfdhebj77zneePLue7o+XMYvM85vkQkxE92m77k1e4MUiYI7MQBHR50bufrm/evHz5eSB9tLtMMkxTJQtqlLM330ZDi6vdnNRdSZzTzd1ht+u2fc+NcF3FWRiUgjT/PCctcFjNpGOZprGcdDqUk8Lvbm/H0yEIiQgz8jwfT4feg9Du2ZOLj7/76MuXx1ev51bOYqoxUN9V7swMV5fx4rK/vAghzJo1CIYe1ZzVuyBW62l/JK9DF/OxjOPp0SNDUgiUDRMYkNbfBWTu4ovavj1ibqL+lu98fW7jQR62VqTXzjN+nqT+LX16l5LLgxnsayP5r03zhduLtbMDkaktatcW9KuaWUSQJEw4TbfUkUcMVzR2/oP/4uOffPFvP7v54tHTTXWtE5hDGXl/U8YTvAIeU7fZxItjnXXaW+uiVTHa3CD9odv1XQeni+1GS9Fcq1X1kmIgSrMeo1DgLtAM8S52EgigPM0lT+aZyRRIGxAggYahk9DtD3macq06TS5C7l6K5VwJwarMU6mKEECgIOH6jVm1UiBS+s6nkQJ51/FuuyGR5sc+jVkLjvvDs8tDSheBrV7jIBkn4hAJnmvO+3w6HrqU+k13cbXrN2nO45wnA2IIFKS6V53rVLnnbhhExG3pPcSthWFvlImdUhcB8ay1mvR48v7uvQ/eOZXDl69fjjUPVyHunAJCBLOWUmudy2zsGLrQxaS51qzkZFahlPrYSWed77ZzDPOj3dPdxa7kentzdzyeJDEzn/anuAl97OBFy0zsIRGLl1LUobXwPHautaiTZ83lVHsbmuHPVCc7mVulbgtntapVQQgxMEtRzVM5TIe4HwsqBJKYEzOTV1R1HgCS+TipVonRYVYrBUDB0Z68s3vv4xd/8qM/qXzsB2yuuovEuUJzdPWXX133XXzn3cth6GtNuRzgyrkGjkPskm+08sZghfJseVYzdbBnz3vVajnPprrZpovL/smTzW7H9N7l4/7Jo8cXIVgp+7rfb/qu224TWAxD2vabLnTiUmvR7CXrPGtxkudPLtX1yzcvK5MMqWgdc/Y4aKdHmubj6Yvbz5/z4/icsh7cw5Mr/e6LJ7/x7vcEw8vT7R//yZNPfvbzV69vcrHQD3/680+MQ61lnqdxmmaamKpIUTdFJcFm0GGw3XDBzqf9cU556HaPry42XfruR09/8zd/7e/87g93IRWcTnr38vjzn736xb//yU/HmV6+LuNMxxP2e9tsQ5fC0LkZHj3a/NrfelHmr8bxNI65TLlOlEsAEVTYIMSbbci53t0cXk9vdB5Po0lAN+y22+Hps8evXn1SavWay8zTib747CaPfLvPZQYy8maOxPWou92mH/rN5iLbbD4TQV0RA8xnnw/T1BVsth/2qTveTdxR56lUg0Hn6kXhgABueZ7/X+berFe67LgSWxF7OENm3ukbq4pFFllNUS212FLLfjDsdz83/OQ/YMD9t/rFD27YsOEHwzDQsIEG1C3ZMtRuSU2KpSJr+ob73SEzz7D3jgg/7HPy3mKVaMGk1D4oXNSXN+/JPFPsiBUr1pIkuWjbhLpOEsBKWpGK6mSHyr9fAqAReI2BDw5lS6JD9fdYy421j05LJiJYxGWWzjaJVi++hXRVUX81pUc0ogWJwpKr1tSmKsGYmJaiolh8whaGBhEvxAIiUnkw/jgR5ats/XIgVC29HwQziKl63dSAz6jry5Ile4IAsqTWtaFlqH2wStzX5VSuH6yynEEfF/leXlrPTFCiBSXwzIuOxC91U04EsGXNqj5nC6pIp6Vt+T2dAKxTa7ZKM58gLVr4XAtk8ejn/48k0b0tN+HDcJx989z8DVjSN1+klT/1+IC/dftWwMVW+tmqbv7tGJ5zDo/O6W8c1Tt90C99sV9vb8vPpepbRjWBmgs7nFT8iaq2Lj1+/ze2X/46f8N5sDW5OuGxIFgd/wGpyUKpEFkmqACYMXxFrSpC8ECrqSygBeIigGu+WAFxNU91MLmybGrl7wAzeCJynr2rcA2pQcFVTZLYsXcGQimmTp0lKxV6EYCqq4QaGUVVgRYzU8+uSomJmjOHqjFvICUTk1JM4QK88wvnjavUrzEz+WpBIdnUBEJqTCCx0ymoI8LEizDzWtTWk3lCl5nIuKawVM3b7HSla9VOMEfO3BpBiB3gVqx/mdhdAF81rbpdC79uKReXHRI5XsAFWgekV/H/9X745h1qNXypERyBeZ1nqr86uf0x8RJ7a4Cmh1u2rk4OEJhhmduyh30s9fcSGOsv15NV32KojZXlgLC2JtZbiKhCpY/cOZbHYDmTK+0HdW4dSmpsVX1dxQBDhDG0VrpQMjn1bbCuoAvGQKtFI1DnvdSszuepVnl781TnP1HtokFExlStJ0FE5J1r21ZKubHkPKSivQ7NJjiP+/tjSiXn3DYxtuwcnj1/OqfjNI9ZBNC396OOcrXrDclHLalKUKpzXhVFUp4TVHIuh/1ggKdABA9jMslpnksKydq+a2LfwRGleRqn5jDMc8Zwd4h0d7kN7aZHB3hDqXxochBVQlEyIzWuLpagJT044Zt1AXuMji8NluVBWG7yh1HlJfhQBQfxMKpTITHnnDwgwZV/p0RwzpEEJm5C23SxxMLkpzH76M4vet/Ys3C+63Zv7EsRPRzu2XsfXYyiRORd13dFStOG2vZrYnwz3xaFGZyDerICsCoy1IXgY+ODhVKmaYptaNmRaC4qy7PgqvbvQ2qwHv+j1sjavyIwWMmYDGxqj3o2BtQe5el2X2Bl0OPHYt037MHL5mFbFAxPf78mL+sKsUqSm6217/K0PxjSriZc1WMDBCaxpa1JAHn1AKq+W1VGPK0RBJAx1GBcWwtl0YpaLnQIwbAQFVWZHJmRZmNzrMizbXatc/Hu3WGYBogAyo5uD/s/+bM//af/+X/Werw73MJotzsbxjHETOS6poU5Ik8huiYiVD+dCj4ZG5zzilJTt4q4BrKmjSH0pYioOuecc9XYvnJs135oVVpVM4VWps6CZNlKtsIqhnW6LkRUxyXsIatZoQ3AiMFuUUdjo0rhrDk/M9QXKc4cCECcJw2+f/r8PfYuNvz23fWcpi+++sXN3ZsnT8+d14vL7c3UuyxOMGOwVGLTbGL/3ZftLPN217188nQTw2HKYuKdNa3fnnV938ZADMTgPJEnDuQDeTaozj7Y9f76+vrLPI2b8wtVdzdM4yFvmy52mxA6QgSFhqNAq2GFQB0CEHbbyyaSlTKNM4TbbRO5ydNwnO+LTrvz4KLd37/JnMULk6jm/eHw5fWbu+OgUGZcnncXFxfEqgUmRUsKUZ6cn3383Reb5p701Zu7WRSeR+/ZsUJRCrY9RS+mImUCsO0bBg0TpKCLXoStzOy0bZgFc9kLxu7KXnyI15/A5soShErtjDhiNoMKoEzkqgMDwb65TNZ2/dKveYA4l2xnLdlW0JPWMu205NJ6F50e769/hC0kwKXfUxdYR6RkIDAxTtZdxmYoKSHYZhdHTUYYI/7R7784e96/+6vb14ebj957ujm//MUnX57vLiCd5UHGBGUytsB+1zZs0UUCSEAuq8AUXdP2Te855CRl1GmcxmGvos6LPhfHCHDkArlGQgOWruldYIEUmQk+BudcJpO3+4ENZsk5C5GH8aimIficS05GRDnLNIFQTKmUarvlHbeOu6IgwDs4bkrh29shz/Nlvw185oPr+o3zuj+8a5pNCHocU+QWkdED4lAURsTEcGriilPSMpUckonOaZrzDJhrGw4GWEk562xirEszpuQyZ8EMNPBNxW6NgogkcnmzQdOH86vN7qqZ746JJgrYXvS0MZAQKYGCoPHORfJwvW8bCpOQJNViaZ7NaNuhdY3rfJrmeR6fvnjy7u27N6+uh+Mcek/G85Q8k5VaWwoRQqB2E82jzIWllIKihZVDgzbGvNfD4dDGhjfQ0WRIiPBNM9uc8tD2nTkqlA24vbtPKU05tbGfcoJzPnCIznkyaCYzszklZuLgVFUsg5ZZKjj4ztodt1t+9+m+26DbtNF3PoZSclGOPpAXGOZx7GN4fnmh1o3DeP/uMI6Da/qLq8snz57/L//mX1rxw2EajmmeVRQoRDNh8RuBc0fvQeabjj7+rV36MTe/d/nRR9+5uug//+pPIpy5IsFJ5xikSlmEyYSKIs3pcBzGqOdnzdOXT6/U8v1wEFViYk3zuH+dJgIF759eXnZxM9j+5vVbT3G37fum2Y9T67dXffef/sHv/if/+McVi3Yh/vP/7n+Ytbx68+rTn//7r96+/fdvAMPZFjEgRgRgOqZ5SGO8DQ6B8OzK/+6PfvyH/+Qff/z999vgzE3eHQd9rZzUhuPw+hdffHIcD8B2zmVMZGZXlxfDcPjZT3/RBP3ow83Tp13kubDBNHje9jsIHY8FAKvvm/5wnO73QzWtklKI0bZwHjGGIuXNm7fHwzgMo5XWlEvq7m9Lniii8TBz1lrUlLKWQx6j68OumVKGkvONMzpMo+PQtI58NJRSskKPh8OwnyXRMGQU0gQk8YD3gYmtiKpWbdyatkOX1jEtUeuhSqG1AbAk+AtUtNQFNSevCaadsqml4URLrKwNQANVCxxSgE9uOFYFJk9w1kN/6VG01YW3BIPOYiYQpaXvravz+iPxVpwW/q9lYVWpuYpBrHH/VKSv+FqV9F267cuvFu1TWsW8apervh2sqhWaUrVqa0SVnWYL7V9tlZqlyu1nsAesqIDgHDOxaLFlcKIOKa3JZRWgXc/tUriv3xkrulVhhhN0tZ4F+6VXamn7GGn5OwJbvrl9K/Lzzbf5Ndt7eNOvg9T8mkdYc9D6/1XN5Fv31jSNrtsJ6vrNbqdzQuuA6K9PwqqHUldTXe2eABAhxmhmInWoDjEE55yqliKlyK/30fbo4VbAmJ33jhhmZKYihsrzwjJM6j2z987zlCYzA0Srva8KE3lfla64qNRdCURFauvbOTgHckbOm6mkUrQ6vDnH3oFzySVnSNVBNynZ2CwYEdWJfTMrSazqdoNN1ZICULK5JHZMUkW2dZZZVW2hB8AMqiKzkqJSdIoUK6eJXDDgmZ33IXhVUS3erNoIixQpBR4AsKrnLH9Y6xNAVElNqzb06QmvQIupUVjVg61GZTMrZlglget3VIJBQawqSzxYoVpInWqj053BBojBMVO1JGICAyZFzExVigk5w8IfWmY+TaVIqYWaq6HNETJoxa7WVQZQp2vLgYhImYmNyiMYqU54sS5zeAazOiSFGGphfAp5yzpE9Oh+W9XwsbCd6mUiXq2/bLU+r+XlihvUGhXLOrFM3MOgVgoJefZ9dCHoJHlIyICZmFglMDrSxY+RpUI1axzPJaMeIsMzMQeYFS2VulsHT8EwR+SI+NSIATGXqVT6WEooJdWRt/Nd6zyNw5ygMeLJ8zNlfP7l66Ii2d68vsUe2w1ySimNRLrbdDH0aZgbOM9p86Rpz9w0l8MwgubYRik6HzKz9H0box/H8TDeb3dnzF4FgQMxsQkBJacn50+eX12Mx0GNS5br670oZ9Hb24Mk9+LJhx//+Ad31/f76z2KeXIypjRlZ44XwZ5lBfNMgFtNP1dzgtNytYicPYI16dQ0Wy7rusKtAY1XezvHrgLNMGEDiWMwVxcZ54hFMR7GW9xy4f27+3d3e2avWnZX7XvvXf3u7/8WBCXLNM3398k3qW27s/PRRQKMGcp6u7/NSXKSXGi76+ZZXCCmZp7KmLPj4GOTplnZucjRt9N4SHNyT/oYYkppGmcIVHOIscp3m1aP0tNSuNwDFeaoQqGVi6G0DFrKwmRcEaUVSloDBC0v2tcejb8xXptZKSsJyNX5fjNYHZO2B1pQESGyVbeJ6tATA0TOSITBjDqGXC9P7Vdkgpl2oTeFkClBhBZZu+XxVSjMnLEazFgcWBf0t15gxWPFVjHJcsjFxRh8XzJJZhUbjjkdJyRwz5uzLiu+ePXFX//1z59d7jx7UyNzJeH2dt9tdrHd3e/Tm+vbnLE/TuRjBegXUwUYsaroIsYIgKG0GCWnlHIuC9D6KFdbhzxhRCWVpYFLS8ehrof1MtXUeHmVyVXknJeTXadtFxx9kSar2AMMC6OGUSeStWYxJmaK4Pmrr4Z/+b/964urlx9+74Xzruv9zz//5P/40z+6vr4Twt1wc3V5dfXksjuLTy6eblyTh3l/c5+meR7Hj3/4Qxc5NlHLdLy95Tm3TWw733bctj4EHzwTycXFZWQfwEzOlFLK8zxavPGcX7x4QsZds41uQxbby85x73iT4MmEjNSkSMlK5Ng8FUix+ezshUexMo9pSuN0+2o40NBE6zZNYBAntRk0jtP9zKWEwCE03bbfSLF2mN+2Tdt1G++9icSAbdf1mzaE2Pbd1dnF97/z8uPvPfvpZ7+4OQ5l7shJu8ndVmP0ni6mPKseITkG5r6Lntsod/fJMff9ufPMVGKwyLvD9RF+eP8HL/5g/J0/nn5yn3LQmHMpWc2sic65kFORoiB2HE7g7DefQH0wMFyKlEegVc0AcQoFtiJXywPqV7kMLJgzERYNyoeNlVnWHHLpTira7YYW4q/V9M8jOvZjOvR9Ay+a8OKj5od/8MGP/qMf/rf/0z+3iN/5vR80Z81f/uzTfGNlSIfb8fVnKe8Bp95lzlPrx6aNV9vzMY0jD+OEotn50IQG2fbD4bg/OuI8zyiAx3aDyI6dN5VcimZLOWcrkNlFFohaIUexdc4F+PL9j3oIE6uq3N7di4zOBxEtJZvBOb+kXrkA5JwPITRN03VtjPH9F1dp1mkqaZY0lzwKsmX2795MKU1Xz86bllIp05RE8rv9vbNcGjr/4OzwZpJZNM9KQCQOrhwFhuTL4WZ0HbbbDXEQyZ6XDoRXEnXpMA376fnLp673sWmJ2WbNRb1n86KqSfKUSmzx/IMnL95/0p/33KE1eoadOuvPevFZVKrrMbzvgmPngkWbbZxERtjIKaWUirHO7aRbbZoYfVTBX/3sJ5vdxdnTC9D9sB+rRVFOmnPiDmct9X3oLxo0lMpEpOwAhcCM5eJJH12cu0Jl3DWB5Xw8T9NdmQ+la2Kei/OkXgNzaLfOubu7+/E4wHN31rsmpDxLTlkFjQuNC5t4/mQbXMy53N7eq1nbBPI6i6jHxfPw3Y+fXT3rU94PM9rembhpNE6aJzcdy/3NMc0ZVo430PfC2eZFGUvel4+efPy9D36rDOFf/a//13/zL/4I519nNxIghrR0u4lRQJNaaMpwgz/62bs/+h/f4fzffPAxvvOd7r/+r/7LMevurL3snuHu87/4yR/P+ebZiychWNPwdrdputhf7aKee+vOL853u+0vPv/8+vaafXz63ofGNKY8jENK06tXX+7xbj5/ebV7uu26V/s3Y0qbsLWU2XLjO+cMxiYoefhn/8U/JTjACpIiAUbQglSdjRQpISXkAiJ4hRSbSYXJRI7Oa8qjkTJSKdOr1198+tln12/vru8G8rofxjnxnHhOKUT86PvPN51ue+Iyju8OPloeDsHa8+3Og7/6/LWoKFmMsW9CKW6YxmmYHTOR44B+08TIh7v7/e2rpmkOOUlxXTzzvs/ju/mNzjYv/Wpv87HAMmy8fztcvXelTsUV38ZN11kO+/3+eCxkzM6ONDJc3pe7twkJGABH5EIXm+i8dy6XlIpYgQM0Z1OGsompkMlDF5tX+s9JtX21AAfoJEdRB0TcgqnUbGoJs0sCRcvsCJtagUHEoDE06xsWr/fqLOQeNQqs1hBQqtPPMFMDNKXZeXbswKSqJRU1kAOZMqoTYA3qVmc+TpAWCOyd2TodhSXtYNK15KlrPgFKYKMH9IdAogUMcgSAjE1MTFbxa6vCVgSQYztJ86yfa6nUOXZCYHLOQZlEyqId7FitqlDVco4XM6zlTGqlrRHTOnr4tWVv0WkFfXMhrCMgp60eCPGC6mjVclk6NN9YRP8DbR7fQLb+9gjUt77zRML61X/7TVCGHklxnQCjb8VuTjv/e4ADH6OPv6Ed4rSzx7v8JbTu9Ll/036+9f2/4mPx0GRXBdi+Ni6hqivRyFQBVVJaW4urdt0CsjM7riN7gDK7Gja8c+QXIzyIqpqqVMnMdfjNYJznWZKqYXmMlAAyWdwIGZEcDcOhwmFr3bzeBQIz9eQNqsWsqEkFHajqR5BZTsYL44BgKFmI4BwT+6pMUW8tJlrM0qwKu6uZVf8unIhIqL12OjXelxO9ahauMDwRcYFVtXd+CINmyyz3MmutpCaqy7DSio6frs8CmC9cLVvVWR7PKtspTlfotmqB8emyVcE/1GNZlL1QazmtbmJL8l2bAlpZuGuZXVWQVoeB9T4DYManL2tMZEQ++HWpWu6gpQfx9efVUaX8Gq9Nk4W0uwjKgMyM+dHKUdfE5XQs54bWzwDmnNjYGTl2FJiCMysoVF08mNkF751XqfPnUOPqrLvsTsWoAmjOE8HBKMAqu0uIibwjj6p2uiw1VL0RCcYwgbKpiRbPbrvZNg23rSuQpvHnl/39fpoOqb/cxE2MwTW9b3p7/vzpMIUiGahcL+HIfe/7zjfqpykb8pwzUVbkOScHsDPnUHIpmSSZUClFffChaUWSqc7DlOYpOC/B55JUYQib/vxwczOmEkJqmmaz2wx3g6qQgh0ZGwPIlVQHp8vAICpHYUGmbCFfyXoP2+mynK6Hndoyj0c0aX24ljlaLH4EdOrkoHpVEmBMLCIO5CmUKedjOdyOOCCexZR0/+X05Kxc7C7u7/ZpnKVIE9mYyLvdWdO3Xb/tu749jENBUUcaHDkSMefIBxdcZPLEgZXLMYNAZKKFQ3A5GCsTieY5TaoZjHXAhL8WRBf2xemhNzJSVVK2RZUNKgC0EkABEB6SA9MHFXxaQ+svr/zfJmV4+uj1VNsKF9Kq/ffwtdaq+XSRmIyZnVU1vRqhHAMiqqJYXFEJCqGlvVmBF1niUV133KLppNVLEevALhGAUgpWKmfRbDBQMIWY+BCHcTjYWNuQLm5ER806j5mZi+DLz756eXVxttkdyzAO49PLF1++eZPVh5nH2ciFkgQ+tB0VFskZpQoTQVSYoQoFXGAXiDxlyXNKNX7DjIjpZAxRScGqeJxMLxfZ+NRrwIIJUoUh6rKx/DhBU6cZ6wXW1DUYPzwStZNsqqohhEBRRZlNJX3y+c14FOIwTom8vH79Zk5T0xOz3d3eOeaLy10qlvez77Bpmu3zFznlcZqeXj01UtF0v0/T/hCNKEJkEoiosFguxXFkg6mVUnzwTWzAbQz2yRd/9vTF1fnm3MSbBpAPbhNpOya7G5PlWyCYUs7zPE9ZJHYb3zdZ5sPx5tnzjTI67p6c7Yovd2+Pw/HOsTvbXpAb9+PnhqHpeNs0mvIxT0LwsTs7b2Kfrt+V7aZpm8aR8128urxqmzgejxK1ZJln5GTT/tC6/PL52cX2A98w+QP8FGP4y7/4UkSUBjGN5mAdm+Z0SHMughiCd8GQVSX2Hbl5SG83u7OzJ/7yefPukxzBjpzARM2qRzHYVBwHhjMDQ41Uv9naVf3av5kBOrFvTz8rUr/oTJrR6mFxelLX54Me0S3XvyOqvXHUue36IY5RSxHVGmIUSmqeQ8pTKrK7xA9/+8PdZRjyPXtsLi+TleP97H1/u7/Px/F4O5UJTWw2mw3UDveDCZ4+u2o2TUozKbUhkPfBd56a4Zjmw6RT0WQgxMbFnjadj64xqLOgaRxTGoc5S84TYheMTaywM9Ou62IX28NtYucgOs3j4TB6DyIpstQ2puKcjyEU0hoAq7hKKRnAdrudXCplGo5TngvA8A3gxvt52N/4JvpRXMguiPOcSkIB+bbfteP1zH2kqdpWEDHnoiqGDDDEofGtD26eJ0mCAjgyNc1SCiDY98cYOjMj8qZpGgdScILMC5lDG7gg7TZYyPvhcD/dzpqMTIYSt4HYBR8bbkg8PNKxHN7u80HnY9ZJNZuJFlMlHPjgnGu3rYn0XT+MUzUIs0rfFoUyMuARPceGQ+C2DRatsAtCLYgDYmh3u+fJsaoAACAASURBVC7LLVMEE0UlP7Xn1MT+Rg7jYJPtu123fXKWppIPKXJb7YBCbMXkOAzGiIHbbe8DA3maR5nQg9pdR4Eckwthe7YBSsTkN3zxrG1aPhxvrvc3Z03wLqq6ksmZlcwi3lE73s9Q7Bow2LJ+58XLzYdbS+0n/+7z//uPP/vrv/yqO9/O1+K8p8DkABJFImMizlPWUuAjOW8mOatvuOtIoiadD2/8l4X+xX//vz97vvnRP/zoo4+enV1+9+Ly7Zs37ovP3l5c8LNnV9FzrA+qlGzJWWhD2LbtyFHFrrrtlJKWVMQ83FzKkIdXfCPMSYVGokvatv393dvEw5PdsxCayI0PUU0lH5jISB0ntVJoNstkc9Ip2+wcOUctMEMmkzoIGZx3zKzlzRdvi6a4CaENHLiNoWt7ou7mdhA7ThkuwIUCQYw4P3Pnm7aPWuasNv/wh98bZ7l+O83jYLqtquF31/v7/U3KRs7XSRILUjQHz957ER3HMUSMYxrHIlmQs2SZ7xUDYttoEVExZRbyxHBkCekornfEXoqxUT6Ijdjsdv2mYVJvPs9ZRmAEKUzgOETuuhADEdSyZikmAhMYAaoQmLAJIIt5ca2OFu/zUwJvS74jp+i3NgMWQIUAtcqTNdVKlD7RluxRVNW1NVX7SrU+InuQVFiK5WWJX9dyMxiZmklNQZffKNaxCwB11sLAbI/C9bJXZqwGxevCD1uUuUCClRRPS6rwtcVimQ2vK8EK1NVTwIAaM+lpJKWW82vJufToqr4qsS0cKyyurWsFWhccLMIfyx8urz5elU713SM6ji72jr/KNHAtOU/Sq6fvir+H7VcjP6fNP8abHh32/3ew5tcEen4JMPpWnCvn/BhR+uap/41s3/zo39Sn/JJEwgJw6iLrDsNJLV712y7kqml1OvBf8cUqlan+b302xUyyVqKbLjd3fW5gpqok1XJUC3ENM8xclU94cR+tIn7rRImrvGTvyMEAFRGTUqSO4BIgCg+RCg+rMcHV6erqGV2DYpXBq7qYVmVbDDByC43DzEpRMrgQzESl6CrGtRyDWH3FDJWzRI55bZgudl1qpRRbdGjU1lPHzAINoanCSIuelgkYZA5AZZMykXMEoCJDoAWNJ1d9qyo0tUJQMKs1JJ2a86oCFWBVB6yoyIJc2eq5So8BnTVpXrze5FSiETF4UecEYxV0rs/FClOtFa5pVcLi00QkUa3ilthPFUxclMVOuIRW5UJblXqImRdds1qrV2wey/ddgvR6nwKnEcF6JEsbe6VjrWaLpqxVJGu1T1xXkWXm4tF4PVRN1ByR4+BCY0IkLBCr+vJiCi0VAtC6DqwLapX0X76gmpGCiV0Vu2ISgSf2vK6VtGAyWMFVIsCcZxeqZjQRSds2IWy4QQx+u2377kxHt708O86DC0xcDnd345ByUeed995AfddvOx/czK54RtvTVmMjsXKdQoRlEGnbOu7i3f0gRVKSaS79pt1sGpD3TMQ0DEeRvNt1h/00j8PZ+ZPLi82rX9yUYgOGL7788snzJ2mY5uNxuh9Ei4iaAOV0Kany46SOstY71dV7bRlZWy4iERMbnTSEHvKLikudMFZe3VOWNY/UCEqkboEQzaG6AYLI1NrY9nErQ5n2ySYL0SNbaMI8z2ft7mJ3cX9zNw6jqmx321SSlMLOdX3jvVMtpeQY276LRWiaUxP8PJkcJqsj0ZWBowIGO6R52m5d2/kQnRmGaZxTBgMtaOaUMlUzuXq8/MAyw+mGhEH0AXcmq88v21KU1nfpoz9Y0Cv6Zr/rQXJhOZ9rmCciOA+YqdaZQMFiPGgPDyXAYPa0+LtSxdJWkteJMVLnd9XMRFeSY20xWGJl0dpqkJV2vyyrBGMG6kjT4u/G9WHAIhi19huXWt6rWEkSW4digswhGlEMDccwz6OIeI4vLj/4yU8/+fj7H55dbmEE4R/9g985HP/tp1+8EduTi7vzF5imeZpjaJzjNFpBRqm3mjnHmpUYTRtCGwosz6WU5Dh6R6ay5s8L3qdr/9QUvgtSZKWRUp03XwN1fbJp6RWbgR3WGEBkVfD0lL/VrNAqaHkyM4SxZxTYIh7HBQKyza69vZsOt9M4ZebQNPHdzd3dfm5atJvm9vCOI55MV13T5GHCmP35k2fnT+JZnOa5i939/ma/vxsO+5IyA2mGMVx0Xde0bdt3fXC+CQ0UxbLZkuU6BB/Dcb9Pk276qz6cZ/Gv393d373REpzr+3YHy/Oc9/e3x+N+LrrZnfW7zZzH63dfKV7Mx31D7sXls6dnz14+v5jSOYc5m9zfvkvlfnMGoxIjebAVcT70YYvg3Dz3HYLXeRpTmpxrSyqDjAZ4v+1aX/KcLMHGplHf++BVRURL47HdNN5x1zVwQWkWmQjmvdttOpg/DEnlaBpBxaDsfOjRkoWubK/cj37vw5/8z38uOwWDmaSKwJGQMYQAZnipoPNJT/Hxo7iaEdH6ANrSkq+w/lIyKRRQMl4KFgMIDHcyS6kevYCtCd6aTgPKtrJTFiBbYIGhBSoi1Q3WiIlC0wA6Fnn6Qfzebz998dFZ+9T/5Od/+cMf/XZi2Y/zl29vj8fjuOfGFRHu2nbT7CK3aZp5du/2N21sQnuW5nmepyb6EHwMUTPKnNOcK4mSA7dt0zSOSYfDlCXlnO9vhmGe5lmUQGSOncKOaShFx6Ntz9G28e31ddM0ITqRUs+Vc8F7NoNUwRc470MIJFJySjmnkktyyTkfQuec3246LWblkJIii8xihG538fzZs2G8yZoAyrOMh2NwZdvGs6vNxu1++vO/al1bExYrCqLQeB/cnJOppjFr0VJ0HEcfOG6iiJbZwPCdg0BVYxPef/ks77J3XuY5jeMwDG0TYueajs+utuZzljLMx8Ow38/qIrrgDcEROfYwlyeZb+bhXb5+dUuJ81HlABhiYAMJ2d00DvuxOW+2V/3Z+WZIUwjUxNYx34X9/s1eZ0WD3a45e9r53gy5SHHKZALAO4AQG991frs7dyTaEZXSO0YXG+2Dc7Eb8lymIYXGQSVTUZkxEznudr0aDofD5e4qyaRzkqRKArDnkKf8broOMZ7tzow0lwQu/UV39f62O/MUNJUJZBeX53AEK1bYzB1uh+FOUBxmwMMZutC9ePJew+3NV9OrT68/+Yu3n/zF2/EGuxhKaD0HNgcVRTF1ZAolNgTfxaZTw5QmsUzeExGH4qwcjzTKvP/XP9ls8MnPr3/nxx/84R/+4L0Pvv/i5dObd5/P45v9zX06zpve9V3vfNv3Fx4srC+eXF10m+NxYObonWt4Ezfs+DAebg/392kvd5pyaqR94V9S5GYTWvZZj2l/iC60TeeMIxxUweadKmbNR7HZOzGdPCvBVDRLEZfmMu7vDqa27bauaUV0nG7Jc8vBe/YhtE236c7Pt/LeC5/V3t68a7qm7ZoQrO/DDz56zpZZxkGciNvfTwrtN917Ly+GsRn/9LNxT6/eTsMM73gqIwgXl5sQmDQ/vbq4enI2zYf9cb+jqFrI0IamDRtyuxfPPyhdLnNOx1mGEQIq5CITqAw63s9taAGM42SYvQWbIGypiIkSsiNy6qJD2+3Uw5SCixATFZEiuUDNoVoqYZWnXUVqCVia06t5+9c6naeQigVneejNLdKWWB3aa4phUgUvadkV1Qf+a9qDJ6Cq6jTUlypcVTVYTiWEmbkqSCwVzapdB6vtptPeTuiSLf+sxwPnqjV3TScqncBWXXmYQe0k5WCoON6Kd1HNICpxvVIoavkHhoG5tsa4yEkqbK35DD56kWIKFRUSVTKncIt0kpSVCrUMYy542SMkYOE9rKdiuQSn1W35vIfkdjkBKoIV53LM7JzBSi3cHxbLvycA62+5fY2B9RiQ+7vevhVzsUfbr3jbr+MG+LfffrOg2Gln39yrKuoERH2srBIn1+0RPPf4xWU//69f0h4GoezxjyInkANcEVxeBkmqLB0MWpaHQlf1hgW1gRqZ945dZTuRJ/LsAYiIipmqj87oJIhjKFADEbVxY0CecimFzUs1YrDMylR95ERPUsi0ikpXvXQStaLFCsy0KC2OEKj1WUWc4Ja4x0zkuVoJmVkV2RWpPzg6X4cEDQoTIvLOP7DQCCfJjFrUg6p2r9VegVRspAYxAGZOSFdUD1hIQ+ROnBQyJTM2WvoDAFBdkghSCgy8nHlaFWhZTRjknCdakmIDFr0OoBIuoALGEvRpcaslgsAIylqJYbWyW4aFFwoaVyrSgmFWcGo563bqcwCAnTSqlv8YBKWy3Fj04GBekcF1TnFZFNS4XqIHZKquhAyiyu115FFYrcreVzSpyEKjXSi2YAI7L6LsHMFxNXbq2AXOM2Q2K2ZmYkWt3gGLO8kDn4UjTMxMpJ5uQKAM75mo8u8UKDX0mzAABgNkBsdeVIiZPcRKSmIEDjwlDY1ru2a7bdoWfdtdnX8/Jfniq7w/Hg/D4dWr66QzOXn69Pzqaa+af/DRh4e714vMj5kZhdbRIjbmugSZESLahkIIbQSR5VSGo4BGHxsia13jvaU8nV1uvZOiTb4f0/72xbMfbPzu7c2kGr/Qz1+8f/7kOy148/oX0/5dLsUD5IMSSLJC4divM5ayuMwxwEoAe18vmlVkiutMpVNRsVIxUzLC2vEBAOIq9u7gFWIQWh5jNVcLSbBH0YpDW4xxnvLVtrm7yeNhpEIxhHGcfWEAm7a/2Jzf3r0e9keTsum64XaCK84FFw2s0zxF3zJiE3e9a9qQx2ne7fI0yP1+nEeFxWlKVMj5JvhQbEg5MWnOcD5Ox9x90PddXyWsARjrGnJAAJRKEdIV/rTKW68uFQSCycIghICY2ZNVw0NRwoIxgbDQNCuWYlipS3U2lhRrwCEA5lbgdSF54dT7MiY4IgW0EsUEZFR/OnIChhiZKomJGsEHZ2S2Inm0NhJRi3gruqwNtmZAC9ZGWkFNgEGOcVIFY5CpMTHXKfIawrzBSpJafsucm+AFZpKIiMMSBcgouLDdbH/680/e3v9ed7nJWV59+eZHH//2X/7Fp8O7N8ISNiXNOYuWUiyXto9XT3aa5Xi/n4YZgAsOzMzON9HFoFm8J9d7yUVr82cVZwWgorUzAgAOq9lGPRos+eeCzhlqMAFVCls1U1tOFJmYVp/sRwOHukQV0grYVgyMmYxQRJjVYCIyT4Dh008/f/rh+YcfPpvKrRor0O06RLRxV7ztyxSMXXRGdpyGTbv1LpDxdHuYD2M+jjJlUiomU8q+D5vNpms3MUYVhOAaHwziKHrnMlLOJaUhts/G6ZAt9ttz5e3rt7c/+9kXr17dPH/+wdWTVkxMNZPeK10fc8pJug6apnKcZPzpT3+yaWPrAxlvNheb7Tn3CGhmuU2Smq4TDHPJ5EDkgoePjXctOZQ8Pz27nPV40DIOxy9uX5Nzmku/2bVnuxCajhy3ISGnY5rS9bs3nx0HVcPFVZD0navznTEVc0khwqLGpE3rjYxcyakwW9O4tm2ZqG0iSVF/vHy/ubh8D9s/Hy03LXwLl1GO4oLkmT1vmGI1Wzau+n8PbZYKJgUXanmDxcvBFtB5EeRdK4HF4cGt9RrBQBxAlW+psAKSZap6gUMZdamrt4qBoAwjI0fQKXkfnI9FLBUj55RdciJRMOO7//HV5YchXd0eOW++026ebe4+u75+dRxuMRw4ZfVemq4nxzLjOI+SEhn1scs5jeN4f38oljgYjDbRSx1CSUKRLVlo/Wa3dY7mPOz345wmyfl4Px1HKRkuIHuXiLOW46DFINmgVnobj1ARgJkdAQRm9m1scpbg6e56HxrORdl5VaclaC4qZk7NKfm02TRd6y1pHkcmYU+aUmhCv+kkT1KyqpZczLQULRhYQ9Nq6LunL56Ot2na38OACHLMkcmRzQr1WlxRl4tmCcpA5lL4pPI8pTHlY7vpuo6aM+p77y1M+3A4kA90drGLjefIo4yppFRycM22UfIuOpfH2bwRuZTK8Xa8/mw/3wIDMCtmCtI6YyskWdUEMclsk8xoqLkMZ08b30mImYJmEZmBHk0Xdxe72PuCxMTB7UyzzTMJB2a2EjB7ot0mmEom3VyAcnLRk8mWmrOXZ7fv7n/6b1+XwwGBytakiAnY2AdmjW278343HTEeBSXDIW66duOhGNJoqnHj53w8jEM8t6tnF1fffZb1eJhu1ev2aV/EqZKp08L7+3T/dp4OCcoRMOC8vfzekx/u6Onrz/b/7k9f/8kf/6JjdLG1puxvb4LfqmSFM5BUZEMlkDrPpkIRDubYVDRjzGoUwQEuUmgdgw9D/tlnv5jpszG/+f0f/+C7Hz67OHvy1ec/39+90TSIE/Ox7y88bUQKrGwa14e+8aFkoIubjWXNYjMFCqHx3DW+iy603LabbsYct8HDzdPh3d07zXKxOzvvzl6efRcmxYpImsqcUi6UfGB4N6RZS3YxTCUVUzEVb9E3GvmAlFHiVS+qM4lpCYXg6Pxs850PsLtsc0nD2LGntmuqDFn0mazMpaiHC93b61ebzcX5xbOri6evXs9t6774asqCEOAjphEx8Mv3n2y34e7ubdvAe8uHdBxK38d5lt35BVvvNDQuvnz/4vbL/fGNZoWJpTnBkKuo8GTST63vMul+Hpn50p9vmn6/P9y+NRA2m7Bp2ja2zZM+zWJOmXyeS54LFStSSi5QYvbkXJmlWmLUZA+8rJJiBgNXT6aqT6krXF87e7W6rblQLSoUbE6soFSPe2UiVlOQGFlVlFy7BA/auSt4svQOTsJZZifFy2WKS1VFTY0AFax5wFL7VHrCQ+28dhlp7UFaBaO0VizGMDA8OavGWqxmENMqClzLvYqfLWCRwTNLMastM4KxgajS3NfasdbmtvZ8ieBR2yWKOpNoaqUIBY9qemRKREp6SkjNFAtpfIXAHuE3tc1CjpiIF38s2Oqqa7wsfzjxLrw7/a2gsvKXpt5asa7pzy9vj9T0HyESvw6E8rf8W/9L7/u7oDL97bfH0NXplf9QX+bvc1u4V98Gb30TvfrWt/1N27efQPr6P1ayThW+U60jtbU8PXEPFhO9igtQDUZVcEDMwcEZFBAjAZS4h2HhPppUiMUcB+eCmi1Dv44YTNBacdgipg3HbnnuUWFsVQMZsxGMNRWixedvIRepLQJQZHhghRqZEnNFM2rnXa0YABOBW8MvKoxOIBGp4PNanBAgvLCEUEWCdKEzLfmvQmuIjOYWUw4sf0BcBZysypDrwsjiE0+JFgSLlQsbUZ05qj4cYKLKiakB3xYkH4u4zgMQtKCKp2u0UCRw4o/YokS/pOM1ZrKQkV/cvnXB1UkIRMqoDWJeUApQxR4WLA5A7UWvOOP6HaxCjvSA9BsZ5CQxqA+3cq2VQVwbGrYsdBU2oOpaj+r76BTK9XVyxAohEJGpFSIHDyI4o6UaN8ABBKN12Gqh8joAjl1Z7MlUSIlJSYlAjpnNSrFavpwCPbl6cKZETLACWgznlKAEERQ1T57gmI2dBGfRuy/ubvY3b9/e7IcpYcL169F8CdQ5NzLl77z3MujokeeSp5STSmV5ee98ZKhoKps2to0jWNc2zoeUik9CREUUUAFIrWg2csWKkTGQDnf9+/Fst/v8eu8KU9RRbptzu7B2GNphlHx07MEkKKYZADx7A5MWI65GViAFLUpmtMqxVeJ3pQYSEZtTCNduFlVMtXaeKiWJlGFGSgvNmRnGMDJjPfk/KEFUD+OYUklzlmJOybKxIs/l5cuz91483XbN528Ox8O+lERk7IQcheBCcM45NuqaRiyEsOnazaan6csvvfcELrlIQRN8MgIxoCLKwY3zHBy61omyCnXNNvoGE8itVMCFgmVrzoEHdLa21swWofclebKq10CBGAyioqgZXcWR1xnoJW9YQJ/19K4ya6dEankL1fC4Ai0ErN6nlYKwOOOYWJWGNqaFOgQYigrgYcUWvwitgRjLbHCF5Jbp6zWJgTOrw7I1yJRKhiR9jE7D2KCktBKD18peoN55ADklg6mIqhCTWQJbyYUdlyTDmPI0fXX99sV33m+77TQOz65enrVnkuAbSMrTOBHHpu+G6bZ1vtt4mFedmTX6Zr8/xNC4EMm5lGQuhQHHpLCshZQduxPrpX6/NciSCa84fU3gjEBVcAZ2YsQaG1Gdlz4la4bF7gFifGKDLnBmxQKrAqGZrsxeUSM1U9NxFER8+uXn731x9Q9/5+Ppdq8mziM0oVCiSJn1brhrt9h2rZLOOQ3j0LiAQuP9mIe5jFlEnHc+ehc4tqFpYoyOCGkeIRI33rGLwRMwl/kwDNN0FGrOL54+6V96dF8d3/3Zn3/66adf+LB7Hrdhs+XYiZETo9mszcpHbqNrgofvdu0Xn37hnj57+uTJxZOnycmb8Zog540n52LXNi3GMho7Ijjn28BGVJDG47x/9zaINyqOXNf1t8f9bnOeQe3ZWXb+OI4pCzHFs37jih33U6N+xjTheJdv/H1WUoYx1DkjzCVZUTaSIt6JazVEbgI7ojpimdPYtO2Lp8/P3zvHd4EvbJ7hImJEOVgpBdYyB4I3FFABVW2R5fqdkiBD1WpcdDlPAaoKAZ9a21TXQVoAy+WpYFeNuBRqzHVeZYE5iVcYuwKdAMBmrsoPGhy7+i3ZxSb6oshOpM0SZ7yP9/7RZen37/A69l2Mm+u723k2lpaPubwxXDB8IHIylemYOFFwwUc/63gcBtfRUFIIXCsuChw8+5bRIkQ2z5tt125akM06TSLjOKdpnkYpM6AQRkmYyOZiJTOH6KiRHI57mUYoivMuRkcUnHNMgSgExwTOSVTIVI2KGjkQhEm1kCnl7eWuDiU6lS7ytj/3vtVERVRk+vLLt6VIjLTddbHpc57HYbjf3/HxHtmevP9936bSpHmcoDDSuSQkA9C2Tdv1KhChfhsEMqQEMzgHKjJJt/Nq41xmpuKjxc1Z1+7as25XWh84tr5oGcfxOI1zSillkAsuOB89OSY4Y4jmSfJUnHJDNotRYVLv2bN4LWg0EjuEonGa3L5YmXR677tX++F+mN6ZqG/k2ctN122abpNF1DR47xpP8DmpCXsXnTdl896CV1YZhyHNJYQIz+k4plK6szNPsUdPV8gHIFt/3rrgLBcuruGGc+Mcv/vqVmcAfQhkLMhSJm127ny7GyVdv7mWqeAclx882z4/n5Bvjnf3x2sfXWtx17emfhpxvJvu76b5yFS85eIajIp/8rt/uPH+3efp//xXP//kpzc4oDg6Spak7caX6WjwsKDwCjYhmJkTZp4leWPyjgMaDhkmnC2oBhQvanhydq607zeqZp998bOmwzjLP/juRx9+8GO8nPb/D3tv1qtbmpwJRcQ7rOmb9j5TnpNjVZbT1XLZ7cJuoK2mjRASFy1u+ldwyQXccNH/gB/BNXdISN1S0yBANCDZTbtc5ZpclZl1hjzDHr5hDe8QEVy8a317Z7lsaGRDSWZl5sl99rC+b79rrXgjnnjieY4vp/51U5nKbURcypPICAaMsZbwwYNnAO3E+TgdBu4vG6NsPLS1axDRkKmaJgMfh8MBCCY+5b1kkWHqp8Nu8wQEFSUDKBqonEFAixlgVBVQj8jeZc3oKw+kqIPyFMM4jW3bMgOTIKpIijkZh5cXTVUjUdu0z9CidXTY79+8e/3u9Ss0aKxxjW8qd3n5LCdVsFOIUxgfPnywP765GkEYGpLtBWw2q8fPdo8ebK7f0udf/OR02k+ZuxU8evLe8XbYrnZ5xDgooa46E7w5sXjnpZYpTaCARkuH1FTkW4/IldZt1Y5vTwCIREBMBqzxgNY6710F0E99UFQgZk3AkFIWKZxTh0hlYEfPLn0ljpbEG8+xVOct9V54xVlfRaiANVCyKwWh4qtCqmZWsSiNZRClud2P8xnuozN43pvnNzK/pTv+TSEcIKhSscku6dVMwgA4JzVzZkd2Hk3BudOOOKNcs79VyZ5IBEEJRESAAe/kTe6lcaVpbnCmjkNhcZSFmZlP56SSzqpeS7ZS8jqgYgitWuhQoqA8M0lKbrhMiYDc+z0WMA5mIhXSInC8MFnmtZpnG2fYq+xwhpY6XFVVszAVf+X/G8f/C0DNr3wJ+zf9qv9Gx19NvPr/j/8nxy8t5EKsOd+2C8NrQWOXY4FFZoEIxEJeAQIkJGNMQYjPFKgyq8iz1gpAJDJFWZykeGYDISGLcGbmYmlMQKSLnZnM8snqK3/GX5g5JQYFo7Ma8fxMFzol8wJ6zswJyQIIAmXMWFkEAMksSeuyCCqSAQiQZbbEAxal80gUABZnvju4+TxJo7O/WHFxm+NCMRNYOrV3dSEAloFlKq4zywWY9d6QDNGyfrN0efmFDCEZS0RZzgoThSqj88ZxFwWh8OhguYRwRy2dv7j4UpzvAQSFYhSgZaAGygh1QdmWAKcFcyPAAgzNwxaKWOa0z5NRqnR+qeX/Wqw3yvLcLxgAimfjeXXv0Fsp7Q5dDNOIgBZ6ECIUjSpdbFMRDBkkMggComa2dSoF+qztT4W5QkoAqAZNEQFCxHlrcIiWChVP+Fz/AiJoUWcEYOWmqTVFFREEIagrrFqsa7/Zdd4ZcgREShQ574/Xv/jyxcvXb8YTAAE1xJk1wu27feJ929Gq+a3V02coceiH/fGoMJGoQ7TeE1FXNZozCaJqTrGqnTFVtwIyhoxVgpQ4xiTCLGPfgzGSkrDAYQQg8/C9xx+e4BfvXjpobo+Hy4vVetc9eMLDUaZ9LKZ0igAWDRgEvIMVwQAwMikoodHZF+aOkauF56iLxRcRERUVbDoLNYnOrKRZPBt0buooFptQVkBAAhWdcgKG46Ef+wkiMEukJCgg8Pvf/Xvf+d2/Yyt7e/Pu5vZdH4/koW2rKQVjjHW2DAdH5hAlxuNYsbUO0DjnrLNqgDw0q46Q45QkhEnGbdse+lR1rqm7rHNYQwAAIABJREFUcYiIxlmvAjCBXWPWWRShuCoIIgJZIllY6iKqJHfJihbFGlBR42hJFoAMCBDcG9aDpeulM/fnrlsl96KzLopw5Tk/Jxi2PElnHT1QWjw8IbMWHF4RCAsRRBfxNhYtcH2JDEhna0ktWD6IzmRaBZAC/9PcFVzeg8yzdvPUOAIAlZG6GQgvLVgCzFpk1KFIzqGismQRoDJxTTHF29s9pvhHf/xHH77/8Tc++ag/Dd75tlsRQc4wRTAury53dd3SjaomQtvUtUS2aHab3dXtqakMGUqZpxCyZENGkIT5fkZbsDnJAEBg1JIx1oasdM68dSbOEhGoCtzznxVZTnXOcItGHwiYr2kUz3Cgzv1NgyV8IYIWCTJUYLFkrTc/e/Xl05/vlPFi99B5Zy0wc9JM2Vgy+8PteuU8IVpQgCmFcZqMQN2uWLMCe+/r1lhPAn1KcRiGFJMyHPZ7Agq7B+vVetOuWHSaYgwpBnnv2SeG3FfXpx/95E9/8uOfH0+pbbbPnn56sXumXJ2O7JwXMM5K10Xj1FhrrKmpUe3+4B/8w5urt2pNn6bXX14RmEeXW8R6Xduu3TAwgrHoEcUZ9Ah9TleH04u3+7fv3r2k02aze/z0ve3uAVaNq9rrw/7d9X5/fH487HOGru2224vVZtN0mwcPIQc9naZpTGTs8y++JG/qrq03jfMmiwzTGMdkjLHOdVXlnCHEIts/HNM0QVv1T9+j7bb+z/7Tf/y//Hff++H/8bPpiOtqJ0PisVykDBQBs1JSTIRWiibA0klGAORS4yzd05LTwEJ0Pn8wS43cJU4AEGQqID6SyHlYft6hc7EcLtA48Kz+N2/eAr6t+34IefIN+6bBlARObuXX77vf/N2P60fNIR0koXX17VV/+3bv0gZ6CNdJbtVtPGTInKdTDP1QY0uWUCGdcoKElXSNNx6MBeOAjBqkzUWHqKCma1rvXdN4QM1g1cZTOpx6gAzooeoqZ73xlXXWiKukUgJVPp76PI1Qz7mjs7Ztq8paY40xxrpaBa11wyn1ExRv1aYiQwgsysoZujoqg7XOGr9abZ2trPMpwzRNfT9NMXECJWhUydmu8UDUD0MWcNaITt0D6zbb4WSnccyZrTHOO0Nu1a7rah1CtBOAg8BTPEVj0LcVGJ84kpcp5/EA5KBaAfTXa+Ku3XpjVPUUDimlDMwUmXJGNkSu8VXVEFHdrVRkOE03p5vrqygjWARTQyFrhyQgqoIaAYyDLJACKPSH3NvDR99+anMQQOsMVkhsKt/4uqGcQopjGnMYGDNDyhCq2jln0RoAgQQ82nBEgGa3e1zZ5qvh5t317dXUr7uH63b7nW9/1p/Gq1fX+30PA0AGAhAvEMbTPgA4MMb5qm4cEKhMWeLplKUCVoAa1u81H332YXfZRh2/+uqrq8ONAKxX4Cwe9r3D9nATv3pxAycAC2Cgbs3D3bpt7Lc++c3/6X/4H3/y/S+e/+wAUhl0acwYREWzZBRQSIplmycQBMhqVFGNASQCg9YSelIRzgEArCXjaZLcbbcxqXEZDI4T//iHLz7/6Zs/f/rmu7/9nctt/Xj38esp9Kc9p5O1aJCddd65xtXgHLBJmve3x1dv35zCXi03TXOxrrMVUNgfT2OIwOrBbtputerWzo+H47ub/fHti48efmbAe28ILVo1hAnMaTjsh+vbfr+fbkMOGXLVtesH265dBU4AAmimmLeXrWEGAAYNKZzGqR/C25v97X5vnHnv6eP1dqVorUVjYApHNHZTrWpPztHnX/y5sBWuBFqR7pNvfPDhJ9/6vYHfvL2JrNY5Bm1b1/c3zunlxYXzpjCYbq+P/X7sb/PpZrq9OiFXkG0+kRFf29q3RlMOY2YGVAALaFRFbGXXXde2zfWrdzU48kCCkvU09NEGVKhcVVdN6EOckrDwlHNQEZnNOokRUFlLE3zGlO4VIL904NdHCe8lObMkrgioCCgQ4EKKVYBFybewhLRkjfqXISjn4aT7uMH5MwioqLLI8sx7+Tzmco8CMlcsS8trTttQAViWfG8eVNJzbTX/4C9VNfffmwCBVcxCCgokhDA3JWHZeu5AtRnSKsnXgv8tszuFOaD3ksk7LG/B487l5vwzZcRG5s7movaA58zyrwRY7pW8Z4zw1xWT+TUCsJYe199qGOtXjnD+ja5DeWDMQp0xxsA8LThbOy+iLl+LETMLSJWFBdSACnCpmqBUq5OQRXBoiQhQEFGREyfOnDjFPBMUClXy3jlBgWBGkoodWPH6ZZzdGEUFZzHoMzdJSzkNADHHZTTyfuk9149YdIABCq9LFk1xLYWrABSJqxmKUhUhQRW6g4cWclWBhHQJ5pJmh4aziPCCAQEKaPGFKLSl8hNUBrMIiMiaufhnBBAtNquE85CjqKgUNouex57PXRBaRkEBFZRL3avLCESZ2yxTgIWMUt7amZ6Ac6l6RwWhhY63RMkCYJUYWl7cKLDM1N4lOMLdn8scdVlnKGBgsRLDueydh7DKN+CyZxUUhGb163INSznJCASKmtEiF+RQVbDcrgqgqEBlZP3erbS0XBAQDKICCgqoIgiQKrICoFoFQDBIlrQQT+ab/Rz3EZC8WkIVmK8zqa/cdre6vNwSIQNXVWWtCyG9eff2xZs34wRgACxYZ62nnBKo5EmSgcb6qnEo0aJRJDHeZeayMETGOo45jmOcJk5ZMgAka7FpvCJNiVOKYUKoQRU4l3QAESBEOPTHulvtdttfvHsJINeHK2NyZxvjTbdtbjvOccoZVICsceRBqOgpFNIPoAVkFACk2WfgDOipnv9WaNjlWLBvXOg/SwdOF9bfAtgWkbvyvBFRIS00TRtDTMyAQGgAFC2ohQ8+eu/Bo8uY++PpZhhOTOydB4KsyTtrCQVImPfHfn87hakEMPrwow/IOOsdESgZaywbiBDLI+8qhwN46+u6yzEh2pwlpTNmWRDXOcNQUAIlIgML4ItcwsUcdZY06Ey20qKOo+VJOS8InM9YBnlVlZbca2ldLjpiyyqrCGABZmcaFp0zlsLELxgWL3IUNH8GBGeyvILwbJIIpEpAirhcJtAZq9WFT1ji453x5vlPnXUcYB56nH/fAt8sIZZEFCQXwBNL4CISFlZGBCJDRCnlIcdVjT/52dt+z9Z4ZVDFpqo3DVwNkBJYMlVVJRZlncIQmlB5j0AikDO3lRNVjikX7wqyKho5UrF0QCMsOef5yZeFCYNIYGAG82COiqL3d9oZEFTIInQnuDrf8zSPds/g+Hweg2XJsLw4ltFFMYhoEJCKJtDqYk0IEsLp1L98+eq3fvfTZ8+eXd2+YJbETCm52qrmaRoHo1RB09TGEEuOIW43G195aztbGVtTylMKmvMEylVVWbQpRVQcx8E7H12VoqQolWubatu6hynpeBpv38Wxx4vNB0+ffvT06YcW68PNKQvsdivjrDVSVVXmMacYAhqjQHR58TCkKUzTu+PNcBy8b+wJmXu4XK+8ZyVQS2SYyzpzf5qu3u1vrm+HoY8KLIfV7uHucnWxWQWFkPdX18eb43GcAACY2LZy+OoWRbbbi7pqjKUp3JzGfQhAwmiT44bAEFlVk1K0xhJaFsCszpIhZw04F3PmEML19Q2lz7/7e9+9/urF1fN3P3p9wyNI7HJM1iJgAAxgEiijLo4L93crAF7Q9uXpWB6S882x9HLgXppanraFuHreyO4a6qAw2yEDohhQQ4tvV5FOmaasBg1R5CmOE3mABnZPm49/59GTb1y8vPp5MoNv/NCHvuc8YuqD9HZtV3bjJtZ44hCyBnWmIbAp5JDGlDMgcMrdrrM1phyIRDSCqLFQNxWnbCwgZiBjHPmVQQPmaCFkcFDVrlutjTFIpqor6zyAjnE8Hm8zjyDQtEQkpftjrQOknJWZGQHBbFYXHPfjKcgEYAEtoRInTUFThK9eXLdt3a5aV3k0JrPkPMXMMUWytL1YpRQRZAqjdaZu1t2qA1IA7aqV3mpFuDLNTqoQQxpTjOl46vt+HMLg3F5EUmZrjFqtagIDaNg3pmsatcFW0a9t3bm6Na4yimaUXrOeTsdxSE3rN+t1a7Y5yzjmzOpd7Y3PzF23UWHNZE0PEoFBAGwNApBFgAUIoAKoLRqghtgD1EAXUO3gNAxZ2PmqtpVMcrrtT+NUx1C3LQNf76+OIVcVgCmCOxkaW/yDONF4DRU92HTrbX1pyU+NsQ/Wlmpv29p3QzVVpucTxIlHmqDk6MiiDJqxJp1ykiCJ0DC6XK2wbvAQFAm+9ZtPut2Kajj2N0Pup2myQGDR27pxq9evXnvLwwmBKzQIRhVT4+2jh9tvffPTn/zgz3/4veevfnQw2JiqymMwjO2qAtb+uldzziW19HAQFQmZRQl95TJwzEmYE2ZAMJbqtva1NfGA3gIYdMbXtbMQ+uH2OuzfPZ+O9PTx9j/+D//+e+/9Rt+/nYbAMWUO4EGsTczjGB9sL4Y+HPf96TiOKWXKp1O4uT7VdUOGhn5o68bZKg7Tpl1/9PTDTdP67fqiaS4fPh2n2FWeyBABgyiwR9dU3ZgGbycQGk7jEEfqeyWsfAuIxlW1s3VOx7EvBuXKEmOYUswgBMoxxJAON1Y1WW9FMyqvmtY3frXugGAYT5vNTsCkaPsephQ4G1FIKQFE64yvlFVEh6q2rl0fDjeZk6+6uq5TyF8dbon1dJ0OV5CnABwqqT2ToBqLztesoyA7W/o7ME0jZEyYCGC1qlFQsqomicwMjDqFeDwMBklYwxRSyDKB5pmsDaSgiirnbB0W7aeym/4SilW614vXRcnpZ+hqpvcU8zC5C69zljTnFucYPGfhIMuo/wIY4T306t73wzmHOidX9z3g53wG7z5zVxCdNT3vpQWzZc5S4Czoz19Arf5CeT4TKhCADBVh6dIBVVi0xJbzwoLUzanYnEMbnecXFOfq625Rzi93Rq+W7K/UlUv1h7rQU5bF+EvAtuWyFRJGqVtppipoaTn/2h6/RgAW/O2Grv6y45ce1H/Tw1ia63FZKiq8A2zvqk68Qw1oOVIqvmmFGXWmyZSjjF/MWZ2I4gwfAyAQgSQoosFilpJJlHPiLJIEGJRA8M4GUWcFFiMgKnO40DJKvYBMIjIDzDDHml86VNWYs1LgvTbAGThfShoEkMIXOZ9Py6M78xVAiyKpAJOUQZpSskpxQ4ZFkLxcJIgLWn8OjwgIWmRjpJheGYSZ/1IGc3AO17KcBA0qEhaxdVQp6ZKK6lxvna0QEWcTd5yVORChSM3LLLKDC/+pgFdESlDs+GC+/sjKAiow43gEhGiK9D7NaNsMBGLZMpbtY7YjWb6CC5/pjGWdtwE9g1NFE7rcijTX7Dh7nM314rycS5GItExfllUAUJW7sSsFQRViKNwUBBLEUi8UVaN5N1RFmdsuCHeToDTvFqxCSjMwYMpdNO9SC36mBjXLRI6JELMGhsLx9bWt29oYUtWmaYxx18fDm+vbvgdXkyETU87CHowl9MbURhojXd1VVtIk3lW114bJ5MyqokiEljBDSOPIKapqTKyZC/FRBKdp6if21hZ/S2ZEMIQKFAH1q9dXFw9q1zqoIUkap3B7gFwlQ3V30W4fy5E13gQAQEKyJElFtMCrgKWqJ1BEgyyMCwtcF/0fpPvpwIw3nit9mIHV+aYol75ElFlxDAAAnLVoiTN7U+3Wl4c3BwAkay0akWQ9Pfqoqbcm8nCKt0Psx6nfXl5utvVhOFDb1m1dea+gw5Sub4+31+PpBClBzLC9uLDWEZIIxIl76uOQVUW0qDtTXYGxBgBTzs5WKTIgwg40FwdOOGPoS63KoIUHiLMBAgECaXGQPv87T9cpnGGte9XvHflqJn7TnMPMYYLOoBKe+Z5FimuGeBft9XJLKiHo3M6TJeCIznqAZV4YF2IdwywgZwCLX1B5kOSMM55RqsWpc2aPnh/JpZYve8S8TrAgw7MiBs2ElnnGUnXJ15aTcwLhGDW3zr65ybfXYwzStCtLbrvdPnr4dP/ilWUAgOHYjyGO/SQMp9MJFHJIMcbbm9u6qkMIIWVAY6wBNJBYcgIyuIwiF+rHjEQWnyGGAlsv8eAuD8SlJXoGa3HmoZbYpvdwdkAsLkblF8bCXyx4HZliVFrQrGL7CMDzXRLGgGAOx9O//F//t7//h7/3wfsfvr16dXX8ymIWERE2FmOaQtJtu6lr7zwxZ5Hc90dUNs7WTWU8CiTDDtihGmt97Wyoa1Q0xhgyqIYTk9q2XTfV9nDLChZh++TBZ7V92nSb7e6BN10MzMlZ55RdZpEsBlQ598eJ8+hrBOR//cPvW0ezj0Fjs9Grfn97M6W8e/rkghAIHQLHOKoBZgh9HE6DMHTdrrZKCCqO1UTWwzi8fnN4/mofeZbA0yj5pk9jtIBIK4BminJ7HN6+PfgGWTXEDKfBZhtiHKeE5IzxhBRTSilnaypfWVddXtoUBRX646m/+cm33//GNz/bvP7y6Zdf3kw33DYb0Cg8EClQno0opXRB7pU9ZcOadSzvohgsBYiqwjkB+xXNRQGVczb1tUJOz/fPvOsbXpxWFEBVSMNwqtaVtUaCKMDmktYfbZ793SePv7HJdjxO7+rNKmSe+gDaVtYfpwRRu7qtfHMj43HsZWSr1lMlMU1TyJpMBWJBFStnkWCSbJBiHvM0psCcJE5ZJBtLbJInKxR95UyDJgICkKeMIURVALVdV6GvrBCGRCv0iFhVmDnmnEIIAMgpxcAggGi8dxfby9RJOGmfYmWdp5oAVFBzgAzDEaZh6o+xWTV1531dkTWKMoy9sBZR9pxFRDPPsg45Cws7E8EAmWwq3zT12lScNCfZHDfvvro9HvteTqwABGEEcNCtXIY0BqgtrDt3+eiyWbv1g6ZdW7B5iv2YQ8ldHBqx3K6971ztGwLn+zScJhVilZjTcd8bQwC0Wrf5UZ6qyBF5YmuBPEgNBOS9M+QASQxj3TaXVfeosmt0tZ2SjGFIIQEbcqatW+vrKYXj6TjmjAbAgHGABJX3la9BWEUq05rRN76jUB1epbHvDzeDCFVeJhlPGmJKrq4ePn3UrVcowCFMwxDHkEz26G6vBqgALBgPZKFawW7XbC83WRQdP/nkkSBc3R7H6SjEXbOqqjrEmCcMJAbtNLBw07SrbJV5VI2rutqs68cPHvzX/9U/vXmTEbcalRNoNpBZiazBqnZTiDSPLOnsx02gIMJZyZBByRLCSN642lJlTY1NU9uKGOvEAQz4umm6DSG+fTNevY4a4u3bn13u/LPHD588ri4u17uLdTwN11e3oZ8khlWzAjEoIikCS+Mr633g8Tge9scb53prbEwxA7aNMb5KRG9P+3e3tznk2voH7S6XvI8soorMrR4LpvMr3BB507arIYXAU1t31npEYYRxnE7D+KMfv6oaaxwaC8aQc6Z1/nK3a6o6a1ZIYThNoyApSGob7xvfNq7c1+9uJlUTAg4Dx0SqWdBn0aoBIYnx0I8ji3TNatV0T5+9B0DHfrp+e3v9KowDa8ihV4gAI0AkVp04qkjV+Kqrq9aDEfQgxGwlxRADi3Icp7bphBUBjSWiWJtm062R8XBzSEPiyGnKwjNpABb3cZWip6tQ8rglb9BzAvT1AxcbnHOeOMfD0qUWATFnsQ4A1a8JqQMsegt495kzE35+AViKnoVmAVBKJSqZ1ozXnLtQd3mdAlBp/ON9oAfuCaDojAHJ/B2zQsNSGCx7xNej/df+ikoESESlaAWeZ3MWqkAZJykD6wvFbFnUr5W0cF7pBZqT8w41M01A7+S3zit+brfczerMGaguC/zLh7LM0KA50wf0LDiOv2L7+//++PUCsMrxtxy9+uu9Uay1WqbzoCAy9w49/1GiigDAwqoAVTXGLB/P9i/zjwmw8hlKwIWUWL5OWJznFBQ0F2px+Soqi2Qp/cdlBOn8RN2VfMXgpgQmLUMoegdgGWOK9lbOpQAoUQbLOOHcEpnLqHNgxBkpW1Bvgdmcq1A0Z2rCXUiArApchokEBA3i7C1EpUYpJfqyIEsMRwAkMIBKNK9PKejn6nRuSxTsSQFYVVEzcyn9S2lUBLMBlDPP6D0tsay4+i0YEQIWbIvO36EkoEVieIH5SEGVEAFpsVkrC8TCy8Bz6UHM4OMZD1tKQVBQEFj8NxAJA2M5Z1EFKRb2AIVstwTTZVtYVgfnCrdghHiOogLnLaZUlEiASmTIIIsSkSgve5gqFql+VFDBrEDgitw6EaCoShbKeub/KkgJ/6ao1MNy7Yoc1jIuVPYSXHZkLKK+BQxAzsJNZ9vWi+QQYlVD1bq6reraFzJg09QieDr2V7cHMLDZtQCk/eC9d9ZAlsZTW/vWY22cAY5KkFGyggCBBUPeGOts7RxXE4cpDb0qTCGKMhrwviIyZNiawgCEnDlMWZ111ik4U8VXb67q1aVr7eWm2x97m2GKkyFsrLFNvX5YGdF95nRiAOGi743F4Q7Lvo9CQIv0y7KVqqqowMI4KfePaJkhliXFWC54gf2KNBPNJb1gsdcEMWCdJWNzGF1VrTebw9sTIpKxqJBF2qb+nd/5rWbnbo9XSfsp9sdTevb+ZndR3R6uu82qbru6rk/H0/7Q7/fjNAEz5AyQ4dWrd5eXO2ZQAWUIIaQYEIwiGwc558pXovl0PClzUzcK2K2bTz949vKLt4SJAIVU5kYjqKrkQjpEU7iQBa8x5Z5GQCmeBYUTqsWXRxezv7swW2LfjGLNXI4F9sLyz/KNeBeR56afiCgXRH9mk5uCruCCai3myXOoICIwAJolA84i41A8WYvuqCw50Bln00J4nVHmpb8q52cUC/S90MVmUAewODEUHABpmanTYsAwx/klnRQgMAaGgWGEr169vbraX+w2zNC2q0ePH3x184os5ZQPb99FZuEICP1pyDF76wzRNE7ONaq4jDwjWEJE65yKCrMCiUhBGIEQGUUZtHw7o+jMGjvj3/dRxaXdoXe/c+nloKDKkj7OimYASkVVT5EISdHMTnZF97AYmwIAGexPfeqDreHq3fV/+y9e/xf/5D9vmvbi4vKmf1NZH6QPcWpsxZLJtJttVzU2pWAyNlU1TEdCcOAoamVcVVXWrBMDQPbGemsRVFhQxRnjXCXOgrW1W1lqX79+se4u2mr3wbPN5W4KSYkqFaMiTbMGwKEPMU3WJ9GcUjye9sMITWeNlZhDt+nQwBQCi9Z17RQ0jO6A24uu9ehszTnnwFQZA7bcPm3XtOutVwbEtlnFJNen4/XpeL3vxwjkSFDBeHV+iImDGLWnPjnLKQGAKf6zxRQm55zGHGMQocr5UhAZ41OcpmGcTKoqt11td5sVKA792E83Vzcv3vvg4bd/W77/p59/eRyyHgWymiykBAYU5/lOPV/Ds9vUuVg65wZ3Xai741zc3O1sQEAy46Q6l2dnyQFEKAqfSAYMzpLAoDqLyIgKkMnKiKotbHbwG3/nw8efPV590koVbsN4efnUNvY4jCFmDTkPKIBIGlPIRVN6QgiAhEqQA+ecwCGRCgApNnXFwERcVTUCjNMpDqIZ4gSFZ5eZgHOWUBljGvAMhIZIp9CHLIBgGShn9I2pdEVeGFSl8fUwDFMYhTWnPJ76/QE0gbNQNXi5fWyMd85XTmpbW3QgSioGWDAbghRgDJKht976mowxQpIyj2NyMaJBQDEGBSQys/CU0hQzooyHXHlotepotWrbatU2rt0+2raX3ekwHW77YZiUwRtnDJFRRQUjpiHf0sOnl1VrfGfU5iGmUz9livXKW2ta6/3KOOdCnDJLU3VqIOYYJlaGGPL+6ui8q3xlnF1fdEQ6HmISaGrj0KbIpOi8BaSsCsT1yl4+bbePOrCaJCrmKfQSxWC1Xe26tlW1p9APqUcLlQNy4CtjCJz3ljwoA0oFjedNvOI3h+vr6+ur22MYAAjQzoQ/AHj8+GHXrtqu2+7WlTfTeMzjZIC8q65eHQAVURiCsWn3aHX5eNOu6zGEdzc3Y7odUupzIEeEDtFmhdRP05SOZnry3u7Nca/ZWKhzmITTeuM++PBJ11Uvvvzy9Q+P4FaU1hLYYrZkUtJT6K0lZ2Z5JARFlXmEWpm5ZBMcY4gpAmrd1H7tjdeMCQmACImm3KPJSVxWMEDThIeTUKKpP51O8M//+3/52W88+Hd+/9vvP750nUxjvb85Dj13VbPb7Ai5rsx2U6ODyHIaIeYwpZBVRDIrRM6UUlO5CHJ1PMYxTsfBWtc307MnT1pKTVNZUx5aA6CWbNuuMKFr3cOHD8YU+zyqUSKHKP1wfP7i5RfPv/jej15XLfgKfAVd1z58+JBWm67p1t1WgN++e90PJ7TQrRpX15kxcZym3hgEkH64nSYYBkgZALyisNiUyVbeeacomIKmNE2cw/iNTz4FoOM+/uLLt29fwG5tp1OC4Ax3nLIGFbSQRTgqqK1d0/pmVYEVhjhJGEKfchIAidDUAgS2OGSn7Jxru1aicOR+mCADRJjHcZDu0hYVZj0LKaEWlQQAWHgNd9nOjM0URQVYxNJxThNnPhDMxjJzPTQDVXIHEN3BVosqVYmv9yOwnvkXcAchzbv5uY9+3rKXtzcXAAtRAxay/GxBXJAxAkSczexp6czPChmKWkhpBVYqUf2Xuxcl5yoJgioUqY2iLb3gT7BkWUt/pMz/IJT8knDphwqjzEYgep4YwjO7AO5aLAAqUlTq7wAsLTbyOBfpMKeSf3GLW+qyRbLrHv5VVvvXEMP6dQSw/jYff+23iLV2xoABVPlrjMpyFPBiAbBEhAiZGRGrqiqfPD8I5bEpd7VoKV8KcgEIyDCb3Bm0YFWAUaAoOGlWIpoZLkYtWmutMSZLsS1UhaK0p6AghCplThpmSJgQGYRFUdEiEooKZ5ZZwR21aGGxornT9isHIRm7FGuz7kWB16EksTMkVCqWOSgoAUhh8SAZ25QyAAAgAElEQVQoLatQ0BW1SGWC7Zyu3r3eAmGTlHY+zBDAPOdXArzOBScQKYjkCGSgTN4srQGVzJmFFRwaWnTNAWSJXCXd5yK0t7CjEEp9vfQJcN6ByljLIoIzo/455YVdAAAgoAbuhcWZhgAsrApECGqQFlOLMz1LUGmZDVx6E7qAV3di6rg0uksFP7sV4tzQ0burdj4PGUMGAVVEcLl1dbklSrnNqoBsyAAVKWVCETAiAMrz1So1NCComyuMuWFRGh9GsXjEaVYGkGXwalaLkuKOogaMz6vt1hoYhmNV2+12vbvYrDcr4RlXZU5osa5t5c3Fg21/HMM+o+Fn732QxsERVxU6A5ICgKJizhJC4shA1hrnfV3V1aZpUxyGw9GaGxHoRyAEX4OvbFU1prLeBQJCgpTyqIRAlipma5y9fjN8kONqXTdddf2mHy3UjTLmpMmS9S3y2toVhKiSVCCoEhknoCgFYgIozggCIAjma3i3ihR5/RIHCsA8j8nj8vzcdW7mD+aLgjPzDueBMqOilmzTNCKMKEgkKpDgwNPHn360veze3bwEx4nH53v4Larqyvb9cbPbWEOEJiQ+HPtDDzmeUxR4++pYVQ0okEFbaeUrTlmCAKlzLsVY1zamlMK+rrz33hqzWq8ePX74+ssbgVRCG51RHQFhINJFjh0RzykUKswkLESQIklacKsFvfpaID93vsq9fuYnnl2gz0F54Xqcf7oQyMq9jzK7NBAiAWaVQpJT0VwmYpEMWSJTyK8ggKZwiYi0ZESqLMAwK8TN7wnLFOHygJEuRCZAQyiiQktaiKXEJ1RVUpJCvxLNORtjiAiRjDArKC98LgFAMMZUzgAi1WGYxhC4aTqR7K3r2rZtOuNoiDL1vW9a8LVgSj1zmPyFb5qWk6aUiIyzGELMKYIX77yrqjiGnDMIo0GyRGjn7quqCp87kHhWMDuPlMu9C7Pku0sjA4iwEJNlVmMtEXXZlAhL9wNIgcy87wAAKVKBAZWBu3alwm1biTD8KD2Eh6KaE0zjUG+8MExT9pVl1ab22wcbSng8HCu1l4/W0zApc0yTDEGx67Zd0zpmynHy3lsDwjxNwZLNOTusTGMQqopahIqk7k8555CTCKAhzyDj2DNo23YKIJKq2gExJ8k5DuOAEwt448DVRgmqps4Ix8PtMKSH63W3W6EjU3kitYQxAwcha33lK1s5542vLi8vhpt9Uzdtu0oC+9tDH6bM2Xky3g0hoIKxjrNO0wRZnBuda52hrusQ9M3NbdVA7b1tKjBgrWUWYGIRh7ar6kFgfzNOY27qqaLuYtfVdWvNSGq/+PzFdz57+vSj7cVT/fzzYMxVYAF2CChqCUrDn41KGSFc/gOc2VkLEHt+CL7WV1syins1Q/leEruwTuGMQwsoFOzeGKDiAHVXQBXRJADBxnMeIQDs4PJp9enf+fjxJw96cxowrqr2crfrcw9Yxcm9ub4dT/Hh+jHVeHizDzkfbxNkBSkPr4gqEhmklDIocMdd12blCO1q1UrGvfaSgRSEYdWuyYLzDjFnFTToPFadsdYjklpFL01Vta0zBslG523V2jDG0/H46Mn7+1t/PBgEct6nMakGFTBIKsAMKbICGnKEltCICqoxaAtjESiRhaZuXFUhYEwxcMiQACGJgmgxvx1DbBOTIV85Y6nbdCI33js1egzHU+p3q13brmrfPf7wyfu2Od1MwzBZcqumjSEcj7e+cZvLlW1M1vDm9nXCLDGHPIQ8ZEiuBYcomhNk4wgIhjAO/W3XbB3543AchwRMOXLs1RA2Vd22tYgcpzAOAARuRW3jwkAxhAyBlZMoI9Te1R36GgLH66s3ObO1AGiEc5KhDwhQNatG7GXev2aEtqsQVXMUEYmiSZEBwd2+HG++Orx9czVNSR10TQUKwykYS9bZxHy4Pe3fHhHpyXuPPvzwva5qm+326ePHT997Ok1hGIab/dX1/rXA8Mm3nr33/pOs/IMf/vDnf/L8OEK3NqvtyjgzjWkaYgg8HEIcBBh2n11eve0VLJHlmMnitls9vNhCjv/6j/8E0HhdxdHXBMJjCqFylTM1QFbJKlEUDBVMVxQARIujCAgMw8Ccm21bN3Vde3Wcp5BzNpYIkSWP4ZTl5CqzWm2abrPZikwY+gDEL776arXJ/fgJArSuhgcP+sP1zc07jjGG+I0P2q4xrD5LTKcxhYkAttvNFCIQjGNigWmKV9d7FNitL9qqRe/HKX41XQ3rcUV16ioiawCFjKokFVQNw5SIm64mTY1vJokxRDDUH8dffPn8T77/ut4AAMQEWUBoWOeYc+RsbW1DCNdvnw8hPHj8aLdd1101xuHq6t1hfxOShIQpwTDBGEpVkqZpP07CSuvtpms2TWuTumkSEjrtb2KMMcnpJr19B9YBJMMDY0QSh0IaM1lDxkRmTvl0OqHrmk1DFhUtxiiJOYFBkJK1AapqTjz1KfHBMpGYmFLrK0UYpyCiFh0ZIyCzq6CKqhLdyxmWD/FrxdY5Ds6BUkr28TXCz5khNW/SeHeu+1hMwYdQVc3sGDUPet+xv++RHs5nKKUWnCP5eaTmjgj2dQALyove5QBzc4KIiJBmBOseDLfoQyz5HPyqo0hwIZXqZR4QBFWV+yDcnTwP4vl9leJnwZHuth+820LOJdUdkIdL+xCkzKnoIus4i6KewSsotc85xVxOq9Y5OE953uO1/Tof5q/4Gs5NSLp/RZ1zzrmqqqqqijH+Nb6VBWTR819LQvwr3rQxvwT0nN/h+bbG5ere/xX+5o777/b88ZLQf/1h+ysP/VUHIlprz9woADDGlM/8X57QeSsiOWdmuX/jLlwaWEiIX3sPosIsRTC1HDIPBML8PJTnRZbJrrkYmB/JwvdSAc2gPI8BqqiyoiAqikrOOaVUUCoEtEjWWEvWOZemBFySMyhIvkEqMJmqShbOXALrPCkmoEWwxpqqbVzlXeWtc2SNIpShGuscWcsiRXJ+RqQI0VqyBhBExHlXCnNhLpQToBmQN2iNN846Sy6lHGPIzJlFmaGIlQNYY4wtTlhU0DgyZpmypnlikO4q/fNN6Zq6iHPJDAqgggKpcWS8ISrDXbro35T5LzSGyBpmKVMRs6CXAgiCwCymr0hkrXHGElpc2gaCVDgZSJ6MN+SNcdY4gwgiDChIQMvNW+4JyZhTTiHGKYQxIJJm0SR6hjFUAYr2PAGitcZ6q6BJBcvQJM241WrdoTWIICgzU48Q0Mx8uDK+ghhizJwBtfTw0IKt7CyUW+p+AuPIeOuscd4CauBond3sNruLzWbTrretbzxZUgSZ9Y0ESJAUHZArM4PG1846UmA06mtcrSvnEUAMERSusaWLR+53v/tb2/V2CqdnHzwRSYZ0t9kYQ3Xlr6+vPv7wg7cvr/7V935gjTWOhqFXkKdPHn388YfPnjzyDjfrerduOY7f+uYnKYdpCsM4Hvvx+9//wS9evn7x4uUPfvTlq5cvIEPlq3W3ql0lgpknAM4MZNQ5CwTGqK+IUx6GTIpN3abILOKqinkaQ195f/lwY7t0sbUIUleNdfbYH+q2/dannz57/H6IQ+AxD4oigOq8K3LsROSMBQTmRM7eQzIX3t0dzMLnFhmc8UoFXVDKZagLClEBDJiK0ABZXG83imi8A4RxGCnrsO8rsCiQe/4n/+V/8tGnT4Xyn/zgX33+/KfXN9ff/Z33mq3cXN08fPyoabrteuddffXuZhr5dIwX2y2JiylJLOZUvF1v1t3m8OVQr/00jMWplEHQqEiuvWublvX0H/0H/6irWgN4/fb6Jz/+WX9MzpG1VlhzAhVAAkNAiOe9HxF93biqsp7Q2tkSukye0tzTQkQiBT0DWQBnjYNzVrUE+hJzQKk4MlORpUEjWSSLZC5AChYypKKIsuiSWiBnSVk5KbOCgkEyxhAaEAVRs7CjVAFEmJkFhAXPPBGc3xyWiTjEIuBVrhgVEwuYQTFjLBHC3FItf4CIKHPR+SlIM5d+BCgCGEtkiagglgYRc2bJakR/8LMvPeg//Pf+wZ/98Psff/IRAr786uWpH25PfVYgIgXNYwYG3ziD1B9Px5sJjc6MWzLoLKBR5rQUAVjG/xgkqxa/akBQUlZJmcxs/lB6NSBLRwPuYKkZhyi/OhbDWVVgY+0cDA2RMcYgGBRlVQEC7z0RibCIKHBSDimkGDkzKIQ+WfIpT1lYdvqdf/cbu+2GCJ6/+vzt9V4J12vbdM2TJ5fH0+3++mrdrbZdR6iSMqcoytZS2zW7i4sHDx90vp6mPoTJOROnkTm99+TJerXxtnamcaZ1UB8O45dfvs5si+evMY6MqaraeRtTOp0ON7fv3t18hZRVwxRP49THOBoD1pBITpz7vp94Cjntx9O7/XWUhKggKcbx+S8+//TD94fTwRvzYHdZ+4YJb4fTy7dv98NQ1RUHfvTooageDsf1btt0KwC8PR7GkJz3ohDGabe92Kx2ynQ6HgB0s+mqyg3TaXPRPHhwUbd1DKHvD3VTrbrOkTGIjmDVtmGacppAoa6azfYBUj0M3PcpjNrfTKBUd/6Tbz79u//2+//zH/2srjlrcqatmgdxUlBnXWtUQZKqEpF1Dg2JCJU87Zwl4pmS/XVU/n4OOXe2waulTJAAIkBGyChCwIQZSQxmMmoNGIMUQnTOImLVenUAGrQS3NIf/OG/9Y/+8b//B3/4BzEP/+yf/rN/8c9/8qc/fP7m5Zuq1inkUx+O/UTOq9r9/vbVu3djmqraU3TABgVr65uq8t4SEmugitxWv/3b32TOUxqA1KABRmTSoGngB9vt6eYQphhCZGFrTIiTqApmNCIanbOrVWUNZA6Je+YBMKlG5lFY97dHQ67ydZzim6+u99eMDM6BolqqlFmyHq+PUx+ncRpPYwqJE8cQ88hoAUjJAjqyjrpVUzceSS0hosRJnAXIYNGuu3XbtMpqEA1RTKGP2TjDACFzFjn2w2F/fPPm6k/+6Gc/+t6f//zLL56/ePHy7Zvnz1/8+Oc/ffnF61+8evXT51/8+Oc//+lPfjHEExJZ6wVMCLrfj794E3ftenvRSIbNahumCIpdteYkn//8ejyxN8RZVMmZWhiMM23XrFfrBw+3H3y8++iTh4Tw9t2tYK7aarVpm7Vd7+zj91YXDzqgPE2nFKYcgzFYOeecVeWrq+Hlm2M/3qKBdl21m6pZ2a5rvDPWmDcvesxs1Vv2hzf99/+bL2/fnFJiFdQJ0sAgVLvamQqZ4hTykFUkJ7m9uX3+6sXrV8+/evXlT376Z3/0x//79/7sey9evjgNe3Tcbr1f2ShTHwdF+MZnH075RgnGaQxjOp3G/fU03CYe1aixzr9486Z2HQx8eHerwJcX7UfPHm1W1Zc/+8WLLw7hncLYWVxLTKRsSn2emXMSzcxMCAXSBwXJwLCYXTAoCFjKkse+Px6PUxq9d+RIhDNPm4fNxx8/ffT4oXWmrquuXhty714fx7F/8LBzPu4uuzFdT7FfbeuVby8fPnBkDemDi51qqJ1tvAXKMYYwTUCQRW5vblLKzvrTcbi9vbXkRHDoJwTqmlWc0p//6Mff3D7dNO2m7YxFLAIKBAgQ0mS9RdCcYlu1ja3RUuPaytQZ0mrd/f7f+/YHHz3+zu989um3Pnr//ccfvv/+xYMHq8o93q4vdqu2rb796We+8zEFMqDIgCjKrCzKSDJlJ0rOU7farNY751tjXcz5+ma4vtkjsXHEmUNI/ydx79pjSZJciR0zf0TEfWVmvfrd05zh9JDDAR8rcncp7C4WkiBB0Af9S/0BfZK0gCBAAiSCK2GX5M4Mh5yeme7qR3VV5eveGxHubmb64B43s6p7nhxyA1WFrMzIuB4eHuZmx44d6/zKlD/95NnnT1/Mozih45UOYaejm68msi5wl4+zluSCg4hK0R7cUejDnOf98VbFCBaY1qt+fXaecznsD3nK0QdHbtpPl89vZNY8iRVzRKqms0jRuhcyMy356Oo2uEabqwnyVuZmi2eyxGmyRDNwd2IUIGkuB2yR12yYUmNIt/PMQM2lybk4gvfee++YIVpJDw1jWsj+4DsA6GSkQ3NBmrDMvWbMiz6UqqqcTD2ar1RySUtfMRWVOla0MkNaons6Ze5rxmtBMWpXWtTqGTB559jVXCgqAf4VRsUS0VTtdqOFqFY3IiJjI7dAbwuMWONfFbOTljMQQnDsasWMLT56S7YSEZFzzI4XqkbLWlYvqIa9tri7d6N6ddM7HUtoQGYWY2wPyDncg3GccyGEWstlr3K4ThjiwpL5TY5fg4FVP741LPtHoJO9BvGc/IbTZL2GcP08SOhrB/ZPjCaq6qn89bfy0V97kV/lynezdw8y/iWProF/d315akTRVvlda4aKExNzLWRZTlcYEPtoCyK+kKkqbH43KjNjrok5M4NVBXh57QZe9SL1DqBs6/4emt4MkOgJPz4Zr/adSuyv6qu4iyUrKadqfrVPXVhCDQyvolikAJxj4litbJ2ppqXVxN0rAcVR5ZTVyJVbhMWVRfqaXWim/nSnC5ez/phRO7tXURmq3cYURMogZjo9V6lEiRaXVkzJVNVOlUQAqPYEY2aSpHd1D9Smml2Ly09vettmzNiw1BUSwGK5TT+IjMRUNBvImauK3ZVexUTWmo9XBppmLaoqVio1Sl3l2NVSNiy81UqQI2NisEKbxLQuex1QuSCmIlScOSUlh4JynI/FOcfegclRt+q6VU/Et8eDkZpZsQStKpUGV0SZnItd7bNozjt2iH0MPoCIwC6guLFipqolz9N4HKkPaZ6jZ3gX2UGEgOhhpDAICgCzJHk87vV4uI7OzNP+eDn0IV2PInJ1dfPx0y9u9igCCt4DaeRPnj5PUznfroL3u92D9NHHfT+sAvvgQDqnSUWc8ylnEPo+rFYrAs95doH7ofOe1RIMQ+9vr29z0uAlRlptV95jtsNYsnXFr5GOgHBwQY5zSRmCQqTe13BO7K7j3tfaiK8xGHTSM3vl9cUdOwlmlnMRGCp/MOf3vvHO5cuXx/18PviJ8NZ7b2Uc8jyvdoO4jX+JlNLO7R49XmfVw372bvbB0ixp1jxb9iaZTANxcYY053mft+cb3ztk6UNMVk7K8QRLKUkuSWy/v96GlaE4r0yNdmfWSubu/KjqsiyWVrXU+8CJjnpK/y3b0ytFlffmCF+3TVfsv6XIQK3fM06ORYujKyBWK/zqq2RoJqpSMpnqDTJsKeM1Y7AuNYQNwl34s3f7wd1X1FKWoKbiX8+v3Dy9czRxV4jb7BG12tLFLUOr4+bGHGuFyEQUfZ81RZdLkaurq+B9yrOU7Bx1XQge04wyJQSCJ++ZCKUUU/iOGn+/qfrBgCotsRgMg9GdC9xOWp7UQu/FK2zPtofee16NhIWFcwdyoNNC1lZyBiLiKgqmqkQ1VV3r0+zUshpEwXtTdewNhoN+8dmXT97cAYhd9+Tx+bHsnXfOWUqjSAYNIA3RDd6vfEfWyG6x60CY0yxsUDZFba5ERCWlftXXRnAEP02yv0nzpCYmQYhRREwtE1gJSN6pRhMUwyTqiky5TLnkkrNqNipA4chk5H1Yd6GQGMN1jpglF3ZwcF03eCtSZLZ5LjOBhlWfS0pl+p133+27eEjT0EcX/f5mnMZjdOh2axf9NOfD4fj8i8+tuONtKTNWqxHI7MAkpDaNJeVyexyLYbUpnjR4MucBkzTnnAn84OJ8uz3vu7Orq+n5l9f7/cRC3eSgLz78cP3GN3ZvfuD+5M/w0d9iMuRxdpx75ikrg6SYSA4hErPCVFVgrQ/IsgpoweV/6UFAmUtwMYRAYDXLOSMrs2PPIQRmzlLymNgj9GSc1fSQR+ecRlo/iH/wR9/58HsfKuE//vXf/OiHf1sm/95DnizlveqR+qFzHV9eHW9ujvsrKXMxAnkY43h9DY1dCMH7GJyCFLkUpkih930/KIsmXfervo/TTZq0sDokStcy3aiPTjopk7oO1Cs6cx15sFXGpqgWMRUi+Oi98z4QwVmxw1WxfFS16ThLQYjk2DlmFS1Fc5IYw+5ik7oyHdN8mxOyd67yrktSinDRd32IQ+A6Z6owCy6sVy52XZ5LiHGz3vWxm2bMMpnB+TCmibj44GKMIYQyF5klZ4ABD3igwGY55gwDOsSefe9c4ELp7OyB47i/TfvjfpynUhSK+aaMa18SZTMqIcB7F8nrtruZjUhZi6kiz1nNopGBsmYSAULfd3HdrXa9FlOirOKJCGzF8pjZgRnOc4euqj9kKZoFhuhBhCzTYRZioWDkfGDnwA92ctafYXbzoYyXBQHMzOoBEinkQImLGHtRU8owg9X+K3AsVoqljOKMCBz1WvZTGt3B/EsaPicXPZj6YXXx8MF7733rcJg++fjz42FmdVw0gg0sifI0v/97bz27fFEm+I5LOTy8ePzWkyc6Tpdf7OUIiCdmlMJmgEAFUK38mHscQ2u+JACQLrLZClJUsMHISCCpuEChcy70kcPx9qjihyH2sbu62auVB29sWFfbNb/11sXF415o/vizpzlN3/3ww4fDbrd68iLP1zeXqXPMZYibs00oZbh+eXmz32czb2yF5jRrKoPrV3HQYsf9cZ9uaDIYzlbb999/79HuousjoKqFSJt0ec0XK6U5Z8mIbpaMzoNoOhxvr27yjYbBO6NhWK37gUiNESWvI4/Hm/1hP21Xx+N+ng7dEAGISFE1MLMHuWG1BducSlEqSUHOhRhi3m65giP72+Pz57kkrLu0Xj2Iceg6i5xAIYmqkmVDglpJpZCo7wOTJUfUk/dOVPbHQyqpJDMlKxC1qaTYpzwXncyyJRNXyJKRkolBwcQg9iziFE0geGHcn4oT2tws6BWdtvfm5tyzjncH1614UfWsrtUpoVe/WNpotDrFRXdmOa1BZY3c1LZvWO2TfNpyX7XPZNp+/65GxAAC309XWKvp5hbdoGX+6HQP1bNdXAWr8dUS8drJ5zhhOlBTI7Cd5LXMXC1uYGne1OJ31V9qqi8AQaTqC1st22uqDvcKi+jkoN4vqCJAICLU2F44nWxumbHm6ujCjW+J56p53ETcf9PjPrZF90oOfx4+9VsBkX69EsITIvNbR6++epwAwtO/rwFYXz3qwCpT6Z8YsfrqME5z9Y8BYH0VCv15SJlqA8Z/3UEQSKuqVIWcqSFBUtlJCmWrGXuiKtC9lMPUTbUVIJmamnET37tXTFvf61ok1qABayBYlW1q9sYW7Rm+AzRP+NQJ17oD4+tGVIrVLKv3FUksIlbVsphVlurH09wSiNhKuce6WtYeuxbYKhtgpN55ZkhVZdIWDwVHC12CGluigl4LD7YKITaxmfsPg0hzMxwLX49BLRSrxW5UATapWuZ3vy5iVFe7qKlCtXbFqUJgBDPS2jeNXb0f3M0jc6s0vMcLQZWZJVgl2VShRbGFnwCC40aFI9TKCONWXFMZsnwynE6UFAY+LaFa6OeKNOJW9XJq7oJASlzDcl22OAIRs7GSVMWrxiJcxkyKhowoFWK4wDCMeS6ZvPPRB3Yxxm7oh67vd9NZ3YFVS85Z51JUBOaci9GFyCATzSA1M+fYOS9FcykK9c5pUcCYiBSS57AeovdD1wXvPNF0PJQ5eYKLwQxc4H1Y9a7raM6HOR04xODJgPVmdXl1Nc3z5fXNJ59cHhKKIAgR0+Ew7q/H26vDk8fnD8+36/UwzxgcO64kKXFMjkOIAQKVmYhKKd4F7z0xhj4aFEjeh0cXZ7dXLwCIFIM5T1M6Pps+08Rv/c6T9z549yfff/rs06s5j6ELne81qUoRKwxjcgWNf3Nvnf68hAFOuNUiOVCjfTSEoOpqqoKhajlnJTjvienl5fPvfvubTx5un93cPjg7++N//uZut/r7px8/e/Z5yrNomRNubm8vLh4M5ys5HPf7o/cDjzaNqWSTAsnQQlSYzQFSJky389nZ7q13Hn3y6VNHETAwYnTrzYpJ8zSnlJNhnA6K0g+82QYXAYKgCaM152DB+u8z3s0MWgC0FgnEDIjJslcBZPZz3YD2Htmr36FFV9qs9Xxho8ZqWno7qzVT0OCoheta55+58t34BLUAd5YWBoNSo5BUs3n3+Xc2tloe0wo3UoXTGmNfqzZew/qZbPEma7qdFsQIzXtrXp5SE5Wzk+pXYDOwIaV8eXm5226YAFLvqO/D2XYjOh4n8eR8FyJ7ySVP2USdqy3LG+nWzAA2MajWDqVL5FQxeVN11Yw1GPL0VOzO2r2+K1rDIbUCgq6BWLWBpC2337SwHDG4NqtWU1FZED67SwgYnPMpJ+8cSDHiB9//4dn5n+x25xfnDxHnLy5T7KgfAjsK0cUu+sCx52iejVfd0HoIOOeDM5CaOfYOzsSYKHgPMueossKgPB7T/jbliYrMXoycU1WDORh7VsvsioMSJ1GVjJTTVFIpWbSRpQ2WprkYhz52uyH2cc5pyhNMbRx9mQXmnHdqjog1e/YPzi5S5Ksyhz7mPGqZ51J8jEMf+8mtOj5b9wU0zknG7Gu1thYA3mPVu806Eknf0ziOZiilMNAFrGNYRw9f3z/2riubdR83Ia6J+8vr8ZNPXnz88bPbWwTDG6sHz599quY/+PbFex+89a//2z9+652b7//li4/+7pol46z3ueg0F5p9jD5GAEWKmn7VrtHrL+kvOkL0rGRiRkrEIXYdMUBZcsmFHalKkcys3jsYU2crx5vderXd/N6ffvvs8c68ffrZs48//eRv/vqzs13XOZ6NcoFldoiqWpLM85xmQJhBUvQ4z8F1NeFN0FRSKlMqyXU+rv2wjex9KjkVsdmkzNdf7m++PKabMl1b1mOaIVEoQB0oIGzQ7Zx3bGrMLsYI4JDGlNV7mGcyJiMm7xyN41xoVEUpSsRd8MyhQe+qOecQ3GazSiwQzMeMjErEgQMIzlPsQiNCFX0AACAASURBVOg9WMZypII8Jy3miNd9v15vpTcDou8hLEllVpGcIavolZTYr9e79Wo1H6cjDpLm1cYzvBQdc5JU2HG3HlbbzpxmmYtmJWOwCOZU9tfT4TChAB7lYOWGpYSUoOqYiF3wap66YpmVqIAMtcFiKuVwOE4ToCXEuoSpW/VWuGRTMxPSYvNIqsKubLbD5mwH7FVNRU0tum7d5xjUdcF7VTmaSYyRWUlAiu1qu/bbw9V8+dnV+CIzkzNHQlDSwrVKVYtaJjW1DFjtTcsgKqVItsIgRjY8etxNs0xSOInr9OoW5qCG9Wa63ufvfOfD9erB8UZur36aDyoTnAAZlAjAxdmD43QYZQakJHzw/hvvvvPOT//Txz/7ZHIHcGEfVMqRrZilWlKhEIMAijtZDlSvlw2tJp/NlEgAbva3zFJhPhdiHOLN55OxPHi8ik8cVuXZ5y/HfQkhbM7Xm7V/+/3HRDdfvvwssqXZSokfvvfBk93uYXzrePN8tQlGedZrtbAZ3DfeeXO3n6+O8wt3fX17Mx32MF5v1wOFJNkXoyL9Kjw8f/CN7ZvvvP3WhqIjpFLMhJwSwVSg4oiC4+CckRrgmQmsZJ1znfOm88V21/d96DwA0TJLclYOh+OL5y8O4/GsnOc8++CddwZKWVJWEVKjLGDuiKAyjVMSkRhXMfZnu3A4jinnNItkcwwfnQsd4EqxNNk0gmfRyTKyzYAaVLxxFVnSJRmmEFHRIrlkVYOYZeQMzDoPuSTV2bQoCUHYTpLt2sQ+lUi5VP5Q7e1zKie7y2q2dCWd4H5attV7GcBlXyUw2NiW3gwwrfJazTuBge60G5aM4OIU0RJcnBQ5bXEqTl5mKyr8inelpgsti5hJX1V4OEEKryFqSrXk5YSYLZisAWJL+rAF30SNtEGLE0EtMFEjbcFNDSUDq5qrm7LepT5xgsdw8tGsxlXW2uS05jL3hw20t8lOaBhXin0dKi1B0l1AaYtSUCXb14d1qhuTUn4Zt+XnHies4z535D4A8o+EGv16DKx/vHF87XH6oLsM/y/89BOABeAknv+f9zhN2m/lOrj3yv2KvDsReaWc1V41Lb/waBgcrDF2KupkBC0CgUAXGBpoJVo1XGFiSQLAqgkxbZ0FgQULW5ScaHmvrJZbKxTk70oj7RQM32Pe3YcFX0E2zaAk7TqmdBeu1ZeLKhGzIlZMWDSYACNiqlRXZl7iudrxvlqXmmmHUWUimS63X/1rjtVGNZQODIg22Sa12iqPW4B1/1EoDCJgrghYUxSDvbIrUAuNTRW1f14r9+Fly2CYmRKkPeA2a65GcOaI4RaMqj4WXbgdQGNJ1OhbtX2oMcy4dnHTU/GiMbjdDVzVVr/DKxpZDVrXZynq2mZDTGiEMZRyV15VWVdN+RHWJHTvrDtqDboam5WFBbjsYgQ7jRtwzD54VcuiAgMyK4hgShERHsrKntmx40AGzeTEmxgzx+j7IRhKTiaatfYtpJJkOhymOenDR/18nGMXujh03dD5eLbZblbDdrUO3k3hkOfJtASHEL2ZeYeu7zbbfr2J15cH1QzuhiFEvzHSucz78TCnnAucqw8tKCiLzFlUDwCnMccQhm6bU5nzsRtCP/jNZtV4LwpAp/08T5edD90qsqdaVRyCDb1bb9bXVw+qIgkRlZKubq/ziE23fvLm4zcevukcw+nzn92wwnkAhto4mbQ1B33FatnXWo7THtl24Po07hbasv4rAGN1YYhWnW1G13u1tFp18ez2u3/8O//Nf/9vn7347KOf/eTp058VmYpMc4Id8nFM21zmMUsWCMZpnqcMRe1DqVm0gJTIsc7l4G4PV/2Hv/u7f/93T6PPVYOj67rtdkOQg6qUHADR2XldhX6765yzhoHUZJo7oUDtLmuLPgJRU7Vry5BqjalIlfskhi4KCb/qscC4DYdthKqFy3QvvWZmsuyHDWhp7yTfMeet4s3Lr1R2f70WN4X22gORcXfxO4akwWraz5YGGgbz1KpHl3wfnTKZdcgLuIbT92gxCbywmdAgppTEFDF6kXJ5efm9P/jmnA8hMFPpAj96cO5C9/L6Fi6Grg/Eo46zJhVlt/QRaVtCo63VPOUyKc2mNPC10QKo5o5r6HRfg6LetS0Z1GX8ILJWIEEghtYqbbPTJxMTWcvhmphYKws4iSgtKVtjdqpC8PV5/eAHP/rDP/79i8fr3W53lGspU8kBMOddjF3XBYMWyVJSOSY6exA4hhCIPIiI2TGHEGLXExfvwNR7x6dbyVmmYy7ZvOtub29jJBda5sQMZCRSiBADjdlUk2iZcslSzJSZmXzdn6fDUWApzdG64N0451mKQMt020lWWEDrBqLFiK0buvNuhzJy9D/5q+9vV6vQd0O3Y6RVz48uNs7r1e3+9mpExtma+n5dlKZJGPrkyXa3DTlL9DJZCQ4x0Ko3c4gOZIlhIhpCt9utQoxz5svr9PLF5bPPj198efvyErcH6Azxx3Gcbqfbv3tq3/3eH7z39nvb3Tub3TM//N3nHz073Hii/qS/WBgmIqpEcM6fOiy32OZuJf/yd5cjaSlSzIyc8yEOzCwioqVI8d65SLEPysliyhPiGhdPnjx+7+GDJw/e/p3Hz1+++PHffvblixeSBRMmTgc1twL3ALwWndNcpkQJHULn11A3znO62e82D5yoqEzpmEvJJYOx26zXu1W3janky5vr/fE2eO/hXj67PL4AZsKInAmZLTtzKpDKXfJM4qlYDt6vzlcg0imnMZcANiOTEJ0ZqXqzGRRiDH10KshZShETc8zOO5ilNLPBObdaD0Q8HueUkyPvnAu9872Pa+87y5b2hxmFOFuV/FYT9NyFbhzHw/VIQNFMylboOObVwziLAHCBQ3RkUXNho+HBylG4uT4wbnPKcfDDLm5Wfcop76c8qQgO+xvvY8ois3jz5t2654G2fOyR0lSZJwRlMRgX780YPjKRC9N8VNHpmPKcCOYjVsU7dia0v540U55UigwhduS9C4FD1/sVVitsSqLDtE9a/NCfDWfrvsxlVC/KmlTgKEZyzkqSPJcH8Y213x5nu/rymF8igqHWaCuqLOydIyJTlWKl1L5mBudRCW5S1LWGmFbcnEuxgmj91q12wTt/HOXZF8ennxzXqwePHz2ObqUTT4ciI6Cqswb0283F8XY6Pztbdfur68tAePLGzjGlPewlQJGMSDN0NIJpAYmaGVWMZLG+qANnmBLABq0qSEY159tyQ4RM4oNYb4HiRx89Q8Amrukho8iXL5/vb7BbdcSlH86M6MXl9fF4c7F9dJTuf/l3f/nZ71/923/xz99/421N5fb2i922D64LzN4HWwUgOtdvu1V69MZ+f7y6uZ3G1BV0vhsGH118cvborSdv7rphxZFhWVIuMxN8qGkPgUnd9voQODh4mi0bk8J263XRi4QyDH2RnA6TmiqqCu88jvv9/nLOc3kx78eRvN8SVDHlMiWZi6Zk4yypzFPm/e18eztmte3WrVYdEFIab2+nuYhztBpi9CvHffSDIyWacwb2AnMqRkZMzLDIJkY55xro1A05dEEglk2kWIZOwAQQxjCnklEUGVZMa7JG2VRaLQUxs7EjaTv2so+anryVClM6cM2/tYingqwndtAr22xj+jhrPZAXvtRdLGR2r0xEW9kKLVyvk7diZnyX8kOLwJYfN/bAq0F3hcCWi5xOoNNPa5YVLQnXTrM7yfi727EF0ANecfLsFLChJgRt6S+vgCkRkWMYu4oOoomnNHWqpVy9xTXkQcpYdJlrHHgXELUxfR1hhSpV657fyMz16ZAuYsALV5LuI3m/jeM1ZknFYV4L1f/hSMhrx28i4v5bH8Qv/aDTirw/Ha8dp9mpDKx/jMn6tY7XQLd/4GDuL4v78/BLLytF7s648/F/pWMJilCJmu1lQKv0tapsdZLDqRak0XGQp4zl1wHUJEY9w9hqDTUx64KvqS7du14ZYW2XAJiJLAZ0OaG+ISchMFMVAlVvfZm1+xWvxs6qkapbUy0tNKsGjl3r5XdqyF7jVLHlteeKv9UiSquksYUG0YLNZvYqWA6GlRZm1Y1iQWdOj+MEnRNQ+wQCMDWwtQTIXZRZcbLF4LRtQlWrsHYLZgEjAim4ZsP0XmuJu1rDikm1nh+ntEm1wqrKNUA2WM2haS2dWYLX1mKDGQpy1iA9JTaqml8EQJpUDjdGlsJgxlbpWCd06vSHFm01JqABc4sMGZMjJyg11HeNLVzpMgu5C1DmWv0GVe2CC86Z0pzSuJ/mlA7zeHl9FYLzwftQ8UIrWdMx+8B9H4sGQFOeYvTMxuzrkiGn7DHPZRznGMMQV5thfR2G3Xbb+UCqTv2D83Pv3G51jAHeVTKcBo8uOmYYcrHETJuz1Xb14PnLL6/2VzeHWyXsdu52EjEHYuLQ9YG64syORxkPl6XkD775wfXN5WG+Zm/DKsSuUy3jOALmgz/IuL+V3s8b7cjbdtd3nYsdh8BDH588flQyjuM0zZOZsYM67Mvh0y8/9tFdvLn9IL9bpp++/PyAlDEBBufRuqaYuwvr65t4bzG+YiLuckennNwpi2Soaq6mpKxWRQCYyNT0sN9fnO2eP3/26cvnv/fBe3/yp7//7vtP/ve/+j8//+LTL559Fjvnva1WIIaozVPJuQTXeRf2KecpS2k9xUzICkyNQUG9Fbu+vNqs1psN8mQmgG+cavaOiHyAY8zToeQprFerdfCB4KrtaczCumThqA15WcP3gI4ThgPHVROBwZUKLj8nt3ASXDp5Y0CtsV0sSO3teN9jq1N/130GMLbaaIYYjXta049mi3pCfa+NWgFgJXKdBmW4q1EkstrV0FU4v2XvTvKfBBJTMoaC7TRyWshkLR2qrUPP6foGEBukAnIwtFlNpYCwAu8P+6effvJv/s1/cXOrXR+rZxc7t7E+iQg8+YhcbEno68IlbRhS/SBbQFMs+Fq755PSBap/fe8ZLIXfTezK7ry7WnFg9YFYgzKscQrvlFtr1kaNHcNgootzT7S4wi2JYKhV52rqGBjw9JPnh8P49vuPLy4eHr+8ZsfWRCPVMUrJt7c3rgiKjTd7Uu3jahhWUTXAfOxA5H3o+15t9o65c56ZlDw7qN7e7Pf7bOIcxyLmCgFVJaOIKGWIFXh475hZJJWcSkmiZI3a6RwYKNvVtvAcveu8g4lz1X0249p9kauU4zzNh/H2iDwluiz7qzxSYJORqes655zM855VH5yvd7vV9up6O3RSZBhW/bA2F5IaTNZ9HFaORttug3OxH4bYdUqcqkRm7esuhbFhEoLmLPub/cvL/eXNcc5wMXRFJtEvnk0XD5j8+Ti5H/zwGbB7/PDxH/6LD1fb/j/8xQ/+v//rS8gePaigzKFKqIDgXaDgkH5TDQ7WWSZ2oOCIPGCFZlU2NnQGs6KTZJgpQsVzwed4+1sPvv3d3337vTf/5gff//Tp55/95Pn17dFx6C+23nmUaXXmbbidpdA8Jct5yjqBkwtucKWz0pM4S6WglFJSSqKABwJ8F7pV7xwd5/n6Zr8/Hld97F2fJmAEFwdxlBkJLGxOYIag5Lh4Q2WWRiuRiFhGTiNohuUyTxKid56YXOTOu9jFPvquFJ3nfZomFYkxxOhVyzSVkueh2/Srvuu7EMfxOBG5rg+r3cpHx9GKm6eUcsqW4DK0sClKLmTRu7y/3asJO4qRuj4E3w2hqJS5mOMpTdMIgwihdJE3mxg4mCRnK2IWEgpmnOEyhWQFZhiPe1UuyQDbbc/Pzx8NIUYi2ZfpMOUyNQVMMiKWUZ05H6MPvhvWL6cJSbWYFoDQDehXA7Pb3xxfvphqLU5HfT5iiP0bD548OL/wzuWUxheHLuzGrMhg18XVuvOAo31+TqQqhQOIJKdRBSpYb9dbt71BynsgVe+60nCJ1JgpgJmdihBBNIoWE4MylCHevGAp1hsPcpwL1BBhDsN2IOpED+MIHPDxT59FWrH5jleaEmYYYAWeeehWl88v3/rmg74rRXHmcLbrn336xfMvXiKBfVcgKjPR1Fq2tb5xC/l08RKowp5gNiMlJpix1Yx2BUDqZgfkKec+awYOQI88lTLKFFNghAhy6eZ2Jpe/fNHtj7cPLt66uHijj2c//MlHjv/uww++994bb5+fPX76yWe0hmvKGwjsOs/ryOtu6PueuNvvj9dXt59+/Gme86PN+cOzx9945/23n7x95ldZRjXLJWkpLnrAAeoZ3jNIUYppceRAcIZsCtLOu4vtxgK+fPnl7XQ7p8l513VhvV51Q0caYu/D4A9TEiurbkvksliaS8qlqCXBNMv1/pgz7ffTzW2tGJthM9iZMlMwMQU735k5VTCHzebs4bm/3uarw95rF+CNVRlWSm02xWTMrA7U07AeVutVlixmMKcm6kpxhQw2wyOImUGqBxDIE0H5VO4GwMCt4q1FBaR3gUrjfztpLgZqycI9ugno/o7bNueTy9+Y67psrM0PUtwlEe/FIy1b1qpY2o8WFOrO2WmXxuvK7rRwlvAqmHL/C1XV2ov2Hj3mRIy4fzKfmOQLDPSqj3wX092pi7f7qT6hA4OqxoPWnCROwrGNKwU0WZ0leiaCEDVB/HuXfAULqZ7hvSHVp4DTVDYf5tTzurIg7gk0MeO1Z/YrH0T0VdF3+yehOv2GXQjvOC+/veO1ay5UNzpRjX5FztF9sfP/LMdCLXrl4f1DhnQf/zp9/Ste8O6sX2MttXiK6Q5DbSwqI4YDyFOUUKgBz61CF0DlowoppOquExyI4ODQUKL2WOvgVKRUCeI6xAW6vn/3y43UN80qeNIE8pmqzWpmyNRKAQjMNfqQnIWInXPOOSCXfHILauDYaE2OiKjehYjUahtHJMAd2K9UpXy1dvKgWlnsa+v0V6DVVumtZlo5acRGULWlRm65sUVMBq6Rr2qXMBVblNRrAzEAZpW+1H5hWV1VDIUrpcwxsauwHb0StpGImOGuI+y9hfSKcBHB8bLA6iOXFvmSGhFB2MzglOAJDJPT72ol7oDZwRaxw2WXKWZsRGqFmGrSe5FxaavUmuhgBaTAYKlUsKqOpQQmNP6tqUklQrAHc/NczExEnXddH/sQvKecVWfLk+b5cMwHS5ilzGkGt3CaDdH5vu92u/XubBUCg820iGYmZ2Q+eEBSSmXWkjITxxCii6rah44Nly8vt+vVB+9/I8Yw73Pv4aPPRUXUMQxFijgHduaDPHp08f777/7ohz+8uT5eXd2AwuZ8+8XPrnIGa2HnQ+g777Tk+Xg7HrJOOL41Aa7vN96rquYyV8U5Ne37wV0Ek5s8I+UM0QfcD13ovdOSyjyXlMXcPM03t7fM9ODBOTtSIwdfaCLXv/Hu4yGuPvvJFy8/v3zx+R4J5GCA/vq18BWVpK9YGTVzS1PMijB4H4Q0y9x3fhg6WPrzP/vOf/1f/usP3nnr8y8++dGPf7ifj8f5aNyB/cOHD9RKCA6wuvXnOacxj4djSt4ymRApqh8gKRMgs0Vyf//DH/3R7/3hRx9/8unVy+D8nKab29u+5yxp6IcYxnHeH6crou16Ezc7wlPICRBZeI2VbHmvUzSBqipDg+2qTDo77xw7TwSIWWGhO4rhUpFkCxZ/D8CihdsEkLGpmrvDyJbDahL73kuqUFYQ00kqH0vVrZpYU+xsuBcbL59hTFXb887lWxIGTWmiqjaoFbvXH4NAokaOlK0qkzpPNXpp2vSLG9lyFe0LtZZEBWAMCEAgR2Y2TenTz55+/wed4/+RGV0MznEpx3nOcwbDjCilVKY551xvVIo6F+qNVXLoKZO4VC0Hx6Cqi2fLHIBU7u7zNN8VeNVl3db7t0bFkspytab2aOQYJ93EtlMZGUG5OflahSAbggjSpuSoECgMqgjs1+fz9FJub2/Z8ZMnT17cfvb48ZtzvmWieZ5zKmmcSpr44uE2rrx3Cw1OSymglHN25jxc3w2lKENjiNH7nLX3gxZ++fLF1UvxvCPk6NfOeQJKyXMSweQ8cUBwzMweLGqiUlREK2xrJDDTUuaLR+dj3gfnanMQMiul7MdrnpMnzRAPc8BmWIWOIuUbjP548ETDZuCL3Wro+i6AdC7Jcei7Xg1s+vjijNlLKSF0iZCJtaRp2h8PB1I53w3RW+j72HXsQi56mEZJk4udWkcupnm8fLF/cTntDxi6zZvvvNm9nL94dhzTPAxk24OI//5fvcDgQHI8dI+fPN/t3Lc+eP/td/7Zu+/+3ccfvfjkB7fPsxJ7SMtGqWHKybUo7O51+NUPDapNkq52adWa3SGu5ZjqQwhDjL1763fe+O/+h//qjbcfPb989hf/71/8T//r/wxFVAQK/Xp9+3I82z28vHx+/sbZw/d2GjdwGOdjMpViMmG+mq2MUULMw+BX18e/992ieszgAD8wBd2PR5tLZ0PJUjImiAtmhTGrCXP2SOzEQ9RALhDYMGHWKRX065VZuPliNqKUGSUUSBkVDggyDL7vguPOlPIskCICnUvJxcSmMpsWIjUzRCuSABicsrIndgTPw6pHMA5GXAq5TmHElqlkIXB0QWe9OlzOt0dEIu8mLkPfrdah7+LwaLhgXfervvMmymoS5Ory8vb2UrNK1j7GED2v+sJipis/PHyyVVOR8rOfPYeoGdb9cLHbbVabYO7w4nj18uX1/jqXtFoHQVYgRBjgvO8G9s4B/Pji8ZinPI+lzCA7Ozs7P9s5BMvhfIehOwscTVxf1tPz6d//H3+NF4ABHdABBgRgi+2j8OjtRxdvXKzW6+Gc2MusE0fEGMfjPJWsOq+6zUDraHvMiORVS+s5a1RFbBhMyqTGYr1zSl7IskWFAwo1t1ZhsOyDW4sT45JnOtxqSFpK9LS2rVw/O96cT+dnZxcXj25e7PdW+hAcBSSabw4lynF/262mN95a7TZD39OPfvC3P/rxl6AOOTKSlqN3AhVwS2bSKQ+qzf5XqY5K8q/sXjKqHV8behUBBwhk1jzm4838rQ9/V3RylKYb7UL+1gfv5VyOUz4cxuO4vzkcHzx4+OjJOWE9zv7lAX/79/jf/t1/KPPhn33vvQ/e+3aan1++vJREQ/9w6B+e9b7zOucCwaYfnrz9kN5x/+oP/mWHnsECZcU8pqdf/OS9Nx6ZFlVhB+cZlosVNY0hECNJLqUEDWRVUCWb5+AcOJKjZ599erO/yTL3q36zGVizCV1fX728fBH74TjnOWkPS6UkQypi5pk8EwGas+bis7CIiGCaineyWg+bzWrVnx3mSUSdcyY2TmW/P8ocQ+x3m61ueXyeRJRUTURKNoXzFAKENETaPThfn2/AkKLM3Hc9eyfI2RKUwA5MECsoRhbIOfamVqyoCGEJH8iqzHqDiE6NWtvzJjTpgK8o+n4dAwuAqfFCaqpuDy/E1+YsLWBWOx+47ya9drVT7tCsqSos+fvXj/sgVE08NYeHjcELcwKolMEFc2mexV1Z4yncJiZg6exHC1BngFhzDxzDFOipgYQteKtLvxCxa0HxwpDXlsNs7LA2z42CYO1rq1W4p8lpgOCrAFbrOt08uhNhAWb3lDvBIFQo5Q5JMIPIP4SNJSIn3MPaEnqle94rAfJv7/i1AawTsaj+97Ux/XZ5Tz/vnn/BXJwwxdcW/WnY/xDF+198fHUqft6PXjvnl87YffSqLovX8M5fjHTSwmh55bPs3l+0yLMhGsSnKj+zU7VZ0+1rUC6Rd6GmqlWkmKjqKyrFBEDvCDV1EK5VXdT3prZ4gBm3p4bq+5mdjGJr7bUMmEyxPMkFIFtyBgRyxsVy1QWo6fD6x07Qz4IfkcEZUTUdjiv0nYucdGTqrqxE5GoH+eal1gtUKI2IqYFCzaJWSaYFHq9GQo2txsTUIHxiY9SgQdUAcLPXle0l1MyWVg5EJZG1oGsJrU/rGQlwVoX0K8erPUolY2aGkQkUxRieHFVqGJmjKmOhthhNavVfDiAVEyutNr5dclFRVFOzyFajWTOY3teXuYvwARCZQYhoeRJGSiGEyqu9W8TNNOuyOxK4Jl9ArC1rUf9nVW/SYIDTSnPmZuhVhEDkg1OCKGpXgIVQwxStrfH6R6GKrCWX2bjvBrdaRQ6AqVixolMpLgHeNMEHiGZHFjxJSZYLmyNjmUsJOXbddrMJMXoXHFgdQoy1ZNIxe/DG973z62771hvv/d//z1+YhSw1B8UiKEXIJBjMM2lnRcuslgHFiy9uNmfdarsFp5xHGUvfua4LyXIXY+diSnp7dXCLRGXwHgSVMs3jze2lIdxcj1fXYz+4R4/fJrZS5iEOMHv6+U996TZh9+F3v3H58Oyvy/evXzQMx5ShVkHVCr/UJWBmFXWtvohVeh8bmYIMxNa0spuEUruYGcERAkRhwnBqSmqB6eOnn/3Rt9/9V3/+Z9/5vW989pOf/fDHP7q5PYgDqJvmxIF759h5gERh7EQw5zLPZRohUtjYihCMAVWAQtbkCEr846c//pd/+ufv6LtJ6Op4pWJpTvWFjTFsVut5mnKZ1Urs3NmDAXpkV10p49r13ohYq/WqBqvhsgu7hlCbg5rnYFyXJxmb1mpDvsuB4R6lqkE+zRlsxEajtvZrhXC9+p0a3Z1JtcVYE4BTj15amP0G41MZGwHELcNQ34PWWtXuJEkJrb5OpWJxbUh6cuMMDfm6swNtLpaBL+zP++zYNk6rbhm3VK2aeqeSLRc6XtvTn34+z7NpDt76YbCr+cWLfSFUHmBJOk6TiRI5ckyq1F543KlR3U0H3WVZl6mG1cVZrcuJO7qAYHdc1nt6raRKsky0nTaLKhNWPV1CqyldXgM7JRSacbmHg1hRKJOSI0/csfHV1T5n7cLKkxtiB0wE1ZxFM9gSEaD9Kqinzabz7GuPXEfkFc6IDUxMNcQ15xHYOSoE8PE47cfShU6ldMOWmFVNSspmSQqZRecJeoeSJQAAIABJREFUntll9oVDRiqGQlpAbI7MqBQrcm6FLSGXPMtsMqZ0HI/7q5c+FdepyKwKV3TWeZIxuTza4XjcTzRF8W7oFFS0OO8dOHrnGC8uL6fjcbXZhN5U59opUsxKmfc3z9N8DIH7vhdJNpmKhijEFJx2nV/3K1EyCi8uj8fjcb+fxPx615335yrXX764UjvGrrvdw/rkPHbDZpzGH//w2eWz+ME3H3b0rI/0/jefvPXOg935R//x3z+/+nLEyE5jsGDJJBXn6sqR2hKZOYLMbCZiGGDOGZ+qQ6sNqB1Bofli8+h43M95AgGhcA+wqWQ4YAAcHr6x+vA73/rW9z4I25D8+Jf/6S8/e/r506efPgzrm5tDGpEkg6+Q0G08iqXhUHZDGJwNLqtMo2gCCmhEmSdK7LGNfRjcClQKlKg2eIMAc866Hy3A9b6+zKQqSb2ykHqriSFHSkVMoCxGDEpFARJ2HJj8NM1ZlRwRPMRQqQMFmbhzzlEsc5okZVYQzCiwT5JNME/iHJjJu0HMpnSQGSLqiM20jGWeA4k5AKE4Jz5ABcowhXNhGLbMw3SjKEewM5gYDjIT5t53++ubOITifIJKypXabor94fZ4BCvWnXSmKjLpURTDyq1WK+e9QUOAGvoYt+t178J4vR9nHL4cX768SftkhsOhVPOpHbvIGgi5aGRH6fFbZ0ndnNw4U5ExDog9d65jcyu/vhjeuL0cn3364uWXL/LVGMbIsSV0dVIXHDny4LK3F59cT0fZPOJH7/bee9Gcx5TKfLgZWXrHQdWDO4cOGcZBTdCSE2YmCitWIFIhIaBpncKEGKByv37ZLIcYAodZTXKa9lOejZxDIe/Zsl1dX59tN9vz7bBd7V/cwLHrO3F2nY5DjJ9ffnlh3Xvn5w/OHlqON88P+8uJrasen4my81IpYo2s3djIp1gfMJhYhTdaUqi6Ycbc2DNUhdGELFE5lNXZMKU8HuY53Uxz//DNh6t+RTY78mKdD7R9sOXIHYZpdqsOxyM++unzb33r4Z/98R+QmWSej6XMZjKWNIKiD37bDcxu1XWRAoFVpkSZBUPoI4cQYb03y1Sry4mMyYyKqJo47xw4hpAlwEzVyJmnRTcWLMAH73/zcDymdPTB+sEPK8cdlPPVuAezdy644vquOJfmnJXBznGgzDCJ3hngPbkIKzBmZUe+j36NwJKPIHbeUVRnx+M+7W/2abSCqdvSzZdjm+sAVEFwb0IojDhgddGFFd/Ox9txX4pEBG9R2Qq0JPEaaspfRUw0M+CIFnK1QqxRfZjrUjO1VoJ3Uj+p1RkFoFpNeLeP4m5TXvbmmrxSRq3VWJJ+jfGksJYZqhdh2FJRVz10MPSUua9xPdW+VqgZgpaAp1NDm0WDpLkpTb98WZ26eGPVyWoyX2SNeV99Llp8Xb5XoHji31tTiTjF3AYztCiRWtjJYCFFS2Pg7h2pmUxapAvIzBmkgmnQiiCSq+Pj+kyMlWuFzkLNWZ7D6b7u+YgnhNFedchswQ9Pwz49ruWaJ1zw3vFVjOI+2vAaEFQRq1attaAxPw8s+q0cXw9gfS34ch+6+iq96PT933iUX/tBFY26rwdmXyf/dJo+ACml03Veg35+s4H96uN/DYA8ff21c3JHUVn+i68849e+eSdE9SuvBgKdOvGZmVa251IqcpqUSlur6uxE5JzzzkvVn7TGTeLaa5q5cp08vGNHRApHWoqW1lC9zjxZczG0lkqDiJy6hsuewDKDIyaQmFgxMNiTaq1UdO1miVQNxt6xkUmR2jBCak/0JdRY8GTANdEuGJRVTWG2dFiwOomeyCngjJix7F8QGCtahLRgQWatRgiVn2VaiUlkgIJJjcHoYlQtDYajKhu15KbqX640iabzjtoPTKFmvmdVLTBjGAOeDK1nmYk1S1Y3AnCbkWUxs3N1oQMkjQmLWq1IYAcHhUjRTk/wO1XMEHAGMxCbVpiitjJzZEZ0v5yzmnDnmZgURdSkBOeg0gDOJh2/QGdtwyCt2wujksgrwYHY2BPMmS7VmQozYVYoahEPGxMRufqAKhvdmMmTw2iOweYAsyqgbCBi751CSxGoOItAKIK5NryLdX3Upgoggvc+dA5wkCKakiZypV/70JNRVi2eTD1ipvWuK7oSPUYW0yl42q77+XgcQuyc73ygzZnzNE/p/Dywc8F3OUm3WW3Pz42x3ew2Qy/7eb3rVn0XabjYPb68Pux2j/the3l1M8/pjSercS9Tys4pc5YsZS5WlIzM2XGfdhe7zXqbyn5/cyVJTEOIgYgrqBxi7HpxJKqpzKJFS1I/xJTG3fkmZ/v/iXuzZVuS5DpsuXtE5LD3PtOdauzqAY0egO4GQYmiSMlI0SijXvQXetCbPkFfoH/Ri6QHSSaD+CAZSQECCAJNsBvdVV11q+50hj1lZgzueojMfU4NPQGUlFZ177n75M6MjMz0cF++fPn+Rqe4P0zlgw86y6lhCuzTNG1vr6dDfnb19OJ8/eS9yx/g+5/89Ztf/OLTNJhjiDG0PrE68+mElsIsregKE3ElogvA0Nm/hjFY5tpVJmLnAEYOTXCF47gfFXFz3jhSBv6Lf/aP/96PfqBT/PT5z55/8vMUdbQ8jRRz7lZ8GIembffjURlQmXK06IYxTQMEcKzTMMCcONKs4ts0RjM5puxIP7t+/Y1vfMs3q3/94z/PJcaYUyqPL84eP358db6+ubnZ3t2NT4bVuv/hj37/X/xvfySOa1aMCUr1wcKsNbeoQqHyzAwnIAWgIgBz1chSImJhZ1VxuS7nNAPai5BBzScQUOvzFg6WkZqWMu/CYK7ZMa2tdGa3qVY/MzPPLS9O2P8MLy5A+3KSWpyNmRxSw28ApjNRfekPbfP5gNlzvRfIA2l1zWZVitpdlYhP1XgVxlrsxfz3jGHPdEzUhEMiglAgbf/Nz25ub+7AB3F6dnYur6cXr699B7gkkkrWFAtAQszk2LmST43+DFVZRYmMKpGqZj6sFLWlhpEWfSsy1WUQdbAnA3sPz9LszNLpAk4zNeeIGahVm/Wy6po6N0cEGUwIcIKqe1sbPgwEY2ZH5I7Hcv7I/eznv/gH4394fn7VtP3uNjUhhIY0c8mua1zb0Krvz85XaZouH59ZQp4MRT3BGUQhTCVlYvHcUDZj7tz6OBUvbkolqbKVw3F85+oREWVVKpInm0xRkFJhEiGfuSlCGSnjeMzjmATsVcE5N5bVpq4x50u2sZgOOY1xsoiA9unmUYfGI7GlYirMzrE3FmfOwB7N+mzaH8nQOu9INaacI6fJWUYahjgcpsGHlrlzEM0Tl1imwQqc0KrvczaYmRbANA2qUrxL2dquu7t5bcoscDCREnzq1+XiiowpEO8aCMN1PA0Hy9i9KWlXJO93r9NqZd/+3Xf6C/7ad9ZvvfP29qX99F9/+vGHb8Zt9qUlY6TsHEFQiIuJkSc2EhUWTSbqhb3lulhDUYhBAidK7GnLFP26a9zKjXYc9QAPf4Z+495+98lbbz+5fLR59+vP2mf96+PNX/7bjz752au7V3s9MmuLyRxZ4Wgo2ODN9FF4Bjwqb+h5L73wuUgbYxpHUOYgDDMdhnGK2Tl/QTFarvGVBxhF9Rhjv276VROHqeTpvO/W7RlHlzcl5Ti+mcYUdST2rYqZ5pITYA1TEIpMyhBhiECXTqq2UBmz5VEzUwCXI4ZpSnZ0nn2oXeqJHatZyeRDE9wqUTykQxlAQN8FoAxDvH51dC36s67ZeHGV3s9KpFZysok1NEyhhe9hxTOa3ncdhQBy+noXiUx9R8SN66okRH9+mUIa3BSn4hx1TSCfGzRZo3GOabI0qVK/ciPyxep81a3TWJ7//DOMPO4SRSACBTqSiLAVDexWUsTSIYYeaUpP3l43nfRdaMY4lOSaUjAUIyJpxHdo7rb7mw9vxpe7kNFIZ0o6FSsKJVl7YmKWnPP2OIyjDpNdXrx7eXHWhObVzSdmksakY8h38ny8losLU0EEelYFOTFiLdkMWmKelIXrDalFy1XZbvYnUVgQfBAv2ZJQbbM0CUsgMUVMU8lRvTYX3e329bN4sbnYPHr36s3t9jhOKoF7V0rsnly+ut5fceeb84uz91o5X/kN4rVOEzufc2QEmFPTrBWFIoIR21y8NacIc1WcNiCjavCQ1AVtZrCQRhMPccwTFU3jsFWOwpIj72+ik7Hrm1RK3/f92Trl7RRH5zPKeNji2eXF9ma8OUx/9dcv/89/+W/+6T/4hmbWiPEQNcX2ke/7lXPShz6VzFamYW/Auu1bcje7N9yuxLWOddVz0uhDUKKcc44TzFJOYHVsAjJAnGTLKScV47nfY0qmBfTo8un5eRnGXUq70KpwHEsKq9Wz997f7g7Tfu/Esvisto/5EEvwrZfGNE+TNk1jYq35DIvJXNNQ8GOyks2SvfzFoBOIiIO6BjHnOI2HcZxKzoXf/+6zeCjpmKYhHfYDRpPGN61LiOfPNu2jcJiOu/12SBMKUo4BWRBUrGhEJFKo2nK7UraoVtuWVIocMTEpWVmCU13IQXwCS2wRBVncIdQ6wgqTPOBCLaiqkMy7o+qS1AV68RdsQWNoCTtqK0g2A4Isp6jA2L3DpAa7pzHUXLxVNQkQERhZC9GsoWD2kHt+OiZR7SO/uK5YslSY+7fX0RJsUXhYLqu6IVoAg0gtCKoXUHTuekzzwRS1EZkWszn8mmsWzAA+eYbVu8mwB/1vZtSNl0wlHvx5murlXhVbTggAUK0jKFBbIr55zj8PohDoVOZ5/+HnYZOF4PLVQAot26kGrmIF+I2L5/4G22/NwLLPt0j8/2arveTMLKX0K4Cbh/N7gpOwoGC/KeLz28BDv2KbQ4FfeZyHo3qIf30Z13yIc52O/De+BWozvjYX4j0A2mwOtTQjP1CnstM+JzzuHmdlcuRqyckXntQlL10Jk/NXdE5ZVwIUFy1VD50dAShqpwiNThYOxMIiAoCZSpkV30+M0HvQnsFMwTkRByDnrKUUVcxUp1mthpTMFuUTzHaCBARSPsUvABnYCHoighGUmXQOg2Y7VtdoAz2gOCwY3ZKZrzGo4tTSqn5YC+9mS2UnugTZEq+epnIeZdVJX4RmLXhvBlVDVRGrT5QSKTFjNqkEhZKWmVihNfDkUgrItK5mDKIqXS4EmvOuhCrrA4YXYRZTmOVcSIvOTJFadSiktUXJTCGujwh4MWsAZg4V8SK/PLN1FlRkpkTUSJeYhJh8zUXU5gzinB92o2dxrYBQrJSkUFMrjtk754IQmxMnTLP814NXpO18ycWgLASaQ2Fv6NrQBm8ljcMx5QEMEW5Cu+rbtmlgMC3jbh88N8H1bdOI7Ltu1a/OzjZ3N9cpJyvIqWilG5l1Tbu5OHPBrVfr1vlhtWudO9ucrVebw2HY7bfenYkPxOzEPbu6xDN59fLmeIymFEuOMaacyTAHBmop5VxKzkiGIyeJqfGBKVkyVbRt57iMQ4kxHoehMWHHsLK5vCK46Xj34cs36Q4vX7xadeHszBdN43TMGAvjev+cXuizx+986/fev3py1Z2HD3/2yWGb5GAq5kJofEdE4zTkUpgIZkpQEnZMxFX4faYiQhUlQx0zMRvDoMaG+joLjAqxlTSkbLp25se/93c++M/+0T9siT77+GPnKE2jlTxOh+E4hIDGy/5wGMep7/sQAgHHacxKSZMqWGEFcUoMgDwRVxKWwXIqU8Fuu5umePn44tlbT2IaP371XAjrzerdd9/qvI+77fbultXeefb4hz/4Pm7/qDxdaloJQsw06y6Zzhk0kmqH9YHMOwFUcp4tFGrA4oBqCT63nC9VakCtLJ6TcnK/BFSPZDHvhWxugLqg4PWIwkJMIhLTNKMxS+ywQFWL1QQAsPvcQmFz4u+BBTMlYphpNYk1MLITgH2Cc+afdIGoq8maOSkP3SpbQK0Zdq/VywAjT2DnnAspqx0wpUlcJrHQNDkXEFIBzErJVntb1fYgUAKVMiuwE2ZSsbGV+7YVJyjKZh1EmjUOURGuOWFDpytasr02LwBcrRQvWoZz/kFYZoWMJX+wmLL54uvSVksdidhkpmgRSbbMXpIWTGMxizH/xU/+zc1n//l33nnbiwyHfX/WVLajc7Je9cHRer26enQJLVyIPLMZVNomtE0ggmkuVjxRE5racyFbCaGJY55icr5p2vZuNwbv2XlvOsWkZjmVAmXjJqs3InKqcUpliimXHFNSKjB4RKXsG1p3rW9lV9K02w3jlCazlJ48e+v73/v+RjYme2ZLKRm4aVxv7Vr7lI2B4GnQmGOhviG27fY2psROSs7bXTaCMWc10gkgs+i9dat6TydxgUVYHDuKaTgOuzghRcfSQFzKKg6Xl6uCACGzSZxtNqFYpCw+gICqHGOGkvPhkD7+5M3dzq1W5Wb78tHjzXe/963zb56Pe7z99cef/vzw6U/v3jy/G3fj7c1BUfPbotBSS/+RzTIARTZkI2NPzJURrMqmRpLpeviMOyebtnRFfH52ddGehf7Cvf3e4/Vld/V4s1o1Y9z++Md/+cmbF89/cb19AxrR5M5BLJeKQKNDe9acXTQ4N1xh0ilbMiZiV1lgBqhqiVmPwAA4OJC25la8Wq/haSxT1Ogci2Mr5uHa9lJEnDlBcN5C630ffEoRZbfdoxGwzv2FBRwYbKVkzlz7b6qZY5bQspCI5JKTqmaNYypRNRq05FRyThD4xjnnSiniZbXqnYQpJssOmhni0fWhWZ3lmIZO2pXvGucSxahTVBA7pRSHGMv+LDTtWaPUE1vXUmhsvfIhWNEpk2+4keRLRiqpRBVywQVNEGMxRUQs2fUg7zyzmeaUDQXEKGiD77oVczge7vavR2QgARHIQAE5ZogaKFGeLFPOrGoTq23vdn5lHMhgTGxUYpqmmENZT7v40c/+7PB6HLcjK9g4T1OJVpIBQsR5KlpMrKAnEklD2t+VVy+2m6vV+nJ9zcGUGGEYpxfXyYbu2SpFy2AUUxQzoBCgBCUrMGeg2u60AFV2sfaHLDAQQ0QaH5qumdJg2bQUELz3zpwqsbEZsdE4HM8v1odhG3q3vuzf+8aj29f74XhUc+1jX2iAgwT4xrVt13Wbru0BoCBrerAKEDMvhfIz1+pzJRgnFWyiSt6Zo+2Z5whxcMQOjsEwijGSL1VFQS29eXkHAQvOLvsCV/jYdJxS12rQ1Pzdv/ejjz/66M2Lm+fPP/of/ueP/st/8N8cVOKQSyzNKlxenLWhT5az5uN02O12h/2x79f58uqiPx/TFOM0Nl0rYZwS9yuuFfNQT3DE6sSqnhTlMQ2lpPoKlpxjKSpFqbZrpXEacylTjGZKKR/1cMwR3epscyFN6/pVMhqmaTdMKZeiaiA1pJSGIbarTkSalkwkZBgFIuzutsftNVL4+Gcvrl8mCNqAvsfZ5UVoQhdWeTi82R8eP73iwN26LZN1+248xlUbmk52w2511hPTdr89jlPXNVpKjCWXwlS8eN/5YTeRAlpvQ4ExSGFkpMYgyIn4XTOVc0RYb/QS7pz+tAUVsso0moOXmb40r7D1cXFc80Ba5mbzIGJ/0qhZfBUANqtKEs21NPcxtFVxYVqW+UWot0aTNHs/NDtK9xeyOF4nzwQPCNhMs87p50VfQbj3ae69qfl3p9zYotQy8wpmkVeUkhcZTmDmHRAIS0dCWiZHZfFXaKkVKaXMzgfVCiSjWs6AXw4p0JJCNFu0T0/A2ynB+PAS76uyTtuXAazTrD+86q9EHioUcCokrDufFKi/8rD/XrbfFMD6Mvb2mw/rK3GW3+rrtNTN/SaQzUN85zSVp98uTJxfM84TTvQ33k7D+GXH+cLnp6GeZNq/8lsPVcn/NsN7iK3SlzTY7MH2cGwnGKt+Jef8BYz2NG9fGN1DOI/MqoY2UNs5oeTaUYMB5FRCH2ppnS3IBdMiTAPU97FowZfft2rVDFYUpLZoCFSFE62WU0DMD5T7li8SnDibG45VhLrG3kQL68FQhaCMiXWO5aEn67jg9LRo/gBzyn4OmyqLhZbG3QY28LxjDRhtweQfXusytaAv3nQDC2up1UzLXgYQsbDwXGNUAyu1SpdRy1SUiFBinjvTsoFhtWDC8qzschrA0k6+fsBEIm4O6SEVrCNTzM1aa3qFMLNGCJUtYmam9ef6eOkSORLAVf3aACKSpeLUMQRqVd0BVfhMixaBOCZgpnARiA1s7MAiIiziKijqPIGFsqYMFIirvaeQc6qNqIWwarHqm6bxKY7irPVBoSzct10IYRwSG4Soa0PbhCDOO9+HZrXqvbjArvENGTnyZG6z2lycPT4OY+tD44J454iR1UoObf/o6tF6vdlu727vwLTbnJ+JkzSOJLLqN/vdNI6pKOVcYslWVYaVpmPc3+1dIHLJyrySMoPZeefVnHMEdp5RSgZMC5tKTjrFMer1+dll08vlBV4kFBt9aFZn/bDf5RLffu+twG6/3R8Pt6/ucH62+eb333v2tWf9v/zTf/XP/214EobjlKZoxeCoEIylgEB+fsZVslkIDcQUgBYQgdlRhQRsltZRNdHGO2mwH7ZwJh1g2KbxP/ruN/7gR99rxd1dv/aC3/2dbyn0x3/0vx4itnuse2hKXtSH4JisQlaAqhqKSPVdUBIURZwHRIsSOxEYEpLe3t5s77bP3n3v8tHFz5//O/0p9Arx3cGsCFyCao6mqem7p4+v4EBU0RAwIwTHzDFOJ7tIi09ky2s5wxjVtMxGcYaWmXnu7PcF6zTbyOrd00PnbPES5waB82Z1RZi7FdS3rxYtL8Z54TYuh2auiT0Yz8FGRZlqCsGWXCWWZqf2YHi0mC4DMcuCP2J5/U9jnbG2GeR6uFbe+5qzsah24gRnaQSESFy92mKkpYiXzdnayODhHOVqxLkq6lbDsagFzjnIxVc9zT8WB45skaNA3c9OZnhBr+5nXE/goM2f1DppPSVOaoD/wGWuaQ2aq9KpGq+5AwmpApoNUMA5cSIRk2tCySnnEWxDLLuXOBz3RWMb/LDfP318aRSzFWKuYar3TR9WhLK9vTNFHDKba5veB0fQmM0H8Z6EK1WWimopZbvbh6YNzdq7tus3XdsqKGX13ndNk3IuVoi5xBynRAYmLtn2u2PCMcMpYskJUvoevhUKpmQx5ykWLSZwwut12FxdPNrpwaVjIxbzmGgqBRBtfOhFRUI87lAmM46TJ8M0DTlbEEnZYi6bq6vQ9nfbXdGpbX3XhqbfpOIB+NB++tlr5uBD8OxYNATA4L2QiFoeB8Bbt2pIujHzMI0M61uXSzMNWK1QBsSk0GzKuWSPIL6ZUm61mSb75PkdyadP3tlfXJ5/8KNvv/+d9uOfvf53f/7XH3/84ev/vapIFoQCB9iEBCsoMmvxOjdCK7RKEEBq1TpUgDNoyodhjwi8hbe/ef71b77/wbfevXx6dnv76rMXH19PZrDdtBsHTRNIISyFNachjxM80KO7bM8erVZnIYZxpCjCbdv2fc/GvvEkGJNiAhRoQMziJbcpnPPZxXm7ahOpTmqjai5pSFJofb52xDfXd7s3d5iYR7gkjTbBt92q2e1v4QieAUBAHUkjbWAtJSHOJEVVsGMm78V774tzJTFkOowwcKGiBLM6P5bMnJmZC65tG1MjlfNwYYxyjDQ5M+fJP7p66lvXdE4Ek01o3DGNB5o2Z5uDn7xvpbHQcFitnSPSlNNQq9OHQd++eDvGPN6Nt9vbw26MR6UCZHpgANWA/iI052Fztm5Wrmld6Fxom5/85Kd9uxJqpmPZb49g+C4UTebMAF7iZDKa8yLEIK0E79vtLqiETgqXYmoRJCZGDFFNrz97Q8l58dm0qJHCiMSJEy/iE+VsyRF55733CWMay6fPX3eb8FjXh33qVm0fNpM7eqTxcDwMO/WledxN1wPEAQIDwwHEZpasxMzeB98wi8IKVK1oFUnMGarZMhnYSVEtyXIBWYFmFdFSYIWDiNHZ2Yo9JR3Wm0a+9qhw2v5iwraAsOkUEa6BcwY251mChwMMhbUyWFWzgWrzEiIyLPoPX70RqIqE6BJQGxGYSURqWgJAGjMbmlaca2Lh3f56TFqA16+Pm0t69n4/DlbikXNe+asf/Z1vX1y6v/7xz//8T27/5b8A/lv07dmjy3fKOq/PL3yAIaUUr7c3+/1xt9u/ur7pu/V+POa3bMhxGkc57NnozfX2B3/3Hxo8CZHPGQm1/ZCmKmltQmaWciQnSkglm2Z4rqqIBI5pnDQym4iwb1JKrz799PzRI/HOh0ZzmVIexmmKKeeUJZlhitNxUPJJSYqaEKTxalKyxnG4fnWng5+OpWUnKq6gHPV62PkQ1pvVqtm891b/4V9/su76q/PHF08u+DFrRs7T69cvpjjc3oqMkmPuOt8Gn0fOpKTEEEdBvEukTLW1iCpVocxFTUBR4XICQ2eN2odh4BcX9/pZRTErYcpmMKbCMw8dgrpAGmAE40V+skogEJb+WLM/Irmo2BzvLL6Dwarb5Gvxi6rNKmun1tn3Ho1hzjadfAM7PaEKY9Q03ewx2KLmpja3mK+/ZtiDiwY+N0hauCbE9wSx+jnP3aoXvIxwit3uAbgqiTqn/k4KBsTESQszQGAGloZiD6JEnO7LPb5hQNVB0Lmo0sxw8l2XksLlu6fB/prtyyjEF+L9L+x8GtV9a7Xl4flt4ZQvn+Urj/DbMbDs/w/6FRGllHLODwfwq0d4+tnMeNnqtB6Px197Ovr3IZW1hCBfoc//cJ/Ty3DC6U4jfziGulsFOH8ZCPpbja0es1QJwQfP2WkYX3hSK3xwuhxVrd/98h1ZopUvXbLBgFJ0oWXRUijLRHPP0Hoc70NKKaWkWpzzlX+XTXPOZela+KVLOp0dVjSVmBArkwIVFTezYpahUnLR2d7qbF9qNOI7D+NF2ukUPdYJoUUoxYwoCE1GAAAgAElEQVRgVe2aa123LoSsufCOZuaPgdmJE6FiCoBZjLRo4SVWWsKn2cLVq6h01zkaXoJnVCztgQWpk5AnhamqQonAQmAnjPrAw3LVti9aVLNGm5CAtJjy2u2ilsE7sMyCMVXxZpbwAjwLGeU4mRmRMJPz7CjU5sFqZY4x55Ilopo+0ZOFPl3CfV30EvEBQFXmYFdVHW1ZtObA2Cq7lwFQ1swrBO/Fiak5x+TVOecbV/WIkuZsEE1WlJn6s9b7HrCccsq5Dc0Up0ruzTmLcONc34THjy7Z2TRsm85vLi77Ve8Dr1ZnTHJzfVdi3nStKFrvzzf9um3OVmsbp7N+FVzz7OpZ1nJ19mjlV197+934+z96ff3qUCIJk4INAnrz6qWHdKEPrr1+9ebNLVK6O6bUtM1xmtKLV1ePrJgVpZRyUaVTZ7dscBiPMQ2p3UgIziGuusY3geG9a1xonSBHHXaHabR+5Zgb8d47Tim9evWybfpHT842Zz/Y70ehkHPc77cpjQWRvevWjeto3b1VEj589dOfffrTdX/1jR+8+8O//8P/43/5s/3N8fWr18NhIPLOBSiTCpMjIs1WopYULTgji3GEKpjYM3sqJc/QpTj2bdM4CeY63Tw5YwcOenmx/oM/+N63f+eD81WfbQgeT84fffDOk/fef/Yf/7N//NGLT/7kj//4L378Z6axFGz6TsHD8aCQKcbsOZbYNlSMp7HURgI5KSAwE8fOOQMVzcdj/NO/+JPvxvyP/ul/+l///n/1Fz/+v01zHI93r15oPEzD/uWL529evXj8rW9+7zu/gwbOC0tmdiXrNCURInK10+EMFRHJbGh4eU8ZQKG5LWApSlygWkDCcsLHTxabSO59DgA0y7TdI1CVw7MsB8JQ4/rlGZteFoaZRYsZ9sU93L+4DrNLtABjC4Z1bypr+9gFGmLiqgBoCsfVOrKSgQ1031mjjuWL1ndG2wy2ZCYfpD1wkk5nZ20CJCUIKSJeXb/Oer06786vLgFarxjOZ0vIwsbKKNk0ae10G8TVpKVqgRIsG4SWThFUCYKzDZ0Tj/WaH6KEywKK5b8FR69/VmFDu79eQm0Hv9BhlzIKRS0SZCEoUSrWeEdEKeVSsjA5Yuc8r9v2rE/TRPDOW9FjBoa8Myvf+87v/vGf/E+tC+vVij3FPFpKjTgGDWkYj8NZ3+73w932ZjrEGGMqyQv3rQ+ehTGmKacUfBt8G6d8OMa3334vpyZGd3b2lilyTqraNt2zp+1FTlnzlONxOk5jUsC5pvHdsydv92e+O1+r6TBsg+SrC7/yKcXjGBOcu7i8krXQkLp1fvfJs0erK9W9kk55MJfBqmQG886vSAD4QJvHG4BLsTjlzeacXeOb/gz0+ub25m6Qg+ZiIPjGxAUyy5qNSKTt2rOUrWQDKQmFIE64cWGY0rAdr28RWmMZXLCSRAu3bdutzi/tsiRf7j7bv4k3t1uNxnCuafOQdnd7BJqm6SL3Wemz1x/bX8J1ePvZX3zt/e+8984H/8nv//2++0dda+Nxv72+ff3Z6+cfvvzwJ8/vXue4ZVJLUVVLhShDq0oaCyRgdSZnF6vQhfe/9Y2m77pV5zoWLybY7W//xU/++fZPb4jx+OqC2O5u7/Y7OtzJ8QCUag6SFb347iNi+I7DmuF1l3fH457Ju5ZJOOccXDi/PNdkN7i92w3UkgsiRWJJb33vie998CHlnI9TLllE1qvzVdvGYXz585dxKukA1Cq5IzBgl441xf/sW+9PltSra+BcLnlIpgaklFOMjQ/O+RBcSimNqYycfFYtMSUHl1+MCExueR8ICJAgnj3IVMsUxxTz2p+dr6802Yvty+tPX+BoYGAAPNAAHdCh7X2zaa/evpTgwv6gZCkNkeLF1RkLxn1W5MJCYJFm+/wYj+nubru9GzFVLj1Z0SoG5Z33rmHh8VXa3oxvmkGpYBZBxw//4ffWq82637x5eROnl0ggD8dspFlNE7TkjIwECDACAQjIZoANQy4eJkyelAgJCjhy0xTH/QCDY0Y2mywVCGaFUMtUAHKEUkqioJ7USjEhHhNefrodUnS9m0aKY767HfKAm+32r+2nX3v6te98/5s//fOfHT5NpFQxfDOxrDCFiSWNlCBVJoXUGfvqWTrLOk5xOkxNG3zbBGu1jGVA6xoyDPsBTpNH6MR5AvLN3XOlzTvvv/W13/m9lLIpieddubm5fb1pzlZdM5XjftjFFENADHAkZqalwLIicG2WZrV6GmZGX4qZ5vjdFj6WGZupQgkJppZiSgQkQxYjb93KN51XlBylJCOmYdRJ0a2L5oNvcL4KrMcf/9s/PTuTb3w7/Oj3vvts3X52++qy6Z89/hpDQ+OPerwZbq73h1dvrtVsyuUXrz69vrn+we//YXt5sT3ut7e30xDTmN/c7f67//5//Po33/n+7373G+9/cHV+ft61jRCrHuPe4jE49I340BQQ1EWNY04ppcIA88ub7Zvbm5u7m6LH0KDr2TWNsnv54rXr2zHmz16/2h2HccIUwYyzMzRtq1R8QCmIpYzTqNButfE+sFHXeEv8/OcT7hAaF69VS0IAGLKa+El7frU57/1n5ZWQZ2ZDiSVNxyGX7Ft34S/3w3G/3Qu7NOWb24QEHIGk2RQlcmHOFotC1UqBLYV8Mz5iaqUyzqmSBlBp2fOShyVym29tXWcNi8DtjDPVsJWtNk/hmgyfKC6uAOY8Z6VyL0S9+qoSs8Fm+3KfXKJii9ABcYYRkWqVkKnjsgXpundITo/g4gc9gNTSSc8KC2O8ukxmtij2VsDsq6Lsh2H7DF1VzN+Ml+5V81HJYHwPbSnVx9/D1/hTwDQL2lVngwgkXIhpvi8LQFbz+DN/vP6w/PN06bXikmsG8j59CVqKeZb+n9VKffnK/ubbQ7zihE78v1c5eNr+5iWE+CqQ7Cu3r9ztNwTkvjARp3q3Xzu20ylOuODJs/8VJ/oV+OJvtT0MJB7CDV/Y53S6h7ARHnRg/PK37uHwv93wfgUsesIoHz5/p3FWNHCuN/zSQZYjzwTFB/fi4SWgqN53g6qEBcwvAAtVlKo2+zsVLWbNKWVTxQPbNPso87mBagYre6qekZUYTJUdS4WsCq2TLLLEtXurmcnpdZ9rYmYkpSb55iBQZ9IEWUW2FoBbZ4bmyWaRVXyo6obNcuUMZmHHmIsUZnao8kK8ZKps7Couf8+/xRwEPoh9562kVAFFsvoAzTmNulfRknNW05kIVmdGbVZLVyaa64GsrlAV+qqx+qxFVuPA2UARZSI3R+5KpyWhqtKjkLGyMZHOGvtGNdI2qyE3n+Lb+Q4SmLiyxWhRaKtNvKrCPQsRM+qc5ewbJ0IQs5JNiw/svDjHWbWUmLNlRVGwoXVoAjkR570FKUXOz8+H41AbIA7j4FjON2ePLy/6LgzDIY0cxAf2rBaPE/Iu+CBGm27lN0E0O5ZN2/RNc7Fe5/OLVdMKSwhNTsVDSiyNNGvfXhc73u3gpO0736/7ttv0540Pfdc1IYxjbAQ543BIEKcZY4nH45iyFtWci5aFAFJviSFPOY2p6RsrpIRSYLGUmAYUtrEkhvFhezgej6qtASzcdV3XWxcn56RtmiaIKV68eLXdbsVx3wX2/jAORdNqvdrHfYpKnQQK5squbMdt+vv/5EfPP/z0r/6q/OzDwXYppVQXfohj1zjx0rG0wciyFZDWJl5Koka+c/UmFiulZC4+pgjR3qPv5IOvf+Odt58+feuKqeQyCGm/WbGV/WE/xfGvfvpz1zXf/Np752ddyukXzz90bXsY0jRtqynwzP26p8lfHw4pIjinxjlmco6YTaHZWNiLg9o4phTjZy8/XX/U/uVf/qUTi+MxHXe9F5QiBCEEJ2vfwTCNGYqmAwtpIdOqbcpMmH3zGceaE3wLaWoW9av/tKKK+grM3zhtJxzn4UtMD3JrxLNsFi1QFBlYtcyeCs1sA8xWUehUnDhb2BmYqf4EzeSr2gNh/u2J87V4nLUGjkhmyWqAeWGIAUR6SiGe/DzMRXT3lLQFjptN52npnaH35UtmBmM1KyAJHh5mGKaxo7Zpm1qSNp9tpq5KZTVZbaPDVUtvsR+ztuxsvKrE7INRzklPq6XEeR7p3IloxrBocb0Vi0AelBfbNCd+Zc4Qzx+i6rmbAjAyEYGpGJeayCAjhsJyyZYnE80U1WvwJA5lBIDDcUekTx8/evvx+3mciqP9fry9uxMpT59eDMfjm1cUp4GvLmOcUp6tWs5TSsoczHsVmuJoRZ00pVhRu9vuz8/Pc7GYy/qs213fAsYgEYFI13XJdLvfxhSH4zBOu9A1bdPuDtthF0NwEsCYhmH76Th944NnQ45TzuCmDa2C0xEraa82VwGNc1MLyzYSxKjU+vpAIVmOZWqcOKaiNJUi7L1vlcJ2H293x8MYm/6qXa3GODLntmXnxDnqexP2Hi3RLsVSirIYOI5xpSV75wyDOLu8iK6RtgsKqTpVqqWUyZTIrF9THEwOiKU4i8TEjQRpITQMw5D3XYt+1eVSDvv4CcVRP359PPSfBVD+5u88yuO+TKP0+u73mm9973se514vciz7/f44HEspMaWiBQJ2AkfFdIrTkIaDv9mm1/mNFjUSZBRDKY7ujmgamJfQhMvQdp3vA3ne5lFZveMAoFt1ysU4FY7RjpMNRRC8mNpwPFpB1/SrZtU0Tbfq81WRHAIalyWjZCnJ8pQTjDi4DW8ciYNsX+6O2wO0SJYyFj0CCVyYGeTIFLkU8cLI3LLvGKx5l8eUrLDCHIuAPLGw80ESSTETkmxWspWcMcE5YUhGUisAgvimCd55Joo5HQ6HkjRIN6VBk+VtxpFxVBRDEBQgGlTZXAidFM8URKggGZdR9y2aoWgeUo7a+taIpilzlOvntzbZ8RgxAkBonJcAWNaiapKEIaTS+BA8QUtCShZVMxLibSykzbo931xcXV7uX20tF0cwzAL4C5uTwERMcMSenXcckGJ0KuIa35LClZJyNi9kimlI7IGInLN4cZ6smCabO3xBczEULSnnmAC2YiqEiXZ3Q2b9+qN3CmLGtOnO5TzeHY4vX7965C+dpyIjDGZS1KpTaMUciQ+hpJRyLlFJQMwwVVMnDc1ZLxDx4c3UnoG8s8wmlCczMQhDyLGs+latqCUSi7rfja88GtVSUkrHdP70vIvCXPbjbdnnlV6OcYwKMEjYclJkrlyVAtSKaRRbirY/54uf4qkHDqsBJMS08FNqmYMhjoULmLIVkBiKWCzFKLSeTYctckxPn54zGlXsD7ers77gMMa83cePP37evP1Bvzl3ooRc8ni3v3n++g2J69fr3jfvsz2Z3n/ra+/KeX+4u73N8XZ7u9vuru+23/7h73Jo3xyH9MnH57c377/19NnFZuOdg8XCRafaOp3JMXPmNNmYYkqq5tzjp4/MCTwfRp/LAO/CaiUShmmaUr693R32g/jVei1NNhB7H6oUY9tC3KqMOccxQ5tWlUueSpmyA3kGxG/ay6lL+5s7VlLWUjS11j5evf30rZ/89GdacDyOJasWtVJzZ9quVnDCRymqaSqYQJmoMBmTCmVGgWVlJVWCCVRrwoYW2gROuXM76cnMXihsSd4sy+CC0cxL8D2d3AwntGjBtWbfiR6ISC6awMDSqdfAIkQ0K6ho5W0pzdIl82G49tyYQ6T71f7ByE6xNXNVyKyeDltthWwPL+H0bbqPm05+xJK6xMmTOUXHtijhPEiD8aKpYCcF0mUOFgnvmrBkW6JUpdpdp84DVUo3L4EnzQ7bg6j/KyP3CroxCCx8mo5ZQOtBAu/014NE5udezi9/9nmuzC+DR76AFdiXBvxbbb8Mh/nyoX5rAOsLh/vbgym/yfa3BJXsgZDTb3KiX13E92s3erBV4MzuRcS/uFv9+UQQO70eD/c80bLwS1Ct33Y7HeELJzrBZ7SUCp4+/wIa+PC7Dwe2HHnBhu/bC85BSW1AasVMsEjds4hUShcRiUhKydSoFtwBKSUAqdYM0jwbmgsA8PySn0yMFQVBBHNoYzCFklaJvTnaolnh5MTwBIOJcsmzDnHVy5vT76dleIkIT7jWDMLBVObABWUOa7nWLC6qhEaV7OqoqgdaBcZnlRyq6tE0A1o4sSeW/5dn5eEzUwdSavPHeloqyjCykxhB1lQ0V0H3CmDNln+W0qcZhiwFZlrU+SqLBrNK+qiUihlYrPwTghqs6FyVXRuuCYnCFlaVGbD0sNPliTmp7pwepPvHjokJwqSmxZZy73khYGYnYBTNMed11zoREuTEMHXehSAi7MkTgkFzKimmkoowwKnoSJoZJGLDcT9Nkxfxwmh83/aPLs/O1j2sENnZqj8/P1v3/Tgcb66v1ezy4rLr1utu1YfWSgzOrbvVWd8/Oj/XIa2alRblghwLQyiTCJ+tN2ft6s3NdYrZQhFjR/K93/2uY3n86HG76pzzl2uYa+CFiL33PvQsbhj3ORc15FQsL3kbUjIuc4MycRyIMsNZQYxlONwNW2jBar0pqUwR5W48DqMW7dZt04aqGQdTJghn1VFLGsY8DvH8YtX3vVkeponA4xSHw5SiMYJ3DUOa90L/GH/45Dt/8IffvX5594uPPrm93h72x5iy5hyLd8TMYgRiSBCAQWowpaxqJmZcmNV77xsLK/+1r7/zzW+9/+jp1dO3ztXiYX+73Q2MVS5TJ50QpnH47NPn0/HYrdr33337d779DRL6V3/S3my3w/iaWWY/XmS1Oefx+Ol4ZwP8hVflnAfnhcXFOKacpIFzLIRcyu327sMPf/7kycXt3Z3liZDTsC9eGrOqg5bTtJ92/8E/+faLX+yef/pZTJmJWJjZ5VyW2mFSK6ZLU5rFfILMaudinkFh+lKh78lmUpUseuADAWCmh8a4AtB2gq6XP1X1BBjRsvfcAbraqhlaAcnyJftc/uCUPZ3BJrtPMBhVrIN0aZx6woUehCLAsgrwQq0k0sWBhc3yf6eDzpbgc86xkhWDOBBrUURMcRrGoZQN2IYxpZxJtRSlosSgKtFXSu1UVLmeVa+v0uutdp+cRcoWcwKgLqn3+BkVK3RKb9m9WMY8RXO9sxHk/jC0VCYy0/IzGERmjGyF5/ojIRAUGdmxC02oQi9aNJbJnI4AOetaz6zIQEYcpxSPOcgf/vDvfPjRv3v12avdcHu7TY8fdZ5DnPJWt8x2d7cVltD4pm3PLs+8lxhz0TLFYt6LFxLnvDdF0/RTfHlzd6eWCH3KKcWpbzsWN4zTMO0hzjUueL/q+pjGu9vkQ3N+fu59SWUfmDfrdtXr9fX29ZuX4t9p+r5dOXJdKeIoT87ev3ry7tO3ibE7HJKL2Q5qMdOkXiJRAedUxuPoWzumY1H2fr1ZbabMx8nAoe3W67NVd7YpBux3OY2H/XR7c3SevXdacoo751sR6bp2tQ5ObEg3U9xOaWDW1vuLiy27TknAjoPjyXbHuDsM05hV3dnlphSJyu6gVMDkSuLhaJoMYk58zKnVYFmKlfFI1zdpm14ijAn7sXyt7eLlWs67dtW6s45733VyNg2puSt+X2JKU0QuYsS1Xj2ZlsQh0+34Kuq02+3GMTdN06/WAMWc2x5k2G6HplHPnih4R857zdmJ26zX/WqVdRrLeIzxGHeZouupCz6EkHI2xTCM4yEe6Fiimmq76Tg7m6Ck5GiUuB92Dm7drVfdmqLZVOIh7t/s8mANMyJhhEsBicqUrNLJBdTQYdhZT85L4ZTycEgpZwSPzgfnHYw0ZktqhpIzhBnEmRBhY4GRp8Y7NylNeWAVBmuywoWFNesUYyvN4bCbhiEfy3SIlGAgFEMidrWJe1HVQxpsHKR3zUWjRbt1mArDlajHYRwbaft1n496d3tb9havJ1Ku7Y6FxXPj2auqgmBKLFBWRckWh5w1QVRcZWnZRz95vt7c6qDdqlu1LQQaVROszGaDmQGe9UONSImUycSKjvscNsFxaIMvJodchmEi9sHaOEUCTNUHL8KULMesJRuZuOBDA6ZYmBtu25Yde3WpURXENE43R1NJichC3zVlOIYmYSIouk3ze7/3/f/roz8HKxMYYCMuYkXzmJ1zTd+aacoxlmgFIM4132JgAZt4dmTMSoGCEaVjSkjoASUrpWmblKI0Ji0yhttjCtk5L86Jbxk0iVOyPI7TNKXH/SFpRgRQW9qWGcq3oqj6lrOrpvowIq6LTV3hFm3TGVvgE6F5XsaYREjHYsoJWnI0aMpaCiCSR1BmKm08Drvr7CwyJ7/esrtpQ964NnT+xYs3716+L+crkZyxP4zH3bAzMdf57XC8e30zpvzWO+9Z62+m49GKO1sHA5s5Yne2OYz5+fXNxy8+c4ZPnz9598nV199+9MHTx33XI5oVVbPRsrJTNoVlzebIN1LYfB9WfGZHbPeaCamAhPrVZvvy9YsXt8r+bNO13UrBZqZqMSZyqe3WwquUJ+BQUi6pQONhXw67WKa0avy+lOFm1AEwJy54hykehrtp2KU8Wuv6POXduBvEiXDbNcS0H45ZVZg12biLORkUyEDFsDKxEgppsXovyE60brM8+y1zrzuiufXVCb2qa9+9Btb8IZ1uI9/3K68h3kI/n/dmkYpgVRmI2ZNZAu1TFm7RR654aA0oTHnJFQIV8hGQiDOd2wzRIrwzMz+YcOoqRVzrb2hxb6w+kwvxfH6cZ7ojzQ4YbJEBrTDQ5zy6e//tAUZjNRtGs6cn7NTmDL/NOJXVckea1eLIDKWoaaVUVFEJGEDOLdc634XTPH8ZvTqFhFRJF6xktcFTrSZSPjHdvgA70ucAq4eZv89tdo9h/Yb4CR5QcH71/n/77asBrF8NkZyuJ4RQcYeHVV0n4Aa/ZLp/7Zge7v8FNOfX4kpf/u1D5axfcXZ7wN76GyBEX/lIfQFy+sKFYMGtsNzvU+/Ch9/9AmJ1mpAvDPIhyPWFgT1UYf/yBH55VPiqG3eaxpr8/8pz3R/qFDs9qCQ0oKbz67uoagRjYVpKds0gws65mCITCwkI9QG7PxOz9x5ABpWSl5OdlFvIFOLIubnaMecyD5MewPIiYCLTRLkysKr+bkW71QwK4tma1a+oacnFCFxrgMiIYbOQF5hIrQDGwlW7maXSNpSJwaRF1RS13I5Mi9ZGP2wgkGtkzvVXEqrNv5gneY4PTUQe3iBVZWMqsFIRs1lguFrQUvKsNyVL6WNRS7XemhmMQk0I2UrRovXMs5gP2AmRlVIenBwA5tnAXFtdzXPtL0/MhGIgZgZDiFiIhMDVYdXZfhLKnGaY+7ZVUomaMc+AoKmVOphZL6FGDaiNcVPJEqjvmn7Tmpaihdl8EBF2TsxKSilFS5MSLHj4Bt5X5I52t6+J4HkVfNt3q/V6vVl1jZNpigJcPnp8fr5p2tD5UKZ82B8sWsYknsS3l5ePSkqt+M63lu1ydQ4glwSlLrScTQQi8mhzwe++txv2Q4oSgqZ09+b6sj8jYC3r9ers0dXjx48e7WMh70gcdZIKUswaNY6Z8f8w96Y9liXJldgxc/e7vS0iMisza+susrtJdpNDSj3UCAMOBEkDSIAgfdHfFCBAgvRBgABBA34YScMhRM6Qw2F3V1d3LVm5xPKWu7i7memD3/siMquqWZimSN5CRUa8d99d/F03Nzt27JgjZYsZMAarWOWraRocBRg/unysHAUxpqwyjj1A7NnFQUMdum4d03A4Crvj5q57VG1FdRzHOI5N27ZtdbFbAfTi5SlGff367smz70/TmFM6HI8x5dMpxTHDeucaz/znH/+fv/Hd73/3w4/q0LZPLDe3zStJU1dR25+G55+9GgZUvuSSmFxxR8w7ct73pwiCr7FZN9uL9QcffHDxePPovfX3fvDRxcV2nI6Sp6aCgzRN/fL1y6PzeZxev3z1/OXz/TQmyDD077z7rF11H77/XeMvUnbE9fMXL6c+Mvfb7qrrujqESZNImXlagGAmLvJ3hbDowK9vXvEX0vxlGMf+eLquHNZtDSbP7tDvxxgF+uLVi//yv/hn/+L/+NNfvnheEeJol1ebcUqmZGqSM4jIsUFs6SVdnDsoA6bMrMSlHWjxa2zuj2lmZw/A1EqrggWLLnPezfbpPN/PjWtFdOYKlQ4ZMyhzPiYXLB5nHb15Np2t8Uw+Lyx/nH0cAPNMn10Z46Wp8+JmLTBzEQu2Oc1YQLRzb2mglDUTwUwkwx40slku6bxwlBuGEYTBJJYxoZ/GfupTTjlL3YY4gFnhADFLee4wofciwLAZrTOgMETNSpPT2ZvkwgY0g1pRHLQiWKul2LsM8r3neV66MKN784gApRjAStXDLF1BNBd0OlQcsuYsapbNEQd2pdmvKyIipFlVtXm8Es6OoJwBcTXAqFsHynWotpv1brN59fzF1KeuxqPLy932ogmNaVbNpkzObXaXzI6DJ+8sQ5Cd82CLMW3anQpEpAou5dyP+5SmpkV9PFTBV5VXw9Cfrm9uzLnVerW+3LVt20/15cWVq9izb+tV59xq7Sunnt12vRJ5ZKCrR09EbBzyulntXz9/drH76N1nF91qyrdJI1GeYko6wiNprNoVGTuDRz2NU9tsiBtVr1J5v245yKRJcj/qp19+OcYUJU/9eDweNY0ZVte1ZByPfRt2RNjtNk+e7a6u1rurd7p6k+R5CI6dN/PONafjmCS7una+qSs/TZyQs46rzeqSXdWtb657y74/JvKO80TONaGexkzGp34kauBDht7k3o95dem3l7v/969+8WiFdx+v5OpCWlzHu5w+3+4ehSrc3N68urk5nvopScySxWL2znU+dM7VgB7TrfMECsQUJ9M0mVFO0lZX3jlWpMEm0TgcTod4d3PUrKv1unMdtYYscRiG3A8WXQWuyYfAzExO1VQkTekwHb16b96Zk7lsBiJKzEYQlbLgpzFOt8N0F715z9L7SoIAACAASURBVJBjTmN2JVcmTOpNshQWoodoBDir6hRjGjPgPbFBJoWkKtQiOvRDzipQzy67DBgJKgsU3LrZZIs6CBg1VY6cThJFyQNiFYWaaiaMp9Nwm0ng2RM4iQbn85SQibyZmEgG2/768KjzXdPF2K+6xjjnGJ3D1eXVutkMQ9zffoaBMBmssOkdkyvlZzklKdGyFs0bJmU2csqqalnBBkJ/PUz90HK1vlpTYXtEKxrWZHDkYCRSmsqQ5cIBNzG1mKt366GPORrBjVMmUM4RwcFsjCIJJOY9SxJTYe+CqwnEzoPU18G08pX3zhOzq1zoaPQpWkSPdXdx/YufeVcBzhQq4uAnHi+rdvWou/hgm45y2vdG5n2dBHnKoGwWHDvn2NgbgUyS6txtpFg0zb4OJpZzdpVr2+b69a1bs0iEQiJEkqSp802zClQzuTSmI5k1VDsOtdZ1VacxJ0kSJVnUYpAZaUwhBCMhJXKcpAQDM7Dh8DBOKcsjGRstAfOc+zUDL4td6StRcswKMlERciY0r01cweDIcRoRs6bxcDqd6lae1ZWopZz2wzDd3Fx+8MNjHwWkAjge4jRZdm2VyF4db1/d3K42lxMEOWpMft0OtyfxLnmKsOvXN85XMOmH/rS/fvHFxz+p2+Ef/YE3ef9qVwPMTi3HKY2IFjI58hVHKNj62INBgV1VdZttise7w/Fi411o9sf+1Jty8nV2gcixCpmpWlZjhTOh4ZT6UxbF4LN3JIkc1etVm4/pVk757g7Rs68tkxHYNVNMN69uV5sVBGmScRpL8PLu0yc5xzjEPGVHPI0xDXOmxMQsCpQ4Q6WUxilw1hU4R2iLewDF3J4Xi1Lvg2zdeWXHnItmYo85KinlMnOeeqYJfA3L5+wJ3O92jiWX7Nc5C4aZN1B+WeCk4qnM+irkHJuV1hsPMt+kJfzxiyoCDAwG3w8AZgXmB+jYcqMzyFdeLFjT/AyfYbRyz2DYTBGfATgtBS6qAKnNZAQqo+HIGS+BnikMLEU4bynDRCnJAVD0LQsOuIgklFGwGdwrzhTzQ6AQhbZ/f0cLymazTBZK9cysDf3m92IP4uw3vqwFNPha5OG821f//Cre8m2glXOcft7/oU/71s6/FgNr5sIshJ1vOsfDt94CpH7F9haY8uts3/JQD/Gm/7CTvoVYPdy+6Qs+7ywivMhdnwHBh/DWV7df8Ty9dVUP4bmvvvtNb331IGZWeFIP7/dr7pHuGcUPcGpg+X3hdN7fmpkVtSmcreO5BKbQpphK2d2Zp7bER2dSTwlBForBYuPMUCpzynlma0I0G+TZjha9di6ouRm4mLeiokcEgxAAMIMcjMgczeLwi0FlwKhUchfNLHVw5B0xWAu7k85NWuf6JAIAUSGi0o3V1HTu24WFj3qG/O5RbT3HyGKzgKIzPkvVLDfLhadAQsYKiOnCJDAzZXYsttRhymxFy5DN4TS0tEIjaBkTIjunR2AzNYIUREU3xhxcIQ+xEZO5Nx778q3x+RlYaB1qIraMdsnclV6IMBWxDHYsKiBMkp1qBntHvvKtK228TUSIC8+Oz/cfAuqG68o7ZjNqqkdMrq3bqmo8u6au26rqqma9auLQrrq2q9v1qqsvHm/b7XG/T1EPh/3xeGcx/cZ770/90FT1um4DfNMEUiA0VOR/xcyEmdd14y+unlw+7uMoZGIY+vH1adputtmyc3y1e3R58dgOx/3UBxeI3XQanYMl06yzcJIu/L9M6hQCSxacv7p8NOT9MFGKmqLkjK4LyFUcpQptvfZD78Z4d+pxc3OsWz8O8eRPlXelsH+z7nxoYnT74/7umIk8u0BZx5jGPh4OqgLvSM0m7b/70ROh/RcvfwJzOdnFk/rJs++0zVqT3d327ZY+/uXL4SUwKEhRAQFwyAFVAxwAh7zC5bP6Ox++/6Mf/vD933h/93htlg+H29vb68ePd48fvxfYLKcXNy+H/eF4u7+7ve3H8ThOePXi0dUjYSbmR4/f+cH3diY/ub45rJqV4+u76+OHT6qq46YLe5dSyqQE54nLE1JkpgooSgD143C395998fnjR9tQGVteNZUzrZhFcjJNpjf7/R/+Jz/+s3/9MySgRmkdUBydGRcvZklBOgNUCz5TwHdFEbeaHXMY7EyPOq/BZ//koe20N2372Wyqnieqzq4TnRvfnB21GRS2s2OFWbT0oY/4wAVdqJ3gBx1nltiCHthD4GwElkPMMvXEJbyYkZ4H1/4Ni4jd+8gEg3qQGRSueHyzrKGIeAYSiiwEKUxMTOksIaEGJjZAoaY096lWlEplmC1Z1/u7sHklUplLnJdv5Gsu8+F9FD5sWSWMTUmYCQU8pNIkyIjY5kRCJkeOyZyKmZo5xyH4Zt003njn1aCaSFNgazfYCXaP6m5VdVWlSE1TrVe1ufVmu3v36ZOu7ggcUxzHvgqtY1Srpq6b4INzjuMomkDOyMYpdrVBVdQltTHG4zGe+kPXZU3ym+9/WHs3xpzTNPS9MXnvVrJipraqmys/pHEaJva2Xq1360r1MGXbdqvVqnZcM1djP+5v7jydLmv//uPd5bY2jESpW3WOU+ZpGJNBj1NunBqzd9Vq5Xfh0STjoU/ZfNPuvL8yhDycfvbJT3/52Yu//Hc/u74NZrLdOLJU1zXAdZ3iaMfT+Mm/vwbZ1SN8/7ef/M6Pvvv7/9EPLh6tH22relsd9fTX9otXL26OvRgj1I2vsxG3lQ+7tRhSHpq1C7U3cinSMPYOrls7wIlwyhOBFZLjiKSIE+pEIQTxVV6F8S5ruB5t+vK4afOmrameJFyvXDPYcaS+Rx8BcYFcxb5h7tSq/qR9f+y2VZqSJJUJOVkyc+w91841ta89+xSnU98P0xjzlCAIMJejDqfJxnTq0xB5CBXqNri6aE2qRM2STWDZIMgpiSgU3qpQBa7ZkR3lBIWpSZQkcTqO436UPgcJmAjRnBCMNLMZl5YnWpqMAlEnj8AEMy1HVrFpNFN1HlqbGSSJRINBSODMOVe5yrvKKvLk0qRpiqgRQmC4ISZPzntPgJhU7AmaxCAgQWn5a0SN86dplASqyQeomkZMfdRJ66ZKWUPlUpY4iik2TVchpKwYgUilM4MZQKbQLGJmWRKZK54QqzhygDMDqTLUlvLnxkMmnG6OhNysupaQiYJjSSaiZA5EjuaotmhSk8EEYPU+9HGKQxpHPwxD04Tg665rOLuqZay9HClPOacIo1XX1HUNYBzj8dR3VSsqmiRTJiYX2LW1dw59RsKqWTGFaSzdRDQb5RRvDq/gp9bXv/nDD159fn2SU7pOykpsfhXISKKMeXTmAC2iqN7IiM9htEItJmMCmWsaDg6WuaqpIXHmV2C2ZCmLB1XELGYxGxuIE+U8DTBxcYgW1WtNAe226h75/kXOmjzXJKVunRg8O+dU1rWZhHO/JpVvbA7i50ozsxkZmB39RWma2Je667O7C4VGA6CE6ZTHnLxX7+uq8kR1cPWqbepGOvDNzek0xT5H75WBY1JXN3VdC7lL55rLq9V6d7F9B+xP4xRTHiz3Eg/T+Prubn9Kq/WucpxjTFMeR8TT8IvPvmi99ndX//iHv91QyDJlvZs0kROqyVGwPESNx+MpAacxxRgVcjhNp+MtUQ1fmbEPiIKUaYoAVDJEU4xpGNI4ZovD3c1wOmRjEMXgfU4w5aZebTd23CA7l0/IY9IkMEVgsBeV/nTqTxNEKM0PqzcXE6YxeyAqJC0dNhUQsHqnjuG46I8tmMoZtsJbwWlZIhdfwN6K4O5XSZQ8fknsFP+BlozYeZ+lzJ/UuDCl6cH6fD47MduixfzmWR5EuA+iTjUjfXD5gJxj9vLUzajXXG04v66Lo7SEODbn4xXn+BE2l8joPWF7fiYN9hY1Z/7E4lcs/5libkTPc2SJ+7CTFgmDsyOy+GTnL0WLGIGVMy49xWzpG0izAieKe3NP0DGYY3/+3bAIpBaheMI55LVz/Ptws7cRx4d1VMC9l/g34ht/Z9uvBWCV7YyW4e/vNv52t18TMlPVgkPRm4/7W9tDlPGsjH4+wt94DUVSHUBRUv+W0ObDP7/9bZ4htq8e5PwKPVCgBwqM8xA2mvc8n9Q5ZmZTzaqw+U8AKUWADEs5i83oFRbygJo6cszsA8FUZClSK9NPreTlrfDO5oLgObacnSAzwISEQcZlTpqqkVOgCDiZEelsno0ZZiAHMOAB5tL2Ts8GC8LOzwhWqQYvlYJEICUCeyLwzMYyLUwKmC183aQFarfS+YKK2BYehKBEMBXm2crdi9/o3AdxrqdhghlD4Ar8ps4VxS9mVSNSGNSodGHMs9m3hTMCmDmDsitFlc6KrBaZkgIMJTUiFTOfdRYEs5KgK42+nJ9tozHYLekQKuzae3Hk8uyXokYzM9OskbRkUWEMYhIzKCwjmXAl7Dj40h5IY+rZ5a7u1utVU1WATdOolkPwUB+9xUpVM8MRA6TsSrWb9xya2jMjjuNwOg6+at559s47j7FWEWlCc7m9utrt4mUch+F06D/75acvX71Mp9i6punCquk23cqz96DKV01Vq+o4joe+JyAwNZWvffvRe+9PKhGYpnhsD8Nx/PC9D2C23x+9rwFXh6ZRa5p2GEfLfUpZJmGBGSgrDKRGKiRIYwK78RSbsHp89eTT531K2g9xHErhVEgxx6zMPlQtORviqR/y3V3PLm/XDRuP4ziNg3O0Xm926/V4iRj7KURHcKDTGOMwjj3SCMeoqjaETqUyw5evvzgeLE1Y1Xj32Ye8ottTPw25rpp/8ke//593G1Wwq5yvzSylnFJSyVHS7/3oR3VT7Xbbum5yznGaTnH88sXruqkAp0o//eknzz//5aef/sXQKxSe4ADJmBKu71C16Fp0HdTwhz/+Z7/3o9//8X/8n/7Gb/wwxul//p/+13/7Fz8drofNbnWx2b6oe4lC7JwPJjnnzEyOmFQlJyKCJ+fp+vYQ0+mdpz/eNJc5DXXtSbOpJMl9ivs4vDre/tGP/3nTVsjglldduLs7OK6ImNnDz1B1MTR89mMWkjzp4iIUC6RqCjGle0znbPa+gue+ZYOX3cuuxfq9bY7P4JnOv+jDt87tX4pDQl9zgNk+l0jNYIsIxvwSkSJjtuqz0l9pGmolaXm+Zru/v4cIEXCfv5zPRSjmTqx00s6mgoSck+RUWL05KzJQyq8NpHDlvFpMKWMpISQrzYMWUwMQkZszHXBEvCQKyEA6D9A5ZLof569upKUZ66yGU/RnoObJeQcmkywqEPAZeWQYLMPmAlGGVcpra9ZV3dU30zUzeYiHtoGvNqva9+tLX7cgZO/RdfXTp4/e908unzzatKvj6dQfj6ehv9vviaq2a6pm3bQVuZAkj1HYsmMPuBhlTAnqyLwDQvBq05Sii3WyVHnznlxWIiVWhWWZJEf2vgrBhUoO6TSNgeG5rUPIyRsF8s41/vOXLz/77PXNq+v9qxfxcP3f/zf/3ZPOez29vn3tG25W1dFS8kGbzZjG569fy8tD8OHi4upqd7UfxKzuulXjr3rjf/3nf/2nf/ZX/+L/+vkvXuHxFtsVVmt+9ux9TTwMadWtcpKpl9cvb29v9PbGYDge6OWrF//qT17U/8P/E9b46CP8+A+/9+6zp7/zg3/6+ZfPT0P/+vb2cNzf7G+I0XZd07Vt8Lf76+AbboNRmEY77GGZeMVQDzSeNCfL2cbjGOMUKuw27eWjbdOsKIXhsya0u+sJP72+w3i3fVQ9/o595/dXJzvFlLj162oj5k5DPvV22A95zHniodd0PDyWDsiB64Y7V1UQD0Hs0/429l7X61bUTsc02oSgu0sPZoMc083h1kIbzOd121Rt5YIb0xT7HE+SxxyjYc4YQSMsChQWomt95Z055LsMARgIZKLpFOMpo4dNCRGsgQWaCUWfgEmNjOcy5hgjCTvzqtAM5BLoEgyWbIjJMQIHJhM1ViJlFs/OMVNVtSqSYobAsfPkyQAxb771zRDtdByaJvNkmgUJKlAVD2J1bFSa/1IAl9hrBG5z2k2rumq5kyFNvU4nZEXzYWejy/uMA5AMiwKHQYVVcl4A9+KFaFbLmhihWOeiolAIqq7GeMJ+OmiOrFxTUGRkZ0ktqag6eIYjAtjMwZiIzRwSSTnv1I+0z8M0VBU755pVs67W8SifHl+kPvkmBL8qjPSEzMzcUOvrrDlqhCoEIApVVTVKFTlPUkNydqAkNPWxP0xQkMN+6BV52zX/5Me/9eEPnr732aOP/+qXX36xr1MI5POYRSRLgjlmeA7muHQvgcAKq7aQep2BYZRj6tFAeKpat974bteFBpNgTKmSwFFjlinCCDSoGeJwnE6YRrQ1nmxCtHj15OL9D/Jf33za+EZPQgYVIfJUxquEKm+wdc5BLwhGalZanpRQn+ZCeps92TlAJ/FmAjBIUDoAMhExspnkEVlUueb+EFOyUAOiqxWtg24cbk+vfy/HU55WVS2g61OU2u9v+yFORi6KXB/Hmz6C3N3t4fnzL5t61dRd3bah8hujVeWCDxUATYlHTfrXP//k5YtPthXeffLuo82uccFcDQdzo5IpScxTPx7HlA6neOwnNQLk9np/OI3eHeqmq9v1xYVNwqFeqVQxyThNfT+O4xDjZAIZ+uPdOJxKp12AMsTLJC3zerd69MTt2qvTzfiLX3zGxK5i8lS1gZ09f/E8HcdCE7IMCHQEIrtMqialaYMAufCDglPH5mhuisyqedaA+tXR34w8YuYRLKvjV9dLM/DcytDIiJXn1J+dd2ZA2RZJgQUPoweRJBNpaQ3/Ky6pfLDkD2GiZgt1psSeX42azQzKi04KWcnDWxGfMoP6wodX0vJYKpTn254huW/Qof7qcJwdIWDmOlkZBHOGWXzFjGd5ZiOaU3FlEOfcZtlEzsHjMvgEED84IRdtKzxwZEpgq67ghbDCO5sVKkqdCxZ6BxGg9OZ90df1ETU8cGLfuPd/INuvBWAV6OTboC1/L9vXomm/+lL/tm7kXDfxFnL51rke7lb2LK98VT39rY0eCGadX/kmmOzhNfyaGNY3AZRvgZjnnc9Z/QcJ/3kfx855l7NAZix9EQtbilywTN6Fc1Tsly77w4rMd9mDCs0qa1IylPrfkkd3BiYQKcGEjIpoezEK90wsYD71+bLVDFAmtplTBALgCI6IyArjci7oAUPORA3MdkkNJIIZ1Ycao8hB28LoPGN8SygMLFKDi4jyTKbAwy8RKHrGMJa5ByyoZNHMtDxFKEOKmTSRi6ch55M6cilng5Ve9ou6IMybFjEy711FxC5rhuQ5iVKWj9JfnEtJERadhlKJWbSQMEe+D63kPaAJIpTSJBRZfQKpKQxiVjq9lVxR2dkhhFDVlQ80TkcfwGyAmiYzMUjw7ENDKqaaNTvXuGQpFRnVrFYEIqxtVlWouqZz5Hrqh95MNafERj7UHMg7x8L9YUzjFEJ45/JxgNt2O5DJlB05B8fGziiwq9h54qwK0dZ7XwViZhUneLTdWQgIPotO0xSH9Pjx436YvvzyJVV+OPVKtFmvnfMx5pInZpCJakqWlY1IqECTRVU/TxnKpra/Pdwe76Y4MbFjncY49ZGoGqcJbMS5aVpyPZHcHeL3fvM7wUM0HQ53w7AfhqldRTXdbNv1JnRtpTrBpET4jtCEatNtVs0OSE+uLsZu06/GNCXHPvhWzYG5aoLz1aSCOBKxpshubNq26nzna88ORE/ffWKAY0o5juO43+/7lO8Owxd/9ZOXz5/3x329onE8grZtk7PE4HwITkUwppXDxeVmHONhGB2Hzz6/fvnij3/7t374uz/60ZPLp7/10Q/6254tmrRNG7oafSxVqkgpmioRszMzUYHz5gghVKQypTxNE5Ef4wQSZ+pFNE3HFE8xjTElTat13V5Cs4UQME28YiJ/tn1MMw1Q7Z49VdALOLrP6RXLUupg72f2vR0rafPzjH7LotIDm2zn9gpfTY09nFNvff48axZX5Q1+fHnLitzoTFuihR018y4JtOi1nq/O5mjjjePYYg94hupxvvxzfnE25ovIK6sAYsYwQYJJJjVSs6yaDTJffulMvbQeMjZHIBW5z0IYDFoYrW/4ccudF+N57/597eDd30858DnuZcw4GUAGB3NkbGAtDTHOrueM3S8/qYJfsW8YFZKLYinm1HbU1qEJoQnUNly52jCO8RiaWi2Fyl1c7bqmu7i6NLPXr1+fDkM2I3iCywmSiOANXgEF5ZgcGOaSSkyJDUzivH/85B3lI/zYNJtHjy6GsedaHPN20+W8izm7qjKRZDnGCZON0+AcO6JpGk+HVHmtuRljf31z63x3uLk73PZOUBm+9/RxU3E/vO7HL7t6E7HpJRo7+G4Y0ucv96fDqa0aE7eqr6r6MfMqC39+M378iy//73/1s5//8jawe7IS70hyiFPz80+u26oLXLVNpaJxinEM0A2m1+iw29SXV81mV63XZH6SePvzn9xcv4x/9J/9092Gye5sW3tX5+tXQ4yD9SrCgZ0jtWhZzVJVhfUaUE8WNHvHwXIzDjlN4rpmu3abXb272HRtm7ObenrSvN+GnToKedvTXR6GV68P1cvjFo69X626KlQuNNgPQ9qf+uF0OyAWfRm8enFatdzu6u36ouZm6vV0GA63d/3hlJDapnLeKWe3sqrltmvNbBiH0xCnCU92gX3dtHWoQhbJx1McskaWSIgGhQsuBK/BsuacNKumNJmpZmACgKoODVVePU2wARghCU69R2VFScgpmAQy17MQQNhdbqwmEc0xWzQy1C64xuWYUhKnxHBQrtiZI82F5U1QUiKqSVUAI8dMlGJCNgggoMSIZD2GOPrsVByyQKBGSsTG0ymqgT07IBfmeAVk5H3SlZlHMsuDphMwgsbQX4/96wEjgnklKRXKaoq8mD5PPPe6KIlLM80mRDOPCgQ4QHpgRE6gLvBY1Vj38W4aMzJMPARiCoP3npiLs6YwUiOCpBQq9uzJYKUnjqSUJ9dtt5dbX7+Gy877Cg0UY9/34xHE6261vdjd3t7MTC4DzERVNDK5dts0nYtTX9RdQZxiwiQGiOIkEZAvbj955+rxu99/rC4L5Vef9NOY5lvyAIsaUmltU/rpuCWBYKi7kDSJ2pDjNETXgCv4Rrptt76olXOtFQhxFEsaBaq8dIR2mtv+NAzHbB2Garq9u/U1rTYtALAmycE8kSO4Yuu1JJiLJIe9uRZRSWooLYkDohl4mTOvZSkCYGxqi677ooKEBT5QJWUAnh3ETocsOu7vxrbBusa2wfef7qhm8SKEAXZzTA7VcUwvr2/ALMSiCm5CVd/tD59/8fzD9z/64P13+DEF766fv9qs1lXTppTrtrp2NzJOntGnxMJ/8fNPv/Msv/fkab3eqR6TpWQmJlnjMJ6IqkKscsQGdqiCGw2WJFdV3a3QUgPXDlFZRUXHse9P2QyVb4HGUQycQF4ST8lMLA5xsOOmZqW8uWpDcPu4CnVTBYZj9tyfTjdfvIaVZBNBYdl0NMtWUZM1qyTLKKK3c+JHZyCkLJNqeeHxEKCl39QyV3RpP0X2VsD2DZuhNMXCwkJ6I0mEB+5JWaNnB4EW/nZpfkMl80cEXsQSvmFbYiXTM53rXJtKS+X/2X2CqrmlRMdmOYKCap1R1AfpLHro7ZSz0X1rguLBqL7paKCwS3FWyXozzC0dm5cY+MHb8zUbCtHToHQfKi2dyvTsoBDzrAo/cxXO2NX9zZ6/A0NBh8kc5rZdINjs082eJJH7itOklN/2kwyk9wjmQ1LOt9n+DnCh/3AAi4jeUr86v/5rX9X/X9u3Gf2/xUH/lud6iz/1Vknmr789PNq5N+K36XD57S/jaxE6LGCQmekCgz98FwARnLtnq9kyIjRLm89FbQvBiohmeprdEzHns3CRac+l3s3mHqiuwDUMVxT1UWg98zRm46XMcKbV0swkKuiYMcBFnomJlADyjNLNTzHLjd+b6LnJl5Uug1Y8ISUYk+fZfLDZHA7eh4zlqynADxc4DOV3KtWIZzp2AbBKlRwBRoHn6mlmYnbFQosqrEiVlV6AgM2SzwQjLoQ0ijkxF5CrPBPzfYgpwZx37Bx7p9GyZVCRLC5+EsxjThJw6a7INJNm52UKJMbuzadpwSLPemTMBhPIgtPNa6ABpmAHeJBDqEPTNqGufIDa0XsKnr0jqMRpMJ2s8l3XOcf9MJpoCN5x7RyJZCKufF2qORjU1PVmvWnqZrveTlOsKDzeXWw3W2ZXOR/H2O/7V6d+HPrHl4/fe+/d956+/+jiceX97atrdgQh1gKYQJPE3IuIxuida0IAzFIm4HKzsarKRP0wWhY4m4bp+vr2en9XbVa77cWY0pCmvu9Ph6MmqaqQySybZbVYkt6AgIiVvKo69inmm1e316+v74bTZrXabsLe+uMhQphql3M+9TEECpV3oclpvBnk4mJH0BiHcTid1Pb7u34aQl1fXW7Xm1W3cjm7zaqSuF7VZik09Wa9etTWa0Ae795Jq1GypCzFxquAPLbbbV3XKYlkIab1tg2Vd44BmKqYwvjTTz87HE7728M0xjKL+zF+/Nlnv/jsky9evKpqfPc7l3VwZkhJYoptS+umJheIfE75uk8Ovt28M56GX3z2XCa1sUGk7373wx/+4HeGfb+/PSSw984HwGMpQs3kwuxU417pSbLVbeVCtb87qjUxxnEcYDmQkaQpayKIc9753/+Df/TJT7/443/5J54zeR9CXegDIkpF5a0oFuqDnNRiwIF7XYl7M/fG/H4wAZYP4usALLxZWP0NFhcAig/Cb3tNi5N3zil8HYZlc6RQjC3MDIudAGZJ0TnmwJzcK8diYrm3ebMZLEStB3yzN050j2HNXeHNTEsjHi5q7ICJzjwLJlNQsZbFUhe7Qi6LuGXIF9VDMwN0qbScqXJzJivQJQAAIABJREFUswpa6pHPSNabw/cQ/KPz/1YGYYn2QaiaYGTGpibKBg8QnJKBjBUMY8DBdRTWrtnVruKEGLU3wXrLqy5s1qtNW7WBK84kljEmGRQMEmKtm7Bed5XzwzCkmE2trpu67qp6baaqDlw5bpg1VP2xP2BKzldMHuTMSNSY3OXjyynTOBUOcD6dBuSuqptVV7O7GKaURERizjKMp5RzyrHu6qrinKehT8266touxny4Ht758J2m6redXlxcbujpxmvOe7G7uhFXmSBFNTH0Y355O3z58iaO09WuAYdQdayPM+oXL27+/N99+qd//pN/8+//et+DODhfTWOmpmqayzhNXz7fQxGjEPmp1ziBOXz0ne+HxtUN1Z2st7TbcbLTlze3H//s2vnri8t321VbNd1mE0LdEPu7492URlNT1aoO4zRKlJRyU4X1Ojiqc/LjqaiWSU4pJ2Hngw8QP9zk8cUxR0j26WCCE8iR527bCWQwHE8Utt6b50zBo2Fquqpbt113RCILLkdEKg1SiI015lM63X15Oh76w/FgYhwwDBMYvsGubtp1WK9rEUk2cC7rbPbOe+8ILDlbBqmvKPhggkzk6qpqmkayxJCmKYrkpDnFbDBikMHDefUUIWNCD2R4cw6BENRU5445KhAiAYMD1OPd954e4nDoe+QJAlYmIlPIYJpBHgUgmVmkQmbGZaEniRSNFI4CBdU89YNAmWmyiYQg1oXGBHlQSbNmjAkrewcahhNXPgRvpJaSOTgiqMkpyTEmlkmzZuIJegPtuX89jNcjBjgmb5UZVFVUVNWKLrGUJl48B69W0olzpdCcoITZ5IKBQTWtnbQNk5cpTr2jyrODFEFAE5MlYC3JZbUsGtF29Xa18i2S9o44Sr69u05DXvnd0/eeBrrrXw7H0z7UVegqrl1KKbFMOqkzc8V1AwxGZiTM2tTVu08fP370yFPo+3S8Gytq93SYxj7HKSfcHeRo17VR41Z+Y7t3V87Xaa/Xr+/Y+9KNJ6dkKhAFHBhWKP4ofVRUyawCCOrx9NmFNdlvtVm5qnHRckVNpnzqE1idr5xjNiVi7zpz26m6zeElOyTBi9dfdtiaywjIU4LBjBz5cjNzP2suZtxpkiV3UAiwXHgumMu1ABBjzuAui2NBqxhW3F+1omLoUYQVYQbLqqUdDZiYjfujpoixhq3JiXFTc+O5wWDD9em4H40hL272n335IgkZe+cZ1K03ejieDodpv9+fDkcmOh0OJtGxdF0wbqLl8WXcn8bA3kN8s/6Xf/6XH3/+4ge/+Zu/81sfhEBGXERs2bFjiJp31FQVkYeRu+CNdRmp7wcxnxIocJpkGCULRL2KE/VMwfkVs2fywdXGVUyIYzTlFOnYn6YgeZDjdAOysEbVUNUEdg5mY4KvOIoig5QgZgokRmKHIGrIGdmgRMbIVrAlhTLOQuiidJZFKPzkZdmmM5pD5xUWb62Rby2hRmaziPHC/VaAFrkqmnvFlP58D32COYc/hwJAKZopTod9LWdj/rF4GGZgYhTlurkWkLGU7QBUHIIF01lKQOYFvjhsD52zwlWfyQuL4uXM78JiFR76M7MPUTLx54zkA7wOAIxpTrLNzoUZ5vbFBXCi8gU90Kha3JriFoFKGaLx4sbMozxPIHqQ0juP6gIKGmmZi1SQ7qWiEGfH8M0h5rdes5k4vwCPuH9W/qFsf5tdCM/gyD+c7e8FTVtS32cn/+tlv+yBntRbPx9+pHAjv/bj+BbP01sgVJmhD4Xt38aVvnIj3/TnW1dSCifPfxZwutDEHsRjIABLsFNuP4SgZipSShQdc87iPZcaybJbyQc4584tHR+yTRddZBR6FRYsmkBzW3YmKwzVYi/IMJfvzaJjompq7OAck2NmVjWlZFTwpyJxwwDIsRU+Jp/pX0vQWKgLMFPL9wmJ0h1Wi/p76QFSxJVL8SIz57QYyUVV4GH4dB66YpyVFFqMJgjkSpMNGDOz48LfW04NlMK/wrdgOy8AM+KvAiZmX1oGqqi40tXHRJWNYFwE52cNZYbxEoy6eeWZVduZQaqFQXGutX8g47hEi0RMBC2RMJh0Xg+IXJHSAnsmx0IKmDr44Kqqct4TkUh2Ad6R9+QYzEpFDDaZpgRHMPVktWe42gunnAnkfQjsPHvN5phC5bu2tQYbtcbVF922CjVAbd1owu3t9f52rzmllZBSVVWhDau2I2HLUodQ+To4YjHNWU2rEBKT5KSJ2TlHcC5sLy5G2Mvbwy9/8cuXL182vlHjaOrqyrH/6KPvvb69+eyLT8dTf7jdQ6hyITOJANFMUIIFMzCYiWMeu+4yJ/nyy5f9cMoZbbOuuvp4jMjR+YrYqQnK9PG+jHjtZ9SSiLq2Nd0Ow5AkmiE02nSU8zH4fHnZXWw2jpombCu3JTSaScU+/eRFmZSzeWAqRJvD4TpnGaeRiZu2blfeOVXVlHKKSbMSuZvb23EYD8e9iARfxZhuT8PYA0BV+cttW4VVSv0UB4VWdbPabuuuPp36m0Pskw13w6bdNl2VbPIWiO3jTz5++fKLj3/y3n/7X/9X33n2Qb/tn1/fvLi+IYL3gCggrvJMLJpVhJ2xAzPUME3xct02XX17cxdqzqqn/kDIjfcVqTChCr5rpjj+4z/88RefvP7j//1Pko+haVRNC917NnKqZ+FznF2UGcEu+Prsg5zdl7dsO81tSx+azXMqbU7gzQ7IMufP/37DOjZ7ofeWcMmSzUFCcUC+eY24NzdvHNNoFkZfdEPfTjwsNz+D1SiaUGdX7/w2itf2Bg+rHE4JcPCuTJoSaAMGZ0UpXefc7tKWiIB5wZjTBGAj41JLYAvby4DzIBMtTZWMzWT2oc8XSFZKVR5cL0GIwAZeCsYdGaxbNVFiUjE1MCggiOPk1VTMlA0O8HA1+YZcTaiUCRVV7LBrK88WalQNN7WvgDzRlPokE6P1FacEgKvgJccUo3fsfAiuaterm7tDzrmqVuuLC+caYu+5YvKSM4zqpq3qRhPlTDBqu474ENMU01Q7fxma/rhPKVZN11RVVokp5pwECsB7lwVkxszkfHDq4AJXm2735B0KfvXk8Xuy2jzd8Hcf1UhDzrdZ9nUbBEMSxIyXx8Or6/3rm7vbw7Rqm832Yre7XIXtp8+HT7988ad/9m//9M/+8pfP+ymDOLi6YVeT5hhpGilFSjmKpinXkul4F29ujo7rZ4+23bZbdcGFEXZ6fX095ZNaWK3Wj652P//ZFxQsBLp6erHa1JeXVz7w7eEmS/KVnxECEBmYyDlikIlMw2ia+1Pfn7JkqFZQ5HQrQ8QIGGrX5uhFCY6qtdY77XbStGi73Xq1gTO1mLJ5FWN1QesWDuys1sRxyIF98N6BDvv94W64eX5CRKHJtKtgwbLmuuWmc20b6oZjkqqmjrEm38cYKp+ziKShnzRZoMr72siEnGSQkmZlc3XFjnkcpzFmUQOhrSqJShnE5sRVVGU3auLCEZZkmkHs4RQsMAXDeYSOrVYzyylLFoav2VmSlEVy1AwosplShrKJmhgXvLYoCsNijq5yFIiZs1qOAoKvKolyGg/bzW6z206n6fpmb9kvs9BDvSqIazPTuU0WMZEHWRKMWQdLJCkruxCMp36gFOJR4jEhwiAO3goF0WDqjGSOgKEKmUMsWgzibEW51KEhkSNCIu05eavqVYW+zz15shLYW+nDA7O5la5ZVjEQNErjq+16FVacMfgWZmkch7vXx/ceufV2p5HyrfbjkJG6eh1qH8ynlPt4FNLC3yyG0jkGTJDrrtlerg1CHi6wC36z29bcnU5HzaN3BD9RI/v06vXt67tX0ySyeefSXdX1qpURJpTG6Xg85ZjmR82BmUBSKgnFctXy5mIdWg9v3/3ed47p9mQ3ycYpUSLxbWVJ+yGFKtTNuq5qyULk2mab8na1Co7g/Uic7vZ3vqsQbH2B/qUROVXy5gAn5x64ADE752JcvvCy3i1J2rIUlOhYZ2ARc4FsIa+ULHJBI3RZ1MjUpETqpepCshiRJFN4oSBMkpFkmFLOKg7uy+Orz1+87oUaC2rO4PvheBzBhCz87Nk7MH736bO6qoeh1yRxmuqKwVlsMtQUyLcVx5SSCtxeJe73Lw/7SO7qnfXji8rX7Ng5sGMigveurRtPlJOllNftatusXx+vD6d+yrQ/Gni628vhlEJV+9CqerNKTU3d3e3xdBiTEFeckk0jDJCEfohZpCG6Pb5yROJTLymmKpjXrNnG1eVKbW8DnDjnvWe/cmtLlCVTZoiHpLm8TAwqSqW9kgEmBTfUWbqX7hM7tvxYkth27xr8qiD6HDueay3uc0UP0IAH9KLluFgWY7p3DrBk1b4m2zRnpwwo7DCmkjOHqphZCYgeXhgKCFfaP509hPONzkgZEcjNFX5KiwzOvRM225PlkpcMPlEJ3+ZwFswGneGoGSmyh+U9dH9RICyt2ZXLgBvdg4e2yGfNny0ZyjcHZB7pEmPTgg0u021m2p5pdzRT68rb5bJMbWk2/WCM+W1Ea+n/9ZWv49ttX31y/tbxr18LwKKl9JQebL+a2vN3iSj9PXLB3oKivulre+t1WtLd5498Eyb4K1Cnv/HCFpT5bz7Iwy/04R190/5vcMfOhu/Mw5o7ad2zDAxWV7VzTlWTas7CTN77nKTc+yxpLyUfzs45dk5Fcs4Q4MzvUTOYlAfPLRaH5rlKM98I5+mqC/3Azej2vHoyEzn23hGV3iOlnJtAxsRWLAXTHM1ivk1jcBECJTYCTDMRBEwgBwPIsfPkvGdiiJmAmAoIVUhjoijVdqaz5VvKz1E6ZxVWySzWDpCzwjCDmfMeYgYj55xjIkeUlUKRxCIiY3MgeIZCSQo9jUxLATmzI+84EEHhRAnmSkPMLEKKBDU503pLQ0CQmpFnm6+QmJk8DGRqhZRbbKjO7gpmgUIuucP50cJCI6PC1J27GcJV3gX2pFOKanN+j1RyyqKxqUrFQNEmc8E7730oPXqV2tCE4Ou2VlKOkRBzljypYCKNrIzMwTWWqXhFOSQvLrjonO9868EQrV1g5xtfmWh/7M0swD198nQ6DQ7o6oaZNcY4CjGvNmsQvbz+UiBN09Tsgve7Zuds+nx4+fOf/ezP/s2f/+6PfneK6fLx4932InT+2ZOt2NSPu8P+qDlVoWvqNrlRMxBBGewZxmRg50SBhLqpRSweeiZfuVzXlfd+mHokWGsum1hEMGLOKQGJWS/WSCmrZmZtm9Y7dkzHQaAxx37sKY2prrp1u1u1u3V7dbF9Fng1nOTu9jiO8r/9L/9jWzUzGF00KJngICJiJcx33px5URdpBgeIiZjt8dNHYx/HU/LBd5ebrg6Ox9d6HCVGxJRMlX3oDDTEfphSNWYKlcKpp+vXU9vUr4/7w2kIjjaP389p3G42u/Xqpz/56eGPThe7y67rrvshBD8JgNm7aJtGRDWKqsLBORTpOhN48k1Vv7i+2T3aZaVxTME7YagnroKvq1XX/vznH//we3/w4bMPsAeutAr+eNc7X2Sw3MzILBKz52353WbdT1rk3csjvjzny8+H6NV9btD0zQO+bZPPTo8tIuV6v+sblzH/XiZ48VpKWGdkc4LUaPbZyr52tod0b5jZMKv/ucUjml3bex+0TF2aa/yK8XqrmPF8bQ8ylrx4VjPKxHAuePJz44LzcmEgo7lKYAb3SnMGfWD0i5j7ovVQzlaSl3Omcu7D8f9x92Y9lmRHmpiZncWXu8SaW2WtLLLIZpOcXjDqgR4E6UXAYARBwggDaJ7nb+hB7/oF+gN606MgQGiNMJqeUXdPs0Syq8hukl1rrpERcVd3P4uZ6eG434jMWrrImYakdtQSkXmvu1+/7nbMPvvs+0o4LcDNmNIdqJ5AACWSjyIYarUMAyoBGUIDjOpnjiOnyJIBFNCBIUPqOEfOWi4TGGCQPsswJAdgGqrn9XLemJhi14Ww51Djcg7W5Jh2uzAMUZeGbG1sJgJDNnYxxWzIGcgq4q1dX18l5rad5Rhg1lpAY9A7G3MixLryra+ismi2KJ5szn3fbVOSoalsOwv70OdUqzjfdDF0sc8iaKluqqqu1isZ0mAE2tZXHjLKkLidH33n/OEHv/rVrJ0bZ86OzLdP712sfiYYgXLd1NucEykb82K9/ejR0+2mX+/geHm8WJzPmrMaTj/41Qe/+OXTn/zkl88uO+vmYM2uT2kdmpmdLRaWgBlF0VeVAtbtcugHlRijAgyuSYp9N2x531kfkIbEyXhf2fbOndc//vRj44ghZdmfqzs5XTjLwBtJA3kXooI4QkBKCtqHqCz9Fq/XCWXo9hAjIFruooQkOUMCUPDqnfqw2ZqmBeLY9UlBaqhm0DRt2ywZwsDMnAAhpbjrNrsdAPOyheW8oWMzaxpOudvGod+HuDcVsBsFaPaaZh68wfnx3NdoLVlrGdR4P6+qeuY3n75Q5ZRj6OJuOyCb2hgHXlU5ybDfd0lBtJnNfG2JUFU4KQAYi845DQFY1GlVuZOTU5t2V3EjCjknjhGVwDu0opRHTQMPtva+9U8eP+1TZIDaeed8HIYhRUfWNk5ZwhAkCxGZ0qQqLHRWZWFlxWjBeeNBQbOSQXRYV01OeR/27tgfLY/WYc0hQq4Bi5OzRSZQaeu2C30KiSpDzhqDqBoSG5uNKKpwEF+1hiBwX5kaGZUFMsTMioWMA2ONSWZqjnLpPpb4y8hjwaeESkSGlCRrFkaGHfRJ9OT0lMBChqyKkjUJluTSGrIIXtUJECgmQWAGNFTVTTO3CWauNYi8ScM2c9d3QxRVW581hjsOsdvuTGXdzLmZM1jHy02p4tEgAhkDSun05OQ77757fHL08w9//tlHFwa8CMza4+P5Mc1n3i1OTmfNAvrmKZIModvkXR+hPprP26PF8XG3GfptWl/lHAMkABLADHaKXxkgQ65gdmRfe/v+/KRNkt/41uufX/CLp8+23VDlwVZu0XoASDmjdd7VTT2PIROa2fxkt7aNnxkK3liVXdzvgaKpoVlSfylsFQOLFAVY4IlLQohIhapRFgRRMIf1YOTy6KHkR9Fi2XNTJpCQoiqSsuCYLRIZwyiSGVU1gybNrMyKloxWBmzxGlhvuhgZwFxerx49fkpmbq1HoqqqqhjCkFgg9CsL9+6dnZ2+e9x1vSbtczdvqtn8aBjCar0WNKzm9PT86OjOZrVfb1bPrrqH985Wm83ZkNaJ5wBLaA0GRGXOKYSz85PBwTDoetX13QCNmS9aX7XD9Xbf6W4LKfPTp92L6zg/cufn54hW1eYsEfDp89VuA8ZgM6slEgenQrGPMIBxfjavU87gyFTYhRCGwZDJfQKh4+VJ2PUpC4KpXe2pnR8v85q7/b4UFIzj6qwCKpIxGSz6+rfaSxPYVMqNQ+Yw4i4vEbZLZvclpTSNOYiUeVJAwYlsN67Pt9Gb2wN+4951YhmUo9x0lvTwnul1dGj+ldkbQZw8mMcCCQ4nOZ19GZ/DIvgyzgDBmH5MuCkCHgzOcUyBsGBC095eUfM8bIcrgkSggMWNsRxpzM/GTzdx2W5f0/KcTLsec7Tp/G9wRUQaW3jlV5g45VLMvws3C8ulVh1NJEf2vBmvyZhzjSz7UUtaXvow04Wbvufpypf9vjz++A23A87w6lG+Yvjgt9t+SwDrFezjG+IpvzXs8k22A1p0MPI7QGm3q4i/dSdlD2V1LOd8mJQ0xui03T4o3Pq2Xpmp/Ft5UgeyFR5m6G7t8GveXvhKh+2rcMPD3sqvMUac9LOMMeUTHU77lQPdPsSXYm23KVevnCoCMHMuJd8ULuFQtU2fOoQBbgoVENaQo3EEADnnoowkE9sq5mQJq6oylU8hZs4AADzRJAjQOQAoYgjADAJiC21JDkGBnHXOkVEBLsECLVVkkTTGLMBJ8jhy6NApsapmBQVnSBBAVEiJbnvJAyKkGEWmuWxCaw0aUlBmBhEVhJxFMhWZ+ANcL0gwDjYC3Iq9FsEVs66yTiAhkJ1uYFblkbAVQ/bOE2JKoesjWmsNsrKAAELReU0oxKAZQEtZq8ZYU/kw5MQ5DQkigCO0VqngSoCmuGyVWUxBgDEhYS3TPca7yUAGeORGCBTldQIy43IyWsygFAnCMi/PLCwCCWBiwaFBBlUDzjvBnJJUFZydtVVtAZEzA3LO6XobT16bZY6Va46Xy8p7Vc2Jd9s9c993XYjZGqjr+vz8DEl2ux2BOVoczetWWFNMJ8s7KNjt4nw2/853v4NZMGar4MgMu+2jjz7+1S/+uqna977z7sPz88pZVqjrum3nFbmMSYWt88eLJYqmGHb7zSePHj168ug73/u2cbaqKx14tdov+3C1WT3/9Ekehj/8vd/LRnrdPd98vKMXs9C6yh6f0pOLOMR1VdtZNd9cbzjSzLWJVZFyAg4ZREFpeXYcr4b7ywfzN9r/+6d/vh5yO4NHn332xjuv/+iH371e7Tarbt8F69zQDUMfyBgWMUaP5vP90D1//iSn/XIxv3f33tHpySksrAFEXa22zs5FHFWzZfOgMotuBe//xZ//xZ/95MVfbwABauhhGGHfsTMj44JmEMgAQcCifTI9X1i6qjD06xxi1fq5q15c7dabNWRoj47euP8GGtzvVk+fb6wjQgHjnPMhGtiJIXe0PP/82WdBct00c79obH19sdtvNlewTrFD1D/98/fffueto5PF8uxk98GHP/j+e599/PTyqqcM+92ARKBIYniQIWldITldVDjsL7t+szg7u3P+5hDTZhueX1w2hu+eLfbrHaZskY+P/RCvj16zf/Bfvv3hzz7ddZuqmQFQSmmyzFOwAFykCQARBbUY/aBXZ4mIUk45MxJYa4hIhCVLeXrJmJfk4Ar1XZXQiEAR34XRYhVERjunAlKXyFBWJgQ0QAIyPuBFjHN6GU797dK7G9tuPB3yNjJOh6AMULr2osZaY4wxBIoCzMxoAAxYQhFbeK/M2ZKdkhoz5koquagsjEnlGB3pEPgnSnFWdMaETe8XDhoAcW0zn8/mVR26XQIEQ0AWchYDlsgogzJk1RiTtXXxnigq7tYAKgnjNDUEhe5O40gRKWsULi4fIqBAZIwBg0Dj1UcEA0TCqqxptJF2YJ0zxgCCGFarz/dXxpNpqRLn0Z/Nzwnq9XpzVNcPHt7//OnntsLr7VWg7rXXHrTn7mL3LNNgFhgo7i9290+Pz05P27qCxLHvh32VhxnpWQV343D14vmVpODvthU47lSjHi2WXeh+9rMfX62enZ7fNbbLwwUk2fR7VA37DUpatueWOPYvVICi7HYyn9/90XuvPzg5+uTTp0+fXLz/+Pl8cbQ8PlY/lxYj0MDax9jvOxvMHX/MllNKeUgdmaN7bzqD1lomUzlfqb1/dPrw7MjC9lerzyRqPXNq7Tb2garHlxebaH75+dMhOzOf/8O3/2B9cXVv+YO89f/zv/qT/+5//FcnM0CgGE3YdEkIgTRH5xtjTMrRgT2/f2+7mT1+9vTFZQAF9JWbb0mhSx+5erlYHO134bOPL0Hh5Ny7ut+q/3V6st2aFy/Wj5+v8h6A4D/7J2/eedCenr8WebXZrRbH9z57/Ph63R8ftX5Zn92xzGR9Qmt3K2gigGq/S9llAIEeIIKnuqG5y/707v3r7fW+W5Ozory/xr3K8nx39qC1HgxIlLha7RFxuVzYB0O/59q2M79EVaDLfr8SY2bHJjOaSmtfzebL45OzqqlizlnFeiIbt7urv/r8s8TgvAWrw/PNfGZd5VQkpWTAEHjpdHW9ZhZjKF1kagkddNvdor2XOM3rhWG77XYctV26WeVDly7XF08D+ExUOX/m4iYBqj+exz45ksLbII/tbOa9I4PW28snF64yjffIGlM3cFSFOGSmjAqaEVk15SxQUiRSIjUEBg1iU0uSmFPJIlTFgMWMhoyzdrVdd2F/9/Tum+++8ezT5+E6GLKQhANXrh22u6ryWSTvAzYEZIaQlsdzt5Rnl8/Pz+cnd+5srtPTZ1eQ4P0//dPzo5OqMW7lEtio0TlLhiRLihlUgcgSqUipTQkQUcFO0ZIFVHJKCkDRLu8dJ867vJvVTYAhSSRsrfO5G1CpamoVVoDIkWPyrqrmM7AwQF/fb2nRfvrs6fDptfdqXcoZlGHpcLu6JJlVdt6cNnfcyb7bJeBhN1Tnjl3qdr07q47cEQ64e7HtU/fwzTfP3jodfPfhB796frWCASwCiaC6y9XF893nWMGb79x3tv/kyeOzb59fbi9DF/xp1Ry59Xb97OKChFq7PLp78vY7D79N7xii0EcqVpQyzGf18dGxq2pEu9v3u6EfOEQNP//s577S07NFuzSM2oew3V7HJN775WJOBl+srrbr3Wqz1R2Y+rSpbNto9oOBra9h0z/5zts/uH9+/m+7n+8gpyxAVrMTzq4yhhLnkFMYh0zHDsxUByAi0c2U2mEAobyUcOxkIugAgETGQhH7FAVUwawIxliNqKppD+C4MNok5S4Ow3Z4dAHffnO56lIAOFveee4uP/zgQzvzpw9Pfv9Hv3N1dX19dXV2dj6fLYZ+6Pr9k4+vLZIIr66vnzxd/e7v/26zOPEJhn2MQWyfU5/iKndXWRg/+uQysvz1459dd/2/+G//qwxrD8gRU98P282/++hTdHVkN/RoqL03O8vqm9nx0dJaAz95/+dNM99cmyefg79I6+snbVvPZsfOLvtBj8/veN+tXgzPPl0PHUAwtZm11dJwpau8G5LxKDD0IaQAoOBrO5vNkPDR00e/94M/eP7sxcXjF9fba7DX/S5UrhIHLAoVOuMls0RWEAIyQsVmQSQzg6EbJSSRSYtqgjSmWTgAoIPhksLED3pZF0tHsRQQyOPAjUVQKqgKiB6cMVmAgfUGHypWMMpZQBQMVJVHgJQSAJnJS11EyvgHOVOYlgVvskhgQURP/lnpAAAgAElEQVSSJhUli2U8BcfmoS1px2hLQ19GucARDyu+VghIhsiMKjSqIKJZ2ViLZEaO5pRgCJcGf8GJ1ChkKM5YRZlrumQEOPp8lQTodnmuhrD4iwkDSuHdK5SJTxBAUwZvx7xOEQFJytkREqEaQh3FvQAL7oRUMlImFJgywIJiURHvGrn4OmJYLwm8gAK4yukkz1NqblJUQ6AAIgWfuEE8Xr6oX0q2+noy0+GqvoKrHBCJr3nvYfsP4EL4/8HtNvoDX4sffdX2Ne/90r19Fdz42223eVJ/K6ntt9jzK3/4VZ/oG163A3T4xV3hrYGYr3o3wDjnd9ikOEYcvsRb8K8wZ8OqyiLjgIvBMsiN1jrnEiuAqOQb4B9L916lmI+qiGRAVJTSCgKYzKpwsn64NVtSCvORg6oqoIRGSQHMQZoeFTNPEQcBUFmAcJSEn8afEdWO5g+3QHXAspof+g9leOeGuXtzbUqJqzc4YPkjEUUsiwWCqigSmUI60yLhCACCaEq7REFRQCXz+HknXoQWAGLyE9RDMJ7oa3j4B4CZi43FdJPipA5YfGZujfFMvTY93B5T7VwYO0ikCEhqkIwzZMghVxUZW8brFZELilJ78FVFGQ2ZGOLQh5xSuStCH1MUJDLoVMzQJySVqKzcm6AJlOX6ah07aZv2aHHkjyqD1lmsXOMQSXHY7Bbt4sG9B96Y2lcqbKmdNXXTtk3drF5sZu1sVjcGKXRDTjHldLVer9e7mHMXkgO1vqqqanlkj5rTBNrO2rqqrTUvri7YZDUc475momzING+/8/Di4urxk89qE2dNe73vJYkKGGMtmaSYUwbR/X7tjhbBRNhLyvnkyPnWVG1lHVlD9+7ePTnhzbYfhmFnN323ZuGYYVnBvG1iCKBqqCrDCykl1pQkkrHK8OC117ab4cHZWw8fvPX8yfpf/x9/+utffBJ2aXav2e96FFOINoW4AwVcVQDEUVq+/AUZFTlYGaCCqtSu7hhUMEcRBCIrlPv9sLpekaHM2RCAauYkmq2FnEQyEEEGmS2alCWF3KUeHGjOKRbswfVD/PWnH1ON3zv+7snZ4vs//O6nHz0iAzknEJrNl0Mfx8EFyaACSsDCUUFAKQ996nbDEON+F+OgxkHt6tm8DsOw22x0nryn+/fPvv/97/3q58+IGERT5qpyipBSYOHxOf5CADsEVBxJ3S/1GafH4KZXAbeQ6gm9Ui3apocwMz3041t0ehAnpHsiPB1aqF846CQOWr4bHQPHS43Y26+/YVDpCIyNbb1yRirTi7CIOMBhWhu0TBZPuiY6nrfo4XfVA4cdQmKsa3QEGowxV1eb+dGcOfuKfAVQ4Ds1SEZLjCdAIdLJCgRLU3D8FHQYdijnB7d/wDE0qY755ui/jUUuR2lywBghLwCrcBN6S2KsVWurWe29gwQYUQHRQr1sAGG9Xy9O5oF7SmQQlYQMWmsFrSXT+Ors9aUHFzrZXa6HbZe7EIfu9aPu6kX32lkWRiKbecjMjsg4Q2xDCuvNar3dIhIS5zzE3IsmgcQxImVnTN/tl01TJKxb11ryqDHHnGMvOYgyEikROEPOorVqKAqvN5vLqxcqCeD1e+dnD1+/P0iPXuvWc44v1pf9Zs8hvf3aG8tZzRqG1IlBrJtAKQvsYtxxulwNkZqqqjZdH/uYjul73/tDoeqXv/r8Fz9/fFIDoWdGFUUET1YUMqgm6bvAqVfNzpmY2JmKjDME1uK5nXknoL1r2DXiE1pPw166LntQAKlbS+BT3GO0YDJYeP60jzEALs/uHNdnC6bK25mjXpXbev782SdAjYAVAEUuOji2QhRmyWIEAFMQTQFTurpYC+b62EOrQXsD1La0WFrQOHQhyp4xA0hm4TzsdrHbQq/XnQmgfHzK1qOvfDSCVsEAWlDkbbfZDpSyCIpxRJSG0EsiBGAhzZITzOdzAI4hceKcMA+DGRxEVAGRkbWsDM55AzZzJiAjpgIPRofN4IwjwcY1lULMaUhJWMCBb+p5O+uoY8nkyv1IYCFwgqxe1VhABc6ZFFizKSYqBlFAFSySFH68IKrS+OCOUU4EABWLdp0qKTHnEAIYyCyaQtJ4vV1BLywBHDhrjHVg1JMdBiBSSwbAjZWHgY4H3Evd4r7fsXiOzhsXa0GVqqK2ai/y2vomDwNzaSXzqEusRU6UAEq+NiYxZegMR/QfEBA8bHebzKk+amfLWchhm/ZgSSSTN5I5pEGErbe2Mq6yGfNutwFSsHp2903wOYYkgplVAZjBIhjrCEwKGmLISVNOAmobIgv1qTeWjAXX16fNcUuz4ajfrrf9vv/0o8+jC4mHmTrjEZhUTE5q2DIESrBbbUH7Ica+jzEBMypr1BhyCgIogtJTpMCRs+QQ+90eVYmCtXCSlglD08z3u9yH2KeYJGYJ5MF5STwkiehIAbz15CBmZkkxJZVMCK1zoU0OoN/tOKT5EpraKmcB2O43LtevvXH2wafP7LziKJjZEHJOSllFCACUzGQepAcKyU1cPix80w/T2GdRDp+SbEBBJSIZ7zwEBCnUfRJQO/NimRlTTKC5qeGsAVFqmgWA2w39EGPbzqgxidP11VW364Rh6AcLNmcGAU+2OCp5Vy2Pmi6y9MPQhf16iH3OPQyBN+t+t05CaFovKM4mBvtiv73njYBBJFRkzqenxxF83KRN18VhQKozHtUL633VDwICsVcSPFlgO6tm88a6Stls9vvdrtOUYpdCxxrARJAeMjDELCKCIgwYBa0gkPNAiM45BPTO3zt9sNv1zGIra9SrQh+7oAOnLCyqokRAoqRIt6yQEADGRuQBeig9rC/+Oi2uX1nPvgRe3OIGiSqhAIKqEJJOblkjg+cmOxgN3A/dtsPBCl8EaQSNbhU/L53OTQJTkJ8x87mhDx1eKzImVy9V9OOvUzFcyFww1ibluJMb4SFVmw544HnBrUyh9Appys5K1YIIqjgNUeGtJHD6b4nxNykejonSTZI3ZdWF3YKj8XIxvEfW29/u+JYxGcKxxBQ4IHs3V09vPaGHdyqoOVyf8erBzYf9jTGU33D7LVAa+PsEYB3Qu9uEpi++4Dfd1Rd5Sa9sh8MV5tc3x33+39q+eFm++Bl/IzDuFbgQ4KUb/tU9HaokvZktwZtYggCQM49W6lOlh0UWUFQyKzHAKJlc8BElQkRrrDNWQQUzF9pQ6fWMo4gCjIJF00e0mJ+X6FcA7OKkMo4EvlJnjo2GctYsMrFZx1cIgN7mw5W1WBBGCT89zN+gFF36IgwDRTKLxqunI+BTxhSnDw0Tmq4TZn1zf6oWWA5QhUVFNTMikCFCUlSaxoVg/InIqGYQVmWGw8wzTosSKhCSQUDSyV1EDn9/+NQIN29HHEelEcfV6gBQjfOF4x1xANhBxmkiHd3qUQnBqDGI1pARY8l6AgQGMVTyVCVL7cyBgiEigBjjMAwpDMY4Y0xKIaSCrAWMwTlX1dYarwqoVGxZUCCHAK5ufH08W9bkHGJrvUECkW1ctc3sjdff9M7NZzNjHCIRmBTz0K9ATFu1s3Ye+r7rgkqyzsznC1aeLWdt06x2264LR/XMKG36bdf3olJVtfX2wf0HScNmWOecOLH3jmMi8u99592Klh9++EFtQSU5BzknZlRB1gyo6FF5OL/3Gvt8tbru43D/zTvo1NWeWYYhWG9FEYEa31THLs3mwinnuFi487Pz9fVz4eSctc4CSt/1kgNiqn3tXXV+cl5T8savr7Y//Yu//Nf/2/ug0PhaQSv06SCHOfGuSvtmmtUvHsajaYyQHHJUAfXGsnOqknMmwsZVbFwSjUMABFVOICypuAoQQY6cgxBC5FQvmxz62EWRjBVj5JxjcXoIGT599EnV0vn90/N7Zz/80Xub1dXd+8c5yvVqh8QsmQpVWgAAUgDjFAE4Axu1UWLgnJhzVlYGaKq68ma9vry6uuiO3wrz3b0Hp//gR7/7x//L/7XutiqYYiZsRuFZGfGp0aZnhGkAinju9CjQ1IWGW5G2PLd4S3zw5QbJFIdgQqH05bA5tcwmXxpFPQiY461nuDDAv7j64Nh6K+cwAj+3DoA36d/YN8Nbed6Yw93sdrLieampOF2QMnMkYzBQOESPAoCRgRzV1U6BAcBXvg/9ZrNJSZ0j5yHHwxKBI51rCosqt1PXQqCCL37gWyvRK3mbSLG2AgYd1eRLLEJCQwah5P1jrCzx0xmTg5BN5R6QJEOXLHn0Nku+7l689d4b3T5KTFk5QVD0lXNGoTGz42YRt2EYcrfptqv9fhNyDzHBd+7uLi/W+9f7GIMhVYpD3Klz6tQShT53uetTd3S6rOctOorCjJhFyixJ2zQxR8QWiSxaTiycWmOappnPtapWALJar1nJOuucz8Lb9XazWq2ur/r93hBs1itncOj3roZ2YZ58fBlTv9+sEcCSPTn7nZpoiNt9t/GeK28T2D6ZbZTLbffxp8/IL1S8AxCQNx6+/sb9Nz/68NP/89/8xYcffB57QJtUSTJBmQNCowTCEPchxl5FtmUNzCn1AJa8w3rWVo0atItF2zQ+xewbClHUWDA2CCUhtD6xJs5lxf3ko4unz4GMm8+Xs4WrG7dsZt1ulWPq+9zvYTZ3VTOLXZerjAs3EMecZFBSEgJjjRGLGVh4Xld9ygpZmDWxMebe+fG9e0ukvNtthRIZBYSckybBDIZBOTMHAGE1xnpnKmGxVcaBGSWkuO9DEgEEUxmrVjUOQzdEAADSVIhCwhBCiENGMN47jZKkKCAaBYEKFFSzEhFETbskKBIEIhBAtxm8Z0OGwFihGJIEKSO27Xx+fna6cW6z3YBVa8haAwAxRhWx2Vi0IMCJc5m8KypKiMwMh8ahTPLIo2nYIUs8uHOOvS4yZCyhJYfsvEGDvvKZM3kDiQVGWSngxJizGsBJvYoVDGblo9Y/fOv86bNHm31vQVnYWIxxmM2bimefwBNjKStCBh17kOXZHkfWbmElo3WgaiGVICCIQt36bugBtJ75dlFThuWy3VPIIVhnjMXUD2iAHJE3YEGYQcR455cWcu6H/X6/iRraJZnKA+Q+ilFGRkmkKbMiKljnqrl1hs7uLI2hwftTc543GlZd2IXUpX3Xd9iry9ZDVTtDlpNI4DyoKkE2rLx5sU8Rs4Pdpo8pqCAWz1NWUaiM9ZUXgl3YxSHFGFNkBPUWGmejaheDoHn87DLknDMzcIZoLPiGFJVVbKlSkwggK4uosuQQUxyM0eV8kQP0664foG195WpnhEMIvZydnt/9/Xf/5oP/tV8nBxaRQEVyNAYQiRRREQ+iPiMVWBGEtAzY36qxxxyylPFSct0DfKLIoEX8UIgMoRFFUlI0qmzBM7CwGlI0aI0qSTObtfU8srxYr7bdHp1l0H7XXa3WCmCQeL3rB8YynCYgrDnnxOSqRQgSQt5cbleX22GfNFFMsuvyfg9glTRkRbRwcXHx4Ye/OP1H3zOoPHZ6TWbNoDHKfh+7vS5mw3xoqtZaYyzx6UmTUoWKIqZq5o1tyRjWpLyOwyYNkAPkBMogGSSy8JBjhsJ+Dgk8YAV1662zCJCzhBxsY2eL+dNHTyRLjpmERCWFBMxF5wrLSomjt1JZpVWhmJAq3gaLvul2gKvGhfX2uw+Tb0VVF1BGOfWDRvGoGy54GE8b6ealFz5WW9Ouy9tuVnDVv/VkFW4KJIDCZsBDV08kw6F3rhMwNKowKECZbcHJ6X1s1t28WEe9MBgj4UulcUn7xs6c6E17UUFG2vsIDty85RbbAxFUFElg0pcv3VflVwkrCgwqMFqS0ZTQfQHTQCDECXW6dTaH/Rx6qAqvSqPehPgbNOAbEFBu9vzNXvgfePv7A2CV7QAnHRClV/72S9lMXxzWKz/8Riykw1Tdvz9h6hUE7d9zb1+z/y/99cD/emVK8eu3W7jyF4LOV8UgHVGsSZgFEQkQiOQA3lBJpxCLrx5Ol4UQpTTiDpyy4thkSJEIrBSlnnEYFEFptBucEBYl1GnAuVwAMuZ2c2EC6aefixaVjAM+xdVUitWPKDpEQB1HZZDKiI3AOE8NwGNALMKDABMkREgyZl04kTlIVUFuaBgjgiAACkWzGEbegRAjCytOdE0BEUHBolel09dKWgY+i0KYZBDWg4ttMQNDIAVEsIREOokjlqg6Am4yscQBtHj04kgJKzTkyQXkBsM6xG4coa2vvJuLqH4unFqALMKghODRFk1nY0zrq2EYSFWtAgCzIhYRh6r27dAP200XejAGUsq+dnVVK6A3vvKVQXvn3TuaddHO7x6fnbbHJqmKJBcFUbOsVtdt1ZzfubOcz5211loA6Ie+67qry+vvv/tDi96iY0xEhiWrQlM3vvboUFB3wxDCkESyyGbYsOp8uTy7cydyPJ75Lu1kLfuwM2gsmoQahn6xrP/wH3730aOPOCoSCAgYVgmKqCSACM64uT8+b5Xyi9XzrDA/nsUcmDkzb3ehH1Y5AQssZ/O69ovFnEhEgq9QQWLsFcQ666wRle1uF/vQtt4ZuXN215r64WuvPf989dMfv//Tv/g1XEF14iDr0IfFfMHaH26+MlQ/sc3LTzI6lBTyoCCggB4Y6EpELCIiZGzlXGYZ9jvh7Jxr6koBcjYxhpxZEAbOEoUMJcnnx8sBQhDgJEF7ylr0WzEAOrAVJIzPr56Yht9++1uLZfWtdx/Wvv3FX/2qu9oDqKopIBMIZgVA61yR1TDIhsDUvm6rut933mhb14Cy2a76Yasa+n5993TxzlsP33jn9MmPVxWAt4ZjHA2X0Rbk5ga8nvIEIjOSFBGISFS+FMA6rCnw0soyDQDqlCq+0i8b91B8fqZ+pRaU/KUXjtDdFMEOUnrFIRBu4crTUQ8J1vjvlMQd+GGTq9dLWdAhIN3aBKZ2QjkCIYwDCeMUIZbEVax1rAQEOSRIUNXOWhPikFK5IKiqaEekcGShjJ8Wbkrq8QO/CvSVY0/J8JdkX6oiSoBgQBWgTB6BAoKUNaUYVUy9DUCDZEyW1G9DoECWCDT2CgxYkZICa/JD3++SGUSg591C68pVVmwt1Qznv/7lx5go9DF0kiMQAzD0Hff71Pep7zvr0FcmyqAcqrZpbMU2N0N1du/05PR4tmirtjbeKQGrRE6Lqm7bJqVorQXAsgamEGLaECVEc+fOeVUvXly+bwyAskrOMcRuH7pdCl3odwDynHvUMDTOmNRsYbW6VEhNXT98+Pq9e69ZSgowyD5obx2CNQI+Sh1M2MX85NmebFoul0fNkZ3P33vwvadXL/7qF4//9MefDQPsd2CtAjKCIhqyBo0lR6AqSXJIYl3cR+akwH3XB0Nt7WcLJ0nP7p5Yr0lyzAms+BZcXZGvc4ZtnyrrWUaMBhB2G9ht4eI4LI/6dhZ+50dv3Tu7Kxmev3j6/PNLVNvUc7KVscE3ppk1zvX7fh/3ggVZIzSOUBGA3dx2O2HhzAIV3H1w/MZb905P7ba7Eg7GKFFZb0SzWgNNTSi+Mo1x5HxKnGIWQXS1swOnmPbbFBOIgJ3BrKoqY1gRSmaYQVS9c8vGrVfblNgAzOqZMQ3kpCmWJ1hELFSSsmYhJR5kuB5IiQOnGEFQFMQlQ2IdOEMkziEAQcrZGGoXLat0sUsasZgMTPUklZUmQ06iDIhgilCVYhYRUSJAnWwgJg1fhCnjwEmQhhAMoEEcpfJKR1HJGOstAVWzJoZdjAlzFkFSQm8yZBAQkiL8CYYAFC00i9Zvqi4qSObUg0e1WC8qUQMeMkcCM3YRyghZSbZESpA7kFBBDSoUxYLiPAPIQEpWhYApD2lfL5u75uzzz55wSkxiEMGCcQhesgRJICb7uTs+P1meL54+exw0pszQgnXVfLlkkc31pt8FSuqgQTCkKKpJuEJjHXlPxiDW5mjWPHr67PGvL/aXUUHI12hIE5BQeQtHjoPmVMKVVZEkakmb86rfxahgEMEaRDJWnMuVq5r5XESGENDDrF6YY0eAzkrlyJB2KexDuthcaUZRVVIBMA4ElSxmBTAkmZPEnMBUSgs0hJxSCGlW+ZOj+W7DGwIQsGSdrb01wo2jWeVmD8/f/KP/6B/9uz/5ye7F3nAlWQ2CNR5BhVl51DEkBFEFvDEPGdcVPKw+OlbGOA5agIKS3IT6kncqFmuikmoaSyrKATkTAfjKGsog+Wolb7z11my+3O6GZy8u1/s9kgs5bXb7zXbrvW+rmqU3ZvDWGXKglBPnlAnRWN930Pe8WcfVdR96wFwwBKycCsFuD1F0Nodnzy7f/8n7//EffU8QWVUU0bqr51dimz4CAxgDCihCwhDDkOLw8OHd3d684HD1IucAcSe+paqlunLLRbsNA4EBw0UWNikoq7IaZwVUeRStotqgImce9kGyktCsnq8vVmXNLeUSKAIrcFFjxLGvTlBIAMWZc9TABJhUTr7RdiiGbjeKDsNwqCBlXYcJQiorvSIgQYFZxsQGRiF5vdkPFB8HhKlNNSY0esg2vuY08WYnBV0HuKX4CRN8WtZ81ZFxhC/vmUYtHSy+4jfpz6Fxd5NuvITpHC4LHj53GZzRaZiGmOV2oxK/qvgxNwqeEy6Ph8RwjLzlxKiAgFLEjUacaeQv3lxWxOn5uyVlNvUi9VA+HxJAuHXww+f+/9H29w3Aglv4y+1e99fAQF/K2Bq/b7xVgX8DUtJvRFz6mp0cqp2/I1zzdil1+KSvnMNv9Fm+iIUd3vzKfl6+yON/x37/+FzdcLFuf5UKCsUG7KX4gVCElkREhJnJu2JzS2MtU0CykecAWBB3IoNKOBJsddTuKUjZgfc0RazxtFVQRYUVRZGMRQMIIpITqygY1HESjlCpZFeAQAYVSFhKoJoKMz2M5alO2N8UsBFAx+TrlbJx4kLopMGnhetfQqiWYRtlYGQ0iCNIN7LHLAiawhchACksM0bRIpNuAIrxFiFZo6q5THTTFKQnJb+Se5gi5w7lwCUZQUSgMpZz6+seb4Bb98Er2L8WGhmAIKmIYgYxwIoiBtU6AgBWRgWydeo6FBUBa62zznhyzjnn69qQwW7XhQFAoO8G66ia+aIJbdF659/79nvdZte6+vz47Khu45BYUsxkEFFhs1q5E+OtXS4WzjlETCn1w9Dtd6vVqtsPMx9qVwMQZ7lerYc4NG09P5pVrg45LJbHJ85U1knIvm3nlbdNjd5crq4fPfs88JBS9s6hYooZ0YRuH8Pu/v3q+LTd7+L6Ou26CACIQhZQQbNqGt5491v1kev3+y53NAfyJKwhhpSh79PlqoOoVLUWLCg01axtau9bgbDvdofVVQGEOaXQB2gq61x9enyeArRHy93F5b/8459BguWdatiLGl24OeQbcERLP0tHxHYsamScYVMoi+gIVSISGV1frcFAIfJYb7jygOjJgGrjfFvVKSeOoFzODFggZKk8GGc8uuNmVgmFPioLZxUESQACszM4f3BneTLfDZvPH3WLZVO3dH5+Yq27uHy+vrxCCxaI1AoBM5ACYREbYFbQTEZNPataX18GOT63i3nNORFmX5nTk1Y5CPZHp/V/8p/+0Z/9yd/4I+dd3e1jiBmREEAYSAUOK8WUCpKhcbL2JlQdMpdX495tB9gxiMGEwxweFMIC5YxP0GjxgzchSQ/HuNkZ4kt+NVPZCcYQTnTzW0FlPOhou3PDOb3Zx8hmG20NbxLfV9ak8S5TVSr3iMGimI4AeJjSK5kYgkGHhplFc/FHdd4iYWJOmUVUlQBphGamTcahxTLSpyOYOoKI+NIZHbq5cphjHtPHcupSpqmhuENgKbS4nD8oCRU6KRtGUCJrDSFAH6IkQKOm8iRBGLQWqIAcDLplN7BXEIgQM6fa1SZj2uYuhevPIgCAAKlxaC1iD4NmErE5S+y7akmzuVPNGbWumqqyCd2C537pEZEMoTfgTBIJktGUhg42dV2If8JAZMlhzkhomtlstjh+aKuf/OUHdWOsA2fEO2wqJMy7zVUMXeWtMXRyOjs9njsMyrvLJ1cvLh+fnp5Xb927d9ow7AFITVarA+SkMQLv1HRs2FRkAZU90clieXbyOiC8/+MPf/yTv3pyCXdOa7gauAjogwAZBSHUIu8rLJoUkrIwa3TODF1QAcxoLWTOOc+y5BCG1W4XWMABelfNlhg5iDSVqeY17KAIlVSV3Ye82QyPP12BGd57763j+SmIH/rw6MlTqmpUE/qUWYylqiZWU2819ZCzMEHGhMhApJYvVwGYwQMt4eSue/2dO8uTRqFPKTAHTzUZAgDJmJKigLUGxZAxvvZgNOcYYjJqfdW0C9NtUxejAABBMzfzZTuftzEGAA3cxR7AkDdVXTfPLzpQmNWGyAEDs4iCq6yISuC6qhIDavboTKK8jZSNJtAIymo9asSkKoZN6xvX+kpSTintQuxD6rNE8ogZswoyF+4FChRiKTBqHgUMUUgJVKQoZ474+7Tcj7lcYcCXJl7BpUsmYRBIBUG06P9lq1zF3pvKtg62oFnVAVlLQiCYeRQeBQQ0xniXbV5tw6PHTxmgbm3aKKiCpWqGgsxO4Aj4urPqR6OQkbkhoirFsvcQARVQiISAcFRsNAKEQxzEADaYNFzuLu7M7lZH3m1oCKCJswGoAKwyZS5plYd22bbLppq5cNFTDfUMTOOt9+SayjsEz+k6CyMTKhgkUcmaQ1brGSAZa/zMrC6fbTdXXT+ogjUVguccSY2JBoSEmaNiJmQQBjAEaEGTw/ZkcfZ0eFQq4MxiDBF6R0iGgCClLChVVVVN40wtogRCJDH0u82u71IcFIq5hANQYIXMgAIZEI0KKuG4PgKAQbTWVBa8J+eoacG3IBkQcehFnZnZOWH16NEzGJof/oMfXj3f/nT7l9wFQqhcba3lxMiKYrHIJikTFqYcT7l0kZV4qR17WINuoVw3ve8iamgNEloWRkUDBgTCIOrAO0tAoJI1Q0cTwMUAACAASURBVA/f/8Hv0qx6evnkycWLPqS69rsh7Ia8G6DSLJBDSACxcY01yqJpyJzFeVfX3oLNSUU8QGWNWvIAxKLWaVLehR4FKlsJyy8/3igYVgLyYLyiDUkyc87knCO0Mel215PT7X673e4Xy7MwpNDFy+fr0CfV/Xzpzh/49kja2ibXpkyKkZWNAisIoEWHalRBOQIBJkz7lANwZgkKCnng0AXjjCTWDKXEAEMACFaLO2JRMAIcvc6L6G3BM27Wwa/dbuEhN98XjuZXL//FIQPQKT0pOQlMvxZ8DpXQFuFeHUlO4xsLgHTD+sEJItKXbpRvtt2kXBNsNjEKbnKaw1FH3QBCwsIDvFW9Hnpp5S0vl7e3gaGXW2g44XmIICB4Q7fHV18FhR+KiGhuWpnj/2gc0Lm5vAhYHLSoFLMlBuuUC03QIQgUFsiYceGru75VO79S3+MkO3ULqvvG/Ku/M6Tib93+HgJYZcNbZKsDHvQ1L34FvXrlh6/ZymsOVoy//RkDqGqpnIuk+m0d+r+L7Us/8ivw3zfcz1desZcplHqLU/bKC1VUUMpDXXIklZHRUHzWSVhYVUAgGkMoamkagxHmrCIghkETEBlrRy1/YMkljoy0CAQoXodKIDLO8410ppIM4a3gBUgyCmKNXRHWUvtYYxFQRJVTzhmsKgFQEb1TEBBFMliUnBiSjkiCGduHBbEqrLNiXzgi+YiIgHJb9m9E4cmIiuEDMxtAEFhVBQjQlH2Nkpljj0Gh+A4CaCY2oIYICC2RCDEzAQJwMRoCArCIFsEiiEI+hE4CgFFJDBAL2EVuWs0OxTSBABCT3qgIFl/nUv8fbgYpVkG3uhJaiGxASgKk5JAM5jLKRACgIeeQs3WmbdvY9aBiCI2xBgkBU0oEWBk3nzfGBBFVycCKYKHMupH1pjqeH7lEy3p+Ojte1LN92oOtrEPnnSVjjTdkmAUArXFExFlQwBp/vDjOUWLPe9P1Yf/s+YunF4/AyHv3vnt6/w4QrZ48tt4AkvEVWtfnmBG8b954+1tvoG7+7X5/8SQMiTwMYUuE85OTB3fvPHry7NHnn/zjf/yfr653f/Zvfsr0cQyQAgiDGqgsqZfv/OCdy+tn276vZ3B0vMySc85DTOtVl6Ia9GwIM149v7qSfNHA3bunD1478xWGfW+tSVnDMPRWrDHWudkszWb1Yn5GUG0u95tnf/PLn30KW5jPHYkH6Umt8SaHXKQbofAOD/nA6Pxyg2agFv0jKXOwJVuy1vnaAWrKyVjnnEFAawyotnVj0ey73X7dAQM4MIScVTIY1yzbeb/q5ot2ftKGJsY+7HBX1YqAQ8rnd+t6XkUO68sXVUXLJ3VVU92ak7P2zTfvcc6f/HqDTgwBiS3GOwgEGUBVVIddn/qwWNaNdyDw2r17d06PUuysh6YyVPH1s2c5xyHiP/2n/8X/8N//T1UlkqK3ROqZRRUMGZEkt6aFRzCXxhykVHXFouCVTPGQDN1ITZVcA1HLbS8TcRhHhabxuSg1pIABnZx4oOiWl7A0ze8i6Mi6mlLIG/C9hJLivnpz6oVsPsJu00niAY0cN1IAVSPF3BDplkTUwbFZcIIjqZyMgSLHp5ABURShmABpzuIcxSE1y7q3+6HvMg9zP1MdTTm4DJFIufOKh8dNJlmw/dKwHfvPr25YFhODL2mUjmb2pbOPrFiouarAoiJcckEoX0gGVhRCsCRknCTx1gGCd85Uxrc2U6LK2NouztoX22dUG2OBAIwBBHDowsDri9VVWMFQjmuQKoOeOUIGSUhCCDCE/cI0vsLMHHLohXJ2m7ALGup5fX19HWMU5brx+7DvQ5h5l3Le9f3x8ijEWLmWrJFM3leVr4lqRIfkAcw/+2f/ddcP+65PmYchXqQtQnd6UmWGpvZdt9vvnu93T2zeffute//8v/knFRkF2HN/8eLjo9O72VhwnDM/vXy+2V+A94Pi9fVlZe2duyc1VU21OD8+ffv1d/73f/nHP3n/V7/8+HNysNlJ3RIBqhKzSlT+f7h70y1ZjuRM7DPzJSIys7KWWxf3YumFvbJFTpMzQ440ks6RREmjPzoa6Wiko796Br2Ijp5BD6E/I1FHo1koDtlkk92tbjTQQF9c4G615BYR7m5m+uERWXUBNNg9XIZHDuCgKiszwjMi3Nzss88+c1mymWgxMSgJikfRzGTdKmrfa4GCxggk3W6SC1oUSs43RSwoI3atb9EPw/pincq4Tzcl5SGXN956uN9uipWPn14n7b/3B99/5ytvnJydPnrwDrT58JMn+93I3sc2qmrWnbi0vvSLJqYNdtf7fDAuQipW8OCidbFpT/zpo5OzR6fdOmzTVf/J1b4/7AeEjrw5IvahKVIUrMXlUVI6FKeGJJWSxMH75jSuFgtZnxeDGYQDx8bHzmctsWsfhOW4kJKVmS0DGc4BwsNu7Hf7fMgw7yKrqI2Ju5aNYD4gcnFla0GMCwVhFaPsmblYydCotjiLwUGSeITdbvvznz9Ry03btV0cR1XV6quUsUjaaw/ASMHGRMTFAZalVPMgWYkruePOU1M1JgGgRQAIlIiNGUoGJWXyRA7OsUGLFO8bio4XXlHYPAtrNk0CFnLOyEHMVIvJ+YMHqwtfbFuSKHt1wILA6trw8vZ549uvfOnxK9fvP7hlDURwzMxIxVTFKu27dluuCULzbF7VwAwuRlBSbgge6wfLxWk76nDb35w0q7NHJ9mG4ZC9wQqkwAwhYrnumlXHwffjbvPJdQxYnSzjsktW+u2Y5Ha5OoE6owgr+92IUVfdihtnYqmMkAIqXRNO1qvv/+DP84jYoJjzGoakpBpjCJlZUJJYLqbOc1PE1JhCNFjk9uLkwbNXL6All1I4eTc5xiK62ezGcXDOcXDDOOxLzqkA2gRIGnab0Q6Y+/BUF1U4WvCNKkkehgHOI7RtWBicSDZSXa8Wy8ar6GF/c3b6cLxY5SwAXV9tGx/9abd/tXn20dMf2c/+s//wH/3Gb32rgf9//u/vtcTROU2SUinZ2uju9h4SVAXNiSpHAFwFJWgOwHk254RZXHp2KAHWWhLAzkiqe1spOqmAQ2i95aHQ4eLh4kvfPHz9699++vzdH7/79OdPX7jQLklebgYxBZFIPAxIA1RtdAIb0ljyOJhS2y6aznvXS7H+QFIiwJ4bFYxp6FPOpoHg29A0Cx/yDz/ItzeHRcirVdcuz+zmarFe3+41izK3cG6/G7a7m80mcsR2u3Hc3t5sD3sdB7ffEfqcx9wuJLbGnCFeE/JBU68yKIr35h07CJyRKqOojchWyIOZQ2CANevLZ68enD3od/1e9ioKsCfPnjg4BkRkTAn2ukzVfG2ZaGpU8ksMmgElvntlcvs+dfC7O0c80a9miGZ+HUxcPZm7LmdTuo6PjA0CkXMGaIW5v2imNncEeP1E1a6hiprUpDgwRVxT+DUhVzZ5KvUxpanK1aaGpnOoiHvzmNOWr4EJn57jES+aLKeZVf0WnkhmVF3mCfNzNcGuAB27PBuxYRJMmJtDU42FbQ5OZUpeThiWTvk8upPcuh9fTxH6fPvu37RPz/3oItaE7L8dVOpXGP+/BbDwGdzql8QIj3DpZxGcLwDC7N64//rxUF8MRR3fdmyAKCLHHn9/Hejm8WvaPTYWjgDKr3KcT/3wqT9/psgDd6c74sOV13OsIp4cpynnPi0+m5q91yYQZohusn1Qmovup75708lhlfp0B4BPAdsUed19U8akqjfjNfXjk/CTwcwc2MhVTgcZqQBmVtSKQWBSDV0NK1lZiBhgNaNqbT6rm3cPYp+5FxPOw1V4b6qurq21AAMRm6mZQsxgxCw623pjR2wEB9VJA4IBZZC5mpYxMSWIgyMm55yYTjwq0srAmnRRa5R4vGYz0baatBr2kUyM3CmGpWnDgNZ2yXMYPJHLDFVZhoiISrmDAFSVeSo9g6pBFstFiMTOuICdElkp0+rph/7x5SmKllKIeC7dsnrgGOPp6WnXpZJLLqN3zjsmUOAQQ2zbdkzJTB3zsu3aGP2C2MG33gcXQ3jj8jLGWO8GM7va4UgkeHeyWJ2uTmNsRLDd9odhMMfdonWNZ/b70v/gxz/q01ikENPhsN/ebMm787Ozx2+9efnw8t/5zd907/r33+9vt9dFkg98SGl1fvblL7319OPnTeNC5K9+43Gz8M+fXz19enV9QMO4OD89u1ivzuP1QcmX5bpbnnQ5pVxKyRj3JgmhdYC3AhKyglFx2I8hxIsHy9jodv+q7zGOxQdbLLrl4gSmbds0vs2D7m7HJz998t57T7uOLPFuNyyWCy06DskHruKP9SF1qCAJaOoKfrdIiUBVUK7mfgyknA5jVXbPUsDJj1TxTx+8tUrO113bDGwMI6gAzAjBNbfXzwK57qyLi7hT5DLEGGMXTPNi3ewOh81OxrR98+E5oM75lA5mevlw7b3/4Mff11BE2MSstjKwKmyqsGJCY3+QMTorCLh8sF6uouRBmIN3fb/Z7q9ubm9PuodvnV3iMRTpZpOaELxrS7FpfUFp6sc8YVE8tWmeDdS0mo9VeNPCNjOui+0zXFcAMAbXBX1fmwpzBe8d8DWBN/eNLc141dF03yW4gQoJHX+bLS57ntfNnYWeizcAs6m+2BSYhEOPsguTrt/df9XNZRDNSvRATQXPp5zbLJJmswA4LBbdO4/X2+1tKtkFct51XZckOfaqQhbqbNSOOwDwWa/rWJZw983qyeek8N3WNr+tOs21EVbF1kDspr2GJgjPjFSpur+A8km3iE0UL+rFLZmaVqhQIBdYFEzStBycN03BRW++H2l/cxh31SRWwoVliDNAoKIGlZKKjGo+NqGMKpL7tB3Eb/e3u/5QcHJ1e52Gwbtwdnaa8kgEDoEkD+M4FjH4NgaHEGPMgpub3Zg2RLFbnC5X64apax0hCPxi6bNc+FBAhzGJ93Z2cf7lr7y5WnWtDZcnjUN58vyDw3DIpWz7YX1xJirKPGp+fvPqybOft+vTZH5zffNgfdq1J4vQdH51efbwpF1/74//dHPLpWfQYreX0/XCREQMDFIrYrWVBpmZFRhLX8jAwclAOjg1KgPlnhG4JM8OsWngGxfzfj+MZTyMu9g0cAUucRQXJedCDOcRosujjmlUwQ9/8GHJ5VvfWZ2tzmPT/fiDD5oxr9romzimYXPoiybyrlkxO+PgZYSWohk546vfeeQiF8rCaS831y8Om3QTV60ohh5l7Vg8Mce4BCFlTaOMaciaSwYgMUTnAyyAHHOIFEIwMyslZWQR6Q99SkkFi24VA6U+D8Oog2IAR4CQS8n7jBEUyMS0CAQlKxuTAYVVxQkoEwtDicVyIWZ28EywBBmNPEytChTsNhs4tJWWDFJRVrZiVrTU/r9ArZxhdZg47PPyMJhicgymEq+KqxMz1GR+j5ooQmBwGjODgvfM1LQtsysQ80BkCGtRFcFdlxsmZqtFTzk/evD4a7/x1vNXH7z7s/9XRNU7OE9eUi6vbl+9+fCdizcfQPe7n94qFWLWGQrXY4bliL8DM5lcpvXrDAzXuGbpVherbt3QiCRJSLrTZl1WzX60sZSUy2iO/WLVnD88o+j342G33e2HsevgyMUQ06CHbSq7nA7k2I27omPO+4SMHBLHqjJZXMdZklpwjuo3FkUZpMgO8MzOu4bJCJIl5wyYeF8jfzNFiLFtl46i17aUPo9iZsrFeRdjYHPDMKQxr1ZRTYdD3/eGTKAikcnUgdSb50YJPsamDeSUXGHfZMGQBWoOwVF03oxK3WK8945o7IfDYf/ojbcWy64UKUnyVjWXXRiHq3xznfSQfvrBe7/+tW9/6dfefP/dd/vNTrNmK5kyyCkdwxg2E4YpHV1D2ETmP6of8V1Pu/o/dy/4B0Co9pfhoaKmZDARUjXV2HA/jCXIxYOT7/69vxvQvLrZP/n45e1W2oUZl34wY2ZaKWgYpIwE48JmYodDHgcDLJXU5LjfvSLzecwyZDYuzpFR38u2H+AR2oZdcAgmAuDpRy/ffNScniyYDy4sXUhCfTYtZszuMO7zOGTJ6/PAHA6HfUrJjLt2gbzcjyNpIfWkIqKSLA86DjkPZhkkk/ysiUKVJv16Y8fOUfSN914Vw6FPu+ROvDPfcCNeQeSJmZ33TkxM4I3FlGxqXz6nmaky5H9BQPY5gz798/zZY/ryPoxDRy8Ex513ehcdPZO7ILfWvlT20zH4NbM7ipjdPQk4uiX3wziiivIQ8JoYpr0Gah19KJr/qX2jJo74fddnztR+Gp+yT8e29/kuZkcR9tfecHdxapRkd2QaYqrVkzZhT1Uz5ujrYUq9TT7dHYAFVEm8mm2z6Rwkd18TmPt51dPCjly2e8NmeGq+S0e1rIm0fh87JJooHlNER6//+ReM+5fkl4QvPsUiuo9OfMH4fADrl/zwX/n4XMzol5zS8bM558892i86wmcRIjNjZnxmfBaEOsJAAEop96lGU9Q/r89fBGDdB8vqLbyDqP8qxq90KLo3fpnD3ge/Pv0RuquJw7QM5uVUVybX1qfz2rnbvWaTe0SBTc1MMOmp1PqPKclGUFEjIzf3gAhM3pFj0Cw1xUTeAVUnyhQmqpazMcx0ds+Air0QMwFMtV0VKZFQ7Zzqg4eDkamYVcZ8KVa0noVrDx81gwDmeGoVLFLUTGd7r6bHZrLH65ZSOgKXNBFZVKh2hqYJRJsKtaFc9em1Skkg+FprQ5jyXZMCs4F0Oi/NDC9RNStWY00idjSRzhzBKTErm6qULACRc+RABubaeKVmKKZwcpQE1IkZGOZo0mqtr3hXJXynjaZ+O56fE3cXDGOGMomhmuGwPl+pZqD4AOeMiEtJbetByGNpfBhdIHAb2xACAFNlI+8CES3asGiXKaV+2MUQYoxt03ahPVmtz5frw34fyDnHbdNYltViYVZ8cM7xolt859u/nnJ2zGfnZ23TmsjQ98QcfWiX0VFguJRTn4b1+dn5m2euoe2wf/nTH2/67b/8o381pNx2q7aLm93ti5dXfX84Wa2/9PaXHz16+J3vfPvs4sGX7Ovl/XdfvvjkcBjgLTRNWaVF12xurpj4ZN2Se6M7WXTL9XCQLOJjaJbNZntVNJnXbtGAbMx5HHIas/MkhcqoxHAc1JmUDMGrm33uc+3u6B0RSSqIRcXkZH1ChoZbQux36f2fPP3pD5/evDwgOclwzpdkmO/gbK+qnzA9J+z46HRq7SBQ9905BV5LBZxzWoSYPDtQVeuGkZKzMo4MduQ8u2ICq8wdcs7BWJJ4aobdgDWWy8XQD2BnjsS0W7SqenX9ahit66DGBCelHA7XKu70bNEtuje+RJBmezP0I4J37BqVSmIqnrBcdmyjp3K6bL/7jcs3HpxHT5KSOKYQswz7cXv9arf8tbOPD0/+x//+P/2//vc/GvZbz7V5p0kRF311DGqXJKD6lw615bNW3WNVnZ0GmwTCiQk6aVHdYTHVZYKr64hsclLsnlYoM+mxUaqZzAnCO3AGs3MzsUdrBdxcLviam3XffIPdLFg3WdsJuD7+QlqB68k7JSIwmamKeOdmXP+4BYCcq4mGqU/ZDDW97l+awsQsLtrlyeLvfPcbT55+6Fph5sWie/Dw7Cc/vG1OfEpg53ROX0D1NaTq+FzazJWdM0c27xoAMJM8qerWqx63FTOrrW4rjlqFqJXV1MiYmOAMDsYQElFZd+sYovd+pPGQdyq58fFktSpWrm+uVotuyH108XRxYkUvT9/AQHsZD706JWQDUy2hkpLZGxg+UAg25p1qljI651MZ+3HwPrDXLHkY+lzyzfW1I6TxUErSErq28eTMqagNY+amGbKmfj/0t7v9sN2M7BrvO3c7NN2NytDGEGKIbey67p0vvXHxYPn48Vmf+lTSGw/OY+uXi9CRrAJMx37YbDY3HOJq1Q3pkOH2qTx99eLqdvv8enPZLA8pp2L9OAahhuLlw8cX64urVze3N/uUT5gawPlOS0mSsxk5F5wnGYvk7F2EY81GnlI/Bu/Zt4ftWEaCUW9aWLmh7U0OSU8uFk2zYF8+efaqz8imq3XnnN8eXg55F1toprazzeaZiBK7bhmZLA/jz3729MGDN7/89XcuHl4Gh3Hs87XEjg2la0ITw34/EPSka1Zvnzc+QqmMKkVPzqKPYd/vXlxvh9veN3BhEcOJSLpNw35jO00GaroIpjHjMJRDKllktNxYYFJjRclFzUqRYo5IVVMayMNHLqXkktM4dnHNxpRp2I3eE/Zgx8F8MQQmi+xjA1FR4dDkw7jwHTEsS39IjoLkAjVSsqIMZ2Tk2AUHoeEwGGsqg0DIkakxU0k5p9IfeknCNfVXQEZWqpYCCAyDqorpa6vLoGKMOb6sJozIKlmgZvFMVc2R841HHlXNN6GUHIIvScZcyPt22VDToRBGcKbD/iBDMhR2sW1W69W6OVk2zWJ/c7h5vjGx4P3YF1jmhrc7LQzXheVqddhZPI1BOJWUSrKaDnOwozqjzXZidjOMDd4QgEAZJTZBWPZpP8roosuWy5Bd5FVY5EMeD9y0WHSLdtmG1g95PAz7bGNsnWMxMRlNEyGxJ28jjTmNmwNU4amJvu2iW0Tv3aub66Z14zhubo2TE0VownLlspGaMxdYyRkZisGMAQfnnFo281XTaLFahTZutru8L1qMxBGgVjii0tgpExRlKFo09xmDARHBW1YYHGrTBAcxFucpOrIq0laMIze+da5BSSnn4lvyLsQQ++Gw3dyWnMVA3mLn9aBGaBeNR1PUChdios6efvKxCS7WZ9/8O19/+v5HH/zoJQzLkxMil/oym9zaFJLFqgfLKjopZHBlHE/iqXVvNoAYzkFtEn4CiNmbmtW6WlUrWlyCqiMUG9g1I4avPj777m99+/d+7z/45Pb5zz74+GdPnm62NhTZ7vtRyCBNZJj1g2ih4D3AWmzo0fdgRillt99evcyePBtRMVJOPgV2/ShpRCSGshYpWYvaVy7xp3/2k/XJd8R8nzR0C7nZFDGwK6aBrD/0qogGGBYn3ctnt6mEcdRcGBCYWhEyZ4phSDnzOMqYTAtISbTU0gUpYqrExGAylFQAcHCsTrNoMmTcvLwmkIPzITCRIwbDBJJVRoESGbQiYsaTlG696PbZjXTeTD8zPhXO0exIVNddAXcXqAGwYztzm7bWelgGJuXJ+u7ZsTm+AZWfVQ9eewbWEpbjDHQukplBLkJVuK75ebWpoEUBGCtjShQSgFJ0DrQAYNYoNvCMq1aW5v2SF6J7jpPqvQiaPxUa32XojgjhTId3d6e8i2oxoT/sphxbdSOPgN/Erpji1rvU5PEGzOor9ovEsU2mJhdWPdF6Je9hD/XqmZpx7TI2L8l6SgBzHpZnxVWdEJIKg7KR4rWr8to4Xp9PPVRfAETcB3k+Bfj8hZ/9IgYW/aKL9Dc+/kI85d/4zX+F4/6dIyLn3H1Y6os/a3Nt3bEM9Qir/TXdhfuzvQ/h/fIY1hcNm0zSEeaty/UYRtV1NS2IIwhud4t8glimuWFGRsBMzlVuchEV4L4IFADENhbV2k8H1QrMcdgx42NkampS5QCYiYlBTCpiRxR6tkgwTBXSkyK7qoqKanX5JqMNF51qmaSpyNgxudoO1yZAvhrReRJzrQ0RkQ61g0jlaExw2tTYBVTnbQryDgZHpMRGwgpTbWInRdS0ZlR1KnmvQrBmlTHMQt6BHYEJpPPmwI4mvVaulC0lEFSrF+hrC8dKA6s7n6pJ/e4VFLPjnkUgYxDzzOonOurv81yuA2Dqa3s/eVOfeYMRB3gPzUUtq2Xn6r2z4Ke7S4r+MKpYDE3bdN77OdtAUoqZdm0XvGdQHntH5JmDdyH6GENso4NbxW656GCa0tCQI8J4GLqug+Dx5aP90DPzannCzIftrmQxBZNjI+dct1z1N6/Y8eN3Hp+v1j/85Ed/8L0//MlPfwLvrna3xC4NlrgboGhiSen5zc3L2w3/iN5/+rOvf/1rb7/9+J0vfTnl8ZNPnjri25tbM90fhuXywKEZx5RyIpb1Rduc6H7fH/rUb/Z2lfrhYNC2a9qmO+x6KWPfp+C7xUnnqC2ZxpSYPIcmlxEJ+81ht3FjOgzjeOS6VdvCxuxjE5am/s/+/N3NC6BHSwHGmPSszUiM3LyjVl7yRGs5NrCr0EVd2mxk0OoeVSV35x3IyBHmGq+6DEFIuRhGMwtNY2OqixDTUQHiLnRwpsVEjIhFIEOmbGNOzpEUR1Y0YbsZPvzw6Td/7Wspa9s2Xdvq7f4/+b1//+mTZ+/9+OkLPZhZSgPM2tYXsVFltXBtg67F22+9vVx8uW1U0ljymEHa+GL55fWzNOLj50/6JP/tP/nH77/79N33rlcNpzSGEMd+H0JgJp0v6dFO6jwMarWW5c4lqZ7UzJ+afJ0jx3QCm232hKZK9HlxVJdo6jY62bjZTE4Ifj3TkRKld07WrPaO2UDOV3lCnz4ziOjTvkINbHn2aSYbM61fvjuKYU4XKE/eqxnAZJOig01fOyy8jFm9nJ6evPnmG59c/eHqArkMRQgMCKTcdUFUfc1SENGds1fjHtg9SYojGD5d6hn7n4X8ZhjNoGrMBFPVWVy29tM0GJGaU3iggW9945s3Th9dv7g+7A/SSOI0Wt9YaLomxMDiWl54FxruWm29cyfN6WE4jEPRDCLAg4h8cI7Z5VJbCbQrcy4R56Zls7Lb3G43m0HSYsFNaFerZXU99zusTzCO/eb6umW3OIkiMua86FYudn0q+9326tXthz97ut0cQlhdXj5eLLgfd7ebm9UKMVCMzclqfX520XVNCPzw0bnYSdEUgiNH5KnkvO0Th7JcLzliSElMn794pq758Nmrnz972qyXp+dvx6Yjl50mLWpK69X55cWj6+vd9//0w81mSNIi+K5r+8OoyEVUlZjNKQGiMAAAIABJREFUe8cZEzBqCpgjZyBTSFEpgDoYq7g8GESffXwVliJk6wdLYogijxj7frmU0KyIsqMcPIXT4L2v3CLvHDuyUlwOw7j7+KOXq/PV+vL00aPLl7cvxzyMgm4Rlt2qqImgadomtDE0rY/MbAJTvb66cskJJMZGsjrmrlmTdofb0tFp2bvdfqeE5Qn7xvclb3b70cABSkj7nEZxlDx85FYShv1YUjaDqLiA0DiDFhFT9Pu+jDTcjrnPsesWiyY67yvNyjkh782XlDiTM2cAq3MgLZJLSTlDICKo3VRIa+8BLipEDqQkOWc4wAMEVRv75JynwihiMBRYNjObnKvJ3E9R4/104531mZfelOqrL09bLsNgShPdFVXdGqkfS5HEGlzbLBsrsKQu+ugiAix3wVzw0TvXLRbNYrW/Obz33g+25eb0PORUlt2yffBwkJ3xzYMH62YdD2O/H3frR6uyy2mXbCI1GvOdrlKt2CaClKQqympQYzOngF28fbbPu9v+pvNd6BrnuaiOQ+/JNS664EMUiBlZLjkNKUlSJ80ysudlWInI/mY/ZuXi2mYZtRtKr2g5UAgUo1ueLrv1woJRM56etnBlf9iXfV4uWnYNkhYUEnLRs1DuxzL0IKEW5CGiKFZVIJr1sjvr1Ovt9mZ/s/MuNqFhzzmltB2HoY9NDN6bYNiOTDAl1pY4BDFv5ipjmnm7GVTZqQlLttynbVaA29OLk7aNu2G/7/dgLFyjSll1GPO+H7XAGLv+oLB+GG9vD4u2PTk98RbLoAJrWv/s1SfPPnn+nW/9+oPL06+dfONq2MutugwzKdejeZAQwdgzO3Zq0Mr/J1NSMgaDyaQoFWaelLVpcs8Zta0Q1TYaAOdSRCTGqKzD2LN3HGl1Fnf7azN8/Ztv//bvfOvLX33rX//pH3/8yaurq0M/aDEHYEhiJI57JnY+evYEL6K55JQpl0pcZFUMY5WZEMvmBJk1OKeTKKtTNYillIn5MODJk6vNNiuCb1YLL+2297uifZ9LUUtDAhNCG+JiFZvIIYsORSlLP5aCnLPjVIqKb8LFy+E2ZzKZ8voVE9AipCBiN5WVwHEgsXwowgagcU1cBtLau8NACsfOOVMtIjpKGbOpefhAXJNJplrRMxgEnxY7/kWDZ8KUzQzo6l5U8OdoG2gq9cBcl1EZQFZTZCCb+N9m4Km7V60FQfVfag/gORKsG7XUKPEegWRyWWYXZDoxABjP9acwAwPGFTQ9soXuGO2V0F2V0I2ONX02OUq/aNB9B+Pz33HncB39PITgq35+bdR9x4Sq15ErMlaJBhXOnRIFRCRSjoey4w+T+jDN3+Vz7+Oxc0K9ovegg2PqbiJQ2ESsn29rje+O5IpKOQBI1erlrE7c5wJM+AzG9DcGwvjPB1/nb/63CsP6m5zJX/Jc9wlcX3yoI3QFgIhE5G/sUaDPUNI++8q/8ZhBp/ur3+Z+87Wd/GsA80zpqtNApSPNL86EAgY8k/fVC5s6ah8Pz4CCvXMFRYuZAlQLfDATRpmNiZgZngmoElDMTFVDqshx5nNIOeVO5tjpeKPIOTDzhOTDBLPZJdQqf0DmijytdYfTJ1HRvXogENXEmd0Zkrqpza1eRYSoimfXnX4SR1NRFY18ZL7ClI2pZh9pkhIDrHbSNdQSvUqkmOhSMGjtaASeNwMjgFxVN6yy8CIqarUNZJkurW+oMiuIYUYiNcDkmqOpCROrLY3m56FuhUcR65oKAMMxiytKWuk9eRxdUMkpuAioFCWCd46Zgwub2w2TCz4Ax3JHE5OcUsnF1Lq2m4y1FMljYoKZdy46v4qtW55wcEPq97utVzQx7vf73e32tr19+513NEu2vCMGsLm+ub3ZiJS2aRgcYmjbLrZN0CYswrP+xQ9+/Od//u6PXty8WK5OCptqDnD9YTfksZiKp1Ko5GRZ/uyHP3756tU/+N3f/ca3fu276/X2n++fPHn3TM+ZYARVgaZUhj71h3G82fZ9X/oxiVKIfru7FS3eha7runaZB3U2QLiJTXSdR5PMdFQjy/CwEQICOXYxeJcR4wT75pxhPQricuVPGtcsNjcIBuaW4Kc+mGTKAqgwrNTuTrNqO2bUYk5P1Wt8BGYqjFkfLMlCDNJamQvUvLiHiAC55ELMVlnUylPLbNMiJaXB1ErOt7fbYjaWMvlC5FMS5+GocexgdnvTH/a3v/6N32BK3gci2x82f/93frdp/CfPPkg/BwalNVrCfswogOLB5eLh5eJi3b7z5sXlg/WHH/740G+b6CpFajfu+jIYhY9efPT02at/8l/9/be+9DC2P9y9Sn4B1y5AGFJfne2aPKzIrGNXpJiaqk7Vc1M2i2pN9NG/uW/TjhZPyuRw3KNDTSLYRFQpWMxQNRxFaeZROyZbNaikDtCpT99syeu+yfdwnInmiRlme218ylmbkwcV0559VrpL6r4+5hokstrQ1LkqmmFmNvP4nMFUBFkZdPnGgx988NwvlimP/WAiBQWiqiUbMRlPydj50lSzMQN5s0t3DwB8bTaqk0tMU7Q+TbgmLZiJSC1XW6+YuveQY3OgCIvgBiH6JjR5yNur7TiObs1DSFJQfL4UtL5b+NWD5YPhMOaxPL58u+uWLeJQRhUBIKOhZRtLrrNhDdHaBss1xVYYYxNdcAQyB3JgRy5WcMZYpDCwXi3aGPIwQNURZVNwMLj9mPrNmJNdXe82+3GzGx1T6AbXrIYkN9sduTgMGkIpmXISH3yRtNtvUxmy5nYZ3nj8xsXF6fbli7K/vrxcnZ2tu0Xz9NknL16+MLdS395stknotDsjHWOgVRcPUB3zSbN+ePk4toufvf/Rn3z/R9e3KeWd2sp7Z0CMUfIoqo6d9z7NCNYMUhMTq2pKWQsABnvmyDBRySVrrtJ15r1br5qmHWOL8/XiZLUiciX61bKLsQk+GMQxNzEAmoZ89eRmTPjk2ct2HU4uV2+//aa68Xa3LQLv0cS49M3jh29dXD5W0Ob6pu8HM0w9zhBUuW0WbTh1260KqG9ub0aReHZ6ISLOL+AgSUJsKDR7P4ql0AYmDCnnpEm0cfANkUKLjWNWhSiiwjsX29ZzLrkcdvvSczpIgG84LBaxabzBDnksklkJanYQGYUdo5ixqjLUiCkuonJCgSlUoGNBiD5UHUhVK2Zzhc+8EGXU2Lim1hoaBCLIDKckc7KisjrvcqX3bMsxKDta/cnuWwFYa0cGK1agRSREhsI7D2PvWShXlFJUIGJmDo4DmqbtfAOhcT988uSp4zYsOxW5OOnKmPfb/q2vvHn51uX15rlf+NOzTlmfX714vrk9Xy21FsvwxNMxwBjQWSzGAKBwBgm8ImD6Fzh7fCq3UqyEpmmXjYhoyY68Y29GmkWLmOrtZgSrXwTf+XbRUGTnHZKOhzGNQgiNRhaylL2xUmiCCwtHAdyQj/BdWGq7WHWimdS8+csvPZQ9X/P+kK92+wNJcnDGKpJAQAQC4AyuNtlxfsm8IPVlOAws3lkIPpJSKYIBpRc0qe0aZxQSE8OxV3Uo7Jx5VmZyRGTOZcdKAAmrqNQsqnktSWRUMnM++BZMSGPZ7Q6Hfig6xd+3m63zrlgppMWKWG7bdrnuUDCm0p0EgXzwyc9PH54/eHz51d1X3v/z9zbvb9Fg9VbXb0fLkGyiYPPeR4OWbME3TUNCEMklZ6vxMZxBpcpOm1mZd1U4BUSm/aeoRPbeczHLlohYdiJWHvwavvbty4ePTwzjBx++v9nsVVqgkdxJkXHMSUbvAzvzzrrWRd85tmIDkB0jOE9MWqyJgcxBjCBUtSgVpYj3LrroglMWAi+6NeB3u7KI50v3oLhRVNZnF9uh7Adc3+x0yCmj7cDeEXt2bYyrtvMhFhf60GQ51ZPlYrFYeheIdciv1NyRPe2dV1MpmcmTVTyItJjznmBW2MgcO+ecCxSCL7nknEsqWUvhwo4pEGXz6gA49lwLCVVIuJaJTHv551QWfU46684UWI04rFpv2N3GbzYJtxBAajXTVjNsCjPjKjhVbf8xlCPc/SoGpqN4NE1HoCkBdpxK9aNgkyw6TYJ3s9QPz5DZnC89RnAGYmab2ihX1GzqR1Q3JJqCTvuMtMOvNj7l1IFAdS2aVRhrSsody7BmNll10OZX5vj39es/TRU11ppv2ZGP8akb96lfK232/lSrUA9PewXuPPrpdNN/1eOcgEAmUmO6i4uZ6fXKymNMZ3Pvu18SRvhL4hu/kIH1twfDugM4/+rglb/WcYzSj/fml5nzHcz9Osb51/F978+t3l/vPTMfxeM/Pyb4FU4AlSMSDGZSUyJyzjPX3cpQ3cd78YfNEHWt6qaZ2kBM5DAxpD3IA1Vhg+9QeZ5kTUjVtNYMGs09+hQTo7W+1TnviUkAruIPomYGMfKVyKoyJ/rZCEomNdh2YABS5QiBiWXExEqmrjjH7LiCMgaTKeCb8KyaqHDkJnJCTf8bzMw3/nhHbNIRrNQUNlUUMUAJOsuiwUyLaDEUDDRoUZiRY3VszmhW8iMiKE/7jCgUYFUwyFebZFYUqqpgM0XlTrCDm6rEzVSyQFKp5J2JS1rF7ONMF6s6V9WTVJ0ySphKpYxUTb33DFaYiKiqj3GK/53z3jvnLJSsQymJDZ5stVjm7IqMpLRom+XJ0ns/DsNwyJvSB88AVIoJVNV7v2g6t1gNwzAe+jQMMYZHDy+7LvgQ6r01SLF8vekXbdc4n9HvNrcBSGNz++p6s7mNXfvGG2+cnKzAXEqpZcjOu+Ddql00cQliIzt/eK77crO9/qf/4p/+4Cd/9mLzslk1hXMmyabb3TU1rQCHNPRDr1kcsY9Nt1psx+Ff/8n3nj5/8rWvfvXf+4f/8Cc/fvCTd/8EWD24uIhdm4rqdisysrP16bJZmN+PY8rOudvdtZp410RuSd1hO+x2ByTLlse8tdITeckSArMxBIhoYmjbOCTXNi07y5IdeyYqsDYuzs8fSLYnH3yIj5HXCEqTFCQpyJRVucTAkrTq+IKmZI3VXNcMr9TlzQDUpnrgyoUkqwo4d3hufV8VyWA2FZiYGtdSFBgAhRzSQXQk6Fjyvh8PY2mWbQiLIQ/720POAkJ0bEVNETx64PZmUOGEstncfPzsw3/2zze/9Zt/7z/+j/6n283+D//gj//Vv/ij7ZU9jJxFQjv8g9/9zptvvbE+W7KT4K2UpFoW3WLZNk3TPHv+XFCK6uFwWLbhev/qv/kf/vHl+Zf/l//5fw2t69OhWXRMru93zjGqM1dl2JzLkqdLVGVjjsykGb2qS1tEZnb3DI4DTOG+pT3mM45b3twlUJW0crEqOoyZjTSJ6hPU1GqebGY71ik5H+hIiJynk9L+czyH6oDO0PlELbeqWFLJqAS8Jip4nLjWWtCpdHwik85cMzMGiJmolMxd1CElSScnJ20XnXPEAKFbLBARmqhwmonu5xgnOz/xWO/At/sJjOkr3/2sasyzKNcRH2Qm571jAKUQgaq2IdiMzEdPAbbIpVFEmDMi+uCnPz9c7x0cGUkrcFi4to1t6zq3CF1e7V4OL5+9eu///BAJOMf5W2eLVfvg7fP9/iA9cixd4xedg4zBaRNw8TA+fLQ4O+/UVrCeVB08qYy7QUWJOZcipfz2b37lrcePJMuw3XuzfDjsRy0U+3RwLmyutvtNf/NqpwXKcXdIuN4WaoYxv7rZ/cmf//B0dfboweM3H1MpIXgDKVG3WCzbZWu+tIv1fiiD2FDS9ZMPHw1n63W3OF0/Dt0HT642m804mHerze14vbtddvZgzY/P1w6xccuz1aUk/+p6//zl9maLoT8450FkUpi9EYwka9IiYx4hgNeJLzDdF50JzJ7YUIvYLMXgvSugovlAITx647Rb+L7flDy8fHbY7tOiXa/XZ+x8KTmX4rw1HTWt77ruZz/4+HDA9W6P7qPztxdf/dZbI92kJ/vtQZdt8/Wvfq1pV5L5B99/7933f/L0I2AHLHFxisCNjPbyVcIOSEACGqxPu/Ozi9Pz87CN+5ubJJqQN8NNe9J2DyIre0cNuXbRBDmMhzyMKAoEOAptJGdxTKmUFMhF1510C3K6322ff3zQAU4cuyZty8kyLsNC1UYtlLNnRqJyk2zM1pCJDaQE8xQcUbtqsWxMVEuRYjb6GLumiewop/HQ96XIJIydDYzG+8a1NkJSRbdMUkGBsjK7amvEptsAmwhZd552DZposiVHiwSpBt/gCIBmRYFBiyGnrGy9AgGLB8tM0o+HLrSri9PWtwHu51c3Y+lf7JINCiBSyMDhkIv1h760p4Di6ZOPDqkfaX8R3WZQPRyuD/tEafHGIyRZpEW/H3ab/bhJJqBApLWVzWS92DM5dg0hghqiaBLsZn/d68DOHcq4veoPhx0yAnHwvjarCd43sYmNHcp4exiDjsuwXLZt27VPfvYxEiK1nVvaoNubQxp6FUEEPey4ifA6qsphdAWb7VW2TkQk68qv1uu4PD1ZLB6sLs5f3l49u3qlo4Z1q2dMJERCpMHFLp4QhTHlLGUvt6aSyti6VpMNaVDRksdK7S872cXDFHY6ZE02JhSMVGvV4RmOkXqgILsBAYAhghrHpvurK9XT9WV3EjoJmnTo+343FIPG2HjPqWTfNOz4jbdWF1mur29v++sh9zC6/PX1zSe7fp+7tutFf/9f/rOTN07/y9/7L7777/72ez9493t/8If9Vc8twiJAXRk095KGxBSZnBmVUqEFBrngIzOB1UzIpBoFV1somSOQgdjMOefbkNJ42ByoxepkQWSD75PoP/y9N//u73zzm995O9NWMPxvv/9/eFnd3spuL0PZWTFA4BHbYmY5jatFf3lJwblhSPtdhqlriQzjWPa9kTqIssIrkZhqZqD1Hqh+ipYsz569vNrsbz4JTz5+WWj7/R///sfXt//1f/ePFuvT1WBXV5tD38eI0GDXH7KW2GhO7MMydj2HPpBePjp/cPEwxrjbHXbbvRaqnlRhkIOxMdday1JzPlorMEcxNpBVdpGQMmGbdqoiUmCoeQKBpN0IA+C8c6KapTAcjKnq84pNoC/TaxVl0yb66d0cRzFLU1WraAXP2/AEDtXt9BiuTu1kbHI1QHXXp5mXMBn/+7/UHsdMPKnDTNNgYuN7EehEsITRJKcAGBwqeY+r+2moKnvHD1UyAntnc/XLhL+TCRnb5KsAeM3T+NWHTknDCc6bTm6o3nH1t6oXJyJqyjTpTjjnFBPAZMCcylRi99nYe86K0nQN6XOQSOD1a30cM4ng7ufPG3QsApsPwuQcPIBZGNqoNs8BoDYjdDXGv2tmfQQufknh7y94z184voiB9bcBw/rs9P5mJvOXPMWnoKgvPtr99Ne/ret8fP7uI0p/qXFvtcxHI+aKiE+yOEek1mBWOSDVMk7mbyqRD84jUEKeGKrV3ZrIxhOGPEPoVEypAsTGZjDWCUGeru7Em9TKY8LU59FEQWhjpzpVJasZmUGNlatZVFOeAsSKTRsRGZuyGSEEhid2jpiVTE0n9XKqR7K6KygZG6bebjOvZaK53nWvlaPiXw1O68VUqMHcZErqRg9VhVaTJgarsobsK7qGGRGkqlQ1M8AIBOJJDX4mcWB6//Tkau2MrcUgtWbBSCvLxpSqWj0TATqnQSfu7txTo0JgYjVAmQSwAABFCk25kenxUM19TsSIDkM/nKwXwfnDYaeK6KnxwXs/aD8MOyISkb7v0zBWRK9t2+B813YE5GE0M2ZedF3X+Kwl5zGLAnCOW24URSHkfNs1sW1drbgyRB82N7fdamkEds6A4H3wXkttUqZt2xTV6J2ofPDRhx/8/P2MErqYrJQs7XKBJOMuiebCnExz1eR07ILfbA8xUNcsbrf9zz/6+PGbj5Yny8eP3m6a0C0WqlpKTjmNqR8FY7LDINvdULK4GInYihhUckkoh34Y+0zmTSwPY0m5DQsYJIkSQvDmSl1FzOiHnqgwzY6BmYrmUXJKHz35BOdoKQx9JhdQm6CwKYkyhE3v9UKg+lebeYwzB8aItMI1NlOxrXZYOeaJ6mM9wcETL3mqdKiPojFPXSvVSp+LMxaFqPCh5xicdzBn6lEUBCmkhczMAWBcvdxePDgByW67y2mUkm63L29u10ThK1998+GD/zz4wGqb3TbL+PY7D7tFMBuklKEf2siWKadEXUtEwkgq291esmtbffe997705jdjF7DCOIiDUQhT4wJM5EGae25U2QU7ZiQhmAWt7gNYzh0bJh9NohFYVQG2uzY005jWKpEBPKvqV5tBk8N0p8hq1R4YiLgGndXuVZSNZgs5o+Sf4+fU73Q/sTcb13sWfeoI6Mx0Kkec/nxXNjkDZUeIaUKyK5wHgbIu12fdapFzCrEZ02Hf9z6szi/O4SByn3HFRgqmYyLEjv1NUQvJ7X4CuV4vnjedKRlDhtlDhs2I392oovQ0EYZZ2TkfPWJGtJp7ONxuG144uCQjARZQJL/45MXQjouwfHb1/NXT683NHgXceSdExYEYjlJOCgPBRW6Xropzhw6n56FdEDAy6XAYx9SHGE+bJudcsgoyEaIPeRirhlQZx+yDV5KCg6rCXZ4tV2fnaURsFTGEBt2SVqv1YnlCLnWrU89nwBLcAQvRwIXZ+3bRhMjs+cX1J0rekEsaleh2u1Nk+Ifr9WnHTbsYrnc7EajR7qa/3uz5jNdvPHzr4aXjFtqF2Dz/+Ob9nz0Zc+kHmBIs52RF4X0TYjQQV85s8MUy2CCAQN20E7IHDGpiSKYKzdDs2CmgmkSKSPGOl13DFktyEvxus7m92e62oxRrunh+cXJy0nQLLzLc7vovf/lrHz99sc/9OKSnH3/01W8/VBl90CaibeNysSiZPnz/o5cf3+h+geEAwVloz9pzZ/7Fy6uu8FgUmZBJB9nc9vryxi7ZN15MClm3XEjW7asrRWzPm+Ui+MZ1iy7vBuc8czGRkitpCkSeIZ6jqaS+jKGIjdvdQW8BQvRNG5rGx/1mXxuSbDeHrOY90cgYCT2YkQVmI4iKZcfOBedqWYcHqwtN631w3plZDcgq9MwgFXOOIzfefC5qhViDQVjVoOxc5YsfiVc1xwY5ZvkmC4djhcnRZBkAP9UVV+OiU/s/hZqZi05EFouFD/8fe2+2ZEmSXIkdVTXz7d64EZGZlVlVXd1V6AWYYYOggMIRDAhQ5pHCB77xc/gP/JH5C1IoFD6NyAxAbI3uri2rcovlLu5uZqrKB3O/EdXd1d0AhEBTBC6VmVERcX0xdzdTPXr0nDhr0ilniLaW0jymMo0jKXwGMsCQIDBupPHGprzPI1hgavf3+24nc0rTPhMHiZFaHMupiyG2Tdw0zbYdt6d0yKe342LfvOq8qCoahA5937fbNgwBHd0d7zmwNOKEKc+YAIUCXqzMBQltZ65o+ygcNgO6bRuGOM2n27v7OeWokUVQUE4l306kGgNnWJlSmtXYUXTbdjGG+p+wcGyuL967f3e6S3M6lnmeE01xC9kNF5dPglATPI374/6g6iFykIBEPmmBOZXgxMxFzUrlq9bJHO6OGYsLLsMLxEMVGQIbM4Iwm1AqrkAhKCBOBBIzcwRi9wA2uGkBQd1PcwlMsREODRNVAQ2OsQkiJx6ng1rqeLu93JSMyRNRSMeENuzv7/7zT/7ivaun7WV8/5Pnx939q/805ZgjF+amaVsFkQfmoNmKFZCLUAgNE7hG8gui4OwoGQwnz0aobeFFGYSmixSR87w/nmAY3sd738Wf/NkfffTxFcf88tXP7g53r97gspm1tK7CyeFCQTmUKKHkjJy8CHlIczke53HMTRCCEGCavZgbw1l8saUleGBvmpaFzVQtF1UtcdtuhpafvfdBjOV4HE3x+s27aUpN21xdX/axO/FBOkIkklgKikk7bJ6934ZGTqc0j2nO+3EK8+gsQ1IPBDCEF9Z05VtXKvcSMFdHPScW0KI77oZqUQBxcTdSW9Ap46U+b7U1geEgYzIn45ptOJF7+cWFf13bv/H/la8EW1bMRaGTUIP5NTxgq5WtZU1eYvzF/IfIljb+Nad4oGjUf9Z8E5XfwMv3Hrg8/niOWoMUrC0AdI6RqpflL19NZVefuUL0EMycA5RF3uEfh6KcM7YlkXlMZbIaua3WjQsvqeoP1xOwhfy6+iWt6RBXbd81RPSFqLXSxpbDPWL7r9dUI7tlALE2hVcNmBrz2fmnv/pqHu1/AftsbTZcz8HXFHIRO/qnADL/RPQKv5GB9S8IXT0+k9+p8/ntt8cI5W/czjDW42v8//Riz6AOEZ0bu/DoqfqHHv1xwlNB8SUDwy8gWTB1GIg9iCz5MVelXXvUS7N0bosIBa60DavB11IyrJPDkq0B4OoUW7XaARCYiavxMtxNSzEzIyNzL+6L4jmBSRwqLASo2tq2XNubqp+K19nVAZaaDrnRKu7DqBUDVYUriEFOAiY2B6C6zm2llAooMdNC4iDKuawZ8ZrVE6O27zlZzWwJRCTEVZrKgimpwkWDup/TvMqWNQXqhZ1nVgmQOk5MgC+ZIDGJs1VqQ10ZTJ2pgAhGMEARiCgwK1WpSIMRuRf1ACYmXvXECIvU+yo7D1CNtmo3IlFVQfAYmgoTVi1+mKuXyHR5tes3oeT5YrONDXVtnOYpiAuhaxu+3G367RefvoZSSWnKORVrBHDPXR920m8uGgkhhGHot12I4mNO1f+7a9uu63bddrvZbofNVb+li92TzZVPuePmcnd5cbVLueT7+ymny8urrmu7fihFy5ya0MQQrnZXYy77/fHl1y//8v/5q+M8Kez2/jTqsRvadjMcxmN2U1MlSIyNo1DOxXRKfYh3+2PO+e7+zV//zfTjH//BB+9/8Oz66uburUPf3N0dptPxeDjsx1ltSuU0lf3BiiIWDJtAZIzAHEBSkqYJwVwaNwPMXB3mU55DS/0xwZZSAAAgAElEQVSuMzo4jIg3w4ZviEPDQiyBWYiElE0xj/OXP7sJDC9EdUF1A9nCrq5lM3JfUJFHy90ZMVnLWUu6YytOUV8LXmEeAhFsoR8+zCoV+1lkcQREgqUxFpqMIrl7ziXNiQpP82zqix+yERRC8IwY8PLl64uLTQBOpxMAc3316utG5Nmz58/e2118vOv7rWc9HO4Ph/396X6eU9sKk0/Hw9XlpZeUUwqx3V5cjHmc5pyKdm2fyvTly88F/XAZ//S/+4P/8n9+OvM8z1PwJoRolpdKGC2wL/PDXHSe6GydDB9go8c1oUV5eMH0zQxrW/E6uACBeJE9KGswsURLdefyKO6pQhOQJUI6Tya88FhXh8Rq2fqtE/tjPvkSep0LeA9CXOtPzsI5FZ9nX/CxdXSW+MzPq4I0bZPm9MH3nn/34++oZ5E4jrenY3r29OLFiy0CSilMUvuZ4UzVkqc6W1QIrPYunyPhb14LwZnF3RemWv2hWoihzlMwh3tlw1mN5h21/RNAURUCmEKMHpQcMIeh6VsyZEr9pqdLUPRpnEOehovtlz/7ar5JMQysCGiO0/7+ds8dXzzfPXn+xEcc7+/bxncXgby7GOR6h/c/2nLIN7fvxtOBHE3sSARCpp7mKZXEwiEIg0qaNWW4BaahbwTNuE/Hw5S3rgWHU5qTanFTduPTNHOYihuJfPjBJwRq2y1LA0SRJggFarqmKSivvr4pxt0mknMIbTHsT6erOV8ycZDxNMOZIIuaMETgQ+Tx7p5D/ujDD3ra/qeXn//nv/ircQ5Twq5vYXKcR7CYd2BwqIuWcySBVLAEioXyQ6g3kBYFxrrcYrNpZz9F4dgQUT6cxhAKqQdud5ur+SinY54mT2kuTNMpEXsu5DzP03y9+957im3eJ7z++Wdv/5z96nLXNDIMF47w5tXbm7fzpz99dfNmzCdiBRMF79OR58M07Ylzx2P2CUKtzyjTMU3lq9tXHPjy2W6cT8NHz19cv6e38/7dod9EKSEfU8kKggjHSAS24lZKns2SuzqRFNU8jSXl0HkjzdSnhprGY2ARcCPdPKb9/f148naIDrPZxEOxJB7MtBgTwYoZStYigSSIBA6N5GPRgqQZgLtKCASGqRBnzsJC4DRn08q9hNdFGBQkpFwZ8OcEbr0dayWwvtILSv4AEwNANdcDbAHvAQ88NL0TTukkIpo1hKaKJJAQM1SL5jTtR0xwBhgQNBzIUFKWEGPDheAFquBAlqxthmk6lrFc7DbDth+P+5vj2y60bdNGjtRQu2ubttkM20CBSdjZDa7abiO3XqQoaxEtXEpRCqRewQCDAwIY2DhSqNUpLZZLLqdUYNIFYhLhlHwaJxTkYuM0pSmV26THEoUZBIVNOs8a+xib2PXdMMTT3LJLmotnPdr0w+/+/puXb754+/LN/RsNxQQNg8fDxW7TX263uyhNOO1PqaRcVI2MC6ClFB/NjxMmNjcCQZdZuAabxd0LKEAYAUIOU4eDDVL5Z5FNUEO+gixiLIKGQhciy+HuYNHaixibYLBAuailXEQCgW9v7jabzlSJMXRtw5LnrHOakz95ennC/OrrO4kcghfCy5uvY8Sz3eXHP/rO4fUu+rv7r+/2b5UttzEyhzy7qYU2tNKAXEvJWtRMuMaKgHP12+sWRLuuoAwmZy9WyCAtJ0Vo+OMfvPfDP3rxwz988d1PnjufuqHFAf/H//5/t4ycvWQjDxIiS+Cg4ES2TPCVdZNmm6ZUJoQOD0t1XvSESEhqmuDCQkRBi806ZTV1TGNC2/Zo3Hw86M1tQsTnn32pzMOwffr0mq/ka3w5l6yszGEe9fZmHvqm7drdFRz7abo/Tfene58P0sShiS0pOIplteBLO4nB3Kw2qDhB2NUcBHUiQ33jhMlqqbq+u6algIRRG2hMGVRTFF/L204EqQnTr6PEPNqWBw/n1Z/Ay9tD9M0K0Fn4ZGHO1Qp3LRo5FsVQ84fexbou+yKRi0X0nVE1mLgytR85GJ+FWWjxcYY4mUGreVAlfK1AWvW69IdIyh4C2HMyej4TWoOVx9ANPcRh9dE5o0T0aE/Oy08WCI2cHmIRB9XWxfVblbROvCTaVYPd3E1XKgNhBbZ47fo7t23X6PFxIn0+0jcBoBUxIzprJlSOeRWytXNc6Wt4//jTbqvZWK02MrmTmdHqxvWNAWSuwohnAGEd0we4Bt++0aPt1xO1fv0WfuVhHn/znxMwOoM45799YRNwZe78Goe+fylg61ce9xegq3/QuZ1R6t/+I4+wj4edfBt29jibqqSAUkoVWvrtz3bJRx5q3QhhoTnp2rVFK7C8JDuERemYqekaMy8lM0sVZreSzIw5tE0z5wm0MNVXxgAAYhIwCQcQjIqu3CI6H6nO05BFmJecmJ2XMpSAOcBd4b7KcQkA5opxkStggDGrkzHgtSebA1jIALdisGqo54BDqwMGg3Qh2lYReAM52ZLlCvEi56RmUDAJpDZkEZMwJxReU+IlgFzF+Ii89tdUmhXcKbBAVvkdc0DYzeQbU2Hl3Lov+SzL+kWd2hbVdFnyTGEicXJ1MzcrWvMKI1sWkTq5Lq4jbu7mEPACKsBhwsRMVdm9Go2hVP1nwOsQh+WJIXc38AKRwF2hYJeG4xC6bd+Gvuvb7UW/u7q4u79N05EluKPvhw8/fHbz6thKn0s+7PfzfNpstkPbD22HUpomfvDhd0JgAQ9tcNP704EjoeFhe3GxubjaXl32u6eXTy+6jU45StvvLp5srlMuFOV+PJ3SJMwuIcQmcoS6Su4kCsVB+tkPX37x8i/+5q+PJXuMb2/e3oyngsJDn4yco1eOgZGrC0dn5DIejzm3U6TAFE7HPE34+7/9/I//+L8eNpdv7+5Uy1xmdy2a5vl0mIy4H6eisxySYkoXlxtTYm5MZUq5CT3sqMWUay7o5qWWsMxp6LcFmYMTqQNN2w+bjTMdDkd1hMAxNi7N4XS4u59LgZYiEt2SQ8nViwMgZldenqGFPbNgLsQEM2I+Y8ZuXpe9eisrtkEsqHKZoIXt7AuhEUBgqg+LKtyNmWOITJjnbEkrmAZC1QN2Qi4FplCCwYrBSYlIjBQ3b/bz97SoOohiPE2H/fHtcbw9zfunT5+rzuO0h2E6nU7Ho5a5iR2TaMltjE0T7OJqPJ2g1Mb+9e3xNFFoLoaLyzTmd/evdruLj77/7A//+Ad/8X99CjLBINxlOzlnNSWmGAXBkk5OFfMGgcEkxKqGouxrfFmtGLj6Jdd3gBbovTJGqSo+LREKVdsJYG3wcSOA+HFOWac7PA6p6h8/I48EVPjQfUUebW3C+2UtDK88zjNEuf4+4O68hpPk8LAIYjlQVVjh9RJWloZrDWcfaReSg1zdYuxQ0ve+++HTDy7vpzuSVnDVdleh2VxcEBK4JSJWQ5VZXSAqN4DVVjqX46yRYeSEivTxunzVYgZpdXhgDixqqAG1w1zNfUX0mLwqgjmRsAU4mycFebTQxVZIdu9dMMHc2q5prqP1VnxqmJtIh/v7+TixNcgEBJscrjqSZQxtf/l8t90MX375uafx6rJ//uT58e6LfvC+o77Dyzfvhq7vY8cc9tP93em+aDFo13fTNL27uf3ku98jcsQQG+HI/W7DRfoRo01B+e27/em+nPY6z9mN+77P8zyFg3rWtH/2/Ill67umCSSevag5cS+u2SwLiZvnZEO/Yeam2eT8VsvIKFfd9eFwGE/CaLdDc9RxUG9CHm/f6T2B4u9/5w8iqMx+f8Q0WowAsSuimaqN48GDS2RyZ0JRU62FfJdOSGDFSbB6nDIFYoYLF4AITeS+77o2qJ/SZEee6ut5sRk69uxT1iRFeQ5+5OwFxWLjDQ1TTtzQ0EafJYpum/h7H7xnfB1i9+5m/usvXv/1X33x7l0yjdJ226t2nGZqCAHFS8mJkpZSUAgOViEmzYXJTO3+tY06R4nXdLUN15v+cp72/YVMSW9vT1fvBQogJjXliP39CCXPzsRt15zG5IYYXaTpu7Z/xmmvNsFnTDa1QzulKbtLBJx0UkxGLk3srICMWYN79VxxVgLBlrp3SdlICe7EFCSEGGMQIJIjhOBqplaKWq0WiFQxZycTAeVV1rC+SrVsX9PE2lhTvf1spVkumQtV30OwU7XuIOemCY1I5GwleGARRMx54oldjZxaiS0FVY3WQEcUcGaxKC5kEgw2p1Ry0/bGmksySU1gmpxj5z5RZhIK4mMuFOBuYx4tOTnFJrZ9S8Jd00UJbiB4v2ljx4nK/nQ4HW4PaSyeQ4wpp2iIECmAQThU6isFRwtEtNtWtZzmGVOWSWIfyZmcYB6dgpEnzWPBBI/VBhr5Bs/evzArkikiaiJK7fF2OtzNlvQo4wfNd8opN1G2m+GQ92Q+3YzTOIq9uN5ctO02IosbVGHEDraQkqUR5WR2ykFjXVfZuWY+tGKNXOd3QjW6UDc3MMOKs1toolX5H6GOI1gLKTccmmBFS0llLm2MDA4UWo1eZj+5uTIRspdSKHqIxJEuN5u78RZqQdwxSa9PnkeHzHk6jOjb0u887pRb6S+f8BB2L3Zf//z23de3SScJDSvSSR1But6LEaO1AIWZWTEiCAcWJvIQmzRnVXNuQuxc2Ck7jRONcMMFfvAHw5/+h4/f//7u2YebXG6DNCnHNPc//fnbklG0lFzchbkJ0hCslDSVUrLGgCaIqWou850qkKvAILN7QMnw7IC6FhYr7gqzRiQ4l/3JOMIMnho/lv5HyDkBuL9D7OL+7hR7R0tDd+lZ2qGZ92lOiUA5qVCAYx7LaV/SkZE3XkTTfDwd9rbf7XZuaqwWAS1mzgww+XQGTxjq5lqViJgIItVsp+jiXoUzKONubgtAYeCqJGW09MmJk1Upyipy+03UYw0ffvE7azRyzsjtbAdzFpQgCBY/LhBsIQU5AJd6JHbAq1fgGrIQ1WslYTZTq3q8NfgQgji8cgDgXK2NzyASOZ2X/HpEq00eVCcwdywKDlU8/RHodGZSrMIzSyfMUop1LCrKvgRDAJy4di1WjwtiVAZcjWXVnRaSu8MZ5EvetUQ7WAfjoRAoXNFvWnJFhwOKlZX1ODZcc+YV76P1opdgjdZyIvBwWQsYi/MV1T1y/bCvZdNl6V1BA6vHAHlVtqfzLglAteQ6PzMrqrBgaMvzR3VFfwzd/Epk6leyc36bL75t+9UA1u/U5o8EQf6lz+W33f7Ro/rbf/CXMc7HyvHnR+fbMCx79MD9g477a0+Ja0lF9RG064A7ZEH0zJ1JgjTEXrSYk1BwwEnMLYhICCj1nQMzzGCmSwuTsPDq4L6wDGpfNBGRwRkQrrM2jMxIF24UedWTJjZSqBsogLnWAaSStIitqDuRgoxohYNYiMBO1QJIHYZCJFVR2ZxqTx+7r+1FC2BOUAdZLZrUuZ8UAlnmT1vKIy7OLLRKUJj7opFsfu76W+6OuddeDAZD4ACrshKY6oqmNfs9NyMRiMHiDDqvIWwVcqv5qhvYwRDxAKPiufZi1+ms0vKr4P7yQHlF/Yhc6VwjqKLNcIYbnJcOyYW/BmYYLwpi7gSeT4kinbvnKQACY8wpD9ZRDNm0agha0eqVHpsmSsMIz66fBWmnaSyl5DxdXl5u+uFis7no++0wvLe7rESiNsSSc/biBIlx111e9Lv3rp5dtMPQDJo8nVLTt0+32yE0qeRkmuDJnRkswVhA3MRWuOk4MMcJ0/1h/+mXn/30s5/RNk6OUymIklI+zcrHuWQt2YhFzbWYu6m6FiRF6wCTGswQGZ99+vL5iw+v37uSOIxpZGEUA8AcmJW4dU/uDFU4VDHPuYCEshnF2FGAF89F3UHE6oVJJHLRUjRDCgdTzftpP88ldkQm46S5pK5vuN04iTpTzziAlYnNSlqFTiqMEc2Z+aEE97DVG6ZW13MQQe0sJ/kArwDuUpfMBdJAqdmSOVV5yzVscCGJEgBnKmYgAQwkDCOrw+KwQnAmczciAxO7lgIb76fxMHYX0rSdUrq5/aoUON72Q+vsp+N9I13gJqf5dDwArtqV1JJbEGHn7XARuQkc3Pj1u+OUuREuRhLjq7df73bbZ+89+e4nT5//gP/ubxGInbhWiA3O7BIDi6ec3N2WOMRpxXoWiIdQ2aDukMXiXbDEdHXElyoAEZ/rN0ufdZ2W6ZxgPkQveFBb+MYXD5oTC3V+qeEthTLUKiCTuP2qToLHFNp1NiP3tXN6hcz83FwKYMEbH05sCeC8omcPAFttLS7Z0YThsm0HOk73SQ1ogTaninqDO6dSk9/6QBJsURw1K+v+/NHjuLDzl3nX6pAyUMvUJCSEQGpgJ6elRdx96YCsEiREEKHIKrRYmBeLMUZvBPTkg6s55WSJN024bKwvNpXI1G7CVy/fcuSgpLMHEdUCamCuJaWUUpquP3m/2HWZ+z4AgU6n+1a45BQDmka2m11AyMXnZMd5YhFiil1j5AMNTRtVSwjchCbG2A5D3mdNGYXYQ/Bu21+L5a6BO+12GxZrGkrFXEPTitZFyJK7wQVOZFnVzctmGPquRRByWClNaJma2DCRAvbi6QvYdCxEDWfznXBHNh7vus3F0PUNUDB5MWaoC5HnbJ6U1IO7Yo6xIlWVAhexeoSEEFS9pLLMM1Vho3bZQ+GYxhR6d2MvVIzcIOhDaMlby42lMR/9dJdOh1PbN9vmauCmDUSsRHx72OecJcxtlE2n5Thtds3l9dX9IX1+//r+5n5/n27uEEJuB0J0djZWpxJ6Kp4IoEAupHNxJXIXcmIE5pRmdty8fccxXr1/fXG1/fqYfNbAPI9wKs5kDjV32DTN0dkzuUhNTshh7oFi5F5icIylGBTqfjwepzQXhzBpLuWYaGJxZ4gXJ3AwqpHC8sSaQU3NNBeQKDkIUZiFl9lDtWZ3Djc1hxuUiShUZYF1eV7NSM91Ln/QM1hSK6yZjqFSH6qr6EKacxgLcyMSAwmKF7Bvt9t+1x+P7ZhOeUxWjJmocyIgEyvDwRrYOHgQD25EblYK1ClGOsEVsg190wUVaWqxgfQ0a8kISFqylmWqVQCjBO77wUgDAghtEyWSBVHyFHVmLWIgSlpqNZGIgxG7MJgCM3GIUsLsDARQZK5j7JZSUVNL3jK33HahJ6c4TVOaYNBSQofCiBA3btF54vGY0r2P7/J4oz7DmvRX0192fctt6LnNPlGksferi6sGrY/IyWiWQbaZslo2M09CI3iCZPHiDxLQWPqbl5IpKkWJAKKlG4DdVM8cmIo9mhIHcoaSuWk2hYGcAqnqvE+hitE7BWNSVPQ8gKBKDSN78iTtRbAIpmHoiamJcnE9EPG4D9sRH3xwPVyGImPS0rbDv/mTH7/9Yl+an7xLt/qmaCroqHnepNNRgpWTgoiMoEy2WJ4RYFBzH1MxEIc2hNZCSFqADMq4M2zwb/4cf/o//N6P/5vn6E73409ffz2+eO8H5tv9nuZjmEYEhgPEyjzWaJhRhIwimhiYqeSUU7YEHuCgkoFIUXpgrCUWhlZikLuUIvNEBoaG2HHOCZlxSpfXLYmWTKWQT1EzWMY8IZmUWWp2IBTMSIJ0fQflu3enu5sxTQRtAncxSJSULbMj10oKgCCubupLhC+AMkCVLF374+ryXHHMhbKNB2TkgfKNBWJYJDlxJrtW+Y9fiV79QhyxrKlrDvEQDazmEOtSz2DDSmPC+THFiq/UmneNab6pu1VJSHSOZOgRgX+Bixb2/hlAozU+oUVZa2mKWTCbSvlcbSy+CcfVqtwK8zxclMN5DZDcAegSwqxJnFagv3IRFtWYRRnM2f2sFEHL+K5SBGuB0NeVbrVopvN41gsnwYog+fJB9wojLRe4XjXW8vDDXa5zN50JZHXHK4lqpdg6Ho09PVJHpfPfy74hYKw8hfO42UqPWZ6sc2Xb1+IiPWjL45sY1q/ZHnOVfiOJ6tds39pC+LuzPZZnqkP5uw+6/Qtu54H6h3K4/ikHZX54cImY2dYEDBUBxvlJpWUeBlAVowAARuTMAnKvdKSqvgsnN6ukWvbYRBLRUsy0CkoDtkDJ7ASSyiYVr6J+zAyhatHFVGmTcIY51ItDQLSEiDXdYndVJ1cywOtq5MRVL6IKkFde2OKzzqgygsxsqgtu/YhCeb4R8zxXB8BGIgjqbqY1PwdrMzRwd1paF9eywCISYJUtXCNYNYPRqiBEoBij17Z0dioFABMFFq1sYQHYltZ3NQRZofW6elR/mtqkU2dRxXnOdVQimLu7aym1PZ0iBwRkP5EzDOfkds2WF1y+5o8L+WJFVN3PEytxLW/42jOqLk6NNJEDGTTrNB+n02no22dX19dPnpjq8TD+/o9+AMP9/b4J1Alf7XbXu8v3rq6fXF4PbduSzNPIJAFRiC9aNNKGEHeby8vt1ZPttaZy8/r2/t3NaX/4zocfXvWb7a5vYnArTFMT2tA27ovLQBO6i6EbYutEd/Pxb3/+d//lr//y869ettftHEts25ZszGmaRiumSclYAqtinLN5VrOSixtOMxJnEokxppT/7uefnnL69//9v7+8fvLu7jXHkA4qEpum2VJwbOaBXJNYVgIM4zF5SQxumnZo2u1Fvy+jjZmigKiU1LW9UBiP0/54u9uFtmtKKV9/9SaV5NTEps3Zb+8Omzy0l65q5hYbnriSAImJHWuTqy+RpVSa1Tc3X8svZ2yEH9v5+lrJq0v4uW5WKUG2oBCq6s7McHWC1A0AcyYG1fJa9URWmBerhHmrb4cQQO6mgOL25vTm9c0H3ZPNZieNt72XPPdts91uujYG5qzTNI7uNuYZpRCM4FaysMQmDH3f9g2BCnwcpxiaNOX9/vTsyZPXr78OxN/7zvd+74ef/M//y//0v/2v/7G0JzOHLIakLPUtFBEbU67PsLpXG+iFz744OjAAFxeJRLT0Ni8/h5dzIcHPNc+6tp9pU0sUuhKvQGdVqGVf5y/oTM5a8a96wxYUqxbd+DdM9vWw6x4eypdrjPQrP0yL6MZ5+jib65wDYRIANo24suYi9kOzH9+M46ie7/aHEDbuzXLqZqa1WljWdoDlqXqEXi17xSLF9xu2UjV+6ExtBRMCs0TxpbDtICg5CWKM0lAMwQmp5Jc/f4WK0l0g5Ka9Dh7Kd198NHT9y7+5lVasciglUUNt12o7n+b969d6l14/fXFxv7+bD8evDvee79MB/e830jSQvu+vTcPtKd3e7O/nQwZd7XpHYZbdxcX7L54JAIpCoW26NnadXNyV+9OhHPfzfT/mbF2zhVkQBWgYhqJjKSnN2d1Pp9M0JiHKqfRN7JrQdU1rykYKa4fBJeacT6fJ/UhuXdv33Qagu+nm+nr39na+f/v68GY84ZRsSgFtj2cX18+fPyfQaT6dTkc4zF3NNStmd3UDQrbM2cTInJmFOMZo5oEDM9tUIDVRoIWAWE1UVAGIBFU77KdUHJzg0sZhPuDll19+7q/fvp7SCBwBw2kzQm08Nf1F6DYcupBmHctM8/jsWVc8ffHVyw/k6urZ5ZyOn33x1dvb293uQrUc51RSakK33fTslFNqQ1OfznWRJTfnOv1kJVAg0aKW8frzr09p+uHT74s2yPPz959w8zZ5Ql3lzCtLtPJjqnlxCEGtaC6n+zGfCo2c7tVORk4Gs6DJsghFigZHMswOdi2qZTGtAYG5Ujmh6hB3ONhCCMRg5shRwFZ7s7JWoBe6KsiQFVBAwwQWXjkJWNKtlVJBXm2niIjOFg01hmOu44JFs1Lgpkzctm1oowRX0+LqsBBC17XuasiZkSULqJR8mPZ5LJZrVa6ApOpuEgtc1WdzJeO5jFC0MQ6bzsRVjRspuSTNavrdjz8aT8eUi4CZKU9lGueUcwxBgkynaX/YE0EY0oTQRvWirk2IbdvevrlZZsbquWgwdzZHRNPEGHkuc8qJAseGIdR2gdhMiwTMrwySmqaLiARxJ1MdNn3YilzgeHcU0FC6cT/f3d4dbo/zAdgDCcnwbn93/exqu2uiNFvZvfjgxThNh/10//bm3ddvtRQ327bbvuthlsZ5Os3zPJekSLCE4g89PnWBWMKrhS7CzEFYYERCRrJ0SzmVpDWo8uJUTZMoazFEhBDiEC35KU3UOEcJjYDESPMx6wx0mDoMvZrbYTJp7k1L3w+7iyuCjIdJgSANb+Xy6ZPN9XCYjqpJJDrx3372tx1vf/wn//Y//I9/Lsyf/v1PP/vJp5//zVeEkMtoDfq+EWNkwBf3OQOKmuV0cdnlonOe0rxHxtB10skHP3z/3/35f/XhJxvjd21vycfxePOzz39WUvfihewP409+8vPjfcpHeEAIYCEyVqtalSQkTQghBFeMx3mekwsuuqGUMo8J1jRtV/m5BA0MdmYOhKgm82Qk0raXbQha9j5PIHzyyUch+P3daZ7d04moKzkfDnkSMm3mec6qU9aSNRCTYRrHr1+++/znCSMQ0PaELPNYyJg2bNlKKgQOIcCoaMmlsAhcvBjcCEzMWCWIqlX0gs8sBJgV3VgUkR5QBl86N2rn/TcE7345rvvl5bNCI/ULOtv4LKW2hxX4XImz1SXlIUJwQJeufy9GUn/yGH9ZKmEPJ0YPp3fGq/AAO7ljLeyhgmQPg+CPogIi0CLL8Oga/7EZLoFWCfP1uHVk1ptxhhDXAfjGmVRIr2IYD7+9jgKvtlxr0e+MUjnWdpXl+zXeZsYjesr5olaIiVaw6zw05sR4RG1ZkbxHCfv6kQXPejyYtcGI6Ey3qnuu8tFYs1QnWrn9D8jUPw9K8/8DAKtuD7nTv27fvj1GT/75j3vOm375F6qQMABdPU3d3c2IFyC5+h+q+jwvKR4RYSHurGR2YmYubmbrhLjOHgsmQyhe6oRm1QQDBKrdd7CqglfHpjaHMzmx1XRtlc3SRbHDQVAzQ8Z6tr9wySt4xUKSPJ2FpM7zXR0JM7O8MFyIVOoAACAASURBVKeK60LHNTsn/Aux11dFQ5yLCERnaRxaApfaF4M1EVWURV8xMJOgko1rPQKLCxeYQFYhqhW+cgLKYi9iBF3B+hX2X1S7yZ3q6lSbt4UDMXHglOHuVLVq1E2cXbwWZLiOwLkTfa0JWXUqROhaEeYgIFczdQObsAUOIQQvOs4zQ0tObdNcXlx0TdM3Ddw15SfXOyLebvsm0NA0fdNeb7ZPL6+fXF4Fp3kcy1wa4SbEph12w2U2I0LX9kNoO2re7e/fvnlz9/ZdyeV6e3G/30cPIYZkWuYkoEZCycVSMQY3IcamjZ0BxU8/+eJnP3v5cwuYrRh5t+3HuylEWfov3OEMo9rZnlXVzN0pwIlTsawmTSwsb+8P99Pf/N73/2C4ej+pOUkxDzH2/bZp4zTHoSW30LStwdqmiYGKEbGL8GbbPbm+tNmO00ys7GxeSIyDYCQQ2j62bVTYeMoQSqkQNUGaNNFmICIax9PxeARh6V8Fg2GuSznU19rOiqect5XN8wsw1vkxf3jt/VHkvURbVeVmkWZzg8FJa++hwXSZEyrcUxtYaw8vbBWLVKfq/wmBg4mMMI727s3dsxe7fttllc32aUontzLNE++pjR0M5CwchKHkRmqwKWeyqWljbGLTBHKUkp88eXa/n97Nb6dpcqCYvXr36uefffZHf/j0v/13f4Tn/7FXGu+Py3svAsC93mui6uLpAJ0FyNcYgRfg5hxj+UMN1JVoFbX/pdjmF6aa+o6fd+wAQVXpIcxbUbFHFoHV/aZy86vCagXiyf3bjrXewV99Gr/2M/QIfKu1dl8Vv9bYmsnJLy923RBCIAfMbH843N+dnl6jaVsAORufJfzWWWnd7RJ7PT6pcyz261e8SsdawzpjJjBCEAQiRkF13jU3gweJIQRywpzmMhYAEgSBjLSk1FGz2Vyc8pSTxotwupuImXpJPrcxtttYAmW2omOj4d2rd19/+TqPJ/Jp24XLC/rgg4/77mIe/f4upem0vxtfv75RLs0guyFIlBiboY9X1xfj4RhCIJcgnUjn3tTif8502E/HvQWJOds0JmLOWadpPo53p/EWAMhKKW2MyYpnyjlPJRciCjxbzmRI0/50mE57prnrTteXKIY563iadlcvnjwZb4/7cpxBLIZI6Druh36z2yXPb94ebu5vU0JKRQ1QY1RxIysZphnIIARBE9olGnEvpZRSAJDU0gwTBFjkzsy16YeipAXz5E5GTOQtm59udRy13CPEyC0XNajdvJ3v7udug90ltZv43scf2eH2eNrnovOEz7/8gmLpLvrjOB32cy5xd3kVo9zdHY+nYwhh6IbpOB0PRwtWC82+llXAcENWFSJ3MjVyxBjdcPz67vXnr3mr6Hjg/ul298b3RF5YhUk4xhBa6lhE1RrpqGX1Uiwf9jN0lhE6AgnBhQTN0JgrFZCwKOA5UIjSaFF391yJ7F51o4yMgsNrQZdKKbykG6buJSctVv2U2UG2BIJ1Kq0TMjGR8YJyPMwlD2t0/fuRvZWvQccSUhpbkLBEPYEq/7RocUIpecoTSVGHMLVDNxl01pKLFQjJZhjmtzMYZpodRmB3IlNxA5SzCiCIQyTBnOZESTioF4Nuh+3du7uixX1RWMxJzbWJsc4HIkKgeUrkztPMbXCCM6SJygUGEYEh5+JJLbuZuiJGIRBFEAuwtGs1XYhdjK2Elvt2eHV724W+b4cOQ9Q2eNSSN5tOBgoXeDUdI8VGYkrleHecb9GwxE0spPM+B43pttwd700sDuHio12M7YRCGfk057mQo1hOyqqaT+M4ziUBBVBgxiJDWbN6JiMscxhqLEtwMiNyYorED13hOefK3KqEfXNbdFQLNHrXBMmh5AJFNGYmkDjIcsbsALxBCI2ZeZ4Od0eAG6Z0VM3pzavbnIuE0G377qL98svXp7TvN03f9+/u7n70/R/nye6mt68/feklEcqL71+8+M725vXN29fvfv6T43hKKI/ChUdxw50fF8L+Fk9etD/6tz949nzXdD7R60+//PTDjy/6y34/3rx88+nXr+4++ejZ7vLy5U/Hv//JTx0BpRp8hFptVStrpMKIWgfH1EwdjK7rTodxGid3a6RtqA1gIiUo3NngzmwSIG7smWyO0Bk4gfGDH32Pox3GfTFkxWYzzHpyTLkUK2SmqjaOJc8Iwp10bsEWM3KwIVIbu2bTU9cN4+Fo2UvWyCyBAVZVmAvBgVIRAQYtbW1nPjYAVBfRhyWPFgLR+ls1VlOnCoDTIryz8ip/YWX8tmXdV3aPfzsfotbWbREqp3V35O5UAfFzqYKk3vIzM2wFQyr7xyv34BuyTOvktJ4GzpPV+fmpAeT5SrCGUgBYhIlU9Vde3W+zrVjMw9dLO+BSVlwo4r84MER4NKQPQcu3xFRV1/2hzohfarLzhSlLBHvw91rsyBZAbaE8VKMHx/lG1yfCtN6fStQ909Xpm+dpqguAdV4LwNUA4jFVajURXrGyR2HZ+czrR35L0PBX/tpviWD8rgNYjwduSYP/lYH1Ldvj5/6fc4gW/Ge5O7WA//iuoSp4VyEzciuqqurV0MrdVc2qIYOpuhpJIPK15k8gERGuon8LOL1q8LgDZDVN5KqtmXKViV2CLwLcSagGylZngVUvpZ4TCPxoQq3ueVjme6sUifVSqwQp1dLXUhqtBuy6wujEqGyyqqlY3BbBQYDgxay2gK+cUhKyYjWkrNLWZ5JmNRQTdyP40gDgWnuSuAgETLMmCVIVvWiJUpdpvH5BtbuvYneVsFbvylJfWR4YkBEIvvb9reHFIoexrgxncGMFLM3r6ak7VwK0L6zlpaF0fT6WMTVzr0brbuRO5oCTmRmrFk1jOsyHcTzOl+3lbthutm54/dWrNE1XV7s2hNu7d9the7EdhvjB9Wabx/mi32xi20uEAtJS423TXW+vLvqLzWZjQCoZQIzMxfM45+ME9xijhGBquRQnyjlpVgijGFm1xTsbNbkBX9+8+vTV52+PN8OTTWYtrk6YcgJTGzpBRJrUfGnRdzJdzG6JfdhspmlUcDKfFFrMCr54+Xr3XgcKplBz4TD0fSly2E+uaGPXt2KkzNq10YM0TYR7O7RPnlzV+jNqoV/hpCREne927bBpnCznrO6RQykeI7fNQC4x9jE2x+Pp7vauZIWv4vrMFT41wqP7+oumeDirB3zz3aezzfFaoFsKNXTOgBxYWuyAKsTgRjU891zKui4iBvEsS82LyNxqzy6BPLubMxNXLSVmgmn2t2/u9vdPQ+t3x0M37FhkyvN4e3fPh6EbGolt07SxBQwMc08lq6upHsaTtKHzLggx0e7y6v7wqpjDcTyerq6enI7Hz15+/uF3Pvz4u7//Z3/2w68+23/2k1fp5MQCZncUBy0KDA9DxLy8bM4gsC2mCfDFbdBXzah1e/zpM0/7UeR0RmzOlcmHKqaeVTnXPVXhKVqIsMsXFbEnYGlBAEyr/jK+ZVuquY/AtvU43/YRXu59ZdkvFE9fQPOzq4ObDPzhh+9tLlsnc3IOMs15PBYibmMHoOoKrsfyBdmrBApb57bzyDjVZvPlz7euel7lv5Z0HjDywEKBwIs8CAgk5rBFXNVJzaxYTokFRJXmAGRo1hia05im4357fXH3xSF0gSHzNFlAUi2UucfV9eb9j57/9Gd/+/Zdfn+7e/7s2fWuD3567+lHhO71q8MXX9zkWefJ372dp3KSxoLE6+v+yVXTtm1swswegphKLg5Q6UQ1wBth0yJpttALk7gXBjexLWU2czPvuvZUwE3Xdl3T96b5bn+yY/n63TswpjJvn14Z+d3h/rC/Ec5Dn8zD/ek6NpxL6dpyfb39mD54Vq7RknLm+XCBfHl1GZs4p/Tll199+fXLoihaH1MmYglsnkMXT2mGITYsQYQFRG3bBKZ5mrNl1F+HkMuyjAqMvCDBmCm2zSARc+bj/v613k3vfP8GAKoXG4xZCYHqypOBo/v9MX3y42HS05zicRr3JxzH+ebuOLy5nbIVh4Nycnfu2j6n7AZy0oLxmAqMCbXIA3LmRbLWCUGYCHNSNzQxUhvKqG8+e90+C++1m3IoFGnYbuZcMmZFZufIsZGWPWTPjNj3LcjG8VhQSladgATMMDcOxC17RilmlOGEDC9uZl6cSrWOYSLy7A6FmDsxWEiIkHIyAlSdFICWvEQgS2GOmIWYYShuWY2JzFE1km2ZtsnJzms7PUqy/DzjEFaIvb6UBjgLRIjYVXNKqSSFLK/ZNE+mOXa9zZpLMbUmxs3QbdrN5cXVuy/f1dXCoWUh4SywSxENDccuhD6knMZ8yiiRg7JJ4Ebk9c3tph/apnX3knOU2MYu53zcH+fjLCwAQpQqcw4ihbmppjybMVggrq6z2mxLB6Ihm4ZYhq6PIi5OERlV0DzFrh92QxuHVz+5nVM+lFOyUk5lThNgCUzqHcLF5a6/ajYXG7s/uQIFsQ997KecZsue/ZSmrIXEh6G/+/L+mE53t7fTcVJVKNyRkYOyO5BJVNzVHLWTEY4FTOQlTSWCVV1WiBspYOoEMBOznPNAs+znUO1BnYbhRsSUmQsLQpAQTCQLkToJORvPtWTJIUamtpnJ4zylm3k/3uc8ldvbgxok4KLglNL+8JYavN8+K2q393dff/5WInNDGpLRNAyxbzwavfjuRyV9+L2P30x71RHjMblWF8ooEpzIrVw+6ZlqE36JrV29120vqR3I2U/TfDsffD+AS2i4HyCBYwgwfntz79MWTOwtlcpBK+So+EkpVrJxX0KMDGY3piIQV+TZyOccVJPzou1prlYrXlaIOJhTPpkWWIoQAesn3//Awn4u+34AJTRd47k1uFtwiJM7SB2pIJdklCwTEdesITQ8tINwdLWAoHlx966xVhXmpSosV5uv60u6BAPnJX8tCNnKyznjnL6S9M7vcA2xltLMsg4/FlJ6eNV/GUBwX5CUxxjWL/8WQXnBVd2XNKrmZ7Y4c6wkcrK1XaZmOov0pFFVYvfVpvxb0bQlFvclW6nC5FghmiU3O6N6REwswguA9Wsil2/fKuXt/FrV4y/U8ocq5JoePYRK9Nsfb8m31qtbNjXnc/S8CJEuUNE5s/YV7KMVPvTarb7EbM70cFbnuaDqKS63lZdvruhK9Zdce27qpTg9qmOvgNovXdo3b9o/J/jwuw5gPWCB/4pb/abt8Uvw/7L3Zr2WJMmZ2Gdm7hFxtrvkzcyqyqylu8keksMNFEbQggEGEDCPAvRL9CP0U6Q3PehNgCQIGEEvAz6MII2mOT1Usdns6qrK7W5niwh3N7N58Ihzb3ZlF5uSSIqAHLmce+45sbu52Weffea/Oif+3xuPw9T64BoqWYnmSeeAEFfcn2iiEDAzE1V1rEmBi0VVvXaHmdu9g2wifxJZTTg2LCE4wWGTiA6Lk9UYzRlSNc2JSPg4Du/pE9e4aUIViObcVVWL4Ul6nLgmGNWMfZJbpu/UfM/fkljLnuauAqbFrboj9TOzHnut71erq0ftZqozBWwyHcSgkgtX7RVmJg4UzN20VKS8lnih8nsqUc1VqbZxJGdzJpDAfRJOrmsW1QKx6Zhpsnc0HwTm3q2YvljBOwM5T5WMAM1NYQjuZJO2u1ltIlkFnKcSQodXGjHP4FiNkOs6VRuN1IMDVc1KqD9aWmEMVy8p3d/c7Q/aCM6Wi8Cc+vH25u1+u8tjEpabm7tnz5798LMfXKzPNrG9e3vbhaZxikYiYb1Z5TYHiefLi4vVxcXFmRON41BKFuFXr75F0q5phYiIYtvEtumWSyYuaoEDMUMRIBIksgiJqSdVCP+rf/O/34/7EmywpLBidjgeD/2RDF1gclb1PBYJas5arBQ3cwjAHtpWNCuzFu2LsdNySd+8+2bzTXhytT7cl1yMQUFiSn7z7m7M1rarZhFAdOz3BHSLKIRx7EFYnS0v09n+uD8eB3dDC+PsZO3CLq82ceH7fq+WzItwl8YirJt2AecY2hDadMy7/TbnQkY1pRNExEVJeV7oQOQP/LnTTDpJaYKZJ0aRz9DVbBYevKTa052AKRFMqDgZT/WFzEyAZU1ZK7odYleK1qxUzSaR1V6FqJlbATNxRRY4BrV8e58O2ySt397fLTfSNOSGw2GvJaXV2XqxEubAwsxNaEQ4a3Z2CqTQMWcnijE0HG9u7776+lvNZblcXt9tnz5/fnP9ps/bX3z784snT/6zf/6f/um//Ne7+/2bbw4UiJmnDjNWRUl4DvbAVVfIXDGTzKvukp/0Qh9x7YFT09Up/4hHadKHGTtBzbNK+YPD8BhgmsW3gMf/T1/x07+P+eAfNPDTh+dax4fEak3xfchB8YktVZsmTqQBIpv3QrPPas0qvPjso/XFYn+42+3vHSiaAFJVVQWDpF612fjSbHyJiKdL9+BKV0+f6decyulj1aEmYPbgq4WeCKhOQhKYm1CsGHlKI9QkcOCmXXScyjAMwcOiXaK1QFPzPpYSutg+6Tizj47iGTk7wNiscPZk+ez55V/+1ZdPzsInHz+7Oj/zPA7b4hrTwG9e76+v+0Y6og6UDvvdcTgGeRv4+ctPm7ZpyPx4PAKcE6cxRUHXXpXCpizcmPIwaBvdjc1qI7yu0VEkxBBWZ2fX397GVjyIC+ds+6Efhn5IQ3E95v7zrkGkY0q7cQzISfcxYnt4vtl0oQnF+vPL9eJskVDiMjp7Ot5K3y9jV6UJ3767fXvztm3R5hgCUkJgbroACtLKaGPgsFotWHjss6p2XYwxOnzIgynIbCrBFSImIzth3rWjYggMlcMe5XA/vAVGLFerI0ZPwSFlGCHgRgDYaGNBIoxDcte2bY59zorN5tIR3l3fD6OakUiz3x/TmN15HJJlZ2fPSoZxLIvQusKltp2Aw5m44ShM7spORV1HJecQmnQ9JB1/9PmL83Z1ZPG2mA1kKadSzEpSFXe33JfAedWuQhut6EDHkhUjMAAjzNyix00zairZiis7o1DJpaRSc0g0NyVgIiDYrCj5UDJrMDODETMRg921zj4S4hACB8lZkU2LGdHcj4zmtl418pxeVNm42ZK715Cysie4puUIRNmKROJAxK5eiuqUcROEiEXXlhyIaRxyytYuwmq5WrSLyI3D0YGUnByTCLXXOAsEhS/WcXNxBsFhOCRPHLgkdTaoH3dHgTAJgVWLqgdyZoYh9SmlNE3/QMIEBkeGTEKKVJwcbKRZrTfoQ7jFQBvicrGi4IWUopMNfc4GdTc1TTldPX82bvP+uLfetM/168Ph6Blt8M8//ZQXKEjFcoztGMeiOtiQiyKimJJTFbTQrPu7493+9nZ3jwwJCARTIBvHWsfGEjkhJ811Ga4CQg6qOyWppk4AN2I3N3O4Vj0vn4v63d1Kdedq+rCaPGZnV4KTDYZCITQdtQyysZg5B2ljK03IZ2mwNBxyaNgUWrhkSnk4bMfcuxc0TWCL48GK+rBHs0beO2nJPf3ky3/TKz55cv75D59fPd/kfNj2b9chXj5pV4u1LMfxWMZDOeyILDTtogkdU1SznIbzs2bRxdiyIqV0GPLNEYVDXG7a5pJzKSr71WoZlmsXd3EJFAIXw3gYYY1ZKGBmJabKaDJTFDMDGlBgAsjIEvJQNBcoXL2MyUZ38TqTrLhbIWcvBI6qcDUJDMTQcIF+/PLi9c0Wkp4+e540p1SMnCUQN24CErVSCsxh2Us+VqGns1VAI21crLp1yXYcj6U/eHFyih5hKFk9F1NnZsvm6gRiYXaeE2R18cVMMqqrcJXpnQIb5rlF8US2qrXAlcA+L+vuD+JWj1ZH8veyWU4VZp6kBE4Y1nfXVa9fnWtmqmdSow1MtNaqHAGSCmYZeMJSnap4eyU4yAn2OSXqKjSEh5OazhhmYAfN2k6zvnndgM1ODklVW51TePThU/ieMZOVHn70udoCmKq0T7n8B+IGAYCdJMlOug8fuHows8eMJ0xxp9MsLEo4aczWLN0EYE7foPl24aRvRjOCRzSrplplYE14gAM1OrOatmOfH5rTidRvOXgKKmdfcca2aH4mMWUXTyr9v3rRfpPx3c//5nfq/+sAFt53vv//cRofiiLeQ6++/+tED3P7bwYOzoCO86PMv80vaE6fP0RKU0UJ1d6o8ywiYhGxrF4UDI4SQ+BAIPSHXqd6NxBxCCG00dzz3C2R2M1JhIgBFuYqw17J9QBOjVdxOpgatzycZUW2ndzBNHU8rZ1irRrRE6bfkNs8q5lBFIKEEDBzKYuWORnizlVMvuY+JuIyJhSKJlaLP7p3tayqatsLg8HELExqbjwRGeoEN3dm91psCTObagVjoMA1WvRCdXtWzXi95JiTHhO3lU5w09S1wx+sK4HYeL5NPuWlp01NBeuVPjphlycFrJoPqR1z3FGlF07yfuRw8ypNRh6kw4NYjhAzCZrobQxRpBQdExpp0ziOQ6tFx7En8Bv3w353GPqShmdnFxdt13GwcXSluDoTcBfb5eJsbMaSlREEMXB0IKuIahRJh6GVNm7imIakqe26xXLZdgs35zEFiSEGAEEkxhjr+dIkff9//Lt/TZ1wK/txH9rGCLfb7XGwQGhDcePU59TnJjbG7kVLVjXAnQLGkrO5MNysqDctn51dHcf++t3dR588SankouwkTFr0zfV9GXFxXlsJ5vvtNjRo41KL7fa7UtJyc35xubm5bbfDgAIQEtRcQ4PlWad+3B3uSimqKG4pGVNZra0UZWYRYbaUk2YnMIGK5iiCWmpGles3rZy/LhtW1xuuyr7mNEszzNZnmn916SabXkzJpiqIxrW7WnDyUoqaBUZoQxsbG0au1HeCu8CZbNKpg1fMmcxABqEo4ikVTUhDPu7347hZLtcsdDzEqpSnZsMwENA0DQsb+TD0bdtKEzgGYzi5MziEL3/2l1/+xc9fPPtic9HeXb998fLjPh1z6l9df/P85qPf/5Pf/vO//DIuHQJuSIiKmhnc5lwYCHDmIMJVSldnepTO7hfeQ9ZnA6Cl+gB+Yp7XD8/88DkbSw+2d35BzLN5m+EtenAg7JRYq3y6OZlIRERhhuf/mvHINpwwrF+3WPB0Ik7MU0MHIvYqbzoN60s6f7JslvLLN29fX3+T8jErQqCcMtkAQogM5apCOC0hXk8UU1q4HszDQc15k9NxvndUp5+q7/b4l36SaROWpmvaRTekcbQ+pwSAFk27atquO786f/X12+JpuVqUphyG4/XrG+6Cq749vNtcrqng5vYaIxDRXmB1wZur1eqsgdiPPvuxePzk+Sc2pL/66tub16//6HeyXcWxd9PYLM5jWOyiBtmn8Xh/tx8+uhJuojSEcnd358Y58XFvTaSztaZEOTmcc7H9/sDUufFud2ybmFJKKQ/HcczJ3Q9D35KszBbCFCJFIQ1eeEzjYdiaAMwQBpMyZcNxRJ/UQYtFe9jv29WigZRU3ElNS9Fl1waEYrZo4pg0Zaw2XUIj2wQbDMRNGyWOOqqiEeq6DsD2bp8GZaIYgwSJMRYqVtxLUbirwclV3RTFFovu/m7Y3R+loaKDFsRmWahIKAERwwHcSttyExyqJZkWMKgBGtzc3CqPsQllDxCunr2kkFmwO+xE2hjo3f1+t7UmtuN+1GLsFIijRPUcm6q7b4VdTVWdYE5StDBXDa+SU3H1l198+vXbn+GIy9Xl8/OLt0fTMB45u9LYYwg5HZLEkZSPxyOBFstls4hFWlH2BKST+hQHDqvFytwIPZuws6mbKswZTMaqqPqfQgKCuVqV2SICewwxa660VgFEghOSpeozCLMECSGaEqy4lUosZ5KJp+2THpZD4JMIAU15h7k4ZUr1GU4kLIZnR8MSmYU0gwXOIIYVFEUTYxMbA9hFGtlsztarlWe7v7t/tXvVLZpxzA8QkjtskmlGQrNoVuerY38ch5EDhS4Y3IqXpGXfx2UofSlHzSmVXJiZebSixBxXEWopZWJXd3IED3C4upkWd4WH4J4dGTBwywSYGRPH0HZt56xuSS0zqGuX7TKGyIf98ebuzR//9p+8+/r2zeucxwMIWAABxRyMI+Pik7NDOuz63WEcKTgixrGkscDQbpq0TSKisJqZc0aQEBxFJ0k9y8hWqCXh2uu69nQrmlzoQeJnWggMc7chZvfsClMYOZOpYSpmUFOF2ZwvkZmTQlAiQIsVNjPvmFtu4TSMpWRru9CGVpg/+fyTr998PQ4pFeTeLUrkhXRyuN/7oCTM1LBz3hfGovE2ljDc5vGQNBmUF2xp7F+9+na756tnq4snXcPqXT9w8cUQW/JWrXNh6domhlgK9vu+tz0VPY4IBpICjNb01PjIdNwPy1W3Odsw++jHYRybLq4Xq+WyJTvcJMSSoW1RJgXYm4h2GcFQJaVigKARj+7qBUgoY9GsXOk6RuwcXIi9mLopOTFInUpWV2Lhtu0MdCDFDmfrxfXepPWLJ+cQ2h2upc0LCSyhSobWLH7bRQvBqI203JzHLko5Qgc3RR5KrUlnRfRgxKWoFrVstZq9aHZV5iDEqA7GhMjQnMb5wNI7v18xaLNpJX6UffcZo3iQ0nx/kXy0gj6ktt7HsL5/+Ok4DKCZRWjwyg0zn1jZXqERpvc1qmqQ9F7e9BQk2Zya80mMArXbDxhEpLOmyuPEVqXVcWV8PTgtJ97Sdw+eHv9wumy/ckWs0semE1R69Ol5CzNoNMeefuKGf+DemZmrM7//i6nY83S9TvDRfCyP7+x06+bip5rxoJkPUpkZD+o3PofqNleVw2dCSc0o12euJjTmBOJ8efyRTgSmq15luZweR9e/0fgenOs3RyTkr//I39P4HhRmvjWPptyJv/O91+X/4aDvDBGJMYrIqW/U38beT+f7K7s+6R//yrHVSLWOtm1DCHULjxEuAGZWSlHVx9f5dPzu3jTNDAs9RC8SuVu0sQmlFBiYSYKEGNqunyNfngAAIABJREFUjU1kqSCLn/A0Ipi5YxJBL2buzswsAqLYxNg1EgQEg4IgItkyiRAA9qaLzFxUmdlguSSzEpooIlPznVnPIec0pt4HQFAV1sFVxXzqEM3MUvvTG2onxC40TFJ5lwDHEJlDCDFIlBBDjMwMsibG0AaOQkwsAKCqRYubi0jbNE3TNk3HJK5uWS2bFjVzoRBCFA6m5lmRQMxN07RtR0xmRqAgbIOD4e5arORCDiauTkm1IJo1p1IREUht3eoOK6ZoYV5U1VwnJjFXhv+czmADXGrfa4fDQC7EwqTZm8AxBK6sqGymVrKhOEr19twnASzwvJqaw9SbrqkYvzBLFAkEoqIFVLWtuYqJWHEtXlN8EgSAlSyx7bqOhbWouXtRT/1iEbplHMZ+0cjTq/bsfHV1dblaLH7vd363Cd1nL7/4/PMfLJbLV998+/Ty7AeffrFpl/320Ch+8PKLi/V56tOYs4R4c7flEK8urs7Wm+39Pg9p1bbPrq7Wq+Xt9c3Q9+2i/fyLzz958SmYt9vdt9++GsYhW/7o+VM31ZzHvhdCTuN2tx3HYUjD3bj9r/+H/2Z5eba+XFuw5CVbcUZKydQFkg+FKQSKKeVcFMShPjPC7uiHvmrhqpm03HSNqy7apuvCet0dD/em3rXd0Oe/+PIXu526YbcfSsmhiWTl6dXTJjSBwouPPzkO/Vdf/dWrt69Z5MWnzz95+eTqozMRv7hYff7FR7FF8d49qdn24C9ePNve9Rfr51fPz0Xw+tXXTy6v0lG//eW3RJIPCqXIkSchlVquBxATM8r0+L33Z1r8ZlBEbWrlSyw1YgoxxjYNyavb4ZMjRbXGtbLIKw7FkouWXAgIEiQEVeuPgxdyUy0l56wl1xwX1GuBBquRwhVaihKkYYWerRfri0js3bo59MdhHHIuDvv9P/zjwLLo2jENYx6aruvHVFS7bhm7rmlaCuGrX3z7b3/6Z7vj0K0u37ze/eTPf3443B3740effCyC5bpbrrqvvvn5ixcvrp4/CWHxk69+Tlk5SCMNMppVy6EhIpaGQuRa5lvTb5XAgBPwxDCHORRQw6wfN2WwZo+EQEx8AosxcShPuTcAj15UIzfzLKtJn9KCPnmkRCQhhBBYZutXgW0rFb6vi+djvL9q+9HpMKYtq+kE2IPeW3DN3RTkwY1iDOv1er+9XbTL2LVp6EVotdkwIw89FP/8v/gnn35xBc6QvN4sOZBEuTi/fPHii7PN5b/4H/9UAplWKpcRMSa1Ba8yN3U9mkqm51Wv1LBtSkDCDapmRWtkLswkVFyhDnViClUdwy2rmZmaadGUU8pZ3dSqEhZUte+H8ZDSMZOSqW+3+8N+V7QorO0Wi8UyhtiEpu3ks89e/NYfff7Zb189e3l+9fH55bNNs5CU0u/84A9//8e/v3t9/O/++//59f+1XzWLf/If/MGiW/70z/4tjHIyLfzq29uvf/nL80379Oml6XBxfibs19fvDoejcHO/6/eHzKFpm01/GPfbw83N/bffvIKF7fbQ92OQ6MDxuDXLy2W7WnUKGylePn26Wi1zSvfbu/vd1tw252ebi7Pnn7zsNqu4aBW6OxyO/a0TLs67s3WMkd0LxMfxkDQjkDFI6KxdULa37968e3vTLc+++ubtX3198+pdubkfmeLlk+eLdtE18ZNPnr+7fXd+vrl6+mSxXKSUDv3eAZCWkokRGwG8qDmYg4DNLAPaLOLivBPg7u7u2A8vP3n54x//btd016+2+7s+eOiPI6Ntu5WNmobUNJHBmsa2iaEJZadnn0YSSsNwdtZdPYmb87OXn768eW3/y7/8szwOb171rGF3n9M+2+iYCDohcGBwRDMcxn436FAYEqUhiJXCwmzuqnAhCJy291uoYoHY4jjsdsP96uOzb759ff1237pExEiL0qfh0COZwj/+6LmWfH93L85n7aKVhjIjk2cvQxl0hHpgcfXUp3TIVCBgy15K0VzIiCEwmFbvaWY2qMWWCe7mUFh2zQqnRqJAyMmLa9aUshsFbpiD1NygUc6KIbnCs0EdNZ70CuaaV1eICAQR5igSmANJYAgTuzdu7moKgkxZPFSB9tigaRZN04YQiJhBeSi5zyWbZc0l94f05Mnl+dU5R1YvoZXQynK1eP7Zs7AJh343pDGXZGQGK4NaMgLa2Cy6Lg+ajqUcko0TlZWJCSzEMC9ZL87Pzzdnm+Vm2S3KWMZhFOIgIZfy2fMXAdHVTNUVVIiJmxi6xWKx7GITVfVw2O8OB3dfLBchNCnl3f0x39ur+1chxmefXL384YurLy7f7a+bdbz4dHXx2er8WXs33I3aJx2tCiOSQQwRCFAoNdDkCNg8XV88PX9z+2Z7u7cqAqVwgwgxKHBgkihNkKlNpyaTSnoTqmp9tSKKiE29qFNVzqk0e4cV1Vy0qM9O49xdtQIWXCX9rFgbI9U2ws5W/LA79MehjDbeDn3frzebnd3v0z5yc7F58vTp036fx8PYNssmdPmY7KAQWHbtPe+VjDzpsD/u7tK4tUDSxY7gx0PfH0e1vZaD+pjK8TDub/c37+7f7IZtr0PhRB0VSYdxe7N7e71/9e27m7vj3W6868sW7WFxjrjS4n0yy5YU++1++4tfbkMMn332suuW3WJxdnn2+dPnf/GT18f7I4q0cfXk/GKzXO53t/ubVJJ6caFAoDSk/tDnMRO4349e3A1WkIbxvL1MfT4cDjq4JlipKGKITWf9nldtjFSs/0e/e/Ff/lf/+dvdT6/vXqeUgeZwHEz6ftwNYyqF1ZhJmsWiWDMM2sXlN7+8RWm8yPWr2/6Qxr3u7w/Dbqgcq+P+qMlKKpqLJfPillRTgYEhXsiKqil8YtFNDoC7mwUWmhK/M2PS4EZegUvIhEfb5CoIi3AQDhLETu0zTjnk2omjBmnmruplzh6d/gBwn3bo/gBVEIEZzJhK2ACvW5u0QwSTGm4Ic0DiMDN1nbs6TWov7rBKz5rjUOZamS5pSOZeF+UH4Ebdi3sxwuRraU2EzDKuk6uqM2mCwMwhhBqtn+LcKWR+iJ4ry7G+OUfNj2HEqnlT7FSVOTlpREJUg9KJVjwfQ/2XiKYAynSitxMHFmGeT3biVYUQ6g9e7bNWEKBunE/cuPf9QJqVG6YbVHVOGVSbegkxgYQlxtg0jQSZ2PTV25m9R3sEIFaYzNXt0fggb8bM2rbleZzAmb+We+S/fvy6r/zK+AfAwPqe8fgy/b2Meq1pbjn3d7zr78EpT3n4X/dMPH7ITh8+/TthTJXy82hHNaIydyKEGE6C4iDSqvRGxMJE8Ae1uUf93302LlPrUwJmXAUTUaEK8dSOOQSA2cjNTLU4prIjIjis6vgY+wzPqZkjgGSauDYpOJC5Vjo1U3BSJxMnRhWRcVOtmDO7l3mWEpEEIYIEqeTMIGxGXq0PVSWfqv2rRKaTeoXWmHRKdVbbB9A88d1MizKxG1WmFjmDlEEAmc8IgU2M8Ck2nVkWrpPNr6tPjXcdXKUk6iJH9e3a3t5n7S0COxsAMxCZU+0fZw7UJo9FoXBjRvCZLQNz0FSZ5A9/4a5u7FNVGMFrGaPRvJJVctsJw2DGQzoIpDoOg6maqnIMFFmdnTTl0V2l4Ribpmk364uPPnq63px9/vmPKmi3Xl78wT/+vSeb9dli0QgV8qFoOhw7btarhYewOluFzXK1OrvcPO1Ck7W0wl3bMigN6ericrVexa6VJm4Pu3f3t2VULyW2zTqyutclkOAOZRGOYozBcp/z2dm5s41pTHl0Uo4cNcYYLCevGhNGRc2diLmWbU64BZFLXS8dgBVN5k1s3V1IlovFdSlwyzkfDv3xkMeMQAAhxHh+fnHc+7LbMJOadV23OjtbrVd3d/f327v9/nZzdnZ59eTi6mw8HpjhnmMbVu1Zymko25QGkKrnXJK7hiAT1byGHbV7ZjGmmUv5eHxHIonwQMnmua3JdIdnA2iqUGXmSmiu7GgCJuKBu9fHo2rKVgqAk1W3qfYjs8oZRC2Jc7dawgJ3o6mshhzMcXLiaRJ8iYuFFo9tEyPDqe+LatX2oKZtwRTbDiIELNcriQFGBhizchjVI1MVwMrZzPV+d8h530SPkfo0/NmXP4lhefmy++M/+Oyn/9vX5iM3woJh6F3BHqd5AUZtrowZQ/JHchWn1/bgkBKRz11Q54QnZhBquka/ciNOQ06M9dm2nxpsY9phJZROmvfvpRlP4Bqm2/JrsqwPybbTx7/7IWaCTovIMIyhXRQrPhaJQcmO+x0FSNvoNv3oH33erTGm45B7Ftucb0JslsuVqdVYPQiVguJGk0oXVSbXrAE4t9+eDSHolBKkOTs5n99JLbaqHtYmAlMNxSTCQZHg7kKRQ5SGmApRRnGQkwcK7DIeCymqbiOkVklbb31ZGdxyHByavT+USFFjRw1JyUwGMn791atf/OTrVz9/04xIin/2T/+jT5592kQsm/U49k5Usppq1/LZ5mKz3oCO2/tDbIwFRM2765v7+6FpzplZAjiyegb0yZOL3VaRtes6wEtJGN2BrGo6DJqKx6ypmDicGKGJbtqnoQwlo9AhKul2v++HbWQsljE2IeVyOB4Y49WT81yK+0AGV0+jHlVDP6hRaBpzd/JKdu6WTNYEgpv5WG7v3rx88XFWJaeSspstugVagJBLGYYRBDN1AomBEwHMMEcqKR3T2fmibYM6Dcfh5u3N/c1u7MeGGyiRkYikYWBnEbZixAbmUjQkgmARl00n/cB5TP14fHL58ThgHPPFEiF0VAYt1oYokb24qmm2IY8wePako5tXcwJFlQRgcj5lut1rVgkEY0HR4Zj6IyTy/d2W4MuGh0GPfW9HUJEgsaRiKaUhERvca5iqA1lRMmIw2EnhZOYCRWWE8dxpwIqRwafaHp+UV6rSjRFArAwT2ERZICfWKUCa+0nUmTlB2fWmAS4OtUrpwWP0apovj6IiY6Iq0jMbBiOEwE4IIUgUAI4CcgQQkQir2tCPqrWissCpNDFEczNyIvZxHFQLB7p8/kRzOfSHQuUwHNS06TpmNlfXqWycCFRgbiUb5yCmphOHQkgCRTD5JDDMKJLV1BNzLQgWMrDSgrrD/cHVWamRxhswByKUNA7Ho6qmnIx0GPtB0ziQFY9dMDIkDwzh0Ke9DFisms1mff7RytTQwYMVtqruUGEDI+dOGiI0cAUM/V3GGl3bdGdt08YVluTHcZeJphMUka7rOIq6k04KTBIktECpzXmmLLCbYV6mea5ieA9KqJb55Eef6CAETLG9EU8CE4GlbVuDl7F4UWoEjZjSzeubZ59e7cZjPwzivXXw4kWJVDarlV3Y/Xhj2Vio7ZbiMZchj4eJacxYX5yjaE79aNAF+EmANodDn7UEiUNKg5ZSkHPidDj6sOhWQZruMobVpZfEVCR62/piyc2KmFUBZjQtFqvVYkWhGZvA/diL52y72ITQjou1YgHa63jY3aaha5khMXpWwKDJSlVto9A0LQmRq7qbqlpBodvrGxgaEYmkRa3AshYdcypgh+92x1uEcbH5LJf92N/tj3dGLcfgwjnrenPOwdOAYRyhphQcxCGO2ZqmUbXDth+GHDUIRNVsVHc0IbIFRn1u2N3VDF5nG/mkwA98iA9xIuDMjgHNt/sUZeH9p2IuLQTVuKDqejzoQczr6RxkzP/j0Zvz8+bvo1c14qv2iSZiPrn5SZ6q2pXa5nw2I05gnoS+JsHQSeHE59K7B9oXu6mI1KjDJmnah/q6iuCRA3Po9DAZfMKt6JEserWMj0Jif+/cT6dZ9z2zUuaLPG/+EcRzwsGqS4eJsuY8t2X80HiIh+fefThpzs6eYPWrp/CNHOTEDifiuh7UCHBCDYkqgOgwOh3jRLyiU+wxn+Okwe6n+z/32sHM+3/v8Xnw/L5nfBd++rvBQ/5BAlgnwAV/E7LZ397B/L3s5QFUeh9joverAqec/PsA1uMo9PGvfoVsVSfwez07Cc6ubkwsMXCN+QF1o+nhBwlLkNKPM+sQp6PE7A+e+npOXe7cqwFSNzKdVNvJHQwigxZTN+JQsfOpa2fNlU/HdcLPg0uVPyBiJgiDyHLViyImARNYSYmt6ghoUXV3Z7TSkLsXd7daYUECh6uWSnljQu0tVzNcPMlOujtpyl4D1MnJoEnaul5bm0t2DK7mbOQutUUZc6ZcC6upBr8GIpoCLa9Zi4coDafValqz+NFaNBUs1yJznptkY2oOOD1GVZfI6hmB4GRatAAKRvXiK1EG1ReuFsx83kvVkjcjmBuBDeSTEBBNvcNmgSCvQf3MGTO4EjsTqSVVpdqKkCoeSsxqqrFtu2XXdk236DbnF8fjuFydlVK0+NNnn3zx2XOxslmsWheViFhci6s2y2W73pw9vxrN7nf7v/zmF6Lo7/fPLi/aZ5+seBk5dIvFuj2TJtz3x7v77bvrGzgCIx4iRJ9aNs+q2U3dAhqRhmvh6uBDiJzG477fH/udRaK2YYaIwKHq4gIIQCwmgSFkBHZlJwVprlK7VNP+bmq59IdDyZs2NO7WNS1z2NHAQusVxdhsjwMJN23ThafCvN/tt9v93c3u7MkmRJEoTRuLlcNw6NJivVkFlTQcx7SXYLHrJHLT0pB6o1J8SEmIC7EB6g5VlOLkxMIOfR/XmB+kCnS9P/ghWTT5Kwbz2cCcTM1EC/XT1K8vJytj7Ozk4ixkBDc4kRdUdbfqyuEBUquOEJwQmcnYFASSwAavQseq5k5du0zjPUsTo6jyMGjOBmcQhaatJCN3kEgq6jXRDd8ehn0/8nb/5OqJuhXHoR9E9Pr6ruhhtQqxIdX07/7ipy8++ezTz3/0H/7Hf3S4G7/88s0yoJOgZpah2amaJFRAfrZ6NUwxhjvVTqrqOM3rWiUns5WoVmzu0Tq7qNNRP75BJ2WpwI/otxOPHCSzivx8xU116kb6aNGETYhVdT4dH3ZTpsSqf/8667Mn6YCPY79Ytqo6pKFZRCLkIcOoW3W6xuc/fPH65hc327fb3d1i0a5Wq7PNWZQmp0JrxgBfE89xKYEwlTpVGB5EU8O4+Qo98s3ny/JoncN0Nc3gk8Lb1PPDgQohar16QmAohIkpOGJBcaV6x8pxJJtFZwJAgKIUdctgtdYchUL2JkSBSKtsqnBXzrFP489/8tXrV2+RgFv80//knzWi129/uYiLNoRSrJQcBE+vnn/80bPVSo59uru9D9FW6xDiqr87jGMW0cNxt9vfO8ih293N+dlT1VGkWa27km0ce7NiRuJubqmMzpxyOsJLGvv+WHKq3Nkhp0FHPXjychwHuHbndHl5vl5HYs8lF4MhD3koBtZs3N7vhnG7Dymt227RbUhouV5cXJ7dDvuVXHhZ6cjURkp5PPbkyGPJqbhpKQVgElcrRXPOgIMFISIIE6OWLJi5qo0ZQO66xhQpjbfXt9u7bRrLQpam5iXLcjns98tuzUIpJ4kuwjUK5QV8BHdiI++H4QB89OzTt9ff3N/tyEAmDBBk2QShiAhVLyWXlDUrlHTMZBwouDjVfrvmzIDrnEyarJCpcRvNdLvd07q9utwc9jt2aiSMltKorBAECeLsqra7vyfxPI6Wi47ZBngBlN2cWCwVgFnczad+gUQwM9WqMik8qRbAKyFnDqccKEROYmFSBKiPeeV/1mebCCAJ86Sv4fGU0p9DpUkAa5rFjkeGhlAZ13OqrJozjxIhJCEQs5qp1SRXZTUGK57KMA65pFJLBUtTYqtBhIiZRM10HJbL5fnFWRpT9mTux+EYYohNyLmUYq4OnYREqcBgRpkgZLXsiLlK/5PASM2Iwc4onnIec990UYKws2WFW+SArG61ux95rW8iDrExNy26u98ZdGpcl3zw3lIT27AKS1rLzeEWbgfD2Wq1WnRN26ScshbNhAQOCFEMpNnNLEikJYlTJVi5ERF1TRvbALgLOHLbRGbWoikVAyiIE6mbpqRmpgrhuOS+L3FqyuY+lRPZdO+dJo/PHmFYPnuHDxmHSpSlOeY3kVCzRYEpxFBKcSvIoOAURK3k+9JKu25W2QtDrJBwu4wcQtN1i+Uy37d3ZgpDzqOzN4FbXrtpxe90a7ykEBdLYsegI9LgHCUXl1g4xNg1wcmGMZd8zL0JusYkhhAk+KJoIircULNoFqtIXCgQwdomtF3nDhiZ4TjsI4c+3Xbr5skz+e3fu/jqF0eJ5irkblkdRs5M4u6urslqBpHYyVyYhJiZ2MkFVbzWjdzhGe4MkrZtzZSXrDIY9Ie/9eTTH10apfv99XHcDUN7f3/c7lKzKuvzpZnu98exdwYZmaFlicdDJsg45P0+aXFWWMqpz2lIDBYjKtMdJKfaUwI2N+5291pY6zTLXr6/JhsmSMVP2MS8utfGv5OqrYPAU7+qGe3ChwQj6b2pPwE+NnfAJFCFY3Tq+UBETiS1ONArwDJ1PifA2R1O5hUtO8EyFWebf+TJANksPzJLKNMJgZsPSGoc6l5t0vz7WXwJc4+qR1hUhfHdTU5+y2wkZ5/lvQvr8wyaP+DuIH5kDek9J3b2zSb3CRNv/eRQfchV8noR3GfSRkWWfL5pJ4+3UufI/XFgR4ZJmMUrp6DO6+kW4QQ0TeHpo/tItU2Tzwc3S6g9QhWI5gDzuzjDbwBv0PswAmaI5jEi8ddv5f/W+AcJYJ3GCWr5LlD9dzMew41/e/fpg5v9lT2eQL3T+1OEOUeVv/L1xwjg488/IEGPUNUHDIuJKtlqDlOrCNQpf1drPJyIme3h4lTNPmAubHk4qzrFHJXDSsRmJkIs7ARzQy0isckI8QMaoqcAeT4dJ3Y2EJgmlb8ajQAwwoRdeS3eMUxM1lKVHgnscRENbjCtLqCRkxXX2ki7iMK9qJk5MYQjs0wqT+7GDCPjmp+GzXyE6fwNj+qJqMoZBJrBppMWus9uZf0zGfcp9vQars7lPkQAP6jCT727DFypC7WHkfu8tDFsyiP4vP7FEGcmGQzF3WFExFW3yKZVZ1qgfLJuPi1KOoWDNYHipyXUyEidZfKoGcCsOjs9ipDAriVE4sDEqkWNjYSaNkhoN+eb9WqxWq/N8e767hc/+6snT565e9MsPv/0xUfPL9LhnguRoZHQrtZNDCFIt+jiotn1u+v9/mdf/eLNL1/zaEj6489/wEBgWrbt4bA7ay4BjON4HEYF2i6Sl/vDvSO/+OhjgzqKuZlnoSiRzSdareqog/b9fhyPsBAERFLDMDOzrMiWBwO7MNep4bXAndyyu6sEaZoYJt23dNylsT+6FSbqFk0Tu91ubFrus1EABSAQmJqwGA/Hu9v9m7f3cJzt7zdny2YRl5uVwl6/fjWWctavu4ZdhyHvxT2MJkLdotlvB2JX74cBRBqCu2vtHWYZbMSRjR+5vI8GfwjAOpkFM5scAnWfGeDzjEZ97uprmlrqvmeAnGDkLLXj16xVXldlm1lIp2TQvFoTCzmpKrMQoKpU1AU55TTm5TLuj8XIi+lud7i7z0Ofp+eWSM2P/bA/HogFvlNDLoWZ73fHY58g/ZOnDCYSDEljwPXtndoRYbNkiVFutzfr4xkFfPqDj//xH//wy5++OeyG2FBom6QPrOtpHk5TfvZxKhfViaYOgI7afbPGFjQr7p3Os/LsHwCsEy7zyD+YbpI8JNtpnmhSp17tbDRlG82sdmKomMHJocOHlowP3PKpcc1DW6LvfAq1UtRMvRSWhasBRRUhMkey5G0Mn/7WSwm+P97e3L7eH/bHvi1aFu1amVsamQWKkk2qur/6KQPq7mrVuX1v79MKM3mRs2dev/NA1HIyY7A5AK++cn3BhIqHOsGyZ83whgOIhOHmZuZQ9UzBmBwEdSUu7kTEgRKUigu4gQSA1RkZSbNbMRIsKe6u98d3SXcEZ7zRq83Vt1///ObtzWqxYtHtbuvuH390tVzGq6er7e6GJeSx5OxaxNnXq/MYVznbu3dvwXJ1/nSxjPvjOweKytlms9kscioSvCiahpqO3EEN5wK1vD/0/eFw3B1Ic4ghRDHLZiVDs2VmFcFyGS/O1uuVRE4iFJsw5v7Qb4ds0hbjxfXtfvf2Lozjx0+vmrAoZqv18snT8+tePaz2W8opNU1sosDkcNxv98dj39fmvSEixiDCXduKpGFwJ8SGQ8MhUAiBBaZWcmmzmufYsDsDltKYU8GsIAyAyWDKRGD32pKQQQZmbxr2TGUgHUV8+dE5f/T0s3dvr/e7gxc2w6pdmTSjkmYXlsWiNbOBh6P2mkvJJaKREGjqIFNq006q7Rdq6Uqda0VDWCYfDmO/yLJYrq0FmIoUITQBpMGympIE0ozd/b2Lt00jItmSFocxmZkaQOI0dX5SN50e3YlT5ah5IHUlSE0NTaFINQlZK6+apgnus6r3lOGqc8DdH2ScawmzAT45LTjJ8U4ymTW8qmJ2XrH2E7Fh+jt5LGTmJRctVv0KFgkcXFHGUvpSy15AsORqhRsKjYQQhKRUyQNVkMcYDOhTPwkAZc0puzk7EUltXGam5hpEKj8JDBhPUTJMtcbJVqjkMechu2OxDCjQbKoaGqlaq3nIeVRTJ5HYhG7RNF2jqnfbG02gpkJ28B6q3kAWcdUtF/vdXs3Ksd+92yL7cbcn4uJGRGqFSEJ0OMyUiILMnTcBh6/OVmYGw1iSFR3SSIT1+aoJUVX7vnei2AZTzykN/aBFwdQ2Xde2/X2vc064+mcOVNkgd+cpGtX30Kv5Ls39c0gCVXxUDSDnyE6masJsrhwodDFrMnMyZQkWcxnKulvzQkrxkrWRsFwvm9jkXFStWy5USx5GG0cL2ratSBVrcya+3R42vOgaiYsgXcuQkuFFko0UsNh03TJy5IVACsMM4i7qBFU3CzmbWXGSxVI4rJoGTEFYg7AwlVIAmHvKCTHd7b6NgsUq/v4fv/wX/+03JWa2utBbKoUpxrajmRRGAAAgAElEQVRxIoeam2Z1swwjAgtYOAQRkRAky0iAmyVVS05MEJLAYOM2jUXDOf7gT1788MfPx7zfH29J5O7u8LOf7ZnD5xfnKWvK4zgW80jEuZiRMQmRG6wUiyLSxHzww6633mreqIwKrQAE6gQl40osqt2g6zR+VLXw3ngkafRoCZ4cc39Q7J2BzolJOTlhc6LHHzsU9PDvI4SGHGCvVGXGHMQB8Emxk05vTK7EJCnvE2w6Y1jmRrPa3XQARrMDQkZ1B9Vq2QOqAofCEaOgRqaY+9yfQLvK4aJJwnh+t9pFc1Cg8OHw+RGzom4YjwLtR3ASHr+POaHqJ6yMKiI05+8eZiH96s07vVHRK0yA0qmCr0aONF131Hj5wVvDg8iUz6TYx+mGaRgef8cmgmq9nnNQPxVh+8N2JjLd7Hx/GHL4nkE2VYS+BzU8RiTwN9/obzL+wQNY7v6I6ff3ME7e/9/eMXxwy6edfg+GhV9j7B5/+IPvPDAszKr6wszYmijuJ2DLzE7kHK/4UPX5mKkGrg+TdmZTENzNakTHM2pdF2k2M45RiMncDc4+EZkqeHYiSU+xS3VxyOaDhTjANdwhgElrvp0q1QjGMCeDFzM1L1XCASRMRDkV16l/mLtnLxB1qWlYlFLgM9VzciaZiGsze6FQaaM2FzrXa1irAmuejHlKj7hVwXMmJrL5DnvF2bzq4HgVr/aJE+Vc66WgTFVoe+ogVKUQK4ejWuWKWs2+qRABZF47GdoEv08lfpUBxiTFCxVkAK421fxNTPdpWeNaEGaz5T+xPOoTU+ACZyczrvpesxGtIB0DalZTS1aSuYowk6lZUQPgpMvNcrlol8vlcrm8vHxCzF9/8+2ff/nnm/W1cHxy+XS9XP3w5QWK5UHZWECbzZopLJZdt+p2Q/+v/s8/u95ut2N/9/aWMxbgzU375GJzebl5sry4ubuLbRu8HccRTMvVqmnj4Xg/9AcRmJWJEE2aTaGjMxXXhOJkOR0ldIHRBE5QAEHCouvKYJbkMB7T3nPvEiGO4NHcs9aqAK9EmcDcxaaNIXMqVkpRdifTNgjXK+tWim63TmFwQWgjAr97dT0ejv2hjwEGpJyOR3ZGt1qG4Mroy7HNHEMbBKv1UsRjw8IcY3NzPcbAJKWUMUZqWiJ2BgWpd3pCfj+YLvoeQzS1wqx32DD3+p4mBYh0Lh+maa2lOf8Dn/r1OUPIAHYD8QRhsZOBAybxqNlwELuhygtAybyQE9zcSjU84zgOQ7+wqMXLcRzHvNsN2z3GUUMgLqpmqpZKubu7N4PWMI3QtktzSGhBAQxmNA1KBhnutlv3cbVZLFdRmhAX3e64/+b11x9dvPy9P/zt/+l//dPhzlyxakkbKSnPKdP6x+CO+SJM5mL6FdhPWcR/T92bLVuSHNdiy90jcth7n7GGruoZQBNggwDB6eqazK6ZXqgHfYGe73foC/SuD5LRTJJdM10ZKQoiQIIEGkB3V9d0hj1kZkS4ux4ic59T1Q1wuLygKa2t+pyzh8yMjPBwX758OQAXq0L81eo6CHMHiMVfIdwhM28dqkoAz0W+QE0wzCa2/t0XH3ix7b7IsvoRLXvDyXjrOEbCC3j1jYki8lkH2s3MyUrJ6oUY6iUghMjJ9fzy9E/+5EdX1y9ubl+O6ZDLdBh2KafTjXZR23DWNC3Oq8/K4myudfTm6WlOtdGiz/b5bmuZvdY5Q3I/bVktFhlBeCayes1wElVuGRkIZGTZDUZeKLqzuxCcoG7F2YSM2QkUyI2KOTGYfILDqYMIhYY5OII7leQKUN+2p6vTv/8/nk2H4sZtCPk99czjfhKwxKaUvcA3q/6dJ4+7TmJju93Lvm1JQtesY2xevH5xdnbS9bi6er3b3/aH/vLs9PQsXj44Gw8Th77vY4jkzo2K19sgCbFZRR6KGzBpKaVknVizRLAIioHUtDBz261WnZ+edm3XiCzZFXguOeVxysbSgsNYdEw5jHkcx8M07g97jrxadSyedNoPaRiSSmNGKY85S06lpFm5oyhi4M1m3XZNUb26fV2KSRQJkIi2E3dVdhbq+lhyCqFhCsLRnUMgYpiWKjVuKOhqx1WXAIgTLDRo2yhCaSyplCnn9cnpdz7+1v42bW+GaSxu0R2rri8ppP2UximEJoZGWEKIgXKx4goIRJisChfUXdnmjH1dirU3gRUJAU7F3UHrzaa5iLKX4SoxDWAYVEd3dW6YQSnl0FDXRBhGjGoe5qgJMBeJzlYp6JV/unBqAJntg7lSlcvjpToFIIcmrWIr83TPMHfX2bvyyh0gt6xzf/q6ZZvXUsQl1ruzLL4QtUFVNoBAy/Z/fFfNqfmsZ5pzhs4fYyImmXd4A5yq/JCWouZC5syb1UZd3T3lfHNzw1IZJMbCBs+plFIsz9p9DiKFa2XHGIxnLqgaM6oumJmpGwmZGZN6ciSU7GamBZagrkY6aSpZ85RLqqlE0aKm1jRN7QKGtJhgQ0nQMVORlqwVfPjogzGPU5o8ed5lLtx2KxJ2R05ZC1jZzEoqhmTRPcIDyFFKCSHmKZWs5CCIuzMRCbEwhKI3Zu4M4RAIoagyxRjbfrXqupsX11Ydv9omzACn2SQCi6KiYXlAb1AnajNYnnVyVaFeKDAFeNWaECpWJHBoYs4J6g5qmyau++31dn2+lrZNeRp2A1OUXtx9v90Pwy5GiQ3DS1Y1TruS9ACMc9h8+uRB0Xxzu4uazvr16nTT9iEntWkYp8FIxzxAbH3St10EvOv6vusFbIr9TYJENRsm2+11syGClBJJuLhBZwaZwdWKwV68/KWmQ8cP3nn6CO+i22Mcc0o5NLGPwSgCAcLurDmZGkxJ2OCmTlbgDhKhUA5ZojSxcadJsyvBoF6cSvbcnOKj7+Cj725OzvjF9vX+sDs5P3ePt3ts1rY5uxjGVynlplkF7t3ci273SRVd1+3ZwNZ3Tc5Iu9FGQ0EIgUBlyjPdslaq15BkQZFnRhFmMYGvb7fuC8CBmXNw77XlH3fy6pvVHPTMwZnTOl/LA1Ua0Rs7ulcUiI6rn2sbrqNfV6/zLm20oCFz7nMuiiNVY7JvdByqH1Z9Qpuv7TjFF5EsvLGhw1GVYYzdzdQIc0xT3Z9ZfGuOKpcaunvlSvfH6u6PR/C3SszXD6v6jCvdtfa7F8fOIz+n530ZP3fDvVF783T3o/V5BO6NHh1f8qOLeO+P9xCib8wkViI96A7Gms/xdjvFJRKbB3WRBGGG2T3/Cd/40L7x+E04A46+470f/hWP/x8DWEfGUP313wrD+jp09V+VMnf/vG9Oyjey6L8J9bxPrcJSM3j/bb+RzrYshWppzT2VYqrQpZcEETET87yI+O1sOXBci4DViN1BMkd2SxLJXEUaMLkWs+Jgu3Oq7syNm9Ms004iVa4LzFomkLmLz8vYjYSF6jxnM0dxzYrspLDibgBToBgkHG73ECYRYiG4F3cqVZKTqOpFOQmcIItYnauVUkopojJLnNexrf9WqU33xTxV7S4zt8BBQvUcQAqqYj/uVEX3OJiBSCtydJcgIdRqmmM7Q1CDylbxY+BPmGkFFVbn2mHXHVUIxslquxJVcGAhISYlhxUvjlp3xRRATuSulbLqXuYrqOb7awmGuvk4uZGxERNp9TSxlOy410vNSZ0hofKnfbVmj9at+rPL065tzAzs3bq7vr79y7/6v198aaCvmhaPLnfDYf+n3/+QTeAuJF0TL84viAUcbm5uvrh+9dc/+et90bjuKXrbttNu+Pnnv3j11VfPv/ziB7/3/dWmpyBFdUppHKddTna43e6u2sAX8ZQimZpEVkUuU7ZcyEcrQ560wbC/OumerNrWA1AmuDVReLUSb2ykdFsKTxLIxZkhAnIq5kQIhJNNZ2ZNjKuuiSyWU87aMvVNK0Qn683t7np/GIiwOmlPxolCs9psutP1ze1tGafXr66n5E1PTUPunnOx/d7Izy7WT5+8Q4xpGodhaAPWm7jeNCw+DuM4jSzo+7ZtA7N1fafedF30ntfrvuyH/BvcozuD8OaLc1bwHsbtqK1AaWbBHFe5Ge69DUBlWtlCJmRiJjbzog4xEM9ceTdqImGuQwUMGuYvdxMWJS+qwsFRYxsEQcllGMdTXYvIlPNccuswY1ObrJBD1YpZyjZOExNLbFgkNr3EDsJNbFUNgWITSi5wud3uiTFNWeJpUW+69vrmZhx+ah/4dz/69H/47//dz/72V7/62WtN3jRh8jTP/7rMrJq4RalhgVkYQnAnW7DneZxlUbFYoL2ayPQ7F3XWN7gzpxWyql0gHFpdEKHajmo2knP3QzgvlYa+OFHH57lUJ/0WR4WOUfP9UuXl++YrNDdhB5EmDU0zjoNEDiGAXa0Ux+l5+8kn3/7e977z2bP/vD1sJVCIcn27T+kqcNds1u5Yr9fvf/v08LLsd5mYoJVDOwf1RLUv+P2k413+ZnYij6/em4011RJcrIpezd68Lv63gWf8sphqLuyEACaAxEC1Pdxc34HKkDFXFw1ogYCGGmYFENoQegotJc1GJk1Yb86++uwfeupKKp88+fiHf/7pqlk1IiXn29vXSW8vH1ycXVw8enjBoiQ5NuF0tTbk9eq0beN+96u+XznZ7nAoPrHoMNxenFz86Z/96JefPXv2+XZMt35t7rEUPQxbsxQj2o6oiRcPHxuLbtKqjbs+6jQxUy455zzlydjWp2dPnj45O42rRtuW3UY1zeqHSS/WXWglEIUYPbbrU7FDAW6caEppGMcQYr9eScOUjEX7dQjqeT8M47Rev6OFmWGmYG+7dr1a95sVC0Wo0fmUplwSsTWthIicLWsSoO36lAd3DqHtu5YQ99sDaMieiIgjVPNq05vmUnLTRoVls1XbrDatQq9ebcc8QHB2evnukw/+97/4T3/32U+22xcONAFNZHYi85JKGnXYjyFEwHPOpRQUOBxz+5laDQ9yZwcUuQLQDA6x+AipPWIKiLu+P+QbYRfhmrYjBxhMROTMiG0zU8DrxmnH9lgqgULDzqxVe9nMFVAQat1zNYd1xmUYaj1hDa2M4NmiCAkqyOdlwaqPHbvm/Jli2barISX3QALD0g7eMdei3dUj1cud0TtfUgkVNvIa+njJinJMSwpTJATMYqOMYiCwcClw09E8uT5+98nVzRXgpvr6+qpvm9A12bKEqEXzlNSMhD27qrFaURyrq6gN8KpKxlZFTcnMjIXc3XN2icSMgCDMhtlbNILisBuYweBQ1SVFiFxdU0oAhGKhXE14FUHzjKmMg7fRYtvLcDhst4ehpNhT3vl2PcEACkhaa7ZRHFIQ4ZK9QZHi7qpKnNKYoYht6Jqq0a7DNAzjQU1TVquxcln+I+RSch5vD7GWKtuCRzJmwYbFDddZRHGB9O/HmuTqBoILRIjnmsxa4EZgYY5cUKZUTA0BiNy2bWyCw8b9mEt2vzkcBkyGGPdt17YRAnV1L7Hh9Xl/8t66a1t27Pf77e0+TSahvf38VXjQPXj88MHTDbXjF89+uT+gjYixaVexXXerVWhWcrvd3h527lh3+3XfCotmMNZMAbBpnK7ySLZdrSL5RJjMxihl1TerVcssKScp5XqrQlfo7XL14D/+jz/6+x/vfvqXL14/3zcIfRsMvJ+UzFWz5Qw4cYhylGI1mOZBi+c7WMGFiCk0bde4qIeJWvzZvz/79A+fnj3S6/3z7fbmZgeK2q3ig0uYR0bY70aHbfreNWRNgGy3dnt79eHTDwiiWfNU0mjuCG1DgQOkTOp58aOXXXmersyVHSw138xv77jHHW3ZAWuwiWMRmTvIFYYlo+RURQrIjyck3CPz4G760L3fyWbhWl5CNkPVPFnSb/P2qxUMdyDgTtAAVdmTMDcsr0DXcq672erscJ53ZBCZ1/qR4wZe/9VqhZzrTVFFvtnVoTYD3lWetXYeZFp8MaWvIUnHSPmtQT3+X5acWS5zbMvL41oqZmaw7psxxPn+7r6Qljs+BrlLeO5vec5+NzKY+zADREvj1uo+17Dv7Qe6fJzetgbuc8fVqvFyjE6XKyU6TiQ4E4NrnbG/9eW/5bBvgl/u44b/9SCRfwTA+jeEh74RRnnrMo6j8zu6pt9w/C4H5+sA01vVH28BW28HJ/fiSkeVY78zpPXj5lYVVViW8uljS1b3KgZJVVdytmVEc+3g0pfKjGgWXKZFQ/BeS6t6CTWemiUeeBaAqpQ6MVcyh1mVHgU7CaqzUqv8wBalCjlXYj0RYGR7G52wrHhFVCaamfVm7KS2dBq2mR5VBVyYGMWIISwkcJCxOhPESYhBzg4l5lqCziByc1UrSS2pCVEN0GtWwecnNUtKmVVelZmSgxSzyj3dKaSyz8mH2iiZieeesUYkzs6Y2bIzZ6vmTGrjXPYquzWXvuuywVHt18WE++1pl/3LijoEwlRpW16JQFqFX6mKhtZeZPcoIctEYboD+b0KxM/Q5IxhVvoyXPzoPNeKRSJAQUrSMJGenZ1wi6bnVbdqu7jfH8aUUimqZqVp+1GAVduvm7Wm0lJsmt48d9x0EtebEwOS2vMvvvr8+bP1alPyOJU8jSOvqFmHMuqhjKOmIvbg4WWQMGXNpofD/vnr10kHx/T4wcP1alWTHhKEg+RpKq4uNOVpGEc4HQb0JcXYNsaju2f1qTTccNOY88lmFS2kVJw8dNx0jcFilqxZTdfrLudS5dxIuKSSkjUtuq51oxA6WMjT0DTNg/OztoNzE7vNVPTXz778zqOP9lfjtN9lclNQIHP3XFLZtV3//sfvX928vnm9L/nQN4jNemVtUR+GPB6yCNq2dvhEE4N3m8Ch65rzk83h+aTBYbV1gc8t80gXgqXx3VxZzMWdxC8tux4Wm1NV0Gan5ohrYMmFMQiktfChoqxEgDq5HrVpAQJkETqaJxCJwyptyYspYBAoWeUR1GjNQZVYoIR2tVLNfd9MqcSGtSQtmQgioeIsLBSChMAhtkFIndrYijQ5KYMFTAATl6wiKDkQOrOpFBvSIefy4tXnTy4eff/T76E0+y/xD1896/p+1sIHMZMq3JlpJo5W5J1Qb7aCPQZiONirZHOZWZFHKhSohsBwd68MN64Gie7Ti+CkNIveoSp2ipEdyVWYgaf7MhFHr3BxS+48pns/H63HvG7rx/WYoazf5nPLIHI4sRGLO5yUpVF18krpyaGJZTc+uLh4/HTTbnD7/DpbgtT4k7Kh5EzkTRPTNH363R/+zfi3t7uX5BICBxL1Upm/Wp2wBT53wF1QjdV8zTMvC3OWeHblaLF4BK+KPbW9RZ07DmJjGBNToFC81OpvJgpEcDDxqKnqbqmrqQKAOUi5YZHIQTiwsmcFgyk05NBpygfLjeEAFccem37zJz/6URO5aNre3txuX7Udzjar0z7CJid30s2m73vOpQiXtm1Cw/tpHKZxTLntViGEaRpLZ0+fvJeTP/vq9e3hingfqDWlaTzkaWLyvmtC25w/7hADh25FcROaw+FQ8nR9cz1tx5Tt/HL1aHX57snl2XkQGVwHcg+BItxT6UK/alTIqV1TWJcu02ma9IBIiGFyNJuTdl1W601sV8Owa7jnTFflpdJ0fXW7H6YpGQvapjLgzLyYuru2gc0YRlFCK20UzmmCgyJxQ0oI4s4GMmYXhgOqkMrAMg9dLAOKps1pu98f4AgSAzclTymNQ0a3hoSmC+uf/M3Pn714nQqaiLa19doIQpGbEMdDGg4ZNHII8CpRV6vEQWbQuutahXeoKrtAqkoaSTDLzDB1KgTjw3avrMzUNO3hMDkgTRSKWgpEY+DYBNNsSu6AwNUpeCRQIAg5MOtfEVCF6ZZE1B1four4aqVYE5gqrDWj/FTNIFFtGVznu3ntz1xD2Wp65mrBo8dRl0zNQ9BcA1NTYbOndzQFi7/o7EyxKkHzXF24kGOJhZkq98sdGQaH1PEEGMbaSkeFbKooFBuTE0r2ECWo5JJEOVAwNUuKAleTqnDlxF0VNsCs0YCqX2+o+xeDyJmZhBkOM3LjmbEJNTCzSBCpCYTKreNSCtcnXFEkhnAg81I0UCMafHKJ4gPs4AK00gUGJhumFIOQRXcERHMvOplmFkGhSt4kh5tFb4QCK1MJBDQUEXwYx2mcPB/DTYdws+7mTZhYWPZIxIy5OQ+BqvQfzRTmO2HCeaudga05eq3CE5UJXEALt8WcmdqmC43knEtR0wJHaGPsWwfGw9i37Xg15KSUQc7GuYRsbVyddU0LRSam2LcqyRpen500FvlWtttDGbX5oFHT3f5aXqe4IbLYSBFqmIMZjwdVVdq6sweLljO4hfREjFz2077tOlMbhkxQ4jAVikw5WUlTEL88M2EJUTRTUhJl8U6oAcYf/NH7gmeH7VVWvbkeNAdwcJFUsqshZ3BkEtYAcrDWWWRmWrxft5ZZE+dC0KbpuhB50iFxQYcf/dHH77zfTLq93l/vUt7uIY1v1vzg4enV691hezvshhibLD4dpqyFm75MctghJyoFxWga8jhqgzZ24qMhOdSY2FWPypFwNz0CCaAZc/RaZ0fHGG3m6NAsTuD3nDCa80hcO8DX5T37CjXtQ/cnSu39hLlU0e/V7c2bp9cxmlkIjlqMPDcxXpx+1HdiKVKsjsgyFasrWf0pOFGVALDF8BzvgcDmdVrPXiO5V8HcO2+n5vZRC1Tm382PxdGECpfzzOafUcG6TO5/CY5KCG8evtzJEWGjeZdfHCVyrigb0z3LeBeM36eGVGbDnBzEXZk2zRrr83OjOw9kHlVaHsGiWHp0ZWgpsLlz4+oHaH44tNh35uMAc20RBjqW8RgbbJHTtwpYEYiMmVH1ehzLQ/cZ+KwnOsrS0+Iq1qG+m1pvIiHfiIr8U1Cdf9bx2wCsrz+bf/Fp/lnHW9SqetzHqo5517dAvvvv/Bec8R/94G9Byo6w7j/r7P/089bvpwUqwj3O3m+/8XtCdPf+OBsgP/IsaDE+6u6KGbHQeX1W8TjVAgURQ+eKoHklGLiWokHg8NriINQeqncVtW9ET5iDNqvd7Cq5icHEBgsci3oNZ22REqxLmIUM6mYcOLKQCYp6AZwCBAF7Go9eAQAWYoap8twgw0yzqzsAcZ5Reya4liwtcwwSyaDqxckgQC01WXoZu4OMyCtbvmb0pYLkPjdeFVhtleoOr34VG9cgVphZGLUrvWZm5iBSmQZLVCgiIQRXMyVVBxkvtr3miOtYiQh4RgGPT9kX8ovX3l0CzFuVM8/a6vWR4Vg65qjCX5VkbChuRExux16ztepw1qSuwjowxqIzX5UbwUZ8nFizc1ubdtlMzXKrFZ1waYVAQURifPj4kiPAZRzTZnOy3sjhcNju9/txWK1lu0UTaN2tnz56er7pbbR104Nby2ZELuzEJHpz2P34b3+yeXgJszyNL69fZsvvXj4mUDrk51cvf/Kzn37v9743jlOGN01j7rc3N6kcTs/685PN5eV5Ksk1s4OEIBRjiKsu7307DkxIBcPhkHMxRgCKl7zbZrSEUDKCoOmYghDz3LSWmUSQsyU0rcTIadD94dA13dWrgQmbh6ePHj1IqZgSIxKSJis5C8X9YTCTrFZKfvjo4fMvX9wOO+FgBSBuKJiXlPTmdvj+5uKXP//85dWuYUBxkpEmT+OUJt2s+p1NXSsllxBioBBX0dTW6+bRw4svfnrdrDLvKcQwZhUTkBAyUXEUAOShYllYegz74sfct73mpm40F7tWxwccAmZlp8Ufgd0lmshh7oWoypAzV0CnNjGFLwrDM2MBtYAI8MkmAXPDpWRkcGQz94wQG5ZmyprUHj04vb297tpmY4eTTbvbpynDPJ90zX7YHcbb1eqk7xuAmGy/u1VFDI0IMdHZ5my4zfAxSHj+KncdyKN7I4HzcBuitC1t96/+7md//Sd/9N998sl3rr/IL57djqmQAp5JhYzJmXzpRVj9lyruYDAcF7ITBWYhprEUCjOL293dyOe6EgZItbijVjctZQWOu64xcw1C9XWMXMmca4f52q21RrVGIPXlEdDRRVo2kCUFR37n2zEIzD63UZ09lllPp/Jh5yZtDq7OzWSOEBq4xCYWK2QohtOzkAK+9e13H7273k8vh7R3Qiq+2+8kELvt97tNN0ThX3/xqz/7d3/6619++cXLFwHUSENOOeUYWEIYx8QiNYFiiy2qXuFM77Rsd+q2oJo3XQhtZrlG3LVOq85nr7dksFygRExeFbWze66mnAgliLoX9QUPmye1uRETpaJsIPVhyKvYUGxSwrBXHYebaQuHTrZZr56+++iT7340jrfTtOv7ru0eXlz0fdPk8WA6Npv1br8/WfdEg+k4DdPZZfvk3ccvb27Hkjk2m37DEM324sWrvj9ZbbrVaasyqZb9OGqCFSNH4LaXky72083Ybvq+7zYnXWr7K3o5DkQnZzaQu3366bcvLy+bVijsIERCKCIc+5a6lqO1qyjkViymMaX92EbQJrrDm/Bqf3i0fsdjJJIQAsGEOLSNS8iQ3X5YtesHl5v1upMoKU2pjHBv26hKpSQvSdgDSeAYWITHtvN+0602/cubQ1wFBiUdg1lgtAGTw5hcnAET8+BgdOvVzX57fnrR931JeRp1bwWC9x5+/ODygWZ89ssvvWDMOAAcc05j18OJVusVFymDqZlNBcIiQRtz41KUCmGRmiyKOMcT7MbuZGPywHkaqKnOPU/7qe3aCen0tAu+fqG3V4ddIC7F8pikIzDaLuScDmPxEKQ1n5wI0sBg2YqCzFwd4LkdS9VomymH9+KCujxnAwCufgzRncQJz8QHzK5W7eelDJcKMzkqNEbFrBoOXqIPMFhobohTfbhj8DY3egVVWKZq9xAxB4ripRBIOAhzIIYg4dhzmaxYDXoEIpDhdkyHPO4nwCUKhG2CZi9jaSVy5jwWEhINkkmzcSZ2DiQuMKpZC0LtaU8GKAfcC5YAACAASURBVDFc3LVwLeBFEYbnXNwI3oQqloomchWnWIYGDtPsaFpimhXBABTAQRwiArsgUxl9l4Zpm/KQKwO0W3eunpJKYXf2ZMVUqkZ4XUeCpU8qC4Vu3YcYU0rjzcDEq37V9Z0XzqqqCUIAQwtxaELHzKZGzpFlX8kki8bZ7HfBuSYWffauK2Ued0Qcc7hENjMjVy/sBGFhKW6uRiwhBmYxS1Z9xQoXkDu8qPfel33Ko0oILOzmnr2UPFrpLuL6YYTYkHbbEaeyWberuIqrTVduczqU5hDyoQQI3NO+DEnV3To1JZpKG9q2WTUccp6mwcqUNXHJrI40GbWFNMHMvajbftQpJ6jnsVhB14DciNKqY0LMypFC2vG+FD189ehcHn+of+AX64v2s5/tf/HLW8lgMScNXWvaRm4DBS9aLLsVBEN0CEIEJ7ZCjLgKKxUyT9v99r332u/9yYdPP24//cP3nr/46W5/lS3tUsoKc+9Xmw/ep76R/e3rLq4ktHnyKZXiJMRN212chWGwq+vRBirZ4EwxiGI6DGmayBCaUA4KEJHQzBY3cxcRFgZ5LV6rG/NRoIHuOxRUd9+ad/ZqReALcjHDYnV7LqgmnkBMnuf045whq6iO3YOe5rPBQW4zXE6AOaQ2UDlmvmh29yrkXvmNbl6bYh1DPAgBRF4YCyf97iRHAG7uN7Wgb7NfM4NhdFRAWFJs7jPRfQlQnLx6PXT3vQRGzvmN8zEdiaW4F4DTkWd6dH7qUNa4j2aZYT+Cd+5vdTzz5agPwMtik3EErwBUvsUS9bvDjvo289uOAKAfmR/ArJ/jCzOqyuHMZmEGwmYvbi7oZswJUKc6LrP0JwkJmGS+u8XfM5guA1Md/OOtApWGZwticBS1mG/kDr9ahvmIsH0Nkfg6/waAquJfevw2AOu3XMfv7HgrXqo/1Bu+m3z/SvjaN0Kzv4PjHz3v/XufK9d+8/t/C8p2PH77TS5rrr7zjql4tFjAERqe/5kTdHdCbvUkfKfWNNvWJe2NOa9Yo6MqRAAmd4aBmdmFTRQFlXNFADlVHGjJWlTkJWe14uLCRAyOUrtLzyfRohCAFlzeZ/THHUSoKtzkZMU0KUeh2gWoSjvwHOwRKpcJxzwpKc85EnAMDQKlm1uKjTQxEJlarlT7KhVkzlWWuFjoGmYqWoqpO2Y1zqpyYFqvLQQW4brRMNWwFuZVPsIr54KZCcxEyYrzgiQuUGH1IWfZqfuTyG1JxBLcY9OIiIAKZs/YF8Rg0bvi+pDm5+XzswTgxb0iVgvwf5cPwd3b765qBr/g5pSpPW1IEAKfnPWnJ6cFaUy7V69enZ2e9Zu+1lmsVqv333+3TL/uQ//k8ZN33nn0wdPHL19f8cWJFv3qi6+2N7effOeTh+88kiYW95vb25t0aE9PmtgI8WF7u4v9w81Z5EatXF1fNWio5RjbYZpONusmBPNwfnp6cX6xWa296OFwCLWLZpB+vQ5dm00P41C4rNeYpmm7H5tV7NYrYUlZc1Zm0WJjGlWdJczZEICZQ+zargFRKWm9OukiX7++uXp9M+0QT/D0yZOLB+clZy2m5gAN+8P1ze1+KFdbnJyM65PNw/NLEWI2ACQILVevJ4ZG07Db7a9e3+xvD5igAZlQEjQTIEGCSIhxYqYYpGmCBK5zt4nh5HQtPecRRsUVBKmq4k4EZuYoQppKZfPVvC/h7Y6l1fDazLya4XVenK66389boC17bAWv6nR0pxCY2XEkSLq7i7Dh6AoYYHOWTjiwgMhgnt2LSxedtZQSY8sSXr++WZ0101RSyjGGvu/btmMREG23t+OUximVkoKE1aofx+nm+nocc5Dm7Px8tepMi7CHhhoVZkkZSTGNZZxGMY1ROjQ5pe0wcMGz51+enb77wz/9g9vt+Ff/6f9VFJ7ZoU7OLJFMkudqPhdBe9QhoWrBuC7jxT+6l7NxwExrz/vZyXGraDiqBsXigZHM6b0ZPnS/+4o3N4E39ovqGi8e3PFRHr1fLOm8Srq42wTe3lns6F1X9WiiwMzEUrmzbqnZxGk7fPB75x997+n55frFzRcOdP06DeN+hxhcGIfhME3TMOy7ZvPBe09Wq5UVhCCRm5JLxc0JFEPQuZRgdp+OaNtCtkLlVd2/1aX1NI4Sssd9C8v0nG/ZFreY3ZfMi9VzVzys7nbCxO7MLqReNLmPTg0kkkQiCRDJRfd7K8FSLFDokL/36e9/+oNPLi9P/u5nv1idrM4vPpZYiPKrl18Oh9v1yWYdw/6wKyGTDyntJVJK43rd3x7G+ZGq5TGJe9eGYdyGrnv/o3eHKV/f7Ha34zDk8XZq2vak36zaHuBU9qKuBifKNnDwpuX1ydlHHz0JQZ4+fSoi19ev0jSsTvn89LKMh2H/2kyZ4pTVDLn47bDdHqarXTpbtat2nbPtxzQlb/f7EBmwVy+/7Nt1GofiJcZ4crq+fnarjToZCYUokEaMYiNEnrOZVz260oQgwn3fQXTIA2Ap5bZHCMLqcFUrRiaR0RgRobippZIA5xUfxkNs49nD08Dx5YsXw37iExjwrW99/PSDp9vtbhhytFhpNaa4zvuuS6tutZLmZN1wiIfhkFIyJxahwJa8FEU2UkRuCKaluMPVTaFqBiVhiexuWgpWaJpYUtnlwYNHbtsurjb56vW27CdMgCB2kQNPWqYpq7KEEHt2ypjMipkD5HpHMiDiWnYDXjB9V5sNKcjI2Bg1aKVaq+dHzKoufQlhbtpjtqyEY9x3F5LR0Ut8Q+ahhlCzpaD7L7lXPQIHlcMIERIOLExMMWIJydTNS7HaLYyBI2LOcFc1ev36atgPyA6CmjJr7OOqW03DlMaErF5ctZAyilFxqrR7iBPlXJQdMPdaqKlgr8lALO20Qd4EVvU8aowSm+CGNGUW8SoGb3M3IGJwCF7MGOwehMBUiulUXCBBcso3+ebk5CRPI1wFnJMdbCSRIIHAJanl4smZg0QmAgpMakV8TQmCG7Js6qWknFN2LeQUmxibGLqgQ0I2iJOEyCGCyakYzEpRI6+6QXODvFrCXNOCd+nZ+SdavNQlw7F4v7WOYnFh4WY52zQOHKTkBLXaKEZLTon7VX/58IwqwK/wKsTB4EgBUna6D+ns4WloghYfUxq24+vXVzE1Beqg2DRN6AtlMlDAmPN4MCNQtCpZYebMoet6ZhrHIY3QabCUiWjK+eFJK0EDcWw7EjFrSsYwTPvdYdWEECSN083VlFZY9+t1f1Km6fp6t5dhs1oN+182YfPk/Yvz83cv39lu01+++kVRRtP3MTSHw6CpoBhJALduXEqBG0WKEftpgCOwkZCDEFO/Gj/9s9/7D3/+vR/8ydOvXv+46UV32/7kbM2hWIptiG2MIk4nr15gc3K6208vXm2NqKhPwy426649mQa9vRqQmUmcKGvpKcY2InuZsqkK11piorlcr6qqwKnSCRfEsrYMreW9Ne9kEA51u607NYFnPZYjPvtGgDcnvusmWaGZI9riv1G6aAaCanqsbrMKuwM4ahsnmidWFcz1O17kW9/mmNmE9/92P6V5PO1dLE938/ttz2P2NmWu+q6nU9NZNoVrzpWJaBqmhd8+Mz+YuG7rb1yCvzVoTke0qeJ9WNzhZcTMrUZni/m5O+qCo7kQZwaXZttK90+6cDOY7h9vgG60AJnHss8Fx5xff3NQK8uyfqG7Fy9VaqO69sREYKqeJ+D3Woff8+2rXzUP/93YLz7j/Yf7NU/zd3384xpYvwUQ+d3APUfn/nglb13SEeG6/+o//drqNx+/5HeGYf2zzktvHr/pPfd/Xbz7b3jzPwXkqt9AoPvl0/eX/f3ncn/MF/N2r/9BjTFm9vqdyQDIHVXoevGxHCSlmJqZwRdFOQfMajP0OQB0Q9bi5lbcslchCVamjojmZMXxaqsNmgO/eQTmSj0CmVpVD2WauyzP3SAiQAQhZhYRrhl/I7eqSEO+tPmQ2cQtm8wRiXd4MSVIK6jGopgFgoONa8trhUtlggcCXETUjbSY6XGczc3d9Mi5k1pW5e4LEW8hkh4fXS3jZK6JR2eKwNwaciao0ZwfUDgYlUFnXEWmK/vcK/awPMYl6nVUrYjaB6hSPcAOYueZkYYqN+C+dMvFrC9dqzYJTBSb2DScSxmGQ8a4O9w2bUMCIlr1PcjPTk/XfffyxStSXp/0q0338NGDF89/ebO73V3f/vqXv7p69erl9c2HH3/48J3H+2kYc8p52Dy4bPtuddNud9fDdpdDFxCb1erRg8sAchJjb5rmwfnFB++/l8twebnpmma/26f9IQ/jpl8FltA2QaTu4UJsAARMTWSPbReaVp3ZlMxUkYu5Mxgs0VyZjUJsGuFQa548JdRYOgiZWWA0DS4vLk9ONl89+5LIQ5AYIshEKqpjasqCzWbz8vWXxQYEFBQqVEUDiMXNdPJhGFMqMEQGM6xQTlZUS8l1TzT3GELf9yGyFYNb08bVuoutbScE5JJKI2t2Vp89pSpJsIAkqGw6sjvu95v2lmiJiJZVBmZ289oaxuf1YMcNuG7iRhCrVINK0MKc/Sn1g7bIVVTWALOzK2ZtZQCEuREiULJOIyXOTeHt7bDd79f9+uRkY85MoRQUNVGp4ixmrmpmVjRP0wGNxyinZ6vdNjcxEPmU9sIxRnCAaklpIM0hOhEd9gmpsN/8+svP2o/On7z/+Huffvvnv/jF65/fmqgpUTG3WtrnMKnCX16VoauvWBskkxGUQUag8AY0RHTMuNtdbqCS1pYRwp2ferd3zI+j1gu9Yd3v99GY03nLan7L1Fcn994+5JgrB2v9ytF43lOpcHcidgqVperE1U47G8gl2pT1/Q/fO3+wzj4eph2Yg7QxaowIgQJiRnKzw2EbuX/86HK1bqEwFJNQW7TVKw7CWop7xVn9OC68OJcLev8GglWBOKphAtHR2a0Off0Q6N5dV5s246zzLZPOu1NNZjJDhSyAhI1rCAoOHGPT9avVeu3qmsrJev3ek6c/7n+JLT7+6INvffvdzUk7jLfvPH1UyrDbvx7G4eXVzXDYnVw+jF3blLi7vRJMbct934zDaDHAVZhKMUvF2FnIfZzSNnR88XD9ILSX44PPP3++vT6cbE660K+aHkrDNMQ1U0yD6rg/7Ha3wrxe9+88efTo4WXft23b3Vy/Nh7dVSQ0MTLaYQzDeJim8cQ9mQ3Jbg95N5Xb7b4RWTUbYp3GXJRzns4vNk+fXj5//gIcD8O4as836xU89KeDEA7jVm1qmkYaYYFO6bA/DMOwOW1Xq56JYhOIOZVs5CKilveHXd+tmhicOZujZBFqu3YaBi0GrYbISKiTZp+26/Vpt+pzyrtpb2IQYIP15drgP/7rH7cWyES1ysG4qedUiilvpGmimo4TszA5qWbhhlmN1NzZqRZacC1XoZriAQyxiQhuklyYxES47fv/56++XLdyshk26xMW6lbNiIk7BtCsWzfLagVgCREhtGQFOSUCRHhSxVFhvVKcGDABBQG5wRmqujhNcyRZd/o5G4S7xT2Ltde+MffxDSzLesG66E38mohsyTw46mJH3abrxg6fS39YREup9UAQEDMH1qpUyjA31VqTBrRwWxo4EkwMyNv91jTPYWxVZgFJiIWyWnJzIjdTz4WMeCad1VCUoWUWxJqzYUZgltrbwcnIixEBQmYoGcwIymaWk4uY1ZaiBmJiESZ39ZILM7ubcCCiVd/sw6i7Yl4gQCDl7DAJEtnVs6mnlDwC7qrqyVBgTIqZykZmVghEYDfyMWdVlRicnJnAccrj9evSdi2DEGsS10MIMUZZsDhVTZrh956s13Z1s+mb3XKfJ83ih/vsZdeayrtYk4jmlgDuQHFNiRCp+mZcfcJC8BDCqu9uvnyec4JXmShFAUWijiggAulWodJJvzo7DV3Ttp1ERoC3zMbD61GhJRfPlk1jZBciF82WoRAchoMiaZ6KptgiMIUobWj6dex65lCNL0IjXbfWwq8MaRyDiBntdigFMUbedP3qQkMJ1AbG5mT9+sVXbUsMF+HH764/+YN3k3+x/QzJhjRleOG+jx60oAlNbNdZNZUhlZRLgoN6FIzlMKIAH+GPf/id//Dnf/xH/83HZ2v93/6vn1486H/woz97vhvLF88070F5f7gl58MhtasmdjHf7q93e45gDjc3msfx7OxsHDIykM3MkJEMjcS2bTg7iqnr7C35snE5agoPrmDMpJ+aL2aECm87KsJlNGvKLmHjXCP6Bno1b/Szy1V/Ir1Xq7FEKXDQW23Q5rTl14LEBb26Q54WJ606OIth+VokS98Ek31TFOpvXMfCSCLcs3R3bs9M5rjjRdxDoxbzB1m4GG/For8ZIjhGsSKyOBXLXd6BPEDdLYiOTY2qU0FEAlErPvtmc+A0D97iR9f7r1DbG0NcLTHhzqn7DcdbL77huC33sIzV4obXPRRVYPSONfbW2H59cI5O5n85PPKvC7B8M4B1xCaOv96/yd/lEWo8d+x79dum3T/yvH/78W+CYf3Tz3tcrvXX/5Ir/EYI7Dc93/ujSvPueTfF6yUdleCxdCirlFM7WrfaEuut758tOB2tK5zdmQi73QBo7Q91zB0SkRECETGbQV1tLDVZVMvTshVPJhFOoEACkDDPItPOzHDPlt3BDGlbYiatZX2CBh69aOV9AgwSNF3wyIWrxBTcyEyhbsXEgyCQec7FFeocup7MbUpFzVUxI1zzANgS/4/jRIwYI3PtNmaqyiLMLCGCoWRDHngkKhWwJ2IwiRsIZY5QAVJzRzandsGEFnjh7uG6H7uosugM+93bXZKmYCxE7BAha4XIkRlUzXE1ArX+YAkkXdwdVkIrqIlWJgicHexGRgwWkhBJYDClAnfXqpdDNaVtAeMwNX0bQri6fumsDx6fPXx02fZNKuNZexJj+OLzr/7Xv/iLh6eX3/72x9//7vcfP3jnqy+e//hvf/LknQf/+a//6tef/cJLaTj8zWf/cDXsf59oKoWIb29ePc5P0Ib33nk3PHn/rF11HDCWdx48+sM/+MHe9+M4jeNkak/ffee9D99PedjevobZeDhM+0NJSae8Xq9Pu87dx/2hTFPDIrG/usGDB227blmCZh/NhrFc39yMg8Gx6s+b2Li6EGp/ZnMbD4f9sL05+B/+/sdfffWVJmdHiKAWD87x5N0H52dnr1+9IJaabh+G6bDPsZPNGsY6TQMIh2ncXDRxtb6+HvZbk8hEnqbJ1MEQcIih6XizXgU2eMwJaSrjpOMwvPNwLaAYQ9dG07LdbrtoXducnOCDDx+9/uyL2HHKLiJwohJQAVYnWNUk8LvN/J5BuP8Di2BJTpnN1WbM4W7DNzNVIiKeEbGamHcmS6W+uxqIiijrOM1ggRAEUiW8FJpKyU4GdhGIMetoaICe9ochb/nx+5cp74c0pBFNsLY5ub46OPT69Y5ITOo0ba+ur6e0FZEQqO0CsxO7CDabPsagJQ+H3ThZG+jxO6cff/K0aXBz+6Jojg2dnXfjbhck3ByuXt4+O33v4R//+x9+8OH7//P/9L9szmO61rK31ckqoNnt9kAVHzNXgytgTKBAM6MbgSvdW2dKBJaEQTXPVbCcZRZyYeIlgqmexNsm+v7C54p4LTjVzDqY8xlft/HL9xzfc3SADH7/A758vAbdi2mH11yAuFMpDiSIc3SDDdP4x//tt/7gR59I51+++DU1GF/nYiBC38dxKKaJgOEw3Ny+noZEUr7ze+8/+9Xnf/e3zwomAogCwKoAWMvRRZ6DcRaw8QJZSWXx1csyMqLaTGKpgEIFTR213etxH5yBVwK55WOlwEKXA2KV1hWgsvhJnD1b4UZiL9w3cS3Scwj04tnzX/3cLy76d5+8u9msU84owDv4/T96//s//LgVf719xm169fLZs68+b/vmMOmrmwN//vLDNq5ON8+/+sXZWt5/74MHj89e3VxT03Xd5uLswf72No/7hvjywebhk4shp1fXVz/5+59vhzEr9f3lyen52cmDVvo86u5mdxiGh+fd5YOLh5cXDru5ubZcONA4Dq+2z8/DaaL9zXS1etCdbs7Gw/azX38xDdsg1nURAc9evd4NUzIyaRXh9e3Oijdom9ioWtu1QD47777zyfvPnj3/+79/8fIVHl+sup6maXr06OHF+YPzizMRvt3efPnl57ubm8NY8gC0eP/D85PNxmH7/eF2e6u7qd/0680K7KWUm5utcRCSGBkh9F1Yrwjl+rAfLSqYV/265CLMGvS73/8uET3//HkpBR2efnTx0ccfdmfhiy8+//H/+TdoUIaRTDwpBCSct3Z9vV29u/YVdtvDbrdv24aFy5izHVDmbLmbT2UKPhMLGFRLfWHeNDH5ZGaxk6RWSum6FW6wj2q6D0273qw+6B9rKdvbw+H24FTGXJP9oY1tRLApmwJuMQSJ7bjdQwjMVH2FWbJhyQQQzVqeLHdZQqqV2uRi/AZ7yl3tSLieF4nUNjALaFUTbm9mge9cSsxk6rfNgoFlNipQjyHCqRKaFIUSVa2HUthg5kohdDGKsJkVLcIsIuRs6ofdFhW6IzJVL5jGTCnlnLxilAZNBgOpz5XR5A51UzoKXVc+JLE7NKu7s8CINJvwXPjCgGWbcnI41AF2VRjB3Mld3YXMrHghpqr2CeHN+enm8uzVq1da9MGjB03XXL+8mm5HTKRWz4lUclatwqYQqrJ7uRSozl3XaKGlEvqHs6xVzYqWVODQBq6ha+L60UMzG4ehpKJ5nNQdrqXUxgLMcTa0tZeJaRV1Nv+aCV+emt/zt484/Nx9m0yY2a024hEhlkBGSuauIcSu74QxDkOMsUjWYpWKVfW8bGcQpITbtI/dBKFhn9WBM+AU7SoQi5b/j7o37bUkObLEjpm7x3K3t+aetbDIItlNsnsw01IDLY0GggYQJOjvCdAf0I+YL4KmJaA1m5ojkb2QbJJFZlUub71rLO5mpg8ecd99L7Oqu9XTFBRIZGXdJa5HhLu52bFjx/B4+ni7bDbrTdLEDvVRUVUVvOtTBzPm0Me4bZbMNp1WJ0cTjalvu7bbgnVms6IIRrLdbdtuF7uWMUmxa9sUm7TdgAlFMXPhKElxuxZPLoTTENiIq9lZ0ti0a1A/WZz+kz/56Lt/8HJ51X35xdvXX1yv3wRv0q+XTWvBYDxTcqoCU6M0f1Eo+lDg5OT4O9/91r/87/7r73//kyZe/fgv/t1v3/y0mpCrpm8vr6+7Dbm2mrCpxLiJEX0vl5ftYtFwKB89Od40u9W6Z89Hp5P5ZHq0KI+n580m3bxeLl+ttOujtIFrYiai4INqtExzU7KkSENkJVk6PRARBODC0VChSlBjgYpqVLJRV4rGdn0E7NP2761jM80apOzGji6qcKxj8dZd+Pn3DC0HhjkPqll7ctOD4/0udR+MQz90flK5C/wPoZncZJOZjc1wL3G3x2WqsnofpuEDwO6+cztgVdmMMmOgGthdW+19bmCw1aDckjWv/cx1cI6TJaJ7vtmDUeTo0LHLYPSeCQXAOZfPv0cG/ta7NIwf8D6oSkopv+KcOwQN9q/n38rx+/5BfLCT4AMU6O84kt/Z8QEAa38995CLDx3/2NfzPiaVb/Ges3c4jAdO/N/reIAv/s4e1d/xd/cTn0ai0wc/tn93/y1ghJ8Pz3YXiDx48QM/jAfTl4hspGHfZ8YdLkJT4+D4YILcrQ0bk+fI2Ww2QhbSGS+VrE8ghTM4cK6yYWKXExOOXK5jlry1Z7OBTGtgADqwJTOFcxzq/t6awRFMRVUhUB2BsiFZjyGjTyNfVjPqY2RmSUlNo8ESsbOkmv0tQvAhSdKkltJwL7PgTVZi2WfTNGdRBI6Ncj8fQ5FdhVy7bH2KlNirI1DevUR1TJzepdzyDed9dHb3uDJv7m4bM9PcwdnuRLAAQFTVNHBuRcgkuZcjgLsny5loBlBGWcySGdQcsZHgrjicxllJRp6cY++YlJTMYtYiG6SORImoT6lrOxSpaXUOhKIgZ7fL681Xu/NHZ8S827SbLbrdddf0FmX78aYOVTUty8XiYtm8ulqdH80Xx8ci0pnBcVVOT89Pr1ZvTYSA0odJUR3VU04miTxx17RQk5iapulF6sm0qJ1zJWSaYiTRkv1us+mbzmAhBOecNA3UilCgds8enQnzdtcZRzBHgygmkxOgg3FdTUCu3XUwZXahcKGoKq2quppMmslkmlKMXSpD8GR1hU9efOvs0TynVlNMACRFEUkJJVFZOQETCxCjbGeTKZjDznwBQLvYST+ENqLJMk/fF0xmisx+ydDTbL4Q6QFT065r22aDxE2zq+vJ977/3f/4v3ylhcCxQPJSycERxEQ1FPx+wuDQwuQgaz/DBqOUF3MWQRCVg2YmNDjaYwiiNAJa2eUahW+HRgYwMzZyREykaiawlHssq4GR9dKVjD27EHyYThe763XXJsAbguPy4t0NSEWtLIuYRIHpbNJ22z6Kz96PZ8DadnNze+m4ns9OXnz0zBfBjLs+zefTULhdu14ub3trJ5Pi+KRaHM8n5cQSb5rlm4vfPjv/+PPvf/zP/9sf/ewnv9A+VtV09W4ZMJnNF8v1ypkz0mQxS5fklThedGZWaOY93L2cxQUNZsawrOae03bEo27yeOzh6Ts/6eBdGizOaHWH8475yAc85XsbimGsTBytyFi7Mpi07MjlKiMmEMMDHgRATCNI2SHrfv3hP/vB/KS6uX335Zsvjs9PurYDOxNLSVM0CJwhxiZ2bbNp37x79fLlo88++dbPf/JGXTLLy0DMzLG/244Gdj6TDiSEXG5FH9gYjYhyCwwzyyrY+x1y3B7HOZotXa44yP5ovmgb5LOHICHniQlGOkT3xky+2TVta2xo23693hShXJTuW9+rXpyezE50u7tYbl91/fLqtu+krWaTUBShnvt6uAembAAAIABJREFUbqbXy5XAV9U0FCBiVTjiX3/xqp7OnQtVKINY5RmavnrzRZu65aZZb68ThWIyS9RHTm7qnfMRYh2C+V+9+uVXl+H87NHJyZHzLhS+qKswKTbr1c1mWRRu2axmPKVdWt8ur5fL2G2Dp10LI6PAmzaZL8q69KHqBU2bYizqelpRmCzmkqJJd3Y6+/0ffvv1VxeTCcBJlQwJzsMZSEWk79q227RdgsIXKCsQqGnaZrfrpVeVUNWz6dxM3r2+fv02Hi0gvZRV7VAQwZfFpJgVNNlt2j616/U2ad/FLvjga//846dffPHFerPOT/L88dnp+cmuad69e+fhVCmos2ipEQ7BB5/6qJY2N9sgrmtadOCSfRFiG0UEZBlrMMp4ARxBFAbzuU8K0KdeWESjJBQzuMDr1RoECGKru21DZN4TBw4F9YhQjWZQT0bo+r5rZd3JTijBswQZW5fqqF+sIMvqk5bAUBkdk4fBXi6LHV+5m/Q6quzuv2J7i7uX+R1rXnIQlm1BFmse7fOB4VAQ0ZhJNIA8eRuwMpVB1oWcD4ANOj7BF4UnbzEpJbjgCl+YWuol9/iDGTs3IPIpsUPhfHQGUXakHhaNsqazQk2BpGZc+Byckw3K0DBTgQyS7maAMoygDE+sChm4uuxcALFCJKNhJsagkg1mzgaxKUPbtqEK5SQo+WpRKrRtW7GB8+sC++DJsalJ0oF2zJQBCKfkzKcMoJvlwmsI5d3ZF+x8yQQVc8ySEsyYHItpLyZmqpEjGaBKamwEURo6sELHAmeyuwAg2ysbqvvH3fWAWjLoqWVCdDaDgw+cm7eAbGg3xo6YSET6XTMPVcdkCouAggv2PiRNOVvsqwqG3a5VBjywA3kIDGQp9lZAe1Bk9FDCzvUUQmBH5BiS3QNm7rpI2BXOXJ7b7J1zl283p+fTsnZsXrWPXS8pbdex7wDFpEI1KUI5ub5tv3p9lTpM68mj05PzkwU5f7NujXpiZdZV96YoZtVJyWU8Ojv6vR+epA26lb765cXP//r6doPYbRDH8nfD2cvp2fmLzz//9iefvqjn5aZ/92c//uLy6vXV7ZdvLn778pPTbRcni8JNfV0HxqRvU9+aiEhCjLi6WfmiNA6SwN5Vk8J6u7ldMhUTN41917WNQiDo+p2yWKspRgf2PPB+sz6I2VCvpmbM8D73IRTzQOAhJ6WmUCB3jLlz8pmyQRgplDbICQxsHhv8CoPCaOi2lGlI+1J54K7u9Gtiwf2XDuExoj27J2uWDP3ocoRyD0h7Py4nek+gmSByGMU/COf3ke9dLKwmg8t478P7j2WsSg/a6h1+8sBfuAsPcQdjZSXf3Ct+4F/v28pjjHmHe2ZDeEekg1bywPkY/h78OxucKWMMbblguYnIHsLy3udz7m/aB2GN9+J9AO+1Srt/N/b/yK+r6p598gCLOPyJh27/P+D4T46rfADA2mMlv2M05/2DiDJk+OC+Hx6HeM3hzf37DvuDz+93cPxdfvcQsfo69OrBCb/pJw2qH1JN+5q5SYfvv8fFOASwDo9BFGY0EZnWPhTxE4iZKf9xZsbGykNHMWiGfmi/cBTmidnxYEKIBWx7ARbNRpx8CHBeuWGXe7FSLrtjIu89DazbPABSScng4ZgIPITTZVUMOr4YO1yImaVcVcyU4QEmhZolidorkjGFMgRLAj2QFRzDx2yjBzPHAw9F1FQTaNA4NzNRRTIGmRskmMmIkEvQyNQkiWHfnyxrNBtTzqnmBzE8FBoZq2P+jpCTc/kGD17diHWZiSLfL4Xp/UXERI5dDp8d5x0063hjYKWNe7AI9s86lx8QE5E3KLLYF7ImMhIJTAOH3aZpexVDUZYGbZr26vri9Tv84A9Wbdf5ks+O6ouL5u3FJvAXnv1nn35alC457sx2hq3IRIRFOtMEnB0ff/ad73SxOz89m04mEBRwUK1CcbQ4/ejx86Ojo4uLiyRpu9tFVYXt+ibGrm+3JuI5S+8rMalZ1sHKFxNcEPC/+K/+5Y//4v/+q5//ZQJPF8cG7rsIArMncmImsW/71qwL5nxwoQxlVVaTYjqflGUxnUwtaHDc0G4+Dd/5/LPjk0XfNTCNsavKkp2bz6fT3S6UTpI6Yhd8VYZpvQjM3NHp2fzsURGjbDbtrum6qOZRFqGsCu+IQCmKIzB88MFxGQJCCCl1KSZJSTR5diDstruzl4+fPfkY9L8KUBRBe0kyNh4lQq7zfC8/9sCr2CdtDnETIhA5ybNBR7h02MvdfosfANKxDh+q2dsxgwNbloPLnMW8xsU4h2xGpmbJlG0IlS1Np7P50ZTIt31sm74IhYqJ2rt3F85xOSnEbLNdE6Xjk7kvnFESSbHvFUrETWzeXb756Nln3sF7LovAHEx7U+y2u6SprCbWatdEmRXVvCpmVdpxsvbt1StLQir//f/w33zy7MW/+d/+/Itfvz2aLRDDbrXxYM4650pmRMxDGwgacvIKNVV3gP6BwKrI1ZFilvtqDfFK9oDGrRAf3vWwTxKOEc3eTR7e1rGX0Pgo772LPZI1nn8wJnRn2Sz3uAINgE+2tKxi7B1x7rYYRXF0XjVl+9l3X767evXqzW+Wm2s3ccFXi9lxu9nFVgrvXEC3kyQ7IlPrN+ub73z74+Xr5l/9qz8L7GJMWe/S++DDIES6F/GjHMZj8A75TgH24F7wsJMYW642urtCA/aNjmi8Zrr37fHMewUtMjCZkeOy9tGJqsYETgxlJMCDGTHK9fWtZz8/Kf6Lf/HDTx8/f/S8WjdvV9tlNXO7dg2iclq/fXNt5J89f+6dN+xi2n37W9/rmuvVqrld3/rC/fpXv1ycnM9ni9IHVottK4i9b5e7dS+pnlfiymQgZvHpan2bupvV9W511XU77Wi923XHp6tPPnk+m027picl71zX79jZo/MFO+xiH3tLauCw7aVb7pyXovRcFG2MdTFlX7iiVEJUa3ssEMDCzNerq2R6fvbke9/79Cf/10+d65ttl0RDyatdt9ktY2qS9JvVpm2jGUIJZniH7a7xzjkXCqa+73frqHFDnAKV3//o/M3Na09F4BLGIqqiXNJ8MTs6OlLou7dvY0oAOc++8k9ePvrrX/1l67ePPj2tj8rHzx53qb989fbVF6/8xHXXqQhVMkmqToI31k58KLbLXeVL7zxc7xyXRUhVEAYSYSjoMSJiBRtUAM1dYMhM+9iWs0DBx5TmR/P50ezi6jLvkwDHFNe7jlmd55QQI1yhoSg1OknUR0HToxHkEjpFinEQbceA3WMAsJwBJmJqNpRJkxmYxyCEDCacFbCGPXgfrx4s4gyPGzASNg/SkTCY8RBi0gBHE90B3XeLHaDccXhoeJcMY4O7UVAl94DRrHAGkAQXfC7ahSs5BK9JRQUuZyAouOCc05jytXhmAcnQBscGbXklkKmaqYqqU8KgWG+HCLzIWNEsgCPnM3ky1ytgKBgfetZ4l0Up1GBJktFQYMQwU9Wu7zppEiSUfttuYoriBC5nQ8HesXfOZ2J5n1ObpgRlqDlzTmFZSXs0O9pGY3XsPILzjoAUeyhSH9vYdq5zTLGLBL6Tl4eZWk7CDhY6l7UOZfa2N8N7K3WPeDW8xzDN8kUM3nPZBnhWLKVo0CSWlZ0lpdT35EikFwqF924aVKjvUpSkvTCRn9S+8BZV+uQkOLakYp253leTOhQFeXbm6mLip65xu6ZrrMdusytMObik2q+2ZXJlDceUou22zayuF7OjqqyKUF5drIOVLFKyq6vKiFVdxTwJvYhOZ2VdlT7Q9c3y3UV7c4V52bbPCSgUddtbGzehMufRdl0oi/PT4+Nn9bSYTsp5laYBs5s3n9y8TdIXSCVRxVwaeTG8Wb8+frx48uykLHi5vH539WXUZr1dX9+s375VZnGFPH1RPPrEwSl7xw5mydQRudPjOpmPUZOhDCGmpu+R2rRdRZWmq1K7iUUVivNi51rbIJCTBBNfhyK2LYGNNftZCjhyzCSk7MgHDweAelK1pM7nBIyRGBSUa1yUmHOLFhjAg3IK67iR6cFmPlgEiMYxaMvVeXvA2sYiGTucSYdHbox+h0zRSIce0e6R2zDamPtffv+EoPdepMHfucOYYIeEKSJS1cy9Gvymff1gbiW/j0kJDJa9ovxBrDpce76IcaD7ri7DH73ztwYdAiPmOwDrECMjQkqKwQIMoiw0tonc/62mJGMMaiBHWSRhfze/Aaj6uoPuqAMAIPcRwK8jVb2PDO7//v/X8WEGFsaLecB1OvzAPxCK+4bjwc/tn8eDbPPhJw+lzR/mlscH9g3Qz+Fj/mYg6f/FWw+Ob4oDv/6W2gGK/D6SeoglPbjMrx3YXTabcHAD7595ALkPqBYfGBVGs3L4c9m+qOkdDSP7HgfpxOyNDb85dL2hITOSPzYEUDrC25qzSDlZub+huWrNkTNWFwpjGTtnZXqDiUiGr7wLcAjOJVFSYTgiYuPsnBkMDsY6tmWGEMg8YCYCx94XJEicpLPc9YnZMbPn0HWNaW7QfO8uDftT/o/BQaEQ1VyoyI6N1TlHbHmHypJVYwMamCJpAswPwo0YlB8zXD9GWUYjmAQAxJmNs3drsiz0uGPtFw97DyayTCWAK5zPjjQJdNgJ9m15TYbmQrm5s6hmpm0GJuFBGWR0RM4RSJKZJrPEMM6GH8Tki0BiMedvJQElRKJqUhPvw3QS376+mB+dzBbzFy+fB3cpfWr7XUw9OZrWtZBFsyhoUtx2XelIHSvR2fl5PalEuqqqHLNXV7liMZnNJ9MnJ+dPT8+P5vO/+OlfASirsqpC1zUFV+/eve2abem89x5qZVHMj46m04kBbdOYGROLpK61Z8+e/eyLXzuum3bnXGjaLiXt+r7vExF76lNKMUaQKOB7h8Z8CswE077v5rNZ6jqJcVIXL56+mM9qsxRTt91tT06Om2bHTPP59Dylpo/R+i7F0le+QF2WfdtxsFlVl+UkJa2mxW7bEdFkOnUsVUGtGpAkdTtRZp1OC+drsx6Gvo2x68sQAJyfP+06UZO6qo9PjhCQBC7rFUcEH4L3KUZJyQVHQzfAQxsykNnvbNGe02c43H0HQvV+3VNuhZlrCJlzfz0oj+3zBn3R3Dt56H+ZT0TSiwJQaBpmGYgH5QXPQISkqq4n00mU2LTNpsWTsqyqSdfF65sb74vzcNxCb65v54taVYuyIPIx9gQQF955IojaxbuLro19b13bvnnz5Wy22GytnlTsOLiCJpUIxV77XrBrnJSadl5lufFk6Z/96D+rwg9MdHX7r7e30YSi9YhWTCZgtk7JEwDHnlx2mIYwx9g02b6sxxSig35fXqIisu+RNXRLGOiXAGV5qntxKUarnR20/ASyAWdmDCC+meq9VN1I5diHs9mIANirox/GSJZTkjb+DihHgKZa1E6SltPJVnePXyxefOuzN+9evbn4bZO2EdJrnM1PppOJ9H1RFCbJM/UM7wJ7q+AJ6fzRyfOXZ9UJbK3ao5yUTNx0nWNTzU1daXDJzZwRWUYJzYwJcDywIMDI7dCUmI1MBTY299hPyzE/TbkigAetLx7l1dRgCvZwjo1ZTdXUu4IDm0fw3FuvqrFPRfRVVZWuXG2WzKh8ZSoXV6//6Xd+8PLj49kJbZtL5SRob9aXtzfrJO7tu6vNWo3LZ0+fq5DBleXcs12++fLy5q2vi1BMU8Rm0zZoSVIB0aaVojVPFMJ0UfZw6yb1EtvNuu822/Xu9ma5vEGzxfwE2w3U+/LytljufvvbXzYNijDMlh/83sehCI7p6dlp6d305NHF7fJyKaHAs8W0k9hEk1a4SotJOD07t0a62K+2O19Q13aXl5e3y7WKPjr3P/r9H/z4xz9f3VyZJefq1XZlFtsYuj7uNrsuwTMVhQ/e7XbtbDLvus4EbRPbXWq7tNk0s4k7Ozs9O59fr15D0G57Ak3q6WQyrULdbaXrerEEp0xWTqpQepC+evtFk9bFMR0/npyenZw/Of3Nr169efNmudyWWpggiVgPFufIWTTrwS5ob5q0qqtSYpKUYvSeyBhEamSqltsnZFwJhLwxs8EUbQpVuUsChyfPHp8+Ofn1l78BPAKHMpSFQ4hR+hiRBPBZtZrZB1McqKqDCZ6Z2BFRAlTNxCDmQABpEk1AUkswMyaXFQmzEiEoC0sZcvf5IX4cAe1D9yxb1TzLRyAq24O7vlF7Tyzz6ked4gO7kDf5oZ8LAM3yCKNHN/ggosnMGGAkVW1bC05ZlDRJTN4P/qFjXzJTGGp/4LJEWIx9SmoGypVu3kEJAjM1HiCbrJAFYJT9Ga7C0UDa5f02keWdZLxuZRvEpkZjpshLPfUC8pCkZOWsdM51sYsQsMlO1NTVPKWpRE3SW2a8CpmayZAHzfA4mNFnFoUNQq8ACI5IyEGQ+igmIHjyGU1j49glyTY/E2swdlm0EVbMukKjt0b7RMOgkDPsmfdA98Fjl8FhTiqmzrOx6djdF2axF8vViA7kQGp911POIUhHREVdmLHA+iYliY7CbLEIIWyWy77r2Tkak6+sbj5dTBfTvkscuQrOmwORKxgFqCI4ShL7XD5psg/oi2l5NDudlBURe6p2t2tpLVRwntlpPSvn02kqkPrr1aY/f/SYWbvYqSoUhQexv121/NVN17ZPX5z266bTFaJ2Cna9hl3k/rZZiW395PxkPjs6OX36EVLvu8ap1oay62zbyub6vLX4H//qr756/cub9W9OFmdnZ4+ZS9XZdrv98U9uIvAvitP5ExIvfWur6yb1vnDzspq+evfOex+KuqrKpLLbSN/smq0tl6IGk9Ru08RNQ10du2LHLVqj2ikpO5ZOnSNSzgrAzEzEIHjn4AeVBXMggrEYsQzQkoEMDkP+XnUg8VBeezlXnHeyYSEfBHI21JXq6NTvkWC6sw0HX8jB9kC9PLQv+7zXIKTrMi15RK8yZ5mx92TMEILDCBo9iFvvzd1hQAfR8bgo9jHjHpQ49EXzJwVCBwfoXoe7vYMqSfYejZlBTbM4KXhsgjBcQl5Hg4uVkTXNDhjtCxCyAPNYD5Q9X31fZmsYKgbPK/dDHKwsBnKbZlj8MNi/a0M5BP45ustR88igHbglRNBkD7zBe3f4IPQ+HNiDG/sAPMm39xD2Ohzh+49y/+8HuM03jOr9F/+OiMrfIuKeB62qe5wC9yGkf7zjEJR5MKTDDxy+/gCH+ltv3AfP85/kk1937J/og39885n3paoYp9cDAOtwhA9mz4fPawYiul8Bu//WXZ0ZYTjD4YS2w9MMKkuHoxo+xjRkFLOqKAaMfE8Uyh/LzCy1USaXmR0Ne+1gxpQGFXMoDJK7RBk5Mm8YGvfxCHLnspLx/DxcWrYJlAkQ+SLd0Ft0LzlBhmRjlw02y4gSEVFuB6bO2DMbWcaVSIzZERwrm5hJZlLbHYqPsRKKXI78GWQQIxnujycO5Fzh2BGZshmUctZUhujTTI00NzHMrAMa1GfMzNSU4TEofB4+lmGzGKaAZQ76CNPdA9hghJxRGrYin9PQBmOoiCpGrXoyNjMimDPRNDiEnPv2EQdHgY3B7IhYRETEVIwUrkim4y4p7EhJ2cM8zKPruqYrigpHxyc+tBfXN+zqqp4eHZ/AiIHY9tPFVJG61FnXgQ0ui1lKPTtywa23G5C9eP5CJXZNE9tut9wWIXz0/OXzJ08modptNj//xS/YsUhi74qqimjIUde3q9WKgCoUi/miKMt6UvsQYopN1yYVNe36fpd6GOqqmtaLVbPru2jKRBT7ru16GBz1IioC58GClGLXU5ciw3Iu1JKk2Dng+GT++Xc+KctwfX3Z991mszo/P1VVZvLBV3VIEOohGkEJxEmoj11KmYCkVV2WVbk4ElWr64qcOpdEt1CfJIlYWRqT955jtOmk2m1Cu1vHvvchHB0dxw4afdd1RL56AblBv+sBQvAgMtUBGJV9S+bDRX0AoNwxdw72rXHePLQY4xpUzbmvcVaOH9vXPyALnez/NyPWABlEDZmSBAenCiNH2fEnB5DtdtvlLoFQTsqirrqu73tlp8RkQEoUU+q7WFa1c2TmvXehcD54AKT0Z//7F9/6ZH20OA2+kqhFUfZd6tq+i23f745Pp24yTdJst20f+zpw6iIiS99L3CX9nq/TZ58//dE/+e7Pfvqb3/x6OZkv0FjX7vykdMGB4IjJDX0XBgtswhlcogMV58NlvL//d87S3T3NH3h/589nGp5a9niQsaaDvcbeV1LBHUr1AX/C7n3IkEXLAACsyiA478SiMVmpW9199Oz008+f/96PvvV//Id/LUjGKqahrOqqYiIf3Gw6bZo1VIKDc9Q2m7qaHR3Nu267OK3+6e9/99//6S98DXYAITjfdf0Ize1toI4Q3RA9Dr7vcBctB62AyaB+rHfG+cArH/1jEDKeDxqU8PMmcsfsEuwfR5ZzB1K0pLHrU1vMplWouW+W7BA8O7a+3RZTs2LXJLtcXSj04ubLy5vrL1/dXN9KjJCIq6sVcX28KItydnW1LZx2vW223fLtm8cvPolqm23bNzukfhKcmyReWFHWxs6M+mhtTJe32z4mh5ooTBYnkylUSYSmc5mUdZ/8tunXO/QNNuO1v3638oEJ2uy6SV08eXw+PT5bKNrmZrnrjk4W2053bSz6/oj45GTe+2hRm66puFwul6vVOqVbApjKJ0/OXr5Yv3u7vL6JZQEwlLpkIpKSAgQx2zWxLqUs+cXLT64uLl998dvXl2t2WMx4Wk1C4fudXHx1vahO1pvN7aplxtOnRf1kNikmzWr55u1Xq9VaSEOF43Cy62Wz29y27y4367oOXCfhbrvdrJab3bZBRErJo6RIiORRQEgNTC7nz1TNOV9XVSdt221zkgZGqmyqYjAxKMEGzqRlwVtHRAQnKoY5ylmhTjbNBqaeQgjOl4GCaYT0EMBVkA4x9hTNokMUxEHmaawSVvKB1CAGMROFMZSyL2FJIQT4nPHPc1RANlas3OmO5qj2/dWcp7YNPtz9boN3NuTgHDaa9MEiDz3sLHetyZkqOAz922lsfmDAoPSee70Dotr3opxUTEWJmNX1sZ/UE4jl3FiWVM89y8wEBPb7KHnIWuZw0hzvRz2EetmVHIzYnUADkVlu00s28ifojmKiukeCkG0GzLypqpBWhtzDR8U6ihA4z9NyVnIZm6RRNMkgxSuaA1Q3lnTzQOlgyhnWnD0gwJjNkJAgpinXHJARCbGZ6JAABMD7wCVfpuUzG+mgJUt09xzveeV7EszhMx97fYspkZLkusu7nXWf3DTN7XbMUspDaKUrijI4z+RCpVEUoKooi6qgTIBWMyg7MpcDbMu4Ydt0NVcQg1EVytm8LhcFFdj0u123Vm3BcB6aEBxCQB3qwFXqXN90MP7FX72bVJN6alVtRSWPn5S19zCVXjbrLsUGnNq26VPvQlgsApPbtTFe3PRx8+j5Zy6UZqVY671xoF7EJ/TNTtXKYrqNG2mb64vNaiWXb5vNzrqe1+t+tekjpgpp+9tdcwVCKMRtoiW9vo6bjcWImLBdUt/6cjo1IoghetLaUnH5eh28FpXVU3beVVpbEdB1G2y0R88iCb50jsHG5KS3BKJEsQclgEhBlPvYOAwpIaMRUyExUgNADBJkVVIHwMEERCYDsRuZ3qScSIYoC2MDvP1yzlMg+xp3UcrQr88eTKH9nMorfGTM74PvAQEYtlAiyuaBxyqPEY/B6C7Y/dN+zbH/1IOAdM+xOgx7DwPPYTLvc2xmRDQUD45Y0v6t8RJHGGH8MrD3Wsnuxjw0YddRRvD9oFsH8ddRfAAP3bL9sO1DHtuAVIwAmQ3MhLsf0rH6e4BEMKD4D9OW4/3GAep075L/NsrR10mDHfzEHQTx4DP/2HDQ1x0fLiHcRykZk3OjEvbdPf3a7pv/3xyW24Lcf2YfBH2+Dv/6xz4Oa033/3hQgPp13x1qYgGMV4qvQa/w/rV/nc0wA4zJsWMaOynsh/H3AiiHdfegzFidqUAJQtDcxSabugGFyci+mpgJYCDH3jvvnHftrs/3idnYMUOFc6mzJQXEiOAcGxGU2JiVWF3WgDHNgoL3LGAujMr+WbYR4BG3AmFogzhczcO7NEBcDiBV0yS5KRJl/rnBVBUJSbKduwcQUY5LKXd7YWLJNC0CGN6TL0LwQVkBo8GnGaaqxlyQaARSNXC2YsMmQHBZfgHAAUY/DDl3tcdAZ8sQnO4vZzR1+36ERpZbaoBUmQgebGwKTaYyNEDLaVAAWdHVGEZgR+wce3LBU3DsR/RQDApLA+NYVTMOoWYKDbX3DghiXsxDVZumrWeLo+PFdNb/5c9+URarqq6n9WS+OFpMZ6lrZ/OZmTVt2/WxnhUnx7XGrm039ZNH3nHb7i7fXZzMF8/OHvVdX5Xlo6MzTui7TpNwxfP5HMDl5WXXx7hZRQgFF1NHDEmpj7EoisXp8bSeJNN2twEwmUyn1SSmtG3b5WpVnlRPHj95c37zmzdv3n55tThbJIUk0ZhzpQrNgryD0leUZAkpRWi8uFizoizx6fPHz58/PTqe9O323dWlifaxXW+XIsn74L0QEUyItSjATmJsbq+3MSJGhLCdx3R0dFxVVT2pYoxAR0BVQZTIUHhStdnU1zNXBi+C3Waz2+wuL7Fa3i4WODt+PJucRLib69XzJ/rP/+g//8mf/+L1b66LEBwVqZO+Fw8E5ph6HnPf+53+cP8eF/v+rWHpZAd7cHfu72+5usLMADfStvLqGLovjfsvjRM1Y9aZlkCUtXszJM6OSNhDRXNOMUp3fX2BLU6fl6ePZ47p5vYGhOAdksAQmNpN29feLSYexN6HIhRFkU0rEz99VJwenx0fnZv505Mu0KSchdlsCkq7bhVld3Nz9e7ydrLA4rhU3+5Wu27b76YzPTn5N//nn758/Okf/NEPv/tG2AsaAAAgAElEQVS97/+7P/vp//Q//s/d5YaYQl3DwcSKUKpI7i5tlltoDWriw1ocaEWW49UkigO3yw7SCXjPETn0KZG7/5GBKLtFWeMiB+K2dynxDzpU4ZiYHYhNiaBqIKckKaXG1RCHb//g5ctvnZ88nv7419dnU7gCi+NS4cqyVJEihLOz0/WKumZbBtOYbm6uJk/qk+PF6nb56Pz0T/7kj3/256+btJY2Bp6wQ2wbdiWBWLPDLkNZzdCsloCsEDLOPsAIxGqgTKoB3FBwPt455MU6CLLy/hZloRBSEFs2e6pmECUAnIw8sXdlQoISEqEjaQWd+uA9kwmkj2TM3P7Rn/yohO6aBuuua7vWVkodFwglHj0+Oz15cX72tNuln3zxK0Y7D/J73//4829/5/mLj3/79rfrdhdTs9x0u83aWc+zaWUFwXW9F+ZdtHUftzvxfkLOSbTUm0TRpJJsfvyo4mK3br96c7VarwtfQsV5dmxFwdfL3jPB4tvL20kF8eHx+aOPH51vVreb9a2vpkLbzXbrAo6OdnUZXOJVsxGLRc03V1d9F5strrAM/Pazz86/8/mnq3Xzk5/+sutiNYGvERx84V2B2IlHUZUVGTvnU5NSi9SEBc+LCZ2cnJweHc3ns0lVlqG4vb1drm/n5Y0RTk/O59XcwNvt9vLqul8aJmgUxtdhalLoydPTp5+dnD06nsyniPzTf/uz5bttu24RYeJIHIRIyXsXYxSNvnBGkkikU0laVbW0ad1G51A4gACn5gA2YjJiJs/kYNCUwORLV0xDhw4Fzp/Ow4zXu+V614LNBfOefKBQV+Sjok0RHOAEfaPoxZmHL8zBuAuFqzgwOKUUoyGjQUZQMiU2g+YmeyAFZwb62IuZMBIuAALDBqIlvsFV26NVw9w+MMlZ3PsDYPVghEmHMsDRUBODVC3XohksYyIwQ6a8E0hc7qYnMdpYbyROs4DmpK5Tn2InmlRVNZkhkjcj8t4yHUlNR38NSgBz/kkgjVws2nunA4Iy7DqDphNBDVm62EjJzAQD4WKI/7KPlnXZxYgZqrGVpNL3QswFBxVJksgzk2ennDhCRASqGMkaIyg44AHMlmP4wcvKwLqogSwOPCtHjpg1QSUrZI302zEyxSCdytkpzu5nfj8Hudlt3svtDwmKvUXbQ/dDQE6aBslCz95MlUztYNwKE4jluZU1yjhGIeqd90aoZ5Xzgb0TiioCp6EuiIm8+dKjsmJSwGnfN7Ftm+1GokFRTYpFOZmUFRUwit5VdUXESZFijEwouUAflu92m2WzWe1MKtwUO7ad61yh1RRot/3G1bNy4hbzolVJMe127aZtwTSpJrOuSc1utxGJ0n319qKu4aqSHBfe1PTdRee5rPxsu9KLN18dT5pup7/8+Rfv3uI3r9F3GKpZt8DUwymCBo+igC1X6w36Ha1WMXUEJUTbbtLlWwmT1qK/eiO3l6tus+y2MqsfcecRA1JZL+bPzj9Rxtury5our66v26aXFqlIruBk2qGLTplgCmOFQ1IbigEdIE40642oZWWn7B95R0O3dEdGDGKldtdZyvlAy63GYQyAnTPODrcNiyYHKch5eiYmMTB4P3+G4tKc/rGx5tDu0G0iRi4gwZgewoAcjb4hjYX6dt+5uPNfkKuZB9j5Dm5/H1Gx+wFy/scebbiDV/a4kw0Bl72H4g/QOt3VkD2AcnKgRRjxOx1PozTiUaym2UoyiJTo/REDnjzoDtbJcaW+b5Mtix4P0MoIkN0DjHLE9uHQfm/BBizx/YHk98CcqxxwGJIf4h7fgGR98K1v/u43n/Af+3AffHUPYGWR/z169bsf6Dfc0HtwyQHysifCZaLyIfR2yDb6HV/LIYtqP4B82EEh3ge/m6/i6wh++fUHkBMdNBn98ICyReKR5Xl/bO+f8O51u/eZO2fi/odDCHvcUAdA5W5eYQS7h8vJY3EZwOIYG3hiTy4LyTiCAwdiR+Swh4iYBkMw8DlVVQXeRsRlqLZjJmAUg8hNtU33bKYx6h6ux0gz9wrIzXaG9LuJEoGNTER6QwKDPHkSWDLAUkrYU1IGB2Fw+4gp96k1UzERMjDYwQXvvGM3aFForjLINdJqJnmkw0nzKGjA44FcSsVZIlYfzuqBITxMAjOjEbwfvNPhDLx/DBn0MlMigIkDe58l9nXwlxnEcEzkiBiuChyIvHPBOe/IsQIiKV+FqVoSTTLSxfL9IMfMnvIDhVOQuQJVGTigrEtfBIN7++5yMpmqInZps9lWoTDV4F1wZNBeRDRan7p21XV6PKtVJBBPyvJkcdRud9v1uuBgyVa3y+1mCyJHvFqvX3355Xw+22y318ubXdu64GVIploI4eT09OT0VIG27xQoqur0/GxRH8GhaZpd39XHc3hut+1vXv3N5SV8UNMMwopn8p69o6p0oaRQuaKqQgh55oFpdStxg2dnx59/7+WnH728fPfmdnktEvMm1vex7TrnfExptdm0fUeOqmlVlGHbNBJZRzoekTnHZioSm2a13iwVHSgWAfNpNZmUk6mfzcu6DiE476nwwUxUOwJOjo+fPH4xn51I5BTt5PjcU/nqi9fXF0vPnpk1JpOUH6apWtbMHWiaI0I6rvc7T2LwqcdjXz5x4CDlNW/Dmt/Xy905HDy4R3ADRjvs8nnqjxIfRHAMJmJmp6wcVCmiwpMXp1Tau5tLY33y/OjkZNF33fXtrWNMJpVzeZqLaipKP5lUBjPVYWsYAGM6O35ahEmMenmxfP368s2by+2mcS4cHR1NJpOUdLPepNR5T0TOBDGKJoX1KfXzWZVix0yz2fzRoyd9H5uuu7lY17NKNaW290UQkfG6c68eYww0AqYhEZpdn0NbSpRvvu2RvbuVzpzrgt8z0MPP2OBvDhZotO/jcvyG7e/ASr93ZgJgSkTs2Dv2MMqdvZR6CmJAOccf/OFHH337URvXX737SuJ1F7VPWBwvQlEfzecp9sFzVQeGeebZZGKJLHXHx+cvn38MYzaOPUz1pz//beqMFAJxvsqSW2NiBoBBCXqnIrs3vEb7gI/2pKyBVGV3E3PIYYwRM+3nb56WeXshGhg5+RF4Zu85OF8EZlKzUHh2FAKLRscaY5t6eLLzs9nLZ4//+Iff23TXl9fvXr/7crW5eXv5Zte1KnZ0dPLs2UdVeXR7vfv1L7/86tXb5fXm5u1NVRYfvfy4nExuVste0SXZtX2foi/8yfFRvZjBV13CtpXVtt9s+7bT29t2vdl1rarAwRehqsrpzbIh+OVt+5uvrldLzGYVUQi+mM7mJ6cn3rmqqkJZdcmiQUHkfVlXk/lsfrxYb1bbXbPb9qbJO4ZZ227X62VRhPlienN9RUZMnGKSqEAoq3o+m/nAXd9cr5JnY8fOkXPMOZtkXPiqLmd1OT87e/zio48++/xbT58+10jXlzcXX13cXCyXV8uu6YlCXdZlUTsuVNBHTTFum4245Gs4h0aMS6vn+Ox7L08eTadHJfsUY/sf/uwXaSXdVqlHMO+0IIEJe+ejdIrkSlZOygpV9lyWPknqYiwCnGcQkzGrIzg2R867ovSFN7KoyVi5ICq0TynM6eV3nhw9WWzjZrm9FUIo2JVwgULhyGcWlVoy68lpCPCeimDOKbOhdL5wgRRJNCbJspnIbBwFxCCD0jmpYxAbI7OUzJDVsHK9EO3T/V+/jjP0bwMh00YMa9+JLLtQwLCID+CuMQmBu5KazOGhYYMfBHb2gVj+Fo9ZQVDuE2gMLjg4djAUHGIvMYqkpKIqZkjE+5COMZLNAFLbr9o8wv1v0dhRgvYB7N40Ya8ImvcoA8xy/eYQAowvArkXiGMiBZhZetGkZV1OJhMYpWTenETpuz7GKCr78J4UMHJgp5wRKDYj4lzzOIBOBHbO9iMEO7BlccNcsiRjpZIi5wM561aZg5ElwDCWnQ4Q4n47Ha/1wJ27s9zgLAieLVumiuYSAwyaHBhvEUZLikHTEJ59Shol9hI76Tk4CtSlLkofrSNHroALTCX70hVTV87KMCkMKsluL65j08W2SxIBU4193yZti4LrKngGYI6pcEUdaot+eb27fLNa30hsUPCxpwKi0qbYoG9is2qSUFVNzLSahphakdS2iNGlTru277ueAO/hfB8qH4rgQvDFJCbX7rQMi6PFKdStbreq3Ee7XbZNp11CqFDPva9DKhkOrsRkxvMjP5k4A3et7m772BHgID0IT54vzp7MnPPNmpcX/c3bePNWbt9he9Furrr1ZbO+3jXLznqzZKGsppPpfH5U+CLGzmDs2Uh3TWcKCjCCD052WWYhK98xdCghNDJlMWdwgIMP3rFjYsfk2XnnvXOpj0Q8LBXHPHQrHulUOaKyHN0Ndbd7B8PGWG9/YIguhpBhALsO3h8cgSGSevi+gWifQb/D0rPjyHssldw9x+br6BF7e7YPFT8Yh+455nsA6/DLo4dgyLEz6LDd3r2gdW88BlT60JwNpJO7YnLi/VfuDea9Axhw9v1nHsTm+289MOD7W6v7qzu4HLO7m//Bu4dBSe1ewdb+DIfHBzEy59zh5WBELb7uu98wjAdX+s0f+4ccfwuAtacIvd+R6ndzfPDiD5/Ng49lxC2/u3+Qe/RtT2X6HdzZBwffcb7vzYA9xPMN4zlUIrMDrlN+QPl48N3hAvE1ANZ4+TkHY2ONK+5Wy+ADfOCr7wFY+BAjj9kdDtUOhBeAfdBrdylxAjEyHSxZz955z8xEboBOOLDzzI5kwKJszL7ZAPeoqiaEEZADaNA8zxT08cPIWuVqQ5n4GDEbLGdi2Qww0gGIV8o5RuRIW8hEoXAgBwcxFYOZxPwEMeoiAONegMwTVhNT5fGbjshnRrnBWNVU1MRMQcrQYUhkNIBPY+nBwElhcuTIkTo11r1JBI36hAR2fFcujgE72CMMB4mTO881w3rkKFPhyDERnCfnXShc8C4E54PnwqFieHKO8y6pZqISY5+SmAqMsqLhMEEsE0KYXQbs1BhKAjZfoKxC7sKbRLs+dm2aTGbbXbO8WV1f3ZpK7LvgfRGC92yEsgzeEURM4qQoHOFoNj+ZL+pQvvvy9bs3b9fLVd+0t9c3t7e3KSbnnJp1fX98suhiv1wtm76tphPn3Xwxr4sqFMVkNnFFULOiqhYnR0VZiMiua66XN+v1xhyo9r4oYLRcrbbrddLExM45U2GCYw6OqrIoJ6Gs6+lsWlWVL4Jz7L232HKJH33/259/9+Oj+eSXf/PXfeyquigKX5Xl9fXNbrdjcn3sN81WVX1VTGfTsirWm93R/LjwIQRXlqEsyyyXRpS6frtabQmt8+KC1VVR16GeBOcBTWbJYMeL40k9m1WLoqjPT5+U1cRRETv1rppMZovZyS9+/qu3by9ZydSgGth5JjYj1miWaYPZxtBoEIb1PsIFNILI47I++G8ufKB907qhgUN+1ner3mzPnQdscIYG5P3OAhE5gLOaE4jMiXKiYNOT6tGzUwq63F4endbHp3PnuW13XbebT6dl6TOHMBQMTmVZhIJTijnD2XWx67qUFHBI4eZqs11361Wz2/bvXi+lI4todt3yZh1jrwJ2lYiJ9IUvp9WkroKq3N72T5/Ubbdd3q6Zw9NnL168/OTk+Hy73X351VdJkg8hqnhy7JyZQQWm41VjUHYfYaesFn7gTxIGCdFDMHDwJR9Y3dHGDk+DB4w7Pz4yHt4bwp5viH0PNgLaP2Xs/2SNGSbigYZgUErkpKhJgn308ckf/5d/OFmE37751V/8/G8+/ezFze2KXH3+5KwoyllVqfQ+cBk8M8oiLGYzGKaTxenpuXdF8OVmvS3D5Ec//IN//2//VMWaXkS0qiYpCSE7+nvNDqIEU8sTcshHDKTXYejEANHQr3YEvrLN5wEhJDfCATooXw9R4kj6G6ExT/COgodzLgTnvXOuqkt2xCwpRu8saVLD0bT89nde/ugHn09n6e2737y9enO7vgYjipVlvVicPn70lFC8/urqV7989cUXXy4vm3bd7zYR1p6dnsFRJ2m13XVJOokGDYWfziZFNREq1tt4s2yul7vNLkZh0RIoyVgTpNfUWNfpcrNzvlQhqJZFUVe1iDoXJtNJKAvTCIIvPAdv3l/e3l7fbnZt5wLX0/rm5hqmIqpJJHYM7bsmpq6q6qoMt9e3/v/h7k2aLUuS8zAfIs50hzfmXFlzD9UACj0BhCCjtKKZKJoWXMoo04+AaaOFfoiWWnChjcxkMtJkFCHSJAAkAQENoJvdVY2uMefhDXc8Q4S7axFx7ruZlVXdaEAAhFNlLzPvu/fcc+JEeLh//vnnVCK4btu123C52CDQ6fVrR6eHvuD7D58RQ0zJJDCHzrty0swP58e3b92tiglRsVqsu8XQXrTnj84vHl9cPltcni0vz5f9IoYuhl66zWAKs9nh0dFRXVdD7AdpowkVcHRc3Hrt6Oja5ObdY6Eh2LbXdQjhL37/wgbFAKxM6tkcCpkZEEYLigG8KauBQQTw5itWELVY1j5Nn8SBAkFLqkmIQIkhHpGBHaA3AT2+M7v77u3msGrjBjwMofOVM1QgLUpPnAAMlt60Vy+elLQVHUwHgyAQTAcNfRyGGNMkTsCSACboSgDVUICMyAjTcjUEE1BDy5zqsYHXVznkOR7bEXZG05IBLEpBVi6zxRH7yY5LauhhZmqQFcQRAZO+UkaB9gFfBAAkyi0iLHE+FUCBkREQFYYuDsMQQxwLIQ0IgLNZodHApIvQrJmYFmriiGdn0SxJC8AIZmWSWPb6bPw3ZET6yo0dQcC8oik1uU5xOIABERE7EzA1z4Vjv1yuQxg0SnIqc0yrgEicEio2Qko4itsnWg2CZT0+yN8BhAYaNcHhmHKD6e+KoDsXFW0fuhpBA8Lc3odoD73MDueuOwilxjvJm84TJWOEu5OnoGNXXbp75pSKKBHZFR4dR4tRo1gI0IsFw0gOyRmQASt6oAqoYmOLIiLaLdo830RjDFGGPm7JyaQpq5JFAoLUVdlUTcWToYPF8+36LFoABzXHwgGCRA0RxOIA262FNgDAZtO5EkT7qpkw1n2Pl5er7SpaFsOC42t101RVXTFXAGUcOAyIwCqgCk0zPzw6QkIFLadVOS2mR5P6YEKVIwfHJ4cHh/XhSTk/8L7C0EvfSbuNAB6ZAIf5Id5+7aiZ1NtNeHJ/9ezhdvE0dBcQ1xCWfthAt46bi255vt6cLy8uln2IVVkdHx0dzGYG6jyxc8Q4DJ0BEqMJKKiFXfRDBJx6MiChkhlrauoLDGkfy/oLmkIIs9REMk0qIqSUSUWiHM4n2lDylHL9bZYBsdzQYA+kGH0s2/cu8nso9VNIEWgqV9xPrSFgklnZAVW4S+GPXs1IHWDaL/G7cjT2DNgVpwtf+PnqOHSkIGQMaxd2vRhHE+XJj/mGXgzDRxNDQAhAIx81OQbMnNDqvIaTqcKXL2YfUdpxNgh5dyX7Gd+XkIfRYdvZKyAk2/HC7Oo79gDGrwCwjIi/bMReuPFXHanX2T7488rv+iIZ6MuOvwGY5as0sGzveMlX/iKE9HfhSCO+T5/bH0EiYubUOfJvqwTyCjZ+cVrvjldOvhjjzuLso1cv8ePS/e5DjV/kVe6uA3bbLhLuTUcbqTrpfV8V53z5ZWNqH5kbHKdlmSrmLUcR4/aZg5FUeKZRhACE2CUcEilrPWTFSeIU/yZhvtQRLzUMRBsJoAl/wivhmGylRAzMjbkCUTMFAkntwXLxDowxEI2+SLLf2WUzJiYPJBZVOI6ooijQaELHPKHtWWYEMEi7jCmreXCIRA4RTU2jMqKKWEJ+cvyV+kiDmoImR3QsDUoa88mNHbUaR2WE5LKNtBmiVNVsCaNMO0TSoMDRnU0PJDENUko1PRHWtPmZR3DExqlcAM0QSNE6S4Vr6eGkZkGJzQICxqiAyGaAZEAiCiaphgyMqLiq3yaiqGKdiEVFjFF9UapAtwmrzapdRwSZTarS+9J7UV9Om4NZ05Q3Z1W5uFiw2cFk+vprd5q6fvTgwaN79ytfoFjFBRM75733zFyU5XQ2E9V6Mqmmk7BZqckQh+Pjk9rXvFo65wDMCKppg0yPHz3+9LPP2u02DIGJylldhlk5m966df39X/21frCffvwxGIDqKA4ijMwOy7p0TVHXDTOHEAkphHByenDr+vXX3rwBYA8fPmRE8oSgKtI0Tde3fdermvPOO19UXgidJ18Ws1njsVIZomjauqIEA3DeM+f4wXlFAoPOFVRXVdf17bZj4qpsytK7SVmXqnpB5B4/eKZyJpFvXrv9/Nn5N9751vHx8XwyWS42GLFk39SldGHoB1+6VnN9arYMRPYKIvcIRCPuLE4yJuNi3Hkk4wfyLLWrGYu7k5opMDFk7lXutQMjzAMGpipJVdipRikbd3Q0ayZlDzqbVac3TpB1265V42w+OZjMREJobRjapqkKXzhHIQQAcc71fR9jNIO6ntQlP3j46OH9J87Ny7KZTg674bwLy7PFEgCggK+/c+voeD5vyra3KOypqMrSu6JwKnHVTL0GWy2f3HtUAfhvvvubxwc3ptXBdtt++uAeKGJQzr0XDMws1aIhIAJ72pXyqmYiJL5oQOxqtEbzimOCYj8Vmey65bS8ZYnVJPoJO32tpKjyS+3cO+sNagoipqkFISBhWTsqFJy+995bdVP0sqqq4uR03g/BlXDj9PpkeqAi2+0aUaCPEsw0es+F803TTOvZwfx4tVotz9cHs+O337z99Te/+Z/+9n/+Z3/y459+9JB0dzs8+nsMI5sNspSYmYGhUeJajRMz27cvCfVz7Ay7kRxDzjy+o84OWO5CQUxECqZiBfrSe1cxDNIPHbkUaUBZwOnpwd07N99687WHj37y+OHni8VawjCbzsuSqa4KnpP4h/eefPbJ84vztt0CS6HkihLu3199+JP7g53eeevGB59+DB4VmHxpFLoQrY3BeLkcFsv+ctP1ClygKxiBVFhClD7EYRMjQF1vu5aM54ez0tdDOwDCZDph5xaXy75fSpT5QV3Mqoh0toh6sV5vu6DtersuyM0P5oXzq4unfRdhGouCnW/M+sXiQkTLwikYoe8G2baXxN4V/uj0+BvfeOdiOTw/Wz1/cta10bGb+hlCRVBWVV3X00f3nq5X248//KR9tAIAcCOoaAAo27NzuMgPanbaFGVd140v/eHhkWg8Xz+rZ/7u2zePbky3cdEN682wKioSHNq1wZDoRIRAJmCiYAwIogOwAZpYzGuIAAzNzHmu2LPDmBWSNf8azSy1WlFAw8IRq5ECKzg4uX5YTatoQVCOTmar9cqXLlowVDVDwRgNlAounC8sYAgSul46hOg4aBwiDEndD2DXSdkQNGmEAwoQAFhSj8/pArAsF5o7WIy3MQ7flzppNpKvX7mYYd/IvLQuxogMUk1eiqQVRg2uF00CjMCSoJkBjxKigqYaTcARmLXr7RiGcdaDItsZMECAXZOQcd1pFqUDiXkR56VtI0w1Rs4Zz0kFoLv9Jouc29XN7rxuBDCQKGjGjk0MCIuiiEE3m1U9aapJpaoQQ/4KuvKqgRL2lXJ3YAZKktUjdjR8ywKvaKCU8LckP5TTAWjGuc3EmGHcj8EVdxeJOBY5E2OGxlJiUxNMhtkFRMq1CJBTkZaaI41agQmntMTLsdSsIM8/w3RHBkZM7J0woKKJiCqUYAgRgTmmhEgSDlNAiYotmBEqX+0PAYIJV1LPymlTFYwAiiaFc9Nm5lwJkTfSDq1aB6CuJy2cMoECMnIKwmOU9VmUeGmN3rx75LyfT5qmqtC61fmqFSg8lBU7LyfHp+xUhEK0tt9u2wCgYINIfzCbHByW04kzBLeJZaGHExJ0wVzZY7XFo+qAyZwbALrtKiwvAyAUdaEDMtFsNnvtzvz4pFGxxYU8un95+SzKmnEoKDKBA1WNg0aV1i7WvZ719XppKgRY1IVzzjk2gEjgCkogiEqUYOAh9RlAJgQmIU1trJKfgBnbJTAQTY00JXlFQI4dAqFL0ummairZ72JmEyO01Fo9T/wk3WZjnhAVXsBxRiuy71mMTQMzToSICDvG9+ju4Yv/j/Yzm4f9ukIc00sjnHy15l82SS+gV1c26Apew9w7SHNPd3gBvYIXcYms174P2o3eqcHOFCSWIirqzn1FwLQoNLWoTxrCOwokvPB1Vy5xbmZjhXtFLP8F9Grkl2R6FVAyKrID10absEsaXJ3nFeiLATCxmn5Z8eBLP195fBGP293I3m3+bZYN7h9f2oUwHUkp7YvDkW5yX+H/b/74ImgCexjWDo7Z15li5i9KZf3NHPvP/qV58HMvYzeN9l9Mj2B3pyN8kHuOXn3LK+dZsh5JAYuSGu0rqVqvRr/2L+yF1WgGAEQIwCKAI6if2jlcTaFxSULyFsf8thmIDALoCkY0IExa3QamqjEAEjLRyPUcS7YNAEHRcjXk2H1GGdhyF2FTE0MyA6JUpGQiZiBknDJSlOTTUfFKZiKX7hCamAEgoWN27EIkCz0gg1LKjCSNlezLJRp4VhcGA0vWkYgADR2aM3aOkUFBTFWUQExUY5IVBUJNeTYxGeGztA9B6jyUxxt2YWx6mJi8LCAEYwBAIkaU1FjXMlBo++KvunvICV9LpTR58ogJAKhJKnFUs6S7oaYKNkCAHUJvlmXInQNRxFx4L0CpjDyKQQTBKBHAQeFKRiZGo8jAcbBexavM59UQOmIeerGIKoaB1use1daTtizW/eDuzsqpr5qDk9Om2R4frlebSVVP67Kp/NlqZajNbBLj0Mwm165dOz4+PjiY1a4eYm8klxcXVV0V3oGqDWHTdeGg1WiisXBlVG27Vpk2m80Pf/SjP/p//qjv+rIop9PJ9GB2+63Xrt2+defu3bfefPPew8d/8sHHB2XPXDEqaWoPZQ7MExeuqH3BTGxmPVp478kAACAASURBVAyhPz6af/+77x9OJ5998rOP/uLDt19/zRj70EeRyawAc2qy2bTNdFqWVVWXm6G3qEVdnh7duHzedm3oth0zQ1UgahgGswGsR4PSw7SpDKJGdcxNXROgDL13xeHBfLVaTyY0DHqxWC2W3ccfPWrX0FQlfqscIn37/en8YO4rDyswNVdQVVfrPraDuSo1dt7l2ZIbTakV1ugb75YzUFqlV8vxBWtitPOP9gySvehywKhcm6I3yHJ2O9cqp/pFzFSAE2DNTNNZU9VeY9dM6tm8Xm4W2+22Kev5bDabNOv1WgbtVn1VFszE7JITlja1EAUMiLiqGsb1agWM3WSKB/MpbAEYuCDyGE3azTCd6KSZHpzMtmE5tJsQgi/44Hh2cFy7yk+P5vM5xpb/9Mc/ODi48ebt937zH3733sPPP/1f7sUnfXVYSYgWUydQMEBL2E/KowJAKoBWUzFCQsbURn7nmhla7rWdkq1X2/TLVvvKVFy5g7tB1DECy+Qie3X8ezXuhmNNjhEA51jRoqkJRknlKoSK0ZW0ihEY3vr6G4+e3cMiHJ0e33n7zr/63d8/Op2//fZrbRfOz54tB6kK6s0k9kwwKWv0xqR1VTR1OWzkB//xT/6z3/ovjo7mgvbtX/+VTz9+AOFhNfX90BKVaZZlXNMAAGQUMEwuNRrZGKnCbuffTU3dv1/LIOLefLZM1EJI3ToSrkGjeFbecckUyNAxF6UvCuoGbrtuNivJcOjAlTCblkcH83kxfTAMm7bdtGsEqyxGCyQMEuKwffT02XrdFUXRVLptB1WY1pMnT7ef37s8em323Vt3H//r/216dFjUjMwK2oqEQfpgy3Vcb6TvqBN1AjFoItCIQOx0GKDv4aDxl2driziZTk9uHWytM3NhUNXh8eNzgxAEynIiXgYIQwTnIQIt1pu237737psHR7OmXPfb5+1WC8fVpDKw8/PLxXrtqSjrUmMsq8pgQJGuX374Fz+809/93vd/4zvf/eYHH3yyWDxZraH0w2RSVMXU44ytWq9W/+GPflCYHzatn04IyQRUgogAGAH6KaODEEIcZL3YfvLxZ4vt5eGNWT0tb8+vVysop3jnrVP2cvZo2V4GclDN5m0vD59cAgIiMXlJVW5BHBMhDDFwQUpsKgkJNwfsGZFcwWQ2SEcMaA6VlNkcgDA5Ru/VJEWBakPQAGbgoJ6XhrLZbttuOzuY+YKKklBYOVX1at8PEKgpG2Y/qEi7ISQFQwTy3qIqqndUFtVyvQVDAELD1IN+ZIjvwJkc2RhoanVFZoqZ5bS3bl8wAob5v5ywGhc6jNA4AQmMGdyd+wYARlf5S0NCFMMr9cy0vPRFc5HteobNFQAt8dMZkQRATNAwE6gCAI7bSoKZCZEwldQlTS8iFAJL8tb54ikHcjrGwPmCdrTdfRTOssnbi/GQsoLCVSdIHXcphFEvHQS0LEsGhAgevSO3XFwC0RVol5rlKDAxp6A3uX5mBqhqRnjV/NlgVOQ2k5RiBaIEWIw4ZBLcSeUXIwyHaSvcIbuIhJyJaAnAAgVzkHm8V4mg3KAVSEVGc2cAo/BOQv41NUrMTz4pgxsQAjIyApVlGWIYuiGCmgp4gAKB8vUBmytdVZRDHDrtDDmaxBBB2aODlDUmVDRgmE0Prh0fHB6XUUPXbx0WVVHPq8Oqmqq4fnHheQncgyD0PZczgChRQgjMTClPq9yu5PiwvHPrdfArLIzcxLR4+rhctb16qCc2afx0Vq83y27VdX14fr5uW6lqODmtT06m02m97Rab7XNVCboA5qpsIqsDY+XpYXX++bOmKN2EvKei5Lrh2IuKtBKrorx549rb79yaTHm57GWgy8sYFgDBMLANiMYQCaOSKcCQ8ejA20V3BufCerm46KWdzGdE1ImW3jtfRBMKGFaaHwoQAiqrQupPp0C62/kTG8oMxMByels1rSAmNFRVk2iqaGhEmapniVxsJnkVJNuSwV/CXYHbiGvm8G2EivbQK7hKNptpqkLZ8R9Ge0MGOlqcK39tBxRBlqa8Ij2B7UUiO6DGdt7hiK1imqSctIB3UX5yRTOmjgRXVmnP6KW5H8c+C4REpKY0EhJ3JhAgyzgAgajkfR4Jr/KGX4XW7IfnCb0CvQqHvyzAfwlXyi/ujYjtWzq8MipfDRwhocWryqcdweWrPvOFS9p/5Yuf3ceCvvrMfwM4198JFO2vfuxQw5cGd/8ppiOE8Ff5li+++DeAgu3zHv+y325fuOR9hBWykwSMlBhqKbSLMcYYX3nCHWq2O8+uSeUeTIsOy93FMbH3nhwBQt/3MUT0WcRBNOjYBpkK4sKxR3QpmFU10dQ8hRJaktsKqpmpStQk2qsCEAEIiLnkkoGJGdBUpQtD0gtNATl7D2CqZkHBRhUqSl6Mes+jaqkqxNzeOqWzDECMDQsuGLxGG7ZDbAMoEDIhxeS5qOWkPY9qLajsuCwKTHpSKAYRwFRT9Q0iUrfqxyas6IqirEoijDEgaoxh6AUIyCc3Ao2QmYiZnSPW4GPUwbLrQLlTa0IHCBiR2CUabdKcQEIjFIk6qJuwJegzgQyATExMoIaADj0iggAZmEDsBxkEzAiZHG2gH7fYtOWN/A4Y+R1mClZgUXiPjqPEIIKOqWJkiBSN1diMIxBQAcXEs3NVWddNrarL5bIfeomRyE5PD49PDgF0s3z6/uuH1+bT+fxg0kynk4O6bqqqmc8P2RWXy+Xs8Nh5V5TVwyePP/vs008+/WhW12+/+dbt6zfKwk991W36pmws6MXZRbtt50eHri4j2NnF5a3XXm+77uPPPv8/f///evj04WLbuqI8ODyoJtXF2dmw3lw/Onr/V7/7G//gN2+/dud3//W/+cN//8cffHiv7WQ+g8PDuq6bo6Pjw9NjA/34459eXCwencPX7lZvvHPtn/3X/+z+vc8/+eSj5XI1n0zVbLlpe9Hlavvg/oPlZVhvoSrga+/efOvtO+zc44ePVYipvLxcc1kpgMUoImpRMRLZZFY0E2cQnIcoHaI69CpY1/V2u5o2UwMIIdbN/OOPP+sHrKr5xeX6yZNNCBCHDM3+D7/z30/95Mf//if/0z//51NfrRfd9flx4Yv7Tx9XvujjkJyhnTNjhmIGsKeblgyM2ljZkJUWxg5QpqYqmryKK6GEF82ImYmKalaBYXaayprBdok1QkJijeqcd76QGCMN2sfJG/7m3UM/Najitdunm2673mzbbeeIm7puqgKRhj5u1usQO6JYeHd4MKlq771HAxGrqprZdW2899n5xfPh7KI9nNfvvvPepx8/WC/Wq8sNlySizgF5+P6vf/u1d24JrH/00z/yXudzd3A0aZoidKaB55MjknJ5ufmv/st/evHosnHzG6d3Vqvud37nvxuWDvoCALbbCN0AQEXhmTiGkJKZiKkFTLK9ZhLBIHU+MzMTAQ/gwReOmRFAVE01BElLLsc9yeUbe+ZlHzbFirngJjcyMwMyl+kJOALkmJdzQvoBZT/XAsIgDOiJCjADUi4BSYP0UAQq4fC6+8avvnXtxsk2tq7AZl4F6fthi94K7wzicrE4e/bk7Tfeef74GSLcunX9+HDWbraLi8tpM797587p4elPP/zo2ZPnt26+/rV3fnU+u/nG629/8OEn/+J//t3//f/4v33NoVcwBPKeHSCEtsVoiGSqyKQRQAW8A2ZyzpcsGmIMgOLYJYOfbD/kVHbOM6f+FZZDcAZlICND4qTjYdECEIEjYgLHxCwkESJXRVE7RXWVzY8nvra2Xxyclt/7zW9997u/Yhguzh792Z/+HhGEQc06JLtz80ZVHCzPww//7JPHD2B5DgwNSMWD65ZdkBYKA4u//huv/zf/7T/5d3/wL4a42g4X8+OT22/e7RU+uffszz940BT1zevXP/voM8bm6OjQu7KPYbVdDzqwI1+y8z5uoC6nXTucPT1fbztHAAYxAjDMpvVqaEHg+q3Da3cOsBZXStR+3S5DiI7hYOqPZpO3bl67e+tkVsLy4tFydTnEaMYmeHmx3SyD9yUADX0/BGWG2aw4Opk1zfT06N3Sz8IQnj569uDek+XF4HAStv7BZ+dPHm8ungSwEgeEQR2AikWJZuZK9mUxWPQFgINofZQABFDA0V187Ws333jj9q27Jz/64AcR2pPr821oHzy+qJr627/+7cVy82/+5Z9vfgTQAwRwWnorcODYyRBCUTp01ocNIPhDb2TR4sGNg+NrM9Gh7TdmsWtj2Fq/UQxcQFHgxJACSJAeWLDmosZiQurD5Lg6OJ5EGICiKxkJzhcXzbRpppNB4/nl5XI7VOSkx3YVptTg4GBA2Wq3HLRV6AWiogILgqBFQAETy2m2JGqAhIkEZiiaWNkABkDAHpgRCFWUrFAFUTMUQkjVQzGGvAePsBWLI2WAjEEYoaI45wRNQS13ekh9R8TS6kjmGgGzEFU+cm44x52qZAJmaEAKtEeCcEknjpFAooEpAhRFUZTl6nIBEQDBl94X3kQCRGVTUULw6ABQg2pQVCA10ATKMCFuVn3y/xLcDJxC2yvgDCBBXDZmTzDbQwDpNe8je8F5GjTknLMkh8BgZMYIjGoaIQLA4cFR3/d9N2gURKx95djpoN2mjUGaqmEkjRpFo6mIgo5JfczF90QEBmKqUZIyfypbHGWBwAxUDRUgk3DNAJj9eJ4MyCOMbcNpTMADmCPJyHtm46CRdGOMg4AEDGQIYjoOyfhAHVkGE7NHn4TtosSE1WLloEBAAQ9F7X1REKppVLNBYwAFB1ARN7Un54xgE8J2GBaDDQAN3Lp9oznwvgyz2XR+MP+3v/8DGQAMqhKOD46Pjk5jkOfPzrbbTVPNUTyhM4191262W+ljkv/wM+nA/vE//aavg2/0fDu0ERGtrr33gKDs4fmzR7PZ6WQ626z7e/efrVddPZ0iIkB7+8Z8OomFk7p0orLp4iYgFhPwxbofVqvtreo1aeNysWi367KoTw5P6mK6vNzGoCp6OJvcvnPrL37y6e/94EMfYeabEuebM1k+7xucaqcao4XepDMIhBA9WA1AAD38J//kN56ePXvw5JFR8I3/zve+84d/+icqMj2cdeuu/bSjgTQYCzl1FsDEVKKYYgnAYAR+QnVdxqChHRw6BxyCdNuARZGBVzEH2LAn54KIRFFRiyoCFsUigABEHFtLjVgGJ2eNLFVWaSqI3ReMVhEBEqbUDAFEVVWYeERGMpxNYxdDASEjBYWxx+Euwzniq3nW2RiTJjazjb9L8Flq1QBZdiLVMiuTuwK5cqOWjC0lhkCqgiDihGWZSQaSQF3hdvmtXXxqo5hUXqaAKICSZU9EBRUAMEYBADLarRozA8vooIghABES0/5v04WKZPRqh0u8kjeDPHI89tgIP7c+bK/k5uXfMPqXXtoP0n/pyrOd0Da+WAS2/+KXXu0vwPn6sk/93OPVGlh/P479UYa9B/lLn/D/azTxl/he3Du+5B0///wGsEOkbO/4ud+IowL9F/pEIOeplcOptHLVVKIIhPxeMEPJIggMwEAOmbkLHaSUkHfsnXOO2CV0SEVFNEHkJoCAxJy9LUImkj7Fv5AvTMZKUkIiYseIlKgFSI45ZbTAQNWimalJZmCqiYEBMBMRJwSfmR371JA7K9MntIsMObW5RWQAJmRGMiAzAmUgQkWTBIilGErB1JLFNDN2jpiRGDGlwiCGXkQkChA4R+yYHCcNKRp3ICQQjJaY6olFtffA8WrgTaJkDGSn70KQ7X0mLIxgFKCpIYBjTwYSVQaJQaSPEk0FEiku2XiwvFGhAibxheRlWvbMmBwSIZBIws8yaqe71C0iJ14JEQGrWBikb4d200kUNUM055mZAZFAbh9U09JVZeGImMmTy/slc1E3yvj07OyP/+xPP/zZz56fn68368vF8smzp8+ePXn27Omdm7eKonBEfdfHYUAkYPR14ZwDhKIoHj9//vFn9z578HAbxDeNn1RYemFYd9s3br3B5GOIEkVVm6o+PJw3NYBtmEJdTyQEUA3tcHl28fDBcxU4OYDvvP/eb/+D7z958mBxcbHerEGBCx8iLNfbxXobA6g4R16G/mINjccb168dzg7WFxsU/9qNt9558xtRzVPB5KbN9OTk9PrxtaODg6qo6qKezaZNObk8Xzx/cknmp9NZWVRnZ8+Lop7PZ2VZ3rv/cLnYGngg3m7781XUAIRc+iJ2cvfW7coVCBq69tFHZ9XUrdbrzXZb1U2MqiZEmT2e0+Bj1cEYG2Ba35QL/IDGLHLSuzXbFS4k83SVXtJRUnfHG8UxwkiVvKOIScoXonOOiCAFWKoSo1qcXp/6CoyHybw6uj4V1POLy7btYlTHrioL7xiBRazv+hAGFWNG711Zls6xRhuGkJwxidi3EIKp9I4rVTiYHXTtsN1sk4EggBih9iV5ADLQMJmXvmJ2QM49f3qBWDE3Q7DNujs9Pbm8OAM0cjA/nEmE9Wb5+OlFGAIRpVr2VLlSl5N+WCf7iSM1KKVVASGp2GVLmdElGwMXAzOVXTnKi9b8avHnfCoijvIUI+mexj6sO8FfGHXH0nPNiUQgBkJCdACO0BM5MjAyx4oWFAecwME1d/Pu/OT6EZe47bbrftv13Xq77obBOWyqsq5K77jwRbvZHh4enp6egNn5+VnXdpNmcv369bpqiODps2fec103xB6ADdQ5Hy2u2osn9y6pgFzwbqm1NpqaiZJz3heGaCogBkTIiQGpagJoRAmUf2kj29tYr5gdnAgblLWzDNE4C+WkfcMMQEy9L6q6VJWi4tnhBFlXq+X5sn3jjeN33n1zOqkeP3zw8P79oqzKqvaOXUHEWBZN18n5RXt+3g29dR2FwMNWSEhV1BEyAsaDk8lrd689fvSxQWTHs4N5NTk4W7aPny8Wy16UHVeXT1f9Foat9K2GXmJUMwwim3ZYrbp+FWWwoYuxE4iGxqB5E1IjC4rAVVOhh6C9gFjarVCJbT49lqgIWBdFVXrT0IchxIDIItZu+ihWljUSksOqcrN5PT+oJ7OqmdQPH9xT653XoiBfoHPomVbr9f37j54+GWwrwAgRESKSEqs5A6fmzDgK9BH6GAdFhQaObjSHt6rJ9ZJLAx+LxnrZGAf0piaAMJvMj46uD70uzhbLT4MjInQgJoNIH8nAMYMpoCkJACiokkIB3/jm12ezCTExExnWZYUC0ot1JgNqMBUhYl8WRe3JixWCpQr3rqJq5g21D/16tV0slgqqoEamplGCRClc4dhDRGeFDZCFyTqBoCAKAqBgghDNgUMzMiRjBEKj7FKkyI0Q0ZCzWQAGYkAe576OOjUIgDtpch3jxfyTjPIemzJzmAtVEiPsysJCVn1Oppd2+jUvLhhOCwJGq5NKkxGB7KqiMSnMZxkdSwwOImLCGIZk1t3YW0ZMdiQqTByTIKaACpb0rSHXvMkgBERZ2S/rZaUAN4e64yK2K39mt9+Mm1C2icnfzKrMyZyk1IvRKAyFQABqVhaViqauyozsyZMRKkhQTBkGRFVLXl2m0O+My44KljsVplxstjoEoya0ZnqTjZ3jEADY2VjHDJl5gchMlIVdMVUCpp6QlisZE5K3K/YHBLZRImn3xK8eKFHOcgIaoREa0k5yFYkYiUgR0IzROeeYSIIMXQjRgABKJF8AESiCwKyeQlQVYY/NpKmaBtDC0PX9EIM9vnfpCQpiTxWJd+gcsYm26+3yYmMGfeiG2CtKAtRcVbjKIcU42O03ZoZBQDddv+2Grt+aCpiKiqn1fViuNpt1MGN2heMSCYJsp1N/eloVPjoKVYEqUSWGINt2tdq0/TB4cOEydqtOoxZcOPQmgGaIttlcbLfL46NDQO27bnV+Nm2a2k/6rYA4Z367ahk5xSSmEUHJABmAgJlTd+S6qgl4kBAs1JOm7Vv0YKgxRLnIAUZeBSapF5M5cyVSBUqgYlVTF5V3wKAmQcyIvZO8awOAgCmlqjUw0TwgpppE6wAgqWomJl/e4+gKVdlf3TjGQqkyH8D2BWpSyDR+CseMWZK/GuneOSWU4q0XPJN9g4KQ5a5wFIaHbCwMjAEYr8qoMKu7vfDptGHn67KxugdzYWMO+JLjRnQlZ7F3rzBagvGMugtLbAcPadKG3lszmBRniHb3lW9jvy/q+IudHvf+x8eR3ovaX7qYL6E1ffHFV4b8SXvrlcdXBPX5s1+Qut+7yhcu45Uv/tLHK2/kFzy+SgPr79mRyiH/tq/ilzz+mnleXzwbXs3vnzvRX3lVL31EYewVkwr71JJFVYsAaqpKCADGBjQyurPKjTp22XDkGjfCpG0iIpKwdgNHREyM3hVmGmM0MyJOwMruNjApWCbEnmjPP0jBYAbNZRSBhx1bAUATJkScUqKQWdx5CrGiIWfUC5JcRao7J8u6ipRhHESjrNGJYtlXMwNDAiMkACR2jKyiqpp5uAgxiBmwJy4cESLnEu2UmjRQBcgaMEko4QtopZmlOl/V3PEkYXPs2BGbJpfJrrIdGZDLJYVqEIPEPqooDGa79j82MtxTKdIuNkyMDrDMgU8ohqqmgDiRH0SZPOzGJu0/ItYDAFjStgUzCQAABIrQth0i1E1ZsHb90NXODUGAFB1hwWpYlNYPbPjg/oNHj5/96Q9/tGm3ZVkyU7te991iVk9mk/rOjddev30HS1I0V5Vl47qhRwBfuAk2i+Xy3uf3fvoXP71cXCphM5koY5AggsQcRJYXlw8fPn1+fvn07Pl3f/39d99967U7t59969nF+fmTp48fPX5w7eQkRGWCb3/rvdu3bxQ1HpzUZVX/2Y//HABDiMy+j7pabRab9baV9XpYr9rQxW1r16bTST0v3ORodh3vVqEHC7R8MDz85CwMUWLwpW9msW4KtSjQT+d+2sxms3o7C8OmkNiHIM6JKTKxGWy27fnFKhpUnp1j57lgCISgEIPCAD/58Y9x0Pe+9o3f/K3vffKTz3oJzrMF9kUZNoPxrrI3YSYKkAQ1xic9xkwAoLl/uIKhpSZcuzwbZE437oHjqSAlUy9h3A8J0RA10a+SV57FCEwsw6pmqgZIoFCUhS+pKKGZ1k3TLNrVYrm2LD2fPCkb2yKYmKGCqA0hiKgphqh9H1TASpPIRVXWjUqcxoAPHn7+G9/77cvzZdK4MIAoYAGeP7uo5nyrPjmcH/smDrIyDaDcTI+P5tdrP9ssW0A+O19cPH9mx3pwNO2l+kf/+B++961vfPCDT//tv/r958/PIzJjIT2CELuiLGuVQXLmfdeyAQAAyAgNwSQ5ialJ2ch/SwS1K2b5yyt/H5RJr1DGm/PJx00AE/gIZpZjKgODmGrmLBtmsiSoYSowzMqixYE9mXPm+1unR4fX6/khk9MQuxC7tt8sll00qZty1hxjWsbGjgtf1wq42fZdu9msFkSIwF3fV1VTAgjY/PDIOdcNbS3ts7MnR4fXvvHe223btsvwyb1HnpLMtoACGjr2SBBVJQhEBUV0BRKliQKgIyZ3lbXCHVL4qgOTfrcaQJIVMQVwzJiMLYgpIpgxErIZSoxeDTS0m+1iuYUpfPvbv/L2m6+b9U8ePfn4k0+v3zziAlXUgBA9uEqiDbELCoNAiGqm4NwQegMBxymdIxrPLxfAnkF9Xdf1oZlfLLqL8223VY29i8uhhdCFzkJZDK50rnBYkhp2XQytcghWARFrFBDQMOaqUzqZwDny7IcQg2xLoIo8ECuwRu0H61bbftUWgIzHpWPDUqCXQWIwV9Q1Ycr0eiqbyld1UVVFURARVFMJeL4eNgxFfcBF1cShaKaTo/mNZw/7D3788cWyZU8xYNo1JaMLEBFu3DmpmqKeVuQg4mAsWIGfEnszwi4M9XRibYxRzHA2mc6nByU7Mpg2NTXbInByM4jQFQ6VwxCDBCYqSh8tSpIwHqAuquXl5Xq7AlQzCm0YtiKd6WAgwdAlLKr0Rap8KyqcHJRcF8WU0ZnG2MVh3fbdBm6+0RgqALJzZVGEYKBgUTWKSIyDwsAWbYxvcMSQzQyIUVKNDyYpiRyEXe3eqUbMsuI4MCbWDpqpRCQmRAOyTCxUYNib2gYJj0EzjABZw8VSv/jEeEhNySB3EDIzIlTLoqg6UjNfNixZE8tAkTCl469KHnM/L7UkiZwzVSoa0bMTUANLjHCCjMGkaiARAzGLY52v7hTa9zoRvYTUYzZ9Wap9FHSG0QO8+tDVqFh+CLvC4pRCVEqOqFF+NdtZMdyVDo84lFkSI0MDEBERlTQMZnvGxcbsIexFyrZ/5dk42a5afu/Octe2K88YRuTQxmg/YRamaNkJBdvbn0dQMitvAaQyrJ3rlt5F+YwEgKCgdBWv54gcDU0hxugCO2TUbEzAQ1MUXFXArnBlU1Sb55dxCKZWlL6Z1OxclH7dbk1DHxRakAoATdquh0GDHR0cVFROyql0K2LttQcDR55L8kUNhl0/IDjwwzaiBoRtWLfDdhgQwDGwY1JSpefPhxgjMTBHNWia6cnJxIjicAYEkwl7cqFde/TlbDKZlKtWl60MYgjF4eGtYRPqum4mk6Hr2+0GQIFVJ1MZBtVIZN4VQ4TKo8XY9V2B86qp+lWvIW+KiQSYGi1YD2n/fPLgSVndPTic80CL9nKxWtZNHY3boUW22fHMOpA+WgBSSo10Yoygg5ARApVQlM7IkuqnqRFiWVW+rDahNwJVkQG1D0GUEj6lO1DsyjeDxLDMDj6qfqnsz170N/oPu1fGQGkvytt7x56mQUKzE2K7g2L2lkD+JF1pFOefCoA5Ewqwv02/OmY3A9mzTckq7axEQo4BE2EF98zBFUcKxsAH1YAMv8TWvRDYEuEeqCfpvsbxgtFemhkwux2w9RXUJxtHwK6q7ZJlfvGu02tfuLQvvO3Vns2V4/2LHfv41G4O7M6TmhVeDeMYaH/xJL/g1/1VAsuOSwAAIABJREFUjr8/ANaXPR77xXSm/i4ff+0X/8XTqY21/L/Y1700fV/x++SD5JUNopJQGQUZryHnGsesHRiYmKpYUXpVjUNMO2tiG0HKR6LLnoPm9BMZxiQRLqpg3nkGhpSRujoUaARKLGcQEn929CHUDHBcDYh7tiBVmED2DqLFlLKkAr1PGBCBWeyFR7haE1CPCQNKNAYkMxEDZFIVVdi1E0LSISgop/KA0Ulih6IgCsQJQ0s5iww6mWW9Z7uiO6VNJHOArwyQmhkQMRCoKkiCzpCRRCNgkm1IsqBp3NAEDMiixWgxiAQBSd+STDJi/lQumFdFQlCxGGJO9yZEwshMVSx3fBz3mVRxBqi5YB0NFCUIIoqIBQVONGEDAAQYBlHdqImV1kXqYuEkysCGgXzAqL2R72Wx3v7Bf/jDxao9XzwnqlwnhWeJqlZu2tj3l//xgw/Lsrp140bV1ORjU1bxMiZWTlGVP/nZR5/d+/zB488NmH2BTEPoN/22mjRV0zx99my72nQtDOFBF9aHB7Prp6fXrl3/+jfeHvo7jx+eHsya27du1ZMyWjTQ2Xy2Wi/W6+VPP/qwa3skBnbMvgtyvlw9O7+8XG7bLZSuEOWo8caNa99+//2b10+1D2Fjy8v2k4/u//EffAjTccWmHdABFHDtWnnz9tF6sb1159p8cjx9a3KxON9sFjHEqpzWdTMM8eLiEhGapppMGna1qK1X25Z83PLQtuDh3oN7DPrNd9+5+8bt977z9r/7lz+qTwsw6togokg8roEMt8LI4MlrIa2UdG3JF6C84jW542NuClMe64sM6v3dO6XtAeCqD1/ywgkARDQ1VRIzBGNHYHyxWLxx4/TGncN6RuvNpo9t1wMzlD5VbWjfR4madBo59zMlEQuDEIZhGGKMnLqGD5F5XhRl1Vi76bcrI0ZfuXkzXS7X2QEi6IZ+6CMZF0VFPPQDKqIpnZ6eHs6v9RtbrM4u15tP7z08e/Zo063UCT749Du/9v1f+/7XTm8cqx9++Ccf/Oj3PgFi30x1oMuzy/lJEYZoedBGY4rJIioSgAGZGe30XsauV69CrEePavyZUItc4aOjqTUAM9QdVL8DsmhUsDZ1SZQaBNSQkSnRQ1In1UklmyH0Q1XDrRsHd946ncy5l2U3bMlRUVCvuFz10UJZO2InAmHou7bruv727Tcf3L9/fvZMVBjVzJbLbhj0vfemR8eVL4t6WquAkXBlMbSrzcV0cvTNb73b9cMn/+P/akW0SCYAQASJj0qqQ4wCYoDE3qWbSIhT+mu2NNmmWKpA2HNYdxGdIRqAUNYCyvZHE6UQwVIvJkTPDsyG7dY4DCFcXrSthmIK7//are999/0Q2wf3n509P7u4aKkE9iwizDKdFkU9IQJ2AzkWUw0AIgCIDglVWA0EALZh8+jZw8PDQ5XWF875yRB5s7Z2K7GDrjVoN7EHHYAM+hDjYGUFLM4IKBKoJpIIOXboFGCIPQi4wjX1tKh9228NgNCJDH0Uc0aeDa0PpgGW0G2Xw0oB9bmKXDudeFcQN9v1yowOjo4RivVyraLOO184dg4Qo6oMMWJL1HNhVUkxSDus2shYVydvTA9uH5Ynb5493ZyfLRfnlxrBO/JFU5SlKz17Vm8Hx5P50QzZtt16sbgMoFCUVJKxrdqVK6CoyjB0UcWzq6uicI7NQIc7Nw+6M1m2azUouayKQiMNQ28WFHxBlJqUIJGQrhbrJw+erdaXZVMUhV+cbSQA9CmgH+tQZOj7YEHcoR7Ppic3m+awjCTrfjP0fVQBBmqgnNRRAjnPjtmc60REZZAYhSRKH2FwEIEAgVidpZ4KycEgBCUSFQDFnegdUipkAQNLTGUyACAH5CgZBDNTMEK13BhMUxrrJYLN6F/lk4+spZSNkF1UZDsS7bjhvrQqXjYxADtMyRJKIpm3kM2IQip8S9EeGICaijhmyqY09ybj3ArRQEAkJnpayvVlPfhRc/+V4dAudNzBZzuJ+/HmDRBTed7ex3Z/mhkqJKQuZV8goz2SRzOGaKKY+q4CmiSxDEDIXdnUNOFXu/h1F3nveBrJ+ckY5WhuR0BghDNfvLY0gDv9IdRMbUvihiNxeey+aiNxLCMXWcci7xhji/Md+jWeM88Gs6xeBmDoCHZuZaLCIQCgDDLQwFAiMBMjindUc0VYoC8mk+nxwcEf//hjGAAEiEREQgzRwhAiAoE6AFABE7UIILIMaxJqqmpezY8Ojj49v2cMIiImTp1DAKPodDqrp7PJ7OAo4mrVbpabbR9C4YsiAHSGZuTw/sNYFYA0DMPQCrz9uj9xha8Uy5JMF+ebeVXPm2uEBRhHKIA0Wh+2XduGiY/9JnpTcBC3sr7cisWD+fTG9RuMHMNw+9ZNay+iQRza7aLvumjgnEExKbvLIW0tOmbhLQKjt2AQNQ7y/MnZW0dvTY+mbkGX20U9KxFIwYytPqnDKso6KhmpEXhQg4gFu177QaIrsJqWYSvbdWutkUFVFlVZuKqIHoxMRAZSxAADIEDqYpUf5d66TTTDzAEY1/duvu1csoSz4NjDHGBsWAgj8m4AlizjuDEiGJpqApsw8zhflMfKl7IHQcMVrxATcxAyq3r0Hc1gbF8BiKCGY43ey4t4rO3LhCnNBi0pIwACAoOZ6dXieGGJXV2UjejzHgSe3rCngzWO2wuGaETo7MV/voABfRWUM1oEHHt824sO9su3/KqP77/hlcH7XwrAeulqvww82SWkv+w8r0S1/tqPvz8A1hcHax9keTl2+v/V8cvNvL/cO9OuLbIbqJ+L+u3Qri8hE2agCmH0CXTMAlASlwRiMMrMgIxhmRlajFFVNRoAAIN3Diz17UGi1M3Ucj8VQxMAMYtJSYFMLYkXaBLUSwaRjNK+r5lNPuYMEwXWACz1lcGk60RgllXhYxRmQMxam4qpRS06zykLB6qmAKqp5RcSuOT6ccpjkgFDbgoGaJKMawrxEYnYgfQaRYCIHBNZok0REKOxASduS87DGZjBbm8xYNp7ShnChxFEH3OC4ICRUUyiCKiZqBGDEqGljtQERohgbABMCIbDEGVI6FVqhESIyMjMzES5IwkiALokymCikkrNMAl+AYCpRgITMCQgBgJAdc4Jxqteaen2zCxx9Q0QmZg0ioF6x4YiBjHG6C0SmnPgCyMfCUNSW1SQQR4/e/7Zw8+HAapqFhVXm2DaFY48s2iMfXzw5Onts7Ojk5PDw+PLi4UQkEeDSGSz2ezTT3/29Omzfgj1wcQY+75frdcbaakqJnXVx54LnhZQetcP3Qc//cnTp0dfe+ed27duNk317fe/dffOzemsOTyaA+n9Rw+fPn16797nXd/ODw4n07mkRBj5vus226EbArlCYQhqha+OD5qb1+9eO75d+/rJ04c/+eHHP/vx58uzHgI4xbKqnOMwhGHoFQC3cP5p3y3OjZ89f/3ym9/6+rtf+9rN6+2Dx5+23TbaAOAWi+XT5wvvuawKXzhyrm7KybRRRWhxUPC132yX9x4MP/3Zh2/cvftb/y93b9ZrW3alCY1mztXtvU9727hxb0TcCEdjO2ynM02mM3FWocIiESAB4oEXxAMSop54QPwABP8BCaR6QCAkHgoBCVmkKNULuFJkltNOOxzp6K9v3O70u1trzW4MHuZa++zbRNiVmVgJSydunLOb1c455hjf+MY3fu+3/+kf/ZQMYuDOxWI68a7FPCFhe/F7anUf/pIhDZWHJOIlkXxMoQ3/ZoNBRENuXy/H7LgcwtCYRYfCCxhlwhFAEVNKogkVpVZQ2T2YHl7dj9g9Ovrcq8tlDbk8Jabg12vvhdgiAiEbi7YomDHEpAopM+vYqOq67QhLUbXWSqX1DvR9O5nVcvVg0a5AgRTZkKIEF0LvFSKL9y4lCApsrXoPJ8er9/7y5+0yHR8tlsv554+efPbg3mRSzfZmV/auHl6//rt/5zdmO83xyfmTn1+kdbT1/uzaQbs6UQkqkClomaSfqYqU2xahUOa24wYvfH6le/b3nK8bb+gQyWy+qLmYKLdBgs2dxhF1BCVSwZyyJyDDhSooSgJJkAR7EQ8G7A4c3Jwe3pgip8XxOmhPhsiaEH3nAhlgZmstAIcQJHFhGgBSJRe066IKWAYA3Wm9qChCUVcR1UVnNHV+UZezLixMLJpp+e4334a9/6kUWC8FIhAJMauqjx6RqtJKAh+DpJR7aYFkNF5QM3NtHGc5OZyH2GZUA279q2OUN6QERpbDuE4hIpAmDdFRJSySEPYP4JvffPPbv/O13d3ZD3/4/ieffNKvXVNYH4VQvRMkXzelsYUqmrrcOzxQCMEv21UCF1Kf+3cAEEAJVELn1ndfu+O7pSIkpeXKr9Y+BjJgjYRuLRwh+Ux4kdhrdGJcpJKZTEnY7NQkaI01ZL2JBlsVKKuynk6ooCQxpqhJk5egggQtBsHoY0SBFsQFUA9PTnqFMwXY2yutKdFEAlM1O6S0XnW564hzIUn0HgBV2c/X67pGIACDotjG1cr7xVlcXIQb117/zvfeVSg/fP+zJ4+Pc8KF2bI1wASk9x/f94Weh1ZiFIj2AC1wlNCluFr4aaSioisHe0QFeiEASNGgVBZZ441r189j61Zt7CVpCKkHNaY0wAqcokiCJARNUc72d9v5GhVJjW8DRGQgAlHOyyCk0AMZ21SJvYKUDeweltM9qnZgHX3o+gheDVlqCmYfY0hBEAwa71NKCRQMUUnMiaOkFAN4oGSyCgHyULOrKJoIKWoWZkdFzlW+mj0WHaclEykrM7PNDeASggKroqahQAiQdUxiPb3RkHYYSF6oiCpAOuji4JhAyMoykIGRLwlONKfzsgHRoXXxkLkYZphSAkVQUlYY6eYKSXIB+rjr7NJli0MqCoKQFJWG0xEk5WysEGjjTz5zMiN2NRo2vIyfcWt12TaSIzi9ydaOzmUCpE0omd8E33tCVMWhB2PKrDHUnMbMYOIWwTPbjNGVHIzLZWICN2yQzbr6VBiNW/vZoFekuX/G4JAnyKhU7i0nYwNuyKE7anY8LxcCgOy8bUJx0oxdDWeDmwMrAloakQkkAVVBJUSSlGIfvKIxbNlYQ8zEAXxyGlJJJlY1uOGCnY+6WBrvkBXZNPV0MtkFPoYEGoGAAFGDrC7WUqXDg/3Dg4MPHn4KM6imRIrexa6LEAGmdno4vXJ9p9mbrl2fegFMxpiiLIA4RALlgisfwHcACFCALSGhOu8APYoUYozs1HQ4od2qmPZtevDo/PSsP527s3m7Wq3ff3ihQaqpme6WKfrF2rOBV169eveN25bs3t7uO2++s9cc//zj904eLZdrjwk6v4QYpuV+goCAigIIIsigqlBzGSV1EK2a+aOFu9nXs539vb0nnz+BXsSokgDhYrmI6xjXEXrwCqAtUzGZ1M2srqBe9ksvrg0uOU0ugQNBEJNCCAkxQhAGUVFKYsAQkEBysIGbtrehglQGYEe2mDVDrLf1ytNTHlW2/8YRvtkQMzfWAwA0JUVC0GeiS8Sx1Hd7WuZ5IZpbaF7qz6jIuA4rXEagzwJYCgK0LbE+4GHj1IZxNuRuBltMsPELz5gD1dEiPn2Y8f3LLber2kasRsnfzf7g+e2LYvONT7YdcX/BHp777os+9tw1DDv/VTCEZ2DNL/ru9qlu4W7PDbxfCwPr/z8aWL+G+/XreSR/5e3Fp/fC157n+42/bI/XL0Je8WmTx8zGmO3XASCrRmluX7JxKRjQZGQHiIENqkE1gwAWcF73MXlBQGY2xlo2BAxDpbmkkEiJiC3ZnFU0YFQVBC3bqqja5TqlmFJWP73sP4+MBDDoWuU4EAcMyRCxYWMGHWoYiwRT9o6Esp2W3Oo698xBQQZkEJaoIUqCLAtqAJnQ0IBcUQ7Gc2dB1XwCSbPiDQISGaKsfKGgYAyzwRjFBycQMefcVFQToAKhggyyYgRKmvsXZSwgl4oPrqcMUhd59QAFVESh3LZDVQloLM/O/R6RkUclbsPMIup7Jy6C4EC/AmJkw9aQYbbBhZzQw6z/rgCIhpmJc2Yya3UIysBpJkAmNqwItrA53TeAjCmCKjKCqmbtQ6a8mLGBqqmKgktLRWlLa/b36+nOzmS2w6ZgWxTFBKlYtf7eg8c/+snP5suu87hs3WodfNAQJSZNqgoCJIRoSrO3f3BwuPfw8YMEEkLous7Y4nDv2n/zP/yXJ2fBBa4mhUtx7cKyb10AYw0IuNanGG1R2coUZblaLI6Pnzx+/Oj46OG9e59cu3K4v79zuLs7mVU/fe/P/9v/7r9+/Pho/2Dv5s2X0JguRO+TT9oHuVitHh2dnl30F8sU1+Dn8vpX3vzd3/7enduvPfn8+A//5z/8P/6rP/n858c++bqoJpPp+rQLfXSdDy6hUGnLuqqLuuhWrl/KyXF7/979dtkd7O1fu3blxvWXYpCY4mq1PjlblbVFa3KZgGEbY3Rt6johMjEmSFIYfnL8AIK+++7XHHXduj+ZXxhbFGUVvNtk8HMi7HKBV7j8RZ4KGFRBQK0ZOHhEG5uQpc8GaIow6xQR8QZSGBx6zvRyAAXEzMSjoZgYCQUiIKiVm7euvv3NV2+/fhNs7OIyqF+u1lGgLKipq6auEKHv1l2vUWJSSSKWua7roqiSaBJBRWurqq6dC0+OLtYr76MWbOqmunbtaoz+8OCgKOzpxRETCwCxCTHF4NlgiL2S+OBW6/ZicX775Teb2eHizH346ScigMQ+6bp3q3V3dLp88Ojjv3jvz+8/uHfr5Ze//vWvvvPVt+3Urtdt79YuuuQ6BVQkJoPMKqCKmpQQCdmgRUAFGpKLmm8kZMMKIsMc3H4oGweRRvxweAqUJ+UA2Gc1OthAiTgg4zCGMsNeADF3qgWFCBiVom/dwZ3m27/3xm9995sH1yb3Hn3y6MlnRVUgQ4hu2V50fR8jGIadWXOwe4WRk08FF9PJrrF12znXdzE5ItjfK69e27lx8zoyrddrH6OILtfLJHGxOicmkVgUJsZgmfbqui5r166dC9n4qWiIkYiNNQAqKpg1nyErVivq0BJ2SE1sLWFPlSYNozkPYSBFQkPATAWQITQCIwUOMZt1IjAFRgnNDN599+53f+9b3/yNdw4Odu7/4tO/fP/9i/M5AddNvY4dFywKgtEWRVU3q3W3XHUIXDdTwILLggtWTM1Up1eKnSvV4fX65ku7+4f1rZeuMKsi9k6OTxcPHp2vF049gsfkxCSbelGPKkYjiJcYEikxccHFxfGym7v1uk0u+c67zkkU37vFYj4/v3BLF7qw6lZBQ4SUVGJKoU8qUBZTSRw9OJd8gCRJAX0ICFRPptZWq1V/frFartd970NMMQUfkgvR9a5tOy7NchmPTvzJ6XLVLo1tjK2raXP7lVd2r+w+PH5wdPEQikgTwAljDcmmdVoeLR4/OPv8bN1f9Ouj1fJ4tW5TR5U3NaOFi0W7aPur12sfWsNUFFCWljDF0O/NpoUBt279HCtbWcuqse1j7yNAYoNsEVldTIBQNTSZ1DduXP/004+aelJQ2XU9K9W2ISSVDJ6LgoJBKpFKqXbl1uu7By9VkdtlPFv086DBVBNT1qJWFE2BgoKIMYnvOt8HDSBOJSiL9W1UBxABgkgWaFNAoEyvIeSkud4agPJolFzyDAjMZAtjS4tMyGgscUFsOKNRIhuIemguhoQ5Pn3qZ2jpIkgwoFeDsRhtxQBd0yUj6AtCHczdIDKORKNsOupQDYSQ69OyskOGpQwyIcEorR581CQQQaJI1EGuJyEoYUKNAjHfCAJlVELIZDVCYJU4ZP5o00JtK5myfVGb2fzM77jhEgMCZJEu2BQ5DjdwCMsGmwgoPqkACYKiJJWQUkyDu5MBoMzk3z4kIRIxDwAXbN/Sp/C1DbX5qQcybBVvLb/50oeDqKqk3H5OIGlWrs+wGgiOdwx1EFQbOgWhEmqGtggBSZEytU8HJxUVVVJRsEgSzcL8l/cZ89hMoqIkUDKzatf7Vdv1bRd679qeQJu6NBZTSNFJ0KAIhS33Zge7u4ePfvEQIhBZRAtAjAYEJESDBkh/8w++M73aCGjn+3JKb331rTe/8eZb73zltTfvXLm5A0W3cscXqyNrbV1ZNmUS7V0AtM10Z7meR422pP3D5srVnZ3dyWzaVGbiV1DilcPqLvX7995b/OM//Is//ke/+It/cvLxn88ffbK+OKlkOevP19FB6EVcQi1KtnGd7n+0/uz+o59/evLKzeu+TykqqVmv2ouLdQqgCUDI2CL0HgVgrPEjIAI2yNHFumm6rgMGH5yYdOXG1cdnD33ypuRmWgIoRmNNUTS2mtXNdNo0k6KwymQKiwahQCR1bdBWIefkRFOQJJI0cWESSFAfUlDJ2iWEiSXqKMybKUkAkPPylIVKEFCGPDqQZp8AGYasTUY/MbsjCKNdGX5oELfNZM/BIDw17Ic+EAMiuwE4hsV2Mx+3Q82sHwiICoOcPGxFZ6NqW55J2z8AILkp4+UJPG+4FEAhAQ4kCtjA2GMqcPz6kDwaPNE8NwFA0tNle8Nhhgmdv70dST9z/C3M+ou3S4B964b+agDWC7dR1+/ZM/lVAKzNh7fOBbIEzSYJncPGbTmmL2p0+Awg8CXbXwdXeTED628DX+mvxScat1/DJfx/6F5tMuwvOuennPmBv/MckvX8oETE3L0CtoZ1tgGqAKgD6X34MOS+FkJKhGQYeCjwGC8DCYlY2eSmGKyq0YecIlJBFIwS84WkkERFDeRs1KBOlUYTiYiY852gmmgbfx89nqEpOhMZJKIYoyoqDnlBAL1MTww82VF9HCDLsYpoUgUFJsjXhaSIAkQ6SPCA5hkOKpBAlXLXjE0STtQYDiEbZSElwEQISUAZKMtaMwAjoCKiAOhQpEhKOJRIDT5O1sCgzeNlIgAUlBgT5yhOM7JABtlLQMQN55eINK8UiAM/QxHRAIqKDC1HsrOqyGBy+5JRcBsRgQ0rCIGGrCG5ydaMHjYiMpks9KWoCqKbO5q/kf+Kw4BUAMtsCoskZBlZFDkhJiRmq2RdlNmsQQ9Pjk6Pj+emnLC40GsfxVouLAOKgJqimNZ27brj09Plql323arvlBBTDF3HVRkgHl1o37bAtY8pJk2SNAEhxCDr0HddSBFEQtJIxAraNM3+wQFbc3Fx/uP3/uJwf29vd7esDTJ+493fKqq69/Hk7AKZV6uu9zEkCCkt1u163fYBLCE0GhDeeevdaXP4yQf3/9kP/uTxk8fNXWPJukVcnLaTCU9nM+f70AckpsKq45RQVGIH5aQAkPVR/Kw4mkya19+69fqbry5Wa21NPXGT6amO3QaSSF1bY5AYAmphCL0qgygeHy0/Nvfefvvku7/33cVp9/lnx1F9dGmwCQMEAlmrTdLgDkCeTRvoBIc5PuTLcOgOtWVRNOeqLh2aS8sJlJ0XEZUBh815NAHFjEBETRjLpgkdkOrO7uSl21fffOc126TjxRwwNk3FcyqLVBa2rpuqqmN0xli2MYqCaowarWbKFSikFADQ2oqNTUn6DpzvLUldVHXTNE2zmi+aSQEg+7u7i8UqREEUjbpYutOT05vNfgwoSsHrfAnHp0uiveB02YEVRI0+xrpqTMHrVXt24WdN0Xb+/qPPROXg+uHf/f5vv/7Gaz/6s/f+r//zT6EwkLAgg4giqaymvu/QmBQFotjSIICKyzc5TziigTGw8Q+HApbBGWJVVRUmA6iqaZRBBQSQUevBGhsl6hiobZaAgXqQRHPrGYIEqWB20ammBAICt96evnL39st3bpCV5fwCDTbTKQCUZWGpbM9bJJjtEAIhGVGFhCkiEltT12Wjqt4Ls5nO6tsv35pMyrosF6uFSmyqae9853tTUd91pxePZ5P9yWSCyWuw3/6tr9dltV4uF8u2X4AxQkYZkUC9c0DATNbamJKIAAoN7NKBcAKXo3mzpOFItxrUeEYqAmfEHdEQmZQiASkZRBAUUBRJDCnb2Z2d2RtvvPb1r72NNj5++PmHH3+wWK4MF6AaNXXOm4pjVCLywQcvy+V6Pr+QYEGTgDMG6r2yOqwmtd093HWxT+CtSZ1bIAWgRAwh+q7r113nnUqnJGyBUBASUiJSViBEZWAWwoAiSgKkTJIRB5oUEyJ23kEIBCosaNCgEa+CggAkBASWq9rMnEspSPBeGboeLhYhJIeAdb1T1JPPPv0opiAhEqJlrmtT5KSKSFIyaTe45Wq5lgT1BAWwLE1K8ujsiKlkW9qCl6t5R6BcEhoSRDaYWKUoTLIlmwKBgFi4sGIVIVIh04InezUsQuvWVd2Udd0tuhB97xZ1Za5cmxx/eFKVe+XUlGtTdb5TSJo0CQIrpqIk38tsNrWNdb4Pp7DmzqCBCGSLlNSFEFMkBCqAAEKMwUWooShh56Aqp+T6MF/7oGAqrpoihKL3KfhUNo0VRkRJybUuBUghpQ7QA2nETCjIcVHMjIMh16+qiDo0d88Yz1aJGRGZwpBlRFCNCgAGwbCAJBIwY3Jh9M+ACBSQeLDLIyaTe2+ggqACDFZji58z+g5blCAYc+zw3Ha5mGu25jCYj6y2jooKeVgiAogCZfGGQYYhechioDkbQgQgWfpQQRGFBk9CMyWcdNSNBkUE3k6FPnVWW6f7jEu7fRGD97u54vxpHLV2Mpefh0pOHJjkEENUVmUFHNQYcqXheO2jj6hjuA9ZOHX8XbdqrvLSNpIscHDVNrHwaL/x8oyHm56hwXEgDU9JFCT7UEPkDaPTSjQstptHqQoIDGNFVGaQqSokyCvstj0kQEMGCBRQVCHJIPAPAEElpkQYRckAMbCSqHSpAy/Toi6LQoJoWrVdD0CMlsCScnQCVID4oeNlFCVkQ4jgo1+sVivXmro4vHlYNOy6funO00U/TbOAJduodiXaTmeoUTWp9265Cm0vzRR27wBrAAAgAElEQVQmO7u7e3v1tGYDk4ktCiyrnA6ye5NbNe4c3w/zR4t77z86exLJg4klgRVfIkw52F1ThLQOziWwxHVZGzJlqOZhIaBw8aj70wc/ufPaKwar/dkBwVFjSMloNJIiaBxybaoETEisFHtRAU6IDqqdYtmtqnmZfGjKJpEgAbOZTqtu6W1tSQ2rwYCpTwFDCKnrugSxnNiqnESvoYuQhA2DaHQKSVF02kxacepFMIhCVEBRvgSuNuPnUrcBBh8NONOTBztz6YfpuPhd5rzHwbZ5RYeZOO5sdA9hg8Pm4SqD3N4w5BERSSTB5TfHaagEg3hCZntjnoiXLuJYqvIMPK06FrfqpRpvPvmNCdURv9uEo5sxfmkQNvMrG0EZobfs3I5Uhu1IeTsg/JLtnwsQyKZm/N8LNnxxjP8rHeRXP5PtQ2xi+RcuBDgSr57/4q95ewED6/kY49e8bYU5l60ItrfNZ7Y//CV0oWe++zd1hptze3p8/83fsS+5iuffema7xJ5oZNiMpw0bawVDYid/kij3VOWU0uYoz5zP9ocRLy3d1hMCwVE8l3K+C9AAMxIR5EyxZWS6lBOGoe+wzW3nmAEgpRRCTCKIbIwh4pQkxRSSpJiyntKmdFkVFFLu/oAIosqZVJX7WqgqAiEaNpw7EHGWYxqoIj74IWmFhEgpr+VDl0PCTJ0fOWWKMHYTBUCwmB25nAiQ3EUnShLV3C9WVDQEiJK/me8dEiJhCCE/SAUVFTZElshm0SRiS5S7UwEoihIgITIhEzGnEPMjYTbMPGYXcHSDGZFEQEVUVESA1FhTFNYUpvNufKAZOCQkyqijiqaYAIDZ5n5IBPlRYdazIJN1uSAjYIigqDG34gYd0rU8rB3AiNYwMzIjUpQ4RJSYF65hESRkpCzBoEiQH1BRGmsZGRWS893VqzvMZLiwtkQ2y2U3me4enyx+9JO/uDhzXrTvA3JR1Q1xkfsBI6C1VFbWhx5JXnnlbjOpvHd9311czOfLRRApps3/+L/8EzZgStOHmICSaExirAVEHyJENAbRIIC60FVlVVUlGeq6LqbY9msf3PnF6WI1v/3qneVqBUjL1fp8sVqs+nv3Hi2WzvnUu9C2/elpm6VSZ83ulSs3/sXv/ksfvP/xRz/+4BcffAwBSBkihnWURHVRY26OrmC5tFwkwc75EIK1xhaFgkRN65ULy7BYLGd7OwqExEAoQFFi00zZGlUwpgguBg++l945ZDEMroudV0q6mC/e+erX110vCVxwwCq9GyIUUNWBSQmqA4SZQwWBQZnt0vdGBCBj8rgYfPPBY386I7fd9CRz+FARIFfYZHoiEmVvpiwLACgaa6x6lW//1tff+saralyfVmAjWmndet2tirIqy3paTwtrow/Re2PYFNYwx5CQqCqrDO+mpEQ8nc1MUXTrbrFYzxcgkqq6rJs6qp80ZVnaLAafYui73lgGAUPapfDmW6/2vlMUBViuneukrnbDUj+5dw+QGKlvE2nlgqqm6WS6XCysKVfz/vHDRwrpxs1rr7/56iuvvfy1t7/26ScPZs2OaIo+BJeaWRP7wIUtbSkRFFAEmQ0Spu0iGtQNEo2IoppjKsChtZYmtbXNouxEmM0/DswPAELDuSX28NBQhpCUkASFsyAZAhkCUmOMk94WMN21OJHvf//3D1/aKyZ2vj5/dPp4vrwAKEyBdV0309q7MJnM6romYlVIQbqVvzhdLOdtcGn3YOfk9KjrusODwzu3X75163pZ2cVycXJ6goTWFmfnZ8baybQG0vli7r2PKSGiKqQY6rraO9jbnewQpFW7VkVBZWZikChlYwFAJOAQHY7OuYAA52ZoG24KDEpZCgrMhmlgi6gioWUyjIbAZoaxTwlR2RowhIxkBNjVdXH95u6/9m98/413XrMlffjhRx9+/OHDR49S0JQw9NF5H9RVTdn3ngBR4s2bL6eg4mixWPWdg4TBOQ1Y1aZuzMHVnZAc22hMNCyHe5PetT7Ek9PF6fni/uMlBlSHBZcE7NdBPYBQZl4YImOZiGOIbdtaMsYQCbo2hC6yMgikIMMzzQYCGQwpAAFZNoaM5bIwtQr3bdCkpS1sURJxigkBjTE7u/s//+BjFbNY+hgTMRRlgYhZRRzA+jD1rojRxMA+onO0blPrfFR0MQSVNvTzZXc275ddWHVu5fo+uqBJSHcOdk3NZNkUbMvCVKUtbVFQM+X9K83Q4iH1hTFVadr1KaimGBB8XZbHj9fey3J9kVQn0+lk2tiyEMU+eGF48+uvlwVzQyJy/8kjrtDaQgHYFLYoX7r5kmGTyyoJUAwUDV+9efX1N29fe2lvco3LHYQyCXtTIhaUhH1AUGuMldiJijUFE6cQfBdYqABbcFFQQdFGLyM1RtnkzseUG8mlpHkQgsIoLqNEQIaNNaawbCi3OAQWKgwVJKACSpYZEA0Cje30CJiNMZy9iJymhFx7PXRdHk3H0ODiMowb8lVjDnFjnzd41ujQwdCHEy53mA28yOhxZD4Y4kAWzbyGgXoLsR9RMwEUyIJyhDRI4WguXsuscsThz8z9kY2TNgbdAIO2lI7R85aXitmUjS76xmHH0QGmoY8hKCCNehIbtxZzppWIOPmImbU04EfZWx6OJBIznX5wZrJvNnQsFRpobQII2Z9BpGyOdOBpYa662iyemNMGTGpHVw7GRrQ63O4smpHZfKTZMczkiM3ju0QmdJDTZtqACcPoGNWnR0pOjvHJICGyYWZCgqSZY08qSgq55aEmFS8MUDYVW6uKpIRKsQ8MZtDx0MTGFLZktL7z7bKrbaNKMSRQhZgEIlfGFAwEHgNfqbrUiQbFBCgAEUCAko+rEJZFHRVaBFdwbcB2nTs98/O1WAPVpLpydT9BQJbJxE4mBWDwXc/JFDCRtvjZn9179NHF40/OwwIlsqWKsIZUaijF8+7ONPYh9IpiSAsJkLy6NkJMk8J+/NmT+fFCA0lIu7PZ4mRtrUkRohfXOvARsniIICEaMqTMyoW1Xd8p5wSilnURMWCBzU7tQ1y057Vt2DEKSRDpUliFsPSxDTFFACDisizLqjDGEhp1QKosmqI2ZVmWxWx/bxzTAJgkKkTFhCADKAlDB09CRMoMO9nyv8apQoMbhpmZBarb4SHiCCjnvDWSDuopuQkfYsZ0BwTo6Z9NGILDDnUIMzYEChxrbAdhlExbzEgSDaxvHGZxDlO3NJPHCTcUsiAgDat9blCa30ICUBk91uxTZiZZruYebEomJA77yUZPkmY/AAdbsg01PHetl3Hx5Q/RZQvCEXR+IUDx7E6+aFN99gfxEiC8NNvPVZG/8ND43CFxZFc9/9Yze9ssEJtPftHV/YrMry8/4pdvXwhg/ZX3+Nfftu/OC8/kmZvyxYPjBfjXX58qNS6GlJlHz/QX+H/j1r1wtG1fziVS/tymg6l5dhvezbfuaQCOx817/yUnI6OSpGxtcHnbIZcKa04uMtjCWGtzpJCBFRgC1yxUsrGM2Q4N3f8yLxVUcFxWIfe/QRy8DASFEZ5RGWH40RWhYa1mNsQMqkRojM2BGYxFNCIiSWjA+HiI3pCIiAe/YHD1ABQJkRQZMzc3R0q0oWZlO4gIsEHHKLPDRBUG6CY3S0NkMkzB+6yjSozESIbYoimZDGK+3pymQ01ZozRLpTDhIMSOgDQ4xqMzNMinqqoqITEiMxnLZI0xhgyjYdd3QypuiOZUByuPIln9SnKSGBGH7o7j/lNMqiqj6CJkRf3B8wRAhIxekYABtrkYNNeIouTHR6MjP65SPLSlzg6kTqYTNiQa2HJZWkBtu/7OnetECMRF2RguFosuJTh5Mv/ZRx+t5yAsAEhcgHIMMbR9cAEoTqf1wf4OkRpLL924Ndudetev2tXxyel8sTRFberyH/6jP9nfLQW4d5lvAzElQEJF7+N0MjXWFkXJxiASGTLGkKHFcjlfnRk2XHDbdz6FSdPs7R0enZyfXizmy/aTTz8/OV+eztdMlozpWndx1ivCznTy8u3b3/r6b7Zz/3//4M8efHRPUgBAFOT8pAWYTduuEdSQYTYKKClrBOTm6phERZQY13378PhCk1eg/cMDW5Xni4veud2DfTYm+OR6XxWV9xIjBu+J1KBJURggePfp50ev3rl1cHjl8Prhk4vHy89XyoMsU4Z6cSNCB0iKCIyqrNm/Jh1wk2E6IVBmmuuQxwMEzY3VN6iBiGx+H/oMIBsyKjnvzmwMGRbVBJFKUtQu9cR469WDd7/9drNnl/2JGFfU2IV2sV4omaaeGC6ZrCSNzscYiLmsa2JOIkzGGBPTIGjEbJtJXdgixtB7d/4wTnbLJGm5XBDKZFYBCrGqpsmsfnJyxgjIWDd27dMbb768XF744JKqj+H8vL9+/SW/lnsf3ldRNhR70VBEwRBlZzJTQe/c8enx8en93rmUki356o3Dd77xznrhbt66kSQ8ungIKhFTjEGTUGlMaZNqSIkG7WMhGsr5huKaDLhILq/cpBAzlg9kWEWIh5JegCzLOgRCMcQBsWImJEmCgFSggggqEQIDGEmQEqfofHMAN25dvX33xmtfufX2u29cLE4eHH2+6FdkSZEBYNJUxMb5wMzXrl+tm0YEJEnXhuV8dfzk7OjJ/Oj4eG+vvlic7cymd+7cvHv3lZhcCGGxWJyfX1zM56KARFVdI0Hv+uViMV8s120rkqw1p6enVV3euHn1+q2rxYSfnN6brwAtJEzT/ao7d1gMVigTP5AHbDQJIBgYfGManVLK/Tp1TEWPDBM0aIgIlFRRRBHBp2AMVU1BVl3oDcUrN6ev3r35+tt3fuu73waSDz/65Mfv/fjR0eOTk3657Du3BgBb2LbvJpMpCGkURHPl4HrsdTlvoxPLtWUbvazWy65b934BJIv1uTE4mRQ7s2p3VscQlvPV5w+PLhb9fJEgKopBhRQkdhG8QFIERsA84QAUCQzmfmGYgoQ+aa8+BO987FMMMesVMVFZlAoQRStbTspJyYUm8i7WdgKJmqra3dmtqyKk6FxPgGXdBC8hxa7z7TrFCAhiDYaY2rXr+xCCdm1laFpXM6RitQ6PHi2OTvoksazrsm5cDOeL+clFezr356tuuW59aoEYjMkFZ23Xt61LKkXVTKfTuqrYIAIyW8MMqowcoyusaerGEiF4NtHYolurC2nVtYJazSblpBaGLrpqVjZ71WtvvbJ7fTo/Wzw8PlOCnZ16ujMjMqKAxAcHe+WksDUF6buY7Awmh8Xdr95951uvv/b29fPuMVdiG61mhkvqfJrPnfNAZMnQ0fExgTASpOQ659tkgavCEhpLJYGJUUUAgoAq5oQZEAIygutibnFyOQIho8ZMuYgeE5ICo6AAEdsseq7GmJTb0cTBd2PLxlpiQqSNQ5fJRZdJhCEay1m4bWeFxzTmi7fL+G2DdDyd0BzQYiDNgSiSiCgIExNwbmMnSVMYyppRLmPRIR4TBVHJnQfzQBYYWNqZ9UQbjscIp23cERhhOBi66cFQ/TY4uiN2Q8N/IzwHI4Q13JfxGgevBJAAY5TspwCgZHdHNjmZTP3fJGeGezU62Jc+9ub14QUYz3CE1zf4Gw7NeEHNgBfmr+Tejioy6O/LUOqKuVftgMjTUCeuqoNjB7IFNw5hNG5Qv3EbMUNA5S1UIX8PlYZUpSCooigKJAeoaquaTalEAMzI7bLFJBolC0GwsZYKDdqtWlIqywoUQgxJI2BCi1iAsqhJsYiwZ+bdxWJxsV6uQ3CFZUMkIXTrVYzdwf5s2hSlMawFQyVCqmIokUXFhChROlugNZBiH3wX+7W6AB7OHq/e/+Hnq8dr6KkoCgOcQvQuqFBpq6ap2+XCdSElYLSQuG997BOKdW0MHqEXv5Z+7SSm0hSv331jOW9Pjs99n0ARQuaIEymyIkZkIYsMCFFTlJRlQ7jCnYNZ0ACMdVNXVdWu1t2Z6y/a+dlyfbZuL9p+0bnOAZq6qMqqKsvKGmNNEfuYRK/sHk7KRkPKCiBFUSTVLHxCgMk5jUhKIGO38fwMFQCQdBD0GF4bA8atqY0wlsFugrshL5mLT4coinRDlQIYqNqb4axbP7BtTlQBVJ4NTnH4yoCh5u/QiNMi8sbejJHJwLHIv8sljqykjJjnDKoqKWd7xEiELEk3ATCPCPaYr6cNNkej3wQDpIsAoGljcQbge1S/wq2JPuDpz0BaRAwZjP5STGDLTvxzb0OsBNs/z5rmrU8+G/7/0le+qDYw34jNnzKGgH/l7Uvuzy/d/raLuH8RMvVLP/NL3/qrbduP9m92z19+0Be+rk/Lp734YhGeeXcYrFsKIJsZC1sXuD1GL781bl9y0PwuIRAzMYcQNSkSGmOYGXIVRhZEzy2vRUGQICkO3Yl98NZaZkIitmxABBUhY0mZUMCENFqzATwXFRVQL4MTk+M0SUDJMLIZpaUBcVjCM2w10sQUitoSIYxXly0djBZfxobfRIyci/UUQBkVCTQMWcgBBkJQGiHt8U4Sk9iBvjK4UkTCABUzEiLkckYmQgY0qoJj10CAYWFSGYKv7GEpscn6V5l3pqibomUVyeQFYxiRVCXvO+NGoxeZHRocu9AAIm16gACASBrGhuaKS7Jsmc3F/GLoK51NdvbBMVPvR2YOqPAgncWGkGgAL5IMnenyGkXDWouaOWwELKiZLiJBQ62FtdYAWbuczGYSQggpJoDSGlP0fVgu3LIDNEBoU1QfHEAATRAFDFR1tbu7s3e47zoT3Lr3vg99kNR5v2jXkCAiKlLIWT8dHrAmkIiQREiDE2+USJEoE/KILRqbELqYVj3MNHqQru+W/fIn77//+7//95KyT5qEYkLnQRRSUN8HHyIkkAiH16/cfunWlYPDf/xHPzh6cqyIxWQmvWNBQ4YrsJyHerLGMhlRDc5HFTbMZBRFkggpIROhxgBLffzo7ODa9cJMXEjHJ+e979nO2TAkDSFIVCRsGrteISQCIVBA5LKqu6PVT957/xtff/fazYNXXr354MFDeAIAIoRoFQmTCITcmogQkZVzOjYLjg+qZ2OEISn3tczjIlPQ8Sk7kVOHSYZZNvQoR1JQhpQEsrvBnBAEktdApUAEmqWvfuuNxP0vHv/C1Lo7qX1yy9W5D91stucDxSirbp1C1BgNIBkmQoOmaWoCRuTgo5cAqgCcomJFZVXv7e5D9agoK+/csu3ZxOnM+ECTqmarhzszB0AgVdWUDcHK29IIQu9dFPFOJpMZEoNNds+EZXRtADVsCkmaQr+ae2Jy3fr6tUNraLnqPvzso9OLs9t3bt99pfuP/9P/8C/f++SP/4g/uvhp/xjSAwd7kEC6kwiIxKQMTqIlIqAkmx4HQ1AWU1TNFCSKMQIqGwbECFGTxhgtFmQIcUgz5FgSok53Z977EIP4BIxsho5amVgXUwICKAArAABtoQ2QzHr/xq233nn9Lz96T1iEtF25oHG6u2sNdatFTMH5TjEVy6pumsKWrgt927suuk5WC4gBHj3+/Or1w/39XcuwWJytVwufAjMx87r1dd0dHh5WdR2jdz7GKL3rU4zGMIDu7Vx1usIgxWR6582b3/G/8fFHD3724yNo4cK39XWSgGywW3tNigQMuUehCigMPvTGkx7CTUCEnHpBBCJrWEFTCDECgTHGEhNbRE3BOQ0usUATfYS6tF/75le+93e/9+Do0fni/Kfv/Xy+6tcrODqFysL1qqons8mkWXU9+DKtZbVaWQtPfnHRdV4CX9m7GQM8/MXDk6N1iHBln+uysraymhDZuXDhVq/dumGQfBeWF21wZAAEGRklSIqZxQEAVFpLCFFTXtNYkZghKQixgkWJJAyMiiElSJDbrYlicomJC6RCbKEFJg1937p+WuzWpqqbsmxM1Na5NZPlonJBHz0+uXL1egpPJHnvoQ+wWveGIUUABWZnDauwJEgRJDEyMIFPuO5SAJdEkOvDK5PZLnY+BR9tUZVVA0gxxl/cf6Ca20WWIYhzokGSxBiSJRFrCYwlDiGFhPs7M62d65YAAJQOb+0JdUu/6s7iPFwkZ7s+YsNXr19VkftH9/d2pzglaKCwYBpmiyLEYhBJGIyhkmzhGRBcCXeu79995/bO9QkVvtmZ2GkqZ7Pz1dxTVzkmXoQYnO99FyyCRWYEiUljRIUksXcSezASIJZABMZokSBAElWJpEhCnJH/LMJ+qSmMmcGsKD5GFCmqAplUBjQ168ADIRlMCmoUUk59ETGgImSvg0BFCJ9uqjVuI6RCY8B5WdTzSzd99pcNHXfIGqrkZmUoCgYJjAEESFGTQsq9/Yazyu7VZUNDBd4Eq/mM9PIwIjq2s33qNJ7fNvN7g/+MMedl69FNzvvyCLnmfVSORkEEUhxaE2Z/JePDkPGk8Zy3jvtsxv35RPvzjrwOKyAI4OBMIRKBZCk0VQACUcy0fclSrAPPTTePTQFzs0kYmhsNr1EWm78s79/SNhz+1EtTCAgoKZFShjhzvUIumgZFFM16oqqQAghCdKoqUcWliCIVFOAwxpT1MkP0ERITF2wtcux8jKGqii5I8lGjhnUIDFABIBxOSVap9W3qwTJYAK/OrXtQ2NlB6JiQxfuSp2VR8iwU5WTZ9130CcPPPrp//Vp5eDgFDcvlHDVdmc726vLo3pP7H7i0TIhsywKigHpLYkxBlIg6iZhCQEBLhtFCAnEKiKZgqzULxmiTRHchj/zJ/Ozk3/y3/p1Z/aTBM+9XbClpzAONMyabVCQGVSUVTWCGuzypJjeuXl9BF9DtHO5gBY8/f/Lxh/dNj9ACBAABQxbRoMflydI2RckFJGy7tm07Ym4mEzKxX3bdqu2WIYhCwbYuipINFAVXwlEFX4RdvHjLIQ2OSO4YSF3Cmgq5GegG1Rp9udz5T8cpM2CxmzkwTIQhd56ngOQ61ae5MgqgA/YhqqigmBKOXv9wbhsIWGADdmW+SB7igjmWA4F8SBwqES8B6yB+2FOGvVDxWdtxOSlx5KMMU9kADKQt3NwrokEn9JmA+pk9bsfmf+MoxOYozx86ayNuXv8S6GD73e3zfObFF353+y0ieuaVX+f2tx3AeuGWi8vyNqZBXnD7nuFG/fU3Ywxs8hg5mfFrgbGewZI22+Uy/MWjZzPxtr8FT18FIH6RR7CB6vK/mz/zTi5Fr57Zv0IkKMkYJmTyMQBQEhEcDiybdTdr4yYcga+ESMQECAkEQaPGoIlyzQtISikkT8S2tCmllIYMExpEJRRRS4WxxhhFjTGkQQ8FKSuhZOAJCSBlNZmMNA1e3OgR6LCwEzKkrJyYu9xj/jjnUF5x1E7P3xlSA5o9IRKgLJuelVlBkdAUBg0NNloz+UyaaQOaywkQh4SjSIqjIqJs5Q1zoxzNaUoBKIpCRHHkf+ZHm0SYhpQl5utFySkGwaSAqIhJ0eaW8pBb14ypOSHiPOhyc8AEHgRIWUUEJamIBEhRMuzJGXlDIAVSJQVS4cGPQoRMPc+jJUlKOtDqNWUelmIW3IEswiwCqqCEuFytFdWUEEJwXauoIUDfewVx6z56crup4KqpZ9OJgwDgwaVoqqKuS8DcQ88BJEBZLBf60E1q266X5+cX5+cNqHrv58v1yfk5VJNbd18HgFUb6qooi4kChRgkIhtj2VJlVxdLsFSWhbWMKMBEIQpzJBQDnsGhOtDTJyc//uDk3W/9TgCYL/r79x/Nl/16AUUF7dpp3xNTUUNE+Mobr77y8u2H9x988E9/RNOpxIQhqo9JBSmSkirFEOqCmEAxpZRExbBBhhiDooAGMACGxOmkqrz6owfzBx/84E9/+MPvfO/b3/+X//V/8N//g+OL5e50ur/fVGV5enQGaATAWHUhehc1Eaj1jtDYP//ZT6Omr339rbtv3Z7ulH/8D39ACSQoERIjEAAxm6FeSaOKQEqCGWWTQR5u2xqiKGxE3EdjObgVRIgYQxDQTPbMk19EmArFmESiCBGiAUIyJXJNrY//wd//d+eLs8/ufaim25nWy67tY19NCyh3L+brGKzvtJv3Ifi6aPYmNaC66A2bpqkRjOtD17rOtaqwE1NZFhmJbprm4GASXIox1BX45BfL07KyCHE6nR5e27l1Dfo1hOCiMEwgIdiqoGRi1ycFNvjZp5+VZvLGndePHx+dPDgnqyl6IiKh89MFE4DGs5MnEAAquLrzYDKdfnLv/vt/+dEHP/v5q7fv/nv/0b/99/+Tf/+jn3/yX/xn/7lbyHru1u1qWu4sLtYYtTBWoiSvEhQiAKtasdZuLHye/sYYVGW2ImIygV2BiTVpUlGISbQoS2Z26EmRlZKQgmZdwgH3N6g21XWNiF4cIh/cwj/4V/+VGzeurdbLBw/ufXDvZ733wBRVi6qBENerWBiqy5loZFOcnD3+4IP7d1+/c+3KgXfp0fy4XUHowRiIBt55642XXr46v7i4f//TxaI4PDhYLleI2JR2UsG0anYnu7Nm5pMPIfTxvPN9oCjnJ2cXZ9/+5s5q2a765e5umFyZvfHNV+585ZXf+E77ox/+5MH9U0RaLXt0YI1JViSCqIokUMBIaIa8zMYZFZHgPagikSIyc1HYlFwSb6wBZVRR7WMCg3Y65YSp815LeOetm9/8F975e3/wu8g0X57+b//7/3o+Xz0+OVqswFZw/WpJBFFkte6Ziv3pbbd0yyfu4QnUJZw/+vTsYqiP2dmFN+5+5eVrzXrdHp8en57MnxyvVyu4dbu+e/fg5q0bbp3Wy7iah34FCVg8pKgoSYJoFCAkYyBh7tcbNaUQwQ/tUEo0IKBJJAnltDyhRRM0gqpEQEXlzJJOfd/KykXwbR/UwS+W93f2dvEAvGtbP1d0Rc1tF0XbELrXvvIVUFwUxWp55vroHFQ75WxqURXQIEZJiz7EmELd4GT3hqIu1qvzs7WXYMpyNp3NdneUvE/riKCSQu9ciGqESnkAACAASURBVG3rZs2uMaygzvXzs4tu1U6aaWkK14a1RoZkSOuCNGLoViUWdQmqtutbH5dmMtl/eQY1lY8X52fd4tTxtCiL6iJeFGzbdillCIXbu0pZEspBn4gTKcT0049+DAmgghs3J7/zm3ffevtuOZs+fHLy/j/78yfnn995/fqEC6OUECbNHlFCqNulrFcxdqmq69IWpMREs2Y2M+K7dHHcug4g9qyCYIu6NHUlPoRVH1wCATJk0PTgAQBkKAfLiCRazO07GURATFmSRYk64DecGy+n3YOdFCSEEHxMMUHSqGIy+ZuVFJENAqSU0rYbPLJ2YGBSbBvsX+4t/z/UvVmzJslxJXbcIyIzv+0udWvtvRsA2Q2QIDkkNZpFY7Qxk+lFMr3KbB70JtMf0j/R2Bj1IDNRspHZUCQFLiAaQDd6qa7qWu72LblEhLvrITK/+9XSADTAkJh4qHsrby6RmRGR7sePH1d62VS0IoJeSPQ23o2JQY0cQUbsRLNpVkiR8RxRlhFMdubGmB/DDIzC7B+rfU5qUqIZowP584LH9KI/Wn6KyOiSTiJaZhDd/+eFMxihFFAuEBCSGrMVHWxmV4pnGAxiNpV0G/12uznqRRd3vKbhxQc+7u5dEUCcYCciYmRLUALoJj9zFN4uD9AX2I9Np6AmiuIRAHY8dWV8BmQTnHdwfd27D4XIMWH5ZTcDl7KzzCPQaQqTkS/mADPuW8lREzJMYOo5JMmqImI6KvcnMKp55cyFmZ9VFc/c2eIWgkaOUVqh5AKJt8VJNZBX8RpyBfYIR/XZ3bfu6qCOaGVH1A+kfeylz2lQA/tZtWgWjTqrF7xZb86fDSfHi9tntwPzwrHPurvuzr9WZDhrLHPuWoP6APJRITr0uVvXvi6q/JoTyCyLxBg1UxUSDHGAUd9K7mTzKb76/afL5uTurQdXVz/xxGIgM1ZjIyhIDIps2UTNjcXVQXDsj5Yny3r1fPs89Rmi2gs6oAdFIBIJJClZhpr2OYfhcZdCE7LGxekx2J6fP0/Xu3491Bw8uL1o4cGzarGcVVVVoc6gDCmFK6daI68O7XEkmE7ypDaCHYX/OKaGlAOLTz2eZCJtACjlSkv6afEcqbhUtIc+Jk/E9mcgUJmBfNAhMxMxUoPCtLiARt7Ilyr1NuFmY7EDMphp8R/JqJQXHh0iTOPbQFMibcmT9s4deLpaLNVifx661WPvDcysqjAy06ZpTI2MbU9eJKKiev/zWSOAiPKBhNY/ML4zdXX03F979T0ZBQfZVDjABwoy9eqBh2Q9np7ka7O1/gHabzqA9eoTNLPi8NA31/r9B+jVPxbiWFoZNDal7/2cLhWmEh2sZeWoQhLFIUZ7AGwVZKoAdof7vITR7ufAS6AYABipKBHDmMmpigoH5wRCTMG7si5JyiajdQIATo3NB29A1qyqWQWCosY+xcwm8iQTaSlryjQGAs2xH7lI0LIY+eCdZzNTg3cORMRIxambAg/T7RQ9TIiomTKFUoOWis58AXoKSF+WVGBMniIiK4Wvi5KFGpmakYxGYVY10ynRaoSiYCgq70pSXssInrEDRHXM0SvWIRwzQZhLdnth2ppq8A4lDUvVzERKJe+xEKEbmXRFK93EkglAxkTGIMcEM55I9A4o1bYYTOwcj+FhLV8RVbOcJUqCjiEZlFQjZ8QeTpQLLGcACpuVXNEpNdFsk3otaCL8KZXbdqNca0l+0oJrkZGxNZUL3ptZTEM/4Or66uToRJUuL6/jkN9981tV1QxtgqCeeYFnCpYQtXcOoeHgw6xxdVWFEK6urgxtGd7FvDAmeJ+BPmcosmg/JECJQs5CQj74mW/EbGhGeYsyEpJoFKldNVvNMtpkmki59r6Z06YFc9XModWj814jqgbeUdPMiKmL/ayZvXHv9snpqt1sf/rxTwDAQAJLQ8kEUxOYGrkxoWJ8mfDO+cDKrCRGpEbkHAenkttdtCTL5TLNt6b+6yfP/U8+vXPrbrtrU8q7bVedVCFUKSv5vFhVudcUheFV2ZLzq2ZW85OnT46+qN/91oMPv/vBT//yp1fPu4tnmzRoVXFw3kqOp7IalIzMHIQYReNftdDuyDmXRaYvZ1kJXli4MA1/dm5ftXycgwTJWtRcxDRbhhFXPAxxPuN/+s8+BOmT5w93w7WjRC7MZk23zW3bJiXvXbtLqh7kyALBmZFkGXQQLwTn2cUY264rn9qddVW1JkIIzoSZwq7biUnTIEVsd0OWgSw1jcvS3r17trmOz59vlPxbD86u11dRsih1MZnh6nL35v2z+3fuxS4+/uIRCVan1Xrdeqpmizp1Q4wChFlwNJMQPHMwqtveHn799GQ133bPldtvf/Cd23dn/9P//D/GNn/8w0//j//9z754eoUtEDCgq6gKIagWxw7eO+e8qriSYUUMkHOOCkycs4FCFcg5Zs8VV4SYBolDCXtqTG0GChvcEcYaR7mqfZj5QbrddTe71Xzwrfdvv7WketgOVx9/+rRtt7t2XYWqalwGaZRd26833RAlODpa1XXtQuOqMNu2qfK191XOutuh26F2OLt1cnRc3z49URk219eq+fjo1u2z065tL68viWk+X4ZQlRWiqWdNMyM4yciWhphiwjau29iL6KD9YnHkvUflFsfz3/sn33/r3cs//bf/AUBz7C1j2/UAiNg7x867udtdbMAebkwjAuDYzeZzM8s5p5Q0SzRREXPwjQVHphhiilHTekAFLHB8hnc/uPdf/at/+lu/817Mmy+/ePTZF18/uP/m1ebTCiewK4Jrtwg1lquaiDe7Hh117dBfWYhYLo6HPlapmzW+ayXtbNhaTTxsbNhZjCFmRZuRAtA4a2bVapN2pDRv6ppWw1xi0rZtDQaGD56JRVRVSoY4EYmaCaDghqFQwBMrwUrlNCZSIrUxOmPs1HkxyblLXRa1BADUZm1y7uLQ7i53VyDMjuAHLOdNXbvNugX7ejZv260hM3Fdz+qm0pxEJYRB1NionjsFq3Kf1WAxi5in7DbbNOQtKCXpc84iyqSSRzTFRFPOfRuTSsWUOrverId+MBVPPKu9LZvgferj9XzAURV8EHWm9OVXnzf1kfpQH9cLckqx3eV+GHLKXC0j4sX2qnZ+dXsJsX6n7abrtllaQQQ86lP/1jt333r/7OTO7Pn2abx+cnm1++TLh5sNTu63buEW82BmXTu0fVKxlGJKKTgsZnPvCKqWlc1izjkl58AEVUiKIKJQlUiecpmgUBNlMgFpccpGWSgjmFiybGRiQiCQKSyJmOXMgbKpCMSe971TIjC0FBY1gmKq6jrZc/yKRXjgkpZQmBVpUHuBs/TNzQ7YWqOrXBRIx7W+JIYTyJGZSlG0hGaoUiEywRhmZmrGILGbj4Ttu/ciL6zYlgB+QcDYsK8gPbqjpRX2FsZk9vEuXh+0vbGSD1IUCko3sioKUx5mhcE+frZoX7/sBQYWXv39NXcwZjGRTVDj5PlPukW2zxac6iOOlSonvKG8h/FtAKWU0QRLjZax6M3TnOj8L8FaCviJa4MSsjUVNjjDmOY58fQBVbZkAJFzhjHN3aFws7UkznrH7Fj7GF3n/Fxdjpu07s0vXTjy2Ym4LB4bGb53/3SwNvYbEB83x7dmd0OeXT/td9fD+uL6Z47UerCEha+X4fje0er2sVv6xP2g3XqXF4uZd947HrromwW5sNusHaqa+4Ea6TzUeyagTzlCQd7G4ryUqcTWJ+aNKxke4JwFmZmdJiMPGD77yRd3H9xfLVdwLEmgI9LDys7IMYOZYGJwjpQsF0gr56vL6/Vw9ejyUYYcnR0t6hl6IBkJGMRwxN6S5ZSrplGHfN1j0OO7p2bohr5BcOQ9ZRNJOw3LkEw0m/SqUM1kwkQjM2jEsOz1Y+21DvVEe7zhDZUlZRwrTMC4cRpMB/NlWm5eJATdXGXvIdJLMwKT9twB8GsGUx0ZKgfMCaKpfHLZV0f1LQCmykXSrqwRqkRsXNBlYoLsveMxN9nMxA5kyA3wpZPT0kNTLatDjJtopGgePrqxey9ihTS6kN/4zH8tzW6e3cHG8lx/EQOrtD2EV17QS1yql7JKX7m6HYYD/7HabzqA9Wp7FVD8pgf9Euzyq7e9qPnP78+vvb1KJSu0hT10hZ9/j9P0uoGNVfcgwri+6A3+eliA4FVkqiwu+y17//PlDhCnJDlLqQJhCoUmSmoKpqpkIpfIcLaRtUUl8mM5ZivMnZIK7c3MRIWZyRErGWnRfiIu6I2JQcUQUc88DJJLLr4SkXeOGCkJgKomIpKsRsbEMsJ140JccpdArKO2kDh4Yibdi9mDiVR0XOExIldM7LghyBh3KOeGialTgllJqgKrWDIoE5cMu3LOIfbls0AgkDoriX4kqlqMFTYz8c4z7YXxsU99tAm+Kq7p+FdS+IJfsYqQhzFpLnw0qGO2UZZ03B8wUy6mlGMU0SJGuScA5NhZIcFpif2V9zXmhnsyZkAwhXVt/Csxk6Lo2o/j0DlnZCN3jYqxxcwOY4UidkTMrFTsYnLeec9DQu5xfbU+PTlx3l1dXnXd7u033q3rQEbIQGBIkeUCYGJmQ0Imh5CCk+xyHmazZr6YVXU99H2fYlY5Pj2tZ82u66GYL5d9K7vdLvhGxVIShkbkrFI3dTI1aBZRFefhAwHk68p2frPtZotZVVWLxeoeKCast93QQxV1xTC0nb79xtHieP7kyddNvfq93/m91Wr5o7/75Gc//pk/bvIusyOLgIGZioAUkRLZKAsHIjaCZsmqU31rG1P5Vcg5l5NJBjLyTi+eXMcc337vvSHtHj96fHl5QeBbJyfX6+tQN25Rx1b7TVf7WpPvB7EcT+pbF+dPfiwpzOTW6dG/+Tf/ww/+4od/+f/8v08ePc+azdgEospwzKGqKm4cAVH6lIdcgFYz9p6ZMSQblWeZiIxQUmRtXMpG36CuawAppbKOOe+dc13s5/O5qwIk5ZRMVJK8+eb9N7519v633vzzv/r323ZdzfxitYiSeIABXR83bfKuyUk9hSoEhnPs+j730vUavYs6R11bzrK3k4Zou13HjpsmENxqtfDMXdwYkvdgBxCypXbYPX369Xw1my9X88XcuHrjnbefnT82MrOQMoKHJWay4P3idPb2W29cXX1sarXjuOtrQJOSwjcVlGHVOnbrbbc6Xpp5H+zJ+aO+2z599vWXX3325t03v/f7399ddz44QBu3+OzHX376+acPv/q6P48FcyBX1nxIUnPmnGce826cc85xzilHMwgomGnOyRGDSbPByIcQqkDKgULKKUsSUjaCR2AWaIzdvbsn3//Xv/fGO2/Mj+qr+PTJxRdfPv5sdbQsBT23fXv1bCDvstpu6NtOUhYmcaxqVRKu69lqOYjI82fnF+fnMNy5Nbt1fHrvzv07d09iHMjh+GTRNPcXi+bq4iKmHmaVr6yemepuu2XiatYAdHR0zOz6Ydd1XTdgSL05AaiN2z73VWhqWjbLk9t33373g7ffe/vbTx9dfvbplz/97BNkg0BFspCDkgKOHU/CFzTmQUjMYJjpGAIgcsHAEJXRe2RFhdkMt28ff/jdb330/fcfvHP79O4SlX719Zc//eSnT55dGS3Wm10WIZCKg1RaVI9MLMpXn1wFrSiziSdppM9xA06eiC3q+mLL6iXRsNUcjStCg8V8sQgrQiPZba6H7SaaeJCDogrBGokKkAUERIYm7ZMxB+8UHpLy5KGW2AdAztEYLt9Hm9RURUWdkodjCmomEgGQR1VXTRVmdT1zLjgIUpg780oEGH/+2cO7t08W81leroLjZRNOTlYqsmnbGNtYkZqxcz40gNt1eb2N623Mhqqumb0k65Gcz6qSo0hWQJiYnRv6FgaRTGaBAZUccxrQt6ZJANGGPNlyHlLkYUCOxOQULoRq11+LbRzPfF0tjxpJiDkTk5jrtRvMhpiosqOmIUXb7rYxwnB27+7x0em33/+gk3V225iHx0+2g26EVFHfPrtz/z5drJ9m7s2dVfO63Q45oaI6wDjH4GfLeuGYoeoqYlCru+vdxlF2ocTGPECuciIqJuQdVx6klE1MMJXIJCI4EJySiYllyyGzYyus7eArzTHpCMCoQXBycqyimlVEVFRoFHM3VaOijKdTSXvC9BMASiWW8m0uMIlOcMjL7QWnrNiRU6ISvbjHnsNenD/QlBdnReJQrBDLoTwCMqUPxhDREawpZ+ZyiE4uZZHj2Zs9sNfKvNyYnS/6AYedPQB7aIrf4gAnO/DGJyoXK42VGwscDCgZsSuVs80UXEomvg5cG73dKclyCoC++DrGZKspj8RAI+ej7DCmLhJQ5iwpkaKILRTieiHR296TLH76JA2P8XJmKNR2jLG7/dOkwo+Z4ITpJtRMTE2NZGTiAyiCSi/6zkWA39TAjjwFY5ES4yzUHEFT1QzeXG0yZcyZiaFeU85IvqLF8fxotrp4/tyxvnn//owaG7B+3A3P2/Wzvr+K/fWOmxlMzHqrtV7i1ibd6tLq7nx2GhaLxWK28BU7x5IUQsvZ8XE9Oz8XGZJte0jtbE7mTVrYxBMRMoHlpEsClEewhkog1RUtzpid86Gqc4xpm2mOp4+erlbHAOpQpT4BMDHKMDEy56kCkZjADEzZEZERQ3PebrbRUo16u74auou8Ojo7Pbad9rskKoW9RUaBA7QkdzAUljVSzE7qxTLFHFuwulBRQWUK4csyJEkW4UIJOIBSSmLewcvex83LzY6+22hK7l3EG6i1WJg80QXYkozYLdGY9weDTpmxNP3p1YwowgE+fbPNsSveC/Rm6tmhM1tOXEa43dwdoWC4Yy2bcjgMN7NaxidgfnTTAMC5EavTQ+D3Rt6CbkpyGhOllDBSG4FS/WckSkyYOo3BgFfB/0NuB72ilP1ravbSqv3adfEXYlg20bXcxFY7BBZee8Ib7G8CAf5jb+FXbf61GYy/GBP5T9kOr1swwpceqIjskb8bUObgqENaEPBCCt6vMpLsYKDvt7z20f16W0GU9lBRmQ855z3xbw8kvabPul8Q7AVIfvoEFWLRi8Gil0fwq7js/rrfNNa9I5GsWsAdVoLkLAJyzMxRYgmFq6iK3uQlj7YMO+du1gQizyMzCmaBfVmzmDHqg5YFU4AEbbRExkZlaEdqZtlExMiQwezMzPx4fXLYZ2erFb1kEjI4lJo+RIDzgV1ZtlSlcIW00Fm1mAaZKxgKlXgUnR+NFjOAPBeIn01JiwKJmZmWYHgp4cRjJd6glrMSeZKiXiDj+zIiZoL5kfBiUJTUgemdmdKNmgagouqoREPLRxYlZ5JMTI1NBKMSFzFZwYuyU1gmgDyx8yoZKLmNpbijg0oeSx/ippBXyQx0pfTHWBS88B2KbVoiVYW362iMOQMKEgc1IlVzwXlmAqsZlDRB2HKdNQlVLjiGwxBb41g1BNfG1NVNMtu5WYRD1pg7gEBVRVyRWQCRSNf2Ofd9dKenq9migkM2bZbzxz/6ITlkiZoTM6FG5UKfVRJY1ZQs05BjHrKYNjxTGYjAbA5qSZE59oNB0mCOaLMZHOVKQ0UnsXfI9ZyOsYPNrKnnw253MjteHtXbXbh/9+zBgzvr5+0nn36W84A+BMepTwCbkgIMM7ISj2WjYiQoAEJGBpGBLBvYVBU5m2QlxsIrKTF22zZ+1T47x3c++M6t41vxuX25uThaDn3c+Frqat5Ui8319vLrzrywAyRx4G7YxV6fXF43n37e9f1//1//d9/7o/e1Gv7yz3/w7NkaPZmyOQe4uq4dkWZhR8WKchyIiwQnqxCHSlEyXMWmQsYmyuRccI5D1tj3Q9JEnok9s6lozlmzOEdGwt6zGflsaqtT/95v3bv7zun59dfJOtfY6dlRs6ourq/W7dAsVqw8bM4Hit7XZMoOJBZzMqUk3A9lZuW6RgiOnGNlUyaiLBhiNIpEOD47na3qGHMWz45CRd4Rk2WlLsYQmrOz20cnsY8p1NLMWDuqaixmod0mF/LFxZPVfHH33t07b5zgU6x3QxBWo66PEAOxkVlVYpimCet2myy6YLOl7bZXnz36+seff3b3zt3z7bYJsypUv//Pf2dezd756N79H62ePXrr8ml3/uz6p58/RAcYlJQZluErR0Y5q6o4DlkSVDUrGlPL1SyYaRSRlOrZHEM0UyVFxaCKnadkSTsY5ivnG8oun96a331jdf/D+YM3Z9ny0y8vlbqMeLXZMEK71Ytn11fbNORIhlkTqlnwHpIx9INj9WFWhXB6dOqg/baT2N29V906Orl/9/6t07Pjo3mbn6m5W7dvi+TLq/MvHz4MTVPVTdt2ohqgqjLETi2HEOoQ3GqxWsz6oTd5lmP2PmTTvu/MLMUhutRb38fdan78/vfevP3WyfJuc3J/cXWxefLoyfnF+dBl1ZwUcAxSdiiIX1Y1VclZTJtVAzIBIZsBzldJ0zBo3eDW3dX8KNy+d/TmO3e+/wcfvvftt+aL6tPPf/Lwk4effP5x2wuouXj+DCJZkoktmsWdN04F3ZCus+L09OzT63Uy9cGxd9fPt13XwSCDGIy8bq62dajbbbfbbSQhAHdP5xXAmRb1CsrnF/HhV5dd71IWcBDVRR2aOe82u8WsSU6GoRenIDCMnQ9ESDlHjZqhDIxq//CMIhMJMzL27IIvLgiTV9WcoXkEN8yEoA7mXKB6IRaZHDlnlhumR589njEtqtPT1apju3vneDZrzp8+YzMHSBL2geAlIxmGpEPOYlBD1hQUzBQ8m7kUKbaaFUxS6DDeETt4MlEwg21QsSp4Nw+xR9em1FuqKLMPfhVoTnB9tzWk+ay+dzQToZgSC7Oj46MwaxYmZslyFo+Fs0rE6qp2qBbV6a2FSMJidnS0Op0fz4d1e32+e75+nGl3fLZsFkvj4ALIJRuQemYJ6Mhac+pnYa6ZhzaqoO+ipOyYTo+OTo5WTRXMSVPXs5PlZtc/Pr8kUq6FhEWgTnjGHAhRSQAPMpCfDB0zZiLnswh5FA+TGcxgTwz2gUGISpaMG7JoVj61ZiCoGjRN5tDku1pJwOGRoFCsvmKuidlYAdrIjG8YF6PrJeZGsMhuRAyZwt56tAnzMBrJ1dP5tVT1KjYno8gxcRKxsVJ9Mbd0zJ3EAY+jmE0GMy3lc9TIZFKPKriNgY1GgYLCXxqpQVPcDCBgKjRIZHl0iyfTyDGz5/Fep0elJWXADrEoAvNkzFlhuYHZFCPZ68axeMHvnuCAyWmfErDYyKQoq0+OuEFIlFTtxjExMzaMKYQGEqhY+dSOzjMYXD4EZijdm26k7KKYQtRkBeDah/ntJfbZ5AWTAWDnSmLCmC5aYtvJCEUloLDniEr5SxVkKwKLUOGm0dEnoULrVREjDr5SQcxi3ryRZht2g0HD3FW+9uwq9k8fPpzP5mdnt5Z+fvH86vnnTy+/6tHDSQjwuRMYEdUW45DkPG2uLq5O7i/f+96b77/5Vpu3Q+6J4IQ02+3V2XG1GLjfnT+MPRAj+cqGpIhA8mVaiKpkiOWeCl+tjBcqT3i8DVJlyQbyVUXSx7bvr3ZX1bJenszPzy8Q4XLFGnz2rM7UqSVyRsbsKEmczWvHxJmOqoV2McDVGtbr7vH6+dt373fVACQVg5gnB4fcS9YMZwjIIW90Y86qVR2lq29Vyepu3XOg2KcyHhWirK7xrDCVnLOJGYF4IgNgrDVZKvDAiBzBbooHTq3grMYlnXfUZSmmG5XzmYJLpsQEi8KsbB7hqwJzjnzQFxAinbBbpVE5dVwoRjbjCPWO8XwDjHSURGYQFa+wKLqVNMARn5iute/hHkwDQHBFHAsjNonpXyoW6QhjkY1KxwU+LxnKzmA3asK8T87kESMzuoEGbaQeFHFJjKvQ2LVfgAaUNZnH2okTHvR6JOrVg/fI+w0L4SUs6dCFp0IL0GlwH+AnZeNreVuHwEL55RB72W/5pTr8/3PPQwLNN+3mX4KBDjv6j9teAqRe+DhMd7XHAl/t8P6+XvtWfvW2h5N+jef85ZuZ5ZwPO/CNdzdZFS/uMH7oppO9Hpv7pksf7mwH2bYHO8FKIAIv4P4Yq6TARJXg2APFCLs5EGLOeULRtKKJEatAzpJVteQOFnSqRATdJMROFVJM7BxNBfjMlAtANQmyF+zHpCzDPPawmHFMzrHqvi6NWmEOWSnOt6fSTjzSYhEWk4xG2GZcrAveoNCphEcpeAFimiIYOqokGntXwB/nS13LgoFNYcCR6zTN0+mhUvkoaLGrDAbS6RtQnjlBJAPMnksOYQkVghlmpoAUjfliJIKh4lU4i5orJmdFBm9JIBAVGBjMnj25bCP7GaQ6Jk4yEWP83mXAFVLVKH9vY7y36MwDGHEuaKmzbayaASYxQlGBBeDgyZGBCVXFx3PUczZLLvDRUZOiiW5ics1Cj49xvQMqdlwRVzlnUjVmeIM6FclZ5ov56mjuap9MYXq9W9fVLA7JO1rO6rfuIbVpiB2DJJdvgTO1lAATGQaTyN65yjFzKNUJ26SaLSObbS66FFNDi+VsAamOV3fWywxFiqiDuQZcwXvyZLdvH4H0+nzz8KtnQVkkeR/YGAW5M6cQkBqriSUBTTgoYEW9hFBKlNOoT0FQEjgWG5wDMYI4DLJ71i5PlvNm9tatpVnc7C6Wq6MQWDQuT2azW+s0tEhsTuGqNvdoUAW+3nTPf/TxR7/9nTsnZ9/9gw9dCH/2Z//35Y87QOpFXTdNf72TTbJGmMiUnHNNVTF8Vh1SliFR46eECozyG1ZyTcmkkOQAomwFcNMJCVY1PTk+vrq67s5brHB6rwkzDnOc3K19LanrTm+fkhP2WO+GPrKK7zu9vMz9FovlvAmNWswqhpSNzGoi7whmSfK+TBvMuHz4DCYGo8xBfDOExi1pefBVRk5ZjAS+DlW9mJN32mmf1mrZOVqu5s45yNXjH3/BHQAAIABJREFUx/HW8e786pGvbD5bfvv9+1/+7OvUepiyd1xDRIxyFAPU3FhlIoko4cmzdV3XLswu1u35+jPvF7/97d/6rW99p/I+pvbD73/w7Y/elqxPH1/98K9/vPl3D5/8ELgC5tAVwOi4Ry7TCDnuIBkMzACPYRsxRz2rmFgG+MYNaoMM3a5FZ720NJ9RVSqyo23zO2+effSHbwkNfd49uf5p9M9B6mo7u30ch/jo4XnXou/s+nn3xrv3u7ZPqVdLfdv2AxzBH2Vmz6axH5yT1GtThTu3TlZHx0fL1dnpMgSNtt1122z16uS0Cl6NsmnNLCKhCqfLZXGPRSTn2KBRTc7xfD5fLOY5xSo0RBylSzEyUzWbkcnV9fPt4y8D129tLs5OH7z9/t1vffvd9dX27/7u73/8o49/9ug5diUeq5JVMoroNQDnwXPIgD71GIAAt4RcQLYRDGQMMyzu0IO3Tv/5v/jjN9+989a79wzxy0ef/eDv/vzp+bNd38YEkaHvtFSpdyEQQU3qWV3NVq7WuglgeJJZ04Sq7naDqbLjlASTf05MkoUMocLRzJ8s64oMKTGIfDVEvtgg9jK0sjiSnNNRc7qYzzRmVUkpZstgiCmbkhIZ8VhxrIROFFTq5hbfU4wVgK9CqIJzpdgiqWhMYxgcCh/Ye3IAZaPELCFHSYguWIOKenTXrZ4czY5r1PW8roNzTJg1zayp6/mMnBelmKnL0qWWelXrxcCaibiqwmwW0mBRA2EITD44Mx0Gnc05hAAqLF/NSYYY0xDZuAoV10wISC52mpzu1sNivqhClS3EPi6bum+zqipS8H5+UvtqdXJ8tJzNAoccKQ3abYVQz6ujJiyQ/XY9XDy92lzv/vIv/6Ib2ra7jjTUcx46F/u4i+1sERK6fgBp7laxroJsNbdDzNftVezPY872rF2Lae2ht6S+7xazRX1acfBgDldXmQTswb7fpRhVJTM5cpDCEq4my2gyggouADZjGMBsAgnkQvBEWuozmGr0eb1Zq4jmkWrHQiZgYxSzS7kojrqS6j3iTLbn+2CMjL2YUmATmFT8hzFjaNLWnDpYrJ0pAnpoSRbbg8ZKnzaaVTa6pTc6NXsjEWMpELwoZ2HTv+W/xd0aL1DSfBSlAskrrAMbRYBon3+055e8WC28FBYc3dExwGtcyOUj0FOuN7nLRc50NMNKj3l/9YnGf3P+sbPl98lCJhSxJIxPd6SW6f5m96FcmpxrMlJV0gPP9sZHn7SIpk7dvKdDv32i3Nw8JOCGqkMv/KusU10WGt/cCHgUhk8JRhlISrY6g0smqppSibTpZISqAcTkpah1sCOCCiyJOW18M583wVPqY991znOKcSftIMPTL5515z12QAaKGZdNrKRHUG1NnUJ3ubvW7e5BLwNm9TxaX1LJ+rY7f3I5v1VzrqRTrmC7ZDxkzcyKggwCmo3NDGzZDiTACHA2JkwQyKtxEhBRRT6nGHO62l2dLI+rJfveWyYngQbPVhG8GUOMHJmKJis2ccrDWX3G4PXV5mpz1Xex9miO5l9efg0BHFABPdJOAodq7ilr9mqkYFOXXUP1ghGzrxqfQ2pbMlhBZpxRAFfsnRND6oUYxoCi8OTISuoGQ4qkicLgOZRhdoOSjD95HBY6Mv72xMOSxVxcnzKWJ9SjMOxRsLLJuHohyQ6TMtzhtW6oVAW8IqKJATr6kjbttl8JUByaPfL6KmBBNq6lZc+xxhf5F8hRL8IIOk5MGleoETQplTSIyGSEEQCzUs2Kis9oNkL+2KNxe9164KWF7ue1/QqBqeDGftn7Zdrh88F4qtfveIAEjTDZK56+vdJuVtEDvOWbTv7rbb8kXPObnkL4Eoz1TayrV2G4l6DBXyN69U3VJX9z2/Steglp+qZboKkVphteGeKHJ3m90tuIHwGAilqReQZQ2GRlwqsRhDwFF8AjGlhkd0MIKScVceSJyVSTZJOkuRjZ4+pQGCGevVoyg3Pe12G76VDxWIXaTATOdLKfxlvQQlIoN1HiBwzAqqYmckRCBNAEwsdsADO7ojJiJKqmB8HD6fD94jPZgUxEVD6PZih8fiMGmcERe0cENlPnvJoSlbptIAUXO+CgThCIsgposgZLhKV8iMarHrxQnkydYrmpmCse+2ThsQfINyBSBgAdS5CpaVQiMyJH3nkfmMVlSSJDLt91T2zBnHOlKJIVUI5Ajsg5MJTU4DBh9GQvyJsSYBnEo8jnCM8wCMg5j6acd3BomsrNqKoJMFWtmmp1KidHJ7t2t5g1JycnOc6fP392coSjW4v33n/w9z98nBzXTchZkbJJ7k1DBWIhZyK4uryqKrfZbLp+l/Lw+RdfH6/qN++9tVzMmlD/l//kX/37//Ovup0Fz5JV1bwPznsYktDQDiB4ImfsQM4Y2SVFytL3KUaAkBXV0kzSdnMpKWbpATAsx/aNO2dJ2qGTpnbvvfPu9nr3+OEzPIfNFUw6CKszJs5Kun8sxgzLVtI2RutCUcoNMTN7R84ZTOELCkTMzjNBTTVHfPKTT4/PVt/66P3Te7O/+dFfDD2OTwIRbdbtanXy9tv+4ZdPu5hmi4WqDrtIADtKSXY9/vR/+18/ePe3v/vR7/3uH/3um+++8+f/11998elXscvSR9RSNz74mSSJQwQVAV81NueZqMpFzW3vAY2CvGSGnHK2yATvHTsnKnkYAMARmOHcerd58M4DwNbdM4T8L/7kn82P6mhdtXBn9a2qdmLpZ5999fzqed0cicj5s2cXz4dQo6r01q1ZSiypl5xiTN5VjimEkHJOMba7QhcUVVMZPZZQOx+q+cKryGK+mC8WTBxj3O16EQFh6Pqhz0yhawfHrEKbTXt+cU5wy+Wyrqqj46N2fXn3zi0zikN/587tj777WzLY+dft+nyjmqqmsagqyq6A2E5ETK2MsecX3Wopy8VMhS8u48f4OPXD8Wq5nM2ePHn8/PwpDCaymB3//h9/9N/8t//LnTt3tpvub3/wd3//dz/+d//2Ty05E2YQiNvN4Kgmjyq4lEUahKVLmlKWyry5ATVOj1fz5SzGbFr1fWuIx2f37r91ev+dW0LxycXnXJE60U70SpmgYjnb+nq33bUpurpe3X979eiTr+HhaswXvm6q2Tz3rcYWy/vL45PlfNHcPjs+OV7FNMTY1aEGUFVVjmm93mzb7dX1lSlOz46rqjo6OmVms3jv7p033nzw/NnVbrdZrzdd34qmvu/m8/lsNmOmrjvOycxyHLIKmLx3VV3NzMKu7Xf99pPPP/30s8891/PmaLVYfevDdz783gdD7PuutWR//ec/7nfx6vqqa3s1c45A5MiBWLLWdVU31dnZ6R/94R9++zvfee+9N11A1M57rRcuarveXf7gb37w9x//9Seff+yDd77etta2SSW3nU9Z4yBMvN3thkfbk9vzW3fms4X3DARUVdXMmxBC0uTEERisAIXahXkQylFiMlQB8yNfL51yTjZoka1yZmXWC3JOkqFAs1wswVfPr7dD55yDmahmEQW4BJQdABgLDALiUduRiBhalIclE5kak4ORqRETnPO1c3PXbjrT6916J5J2fUIRqKwQGtjto0Du8tnuwW3l46quZgqXFbPFwjmuq2q7G9S4kNvikDfrdr3uh4gkUEVwKRNiN6gyw4ILzOQ855zJtAlNVVVEpKJZcju0GrXfIg0aqn45O3YIBN5uu027GXZoZg8e3F+Q6mZ9wc5FU3XO4Mw5ddoO26uHz46WqzrUs7BYzk7O7p90W3v41dc//JsfPfr6Ej2QgQQfljnuYIYaxto/uc4RwXuns6hJDfPjWZUbVnKxuXx6efX0aruB9UDC6t5SJQ+74ctnF19+cnF0gttnt8/unrWxf3512crg61pyFBg1CK6pyWnMWbKooZ7gJwWMTUU8gQkMCn7WVMzknIdjNvLOgg9VVS1sMQx9tpxzyoXwTUWVUCULhEyMBGZqMKZAB5bANxl+Nm7cA0J7JcsbPAWjeTOhH3ZD4JgQC8Je1pcYe5Nu/Dv9ssyCn9dKJ5mm4GjxfPUGSBqvZXYAsr32RDbhPwcH4kVvbdrxxaTFvZuKyXklw4tu++GpMOkGlS8g6LXOyKtbeL/RzEaJ9/H+x5q/E8T2uuvaGObae+CT3sTIdaH9+zuEsYASYYQZkQMRm2jhn4xgIWHvqGspOSRTLB+HSSGqYz00MxQAy0zAU2SX2bErlnCpEbu97mvnIqVu1z/76jpdAAOgKIquRIGMTQUMathT4OTaS33408eJ+2//0btXV5eb7a7x88vL9vGP/oa/x9wTE2YV76AyZWUweViCgo1V2AiWcwEmx2BCSUu7gV4zhAwQJXjENj97dj6/vTg6OyHvHm2fcCDzllWdeeecaBZT80wzdmzGXFV1fbx4enn5+OnTaApD7VxdN7/77Q+26+3u2S7yoE6qo4aE1uu1Muom9BRhRh6+8fU8wFdVVcc28QwUoRVMwY5D5erGs3OIGlGcitFDIiO4cbLqeE8HuaP0jfPipeE4TuCbIb+vm0pmWriZB6DL3tAv2O6LM95GBB3T6kFExs5gpRorG/TggL2zeTM3xzlV5E9sf7UbXJ5AxiAYtEwTUSkaxXipIwe/GPZx4XFr+em9fwn3OZxir8WAfuGDfbX9R0MTL61UL3Vv/6eXHPb9Cvkqv0lEXtpCk9b24Zl/o6CP/wwArD0KWFpRvH/lM/MaDGvfDnHEX7EVwR+aamZ90xV/c9qrI/jnjPtXD3ztn16CZl/7YFVuNC5NCnJf6Ee2B35UJVDFjm2ClmCqZMxMoJKj55hzoQ8pQw+SpQ0FJiFjU5JsZEaekKFO9ugJzMRuXGkUkSci0zGeAMUoD08TGn/DHSFVMcAUYgpAX2ROTk9qvJtJ62DaPKFZ45pAxpPhNZpyzGRmPNVlM1U1UZE8sslLXMKmZXsyOQw8ChEzuHgX4zfGphW9uDJFib3UB3ROaaK9KkokNYSKIAQD1Cwbk6lApgwEEiJWIl975zjxmIVYRr6rPcEXI4ccgWBsCiMmEEmJnqgCqoV6ezN4oLoXaClKi+V/AJFjArOBRKSiwMxgKzVtnA+Lmpyr2nYNwWoxh/H1dgOEs1v333r7weNH10+/bgfaqTqUyjgqORM5Q0ICPrp77969s+Pjo5Ti0HeqkAjH3G53V5eXv/PRd3/y9188erwZKyWJgDw7ZnLkqJeBiqUsJEUwl5gcaeQ8cOqVHaoKy9lstWp22/UQY8xb1GCCKc/nfnN9HXu+8+Dsjfv3/+zj//Dw4VcIMCVLpafqKDBIS3SeSw1M1jFBAOPA5JHSVBYiFPFFELw3B1XloqIFmOLrrx5fbM8//O6HJ7cW89kyt52p7nZdSllyds4dH60al5iqvkuDdibIzrz3RwvuekuwR88epSxvPnjnX/7Jf/GT+5/+7Q9++NnfPgYwO13EbpBs5Ekt9ymZkXNVXVfe19frNY2zfVovACll3QGoGBGBVUU1YzKMYYIMrdzjLx8f31t89Lu/ffeNI+F4ub2aH9UUKHi367q2754/7Z6t4+lpD636NiPDPDbb9iyfiZCI5SwxqnIMgVRVREUNbc9UilxaykMekDPqJhCaqpqtL9dNLTCIStv2V5eXKQmMhiGmnNpdGno9Oj7ywREFE98PfRykChUMH3703mw2Y/ZNVVWVb3ft7TsnedDddiMRfepx4AuqTFQwY4Zr5r7vB5Pee2pqOr8crnYfv/PGux9850121A4bggbvL7fdw0ef/PXfysnp6Z0794/Olv/8T37/7O58t+2ZQghV8PXm6roKdVk5hqE3YLFYPL+4+OLLL55dPB+G4WePnq3tMqXLdQcCjufze/fO7j04CzN88dUn1+2TxfHR8dHq6NaJr32f+l3Xm5AkHYZsRjlJ6jd54PrEm5pB+pi7BGJk4I1bs9Oz01lTEauotH3bNGG5OskxbrfbmNoc88XFRZShbbcxpiF1zjnHDqC6npUHmFIchjjEIaXoHLquY3aLRXLscsrn5xfOMRE7F5hditlsaPs+ayZHSYbYZ+eCWnJBFlY5doI+2i7l9Mf/8vvttm/bVkWrEJqm8d7P6qYUEnjw4L6qOubVvDk5bm7d8uSx3uWL9Xl7udv22113/fjZ1xfbTduFhgligPfBJ+Ndt0uJczQET05Fre+3XafVvKma2eIINTkXcrac8kCkLlDjw3ze+MpVnrP0GT0HuAquUvLJSI0iecmWQs3HJ0hNvQmpaeq264YYU8pVCHBcVxWMBYI0Br6JqeTf55SLEDWRTV/fCRkniClEFBq4LquaY+eCr2ahagIbPLEl5AHoJmHDjJzR+2F1PI/DhiVYZuIgmYhQzWYgFSLi4OArMnZwNZJ4o/Xl9dopqpoduRw1x51zFbMLwUuWoU9qGhiauc+iSUSVCZDgSSqnKakyKl+zuiw5DklarIHry/ZoVTO7lMOu3ZIj72YuOPYER82sOW2WTATVmIZn10+G9uur83zxvLu+Xk/0XyAj8wDvyBmcipglQKAm3XYnpGdni7PVmZMw7KJ0pDvu17AdKLMJNk+2FGARGEAK7XnY5n6Z2fuqarZtn3K2UlWC4Cvn4IyUIkMFGcJgg2iJx7E5g1MALpCbee+cKXV9FJEizeOc997D8cxZTEMasiTVJAKD5TFrdOQVTT8mY+jAFNw7nC9YfCPTaNytgKFk+7Vr9D6/0VzEJNYxxUlHY+8lbOjFw/br4i9oRbeBsO/PoeANblgWBhBKrYuppPPrvMrJhKMXLbpXPb1DVaEbN90muG/aDh1zGMeyP0Q0Ct/c+PATf2U84+hDTjbigSMzdrn8tP0Nj3AVG0aIaWKvvSbHZ3reN10s1u5ooo6xzEOgYrreiIgRrGR3TfSkFz2s6d9yI5MDnGV647iRLCMzNSmlJYxMFUakJFHikOrgq3lVN4v1ebeY18tmmUUr9zxpYgYJqcCUnPMAi7JJn3qRCp5C0nTxNF7snnznDz7Q6FNrdQ0bcPWU12/s5tTU1QmwgyaCEhMLsxnMmRqpY3IAqcTx3smU1GEsJcRWgDWUpy1qfhaiDHknntzp2XE9qx79+EmiSD47eLOsxqqWsjJjsVhkky7t3nv3o/q0+fLRF1G0WtQh+JKufnFxcbI8fuM7b/BAl19dfP6jLzZXO8esTsHsvc9IpQZ6kgQlscyemnlQNl/5OCQwk2djyipZk0HJMXtWlJJ+PAqhGahUpTTDpBb1S7Zp+h4wg2h65YWVVdDO/SDfj6rJZZ9A0tKPw8k17kVE5ABzKJDWAVvwNf4pERNrKWO1F/yaqF8vd/5w7hLRpMBeGIL7BcFu1okyC28WhBDCja9nL0PUr0GvfrX28/3xn3/U4S+H7aW1t0AW+1UaU/3BsnFPWHn1Er8QLvjHav8ZAFjllwJdEdFYY24aWGZ2KHF1eNSrIMuviGGNNBweOYT/aYTZfv3tcPwdooGHQMxLcJVNbf/Xn3+JV4Z1ucrkdQMAnHPsWERuJL1gIiI40OAn8s6PYZwiS56FdJ/WXcwSZhozl30JKQs0Q0QiIhgwMxnThYgB8FjeRWFOiRwzU9FWm8LSZaklw6gBblYUGPeiAjAoKY0ShkyFO1VMChopuyBjHcsHj8t4SflCCTCY2ciYL7IKxcYjM6Mx/VhFJKvK9JFxoy14o9BJU944F/Iba9QXu7KPH4G5eIjMTOaclI4Uy8LYzDRJUQQdU/+BUR58fPkipVyt8+RR+YoAJlbTArIZETExO3JgYjFRycSlzGwpUz3yqEH7PFMCSFWIaTQO9/BFuTY7Dk7MDBaHmIEA1MzOuRACBb/btkb/H3Vv1mRJdqSHfe5nieUuudXW1QsaOwSAoyEp0iBqJMpGMvFFMj3oTT9N/0AyPuhNIz1Ry2gZShRpHA3QGAzQW1V3ZWXmzbxLLGdx18OJuJld3T0AZjDS8FhbV2beiLgRJ87i/vnnn2MYxhQjQyvn+9B3Q7c6Wbz1/OJy2+U4ImPmUk9xQm9hKvyDv/8Pm8ax0d1+KykvqiqM49XlVRxGQ/Yf/jt/8P3vfXt73X36+SUJkJBzIGVjCICFE0TNyAGCnEGSkvWGyNWOc9inoFkQQ6j9wprUnrZ49+zfur548fk1Q5nift9V7vQbb7/b1u3Vy+uPXrx03mgmxOycgzIyAZpzUsnExM4YNiqBgJKzUeo0Yk5umMo/KYjI+koop9RLBhMroBlhQIjh6uU1/Pr87FGWfRrzdr/3pt7v9ynwyckq1brb9oCyJ02as4xD8jVnke2hU7q6291lxB9994fvfOPpt7/z7i++9+G/+hd/+unlFQiV8QrJyFzeLOWoUZKSKbxGIpgyFLPmLBnGYCoXIzEnEAAhM0c7CQCWpyetq378d7/7zncuxBw+evnTemEz62EYd4f+8up2dxju9uP+ANK9cws2vlkpSMM47ncDkaqQKkvOISURJhQyI1KENcpsraMYBRlF4kAEcZQYY0ophBhT2t5tN5vtOIIZUIwjdtv9bju+9Za8897bZycNxFy+vtxsNhDrPL397HlK6fR02TZNjOPN7fXypHoLZ2Tk+mozBNGMUi26/FPKc7Kx1jrNak0NRQyJSNu2AfVDHG93t9v9dY6hXdS1dyEMu93mbrv7fOOvts+enj+vq9WP/8F39tuDZrbWel8jv+N9pRkKutveDf1wenY6js+/e/dujLFt2uurjXPeWrPb7jebbda46zfXd9c3N7tE+/PHjxerVl3qwxD30vUJkBD6w25/c637A6BgZNacRsCh8lg07Wq5OD1ZtW19fn5ydrFOeRz6nagMIeQ0erdMMfT9QVVTytvdZnc4XFycG2NefX45DLGpK+9907a7XTcOn93e3nZdN/SDQkMI+/1eVZtmYdh03bDbHeq6bpuF91WKcRyi9S6DMnI/DjmLs75ua7JpP17vP73WLETUNL5pl9F0ZqEnq7qtm9VquV6umbmkkxjmd995XgALyHgYP//g55+qUYGEnBLkZ7/46a4/bLbbXTdmQh81hijZWNfAmpj7kEDWquTGV2dP2rpVNiGGfnTmredryg5A3w2ZQzZwPq1PFucXazKA5H23b05zS4CBa4V9JspkUsZo2fjKrE/WqbGgztlWVMc4HPqu8o3zDmokSk5KanhejienOEyeqM6LLhGVyIcx7Lx33hHYCOUoIlk0s7CkHEdoRkoiKedRKJUuIkog1X4znrRNY5exy+NB1+crYgmxT5oO3TaE3G0UsFmVjOHKk5q2bmJOMUVjjTc2xhBChkRr4QxLSjlmUjjrkU0c49APItrUbeUbWytpYoqn69Pl4uxus+223TiGEnna78frTb9oLKherO2QxiFI6npnc7WohFM4dMzkmB1Vh75/8eLV5gZDj0NGifG4ha9Pm3GI1luwxjTEGEGAg3PU+Gqxap8+O62cu7ncbDfbHKi/ixqAbEidYdYQDJiYqIVzIMFuM0i+bS+aDMSUk0ZS46uKXKk5qJpVaxg2GZmVWJnABGKYzFmMABDVgBATadA4BFEBGUlCbJ3XYRhdQzGmlLPkYyVqTK9YZxylhO30yxjRV7o694bcZDGCaYpYTTJRqoVN++YljtHl8usE3MwflcuKyptf+1u5QtPmN2XLCU00k7kUzbxJYq7h8iW605dRrOPz3t/qF7PtyvdNUZiJYXbfnSQQnp36SceHoFNxO5oY+A/M7KNMerGEZlt8BqeUjhy1Yt8WH/0eQShfrwAKb16nU2aX+z5OMmFvOtVSKyfSDDYUr2l+wtmunC6fBQoiLqsIzxAjTflc5enl/scZFyAiyV+M7E7fBYUSlyi1IAkMVIjBhpiEKRMyn9ZLIzb1koesA5BLyUVDQppLcgIBnNTlPnXSUSW2MZJz2mJ3ddBBjThEY8Q5k7ebzi3q9ersVdpDoZIYTkEiSpmhIDVMjplT6opFNb3n2VPAlFNnSpVQEXhTBxqhsMb6xiWN9hx2sMkmCUEzi4LgTOQU+z5rXhIIZ+9fZJ93H+1Rk2t9XdVMZKxh0HgY9ocdjyb0oV00jatFdEjDkPtklBsiT0lCyi4O0SgAVE1NlhwsH4aUBQxBDjGMYSxlD9Rw0dQvQ7Gscijzt7ya39Jn/QJgPQ/OyVqbgKsZFz3OGQJwL3l+HPwTgjv96SFiWkCpgow9gJbmtejoMBIAJlZWqE6C49PtKE8Bmgd3W4zjIv5ERQpeRMA45gOVbweRqPI94K1TlP1hmzxkeviHrwgE/JbwDj1omCG03+4SD66DL2l865foV+XIAqE8lNsv8lgPj5/kwB6c+1e4sb/p9rcdwMKDTj+iV18+5g385eFZ+B2hV5hHyVfqyv+tbV+JXuGLyODDvjput8cH/PIVju3rH38KNhGRzPUNjTHW2TLDC+tIoFlykfUEwxprrDHWDuNYZM6LbWYKlSODhKCwVGhFExySJZMQQ5ERQ5oiKDItZuVYVSpFeSQpWIiZXSlGhSlUSAWbF9GU0yyCVXrjqBRBxGwm6G0uvYiCZ9OcxE2YWLBKBDKF3EVAnijbk96T5uJeFCqsMYYYBY4QmcIVIBDrtEPwbIcwFVOAuBBcOOVogPs4J09QEBsupSq5mMcgVsqqKtCkkKRAkEisZJQYxNMrdjNldMYwc0zKJGystYYtG1AGpzCW5Muy9UipM0TH/URo0kIAAGJi8BwmVVIm1ZlbBirWIc8kMuWCHaYUwKBIFSpmo4I4psN2/9bzxxC52742LN/6xjdVebvfVm75/L0n3Zh222F73Q1DhOEide8dHj969OSt87eev933u93uVrIul8tHj06uL6+vX28Ysrm+gsr733j76sXtr15cOoUxpGDJWXMCia1MyEmipJyzChGriCQ47yyzUZtyBIE0LhtPiItmefrNZ0xD87MPsqg1tq3P3nvvvXfffntzvenuehxAjhE7vSnbAAAgAElEQVS1ILCV9QJNklS0VH4kZcM26MizFTAJvMtclmWaWUTGTAVEJiuaRSApsyPJ+osPfjnw47fff2u7fbXvhv0uLltDZJl9VTlWUc2i2TkHhxxzjDmmfPp4cbPbdmPXNnVVu7PT9vzk4u1vPXr29vnps8UH//qXoc/Xr24vb64FsAyANGuMY4i9sdU0+xUEERUuHErNIMAQUNh5RUMNAIyjk/W6Xja/9/f/YUR85xtn1SJ9+upyHzZuvU6g3W64urnbH+T6ppcMyxgGQNTbJhNCGHMcd3d92zrrfO01jhKDSk7MsEzGWu+MdZbZAMwYDjq0jWnqShJub3YxxRhLdqGklGNECPCW2ZAxSrDjGHLkFOErs1qd9v24ue42mxEWpy9fVpUnwjgMqjmloJJ8a9/51oVr9dWrG0mIA2IEEay3BAtlIkNk+u3+9NE5QQ77u6Ztnj27IATjFZTI5Q9/9bPlcrFcNhfnJyePK9NK3w+3/Yu7T14cDtun7/+XXdre3Gx2uwMTnZ1eVFWDDGKz2+222+0+XXjvucLZxeK9954/706rqrLWbja3d3d33dC/eCHbX77SuHvy6OzZ28/ak8Xm9uZ2d3e9/XzfpdVyfXp6tmzOa7cf+gSwtd7aajzE5Xq5Plk2ra9qt1g2zjGRpBz3+/1utwElZlku6mbp9vvt3e7Wu6quq6auQ8qPnj6JY359dd31/aOLx/tut4gyjCHGuFwtdSpbabPGblClQ9v11ppuGPpxTKIKkwRpLqiqrMYwWc0SiGTbjTrVv0oAiHQbyO69t6eAqZ1fNItDXuyGFio5ZW9d7dx+uGzqWlLqdte72+tuHJrFyjeLMeUxpw/+/C8Ow9DFEcaQbfe73TCo5LhaNc5VVdMaQwoaYu+caZqqWWjWOI6H674/fXLuufHOH/aDunDYRevRnlB7AiX11tnWnz4+sxbD2BElV6uqDrm/urn8/vd+XLeV9TZnJVLvTVW5vaQxRe8bBYhZCsXVMAkpE0r5MHkDLDime+nMzCViMFMec4wxpaCQxAYBKae2buMYcsh5FBV441k0hMgW4Q79Ipw9Xt2+7ow1j59ccKXXt7u73ebqdqOSt69ySjh0yMDq1D168thXVVvnQ3eQstlnhVJOGVDv6srXjirJRRvIUSYS9WRqs/DWx5yjGdrGrhZrY0wM42F/YMB7VBWlqN0+ODKmcicXp7K/24+7u/0hy6EJbrWsFo0dh60kad1KyVSLeiW5bsjaFHYSIxgqJj97/jjFFMa+60YhZIGxqJf20dPzJ08uvOe7ze3d7d3dZog9EGHJA0iZna9CGjgxMVlrLZmccrfvttdDM1RmbZfLNTcmSEgmAypJUtbMiRxZa0WygTEwTMaQIbKJUqSRiGOI4zhAgDBt6JAcgoaQoDz0Q4CmFCWJpImfTiKFDENTKT5lKiVujmWL9S+12SZsZNYEmkhcE+A+nVjUwWeC+EwWmrgURatRVKYq1zgGm0VEsrxputP8nb9BY8y3UYjQs+LwDF3phJUcSUFaNJ4LMkNKx5RCTAeSKB4YvQXs4y8yjDAZJ292VLGNUWJkACaXmBhcpCmn3e8e54Fikn586K1MLvMX7oz4iLgRTZo+kwbFHKGcixQKwYCUVWXC8VShRXT+ePNHvpXOqQsgUpIZ2p6lxGgGcFSVSCYPfbIqisRQnsdJKQowX3YG7EQmGGEaFOX9KFBqVRvOyJojMpCJhDQhhxxJobRs1tvN/jZstc/jLiKCFBrBQpJZUiIYMsYYl4ViF1nhvTFAcvnjD17apTGm6ncp9fBGX3z8+em3n56dPqL0GVzWIauUHAHlwk4iy2zBxGxLR81dLcWMZRAxF2BPBaLCbEGAhWjuQnfbbX7w4+/srve3r273d0MOAoJBosTIiDK+953329MGp3JzcxVsOH20JhgmeOequtpcvn69H4ZNxA5MOPOn3lXeGMeWIrm1a86aUYYDdeztuD2wkBNrnXPOefics4bEBkqSJIQ4ln2/yGBRIVAqASQGqnkahb+9uzrT/KbhWtyl8m6Vj14ejuykSdFu8vLmTp2x1Hn4TP/M9bRpCjfPLMGHyYHy8KYLqVSpzDeSac2Zxq/MtMD7laGIF1PJm5qwt1JOdA4GzzD/8Umm+6fCU57TJ3V+xvvhTbP+jNzP9OMs/u06eUa6f7vTvujRf9m7f/j/h6QfY8wRWD+ihA9d+4cg1/GYv51YxwRg/dW67//LduzTrwSw8CVc5is//Z3cw195tP1u229+D28c+QbWexzB+Kpx/5VX+7XHACA6ioVlJTCDDVtrc84KncDdwkMtxXpB1lpfVb6qus0etmz5QMrwzoIlyVQaRSYOpDVGREQSgRyxsmQB2yIeOm3xhoyxFpAQo6YsUdVk5iL5gaJrCExLoALEUJGy6wOAAiVaO0UV7hNIj6UwmRlM94VcMXFqC8qkSnPJ5YmZP8MROtlYUFsoZW8MUgEUPJU9VlJiw8oTA63IVDFKsTq673QCMbMxbCbGYjF6iv1GWSVljVPSAlTVEgG25AFOiZv3lMbSPylJzEIpJGErmUoNDmswVa/ImkVFCr6MIgKpc+XlOUf+GG3UEt+DzpnpQlBDrISURAqBxzIRrPNwaizYWiHtxuEw7Ichf/97Z5r18vVnAE7Oz+MYb67uxjE/ffzOt75trq92v+g/6nYjCIgAYWhw8ejixz/8O9dXm6vrz1+/flVV5ulbT9rF6tbcdSm3beucGcdusahPlifoQAu0da1iY5CcRDQXlf6EjAzkbFwFZ5hMClk0jWO0bE/WzZPHpxePTvaHmyzD+++/993vv8c2dt1wc3371tP3v/O9b69XJz//+V/EmMhBBiFlUpO7qK2fuqpsl1IgWs6lxCShCA5AAVNqSUJVsijNoiPFvGSyzJyzaEC7bMc+fPLxZ9Wp+bt/70c//UD7rhsDrEnLla9sQ4qUR2NhDJKKYU/GpDxC5bY//P53f8SQy9eftnv/+u7zu9314/MnP/7B3/m93/vxy49e//H/8s//6I/++zhkWASjBS9gb1zlY0jHwadSQFMBqRYNO571PUqiQQIycq3P3n7yznvf+E//i//8oxe/vN19tute3O5uMu23h2Ca893hEHM4O3t2ffPJELFoa0lKcIBLIY6HIBmDD21TVVVF4HGMOcUy8pzz3tu68dZZawzKFERcLReLZRvjeLvpyMh6nQCyxhlTMcNZVJVndt5RXTVd17XtchxTynm1Wpyent9c3W3uRkS8enXz3jee3d1tb/L1er1oF9XHH3/ctsu333kaYvv69iYDUYEErVDVznCtmVLKKaeqquuq7g/70MemtSJ5v90Oh3j+aPX02eqf/fEf2+vbd58vXB2q2mUKaoL39Wpx8ohPunS9HW9+8fEvP/j5B11nvvnNi9XitG0WKWUistbIrgsxXr++bhdtl344hnG1XLVtu9/vX119nnKq1/yTP/j9dr1gpjHH7WFvKl5dnNSrRdcNJ2enzx+909g2JR2HNA6RyNR129TL1WrpK9f3+6ur15vb68OhO3T766vL/W6rFOvKtq1fLGsw3W43n796eXH29vnFibFPnxrXNIuPPnx56Pvzs8fn588+/OhXKfZxKSEMb7/7rjFWRH1lQxhEEJOGmFKW/aFbLpc5S1YJMYYQVVAvqrPzlbX28vLybjswcd+L86gqeMfGsgLDKOMwrFeJ1AzOBT1E1H1orGFnbLs8tY4+fvHzuvKGTb+92d1tRIidsXXNxlS+fvH5pcBmsmThWnO9kZzgHOrIdVMtF+voJcTULipXqeQgWb0DlLuQzlbjetWenZ2EsGA/3FxfKYx3EfagIs16XS1901TM2Gxy1ye2EmPeHe7CZ7t/7w/+cbOohFKMMcRxuVRfOxNHIibLMSURmuoHoQgokgI5S07piwyZ2adIilI9QAYaoUqcjUTRnNmyN9Zao4xF2w6Zk2QNioBkE0OR4MikPnOyJ8vzw9htN6Phxnv0Y77e7K+3oa1hrR973d3FYYBQfPa2P1mfOV9JlmHsVDIrebYxxRSyZVm1q2rZjGM+bAdS69lb3zjr2qoBMI6H4RBiSjveieh2ewsFGzgPYwFAMlSMKm12h1GEvK8XGkXYUUIcUoQBMwmrpJh1GDNGASzsClZBWVM+2PZ82PZd2kcKpoElhIxsYrUy1cLst7urm9cpp6qymhJxbXwjw4gQEjtHFWWVQXodRsMqOYugQT+ObTLrkxO7tNc315FHJU1ZGKQsashZP+wHYTCXMsDMpciwqrWcFIizlxVBxiJDMxnrvK9iiq6i0Y45JmHVPBejTzJRHOa94otwzNfl/03Y1EwnmMAVnhm/VBzGwnhi1Sl7TWcS+T3mAp0KWhUgpnhKD77jS1/8debj1x5arsZzLhQ9vMb9L6ooqbM0B/cefNPUM1/wN/U+S6qgNveeMX3ROX2QU/DmAyhkMmqm2QiDUggIKpqgrLgv9TW52UQPr11+Y0Jh9R9h5wePP9UdKogVgbSIVxyzulDCt+VSk3p/Ofdo8z8AriaXHzMEcXRXJyN6KsFD0DlLQBWqjBJWkyOywcQi6YgJ0uztl9FSVNGERAVErOAwxKCji2Zpm9pVIaRuOzAZlpkzlFTGTGBJWSJAwp4Ms7GVtbV1qpLiOELy5afXb3/rebtutrtdHrW2y8uPtv6by+ak7oaBPcuQJSnAyKLqzRSzJWOMyQ4sU+xPVFQn4o4xNBUmhDKyoGRUwiDEMe6Hj64/+c/+4//kxS9fdHGfOyABDjlnSMYJEPCjn3x3eb58+dGrP//kz6F49PbZsA9jN5BT53jz8Y4cHBmuSbp8+3rHul+eL04er5rT5vzds8X58uX1ZxhRLaq7m7uUElSd9c5Yz5ULIasaZ9iQlmLlBVkuhiFDqaRV6FyZTyfAJf8Wc47oqK+LIyPh4Yyeos2Fbw8UKlMJ1U/HYy6ec7zQEbZWUaXiy9GRq6XFXS3Y6+xrYnZR58FbIuLTUOcJpypj/4Em3DQOaV5fVZWJhR5EdyZADmaWBjo+GinlnOk4Md7smhn+IiIqgs6/NW71sJ+Pt6pvrFZfPObYHszlL1zhL/+i41lvfNfxxKNLe3zRD1labxz8t6H9tW7lIar38I/Hn9/49I3R//CsN97Hw1O+7mp/nUYzker4tsr1S2m/rxtG/ICc8vAF/05u6W+ofXlkF6CBZhmvnO8r0Rxf6PHp9IuZkn/5O3poLZGZ0+D1YbHhUtLesDGqmkUyMgyMddYYBuWci8ryfaomVLJIFsQj5QQALBljDDGb4x2JJuSx5DyUZpjNFEjJOQHwdWUMA5pyTpKtsb72xnKMse/71dnJOA4xZ8NkDKeUcs7IQAIYrnXHpGhjjLFGVVNMKaWsIjTX4i2xR2VSSFYGQ7TINjPRXKuwyI6ADIHhqso5m3MaYwBgTFG+zLkUHa8rlER3TcRga8kUrSRVgV5HTCElY4zRUuRN1VXOOquT/SZQI5lSFMSEPLGmuK6ZFExqVFkUYg1ba6b3jkIxzZJVWclSMYysY1dXw9A/MIbAyjQTvwiaUy7FWoWL8cU62ccMkDUFqMmYim+XkYFSqpGMg4EazZzVZtPCt2RrLfqUTx4/atu6alzdcNv6z159vGgWknXZnDx7+g6jefXq6snjtyzaPMI6FsmApjS+fPnJh5/8Isb9anHSLirr6Cc/+Ynk3ltdLtbLxToGSObr6+3/86d//tM/+/NPf76Dwep0BbL77c7WJDkxU1U3ZHzfdWkY4UzTVsTahd4Rvvntt7/97UeLFnVjVaNorJt6vVoZri5fbdrm9Nmzd87Pnv/z/+Nf/E//w5988osbxz6HLFEsbGUqSy7n3I9DjhGiRdfcoTB9QYbJFhhNp6JAhthPsyAbqIG1sBYM5CQhp5wKNVGfv//o0bur//A/+sk/++P/8XLzqqkXh/3um9/43qvPXl+/vjkcIAlW2dm69s1qfbo+WX/zB+9dvn7x6ScfGZMIQfPh+bO333n29jvP3z1dnY+dWq7eevrWdn/4v//lv/xf//h/29+kFCSkoJo1QjKgsGyNYVKNkqx1EmTYxbN3VrFLGslW1tb8ve9/54c/+uGzp89E8pDSf/VP/5vD3Wew+Nb3zs6f+P/gD//erz75xavXr263/X4fV8vnh72++mwzdgMLDFVQV7x1V3G7YOv00O32vZyunHfVMIzMXFVVzvnm9iCC5QInJ4u68U1TQ9H3w36/78e4PuemaeuqVqXDob/d7FMiw+x9s1wsra2LQm2UXhGbul0sWmLsttur1zcXZ62qOOfqyjMjpQjSpNL3h/PTR++//13J+OzTy6vL2/3dcHN9yGOxrVhV6qbNeWTLlTPMKaeUgd/74bv/6B/93jvvPX3vnWcvPvv4889esE/OUVVVIEPE3vm2XXzwwZ/3h/H6enP5+urutksJ3sEapISqqiXHrs9VhdPTRyfr9Xq9BpBSquv6/OL89fXlMIyHrlOgXSxh7BizKJExALO3RDbnPHbpsOtSkKZtjLFQZsMQVqiIjONw6A7b7Wbo+77r+gHMWC9gLJ49u3jy9CynuN3dSpLVYlXXdUppsT4fQ7LGiaKp2932YK0bx3EM3dOnT713Xbfb7Xa7wzUz3d1tr29CXeH8bFXX9U9/9townMXJyeLs7Gy5XDpPrmJV6bru9eZyHAdrbdNUICDn4giGcewHGTpUFU7Xi7PTc+/MbnuIY3+2Pl0vV3EYbm/vUhhyTmeL9TvP333y+Nnr67sxm5jpo89e/+//50+r2ilzUDnECAEDTeuaeqHCzjXWuu5w6Pud6MAWzQInp1ifuKqhoQsXj05PT0+ZzWHf393uxzDGMIpisawuLs4q70MIKSFnhHFMKYHUgFMKf/Dv/uHl55tf/NmLDz/52HKliWNiXy2z4MWnr9bLdX87xCGADFJGBlvrnCt57sOux/3yDCjIEvmSYC8KsGHnPCdKIccUAPjGL1bLdrEYD52Kjl0c+8G7+nC9q2qPrGOIpkKztuKSWJw/XVw8b//9f/KTy9tPX72+vLp7YRhLvHd1ud11+yGkLuLd99bvvv92kvwXv/jk81f908eoKwuQ844IdbU07Lebw6vPN4cDsAEaAMAIEN5998n507Pr283V9nK1XL/11rNf/vLnhnjodEz6+//2297bcRwPh93jtx+Ni8N2OKSkknM3xKrG6UnVttYzDFEaBMku2pO2We22/UcffrrbRmfrZbNuquXnLy+dsSXi4yz7ygvldtWsTlanJyf/3R/9z3bE0q28NzeXh/1trO2SpJJErWu711eUIVkn4pJhtSomZkRdy3d+/ztd2F/uP08Kf2Javxh2g8nWZj/ejbVrYhckiiHDTDmniLg8XxpnwxDuPrpDTQgKGAzZkDs5PV+2SyQd8xjMmDXkpHnMEhNGQpI0Zo2qSTlbVUGWWYqIjgYeEeU4KQ8yTVoKVBjgJfYmZaNXiVknMjqbQqAmJUfEynMprmP6YjGjj5bXfWhwdn6/znoUylAwE/MxJHZPGbu3wTNNWg8kVAQfSKd0okKDKCDE/BWzTOhkWUxmrWqxIRUQnutKFwd3/p77h1JAYZyRL1vROcuRfV98vCJAZFwxrUv+AJERyTlnBYxhaxyRhDhMwBABkzQAjvpZ4EkTlcSwQgUpSc6ZlblQgVLWpMiAKdbWLIz6ayLKOiFWRz+7JAgwqZnepqiIKmOizhefH7MHSyXsCJ1Sw77oOR77p3SdqpbRpUwAGWfYmUw5sagReIUVOOWGmtP65GK5WLW3r+4o6mlz4cn/xb/6VX811sYjcI5q1IBdjFFVyTI7ttaw1exi8mOqcvuMn37rSbOowxAomV/+7BMbUdnme9/8/vvvv/9P/+v/FgcgYO1PLfndbRe7cbE+qapqv9uFcYvZXSciM+VCSgzJewsgjMlZQ94mI/6ZiYvw1vcf1Rd+SIeL09NFvWpdk8a02203240EeNsSk2t9vXR3/V2QEEO0ZPrdsF6edJvhsxc3GIEOCMCAUkqCSwqwRSbA490fPvXrupdx5GE73MZbOOalb0w2sYsSEMZhHLUAaqBShAkwMMZBSJNIzBbOkGUYyZJjlqwGHO96hlFoqbwzjRmZcoN5Hj4lJg2e3cAyHWhGfI6OPE2CW9NZ5W9sJtCHJmITAJUM3M84HJmPDzKBeJ6GZZrKpCmupfAfPWwTDUBzURLMApnpjMf/SmsIJWXlqF4NzUUz8AjHEBimYGfTr8QgGob+wYSZ7gwgNkZVNGUQsbX84FkUKE6PdG/CAl8B/30NoGHtVyfGPcSbvhKj0K/RU/o6jOJ4P0dn/40Tv9K1/8pmjPm6j37tuX+d9jtOIXwDb/ryAQ8hQHwR0sKvA4N+t5iRiBwX6COt5tdiZG/sZH9Db+V33o7j/o3B9LAnHz5LmQm/4dMdpxPm9/uFXpwWtWMwDFlEymFQZsYR/J5WEJYcARzZ1DwXlyi5atCSX112fZnsl/nbHdtME9DF88NAJ1MhpyIIrklyMTgLZFYqjpVlmueAkjGWiIVE5uIYKWUpQndHsnqpfsgUNZaqK9MVhFSgkhXEoixgcsawIitl0WzmrEA92k5z0UJmzjrJeE2fFnNzMjmPJG0wkVRcImQTEYeNzsTPQntWzSoiSTUbikmTIJWUeDKpRB9Apdw6k4pKATSpMHJVRFRADG8rUCnfpjmqueemz6Og3OZUbJGhSiBWkZmeO3PWkZIAudR7LxrzNL3Qkt9SqMGZrRXDIjFlGLK+sr5yl5/fXTyilKTvpO/6cdDiWWdoiON6uTg5WZDmFIb+kPf73c31zf6wXyyaurEkftU+qSs7DuN223/y8Yvlwl2cLWMMl69f7ba94UqEvafTs+X+WTx0A0EVqW5cs/IxjCHEru+hHdia2ormvutAqNZYtHW7cGxgDJwnYguQc6QUwKZujTEUQw4h/epXn8aoIJakkgRJlUWNKImW7Aya8Skmmgr6Kakis5aSMke7G1NOK0rheUxbbzFQkJSMUUa3HzfXuL3enaxPt92h7zprPZFYz01TxzCEjBQlxyEOEgYc9mPW1A1bJFYYyUgJl69vvfVN2xpn4phvb3c//9WfGeNMRX/4T/4xlK5f311dXkvWP/mTfw0AI3KaJjIUYTViASzxrR98Y706PTs7PTs7TzkhqVD+5Ue/vL6+vt3vWHK1WBs/9MP44vPN55evxzER+xSGMGKHMQXL5AwniOQMFZXMxCDlnJVYmLn2Ygw7bwH0/bDd7kWm+tnjiK4fjdNKbAjp0HU5c1s3KpHAxjgirry2bR6GNA4x516yWDMoyFojyFnCPsUYR+cNIOt1fXp6stttD91u6FHXlXU2ptQNo3UsLF2/ZXJ14548uVivcttuD/thHNN+6DHAmCyax5BjiM7AejBhHLrN5mqxMmcnbY5RJKcwZskxByJm4zJER9jKrSrvF9XydHm9ub25eh3GmBISABkgYAt2aJfV8qQ5OW1LOLSpm+W6Vnd62Hdyk4chZmjlvXGcMlLWYQzd9m6MSQShD2M/WmutI4UbumEYRgDGOGbKOQ99Nw5DjJEI3sI6tIvKGBhjoGBmZyshYWMBFpjNZud9w+BhiGPXXV/fxpAOhy6leHO1bxeeSLMkgJpV+/TJsq62KQWA+z5enHlRNcx1XRnDWspLRWImNtrUlXfGV94wx5SCiJa0VWFAFivjrambqm5c09Teu3GsHRll6cZus72xbNumalcnVbMwrnZVShH7Yby92R92CCnZ2hlXtdZ1YYCKaB7GPkU4E31VxTjmHAEwYMuelZSiNi2pdn0HgGNM1mUQnLXe+6atCOFw2HV9B21V3DiGcRxUpKlqa+ns9EwCXV/cvb7ioYv7g6jC+wUURjiFyMwzSkWTziCIjvodZXGedwtSYmWdl+zCZSYiwyzEUmQaRVKK1rkQgqQcQ2SyYLA1bCQoiCFgiJWYDvuQLg+G6zRKzqn2zttmdzks2hMyTrZ3tk5VXaeUm9Y/frRMsa8cvHPERiRLwiAhj3F720nAwrmDjZSgCYiARb8bbvi2S51nl9OYxsOi8V0XlLE+gfMa4iHluFzV5+enlykOw/ZwCERgA2NYARExzrW+iZK7IdzdbHVJrPzo7My7oT+EfXezP2zv+sExmGAMKmt9rmzDjtBFXVFTVyA2292Oe4wBhokYIikKggyahQQkRVDTFM3qVOhBAYf9PiIggmoQKPZ9GGKlbJ3162rpVtGFPGYVMElKMWjwtvLeWTV37s6yIW8RVRw74+Mw3uwGZmNra9dORCgnADmLJEGSmbZT2N8sOFb9mu26OV2mbMnFZpoMNpkPmPCHGeYAz1LMoNmVFS4iVFp+JZpTxYqR94DeNLMmvq5NR07Ml6Nm+b3JOl2FxaAk+xRZ02nMF7tBtdhC99o20xXuHTM9IrcAoIRikE67p35ZoXl6ggfF+47IzwQZHIkhhk0RJZWsUooalBsjVUFJeoSQkBCByADyAAEoooVz95Y+EZqU1KEE8GTnlnO4GGulUIsKaYkR6pFMpUX59evbF7xy0hInnk4tfUXzKCoKUHOfPRgGE/ZBM2+LMNU31SIOMTHJVMkQirprAUy4vEV1tWuWlfcu9vGm37R1O0rKkjOSrZgcCMiaZCLsZ5CAVOfidyqgpGxQIuBOrURFpmW7Ol2t99eHMMqu2ykSW4iirlyQbhxjhoARc2RhckCyMwtHdR6HCrVuGorOE6BkAMpDilAcwmHoukj9Am0a7vowIMugQzQ5cYw5ShJrLK9Pqc6cMpCNtVW2TCIpQuEIMYISij4J5wnAYsNgzaQxJgpBNI46QtnVQNQwhto0J+vT26tbgkFOE6hkiu+gbExR7cwzQlRAj2NpyOO0nOAlKvy4iWsH3K8VCiWecj0IJPSgYOeD6Yk3uBGzktob42T6iea75KoAACAASURBVAiiuMeKv3hJmlen6VLHIpnz8feXmg6eJyCm+VcGcYHaaBqyTKwkBRSexn5x/OarTh79w4VKkSXPaBPN3YV5Zk0XOurTTwuFyPTL10AIDx3kN5CsLx/5xh/fgKv0N6D7/CbtN8E6/pa33wGAdQQvHrY33sGXgS36YisfvYFMfSXK+Dvs1nLxr0Rqvu7V/puCWB3bEZG9x5u/ZgJ85Xv8y1u5SIFOpkDcEcl6aMJM5gImo6fsckTEzIZhjwDWfIqgKPDxbAgIkbCWqigo4UFkBgicp+oVE2jDxhf+d2EZUammOlttktNEClIla9iwiqacBcLEErPkyXzDFBIkBhfFBQarqCRhNkXXsTyFMcYaI4BRncusKBXCsRooSVYIg8mQUUZSORJQC0c9ixioFO0CJjWkpfgcTzDVBOxNtWknK48UpOorL1lFhEqFAVMiKoWdNYVAJOccCEkQM5JCpj4ko+Ayv4iAUjpwZv4CKJrTBCiTtXAAsqYsU8onFZDw4dumIm8FzVDlY5CmBHgxMbAUkkrVRaKZJlwwUDBQJDMgUMcWrFkRo3KQqgFbu7uOVRVilJAOriLlsForE4ZhF2P2tlksGhK8+uzqxcevr15vDt1hPxxWTdO2DbHWvobYbr+72ew/XHzy7K3zduGdd93QXW+u+iFKorpZfu+H3z6/uP3gZx+++nAPg9NHy7EfytAtsWUmYUcMpAjv8fTxabvwVavKCdayIbKkKllzH1JbG2Xphh7Y+vr0//rTP3VdTeCpGh1QhmvWKBAqg061lMVhdoULN4VSyuA0KBv3hOwSQxIkSubEaohFVARVvTTWgHTsh+7VbnO9vTh7fLfrXl/dLVs3jiNBqtr6HpIQRmiWlEMa0fWh63aq6eSkBUsWBbnPPz/E4VPvq6atvXeHePPRpx87056dPX7+7Ll1fim1bS6Wi+WTp49LxM9Z67wlwMC0zQoGoml9fpKzGDCz225315vr3W6/ubndXN0eun5nejbQlLe7cGD0fcrZ5GTCqDlilCzCE1IqImmG4zOlLHF7sBWBU0m/dN5WlWfmzc1+DGX1QEzIKQGWjRaKp7V129Tkg/feuQoga8U5l7OOQwwhx9AZM1pr67oyTkASU1Ikts2iaVar6p13nm829c31zeGwC3HMIkpqLIzlmPLN5tawRWZlwwZVbaxdVLZu3aKxzedXnzJoGIbucBCEs4vVeuWfPj1xlsa+u7m+vNvebre3SQdQSkpEZI2zvnLW+cpXVbU+O3vy7K3Hu/1nL862d7uhH1RgnSEiJmqaan2ybNumqbyIiJL1ZC12+9ssygYph8NtSNd7grW+FqEQ43Z3GEJg4nEYcwpN0/RDxyPtdtvdbgsiYxwTqyKENAxjziAGG1iLuqmsM8aYELNoFiEimzJlkZTk5ub2ZH1RVdjeHcYxfvbyOgx5DEEIl693qxW1beMr0zTOnTVn52dNvdzcbvq+jyFcXFykFAF4750zRCqSWQA2zFQ5S975pjbWhDFIRznBONs0jqBMgUmrqjLWMJFzllBVzhk2UXJIaFbV+vT0/PGT1emZbZd+ROxS1+8//fSq7DmGTdM0xhk/+pA647LmGKKEfkxpZBCrGkZbYd26Ve1qz4alakQ0D/2ByDDZ2jt1VlWapmmaiowOPSQjRx+yDcMw9EIKR2qJx25sm+bx+dmr5SqPW82FX0nWWmdNDHGS6cWc/yRa8t8lK8Hcm9I0h8ZnZ/WYdl4C4kVTEkDOKYbRGjdFfBhqCIyMHCXCgb2LWWJIMEjbeLeDdw2ps2RavwDZ7hBXi6VhX/kKzkMRhnG5rB8/OofGFDIgmsUal0GHQ9jfjoe7HBMW3kCiJiBM6fO7m93h0PNK26UDZVB8+uzkdrOLaTg7a5oFjZsh5qFuVqrJmUbFhiGwgavAMAbWKFmy3lVVbSiEOGoOAhVSsmDDJMaAzDfffS/GlHNkUu9N3VTkci8HzhBNAjQVacDhBmGAL9E6SVlyiiqSkEiFVAgkJdxvjM2UkWXYj66l2vtBgxGpXevbmoKhRBIR9iGPWWIpr6KSoYpggyVjYWHQ+Ka2jSbst/t0CFnjRG3psF6fFkkFwawyrUUaEbND9hVx1jnRpnx0jLproUhPqEQReJLZIZylZCavMWclsDImAOuhWznphNN03lcY1XS8uxl45SnXrxgC9EWb/97rZPMFUEYhk0A5lMCFzcRKOPL+j5Ha8kqmpMCj5XrvlRYYC/cf6iTXPMnfH4EeUhyj7wzKJV2JqQQPWXMJcAoRsWHmeQLK0avV0s3TRWa6CUOmCkJUul9JtYhKTDK0OuFTPOOSinm+0xQy1KPGl4L4zQC/HjtcH/RpGSNa4pfHNeS+dGMBB3myVic5ewIIAjWqNGdtHf833dhEalEUIfvJoiMlS8Zw1qRZWY0Ba9ZxGHb94N6qhDIsGTLrk9Xuuk8xC4kQCjVPudisGQoRIhWFaFIYWFAaozPqrKucN8YY54YhX91cXW0uf/SDd69f3d683IUdSAW2ospGJI1JJZN5WKlJi5nlmMlwDJGIvLdZhBwAmAp2ZVBJokyOyNPQD/04GjJslGoyZEhYUoq53488piFLtmzbthoTU2AJigDKQABFaABncAZlIgKV8ukRw2FIlLKTlDM7rivfj0N3iK6p2nV7p3dc8gYFyKUejOHiYZRxJCJTLeqJYKUTZfB+4pUpS1OZ0Tl5dW7FbTymkpV8vZTS8SVP0/kBWDrtMTqBYrj3BEvfzk6PYi69cBycE3DFCiVMORt6PAszsbJgaTqhVyQllbAw9KjIHOsRslciUgIzKd0z7Mqg/gLodrz0PISP6w/N3TKfNq8E97AcVAQ8K7niOAXntXjuqPsem7+63M7DBL37Dvn6vzz04r+yfZ0L/8Ypb9zSr73sr23/fyWi/S4ZWA+xkq8EaB+2+8oCczbf8Y/HY77yZfwOIaRyqeOd/NqL/xuHXmGm9t1v529M0Vmg/QgMvzFVvq49nIfHH+5nAiiX4tsPjqE5eqYq+X6bZ72PkqmWlLKynEEZE+2IgKKlhXmpKHu6HHUlC4e8gFlgUIkol42UiIhN4WsVYpGAyRq2ZHOhXwGuhJ0LRoCJ0cooisLmuNzMKliz+Mj01MzEQvl+/RIFYAwjQ5SyKEElT1bilBTOkxxQVokiCimqgRPMVxAwZszhlLIO42hlqqqQsXOuZsG4SImIgXxMt1QVUSRBJMQpb2+qqJ7yZLvxvHibgi0yT0wynVLMhSWIqOYsANiU1AOdlOdnV0losmhzKgYXgaeCh+WVlpz6iSJLmUqavipyiTNi6hyGapZstMRVBGMQOoxFmj8Flpy3+4Eq1A2NKXtjhnGIIaZnofJVt+tevnzxqw9f7vZjXTkL2/Xj7bZ/9Gg9DDln6Q5xHPHZZ1dtW4UY7/a727vbmAM79pVvG29d07R1s2xfPn798ccvb2/308jjyYoE5RwgGbzA6hE9eeekrtk5JpuTIGSF5pR7yaHQ97aHsdvRqnXrMx0/QWgDxABKlgyTQrNEBUOVDDGzFAdCSmB5mkZSPIq5wFTZplF27FLGasr6FMnQJFxZ5zxYDqFLB1y+uv7mD949Pzv/5LMPU45df8g5GcPWMdsyhAzYQoxG7fNoJA/G5xxgZblqIXfbXby5u11vrk7OWq5ifUL9Yfvy9eH1zcuqbpltXbUetHxqs7B1vFwtFovGEMcopK5yFRPljBefvHz54tXtzd3d3W57dxdjjjFpIibrmGLowwgYnKzRNmd9nw7bzThkaxc5Uk6Sg8SQkEAKa6wo5RTjkDXnDNQNnAUhk2bvXXKOACQIgRlNQ23jvHXWkmEPtTlYYrNaN95b51xKGRNYKLHgegJwLvXuGsvM2ToYI0RiLNWNV82LRU10ykZ32+04RlMZV/kY43Z/N/Rj5WtvKhLuh7HrO1Lb1HZ57s9OFvXysbPm0O2vrvMYwltvLd575/l733heNUZiuL56fXd7u99thXPSMI5RVMkYYsoi77z7fspgW7Vtc3ZeWed3u21/2DKzc66smt5OWS0qOaUgIgwN0bx+/apdrIhIQYfD4eZmFwJ53xjjwaYfwjiO1jpfmXq18t6MoR/Hfhx7mEyEmFNOyBk5QxTEpc+hBGbjvVdgv+9TTKpqjE0x5hxykr6P1o6HLl2+uh6G8PrViITlojKV9GOsanUJZJAOQ7sfVmswe8CKkhIv18swjiLZGENGUw4EIQJBUkohhLJyC6jrx8N+ZLaLZdsuzxZN1R8uVSKEwhA15JyFgKZunXNV06xPVxfn52fn565p/l/23mxHkiTJFjsiutjiSyy5VGVVd0/fwR1cDDAcggT4/w8kHy4f7huHAGfppbqW3GLxxRZVFRE+qJlHZFZVT2O675AD0FAViPQwNzc3U1UTOXLknKwm45REjX0SfXhIHCpar8QSGsfeBwlEZGqS8zjZPKW+5Ritje72anNzu9lsvGcpNgW2uUxSjInJO88NzHLJeRbHst1ufBcczw93Mp7S4/0sBU1EmXWY59/99psvX3+567vdZjMcH71D17BnirHdbjd39w/IvJadq8xihbhViniO9UmnBpBVgcNVLac6ValW8eeqxEiVflUUml1m9q5zne9cCOmMRCl2ftvvQgzH8zmPBY5UgLMxNV2z7ZpumKY0F5j7+OFRKbMnlTKNE3FxHtdXm9vbfR7zNJ1zFhMex/J4N5wO8IardtuETdxvNEuekpTCjDklnfK29W30IHNeX72+ajsljtc3OyIq4nl0vtHj6YF2feObTSsACOIQGtd00UvKQx6dRCqu4chwOc9lmtnCpu3ArEBsow5SRjUiF3zTdaFB55vb/fXt1W3jYHOxmdLZkEGBkM2KIUtBUilQghGUrCJvZoDCAROGx/N1v+mbtqTExbqudRyGKR3vTuUoHw8Jqx8iHDxRYdu7nboYm7ahGCl2oQProKdyzmBy3omq5TKMQ0ExWd39nMNSW1mgK1qiOzwPbJcA6dM2E1VbqBi2Ija2wBlkKya2SDFWx4CKnDwLFAmLFTJdQsef0Nta9iS6UC0IIHaXQqCZgdylwPnsnYQFQsKTSvglVV0cAkkXbaxPPvhJ2vkZxgIszjZ2STwvV2P5K5Yi4bNToCfmCpY+upq/1NNSqKiVYoCpN/cELuHSU8lWe75q2oMVb1xYT6aXb1k/iBVqq+GN1XjW1vOtL1Z0DLXku37lz3KupTBp6wljrVCuL2NBQ2xpcahj4Um4iJ8UuJdrqVaNDFdwrb5+8ROnNfk3UyibAczk2YUQslGSkoc0sHAiRYbg4fDoHF9vb0KM169uvv3duzIIOTI1Y0Ed3ERV30uVwWpSap265Hw6nnZxt9304zQ+Pj44amMIWfNvv/nn/+V/+vsP3737x/Tttw8P4MLOMwdVyZIghShcLjdASxpRC8l1iDKIKFtRr/0uxmsXel+CchuaXZdyGabRwcUYKQQ25kJwSDKdhtMwzUTYb7feN0JcksoIJJAwZrVCLMSFuBgpL6QnKNjmYUrkwsbXpMm5AJltREIqSRieyZzjYgqQp+C9c67iiQxTcVAjKzWREJiYLWbvFQVaoGRaIRXmWop2l0o0LiN9/aXe1c/TQ7tMHrp0CxuoClx9xpawZafKKrAL6rnOYSWsjOLPFw+zFRC7HNQWz6hqe77klyuATos6PIS0ZhZ46gBZ5sryXQnr1KijtS4/F1dXA9HljQstsX79mqBV21EmVX5KpSvr8t+KF/yYUvM8Mcenufafsv0YhPk5JfH/cNtfBsB6wjeBH8OKn2FDz395jv999tf/rttzxLGexp/SMfcfEcD6MSD445/AJxjNvwqmXm705QJekMenF6FPhO01aFi19Fg1Y1nrYIsIbS0gG8yW2lRtYCNirtlDvU2L8QQMtbZFKxMeS+F2KXthqTIoal8Vk8GswCB0sbM0WsJ4eqowAKRQIalfp4ZHF+JY1Vqty1lljTKRqBMSq058ujwvqmU51TqACdQgaqTKWpk39eFETMWUFnYPoJoFBIJjE62KA/RECV72MxNTMyOt4g+4LO0LlvTcwrkWNipFX81YsaCGSeGX5vdK6gFJNZjBSpSt+JEBuWQVUzHvAkdyYLOykMYBqAnV0MnMoCIgt6JPyyOL1mfWqltGZmRrxZQqmGwGYiUCqJQCNngCGxRTNoxTt7+KYZNlKhlgsLNpnItnNQ0hKOzx4f4Pv/nh9998M8+y6VozjGnyLjTBpUlOmIh0mpNnnI55HOfzMDhP4zhud7uU0jie8yk3zbTfvfj6l6/6bdfswtsf3n3zuwfkRZzF/Pp83eP1l+3LV/v9VRSdC6aibcrBxtkwFxlFJ1URoYf7NA8u+BdLc0821KidHXuyLKWIIyF2S3RrzrQ2yF3mKXH1w6yrphlVmh0vT1E4XqP1JaycjmfbgB1KLvD49pvvXn51u7/ef/XmzYf3H0tJxOw8nGOCQeqgdCCGobEIJ2koc0qhZXRxt7luN6RK37/7/nFAuw23X2w+/HB49/1dSnZ9c9M07f3h42/+8C/EZqZNG/f73Wbbq2maChXe9PtNvzGju7vHj8ePHz7eHw6nPCsbL6btDi5wLoChafz11aaJm5I+Pj6k4ax973OSIrBsyAYFOXLOkZFYtpRd70KQvgs+kEhJaWKmaZzyrIvmr0Pbtl0XfICpVqhlLjyM8w3va753UfEgQghPARozQMW5ELsYY6hCfjGy9/ztH77Z7rYhhN1uC5OUErwThmYysxjjdrvpu22ek0g+Yx6mqejZMOe8u9n0XeO22/3VPoT4q1/+8usvvnjRdyGX+azzw+Mppdm5IGo5aZq1jgMzmfN8fDgfeDwcxn6z7bo+xLDb7Td94z0756EiRWDIOYuI5lJyhloGxpH7fhNDm0wdhxi6TcdtcM41RQ3wHjSbElwMse8jMx4Px2E6eU/7XRNjHMc0DHOaQQ7egeGD92qaS3KeiGia52mccsrMoQkNDDmrqDVxI0rDafzw/qgGFICwv7putv7u7n3XLWqAp8dRynvAe885C7PvulCN24rU+ruoCirvRTDP83A8ZsE0JmZ/HueHh6yK9lEO97mJYd9nWHLsJEii6tiGpmmZfAjN7e3L/c0V+/D+/q7MH4kDc3N19UXsom94FlGFphlDUURiI1d8YCg2WyIyNjTBtcG3TbjabvfdpgkQmUpBmiQrqVABpMDEAExTmabJB7650bYNIjSd9XRI49lCQOM7Bs9T/ua3f9i32xDj9X6X5/3D/aEJwTtWlbZr4sFPU3kON9SZD1HNFj0roAY2rTQqglFVUCYj1WIGUqn6v2QGK6KSxcQ2+12IvukagJrQZCneO+fQdA1zsDRiBojgDRHTeW6bvvHt3Wk+D2fPX/xwd1csb64CRWGnsbWcZtWm7zv1wSx7r/cfj+/v8+keyIg7f319E7l/9asvLMv5dB6OR1NJeXqc77pduLm+ii1znLe72PZb57Xt/DiOL19vpjlK0XEeh6NBqO96JlbNjojNlSTjcXBim3Ddhb5v9iacNTf7a3jORofz+f7xeP94Nw5DynMTI9h1Ag/um/bNF29eXL38L3/1N++/u3s4nINNBHAyUbECyqaWVqMqYygZL0CiGBxDoaNumk2z9Z1EQWk4WOIylOk4Yqz+MNV+EVQAB3joJNllLm4+J57PNgqBqBg3XlORoQDg3o/zbKw1T2NmcSBdKTtPYRoxLxDm5eVLrPujOLA+OZ6CRVqp7QvWoWqkFTW6AGNYs7xKLHoW2/8UgrUEJ8a0JHt4ljWg9vuIXMCsS1xnprSkqXj+KsiMF+Dhgussu617YYXtngWiNfSip3T4s7NcC65mKxRzga7W9n13oagsIVkNBpdzuSgvPH2ikamRM4JWyegFB4M970a8fBIWNeo189dVwWutVC58rSrivlz5C4L14yu/AIaL5SBV7QZbr1Ptx7I1gF7vVD3mp4yVFQrFJTJZMDQDzGhxlFk4LwpZsglXm68cETN7sqglzSfhFk0f9zt3GEbfcpJZqbt+cR02yDNcdZtbusNkOTFyhgJVJa3FvWk2nwsBqjocz/PBXMjqab/dfjh9pCD7F5uv/vr2h8cHuYdOMweisESeJvhsIyaFQbRCIaJiDBVFg3YXrTEhKSSeoQ6ZdCqZJCcVYrZZMSk5ZKiZpQRilMKaOU+UzpJHwwQ1RlYWdsKkREpcg/qyVODzLOyl2cYYgzmUJCYGgyQ5PhygcOya0DAVI/iFBVCTlVqwgEMtCqsqqQq0hkC2YjLLuKILGdDoMryxDOKnJWJJ6z5N6u3ZIoDLu7BmIBeEmwir56ctSBGW99qKK/MKzT5DxJ4POVo8PZf3XjKd5xj9Ah7xAnYz8yLI/8m8WPDiy+q0orQ1GanfWZ/WmMsCcDmZJ+CCwWSqRHURtgtaXVkBVYzyM4jDPjVP+zlI4ceQ0/NXnqfeP75Wf8rRLqJJz9/15+Abf/y9Pz6Bv9T2ZwFYPz7pP3Kil3T65w7y7w8PfQac/UfEp/7VbYEXLl3Qz2bU85vlnFsqYM98B/7VYVd3EJGLjtgzKNMZXbqv64nY831UFSooS32mwtpkhKonXjsNln42GJGSLlWD1Uas4mNLSYqgBjVIKWYsIIKSI4aHVZkztwBBtW2PGIZScikKYWMtpeAiZ2mkYuysVq3NTJ7EKSk4Ai1dekQLxSileXHiVUBBwlpP1jwxOwfWSv/WFcUBV52t4EWKY5Yq58W2FtuwOOHWFkJmVBRMq/ucwUBmKc9W29U9q1VZGLPaVcOLTj8TO++9sKgaCZEtkodlEQIzmKE29UHUiGQNS41ULasSmZHpUmKmSp0zNpgpa40wzUSFKkteDWQCYBFzNZDW5yQIOmvtCgWedCOVsISUTEyk5CAFqs57aoSDxd73cbNpvmqbPuWzi0Yhz3IsQBozaQ7ODcPw+PHhu2/f3T8IC6AlTYUKoeOUC0xVJlVLpcQWmvw4zfcPh/31hmNouvjh7sO//OZ3m66/ffE6ZTkdp8fHU2y7v/+f/+5/+B/BLhCRqJkaMRlr27kYIRiJ03l8lKIoMmebymw2KUZAnKN/+d23WtD4V2oYhhkbYAIIKqJm3i1WwcXAJo7ZOQcjAaBQNaxZw9PEWxh9YFVTBhFcrQozkTkidlAjleUh511sevrD7+43N//y1X/+8sWLF/cfHkMIbdNASYvN43kkWVAeJRRV1e1+k1Jy1mjSh7txe+M33X6/742H0/TQ7LZXtzcxdKbu492DD0ROC6bTdHj95cthGic96Tyflac0y4yGuikPHx7w299/8/4DcEbbAJURiKpmJZDM7Npt03V+c9XC7PCQ7u+HMvDjI0zT4TBG35HV6buCTVXszqxGEjHG2NL5nIvMZo3z7ALarmtiJ5ZjJFWbpinnSZXS5OaBx5TbXkPLMTY1oosxMnMInohCCADlnMzQdNRv/W63dc5Vod/gXZZpGBElOsdXV1c5pzGXu+OpCFvB4XBIKQ3tsOv6/dV22zelqIkyOdX0h2++bXzY7XavXr18/eXLl7dbRrn/+Hg8PeY8n88nkZJyVgKj8Y6bpoltp2pTSt9/9y6XMuckWmLsd1dXmy62bdUVJQZVM9LoAxNBTNVEyjzPh8MhcjON6XAYjofRxG/6fSl8Os33d4dxnqYpTRNCg+sXTdHOB5vmiRmbbbPd9ldXV8Mwnk/DOGZTds4vEDjRNJ59bAx0Oo3DeSwZMYg1zhQli8Kur17NWYZTHg/wDRAAxmazbTfx8eHBcTTFcE4PD3Y6D8D3N7c3m0131e2bNjoHZhJ1zMZMpRSVQipsWqeEiZasm22zRZPmcRzy8TC9fzecR/z9f/bBoW3b2JD3rErENpxnUxaxpt+Sj/cPpw/v3h2Poxlf37ze37y+ut69eN2H8cSOyYG9ss8+GDMBIpD91eaXX986c2nMkgqTQDCezvMgOQ1jGrh3BohoyQqa2ka9d9NUxiGLYTq+6ze9D41KbJvdy5umib6JvuQ0W/rww8f7Lx6+/vKLX//q61//6ivP/03L/uFA79/dm1HjQqJiBCZXk9hAzOSUrJCamhVUhg45wMhcHRQEYiliCmFZnMJ5IQHVB8/x/ngMx/r7bnM1l3PodhzcYTxqbcrfdMQUGkxx+P677/dXjop/vDuPI9iE4fOUD5S313DeA5TLfDwdXtzevPnFV7/QN9dXt+R255O8//7u8WGK1HVxHyj+/jffhRgGm3LK3tHVbtdeufaFe/n6+ua2e/f+d8P5wfls0POgw3m8ffFqzprzMGd7e3ecZ2n7/ub6KsQemCRJHuY8zoEiyJtxKuoRznfnf/jnf/jhDoh4/Wp3dfMieneGnIfp9DB/fPv2n8tbBLx+hYfvHr98+Wbrt7PPj/O4cR7G0ymXlAiejSofWRc2zgocGBOInRNXHPh2f331anOau9Nwmk95HlIeEhK6uBnPA6mDqKkaFtGAUcc8l90GmCFSihTHzsQciBzbUsFACL6QOGOYFaJ6py9RWbU0ZvJi8hyfsfUxQmsdsL66cAsuOR0IVAsjRsYrumGAXTKGS3C4pG3PgkW75KU/FYvSMwdDM5MFKViPpsrMBtBiH7OgKEa4EH7W1kVTrjZmfAGsjJ8+7MIMWr/ms8D1Cbn68XnWsHLJl+nJZG25ybRCg0TkQaJaRKQIhBkwdhXPMrW1G2pJr0GkUCKrBaOah9eAvEpYXErDzA6lNiVLRa9QW+bNyFZFiSVrr/qsRs/0SO2nK9BEtkiwMxh2kStajB2Wi1ExrGf8jDVT+ORC1fJx/awV0lqKyQxyuBi60QKcqAmgOSurixS8L1ZUVTMY3HXdCWMp+vHxo6T88lcvvnjzxSmez3dnVwemlIr04RM/5idw8PXrF/2+H4c5Nj5cI4/FkR+mcyr4x9/8X29evfmbv/t1DrY9sQAAIABJREFU027+z//2m/vfnsipa4J4p0L2KKBQAcb14rMV0SJgKGEuGiJRh82b9sWXLz7KhyQTGnBov3//djpM05A0gwiqsHkJ7VxLVy+2zmFOaRplbmw6lvlYZAQyS2YqxMZk7ODICKpkKpLqOiwFVuA5xm0zzuMwHKHa9I4zPz6cWg6OvPfBsWQRExMyNeEKIpalvZJWp8hqUfo0AReWEP3kJH2+qT0ppQAwq34G67hhpqr5t878dTmpM+gZXWuZA+aUjGG48KmeBtlqK/rTKad9Shm7rGNmBhJD5Yp+AvFcftZ1YCEi2LouXD69rjXGF8rUSrcgqNbztGeeb1glJqtLhDI/P+ACIxgWpsWnkMKz7PiPwR0/96fPMIq/CN7074N7fIY2/AW3vyQDa7GN+/nLcbl5P7nbz33Df8P1/Tcc6i81Mv57bPTZbP+pV35uq/1xz4fpTwLAzz1En0ONf/xuPh+XS+TxnC/6fIFSgD6xmCHQ4gizAFN04Ucv6+DlEb3W1zy5GmWpCRFjOcnLylPXHDMIlsWu/mGF/G09bVQQvkZkVYIVZro0DbI3A6rEOEhNtUBFbCXoy3qQpaeP4EBclOuz1QCpwA0bKmDENdxRoir7VDvRjJm8N8dMDp6gTHBmBVjqZOw8MdsikgozhgkpIEa1QEcoqgDDEbHUQrpCmBZh/FKKiXqwo2ofpqZsKkSAwogWLxJbUD4swZkn86qqhVTItJrMutpfqQrJ5jwZ3Lpek9lCPasloCpeZmr6FPkwrVFuFRcgB2IlYPUYWdpcjAEH8goycnAEBrcxbLu+aburzZaImrYJ7d539vEwOGeSVbUwwvl0FoULETxo4pSU1DdN63yw8yhqzjxMpaAAzGpgGOU5pzwP0QHW9w2xPRzv7h7v01zGUb1vpjxG869ev7p98YKZh3FU09D5potTOg2Hg9A0z2fR4hBIWU1AjnjLTHD87sPbNqDZBzOaxhFWeRAACKJi5OBWzTJmuNo+SnAGFChYrcoGPF/WDAAqy4Jo6UqtPspEFdCkpu9c9CBrXe9aOt/N3/3u3f7mdnPTEpiI27aF0Bgl+gyMqI9yzRBYMpir8AQTpulwPrh807bNTbdrsrrdJnZtV5KI43cP89uPc4gI0bXbLbw3UCpSxsJJ51lNiLuI6EKI3fZqPx9zVJmQCwxgYnJMPvhIpkPT+34bQgRI3n/4YRwHGCFhPCXMTsFsnrUhMe8aZ1ysMGX1WkZlD5Gs6kLwRGDmvt2knbVN13X9PE1ZhpzEhzCep5xsGq1kKOjx4Ry70PcUoweccx6AQb13XduCbJpFpXhfnXIqMlzqhd/vd0XKPI9mi21PiN2XX+xFdR7H4XTMedIsp4ej926/aR37XPI4zGma37zaEYw78hvvujCUsUzpcHg4nY4ikvIkqtM0zSllUwJvlTtqDDwmjt2tpVIszeM4n6RYTnNpWm2b4Ng1Td9y413MYqrmTEFcVMdpnKaUlaapPB7O05BArWOo+nnMp+M4znmaAYVnnB7nXOZN75znpm0a74DiWJvo0bfB+aKG4lW1XjTPPvp+nnOefJoY5swFkYqbQEthF8o5pTGhoHhEXx1poaKqWuaCiJLNFGNCLjl4v91s+rbtumgmiViNmQ1MGljFS84ANuxPpxFmsYnMLgS33zddi3m2cShdMw/z0Abm4Fgd1JsZipXCZs7Um6IkO5/H4zmdxmTKbV/UEJq42/ftvvEe5NUomxVmAek8JFHs2/CLL144Cw93j8eHo4qWabakqlnKmIo43gqQ0zzNkwj2+yk0Tk2KIQswqrl546L31m/YbXsYSkrzNM1zJm/H0z3o1de/eLPZbA+H0+ODnM53h/Mj5dB0TRPDLIVAzMGT4wWDoOCjFlWtPenKRlgesgpiJnLmK4ltMfZ1K/xCACG2sXa0GAOemquN76OajNMAsbjddL6FqSF1jB/evWu3r9X8OCIlQCy0G5eLpOzAMXjHtNtsRMu79x+O92eYvno1/9Uv9y/2Lw9vT9Ph/ffvvkuDasJ0Kt654+n4cPjQ+u7mxZXrpdWOiGJs5jIe70Zyqe+9mebEbTMd76fzaWK/Od2Pc0ZDKe5TC+fqeokmmYu0wal7PJXh+HEa5nlKUmKUlAYcP45W7mPX+oJ92BibKhWoSUkP+V25m+/0r978ums3m00v2Wymc0klIbBzFDQTNDERo0KHzAqFoogzlmJMcApnrgyaT8hnK4Pms2CCRUE2M4GgEmnIOYOqEIRg2O93bdPG2JQ5D+OYpxyi953LWcpYts0uWxJBqX5hKhe2gNXamJKZglAb0i96izBzzKrG5GqtEovYwjPNJ10pOTUlRi2toRYOaTWrWeJ5U70EbU9Bvq2o0ROERMQLmWEJyghQM7H6QNQKSik7z0yq6sgpaXXdXfsjsXDhsWBhNUHnalVGS+hEl49+nqXi6f/LmV2oHOvLtQ3LaAHMVshq+X8hRhFVChbBYComSkIwcxWUqM7HeLoGS6i8QFasyroImi6XmGqVErTm4YyKQiy4EJOSqZIxQK5CCcvFJCYiXSTBLl1Rn6FNxLXEBSVjWgDEKnxNxotvWuXDWw0hQFUogRxVySlTrDIPNbSrt+Ui+lEf5GvwURmfBgLXQLV2ZIjpLEauWlbXvkgrVBL22/3pPE4pH3B+nM43b16B43FKMhQrwiGQZROQkYdjqvGSqAkUzofbNy/bfZzefcfsr3/RPLydy1lPj4oGP9zd3bzady++/EKvf/jY3x9OUnK97d75rMLKSspMzhGIUc0YbYE8tKh429/urt7srm7242k4WHLgJnbffveeCmyxEQyWBMlI2IqIsdemAaU5EVE+5XxKNIMyIZEzV0whZILqX4klG6LqG2oGYnbe+egt22TSNCFS1FHO80SG4MjVqkPVPSy6CEvV6axEys7qcBI2Vy/UE570KXpV8RutvTBQIra6gxkWD4Iqwb4kW0QryQigVeAYC3K9aLeRrhRLAxFqa7cSQFrXqfU9eAZnVwTVgNrFWU9VK8Vw4Tgw0fPO3oWbyE/zubYVrqvQ81nwxwE7vUzYC/S2rDc1gVSqWNV6uLqAXVCqdTLUW2BMAfiE6/oclPjjyfVPvv7ZW34OEvo5rODnPv35z/+IfYV/LoD1HFOsPz8X87aKYH6+5Zz/FEzuJ+/TH0dVLj8v7/1X4Z5/Hxjy37w9R/0+gZb/hO0z3Oqz41z+9JyiVW+Q/Yz75nPE6rOPqG+vSFbOBbQa1C4rEQHIJS9s5qVPkJYndD1s1fPxazSBJ/amB3vnAStFSJ4WQIDsEiU9CVAuy6+YOOdgLLkAgKsfpKrKDCxegABVlVBz3pFfCB0AyEDKkrOJVcM3U7Oi4KqdTc4xOUgpLXuoqJkKRGACkBmJAMTmXTCFqGYpRgKuIrMsBDWl4I1t0QJcTJsZilVsSVUqmx9mpOXijY1alyQGHIwNLIAygUjYOVLRPFsBkTMtVgG1JSZVU1SDmFrZqt2LMICcC5HMSUpSFngBi4SYQorBK6jUunPVy1/Is8RGVVebAzFBdOk/J3KOHRszMYFymanS6MBLaMSOKJJjUCqWYcaezIEDTAsXROsiAmcc3n+Yy+x79Ffu5aurjK5pfHTeJFzfXKdJd/ub+5hRHsCO4IjY1OvEIW7mcSDn4QsXTkVf/aJvYiti4zCJlo93d+y43/XBh6yak4Sup5DOw3wYp9tm67Bp4s6Iyvk+SyFtqfA0D1M5wiFJKaVET4695x7ka3+lKE3z2+CCKM3jnOYZZ1DPpESBxOAseOep5CIKMMiTrdr4jiXNz8qhz+LxJTphNl4wWCYoqULYvCNHiAG5TD66JjaVx3X8mGPZ9qHf766m8Rj8RMpSlCnEICCSLFIyGXOzGYaU8rTZdt2+yYfj+JitWNeF2+uNUjSay6RFCU2jHqcZOqGLcs0UZ0vZVAlCUozBse85xOM8dcTXr16K8tvv70s1wfSs5sEO5IWl2UJ5nmUO3F1d7R8e34mUrGPbcYzbxvlp1jwJ56bxsWtaozyXZFayYROwuW5jIEB3+1ZE0jijkAORiePctkSTU0PjurvDkDOVGQryjTud5lhUhdvWnEclzUgpQBFl58h5DcGFEJh4HjMgBmUm1dJ2LRdKJT8+Ps6zbLpNt41daJvIkULjfckpTzOM2jbud23woWTtO52m9NWvvyAydjQhffP2DzX8Eck5p5RTKTmXrKIp5yISY5/JewoimIumWRRe4ApsmIYkOWfbiJitcgzKiU3VUp6jc/2mcTF4JY80nsqcLWU2bmNopdA4nR+PZxCuttvGFyLyzs16Hgfb9eH1y5uu9zmfp3R6vLsjZiYXA1PRnJNWyF6pa7eQOB3zPLo0BR9czl4VbedjG20a85xOx9MwnpoNYoxdvwkhgCRNpWuaeRrNvCP0GxxnuOhiiFCazhMrGs/5PKtm58FsHLnvNtaiesh+9/btNJaUvBtG5wNxG2KMMfZbB1WTx5yGw5DnzE2sZFANLQMxp3w+HZpmHk9pPOd5zo7b4/H0/v1HHz07pSI+uNg49iCGD55BEhvJ2rfRSZrH8Xj3mKbRORdiDIHJImIHdidriCnjnPI0TOh32YqwMxexaft5mlPOehpubrDtgoMbTtM0Huc0OQb7cjrdg/SLr7643r4YR33/9ng6/+PbDx/ufjh13a5MNp4yM7HzzgUVlVLUqv2I1rWZmNixI2dmKkstIppTUzEpasZCuma5tcsjMzlQZHjMJZuzoYxwQAQI3BN7zTnlPG437R++/d1Xv7wFfFGkjGlUxw37IJoJHmYlJbKdZ//u/f1v7983gaH7ffcYX/Qff3j38MPHD9/eHx6PIsgziBBDcOTPwzjIGLYocd9dhc0+TDkrmaNQiPKsDDo85jRQGWLT+ijoIm770Ls0H4/9tncWnDX5oPNMw/18vJf7D6ejHNXh17/6kmOZ8uyMeu4eP34MPnQugmMpnBNKGfPweP84nz683/lbU2z2u/vHRyMnxDCoeEawhC44mMAYWgXxzXsCMaxA7YvXL0zt7oe77797p8bRBS4+cJAg3jlyIK12vdWM2YlTdUrslLC7vqoxkiMfu3Yek5hZFijFPrTesaKoGsRREVdFGGBqVCtmSmrmCAqzqkeqVu0xGTUGghnxohDDkGeAlV4iBRikxlq8Vv5gREb1UW5mjFoSIyIQMy1GMMtjanGkJpjBfS7EvsZ4S95wKW0aGfHClXemsiiX4oklZtBapVMoTNVArLYSy5ZQ8hKcEgAo10BviRuldhGDFuGCZTdDvTq8cNi0yNJWX3lOsrTUOXJsVHLWootSKdGagi+C8c84UQtliIhJqiQ5ADYsyRJAtGIFVKXoHYxJ1UTUwRGxmjjDKiOb1ZSYCI6qJR8MqMxQKqxP8ur16zqQf6oJ18tMAFDHCUPJmcFUTcGLp/XisFOROoVVujOwAOWqqBgbFrshYiLHxFU0vwqLGJjMDAzHVe9CuXL5K6IulM8l58f9f7qJnWjWrPoPv//Hv/ubvzuXsi/Xhx8OMopzDiqeGNlICEqmpL7WRcr2ZttdbdobH2Y/DMft62DmhrcYMMAh7DD78/v5O+r97X9qXw/N9EDlbGXi1rVKoyNSUZOlw00hYBCTmoXWW0S7jftXu7AL4zw65yk5naGDYax8LUfGgRoDiYmomgxBG04hGhqJbsKcz+k4bv1VoXIeBV69iySAwqrzNAGBPYdJZjDgKbQNR5c1TzLDgRyDyIRiH+dRiiQnjghqalq1PbSmT6yOa1hIDGNSWrCg6uwji8L/JX0yGBHYsYlU22gfKrNvASwrVA2CyVJfxtpEXPFKvmDWtc2VlgG//EcEooKyTOwVJ6hvqiPKVesnq8q9RCx19tUhWvehSxdsTe50gZZrloS6LAFuEQFG5Wwx0aoU94QpXyCLpzxq1RpWW71MbWlyXNqyyRgEx1b5npV+X6E2oidNQFtNwitO/GxbF6NPUvI/glX9KS9egI4fp/mXRP7H7/rx0S7H+bmP+PO3Px9g+cmv82cBWBda3WdoyI/P1Z6NG3qm2v7/b//+GxF574k+mV0i8vwV/Amo32fHrL/Ut6hqfZ4x09q7R1rVgBasXdeghp+PHzNT0+DbylzVyigCmCg4vzK8tKqQruTldblZz+RpMsOsRkZLuUihxM45T1blrmGAOWZjMjPn+OlUKlC4uv5ijc9qC59lA4Fb771X1Wma920jVcerms4A0GqQTExV8gFKBkdw3gXvvCdXlzjRUuBWnYbKRlFSyfUlXR4TtQygWrvhV9NreCxivQARQvAVkVqwRIEWZBU2IlErhmK2PDgBMWIwiIwgtjDRCJoNru5GtcJaTUysSMX4QhNznuAukWoFVWvMZ6ZQXWv7fGn5rDf42Y0xJWU4OOfMuRpLW62v8BLDKtAFF5sAo+E0EdH3776FQ9vhl/FVnts056aJXefShHGe+7jrN1vn7sBogiMNkiTNk6cQQvSBjURSlqzocfPi6up6b5qmkofx7Lx22y7GGGMgzc67tuu7voTTKU/59uWtsr398G4ch/vHOzVpN+1m1ytsmAcA0zwqjIx823SbLSHkoiLCjvse+6srmB2Px1cvBB4qxVFwxHCO1dUe0dWHwBiM2swKE3pWEfp0MyxhImjJQwxY/L1FjWmexqKqxiBwqMeDZmti9+Lm1T/95lspOfgAa9ombveYj7lMM8xcMOcxD4PlkbkRm3IRCKILu13PHlLK4+GhqBTui8hm652TcbDxjHE4tp03JabIAKw4jya0PrQla06lFLDjq+udbGia8nQaIQXBdTHE6EOb2JemiX3ftm3ISaWUkoUAx6wCLWYFjgO7IKLKAljbxD6g39Jm17CnorlmC4AOwzCcM/Ew5yk2oWmanHNWzYKyOHhZmUXZbE4ARKRpQ4zOuUBExCaioiJSnHOqiZlDcICKZlUxQ99nMytFnHPe65xnPZ9gvmmiD24XN6Amz2ymMfhNF5vYeecBVtU3X385z9MwDKfTaRiGnBMzOefmNOWczeqqWVNXkzGFkMiVeZbHh+PpnIhYDOMwD0NqWjZxTRPnWaUoI3nH0UcDSlFuXV1EfdRg9Mu/+vLDu481MwmhPR3H4ymB5hcv91dXN9MkBIoxFpkV89XN5uWrK2b5eD+ND8KbZAYiR/BmbglbxUop0JmZxjEdHoYiwknNUtux9+ScJ+aH+/vDwzEldH28ub4OYUNg57mUuWs71TIMp9jE2AQvWTLNkwWnljWN4/B4OI9HkdS0frNpr15cBee956YLarrf3aocT6fpPI4AfGhi07bN1sfOO+dCOJ/y4TjGMFxf7zd970MIPuRUxmGc50kFJWsIoVGb03Q+5Ye7u27bOc8f33681oa5a7yL0fd9ZKUhnZrQeOfOx9PD/fH9h3sT7Pfb6/0+BAcrxOZCcz6LqqQkU+UbGkzNh9Dv/G53dTicmrjZ9le7bQiOm7gr1zZcz+N4ljIBut1FyXY6TJsG1/tXnq/evT/f3z9u++PpYeq6ME+RzMM457I6eyBb9uRW8kgtjNfCNtNS3VnAqrpgoGYBaxNHSYJATKaVYJIEgdEyYPDsPDsmC6Tq0jydzhinGUDwmIBxmiAzhbzb9W3vyMyzOx4Ow3nKeR5OGKD3m+MPzfvHj8M//t//9Iff3c0neIJj9F04DZk9h8aJqMxqOxSfHoZ7eTcchqHfhs229x4hWJ4kzblte0/x7dvH21sOjb+96bqGLU9N6FreIIff3d199/uHh/eAANmFhrizTbdvGp3ypFS4UD5lCxYckTlJViY2oTy5swqC/pP+5m//9m9vb/vf//a74TRDyYfGJspFWm4COdMkAhFRMBZeuGgpMHzx5sui8/sP99/9cO8Dbnc3bA6mmnQ+z6GJVqAQq02EJkqmotM4XL3cX7+6HsdJSqHgXctgaBEl9F2/u95O81lJDWBH3nuIgJiFVauXDK25Gp46zpbS58qvt0vmwzCrzYlrDEXkFpX/NUukyrQGVZWDJVFb1GQYC0H4IqJzyamIaBVz+owY9CwgWP9hAFCKoJLolyySHDkI0VrPXIkR9SMu5cuFdP+ssgk8++flvJYasD1poH9K1Vg4UYtKRU2GK1FkvRqXKHe5jvXrCgxYann27CN//HUNKyHObO1IUlsZkhVP8/757rDncFT9zrYgQytEuOBzREt0Z8tFZ8fGULVKimJe2F62oAUr865Gf7S2Qyz3jFatLVrWk7qn2vIpT1e2Ru9Vcx5YyHUKNfgKvDl2BHY1aOfFnwm1N3s4DhbAoCxlMpzTGPrY7trT+Rz7ON6fYGYe5k20UAHBEZF6Q8Hf/Je/sUTvfv/x7u2jpORBPba715vT6cFvypdf7ZrOf3h4Z9kPee5f9i9eXZWR794+jg+jNKWq+ZtpgoAQgnPBpbkAtn+92253Vy927pbu7e77Dx+5o27bZyqP949V/sD7EChSZuZADRfOmb2pShJ2pDPOMkmUIkIduGdE5Gn21oCZIlnWLAqt1D6DBxxcQ6FxIEzzPOW5AiYGZXbdJp7mAQpRqS0t9covY6V2YdQFnxkGMiIjB9LaOSo/gUdUsPEyvgxW6/kKNcXCy6ugzDpLa/DJePJBWA1FYRB68hutx9fP5sIlR7OV60QLcl5huAUTW+Y8ChZe1/rR6zqG9QTMnmr8y1QhmCm4rj/LgxA/A8fQ0oGkkOrIaTBjdqa6CM8v3K4l1zVeUsULOoaFgLgg05AnuOoz3OrP3P44ovScdFI/uuItlyz7eYL/2Xtrt9aPt38Vcfv32X7yi/9lNLAuT4VlJjxDBJ/v/Pxe/jkX4ie/yf+LV/b/I9ufiJU+BxAvN+LHY/ffdpGf7uxCiXbMvNhgrd3LNeleHrCfoFcL1ETr+njByy8djk/jB/bHRtH6h7oHYSXQV3krATGpmomSJzATSO1Jh77CXQs/dK3oPZHBaNFb9WHFAdXIOxZTK0ZiDCuXUxExcjCriDwRHLkQgvdGVrQUEXZMakvf3SLoo4vsYpUqcGzswFjM5mxtf0Stj2llnYNWGdeq8S7VFbgezJyYCUyXIJMJWgNXXSSrarzCWDyqoAqRtWpxWaQBEpg8M6a5XPILTr3Y6VQUD1USc5F9MMIq0WomCwEPIDOuogOLC5ABMQah3PWbrmtE9Hg+qioErJgEWniepMxpHsKoVnJB4Xa/8c5dvdz2XRiOE1uxoqaWLRVKTeezjFkLerx43W22bU28VVGKZpWQ1UU+j9MwjcTOt03TNRvD2Qb24Tyl8zicT4cpDSH4qaTD+RS7WEdOKcWHyORrO1wpOs9JVWIMb7584yjkoRCbDw4RTKxJqqy+WSnCJs+9UOtzXC/l6bWivY72S1xgRmYQW3zNZY2KCUXF4BSqxVDEV4GbjMePx6uvd/ur65RAmIMPIXBxRTRlmdQBBiWd80m9ImCQg3xQeOx/ha/++oWL9M0ffuujJB1ijON4HIfJOdd37CyZYB5hxYJrYgyqZRyGeUolzd0mOOfHYX73w0ctdPvium038ySPj8d5KsGF7Xa33cVhmJnIex9CYPI5j9M4lSR5NORxngANMTaaZJwnpKyW2ZemZ+f45vaFshSZ2bkQYs5zUc1FQGqmU8rG5HwAsRrNuWpcA4A5a2JUk5xLvdg+sCcOIZipSMk5qapzGpvIjJxFteQylyIiSCl772Jodrt9CI1zQZTnuQzjgDHvto33KJJLzvNk8zj23Wa32W/6bey7x8dzyXkc5+Gc5lnMSMiGcSg5q1mlB4hYKUUVMVopcj4Np+P88HB492EOAUaYZ+QZTYZ36Hrv2RE4zSZOovfBexgzOREr43weTqfj8fr21gX4YCpgzuDkfO42iC2azvpNG2PLzCFeg5WdOOemecgpq0qM25RyyagKpqZsZqWoipiU4EVE85ymDBckeJiFXJJNuWi63b5SvU8FexebpnccRcTUmDwcVC0lMGuaLJ+ht5GpJeuG82mehsPDMaVJLbcdVBAa7xyu9l0MbUpp217LllOefPRpLvfHmc5zbEZyQYt8+WVfdATDewRPsfFmOBweu9iUUkKIbds1TRtCOA7nZvJF1DHtNv1f//rXh+OH/W6/6SN7MyuatIjmnPuucc7NqRDzfr+b59zE1oUwp3moouI+hN3VNM5FUmzQbeAdRK0JsWv6TbsvI15cf3FzfbvpujY2V7sXbbdxHLyj4Pm//tf/rWl9E/ZpxvmUp1GI/MuXL3/x9dc3N+P//r/+Hw5tTslXS9gLVnXhnGClmCxx7YIz1s6dmhGRrbstEr8AmbNgUnV36+PPAvnQNBobZibjUkSKVOZzKQagaZu+3w/DESggu9pvrl/2zFPJYxN8nkoe5xjajqeu20Dp9DjnyCH0MT7kqDDMgqvrzak8TJYDqewVAbdvdi++3grSw3ScBFQ0ZPVKXdv6UMZpAFvsuOnL5nZnKBzIxdhv9n13Mx/z3Q+PH9+n4QAkNL7h6OdpVLE8zFkwzfM4j1Oa+m2QWZMmLZpmygN7FjjnIawYz/l8GDeb7a7b379/T4liDMIsWVzDeZiDo+gCXJNLmUsuJcFps2/maQbzw+E4pBkOcCjIjuAaHzZekmmu4Y4YgT3gHDcEJjVMOhfOceMN7vHD45AHbGnje1ZidcpaihVkFROBqBFXsSAmJq6t5XC0JJ/GXDWPaoRzqVN+Gs49F2bHpb+OP48C3WIuDIaRoirHM0AwUoKr9vaw1bml6kaDiJYewfUBphU4w6dPNgAiC92qev4QEbPTS4iyDGxaFG2ezs/McElWF1zmpyLiNUD90Z9tAWgWmMYq22Q5P1phgsWy03SZRFUZ1cgqq2tFjvhHVw5rulvrlqq6+BeuJ73U/LRKFAXoMlWrNQ5UwQ4L/LXEZYuuRT0ILYSXqs+o8tTwRETV8mgNZStMtf61vsIMULyAAAAgAElEQVRQVIuHSr9CHVAEZWJFlc62C1yyVNaewYV8SZRrz8Wyu5JV+BNsrLAihQv71sUQfBOaJrqe344fGgQwm5FnjNPQxBbeJMj+qh/HAxhCgrSGxCIoQAE8Xt9++cPH7z6+f5gfC4mHcozN1avbr7/+8uo2xO0sdO60/d0/v/9wuN9tX++2O5KGG3fcnoZvh4wEAvyC4Ocs+SwIwB67X26+/vrNl19/OdBpeje+n95FNLFpADpNZwBazDNFCipEhTy77a43yHE+5pR8w+RIULhpvXLYNT35h+EoH3M5z4Anw//D3ps1WZYk52Gfu0ec5S6ZVVnVtTS6Z8FgSJpMgMwoo9EoSjJRJr7qD+hdv02PfJeZzGR6EBfBSBDEMgBmxcz0dFdVbvfes0SEu+shzrmZVd09GGBmTJTE6K6srMxzzxInFvfPP/+chYVBDnUtpLIl6kjJjGAwzUpOMQZx0WTIyiRSuXvFrOjDxFmx3Dow3cXY2NzUoWstoOWlfI1n5w/zqyIfy3nXHzLVDOIHcaczL5LIPmCluK8VLt2XuMkZsn10jK9YMD1S5avuw0pOdGE+3+Dq1z1CanwhMgSWFfA6e68Lpk6PxbO+otGa3ruA/c6MtcrEAr0/IjYQL8H6mpW/dlP1Y5a5UFemxz7vV133b90e8SseHOevO+AMVH1w5NcBBWcY54Mf/oqf/Zvv/tdrX3mJXwvAeiD9EnndJr/UPnjgX10g/D+131Izs5TSB9m5j+fYY6joV2mP14WHT33p9dadFYC5sS1X9y9H5QilFF8TGLmqka/lEc9tDe/9sht7gMCYY4wAkqkXdQNkPYbcyIkrrGZMvCTELeXiqqxUjS7B2QEwc9M2sWvcPefs7rGPzmROYIE43BDOQT2myBAmAox4YdZUxryVkr0k2vRwo2rRAW7qq2u91NgmQJyrNnMNOKyBPidnEmJydnPLFfYCCkrVcYYYiKg4dNlsWMDCBGEzY1czV4BBHIKEKJGd3EyVYAwtZ8CuruYFRVPpN1ucg5ClqKmrQx/2xkpvtwAjI5IFzyRy8xCDmRcvVUsBqkYKMZAYGRhLGKqJc86x65u+n4d0OL5DATmZe9MAifKhPNl+RIIpjZGa/f6JGt68e7fZb775nd/56Y8/O9zMiOAOkUITZZxOxSA9vvGtj771nW84ytvrN2k69ZvOlI19mpRyMVRRkTxNEzYcWtnL/i9++CPNNgxjzggBXa+VwrxTFaGmjcJN32522wtyubk53t3e397fpzyZ4T//z/7eLz77wmffPn1ilpHgrVbAUoTJqagSUZC6GruZ14Llaxit7uqPJ8pifS6ThOB5yfvwJWXEzdG0ApCb51yoEwBg3A+H+9vD60+u7gdcuAFz31LOOQR//frZtu+n0/jmi3cFlUSJGJByeP6i/c4/+PQ7/+CTYb79/N1nz19cSORkqSii2KYVpnC53T+/YiuUZ83q82mYxzQMkzrabjweS7UuNFvK9vbtm8vL/PTp09/59Pdy1tvb2+F0Oo4H9ZlNnTzlFGNTcrHZ59EDsOs3DdE0apmSE5zV04SixiDxgfM//XvffXf95nQ6hMDShPv7e7cTS9zuN/2mD4FVCwkRsQtBIMwUEUMrEgjFipaic9J5nsd5IKCohrD0fddz18WSPaekWszVlloTYDItSwIxkwfhpolmOB5vUz5tN8+7rmfqciIzJXURjjGwCEh+9IOfcog559PpdBqOpmqGlIsIQmBZKnmCSfqu3e8uReJpTMMwlWz7XajRSGHNwbueRKLmCNoShWEqmhOT9a3n7ICGxghaspr5977356qac2YOoQkfvdg/e7Ybhun29i6V24uLy4uLPqV0Ot0Tc9u2WuZpHkXCyxevYmxKPuY05qxwMxPNnouZEly3GyGS2HZTnuBoWgJ0mnK/aXe7/fPnzw+HQeR0cbGLMY7DPM+p7/umbcex5JThfH+vhRwdnj/9pG+vpiH/9K/f/eKzX+S7qvoBIEEOaD5DwJMrvH51sd3tXrz86Nvf/Pj3/+C/HIbh55/9/Ps/+uE8a2wE8FOZLi6vnly+BEiLTeP89t1nOWkIcdftuqZr255ZVDU20is33BW1KNoG3u+ffPrxp6EhgqnPpWAuc9c1H3/6CZxTsnGeWMJm17x8fbnbbFNKd/d3t4c7wFkkMnaX+/2+zaUX9o9fvnL4ptu9fvnxp59++2c/+dzU7+9ONz8/3b394s/+8n/7/g9vcYsKEPxP//N/30rXN1eRLk5H+9lf3xxPx/v726eXl5+8/uRnP/zs9uaYT3Y6zhzQSm9u5ZHm7rLrYvGW3WrR+WrOqy+sDaNVO6cmfxkg5m6qplU1ObaBidk5cHDYPEw5T67ggNgABnIWjkSSs3PQru2fPt3ttvF0PJY8aehVnT3m0fq4ebb/KA32r/7435rg42evt/snsck558NhihfNRehPx6nE8vF3Pvrmt77Bvd7Pb9Okp9PkjQzZ0s3R1Lf9dLXbh6ad87jZdH/v97+tYf78i3f3wz3ThaC9uyk/+as3P/mr4/gWKCBdnBQmmCMddZzTOM8p53Qqm7a3ec5zTlNGBnKTqVALGJdifpH/9R/+6e9/5++/ev5qvElv7u6gxEbIOussai6CCBYKLCUYOGhQCGOHYZ7vj8dhHkEoBA+IEpvYdU2XBx0OgxfXwjXvTwKrmHfWbbqE6bObX2z6vqQM8acvL7ftrg3t6fZ0++72OB14Q3MpmoClcrILheLuMIApCjuIxXItp/xgchORlVLDWr4SdZhYAi/jpCpOnYGmx9uOgwRgJwbIFn+Y1yIa8CV9DkTuskReFrFHIpjpCv8sZIn31WwWCdEHWxJEJCzCTLUwD9ECxK3m0fv74tf4aV9pyrovMj1Kq0o9r894fuiVf1YdZlr3Xa/K2OaqdRcgpjVfCV6hnK+7LoCapkSV9o/Fb6IlJ2HteDNDlRZ1d3MFOcyoFtOmpa+X/nNCTc0zgsGDCAiGOn9hbuRMa0HranQvCOUiYFTFuJ2AXJSobv1SF4+q+U5GTFJfUaXHVQ2N1V12d0hgWpSkYAApsVPNvnSCmUHdTJuuIVlM+mkcp2n0o8uOy6QkxsyNxOvbd1dPn8qG+6ft/mofL0RA8zBlGiVSzK2PRBpePHv97e/+7r/4X/4FjsAMRI4SKFPyux/v//rVt188+7hHf0p0D8lNt794uT9cn27f/KDh7dNnV9/+9jf/2f/439ze3M5TAnkuZZ5nCrTbbVj4eDrN03xfrofDIXatRsSuS8h3x4Mia9Zd2+eh+Gxwl8zlME82hwvqdk1HcpoGkdjtIjjudts86uaipaeRtjS8G+9+dMRJ85wIkUPQXNw0tqLBNNjVs6fbq+1s03ia3IxDZJeSch6ywhhiSlCgYKXmAajau6hResAURYuZE4pBKzOgTpyvBSlEVr9M9ZxVWychEVkuH3zQDGbO7DWqvlAb34eoALiBGbbAy6vLR5XiWxGWlRG8Lghu7roEUEIffMnh8/MT1sXDHQ6FgRwmRLSkkdQbdTLhsEz2NXz+FRNycTmXaVshcxCgXlNsyVBnj/OjndWXR3mYv0sCjsOdV2jlK3V4/m7tMTj1y485FxmsV6/5VX8jA+v/jZjMb0bE/TGM+rgXHigtjw778ve/pP1ylPHL9/D/8/Y3Aqh4nwr3dcf8kvaVJ/yaNwJ3rWkNldB5hrrON7DgQouO9xlVqwa3oQI4TA64etFSkxOBZdU+38oH1195Q3WtdMLK4bJHRLMz28ntsUpbtWDsnNJXs/eIqhA6zESocspq+UVibptQzBxudY2LS2odVVUAkSDsYDMCaa2vU8zM1bRWmbEaCmcQM6s6zGj59xnYN4IsfYRa+dDdXahWCKyL6TnmVp9NKAIsroBZpTihKm5QEAllTou+vMAFYBaw2CqM6qCKNp8jMYKlFJCBmcyqzs7DAr2YSGswlJmrIjt77UQmrxWgjQhCXIWZSr19cYgxw4SpQWgDCeMIcxAFcce0vlrC08tnXdN7wetX3xjmo+sNsbRxO83p5vqubeZmE/dPN8d5dodlzHOe59xsEAPiBu0mcqTTaby7vdViMbbMwY1KqdUnwdQa8uEwHMc5iERpPn9zEsE8QxWbDQKEHEFYFTkXdydGjO08pZzscD8O41yy55nuRx/GqeTccBdjrIHZ2hkMjhLcoaVIkCWi6+614hDV4GrV5FhD4iu98TzEzSpAuYiaVIumhrrJmLgObycIBIg8jOPN9f3L10/KLQaH6bzbbK6unvavtk8vnu767elwv9u3t8fDPM9gvHj5fHexu3jSP3/5tNlIcvn4k9dPnm7mfDocj/M05ORQi1272+y7Zsvc/OiHP5uPw93tcT4CBdTCcplO5fnzJ/2uZz/o8RgkquWUh2EMwzBe31yP8xAjtn1LIGYhZg5hv9l54fF4d3+bDjfHktiViIKzOxsaQWuxC0+e7nZPNl98/ub65nqaxrZv264ZhzJPdjqlNjqToGutAtNsUIKCI0kUImSdL7a7UGLRVHIpWoaTMqNpRIi1Cowru9E05ZyT2aJiR7ykOAOSU8lpGIe02Vjb9SwkImJSNKVEOc9EHoI0bdv1vTvevbs5HKZfvL1pQm9uw+k0nJIZJKBpA5O4WSoWY+z7rm1C38W+2+dibkU4NE3XhTDPWd1ijG1rIXAIjXtzOqRSpnnK4zAd76a+b9zyZttc6bbrAkBN09ze34UQhIMDqqVpYt+3m+2G2FOaiYthymVOJYk0wUPJ6e7+OI4nFrq6ej7PnjOV4qo2DSmlAogpVNUhMbRNH0LC6hzBABbe7bZqxiwxdu44HE6314dcdLctXd+aadP0bevmdprm0LebzUUpfn97ur0Z8iBQRahiLgghUGRibRDTIGkacnpze3N8/vL5xeV2s9m9eP5RKqlpo0g06DTcbjZd13VV48WsdC11bRel7duu6/oaKWkbDmxCwcG77aZtpG1CIJzujqfTwUnbTdj2jRY/3B+1eM6mRZqui9LH0E6pvHlz/fkX16V4vxEBjXfX0pCpjePN5f7Jq5e/8/TJVeBmPOXv/fEP//f/9f+EyTiMyJ6n8u7mgAFgNB0o4t/+y79gsYuLH2y2fbfZDGMKkS4u+49fvXr29OoPfv8P/vzP/nK4TSdJgTjnGRBhxlIfHksAue62VuWWq3lvqAq77uClbhsvywmIoEmNFv4vkRubWVItsWsBT+MMAwRM6Jqm7RqmUNceZgKMoKXMec7uJUqIIQSCTjbcp4v9zmY6vJvnA8BoPt1u95cSQkrz529+8dndF8+fP718veeWL55ceGODnu6n2zGPk+rFbj9P82m04ViOTYo8brtopC66vYw3pwOFTBodZMZ54vFEVGq1X1gBAGYKYM823I33x8HdnR0F091cimkCMqBEzqAmmFgpqrmMBkUoDbVRs6PAuEjo2m3fIPAM1zJPsxO4kdhJaLlI8YCnz6+GaSjmp9MMQ2iw2W2e7Z7t+ksuksf8/e/9QItOwzRNk6sXBSLCZeifdF5Da0FLTu5uFBQlG2VNzha7OKbBbEn/BMASCLLk8fGqp0SLIvQKVC17uZ1/8NhgemS21w1msd5XG++9X1bNo6XG3GJ+nUXEq6rOwsOqiYcLYLLSJxbT6gGpwope4XEAdYWNFv3RBUAiZ2fwappUfL8KNr3nPH9glH4YZF320nOy5eMjH7qFIvsD96N+Zqll5rrYqLT+ttqvX770Q1t0xJZ0O3rEKVu5TV7FtOuuv8hyq8HIzQxlNbAWxhURrdrcFQ2zGjCswZXKyq+1cYgeSWm6u1sVt8ASgV4MVucF6Fp48etrWirOQYjMK8Ll1YRZOwC6nK/Kh/ki9V9PpXCCmi4RLCYIS43SATDW2EeHE1gkSAj3d3fSsJlxY6Oduiex7zo5+d1xgGCz6bmPp7fjmy/eeHEkQIR73oRNg86TM6ZZ59O7Y2jKk0+k7XaTnUYrhbi0NquaTHMz6ab84ff+8O7+fp5nZjbT0MaLi73vrprQTXE8pePsSUxoDFOeLUCL5bkAxo4ya0TUsRyPd6HEPFhOk2sx3ZgUzeU6j1VePOlUUuHA227f7CMRvf3jNxUeLZSLZwhA0KJ1RHfb9uJie3PM7lUyVwKk0vqEYplLVS2sk21ZBPzh+zrIzArUYQRdUlCJ3geM358ajzGOM9PpMWhi/qiiFgE4R1er7/Hg1mHBeesHH009AKu3aHXPeMgFBtwX72bBWJem6u7n0llLrGVlWNYaFO6ArfXKgAeSGEdZClgsDqOvPsrj51/0f+3MugJonc41GWKdY1gJDcvCcX7e5dnr1zWv8wNv99dBiD5Ar37JqR4nDJ6vfnbSz3fyK3r9H3j3/59iYP0qQNKZ3fP4BVTn/9e59H9qH7SvQ5G+3B5PgPPLove3/7/tcPyy3VDXJTOYfQjbn0F6Arxyjvh880R0vhnUcxSUwEJV9KpWX1niyqsR9oH2Ac42yMOytQDhqgAoUDXCKHBdb8idZdHqIl7phL6sYipsQBBmZiViIVVNY659HkSYJeWEJUOQaYXDmGXlkIkToSzpcqZai9rXB9CiTkoiHJiEajUSmC+1XHhZNtWUsGoNoqYH1tKH5lXVigEmEnJn+BJcR41mrL4MKk9WiIQKTERiFApsbOpmWoqeV1sTgi7QGNzg6sxgIQpcNLvxSigHgcAQZiaGebHiS0TWgJpHTlyTDLDmMjBYxFm5KuIHpggSoWDSSGyjNKGGh0VCtQMg1GpH4s+ePgvEh7tb+bgZbtLN9dB2Ufw+xtYN129vxmFMef7db756+vRJmsrdu7t5mtudkFDWeZjvf/6zchqGw2HYdjtYKKpTzikxWElIGnGicZpT1hC53/SnhD4ugBIHdO2GGczurvM851yIYJlL7/Os45AlhL7vc7Y85ndv34UgjUSzEkQQK3DrS5Ig3MyZzA2qNenTljKTTLR28ofB8EcTjxw1RLuqECxHLhVIDc7OxBCGy939YXvfR2kR8NGzzdWzpy9ffLTfPtm2eziR+WYTd/tumE/jNA/TcHG57zedIR+Od8fxJttctNzeHZOODjNV06JqaeYBIQ3FMl1sL8rkc1A0ZbbsCeaQQMNdhpEwbfue2OE6Tqds02k6zVpCi65vmhgAgcMUmk1YYmiZRDMICRqFIzHZkj9Q6tLlBCH+/g9/PMxHLWjbGELQojq5ZT+chuE0dtsuRolNDG0MUahB13cSQ8ppnlL7rI0WVENK8zTZOBk7miht16pmM+/brmvbaRoKitQ6X0xmOs9+ebmFU846DFOap+N96bdjv21DkBA3qno8HbRMu+2+a9vL7WXf7+ch37x7+4Pvv2k2mxyyqh5P+XgCgP0mbnctgHGch4PGhuypRmmmyU73t3Mq45zTXHK27UXIWQ3etm3bsogwyTzj3dvb4TTBbRwy8+3lxYa4bDdxTrt+E9SSaun7Hi5maqaFfeZSskkIFxcXpZTD4e5wuJumfDxm9RCOJ0cZx6EUCyHc3g05FXMRieY65zxOCFK5YwjzFJqm7eMevQhdPtn2m8YsExszuq4V5mkep6HMc0m5ROnu7w53N3ftpmEyKxY62Ww23W4TQjjcHa/f3Uxjim0DcwlBTbMWCjGGFsiWME9sKKWM128PpdA8z0al73vJrKYs1ndxRqOWjqdEEDcTYS04nZLnfJSp30whxCCy2zK5NrGJbde1gWGW0363vbu9uX47gPFMrH9yyZFPwzEltUIh9CIM4mGaTsP42Ref397r5S5sNjuOXMZrqO773Xe/8XsvX7y43FzcfH5Mo+Wkd7fHP/ujX4ABBaZlzhKxE6XRcPLv/9VPZwXk5xA82bTR+t1F/+rjSyqwmb77nd9ruHt99cmff+97X7x7d387RZHNtiPwNM02l8eLhLs/ZI48hH0W/50eoeLkQLYQmYVc4G46mxPILHAgJmQHoWkCYIGjUJhTTinNczaDEEqaj/eFqdlsm03ft00zHtNwPJzu8eyiGw7TeJjRBkxlHJM1vu+7IK6Ml69eNtsQO045ff7F23h6t30WuQ3k4qKb3WXJh3EeU0ITMCcNgUJA0vEXb77IfC+tR4kp2+n6pAc9HQzWtkJCYcYMdSLqYhuUWFlHFQ7cCEGne10cciOoeGEOjEQgafuYDke+pMPh2GgEEVqoKzwTiUHZ3cmJDUxGxVDM3QNi3z5/+eynn/1MpbR9Q4Ek+Dzlg544hYhWJ5unGQAH3u63TYxtF31DulUXN9ec9DSerJhqdlVTZZfxOKQpN02Tk4EBgcRIxEyBjFzVeeHZwcxUfY3DrU7p4mZWJ3Td6B8ZSEAFYs6fonWTWRxXhnMtPwZ3twpUvW94Eqqc/FqCePW0H0Eoj3YwWobk2WteDJWq5ejq7uweKFQA6zyGq4ll4FogjGpRE6vYHX2FlVvDQGeLt9b0Ay2iQSuetvbXch0mLHuyr3jXorK+zioDg9QMXms/LxiW1b75yrY6ur7CYQC8aqRbrXsNgGGLM74EARQOc5HV5qU1P3OVTF872rKvOCOxMDODCVW+dbm3WiiNKgkNXnn+i5u2VHyrJhu7Y6FvASAW03pF49VarsClOrvrkmlV1fNg7spe5a/JsTC2tBQlEDcUaKkMYIjUhCZIFDTkAk+laJGAvu+mNHTtvtmLxbbZPctTxhFlLtMx3V9fX39+Q0lEGiilydSLzFKjxAfMKoP3fXvF2rATMrmKe+Bienu8PU3j7d2bcbSqZgXD89cXzT4W0VxO14frYRxSSq4IocmpDPMMNgnsTmnChnCx2c9jejfcWNGorWY63R1Z6Mnz/f7JdijDWMauby8/enK6P0JoyFMa03RI+48vNl1PoNPhdLg7IIMbPH9+9fTV1VCG+/Euv83JEpmjIKdkMJ/NM5gd6kuSGxZ1qiXYsMLUVJHS9ziONXdjRWK+PCJ9cQLr0F3HQR2B7u6qVSb+vIssnpqvM3E9y4cXcK/a7R9cDMu6sKBQXj26Jd+vshmxOImqZZ2oK/RNxDVrZv2gV+lYwMGwmtjjSiuqhIf/cJZ4e9zW2PAD5ARvQ7MsgGvR+bqC1OWyVm6o83a5+eXyBBaU3wqg8zeiV2ve0sIA/TJ2dnbzvwz3f53Xf8YWfh0A7rfU/o4A1gfwxy9pj2HIx6Dg41Od21fqZ335Kl95ni//pH5fN5XzT0r5Mp7y22r0SLyplPLl1/+rg6AffP3gs1Vn6gNlq8fD9+vO+cu//7u1ZXrwe2c7L1kAFq2NNUEaa34yEZ1r1C8eOxYMS3U1PlYyCs5A+RoNWLu3JijzIgG/aloX8ofuN0AQRDgGMysliYSmbarW4HkQLhr0zk3TiJl5qatD5dlnLwCqHD5L4BjMl7wiZwjLw34Ay5pJSAJXo8x9qT8DZmKwSIWAzJzhAoDFSjGv9ZS9apxUHXhdqmr4eZ+yGmKo8Uk5W3kLJ3e1XM3Ia5wH5MoOVg2IDbddy4GKlzFNWtyL0cL7N4f52uEskMgcmYWIOSVdCO9erSdjVHaVgxBDNDOrBHuBk8JJDUQcJJj7QhmulZEIYDeyRmLsY7LZVEPs3YEWVgygVDIEgDeXPVTnKYNCnux7f/L9u/v7d8dh0+Fwd3r58pWZedE05awptHRx1RNzs/dpmiwrR5lnGofh/nA3p7mWbzweZjU1L84wzxyYAsxLUnUgZy1J95tOOKQ0gWi32+92e7PZrcxpNIVIM46JXEVyjSLCSUIIISDn43H+ndcf2eyqUDVcgE4EtULFU6WzsWVTU687Ka27LHmNfGKJBblXCuFj67y+n5rlusSoa0FCMCSl5OyEOA0zx06Ec5labq6eXH36ze3Ll89+55PX281eOM5DOtzepzF1Tej7Ztts9pebKW3Hcby+uQYVBJvSMOUDc+r2mxjJrAAuwmm2NM+lGGnIyTbdMzMT4aZr+s2OCoqnXNLt4XQ7nL773dfmdhxOw3QszrvY7/ebrpuz5cBgFrir+pwLTiNZmE9JrYjAlUjgblaSSUH00DXuljwdBzfKcGcL7ppnnU5ZC0gZM5Ch6icd275lacSJmXeb7Xa3ZWEfHfNITG0IoAD3XBLUXMAUN/1umseUctdvNpuNO5l5jDE2Mo5jykPXBFMIB2GG53nWcZzmnA3adY0EmEGEmQIAIjaHcCylHI8DCNNYSGoJ9uZiS8wIkUvmXNLpmIcRrRaSkR3MnpOmnFO2nK0UkEjKGUwxGnMUEbjMc7m/H4YhwwEFgFMcXr58cTp+IdGPI9xmNX39alcS3Nkdk9o0TUTWdV3ft3CC83CajsN4uM9ZQYQQKYbYtV3TNIfDwBSbphNuzXKQuW+FuWbCqlVmCFmICJGvnl12XZPyNI5HLSWX3HZtE7rb4ZgGtF0DqmHtOeckDeVkvcVt23/04mqaTne318fDfU5T03QmjkA+A8WUjYIRHG3wwlkxjynZCczDPOz2bbsJpmYwVT+dpqvL7ZzGNKsWM9OqjT8MeThqExBPYbO56Lsup9JGa5sW5lrSNEOKXO63pye742E+jYOm3LWtRNaS8zyo6bbpm9hPow7DOI3zeCpdi8120/W9BHZcfvrqW69fvd5utm742Y+/+MmPf/b5Z1/0cUcWX7y4TKmc7iclI2dTXirMksP9xdXHcx5Snuacj/eppPzm+vZ4eHvz7u0Pt3/93/2zf/bNT79x9eT5xeX+L//yR//m//ij7nl0VXOFO6rQpUPfT2GgR3/qQkJLScYVzYIzkZuLSwgho5ScUKM+xVl42+7mMjbShobHYTIzTebm94ejKQJB1aepdC3td+223zZNnA4+TzBH2/bXb97dH45wQwjX9/cEkz5KK80mqlh2nU7j3f39dCrbp2Ky4d4vNk+fbBpN8BLasGkve5GSU5okdZ1b1vt3txfPwBzbthlGv7k+HD4f8kTwtms7ZO/R9A0AACAASURBVC9BLRfNmYHtbjceZziZExsR2IsGgRCDRJ1VzYobg6M4UYhtnuZpnEMnm93m+vrOoVaKSUnZW/hu1yvCKY0mWmBe8OTicvN8O5V5PA6bj3bdpu02jWtOh3x9//ZN+qKMNh1S1VWWIO227bbd5bO9b2mS8TQPaZiGKVmxIMxMXegDx/EwTnPyhDHNCBDhEKIs5SAWeIqIg3Ceszi5uZbCBq0iOBUOoTU90B/CeytUdR4iWAVpfN1tqiMHZugZ3HrMH6oKS3TelZywVDKslzNbZBtWikP9ykRcq3VBVvoS2NyddClyR1RFpauhUS93tnXXpKQ1ivZIDYNWfdJHluT7JHVb6qwtQR9bSi77OfJJcLUayHwcIHV3mJvamUHFK5nqsdVtugJJ65xbflMhoOWNrW71sr9XiXQIka5vBk4MNjaGCFGt6UEB7otG2YparEy3KpHBYOFaXq1aacIEg6rCl9px7q5m7liSo9jXSjK8FvpZEA2ghtvM3ZmchBZSFy0sMWLKpbDzUp8JMLLVtmciKgDMiZ0crihZxYWEiCEu4pLHFGTDkNP9MbTNPE2XV3uOmO7nZM1YpN/2UnqQ/8kff4+GYEfHyRJnwE0UhlI8eMXtmE0sl/Eam5dJTxxjLMCkZShpLo4CzICjpdD3IedSJkNAcTsN4zDN4/F0moY8p5xNRJrOtVguiQzGHCJfdrvpduaOA0SUSNGwGIc55zROXfPR7sl24/1hPrqYCO8vLkx9OI3jaTicTtvtzhtvm3bzpHvyfMdO1/fvwkXoLhov9u7N29PhFJuWFGKx8WAFaVRLyoFh5AooyB5BV1aFwyvOQm5ek7t5KRyIVR33YRyfsZpFenytKMjGaq6oJNzqrHyowl4nwRm6WjyjOo+FCYvm2uq0AvIISls3n3pOd4d6jaIsJ1y15xb/cVFzwQOmVQtyrQ5xndd1jnJN8gAICORzKQ+g18q98ve2xHPnAL5WgljWA3c8rIsrnLeW+KzJww7TpaLW2Q8lohqK/uCBHzruq77/jbQvvY730KvHx3wZZvklN/Mbv8/fVPu7AFi/Og73Sx778Unoa+oS/hJQ8HzyrzzgA5Tn/xHgkN5vv9ULVZDug9Wktl8xBfe3PUBpjbOdv19+suBWZ/FHYuJSymLmVBPJYDDomvFXIXs8rJ7vw8O0rn20VNZYNI0ItfpKXbLrWrZ+sLZ6Xav6VAQWpprphQodrGWEF7Hb2m1uZmq1hmPdUHxV9luslSqqxWAKoa6CtBLq6+WlkqXgMKtMWVpDAuYQr0E6dnMjq/ILy2OSIcaqkblGJ855mpWgTgj1fEJsMAKEKn2EWUAcGZGMfIn9kTs5USBCMa19ZjVfQECy5qovj7Z+Wf8qperUk4jAoeo1hRAPqD9Y2Bap9prb5rULRISDgMmyFS/zPDdds9ls4UjjPM4jSWCSru3G0/Hm9nZXNmp+/fZdKUUMY0Kepz4e267Zby/E5e39dHd3u9t1+8v9bre5vNj+9U9/GiwAHiRAKITWAlnmw80wTDMzml4kEhWYlwKVhppGmGDFL/cX8DhzAGHbX8TQ5GTF3U2Y0XedaRHmpulEApNOU3J3ZiCi72LTdkULkbjjO5988vand3fHA0BZMxQhhCq2Vgcw00ON4CpCQYSFlYezNu1qUq9mMBxrJsAa67ZqQxM7lVwkcBMiiW82mxcfPf8n/+ifKOYQ+XC4Px3T28+u3729mafpcrt78dFVt2l2uw2HUIoOx5OiNJ2EGCO3FEIbutCIapnHScvkjhC4a7soHXnz+S+u72+nYbCn+6fPn79yw/3h5vb+i0ZgjH6zmdLkRrmAxcwtcghRNBVzm1MKHEHkTlld55xSdoACinsgzcUBBTsEFIK7wVAsz4kEZAqCkHEu2WaH2iIM4UBGoZJCJqIQI4OFmAhRaNsHsyyxqTq1BGp6xBhUS845SJQu9N2GKRCEKLgzXNzZHCIyjbnrAnMTg8aQxhHzZKfTbKqhIeoohgCEkjVxSVxK6yUTEC8uLubclGKqGkIMIUgIplpKFur6PoiMTCIUcgIz4DFIcDeCEUrJVdFIqPoBizVHTMKcTcGC2PB2u9/uNkGuSLJpIoYQz6O5MQBVLyWnMhFst9eSIULuAgRyrl6oFag5XEUadzYTcycYosOpabqmgQQm8nlO4ziaZwlIORfNIrUyqaecDTrNQ9OE/cWmaDnq3DRRFRRZs5qWWhmCGMTetvF4dz+loyJB4F7KXIxqKpwqSBPYysg+z5rzzA0cfH8zqJecNxfWxU7aKCCb82RmwtK2gkhmaKOV4rCxzAcmdmNTSymjpEaimalmuKsVCRJjfPr0YkqzXA+mmKe58RAlBKmrwUakm8fheBznKRHTxX775MmT/cUWZt/65He/8Y1vXVxc3ly/+8mPfvyDv/jJOMxBNrfXw+F+tCKuTM7mKi5MYkRO1MQQWjTS55ysQJMDvGk2xKVM6bOf3Mz29snF1SeffvOb3/jWN77xLTP6oz//I2Gep9R1G2Ye0liN+RoXrCvJSi85m+TrJuIP2zMD7JJLtuKuTkBNUgpOrERwCSFDBALzYchU3VJiONquyXPyxa1yB5WsWsr93TAXSAsCpZTnVNAAXSCmMc+z5p6p23c/+7OfN1ch9OLmEjAMGm/H5/1Va717yKfUY99dto4yTndzGqt8eNMCAhhCE5vQz2yl0GmYg+6E20Y6wLwrhRMDKQ1Nae8O9zAGKzIhF9nQkukOAZaqGFC4UBpz6IGCpg39vjUp8ZrF2LKRQTKylUFHRPfelc1bxC02H/VhG4Y8oAMJb/f73aZL42in+2Jko5djwQTPrqwalYRKn6vnX1yz5VQZi7HWSQghhAo9LPKdizpUCBwIbDUqZu5m5AyulozAoaautS78+R1XU+P9geAfenVnpsbZuCIHUVVcxGNfZ7Vl4KsLZ+a8quOu6Uw4O4Y1KrcokvE5kvkeQvRQGPDBB/ZzuIyIHO+Fwx+hWMuBZw6Cmok8KFKtf7CU3/N1Zqx3tjzg2j0PhlUNtGEp97vezrn76OytnCGyBTsjEC/+9cORC9xkIH7wVs6Pv9wBM2BVM59WdJCIADcQKvnPF+vvMZpYdSd4cbSrkUoCUDgjjLUWYf1dKQaQVOSDfWHJr4jgQizxatnqEkamhS/jrlgY+g4ihRNseetU6wAvQIW467lbCa5mBKEgYGezXE7DEUqsMtwd6SLkw9zGiNbmYzr2R9PSXIZoHeeQPgdSiR7JqJNm1slca/8UGJCJQBAofAK55FJ0QhHKDqLYdsQkgSUSz7dT27RN0CyZhdjD8X4ocz6NRybR4jaDoiXLIIezm2kxmJWSUTyd5ukw6+Tuzj33u66ViGaZYkzBJrsb7w6HUyMxUGTDLmy2T/pf/Ozt6f74ZH/5yTc/fvHdTy82ux98/0c//ewnX1ybQpumbbgp5l3bSghQKMwFHLHrdnc3h4VsZSvI7IBTVWonA9VFfQGGl0GAR6l852nmK8BMRA6sOmkEcqq8KTujRFXNjM7w9fnr+s2jk9eMjEXk3clAJkvmKZblqw4yXxcFr0W03JfbWFJi60yt09JWKNgr2FsJV+v/C5DFy/BcnCFfA/20OFZfgd08mnXA2ZFcdeJ9gf0epQ096rfzAkVYf+AuRGYPeJa/n773qMd+8+3xhX7jl/iPEMb6zWhg/R3aAwz728R3zoAO/UZrAfyK1/0toVfnHej8RGfe4PlXv0HpuN9sO3eGrwU+H7ppKaFTD6vb/KMFmt4/A6EWqMGyzy6fWmz1JbrHBgUTHtU7BhYzRU1Zl+oTWLTtCwlo0daEsZk7w9WslKJaXH0pniOgSMyBakAsJWcze1g6varkruuXO1Q1uzH4EYZVI4Tm5r6UnAPWhZkIlSzOxASBo6gtT+ELwQaoBW3EYRBzAys5gc/rN0GCSCA0DAvQKqopTIFZuI/upihmWS07O8WaPkDqWrWyOLCIEzGFahQSAWRc3Ro6hyvqfqPuAHPd7lCl5cEIxE5usPP79crCrVsacS08JyGUUpi5ia2qsmPXb2D+7u3b4TAKPDay3XXqWYhLseE4na4zfKkgk094g7fb7f7Fq27T7zbDNJ6Gd+9usxaJREzFVYuXOU9jRmECkUoe83Ccp8lAmGfvumDQbCqCpqdggRtmkohNLkoWQoxkMp3SOE+1zK5b0zQdETHTdrdjkGtSdSOEIE2Hi8s9gTebnSeY0n/xB//w309/evfFgWuuZ4YVZSLmysd2LIHVhYW1yODSOuXxvrW6dCjByRfLAwDELU8zYCIh1MrnSuwgQBi7Xf/P//n/8L2/+pM//ZM/+6vv/+Dm5v7Nm4IZGPC2v8m5HA6H1y9fPnl66TC30LVdCJI1MW2ArEkCSxNj00oubJSitE3fRW4Jsd91aiRSYiexo6bpmi09fbllJgn06tXrcR5EyG9GIghLG6JDqmbs558dNz0JB3djtgCW2Gz2oWk1ShelrQXbM83Jp3meU8pkICPLRRXuaEIvEhSsaao6IY5FqkUnPfpg5k3TVESaCSHwbrdNadxsGjczz0T28sUzMz8ejqfj+NGLFyFI1220qBu00DTOU0juKtSoUkpJuO/70HW7lPx4PObZ55ynLnc9wSITmkjjWEqeg+/mBuPR5gnkPRmVOU3z7I4QNFR8LYTNdiNbnqap5CyBTIvmIlxzmkXYKQSFMXEIoYlNCJHI1Ikit5u2QNOQTZGLDePhhz++++TV8+NxziU1LYvQ8TATGkBzTuM0nE5zUWy3w9VV3u56ZlINQTabTZQpDUPyDGcmDVQCFT6ejiWfgjRE7E4hoG2a7bYvnbgOXUTXd210sxLYocU1R6YmdgQ0bWibGAJLRL/p3ViLqZaUCgAYcsoiHYkeTjdpHmJHT9CXrPkAESMRb9qubQt8HMs4zOaG4rxldxsnK16G8QQ8e/nxsybQMBzTlO7IiCDCQSJDiImYRCQEJjA5M3NdtVPWNJdSrFhmIpFw9dHz7b57RVdO8/XN3RfvPm8kEIsWi03HTmlMd9d3N1/cqJUYm8vLpy9fvn7y5JLBvW//4t/9+D/8yX/44Z9c4wR8hKsnmyaWac7TlOFavVmJgQrgzMwioevafis///nPIYWIBOLqwzAxykxeZmz2+ON/9+f/5l/9X//oH/5X//if/OP/9p/+11dPn/+rf/mv//Df/ftpSuKBhdYsp19m8zgBxAZeXNbKnCCCoahRMSOriocCoQIrSoVhoI7KpBhgLWBELG27bUJ3urkNZF2gTbtpOc5TdmjT49NPL3bbp33ct7t3PJ48skdXypbn69vP6cin4Xj1zafjME63c5Tw4unVJ5980vXhMNydPh8Ph/s8+Xa7C0+apm1Iss5HshRis9lLbGB57ON2Gy9mScg3aTIvOXAHJmli7NoQJLCH0LVdexpnogAEJ9e2AGUVh3FicN3ynWEOzSUqIsJWmn3MHLqnYTjNSgBR3DbcyKw5tEIMY3zzu68/+dYnQ5p+9ovP7se7/dWuqE3DNN0fp8PxcD3hBGSwCmcWimZmc5ltvjUz8qjBtpanRMYxihbNk5oX0USpTKeEvJAFmhAChUBiRlqyZqtVlfksLuCLUA4eIzKLU1V33ccm8fv+53ummjMTQAJyCgrl9w+sntvCDH5w5Ji90voqEWOBQKqltvjIxIbK7OCzA7x43e4wXp+kYonVTqoMIK620bIXnlke1a9dTGJnrtf+imFPWBTc4dCFDgUQuFbKI18y8ddMgfe0qha77cMe+wAge+iO1TRd/lqd6Nrr/ogSQ+tHvMrxVAToHPs1YgIzma/d6KRm9mX/InIF2xx+Zt45EcOYOYQAr/gCEVhLqf2oULhzVzEnX2GwM/bpRA4jCMHN9BFWV6PMNfAAnMNoxAQDL0XbXB8Z4KjsskpJE3d2N0JBGmaAPQHJMGOWiXeMQuPtbGNptQ0S4xwwgzMEC60LTmBbM+ioEAJInNUI4m2zm3wYTzkLKWAukZsmRDaCuSCyNUFkuxURKakcD6fD3REKikZGSK7JNdUMgEUDSgecdG4lWLG2bXaXNh6m+9M9BWwu+s1mM8zj7V/fSBunMR1uRhQgAYLdpt91OwnxxYuPhmG8P939hz+7A+Hv/97vBuaXH7+8ubsZx7HfbTny8XAaTwnjPB1njKgisN47g2BOSmRLHh0W7lF91+wgY0ANVf9qmX7gR2jsB23FhYEPtgyiM5gdY3Szs7zUaosuo3z1eUEruQ8gZpg5sbpXzHnxi9d16UxKXCAmUyI+T81lXscmrmavVUkqLNoz1WPCMjrVmLBK7tHyOPTwIOfHoi8lM5PXMpuLub3gBnWSr2wmLPOQF27WUtjxUYeuCZuVxPDl7v3Knv9P7ddpf2sA6zHb5dfBg85n+Ep48jfVzuf3tf3GL/Hl9uUu+vXH7vnOv4yInTEsel9ZzN3/Y4OxPuiG5Y24r7mDUOh7T3cGSB6Cho/QdOLzwec+N9N18VuNFwKkIifv4d+qrsgiTFTLwBcRJiawm8EWTQLNjpKt1Koc9HAnVdqqnm2t3XN+0UuRQKz36V58DWaQUlUrqHG5Gk4A3KrELsHVBRBmJ6/poXAiN3E2rystCEugy3PlTD1ENVio+mI1E9xhzsIVBONljXVyZwtRVFFyybXkMoMjQdgdMHIjZnBgicJMDifmBR9Zd6APWzWcKhBZgyiom8hCQ1sqSK4vf3l3TERUixi6OYfQNDGX5GrC7IY0zWXObRMC0ZTG/eVu2+/TON3fHGFgiE1KARLIZxrKMHTD0+dPrp48z2VutzGGQKQS2K0OKLFcxuOYM8QImd287yIRzzmd5kyCEAWO6ahlnrq+3W4392/vcypFS9sFVi9lHOZhf7kNLZdiw2mSgL7fMFHOKeUpNKFpOmFsu2PONti0iSEN07u3t9/65O//afgBCowX1LLK4a/DeNG1WMucPA4off1SuQJej0RpybIZIziRM7R6OGpQLdMwDN95+rGV8u7t9edvrk/3CMb9PuZo5oVpc397CHQ3nAoRJNKz51dscT6NWVPxeW6l24SmixJi0yEVL+bzPCcqnv3p1eXFBd3fDXfXp5//4qf73UVoQ9Nx13dg3N5fF8vq2nc7hwYOBCFwFAgH1WOazTRp0RBy123IeczZ1IrPWVXVmLndhOCcyJnRdNK2Xd92b96+i2ib0AaOJjSzsTqZq9WRyWaK5CXkMhUr5qU4ETNE4jiPcCVAAqKH7X5bks5TKqaA55yHYSSiWn9rHCd3C1GEqWRzcM7WNBQkdO2mbcaxqM+YHIA3UYMweailC7XjebbjfXr75lawJWmLmivP8zzYxIE2bR/3rSncNE32f7f3JUuSJEd2T1XNzMMjIjNr60YDHGIRjGAucyGHwwOv/HVeuYzMhZwdQC/o7sqqzIzF3RZV5cHcI6OqGxxSgAEhFPqhlohMc3dbVZ8+fWpqhKDaRSjcHbbgmlTNiJ0ErRmLmdWuKB8HuZHRNpt5KqdDrtky4e7VrSRvehw3cRjGr7+YhN1day3TVKYZnWu/3dZh2ADWtMCR4uguOZuZCyfmSBy329t58rme5rm4wRwhoOrEbCFwSpIGjomIk5lIQCm51gLQMCTU5k61ldP5PGfc7h1k5o3IWcDMIKuGEGKM8Xw+5pKHsI8bMSsUEWNgDiJhM2xyKzVntyZEKs5GzSFCbpwnnadmjTVgmsrhcK6ViBFCSHEIHM3QqremMQ5w5LmZeUqBlyg2mXvJtbVKgV9/+tphIdFuP0w5nk71WFUcm5HHtCXzPOenx8P51NKA13cvX718/eLu5X63Ew9//Z/+9v390/svCwBsMTTKj5rjPIzjdkxNGzNvhg0ZrHgtkJBiGEBeWyFybaoLIViGmCKPVrXhFGg8P7TDt/jP+leA/5t/9xd/+rOfnY6np6fDl7/5Qnw4nc7k/MFGsdKG1zj2ehRi5cnAAVJQkkhdudIcDFm5DVq1WQvR1bWlZqQgBBEicfNSKnsKCObGRCKRKNR6qlrUbL9/+eLVy2++eTqVyQyIjlCRwiib7X5bSkH1d1+/j1FebF8MYcMz/+qvv4A7BT8ejsfzzAH+AlJId5EjXty8jDvd3HIcEROdskbaDnGbehJ9g1lrVKkSmrc6B6KUIshzm+cpQ+oCkQSKG1nKbpm6kpN0yWlEIbgTwGhepnYsMt98ekPH8+kwa/XqBZNjRIPCgR22n46bN8P8OFfJReuf/PBPyqynp9PD23s/AUegEhuLBjJEjmragNaqVUdxb27amQhoqlYcCleoGlWPLmCCo1WVRMGZjUzNS7NqAJPB1JgIqkTceXAfuazL3rFQgwDvMNEHaMzFM+MlS6yHCsmJdDFX+pwx6sQ1W1II3eHUZRu6+sBlBtKiskVOSzCG1jBXR7Y+nJPPUActhqyRmZqrO5x9FenCxaqnRff5wmP29YG+x065NE+0FrbxZ5XJXlymG2t01YDjw6qJ/txvKxtjffSL1fqdnvfnJ1hf9RrB6mc4Q5sRyJYOZTKDGVgAImJy6x1ttoimgxkLr91FxHtZ66UHVrAMQM++XEzAq+ewxfO+fLLiEh+Ejy/mNguwJIktEVUCiK+6p88bXqpmPwfd/GLSwJqSwIjM7CbGOcUQI4k0LuyiTS1j2MZxMCvV1Ku0MjTxiIgkIdaQpzrPcxhFe7QW1BXgFmvIycXHtDP2uXqrRV2gXsWJFc1qnt/cvmpVq1YEUJJWoNnI2M1RurnMAkkhKloupdvtXW5pjON23O5ut2Vs7799//j20KqBOGxkns/fPjzc3d1IEBiQgRNgKId8DK5UP/2zz4rmqIFA1ioHpBhLrXEYkqo7yHmTNt7QqiKiJ3GQU0rDfM5knX5Fi+3vdKV7vi6NZRwvbMbnopofXRd60fOf3RK9Pj68S5gxVvu9ewF2lTp3mcVYUSqHE2FBKIlW+Omq1fUW3ivSG/p7rkiuAy4kIO+V5x0rV2uZ0ot336sTq3UMjLCmPOMSMV9ZLLTgrN/phPWxL2QtNfdLaYl14i89+7zgP3D1Lz/bF8Zvo1/9cV7fC1P8kT/2/wGA9RFY8Dte1wumgy+/e5v/7L3+wINxvTh/Lw0uRKUrhbZL+xeo7tKTf/j3/eevK8YO0I0nA+DUSz0sm8flEH0mYV01sKJXHxcHwIrZdSr0Zf8lIg7StTr1mSff44Hu7CLiBFVNKaITWWBu6u5q6mrWzN059MqDtsTC0KMPy5jk2kSk24buTm5mzj2CxmQd5Fq4VuwrkxVwENQMZN4reiyCurzksoO55wgYWbOl9LV1k4EBd+k5e2AADRDrIXTrBV56BKHHJghLkhkxw9kpSlBrxgpeUgOop/Q5wSlo1+diCdI792KqOHXD7/uu1V7qlvFyWFyCsLbU13N/bsABN2hzqs2gRFRzba1qqUQkzFYbGhTaqLyzdz/84Q/H7dByrXNDg8TgpmRECp3cGKJhOpTcsqJOU4YgjbTbD+fjHEMkj4wEVzGwUa3FHYEFLl4qmvMmcozsXuapHuFNx0jvv32wZgDaGLS22uap2ph0GJI2HA6HYZO2u/08T8fj0zy3m/2LYTO463Yc3t0/pLA5S85HPzzoz3/856UUXKLWAtcl3aDHr54jt0Smzisf369MjY/W1cWIWM70zue3ngFEaGYwYtJaNcy5zm/ffvPVb8YvPv/y7f29tTW7yCORMsQ03mxGnXF/OJRaOaFV3t+NTmIqDm6OymCiVvVUymkqBAxJgwR3VCtNkes0lVMpXnSOMd3d3bKwtnp4OIfEZq1PUFPPU9OmZi1EpDgAnEueJwO3XYVwAMEDGdnUptpaDGJZzGorsxtchEFCHEkYDAWcBXGQAa5WKtTZhYW7r96Ktdq0VmuRpLPYVQLVlpl5HIcQ1E3Nm0RC4+PxKc/VncbtOG62w7AFTtNZgzQO0IbtXnIuQeo4xmHYjmNu7VSLmnprKNmEVUgIosqtIIudD/XxLeCnYVNDiiwcWFw9IDC45lpzbbXkXAEbhgh21Vqrmbp3WqVIqZUYtTXTmouoVjePKYqE3X4zpLHk+jQ8ufsn282bN29ubre5nFL0zWb7+S//1ohUW2vFzGNAFIwbHlISkZzzNM0iwsK19EKXQSQRBWs0DJvttrh7zmWemxvUUBtyOZiLkzqVUlspjUDuClitdZonAJYtpQ2gIhDGNJ/LpGpqbkTEAgjGgXe73e3NLXOoNYu6kc3nnIZARJ256eallDYXdlB6jncGCTBqpudTOR6m0aM21sbanIWM2EWIYwgcmFIYYV5yzfPDChQRQBISB8q1aMuBKCSa5uLQ7X77mq20t80xEO3H7XbYwqC5WtVhwMuXb/7057+4vbtLKRyfTvnY/tt//Zt29JxPYUghBS+Yphq2HgMMWkqJm7jf7VwtIxMQkwwp1FqOp7MEdiVychYiFg7CCVWpzIeHOSSRPc85/+Pff54n/ff/4d9++unrv/zLv/ir/5J+/csv1PRiJXx0AgOrx+lwegawfGHPEBETS+8JIjgpOayZqWs1t6rwNleP3juciOrc3h/KSN4yuXojlHPLqTZr1TVEHvfb21e3X35zv3+539zeNGmHcry93Q6b4eb29nw415Z/8vqnTw+H8+M0neZynM/HCSoQ7dXifUCu08PUxrt4+2b85AcvaafZj6fzJIVspjaQCcGEScBgIrBpy622WnMKEkFDYCeErQxp27LlWtKYDHWJ7i9utgMCIkJzOAeYYGpn1Bq38ac/+dfneX57//DNN9+Wg968ujE39ba/3X724zeb/fD1w2/mPL94s09DTEOwBqhRgzgagYmCCWZqszYrJO7iiIREMIaSqweKTsjljAIAY9oMnIIEZ3Bjr57noq2A4W5aWyvqRsJY6hLKJbWtH8fPU4BW7lNn9/iqR7DYXBcgpeM4C49mKVS3CSId6AAAENlJREFUoJ+d5bA0yUREtib7dG91xaNW++NCZiLv66s30wVkvOf89JjNBZRawjgALoWi3d1WdlUndyxH4co1fz4KseI1/yuXYrEzP+BRdThtPUex1KN+1l39wOLxle/yrD51AbP8g/t86DHRc/7jMt2uRQH6Vwxo0wVpWi1dmPsimc0LkZ9oASVWCY7+GMQXssmK0i1xMu0wExOvCN/zPLngHlfsEV9N9hUaufC7RQhe10JyuIzeqlLWIU/uwTN3WwvBXSKfbuukI0Bg8BAlxNC7SkxUYdWkyZa3cz2ysTQuKBQYDlWj1pxsu0nVG/WojhOc2RjmarWbtUziKlZJew0lpIiUPAawx81+vDvo03w6FbSUtJVWc2VnVXVXkZRSGoa02aW5nPOpQBGHkIbIgbbjaIbj6VzPjYRe/ODOyYebwclzqymlGAadFCdAQY7QRAqTubpO57mh3d3d8Uucn06n4/kxP3F04sDMx8NZiEWEq1gxUgQSF/LmWhSdz2R9rLBAwr50befr90Xdh98vE5ng+lsoWMCy911zPS7z+2o2Xc3jznNi0POUWczUJah/5Xcv2YLL5nHtpV5woOUR3K/yatxhZCu85Vh1GtepDXifbHCnJYlyudPlaXnZh7AIxzj0YxN6KSS6BCwWg3tZkpeIMD/fFKtfSuucF1t76NrBvc49/P8MrH+B638XwPouevW7j8dHEMy/0ABfbvEHoyNd1u01/vq7vN13XVZadaMWQccPtoM/3qt3xPPeiDUocNk6r4JRl7TAHhF7bmS9Op3nWc6Tnm0XupBWrmwS6jEhZhEyWNMGQFhiCNaTBtyZaTHgfT3gfQEXRKQbfuZghqlBF/ZQYHZTJ2KRblO4delLZ1Zyhq0gBVai1mqtwd3Nl3dcP+vYGmzpLesgWrElh9GXkwsABgJ3rL9vqgRzbe4AL8oJTu7qaL4W2V2ErUibwhVsCOBupBjMXQgLEACAoabmWFTnsRomHx5nH/V0j5OYOxELA94DrgsX2dSW119gRjcnNAVDYjBr8zSDzA3mT8MQyRVAK+5cZQjnPD2dDlOe1RQNyiCKXrU1AyMwSKVNes7TqRzOuSpjt8fN7XB/n4dYB0lWUSZj4ygB7NNcszXArBg4sEdvZArXAG/eOJ+blUWFzauVc65uMLiScCRw08ZNp3kuaKfzURvVWkrOqjpshvu3T5rOp2mej3pq9//RnIjClvTkbisxgp4ndg9KEwHE7uq4SHi4f29IuUdLmdZ4+xodclAX7VUzUwnsxUGY8vHd+7d/9zf5159//vD0mGK0AaejHU/FFVHC+VRb5lbLnCsUGHD/7dM05d3NZrvfbuK2tINXkjGe5+l4mubSgpDEIEwscpqP3rzqDPEQYShTLZKp0Zxz/ubr0/4GpthuUkopDgmOaZ5rzhKMEYk4RRaYA7lWq1k8yMibccO9JHggsCWRGLYll3lqj+fjETkEqrVapsqu1aBgsHc5mxVs7hHgVlvNTZtSYPXapnr3Ysxl2mw2m3FMgx0Px55paGKPD4faap5we6PDD8YQklBELeoAQxXzpK0U4bIZdjGkIQ1TbLUWaLPmtXgQbdGCcFU/nypDy2zIACM/lZJqGCILD8MgzGZ+Pp7VrLbaA5a1NhZy96aLp9FUmXtIEurNvUmj1twdycpuHFVZLcTENy9GkP/oR5+N281mG86TweuQ0n63bQ06G2BpoF2MIYRxHG7vblIK8zzlPIcwSKBaO3of4FLmVmtWNTPt9SsA1NZiwm6PNIiZ1opaswi3VkR6xU3X5jnPzFzP8+0dS8B+v2FSU51zWWqbglSVCOM43tzcvHnz6e3Ny/xkaF39WQBqzU1bDORDd5tgq/TbMAwJLoHNmhrOp3z/9v0L3YNBFDabZK5MDCMzYhCzBCKt2tNh3G2es2lum7C70TENHIQahxTApK4Q2g7jsA3H81FjST7sx62wlJxhvhu3r15+8ukPPvvxj38yTdO7+/svvvri8HY+vy04OyhI2JKIIYNIjeYp55bdmlJNg2hrU5thggq1VkvJZbKsccS4CcKxZj8eTqEVQnCPbICqCE+H9sv667//p1+rlF/84s8++fT1v/rJDw/z4envjotodnfEl0K9tJ7Cl/N4cXz6tw7Aybr24tq9toqpWHPXJRdIq3W/aNiMKW10Ns04ecVEULh5SBOCSmoQmHs1rVbeHx94GG7GnbLapNubUUSInQO/uHv5+rPX02E+vn2b381QsAV2ZgrEDFKdy7nOp8e5Fd7fxU0cpnq6f3yacbq72fmpnSgHyzU3BiOA1Zl62pUZalPLjQwUYtjcDPv9zXTI+SkjEPe653pxi4yWw14dHiN8g0a1WAuBbj7dhRJ14zqqZkflPGdh7D/Zbl6nw+np3dPbIY7bcftmtz+8Oz/ePx3vz3aEz0AGFK6ECmpkzSkuqfcN9ZhOKQZObGTktJFBpWnVQEFI4CygyNHEGmvLasROaKVZ0RCCELs3JmIHLy4ZXV5pOSiWsEjXJeA1cvydnPSrMOHFSFnSk4jhbLZk3LAwHGRG1l1I9MnSWRyL3+iEzty2NfrV83S6h0qrOo9fycYQAWG95wWHfT77Ls9GnRDT36qbE1d23+pifvfExMqQwPe8fm9gxXQunvDlH+4fxVWfO/nKo7mgV1cPfIlCdfCt+7ur3BDW8FX3spl69UBmcW1w2JVxfGlr+R8LrzTKJXV4AYcYi44ruTVT1258fkAlew6YrcjnVQbUAkouHUsduSDhPtJAly5Y384XoU6DCxM5sZF/UDpgBQIdnUC0/AmkNMQQjVwk7Mf9xCJMogHuem4SNzxKQaFACKjVVAsTxnFXj0/SO8OZXKSJsVpwZlFSV1h1K44GBIlhwxbYJXKMcayltqa1VTOYueZWS2MSEOAmnIZhu9kMSah5gYKdIsfEA9wJknN++OaxPrW0ldsXdyRopGWe1XW73YqEeqo4AASu4hlenBwpxXdfP+x+tH35+mUt5f43D0/n38DwYj/udnsimvLU69IGDXpuXhAlsrFmzXWKkpb6CH1i9dVDBOLFk1qhQVrArDUbzz7AqS/Dv2CkKy79IYC1/gQvQfE1f7bfuufOPLd4LddzDYWt3s3yi1fg6RVlEgQsciprQW0CuGm9wMPuXabeaa3csC50ohX5xpIOf8FK15PuijTz8dW7rSPszHg+LsmxCtgTCJC+YTGWUo1AV4q0C7bFIEBXj/Xinv/LQRy/r+u7j/dHjifgd6xC+Ltc111z+felBu3v/fq/MhLXC+b3MncvLu5HpRX7Vx2huxztfcFcJxX+MV4f9cpls5P1OF+skI/99n7Gu0O1v/XSw8yCbmYR1pCUmxphkS4PIcQUVKuTKTzEEGI0ty50JRDw0nVERM7EZD1IyHTJz+4BQRhcYH0gzH0Rh1jrsixC5bYAD7rkRl9e6DngeWXuLFEqs2agJS3dTc0L0AwG2MUqdcDJwoJb9U/MO9bEAiIEXup5qD9bae7mRE7c8sS9Doz0g869ORnAkDW/nghdZJp6QIVYyDu17KORE2IJ0sOYImxEDmcmZuppmUywPjlttaMJHTlzN6ir0rAdADbVYYgdktvEyGmTw2xa02ZMb+6mXN4/vEfjMKQm1Zv2PLDAom511sPT2dgO+VC0KiGNYHDJjQBVK1rK5OXo5Bq2IhTIKjG62cUsbqSzOnmIIWySCJW5BArG2ksRazMHwOhoKAsLR2aep4mp9QVXSrbjI4FjjCEghvA0lznDzxCJ2+14e3P3ND+0dumMZ29hUd/HYtmbOzH4OYf/O1vZ6iR89BUv+RFAW2omkft2iMKA6/uHhzznIJFCNGNvVDOYSERas1rclYUDBQLb8XE+PMz7/emzn36yDel0nM2bg3ygECLXuoyim5mmNN68ur25qV9+/vbdu3kTZByH7W4kBmvjgDQM+ZzdKcV0e3Pr7i1bnaspSmmbzfbmZhdCBPDw+Hh4PFSvKe3jZshlqrnMk++CpO1mu921TWU/Hg91KnUE5hlojVDhIE9JWMDNYOheIUDODjdrDWYGp1brYdLXn4Tz+bjd7IdNMrWvvvpaJL7Z3ZjZN/lRAqG5ZptzFo59EALTsIk22Pmh1ajDUN0hIsSxJ0W6o2d+tAYzMqJa6qnNUaqZIyCmTS2zV69etvvdZtiYt5JLKRmgKCEkVrNaWi1dvQzcy9g7rHkcRU3lagvtZq2aHp6e7sthSDKkuNkML+5uT6dTjFRyNZ3I6dWrV9M0EzSzxRh3u+0wpJjibjd2gq8ZzHUIO+oOL4mpT9N0Ok9Pj3Z7I7d3u3EcRcRMh9HGvYdA01SqqhmGgcfxRS+PqzoZbEjj3d3duzz1Mu0SZNwKWSqlCSciKjWX7FAQ0TCMd3cvXrx4fX7MmilJDDzcf/OeAXWMIe52+7TdCGE6HYiYmG9vb0Ew6DRNCa0WfXh3EKFxP2jzlDalzLW2MvcCVDD1MmmerBRzU9u7KXJu4w43tzchiS6MDyutmVuKMSQJ4GETiULSNKTBnarbZhw/+8HNm09+8PLl6+12+8UXX/zD3//yV1/+4/yI3eZ1Lla91tmQmwUfxnGzjRwpeXJpIZJ6M5RhYI+xlZbnYk1ZMN5F1TpP6mpwH0KUsNHCMUZmz/UQmYYxaG044uuvfyMUfvrzn+33u5///Oe/+u9feg9K/HYiygXc6AbE4voTt64H7mw9UakBRCTPmw0cpu7iSBjHcbfbezVEBEVtgHmryHNNGbsUJDLYS5kfTk9ffXUY9+cXxIjerDq7Qs1sv9998ic/+/XffP72q/v8fkaTMW7bZPWchSADcxBy7rydls2rmtpxPt/fH7DBm1fp8Xg4+SSYaobDB+nHZo0cOYAITXWa55l9tx22u9u7Fy9cD4+HRzWNkdDI2fuuTqDADGP1BoMEotE5kkGP8/H90/1xzkX1xScvX754+U//4wuP4DDMlv/h839i8c1uqHP+9t3ppz/62bgd5zQ/+gG8ntgKNCIlGAQcJSJRk4rBt8NIgjxn5SYStpuxUs21zPNctdrZURApsnKeZxYyNQO0KhQI4K7AvAI5tPz9fCRQrwayWBzLJ5eo37V9SuuR9DxVVvkZYVl9Tlqx0U5VWhnxHTozX7W8r82axdP0K6JxN5Gv77U0yGzdylqIHh/4yau9R3QNezGb+gWrvaBT3z/3u897He/5voVyqXzA32lmjW/iu77Fh5982C59fExfndvUBaOWwn3MzKDgBHchI8Va9mf5YV8BSSJmXpLF3NXqM9LX6zsxuSu6nUXaDa8PdgbuCNQq99VfjT58NLr0El1GXu2KsdUfrm8kTBerZkELfelPWormLbhm78RhGBJ7iLGZqvvrV6+aqqm6ap7n+exxcK/eqA1xoFukKGaqZ2hb6FcOYWM2YRNiIEZOQWOGyzJ3neDijUqpNc+FZLORk5/Naq01cATg7gEShoQGVQ0hdCjbmnlVOIJIlMCg0mqMMYSQt6WeDkb2dDi0SXmHuA3b3Y49MDjuBtmm2AQNmrOelTimIc50PB5OT+lJApMQKnDCoU0Axxhf7G9LKmVuODmUoN4pbUwOCs+Svt1zuA72r0N0KVN1mdsd+fkty+F5/Naw/fOPdfSKibUpLfjM85dM/AHytf7uM3rlK7TzW5bYB9fyq9Sz1/tbtdZTFfz6dWiBUp+nK61z84PV5+ubXd39e9CA/oF5n7f9DZh7fZPr8olEy0pYCqEuKs2L8MD6GH/UONX/U9f/BAjfrssZc7+cAAAAAElFTkSuQmCC
See [[Group theory]] for the mathematical study of groups.
book: [[Group Theory: Birdtracks, Lie's, and Exceptional Groups|https://books.google.co.uk/books/about/Group_Theory.html?id=xmQGV0bi-S0C&source=kp_cover&redir_esc=y]]
[[Semigroup]] -> [[Monoid]] -> [[Group (algebraic structure)]]
See [[Measures and metrics for networks]]
Many networks naturally divide into groups. These are substructures that are prominent for some reason. Simple examples are:
*''clique'': a maximal subset of the vertices in an undirected network such that every member of the set is connected by an edge to every other.
*Generalizing the above, a ''k-plex'' of size $$n$$ is a maximal subset of $$n$$ vertices within a network such that each vertex is connected to at least $$n-k$$ of the others. We could define this using //fractions// of others as well.
*A ''k-core'' is a maximal <small>(i.e. it is not a subset of a k-core)</small> subset of vertices such that each is connected to at least $$k$$ others in the subset. A way to find them is to successively remove vertices with degree less than $$k$$.
*''k-clique'': a maximal subset of vertices such that each is no more than a distance $$k$$ away from any of the others via the edges of the network. See also //k-club// and //k-clan//l
Many other definitions related to the idea of "groups"
Generalization of components: ''k-component'' is a maximal subset of nodes such that each is reachable from each of the other by at least $$k$$ vertex-independent paths. Equivalently no vertices in this set can be disconnected by removing less than $$k$$ vertices see [[cut sets|Independent paths, connectivity, and cut sets (Graph theory)]]. A variant can be defined using edge-independent paths.
-------------
//Curiosities//
[[Ken Thompson Hack|http://programmers.stackexchange.com/questions/184874/is-ken-thompsons-compiler-hack-still-a-threat]]
A half-space refers to a region of $$R^n$$ on one side of a [[Hyperplane]]. It can be defined by a linear inequality:
$$a^T x \leq b$$
Refers to a compound that contains a [[Halogen]] bound to some other [[Functional group]].
It can also refer to the ion of a [[Halogen]]
[[What hallucination reveals about our minds - Oliver Sacks|https://www.youtube.com/watch?v=SgOTaXhbqPQ]]
The Group 7 elements are known as the halogens. They are reactive non-metals and are always found in compounds with other elements. Chlorine, bromine and iodine are all halogens.
Group 7 elements form salts when they react with metals. The term ‘halogen’ means 'salt former'.
!!__Physical properties__
!!!__Melting and boiling points__
Halogen molecules (which are diatomic), are attracted by [[Van der Waals force]]s, which are rather weak. As we move down the group, however, the molecules become heavier, and the vdW force becomes stronger, and so the melting and boiling points increase.
[img[http://image.slidesharecdn.com/chemmattersch7covalentbonding-120712101450-phpapp01/95/chem-matters-ch7covalentbonding-28-728.jpg?cb=1342088275]]
[img[http://a.files.bbci.co.uk/bam/live/content/zvktvcw/large]]
!!!__Color__
The halogens become darker as you go down the group. Fluorine is very pale yellow, chlorine is yellow-green, and bromine is red-brown. Iodine crystals are shiny purple - but easily turn into a dark purple vapour when they are warmed up.
http://www.bbc.co.uk/education/guides/z3vwxnb/revision/2
!!__Reactivity of halogens__
The non-metal elements in Group 7 - known as the halogens - get less reactive as you go down the group, as the atoms attract less strongly (and their reactions depend on them gaining an electron, unlike typical reactions with [[Alkali metal]]s)
!!__Halogen [[displacement reactions|Single replacement reaction]]__
This type of reaction happens with all the halogens. A more reactive halogen displaces a less reactive halogen from a solution of one of its salts.
Halogen displacement reactions are [[Redox reaction]]s because the halogens gain electrons and the halide ions lose electrons.
When we consider one of the displacement reactions, we can see which element is being oxidised and which is being reduced.
bromine + potassium iodide → iodine + potassium bromide
Br,,2,, + 2KI → I,,2,, + 2KBr
As an ionic equation (ignoring the ‘spectator’ potassium ions):
Br,,2,, + 2I- → I,,2,, + 2Br-
We can see that the bromine has gained electrons, so it has been reduced. The iodide ions have lost electrons, so they have been oxidised.
A quantity that is conserved due to the [[Time invariance]] of a physical system described with a [[Lagrangian]]. It is most often equal to the total [[Energy]] of the system. It also gives rise to a formulation of [[Classical mechanics]], and a natural way of doing [[Quantization]].
A [[Protein crystallization]] method.
See [[this video|https://www.youtube.com/watch?v=BXBTP36G0lk#t=3m24s]] for a description
A cell that contains a single copy of each [[Chromosome]], so that its [[Genotype]] has a single [[Allele]]
[img[http://www.geoffwilkins.net/images/feynman/feynman2.jpg]]
[img[https://webtoolfeed.files.wordpress.com/2012/08/ifa2103_moontag_na_b1.jpg]]
//GPU computing//
CUDA optimization: https://github.com/akrizhevsky/cuda-convnet2
Nice Nvidia hardware for deep learning: https://developer.nvidia.com/devbox
[[NVIDIA GPUs - The Engine of Deep Learning|https://developer.nvidia.com/deep-learning]]
[[Deep learning hardware guide|http://timdettmers.com/2015/03/09/deep-learning-hardware-guide/]]
[[https://www.reddit.com/r/buildapcforme/comments/3vrokm/high_end_pc_for_deep_learning_up_to_3500/|https://www.reddit.com/r/buildapcforme/comments/3vrokm/high_end_pc_for_deep_learning_up_to_3500/]]
A [[Topological space]] is //Hausdorff//, if for any pair of points $$x, y \in X$$ there exists open sets $$O_1$$ and $$O_2$$ such that $$x \in O_1$$, $$y \in O_2$$ and $$O_1 \cap O_2 = \emptyset$$.
https://www.wikiwand.com/en/Headgear
[[Portal:Contents/Health and fitness|https://en.wikipedia.org/wiki/Portal:Contents/Health_and_fitness]]
[ext[https://en.wikipedia.org/wiki/Heap_(data_structure)]]
a specialized tree-based data structure that satisfies the heap property: If A is a parent node of B then the key (the value) of node A is ordered with respect to the key of node B with the same ordering applying across the heap. A heap can be classified further as either a "max heap" or a "min heap".
!!__[[Anatomy]] of the heart__
[img[https://s-media-cache-ak0.pinimg.com/originals/c8/ba/87/c8ba87fa58f0f857869f0abcadd701e0.jpg]]
!!__Tissue layers__
* [[Endocardium]]
* [[Myocardium]]
* [[Epicardium]]
!!__Functioning__
Heart beat
* [[Ion]] movement is vital
* [[Action potential]] -- initiated in [[Pacemarker cell]]s
!!!__[[Cardiac cycle]]__
* [[Electricity]] ([[Cardiac electrophysiology]])
* [[Pressure]] -- [[Volume]] relations.
** [[Frank-Starling mechanism]].
** Law of Laplace. Wall stress =
!!!__Coronary blood supply__
LCA
RCA
!!!__Sympathetic and parasympathetic nervous system regulation of the heart__
!!__Measurements__
* [[Electrochardiogram]]
!!!__Heart imaging__
* [[Echocardiography]] ([[Ultrasound imaging]])
* [[Computer tomography]].
** [[CT angiography]]
* [[Magnetic resonance imaging]]
* [[Positron emission tomography]]
!!__[[Disease|Cardiovascular disease]] and medicine__
* [[Myocardial infarction|Heart attack]]
__Increasing cardiac output__
//Myocardial infarction//
Cell death of part of the tissue
Leaves [[Colagen]] scar.
Heart failure
//"Cells that fire together, wire together."// ,,However, this summary should not be taken literally. Hebb emphasized that cell A needs to "take part in firing" cell B, and such causality can only occur if cell A fires just before, not at the same time as, cell B.,,
https://en.wikipedia.org/wiki/Hebbian_theory in [[Neuroscience]]
Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows:
<<<
Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability.… When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.
<<<
A fires just before, not at the same time as, cell B. This important aspect of causation in Hebb's work foreshadowed what is now known about spike-timing-dependent plasticity, which requires temporal precedence.[3] The theory attempts to explain associative or Hebbian learning, in which simultaneous activation of cells leads to pronounced increases in synaptic strength between those cells, and provides a biological basis for errorless learning methods for education and memory rehabilitation. In the study of neural networks in cognitive function, it is often regarded as the neuronal basis of unsupervised learning.
[[Mu-ming Poo (UC Berkeley, CAS Shanghai) Part 2:Hebb's Postulate Revisited|https://www.youtube.com/watch?v=hLs3m6nIJ1E&index=26&list=PL4C48902B3A4ED0F4]]
[[Cell Assembly Signatures Defined by Short-Term Synaptic Plasticity in Cortical Networks|http://www.worldscientific.com/doi/10.1142/S0129065715500264]]
The cell assembly (CA) hypothesis has been used as a conceptual framework to explain how groups of neurons form memories. CAs are defined as neuronal pools with synchronous, recurrent and sequential activity patterns
!!__Hebb's rule used in [[Associative memory|Content-addressable memory]]__
[img[Hebbs_rule.png]]
!!__[[Spike-timing-dependent plasticity]] (STDP)__
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
//Heráldica en Español//
https://www.wikiwand.com/en/Heraldry
https://www.wikiwand.com/en/Heraldry o ciencia del blasón. Ver en la enciclopedia espasa, y mis notas.
[img[http://escudosyarte.com/modules/wpblog/views/uploads/19-3-13-3-Dise%C3%B1o%20her%C3%A1ldico.jpg]]
[img[http://www.heraldicaargentina.com.ar/1350px-Piezas_honorables_ES_svg.png]]
!!__Timbre__
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/4/40/Heraldic_Crowns_Spanish_Heraldry.PNG/740px-Heraldic_Crowns_Spanish_Heraldry.PNG]]
!!__Apellidos__
[img[https://playhistorymove.files.wordpress.com/2014/09/apellidos2.jpg]]
The ''Hessian'' of a function $$f$$ of multiple variables $$\vec{x}$$ is defined as the matrix of second [[Partial derivative]]s:
$$ H[f](\vec{x}) = \begin{bmatrix}
\frac{\partial^2 f}{\partial x_1 ^2} & \cdots & \frac{\partial^2 f}{\partial x_1 \partial x_n} \\
\frac{\partial^2 f}{\partial x_2 \partial x_1} & \cdots & \frac{\partial^2 f}{\partial x_2 \partial x_n} \\
. & & . \\
. & & . \\
. & & . \\
\frac{\partial^2 f}{\partial x_n \partial x_1} & \cdots &\frac{\partial^2 f}{\partial x_n ^2}
\end{bmatrix}$$
Refers to an organism's [[Genotype]] being diploid and having the two alleles different.
A directed [[Graphical model]]
When modeling some [[Stochastic process]], there are some variables in the graphical model that are a [[Markov process]] that gives the model dynamics.
A Hidden Markov Model (HMM) is a discrete-time finite-state homogenous Markov chain observed through a discrete-time memoryless invariant channel.
This is used, for instance, in [[Machine learning]]
[ext[STATISTICAL ANALYSIS OF HIDDEN MARKOV MODELS|http://math.bme.hu/~molnar/Molnar-Saska_thesis.pdf]]
. Over the past years, we have pursued this perspective in a Bayesian
framework to suggest that the brain employs hierarchical
or empirical Bayes to infer the causes of its sensations
(Friston, 2005). The hierarchical aspect is important
because it allows the brain to learn its own priors and,
implicitly, the intrinsic causal structure generating sensory
data
See [[Hierarchical model]], [[Free energy principle]]
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
See MMathPhys course
[[Extragalactic Relativistic Jets: Cause and Effect|https://www.youtube.com/playlist?list=PL04QVxpjcnjgdvOwLdGAkZHz9wE7dVo-0]]
[[Parallel computing]], [[Distributed computing]], [[GPU computing]], [[Neuromorphic computing]]
!!__High-performance computing with [[Matlab]]__
!!!__Code profiling__
Identify bottlenecks in the code.
``tic``, ``toc``
``profile``
code analyzer
__Vector preallocation__. Arrays which dynamically change size can be slow, because array memory has to be reallocated.
Use backlash, and store sparse matrices in sparse format.
vectorization
!!!__[[Parallel computing]]__
parfor: parallel for loops. [[Variable types in parfors|https://uk.mathworks.com/help/distcomp/classification-of-variables-in-parfor-loops.html]]
Multithreading. Several execution threads, [[Concurrent computing]].
MEX functions
Parallel computing with [[Computer cluster]]s
spmd mode: single program multiple data. [[Concurrent computing]].
https://en.m.wikipedia.org/wiki/Hinge_loss
A [[Loss function]] that appears in [[Max-margin learning]] classifiers, such as soft [[Support vector machine]]s. It has the form:
$$\sum_i \max{\{0,1-y_i \tilde{y}_i\}}$$
Where $$\tilde{y}_i$$ is the "raw" output of the classifier's decision function, not the predicted class label. This often is interpreted as the probability of the class. For [[SVM|Support vector machine]]s, $$\tilde{y}_i = \mathbf{w}^T \mathbf{x}_i$$
This means that getting something correct by a large margin (, is not rewarded much, but getting something wrong by a large margin is penalized a lot.
[img[http://i.stack.imgur.com/4DFDU.png]] Hinge loss and some approximations to it. The hinge loss can also be considered an approximation to the [[0-1 loss]], or classification error. On the other hand, the [[Logistic regression]] loss function can be seen as a smooth version of the Hinge loss.
Histology is the study of the microscopic [[Anatomy]] ([[Microanatomy]]) of [[Cell]]s and tissues of plants and animals.
[[History of film|https://en.wikipedia.org/wiki/History_of_film]]
Le Prince, first
...
Edison, Lumiere
Real film continuity, involving action moving from one sequence into another, is attributed to British film pioneer [[Robert W. Paul|https://en.wikipedia.org/wiki/Robert_W._Paul]]'s Come Along, Do!, made in 1898 and one of the first films to feature more than one shot.
[img width=200 [https://upload.wikimedia.org/wikipedia/commons/0/00/Robert_William_Paul.jpg]]
In 1900, continuity of action across successive shots was definitively established by George Albert Smith and James Williamson, who also worked in Brighton. In that year Smith made As Seen Through a Telescope, in which the main shot shows street scene with a young man tying the shoelace and then caressing the foot of his girlfriend, while an old man observes this through a telescope. There is then a cut to close shot of the hands on the girl's foot shown inside a black circular mask, and then a cut back to the continuation of the original scene. Even more remarkable is James Williamson's Attack on a China Mission Station (1900). The first shot shows Chinese Boxer rebels at the gate; it then cuts to the missionary family in the garden, where a fight ensues. The wife signals to British sailors from the balcony, who come and rescue them. The film also used the first "reverse angle" cut in film history.
[[George Albert Smith (film pioneer)|https://en.wikipedia.org/wiki/George_Albert_Smith_(film_pioneer)]]
[img[https://upload.wikimedia.org/wikipedia/en/1/18/G.A.Smith.jpg]]
''Science fiction and special effects''. [[Georges Méliès]]
[[Sergei Eisenstein|https://en.wikipedia.org/wiki/Sergei_Eisenstein]]
!!__Early application-sepecific computers__
[[video|https://www.youtube.com/watch?v=s1i-dnAH9Y4]]
Differential analyser
!!__Early programmable computers__
ENIAC
Program-controlled computers
!!__Architecture__
Logic gates
von-Neumann architecture (stored program computer)
!!__Harware__
Valves
Transistor
Silicon chip
!!__Memory__
Mercury delay lines
Williams tube --> Selectron tube
Ferrite core memory. First persistent memory.
RAMAC
EPROM
--------------------
!!__Inputs__
Mechanical, electric swtiches
Punchcards
https://en.wikipedia.org/wiki/Neocognitron
LSTM http://www.mitpressjournals.org/doi/abs/10.1162/089976600300015015
https://plus.google.com/100849856540000067209/posts/9BDtGwCDL7D
[[AI and ML Futures 3: The Trojan Wars of Machine Learning|http://inverseprobability.com/2016/01/17/machine-learning-futures-3]]
[[Geologic time scale|https://www.wikiwand.com/en/Geologic_time_scale]]
Divided in [[Geological period]]s
!''Precambrian''
!!__Hadean__
!!__Archean__
!!__Proterozoic__
!''Phanerozoic''
Phaneros -> phenomenon; zoic -> animals. //Animal phenomena//
!!__Paleozoic__
//Old animanls//
!!![[Cambrian]]
!!!Ordovician
!!!Silurian
!!!Devonian
!!!Carboniferous
!!!Permian
!!__Mesozoic__
//Middle animals//
!!!Triassic
!!!Jurassic
!!!Cretaceous
!!__Cenozoic__
keno -> new (from greek). //New animals//
!!!Paleogene
!!!Neogene
!!!Quaternary
-------------
http://www.ucmp.berkeley.edu/help/timeform.php
https://en.wikipedia.org/wiki/History_of_genetics
https://en.wikipedia.org/wiki/Imre_Festetics
https://en.wikipedia.org/wiki/Hugo_de_Vries
https://en.wikipedia.org/wiki/Survival_of_the_fittest
https://en.wikipedia.org/wiki/History_of_evolutionary_thought
---------------
Older ideas influenced by the [[Great chain of being|https://en.wikipedia.org/wiki/Great_chain_of_being]]
[img[https://upload.wikimedia.org/wikipedia/commons/d/de/Tree_of_life_by_Haeckel.jpg]]
[img[https://upload.wikimedia.org/wikipedia/commons/7/71/Human_pidegree.jpg]]
A.k.a. "Universal history".
[[history of Japan|https://www.youtube.com/watch?v=Mh5LY4Mz15o]]
[[History of the World: Every Year|https://www.youtube.com/watch?v=ymI5Uv5cGU4]] --> [[new version|https://www.youtube.com/watch?v=-6Wu0Q7x5D0]!
[[The History of Africa: Every Year|https://www.youtube.com/watch?v=NzKejJIwieE]]
See [[Paleontology]], [[Evolution]]
[img[Selection_636.png]]
[[MathHistory: A course in the History of Mathematics|https://www.youtube.com/playlist?list=PL55C7C83781CF4316]]
See [[Videocamera]], [[History of cinema]]
Muybridge
Le Prince, first
...others
Edison, Lumiere
A __description__ of the ''Cosmos'', from the physical, cosmic, non-anthropocentric, perspective.
Its State, the Information it holds, i.e., what is actually found and observed in it, both in the vastness of space and the immensity of time.
!!__HIV viral kinetics__
Models:
* Target-cell-limited model. Extension: [[paper|http://www.sciencedirect.com/science/article/pii/S0022519309001702]].
Qualitiative behaviour: Viral concentration grows exponentially, reaches a peak, and settles down to a steady state, called viral setpoint.
Extended model: add immune effector cells, that kill infected cells. Assume quasistationarity, because separation of time scales, to derive final model.
Let $$Z_1, Z_2, ..., Z_m$$ be $$m$$ [[i.i.d.]] Bernoulli($$\phi$$) random variables ($$P(Z_i = 1) = \phi)$$.
Let $$\hat{\phi} = \frac{1}{m} \sum_{i=1}^m Z_i$$, and let $$\gamma >0$$ be fixed. Then
$$P(|\phi - \hat{\phi} |> \gamma) \leq 2 \exp{(-2\gamma^2 m)}$$
[[Video|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=22m30s]] -- [[Intuition|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=24m35s]], similar to [[Central limit theorem]], but this isn't an asymptotic result!
https://www.wikiwand.com/en/Hoeffding's_inequality
Homologous recombination is a type of [[Genetic recombination]] in which nucleotide sequences are exchanged between two similar or identical molecules of DNA.
https://www.wikiwand.com/en/Homologous_recombination
It occurs, for instance, by [[Chromosomal crossover]] during [[Meiosis]]
See [[Evolution]]
''Homplasy'' is the appearance of similar traits in organisms when their most common recent ancestor didn't have them.
See //[[Wiki article|https://en.wikipedia.org/wiki/Convergent_evolution]]//
[img[http://rpdp.net/sciencetips_v2/images/L12D3_5.gif]]
The causes of homoplasy
are sometimes elaborated in the context of the difference between:
* ''parallel evolution'', where homoplasy is thought to occur because
two organisms share a common genetic heritage, and
* (proper) ''convergent evolution'', where the same solution is found by different
genetic means, and where the primary causal force is usually
attributed to selection
See [[ Convergence, adaptation, and constraint|http://onlinelibrary.wiley.com/doi/10.1111/j.1558-5646.2011.01289.x/abstract]]. This binary distinction may be too
simplistic (see [36–39] for some recent discussion). For the GP map bias in the [[Arrival of the frequent]], the reason for this repetition is not a contingent
common genetic history, nor the Allmacht (german for //omnipotence//) of selection [[[40]|http://www.worldcat.org/title/all-sufficiency-of-natural-selection-a-reply-to-herbert-spencer/oclc/37315932]], but
rather a different kind of ‘deep structure in biology’ [[[41]|https://www.templetonpress.org/content/deep-structure-biology]].
Refers to an organism's [[Genotype]] being diploid and having the two alleles the same.
A type of [[Artificial neural network]] that has thresholded binary units (activation function is a [[Step function]]). It was a very simplified early model of [[Neural dynamics]]
See [[wiki|https://www.wikiwand.com/en/Hopfield_network]]
[[[11][1]Hopfield Nets (13 min) (Hinton)|https://www.youtube.com/watch?v=k31Ox9hOh7M]]
[[They are related to|https://arxiv.org/abs/1105.2790]] [[Restricted Boltzmann machine]]s
They are sometimes called recurrent cooperative networks, attractor neural networks, associative networks, Little and Hopfield networks, and spin glass networks. The random variant is a type of [[Random Boolean network]].
!!__Hopfield network energy__
If the connections are ''symmetric'', there is a global [[Energy function]] (also called the "discontent" function), which is minimized by the network's dynamics. Often Hopfield network is used to refer explicitly to the network where the connections are symmetric. It is
$$E[\mathbf{S}(t)] = -\frac{1}{2}\sum\limits_{j,i} S_i(t) J_{ij}S_j(t) + \sum\limits_i S_i (t) T_i$$
where $$\mathbf{S}(t)$$ is the vector of neuron states (either +1 or -1), $$J_{ij}$$ are the interaction energies (synaptic strengths), and $$T_i = 2\theta_i - \sum\limits_{i\neq j} J_{ij}$$, where $$\theta_i$$ is a constant. $$T_i$$ is the activation threshold of neuron $$i$$.
The energy function corresponds to the [[Hamiltonian]] of a [[Spin glass]]
!!__Dynamics of Hopfield networks__
The Hopfield network model is defined as a threshold [[Boolean network]]. See [[Dynamics of Boolean networks]].
In the network a neuron fires when its membrane potential is over the threshold. Mathematically, $$\sum\limits_j J_{ij} S_j > T_i$$
__Update rule types__
,,there are four types of modes of updating the net-
work's state: sequential, random, synchronous parallel, and asyn-
chronous parallel. In sequential and random updating, time advances in
1/N of a synaptic delay, and the neurons have immediate effects on each
other. In parallel updating, the effects appear only after a synaptic delay.
In synchronous parallel updating, time advances in one synaptic delay,
whereas in asynchronous parallel updating it advances in a fraction of a
synaptic delay. The latter mode is the most physiological, but the least
frequently used for recurrent networks.,,
When a Hopfield network (with symmetric connections) is updated in parallel, it may contain stable limit cycles. However, when it is updated sequentially, or randomly, it always falls into a single local minimum energy state. These stable states have associated [[Basin of attraction]], which can depend on the update sequence.
!!__Hopfield [[associative memories|Content-addressable memory]]__
Hopfield proposed in 1982 that [[Memory]]es could be energy minima of symmetric Hopfield nets. In terms of dynamics, they are stable firing patterns/constellations.
* The binary threshold decision rule can then be used to "clean up" incomplete or corrupted memories/thoughts (but which still fall in the basin of attraction of the real memory)
* This is a type of [[Content-addressable memory]], i.e. you can access an item just by knowing part of its content
The idea of memories as energy minima was proposed as I. A. RIchards in 1924 in "Principles of Literary Criticism". The idea of memories being distributed over wide neural networks, and not just in individual parts of the brain goes back to experiments by Lashley.
This can also be seen as kind of [[Classification]]
[[Storage rule|https://www.youtube.com/watch?v=k31Ox9hOh7M#t=11m52]]
[ext[Topological characterization of a Spin Glass transition in a Random Boolean Hopfield Network|http://pcteserver.mi.infn.it/~caraccio/Lauree/Papale.pdf]]
[[[11][3]Hopfield nets with hidden units (10 min)|https://www.youtube.com/watch?v=ujLONBqChkA]]
https://www.quora.com/Why-use-reduced-Boltzmann-machines-instead-of-Hopfield-networks-for-deep-belief-networks
[[Multilayer perceptrons, Hopfield’s associative memories, and restricted Boltzmann machines |https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126437/]]
See more at Neural Networks: An Introduction [2 ed.] by Muller et al., chapter 3, and at [[Content-addressable memory]]. Also in Corticonics book, section 5.5.
!!!__Learning by [[Hebb's rule|Hebbian theory]]__
Need to learn weights so that each stored pattern corresponds to a stable configuration of the network and so that small deviations from it will be automatically corrected by the network dynamics.
[img[Hebbs_rule.png]]
The smaller the ratio $$p/N$$, where $$p$$ is the number of patterns, and $$N$$ is the number of neurons, the greater the likelihood that the pattern v is a stable configuration of the network, and that the pattern is recovered by a damaged pattern in a single update step.
If $$p$$ is comparable to $$N$$, the patterns can't be recovered. Using tools from [[Statistical physics]], one can show that there is a phase transition between these two cases at $$p/N \approx 0.14$$.
[img[Hopfield_net_learning.png]]
See [[Statistical mechanics of neural networks]]
!!!-->[[David MacKay lectures|https://www.youtube.com/watch?v=OvMGPHpa_tM]]
We note that Hebb originally spoke of strengthening synapses in which
the presynaptic activity slightly preceded the postsynaptic activity.
Thereby, Hebb's cell assemblies produced a sequence of activities at the
recalled memory, not a group of neurons that coactivated each other in a
stable fashion. For treatment of this more realistic kind of memory/learning, see [[Spike-timing-dependent plasticity]], and "polychrony" in [[Spiking neural network]].
!!!__Spurious minima__
When embedding multiple memories in a network, one faces the prob-
lem that in addition to the main valleys associated with the embedded
memories, one generates multiple shallow valleys in the discontent ter-
rain. It is possible to prevent the network from being trapped in one of
these shallow valleys by making the transition from the firing state to the
nonfiring state gradual, as shown in Figure 5.5.5.
This can be interpreted as adding non-zero [[Temperature]] to the system, which allows the system to escape the shallow local minima. Gradual cooling ([[Simulated annealing]]) can also be used. Periodic changes in background excitation (fluctuations ~ temperature) are
known to occur by way of the diffuse projection systems of the cortex
(Section 1.3.3, of Corticonics book)
Superious minima also occur with linear combinations of the stored memories. The effects of these can be reduced by requiring the memories to be as orthogonal as possible.
!!__Memory capacity of the network__
,,According to Amit et al. [1985b], in a network of N neurons with sym-
metric connectivity and uncorrelated prototypes, __as long as the number
of embedded prototypes (P) is smaller than 0.14N, one obtains recall
with a low probability of errors__. As soon as P exceeds 0.144N, the
probability of error increases very rapidly, and the network becomes
useless [Nadal et al., 1986]. Note that the critical value of 14 percent is
valid for large recurrent networks with uncorrelated prototypes and with
synaptic strengths that are programmed according to Hebb's rule. Pro-
gramming rules that allow for embedding many more stable (but corre-
lated) states have been developed [Kohonen, 1984; Palm, 1986a; Gard-
ner, 1988].,,
See more at Neural Networks: An Introduction [2 ed.] by Muller et al., chapter 3, and at [[Content-addressable memory]]
--------------
//Notes from corticonics book// These are mostly on random Boolean thresholded networks (with connections which need not be symmetric).
!!__Point neuron (threshold model neuron)__
A kind of [[Artificial neuron|https://www.wikiwand.com/en/Artificial_neuron]]
[[Definition of point neuron (following Corticonics book)|https://keep.google.com/media/1eLrelhvCoDFx2hpETk2z8PEqTmqm-s4?accept=image/gif,image/jpeg,image/jpg,image/png,image/webp,audio/aac&sz=w1855-h941]]
https://en.m.wikipedia.org/wiki/Post-tetanic_potentiation
Model described here is a threshold network model. It is also a random network model. Analysis officer stability is also presented, different stable steady states are found depending on the threshold.
Netlets. A small random networks with sparse connections.
Dynamical system analysis is performed, including web diagrams, and bifurcation diagrams, when an external fixed activation is varied. This shows a typical hysteresis Curve. It also shows that as the background activation is increased, it is easier to take the Network to the active stable steady state, that is, the neurones are more willing to fire when the background level is increased just as it is found in real neurones.
It is hard to estabilize neuronal networks at low firing levels. Cortical networks appear optimized for fast inhibitory feedback.
[[Random vs actual networks|https://keep.google.com/media/1U4dqKKV7YH49SYls-4kAdcnI0WznQUk?accept=image/gif,image/jpeg,image/jpg,image/png,image/webp,audio/aac&sz=w1855-h941]]. These comments apply to other models, like [[Random Boolean network]]s.
!!!__Externally driven ongoing activity__
it appears that in each cortical area, a major portion of
the excitation that drives the ongoing activity is derived from activity
coming through the white matter. The inhibition is generated locally.
This arrangement assures the local stability of the ongoing activity.
When the entire cortex is viewed as one huge network, stability is as-
sured by the short delay of the local inhibitory feedback, as compared
with the conduction times of excitation through the white matter.
!!!__Modes of activity in random networks__
even completely random networks can generate stable
firing patterns (modes of activity). Using models, one can create a whole
spectrum of stable modes by a variety of assumptions regarding the
connectivity, the distribution of synaptic strengths, and the internal prop-
erties of each neuron. The question remains to what degree the modes
of activity observed in the cortex are due to the internal structure of the
cortex and to what degree these modes are due to pacemakerlike activity
derived from deeper nuclei.
!!__Relations to real [[cortical|Cortex]] [[Neuron]]s__
There are several attractive features, as well as weaknesses of the Hopfield network model, as a model of real [[Neuron]]s, particularly in the [[Cortex]]. These are mostly discussed in the Corticonics book (pages 187-193).
<mark>Is there any recent research on the applicability of the model, and the idea of content-addressable memory to the [[Brain]]?</mark>
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
See [[Measures and metrics for networks]]
One can distinguish two types of important nodes in directed networks. We describe them for the case of an information network, like WWW first:
*//authorities// are nodes that contain useful information on a topic of interest
*//hubs// are nodes that point us to the best authorities
This idea was implemented by Kleinberg into the //hyperlink-induced topic search// or //HITS// algorithm. The mathematical definitions that tries to capture the above intuition are:
*//authority centrality//: vertex pointed by many hubs (i.e. by many nodes with high hub centrality)
*//hub centrality//: vertex points to many authorities (i.e. vertices with high authority centrality).
Mathematically,
$$\mathbf{x}=\alpha\mathbf{A}\mathbf{y}$$
$$\mathbf{y}=\beta\mathbf{A}^T\mathbf{x}$$
where $$\mathbf{x}$$ and $$\mathbf{y}$$ are the authority and hub centralities, respectively. These equations combine to show that these centralities are in fact the eigenvectors of $$\mathbf{A}\mathbf{A}^T$$ and $$\mathbf{A}^T\mathbf{A}$$, respectively, with the same eigenvalue (which must be the leading one, suing similar arguments as cases above, and which is equal to $$(\alpha \beta)^{-1}$$. $$\beta$$ (or $$alpha$$, but not both) is a free parameter that can be chosen to be $$1$$ as we don't care about relative centralities.
This connection means that these centralities are similar to the eigenvector centralities for the cocitation and bibliographic coupling network, respectively (see [[Mathematics of networks]]).
A rule used to determine whether a [[resonant|Resonance (Chemistry)]] cyclic molecule is [[aromatic|Aromatic compound]], so that it has more stability than mere electron delocalization would suggest.
[[Aromatic Compounds and Huckel's Rule|https://www.youtube.com/watch?v=RaBI3lAACKg]]
[[Google|https://www.google.es/search?q=hudson+river+school]] -- [[Wiki|https://www.wikiwand.com/en/Hudson_River_School]]
__Albert Bierstadt__
[img[https://upload.wikimedia.org/wikipedia/commons/5/5c/Albert_Bierstadt_-_Among_the_Sierra_Nevada,_California_-_Google_Art_Project.jpg]]
[img[http://luminous-landscape.com/wp-content/uploads/2015/02/IMG-1.Bierstadt.jpg]]
__Mauritz Frederick Hendrik de Haas__
[img[https://americangallery.files.wordpress.com/2013/05/hudson-river-under-the-moonlight.jpg?w=600&h=402]]
__Thomas Cole__
[img[https://upload.wikimedia.org/wikipedia/commons/b/b1/Cole_Thomas_The_Oxbow_%28The_Connecticut_River_near_Northampton_1836%29.jpg]]
A code used in [[Data compression]] that is optimal, in the sense that it achieves the entropy limit (within less than one bit).
https://en.wikipedia.org/wiki/Huffman_coding
https://www.cs.cf.ac.uk/Dave/Multimedia/node210.html
!!!__Algorithm__
:1. Initialization: Put all nodes in an OPEN list, keep it sorted at all times (e.g., ABCDE).
:2. Repeat until the OPEN list has only one node left:
::(a) From OPEN pick two nodes having the lowest frequencies/probabilities, create a parent node of them.
::(b) Assign the sum of the children's frequencies/probabilities to the parent node and insert it into OPEN.
::(c) Assign code 0, 1 to the two branches of the tree, and delete the children from OPEN.
In the animation below, the blue nodes are in the //OPEN list//., at every iteration we choose the nodes with the two lowest frequencies within the blue nodes (with preference with those not yet in the tree, if equal frequency).
[img[https://upload.wikimedia.org/wikipedia/commons/a/ac/Huffman_huff_demo.gif]]
https://en.wikipedia.org/wiki/Human_behavior
[[Introduction|https://www.youtube.com/watch?v=IdFkAV3In0k]]
[[Real human genetics|https://www.youtube.com/watch?v=l9_lT0odWww]]
[[Analysis of flag designs|http://flagstories.co/]]
http://www.open.edu/openlearn/science-maths-technology/science/biology/hearing/content-section-3.3
http://vaczy.dk/htm/acoustics.htm
http://www.newmusicbox.org/articles/The-Musical-Ear/
Actually, which sounds sound nice together is apparently a far more complex question than rhythms (not an expert here just curious). The main explanation I can find (given that there are many things yet unknown, such as the roles spatial, temporal, and neural encoding play) is mentioned here: http://www.newmusicbox.org/articles/The-Musical-Ear/ The basilar membrane is known to certainly play a role in pitch perception. Now, most times we hear a frequency we hear it from some object (like an instrument) that generates harmonics of that frequency (ultimately due to ratios of lengths and linear dispersion relations). Now, harmonic frequencies (with simple ratios as you say) share a lot of harmonics themselves. These will excite the basilar membrane in the same spots. And as long as the harmonics don't differ by more than about 10Hz, they will be indistinguishable (as far as the basilar membrane is concerned, due to bandwidth). However, if you make to non harmonic sounds with two non-conmensurate objects, a lot of their harmonics will be very close, and within the so called critical frequency, which has been shown to cause dissonant perception. Now, a plausible theory for why even pure sinusodial waves at simple ratios tend to sound better (though I did the test now, two non-harmonic sin waves don't sound nearly as bad as two non-harmonic piano notes), may be that the brain develops neuronal networks to prefer these sounds.
Your theory of the brain detecting the rhythms is still interesting though, and may be relevant to the "temporal coding" theoreis that have been proposed, but I have not read much about those..
http://plasticity.szynalski.com/tone-generator.htm
[[The Neural Code of Pitch and Harmony|https://books.google.co.uk/books?id=gAvUBwAAQBAJ&pg=PA64&lpg=PA64&dq=Basilar+membrane+harmony&source=bl&ots=Q5Q0ORrlbs&sig=EfeuL2zPqDSMu1JbJcowhRJG4K8&hl=en&sa=X&ved=0ahUKEwjg9N7bmeTKAhWGvA8KHSEJB4YQ6AEIKTAC#v=onepage&q=Basilar%20membrane%20harmony&f=false]]
https://en.wikipedia.org/wiki/Basilar_membrane
https://en.wikipedia.org/wiki/Pitch_%28music%29#Theories_of_pitch_perception
https://en.wikipedia.org/wiki/Consonance_and_dissonance#Physiological_basis_of_dissonance
https://en.wikipedia.org/wiki/Music_psychology#Neural_correlates_of_musical_training
https://en.wikipedia.org/wiki/Psychoacoustics#Music
[[Music and measure theory|https://www.youtube.com/watch?v=cyW5z-M2yzw]] The reason it works so well to have twelve notes in the chromatic scale is that powers of the twelveth root of two tend to be within a 1% margin of error of simple rational numbers. And it's good to have powers of the same factor for the notes, because the brain perceives separation between frequencies logarithmically not linearly.
* [[Neuroscience]]
** [[Behavioural neuroscience]]
** [[Cognitive neuroscience]]
* [[Cognitive science]]
* [[Psychology]]
-----------
* [[Intelligence augmentation]]
[[Wittgenstein's languages games and learning language|https://www.youtube.com/watch?v=yXkEpzexYIU#t=26m]]
[[Hebbian theory]], [[Neuroscience]], [[Memory]].
[[Cognitive science]]
[ext[Olfaction - structure and function | Processing the Environment | MCAT | Khan Academy|https://www.youtube.com/watch?v=5-McqAO8_Qw]]
[[video|https://www.youtube.com/watch?v=zN6-Eka5jRA]]
[[Science on Saturday: Scents and Sensibility: The Molecular Mechanisms of Olfaction|https://www.youtube.com/watch?v=bsU-H4H_ACo]]
!!__Anatomy and miicroanatomy__
[[video|https://www.youtube.com/watch?v=cumUsw1GS74#t=2m]]
[img[https://highered.mheducation.com/sites/dl/free/0072351136/234429/mc_ch15_fig01.jpg]]
[img[http://www.leffingwell.com/olf2.gif]]
!!__Olfactory pathway__
[img[http://what-when-how.com/wp-content/uploads/2012/04/tmp15F80_thumb.jpg]]
the [[G-protein]] binds to and activates Adenylate cyclase which converts ATP to cAMP. The cAMP then binds to cAMP-gated ion channels on the cell and causes them to open, allowing Na+ and Ca2+ to enter the cell. Na+ causes depolarization and Ca2+ causes Cl- channels to open. This causes Cl- to flow out of the cell, increasing depolarization and eventually triggering an [[action potential|Neuron action potential]].
[img[http://www.nature.com/nrn/journal/v11/n3/images/nrn2789-f3.jpg]]
[[receptors|https://www.youtube.com/watch?v=cumUsw1GS74#t=3m32]]
The [[olfactory receptor neuron|https://www.wikiwand.com/en/Olfactory_receptor_neuron]]s are [[bipolar neurons|https://www.wikiwand.com/en/Bipolar_neuron]]
ORs, which are located on the membranes of the cilia have been classified as a complex type of ligand-gated metabotropic channels.[5] There are approximately 1000 different genes that code for the ORs, making them the largest gene family. An odorant will dissolve into the mucus of the olfactory epithelium and then bind to an OR. ORs can bind to a variety of odor molecules, with varying affinities. The difference in affinities causes differences in activation patterns resulting in unique odorant profiles.[6][7] The activated OR in turn activates the intracellular G-protein, GOLF (GNAL), adenylate cyclase and production of cyclic AMP (cAMP) opens ion channels in the cell membrane, resulting in an influx of sodium and calcium ions into the cell, and an efflux of chloride ions. This influx of positive ions and efflux of negative ions causes the neuron to depolarize, generating an action potential.
__Desensitization of Olfactory Neuron__
-----------------
!!!__Olfactory receptor__
https://www.wikiwand.com/en/Olfactory_receptor
Rather than binding specific ligands, olfactory receptors display affinity for a range of odor molecules, and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities,[8] which depend on physio-chemical properties of molecules like their molecular volumes .[9] Once the odorant has bound to the odor receptor, the receptor undergoes structural changes and it binds and activates the olfactory-type G protein on the inside of the olfactory receptor neuron.
!!!__[[Golf protein|https://www.wikiwand.com/en/GNAL]]__
[[Golf: an olfactory neuron specific-G protein involved in odorant signal transduction|https://www.ncbi.nlm.nih.gov/pubmed/2499043]]
!!__Sensitivity__
http://www.pnas.org/content/early/2010/10/06/1004571107.full.pdf
35 binding events (per sec) min. About 0.1 pM (pico mol per litre)
-------------------
A metabotropic receptor is a type of membrane receptor of eukaryotic cells that acts through a secondary messenger.
http://www.ucalgary.ca/pip369/mod8/smell/pathways
http://physrev.physiology.org/content/physrev/78/2/429.full.pdf
[[Human Body Systems|https://www.youtube.com/watch?v=gEUu-A2wfSE]]
[[Human vision]]
[[Human olfaction]]
Human positions refer to the different physical configurations that the human body can take.
https://en.wikipedia.org/wiki/List_of_human_positions
//and primate vision//
!!__Anatomy of the visual system__
!!__Phisiology of the visual system__
!!__Neuroscience of vision__
* Retina, rods and cones
* [[Ganglion cell]]s
* [[Visual cortex]]
------------
[[Color constancy|https://en.wikipedia.org/wiki/Color_constancy]]
[[Land's Demonstration - in Chapter 04- Senses - from Psychology- An Introduction by Russ Dewey|http://www.intropsych.com/ch04_senses/lands_demonstration.html]]
[[A theory of the Benham Top based on center-surround interactions in the parvocellular pathway|http://www.ncbi.nlm.nih.gov/pubmed/15288897]]
[[Opponent process|https://en.wikipedia.org/wiki/Opponent_process]]
[[Receptive field|https://en.wikipedia.org/wiki/Receptive_field]]
Land effect: [[Red and White Demonstration|http://www.t-a-y-l-o-r.com/land/]]
[[Changes in pattern induced flicker colors are mediated by the blue-yellow opponent process|http://www.sciencedirect.com/science/article/pii/004269899290074S]]
[[Contribution of local and global cone-contrasts to color appearance: a Retinex-like model|http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=876256]]
[[Colour]]
See also [[Computer vision]],
[[A biologically inspired spiking model of visual processing for image feature detection|http://www.sciencedirect.com/science/article/pii/S0925231215000326]]
A lot of processing is done already on the [[Retina]]
[img[https://45.media.tumblr.com/51f9fefa9b86967a42f2d2210cbbf2af/tumblr_nl74soY4f41qg20oho1_500.gif]]
https://en.wikipedia.org/wiki/Human_voice
The knowledge regarding all the [[natural aspects|Science]] and [[artificial constructs|Art]] related to Humanity, the collective of the [[Human species|Human]], [[evolved|Evolution]] in [[Planet Earth]].
We include here what is normally known as [[humanities|https://en.wikipedia.org/wiki/Humanities]], but also [[Social sciences]] that treat aspects of Humanity ,,(so for examples scientific studies of animal societies are not part of humanities, although part of social sciences),,
Although humans are the origin of our currently known complex social systems, [[transhuman advancements|Transhumanism]] (like the development of [[AI|Artificial intelligence]], [[Mind uploading]], or [[Genetic engineering]]), or the discovery of [[Extraterrestrial life]] make may future //non-human// agents as, or even more important, in society. Cosmos will need to then be upgraded with a new term more encompassing than "Humanities". Society is one candidate for such a general term, and indeed [[Social sciences]] have gone beyond standard //humanities// in studying social aspects of non-humans. In any case, our current social systems are still mostly human-centered, and the centrality of this tiddler represents that state of affairs.
Note that even as animal right movements are succeeding in giving animals fundamental rights of living and sentient beings (as the right to be protected from suffering), animals will probably still play a secondary role in society, as humans are generally more complex and intelligent in their behaviour.
------
!!__Humans__
The study of [[Human]]s per se (whether individually, or collectively in societies) is called [[Anthropology]].
Humans are part of the [[Tree of life]], and their natural aspects are thus studied in [[Biology]], in particular in [[biological anthropology|https://en.wikipedia.org/wiki/Biological_anthropology]]. On the other hand, the collective of artificial constructs created by Humanity is known as [[Culture]] (studied by [[cultural anthropology|https://en.wikipedia.org/wiki/cultural_anthropology]]).
!!__Human society__
Humans organize themselves in [[societies|Social sciences]]. The organization often involves systems of [[Law]] (~what can* be done), [[Politics]] (~what should we do), and [[Economics]] (~how to do we get what we need).
,,* what can be done, here of course refers to not just what can be done by physical laws, but what is permitted by [[Law]], the societal construct that dictates what humans are allowed or not to do, by society,,
Physical aspects of these societies are mostly studied in [[Geography]], particularly in [[Human geography]].
Human communication is a crucial aspect of the human condition, and of the resulting societies. It is studied in [[Linguistics]] (and in particular, for humans, in [[linguistic anthropology|https://en.wikipedia.org/wiki/Linguistic_anthropology]])
https://en.wikipedia.org/wiki/Hund%27s_rules
http://hyperphysics.phy-astr.gsu.edu/hbase/atomic/hund.html
The first two rule are mostly caused by Coulomb interaction.
The third is caused by spin-orbit coupling.
An extension of [[Levin search]] to evaluate any computable function with asymptotically optimal [[Computational complexity]]
http://www.scholarpedia.org/article/Universal_search#Hutter_search
[[video|https://www.youtube.com/watch?v=oIJmGIZ_-7M&index=2&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp#t=1h38m15s]]
[img[https://www.nbpower.com/media/1664/d-html-en-safety_learning-learning-electricity_generated-hydro-hydro-anim-en.gif]]
An [[Organic compound]] consisting entirely of hydrogen and carbon.
https://www.wikiwand.com/en/Hydrocarbon
A kind of [[Interfacial force|Interfacial forces]]
[[Hydrodynamic boundary conditions|http://web.phys.ust.hk/index.php?option=com_content&task=category§ionid=24&id=252&Itemid=84]]
<mark>Probably good explanation: [[Giant Amplification of Interfacially Driven Transport by Hydrodynamic Slip: Diffusio-Osmosis and Beyond|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.96.186102]]</mark> [[article|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.96.186102]]
[[Wetting, roughness and flow boundary conditions|http://iopscience.iop.org/article/10.1088/0953-8984/23/18/184104/meta]]
,,[[Wetting, roughness and hydrodynamic slip|http://www.crcnetbase.com/doi/abs/10.1201/b14789-3]],,
[[Hydrodynamic force and boundary slip|http://www2.mpip-mainz.mpg.de/documents/akbu/pages/hydrodyn_force.html]]
A [[Chemical element]] composed of hydrogen atoms. These have 1 proton in the nucleus.
The hydrogen atom tends to form a single bond, as it has a single electron in its outer shell (see [[Octet rule]])
''Hydrogen bonds''.
Attraction between the positive part of a [[polar|Polar molecule]] [[Moiety]]in a [[Functional group]] (like [[Hydroxyl]]) of one molecule and an [[electronegative|Electronegativity]] atom (like [[N|Nitrogen]], or [[O|Oxygen]]) in another functional group.
Hydrogen when covalently bonded to a more electronegative atom (like Oxygen) will develop a positive charge, while the electronegative atom will develop a negative charge. The hydrogen atom in some molecule can then attract an electronegative atom in another molecule. $$\sim 1\text{ to }5 k_B T$$.
http://www.bbc.co.uk/education/guides/z3vwxnb/revision/5
A [[Hydrogen]] [[Ion]]. If not specified otherwise, this almost always refers to $$H^+$$, the positive hydrogen ion, or [[Hydron]]
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
A [[Decomposition reaction]] where cleavage of chemical bonds is accomplished by the addition of water. Water splits the [[Molecule]] and joins the two resulting molecules as a [[Hydroxyl]] group + an [[Oxygen]]
The opposite is [[Dehydration synthesis]]
https://www.wikiwand.com/en/Hydrolysis
The positive [[Hydrogen ion]], $$H^+$$
In water $$H^+$$ coordinates with water to form [[Hydronium ion]]s, $$H_3 O^+$$
A compound that tends to mix with the solvent when dissolved in a [[polar|Polar molecule]] solvent, like [[Water]].
Hydrophobicity is really part of an spectrum, the other end of the spectrum being [[Hydrophobic]]
A compound that tends to unmix when dissolved in a [[polar|Polar molecule]] solvent, like [[Water]].
Hydrophobicity is really part of an spectrum, the other end of the spectrum being [[Hydrophilic]]
The physical effect controlling hydrophobicity is the [[Hydrophobic interaction]]
''Hydrophobic interaction''.
Effective force due to a [[Non-polar molecule]] disrupting [[Hydrogen bond]]s in a [[polar|Polar molecule]] solvent. It has entropic and energetic contributions. [[Gecko]]s use these two climb up very smooth surfaces.
Water in its liquid state forms a 3-dimensional network of hydrogen-bonded molecules, that leave more space for each to fluctuate in position, thus reducing its entropy (similar to how a colloid suspension will "crystallize" above a critical concentration for the same entropic reasons). A large molecule will disrupt this configuration, and will effectively reduce the entropy of the system. Therefore, there will be an effective force (entropic force) pushing large molecules together so that this disruption is the least, and so entropy is maximized, as it will in equilibrium. This is the hydrophobic interaction. __Question__: doesn't the fact that large non-polar molecules attract via van der Waals only while water (polar) attracts via Hydrogen bonding, but barely via van der Waals, and therefore these two different kinds of molecule barely attract, not also play a role in they wanting to clump together with like kinds, but separately from unlike kind?
Compounds that experience hydrophobic interactions are known as [[Hydrophobic]]
[img[https://media.giphy.com/media/3oEjI2rJrjb2uO5CtG/giphy.gif]]
The hydroxyde ion is [[O|Oxygen]][[H|Hydrogen]]^^-^^
A [[Functional group]] composed of a [[Hydrogen]] bound to an [[Oxygen]]
[[Cleaning]] processes carried out by a [[Society]] of people.
https://www.wikiwand.com/en/Hygiene
[[Water]] is crucial
* Cleaning spaces
* Cleaning tools, utensils and containers that get in contact with [[Food]].
* Cleaning food
* [[Food preservation]]
* [[Waste management]] and disposal
* Cleaning ones body
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/2/2f/Poster_%22Stop_microbes_use_good_hygiene%22.jpg/640px-Poster_%22Stop_microbes_use_good_hygiene%22.jpg]]
A fixed point is called hyperbolic if none of the eigenvalues of the Jacobian evaluated at the point have zero real part.
Geometry corresponding to a constant negative [[Curvature]] [[Manifold]]. It can be derived by embedding one sheet of a [[Hyperboloid]] in 3D [[Euclidean space]] (although generalizations to . This is the [[Hyperboloid model|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=31m55s]]. The induced metric on the hyperboloid gives ''hyperbolic geometry''.
[[Mark Norfleet - Hyperbolic Geometry|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=2603s]]
!!!__Geodesics (lines) in the hyperboloid model__
Lines can be constructed by taking a plane that passes through the origin and finding its intersection with the hyperboloid. Note that this is analogous to how great circles are constructed in [[Spherical geometry]]
!!__Projective models of hyperbolic geometry__
Different ways of projecting the points in the hyperboloid to planes or subsets of planes give other models.
!!__Projective disk model__
[[projection|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=39m30s]]
[[definition|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=2m]]
!!!__Poincare model (aka conformal disk model)__
[[projection|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=43m20s]]
[[definition|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=5m45s]]
!!!__Upper half-plane model__
[[definition|https://www.youtube.com/watch?v=ZNNZFSxe7oA&t=10m50s]]
In [[Learning theory]], a ''hyperparameter'' refers to a parameter in the learning algorithm itself, which isn't learned by the algorithm, but is chosen before running it. Hyperparameters may be learned (or //hyperlearned//), via methods of [[Model selection]].
A set of points in $$R^n$$ that satisfy $$\mathbf{a}^T \mathbf{x} -b = 0$$
identically and independently distributed
See [[Simplicity bias in finite state transducers]]
On the second question, there is actually a stumbling block due to the random FST ensemble I'm using, which consists only of accessible FSTs (of given size). Accessible means that any state can be reached from the initial state (so that there are no 'useless' states). This is in contrast to random unrestricted FSTs, where each of the K_i n out-stubs are connected to a state, independently and uniformly at random.. Answering probabilistic questions for the latter is much easier than for accessible FSTs (see attached or http://bit.ly/290fHji). I guess we could simulate random unrestricted FSTs, though I think accessible FSTs are a more interesting ensemble, because you fix the actual number of states in the automaton. Anyway, there may still be some things to say here, because in the article I attach he finds a way of relating statistics of automata to those of accessible automata, but only asymptotically, and with inequalities. There may be other approaches with [[Analytic combinatorics]], but they are potentially quite hard.
Regarding the first question, I've been refining my ideas about loops of 'noncoding states' (with output symbols being equal). In particular, looking at the experimental results, I've noticed that bias is associated with 'absorbing regions' that contain at least one non-coding state (approximately absorbing regions also show some bias). An absorbing region is a set of states which you can reach, but which you can't leave. Now, I've found two main factors determining the frequency/neutral-set-size/designability (call this NSS) of an output of an FST that contains this:
* The structure of the absorbing region
* The number of steps spent in the absorbing region, call it m.
Now, I've also found that the NSS is multiplied by 2^(a*m), where a depends on the structure of the absorbing region (in an interesting combinatorial way). So the NSS \propto 2^(a*m). The proportionality constant will depend on the particular string, and the number of noncoding states it passes through, outside the absorbing region (this requires more attention).
Now, if the m output bits from the absorbing region are composed of a repeating pattern (often the case, but I can think of exceptions..), the Lempel-Ziv complexity C <= n-m + const., where n is the total number of bits, and const is the number of bits in the repeating pattern.
Under these assumptions, one can see that the frequency of an output obeys P =NSS/2^n <= 2^(-a*C + b), where I lump all the proportionality constants above in b..
The Fibonacci GP map described in the paper on constrained/unconstrained parts, is actually an example of the simplest kind of FST with the properties above. It can be implemented as a 3-state FST, with an absorbing region consisting of a single non-coding state, and no non-coding states anywhere else. Thus the arguments above work very cleanly. Unfortunately, general FSTs can show more complicated things, like:
* regions, which are not completely absorbing, but still produce bias.
* Several absorbing regions
* Non-coding states outside absorbing regions
* Absorbing regions, which don't produce simple repeating sequences. I think these won't produce as much bias
All these make complicate the picture, and should be taken into account more fully to improve the argument above. In any case, it makes sense the argument above can't be exact (except for simple cases like Fibonacci GP map), because most FSTs show a complexity/frequency plot which is not perfect, but has some noise.
Hope that wasn't too long. I think also that all this will be easier to understand with pictures...
[[ImageNet Classification with Deep Convolutional Neural Networks|https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf]] (AlexNet)
The branch of medicine and biology concerned with immunity, that is, the ability of an organism to resist a particular infection or toxin by the action of specific antibodies or sensitized white blood cells.
[[Immunology in the skin|https://www.youtube.com/watch?v=_VhcZTGv0CU]]
Mutation means: changing objects in place
[[Avoid mutability|https://www.youtube.com/watch?v=e-5obm1G_FY&t=644s#t=13m10s]]
[[Adjacency Matrix and Incidence Matrix|https://www.youtube.com/watch?v=LUDNz2bIjWI&index=7&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
See [[Adjacency matrix]] also
Incremental learning is a machine learning paradigm where the learning process takes place whenever new example(s) emerge and adjusts what has been learned according to the new example(s).
See [[Universal inductive inference]]
[[Springer link|http://link.springer.com/referenceworkentry/10.1007%2F978-0-387-73003-5_304#page-1]]
See here: [[Chapter 2 Information Measures - Section 2.1 A Independence and Markov Chains|https://www.youtube.com/watch?v=nuJ3jTL5qqM&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=4]]
!!!__Independence of two random variables__
!!!__Mutual independence__
!!!__Pairwise independence__
!!!__Conditional independence__
https://en.wikipedia.org/wiki/Conditional_independence
See [[here|https://www.youtube.com/watch?v=nuJ3jTL5qqM&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=4#t=3m52s]]. Note that his definition is the same as in wiki. Just divide by $$p(y)$$ to see this. His example at the end is rather illustrative too.
//aka ICA//
Similar to [[Principal component analysis]], but to find the independent components of variation of the data. An example is the "cocktail party problem", where there are several speakers speaking simultaneously, and we want to decompose the signal from some microphones, into the speech of each individual speaker.
[[Intro video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=39m50s]], applications to "cocktail party problem"
[[Cumulative distribution function]]
!!__Derivation__
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=47m40s]]
[[Example|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=53m18s]] the axes after transforming are the observed $$x$$ for each of the microphones. The axes before transforming correspond to each of the speakers! If the data are Gaussian, however, [[ICA is impossible|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=58m40s]]
!!__Algorithm__
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=1h04m27s]] --> [[algo|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=1h10m05s]]
!!__Applications of ICA__
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=1h12m35s]]
* [[EEG|Electroencephalogram]]
* [[Computer vision]]
Number of ''//independent paths//'' between two vertices (the ''//connectivity//'') gives measure of how strongly connected they are. Paths can be //vertex-independent// if they share no vertex (other than starting or ending vertices), or //edge-independent// if they share no edge.
A //vertex (edges) ''cut set''// is a set of vertices (edges) that if removed will disconnect a specified pair of vertices. A //minimum cut set// is the smallest such set for the vertices (or set of vertices..). For weighted networks a minimum cut set is the set of such vertices that have the least total weight.
See more [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture2_1.pdf]]
__Menger's theorem__:
If there is no cut set of size less than $$n$$, then there are at least $$n$$ independent paths.
This actually implies that size of the minimum cut set ($$C$$) equals the connectivity of two vertices ($$I$$): $$C>n \Rightarrow I>n$$. $$\neg (C>n) \Leftarrow \neg (I>n)$$. $$C\leq n \Leftarrow I\leq n$$. In particular $$C\leq n \Leftarrow I = n$$. However if $$I = n$$, we need to cut at least $$n$$ vertices/edges, so $$C\geq n$$. $$\therefore C=n=I$$.
The //maximum flow// if the network were made of water pipes ([[Flow in a network]]) between two vertices is the number of edge-independent paths times the maximum flow of a single pipe can sustain, or pipe capacity, $$r$$. Let $$I$$ be size of minimum edge cut set. Clearly, $$Ir$$ is a lower bound for this max flow, since each independent path will independently carry max flow $$r$$.. Also, if we remove an edge that forms part of a path between them, we must decrease the flow by at most $$r$$. Thus, if we remove the $$I$$ edges from the minimum cut set, we decrease the flow by at most $$Ir$$, but this must remove all flow. Hence total capacity is at most $$Ir$$, which is then an upper bound. $$Ir$$ is both an upper and lower bound, and hence the maximum flow must equal $$Ir$$. This is the __max-flow/min-cut theorem__, for special case of the same capacity for all pipes.
|The maximum flow between a given pair of vertices in a network is equal to the sum of the weights on the edges of the minimum edge cut set that separates the same two vertices.|
The max-flow/min-cut theorem can be generalized to weighted networks. This can be shown by transforming the weighted network into a multigraph.
See more here: [[Max-flow min-cut theorem]], [[Flow in a network]]
!!!Applications
This result is useful because some computer algorithms (maximum flow algorithms) can compute maximum flow easily. But, by result above, they also calculate the minimum cut set size, and the connectivity, which can be used to find clusters in networks. This is in fact the current standard numerical method for connectivities and cut sets.
The max-flow/min-cut theorem has been used in a polynomial-time algorithm for finding ground states of the thermal random-field Ising model. See reference [257] in Newman's book.
''Induction'', or inductive reasoning, or inductive inference, refers to infering general models from specific observations/facts/data, which usually exhibit some regularities, properties, or relations.
Another definition: [["inference about the unknown by extrapolating a patter about the known"|https://www.youtube.com/watch?v=yXkEpzexYIU#t=8m38s]]. He also discusses justifying the use of induction. [[Part of the reason induction is useful is the|https://www.youtube.com/watch?v=yXkEpzexYIU#t=13m20s]] [[Simplicity]] of the world.
See [[Universal inductive inference]], for a formalization of optimal inductive inference.
__Principles__
* [[Occam's razor]]
* [[Baye's theorem]]
* [[Principle of indifference]]
* [[Principle of multiple explanations]]
See more at [[Universal inductive inference]]
''Industrial engineering'' is a branch of engineering which deals with the __optimization of complex processes or systems__. Industrial engineers work to eliminate waste of time, money, materials, man-hours, machine time, energy and other resources that do not generate value. According to the Institute of Industrial and Systems Engineers, they figure out how to do things better, they engineer processes and systems that improve quality and productivity
[img[http://mime.oregonstate.edu/sites/mime.oregonstate.edu/files/ie-wordle_0.png]]
Industry is the production of goods or related services within an economy, by processing [[raw materials|Raw material extraction]].
This process is more generally called [[Manufacturing]]. Industry is therefore, manufacturing in the context of an economy
https://en.wikipedia.org/wiki/Industry
//How to know something previously unknown, by using something known.//
[[Inductive inference|Induction]], when we make a //prediction// that //generalizes// observed data, but doesn't logically follow from it. See [[Statistical inference]], [[Learning theory]]
[[Deductive inference|Deduction]], when we find a statement that [[logically|Logic]] follows from observed data.
[[Complexity, Phase Transitions, and Inference by Cristopher Moore (part 1)|https://www.youtube.com/watch?v=asw9M8RBcsU]]
__Other classifications and types__
* [[Active inference]]
* [[Hierarchical inference]]
__Influence maximization/optimization in complex networks through optimal percolation__
Keywords: [[Social dynamics]], [[Networks|Network science]], [[Percolation]]
[[Influence maximization in complex networks through optimal percolation|http://www.nature.com/nature/journal/v524/n7563/pdf/nature14604.pdf]]
[[Annotated paper|file:///home/guillefix/Dropbox/Oxford/MMathPhys/Networks/Influence%20maximization%20in%20complex%20networks%20through%20optimal%20percolation.pdf]]
I think this article will be of interest to people investigating social or other networks over which something is transmitted over the edges (whether these are infections, messages, opinions...). These arise in many problems in science and engineering, especially those involving complex social networks. In these networks one can often assign importance to nodes by seeing how much does their removal disrupt the potential spread of the unit being transmitted across the network.
In particular, the ''optimal influence problem'' tries to maximize the influence on the network by affecting the least number of nodes. This article presents a novel algorithm that can find very good approximate solutions to this problem, which is generally NP-hard. They do this by first expressing the problem in terms of a percolation process, so that maximum influence corresponds to making the giant connected component disappear with the least number of nodes removed. Although for small networks this can be tackled using methods from statistical mechanics, an adaptive algorithm is more effective for large networks. They demonstrate its effectiveness, as well as its superiority against other heuristic algorithms, in both synthetic and real networks.
Although I think the article does a good job at summarizing the results in the 4 pages of the letter, I think some more explanation on the connection of the optimal influence problem and their mathematical formulation would be useful to aid the reader's understanding (leaving the SI only for non-crucial details). For instance, I think that it should be mentioned that the stability of the $$G=0$$ solution, under locally tree like assumption, is what determines whether the GCC is present or not, for large networks. Optimal influence chooses the minimum number of nodes that make the $$G=0$$ solution. Similarly, I think the vector $$\mathbf{w}_0$$ is introduced without explaining what it represents (a perturbation to the order parameter vector $$v_{i\rightarrow j}$$.
[['Smaller is smarter' in superspreading of influence in social network|http://phys.org/news/2015-07-smaller-smarter-superspreading-social-network.html]]
[[Containing Epidemic Outbreaks by Message-Passing Techniques|http://journals.aps.org/prx/abstract/10.1103/PhysRevX.4.021024]]
See [[Information theory]], [[Information science]], [[Information measures]]
* [[Entropy]]
* [[Joint entropy]]
* [[Conditional entropy]]
* [[Mutual information]] (the difference between the entropy and the conditional entropy. I.e the decrease in uncertainty on a random variable when you learn about another random variable. I.e. the information you gain on a random variable from another RV) Measure of dependence.
* [[Conditional mutual information]]
* [[Relative entropy]]. Mututal information is a special case. Defines a measure of "distance" between probabiliy distributions. Applications in estimating hypothesis testing errors and in large deviation theory.
* [[Cross entropy]]
[[Shannon's Information Measures|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft]]
[img[http://i.imgur.com/lFj7iId.png]]
[[explanation|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=16m13s]]
[[Continuity of Shannon's Information Measures |https://www.youtube.com/watch?v=L6S2LO7S-7U&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=8]]
[[Some Useful Information Inequalities|https://www.youtube.com/watch?v=tIt4pJAbCDQ&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft&index=13]]
[[Three approaches to the quantitative definition of information|http://www.tandfonline.com/doi/abs/10.1080/00207166808803030?journalCode=gcom20]]
__Information retrieval__
http://nlp.stanford.edu/IR-book/html/htmledition/irbook.html
[[The Library and Information Science Portal|https://en.wikipedia.org/wiki/Portal:Library_and_information_science]]
See [[Data transmission]].
An information source is often modelled as a discrete-time stochastic process, so it is a sequence of [[Random variable]]s, taking values in a set called the //source alphabet//.
An stationary information source is one corresponding to an stationary stochastic process, so that any {finite block of random variables} and {any of its time-shift versions} have exactly the same joint distribution
An important property of an information source is its [[Entropy rate]]
!!__Types of information source__
[[Discrete memoryless source]]
[[Markov input process]]
https://en.wikipedia.org/wiki/Information_system
__Decision support system__
https://en.wikipedia.org/wiki/Decision_support_system
http://reasons.club/
[[Knowledge management]]
''Information theory''
[[Information Theory|https://www.youtube.com/playlist?list=PLE125425EC837021F]], [[Information Theory (CUHK)|https://www.youtube.com/playlist?list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft]]
!! Entropy/Information
* ''Asymptotic equipartition property''
* [[Information measures]]
* [[Data processing theorem]]
* [[Fano's inequality]]
!![[Coding theory]]
A code is a representation of information/data.
Coding theory (and/or coding methods) is the study of the properties of codes and their fitness for a specific application. These applications include [[Data transmission]], [[Data compression]], [[Cryptography]], and [[Network information theory]]
!![[Data transmission]]
See [[Source-channel separation theorem]]
The main problem of study in data transmission theory is: for a particular [[Communication channel]], find code so that data transmission rate is as high as possible, while receiver receives the information with negligible probability of error.
The limit in data transmission rate turns out to be the [[Channel capacity]], as established by the [[Channel coding theorem]].
Data transmission is part of the broader area of study called [[Communication theory]], which includes consideration of the information source and destination.
!! [[Data compression]]
Study of theoretical limits and implementation of codes that make average length of the value of a random variable as short as possible, whether in a lossless, or lossy way.
The limit in the average length of codewords in a lossless code turns out to be the entropy, as established by the [[Source coding theorem]]
Limits in lossy codes are established in [[Rate compression theory]]
!![[Cryptography]]
!![[Network information theory]]
!![[Algorithmic information theory]]
''[[Kolmogorov complexity]]''. Shortest program that will produced desired output in Turing machine. Occam's razor
--------------------
!!!More related areas
* ''Ergodic theory''. A dynamical system is ergodic if it has a unique probabliy distribution in the long time limit, I think Asymptotic equipartition theorem gives probability of each typical sequence.
* ''Hypothesis testing'' (See [[Statistics]]).
* ''[[Statistical mechanics|Statistical physics]]''
* ''[[Quantum information theory]]''
* ''Inference''. Kolmogorov complexity is often applied to extrapolate from data. See also Solomonoff's algorithmic probability, and [[Machine learning]]
* [[Signal processing]]
* ''Gambling and investment''. Theory of investment in stock markets. See [[Game theory]].
** Doubling rate. Has parallels with entropy
* ''[[Probability theory]]''
* [[Sequence space]]s and [[Symbolic dynamics]]
* [[Complexity theory]]
** [[Descriptional complexity]]
----------
[ext[Shannon - A Mathematical Theory of Communication|http://worrydream.com/refs/Shannon - A Mathematical Theory of Communication.pdf]]
[ext[General theory of information transfer: Updated|http://www.sciencedirect.com/science/article/pii/S0166218X07002326]]
[[Entropy reduction]]
[ext[Storing and Transmitting Data: Rudolf Ahlswede’s Lectures on Information ...|https://books.google.co.uk/books?hl=en&lr=&id=EZ6KAwAAQBAJ&oi=fnd&pg=PP5&ots=bqpF4UZhji&sig=fmxtdgsKYFUjKFcYDe9bxdoagFM#v=onepage&q&f=false]]
[ext[Information Theory, Combinatorics, and Search Theory|http://download.springer.com/static/pdf/860/bok%253A978-3-642-36899-8.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-642-36899-8&token2=exp=1467511400~acl=%2Fstatic%2Fpdf%2F860%2Fbok%25253A978-3-642-36899-8.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-3-642-36899-8*~hmac=07f9d2ad15fce4ba4ad13e57c22b7ffbbbabc694ce1928057668a650bdd9c175]]
[[Theory of identification]]
[[Theory of ordering]] (see [[Entropy reduction]])
[[Search theory]]
[ext[YB videos|https://www.youtube.com/user/cse6222yorku/videos?view=0&shelf_id=4&sort=dd]]
-- [[MIT videos|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-050j-information-and-entropy-spring-2008/videos-homework-and-readings/]]
(see [[Civil engineering]])
[[Mode of inheritance]]
[[Genetic linkage]]
[[Genetic dominance]]
!!__Epigenetic inheritance__
An injective function, also called one-to-one, is a function $$F(x)$$ such that $$x \neq y \Rightarrow F(x) \neq F(y)$$.
[[Deep learning]] -- [[Artificial intelligence]]
[[Integrating Symbols into Deep Learning|https://www.cs.ox.ac.uk/seminars/1627.html]]
''Abstract of talk'': Computer Science is the symbolic science of programming, incorporating techniques for representing and reasoning about the semantics, correctness and synthesis of computer programs. Recent techniques involving the learning of deep neural networks has challenged the "human programmer" model of Computer Science by showing that bottom-up approaches to program synthesis from sensory data can achieve impressive results ranging from visual scene analysis, expert level play in Atari games and world-class play in complex board games such as Go. Alongside the successes of Deep Learning increasing concerns are being voiced in the public domain concerning the deployment of fully automated systems with unexpected and undesirable behaviours. In this presentation we will discuss the state-of-the-art and future challenges of Machine Learning technologies which promise the transparency of symbolic Computer Science with the power and reach of sub-symbolic Deep Learning. We will discuss both weak and strong integration models for symbolic and sub-symbolic Machine Learning alongside ongoing work on applications in this area.
Integratint symbols in deep learning talk notes:
* Motivation
** ''Transparency''. Easily interpretable.. See [[Explainable artificial intelligence]]
*** Comprehensibility test. Given a program, ask questions about it.. How well someone asnwers the questions..
*** Depends on how our own human minds work..
*** Can we even understand some of the problems..
*** Alternative: Machines that teach us how they work would be wonderful, because at the moment we need to make the effor to interpret them.
** Computer science. Clear semantics, verification, etc.
** Deep learning. Very different from rest of CS
** Royal society + others... Public concern
** Neet to integrate CS transparency and power of DL
* Deduction and programming
** Howard-Curry correspondance.
** Proofs as programs!
** Used in verification and synthesis of programs
* Machine learning, deduction and programming
** Logic programming (Kowalski 1975). Program <> set of clauses in logic...
** Inductive logic programming (Shapiro 1982, Muggleton 1991). Start with prior knowledge, hypothesize from data addition to knowledge, if hypothesis is verified as sufficiently valid, you add to your knowledge.
** Inverse resolution (Muggleton and Buntine 1988). Resolution?.
** Inverse entailment (more efficient). (muggleton 1995)
** Problems with recursion and predicate invention (muggleton et all 2011)
** Meta-interpretative learning (muggleton et al 2015). Make it into higher order logic framework.
** target theory....
** Hmm, gotta learn more about logic
* Symbolic and non-symbolic machine learning.
** [[Neural Turing machine]]s! (Graves et al 2014). NIPS 2015 workshop. Still doesnt make things necessarely transparent..
** Bayesian-neural integration. Sum-Product Markov networks (Domingos 2015)
** ILP-neural integration. Bottom-clause Neural Nets (Garcez 2014)
* Applications
** Sensory
*** Staircase, Euclid project, microbe movies now
** Motor
*** UCAI 2013. Build stable wall
*** UCAI 2015. Learning efficient strategies.
** Language applications.
*** Learning formal grammars (MLJ 2014).
*** Dependent srting transformations (ECAI 2014). Transparent?..
** What next for meta-interpretive learning
*** Neuro-logical Turing machines
*** Problem decomposition. One of the central issues in programming. Predicate invention is part of this
*** Object invention. Intrinsic to learning and perception. Introducing new entities into language. Hard problem to make the meaningful
*** Large-scale background knowledge: How can learners scope relevance of background concepts?
*** Probabilistic reasoning.Bayesian.. Single examples?
***
!!__Approaches__
See some papers above
* [[Neural Turing machine]]
* [[Neural programmer-interpreter]]
* [[Deep symbolic reinforcement learning]]
* [[Program induction]]
https://www.ndcn.ox.ac.uk/publications/420742
[[Learning symbolic rules with ANNs|https://books.google.co.uk/books?hl=en&lr=&id=TrqjBQAAQBAJ&oi=fnd&pg=PA73&dq=combinatorics+of+neural+networks+-optimization&ots=v1Z6XS3XVt&sig=gfVu4LqQGakrhkmsvfGlTkYS7Yc#v=onepage&q=combinatorics%20of%20neural%20networks%20-optimization&f=false]]
''Intelligence'' may be defined as the ability of an agent to achieve goals in many different environments.
!!__Features of intelligence__
* [[Learning]]
** [[One-shot learning]]
** [[Learning to learn]]
* [[Inference]]. ,,[[Active inference]], [[Hierarchical inference]],,
** [[Induction]]
** [[Deduction]] -- [[Logic]]
* [[Generalization]] -- [[Abstraction]] -- [[Concept]] --
** [[Compositionality]]
** [[Causality]]
* [[Memory]]
* [[Attention]]
* [[Perception]] -- [[Emotion]]
* [[Imagination]] -- [[Creativity]] -- [[Fun]]
* [[Play]] -- [[Exploration]]
* [[Communication]]
[[Dual process theory]] -- [[Understanding]] --> [[Reasoning]]
!!__Types of intelligence__
* [[Artificial intelligence]] (aka machine intelligence..)
** [[General artificial intelligence]]
** [[Machine learning]], [[Deep learning]]
** [[Logic]]
* [[Natural intelligence]]
**[[Human intelligence]]
* [[Intelligence augmentation]]
* [[Hybrid intelligence]]
!!__[[Neuroscience]] and [[Artificial intelligence]]__
[[Searching Rat Brains for Clues on How to Make Smarter Machines|https://www.technologyreview.com/s/602627/searching-rat-brains-for-clues-on-how-to-make-smarter-machines/]]
[[Toward an Integration of Deep Learning and Neuroscience]]
[[Neuromorphic computing]]
[[What are the advantages and disadvantages I should have to be aware of if I would like to to use Spiking Neural Networks (SNN) as machine learning tools?|https://www.quora.com/What-are-the-advantages-and-disadvantages-I-should-have-to-be-aware-of-if-I-would-like-to-to-use-Spiking-Neural-Networks-SNN-as-machine-learning-tools]]
[[Spiking neural network]]
!!![[Binding problem]]
[[AI for science|http://slides.com/guillermovalle/deck-3/fullscreen#/]]
[[Center for Brains, Minds and Machines (CBMM)|https://www.youtube.com/channel/UCGoxKRfTs0jQP52cfHCyyRQ]]
-------------------
!!![[Cognitive science]]
!!![[Free energy principle]]
!!![[Philosophy of mind]]
------------
[[Godel, Escher, Bach]]
[[Augmentation Research Efforts|http://www.sis.pitt.edu/spring/arc/]]
https://www.wikiwand.com/en/Alan_Kay
[[AugMath]], [[Human-computer interaction]]
[[Constraint Hierarchies|http://link.springer.com/chapter/10.1007/978-3-642-85983-0_4#page-1]]
http://worrydream.com/
http://michaelnielsen.org/
[[Kernel’s Quest to Enhance Human Intelligence|https://medium.com/@bryan_johnson/kernels-quest-to-enhance-human-intelligence-7da5e16fa16c#.2a5wxazhn]] http://kernel.co/
http://michaelnielsen.org/
Facebook, twitter news feed...
Recently seen in PRE:
[[Fractional telegrapher's equation from fractional persistent random walks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.052107]]
[[Nondeterministic self-assembly of two tile types on a lattice|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.042412]]
[[Turning intractable counting into sampling: Computing the configurational entropy of three-dimensional jammed packings|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.012906]]
[[Synopsis: Trees Crumbling in the Wind|http://physics.aps.org/synopsis-for/10.1103/PhysRevE.93.023001]]
[[Non-Hermitian localization in biological networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.042310]]
[[Physical origin of nonequilibrium fluctuation-induced forces in fluids|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.93.012148]]
[[Pattern formation in flocking models: A hydrodynamic description|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.062111]]
[[Random walk with random resetting to the maximum position|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.052126]]
[[Flocking with discrete symmetry: The two-dimensional active Ising model|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.042119]]
[[Spatial distribution of thermal energy in equilibrium|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.060103]]
[[Signatures of infinity: Nonergodicity and resource scaling in prediction, complexity, and learning|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.050106]]
[[Stochastic thermodynamics of hidden pumps|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.052114]]
[[Stochastic thermodynamics of Langevin systems under time-delayed feedback control: Second-law-like inequalities|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.042114]]
See [[Phoretic mechanisms of colloids]]. [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]
[[Interfaces: in fluid mechanics and across disciplines|http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=7280640&fileId=S0022112009994186]]
!!__Microscopic interfacial forces__
See [[Intermolecular forces]]
Excluded volume
van der Waals
Hydrophobic
Electrostatic
[[Principles and applications of nanofluidic transport|http://www.nature.com/nnano/journal/v4/n11/abs/nnano.2009.332.html]]
http://sci-hub.cc/10.1017/S0022112010004404
!!__Mesoscopic interfacial forces__
__[[Osmotic forces]]__
[[Diffusio-osmosis]], [[Thermo-osmosis]], etc.
__[[Hydrodynamic slip]]__
__[[Surface tension]]__
!!__Theory of interfacial forces__
Debye-Huckel double layer
See book by Hunter - Foundations of colloid science
[[Surface Forces in Transport Phenomena|http://link.springer.com/chapter/10.1007/978-1-4757-6639-4_11]]
[[Surface and Interfacial Forces|https://books.google.co.uk/books?id=pR0YPNBdf_kC&pg=PA335&lpg=PA335&dq=interfacial+force+excluded+volume&source=bl&ots=cxPn8HM9MR&sig=MOiSvJtBEOZimTqnvMEkDHOQv14&hl=en&sa=X&ved=0ahUKEwjJwb2n9NTNAhXmB8AKHei1DDsQ6AEIITAA#v=onepage&q=interfacial%20force%20excluded%20volume&f=false]]
Intermolecular forces are usually composed of a repulsive and an attractive part:
*The ''repulsive part'' is essentially quantum mechanical (in particular, the [[Pauli exclusion principle]] plays a key role). However, often we approximate it by a hard-sphere infinitely steep potential, because the real potential is much steeper than other potentials in most problems.
*The ''attractive part'' shows more variability, but it almost invariably is of electrostatic origin.
If the potential indeed has an attractive component (the repulsive one always exists), then the potential will present a minimum, corresponding to an equilibrium state, known as a ''bond''. The depth of the potential minimum (relative to the thermal energy, $$k_B T$$) determines the //strength//, or //stiffness// of the bond. One often makes a distinction between:
* ''Chemical bonds'' or permanent bonds (see [[here|Chemical bond]]) are those with bond energy is much larger than the thermal energy.
* ''Physical bonds'' or temporary bonds are those with bond energy comparable to, or just a bit bigger than the thermal energy.
__Common intermolecular forces__
* [[Van der Waals force]]s.
* [[Hydrogen bond]]s.
* [[Hydrophobic interaction]].
--------------------------
See [[this video|https://www.youtube.com/watch?v=yFq4EieGWF0]], [[examples|https://www.youtube.com/watch?v=yFq4EieGWF0#t=6m]]
[[HTTP vs IPFS: is Peer-to-Peer Sharing the Future of the Web?|http://www.sitepoint.com/http-vs-ipfs-is-peer-to-peer-sharing-the-future-of-the-web/?utm_content=bufferb4aaf&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer]]
Find websites with certain TLD (top level domain): https://domainpunch.com/tlds/topm.php
[[Device democracy|https://drive.google.com/file/d/0B1foXI_b_a7DZkhfcjNuWGxOdmpSenRqbHQtT0FnUEp4ODB3/view]]
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
[[Dynamical system]]s
A fixed point (and other structures too, if suitably generalized) of a dynamical system has three kinds of invariant manifolds:
* Unstable manifold
* Stable manifold
* Center manifold
See Chapter 3 in Wiggins book.
[[ChaosBook.org chapter Stretch, fold, prune - Stable, unstable manifolds|https://www.youtube.com/watch?v=w72O2xMUlp8]]
[[ChaosBook.org chapter Stretch, fold, prune- Plotting an unstable manifold|https://www.youtube.com/watch?v=4j6iP8yS7HM]]
a [[Measure]] that is preserved by some [[Function]]
We say that the function $$f: X \rightarrow X$$ preserves a measure $$\mu$$ on $$(X\mathcal{B})$$, if $$\mu(f^{-1} B) = \mu(B)$$, for all $$B \in \mathcal{B}$$. The function is then said to be $$\mu$$-preserving, or $$\mu$$ is said to be $$f$$-invariant.
https://en.wikipedia.org/wiki/Invariant_measure
An inverse problem is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in computer tomography, source reconstructing in acoustics, or calculating the density of the Earth from measurements of its gravity field.
https://www.wikiwand.com/en/Inverse_problem
[[Linear inverse problem]]
<big>[[Convex optimization heuristics for linear inverse problems]]</big>. Seizes [[Simplicity]] of data to solve underdetermined problem.
http://www.bbc.co.uk/education/guides/zd8hvcw/revision
[[Ionic bonding]]
[[Ionic compound]]
A [[Membrane protein]] that regulates the flow of ions. This is a kind of active [[Cell transport]].
They can be open or closed and work as molecular electric nanoswitches.
[[A permeation theory for single-file ion channels: Corresponding occupancy states produce Michaelis–Menten behavior|http://scitation.aip.org/content/aip/journal/jcp/117/24/10.1063/1.1522709]]
[[A permeation theory for single-file ion channels: Concerted-association’dissociation |http://www.circle4.com/nelson/pubs/nelson2003.pdf]]
[[A permeation theory for single-file ion channels: One- and two-step models|http://scitation.aip.org/content/aip/journal/jcp/134/16/10.1063/1.3580562]]
!!__Examples__
__GABA receptors__
__Sodium-potassium pump__
Uses huge amount of [[ATP]]
!!__Properties__
Selective to particular [[Ion]]s
Gating: they switch between open and close state due to certain signals:
* Ligands
* Voltage
* Mechanical signal: membrane stress, as in the sense of Touch!
[img[http://www.nature.com/scitable/content/ne0000/ne0000/ne0000/ne0000/14615298/zagotta_440427a-f1.2_2_1.jpg]]
__Selectivity for potassium__
Sodium, being smaller but with same charge has a larger electric field around it. The selectivity is due to the fact that the ions are in [[Water]] [[Solution (Chemistry)]]. Potassium is easier to dehydrate as it attracts water less strongly as it's bigger.
Isoenergetic and aquomimetic diffusion pahtway..
The [[Carbonyl]] group in the [[Peptide bond]] gives the polar bond (like those in water). Their arrangement mimicks the arrangament of water molecules in the hydration shell of the selected ion!
[img[http://www.nature.com/nrn/journal/v4/n12/images/nrn1244-f3.jpg]]
__Selectivity for sodium and calcium__
Ongoing research
__Voltage sensing__
Positive charges (often Arginines --NH,,3,,^^+^^) in S4 subunit act as voltage sensor
Electromechanical coupling
!!__Experimental techniques__
[[Patch clamp method]]
-------------
Armstrong. Life among the axons (2007)
How good were the early predictions for the mechanics of ionic selectivity and voltage sensitivity?
//ligand-gated ion channel//s
Signal receptor coupled to [[Ion channel]]
!!__Examples__
__GABA receptors__
See [[Ion]]s
Electronic transfer of electrons between atoms makes them ions which attract via the [[Coulomb interaction]], so $$1/r$$ and isotropic. It is $$\sim 100 k_B T$$. However, interaction is strongly modified in a solution, due to __screening__ (similar to Debye screening in [[Plasma physics]]).
A type of [[Chemical bond]] formed by [[Ion]]s
In ionic bonding, the metals are oxidised and the non-metals are reduced.
http://www.bbc.co.uk/education/guides/zd8hvcw/revision/5
[img[http://a.files.bbci.co.uk/bam/live/content/zy96yrd/small]]
See [[Ion]], [[Ionic bond]]
[[Testing for ions and gases|http://www.bbc.co.uk/education/guides/z27ycdm/revision/1]]
A [[metallic|Metal]] element
!!__[[Iron extraction]]__
!!__Uses__
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/5
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/6
Iron is extracted from iron ore in a huge container called a blast furnace. Iron ores such as haematite contain iron(III) oxide, Fe2O3. The oxygen must be removed from the iron(III) oxide in order to leave the iron behind. Reactions in which oxygen is removed are called reduction reactions.
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/4
[img[http://a.files.bbci.co.uk/bam/live/content/zm3jtfr/large]]
Lattice with spins interacting with nearest neighbours to favour either alignment and anti-alignment, as a minimal model of a ferromagnet. It has many connections with other systems in [[Statistical physics]], and [[Complex systems]], due to the abstract nature of the model.
1D Ising model was solved by Ising and others.
A major breakthrough in statistical physics was the exact solution of the Ising model in two dimensions [107]. Onsager
gave in 1944 a complete solution of the problem in zero external magnetic field.
But in three dimensions, Istrail has
shown [108] that essentially all versions of the Ising model are computationally intractable across lattices and thus the
3D Ising model, in its full, is NP-complete.
For another model with many interesting connections, see [[Spin glass]]
A [[Morphism]] that is [[bijective|Bijection]]
Isotopes are variants of a particular [[Chemical element]] which differ in [[Neutron]] number, although all isotopes of a given element have the same number of [[Proton]]s in each [[Atom]].
[[M-disc|http://www.mdisc.com/]] discs that last up to 1000 years.
[[Artificial intelligence innovation]]
[[Virtual reality]]
A particular kind of [[Self-propelled particle]] with a kind of asymmetry corresponding to half of the particle having one property, and the other a different one. Most often a Janus swimmer refers to spherical colloids, where one hemisphere is coated with some material, and the other with a different one (or just exposing the material of the colloid itself).
A particular kind is the [[Catalytic conductor-insulator Janus swimmer]]
//The language of the web//
A [[Programming]] language, often used for [[Frontend web development]].
!!![[Redux|http://redux.js.org/docs/basics/Store.html]] is a nice functional programming-like framework for [[React|https://facebook.github.io/react/]]. Learn [[redux|https://www.youtube.com/watch?annotation_id=d112cc03-a081-455c-99e4-4f6a60460b90&feature=cards&list=PLuykYQ1am9zY9-O-Y8w7uISxLjQLcPmN4&src_vid=j5a9l1Td2Lo&v=hmwBow1PUuo]].
[[Javascript in one pic|http://coodict.github.io/javascript-in-one-pic/]]
!!__JS libraries__
https://github.com/dominictarr/hyperscript
!!!__[[Functional programming on JavaScript]]__
!!!__[[Object-oriented programming on JavaScript]]__
!!![[JS animation libraries]]
!!![[Meteor (JS)]]
!!![[Math JS libraries]]
[[Graphics and visualization web libraries]]
[[5 JAVASCRIPT LIBRARIES FOR JULY 2016|http://www.devstrend.com/5-javascript-libraries-july-2016/]]
!!!__Other__
https://jsx.github.io/
Reactive programming: http://reactivex.io/
OOP on JS: https://github.com/jneen/pjs
http://requirejs.org/docs/commonjs.html
http://requirejs.org/
http://www.typescriptlang.org/Tutorial
http://brackets.io/
https://react.rocks/
https://material.angularjs.org/latest/
https://getmdl.io/
https://www.polymer-project.org/1.0/
Animation and graphics:
https://www.khanacademy.org/computing/computer-programming
https://developer.mozilla.org/en-US/docs/Web/API/WebGL_API/Tutorial/Getting_started_with_WebGL
Data structures: http://jnuno.com/tree-model-js/
[[Functional programming]]: [[Functional programming in Javascript|https://www.youtube.com/watch?v=1DMolJ2FrNY&list=PL0zVEGEvSaeEd9hlmCXrk5yUyqUag-n84#t=71.591166]] Functional progr JS library: http://ramdajs.com/0.19.1/index.html. https://lodash.com/. This looks awesome: http://elm-lang.org/
Other tools: https://babeljs.io/docs/setup/ To compile ECMAscript 2015 to normal compatible JS !! Meteor has ES6 package already
Testing: https://github.com/sindresorhus/ava for concurrent testing
-----------------------
Other JS-related languages
__TypeScript__
http://stackoverflow.com/questions/14412164/is-there-a-tool-to-convert-javascript-files-to-typescript
http://www.typescriptlang.org/
__Coffeescript__
__JavaScript CAS__
http://algebrite.org/
[[JavaScript-CAS|http://af.id.au/javascript-cas/]]
[[Coffeequate|https://github.com/MatthewJA/Coffeequate/tree/master/src]]
http://algebra.js.org/
https://github.com/antimatter15/cas.js
__General maths__
http://mathjs.org/
To deploy: `bundle exec jekyll serve --watch`
See [[here|https://help.github.com/articles/setting-up-your-github-pages-site-locally-with-jekyll/]] for set-up
Similar to [[KL divergence|Relative entropy]]
https://www.youtube.com/watch?v=QPkb5VcgXAM#t=20m55
[[video|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=43m30s]]
Let $$f$$ be a [[Convex function]], $$f'' \geq 0$$
Let $$X$$ be a [[Random variable]]
Then,
$$f(\mathbb{E}[X]) \leq \mathbb{E}[f(X)]$$
where $$\mathbb{E}$$ denotes [[Expectation]]
!!![[Picture|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=45m]]
[img[14_ExpectationMaximization_8_0.png]]
(this is a nice case, one can imagine less intuitive cases, but the inequality is still true).
Further, if $$f''(X) > 0$$ ($$f$$ is strictly convex), then
$$f(\mathbb{E}[X]) = \mathbb{E}[f(X)] \Leftrightarrow X = \mathbb{E}[X]$$ w.p. $$1$$
If $$f'' \leq 0$$ ($$f$$ is concave)
$$f(\mathbb{E}[X]) \geq \mathbb{E}[f(X)]$$
etc.
A ''join'', $$\vee$$ is an [[operation|Operation (Mathematics)]] defined on elements of a [[poset|Partially ordered set]] $$P$$ (not necessarily all of them) defined as:
The join (or //[[Least upper bound]]//) of $$a, b \in P$$ is an element $$a \vee b \in p$$ such that:
:(a) $$a \vee b$$ is an //upper bound// of $$a$$ and $$b$$: thus $$a \preceq a \vee b$$ and $$b \preceq a \vee b$$;
:(b) $$a \vee b$$ is the least such upper bound: i.e., if there exists $$c \in P$$ such that $$a \preceq c$$ and $$b \preceq c$$ then $$a \vee b \preceq c$$.
Note that, if it exists, a join is necessarily unique.
See also [[Lattice (algebraic structure)]]
In [[Information theory]], the ''joint entropy'' of a pair of [[Random variable]] $$X$$ and $$Y$$ is defined as:
$$H(X,Y) = \sum_{x,y} p(x,y) \log{p(x,y)}$$
[[Joint entropy|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=6m20s]]
Animation: http://laughinghan.github.io/radiance/
<mark><big>Awesome</big></mark>: timeline-based web animations with gui: https://spiritjs.io/
Also for animation: http://anime-js.com/ -- https://www.sitepoint.com/animating-the-dom-with-anime-js/?utm_content=buffer04622&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer
Jurisprudence is the science, study and theory of law.
https://en.wikipedia.org/wiki/Jurisprudence
[[Law - Springer|http://www.springer.com/gp/law]]
See [[Law]]
One can use the [[Jury test|https://en.wikipedia.org/wiki/Jury_stability_criterion]] to find if the roots of a polynomial are inside the unit circle, which is useful for stability analysis of [[Nonlinear maps]]. This test turns out to be [[useful in stability analysis of discrete time systems|http://nptel.ac.in/courses/108103008/PDF/module3/m3_lec1.pdf]] in [[control theory|Control theory and control systems]].
__Jury test__
Given a quadratic equation of the form:
$$P(\lambda) = \lambda^2 + a_1 \lambda +a_2 =0$$
Both eigenvalues fall within the unit circle //iff// these three conditions hold:
* $$P(+1) >0$$
* $$P(-1) >0$$
* $$a_2<1$$
The way to show this is to divide the problem in two cases (given $$a_1, a_2$$ are real):
* __Eigenvalues real__: Then by a simple diagram, one can show that if the parabola crosses the x-axis, then $$|\lambda_1|$$, $$|\lambda_2|$$<1 is equivalent to $$P(+1) >0$$, $$P(-1) >0$$. Also as $$a_2 = |\lambda_1 \lambda_2|$$ condition three holds.
* __Eigenvalues complex__: Then $$\lambda_1 = \lambda_2^*$$, and $$a_2=\lambda_1\lambda_2 = \lambda_1 \lambda_1^* = |\lambda_1|^2$$. Therefore $$a_2 <1 \Leftrightarrow |\lambda_1| <1$$ (and so $$|\lambda_2| <1$$ too). The two other conditions are immediatelly satisfied because the parabola doesn't cross the axis when eigenvalues are complex.
[[Intro vid|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=5m]] -- [[K Means with Titanic Dataset - Practical Machine Learning Tutorial with Python p.36|https://www.youtube.com/watch?v=j6jstahQp2A&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=36]]
Input is an unlabelled data set $$x_1, x_2, ..., x_m \in \mathbb{R}^n$$
#Initialize a set of points (''centroids''): $$\mu_1, ..., \mu_k \in \mathbb{R}^n$$ randomly
#Repeat until convergence:
## Set $$c_i = \arg\min\limits_j || x_i - \mu_j ||$$. (Assigning the point $$x_i$$ to the cluster with centroid closest to it.)
## $$\mu_j = \frac{\sum\limits_{i=1}^m 1\{c_i=j\}x_i}{\sum\limits_{i=1}^m 1\{c_i=j\}}$$. (Update the cluster centroids to be the mean of the points assigned to it)
[img[http://simplystatistics.org/wp-content/uploads/2014/02/kmeans.gif]]
[[K-means visualization|http://bl.ocks.org/blacki/c41127e3593052d6cf4e]] -- [[Visualizing K-means equilibria|http://bl.ocks.org/blacki/ebba08223eba20b56b62]]
[[K-means is guaranteed to converge|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=12m07s]]. If we define the //distortion function//:
$$J(c, \mu) = \sum\limits_{i=1}^m || x_i -c_i || ^2$$,
k-means is [[Coordinate descent]] on $$J$$
Choosing the number of clusters is often done manually, but there are also automatic algorithms.
It can fall into local optima, and to check that, one can try different random initializations, and see if any converges to a lower value of $$J$$
[[K-theory|https://en.wikipedia.org/wiki/K-theory]] is, roughly speaking, the study of certain kinds of invariants of large matrices...
[[K-Theory Past and Present|https://arxiv.org/abs/math/0012213]]
Examples of abelian invariants are traces and determinants
An [[Explosive percolation]] process that is based on chosing $$k$$ vertices at random and adding edges among those vertices according to some rule.
$$k$$-vertex rules are actually a generalization of $$m$$-edge rules (aka [[Achlioptas process]]) because a $$m$$-edge rule can be constructed from a $$n$$-vertex rule, where $$n \geq 2m$$, which chooses $$n\geq 2m$$ vertices at random (possibly repeating, but still being able to have $$m$$ distinct edges), and then choose $$m$$ edges at random within these $$2m$$ vertices. Note that we need $$n\geq 2m$$ so that we don't restrict the chosen edges to have some vertex in common.
__$$m$$-vertex rule__ (as defined [[here|http://projecteuclid.org/euclid.aoap/1344614200]]): In processes following an $$m$$-vertex rule, the agent is presented with the random list (set) $$v_m$$ of vertices, and, unless two or more are already in the same component, must add one or more edges between them, according to any deterministic or random rule that depends only on the history.
Some $$k$$-vertex rules are examples of [[Non-self-averaging percolation process]], showing novel supercritical phenomena, like stochastic staircases!
In [[Achlioptas process phase transitions are continuous|http://projecteuclid.org/euclid.aoap/1344614200]], it was shown that the [[Percolation phase transition]] for processes following a vertex rule was continuous. However, they can still show some discontinuity arbitrarily close to the critical point (see [[Non-self-averaging percolation process]]).
# All mentals processes derive from operations of the brain
# Genes determine neuronal function
# Social and developmental factors contribute importantly to the variance in mental illness. These factors express themselves in altered [[Gene expression]]. Nurture is ultimatelly expressed as nature.
# Altered gene expression induced by learning gives rise to changed patterns of neuronal connections, which give rise to different forms of thinking and behaviour.
# Psychotherapy produces changes in long-term behaviour by learning which produces changes in gene expression, and hence changes in neuronal interconnection.
[[Top-down causation]]...
Theory of [[Memory]]
See [[Measures and metrics for networks]]
Katz centrality solves the problem posed above by giving all vertices a "free" centrality:
$$\mathbf{x}=\alpha\mathbf{A}\mathbf{x}+\beta \mathbf{1}$$ ....Eq. 2
or rearranging and setting $$\beta=1$$, because all we care is about relative centralities:
$$\mathbf{x}=\beta (1-\alpha\mathbf{A})^{-1} \mathbf{1}=(1-\alpha\mathbf{A})^{-1} \mathbf{1}$$
This is the ''Katz centrality''. Often one computes this not by inverting the matrix (which requires $$O(n^3)$$ computations), but by iterating using Eq. 2 (which requires just $$m$$ multiplications per step (number of nonzero elements of $$A$$, often less steps overall).
A useful extension is to take $$\beta \mathbf{1} \rightarrow \vec{\beta}$$, i.e. give each node possibly a different weight maybe expressing some non-network importance
------
By Taylor expanding it we can see it is like [[Eigenvector centrality]], but taking into account paths of all lengths, but with with a weight.
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
I am a member of Kellogg college during the [[Systems biology DPhil]] program in the University of Oxford.
[[Events|http://www.kellogg.ox.ac.uk/events/]]
-- [[WebLearning|https://weblearn.ox.ac.uk/portal/site/:colleges:kellogg:academic:freshers1617/page/66ea93fb-1e2b-4fc0-b1f7-0eca09303831?null]]
* <big>[[Oxford University registration]]</big>
* ,,~~Complete the online form for the Matriculation Ceremony. Those students who have matriculated at Oxford previously don't attend. "You matriculate at the start of your first degree from the University of Oxford. Matriculation confers membership of the University on students,~~ therefore you do not need to matriculate at the start of any subsequent degrees at the University" (from [[here|https://www.ox.ac.uk/students/new/matriculation?wssl=1]]).,,
* ,,Complete the online form for the Coming-Up and Induction Dinner. ''done''.,,
* Note the Welcome Weeks (from 21 September 2016) events. See [[here|https://mail.google.com/mail/u/0/?ui=2&ik=4fdc192c0f&view=att&th=15732b062e7fd8c4&attid=0.1&disp=inline&safe=1&zw]]
We believe you can look forward to an exciting time - both intellectually and socially- while at Oxford.
[[Catering Provision|https://weblearn.ox.ac.uk/access/content/group/8b1fed65-4d6b-436f-b6e3-75729e44c7dd/Catering%20Provision]]
''Coming-Up and Induction Dinner'': Monday 3 October 2016
[[Register with the college doctor|https://www.campusdoctor.org.uk/oxford/index.html]]
[[Student handbook|https://weblearn.ox.ac.uk/x/oN448z]]
--------------------------
[img[https://weblearn.ox.ac.uk/access/content/group/fb9ae38d-0184-4872-b1c3-2c4b5cc21a5e/Images/Kellogg_College_by_John_Cairns_15.5.14-129.jpg]]
[ext[College Offer Letter|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez%252c%20Guillermo%20Jorge%252c%20College%20Offer%20Letter.pdf]]
-- [[Completion of Conditions Letter|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez,%20Guillermo%20Jorge,%20Completion%20of%20Conditions%20Letter.pdf]]
-- [[Kellogg College Student-College Contract 2016|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Student-College%20Contract%202016.pdf]]
-- [[Kellogg College Essential Information for Offer Holders 2016-17|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Essential%20Information%20for%20Offer%20Holders%202016-17.pdf]]
* <i class="fa fa-check-square" aria-hidden="true"></i> Please confirm whether you wish to accept this offer by contacting the Academic Office via academic.office@kellogg.ox.ac.uk by ''29 April 2016''.
* <i class="fa fa-check-square" aria-hidden="true"></i> The deadline for entry into the initial ballot to allocate accommodation is ''10 June 2016''. [[Accomodation Request Form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Accommodation%20Request%20Form%202016.docx]] --> [[Filled accomodation request form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez,%20Guillermo%20Jorge,%20Financial%20Declaration%20Form%20Corrected.pdf]] -- [[Kellogg College Guide to Accommodation|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Guide%20to%20Accommodation.pdf]] -- [[Kellogg College Oxford Accommodation Information|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Oxford%20Accommodation%20Information.pdf]]. Ask about whether I can stay over the summer vacation, and if not, if I can leave the stuff in my room. [[38/40 Woodstock road|http://www.admin.ox.ac.uk/media/global/wwwadminoxacuk/localsites/accommodation/documents/handbooksaugust2013/38-40_Woodstock_Rd_2013.pdf]] is my preference because it's closest to science/math area and city centre, and supermarkets, etc.
* <i class="fa fa-check-square" aria-hidden="true"></i> Reply email about accomodation!!
* <i class="fa fa-check-square" aria-hidden="true"></i> You will need to return the Financial Declaration Form together with your supporting documentation by ''29 July 2016''. [[Financial declaration form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez%252c%20Guillermo%20Jorge%252c%20Financial%20Declaration%20Form.pdf]] --> [[Filled financial declaration form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez,%20Guillermo%20Jorge,%20Financial%20Declaration%20Form%20Corrected-Filled.pdf]]
* You will be asked to sign and return a form confirming your details and intention to enrol at the University of Oxford and the Student-College Contract 2016 as a condition of enrolment. [[Kellogg College SAMPLE Student-College Contract 2016|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20SAMPLE%20Student-College%20Contract%202016.pdf]]
[[Kellogg College Student-College Contract 2016|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Kellogg%20College%20Student-College%20Contract%202016.pdf]] --> [[Filled Kellogg College Student-College Contract 2016|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20college/Valle%20Perez,%20Guillermo%20Jorge,%20Financial%20Declaration%20Form%20Corrected-Filled.pdf]]
you will need to be in College in time to
attend induction events for graduate students, which are expected to begin on ''3 October
2016''. A wider range of welcome events will run from 23 September 2016.
Your __departmental
induction programme__ may start on a slightly different date, so you will need to arrange to be in
Oxford in time for whichever begins first.
!!!__Accomodation__
Room 7 in 38-40 Woodstock Road (See [[Email|https://mail.google.com/mail/u/0/#search/college+contract/156698217e944979]])
[img[http://www.admin.ox.ac.uk/media/global/wwwadminoxacuk/localsites/accommodation/images/graduate/woodstockroad/38-40woodstockroadbedrooms/38-40---Woodstock-Road---Room-7.jpg]]
[[38-40 Woodstock Road info|http://www.admin.ox.ac.uk/graduateaccommodation/lookingforaccommodation/properties/38-40woodstockroad/]] [[more info|http://www.admin.ox.ac.uk/media/global/wwwadminoxacuk/localsites/accommodation/documents/handbooksaugust2013/38-40_Woodstock_Rd_2013.pdf]]
[[Accomodation handbook|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/accomodation/Graduate%20Accommodation%20Handbook%202016-2017.pdf]]
!!![[Pay here|http://www.oxforduniversitystores.co.uk/browse/extra_info.asp?compid=1&modid=1&catid=1500&prodid=5099]]
!!![[Sample tenancy Agreement|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/accomodation/2016%20Sample%20Tenancy%20Agreement.pdf]] <mark> Will have to sign this, and take keys, once I get back to Oxford</mark>
I'll arrive on the 22nd of September, after 6pm. Tenancy agreement and keys to be sent over to Security Services for you to collect and sign.
Security Services are located at the Old Observatory on South Parks Road (please see attached map).. The Old Observatory, South Parks Road, Oxford, OX1 3RH
[img[https://s10.postimg.org/vuagdsp3t/Selection_628.png]]
Regression using certain basis function (i.e. find coefficients for a certain linear combination of these that fits the training data). Standard ones are polynomials (see Weirestrass approx theorem, but possible terms become very large as we increase degree).
Can also use Gaussians, or //radial basis functions// (RBFs).
Once kernel functions are used, then can use same methods as for linear regression. Basically, we replace each input datum with the kernel functions evaluated at the input datum.
An [[Organic compound]] with the structure RC(=O)R', where R and R' can be an [[Organic compound]]-derived [[Substituent]], like an [[Alkyl]] group.
[img width=300 [https://upload.wikimedia.org/wikipedia/commons/thumb/4/40/Ketone-group-2D-skeletal.svg/640px-Ketone-group-2D-skeletal.svg.png?1473062835602]]
https://en.wikipedia.org/wiki/Kelvin%27s_circulation_theorem
[[Proof of theorem|http://web.mit.edu/fluids-modules/www/potential_flows/LecturesHTML/lec07/kelvintheoproof/kelvintheoproof.html]]
[img[http://thebestofgifs.com/images/tumblr_n7xiqdbaEn1sgnfa7o1_400.gif]]
https://en.wikipedia.org/wiki/Kinase
A ''kinase'' is an [[Enzyme]] that catalyzes the transfer of phosphate groups from high-energy, phosphate-donating molecules to specific substrates
Many are [[Enzyme coupled receptor]]s
Human kinome
(from my email)
In case anyone cares, I think I worked out the irreversibility thing (it's been good revision trying to figure it out, so may be good revision for you too:P):
1. All flow is time-reversible in the theoretical sense that if you reverse all particle's trajectories, you get another physical flow. This is not in general true, though, if you include the viscosity term (although it can be), as this is a term that is there to account for the degrees of freedom we aren't accouning for, so it is in general not time-reversible, just like friction isn't (balls don't just start spountaneously from rest and cooling the floor slightly, this is just the 2nd law).
2. What we usually talk about in fluid mechanics, though, is whether the flow is time-reversible in practice (I think this is called ''kinematic reversibility''). What this means is whether or not I can perform the above theoretical operation of reversing the particle's trajectories, by performing a practically reasonable action. Such a reasonable action is usually changing the boundary conditions of the flow, as that is easy to do. In the case of the die drops, this is what they control, the surfaces of the cylinder
Now, the boundary conditions determine a certain steady-state flow. The important thing about viscous flows (low Re), is that they reach stead state very quickly, so that most of the particles trajectories is spent in steady state, and so most of the trajectory is determined by the boundary condition (b.c.) we control. So we can just turn the cylinder one way, and then the other, and they will have very nearly retraced their steps (I think they turn the cylinder slowly because that keeps Re=UL/nu small).
In higher Reynolds number flows, however, the time the system takes to reach the steady state set by the b.c.s is very significant. Therefore a significant portion of the particles' trajectories is spent in these transient periods. Now, I think the reason these transient periods break (practical) time reversal is because they are not deterimed completely by the b.c.s you control. I think this is because turbulence will most probably set off in them, and as we know, turbulence is random, i.e., out of your control, and thus you can't reverse that (significant) part of the flow. The reason I think turbulence will set off is that when you start moving the cylinder (in the experiment with the die), the no-slip boundary condition will cause a boundary layer, which is very thin due to the low viscosity. This sharp gradient in velocity means high vorticity, which as usual in high Re flows, will spread around, before getting dissipated eventually. This is just the standard onset of turbulence, actually.
Another note: I changed my mind on the pressure thing. I think Chris was right that the gradient of the pressure (though not the pressure itself) will change sign, for Stokes flow. This is actually just because what you do when you time-reverse is change the flow, and the flow determines the pressure distribution, so you can calculate what will happen to the pressure. If you do that for Stoke's equation, its gradient must change sign, as the viscous term does. Examples:
*In the Stokes flow around a sphere, if you reverse the flow, you clearly reverse the pressure gradient, as the drag is in the other direction.
*The cylinder with the die is interesting. If you compute the viscous term, it turns out to be zero (due to symmetry, although not obvious really), so the pressure gradient is zero, so its sign doesn't matter. Actually, if you are more careful, you realize that it can't be zero, there should be a radial component to make the fluid go in a circle, but that radial component would be of the same order, and canceling the inertial term, we ignored.
However, in non-Stokes flow, like say in steady-state inviscid flow, for which Bernouille's theorem holds, the gradient of the pressure doesn't change, as the other terms in NS equation don't either! Example:
*Venturi tube. Clearly, if you reverse the flow, the pressure is still high in the wide parts, and low in the constriction.
The mechanism by which phase separation occurs, depends on whether the concentration proportions fall within the spinodal, or outside it, i.e. whether they are the stable or metastable (see [[Thermodynamics of liquid-liquid unmixing]]).
When it is unstable, the phase separation proceeds inmediatelly and continuously, via a process known as ''spinodal decomposition''.
When the mixture is in the metastable region of the phase diagram, then there is a free energy barrier to be overcome, which requires a large concentration fluctuation to form a //nucleus//, which can then grow. This is known as ''homogeneous nucleation''. However, most often impurities trigger the growth before this happens, and this is known as ''heterogeneous nucleation''.
!!__Spinodal decomposition__
When mixture is in the unstable region any small fluctuation in concentration will tend to be amplified, and this is known as spinodal decomposition.
This kind of "uphill diffusion" is because the fundamental quantity that tends to be equilibriated and thus diffuses to remove gradients is the chemical potential (how to derive this from a more macroscopic description, perhaps using [[Kinetic theory]]??). The chemical potential is related to the first derivative of the free energy. So if the second derivative is positive (as outside the spinodal region) the higher the concentration the higher the chemical potential, and diffusion acts to reduce concentration gradients. However, inside the spinodal region, the second derivative is negative, and the chemical potential decreases with concentration, and thus diffusion acts to increase concentration gradients.
If this was the only mechanism, sharp features will grow the fastest (just as they decay the fastest in normal diffusion). However, there must be something we have neglected. This is because, experimentally, it is found that interfaces have free energy, which isn't included in our free energy (See LectureNotes regarding surface tension).
[add fig. 3.7 here]
A phenomenologically motivated addition to the free energy to account for this is a term proportional to the square of the gradient in concentration with respect to position.
Then one can derive a modified diffusion equation based on:
*a continuity equation
*the current being proportional to the gradient of the //exchange chemical potential// ($$\mu_A-\mu_B$$), with proportionality constant called the //Onsager coefficient//. The way to understand the origin of this is to realize that what matters is what the derivative of the free energy with respect to the concentration is, to determine what must happen at equilibrium.
*the fact that the chemical potential is the (functional) derivative of the free energy with respect to the concentration.
One then obtains a noninear equation, which when linearlized around a $$\phi_0$$ gives the ''Cahn-Hilliard equation''.
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See more here: [[http://pruffle.mit.edu/~ccarter/3.21/Lecture_22/]]
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
A [[Kleene star|https://en.wikipedia.org/wiki/Kleene_star]], in [[Mathematical logic]] and [[Computer science]], (or Kleene operator or Kleene closure) is a unary operation, either on sets of strings or on sets of symbols or characters.
If V is a set of symbols or characters then V* is the set of all strings over symbols in V, including the empty string ε.
It is often used in [[Coding theory]], [[Formal language]] theory, etc.
!!__Personal wiki__
This, TiddlyWiki
http://www.openfst.org/twiki/bin/view/Main/WebHome
,,//aka algorithmic complexity, although that term may refer to some generalizations of Kolmogorov complexity too, I think//,,
One of the main kinds of [[Descriptional complexity]], based on the minimum size of a program (interpreted by a [[Turing machine]]) that produces (//describes//) the object.
Kolmogorov complexity is central in [[Algorithmic information theory]]. __See more in that page__
[[Math 574, Lesson 4-3: Kolmogorov Complexity|https://www.youtube.com/watch?v=S31CbvpZBU4]]
[[other videos|https://www.youtube.com/watch?v=OHCpECIFNxM]]
This is based on describing the information content of a discrete object such as a binary string $$x$$ in terms of the length of the shortest program that generates $$x$$ on universal Turing machine (UTM). This measure is called the Kolmogorov-Chaitin complexity or simply ''Kolmogorov complexity'' $$K(x)$$ of $$x$$.
AIT differs fundamentally from Shannon information theory because the latter is fundamentally a theory about distributions, whereas the former is a theory about the information content of individual objects. Descriptional complexity also differs simplcitly with the notions of complexity in [[Complex systems]].
[ext[Lecture notes on descriptional complexity and randomness|http://www.cs.bu.edu/~gacs/papers/ait-notes.pdf]]
--> [[Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines|http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0096223]] See [[Coding theorem method]]
!!!__Invariance theorem__
See [[Algorithmic information theory]]
!!!__Computability of KC__
KC is not computable, but it is [[semi lower computable|Semicomputable function]], meaning it can be approximated from above, for example, via lossless compression algorithms.. See [[Computability theory]], and "Li, M.; Vitanyi, P. An Introduction to Kolmogorov Complexity and Its Application", for formal proofs.
__Computable approximations to KC__
Levin complexity
[[Data compression]] rate
!!!__Paucity theorems__
Simple strings (paucity) are rare among all possible strings
[[The frequent paucity of trivial strings|http://sci-hub.bz/10.1016/j.ipl.2014.05.006]]
---------------
[[ A Computable Measure of Algorithmic Probability by Finite Approximations|http://arxiv.org/abs/1504.06240]]
See [[MMathPhys oral presentation]]
__Deficiencies of KC__
[img[http://i.imgur.com/Eyx7L1A.png]]
from [ext[here|https://cs.uwaterloo.ca/~shallit/Papers/auto5.pdf]]
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
//also called metric or measure-theoretical entropy//
[[Kolmogorov-Sinai entropy|http://www.scholarpedia.org/article/Kolmogorov-Sinai_entropy]]
See the related [[Topological entropy]]
For a [[Measure-theoretical dynamical system]], the metric entropy of the system with respect to a partition $$\alpha$$ is defined to be the [[Entropy rate]] of the [[stochastic process|Stochastic processes]] resulting from the partition.
The metric entropy (aka (Kolmogorov–Sinai or measure-theoretical) is then the supremum of {the metric entropy with respect to $$\alpha$$} over all finite partitions $$\alpha$$.
Metric entropy provides
the maximum average information per unit of time obtainable per unit of time, from the dynamical system.
See Amigo's book for details. He also gives a good example with the tent map.
Note his notation $$\vee$$ refers to the [[join|https://www.wikiwand.com/en/Join_and_meet]] of two sigma-algebras. See [[here|https://www.wikiwand.com/en/Join_(sigma_algebra)]]
//or KS test//
See its application, and explanation in [[Power-law distributions in empirical data]].
It is a [[nonparametric|Nonparametric statistics]] based on [[Likelihood function]]s.
----------------
https://www.wikiwand.com/en/Kolmogorov%E2%80%93Smirnov_test
http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm
An effect, observed in [[Dilute magnetic alloy]], by which the resistance rises at low temperature.
It is named after the Japanese
physicist Jun Kondo, who in 1964 published a calculation that
indicated how the resistance minimum arose
Father of [[Rocketry]]
[[Konstantin Tsiolkovsky: Russian Father of Rocketry|http://www.space.com/19994-konstantin-tsiolkovsky.html]]
[[Konstantin Tsiolkovsky|https://en.wikipedia.org/wiki/Konstantin_Tsiolkovsky]]
[img[https://upload.wikimedia.org/wikipedia/commons/0/0e/Chertrg_Tsiolkovsky.jpg]]
''Alfred Korzybski'' has been variously described as charlatan, dilettante and ge-
nius. He summarized what he felt were the most important general principles
in the history and philosophy of science, and tried to apply those principles
to everyday life as well as to scientific investigation. I found his major work,
"Science and Sanity" (Kor 58) unreadable, but I got several important heuristic
principles from authors that interpreted and/or popularized his work (Rap 53, Joh 46, ay 41)
A few principles:
a) The map is not the same as the territory it purportedly describes. My
interpretation of this idea has expanded over the years. Korzybski S emphasis
was on features of the territory that the map did not have. Here, we mean "territories
and "maps" in a very general sense
anything in the real world and
something that is supposed to describe the thing in the real world. Since then
I have learned to appreciate the importance of the rich heuristic associations
of maps features that the territories don't necessarily have, but nevertheless make it much easier for us to understand and often misunderstand the
territories.
(b) Two valued logic is usually inappropriate for dealing with events in
the real world. Part of this takes the form of a gray scale for both data and
predictions. Zadeh's "Fuzzy Sets" (Zad 65) may be regarded as one way to
develop this idea. Probability theory is another.
(c) When working on a difficult problem, usually people break it down into
subproblems, and try to work the sub-problems -but often the set of sub-problems is not solvable and or is not really equivalent to the main problem
Either try to break the problem down in a different way or solve the main
problem directly. This last would be the "holistic approach".
(d) en people do not realize that the ill-defined or apparently unsolvable
problem they are working on is really a sub-problem and that (c) is relevant
[[Laplace method]] approximation of the [[mean first-passage time|First-passage time]] for a degree of freedom following a Fokker-Planck equation to overcome a barrier. Most easily solved in 1D, where the result is:
[img width=300 class=img-centered [Kramers_escape_time.png]]
which is known as ''Kramers escape time''. The exponential has the same form as the phenomenological Arrhenius equation, and the pre-factor is known as the //inverse attempt frequency//.
It is used to estimate reaction rates in [[Chemical kinetics]] where one defines a //reaction coordinate// approximating the evolution of the relevant molecules and their potential energy.
__Barrier crossover time from probability distribution__
Can use the (conditional) probability distribution $$P(x,t|x_0,t_0)$$ when a barrier is present to calculate the crossover time. This is done by considering the flux $$J$$ (see [[Fokker-Planck equation]]). The probability distribution for crossing the barrier is then:
$$P(t) = \frac{J(\Delta x, t| - \Delta x, t_0)}{\int_0^\infty dt J(\Delta x, t| - \Delta x, t_0)}$$
where we assume the barrier is at $$0$$, so that $$- \Delta x$$ and $$\Delta x$$ are at opposite sides.
The probability distribution for crossing the barrier above, is the same as the probability distribution for the first passage time. To understand why we use the flux (current, $$J$$) to calculate this, imagine many instances of the Brownian particle in the potential. We can approximate the above $$P(t)$$ by just considering frequencies, in the limit of infinite instances. Now, $$J$$ is just calculated by counting the number of times a particle is found within $$dx$$ of the point $$\Delta x$$, at time $$t$$, multiplied by its velocity at that moment.
Now, consider a first-passage path...
[img[first_passage_path.jpg]]
Well idea is that for every second passage passage path, there is a symmetric one with opposite velocity at measurement point (x,t), that thus cancels it in the sum:
[img[second_passage_path.jpg]]
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
https://en.wikipedia.org/wiki/Krohn%E2%80%93Rhodes_theory
[[Hierarchical Coordinate Systems for Understanding Complexity and its Evolution, with Applications to Genetic Regulatory Networks|http://www.mitpressjournals.org/doi/abs/10.1162/artl.2008.14.3.14305#.Vt8sFkK2HCI]]
[[Scihub link|http://sci-hub.io/http://www.mitpressjournals.org/doi/abs/10.1162/artl.2008.14.3.14305?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed#.Vt8toEK2HCI]] (dunno if it'll work).
[[Automata theory]]
"The Wild book" by Rhodes: [[Applications of Automata Theory and Algebra: Via the Mathematical Theory of Complexity to Biology, Physics, Psychology, Philosophy, and Games|http://www.amazon.com/Applications-Automata-Theory-Algebra-Mathematical/dp/9812836977]] [[Google books|https://books.google.co.uk/books?id=0ukzw5VszNwC&pg=PA259&lpg=PA259&dq=genotype+phenotype+map+finite+state&source=bl&ots=XDLg9roxoc&sig=WOU4eJHD3sYdPvFemQxXfIdUUJU&hl=en&sa=X&ved=0ahUKEwjsj6-b4LHLAhVLnRoKHb6YDVsQ6AEITjAH#v=onepage&q=genotype%20phenotype%20map%20finite%20state&f=false]]
[[Introduction from book|http://www.worldscientific.com/doi/pdf/10.1142/9789812836984_fmatter]]
See NonEq statmech notes.
Also:
http://www-sop.inria.fr/members/Olivier.Faugeras/MVA/ArticlesALire09/acebron-bonilla-etal-05.pdf
http://arxiv.org/pdf/1403.2083v2.pdf
https://en.wikipedia.org/wiki/Kuramoto_model
Things to note:
We transform in most manipulations (including in notes) to a frame that rotates with angular frequency equal to the mean angular frequency of oscillators, $$\langle \omega \rangle$$.
In this frame, the assumption is that the phase of the order parameter, $$\psi$$ is constant, and so can be chosen to $$0$$.
The fact that it is constant is used to deduce that for the non-phase-locked oscillators (in case of partial coherence) their probability distribution must be constant, so that they are in a state of dynamic equilibrium (because their drift velocity $$v$$ can't be $$0$$ as for the phase-locked states).
These differences in behaviour between phase-locked and non-phase-locked oscillators comes from solving their dynamical equations (eq. (9) in [[this paper|http://arxiv.org/pdf/1403.2083v2.pdf]], the behavior of which depends on the parameter $$\omega_i/(Kr_{st})$$.
!!__Inequality constraints__
Se [ext[here|http://www1.maths.leeds.ac.uk/~cajones/math2640/notes4.pdf]]
[[Langevin description of Brownian motion|http://www.youtube.com/watch?v=dUt2bbGREgQ&index=2&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=67m48s]]
!!Solving the Langevin equation
!!!__Non-inertial regime__
__ with potential__
//Harmonic potential//
[[Fokker-Planck equation]]
__General case__
A system used for [[Communication]]
__Types__
* [[Natural language]] -- [[Natural language processing]]
*[[Formal language]]
__[[Evolution of language]]__
__[[Language learning]]__
[[List of language families |https://www.wikiwand.com/en/List_of_language_families]]
* [[Indo-European languages]]
__Universal grammar theory__
A key flaw in Chomsky’s theories is that when applied to language learning, they stipulate that young children come equipped with the capacity to form sentences using abstract grammatical rules. (The precise ones depend on which version of the theory is invoked.) Yet much research now shows that language acquisition does not take place this way. Rather young children begin by learning simple grammatical patterns; then, gradually, they intuit the rules behind them bit by bit.
The arguments that proponents of universal grammar are putting forth (like making the types of rules more and more vague (principles, like recursion), saying the don't need to all manifest, or saying they are masked by some imperfections in the mind, are signs of a weak theory (it's becoming more like a list of curious facts), or even an unfalsifiable one.
__Usage-based theory__
The theory, which takes a number of forms, proposes that grammatical structure is not innate. Instead grammar is the product of history (the processes that shape how languages are passed from one generation to the next) and human psychology (the set of social and cognitive capacities that allow generations to learn a language in the first place). More important, this theory proposes that language recruits brain systems that may not have evolved specifically for that purpose and so is a different idea to Chomsky’s single-gene mutation for recursion.
Usage-based theories are far from offering a complete account of how language works. Meaningful generalizations that children make from hearing spoken sentences and phrases are not the whole story of how children construct sentences either—there are generalizations that make sense but are not grammatical (for example, “He disappeared the rabbit”). Out of all the possible meaningful yet ungrammatical generalizations children could make, they appear to make very few. The reason seems to be they are sensitive to the fact that the language community to which they belong conforms to a norm and communicates an idea in just “this way.” They strike a delicate balance, though, as the language of children is both creative (“I goed to the shops”) and conformative to grammatical norms (“I went to the shops”). There is much work to be done by usage-based theorists to explain how these forces interact in childhood in a way that exactly explains the path of language development.
http://www.scientificamerican.com/article/evidence-rebuts-chomsky-s-theory-of-language-learning/
http://groups.csail.mit.edu/mac/users/gjs/yip/learning-2col.pdf
The [[Laniakea Supercluster|https://en.wikipedia.org/wiki/Laniakea_Supercluster]] (Laniakea; also called Local Supercluster or Local SCl) is the [[Galaxy supercluster]] that is home to the Milky Way and 100,000 other nearby galaxies.
For integrals of the form:
$$I(x) = \int_a^b f(t) e^{x\phi(t)} dt$$ as $$x\rightarrow \infty$$
Contributions near global maxima of $$\phi(t)$$.
!!__Watson lemma__
Special case, for $$\phi(t) = t$$
!!__Laplace method__
:''1.'' Restrict integral to a small region (of order $$\epsilon$$) around maxima of exponential function $$\phi$$, and confirm we are making an exponentially small error.
:''2.'' Expand $$f(t)$$ and $$\phi(t)$$ in series valid in this region, so we get a series of integrals.
:''3.'' It is then usually easier to evaluate these integrals by extending the limits to infinity (after rescaling), confirming that we are again making an exponentially small error.
:''4.'' Confirm assumptions are self-consistent.
!!__Genera Laplace integral__
Three cases:
__Case 1__ The maximum is at $$t=a$$
$$\phi'(a) \leq 0$$ (since it is maximum), and we assume it is not $$0$$, so $$\phi'(a) < 0$$
$$I(x) \sim -\frac{f(a)e^{x\phi(a)}}{x\phi'(a)}$$
__Case 2__ The maximum is at $$t=b$$
$$I(x) \sim \frac{f(b)e^{x\phi(b)}}{x\phi'(b)}$$
__Case 3__ The maximum is at some $$t=c$$ with $$a<c<b$$.
$$I(x) \sim \frac{\sqrt{2\pi}f(c)e^{x\phi(c)}}{\sqrt{-x\phi''(c)}}$$
[[A trick|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=1h09m10s]] to fix a [[Problem that comes up in Naive Bayes|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=1h02m45s]]
__Components__
Networks often have the largest connected component covering most of the network (often more than 50% or 90%). This is sometimes called the "giant component" <small>(however this is sloppy usage, as the term "giant component" means not precisely the same as "largest component" in network theory).</small>
In directed networks, we can represent the largest strongly connected component, and its in and out components using a "bow tie" diagram
__Shortest paths and the small-world effect__
The ''//small-world effect//'' refers to the finding that the typical distance between nodes in many --perhaps most-- networks is surprisingly small. The "typical distance" usually refers to the "mean geodesic distance". <small>Networks that show this property are dubbed //small-world networks//.</small>
The origin of the term comes from a series of experiments by social psychiatrist Stanley Milgram, the so called "small-world" studies, in the 60s.
Models of networks often show that this distance scales as $$\log{n}$$, where $$n$$ is the size of the network. This is often given as an upper limit for the growth of the distance with $$n$$, so that the network is said to have the //small-world proprety//.
The diameter (the largest geodesic distance) is also found to scale similarly. For scale free networks, however, an interesting structure is often found with a core that contains most nodes, and is of lengthscale $$\log{\log{n}}$$, making the mean distance scale like that too, but there are a few nodes along "streamers" or "tendrils", around the core, whose lengthscale scales $$\log{n}$$, making the diameter scale like that too.
Another interesting effect that is observed, termed //funneling//, is that often it is found that the geodesic path (path(s) with shortest length) between vertex $$j$$ and $$i$$ passes through only a few particularly well-connected neighbours of $$i$$ for most choices of starting point $$j$$. Thus if one follows shortest paths to try to reach $$i$$, one is likely to be "funnelled" through those few or one particular neighbours of $$i$$.
__Degree distributions__
The degree distribution $$p_k$$ is the fraction of nodes in the network that have [[degree|Degree of a vertex (Graph theory)]] $$k$$.
The same information can be given in a //degree sequence//, that is a sequence of the degrees of all the nodes in the network. One can easily see from simple examples, that this information doesn't, however, specify the network structure, in general.
For directed networks, we can define the joint in- and out- degree distribution $$p_{jk}$$, the probability that a vertex has in-degree $$j$$ and out-degree $$k$$. This has been currently rarely been measured in practice though.
__Power laws and [[scale-free networks|Scale-free networks]]__
Often (though definitely not always), real networks show a //power law// degree distribution:
$$p_k=Ck^{-\alpha}$$
where $$\alpha$$ is the exponent. Values $$2<\alpha<3$$ are typical. These are examples of right-skewed distributions. Typically, the power law is only obeyed for the tail of the distribution, but not for small values of $$k$$. And typically it is also not obeyed in the high end, for example, due to some cut-off.
Networks with power-law degree distributions are sometimes called //scale-free networks//.
__Distributions of other centrality measures__
Distributions of the values for nodes for others centrality measures defined in [[Measures and metrics for networks]].
__Centralization__
We can use the distribution of centrality measures to answer the question: "how are the centrality values spread?". High spreads indicate a good centrality measure (or very high centralization, I think), while low spreads indicate a low centrality measure (or descentralization, I think.).
A measure for it is:
$$\mathcal{C} = \frac{\sum_{i=1}^N [C_b(i^*)-C_b(i)]}{\sum_{i=1}^N [\tilde{C}_b(i^*)-\tilde{C}_b(i)]}$$
where in the denominator, $$\tilde{C}_b(i)$$ is the betweeness centrality of node $$i$$, and $$i^*$$ is a node that maximizes it, both for the graph that maximizes $$\tilde{C}_b(i^*)$$ (a star graph for betweeness for example). The $$C_b (i)$$ without the tilde is for the actual graph.
__Dynamical importance (& eigenvalue elasticity)__
* measures changes in eigenvalues of $$A$$ due to some perturbations
* suppose $$G$$ strongly connected.
''Edge dynamical importance'' of $$(i,j)$$ is:
$$I(i,j)=-\frac{\Delta \lambda_{ij}}{\lambda_1}$$
where $$\lambda_1$$ is the largest eigenvalue of A, and $$\Delta \lambda_{ij}$$ is the change in $$\lambda_1$$ from removing edge from $$j$$ to $$i$$ (i.e. removing $$A_{ij}$$).
The ''Node dynamical importance'' of $$(i)$$ is:
$$I(i)=-\frac{\Delta \lambda_{i}}{\lambda_1}$$
where $$\Delta \lambda_{i}$$ is the change in $$\lambda_1$$ from removing node $$i$$ (i.e. removing column and row $$i$$).
One can show that:
$$I(i)\approx \frac{v_i u_i}{v^T u}$$
$$I(i,j)\approx \frac{A_{ij}v_i u_j}{\lambda_1 v^T u}$$
where the approximation is in only considering the changes in eigenvalue and eigenvector to 1st order. See problem sheet 4 answers for proof.
//Structural things related (by spectrum, often) to dynamics// Dynamics of removing nodes and edges he means?
__Clustering coefficients__
(see [[Transitivity (Graph theory)]])
Clustering coefficients, $$C$$ are often found to be larger than one would expect if edges where randomly chosen (for a fixed degree distribution, for example, see formula 8.24 in Newman's).
This is often the case for social networks. One mechanism that can lead to this is //triadic closure// (when an open triad is close, say because the common vertex introduces the other two, in case of social nets). This has indeed been found to happen in cases when time-resolved data for network formation is studied.
In, the Internet networks, however, $$C$$ is much smaller than the predicted value given by chance (eq 8.24 Newman), suggesting there are forces that shy away from creating triangles. However, different models to compare with (i.e. other random graph models), and other ways of measuring clustering coefficients give different results.
Other //motifs// apart from triangles are also measured sometimes and show interesting patterns (like in neural networks).
Local clustering coefficients often show an interesting anti-correlation with degree in real networks. An explanation to this phenomena can be given if the network has a community structure with nodes grouped together in groups of varying sizes. A hierarchical structure has also been proposed to explain this.
__Assortative mixing__
[[Assortative mixing]] is the tendency of nodes to connect to others that are like them in some way. The formula given in [[there|Assortative mixing]] is not very efficient to compute, because of the double sum going like $$n^2$$. There is however a more efficient one that goes like $$m$$, the number of edges, which is often scales slower with $$n$$ (see eq. 8.27 in Newmann book).
Empirically, it is found that most social networks have positive assortativity while most others (technological, biological) have negative assortativity.
Part of the explanation for this seems to be that most networks are naturally dissasortative by degree because they are simple graphs (see [[Mathematics of networks]]) and so the number of connections between high degree nodes is limited, and so if there aren't many high degree nodes, they will have to connect mostly to lower degree nodes (I think this is gist of explanation).
Social networks, on the other hand, seem to overcome this due to their group structure (high clustering coefficient) so that in small groups people of low degree will be mostly connected to people with low degree (i.e. within the small group), and the larger groups will contribute to making people of high degree being mostly connected to people of high degree (i.e. within the large group).
//aka least absolute shrinkage and selection operator//
Like [[Ridge regression]], but using l1 norm, it gives sparse models. It's a form of [[Feature selection]]
Lasso can be optimized by using [[Sub-gradient descent]]
[[Essentially application of PCA to text data|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=5m05s]], where we usually skip the pre-processing step.
We use it for measuring document similarity. Use angle between vectors representing documents.
[[Intuition on applying PCA to text|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=15m10s]]
[[Random variable]]s in a [[Probabilistic model]], which don't model observed data, but which may have some form of significance in the model, as is often the case in [[Generative model]]s.
[[Latex|https://en.wikipedia.org/wiki/Latex]] is a [[colloidal dispersion|Colloid]] of [[polymer|Polymer]] particles in a liquid.
A ''lattice'' is an [[Algebraic structure]] defined as:
|a [[poset|Partially ordered set]] $$L$$ in which every pair of elements posseses a [[join|Join operation]] and a [[meet|Meet operation]]|
A //unit// element in a lattice $$L$$ is an element $$1$$ such that, for all $$a \in L$$, $$a \preceq 1$$. A //null// element in a lattice $$L$$ is an element $$0$$ such that, for all $$a \in L$$, $$0 \preceq a$$.
The lattice is //complete// if a [[Greatest lower bound]] and a [[Least upper bound]] exist for //every// subset $$S$$ of $$L$$ (all that is guaranteed by the definition of a lattice is that these bounds will exist for all //finite// subsets of L). If these exist, they are denoted as $$\wedge S$$, and $$\vee S$$, respectively.
[img[http://i.imgur.com/eB76RuU.png]]
[img[http://i.imgur.com/S2qDCFr.png]]
[img[http://i.imgur.com/imuGxNU.png]]
A [[lattice|Lattice (algebraic structure)]]:
* whose members are all the subsets of a [[Set]] $$X$$, i.e. the elements of the [[Power set]] of $$X$$
* The [[Partial ordering]] is defined as [[Set inclusion]], $$\subseteq$$
[img width=300 [https://upload.wikimedia.org/wikipedia/commons/thumb/e/ea/Hasse_diagram_of_powerset_of_3.svg/640px-Hasse_diagram_of_powerset_of_3.svg.png?1468455817501]]
[[Lattice (algebraic structure)]]
https://en.wikipedia.org/wiki/Law
[[Law - Springer|http://www.springer.com/gp/law]]
[[Portal:Law|https://en.wikipedia.org/wiki/Portal:Law]]
See [[Jurisprudence]]
See [[Statistical mechanics of multispecies systems]]
!!__Local functions__
Apply some nonlinear function $$\sigma$$ to each element of the input vector.
[[Linear layer|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=43m19s]]. Linear function
[[ReLU layer|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=46m20s]]. Rectified linear unit. Very popular. For x=0, may use subderivatives..
[img[http://cs231n.github.io/assets/nn1/relu.jpeg]]
[[maxout unit|http://stats.stackexchange.com/questions/155422/exact-definition-of-maxout]]
!!__Max-pooling__
Compute the maximum of all input vector elements
!!__[[Softmax]]__
Exponentiate all vector elements and normalize them to so sum to unity
[[LC circuits|https://www.youtube.com/watch?v=aU2pyB-49m8&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp#t=1h6m]] (applied to [[Neuronal network]]s).
They are [[Low-pass filter]]s
See [[Machine learning]], [[Human learning]].
[[Learning how to learn|https://kat.cr/learning-how-to-learn-powerful-mental-tools-to-help-you-master-tough-subjects-pis20l-t9786468.html]]
See article on how Elon Musk learns, etc.
http://scholarpedia.org/article/Adaptive_resonance_theory
Learning <==> Education
[[Education - Springer|http://www.springer.com/gp/education-language]]
//aka computational learning theory, statistical learning theory, although these have slightly different connotations//
Mathematical theory of learning, and learning algorithms. See [[Machine learning]], [[Deep learning theory]], [[wiki|https://www.wikiwand.com/en/Computational_learning_theory]].
''Learning problem'': Design a system that improves on its ability to perform task T, as measured by performance measure P, by going through experience E.
!!__Types of learning problem__
Some important types:
* [[Supervised learning]]
* [[Unsupervised learning]]
* [[Reinforcement learning]]
* [[Statistical inference]]
** [[Causal inference]]
* [[Inverse problem]]
** [[Linear inverse problem]]
<b>Most of the topics below apply to [[Supervised learning]], which is the most common learning problem in practice.</b>
!__Principles of learning algorithms__
!!__Risk minimization__
If one defines a [[Loss function]] (or ''risk'', or ''cost'', see [[Decision theory]]), $$R_f (\hat{y}, y)$$, one can ask what is the prediction scheme (for instance, the function $$\hat{y} = f(x)$$ that minimizes the expected risk. This is called risk minimization.
!!!__Generalization/prediction__
[[Making good generalizations is the goal of predictive/supervised learning|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=17m45s]], where ''generalization'' means
making predictions about unseen data from seen data, and good generalization means these predictions agree with the actual results, as often as possible. See also [[Induction]].
For the case of 0-1 loss functions, the expected risk is also known as ''generalization error'', $$\epsilon$$, [[defined as|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=18m10s]] the probability that if I sample a new sample $$(x,y)$$ from the same distribution producing the data, my hypothesis misslabels that example.
!!!__[[Empirical risk minimization]]__
Risk minimization, requires knowing the joint probability distribution $$P(x,y)$$, so one often uses the sample mean of the risk as an estimator for the expected value of the risk. Minimizing this empirical quantity is called empirical risk minimization.
The empirical risk, for a 0-1 loss function is also known as ''training error'' $$\hat{\epsilon}$$, which is just the fraction of training points that your hypothesis missclassifies. See [[Training error (vid)|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=11m]]
!!__[[Maximum likelihood]]__
Minimize the negative log [[likelihood|Likelihood function]] (similar to entropy. More precisely, cross-entropy, or relative entropy), which corresponds to ''maximizing likelihood''.
!!!__[[Maximum a posteriori]] (MAP)__
!!__[[Bayesian expectation|Bayesian statistics]]__
!!__Design factors in machine learning__
[img[machine_learning_design_factors.png]]
!!__[[Overfitting and underfitting]]__
Overfitting and underfitting refer to ways of misstraining a model, i.e., making it have poor generalization error, compared to the optimal model.
[[Bias-variance tradeoff|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=4m1.5s]]
''A lot of the theory below is about dealing with the issues of overfitting and underfitting, so as to train the model as well as possible''.
!__[[Convergence and performance results in learning theory]]__
Mostly about general bounds, that often are pessimistic because they have to include worst cases, but give good intuition of general relations, for instance, between training set size and model complexity.
-->[[Theorem|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=17m15s]]. Let a hypothesis class $$H$$ be given, and let the [[VC dimension]] VC(H) = d. Then w.p. at leat$$1-\delta$$, we have that for all $$h \in H$$
$$|\epsilon(h)-\hat{\epsilon}(h)|\leq O\left(\sqrt{\frac{d}{m}\log{\frac{m}{d}}+\frac{1}{m}\log{\frac{1}{d}}}\right)$$
where $$m$$ is the size of the training set. A corollary is that for ERM, the number of training samples needed for a particular performance is roughly linear on the [[VC dimension]] of the hypothesis class (see [[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=22m]]). ''Sample complexity is upper bounded by VC dimension''.
!__[[Model selection/assessment|Model selection]]__
Model selection algorithms provide methods to automatically choose optimal bias/variance tradeoffs.
* [[Cross-validation]]
* [[Feature selection]]
!__[[Bayesian statistics]]__
!!__[[Regularization]]__
A different way to avoid overfitting, while keeping all parameters in your model.
[[Intro vid|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1m]]
We use the [[Prior distribution]] from [[Bayesian statistics]], to make [[simple|Simplicity]] hypothesis more likely. See [[Simplicity and learning]].
[[Intuition|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=12m]]
--------------------
!__[[Optimization for learning]]__
-------------------
[[Adaptive resonance theory|https://en.wikipedia.org/wiki/Adaptive_resonance_theory]]
The primary intuition behind the ART model is that object identification and recognition generally occur as a result of the interaction of 'top-down' observer expectations with 'bottom-up' sensory information. The model postulates that <b>'top-down' expectations take the form of a memory template or prototype that is then compared with the actual features of an object as detected by the senses</b>. This comparison gives rise to a measure of category belongingness. As long as this difference between sensation and expectation does not exceed a set threshold called the 'vigilance parameter', the sensed object will be considered a member of the expected class. The system thus offers a solution to the 'plasticity/stability' problem, i.e. the problem of acquiring new knowledge without disrupting existing knowledge.
Natural extension of the [[join|Join operation]] of two elements to an arbitrary [[Set]] of elements of a [[poset|Partially ordered set]]
Interpreting the [[Partial ordering]] as "less than or equal", it can be understood as the least point that is greater than or equal to all the points in the set.
[img[http://i.imgur.com/42yTLLV.jpg]]
This has applications in [[Linear regression]], and in [[GPS]]
[[On the Complexity of Finite Sequences|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1055501&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F18%2F22688%2F01055501]]
[[A Universal Algorithm for Sequential Data Compression (LZ77)|http://lanethames.com/dataStore/ECE/InfoTheory/0337ziv.pdf]]
[[Lempel-Ziv algorithms|http://www-math.mit.edu/~shor/PAM/lempel_ziv_notes.pdf]]
[[video|https://www.youtube.com/watch?v=bjDFPuXNf2o]]
---------------
__[[Lempel-Ziv complexity]]__
See also [[Algorithm to compute LZ complexity measure]] for implementation and explanation.
-----------------
[[Elegant Compression in Text (The LZ 77 Method) - Computerphile|https://www.youtube.com/watch?v=goOa3DGezUA]] http://www.data-compression.com/lossless.html
[[The LZ77 Compression Family (Ep 2, Compressor Head)|https://www.youtube.com/watch?v=Jqc418tQDkg]]
__LZW algorithm__
[[Lempel-Ziv-Welch Compression Algorithm - Tutorial|https://www.youtube.com/watch?v=j2HSd3HCpDs]]
[[Complexity]] measure based on [[Lempel-Ziv algorithms]] (in particular on the LZ77). In fact the measure was proposed earlier, in 1976 on [[On the Complexity of Finite Sequences|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1055501&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F18%2F22688%2F01055501]]. It is defined as the number of tokens in the LZ77 algorithm.
[[Algorithm to compute LZ complexity measure]]
See also [[Descriptional complexity]]
[[On the non-randomness of maximum Lempel Ziv complexity sequences of finite size|http://scitation.aip.org/content/aip/journal/chaos/23/2/10.1063/1.4808251]]
!!__Relations with entropy__
[img[http://i.imgur.com/rUUJPW8.png]]
[[Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity|http://www.mitpressjournals.org/doi/abs/10.1162/089976604322860677]] [[pdf|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/lempel_Ziv-neural-spikes.pdf]]
[[Lempel-Ziv Compression|http://web.stanford.edu/class/ee376c/lecturenotes/Chapter1_Lossless.pdf]]
[[Lempel-Ziv |http://www-math.mit.edu/~shor/PAM/lempel_ziv_notes.pdf]]
Or ''universal search'', or Lsearch
See [[Algorithmic information theory]]
Suppose there exists an algorithm, A, that can examine M and x, then print
out p within time T. Levin had a search procedure (Levin search) that, without knowing A
could do the same thing that A did, but in no more time than CT2^L
Here, L is
the length of the shortest description of A, using a suitable reference machine,
and C is a measure of how much slower the
reference machine is than a machine
that implements A directly. An alternative form of this cost of the search is
CT/P. Here P = 2^L is approximately the a priori probability of the algorithm A.
$$T/P$$ is called "conceptual jump soze" by Solomonoff.
<<<
Though Lsearch has been widely described (Lev 73; Sol 84,86,89; Li 93 pp. 410-413) there
has been little application of it to real problem solving. Paul and Solomonoff (Pau 94) discuss
its application to several problems and calculate T/P (Conceptual Jump Size) for solutions
but Schmidhuber (Schm 94) was perhaps the first to actually run a computer program that
used Lsearch to solve problems. While it only solved simple problems in neural net design the
technique used is very general and of much interest. The probabilistic version of Lsearch used
in the program had a serious error in it, but it has been replaced with a more conventional
non-probabilistic Lsearch that seems to work fine
<<<
See [[this vid|https://www.youtube.com/watch?v=wMcRMO9ejeM#t=12m42s]] too.
See [[Universal AI]] for more general techniques, inspired on this.
The problem with Levin search, is that it is only __asymptotically__ optimal, and for [[most problems we care today the $$O(1)$$ constant is very important|https://www.youtube.com/watch?v=mF5-tr7qAF4#t=17m20s]]
http://www.scholarpedia.org/article/Universal_search
If there exists a program $$p\ ,$$ of length $$l(p)\ ,$$
that can solve the problem
in time $$\text{time}(p)\ ,$$ then Universal Search will solve the problem
in a time $$2^{l(p)+1}\text{time}(p)$$ at most. This exponential growth
of computational cost in the algorithmic complexity $$l(p)$$
of the fastest solver makes practical applications of Universal Search problematic:
nonetheless, the algorithm has inspired various others, including
Hutter Search, the Optimal Ordered Problem Solver (OOPS)
and the Gödel Machine.
https://www.libertarianism.org/
https://www.youtube.com/watch?v=RWsx1X8PV_A
Although, there is no consensus definition, ''life'' refers to any or all beings that have a certain level of [[Complexity]] in their [[function|Physiology]], and/or [[behaviour|Ethology]]. They are studied in [[Biology]]
!![[History of life]]
!![[Tree of life]]
!![[Taxonomy]] (classification)
[[Artificial life]]
!![[Planet Earth II (trailer)|https://www.youtube.com/watch?v=c8aFcHFu8QM]]
https://en.wikipedia.org/wiki/List_of_life_sciences
"The life sciences comprise the fields of science that involve the scientific study of living organisms – such as microorganisms, plants, animals, and human beings – as well as related considerations like bioethics. While biology remains the centerpiece of the life sciences, technological advances in molecular biology and biotechnology have led to a burgeoning of specializations and interdisciplinary fields."
[[Life sciences - Springer|http://www.springer.com/gp/life-sciences]]
[[Life sciences - Elsevier|http://www.journals.elsevier.com/life-sciences/]], [[SicenceDirect|http://www.sciencedirect.com/science/journal/00243205]]
----------------
[[Cochrane review|http://www.cochrane.org/evidence]]
Alan Hastings - Population biology
Ben Goldacre-Bad Pharma_ How Drug Companies Mislead Doctors and Harm Patients-Faber & Faber (2012)
[[Five-seconds rule paper|http://www.ncbi.nlm.nih.gov/pubmed/17381737]]
[[Forced movements, tropisms, and animal conduct|https://archive.org/stream/forcedmovementst00loeb#page/28/mode/2up]]
[[Hyaloid canal|https://en.wikipedia.org/wiki/Hyaloid_canal]]
[[Fruit and vegetable consumption and all-cause, cancer and CVD mortality: analysis of Health Survey for England data|http://jech.bmj.com/content/68/9/856.full.pdf+html]]
Singh S., Ernst E. Trick or treatment alternative medicine on trial 2008
[[Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits|http://www.ncbi.nlm.nih.gov/pubmed/22991468]]
[[The mechanistic conception of life - biological essays - Loeb, Jacques, 1859-1924|https://archive.org/details/mechanisticconce1912loeb]]
[[http://www.trickortreatment.com/]]
[[Why dont animals have wheels - Dawkins |http://satdude.com/4don/ebooks/Popular%20Science%20Books%20Collection/Richard%20Dawkins%20Collection/Dawkins%20Articles/Why%20don%E2%80%99t%20animals%20have%20wheels.pdf]]
Lighting or illumination is the deliberate use of light to achieve a practical or aesthetic effect.
https://en.wikipedia.org/wiki/Lighting
[[Likelihood function|https://en.wikipedia.org/wiki/Likelihood_function]], $$\mathcal{L} $$ is defined as
$$\mathcal{L} = \text{P}(\text{data}|\text{theory})$$
I.e. the probability of the data given the theory.
One often considers the log-likelihood, which is just the log of the likelihood.
This function is used in [[Machine learning]] and [[Statistics]], See [[Maximum likelihood]]
See also [[Fisher information matrix]]
https://www.wikiwand.com/en/Limestone
A [[supertask|https://www.youtube.com/watch?v=ffUnNaQTfZE]] refers to an infinite amount of actions in a finite amount of time.
This is analogous to other "super"-things, like __supersolids__ which are solids with a finite volume, but an infinite surface area (like Gabriel's horn, or other ones that don't have to be unbounded in linear size).
[[How To Count Past Infinity|https://www.youtube.com/watch?v=SrU9YDoXE88]]
-------
Another mathematical object defined as a limit are __space-filling curves__, described in [[this video by 3Blue1Brown|https://www.youtube.com/watch?v=DuiryHHTrjU]], that also explains the __usefulness of infinite results in a finite world__. Basically, infinite results are always described as a limit of a sequence of finite results. And these finite results themselves are useful. The concept of infinity is still useful because it allows to understand and summarize these finite results in simple ways.
[[Gaussian discriminant analysis]] where the covariant matrices are the same for all classes, but the means are different. Reduces the number of parameters, which may prevent [[Overfitting]].
The decision boundaries are linear unlike in GDA
See [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides07.pdf]]
The predictivion distribution $$p(y|x)$$ has the form of [[Logistic regression]], i.e. a [[Softmax]] with a linear model. The difference is in the training as we have a prior, which we fit also.
[[Linear filter|https://en.wikipedia.org/wiki/Linear_filter]] is a kind of [[Filter (signal processing)]]
An [[Inverse problem]] where the measurements are [[linearly|Linearity]] related to the quantity to be recovered.
[[Linear Inverse Problems|https://www.ncsu.edu/crsc/events/ugw06/presentations/jlsloan/pres5.pdf]] See [[Learning theory]]
[[Ankur Moitra : Linear Inverse Problems|https://www.youtube.com/watch?v=O2exN1siUOQ]]
!!!__[[Matrix completion]]__
[[intro|https://www.youtube.com/watch?v=O2exN1siUOQ#t=1m22s]]
Fill in the entries in a matrix, given a small number of observed entries.
To tackle this problem, we assume, that the matrix is approximately of low rank. [[This is a way to understand why it may be approximately low rank|https://www.youtube.com/watch?v=O2exN1siUOQ#t=5m00s]]
[[There is a natural non-convex optimization problem to solve this|https://www.youtube.com/watch?v=O2exN1siUOQ#t=7m45s]]
See [[Convex optimization heuristics for linear inverse problems]] for the general theory of this kind of convex [[relaxations|Optimization problem relaxation]]
A ''linear program'' is a type of [[Optimization]] problem where the objective and constraint functions are [[linear|Linearity]].
[[Slides|http://mpawankumar.info/teaching/cdt-optimization/lecture3.pdf]] [[ppt|http://mpawankumar.info/teaching/cdt-optimization/lecture3.pptx]]
!!!__Definition of vertex__
Given a point in the [[Polyhedron]], it is a vertex if
* It solves the linear system defined by a full rank submatrix of the constraint matrix.
* It can't be written as [[Convex combination]] of two other points in the polyhedron.
/ / / / /
Linear programming, best way of solving discrete [[Optimization]] problem.. either exactly (when the solution can be found polynomially), or approximately, when NP-hard. There is a conjecture that is unproved, to show this.
[img[http://i.imgur.com/0SOIR7g.jpg]]
!!__Solution methods__
* Simplex algorithm
* Ellipsoid method
* Interior-point method
Mosek
!!__Applications__
* [[Operations research]]
!!__Duality__
Finding the tightest upper bound using constraints! => Can be formulated as a linear program itself!
[[Max-flow min-cut theorem]] is an example of duality
Lagrangian duality. Reformulation of duality using [[Lagrangian multiplier]]
!!__Integer linear programming (ILP)__
Only integer solutions considered.
[[pdf slides|http://mpawankumar.info/teaching/cdt-optimization/lecture4_1.pdf]] [[ppt|http://mpawankumar.info/teaching/cdt-optimization/lecture4_1.pptx]]
If the vertices are integers, the continuous optimization problem is equivalent to the ILP.
Otherwise, we can approximate with a continuous LP.
Totally unimodular matrix define integer polyhedra. [[http://mpawankumar.info/teaching/cdt-optimization/lecture4_2.pdf]]. [[Incidence matrix]] of digraphs are always TUM.
----------------------
Linear model with absolute loss can be rewritten as a linear problem
Can rewrite inequality with absolute values as two inequalities without absolute values.
An type of [[Reinforcement learning in continuous state space]]
-->using [[Dynamic programming]]
[[intro|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=27m50s]]
[[State transition probabilites|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=30m]]. These matrices can be obtained by [[Linear regression]] from samples of the real or simulated dynamics of the system; or they can be a linearization of a non-linear transition function, derived from physics, or other assumptions. This constitutes the linear model neede for LQR
[[Reward function|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=33m10s]]
Goal: [[Finding optimal policy|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=53m20s]], modelling world as a finite-horizon [[MDP|Markov decision process]], which can be solved recursively, using [[Dynamic programming]]. It turns out that the optimal action is a linear function of the current state, in this case.
The recursive equation for calculating the optimal value function at time $$t$$, given its value at time $$t+1$$ is known as the discrete-time ''Riccati equation''.
[[algorithm|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=1h12m05s]]
[[Advantage over discretization methods|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=1h15m20s]]
[[recap|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=18m50]] --> [[some comments|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=31m30s]], don't need covariance.
__Differential dynamic programming (DDP)__
Turns out to be a form of local search algorithm
[[video|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=35m]]
See [[Regression analysis]].
!!''Least mean squares''
See [[Least-squares]]
Use [[Matrix calculus]] for optimization: leads to ''normal equations'' (analytical solution to least squares), etc.
See [[here|http://cs229.stanford.edu/notes/cs229-notes1.pdf]]
!!!__Probabilitistic interpretation__
See [[here|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=28m40s]]. We assume the errors between model values and actual values follow a [[Normal distribution]]. This implies the data would be distributed as a Gaussian with mean $$\Theta^T x$$, and a certain [[Variance]]. See [[here|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=33m]]. With this we [[define|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=41m20s]] the [[Likelihood function]]. One can then derive that [[maximizing likelihood|Maximum likelihood]] is the same as mimimizing mean squares.
__Doing linear regression in Python with [[Sklearn]]__
[[Regression Intro - Practical Machine Learning Tutorial with Python p.2|https://www.youtube.com/watch?v=JcI5Vnw0b2c&index=2&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
,,[[Regression How it Works - Practical Machine Learning Tutorial with Python p.7|https://www.youtube.com/watch?v=V59bYfIomVk&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=7]],,
-------------------
There exists a [[nonparametric|Nonparametric statistics]] generalization of linear regression: [[Locally-weighted linear regression]]
https://www.wikiwand.com/en/Linear_system
[[4. Linear Response|http://www.damtp.cam.ac.uk/user/tong/kintheory/four.pdf]]
[[LTI system theory]]
A [[Function]] is said to be ''linear'' if it satisfies"
$$f(\alpha x + \beta y) = \alpha f(x) + \beta f(y)$$
for all $$x, y \in \mathbf{R}^n$$ and all $$\alpha, \beta \in \mathbf{R}$$.
https://en.wikipedia.org/wiki/Linguistics
See also: [[Formal language]]
__Sentence diagrams__
https://www.google.es/search?q=sentence+diagram
http://www.german-latin-english.com/diagrams.htm
[img[http://www.german-latin-english.com/dailydiagram34.jpg]]
__[[Evolutionary|Evolution]] linguistics__
[[Novak's book|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Martin%20A.%20Nowak-Evolutionary%20Dynamics_%20Exploring%20the%20Equations%20of%20Life-Belknap%20Press%20of%20Harvard%20University%20Press%20(2006).pdf]]
Linux is an [[OS kernel]]
[[The Linux Documentation Project|http://tldp.org/]]
[img[https://upload.wikimedia.org/wikipedia/commons/a/af/Tux.png]]
!!__Command shell__
__Multi-user__
!!!__Bash language__
[[How do I create a script file for terminal commands?|http://askubuntu.com/questions/223691/how-do-i-create-a-script-file-for-terminal-commands]]
[[BASH Programming - Introduction HOW-TO|http://tldp.org/HOWTO/Bash-Prog-Intro-HOWTO.html#toc7]]
[[Bash script variable declaration - command not found|http://stackoverflow.com/questions/2268104/bash-script-variable-declaration-command-not-found]]
https://www.wikiwand.com/en/Lipid
[[Fat]]
A condensed [[Fluid]] phase of matter, which thus flows under virtually any amount of stress. See [[Condensed matter physics]] for more details.
[img[https://media.giphy.com/media/wyUehgweohXIQ/giphy.gif]]
Liquid water flowing in a stream
Liquid crystals correspond to matter in non-isotropic phases, like the nematic, or smectic phases, but which don't have full crystalline order.
See more in Principles of condensed matter physics book, and de Gennes and Prost, "The physics of liquid crystals". [[Liquid crystal theory|http://www.springer.com/cda/content/document/cda_downloaddocument/9783319008578-c2.pdf?SGWID=0-0-45-1418012-p175260985]]
!!__Landau-de Gennes bulk free energy density__
I think derived following Landau's theory of phase transition, when given an order parameter: including terms that satisfy certain symmetries.
$$F_{\text{bulk}} = A Q_{ij} Q_{ji}/2 + B Q_{ij} Q_{jk} Q_{ki}/3 + C (Q_{ij} Q_{ji})^2/4$$
where the order parameter, for uniaxial LCs, is:
$$Q_{ij} = \frac{3q}{2} \langle n_i n_j - \delta_{ij} /3 \rangle$$
where $$q$$ is a scalar indicating the level of ordering (i.e. the variance of individual molecule's direction from the director field $$\mathbf{n}$$). $$\mathbf{n}$$ is the director (the direction in which the molecules point in average at a given point, where the direction is considered as a ray, i.e. $$\mathbf{n}$$ and $$-\mathbf{n}$$ are physically equivalent.
!!__Generalized elasticity of liquid crystals__
The free energy of distortion (per unit volume) of a liquid crystal has the form:
$$F_d=\frac{1}{2}K_1(\nabla \cdot \mathbf{n})^2+\frac{1}{2}K_2(\mathbf{n}\cdot\nabla \times \mathbf{n})^2+\frac{1}{2}K_3(\mathbf{n}\times (\nabla \times\mathbf{n})^2$$
where $$K_1$$, $$K_2$$, and $$K_3$$ are the elastic constants corresponding to the three types of elastic deformation that alter the long-range order in liquid crystals (and are thus opposed by elastic forces):
*splay
*twist
*bend
[img[distortion_types_liquid_crystal.PNG]]
__Friederik transition__
----------
!!!See [[Complex fluid dynamics]] for the dynamics of liquid crystals
-----------
//People//
P.G. de Gennes (see his book on Physics of liquid crystals)
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iVBORw0KGgoAAAANSUhEUgAAAgUAAAFtCAIAAAAYsY7wAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrsfXdc0+f2f/ZOIBASQgh7JwKyd1FQEURx11Zba/X22j2sre21xT2qdWNdqLUWRFERQUAQVBBk7733JiSQkPXJ74/zu3nlBdba3rb33u/1+cOXQPL5PM95znPG+5znHLRGo0G9HC/Hy/FyvBz/8wPzkgQvx8vxcrwcL8fv1wcajUatVk9NTU1NTWk0GoVC8dLPeDn+vKHRaBAEAWb7Hd9VKpVyufwlGf+MfVEoFP9Ti1Wr1X/sM//YB/6Lk8f9vkcrlcqrV682NjayWCw6nd7a2rpr1y48Hv9/kglUKlVqaurY2NjcuXPNzMz+W6atVquLi4tra2v5fP68efP+gjfK5fI7d+5IJBIMBhMaGsrn84F6t2/flkgks2bN8vT0/H1P7uzsLCwsrKqqmjVrVmRkJIlEevGvIwhy9erV8vLyo0eP/gduk1QqTU5OnpqaioqK0tfX/+86GgMDA9999927775rbW39V763q6srJydHrVavXbv2LxA7Go1mfHy8uLi4sbFxYmJi9erV5ubmf8hja2pqUlNT33nnHT09vT9v8mNjY6WlpQ0NDVKp9NVXX+Xz+X+kf4AgyIMHDy5dusTj8WxsbGQy2YULF/4aLfdvGQiCtLa2Hjx4sLm5+b/ruA4PD588efLGjRt/zRvRaLRMJjt69GhKSgqRSNROo6ys7Pbt22Qy+fetQiKRfPfddxQKxdzc/PLlyxMTE7/1CaOjoz09Pf+Z1q5arS4rKzt48ODIyMh/voEPjppSqYQfJRJJcnLy2NjYXzxtuVx+/fr1gwcPqlSqv0YCJCUllZWVmZubFxQU1NbW/iE012g0/f39sbGxIpHoT5387du3KysrzczMnjx5Ul9f/wf7ByqV6ty5cxqNZv369VQqtbOzMy8v7/+wn4jFYvl8fktLi1Qq/e+atlAoHBsb6+vr+2uUAYFAmDt37tatWx0cHFgslpZbysrKQkJC7O3tfx83P3nyJCEhYceOHVQqlcFg/Fa9gsFglixZEhQU9KsvKi0tHR0dnT9//l+5TUQikcVitbS0aIXsX2noFBcXSySSkJCQF5dld+/etba2FggEKBSKw+Hs3r3bwsLiL565sbGxgYFBS0vLXwBTgz1x7ty5VatWLVy4kEKhPMe+fkGai8Xi0NBQNBrt6Oi4bdu2P88vBKPw3Llzb7zxRnh4OIVCsbS0/OPxIolEMjAwUFdX5+npyePx3nzzTQwGo1Qq7927x+fzXV1dJycns7KyqFRqUFCQXC5vb28fHh5mMpkdHR0YDMbFxYXP54tEosbGRjCRhoaGMBhMYGAgkAZe0d7ePjY2JhQKDQ0N4ZcTExMdHR1tbW3Ozs4cDodEImk0msnJyZKSkvHxcQ6H4+XlhUajdY2vgoKCkZERMzOzWbNmPXr0SCKR2NraOjo6qtXqwsJCPT09JycnoNqTJ08wGIyDg4OVlRUWi9WKOTQaTaFQtMStra0VCATaKY2PjxcUFCiVSm9vbzabDb9RqVRoNNrQ0FCj0YjFYqVSyWAw8Hj86Ohobm4uGo22t7e3sbHRvkVL2KGhofz8fBKJ5Ovry2AwZpIdLAsDAwM0Gj0xMSGXy2k0GpFIVCgUQ0NDZWVlnp6eBgYGBAIBjUZzOByQnhqNpqenp6yszM3NjcvltrW11dTU8Pn82bNng7UikUgYDIZcLpfL5Xg8nsFg6L4Lg8FoNBqNRtPa2lpTU6O7U9NUgpGRER6PRxBEy/2PHj0iEomrVq36Vb8ecKHy8nIMBuPq6gpw0/j4+OPHj8fHx8VisUajWbFihXZ/ARMTiURUKhWFQk1OTqLRaAMDA6lUKpPJUCgUg8EAOhgZGWktMtgOWJdYLFapVGQymUwmFxYW7t6929PT083NDYPB5ObmOjo62tjYDA4OPn361NDQ0NfXF41Gq1Sq8fFxBoMhFouBUHK5vLq6uqenh06nBwYG6i4TQZDa2tqWlhYmkxkQEFBWVtbT08Nms318fBAEqaurk0gk7u7uAH8hCDI4OFhbW+vm5gZbDzQfHh6uqKgwMzPj8/laPuzv76+srEShUEKhkMfjaVGUsrIyNBrt4uIyDdDQaDRTU1N9fX3V1dW2trZmZmZkMjk/P3/Pnj0BAQEuLi7Aq8PDw2VlZVQq1c3NjUKhAAY4MTHBYDCKi4sJBEJXV9f+/fvXr19vYmLCZDLpdPq8efO0sxodHcXj8Wg0uqioiMPh2NnZATUAFoNNIRKJdDp9JtIIbh+VSiWRSEqlUiwWEwgEBoMBs6qqquJwOBYWFlQqFY1Gk8lkDoejPeMpKSk8Hs/NzU0mk92/f59Cobzyyit4PB6mRCKR8Hi8RCKBTVcoFPAuGo2mBR7hkxqNhkql6hocMLeWlpaysrIlS5aMjo76+voSiUSxWIzFYlUqlfZoj4yM5OXl4fF4f39/Lfij0Wi0bp++vj4Gg3n69OmuXbv8/PxcXV0NDQ25XG5ERASNRtP9fFVVlZGRkYWFBfweqKdWqykUCngSenp6M0+TrsycNWuWgYEBbHpzc3NlZeXU1NTY2FhAQIDWcX+2ERkdHf37cMPExMSOjg40Gi0QCNhsNoVCUSqV+/bty87OXrVqlUwmS0hIuHLliq+vb01NzeHDh+/evQtLffjwYWlpqbOzc3Z29qFDh7Kzs8fGxqqqqtLS0jo6Ojw8PIhEYn9//7FjxwgEQnd395UrV0QikaOjo0ajOXPmzOjoqEwmy87OBkU9Ojp648YNBEFaWlrOnz/P5/N1FaBarU5KSjp16pRAILCzs7t3797x48f19fU9PT1VKtV3330nkUg8PT0rKysvXrxIoVBqa2uvXr1qZmamGyfQaDQtLS0///wzmUyuqKh49OhRTk6OpaWlkZFRZ2fn3r17cTjcwMDAtWvX+Hy+kZHR7du3T5w4MTIyAsf+wYMHd+7ccXNza25uPn/+PIVCaWxsvHLlCpfL1TWsEAQpLy8/fPiwoaFhbW1tSkqKQCDQRRVBth48eLC1tdXf3x+FQpWXl589e9bT0xOLxV64cKGnp2dychIcW1tbWxqNplKpzp49a2Bg8Oqrrw4MDHzxxRcajcbb27uvr++HH37IyclZuXKlVCo9efLk5cuX6+vrq6qq7t+/n5qaSiQSr169WlNT89NPP5mamvJ4PFhIW1ubWCxOTEysr6/38PCYieMjCJKRkVFfX79x40Y8Hj8+Ph4dHf23v/3Nzc1NV08/027Kzc1NTEykUCgDAwM///wzi8UyNTVNT0+/detWe3s7m80eHR0VCoXa5yAIEh8ff+LEibKysrq6ury8vPj4eDwef/PmTdhHtVrt5OTU29t7+vTphISElStXajSa0tLSvXv3ZmRkzJ8//9ChQzU1NdbW1jQaLSkpKSYmxtDQ0MnJiUqlfvPNNx0dHfPnzx8dHb148WJiYmJUVBTw2E8//VRXV3f16tXu7m53d/eEhAS5XD46Onrs2DEMBjN79uxpexodHU2j0fz9/UtLSw8cODAyMrJw4UK1Wh0fH//w4cP58+eXlJTcu3ePRCLBf4qLi4VCoZ6eHoIgWVlZaWlpOBzuyZMnGRkZTCaTy+UODAx8//33LBYLjUbHx8fPnz8fvKjr16+DYktMTBQKhUZGRrozuXPnTllZmVqtLi0tHRwcdHR0TExMPHv2LJvNdnR05HA4GRkZcXFxdDr94cOH5eXlgYGBQ0NDBw4ciI+Pr6+vP3/+/OPHjxsaGrKyshQKhZeXl5GR0bFjx+Li4jgcjqmpaU1Nza5dux4/ftza2lpQUHDjxg1DQ0NbW1sQtUeOHMFisZcvX87MzGxoaJDL5brMPzo6+vnnn6enpwcHB1OpVLFYvHPnTi6Xa2Ji8vjx41u3bpFIpMLCwrt379LpdD6fD5QpKCj48ssv0Wj03r17MzMzX331VcCRLl68GBAQwGKxMjIyDhw4UFRU1NjYWFxc/OOPP6rV6oyMjIqKioSEhP7+fk9PT5D4KSkpubm5WVlZJSUls2fPJhAI2rm1trbGxcU9fPgQjABbW9vr169fuXIlNzc3NTU1OTlZKBT29fXt37/fyMiooaEhKSnJyclJX19fJpNlZGQUFRXhcLiYmBixWCwQCG7evPnDDz8YGRk5ODjI5fKEhIQLFy74+fnR6XTYxBs3bpDJ5OLi4uTkZBBxycnJly9fTk9Pr6io+PHHH9PT06lUqq2t7UyZ/P333xOJRK3MdHBwgMk/fvxYT09PLBbb29uD8v4j4wdYLHbp0qVvvfVWWVnZ3r17t2/fLpFIwI6Wy+W5ubkoFIpEIvF4vMLCwuHhYWNj46qqqsHBwblz565YscLZ2TkhISErK8vMzCw3N1elUoWFhS1fvpzD4cTGxpaXl4+Oju7Zs0ehULi4uAQEBNDp9IMHD1ZWVqpUqosXLxIIhDlz5hgbGw8MDCgUijNnzpSVlfH5fCcnp/r6+nPnzunioVgs1svLq66urq6uDovFenp6lpeXg5upVCrb29uFQqFSqTx16hQKhXJwcLCxsblz505MTMwvySxXV9ewsLCEhIS7d+8iCFJWVpaQkODm5jZ37tzk5OTbt2+j0WhTU9OkpKT09HStRKBQKFgs9syZM0ql0tHR0c7O7s6dOydOnJiGI9+/fz89PT0kJMTLy+vSpUvTUDg0Gs1ms3Nycu7cuaNUKjUaTWNjI4IgBALh0qVLjx49cnJyCgkJsbOzi4uLu3bt2rTvslis2traqqoqNBptYmIyNTUFO4VGo0Ui0bVr14aGhuzs7BwdHS9dunTjxg2BQODk5FRcXHz69Gmwc/ft28dkMh0cHDgczoULFyoqKp6JGgkEgu7ubqVSiSBIZmammZnZK6+8gkKhcnNzExISkpKSSktLZ1oYHR0dO3fuFAqFISEh8+bNUygU0dHRXV1d5ubmbDYbjUY7OTlNOwMoFAqPx8fHx1dXV9vY2AgEgqysrDNnzpibmwsEgr6+vkOHDoG7U15enpmZCdPjcDhisTg+Pr6urk6rdDEYDLiJRkZGJiYmNBqtr6+vuLgYLEoymZybmyuXy0kkUmlp6bVr12g0mqmpqb6+/u3bt5OTkzkcjr29/eTk5Pfff68LKmIwGHt7+/Hx8dLSUgwGIxQKe3p6amtrVSoVLNnBwUGr3nA43OzZswMDAy9evJiXl4cgyMOHD48dOyYUCgMDAz08PJ4+fXr8+PGpqamSkpLbt29bWVn5+PgQCAQwDI8ePWpgYODg4GBiYpKYmHjp0qVp3HX9+vWhoSEA7vr6+oCkGo2GzWZzuVy1Wh0bG9vX1xcYGGhsbHz69OmGhgYcDjc6OhofHy8Wi+fOnSsUCoVCIQqFcnd3Z7PZAAZeuXKlo6MDTPukpKSsrCwbG5uIiIiRkZHDhw/DEbh06RJsJY/H+/HHHxMTE6c5l2QyeXh4OC4ubnBwEIVCiUSihoYGDofz9OnT7777zsHBwc/Pz8vLq6qq6siRI9MCSGg0WqFQPHr0CJwPU1PTwsJCeI6enl5cXNyTJ08sLS0FAkFZWdnx48cNDQ2FQuHU1NSxY8f6+/sRBDl79uzQ0JBAIOBwODExMTdv3tR9vp6enq2tLRqN5vF4QqGQQqHQ6fSLFy8WFxe7uLiQyWQajQY2X0hISGBg4KVLl3JycjQaTUFBwZUrV+zt7cEjP3nyJABECIKw2WwTExMCgdDc3BwfHy+RSABHOnDggJ2dnZ+fn6enZ21t7ffffz8xMcFkMuPi4rKysszNzT08PAoKCg4dOjQzYrxr1y6VSuXq6hoYGEin0/fv319VVcVkMm1sbEAoCYXCX8Vaf48+QKPRNjY2X3zxxWeffaZSqWJiYnbt2qVWq8GPgw/gcDgDAwPtkWAwGDweLzw8fN68eevWrWOxWGAyY7FYgUAQGho6b968TZs2TU1NpaamZmVlXbt27a233rKxsbG3t3/jjTfq6uouXLgAcaQ7d+7U19evWLHC3d1dLBafPXtWKpUWFBTU19e7urrK5fLx8XHdqbq4uLi4uKSlpWk0GhsbGwRBCgsLgedoNJqvr29fX9+dO3cUCkVBQUF3d7ePj88vacFXXnllxYoVkZGRcJiBDh9//LG1tXVTU5NMJmtvb8dgMJ6enuHh4fX19UNDQ3K5vK2tLSoqSiQSJSUlKRSK/Pz89vZ2X19fDAYzDeb28PD49NNPyWRyc3OzTCbr7u6eRnYnJ6fVq1d3dnZ2dXUhCFJVVbVixYqhoaFTp055eHh4eHjw+fyVK1cSicTLly/39/frfpdEIsEb0Wi01ikG0N/R0RGDwYSEhCxcuHDx4sWQPbxq1aoFCxaYmpqWlpYiCJKSktLc3FxbW/v06VMSiWRnZ9fa2vpM3rC0tNRoNJWVlX19fXFxcRs2bCCRSC0tLeCpGBkZxcbGTlMJoAvz8vLmz59vampqa2v7xhtvPHr0KCsry9nZ2cLCAoPBBAcHu7u76zoZaDTa2dkZjUZ7eHhEREREREQwmcyxsbGVK1eGhITMmjWrqqpKpVIxmUyt9EGj0VZWVlu2bOFyuTt27IiIiFi4cKGenh5sJRqNNjMz4/F4BAIBLESgG+AbcKjYbDYWi123bt0nn3yyZMmSc+fOicXioqKiwsJCBwcHQ0PD9vZ23aXxeLx58+aVlJT09/ebmJiQyeTGxkaRSKTRaNrb27XwFxaLjYiIiIqKWrhwoUwm6+npUalUR48exWAwYWFhpqamwcHBAoEgNTW1qKjIwMBgYGDg7NmzfX19b7/9NlgGmZmZk5OTBQUFIpHI19d3Zn6tUql8+PDho0ePQkJCwsLCMBiMtbU1Go0GMY3FYgMCAt58800jIyO5XD4wMNDd3c1gMFxdXTEYzMKFCz/88MOPPvrI2dkZ9oLL5aLRaC8vLwDfQFzi8XgrK6vw8HDQOiUlJaCrLl26RKVS7e3t165da2RkpFarQa9oN4VGo7377rtUKjU3NxeYJzg42NTU9NSpU5OTk5GRkaampgEBAR4eHvfv33/8+PE0lgObV1fs6LKHQCBYtGjR/PnzzczMent7ly9fPm/ePE9Pz9bW1tHR0ZaWlhMnTuTl5RUVFXV2dvb394Oo0T6Ew+H4+Pig0WgHB4e5c+dSqVQ/Pz+5XO7q6vr2229v3brVxMTEzc3tiy++oFKpTU1NU1NT3d3doGYcHBwCAgLMzMw++OCDsLAwLZsBzTkcDmB9oDVPnz49Pj6+ePFiHo/n7+/v5eX14MGDR48egRNjZWW1cuXKzZs3u7i4TDs+Go0mMzPz559/fvvtt62trUFm1tfXx8bGaifv6Og4Z86c5zsHv0cfACYlEomsrKzefvvtffv2CYXCGzduTNukZ0oKGIDGDA8Pa+Ug/Ovq6kqlUgcHB0tLSycnJ8Hbhc8LhULA5r788suqqqro6Ojz588bGBjI5fK+vr5XXnnFxcXFzc3t008//eijj3R1IBqNxuPxixYtqq6ubmhoyMzMNDAwqK2tffTo0b179xYsWIDH40tLS8G3cnV19fX13b1790cfffTMJRgaGmKxWAwGA2cYjUbb2tqam5unp6cTCASttCUQCBs3bpRKpbdu3aqsrDQwMODxeJWVlcPDw/b29q6urt7e3rt37/7ss8+m6QM3NzcqlZqenv7M+BKsZe3atWQyOS4urr29XSqVCgSC3t7elpYWIyMjIC+VSp07d25jY+PAwMCLR1wh2oHBYOD/BgYGOBwOHoggCAgvBwcHFxcXV1fXiIiIXbt2eXl5PfNRbm5uCILk5OTExcUFBwc7ODggCJKWltbb2wt2rlgsvnv37jSmamtr02g0WmaYNWsWgiBtbW3P5yjtbLFYrHb5wPQQ83jmtzw8PJYvX56eng6a5jeFpuGNRkZGHA5HX1+/vb3dy8vLxcVl9uzZGzdu3LFjh1YewbuwWOyiRYsGBwfz8vIqKiqkUqlYLL5582ZeXp69vb0WBEehUCwWC56vFRCPHz+GX4KkCw8PHx8fr66uFgqFr732Wlpa2rZt2xITEyUSSUFBgVQqhd0JCQnZvXv3W2+9Nc2a2bx589TU1N69e/ft2zctNAVLCw8Pr6uru3nzpha2hvnD3PT19U1MTHTPLPg0056jp6cHv8RgMBBGwmKxRkZGRUVFU1NTVCqVTqcvWLBgWuQMjUb7+/sHBgbGx8cPDg7ev38/PDwcKMBkMoEVgZITExNlZWUvvl/g4cETMBgMkUgEDFYbEuvs7BSJRAsWLLCzs/Px8Tl58uTGjRuf/1hYIETpbGxsACRkMpkpKSlagBfwTxcXF9i+oKCgv//979OWjMVitXSAxUJgAP4UERExMTFRWloKvM1gMIhEIh6PZzKZ2vic9rslJSWTk5PgtKFQKAsLC6FQ+Ksy+Q+IJ0NQMSUlZevWrUwmc/HixVKpdMOGDQ0NDX5+fi/yBKVSKZPJZn54YmICQRBvb+/x8XEEQYqKisLCwoCfaDQaHJXAwEAMBpOSkhIbG0ulUpctWwYx2PXr12uju9OkABaLDQ8PP3369L59+5RK5a5du86ePbtnzx4cDgc+tdZACw4OBuJ2dHSIRKJfDfqr1erbt29fvXr1ww8/dHV11YLpYOnb2dmdOXPGycnp9ddfh6gmvEv7lq6urtHRURAfkKd/4cKFgoKCrVu3/lIyMhqNBq4F8BocQwqFgsPhioqKgAjAOiQS6Tcl6b/Ivnd3d4PzC0mHz0xbQqPRXC4XQZAbN244OTmdOnUKj8crFIo7d+5QqVQikahUKg0MDFJSUr7++mtdoQDns6+vD0QVKPXfJKxffExNTeHxeB6Pl5CQEBYWphVzv48sXV1dfn5+gNuoVCqtoaNdl6enp0AgOHPmjKmp6d///vfi4uKTJ0+amZnt3Lnz+dpOT08PfFnttqLRaH19/YmJiU8++cTFxSUpKenYsWNWVlbAXWQyWctdjY2NUqlUaw9CosRXX311+/btGzduTE5O6t7G0Gg0IpHo/PnzeDweMJA/kNoUCuXTTz/dtGnTnj176HS6n5/fG2+8MXOxdDp9xYoV77777r59+6ampgBJ09fXLy8vVygUJBIJKIBCoZhM5h+buqpSqdzc3Ozs7LTn+remDMXGxj548GDbtm1aex+FQslksoqKiqVLl4KNaGBgME2Oz9zuqqoq0JrwIxqNfpHFwsc0Gk1hYSFkx2GxWCqVOlNb/7oG/R1gEZ1Ov3v3bnl5OVhk5ubm2q0C+ra1tSkUCl01rtFoZDKZXC4HhTw8PPzaa6/BnwDegWw/FosVHh7u7e2Nx+MB8EWhUFKptLm5efXq1QiCPH36dOXKlV999VVgYGBGRgaJRDIxMfnpp58KCgp6e3tra2vPnDkzLZ8afDQ/P7+kpCQWi7V27dqFCxdC9gibzdZa5adPn87NzZ2cnMzLy0tKSnqRSy4qlerSpUtaiEnLRkCitWvXVldXDw0NeXl5gcGrp6d39uzZR48eTU5O5ufnJyYm6oatFArFiRMn1Gq1h4fHLyW2Anzx2muv9fX1VVZWhoSEgP9kaWmZn58PGRQIglRUVAQFBemypm5gXKlUgpv8mzbd1ta2qanp8uXLTU1N3d3dqampWlE1bQCK3dvb++qrr2q1XWdnp+406uvrddU2BoMJCgoikUjZ2dnwgcbGRhqNBoGHP3ao1erExEQjI6Po6Oi6urqLFy8+8+qyRqMZHBwcHR2dmJj4pXxzNBptbW2dlpaWkZHR09NTX1//ww8/zES3mUxmVFRUbm5uX1/f3/72t5UrV0JanZOT0/Nt2+Dg4NbW1qamJm0gysLCwsvLq7y8vLe3d/369du3b9doNHl5ed7e3kQi8dChQ0VFRZOTk9nZ2Q8ePNBVt2B+Lliw4Msvv1y7dm1SUtJMrXbx4kVDQ0M/Pz+xWPxLs6LRaFgsVheSfRFUwMjIyNXV1cXFRSAQbN68+Zn5qYBYmpqaxsXFLV26FEyo4ODgrq6uuro6WEJZWRmPx3tm6rBSqWxpaVEoFDOjU88fVCp1amrq7NmzIKxlMll8fPxv5agTJ05MTU15e3tDDpVW7Fy7di0/Px9yIGNiYp5zUQONRs+ZM6enp6empkYrD7lcLij4XyUyRJLu378Pv5mcnGxqanr11Vf/dP8AoppyufzgwYMAI968eXPx4sW+vr5YLHbu3LlpaWnR0dF2dnbt7e0UCiUnJ8fd3R28ikOHDjk5OeXk5GzcuNHZ2VmlUgGaHxMTo6enl5OT89lnn/H5fDqd/u6772ZnZ9+8edPd3f3u3bseHh5RUVEqlerq1at8Pt/c3FxfX9/FxQVgx8OHD3/11VdmZmb6+vqWlpba5C3thIlE4ttvv11QULBy5UoKhbJ06dK4uLg1a9bAX01MTD7//PMTJ058/fXXs2fPHh8fX7FiBaQwov55Aae9vR0wE7Va3dnZqVQqIWSKxWL7+vp2797NZDKNjY3Ly8svXrz41ltvYbHY+fPns9nsefPmgUw0NjbesmXLkSNH/vGPf7i5uYlEoqioqGlTxWAwtbW10dHROByOzWbfv3/f0dFx0aJF0z7j7+9vbW3t5+dnYmICaMmWLVu+++67ixcvRkZGlpeXi0Sibdu2USiUtra2yclJlUoll8uxWGxkZGRycnJ0dDSdTpdKpRgM5tGjR97e3h0dHbA6X19fwG26urog5294eHhiYmJ4eDgsLOzWrVuxsbH5+flGRkY8Hm/p0qXPZA8ajWZlZbVo0aIFCxboBkunBbenLcrX1/f9999PSEhgMplUKvXevXsfffSRj4+PTCbr7OwETebs7DxNxsFsOzs7VSrV0NCQRCIhEonj4+N4PL6rqwtgKCsrq+7ubpVKVVRU5ObmVlJSEhcXB3k1mZmZsbGxfn5+/v7+RCKRw+Gkp6cjCPLRRx9FRkYePnz422+/5fF4w8PDFAolMzNz8eLF3d3dGo2mubnZ0tLTRnyxAAAgAElEQVQSi8W+8847W7Zs2b17t42NDZlMNjMz04WAtKuLjIz88ccfV69ebWBgEBgYOGvWrGXLlkG2tEqlAvq3tbXBqYEVaTSaTZs2tba2njx58u23356YmMjLy/vggw/MzMwKCgpycnIA32OxWN7e3g4ODh9++OG5c+e2bdvm7OwskUjeeOMN3cxCtVqdnp5OoVCCgoIoFMrChQvBnzAyMkpJSZHJZBEREQiC3Lp1a3x8XCqVar1niBW3tbU5OTnhcDhHR0c9Pb1z5851dHSsW7cOAL329nZIZpXL5f39/TKZDLxJtVrd29vLZrNv3LgxMjJSXl6OQqEKCgrCwsJAXEzjHGNj44ULF2ZkZIAdgMFg3nzzzZqampiYmM2bN0Nq0HvvvWdnZyeTybq6usBYJBKJISEhKSkp0dHRDg4ObW1tVCo1JycnICBAl5klEsng4ODk5OTAwAAkvsPM3dzcZs2aFRcXh8PhTExM+vv7dYEBSDxpbW2FkOHU1BSBQIBVd3Z2ymQy8KWwWGxTU9O3334LeTQPHjwQCATvvffe559//s0333h5eanVagKBQCQSSSQSm81OTU2Vy+XvvfeeduttbGzWrl1bWVn5ww8/YLFYjUaTnp7+7rvv2tvb9/b2Tk1N9ff3g5kIhO3o6NCmFKPRaFdX1/fffz8rKwtkZnJyspeXV1RU1LTJ/ypm8HvyTUG6WVhYSCQStVoNRreDgwMGg+HxeHp6ehqNxsXFxd/fPyAgwMnJic/nQ17QmjVreDyegYHB0qVL6XS6Uqk8ePCgs7NzREQEm802NzcPDw8Hkjk4ODAYDFg/giBLly6F20yQlTwxMUGlUiMjI/X19a2trc3MzFQqlZGRUVBQUEhIyEwPC4S+lZUVZCUbGBjo6+uHhISAE4DBYBwdHa2srORyOYPBCAkJmTt3rq7lrlKp6urqTExMzM3NnZycmpubCQSCnZ2dUCi0trbGYDB0Ot3T09PX1xePx3t6elpZWcFhw+FwERERIPvgLTY2NlNTUzQaDbJodN8CUpJEIhkaGnp5ebm6utJoNC8vLy6XO/PaF5FIDA4OhqRYsFL5fD7kRItEojlz5sCJKisrIxAITk5ONjY2+vr6tra2OByOSqV6eHgEBAQEBwfb2NjQ6fTGxkZIb4ccLchmg7tsYrHYwcHBzs4OLkzQaDQCgeDs7DxnzhzARp/JHng8PjIyUotmajSa8vJyqVS6Zs0ayBTkcrlLlizRagttWJtMJk9MTCiVSltb2xUrVujr67e2to6NjdnZ2XE4HBMTE10ZB9f9DQ0NraysIKFIqVTa29vb29tjMBhAt8zMzOh0+sDAgKOjI5/P5/P5JSUlFAolKioK8sfhOhiPx6PT6QYGBng83t7e3tnZ2dramkAg4HA4Ly8vPz+/V155xdbWlkwm9/X1OTg4sNlsCDubmZlZW1urVCoajRYUFDRv3rxnok9MJtPa2jokJIRKpVKpVD09vblz54JLLZVK29raLC0t+Xy+vb19TU0NcLVQKLSwsLCxsYGArUgkEggEkKtOoVAMDQ2npqZGR0d9fHwWLFigp6fn6OhoamqqUqkMDQ1DQkKCgoKmCdyJiQk8Hi+TyRQKxYoVKwwNDQGMxuFwDg4Onp6eADOamppCBj2DwQDMwcLCwsTExMTEBCaPxWIJBAL8srOz09jY2NzcnMvlDg4OAp7p5OSkUCj6+/udnJw8PDwYDMbp06cZDIaBgUFeXl57e3tXVxeFQnlmiQsmk2lubg7p1CgUis1m29rawiVksVhsY2OzePFiBoPR0tIyNjZmb29vbW3N5XJB7CAIAhmJgYGBAoHA0tKyrq6OQqEAM4tEovHxccghpNPpLS0tQHMPDw8TE5OxsbGamhqVSuXk5BQWFqZrr4yNjTU2NrLZbEtLSxMTE319/draWjqdbmNjw+Vy4R6SkZERkUg0MDCA+ysUCsXHx8fPzw/uCREIBEtLy8jISBMTE5A/OBzO3t5eX19/cHDQysqKz+c7OjoaGRnZ2toCzCCRSKysrJYsWcJgMJqbm6cR1tHR0dLS0tTUVNfkdXR0pNPp4KAgCLJs2TJbW9uxsbGmpiY2m21hYcHlcn8VfUL/7gt+CIL09PQgCKKvr697/2J8fHx8fJzH42lNwqmpqYCAAD09vaysLN0nSKVSFou1cePG48ePz/TWwdYAJAqWAffRJiYmFAoFnF6tAu/t7SUQCC8IBIP7pmubgxPQ1dWFw+G0VJ72J20SxfDw8NTUFBjmFAoFvsXj8ZRKZV9fH5/PBykJ92j09fW10JM2foXBYGbWQYJA/cDAAJlMZrPZUqlUJBLNxHy0aC+JRNLFeWE71Go1IOPad2mhSX19fUhS1mg0Wh0D9inUcoD8GcjiBeWkUCgAGaDRaCwWC1YEu6b1n545PalUSiaTp4VG9+7de+XKFQqF8sYbb7z77ruhoaEzv6hQKCAVksvlAiI/ODgILA724zR9ALYSJIEAb0BIk0AgDA0NoVAoAoFAp9PhThCZTDYwMOjp6dGSqL+/Xy6Xw2IpFIpUKh0eHmaz2WQyGW4GSaVS7U4B+8GjtDPUgi0ajUa79S/Oflo+BxvT1NRUd0XgQAwPD8NVO90zBbEWpVKpOw2gHpFInGZDaCcP175IJJKxsbF2JiMjIxwOB+5YjY2NAavANHSfwGKxaDQa8N74+DiTycRgMNrLVnp6egqFAnYKhCD8Ca5ef/vtt19++SWHw2lqalKr1RUVFWq1+uuvv37mqZdKpboxebi+ABntM7kCTj1cM4TzMo1EWmZWKpVwmYtGo9HpdIh+YTAYPp+vUqnq6+t7e3vhdqpusB2YGXgJhUKB2Ont7QUlTaFQ4AoqUJ5EInE4HJlMNjo6ampqqsswQD3tA4eHh3U5FiogaDNHxWKxltshPgqWsS7NtZs4U2bCdkBEYXJyUhvQApX8Z+mD33TbOyAggMFg5OTkaEUYHGZbW9vly5dfvXoV9XL83x1wBu7cucPhcAgEQlNT08qVK6dhZS/H/8mhVqvPnj17+vTpb7/9FjQr5J4BePCSPv9p43fiRb9JFjQ1NfX19ZmamhoaGmoxL8iRkkqlfD7f2Nh4Jur6cvyfGZApa2NjA2iVt7f3S2XwvzOgnkdpaWlVVVV1dbWxsbGNjY2Pj880OOvl+I84qn+Bf9Df3z88PAwgl/aKKaR1TkxMAJrxr5SIejlejpfjP9Y1lMvlULgJUA4XFxcTE5OXyuB/VB+8HC/Hy/FyvBz/FeNlv8yX4+V4OV6Ol+OlPng5Xo6X4+V4Of45nnEfTa1WFxUVPbOsG4IgnZ2dDQ0N/v7+Lx4ShMvJv1pK6Tlfh9tGWCy2tLR0GsAFRfQCAgJ+x+XsXx1wKXRwcNDZ2flfqWrw3zsQBGloaOjs7ISOmz09PdXV1Ww2283NTaVSjYyMVFRUzJs3708qLPFnD2Ct5ubm9vZ2a2trW1vbqampsrIysVjs4+Pzr3QpgVQ/FApFoVD+GuJAFmZZWVlgYOBzsoF/0wPVavXTp0/5fP6/sU0sTKOtrW1wcBCK4f+VvPFnN+OELPOOjg59ff1p+aO60xCJRD09Pa6urn+1fwCZvCdPnnxmWzUoJHDo0KHn3Gif+ZW+vr6vvvrqd9Oru7s7ISEBh8MRCIS6urro6OjTp08P/HNUVVXt3r37+U3gfvdQq9VPnjzZuXNndXX1/6a9oNFooMyyWq2G5kL79u37+eefUSjU2NjYjRs3du7c+V/dKnVycvLBgwc7duyAUhm9vb0//fTTzp07X6S/5nOUaHV19ZYtWz744APQCn/2UKvVycnJ9+/fLy8v/+KLL7T58v/iGB4e3rNnz2+tAPGHWyTnzp0rLS1NTk7evXv3X8b20DbjT+2fCrL+7Nmzn3/++S9JMKib/emnn/41XW8xz5SAaWlpqampMz8N1+RWrVo1sz7ic7azsLAQCrb8DnpJpdJjx47BpT4GgwEV+Xt7e+f8cyxYsEAgEEwrIvZHDSjOUVJSMjo6+r+pD9Bo9OzZs1etWgW1GKGgAlTUgWoHJSUl/9ULJBKJQqEQmAqFQunp6bFYLKgW+a8QjcFgQLnvZxZH+sPFSk9Pz4EDBywtLRcsWAB3Ev8VYxz2F5ybJUuWwH37f5cygG6pzs7OPj4+v8PTAhP2d7w3IyPj6NGjz2zy8ceeLywWm5aW9kuljaD60717935TwbE/TB9A0Sg6nZ6enq6tzaQ7OXNz83Xr1r04WKRWq4uLi5/ftPM53719+3ZLS0tISAhUrIVrCiQSyeKfY9asWR9//LGDg8OftFtaJw5BkObm5r++3/q/XR/MmjVrzZo1UF/WwcFBW2ueSqX+SWT/K1dHIpGgFTDqn7Xn/nXxB/VRdEv8/9lCEzwDJycnFxeXjz/++MXNtZmPunPnzo8//oj6Z1nGN99809HR8d+oD65cuQJ1JkJDQzds2PBbv15WVrZr167fqkLGx8cvX77c0dFx/vz5P5X94Ew9/zNWVlZ/GUqGm0YIKIy3atWqixcvtre367IC3KV+/Phxdnb2l19+yWazq6urKyoqDA0Nc3Jy9uzZo2uVwKPS0tJaWlqSkpKMjIxOnjy5YsWKZ2Jkz0HWjh49+vrrr0ORkJlDpVKlp6f7+fmNj49fuHChvLxcKBRWVVXZ29u/9957TU1NmZmZY2NjCIIEBwcHBgZCIZ2ff/4ZqppAV2doJg4mobm5+QcffDCTq/Ly8mprazs6OgwNDT/44ANLS0sIpaSlpUEZtbCwsKCgoM7OzqysrMrKSpiGo6Pj5s2bGxsbnzx50tvbK5PJNm/ePK0eBvTRrampaWpqsrOzc3d3t7S0nJiYAHacPXt2fn4+CoXy9PRcs2aNlsIQ2IiNjdXT09u5c+eTJ0/i4+NZLNaOHTugL3RaWtqWLVuoVGppaenjx4/hBnxkZKS2myM0KtmxY4dGo3n33XdpNNqBAwcQBIGSgmKxePv27Zs3b2axWKmpqaWlpYcPH37BCA2CIPX19Q8ePBCJRAwGY/ny5dBus7m5+caNG3Z2dqOjo8uWLTM0NFSr1Xfu3BkbG4O6C4sWLbp3715GRsZHH31kYWGRlJT06NGjOXPmLF68uL+//+LFi319fX5+fl1dXYODgzweb+7cudAqFabNYrGgwt3jx4+7u7snJibeeecdXUMEaj/cuXOnr68Pj8eHhYW5uLi8ICsODg7u379frVZv2bKFz+ePjY19//33ISEhwcHBUqn0/v373d3dUILJ3d2dQqFoOwegUCilUvnNN9/o6+tv3bp1cnLywIEDU1NTn3zyCZfLHRoaevjwIYfDYbFYlZWVUHQdSr+BpHB2dgab/cmTJwUFBRKJhMfjbdiwQVv5Curs3717V6FQ3Lp1i81me3l5xcXF5efnz5o1q7KyksViffvtt9qvW1lZrVq1CgpyDA4O3rlzZ2BgQCaTWVtbv/7667m5ubt378ZisSEhIc7OzqOjoyUlJXw+38/PD8CNnJyc7u5usVhsbW0NRWgmJiaKiopEIpGNjU1qaqpCoVi8eLGrqytUtjhz5oxAIGhpaVmwYIFWmIBw6OjoaGhosLGxqaurMzMz8/b2rq6uLiwshCITH3zwAYvFun37dl5e3uTkZEJCgpmZGdQ3TElJqa+vl0gkNjY2q1evxmAwXV1dtbW1UP2Jx+PBzWeAmrdt21ZYWJiRkWFnZ2dubt7f35+cnDw4OAhFdLRFzKZtd05ODpvN9vb2Tk5O/vDDD7UWw3N4vrKy8uHDh2Kx2NDQcNWqVYaGhuPj4/n5+dANDXrQLlu2DKpqazSa6urqnJwckUj0TCwacPubN2/29PRIpVIoG6Pt3w59vIeHh/38/Hg8Xn19fXV1dWNjo42NjYeHh5WVlVqtHhgYKCwstLOzq62tRRCEwWCEhob+quOImalO+Xz+unXrRCIRIKrT9EFeXl5sbKxIJFKpVKdPn5ZKpVwud2xsTBdEBomwc+fOpqYmKpXa39+/fPny0tLS3bt3Dw8PAyPm5eU9v2ouVHytqanx9fWd9qfe3t67d+/u27dv//79R44ckUqlKpXq/v37sbGx/f39UEelubn5+PHjTCbT2dkZOm5mZGSgUCgcDhcfH3/t2jUEQQQCAcwKOhdCxWmts6y78P7+fjMzM39/f20rSpVKdfjwYRKJJBQK6+vro6OjW1patNMYHByUy+XQzPrq1auWlpZOTk5JSUk7duyYtsaamppTp07p6ekJBIK8vDxAEhEEaWpqOnv2bEFBAZPJbG9v/+6773T7naFQKAaDce/evYcPH0KZ+EePHkGdXrgQXlxcjMPh2tvbL1y4YG5ubm9vf/fu3f379+vSHIPBtLe3x8XFQfHFwcHBixcvQnUUmUx28+ZNLBY7NDQERUCfU7p9Gq1GR0e//fbbrq4uoVCYlZW1a9cu0D3ffvutvr6+mZlZX18fVAktLCy8cuUKVG2D8uYajebChQvQFJ7H492+ffvOnTsoFIpAIDx58uTChQu9vb1Q4u3IkSNJSUkWFhaWlpYXLlyA/nednZ2xsbHQLzMjIyM6OlrXn4Mtu3///qxZs3p6er755psXDxLg8fjKysrY2Fjw66VSaX5+vrGxsUwmO3HiRFtbG9Rz3Lt377lz52bSpLa2FpqwAux29uxZaNpaWVm5e/fu7du3Z2VlSaXSmJiY7du3x8fHS6XS1NTUgwcPQlOQpKSkuro6oVDIYDCOHj1669ataVwEuwPxTygLf+HChYaGBgwGIxaLq6urofSmra1tbGws9P+C/uGjo6POzs5kMvm77767d+8enU6HAqssFguHw129enXv3r0AbWs0mps3b6anp0NZt/Pnz2/btg1BELFYfPXq1V27dt2+fZtIJBYUFOzfv18sFiMIcvLkyf7+fj6fT6PRdKujazSaurq6vXv37tq16/z585cvX37y5ElVVdWNGzdsbW3t7e2vXbt28OBBQAigEhdUHkQQJCEhob6+Xnuor1+/3tTUtH//fuhrcuXKFd0mMCQSqb+/H1re02i0wcFB6DTp7Oxsbm5+6tSpK1euPBPTv3Xr1rp16zZv3iwSiVJSUl4k2PDNN9+IRCI45vCWsbGxs2fPRkdHQ52e9PT0I0eOQM3/qqqqU6dOcblcZ2fnZxabGh8fP3TokEQicXFxsbOzA6AMUKyvv/56+/btKSkpx48fHxoaqq+vP378OJ1OFwqFT58+/eyzz2pra6VS6alTp3bu3Llv374HDx5kZWVFR0dPa6H66/pAqVTevHlz5cqVVlZWnp6eEDbU9VyYTKaenh4071Wr1SUlJePj4+bm5oAn6Gq2nTt3FhYWLliwgMvlcrnc1157zd/fPz4+vqqq6unTp2fOnKmurj5y5Ai0qP0lKtfW1mo0mmk1+aB6VEtLy8jICJSnR6FQbDabRqMhCLJy5crPPvts2bJlly5dam5ujoiIiIyMXLVq1cjIyNGjR0Uikbm5OYFAMDY2DgsLW7Rokb29fVVV1bx585YtWwbF1me2gcRgMF5eXqtXr161ahXMSq1WP378OCUlZWxsDMzbp0+fgoCAaaxateqzzz6LiooCUdXe3g5y5MaNG83Nzbq7vnPnTjKZ7O/vHxkZuXTp0qKioh9++AGHwwkEgqmpKXd393feecfX17e5uRnaG2inxOfz/f39e3t7pVKpjY2NmZmZWCyGCoOtra1r1qzB4XDXr18vLS0dHh4Wi8Xj4+MZGRnabo4AlURFRUF7Pzqd7u3tLZfLm5ubwcoODQ01MzMzMjKiUChQvevFnXRohRYeHo5Go0F4TU1N3b9/v6enRyAQREZGUqlUKIGen5+vUCjmzJkTFBQEBfUUCoVIJIJ+eXg8fnR0FOB4Y2NjtVq9aNGiiIiIOXPm9PX1GRgYrF69esWKFVNTU8XFxWq1+scff7x7925bW9vY2BgGg7l16xaUztcSHKqTRkREmJmZZWZmvmALObhC//e//x2NRkOGW3t7++zZs+3s7KCTdmhoaEhISEREBJfLPXny5DTAGgqxwRV9AoHg4eEhk8ngZj6fz6+vr8fj8b6+viEhIdBIDuqkWlhYpKam9vT09Pb2fv/998XFxUNDQ/Dqy5cv6zbbmDVrlqWlJfRL8PHx0dPTY7PZarV6/vz5n3zyyTvvvAN1CefPn79w4cL+/n6o6Z2Xl5eamrps2bLIyMj169f7+vqyWCwoZw3/odFofn5+MpmsoaEBooBHjhyBLmbh4eFz5sz56aef0tLS6HT66OhoW1tbcHDw6tWrAwMD7927B/1cc3JyoLhmVFSUbmVGCMv19/e3t7eHhYVt2rQpKCjo5MmT2dnZHR0dYrFYpVLFxcX19PQEBgZC4DA0NNTBwUEqlR46dGhgYAAOXUtLy40bN1gs1uDgYFNT0/z58zdu3AjuPgxo943H411dXZlMZlJSUkZGxuLFiyMjI1evXk0ikY4cOTKtvykKhWpsbISSa/Pnz+dyuVeuXJlmis0cUMsyJCQkPDxcoVBAewk9Pb3e3t7R0dHg4OC1a9cKhcLExERYHdScX7hwYWRkpO6EtScoPj4+Ly9vyZIlixYtWr58OSSModFoe3v7goICAoGwZMmSzZs36+vrR0dHEwiEgICAyMjIFStWlJaWxsTEAJxbWVlpY2Pz2muvrVmzZmxs7MSJE9OaczxPH0AhvYyMjBs3bhw4cEAqlVZVVUFzBu0u0ul0LTSJxWJDQ0MvX768e/duMpms2/ituro6NTV16dKljo6Ojx498vf3ZzAY5ubmEomkv7//9OnTdDo9ICBAqVQ+J1UJ8KJfivECG23cuHHz5s1QIhucdKjMbGpqmpGRAYWF4fMhISH5+fmDg4NQxNjQ0BBCEWQyGZq94HA4MpmMIMjMCAGcWzqdrm2KqVarExISCAQCl8slk8mLFi3avn27ra0t1ByFaUBn88zMTHd3dzKZTKFQNm3atGXLFt2qn5WVlenp6UFBQdAAztvb29bW9ubNm2KxGGZuYWHB4XCeCQfjcLjFixf39fXl5+er1WqxWCwWi6GlT1NT04IFCxQKRXx8vLGxMYPBoNPp8HZd5QodoUkk0r1798C7hyr5CII8ePBgxYoVJBJJX1//tyYK6+np7dixQ19f//r16wMDA7CJVCo1KCjo8uXL27dvhzqUEKnGYDA7d+48deqUjY3N8x87baegERCNRoPOWTKZTK1WZ2Zmzp49m0KhkMnkN998c+vWrbrAKw6He//994ODg69du9bU1KRSqV5cz2EwmNDQUD8/v59//nlsbCw5ORkacsTGxtLpdEdHR2Cz8PDw9vb29PT0F1Qz5ubmWCzWwcHBw8ODy+WyWCzoi2JiYmJqajo5OSmRSKAhDHS84fP5//jHP6B7gfYh+vr6NBoNAo/QcJFOpwPubGVlZW9vb2tru2fPnv7+/sTExMnJyampKWgKpFAooJ2viYnJl19+6eHhAaeDSCRCj8bg4GAAsqA1Qmtra2hoKBaLhQ4KWCwWCtbC6QsMDORwOHw+XyqVSiQS6Pz8+PHjr776Kjs7e9asWbpz5vF4YGosXLgwKioKOpxDUxcqlfr++++///77GAzGyMgIpgTVXp8+fVpXV2dnZ0ckEq2traOjo5cuXcrlcqE+a0RExJIlSzw9PbVvgWR0DAYDlWKzs7NVKpWxsTGIy8WLFzc2Nk5L7FGr1RcvXmQwGCUlJRUVFaCwpyElMweHw9mzZw8ajb5+/frIyAjUP6bT6Xg8nsVieXh4QLV2kUg0NTVVU1OTkZERHBwMUn5mNzpouGZmZgatxohEoraPLPSvdnR0DAwMfPXVV/v6+lJSUgIDA4EBPD09HR0dQYA4OTlBr5TAwMCgoKD169c3Njb+avYHTpcQ5eXlISEh3t7eGo2GzWbv2LEjNTX1l7AzHA63YcMGaIXY0NBw4MABCKCp1eqkpCQKhbJixQqlUlleXv7WW29BlJ9MJhMIhNzc3K1btzo6Or722mtz587Vtkh88UGhUKAdApRunpltDT6KLv+ZmprK5fI/KtkDQH8ymRwUFKSVOM+Um2KxmMvlQvK+NgyrnSSIS7BSIbg0e/bsJ0+ezIzkP1NC+fv7Ozo6xsbGwucdHR0vX74sl8vt7e0NDQ0nJiYaGxtdXFx03w6t4XWj5UuWLElKSoqMjMzPzw8PD8/IyLh7925HR8fmzZt/N3EaGxsnJycDAgLYbDbAnRQKZdu2badPn05NTS0pKfn8888jIiLs7Ox27dp1/fr1M2fO5ObmHj58+F/cF7FYbGRkpF0v6KFp8YPMzMyoqKhpUZwXkd10On3p0qVffPFFTExMW1ubm5sbCoXq7Oxks9lKpRKHw2EwGGj9BNXRX/zJ036c9huZTKZSqVxdXbWxEGCV37Qjubm5Dg4ODg4OQBCYpPZdGAwGcG3dA6L9k7OzMwqF6urqUigUIyMjwEIg+nXb3k2bNgaDefXVV0dHR+/fv19aWvr6669/8cUXz1m+WCw2MzPT3TtdXtWiTOAPabXLtD5Lz0d1pskEPp+vVqt1TWbgkMePHxsZGcEB9/HxKS4uvnz58pIlS55jGAEERCQS3d3dDQwMdF35aRODzk7PF0QAQjynfZ62Fz0EQrQCBI1Gu7m5ZWdnaxssatv0+vj4IAgybWLP8w/UanVubu66desWLVq0aNGi119/3cnJKSEh4ZcSocCf+Pjjjz///PPGxsbLly9r/ySXyzEYDA6HAz8uICCgoaEhPj5+9erVOBxOpVKBe2tpaSmTySYnJ6HHwDRvAIyIXz1LTCZTt6uMboJHQ0ODlgPUajWDwfjdeRczZbFQKOzp6WlsbDQ0NDQwMCCRSNO6O2hnkpaWhsFgDA0NmUzm2NiYFsGAgCGZTC4rK4NLdnBKoVHGi8gRFou1cOHC9PT0o0ePbtmy5b333nv8+Bk7yYcAACAASURBVPHZs2dDQ0Mhnung4FBaWiqVSuHtEolkmoGAxWLXrFnT0dERHR3t5+e3detWBEH27t1rZ2f3q6XSf0n0wHygFwq0xNHW2f/yyy+//vrr3t7ew4cPq1SqkpKSoKCgHTt2rFy5Mj09XZthrQUkXzBooUuTrKws6AljYGAwMTGhdXDhYh34sl5eXr/jghUWi4VOKRcuXAgPDwd/1M3Nrbm5GdgMAhg4HE5ros5EFbT//iZmk8vlqampTCYTwJMnT568+J0PtVp97ty5W7duubm5eXt7a9PDeDweCGsEQeAsP3r0aNoBl0gkgIii0Wh3d3eZTKblXolEIhKJnnlrVfv1oqKiDz/8cMeOHcbGxj/88IMWKf2lvUtMTGQwGMCrvb2905Ac0AQIgmRmZurp6RkYGNDp9MLCwhe8CwVLHhkZ0QLCEG7RrayMIEhycrKvr+8HH3wQGho6Z86cdevWhYaG5ufnP3z4UBtdmCbNEQRJTEyMiYlxc3Pz8PB4/sEB8IBAIOTl5f1S7Tg0Gi0UCgsKCp7PKgAfUalUrQABA8XW1nbmHAYHBykUChgxv64PICs0Pz8fbBAw6Dw9PWtrayEMqx2jo6MQWIabFAwGY+XKlSYmJlqyYrHYxYsX0+n0K1eupKen43C4jo6OHTt2ODs7f/TRR6DSp2laBEGgj7yurgZri8FgaFkQ3gvRvGkdhrV/gosCOBxu7dq1wO4gjAAAgR4UcrlcLBaD0NF+a9oTZq4X7AulUjk+Po5Go6OiohAE2bFjx08//ZScnLx37140Gj3tIVgsduHCheXl5bt27YqPj4+JiTl69Kg2Vwo8+ldeeeXBgwf9/f3QPaO+vn7Tpk00Gm3aNMAjmSmhVq1aBckGCxcuDA0NZbFYBgYGYD0RCITVq1e3tbVt3749KSnp6tWrMTEx05xTsP78/Pzq6upWrlzp5ubm7+8/PDysi0jATIAOk5OT2sMA9to0ikEGV3t7u0QiqayshFhLdXX12NjYjz/+aGlpuXz5cm9v74mJCTCpiouLvby8Nm7cSCaTp6amAPq7f/9+RUXFpUuXhoaGxGLx4OAghKmnTQb+BZgLAgYRERE1NTW7du26evXqDz/8cPjwYW2nJhQK1d3dXVRUpFQqa2tri4uLwVIbHR2dNv/nZILzeLx58+bJ5XJoYorFYleuXIlCoSDoDWzs4eExZ86cad9lMplKpTIhIaGkpOTKlSsQBoC2X78qxWxtbW1sbC5dunTkyJHr168fOXKkpKTk+f6BLq0QBHn48OHo6OjAwMCTJ0+Gh4clEklDQwO0a/3mm2+OHz9+8uTJuLg4oBWEtaqqqiQSydDQUGdnZ319PRqNDg0N5fF4iYmJcHCam5tVKtXbb7/9HD109epVMpm8YMGCpUuXQkOb5+i8RYsWPX36dOfOndevXz958uS5c+d09w5I4ezs7O7ufuXKlX379j1+/HjPnj21tbUzzcFpkkGtVldWVg4NDS1btoxMJicmJkIEPiUlZe7cuVr8AzogxcTEhIeHh4WFOTo6WltbOzg4zJ8/XyKRxMTEqFQqjUZz+/bt7du36+o2yIzo7u4eGxsrKyuDNs5VVVXP1NnQzTAoKOj69etpaWmVlZWQg1RYWKiV/hgM5rXXXuvt7T158mRFRcXDhw8nJydbWlpmhjEsLCxCQkKys7N7e3vheFZXV//tb3/TbqWWB7Kzs6Oion61yML/73+gVqvz8vIgPs7lcoEnmpqaiEQimUx2cnKiUCiQMlhdXa2vr8/hcIRC4cOHD3E43MjICJFIXLNmDUwCbgkYGho2NjbeunULFD6Px3vzzTdtbW3b2tru3bu3efNmDAYzOTl54sSJDRs2AKpQUlKyYMEC3Q6fFAqlo6OjtbU1IiICspIKCgqwWKyFhYVunrj2pj6Hw2EymTwej0Qi8fl8EolUWFhYUVFRWFior6+/adMmyJHt6+szMTERCAQKhaKsrIzL5ZqZmZmamj58+BA6HM2ePRv8ULVanZOTQyAQOByOq6trdXX18PAwl8t1cXGxsrKi0+mlpaVlZWUjIyP29vZhYWFisbi8vNzY2NjAwMDU1JRIJFpYWIjF4uzs7Pr6eiaTCc0XtZwBaxkaGiopKZHL5ffu3bOxsVm/fj0Oh8vNzaVSqWZmZvb29nAgjYyMvLy8ZgqaycnJpUuXCoVC6CTq6+vr7e0NziPA9Hl5eTU1NVKpNCAgwM/Pb5qLjcfjaTSapaVlREQEgUBgsVhisXj9+vVYLBZBkKqqqsbGRmNjYyhakJ2dDRkE9vb2CoUiLy+PQqHw+Xzd3ocqlSo3N7etrU2tVgsEgrq6OiKR6OzsXFhYKJFIWltbe3p6VqxY4ezsPDAw0NTU1N3dXVZWRqFQNmzYYGpqCgagXC5ns9l4PN7ExMTf318mk2l3is/n5+TkaHeqtLR0bGyMy+W6ubkJBAKJRPLw4cPa2loajebt7e3n56crOp8+fdrS0iKVSu3s7Do7O6empszNzevq6tRqNUDt/f39FRUVdDqdz+fPREoBrGcymREREVpWJ5FIRUVFw8PDlZWVPT09GzZsEAgENTU18fHxQ0NDgYGBVlZWenp6zc3NhYWFMG0Gg2FlZeXq6pqZmZmWlobD4ebNmzc4OHjp0iWZTAaYQ2xsbHt7O5fLhUbc9fX1T58+HRgYMDc3Dw0N1eJdEK67du3a0NAQn8+Htq8FBQX6+vosFsvU1JRMJovF4ry8vM7OTn19fVNTU6DkokWLWCxWeXl5UVERREfc3d0xGMzg4CBoTYFAcPv27fz8fDwe7+/vb2dnZ2xsXFZW1tbWNjAwUFxcvGDBgvDw8I6OjtjYWKlU6ubmZmRkFBsb29ra6uzsPHv27OLiYpFIBPvr7+8fHh4O+Y7QzvfChQtSqdTCwsLKygqHw1laWo6Pj6enpzc1NXE4HB8fH4A+kpKS5HK5paWlra0t9Ons6el58OBBZ2cnk8lcvHgxXGCemJjQPkp3y4BLRSKRpaWlu7u7oaFhcXFxVVVVbm4uGo3etGmTNgF0YmLi2LFj2dnZPj4+UBkCQpg5OTmlpaXj4+M2NjagmH/++Wd/f39t6X5Il4BWoBgMBlJUKBQKlUpNSEhQKpW+vr4EAuHChQv9/f2+vr4ODg6WlpaDg4NZWVklJSXQuNvc3DwgIACisHBysVhsTk5OcXHx8PCwgYEBl8udM2dObm5uWloaHo93dnY2NjYGATIyMlJSUqJUKlNSUiwtLTds2ECj0RoaGq5du6ZQKFQqVXZ2dl9f38cff/yr6f7/v941pJRMTEwYGRlB/zmZTNbW1qZUKjEYjLW1NSSEDA4ODgz8P/a+O67Jc+0/kzASMtgjEEYg7L0EZCMqKhWxth61Vds6jnpstXhaR7VWa7VqtS5AwS0qCFjABcqUIXvK3nuFQBYZvz+ut3nzC0Nqree853D9wQcxeZ57Xvd1X+P77RWJRPLy8iYmJqCn0Gg0DofT09OTnP9QV1xRUREcHLx3714fHx89PT3gb2ttbV25cmVERISVlVVaWtrOnTuzs7NJJFJvb29fXx+DwZA+7SEdc+/evSdOnDA2NmaxWMCcDkcFTKTEMwgk1zgczsDAAMJHg4OD5eXlHA4Hi8XS6XQajQaZYZDpoaOjg8Vi4VtAwAB6AehkYVWJRKLq6mqBQIDBYOh0em9vL6S76OnpkUikkZGR0tLSgYEBFRUVGxsbCoUi3QxDQ0M5OTnJISoWi83NzY2MjGQYHyG1tL6+Xk9Pr7+/38TEhEqlTkxMvH79WigUKigoGBsbg7kNtNKT/TOdnZ1kMhnymtrb2yHKLXl+Z2dneXn5+Pi4rq6unZ3dZEJtMLE5HA7MO4/Hq6mpgTIF+DrUfkNGQF1dHY/HQ6PRwAQL0wHaTTq1/MWLFxwOB86Jly9fUigUW1tbqOZDo9FcLhdSJ/v7+4GxEigSIQLW09OTnZ1NJpMtLCyGhoYEAoGJiQmfz5fMlJ6eHlw7gIS2s7NzZGQEYu8EAqGpqQlMM8gskIw23PRfvnzZ29urqqpqYWEBYVJzc3MmkzkxMQFkyBwOp7u7WyQSKSgoQIxKZqwkbIjSHufy8nIsFgtxS1tbWzQa3dXVVVxczOPx7OzsIB+8sLCwo6MDyHK7uroIBAKNRqupqampqZGTk/P29ubxeNnZ2cA9DtYJBJ/c3d25XG5xcTF8y8rKChSB9BSXlJRwuVw9PT3w9dfX14tEIiwWq6+vr6Sk1N/fn5WVJRaLLSws8Hh8Xl6esbGxra3t+Ph4cXFxb28vlUp1cHDAYrHg8iooKFBRUXFwcKisrOzs7AQPmK6uLofDKS4uBi0hmcTBwcHMzEyRSARJnBkZGUwmk06n29jYvH79enx8HIPBDAwMMBgMifsX9iZ8y8jIyMrKCoyPurq6iooKNBptZWVFo9GwWGxtbW11dTUCgTAxMbGysoJJrKqqqqurAx5vGo3GZDKfP38uEokMDQ2trKxkqqBGRkYyMjKwWKy9vb2mpubY2BjgUyGRSGNjYzqdLmG35fF4mZmZTCYTCLQRv3Pxwn0XnDOQ03n06NEdO3ZI8oLAes7IyODz+YaGhrq6urm5uRoaGjo6Oq9evUIikY6OjlCkxWazbWxs6HQ6dLayshKaAYEuIGOXzoUrLy9nsVhaWloQLjY1Na2vrwcDy8HBASg5QcMABXpfXx+UWUCO8ooVK/bv3x8UFDQ2NkYgEBwdHd8YdvoL+Q84HI6NjU1SUpK0FpuYmDh9+nRvb++6deuOHTvm6ur697//fWbvZ3JycnNz89q1a99IBj0nczInc/LXCbgTIyMj169fr6am9m/bTjgPVq5cmZqaOpmofFb5Re9cICFahvgMg8F89NFHr169Ghoa8vX1XbJkyRsfEhgYWFFRMWXu6ZzMyZzMyfsUqNr5dz4MEL/nLsLPP5aR8dfdD8DbI513LGkrj8djMpkKCgqzTPgBR97kRN05mZM5mZM5mawto6KiioqKXF1dg4ODZ59dPceXOSdzMidz8h91HggEAkirhTyU2Xva586DOZmTOZmTOUEg5vgy52RO5mRO5uRffB6IRCLApJubgzmZ4ebLZDL7+vrmhuLtRq+lpeWPRhTn5L9Z/qceTWYZ8Xi88PBwAJX9K06C9vb2+Pj4pqamGzdukMlkXV3d0tLS7Ozs1tbWiIiI7u7ut2AKhQPm8OHDKioq/1quY+CVPH36dHNzs6Oj43vb/AKBIDc3V1NT86+gkp751YCxPCV2yJ8Zxjt37ly8eBGBQEzOSpCe96KiIkASfD+DXFVVFRMTg8Vi/ygI0hsf3t7e3t3draqqivgd772+vp5Go838rYGBgby8vNLS0rq6ut7eXsCz6+vri42NbW1tvXnzJhaLnQwXCJUip0+fjouLo9Pp0i5meOa3334LxFPvajYvXLhQW1s7S86JOZFZ4TExMS4uLpK6k/dxPwAYEwQCMTExERMTMzM/wZ9ZGXfv3m1vb3dycpKXlx8ZGSkqKoqKiqLT6Xp6ehgM5q35WgUCAZfLfVcgRW8tgCyUmpo6S5zLdyUDAwM///zzv4TBjcvlHjly5N1yBQNiaGxs7GREYplJP3r06HQgE+/8PGhubs7Lyzt79uwbMS/fYl9cvXpVwo4Cq6i+vh6Qc2YQBQUFHA538ODBy5cv6+jo4PF4oVD422+/VVdXOzg4kMlkGewTyTbHYDB8Pv/KlSuT7xBIJLKtre0dah9AB+nu7p7T728hjY2NeXl5swE4eWfngUAgSEtLu337NvyTzWb/UTSxWS6LgYGB6OhoAoFgbW29detWGxubxMTEiYkJW1tbc3PzL774Ys2aNW+nPnR1dbdv3/6uLJq3H1MUikqlotHo98CdK61Nnj9/PjY2NrkC+T3YL1lZWT09Pe/2NolEIhkMxsxjKBKJXr16VVtb+37ywZFIJIVCcXJy6unpebeuTgCPu3Hjhr6+vuRdVCrVzc3t8uXLubm5MzRJSUlJU1OzoqKipaXF2NhYWVmZx+OdO3cOh8NZWVl9/vnnnp6e0vebBw8eJCcnA1QJYEpO3ulEIvGbb755h7Y8CoX65JNPli9fPvMgcLnc6Ojo/yRVDugJN2/e/DOrztnZedeuXW9Eampra3sje8/MgpHsq6qqqv379wuFQnt7e4Af4PF4ly5dGh8f/+STTygUCizZkpKSqqqqhQsXylAii0SisrKy8fFxwBxlMBjV1dWjo6MWFhYEAqGsrIzNZmtraxMIhMzMzPr6+ubmZoDPa2trS01NNTc3z87OliwdJpMJ3xofH5eTk3NwcACADhqNNh3oKWDwYTAYQAWY0pvU29sLmNLT+Ragkh5wOGg0GgqFAhprEolkYWExODhYV1dnbm5OIpFgmisqKmZ4IOBzAJZAUFAQfGtkZCQ1NbW5udnAwCAoKIhMJgMKLFSuq6urAwaqiooKg8EAcpuenh7gh5kOcRfQ7tLT0xEIRG9v77v1Y7zxMGhoaHjy5AnAmUw+jKGkMzU1taWlxcDAYOHChYBcMjo6Wl1d7eLiArgOAEyE+D1mAATiM0NXgn/8yZMnAoGgr6/vPdwLkUikiorKHyWEmI3KYDKZWVlZra2t0sESALMzMDA4e/asBPZqNucK0I1ZWFjk5uZSqVRpsKOkpKRDhw5ZW1ubmJhIk6dmZWWVlZV5e3tbWloCCI28vDyLxVJWVgZIuLy8PDihZchrYUkDXeXY2FhHR4eSkhLAk/T29gIELPBVaGpqAiEdsL2y2WxgByosLATMYw0NjfPnz1+/fh0Q8gcHB1+/fm1hYUEkEnt6epqamrS0tAwNDeG/WlpaqFRqfX29pqamsbGxWCyura0dHBxUUVGZTPgMurK9vV1BQcHBwUHyx87OzpaWFhwONx0krfQTxsbGysrKlJWVAc0COlJYWAg8nSgUys3NDSDkampqVFVVGQwGzOyPP/7Y0NCwevVq6VsmoI9ITlxoYUdHh4uLi4y/F3SRDGU90IK9evXK0dERh8MBEs+3335LpVIBXEvSwvz8fAsLi1nujv99MYFAANoNwBEDshplZeXCwkIWi7V3714Wi3XhwgUSiVRWVpaWlvbzzz9LNj9Qu1y+fPnvf/97U1PTkydPDhw4wGaz9+3bFxISsnXrVgUFhe3bt3/00UdBQUEArtLT0wPUFg0NDbW1terq6lVVVYAQ2dLScvbsWQsLCyaT+cMPPygoKNy7d+/48eOLFi2ajtob9EtiYmJsbGxgYCAAqUr+i8PhREdH83g8eXn53NxcOp2+e/fu6XY1Eok8derU4ODg7du3MRhMRERER0cHEOAhkcizZ8/CsBQXF5eWlvL5/NzcXBMTk127dsk8EPA7T548qaur+/Dhw7y8vOPHj4tEou+++w6NRvv4+MTHx798+fKnn35CoVBHjx5ls9kJCQnwlvPnz+/Zs4fD4Vy9enVsbExRUTE/P59Kpf7zn/+UAfSHrXXv3j1VVdXc3FxLS8sDBw4EBgaGhYX9IYj8tzsJampqbt68SSaTMzMzNTQ0jhw5Mm/evL/97W+SBQ2xKCBr9PLyio2NzcvL++mnnyoqKi5cuFBXV+fs7Nzf39/d3a2rq3vhwgXwHx47dszQ0NDOzg6wa6Z8dVNTU0xMDIFASE9P19LSOnnypKWl5caNG99hAOP9GI/9/f23b98Gbjs1NbW0tLTMzMyvv/5aRUUF9LKTk9O5c+dg58/mmWw2GyhXgWtXxm5DIBAVFRX6+vpqamqwQgQCwS+//GJmZtbW1paUlLR//35XV9djx469ePFi48aNK1eu5HK5wNlnYmJy9OjRvXv3SvDYAeHnzJkzjx8/NjIysra2ZrPZmZmZS5Ys6erq0tfXT0xMDAsL27Bhw7Nnz2JiYjAYzLVr1xAIxMjIyJEjRxQVFePi4o4ePRoSEmJmZtbR0REVFdXc3BwbG+vo6CgWi/fv3x8cHPyPf/xjcHDw0qVLbDb77t27L168uHLlSnt7u5mZWUtLy9KlS7W1te/cuYPD4fr6+h4/fvzPf/7Ty8tLepBra2t//fXX1atX5+fnFxUVffbZZyKR6N69e42NjRQKJT093cDA4ODBgx0dHampqcXFxTY2NqWlpXD+7dixA4fDAV25paVlXV0diUT68ssv+Xz+4cOHCwoKAFoNaNGysrLi4+PNzMyqqqoMDAw2b95cWlp67do1eXn5lJQUJycnZWXla9eujYyM4PH4R48e2drafvfddxMTEydPntTS0uJwOPfv39+8ebM0OFtbW1tUVFRtbW10dLSiouK9e/dSU1OBLa6srAyIajQ0NNLS0uLi4mxtbV+8eOHs7CwvL//kyZOKigoikZiYmEgikT7++OM3wryjJEoQqIi0tLQAcw28t5988omFhQXEEh48eABkXq6ursnJyRLPEuJ3lKG6ujojIyMgqALup9LS0rKyMoCBzMvLa29vV1NTA/RNY2NjLy8vMplsY2PD4/H09fV9fHy8vLwMDAwaGxvJZDLQA6ipqeXk5MTFxQ0NDc2fP38GYgAcDken09PS0mTczeBSyMjIAKogHA4XGRlZXl4+3XMA7DM/P5/JZBKJRBMTk7y8PDabDeG+oaEhEonU3t5+4MABGxsbT09PPT296R6Ix+MBA1JLS+v27dsTExMAmKqjo+Pv708kEmNjY9lstrKysq6u7suXLxsaGgDHCoVC6enplZaWPnv2zMPDw9PTU0FB4cqVKyUlJTI+ori4uPDwcHV1dS0trbGxsU2bNtHp9KNHjwJdLWzX27dvz+Dshovd3r17v/3227179+6fJAcOHICDSubVjx49glPQ0NCws7Nz+/bt9vb2x44dg2uKtB8yPT2dSqX6+/sTCITbt2/z+Xw1NbWenp6ioiInJ6dVq1aZmJgkJCTU1tYKhcJz5841NDQsXLhwwYIF0rDb0g3OzMz88ssvAT+1sbFx27Ztnp6eJ0+ejIuL+/XXX/fu3QsdOXfuXH5+/pQVNgKB4NChQ/v27QM22v3798PvIPv27Tt06NB7OAw6Ojq+/vrrvLy8efPmNTY2hoWFBQcHP3/+HOwPuCubmpoCdOAsH0skEj09PWEDAsGZtNPGwcEBPKsSKFAASluyZMm6deueP3+ek5ODRCINDAwAFBOBQDQ1NZ07d87c3NzW1lZeXl6GrAmFQlEolPz8fBKJ5OXlFRQUlJeXl5WVtXDhQm9vbz6fHxUVJWEGhW2CRCItLCxga9+7d4/JZHp6egLLm66uLgBKkkgkFRWVsrIyWPNaWlqAWg+Nb2hoqKmp8fX1DQ0NtbOzu3v3bllZmYODg4eHR0tLyy+//CI96YC83dLSYm5u7urqCqjRbW1t169fd3V1hc0VFRWVk5ODQqGysrJgiZqamoL9d+3aNZFIFBERkZOT4+3tbWxsfOHChdLSUsB+fvnypZaW1kcffbRs2TKhUHjmzJnKykpvb291dfUzZ840Njbq6+srKioSiUTA2QTuSNBFfD7/0qVLZWVlLBbr3LlzgH6PQqEguiM9wsPDw0lJSRA/QKFQN2/eLC4udnV1DQsLS0xMjIuLQ6FQNjY2fD5fS0sLnNVpaWlnzpyxtLT08vKys7O7f//+hQsXZns/QEoJCoUCw+SDDz6wt7fX09MDGq+HDx/29fXdvXuXSCQCFZq0KCoqVlZW/vjjj0uXLg0LCwM+KTQaDT5lia2qpKRkYGAAxw+dTheLxVQqFdyyJiYmAGZJIpGA005dXX3Xrl3l5eXHjx//7rvvpEGVJxv18vLyU7o7Af+9uro6OTkZbnMkEmm6yCc4VVevXn3//v0XL14YGxsTiUQAcHZxcXn+/HlYWJicnNyDBw9evXr18OFD2NIEAuHly5cy3CCwBxYsWCAUCvX09FgsllgsxuFwR44cATOwpqZmbGxMKBRisdhPPvnk4cOHDx8+tLa2zszMDAwMVFRUzMzMrKqqSklJASsSCF6ktUlvb++ZM2c0NTU/+uijrKwsCoUyb948AoFw4MCB6upqV1dXaN4PP/zg6uo6GZRfOm6ppaXV0dFBJBIlPgTpD8jka8Et+NSpU2g0eu3ata9fv5aTk/Py8jIxMdm2bVtZWVlgYKD0OX3s2DENDY1nz57V1tbCOOjo6ABC6vLlyzEYDIvFioqKGhgYGBgYuHPnzurVq6lUqlgsnnz8g4v51KlTw8PDGzZsGBkZEYlE3t7e0JKSkpLFixefP39eT09v586dLBbrxx9/3LBhA9AVyIi6ujqZTC4vL7ezs1NSUuJyuXl5edBfAwMDGdytWep3sVhcX18/wyrV19eXQK4KhcJbt25lZGRcuHDBwcGhv7/f29sbZvDJkydHjx6Fj2lpaSkrK2dkZMzsfJfeCJBNRKFQpDGZQWBIiUQiGo0GgH4UCuXr6+vo6MhkMuGejUKhpP0ncnJyo6OjV69e3b179/r166UnBdQFqE5PT09nZ2eAsMXj8d7e3kKhUFNTMysrC+w/MpkMQRfY/uHh4aWlpT/++OORI0dgaxOJRB0dHQwGAxsZHiUWi4G/GjxXMDsqKiqDg4MhISHAGbBhwwY9Pb1bt24JhUIKhdLR0QHOSemOV1dX37t3b9myZR9++CFgqpeWlqanp6NQqLGxMQ0Nje7ubjc3N0AS/fDDDwkEQk9PT2Zm5vXr19esWePh4eHs7Kympga0ED09PQoKClZWVigUys/Pz8vLi8/nA2w41APDhW9kZMTU1FRZWZlEIpmZmYHdXFVVlZqaCq2iUCjd3d06OjpMJjM+Pn7Dhg1btmyR8e2oq6uHhoZeunQpIyNjyZIlOjo6YrHYxcVlwYIFXC53165dxcXFSCQSSFsB85zFYp06dUpbW9vPzw+Lxero6Ny6devWrVvr16+fvCSm9hdNqSZkvMDe3t4eHh6qqqoODg7SfnwgfmlsbIyIiMjKI9H1cwAAIABJREFUytqxYwe4klAo1AwMStMJGo0G0FqgIXN3d4+JiXnr2DrQ6uro6Hh4eCAQCE9PTxQKNUP+IhAYubi4PHz4cN26daWlpQwG4+7du8HBwenp6efOnQMieDs7O8kD16xZA0RgMoLFYiW7Tjob5OnTpx4eHhIlC3RICxcujI+PX7FixcuXL3/44Qdotra29nTNhiy08vLyr776SkVFJTc3F+hnIScE4qtwFiorK6elpVVVVU1JfQrq/sMPPxwdHcXhcG/kpIPFUFVVlZ+ff/r0aW1t7ZiYGGdnZyDdlbxa2rrB4XDPnj1zd3eXPlfA+MDhcEKhUKIiBwYGWlpaZiivhzSVjIyMb7/9lkajXbx40crKikgkAtyhpqamq6srn89XVFQMDAwcHh6+ceNGRkbG5PMAqGyA9ElHR0dOTk4gEICVA0ECGTKWWYpAIEhJSZlhYa9evRo6C47+xMRECwsLLy+vmpqawcFBFxcX+JhkDMFAQaFQra2tf11QRBqDfbJoa2tv3Ljx/Pnz3d3dAQEBW7dunfkh8PvM7JWSrX316tW32NpgsMrJyWGxWB6PV1dXt337dogaenl5wfkh/a7ly5cnJyefOHEiJydn7dq1hoaGDx8+VFFRAbcSXKfodDrQMYG/Hs4nHx+f+/fv83i8hQsXJiQkJCYmTk7mxuFwWCwW0MKXLl2anJyclpY2pd9SJBL99ttv2traEOGH90KENTw8HCjkPvzww48++ki6p3JycmAeSacOamlpgZ4E+rzJPsOsrKyvv/4amqGgoLBw4cLU1NSampq3PA+mi7UCwakMjRQY+F999ZWVlVVycvKhQ4dMTEyAjOXPZIVDlBuBQFhbW58+fdrJyektaA7hnlFRUWFvb6+qqgoulOLi4ik1uGQ1L1iwIDw8/MSJE4qKit9///3KlSu/+uorCwsLIAsSiUStra1Ar4GYkVRrsmdm3759H374oY2NjaQvEAlfsWLF9evXv/rqK2tray0tLYFAoKam9urVKysrK3ipQCB49eqVhIcOIkVCoXD+/PkcDicnJ+frr78WCoUPHz4kk8lA5MtisTIzM48cObJ58+ZLly6dPHly8mqGOxMQd0y3dc3MzKRRcyGMxuPx5s+fLxQK09PTV61aJRQKk5KSlJWVQalJHl5UVLR///61a9dKd3k6IRAIRCIxKytr06ZN0y3CoqIiDofj7e0tEonS09O9vb2RSGRSUpKioqKbmxtCiuFrYmKis7NTOrwm/Zzy8vIZ3IYYDGZKxfdGU0bacz1lyoPkn+Df37VrFxaLffnypZGREdD2VldXSwJgUCUwMTExf/78f2GcY926dfr6+g8fPjxz5gyRSPziiy/+fPCpvLwcjUZbW1ufPHnSwcHhLS5k0rPZ19cHawb0pvRiBovn5MmT6enpN2/erKuri42N5XA4XC5XQm8JRt7k+dLR0dHU1BQIBNHR0TAvEBKfLpJ/4cKF4eHhzZs3T4fHDHmbXl5eEAQGTYLBYFauXKmgoJCcnHzs2DFFRcXJd0G4GM1e6aFQKAkBKlzIEP8/3fRM8QP4DiTnDA0NARul9HGEQqHmzZuXlZV18+bNwcHB5ORk6eR6gUCQlJQkFArXrFmzc+fOsrIyGFyhUJiVlTU8PFxbWwvZILMhjxUKhUBNNzY2dvv27UWLFh08eLC5ufn06dMTExNQp5OQkACZP9PNjUAgyMzMfPLkCQqFcnFxaWpqunTpUnt7++Dg4OXLlzs6OiAx5unTp5PNEzQa7efnp6KicvXq1b/97W++vr5Ac7906VIsFguXssbGxtu3b4+MjLBYrIKCginJkyfvAWCIpFAoQPAi4eBEoVCOjo62trZ5eXkff/wxGo2Gq1Vzc3NERERbW9vg4GBMTIy0kQhuXyQSWVVVxWKxWltbGQxGXFxcSkrKvn37NDQ04HKARCLd3NycnJzi4+MnM25K9lJ9fX3TNNLY2Cjj0IQrFBqNrq6u5vF4tbW1lpaWKSkpN27c+Oc//ymd3CUWi8vKyoqKiiRdRiAQTCZzSpMQrqQeHh4ZGRkvXrwYHh5+/fq1zLIBOw6NRldVVfH5/Orqamtr6+fPn//666+7d++W3J9GR0fT09PPnj3b3d0tySeR6fXAwEDTjDLdPE6XAgtGq/30IpOHpqysrKOj8/r1ayBdsbW1bWlpOXz4sLu7+4oVKyTtbGpqYjKZ8+bNgxy5hIQEYCj6M8LlcsHVNpsPt7W1FRYWrl27dt++fRQKJTY29s8HTsbGxm7duhUcHHz48OH6+vpTp05NuSTA4Ql1RTPckHR1dW/cuAH0O0NDQ9HR0SMjI9L77s6dO5DdvmPHjsLCwuLiYk9Pz46OjvPnz7NYLIiB5+fnT96wBQUFvr6+TCbz119/1dTUtLGxkebbkWlqQ0PD5cuXjYyMzMzMpizdQCKRQCYfHR09Pj4+Pj7+9OlToKtqa2v79NNPDx06pKmpKVNxAlk28PxZjjCBQLCzs6uqqoJ0Ncg6odPpb+RPxkgbREuWLLl3797333+/YsUKgUCQkJBgZmZWWVkJmSRr165NSUn5/vvvIZvl008/lR6L0tLSzMzMrVu3trW1OTo6gr7w9PS8e/dud3e3jY2NmZnZ8PBwUVFRaWkpGJjNzc36+vqQCwGskywWKycnp7u7Ozc318bG5tq1a5WVlQcOHEAgEBYWFrdv33Z1dQ0ICMjJybl8+bKfn9/PP/8sbUalpqYKBIKysrLBwUE0Gn3kyBEMBuPv7x8QEJCSknLx4sWcnBwVFRV9ff3g4GChUBgbG/vs2TMzMzOZBE0kEqmlpRUaGjo8PAwjuG7dOmAkh9MiMDDw1q1bp0+fTk9PB4rzlStXytg+/f39cOQQCISSkhKhUJiRkWFgYEAkEs+ePVtcXGxgYKCoqHjixIk9e/bo6+uTSKTQ0NBHjx6BUoMzycvLKyoqKi8vD5r9+eefSx9aAQEBH3/88aFDh4yMjEQi0c2bNxsaGtavX79q1Sq4RcbFxfH5/IyMDMjITE1Nnewog85Kz+bkD8g4cMA4+Oyzz44fP56ens7lcpOSkpqamlauXLlu3Tpp5wOwxSorK586daqgoIBOpysqKh47dmzdunXl5eUTExOZmZlOTk5ZWVlwenl5ee3evZvP5x84cIBMJmtoaNjb27PZ7PHxcXBbI5FIGxub7du3X7hwobKysre3Nz09vaura+HChZ9//jkejwf6tg8++MDX19fExKS5ufncuXMQ0pzchckMaNIfmHLPNzc3X758GVZsXV2dJA/kLYRCoezdu/fo0aOHDh168uSJk5PTsWPHiETitm3bJJl74B+DHEqRSHT37t179+5FRUVJfLmQ7llRUQGkhIWFhRDdFYvFUN4s4x/AYDDu7u7JyclYLHbnzp05OTkikejFixcuLi7p6enwrcbGRkggLigoaG5uHhkZiY6OdnR01NLSIhKJcAmTNrwyMjKgBiUoKCg7O5vH41VUVPT19XG53JqamvHx8dzcXKFQ2NrayuFwysrKaDRaTExMdXX1wYMH0Wi0hYXFzZs33dzcAgMDVVVVuVzuTz/95Obm5ubm5uPj8+zZs2PHjkE2B5/PT0tL09PTA+Lrp0+f+vr6YjCYzZs3Hz58eOvWrYaGhkBSJh3kEIvFhYWFSkpKoaGhWlpakMltbm7+/Pnzixcv1tfXEwgEHA4n4YKGS7aXlxfYsvv27YOEqKysrJ9++qmnp0dOTg4ydrKzs4Ga2NTUVFVVVSAQAOUnn89vbW1FIpG3bt3C4XAqKipNTU3Hjx9funTpZ599VlRUdOLEiVevXoFjcMOGDTwe7+eff/7111/pdLqOjo7MJhWLxbm5uZCvuHLlSjDO+vv74R7M5/OBRhCBQAAb6IkTJ9avX79r166vvvoqOjp67dq1AwMDubm5W7dufSNf5v/iVaBQKGNjY+CKYzAYDAbD0tLSyMhIQUHB19fX2tra2NjYxMTEzMzM1NTU29vbyclJ+qgkkUjq6up6enqKioo+Pj7AgUen0+l0upmZGcyul5cXlUrF4XBubm7Ozs76+vp4PB6I99zc3Oh0Olyo582bZ2ZmRiaTeTyeg4ODhYUFGo0GglxjY2Ngj6urq+vp6ZF2tIlEIg6H4+TkBFyv8vLyQF5oaWlJJpMtLS0ZDIaZmZm5uXlgYCDEr9BotKGhobW19WT/KdzO3Nzc1NTUQGNCyrZkJxsbG0N5p42Nja+vr4ODg0ySJZ1OhxCrvLw8iUQKCAiAVUin0y0tLW1tbX18fGxtbS0sLExNTSFBW1tb29bWVhI2h6IHMzMzaHZAQID03oZCJAaDQSAQ7ty54+bmtnjxYmdn56CgICKRKBaLX79+nZeXt3HjRuCVHRwcLCwsXLZsmXTGqiQCqTGjyAS44CtmZmZEIvHBgwcMBiM0NNTBwWHx4sUyyemwRk1MTKDLvr6+NjY2FhYWhoaG2tragYGBsJGQSKSXlxewUmtra5uZmWlraxsbG3t4eCxatGjevHlUKlWSDIPFYs3MzCgUyqNHj1RVVdesWWNtbb106VLwpAmFwvPnzxsZGa1evZpGo+Xk5CQkJISHh8ucB0gkUllZeYYuT+dOBD+Ar6/vvHnz4HR/a689CoUyMDDQ0tJqaGioqKj4xz/+YWZmtmTJEnNzc2gtXB9Pnz69Zs0aiMPBinVwcJDORhcIBEKh0NHRMTAwEAgykUgkcEfTaDSZFqLRaGAShdEGqk4rKysDAwMul+vg4ODm5gapR5JNSqFQKBQKh8NpamoyNTUNCwuTsQ9EIpGnp6ednZ2RkRGXy7W2tvbw8DA1NUWhUBoaGgEBAbAL6HS6r6+vqakpgUCQbG0UCqWlpeXo6AhbW1tbm8/nKysrOzk5qaqqGhsbA5Wpm5ubu7u7n58feNt1dHT8/PwMDQ01NTWB0NfIyKi3t1dJScnPzy8gIEBCGSvZSiQSqbGxcWBgIDQ01N3dHRJYCAQCi8UyMDAIDAyETIrU1NSioiJInK2trV2yZMn8+fMVFRUVFRUFAoGurq6np6e+vj6RSHRxcVFTU/Py8rK2ttbR0VFQUFBUVJSTkxMKhTQazcvLS0tLCzjPGQzG6OgolUq1t7eXEEGz2WwgXTc3NxcKhUwmk81md3Z2ampqLlq0SDK/cJEtKyvT1dUFLZSfn4/H4yWM7iwWi0ql+vn5YTAYCoXC4/Ekk2toaDg0NMRisZqbm+fPn79w4UKZvT/FspQkZkF2xMTEBAaDQaFQ4CySk5ODX9BoNMT64eYOcQwZM0Fy/cRgMPBh+DzsYYFAAH+UXAxRKBQGg5mYmIA2YDAYqHyB/0Kj0eBIgUCNxHmFwWBGRkYOHz7s7+8vcQ1L3iX5DAqFAqcTRFQkT4AHSpL3hULhGzPW4ZNisVha4wuFwu7u7rGxMXV1dQqFIq1upEcDjUYjkUjosmQcRCKRpIXgppN0Af5LpupEElaa3DBwv3h4eOzYsWPt2rWSeeHz+fv27dPW1t62bRs0ICIiYs+ePbGxsYsWLXpX6ZJjY2OLFi2CDHGY9Ol8d5Iuw5zKjIlkcuXk5JBIJEwlzN2UYUm4Dn788cdmZmaHDh2SvBp8Xw4ODq6urnfv3i0tLd2+fTuFQklMTJw5vDn7Lkuvc8la+jMP5PF4Fy9evHPnztOnT+Xl5aUfKBAIrl271tXVtW3bNjjjRSKRQCCQ3n2SP0rfbGZoofQ2RyKRki0jJycn2YkyT0Cj0Xw+f2BggM1mq6qqkslkaaZ0acey9ENktrPMA0EtyMnJSW9t2OnNzc0YDEZXVxfURWtrq0gkgsgTrCLJY6UXDJfLhS8aGBhM7rJAIODz+V1dXZDiBS+CEo2hoSEymaympoZGowUCwbZt26Kjo4uLi2GrSsjYh4aGoOZRQ0NjaGgI+MYlnUKj0dCwvr4+yQOBal5TUxNcPUQiUUNDA4aip6dndHRUVVUVqkzgPAAPHolEks7IgKXe3t4uFotRKJS+vn5bW5tQKESj0QYGBv39/UwmE/y3kCjV0dEBiXOwxTo6OsDHDmf/bJPk/g+JSCSCGyiHwxHPiVjMZrNdXV1bWlqkh6i5udnDw+Ps2bPwF/D+0Wi0v/3tb3w+/129msvlent7V1dXv/9e83i85cuXA028pNc8Hi8hIeGLL77Yt28fFED98ssvRUVFcJz/e8rExMT58+f3798v83ehUFhdXX3z5s22tra5Rf7e5mLTpk1wAPx3yhT4pv/+Ahm1f9I0+48RSOLy8PCQNoEh49vOzg4czeAecXJysrOzMzQ0fFely2Ddz58//6+GXZxuGcybN08mXIHFYl1dXW1sbAA319XVFepd/p1nEHzoU/p2DQwM/rVgvf89ApAPp06d6unpMTY2nq1B/R+mTOb40f4D1jHgzPyrXk0gEN6/wgVvlZKS0l8Ny/EeOsLj8d5YBDAn72EiRkdHX7x4weVyIdY4dx7MyZzMyZzMyX+pzPFlzsmczMmczMnceTAnczInczInv8tfEk+GgqzOzk51dfX34N4FII2qqqqurq6enh4ikQh5bMPDw5WVld3d3QCw9SdfweVyr1+/3tnZKVOCBGGouro6gPB7t8P4+vXr1tZW6NH7WRBQ5JKcnJyXl6ehofFOegS+/jNnzujo6MyAUPvvL4CVm5KSMmXN818xF319fQD7+taFDv+ew1heXl5fXy8h/5FeJ+Xl5WNjY9Lgae9kJGGTolCoP6kK/mhPnz9/HhcXp6Ki8q56JBKJqqur0Wj0O+fh+EvuB1AbffDgwa+//vrdEijOLAD+k5ycLJ2aHRERERkZ+U6inTweLykpSQIJIhEoPN61a5cMzvOfH8a6urrjx4/v3r27vb39vR0Gw8PDhw4dUlZWrqurk0Bs/vnHNjY2Xr16dfagzbMXgUDw448/zgBe8g4Hp7Oz89y5cydPnnw/czEyMnLjxo0vv/zyt99+e28LgMPhHD16dOPGjdu3bwfQDigROHHixBdffDEbXJbZrO2zZ88ePHhwMpFnbW3twYMHL1269G471d/fHx0d/eWXX77bTTrzS3k83pEjR4C/ZPfu3TKgL39m9I4fPx4REfFXNPvdnweAH6ekpPTy5cv3QPgJoqys7OzsnJeXB1yy8Ec2m52bm+vh4fFObFJFRcWdO3dKKqKBAACBQECRSG5ubkdHx7sdRgqFoqmpmZubKw1z/ZcKUFsXFxe7uLiEhIS4u7v/mf3Q09MDVNiACxYeHj4DPsRbv6W3tzchIeH9sITi8Xg+nz8zn/M7FHl5eRcXl9zc3L8O3HSyYDAYCwuLxMTEuro6SR0yEolsbGxsb2+fPaTaTEoHhQoMDFy6dCmgOYlEorS0ND6fDyX6dXV1gGL5DkVJSQkgyN7tJp15ZZaUlFy8eNHR0TEkJMTX1/eNtcFvXOeSuXB1dX0jEtFbzr7MWwEQSkNDQyb7DRrE5/M1NDSgJrurq0tbWxtKDbu7u5FIJB6Ph0pdDQ0NyU1QJBJ1dHTg8XgymSwUCjs7OzEYzGxAlWWOdy6Xq6CgMCVNLpT4mpubIxAIINKR6Gtzc/OlS5e+kXeUx+MBt5+WlhaUYgLtBhKJ5PF4/f39VCpVTk5u/vz54+PjYENFREQUFhYGBQWBspO2r5WUlN4idxBqIFEoFGxCOA8k2BXAk4PBYNTV1UUiUWdnp1gs1tXVnb07DsptYKYmz6/E1n7w4AEGgwE8rMlgR1D21dHRITOJ4LIDtlRYFa2trQcOHAgICLC3tweguhUrVkjQ3GTGfHJBKYvF4nA4EjDXGWylsrIyHo83HbzEzDehsbExCoUymYlweHhYLBZLY28AsBog8s/wTIDZQaPRb0FZCsgEHA4H1rkMpQcUFXZ3d5NIJAKBwOfze3p6AGjk3VohGAzG29sbg8GQyWTJeTA0NFRQUHDo0KHJTLRv95bg4GA+n6+goCASiVJTUw8fPvzs2TM5OTl1dXUJHjiHw5mYmHgLRxnoMRaLBagVgIIzmbLlrz4Pnj9/3tfXp6qqisFg1q1b99buHZFI9PTp06Kiom+++QZO05UrV/4VzqL/7zwQCoVlZWUJCQlCoZDP5//000/SbhaBQHD9+vUXL16cOnWKTqePjo5u2bLlypUrJBLpxIkTDg4OjY2NBQUFR44ckSmfmZiYOHTokEgkunz5MofDAc6gn376SVNTMyEh4fXr1w4ODu3t7b29vWpqamvWrImOjh4aGsJgMJ9//rmurq5AIABaO4FAUFdXt3z58rCwsOlMAAKBUFRUtHHjRlAoSUlJe/bsmc166unp+fLLLxUVFc+cOdPT07N7924kEnn37l15efm6urp9+/ZdvHhxfHw8ISEB3Cl5eXmnTp1CIBBJSUnAHALuHWCCBBqfyRwyIyMj8JwVK1bY2Niw2exLly4B98DIyMilS5dUVFSAVTUkJERm40EVa2Nj4/nz5/F4/LVr13Jycvbu3evq6lpVVZWYmKigoGBiYpKbm4tGoxcsWCAnJ5eQkABooMBG29XVFRkZKScn19DQAODkMhgvfD7/u+++KysrU1BQ2Lt3r5eXl6GhYX5+fnNzM5VKraurc3FxcXNzu3TpEhqN7urqotPpmzdvxmAwQqEwISGhpqYGg8FUV1f7+fmtXr36/PnzcXFxPB5PV1d3/vz5zc3NSUlJgNoESjMyMlJRUXFkZASNRu/cuVNVVbW7uzshIaGzs9PW1jY1NXV0dDQ4OPiTTz6ZcrOBDzovLy81NbWnpyciIiIkJGSW5A0ikejRo0dFRUVYLLa1tfWLL76wsbFpampKTExks9n6+vqPHz8GUpQlS5ZABfiFCxeg7n+yw1CyaQsLCxMSEpSVlbu7uw0MDDZt2iQD9g7Xr4qKCjMzszVr1gA7Sk1NzebNm4EHsaGhATCGvby8Jq/z0dHR8PBwGo125MiR/v7+48eP9/X1nTt3TiQSJSQktLW1ubu7l5eXj46O6uvrL1++/OLFi2w2W0lJafPmzSoqKrACExIS6urq5OXlN2/ePOUhCjASSCSyr69PIBBgMBiRSAQElt7e3rNx0wMP16ZNm/h8fmRkJPDt+Pr6dnV1Xbp0aePGjTo6OkVFRY8fP965cyefz//++++Liopu3rzp6ekJTD6Dg4ORkZElJSU8Hu/TTz+VqbWEkYyJiWlsbHRwcAgNDRUKhffv3+/o6NiyZYucnNzVq1f5fP7g4CCbzf7ggw9kgj1AIv3q1astW7ZoaGjcvn27pqbG39/f29u7q6srISGhq6vL29s7Ly+Pw+EwGIyAgACYfSKRuGXLFgKBAGDpCQkJfD6fTqeHhITIADoJhcLo6OgHDx4IhcJ9+/YZGBiEhYWlpKRkZ2fb29sD2P6OHTuqq6sTExPHx8c9PT0XLFgAwBssFgt2ExKJdHd3DwoKSktL27dvHx6Pd3V1BZClxMREoVC4ceNGyUU8Pz+/sLDQx8fHxcUFUB0fPHjQ0NDg6uoKaIMuLi5Lly59o+ccJa0ODh48CFSOWVlZMpirABr1/PlzuHBNTEz09/fLy8tfv34dOK/d3NxYLFZ4ePhkJoCRkZGHDx8iEAgsFqutrf348eOOjg40Gl1RUREZGfn06VN9fX0tLa1Tp07t3buXSCQ6OTklJiZev34dgF6fPn0aEBDg7+/f2Nh46tQp4PCb0klFpVJfv34N8xEfH29tbQ3KGnbCDM5rZWVlYEIWCASqqqry8vLp6elCoRBKVHp7ewkEgrKyclZWVkpKioTlikQiMRgMsC7FYnFNTQ2FQgkMDExJSZHwHUoLFosFRFxwmwqFwtzcXAMDg6GhIcBwdXV19fDweP78+Z49eyaHXvh8fnJy8tjYGDBSPXv2DPCrkUjkjRs3oqKiOjo6vL29CwsLw8PD09PTnZycRCLRyZMnGxsbORzOiRMndHV1/f397ezsYmJipOlOQYDVWVlZmUKh+Pv7GxkZDQwMREdHR0VFNTQ01NfXM5nMy5cv37hxw9/f383N7fTp06mpqYCIef78eX9/f7gUwxutra25XK6hoSGNRhsaGsrOzv7ll19KSkrgthceHg47bdGiRa9fv/7666/ZbDZQ7EVGRjY2Ni5fvlxVVfXUqVOTnTMQdYyMjLx8+TKBQGhvb1+1alVXV9euXbsATxu0koxvWlq6urr2798vEAh8fHy6urq++eYbqN/OyMiIiooaHx8PCwvjcDgnT54EOLAjR44MDw/7+/v7+flNx+AtEokeP37c1tYWEBDg5+d35syZKdcbBoOJjIx89eoVtLO+vh6DwWAwmAcPHjx69AjWubOz87Fjxx48eCDzXRwO19ra+vTpUwQCQSAQ5OXlk5OTmUymvLx8ZmZmZGRkdna2paUlBoP56aefjh07pqura2VlFRMTA0R+w8PDv/zyi7GxMYCGhoeHT+eHRKFQPj4+lZWVXC4X1E1ycjJwo3Z0dFy+fPnixYvTBWzAURwVFQVUFm1tbbdv34aDRygUpqWlKSsr19TUxMXFRUZGslgsJSUlYD6wtraG2z9M3/DwcHBwcFNT0549e6YEGBcKhZGRkZWVlfCVyspKAoEgEokuXLiQn5/v4uLi5+fHZDK//PLLySzcWCw2IiKiqKgI6Gji4uLi4+PBJ5yamhoREZGXl+fg4MDhcI4cOXL27FmAsD5//nxaWhqgpUZGRrq5uVlYWJw8efL06dMyyOFIJNLOzk5fXx/Y05ycnDgcTmJiYmRkZGZmZn9/f3t7e1VV1fbt26lUqq2t7bFjx4BWWigUQljF398fh8Pt27cvIyMDmO3Hx8cBDDQ7OzsiIiI5ORnxO7vyoUOHcDicj4/PgwcPPvnkk4aGhomJifz8/HPnzt27dw9U03fffTeb6B1KeqUuXrx40aJFQA8t47JEoVDz58/X09MDiNfi4uIlS5aIRKJbt24ZGhrCylu6dGlSUpIMxwiNE5CwAAAgAElEQVSwTUEFJhaLNTIyAseFnJyctrY2k8n08vLy9fUNDAzs6upCIBAhISEBAQE4HO7FixfgvigqKkpMTHz48OHIyEhdXR18bPJ5oKCgQCAQ+vr6RkZGamtr09LSgF0dDoNDhw5NqaMRv2M5hISEDA0N1dfXk0gkY2NjgD6Hnm7cuBGPxxOJRJFIxOVyUSiUjo4OhUIBdmU4D5BIpL29/bJly0JCQhQUFIqKiqZs4ccffzw8PAzqgMViodFoKyuruLi4jIyM0NBQS0tLT09Pf3//1NRUCE7IDCOYqMB8ACcEeKuEQiGZTA4KCvLx8dHX1y8uLg4MDAwKCnJ1dW1oaHj9+nVfX9/Nmzfz8vLi4+NfvXrFZrNfvnw5+TyYP38+gUAgk8k+Pj6GhoYGBgbAAvjRRx99/fXXPj4+VCo1ODjY1tZWXV29vb29sbFRKBRGRESoqqoCy8KmTZs2bdqkqqpqaWkJGLHAH2tqatrZ2cnhcEQiUXJyckpKyqJFixwdHd3d3b29vePj458/f66kpITBYJhM5rJlyxYuXOjv719XVyeD+Q7APleuXDl//rybm5uVlVV3d/emTZtWrVr18OHDpKQkyL7YsWOHND+HjCgoKFhaWi5dutTS0pLD4RQUFCCRSBKJBLs6ODg4ODjY2dm5qKiov7+/vLz8/v37K1eudHJycnBwmMFhoq6uHhYWZmtrq6mp2dHR8eLFi8l61t3dnUqlApGRUCgsLS1dvnw5Eok8efIkGICOjo5Llizh8XgnT56UDr+B2Q7IoABtS6VSAVxPUVFRVVWVyWQuXrzY19fX3d0dctJgGCVw07GxsQ8ePACXlLy8/IMHD8B4mnJH0Gi04eFhPp8vFAovXboUHBxsbGw8PDz8ww8/lJWVPXv27Jtvvpl84kKKXVhY2NDQUHV1NYlE8vX17enpGRkZAa1kZ2dHJBLV1NSUlJSGh4eh8UZGRkARKMFW0dHRCQsLW7Bggbm5eWFhoQzDIIykv7+/ioqKZCSrq6uXLl1aU1Nz+vTp4OBgOzs7FxeXzz77LCcnJyoqavJMDQ0NgXvWwsKCy+X29PRA40kk0ujoKHj8nZ2dGxoatLW1ly1bFhwc3NfXl5+fD0fO4OAgl8uFsMqVK1dkAqXAZgxMwN7e3vb29iQSiUgkjoyMBAcH79ixY/369cAKM2/evICAgJaWlsePHwPj4ZMnT4KCgnx9fVevXq2jowNAwoqKipqamoA2zWAwmEwm8M6CES8Wi11dXX19fZcvX56fn3/lyhU5OTkzM7OBgQE7O7v169c7OjpWVlaOjo7+sfNg2bJl5eXlUVFRk1lrgILuo48+unPnDpzzq1evZjKZpaWloBCBGYrD4UymlZhuzQFVKaDOwu9UKlVdXR2LxeJwuLGxMR6PFx8fb2VlFRAQsGDBgp9//vny5csSaPgp1VlXVxeYJL6+vpLYl5ycnLy8PMQ2ZzCIMBjM48ePxWJxdXW1UChMTEyEU0GaGmyGJ0Dj5eTkpgseoFAoZ2fnxYsX37p1a3BwMCkpacmSJWg0+tGjR4DLKO29BTNwNsMoLy8vJyenoqIC/cXj8bDKcTgcWEwsFuvJkydMJjM4ODgwMHD16tW3bt2SMHDN8GQymaygoKCkpGRubu7o6Kijo7NgwQIfH5+YmBhJxA+cHhJHrYWFxZo1a4BzSvoglLBfAecdj8eTEGt7eXkBtrDk85DRSyAQhEIhUDNJC5vNPnv2LDCMNjU1qamp6evr0+l0Ho8HoPPASTtDDJZEIm3atKmlpSUuLk6GHV7SVNC8XC43ISGBzWZDdGoGQaPRixYtQiKRMTExcA0C3vbJmmjr1q11dXXp6em1tbV4PF5PTw8OBolhQSAQHB0dy8rKZslXA19BIpHm5uby8vIEAgGQtCkUioKCAhqNHhsbAze9np7eyMjI4OCgn5/f+vXrp8MmQKFQ5ubm4AGvqqqqrKxctWoV4O/7+PisX79+27Ztz58/nzLtDYVChYSEGBkZJSQkAOg6j8eLjo4eGxuLiYnZsGEDBJOkV8hkoVAocO7OkO5MpVI///zzgoKCwsLCV69e0Wg0NTW13NzctrY2SazV1NSUwWD8oewsGD0rKys4fYHAg0QigYJisVgdHR1paWkqKipDQ0NcLnfTpk0rV66c2Q8DWwAwR83NzS0tLc3Nzc3MzKKiokZHR2NjY0dHR2GOYmJixGIxOM0MDAwOHz5sZWWlqKiIwWAUFRUBGJhGo0kwm4uLix88eODj4wMPd3d3p9Fot27dGhgYUFdXB3cxjUabfaorRtpDHRMTg0QifXx84DIyecUDWfmPP/7IZrNpNFpzc7P0doJg8p9hCJl8B4dN5evrK/H8zsBOpaenNzo6eujQIQ0NjZCQEMnfcTgcjUabzvOL+J1Rb+nSpffv3wdM2k8//fThw4dqamo0Gu1dAYrBsli1atW6devOnz+fn59//fp18Bh2d3d3dHTQaDRoiZKS0jvMKQLdBOMDWwWCdYCaO/uHiESi3Nzca9eu7d69W3reh4aGJKDcsHBnzisDa4PP5wPkMqgGaTK+mZdEVlZWW1vbL7/8oqysXFpaamFhgcVi6+vrgQkOLlIzb4ChoaGbN28aGRn5+flpa2tPSRsnHcaHFAOZcMtk98WNGzdqa2u3bNky3agCgdrixYu/++67X3/9lUqlBgQEQEbAxMSE9AhQKJTZMAn+0fi5paWltHEzXWgNznXws6PR6L///e9qampisZhOpzs5OSkqKvL5fIFAMPmoRvxOcgde788++6y+vn7Lli137tyxtbUdGxubksH7rePeH3744cGDB3/99VcMBgNxprGxMbFY/OrVK4gkAafLLC3UWUpnZ2d/fz+DwYCRBP7gN/JQTulYKy0t1dXVtbCwgNQjSMsGFgDQt5BNMMPW6O3tZbFYYPjDmHh4eJw8eXLKqZlV6pdkm9XU1Fy+fNnY2NjJyWnKhByAzGQwGJGRkcDOoaKi4u3tDQ4iiO8RCITJcXxQJYODg5CFMvvGycnJubq65uTk5ObmSvLSpptdMIoh1BMWFvaHqj/gMr58+fLW1tYzZ85s3bp1586dfX19kZGRixcvfoe1YMAZx2Awrly5YmdnR6FQ4FoD3JCSNcHhcJYsWTJdCgr8/EMvnT9/PlAgwDWzu7v7xo0b052s0wmXyz1w4ICCgoK9vb0kcgs3/WfPnoF7RCQSJSYmzmCbg/EFbGiSHiGRyMm5TNPJyMgIuHeEQuHjx4/BJXLx4kVra2tYljMLxJbu3r0bEBBgZmY2cxYguElZLBaswBlEIBBERkaKxWJ7e/sZngnH1apVqzIyMurr6yFCCwzV0vbK4OCgubn5lMljXC6XxWIhEIg/ypoJ0TggZ9fV1QVSqekaSaFQlJSUgJLBw8NDYjMpKirC0UKn06ezk1Ao1AcffFBTU7Nly5bg4ODPPvtMIBCcPXs2JCTkHWISQ5pcaGhoamoqk8l0cHAAViXopqTLJSUloaGh7/A8UFdXx+Pxubm5GhoaVCpVR0dnZGTkj1YIQQVGXFycjY2Nvb09ZEvD2hgYGCgtLUX8jq9XUFAwwwgYGhoqKiqWlJRInxBUKvWtqxdRMvl/JSUlV65cgWQhaQ5SxO+EXAsWLEAgEGCI4fH4jRs3FhUVPXjwoKen58WLF/v27dPR0YFqXunrv0gk+uWXX65fv37r1i2hUJifn8/n8+EzELOC34HSQCAQTExMCAQCFAq1detWHo8XHh7+/fffh4eHZ2RkTOcvQiKRZmZm4KOXpnSf7UCgUM7Ozg4ODhoaGh4eHoaGhgsWLDAxMbG2tpa4rXk8HlDiIRAIeXn5/v7+27dvt7a2Srog3fjpKIJVVFQWLVo0NDT0wQcfgLIODQ21sLC4ceMGRC9zcnLs7OwCAwMRv7NxIX4nnkSj0VFRUTdv3rxw4QKkWgL9MliX4GYFy136J4/Hs7Gx+eCDD+Lj47/44otz587t2bNHRUVlStoQeBpQCUGmGfwETVpbW1tTUxMbG3vjxg0MBlNSUlJUVATR4D179oAngcvlqqqqAoFSfn7+vXv3pGcZhUIFBAQsXLgQ0qV6enpiY2M//PBDYGGc3HgZfw7QShsbG9+5c6e6urqzs1NbW/vo0aNVVVWQtDabuYZwZUJCwu3bt8F5defOHRaLxePxJJ2VDN2CBQucnJyOHz8eExNz69atjIwMoVAInZIRJpPZ29t79+7d2NhYiHBOGetCo9ErV67k8/kuLi5wN5KTkwsPDx8aGrpx40ZPT09FRUV9ff2ePXvQaLR095FIJIPB6O3tvXTp0uXLlx89eiQSibKzs+G2J2mz9GqE6YOQg5+fX21t7bFjx1JSUuLj448cOTKDoUOhUExNTfF4/ObNm6U/BsG/CxcuHDhwYLoLE3CaOjg49PT0LFu2jE6nL1myRCAQLFy4UOJXgZ0OLnh5eXmRSHTv3r2CggK4ecDP6daA9GJYtWrV+Pi4t7c3+HasrKzCwsKePHny+vVrPp9fWlqKRqOBCFP6IUCglJ6e3tPTc+/ePQgGQAaHzEjKjCeXy9XW1p43b96TJ0+OHDlSVVV19erVmJiYKf1aMo2XPE2SQjowMIDFYpuammDtDQ0NhYWF8Xi8r7766saNG7du3bpy5YokrxT0M5/Ph+05MTEhFAqBLO/Zs2dDQ0Mw3VVVVevWrSORSBLVIZHZ1Gz+D14FzEpnZ+fg4CCdTofuBQQEyJT5QKgHhUIFBwfDZR8oVQcHB0dGRvT19RcvXozH48vLy7OzsyGKaGhoqKWlxePx2trajIyMXF1dLSwsbG1ttbW1f/vtNzD0HB0dU1NTe3t7lZWVXVxcmpqaCgoKlJWVLSwswG3d2dnZ19enq6sbEhLCYDCm9NbBdYnFYm3atEmGtRHMhLKysvXr18/siNfQ0ABKP7A+DAwMHB0dIQ+svr4+OzubQCCoqqoyGAwikVhfX6+srGxpaZmdnd3f3w81cXV1dUVFRQQCYTpEeyQSqampyWQyP/nkE9DIJBLJyMior6+vubm5ra1tYmJi9erVxsbG9fX16enpKBRKT0/PxsYGNHhTU5OOjs68efMYDAawgZaUlFRUVBAIBGtra4FA8PjxYzwer6WlZWRkFB8fz+PxlJWV58+fb21tjUaj6+vrEQjEvHnzFi5cKJN3LxQKU1NTGxoa8Hi8ioqKoaHh69evc3JyIFEECLGRSGR3dzcWi3VyctLV1R0bG4MkVCqV2tPTMzw87OXlFRQUpKqqisPh2Gx2X1+fvr4+lUpNTk4eHh4mEAhubm7q6urm5ubDw8OlpaXl5eUaGhrr1q3T1dXt6el5/PgxsCEaGBjEx8fz+XwDAwNnZ2eZZDB9ff2CgoInT540NjaCl/Ljjz/28fGB8QR9raurC4btZCESiZ2dnUNDQ5BwNTIyoqmpqaSkBKuOTqcrKys/fPgQjUabm5s7OTmZmppCrgGfz7ezs/P09LS1tZVERKS1TGdnp0AgCAgIYLFYWCx2wYIFU2oKZWXlzs7Ozz//HOoMwCmspaVVVVVVUVHR3d3t5+e3ePFiDofz22+/9ff36+vrW1tb4/F4fX39wcHB7u5uW1tbOzs7W1tb+HtqaqqCgoKmpiaDwYiPjx8fH4etVFhYCFEKJycnW1vb9vb2p0+fvnz5ks1mOzo6enh4TOcJQKFQubm5n376qZ+fn/R2A8WNxWKXL18+XZwMbttkMtnd3d3Z2RmNRmOxWCqVumDBAhQKBfG5jIwMLBZLoVAg1trZ2cnj8SA7oKysDBazWCxOTU1VUlLS1NScLn4D1MQ7duwAvHc5OTlzc/OJiYnS0tKxsbHq6urly5d7eHgMDw8nJyeDjrK2tiaTyUwmE5Kb8Xg8h8PB4/Hu7u7j4+OPHz9WVlbW1dXV19ePj4+fmJggEAguLi7Pnz9vaWkhEAgeHh4wkikpKS9fvuTxeMuWLTMzM5MZpZKSkpycHDweTyAQaDTa2NjYb7/9hsPh8Hg8jUZTVFRsaWl58uRJVVWVSCRSVlYG3RIaGorH41+8eJGZmclms4OCgqytrTEYTFVVVUZGRl9fn42NTVZWFmxSKysrHR0dQ0PDpqYm8Jrcv3+fSCRu375dXl4+Pj5eKBTq6elZWVkVFxcPDw+TyWRPT8833LokMSUgf2cymVQqdWxsDGJoMn4xqLjp7OyUbAZI/gNyZ3V1dUjO7evrA4I3TU1NKpUqEona2tr6+/t1dXXJZPLo6CgOh5OXl6+urp6YmFBSUjIzM2toaBgZGcFgMAwGA7KbwN+trq4+Pj7e0tIC1UkzV2BBodbkjSoQCK5cuXLt2rXs7OyZfaxsNhuDweBwOLC5xsfHJTlwQ0NDcMCCrmSz2VVVVUQiUU9Pr7W1dXR0FBo/Ojra1tYGOalT5neDGQ5UtNI2V1tbG4vFwuFwioqKVCoVhUINDQ3B8QB0zRAGAD48LS0tGC4ymdzV1dXZ2QmXRxwOV1NTA7VUNBqtsrKSx+PhcDjgoIZP4nA4Q0PDyXpKJBI1NjZCujAETgYHBwGxgEwmQ4yrr6+vtbVVUVGRRqMxmcz+/n54FJvNbmlp4XK5EHyDTkFZiba2NplMbm5uHh8fx2AwcIeD8i4ojgNiWFhItbW1YrFYVVVVX18fGk8mk2UY4eEuW1ZWFh4eTqVSt23bpqKioqenJ7nu8Pn8lStXurq67tmzZ7rxr6mp4XK5Wlpa6urqNTU1RCJRSUmppaUFLB4KhVJdXS0QCGABC4XC9vb2/v5+PB4PfkgCgSBTWwC+0KamJnl5eQaDUVdXx+fzIao/5UJtaGiQZnaEtdfc3AwVAwYGBgoKCjwer6mpCWgeaDSakpKSSCSqr68fHR01MjKSl5cHLAQkEllTUyMSiSAMW1VVxeFwQDP29vbCIMMhV1tbW1VVNTExYWhoyGAwZqjbh8w6ExMTCa8GjNv169crKys//vhjNTW1169f+/v7T7kfISoGgW5I8AOCSYmHEEgfCQQCg8GA6QBOR2B8RCAQhoaGCgoKkn7B8pvyRTU1NdKnBbhDOzo6yGSyQCCg0Wjy8vJA/sxms/F4PFBgtrS05ObmkslkBoMBmU4MBgOBQEAwSU1NTU9PT3r7wAKQOCGqq6sh68TU1BSCzzKt6u3tBR1IIBAMDQ2FQmFNTY1QKJRMbltbW3Z2Nni5sVhsSUmJqampvb390NBQcXFxf3+/np6eo6MjkLXV1NSUlJSoqam5urr29vbCJjUwMFBVVYXcqra2Nn19/YGBAW1tbRMTE6FQWFlZyefzwdZsbW0dGBhQUlJ6Y/zmP5//ANydW7ZsqaqqiouLe4fh7jn5Fwqfz1+1atWSJUs+/fRTGUVWXV0dGhrq5eX1448/zpzH8t8m4AMEJvCZU2LA8oO7i2Rgnzx5sm3bNpFIZGBggEKhFi5c+I9//OPfnHtuut6BmQhkzn/pSM7wBPCJgc0NpX/gioCHS54saS0ajZ7u9IXGSMjY31ow/w3bQEFBAaolZfxIc/J/VyC8OW/evCndcT///LOampqMCT8ns9cX0ieB5C+mpqbHjh2T/NPCwuL/4mEAjUcgEH8muP3nNS/UY0n+KfkdRl5a77+xtX++Mf9d94PJS2FO/q8LZMTR6fTJV/W56X4P+2hueP8zLYY5vsw5mZM5mZM5Qczxo83JnMzJnMzJ3HkwJ3MyJ3MyJ3/xeQCh8/7+/rcum56TOXkPAiWg741uaPLbORzOdMVWczIn71+mjkoLBILk5GQoHXq75/b29m7cuHHDhg0rVqyYG+W3FihsSUpKotFoMomV77MNZWVliYmJGAxm7969/zEnAYvFSklJAebt0NBQPz+/yZ+BopC/gkoF8I4KCgqCgoKksUkg8f/Vq1fStc04HO6DDz54I6aeTOP5fH5jY+PM3xIIBDExMW1tbWg0Ojg4GKgCoG1NTU1WVlZ/xf4ViURxcXEVFRUABwLoZACXVFJSoqenBxXFM3StpqbG2Nj4LyIVF4vFdXV1QG+Jw+EkmPkNDQ3A4GRnZzcDHQ3Ux7S0tEBBwx9dElNWEUM2l6mpaXx8vK6u7mf/j733jovq+P7/d+82lt1ld+lLk947UkUEe8WGUUSTaFQUWxJjb7Fjw4oxGjRiiWJBsERFAUFpItJ7U3qvyy5b7v7+ON/sb7+gaPKJ728+78zzjzzisnvv3Lkzc2bOnDmvpUv/c+sDaEmHDh2CNCl/qh77+/vFYjFMfJ49e/b36uXCkaV/ybwV8s0RCAQul/vkyZPY2NjPV2NDfw3OkCckJERERPyTa+xPtQ0cxxMTE1+8eAFyqpBGf/BYuXv37jNnzvy9qeXkqKio/PbbbwMUHCGOtri4+Pz58yKRyMfHx9bWNjc3d+XKlX9KuxjH8fv37w9WuRjY/zEMzrHHxcXJ8xGBsYyLi/t8h3XMzMweP37822+/DcgfHh0dPfRN4dzf+vXr/5rvASY3H9XxlUgkhw4dWrdunaJVFgqFP/74Y3p6+tBHFnAcv3Pnzq1bt/5CG37w4EFdXZ2Pj4+dnV1UVBTIbXl7e5eUlIB+3O3btwcLY3x2fxGkEf3EbDCKVuRDejV/y3zq0aNHn5gF+n+7MeDz+aGhoXDCU0tLSyKRDMgl9YnXaW1t3b9//0e/Vl9f/yFxCEBbW1tHR+fPJlD7jwHJyYfIX/ven4SHh4vFYnt7++Dg4ClTpgyulurq6tjY2Ojo6Ly8vL+9zCAOMXjKRSQSNTQ0MAxrbW3V19eH/B/Lli1LSkoa+h0NfsCoqKihc7LC7VxcXGg0mlQqlfd3MJYTJ078UyuSP/XslpaWGhoaPT09BgYG8ps+f/58xIgRMB8forkmJyfz+fy/JhiJ4/jZs2c/ag/09fX19fWzsrLk5goWizU1NR9NcInj+G+//fYXBFMJBAKdTg8JCRk1ahQkvlVWVgbhtuDgYAqFoqenR6PRBguOfUZ/EZz2joiI4PP5sGD89CEsLCzswoULzs7Ocvspk8nevn37+++/6+vrQ5eDQSo+Pr69vV1XV3fq1KkYhuE4XlNTo6qq2t/f39nZSaFQ5PLL8sYdGxu7Z8+eyZMn29vbg1QAnO9/8eLFyJEj4TT/e9crGRkZ+fn5GIaBRIZ8BMzNzRUKhS4uLtAiIRuEUChUU1N7+fKlUCj09fXlcrlwvLmkpCQnJ8fBwcHCwkJVVRU+TEpKqq+vV1dXnzlzJoVCwXG8oaFBWVkZlBt0dHQgjQSDweDxeDiOg3qXsbGxRCLJzMx88+YNyCcp5mMAj/bevXuvX78+ZcqUYcOGsdlsiPJua2uDXAUjRoyAh8VxHKoXwzB3d3fQ0pNfp6WlZcOGDcnJyYsXL+ZyuWpqaiB9nJ2dDbWhq6sLqUQ2btxYWlq6YMECDQ0NkHt88uQJ1ABkiwJF5Q+9+qampri4OD6f7+3tDa4VHMerq6sZDIaKikptbS2kHhGJRJA7QU1NDfQF5UkaFF8ipM3AMAwqCnJI8Hg8+FNlZSWbzRaLxU+ePLGwsHB1dSUSiTdu3AgNDQ0MDLS0tBww34RkCc+fP4c3NWbMGEglXVZW9urVK1VV1YqKClBoGfAriUTyyy+/+Pj4gKwVaEB+qP/n5+e/ePGCzWaPGzdOU1NTsS29ePFCJBL5+vrK03j09va+ePGisrLyozMnyPwDAvcgyPqJnRHyYeTn5/v6+orF4qGPMkHyGIFAIBKJwDCAFNWiRYv+rlNOg29KJpOZTKZUKhUIBPBm8/Ly8vPzw8PDB+RMGzw6paWl0Wg0Pp//F/xFkIhs6CB76LMGBgYg+qI4yi9atEieZua9F5dKpVDzM2fO/FP55GGt9v3339va2pJIJNBgp9PpkNzFy8sLdBshlU57e3tiYiKdTh85ciSDwejp6WlubgbxHNC34HA4kFhFJpNVVlbKZDINDY1PSXpKVnwYsVgcExOTm5ubmprKYrG2bNkSHBw8depU6B4ymYxCoXzoBIpYLM7Kyqqvry8tLYU+CYM4n88vLS0tKioSiUQzZsyoq6u7fv26jY1NW1vbjh07+vr6AgICfvvttytXrmhra4vF4qamJhqNtmnTJh8fH8UuV11dnZubC9mNCASCQCA4dOiQgYGBhobG6dOnpVLp+vXrByS6gQzPXV1dNjY2GRkZMGq4urrm5ub+/PPP/v7+nZ2dq1at8vX1Xbt2bXV19eHDh8vLy0FmMiMjIyUl5eDBg6DUCmpujx49qqysnD9/fltb24ULFxwdHdls9p49e5qbm4ODg3fv3p2VlcVms3t6eoRC4alTp86ePZuXl/fdd99NnTpVIpFERkZqa2svXboUvIROTk6PHz++e/fuiRMnFBuZSCTKzMxsbm4uLS3V0tICXbaysrL169fr6ek9e/bM19d3x44dZDI5NTW1rKxMS0srKSnpzp07R44cgWys8uVtampqS0tLeXm5g4ODVCrNyMi4fPmyv79/TU3NuXPnJk2aFBwc3Nvbm5qaKpFIampqVFRUSktLt2zZAtIu69at+/bbbyHD+4c6QHV19caNG8eMGUMmkzdu3BgSEjJx4sQHDx4cP36czWZDjsz4+HhI8UalUgsKCgwMDA4fPkwkEoVC4cGDByFL1cmTJ3Ec37Bhg5GR0aNHj2JiYg4ePGhjY/Py5cvLly8fOnTIyckpNTV1y5YtGhoatra2DQ0N586d27p164QJE8rLywsLCysqKgZMt8G3sHv3bmdnZ21t7fT09IcPHx44cIBCody9exdmPNHR0dOmTRtgD6A9p6SkHDlyBPKONTU1vVe5XiqV3r9//8qVK4GBgdnZ2TExMUeOHBGJRIcPH66oqHB1dYVqT0tL279/P0xiQkNDeTyejo7OR72pkOkTxIHJZPKsWbM+OthJpdKXL1+Cd7G+vj4jI6OqqmrdunXvLbx8GHJ1db18+XJNTT1BWqUAACAASURBVI2JiYlQKDx//jxkGPzEERbu+6eO+xKJRDc3t9jY2JycHC8vL9BX9/f3H9CFFW8BYtEYht27d09fX3/dunXz588fkG7vE5cIaWlpfn5+H10i4Dienp5uYGAAA4JQKPzqq68+VAkSieT58+ePHz+WSCQwWSwrK1u3bt2nJ94nEon29vaDHwfyA9ra2sKyprq6+ujRo/39/SkpKTNmzPjhhx/evn373XffBQYGLlq0qLS09NixY0wm8/z585B8/tWrV56enhkZGSEhIR+VcsEUW/bjx49Pnz49ZswYgUCwYMECW1vbY8eOdXR03Lp1a/bs2QEBAfHx8UOsdOzt7SG7PSw8YeXr7++/cuXK3t7eGzduCIXCQ4cOFRcXq6ioGBoadnd3X7hwAbIxFxcXZ2dnBwUFrVq1Ki0t7eHDh4ObLOR8hmljWFhYSUmJn5/f6NGjZ86cmZKSMkAVD6ZIV69ehe8sWLCgt7e3ra2tqqpq8+bNsFYYO3asg4PDqVOn8vPzIedlZmbmiBEjAgMDR4wYcfXq1dLSUqlUeu/ePZFI5OfnB9nVJRLJ6dOnMzIyIPMi5KDu7e21t7d/+vQpjuMhISG+vr5aWlqOjo5paWnybOYFBQUuLi4wFltbW2toaHC53ISEhGvXrimWHNJOgeQe7OfDJG727NkzZ840Nja+dOlSX18fqBD39fVpaWnZ2dklJyfHxMQoXofD4Zibm1OpVEdHRw6HU1RUtH379hEjRnh4eIwbN87Y2PjkyZMgB2hgYAAJWVksVklJyYsXL1xdXSdNmgQD3NBjQXl5eWJiorOz88SJE4uKiqKjo0He+dWrVzU1Nf7+/pMnT5bJZBcvXvTy8vL397e0tLx69WpJSYlUKj1y5EhpaSm8oNmzZ8NLhIxySUlJlZWVoC2cnJwMmgd6enovXrxobm729/dfunSpTCY7deoUkUiEtmFmZiZXxFN0CrW2to4fP3706NGBgYHJycmhoaFKSkoTJ06EZejkyZPlWg4DXMBWVlaOjo6LFy+ur6+/ffv2hwYXEBX38/NzdXV98OBBVlYWl8utqal5/fr1yJEjg4KCPDw8IiMjKyoqJBJJaGhodXU1CFsOYWih8NevX58xY8asWbPCwsIsLCyCg4OHfhd9fX379+8/fPiwn58fjuP29vbLli0rKSlZt26dQCAASb5Hjx4N0HIAXZPe3l4+nw9JigwMDGB3HR48JibmvUsTSG159OjRbdu2zZkz5+ggwsLCPuRGh/clFovb2tpggBaJRHPnzoUEPtXV1aAnLL9RQkIC6O7Z2dl1dnauWbPG0tJyw4YNr1+/ht2OBw8eyCX2Pgpk+R16qj58+HD4JmzmXbp06auvvtLW1u7p6YmNjQ0LC4uJiYH5B3hHdu/efeLEiTFjxvT397u5uQUHB+fk5Kxbt04ikRQXFx89evT06dND6IIQ3pcj5L1/olAoY8aMWbBgAZvNPnPmDGTnTU9PBzloGFfBr97Q0LBz505PT0+QKf0URxOmOCEKDw93cHAAt8PcuXMDAgJev3797t274uLiyZMn9/f3nzt37kPFJZFI6urq4O8G1x6RSHR0dITEvCwWq6Wlpaen5/r16yQSKTU1NT8/38fHB3KpmpmZQbbeCRMmQFLcAbI5RCIR5N/U1NSYTGZVVdWFCxc8PDyMjY05HM6IESM0NTVv3rypqLUrlUqvXbvW3t4+fPhwDodjZWV16tQpR0fH69ev5+bmBgQEqKqq6ujoTJgwob6+HuS/GQwGg8EYM2aMra2tubl5e3u7XHrl2rVrkZGRjo6OY8eOlUgkkP0/NTX19evXbm5utra2ra2toMYDI+OyZcs4HM6kSZMcHR2TkpIEAkFtbS2TybS1tU1NTS0qKqqvr09PTycSif7+/oozCMhqAjmctbW15Rl4tLW1x48fb2trC/L0IpEoPT0doiDS0tKam5unTJkyQG6XRqNxOBwymQxGKzIysqamZtq0aRwOR19ff+zYsVVVVZGRkcrKykwmk0ajaWpqKikpOTs7Hzt2TE1N7cmTJ729vUPvGUDG+WPHjuno6MTFxUHGU8jtSqFQzM3NPT09bW1teTxed3f3mDFjwOHW0dEByWIvXLjg6elpYmLCZrO9vb01NTWjoqIqKyvBCkJ+LrmbGJoWSMc4OzuD/HpVVRW0DQKBAM6uAUPq5cuXVVRUdHR0OByOtbW1h4dHVFQUZB7FMExVVRWs4OBVxfnz54OCgoRCobe3t7KyMkgJvdelM2/evJ07dzY2NoJrqKuri8ViQa36+flBW2pra4PKuX379ogRI4yMjFRUVIben8MwzNHRcfr06SDK3dLScvbs2SF2tmUyWUpKyrlz53x9fX19fXt6elxdXYcPH25kZPTgwQM+n3/lypXq6mpTU9PY2NiXL18OsAcymezly5eNjY0XL15cvHgxi8USCoVhYWGw93vq1Kn3xr2AnK+Li8vUqVMt3sfgZMNydHR06HT6y5cvu7u7jx079uWXX4Krraqq6vLly2fOnJE/V0dHx8GDB4lE4uzZs1kslpKSkp+f35gxY3Jzc3Nzc3Ecf/z4cWho6HtHeRCiuP0Hd+7caW5uzsjIUPwElA8GoKqqimFYWVkZjuNRUVGqqqq+vr5SqfTixYvPnz+vqqo6dOiQXNQ+MTExIiJi/PjxPj4+XV1d7u7urq6u+vr6d+/eLS4uPn78eHV1dVxc3LZt2/7n4cWamprgmHVycqqvr+/v72ez2RiGicViGCHBoQpfbmlpAZMcEBDwKfvBZMU+kJ+fv2LFitra2u7ubhgRQHl4/PjxVlZWw4YN27t3759aEg7Y8wExmXHjxkHa1WnTpoGHDnq+kpISmUz+FN3E9vb2+vp6SPkEi6kJEybs2rWrtbVVnhcX8lzCZaHfenh49Pf3FxcXS6VSMLYYhllaWpqYmMjDS0gkEp1OVxxYKRTKpk2bNm7cePTo0devX+/evRv8dyNHjoQ4OflQBYEikH8Y/A9qampLlixZv359cnJyZmZmQEAAmUxOT0/HMExxA/Ojfj14RgqFojgctLW1sdnsqVOnwl4C7GEMMVgUFhZCPcODg/JPYWHh4NbW1dX18OFDU1PTj+aDA3FEPp//4MEDU1PTAVs4DAZDPqnBMIxOpysKo7e1tQ14iZMmTdqxYwdYIBqN9qFc7UMrmg146ubmZsUR1tjY+Pbt20PHC8EIkpmZGRYWZmNjIxKJwI326tUr+RtXrAFDQ8OIiIjW1lZFZx3MkBQfGfbS3r1794kx3JBaOSgoiEAgtLa2pqenR0ZGzps3D+at711PxMbG4jgeFBQkk8ni4uJ+/fVXqC4qlVpbWxseHv7w4UNDQ0NLS8sff/xRHpoBhodAIMDQPHbsWAsLC5lMlpqampSUtHHjRjabzWKxjh8/furUqQE3ZbPZIPE2xBbIh57O2NiYzWZnZmZGRUWBQDf8SU1NTU9PTx52Ba8jNTX15MmT2trax48f9/Pzo9PpMLbQ6XSQ32lubn7vUAs+HxDvg3+2trbm5ubKxQE1NTVBe2pwM3N3d8/Kympvb3/06NGmTZuYTCZo0Xz11VcYhh05ciQ+Pn7evHk4jkdHR5NIpMDAQKFQmJiYuGbNGriCkpJSaWnp7NmzdXV13717FxgY2N3d/T9Ms0ihUKhUqlQq/eiOupqa2tdff/3TTz/V1tbOnDnzUwLWyfJqKikp6enpUVFRAa2+/v7+5OTkSZMm6evrw3SPQCD8zwN+4fVAUDPII/f19f3ZCmKz2UwmMy0tDeqdQCD09/czmcwByY1JJBJoJxgaGsLuSHl5OaxI8vLyYH9CIpFIpdIhZjEEAoHL5e7fv//hw4cxMTG7d++G7YqUlJSQkBBY3nZ2doJo2uDO4Ovrq6SktGvXLhaLtWLFCjDgIpGopaUFCiCVStPS0jQ1Nf/C3l1bW1tTUxOYFhzHh1gvE4lEfX39Fy9eVFRUQOcXi8U4jsujO+QG+/z58zdu3Dh69Cj4mj4axHLp0qVLly4dPnzY2tr6T71H0ChPTU1dvXq1fMODxWJxudzW1lYMw2DP+X8IjUaD/TR5kkgKhTKEhIZ8Zbl582YLCwsDAwOZTObg4LB06dLw8PABAjLgqdixYwefz58/f76i7XkvTCaTQqEkJyd/YlA/iUQCzSIqlaqpqfnq1ash5GbB1ePm5qapqZmbmwup+YVCYXJyspubW2JiIqTIxzBMV1f39evXNTU10OxhBUylUuPj4/v6+s6ePUsmkyUSyc2bN/v7+zU0NKRSqaam5v3797u7uweswNra2oYO+ePxeIONqHzPlslkZmVlyWSy8+fPyzUjWSyWopsbZt/9/f2wCZeenr506VLQF6PT6SNGjMAwTC4x/95llq+vr/wEiVQqLSkp8fX1BRFNmC8Obrew462pqZmVlbV8+fLx48dDqBWZTA4ICDAwMJBKpcOGDYMeBzXv5eWlqqqalpZGIpHMzMyg5keNGuXu7g69W1VVlc/nf6bY5Q9ZjiVLlujp6UVFRYWFhZHJ5BUrVnySvwjCkGk0WkNDw4sXLywtLZOTk4uKilasWKGsrKykpCSVSuPj42H8lUgkd+7cSUhI+AvRVGZmZrdu3YqNjS0tLU1KSjp27NhfCE7Q1dW1sbF5/fo1dA8IThg3bpzisE4ikaZPn97d3b1u3brExMTk5OTIyMiOjg4fHx8ikQgbIRCE09TUNITllEqlz549c3d3DwkJCQoKysjIwDDM3t7+yZMnN2/ehKcIDQ0dIlIzICAgKytr5MiRsKzz9vYmEom7du1KSkpqamqKjIyE8Kc/VQkYhtna2vL5/JMnT758+bKkpCQmJmaIMwoYho0ePbq/vx+CMiGgSyAQBAYGDnjYO3fugDquQCD4qMCyVCq9e/duS0uLubm5SCT69LUwbAbY2NhkZmbKX2Jubu748ePhJcJ2GQQvEQgE+O+fhUQiBQQEZGdnw89xHM/Ozp44ceKAQW3AqJqbm1tYWBgcHOzv7+/u7u7u7j5t2jQHB4eEhAT5NFNOV1fXzZs3IRwFTjAN8cgGBgaWlpZPnz4Fd3xTU5P8AYder1RXVxcVFVGpVA6HA9Fxu3btgn2pAf0CBNpyc3MNDAyYTCZIq3///fcDBH4FAgHodcubx6hRo7q6uoKDg+UCUBAOp7i4GeyAlslkaWlpTz/As2fPsrKyhmiTvr6+3d3dQUFBA+IJB6CnpwfhniKRqKioyMHBITEx8ddff928efPgvZ/B1W5iYuL+B66uriwWa9iwYfBPNzc30A18b/GcnJyEQmFfX5+/vz+NRoM01PJwxK6uLtiUhpqvra2VyWQ5OTkmJiZkMhnGhO+//15XVxcm0y0tLV5eXtD2oJnl5OQM/d67uro+vU81NzfDxr68HTY3NyckJHz55ZdHjx5VU1MLDw//1PUBnIIJDg6+cOGCVCplMpm1tbU//PADzCVh+NDU1IQdMKlUGhkZ2dzcHBMTIw/MwDDMzMyMTCZv2LDB39/f19cXMhILhcK2trbW1lahUCiVSrdu3bpjx44tW7bo6uqamJh4eXkxmcyysjJ4crkacHJycldXl9yRArMJIyOjyMjId+/ehYaG/vjjj9u3bz9w4MDcuXNzcnLEYvGmTZsU7TyJRJowYcLatWsvXrxYVVWlo6OzdOlSa2trIpG4YcMG+cI5Ojp68eLFbm5unZ2dlZWVAoGgqKjI0NAwLy8PQtOcnJyePn3KYDA8PDw6Ojq++eYbCoWycePGjRs37tixQ1dXd9iwYV5eXmpqasnJyeCkAmk6uRtkxowZt2/fnjx5MogFOjs7b9269eTJk999952xsbGenl5ISMiAdOcQ5bly5cqZM2e6uLi0tLTw+fza2loVFZWSkhI4U+Pu7r5y5cobN26sXbtWR0fH2tra399/QIO2sbG5e/fu4sWL582bB2FUN2/e1NLS0tHRuXnz5sqVKx0dHYlEoq2tbUZGxtKlSxcsWKCvr5+ZmblkyRJzc3MrK6u0tLSDBw8GBQWVlpaC+0XR3QHLjoSEhGXLloG/GFxqU6dO7e/vLy8v7+7uhlOyQqGwsLDQ2Ng4Pz9fXv7du3dv27YtNDT0iy++gJe4ZcsWOp2urq6uoaGxdetWW1tbVVVVJSWlW7duzZgxA5zFJSUlfD4fdOh6enoaGhq4XK6ent7Zs2dLSkrkCfqhDaxdu7atrW3btm2enp49PT1KSkqbNm0iEomZmZkikai0tFTxiUC1bc+ePXw+n0QiyaXNJBIJg8Ho6uo6c+aMu7u7on+PSqVqaWk9ffp0yZIlPB5PV1f3woULEokE9OBKSkpAZgvakrOz8549e7Zv375y5UpVVVWpVMrj8XJzcxWbOgRk9/T0wAECiGN+8OABjuObNm2ytLSEFTbM4qF7yh92w4YN69ev37t3b3JyMp1ODw0NzcnJ2bt3r5ub24C4ALkYi/w9WlhYWFpa+vr6ypuionMP/jk4TJPL5S5dunSIOe+HwpQJfyirBwYGzpw5c4i4TAzDJkyYMGPGjB9//NHGxoZMJsfFxSUkJMybN+/rr7/+C2o2g/3YQ/jrNDU1v/322wHRWbABrqqqKpdA37p168aNG/fu3fv48WM2m71v376CgoLQ0FA47w1b/REREYcOHZJHip84cUIikVy6dGmwGQBxzerqagKB8Pjx4wkTJkDUKcgGE4nEd+/eqampgRJiaWmpl5eXg4NDWlpaRERES0tLUVGRQCBITU3V1NS8du3apEmTzMzMDAwMhgjk/f9bEegny4chdXX16OjoOXPmzJ4928vLC9TampqaUlJSJk+eDDvGsMhKSkqaNWuW4pCtpqZmZGRkYGAwatQoTU1NVVVVW1tbcOgzmUwPDw8nJyfQhIOQmGnTpnl4eNDp9ObmZh0dHRcXF5DDVFVVHT58uKWlpaLAL41GMzc319HRGTFihKmpqb6+voODA4VCUVJSolKpMIMbMKrS6XRra2tbW1s4/eDt7c3lckHO0MjIiEwmUygUQ0PDadOmqaqqdnV1wfLTwMAARD1h7mBgYMBmszkcjkgk0tTUnDJlCoPB0NfXd3V11dDQsLa2njlzJli1hoYGOzs7a2trTU1Nua8DqoXH4/n6+kK0Lo1Gs7S0tLe319HRcXR09Pf3Nzc3V4wrgN0IQ0NDQ0PDESNG4DiuoaHh7u5uZGQEfkNPT08DAwNTU1NbW1sbGxt9fX0vL68JEyZA5PKACam+vr65ubmbmxuI0Orr61OpVBKJZGFhMWXKFA6HA55cHo8HatVOTk46Ojqmpqbjx4/38/PT1dUdNWqUVCpVUVHx9vbW1dVVDM2EKBHQaoYYHh0dnVGjRmEYZmRk5OLiYmJiIhaLlZSUoGKhnt3c3AwNDS0sLPT09OQvkUKh+Pv7Q4gag8EwMzPT1dV1cnIaO3aslZWVv7+/gYFBQ0ODubm5k5MThEUymUwvLy97e3t1dXUzMzM9PT04xDBgVxAUhul0uoaGxrRp02xtbUUiUXV1tbW1tbOzs7q6uqI9aG1tlclkbm5uoO0q94ooKyt7e3vb2NiYmJgojnFUKtXc3NzQ0NDOzm7s2LHu7u6mpqaWlpY8Hs/LywvaUk9Pj5ubm4ODg56enr6+vqOjI5PJ1NXVnTZt2uzZs319ffX19RWP7NTW1tLpdHd3dzs7O4g65/F4S5YsmTBhAgg6icVikUjU29s7adKkAesDIyOjpqamO3fuLFiwwNTUNCAgwNPTk0qltre3x8bGbtmyBcOwqqqq+/fv79+/f8BevZeXl3zgg4GmrKxsxYoVMpksIyOjoaFh9erVintUsEcC04sPMYQCFWyzOTs7w3EixQGxsrIyNjb2+++/lxsVOAh1/fp1MFoQqyZvijiO//zzz6NGjfqoHiSO41evXl2zZs2neCNpNJq6uvqsWbMGOAnLy8vv3bs3d+5c+bJGT0/P0NCwvr4+NjZ24cKFZmZmAQEBHh4eFAoFTO+5c+csLS3HjRsHLxoshLGxseKek5zOzs6mpiYbGxsfHx8ejyePK2lpaVFTU/Pw8AARULFYDO1fS0vL3Ny8oaFBKpV6eHi4urrCYKumpgYukMLCQhUVla+//vqjW8r/l/4BtMXZs2ffu3cPWgY4x1esWCGVSkeNGiUQCCDkEUJTNm7cqGhpIe5KLBZzOBwcx8GlDp0HYjPAYQJ/IpFIYEvgV7CNTKfTMQyD7X7wUyleXCQS8fl8FosFjRLWUziOyy/13jUX/EpFRUXuoIe9BEhvAHeBk2twAp5CoSgrK0PhQc24v78fIsGpVKrcREHYA5FIlB+t6uzshMqk0WiKe57gZVb0UcgLoHjBwXMEENru6+sDvw3st0Ox4ZHlxVZSUnrvlAdOt2EYBm9B8THhwIv8a52dnVQqVVlZGf4fwzA499DV1cXhcHp7e2E6SaFQBkfjQD2AK6Ozs5PNZvf19cGcEUo1uGJhagm7L/ASMQyTy/kqPhedTofag2qEYsAJJlhKs1gsMpkM31d8ywMCMfv7+6HwsKbu7u7+PwtkMllRIlggEAiFQsWXKJPJhEKhfNk+uFnKXyWDwejv7xeJRBQKBb4P4RhwL8ULwiNzOJzBfkJ49QNm3AMqRyAQ/PzzzyoqKgPy/EBRk5KSZs+eXVxczGQy5YfgysvLZ86cee3aNWtr659//rmgoEAewCM/uED4Q7sRxs0XL16sWbPm999/19DQWLt2rbW19cqVK/9G7zacKpBIJANc/7A38M033yhuKYP3Y/To0cuXLw8KCmIymYq/EovFzs7O27dv/+KLLz7q4QwPD1++fPlH98bgzXZ3dyuG/0Fcxo4dO7766isLC4vW1lZtbW0TExOo+SdPnixatCgvL4/BYMhrvq+vLywsTCgUzpo1i8ViVVRUTJo0CRozgUAY7LqUD1mK205UKlXejKEtUalUuAKdTgd/PkRX6uvrwxWYTCaJROrq6uru7pZIJDQajcfjfXyTUqaAWCx+8ODBF198If8ERoTg4OCgoKAVK1b88MMPTU1NcBC3uroax3EZAoH4zyKRSK5du9bY2Dj4T1KpNDU1dezYsYof4jguFAofPnx49uzZBw8enDhxAlwNQ4DjeHd3d2Rk5NWrVx8+fHjkyBHY7fjcQFFDQkI4HM6jR48U/yQSiVxdXUtKSgY/ckJCgpaW1qJFi/h8/kev39jYCL6vv1A2gUAwadIkFovl4+Pj4+Mzffp0ebVAMaZNmzbgTUVEROjq6lpaWvr4+Pj6+l69evWf3LT+r/UBDPRtbW3yVQzUQlVVlXzSZGRkRCKRxGLxZ0ouiEAgPiWO9r1HjmHfNS0tbe7cuYNnnbW1teDB0NPT+6jnHeawbW1tIOP+1xLy/IVHgwyv7e3t4N5UnNqfOXMmODh4sEJqQ0MDHCl1cXH5TDk25GVLTEyUx8QzGAwvLy+4o0wmq6ioyMvLg00F+U/KysrkRzcgNPajSaX+H4L0MhGI/ypTIRaL+/r65P6l/6ZHa21tHZxZ5J9TPJFIJBQKPyVNELIHCAQCgfhHg/QyEQgEAoHsAQKBQCD+y+wBhFU8efIEub8QCATiX20PIIXIli1bBhyqRCAQCMQnQv7veAw41G5qagoHfCAgj8/nD1DLQiAQCMR/+foAwzBnZ+dZs2bBkdeGhoYNGzYoyiEgEAgE4lPXByKR6Ny5cxKJZNmyZbdu3WptbQVlmPT09La2tqlTp7a1tUVFRYHYQmBgoDzbASCVSp8/fw5n/wgEwrx580gkUkVFxfPnz3V0dGpqar744gs2m/327duHDx9aW1u3tra+ffuWy+XOnz9fMQ8dJKGMj49nMplz584tLCxMSUkhkUiTJ082NzfPzs5OSkpauXJlVVVVZmYmlUrt6+tra2ubPn16S0sLJE8WiUTbt2+/e/cuh8Oh0Wg+Pj4CgeD58+eQRtTLy8vT0xO9eAQCgfjg+gBkwV++fAm5pU6dOgXn8dLT0/Pz8zs6OrZt22ZmZmZubn7lypXr168rXgXEgZ8+fQrJ4/bu3RsbGysQCDZv3kyj0aysrF69enXkyBEcx1+9enXy5Mn169dnZGRUVlYePHhwgFokgUCg0+mRkZExMTHKyspaWlo3b958+vQpZBERiUSvXr2SyWTx8fE7d+48cOBATk5OVFTU8+fPw8LCoMyQrE0gEBgYGFhYWEgkkqNHj+bn51tZWTU1NW3YsCEjIwO9eAQCgfigPSCRSK6urunp6QQCwcfHp76+vri4GLKVjR49uqio6Pbt2xiGCQQCkUh0+vRp+Q8hAWp4ePjo0aOtrKxsbW0tLCy6urra29u7u7stLS0h+V90dHRnZ+fw4cN7enrYbPbixYuDg4NramoKCgoUCwQplJ2dnUtKSjo6OnR1dV1dXbOysnAcB63w4cOHk8lkLy+vqqoqGxubpUuXHjlyZOTIkSDeAA9iY2MDqo2ampr5+fn37t0zNDRkMBgqKiqvXr1KTk5GLx6BQCCGsgceHh4EAiExMbGzsxOS1EOGPxsbm6SkJA6H8+bNm1evXjk6Orq6uiouLDIyMiD5KplM5nA4oaGhEydOVFNTO3DggJqa2pUrV548eVJbW9vZ2cnj8SgUiqamppWVlZmZGZFIVMzDTvgjO/mqVatAI5BIJJaXl3d0dDx8+FAgELx48QI2CfT19eG/lpaWkEtZ8YA+ZBSB3PEFBQUNDQ01NTVZWVkSieSLL74YIAqGQCAQCILi/oF8Yp6WlsZisSwtLe/fvz9jxgxIu9/W1gaqv5BrWjEZFugJd3Z2dnZ2Kisrk8lk0JYTi8UZGRmdnZ0jRowYPnz4q1evPjEYFJQobG1t79+/b2Vlpays7OXldebMmb6+Pg0NjT+VVwvH8devX5PJZD8/P0jUDJmZ0YtHIBCID64PQEBm3LhxV69eTU5O3rt3b3NzUXOLwgAAIABJREFU886dO0ePHg3aZ42NjSKRyNTU1MjIqKWlpbGxUf5bJSWllpYWUFIFPYPHjx+npKSEhYWZmJg4OTkNrYc32B6AunpMTMwPP/ywZMmSL7/8Mi8v7/jx4998882fUkQiEolGRkZtbW3l5eWmpqYmJiba2tpD6EoiEAgEWh8QCAQCmUyeMmXKpk2b5syZ4+vra2lpKRQKzc3NMQxzd3enUChhYWELFixob2/Pz8/fsmUL/IpEIo0cOVJTUxMkQ7W1tZOTk83MzGg02rt373Acr66uBr3iwUBs6ODPSSTSzJkzz507R6VSR40a1dPTY25uTqPRQCbpE1cGOTk56urqPj4+EonkxIkTfD5fR0fn5cuXioqPCAQCgfg/A69cL1O+ROju7p4/f76Ojk5HR4erq6ubmxuBQGCz2Twe7+HDh8XFxRKJxN/f38jISP4rJpNpbGyckpJSVlZWVFTk6Og4adIkEokUFxdXWFiI4zjISdLp9N7e3uTkZNDJA5lQmUw2YcKEwTpBKioqUqnU39/fysqKRqO1trZOmDDB2dmZSCRKpdIbN26AxLG5ubmWllZGRsbt27dlMpm2tratrS2DwaioqCgpKQG5RyaTWVhYWFhYmJ+f7+Dg4O/vP4SiOgKBQPw7GZjvGiRxNDQ0KBRKY2MjhUKBQE8QxygqKiIQCFwu19DQcICmKAimi8ViEolkaGiorq7O5/Nfv37d1NTk4OCgpKTU2NjIZrNZLFZtba2ysrKhoSGRSCwoKAA998Fyj3DGmMlkgjhifX09g8EAcUpYczQ3N5PJZCMjI1VV1dbWVtBr09bWNjAwwHG8vLy8s7NTV1dXV1e3vb397du3IpEIwzBDQ0MNDQ1FvVYEAoFAED6r/gEcXxCJRIrHzRAIBALxr7MHCAQCgfhfBNI/QCAQCASyBwgEAoFA9gCBQCAQyB4gEAgEAtkDBAKBQCB7gEAgEAhkDxAIBAKB7AECgUAgkD1AIBAIBLIHCAQCgUD2AIFAIBDIHiAQCAQC2QMEAoFAIHuAQCAQCGQPEAgEAoHsAQKBQCCQPUAgEAgEsgcIBAKBQPYAgUAgEMgeIBAIBALZAwQCgUB8DsioChB/AZlM1tHRwWazSSTSP7aEQqEQx3EGg/HPLF5vby+NRqNSqag5Id7bQkQiEYlEIpPJMpmsvb09Ozubx+NZWVkRicTBX25ra5NIJIofqquri8XiP9UF0PoA8VdaanNzc1BQEJ/P/8cWUiqVHjp06P79+//M4onF4pCQkIKCAtScEO/tYjU1NUlJSWKxWCqVnj9/fs6cOSEhIfPnzz927NjgL9fV1QUEBExRYMaMGR0dHV1dXcePH+/s7ET2APG5wHH89evXOI7T6fR/8vLl7t27jo6Of+0B8/LyHj9+/PkqsLy8PD8/39DQEDUnxODW29DQsGHDBi6XS6VSq6qqSktLt2/ffvLkSVNT0+PHj1dUVAxoTtHR0T4+PqGhoaGhofv373dwcCCRSCwWi8vl+vn5HThwoLu7+1NujfxFiL/SXnNzc7lcLpn8z20/nZ2dFRUVOjo6f+0Bc3JypFLp56vAsrIyiUTC4XBQc0IMXtqeOHHCzMzM2toawzAmkxkcHGxkZITjeFFRUWxsbG9vr+L3iUSij48Pj8dTVVWFn0dHR/v7+9NoNAKB4OTkdO/evd27dx85cgTZA8TfOYr19PRERkaWlpbev3+fw+GsXr16xYoVNjY2n++O3d3dz549q6ys9Pf3NzMz6+3tvXbt2siRI62trT/Ulx49epSWlpaenk4ikZYvXz59+vQ5c+YMdrkOfd++vr6+vr6PTvPz8/MfPXpkbW3t5+dHp9OfP3/e0NAwf/78D11WLBZfv349Ly8vISGhp6dn2bJlQUFBvr6+qHUh5I0qNzc3Kirq+vXrysrKMplMTU1NU1MTwzCpVCqRSNzc3ExMTAbYAysrK9iIkslkb9++TUlJWb58ObR5JSWlJUuWeHl5BQYGuri4DH135C9CfGozLSgoWLx4cXd3t4+PT39//5YtWxgMxsqVK8vLy3Ecr62tjYmJSUlJkclk7x1ebw3Jo0eP3mt+Nm/e3NjYaGVldeDAgZKSkuLi4uPHj3O5XHnPycjIkH+fz+dv27bt2rVro0aNkslkgYGB/v7+R44cuXz5snz4Tk1N/cTnTUxMHMJgSCSSu3fvnjx50tbWtqys7KeffhKJRCdPnmxubpbJZP39/Q8ePLhz5458KgdOgDVr1mRmZo4ePbq3t/e7775zcnL64YcfEhMTpVJpQUHB7du38/LyPt+6BPG/Ytb1+++/q6io2Nvbw1hPoVCIRGJ/f/+VK1ciIiJsbW2VlZUH2AN5VAKO4y9evGAymZaWlvIv6OnpdXZ2PnjwAK0PEH/bPH3Dhg29vb2zZs2qqqpSUlKaOHGiurr6yZMnMzIyqFTqunXr9u/fHx8f/+7du3nz5g2+Qnl5+atXrxQbsaGhoY2NjVAofPbs2fDhwydOnKj4E4lEsnXr1jdv3mzYsIHD4dy9ezcsLIxIJLq4uGhoaMAe2ubNmy0sLNzc3GBlEBERcfPmzd27d7u6utbU1KxatQqcqrdu3Vq4cGFjY+O2bdt4PJ6np+enPHJHR8cQf01OTt68efPWrVtHjhypoqISGBiop6eXnJwcHh7O5/NDQkIEAkF7e/vly5cvX77MYDDEYvGePXtevHhx9uxZbW3tpqam6dOnKykpbdiw4dGjRxUVFY8fP5ZIJLW1tTt37pwyZQpqdf/aiVdycjKdTlfcnJPJZFlZWTExMXV1dffv3x89evQXX3zxoWnKw4cPx48fr6SkJO9oGIZNmjSpvLwc2QPE32MPSkpKkpOT9+/fb2hoeP78eV9fX2VlZS6XK5FIent7d+3aZW1tbWRk5Ovr+9VXX1lZWTk4OCheQUlJaeHChf7+/oof0ul0JpOJ4/ioUaNUVFQG9Iq8vLybN2+uW7dOX1+fQCBMmjRp8eLFSkpKEREREIHH5XL19fVbWloIfwTn3bhxw8DAYMqUKQUFBWKx2NPTU1lZmUajQRwUm802MjJ69+7dezthdnb2/v375c9bVVVVU1MTEBAAn5BIpK+++mry5MlyW3Xq1CkWizVlyhQmk2llZcVisbZs2eLt7a2lpfXs2bPx48c7OTm1tbXNnTu3uLjYxcWFz+dHRUXNmzfP2dn5xo0bNjY2PB5PJpPBMqiysnLz5s0kEungwYOxsbHIHvyb6enpGfAJeIT27t375ZdfBgYGRkVFvdcewG+fPXu2fv36AT9XV1ePi4tD9gDxNyCVSmNiYmQy2fz588FLM3PmTJlMlpmZiWGYjY3N3r179+zZQyKR9PX1GxoaCgsLFe0BkUgkEond3d0D4t4U/ykUCvX09BT/2tbW1tHRYWpqSiKRpFIpjUbr6ekJCAjw8fGBa9JoNFVVVRjrZTJZUVFRXl7egQMHGAxGQUEBj8dTU1Orq6urq6tbvXo1fF9NTe299oBIJOrq6np7e8vNA4ZhXV1d8k8wDFMMVYLljo6ODniuMAyjUCi9vb0//vgjhmEuLi5UKpXJZAoEAvCV4Tj+6NGj3t7eefPmUSiUN2/e2Nvbk8nkjIwMHMenTZtmbW2tp6cnlUqNjIzKyspQk0MMaJ8cDofNZg8bNmzixIkpKSkfWls8evRITU1twAYD8CknXZA9QHxSc1RVVcVxvK2tjcPhZGVlHTt2LDc396efflq5ciWJRGppaSGRSLAyxXE8KSkpMDBwgEWJjIz8UDsmEAi6urrXrl1THHBxHJfJZCQSCYbUX3/9lUwmr1+/nsVivfcKsBRoa2sDF+rIkSP5fP7evXv19PQG+68Go66u/uWXX8pLC/4o+ScEAmFALJBUKsUwDHb5nj59WlVVFRwcbGtrSyQS1dTUCH/sHmtqampra8OHcGgIHAIbNmyoq6vbs2ePv7+/h4cHXFwqleI4bmdnJ6+E9vZ2qHzUCP890On0ARFE8m5Io9E0NDT8/Pzka2IymSw/E4rj+I0bNxYuXDhgtS2TyUpLS0eOHInsAeJvAMOwadOm3bx589ChQ9bW1kpKSjk5OWfPnh03btzq1aurq6sVt0BlMllXV9eAK5BIpCVLlsyZM+dDt4DYOMU7mpqacjic+/fv0+n02NjY7OxsiJ2ora0dM2bM4K5iYGDwzTff3Lhxw9zcPCUlJSgoaOvWrdXV1SdOnNDV1f2owSORSPJhVyKRKCsrUyiUDw3EGIa5ubk9f/48Nja2o6MjLCyMSqX29fVdu3ZN0aiEh4fv2rVr2LBhsO0xefLk06dP9/T0NDQ09PT0rFmzhsvl7t69G3ovjuMlJSUCgWD16tVwBbFYvHr1ahzHIyIi/pmnrBGfo6+NHz/+0qVLPT09LBZLJpO1trbm5eU5ODioqqrW19cXFxcfPHgQjt/v3LmTRqPt2bOH8Edk0Zs3b9asWTMgawAEiIeEhCB7gPh71gfGxsZnzpy5devWL7/8wuPxmpub16xZM2LECB6Px+fzYUYsH/rHjx8/uJW/dw07BHp6evv27bt9+3Z4eLiDg8P58+d//fXXCxcu/Pjjj+8tobKy8urVq9XU1KKjo1tbW0kkkp2d3dKlS62trf9CUg0Mw6ysrD70VxKJ9P3334tEohMnTri4uKxevZpGo/30009OTk5yYxAXF0elUseNG0ej0WC3IzQ09Pr16xcvXqRSqbAz7+npaWxsTCQS4cj39evXv/76ax6PJ38oFRWVJ0+etLe3I3vw77EHc+fOPX78eFFRkZubG0ztN27cyOVyDQwM1NTUDh06BK5LsVicn59vYGAgH/R7e3vt7e3d3d0HOJEKCwu1tbU9PDyQPUD8PfaATCY7Ojqqqandvn178eLFM2fOZLPZEAKho6Pj5ORUW1srk8laWloYDMbo0aP/53ekUqlffPGFt7e3VCpVU1NTV1c3Njbu7e01Njb+0K90dHS++uqrlpYWZ2fnRYsWKSsrczgcDMP+WgEg4O9Df7Wystq3b19XVxebzVZVVcUwzMHBAYZyqVT6+PHjly9frl69mk6np6enu7i4kEgkc3PzpUuXZmVl+fv7z5s3j8lkslgsuTHYvn17SEiItbV1Q0NDX1+fiYkJ+MdkMpmGhgZqhP8edHV1169ff+7cOTc3NyKRaGNjs3PnTrFYbGZmpqSkZGRkBE5UZWXlo0ePKsYRmZmZnThxQtFZBIv1w4cPb968+aOrZGQPEH9ifCSRSDweT0VFZdSoUfI5LIFAoNPphw8fvnTpUnZ2dnZ29saNG//aqeDBd2Sz2Ww2W/6JfCpE+COcPycnh8PhVFRUmJiYwOkbVVVVNpvt7e09YHdaJpM1NTW9fv2aQqGUlZWZmZkNcWsSiTR9+vQhjrCBgRyQbQLsB+xerFmzpq+vLz4+HlZLrq6usKmuoaGhrKw8ZswYeRXBYYVly5YlJCRkZ2dTKBRlZeWrV6/Cpd69e7dw4UJ5n0f8SzrawoULDx06lJKS4uXlxWazx40bNyA9DLRAxSUskUhkMBgDGjaO4/fu3XN3d58xYwaFQvn43QefHkIgPoRYLN61a9f27dsV3f0QNFlTU9PZ2amsrKylpTVgO+tzAMNoVVUVlUrl8XjyEzoQCqWhoTFg9ww236qqqshkso6OzoATPYMvLu9jf7ZgOI5XVVW9fPkSfgvhRhYWFvBPCFQNCAiAIFrCHzHj0dHRQqEQbAaXy50wYQLE1HZ2diopKf1j80QhPlPbJhAINTU1lZWVw4cPZzKZf/k6tbW1NTU1FhYWqqqqn9KYkT1A/LkW1tTUpK2t/d4/CYVCCoXy/zapESyQqVTq0CP+Zy2ARCIRiUTyT5SUlOQbGLA9qJj6CTqgYm4MMpk8YHcd8e80Cb29vXQ6/S93KJgz4Tj+6X0B2QMEAoFAEAgofxECgUAgkD1AIBAIBLIHCAQCgUD2AIFAIBDIHiAQCAQC2QMEAoFAIHuAQCAQCGQPEAgEAoHsAQKBQCCQPUAgEAgEsgcIBAKBQPYAgUAgEMgeIBAIBALZAwQCgUAge4BAIBAIZA8QCAQCgewBAoFAIJA9QCAQCASyB4j/veA4np+f39TUhKoCgfjfZw8kEsm5c+emT5/e39//WYeJtLQ0f3//FStWfKbrFxcXh4SETJs2LTU19VN+IpPJamtr582bd+7cuf+aVy6TyQQCQXBw8KZNm/7zlqC0tHT//v1PnjxZsGDB77//Pvg7Uqn08ePHU6dO3bJlyz+5GqVSaXR09NSpU/fu3ftfP0zIZDKhUPjLL79MnTq1vb39P1C3ERERU6dO7ejoQGP0P84eEIlENTW1xMREHMc/X1GIRKKZmVlPT09GRsZnur6enp6JiUliYmJra+sn/opEIpFIJCqV+t/01olEIoVC+c8/lFQqvXDhAoVCmTdvno+PD41Ge0+LxDBnZ+e3b99mZ2f/o3sOhnl6ehYWFhYUFPwbRoqenp60tLSEhASRSPQfMD9ZWVkJCQlisRiN0f9Ee2BkZPSZ3g1M269du0YkEhkMBpVKlUgkn2kQpNPp5ubmIpFIJpMN0RZramrkCwJ1dfWDBw9Onz79f/v8rqur6/Dhw/BPKpW6devWVatW/YfL0NDQEBkZSaPReDxeSEiIu7u74vQzLCyMz+cTiUQVFRUMw/5CM5DJZL29vaGhof8Zm8rlcmUy2Wdqrv80VFRUeDyeWCweou/8jXC5XGQM/vOQ5YNyQ0NDTk6Orq6ugYFBSkoKhmHe3t7KysrJyclWVlYUCoVAIHR2dsbHx2MYNnLkSCaTKR/Nq6qqOBzOiBEj4JPs7GwGg9HZ2dne3u7m5sblct++fVtYWEij0caOHTvYgfDNN9+MGTNGsVe/ffs2KSmpvr5+wYIFurq68tnls2fPpFKpjY2NgYHB4LlnRkYGj8d79+4dn88fOXIkg8Hg8/nPnz/HMMzDw4PL5RIIBHgQxQLU1NQUFBQYGRlZWVmBgyg4OFhHR2fZsmVEIpFEIonF4rKyMhcXl6ysrObmZhKJNHbsWAzD8vLy6uvrHRwcdHR0cBwvKSmprKxks9ne3t6Dy5aZmamhodHQ0NDZ2UmlUseNGyd/fIFAQKFQampq7OzsdHV1m5ubk5KSnj59OnnyZG9vbzU1NbhCSkqKsbFxSUmJQCBgsVg+Pj6KT5Gdnc1kMs3NzRWfC8Ow/v5+KPzWrVvT0tImTJhgb29PIBDIZHJOTo78dUil0vT09M7OzmHDhtnY2MBb6OvrS0pK8vPzy8rKUvwTjuNlZWXl5eUDiqH4Bru7u1+8eIFhmJeXF5vNlslkjY2Njx8/bm5uLiws/P33321tbeHR4O7Hjh07ffr0xIkTra2t5RcpLS1NTk7u6elZsGCBuro6fCgWi+Pi4ohEorOzs7a2tuJN+/v7t2zZ8vDhw0WLFmlqatbV1eXk5BCJRFtbW7FYXFxcTCQStbS0nJ2d6+rq8vLyPD09ORwOFADauZaW1nunLFlZWRwOp6Wlpb29nUQiTZw4UfG+BQUFycnJUqk0KCgILghVVFFRYWFhYWJiIr9OcnIyn883MzMzMzOTf/jy5cuenh5jY2NLS0v5h+np6TiOQ5/622dgz58/FwqFfn5+SkpK8ElBQQGGYZqamhkZGRiG+fr60ul0xRKSSKT3ruf+riLFxcXBWCFfvxL+cNjm5uZ6enrCn+DDxsbGrKwsDMPGjRtHJpPROP432wMY6zds2PDDDz+oqqqeOHGCwWCMHTtWLBbv2rXrwIEDDAZDJBJ9++23np6eFy5ccHV1/eWXX2BO19PTw+Pxrly5Ym1tff78+fXr1//+++90Ol1HR6empuby5cv379/v6uqSyWSXL18OCAhYt26dfFCWSqX37t179epVf3+/s7Ozr6+vTCarqKhYuXKlr6/v3bt3ExISrl69yuVyq6qqduzY4erqWlNTs2XLlm3bts2ePVte+P7+/m+++SYtLY3D4XC53KampgcPHhQVFcXFxTGZzOfPn1+8ePHcuXMsFkvx4fv7+5cvX66srGxhYfHzzz/7+PisXbs2Pj4+KSlJW1v71q1bI0eOjI6OPn/+vI2NzcWLF1taWtauXTt27Njx48fLZLLOzs7Lly/7+voKhcLz589TqVShUHju3Lm1a9cuXbqUSCTK77JixYqkpCQ2m62hoSESiRoaGhYsWPDdd9+dPHnyypUrEonE2Nj47du3R48eJRAI69evDwwMDAkJOXPmzL59+8LDw21tbefPn5+Tk6OpqamioiKRSOrr61etWhUSEkIgEHJzcw8fPuzr61tcXPz27dvly5ePGjXq3LlzP/30E4Zh2tra5eXlc+bMSU9Pf/fuXVxcnLKycllZ2f79+wUCQWZmpkwm6+jo2Lx5s6GhIYPB+Pnnn52dnTdu3Jifn7958+bS0lIrKysCgVBXV0cmk58/f85kMjMzM0NDQ7dt2/bs2bOkpKRt27YN6Nupqanh4eFeXl7t7e2hoaGhoaEeHh59fX21tbUymay9vf3du3cD7BnY2pcvXwqFQhsbGxzHX716tWnTphEjRkRGRiYmJt64cYNCoRQVFcXExLBYrPT09DNnzpw7d05HR0fR7qanp7e1tSUkJDg6Ompra+/cubOrqys7O1sgEJw4caKhoeHGjRsEAoHFYh08ePD69etSqfTRo0d37951cnK6dOkSiURau3atnZ2d/JpisXjt2rVxcXEMBoPH4/X399fX18+dOxe2N3AcT0hIIJPJLi4uFy9eTE5O/u2338Ri8YkTJ0pLS+3s7MLCwmbMmBESEiKVSs+ePVtaWvr111+HhYUtWLAA6mf9+vXm5uYCgWDr1q1ff/31mjVrOjo6goODx40b197evmvXridPngyeXty8efPp06dkMnny5MlTpkx58uTJiRMnbt26BbO0IdZPzc3Nq1atcnZ27u3tDQsLO3LkiI2Nze7du6OiojAMs7a2bmlpeffu3erVq7///nscx5OSki5evOjl5dXS0hIREfGhNdn58+ezsrJ4PN6CBQtsbW337dvX1dUF7fmjLsQbN26kpaWZm5v/+uuvXC73+++/NzIyIhAIEolk4sSJWlpa9fX1VCr12LFjI0eOxHH8/v37ZWVlVCr15s2b8fHxu3btevz48YEDB0xMTH755Rc6nZ6UlLR///7Tp0/Lp0eIP7HElslkOI53dHS4urpu3bqVz+fv2bPHzs6us7NTIBAEBgb29PTk5ubSaLQXL140NDSsXbt22LBhEokkKSlpypQpVVVVdXV18+bNY7PZiYmJmZmZJBJpwYIFJSUlMTEx9+/fnzBhQmNjY319/aJFi3R0dOrr62V/IJVKy8rKSCRSSEhIe3t7X1/f+PHjhw0blp2d3dDQsGPHDhaLVV5e3t/fv2bNmhMnTjQ3N5eVlVEoFA8PD5kCEonk/v37ZDL5u+++Kyoqun//fl1dnaura3Z2dmNj4+XLl1ks1vXr1yUSye+//06lUmNiYmQyGZ/P19XVvXfvHtzL09Ozu7u7trZWU1NzxowZbW1tIpHo3bt3lpaWEydOxHG8paXFxcXFzMysr69PJBIdOHDgxo0bYrH42rVrgYGBzc3NdXV1EydONDAwkEqlimV78uQJmUxeuXJlWVlZQUHBmDFjYB1TWVmprq7u6+tbVFR079695ubmoKCgZcuWdXd3SySSgoICW1vbhQsXikSiK1euUCiUnTt3lpWV5efnOzg46Ovr8/n8goICd3f3GzdutLa2lpSUzJkzx9XVtaGh4cmTJxiG2draZmVl/fbbb0VFRaNHj7awsGhqahIIBM3NzTNmzNDW1sZxXCgUrl+/fu3atY2Njc3NzfHx8RoaGhEREZ2dnStXrqRQKI8fPy4pKQkPD6dSqdHR0SKRaMmSJXPmzOnr66uqqjp06JDii8BxvK6uztHRMT4+vqWlpba2dsWKFY6OjnV1dUKhMD09nUwm7927t7W1Fcdx+a9gqkGlUqurq3t7e4VCoZ2dnYODQ2FhYWNj4/Lly1VUVLq7uwUCgaenZ0JCQlNT08OHD5WVlcPDwxVvLRQKZ8yYoaOj09bWBu9o27ZtVCq1oqJCJBIdPXqUwWCkpKRIpdKEhISZM2cKhcIHDx44Ojq+efOmpaUlMzPT09Nz9uzZ4FGUN1GYHS9evLisrKywsHDKlCmampqlpaVCoXDYsGGenp4lJSUNDQ3z58/ncrnQTjQ1NTdu3NjQ0LB06VJdXV2BQNDb28vj8S5dutTX1/fo0aOHDx+KxeKjR4+uX7++oaGhurra2NjYzMysqanp3r17NjY2UHtz584dUL1isTgiImLUqFEFBQVv3rzx9fWtrKxcunTp6tWrJRIJjuPNzc2HDh1KTk6WDUIikURERLBYrIyMjOrqaj09vZUrV+I4XlFRQaFQpkyZUlZWlpOT4+Li4uTkhON4ZWWlra0ttK7a2tqFCxdSKBTF/ovjOMQmrFixoqysLDY2dsaMGQ0NDQ4ODnfu3MFxvL6+fvfu3YGBgfv27WtqahpQHqlUev36dTc3t/z8/JaWlpSUFDs7u8WLF0skkh9//BHDsKCgoMzMzKioKDU1NR8fn46OjqysLHd394aGhsbGxi1btqiqqr5586aqqkpfX9/e3r67u1sqlWZnZ8+aNUsgEMgQfxJM0bc+fvz4Z8+e4TgulUrfvn3b0NCQmZk5fPhwZWVl2ECzt7fX0NAYM2aMUCiEqX12dvaWLVt++OGHhoYGU1NTPp+vo6NDJBKhcfv6+v7yyy+VlZXff//9unXrqqureTxecnKyohNWXV2dSCSy2WwulwtzahaLBc4E8CFKJJKOjo579+7dunXr22+/3b59u7W19YC9UCKRyOPxiESiubm5hYWFr69vdHR0RUXFvn37vvvuu6ioKBMTk8ExRRQKZfv27X5+fn19fQUFBQXF5uzCAAAgAElEQVQFBW1tbVwul0wmM5lMVVVVCoWirq4OqxkikcjhcJYvX15XV5eZmYnj+Js3b7y9vSUSybFjxwoKCr799tt169bx+XwNDY0Bzwh1YmZmZmpqamFhsWrVqtbW1tu3b2tpaZFIJD09PQsLizFjxlRUVDx48MDLy4vFYmEYZmRkZGRk9PDhw6KiIng6S0tLuMKKFSuamppu3rz5008/kUikKVOmqKqqGhkZjRs3Lj8/Pzo6evjw4VZWVmpqavb29v7+/sOGDYMNZE1NTSUlJRUVFQaDAcVrbGy8ePGijo6OlpaWurq6s7Mzj8cLCwtjMBgcDgfDMCcnJ1NTUzs7O5lM1tPTA9vyz549CwsLo9PpixcvHjDdu3btWklJiZ2dnbq6Oo/HmzVrVmFh4bVr16hUKvhSGAyGmpqafP0EKCkpgUceCgYNw8LCQlVVlcPh9Pf3SySSmJiYwsLCU6dOffvtt+fPnzczM0tLS1OsZyKRSKVSMQxTVVWl0+kkEikoKIjH4z169IhIJPb09PT398fHx8OaYPny5QQCITQ01MXFBdqbjY2Nk5NTXFxcenr64NdnamoKlb927dr29vaoqCj4q7a2tpmZmZqamoqKilAoBFd7aGjosmXLurq6SkpKWltbZTIZeGP27duXmJjo4eHh7e3d19cXHR399OnTdevWbdq0SVVVlcvlSiQSEolUXV29a9cuMpk8YIotk8kyMjJ27tw5b948S0tLCwuL/v7+bdu2PX361N/fn0QiwQogPDy8trb2vXvgkydPPnz4sKWlZW5ubnd3d3t7+//H3nvGRZF0faD05BmGDEPOSBBUgoACZkSCIhgBMYMZXVTEsIZdM8ZVEdMi4q6oGFAEUTBhRFRQEEHJCEiYgZlhcnfP/VD36Tt3CKLuPu+++/b/gz/sqa46depUnVPnnKrGOmhhYWFtbW1nZ2dgYMDj8VAUTU1N/fTpk7+/v46OjoGBAeb4UtzYJSUlZWVlRUVFWVtbDxw48Pnz51u2bGGz2cC7sGvXLjKZPGTIkCtXrly8eLHHmNaoUaPs7e11dHRcXFwcHBxu3LhRUlICqF2/fr2zs3NAQEBMTMyrV69KSkpOnTrV2Ni4Zs2a2NjYV69emZmZPXnyxNjYOCYmprKy8v79+3K5/M6dO5GRkcAVhuM7/UVg75mUlNTV1fXo0SOpVHr79m02mx0REaFYRkVFBagHBEFu377t7Oy8fft2xcVdIBCAkmBydnZ2RkREzJ49WzEK99XMDSKRiOUyyeVyYOZv3boVc80TCD1HwrF2uVyus7Pzrl27wLoDQVB37yeRSBwxYsTatWs9PDwMDQ2lUimCIH0QBlbeo0eP/vbbb3PnznVyctLX15dKpZ2dnbGxsX5+flgf9fT0eqQNUD506FCwtmLVAppFIpFAIGhubgaVkEikcePG3b17VyQS9VgDl8t98+YNmUym0+lYeQqFUlxcHBwcLBQKAScZDAZYp3rcHcpkMi6XizlhaTSara2toj4DP2EFwCILHBR37txZvXr15MmTscUdeJ9QFAXlIQgaNGgQgiDfkThIIBAIBILiiHC5XEtLyz179mCjrxQN6h7yNTc39/T0vHnz5ty5c9+/fz948OCUlJQJEyYUFBRs2LABRdFXr165uroCaslk8qRJk06dOlVWVtY9CEQkEkGdPQ6fYqMkEsnd3T0tLc3MzMzQ0BCL4W/dunXp0qVLliwZNmzY3r17JRJJUVFRfHw8NsWA5Hh5eS1btuzUqVMlJSXr1q3D4mdg/c3JyWlra5s+fTqBQCCRSKNHjz527Njw4cO9vLxADaamphoaGr1FuYGSTkxMHDBggNKMAHMHxMzAUHI4HBRFMdMBPFfSB1evXjU3NwceNiMjIysrq/T09JiYGCaTKZFIRo4cOWbMGLlcXl9f3z1hTCgUlpaWTp48GdQM+H/t2rVPnz6BvrBYLCKRSKfTWSyWRCKprKzs6OiYOHHi2rVrMY6pqamRSKSIiIjjx49nZGQEBgY+ffp0/vz5+OL+Q/lFwHtoY2Mzb948FxeXyMjIy5cvczgcLPDVfbJRKJS6ujpgOFhZWZmZmXW3SkAQWF9f39ra2tra+vvylCgUCgRBjY2NoBIrKys6nd53ziiKom/fvpVIJFi73SPJr169Cg8PHzRoUGBgoImJSX8o0dbW9vX1vX37dmxs7MSJE4EcIwiSl5dnamqKtYWt4L2l+pBIpEmTJinx08zMTFdX99WrV4oBVUNDQyXaQOiCSCQGBwerqam9e/eutrYWm9JEIlFDQwNM7P77DNva2gANgNt9l1dVVT1//vzOnTs/f/68evVqoMC6+6nB339hEFIul1dXV7e0tGBi0LcNCEQ0KCjoyZMnq1atsrOzO3LkSE1NTURERGBgIAgmMZnMzMxMxfJgt9pHtVwuFzC/NyJrampiYmLU1NQmTJigGPF2dXXNyckJDQ29e/fupk2bgNasra3FugNCXzAM//TTT3v37uXxeDExMa9fv1asHOghQLxcLi8vL6dSqQkJCcBKA3ZPbyMIlu9t27b5+/uPGjWqb22KARvKHsHn8+l0OqiKx+M1NTU5OTmtWrUKCFJAQICurq6WlpaGhkb300vAWOnOf6U4H/arvb09iqL379/X1tbG5hrId2KxWPPmzcvOzj558qSBgYG2tja+uP+QPoAgiMFgTJw48eXLl5MmTQoNDS0rK3NycupNaAgEgq+vb1VVVUJCAp/P5/F4V65cKSoqUhpCGxub4uLimzdvcrlcNpudkpICNoPfZCcOGTJEV1f3999/f/LkiUQiqaioOHz4cB/SDJwznZ2dx44dY7PZPB6vsLDw3LlzSnOjqqrq48ePTk5OWlpa1dXV/UkxJJPJ0dHRKioqAwcOBJkwEARZW1uDKDSfz29paTl06FD3JRIEljHl4eHhoRTsAi4vb2/v58+f19fXA8u9oqJizpw52G4Dq+H+/ftgrRk/frxAIAAsBVlGZDJ55syZqqqqmFmnqJuVlDHY0nl6et6/fx+kEsIwXFNTM3HixN6YAMPw4cOH1dTUZs6cuXv37s+fPz979kxxhk+YMIFIJIIoqFwur6iooFKpEyZM6M9Y93HgEchSV1fXkSNH2Gw2iGmdOHGix1UPy5EHHhJjY+O8vLyoqKjBgwcPHz6czWZPmDABGMLjx49vbW2tqqrCEmlsbGyUsuCw5CXAw9zcXGdnZ5Cm1WOA9M6dO4WFhT4+PlpaWtj+RiqV7tq1a/DgwfHx8cHBwXl5eerq6k5OTllZWVevXhWLxV++fPntt9/4fD6IwEVERKSkpJDJZGAsK9pGKioqYrEYhuELFy48fPjQ2dnZ3t6+P8cCEAQ5deoUhUKxs7OjUql9Z44C7yuCIImJiUBsAAeUxohCoQCnrkgk2rFjR3Nzs7+/P5A9AoHAZDJBfIjNZne32TU1NT09PRsaGhobGzH+DxkyBOx1FCGVSocMGeLg4GBra1tbW5uamtrR0dHZ2Xn9+vWHDx+CPdm8efOoVOquXbt8fX27b2Vw9AfEbdu2KQo98PYsWrTIwMDg1q1bcXFxurq6MAyfOXPm0aNHwGV59OjRly9furm5+fv7v3nzJjMz8969eyB8NGfOnGvXrmVlZUEQ5Obmpq+vr6+vn5mZeffu3Rs3bqSlpdFotKlTpyouVVKpNDk5ua2traysTFVV9fTp01wu18vLi8lkHjx4sLKy0sjIaPTo0SYmJteuXcvOzn79+nVycnJERISTkxPmN4Bh+PTp0/n5+RQKxdnZWVdXV1dXt6ioKCcnJz09PTs7++3bt5GRkTKZLDk5+c2bNwMHDvTw8Pjy5cuFCxdA/klxcXFdXR2CIOPHj7948WJdXV1VVZWNjc39+/cvXbokEAjGjRvHYrGAdfzixYspU6YMHToUmOG6uro3bty4fft2dnb2H3/8wWKxQkNDMXUll8vb29sTExNramokEsmzZ8/u3r27e/duExOTnJycCxcuiEQiNzc3ExMTIpHo5uZWX19/48YN4IjX0tJau3Ytk8msq6tLSUmpqqqSyWR5eXmvX7/evXs32JlVVFQ8fvzY2dmZz+efOXPG29t7+vTp+fn5J06cUFNTi4yMpFAoIGsrKyursrKyq6tLIBCcOHGCzWa7uro6ODjY29tfv369tbVVLpffv3+/vr5+165dMAzv27evoaEBBA8SExOfPn3KYDDGjx+fmprKZrOdnJxKS0tfvXq1e/duYJwC6Onp0Wi006dPGxgYNDc3nzhxYubMmVOmTOFwOOfPnwfZOK6uriB/FINAIEhLSysrK6utrSUQCKdPnxYIBGPHjlVRUdm/f//nz5/t7OzGjh1bXl6ek5Nz9erVrKysgoKCGTNmWFhYKApwY2PjzZs3KyoqOjo63NzcMOehh4dHQEAAiUQiEAhkMnnhwoXAPWJra/vs2bOamhoHB4e6urrk5ORFixZ5eXkp7q64XO6hQ4dqa2vFYnFhYWFGRsbevXvNzc0fPHgA4sP+/v5isXjv3r2tra1OTk4qKipXr16tqqoqLCysrKwEXg5bW9tt27Y5ODgYGRndvXvXwcFh5syZdnZ2QHJevHhx5syZMWPG+Pj4lJaW/vbbbxMmTABHwObPn48ZBBAEaWtrp6WlFRUV5efnX7hwYcSIEW/fvq2vr7e0tATyCQ79DRs2rLvGAsk8b968qa2tffDgQUNDw5cvX3g8Xltb2+XLlxEEmThxYmNj46FDhzo6Ojw9PT09PQsKCnJycsrLy/Py8tLT03k8nrW1tYeHhyLPz507V11dnZ6eXl5ebmFhUVlZWVJS4u/vD3iIouiVK1d0dHQmTZqkaMNBEEQgEOzt7XNycjgcjr29/cePH5OTk+Pi4oYMGSKVSv/8808DAwOxWFxUVPTHH38kJCTY2NgYGBjcu3cvJyfn+vXrly9fFgqFM2fOxOJSjY2NHA5ny5YtigKJo/+AFG0EoA8EAoG+vj6KoiUlJQMHDiSTySC5ns1mg9MJ79+/5/F45ubmRkZGVVVVubm5tbW1rq6uI0aMMDIyqq6ubm5uptPpZmZmIL2ytLT05s2bAoFgwoQJgwYNYrFY2DoOcgzy8vIePHgwatQoFxeXmpoaFRUVKysrDQ2NsrIyoVDIYrFsbW2FQmFJScmVK1eoVGpwcLCTk5OiUgHHINhstqqqqoWFBUjzqK6uzs3NBdn3w4YNMzMzEwqFdXV1PB5PT0/P2tpaJBKdP3++qanJ29vbyMjo3Llznp6e06dPf/ny5bVr14YNG+bn5weybggEgq2tLciXB6nlenp6YE8Krn8oKSm5evWqiopKSEiIjY2Nnp4etqCgKPrhwwdnZ+dVq1ZhJpKtrS2RSGxsbKyrqyORSKampsbGxiDE39LS0tTUpKamJpVK9fT0WCwWSBj39/f/5ZdfQkJCEAQhkUg2NjYgflhbW/v06VMej0ej0UxMTFxdXTU1NU+dOvXx40cGgzF9+nRXV1dwyC4xMdHa2jowMBCCoPr6egRBLCwsjI2NZTJZWVlZfn6+TCYDNVhZWYnF4vfv30skEiMjI0tLy7Kyso6ODjU1NQcHh8rKSqFQ+OHDB6FQOGzYsCFDhiiunsCdVVBQADYrbm5uzs7OGhoaQqGwtraWw+EwGAxzc3NFfQBeSUpKgiBo+vTpqqqq1dXVgOdUKrWsrEwikRgbG1taWtbV1d27d6+kpGTQoEE+Pj7m5uaKLiOQmX7s2DEDA4OQkBBTU1MspIEdHwP7RSsrK/ATDMMfP34ERyVgGHZ1dR04cKCivwKchrGxsVmyZMnSpUshCEIQxN7enkQiNTU11dTUEIlE8N/379/LZDIzMzMmk5mcnNze3j5mzBjgT3dwcBg/fvy7d++6urpaW1vJZLK3t7eJiYlUKn3//v2NGzekUunYsWM9PDyAA7ClpaW1tRWk3rq7uyvaFlKptKio6MaNG3Z2do6OjiAx2tjYeNKkSeDEgEQi8fHxWbVqVWRkZPedU1lZ2enTp3V1dadMmdLZ2Xnjxo3IyEg1NbXPnz9TqVQHBwdwUEMul1taWurr61dWVn748OHly5eenp58Pt/c3Nzc3Bw7/QOcn3l5eUVFRZ6entbW1iQS6fz584GBgcOHD4cgCEXRvLy80tLSefPmdffhAP5/+PAhPz+fwWAIhUJvb287Ozs6nd7V1ZWVlfXp0yc6na6mpjZ8+HAHBwcSiQTDcHl5+a1bt9ra2kaPHu3m5mZgYIC5bUEW9Y4dO3qLL+L4Bn2gNFQoimKRJWzbSyQSwd9AvQMVIpFI6HQ6FmfG9D9YsFAU5XK5KIqqq6t392wCEefz+eBwMqAHVI5VRSKRAA2dnZ1gm6l0CEWRQqzd7rQBYhSDY11dXRKJhMFgUKnUjo4OGo2mqqoKwzCXy6XT6XQ6HSsPwptYJQQCQTGIiiAIOGPRnTagD1xcXA4cOACuZlLkDNZfbIer2BdQFYIgjx49CggISE1NBacuFIkBB8fEYjGBQKDT6WB9BJFA4ANkMBigWEdHB5lMBlt4xXYBJSBXj0qlqqqqQhCkxCtFAQAZaF1dXeAscfe9ORhTHo8HfMHANaFYoWJ/QXlghsvlcnV1dewJ6KMiGVhnAZ1K0x60AoIrIEerx+xqxXwEQFVXVxcIwKqrqyv5IYE+GDBgwPbt20EYs/vwKdIJRJfH48lkMlVVVSqVyuPxyGQyg8FAEEQsFkulUgqFwmAwwPRRmh2AdaCbcrlcTU1NacpgE4FKpYJKeDwekUjETh70oQ9AcxwOh0AgaGpqgqY1NDQAJT12BNDT1dUFpIhKpWKyhw2TWCwWCASgs0D2QF9A9Pvnn3/+6aeftLW1m5qaRowYAY6zKJHE5/OBgGlqagLegmq7urrALMDEDCsPwzCTyaRSqdg0lMlkkZGRO3bs6C3kieMb8ou6ew+xGQvcc0oJJ4rxfUV7Smk1BPX0Ed4BEbAeo45KDZFIJCUng9KvSk+60wZEXLGYYgGscpBm2lsik9JahrWOnbbtMQIJIm9KPerRy9m9L9ha2dXV1WM3mUym0kEkJWJAsd4oBJQo5X0p8UqxXXCn01fHVDHJChDQm9UGpjTY9fcYQFIs2b2zSq30TZhSmB30vY8AMjhr3Z353YdPkU7FCrF+gTzmvmcHlgjXW6i8+0RQbAscrUBRtLeQLJFIxMaFSCT2OKGUGE6j0fogRkVFBVhOiilM2L75wIEDIpEoOTkZZB+Fh4f3SJLS0PdYbW/lURTNzs4uKSlpbW11dHQEZ9lw/MX6AMdfBXBoNjg4mM1mv3nzxtXV9VuTahAEefv27eTJk2tqasrKyrAbHXD8F4Ci6JMnT0JCQvh8fmFhobu7+z86P4RA8PLySk9P7zHj+b8MGo2meDEwhULp+/j090Eul3/48OHAgQOBgYFxcXH49RV/i78Ix18or+3t7TKZjEAgqKurf2ukC7g42traEAQhEonq6urdjSYcf+vwgZPqwDnWPWsLxz9hfrW2tmpoaBgZGeGRA1wf4MCB4/+uPvj/lrN+n7nBgesDHDhw4MDRK/C9FQ4cOHDgwPUBDhw4cODA9QEOHDhw4MD1AQ4cOHDgwPUBDhw4cODA9QEOHDhw4MD1AQ4cOHDgwPUBDhw4cODA9QEOHDhw4MD1AQ4cOHDgwPUBDhw4cODA9QEOHDhw4MD1AQ4cOHDgwPUBDhw4cODA9QEOHDhw4MD1AQ4cOHDgwPUBDhw4cODA9QEOHDhw/F+AXC6vr6/n8/m4PsCB43/BdJXJZC9fvly0aFFubi7OEBw/KE4ikejx48d8Ph9F0cePH8+aNSswMDAgIOD69eu9lT9z5syCBQsWLVr0+PFjqVSqoqKCouitW7dgGMb1AY5/5zyRSqU3btz4BxL27t27+/fvX7x48fHjx/hI4fgRWers7FyyZIlMJmMwGG1tbb/99puvr++yZcsIBMKGDRs+f/6sVJ7P5y9fvlwqle7cuXP58uU7d+68ePEi+JVKpR46dEgul+P6AMe/ECKRKDU19Z9GFQRBjo6Os2fPFgqFYrEYHyYc3w0URS9fvqyqqjp8+HACgcDj8bZs2TJjxozIyMjQ0NCampqOjg6lVxoaGq5evRoSEmJgYODg4DB06NDbt28DsRw+fHhbW9uePXtwfYDjHyfoL1++BOYzcLDk5OR0dXV9q/XUHy8qiqIFBQVPnjzBdhU5OTkCgeDv0wdUKlVTUxMfZRw/uDmor6/funVrREQEnU5XUVGxsLBwdHRkMpmqqqpqamrm5ubGxsZKb8EwLBAI/vjjDwiCIAh6/fq1trY2EEtVVdU1a9acOnWqvr7+q62T8AHA8d+Rch6PFxcXZ2BgQCaTT548mZycfPHixaSkJGDIfJNSef369efPn01MTHpri8vlxsXFGRoagrbOnj174cKFU6dOZWdnA93Q2NhIoVB6rEEul7e3t/N4vD6WfisrK3xMcfxNNlNOTo6+vr6rqysQNjKZDJ4XFxcfP3582rRp3c0Oa2vr6OjohISE9vZ2iUSipaW1efNmTFy1tbXd3d1TU1N//vlnXB/g+J9XBgKBYNWqVS0tLXv27IFhePr06bm5uRkZGQEBAWpqakBbbN261c/PLzAw8KsVCgQCEC7rsa2urq6VK1ey2ey9e/fKZLJp06bl5eVdv349KChITU2toaEhNja2oKBATU1t9erV0dHRSjVIpdLg4OCGhobeWqdSqVVVVfiw4vib9MH169fpdDrYHGAP79+/HxUV1djYyGaz/fz8Ro8erfiWqqrqr7/++unTp6SkJAKBkJycrK+vr2jBqKmpXblyBdcHOP4RIv7o0aPr16+npKRoa2vLZDInJ6eoqCiZTLZlyxYikYii6MePH/Pz821sbLqv7yKR6Pfff29paQFPxGIxDMMHDx4EVhIEQYaGhsuWLcPaevDgwY0bN86fPw/acnR0nD9/vkwm2759u1wuz8jImDNnzs6dO2/fvr1t27bu+oBMJv/55599pGQQCLiXFcffCODVhCBIcUH38vK6e/fu3bt3Y2Nj09LSFPUBBEEoir5580YgEAQHB2dlZcXHxxsaGnp5eSlWi/uLcPxT9gelpaVisRjbAtvb27e1tcXGxjo6OmJPtLW1EQTp8fXOzk42m43pA7lc3tHRAQpDEDRw4ECltiQSiWJbZ86cWbt2rYODA4FACA4OBj6rjo4ODofTozvI0tISHzUc/xxAEESn0wcMGKCvr5+ZmXnjxo2TJ08qynxNTc3y5csPHDjg5eU1efLkxYsXb968OTMzk8FgYMV6nFy4PsDxPwCZTAY8ocB3lJaWZm5uvmLFCuAbBcFYEqlnaaTT6TExMUCagW64cOHC6tWrLSwsQAEajabUFjDzge/o4sWLFhYWy5YtA09MTU3BjoRCoejo6HRvDobhLVu29OaPAjX3M1sDB46/UCUAv5CJiUn3zatAIPj8+bOvry+DwQgKCoqOjk5MTOTz+Yr6oD/Ad744/huibGdnh6Lou3fvOBzOmjVr3r17p62traqqWllZ+dV3CQSCpqamzn8AEie0tLSwJ6qqqr21FRsbW1paqqOjQ6fTKysrIQgiEonAVkpLSzt37lyPLZqbm6N9ojdqlbQIiF1nZGQUFxfjYoCjXysygRAQEIAgCGYAyWQyHo8nk8mAONXV1a1Zs0ZFRQVF0Tt37hQUFIBiCILU1tZCEESj0TQ0NAwMDBTtJBiGAwIC+rWXx4HjbwWKom1tbWFhYUZGRi4uLmFhYdevXzc3Nx8xYkRNTQ0oI5FIJkyYcPjw4a9WxWaz9fT0Pn/+3FuB1tbWmTNnGhkZubq6hoeHX79+3czMbOTIkbW1taAMDMMZGRn79++XSCQ91sDn8zm9o6Ojo/tbCIKUlZXNnDkTgiBPT893796Bqmpra62trWfPno2LAY5+Tpbi4mImk1laWgrkKicnx9TUdOrUqYsXL164cOHVq1fFYjGQ0pEjR7q7u6Mo2tLS4uXlFRYW9vDhw3v37gUEBCQlJSEIgk0uDQ2NtLS0r7YO9fPcGg4cPxI/kMvlHA6npqaGRqMZGhoymcyqqioikWhjYwPcRCCrJyAgYNWqVX1XxeVyQ0ND8/LygKXfR1t0Ot3AwECpLQRBbt68WVNTs3DhQjU1tc7OTrDh+PE+tre3NzY2isViCoViaGhoaGgIdE9ZWZmGhgbm3cKBo29BkkqlO3bsQBBk165dQJivXbsmlUpHjBhBp9NNTU1pNBrQHPfv329tbY2IiACWB/gvgUAYNWrUkCFDwL4ZQZDLly/fvHnzxIkTGhoaX9mO4/oAx39N0BEEAR4bIM3AF6Tyn9MJ48aNmz179lf1gUwme/jwoZ+f33e0hSBIRkZGTEyMnZ2dmZkZBEFDhgyJjY39S3qHoig2mzDHlFJPceDojyzV1dWtXLnyxIkTwKoAGwIajYbJFTYXEASh0+nADBKJRCBQx2AwQGQOVDVv3ryjR486OTkp5izh+gDHPxQgWy4zM5PFYs2YMUNPT6+PqQI2E1Qq9TsaQhDk6tWrRUVFFAqFQCAQicRFixaxWCx8CHD8o/QBiqL19fWPHj2aOnWqmprad1eFIMjFixcHDBjg6uraW74Grg9w/BP3yBKJBJg2PTqC/qqGRCKRYnqGmpraV40mHDj++zMCZOKpqqr+yM4SVEKj0fqjDHB9gAMHDhw4/l/gPk0cOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwIHrAxw4cODAgesDHDhw4MCB6wMcOHDgwPFX4v/9yDKKolVVVVwuV/E3CILU1dUHDNLpHsMAACAASURBVBiAs+l/CuBz2J8+fXJxccG58b9ivLq6urhcromJyb+jRyiKFhcX6+npmZqa4uP7rwckl8vlcnljY6O3t7dMJlNRURGLxUQikUKhIAji4+MTEBBw6dKl9PR0DQ2N/3FyEQS5ffv2gQMHGAxGVlbWv3tsEAS5devWkydPqqqqaDRaYmKilpZWfybwx48fY2JiSCTS7du3/z7aUlJS/vzzT39//3Xr1uETSUVFBYbho0ePXrx40d/f/5dffvl3dEoqlZqYmERFRe3atetH1GRjY+Ps2bNRFCUSiVQqFYgQDMPbt2/39vb+J3NAJpNNnz69o6ODQCDQaDTQHYlEMnfu3Hnz5v24tffixQtfX1+lKfz48WNHR0ddXd3e5nhGRoa6urrSiz8OAiBLJpMZGRkVFha+ePFCJpMFBwcXFxefO3dOIBAYGxs/f/4chuEfN52kUml7e/tXi3358qVXcgmEkSNHqqiovHjx4l9vaTY2Nm7YsGHdunVJSUlEIhGCoL7LSyQSDocDQZC5ubmZmdnfyiICgTB16tSSkpLKysp//UD0IZCKIBKJs2fPLi4uFolE/wWqEARpaWn5uxsiEok7d+4MCgr6wXr09PTkcvmLFy9mzZqVlpZ24cKFw4cPCwSCvqX6H2EyQ5C5ufnz588HDRqUlpaWlpZ29uxZdXV1qVT6gxuv58+fh4SEgAVNybCYP3++krdGiSR/f//Xr1/n5OT0Jh7t7e0PHjz4Hn2goqJCoVBiYmKMjIy0tbUhCKLT6bq6uiNGjAgKCrK2tkYQRC6X/6D4ikSijRs3Pn/+vI8yYrH4wIEDGRkZfTCCSqVaWloiCPKvNzYvXLhQX1+vqqrKYrGOHz+urq7et6Gxdu3aN2/eQBBEJBJJJNKPq/C+JwmNRkNRFEXRf7EmkEqlSUlJ58+f7+crdDr9vyCZYKZs3br14cOHf3dbBAJhzpw5np6ePygtBAKBQCBoaWmNHj1aU1NTU1NzwIABixYtcnd3/+dLAolEksvloaGhmpqaGhoaLBZr0aJF48eP/5ERFAqFO3bsiI+Pp1AoSnoiKytLV1fXwsKiD37S6fS5c+fu3LmzRxmQy+WFhYWFhYXf3FNQu4GBwdSpU5V0NZ1OX7hwYXNzM/CKvn79mkAgeHh4aGhoyOXylpaW1NTUkpISLS2tbdu2aWtr9226rl279vz58wwGQ0NDY+TIkQiCFBQU5OXlEYlEPz8/d3d3GIb379+fkJAQHh6em5s7btw4BEHu3r2blZUlFArDw8MnTJgAqCUSid9kZaekpFRUVBgYGGzevFlNTU0sFj9+/NjKyqq9vf3MmTPjxo0LCwuDIAgM0p9//pmfn08mk3/++Wdra2sURevr69vb2zU1Naurq21sbCwsLMrLyxsaGlRUVMhk8tixY8HmNz8/XyqVqqurDx8+HEGQ58+fi0Qib29vBoPxVd9Lbm7unTt3bG1tx44da2dnh6LomzdvXr9+LZPJ8vLy6HR6H8IHyF61atXly5cNDAzodDo2x9hs9pMnTwoKChYuXGhtbQ2krbS09MyZM52dnS4uLrGxsf3kYUNDg5GRUXl5OQRBQ4YM0dfXx8S3pKTkwYMHVCo1MjJSVVUV9OjatWs3b97U09OLjo52cHAAAvP48ePMzEw3NzdfX19HR0e5XN7W1paamvr27VsNDY1ffvlFR0ene+t8Pn/Hjh2mpqYdHR0LFiwwMTFBUbSysjI5ObmxsdHKymrBggXm5uZyubyurg6MVFVVFQRBbm5uOjo6crm8o6MDzA0IgpydnVksllwu5/F4BQUFQ4cOLSws1NXVdXFxefXq1cmTJ2EYjoqKGjFiBIqit27dio+Pd3JycnZ2HjlyJJlMLisrO336dEdHx+DBg9euXYtReP78+W/aRqMoWlhYePXqVTKZPGTIkOnTp0ulUjC39fX1nZ2dEQS5d+8egUAYN26cWCzeuXOnvr5+a2sr4MDGjRvPnDmzbNkyFos1ZswYUBsgftiwYZGRkWpqahKJJD8/38rKisFglJSUEAiEsWPHNjQ0VFRUKA1i36isrCQQCGAQv3z5smfPHhMTEwqFMmfOnP44MAGLWltbP3z44OLiYmFhASTK2Nh41qxZZDL5v6ngP378WFdXN27cOCKRiKLos2fPbGxsDAwM+n4rPz/fyMjI09NTLpd3dnZSKJTx48f3fxXqcfQTExM5HM7o0aOV2iovL3/8+DGfz//48aODg0Mflejq6k6ePHnfvn1KlWBuru+xCOX/f/D5fDU1teXLl4P/gjgzgUAYPXr0r7/+amZmFhISgqJoU1NTdHR0aWlpSUmJlZVVYGCgVCqV9wIURSUSybZt20gkUnx8fFNTk0wmO3v2bGho6MePHzMyMiwtLefPnw8eEonEyMjIhoYGqVSakpLi7Oz8+vXrO3fuWFlZPXnyBKiWqKgooJP6BoIgtbW10dHRFRUVJSUl+vr606dPl8lkycnJ6urqVlZWa9euXbFihb6+fkpKCoqiXC43Njb2yZMn79+/DwgIcHV1ra2t3bdvn6WlpZ6enpubm7GxcVJS0ps3b4YNG/bq1asjR46AdSQyMlIqlW7evFlbW/vgwYPArty7d++GDRv6YAvgjEAg2LRp05o1ayoqKg4cOGBlZZWQkCCTyS5cuODj40Mmk7dv337t2rW+KxGJROvXryeRSNu2bWtubpZIJIsWLSIQCJ6ennFxcV5eXo6OjpWVlTAMP378OD4+/uPHj5cuXdLV1d2/f3/fPJTJZMePHx8wYICOjo67u/vAgQPNzMxGjRrV1NQkEok0NDQ0NTUDAgI2b96sr68fGRkJXtm5c+fQoUPLy8v37t1raWlZUlIik8n27NmzadOm8vLypKSkmJgYFEVbW1ujoqLevXv3/v17e3t7Pz8/kUikRIBEIpkzZ86vv/7KZrOTkpLOnTsHAiRjxox59OjRy5cv7e3tx4wZ09XVhY3U0KFDBw4caGJi4ufnx+FwJBKJv7//ihUrqqurw8LCZs+eLZVK79696+zsrKGh4ebmZm5uHhERkZ2dbWxs/OLFi6ysLGNj4/PnzwOtQyQSY2JigEA+ffo0Li7u06dPV65c0dHRSUhIQFG0s7MzMjLy0KFDFRUV165dIxKJcXFxX5XMd+/eubu7FxUV1dXVBQUFgUGMjIzU1ta+fv06EKElS5YkJSVJpdIVK1bEx8ez2exz584lJibKZLJ9+/YRicSVK1c2NjbCMJyZmTlx4sTS0tLMzEwNDY21a9fKZLLNmzerq6tbWFhERkbGxcWxWKzZs2cHBgZu377d0dExIiJCJpN9dfRXrlxpZGQUHx8Pejpq1Ki0tLTW1ta4uLiCggJ5/4AgyOXLl0kk0qZNm+rq6l6+fLl06VL5jwFF0S9fvtT1jqamJsXCYrH4l19+Wbx4MXB/ff78+cWLFyYmJh8+fOi7lXfv3jGZzMmTJ9fV1VVWVkZFRbW3t/f9ilQqbWtr63vWe3t77969W/Hh+/fvJ06cuGTJkgEDBgQGBvr4+GzevLmPBQRBkKtXrzIYjKdPn3b/6fr1625ubt/K1X7pAyqV+vTp087Ozi1btmhqakokktjY2KFDh6anp1+8eNHPz4/JZJaXl/fRfxiGb9++TaFQLl26JJPJHj58aGVl9erVKxiGhUIhiJQ+e/bs/fv3ZDI5ISEBQRCpVHr06NF58+bJZDIej2dqarp+/fpv0gdisXjhwoUjRoxIT09PS0vz8fHR1tauq6v79OkTkUiMjo7m8/nt7e3u7u6+vr4ymezMmTOGhoaXLl26dOnS4sWLaTTa5cuX2Wz2wIEDXV1dGxoaHj161NraunDhQldXV5lMxuFwBg4cOH78eC6XiyBIeXk5i8UKDQ0FRMbFxT148ABF0a+utk5OTu3t7TAMc7ncxYsXW1patrS08Pn8lStX0un09vZ2sVjct/zJZLKrV69SKJSbN28iCAL0AYPB+PDhA5fLTUtLo9Fod+/ebWtrc3d3j4qKSk9PT01NNTQ09Pb2FgqFfVfe2dk5fPhwW1vburq6tra2U6dOUanUhIQEkUikpaXl6+vL4XA6OzunTZtmYmKCLWRBQUFgoCkUysWLFyUSyfTp06OiomAYbm1tvXTpklQqjY+Pd3Z2vnz58qVLl4KCghgMxrt375QIEIlEZmZms2bNkkgkAoEgLy9PKpVu3LgxODj40qVLaWlpDg4OdDq9sLCwo6Nj4MCBLi4ujY2Nra2t+/fvp9FoJ0+eFIlEdDr95s2bEokEbBBbW1u7urqioqIoFEppaenbt28rKipSU1PNzc05HA6Px2MymStWrEBRtKWlhUgkbtmyBYZhNpvt6em5YMGC9PT0P/74w8jIaNiwYZ2dnStXrgwKChIKhTAMd3R09EcfwDB8+fJlTU3NzMxMmUyWlZWFoiiCIA8fPlRVVV27di0QocjIyPLycrFY7OTkFBoaKhAIhEJhbm4u2IySSKTk5GQEQcRi8ejRo+Pi4tLT08+fP08kEnV1dYEyIxAICxYs4HK5HA7Hw8Nj8ODBDQ0NXC73559/ZjKZiitmb6PPZrPJZPKqVauAFUihULZt24YgSEVFRd8rqZKcb9y4kUAgzJgxY+7cuZjZ9COQSqUTJ07U6gXa2tqjR49WZPgvv/xia2vb2NjI4/GWLFmye/furVu3Tps2DShFGIZ//fXXI0eOdF9Y09PTwdZq3rx5VlZW8+bNA/7zPpbpvLw8R0dHPp/fG1dLS0upVGpSUhL2yqVLlwwNDZOSkt6+faurq1taWlpQUMBkMk+dOgVM1ZiYmJs3byrVU1dXp6Ojk5ub26M+sLGx+VaukvrpQ7SxsWEymb6+vgcOHEAQ5P79+4MGDfr8+bOKisrYsWNHjRolkUj68HYBHxz4F0GQo0ePMhiMIUOGgEQmJycnkUh09OhRkJVBIpEIBAIEQbNnzw4JCXn37t2lS5fa29uBi+abNmX37t3z9fUFdAYFBQUGBgqFQgaDAWJETCaTRCIRiUSxWIwgyKNHj+zt7ZuamlRUVGxsbH7++WdNTU06nU4kEvX09IyNjQ0MDGAYrqurgyCIRCIxmcyZM2c+f/5cXV1dLpebm5vPnDkzNTW1qKjIwsLi/fv3O3fu7DtcJpPJDh486OnpCcI2DAZj0KBBZ8+eTU1NXblyJdhK0+l0kI/RB3sBPeBfAoGAjZqtra1cLqfT6UDim5ubS0pKQkNDAUOWL19OoVD63lSCOAGRSNTU1DQxMYEgKCQk5NChQ3/88UdMTAwEQaamppqamjKZDKuKRCLt2rVLIBBkZ2dfvHgRNA08jb/++mt1dfXx48cnT56Mouj9+/ft7e0bGxtVVFRGjhzp5eUllUpfvnx58+ZNLHdg1KhRkZGRBw8elEgkq1at8vHxkUgkmZmZhoaGYKRmz54tl8uBowwshYaGhioqKjNnzjx+/Pj58+ejo6PLysrIZHJ+fn5xcbFUKkVRlEKhUCgUCILs7e1BT01MTMaOHVtZWXnp0iWJRAL6AoYPcLilpaW4uDg4OBjjHolEYrPZubm5kZGRgMn99H4AL5C6uvqCBQvi4+NnzJgBGnJ3dx8zZszZs2c3btwI7AMwpWfPnr1ly5bw8PCffvoJZONgw62iovLx48e3b9/a29sDwrZt2wZc0nQ6Hci5urq6RCIhkUgMBsPIyAhFURqNJpPJvhr7gSCIyWRisUNtbe1Jkybt37//8+fPq1evtrW17f9MvHjx4uDBg48fP04gEICL+Md9+qdOnepj2cH88sBNdPz48WXLlhkYGMjlcjc3tzVr1hAIhKNHj4LYQF1d3ZMnT7rn1KIompaWpqend+zYMUNDwxMnTlhbW2NTrDemeXt7Z2dn9+EoBrlVYNAxj6iHh8esWbOKi4vB+iMSiYRCYV1dHXAiPXjwALh8FaGvr0+hUC5fvjxu3DgOh3P48GEwWHK5/NOnT+3t7T///DNG1fDhwwMDA78eP+inBGPyB/pjb2+/ZMkSxeHpv4eKz+d3dXVxOBwWi0UgEFxdXc3MzLq6upSKNTQ07NmzZ/DgwdHR0X/++ed3hC4RBBkyZEhUVJQinU1NTSDA1T2Eq6enp9gpIpGIrQug+3K5fMyYMfv378/Kyho3blxBQQHw7EMQBGLyZ8+ezczMHD9+vK2t7VdXB+DFBlt+MplMJBKDg4N/+ukngUDwVwUDFcObYLMyYcKEgQMHYg/7VjZKIUG5XK6urm5jY1NWVqYoGEqF2Wz2hg0bIiIiFixYcOXKFcDJJUuW8Pn8nTt3jhs3Likpyc/PD4bhAQMGKDKcQCA8e/asqakJhuGnT5+6uLiQSKTY2FiBQHDy5Ml79+5t3749PDy8oqIiKChI8UUKhQKypcFIyeVyPT09MzMzLpeLomhRURHYgtjb29+9e1cpfwYMBAzDW7dudXd3X7FixcmTJ3vzrI4fP37QoEGKqUdVVVXf4QTX0NBITU1dv3795s2bU1JSbty4YWVlRaPRVq9ePWHChOzsbAiCgJNaLpcvXry4vb39xIkT+fn569ati4+PV6SqtrZWIBAEBQV1zz5UknPw3+9OAaBQKPv37ycSiampqdnZ2SdOnJg0aVJ/lEFBQUFTU5OHhweIMm7evBmsvCiKPnr0qLGxkUAgTJ8+nUQitba25ubmEgiESZMmqaqqXrt2TSwWd3R0fPr0aeXKlTY2Noo19+33V2RRXV0dh8NxdnYG3Xdycurq6po8efLEiRMxa8DR0ZHD4Si92NbWlp+fr6ura2dnB0HQrFmzQNAFRdEbN24MHToUBI2mT5+em5vb2dkZFBSkrq5OpVL7f1xDLpeXlpZWVFTExcXR6fSsrKyAgAAKhSKRSCAIsrCwgCBo0KBBBgYGSgMHRF1FRQUsFxKJBMR6QZ0cDgdBkObmZmxmsVis/uYXfV/2i0gkotFoVCqVz+e/evWq/xlsQ4cObWlpAamK2GgpZRpIpdKlS5e2tLSsWLHC0NCwb53cB52///67XC4HdLLZ7Ldv3/ahPO7du1dZWQkKIwjy5MmT7lbJ8uXLAwIC9u3bFxUVFRISsnTpUmx4zMzMli5dunfv3jVr1kRGRvaHFW5ubq9fvwa5a+DsD4FA+PuSLmAYPnHiBI1Go9FoZDL5zZs3nZ2d36piBQJBWFhYH5HDkJAQLS2tgIAAOp2uKPTr1q178uSJh4fH/PnzYRgG22Q+nw8YLhAIXr9+7e3tfeTIkcTExMLCQuBYf/ny5c6dO9+8eWNpaXno0CE2m+3o6HjhwgWxWIwNa/fUOqlUKhKJwsLCnjx5EhUVtXr16ilTpoBwd48btQULFpSUlMycObOPKCsMw0lJSYB7FAqlqKgIQRBra+sLFy58a9CutLTU1NQ0Ozv72LFjdXV1R44cASLk6ek5efLkuLi47du3z5kzB0jF06dPt23bVlRUNHDgwOPHj1dXVysuCgMGDGAwGGfOnCGRSICwN2/e1NTU/OXCw+fzq6urT58+/fDhQwiCfv311/6oFrlcXlFRAcNwZGQkWL/MzMxAODczM/PUqVOTJ0++c+eOWCx+9uzZr7/+6uXldfz48cjISBiG165du2nTJtDN4OBgbHWTy+VcLnfLli2xvWD16tUHDx5UsoSA7kdR9Pjx48ANCM5UATXZ3aKVy+VNTU2dnZ2zZs0C64+xsTGFQkFR9MGDBytXroyNjeVwOLt37/b09Pz8+XNxcXF4eDiCIOvWrTMyMuJyuTKZbPLkySYmJvn5+UOHDq2vr++RPyAAMHLkSPC3j48PiqJHjx5VU1MbM2aM0r5f8UXgqQaT0cDA4PDhw7/9B1FRUXp6eth/Dx8+7Ozs/LfoAyKRGBQU9OnTp/Xr12dnZycnJ8+fP7+fBzKlUqlMJvP39yeRSJg7rLGxkUQiRUdHY5MTxBUFAgFw1T179qytrQ1ssr6VzrKysg0bNuTl5Z08eTI6Otrc3Ly3woGBgVwuNz4+/sKFCzdu3IiJiem+G4VhOCUlBXgVDh06NGPGDMw2hCCITCbPnz+fyWSiKGpnZ9cfCidPniyTyW7dugUk9cOHD56enqNGjfru/EixWNybgW9mZjZo0KCrV68mJCTcu3cvMTHx2LFjX01/wmYUmPwdHR0vX74MDQ3tY9WoqKgAFndZWRlwH0skkry8PARB3Nzc4uLiRCIRkUicOHFidXX1+vXrs7KyUlNT58+fr6+vTyaTVVVVmUymlpYW8EEdPHiQRqPZ2NjMnTtXIpFQKJSgoKCmpqY5c+YUFBRkZGSsWLECS84DdILNZVlZWUhISHl5OZ/Pr6mpAV5vYEkpZYXK5fLi4mKgosDiBSJYgG/l5eUSiQSk/WRkZOzZswdw78iRIwYGBn5+flVVVcA8Ki0tBbv7vrNO5XJ5dXV1RkaGpqbmjBkzbGxssGR2Go0WExPT2dlpb2/PZDKByB06dIhKpZqbm0dHR4MAo8p/jg1JJBILCwtXV9ecnJy1a9dWV1cnJCQcP37czMzsL9cHQqEwKSmJyWS6uroGBwf34atR7ClI02IymZaWlopbFrlc/uHDh/v37xcXF+/YsYNMJh84cEAgEDx8+BBFUbABFYlEw4cPj46O3rZt26dPn/744w+sZnV19bCwsPBeEBYWhrmkIAgyNjYG4TSBQPDbb79duXIFgiAbG5vy8vK+ic/MzFRRURk8eLAi5cD3QiAQIiMjIyMj1dXVwdGTcePGFRUVEYnE+fPns9lsoIHWrFkjlUr37NmTlJRkbGwMajY3N3dycgKrGYFAAJmT2dnZMAxXVFTY29tfuXLl+PHjZ86c6SPrVC6Xv3z5UiaTWVlZAdqY/4GqqiqNRlN60i8XjlLkcP369WQyedCgQViSw/79+8lk8unTpyUSCciWvX79emtr68yZM5lMpoaGxpQpU8BU7zswVVNTM2jQIHV19Tlz5ojF4itXrgwZMmTdunUnT56cNm1aZmYmgiBtbW2jRo1SVVUdP368QCDYsmULiUQyNDTcvn27ra0tk8lMT09/+fKlg4MDk8ksKSn5ajTs8+fPoaGhdDpdQ0Nj1qxZ+fn5Eonkt99+IxAI48ePb29vf/bsGYvFMjExaWho6OrqWrt2rZ6eHpPJ9Pb2vnTpkkgkevjwoba2toWFxb1790CMetasWUQiEYStdHR0Jk2a9P79e8XMgWHDhiUlJfUdScbKd3V17d2718PDIyEhYffu3VOmTHn//j0Mw2/evBk6dCiZTD516hSPx/tq/sbHjx/t7Ow0NDSio6Pr6uocHR2pVGpGRoZAIIiKiiISicuXLxeLxYWFhS4uLnQ63dTUdM2aNR8+fPgqnWKx2Nvbm0wmR0REXLx40dfXNzExUSKRXL9+nUKhODo6fv78uaqqCkSYbt++zWazR40aRaVSHRwcNm3a5Orqampq+vvvv0dFRUVHRz948ADz/nE4nPDwcHV1dXV19eDg4Lt378Iw3D2/KCQkJD4+/sqVKzNmzNi7dy8MwzweD4yUhoaGt7f3ixcvYBgWi8Wg1wsXLjx//jxwxMtksuLiYhaLxWQyPT09vby8gJWXkpIyePBgEomUkpLS1dUllUpXrVpFJBKNjIyWLl06Y8YMBoMRHx8vkUiio6OpVOrIkSNBBrCbmxudTjcxMfnpp5/ev38PYn3Lli0zNDTU1tb28fHx9vYOCAgAbt++Q45TpkxJTEzct29fQEAAUCSYSOjp6d29excMjUQimTVrFuBAeHj4li1bZDJZY2Ojq6srk8mcNm0aiqINDQ1TpkxhMBhaWlrh4eH19fUymezYsWMQBI0dO7a9vb2goEBfX9/Q0LCwsLC1tXXs2LEkEunYsWN9CyePxzt9+jQEQS4uLu/evWtraxs7duyuXbtSUlImT56clpb2VeGBYfjYsWNkMlldXR3kkijW39bWNmPGDF1d3djYWKFQ6OXldeLECZFIxOVyOzo6JBIJi8WKjIwE2UEEAmHNmjVKWSqy3oHJEshvXL16tZGRkaGh4YQJE27evOnu7m5lZXX//n0s4h0XFzd37lzFMcrJydHS0iISiQcPHuzs7FQSS3Nz89u3b0ulUh8fH3d3d+Bd0NPTAzk4ZDKZw+EAypcuXerq6oqFl0ECyNq1a0eMGIHlI4H4hL+/v6am5vz5811cXK5cuYIlF0mlUj8/P6UgPAzDJ0+eHDZsWPdZgyBIRkaGl5fXt8aTISxYBGZ+VVUVuK9CS0vLwsICRdFPnz51dXVpaGhYWVl9+PBBLBbr6uoCd39VVRWKolZWViAw+1UzoaGhgc1mW1lZgQhkS0sLl8sFsUpdXV3gnf/y5Utzc7OJiQmLxRIKhR8+fCCRSLa2tl++fAFGU1tbG2A0i8Xq20kHetjV1QUcUwMGDKDT6QQCobKyksfjUSgUKyurrq4uEE6wt7en0WhCobC+vl4oFBobG2tra5PJ5Obm5ubmZnCVk7W1tVgs3rx5s6Ojo6Oj44sXLyorKzs6OhwcHDZu3IidC5s0adLly5f19PT6f7aoqalJLBZDEKSvr6+pqQlBUGNjY3t7O4IgTCbT3Nwcc7z0wd76+vqOjg5ra2u5XF5TU4OiqI6OjrGxMTBvaTQaiJ1yOJz6+noGg2FhYUGlUr+aRi2RSHx9fTs7O//880/gpre1taVQKOBYBoFAABnltbW1crmcxWIZGxuDQVRXVzc2Nm5vb+/q6rKysuJwODAMg52flZUV2Fd1dXVVV1fDMAykqLsjHoygUCjs6OigUqmGhoY0Gg3kHdXV1YGRAsIjkUjc3d1VVVVPnjxJJpNRFB0wYACZTEYQpLq6ms/nGxgY0Gi0mpoasDx1dnYC9gI+8Hi8T58+AamQSCS1tbX29vYMBqO9vb2+vt7IyEhPTw+CIDabDbhnbm4OIu3g/Edtba1YLDY1NaXRaCA1oA/GgsksEona2trABH+QewAAIABJREFUqgfWHay//v7+OTk5ampqmFAJhUIOh0Mmk42MjMBJwKamptbWVgsLC21tbeyeK7lcbmtrC9xi4EYyMplsbW0N5FxFRcXIyEhNTe3Tp08IgvR9OxlY9WpqagQCAUipMDIy6urq4vF4IAuRxWIpnaXqsZJPnz7xeDwQmraxscHYAjYBZmZmly9f3rdv36ZNm5KSkjw8PA4cOEAkEiUSCYFAMDU19fPzS01NlUqlmpqaubm5Pj4+37d1BgIjk8ksLCzodPqXL194PB4W5INheOPGja2trSkpKdgrnz9/bm1tlcvlYLIo7qSlUqmtre2JEyfGjRs3duxYiUTy4sWLhw8fhoWFtbS01NTU2Nvbt7S0aGpqNjc3b9y48c2bN2FhYWCVwDxRYWFhiYmJgwcPBqx+//79Tz/9pKOjs337dk1NTRArxlwmEydO9Pf3xw4MgRPIISEhx44d6365GdiTFRUVbd269TvPH4CNNvwfAHtf8Qn2t9JP/TGEQXng8AHlsf8q1oDRgP4HWAHsXeytvnckSnaEYruKPVKioQ8iAfLy8rS0tNhsNjBIgVI8evQoprGzs7NBQt43ZVL3Rkb/OaxIueJIKfUX+7X/FIrFYh8fHw8PD6weJQoRBFH8W7EJUEzxD6yGHkent651p1lppACdgwYNAmFqxVZ640yPbFEspiSQvVHSIzHfMSMUU5DBMYs+OND93X7KuZJI9E1ejwsCqOpbZ1/3UYZh+PDhw5mZmV1dXWPGjLl8+fKBAwfodHp8fPzZs2eXL18ONKWvr69EIklJSZk6depXD0z0h9vY34pdkMlkERERivuDvuegRCIxMzM7c+YM2B/Y2dl1dHSkpqZqamo2NTWBA60cDgfsA548eQJS6gsLCxXZkpGRsWjRIsUTEn5+fgkJCd1Fncfjubm5Ke4PZDLZ+vXrz5492+MgAuuwe/b2N+SbglCPklGjdBhY8e9vOiesGA3v8b+90YD9jRX+1gtPlOjs/t/+E4miqLa2tkgkCgwMBJkVMpns48ePu3fvFovFY8aM6ejo0NXVPX/+/DdFv7uzokfmfFMlvY1ab0/6tmRB/iWCIJjB8lUK+zlw/ZGi3iRTsUIwRaVSqUQiQVFUcZ/RB2f6YAv4W6npHin5vvFSeguYeyNGjABhnvT0dCU57D77ustM/+W8PwLQH7Z/6+xT+mnw4MGvX7/mcDhRUVGTJk2Sy+UaGhqNjY0IgmzevBljy4ULF9ra2k6cONH/JMa+ud1deBoaGmxtbel0enl5OdhG991TIpG4bNkydXV1EEUAxzMnTJjw4sULcBhr3bp1Dx48cHJyAkcC9fT0GhsbX7165eDgoKqqCtz9AQEBDAbj7t27fn5+4AmRSJwxY4YSx0CgJTAwkEAgtLa2slgscLLa29vbz8+vN/YaGxsbGRl9M5d+8GKi/1MAi2N+fv69e/dqampYLNbEiRO9vLzArTV79+4tKSnZtGmTk5PT92VD/QOBoujDhw8TExMJBIKvr+/ixYv/mXQCb29ycjKRSJw0adLs2bP/14kWuOCro6MDXATwz7/o7ce7jKXhg1wMYGChKAqyt2Uymampqa+vb3Jyslwup1KpfxNPMJ++iooKSPvuZ+4GIBt4+RVNJfAErO/gaA6w6EG/FI0AsA8AfQc33A0dOlQpBVyRUWQyGaR9g1j0X37bB64PvkeIMaklk8lgSIB9iiAI8Cn/y1QgyH4hkUj9PKyA0/kd9KuoqICD6CAzBJ9rUqnU1NR02LBhKSkp/bwo6V+wtnz1JuO/Fbg+wIEDxz90b/rgwQMIghwcHMCZcxy4PsCBA8f/3b24iooKuCsbZwiuD3DgwIEDx38J3xmvB/djfPjwoftPFArFw8PjR2hCEOTly5ceHh5KjnhwJSx2e0yPG8y+C3xTB7u6ut6+fauurg5OJyq2UlhYmJqaCs779Pgul8t9//69pqamo6MjLmSAaW/fvr1w4cLGjRv/Vl8w+KLqu3fv1q5d+9Xs+H+IFdzU1PT8+fO7d++amprOnTu3+9FiFEXLy8sVb9cBHzAAB5h/nIDm5ua0tDQTE5OZM2cq/fTly5fnz5/n5OQYGhrOnz+/x+OyKIq+fv369u3bXC530aJF/TmZj+OfK47fl8zb2dl54sQJVVVVU1PTDRs2gC87ent7BwYG/kiOMJ/PX7x4cX5+vlLCLwzDWVlZinfY9ngFbmJiYnp6uvyHAY4a2NjY+Pr6dr+898yZMywWC9zK0OPtvufOndPQ0AgJCZHjUDiZYWtr+/HjR8WE67+8IZlMtn///uHDh3/1UPc/AeCQ5ogRI+Lj45ctW8ZkMocNG9bjMXuQPgigq6uro6PzHdnlvQ3NuXPnVFVVV69e3f0DA6NGjVq3bt3KlSuZTKazs3OPd60nJSVNmzatpKTk8ePHI0eOBOlAOP434vv1AQzD9+7dA/dWikQikUgkEAjAJSo/cqf5kSNHYmJiuh88kUgkK1asSEhI+OoJ++nTp/+4SgCaydPT08fHp/tPYrG4tLS0t+M84A6DgQMHBgQE4BKm+JEQHo8HmIYgyIMHD3bs2PF3NCQWi/l8/jcdDfufgkwm+/333zMzM0UiEZ/PT0hI0NDQKC4uVipz7NixM2fOcLlccJFDYmLi0KFD+z5N9k0cA8f1V61a1V1PXLt2DUztI0eOMJnMV69eKb3b0dHBZDLBdJBKpcnJyUOHDsUF/n8pvtNfBEEQiqLgoxwhISE0Gg1sNXx8fLofnu6/S6GiomLHjh3Pnz9XOngC9tQfPnzQ1dWVSCS9ZRNCEKSqqrpr164pU6aMHTu2j0949qeD4Ip5lf/kkkokEuw2RAqFYm9vLxaLwcUAcrmczWaDCyfAVawgTRhzrFEoFHD3gFKs7MuXLxAE6ejoQBDU1tYGQRCLxQKfiGhpaTEwMADXIQgEgs7OTgKB0OMBEzAtwdWPdDodfHISjG5TUxORSFTKzQA/NTc3s1isHu+H6OzshCAIHEPT1tYGN/uD2w40NTUZDIZIJOJwOOAzq+A6YkAbSKLn8XjgImJAuYqKCpfLBf3CsrAfP34cHh4+ceLExsZG8BMMwy0tLRAE6erqds+/ZrPZ4IYScH8qDMP6+vqgQnCVBQRBRkZGIJMd3ECJoijmb8SsXfAW9rCtrQ1kkWtpafV4rx849sxms0FnsSslOjo6hEIhGDuBQKD4mU/gaZRIJLq6utgTqVQKPuSpdMEqkUicMmUKuO4FQRA7OzsDAwOlW52JRGJERAR2mYdMJqusrJw2bVr3tGaMG0wmU1NTs/tPAoFA8dJj8LCzs7NHvxOBQAgODlZVVQWXf9jZ2eno6PToCxIKhenp6du2bQN3+fWYFA9kg8PhqKqqYg5DbOIwGIwfma04/np/EYIgRUVFS5YsWbJkCZvNbmpqUrIXun+4ChzFAvPz/v37d+7cwW6X/L7NwS+//DJq1ChFNwKCIG/evAkNDZ00aRKZTPb19QXXSfZt148bN+7UqVN93CZWVVUVFhY2Y8aM4uLi0tLS0NDQqVOnnj17Fvw0e/bst2/fikSiYcOG2dnZ7dixY8SIES4uLlevXgUr2tmzZ6dNm5aamgrITkhImDlzZlhYmI2NDbgjTCgUgo/ubtmyxdLS0t3d/datW0p0Njc3W1lZmZmZgdvPwT08ZWVl4O4/HR0dcLV6bm7u9OnTw8LCzM3NV61aJRAIlOppamqaO3duREREaGiovb19aWkp+BTlwoULw8PDfXx8wAcVZDLZ+fPnp06dumvXrjlz5qirq4eGhjY2Niptwn766acBAwY4OjpaWlpqaWnl5uZyOJzFixeHh4cPHz7c29v76dOnBQUFurq6Tk5OXC43Ly9PTU3N0NAQWJSZmZlWVlb19fWpqamhoaErVqzw9fXV1NRMTEyMiYlxdXW9d+8euIQcgiAnJ6fc3Fw+n9/Q0LBhw4bw8HBnZ+elS5cqiRD44JqpqWl5eblUKl29erWmpuaZM2eAcTpt2rR9+/atWrVq48aNgBvbtm0bM2ZMS0sLDMNnz56dMmXKnj17Zs2apa6uPm3aNHBHPLhRzsfHJyUlxcjIaPjw4dOmTXv58qWSnJSWlsbGxoaHh9va2u7btw88LC8v9/Ly2rFjx4YNGwICAuzt7Ts6OmpqauLj46dNm3b8+HEXFxdLS8u9e/eC8vfu3YuNjY2IiJgxY8a5c+e63wmBXWMXGRl5//59pe4rzilwV5qJiUn3zxGCz6tNmzYtPDzcy8srNTUVRdHGxsbNmzdPnToVXA1kYmKyefNmbNuxa9eu1atXR0RETJ48mUgkKs13RdrEYvG8efOys7O70yYSicClhL/99ltKSoqHh0d3RxaCIM+ePZs2bVpERISXlxe4gh5BkNevXwNSw8PDlSYIjv9JfxEYG/BJ8ePHj69Zs+bGjRvgw+5fvnxJTEz8+eefFbex4G5CQ0ND8LmSuLg4c3Pzvh2aMAzfunXr2bNnvRUQCoV2dnZhYWGYFEokkl9++cXCwuLZs2dnz551dXVtbm5esmTJoEGDwBfed+/evXnzZuxuSEx2w8PD+whjoCgqFAqDgoKYTGZHR4dIJFqyZImWllZzczNYSb28vMRisUgk8vT0VFNT27ZtW01NTUhIiK6uLlhlwDfuf//9dxiGr1+/7uLiwuPxuFzuqlWrWCxWWVmZUCgcOHCg1v/D3leHVbV8f3P60A0CIiECUtIlKCElIJiooCKK2IpYqBjYCrZiXBPzgiiIooCFoCKhgHR3S5yOvc/7x7x3P+d3CLnW997r/vzBc9h79sSaWGvWrFlLWjo+Pr6qqmrs2LGWlpYsFou/DiwWa+vWrQoKCpWVlSwW6+DBg2QyGazmtbW1xsbG/f39HR0d5ubmFRUV/f39O3bsEBUVBX5n+WfjokWLIiIi6HR6Y2Ojrq6um5sb8OYoJSUFHAIKCwtHRUWBm9V4PN7MzKyoqCgrK0tZWRlZHfiXGxwO5+bmVl9ff+nSpf7+/tDQ0OPHj9NotPr6ejwe7+HhwWAwvLy89PX1aTQaWA7ExcVBFycmJoIYhK9evcLj8VpaWvn5+QcPHqyoqLh27RqJRAJuO4GCYvXq1RwOp7u729raury8nEql/vHHH8LCwrdu3RIYOVevXiUSie/evQN8FIfDRUREcDicffv2eXh40Ol0CoUSGhoK/Mtu3boVOCwDgfzweLylpWVJSUlmZqaCgsLevXt5f4XhTEtLYzAY0dHRBAJh48aN/NGbQZRmMzMz4L4tPDxcXFw8MzOzsLBQX18/KysLaKVmzJhhbGxMpVIpFEpQUBCJRNq5c2d9fX1ERIS8vHx5eTmLxfLy8jpz5gyNRnvx4oUAwZEG3rlzR0dHh0gkzpw5c6g4iyAlWHMHhtVlMBhqamqLFy8GQYekpKSqqqpoNNqGDRuALqihoSEqKkpcXPzjx4+AGVhaWlIoFBqN9vLlSzweP6j8BwJG6unpEQgELy8vgVMZwDN6enp8fX2JRKKIiMi1a9cGujZisVja2trz58+nUqlRUVESEhIlJSVsNtvExOT8+fMsFis/P//8+fPocvw/x/+36mWz2RcvXnRwcDAyMpowYcLdu3dDQ0PBdN27d292dnZSUtKcOXMQj+cg5lFnZ2dAQICnp6eGhsaoUaP4o24NuhHp6OjIyckZJg3YgyNamqKiosOHDwcGBpqYmNTW1oKo7kZGRlVVVTU1NbNmzSotLX379i1/oAzE4KeoqGgYXRCYIWw2Oz09nUAgzJ49m0ajvXnzBobh9+/fm5ubA9MUEJkoPDxcWVnZyMiIRqOBa8kSEhLAMppOp584ccLDwwM4GQ8LC3vw4AHYU4OwNiAaBvCJDS7EI3XA4XBgbX3z5g3wVA5BEIiO++LFi+XLlwsLC6ekpJSXl69YsWL69OkgCvHnz5/5SVpWVnb//v3Zs2eTyWQlJaXY2NgzZ86AsAqbNm0iEoldXV0cDgcQVlxcHIPBBAYG6unpTZgwQUJCorCwUIA4IHKnkZERsHUhEAg3b96MjY319fUNDAzkcrmfPn0iEAjTpk2rrq4uLS3F4XCioqJsNvv58+cgBObGjRuxWCyIITp//vwJEyZs2LBBQ0NDQkICRFBAnBOAq5gPHz7MyckJDg729fW9cOEC8KQtUCtEUSP0VxxE8FteXv7FixdnzpwRFRUFrh8JBAJw/wk+BGq6oKAgHR0dU1NTUVHRgoICEBu1vb29o6ODRCLNnz8fhmGBuKSACRUWFs6YMWP69OlJSUl0Ov3hw4d//PFHbW2tlZUViUQik8n6+vodHR1sNptEIhGJRCwWu23bNmVlZTMzs76+PhC4hkKh3Lt3r7i42N7eHgnyITAgDQ0NDx8+bG1tnZyczO/lf6D1VHJyspeX10BPPiBSU0BAAIlEam1tpdPpEAQRCATg5gHUytLSkslklpaWfvny5ezZs56enqKiosLCwhYWFkMZ+INt3OHDh+3s7FJTU69cuSLwFjSwpaXFysqKTqfv2rULiZ3H333Lly9fuHAhiURqa2tjMBhg+sjIyOzbt6+wsNDIyMjT0xPV1vzPgUX0oS9fvtTT0wPhD1tbW4lE4pw5c7BYrIODw/nz569du9bT04NMMy6Xe/PmTRKJtGjRIgcHh8WLF2/YsGF4Pw04HC4gIIA/xuFXDQeTk5PJZHJAQACPx7t3756/vz9YRvF4/Pv378+fP3/hwoW7d++CuCsDTyOGazYWa2tra2trm5iYCCQgEPqqr6/v4sWL69evR/gKFosFLkcGnTBMJvP9+/fgpAGE3bCyskJSgqqCo4iB9cFisWZmZsrKyiCo+ocPHyAIAvV5/fq1i4sLILK2tvb9+/fv37//4cOH9vb2sLAw/jZmZWVxuVxQChaLNTEx0dTUxGKxNjY27u7uO3bs4A8PCRoFzjZARw+sFUgD3mKx2OTk5L6+vv3798fFxT148KC7u7u4uBiE/yWRSElJSSB+GZfLTUpKotFojY2N48ePB3H+DAwMVFRUEAIOZZvb3t7u6uqamJgYHx+fmpra2dkpsOgMM6KmTZtmZGQUERFha2tbWFg4qJe3gU0Gva+oqAiinfT390tISCxevFjg246OjmXLlsXHx8fHx2dmZnZ0dGzfvr2zs5PfiRgej7ewsAAHSwBg/QUHPzweD4/HHzlypLKy0sXFJTo6mv+kgb+S48eP9/T0fPDggby8fEZGxjBG3q9fv540adJAYuJwuODg4Pb29oiIiI6ODgEK8I9hYBTU3t4O+PFXXQpqa2u7u7snJCSoqKgI1A1s6318fKZPn/748eP4+Pienp6AgACB2LdYLHbJkiV9fX07duxAYjricLjNmzdTKBQnJ6eFCxf+5/01/WvuH4BObWlpQaKJ4nC4oKAg4MHf19cXnEkicQTBIVt5ebmioqK9vT0Oh8NisTNmzIAgKCMj49ixY0ZGRgUFBVJSUvb29i9evOByuefOneNwONHR0SQSad++fZcuXbp79+7KlSsbGhoaGxtBsMBB+YGxsbG6unp1dTUIA8TlclNSUgwMDNauXQsWQTC9vyEkLAizFRMT09TUVFtbe+zYsS1bthw5coTFYiFhjEbIt4Cwg8ReH2FlMBgMiURau3ZtWFjYkSNHampqTpw4sXnz5uXLl8vKyqqrq4NYcr29vSwWC4mmwB8hDmzYQR2E+KLjwjD88OHDTZs2vX37lsvlHjx48JvHB/D029zcLCEhgbSXx+ONHj163rx5V69eZTAY48aNc3Jyun79em9vr4uLCxDJ+/v7wTHsSOwI8vPz2Ww20saR96asrGx8fDyIVbd06dKMjAwQhOurEBEROXXqlJ+fn5OTk7y8/LVr1wYGzgMbNTExMYTBMxiM8vLyiooK/mQEAmGYZoKLAn/++Wd4ePiePXvq6upiYmIGpgEQFxf39PTs6ekZilCvXr2SkpIaGPgQnLJs3LiRQqFcvnz54sWLDx8+/OrB4UjojNRNTEzM29u7vr5eIAGHwykuLp4+fTpIsH379oiIiJKSEuQSEjirCA8Pb2lpiY2NvX79+r1790DOkydPfvXq1bFjx+7du9fb2/vo0SP0HvL/fn+AzHwg6CUmJhKJxLVr1wKLFyDblpeXjx8/HuxSeTxefX19cXExiBSGWOMADUldXZ24uPiFCxeKi4uLioouXLhAoVCOHj0qJydHpVLLysqwWOzkyZNbWlpu3rxZUVERHh6OCBHW1tb8MoW5uXl1dXV7ezv4SktL68iRIx8/foyJiQF7c2C7oqGhMX78eAF5xMbGBlFSDYyZDGQiNze3lpYWMzOz4OBgf39/MTGxM2fOLF++fOReA8lk8oQJE2JiYtLT0wENT5w4IbBeDL9NcXZ2BpECDx06FBgYqKamFhcX5+bmBgK6glhXp0+fBjHiS0pK+ANc4HA4a2trEGi6q6sLyNo7d+4EB7AeHh6jRo36Hg+IWCzWy8tLTEzs5MmTQCP35cuXPXv2NDc3g2iXLS0tMTExV69eBY45Hz9+DDz3CgkJKSoqDhPqjx/y8vLd3d1Hjx4FH7a0tOzZs2cofSP4i6zXp0+fptFoa9euTUxM7Orq+uOPP0ZuHZefn3/27NnHjx9fv34dOBMWSCYnJ1ddXQ0ChAHt5fnz56dOncpiscBqC9wOCw3rgx2G4T///NPW1vbp06eHDx9OTEwcplY8Hq+mpgYMXXCWwx8qGYKgO3fuLFmyBOHN/KUkJibeuXNn+fLlI/GoiMfjJSUlr169OsLo2aBu1dXVyLSqra0FYaZA6YD3A8GRRCLxG2vxeDzgejYkJERYWBipGwRB69atMzIyiomJCQ0Nff78eV5eHroi/+/5AQaDkZeXt7W1vXLlSmhoaExMDIhkff/+fYRV3Lt3LzIyElj4MZnMqKgoEC9ioE4cBCaVlZVVVlYGQYXGjh3LZrNxOJympiaPxwMJQkND09PTTU1NgW0iWN28vb1fvnzZ398PxK7NmzdLS0uvW7fuxIkTsrKymzZtunfv3t27d8ENZHBOtXfv3uPHjyOGmOBgLT09fdq0aeBcZN26da6urgMV5SAQ+YwZMzQ1Nb29vSUkJFauXCkrK+vk5ARGP8QHkBWQwpDfDAaDRCIdOXIEi8XOmzfP1NTUwcFBU1Nz3LhxIFoAh8MB34JzFyRGLn8d1NTU5s+fr6WlZWJiQiaT58yZY2JiAuIngzXXxMTk6NGj7u7uy5YtW7Vq1eLFiwX0zps2bcrOzraxsTE3N1+1ahXQUHM4nMTExJMnT+7cuROHw71///7JkyegAuBYG6khv5AIw/CnT5/ANW8qlYrBYMhkcnh4eFlZmb29/bZt2xwdHZWUlIAWyNHR0crKaurUqaKiouLi4r6+vjNmzAA8gMfjVVRUFBYWFhYWIhFIgO0psI8CWunbt29PmTLFwsJi7Nix586dMzMz8/Pz8/b2RiLf8vcUiUSKioo6ceLEkiVLeDxeXl4eiAf39OlTHo+npqZGIBA8PT1BHwGjT4TyoMmgO0CTIQg6derUoUOHQITLGTNmCGhCcDhcYGCgtLT0tm3bJk6c6OPjs2LFCg8Pj4ULFyoqKi5evBh094cPH5BPQLlIiUJ/BWpOSkrKzc0lk8nq6uoC99W5XO6BAwf8/f3z8vK6u7svX74sKSm5aNEikJuzs/P69euRgd3W1paVlWVkZDRUJAkWixUVFXXq1Km7d+9CEBQbG1tdXc0/9pAxLCMjExIS0tjYOHfu3BMnToSGhrLZ7KSkJIHt0dGjR+fOnfvhw4fu7u7r168DlRQYXW5ubqtWrQKhJsaPHx8dHd3T09PT0/P582cfHx8B+QwUfezYsVOnTt2+fRuG4Vu3bpWVleXm5paUlODxeHV1dW1t7eEPIFH8AuB2794NlCfW1tYvXrywsLDYs2ePu7u7srKyl5eXiIgIBEE5OTl2dna6urpAhurp6SEQCOCkFEQb5h/ff/zxh6Oj47hx4+Li4jQ1NS0tLZ89ewZiRr9//76xsXHevHlCQkKdnZ23bt3CYDBeXl7gHA/o33Nzc6WkpEBICklJSQ8PDy6Xe+nSpRkzZtjb2x88eFBDQwNUg8vlXrlyBVwhRoQ7GIbT09Obm5u3bdsGbkX09PTk5eV5eXkJBNcEu2B1dXUPD48xY8aAI1AdHR0bGxsgP7548aKgoEBUVBQErrt9+7aSkhKFQrG2tj59+rSwsHBjY+PEiRMNDQ2dnZ37+vrExcUjIiIcHR2FhIRSUlIqKipADHQgIaqqqiopKWlrawvUAYvF6unpTZs2TVlZGYvFGhsbCwsLm5ubgzkvJiY2depUIpHY2tqqoaERGRkJYmfzC3r29vZ6enr19fV2dnbbt28fM2YMDofT19evr69ns9khISE2NjZ1dXX29vaJiYlkMplCodja2j5//ry6uppEIrm6uiLSHI/Hq6qqcnV1nTBhAoj+iMFgLCwsLC0tQWRQYLwINHU4HM7Y2Hj27Nni4uI4HE5bW1tXVxeoa8D9BktLSw0NDSaTqayszGKxampqvL298Xg8CGPp6empp6e3fPlyXV1dYAxGp9NNTEyioqLGjx8vIK2PGjXKxMTk06dPo0ePjoyMNDU1tbGxsbS0lJGRYbPZCQkJCQkJkZGRkydPbm1tBT1VWlrq7u4Oeqq/v9/e3v7p06cNDQ04HM7T0xOPxwOx1MjIqKWlBYKgR48emZmZ8d/VkJWVdXV1BZcJnJ2do6OjlZWVpaWl3d3dTU1N7e3tgTDe1dU1a9asqqqq+/fvjxkzhsVi6enpgXhYoqKidnZ24NClqqrq5cuX586dE7iCQCQSP3z4kJqaCnYGa9euBfFSeDxeU1PT3LlzkZCWdDq9s7Nz0P0rBoMZO3YsnU7v6OhQUVGJjIyk0+lEInH06NGPHz9WUVGhUqmWlpYnT54UFxcnkUi1YC6KAAAgAElEQVQuLi52dnYGBgZtbW2NjY0uLi6Ghobz5s0TYFckEik3Nzc1NbWystLCwmLDhg1iYmJI3WbNmqWrq0sgEKZOnVpXV3fx4sVHjx5NmDBh586dAjdINDU12Wx2e3u7oqLi3r17GQwGHo+3s7PT1tbOy8sDcWcPHjwIbpCgi/L/EvzB4ZhMJpvNBrEXgBjF4XDi4uLmz5/f2NjY1NT08eNHoJ5GglYL2CPT6XRDQ8P79+8zGAxPT8/o6GgWi7VixYo1a9aw2exDhw5NmzYN+LoICgrauHGjnJxcTEwM/53n7OxsT09PcAUB1Kqurg6EvUWKA8aax44dCwkJqa+vb2ho+PPPP5lMJrDUnDhxYm5uLr9Zt5+f36DxzfnD5iHbHf7KgHvXQJQGFqhsNhuUzmAwmEwmEgmSyWQymUxEFuZwOAO/HTTan0AdwLcC9nxsNpvBYABhc9AcQHEgNBh/5UENORwOqBtSbeQT8Fvg2vnAcORIbgKhLkHzef83GCE/MUE+A8cM8gQhIKgbIO9Q9+GRBEi2oBQWiwXqhvQF0rRBm8xmsyMjI/fv389mswFtgUVpWlrawK4RqBh/08CNGRDRHoIg0OMgJf9oYf8FAWoj7QKJQRA6AYtkfpKCJ0Pd70EaiwxR8PnAcQt2S4AgYNyCtgiMT35iDlM3pGL8zR9J3cCAAZQZamyj+Gf5q2AwGJMnT8bhcGQyWVJS8vHjx8MkBpcYpKWljx079uXLF1NTU09PTwaD4e7urqen19TUZGNjY21t3dLSMnv27KNHj1Kp1MWLF8vKygp4NXj58mVMTAyyRDY3N1tbW/Pfw+JyufHx8SCSEZlMFhcX3759O/j2/Pnzz58/R8YWBEFVVVX8T1CgAPK+sbHxpUuXHjx4kJCQcPbs2cOHD/9dDxBMJtPe3t7Ozu5nOGJCgeLX4yv+roH3AqD5xWAw/Nf9B03MYrG6u7tFRETExcU7OjrweLy8vHxbWxuPx5OVlQWHTrKysuDaupiYWG9vL51O57fnQe6UiYiIgJ0plUp98uTJnDlz+OPMARcOyGYZ+BsAGxT+8zSknf+lmGUovhMgMOHhw4erqqqwWKyBgcGGDRuMjIyAgnGEu2omk3nr1q2YmBgmk3n16tXv9OmLAsU/AV/nBwM1lSNPPNJK/N88kXwAPwBHW/x8aNCCkMSoChLFV1dzoKgBZ+nAlAvcThh5DuAEC+w7iUQiKnCg+O/zAxQoUKBA8ZsAvf2BAgUKFChQfoACBQoUKFB+gAIFChQoUH6AAgUKFChQfoACBQoUKFB+gAIFChQoUH6AAgUKFChQfoACBQoUKFB+gAIFChQoUH6AAgUKFChQfoACBQoUKFB+gAIFChQoUH6AAgUKFChQfoACBQoUKFB+8JuDw+FER0fn5eX9grJgGM7JyYmKikLJ/lVCvX379tSpU7+gLB6P9+XLl9WrV3M4HJTyKFB+8PuCx+NRKJTY2FgpKalfUBwEQffu3UMjZ4yEULdv3/41AZp4PF5paWleXh4Wi05qFCg/+O3lUAqFoqmp+WuWuYSEBCMjI5Ty/xxCQRD08OFDPT09lB+g+Gbgdu/ejVLhX80JGhoakpOTb968WVpaKioqqqmpKSoq+pMkUCqV+unTp+jo6Hfv3vX19enp6SkoKKC9MJBQ/f39+fn50dHR79+/7+vrMzQ0lJOT+3ljoLi4+MaNG8nJyQ0NDYqKihoaGgQCAe0IFOj+4DdadDgcTnx8vK+vb2dnJ41Gmz59en5+voeHR2trK48PP2rRKSoqWrBgwdmzZ8eMGSMuLu7t7e3o6BgXF8f7v0A59KdPn/z9/S9fvqykpKSgoODm5mZnZ5eUlAR67QdSicfj0Wi0Xbt2LV++XFVVtaamJiQkZPfu3SEhIbwBQKcMihENKRT/RrDZ7GPHjpHJ5EePHrW0tAgLC9fV1VGpVAUFhaCgoJ6enk2bNtnY2Pj6+j59+vQ7y4JhuLy8XEFBwc/Pj8lkzpw5MzIyksVirV27VlhYmEajzZs3z8rKSkxMLDg4mMVi/badAkHQ58+fZWVlFy5cyGQyvby8Dh8+zGKxQkJCxMTEYBim0+khISEaGho/pDgWi+Xl5aWgoNDc3Hz79m1DQ0Mul5uZmUkgEGJjY8vLy6dNm3b+/HkXF5fk5GR0yqD4KvAoR/yXgsvlHjt2bMaMGR4eHhkZGSoqKuLi4hgMBuwbEhMTW1pa3rx5U1ZW5ujomJeXp6qqyi/D5uXlBQcHwzA8MGc8Hr9w4cL169fzl3XlyhUajXbu3Dkmk1lbWztv3jwMBoPBYCAIKikpsba2vn79+o0bN9asWTN79mwXF5ffs1MgCLp06RIMwydOnKDRaPX19cuXLwfnyYDUWCzWwMDg2bNng37OZrN9fHyam5sHvsJgMCoqKk+ePBHoxJcvX544cUJeXr60tHT8+PGgU0BWQUFBixcvDgwMnDBhwurVq01MTJSVldGJg2IYoPzg37ruZGVldXV1+fj4wDCcm5uro6MjLS3d0NAAw7CtrW10dLSfnx8Wi1VVVdXS0rp27VpERAT/4mJiYhIZGUmlUgddesaPHy+gA0lMTHRwcJCWlm5raysuLraysuLxeO3t7RMnTpSSklqzZo2QkFBAQEBKSkpDQ8Nvu9XmcrnJyclOTk5SUlJ1dXUVFRUIoSZNmgR4rbq6+pCzEY8/ePBgSUnJoG8FjoVgGH7y5AmBQHB1deXxeLm5uVOmTOHxeK2trTgcTkZGprS0VEZGBovFGhsb19fX19XVofwABcoP/ptLT1tbG4/HU1ZWhiDowYMHwcHBTCbzzJkz4uLi9vb2W7ZscXd3x2AwJBKJf2eArPh4PH7atGkjL661tdXOzg4YzNjZ2SkoKOTn56ekpBw4cEBLSwuk6e3tzczMPH369O98eNDW1qakpAQI5ezsLCkpmZ2dnZ6efvLkSSC5D2N+CtZuY2PjkXcKgUCQl5dvaWl5+/ZtTEwMlUqNioqysbERExPD4XCurq6gOAiC4uLibG1t0bmDYhig58n/TjaOx8+cOVNdXf3IkSPd3d3d3d0aGhoHDx6Mi4t79OiRhobGDy8uLCzs1q1bjY2NJSUl2tra+fn506dP37lz58qVK5Ety/Xr18PDw5WUlH7PTgHcd/369bGxsU1NTaWlpdra2u/evZs5c+bhw4eDgoJ+bHE4HG7lypVsNvv8+fO1tbVSUlJYLNbPz09cXDw+Ph4k4N9SDLoXRIEC3R/8F0AikRITE/39/a2srNrb28PDw9XU1B49emRgYECn03/40hMWFtbW1ubq6lpXV6ehofHp06djx475+fkhcnFRUVF1dfXJkyd/507B4XDh4eHt7e0uLi61tbVaWlq5ubmnT5+ePXv2jxflsNgJEybcuHFj48aN7e3teDx+xowZdnZ2e/fuFRERIZFIHA6nuLhYX18fVAzpLBT/UpVAT0+PiIgImUz+ucWgGKEtR3h4uPP/xZQpU7Zu3fo/rBWTyQwMDAwICBB4OH369P3798Mw3NHRMXr06Pfv3/8Q45m0tDRpaen29naB54WFhVOnTqVSqRAEVVdXD/yWw+FEREQMpN6mTZu+v2JcLjclJQWGYQGbqNra2vLy8mGaU1VVNWhtv78+jx49UlRU7OzsHPgqOTlZXV39BxbHYDDU1NSuXr0qMAb09PQSEhJgGK6oqFBVVS0rKxtIgfT0dOcBcHd3H1jzb7BJKysrq6ysHFhodnZ2T0/PUF8xmcyXL1+iCw4EQZmZmb29vRAEffz4MSAgYMyYMZaWlkOZC0IQ9O7du9mzZy9cuLCgoAAQs66ubmC/DwOUH4wUHA4H+B6wsrLq7u7u7+/v7u4ODQ318/P73/KDoKCg/fv3C4yMnJycSZMmdXZ23rhxY9KkSX19fT+KH2hraw8sS0lJCYvFiomJSUhILFq0aNAl8s8//8RgMObm5l1dXf39/V++fAkLC5s1a9Z3LjodHR3u7u75+fkD+beHh8eNGzeG+ZZKpS5fvrykpGQkba+oqBi4ug3FD5KTk42MjAaWyGAw1q1bp6ysXF9f/wPHgJaWVmZm5sDOmjFjxsePH5ctWxYWFjYoBfr7+8XExIhE4vv37/v7+3t7e588eaKuri7A8r+BI+7ZsycyMnJQuUpGRmYoPg3DMIfDuXjx4uXLl3/bpQb0i7+/f1JSEgzD3d3ddnZ2x44dO3r0qLGxsbKyclNT08DVKSQkxMrKqra29vPnz/r6+hEREcC+ec2aNQNnB8oPfgA/iIuLw+PxyCiHYbi3t/fu3bv/W34QHBw8cEWDICgvL2/fvn0bN278flkPyfPFixcC+yEgZb/lQ0NDw6ALxIMHD3A43K5du/iX41u3bn1np+zatWv79u0DZ1RNTY28vDyFQhm+RSUlJWZmZl/dJbDZ7G3bto1QbgX7ld27dw+sFYvFAlQaZuPyDWPA3t5+0NaVlpa+ffv23bt3HA5nqL2FhISEvr4+l8tFSHrlypXvXM6KioqMjIyoVOrAKiUkJNja2n61Wzds2PDbsgQul3vjxo25c+cCin369AnI+Fwu9+LFi3g8/tOnTwIELy8vl5SUvHjxIki2b98+OTm5t2/fgjXKxcVlJEIPyg/+xhBnsVjr168XFxfPycmBYRiCoPb2dhiGBdQUv75iv6wO31wWDMNsNjssLExMTOz9+/cjpN5Xy4Ig6M2bN2QyGdn9gE8gCOro6Lh79y4QeyEIGiYf4Bd29erVw5cF+MGLFy/+aZ0CioMg6Js1EmQyeevWrSCTtra276w5DMM9PT1GRkaXLl0SIAiXy62qqtqyZYuRkVFtbe0wBcEw3NLSIi8v//nz599wqWlsbCSRSAJCPSDgxYsXtbS0BCQ8Lpd75swZPB4PyAVywOFwQG0AQdD9+/cHZc8DgdoXjRQ0Gi0tLU1JSUlXV7e3t3f//v3V1dXI9Z/vPL+Bh8XwNi3fX4eR2898c1k0Gi01NVVeXl5fX7+vr+/AgQOVlZXD5Mbj8YSEhIBUO1SeEAQlJiZOmTIFWNGAlDQaLTQ0dMGCBUePHlVXV9+4caO/vz+bzRYawlcEDofz8vK6devWoLfABhb3swn1bf3ybT7sIAh68uQJBEHOzs5UKvXdu3dnz54dvuaD0lAgQWVlZWlpqY+PD/8nzc3NPj4+W7duvXbtmqys7LRp044ePYrwA+QH0iI5OTlra+vDhw//busMDMPJycna2tq6uroCZG9sbLx48WJgYKCsrKwAzWtqakCHIgTktzvw8vIqLS199OgRal/0w9Df319SUqKpqent7V1dXY3H43fs2PH92XK53MOHD5eWlg411TU1NSMjIwddLv/59pf8xo6fP3/W0NAA1MNiseHh4cN/3tHRERgYuG/fPjMzs6GWs1u3bjk7O+NwOECTiooKDw+PiRMnJiYmOjs7h4SETJs2zc7ObtmyZdeuXQOXh8E+jz8fGRkZCoWSnp4eGBg4FIXBhASnoEO18d/VKaBF2dnZJBLpwIEDfX19xcXFycnJXxVf4uPjOzs7V61aNdRyFhsbKyQkBNYsUEpiYuKCBQuOHTvm7Ow8ceLECxcu9PX1WVtby8nJTZ069fr160VFRdbW1gEBAYjDdgwGo6iomJGRwePxfhln/Yfwg9jYWBEREWFhYX6yP378GHiLaWhocHJysrGx4ZdpFi5cePLkyQcPHhgYGAw6FBUVFbOzs+fOnYvygx8ALpcbHx9PIBBOnjzp7u6elZWVkJAwwmHK3zcDP8HhcIGBgTQaLTk5ubu7W19fX0lJKS0tDUk/atSoQbPt7e0dKvIJkNG0tbXBVTVJSUkBBxJg6cRgMNra2vwDMTs7W1tbW0ZGprKycty4cR8/flRQUBg9ejSSICsry8DA4NOnT1ZWViIiIkhBSKHjxo3Lz8+nUCgzZ84EyzRYuOPj4/F4/PHjx728vN6/f3/nzh3k7VAQFhb28PDQ0dEZIZG5XO6hQ4fwePy+ffuYTGZdXZ2urq6UlJSsrGxtba2QkFBTU9P9+/clJSUF+AH4HKThf1JVVXX//n2k7e/fv6dQKIcOHUI6btq0afxCnNBfTqfB1mfcuHEVFRWDrsj8r8C/gHTgIdIvCEkrKiqAdamkpOTr1681NTUpFMrYsWN7enrGjh379OnTWbNmtbS0gK/AvWUvLy8ej9fU1NTV1SUlJaWiokIkEgkEgrS0NFKTpqam9+/f+/r6xsbGUiiUadOmTZky5auklpKSGn7PKoC+vr7t27c7Ozv7+/sXFBTQ6fSxY8cCFV95efmLFy/k5OSUlZUjIiJIJFJwcDAi1Xp4eCQmJtbX1w9zo/s3AZDxCwsLHz58uHXr1qtXr/LzAyEhoXHjxgUFBR05coRKpcrIyIC4WIhlKhaLdXd3LywsRPcHP8YkF4KgpKQkHA5nbm4OZqaBgQH/Qi8gxSD/AvmIQqFkZWW5uLgQCAQBlgD80vB4vNDQUOShg4PDMCwEKFIOHz5cXFw8wibcvXv3x9Lk5s2bw7wlEAhTp04VExMDFIBhOCkpCYvFmpubYzAYAwMDcNY6jEyNwWDExcVXr14NPDKBZOD3UAqNL1++vH792tnZWVVVNTExUUxMzM7ODmiKRo8ejcFgRo8e7eDg8PHjxxF2emVl5du3b5F/m5ubwWkweEImk/39/Qf2y/Xr18HvrKysoTIXeAX+5X846O/MzMyhcn7z5o3AkwcPHgwkqY6OztGjRxHW9ezZMxaLZWFhAagNaj6wXwDZET0Y4Bn8yYbpFx6PV1paWlFRsW3bNhKJdO/evfnz5yPppaWlzc3NZ8+ezeVyWSxWbm4uwg8Qi/uamhqUHwAia2lprVu37tmzZ/fu3bt48SL/KxERkfPnz0+dOlXor8tAWCx23rx5/NLeSIInovxgRGAwGHV1dU5OTnJychgMRlJSEoxXNpsdFRWFx+O7urrU1NRCQkKuXbvW2tr66NGjpUuXuri4+Pn5NTc3jxo1qqmpSVlZ+dGjRwLeIyAIunbtWl1d3VCDQEVFZfny5QLPiUQiIqj+80Gn02trax0cHBQVFTEYjISEBBighYWFW7duBYaqnz9/trKyEhISqqioMDExOXr0aFpaWnh4eHR0tIWFhb+/PzDidHZ2jo6Otra2HnT5bm5unjJlCgzDHz9+NDEx4fF4OTk5RUVFGzZs+Lt1xuFwnp6enp6eyEIfERHR1tZ27dq1YWassLDwSLS0/xApp6SkBIfDzZkzB1ReTU0NDMizZ8+ePXvW09PzzZs3YmJijo6O2dnZ1dXV+/fvNzMz27Ztm7S09NmzZ0tKSmbOnDlr1iwXF5eLFy/u379/4MLN4/FevHiBxWKBb6X8/Hx/f3+guBMREZk/f/6YMWOGEX2kpKRAiCf+o4XfYekf5pW6ujpQDAjQBIvFgjOb8vLyjIwMHx8f/tgkwGXZ1zci6Fr/1WkD9CQtLS06OjoCB3f9/f379u0zNTUNDQ3V0tJKT0+PiorS1taeOnXqzp07VVVVp02bpq2t/fbt2+zsbLD0D8y/paWlamg0NTX926n3/v37xsZGAephsVg9PT05OTlFRcVbt275+PjcuXPn5MmTz58/v3z5ckVFhYWFBYVCYbPZ0tLS4eHhHz9+9PHxWblyJcIMgH8ecBQJhF81NbWnT59yudzCwkIjI6PKysqgoKDg4ODhrwfDMAyy+n2GNDCsun//voqKCmDP/AuHmpoajUbbvn17Wlpad3c3j8dLSkoyMzM7ePCgqqrq2LFje3t7MRiMrq7uwoULY2Njjx49GhYWBpgBFot1c3PDYDBAp4TBYABhU1JSuFxuUVGRoaHho0ePoqKirly5ApgBGCR9fX0C8uyzZ89kZWWRu3vZ2dkj3Nv921VDbm5u/DswYFkE/YWmpqbNmzcDmrx58+bz58/83Uqn0yMiIlRUVM6ePYuoZGEYTk1NHQk/QPcHX0dzc/O2bdsAcbu6uuTl5ZFXZDLZxsZm/vz5O3bsWLJkSXh4uL6+fmtrq5SU1J49e0AaOTk5MpmsoqLi6OjY1tY2ULWyc+fO/zD12tratmzZMij1AAZ1uonBYGRkZERERMAMsbW1nTVr1vXr1x8/fsw/c6ZNm7Zo0SIKhSIhISEnJ3fp0iU/P7+goCCwlCxYsGDmzJl79+4dRuACIY61tbXBQdzw+DXhqX8BmEzmjh07urq6dHR0GhsbBU5BhISEhIWF5eTkOBwOOHsAD1taWgRWrtDQ0Nu3bzOZTMQHHwaDMTU1HTNmzM2bNwMDA4FYevDgwYiIiAcPHhAIhHv37qWkpJw7d27WrFmIMvbatWuTJk2aPHky/9LW1tYWEBCA7M+cnZ1XrFhhamr6n+cH3t7ehw4dKigoMDY25vF4KSkpAQEBbm5uysrK3d3d/v7+gGEAtyhjx44FdwtgGH716lVUVJSQkNCjR4+QzQF41d7ePlC9ifKDbwEOh4uJiQFdxWKx+F+JiYndvXv36tWrW7ZsaWxsZLPZDAZj7dq1WCwWGHQjXSI04IzhZwh9v8bMEWnOSMwcMRjMuXPnwA8B6o28OAiCGhsbeTzeiRMnwsLCkA2yi4vL9OnTk5OT582bh8ViJ02a9PLly+PHjysrK/v7+6uqqvIfmAsNZjXE5XJTU1MPHjwIdIDDTRU83tfX9+cR6kd1ykjGABaLnTlz5syZMzEYDJPJ/OZCu7u7KRRKW1vby5cvnZycQNGKior79++/e/fuwoULsVgsgUAIDQ21tbVds2aNlZXV3Llzt23bBqwkkFWssbFx165dMAwjle/q6mppaUHsYfB4/K1bt/iVS/9hZZGBgcGaNWsePXo0YcIE4BAhMjKyv7/f0dFRQUEBcScsLS29fft2YO7B4/GSk5Ozs7N3794N9K78zODJkyfe3t4Duf6Q6wiKb7s50tvbe/r0aRaLdefOHR0dnaSkJHC7JzMzc82aNeXl5ZGRkc7OzgwGg0qlOjk5FRUV/aSacDica9eu/aT8B95jKi4uBpchvwcsFsvf3z88PJzNZm/dupVEIvX29tLpdBERkYKCAgaDoaurm5iYyGazT506df369bi4OGVl5dzcXMRcHVwwdnV17evrAw85HM7evXtnzJgx6J24tWvXzpw5E6QET44cORIUFDSSJmdnZzc3N/9dQn369EnAs9DPG419fX27d+8e6iryyC/HJiQkaGpqQhDEYrGAeSiHw5k7d+6oUaM4HE54ePjcuXPB24ULF37+/Hn16tUTJ07s7OxE+oXNZs+ZM+f58+f8T6ZMmXLq1CmBa3SPHz/W0dEBd7Zv3LhRVlYG7n76+vry32j73RaW5uZme3v7jo6O77wbCC7qm5qaFhcXj+QT9Pzgu8DhcA4dOnTmzJkPHz5s27bNw8MjKirqzz//PHToEAiLCK6AhoaGLlmyZNWqVSNRSnwbGAxGdHT0L5BDhf4y/G9tbf1+UQiPx6enp2MwGAKBQCaTnzx5UltbGxwc3N3d3dHR4eXlxWazwS7Y19fXy8urv78/ICAA3L4Bcq6Ojs6RI0f47Z1wOBxyGYofLS0tBAJBT0+vqKhI6K8jaHFx8TNnzoxkF29pafl348lAEBQbG9vR0fFrTgWqqqoSEhK+P5+ampr+/v5bt26lpqZWVVU9e/aMw+G0tLRgsdi6urrU1NSsrKy7d++ePHmyqalp/PjxPj4+BQUFgYGBDAYDEecvXbpUWlqK9BR4KNAvnZ2dS5YsaWxsnDJliouLy5kzZ4CR9J07dzw9PZcuXfp7rioYDEZJSenu3buxsbH9/f3fkxWbzT537tzFixf19PRGVDQPDbT9k7lFQUFBXFzcT1LjgO7jcrlPnjwJDQ2tqqr6eSojZKgwGAw9Pb3z58+Dk8N/FM1hGC4pKZGSkkKuTfx6IISi0+laWlq3b992cHD4qapCMPO3bdvW09Pzxx9//Mrb0SPvl1evXtnb2xMIhOHbAngPamP6QwZGQ0ODsrLy8DT/P3IPSrWfqtBnMBgcDgc5SPgZRXz58uXVq1cJCQkUCiUuLg54KflJiw6Dwaivrz927FhfX9+DBw+am5v5XQ78rWtKPwkgQPH/lhmAfq+pqTl+/DiNRouPjwfOmn5SWcAZ1N27dz98+FBaWvrmzRtwTvNP6xcnJ6evLkwYDIZIJKLM4EftM9TU1EbODFB+8HPXhZaWlpqaGjwe/zPs5ICqNz093d3dPS0trbKy0snJ6d69e15eXoi7qx/FikBu5eXlq1atWrlyJZVKFRYW1tLSsrCwAKHhGQxGcnJyWloacJP5mwsBZWVly5Yt27BhQ09Pj5SUlKqqqomJCeIbFYKgoS6WfwNoNNq5c+e8vb27u7tBFIrg4OAtW7YANtDU1PT48eO8vLyfJJGg+G+OYBT/Rv/bFy5cEBMTu3HjRltbm5SUVElJSXd3t5yc3MqVK4GFmaOj4759+4byiMkeGgJnkjAMV1VVaWpqTp06lUajIYfAwcHBkpKS5eXltra26urqioqKc+bMYbPZv22nQBBUVlY2ZsyYGTNm0Gi0WbNm7dmzh81mL1iwQE5ODpyU7tmzx8LCYhi7gGH6hd+PKQgdExAQIC0tXVFRcf/+fX19fTqdnpaWRiAQ/vzzz8ePH+vp6amrqysoKERFRaFTBsVXgdqb/lu5OLCNcXV19ff3z87OlpSUlJeXJ5PJwIIQOMkgEokUCmXQzwsKCrZv3w4Uu8gpNFAs4PF4c3Pz3bt3I+khCLpx40Z7e/ubN29ABDQPDw8hISERERE6nf7s2bMjR47Y2Njk5+fb2dl1dHQgFuu/W6dAEHTlyhUKhXL27Fk2m11bWwssJkVERIBZJwRBGAyms7Nz0Bw4HM7SpUu7uroGfYvH43ft2oV49+PxeIWFhUlJSQcOHNDQ0IiLixs7diyJRAKXNuh0+ocPH168eCErK3vixC0MzfoAACAASURBVInr16+HhYWhEwfF8ED5wb8SMAzn5+c3NzdHRERAEJSRkWFkZCQrKwvuuwEnS6NHjx4qtD2wcb59+zYIU2Nra6ukpFRZWZmVlYXD4ezs7ICNMz8/ePTokZWVlZKSUktLy6dPnxwcHHg8Xm9vr4WFxdKlS4WFhXk8HjC/+a28UQoAONWwtrZWVFSsra0tLi6ePHkyj8fr6+sDboKIRKKpqemVK1cG/ZxAIJw5c2YYdT/w7I2MAeD30NXVFYwBd3d3cJ5EIBAsLS3nzp1LIpEgCFJWVv6dOwUFyg/++6JoVVWVkJCQrq4uBEGpqamzZs1isVgXLlwgEAhOTk7Dfw7sO8FtW8SDmJWVFf9NFoHiKioqFi1aBEHQ06dPLSwsQMjDpKSk8PBwxDEvBEHq6upAPv1t+XRVVZW7uzsEQSkpKXZ2dmJiYiUlJcnJyQcOHPjq54hzpxGOgfLycmFhYQ0NjZaWlo8fP544cYLJZB47dszAwGD8+PH82uAR3UVC8dsDPU/+VwKHw82ePVtZWfnEiRPd3d3Nzc2qqqrnz5+/cuVKQkLCCH1E/63i1q1bd/PmzdbW1uLiYnV19bKyspkzZ65atQoJzMtisSIiIh4/fvyfcerwDSAQCKtXr75x40Zra2tJSYm6unpRUdGMGTO2bNkyVMCA7+mUFStWsFisS5cuNTQ0CAkJAX/RHA4H+NQDB/vt7e3JycnDuOFDgeL/SBko/qVHlx8+fNDQ0NDV1SUSifb29m5ubm/evEESMJnMwMDALVu2/Kib2HPmzNHW1iaTyXp6eqampidPngTHzuBg89q1axcuXPjm2I3/mZulX758mT59uo6ODpFINDAwMDMzO336NEIToFBCfLR9J7hc7pUrV5SVlUeNGqWgoGBpaenv79/e3o6YmVKp1PDw8MzMzN+8X1CMECg/+HcDLPqzZs0auDAxmcxFixYB08MfxYHS0tKkpaXr6+v5CwIi6o4dO5hMJp1Oz8vL+807hcvlAodiTU1NAp3C5XKTkpLU1dV/YHRlBoMxZsyYc+fODWThQUFB6enpDAaju7sbxGRHgQK1L/ovA4PB6OvrD3xOo9EqKipkZGTYbDaJRPpRxUlKSvK7FYNh+N69e6GhodLS0gkJCVgsds6cOf95J5Qj6RRpaemBdlYwDH/69AmLxVKpVHFx8R+oOwIHBgi4XO62bdtu3ryZmZmJx+OxWOzx48d/uCIRxX8MKD/414NMJg8MiwrsTDZu3IjFYru6un6UASiBQEBcEPNzIyQoGOK9/TfHQEIBQBCkr68fFRVVWlpqaWn5o3iPhoYGf0w9ob+iozg7Owv9dUwNfqNAMdxY4qH+i/7lxz+9vb1iYmJ/61b6N5fFZrOZTOZXXUOjncJisdhs9siNhb6zuM7OTv5gWChQoPwABQoUKFB8O1B7UxQoUKBAgfIDFChQoECB8gMUKFCgQIHyAxQoUKBAgfIDFChQoECB8gMUKFCgQIHyAxQoUKBAgfIDFChQoECB8gMUKFCgQIHyAxQoUKBAgfIDFChQoECB8gMUKFCgQPFP5AdINJV/WuORyCE/KjcQ5GTkRXO53J/kT/AHtut/3kf/hJED6PkPHMO/ctB+zwRHwgH9k4flSGbNMGn+A5MO+3fpxeFwqIOBRqNxuVzwY+CHTCYzLy/vH0isnp6ez58/f/+iDKZEU1MTnU4fedGvX7/mcDg/aVjX19ezWKx/9VIFRlReXt4vK5HBYFCp1IGdwuPxqqqqioqK/tZQAU2g0WhUKhWCIBiGQf5sNvvb+CKdTgfTjclkjmQ2gWGJfEX7C+BfII6UlZV1dXV9z7BnsVg9PT0fP35kMBgDa4UE8mtoaHj16lVRURH/sER4yVDsBKw5v8ANM2hIfX39Vwnb0NDAYDD+7iswK795APxSGXmE4HA4sbGxRkZGkyZNMjMz09HR0dfXd3BwsLCwmDx58tOnT01MTGxtbQd+dePGDXl5+dra2n9ChFskkCybzY6IiFBRUQET4zuz7ezstLe3Dw8PH2GMQ1dXV2FhYRDt9vvbIvC8oaHBzMwsOjr623L4NfT/anjOt2/fTpgwQVdX99fUjc1mr1+/Xl9fPzY2duCrrVu3jh49mk6n/60Io+/evXN3dzc0NCwsLGxqalq1apWent6ZM2e+IVhpTk7OzJkzdXV1DQ0Nd+zY0dXVNcJ4zvPnz9fV1dXV1XX8C5MnTzY2Nk5NTWUymePGjfvmINtg2IeFhRkYGMjJyfn7+1dWVg5M09/fv3TpUjMzMwUFBTk5uR07diDhQmEYptFoeXl5JSUlQzU8Li6ORqP9giin+/bts7Cw6OzsHH6Q2Nvbr1q1in88g+YIvBpIh7q6uuDgYD09vatXr/4z42X+bX0RlUp1c3N78ODBokWLKisrZWRknjx5cuDAga6uLklJSX19/erqasE9CBZrbm4+e/ZsWVnZf4LyAakhBoNRVVWdOHHi9+cMQlA5ODioqqqOJD0Oh7O2tv7+tlRVVQ36lkQimZqampiYfFV6HdhfP1vkH2GJWCzWzMxszJgxv2xbicPhli1bVl5e3tvbO/CVt7f3jh07/lbcITDyLS0ty8vLWSyWkpLSggULysvLu7u7//ZGHos1NTVduXJlTU2NoqLi7t27RzKbQNjOy5cvt7S01NbWPnv27MWLF8+fP09OTtbX1//48SMWi50/f76jo+O3UQyCoFOnTikpKe3evXvbtm0JCQlXrlwRSAPD8J07dzQ1NXNyckpKSoyNjRMSEigUitBfEZYOHDjw8OFDgXif/JCVlT1w4MBQcvcPhLKysr29vZyc3PAkNTIysrOzQ0T+6upqMET5Xw36oaqqqp+fX3l5+ZcvX/4j+4O4uDiw00xMTMThcHPmzAGdunfv3ry8vICAAEVFRQiCWCwWnU4HcjcMwzAMs9ls+C+wWCwqlUqn08FOcFBeyuFw2Gw2+Io/HDl4CEEQh8MBzBn8i/xGCgXVoFAoNBoNJGaz2ZmZmZaWliAZ8gkogr9uTCZzYOVBlYapM6gV/1cAA/cfbDZ7586dZDK5ubkZbCGZTOYwzedvO1KZnJwcIyOjQfMH6QUqg2QL2s5ms1+/fm1ra8tPNKQUgXwgCKLRaIDOgOAgGUINgeegUP5WANqmp6dPnjwZpES+4i8ReUihUL58+TJ16lRtbe2hCI7UFqEAUmHwCrQUKDkpFAqLxRJIxl9DCIJKSkrwePzp06fZbDadTudPj9AQ+ZxGo1EoFETxAh7S6XQKhQL0OYD/Xb58mUgk5uTkwDDc1taGw+H27NkjMJiRf4fZqkIQlJeXJyIiEhQUhIw38DkYtPw0FNiMSkhIkEgkkAC0pb+/H6hwkXEiQNKhxrlAlTIzMxGt0ahRoxYtWjToPg+0i8vlnjt3Tltbu729HdQ/IyPD1tYW7LrAEwaDQaFQ6HQ6so/kcDhbtmwJCwv76s4S9DXoAgaDgYwxMB74B+dQnyPdMdSsRygGfhQWFhoaGlIoFDDS+InJP7yRf6uqqnA43FAbd/51Q2BII4omgQVh4KQWmE1/C38vfjIej581axaQC/ifEwiEHTt2ALUgaPO7d+9ycnKWLl1qaGgIwzCFQklNTfXw8JCQkOjt7U1JSUlJSVFRUXFycnJ1dRXgT0JCQjQarbi4uKmpCYKgyZMng1iAHA4nPz+/tbUVi8VOmDChoqLCycmpvb39zZs3NjY2qqqqdXV1OTk5ampq1tbWPB6vpqbm1atXaWlp4uLigYGBtra25eXlfn5+TCbz6dOn48ePHzNmTFtb29u3b+fMmSP0V8zhFy9epKSkmJubT5w4cfz48UQisaen59mzZ5MmTSovL29vb1dWVp44cSIejx+ofKyurm5oaPDw8BASEgJNJpFIHA5HV1dXT09vUPEqMTGxr6/v3bt3rq6uQUFBZDKZx+PRaLT8/Pyuri4Igtzd3cXFxWEYLioqqq+vx2AwLBbLy8urubl57ty5TU1NKSkpWlpa/PkDdW1FRUVnZ6ezszOXy+3q6nr16pWzs/PHjx+/fPmipqZmZWX1+fPnuXPnwjD89OlTfX19DQ0NFotVW1tbUlIiJCQ0depUMpnMZDI/ffrE4XBUVVX37NmzefNmOTm59PR0Gxub3NxcCIJUVFQsLS2JRGJfX9/r16+1tbXLyspYLNb06dO5XG5RUVFzczPoRDk5uby8vHnz5omIiDx9+tTIyEhVVZVKpWZlZdHpdDwe7+bmRiKRhISEGAxGWlrarVu3YBjOz88fNOokWFw+ffrU0tLCYrGUlZWNjIyIRCIMwyUlJb29vRISEtXV1WZmZurq6llZWTdv3qRSqV5eXrNnzyaRSHQ6vaCggMvlYjCYpqYmISGhKVOmIBI3nU5PT09//vy5rq6uv78/mUzmcDhdXV2vX7+eNWsWHo+HIKigoODWrVtNTU1gtbKwsBASEvr8+fONGzeam5vNzMwWL148jKTJ4/FKSkoKCwsJBIKrq6uEhERNTU1eXp6pqam2tvZQn5SXlzOZTESMa25ufvPmjbGxcWFh4b179wICAqZNmzbMDgY5PaZSqf39/SYmJnQ6vbCwEIPBgCnD5XI/f/7c0NDAZrPl5ORMTU1JJBKZTB5m1zJx4kTkhACLxU6ZMmVgGhsbG1A0nU6vra0NDw9XUFAA1QgNDZ03b56wsDCif79x40ZxcbGWltbixYvHjh2LwWAAB9XQ0AgJCRk3btzwrXvx4kVmZmZ5ebmBgcHSpUtHjRpFo9FycnJERUUlJSXBWZSvr6+IiMigxzMpKSlTpkyRkZHp6el5+vSpg4NDSUlJZ2enioqKra0tDodjMpmlpaV9fX0ODg7Nzc1+fn6VlZWpqanjxo3T0tIqKSnp7+93dHQEbIxOp798+ZLH47m4uIiKimIwmK/unjs7O9+9e8fj8ZSVlS0tLXE4HBjnb9++LS4udnZ2BgsCj8crKCgoKytzdnYuLS3t6OhQUlIyNTXNyMigUqlYLNbb25tIJP7c/QG/ro1/f4AMiICAABwOZ25uvmvXLhsbGzU1tYqKioyMjMmTJ5PJ5LKyMg6Hc/fuXR8fH7COOzk5DeSQPT09ISEha9euPXLkiIWFhZubW09PD5PJTE5Onjx58sOHDxMSEgwMDCQlJaurq4uLi6WkpBYvXgykJysrK0VFRVCZuXPnzp8/v62t7cKFC5KSknQ6vbOz09jYWEZGJj8/v7+/Pzk5WVdXV1hYGLDW1tZWPz+/48ePt7a27tmzR0FB4eTJk0wmc8GCBUJCQkpKSubm5rq6uuLi4s+fPx+4c4qJiQFpkA3T5s2bW1tbo6KioqKiBt0fgC1kWFiYt7c3mUxeu3Ytl8ttb2+fO3fuli1bDh8+rKOjs3DhQiqV2tXVZWlp+eHDh8rKSmdn587Ozt7eXjs7OzKZ/P79eyqVKpB5dHS0goKCo6Mjl8vNzMzU1dXFYDATJkwwMzNTVFSUlZXt6upqa2szNDSUl5cvKCig0Wh0Ov348eMHDhw4fPiwqqrq+vXr6XT6+fPnRUVFRURE7O3tNTQ0jIyM9PT0MBiMoaFhaGiokZGRuLh4dHR0f3+/hYUFDodTU1MzMDAYM2ZMY2NjSEjIunXrkE788uVLY2PjuHHjRo8eXVJSQqfT6+rqXF1dIyMjDx8+LC8vv23bNiBfR0ZGzp8/v7Ozs6amRk9Pb9D9AQRB6enptra2+fn5M2fOJJPJGhoap06d2r17t6SkpIiIiLm5uZKSUmxs7Js3byQkJDIyMnJzcxUVFSMjI8E5gYiIiLi4uJWVlZGRkays7NSpU3t6egAvVFJSmj9//qZNm0RFRcPDw7lc7tOnTw0NDUkkEtgkff78WU9PLzc3t6Wlxc/PT1NTs7q6ura2duzYsWfPnq2trTU2Np4+ffow+wMIggoLCyUkJIyNjcFmoqamxsjIqKOjY5hJd/v2bSwWGxQUBMMwk8ncvHmzkJCQhobGvn37Vq1aJSoq+vjx46H2B0Qisba2tri4OCcnZ8uWLQ8ePGCz2WFhYeLi4kuXLgUkBaJVdnb2okWLSCSSqqrqwKE76C6tvr5+3bp1qqqqLS0tg0rfQExctmwZiURKTEwEM+7Tp08EAqGurg4ZtxYWFitXrmxtbZ01a5ahoWF/fz8iZfv7+2/atGn4mjQ0NIiKiiYnJ7e2tk6ePHnVqlUcDmfBggVEIlFWVtbOzm78+PEEAuHw4cMDh1N2drabmxsej8/NzeVwOPPnzwcaJAsLCx0dHRERkdevX7PZ7IMHD8rIyHh6esIwTKVSXVxc8Hj869evv3z5grwCnXX16lUdHZ0jR44Asbi1tXWY/QEgY0pKipOTU1RU1Pr166WkpNLS0rhcblpamq2tbUFBQWlpqZWV1fjx42traxsaGiZMmIDBYIyNjbdu3erj40Mmk1esWOHv779hwwZRUdGBZ2AjwY/nB7Kysp2dnRwO5/bt2yQSKSMjg81mnzhxAvADNpu9e/duGxubjo4OBoMRHx8/qErK3d29t7e3u7s7PDxcWFj4/v37qampSkpKZWVlQBLfunWrmZkZUDqNHj16/vz54PmSJUukpKRAZRYuXBgXF8dkMrOysohEYlJSEmASo0ePRna4q1evBvyAyWSuXLkSMHbw+Zw5c9TV1QEXweFwwcHBEAQVFxcTCITTp08POuscHR0BP6DT6aampjt37qTRaCwW6+bNm4PyAyKR+ODBAxiGu7u7vb295eXlS0pKTpw4ERQU1N/f39XVtWjRIhERkezs7JcvX0pJSRUXF9Pp9MePH3d1dbFYrJCQEFFR0aFUBObm5qA5bDZ7+/btZDK5uLiYy+UmJCQQicQbN24wmczp06dramoCssfHx1tbW/f393d3d69YsUJYWLimpobBYEhJSenr67PZ7Kampqampv379xOJxNzcXHBWaWpqqqWl1d7enpqaisfjz507R6fTP3/+jHTily9fwsPDyWTyw4cPWSyWi4uLkZERqNWqVasOHDgAWmpnZyciItLT0xMXF6esrNzQ0AA6yNvbeyA/AKuhl5fX3r17gQJXQUHB3t4edJympubkyZOZTGZhYSGLxXr+/LmOjk5dXV1PT4+6uvqMGTMAfcTExHx9fUHbIyIiiERifHx8SUkJDofbvn07yEpfX9/d3R3UduPGjYAfsNnsDRs2BAQEIMe8Gzdu/PLlS2Vlpba2dkZGRn9/v4+Pj5qa2jD8AOQZHBwsLS1dWFgIFC8bNmwYftIh/AAUnZaWBmgOWiQjI7NkyZKh+AEGgzExMVFWVpaUlJSSknrw4AF4JSUltXTpUqDNmzt37ubNm2EYbmlpUVFRmTBhwkiOlBsbG+fNmycuLk4gEHx8fPg1n/yVP3r06MyZM8XExKSkpEpLS7lc7p49ewgEQltbGzIpTExMzp8/T6PRtm/fTiAQEGsLDoezePFiHR2dr9bE0NCwp6eHRqMFBweDw6fOzk4sFhsSEgLDcG9vL5CKBq3hlStXAD+AYbijowOLxS5fvhxszXE4HKAzi8XS0dEBiz6Hw9mwYQOBQABNFni1devWFStWgGmCx+MTExOH5wcdHR2GhoaPHj0CC4KJicmaNWuampoUFBT+/PNPhOERCIRdu3Zxudy9e/fi8fj8/HzAWbFYbGRkJKjG2LFjfXx8gP6N+xdGYseB/+EHEng8Xk5OjsvlDrXBtLW1PXfunKmp6ZkzZzw8PHg8Hv82CobhV69eFRYWzpw5U0hIiMViWVpaSkhIpKenA8ENnMwoKCg0Nzf39PQMeqrG4/GIROLZs2ebm5uTk5PB0O/o6Bhmk0SlUi9fvrxhwwaknnp6eg8fPrx3756XlxcGgxk1atTfOpm0tLQ8duxYW1vbmjVrQFsGTWZrawvOol1dXZ89e5aRkfHq1auCgoLp06cDO11LS0sxMTF5eXkZGRlfX98NGzZ4e3tLS0sPReFhzsEUFRXB34FvuVzuqVOnurq6QLkcDsfc3DwzM3P27NlYLNba2ppAIABDLP6sxMXFg4OD161b19jYCJ6PGjVKWFhYW1s7JiamoKCAvxOlpaUFjAhfv37N4/GeP38OngCVS3Jysrq6+ujRo4dvTm9vb25uLvhQWVlZQ0MDaRcGg5GRkSGRSIaGhjwez9HRMSsrq76+/uzZs/xjACEFDocLDAyMiYm5d+/enj17vtrXHA7nzJkza9euRU6MgRAgJSWVnZ3d3t5+6dKld+/eITqQYQbJmjVrbt++HRMTc/LkycePH3t7e3+DIcOgHToQRCLx5cuXeDyex+Pl5OQMtAtnMpkZGRnjxo2DYVhWVlZXVxeHw42kAioqKteuXauurt60adOTJ08aGxu1tLQGNjYsLAyG4Y8fP9ra2l6+fPnQoUMDl47Xr193dnbeuXMnKSlp4CRtb2//6oFwRkZGZWVlXl7es2fP+NOPGjUKg8GIiIhISkoOahM/KP7WrBdY6Hx8fOTk5Lq6ulJSUmAYfvv27TD9C8NwSkpKWVmZnZ0dsALIysrCYrHHjx/v6emxsbFB+lpWVvbkyZMRERHIjEM6YmBtu7q6KioqwFswTX7k/YMfcN8Bi500adLVq1fZbHZAQMChQ4cE1jUIgl6/fu3k5PTs2bP09PSMjIyXL19aWVlVV1erqqoiGjEsFmtoaDjMqsHhcB4/fhwUFEQikcDUHYnqrKysDBm+bm5ugI7f0EwCgbBt27Zly5bdvXvXzc0tMzPzq0YyGAwG9OiHDx/8/PxSU1PT09PfvHnz4sWLcePGjRkz5tatW6Kiops3b16yZMlAA5gf0jWrVq1KS0tLT09//fr169ev/f39R/IVgMDgfvnypbOzM9KJr1694renAub8zc3NGzZsACWClhIIhJqaGnD6NzytZGVlly5dmpubW1FR0dTUBFQfQ93zWLt2bWZmZmho6FDTW0lJSVxcXOBMaBjwX60CoiXQHkRHR1+6dMnX13fSpEkjIZ2Ojo6vr29ycnJPT8/79+8dHBx+6uwTERERFRUVFRWdOHGigFkdWCvXrPl/7V1rUFNX184JhEAC5M4twIRLCXdqobaFwcs4BR3agFgFiyJlCsVWtFJghNqZilBtUOmgCBQYsANqkQ4IKFhrrfYyCNICglZCpRgTEonkAiaQk8v7Y73fmXyJ+vK1Vb93JusHk8k5OWfvtddae++1nmeTe+PGjZs3b0okkvn5+fz8/CXOSXZ2dlwut7i42GAwXLhw4XG32djYREREBAQEPJKmoNVqz5w5U1xcHB0d/bgl1JPlwYMHJSUl5eXla9asSUhIeI44HQRBAgICWltbDx48SKFQlhJ8IHBjUCV7e3vwLKPReOvWLcxm4uPjlxiUjEbjlStXeDwej8dLSkqqr6//zzb5jNVkMBigdjo2NrZz585Dhw6Njo6arSPi4uLa2tru3LkDGxyFQtHb20sgEEZGRuRyOba1NHusGUlSKpVu3bo1ISFh3bp18KUppeXfybL/DdCMiorq7+8HLhKAIuzt7WFm/mvASj6ff/ny5YiIiKysLJVKZWkxZpQcBoMRFBQUGxvb1NQkkUigUxKJ5Pvvv1epVAEBAQMDA5WVlUNDQwcOHHhCX/5Ca0GH9fX1mIYXFhYkEskTXgHfSCQSHx8fM5QtHo9fu3Zta2vr5OQkNog9PT2mfedyuRwO5/jx4wqFAiPQ9ff3Q6r0119/NUVcWJKVbGxs8vPzHR0dc3Nz9+7dW1VV9corrzxyWfDBBx8MDg6mpaVRKBRos2Vf5HI5JJqX6OqwDr179+7CwoJGoxkaGhofH6+pqSkvL8/KymKz2ZYm97jNdFFR0fz8fGxsLARo0PyTWY1/c8QhfJtu1zCVvv/++2w2Oy8vb/fu3Xw+H4rDGKvucVwzaAysaolEIlSY9Xq9SqWC0TfF5+j1eg6H4+HhAVsWs+CVnZ29cePGF154AVOgaWft7OzAJObm5iw5gwaDoaqq6tixY8eOHeNwOM+S82U5IjqdLi4u7uLFi3w+fynTPIIgBALBaDT++eefoDSdTicWiyF/gIG4DAZDX1/fypUrl7jC27hx4+zs7Ozs7MzMTFlZ2VOZD2BQAdIECEucCR8dC9bYX7gZPhsMhuHh4Zs3bzo7O+fl5VEoFDM4BB6PDw0NRRCkqKhodHR0amqqpKQERVEej4fD4crKyu7duycSibq6ukydSiAQQLehHri4uIggiK2trVKpFAqFXV1dCIIolUoURQkEgl6vF4lEQKiGxmu1WiKRuH79+sXFxZ6eHo1G8/DhQ4FAkJKS4u/vD43HYF5AwjDzDUiAAFIN4F+5ublzc3PBwcFbtmzR6/WWiGMSiYTH4yHXqVQqBQJBenq6j49PaGioQqHYu3fvH3/8MTU1VVBQQCQSb9y4UV5ertPpNmzY8NJLL8FGGNxDJBIBmttsqQWcTwwGB19if8E/7ezswOw0Gk1YWNjExMTJkyclEsm9e/fq6uqGhobgZtCV6fPlcrlWq1UoFBcvXly7di2NRjMdbhhEPB6/Z88ewKvs27cPgDEEAgFFUbFYvLCwEB4ePjo6euTIEaFQ+Pvvv2/fvt3Pz4/H4zk5OfH5fKFQODk5OTU1pVarLSkLer2+oaEhPj6+oaGBz+cDUwyUjwF/oakAARKLxWNjYxC+MToukHXVavVPP/3k6OgYExMDGDl4CPYoyL1ipkIgEPLz82/fvp2amnrkyJGqqqq2tjZ3d3dImk1PT0OhRafTTU9PA6QVGgy5XfgM9oPH4wMCAng8nlgsTkxMxBD9H3/88eOcDpoNJWhM52bDahanADULGSHsquklLL988uTJl19+uaGhoaKiwsfHB+YAo9F47dq1jz76SKlUWkYDiUQCm4m5ubmRkZGkpKSwsDAcDjcxMZGYmDg+Pm40Gru7uy9duqRQKNRq9eDg4NTUVFpaGmBgbGxsgHlUhwAACaVJREFUIHtjNBrv3r2Lx+NnZmbEYrFAIEAQRCqVQh+h1JGUlARLvbfeeuuRuxACgYAgiFgshoKW0WiUyWTwBAwhijmpJTYJ7oQxgs8Y1wzzegyaDB4BbxSJRCqVyvQSRHYvLy9AssEDURTFQJhmAQRBkMTERBKJlJaWNjw8LBQKf/zxx9OnT4eFhUVERHR3dysUCq1WK5fLZTJZfn4+1gUYd6zNmLNDT58FvggoXdnZ2VQqNTw8/OrVq/ClQCAICwtzd3fv6upSKpXp6ekMBiMvL29kZARSaZ999plWqz106FBqauq5c+f27NlTW1trWVeRyWSZmZlUKpVKpfr4+EDNcHZ2dv369RQKhUajRUVFhYeHv/7666CIoqIiJyenTZs2paamcrlcV1fX5uZmlUq1adMmKpUaFBR09OhRLy8vPz8/gUDQ1tbm5ubG5XJbW1uvXbu2fPlyFot1+vRp8KiDBw+uWLGioqKiqKjo3XfflclkKIrW1NTQ6fTs7GypVAp13aioKKVSaVaM6uzs9PPz8/Pz+/nnnzUaTXR0dEZGxrfffpuVlWWJZ4DSYnR0dExMzDvvvJOeng7EZigZQU+pVGpwcHB1dbVOp7ty5Yqbm1tjY2NHR8eqVatGRkYAjeDp6enn53fixAmzmvzXX3/N4XACAwMHBwfFYvHq1auZTGZtbe3i4mJBQQGdTk9PT1cqladOnXJxcQkKCmpvb799+3ZISAiJRGKz2RwOJzc3V6VSffPNN0wmk8Vi9fX1wZPLysoQBImOjj5x4sTbb7/93nvv6fX6hYWFHTt20On0rKysyclJs0H09fUtLS3FQBcMBiM0NLS3t3d0dDQ2NhZ6GhkZ2dHRAfecP38+MjISrCsxMTE5Ofns2bNm2gPQLYAI7e3tyWTyrl27JBJJT0+Ph4dHaGgo4PxQFK2qqqJQKEwmMycnp7CwEBqp0WhIJJKDg0NhYWFlZeWqVav6+vpQFN2/fz+NRktOTpbL5d99952np2dwcPDw8PD169djYmIYDAaoGkXRw4cP+/v7u7m5ffjhhxqNBjBIbDabRqMlJCRUVFS4urquXr26v78/NTWVwWDU19fLZLLy8nI6nb59+3aMXYyi6NGjR+Pj47EAvWHDBkB/mjnd+Pj41q1bKRQKg8GoqamRyWS5ubnQnYcPH8JIRUZGmuHf5+fn6+rqmEwmg8Gora0FxI7ZpcjIyIGBgcXFRUADUygUBwcHEomUnZ0tFot1Ol1VVZWfn59YLLaERbz22mve3t4ZGRmZmZklJSVQAYZyFIfDuXr1qk6nKykpcXFxeeONN8rKyg4cOHDnzh1smb9ixQpgYxgMhvHxcS6XS6VSY2Ji4I1RUVHDw8MGg0GpVJJIpPPnz+t0uqamJgqFYslaB4yQj48PjUbbtm1bTk4OfKiurqZSqYDKGxgY8PX19fX1/eWXX8wsCiZ4Go0GiLLjx4/TaLScnJz79+9funQJvH52dra5uZnNZgcFBY2Ojur1+suXL3t5eXl7e1dVVZle0mq1y5cv53K5W7Zs2blzJ5lMXrZsWU9PT0lJCY1G2717N7YRN40hTU1NNBrN3t7e2dl5165dWEBISkp68803T506lZaW9uWXX0LxOS4ujk6nV1ZW6nS6Tz75hEajpaSkKJXKCxcusNnskJCQx1G+nyDIX9h4Go1GlUoll8uxTZyHh4fRaAQCEQ6Hc3BwoNPpIpEIbnB0dJyfn4cNqaen5/z8PIIgMpkMQRBvb+9H5sIAKmA0Gu3t7SHnC6tU+JWzs/NXX3117tw5WAIsLi62tLQsLCykpKTA6onBYJDJZIAGkclkJpMJqQ93d3fAlRIIBBaLJZVKYdFKJBKhUm00GmdmZtRqNSBB8Xg83I+iKIIgTCZzcXFRpVJBYccUl20wGABoj8PhnJycaDQa/Apmfk9PT8vSHNYjTIemuSbQnqOjI5PJhBwCVhwjk8ksFgvuBDaGWVoc0x4OhwMi0szMDLzFzc0NLiEI4u7ubmtrKxaLiUQii8WCkntbW5tSqUxMTAwJCYFvgBcKKoIk2L59+2B+Aj0QiURY3MHbYQ7AVnymgwhfCoVCMpnMYDBg0Qc1XuxXpgYG0/8jLXBubm7btm1paWnLli1rbW1FUVQoFHp4eOzYsQPWm7a2tlBeMhqNU1NTYHuwNfT09ERR1MXFhcfjlZaWgsUCTBkoL9AvOOQHh8NRKBStVgt6wEYKTEWr1WJFLBgOFEXd3d0JBIJIJKLT6QsLC5AqxOPxYHJgEiwWi0QiwVhXVFSw2Wyo1oDOdTodm80267JCocBW6ACpwJ7m4eExOzur0WjMfMrUlrCSI5A8zC4RiUQnJ6fs7Ox169ZFR0e3t7er1WqpVEokEgFPrNFoLKsvoNuWlhYej+fs7Mxms7EaDKQ6MbcCxdLpdFM2icFguH79ekFBQXd3N2DqHzx4MD8/D8q5f/8+REadTldXV3fr1q3Dhw/D/nJ0dLS4uLi3t9eyPWCxgHeQSCQMBkOlUoEnuri4YMPh5ORkCkWBLS82Ul5eXiKRCHYApr9ydXXF3BAsFroJl0xdgEKhTE5OtrS0sFis9PT09vb26enpjIwMsCioVFsSOwDL1NXV9eqrr8bGxlqOlGVAsLW1ZbPZQqEQNhzu7u4qlQpcwNSnni7/4PmKVqv9/PPP16xZ84zP3rEKiqKlpaVEIhEC/fMS2GckJCQoFAqI2nNzc83NzdXV1Us8dUetVkP4e47naAGtZHx8HJgKz1d0Ot2ZM2dWrVplqtKOjg4+n/+037t///7GxsYn0P7HxsZWrlwJ6xg476i2trazs9Pqj/+42OL+2wSW1WfPnpXL5TMzM0sE21nlH9G8Xq+fm5uzs7ObnZ318PBYCh7xKbVErVb39fWlpaVBoYJOp+v1egwu/B9FLpfb2toCmeCv0Dj/tuj1+i+++KK6uppMJi+l0PcMBLjKKSkpL774ImB2tVptQUHB0wYcFhYWdnd3T0xMBAYGPjJV8NtvvzU2NmL7MDs7u5SUlKWAdqzyfxWbTz/99L+rxXq9vq2tDY/He3p6enl5LfH8OKv8IyKVSn/44YfAwECZTObv7+/k5PS8wHxhYWHe3t5yuVyj0RCJxM2bNycmJi5xfjIYDJ2dnY6OjnAYgyVY/tkI5FEzMzPhuJTnKwiCBAcH+/r6Qt7JxsZm8+bNycnJT3vKBxBqUFDQ4872wOPx4eHhWNoQQRA8Hv+EIzSs8reG4xkcLG4Vq1jFKlb5/y/W/5dpFatYxSpWsc4HVrGKVaxilf+RfwFbvfQI2vnyZQAAAABJRU5ErkJggg==
[[Review: liquid phase sintering|http://sci-hub.cc/10.1007/s10853-008-3008-0]]
[[Cermets: It, Wettability and Microstructure Studies in Liquid-Phase Sintering|http://sci-hub.cc/10.1111/j.1151-2916.1957.tb12628.x]]
[img[http://image.slidesharecdn.com/u1p3powdermetallurgy-150422035634-conversion-gate01/95/u1-p3-powder-metallurgy-29-638.jpg?cb=1429675178]]
[img[http://physics.kenyon.edu/EarlyApparatus/Oscillations_and_Waves/Lissajous_Figures/Liss_Fig_App.JPG]]
[img[https://upload.wikimedia.org/wikipedia/en/6/6c/Max_Ernst_making_Lissajous_Figures_1942.jpg]]
[img[http://www.local-guru.net/processing/lissajous_explorer_sc.png]]
[img[https://i.ytimg.com/vi/u7tyPmS9lME/maxresdefault.jpg]]
[img[http://www.creativeapplications.net/wp-content/uploads/2013/04/lissajous02_blog_two.jpg]]
http://www.epsilones.com/paginas/historias/historias-038-lissajous-1-dibujando.html
[img[http://www.scielo.br/img/revistas/rbef/v35n3/a31fig01.jpg]]
----------------
https://www.wikiwand.com/en/Lissajous_curve
The [[Local Group|https://en.wikipedia.org/wiki/Local_Group]] is the [[Galaxy group]] that includes the [[Milky Way]].
A variable is conditionally independent of all other variables given its neighbors ([[video|https://www.youtube.com/watch?v=lekCh_i32iE&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=37#t=14m37s]]).
Find local optima, as a method to approximately solve hard nonlinear optimization problems. Main methods:
* ''[[Gradient descent]]'', and variants
* [[Coordinate descent]]
* [[EM algorithm]]
[[THE EFFECT OF GRADIENT NOISE ON THE ENERGY LANDSCAPE OF DEEP NETWORKS |https://arxiv.org/abs/1511.06485]]
[[EXPLORATIONS ON HIGH DIMENSIONAL LANDSCAPES |https://arxiv.org/abs/1412.6615]]
See [[here|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=14m46s]]
[[Animal locomotion]]
[[Robot locomotion]]
https://en.wikipedia.org/wiki/Locomotion
__Some types of locomotion__
[[Walking]]
[[Swimming]]
A ''locus'' (see [[wiki|https://en.wikipedia.org/wiki/Locus_(genetics)]]) is the physical part (the location) along the DNA sequence of a chromosome, that a particular gene is found in.
$$\ln{\det{\mathbf{M}}} = \text{tr }{\ln{\mathbf{M}}}
* [[Mathematical logic]]
* [[Formal system]]
* [[Propositional logic]]
** [[First order logic]]
** [[Second order logic]]
----------
clauses,
open propositions, with free vairables == [[Property]]
closed formulas with quantified variables == truths or falsities
''Quantifier''s
* Existence
* Universality
A variable under the dominion of a quantifier is called a quantified variable.
[[The game of logic, by Lewis Carroll|http://etc.usf.edu/lit2go/136/the-game-of-logic/2510/to-my-child-friend/]]
A type of [[Classification]] method.
[[Logistic regression|https://www.youtube.com/watch?v=FYgsztDxSvE&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=7]] [[Definition|https://www.youtube.com/watch?v=FYgsztDxSvE&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=7#t=14m42s]]
See [[also here|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=50m]] for intro
__[[Probabilistic interpretation|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=57m17s]]__. Logitistic regression can also be interpretedas a [[Maximum likelihood]] estimate assuming the Logistic funciton (sigmoid) gives the probability of belonging to a given class. We can then use [[Gradient descent]]. More theoretical understanding can be acquired from the theory of [[Generalized linear model]]s
A simpler version: [[Perceptron]]
See [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides08.pdf]]
!!__Training__
Maximum likelihood. Log likelihood turns out to be cross-entropy.
To see if problem is convex, we test if the [[Hessian]] is positive semi-definite, and it is. See [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides08.pdf]] for form of Hessian
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The toppest of the lels
[[VERY NOICE!! (◠‿◠ )|https://www.youtube.com/watch?v=dhdxR3A5hHY]]
http://kek.cat/
http://niceme.me/
http://nicemem.me/
http://nicememe.website/
http://nicememewebsite.website/ etc
http://meme.ai/
http://rarepe.pe/
https://wowsuchdoge.com/
http://www.nyan.cat/
http://trololololololo.com/
http://hristu.net/
http://leekspin.com/
http://www.shrekis.life/
http://www.ultimate.com/
http://trolololo.lol/
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https://www.youtube.com/watch?v=y_e6M0x3Lqw
https://www.youtube.com/watch?v=tKNhPpUR0Pg
https://www.youtube.com/watch?v=BQ8ZqF6JNfA
https://www.youtube.com/watch?v=VtmQ0vKPKqQ
[img width=200 [https://media.giphy.com/media/11caEgnSDg0avS/giphy.gif]]
[img width=200 [http://static6.comicvine.com/uploads/original/10/100439/2506710-tumblr_lxpxkmgtq81qko4x4o1_500.gif]]
[img width=200 [https://media.giphy.com/media/11LPqjefhW3ACk/giphy.gif]]
[img width=200 [https://media.serious.io/078320348a4e7e82/static.gif]]
https://www.youtube.com/watch?v=2gmQYBZPV7g
https://www.youtube.com/watch?v=SwxdBiazu8M
http://pepefrogme.me/
<a target='_blank' href="https://www.youtube.com/watch?v=bEuAkE_twdw"><img src="http://66.media.tumblr.com/3f7842c7ab32aad38fcdf0073e383e12/tumblr_mler3xqn4h1qhbw13o1_500.gif" style="width:100px;"></a>
https://www.youtube.com/watch?v=N3Q6TqtDyF0
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http://m.ytmnd.com/ etc
A kind of [[Recurrent neural network]], [[Neural networks with memory]]
!!![[Understanding LSTMs|http://colah.github.io/posts/2015-08-Understanding-LSTMs/]]
[[Video|https://www.youtube.com/watch?v=56TYLaQN4N8#t=25m30s]]
[[Backpropogating an LSTM: A Numerical Example|http://blog.aidangomez.ca/2016/04/17/Backpropogating-an-LSTM-A-Numerical-Example/]]
Introduced in [[Hochreiter & Schmidhuber (1997)|http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf]]
[img[http://blog.aidangomez.ca/assets/lstm.png]]
[[video|https://www.youtube.com/watch?v=hWgGJeAvLws#t=10m20s]]
[[explanation|https://pythonprogramming.net/recurrent-neural-network-rnn-lstm-machine-learning-tutoria]] [[implementing in tensorflow|https://pythonprogramming.net/rnn-tensorflow-python-machine-learning-tutorial/]]
[[Number of hidden units|http://stackoverflow.com/questions/37901047/what-is-num-units-in-tensorflow-basiclstmcell]]
A crucial innovation to recurrent networks was the Long Short-Term Memory (LSTM)
(Hochreiter and Schmidhuber, 1997). This very general architecture was developed for a
specific purpose, to address the “vanishing and exploding gradient” problem (Hochreiter
et al., 2001a), which we might relabel the problem of “vanishing and exploding sensitivity.”
LSTM ameliorates the problem by embedding perfect integrators (Seung, 1998) for mem-
ory storage in the network. The simplest example of a perfect integrator is the equation x(t+ 1) =x(t) +i(t), where i(t) is an input to the system. The implicit identity matrix Ix(t) means that signals do not dynamically vanish or explode. If we attach a mechanism to this integrator that allows an enclosing network to choose when the integrator listens to inputs, namely, a programmable gate depending on context, we have an equation of the
form x(t+ 1) =x(t) +g(context)i(t). We can now selectively store information for an indefinite length of time.
From [[here|https://arxiv.org/pdf/1410.5401v2.pdf]]
[[Statistical Mechanics of Systems with Long-Range Interactions|https://www.youtube.com/watch?v=0-lKbPDNSGs&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=7]] (on first lect of this part)
[[book|http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199581931.001.0001/acprof-9780199581931]]
Book: [[Physics of Long-Range Interacting Systems|http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199581931.001.0001/acprof-9780199581931]]
Often take them to have two-body interaction of the form:
<big>$$U(r) \sim \frac{1}{r^{d+\sigma}}$$</big>
where $$d$$ is the dimension.
For $$\sigma \leq 0$$, the systems are //non-additive// (or //non-extensive//), in the sense of [[Statistical physics]], so that, for example, energy is no simply proportional to volume.
!!!__Examples__
* self-gravitating system ($$\sigma = 2$$)
* dipolar magnets ($$ \sigma =0$$)
* charged plasma
* vortices in 2 dimensions. $$U(r) \sim \ln{r}$$, $$\sigma = -2$$ (effectively)
See [[Power laws]]
Another interesting quantity (here applied to networks, though applied to wealth distribution and elsewhere of course) is the fraction of ends of edges $$W$$ that connect to the fraction $$P$$ of nodes when ordered by their degree (i.e. the top $$P*100$$ percent of nodes, by degree). It can be shown that for scale free networks:
$$W=P^{(\alpha-2)/(\alpha-1)}$$
The curves $$W$$ vs. $$P$$ are called Lorenz curves, after Max Lorenz. For example, for the World Wide Web links, $$\alpha \approx 2.2$$ and the curve shows that 50% of links go to the top 2% "richest" pages ("richer" meaning with higher number of links). Actually, as the WWW doesn't follow a perfect power law, the real number is closer to 1.1%
This is related to Gini coefficients. [[More on power laws|http://tuvalu.santafe.edu/~aaronc/courses/7000/csci7000-001_2011_L2.pdf]]
As a comparison, one can calculate the Lorenz curve for a exponential distribution, for example. Both $$W$$ and $$P$$ go like $$e^{-x}$$ for large $$x$$ (i.e. small $$P$$ or $$W$$). Therefore the Lorenz curve (at its extreme) goes like $$P \sim W$$, and so the top $$1\%$$ have just $$1\%$$ of the wealth.
$$W = \int x e^{-x} dx = [x e^{-x}]^{x}_\infty+\int e^{-x} dx$$
$$ =(x +1 )e^{-x} $$
$$P = e^{-x} $$
$$\therefore W = P-P\ln{P}$$
The typical plot however plots the income of the bottom $$100(1-P)$$ %, i.e. $$1-W$$, vs that percent from the bottom, i.e. $$100(1-P)$$ %. [[Here|http://www.wolframalpha.com/input/?i=plot+1-%28%281-x%29-%281-x%29*ln%28%281-x%29%29%29+for+0%3Cx%3C1]] is the resulting plot in WolframAlpha. This shows that indeed inequality is not exclusive at all to power law distributions. In fact the only distribution with a perfectly equal Lorenz curve, corresponds to when everyone has the same, so the distribution is a Dirac delta centered on a certain point.
However, power law distributions often do show more inequality than exponential distributions. For instance, in power laws a typical situation is the famous "80-20 rule", by which the top 20% have 80% of the income. For exponential distribution, it can be seen from the plot that the top 20% has "only" 65% of the income. //try different exponential distribution, do I get different Lorenz curve, I think I would! So this statement was not very meaningful..//
What preferential attachment (and its resulting power law distributions) does is not make extreme events possible (they are possible in other networks), but it makes them more likely (power law decays less rapidly). In the preferential attachment model, this is because extremes are amplified due to the nature of the model.
//aka risk, cost, loss; or its opposite, utility, reward,... depending on the area or context//.
A ''loss function'' refers to a [[Function]] that one wishes to [[minimize|Optimization]], in some [[decision theoretic|Decision theory]] framework, like in [[learning|Learning theory]], [[Operations research]], mathematical [[Ethics]], etc.
[[Loss function for learning|https://www.youtube.com/watch?v=PpFTODTztsU&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=8]]
!!__Loss functions__
__[[Hinge loss]]__
__[[Cross entropy]]__
__Negative log [[likelihood|Likelihood function]]__
__Training error__
See [[Empirical risk minimization]]
[[The Science of the Friend Zone|https://www.youtube.com/watch?v=IGK2KprU-To]]
[[How Much Money is LOVE Worth?|https://www.youtube.com/watch?v=Jf7Uo6nqaIg]]
See [[Active matter]], [[Microhydrodynamics]], and [[Kinematic reversibility in fluid dynamics]] for more
Zero reynolds number doesnt mean no acceleration. It just means that no force is needed to cause that acceleration
In the zero Re limit, if the swimmer accelerates (say by varying the velociy of the corkscrew), and if it has a finite mass, the fluid will exert a net force on the swimmer, and thus the swimmer will exert a net force on the fluid, momentarily creating a Stokelet component. If we somehow had a small but very heavy swimmer with a large thrust too, it would then create a Stokelet velocity field for a significant period of time.
[[Life at low Reynold's numbers|https://www.ethz.ch/content/dam/ethz/special-interest/mavt/robotics-n-intelligent-systems/multiscaleroboticlab-dam/documents/microrobotics/HS2015/Purcell1977.pdf]]
Happel and Brenner book: [[Low Reynolds number hydrodynamics (book) |file:///home/guillefix/Dropbox/COSMOS/Physics/Fluid%20mechanics%20and%20thermodynamics/%5BJohn_Happel,__Howard_Brenner__(auth.)%5D_Low_Reynol(BookZZ.org).pdf]]
__Reciprocal theorem__
The reciprocal theorem allows one to determine results for one Stokes-flow field based upon the solution of another Stokes flow in the same geometry, i.e. having the same boundaries but different boundary conditions.
See //A physical introduction to suspension dynamics//.
Linear quadratic [[Gaussian]] control
See [[here|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=46m50]] --> [[and here|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1h8m55s]]. See [[Reinforcement learning]]
//Linear time-invariant theory //
Lyapunov functions always decrease (or increase) with time and are used to establish the stability of fixed points in deter-ministic dynamical systems.
See [[Dynamical system]]s
Often programmed via [[Assembly (programming language)]]
//aka statistical learning//, see [[Statistics]]
See [[Artificial intelligence]], [[Deep learning]]
--[[Book recommendations|https://www.quora.com/Machine-Learning/How-do-I-learn-machine-learning-1]]
[[Building Machine Learning Systems with Python|https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-systems-python]] -- [[Machine learning in Matlab|http://uk.mathworks.com/videos/machine-learning-with-matlab-87051.html?s_eid=PSM_12825]] --[[Lecture list of Andrew's course:|https://www.quora.com/What-are-the-differences-between-the-Andrew-Ngs-Machine-Learning-courses-offered-on-Coursera-and-iTunes-U]] -- [[lecture notes|http://cs229.stanford.edu/materials.html]] -- [[Andrew Ng machine learning course|https://www.coursera.org/learn/machine-learning]] https://www.youtube.com/watch?v=UzxYlbK2c7E . On [[lecture 2|https://www.youtube.com/watch?v=5u4G23_OohI]] -- [[Machine Learning - mathematicalmonk|https://www.youtube.com/playlist?list=PLD0F06AA0D2E8FFBA]] -- [[Machine Learning: A Probabilistic Perspective|http://www.amazon.co.uk/Machine-Learning-Probabilistic-Perspective-Computation/dp/0262018020]] [ext[and here|https://www.cs.ubc.ca/~murphyk/MLbook/]] -- [[Machine Learning: Discriminative and Generative (The Springer International Series in Engineering and Computer Science)|http://www.amazon.co.uk/Machine-Learning-Discriminative-International-Engineering/dp/1402076479]] https://en.wikipedia.org/wiki/Generative_model
[[Machine Learning with Python|https://www.youtube.com/playlist?list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
[[Supervised vs unsupervised|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=4m47]]
!!__[[Supervised learning]]__
Training data consisting on inputs and outputs. Want to find function relating inputs to outputs, to then be able to predict new outputs from new inputs. Need ''a way to represent the function approximation'', with some parameters (the ''model''):
* Linear functions
* Kernel (basis) functions, polynomials, Gaussians, etc.
* [[Artificial neural network]]s
* ...
and a ''learning algorithm'' to find best parameters for the data.
Two main types:
* __Regression__. Output value is continuous
* __Classification__. Output value is discrete
New paradigm: [[Deep learning]]
!!__[[Unsupervised learning]]__
<<<
Actually, I think unsupervised learning is the most general. After all, supervised learning can be seen as a special case of unsupervised learning, where the data points are pairs $$(x,y)$$, and we want to find a function so that the data can be modeled as $$(x, f(x))$$ as well as possible; no need to interpret this as "supervising", but can instead interpret it as "finding structure"
<<<
[[Intro by Andrew Ng|https://www.youtube.com/watch?v=UzxYlbK2c7E#t=50m40s]]
!!__Variations on supervised and unsupervised learning__
[[Variations on supervised and unsupervised|https://www.youtube.com/watch?v=pytUuJPOnVI&list=PLD0F06AA0D2E8FFBA&index=4]]
!!!__[[Semi-supervised learning]]__
You are given a set of inputs $$x$$, but you only have the corresponding outputs $$y$$ for some. You have to predict the $$y$$ for the rest (by learning the function $$y(x)$$ for instance, like in [[Supervised learning]].
!!!__[[Active learning|https://www.youtube.com/watch?v=pytUuJPOnVI&list=PLD0F06AA0D2E8FFBA&index=4#t=4m07s]]__
Like semi-supervised learning but the algorithm can //ask// for extra data, which it deems to be the most useful data to ask for.
!!!__Decision-theoretic learning__
Basically loss-functions/costs used by the learning agent are based on [[Decision theory]]. See example [[here|https://www.youtube.com/watch?v=pytUuJPOnVI&list=PLD0F06AA0D2E8FFBA&index=4#t=5m32s]].
!!!__[[Incremental learning]]__
Incremental learning is a machine learning paradigm where the learning process takes place whenever new example(s) emerge and adjusts what has been learned according to the new example(s).
!!__[[Reinforcement learning]]__
To me it seems like the difference with supervised learning, is that you //don't specify input, output pairs, but just outputs//. You specify desired outputs, and undesired outputs. There is no input, but still the problem is not just trivial (i.e. it only ever produces one output), because the model is probabilistic.
Sequence of decisions
Reward function
Used often in robotics.
!!__[[Learning theory]] and learning algorithms__
!!__[[Deep learning]]__
<small>Go deep into the rabbit hole</small>
!!__[[Bayesian inferential statistics|Bayesian inference]]__
Good framework: [[Stan|http://mc-stan.org/]]
!__[[Probabilistic model]]s__
Models for [[Probability distribution]]s. These models relate [[Random variable]]s, using some more or less general assumptions about the nature of the data.
[[Graphical model]]
[[Artificial neural network]]
[[Energy-based model]]
Many other models used in different areas of machine learning.
----------------
__Applications__
* [[Speech recognition]]
* [[Speech synthesis]]
* [[Image classification]]
* [[Text classification]]
* [[Machine translation]]
See more in [[Machine learning in science and engineering]], and [[Applications of AI]].
--------
<mark>Try [[Torch|Torch (Deep learning framework)]]:</mark>
See https://www.youtube.com/watch?v=DHspIG64CVM#t=45m40s
[ext[http://www.robots.ox.ac.uk/~az/lectures/index.html]]
!!![[Can artificial intelligence create the next wonder material?|http://www.nature.com/news/can-artificial-intelligence-create-the-next-wonder-material-1.19850?WT.mc_id=FBK_NA_1605_NEWSFWONDERMATERIAL_PORTFOLIO]]
See AI and nanotech in [[Nanotechnology]]
[[Deep Learning Applications in Science and Engineering|https://www.microway.com/hpc-tech-tips/deep-learning-applications/]]
neuronal networks in physics.. See dissertation by Nicholas Chen
[[Neural networks modeling for refractive indices of semiconductors|http://www.sciencedirect.com/science/article/pii/S0030401812009649]]
[ext[Computational physics: Neural networks|http://www.snn.ru.nl/~bertk/comp_phys/handouts.pdf]]
[[The role of networks and artificial intelligence in nanotechnology design and analysis|http://www.ncbi.nlm.nih.gov/pubmed/15209351]]
[[Advances in Machine Learning Research and Application: 2013 Edition|https://books.google.co.uk/books?id=5E2BSvz8dEAC&pg=PA936&lpg=PA936&dq=neural+network+nanotechnology&source=bl&ots=gXbk8U9DbB&sig=-X2YonpGYQqGeMfQaUp5epwSA88&hl=en&sa=X&ved=0ahUKEwjtzuiIuKXLAhVLbRQKHcpZBnE4ChDoAQhGMAc#v=onepage&q=neural%20network%20nanotechnology&f=false]]
[[Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.058301]]
http://knowmtech.com/
[[Procedural generation]]
!!![[AI in medicine]]
-------
[[AI for science|http://slides.com/guillermovalle/deck-3/fullscreen#/]]
Random idea for neural network for chemical synethesis and manufacturing etc. Facebook post: [ext[https://www.facebook.com/guillermovalleperez/posts/10153853693416223?]]
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
See Khanacademy
[[Modern Finance and Macroeconomics: A Multidisciplinary Approach|https://www.youtube.com/playlist?list=PL04QVxpjcnjjryApbpp-jva3QEV-7roP3]]
[[Oxford notes|http://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/KT/2015/KTLectureNotes.pdf]]
Magnetohydrodynamics (a.k.a. MHD).
[[GdR Dynamo 2015 (nice lecture series on MHD and related topics)|https://www.youtube.com/playlist?list=PL04QVxpjcnjiAfHgi_WIAAOB85ejbnRjJ]]
See also other lecture courses in MMathPhys
-------
Note:
Flux freezing does not imply a one-to-one correspondence between the magnetic field strength $$\mathbf{B}$$ and the displacement field of the fluid $$\delta \mathbf{r}$$, because the relation includes $$\rho$$:
$$\delta \mathbf{r} \propto \frac{\mathbf{B}}{\rho}$$
$$\quad\quad(\dagger)$$
In waves in MHD, $$\rho$$ also changes, and therefore its effect is important. In particular note the MHD linear wave equation for $$\mathbf{B}$$:
[img[MHD_waves1.png]]
The second equation means that if the fluid gets compressed in the direction perpendicular to the magnetic field, the magnetic field increases in magnitude. This has to be the case because:
*If $$\rho$$ doesn't change, the compression in the perpendicular direction will imply an elongation in parallel direction, and thus $$\delta \mathbf{r}$$ will elongate, and because $$(\dagger)$$ implies that it is proportional to $$\mathbf{B}$$ for constant $$\rho$$, then $$\mathbf{B}$$ will also increase.
*Conversely, if $$\delta \mathbf{r}$$ doesn't elongate, then $$\rho$$ must increase. But now the LHS of $$(\dagger)$$ hasn't changed, and therefore the RHS shouldn't too, so as $$\rho$$ has increased, this implies that $$\mathbf{B}$$ will also increase.
A type of [[Tumor]] that develops during [[Cancer]]. They invade and destroy the surrounding tissue, may form [[Metastases]] and, if untreated or unresponsive to treatment, will prove fatal.
Production of goods, by processing of [[raw materials|Raw material extraction]].
When manufacturing is done in the context of an [[economy|Economics]], it's called [[Industry]].
[img[https://upload.wikimedia.org/wikipedia/commons/7/7b/Robocrane_Project.jpg]]
A4
[[Forge Devcon 2016 - Transforming how products are designed, made and used|https://www.eventbrite.com/e/forge-devcon-2016-tickets-21357894036?utm_campaign=order_confirmation_email&utm_medium=email&ref=eemailordconf&utm_source=eb_email&utm_term=eventname]]
[[Autodesk Spark|https://spark.autodesk.com/]]
[[Authentise|http://authentise.com/]]
[[Joint probability distribution]] where we Integrate out one variable.
Fish, algae, sponges
--------
//[[Tunicate|https://en.wikipedia.org/wiki/Tunicate]]//
[[Pyrosome|https://en.wikipedia.org/wiki/Pyrosome]]
[img width=270px [http://www.deepseanews.com/wp-content/uploads/2013/07/Screen-Shot-2013-07-23-at-10.10.13-AM.png]]
[[Salp|https://en.wikipedia.org/wiki/Salp]]
[[Giant Pyrosome and Salps - pelagic sea squirts|https://www.youtube.com/watch?v=5EQGA_4BZ5s]]
[[Nautilus|https://www.youtube.com/watch?v=HIRCI0G19Uw]]
[[Shark]]
[[Sunfish]]
!!!__Marine [[mammal|Mammal]]s__
[img[https://media.giphy.com/media/l0MYGqwfuj0MHZcLC/giphy.gif]]
--------
[[Deep sea creatures]]
[[Markov process]] with a discrete state space. More generally it's a chain (a [[Directed network]], where every node has out-degree and in-degree 1, forming a chain) of [[Random variable]]s that satisfy a [[Markov property]].
Can have:
* [[Discrete-time Markov chain]]
* Continuous-time Markov chain
[[Definition of Markov Chain|https://www.youtube.com/watch?v=bPqg0G1-k1U&index=5&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft]]
[[Ergodic theorem for Markov chains|https://www.youtube.com/watch?v=ZjrJpkD3o1w]]
Has applications in theory of [[Stochastic processes]], and in [[Machine learning]]. In particular through a [[Hidden Markov model]]
See also [[Finite state channel]]
Order of a Markov chain. See [[here|https://cw.fel.cvut.cz/wiki/_media/courses/a6m33bin/markov-chains-2.pdf]]
[[Markov subchains|https://www.youtube.com/watch?v=bPqg0G1-k1U&index=5&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=2m55s]] A subchain of a Markov chain is also a Markov chain
__Regular Markov chain__ [[here|http://www.math.iupui.edu/~momran/m118videos/notes/sec92.pdf]] [[here|https://www.math.ucdavis.edu/~daddel/linear_algebra_appl/Applications/MarkovChain/MarkovChain_9_18/node2.html]]
See book Markov chains by Norris
See [[Markov chain]]
[[Markov Chain Compression (Ep 3, Compressor Head)|https://www.youtube.com/watch?v=05RFEGWNxts&index=4&list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H]]
See [[Reinforcement learning]]
[[Markov decisions processes|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=43m15s]] are [[Markov process]]es extended with //actions// and //rewards//. They are related to [[Markov reward process|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=13m]]es, and in fact they are an MRP if we fix a policy (i.e. distribution over actions given current state. see [[Reinforcement learning]]).
A Markov decision process is a 5-[[tuple]] $$(S,A,P_\cdot(\cdot,\cdot),R_\cdot(\cdot,\cdot),\gamma)$$, where
* $$S$$ is a finite __set of states__,
* $$A$$ is a finite __set of actions__ (alternatively, $$A_s$$ is the finite set of actions available from state $$s$$),
* $$P_a(s,s') = \Pr(s_{t+1}=s' \mid s_t = s, a_t=a)$$ is the probability that action $$a$$ in state $$s$$ at time $$t$$ will lead to state $$s'$$ at time $$t+1$$. I.e. __what happens when you take an action__
*$$R_a(s,s')$$ is the immediate reward (or expected immediate reward) received after transition to state $$s'$$ from state $$s$$. __What reward you get when something happens__. ( This is called [[state-action reward|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=4m15s]]. An alternative is that rewards are associated with states!)
*$$\gamma \in [0,1]$$ is the discount factor, which represents the difference in importance between future rewards and present rewards.
(Note: The theory of Markov decision processes does not state that $$S$$ or $$A$$ are finite, but the basic algorithms below assume that they are finite.)
[img widht=400 [https://upload.wikimedia.org/wikipedia/commons/2/21/Markov_Decision_Process_example.png]]
[[Video by Andrew Ng|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=9m]] -- [[operational definition|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=19m]]
!!!__Finite-horizon MDP__
[[intro vid|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=10m10s]]. Maximum time that is considered. When that time is reached, the MDP ends.
In this case, optimal policy [[may be non-stationary|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=22m10s]].
!!!__Non-stationary MDPs__
Several of the quantities in the definition of an MDP may be allowed to depend on time, like the transition probabilities, or the rewards.
This can be mapped to the previous case, by letting time be part of the state space.
[[Definition of the optimal value function for non-stationary finite-horizon case|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=17m10s]], which now depends on time
[[Value iteration for this case|https://www.youtube.com/watch?v=-ff6l5D8-j8&index=18&list=PLA89DCFA6ADACE599#t=18m55s]]
-------------
https://en.wikipedia.org/wiki/Markov_decision_process
A kind of [[Information source]], produced by a [[Markov process]]
[img[http://i.imgur.com/yWAhpru.png]]
A ''Markov network'', aka a ''Markov random field'', or ''undirected graphical model'', is a [[Network]] of [[Random variable]]s that satisfy a [[Markov property]]. In particular they satisfy the properties below. It is also a [[Graphical model]] with undirected edges.
There is a __node__ for each of the [[Random variable]]s. In the case of [[Conditional random field]]s, one for each output $$y_k$$, and each input $$x_k$$.
Then we have an __edge__ between any two nodes that in such a way that the r.v. satisfy:
|__[[Global Markov property]]__: Two notes are conditionally independent if all paths between them contain at least one of the conditioning node. [[Example|https://www.youtube.com/watch?v=ZYUnyyVgtyA&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=25#t=5m40s]]|
<small>More generally, given disjoint subsets of nodes A, B, and C, X,,A,, is conditionally independent of X,,B,, given X,,C,, if there is no path from any node in A to any node in B that doesn't pass through a node of C.</small>
A [[Conditional random field]], is a Markov network, that models a conditional function $$p(y|x)$$, they are thus called discriminative UGMs. To construct the Markov network, we put an edge, whenever two variables share a factor in the ''product of factors form'' of a CRF. Of course, the product of factors form can be applied to Markov networks that arent CRFs!
See also the generalized [[Factor graph]]
[ext[Chapter from Murphy's book|https://www.cs.ubc.ca/~murphyk/MLbook/pml-print3-ch19.pdf]]
[[Markov Random Field Optimisation|http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/AV0809/ORCHARD/]]
[[Neural networks [3.8] : Conditional random fields - Markov network|https://www.youtube.com/watch?v=ZYUnyyVgtyA&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=25]]
[[wiki|https://www.wikiwand.com/en/Markov_random_field#/Definition]]
A [[Stochastic process]] where the [[Random variable]]s depend only the previous variable. More precisely, each random variable is independent of all the others, given its immediate predecessor, it thus satisfies the [[Markov property]]. For [[Continuous-time stochastic process]], the definition needs to be tackled more carefully.
__Chapman-Kolmogorov equation__
__[[Markov chain]]__
Visualization: http://setosa.io/ev/markov-chains/
[ext[Markov processes and reversibility|http://www.statslab.cam.ac.uk/~frank/BOOKS/book/ch1.pdf]]
[[Markov random field]]
[[David Silver video|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=3m25s]]
A ''Markov property'' refers to any of a certain class of independence properties of [[Random variable]]s defined on the nodes of a [[Network]].
[[Pairwise Markov property]]: {{Pairwise Markov property}}
[[Local Markov property]]: {{Local Markov property}}
[[Global Markov property]]: {{Global Markov property}}
See [[here|https://www.wikiwand.com/en/Markov_random_field#/Definition]], and [[Markov network]]
-----------
[[Stochastic process]]es that satisfy the Markov property are known as [[Markov process]]
[[vid|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=3m25s]]
R. Kindermann and J. L. Snell (1980) -- Markov random fields and their applications. also ''Markov networks''
[[Combinatorics of Feynman Diagrams for the Problems with Gaussian Random Field|https://arxiv.org/abs/cond-mat/9706062]]
SpaceX mission: [[video|https://www.youtube.com/watch?v=W9olSzNOh8s]]
Mars One
Nasa's Orion mission
[ext[https://en.wikipedia.org/wiki/Martingale_(probability_theory)]]
We become what we behold:
https://ncase.itch.io/wbwwb
See [[Medium]]
For discrete space [[Stochastic processes]]
''Discrete time master equation''
For discrete time, probability to be in state $$n$$ at time $$t+\Delta t$$ is:
$$P(n, t+\Delta t) = \sum_{n'} W(n'\rightarrow n)P(n', t)$$
where the $$W(n'\rightarrow n)$$ are the transition probabilities (which can be expressed as a //transition matrix//).
''Continuous time master equation''
For continuous time, we can subtract $$P(n,t)$$ from both sides of the discrete time equation, and divide by $$\Delta t \rightarrow 0$$. Then
$$\frac{d P(n, t)}{dt} = \sum_{n'} w(n' \rightarrow n) P(n', t) - [\sum_{n'} w(n \rightarrow n')]P(n,t) $$
$$= \sum_{n' \neq n} w(n' \rightarrow n) P(n', t) - [\sum_{n' \neq n} w(n \rightarrow n')]P(n,t) $$
where $$w(n' \rightarrow n) = \lim_{\Delta t \rightarrow 0} \frac{W(n'\rightarrow n)}{\Delta t}$$, and where for the bracketed part we used that probability is conserved (i.e. the particle has to go somewhere), $$\sum_{n'} w(n \rightarrow n') = 1$$, and in the second line we cancelled the $$n' = n$$ terms from both terms.
[[Solve using Fourier series|http://www.youtube.com/watch?v=XfK1y3YRSxE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=3#t=38m35s]], as if it is in a (discrete) lattice. For more general networks, Fouriers may not be appropriate.. You can then [[use eigenvector methods|http://www.youtube.com/watch?v=XfK1y3YRSxE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l&index=3#t=58m00s]]
Perturbation method to get approximate solutions to ''singular perturbation problems'' of differential equations, often when the small parameter $$\epsilon$$ is multiplying the highest derivative. Then the $$\epsilon=0$$ problem is of lower order, and will in general not be able to satisfy all the boundary conditions of the original problem
If y is the solution to $$D_\epsilon y = 0$$ then one possible behaviour in such cases is that:
* over most of the range $$\epsilon d^k y/dx^k$$ is small, and $$y$$ approximately obeys $$D_0 y = 0$$.
* in certain regions, often near the ends of the range, $$\epsilon d^ky/dx^k$$ is not small, and $$y$$ adjusts itself to the boundary conditions (i.e. $$d^ky/dx^k$$ large in some places).
In fluid dynamics these regions are known as //boundary layers//, in solid mechanics they are known as //edge layers//, in electrodymanics they are known as //skin layers//, etc.
For this reason the subject of matched asymptotic expansions is sometimes called ''boundary-layer theory''.
Boundary layers can also appear in other circumstances, for instance when the perturbation converts a linear DE into a nonlinear one. See the example in question 2 [[here|https://www1.maths.ox.ac.uk/system/files/legacy/12807/C6.3a_13.pdf]] (in that case, the linear problem has a solution with a singularity at $$x=0$$, but the nonlinearity makes $$f(0) \sim \epsilon^{-1/2}$$. See solution in black oxford notebook.
[[Handout from lecture|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3128/11/OHP-HandoutLecture9.pdf]]
!!__Method of matched asymptotic expansions__
:''1.'' Determine the scaling of the boundary layers (e.g. $$x \propto \epsilon$$ or $$\epsilon^{1/2}$$ or ...). <i style="color:yellow;" class="fa fa-exclamation-triangle" aria-hidden="true"></i> Note, it may be appropriate to rescale the dependent variable too! See example in question 2 [[here|https://www1.maths.ox.ac.uk/system/files/legacy/12807/C6.3a_13.pdf]].
:''2.'' __Reescale__ the independent variable in the boundary layer (e.g. $$x=\hat{x}\epsilon$$, or $$\hat{x}\epsilon^{1/2}$$ or ...)
:''3.'' __Find the asymptotic expansions__ of the solutions in the boundary layers and outside the boundary layers (the ''"inner" and "outer" solutions'')
:''4.'' Fix the arbitrary constants in these solutions by
::''(a)'' obeying the boundary conditions (often for inner solutions)
::''(b)'' ''matching'' -- making the inner and outer solutions join up properly in the transition region between them.
<big><i style="color:yellow;" class="fa fa-lightbulb-o" aria-hidden="true"></i></big> __Trick for finding scaling in boundary layer__: in the boundary layer $$d^2y/dx^2$$ is often significant (though not always!). We must increase $$\alpha$$ (where $$x=\hat{x}\epsilon^\alpha$$) until this term balances the <b>largest</b> of the others in the equation.
!!__Matching of asymptotic expansions__
!!!__Prandtl matching rule__
Most elementary.
You simply require
$$\lim_{x_{BL} \rightarrow \infty}y_{BL}(x_{BL}) = \lim_{x_M\rightarrow 0} y_M(x_M)$$
where $$BL$$ and $$M$$ refer to boundary layer, and middle (outer) solutions and variables.
!!!__van Dyke matching rule__
Van Dyke's matching 'rule' usually works (more powerful than Prandtl's) and is much more convenient than the Intermediate variable matching below. The rule is
|$$(m\text{ term inner})(n\text{ term outer}) = (n\text{ term outer})(m\text{ term inner})$$|
<span style="color:magenta;">^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small>^^o^^<small>o</small>,,o,,<small>o</small></span>
I.e. in outer expansion, in the outer variables expand to $$n$$ terms; then switch to inner variables and reexpand to $$m$$ terms.The result is the same as first expanding the inner expansion in the inner variables to $$m$$ terms, then switching to outer variables and reexpanding to $$n$$ terms.. <span style="color:bisque;">Hmm, but these expansions are expressed in different variables. I guess, as a last implicit step, I should convert to the same variables to compare.</span> <span style="color:coral;">What's the justification of this rule?</span>
<i style="color:yellow;" class="fa fa-exclamation-triangle" aria-hidden="true"></i> When using this matching rule you must treat log as $$O(1)$$ because of the size of logarithmic terms.
!!!__Intermediate variable matching__
Most advanced and powerful of the methods. More tedious to apply too.
Expansions for two "contiguous" regions should actually have an __overlap__ or __transition region__ where __both expansions are valid__.
For example, suppose there is a boundary layer for $$x=\epsilon \hat{x}$$ for $$\hat{x} = O(1)$$, but the expansion we find is actually valid for $$\hat{x} = o(\epsilon^{-1})$$, i.e., the expansion breaks when $$\hat{x}$$ becomes $$ord(\epsilon^{-1})$$ or larger. Suppose also, that the middle, or outer region is defined for $$x=ord(1)$$, but the expansion is valid for $$x=ord(\epsilon^\alpha)$$, for $$0<\alpha <1$$. Then in any region with $$x=ord(\epsilon^\alpha)$$, for $$0<\alpha <1$$, both expansions are valid, and therefore should __match__ due to the uniqueness of [[Asymptotic approximation]]s.
Note some terms jump order: a term in the examples in the notes comes from the inner expansion of the first-outer term, but it also comes from the outer expansion of the second-inner term. "First-outer" refers to first order in the expansion in outer region. The terms "inner and outer expansion" here refer to the expansion in terms of rescaled variables, but these terms are most often used for the van-Dyke rule where the "outer expansion" refers to the expansion of some term in terms of the outer variable, and similarly for the "inner expansion". The nomenclature he uses, is a bit confusing though.
[img[Selection_197.png]]
!!__Composite expansion__
A ''composite expansion'' is an expansion that is valid across the whole domain. It built as $$y_{BL} + Y_M - \text{overlaps}$$, where $$y_{BL}$$ are the solutions in the boundary layers, $$Y_M$$ are the outer solutions, outside boundary layers, and $$\text{overlaps}$$ are overlaps, removed to avoid double counting. The $$\text{overlaps}$$ term removes the contribution from the inner expansion, when looking at the outer region(s); or the contribution from the outer expansion, when looking at the inner region(s). In practice, this can be done by substracting a term of the form $$(m\text{ term inner})(n\text{ term outer})$$ at the right order.
It is not unique, because it is not in standard Poincare form
!!__Boundary and transition layers__
__Boundary layers__
[img[Selection_198.png]]
Think of the $$\epsilon = 0$$ problem, and that to have the possibility of a non-trivial boundary layer we need some solution in the inner region which decays as we move towards the outer. In the problem considered in the notes, for example, the non-constant solution in the right-hand "boundary layer" grew exponentially as we moved to the outer, so there could never be a boundary layer at $$x = 1$$.
__Transition or interior layers__
Regions of fast change, not in the boundary, but in the interior of the domain. Finding the position of an interior layer can sometimes be hard.
__Non-linear boundary layers__
__Boundary layer at infinity__
<mark>Revise these</mark>
---------
__Example: van der Pol oscillator__
<mark>Revise this example</mark> pages 36-41
A particular kind of [[Bulk matter]]
See [[Materials science]]
''Materials science'', also commonly known as materials science and engineering, is the [[Science]] and [[Engineering]] of material properties, their design, and uses.
A ''material'', I think, most often refers to a type of [[Bulk matter]] (identified by its composition in terms of phases and [[chemical|Chemistry]] composition). However it may sometimes refer to chemical substances per se, or other non-bulk, but relatively simple, arrangements of matter, as for example, in [[Nanotechnology]]. It may even be used for more complex arrangements of matter so that a bulk description is not totally appropriate, such as in "smart materials", where ideas from [[Complex systems]] may be necessary for their description.
Materials science needs to describe the specific properties of each material. [[Constitutive equations]] play a fundamental role in the theory of these properties.
The physics of materials is based on [[Condensed matter physics]]. If dealing with fluids, it of course uses [[Fluid mechanics]] too.
[[Best materials course ever (mostly metals)|http://www.msm.cam.ac.uk/phase-trans/teaching.html]]
------------
See classification of materials in [[Condensed matter physics]].
Some important materials: [[Polymer]]s, [[Metal]]s, [[Ceramic]]s, [[Composite material]].
See also [[Soft materials]], [[Chemistry]], [[Surface science]]
Some material properties:
* [[Hydrophobicity]]
* Malleability
* Ductility
* Strength
* Hardness
* etc...
<mark>See for a good resource on materials properties</mark>
------------
[[Variational Methods for Microstructural Evolution|http://www.ctcms.nist.gov/~wcraig/variational/variational.html]]
//Some IUPAC definition recomendations//:
[[Definitions of terms relating to the structure and processing of sols, gels, networks, and inorganic-organic hybrid materials (IUPAC Recommendations 2007)|http://www.degruyter.com/view/j/pac.2007.79.issue-10/pac200779101801/pac200779101801.xml]]
[[Terminology of polymers and polymerization processes in dispersed systems (IUPAC Recommendations 2011)*|https://espace.library.uq.edu.au/view/UQ:266979/UQ266979_OA.pdf]]
Libraries for [[maths|Mathematics]] on [[JS|JavaScript]]
http://algebra.js.org/
http://algebrite.org/
http://coffeequate.readthedocs.io/en/latest/
http://af.id.au/javascript-cas/
http://mathjs.org/
[[AugMath]]
See also [[Maths frontend web libraries]]
[[NIMBioS channel|https://www.youtube.com/user/NIMBioS/featured]]
http://quant.bio/
Has applications to [[Systems biology]] for instance.
//Things can make sense//
Mathematical logic is an essential part (if not //the// essential part) of the ''foundations of mathematics''
See [[Discrete mathematics]], [[Theoretical computer science]], [[Logic]]..
//Video lectures//:
[[Mathematics - Mathematical Logic|https://www.youtube.com/playlist?list=PL3o9D4Dl2FJ9q0_gtFXPh_H4POI5dK0yG]]
[[NPTEL Computer Sc - Discrete Mathematical Structures|https://www.youtube.com/playlist?list=PL49BFCFA7DE423CEC]]
[[Metamathematics]]
!!__Boolean logic__
[[Boolean algebra]]
!!__[[Set theory]]__
[[Theory of types]]. An axiomatization of set theory by Russell and Whitehead, that creates a hierarchy of sets to avoid [[Strange loop]]s and [[Paradox]]es
!!__[[Proof theory]]__
--------------
[[Formal system]]s
http://us.metamath.org/mpegif/mmset.html#overview
[[Metamath Proof Explorer: A Modern Principia Mathematica|https://www.youtube.com/watch?v=8WH4Rd4UKGE]]
http://ghilbert-app.appspot.com/ -- http://math.stackexchange.com/questions/1111758/is-there-a-canonical-database-of-theorems
[[LaTeX to OpenMath|http://www.maths.tcd.ie/~richardt/openmath/ml2om.pdf]]
https://en.wikipedia.org/wiki/OpenMath [[A critique of OpenMath|http://www.cs.berkeley.edu/~fateman/papers/openmathcrit.pdf]]
<<<
While I applaud the occasional successes in these ventures, the result have been unimpressive even from the range of computations routinely performed by computer algebra systems. They certainly represent a small scope compared to the kinds of mathematics human researchers deal with informally on computers. (Consider all the advanced mathematics routinely typeset by use of the program TEX.) My view is that much of today’s applicable mathematics, including that in ordinary texts and journals, is simply too informal tobe handled by the logical and algebraic means typically proposed by the con-structivists. Indeed, much of mathematical discourse goes beyond informality to be (unintentionally) ambiguous on its face. The ambiguity can generally be resolved by a sufficiently contextual interpretation, often requiring a reader to be skilled in the mathematical subdiscipline – not merely the notation – being represented.
<<<
<<<
Almost any ambitious computer algebra system that must eventually meet performance ex-pectations seems to abandon proofs or (complete) formal rigor
<<<
<<<
One person’s syntax is another person’s semantics
<<<
[[AugMath]] should be able to represent informal mathematics, by basing its philosophy in the notation, just like LaTeX itself, rather than in the semantics. Semantics can be added later as a layer...
Get functions mathML from here: http://functions.wolfram.com/Bessel-TypeFunctions/BesselI/11/0001/
While all aspects of mathematics //can be potentially applied//. Mathematical methods refers to those parts of mathematics //designed to be applied//.
----------
This can also be called ''applied mathematics''.
One important sub-area is __industrial mathematics__, mathematics applied to industry.
See https://www.siam.org/
Special functions and their properties: http://dlmf.nist.gov/
[img[Selection_611.png]]
See [[Neural network theory]]. For choices of nonlinear operators see [[Layers for deep learning]]
------------------------
Notes from Rodrigo Mendoza's talk
Deep learning is an area of machine learning that studies learning algorithms with //multiple levels of abstraction//
Why Deep Learning models perform so well?
Seems to be a result of:
*Very large datasets
*Increasing computing power
*Flexibility of the models. Lots of parameters when lots of layers. Furthermore multiple layers avoide the curse of dimensionality
Mathematical difficulty because: Nonlinearly, non-convexity (convex optimization or complex analysis techniques not available), many d.o.f.
ResultsL
*Universality
*Loss-function landscape
Neural network composed of neurons.
Data into Dendrites, scales. Axom computes (apply nonlinear function) and propagates output trough synapse.
A //multilayer feedforward neural network//.
L+2 layers. L //hidden//
The neural network is just a funciton from $$R^N$$ to $$R^M$$, $$M=1$$ wlog..?..
Training, given dataset of inputs and outputs and want function to map these as well as possibly
Use Loss function and regulariser (penalization on size of parameters. Could also try to maximize sparsity, Occam's razor, bias towards simpler model. Also makes surface more convex).
Then minimize //empirical risk//. To minimize we use stochastic gradient descent.
Assuming function as being continuity, differentiability, convexity.
Can a multilayer feedworward network f approximate g arbitrarily well, for a very general g.
__Universality__
We can't expect f for the model considered (one layer) to approximate any g whatsoever, there are some very pathological functions.We can assume g is continuous, or just Lebesgue measurable (use [[this|http://www.jstor.org/stable/85935?seq=1#page_scan_tab_contents]] metric for defining closeness in this case).
We can show then f can approximate g approximately well.
Many other models are also known to be universal.
__Other minima.__
Loss surface is the surface defined by the empirical risk, EM..
The epigraph is non-convex.
Local minima o EM are known to abound.
Results:
*For large-scale neworks most local minima are equivalne and yield similar performance on a test set.
*The probabilliy of finding a bad local minimum is non zero for small networks and decreases quickly with network size. The higher dimension the dimension the lower the probability that all curvatures are positive, so more saddle points and less minima... Hmmmmm
*Struggling to find the global minimum on the training set is not useful in practice and may lead to overfitting.
Other results: only a few parameters matter.
The manifold hypothesis: meaningful data often concentrates on a low dimensional manifold, so large amounts of parameters don't matter.
---->See dissertation topic proposed by Ard Louis.
Energy propagating from node i through path j
Analogy between loss function of neural network and hamiltonian of spin glass.
(Multilayer: composition of functions.)
*Minimizing the empirical risk is a good idea.
*Neural networks may be over-parametrised.
*But over-parametrisation gives these nice results about local minima
[[Selected Topics in Mathematical Physics by Prof.Balakrishnan|https://www.youtube.com/watch?v=b5VUnapu-qs&list=PLiUVvsKxTUr66oLF6Pzirc1EgSstMbRZR]]
See this combination of [[Machine learning]] (in particular [[Natural language processing]]) and [[Computer algebra]]. http://www.parsegon.com/
[[Matlab]]
Maple
Mathematica
[[AugMath]]
http://www.cinderella.de/files/HTMLDemos/
http://www.geometrygames.org/KaleidoTile/
Geogebra
http://mathgl.sourceforge.net/doc_en/Main.html
http://www.swmath.org/
Cinderella
Cool surfaces software: https://imaginary.org/program/surfer
__Mathematical collaboration and organization__
http://formulasheet.com/ Save, share, organize, and find equations on the web.
Mathematics is the study of ''structures'' themselves. These are necessary in [[Science]] and in [[Art]], as both require the invention of structures to either explain (and thus //understand//) the world, or for any other purpose (in the case of Art).
Mathematics, however, doesn't concern itself with the purposes or details of particular structures; rather, it commits itself with the abstract properties common among many structures.
It is both the Art and Science of the ''structure of structures''. It studies many structures in the world, and creates an abstract structure to understand them. In this sense it is a Science. It also creates new unobserved abstract structures, often, generalizing observed ones. In this sense it is an Art.
!!!__Common structures__
* One can have things and sets of things ([[Set theory]])
* Relations among things
** One can get new things by putting together old things, [[Abstract algebra]]
** or things may just have some given relations ([[Graph theory]], [[Network theory]])
* One can count things ([[Number theory]])
* One can have many, many things ([[Analysis]]). For example, it seems like there is an //infinity// of instants in every second..
** Can we define things that make sense, as the number of things keeps growing? [[Limits and infinity]]
*** Can we still add and subtract these things? If yes, -> //Differential stuff//! (e.g. [[Differential equations]], [[Differential geometry]])
* Things may change, for example, in time
** Things may undergo processes, that can be composed, one after the other. [[Category theory]]
** Things may evolve according to some given rule: if you're here, go there. [[Dynamical system]]
* Things can have shape ([[Geometry]])
** Things can have a shape, made out of many, many flat pieces. If done right, we get [[Differential geometry]]
** Can we get shapes by combining things in certain ways? [[Algebraic geometry]]
** Some shapes are more similar than others ([[Topology]])
*** Can we compare shapes by subdividing a shape in many (possibly many <big>//many//</big>) parts, and looking at how these parts relate and overlap? [[Point-set topology]]
*** Can one combine shapes? [[Algebraic topology]]
Mathematics is sometimes called //formal sciences//.
//Useful resources and tools//
http://world.mathigon.org/
[[Geogebra web app|http://app.geogebra.org/]]
[[Demos graphing calculator|https://www.desmos.com/calculator]]
[[FormulaSheet|http://formulasheet.com/]]
[[Online equation editor|http://s1.daumcdn.net/editor/fp/service_nc/pencil/Pencil_chromestore.html]]
[[EquationMap|http://equationmap.com/#B5F8SRR330]]
[[WolframAlpha|http://www.wolframalpha.com/]]
[[https://en.wikipedia.org/wiki/Category:Mathematics_portals]]
http://www.msri.org/web/msri/online-videos
//Books//
[[How to solve it - Polya|https://notendur.hi.is/hei2/teaching/Polya_HowToSolveIt.pdf]]
[[Street-fighting mathematics|http://streetfightingmath.com/index.html]]
//People//
http://math.ucr.edu/home/baez/
[[Steven Strogatz|http://www.stevenstrogatz.com/]]
[ext[http://euler.nmt.edu/~jstarret/]]
//Other links//:
https://jeremykun.com/
http://mathgl.sourceforge.net/doc_en/Main.html
http://www.theshapeofmath.com/princeton/dynsys
https://www0.maths.ox.ac.uk/courses
From http://bactra.org/thesis/single-spaced-thesis.pdf :
Formalizing intuitions (Quine 1961) insist, the goal [of formalizing some notion] is that the formal notion match the intuitive one in all theeasy cases; resolve the hard ones in ways which don't make us boggle; and let us frame simple and fruitfulgeneralizations.
https://betterexplained.com/
------------
http://us.metamath.org/mpegif/mmset.html#overview
http://planetmath.org/
http://map.mathweb.org/
http://www.cut-the-knot.org/
http://www.ams.org/open-math-notes?utm_content=buffer7c046&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer
Classification of mathematics: http://www.ams.org/mathscinet/msc/msc2010.html?t=53Axx&btn=Current
A ''network'' is a collection of ''nodes'' joined by ''edges''. More generally, it is a collection of elements and their interactions. Most of the time, it has
the same mathematical structure as a ''graph'', $$G$$, defined as an
ordered pair $$(V,E)$$, where:
* $$V=\{i\}$$, a set of ''nodes'' (a.k.a. ''vertices'').
* $$E=\{(i,j) \in V \times V\}$$, a set of ''edges'' (a.k.a. links, tie,
etc.)
<small>However, by interpreting an edge as a more general kind of relation, its
mathematical structure can be a [[hypergraph|hypergraph]]. One can also have different types of vertices and edges defined for a network.</small>
A ''simple network'' is a binary, undirected network that only has a
single edge between a pair of nodes (i.e. no ''multi-edges''), and
doesn't have ''self-edges'' (a.k.a. self-loops).
!!!__Types of edges__
|Undirected: $$(i,j) \Leftrightarrow (j,i)$$. |
|Directed: $$(i,j) \nLeftrightarrow (j,i)$$|
|Weighted: edges can have any real value associated.|
|Unweighted: can only have 0 or 1 (a.k.a. ''binary'').|
!!!__Representations__
Representations: Edge lists, adjacency matrices<small>(a.k.a. network matrix)</small>.
__[[Adjacency matrix]]__
Related: [[Graph laplacian]]
__[[Incidence matrix]]__
[[Adjacency Matrix and Incidence Matrix|https://www.youtube.com/watch?v=LUDNz2bIjWI&index=7&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
__Cocitation and bibliographic coupling in directed networks__
Two useful matrices, derived from the directed network adjacency matrix
$$A$$ are the following (both can be used to define adjacency matrices
that are symmetric and thus undirected! $$\leftarrow$$ easier to
analyze):
Cocitation matrix: $$C=AA^T$$. Nodes related if there is a node that points to both.
Bibliographic coupling matrix: $$B=A^TA$$. Nodes related if there is a node to which both point.
!!__[[Families of graphs]]__
!!__Other Mathematical aspects__
The [[degree|Degree of a vertex (Graph theory)]], $$k_i$$, of a vertex, $$i$$, is the number of edges connected to the vertex.
[[Sum of Degrees is ALWAYS Twice the Number of Edges|https://www.youtube.com/watch?v=YoRhmz_OSBY&index=6&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
__Paths__
A [[path|Path (Graph theory)]] in a network is a sequence of of nodes such that every pair of nodes in the sequence is connected by an edge in the network.
[[Definition of path, cycle, trail, circuit|http://math.stackexchange.com/questions/655589/what-is-difference-between-cycle-path-and-circuit-in-graph-theory]]
Definition is extended to directed case by only permitting traversing
in the direction of edge. Note only directed graphs can have 2-cycles.
__Components__
A [[component|Component (Graph theory)]] is a subset of the network for which all pair of vertices have at least one path, and which is maximal (i.e no extra nodes can be added that preserve this property).
__[[Independent paths, connectivity, and cut sets]]__
Number of //independent paths// between two vertices (the //connectivity//) gives measure of how strongly connected they are. Paths can be //vertex-independent// if they share no vertex (other than starting or ending vertices), or //edge-independent// if they share no edge.
A //vertex (edges) cut set// is a set of vertices (edges) that if removed will disconnect a specified pair of vertices. A //minimum cut set// is the smallest such set for the vertices.
__[[Graph laplacian]]__
The graph laplacian is a useful quantity, derived from the adjacency matrix, which can be used to describe diffusion precesses in a network, as well as in problems of random walks, resistor netowkrs, graph partitioning and network connectivity.
__[[Random walks|Random walk in a graph]]__
A //random walk// is a path across a network created by taking repeated random steps. They are usually allowed to traverse edges more than once, and visit vertices more than once. If note it is a //self-avoiding random walk//. They are mathematically connected to resistor networks.
[[AsciiMath|http://asciimath.org/]]
http://mathquill.com/
https://www.mathjax.org/
https://khan.github.io/KaTeX/
[[AugMath]]
http://mathnotepad.com/ (uses math.js)
http://jaxedit.com/note/
__Packages for network analysis__
[[Brain connectivity toolbox|https://sites.google.com/site/bctnet/Home]]
[[DistMesh - A Simple Mesh Generator in MATLAB|http://persson.berkeley.edu/distmesh/]]
[[Matrix Norm|http://mathworld.wolfram.com/MatrixNorm.html]]
[[Matrix calculus]]
[[Random matrix theory]]
[[Binomial Expansion for non-commutative setting|http://mathoverflow.net/questions/78813/binomial-expansion-for-non-commutative-setting]]
!!__Identities__
[[log-det identity]]
!![[http://www4.ncsu.edu/~pfackler/MatCalc.pdf]]
https://en.wikipedia.org/wiki/Matrix_calculus
[[pdf|https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwi74Kvq_f3NAhVCAsAKHTU7AvkQFggeMAA&url=http%3A%2F%2Fwww.colorado.edu%2Fengineering%2Fcas%2Fcourses.d%2FIFEM.d%2FIFEM.AppD.d%2FIFEM.AppD.pdf&usg=AFQjCNFDszV1tyRWnfNpnL4SM3-aocs71g&sig2=2EOihoSvho3_KS8X_OGchg]]
http://math.stackexchange.com/questions/553609/is-there-a-general-form-for-the-derivative-of-a-matrix-to-a-power
//Matroid theory//
A [[matroid|https://en.wikipedia.org/wiki/Matroid]] is a structure that captures and generalizes the notion of linear independence in vector spaces. There are many equivalent ways to define a matroid, the most significant being in terms of independent sets, bases, circuits, closed sets or flats, closure operators, and rank functions.
[[Matroids as a Theory of Independence by Federico Ardila|https://www.youtube.com/watch?v=4EvpzV_3RXI]]
See books on matroid theory
See [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture2_1.pdf]]
Basic inequality:
| flow out of vertices on the source part of the cut $$\leq$$ capacity of the cut| (1)|
__''Ford-Fulkerson algorithm'': algorithm to find maximum flow using residual graph__
* Can prove that using this algorithm you find a cut for which the inequality (1) is tight.
* As the inequality holds for all flows, and for all cuts, this should be the ''maximum flow and minimum cut''
This is an example of using continuous optimization (maximum flow) to solve a discrete optimization problem (min cut).
For irrational capacities, the FF algo can lead to infinite number of iterations.
__Chosing paths optimally__
Dinits algorithm
--------------
[[Independent paths, connectivity, and cut sets]]
!!!Maximum margin principle
[img[max-margin_illustration.png]]
Maximise the distance of the
closest point from the decision boundary.
Points that are closest to the decision boundary are support vectors
!!![[Support vector machine]]s
!!!Application to [[Transfer learning]]
''[[Max-margin|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=29m25s]]'': learning a function that identifies sensible data (e.g. sentences that make sense), thats what we do with the algorithm he explains of finding a prob dist bigger at the data points that "anywhere" else. This will, in particular, make the NN learn a good representation of the data, or //embedding//. For this we use ''hinge loss''. In practice, [[we do this|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=37m30s]]
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
A learning principle that can be viewed as approximating the expected value of the output from a model, using [[Bayesian statistics]], by only considering the hypothesis with maximum a posteriori probability.
[[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=9m36s]]
It can be seen as formally equivalent to [[Maximum likelihood]] by multiplying the likelihood by the prior (adds the log of the prior to the log likelihood).
A learning principle that can be viewed as approximating the expected value of the output from a model, using [[Bayesian statistics]], by only considering the hypothesis with maximum a-posteriori probability (the most likely).
[[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=9m36s]]
It can be seen as formally equivalent to [[Maximum likelihood]] by multiplying the likelihood by the prior (adds the log of the prior to the log likelihood).
//aka maximum likelihood estimation, MLE//
''Minimize a cost function'', which often is the negative log [[likelihood|Likelihood function]] (similar to entropy. More precisely, cross-entropy, or relative entropy), which corresponds to ''maximizing likelihood''. Likelihood is the probability of getting the right $$y$$ given $$x$$ and $$\theta$$, i.e. the probability that a given model predicts the right outputs. This is equivalent to finding the most likely $$\theta$$ in the Bayesian posterior, given a flat prior (but if we add a ''regularizer'', we can tweak the prior, by just adding a term to the log likelihood). If our model uses a Gaussian distribution to predict the data (where the $$\theta$$s are the means), maximizing likelihood is equivalent to minimizing spring energy for springs vertically placed between fit curve and data.
The maximum likelihood is found by [[Optimization]], often by [[Stochastic gradient descent]].
If we want the whole distribution of likelihoods over $$\theta$$s, we need to use Bayesian statistics, which involves doing complicated integrals, often done numerically using [[Montecarlo methods]]
See [[video|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=43m20s]]
Too see the application of this method in [[Supervised learning]] see [[Discriminative learning]], and [[Generative learning]]
https://www.wikiwand.com/en/Maximum_likelihood_estimation
(See [[Arrival of the frequent]] for context)
See also [[Wright-Fisher model]]
The //Hamming distance// (i.e. the number of differing letters, or mutations) $$d$$ is then distributed binomially:
$$h(d) = \binom{L}{d} \mu^{d} (1-\mu)^{L-d}$$
The expected number of individuals with genotype $$p$$ that arises at generation $$t$$ can be written as:
|$$m_p (t) = \sum_i^N \sum_{d=1}^L h(d) \Phi_p (g_i, s_i, d) = \sum_i^N \tilde{\Phi_p} (g_i, s_i)$$|Eq.1|
<a id="manual_links"/>
where $$\Phi_d (g_i, s_i, d)$$ is the probability that a $$d$$-fold mutation of genotype $$g_i$$ (selected for reproduction according to fitness $$1+s_i$$) generates an individual with phenotype $$p$$. It takes into account the ''genotype-phenotype map''. $$g_i$$ is the genotype of the $$i$$th member of the population, with a total of $$N$$ members. See derivation of this below:
As the number is distributed binomially, the average number is $$m_p = N(\text{probability for single offspring to get phenotype p})$$. Then we define $$ \tilde{\Phi_p}(g_i, s_i) = (\text{the probability for the single offspring to get to phenotype p}$$ $$\text{given it inherits a mutated version of parent i})$$. Furthermore, $$(\text{probability for single offspring to get phenotype p})$$ = $$ \sum_{i=1}^N (\text{probability of single offspring to get phenotype p through parent } i) $$ = $$\sum_{i=1}^N \tilde{\Phi_p}(g_i, s_i) \times (\text{probability to inherit from parent } i)$$ = $$\sum_{i=1}^N \tilde{\Phi_p}(g_i, s_i) \frac{(1+s_i)}{\sum_{j=1}^N (1+s_j)}$$. Finally,
$$m_p = N(\text{probability for single offspring to get phenotype p})$$ = $$\sum_{i=1}^N \tilde{\Phi_p}(g_i, s_i) \frac{N(1+s_i)}{\sum_{j=1}^N (1+s_j)}$$ $$\equiv \sum_{i=1}^N \Phi_p'(g_i, s_i) $$
By fine-graining the transitions from $$g_i$$ to a phenotype-$$p$$ genotype into transitions with particular mutation numbers $$d$$, we can write $$\Phi_p'(g_i, s_i) \equiv \sum_{d=1}^L \Phi_p (g_i, s_i, d)$$, recovering Eq. 1
[#[manual links]] (try to upgrade TW to make this work)
//The actual number of individuals with genotype $$p$$ will follow a binomial distribution// (as explained for a simple case in [[Wright-Fisher model]]), with probability $$m_p(t)/N$$, and number of trials $$N$$. The probability of none of the offspring having phenotype $$p$$ is: $$(1-m_p(t)/N)^N \approx e^{-m_p(t)}$$, the approximation holds for large $$N$$, and may be seen as [[approximating the Binomial distribution by a Poisson distribution|https://en.wikipedia.org/wiki/Binomial_distribution#Poisson_approximation]].
If we __assume__ that $$Ld \ll 1$$, i.e. the average number of mutations per genotype is very small, then $$h(d) \ll h(1)$$ for all $$d>1$$, and $$h(1) \approx L \mu$$ ($$h(0) \approx 1$$ while $$h(0) < 1$$ of course).
With the above assumption that $$Ld \ll 1$$, $$\Phi_p'(g_i, s_i) = \sum_{d=1}^L h(d) \Phi_p (g_i, s_i, d) \approx \Phi_p (g_i, s_i, 0) + \Phi_p (g_i, s_i, 1) L\mu$$. Also, $$\Phi_p (g_i, s_i, 0) = 0$$, if $$p \neq q$$. Next, if we __assume__, $$s_i = 0$$, for all $$i$$ with $$g_i$$ mapping to phenotype $$q$$ (i.e. in space $$\mathcal{N}_q$$), __and__ that it all starts within $$\mathcal{N}_q$$, we have
|$$m_p(t) = \sum_{i=1}^N \Phi_p'(g_i, s_i) \approx \sum_{i=1}^N \Phi_p (g_i, 0, 1) L\mu$$|Eq.2|
We can also __define__ the averaged {expected number of offspring with phenotype $$p$$ at one generation, which inherited from genotype $$g_i$$ at the previous generation via a single mutation}, i.e the average of $$\Phi_p(g_i, 0, 1)$$, over all $$g_i$$ in $$\mathcal{N}_q$$. We will write abuse notation, and use the label $$i$$ in $$g_i$$ to label a genotype in $$\mathcal{N}_q$$, so that $$i = 1, 2, ... N_q$$. The average is then:
$$\Phi_{pq} = \frac{1}{N_q}\sum_{i=1}^{N_q} \Phi_p(g_i, 0, 1)$$
Furtheremore, we should note that, as $$\Phi_p'(g_i, s_i) = \tilde{\Phi_p}(g_i, s_i) \frac{N(1+s_i)}{\sum_{j=1}^N (1+s_j)}$$ (and a similar expression for the $$d$$ dependent quantities). When $$s_i = 0$$, we find $$\Phi_p'(g_i, s_i) = \tilde{\Phi_p}(g_i, s_i)$$, and also, for example, that $$\Phi_p(g_i, 0, 1) = \tilde{\Phi_p}(g_i, 0, 1)$$, where $$\tilde{\Phi_p}(g_i, s_i, d) = (\text{the probability for the single offspring to get to phenotype p}$$ $$\text{given it inherits a mutated version of parent i, via a single-point mutation (d=1)})$$. Thus $$\Phi_{pq}$$ is the average of this probability.
We also define the ''robustness'' of phenotype $$q$$, $$\rho$$ as equal to the average probability over all $$\mathcal{N}_q$$ of a neutral mutation (i.e. one from $$\mathcal{N}_q$$ to $$\mathcal{N}_q$$). Under the approximate assumptions above, $$\Phi_{qq} \approx \rho$$. If we __assume__ also that the population is large enough (more precisely, we are in the [[Polymorphic limit (Wright-Fisher model)]]), we can use a ''mean field approximation'': approximate $$ \Phi_p (g_i, 0, 1)$$ by $$\Phi_{pq}$$. This approximate works best if the population is large enough that most of the neutral space $$\mathcal{N}_q$$ is populated (or in the author of the paper word's "1-mutant neighbourhood of the population is similar to that of the whole neutral space"). Using this in Eq.2:
|$$m_p(t) \approx L\mu \sum_{i=1}^N \Phi_{pq} = N L\mu \Phi_{pq}$$|Eq.3|
[[Statistical field theory]] that ignores spatial fluctuations. I.e. just describes the behaviour of the //mean// quantities of interest. Can get such behaviour by applying the method of steepest descents to the partition function.
A mean field model is essentially a simplified model in which ''every degree of freedom finds itself in the same environment as every other''; in other words, ''local spatial fluctuations have been discarded''. It is precisely these fluctuations that drive much of the interesting behavior of many phase transitions, so mean field models are often a poor guide to understanding behavior (called the [[critical behavior|Critical phenomena]])at or near a transition. On the other hand, they’re often fairly reliable at providing insights into thelow-temperature properties of a system—its order parameter and broken symmetry, and the low-energy excitations that determine its thermal properties.
!!!__Approaches__
There are different ways in which the mean field approach can be realized, which for technical reasons turn out to be essentially equivalent.
* One such way is to ''extend the range of the interactions to infinity''. This means that every spin interacts equally strongly with every other, erasing any notion of distance or geometry: everyone is effectively a nearest neighbor to everyone else.
* ''Extend to infinite dimension''. mean field theory typically becomes exact for the corresponding short-range model in the limit of infinite dimensionality [85]
mean field models, infinite-range models, and short-range models in infinite dimension are indistinguishable. The claim is that for a given system, all three should display essentially the same thermodynamic behavior, but the models may be different in other respects.
!!!__Examples__
[[Regular solution model|Liquid-liquid unmixing]]
[[Bragg-Williams theory]] for binary alloys or Ising model (similar to above).
[[Curie-Weiss theory]] for the paramagnetic-ferromagnetic phase transition.
A hierarchical [[Clustering]] algortihm.
[[Mean Shift Intro - Practical Machine Learning Tutorial with Python p.39|https://www.youtube.com/watch?v=3ERPpzrDkVg&index=39&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
See [[Measure theory]]
A measurable function between two sets $$X$$ and $$Y$$, belonging to [[Measurable space]]s $$(X, A)$$, and $$(Y, B)$$, is {a [[Function]] $$f: X \rightarrow Y$$, s.t. for any $$E \in B$$, the [[Preimage]] of $$E$$ is in $$A$$}. I.e. the preimage of any set in the [[Sigma-algebra]] of the co-domain is in the [[Sigma-algebra]] of the domain.
------------------------
https://en.wikipedia.org/wiki/Measurable_function
See [[Measure theory]]
A space consisting of a set $$\Omega$$, and a [[Sigma-algebra]] $$\mathcal{A}$$.
A ''measure'' $$\mu$$ on a set $$\Omega$$, with [[Sigma-algebra]] $$\mathcal{A}$$, is a [[Function]] $$\mu: \mathcal{A} \rightarrow [0, \infty]$$, s.t.
# $$\mu(\emptyset)=0$$
# //countable additivity//. $$\mu(\bigcup\limits_{i=1}^{\infty} E_i) = \sum\limits_{i=1}^{\infty} \mu(E_i)$$ for any collection $$E_1, E_2, ... \in \mathcal{A}$$ of pair disjoint sets.
Specifying a measure on a sigma-algebra is simplified by the
!!Types of measures
* [[Probability measure]]s
* [[Lebesgue measure]]
------------------
[[Definition|https://www.youtube.com/watch?v=xlfH6Rk2GCM&index=3&list=PL17567A1A3F5DB5E4#t=7m41s]]
[[(PP 1.4) Measure theory: Examples of Measures|https://www.youtube.com/watch?v=TxBLRz-gNq4&list=PL17567A1A3F5DB5E4&index=4]]
[[(PP 1.5) Measure theory: Basic Properties of Measures|https://www.youtube.com/watch?v=ILXe_NsvQ6Q&index=5&list=PL17567A1A3F5DB5E4]]
A [[Measurable space]] with a [[Measure]].
[[Math 574, Lesson 1-4: Measure Spaces|https://www.youtube.com/watch?v=WKdy_OxdUbk]]
----------------
http://mathworld.wolfram.com/MeasureSpace.html
[[Measurable space]]
[[Sigma-algebra]]
[[Measure]]
[[Measure space]]
[[Measurable function]]
[[Measure Spaces|http://www.math.uah.edu/stat/prob/Measure.html]]
----------------------
[[(PP 1.1) Measure theory: Why measure theory - The Banach-Tarski Paradox|https://www.youtube.com/watch?v=Tk4ubu7BlSk&list=PL17567A1A3F5DB5E4]]
[[(PP 1.2) Measure theory: Sigma-algebras|https://www.youtube.com/watch?v=21a85f1YS5Q&index=2&list=PL17567A1A3F5DB5E4]]
A ''Measure-theoretical dynamical system'' is comprised of:
* a [[Measurable space]]
* a [[measurable map|Measurable function]]
* a non-singular [[Measure]]
This space can be considered, without restriction to be a [[Probability space]]. See Amigo's book.
See [[here|https://www.dropbox.com/s/fv3fc6jawf9oswl/%5BManfred_Denker%5D_Ergodic_Theory_on_Compact_Spaces%28BookZZ.org%29.djvu?dl=0]] ([[local|file:///home/guillefix/Dropbox/COSMOS/Mathematics/Ergodic%20theory/%5BManfred_Denker%5D_Ergodic_Theory_on_Compact_Spaces(BookZZ.org).djvu]]).
A [[Dynamical system]] on a [[Measurable space]] has a //natural// or //physical invariant measure//, corresponding to the [[Probability measure]] that numerical simulations of the system would produce asymptotically.
If we know the structure of a network, then we can calculate a number of quantities or measures that capture features of the network topology (and geometry). Originally, a lot of these ideas were developed for //social network analysis//, but they are used elsewhere now too.
!!!Centrality measures
Trying to answer: "Which are the most important or central vertices (or edges, or other substructures) in a network?"
__Degree centrality__
Simply the [[degree of a vertex|Degree of a vertex (Graph theory)]] can be used as a measure of its centrality.
__[[Eigenvector centrality]]__
The ''eigenvector centrality'' (first defined by Bonacich in 1987), is defined by:
$$\mathbf{A}\mathbf{x}=\kappa_1 \mathbf{x}$$
where $$\mathbf{x}$$ is the vector of centralities, and $$\kappa$$ is the largest eigenvalue of $$\mathbf{A}$$
A node can be important because it is connected to many nodes, or because it is connected to important nodes, or both.
__[[Katz centrality]]__
Katz centrality solves the problem posed above by giving all vertices a "free" centrality:
$$\mathbf{x}=\alpha\mathbf{A}\mathbf{x}+\beta \mathbf{1}$$
__[[PageRank]]__
There is one potentially undesirable feature of Katz centrality. An important vertex pointing to many vertices makes all those vertices important. The centrality gained by virtue of receiving an edge from a prestigious vertex is diluted by being shared with so many others (think a web directory like Google or Yahoo! pointing to my page. My page is not that central because it's just one of millions). We can solve this by making the centrality derived from neighbours be divided by their out degree:
$$x_i = \alpha \sum_j \frac{A_{ij}}{k^{\text{out}}_j}x_j +\beta$$
which is the basis for PageRank
__[[Hubs and authorities (Network theory)]]__
One can distinguish two types of important nodes in directed networks. We describe them for the case of an information network, like WWW first:
*//authorities// are nodes that contain useful information on a topic of interest
*//hubs// are nodes that point us to the best authorities
This idea was implemented by Kleinberg into the //hyperlink-induced topic search// or //HITS// algorithm.
__[[Closeness centrality]]__
Closeness centraliy of node i is the mean geodesic distance to all others nodes in he network. A variant is //exponentially weighted closeness centrality//:
$$C_C (i) = \sum_{h \in G_i} 2^{-2L_{ij}}$$
where $$L_{ij}$$ is the geodesic distance between node $$i$$ and $$j$$; and $$G_i$$ is the connected network component reachable from $$i$$ (except for $$i$$).
Main disadvantage is its often very low dynamic range (range of values it takes)
There are also problems when there are disconnected components. One way is to define closeness centrality over only connected nodes, or to use harmonic mean (mean of reciprocals, ignoring self distance, as it's 0).
__[[Betweeness centrality]]__
Measures the extent to which a node (or edge, or other substructure) lies on paths between other vertices. These paths can be defined in many ways, but often they are taken to be geodesic paths.
__[[Groups of vertices|Groups of vertices (Network theory)]]__
Many networks naturally divide into groups. These are substructures that are prominent for some reason. Simple examples are ''cliques'', ''plexes'' and ''cores''. There are also generalizations of components called ''k-components''.
__Transitivity__
[[Transitivity|Transitivity (Graph theory)]] (a property of mathematical relations) in a network is usually applied to the relation "is connected by an edge". So a network is transitive if for every u connected to v and v connected to w, then u is connected to w. One can define the ''clustering coefficient'', $$C$$, as a measure of "how often" transitivity holds in the network:
$$C=\frac{\text{(number of triangles)}\times 3}{\text{number of connected triples}}$$
__Reciprocity__
For directed simplest graph the smallest loop size is two, instead of three, and thus one often measures the frequency of length-2 loops. This is called //reciprocity// (see [[Transitivity|Transitivity (Graph theory)]] for more comments). Pairs of reciprocated edges (that is edges from i to j where there is also one from j to i) are sometimes called //co-links//. The ''reciprocity'' is defined as the fraction of edges that are reciprocated, and this turns out to equal $$\frac{1}{m} \text{Tr}{\mathbf{A}^2}$$.
__Signed edges and structural balance__
''[[Signed network]]s'' have //signed edges//, that is their edges can have an associated weight $$+1$$ (like friendship) or $$=1$$ (like animosity).
''[[Structural balance]]'' refers to the situation when a [[Signed network]] contains only loops with even numbers of minus signs.
__[[Similarity|Similarity (Network theory)]]__
How can we measure the "similarity" of two nodes (or edges, etc.)? Two main approaches. Two nodes may be:
* ''structurally equivalent'': if they share many of the same network neighbours.
* ''regularly equivalent'': have neighbours who are themselves similar.
__Homophily or [[assortative mixing|Assortative mixing]]__
''Homophily'' or ''assortative mixing'' is a bias in favour of connections between network nodes with some similar characteristics.
https://en.wikipedia.org/wiki/Mechanical_engineering#Subdisciplines
[[Mechanics]]
[[Theory of machines]]
[[Mechatronics|https://en.wikipedia.org/wiki/Mechatronics]] and [[Robotics]]
[[Structural analysis]]
[[Thermodynamics]]
[[Hydraulic engineering|https://en.wikipedia.org/wiki/Hydraulic_engineering]]
[[Pneumatics|https://en.wikipedia.org/wiki/Pneumatics]]
[[Acoustics]]
In ''mechanics'', we __describe__ the motion of bodies, and the __causes__ that effect them. This includes the special case where the "motion" is //no motion//, i.e. bodies are stationary.
The description of the motion itself is called ''kinematics''. This just sets up the relevant degrees of freedom, represented as variables in a relevant mathematical form.
The description of the causes, and how these causes effect the motion is called ''dynamics''. These causes are often divided into forces and torques. This description relates the variables describing the motion above, to forces, which should depend on those variables themselves. This means that in dynamics we often have closed equations that we can solve in full generality.
[[Rotational dynamics]]
-------
Another division of the areas of classical mechanics, used mostly in __engineering__ leaves the definition of kinematics the same, but what we referred to as dynamics above is called ''kinetics''
Dynamics then refers to mechanics applied to proper motion only (i.e. not including stationary case). In other words, dynamics is the kinematics and kinetics of proper motion.
Mechanics applied to the stationary case is referred to as ''statics''. In other words, statics is the kinematics and kinetics of static equilibrium.
---------------
See the mechanical universe
[img[https://s-media-cache-ak0.pinimg.com/originals/34/d7/72/34d772d2c28e8a80259d47d9aaa62df9.gif]]
see video on mechanisms
https://en.wikipedia.org/wiki/Mechanistic_target_of_rapamycin
A [[Kinase]] that regulates cell growth, cell proliferation, cell motility, cell survival, protein synthesis, autophagy, transcription.
It's signalling circuit has been studied, for instance as an [[example of GP map bias|Examples of GP map bias]]: [[Evolvability and robustness in a complex signalling circuit.|http://www.ncbi.nlm.nih.gov/pubmed/21225054]]
Including [[Biomedical engineering|https://en.wikipedia.org/wiki/Biomedical_engineering]]
[[Medicine network image|https://goo.gl/photos/dL2SB5GuQSyxye7W7]]
[[Theory of Evanescent Mode Applicators (applied for cancer treatment)|https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwiB5-Wi07vKAhUDVxQKHdKkAyoQFggiMAA&url=https%3A%2F%2Fpiers.org%2Fpiersproceedings%2Fdownload.php%3Ffile%3DcGllcnMyMDA4Q2FtYnJpZGdlfDVBM18wNzY3LnBkZnwwODAxMTkxNDI2MDg%3D&usg=AFQjCNE0v4tU5xaTopXumHOU4EbmF8JkvA&sig2=guJTYL0skn93BCnF4nMHig]]
[[Big data has not revolutionised medicine – we need big theory alongside it|http://theconversation.com/big-data-has-not-revolutionised-medicine-we-need-big-theory-alongside-it-55356?utm_content=buffer4529f&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer]]
[[They became what they beheld|https://www.youtube.com/watch?v=bm-Jjvqu3U4]]
[img[http://forums.tapastic.com/uploads/default/3526/0dca4429e7305563.gif]]
A ''meet'', $$\wedge$$ is an [[operation|Operation (Mathematics)]] defined on elements of a [[poset|Partially ordered set]] $$P$$ (not necessarily all of them) defined as:
The join (or //[[Greatest lower bound]]//) of $$a, b \in P$$ is an element $$a \wedge b \in p$$ such that:
:(a) $$a \wedge b$$ is a //lower bound// of $$a$$ and $$b$$: thus $$a \wedge b$$ \preceq a and $$ a \vee b \preceq b$$;
:(b) $$a \wedge b$$ is the greatest such lower bound: i.e., if there exists $$c \in P$$ such that $$c \preceq a$$ and $$c \preceq b$$ then $$ c \preceq a \vee b$$.
Note that, if it exists, a join is necessarily unique.
See also [[Lattice (algebraic structure)]]
The type of [[Cell division]] that produces [[Gamete]]s for [[Reproduction]]
See [[video|https://www.youtube.com/watch?v=cbbnGiiu_SI]]
__Basic picture__
[img[https://s15.postimg.org/tkgb3m13f/Selection_604.png]]
__More complete picture__
Includes [[Chromosomal crossover]]
[img[https://media1.britannica.com/eb-media/88/78588-004-8A1C39DB.jpg]]
[ext[Membrane potentials - part 1 | Cells | MCAT | Khan Academy|https://www.youtube.com/watch?v=PtKAeihnbv0]]
''Equilibrium potential'' for K+ is -92mV
[[Membrane potential in neurons|https://www.youtube.com/watch?v=aU2pyB-49m8&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp#t=37m]]
Can be computed similarly to how the [[Nernst relation]] is derived.
See [[Spiking neural network]]
* ''Periodically firing neurons''. Fire, recover, fire, etc. at approximatey periodic time intervals Found in motor neurons in the spinal cord for instance.
* ''Randomly firing neurons''. Random fireing, due to strongly fluctuating potential with small postsynapitc potentials. Almost flat auto-correlation curve. Moslty found in the [[Cortex]].
''Postsynaptic potential''s. The membrane potential in the postsynaptic cell, when it receives an action potential from the presynaptic cell (I think). Two types:
* Excitatory postsynaptic potential (EPSP), depolarizing.
* Inhibitory postsynaptic potential (IPSP), polarizing.
Noise, is mostly synaptic noise.
|<mark>Do exercises of chapter 4</mark>|
Can use the [[Auto-correlation]] function measured from the membrane potential (when under threshold) to extract parameters of the postsynaptic potential, like the time constant (if it has an exponential form).
:After general statistical considerations (see more in book), we will describe the effects of EPSPs and IPSPs on the firing rates (see ''synaptic effects'' section). These are of course crucial in knowing how information is transmitted and processed in neuronal networks.
!!!__Statistics of firing rates for randomly firing neurons__
Use theory of [[First-passage time]]. See Lansky [1984]
__[[Refractory periods|http://www.physiologyweb.com/lecture_notes/neuronal_action_potential/neuronal_action_potential_refractory_periods.html]]__
* Absolute refractory period. The period from the initiation of the action potential to immediately after the peak. This is the time during which another stimulus given to the neuron (no matter how strong) will not lead to a second action potential. Thus, because Na+ channels are inactivated during this time, additional depolarizing stimuli do not lead to new action potentials. The absolute refractory period takes about 1-2 ms.
* Relative refractory period. After the absolute refractory period, Na+ channels begin to recover from inactivation and if strong enough stimuli are given to the neuron, it may respond again by generating action potentials. However, during this time, the stimuli given must be stronger than was originally needed when the neuron was at rest.
[img[http://www.physiologyweb.com/lecture_notes/neuronal_action_potential/figs/neuronal_action_potential_absolute_and_relative_refractory_periods_w.jpg]]
In pages 130-131, the following approximate equation is justified:
|$$\lambda (t) = \text{pr}\{v(t) > \theta\}/r$$|
where $$\text{pr}\{v(t) > \theta\}$$ is the probability that at time $$t$$ the membrane potential is above threshold, and $$r$$ is the absolute refractory period.
the action potential "resets" the membrane potential at the soma. But there are many more electrophysiological effects that makes the effect of the action potential more complicated.
Randomly spiking neurons correspond to neurons that do not show marked after-potentials and whose excitation is derived mainly from portions of the dendritic tree whose potentials are not reset by the action potential in the cell body.
!!!__Autocorrelation of spike trains__
What neurophysiologist call autocorrelation is acutally called an intensity function, or a renewal density, in statistics. This is the function that describes the rate of occurrence of an event as a function of the time elapsed since its previous occurrence. Actually, up to scaling, this is the same function as the autocorrelation (imagine one factor in the autocorrelation is fixed, then the other has the shape of the renewal density).
we can use the autocorrelation function of the spike train of a
neuron to assess whether it behaves like the periodically firing model or
like the randomly firing model. For large cortical areas in awake ani-
mals, the randomly firing model is adequate to describe the neuronal
activity.
!!!__''Synaptic effects''__
The above considerations consider the average behaviour of periodically and randomly firing neurons. For a more detailed understanding, however, it is important to know what are the effects fof postsynaptic potentials on the firing rates.
__for periodically firing neurons__
Periodically firing neurons, have a relatively long recovery period after each spike, and a large excitatory baseline, which means that after these periods they will fire again. However, EPSPs can make them fire a bit sooner (IPSPs can make them fire a bit later). The statistics of this change can be understood from the EPSP curve
According to Knox [1974] and Knox and Popple [1977], the firing rate of the motoneuron is related to the derivative of the postsynaptic potential. Kirkwood [1979], working experimentally on motoneurons, found that the derivative rule was too extreme. He suggested that a sum of the EPSP itself and its derivative would give a reasonable approximation. The following argument explains the reasonings behind these considerations.
[img[synaptic_effect_periodically_firing_neuron.png]]
What the slanted lines show is the decreasing threshold, for several possible times for the previous spike. The time origin is at the presynaptic firing event. The ''postsynaptic potential'' (PSP) curve is shown. When the PSP intercetps the threshold for some of the lines, the neuron will fire again. This gives an intuition to why the firing rate appears to be related to the derivative of the PSP. Left-hand side shows excitatory (EPSP); right-hand side shows inhibitory (IPSP).
__for randomly firing neurons__
Apart from the random spikes by the fluctuating membrane potential crossing the membrane, an EPSP (IPSP) can increase (decrease) the chance of firing.
//small synaptic potentials//. The argument in pages 140-143 indicates that for a postsynaptic neuron that
does not fire periodically and exhibits a low spontaneous firing rate (thershold is
at the tail of the p.d.f.), and when the EPSP is small, the cross-
correlation function will fall off faster than the membrane potential.
For the same reasons, cortical neurons must be very sensitive to syn-
chronous activation of several EPSPs.
,,A word of caution is due: Estimates of average membrane potential
and variance are always based on a finite sampling time. An evaluation
of how true to life these estimates are must be based on what is called in
statistics the number of degrees of freedom. To be on the safe side, we must compute the autocorrela-
tion function [equation (4.2.7)] and determine the delay until the correla-
tion drops to zero. Those samples that are as far apart as this delay are
uncorrelated, and therefore can be assumed to be independent.,,
//large synaptic potentials//. When we had only a small EPSP, the probability of getting two or more
spikes during a given EPSP was very small, and we therefore ignored
these cases. However, that is not so for a very large EPSP. Therefore, the effect of previous spikes has to be taken into account. This can be done by considering the threshold $$\theta$$ to depend on time, and be increased for some time after a spike. This leads to two simultaneous equations. One for $$E[\theta(t)]$$ which depends on $$\lambda(t')$$ for $$t' < t$$, and one for $$\lambda(t)$$ which depends on $$E[\theta(t)]$$. See page 146 for the eqs. These can easily be solved iteratively.
A membrane protein, or membrane-bound protein, is a protein bound to the [[Cell membrane]]
* [[Channel protein]]
Very hard to [[crystallize|Protein crystallization]], because they are [[Amphiphilic]]
[[Mind]] [[Gene]]
tropes, archetypes
http://www.dictionaryofobscuresorrows.com/
http://tvtropes.org/
Memory is how information is encoded, stored, and retrieved. ([[wiki|https://www.wikiwand.com/en/Memory]]). It is a foundamental feature of [[Computer]]s, and of [[intelligent|Intelligence]] beings.
!!__Types of memory__
* [[Content-addressable memory]]
https://github.com/FlyingSpringrol/Human-memory
!!__Working memory__
While the mechanisms of working memory remain some-
what obscure at the level of neurophysiology, the verbal definition is understood to mean
a capacity for short-term storage of information and its rule-based manipulation (Badde-
ley et al., 2009). In computational terms, these rules are simple programs, and the stored
information constitutes the arguments of these programs.
working memory process has been ascribed to the functioning of a
system composed of the prefrontal cortex and basal ganglia (Goldman-Rakic, 1995)
!!__Long-term memory__
__prioritized long-term memory__
After working memory fades, but not yet in long-term memory -- [[article|http://www.sciencemag.org/news/2016/12/newly-discovered-state-memory-could-help-explain-learning-and-brain-disorders?utm_source=sciencemagazine&utm_medium=facebook-text&utm_campaign=memorder-9541]]
!!__Memory and learning__
Memory and learning are very much related. [[Hebbian theory]] is also a basis for understanding memory.
!!!__Long-term potentiation and long-term depression__
__Importance of timing__
[[vid|https://www.youtube.com/watch?v=hLs3m6nIJ1E&index=26&list=PL4C48902B3A4ED0F4#t=6m40s]]
-------------------
[[Kandel's principles]]
http://ezproxy-prd.bodleian.ox.ac.uk:2153/view/10.1093/acprof:oso/9780199232703.001.0001/acprof-9780199232703
//a.k.a. memory management//
The [[Operating system]] allocates memory to ''processes'', so that a process can only access that portion of memory.
This memory is divided into:
* [[Call stack]], or just the stack
* [[Memory heap]], where dynamically allocated variables are stored.
* text section.
The addresses that the program uses to reference variables are actually [[Virtual memory]] addresses, which the operating system translates to physical memory.
https://en.wikipedia.org/wiki/Memory_management
------------------
[[What and where are the stack and heap?|http://stackoverflow.com/questions/79923/what-and-where-are-the-stack-and-heap]]
http://stackoverflow.com/questions/18446171/how-do-compilers-assign-memory-addresses-to-variables
See [[Memory allocation]], [[Heap (data structure)]]
Advantage vs [[Call stack]]: More memory than in stack, and it's also not freed when the function that created the variable returns
[[What is a Memory Heap?|http://stackoverflow.com/questions/2308751/what-is-a-memory-heap]]
//a.k.a. memory allocation//
The [[Operating system]] allocates memory to ''processes'', so that a process can only access that portion of memory.
This memory is divided into:
* [[Call stack]], or just the stack
* [[Memory heap]], where dynamically allocated variables are stored.
* text section.
The addresses that the program uses to reference variables are actually [[Virtual memory]] addresses, which the operating system translates to physical memory.
https://en.wikipedia.org/wiki/Memory_management
[[Malloc|http://stackoverflow.com/questions/1963780/when-should-i-use-malloc-in-c-and-when-dont-i]] (a function available in [[C/C++]] is used to put variables in the heap instead of the read only "text section".
!!!__Garbage collection__
[ext[https://www.wikiwand.com/en/Garbage_collection_(computer_science)]]
------------------
[[What and where are the stack and heap?|http://stackoverflow.com/questions/79923/what-and-where-are-the-stack-and-heap]]
http://stackoverflow.com/questions/18446171/how-do-compilers-assign-memory-addresses-to-variables
This tiddler is about this ~TiddlyWiki itself.
[[BACKUPS|http://kosmos.tiddlyspot.com/backup/]]
[[Upgrade TW|http://tiddlywiki.com/upgrade.html]]
[[Creator, he lives in Oxford!|https://twitter.com/Jermolene]]
https://github.com/Jermolene/TiddlyWiki5/issues/2180
[[plugin or feature request: inner-tiddler-anchors|https://github.com/Jermolene/TiddlyWiki5/issues/1783]]
[[Manual links (for inter-tiddler links)!|http://scroller.tiddlyspot.com/#Linking%20in%20WikiText:%5B%5BLinking%20in%20WikiText%5D%5D%20ButtonWidget]] <mark>Check how to implement this, maybe I need to [[Upgrade TW|http://tiddlywiki.com/upgrade.html]]? </mark>
[[Creating SubStories|http://tiddlywiki.com/#Creating%20SubStories]]
[[Creating A Tabbed ToC|http://tobibeer.github.io/tb5/#Creating%20A%20Tabbed%20ToC]]
[[TiddlyWeb|http://tiddlyweb.com/]]
[[ServerCommand|http://tiddlywiki.com/static/ServerCommand.html]] hmm?
[ext[Nice collection of plugins|http://tobibeer.github.io/tb5/#]]
<mark>[[WOW TiddlyMap|http://tiddlymap.org/]]</mark>
[[TiddlyClip|http://tiddlyclip.tiddlyspot.com/]]
[[Nice too! Codemirror editor|http://tiddlywiki.com/plugins/tiddlywiki/codemirror/]] <mark>Install this</mark>
!! [[Custom stylesheet]].
In here I have an example of a <big style="color:Aqua">workaround to get javascript working on there</big>. Even though script tags are supposed to be removed, they aren't when inside an `iframe`. However, I need then to substitute document $$\rightarrow$$ window.parent.document to access stuff in our document. Maybe I can define a Javascript Macro like the one below that takes javascript code as input, and does the right things and adds the iframe dressing, etc.!
Also should think of adding jquery, via a custom plugin..
Trick to embed stuff from other pages using iframes (and position the embedded content correctly). See example [[Apollonian gasket]]
Font Awesome: [[$:/plugins/TheDiveO/FontAwesome/fonts/FontAwesome]] [[TW on Font Awesome for TW|http://thediveo.github.io/TW5FontAwesome/output/fontawesome.html]]
!! Example of custom [[Macro|http://tiddlywiki.com/static/Macros%2520in%2520WikiText.html]]
[[$:/core/modules/macros/testMacro]]
This is an example of a (global) Javascript macro, as one can define local ones.
To use it, do `<<testMacro>>` in any tiddler, where this isn't the name of the tiddler, but the name defined inside it in `exports.name = "testMacro";`. It then runs the `exports.run` function.
!!TODO
* Change hosting of linked google photos pictures to something else that is public
* http://blog.jeffreykishner.com/2014/01/23/how-to-incorporate-font-awesome-icons-into-tiddlywiki-5.html
*Create plugin/custom button to add child to tiddler (child defined via tags). I know this is a hierarchical idea, but still useful!
*Also show backlinked stuff.
*Make Table of contents Tiddler
* Add automatic link to wiki page in tiddlers.
* __Scalability?__ There is a server side tiddlywiki apparently. At the moment in 15 days it increased by 1M. Therefore in a month, 2M. Therefore in a year 24M. I think the biggest thing I added was the pdf: [[The Hallmarks of Aging.pdf]]...which increased it by about 5M straight away. Big files, and pictures should be hosted somewhere else and linked.. There are TW with 1000s of tiddlers apparently that go well.
* References. How to add ~LaTeX-like referencing..
* See ~CosmosBrain created in The Brain
* Define `root path` for offline `file://` links!
* Find way of saving current color scheme, and try other ones. Like black on white (better for reading).
* Subdivide tiddlers more.
* Learn more about tiddlywiki and how to hack/modify it.
* TW is kinda a OS on the web, can we give it more features like better window (open tiddler) management, etc. Tiddlers are like files. Shadow tiddlers, macros, etc. are programs.
* Add AI stuff like http://home.ideapad.io and concept map stuff! :) See also http://ideaflowplan.tk/
~LaTeX test: $$x^2=3$$
Font Awesome Test: Waving flag: <i class="fa fa-flag"></i>
Tricks that life uses to carry out specific [[Metabolic pathway]]s
* Speed up reactions ([[Chemical kinetics]]): use catalyzers: [[Enzyme]]
* Make reactions happens. Sometimes, a reaction's [[energetics|Chemical energetics]] is unfavorable ($$\Delta G > 0$$). However, if the reaction is coupled with a very favourable reaction, the overall reaction can also be made favorable (happen spontaneously).
** ''Direct coupling''. Couple two reactions so that they occur simultaneously, by making the enzyme that makes one happen, also make the other happen. See [[here|https://www.youtube.com/watch?v=C5lRsZrx_R0#t=2m]] This is another way of saying that the favourable reaction //runs// the the other reaction. The fuel of the very favorable reaction is often [[ATP]].
** ''Indirect coupling''. See [[video|https://www.youtube.com/watch?v=C5lRsZrx_R0#t=5m22s]], we deplete the products of a reaction, and so keep the reaction from reaching equilibrium, and force it to keep running forward.
!!__Energy sources__
* [[ATP]] --> [[Phosphorylation]] --> [[ADP]]
* [[GTP]] --> GTP binding. [[Hydrolysis]] gives [[GDP]]
A [[Network]] of inter-regulated [[Metabolic pathway]]s.
It is based on ''regulation''
!!__[[Regulation of pathways|Pathway regulation]]__
* [[Allosteric regulation]].
* Kinases, add phosphate to proteins to activate them.
!!__Metabolic networks__
* [[Cellular respiration]]
* [[Fermentation]]
* etc, etc.
System of [[Chemical reaction]]s that carry out some [[Metabolism]] function. Metabolic pathways are often part of a [[Metabolic network]]
!!!__[[Metabolic mechanisms]]__
!!__Metabolic pathways__
* [[Glycolysis]]
Metabolic pathways can be driven by complexes of [[Enzyme]]s linked together, as in the outside a [[mitochondrion|Mitochondria]]
Metabolism (from Greek: μεταβολή metabolē, "change") is the set of life-sustaining chemical transformations within the cells of living organisms.
[[Metabolic pathway]] --> [[Metabolic network]]
[[Metabolic mechanisms]]
!!__Types of pathway__
* Catabolic. Degrade molecules and release energy
* Anabolic. Construct molecules and consume energy
!!__[[Energetics|Chemical energetics]] in metabolism__
-----------------
https://www.wikiwand.com/en/Metabolism
A [[material|Materials science]] made of atoms bonded by metallic bonds (see [[Chemical bonds]])
A metallic element is one that forms a metal when in its pure solid state.
Pure metallic crystalline solids are found almost always in either BCC, FCC, and sometimes (HCP) crystal arrangements. Furthermore, BCC, and FCC appear only in metals, at least, when looking at pure element crystals (see [ext[Periodic table (crystal structure)|https://en.wikipedia.org/wiki/Periodic_table_(crystal_structure)]])
!!__Metal groups__
* [[Alkali metal]]s
* [[Alkaline earth metal]]s
!!__Reactions__
!!!__with water__
As a general rule, if a metal reacts with cold water, you get the metal hydroxide. If it reacts with steam, the metal oxide is formed. This is because the metal hydroxides thermally decompose (split up on heating) to give the oxide and water.
!!!__with [[Acid]]__
Metals react with acids at different rates, depending on how reactive the metals are. Hydrogen can be produced from acids when they react with metals. [[page|http://www.bbc.co.uk/education/guides/z8ktyrd/revision]]
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/2
* [[Aluminium extraction]]
* [[Iron extraction]]
[[Mathematics]] applied to understand [[Mathematics]]
[[Godel incompleteness theorems]]
Study of the nature of Nature.
See [[Philosophy]] for the basis of my metaphysics.
Basically my ontology is based on two levels, depending on certainty (,,not sure if these are the best names,,):
# ''Observer perspective''. The most certain parts of Knowledge are those pertaining to what you experience.
# ''God-like perspective''. The next level in certainty is about things we infer from what we experience. This is where most of Knowledge resides. This deduction uses tools like [[Epistemology]], [[Logic]], [[Science]], etc. to infer our Knowledge of [[Reality]], or Physical World.
The physical world is based purely on primary substances (concrete things of the [[physical world|Physics]]. Other things are just emergent properties of it, including us and our thoughts. Those thoughts is where abstract [[Concept]]s, [[Knowledge]]
I think a good way to approach metaphysics is via [[Systems theory]], and [[Science]]
[[Introduction to Metaphysics|https://www.youtube.com/watch?v=qKq0Afmsj-U]]
!!__Topics in metaphysics__
!!!__Aristotle's metaphysics__
* First causes. See [[Theology]]
* Being.
!!!__Continental rationalists and metaphysics__
Decartes, Leibniz, Spinoza
* General metaphysics, or [[Ontology]], the study of being or existence.
* Special metaphysics
** Cosmology
** Rational psychology
** Natural theology
--------------------
https://en.wikipedia.org/wiki/Metaphysics
A very rough way to distinguish ground states from metastable states (in the context of [[Spin glass]]es, as an example) is as follows:
escaping a metastable state requires overturning a fixed number of spins, independent of the system size.
On the other hand, escaping a ground state requires overturning a number of spins that grows with the system size.
Metastable states are surrounded by relatively low “energy barriers,” of $$O(1)$$ energy, while ground states, or true global minima, are surrounded by energy barriers that grow with the size of the system.
[img[Selection_618.png]]
This phenomenon (and its consequences) was dubbed “broken ergodicity” by Palmer [[[Broken ergodicity in spin glasses|http://link.springer.com/chapter/10.1007/3-540-12872-7_51#page-1]]]
A powerful [[JavaScript]] framework for both [[Frontend web development]] and [[Backend web development]]
Assume functions in the asymptotic expansion depend on $$t$$ through variables, corresponding to different time scales: $$T_0 = t$$, $$T_1=\epsilon t$$, $$T_2 = \epsilon^2 t$$, etc.
$$I(x) = \int_a^b f(t) e^{ix\psi(t)} dt$$ as $$x\rightarrow \infty$$
with $$\psi(t)$$ real.
Uses Riemann-Lebesgue lemma:
__''Riemann-Lebesgue lemma''__
... Useful also when doing integration by parts for [[Asymptotic approximation of integrals]]
See statement on notes
__Method of stationary phase__
Split integral into region close to stationary phase point(s) and the rest. Then it's similar to [[Laplace method]]
See example in notes..
__Important notes__
* The error terms are only algebraically small, not exponentially small as in [[Laplace method]].
* Higher-order corrections are very hard to get since they may come from the whole range of integration.This is in contrast to [[Laplace method]] where the full asymptotic expansion depends only on the local region because the errors are exponentially small.
$$I(x) = \int_a^b f(t) e^{x\phi(t)} dt$$ as $$x\rightarrow \infty$$
For $$\phi(t)$$, $$f(t)$$ are generally complex, and the integral being along a complex contour in general.
See justification in notes..
Also: [[Handouts from lecture|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3128/9/OHPHandoutLecture7.pdf]]
''Steepest descent contour'' refers to the contour of steepest descent of $$u$$, the real part of $$\phi(t) = u(t) +iv(t)$$. That is, the contour parallel to its gradient, $$\nabla u(t) $$. This is because, for $$\phi(t)$$ an analytic function, $$\nabla u(t) $$ is perpendicular to $$\nabla v(t) $$, so that the steepest descent contour is also a __contour of constant imaginary part of $$\phi(t)$$__. This later condition (together with others, depending on the problem) is often used to find the contour.
The other conditions may be:
* __If the contour goes from one valley__ (valley in the $$u$$ landscape, which can only have saddle points, due to [[Cauchy–Riemann equations]]) __to another valley__, then the steepest descent contour __must pass through a ''saddle point''__ (in $$u$$ landscape). This is because in one valley $$du/ds<0$$ ($$s$$ being distance along path), and in the other $$du/ds>0$$. Therefore, at some point, $$du/ds=0$$. However, in a steepest descent contour $$dv/ds=0$$ everywhere. Therefore, at that point $$du/ds=0$$ and $$dv/ds=0$$, which implies that $$\nabla u(t) $$, so it is a saddle point. In this situation, the Laplace integral will get contribution from the saddle points (where $$u$$ is largest).
* If the contour starts at a certain point, not infinity, then that point has to be kept, and the Laplace integral may get a contribution from it.
!!__Method of steepest descents__
:''1.'' Deform the contour to be the steepest descent contour through the relevant saddle node(s).
:''2.'' Evaluate the local contribution from the saddle, exactly as in [[Laplace method]].
:''3.'' Evaluate the local contribution from the end points, exactly as in [[Laplace method]].
<i class="fa fa-exclamation-triangle" aria-hidden="true"></i> Remember that when deforming the contour we must include the contribution from any poles that we cross.
__Example: Steepest descents on the gamma function__
__Example: Steepest descents on the Airy function__
Both of these are moveable saddle problems, so we first need to rescale variables, so that the saddle is fixed.
<mark>Revise ''Watson lemma'', and examples</mark>
A ''metric'' on a [[Set]] $$X$$ is a [[map|Function]] $$d: X \times X \rightarrow \mathbb{R}$$ (i.e. from the [[Cartesian square|Cartesian power]] of $$X$$ to the [[Real number]]s), that satisfies the conditions:
* ''symmetry'': $$d(x,y) = d(y,x)$$
* ''positivity'': $$d(x,y) \geq 0$$, and $$=0$$ if, and only if, $$x=y$$.
* [[Triangle inequality]]: $$d(x,y) \leq d(x,z) + d(z,y)$$.
A [[Set]] with a [[Metric]] function.
It can be used to define notions of [[Convergence]], and [[Open set]]s.
Because a metric space has a natural notion of open set, it also has a natural [[topology|Topological space]]
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A.k.a. ''microfluidics''. See [[Complex fluid dynamics]]. For fluid at even smaller scales (nanoscales), one talks about //nanofluidics//.
[[Microfluidics: Fluid physics at the nanoliter scale|http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.77.977]]
[[Nanofluidics, from bulk to interfaces|http://pubs.rsc.org/en/content/articlelanding/2010/cs/b909366b#!divAbstract]]
[[Encyclopedia of Microfluidics and Nanofluidics|http://link.springer.com/referencework/10.1007/978-3-642-27758-0]]
https://scholar.google.com/scholar?cites=17428969843030616661&as_sdt=2005&sciodt=0,5&hl=en
[[MAE6240 Fall 2012 |https://www.youtube.com/playlist?list=PLADE976650940CCCF&spfreload=5]]
!!__[[Interfacial forces]]__
See [[Phoretic mechanisms of colloids]]. [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]
__[[Osmotic|Osmosis]] effects__
Diffusioosmosis, thermoosmosis, etc.
Small sections of [[RNA]] that binds to other RNA.
Double-stranding the RNA silences the mRNA, or makes it be cut up
See [[Nanoengineering]] (a.k.a. nanosystems engineering)
[[Microsystems engineering]]
[[Microsystems & Nanoengineering|http://www.nature.com/micronano/]]
''Microtubules'' (micro- + tube + -ule) are a component of the cytoskeleton, found throughout the cytoplasm.
These tubular polymers of tubulin can grow as long as 50 micrometres and are highly dynamic. The outer diameter of a microtubule is about 24 nm while the inner diameter is about 12 nm. They are found in eukaryotic cells, as well as some bacteria, and are formed by the polymerization of a dimer of two globular proteins, alpha and beta tubulin.
(https://en.wikipedia.org/wiki/Microtubule)
Some times of [[Molecular motors]] walk along microtubules to transport molecular cargo inside a [[cell|Cell (Biology)]].
They are the primary component of the [[Spindle|Spindle (Cell biology)]] which separates chromosomes during cellular division.
__Microtubule turnover__: the process by which microtubules decay, and are replaced. "Turnover" can also refer to the //rate// of this process. See [[turn over (definition)|http://www.thefreedictionary.com/turn+over]]: To be replaced by something else of the same kind. See [[here|https://books.google.co.uk/books?id=BEabBwAAQBAJ&pg=RA1-PA640&lpg=RA1-PA640&dq=microtubule+turnover&source=bl&ots=7KjSVvpjpm&sig=yDCN07eODRCTTsXRoHgYZyiVVPc&hl=en&sa=X&ved=0ahUKEwiCj6jaydDMAhWDKsAKHWd6B-04ChDoAQgiMAI#v=onepage&q=microtubule%20turnover&f=false]].
Also [[microtubules page|http://www.ncbi.nlm.nih.gov/books/NBK9932/]].
!!__Microtubule dynamics__
[[David Odde - Microtubule Self-Assembly|https://www.youtube.com/watch?v=OoRQWEeXcQc]]
[img[http://www.pnas.org/content/110/51/20449/F3.large.jpg]]
The Milky Way is the [[Galaxy]] that contains our [[Solar System]]
A [[complex system|Complex systems]] that has features associated with sentient, intelligent and conscious beings. It is capable of thought and emotion (see [[Philosophy]], [[Cognitive science]], [[Philosophy of mind]]).
It currently only physically realized in the [[Brain]], but [[Computer]]-based versions are very likely possible, and are part of the [[transhumanist|Transhumanism]] vision.
A mineral is a naturally occurring chemical compound,[1] usually of crystalline form and abiogenic in origin ([[wiki|https://www.wikiwand.com/en/Mineral]])
http://www.minerals.net/
http://www.mindat.org/
[[Encyclopedia of minerals pdf|http://fac.ksu.edu.sa/sites/default/files/ebooksclub.org__Minerals__Description_of_Over_600_Minerals_from_Around_the_World_0.pdf]]
[img[http://image.shutterstock.com/z/stock-photo-collection-set-of-semi-precious-gemstones-stones-and-minerals-with-names-isolated-on-white-183284576.jpg]]
Inspiration from neuroscience -> neural networks.
Convolutional network. Matthew Zeiler & Rob Fergus
Supervised vs unsupervised.
A good principle for learning is for the machine trying to reconstruct the things it wants to learn using its neural net. If what it reconstructs doesn't agree with what it then sees, it should learn. This sounds like learning by imitation.
Regularity helps..
Multimodal, learning combining different kinds of data
Sequence learning and recurrent nets: have memory, can predict sequences (in time say). Can [[parse|https://en.wikipedia.org/wiki/Parsing]] words, and they show that grammar can be learned.
Being able to fill gaps in the information you receive (like our brain does, or like machines do with generative models, which also learn) is useful for decision making, as you can know what to expect, even with incomplete info.
Siamese neuronal network [[Q|http://stats.stackexchange.com/questions/154652/how-does-the-back-propagation-work-in-a-siamese-neural-network]]
Reinforcement learning
Imitation learning
Back-propagation.
See [[video|https://www.youtube.com/watch?v=uLsVEYdn_e4]]
[[Spindle self-organization]]
__Stages__
[img[https://media.giphy.com/media/l3V0FrQ0sfJdjDCq4/giphy.gif]]
[img[https://media1.britannica.com/eb-media/87/78587-004-0A22AB7F.jpg]]
!!Prophase
[[Chromosome]]s condensing
!!Prometaphase
Nuclear membreane breakdown.
Spindles attach to kinetochores at the [[Chromatid]]s
!!Metaphase
Alignment of sister
* Astral mictrotubules
* Kinetochore microtubules
* Interpolar microtubules
!!Anaphase
Synchronous separation of chromatids
!!Telophase
Reforming nuclear membranes among the two sets of chromatids.
!!Cytokinesis
The [[Cytoplasm]] divides in two by contractile ring.
A mixture is a material system made up of two or more different [[substances|Chemical substance]] which are mixed but are not combined chemically.
https://www.wikiwand.com/en/Mixture
http://www.bbc.co.uk/education/guides/zgbqtfr/revision/4
https://www.wikiwand.com/en/Mixture_model
[[Gaussian mixture model]]
[[Naive Bayes mixture model]]
Outcome: ''Distinction'' (First class honours).
//Exam marks//
<table class="sitstablegrid" width="100%">
<tbody><tr>
<th class="sitsrowhead" width="10%"><strong>Year</strong></th>
<th class="sitsrowhead" width="10%"><strong>Assessment Code</strong></th>
<th class="sitsrowhead" width="50%"><strong>Assessment</strong></th>
<th class="sitsrowhead" width="10%"><strong>Assessment Type</strong></th>
<th class="sitsrowhead" width="10%"><strong>Mark</strong></th>
<th class="sitsrowhead" width="10%"><strong>Grade</strong></th>
</tr>
<tr><td width="10%">2015/16</td><td width="10%">A12169</td><td width="50%">Nonlinear Systems (Combined)</td><td width="10%">Overall Mark</td><td width="10%"> 77</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A12206</td><td width="50%">Perturbation Methods</td><td width="10%">Written</td><td width="10%"> 77</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A13117</td><td width="50%">Networks</td><td width="10%">Submission</td><td width="10%"> 73</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15088</td><td width="50%">Quantum Field Theory</td><td width="10%">Written</td><td width="10%"> 100</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15089</td><td width="50%">Kinetic Theory</td><td width="10%">Written</td><td width="10%"> 75</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15091</td><td width="50%">Scientific Computing I</td><td width="10%">Submission</td><td width="10%"> 70</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15275</td><td width="50%">Soft Matter Physics</td><td width="10%">Practical</td><td width="10%">-</td><td width="10%">Pass</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15280</td><td width="50%">Scientific Computing II</td><td width="10%">Submission</td><td width="10%"> 100</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15282</td><td width="50%">Nonequilibrium Statistical Physics</td><td width="10%">Written</td><td width="10%"> 80</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15416</td><td width="50%">Topics in Soft and Active Matter Physics</td><td width="10%">Practical</td><td width="10%">-</td><td width="10%">Pass</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15417</td><td width="50%">Complex Systems</td><td width="10%">Submission</td><td width="10%"> 76</td><td width="10%">-</td></tr><tr><td width="10%">2015/16</td><td width="10%">A15430</td><td width="50%">Oral Presentation</td><td width="10%">Oral</td><td width="10%">-</td><td width="10%">Pass</td></tr>
</tbody></table>
---------------------
BACKUP LECTURE NOTES
[[Website|http://mmathphys.physics.ox.ac.uk/]]
,,[[old unofficial website|http://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/MMathPhys/]],,
[[Courses to take and course requirements|https://files.acrobat.com/a/preview/c35ab46c-26e7-4441-a1da-86cb70c6d0e1]]
!!! Hilary Term
[[Combined timetable|http://mmathphys.physics.ox.ac.uk/sites/default/files/HT16_MTP.pdf]] No soft matter on Tuesday. Instead Friday at 12am
[[Lecture courses|http://mmathphys.physics.ox.ac.uk/ht2016courses]]
[[Examination conventions|http://mmathphys.physics.ox.ac.uk/sites/default/files/ExamCon2015-16_7.pdf]]
''[[Handbook|http://mmathphys.physics.ox.ac.uk/sites/default/files/MMathPhys_Handbook_2015-16_9.pdf]]''
''[[Gingkoapp tree|https://gingkoapp.com/app#5bca195b41d7c40dc2000011]]''
[[Mathematical institute classes|https://minerva.maths.ox.ac.uk/perl/classlists.pl]]
* ''Nonlinear systems'': Class Tutor: Prof Irene Moroz Teaching Assistant: Mr Graham Benham. __Thursdays wks 4,6,8 C4 2-3:30pm__. Hand in written work by: Mondays 5pm in MI basement
* ''Networks'': Class Tutor: Mr Sewook Oh Teaching Assistant: Mr Marco Pangallo. Wednesdays, weeks 2–7, 14:00–15:00. Hand in written work by: Tuesday, 5pm. Now: attend on __Fridays 10am__
!!! Trinity term
[[Timetable|http://mmathphys.physics.ox.ac.uk/sites/default/files/MTP_TT16_20416.xlsx.pdf]]
---------
The ''[[Oral Presentations|MMathPhys oral presentation]] will take place in week 5'' of Trinity term not week 4.
The Trinity term mini-projects will be released at 12noon on Monday of week 6 and are to be submitted by 12noon on Monday of week 9 (rather than weeks 5 and 8 respectively).
The Trinity term take-home-exams are to be released at 12noon on Monday of week 9 of Trinity term and are to be submitted by 12noon on Wednesday of week 9 (rather than in week 5).
--------
!!!__[[Exams timetable|https://www.ox.ac.uk/sites/files/oxford/field/field_document/DMTP1516.pdf]]__
* ''1st of June'' 14:30 - ''Nonequilibrium statistical physics'' (1.5h)
* ''6th of June'' 14:30 - ''Nonlinear systems'' (1.5h)
* ''9th of June'' 09:30 - ''Perturbation methods'' (1.5h)
!__Networks__
!! On [[Spatial networks]]
In particular I looked at networks formed by the Physarum polycephalum, when connecting food sources. I used a mathematical model of these networks and looked at their features. They turn out to perform rather well under metrics of efficiency and robustness. They also display typical features of [[Spatial networks]], in particular [[Planar network]]s.
See [[Physarum machines and physarum solver]], and project in Overleaf. See code in Dropbox.
-----------
-------------
!__Complex systems__
!!On [[Percolation]]
In particular, on the [[Relations between the stability of Boolean networks and percolation]]
--------
----------
!__Nonlinear systems__
On the ''Duffing oscillator''
The effects of small damping, nonlinearity and forcing on a harmonic oscillator:
$$\ddot{x} + \beta \dot{x} + x + \delta x^3 = \Gamma \cos{\omega t}$$
* The simple harmonic oscillator (forced and damped, in general)
* [[Duffing oscillator]]
** Free (unforced) Duffing oscillator
*** Free undamped Duffing oscillator
*** Free damped Duffing oscillator
** Forced damped Duffing oscillator.
There are potentially $$8$$ qualitatively different forms of the equation, depending of which combination of the $$3$$ parameters considered are non-zero.
The Duffing Equation: Nonlinear Oscillators and their Behaviour
[[References on the Duffing oscillator]]
<small>The presentation should not be longer than 20-25 minutes and there will be a 5-10 minute discussion session
after the presentation. You are free to choose whether you want to give a blackboard presentation or use
slides.</small> [[Timetable|file:///home/guillefix/Dropbox/Oxford/MMathPhys/oral%20presentation/Oral%20Presentation%20Timetable%20for%20Students.pdf]] My presentation is on Friday 27th May in L5, at 12:30. <mark>Practice it</mark>
!!!See slides at [[slides|http://slides.com/guillermovalle/arrival]] for a nice and ordered presentation of the ideas.
!__[[Evolution]]__
[[Modern evolutionary synthesis|https://en.wikipedia.org/wiki/Modern_evolutionary_synthesis]]
[[Contingency, convergence and hyper-astronomical numbers in biological evolution|http://www.sciencedirect.com/science/article/pii/S1369848615001879]] [[Notes on Ard Louis' paper on contingency, convergence and hyper-astronomical numbers in biological evolution]]
[[A.A. Louis: Publications|http://www-thphys.physics.ox.ac.uk/people/ArdLouis/publications.shtml]]
<small>
[[Hunting Darwin's Snark: which maps shall we use?|http://rsfs.royalsocietypublishing.org/content/5/6/20150078.full]]
</small>
!<big>[[Bias in GP maps]]</big>
{{Bias in GP maps}}
---------------
!!__''[[Genotype-phenotype map]]''__ (GP map)
[img width=400 [http://1.bp.blogspot.com/-T7ODIpnghZ4/UGY43-q09OI/AAAAAAAABgA/5I_P0s_I8A4/s1600/Stadler2002_fig1.png]]
--------------------------
See [[Descriptional complexity]]
Evolutionary Robotics and computing, uses GPMs. See [[Evolutionary computing]] and [[Optimization]] .. See [[References from Complex Behavior in Evolutionary Robotics book]]
------
!!__[[Survival of the flattest]]__
An effect, where //effectively// large neutral spaces are also favoured, but <b>in equilibrium</b>, not out of equilibrium as in the [[Arrival of the frequent]]
-------
__More__
[[Convergent evolution as natural experiment: the tape of life reconsidered|http://rsfs.royalsocietypublishing.org/content/5/6/20150040.full]]
!!!Applications to [[Deep learning]] and [[ANNs|Artificial neural network]]? [[Chico's application to networks|http://www.youtube.com/watch?v=vLYpjUANUdc&feature=youtu.be]]. [[His slides|https://docs.google.com/presentation/d/1l-IgqXy1ZdBn__aBQX0fUH8Z2y6iuogwt753omsiyAw/edit#slide=id.ga17a5664f_0_49]]
!!!Relation b/w bias for simplicity in GP maps, and regularization in [[Machine learning]]. <i class="fa fa-exclamation" aria-hidden="true"></i>
Genotype is the weights of the NN, phenotype is the function the NN approximates. NNs are expected to find "simple" functions much easier then I suppose. In other words, they are able to recognize patterns much more easily if there is actually a pattern (in the sense of a simple pattern..)
--------
-------
__[[Sloppy systems]]__
A ''mode of inheritance'' refers to a particular way a [[Phenotype]] may be inherited.
[[Sex-linked|Sex linkage]]: the gene is in a sex chromosome (X or Y)
[[Autosomal|Autosomal inheritance]]: the gene is in a non-sex chromosome (an //autosome//).
Dominant, recessive, etc: [[Genetic dominance]]
[[Pedigree analysis|https://www.youtube.com/watch?v=VQmZXw8UBh4]]
A [[System]], often a [[mathematical|Mathematics]] or [[computational|Computer science]] one, that [[simulates|Simulation]] another system, i.e. it represents features of the original system, both structural, and behavioural.
* [[Fruit fly]]
* [[Yeast]]. Have been used to study [[Cell cycle]]s
* [[C. Elegans]]
* [[Zebrafish]]
* [[Mouse]], [[Rat]]
* [[Human]]s
* [[Xenopus laevis]] (a frog)
* [[Chicken]]
[[Synthetic biology]], to create new model organisms
[[Introduction|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=36m40s]], see overfitting and underfitting below. Model selection algorithms provide methods to automatically choose optimal bias/variance tradeoffs. [[Explanation|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=40m10s]]
!!__[[Cross-validation]]__
!!__[[Feature selection]]__
----------
__Model selection for [[Artificial neural network]]s__: [[Neural networks [2.10] : Training neural networks - model selection|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16]]
,,//Old comment//: One can show (maybe technical details I don't know..) that given the real distribution of the data, and a sample used for training, one is likely to underestimate the error. So I think cross-validation can be shown rigorously to be good for assessing a model's predictive power (i.e. probability of predicting rightly). See Elements of Statistical Learning book for all details..,,
It is a way to find out if you are overfitting
Related: https://en.wikipedia.org/wiki/Testing_hypotheses_suggested_by_the_data
See also finite model theory
Artificial intuition, understanding.
Methods to build models from data. Automatic reductionism, automatic understanding. They are model-free because we assume you don't have the model to begin with.
See [[Dual process theory]]
Are these similar/the same as [[Nonparametric statistics]], a generalization of that?
[[Multi-cellular organism simulation]]
[[Systems biology]] -- [[Computational biology]]
[[Molecular dynamics]]
Models that describe the processes by which a network //forms// or is //generated// are often called ''generative network models''. One of the most famous ones is the "preferential attachment" model.
!!__''Preferential attachment''__
<small>related to "rich get richer" idea in economics (Herbert Simon).</small>
Preferential attachment (also called //cumulative advantage// in older literature) refers to the idea that new nodes in a network //preferentially attach// themselves to some nodes in the existing network rather than others.
The __attachment__ is described in terms of a probability distribution over existing nodes for the creation of an edge. The __preference__ is described by an ''attachment kernel'', $$a_i$$, which is the probabilistic weight of node $$i$$. The probability that a new node connects to existing node $$i$$ is thus:
$$q_i=\frac{a_i}{\sum_i a_i}$$
Different __preference types__ can be considered, the main categories being:
* __Structural properties__. The most common one is degree (higher prefered). These can be expressed in a vector over nodes: $$\vec{\alpha}$$.
* __Other properties__. Most common one is fitness. Fitness refers to some inherent quantity assigned to each node at its creation, and that is independent of network structure. Another example, could be external factors. We can also write these in a vector: $$\vec{\eta}$$.
The attachment kernel is then generally a function of these: $$a_i=a_i(\alpha_i, \eta_i)$$.
Note: We need a //seed network// (initial condition), to get any network out of this model. The network will eventually be independent of the seed, but this can take a <big>very</big> large number of nodes $$N$$, sometimes in the order of billions.
!!!__[[de Solla Price's model]]__ (dSP model)
Proposed in the study of citation networks.
The main assumption of the model is that the probability of each new edge created whew we add a new node only depends on the degree of that node (on the //in-degree// to be precise, i.e. the number of citations it has). In particular it assumes an //affine preferential attachment//:
$$q_i=\frac{k_i+a}{\sum_i(k_i+a)}=\frac{k_i+a}{N(a+c)}$$
One can write a //master equation// for the degree distribution, which has a steady state (i.e. $$N \rightarrow \infty$$ behavior given by power-law decay with power:
$$\alpha=2+\frac{a}{c}$$.
Thus, many scholars believe that this simple model may describe the fundamental mechanism by which power laws are obtained in many real-world networks.
!!!__Barabási–Albert (BA) model__
Almost a special case of de Solla Price model, but with new assumptions:
* undirected edges
* exactly $$c$$ new edges per new node.
* attachment kernel (a.k.) is now exactly proportional to degree (undirected). Note that now degree is always greater than $$c$$. In terms of the parameters of the dSP model, me add an ancillary direction to the edges of the BA model from new to old nodes, then the a.k. is proportional to $$k_i=k_i^{\text{in}}+c$$ where $$k_i$$ is now the total degree, and $$c$$ is the out-degree. We see that $$c$$ plays the role of $$a$$. the exponent for the power-law tail is thus $$\alpha=3$$.
!!!__Other properties of preferential attachment models__
__Degree distribution as a function of time of creation__
Nodes that were added earlier to the network have had more time for new nodes to attach to them, and thus in average have higher in-degree.
This can be shown by starting with a new quantity: the fraction of nodes (<small>in average over the ensemble, so effectively the probabilty </small>) that a node was created at time $$t$$ and has in-degree $$k$$ when the network has $$n$$ vertices, $$p_k(n,t)$$. The "time" $$t$$ $increments by $$1$$ every time we add a node, and thus effectively labels nodes, in the order by which they were added.
One can then write a master equation, noting that no nodes have $$t>n$$, except the new node which has $$t=n+1$$, and also in-degree $$0$$. However the fraction of nodes having any being created at any particular time goes to $$0$$ as $$n \rightarrow \infty$$, and so we change variables to a probability density in $$t$$ by dividing $$p$$ by $$n$$. We also rescale time by dividing by $$n$$ for convenience, and to properly convert the master equation into a differential equation.
__Sizes of in-components__
Can also derive a master equation. See [[homework problem 4|https://www.dropbox.com/s/3j8o9av52umrejp/math-c5-4_4.pdf?dl=0]]
!!!__[[Extensions of preferential attachment models|Extensions of preferential attachment models (Network theory)]]__
* Edges (like hyperlinks) may also disappear. They may also appear at times after the nodes are added.
* Nodes may also disappear (like websites).
* Preferential attachment could be non-linear on degree, or it could depend on other network property of the node.
!!!__Vertex copying models__
Kleinberg et al [[have proposed|http://cs.brown.edu/courses/cs253/papers/klein-web.pdf]] a model where new nodes imitate the out-edge configuration of an existing node. This is done by linking to some of that edge's neighbours, while the rest of connections are to randomly chosen nodes in the network. In particular, we first choose a node uniformly at random, and then go through its edges, copying it with probability $$\gamma$$, or ignoring it and choosing a node at random with probability $$1-\gamma$$. Remarkably, the expression for the fraction of nodes with degree $$k$$ when node size is $$n$$ has the same form as in Price's model, but with an $$a$$ give by an expression depending on $$\gamma$$, and thus it also follows a [[power law|Power laws]]. The networks still differ in other structural aspects, in particular regarding correlations.
This model reminds us that just knowing the degree distribution, doesn't tell us the mechanism that gave rise to it. We need more information to make this inference.
In some biological networks (metabolic and protein-protein networks) vertex copying seems to be the most probable explanation for observed power law distributions. The mechanism by which this happens is gene duplication (by which, when copying DNA, a gene is duplicated by mistake) and //point mutations// (a mutation of a single base pair). This, through evolution creates different proteins, which (due to their common origin) are still similar and have a lot of protein-protein interactions in common.
//Observations of power law in protein and metabolic networks//:
[[Lethality and centrality in protein networks|http://www.nature.com/nature/journal/v411/n6833/full/411041a0.html]]
[[The large-scale organization of metabolic networks|http://www.nature.com/nature/journal/v407/n6804/full/407651a0.html]]
//Proposed models//
[[A Model of Large-Scale Proteome Evolutionhttp://www.santafe.edu/media/workingpapers/01-08-041.pdf]]
[[ Modeling of protein interaction networks|http://arxiv.org/abs/cond-mat/0108043]]
!!__''Network optimization''__
An alternative networks may "form". Often these are rationally created networks to optimize toward some goal.
__Travel time and cost trade-offs__
A good example is: airline networks where a compromise between lowering cost (so having more central hubs and spokes to fill planes more fully, than flights between two minor destinations) and length of travel (to satisfy customers) is sought.
Ferrer i Cancho have one such simple [[model|http://link.springer.com/chapter/10.1007%2F978-3-540-44943-0_7#page-1]] to find compromises between mean geodesic distance (travel time) and number of edges (cost). They find interesting regimes with local minima with trees with exponential distributions, passing through trees with power law distributions, and finally star graphs, as they varied the parameter controlling the relative importance of the two compromising variables. However, for most values of the parameter, the global minimum was actually the star graph.
An [[alternative model|http://arxiv.org/abs/cond-mat/0603278]] that shows interesting behavior in the global minimum too, by assigning an actual geometric distance to the edges (so that it is a //spatial network//, see [[MMathPhys miniprojects]].Networks). Depending on whether they assigned more importances to travelling times, or to waiting times at nodes, they got more road-like networks (waiting times at intersections negligible) or more airline-like networks (waiting times significant).
See recent research: [[Like air traffic, information flows through neuron 'hubs' in the brain, finds IU study|http://www.eurekalert.org/pub_releases/2016-01/iu-lat012016.php?utm_content=buffer6c26c&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer]]
a term used for part of a molecule. Larger moieties are often [[Functional group]]s.
---------------
https://www.wikiwand.com/en/Moiety_(chemistry)
The [[Mass]] of one [[Mole]] of a [[substance|Chemical substance]], often expressed in grams with symbol $$g/mol$$.
In a mole of substance, there are [[Avogadro's constant]], $$A$$, molecules. Each molecule has mass $$M_r \times u$$, where $$M_r$$ is the [[Relative molecular mass]], and $$u$$ is the [[Unified atomic mass unit]], by definition of the former. Therefore, the mole of substance has mass $$A M_r u = A M_r \frac{1\text{ gram}}{A} = M_r \times 1 \text{ gram}$$ (if we had kept track of the $$\text{mol}$$ unit, it'd be $$M_r \times \frac{1 \text{ gram}}{\text{mol}}$$. Therefore ''molar mass'', in grams, ''is numerically the same as relative molecular mass'', and only the units change (see [[here|http://goldbook.iupac.org/R05270.html]]).
https://www.wikiwand.com/en/Molar_mass
In [[Chemistry]], the ''mole'' refers to a unit of amount of substance, and it is defined as a certain amount of atoms. It is defined as the amount of substance that has as many atoms/molecules as there are atoms in 12 grams of carbon-12 (12C). This number is called [[Avogadro's constant]], $$A$$ and it is approximately $$6 \times 10^{23}$$.
From this one can conclude that:
$$1g = A \times u$$
where $$u$$ is the [[Unified atomic mass unit]]
http://www.bbc.co.uk/education/guides/zysk7ty/revision/2
[img[http://ichef.bbci.co.uk/images/ic/640xn/p01l3y2z.jpg]]
One mole of any (ideal) gas has a volume of 24 dm3 or 24,000 cm3 at rtp (room temperature and pressure). This volume is called the molar volume of a gas.
[img[https://media.giphy.com/media/d2Z80h0V2OAWFNbW/giphy.gif]]
See also [[Biochemistry]]
[[Inner life of the cell video|https://www.youtube.com/watch?v=FzcTgrxMzZk]]
[[Assembly of Bacterial Ribosomes|http://www.jstor.org/stable/1735327?seq=1&cid=pdf-reference#page_scan_tab_contents]]
[[David Odde - Microtubule Self-assembly|https://www.youtube.com/watch?v=OoRQWEeXcQc]]
[[List of protein structure prediction software|https://en.wikipedia.org/wiki/List_of_protein_structure_prediction_software]]
[[My 65 years in protein chemistry|http://www.ncbi.nlm.nih.gov/pubmed/25850343]]
[[Programming the Emergence in Morphogenetically architected complex systems|http://link.springer.com/article/10.1007%2Fs10441-015-9262-z]]
[[Protein folding problem 50 years on|http://science.sciencemag.org/content/338/6110/1042.full]]
[[A review of recent advances in ab initio protein folding by the Folding@home project|http://biochem218.stanford.edu/Projects%202010/Ito%202010.pdf]]
http://molecularmovies.com/
https://en.wikipedia.org/wiki/Ribozyme
See [[DNA]]
[[Foundations of molecular biology|https://courses.edx.org/courses/course-v1:MITx+7.00x_3+2T2015/courseware/Week_6Global/Molecular_Biology_1/]]
Molecular dynamics (MD) simulations provide a computational microscope that lets you watch how a molecule moves over time.
MD works by calculating the forces that result from the interactions between atoms (e.g. electrostatic attraction and repulsion, interatomic van der Waals interactions, bonded interactions). These forces are calculated for every atom in each molecule in a molecular system, and used to work out how each atom would move over time. The result is a molecular dynamics trajectory, which can be used to produce a movie that approximates the motion of the complete biomolecular system.
[ext[Introduction to molecular dynamics simulation|http://udel.edu/~arthij/MD.pdf]]
[[Video intro to molecular dynamics simulations|https://www.youtube.com/watch?v=lLFEqKl3sm4]] Watch!
Wiki page: https://en.wikipedia.org/wiki/Molecular_dynamics
See [[Computational chemistry]]
[ext[http://www.chryswoods.com/dynamics/|Workshop on Molecular Visualisation, Modelling and Dynamics]]
[[VMD (molecular visualization)|http://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=VMD]]
http://www.nature.com/articles/srep03561
[[NAMD tutorial|http://www.chryswoods.com/dynamics/dynamics/README.html]]
[img[http://www.chryswoods.com/dynamics/dynamics/vmd_theory1.jpg]]
the [[particle mesh Ewald algorithm (PME)|https://www.wikiwand.com/en/Ewald_summation]]. This is the clever algorithm that allows each periodic image to interact electrostatically with the infinite number of other periodic images. All simulations that use periodic boundary conditions should turn on PME.
!!![[Simulating in thermodynamic ensembles|http://www.chryswoods.com/dynamics/dynamics/pressure.html]]
Note that the periodic boundary condition doesn't change the fact that a simulation where the (unit) volume is constant is a microcanonical ensemble. This is because the conditions required for the microcanonical ensemble are satisfied: the particle number, energy, and volume of the system are conserved (again, where the system is the unit volume, which we are simulating). If you think about it, reflecting boundary conditions and periodic b.c.s are not so different. The periodic one is just like the reflecting + teleportation to the opposite wall!
If we want to control the pressure, we need to use a barostat. Again, there are many different barostat algorithms available, with the choice of barostat normally coupled with the choice of thermostat. The best barostat to use for biomolecular simulations is namd is the “Langevin” barostat. This randomly changes the volume of the periodic box, and can be switched on by adding the following lines to ‘mdconfig’
[ext[Amber tools|http://ambermd.org/#AmberTools]] has many tools useful for MD simulations
[[A water-swap reaction coordinate for the calculation of absolute protein–ligand binding free energies|http://scitation.aip.org/content/aip/journal/jcp/134/5/10.1063/1.3519057]]
__Steps__
#Minimisation. To remove any bad contacts between atoms that have been added (e.g. hydrogen atoms that have been added in a position that is too close to another atom of the protein), you first need to minimise the system. This involves calculating the force on all atoms, and then using this force to push the atoms towards stable, minimum energy configurations. The result will be a minimum energy conformation of the system.
# Heating. The minimum energy conformation of the system is an approximation of the conformation that the molecules would adopt at near freezing conditions (near absolute zero kelvin). Molecular dynamics simulations of biomolecules are normally run at room temperature or body temperature. To prepare the system for simulation, you now have to slowly heat the molecules. This is to prevent the frozen atoms from exploding if you instantly ran the simulation at room (or body) temperature (imagine what happens if you throw an ice-cube into an extremely hot frying pan - I should add, you should not try this experiment at home as it can be dangerous).
# Equilibration (NVT). The next step is to equilibrate the system using a short run of canonical (NVT) molecular dynamics. This will help the added water molecules find a stable (equilibrium) distribution around the protein and drug.
# Equilibration (NPT). The final step is to equilibrate the system using a short run of isothermal-isobaric (NPT) molecular dynamics. This will adjust the box size, ensuring that the density of water in the periodic box is correct for the simulation temperature and pressure.
# Production (NPT or NVT). The final step is the actual molecular dynamics simulation. This can be run either NPT or NVT depending on your choice (some people prefer NVT as it is quicker, and they argue that, once equilibrated, the volume will not change much). In our case, we will use NPT, and will combine steps 4 and 5 together.
http://www.chryswoods.com/dynamics/mutation/heating.html
[img[Selection_641.png]]
[img[Selection_642.png]]
See [[DNA]], [[DNA replication]]
[[The transforming principle|https://www.youtube.com/watch?v=gsFld6gZVVw]]. Early discovery of DNA as the substance of inheritance/carrying genes. [[Another early experiment|https://www.youtube.com/watch?time_continue=221&v=ymDAQtczyi8]]
!!__Information in [[DNA]]__
[[Genetics]]
[[Second layer of information in DNA confirmed|http://phys.org/news/2016-06-layer-dna.html]]
See also [[Chromosome theory of inheritance]]
--------------------
https://www.wikiwand.com/en/Molecular_genetics
[[Molecular motor proteins|https://www.youtube.com/watch?v=9RUHJhskW00]]:
* Kinesin. Moves along [[Microtubule]]s towards positive end (mostly towards periphery)
* Myosin. Moves along actin filamens
* Dynein. Moves along microtubules towards negative end (mostly towards inside of cell)
[[Electron orbital]]s of [[Molecule]]s. See [[Molecular physics]], and [[this book|https://babel.hathitrust.org/cgi/pt?id=uc1.b3754016;view=1up;seq=10]], and [[these notes|https://users.physics.ox.ac.uk/~smithb/website/coursenotes/moleculesandlasers.pdf]]
A common approach to approximate molecular orbitals, is to construct them as a [[Linear Combination of Atomic Orbitals]] (LCAO). [[Atomic orbital]]
!!Diatomics
For homonuclear diatomic molecules, it is easy to see that the [[Hamiltonian]] has a symmetry corresponding to inversion of the electron coordinate through the center of mass of the molecule. This means that the [[Energy eigenstates]] can be made to be [[Eigenfunction]]s of this reflection operator, which can have eigenvalue +1 or -1. The corresponding classes of molecular orbitals are known as ''gerade'' or ''g'', and ''ungerade'', or ''u'', respectively.
* The gerude orbital is lower in energy, and can is responsible for bonding two atoms. It is thus known as a ''bonding orbital''
* The ungerude orbital is higher in energy, and makes atom not bond. It is thus known as a ''antibonding orbital''.
[img[hydrogen_molecular_orbitals.png]]
[[hydrogen mol|http://www.chemtube3d.com/orbitalshydrogen.htm]]
To determine whether a bond forms, we define the ''bond order'', as
$$\text{bond order} = \frac{\text{no. of electrons in bonding orbitals} - \text{no. electrons in antibonding orbitals}}{2}$$
Some of the ideas from homonuclear diatomics, naturally extend to heteronuclear diatomics, and polyatomic molecules, as they capture the essentials of [[Chemical bond]]ing.
!!Molecular orbitals
See [[Molecular physics]] to see derivation of the electron orbitals.
!!!__Principal quantum number__
$$n$$.
The extension of the [[atomic|Atomic structure]] [[Principal quantum number]]
!!!__Angular momentum__
$$l$$, as for [[Atomic structure]]
!!!__Magnetic quantum number__
[img[molecular_orbital_magnetic_quantum_number.png]]
!!Electronic state in multi-electron orbitals
As for multi-electron atoms, individual $$l_z$$ don't commute with the Hamiltonian, but the $$z$$ component of the //total// angular momentum, $$L_z$$ does, and this becomes the good quantum number, $$\Lambda$$.
[img[angular_momentum_quantum_numbers.png]]
We also have the total spin $$\mathbf{S}$$
There is finally a binary quantum number, $$+$$/$$-$$, corresponding to reflection along the $$y$$ plane.
[[Molecular physics|https://en.wikipedia.org/wiki/Molecular_physics]] is the study of the physical properties of molecules, the chemical bonds between atoms as well as the molecular dynamics.
It is closely related to [[Atomic physics]]
[[Quantum theory of molecules and solids|https://babel.hathitrust.org/cgi/pt?id=uc1.b3754016;view=1up;seq=10]]
[ext[Molecules and lasers Oxford notes|https://users.physics.ox.ac.uk/~smithb/website/coursenotes/moleculesandlasers.pdf]]
* [[Molecular orbital]]
!!__Hamiltonian__
The potential energy has three contributions:
* Electron-nuclear interaction
* Electron-electron interaction
* Nuclear-nuclear interaction
Since the nuclear-nuclear, electron-nuclear and electron-electron separations are similar, the interactions above have approximately the same magnitude. Hence the forces between electrons and nuclei are also similar. However, since the masses of the nuclei are much greater than the electron mass, the velocities of the nuclei are much lower than those of electrons. This fact will lead to a great simpli cation, known as the [[Born-Oppenheimer approximation]]
!!__[[Born-Oppenheimer approximation]]__
See page 13 in [ext[the notes|https://users.physics.ox.ac.uk/~smithb/website/coursenotes/moleculesandlasers.pdf]]
[img[molecular_BO_approx.png]]
[img[Born_Oppenheimer_approx.png]]
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9Gzbtg3DMIFAcPLkSWK5oaHhhx9+2NvbS15KGYPBCAkJKSgokF/48OHDJ0+erF+/XpPjbGpqkn/54MGD6urqTZs2kRRB01yiv7u6ukxMTAQCQWFhYUhICNGT9eHDh8QKHA5HeSPqIqByjzpsX5OzoNLIkSNjYmLy8vLke7x0dna2t7cTG9Ek7GZmZvLP6ezq6qqtrVX+clSH+KMcZfXq1WfPnm1tbSV6P2MY9s4778yUgzIkTWpEHqjOzs5bt269xCAPvLiGTUK5req2O0tLS+UHYmh4DAqnuKCggMvlolOsc8NWV7uBX7gGfknRVn19fWBg4Lp164ghJZGRkQYGBiQT5GdmZjZo4PHjx8r5PfHZ7Pbt2+3t7cSS8vJya2tr5Qcg8vn80aNHy3/8q66uJh8qAAAAQK9TfNSLlORxQkKhUCElFQqFxK/5OI4fPnxYJBIlJyejJRKJ5Msvv/z444/Ry+++++769evob5lM9vvvv0dGRvZbSgGO49nZ2XV1dcSE6EKhkMVirV69esmSJfIHxuPxVG5hzJgxxK1UKBRu2LAhOjp62bJl8mXlb4QYhgUEBNy+fRtNlicUCmk0mqGhoaOj440bN9AINqlUevHiRQ8Pj5aWFjRZpMqIqYyAyoPUfPsK1dQ2nsjevXstLCxSU1PRS7FYvG3bNjR7EvoqV5OwBwUFPXjwgMjys7KyPDw86urq/v77b/lUW5P4q/zk+qpMRQAABPRJREFUs2rVKolEsnDhQk0asyY1IgmUl5dXZmZmdnb2yZMnT58+/euvvzY2Nmoe5AG+U1SeWQ2bhHJb1a1JuLi43L17V7dm2dbW9v3336O/nz9/Hh8fT5xinRu2utqRX9AUuqaoe8toeElRPqckZ5k8vw8KCtq8eTOxcNSoUeHh4SdPnuzr6xuk+8GSJUuCgoLS09PRy/b2djabzWaziUHkhKqqKvmfFvl8voeHx/Tp0wfv2AAAAGgFl2n2pPfy8nI2m93Q0HDnzh0+n0+j0dzd3e3t7QMCAjZu3IjWqaio2L59e1lZmVgsZjKZmzdvNjExSU1N/f3336lU6qxZs3bu3ImmpOjo6EhMTGxsbLSzs6NQKFFRUegBWwUFBRUVFTY2NrW1tcbGxm1tbcHBwYsWLULbV1dKnfb29l27dnV1dY0YMaK1tXXx4sUfffQR+kn90qVL6MAoFIqHh0dYWNiuXbuIgosWLTp27FhhYWF5ebmBgcGzZ89CQkKioqJQ2T///HPbtm1lZWUikYjJZGZlZU2dOhXDsL6+vk2bNt29e3fatGmrVq1Cx1ZfX5+QkCAQCNzd3Xt7e2NiYmpqajZu3Lho0aLU1NT79+8Tm/L3909ISKDT6SQRUJkKkGy/tLSUpJraxhPDsO7u7sTERIFAYG5uLhAINm3aFBgYiL7N/eGHH9DDnkjCjj60oAcM2draisXiDz74ID09vbS01NLSct++fQsWLNAq/ihooaGh8ge5fPnyEydOqHtOlg41UhcomUwWFhZ28eJF+Q16enrm5ua6uLiQBHng7xSSBkzeJNBX2irbqg5NIi8vLzY2tq6uTqtmaWJiEhgYOHLkyE8++aSsrIxKpdbX18+fP584xQNs2Opqp6CysjI+Pv7q1asikcjNzc3f35/NZpNfGUjaNsk5pVAofn5+SUlJXC734MGDFRUVI0aMCAgI2LdvH+ofpWzevHlSqTQvL09hcPnly5dDQkKOHj3KYrEG6ZYgFApTUlJwHKdQKDU1NVFRUehdqYDFYnl7e2/YsIGIub+/v5WV1fnz5+G2CgAAwynFF4lEvb29NBqNRqNRqVSpVNrX19fX14fjuPJ8asMImnMa03gSTKimnnvy5AmHw9m6detg70goFL733nvR0dFoKvSOjo62trYnT57s3r1bIpGUlpa+CWe2p6fHxsbm1q1bEydO1KogSvEvXbqkD9VXuZFXG9ja2lpbW1uVl9aqqipjY2N7e/tXez1xdnbOz8/XfFAEAACAIabpcFsDAwP5IWsUCkXDgaf6/hEHx1/7rPe1r2ZZWdmRI0e++eYbOp2elZXVb5f9l+Ly5csikSg6Ohq9NDc3Nzc3d3BwMDU1DQoKGuD0QcPlzBoaGi5duvT48ePosV/DtGGr3MirDSz6+UgllVPaD7HS0lIjIyPI7wEAQJ9RIARguMvLy/vhhx94PF5dXZ2NjY21tfUQ7NTX17e1tfWXX36RX9jb2/v111/HxsYOTX6vD3bs2HHq1CmF5yX1q7e3F826CIajrKyspKQkiAMAAOgzTTvqAKC3mpqa9uzZM3bsWAzDtm/fPvAZEjXE4/HYbHZjY6OlpSWFQunr62tpaQkNDSV/qu7r54svvhg7dmxcXJwmK1+6dGnv3r2oh/rMmTN37dql8MhYoOdu3LiRkJCQn5//5nyOBQCA4ej/AB0AwTuiw40XAAAAAElFTkSuQmCC
A groupt of [[Atom]]s bound together by [[Chemical bond]]s.
[img[https://media.giphy.com/media/l2JJqOQfXaw4ytCUw/giphy.gif]]
As can be shown again by approximating sum by integral, all the moments $$\langle k^m \rangle$$of a power law distribution diverge for $$m>\alpha-1$$. Of course, this is in the limit of an infinite system with the same distribution, in finite systems (as in networks with a finite number of nodes), the moment will of course be finite (for a network, $$k$$ will have a maximum value, cutting off the domain of the integral used to calculate $$C$$).
In abstract algebra, a branch of mathematics, a monoid is an algebraic structure with a single associative binary operation and an identity element. They are a [[Semigroup]] with identity.
(See context at the [[Arrival of the frequent]]).
Neutral spaces can be astronomically large, much bigger than even the largest viral or bacterial populations (see [[this paper|http://www.ncbi.nlm.nih.gov/pubmed/18973652]]). In that case, the local neighborhood of the population may not be fully representative of the neighborhood of the entire space.
This scenario can most easily understood in the //monomorphic limit//: when mutants are rare, $$NL \mu \ll 1$$
Now, the (average) rate of neutral mutations (per individual) is $$\nu = L \mu \rho$$, as $$\rho$$ is the probability that a mutation is neutral.
See more in the [[Monomorphic limit (Wright-Fisher model)]] tiddler.
Furthermore, Kimura showed two things relating to //fixation// (see [[Population genetics]]):
* ''Probability of fixation''. In a population following the [[Wright-Fisher model]] in a neutral space (no relative fitnessses), with no mutations, a single allele will eventually fix, and the probability for a particular allele to be the one that fixes is equal to its initial frequency. See the derivation [[here|http://websites.math.leidenuniv.nl/probability/lecturenotes/BioStoch.pdf]] or [[here (page 15)|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]]. For the generalization to non-neutral space see [[here (page 201)|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]]. See [[here too|http://jaguar.biologie.hu-berlin.de/~wolfram/pages/seminar_theoretische_biologie_2007/ausarbeitungen/zackay.pdf]].
* ''Mean fixation time''. In a population following the [[Wright-Fisher model]] in a neutral space (no relative fitnessses), with no mutations, the average time that it takes for a particular allele to fix, given that it fixes, is $$\bar \tau(p)=-4N\left(\frac{1-p}{p}\right)\ln(1-p)$$, where $$p$$ is the initial frequency of the allele. For $$p$$ small ($$\rightarrow 0$$), $$\ln(1-p) \rightarrow -p$$, and $$\frac{1-p}{p} \rightarrow \frac{1}{p}$$, and so $$\bar \tau(p) \rightarrow 4N$$. See [[this SX question|http://math.stackexchange.com/questions/585578/biology-wright-fisher-model-of-genetic-drift]], [[the original paper by Kimura|http://www.genetics.org/content/genetics/61/3/763.full.pdf]], [[here|https://services.math.duke.edu/~rtd/CPSS2006/cornelllect.pdf]]. For another way of deriving it, for the related Moran model see [[here (page 57)|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]].
Now, when mutations are rare enough (that the same mutation occurring twice simultaneously is very unlikely), a mutation will initially just have a frequency $$p = 1/N$$. This fact, combined with the above results imply two things:
* //The rate of fixations is equal to the rate of (neutral) mutations of an individual//. The average rate of mutations in the total population is $$N\nu = N L \mu \rho$$. As their initial frequency is $$p = 1/N$$, then they have a probability of fixation $$1/N$$. Then {the rate of {mutations that fix}} is $$\text{rate at which they appear} \times \text{probability they fix}$$ $$=$$ $$N L \mu \rho (1/N) = L \mu \rho$$, where $$\rho$$ is probability that a mutation is neutral (otherwise it can't fix as we assume non-neutral mutants have $$0$$ fitness).
* //{The mean fixation time of {a mutation that fixes}} is much smaller than {the mean time to get {a mutation that fixes}}//, which we write mathematically as, $$$$\bar \tau(p) \ll \tau_m$$. If $$N$$ is large, $$p = 1/N \ll 1$$, and so $$\bar \tau(p) \approx 4N$$. Also the time scale of getting {a mutation that fixes} <small>({the mean time to get {a mutation that fixes}} would be of the same order, of course)</small> is $$1/\text{rate} = 1/(L \mu \rho)$$. Their ratio is $$\frac{\bar \tau(p)}{\tau_m} = 4N L \mu \rho \ll 1$$, by the defining assumptions of the //monomorphic limit//, and noting that $$\rho$$, being a probability is $$<1$$. See [[here|http://evol.bio.lmu.de/_teaching/evogen/Evo10-Summary.pdf]] or [[here|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]]
The second point means that we are in a situation where the population fixes to a particular genotype in $$\mathcal{N}_q$$, in the relatively fast time-scale $$4N$$, and stays there during the much longer time $$1/(L \mu \rho)$$, before it fixes to a new genotype.
-------
+++++++(...)++++++
* Large population limit
* Large genome limit
Short term correlations refer to: p-type individuals are being sampled from the same set (the set of p-types in the 1-neighbourhood of the currently fixed q-type genotype which most of the population has) throughout the time that the population is fixed to a particular genotype. When the population (relativelt quickly) transfers to a new genotype, the p-types produced are now sampled from a new set, but still all of them from the same set. The fact that they are sampled from the same set in inter-refixation times (tau_f), means they have correlations that last tau_f in average ("short-term")
If fixations occur much before the set of p-types in 1-neighbourhood is explored, these correlations are no longer observed.
As our evolutionary process is a Markov process, the first discovery time of a neighbour genotype as well as the arrival time of the neutral mutant ‘‘destined’’ to be fixed, are distributed geometrically (or exponentially in a model with continuous time). Thus the mean of these times are equal to the respective standard deviation, and we have large fluctuations.
The geometrical distribution comes about because the Markov property implies that one can define a probability for each of the two events above ({discovery of all neighbour genotype}, and {arrival of the neutral mutant ‘‘destined’’ to be fixed}), and then, each generation corresponds to a Bernoulli trial, and first arrival times follow a [[geometric distribution|https://en.wikipedia.org/wiki/Geometric_distribution]]. For example, the probability of {arrival of the neutral mutant ‘‘destined’’ to be fixed}, is approximately $$L \mu \rho$$ (valid when $$L \mu \rho \ll 1$$, which we assume. This ultimately comes from the fact that {when the probability of an event is small the average number of times it occurs on a set of trials, is approximately the same as {the probability of it occurring any number of times}}. Essentially $$1 - (1 - p)^N \approx = Np$$ when $$p \ll 1$$. See [[Probability theory]] too).
The __continuous time approximation__: the mean {generation of first success, $$k$$} is fixed to $$\bar{k}= 1/p$$ (where $$p$$ is the prob. of success in Bernoulli trial). We rescale the time variable as $$\tau = k/N$$, and the mean is $$\tau_f = 1/(pN)$$, where $$N$$ is the reciprocal of the time step (i.e. the time we define that a generation lasts). The [[geometric distribution|https://en.wikipedia.org/wiki/Geometric_distribution]] becomes $$\lim_{N \rightarrow \infty} p(1-p)^{k-1} = \frac{1}{\tau_f N}(1-\frac{1}{\tau_f N})^{\tau N-1} = e^{-\tau / \tau_f}$$.
Now, $$\tau_e = (K-1)L/(NL \mu)$$ is the time scale to find all the 1-neighbour genotypes. If $$n_p^g$$ is the //number of mutations that can take $$g$$ to a $$p$$//. Then, $$\tau_e/n_p^g = \frac{1}{\left(\frac{n_p^g}{(K-1)L}\right)NL \mu}$$ is the time-scale to get a $$p$$ mutant from $$g$$. This is because, $$\left(\frac{n_p^g}{(K-1)L}\right)$$ is the probability that {a mutation from $$g$$ leads to $$p$$}. The mean will be of this same order (and I think equal actually). Therefore the time to {first get {a mutation from $$g$$ leads to $$p$$}}}, $$\tau_1$$, is distributed according to $$Q(t_1) = \mathcal{N} e^{n_p^g t_1/ \tau_e} $$, where $$\mathcal{N}$$ is a normalization constant. Therefore, the {probability to get {a mutation from $$g$$ leads to $$p$$}} in the a time $$\tau$$ (the time between two consecutive fixations)} is $$\int_{t_1=0}^{t_1=\tau} Q(t_1) dt_1 = 1 - e^{n_p^g \tau/ \tau_e}$$. Integrating over the distribution of $$\tau$$, we have the probability $$P(n_g^p)$$ that phenotype $$p$$ is discovered before the next neutral fixation:
[img[img/arrivalfrequent1.png]]
$$\xi =\frac{\tau_f}{\tau_e} = \frac{N}{(K-1)L\rho} \approx \frac{N}{L}$$
For $$\xi \gg 1$$ (//large population limit//):
* If $$n_p^g \neq 0 $$, $$P(n_g^p) \approx 1$$
* If $$n_p^g = 0 $$, $$P(0) \approx 0$$
We can apply a //mean-field approximation// to the monomorphic limit. Let $$p(n_p^g)$$ be the probability that a genotype $$g$$ in $$\mathcal{N}_q$$ has the given value of $$n_p^g$$. Then $$\bar{P}(n_g^p) \approx p(0) P(0) + p(1) P(1)$$, if we __assume__ $$p(n_p^g) \ll p(1)$$ for $$n_p^g > 1$$. Then $$\bar{P}(n_g^p) \approx (p(0) \cdot 0 + p(1) \cdot 1) P(1) \approx \bar{n}_{pq} P(1)$$, where $$ \bar{n}_{pq}$$ is the average of $$n_p^g$$.
For $$\xi \ll 1$$ (//large genome limit//), $$P(n_g^p) \approx n_g^p \xi $$. In particular, $$P(1) \approx \xi$$. Then $$\bar{P}(n_g^p) = \bar{n}_g^p \xi = \bar{n}_{pq} P(1)$$.
Finally, $$P(n_g^p)$$ is {the probability that phenotype $$p$$ is discovered before the next neutral fixation}, i.e. the probability that the {number of times {[phenotype $$p$$] appears} before the next neutral fixation} is greater than $$0$$, which is __approximately__ the same as {the average number of times [it] appears}, if {{the probability that {[it] appears in one generation}} is small}, which is the case as {in the monomorphic limit, mutants are rare, $$N L \mu \ll 1$$}. Then, $$\bar{P}(n_g^p)$$ is the average of this quantity, which we use in the mean-field approximation.
Then, following the same derivation as in [[Polymorphic limit (Wright-Fisher model)]], we have
$$T(\alpha) = \frac{\tau_f log(1-\alpha)}{\bar{P}(n_g^p)} = \frac{\tau_f log(1-\alpha)}{\bar{n}_{pq} P(1)}$$
where $$\tau_f$$ is the (mean) duration of each "step" (corresponding to going from being fixated to one genotype to another). Now, {the average number of mutations from a genotype in $$\mathcal{N}_q$$ leading to phenotype $$p$$} can be expressed as $$ \bar{n}_{pq} = (K-1)L\phi_{pq}$$, as $$\phi_{pq}$$ is the mean probability that {a single-point mutation from a genotype in $$\mathcal{N}_q$$ leads to phenotype $$p$$}, and $$(K-1)L$$ is the number of single-point mutations. Now, we can find $$T(\alpha)$$ at the two limits of interest:
[img[img/arrivalfrequent2.png]]
A [[Carbohydrate]]
[[Glucose]]
[ext[Sampling (statistics)|https://www.wikiwand.com/en/Sampling_(statistics)]]. Selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population.
!!__Independent and dependent sampling__
!!!__Dependent sampling__
Dependent sampling is often more computationally easy.
__[[Markov chain Monte Carlo]]__
[[Random walk Metropolis]]
[[Gibbs sampling]]
[[Hamiltonian Monte Carlo]]
Stan programming language
!!__Monte Carlo approximation to [[Integral]]s__
See [[Simplicity bias in finite-state transducers]]
!!!__Statistical properties of FSTs__
[[The graph structure of a deterministic automaton chosen at random |http://arxiv.org/pdf/1504.06238v1.pdf]]
See [[Random deterministic automata]]
!!!__Origin of bias ideas__
[[Topological trace formula]]
[[Random matrix product]]
[[Entropy reduction]]
[[On the entropy of a hidden Markov process|http://sci-hub.cc/10.1016/j.tcs.2008.01.012]]
[[On Grammars, Complexity, and Information Measures of Biological Macromolecules |http://sci-hub.cc/10.1016/0025-5564(80)90004-8]]
[[Activities and Sensitivities in Boolean Network Models]]
!!!__Complexity__
[[Complexity theory]]
-- [[Descriptional complexity]]
-->[[Entropy and complexity of finite sequences as fluctuating quantities|http://sci-hub.cc/10.1016/S0303-2647(01)00171-X]]
-->[[Lempel-Ziv complexity analysis of one dimensional cellular automata|http://ezproxy-prd.bodleian.ox.ac.uk:2837/content/aip/journal/chaos/25/12/10.1063/1.4936876]]
[[Coding Theorems for Individual Sequences |http://sci-hub.cc/10.1109/TIT.1978.1055911]] . <i class="fa fa-bullhorn" aria-hidden="true" style="color:coral; font-size:20px"></i> His complexity measure looks very similar to the topological entropy defined [[here|Descriptional complexity]].
[[http://arxiv.org/pdf/1512.04270v2.pdf]] . $$\epsilon$$-machines reconstruction or computational mechanics, is a powerful tool in the analysis of complexity, which has been used in a wealth of different theoretical and practical situations.
[[Lempel-Ziv complexity]]
[[Network complexity]]
---------
!!!To look at
[[Entropy of Hidden Markov Processes and Connections to Dynamical Systems: Papers from the Banff International Research Station Workshop|https://books.google.co.uk/books?id=1Zz_zHpfbIAC&dq=Entropy+of+functions+of+finite-state+Markov+chains+Blackwell&source=gbs_navlinks_s]] --
[[Codes, Systems, and Graphical Models|https://books.google.co.uk/books?id=z2Pd93k0hsoC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[An Introduction to Symbolic Dynamics and Coding|https://books.google.co.uk/books?id=qSkNs3jr-DIC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Fundamentals of Codes, Graphs, and Iterative Decoding|https://books.google.co.uk/books?id=D0bW8D6BThMC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Topological Entropy and Equivalence of Dynamical Systems|https://books.google.co.uk/books?id=ozdOJ5HyDgQC&dq=Entropy+of+functions+of+finite-state+Markov+chains+Blackwell&source=gbs_book_similarbooks]] --
[[Symbolic Dynamics and Its Applications|https://books.google.co.uk/books?id=MlocCAAAQBAJ&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Ergodic Theory and Topological Dynamics of Group Actions on Homogeneous Spaces|https://books.google.co.uk/books?id=T5NgCaa1j-4C&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Substitutions in Dynamics, Arithmetics and Combinatorics|https://books.google.co.uk/books?id=Cmogpq-lSnoC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Combinatorics on Words|https://books.google.co.uk/books?id=X2G5BQAAQBAJ&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Fractal Geometry, Complex Dimensions and Zeta Functions|https://books.google.co.uk/books?id=kurIRPWxR68C&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]] --
[[Dynamics and Randomness|https://books.google.co.uk/books?id=EzOTVDHcKIsC&pg=PA213&lpg=PA213&dq=Entropy+of+functions+of+finite-state+Markov+chains+Blackwell&source=bl&ots=HuvmLJWIzf&sig=rGysf0w5R1B0sQ-Er_7aKwptbvE&hl=en&sa=X&ved=0ahUKEwj2oqWz4NLNAhWBI8AKHc2HB2sQ6AEIODAG#v=onepage&q=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&f=false]]
[[Resolving Markov Chains Onto Bernoulli Shifts Via Positive Polynomials|https://books.google.co.uk/books?id=R9hw4RusEYgC&dq=Entropy%20of%20functions%20of%20finite-state%20Markov%20chains%20Blackwell&source=gbs_similarbooks]]
[[Complexity of strings in the class of Markov sources|http://sci-hub.cc/10.1109/TIT.1986.1057210]] -- [[citations|https://scholar.google.co.uk/scholar?cites=12275133346903048487&as_sdt=2005&sciodt=0,5&hl=en]]
[[On the entropy of a hidden Markov process|http://sci-hub.cc/10.1016/j.tcs.2008.01.012]] -- [[citations|https://scholar.google.co.uk/scholar?cites=15970945639303496057&as_sdt=2005&sciodt=0,5&hl=en]]
[[lempel ziv complexity finite state channel|https://scholar.google.co.uk/scholar?hl=en&q=lempel+ziv+complexity+finite+state+channel&btnG=&as_sdt=1%2C5&as_sdtp=]]
[[lempel ziv complexity markov model|https://scholar.google.co.uk/scholar?q=lempel+ziv+complexity+markov+model&btnG=&hl=en&as_sdt=0%2C5]]
<mark>Check what these are!</mark> [[epsilon machines|https://scholar.google.co.uk/scholar?hl=en&q=epsilon+machines&btnG=&as_sdt=1%2C5&as_sdtp=]]
__Random matrix product__
[[Capacity of finite state channels based on Lyapunov exponents of random matrices|https://scholar.google.co.uk/scholar?cites=16832761267123139480&as_sdt=2005&sciodt=0,5&hl=en]]
[[Basic properties of the projective product with application to products of column-allowable|https://scholar.google.co.uk/scholar?start=30&hl=en&as_sdt=2005&sciodt=0,5&cites=327936507223547539&scipsc=]]
A structure-preserving map
https://www.wikiwand.com/en/Morphism
https://en.wikipedia.org/wiki/Morphogenesis
"How the tiger got its stripes."
Turing foundational paper
__Reaction-diffusion equations__
[[Computer simulation of reaction-diffusion equations|http://www.pacm.princeton.edu/documents/Kimura.pdf]]
[[Simulation in Matlab|http://blogs.mathworks.com/graphics/2015/03/16/how-the-tiger-got-its-stripes/]]
[[Xmorphia|http://mrob.com/pub/comp/xmorphia/index.html]] Nice exploration of the Gray-Scott reaction-difussion DE.
http://mrob.com/pub/comp/xmorphia/pde-uc-classes.html
[[RSA ANIMATE: Drive: The surprising truth about what motivates us|https://www.youtube.com/watch?v=u6XAPnuFjJc]]
[[How Earth Moves|https://www.youtube.com/watch?v=IJhgZBn-LHg]]
[img[http://giant.gfycat.com/InexperiencedQuestionableAegeancat.gif]]
https://en.wikipedia.org/wiki/Mpemba_effect
warm freezes faster
http://www.eoht.info/page/Erasto+Mpemba
[[O:H-O Bond Anomalous Relaxation Resolving Mpemba Paradox|http://arxiv.org/abs/1310.6514]]
[[Why Hot Water Freezes Faster Than Cold—Physicists Solve the Mpemba Effect|https://medium.com/the-physics-arxiv-blog/why-hot-water-freezes-faster-than-cold-physicists-solve-the-mpemba-effect-d8a2f611e853#.i6swm0wpz]]
[[Mechanisms Underlying the Mpemba Effect in Water from Molecular Dynamics Simulations|http://pubs.acs.org/doi/pdf/10.1021/jp511752n]]
[[video (basic)|https://www.youtube.com/watch?v=8dsTvBaUMvw]] -- [[video (advanced)|https://www.youtube.com/watch?v=TfYf_rPWUdY]]
<img style="background-color:white;" src="https://upload.wikimedia.org/wikipedia/commons/4/44/Protein_synthesis.svg">
more details........
!!!__Translation initiation__
RBS. Ribosomal binding site. Translation initiated by [[Ribosome]] subunit binding to the RBS.
Shine Dalgarno (SD) sequence is the most common one. It binds to the 16S [[rRNA]].
Secondary structure at ribosome binding sites. If the SD sequence is hybridized, it can't be bound by the rybosome, and the gene isn't translated.
Regulators can change the secondary structure, giving a way of regulating translation.
RBS calculator, UTR library designer.
!!!__Ribosome drafting__
When successive ribosomes bind to a mRNA faster than the mRNA can refold. Maintains mRNA in unfolded state. Accelerates protein synthesis.
Therefore protein synthesis depends on the speed of folding of the secondary structure.
A system with multiple [[Agent]]s.
A prominent example is a system of multiple [[Reinforcement learning]] agents.
See [[Deep learning]]
!!![[Max-margin learning, transfer and memory networks|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=2m08s]].
good for generalizing models, ''transfer learning'', ''multi-task learning''. Good when don't have much supervision data.
''[[Max-margin|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=29m25s]]'': learning a function that identifies sensible data (e.g. sentences that make sense), thats what we do with the algorithm he explains of finding a prob dist bigger at the data points that "anywhere" else. This will, in particular, make the NN learn a good representation of the data, or //embedding//. For this we use ''hinge loss''. In practice, [[we do this|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=37m30s]]
Learn embeddings in one task and transfer these to solve new tasks
[[Example|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=15m50s]]. He exaplains how deep multi-instance learning works. Nice
[[Matching|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=22m30s]]
[[Corruption|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=25m10s]]
Example: [[Bi-lingual word embeddings|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=41m07s]]
When you can't corrupt the data: [[Siamese networks|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=42m50s]] [[Paper|http://yann.lecun.com/exdb/publis/pdf/chopra-05.pdf]]
Example: [[Question answering system|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=45m09s]]. Followed by //relation learning// (learning triplets like "cat eats mouse")
memory networks (see below) may be useful for transfer learning too..
One-shot learning using conv nets, as we've already have good embeddings, just compare objects in embeddings. [[See beginning of this|https://www.youtube.com/watch?v=56TYLaQN4N8&index=12&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw]]
Review paper: https://arxiv.org/abs/1309.7233
When a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications. Such systems include multiple subsystems and layers of connectivity.
[[The structure and dynamics of multilayer networks|https://arxiv.org/abs/1407.0742]]
__Some types__
See paper for details:
* [[Multiplex networks]]
* [[Interdependent networks]]
* Networks of networks
[[Multilayer Networks Library for Python (Pymnet)|http://people.maths.ox.ac.uk/kivela/mln_library/]]
A network in layers, and with connections between layers; the interconnections between layers are only between a node and its counterpart in the other layer (i.e. the same node).
http://cosnet.bifi.es/network-theory/multiplex-networks/
[[http://people.maths.ox.ac.uk/~lee/slides_Arenas.pdf]]
See [[Concurrent computing]]
[[Introduction to Processes & Threads|https://www.youtube.com/watch?v=hsERPf9k54U]]
Processes are divided into threads, that each has their own [[Call stack]], but which however, share the memory (owned by the process). This can make programs more efficient. For instance, microsoft word may be a single process. However, it may have a thread for reading input, and one for writting to files, and another one for printing to screen. [[Concurrent programming]] designs the program so that these threads may be running for the duration of the process, instead of switching between them. This abstraction of concurrent threads allows for easier design of many large programs. However, it creates some challenges to keep synchronized execution, so that actions between different threads don't mix up.
For instance, a thread may begin writting ot some object in memory, and the scheduler switches to a different thread, which now begins to write to that object. The result of this may not be as desired, if one didn't take this possibility into account..
A thread that is independent can be called a deamon..
* [[Vector calculus]]
* [[Matrix calculus]]
__Important quantities__
* [[Gradient]]
* [[Hessian]]
An extension of the univariate [[Taylor expansion]] to [[Multivariate calculus]]:
$$f(x+\delta x) = f(x)+\nabla^T f(x) \delta x + \frac{1}{2} \delta x^T H(x) \delta x$$ $$ + \text{higher order terms}$$
where $$H$$ is the [[Hessian]]
[img[https://media.giphy.com/media/6nz2wWbvEixYA/giphy.gif]]
The manipulation of [[Wave]]s and [[Vibration]]s ([[Sound]]s) by [[Sentient being]]s. The physical manifestation of the [[rhythmic|Rhythm]], [[harmonic|Harmony]] and [[melodic|Melody]] temporal patterns present in the [[Mind]]/[[Brain]]s of these beings. Its perception is able to evoke [[Emotion]], so removed from [[Logic]]al and [[linguistic|Language]] thinking, that it is probably on of the purest [[Art]]s.
[[Music composition]] -- [[Music theory]]
!!!__Classical and orchestral music__
Beethoven
Mahler. Symphony 5 [[Symphony 1|https://www.youtube.com/watch?v=cQFjDBFXN58]]
https://www.youtube.com/watch?v=eqfmwxakJEk
[[The Greatest Waltzes of All Time|https://www.youtube.com/watch?v=csZj-jRds38]]
Best acappella: Carmel Acappella
[[Bach]]
!!!__Electronic music__
Stimming
[[Haywyre: The Voyage Full Album|https://www.youtube.com/watch?v=xUVmvqwyAeg]] <big><big><i class="fa fa-smile-o" aria-hidden="true"></i></big></big>
[[Concentration \ Programming Music 001 (part 1) |https://www.youtube.com/watch?v=svngvOLPd5E]]
https://www.youtube.com/watch?v=eHOb7IJ6Bk0
https://www.youtube.com/watch?v=s1lvEVg1T9k
https://www.youtube.com/watch?v=uQ5FfZ1wKSA
https://www.youtube.com/watch?v=WXiJBR5i9bM
Experimenting with alternative tunings: https://soundcloud.com/roberto-la-forgia/sets/beauty-in-the-beast-by-wendy-carlos-1968
[[SOLAR FIELDS - SWOOSH|https://www.youtube.com/watch?v=tNZBXbsXzos]]
nice psychedelic music: https://www.youtube.com/watch?v=wzLLPccLjlk
[[TheFatRat - The Calling (feat. Laura Brehm)|https://www.youtube.com/watch?v=KR-eV7fHNbM]]
!!!__Space ambient__
Stellardrone.
https://www.youtube.com/watch?v=7OQx3dMjBMQ&list=PLmGEbmwqAA4IYqCuH3bHzTVVtdpG6N4IJ&index=4
https://www.youtube.com/watch?v=1iKA2wJp97s
[[Jón Hallur - Red Glowing Dust |https://www.youtube.com/watch?v=1iKA2wJp97s]]
[[AlienHand - Catarina|https://www.youtube.com/watch?v=uc_aci4zSKc]]
!!!__Nordic music__
Wardruna. https://www.youtube.com/watch?v=bn1ct1xomoY https://www.youtube.com/watch?v=b_AlO85w3wE https://www.youtube.com/watch?v=CriOF8z-wTM https://www.youtube.com/watch?v=z0PvZGVPiJU https://www.youtube.com/watch?v=7fPoRacRhKE
!!!Music from around the world and time: http://radiooooo.com/
!!!__Eastern music__
https://www.youtube.com/watch?v=y5tcbD5in7k
!!!__Medieval music__
------
Vangelis. Cosmos, voices
To the unknown man, messages, ask the mountains, conquest of paradise, alpha, entiends vous les chiens aboyer?
-----
__OSTs__
[[The Martian|https://www.youtube.com/watch?v=V8dE4ZrjcC4]]
Interstellar
Oblivion
[[Everest OST|https://www.youtube.com/watch?v=1dNxaVa5-Do]]
-----
[[Transistor soundtrack|https://www.youtube.com/watch?v=-zA1jRmAYfU]]
https://www.youtube.com/watch?v=l8SfXhG2zxg
https://www.youtube.com/watch?v=Bvf5F7UfQ3c
----
__Xenharmonic music__
https://en.wikipedia.org/wiki/Xenharmonic_music
http://xenharmonic.wikispaces.com/
https://soundcloud.com/roberto-la-forgia/02-beauty-in-the-beast?in=roberto-la-forgia/sets/beauty-in-the-beast-by-wendy-carlos-1968
Master class by Hans Zimmer: https://www.masterclass.com/classes/hans-zimmer-teaches-film-scoring?utm_source=Paid&utm_medium=Facebook&utm_term=Aq-Prospecting&utm_content=Link&utm_campaign=HZ
Melody
Harmony
Rhythm
See [[Human hearing]].
Equal temperment and just intonation:
https://www.youtube.com/watch?v=VRlp-OH0OEA
See also xenharmonic music..
https://musiclab.chromeexperiments.com/Technology
[[What is up with Noises? (The Science and Mathematics of Sound, Frequency, and Pitch)|https://www.youtube.com/watch?v=i_0DXxNeaQ0]]
!!![[Twelve Tones|https://www.youtube.com/watch?v=4niz8TfY794]]
http://www.lightnote.co/
See [[Population genetics]]
[[Neutral evolution of mutational robustness|http://www.pnas.org/content/96/17/9716.full.pdf]]
In evolution of ribozymes in vitro, mutations responsible for an increase in fitness are only a small minority of the total number of accepted mutations (see [[Continuous in vitro evolution of catalytic function.|http://www.ncbi.nlm.nih.gov/pubmed/9110984]]). This fact indicates that, <b>even in adaptive evolution, the majority of point mutations is neutral</b>. This is the basis of [[Kimura's neutral theory of evolution|https://en.wikipedia.org/wiki/Neutral_theory_of_molecular_evolution]], see [[the paper|http://isites.harvard.edu/fs/docs/icb.topic887718.files/kimura.pdf]].
A ''neutral network'' is a collection of mutually neutral genotypes (i.e. producing the same phenotype, whether structure or function), which are connected via single mutational steps; they sometimes form extended networks that permeate large regions of genotype space. A population is ''mutationally robust'' (insensitive against mutations) when it inhabits a highly interconnected region of the network so that most mutations lead to the same neutral network, thus leaving the phenotype unchanged.
In [[Neutral evolution of mutational robustness|http://www.pnas.org/content/96/17/9716.full.pdf]], the authors found analytically, that for a range of population sizes and mutation rates of biological interest, <b>the population's distribution over a neutral network is determined solely by the network's topology</b>.
In [[Information theory]], the ''mutual information'' between [[Random variable]]s $$X$$, and $$Y$$ is defined as:
$$I(X;Y) = \sum_{x,y} p(x,y) \log{\frac{p(x,y)}{p(x)p(y)}} = E \log{\frac{p(X,Y)}{p(X)p(Y)}}$$
where $$E$$ denotes expectation. The mutual information measures <b>the amount of information we obtain about $$X$$ by knowing $$Y$$</b> (see result below).
[[video|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=11m50s]]
[[The mutual information between a random variable and itself is equal to its entropy|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=13m13s]]
Some results ([[video|https://www.youtube.com/watch?v=6RJP5m3m1XA&index=7&list=PLJfu_xpF92pvTfcJAILr5Kg1ptMvHUnft#t=14m23s]]):
$$I(X;Y) = H(X) - H(X|Y) = H(Y) - H(Y|X)$$
$$H(X|Y)$$ is the [[Conditional entropy]] and thus gives you the information about $$X$$ that $$Y$$ doesn't give you.
* [[Myocyte]]s, [[Heart]] [[Muscle]] [[Cell]]s
!!__[[Calcium]] ions activation of [[Actin]] filaments__
[[Calcium]] ions activation of [[Actin]] filaments, so that [[Myosin]] can move the actin filaments relative to each other.
!!__[[Mitochondria]]__
A [[Generative supervised learning]] algorithm used when the input space is $$\{0,1\}^n$$, so an input point consists of $$x_i \in \{0,1\}$$, $$i=1,2,...,n$$.
The particular variant below is called ''Multivariate Bernoulli event model'', as it is part of a family of models called ''event models'' (another example of which is below).
Even though the assumptions in naive Bayes are too simplifying, the model often gives good results, because it isn't prone to [[Overfiting]] due to the relatively small number of parameters. It is however, not very good as a [[Generative model]], but it does well as a classifier.
See [[Wiki|https://www.wikiwand.com/en/Naive_Bayes_classifier]]
[[Intro lec vid|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=44m35s]]
[[Definition of naive Bayes assumption|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=48m39s]]
[[Problem with Naive Bayes|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=1h02m45s]]. Probabilities $$P(X|Y)=0$$ for $$X$$s that have never been observed, and this causes problems ($$P(Y|X)$$ undefined). [[How to fix it|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=1h06m40s]] [[actually here|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=1h09m10s]]... (the method is known as [[Laplace smoothing]]).
[[Naive Bayes is a linear classifier|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=27m]], just like [[Gaussian discriminant analysis]], it creates a [[Hyperplane]] [[Classification]] boundary, and a sigmoid posterior, like [[Logistic regression]]
!!!__Generalization to when $$x_i$$ can take any of $$k$$ values__
[[here|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599&spfreload=1#t=3m25s]]. Can arrise when discretizing a real valued $$x_i$$.
!!!__Variant for sequences (Multinomial event model)__
[[here|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599&spfreload=1#t=6m0s]]. [[description of model|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599&spfreload=1#t=8m5s]].
[[This is the log likelihood|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=20m33s]]
[[Maximum likelihood estimates|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599&spfreload=1#t=12m45s]] [[Laplace-smoothed estimate|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=14m55s]]
[[Video|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=20m]] applying it to [[Text clustering]]
Uses a mixture of [[Naive Bayes]] distributions.
[[EM algo for mixture of naive Bayes|https://www.youtube.com/watch?v=LBtuYU-HfUg&list=PLA89DCFA6ADACE599&index=13#t=24m50s]]
__Eric Drexler's scheme__
*Structural support. Large slabs of rigid protein (manufactured by self-assembly). Or out of DNA?
*Stepper motors.
** Three steps (phases) to be able to go back and forth.
***Actuators are molecules (like azobenzenes).
***Control by three wavelength (visible; what is problem with UV ones? Not enough non-overlapping wavelengths I suppose was the problem).
***Nanosecond response times.
*Material transport by diffusion.
*Material deposition by tip that activates site (catalytic).
**To avoid a significant error rate by thermal fluctuations:
***"large" structural components
***larger molecular building blocks.
[[Oxford as one center to develop this!?|https://www.youtube.com/watch?v=50iAoe7bs9o#t=24m19.5s]]
[img[nano_3D_printer2.png]]
Questions:
Exactly how do the blocks hold together? The stepper motor surfaces should be designed to have modulatable //attractice// potentials, I imagine.
Predict the stochastic motion of these. How large do surfaces have to be? How fast will they move?
[[Slides|https://drive.google.com/folderview?id=0B1foXI_b_a7DRUV3WEZZajRlVm8&usp=sharing_eid&ts=56aae62b]]
[[Talk at Martin School on Jan 2016|https://www.youtube.com/watch?v=lvUFNp-TWbg]]
[[Notes from talk|https://files.acrobat.com/a/preview/44cb112e-3557-4e82-a7f2-cecb1f8631bb]]
__Protein engineering__
Extended structures:
[[Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces|http://science.sciencemag.org/content/348/6241/1365]]
Compact structures:
[[Accurate design of co-assembling multi-component protein nanomaterials|http://www.nature.com/nature/journal/v510/n7503/full/nature13404.html]]
__Photoswitching__
http://pubs.rsc.org/en/content/articlelanding/cc/2013/c3cc46045b#!divAbstract . Allows more wavelengths to be used, including red light which is penetrates skin more.
http://onlinelibrary.wiley.com/doi/10.1002/anie.201207602/abstract . Can now switch at nanosecond rates.
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Key Challenge: Coordinated cross-disciplinary development
DOE workshop. Oxford, etc.
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
(a.k.a. nanosystems engineering)
[[DNA nanoengineering]]
https://en.wikipedia.org/wiki/Nanoengineering
http://nanoengineering.ucsd.edu/
http://web.mit.edu/nanoengineering/
[[Microsystems & Nanoengineering|http://www.nature.com/micronano/]]
[[Microsystems and nanosystems engineering]]
!!__Nano-drugs delivery systems__
Only 3% of medicines often reach target. Particularly bad with cancer.. We need smart nanosystems. Problem with aggregiation. Use circular DNA wrapped around carbon nanotubes makes it stable in many solution media. Target only cancers with molecule added to DNA. Add fluerescent moleucle for diagnostic. Then theragnostics, both therapeutics and dignosis on spot.
Can use the wrapping of DNA for other nanoparticles too!
Nanotoxicity and nanowaste are important problems too.
[[A Logic-Gated Nanorobot for Targeted Transport of Molecular Payloads|http://science.sciencemag.org/content/335/6070/831]]
!!__Nano-sensors and diagnostics__
Detect causes of diseases before they are pathological.
!!__Nano-devices for medical surgery__
Nano-needle. Very non-aggresive.
!!__Nanotechnology for regenerative medicine__
3D-printing with cells. We need extracellular matrix (scaffold) to guide stem cells as they develop (in particular when they stop growing).
-----------------------
__Stability of DNA nanomachines in cellular environment__
One of the main challenges in DNA-based nanomedicine! One of the main arguments for approaching nanomedicine with some non-organic materials.
[[Addressing the Instability of DNA Nanostructures in Tissue Culture|http://pubs.acs.org/doi/abs/10.1021/nn503513p]]
[[Stability of DNA Origami Nanoarrays in Cell Lysate|http://pubs.acs.org/doi/abs/10.1021/nl1040836]]
News: http://www.nanowerk.com/
[[Nanomanufacturing course|http://mechanosynthesis.mit.edu/education/#ME599-3]] [[YB|https://www.youtube.com/watch?v=IyhjoYen5rI]]
[[Nanoscale Machines: Building the Future with Molecules|https://www.youtube.com/watch?v=NJW3KfjM2aw]]
Foresight Institute
http://nanohub.org/
[[Nanosystems and nanoelectronics|https://nanohub.org/groups/nanosystems]]
https://en.wikipedia.org/wiki/List_of_software_for_nanostructures_modeling
http://nanohub.org/resources/4540
!!![[Autodesk Bio/Nano Research| https://autodeskresearch.com/groups/bionano]]
[[Engineering programmable molecular systems inspired by biology|https://yin.hms.harvard.edu/research.html]]
http://singularityhub.com/2016/05/16/nanorobots-where-we-are-today-and-why-their-future-has-amazing-potential/
!!__AI and nanotechnology__
See some papers on my facebook posts.
[[Unconventional computing using evolution-in-nanomaterio: neural networks meet nanoparticle networks|http://doc.utwente.nl/100187/]]
!!__[[Nanoengineering]]__
!!!__[[Atomically precise manufacturing]]__
[[DNA nanotechnology]]
[[Order custom DNA origami parts!|http://shop.tilibit.com/index.php?main_page=index&cPath=70]]
[[Nano 3D printer]]
http://ezproxy-prd.bodleian.ox.ac.uk:2076/nnano/journal/v5/n7/full/nnano.2010.147.html
__[[Protein engineering]]__
Link my slides from Physsoc talk here~
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Eric Drexler blog
[[Self-assembly for nanotechnology|http://metamodern.com/2009/01/26/self-assembly-for-nanotechnology/]]
[[Brownian mechanosynthesis|http://metamodern.com/2009/04/11/brownian-motors-and-mechanosynthesis/]]
--------
Software:
http://cdna.au.dk/software/
See also [[Computational chemistry]]
-------
Bionano
[[Remote control of myosin and kinesin motors using light-activated gearshifting|http://www.nature.com/nnano/journal/v9/n9/abs/nnano.2014.147.html]]
* [[Human intelligence]]
* [[Physarum machines and physarum solver]] (fungal distributed intelligence)
* [[Animal intelligence]]
* [[Plant intelligence]]
Classified in [[Language family]]es.
[[Evolution of language]]
Processing of [[Natural language]], by [[computers|Computer science]].
!!__Techniques__
[[NLP with python|https://pythonprogramming.net/tokenizing-words-sentences-nltk-tutorial/]]
!!!__[[Deep learning]]__
[[Convolutional neural network]], [[Transfer learning]] (for learning embeddings), [[Recurrent neural network]] ([[Long short-term memory]])
Hybrid character-word NNs: http://arxiv.org/pdf/1604.00788v1.pdf
[[Latent semantic indexing]]
!!!__[[Parsing]]__
[[Google SintaxNet (includes Parsey MacParseface)|https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html]] [[code|https://github.com/tensorflow/models/tree/master/syntaxnet]]. See [[Grammar]]
https://demos.explosion.ai/displacy/?text=I%20like%20some%20good%20almonds&model=en&cpu=1&cph=0
!!!__Features for NLP__
Word vectors: see [[Processing our own Data - Deep Learning with Neural Networks and TensorFlow part 5|https://www.youtube.com/watch?v=7fcWfUavO7E&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=48]]
---------------------------
[[Visual question/answering system|http://iamaaditya.github.io/2016/04/visual_question_answering_demo_notebook]]
!!__Software for NLP__
[[Natural Language Toolkit (python)|http://www.nltk.org/]] It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries
http://textprocessing.org/tag/information-extraction-in-python
http://www.nltk.org/book/ch07.html
[[Sound]]s produced by [[Nature]]
[[The Sounds Of Earth|https://www.youtube.com/watch?v=s-6CvmmcG0w]]
Most sounds we perceive are transmitted through [[Air]], the medium in which we normally live. These are produced whenever vibrations are excited in the air. Because these require motion, it makes sense that most sounds in Nature are due to the more dynamical aspects of it: [[Life]], [[Fluid]]s
See [[Ethology]] for the immense variety sounds that [[Animal]]s produce.
[[Fluid]]s include [[Liquid]]s and [[Gas]]es. The most prominent liquid is water, and indeed the interaction of water with gases ([[Bubble]]s), itself (waterfall, waves on the sea), or with [[Solid]] matter ([[Rain]] falling on the ground, or [[leaves|Leaf]], [[Pebble]]s rolling in a stream, etc.) are among the most common non-biological natural sounds.
The complex interaction with air with solid surfaces can also produce the recognizable sounds of [[Wind]], sometimes producing sounds with a relatively clear pitch, like of air flowing through imperfect organ pipes.
[[Electrical|Electricity]] phenomena, such as thunder, produce remarkable sounds where the air is directly stimulated by its sudden ionization.
[[Rock]]s falling downhill, [[volcanic|Volcano]] eruptions, earthquakes, etc.
Nearest-neighbor methods: To get the prediction Ŷ for a point $$x$$, use [those observations ($$k$$ of them) in the training set T, closest in input space to point x]. Remember training set is a set of pairs $$(x,y)$$. Closest often refers to Euclidean distance.
It turns out that the //effective number of parameters// of k-nearest neighbors is $$N/k$$, even if technically there is only one parameter, $$k$$.
--> To me it seems more like a method in [[Nonparametric statistics]]! Indeed it is (see [[Wiki|https://en.wikipedia.org/wiki/Nonparametric_statistics#Non-parametric_models]]).
[[Classification w/ K Nearest Neighbors Intro - Practical Machine Learning Tutorial with Python p.13|https://www.youtube.com/watch?v=44jq6ano5n0&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=13]]
When a flow of liquid occurs through a membrane from a more concentrated solution to a more dilute solution, it is designated as negative osmosis. Compare with (positive) [[Osmosis]]
See [[Physical mechanisms of osmosis]]
!!!See here: http://physics.stackexchange.com/questions/265752/can-osmosis-go-the-other-way/265879#265879
!!![[MECHANISM OF OSMOTIC FLOW IN POROUS MEMBRANES|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1334591/pdf/biophysj00323-0049.pdf]]
Many standard theoretical calculations of equilibrium osmotic pressure work under very ideal/simplifying assumptions; like the lattice model in Physical biology of the cell book.
Similarly treatments of osmotic flow are often simplified see for instance
[[The solution-diffusion model: a review|http://www.sciencedirect.com/science/article/pii/037673889500102I]].
Real life application of osmotic flow need more complete descriptions, which include parameters, which are often measured, mainly the ''reflection coefficient''. Results can often differ (often just quantiatively) from more naive thermodynamic treatments.
When you try to find these parameters theoretically is when you get into the hard part, as a microscopic model is needed, whether based on kinetics, or hydrodynamics. This is where the richness of real-life phenomena comes to light.
Careful theoretical treatment has found negative reflection coefficients to be possible: [[MECHANISM OF OSMOTIC FLOW IN POROUS MEMBRANES|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1334591/pdf/biophysj00323-0049.pdf]], [[Diffusioosmosis of nonelectrolyte solutions in a fibrous medium|http://www.sciencedirect.com/science/article/pii/S0927775703001444]] However, I think they are only possible for non-perfectly-semipermeable membranes! See below. Actually Anderson's paper agrees! Note that in his figure 5, negative reflection coefficient is found only when the solute is smaller than the pore!
[[Configurational effect on the reflection coefficient for rigid solutes in capillary pores|http://www.sciencedirect.com/science/article/pii/0022519381903210]]
In the case of osmosis of electrolytes, there's more studies: [[Charge-Mosaic Membranes: Enhanced Permeability and Negative Osmosis with a Symmetrical Salt|http://science.sciencemag.org/content/161/3836/70]]
[[Diffusioosmosis of Electrolyte Solutions in a Fine Capillary Tube|http://pubs.acs.org/doi/abs/10.1021/la062683n]]
[[Anomalous osmosis and salt concentration dependence of the reflection coefficient in charged membranes|http://www.sciencedirect.com/science/article/pii/S0376738800821614]]
Although regular osmosis looks at semi-impermeable membranes, similar diffusio-osmotic effects can be studied for membranes where both solute and solvent can go through the pores:
[[Osmotic Flow through Fully Permeable Nanochannels|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.112.244501]]
[[Drastic alteration of diffusioosmosis due to steric effects|http://pubs.rsc.org/is/content/articlelanding/2015/cp/c5cp05327g#!divAbstract]]
[[Kinetics and thermodynamics across single-file pores: Solute permeability and rectified osmosis|http://scitation.aip.org/content/aip/journal/jcp/110/1/10.1063/1.478118]] (only find negative reflection coefficient (negative diffusion) when the membrane is permeable to solute as well).
--------------------
__Experimental measurements of negative osmosis__
[[NEGATIVE REFLECTION COEEFICIENTS |http://publications.tno.nl/publication/34619959/6PrnBZ/talen-1965-negative.pdf]]
[[Entropy-Driven Pumping in Zeolites and Biological Channels|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.82.3552]] (finds negative osmosis, only when the membrane is permeable to both species)
[[Binary Diffusion and Bulk Flow through a Potential‐Energy Profile: A Kinetic Basis for the Thermodynamic Equations of Flow through Membranes|http://scitation.aip.org/content/aip/journal/jcp/49/6/10.1063/1.1670468]] (finds negative osmosis, only when the membrane is permeable to both species)
Nonequilibrium thermodynamics in biophysics book by Katzir-Katchalsky, Aharon. | Curran, Peter F (in Maths Inst library!)
[[An Experimental Study of Negative Osmosis|http://jes.ecsdl.org/content/61/1/477.short]]
---------------------
[[Anomalous effects during electrolyte osmosis across charged porous membranes|http://www.sciencedirect.com/science/article/pii/0021979782900030]]
[[Osmosis and reverse osmosis in fine-porous charged diaphragms and membranes|http://www.sciencedirect.com/science/article/pii/000186869500246M]]
[[OSMOTIC PRESSURE, ROOT PRESSURE, AND EXUDATION|http://onlinelibrary.wiley.com/doi/10.1111/j.1469-8137.1921.tb05777.x/full]]
[[Osmotic properties of polyelectrolyte membranes: positive and negative osmosis|http://pubs.acs.org/doi/abs/10.1021/la00029a034]]
[[Theoretical calculation of reflection coefficients of single salt solutions through charged porous membranes|http://www.sciencedirect.com/science/article/pii/S0011916408006577]]
A ''neighbourhood space'' is a weaker notion than a [[Topological space]]. It is a [[Set]] with a [[Neighbourhood structure]]
See Csazar 1978
A ''neighbourhood structure'' $$\mathcal{N}$$ on a set $$X$$ is an assignment to each $$x \in X$$ of a [[filter|Filter (Topology)]] $$\mathcal{N}(x)$$ on $$X$$ all of whose elements contain the point $$x$$.
A formula relating the potential difference between two planes, to the ratio in concentration of [[Ion]]s at the two planes, when ignoring the interionic interactions (ok at low ionic concentrations), and at equilibrium. For out-of equilibrium, on gets a [[Fokker-Planck equation]] (advection-diffusion equation).
For derivation in [[electrochemical|Electrochemistry]] terms, see [[wikipedia|https://www.wikiwand.com/en/Nernst_equation]].
For a derivation in terms of [[Kinetic theory]], see the [[Nelson's biological physics book (sec 4.6.3 page 125)|NernstRelationDerivation.pdf]]
|$$j=D(-\frac{dc}{dx} + \frac{q}{k_B T} \mathcal{E} c)$$|''Nernst-Planck formula''|
At equilibrium, the flux $$j=0$$, giving (after integrating over $$x$$):
|$$\Delta(\ln{c})=-q \Delta V_{eq} / k_B T$$| ''Nernst relation''|
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
[[Neuron]] --nerves
* [[Central nervous system]]
** [[Brain]]
** [[Spinal cord]]
* [[Peripheral nervous system]]
** [[Somatic system]]
** [[Autonomic system]]
*** Parasympathetic
*** Sympathetic
http://netwiki.amath.unc.edu/VisComms/VisComms
http://vlado.fmf.uni-lj.si/pub/networks/pajek/
https://sites.google.com/site/ucinetsoftware/home
https://sites.google.com/site/bctnet/construction
__Visulazation__
https://gephi.org/
Measures of [[Complexity]] of a [[Graph]] or [[Network]]
[[Quantitative Measures of Network Complexity|http://link.springer.com/chapter/10.1007%2F0-387-25871-X_5]]
[[What is a complex graph?|http://www.sciencedirect.com/science/article/pii/S0378437108000319]]
!!__[[Algorithmic complexity|Kolmogorov complexity]] of a graph__
[[Correlation of automorphism group size and topological properties with program-size complexity evaluations of graphs and complex networks|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/complexity-of-graphs.pdf]]
They show that: <span style="color:pink;">[[Kolmogorov complexity]] can capture group-theoretic and topological properties</span> of abstract and empirical networks, ranging from metabolic to social networks, to small synthetic networks.
We derive these results via <span style="color:aqua;">two different Kolmogorov complexity approximation methods</span> applied to the adjacency matrices of the graphs and networks. The methods used are the traditional lossless [[compression|Data compression]] approach to Kolmogorov complexity, and a normalised version of a [[Block decomposition method]] ([[BDM|http://arxiv.org/pdf/1212.6745v4.pdf]]) based on algorithmic probability theory.
!!!__Complexity and edge density__
Complexity is minimal for
empty or complete graphs
[img[http://i.imgur.com/v2sXtc3.png]]
[[Kolmogorov Random Graphs and the Incompressibility Method|http://epubs.siam.org/doi/abs/10.1137/S0097539797327805]]
!!!__Complexity vs symmetry of the graph__
The symmetry is measured by the cardinality of the [[Graph automorphism]] group. The following plot from empirical complex networks shows that they are indeed negatively correlated. The graph automorphism is normalized, and NBDM refers to the normalized [[BDM|Block decomposition method]].
[img[http://i.imgur.com/H1mbIzL.png]]
!!__[[Information]] content in a graph__
[[Entropy and the Complexity of Graphs Revisited|http://www.mdpi.com/1099-4300/14/3/559]]
[[Information Content of Colored Motifs in Complex Networks|http://www.mitpressjournals.org/doi/abs/10.1162/artl_a_00045#.V4aO-O02fCI]]
!!__[[Symmetry]] of grahs__
[[Emergence of symmetry in complex networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.77.066108]]
[[Network quotients: Structural skeletons of complex systems|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.78.046102]]
//MMathPhys course mostly about Network Theory//
__Books__
[[Networks: An introduction - Newman|https://files.acrobat.com/a/preview/25f27470-e977-4a86-b52a-7c7236ebd0a2]] -- [[Interactive network science book|http://barabasi.com/networksciencebook/]]
See [[books by Barabasi et al.|http://barabasi.com/book/network-science]], it has nice ones.
//Other research articles//
Check wikipedia network science portal and others resources..
~my problem sheets [[here|https://www.dropbox.com/sh/evp1kycu7k3zd6b/AACmUzNOtkkmpJO2FV6nswDva?dl=0]]~
[[Oxford course website|https://www0.maths.ox.ac.uk/courses/course/28833]] and [[blog|http://networksoxford.blogspot.co.uk/]].
Some important classes of networks:
*[[Scale-free networks]]
* [[small-world networks|Small-world model (Network theory)]]
* [[Spatial networks]]
* [[Multilayer networks]]
* [[Temporal networks]]
,,[[Apollonian networks]],,
-----
!!Empirical study of Networks
-------
!! Fundamentals of network theory
!!![[Mathematics of networks]]
!!![[Measures and metrics for networks]]
!!![[Large-scale structure of networks]]
---------
!!Computer algorithms
!!!Basic concepts of algorithms
!!!Fundamental network algorithms
!!!Matrix algorithms and graph partitioning
-------
!!Network models
!!![[Random graphs|Random graph]]
!!![[Random graphs with general degree distributions]]
!!![[Models of network formation]]
!!!Other network models:
* The [[small-world model|Small-world model (Network theory)]].
* [[Exponential random graphs]].
-------
!!Processes on networks
!!![[Percolation]] and network resilience.
!!![[Epidemics on networks]]
!!![[Dynamical systems on networks]]
!!!Network search
--------
!!//Further network measures and analytics//
!!![[Community structure in networks]]
!!![[Network complexity]]
--------
//Review articles//
[[Statistical mechanics of complex networks|http://barabasi.com/f/103.pdf]]
[[Complex networks: Structure and dynamics|http://www.sciencedirect.com/science/article/pii/S037015730500462X]]
Others
Many many good references here on ''random and evolving networks'': [[http://www.fzu.cz/~slanina/bookmark_files/bkm3-1.html]]
[[Multilayer networks|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3127/23/community-moremultilayer.pdf]]
[[Multiplexing|https://en.wikipedia.org/wiki/Multiplexing]]
[[Like air traffic, information flows through neuron 'hubs' in the brain, finds IU study|http://www.eurekalert.org/pub_releases/2016-01/iu-lat012016.php?utm_content=buffer6c26c&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer]]
[[Mathematics of networks]]
[[Measures and metrics for networks]]
[[Large-scale structure of networks]]
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
[[Stanford Large Network Dataset Collection|https://snap.stanford.edu/data/]]
[[http://www-personal.umich.edu/~mejn/netdata/]]
[[Network data repository|https://networkdata.ics.uci.edu/resources.php]]
[[The Klobenz Network Collection (well organized)|http://konect.uni-koblenz.de/]]
[[Complex Network Resources|http://math.nist.gov/~RPozo/complex_datasets.html]]
[ext[Wilson–Cowan Equations for Neocortical Dynamics |http://download.springer.com/static/pdf/197/art%253A10.1186%252Fs13408-015-0034-5.pdf?originUrl=http%3A%2F%2Fmathematical-neuroscience.springeropen.com%2Farticle%2F10.1186%2Fs13408-015-0034-5&token2=exp=1477143431~acl=%2Fstatic%2Fpdf%2F197%2Fart%25253A10.1186%25252Fs13408-015-0034-5.pdf*~hmac=2f4240b489db249e90b2be101c15c661c56d7eb74e22c14c562d23f86883a345]]
The theory (mainly [[Learning theory]]) of [[Artificial neural network]]s. See also [[Deep learning theory]], [[Mathematical modelling of neural networks]], [[Statistical mechanics of neural networks]]
[[Neural networks class - Université de Sherbrooke (Hugo Larochelle)|https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]
Note that the notation in [[this paper|http://arxiv.org/abs/1608.08225]] is opposite to that standard in [[Machine learning]]. __In the paper, $$y$$ is the input, and $$x$$ is the output.__
!!!__Neural networks are can approximate any smooth function__
Even single-layer ones. Find papers
__Universal approximator theorem__
See paper mentioned in Hugo's vid, //single hidden layer ANNs can approximate any continuous function with sufficiently many neurons in the hidden layer//. There may not be a //learning algorithm// to find the right parameter set though.
!!!__Baye's theorem as a softmax__
As in [[Generative learning]], we can relate $$p(x|y)$$ to $$p(y|x)$$, using [[Baye's theorem]]
[img[Selection_608.png]]
Baye's theorem can be put into the form of a [[Boltzmann distribution]], by defining the "self-information" or "surprisal", or //Hamiltonian//, in the context of [[Statistical physics]]
|[img[Selection_609.png]]|[img width=350 [Selection_610.png]]|
This on turn, can be succinctly written using the [[Softmax]] nonlinear opeartor $$\mathbf{\sigma}$$ as
$$\mathbf{p}(\mathbf{y})= \mathbf{\sigma} [ -\mathbf{H}(\mathbf{y})-\mathbf{\mu}]$$
That means that if we compute the Hamiltonian (which depends on the generating process encoded on the conditional probability distribution $$p(y|x)$$), we can add a softmax layer to compute the Bayes a-posteriori probability distribution. The a-priori distribution $$p(x)$$ goes into $$\mu$$, which is the bias term of the final layer.
!!!__What Hamiltonians (and thus $$p(y|x)$$) can be approximated by feasible neural networks? __
__--> Neural networks can efficiently simulate multiplication__
[img[Selection_612.png]]
See [[paper|http://arxiv.org/pdf/1608.08225v1.pdf]] for proof.
[img[Selection_614.png]]
__--> This means they can efficiently simulate polynomials__
[img[Selection_613.png]]
In the case of a polynomial of degree $$d$$, there are $$(n+d)!/(n!d!)$$ terms (and thus parameters), which corresponds to the [[Number of ways to put n+1 objects in d bins|Number of ways to put n objects in k bins]], where the n+1 objects correspond to the n variables, and an object corresponding to "empty".
In the case of $$n$$ binary input variables (with possible values $$0$$ or $$1$$), any function can be written as a polynomial of degree $$n$$, and only $$2^n$$ terms (as repeating a factor doesn't change the function as $$y_i ^2 = y_i$$.
Furthermore bit variables allow an accurate multiplication approximator that takes the product of an arbitrary number of bits at once. This implies that any function of a bit-variable $$\mathbf{y}$$ can be simulated with just three layers, the middle of which does the appropriate multiplications (so we need $$2^n$$ neurons here), and the last of which sums the terms with appropriate weights to create the polynomial.
!!__Learning of neural networks__
See [[Learning theory]], [[Artificial neural network]]s
//aka [[Memory]]-augmented neural networks//
''Memory'' is good for recognizing time sequence data.
''[[Memory networks|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=48m40s]]''. Apply max-margin. [[Actual drescription|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=51m52s]]. [[Paper|http://arxiv.org/pdf/1410.3916v11.pdf]]
[[Time constraints for facts|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=51m52s]]
''[[Recurrent neural nets|https://www.youtube.com/watch?v=56TYLaQN4N8&index=12&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=7m48s]]''. Vanishing gradient problem, naively, RNNs don't give you long term memory.. [[RNNs|Recurrent neural network]]
''Long Short-Term Memory'' ([[LSTM|Long short-term memory]]) was introduced to solve this problem.
See also [[Content-addressable memory]]
[[Associative Long Short-Term Memory|https://www.semanticscholar.org/paper/Associative-Long-Short-Term-Memory-Danihelka-Wayne/3ed48ecf9e70a513247e3a710ede484e4114c2f0]]
[[Active Long Term Memory Networks|https://arxiv.org/abs/1606.02355]]
[[Attention and Augmented Recurrent Neural Networks|http://distill.pub/2016/augmented-rnns/]]
[[Neural Turing machine]]s
[[Integrating symbols into deep learning]]
Also see [[Neural Turing machine]]
[[Two Minute Papers - Neural Programmer-Interpreters Learn To Write Programs|https://www.youtube.com/watch?v=B70tT4WMyJk]]
[ext[http://www-personal.umich.edu/~reedscot/iclr_project.html]]
Circuits that subserve similar functions are grouped in neural systems that serve broader behavioral purposes.
https://www.ncbi.nlm.nih.gov/books/NBK11061/
!!__[[Decision-making]] and reward systems__
[[Reinforcement learning]]
__Canonical circuit for neocortex__
!!!__Thalamocortical system__
!!__Sensory systems__
[[Sense]]s, [[Perception]]
!!!__[[Visual system|Human vision]] __
__Feedforward connectivity within the visual system__
__Feedback connectivity within the visual system__
!!__Motor system__
Sensory-motor coordination.
Inverse model, neural emulator.
Hummunculus
!!__[[Memory]] system__
!!__[[Sleep]]__
__Sleep switch__
REM sleep subcortical circuitry
A differentiable [[Turing machine]] the internal program of which can thus be [[learned|Machine learning]]. The program can be represented using [[Artificial neural network]]s
[img[http://image.slidesharecdn.com/neuralturingmachines-150104010840-conversion-gate01/95/neural-turing-machines-7-638.jpg?cb=1420333769]]
[img[http://image.slidesharecdn.com/nndl2-150804165908-lva1-app6892/95/neural-turing-machine-tutorial-60-638.jpg?cb=1458368226]]
[[ Neural Turing Machines|https://arxiv.org/abs/1410.5401]]. It emulates working [[Memory]] in the [[Brain]]
__Key aspects__
* [[Recurrent neural network]]s for the controller, and read write heads. Often [[Long short-term memory]]
* [[Memory]]
* Addressing system that implements [[Attention]], and is differentiable.
It can learn basic [[Algorithms]], and thus it's a form of [[Program induction]]. It also addresses the [[Binding problem]] and the problem of computing with variable-length structures, both of which had been studied before. These are important steps to address towards creating [[General artificial intelligence]].
Crucially, every component of the architecture is ''differentiable'', making it straightfor-
ward to train with gradient descent. We achieved this by defining ‘blurry’ read and write
operations that interact to a greater or lesser degree with all the elements in memory (rather
than addressing a single element, as in a normal Turing machine or digital computer)
[[Symposium: Deep Learning - Alex Graves|https://www.youtube.com/watch?v=_H0i0IhEO2g]]
See [[Integrating symbols into deep learning]], [[Neural networks with memory]], [[Augmented RNN]]
Also see [[Neural programmer-interpreter]]
!!__Reading__
The //read weights// vector $$\mathbf{w}_r$$, is outputted by the read head. These are multiplied with the memory locations to give the //read vector//s.
!!__Writting__
A set of vectors with elements in the range $$(0,1)$$ is outputted by the write head.
* An attention write weight vector, $$\mathbf{w}_w$$
* An erase vector $$\mathbf{e}$$
* An add vector $$\mathbf{a}$$
!!__Addressing mechanism__
{{NTM addressing mechanism}}
See [[here|http://distill.pub/2016/augmented-rnns/]] for interactive version. This diagram is missing a few variables used in the NTM defined on the [[paper|https://arxiv.org/pdf/1410.5401v2.pdf]]. See below for fuller diagram.
[img[NTM_addressing_mechanism_diagram.png]]
Two combined addressing mechanisms:
* "[[content-based addressing|Content-addressable memory]],” focuses attention on locations based on the similarity between their current values and values emitted by the controller.
* "location-based addressing". In certain tasks the content of a variable is arbitrary, but the variable still needs a recognisable name or address. Loops are an example of where we need this.
<small>Content-based addressing is strictly more general than location-based addressing
as the content of a memory location could include location information inside it. In our ex-
periments however, providing location-based addressing as a primitive operation proved
essential for some forms of generalisation, so we employ both mechanisms concurrently.</small>
https://www.wikiwand.com/en/Neurodegeneration. Mostly used specifically to refer to neural loss or damage. More subtle mind disorders that need not show neurodegeneration are known as [[Mental disorder]]
* [[Dementia]]
* [[Alzheimer's disease]]
* Mild cognitive impairement
__Age-related cognitive impairement__
Initial memory deficits and effects before even Mild Cognitive Impairement diagnosis: [[A specific amyloid-bold beta protein assembly in the brain impairs memory|http://www.nature.com/nature/journal/v440/n7082/abs/nature04533.html]]
[[Computing system|Computer]]s that imitate the working of [[Neuronal network]]s, at hardware and/or software level. A basic model is the [[Spiking neural network]]. One advantage is that they tend to be more energy and resource-efficient.
https://www.wikiwand.com/en/Neuromorphic_engineering
Numenta
IBM TrueNorth.
!!!__[[Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing|http://arxiv.org/abs/1603.08270]]__
This is direct evidence that an “integrate-and-spike” mechanism has the similar computational capability as the more proven ANNs. The IBM paper however highlighted one major weakness of SNN. That is, training of the TrueNorth system required simulation of back-propagation using another conventional GPU:
Training was performed offline on conventional GPUs, using a library of custom training layers built upon functions from the MatConvNet toolbox. Network specication and training complexity using these layers is on par with standard deep learning.
See more interesting stuff here: [[Microglia: A Biologically Plausible Basis for Back-Propagation|http://blog.alluviate.com/?p=123]]
There however has been no biological evidence of a structural mechanism of “back-propagation” in biological brains. Yoshua Bengio published a paper in 2015 (see: http://arxiv.org/abs/1502.04156 ) “Towards Biologically Plausible Deep Learning”. The investigation attempts to explain a mechanism for back-propagation exists in Spike-Timing-Dependent Plasticity (STDP) of biological neurons.
It is however questionable whether neurons are able to learn by themselves without the need of an external feedback pathway that spans multiple layers.
There is however an alternative mechanism that recently has been discovered that may be a more convincing argument that is based on a structure that is independent of the brain’s neurons. There is a large class of cells in the Brain called Microglia ( see: https://www.technologyreview.com/s/601137/the-rogue-immune-cells-that-wreck-the-brain ) that are responsible for regulating the neurons and their connectivity.
In summary, biological brains have a regulatory mechanism in the form of microglia that are highly dynamic in regulating synapse connectivity and pruning neural growth. The activity is most pronounced during sleep. SNNs have been shown to have inference capabilities equivalent to Convolution Networks. SNNs however have not shown to effectively learn on their own without a ‘back-propagation’ mechanism. This mechanism is most plausibly provided by the microglia.
[[Energy-efficient neural network chips approach human recognition capabilities|http://www.pnas.org/content/113/41/11387.short]]
* Myelin acts as an insulator.
[[Neuron action potential]] spike
!!__Types of neurons__
!!!__According to morphology__
Neurons in the [[Cortex]] can be classified as belonging to two types:
* [[Pyramidal neuron]]s -- excitatory.
** Have an ''apical dentrite'' (from the apex) which shoots upwards to the surface of the cortex. It branches little until it reaches the cortex, where it branches a lot (cortical tuft).
** Many branching dentrites from the base of the neuron, which only connect to the local region
** An axon that most often goes down into the white matter, but sometimes it has a lateral branch that reaches to another part of the cortex.
** The synapses it forms (from axon) are excitatory (asymmetric).
** The synapses it receives are mostly inhibtory when in its body or branches, but excitatory at the far ends of the dentrites.
** As most excitatory neurons, they have a many [[Neural spine]]s
* [[Stellate neuron]]
** Axons and dendrites reach only local regions of the cortex where they are located.
** As for pyramidal neurons. The synapses it receives are mostly inhibtory when in its body or branches, but excitatory at the far ends of the dentrites.
** Main types:
*** Spiny stellate neurons. Have neural spines and are excitatory.
*** Smooth stellate neurons. Don't have neural spines and are inhibitory.
*** Sparsely spiny stellate neurons. Have only sparse spines, and can be excitatory or inhibitory.
*** A particular type (sometimes considered separate) is the ''Martinotti cell'', situated at the depth of the cortex, and whose axon grows toward the cortical surface, extending few collaterals on its way up, but branching out profusely under the cortical surface, where it makes synapses on the apical dentricit tufts of the pyramidal cells.
*** [[Chandelier cells|https://www.wikiwand.com/en/Chandelier_cell]]. Chandelier neurons synapse exclusively to the axon initial segment of pyramidal neurons, near the site where action potential is generated.
*** Basket cells
One can of course, just divide them into
* [[Inhibitory neuron]]s
* [[Exitatory neuron]]s
!!__Synapse__
[[Neurotransmitter]]
!!!__Symmetric or inhibitory synapses__
!!!__Asymmetric or excitatory synapses__
[[Neuron action potential description|https://www.youtube.com/watch?v=h2H6POZowiU]]
[[Action potential]]
__Equivalent electrical circuit!__
* [[Huxley-Hodgkin equations]]
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
[[Network]] of [[Neuron]]s
[[Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits|http://www.ncbi.nlm.nih.gov/pubmed/22991468]]
[[Brain connectivity toolbox|https://sites.google.com/site/bctnet/Home]]
[[Video|https://www.youtube.com/watch?v=cjj9ihYJkOQ#t=1m30s]]
One important thing to model is the output (set of parallel spiking trains)that population of neurons produces upon receiving a certain input (set of parallel spiking trains).
For a single neuron, we can define the asynchronous ''synaptic transmission curve'' (aka ''synaptic response curve''), which is the instantaneous firing rate as a function of time, when the neuron receives a single isolated spike. If integrated it gives the ''asynchronous gain'' (ASG), the total number of output spikes per input spike.
------------
[[Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding|http://sci-hub.bz/10.1038/nrn2886]]
!!![[Neural coding]]
Stimulus or task-related activity is said to be
‘rate coded’ when it can be decoded using only the
firing rates of neurons in an ensemble. On the other
hand, when stimulus or task-related activity can be
decoded using synchrony (BOX 2), it is referred to as a
time (or ‘synchrony’) code
------------
!!__[[Signal transmission and processing by neuronal networks]]__
''Cross-correlation'', post-synaptic potentials..
Neural chains
Synchronous transmission. ''Synchronous gain''
!!__[[Membrane potential and the synaptic response curve]]__
Firing rates of neurons from noise.
Effect of ''postsynaptic potential''s in the firing rate, thus giving a way to compute the synaptic transmission curve ,,(which we can experimentally find with cross-correlations),,.
!!__Neuronal network models__
* [[Hopfield network]], a kind of [[Boolean network]], with thresholded activation. The main model has symmetric synaptic strengths (i.e. same strength from neuron i to j as from j to i).
* [[Spiking neural network]]
* Standard [[Artificial neural network]]s.
** [[Perceptron]]. Multilayer perceptron (now much more developed in [[Deep learning]])
The study of neuronal networks in the [[Cortex]] is known as [[Corticonics]].
[[Neural Networks - intro|https://www.youtube.com/watch?v=aU2pyB-49m8&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp]] -- [[LC circuit]]s -- [[Linear system]]s
-----------------
See [[Neural system]] for well studied neuronal networks
Traditionally studied via staining methods:
* Nissl stains. Mostly nucleus visible.
* Golgi impregnation techniques. Only about 1% of neurons impregnated. Makes most of the cell visible.
* Weigert stain for myelin.
* Reduced-silver method.
* Staining of degenerate elements.
* Retrogade staining. One can stain all neurons whose axons terminate on a given region, using materials taken at the dendrites and then transported to the cell body.
* Anterograde staining. Find the regions which the axons of neurons in a certain zone reach, using materials absorved by the body and transported to the axon terminals.
* Intreacellular dye injection. Shows more of the cell than Golgi impregnation techniques.
* Histochemical staining. Identify cells by particular chemicals they contain.
* Metabolic staining. Staining that depends on the [[Metabolism]] of the cells.
The study of the [[Brain]], and the [[Nervous system]]. (//Brain science// included)
https://www.youtube.com/watch?v=4y43qwS8fl4
[[The brain dictionary|https://www.youtube.com/watch?v=k61nJkx5aDQ]]
[[Organizing conceptual knowledge in humans with a gridlike code|http://science.sciencemag.org/content/352/6292/1464.full?ijkey=sXaWNaNjkIcik&keytype=ref&siteid=sci]]
[[Cognitive science]]
[[How brains see|https://www.youtube.com/watch?v=0oNHukxz5rI]]
[[Neuronal Avalanches in Neocortical Circuits|http://www.jneurosci.org/content/23/35/11167.short]]
See [[Neuronal network]], and [[Neuromorphic computing]].
[[Karl Friston talk|https://www.youtube.com/watch?v=zWFfZHqOnvM]]
!__System levels__
!!!__1. [[Neuron]]__
!!!__2. [[Neural system]]__
-- [[Neuronal network]]s
-- in the [[Cortex]]: [[Corticonics]]
!!!__3. [[Brain]]__
--------------------
!__Areas of study__
!!__[[Neuroanatomy]]__
!!__Neural codes__
//Understanding the way [[Information]] is [[encoded|Coding theory]] in neurons, and their firing//
Firing rate <> Amplitude of estimulus.
Firing pattern also encodes information.
[[Grid cell]]s in the [[Entorhinal cortex]]
Prediction error
Temporal coding
Binding through coherence. [[Brain oscillation]]s
!!__[[Computational neuroscience]]__
From brain activity
Circuits <> Computations <> Behaviour
In trying to understand machinery we often assume as if it was constructed, but it evolved
!!!__Theoretical neuroscience__
[[Theoretical Neuroscience book|http://www.gatsby.ucl.ac.uk/~dayan/book/index.html]]
!!__[[Cognitive neuroscience]]__
//How neurons and other systems in the brain give rise to [[Cognition]]//
!!!__[[Human learning]]__
__[[Hebbian theory]]__
"Cells that fire together, wire together."
!!!__[[Consciousness]]__
-----------------
[[Mu-ming Poo (UC Berkeley, CAS Shanghai) Part 1: The Cellular Basis of Learning and Memory|https://www.youtube.com/watch?v=ATR0os9w2jY&index=27&list=PL4C48902B3A4ED0F4]]
[[Carl Sagan on the brain|https://www.youtube.com/watch?v=HvRKdG-QM6c#t=9m32s]]
''Kimura's neutral theory of evolution''. He proposed that (at least for molecular evolution) most mutations are neutral, meaning that they don't lead to a change in fitness.
Because different phenotypes often do have different fitness, the way this comes about is because of the large redundancy in GP maps.
When the redundancy is large enough for some phenotype, or there are genetic correlations, so that nearby genotypes (in mutation network) tend to map to the same phenotype, we find large ''neutral spaces''. If Kimura is right, most mutations occurs within these spaces, and are governed by genetic drift, random changes in allele frequencies in finite populations, not governed by natural selection.
''Genotype space'', links represent single-point mutations. It has a hypercube network structure.
''Neutral spaces'' or neutral sets are those sets of genotypes that produce the same phenotype. These are important in the ideas of the [[Arrival of the frequent]] above which relies on the many-to-one nature of the GPM. It seems to also be related to the [[Survival of the flattest]].
Evolution explores neutral space, being exposed to larger number of neighbouring possibilities, before switching to a different, better, phenotype
[[Wiki article|https://en.wikipedia.org/wiki/Neutral_theory_of_molecular_evolution]]
See [[Monomorphic limit (Wright-Fisher model)]]
[[Presentation about genetic drift|http://www.slideshare.net/dkavuru/224-powerpoint]]
[[Founder effect|https://en.wikipedia.org/wiki/Founder_effect]] is the loss of genetic variation that occurs when a new population is established by a very small number of individuals from a larger population.
[[Neutral evolution of mutational robustness|http://www.pnas.org/content/96/17/9716.full.pdf]]
https://en.wikipedia.org/wiki/Molecular_clock
[[The Molecular Clock Hypothesis: Biochemical Evolution, Genetic Differentiation and Systematics|http://www.annualreviews.org/doi/abs/10.1146/annurev.es.13.110182.001035]]
[[Smoothness within ruggedness: The role of neutrality in adaptation|http://www.pnas.org/content/93/1/397.full.pdf?sid=3796ca29-c804-44e7-a358-7a96cdafff5c]]
[[Aicd]] + [[Base]] = [[Water]] + [[Salt]]
[ext[https://www.wikiwand.com/en/Neutralization_(chemistry)]]
https://www.wikiwand.com/en/Neutrophil
!!![[Batch normalization]]
[[ Deep Networks with Stochastic Depth|http://arxiv.org/abs/1603.09382v1]] [[Stochastic Depth Networks will Become the New Normal|http://deliprao.com/archives/134]]
[[ Highway Networks|http://arxiv.org/abs/1505.00387]]
!!![[Dropout]]
https://en.m.wikipedia.org/wiki/Modular_neural_network STN?
DCGAN http://arxiv.org/abs/1511.06434
DRAW http://arxiv.org/abs/1502.04623
Soft/hard attention https://www.google.es/url?sa=t&source=web&rct=j&url=http://arxiv.org/pdf/1502.03044&ved=0ahUKEwi4yof-jPjLAhVC5xoKHcTjDM4QFgggMAA&usg=AFQjCNEs1Yw8fZF9oaqo73cwbHJqKwQHTw
CharCNN https://www.google.es/url?sa=t&source=web&rct=j&url=http://arxiv.org/pdf/1508.06615&ved=0ahUKEwjZqaXnk_jLAhWCsxQKHZsuApUQFgglMAM&usg=AFQjCNHk8JQpI98eUtyiluv7d2G9aWRtyA
NeuralStyle https://github.com/jcjohnson/neural-style
"Take a look at @karpathy's Tweet: https://twitter.com/karpathy/status/709465955223543808?s=09"
http://arxiv.org/abs/1604.00790 bidirectional LSTM
http://www.computervisionblog.com/2016/06/deep-learning-trends-iclr-2016.html
Adversarial networks
Neural Turing machines, neural programmers-interpreters
http://www.kdnuggets.com/2016/09/9-key-deep-learning-papers-explained.html
---------------------
A couple of cool recent neural network developments!
* Lip reading
* Neural enhance! Super-resolution of images (like in movies but real ;) )
LipNet. Lip reading NN: http://prostheticknowledge.tumblr.com/post/152735696866/lipnet-deep-learning-research-from-the-university
image super-resolution using deep convolutional networks! try here: http://waifu2x.udp.jp/
NeuralEnhance lets you apply 4x super-resolution to your photos CSI-style in only 340 lines of code!
https://github.com/alexjc/neural-enhance
https://twitter.com/karpathy
https://twitter.com/alexjc
https://twitter.com/NandoDF
A method to find stationary points of a function. Note that it doesn't necessarily minimize.. It's more computationally intensive than [[Gradient descent]] per step, but it tends to converge faster!
It is based on a local ''quadratic approximation'' to the function using [[Multivariate Taylor expansion]]:
$$f(x+\delta x) \approx f(x)+\nabla^T f(x) \delta x + \frac{1}{2} \delta x^T H(x) \delta x$$
If we minimize this by taking the [[Gradient]] w.r.t $$\delta x$$ and setting it to zero:
$$\nabla^T f(x) + H(x) \delta x = 0$$
$$\delta x=-H(x)^{-1}\nabla f(x)$$
See section 7 [[here|http://cs229.stanford.edu/notes/cs229-notes1.pdf]], [[video|https://www.youtube.com/watch?v=nLKOQfKLUks&index=4&list=PLA89DCFA6ADACE599#t=3m30s]] -- [[Hugo's video|https://www.youtube.com/watch?v=Bver7Ttgb9M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=17#t=15m50s]]
(//Offline algorithm//, you process all the data at each step)
Taylor expand to second order (in multi-variate way) and minimize that (i.e. take derivative (gradient)) and set to 0. [[It performs upper bound minimization|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=26m33s]].
Newton CG (''conjugate gradient'') algorithms.
Expensive thing is computing Hessian, and inverting it. It only works if the function is locally [[convex|Convex function]], so that Hessian is invertible. Approximate methods like BFGS, LBFGS.
Trust regions..
Line search
[[It is very similar to standard gradient descent|https://www.youtube.com/watch?v=Bver7Ttgb9M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=17#t=20m20s]], but were the learning rate adapts to the curvature.
//Possible problems//
Quadratic approximation may be inaccurate
Hessian and its inverse may be expensive --> [[Quasi-Newton method]]
!!__[[Quasi-Newton method]]__
http://www.nature.com/subjects/next-generation-sequencing
[[Nanopore sequencing|https://www.youtube.com/watch?v=CE4dW64x3Ts]]
The [[Nitrogen]] ion NO,,3,,^^-^^, or a compound containing that ion.
[img width=400 [https://cdn.reefs.com/blog/wp-content/uploads/2015/02/Nitrate-ion.png]]
Refers to the ''nitro'' [[Functional group]], NO,,2,,, or a compound that has the group.
A [[Chemical element]] composed of nitrogen atoms. These have 7 proton in the nucleus.
The hydrogen atom tends to form three bond, as it has 5 electrons in its outer shell (see [[Octet rule]]). See, for instance, [[Ammonia]]
https://www.wikiwand.com/en/Nobility
Group 0 in the [[Periodic table]]
*they are non-metals
*they are very unreactive gases
*they are colourless
*they exist as single atoms (they are monatomic)
The uses of the noble gases are usually linked to their inertness, or to their tendency to give off light when an electric current is passed through them.
http://www.bbc.co.uk/education/guides/zb3j6sg/revision/3
//Resources//
!!!<mark>[[Lecture series by Balakrishnan!|https://www.youtube.com/playlist?list=PLbMVogVj5nJQqNx0ElSk3Ip04Ofg7B22W]]</mark>
[[Notes on Nonequilibrium StatPhys MT2015 Oxford (mostly stochastic processes)|https://files.acrobat.com/a/preview/c7779092-2b46-4bc8-a927-cd5c8c52a279]]
[[Statistical physics -- a second course|http://www.uio.no/studier/emner/matnat/fys/FYS4130/v14/documents/kompendium.pdf]]
[[A Kinetic View of Statistical Physics, P.L. Krapivsky, S. Redner, E. Ben-Naim|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/%5BKrapivsky_P.L.,_Redner_S.,_Ben-Naim_E.%5D_A_Kinetic_approach_to_statistical_physics.pdf]]
[[Stochastic Processes in Physics and Chemistry, N. van Kampen|file:///home/guillefix/Dropbox/COSMOS/Physics/David%20Tong%20Lectures/Kinetic%20Theory/Extra%20material/(North-Holland%20personal%20library)%20N.G.%20Van%20Kampen-Stochastic%20Processes%20in%20Physics%20and%20Chemistry-Elsevier%20(2007)%20(1).djvu]]
[[Handbook of stochastic methods - Gardiner |file:///home/guillefix/Dropbox/NewForCosmos/AAA%20MUCH%20NEWER/%5BCrispin_Gardiner%5D_Handbook_of_stochastic_methods(Book4You).djvu]]
-------
''Non-equilibrium Statistical Physics'' is the branch of [[Statistical physics]] that deals with systems out of equilibrium, so that averages can change in time (<mark>Actually not quite: see [[Thermodynamic equilibrium]]</mark>). This is much harder to do in full generality, as systems offer much more diversity out of equilibrium, as may be expected. As said in that page, one often has three approaches:
*For a small system coupled to a large chaotic system, one has a [[stochastic process|Stochastic process]], which describes the evolution under the random influence of the large chaotic system.
*For a large system which is only slightly out of equilibrium, so that relevant macroscopic averages analogous to those used in thermodynamics can still be defined, one can describe the system using [[Non-equilibrium thermodynamics]]
*For a large system that is considerably out of equilibrium, one has to use the tools of [[Kinetic theory]] to describe it (or newer approaches, see below). However, if the system is //very// far from equilibrium, even these may be inappropriate, and finding an appropriate description may be extremely hard. An example of this are systems with strong [[Turbulence]]. Our only approaches to understand these systems are often [[phenomenological]].
-------
Related things (also in the course/exam):
* Pattern formation.
* Synchronization: the [[Kuramoto model]]
-----------------
!!!__Other aspects and approaches__, some of which have lead to the recent understanding of systems very (even arbitrarily) far from equilibrium). In approaximate chronological order:
<b>See overview [[in this lecture|https://www.youtube.com/watch?v=OnZIaNgU7o8&index=8&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l#t=5m0s]]</b>
''Large deviation theory''.
Einstein formula (1908)
Application of large deviation theory to dynamics: Onsager (1931)
[ext[Projector operator method|http://www4.ncsu.edu/~franzen/public_html/CH437/lec8/pdf/projection_1.pdf]]
[[linear response theory|http://www.damtp.cam.ac.uk/user/tong/kintheory/four.pdf]]
[[Nonlinear response theory|http://link.springer.com/article/10.1007%2FBF02846371]] [[Nonlinear Response Theory|http://www.hpcoders.com.au/docs/thesis/node34.html]]
[ext[Nonlinear projection operator method|http://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/contents/pdf/1667-15.pdf]]
[[Zwanzig projection operator|https://en.wikipedia.org/wiki/Zwanzig_projection_operator]]
[[Nonequilibrium Equality for Free Energy Differences|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.78.2690]] Jarzynski 1997. Discussed on lecture 3 of Shin-ichi
[[Fluctuation theorem|https://en.wikipedia.org/wiki/Fluctuation_theorem]]
[[Fluctuation Theorems|https://arxiv.org/abs/0709.3888]] ''Fluctuation theorems'', or fluctuation relations, which have been developed over the past 15 years, have resulted in fundamental breakthroughs in our understanding of how irreversibility emerges from reversible dynamics, and have provided new statistical mechanical relationships for free energy changes. They describe the statistical fluctuations in time-averaged properties of many-particle systems such as fluids driven to nonequilibrium states, and provide some of the very few analytical expressions that describe nonequilibrium states. Quantitative predictions on fluctuations in small systems that are monitored over short periods can also be made, and therefore the fluctuation theorems allow thermodynamic concepts to be extended to apply to finite systems. For this reason, fluctuation theorems are anticipated to play an important role in the design of nanotechnological devices and in understanding biological processes. These theorems, their physical significance and results for experimental and model systems are discussed.
Shin-ichi calls them identities, and explains them on Lecture 4
[[Stochastic thermodynamics|http://iopscience.iop.org/article/10.1088/1367-2630/18/2/020401/meta]] [[Focus on Stochastic Thermodynamics|http://iopscience.iop.org/1367-2630/focus/Focus%20on%20Stochastic%20Thermodynamics]]
''Stochastic thermodynamics'' has emerged as a framework for describing small driven systems using thermodynamic notions on the level of individual fluctuating trajectories. Topics on the article:
*Stochastic energetics and entropy production along trajectories.
*Non-equilibrium work and fluctuation-(dissipation)-relations.
*Efficiency and efficiency at maximum power of heat engines, thermoelectrics and isothermal machines.
*Thermodynamics of molecular motors.
*Dissipation, irreversibility and information.
*Thermodynamics of molecular and cellular information processing.
[[Stochastic thermodynamics: A brief introduction|http://itf.fys.kuleuven.be/~fpspXIII/material/VanDenBroeck_FPSPXIII.pdf]]
[img[http://cms.iopscience.iop.org/alfresco/d/d/workspace/SpacesStore/eaea44bc-496a-11e4-ba5c-29411a5deefe/stochastic_thermodynamics_edfig.gif?guest=true]]
,,Figure. Artistic view of a driven molecular motor-cargo complex with its trajectories. Image by Daniel Schmidt, University Stuttgart.,,
See also new advancements mentioned in the article on the new theory on the origin of life (linked in [[Abiogenesis]])
[[Shin-ichi Sasa publications|https://scholar.google.co.uk/citations?hl=en&user=ywOAAjkAAAAJ&view_op=list_works&sortby=pubdate]]
[[On Various Questions in Nonequilibrium Statistical Mechanics Relating to Swarms and Fluid Flow|http://www.hpcoders.com.au/docs/thesis/thesis.html]]
<mark>Read Ilya's book on thermodynamics</mark>, where he covers the non-equilibrium part. Also his book on [[Self-organization]], and other books on non-equilibrium statistical physics. See if then I can get a more clear derivation of the Allen-Cahn and Cahn-Hilliard equations in [[Phase transition]], describing general forms of diffusion and phase field evolution.
See also [[Complex systems]], which are often analysed using ideas from nonequilibrium statistical physics.
Fluctuations in nonequilibrium statistical mechanics. One project
is about rare event simulations, non-Markovian extensions of large
deviation theory, and zero-range processes (Harris, Touchette). A
second one is about random packing optimization problems, which have
very different solutions depending on the shape of the objects
(Baule).
http://www.research.ed.ac.uk/portal/en/persons/martin-evans(2f8bc4da-9178-4a62-ad41-059a612018c6).html
<mark style="background-color:blue;"><b>[[Stochastic Thermodynamics in Biology|http://agenda.albanova.se/conferenceDisplay.py?confId=4462]]</b></mark>
[[Thermodynamic Costs in Implementing Optimal Estimators|http://agenda.albanova.se/contributionDisplay.py?contribId=255&confId=4462]] -- [[Kalman filter|https://en.wikipedia.org/wiki/Kalman_filter]]
[[Dynamics of protein synthesis: transcription, translation, and mRNA degradation|http://agenda.albanova.se/contributionDisplay.py?contribId=251&confId=4462]]
[[Simple models of evolution with selection and genealogies|http://agenda.albanova.se/contributionDisplay.py?contribId=270&confId=4462]]
[[Universal constraints for biomolecular systems|http://agenda.albanova.se/contributionDisplay.py?contribId=262&confId=4462]]
[[Stochastic Thermodynamics of Chemical Networks|http://agenda.albanova.se/contributionDisplay.py?contribId=267&confId=4462]]
[[Stochastic approaches in systems biology.|http://www.ncbi.nlm.nih.gov/pubmed/20836037]] See [[Systems biology]]
[[Stochastic thermodynamics of Langevin systems under time-delayed feedback control: Second-law-like inequalities|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.042114]]
[[Stochastic thermodynamics, fluctuation theorems and molecular machines|http://iopscience.iop.org/article/10.1088/0034-4885/75/12/126001/meta]]
<mark><b>Video lecture!</b></mark> [[Udo Seifert - Stochastic thermodynamics 1|https://www.youtube.com/watch?v=YKnP0SJTZfU]]
[[lecture series (school on thermalization)|https://www.youtube.com/playlist?list=PL04QVxpjcnjhfB35Igp6sijgxjXmLuO9e]]
[[Portrait of Udo Seifert|https://www.youtube.com/watch?v=AIjdqL5kmD0]]
[[More literature on stochastic thermodynamics|http://www.theo2.physik.uni-stuttgart.de/lehre/hauptseminar/SS_14/HS_StochTherm_ss15.pdf]]
[[Martin Z. Bazant|http://www.mit.edu/~bazant/]]
[[Chemical Kinetics in Nonequilibrium Thermodynamics - Martin Z. Bazant|https://www.youtube.com/watch?v=Vc63enulmYs]]
[[Prof. Dr. Udo Seifert|http://www.theo2.physik.uni-stuttgart.de/mitarbeiter/udoseifert.en.html]]
[[Introduction to stochastic thermodynamics: (prof. dr. M. Esposito) Part1|https://www.youtube.com/watch?v=FDaM-M0G9IM]]
[[The stochastic thermodynamics of a rotating Brownian particle in a gradient flow|http://www.nature.com/articles/srep12266]]:
See stuff in here: [[MMathPhys Condensed Matter and Astrophysics/Plasma Physics/Physics of Continuous Media Strands Short Syllabi|http://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/MMathPhys/cmstrand.html]]
1. Dynamics of Stochastic Processes (12 lectures)
• Langevin equation and mean-squared displacement versus time, fundamentals of Molecular Dynamics and Stochastic Rotation Dynamics simulation methods
• Probabilistic description of stochastic process, Fokker-Planck equation
• Kramers rate theory, escape probability and first-passage time
• Master equation, equilibrium and detailed-balance, fundamentals of Monte Carlo simulation method, chemical reactions, one-step processes (traffic models), fundamentals of Lattice Boltzmann simulation method
• Diffusion-reaction processes and pattern formation
• Heterogeneous catalysis and the Michaelis-Menten rule in enzymatic reactions
• Rectification of stochastic motion and Brownian ratchets
2. Fluctuations and Response (4 lectures)
• Equilibrium fluctuations, correlation functions
• Density fluctuations, hydrodynamic fluctuations and the long-time tail
• Linear response theory, response function, causality and Kramers-Kronig relations
• Fluctuation-dissipation theorem near equilibrium
• Small-system (stochastic) thermodynamics, Jarzynskii inequality
• Generalised fluctuation-dissipation theorem in nonequilibrium systems
https://scholar.google.co.uk/citations?hl=en&user=1V6ZcgMAAAAJ&view_op=list_works&sortby=pubdate
[[Viewpoint: Debut of a hot “fantastic voyager”|https://physics.aps.org/articles/v3/108]]
[[Open-System Nonequilibrium Steady State: Statistical Thermodynamics, Fluctuations, and Chemical Oscillations|http://pubs.acs.org/doi/abs/10.1021/jp061858z]]
[[Information in Biological Systems and the Fluctuation Theorem |https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=20&ved=0ahUKEwifmYWol8jMAhUFBsAKHZmvCTY4ChAWCEkwCQ&url=http%3A%2F%2Fwww.mdpi.com%2F1099-4300%2F16%2F4%2F1931%2Fpdf&usg=AFQjCNGMeiDdCzApHxfkwW1U_ognSBRz1Q&sig2=vB4kXTrHMRbUF8DXUVlooQ&bvm=bv.121421273,d.d2s&cad=rja]]
[[Stochastic thermodynamics with information reservoirs|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.042150]]
[[Non-equilibrium statistical physics (long lecture series)|https://www.youtube.com/playlist?list=PL04QVxpjcnjjoN7xfc7Vy63uUSkDlOYiU]]
[[Introduction to macroscopic fluctuation theory by Giovanni Jona Lasinio|https://www.youtube.com/watch?v=JJR2C-AlZmg&list=PL04QVxpjcnjjVcqqdkDXybf2g6mfrV0Yv&index=4]]
[[Foundations of Synergetics II: Chaos and Noise|https://books.google.co.uk/books?hl=en&lr=&id=t0OqCAAAQBAJ&oi=fnd&pg=PA2&ots=vdO5l7J-o1&sig=jR7Ri3cRDkRAcWt3GqIddFhfqgE#v=onepage&q&f=false]]
See [[Biophysics]]
[[Non-equilibrium statistical mechanics: from a paradigmatic model to biological transport|http://iopscience.iop.org/article/10.1088/0034-4885/74/11/116601/meta]]
Euclidean geometry where the [[Parallel postulate]] is modified. It corresponds to Riemannian manifolds with non-zero [[Curvature]]
[[Elliptic geometry]]
[[Hyperbolic geometry]]
Riemannian geomtry
[[Differential geometry]]
See pages 88 and forth in [[GEB|Godel, Escher, Bach]]
A [[Molecule]] without a permanent [[Electric dipole]], the opposite of a [[Polar molecule]]. It can refer to a [[Moiety]] too
A type of [[Percolation]] process that is non-self-averaging, (often? ,,def. of self-averaging?,,) in the sense that the relative variance of the size of the largest component doesn't vanish in the thermodynamic limit.
* Some types of [[k-vertex rule percolation process]]es [[Continuous Percolation with Discontinuities|http://journals.aps.org/prx/abstract/10.1103/PhysRevX.2.031009]]
** Fractional percolation. Its rule implements a kind of cluster size homophily where clusters of similar sizes are more likely to be connected together. See [[here|http://www.nature.com/articles/ncomms3222]], [[Crackling noise in fractional percolation|https://www.researchgate.net/publication/252325326_Crackling_noise_in_fractional_percolation]]
See also: [[Achlioptas processes are not always self-averaging|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.86.011129]] -- [[Phase transitions in supercritical explosive percolation|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.87.052130]] -- [[Unstable supercritical discontinuous percolation transitions|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.88.042152]]
!!!__Discontinuity in k-vertex rule percolation processes__
O. Riordan and L. Warnke [[showed|http://projecteuclid.org/euclid.aoap/1344614200]] that [[k-vertex rule percolation process]] were continuous, however, it is equally true that certain percolation processes based on picking a fixed number of random vertices are discontinuous. A paradox resolved in [[this paper|http://journals.aps.org/prx/abstract/10.1103/PhysRevX.2.031009]], where they show that some processes, while continuous at exactly the transition point, still exhibit infinitely many discontinuous jumps in an arbitrary vicinity of the transition point: a ''Devil’s staircase''.
This staircase is in fact stochastic, as the jump points and sizes are stochastic random variables. This stochasticity is present even in the thermodynamic limit, and that is what gives rise to the non-self-averaging property.
[img[http://i.imgur.com/s4haYQr.png]]
''Continuous dynamical systems'' are systems of 1st order O.D.Es. Linear dynamical systems (O.D.E.s linear) are easy to analyze, and can be analyzed by looking at the eigenvalues of the Jacobian.
''Nonlinear continuous dynamical systems'' are those where the O.D.Es are nonlinear. They offer much richer behavior and thus require more variety in analysis techniques. Locally, however, they can be linearized and analyzed by the same linear Jacobian techniques
//Autonomous// systems are those that don't have explicit time dependence.
!!!__Phase portrait features and attractors__
''Attractors'' are regions of phase space to which points converge if they begin within a given //basin of attraction//
//Features//:
* Equilibrium points points
* Trapping regions
Only in 2+ D:
* Nullclines, lines where the derivative of one of the variable becomes zero.
* Limit cycles
* Isoclines, lines of equal inclination (equal slope of tangent to trajectory).
Only in 3+ D:
* Strange (chaotic attractors) Attractors. [[Chaos theory]]
!!!__Equilibrium points__
A.k.a. fixed points.
They can be classified by their ''stability'' and other qualitative features. See [[Classification of equilibria in 2D|http://www.math.psu.edu/tseng/class/Math251/Phase_portrait_reference_card.pdf]].
The classification is done by computing the ''Jacobian matrix'' at the fixed point, and looking at the eigenvalues and eigenvectors to see how the flow behaves localy:
[img[fixed_points_classification1.png]]
[img[fixed_points_classification2.png]]
[[More on stability|http://planning.cs.uiuc.edu/node800.html]]
__Poincare-Bendixson theorem__, trapping regions. Useful to prove existence of limit cycles in 2D, also makes chaos impossible in 2D. Need at least 3D!.
!!!__Classifications__
Conservative systems:
* Phase space volume conserved (Lioville's theorem)
* There is an energy function (that has to be independent of time, I think) that doesn't change with time.
Non-conservative systems:
* (Strong) Lyapunov function (also non explicitely dependent on time, I think) that is monotone decreasing or increasing with time in some region, except at an equilibrium point. This region is called the //region of asymptotic stability// for the equilibrium point. Can generalize so that it's only required to be monotone changing in a region enclosing a //trapping region//. Can also have weak Lyapunov functions which are not required to be monotone (i.e. $$\dot{V}<0$$) but only $$\dot{V}\leq 0$$.
!!__Bifurcation theory__
__1-dimensional flows__
__Bifurcations__
* ''Saddle-node bifurcation'' (a.k.a fold), stable and unstable nodes collide and anihilate each other.
* ''Transcritical bifurcation'': stable and unstable node collide and interchange stability
* ''Pitchfork bifurcation'': stable (unstable) node becomes unstable (stable) while two stable (unstable) nodes appear, for a supercritical (subcritical).
** supercritical
** subcritical
__2-dimensional flows__
* Same as in 1D
* ''Hopf bifurcation''. [[Hopf Bifurcations in 2D|http://www.cds.caltech.edu/archive/help/uploads/wiki/files/179/lecture8As.pdf]]
* Saddle-node bifurcation of limit-cycles
* <b>Global bifurcations</b>:
**Homoclynic and heteroclynic bifurcations.
__3-dimensional flows__
* Same as in 2D
* Cycle bifurcations
**''Fold bifurcation'' (saddle-node for cycles)
**''Flip bifurcation'' (for supercritical: stable cycle becomes unstable and gives rise to a cycle of twice the period, often a Moebius strip, so it requires 3D)
** ''[[Neimark bifurcation|http://www.scholarpedia.org/article/Neimark-Sacker_bifurcation]]'', or secondary Hopf bifurcation: a stable limit cycle becomes unstable and a limit cycle around the limit cycle forms: i.e. a trajectory that lives in a torus.
* <b>Global bifurcations</b> (play important role in route to chaos). See pages 259+ in Thompson
** Intermittency and mode-locking. ''Intermittency catastrophe'' Intermittent between two connected attracting regions in an attractor, that become separate attractors at the catastrophic (discontinuous) bifurcation. Just before bifurcation there are still jumps between the still connected attracting regions that technically still become belong to the same attractor. These jumps become less and less frequent. If one of the attracting regions becomes more and more transient (see example of drift ring and saddle-node in Thompson p 259) then we only have one attractor after the bifurcation. This kind of catastrophe is observed in [[maps|Nonlinear maps]]. However, it is also possible in flows and is then called a ''Omega explosion''. See Fig. 13.3 below.
** ''Hysteresis'' and ''blue sky catastrophe''. Blue sky catastrophe refers to the global bifurcation in which a limit cycle disappears discontinuously (at a given control parameter value), when it collides with a saddle equilibrium point.
[img[Omega_explosion.png]]
* ''Bifurcations of chaotic attractors''. Routes to [[chaos|Chaos theory]]
__Other concepts__:
''Global bifurcations'', bifurcations that are not identified by a change localized close to a limit point or cycle. These occur when there is a qualitative change in the topology of invariant manifolds, or in the topology of basins. Global bifurcations can be accompanied, or even caused by local bifurcations.
''Poincare section'', snapshots of phase space of a dynamical system define a map, so that we can use the theory of [[nonlinear maps|Nonlinear maps]], to analyze, for example, chaotic attractors.
''Structural stability'' refers to when a certain qualitative feature (like a type of bifurcation) isn't changed by small perturbation of the equation, by which we mean, addition of small extra terms to the equation.
[[Catastrophe theory]] studies bifurcations and other qualitative phenomena as control parameters are varied.
One can also distinguish: discontinuous (or catastrophic) vs continuous bifurcations. See page 252 of Thompsons book. See also page 257 of that book; one distinguishes ''safe boundaries'', ''dangerous boundaries''.
[img[continuous_vs_discontinuous_bifurcations.png]]
[img[bifurcation_types.png]]
------
Examples:
[[Duffing oscillator]]
''Josephson junction'' <mark>Revise this</mark>
------
//Books//:
Strogatz
Thompson and Stewart. Nonlinear dynamics and chaos <mark>very good</mark>
------
http://www.scholarpedia.org/article/Canards
http://www.math.harvard.edu/library/sternberg/
[[Oxford notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3082/161/main_3.pdf]]
Discrete-time dynamical systems are sometimes called ''maps''. As usual, there are ''linear maps'', which cam be represented by a matrix (plus a constant vector, if the map is affine, instead of just linear). However, most interesting behaviour is observed in ''nonlinear maps'', in which the state at discrete time $$n+1$$ depends on the state at the previous time via a nonlinear function $$f$$:
$$x_{n+1} = f(x_n ; n)$$
where we allow discrete-time dependence of $$f$$. Autonomous maps, won't have such dependence.
-------
!!!__Poincare maps__
Cross-sections of the phase plane of a [[Continuous dynamical system]] that are nowhere tangential to a trajectory are called //Poincare sections//. Trajectories become points in the lower dimensional space of the cross-section, and the dynamical system becomes a discrete //map//, called the ''Poincare map''.
-------
!!__Features of maps__
The equivalent of equilibrium points in dynamical systems are ''fixed points''. A fixed point is one that is mapped to itself.
''Periodic cycles'' are closed orbits (like limit cycles, or orbits, in dynamical systems).
!!!__Stability__
The stability of a fixed a fixed point is determined by its ''multiplier'' (which is just the derivative of the function defining the map $$\lambda = \frac{\partial f}{\partial x}$$) evaluated at the fixed point. A point is stable if $$|\lambda| <1$$, unstable if $$|\lambda| >1$$, and neutrally stable if $$|\lambda| =1$$ (at which point a bifurcation occurs).
One can use the [[Jury test]] to find if the roots of a polynomial are inside the unit circle, which is useful for stability.
The stability of a periodic cycle can be found by multiplying the multiplier evaluated at each of the points in the cycle. These numbers are then called the //characteristic multipliers// or //Floquet exponents//.
!!!__Bifurcations in 1D maps__
* ''Fold bifurcations''. Bifurcations that occur when the multiplier $$\lambda =1$$. Can be:
** Saddle-node
** Transcritical
** Pitchfork
* ''Flip or period-doubling bifurcation''. Occur when the multiplier $$\lambda = -1$$
* ''Hopf bifurcation''. Occur when the multiplier $$\lambda = e^{i\theta}$$ (for a $$\theta \neq 0, \pi$$, I suppose).
One can also have bifurcations of periodic cycles in 2D maps, I think.
There are also ''global bifurcations'' in periodic maps, some of which are routes that lead to chaos. See [[Nonlinear dynamical systems]] and [[Chaos theory]].
!!!__2D maps__
Local linear stability analysis done by Jacobians, and multipliers are replaced by the Jacobian's eigenvalues which must now be less than one in magnitude for stability. For periodic cycles, one multiples the Jacobians.
Another very interesting feature of nonlinear maps, is that many of them exhibit [[chaos|Chaos theory]].
--------
!!__Examples__
!!!__Henon map__
!!!__Standard (or Chirikov) map__
!!!See more examples of chaotic maps in [[Chaos theory]]
Can analyze using [[Perturbation methods]]. In particular:
* ''Poincaré- Lindstedt method''. Letting dependent variable $$x$$ depend on the independent variable $$t$$ via terms of all orders i.e. $$t$$, $$\epsilon t$$, $$\epsilon^2 t$$, etc. However, these term are forced to only appear together, with the form: $$t+ \epsilon \omega_1 t + \epsilon^2 \omega_2 t +...$$. That is, we just expand the frequency as a perturbation series. A consequence is that constants of integration are not allowed to depend on $$t$$ at any order.
* ''Method of Multiple Scales''. We allow dependent variable $$x$$ depend on the independent variable $$t$$ via terms of all orders i.e. $$t$$, $$\epsilon t$$, $$\epsilon^2 t$$, etc., without any constraint. A consequence is that we can treat these as independent variables, or //scales//. "Constants" of integration can now depend on them (i.e. on the slower scales than the scale corresponding to the order considered)
* ''Krylov-Bogoliubov Method of Averaging''. Assumes that solution, $$x(t)$$ has the form that it has when $$\epsilon=0$$ but the constants of integration can now change with time. As we have two arbitrary time-dependent functions (in the case of a second order ode), we are clearly underdetermining the problem. Therefore Krylov and Bogoliubov added the constraint that the time derivative of $$x(t)$$, i.e. $$\dot{x}(t)$$, also hase the same form as when $$\epsilon=0$$ with the same constants of integration upgraded to the same time-dependent functions.
For example (for the method of averaging), if $$x(t)=a \cos{(t+\theta)}$$ is the $$\epsilon=0$$ solution, then we require:
* $$x(t)=a(t) \cos{(t+\theta(t))}$$, and
* $$\dot{x}(t)=-a(t) \sin{(t+\theta(t))}$$
[[Duffing oscillator]]
Van der Pol oscillator. [[Paper about it's periodic solutions|https://projecteuclid.org/download/pdf_1/euclid.hmj/1206139799]] Apply method of multiple scales.
!!Relaxation oscillations and transition layers
As an example consider the van der Pol eq. with the nonlinear term very large ($$\Lambda \gg1$$), instead of very small.
We introduce a variable $$y$$ s.t. eq. becomes $$y'=-x$$. One also shows that $$x$$ evolves to a state of quasi-equilibrium (very quickly on time scale $$1/\Lambda^2$$) given by a curve on y-x plane. Then it moves along that curve, and one finds that the system must do jumps that are also very fast (on time scale $$1/\Lambda^2$$ again) periodically. See plot... Well... I'm ommiting many details. See starting from page 11 on [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3082/137/main_2.pdf]]
!!Synchronization and coupled oscillators
[[Kuramoto model]]
--------
[[Lecture notes on nonlinear vibrations|http://audiophile.tam.cornell.edu/randdocs/nlvibe52.pdf]]
//Books//:
Nayfeh
Hayashi
''[[Nonlinear regression|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=15m50s]]''. Like linear regressions but the parameters enter nonlinearly in the function representation, for example as weights in a //multi-layer perceptron// (MLP), i.e. a ANN, with usually a few layers (shallow learning..). [[Vowpal Wabbit|https://github.com/JohnLangford/vowpal_wabbit/wiki]] is good for logistic regression.
See [[Topics in Nonlinear Dynamics by Balakrishnan|https://www.youtube.com/watch?v=nh4TFzg30eQ&list=PLiUVvsKxTUr7IHEbT0-NPVqKW05CFWCaE]], and [[another lectures by him|https://www.youtube.com/watch?v=EF9T78DPzGg&list=PLVbyDf9daF9tFUpKqKzkzfEg-mRooTVAs]]
''Nonlinear dynamical systems'' (often abreviated to Nonlinear systems) are [[Dynamical system]]s where the O.D.Es or the mapping functions that describe the dynamics are nonlinear. They offer much richer behavior like ''bifurcations'' and ''chaos''. Thus, while, locally, they can be linearized and analyzed by the same linear Jacobian techniques, they require more variety in analysis techniques, such as ''bifurcation theory'', ''Lyanpunov functions'', ''trapping regions'', ''attractors'', and ''chaos theory''. <mark>Make subsections of these and organize better</mark> See Wiggins book, and Strogatz.
!![[Nonlinear continuous dynamical system]]
!!![[Nonlinear oscillations]]
!![[Nonlinear maps]] <small>(aka Nonlinear [[Discrete dynamical system]])</small>
The theory of discrete systems has many analogies to the theory of continuous systems.
!![[Chaos theory]]
------
[[Invariant manifolds in dynamical systems]]
--------
[[Oxford course|https://www0.maths.ox.ac.uk/courses/course/28740]]
[[Strogatz YB lectures|https://www.youtube.com/watch?v=P_YCvTabMO4&index=4&list=PLbN57C5Zdl6j_qJA-pARJnKsmROzPnO9V]]
[[Chaos Journal|http://scitation.aip.org/content/aip/journal/chaos]]
-------
Books
Strogatz Nonlinear systems dynamics and chaos
Deterministic Nonlinear Systems: A Short Course
Vadim S. Anishchenko, Tatyana E. Vadivasova, Galina I. Strelkova (auth.)
See books in oxford course website
Other lecture notes: http://www.jpoffline.com/physics_docs/y3s5/nlp_lecture_notes.pdf
More LNs: http://14.139.172.204/nptel/CSE/Web/108106024/Module5.pdf
Formally, the number of "parameters" grows with the training set. Here number of parameters basically refers to "amount of information in learned function". For example, in neares-neighbour models, the parameters are the position of the neighbourhoods, and the categories to which those regions map. The number of these parameters clearly grows as more data points are added.. A more intuitive way of looking at it is that the algorithm doesn't fit parameters, and instead uses some other method to generate the function it is trying to learn. See [[Nonparametric statistics]] An example is [[Nearest-neighbour classification]] (note that the model has parameters, but they are not fitting parameters, instead they are chosen before using the algorithm, and then are fixed)
https://en.wikipedia.org/wiki/Nonparametric_statistics
not based on parameterized families of probability distributions
__Nonparametric models__
* [[Nearest-neighbour classification]]
* [[Locally-weighted linear regression]]
They are both based on looking at local neighbours near points for which we are going to make the prediction.
A [[Probability distribution]] that has the form of a [[Gaussian]].
See [[Power laws]]
The normalization C , assuming $$k$$ starts at $$1$$, is related to the Riemann zeta function, $$C=\frac{1}{\zeta(\alpha)}$$, or the generalized or incomplete zeta function $$C=\frac{1}{\zeta(\alpha, k_{min})}$$ if there is a minimum $$k$$ over which we normalize. Or we could approximate the sum needed to normalize by an integral. $$C=\frac{1}{\int_{k_{\text{min}}}^\infty k^{-\alpha}dk}=(\alpha-1)k_{\text{min}}^{\alpha-1}$$
Modern synthesis
1. Variation unbiased
2. Space of possible genotypes very vast (even after discarding biologically unviable ones). Evolution is contingent. C.f genetic drift.
However,
*Contingency in genotype space does not imply contingency in phenotype space => convergent evolution
*Genetic code (mapping from codons to aminoacids) has redundancy. Mackay suggested this could have arrived because it was fittest code. However, evolving the code is very costly (as it would affect many proteins at one) so probably very unlikely. Thus, Crick proposed it was a "frozen accident".
*Neutral theory of evolution.
*pre-Darwinian evolution of genetic code. Optimized for error reduction
Protein coding
Hoyle-Salisbury paradox. How can evolution find right proteins in hyperastronomically large space?
Maynard Smith argument
Keefe and Szostak computer experiments
Levinthal's paradox
Redundancy, correlaton, and funnel-shapped landscapes
RNA case study
When talking about the word game, word probability incorrectly used
For self assembling system the many to one map is from cluster configurations (like genotype) to physically distinct systems (like phenotype). However self assembly explores the phenotype space uniformly and thus shows a bias in the genotype space, and it's a bias against simplicity and symmetry.
Algorithm information theory....
For fixed length codes, simple codes have many ways of appearing
Fixed code lengths means we have a finite state machine. Algorithmic complexity for finite state machines?
~~The formula given in the slide of Solomonoff is not a probability, but an expected number of times a certain program will come up, that's why it's not normalized. For long codes, it's approximately a probability, though~~. No
Feed fixed input length codes with a short pefix corresponding to the map (the conditon of it being short, in particular much shorter than the inputs, could be the quantitiative condition corresponding to Ard's observation that the map should be "simple"). Then feed this to a Turing Machine (TM). Results will be of varying length. You expect shorter lengths to be more common because:
Input to the TM is approximately like feeding random fixed-length codes (because prefix code is much shorter than input, by assumption, and inputs are random).
If we reverse the TM, hmm no it doesn't work. Well the output will be an input that produces a fixed-length string of bits for the reversed TM, but the distribution in outputs is not random now?
Are there more fixed length strings that will produce shorter codes? Seems unlikely. But im missing he many to one nature of the mapping in this description. Or hmmmm the little prefix code should make this happen somehow? What kind of "prefix codes" can do this?
[[Extracting Hidden Hierarchies in Complex Spatial Networks|https://www.youtube.com/watch?v=BTYMqiemQR4]]
See [[Spatial networks]]
* Leaf venation. Most efficient structure to do transportation from one points to many points in a region of space is a tree-like structure. However, most modern plant leaves have an intricate loopy topolgy (reticulation) for increased resilience against damage.
* Physarum polycepharum slime mold. Nice network. It is "smart".
* Loop hierarchy structure of planar network, forms a tree representation of it. Nice
* 3D networks. Connectome.
* Quaking aspen root network. Network of extended root structure of plants symbiotic with fungi. 80% of plants do this!
* Ant colonies
* Sand piles, dunes & granular matter. Network in granular media under applied stress
* Vasculature. Except in lungs, you get loopy, reticular network structure
* Any graph can be represented in 3D (without edges crossing): Book representation!
* A graph can't be represented in a 2D plane without edges crossing in general (graphs that can are called planar). However, graph may be embeddable (w/o edges crossing) on a 2D surface other than the plane (like a torus). The genus of the simplest surface on which a graph can be represnted like this is called that graph's graph genus.
* Cycle space (set of loops or combination of loops that live on the graph). Fundamental basis
* His algorithm for determining the cycle structure in a 3D graph can be proved to work (asymptotically) for 3 regular graphs. In biological networks, this is essentially always the case due to how they form. For other spatial networks, degree distribution is usually highly peaked, and the average degree is low, and he suggests that this may mean it also works for them. He thinks it won't work mostly for scale-free graphs.
* Can start with hexagonal lattice on surface of certain genus, and apply perturbations (like dislocations)
* Growth model for the [[physarum slime|Physarum machines and physarum solver]]
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<title>rnn</title>
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<text transform="translate(76 75.88)" font-size="13" font-family="Open Sans">First, the controller gives a query <tspan x="0" y="20">vector and each memory entry is </tspan><tspan x="0" y="40">scored for similarity with the </tspan><tspan x="0" y="60">query.</tspan></text>
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<text transform="translate(77.83 213.88)" font-size="13" font-family="Open Sans">The scores are then converted <tspan x="0" y="20">into a distribution using softmax.</tspan></text>
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<text transform="translate(77.83 352.88)" font-size="13" font-family="Open Sans">Next, we interpolate the <tspan x="0" y="20">attention from the previous </tspan><tspan x="0" y="40">time step. </tspan></text>
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<text transform="translate(77.83 465.88)" font-size="13" font-family="Open Sans">We convolve the attention with <tspan x="0" y="20">a shift filter — this allows the </tspan><tspan x="0" y="40">controller to move its focus.</tspan></text>
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<text transform="translate(77.83 598.88)" font-size="13" font-family="Open Sans">Finally, we sharpen the <tspan x="0" y="20">attention distribution. This </tspan><tspan x="0" y="40">final attention distribution is </tspan><tspan x="0" y="60">fed to the read or write </tspan><tspan x="0" y="80">operation.</tspan></text>
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<text transform="translate(558 -161.12)" font-size="13" font-family="Open Sans">The RNN gives an attention distribution, <tspan x="0" y="20">describing how much we should change </tspan><tspan x="0" y="40">each memory position towards the write </tspan><tspan x="0" y="60">value.</tspan></text>
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<text transform="translate(475.41 40)" font-size="13" font-family="Open Sans">memory</text>
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<text transform="translate(478.5 163.63)" font-size="13" font-family="Open Sans" font-style="italic">Blue shows high similarity, <tspan x="0" y="20">pink high dissimilarity.</tspan></text>
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<text transform="translate(795.09 335)" font-size="13" font-family="Open Sans">interpolation amount</text>
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<text transform="translate(795.09 467)" font-size="13" font-family="Open Sans">shift filter</text>
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<text transform="translate(775.09 19)" font-size="13" font-family="Open Sans" font-style="italic">RNN controller</text>
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<text transform="translate(628.56 19)" font-size="13" font-family="Open Sans" font-style="italic">attention mechanism</text>
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<text transform="translate(795.09 71)" font-size="13" font-family="Open Sans">query vector</text>
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<text transform="translate(557.03 273)" font-size="13" font-family="Open Sans">attention from previous step</text>
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<g opacity="0.6">
<text transform="translate(296.09 735)" font-size="13" font-family="Open Sans">new attention distribution</text>
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http://nptel.ac.in/courses/115104043/
https://en.wikipedia.org/wiki/Nucleobase
There is many polar bonds that can bond through [[Hydrogen bond]]ing
!!__Purines__
* Guanine
* Thymine
!!__Pyrimidine__
* Adenine
* Cytosine
In RNA, uracil substitutes thymine
A [[Molecule]] (or [[Molecular ion]]) which tends to bind to partially postiviely charged parts of a [[Molecule]] (where the [[nucleus|Atomic nucleus]] is more exposed)
[[Addition reaction]] where an [[Nucleophile]] is the one being added
[[Substitution reaction]] where an [[Nucleophile]] is the one substituting
!!!__Sugar + phosphate backbone__
!!!__[[Nucleobase]]__
!!__Nucleotide synthesis__
$$\binom{n+k-1}{k-1}$$
See [[Stars and bars]]
$$\binom{n-1}{k-1}$$
See [[Stars and bars]]
//Things can often be counted//
[[The LMFDB is an extensive database of mathematical objects arising in Number Theory|http://www.lmfdb.org/]]
[img[http://i.imgur.com/RX7iOuq.png]]
Note this is calculated with zlib complexity..
[img width=400 [complexity_transducers.png]]
,,Average bias over 100 samples: 0.74. 74% of the outputs states have most of the inputs.,,
----------------------------
!!See code [[here|https://github.com/guillefix/fst-bias]]
------------------------------------------
I also have got the code working. Due to the way the libraries I'm using works, it has to be done in 5 steps: generating the fst files, converting them, running the fsts on random inputs, counting number of inputs per output, computing complexities of outputs.
I'm going to write a bash script that calls these in the right order. I'm also using the (modified) Lempel-Ziv complexity measure that you use, that Chico gave me.
At the moment, the random generation of fsts is done in python. I think this is fine, as the bulk of the computation is the "running" and complexity steps, which are c++. However, I found a C++ library that can randomly generate automata (http://regal.univ-mlv.fr/); I haven't yet managed to make it work, but if we do, it's maybe better to use that one.
From preliminary runs, I have indeed found the c++ to be much faster, so that I could rather quickly run 10^6 input strings on 50 random 5-states transducers. Of those 11-13 showed clear simplicity bias, the rest showing much smaller bias. This was actually using some python code that is now c++, and should now work even better.
Other statistics and complexity measures that we were talking about are yet to be implemented.
[[Oxford course|https://www0.maths.ox.ac.uk/courses/course/28809/material]]
Over and over again we see a pattern like this:
nonlinear ----------linearize & iterate-----------> LINEAR
PDE ------------discretize-------------> ALGEBRA
Because of this, computers have brought linear algebra, and numerical linearalgebra, to the forefront of the mathematical sciences.
Standard algorithms to ''solve linear system'' $$Ax = b$$, i.e. matrix inversion, grow like $$O(N^3)$$. To improve this one can:
* use ''parallel computing'', or
* algorithms to ''take advantage of sparsity of matrix'' (many entries are zero)
In recent years flop count is less and less important at the high end (i.e. for many processors) – communication is a bigger bottleneck.
!!!''Initial value problem''s (IVP) for __ordinary differential equation__ (ODE)
In standard form
$$u' = f(u,t)$$
could represent system of equations (i.e. $$u$$ vector).
Discretize time in steps of size $$k$$ (//timestep//).
Numerical methods (//finite difference discretization// methods):
* ''[[Multi-stage|http://web.mit.edu/16.90/BackUp/www/pdfs/Chapter10.pdf]]''. ''Runge-Kutta'': 1 step, i.e. only neighbouring grid points.
** Modified Euler. Accuracy $$O(k^2)$$
** Fourth order Runge-Kutta. Accuracy $$O(k^4)$$
* ''[[Multi-step|http://web.mit.edu/16.90/BackUp/www/pdfs/Chapter4.pdf]]''. ''Adams-Bashforth''. Uses points n steps away in grid. Drawback: they are tricky to start up because extra values are needed.
** 1st order. Called (forward) [[Euler formula|https://en.wikipedia.org/wiki/Euler_method#Formulation_of_the_method]]. Accuracy $$O(k)$$
** 2nd order. Accuracy $$O(k^2)$$
** etc.
__IVP codes in MATLAB__
`ode23`: low-order RK
`ode45`: higher-order RK
`ode113`: variable-order multistep
`ode23s`, `ode15s`, `ode15i`, `ode23t`, `ode23tb` variants for stiff problems etc.
In ''[[Chebfun|http://www.chebfun.org/]]''
`N = chebop(a,b)` % define the interval [a,b]
`N.op = @(x,u) ...` % define the ODE, with diff(u,k) = kth derivative of u
`N.bc = ...` % boundary conditions
!!!__[[Order of accuracy|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/2203/7/2.pdf]], convergence, stability, etc.__
See [[here|http://web.mit.edu/16.90/BackUp/www/pdfs/Chapter3.pdf]] for explanation of ''local truncation error'' (LTE), used to find //order of accuracy// (what we call accuracy above, $$O(k^2)$$, i.e. error decreases with the square of the time step.
''Convergence'' and ''Stability''
Theory of convergence of multistep formulas by Dahlquist (1956). Analogs for RK too.
Key definitions:
''consistent'': order of accuracy > 1.
''stable'': if for f(t,u) = 0 all the solutions are bounded.. I.e. does error grow or stay bounded.. See [[here|http://web.mit.edu/16.90/BackUp/www/pdfs/Chapter5.pdf]] too.
''convergent'': $$v\rightarrow u$$ for each fixed $$t$$ as $$k \rightarrow 0$$ (ignoring rounding errors, from computing..).
''Dahlquist equivalence theorem'':
|Convergence $$\Leftrightarrow$$ consistency $$+$$ stability|
The Adams formulas are consistent and stable, hence convergent
Adaptive ODE codes adapt step size and other parameters so that estimated errors (using methods above, like LTE) are smaller than a prescribed value.
__[[Chaos|Chaos theory]]__ and __[[Lyapunov exponents]]__. The [[Lorenz equations]]. Sinai billiards is another famous chaotic system.
__[[Stability regions|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/2203/13/4.pdf]]__ regions of $$ka$$ space ($$a$$ is a parameter in the model ode, a=0 corresponds to f=0, as defined above for stability, I guess here we are being more general..) in which solutions remain bounded (this is achieved when characteristic polynomial of the recurrence relation, obtained by the finite difference method, has roots with $$|r| \leq 1$$ and any root $$|r|=1$$ is simple). See [[here|http://web.mit.edu/16.90/BackUp/www/pdfs/Chapter5.pdf]] too.
''Stiffness''. A stiff ODE is one with widely varying time scales. One may need very small $$k$$ because there are modes with $$ka$$ (i.e. part of equation which create behaviour corresponding to certain $$a$$ value) outside stability region, even if our solution of interest has effective $$ka$$ inside it.
This is manifested as our solution changing on a long timescale, but depending on short time-scale terms in equation.
Solution: backward-differentiation formulas, or ''implicit formulas'', that include $$f(v_{n+1}, t_{n+1})$$, unlike explicit formulas.
These require solving a (generally) nonlinear equation (or a system of equations for PDEs). And this may need to be solved numerically itself often, for example by Newton's method.
----------
//Aside.// We've been discussing IVPs here only.
''Boundary value problems'' (BVP) also important. Nonlinear BVP may not have unique solutions! (unlike IVP).
Can use chebfun to solve.
--------
!!__Partial differential equations__
Many of these methods full under [[Finite element method]]s
Now have time and space.
Simplest approach is again //finite difference discretization//. Now discretizing time and space.
[img[Numerical_method_PDE.png]]
__Numerical stability__
''[[von Neumann analysis|https://en.wikipedia.org/wiki/Von_Neumann_stability_analysis]]'' or discrete Fourier analysis. Plug imaginary (oscillatory) exponential into the finite difference formula, and see if some mode blows up (by the //amplification factor// being greater than 1), or not. Define region of stability thus.
PDEs can also be __stiff__ for same reasons as ODEs, and then need to use implicit methods too. A non-linear example is the Kuramoto-Sivashinsky equation.
__Order of accuracy__
Defined now for both timestep $$k$$ and space step $$h$$ (see [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/2203/31/7.pdf]]). To improve order of accuracy over straightforward Euler method (which is first order in $$k$$) we use the __trapezoidal rule__, which is symmetric in $$t$$ (so that first order errors cancel, and is thus 2nd order in $$k$$). In case of heat equation it's known as ''Crank-Nicolson formula''. In the case of heat equation, it's known as the ''leap frog formula'' (1928).
Reaction-diffusion equations and other stiff PDEs. Can use exponential integrator methods... Solitons
__Finite differencing in general grids__
Not necessarily equally-spaced.
Principle:
1. At each $$x_j$$ decide which data, from neighbouring points, $$v_{j-r}, ..., v_{j+s}$$ to use.
2. Interpolate these data by polynomial of degree $$r+s$$.
3. Finite difference approximation to $$k$$th derivative is: $$p^{(k)}(x_j)$$.
We don't do these steps explicitly at every step, rather there are slick algorithms to get a formula for general $$v$$s for arbitrary grids $$x_j$$s, and one uses that formula. See //B. Fornberg, “Generation of finite difference formulas on arbitrarily spaced grids,” Math. Comput. 51 (1988), 699-706// and //B. Fornberg, “Calculation of weights in finite difference formulas”, SIAM Review 40 (1998), 685-691.//
In multiple space dimension same principles apply, but the system of equations needed to be solved for implicit methods corresponds to a matrix that has a much wider "band" (i.e. set of non-zero diagonals) than for 1 dimension. The structure of this matrix, in the case of discretizing the Laplacian is the famous "discrete or lattice Laplacian" (related to the [[Graph laplacian]]). See [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/2203/38/8.pdf]]. This Laplacian can often be written as a //Kronecker sum//.
[[Spectral methods]]
-------
Examples of Differential Equations, with nice explanations:
[[Trefethen et al.'s PDE COFFEE TABLE BOOK|https://people.maths.ox.ac.uk/trefethen/pdectb.html]]
Reaction-diffusion equations in [[Morphogenesis]]
-------
//Books//:
Griffiths & Higham, 2010 - introduction to numerical ODE
Iserles, 2009 - includes connection to PDEs
LeVeque, 2007 - likewise
Hairer, Norsett & Wanner I & II - authoritative; full of fun and historical remarks
Ascher & Petzold 1998 - also includes DAEs (differential-algebraic equations,
which combine ODEs and nonlinear eqs)
Deuflhard & Bornemann, 2002
Trefethen, old online textbook ([[http://people.maths.ox.ac.uk/trefethen/pdetext.html]])
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
Nutrition is the science that interprets the interaction of nutrients and other substances in food in relation to maintenance, growth, reproduction, health and disease of an organism. It includes food intake, absorption, assimilation, biosynthesis, catabolism and excretion.
https://www.wikiwand.com/en/Nutrition
recommended daily intake
[img[http://image.slidesharecdn.com/unit1howourbodyworks-131004111527-phpapp02/95/unit-1-how-our-body-works-5-638.jpg?cb=1380885363]]
!!!__[[Vitamin]]s__
[img[http://www.compoundchem.com/wp-content/uploads/2015/01/Chemical-Structures-of-Vitamins-2016.png]]
[img[http://temubunda.com/wp-content/uploads/2016/04/Vitamin-dan-Mineral.png]]
[[moar|https://www.google.es/search?client=ubuntu&biw=1855&bih=985&tbm=isch&q=vitamins+and+minerals+rich+foods&sa=X&ved=0ahUKEwjQzeDw2_vQAhUDXRoKHfrwBKAQhyYIKA&dpr=1#imgrc=_]]
[img[https://s-media-cache-ak0.pinimg.com/originals/1c/d9/f9/1cd9f9408375083c03607fc9ab6db06c.jpg]]
[[Metabolism]] determines how nutrients are processed
,,or just sampling theorem,,
It establishes a sufficient condition for a sample rate that permits a discrete sequence of samples to capture all the information from a continuous-time signal of finite bandwidth.
Perfect reconstruction may still be possible when the sample-rate criterion is not satisfied, provided other constraints on the signal are known. See [[Compressed sensing]]
https://www.wikiwand.com/en/Nyquist%E2%80%93Shannon_sampling_theorem
a.k.a. OOP
''object'' = collection of data and functions (methods), that often act on this data.
Keywords: Encapsulation. Message-passing metaphor. data abstraction. Modularity.
Abstract data types (often implemented as classes). A ''class'' is a collection of objects with characteristics in common. A class is represented as a template from which one can instantiate objects. Instantiation is often done by "calling" the class, as if it were a function.
In many respects, classes and objects are similar.
|__Data hiding__: One can only access instance values through defined methods. Sometimes built in language, but even if not, it is often good practice.|
An object built from a class, is an __instance__, and it has __attributes__: methods and fields (variables). These are often called using ``.`` notation.
//Methods in Python//
*_ _init_ _: create instance
*_ _str_ _: printed representation
*_ _cmp_ _: comparisons (returns -1, 0, 1).
*_ _iter_ _ and ``next`` to define how iteration happens over an object that represents a collection.
These are doing operator overloading. In Python, ``dir(p)`` shows all methods associated with an object.
``type(``instance``)`` returns the class.
__Inheritance__
A class can inherit attributes from another class, when its defined.
__Shadowing__ (a.k.a. overriding an inherited method).
OOP is good for modelling systems where you have lots of elements that possibly interact.
--------
__[[Factory functions in JavaScript|https://www.youtube.com/watch?v=ImwrezYhw4w]]__
Factories are functions that implement the same functions as classes, but have some advantages. The only disadvantage is that they are a bit slower probably.
I think this is related to //prototype-oriented programming//, JavaScript's version of OOP.
//aka law of parsimony//
<<<
Among competing hypotheses, the one with the fewest assumptions should be selected
<<<
[[https://www.wikiwand.com/en/Occam's_razor]]
Formalized in [[Solomonoff|Ray Solomonoff]]'s theory of [[Universal inductive inference]]
Trivial example of Occam's razor being true: [[the case when one event/hypothesis includes the other|https://www.youtube.com/watch?v=yXkEpzexYIU#t=15m23s]]
See [[Simplicity]]
[[https://www.wikiwand.com/en/Octet_rule]]
The octet rule is a chemical rule of thumb that reflects observation that atoms of main-group ''elements tend to combine in such a way that each atom has eight electrons in its valence shell'', giving it the same electronic configuration as a noble gas. The rule is especially applicable to carbon, nitrogen, oxygen, and the halogens, but also to metals such as sodium or magnesium.
http://www.vikingsofbjornstad.com/Old_Norse_Dictionary_E2N.shtm#h
https://www.wikiwand.com/en/Old_Norse
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
[[Medicine]] for [[Cancer]]
[[Learning]] from one or few examples. A current challenge in [[Deep learning]]
people seem to learn rich concepts that generalize well from sparse data. See [ext[here|http://cims.nyu.edu/~brenden/LakeEtAl2015Science.pdf]]
!!__Approaches__
*[[Program induction]]
** [[Bayesian program learning]]
//What things exist?//
[[Contemporary ontology|https://www.youtube.com/watch?v=qKq0Afmsj-U#t=3m45s]]
#What are the most general features of the World, and what sorts of things does it contain? What is the World like?
#Why does a World exist -- and, more specifically, why is there a World having the features and the content described in the answer to question 1?
#What is our place in the World? How do we humans beings fit into it?
See [[Metaphysics]].
!!!I think the answer to these questions lies in [[Systems theory]], [[Mathematics]], and [[Science]].
!!__[[Concept]]s__
[[Entity]]
[[Property]]
[[Process]]
[[Structure]]
[[Conceptualism|https://www.wikiwand.com/en/Conceptualism]] Conceptualism is a philosophical theory that explains universality of particulars as conceptualized frameworks situated within the thinking mind.
------------------
[ext[https://www.wikiwand.com/en/Categories_(Aristotle)]]
[[Is Anything Real?|https://www.youtube.com/watch?v=L45Q1_psDqk]]
A [[Multi-cellular organism simulation]] of the [[C. Elegans]]
http://browser.openworm.org/
http://www.openworm.org/
[[Operating System Basics|https://www.youtube.com/watch?v=9GDX-IyZ_C8]]
!!__Device management__
!!__Managing processes__
Modern operating systems that are designed for multitasking, make use of [[Concurrent computing]] ideas, such as [[Multithreading]]
//Interprocess communication (IPC)//
//daemons//
!!__[[Memory management]]__
!!__System calls__
!!__File system__
A [[Function]] between [[Cartesian product]] of [[Set]]s, and another set. Often, the domain is a [[Cartesian power]] of a single set.
"My earliest contact with modern scientific philosophy may have been P.W
Bridgman's concept of "operational definition" (Bri 27). An ''operational definition'' of anything is a precise sequence of physical
operations that enable one
to either construct it or identify it with certainty. When one can't make an
operational definition of something, this is usually an indication of poor understanding of it. Attempts to operationalize definitions can be guides to discovery
I've found this idea to be an invaluable tool in telling me whether or not I really
understand something.
Though individual concepts in a theory need not be operational, the theory
as a whole must have operational meaning. Rapoport (Rap 53) discusses the
application of operational concepts in daily life as well in science" from [[Solomonoff|Ray Solomonoff]]'s
[[Operations research|https://en.wikipedia.org/wiki/Operations_research]] is a discipline that deals with the application of advanced analytical methods to help make better decisions.
__Transportation, Assignment, and Transshipment Problems__
(Basically problems in linear programming, a.k.a linear [[optimization|Optimization]])
From Winston's book on OpRes: http://www.producao.ufrgs.br/arquivos/disciplinas/382_winston_cap_7_transportation.pdf
http://uk.mathworks.com/help/optim/ug/linprog.html
[[Ambiguous Cylinder Illusion|https://www.youtube.com/watch?v=oWfFco7K9v8]]
[[Ambiguous Cylinders|https://www.youtube.com/watch?v=SzC-pV_moFc]]
[[Troika, squaring the circle, Kohn Gallery.webm|https://www.youtube.com/watch?v=dVG4RwxDGA4]]
[[不可能モーション2 〜 Impossible Motions 2 〜|https://www.youtube.com/watch?v=1dISzq4kIPc]]
I wonder if there could be some formal analogies between how these illusions apparently distort space-time, and how [[General relativity]] works.
[[Optimal ordered problem solver|https://www.youtube.com/watch?v=mF5-tr7qAF4#t=18m]]
http://www.scholarpedia.org/article/Universal_search#OOPS_and_other_incremental_variations
https://en.wikipedia.org/wiki/Mathematical_optimization
https://en.wikipedia.org/wiki/Optimization_%28disambiguation%29
,,[ext[oxford course|http://mpawankumar.info/teaching/cdt-optimization.html]],,
http://www.benfrederickson.com/numerical-optimization/
-----------
$$\min\limits_{x \in X} f(x)$$
* ''Continuous otpimization''. The space $$X$$ over which you are optimizing is continuous
* ''Discrete optimization''. The space $$X$$ over which you are optimizing is discrete. [[Good book|http://www.designofapproxalgs.com/]]
!__Continuous optimization__
Good learning resource: [ext[book + lectures|http://stanford.edu/~boyd/cvxbook/]].
!!!__Unconstrained and constrained optimization__
$$\min\limits_{x \in X} f(x)$$
See [[intro slides|http://mpawankumar.info/teaching/cdt-optimization/lecture1_1.pdf]]. Often $$X = R^n$$ an n-dimensional real number space.
''Constrained optimization'' refers to optimization where the optimization space is some subspace of an "underlying space". This is a bit arbitrary, but the underlying space is most often assumed to be $$R^n$$ and the constraints then define a subset of $$R^n$$ through inequalities and equalities.
!!__[[Constrained optimization]]__
//All of these are mostly refering to continuous optimization//
[[wiki|https://www.wikiwand.com/en/Constrained_optimization]] -- [ext[notes|http://www1.maths.leeds.ac.uk/~cajones/math2640/notes4.pdf]] -- [ext[notes2|http://www.stat.cmu.edu/~cshalizi/statcomp/14/lectures/18/lecture-18.pdf]]
!!!--__Optimization problem with inequality constraints__
A //mathematical optimization problem//, or ''optimization problem''.
[img[http://i.imgur.com/BwndXEY.jpg]]
One can also have equality constraints, apart from inequalities.
!!!__Primal and dual problem and KKT conditions__
[[Andrew Ng video|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=23m30s]] -- [[General optimization problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=27m]] -- [[Dual problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=34m30s]], uses [[Max–min inequality]]. [[Conditions for the primal and dual problems being equivalent|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=39m]] (includes [[Karush–Kuhn–Tucker conditions|https://www.wikiwand.com/en/Karush%E2%80%93Kuhn%E2%80%93Tucker_conditions]])
Has applications in [[Support vector machine]]s. The reasons we use the dual problem is that it has many useful properties, I think it is convex?
!!!__[[Linear programming]]__: [[Linear|Linearity]] objective and constraint functions. Used in [[Operations research]]
!!!__''Nonlinear programming''__
Objective and constraint functins are non-linear. Some special cases:
* [[Convex optimization]]. Generalizes linear programming.
* [[Quadratic programming]]
** [[Least-squares]]
Often for global nonlinear optimization, we need to use brute force methods, with [[Computational complexity]] exponential in the dimension of th optimzation space (space of optimization variables). For approximate but faster solutions, we can use local optimizal optimization, or heuristics.
!!!__[[Lagrange multiplier]] method__
http://mat.gsia.cmu.edu/classes/QUANT/NOTES/chap4/node6.html
Good explanation of inequality constraints using an extension of Lagrange multipliers. Think of planes in 3D as constraint surfaces for intuition on equation! Delta f should be perpendicular to hypersurface defined by constraints.
!!--__[[Local optimization]]__
{{Local optimization}}
[[More things on optimization|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=56m20s]]
!__Discrete optimization__
!!!__Discrete optimizatino using energy minimization__
Can formulate discrete optimization as an [[Energy minimization|http://mpawankumar.info/teaching/cdt-optimization/lecture2_2.pdf]] problem on a set of random variables which can take values in a discrete set. This can be formulated as a [[Graphical model]]. [[Energy-based model]], [[Ising model]]..
In simple cases it can be solved iteratively using [[Dynamic programming]]. However, in general, the problem [[NP-hard]] (non-deterministic polynomial).
We can solve it (approximately?) using [[Max-flow min-cut theorem]]. Partition of the graph will correspond to the labelling. We will make terms in the energy correspond to capacities so that the minimum-capacity cut will correspond to minimum energy. For the energy, we will use:
* ''Unary potential''. Links of a particular random variable / node in the [[Graphical model]] to a source, and to a sink, with capacities corresponding to the unary potential (cost of one label or the other).
* ''Pairwise potential''. Links between non-source/sink nodes. Corresponds to cost of two labels being the same (no cut through edge), or different (cut passes through edge). They may be negative, in which case we can't apply this method, and it's NP-hard! This is case is called super-modular. To apply min-cut algo, we want the weights of the link to be postivie, and this is called sub-modular. Sometimes, we can avoid supermodularity, by renaming labels, but in some cases, even this can't avoid negative links, these cases correspond to [[Frustration]]. [[see here|http://mpawankumar.info/teaching/cdt-optimization/lecture2_2.pdf]] (...remember you substracted P from all link weights, on slide..)
Multiple labels: move-making algorithm.
* Expansion algorithm. $$\alpha$$-expansion.
** Binary choice: Keep your label, or change to a new label $$\alpha$$.
** If the distance function is a [[Metric]], the [[Triangle inequality]] ensures sub-modularity, and can use min cut!
-------------
!!--__Heuristic optimization__
[[Evolutionary computing]]
[[Artificial intelligence]]?
-----------
!!!__Hyperoptimization__
[[Gradient-based Hyperparameter Optimization through Reversible Learning|http://arxiv.org/abs/1502.03492]]
----------------
[[Probabilistic programming|http://probabilistic-programming.org/wiki/Home]]
See links [[here|https://en.wikipedia.org/wiki/Multidisciplinary_design_optimization#Problem_solution]]
[[Memetic algorithm|https://en.wikipedia.org/wiki/Memetic_algorithm]]
[[Evolutionary computing]]
!!![[Simulated annealing|https://en.wikipedia.org/wiki/Simulated_annealing]] ! [ext[http://www.mit.edu/~dbertsim/papers/Optimization/Simulated%20annealing.pdf]]
https://en.wikipedia.org/wiki/Inferential_programming
------------
!!__Applications__
Many applications in [[Science]], [[Engineering]], [[Statistics]]...
* [[Portfolio theory]]
* [[Electronic design]]
* [[Machine learning]] (data fitting, in particular)
* [[Computational geometry]]
__Algorithms__
* [[Gradient descent]]
**[[Stochastic gradient descent]]
** [[Newton's method]]
* [[EM algorithm]]
!!__Parameter initialization__
[[Neural networks [2.9] : Training neural networks - parameter initialization|https://www.youtube.com/watch?v=sLfogkzFNfc&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=15]]
!!__Batch learning__
The most common procedure, described above and in [[Machine learning]], where the algorithm is run on a particular data set all at once.
!!!__Mini-batch learning__
[[video|https://www.youtube.com/watch?v=Bver7Ttgb9M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=17#t=11m37s]]. Performing the optimization algo on a sample of a given size from the data set, per iteration.
!!!__Momentum__
To get through plateaus, for instance.
[[Momentum|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=50m40s]]. You add inertia to the particle so that the gradient descent is not just velocity = gradient (as it'd be in viscous fluid), but it is acceleration = (viscosity) + gradient.
!!!__[[Backpropagation]]__
for [[Artificial neural network]]s
!!__Online learning__
as opposed to //batch learning//
[[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=17m30s]]. You have to make predictions even in the process of learning.
,,
(//Online algorithm//, you process the data sequentially, by chunks. You need this if you do not access to all of it at the same time, or you have so much data that not all of it fits on your RAM..)
,,
What we care about is the [[online error|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=19m25s]]
[[Can apply batch learning algos for online learning|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=19m57s]]
[[Several theoretical results exist|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=21m58s]]
!!__[[Simplicity and learning]]__
The simplicity and structure in signals in the real-world is often seized to make the learning problem easier to solve.
!!__[[Advice for applying machine learning algorithms|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=24m55s]]__
!!!__[[Diagnosis for debugging learning algorithms|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=28m37s]]__
Diagnostic:
* High variance (overfitting) -> Training error would be much lower than test error. ([[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=34m05s]])
* High bias (underfitting) -> Test error will also be high. ([[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=35m50s]])
[[Ways to fix high variance or bias|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=37m50s]]
[[Is the algo converging?|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=37m50s]] -- [[Are you optimizing the right function?|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=43m30s]] --> [[Diagnostic|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=45m]]
[[One more example|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=50m45s]]
!!!__[[Error analysis|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1h03m20s]] and [[ablative analysis|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1h08m48s]]__
!!!__[[How to get started on a machine learning problem|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1h11m45s]]__
-- Premature (statistical) optimization ([[video|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=27m30s]])
[[The dangers of over-theorizing|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1h16m45s]]
!!![[Optimization for training deep models]]
[ext[pdf|www.deeplearningbook.org/contents/optimization.html]]
//aka structure//
''Order'' is the [[Property]] of a [[System]] that has some properties which are [[Random variable]]s distributed according to a non-uniform [[Probabililty distribution]]. The degree of order can be considered to be the degree to which the distribution is away from a uniform one.
Some quantities/concepts that can be used to measure/describe order are:
* [[Entropy]]
* [[Randomness deficit]]
* [[Sparsity]]
* Compressibility
* [[Simplicity]]
-----------------------
"Everybody knows that because typical signals have some structure, they can be compressed efficiently without much perceptual loss"
"When we have prior knowledge of the smoothness structure we expect to see (e.g. in natural images), we can impose this structure directly through the choice of factor. " See [[Learning theory]] (paper on predicting parameters in deep learning)
"many interesting signals or models in practice contain few degrees of freedom relative to their ambient dimension"
!!!__[[The World is Either Algorithmic or Mostly Random|http://fqxi.org/data/essay-contest-files/Zenil_FQXIEssayDigitalAnalo.pdf]]__
Physical laws are like computer programs.
"In an informational universe, the world would be computing itself, enabling things to remain themselves"
He proposes the [[Universal probability]] distribution as an a priori distribution, if the world is to be algorithmic, and they claim there is some evidence that data from natural phenomena agrees with this universal distribution. They argue that the world being algorithmic means it is probably digital/discrete. If it were analog, it would have more possibilities, and it would more probably be random.
A similar thesis is found in [[A priori probability estimates from structural complexity]].
He finds that feeding random inputs to their [[abstract computing machines|Automata theory]], and using machines without a halting state gives results (probability distributions over bitstrings) which agree most with empirical data.
He discusses a bit the issue of quantum mechanics, but I didn't quite get what he meant
[img[http://i.imgur.com/3CvNAxf.jpg]]
!!![[Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments|http://www.mdpi.com/1099-4300/14/11/2173]]
See [[Biological complexity]]
!!![[Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales|http://arxiv.org/pdf/1205.2026.pdf]]
See [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3128/8/OHPHandoutLecture3.pdf]] for defs, [[Asymptotic approximation]]
Big O: $$f=O(g)$$ as $$\epsilon \rightarrow 0$$
(f could be asymptotic to const*g, or much smaller)
Small o: $$f=o(g)$$
f is strictly much less than g
Strict order: $$f=\text{ord}(g)$$
f is strictly of order g, i.e. asymptotic to some constant times g.
[img[http://i.imgur.com/GGsYuKB.png]]
Also: [[Big theta notation|https://www.khanacademy.org/computing/computer-science/algorithms/asymptotic-notation/a/big-big-theta-notation]], and Big omega notation.
Often refers to a [[Total ordering]]
//Ordinal analysis//
The study of [[Permutation complexity]], which we call ordinal analysis, can be
envisioned as a new kind of symbolic dynamics whose basic blocks are ordinal pat-
terns.
* [[Immune system]]
* [[Cardiovascular system]]
** [[Blood]]
* [[Nervous system]]
* [[Reproductive system]]
* [[Digestive system]]
* [[Respiratory system]]
* [[Sense]]s
[[Organic compound]]
[[Biochemistry]]
!!__[[Organic reaction]]s__
[[wiki|https://www.wikiwand.com/en/Organic_reaction]] --
[[Nice website|http://www.chemtube3d.com/AIBOFundamental.html]] -- [[Khanacademy videos|https://www.khanacademy.org/science/organic-chemistry]]
* [[Addition reaction]]
* [[Elimination reaction]]
* [[Substitution reaction]]
* [[Organic redox reaction]]
* [[Rearrangement reaction]]
-------------
[[That's Why Carbon Is A Tramp: Crash Course Biology #1|https://www.youtube.com/watch?v=QnQe0xW_JY4&list=PL3EED4C1D684D3ADF]]
An ''organic compound'' is any member of a large class of [[Chemical compound]]s whose molecules contain carbon.
!!__Classification__
Organic compounds are mostly classified according to the [[Functional group]] they posses.
__Classification by functional group__
* [[Hydrocarbon]]
** [[Alkane]]
** [[Alkene]]
** [[Alkyne]]
* [[Alcohol]]
* [[Carboxylic acid]]
* [[Aldehyde]]
* [[Ester]]
* [[Ether]]
* [[Ketone]]
* [[Amine]]
* [[Amide]]
* [[Aliphatic compound]]
* [[Aromatic compound]]
* [[Nitro]]
* [[Alkyl halide]]
* [[Cyanide]]
* [[Acetal]]
* etc,etc,etc.
In general, carbon atoms carrying functional groups can be classified by their [[Oxidation state]]
__Classification by structure__
* Chain
** Linear chain
** Branched chain
* [[Cyclic compound]]
** [[Heterocyclic compound]]
** [[Homocyclic compound]]
* [[Polymer]]
--------------------
https://www.wikiwand.com/en/Organic_compound
A [[Chemical reaction]] between [[Organic compound]]s
[[wiki|https://www.wikiwand.com/en/Organic_reaction]] --
[[Nice website|http://www.chemtube3d.com/AIBOFundamental.html]]
* [[Addition reaction]]
* [[Elimination reaction]]
* [[Substitution reaction]]
* [[Organic redox reaction]]
* [[Rearrangement reaction]]
__Other__
* [[Dehydration synthesis]]
* [[Hydrolysis]]
A [[Living being]] seen as a system, often of [[Cell]]s, although a single cell is also an organism.
!![[Organismal biology]]
* [[Metabolism]], [[Organ system]]
* [[Self-reproduction]]
* [[Development|Developmental biology]]
* etc
!!__Number of cells__
* [[Unicellular organism]]
* [[Colonial organism]]
* [[Multicellular organism]]
------------
[[Model organism]]
---------------
[[Taxonomy]]
[[Evolution]], [[Phylogenetics]]
The [[Biology]] of [[Organism]]s
[[Developmental biology]]
[[Cell]] --> [[Tissue (Biology)]] --> [[Organ (Biology)]] --> [[Organ system]]s --> Complex organism.
[img[https://media.giphy.com/media/3o6Ei0notplH3iJ0Xu/giphy.gif]]
Trying to explain prevalence of [[genotype-phenotype map bias|Bias in GP maps]]
Ideas:
* ''Constrained and unconstrained parts''. See [[The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype–phenotype maps|http://rsif.royalsocietypublishing.org/content/12/113/20150724.full]] [[pdf|http://rsif.royalsocietypublishing.org/content/royinterface/12/113/20150724.full.pdf]]
* ''Algorithmic information theory'': Shannon-Fano code, universal probability. See below. See [[draft paper|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/APrioriProbabilityComplexity.pdf]].
* ''Random finite transducer''. See [[Simplicity bias in finite-state transducers]]
!!<i class="fa fa-lightbulb-o" aria-hidden="true"></i> [[Evolving automata]]
See [[Conversation with Chico Camargo on GP map bias - 22/4/2016]]
See also [[Abiogenesis]] and [[Artificial chemistry]]
!!__[[Algorithmic information theory]]__
''[[Levin's coding theorem|http://www.cse.iitk.ac.in/users/satyadev/a10/kolm_3.pdf]]''
[[Shannon-Fano-Elias code and simplicity bias in GP maps]]
[[Discussion on finite state complexity and GP map bias]]
__[[Coding theorem method]]__
__Yuri Manin's ideas__
[[Physics in the world of dieas: Complexity as energy|http://merton.physics.ox.ac.uk/notes/manin.pdf]] [[talk|https://www.merton.ox.ac.uk/event/17th-ockham-lecture-physics-world-ideas-complexity-energy]]
[[Zipf's law and L. Levin's probability distributions|http://arxiv.org/abs/1301.0427]]
[[Complexity vs Energy: Theory of Computation and Theoretical Physics|http://arxiv.org/abs/1302.6695]]
__More__
[[Statistical Physics and Complexity|http://www.ph.ed.ac.uk/icmcs/research-themes/statistical-physics-and-complexity]]
St Anne's college lib has "wild book" (see [[Krohn–Rhodes theory]])! Complexity of cellular automata, applied to life and evolution
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
''Osmiophoresis'' of a spherical shell which is permeable to solvent but impermeable to product particles refers to its development of a nonzero velocity due to osmotic forces that cause radial flows of solvent across the membrane.
[[Movement of a semipermeable vesicle through an osmotic gradient|http://scitation.aip.org/content/aip/journal/pof1/26/10/10.1063/1.864051]]
''Osmosis'' is the spontaneous net movement of solvent molecules through a semi-permeable membrane into a region of higher solute concentration, in the direction that tends to equalize the solute concentrations on the two sides. https://en.wikipedia.org/wiki/Osmosis
[img[http://i.imgur.com/hpT5CCW.png]]
It is often described by a "solvent potential", which is lowered by the addition of solute, and raised by increases in hydrostatic pressure. Thus, the solvent tends to flow from regions of lower to higher solute concentration, and this tendency can be countered by a sufficiently large pressure difference. However, the physical mechanisms that cause this are tricky. See description of mechanisms here: [[Physical mechanisms of osmosis]]
See also [[Osmotic forces]] for more general related effects, caused by interactions of the solute with the boundary
<b>Osmotic pressure</b> is defined as the external pressure required to be applied so that there is no net movement of solvent across the membrane. Osmotic pressure is a colligative property, meaning that the osmotic pressure depends on the molar concentration of the solute but not on its identity.
See [[Fluid mechanics]], [[Thermodynamics]]. See [[Microhydrodynamics]] for other possible osmotic effects, which can also cause pressure gradients.
See also [[Biophysics]]
In [[Reverse osmosis]], the process is reversed by applying a pressure greater than the osmotic pressure. This has applications to desalinization, for instance.
[[The theory of the reverse osmosis separation of solutions using fine-porous membranes|http://www.sciencedirect.com/science/article/pii/0021979780904671]]
http://physics.stackexchange.com/questions/212183/physic-explanation-to-osmosis?rq=1
[[Capillary osmosis through porous partitions and properties of boundary layers of solutions|http://www.sciencedirect.com/science/article/pii/002197977290392X]]
[[Negative osmosis]]
[[Molecular Understanding of Osmosis in Semipermeable Membranes|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.024501]]
[[Forward osmosis: Principles, applications, and recent developments|http://sci-hub.cc/10.1016/j.memsci.2006.05.048]]
A particular kind of [[Interfacial force|Interfacial forces]]
* [[Diffusio-osmosis]]. <mark>I think this is what people usually refer to as [[Osmosis]]</mark>
*Thermo-osmosis
*Electro-osmosis
[[Manipulation of Colloids by Osmotic Forces |http://hal.in2p3.fr/tel-00597477/document]]
https://www.wikiwand.com/en/Outer_space
Ovarian cancer is the most lethal gynaecologic cancer, in large part because of its early dissemination and rapid development of chemotherapy resistance.
!!__Dissemination__
!!!__Spheroids__
Spheroids are clusters of tumor cells found in the [[peritoneal|Peritoneum]] fluid of patients that are thought to promote this dissemination.
[[Spontaneous spheroid budding from monolayers: a potential contribution to ovarian cancer dissemination.|https://www.ncbi.nlm.nih.gov/pubmed/23213456]]
__in vitro experiments__
Spheroids can be produced from many cancer cell lines under conditions that favor cell-cell over cell-matrix adhesion
,,Not all cancer cell lines form spheroids, and the features that allow spheroid growth are not well characterized. ,,
__resistance__
A major property is the resistance of spheroid cells to cytotoxic drugs compared to the same cells grown as monolayers
,,drug resistance is proposed to arise from one or more factors, including creation of a physical barrier to drug penetration; induction of genes or signalling pathways that enhance survival, such as drug efflux pumps; and selection for a subpopulation of drug-resistant cells, which could include cancer stem cells,,
-->In the experiments in the paper, the resistance could be completely reversed by dissociating the spheroids.
__spheroid formation__
Current models suggest that spheroids form by aggregation of single tumor cells shed from the primary tumor. Another mechanicsm is clonal expansion.
Here, we demonstrate that //spheroids can also form by budding directly as adherent clusters from a monolayer//
Their experiment suggests that the ability to form budded spheroids does not require supplemental serum or growth factors added to the spheroid media.
//Spheroid budding correlates with epithelial to mesenchymal transition (EMT) markers//
Overfitting and underfitting refer to ways of misstraining a model, i.e., making it have poor generalization error, compared to the optimal model.
[[Bias-variance tradeoff|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=4m1.5s]], see also [[Relation to bias/variance tradeoff|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=1h03m40s]]
[[training error/generalization error|https://www.youtube.com/watch?v=tojaGtMPo5U&list=PLA89DCFA6ADACE599&index=9#t=1h08m20s]]
''Underfitting''. A learning algorithm with a lot of ''bias'', meaning that they impose a lot of a priori structure/assumptions to the fitted functions. These, however, tend to have low ''variance'', meaning that the fitted function doesn't tend to vary much when different training data sampled from the same process are used, they are //stable//
''Overfitting''. A learning algorithm with low bias (it is more //flexible//), which however has a lot of variance, as it fits the idiosyncrasies of the data; it fits the noise.
[[See explanation here|https://www.youtube.com/watch?v=JfkbyODyujw&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=14#t=6m45s]] and [[here|https://www.youtube.com/watch?v=Fs-raHUnF2M&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=16#t=9m05s]]
[img[https://lh3.googleusercontent.com/1vNipHvUofw7v2XurbRcoKWdrha4XwW2Wg6iv_CjnPJ7yaJeLuOGPHEXP5r0bHiXDa5jXmi3gXWzRs-rnOmoWT2qdrpDlhqoPaINOW1e8wCnkcMmsfjL5I7MAnuysZNkA0ZS-AduSU6My_vj8QjrLwgU7PtqeOxEmOHYOzJMm1COtI55peywxXwYc4Ot0XMg3WSk4ctE620Fg-kQuA8Zw86ejVU0wPx4C6f-yYJYDol4KmH_zV43EJREoK0ZJaU0v4j54Luq0_enrS9FA4oPcWX5v4h6hTCXJq3aubFRI-HBAP0Az3Js3cA9ZxPQV0U-1MZBCEdfI-0b87bEVSEAvZ7vsWTfyadsG43bfwc8ZGr4XRhXWYVlGj48WxrpQyTPFhPQMXNoiRURzx5bm4ZHukhomdEE98JJ4c5XqhybUHdIk6qJbUS7BXjcYaBlm3z8bGiBlPtDSdt61a59mbotPi7DS3N-LdHrHUd3PXtG59t_5fHfKi3WpqNS_dJOefgRukPJ0OAK4fE579XHNw_8l0Fi2mAqsP7Y8WNm1lg8yXQI2c6hrlGzWt2jO_4it_Zef_2r=w1269-h675-no]]
[[Deep Learning Lecture 5: Regularization, model complexity and data complexity (part 2)|https://www.youtube.com/watch?v=qz9bKfOqd0Y&index=5&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=25m43s]]
So the simplest model that works seems to work best most of the time. Seems like an example of Occam's razor, and thus related to Solomonoff's ideas on inference (see [[Algorithmic information theory]]). Epicurus principle also related to Bayesian inference, because we give a distribution over models, but we keep all of them.
Hmm, also your error can't be smaller than the fundamental noise in the data. Well it can, but your model will at best be wasteful then.
Oxford Artificial Intelligence Society
[[http://oxai.org]]
In the making...
See AI meetup too
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[[Oxford Centre for Theoretical Neuroscience and Artificial Intelligence (Dr. Simon Stringer) |https://www.psy.ox.ac.uk/research/oxford-centre-for-theoretical-neuroscience-and-artificial-intelligence]]
[[THEORETICAL AND COMPUTATIONAL NEUROSCIENCE AT THE UNIVERSITY OF OXFORD|http://www.neurotheory.ox.ac.uk/]]
''I'' am currently living in Oxford, and thus a big part of my activities are related to it.
[[Buildings in Oxford|https://www.ox.ac.uk/sites/files/oxford/field/field_document/University%20buildings%20map%20(Nov%202014).pdf]]
https://en.wikipedia.org/wiki/The_Headington_Shark
[[Nexus mail|https://owa.nexus.ox.ac.uk/CookieAuth.dll?GetLogon?curl=Z2FowaZ2F&reason=0&formdir=2]]
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[[Slack channel|https://ox3dp.slack.com]]
[[Website|http://oxford3dprintingsociety.com/]]
[[Github repo|https://github.com/guillefix/ox3dp/tree/gh-pages]] Using [[Jekyll]]
[[Meteor prototype|http://ox3dp.meteor.com]]
__Domain name registration__
In Wordpress: https://wordpress.com/domains/manage/oxford3dprintingsociety.com/name-servers/3dprintingoxford.wordpress.com
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[[OxLIP+|http://oxford1-direct.hosted.exlibrisgroup.com/V/VT6N7N3NJTRYSDE9DV34734BJYA573A4THBF9K4GV5R8LRFPB4-05770?func=find-db-1]]
[img[http://blogs.bodleian.ox.ac.uk/rdm/wp-content/uploads/sites/126/2014/02/RDM-Site-Header-3.jpg]] [[Research data oxford|http://researchdata.ox.ac.uk/]]
[[ORCID Id|http://orcid.org/]]
Complete New Student Registration. You will find information about this on the Kellogg Freshers 2016-17 site and you will also receive an email from the University giving instructions. Registration opens on 1 September 2016.
https://www.ox.ac.uk/students/registration?wssl=1
1. Make sure that you have returned your __[[University Card Form (filled)|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/University%20registration/University%20Card%20Form%20for%20entry%202016-17.pdf]]__. This will have been issued to you by your Department with your completion of conditions letter. If you have not yet received your University Card Form then it may be that you still have an unfulfilled condition. If in doubt - check with your Department and College.
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__[[Collecting University card|https://weblearn.ox.ac.uk/access/content/group/8b1fed65-4d6b-436f-b6e3-75729e44c7dd/University%20Card]]__
//aka oxidation level, oxidation number//
the hypothetical charge that an atom would have if all bonds to atoms of different elements were 100% ionic, with no covalent component.
https://en.wikipedia.org/wiki/Oxidation_state
https://s10.lite.msu.edu/res/msu/botonl/b_online/library/newton/Chy251_253/Lectures/OxidationLevels/OxiationLevels.html
<img style="background-color:white;" src="https://s10.lite.msu.edu/res/msu/botonl/b_online/library/newton/Chy251_253/Lectures/OxidationLevels/CH4-CO2Levels.GIF">
Not sure if different, but the oxidation level refers is used to indentify which [[Functional group]]s can be interchanged without oxidation or reduction.
Oxford Transhumanism and Emerging Technologies Society
[[http://oxtet.org]]
A [[Chemical element]] composed of oxygen atoms. These have 8 proton in the nucleus.
The hydrogen atom tends to form two bonds, as it has 6 electrons in its outer shell (see [[Octet rule]]).
See [[Measures and metrics for networks]]
There is one potentially undesirable feature of Katz centrality. An important vertex pointing to many vertices makes all those vertices important. The centrality gained by virtue of receiving an edge from a prestigious vertex is diluted by being shared with so many others (think a web directory like Google or Yahoo! pointing to my page. My page is not that central because it's just one of millions). We can solve this by making the centrality derived from neighbours be divided by their out degree:
$$x_i = \alpha \sum_j \frac{A_{ij}}{k^{\text{out}}_j}x_j +\beta$$
or, in matrix form:
$$\mathbf{x}=\alpha \mathbf{A}\mathbf{D}^{-1}\mathbf{x}+\beta \mathbf{1}$$
where undeterminate values $$0/0$$ are defined to be $$0$$. This can also be rearranged to get x and $$\beta=1$$. The result is known as ''PageRank'', the trade name given by Google which uses this measure in their ranking algorithm.
Just like with Katz centrality, $$\alpha$$ has to be fixed and it must be less than the maximum eigenvalue of $$\mathbf{A}\mathbf{D}^{-1}$$, as if it equal the centralities will blow up, and if it is above the answer turns out to be meaningless. The maximum eigenvalue (at least for an undirected network) is $$1$$ (as can be shown using the [[Perron-Frobenius theorem|https://en.wikipedia.org/wiki/Perron%E2%80%93Frobenius_theorem]], see footnote in page 177 of Newman book, and Meyer - //Matrix analysis and applied linear algebra// book. The theorem is very useful in stochastic processes on networks in general).
Google uses $$\alpha=0.85$$
One can see that this measure is mathematically the same as that gotten by the steady state of a [[random walk in the network|Random walk in a graph]], with an added probability related to the ratio of $$\beta$$ and $$alpha$$ of "teleporting" to another part of the network, so that one doesn't just get stuck in nodes without out-degree in the case of directed networks or that one doesn't just recover the simple //degree centrality// for undirected networks.
Any two non-adjacent variables are conditionally independent given all other variables
[[Paleontology|https://en.wikipedia.org/wiki/Paleontology]] is the scientific study of life existent prior to, and sometimes including, the start of the Holocene Epoch roughly 11,700 years before (present) present.
https://en.wikipedia.org/wiki/Paper
Chromatography can be used to separate mixtures of coloured compounds. Mixtures that are suitable for separation by chromatography include inks, dyes and colouring agents in food.
Simple chromatography is carried out on paper. A spot of the mixture is placed near the bottom of a piece of chromatography paper. The paper is then placed upright in a suitable solvent, such as water.
As the solvent soaks up the paper, it carries the mixtures with it. Different components of the mixture will move at different rates. This separates the mixture out.
[img[http://a.files.bbci.co.uk/bam/live/content/z2hcjxs/large]]
!!__Retardation value__
R,,f,, = distance moved by the compound ÷ distance moved by the solvent.
The R,,f,, value of a particular compound is always the same if the chromatography has been carried out in the same way. This allows industry to use chromatography to identify compounds in mixtures.
[img[http://a.files.bbci.co.uk/bam/live/content/zmp4q6f/large]]
[[Dynamics and growth of Dynamics and growth of bacterial colonies bacterial colonies|https://www.newton.ac.uk/files/seminar/20050923100011000-149334.pdf]] Some patterns are similar to [[Diffusion-limited aggregation]]
[[The Mechanics and Statistics of Active Matter|http://www.annualreviews.org/doi/full/10.1146/annurev-conmatphys-070909-104101]]
[[Statistical mechanics and hydrodynamics of bacterial suspensions|http://www.pnas.org/content/106/37/15567.full.pdf]]
[[Geometry and Topology of Turbulence in Active Nematics|http://journals.aps.org/prx/abstract/10.1103/PhysRevX.5.031003]]
[[HYDRODYNAMIC PHENOMENA IN SUSPENSIONS OF SWIMMING MICROORGANISMS|http://www.annualreviews.org/doi/pdf/10.1146/annurev.fl.24.010192.001525]]
[[Excitable Patterns in Active Nematics|https://www.seas.harvard.edu/softmat/downloads/2011-08.pdf]]
[[Defect dynamics in active nematics|http://arxiv.org/pdf/1403.5254v2.pdf]]
[[ACTIVE MATTER - Brandeis University|https://www.brandeis.edu/departments/physics/hagan/research/activematter.html]]
[[[Video] 2D Active Nematic Under Fluorescence Microscopy|https://www.youtube.com/watch?v=jny3Df6xn3w]]
[[Live Soap: Stability, Order, and Fluctuations in Apolar Active Smectics|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.110.118102]]
[[Active Matter - Ramin Golestanian and Sriram Ramaswamy|https://www.researchgate.net/profile/Sriram_Ramaswamy/publication/242653255_Active_Matter/links/0c96052895fdb7044e000000.pdf]]
[[Hydrodynamics of soft active matter|http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.85.1143]]
[[Computer cluster]]
[[GPU computing]]
– Clusters and job managers.
– Jobs vs Tasks.
• Creating and submitting them.
• Getting the results
– Code portability.
– Callback functions
• Advanced parallelism.
– spmd mode, message passing.
– GPU computing.
https://uk.mathworks.com/help/distcomp/how-parallel-computing-products-run-a-job.html
https://en.wikipedia.org/wiki/Parsing
See [[Compiler]]
A ''partial ordering'' on a [[Set]] $$X$$ is a (binary) [[Relation]] on $$X$$, $$\preceq$$ that is:
* ''[[reflexive|Reflexivity]]'': for all $$x \in X, x \preceq x$$.
* ''antisymmetric'': for all $$x, y \in X$$, if $$x \preceq y$$, and $$y \preceq x$$, then $$x=y$$.
* ''[[transitive|Transitivity]]'': for all $$x, y, z \in X$$, if $$x \preceq y$$ and $$y \preceq z$$, then $$ x \preceq z$$/
A set with a partial ordering is called a [[Partially ordered set]] (or poset).
A [[Pre-order]] is a weaker kind of relation
For many common examples, the [[Partial ordering]] $$\preceq$$ is often interpreted as $$\leq$$ (or less than or equal).
A ''partially ordered set'' (or //poset//) is a [[Set]] with a [[Partial ordering]]
[img[http://i.imgur.com/IJdAffv.png]]
A partially-observabe [[Markov decision process]] is a Markov decision process where the state is only partially observable by the actor, so that the policy can only depend on a function of the state, which looses some of the state's [[Information]]
!!!__[[Kalman filter]]s and [[LQG control]]__
[[video|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=46m50]]
A type of reinforcement learning, where we don't observe the state explicitly!
[[Want to estimate actual state, given the noisy and incomplete measurements of the state|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=53m40s]]. Can use the method of marginalization, as used in [[Factor analysis model]]s. However, it is very computationally expensive. Instead we use a [[Kalman filter|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=55m52s]] model, which turns out to be a [[Hidden Markov model]] with continuous states.
[[Outline of Kalman filter|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=57m35s]]
* [[Predict step|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1h22s]]
* [[Update step|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1h03m30s]]
[[Intuition|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1h7m40s]]. I think this can be seen through the lens of [[Sufficient statistic]]s
Kalman filter + LQR = [[LQG control]] <- [[video|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1h8m55s]] <-- [[how to solve|https://www.youtube.com/watch?v=UFH5ibWnA7g&list=PLA89DCFA6ADACE599&index#t=1h9m50s]]
[[Separation principle|https://www.youtube.com/watch?v=UFH5ibWnA7g&list=PLA89DCFA6ADACE599&index#t=1h14m32s]] of LQG control
[[recap|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=0m50s]]
!!!__Other POMDP__
[[In general finding optimal policies of POMDPs is NP hard|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=3m55s]]
[img[http://www.lassp.cornell.edu/sethna/Sloppy/SloppyFigs/Hierarchies/HEPCropped.jpg]]
[[pastes|http://pubs.rsc.org/en/content/articlehtml/2007/sm/b611021p]]: materials that can be deformed easily (like liquids), but keep their shape after the force is applied (like solids).
Two common qualitative characteristics of the structure may be distinguished: disorder, as in most of these materials no specific arrangement can be distinguished, which explains their ability to be deformed at will without losing their mechanical properties; and crowding as the elements making up these materials interact significantly with their neighbours, which explains the solid behaviour of these systems as long as the applied forces are not too large, and from that point of view we are dealing with //jammed systems//.
Pastes typically consist of a suspension of small particles in a background fluid. These particles are crowded, or jammed together like grains of sand on a beach, forming a disordered, glassy or amorphous structure, and giving pastes their solid-like character.
[[Rheology of Soft Glassy Materials|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.78.2020]]
[[Condensed matter: Memories of paste|http://www.nature.com/nature/journal/v410/n6824/full/410032a0.html#B1]] The authors make a remarkable observation: although the sample was completely fluidized by the large shear stress, it developed a 'memory' of the direction in which the stress was applied, and the solid-like paste slowly 'pulled back' on itself in the opposite direction, eventually passing beyond its initial position.
[img[http://www.leica-microsystems.com/fileadmin/_processed_/csm_Figure-3b_2e4637ba06.gif]]
A ''path'' (sometimes called a 'walk')in a network is a sequence of of nodes such that every pair of nodes in the sequence is connected by an edge in the network. For directed networks an edge must be traversed in direction of edge; in undirected, in either direction.
//Self avoding paths// (a.k.a 'simple paths')don't traverse the same node or edge twice.
The //length// is the number of time one traverses an edge in a path. However, sometimes it is defined as the number of nodes.
$$A_{ik}A_{kj}$$ is only non-zero if there's a path of length 2 from i to j. The total number of such paths is $$N(2)_{ij}=\sum_{k=1}^{n}A_{ik}A_{kj}=[A^2]_{ij}$$. Similarly, the total number of 3-paths is $$N(3)_{ij}=\sum_{k,l=1}^{n}A_{ik}A_{kl}A_{lj}=[A^3]_{ij}$$. In general $$N(r)_{ij}=[A^r]_{ij}$$.
__Cycles__ are paths that start and end at same vertex. The number of cycles of length $$r$$ is $$\text{Tr}[A^r]=\sum_i \kappa_i^r$$, where $$\kappa_i$$ is the ith eigenvalue of $$A$$. This can be proved by the //[[Jordan decomposition|https://en.wikipedia.org/wiki/Jordan_normal_form]]// of the matrix if it is diagonalizable (so the nilpotent part is zero, i.e. there is no 1s above the diagonal). Otherwise one can prove this using the //Schur decomposition//
A __simple cycle__ is a self-avoiding cycle.
!!Geodesic path
Shortest path between two points, defining the geodesic distance. They are always self-avoiding because any loop could be removed to make the path shorter. By convention we sometimes assign a distance of $$\infty$$ to unconnected nodes. They are not necessarily unique.
The //diameter// of a graph is the longest geodesic distance between any pair of connected nodes.
!!Eulerian and Hamiltonian paths
An __Eulerian path__ is one that traverses each edge in a network exactly once. It is not self-avoiding in general because a node with a degree higher than two will need to be visited more than once.
A necessary condition for a graph to have an Eulerian path is that there are zero or two nodes with odd degree, the first case corresponding to beginning and ending the path on the same node, and the second case, beginning and ending on different nodes.
See [[Seven Bridges of Konigsberg|https://www.youtube.com/watch?v=eIb1cz06UwI&list=PLoJC20gNfC2gmT_5WgwYwGMvgCjYVsIQg]]
A __Hamiltonian path__ is one that visits each node exactly once. It is self-avoiding because traversing an edge more than once will imply traversing a node more than once.
The general problem of finding Eulerian or Hamiltonian paths in a graph or proving their non-existence is hard and still actively researched. This was used by Euler to solve the famous Konisberg Bridge problem in 1736.
These paths have applications in computer science in: job-sequencing, "garbage collection", and parallel programming.
The Markov property of many [[Stochastic process]]es means that one can naturally construct a [[Path integral]] description. This can be used to [[draw parallels between stochastic processes and quantum mechanics|Stochastic-quantum analogy]].
__From Langevin equation to path integrals__
We begin with the general Langevin equation with no inertial term, but a deterministic force. We also assume the noise term is [[Gaussian white nosie]]
[[Ito/Stratonovitch dilemma]] and [[Multiplicative noise]]
--------
See also
[ext[State-dependent diffusion: Thermodynamic consistency and its path integral formulation|journals.aps.org/pre/abstract/10.1103/PhysRevE.76.011123]]
https://en.wikipedia.org/wiki/Pathology
The study of the abnormal (an often restricted to detrimental) function of a biological organism.
In medicine, a [[physiologic|Physiology]] state is one occurring from normal body function, rather than pathologically, which is centered on the abnormalities that occur in animal diseases, including humans.
See section 7.12.2 of Newman book.
It is the number of common neighbours minus the expected number of common neighbours if edges were random ($$k_i k_j /n$$), normalized in a certain way. It is also the covariance between two rows of adjacency matrix divided by the product of their standard deviations:
[img[pearson_coefficient_network.png]]
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
See [[Deep learning]]
http://ronan.collobert.com/
https://scholar.google.co.uk/citations?user=_WnkXlkAAAAJ&hl=en
[[Geoffrey Hinton|https://en.wikipedia.org/wiki/Geoffrey_Hinton]] https://www.youtube.com/watch?v=GJdWESd543Y
[[http://www.iro.umontreal.ca/~bengioy/yoshua_en/research.html]]
Yann LeCun
[[http://people.idsia.ch/~juergen/]]
[[https://www.quora.com/Who-is-the-father-of-deep-learning]]
[[http://www.robots.ox.ac.uk/~karen/]]
A bond formed by [[Dehydration synthesis]] between a [[Carboxylic acid]] group, and an [[Amine]] group. These are the basis of polypeptides, such as [[Protein]]s
[img[peptide1.PNG]]
The nature of the chemical bonding within a peptide accounts for the bond’s planarity. The bond resonates between a single bond and a double bond. Because of this double-bond character, rotation about this bond is prevented
[img[peptide-resonance.PNG]]
[img[peptide-bond-lengths.PNG]]
There are two possible conformations, the //cis// and //trans// conformations, but, for [[Amino acid]], due to to [[Steric hindrance]], the trans is by far the most common. for X-Pro bonds, both have steric hindrance and so both kinds appear.
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
The term "perceptron" was introduced in the 1950s to designate
a simple mechanism to achieve "perception."
See [[video|https://www.youtube.com/watch?v=HZ4cvaztQEs&index=3&list=PLA89DCFA6ADACE599#t=1h10m]].
It is basically a [[Feedforward neural network]], with 0 hidden layers, and [[Heaviside step function]] activation functions. They are a simpler version of [[Logistic regression]].
https://www.wikiwand.com/en/Perceptron
As most older models, the original perceptrons, had threshold activation functions (see [[Hopfield network]]).
The hopes to build "[[seeing machines|Computer vision]]" vanished when Minsky and Papert published their
book Perceptrons [1969], in which they rigorously demonstrated that
perceptrons are quite limited in their ability to extract global features
from local information. They could only implement linearly separable classification.
!!__Multilayer perceptron__
However, the reaction was too drastic, because adding more layers to the [[Feedforward neural network]] (giving so-called "multilayer perceptrons"), avoided the issues pointed out by Minksy and Papert.
Multilayered perceptrons work essentially in a manner similar
to the prevailing neurophysiological view. According to this view, on
arrival at the cortex, sensory information is subject to a hierarchy of
feature extractions. Further comparison with the [[Cortex]], is done in the Corticonics book (pages 200-203)
Generally, ''percolation'' refers to qualitative changes in connectivity in systems (specially large ones) as its components are added or removed. In particular, percolation most often refers to the case where a system goes from being "mostly disconnected" to "mostly connected", in some sense. A more general mathematical model inspired by percolation and the [[Potts model]] is the [[Random-cluster model]].
[[Percolation theory|https://en.wikipedia.org/wiki/Percolation_theory]], from the perspective of [[Network theory]] describes the behavior of connected clusters in a network (often modelled as a [[random graph|Random graph]]), as some substructures in the network are added or removed. The most common types are random site and bond percolation, where one removes either nodes or edges with a uniform probability, known as the ''occupation probability''. However, there are other types (see below).
Again, from the perspective of networks, the transition from the system being "disconnected" to "connected", is most often made precise by the appearance of a ''giant connected component''. See below.
,,Often, the theory of percolation is concerned with the clustering properties of identical objects which are randomly and uniformly distributed through space with a given occupation probability. However, these uniformity assumptions may be relaxed in other types of percolation.,,
Keywords: [[Network science]], [[Complex systems]].
[img[http://i.imgur.com/WyFMY2q.png]]
from [[here|http://www.sciencedirect.com/science/article/pii/S0370157315002008]]
!!!__References__
Newman's book, and Mason and Gleeson tutorial have good reviews. See more at [[References for percolation]]
!!__[[Percolation theory]]__
Mathematical theory of percolation, with several important results, and discoveries.
!!__Percolation [[phase transition|Phase transition]]__
!!![[Percolation phase transition]]
A phase transition occurs between a phase without a ''giant connected component'' and a phase with one. A giant connected component, or GCC, is a connected component that contains a finite fraction of the nodes as the network size $$N \rightarrow \infty$$, i.e. it has an "extensive" scaling. The transition occurs at a critical value of the occupation probability, known as the ''percolation threshold''.
!!![[Critical phenomena in percolation]]
!!__[[Types of percolation models]]__
Main types:
* Site percolation
* Bond percolation
* K-core percolation
* [[Explosive percolation]]
* [[Bootstrap percolation]]
* [[Directed percolation]]
* Limited path percolation
* K-clique percolation
* Percolation in Multilayer networks
* etc.
!!__Applications of percolation models__
!!!__Applications to porous materials__
!!!__[[Applications to the study of landscapes|Application of percolation models in topography]]__
Applications in topography (study of landscapes) has been found, in particular relating to:
* Statistical and fractal properties of watersheds.
* Percolation of water bodies as water level rises in a landscape.
The Bethe lattice is defined as a graph of infinite points each connected to z neighbors (the coordination number) such that no closed loops exist in the geometry
[img width=300 [http://i.imgur.com/26IMEOd.png]]
They are related to Cayley trees.
Several results exist for [[Percolation]] on these lattices. For instance, their [[Percolation threshold]] is $$p_c = 1/(z-1)$$, for any $$z \geq 3$$.
[img[http://i.imgur.com/uubwz9d.png]]
See also the chapter on this on the phase transitions book by Sole.
[[Percolation]] on hypercubic lattices, which can be represented as $$\mathbb{Z}^d$$, where $$d$$ is the dimension of the lattice, and $$\mathbb{Z}$$ is the set of integers of course.
Some mathematical results exist for [[Percolation threshold]]s, and [[Continuity of percolation phase transition]]. In particular, it is known that the percolation threshold at dimension $$d$$ is greater than or equal that of dimension $$d+1$$ for percolation on $$\mathbb{Z}^d$$.
See [[Percolation theory]], [[Random graph]]
See [[the chapter of the book|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/Networks/%5BMark_Newman%5D_Networks_An_Introduction(BookZZ.org)%20(randgraph).pdf]].
If we let $$u$$ be the probability that a randomly chosen vertex in the graph does not belong to the giant component, then
[img[http://i.imgur.com/DKYzRPK.png]]
[img[http://i.imgur.com/XLaKJIa.png]]
[img[http://i.imgur.com/SS2eBjf.png]]
[img[http://i.imgur.com/QvqHZDV.png]]
[img[http://i.imgur.com/XHrra74.png]]
See [[this chapter|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/Networks/%5BMark_Newman%5D_Networks_An_Introduction%20(randgraph-gen-deg).pdf]] for random graphs with general degree distributions, and [[this chapter|file:///home/guillefix/Documents/%5BMark_Newman%5D_Networks_An_Introduction(percolation).pdf]] for percolations
!!!__Giant component and phase transition__
Percolation is the simplest fundamental model in statistical mechanics that exhibits [[phase transitions|Phase transition]] signaled by the emergence of a ''giant connected component'' (or GCC, it is a connected component that contains a finite fraction of the nodes as the network size $$N \rightarrow \infty$$, i.e. it has an "extensive" scaling, in the language of [[Statistical physics]]). The parameter that controls the existence of a GCC is the occupation probability, $$p$$ (or the "attach probability" $$q=1-p$$), the critical value at which the transition happens is called the ''percolation threshold''
In particular, the transition is often a //continuous transition// (2nd oder) with a critical point. Behaviour at this point is thus an example of [[Critical phenomena]], and at this point the system is self-similar (see [[Fractal]]s), and as a consequence, many quantities follow [[Power laws]]. See section 12.2, and exercise 12.12, as well as exercise 2.13 of [[this book|http://pages.physics.cornell.edu/~sethna/StatMech/]].
__Percolation threshold__
For random site percolation on a [[configuration model|Random graphs with general degree distributions]] graph:
$$p_c = \frac{1}{g'_1(1)} = \frac{\langle k \rangle}{\langle k^2 \rangle - \langle k \rangle}$$
where $$g_1(z)$$ is the generating function of the excess degree distribution. See Newman's book.
Note that even if there is a GCC, its size may be small, so a full understanding of the network's resilience should include the dependence of the size of the GCC with $$p$$.
__[[Critical phenomena in percolation]]__
The [[mathematical|Mathematics]] theory of [[Percolation]].
!!!__Basic concepts__
//Cluster//: a connected component of the occupied subgraph (the graph obtained after removing edges in the percolation process).
Probability that there exists an infinite cluster.
__Probability that there exists a //giant cluster//__ ,,(or giant component, or giant connected component (GCC)),,, defined as a cluster with size (number of nodes) or [[order|Order notation]] $$O(N)$$, as $$N \rightarrow \infty$$ ($$N$$ is the size of the whole network).
A related, but different quantity is the __probability that a node belongs to a giant cluster__, $$P_\infty$$. Often it's easier to work with $$u$$, the probability that a node is //not// connected to the GCC.
Another property of interesting is the __[[Distribution of sizes for the small clusters in percolation models]]__. A related quantity is the the mean cluster size.
The __two-point correlation function__, $$g_c (r)$$ is defined as the probability that if one point is in a finite cluster then another point a distance $$r$$ away is in the same cluster. This function typically has an exponential decay $$g_c (r) \sim e^{-r/\xi}$$, $$r \rightarrow \infty$$. $$\xi$$ is then the __correlation length__, or connectedness length. Note that the correlation length can also be defined in some other ways that measure the characteristic size of clusters, in particular one can use the radius of gyration to define it.
See [[here|http://physik.uni-graz.at/~cbl/CP1/contents/Texts/sec_3.pdf]]
!!!__[[Percolation on hypercubic lattices]]__
!!!__[[Percolation on Bethe lattices]]__
A model which is particularly tractable analytically.
!!!__[[Percolation on random graphs and networks]]__
!!!__[[Percolation threshold]]s__
There are some exact results for some models, in 2D for the square, triangular, honeycomb and related lattices, but not for many others, like site percolation on the square and honeycomb lattices, and bond percolation on the kagomé lattice.
!!!__[[Continuity of percolation phase transition]]__
!!!__[[Continuum limit of percolation models]]__
The continuum limit, at the critical point, it is often a [[Conformal field theory]], as percolation models at the critical point are found to have conformal symmetry.
A relatively new method to describe the continuum limit of the critical lattice models is [[Schramm–Loewner evolution]]
!!!__[[Relations between percolation models and Potts models]]__
!!!__Infinite clusters__
There are some results on the number of possible infinite clusters which can coexist
[img[http://i.imgur.com/tWnpYRF.png]]
See [[Percolation theory]]
The values of percolation thresholds are not universal and generally depend on the structure of the lattice and dimensionality, and are believed to achieve their mean-field values only in the limit of infinite dimension ([[Some Cluster Size and Percolation Problems|http://scitation.aip.org/content/aip/journal/jmp/2/4/10.1063/1.1703745]]). Finding rigorous proofs of exact thresholds and bounds has also been an enduring area of research for mathematicians ([[The critical probability of bond percolation on the square lattice equals 1/2|http://link.springer.com/article/10.1007%2FBF01197577]], [[A bond percolation critical probability determination based on the star-triangle transformation|http://iopscience.iop.org/article/10.1088/0305-4470/17/7/020/meta]], [[Percolation - Grimmett|http://www.springer.com/gb/book/9783540649021]]).
Exact thresholds (for bond percolation) in 2D for the square, triangular, honeycomb and related lattices were found using the star-triangle transformation ([[Some Exact Critical Percolation Probabilities for Bond and Site Problems in Two Dimensions|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.10.3]]). It has been shown in [[Exact bond percolation thresholds in two dimensions|http://iopscience.iop.org/article/10.1088/0305-4470/39/49/003/meta]] that thresholds can be found for any lattice that can be represented as a self-dual 3-hypergraph (that is, decomposed into triangles that form a self- dual arrangement). It is also shown in [,,G.R. Grimmett, I. Manolescu, Probab. Theory Related Fields,,] that thresholds can be found for any lattice that can be represented geometrically as an isoradial graph, yielding a broad new class of exact thresholds and providing a proof ([[The critical manifolds of inhomogeneous bond percolation on bow-tie and checkerboard lattices|http://iopscience.iop.org/article/10.1088/1751-8113/45/49/494005/meta]] of Wu’s 1979 conjecture ([[Critical point of planar Potts models|http://iopscience.iop.org/article/10.1088/0022-3719/12/17/002/meta]]) for the threshold of the checkerboard lattice.
However, the exact value of thresholds for many systems of long interest (such as site percolation on the square and honeycomb lattices, and bond percolation on the kagomé lattice) are still missing ([[Recent advances and open challenges in percolation|http://link.springer.com/article/10.1140%2Fepjst%2Fe2014-02266-y]]).
There exist also bounds on the percolation thresholds for infinite connected graph with maximum finite vertex degree. See Grimmett's book.
The percolation threshold for bond percolation is less than or equal to that of site percolation.
The vertical columns in the periodic table are called groups. Each group contains elements that have similar properties, because they have the same number of [[Valence electron]]s.
!![[Cool interactive periodic table|http://elements.wlonk.com/ElementsTable.htm]]
http://www.bbc.co.uk/education/guides/zsp4jxs/revision/7
Elements in the same horizontal row are in the same period.
http://www.bbc.co.uk/education/guides/zsp4jxs/revision/4
See [[Atomic structure]]
Development of the periodic table: [["Law of Octaves"|http://www.bbc.co.uk/education/guides/zfn9q6f/revision]], [[Mendeleev's periodic table|http://www.bbc.co.uk/education/guides/zfn9q6f/revision/2]]
[[Some properties|http://www.bbc.co.uk/education/guides/zb3j6sg/revision]]
[img[periodic table.png]]
[[Chemical element]]s and [[Chemical compound]]s
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0pI/ip0BaINdvfIrs4BeEMg22xCAPvqWeLcXccFzM7qET8cJmS4sErpUqQc9Vex1liqg88pCaQL6wluyv8QKV2rS7BVCQ+kArddO+eef7ODLRDFdfcIwoLOqiph0lEoO6Ly5Q/KQz8/oSj9w2Xk5mb7eG/mnqQqgRbjfbECLVIeUB/SV45KA1jtNxE5eqVPAOKDNFEvSa6f836sr+UH7VJIa7OrLhgGdS7GJDQDoii7f845aSpdMO3AilE1BicjYkjagl1sP6DfECnEWD2jtXCGR/ZM6BcoJaM12msptDg1AG+zqiX9YB9BFrdTTNoBO7S0KR+3CWxLXPaKATh20aCagxXjRNECL1knWBXRaccgJY6eJEOfkToF1A+gL6oDOX9Td4LYVC2ihjVtuf0BLx03fOG4O0MuFA9r71JUmANp8Ekchi8aqAfoNSUBrniYGAR39VNkArdlOhQLaYFc3D2gxb+ToWwC04aOWceCuCPXON3IBLZKd1X6AviJxYIr3oAsCtMYpAEC3ENAX3jIOaLETXjetY0MAOtxFBFggBmixtJ+CAX2lPIAezmv7qbIDWqT9NE6BdQPo1AozJQC0VFfXBHRTCL2hPWgtQMODzjtZY4fWIKAFBgnhQcODLhrQYkG9ykYGtPzPkw6gSz5I2EpAN/SlxuOqB2jZPGjt1b42yCChZjs1D9AFdHVtQIvllC4D0AB0qwGdX9UMgAag1x+gReIcWgOF7QfoyNebC2ixrOPIETvaxDzoFgJaoCKOJqDT8teFWsYcoDVOgXICWrOdmpdmV1ZA/yp/wuPyxgW0PJN0AC1wOv4qZRqZSMdu44kqUwKxXIOArrTup0v9FGgDQMu3U/MAXUBXNwXohEtIY1Ho9gN0pCmaDGiRWS4pKBGo4aBSLEl1ZWqzgBYaOtMD9JTIZfCEsdNEzFtqbS0O81O9Swbooru6SUBnRaR1YhxtCOgFLadRC9DDIluejBKBKmhXdKvZtQzQIu0SOezSgE69VBBrGXPXFhqnQDkBrddOxQK64K5uHNApQWkd/6ANAT2sxSQtQEsnywVn1XD+T6pKwX4Bs00o2C9y3Z/VG/JnD8kveTVczE+XxilQTkDrtVOxgC64qxcD6MZus8EAnREJKBrQIkGxlBNSIAowpQDo/NM/9NWilrwSGswZFpxJmPxHUuvki601Y64Qq8YpUE5A67VTsYAuuKsXBuh4SHp5QwFabGx3OOVXVwvQIiHfFD84f22qK8cVAJ0/Shgye/StJgD6qMDanpmArkj9eIm1jPRpItj1pE6BcgJar52KBXTBXb1AQIsNJq9PQAtFpsJ/5MJbxgCdH1FIrdCcu/bElKMA6Hy2Tem0tTlAZ/5A5S5OlF71XbBlZE8TwQjb0Vau6m0G0HrtVCygC+7qRQL6yvGNC+iMLNPEblQx50Hnl/dMPR/zlrCMsVAU0Hnnf/iby80AtEgWRiagk/5KOsEFW0b2NBEkndwpUE5Aa7VTwYAutqsLAzo1NriQehTe2MCAFkj+TV8OWA/Q+fX+U6/Fo6xr+Gp8rrQooPPWVFkw5weIAVqgm+YAunE7M6I/oi0jeZqIXsBJnQLlBLRWOxUM6GK7ujCgE/7ycA6835BeL379AFpg2aqF1D6kCei8UHL6KtuxwiqVrEaRAHROY4RPM92LFUFA5y7PmQfoBgtvZGyFcstknybCLrTMKVBOQGu1U8GALrarZwI6600Bx15ovdv1CuhoF8lbcnfZ4CBh3vBs1kDfcAajGstiVdR+MmJni+6FlkqaXcKnGkopZQM6a+fjuyjcMnKnifD4j9QpUE5A67RT0YAutKuLAzrWrfKPg9C4+boFdKxDZ3op8dbRBXSWNxfrnLHtilMqtGHu9547rgDoWGNEdlf7NFGZqJLtxgsBOmJiOPO74i0jdZqI+wcyp8Cvmraqd3YWkbl2KhrQhXb1TEBnRlcW8qZyG5vh256Ajp+okSOTDRVdQGddji9kUqgRQ+7f9wn0fyoB+o3UrPgr2isWqkz1Trk6uDAlAejgIws582azWkbjNJHwD2ROgXICWqOdCgd0kV09s59nXii9kT0T5Y3jpuaptCmgEya9Lyc2a6N9bUA3dBLXSsPrueOADbx+QwnQDQxzT4grx/ULAigVS4psvv9OZUEO0GlaljhW6qeJHCeFT4FyAlqjnQoHdJFdPRvQC1lXbhl+Q0M332DlRuW6dEPjaANadO29hN/NnI2eUAS0WLdVSvVRKzea+OvzlgCgB/8/6eK6cp1M+DSRahaJU6CcgFZvp+IBXWBXz26T4bQTWfJI6FXqaldACzZQ43HRB7TYGZN0WLI3+sJbioAW4oVaHEwU0PmHYyIr53jB72MLsgc0u2WUTxMT/kFizywnoJXbqQmALq6rZ7dJygWva0l8iWS9OjDtCmixw5bjxSoCOrP2q0w2cPxAqgJawIEttlhS/vlK/n74IynDORO5h3VZ8lipniZymRwSp0A5Aa3cTk0AdHFdXckR8ywVdHG2bgAtctiSOp4JQAv86WXpUEDlV+qA/tWCaRdReiRtOPfvv5ELaHq8sgP1E0UcK5VrUOVToKSAVm2nZgC6sK6e0ybJp6JvaaEZfG5jQOcftsSDYgLQuX86vcsviCJMDtA5Z4vyWSKR6rCQ1x4ZdS8WQpuZRehKAcdK8cdL9RQoK6AV26kpgC6qq+e1yXD2nxqWOgAbD9BqVDIC6JxL3CweLmScYRqAzjxb1NtYJhdtIQ9W6WxaCL+YTugJtWNV0I+X2ilQWkCrtVNzAF1QV1dye9IWLDY/Ptj+gM5soeV8jGgAOivomt3vMn6WdQCd0RYapVqkkoWHc7pPehrHQuRwpGFoWfVYKZwmmrkcYsuflwzQKu3ULEAX0tXz22Qhx1kfLnB4cD0AOr2TTIj4eTqATv1Rn1DoZZXGv1uR36Jh82eJ3GyOZH4sJxmrJDRlJfOoVnSOlfRponUJNyHod5cN0Art1DRAF9HVBdqk8Y/GLA0Xiuf2B3TiSZt1ZWEO0Oqrj6UVl9AEdNIGLRv9/VuWPhjhBkkPQi80WB8WjdKIHivJ00TdQcixWm5AS7dTEwFtvqsruT0NlhIPirElfFoA6AJ05bgxJGlEImV+Mv1z48JbhW3Q0bdacjAWDG1AcFAnyn2aTJn2mjZwdyrltg3nDyhPOQWdBOsD0BAEQetQADQEQRAADUEQBAHQEARBADQEQRAEQEMQBAHQADQEQRAADUEQBAHQEARBADQEQRAEQEMQBAHQADQEQRAADUEQBAHQEARBADQEQRAEQEMQBAHQEARBEAANQRAEQAPQEARBADQEQRAEQEMQBAHQEARBEAANQRAEQAPQEARBADQEQRAEQEMQBAHQEARBEAANQRAEQAPQEARBADQEQRAADUBDEAQB0BAEQRAADUEQBEBDEARBADQEQRAAnQ5oCIIgqKUCoCEIggBoCIIgCICGIAgCoCEIgiAAGoIgCICGIAiCAGgIgiAIgIYgCAKgIQiCIAAagiAIgIYgCIIAaAiCIAiAhiAIAqAhCIIgABqCIAiAhiAIggBoCIIgABqCIAgCoCEIgiAAGoIgCICGIAiCAGgIgiAAGoIgCAKgIQiCIAAagiAIgIYgCIIAaAiCIAAagiAIAqAhCIIAaAiCIAiAhiAIggBoCIIgALq5er+0xsq8bTAGYzBWUm68Lw/ottwbABrGYAzGAGgAGqcnjMEYjAHQADSMwRiMAdAANM4oGIMxGAOgAWgYgzEYgzEAGoCGMRiDsQ0K6J2LP/2Zob157zOLi8asbfk2MTZhsKE/8uHFxctGzLFNo/p7I9u2h7baQQNb5m+XiL33RY/nQTOHgBn7exPHMzhj6SFdfHu3GWMCfUHcmEBXEDcm0BWkdjOvJwgbE+kIEluW3xEEjYl1BNmjebAlgB4xh9SdbptMmLA2IgoaYUBTi2YAzY6XKUAzyIhtWpMBvWfR2Jb5xrJpKmQsOGPd45C5r+9LnP4jmkwNvi/SFYSNiXQFmd3M7QmyB0AH0IExkY4gaMwIoIMtE+oIBQF6jzmfd8RvlMv61vwmNkJ73+Jls3tqAtBeXxZAlwSgDWyZ3/sEfiTfF24y7eMZnLFej85suvfFT/89mk5v8H2hriBqTKgrSOxmfk8QNibSEYSN7TR3NMU6guiWiXWEQgDNd8QMoGl3IW1LTeazRqRDk+bYY4YOwfE3A+g9gtfqohi87N4aulQgxkz8rO1hZ4ahLdvJzoo9Qifb+4Jn7Ii3gVk2RY0J9QVBY2JdQWY3c7vC+xK9fKeOnxoxJtIRRI0JdYT3pWCW0xFEjYl1hCIA7V0iGgE03aXL/HwyAOidzBixqdmhYy6cEUCLBrNFMUiba6epgDbbPCOBoZ3cZzOyZe7JQVtOy1jkjHW3bKeqmxQxJtQXBI2JdQWJ3czvCu+L9/IRnUBCxJhQRxA1JtQR3peBWV5HkDgAAh2hIEC//Y1vmxsk9I6/AUD7G2jIgybn99ufNARo2ldOGKK9GLKkWk3Qvxf56TAJaHaW7RSJcbwvdsZ6eNiTaVPQmFhfeF+uL+kAOm4spyuIGxPoCaLGhDqCxNH8e1OnhlhHEDW2p3WA/oODgk6qBKB1+6A8vd4X26rLprI4/JiUgUACo8zORYPHgB7Qg4Z2Mz+CIO9Ba/16h89Y714dg+HTX6gvvC/Xl3Yq/3Q0GMvrCuLGBHqCcJt9Ri86HjYm1hFk2iy3I0jspkBHKCqLwzSgRxaNRSV2LhryBdlWTRhLszM5GhoMZxj6JRIOkDc1i8Ml88iigcsrY4BuOP11AJ3w/ZyuIGMstysIGxPpCaLGDIyFho+mQEeQabPcjiBsrJVZHKYBPWIu8YIN0otsm9Bg6E8PGgP0ToOjocF5aehnTdSBFjG2x1zcPujLGwbQI3ppdmFj+V1B1JhQTxA1tlN3LDQR0IZ+1PI7grgxkY7QHoAeMZPqKrdxQr7gZYMTVYSiguKAJrtI78wEhkYEZ/dIZDoaSAAMkqg2DKBzu4KcO64+SBj5tlBPkNuynI4gAej8jiCxZfkdQeJHTeDUbQtA7zE8+U8MNyLR1Ik144AWajkRQE+smRtaFc8wkbhQMJJfwhzKPRsG0Ht0J/9taRxx1CeXWE+Q3LLsZpMA9ITBoynQEeQvFJo9SGga0HsWjdEhOCsNcGvP4qLJGRwmAe0N/pgCtHCEQzjxwmRWjpER5C2msjiKBLRAV5AHtD65xHpCKwAt1hHEt0ygIxh1BNoB0KKzxteER/3X9pQQ0KEsVwMTqnea9aBHxEJMTQc0303tXKq4Z6OVB10goEW6goRrmd8VWgFosY4gcTRNetACp+1GA7RYQpa4Y0kOOs3jMRDiMOxB72TbZihsPMK2ie6vkRj0HtEQtGjihbndJCfHHhNjoeEkAr2ZhIUBWqgrSLiW+V2hJR60UEeQSQnJ7QhSlzAT5g6AQEcoP6B3mhuoD436m8rZMxiDNrptfkEJMzu6U3jei8TPWrlqq8gN3rQE0EJdQTqZzdTv0JrxNDsTWybUEcR3U6AjSAysLurUcSoJoP2sdTMX60ZLqZkFtNlt8zBjxJjELHTxX9wJg21mIMUnOGMNVLMrBNBiXcFoGm5LAG12y0Q6grAxkY4gbEyoI5Qe0EGmq5loKjvLheKpTQc0P5eMbdtOc1WXjQLabH1vZuyygS2LDdXr1YMuBNBiXUF8ywS6QmsALdIRJLZsp2496IIALdQRsKJKkzYN60nAGIzBmDlrADQADWMwBmMANAANYzAGYzAGQAPQMAZjMAZAA9A4PWEMxmAMgAagYQzGYAyAhiAIgponABqCIKjtBEBDEAQB0BAEQRAADUEQBEBDEARBADQEQRAADUEQBAHQEARBEAANQRAEQEMQBEEANARBEAANQRAElQnQHzUltDIEQetMK6YEQEMQBAHQADQEQQC0EqBvPbx262MANARBUBkBPfIkPGgIgqAyAvor25sb4vjuHwDQEAQB0Am6eHzwdBTQv7vzYXlAf/evLivy+dZQfwTQN53D9G7k4eS/98DTD8Ze+LvdW37vQZwJEASVE9DnhxznQp8aoF883X0mFuLY8vXd0oB+bfCyGQ96S8+PLhxM4HCqNlXWDn3tIM4ECIJKCejzQwSx80cVCb3SfSw+SDgiO0j43dcdU4DedOHfDvXJAHq0jzrROBMgCColoLtpkOLi06fV+Hz+Wf00u639t542BOjRo9/oqaw9QK4JDhNv2nEqFNb/iT6lr/UxcruvEx0ad5iOgtAQBJUzxMFiyYqAPv+TPhN50KYAfWj88NrNCwddDlfY/w8MEf7epBAm75A36GuHxvvcL3ztIHWiIQiCygto1RDHvOOcaS2gI2l2myich7ijTB/TmwdYzMMNfPB/wd/HGCEEQWUH9LXB0y2dSWgK0KOVNe41U0DTwIUHZO+G/GPg9nTzMMYIIQgqNaCvOcdW1gOg3Zgyi2SIABoxaAiCyg7oeV3/uSyAvsnY+8BQHwP04IM8xBEDdDjEQcMbNw/jPIAgqKyAvqaaBF02QNPgBr+jg4D+IGEM0N7rzIXGGCEEQWUGtHKGXekAzUYCqSM9+OCoUwnS7KKADqXZ0WkqGCOEIKi8gL7G47DHUG4UgiCobCEO1IOGIAgCoAFoCIIgABqCIAiABqAhCIIAaAAagiAAGoCGIAgCoE0D+iZLGkyffDLa8N6h8QuoxgFBEACdCOitMzMfZg9+8PszM3+kBWha9dmtxwFAQxDU/oDunpl5hz3Y3jMzc39bA3pLD58jeGg8tQASAA1BEADdCkBv8uZwHxoffBCAhiAIgC4hoAmH3YebHKePL4FFX6NVOvrIS2ztb1Zt9MJBABqCIACaa+fiT39WFKAfGPIdZw+7hMo/4uOGo/R2cN59enT3TTdc/V8AaAiC2gfQL8zMzPzi14sB9MhigYCmOHZcRvNYBvOSD7PkjkFWyO5xXuJuyPn8EHOjb2aNKEIQBJUL0PSO6v4iAL1nMRHQgfQATSMabhIHD3fQ5xUO6j721OKhDy/MwQgNQEMQVF5AB7qf+c/vUErL+NCCgN7y7cWCAe160YTKW3oId7f0DD7uxpvd1VYsPkhIfGnX0yboBqAhCGoPQJ///sy7tI6/51cbBPR7n1lsAqA5fp3DNwmZHxiqeKEOD9Ccy+QTLpYBaAiC2gbQhMyvklcJp18tANBvf+PbRcag14JQx9HvDtGBwD4AGoKgtgZ0OAYd8Ppd44D+g4M0ylEYoEPZz4fGj36jZ/CVngsH44DmIQ6CZfezDwwB0BAEAdDMdS3Sgx7186DpEOEm5/NDlbUGQGOQEIKgNgb0OwXmQRcKaOINc7/4Jr3nXnIDoCmYyQf/9RBDNdLsIAhqH0C7g4TdBQwSFg5oL8vOrWc3SityNACaT1SprGGiCgRB7Qbolcni0uwKB7RXbtSb5n14rRHQbKq3P4kFU70hCGojQBc6UaVwQIf/VE9axaQC5OSprOeAAzVXrWt0AG9dALrYqd4JgC5qRZWgdBIADUAD0AB0ewK6uQX7mwVoOleliQ70Ws7pX2ZAox80vblb0eg40AB0mTzo0ayFrwBo9FsAGgKgWxniKNPpD0BDADQEQAPQ6LcANA40AF3SVb0BaPRbABoHGoAuIaAf+MnBtbVHHmxhxwOgIQAaWleAvvWP5OaFyz5rH/m5MqCHKuUA9E1/MiMADQHQkAagLz5Lbl48zVOiz3Wfa2dAf2K0jwCaVeTY9PmhC7/D5gnS+d5NPf39+eahNL/g7U2xd5i29BzdTf93n7JfGvRbABoHGoCOArp1HvRrb3/0o1v7v/u68+Ofb/3x86/0OAOf/u7rg9d+Tl4Z+PRWx3n+FQFAH/rawUce/MPdazf7Nh3dfbNC7m/2rW063NTTP6gHEqrC5L896r5VAaBz5ReyYpPy40mTjxyMtmBzfoiNA3rUrzugfMzFWgKAbmtAnx9yjvZRD5pA+tqx7q8ev/BB50JfUwA9RF3Ky9/92is/+OJl4j6/9vOt/R995G3y75Gf/6Dn5+SVrW/TV34uAOi1TZVHHqRzVPoIlcm/m2wt70ozOUdhwqgy6lc0Db29iXce4uT3xQEdegpA+4Bm1xqbnAZAxyuotDOg6YarA1q0JQDoNgX0cdoNTl87tsLxzAF9tO/aGXLfzBDHaz8nj8j9Iz/f+ja9v/WP7MlrZPP6yStigF4bHXzwkQfXRn1A3+xrMuduOl7/uJkQ4rjpLxNwGIAWAPRzrJ1uDj4eB/Sos34ATXdNHdCiLQFAt7UHPU/OkzMBoM+tsPtmAtoFMvWg3/Y8aPKEgVkc0If+6kHib/3osAdo6tA2M8TB3Pf0t29G3qQfZr0pCHHQ7a0A0B6gXxqnLTF6ocNtVe+CaNSNID0w5HrZLpbY8GyZSZ0IaLLBHqDZDh3mez/44CjfOfomr8F40x+/kG4JALqtAc1g7AJ6viWA/ugLNz79UR6DfvujP+AxaPKE3DhviwG69R0vvJZW4tu0G1UCR9mLVPuA5i89B0C7gP5zujb7ofGjr3lupttgLpY2+aOxHEs347H/9gA02TcX0O4O+ITlO+fud2hkQ6ElAOi2BvR5QgaGZ/LgqaYC2tMPeuIIZh50m01USVmD1u8dLpQrvG9W3FsP0KRz8fVeAGhOq8OjBDkPDB2+yQDNruZJCx92H5LmqrDmOsyxxCm3qTnXTMYAfaHb33SyKxyuh7212Nhjfhno+9CHlVoCgG5PQJdlospWpz9OXZbAsc4A7flMzC9iV6BbiJPoAdqNbWwCoD1Ab2JM6rvpepksIs0dR6+Zb7LfO4alNlgAOAnQfzbu9HGijnrjyxzNfe6PNc8V5bcMwiotAUAD0Foe9PqY6p0T4ljzP1XxBwpvDj4YAPowfxuAdgFNf7KIF81o5V59OHypSQogFsQPsOQ+PVziLpcE6IM3naPfGPd2Ys1dUvOmH3524x++k31YqSUAaAAagM4bJKTjmGuu2wxACwCaXGZ8o4cijLRqeAaQd2HvuM4nZ5sXrO0r7T4lApps9p8GIGahib5MQKu0BAANQLcc0KP0/P7D6CB+ME9lEzuT+4rlXCjNrrF3+DmrFNAIceQDum9Lz+B/Gjq6e5PrQfeFucZhtXYo7HyWPY8jEdBko58bkvSgpVsCgAagFQHNEzR+0OP085tHyIn19ndfZ0HpW9/8tDigD33ucwfXDv1JWu/cxAacCga0P1HlZniKjPf2KA+A8DGdxkFC8gSDhBFAkxb5EWmNTaFMhwBLm7wwrTs0trbl9x5ca8wMLj+gmb/bEINOB7RKSwDQ7Qroi39DZwxuv+Sc4Tfnh5wLfeTR0b7gaZGAfs1hgN76Nk+BZokbL7xCZxD+nAB7QALQNw/fpJeGFXaOetU4Nh0mT9l5uunz/93a1mt9rFYHG8xLGdHT41xoqncQjQ5HQPxEKvcylKVGRdLsPo80Ox/QNx03utHnTovmY2UMXyzpgTZpMDRG2dTTdh40O2kasjjSAa3SEgB0mwJ6+6WjfbwOB8t/nj927djKtXP0JvS0QEB/97/nHvTHLxNGsxtvYgqd4P1f/kQc0MRreODvdhMP+uZhwmqvGscmNmmlwoIdH/7Gh2/2sVodhORbPs1ujHNOoFiSe4HKcF1ZC09UYZ0ME1UCQLOfUxfQwS8aa8YLf9bjRIbGvOzfwQfX2gzQnK1+8nNlLQfQCi0BQLcpoK/9+TcpoH90mjCa3VBaH/vc48SDDp42IcTxAmXzCxzQL7xCc+ye+8db3/y3EoCm7ifxjf9k9yPEpfiEN5dw02Fvuvemw4+88ls3+9g4Hsu2SEm50ObcaBsNoZca0HySBo+x9q2Fpl6yNh58kC8NTLPNXGeRXYGUOdUuBdAUs8FMwr61PEArtAQA3Z6Avvg3f8oA/SKF8YucyOe/2Td/LPK0CYAOedBsciH1o1k0WhjQo30Uwr4H7QOa3BHPmr636UfEdWa1Otbc0UNTpe5QsB9SAjQONJQJ6GuEgeeiHvT5n/StfK4v8rQJgA7FoKkT7U4j/K64B33oa3QO7Nf+rMeNQfuA9obmCLy/dpC8QGt1sHlaN50CYtAANARAQ8ZCHK6DHMSgL1Ig0+p2oadFA5pwOMjiYMTmj2QAXWbOAdAQAA2pApr8C7I4aGG7c0EWx7zrYmOiCgANAdBQswGNmYQANARAQwA0AA1AA9AANARAA9DotwA0DjQADUDz0z9HADQEQEMANAANQRAAbQDQEARBUCsFQEMQBAHQEARBEAC9XnRbRfSLd4yKWvznloj+5XsKot+7qyD6vVVV0S8XE4iEAGhDdCieGBsd0OMdZpt7vBOAbkdAr5oSjDX5UJsaJFw/gG7bLI5EQDuO9bJic7NSq9MxQBN7vW0A6K2v+6W8n0jB8qT/jiFAB2dIvIcmvZraa88PhU+25BU2AGgAGoBeD4C+fYpucYdKc7trlcZ4vERf69wIgD4ZOejPqwPa9l62AWgAGoDWB7TO2yWMQVPSprrRqc09StA853TNxX1oTu4MN7pUIY79j+281yxA+zyuxvnMXqhGCS3Qa7dfcpxjCHEA0AD0ugZ0jzVHEbNLrrl7CIMJoNl9/J2Xqb2udgD03iMD97RCHLPOWXp3QBzQq1bEU645VoDqmkyvveY4R/sQgwagywHoN4c4QswAuneIAwSApoAm7vM+6vbKAHrcvsMAPdpAYoZsGqC222CQcDIc4ggCH5Hgh2FA207as7ALnddrzw85g6fLM0hYda8DYEzNmDaYLx7np4MeoHscZ0oR0Pt2nbLixOgd6lIE9GjXkg1AhwBNWzjJiU4HtOdBJwOaBUG6Sg/ora+3GtBhKIffyem1845zxnQWR5WNKajBxq7W7Ci5bGVbDcZq/IDUDG2ZZW7L2MhC3YAx72f36dPu0T3aJwfoF093n9EG9D6C2HFVQt8+1REnRo/TpexDL3UC0DEPWgrQo870HRaDtu+kedAlBnSAYs0Qx1VpQNeidFAC9MXjKaODWoCuWTr+YK0WIZdNsGVbhowxg6aMWZZhY1Zd35j3u8vc4Gt0BZUzsj40X/DbP6S3Hl679TE5QL85RAiwIzutK0PzcWLMWUPqgO5ADDoag56Si0HTINFcIoXdGPR0W2Rx3LinC+iKKKB917yuCWg6OHiugDzouq0DaDsSnK3Sq/dqbDxU1Rj/XauWcMvYVtUc/S0Lh63ODxHUdl+QdKHPP7sSA/TIkyoxaGVAj++KEaN3qEsd0ONdGoD+5TPP/AN7/IF3nnmmr+0BnT5EmBnyH6eATsBwT9YQYdmyOAa36QH6pDP4KA109IsD2l7Vi0F351//qgHarmvw2YmOnul5407jUJxlGzKmB+j4bjqrZozxI3vmIg1xsBtGaRk+uwvKBoD+ynalQcLcuWtpMWh3ECsgRk+nRgzaHcIqDtC/9N/4wDvf251oKfTGH37nH1oD6DeHUkYHFZNmeodSRwfXZRbH3eucumdVZxKGIh6WUBZHcXnQjpUwiUbUF3R/eDxjdbtmzpiWA91gTCfEETfmetA1bWNe7IqymTnPsoD2BiUCQP/uzoflAd3jKEc44sSYszUGCfXS7NYPoMcznGelqd6ZznPZsziUpnpfTcmCTgC03ehAB3nQNcE86MIAXaWxl6qzqiXPmE13Rs+NjgDatldXTRnTGL5sMEZ301IEdMKhDgP6nF6a3a2Ht3x9t4IHfSobCMKApnBuD0CLqGWAtpTTznvojMH4ERi326sWRzSLo+BaHCkzvSVnEhZci8MAbIIhPUPG9C01MtUU7Wl2iXp4fNWYB50A6LWRjykAWjnGERsknOMndWcr8qAbAf1Hz5AH7OX2ArT6vCCeprHkSCfSlDiLI2UCuCFA29xvsxt8aLlaHOUEdC2WIMwHHJWxasUwqD4OR5MHa8bCxnFjq6saxtJCHEox6IvH+cCxTpodd54VAf3mkHW7LHnQDYC+/xmq/yMZ0DyS8YHvkHc/QDjsPiW3oTdaGeIItEtuokrv0PSdpWjAOWqvDdLsIlO9ZQF9gH60XxTQlhW9V59eNk//7hnTgOYQVCVXLP9My5jH46AB6+oxiVrN4LieXU0YcVTfuHotCdBKWRzXjm3/TJ9uHnQPYfMpc2l2WiEOnTzoXz4TUh+F8TN/fZB50amA/sPv0M/+ZSOg+Rvfaz9Ak/YbJXAejUz1bhdAZ2vMOSEQ4jiZUYYjMYvDTpqoEmOSAKC9IHRGD1bzoK2aRtg4zlSaHKxMLjueZqcRgq7HJ//R46A6SGhZMWOWTSCtHH6xE0McK/MqedDz8ZmEtx5WmkmoPkhoFtAdd4wBOuRHpwGafOQvaSDjmTigQ2+0V4iDAnqOwHlUNsbRBoCODR2mAPqAM8Dv+nU86FroB02sWNI8z7Kbz/ChFUMcjs7oWdXcfL1aLQ5oSycDcLVx8p/qllnVBGM1PQe6EdA580STz4pj2+/r0wa0luZNFkvSzYOOAPo7z/z1gzwQnQZoN4TxywZAh95osxi0TWuLdrUvoCfT56nsPRKJfCQDerM1ELnPBXSdY8GKxqCt8CVHVQDQ2y/xLGjvvhy1OOwGcmmo3phmV5ItM2rMdaDN1OJ48fT2+06vH0AbzYOmgD7IKJsB6L9kD7/TCGj/jfYKcdAANLmC6R1SC3H8rfPJPJ5u6nnsQ0LgDX3wPw99VgzQXrg5vdxoHqBPep7zged1sjg8XNfEC/a7ztX8hRIB2mgVoaSZhOXYMrO7aRLQjYOETQd0ecqNAtB+Fk1sLqEpQO8Y/J1iAT1J0Lx/cNv+qA+994jjnLj30NPbBAAt7UEn50FLA7qcHnRCZhyMyafZmSw3CkCHAZ0T4vhAOMRBaf6B75QmxLEjq8Jgegzai5smoHs6P8SRA+h9MoAOSRTQLIhBAB0LZtCwx+C2MSc6ATwlBn2dxaA3W6IxaFO99hqLQW+/ZD4GDaauK0B/61tPAtChQUJ6l5rFcX8wFkgfks+6WRz3t3yQcF/WXO/U5u7IDR+VGdBbXx/ghThi9aAH7j00dOPeWLTGnaEsjpR6DBG1NIsDTF1XgFZIs1ungE5Js/MGERmHPxBk07F3vvffRtLs/peWTVShixK+lk7oXA86HsigixLuyiJ0I6D/llr5PAtV3ByijzbRekufJU+/MM7eSPgIi2zQGPKHvBDHJvLZz3JA09qphPCZgPY86CigTxAvmsB5UmCQUDoPOnlNQnlAF5UHDaYC0OsU0O5ElX+ZAWjuX/OABiH593YHE1XeaeFEFVoridaATSW0JKBpraQuGuWwxQG9g5txuUwfeYB+7ojL5caPUGeZTylxXW3+9DkK6H38jS9nx6Bv3GMx6OhMwhN8mcLJImYSpq/qnZQc3aqZhGAqAL3+AE0J/dcPRgYJWzajW3KQcMqNQ+9Sa+6l6GT7cTf+PJeefBcH9KZx6uxuGn/sQ4S+n6Uw/qwX4qD+8d+Sp8kfcbiz/FkGaPIGhzb99GeZz/35LEA/NETpHF/Um3rPY+SlQgDtozhxElu8nCYADUA3HdA7wtHOcUepbJJPjKWcbIHmLxpLPOO/bDNAH/GmDe1QBHQsD3rey7mb65KJQVPHmELW47ALaOoEs6cJH3Ffpy9QQLvBZ45zJzl4HcmD3vpXFNCxPGgagH7o6W0PDRUR4khDcbIL3fxqduE5M1Uj5KprrFQVMVabmZnpZGlu35+Z+ZKBLZuaodqlv2XTM57+4kvagO6emfnFr7OcuZmZd9cToLPTBooH9P00ZkHd6b9+sM0ArX/B0riqt9BElRCg3VgFpa8fUQ4GCUPxi8hH/vPQ592EvC+HnjLvmQdEPqswk3C/k7TQiuFBwuSp3uUCtPI6e6F9rmnjPgLoUXOArvlU7SwboGfeWZeAVvahzQDajzf/w1q7AZr4pR18LTJFQC9F2z6xCGlOiIMFl8czAJ30kQxAM5NOoxudBOixxEVjB0TKjcpO9c4EdC0++zgri+MMS4M2nsVRS5nUqIbBmpMZdJcGNIOpEUAHfFYmdHGAZi50EwD93mcWFxd/+rMMQOvGoJe8bC46MNXZ2hAHz9Fg4ej2WvKKrxV7SmHJq/Dvoy1ThDQOaP4oE9BJH0kPcfih7S9nAHostPk+jrd+TmImocJElSQUp/msGbU4vIkqZ8wD2vbmy6kGJiJFKhxvdk7dBKApAY0AetwFM7P6JW1AqwdKkgA982pTAL1zkWuiUA/a9qnQ6U9u62pdDFrk7ZIBetwi7vPU7VPyWRw9iRcwyUVIcwD92X/mceMIoL8cAXTSRyKDhOSBN0jIWc0j2OkTVUJb709LkSo3Kj3VO2XR2MSVClsy1TtY08XWB3Tdr0hUNxPiYFA1AehpH8vU2q6yAXrm/hCgX/B8asOAHln0dLl4QLupXR4ypgFoCUB3EC/aov+/LJtmZyeFOJKLkCYC2tUnN7kJe9wTdum7g+dBh0IcDR9xX/RIzsPUPw7S7BqD0PGJKukhDhFAS3vQaSiWHNo/P+R50IUBumogKmE5BhdBIYD+i+9TF9oEoOeDwMaUamSiMED/v8yFdgG9vWfGQ7ZZQH/kw4uLb+9e2/JtdteEGHQn959tRukuAFoK0HSd9X3SaXbpgM4pQhoHNCftJ/fxWHJA38e+EINx7CPudJZ/Dj91J6rs4IalAR1UG23mVG87cVAuI8RRVLnRcNS4pstUnVSQJECPTlOumgD0eADommqMIyEG/SUjgH7nBcpjF9Av0DFDQmkZH1oI0JTMl7kj3RRAM3dtnKGZuNN20YDOUVvFoC2+0M0+1Txo+SKkHNClrgcdW+vbUBZHypiZdw4LA3r7pYKmeocAba0aAPSqUUBTsH7JEKA9E9RcZ7kAff77hM0c0Owhc6ffKSiLo1mApmgmZHY5LZP3tdEBTQPQbw7tenNIPsSRWLcuuQhpCQGdXLdOqmC/manedKXCulOtiw8S0nJJhUz1NprFYR7QNJqw/gFN3eb7OaAv8hFDwulXCwL0zmCUsMhBwh76SG3eytoGUnIlO1dTt40Aei4/M70cgE6uWycJaKWZhLF1oOj6KnQYzbLEAV3QTMJgkNASjZQ3McTBgsdfKmGIw2gMmoU03v0yA3S3D/93iwH0SCjRrkhAs1FCAFptqrd7SauaBx2LZaQXIS3borGJdev8HDyxmYRKgI7NJKQkpIC2nRIBWn2UsLBBwlFvqNDEIOGu0g4SvuMNFTYB0CPNSrNj4eclRyr4DECHVqnRmkloixUhLRugk+rWBVkcN0RWVHFygtBCE1Ucz4MuxUxCOwjHGEyzq5kBNEXrzDpPs3vHy91413ta2ExCymcvAl14HrTV6w4SSnIaHrTqiirJLnS7rOqdXLdOaiahMqDjMeg6j0HbJQK0rTxM2DhRpe7ox0tcQNeMANqfqDJdwokq73jp0MEgYXcxg4R7wv5zAGhPHWYHCae9OvHFp9kB0OsA0Cl162TWJPQ065yVHCSM4IqucldPmA7dmhCHdjGO5KneVTOA5jWOyjbV2zigVybdqMZkUWl2Lp8vrzUL0CxnoGkTVdZRFod2saQlR61YUqsBnVy3jjB7G3lLrBaHn8shOZMwjj4GaIk86KYA2tKNSpguluTXSipdsSTzgL44U/BElej4YPGAng6lEDRhqjcAHfaVp++0I6CT69aNOc4JFue4IQ5o2VocgjOfswDNVlQ5VySg66v6gHan4KjbagQ0c6FNlBudNlhu1Dygqetc7FTv9z4T4/P6Kti/jmYShsIb+6RCHMn5GuF1VkZLHYNOijbvPUIc6DFnILaUbKFZHPKA9oLQR7Em4fox1uSC/Tv9WhyRiSoA9PoB9J3chbBKDejEunVsAvikc6LQPOh4FkdKTc7sqd7XBk9fy/ChAWgAOgvQrNYoAL0RYtBqTV4eDzpSGokCeuvrBS95teroAXr7JeI6E0CzewAagFYAdFDMDoAGoNsH0HSNbzpsKLrkleKisUkhjlo8WTgjze7MCgW0+XKjYOqGCXEYogMA3W6AHs+fzlmOQcKMJa/oMKHEIKE0oJMTJCSWvPI8aAAagAagAegNBGhKaBrluHHvXnEhjmSJ1+KYd86tsBj0GcSgAWgAOpXAm2ZmPswebPn9mZl/AUCnV+goI6ATM55lJqoozyTU7bUXj1M6F1BuFEzd4IA+NcVv3nzZe6RBjCVvfkp41sQ0/a80gD7Eki0/vM7zoBNZ3GOXHNDJGc8FA9qWSAvO6LXnn6aANp4HXdOpA91Arui6hrW6jrEqDf/YVWKkamjLqoZ2s8qOaGzvZHfWO9QXf0J+cl883WJAEx15WY3NUUDT2d1djYAujwe9w52t9ItPbzxAl71gf3LGc2TJqyCTIzvEcX1ANMQhNUmv+TMJKVdsU+RaddgcSVOAtt1Ns0wwNbJlmsZs9b1rBPTxMyUA9KmpHY516vEhZ9epKfLCjg76eFR8VmEM0LQ+/9LjTgd5tmRzD5q8M9e5NEX+Qv68wgIBvcN9ccfMu7/RFnnQSiGOueSZ3mUHdHLGsxKgN1uCS16lleYvFaBpnVBrtWY5/F66ql3YmOetEmvkn7MqbTLAoF1jHnTdsb1NIz935EVH3KJnrF5jm2fbq7Ztk62s2dKmGgFNdpfYdZuOPGV2ZH+LLz47f4wA+vyQc7Rv+yVy050ZxyouxEE8aOtlQmYX0OSxRe4VQhxO11wndZvJ9fR4152erjCgrd45m9y3DNAP+Fz+p+DN9Qfo5GBGVoWO1jbCvcyMZ5ViScK1ONJK85cG0CwZu05QUyfQ8u9rSoB2v1alj4gV+q8ubTKEQYeHOKxVb9MoDwkJKRzFLMYATfHM/HyrKm0qFuLwAO3tn2uHWZQD9Pmf9L14+tqxle5z186tXDvXfWaFPGkJoBmZXUBP3Wb3Ch703PQoTStlznRn79SdMKCn77D7lgE6wPIhRupNNNrxR17ooxVOdUaj7khb8Uq5mt30nVIDOiXjORhBFJ+oclI0Bp1Wmr9MHnS9blcJDym/3HtFQDM01XjdfvKYho9taZMhQNdsD9DuppEbwkHa/QUtxgFdpWEOu0ZsS5tK8aC9/fOeitZZDQC90n3mxdO00gq5I0+7z7Ue0Pu0AN3JCEwf9k6NdgWAHm0SoAPFAb3l91+NMPif+Mf+yAtNtyAwndWqPZYqoMcTAW3fKTegUzKex0KzVwaEBwkFQxxppflLBWjXDayv+vdqgGZRXosyy2aADjxoNUCTnzUf0J4Hbdc82MoA2otBWzVr1QO9pKlEQNt+03kOdU02Bv3sysr84GnGZO5BNxvQdISEwLjH8lznceeSMqAdr0w/Hxkcner1sjjGncdbDuhD0eyNQ8xnPjTz6m/wNzZxZ7o0gJZf1dv3le3iMxsLAHRixjNdSTaYXrhNENCVu6Ix6OTS/GUKcVhuoLju36sCmmdx0DUAGLOCGLQioFc5oG1v02iElwaOnbokoN0sDqvOVoe0mWlJUwmDhMyEu39eSFo0ZScM6PNP0xi0c47HoJsM6ELzoHs6W5AHnQtonmnHnWkaCaGAnnm1NYOGWa06rgzo6YaQR04JUmrxly1R7kQVNnQoG+K4PvioGKDTSvOXBdDtlW3M3F59YwSr8qYwUUUa0EsqCxIWGYN2Qxw+oB+Y8R79U6uyozMHCVVDHHOxdI3x0AoKGwPQwlkcaaX5pXotLcKxcq2YetDtNR1ENmk7yViNX83I538D0G0/k3CHH2WmrD7E4s+HmPMc9qrLAugpQ4vGjhI0E2bP5QwSlhTQxWZxmOi115wLfV49aMwkxExCAFojzc5DMAX0JvaBQ/5rh1owSpiVxZGahi6ZxdFDXGfqVPdkp9mV1oNWyIM+KTvVu6Y+SMgKJM2zIhzbL6EWBwANQOtPVHmAesub6EdZ+PkB9qUtv18qQJvL4rB51CNnosp6ALR0Fkd4yT9brdfSUqOsmp0HawAagDYI6B6H59uOs5Dnm5fIE+HsjQZijLth5x52T/M1xtnMQfqox03w6GohoP2p3jSB41Dw0H25+UHoZmRxjHsedFsCWq0Wh+hUb8uRWec6A9Cu52y+HnSdJS7b7tZaXtKwTCJH1Jg3IsqNeubrMukNgbHVqhUYc28sVWOWewjYb2Vw4/0NWWPWatQYf6Vqhbc2dXjYO9Tnh5wLfcGV0bVjbLDhHHn5DH9UNKAJjBmPyc2pDuq1vUzAoApoOofQTYIe7SQeWyd9ZW6aPWIJdvxpK4sl0de9OSmM0P+CBab/KZL10e5ZHNFYxqgzfYfFoO2NE4MWrgdtGwhx0EnAngdtekUV22Fz3+wgI5i+wm+kAU2/RSzU6+68vVrEvC1vzKvIykzwvOMaB7eKMdvHa60W3KwKTvNcjbeZ90Pm2nFfsaxga6teY6Qfakpkmvs8f4xXlWV3n+ujMwuPsUdFA3rfPPegKaCt2zumjrx8e3SHDqCZ60znp9zZxTOeCbJ3zXX6GdBLnS0FdMlUSBZHTL1DlM6Zi6uXG9CTDSvJlgnQrBY0q6lD+Dx42vSq3pQhVXcSIEMMm2xRU/Kg3W/VGLmqbnqwZ16wulDUWL3O4MlMsBvbZn6qirGqm7hB99EObry/IWcsDGhuh79CjXntafmNkXmou4/96PRKN3WVz/8PLAWap0J3n1nhrxYM6A63oN24Yz3+5qWXj2iGOKypO6xgEp9USF+b7+WP3CyC+V4U7BcDtPpU7wbPmgK6TfOg/SB0tEBHKqAPZM5TKSKLw8vgyEnjUA9x2C5QVnlNJ80Qhwsm12hg3lYwVrVCxvhNTdkYnepddzPs7ODG+xuSu+nVvwqM0VeYMXeH+Y+zlXeoz3+z78XTHoqvuW4zOebPPSvqQOsBepdfcZTWtGPJXeqA5lO8XQ+aA3q8i7vWc9MsujHedQeA1hynzQB07pSU9gP0pMNKc0xGfegUQJ+UjEGzuhS8BIT6yNH2S8UC2vP42LRlfUDzi4W6D2j+qKrCVC/YHPKgV5WNhRxv74KB3qgFtN22Chnjk9GpsdAVyaqTd6jP/6Rv5UcRQNPJhdyPdh8VHYM+5cag93WwutAagCYcHg1i0PRp71CX+wYLf7hPAeiCAJ0/JaXtAO1Vh45WiU4D9AGC5uuDj15P9aEbpnqz2puC1eJbMZOwHgSJ+RW/JqCrjo8tuxYyX6truOORGHRN0ZgbcfbLcLg3q6sqHrTbVlFj7BU3Bs12vOrkTvWmBfv9GDQDNGU1uZ8/JhrhMJDFQbDcw0OeeiEOlr0x3xtkcYxyh87L5xgV8e8A6H2Z81TSAS0wJaV9ZxJOCswk3GwNsHne7F4wBl0l/lmtrLU4QlkclpdzoAdomzmkVjyLQ9hgAqCteBaHojFvN8PGssIQ+ckqSRkbVmhD7VTv3DvUtIzdOZbFcf6bfRzQ9H+e1yFalAN50OsL0OOqMWiBKSnr24M+SfOfaSEO0ZmELHmA1mXTrAdNoxzHVi4+fXoFE1WQBw1Ar2tA7yNo3uHs2pHqQ6en2eVPSWm/GPR+FoPee0QkBn3S8TxoCUCzAmqa5UapozV4utsxnsUBpgLQAHS5AE1z0ek87540Fzod0PlTUtZ5FscBp8Jj0KJLXtk8xU4T0HSiysXj51a6MdUbgAagkwico7ZKs7N4IQ75mYQCU1LWeR70VYfSOX1R78Zyo2wZj6pjaQL6GPGiCZznj2KqNwANQK9zQLsetDSgBaakrPeZhCcZoIXzoOveCVLXB/Q1Aud51OIAoAHo9aPkGPTUbRaDVphJmDslBVO9ozFo4UJJOTFoOq3sAgANQJsENFRKQL85ROmcvqi34d/DdqpmJwzoWcFBQttQr6UB6ItPn7543GCIA9oQAqDbDdC3b49TQE+pX7AsraNBQjlAz4bCWv0SHjSXOqCveSbOrQDQEAC9vgGtGlFaClc3VgL0niODH0vi6J4jA//qlzlvbB3qLzDEMRksGJs1USW8wuyjTQO0X47jzAoADQHQGwLQp6QHCXvCtOlSAfTWIecTcYY+8vz2EgB67xGhPOh+uRCHocDk+WcLmEkIbXRAI4ujlIA+FdpuS3qiil6IY/L5eYLjqCYbXklWsYAWmurdKkCvrHQPnl65eNyoB33XlLT2GYOEyOIAoKMTVcIbvqupgP7Q6/2/3eBCtxGg5WFVc6q0ELFuFke34xxjcY5zADQADUA3Alrn7ZIBetxSDXFoZ3E84vzmh153YxYfet1xWHCDjrfRSAb5/+OEQZ/gkQ06d+RfeSEO+tl+Dmg6q0SQ6FKAHnNEqtnRIPTZu1cTw88paxLWVvXzoFml/m7njNEVVQBoABqAXl+AJs63X+JVAdB7jhC0Tjq/6UajGWrDgOZO/Se8Nx0vOM2fPkcBPcnH5z5WQBbHDaGp3nRwcNZJJXSsF1vEgaal7CzdmYRn+HpIJvOgAWgAGoBeV1kcrFx/15LyTMLf5vDt5y7yJ5hHzUMcLqD76UsMw9xZ7vfe4NDupzESz45pQA/cExskvOpU7s6K1uKgsQ26hJ2BWhznhwxPVAGgAWhN0SkV5gBNJyoD0DwI3UHadpc0oMdt0ojTd5ZUa3FMUs+XZ9px0voxaM5hGrqgIRA3DEJfoG+4weffZoB2UtI9mrSq91niRRM4HxCvB73q6BdL2n7pQh+dpGJ0ooo2mK+6FxJGyFV1FzXYQMa0wXzxOK9uqAvo8V3Re2Ht23XKihODr2k1rlAQYrSLrTiLcqNscPCUwkzC8U7SiqQNR9XqQX/Ic1aZP/yJRkB7QWfvzUcGPxZ6ypj+CJ8j0kpAXydwFq0HbTmrtFCSbrEkPlGFDhOaHyQ8yShLg+sVSUD/8NHZ/vg+e0vHiK7yFcy5rLL1SFYbjFVZtpEhY7SEvqStVGM1fjLXlI15l0esyjet+H20Tw7QL57uPmMA0F7VtNTqaVm5uh0xYvBSxOMqlPBW/EYMmrjPU7dPydfioICeI82uWA/6ES/aS4isCmiX8sJutFlAM++ZptiJArrOu7DuICEjNI1ynDOfZneAAZrs2ElpQt+dPRvbZ9vjsiULaG/96wZjNUvFU00xZtdFF08QMMYeaRjz6qxQN5gN/87LEnql+1jk0N96eO3Wx2QBPe66auOOAqDnY8QYZ44zS/NSGKvq0ItBP/BBT5/8GXv5vW7y+Mm2AzT50dtn0f9l60FT73lJuWA/D2Gw2PJvJoc4PECnhzh+6SaACI8SGgY0DUBfHXz0qiMY4qCEplGOevGBSTVAn+QzIlleyvUBST6f7I/ts+MtvlhXALQdi/S6xuq2CqCTjVX9GxNb5mZRKhvzJolSQLPFcjJXzMmYwBQC9MiTsh70KYtHO717KblBEZ8Y4WVh5QHtrvhtANAf/OBlj8/0kQfoWz64w830kY//698oG6B3EDjvUyg3Ok2bvXdIKcThA3brEBv4+013wJBGpqOAjg0SkgfeIKE3wtgqQF/3LgIqTZ6oUhSgZ/uDnEFZQJ98PrbPNduFH7mTJpcTG4rzjNl1hZZMMabmjadtGb1QsDWMcR/4TMBmWUDTFcGjgP7KdoUQhwdmeUDvc6e6hYgRYFk6xDHqFpAwAmiKYvKco7e9AE2951NKBfvnPDwpLRo76VOVutA8dY6+9EiQB+0B2o1Wu+R2P/vvgzQ78SC06Rh0VqGkQgE9n10qST3E4QOaBdhldMBth9A+u+SyavIxaHc2T4MxxxKoYiJorG7XzBlTcqDDxryhvqdVQxzzbnGWANC/u/PhZgI6gRg+oOekBwm10+weYPEMoi3dzHH2n7cXoGkAmhyLN4fkl7xSKZTkNXkoqMF8aXeiCnsw8D9FAe1OX/ll+Kk7UYUFsn+zVYOE/YWmnKUD2quWlNGDNQG92XIG9NPsql5UQt6DbkxmcwMSdXpjxphN6ajmRicC2rYNHGrXb56XHyRsOPS3Ht7y9d3lAPSc03mnZYBeu0UA/ZGPM1eawre9AL3DcwOlF43tWIf1oNU8aD7W2TxAz5POe23w9LUCsjiCEEdqgRFJQFOcGgO0GxiomQG0ZdCYuqUEQNNMd5pMqQvotZGPNRHQbw5xiDQCelTBf+4d4pfmZjzoB3MATbD8A+5oM0Bv6f7k7uAl+iL/Lqf3A+7nvhH6RHEx6KxCSUIetHQ5OwBaD9DsApgAuoip3gGgZWMcV91QfEMgQSX/rOpmuhgBdJoxPuBobMtq8o592FgY0HS5HOkY9MXj/AdbM81OHdA7Om5PvpwEaKX4xlznndd6jcWgd+eEOFx+E9hSBhM+/yz0kju+SK2w73yBsvq97suhTxQH6HnlmYQbHtAFz6rLnupNAF3ETEIGaOY8ywL6+tnNLyXHoBU86HptNTHSyyEoaa0pxmiuivQhDhvTBvS1Y9s/09dKQHvjWHFAK2TYhdxuE4CmfM4F9JM0FvIk94zpO8FLhMj0m/T2ve4H6Rsc1aFPFO9Bp5azK65YEgCtCmjPgy4I0JstwuZZ2SD0gYaZhOqA9nKLG4xZNYWwcaqxugJW04wphaDthpmEfohDPg96Pj6T8NbDzc3i6LjdsysB0G42gWQUerTzTk+XEUC7/MwBNIX4lu5//RsE0L/D3gheov+7L2whn33vW//3t3629gX6Ue8TAHQ5AT1LmHS1+Vkc8+RalsWgzxQUg6YzCaX5fHbzY8YAbddWrWQMOgqT/1KNWUaNyWcAho1FBgnpMLA0n49tv69PH9Dq2rerAdAaGu3SBzTzbz0u5wCaUpbesrjFZX+0kN6+133Z/wLh8gOf/Eb35S2RL5WyWBKbpdI7pJbFsS4APes4Z0+2IA+aVl2g070vmM/iUNcPH9383KOmanHY1VWraqriRXsY067F8eLp7fedbiWgEwYJ9YolGRkk/IIXJM4A9OUIoD/5Z908xJEE6Ac++bMvPPmRjz/JYx2lBvQSvWoZV82DXgeA3mwRd3PW6d9sDTQ5D/r80xTQReRB6xRLahgk1KoiVDdZkqgNjBkolhQfJGwyoEtWbtQFMs3hYCRuAPQD7ujerQ8+GAE08ZHpJ4OXQiEOYu6Vj18mqP4d8rg5gKazVMhvn3wWRw9xoGkpux61YknrIYuDVrJzzgrX4ij9TEKUG22dsQLKjQLQXiyaJ8fFAE3QfZm9H2GtG+aI+MfBICGl9LeoH/3/RBBeIKBP0Wqj4yp50KxGFXGiR5XXJFwHgD7pSBRLAqAB6KYC+lvferKpgJ6/bTTE0WUE0CzI8WACoFl82k2TiwJ67b1u94GXFh0UXbr1QeZHR79UIKB7iANNS9n1yM8ktGmqXdfGBfRm6/m7tFCSeLEkU722jIvGzpqsB73KB8+MBRJq5TSWMNXbZIhDKc1OJwZtGQS0dj3oyEQVAtVGQPP8ZjdlIwJoAvXLYfyykcMng3mHH/l4NEpdbLnR2/uIEy1fi6PHYYWSFIslrYdBQlYsiQ4TNnmQsJSLxj7aWG5UQ+6sDyPGajWDTq9dNepB12vGAG0oD7osHrR2PegHwgl2xOFNAHRblBu1aKqdcrEkOkw4vWHT7K47Tmbl5KJmEpZy0Vh3brgZctm2OQzWTS6CYlkGjTWUG9VSNA96ZNvutY80VEtqJ0Br1oNWfbtkgO5xWKEkhWJJlNA0yjG9YdPsWjmTsISLxl7tNwboWs026ac2TP7TAHTVoDHXgTYD6Fge9MgTD6+994QsoE95kyHeHFKo2B8D9Kg3xbh3SKGomm496HUCaFYsiQ4TTjVlTBaANgPo4haNpXGbs16tkedl8qBPNgDaYrOf3FJCMpU96/GinjV/LlVdJSrRwNTwlmkbW52eoepkj8dnZr4k6UBHD/ULxNT9+nnQI1/5N2u3/qMKoC2jgO7kGbnSgNauB71OAE0JTaMcU7cB6DYBdKGLxtJJhO7USDlANy4a60PVkgZ0w7olAaCl5/4lrPNaU7aVtGhsbcZTpwFAb+8hht7RHyQceWXP7v8wogJoBmYlQN9uALQ1NO1FQ+0mp9mtF0A3N6sRgDYwSFjgorF0vonHZTlAN+xz1Yl4vfK18VMA7dQ1GjRpyzTT7AI+MzRLATrhUF+kdt7VT7MbeWXkK5/OAvSWby8uLk4kAZpGO00Bet5my6nMA9AA9IYBdIGLxt697gz+0I1xaAK67iLZVkJzI6CtVcXyGQ3GjG4ZJTJD8hS536UP6BdmfvF7ajGOOKC3fH13BqBHFpl+erAR0E5HCNDjHrLVAP0azfHqsXtcQFNfunNJhtYANADddoAubqIKXUrlqlspSR/QdS/6XDXgQVu+92sA0OEt0zM2PTPzF19yH0mHOBoP9faemVeJE/2q+/jdL0tHpMXS7Jj/vBj2oT1AW0OUxy6g3xxKL6MmBmhWsGfaBTSLSjuPA9AANACtBOhZx6kQSLNwsiagaVQiVIGzRICObZmesXlvdHB1VX6QsPFQdxMeEzD/4tc5oH/xFy6sTQN6hDnPe0IutA/oHdSFdgHd491OKQJ6l9N5Z8np5IBeYlkdc07hgM4RAA1AtymgD1A2X+dTbzQBzSIIQZjXEKAdAyGO2JbpGRs3C+hJyuYXuNdMxwsZqQsA9M7FxcvMj/7pz+KAplGNXZEY9A5lQNtLzjRdUYXnZPTwpI5RABqCVAB9kkU33BiHLqA9DnIyl2iQMLZl2oD+kjlAn/8+dZjdGAcF9DsrxQDanev8mQQPmvE4BGgW5lAFdO+QTYtBcCaP87TouYIBDUHrFNCzzHd2YxzagA7yJUwC2l7VB3Rky8oE6G7mO7sxDgro+4sE9Ec+vLj49w0xaB7YcAG9L2dN6TxA03I9PVZvBNBLADQEqQD6gI/BihFAe2ytmwN0ddUIoENbVqYQx6SfsXd/8YDeuRjicxjQfKjQjT471ssaIY47PYT19h0AGoK0AX0yski5JqB9IvP4saEYtImwcWzLSjRIeP77PqDfLRzQ1H8OQtBhQDMuO26h+Jd1YtDT5KbDiQEaIQ4IUgH0bCjSe1YX0JbnnpYO0LEtK1GaXXdo0sv9xYc4UgYJvXToXd7TfRqAnnPc22CQsAeAhiAFQB/wynAc4GX6tCeq1N1or10qQMe2zNBEFVqQY1QT0JMekSfp8GDxgKbZdhMJgOah511ust0ORwPQS6wex1wz0+wgaF0C+qpP5Fn6SDcGHXLHq6UCdGzLDE717tQD9EV/knc3fdQcQL+9OwHQLHNjlxfr8CooqQCaVrLr8qIafKJKBwANQfKAvu6VSWLB6LO6gA5KXtRWywXo6JbpjjhqFEuKAfoFP62OBqPvLxDQdCIhXZBvTwqgmQvtZXFY7nwVJUDzwLMXdqaE7sIgIQQpANryIhw8xqGfxVEPlYwrE6CjW6afEjLF8LxLe5AwBGQa4ygQ0HSA8KcHaR50NMTRlEVj5xyJRT7QNSEIi8a23FgBi8ZmhTjcWkmLsUHCYgFN5373skHCLgAaggBoADotBr3HBfTlteYBesmfbHQHgIYgABqATgM0C2/4AehmhThY8VKWawdAQxAADUCnATqu5sWgiy7YD0EANAANQAPQEARAA9AANAQB0AD0Rgf0vvCUlB0dp6Y0AL1EczV60uPNS9MANATJAPpA/927s5UIcN2nsVcFAG3TedS1Ov1PG4OsmN1qkiEJ49Et875dVSto5xursukubDOCbZHc5QDQ82daCuhThM77OgJAa3nQS2y1q0540BBkBtAnH3tMAsXZgK4RBto1aValALq+uppMegVAe1vGv12v6XnQrNZ1NQZo5Wp2f/zHfa0E9JuX2OqwPbSG3bhziXjQxIcmjvTjQ86o8GRCH9BTHXfmOjr5XO9xp6OTl+IYp7nQdHrh0jTxoec6l6aGnF3pmdHomhDkAvp65fpZAmiC6OtnZ19ynp91nqdPHX4XfjUf0FWLE5Bx1aLTCC3HYq6wOqBtzwybl8ieBq/VLIfzNu1PxLeMfLZWJw5wlT+0HNWfDgZ97uH7G8J3VHCyog/oa+euHVvpfurC/zg0+ONj2y85R/u6HedCX/NCHKdY+WcC5SniPu/zAU1es4Qdah/Q06/1vrars7eXUHiu805P55LNHy1Nk5s7vR6grd45+gYADUGZgN783KNXB3wUD9y93k/vK7PuXfhVsUVjLRfQhFw1u04wSBgr5bLGQhwW+TIzQ21Ua8y8/1rN5tBl7+XPG3cBTTeHP7SVPGh3b9hmkO3wN4TtaL0m5lV7gN5+3+mLf9PXfWblGqHzsWvnCLDZk6YOEu6Y2rfr9puPk5sdPqCnbrN7WUCPdu2iZHacztEuimLK41GHr7MSeNDTd9g9AA1BmYC+SvrO4KMeiit33fvoHX9VsBaHi2dGMbu6WrUlYwpRP5V9mZmhXjJ1fF2Dnmnfg67m1uKoNwC6rhx8WfVNBBvCt0uwnqkH6IvHyQE43X1u5cXTBMvk5uKz5EkTAU38ZOo8Rz3ofcqAXuogDjNh8yj1m0c5oD0SUzyTF0YBaAgSA/SBs3eZ/0wQfCAR0AckAF23A0BTlFrcu9QGNDPDgye2B0LPNPnHgsvJsI1vGfmsD2hbFdCr9MfAqrmADjbEd+ZlQhzzBMXd5ziT510PuqmAZlkcL4dj0N6dEqDvjHfN0chzB3nkPM4BTZ3n6TlW1M5/FYCGoFxAn3ye3cxWTjrOc42AjrwqlsXhhTjo4yqPz2oDmpmp84gHj/u6r9XYwodWrZ4Xg+Zbxj7rbo77UC+Lgznh7oa4gF4VXPTQBfT5n/TRmw+eWzk/5DzlxqDPNTvEUUgeNPOgkcUBQRoedJvlQcsmTTRvy7TzoJkHva4mqrDcDQAaggDo9gc08aCP9mEmIQANQW0LaMwkBKAhCIAGoAFoABqCAGgAurWAHqfzBcfdSYPjtC6Hm9FhuWt7+0/5p9jTNECz1Qjv9D7Ogs89tEq/e0Ne7hEt2o+uCUEc0GwRws2WM+A+6feeXD9LHw0+Sm7c17xPZQDa8af9rdJ7231i8YQOseW0fWPu923Xss3yOOrsFe+RlbfuYdSY99nYlkkD2v2++9VqsIe2PKC3X3LO0PjzGTcOTe8v/k0fS+doTh50B8+A3jHFn5zqYOl17BFNwttF3+NP2acSk+88QM913pmbJjxmo4M05bmL5T3f6XCfdgLQECQBaMJhNtmbZdHRSd9neUrdAefs3ZP9vGLSDx9lr3mfysiDroXSnkNJx4xbtiQG6ferXpYzzVxmM1/4y+wR/Ws19icFjXmfZUbZt1dtFQ+ab4L/VcviO+dtmRyg2RQVOtn7GM/kIPfbL8mm2mmGOBiJ2Q3lsOUDmvjMdNLKPJ0Kzp96+M4IcSxRRs+76Rs9XXNdhMy9Q47Vyx4B0BAkF+KYPfvSAe4bU0D3MxifpDi+6rCXNz/G86C9T2WGOGpenvFqveqlBldpDnJVdEHtkDGLG3EBbXtJHJZLQ5tbrNUEjXmfZUbZt6tSq3xHjPlfrdeDJ5ZKiGP7fX0UzGdcQJ9Zufbn32wuoI+87N3QSMbjt3c4U+4j4kDTUnds8gp9Sj/F3k0H9Hxv7+O9LqDHbeJDswmEd3o7RgFoCJIG9MkBOp2Q1bOj81L67153Ki6sK3evVsiLxJGmr3mfygQ0QVSdT9SwGVvpEzqpkM0srMth0LFdIyzEYdmuF84CCbw6HXvPEjXmfZYZZd8W3qhGY95Xq9aq5T1RCXGsnB9iIY7nnuUhjueevfg3f/rNvpVrzrlmDRKO7/JumDvNp32zR7ff5Iw+5T6ln/LeTQH0eNcdOmdw2pvc7fnNwSMAGoKEAU3nEr4UFBydrVwn3nLlrhvNYC+7r710Nx/QDvUoeSCB+anBJG3hJOawO173PGi3jrMdfuR61I6wMe+z3IOW2qgkY65v784cVDHm4rX7nHfD7q8Ri+fYnO/mlBsd2uXe8BDHPh7dYI8YlL3w874O9ikv2JEI6N6hLteN5gFpt/YGfdSJGDQEyQL66vNe7JnfHzjL4hw8OE1fZp40e837VEa5USeIRviR3prNAsheFFmmZhyfMu7GoF2HmdfR8B7Vqo64Me+z/paJb1SjsdBXrVXfmDygaVTjnDeL0L0//00/6FE8oPfRTA12Q+MXPeFkDbd+f49bq4N/1E/4SAL0qOs8E0CTfz10KmE4lQNZHBAkBegDpEdVWH7GSZan0c/zOrwsDjeBI5LrkQ5om3mTPJUjnDgRyceQyJXwjHj3LLbNXvYf2dmlLyLG+GetaBaHvaqSxRHastWoRYUsjqN9PJXjm/yeAfr8kExNaM0YNPKgIaisMWjkQWOiCgANQQA0AA1AA9AQBEAD0AA0BAHQADQADUBDEAANQAPQEARAA9AbBNAQBEFQKwVAQxAEAdAQBEEQAA1BELS+AV3iQcJ7pmTUmGFzMLbejBkd1yuvMQwSbvgsDgAaxgBoABqABqABGxgDoAFoABqAhjEAGoAGoAFoABrGAGgAeqMD+s0hXhvaDKB7h5wuY4B+aGhwm8E+aNQcjK1XY9r4u+oMPmqMqYUZ08Zf1V1yu9zGtMF88fjgaROA5utdjTsJqw1ma98uvrpKAGhihFF21HGsXklAj3Yt2RFAb33dcQafYI/+aptkt/nUtrGBSB/0jAVGjZjbe8RxbpgyRrv709sMGXtoiByLx3Ya2rJJaVupxsYcphPmDoCpLWP3OkeToWyz5bBlA2m1/QFJDP7wUbpcSoipvrG7JzkgTRg76fCq/6rG3JVK3Fr8VmZN/kTZVbaqy2qjMYrIqiFjVXqaWerGVtyK/Xz5wXnHOdonB+gXT/NlVzQBvY+5wT103RRZQvPFwANAjxPCjhIyz9G1VGxpH3qpMwzora+TE3+Sdb7JwW3Sns3YiXAf9IyFjJowd29ygDy+YcgYxY38nqYYG1PYyfTdvKHSaqm7ac7Y3iN06wwa23tE42gylB2gy57QZQPpGij9sp4qX7aqwRh5JA3oNGNsndkDA+rGOMrogiz14F5OfD2qBmOMrlVDxmqWig8dGGOQnadrxhJCz9P/ZQm90n0sAuhbD6/d+pgsoPkaVqf8GynNR2LQS9R7pgsTjne6T+TUEYlBj1FWUY+S+DXy2Nr6uUiY0TPmGzVjjlnaL8uHFGPk4f7npDctzdj+AQU+Z+2mdKul7yZ/XLotY/djstdXIWMsFkBBep2uQ0WANivrqJ7sj4SNPWPU6ZUHdIqxWXp/VdZcyJjv6NYt/17Wh46EjUNG6gqATjFWt1UAbUdi0BefPr2ycu1oH7tnNzI6/+xKDNAjT8p60KcsthgsY7O3eKyw3MXAIzFoAmi+eOx4pySfx7saBwlp3xsbkCfq1q890TgO5JkxbE4W0OnGHnq6W5o1acYmbyjwOcWYkjee0WZ7jwwYMqYE6NTdZKEhDWM+zQgGGQEZpWUo+HzCuB4F9Gy/NFHTjfm0VjTmw8wDszSgnYRxPWaE0FUa0GnG7LoCn52EQUIC6G5p55ny+Sd9MUB/ZbtCiCMA9CmnQy4G7ThWA6BHrV7uPMsCetRx7AZA86tXeaJOOs5AQx9Uv77OMrf19ROGjO09ckJ6T9OMbX39Kflge5qx/QNj5owpOdBpxpRCHGnGuActGR0PG/NpRrjMnGdZQB9wnP44U10b8oDOMCYf4ggbC2hWi94Le6mOYzcwlRmxavIx6DRjjsXWxFU25nN26NjKtTPdjsw6sStu2Doag771uzsfVgT07XGLLuDdoZ1mN0fg7AJ6Wj/Nbj/vyQoxiYRMKteYf2/E3N4jjlKwN8nY/gH1PY0be2joBm23J4wYm6QMGlPcz4RDMDlg7gAoDF+mGaOxaHI8Tygbu+uNxQ3c9QBd0cyM8xfrvqoQg041dve6qrUQBr1lsi3HUsyZaDBWt+UHCdOMVWkcuuqoG1tZ8df1JqwlqFVyo6Mhji1f360IaBqLfk02xNEI6DnHDz9LhzgaAb3f7SxGAO0Z26/YA1PMKUQtU4xRnJoAdLBl0s59ijHmopoypm4pwRhnqqEDwEY7uhWPQCSQQOis5EEnpi7zQLYJQPvGrituV8yDrjnRe63UZWKE4tQEoENbJOvcJ+VBd1/oY+OD1JXWBPTayMdUAX1bPgb95hDPzAsAPcrQrBaD7h1ypqOA9pM35LH10BDPl2o0ppIRkmFOgTdpxvar5J81Z8sGDBpT+kVLM6YUNs5sMx1jd0ORBKUY9FU3qS5uTAnQ6cYUMkLCxlZ1YxxVN6kubqzOe4AZY9pbthKKcVw7syIP6IvHeYaeZpodwzK72WG9LAXoHR23J18OA3rOzdxQyuKY67zzWm8Y0Pv9fiwP6P0n9n5uZ7gPesb2K3lbaebGePbsCTPbprKn2VsmmT/eFGMKaS85WybbaGnGlHJywsZ8F5VgUCmL4/rZzS+FmRpyw+UBnWrs+vPynnPYWOCiOjXvXgqD9dpqJGwcNiLtQacZc++rysZc55mBmd9LZnFcO7b9M32GAH27xyIPZEPQ+6IzCbnnzAcKFfKgR6MzCUPdTuHCfzI6WUw9gSPT3N4jJxSCsynG1LavGVvGkoP3G9tNlRB0ijG1vPbU3RwgDvEJ9S3jcV4K5gE2DCefB30gOvnPN6YU4kgxphYsORCbSWjVeKaxdy85Fhed/BcyIh/iSDOmu2U8An2MxZ63XzrHsjkkRwnjMwlvPawMaBqDluZzx+2eXSFAz/ErlM4gI0OKz513erpCgA5d8Stg68TeLz4R6oOeMaUwQro5pYlsqcZU9jTVGJ0VZ2zLjO6mwlyQJu0mNaZzavjz9QbCiQ8yFDy7+bGGyX+qg4Rpxq7z3T2rbMyfr2eF72UoWFu1Gib/WaozCVONOXpb5s8kpFz27qX4fGz7fX36gFbXvl1RQOtptCsKaC19atveL267Z6wWh1FzMLZejWlXvPjho5ufe9RU+YzCjGlXvLCrq1bVVPmMwoxp1+J48fT2+063EtCNg4SaxZKmDRZLio8DlcccjK1XYwZKEiWM65XOmImSRHWT9Y2KMWagWFJ8kLDJgEa5URiDsaQ0O5QbRbnRpHKjADQADWMANABdVkB/61tPIsTBLzx55pQJY1s/R0ePTpgxR0vrxGr1aBkbc0zVNjZt7B4fPDNj7KEhgwfAtDFDIY6T/QajEkUa043zmoxKFGhMj8rnnzWVB62uhjxoLTXkQesN3Tz0VUOAfmho4N7+E1vv22nCHDVG/79nytjXY6Uzy2PMm49ixNjYiXvm2uxT2wwai+dBa0R5+xtSl8tpTDPKazekLpfTmGb8+YypPGidNA6TK6rE86DLAmjqJv3eE/RfGT1oYxg0bmzv5140Z2y/Qd9+7xcvmbxQmDS1ogot6HnA1CIoRRrT9lMbUpdLaUzbg47lQY9s2732kYZqSYWm2XUYTbPrNJhmN+Y8t0EAfc/UL5FpY2Mnfs/gT4fbaGYAvc2cscY8aB0MNqQul9KYNgYbU5fLaEwb0LE86JEnHl577wlZQJ9yS4bSgLIjWbA/MQ96zpusYiAPms6PcBy14nNj0UyqSSekG7QqzhMyDlwsxHHErTHJfgqkJkqkAXq/ygQaYuhTcdhMei3G1rwa0DO2328y2ZrX1OlNKOppbDfHvPOC7CY5lOIHNMmY3pZF86BPBqfZWWkMJqYuzzJjsvWbCzQWTIyWLpzhYjAhddliG1Y1YOx/fsbTr1V1jPFCSTMz7/CYxczMzLtygI7lQY985d+s3fqPyoDukeZz0iDhkn92dukPEo4p0oF1t9jFuh6g44OE+4PyyJNyvToZ0P6eyv0YsTGq2OX6pMcZZnNAz5gOoO/da/CgDe7mmLdzCoBOWDRWZ8uig4RagE4Y17vqm3u+LMZWw1C1jYzr1bztsvSNBYB+5pn/qjtI6AF6e8/MzC9+XWuQcOSVPbv/w4gqoPfJ8zkhzW4pRMEu3TQ75gK6RNXOpNIAdII5SgWvGISjWOzyXsIvkaNvjOzoc7QWNIfrgJ4xZUAXvptjoQsFKUAXuWV6gE7MjJsNnbYDJTEWmtUhXxI/MTOuGmxXXdtYGNC/plG7NALoSUk+J6TZjbwy8pVP5wD6Ix9eXLycBOgdGnxOXtXbmdYF9P5gRWnVXhMLM/LObCBzNljMe0wVgilrZ6v+FoUB/dglukmTj10yAegb9zRVzG6Oeb8aGsfU+JYFHAtqaOgx9aQH+pPqxDduLBThsB3FgstRptZd0NsawA8D+iX24H8nhK6ZAfQLGnwOAL3l67tzAD2ymAzoU4p8ji4aS+PPVm+08Ci7bOkVDHF0xQF9w3NSt/kutZgrl3AVGwa0rMOVdO3PN2RSvrxOujG+SAih/2D3kKjdeLyEArqHrZ/1WR4pJ9ZPjIm5hklbdiMSOJKIAeTtpgtGsQOaGOJgTaTgQedu2STfbbGfp9iisW51Th5EIHdnZyUCCledWOLFdf+7m63nA8oKwX823xgrnCQWkOZjhHejYWOrGipy5AgHPKou1sOA5p6zF4auiwekG4z5gF793xigv/fMvxNGdcOSVxzQ3R6ft/fMvPvlmZmZ+4upB73l28mApgOEHSoTVawooHtio4O9QxLhjtGupeiahGOxS/T9Etegn9o2NmAQ0A3mvBgHMSR98R83Rt3xMIwpoC+J/xINJACarXn1eR/QTwk2XMNuRhDFh2yFXcy83QwCCycUDsAYjeTQNlIAdO6WyQA6fAAiQ3FnOf+ekwn5/vDR2f5ohdC4p3tVPIb86N3Zs9nGNvOROaF1udzS1iFA1yhVrTBRRSMetVrM6a3F2G5JhDvsaoYH/e9WKaB/7XvPPDMgXhG6AdAXfSQTQP/iL2ZmXi2oHvTOxWRAj3sjhZoe9HgMxT3seY9ouGOpM7aiSgQIfN3S/aKX7UlTLpQB3WjO7cNjSpfEUWP+FUIIhOJjVUke9AuEN2POCR/QZBsFK2nGdnN/ODLLmp7+emwzspvuj1wQzpfaMhpaotcGajHonC3T9aBPetC7zh6clAgoRJl6Mu7fEqQ+z8FakWJqojG6ef3UmIAPvfmll+KAtimbPd+Xe9KCUK078dRlO0LkOsO1JeZDW1bMWDgGXWOAlglF240hjvPf91I5JMcKY/WgRz72G2uZIQ4a4EgCNE3gUFsvNgfQfuKdGKA74rU4JsMDNzyYIAqIxFxjdUA3mHOz6yZVkgBjxuIbs/eITOw4AdADYwQs5GJ90gM031IB2sSNhQHtbiZpwwEjuxnC4ID8blJAM4sqgBbfMiVABwHo6/zBAUd08diT/XGmPh/ym/tDZBUxeLU/05j7wlWRutWzZxsA7fClWRmZq7L5F/HJf3bYA+d3VbGIiVWNGQsBmrnN3/NDHsIOdATQrxIohzxoj9Xy9aBHnnglE9Bbvr349icTAO1qVzGAZmEOIUCPdzUWS3IzOdwuKM7CrV97wiSgG83xzVGJcDQYSwL0DS1A08vuycEnfEAPCHKwYTfDgH6IRRTEdzlvN70DKjTK17BlbHCWElQB0HlbpgvoINZ7nbPvumjp/pPP3xUA9FWxsMQPHz2ZDeir/OfjpEhI29uFSGZcfdX3cyUi0Cwq0Tg7u+oTuuoX3LdUjMWzOL4nk21nNw4Scr3rA/p+1XrQIw/vPJgF6J0Ezh9OBPQUDUJbBQB61G30aaGZ3o6dONV7zLtGl2DqZNIsCXVAJ5hjnXjMUVgiPG4sKcRxQgvQW18f/PKRx3b6gBZ1VBt2M4yoMclMtLzd9I6B0LFo2LIxL97SLQ/ovC3TBPRsENFwPV1hQB8IYTAclQgB+oAjGjeOjzg2GJuVyoqOe9B2JDOuLpMlV3VSZmfXmIVakHSnYiwYJOS+8/dkcjkSAX0/DUK/Iw3o+CDhyMPv/dZ30wE9srg4kZhmR2eb7FANcmQOEvawFI45uZS7Rr+GhRPUEo6NxaDvJcwtGaARDvW0vYxBQnnsRwC99wjh1sA9aUBnptmNKaYKp+2mFKCT0uwGvKFC3TxorUHChjS7kyF6ygK6ITPuQMRWPx/WGxANceQYm1WYthIw1Ylh1JLPY/aN+SiuUa9ZDtDpaXbuKOH3FJLtIoC+n6XZMTBLATpebpR4z7fSp3pv+fbiTw+m5kHTcUL9iSrhNLtOFt2gTxUBHck15oDeViJAUxNffl05CToly8sNs+sB+ga5edEpANADJndTKsSRAmi3FoDuRJXYlnmAnlQBdCQDWhvQs8HA3vVQVEIN0HFjs/KLJt6NJF54qoUcYCWmWh7YPUDLz08sDtDUdabjhO8aAHRGsaQ9FM3pgHY9aUMTVWhBDpvOK7R57GJacaIK6yA0Dj3gZxzLJR4XB2i6IS8q1glJmyex33Ev3HUBzZtuv1FAu20mzem03ZQbJEwGNHfrtQEd3zK+23JjAR4Gr4f9UW1A+1NKmOvsM/WAEqDjxtygtBSnfQz6U1RY6rA3oKcI6Lrreld5IJtbkeR0ch70gBlAe560FqAz0+ze+8ziRMZMQq253mlTven4YBeDtRKg2TSGoEICp6vkxLECAT2mNwM6babxNhOAHmPZxWYBzR1ymTS77N2UTLNLBjSvDWV0qve2UEanAqCtwFS/PqBD1TMYXK8yJ/i6owTouDEe8hZLs4sDuhqOSjjsac3Lj1NYBCW0XVVvuoglVzspcZCQDg8aAbQ717s4QO9ZDPT3adXsrJd1l7yKFkvq8Z7YSkteBcU4ToRTCk7cKwWg2e+HzkTotFo9BgDNqWcY0JITVfJ2U2qiSiqg6TmiD+jYlrmuwVMlAHSsvtFmKzCubUxqokoM0CEUMzbXFaLGIUBXo+EShXh2MqAHVk0Bmo4TvtpKQLNxwildQHuJG9PBE9udr6KyJuH+SKEeBmy1EaoCAM1qhGwzA2gv5fuGkUFCL+XFMKAlp3rn7aaHfKmLkAZAu5VadAEd2zK2YSfGygBor8TRQJDo4fTz+Sr6xiSmescAbQWRZ3d6tFSiXeMygvVIMbu6fO3RJED/11VjgObjhM0HNBaNbZk5GFtvxrBoLBaNVQV0WjU7ABqwgTEAGoAGoAFoGAOgAWgAGoAGoGEMgAag2w7Qhlf1BqBhDMYAaAAagAagYQyABqABaAAasIExABqALgWgT4UKjb4Zn6ZyakoS0HTqoFstaWk6fKcE6MnkzN39J8ZuyPZBNvNg8IUb9/aGkm7Hbqh26b1fpBPh/ninkW3j+d0nkjdH2JxnbGzwiXt7j5wwQ66t9+00iMGHgmW8gt0aix4TUWMPPf0EWxnlRqM5vS3TBjRLNO6frZhh6tVgGslshf5nyFhyzeeKDKDtxJznmlKxJNvPoA5/v6Y0UaWWuDa4nC0f0N3nVlaunYkB97f6mgjoqYDDR17W9aBpRWe3qvPStK4HTZclmjyRBGiVPshZo0scz9z+G8nbobRttDzx1r/aNnbDxJaNsdnTZQS0u5sNRJX6I8Gy6gMU0PfumQB0eMtMeNAnpaZ+ZDGVWtr83KM+oI0ZM+BBW5Yxp7dG6GzXVECaZKweLIOl7UETQHefi/H2/DebD+gex3p5h2PR6d67aGE7fnNqiry1o+PU40POaFahDg/QLpRZCQ7yuIfdkQdznUtTQ84uwfmEfh9kHiqt/cBWzdjGCiQQV/gp4qWSfkic1R8PDb6QM4EsAuixG/tpMXvPloSZBHLt/WJos9gj1W3z3EDylSfGnhr88hHnsZ3e94XN+cZ+/Jl7j7x4Itxig9GnXunWjMr7od30N0h5afXYbu5l1p7yjyo9JgqA/ir57aYeNDs/6N0Ntj9KgI5sGTsK9Ibbe0p0rwNAb7bOUprS6dRSM/4SmOoimVXg4B40eeX62dmXnOdnhS3HjLH6/LPPPe8Z4cbp1opYD+ob1eu11Zrl8MpGXpVQikdLeL63X9jD8pdoId8P2SLP6rUarcuUbzMCaLZlFjXkfpnY8jdUCtAXnyW3T114nGC6+0z3V49f6LvmnNl+yTna1+04F/qaE+LYQTg8RTzoN18mPN7Rcfv2HLvxAE3gbd3e0ZEL6Dke3ujtpUimZF6yPUBbvXO2975oiINVGSWdZ2yAXAQTSA2QG+KiTvoQfGzn/oEcpzUGaApW35aEmQZzn9r20FfvBabYI9Vtcz9Fv8Kske/f8L4vbM6Hzec/t/NzL5wIt9jeI5Gn9HfqxL29X99/ItXfDAPa26ABucuD1N30rBGoso1S9KC/StxeCmh2foz9e+L/sv1RAnRky+gpx264vQF5D/pAhbm7/ZR1lbuz/RqAvn6Whkwqj95ltgJAD9y9Ts0rGbt+lm+dZ4Qb73f/Qp71oEJotUrxx9aIqlJW19kTBtWaLRniYFVGuZF6zBa5I2/Z3lpUYiEOh20Z+XLd+7JrkhmXAfSfDzEyr5z/Sd/2+053EyyfIx70tXMr186RV68da4YHffv2vl2333ychjh6aNn+Bg966ja7F/Ogl7pY3f6laYZjD9DTd9i9dC2OG6zzsOoUjFSf2hai1o177F4S0L4tCTMN5jjkfFPskeq2Maj89hPe94iZh77qfV/YXGDsU9/6trtBQYsFT2nJCbaY37ZJJ7U6RxjQwQZpAtrdTc/aQ191N0oR0ITLFNBso8ZohRC2P+oedHjL2I2kPR/Q1/u9eMT1s6IMzXR6ZytsPe4woCt32b2SsQNujNwz4hoPATrLerianVOlsKP3dHUVm9O0Xq8pjevV666RsC33bpXdS3jQdfpNu7patb0vu7ZswXohPqAvPHnfaRblmD9GfGny4OKzBNAvnib35EmzAO150ATU+zq8VymeyYN94oBm8eeeztGuO6Pcg+59/GV6N6oE6P200A/l00N/TLrOJOdL4KVOKgI6sCVhJsHcfU/cC0yxR6rbRsOfxMv1SMwduTCgJ6UAPfbiCXeDghaLPA1+YQQiOaEN0gS0u5uBB+1ulCqg700Ocg/6oT9+hBrhqL5hYsvYjaQ9H4P9dwNAk5urA5phY+KR//DRuwcCQB9QBLRrjH0tBGjXuAfoA2KApiFjBj2GREbPAIRVSw7QxMflIZMEW7YSoOmXuAcdBbTor0coBk18Zwroi88SKhOnOeRBNw/QLAZ9u8c65TjzUztY0MNhHjRxpC9JAJpncSwRN5xxmYeix53H1TzoSVbpbJJHT1/kiHDjvO6dNKD3HhkIbEmYaUzMmuQLLnmm6CPlbfOzOBigeSjUB7SguQDQ5Nrf3aBQi4WfOjf2u9Fo54YIoL0N0gS0u5tBDNrdKHJM1ADNB1bZ+UE2boDtj04WR2jLnvLaRxrQvILngAvouwccpQHD2PpZs47zkotn8sJzioB2jbHbEKBd4wzQ+dY9DPLVtyn03NCu47u7tnAdunAWh+UbCdsir0sD2nFj2TwGHQX0qmAR03AWR/fRD9Jxwhf/rm+l+ynnQt/2S24MuhmARh70es/pZR40UpdFjTEiqyTUIA96fedBb790bKUxowMTVQBoTWMZyRoANAANQIsButs5swJAA9Aw1s7GAGjMJASgAWgYA6ABaAAagAa5YAyABqBbCegeuiThuLsuYfCEp3V4yxUKA/r/Z+/9Y+s6rntfSiQMWmQoSnRCkHZIgjnhNQ9sMgh0UaGiGLE9NXN0rFdCLFNdKWWaCk4OQlRyY/0R+UEGBFshLFzlIch9EAwlSNLLoi16UfQJAg2kfzwECAMDzasPCQMWWh8BaZEI97/CkgCR8C7frDUze8+ePXvvmdlD6liesXV+8ezvWbN/fM46a9as6TvRd7+XLREL93RFb6LTZ7VoLMwlpBMKO9/jK0rjDT7FAbCcxehiYnyZZhyux5uS4RqoXI5bUt7itjFDaXa03rp9MTE+XQLFeG+PD2jPHpfE4nutHHaZGZpjo9xNfC+zJ3/rHLHjCcuiQ5m7arhSDO8jRXWZlGyxcOcIO5DLmwG6vRaUw5Wyyf0wfcWOqbjpHFvRENfynmMTFIfNxaLtufKmeRKgsGgspEOEcwCbD+mUQsy2gPQJctPUZSoVqwWCWC2oWQKaivF0ZybWjOYrGgEa0zXIDZbjuEmUz12YJE/w5d2a6j06eLDt3kmW/jzahk/4BJXRQTNA99b6MO+ZzlrB+5ku7QQ7CdBD0+T6wBu8fivVzlNwaZ/iT7fqQRUelRoagGY6ryzQMSBMCEb2vbJgAWg0AjOUQ2PwA8Ai/JuxGG7KxfhNqcpfNhQT9xpONeE5fHVqaI6NMTH+Xppop7F1zj4rVWXLICGaHkp2jM3F6BRJNs+H9V7bMtyebiruQH6GmAF6dZH8Pzcclh+6NWWQEaeY/IezXZbZ9tfxlQ6UtfGg2fZcmWC6bO9BN8OCHDA/D1KMNyDHbh2e0ny7dX2ntxmm0oVi69YedJOKcDFmSs0C0JhKR26unKasPdV/c/ZBz6x2hp2LEEcvAhp85YODhNH4hOc995oB+tr5tb5rXXRGIbs3yYCWAF368f4BekMvaCijcXwAb/Bp5+fo9VPRSA9mOnR4Hi/sV9bQPzIbsI9q9ZCNn+umW6Mx+AFoEf7NWIx3BsXwBg3kL5uJxfYaFN+j0xSpwfC3HBtjYvy9FIcaW2eJiYCmluENdjM6xoZiuKcERdZ7bcvYqYDGCDuQvWwI6OvjxDVdCRfObj++WQDQKAaAHhbKzQGtiawFoKPtqfLm6s/sAU1n7IWABlyv4yzth80mTNweyZ9UHRMTAd1ECVtAUyW0CO+pKcxWC0ATR3o/9Zfp054zuwnoeRrVOEFnfOPcFPLkYLDE/mYA6L4TfWt9MwzQ7J7c3b8WnLeIQY/99BBhAdzQn8QXcQbui3iDT9nP/8yZaDGx0F0uBehLAl6NHGhxcvDYi0cYoNEY9gG0wMXYi8ZiQojj4ht4www0BDSKxfYauS3TLqPB+LccG2Ni4XtBQmfrzG6WaEhJsAxvWIiDHWNDMdxTkSLvvbZldE9TO4QdWK9uGRaPxUoci3Qa4UoHnRsyDLGFDssQB4rB7JFh5gCDZJnJmgM63J4pr5Tn7AHdxKBBWOYI/WmKxCZwumkEaIQpm0ICYs1147p2cTFmERUDU0JbzWLQN4NzDx5cmDzDHWjyOLj4Mn15lzxoNq+be9D4hM791q0IHRZLgohz3IPuWwK/Gv43BjTGh4UgcZShGt4AvKBWpMavWNSB+WdbrCoOIXMlfMViWKnS4B40PmGGMp++YSwmkJh1jxpoCmjRGEEMu4wG879VGtqWsR8KIKGzdaZljTAilTyUGlnISjG2p8K+6g4shB70QvyDmQR/2dCDDotecK91tYNGFWw86JjYClB57rJ27eZEPWhhe1RezSkQnQXokWYYiOb+dMC86SbO2DYBNIrh5Gwm1nxoD+iRZqxwKTNlQ3MOYRzQOKc7TICGynb4hL+884CGgAZENUbFGDQNRNfwb4ZZHGtSDBpYfY3cNW0GCdE37uQ/1uvVWHwWwr8QUHhJr9wom+u9FQsjVE2nJAhRy0pViEHDfSfzoKmwqRhHFO8o660xoNlW0l7D0mxlZjCtW6ETGIp2eBSVyN86T6ycsKzBd1zYa1OxSrTPGtp1rBNijdgONO8mrxkXho2xclwUorCqZgdi44scyiuXuaw5oMPtuTJ3p20AzfjHQxzN9RFaEJRGj9fNYtC0fkYYlWiu8xiyDaCZWHOdi3FTLDxoDGjAzbmwfP/sg7VZfHnXsjhYusY0u2epHMEg/ZspoGkWB7/H4PO8ZiXoNEDTGnTiqH809F/PdpfiYiV65WHmBx2jN6wvIYz7MyO4bRGgeTqAmRj9kS911C6LgxkjiB0Pu8z+lmOjspssXyZ/6ywxWolatCzqpnhkTcWOD4j7zBDQkR2xo1ksi2MY4MezMC4XyeLgYhjJhlp0HWZ5IVGdPb49t6wIoNkYXo3+HzShnkawYZfFQcUwC4RvaJ/FQcWoSCjWfGgH6AuTWHwjeKEfyvRjOBpSOvBlnwft86C9mM+D9nnQfqKKB7SHjRfzgPaA9oD2gPZiHtAe0B7QHtAe0F7MA9oD2gPaA9qLeTEPaA9oD2gPaC/mAe0B/YkAtG+++eabb4+yeUD75ptvvnlA++abb7755gHtm2+++fZ4A9oPEvoBLy/mBwn9iKPP4vCA9mIe0B7QHtAe0B7QXswD2gPaA9oD2ot5MQ9oD2gPaA9oL+YB7QHtAW3W7kwGg+4A3TdJq0Y7uWzGJuna0I6uQadyXuxxFStMrBW6GPjmJ0isMEtHgmDEGaBFscJgvvTlidPFAd0bwPKDJwNsbUaAHh3EtWbFVb0Duvwgua/1GQJ6pouuuxJeNkPTtBZ/53uaSxgJ7Ug3rrURuwbHXoIrqR6YlGHPldvq/EW3KzHo6MSCIzG+9xx1M7wvLjY2GRgfA6fHM02sQi+CqrVYCCDgT3stCEzL4d+aomuvJMTmzBenSoqtQO/ApHEHloVim3MTUwXEOBcDrNAfYNV+o9YcwYVYHibFaiaLXCXFGGSJ2AtYnP/SS6fNAH3lNF12pRCgR2H5FLaw1ajeAipCO9kWA/QMIew8IXQvofOMMaHv394TA3Qd1sxoENLAchemrGGrFQnX4NA0uDolECubO0opcsTKiW5HYrhqad342yPFMrb3XHWT3zsQq5h/QWZ0s+Fwn+HxLCDG+NNeI8hqrxF6jZtykK6UtakSa691FBRbZtasgtiwIzHSSWNAi2J0lSq22AmsfNI0XUqFLY6VEGsSMWNCC2J0/cEX+MopB65OnDb1oXtmY4C+++z23S+YAfrO5OC9ewcpmE/SgIVJW4uv6j0JS3jX+vAeb8xaW3xV75coTyt4UZt6lp2n5DBj6eJLAMGqhViqHK661O1IDDtq7KimiPG956ab0b0DsZLF92NmN13tM6TtRIFuMvqsXiTIQsd3xZRdc8NypBfFlkFn2XThLFlslT6fCxbdiYFvbw5oQYyuUsXWeYX4wggNMpi4vdKSV03mSBOdDWPaN6VVvcOlB29eNPWgH1x4+YEE6GNfsYlBM0D31kz5PD+YHCS0B/R8V3KQEAG9YH4N8rW+I7Gxl3r4BY2UdiK3VSmPmYMrTcwmkpApZgrodDFBtLBYvWHB5xQxK288Y5+Z/7oSxVhM4vKKLaDZktubshjitLDYeIcYM1l0Ira5PGz8LRQTo1TcEMPAhoAOpEFCUcwY0IE0SLjGF+++9KsvmQL6wq/6JUB/54DVIOF8m50DPRoEtQSg5/dYhjhmgqApAxpQSj1ow8hgPQjiYcah6SqGGXHdU2NAp8nZxGazxMx/YWeJGfczVUy0sKhY53tnzUPtaWKlcsWdmJUDLYqxmMTiim2IYzwI4pFeJkY9aEOmymJzwUVcvhZpP+dIzOKLIy5GsViLYs+mIY5mEMRj0KJYsG4vRheNJScrrA974OqscQx6LQjiMei73xp41hzQfO3u0ZqDNLteOjg4YzFImEyzo8sqQ2iWPKpu2bRQjPyuFgDd2NpyImcF6AyxrdJEtysxs0Wps8UECwuLjU02YK8tOBGrAx0rlv1UHIB6eavA0eS//SmyLIbiEslsTGyOAK29ZshUWWwFhhlXLnNAdzgRswK0nGY3AqHiEQrVDeMIh5RmJ4iZLw0up9ld+vI5cJ77IdRhDOhEmt3dZ5948xkLD5r6zvNtTvKgbwdd9+ebgOouB3nQAFSI8/ZY4iEKaC9sFfCg0+ScAFoQKwUOLbMKtivFYqJOLLM9BLIY/uBwJVbkzAgBDdCKmHq5GKC5GEZ6/9EShLHMOOI5W3nQaWJOAC14uxumPm9KHjSTWQ8c5EFfmJwFRrsA9PaxL9jkQQObLYYI70wGS8k86Pk9wGjzGHTfJE3RiwGaXzGmeBibpDlmXKzEMqgsY9BpclaAThezyAjJsMy8o2liJZv8s92xrOxQzOobTRRDn5eKLVqFjVdYMp0sZhVKkMU4U61i0GliVoAWxeJMbZr7zyMsmU4JaNMYhygmAvomPRCzhnnQwbmiaXaR83zQOMfu3sG2e/UbAqARzNaAvrbn/j/0CYDmzq5VPkKpOnRqQJHqapnFkSZnBehUsZKFw5smZvVTIaOb5v3Mtswwe3xXxCzSXuJiYuqyFaBXF9uvq/KgUWfVMGAii1HPeWLKKosjTcwK0KJY5OcSNm9YOLwb6w9jMWguxu7XrcUwTw7izxeo62zsQd+cPfBif9E86F5wnoHNNiHoUWkmYe8eQulaH4Y4zPOgZ+IzCYemqxhehIH1sUnjYb3kZDG8But2edBpclYhjhQxuyBCihjfe666aTMYuguWYYJ8yVk3bULQ9eRMQh7iMM+DHk/O16MjjsPE7VwsJtZeW6Tpy+M2edBpYlYhjnFpJmFtHdOXR6ziz01pJiETC+9txWjy82yYC20e4liTZxLefdZqJiH6zr1L5nxuu9c7KM8kRC7P28wk3HO/t0ueSUhDjIFxaLZeHfrmwlbKzDMLPqfK2YArRcwqkJBqGd97jrpp3s9UMTiezixz2k2L+VAxscTkP2M+L7YfT51JuFhULLSIZ1E4EbPJ4hDEWCQC5/5t0CvAzOltrj+sxUMcbCIhzCQ05rMgxsIbfCKhOaDXZg/s7y8M6AJtdFAGdJE20yUBukg70j30ze4tZ7U4nMp5scdVrHCRiltT7RenXFW8+HiIFS6f0Rx5WBtxVYtDFCtci+PK6QP7Tz9KQKsHCQsUSzrvsFhSfByoleS82OMq5qCKkGIo7vEWc1HfaMNlsaQNh8WS5EHCXQa0LzfqxbyYlGbny436cqOp5UY9oD2gvZgHtAd0qwL6rbe+smuAXnMa4mhzGOLoPOX0V6xTOS/2GIsVw9XcsMNAwsdGrGjQ2GWIo+kwxHHhZSd50AXiz7VEHnSR+HMzkQddICpYVqa6toKcF3ucxQoGZoeVedCPuVjBkHEzkQftTKxg/PmMmzzoIh50Ig+6kAct50EX8mtUqa4tIefFHmOxwq6lKg/6MRcr7PQm8qBdiRX2oKU86GPdz2x/PlEtaScBncyDLgLoRB50kctGleraEnJe7DEWK0wuVR70Yy5WmKnJPGhHYoUBLeVBH1t4dvvDBVNAs7WuoA2yEqJt2oBW5EH3olSXDaClPOh6WEfSdPUmctnIqa4wOSKwmQiiloPVkajjNDaJVtZ1dVViZGOqhotBlYtZVg+E1ijeTdYMq4ToiJV07csWEzUq+btPJcasKXxqRHOZhRIafA2R3MkhhFxytvEcL+lpg0FF6jIsw2VRYF9DbFx7Io0kxqt8Rm3DkKlyHrT5qllqMcTs/3rttadwSmHva6/9yBDQUh70se/88fbdvykAaBzxMwF0cpDwNpcynkeYHCQEppb5tWM0WUwxDlQQ0IlhpQonqQWgE2J1bhZSp1zMsiKAVnbTRktLzATQWWLCuaEHaNUgITgB5lNM1YOEy+EX0ZQhoOWhuEKATo7rhYaVnYsZAToxSFgE0IlBwiKATgwS9rz22m/h/vXXXvvfv1tskPDYDz/7zF8dKwJo8KFHTVeOFQHdNxlKnS+eZse9VKtlpaRMqiKAViVmVQSn1wjQKjGy8cVJhiybiehuAJ3WTUsfOl+sZGFfzldHxWj3xaZ6w6lrWZ1VSrNbjiy7bAJoRTKbPaBVmXErkWEdrsXGA4v6pQ4ArUizswe0Ks2u/tprvxE86QJpdsd+eOw7v5cB6Cd+8i5t/y4BmlVJmkcXuhCgr7HoxoxVlEMGNC+zULcGjRxmtCnckMEHkHIE6ONXASz141cLA3pL8OtddJOaY7Oyep5YUUDjkYwfUntAl4KJK4W+vGNFKi4zp1IAYQsAejUy7LJrsWKADlfjdpEH7RbQBM3Eda4bBjjUgH7izWcyAP3hi9mAPhgC+iQLdxhP9b7GPed5BHQvuSWOyR7bqd7g1VS3Kjaezdgk3SbOrRJKkWt6omdS/2okv2MJUqoKB64aA3RFx2XFH8VSEgEAupdQZmj6/5hmhEGPP/e7hIhVAlVGggho9A01vpYgI4GOdymYymha1w1O0N/+1UwxuAXjdLqpEqPb8a5iDNk6xAHLzxyaDE2xFOPk4qtnsxDHKtaHtg9xrNLNjaiqikqsshfYOq/6shpi40yswyrEkQA0lk0aaYEQBwY5fnTptdCBfv01vWCHeR70sXdzPeg2BPRVGkW+YVwPGkPQzQi5BNAn9MPRijxoAOpfTNs4Nke6x95IcKtCmQqAvqrvStNk1879AxIfLuL1HAH6rBwQTRM70l0pJwE9AYtBfZ0BuqIVjgGxN7cq1UxAsxp5ud9xIMYrZaud3qo+oEGsUs3yoKuhZbm20X2W4kGzrmIIGY9B2SoPmsg14LzoFsJE5mJ86CzmS9KxNFjCb9g42zgE9EU5YmKTugwAFWzQltURG+diZUMxJaBrmsEOZR60LaDT8qCJ9/waxjnYWOFrr2mEOyzyoD8boTk7Bg2cntfyoRN50DOxAHSvWaQjmQfNLjuLH/0qQPOf6aBqElAlbtIrC/C/BJsSYCYCNHmiEQgAP1VmKgD6dfytUKWABtFudpsnVlH9VIgATX9/lDR2IhEbOnVlIT1svGDmQZdk314WK+EvDo1isp2nhr55NSmGgGa1S+lvo0qg5fQq8qDrYCzvVrjPTMUEjzLGwcsJnmlmG4eAJh6nWcVRZeryeCwArS+rITaOMnMaPnRqHnQE6A1curWm40Mr8qCLeNCqPGiIP9ORQvSffwOUzvehk3nQ28e+8Pvb6SGOz3/u3Xe/lw3owWil7pM6LrQiD3qGa3VRQDcL1IMuMnRTCS6+kfwVG4UtTZifBmgYvFyIAF0W/brMSxohHQd0uULYUJropjoRB8v5tFf8VBAAXQ9/NHTnd7NSfSUV0KhnAmjez1QxlpyjIzb0ze50MbL5EPuZVddiajIPmhxK+msIDLIXU4WNuUc9rgNoOds4BHSZKnSYAFqRujwuDl7qy2qIse4t57vQqXnQEaDpgxG2wrZpHnShNDtVHvTroctMWA2kvsQdaqM86O1jCz/MAPQTP3n3X6rvipCOA7rGnWJ0ne9MBvlrFCrrQfNMDhqDPl+wHnTJOhWhIocZSxz1FmnVqhBHmQdRBdcyf3AOAtrfXUgCGn4t1ycWEAo8bSVXDdNwJXLFAW2QAYNOb1BWY7DMHU19QB9JZWoUiS7rfA1li+HW+F1ZIA+6gh1iX2N8n5WMxVSA5s8L5EGv0k1XTYYZ1anLYfLF5U0TWQ0xhvmV/ICJKg86DugRVmhfp97+DudBP6A45kOEl+gDwukfmedBEzgPPJ8O6HCM8KvbyRj0wZDQPItjXgPQqcWSbtMwR6/2AGFqPWjbdIRSIP/yr4Qh3SHDqHbKIGGZjzYKWRwcFNk+l4zBOrrjE38xfXwgBPSCjppqxDEJ6AXtbm5tvaKKQUc/9s0GCZNRiZhYSfN3QpqYkP1nBujkIGFdTNmzF1OFOIwAnTpI2GEB6NT6RmwwT19WQ4xlccxpATpnkHA9+vJtgUFCFoN+ig0YsvZbi0HCY89++Id/nQrocIww9KHFQcJRnrhhAuhEmt08jznfxrFBM0Ary40WzBeLrkEhPDw0bZ1PJcGGDhUaATolza48NE1YX94yA3R+mp2RQamZcXX+O6ZuOMUkU0wb0FlpdmGIQpepaSdHFHyxF1MNEuoDOjXNzgbQmTl7NBBhJZsmpg/o/DQ7E0DveJodTlX5C5a5YQBoRblR4j3fTZ/qPfDuu//2DCZDk7tkFsd8FIPWDnEkAB3GNFoO0GK6rDtA00FMoxBHCqAb5OZKIAC621CteIgjg6kAsInuCND1IoAOxRwDutse0GJAu2oS4lDlQQtpdsAs7lE/ekDDV0eHK0DLYvohDi1AN1spD5p4z6/T2EaPRvA5E9D5xZI+fPHdf3leAeiTLLNulN5F2Xd5Fe3kiSrnWRy6aRHi6HIGaPkncUkYa7QAdMrPdXplM0ADL/QAoRgkbLBoe8lokFAlphwk1J1II4vx/lQCcUBPM4ivJ6bJQYWYAGiDcT2K80QaTTX8LcPFdMeSBcviE1VWMXFDf5AQ+ZaSxWED6GVJjKVt0NDxsKksHdZLFRunX0t6X0Mr7EdG9iChJqdH2CqzTgDdZJ8Zm0n4I5pe91Q4SKjJaat60DBW+K+qPGiWX8diHfM6EwqhJnQ8Bj0feSJdpoCe6brddAZoOdd4WhhTsgB0InWZw6YeAVovZYxnHCcATWPkJaM0O5WYtNvoI83dmBCrCMFn6FmUgNYoLmYCaJWYmC9T0U6zg0+UhnzlpET9NDvJssRUbyDksm6a3Saspro87AzQU5vLizGmzsUNM5NdvryZJTZukgq4vJg9k7Cpn2aH67y69KA31uVaHBh+vkSDHHXtNDvSrOpBpwKaBTmiiSr3zD1ooRjHnvv3jUMct/c4DHHEc40LAjqRulyJaiUxQE9c1c7ZVnrQFMclk4kqOh50OB1Eq8dpTi+NSyzwYO3ZQh40F3PoQevPLdmiI6GxpMnIgmg+DmlX7DzoRLGkcb2JKiK73IQ4ZKYK9TMWNw1l269fzxQbDybo7BIdE1eD7Dxo7Ykq+N6aszxolgstVbP7jeRJa01UwSblQatWvAoBDcHn79GxQmWIgwY5lgDQg6OaU72TgKZRDj570BTQbQ5j0NIFXRTQqbCph4DuruumBCoBTYemOCswuq011zEP0Ea55Knd3GLz2NGuaqUYoJmYU0BTt75iBWjhfKiHA5kT3RVbQHMmdwjFRzv0fvzPDbuMQa8My4kXq8JsPyPZ5cXrm1liBNBT4/pVmOaGHU31fghpcU13gKYOdAjoejivm5dL0p3qDXyW86AJnT+TNUhIyAyc/qq7RWPXXC4aO9/lbtHYRK5xK8kpmerFdk0skdWelqqp9X2rArR1MfvLDpdmvTU1N+xMjGPcuWWFx/OaI46WvBIcaDeLxsp50J8hnvGHB3LT7HiEo9UAPcPmHTq5BhO5xq0k55n6aMUSg4TJo42lq/QSYFwCetwlBuURx4Lt+uaOWFYYqSOBsyWvHANaHiTMBjTU4oilQbsA9D2XHrQqza5ocyrmWM6LtaiYPOXRLM3ORfsEiT101ZyLPXDV9EIcrCA0T4L2gPbk8mIpYmwstLrlAe0B7Q7QmYOE7heN9YD2Yl7MA9oDWhvQOml2HtAeNl7MA9oD2gPaA9qLeUB7QHtAFwA01NzgOc8nl/jNwbaTSzaApokYfdISKn19t8+bA3poGqs+NLaGBuB/Xj/U8hqk62WrJIxkw7lnLy3g9MJGJFGxXl+vgiuCVGPW8PtS1UwMo6dC0rNs1dCAjp3CFLso1SyxqWaPJbHYVqWq4W4Tjyef/deINMz0YtWqYjpFAL0Sm023Gj5c7jDH4FxZEFruKMRUnPp3ebnDFaDHh4Upix2FAB3VRVrfWA9np6xv2AG6JiQ1r28UA/TN2Qc9Zx4poE+Qm97BCNB8LSsbDxqmas/sub8mAXqtz8qDhjK7lfJW5/4BmrVa1Enq/EW3M58L5/fyZZi2LC/sCNAwrdsNoLe24jtLMk1zT4bdfIMeBrapXT8lMQnQtvusEfYtDmgrMSh/UrU+jnFAQyrzXFRwdHWxCAZjgC7M1LmyQw967vhxnrxdLu5B10Io2yJVDeiiHvSB/V/BuSaPGtCEzcRrvhoE8Gg+uEo8aPrSiclgJreuHQd034k+nEvYvH0i6OoNan1QF7oLnp8nPvS1PbeXJoPB3FWwQtSM/fTQfljMqEz+r5ydeB0uROIivTM58br29MII0OCjkmv5LCxyOLEAi4QOYM2FiolsBBtyQYMHTXXOmurE+fDOi1vPXalSqUYd0FNGSeIOn63iYh/M0gz9GKBxG8jjXYC3L+DW+BrsSQ07k0wtVWFTEBPt0eqxLAYi2FfsnuFuiwMap8eDAj4w1gst++kAAz3ZeUPfZF08azaFlZOLOZMrMNGbOK0XF5evE781uEz+QP60Gj7VBTSW8qBCBgKpgF7uWC60UnhULKmDfGWg1mowTFSZVe21gNk8TnbE8rABoKE+PwCaIJq4vrWAP2oGwbrG5EAR0DUo9U/0iAe9js65Tu1/ZYij5+zsgwuTwQv9PUHwav+Bq/zRLoc4KI1r94DLxH0eDQFdu3GwlutQi4vG1vqIx0xc6WuEyOfhHjxqDuha3zV8RTMGXcH1LdCDrrCfoOTSI5gpa7tKQk12vKRRhwCwRKTgSalqJBvBpvO7CwBorgMqpuaFsPn6qYFTr1epVIMIA8ZAkqjUq6UqNRt/vafrxwBNt4F+wturuDW+hm5wvp3JqAROvkMx0R6tHstiKAJ9xe4Z7rZ4iGNogJmBD4z14vPGcUtcy5J30cqDZp4uFCNaJI/HF5fLm6vDGKGgfGVPtQE9HAoZCGQBeriANx6VG704tcKMAyM7uFWrxET6EeSnBF03RRPQxN2leGZYfhii+uFGU8MZFgC9QbbbgPVfAdCwLWpbAfrCr/oxznGuBxaBvXnuwU36aBc96DtXbzBAL5GnJ5dGB/Exfwnv9QcJCZgByLCAVd8SYlkA9Pn79BVNQOMPcgboRghoBgxDQJfK/Ncwbnqkm0CW6RnICt5gpQyA5jpwY2pe5A0eeesnpSqXqldBHSTJK6VqnQXPOaBT9GOAxm3wPdGG+JoA6Cw7hW6CdxkCuiHZo9VjlRj2FbtnuNtED5pVGUVAwwNjPXGQsES/Yem3Ytp4hbYH/Y+0yuitKRo6pmBlfGVPtQENb2ZC+gJZgO5wAegVrAWFWhTQHaGlK8P0I8YXV4YNQhzEUQ6aEaA3HoqPzADdHHk40iQ3sDFui9pWgL75P849WCNbn+khbJ69cvrBpZfx0W6GONBzBq9Z9qBHDQFN3OMQ0NSDFgE94wLQdUtAU3+IXYMEFK9Td5Vf0XVzQMNqzgkPum4H6MqVaol70JRcMQ864mxdD9B8m7GfPhcCGl/jgK5rA5paQjbggBbt0epxUizhQdctAU12FFXAB8Z6YTW7cgjozv37F8LdZxeDnpgidAZQjXPHVwD0uB2gIw96vEUAPb4YasUATT1o/IiV4VtTm0Ye9EMe4miGgG7aADrmQW9QD9ouBn0JVhZEHCOWqQe924C+N8rizrEYNL8z8aBn6EIqzdu4IGGtj+IYn88HJ+wAPTRdJv/jBceCjBaApkufHH8Ox5Og8hwL+CJmDGRF2HT+QopBm5oXwabzuwslHoMm2PkfxM8UY9AB/SrJ1Jdj0LhGy0R35EHja7gn8+0Uu7lVpxvQg1AS7NHssSSG7xVj0Ea7LQ7oShBcQbDiA2M9MYuDhTi26mW2PJotoFkWx3IQXO9goWMO6NhTI0CzLfUFdhrQWNVp7jJqtdeGI0DTGDT9iFvXjQYJob4oApUGjx/GHhkBOhaDxm11a5dKgIZiR5f++e8mg4BimcagdxPQPg+65dJwecadzzb2edAfazHyO8LnQXtAP26ArgRlj0EP6I+/2HJ+mWkPaA9oP5PQi3lA+5mEHtAe0F7MA9oD2gPaA9oD2ot5QHtAfyIA3RvUbpAbNlkQcqLhlYM4fQX/ZgJoyNyARQnP8yewzHeXJaBxpB9vtnBgvQyvlOlCF/xvuUtecDHcnk8FxuX/6BqAbBaZ6SWNckwhbhuaxR6ZiPHO8CfHByxhM/YGSvCVtyPj8BW0+Ui3NrnIDsON+a6LlCwwyMWUOw4PKt6UjcSifUUOJVe2tYz3LDr3eL5JrmxELsyRIDdz4ZS9lbLwshkGo61QhM7Uw1fYIxsxvukqXUSQvjJsLsZ6SDuFYqhsJBZNyoYpfxs83QLzMGomyctJMSqC+SFNLjZSozcb2XkdEaBvzj44cDU4Qx/BzJXJ4NV+cnOGv7yzgKZJdGsctb2EzW00rW50UCPBTqrFwXLoZoDJ5NG1PXBz3hLQUYYYvYIqNBEYVxiiCV+n9K9B3H6rTmuwkyeYhVtqkCvxuA2gUY4qiLbBK1Wcj6aTMxYT450JlauWgH5lgfZ1iy6MGhnH/1Zq5O44If+sSrOg+a6LlMwtC8WSOw4t4ke2XjUVY98dMEeRKttaxnvGM76jHPJc2ZBc41AqCW4It1Y7KFTLwstGGIy2QpFNlsEGr2inyyXFhE2vh6+Mm4vRHkaduo6vLBqJ0YWmgnXA6sYGX3QKnqxjGrQ5oEMxFKFi61ysVnvIbh42dTzotQCmET64chofUUzfPAdzC2fpy7sB6DuTzFU+uDR9Y3QNn+hlQCsBTWvXzbTRtb1v73EF6PJz3bT+AstgxkcGECx3fi7EHhKM3JR+vN8W0GUuE9n2yhpaNPTNBVNAl3ln8AnTsQE0m6lc5qnCkXFh8nB1K8+FDn172GG4Md91MSXDXx2hWHLHYe/xhr9BWyzcV+xQVqqFLGP7CA4fKvMDWalqAnoOZpXgDeCU+pY/K8df1i+WFG0FIhzQ+IoxoCOxaFPyCF/5uW5FupgY9jDqFFG4Pk48aCMxXiMJ79Z5Dbtmkzi/GyMmE7STYijCAN2kYhsbMCUGbrKlOaAv/A76zQf297NHWJ9jlhW5O6BXSKlQiOMgrcRxp40GOAig27Cs3egg/ZtRiOMaBjfQgYaydkhqw1p2Qgy6BL82S/THNPmReRFn2OFcuxfxZfpIO4xw8Y2o2hmfo0jrMVmFOECOFoeLbKujI9b5Xjm0W1uMdwafUB0rQOPno3HUyY2MY6+EMw11f/uzjek2opJNIIFtL+847D3eHNEDdCTG9xU7lCaVD1WWsZ7B4aPK9EDmy6qiErTO20p5rniIg4lAJKGDvUwfWcVLwk2vs5dvmQJa7KHojQP9bxkDms1DqYV+bROKZzTtAB2KNXkFjiCoNVFspEZexptsBzoe4nhwYTIKcZBn34cQx8WX2cs7C+iDS/A/LwMNkWdCZizKEf1NG9A4vft+3xKdVdiFgJ7vsh0kpNOBG+GPy0ojdL/ClysN7WtQoMxW53cX6I1ZNFWWQxnRNnJ1SwYa2CaUGuU6dr49lcKJe7Edh6+gzXniMXI9JwJaULLCIN0+seOiXfCcAaBj+5weykjZzjLWMzx8qEwPpIasAoNzlzfjkd4CgGYimziVepMFF1Y7LMX4prRYho0HLfaQdQrEroMf/XNLQEPFupEmX1x7fWOjCKADJsLLmKIYRp5p+HnEANA40ZsDGsonsVfozc4CmvjLNbhhsYzpG/QJABv/ZgToPVASmlXnhyd7+ia7rLM48AcwjyWwOgusuls1/JtBGAEijJQyWG4fb8w8LkmOKahsa3C7tcV4Z2JP7Dxo2leGucg4fIXabORBs+BsSYhBVxq2gKbFoNJ3XFU3Bh2KRfsKfhG9tFDIMmGvsfOLxp80ZBVOb1jVc87FICH1oCFAMUwpu5hXzTMd0HxTytFVmxi00MMoXIJSFjFoYOpIIFTpF8PGNoBGMRSh981QrMZc9Wz0xwCN1ew4oC8Bn8nDtVn28g6HOOYhgaM3qAGbEdA0dwODz/O5laClEAfmbOA44VofZnHM8JQOC0BHuRZQpXdaGPBneQA5A/6xazBKRSBiUK2sUafOsx2gUQ4VZNsMx/1DMdqt/fo5IOkxaNpXAGrMOHyF9lo3Bi1lcXA5sxHMpJhyx4k3xlkcPGRVL5hfwvcaP7/YgdSRTWJwHJxexKorQMP/YeLEnG5d55T8EjCK5V/YZnGMh78NuFiBLI4mOrYb60I1DfssDipGRZgOE6uJtZm0szheoFS+8P1+KG13DhM42Ms+D9rnQZtlceS+Vz+Lw+dB+zxonwftJ6p4QLsT04gPG+RBe0B7QHtAe0B7QHsxD2gPaA9oD2gPGy/mAe0B7QHtAe3FPKA9oD2gPaA9oL2YB7QHtAf0LgD6ox1oHjZezAPaA/pjBujWbDvA523ffPPNt1ZsHtAe0L755psHtAe0b7755psHtAe0b7759ngD2g8S+gEvL+YHCf2Io8/i8ID2Yh7Qnqke0I8NoP/TSfOA9mIe0B7QHtAe0F7Mi3mmekB7QHtAezEPaC/mAZ3b7kzSgv5OAN03GXS1LKDHJie6nV3SXuxxFSsMmZVgYsoZuT6BYoXBPBIEI84AfenLE6cLA5pANoAlVPi9SRsdpEtihYDuQ5G++/dn6J1Jm+m63dxJQFcCbFVYjSV/tROpHemmC1jxSzoUG5o2W9QwUwwu95e6HYmNwbEwXJcl3bK6sVaqmNhdNwfAlWV4ahQ5mgiM9loQ4OpU4+zeoN2aoktRJcU25yiGXIjNBbqLsWiIwX2Hu25urpj2UxSjlCViNQpb+sCgNUfWmzFAH7ga0HVT1gLN9VOiduV0z5nCgD7JoHzSEM600aUMQ0DfZlSeOU/+mRL6/u09O+5B12ENozLeG16HdN27mM8FInVYfsv0mk4Tg9WvJrodiVWMu5jVzYbDfSbeFxUbmgbrHIoNTRc4mpQ1hDTjsAIUrP00bOoPLi+K5ArFyK0xoNPE5mBBqvGyI8vGh4lgh7NuttfM+xmJUT4TKDdh1cGajQ+NqxiGgD5wlVB5Df6de4D3Zq1nNgbou89u3/2CIaAPsmVhD9Zsghxr8Rj0tSZzpLvYjVFr2/EYdIXgD/6ZO6pslSjxkgYh1CmZ8iFFjLTSRVPDUsVKZQs+Z3XT1T4T71vLMrSqYvrrShALPUByMxcQbCybOqpzw7HgLBcDp9ccXCliy1zUhRjer5YddZNIXTTupyBGoxQj9GajaQPoZiwGfeml03jD7834fOHlBxKgj33F1IMeXboXuzdq84NxQM+cjznSZm2+a6cBPTTNoWV6SXd+d0G+pCMxU0Cni4291GPMmjSxesOCzyliVt54xj6L9l1RMStAp3ZzYqGYWIJcSGkT1lzeVJNreXjFHFxpYjaRhEwxU0Cni61cNv/muLypBnRzw4LPwUMloHuMnWfg86/6JUB/54BxiGP+aoBrd/N7oxh0EMRj0PMnAlzXu3kb781i0EHQ3GFAR36b6Y/iehCUpUs6FOt8zyycmi42NF01dgbTxDrfO2seak8TK5Ur7sSsHOg0MasQR5oYvTGMjoti4s91dJ5NAT0eBMMpv/3NAZ0hZh7iyBIz7WW6WHtt0bifolgsxBHUCIVM/ecgaKpCHDfP9ATBq4aQXguCeAz67rcGnjUE9J3JJbgZ5PeF0uz6Js9jaGMGUGvnRu8ooOuhz2se6U0kZtW5MxhYBXtVYqWy+a/1NLGxyQZ4gwtOxOqBrRut3GfRgXAgZjF8mSYGwxPkeFatxUJilDc5oI2js1L+WTjSuGIRg04V21y1VUuKtdeMx0JTxVaH7fsZDRI2cWxwJNiAm6JpdnRwcA1Qa+VGx0McT7z5jE2a3Xxb/L5QHvT8Hjo+OL+nxQAduroly2tQvKQFv9k4apkiBjh1AGjBMmPnPkUMXVRXYvZKCjHKVEcHALI4JnosjwCHDQzBtdcu23nQMrm4mBNAC2KrlnYpxSxC7SliK5c3HQAafOAaB3OwXgjQFybPEC/61X4cH7wwOVsU0NvHvrCLgL4zGSypAE3HCg0B3TcZnN9ZQHOQ1s3957FJmn4VXdIClU15kyZWssk/2x3Lyg7FrL7R0sSswsaZ+6yIWAgr2xj0CktZk8WsAJ0uZpERkmGZu26u0ivAXgzTMAIeiLYA9EgQbIiA7oGwxqWXTt8888Ac0Je+HJwrmmZ3EuPO84P83gjQB9vu1W8IgL6Ncef5Ln5vBOhre+7/Q9+OApoN5pUs/K1SdejUQOySpmJ4YZuSK03MKg8627JfdLeemEXaS45lpjstTcwqJ0cUE2FjlcWxuth+3RmgU8VWLRzeNDGrHwoZ3TTvpygmAhrvH3JQa7aN9YdNFaDx/oJhFsfN2QMv9hfNg+5toznQ/N5wlDA+k7B3D4099xJf+JrxTJWdnklYL1shUPS6o0uaig1NVy2CsylidtbthmWYHFxy1k2bEHSKmF1We2o3y8Qhrtpbxn+u0wRhmzzo8fgUOyFl2eKnf4qYXRAhRay9Bt9DZWfdtBkMlWYSQogDBglr6xa50M34TEIIccAg4YGrxBe+aRqDXpNnEt591nyq9zybQDhvPJHw3mjbvd7BWIhjns0g7LWYSbjnfm/XTgKaTUGwCiTUq0PfXBAvaT6fwWYiW6qYDaBTxWBWnDPLnHbTYi7ILnUTxKoFLGO/96OZhMZ8Xmw/Hhs9C8VswJUiZhVISLVMmAToopvm/RTFWFiDTSA0n0j4sLn+sBYbJLwwSWcQhjMKTfg8e2B/f2FAF2ijgzKgC7SZrh0GdJF2pHvom91bjqo3eLHHVaxwXYlbU+0Xp1wVqfgEihWuxdEceVgbcVWL48rpA/tPP0pAqwcJ7YslnW/hYknysJIX82LKQcKChX/io2dezHyQsGixpA2HxZLkQcJdBrQvN+rFvFgiD/qxL+rZumKtXm7UA9oD2ot5QHtAtyqg33rrK7sG6DWXIY62Fg5xdJ5y+KPYiz3GYsUIMzfs8Lf/J1OsaATaYYjjwstO8qALxJ9riTzoAvHn5i7kQVsHGcuKzFkv5sUSYgVjqcOJBGEvZiZWMP7cTORBF4g/n3GTB13Eg07kQRfxoHc+D7qAm5TMnPViXiwhVtgblBOEvZiZWGEPWs6DLuRBS3nQx7qf2f58olrSTgI6mQddANA7ngdd5CpMZM56MS+WFCsMm0SCsBczEisM6EQedBFAS3nQxxae3f5wwQbQBzFxvc0c0HIe9O0gbF3GgN7pPOgKqwuJsy6qNEGKv5R3FSYyZ+uB0Bpml7QsxlfNKnFzKrpzL1SWVUKzDEuOqMSirja2iopBJaIFWwxmdLMRObNFulkKzCepyGLIjK9+4xt/Senxt9/4xqIZbBIJwuPiedYxp79UlUpsOVJi2osuxNCB1TdNwzLrfRZN2SZS61IRfi1Ay3nQPa/x9r9/1xTQUh70se/88fbdvzEH9Mlw5wwWHSQUAE1H/FppkFAGNPJZBzyqYaUigJbFSsywOl9EsKT1vZFiWcXSsJTRs0iuWlCsEKCzusn2WblIN/GkCMoFLSsM6MToWRFAJ8QiDOK0PSNAZ4nBX4wAnWdZ8UFCKAXdDGHdtB8kjAD92mtPFRskPPbDzz7zV8eMAX1S2NGDBdPsRECb+tA7nmYnA7piUUi4OKAVYswQmGeMCOMevp1lIqCLl70W1arFxOwBndfNhnBwbdPs8Ou6iH3FAa3KP7MGtEpMYup4YFF0VClG1+S67Myywml2uF4sqzi6HgRN+zQ7EdCGPrScZnfsh8e+83uZgP7su++++y/PJ2txIJhHyf1ScUA3w+W997Q+oMtFLmm8qIte0oIMubuChgHJuouQi3bLZolqWQxXQO9mPCxYddk5oNkyu/igMKBLwcQV6++gnQM0nyt3mZesKAhoXmIfHhQG9DC3LijaTcmywoDeICDiMY7CgP4N9Yj/l6ELrQD0E28+kwHoz3/uXWzfiy8aG9ZIOkgd6Dv4y79mG+JohgtY7WHVk7TqJu16iAN/0mr50BWCqLFJ1bi/AGh0fzXUVGLsC4Mgogd/LhNZPddeaVmEqpIQ284nvlKsFGIZPMwG9zRzYagSQ0CTvkIvjUiY1k26k/Ag1HUPZtrRhIVxDvH9XqddLeV+wcliKYAmr3xjMXo5pS0TR3QlUKU3WABaKbYcFl5CHQD0so7LmibGSkEh6LVN07GMVk/SQLUsFkU4aiOsUlITTw2dokmE5CNkqxE1oB+8joCGW/Cqf5u3nncwcfrSl+VqdplpdgOUz+/+2zOxcqPS6OBBzXCHMg865kF30TudcMeu5EHbAvrNrUr1SHelnAXoMdbRXBdRKUaBUCfGTOPaUrreoFIs5kFXWXBVIw6jEhODLXRpqVKg1VGVWAjoq4axpbRuWgE65WgSuQbY1m0EaFlMDei//Aa0v80D9NTm8uKtqeVhJ4BWiiUBfVEr7JsmNiyIaZumY1kY8lg0FItQuwFh6BEjQI88XF9vjqw3Mz1oAuj/D+MdOYT+woOe2Sune87oA/rDF8F5prfiorESiufRoZ7XCHco8qDFGPQeWnW0C2/Pt0AetBi1NApxYFH4SjUD0HBpLyDOGjZiaMkQwLkOOiVtBzNFLIoNLrARx5A9ZmJisAWXjSUvEApqBE9SxADQ5vGblG4ij1m5Uf0Qh/po1sEqTmRtQMtiHNBRW6TP6e1f5riDiKZFNyEOlRjHICvuOR4w1zfXh04RC9uikXOfb9kKhrVXWIKIgVi09OsIhDk2zEIcWOJ/fT01Bv1b6kcTTmvEO7DEf8+sCOhjX/j97fQQx2ep70z86H/PAPSdSe2q0Io8aAHQQljjmhag0/Kgn6LPT//nf37A/vTR0yKD5Vc/OO0a0Ftjb/AkruwYdEkn6KsQw5gGZgPAb2YdmGaIVeJ8ZpFfol42FxPDxtDZbu3oS5oYANo8WJzdTcNBQtXRpF88vHf6gJbElICO/Oi/zJsXN4wTL9zEoBViyUHCYdF7tRYrm5mmZRl8Z6xqFNSOi/GFCOmisdRvNohBjzR5Sp4K0L9lgY4fkbt6fkD60ss4WUUE9MIP0wENEeh/V2RxJD1ovQh0Xh50GNbAMMd5+zxoQ0B/8JFrQB/p7jzV+d2FXEBjmKNhI4YOOLAZc7YoLKwtC7tZjuDPCWQqlgA0DbWXrSwLAW06cpndTWqONqDVR7OCVvGvRm1Ay2JKQJPbqVjkI6XdmpobnrvsaJBQKSZgcHgzxOBKrmiemFEWh4Zlc8x1NrdMiHA85DEObUA3Rwidg7QsjigS/ZvoLqsW9IWXL/yqPw7oZweezwT094j7/C//mg1oHoNeKjZI2EsfzegmRacPEn7qvz0bi1o8FSOw9OqTH3yUBWirLA4YBaqz96YCuq6ZcacWI69U6yxKUtZxdjPEaLfESS96YWOVWCLEEcagG1tWYgs2KYRp3RRTCbUBnXoAhI5pA1oWU8agMcKhAWgY7OKLsBQGtFJsOTa1hGdx5IumiVHPFTIvhvVN07BsLhopNLQsjHCwtmECaBggbLI3SzHo10NC06HCfEDDAOFaEJyJA/rDP/zrNEA/8RM2Rhj50cpBQnwlMEu5UwCajhL2YqzjmtGsFRnQH/x5jMRPSs9jrxI8/45zQGuk2eFA3PGBkpl3KKxZGgRfx/FBGCl8zio7Th4krDPYaANaJSb6u3SQUHvMMSXNzirHOyvNLvr6KJBmR38YhHvJIMShkWanC+jdS7PbFLIvTEUVWRxoXuE8aMEyfUCr0+wE395Vml2dz1PRBbSq3Cjxnu8u5AM69KETaXYhqU+azVpRABry67oIpSEUXQjQT34wG0Pxp+IBjvir5L1PPgpAsziCNaDJ9hcnGU8nrlrNL5EBzTOYi5ErmWa3ZZwU/TEAtDQdpx5zpB0AeqpVAa0X4sgB9NwOAFozxKEE9LpwNNcdARpGBXGeSkFApxdLAkATNMPdV5UTVQ5i7BkGCVWRD70lr2J50LW+22Gc47z1klcEuMQvDsMcT300qwxwzArvdw3ozlMAl6wsjshrbWiIKceo2G91swltONM4JQ+6QvPOWBhZo7NErBJIYmhYledSL/Cxxvw5J9BFWkTIAaDphOqqG0BDfSM5xFHnRtV5fKixpZWUozPVmw0S5qbZpRdKtgF0yoRqCdDlGGlNxYYFncJTvRVfHavGlvEIxzp/0DQCtHqq9294LPpHJoA2rQfNyXwsSoRWTfWGaSpt1K/O95xVedBiMQ4a57imV5gjJQ+ajRF+1M8CHlJEOvHqkzsQg4aiv537BzI9aJqlpRGDLuO/RJYXwzISUTsfgQil50HXQ3dQK80OxN5M5J9JvuXYJJtTk2MjdrEy4QbQIFap5nrQeiOrdOeXqoqpnGGgPQq3N3RODaketAxo3TS79ELJVjFohVgSgwRtc/npxmliYuaFQQw63zLtNDtVPegRcZJ3gLc1+3rQYR40C3Lox6AN60HzLI4EoKViSQdN6nJk5UFDcKOXP2nqLOutzIOmo3888vyk0oEWX90ZD/qVBfg/OwYdaCU4KD3oaEwvjB3rWqZOqg6naS/oB41BTGLqVqJYkuZEFRAbOnXFnQddCtJmEoq/QRY095l0AKLvGzq5h4Wkz2p50Il60CkTVf5Sx4NWF0q29KATYglAT9TClA4bMTHPzsiDzrNMe6KKqh70RuQx0xiHUJfDvB50bKLKb808aKketHLFqygPeiDFg2ZlOKJRQf1Eu6w86PM80kHg3KtTOSm7HvRTNMjM7sLUOppc95QQl34kgKZcLdP5KjaAjiK8JZOJHCqxqFuVIBzs0tFEobE3EpGcUozvmol2EC+pvuIO0LyfaYDGPai140CHOtBivVdhvmSZfeFWK1qATtSDTk71BkJPfVUH0OpCyZaAToglAT01rlWdKEVMLG9kBOg8y2hqiE5VDkU96FpUaJTGOLBy0ohlPehoqncPutAmgJbqQW8fI3T+TOpElWOYwAGO9FddLRqbyIMu0rLrQXMy//l/KgAtJnakA9q6gQOnDHFYiqlnvViKqTO0LcUgr9eZWEmZmtgKltEvW2eWSfWgUxoBdId5oeQilew/gWLFC/bL9aCLFOyX6kFvf+b57e0PD6QBmtdKkrI4iq1L6GzR2NRBQhZeptnQTypzoGOv7gyg1YOErQDouksMqmtC2XZz65WF1rSMBo13a9FY4j//LXWnpywHCS3J5ReNbbFFY7MBHSbafW/bFaATaXYumjoGTaPMT/GxQsm77t9RQKem2XkxL5ZMs1O4zrTpZ9k5INcnU+yhq1Yc0Ko0u8wQB6tnl6gH3eKAZuEM6kc/pUyCjr3qAe3FWgvQmAn9DbPS0B7QjyOgswcJnS8ayyraOQxxqKvZfYo8+3P1tG/FqzsDaHe/sL3YoxdzF2OSxApDRl0P2rItuxTbpCNxm466GSzuiFhhMCemehdpRnnQOwFoqAl9z90g4e3mjpYbLdLU9aC92MdTTJGI7kasMGzU9aAt25Sydqk17i+7A/TyokMP+taUUw96Y90ZoI3yoFveg75///aelgW0uh60F/uYirWsB73Zskxtv37dndiqQ9++/WItuaJKoYFCdyEORR509/OGgGZTB+Pt5JIVoG/H6kDfPm8I6LYdXZMQM3yPdHO3h2a4VhpWl3RiWsTQgIlcjlhC1gQ2rOipZIluPxWVquXk4krDEoM0URE3L1UrjWJMpeVAuMrQQKVRBNBCoRFmnz2ggYrtNctF+qRCybjw0+XlMD1vuQP+M/j1H3PHk1uuLhp8ccQBvYx5ykpjpjbzbZwblsUu8y4Kn9mhBeipObmaXTNaJCVcLGXDxIEOAX3py8S0c4JPbMRnKQ96++6zWVkcakDPD9J/LjxoQPJMl60DPd+1e4AuGU6WSGQbU9qEf95vAugcsaSsiRh0c+ib3RWr5WITYi8tbHX+wnJp8EQ96Kg3pWpRMehfpcF6qbOfMr86SBdpMrMLQOMkZUtAJwolz5VFTpnh+dbUnDtAr0oVQkHsljJvcK6cS1aVZWyb5Q7zEIcM6Fo4tbsm3es60BGgX37wgCYzWwBazoO2ATTzlcGPHqTLXUGZpJNL5PWDbSdPTAYzmZO+VYDGChy3TwSD58nza3tuL00GgxpTCWfYhPAdBjRbGGSiu0JdMHJBEn/uncmJ17NmASayjYEJKIUyJaziTJ5oySnF6IZ0WamJK1WcdkdksdB+JdAX44AmJixEG2v2UxZDUFUaaAzfVneXJcRILytnJ14HtbNVbZUUMQ5o3O1kP5HHzKXWEZXdccp5WDh2oELtKwDo6x2bP7+1OIcO5sXL7TXiGxLqrC6SJ+MAoqyJ1YlCyQjo60QCC1NQD5qqkReXsyfvySOOy2zGX5mKkUcXTb5HJA+6A15Z7sAZhNwYtGw1GEaLDS1b7iC7qhzeoaxWVxOLxm5sbNAJ3g83giZMIxwh9+sbtDJHXmEONaCJIz1x+sJkcHb2wNXghf6eIHi132KQ0CLEcZCGN+7cII/I45NL8MI1DujajYM1/haNNDuc6d3V1wdYbhJcU0DX+q7hkrCWaXbOAI114rqHBgA75P9KGX9p00v6+ECprOM3xZiKUhVWSYk+MZJTABq2KlWHpsnN1tCb5HUwtFExEOMhDmJCNdrYsJ8SoNEYvq3pLosBukzV6uYqkhgPceBuB2XeT5ujCfuJ7LQS2bjB7LNPs1v+2fX26wRTi8CXYWDP8jDlzDA4yHTWm3b+GQK6TLaeAn9XBDR5cVjPBY4BGu1CMfJo3NzRj0clljuISvsUNwYtAw+6bGgZiq2SrUnn6N0w665+V0NA10ZGahiqGCGe8whGLWoPCaChFBJ5rBXskEIcf9hPnGfiPq/N3jz34Oa5njNGvrToQZsOEqIHfXIQ6/aPYg0O0YNeuof32oAmHvS181B6Yw95yAENj1oB0NSDpsUgEF0CbRr0qSGgQQq3A0DTJyZyCkDDzZFuUIS1TMjrWOPDRIx0c+ynTC7a2LCfCg+6m29rustigIaNsH/GKjKgG/QWdzsFdLgDjY8miqFhY28w+woAuuPWtwm2oMgFBTNFI9KLEHFleNMY0LA1FKeIAbpjk6sbARrtQrFbUyYhDpUY4HSOevZhFymgbSyDiMkK2WXsTgC0XlfFanbByEO8qbHSHAjoDQJoWGylaQLolx9c+uf+B8RvDmavnCZYJjeXXu45t2uAxvhzb9vo4L3RNk5iwDMB86gdoPfMdN2fCQE902qAJpdfXQJ03RLQKMUBzZ6YyMmAZmLcgyNgRA96a8sQ0FvoqFKlLat+JmPQKGC1yxKAjjzoenFA426PAdriaGIX66486I7l64vonyJ4yP8rZXIzjoBeGb41ZQdost14BOhxa0DjFihW0IPu2GRfOjQSwVE6bg/omAcdAnrcFNBNKNKPa11tEDDDQoMCoDfWzSaqQIiD+MsEy2uiB20JaJs0O5rFcTII1pbAeV6CcqPEgyaPr5oDOmBl+tvOUyzPBydaDdDkt+yVhgBoFhG1ATRK4XZD02X2xEQuJsY3ROf5bBWXMiGykOLRMAU0gQ1XCho2/ZSyOEosvGu1yxKAZpsbqqQAGnc77P5GtO8sjibsKNsYdALQc5fBj4Qqb+g083AvUujW9U07QC8HwXWGZ65mjEFwnqldIGYag95UZnGs0kgHNQYl22vDdoCOxaApoE26ygGNlUWDDYw415pQrn8D7imgH7KFCk0A/WDtXE8Q/I9zQgx6FwHd8lO9WyQPevdmGtt5cH52dguI5eeEaebf+anej+VUbw/oxwHQmHvhMfg4Ano5GPZM9YD2gPbFkrxYS3rQnqke0B7QHtBezAPaA9oD2gPai3kxD2gP6J0ENCRp9MIahPNszuA8POmlN/DKnas32CN467xiucII0JCs0Rs0o5W84cl9otylubb3TgIaJqjALA4cradJCj8d6HxPexHt2CUNkzdAh9yUWeS4TBWjz4g+yFCMbQgJzYUsw0/nawGWtZYdT4phz4RuMjE7y1AMRbhYdFysLcNyIWiU2Y5TivF9Vhb2In4GPko/XThscGpdey0Ypjc0OwETOYbNyRWJbW6ulJnYMM13iH2Gmdiq8UKCGWJoDH1FtAwNzjEvBPTKcJYeM5PoZSUphoAeaT6kKRyQ8czTnvG+FtRgTVnI44Dlu0c0AH3p5QuTwav90Q157cDV4Ayd930TprFgYseV0zsE6FFIslu6NzpI6HtwiQL7ZBumQbOJ3L21G/QRvBX/mgromWAP5NRhPQ68wSeE2tfO39ct07FjgK7TVateWQhzsIamj+NUPfMsLxSLMm/pJV6pomL0GTnJXkqxI91h4jMTs7WMTpik/GtwM19ZMBbDngndRLEj3XaWoRiKcLHouNiJsZnWQiK59o5TWxYeTXyCN/gZ/GnK6cJhs7pI03jHaVYwLwwEM/gWjTEYiRFUlVlG2q0pnnSMj3IzqxVibOI2vmIH6Fg3MQUOexilQ6PB/NPyAH09U4+aCXpzwxqAhhmDDzcgra6JMwfXaQ2k9XWaaMcW714Pp3VnAvpUP3D4XHQDy8eee7A2+2AtmI3eMAuLeO8IoGdomjMu/oroBQTXDg4Sat+ZhNocB5emb9BH8Fb8ayqgB2m6Myz+Gtayw5VgoZKoZnW7nQJ05+f4vI2Qm6Uf07nUZWPYoBjqPNcd1teBycY/hro9UcqwFqAjMSijsRACmopZW/bKWui/V7iZmjWUYmLYM97NLVr3k5q5ZSm2tRVSjgA2PC52YmOTtJtoodmOS4rxfRY9wRv8DHyUfroIP9eXF38OFd1+zsq6rUDGMOBm2Oa3PxPbXP0ZW+S6/ThPC8Ya+qyQvplYVJNoedE6KsHERKDSDOjI4J9nV7bjYnR6ZaoeNRN3QMa3UTiTELlLaAwl7ADMTQboJgM0zGLBGSsZLnQsD/pBz2zs5penCaMv/A6mQhNYnzpBPOgHGS508RDHvXmE7vQNFuI4MTqI8wnv3Wm7c/XG9A18FIY4TmSHOO7PNwV3GZ/cX+vTrnO3oyEO6qiV6M/psZ8e2g+/WS++YfdzHXWOMHKhDioKn1HK/N2eFCMq9OqHJ0zM2rJ6dSuq9sbM1HNTE7/9L75xpFsQC820FIvqz+F9Sd+1V4gRs8Ze3NpiB8JoxyXF+D6LnuANfgY+Sj9dInLN4U9xnLPMZtptruCUCxtAc7GV8hwF9BwEDVYhQoGP5vRDHJEYr3xEJ8JYAjoUW6WLttIewpPI4Ft6gKZlnFL18G90B2RMV+GAprU2cA4heRgEtSYNcZD7DZyk0uRlRTOmFXJA94DHfOH7/eINsBheR0Cf6gdvOnvmigNAY02OsOroySX0oOmjIAiW2Buit2YCGnzlviWxLDRUEo1eeZSAhol2OKUXKUgDnwalOWOXNOqIrmWDKoafwT9IW4wbQ7fWjcumiBHkUcugVCc1c+wNG9qDUWE3Wd1P231GN+XFQ+k9Py6WYuwGLTTbcUmxcJ+FT/gr4qNsQEPJ0JgHzQlkUEkzKcbDxqiDs6G1ZZNim7wiyNxl63G9yLKOME7CnkQGa3rQgN0MPfwb3QEZahzQiN2A3I+EM74fUnBvEA96g3nY3JXOATRg98Kv+sUb5kHTv4GHTRhNnvac2zlAYxm7O5OD/PkojUHzePP0DfaIvnW0LRPQ1zAMzeIZ+KRvssugfv/OAhquruhnKi12Ua9aYhB0hOAs3LOyGvRvOeGTpFipKsZLjOocq8XAMiioQSO02liVxephDBrFSlX7LzUQQxEuFh0XOzHeTbTQbMeli0VPkjf17Bj0ymUKzSgGjcFUs8oXSTHu7GI1Ovz1Hz7qMBdj26wY81khxoM32EMel2AGa8ag4SsjQ4+Zqe9BjwT0HmPQTRaDpgHpJsOyvgd9Cagc3YQxaAQ0A3XP7M560L1B7cYousrTN3gCB7+5F74WJXzkZHHU+qgrvdaHT2YwgUO3GsfOAhr+YfIAXsO0Cl2Bn+ssoyHSAdnoM97LrEqsFDs+0IlxF9jQGtAxsTrLKinrF6KXU0JYFocgdtw+v6S8hSJcLDouxSyj90Y7TimG+yx6EmXXxPJs0gEN5eI6ogyLOYN0iyS5IjHkExUrhykU5TDlwVBslfJzPHLL7S1DY3g3xbSTOe0sDuLQZ+kxM+e0Y9BNzNSo0cSN5kNa1K5Ja0QzLOvHoNcgUyO6ufD9/iiLA/9hFsfOxaB9HrTP6fViPg/6kYpd19xAM4vDbPWUnCwOvVznHcvi8ID2sPFiHtCPVmxF89eFbh60Hp/18qB1l7fygPaA9mIe0F7MT/X2gPaw8WIe0B7QHtAe0F7MA9oD2gPaA9rDxot5QHtAf3wA3aLNPaC3ffPNN99asX3sAP2RB7RvvvnmAe0B7ZtvvvnmAe0B7ZtvvvlmAmg/SOgHvLyYHyR8jMScNp/F4QHtxTygPaA9oD2gPWy8mAe0B7QHtAe0F/OA9kz1gPaA9oD2Yh7QXswDOq3dmaTrgDsBdN9k0NWygB6bxJWj3VzSXuxxFSsMmZVgYsoZuT6BYq0F6EtfnjhdHNC9ASwIezLA1mYE6NFBuoBsBGgQ6xPuDdpM1+3mDgO68xd4KdUDXm9+7CXNxamPdNOlUYRLOi42NhkEulXsc8UECwuLVeiBrbqxbGjanWVQXV97Ta90seRRdSAW3puJ8arFlBjsfi6AovO65TTpyrKpYu01/RL7uWJAt4kpR2IrcJqVXVk2rq0VE2Pti794OrrfS6+AfltAX3jptHB/4GoA5fk1S5D2nCkM6F5C59HaDQpcdq/fcEmsCNC9hMoz5B+/N2u39+wwoOvo65RgXQy8poamJ3QvQ7YMtXBJx8UqBkuM5IrVCbbq2oI5YviKI7GhaSLkUmxoulFwn6m6W1gsujcTY8gYZ7DBe1zVdVx7bVa6ynaa2OY4LDLS4UgMeK8L6FyxZaPlZ/O62WG3z1ibmXg6dk8evfCMLaDXqBtM7w9cJXRe0yU0XQQ8AvTdZ7fvfsEM0LgSIVuO8GQwaBrkWIvFoHHxQXLD7w0B3bazMWhYDqkb7mAJPFyKqnRR14Pe6jwVj1rKYiWDdbPyxNCv13bu8ywDgkx0t6BlaFVlYqGQmKq7hcXCe1Mx6gMGAfec4X4ZbrQdVbZkSJoY6qzqkitHjLTVi9qAzhNbNVjRS6ubNvuM+s3zAYKZ35O2NyS1KaAvTAYIaHZ/6SV+Y7DMigDoY1/Ztgd0b82Uz2wdcDeAnu/aWUBXyhFf8Hoee6lHmzVsGerwkpbF6g0DPueIGXnjuZbBD4WyIzEjQOd2E3BaVEzR3eJi4b2pGPXnhila+L1JJIGvsp0ppgvofLGVy/oUzBMbN1jcME/MyBsXxSiNOz790tPC/fb2E70dtjHonjMUx+zeCNBsEXAB0N85UCDEYe5AjwZBzVmIYyYIdjoGjVcdcgEu5aHpqvZlWA8COWoZE+t872wQ6PpveWKlcsWdmJEDnSdmFOLIE6MetGZ0PE1M0d3iYiajEzExCccR/XR/ro8HgRycTYjNBYuOxNpri9qAzhObCy7qh9rzxFaHl+3EWONg5vdWDjQPcXAc471RiGMtCOIx6LvfGnjWeJBwFAcJMQJdPM1uhg0OzpgPEu5Cmp14KTcgKqF/GSYTs2JiY5MNeGXBiVg9MA5qp4sBQspbW1uOxAyG4vLEOt/DlbKrhcQU3S0uZgRoRZpdgqmr+pHeRP6ZJKazjLeu2OqwfhwhT2wFIuMrl92IjQNyl8vmYimAnunYdgRopK52CFpOs7v77BNvPmMI6PkaJHKA7zzfVhjQ801I4OgK71sY0FXAqStAV1kks+pErE5THKqOLDNVyvyhAEydWHBjGUR6ewyPgBMPercBvarr82oAGuIAjjAIOF1x99Vh4tznAbpsKaYG9Bfn+10B+sLkGeJFv9pvC+jtY4aDhBjXwBi0xRDhnclgSQT07YDGnvm9aR70+d0ANI9Wlkzyz8YmaUKYfEnHQp+6fMgTwwFHV2IGQ2f5YkZhY619VlRMKVpUzAjQopiaXOP6EFxhSXROMJgntkqvgMUWtGzYUkwN6L2vPu8K0D3AZt0Y9KUvB+eKptlFgD5onGN372DbvfoNV4C+tuf+P/TtAqBFaGlfhqXq0KkBxSUdZSQs6OfO7qoYJqDpAlrLMt2dlieGT3SNSxPbsvkqyhMzArQopg4kGDi8q4vt17PIhc6zLrnyxIzyoPUs01TbMTE1oN+3yLFzAeibswde7C+aBw0hDhwktAlBj0ozCSG0AYOD/N5wlLBrNzxoGOTieQ0GQ0GJuWcxsaHpqkHYOFesYYDVHDGzEHSOGIQ49POgc7tZJu5ntaBliqNaXMwoxFFPzCSMBxKMggjjiSl2MbH22qJBcDZHzAjQu2pZe63DIJtwPDGTUAK0XQg6NcShnwe9Js8kvPus+UzCeTZI2Ltkzue2e72DsUHCeTY4OG8xk3DP/d6u3QB0OO5ucBnWq0PfXFBe0kwMZsVpgytPzGS+noaY/sjZ7nYTxKqFLUseVQdiJl/dgljhQML4YvvxnMQL/Sl2uWImgM4VmwscWmbbTSWgn+g96gzQkA+tPUi4Nntgf39hQBdoo4MyoAu0ma4dB7R9O9I99M3uLUfVG7zY4ypWuK7Eran2i1OuilR8AsVaqxbHldMH9p9+lICWBwmLFks638LFkhLDSl7Mi6UMEhYp/JMYPfNi5oOELVMsSR4k3GVA+3KjXsyLJdPsfIVQX25UXW7UA9oD2ot5QHtAtyqg33rrK7sG6DWXIY62Fg5xdJ5y+KPYiz3GYsUIMzfs8Lf/J1OshQB94WUnedAF4s+1RB50gfhzczfyoG2DjGVV5qwX82KyWMFY6rAqQdiLGYi1DqAvffmMmzzoIh50Ig+6iAe9C3nQ9m6SInPWi3kxWaywN6hIEPZiBmKt5UFLedDHup/Z/nyiWtJOAjqZB10A0LuQB21/FSoyZ72YF5PFCsNGkSDsxQzEWgvQUh70sYVntz9cMAX0wYA306nea8k86NuhmGmlpLadz4Pu3Bc2OiN4qIc8PKx1FSYyZzslrUP79r2te0mr0nB7BC0jPmRYRuWIZd1FxA6HBr5d0LJD3KZoxw+9XbybC+73ma0YMuPX+/Z9CR+0f23fvj+SgEJe+tMM2CQShDPFyKv/4VAsE4OPUOzX+vuMjsTt20dH4j5/aN/hfy0I6H/at+8PKHHf2nfYENBSHvSx7/zx9t2/2U1AJwYJBUDTEb9WGiQUrkJEFmJCB16qYSVB7LApoJNjVKHa4QFTPmRZhp0zAbRKzBrQCTEE9NvcxMP4ymEH3TzsfJ8VGiQsAujE6Fk2Bn/N/uhEzHBcb/fEfq2/z1oL0NIg4bEffvaZvzqWBugnfvIub//yvBNAK9LsREBbVhvdHUCDo9RpzMNsDL69ZStGvyrM8ZBrGXTzkIVocUCrxADQPd2c1IdF9eIHwOk+K5RmZw1oVf5Zpti396UD2ljMNDNu98R+rb/PWgjQyTS7Yz889p3fswH0krM86NtsVRQsxnG+9QB9OORhtxUekuRCti4UBPQh9lVxyOIrI52pQ5SpLQXowz3oOB/ucQHo2AFwt8+6PaA9oHcG0E+8+YwOoP99Ow3QvUEwOBkEOpX7T5K33pmUsjgiQF9jgJ5H3zyvbhLZrqtvMpnF8QF5MEtR+6noYbx9cDp6w2n5vUpAU2b16MYUKsFE99ikNO4vX9IA6E4NZ04pxhkKWjxujHKHi1jGvjRAHITzepojxgBNnf3DW5bdJIAmZvRQQB/SPAJaB6CQZdKpoX0EZDElbBiTKWbgCeGqijjLwcTUSiClN2SJfY3uPyWtjMXo/b7D/+8PktA3F+Pd/JILy+B27gfKnspiSkD/2b5936Mvw92HeJ58xRbQb+3b91/oy3D34ACI/YFqPe9g4vSlL8vV7PLT7D588d2vbmcB+qpmrOPavZNto4Mna+ke9B6sr6EV7ui7f3vPTNdtaU3CJz/AR38efyjzmVH5U/iG0xzr7L2pHvTb+oB+c6tSPdJdKadf0kSE3L6lI5gmFiMBJddbubjJtox0E4w5pBnfzulm6I5r7TalGAKafAMN9XQbAVr3ANhbJv/q0D0CspgWuQ6ncHVqc3nx1tTysBNAG4ttMjkVVc3FQi0H3cQvDir2R3li+YC+y7WecQHobzG1300A+gsPemavnO45Ywjoz38uDHAkYtCDCGjtdVWw1P/JtswYdC+/PZ/rQpP33d4TB/RT4AYTND8N+P1vz8Kt7EMDuBHKT8EbnvwI3vsUsvmDj/ozYtBwGWv/wMY68JVqCh86Qz68rfMLWSXG6dItKx62syxsnDXdIXkKiNH+Ect04gAqMSDpIaLSue9tsxCHxgEoZpnq1NA6ApKYHrn+dLP9ByofGsvULy/qkysrxGEjRl5Tu73GYk67+Wt9sVxAP9Gz70u/D7f4UlFAX9gHr9HbhAsNpf17ZkVAH/vC728fy87i+GwU4EgBtH7Z/jsncLJKGqAjp/maRjy6bwknq0iAfhpvCWk/AD6Hd4L7/NHvUEB/ir2XPPkUvgkfpgEa3Sz9COjYGzgjIQfQh7e0Bh4VYpJnGnlxh+0si3WTBbY1QtHZYhGgbfcZWNJJrDi0b+GQWQw6/wAUs0zeZ/pHIC6mRa4v0eixwvNdGcaJF04AbSrW/rXQj/5Sccu+Rvvnppu/pirqUHRcLBfQHyKgC8SgY4COniiiHJdexskqIqAXfpgD6Cd+IjjQakAv6deCXrs3P5gC6GasjGguoGe6CJ3nu+6nedBPfkCDGxTZAqBnidd8OkL3k5GLjY63GtDCha1zQR/p7jzV+d2FXEB3R2EFQzEhk4O5gQtaeEizTM7iOKyjli/2tm6cN0UMTBjqObx16PCAEaB1DkAxy6RTQ/sIyGJ6wVnIDvtB8vf6ram54bnLm24AbSwGDuofpQw8mlvmtJvsj7/WsEzHg9aMQGsA+gBznVUu9JXTF16+8Kv+OKCfHXg+G9AxB1odg27TrwU9OMocbikGfS0i9IxeUjQMEM6wjYRBwqfw0dOR6/wpjFvEgxwIaEbwCOQf0Q2SMejod6suoGEUiC/XkQXot3UArRQLs2p5NELTw8+xrId3uFsHNvliQgy622afMUAP9BgCWvcA2FsmnRraR0AWi+dWZJCrXUEuGOwaD4J4cPbbloA2FuMWqTTNLXPazV+HT3Ito+uo6MSgv6cJ6G9pAPqAAtAwQLgWBGfigP7wD/86C9BxB7oYoLPS7GY4knsxheOaUcqdAOho4O9TGFcm3E0FNHWdI0BTQisGCQ/xq9hJmp0wRqUFaJVYtFHs17qZfQrLqJAuoDXT7HqMU49jgCbb/0XP4a1DztLsouTEApZJp4bVEShMLmX+2betQxyGYlmANrfMaTczAK1Ms8sENLyoSehCgFaVGyXe893Mqd7H3o1SOHYS0Jhchwt7Y4adLaDpmCCO9rEsjt/RBPR/8qFCBaDDxFk3gI7S7LptAb0VDm2Fv9YXTJG6a4DmSScDVoCGAPRb+5wCWhwYtLVMOjWsjoAIG0ol9gM/Cu5m//ZPI1e6mAWgU8V4iOPXBoDepW5aAJrmaHzYgw8YoP8sgvKntdI4OKApfFkcgwH6rbwQRwqgM4slff5z7777PXeAVk/1bvJYNEFz5FCft5jqHQ9bfAA+8VMfPf3BR2F7OjXEEQ4bqtLsOg2zOLIzZ6OJKlqaaQnCYSrv4ZCFPQ7yoA0ArZMHDcjX+hpKT/emfTUCtM4BKGaZfGroHgFlHnQ7S9nl95Qv7V+TRs/0so0zxTIAbS72tfDJl5yIuetmBqCVedAQZ4aRQH5PXWfwnHGQ8Cv0LZqAPsDynPn9PwmAzhoktMmDliIcRWPQinrQYR40BDn24PhgF4akz1vUg056xRCKVgM6OUhIBxSVedA0JU4b0Kmpy9JUb61kNqWYMNU7moOukeSVa5ng2x8yzelNATSLRNtYhpZ04s6PAD3g5gAUs0x1augcAWUedJQETMFCvUOaK5aVf6ZMEM4U+3ZaFrStGH3ypeJiTruZAWhlHjT4yvuEUDP1qO/uY4De97Qwjphfze6tSOy/hB71P+3LS7OzyYM+9u67//aMSw86UQ86NlGFsLlXkdWhXQ9a9Io/xfibnKnyZCLNLhxQfDpjogq5/ormQcvFkt7SqtyjzIOOCP22yUQVrZxe7RBHdrax2USVtDzobhY+oNbQqnYDrg6AvWXyqaF9BFR50Oj4CdM0AFP7cH7Kn2bNBlEnCGeK4ZOUGIKxGJ/3opsHndfNw866mRXiUOVBh2Fm6kCzzI19/2Q1UUUg9B+EUwfRsuyJKqo8aNWKVyKgPxsPQRcHdKIedATo29RtnkE49+ZXTlLVg+Yx6NM84y6cy50EdGyiymmeo5cy1ZtmSxTNg44BgZwSC4e0hqiUedDSrDp4ttBZOA+6W5i8bJzTW2iqd1oedHcUGD9sUEhD4wAUskw+NfSPgCIPmjqA+/aFRSUQPjDzmZLrj762L6W4hCJBOFMMIrapdTCMxajD+m3dPOi8buLsbCfdzIxBK/KgWZB5X1iIA4H99KepP/2E2VTvkMKhkwzA/t1vsane+OwP1GuqJPOgyad+JiMGPRBLsnNRsH/QZcH+RD1ocX43fagoxvFk2lTvRBaHbUtNXd5hsfypJY/Ksk+KWO4RUOZB2zZlgvCui2nnQWe2jJpQO9rN1inYr8qD/szz29sfHkgFtDxG+DFYNFYolvTBRyr/OQJ0frEk25aZurwTYofCkaqFFrPskyKmewSUedD26+spEoR3XUw7D9oW0DvazVZakzCZB73LgFak2blorbfklSoxayfFOm0q0e+KZZ8UMZsjUHz5JlX+2a6LaedB2wJ6R7vZQkteqdLsckIcjtck9IDeKTE2Zvi2Z+qjErM4Ah7QHtA5gM4bJHQOaIchjvs7v+SVdes8tdX5XlB1wwcYUlIMElqLJXJ6i4hBXq+7btLFVF110+EBcBYvUS55VWQB1MRaUF7MSKy1Fo2VlrzSqgftFNCJPOgiLZEH3SqAHpssb5WqnfsH3IRAy/hvy5VYIqe3iNibiQTAAmI0B82RGLXLlWXkeDoTK1WHTg24iUEPb64utl93FJz9RIq1Ugz6zIObswde7H+UgE7kQRdqM8kVVVrGg35lAf5vRQ96yxVTUcwVU0Fs6NQVd2Ilp7690wNQl2YSFvEGN8elKXZezEistTzoB2vSTMK7b73V/bwZoO9AMVBFidGTOmVH5TxoqbLotT23DWpwJPOg3QJ6DIxr0Ajjcw3BCQofl640dAENYhMsBasSblVp2PGB/+ROlUkTVohVSC+PD8S20jGL037sDVEMnx3p1rRGjpdUX4kBGuA/NF3lEkMD2qJoGe2n6gDEgsdMlfi1z6UeTeZAx8SChlInxzaIl1RpKIfDZmUY07/kCRUd/CYTNuOL7cdFcqnFNqc2c9X0xaK2er3DldhUunXaYpKEUlESwxzo/0punns6jXr/958dNQD0pZcxZS6dw3/Y33MuDdBrswf2xzzou89mZXGoAX2iiAMt5UFD1X1KWR60MHGgu3YY0G9AVBSu6c79wrXLrlXpYcKBk0IcIMYTYDX5l8FUQud61QyAUXRcyumFjRlSzQwDMcjrzQe0ttMbj/RWCFDHJnk/6f4sZBnvuvhOrlr6QZo+6LwS32fRqbFlaB1aRjc1gk0auW5NtV+cyiXXXNmhmAjoRVdiWRZqi1nss3xAf/F/PrPtENAXvt+f7kFfOX1g/2kngD55FReLHTyJdfth6diTS8SHPth28sRkMJO6DJY8SMgATUtwzAcniAdNfGjiSC9NBoN5swl3epCQXoU3G1uls0HwzuTEX7wXHH+OPJx4a5o+CM5eOUv+eoX87fVgYiFzkBDJVaoSBJKbs+TdxHElNw36QkIhG9BjP8XalsSeAeLLTXSj4BCxaqBylpg5caWaJqwY8AIqv8K2Jm9fIBKva5ilHnFkgEariH0TC3ij280tyYN+58Wt565UsZ+VRiko4z6jT7ONTLOs9H8Rw26eDS7iNuSATtwkj8kRfS84Sw5o6tGkQWMZ0HAeHIKTIkAdst9/wJ69rlZSDxIy2CwHwWVAzOoifXQRn9IXrgeXl4PLOqNnarHVYHj54uVstVSxnxMF2PA6uZ8LJm4Rr3n1Z6ST3w6Ci9cvwh+SglpiYMgcORvBxFUippYy6CYIboLi5jjxk4eV/VUMElJA/1MQvPonR7ff/yW5//t5/PfCn3198tUecvHDy+ThnwSvPq8JaLLVq+Aq35zFRweuBi/Azav9N4MzPefoH9748qv7glf7swYJbUMcsPbrnRvAYyiARMh8ssYBXbtxEIsiaaXZsRBHXx+BMnGfZ0JA1/quNXUd6p0NcQAFfrD/ueMDpbPVrcpZGOMpAbPLxH2uU0CTv5XTvOkYHzioyvCojLymL2QpqLK8KhCVIO+vNMgvayYIVlHVoWkdYTHEMbFAtwZRap2JWfJv/4lutIpsOPQm3lh2s/L1UwOnXq9iPysN4qNi7+hTbSPjB+ANYtiVMtuGHNChQ/vfHMBHdXKQ9Y8mnhqwzwJ2Uvxg/+tkv/NTJP+8UAAaRq8oUYbpDQCGvlDeXB1Od1dV5IqLEf+U6WmpSUwdxlDG6nVyf3GxvQaPCeDI481xCuhMwXQxst1ysEi+isjjfywv50vldRN6tkg2Jq+MX8/vrwToDkJhIDG5f6d/+4nn+rf3vvPCM3v/43/+GQL6hWfeJ3/p1wU0jPhRDsOjm+QRYLnnDPGgOaBf6L8Jf8tMs3vWeJCQedBLtA4HQhlxzAG9dA/vNQG9dL/vRB/W6d8z04UxaAro8/fx/tEC+g1wVRmg4VoMMPBYqh6BX94NcssuxMYWoiKfD9yDbpCn7BF/IV0hJQ231CCucFAmnm9ABcEqUAW7dIRFD7rU4FuzbYzMSnrQaBU4z+hGd1t2s9I48tZPSlXsJwU0bM2e6hopHQBi2JUG24b4uxNv7R+YxuB0iQNa82iSUwP2GT8pfrAf9jt/ln9eKADdEcKG3ayEPmAHdRMNAB0XA0B3bGqrSUztYEwl/yam6P1iLQjw8UX6hwzBdDHybwX3WEcE6BzbcvfZ6uJ4ABMFV4h1ef2VAH2UAZr8+7v5YOIEWHZ0+9NfZ4A+ur33qAGgz4WAhpsrp8kfkMUCoAmvz+0goEcH7422cSjfuXoNAD2aC+g1GdD3bzchmjwjeNAzeoCGZa92OsRRARTUKaCJe0SvOPSgG9yDrisvRNUv7M7vLoCa6KM26As5l7IsRhwzwlR8P8FCXfSgUaaeJSyLIaCr0dacfXUdoKaEONAqHtQGNatuks2uVNFlhscc0OxpnpHqA3ClG45XtE3lxwDWeuRBq49mIsaEpwbzoCnsiQeNOvgs/byQxPBH92X8x2EyHrqEzIMez0KqXChZLSYAOkttWSm2TME5DkxFr7kD0yDGuQc9nkJVOhKXIQZOLvGgcWMK6DQpAPlifjfxBjduv/iP5dT+imIYZf7u8+Tfn1AKz/ySYnhvADcd28yDntEFNJTTIP84gtcooLkHfemf/44Bek0FaBd50CGgTwbBGvWa741iDPrefHA1B9BQEzoRg545f5v44udZDJrf5QN6put2c6cBvVX/8XvBWeJ3UYcLo5RViNc+1yC+4dkr8FflhShnG7MkAtiIxaApDOkLOeRKpC7XIcRBNg0aFfQIoxh0g31EurAsRrM4+NYM0FpmqbpJAY1WlTB0QkPtVt0km313oVSl/WwMTZdxa/Y0z0j1AQDDznJAw3jCXxD/ObjCDnLq0ZQT0emp8XUag6YnxfRFsjE/RdLPC0mMcRGIQUkaBBcZbGgMmr+QBuhEoWSlWHttGDVy1Kbkop4ohvyEeDP1nC/i4yC4/jO4/xn9g0pw+fJmttj1ixiDxuAzEc6QYnbldZM/DX5WI4/Kaf3lg4sh1/aSTfr3Us/5HQD0OzQOHbzzDrnvDf6DvqwF6Ac9RGyWovfCZHCWAhpj0A/WgonTB66e6TnH/yAD+tHnQUsedMF2e08LT/V2lW1sKoYedEta9jEW08iDzt/vKR50wSYXSi6kdTl/QnVmpEV0oK9fzxHTSbrgHxq4yoMG77qmmwe99+gu5kFDk/OgP/PWWz/8GAO6rYVrcTib2mAqhlkOLWnZ4y2Wu993BtCKQslFJtoNOwP08qJDQPN+ugH01NxwawJazoN+BMWSXAJ6vqt1Ae2sHLEXawGxHaN9cT67KpTMiyU7E1t1VSHUuWW3tAG928WS5DzonHKjLQ7oGbYaS0sC2l15HS/26MVaF9DjLjG44jCQQNr1zda0LLFobMsAWh4kRED/lS83+rEvN+rFPqZij0G50Y+3WKvXg37izQXDiSqQxjEPUwXn6RzCGuTbWQO6bwlWi+2iN0Ssb6ardQA99gbOg8MEBxwEspjDHF7Sohg+ciWGN67Etlh+b1GxEk7kgJtW62aJVtFwczRRrMjRZIHfOZgH114LynAzMZU1uzqPXKIYeVbedCU2B766KzG8cSCGRuEjSzH3gL708oXJ4NV+cgOLo1z65/6swhwa9aATBaHzAD06eLDt3sElvKHp0Gv2gJ7purbn/rXz4c0eNvDXEoB+ZYFcxphvDCP0QZX/NrW6pEUxfORSrOpKbGtomnx/FBfj07ZfWXBlGU2xc2WZo6MZPbIUY6GA1cXNVTqrAqOjbODPilyiGOFg2ZkYzNBbdCUW9bWYGBqFjyzF3AP6VP/N2Qc3z5GbntkHB66+0M8WgrUCtH0edBu/6R20cKFjedA0W+72npk24kHfN3ehdzQPGkqsrYHT+zlIaDX3k2KZs1yM5oA5EqOKriwr/Xi/C7FwjoqzfUZTih1Z5upo8vpS1kczypxYptBagUoSFu6gUmxz9WfuxICFw67EqHnFxahRmGtoJ+Yc0DiTkLAZAH3mwc3/5/v9D8xd6CKApmVFp2+wm/navdyJ3emAptVF1/rwZmaPwfzuXQA0Xnud+wfqVTbbbktv2rPykpbEoPiZIzGq6Ehs7KeHnFgWOtDu9lmJRSbcWObmaDIx+6MZZptBNbfVAKdUrHRop7IlyRUTWynjIzdiMOlj2JUYuyksRo3atO+mc0BjLdEL34cQx8WXceKgejb3jgEaaTw/yG/u0amDloBGGmO2HLkhvjOdQdgigIZLDpK1yDXIAW1Yj1O4pONimAPmSIwqOhKjEdriYtTHZBWi3FgGc9GdWeboaFKxAkeTJxZDttwqLUJEJ2Xbkismtop1LhyJubUMFYuLUaPwkZ2Yc0ADjWG6N7L6JjkA5x6k1H/eOQ/6zuTgPXpDaK1RGinTg+6b7LpPbwitb+9pLQ967CXqAlaqDnyuSAwfuRKj5jkSc+Db086FEQ6X3Sw7s8zR0USxIkeTEWblMoXO8jAGVYu5lpFYEddSZdn4okOx5WE3YuOL+KiFPOhLwGcC6rVZWv55dz3oOyeg9EawhDeQxXGjWAx6BgqO4g1mcbRWDBoqpzWiLI5iUctIDB+5EqPmORKjgC4uRnnFyzm5sAxzJZxZ5uhookyRo8niqVCBrYPnOAwXDBtHYhTQjsScWkbNKy6GRuGjFopBr4HffOAqZnFc2PUYtALHhbI41NO3WySLQz3DwHLc34t5sZQsDvX0bcv0Bi/2iLM4FGsN7iagE2teFcyDTqxj1UJ50NIlVSxz1ot5sZQ86MRc5CIJwl7sEedBJ+Zv7y6g/UxCPyvOizkS85P//ExCD2gPaC/mAe3FPKA9oD25vJgHtAe0B7QHtBfzgPaA9oBu/bYTgN72zTfffGvB5gHtAe2bb755QHtA++abb755QHtA++abbx7QHtC++eabbx7QHtC++eabB7QHtG+++eabB7QHtG+++eabB7QHtG+++eYB7QHtm2+++eYB7QHtm2++eUB7QPvmm2++eUB7QPvmm2++eUB7QPvmm28e0B7Qvvnmm28e0B7Qvvnmmwe0B7Rvvvnmmwe0B7RvvvnmAe0B7ZtvvvnmAe0B7ZtvvvnmAe0B7ZtvvnlAe0D75ptvvnlAe0D75ptvHtAe0L755ptvHtAe0L755ptvHtAe0L755psHtAe0b7755psHtAe0b7755gHtAe2bb7755gHtAe2bb755QHtA++abb755QHtA++abb755QHtA++abbx7QHtC++eabbx7QHtC++eabB7QHtEHbG/D26vN6W3xxXvedifbp/6rxpveDo+ytT/ROPL3t6qNmgv6cHtAPLmR7rklFuuSiCXtBu71PTo6j2n3Y0b2YeW7k2lbgzJWtT/kc9gnCHsNX2D4Rd2TuHsvejx+DU88D+mMH6L1Bh+5FiG8tcEolP6ogoPVszzXpYwhoPEP6tfuwo3sx69zIt60ooAXrMwEt7jEB0OLLuwvoR3LqeUA7ArTpJbPTgHZyStkA2vF+elwA/b7Qc/eHxd2ObB1Ai3tM+Mz3XXTeA9oD2gPaAzrFlfOA1gP0UTWgjz6io+4B/dgA+ovzYbBj5tW/nw+iY/rpSfYDjZ1y4XO46OHJUXjENwj/CqcFe3kGfuJ1sJ968qlO3QuwBs5j+lb40/uBYIMgFrdV/DXesR19FIb9gheeoVbuZTHARA/EC0i0LvqEUFDcQZFiXC3ewRCNyS7JFqj2ZNQDUVf6CGHHsP356UmyTVIvzWbpYEe9xLfwT9Lpg7O9aHhuaNjGjnv04fHzCR8xiqqO5ozQp/jnhMcIPiG2x6IQR/Ry/h7jr8btS+4t4ezmxy/9wkvdNeIn553FHtCPFtDvs3j0UTzmbZwM0V86Ii8hiE7cX+LjfjwR2CXF//pEL31IXmYnOPuboNyPb4MX4HHsIrwZStLLIhSL2xqzEcmEH8XfDwZzK8lfEz0QLhTROuET+MUZ20GRYkxN7qAEkJuKvRS+R96TYg8EXfkjhB0TB7Ssl2az8mBDL9WAzuiDq71oem5o2BY77vDh4vmE2A7I1kfTjqYE6JuKY6QD6Pw9JgBaON9jZwi8L3Z2s+OXceGl7RrFsUo/iz2gHymgyUlET096LQvf3J+ehNOAHPR+esoJz+H40zMM8UCv6vCvcJ7gbQf7rC/Os5O6X7SAXB5kE4SLOBDEtj0qcIiLxWxl10KkvJedZNStYVbyrRI9iC4JUSP2CXu58yPuoMiO2P6ROhj/nRl1KWlBck8KPRB0Ex8h7Jg4oGW9FJvlgy3uWkWII6sPjvai8bmhYRs77tGHi+fT+/RDgoyjGQtxRJ8TO0bKEMf77COPbuvssTiguX3hGRLurfjZzY56+oWXsmvixyr3LPaAflRZHNQXPhoNZ8yI6J6h1+8X5194Bk854Tl7Iz1R6Lkg/JVdQnsFQEuBQNTYSzyDfvowdhEejX2HiC/EbE2EGGNRt/cpmjroHxQ9EC+USCP2CXtVOwg33YvelbR/0gOBQg8SFiT2pNgDQTfxEYJsHNCJIxPtBcUxVHVcCeiMPjjai8bnhoZt9LgLHy68mwIJ9tXR7bSjGQf00dRjlAno/D0WA7TUSWFvqc7urAsvZdfEjlX+WewB/QgBHQ4jxM5k8Sc0/J6CP4rP2RvDwG5H7N3sOxh5EX6Rx489nBbvv/p/Th4lbzgaT6WKtuVm8BfitoZG8sd7xZ/J7Od1P32Togdxn4W9EP+EvaodFCpKPVamLMpdUliQ2JNiD2KmSR+R3DEM0LJeis3SwY7tWhWgM/rgaC8anxsattHjLny48G6+t2eEyIJ8NOOAjn88PUb5gM7fY/FXpU4Ke0s6u49Kl6nqwlPtGum0yjuLPaAfYYgjZJ145UTjPAKgxefsjQIGxL+KvNgbjZGIB//9oP+J3hf++3wHDTkmcl1FQIcvxG0VRjioMuuWGP+kFyZIJHogxAIjjfgnxL1/0QenioJaooNJp572QAHofhnQiXCwMHQXfYQgKw0SyoBOsXkmOZaWAeisPrjai6bnhoZt9LgLHy68m18H1J1VH81kFgf9+OgYCXuMej79MqDz95g0SCgBOtpbUnS/X7pMExde2q4Rj1X+WewB3aKAjo5U7DRXYkX8axLQ/MQ6GoU8O75IrsCZV/++Vzi9LQAtKO+NBjqOsh+BMqAT554w3ysQf3VqoSWmJnUwDSAJC5JAFXsQ041/hB2gE8fQAtA7uBfNzg0N2/QBrT6aKYAWjpEOoPP2mDagY2e3eKTVF176rkkcq4yz2AP6EQI6/PknXN3i+Jt4msdTf2RAxzPjZEBv84Ef/pYX/nqyf/v9iR/OhzHPXEDHbY0nCkYkiEXp+sWLNNaD2IXCNeKfEP9xLu4gtZrYwTSAJCxI3ZOSaYmHMSrjQxrTTQI6xWbxYEu7NhvQO7sXDc4NDdtiIQ7py4yHOKIRu5STSuEqmMSg8/dYNqCTeysG6IwLL2fXBHpnsQf0o8zikEZvYhm6Hdvi16/wXImBDsU1oPbWMcerh7wJxoKOagNaMUgoKu+lg924Ic9fkAYJhR7IF0pyOEk9vCUMuCXUEq5SokvJbRJ7MtaDhK4Yfpfd5veDrCOTsFk62DmDhFl9cLsX9c8NDdsUg4Qys9ggofpoqgEtHiOdQcLcPZYN6HBvSWd3v3SZZgE6rYMaZ7EH9CNOs+sQ8p/6Y2OJR9npy87V8LkCA8JfxdOC3bB6MtFFuJdlJwtpXfjWTEDHbBVSAakyvoWmL0BkrYOnsJGt+pM9iC6JuIbwCdQIaQeFiqKaooORvxi/bGQLVNH8sAeCbuIj4r+4qXYKoJU2xw92fNeKuNHog6O9aHxuaNjG0+w6ojQ7cbdFaXYpR1P4sHhANzxGGoDO32PZgBbO4tjZ3S9dpokLL2XXiJ+scRZ7QLfORJVYCmSUtx5L94fDlz60JZ0WMO7QQdPmY9OjyBnREc5HiMZMOjIBrZioIijHPoqdwr9UTrWJTw2IWSd+AhWUdtA70ZSD2P4QzIgckGSXEhYogSr0IIjmmwTSDJ74Xg6Cr6f9tvllis39KaeBBOjcPrjai6bnhoZtiokq0bvDFIajGUczNpMwckfDY6QBaI09lgnod4LYzMbw3OiXLtPEhZe2axTHKuMs9oBunane8Rx1vO7lidJHU3IPor/KpwX9no7PUGIJQDP8ImWXyAv/PRPQaVO96ZvfjyZWHcUTjE2S7Vf1QPypKVonfsL7fDKvPEm5X9o/okTs1E52Sbbg/2fva0LrOrJ1Qbwj7NDqWELYfhg/oQMHhfa5lniOrGMPPHBf4RCChDBBHYMHulJujhsMV/i1uXmokeOmm7zOwGoTLkST7h4I/Aai4YlHX4EGxs5NBy54ouA70SDj+zd70sTHelVr1d/eu/beVbXryFK0Fol8fvb+zqq1Vn279qpVtfMuddgCU7WUDROG4ahncpNPdp1Tzk42PGGjsjZEs6JnbDjoZl3qrY/mlPRf/gU1sXpTam8dKoCPXAjawWKFOWhtrWR0pwyY6Xi5pjF/uTyKiaBpw/4jIi4bD/333/wVGaqyFQ9SnTe7mdURsxYRNBH00e4s/xK+lwFZ8SBFTBL2dP7nX5G1iKCJoI8HtfTeO0d2OhqUIzO6Z8haRNBE0EQtJIfMij0VV85RzBFBE0GTkJAQQRNBk5CQkBBBE0GTkJAQQRNBk5CQkBBBE0GTkJAQQRNBk5CQkBBBE0GTkJCQEEETQZOQkBBBE0GTkJCQEEETQZOQkBBBE0GTkJCQEEETQZOQkJAQQRNBk5CQEEETQZOQkJAQQRNBk5CQEEETQZOQkJAQQRNBk5CQkBBBE0GTkJAQQRNBk5CQkBBBE0GTkJAQQRNBk5CQkBBBE0GTkJAQQRNBk5CQkBBBE0GTkJCQEEETQZOQkBBBE0GTkJCQEEETQZOQkBBBE0GTkJCQEEETQZOQkJAQQRNBk5CQEEETQZOQkJAQQYcRNAkJCclhEiJoImgSEhIiaCJoEhISEiJoImgSEhIi6B8IQRNFk5CQEEETQZOQkJAQQRNBk5CQEEH/IAiahISE5PAIETQJCQkJETQRNAkJCQkRNAkJCQkRNBE0CQkJCRE0ETQJCQkRNBE0CQkJCRE0ETQJCQkJEfSRlpOimXfzD+n76J0w6B0FunPX6YydV69uOYNzrc85K5NqRE6bBjnojbRWQqc+/Z16uSPL/c8pgHPykBvpnykxpPrawSf5kDtnSg5y1gLbdibHpRGDZfBGCMZJbumTHiFQrIMGCo331xHVIYImgk6SQaondpegB+1xPFikRUonofSNygRt6HISKXEweZXYwbeCr+4mX1oI+pakt8oE7WCNDOTg3ddRCPqkapnpq+4Q9MnURSXlnLxouZvTXG9GjkfQ4eoQQRNB5xD0rdTQLx60L0H3OasgtD3pTOj5PKJ1OSnBTu7cSozUb6Fy/BQcF+uXEuOWevWP2NTBj3ZueJKXQdDOPklDngzgdNvXJ+XVgbf/TJcJOs1rbgTdd0P+OTwEHa4OETQRdCFBswi98cYJ2rVnnHwljjz56m48gua0vAPEpO9U2fsJtNAOnsH/MV6mGzrIDj+HXbU6QTv4JA3pMIRz0YLR8pmMsbtH0KnLihNBw7D75M6Zw0TQFdQhgiaCLiZoQaI60Toob28xYDl1jezAbfvsjplbOClTDeYX7MXdNEGr7/tEfkD9Vt/dQU6E+PFJnbrYUTfYfYl0xqDq0BPqW1CSdbNBPEcc0ncXwc9kGvFOUhc+5mXUewPziGokxD5AC8nGsF8wXmZG/oOv/h90UtZVd26YphOGlAYyGqmtkCFotJs8VjfJtPk7pjNw7M9a0icbd/d1iBbwU2BJ3l5xhVIu9VAo7UP0Ukq/9AU86Rz0kPas+NlB0JMhwQVF/Hb+m3ekywRKXyrYDHw8uC+VQHNpx2D42JsImgi6hKB5XBrZ1UGVBTW+kL3GCN5Byxd49EdpgpbfY+cwfqvvo51XH/3DK9ETkygwFbSTnDRLjnGkbkDL94XWJ2EAy1sH4O+kG/FRn6mLuD1VHczsaScTI+g+hm28TI9zWT8HcmcAkqB1M9SPZht5107Q/CN1rG7SYLYd5pVr8CM44FafOshTC/gl/JZnbICBtUt9FMr4ELyU0i89nE06RxK09KxspEhBi2sJap3/RtpHovSlgs3AT3UEj3YcqRQ0EfQRI2jeSfrEaOKWGryJ/t0nujHwMHTSu2pkcU7Ql/5CHp0maPn9II5h1G/1GYM3E+9G4vvB1GBfk+Ld1woYO+VdNRKUbco0gvdCpYvIcKgOZs7Gn5Q5aHHZOmO+TKQ6xEAMEtR3X++YphPNkD+aaqT4OkvQXDnjWNkk83QJaQzqBSnhV+I8Ly04jAS5gZcrw6U+CumfTXgpqZ95S6TS/do54o/yrE5I8T9w09D3CjQ+k/9GjSbOmDGo9R4UF/i7htOMiHNrx84tImgi6C4StLx574NuKPmCBaz4AvlaBbXRo4AH5Bfq6DRB695w7rX5WyJHoBgK8RQNm4daCFoNaFVPVC93FHimEWcMXRRB38gnaDFymoDRuXop8QyCPglH3FIErZXVP6oambCCnaC1QVSTTJubkAICraDa7a9Fn6JhMQo9l3apq0LGTVTaS31GPuFkonAm5ZxBM2UlHaNT0Dv8ZmyEvRrEZua8MXNjqMS5TFPwm76kQdzbcbRS0ETQRy/FoWqr1J21uOlVJKXyqulyWTmeQpgb6ajWt/B9iqD1bwkwOT+Fn6r70sSh2RSHPI53F9HrkDhE+lirZW2E7qgyxWH2aNNCO1wBPNx4mbw9h+HkDfmPaYyEAYxGZqyQk3aCEZpoksXmSYI+l/g1by36bsjLDpJj0qUeCpk+THvJPDJF0EnnmDOFeiwsUtCo3atzDB7SL7lvzAueUkLrbXyT6gju7ThaKWgi6KNF0Cd37hrFr4KFZJ8rIGicztkJJ2gcsxgpDoFnIWhdbXxGJ13zCHpQUKgrQctJwkFkKMslLJXPkMUcd1PFAPyH774uJGijkRkrpHxiGFg1yWLzEILO1YLfTKAOwDkQGdqlHgp1j6B1kR27YxnkU8GQ0ch/YyVorXcOQYvgcGvHkSqyI4I+YgTNe+TJTGnYjgxYIzuQ7IJ6Cs0gaHuKI0XQN9J1VTCq03hGiuNGupxJEYCuekulOHj33Llh/qy9EZkyO1DiXMZCkknuJl6muQVaxn741mtbiiN1qUhchexldrcSc5SiSTablxC0nxZwD3BLWn4QcjbKpV4K5aQGQgg6meKQKWj4y29+RH1j/htLisPQO53iSEWcUzuOVgqaCPpIEfSgWHxxS3ZDWXV3JjO/liJoXFCX6JuD9klC4/sz5m8lCVrj4c3z3cSh5mSPWLeXnCQ8p6aSds5CTtAgKlsj9GjculBFWQjbJH5QvUzPb+G47D78VZOEqhmaGpONTFgh5RPjWNkkq80Tk4RZgvbSou8uXvqgjYNivky61Esh/bMJL6UJOjVJmHSOrPk7Z0wSmuu8+z7a4aXruEIo/42Im3NKiTOm3plJwmTEubTjSK3zJoI+MgRtLiuWt3ZnVDHV3WyZXSbFkbhF10efLUhx6DI7WdhkpDgEnt4MwjhUT0vqYj9T6X/UN6Z4zcnmXNME/UrXbtxVnTF7CdtJ/+CN19kKsUFNI6kyuzOp5EKykYYV0j7ZMW62RZNsNjfL7CwE7aUFVnG8MrcEMVzqqNCg4bkzKS9lCDpxpUw5R/z5R11LecZIQUvW3ZFJ85w3g6n4AFSttyyzO5cMFXl9cGnHEUtBE0EfKYK+YTCfinscJGbXeCTm6fgXt0Tu7rVR5m9ZqPKOZmEcr78yOdT4oVuDqi+kFgck9dYT8XIbjXN96ZkdUy1bI3YMYNtmSeYkoeVlsiZbEPQtg6ATS0TMy9AtWQWQtELGJ8axKhVss7n63kbQXlqIoSJTwNi+SrvUTSFBuEkf3n392kbQOzdeWwkanbODM7J9r3RNnrnO+6SoETpT+EbWo6j4ENBCb+MbvVDFHN2Xt+OIpaCJoH+AbL5zyGMwVVFx5kg2orB9JYVckUZxg6+SVZTnghVyHCWc8fJsnPg47kIE/QOSHTEIO3PYCexcWuej14hSN1SjOifR9yGvd4p2pNqJckFwWIFHBE0ETQRdFNmuOxQfFoK27C19RBqRz4YO22XHWm2sU9AFW+p57N9dfGN2xsezRNBE0ETQ1g576/Brqfcks+wEdzQaUTCsdUjORFvNdjK5OChYIQev3fDyLBE0ETQRNAkJCRE0ETQJCQkJETQRNAkJCQkRdIE5SEhISN6YEEETQZOQkBBBHyWCpsAgISE5TBxNBE0ETUJCQgRNBE1CQkJCBE0ETUJCQgRNBF0khoIERmAERmBE0BEIei+WcAUJjMAIjMDchQiaCJrACIzAiKCJoCk8CYzACIwImgiawAiMwIigiaApogiMwAiMCPrIEvTL0YuL0fxGYARGYMcIjAjaiaBfjnY6nfdPb3dAWl6mri9uTyX8JsD2ek7BP5HAbnY6c3sVwfbqQqN6BM00SM/Xi7E04828eDsW2KmYNmO++HgxEpj06qHzZpweYDogWpzF6AG6eRFsZtgqvAcQQTsR9LbhrLqv4/a2W4mIEmA9p9i/McF6TvnGZxqsPofNG+BgU5HA2N+Li3txwHpuTkVwgNSsPsV69Vy0Zvac8m9nDti2dxOLmjkX0WZReoD0ZpQeYIBV7wGyeVF6gLZVeA8ggnYi6AHtq21vW/f8LJmaEmAw3vIedOWAgVbbvmPLFJjUqOdmKx4YH9n4h2cOGDSzqs0kGPw74MsPec1kUJ9+vBinmWa8xWlmLJtF6QFd0SxKD5DNi9IDlK2q9AAiaCeCrqsrs/91tefr23uZS34oQeeBQTBVBds2b9UhRiOA7W1PvfQnrjywkExCIZgvQeeDvfz4XW+uyQOrzwXwcw5Y0Gi8wGbVe0AizmJ5M0oPkM2L0gOUrar0ACJoF4LuuTkvU5/+w4d6p5NITUmwoBu8PDAcP/jmBlNgA1PbAuy2f3jmgYXkZovA9irbzATzbWU+WM+pln8OOgfMiLfqYAnbRbBZ9R6gmhmjB+igjdADEveiVXuAYavwHkAE7ULQL0fnuJF5fNZDbj6T92QKLGAiIg+MJ2d7TnmGZxqszmOCjUhEeM5FAQsKzwKwvYGLi7HAmMWqOkCBDUyFtzMNZsRbdTDTdjEcUL0HaLAIPUCCRekBsnlReoBhq/AeQATtXGYHF1TvEZfVb4CDEXXxdhQwyHP9ODAMVKzjZHgraPyQBxaHoDXYQKcVDywg0ZgDxum0OkGbmsVyQAK0umYReoAEi9IDlGYxeoBsXpQeYCAQQR8UQQf055ejWP2T5tSgpFkeWFAYpMFgagrIJiADlwcWFJ75YAHz4QWaxWvmQEj92cFoNrUX05sReoAEi9IDEs2r3p2weVF6gGGr8B5ABO1C0HhB/Tpk0p+d0uq5d9qc1RBgQeGZBxZUkZAHFtQR88CCwjMXbCBgvFXoAN9eWNBM/3YWa/b14uED+4H3AIkQpQcY6oT3ACJop0nCUy2ZNAtIwNWTC4wkWFhNbx7YqSl20W1V1WwOg6oeUgWaBxZ0g5cDFnarmAOmvRqnmSFTQQegmalhhGZG6QFCszg9QDYzQg9QzYvRAwxbhfcAIminFAdfpYSzSv7zBvVWzye3Tb8psJsBq5WKwFqVNTul155NRQMLIa4csKBEQq5mQQvZ8psZsJIwV7ObETWL2sw4PaArzYzTA0Tz4vSAuWCClmBE0F3fi6O+2PPJ4l6kJfoERmAEdozAiKAPYLMky7wegREYgRFYKRgRNG03SmAERmC03SgRNIUngREYgRFBHx6C7vlZxDsfAiMwAjteYETQXSXol6NTlvJIAiMwAiMwFzAi6K6PoLPlkQRGYARGYC5gRNBdJ+hMeSSBERiBEZgTGBG024b9/mXr2tS28siBgAUXVjDxXJ2O9+N+csDwuv1y1Nygcru09V3XDNcjdDohe8UXaOapW543ETCpW6nRbGD1TkK1unOIFDbz4mIUm00pP7QOkwNSNqsEVtf70J6q7oAYrEEE3XWCtswdBHYdG5gR635rsvLApgIJuruaaTTfDfaLNfPmB4s34QGC6M7bfgSdAatC0EXNnIphs2CC7q4DqhB0GoyvRpySPZ7veVDJATFYgwi6uwRtiIVs/DdSz4AFx3oeGFwzfAm665ppEgzG6pJmCTTj6uFjtOoEfRChEUbQXdcsmKBzNIMOIJ5SVc0BMViDCPrgCVo9mboeJ6LEE0ur732OHUc8VToGQcfTbECbLPSaltUsmjfxyc03E0mrIILeS96+VCboKRVvi4eMoOM5YC97y1fBmyJY69gziaCPJEFDV3QLsZw7H3GufDjIgFu2A8AwDrOxDiHK4uviu6MuUcWAFjNPudyWmXEV71yzVinXcDAALNbsNl6R+Gi4oDdxoO1OCmxAXMpwZOMHtofTLbn8IDrjQOnVEpvZaVkvHXt673kno1nBLAS97XIV52CZJy5pTmXxOidRnZtZluKAXlDaCURoFDnAPWh5WLCfLbKZe2hAjGWe8/oSFNnW4wE3B3CwTA9IsIZzlCXBiKD9CVrebjtcsm3lkZkhCE5/lTuOg9UXX35ZQoO/dbp21Be3pzhgGuzTUX62iHeh2XwZQXMw/n+xZkLmS4zHgU6kn2C/nUik+oHJjX0rEzQH224lh0nZAaWj0WxgFoKed0q8o/EHWnZOhSHB3whF66VDAQ6WqenNELRMU7T2HEIjL2gVQbsFLQ8LptnbpwsJ2jE0OFimB4gLrnSqswM4WKYHhBK0CUYE7U3QcI0Ws7wug97MBrbph7ADOEddLAfLjXXcuZFr5Xo3y9jBMoKeGuCxKeIdR4fbDrNMnGqynJrW7DYMLvHNXCFYmlNlpnFOkYQ7WM+9e7fzUqAXb/uNbVoDnRJvuhstC2Yh6E4LB8CB3lTplou38S0DK2dCBlbP3g9pEfdYi+JvGZgtaA0HeAQtCwvmy3u3iwnaMTR4jGVG0JLhpzwdAAG73YpC0CYYEXRoDnrAlaDT5ZG8S5uXdfGehdhUOdh259MvC+ZbeHQ5pr14aNq6NKiD8d6jBl0OVRw5+RJTsznZr4uNB0CpLq3nguTI3h1suxWLoEEzbGfam+K2asrdaBYwC0FPuaVsOQ4OoHMJGjWVuQvPoM0QtDbaVKWgFWHmmqt9+aUDQTuGBo+xLEGjJ70dYAMLJmgDjAg6jKDBi44EnSqPTBP0y1G537hLL9zbLqqlchzXc6yvb9sJGkJIELTQtLxijIEBYLFmOrld1K85ELNZlrkEB+orhyPYgCU5G0TQNs2yBO1otNxmJgl6zmkGDIx/73YhQeOM10B5rldoll+6jINKS7lPnmYFQet+Mwr5kp6fOaQ43EIDjG8haBh9z+35OYCDZXpAKEGbYE4EvbEUS2r7+7Va7agTdN29psdea5m4odt2rrljYAOdizmjQawOcp5ih7GBlaDFnI0PQXOwei4NSs34v+JqVNhx2HeZ+RbTWHOeYJK6quegLZoZTOVH0PnNzFRxpC/pdjBMGhcQNLyvl0+doGbFk4RSpVLV6pA1K5skdAxabi+HSUK30LBOk6cqQpwdYJ2lDSVoE8yJoGc/Xy6RycnJz6V8kS8PL9S6yc8HloPm8TXgWyKXN620HVIUXTnWC2qpcKrQh6DdNHPsOFabqR6yLXKLFcCCCdoKVtenDfgQtEvJmDM/FHhT1w0BzCm/yq/KBN39oA0l6FywEIK2goWnOLS4EfT94TK5n5SzdnmwtrVx5FMc2vdhBG2W2XH3b4dUS3aToMWi6ttqdHgICFrdBXePoOthBL2tZ7gUQS/GI2i3O+wSTr2pyOH/jPrFRxFBL/qqdiQJuoIDbARdf0MEnSVpK0H3P92qHXWCFqHqbOlMFahaqDJg3hO7dejyklKPWM+7j91OpnrdHqBpAwsmaFvtuOwquuQlFCxF0HipdcyEZsD0QpVTfpOENm9mCZor6hoaOVkJVSVhTn+Fgsn2OU8SOoVGlaCtQtBWsCRBV3BA4te9okyHhjdBT5hSxNBWgh57snBUCVpNkOAE8UDHfWYjXZFgzpEsynTwKadSo/KSUo9Yzy12rYuOvO1cZmcHCyboDBiuDZImqwiWWpy9rQqz5gJsZq5C74g7IlejZUMjQ9A84+72uOrCZs7t6UtIpdAwZ+HcyuxKHVAxaKsQtBUsSdAVHGCyhl+U6dDwJeiJIoIePhYErUvhpwIJ2jKz57qPQFSCthW7yr2S9GJ0h4UqeWDhKY7M1rqaBluVwVIELch/3tEDmXm99GZJ7kYrJ2i+gsM10gqaqXPRruGRFxq+C1UcHFAxaCulOGxgCYKu4oCBVN2LR5QFEvRERvwY+gdB0NgDp3C9ioNkqkB1JzZmlxxL9W0lpcEEbSt2VQX6eqn3nNMdng0smKBtW+sO6CVdFcHS2xvBFZIv6Z0LsJkGVK11Npo1NJIEvei8YUt+M1WcuudS80NDL/U+5brfQYkDKgZtFYK2giUJuoIDkqzhE2U6NHwIesIqx4Kgq8l2vKexRwWz7m1MYAcHdtDedFgMRd48XKHhRtDDBQQ94ZGFPpYEnakCPTRg8Z5ySWBHwpvuJQTkzUMSGu4EPTExUXkIfUxH0Cj00HkCe5NgHjUcZLNDAxaBoCeIoCmiCOzQg+GmVWSzHyhBT0x4MzQRtBi5xHrYL4ERGIEdLzBXgp6YcGTowiH0sSTozDaxBEZgBEZgTmCOBD0RQtA0ghay3Yp450NgBEZgxwYsDkFP/MBH0Nupue9/P73tsaA+vWPWy8Tjfbb9dvRIgW3nTvwMJDZkmnMBe/kx33xzMR+mUF1nzZT9tuecbZa/cNrBfhbNbIW3bp6weXMuba7tOQFWgpkEg7UMymZlJir15mh5cb2zN2HVhAgNfZKrdnkO8G5ins2ahkrbc+Fgp2C7jDkWoPw/X0ekmzlnBLw3cfjsB+1D0MOeBF3TYqPckq/fDEH3vO1D0OltYnHz5MCHeKbBuB52XQZa3mDwAKASgo6gmYP9MmBcscBHlVo1C5asN/kzDxczBB0EtodbHQddubPe/FJ/VrmZdoKu6oAQT1ht5n/NyPEm8ySLNQZpeML5MpQbZxLMdK8jWAhBj4xcNWREiGRpP4KuFTNw7RARNOw7ACvqBzpT29+O4nNH8BN2wECLf9bMjhrT28QKv8EG/dvz7OJfdPKeA9j2PH9u2sV/5psu3YSHz73/Nzc783xct91B2OY8+41fp38iDfbyS0aC9UXQrOcU/8NgWnWOMyX1285T16rZHGvgbY4kjwdsab9crKxmfzytPCCOxjcu9rM7AM8y1CtQp9yboA2YCwzHoURg+IQG9GAVGPMdR53yvAkXDHQf7MiFrRRNxk9cvSkIWjauLBicHODfxFybCf9xmDkfvAzYyz/+DYMb4HtYT/k6wtpMOEuC8cB31M5vP+gEQY9cvZQWxdUTJkEDX39RRNCMdhtC2KsMBcOXvfL7N03Q7DaFGRYeAstGgMzaLf0JGp19NpU/5JR+Ewewf5izpvakx4pPzgODREJzimsy39rrqfNNWeZgG9P6W1/f7vnkVwj7ayDovJ/QvZBdt+uLoNkAO2GOvaq3ejjOotSvVN1kioNbhyPJ4wFb2q+86cl142hvcbQ0vrv9UprNCecJ9XTPdvKE4U2+ehe0AXMh3hz41qWJGbJRgYFt846OBKcyY4P72Kk9/w1bKZqMn7h6E4uoF2XjXIOhJDRCm5glaAynBEH74BkbmfGsEI6gQx2RJWgJBreOftr5E7SFny9d1RytGHp4AgfW93MJGsbFnHprjd7eXsbE8KFJ3w1xSIMfUHvDBA1bBkh747/qE/kH/nXyGzwafgpOcTm5JAi4Jm/dFDu7LO69ZP+zsVPr5ZcCFgk67yeMLs0fwQyasdtZNqDmMHscZ0/qV6puZpwKSPJ43MZE2K+86Ym9OOakvRPGd7efbQSt1eN/PDxhcUALzCXwFJhPaADZ6MDw1clC0NJ9sH+zQMQmi08cvSlG0Kpxex6ty3dAaBNtKY4MQfvg6TiDLAQSdKgjrAStA99PuwCCvnQpbwQNDD2B/DwhUx/DhSNoMUBGpk4RNB9B98IYGo570wTNgrOeJGj9CY96114IWctTrYGWDFKXk0uCADThQ5PWHoyPOtgv64sGQdddCJrvyAVH6BE0EnWiT9Z9CFqMusTNXkvloB2w9Dh1imsk7Z0wvrv9speOllJPDZLqngQNswl1VC01gnZrom0EjYHhrdOeNQcN7sPpM3m/Af/tucCnCFo1bs+jdQUEHdjEXIKut8LwrAQd6og0QddbEkwSdL3bBL3208zTBheur81OK4YeBm5eHrvEhtAFBM1p9+H6cybrK/uZETQj6NrSJn7dv/9GCRqupZ3Or+fE4G0KI0J/wrOPrr0QqzjgMRdwisvJJUHANYH7Rg4qctCMLX5/WhL0v7EPnAiaEQ5opnPQexzHIOgSdTO9UOQt96ShOPaUG1aiioOBCHsnjO9uv0QRgToL1cM0o4cnEjtVz+2BNqkctFsTbTloDAxvnfbsVRzcfQOQVEBEbDJ+4urNVA7aNRiKHFChiXaCFjAheGmCPjXF/wt0hNnMKRETUzrw/bQLI+jXqSk8cdwSUPTIsMhujPQvXWd/C1IcbHi8v7m6euXKldWVWpag2ddL61e4rE6zY2mptx8YG6ZHAXPGeTPNjAHmX05wdJqp3RdQNEGrs98wWCBBc06umSNd8eb6tK7rmL7O3hcRNJzY2EQGXhEgtUSGoyYI+sp0gwjaE2zb+Zl4xWDbgY8ZJYI+FGCG+4igjxNB1yz1cgZDj60tsQ85Qd/PI2hIPfdurgqCrlkImo+gVwVB14igCYzACIwIupyg2XAWB9HJCuVaY/81Dp8vLfADigkaOLp3kzEw4+CVRmYEzeB6t56rETQRNIERGIERQbvloDk/q3G05OlaozbLRs8jI0v8OzagXk5OEv7oyULy8EZj88pqYgQNxN8A5JrKQZsEja+gbBoZvUYETWAERmBE0OlJwoXrKBeWavuSX6/DCHoJmZsRtBpB85Ur/+MXW1BPx79t1ARBg6zIYjuouhP8myBoSELDNUEUTzdSA+5uEjQv6z+FD9/Gp+LdxDfqcdwv/3i65Im92m8wectOgPP1J/gbblv25oNpzUAfrMYofmR4Fkyu3YPlZgh/03Gzd12s8mVCuYuL9cUKsY7Gubiomml6IxRMrhqSNntfNTwATLofLOX4kPaiZhpxphDNiHMFe1/5LgExFaTZ+2Zo6B4g/xQHSRYsazOADdMs2zfNyHUq8IHDZL9JxJno496aiRYmbSYX6jqEr/92owZB789ehRLo6emrs9fF2Le2cUkRdA0mCUcmJu4/uD/Ml4iP3PnFFi+tA4Kt7SuCxhQHLCfEr3B4nCZocYax9jC1ArxrBF3nz03nFf6yNoYvDMLCS9zUpOcUmPqeS3jW8RGSUHuGG0zU8VG0LfCoVy1VFkxrBvoAoth4xR1MtoefPQdv8JWPZswWCg8UKNGiVDM4X7YMvOFsrhwwVFDYDMFEw0PAhPvBUn5ttTZTx5lGhFb7eBMaJX2nDagiz0uzhIVUnC0qxMWSILGAZWwGsGGaZfrmohG59U7LuQdwpfB8Wcds9nHPvgktNG2mXNJyKbSrRtBrV9U6lenr+yKHPAsEjSVz1+U+HVB4NwEEjePk3l6xSBAIepWnOMTC7lovrE3BkXIyxVHDRSvIz+xVLyf7AyDonv+Fdeaf3DaDYOqv+foNfH7wwL/x+snCaXK1tAHA+AlwvvwE/tz7J88RdBZMawb6AKJ4xrE7mGgPF9ZdxJtt33USGg8V8B9CJzQDENlM8IazuXLAhF/RZgimG+4LZm4C1CqxeClYIs5MRNZqH29KC4HvtAG1FX00S1hIaMb0EWD4SOuiILFplraZbHCAZimbcX1U5EpPO/UA0SuhPZk+7ts3Acy0GeiaULi7BC2XEF5aEjmH6zwJvYQHvF6eWF5elosKR5Z//vdPFxYubNX2YYkgUC0StEhxbF1YWFjaaPSKoXSKoBu46LuxtcBkSbL1QaU42A0KX8+GWQx2s/IpLrDjC0G/wT1WCgfQyTsfOKGuuokMrHrLs+NkwbRmOIhtSR19wER79qBwX7zp8QtPebWAs1GBgVYoQYutSxiIshn3hrO5csCMFMenXwKYbngAmHR/j2xwBc3MODMQeat9vCkshL7TBqwvhsRZwkKoGXgBwKB3FAeJTbO0zUSDQzRL2ozrY0aue4oDlcL27GX6uHf6kYElbAa6JhSOQdDDeQR9FffnYPJajKCvX117uraBc4FLa2tr1y+JNd+bz9dhUcqV55sraxuaoFdFDnrj8sPnjKzXN8eu13CInUpx8JH1/sLYJv9s9fnD6QsiG31ABL0n9xASl3w1DmEfQ6bp5Zd+qam/zhA0c2ZAx0mBKc24PhJxe84HTKXT+VphfOO6c2ViTyidhBNLEasQdMLm8MbZXDlgRrcVYCXzCIVg0v3CUpU0S8RZAtHPm2gh7TthwL8OIui0hYQquhuUBIlFM5vNgjVL2Ex3S8T2IGihFICk+7i3N2EqxrQZ6JpWuDpBDxsEfdUk6GG+zShn6FkxZ3f9ElZWiJk+dhQfQg8/R3Lmo2X+/+aaSFTIKo79p5ureAj786ON3swImh/cu/Wj9VUJdGV9eatRM+vvukrQuMmbuAODqzbkp0TSLLkrrUMvxCFDvZUgaP8MXAZMayYZaLtVApsFk0Mh2MIfh9Ef3/YjGzmChrNRgYoj6ER2XXmjVQFMdlvcREM7MgxM7jz68W2PVGoOWCLONKJLq7Ng0nfagP45aMNmPfJ2HW02p7rBXEmQuNgMh8PVbTagbh2EUh4ELfuN2kujQmjI+72kzVoJheMQ9HCKoGtI0CPwnSJoXlp3aaOB84VYiwcEPbwuuXdV/j+NyeRN/HBlVvAuHrS5wOcAUwTd27j+WB0Ehz9+2jCXGHa7ikNMiPO9VJLT18Y2Nx40iOer+68KVRwGmKEU5GXEdPHUnjdBiz24MMzrvuMHuZmaVq5CDjpRRiOb6TYNXgSGr7TN3j8d1gsNcwtLOZdJ5DXTjDON6O1NOAHPtwRtWBUHhkZKH/1DXmAZm1XQLN03ha5CKQ+C1v0m0Z3CCFok0bI2e9+pMsqDoCVDI0FDYmGW8bJKcawJRmYEXROrWLAqjhH08CoS7xVFr+z/NT4kbuBKwivr68mvHy/0pgiavX+6rikcQdbXDmYEHUGOWxVoJiFfpYqDHEBgxxLMjaDvDxsUzQh6TRD0mvlolaUGDpvXLtVEbYWojF6bmHi+irS7yuWKGCtv8joMWWYHhLsq0xfs9UMYX5uThI2t1PiZ//t84UBG0BRR3mCZjHylOmhyAIERQZcRNDD0VU3Qs8Y+0Gu4IWijNnt1aWkJJgkbtQ2+E+nayH3Jq9+vjE2vSJpdf8rHyJtqbL26uTw9vSkTzKuztRRB11bk6Pnh9PSyHEyv7BNBExiBERgRNCfoYTtBT6/VcHF3Y2N65OrY1SXMUos66OdIrOvDf/8nXpyxIkbMs701tZKQJ6UbvbX9xt+/QL5e3eQThWYOeg2ZfPXFEz5/uPC5eLtGBE1gBEZgRNDI0TzdLKYA12aZrM2urV1f2pfzgmKpN+6qcR1qoPlol+ckhkfu/GWrt1FbeIFD4WleDL25ihmO1dn9Xv5+/+m64O+15Ai6IRj5ymt4AFZjQ+3iQQRNYARGYETQaYJuiC2T9J6j+z/tF3tx7IvNkmAJ4fDwF5vP/25k+c6zLb76T6Q1oDRDEDTfEFrswzEmhsbLtUavQdALL5C4V2p8FM64fA1nHl8sEUETGIERGBF0mqBFmYZYKwIbIK2NKIIW+0GrpxOyoTQbQbMxsiyWG+NFzJuipuMprhXkyYt1nFHcZDRsEPSsSF2v9eISFyyhZh+udZOg90lISEjekFQiaExj1PTjUfbFXnaCoGFruwnYJglH0mN3/nJhbfoDkfGAQTMS9OqV51tiFzs2PH6IBP18qda7pQl6GQfQL7Z65W5J7JO/ZR+NEUGTkJAQQZsELevoFFPzlSWSn2EvDp6DnhiZeCCf8D0x/MXDxy9WVSnzlTG5FwdW1cktovdXxCFPEznoL/Csx3JDu979aSzeWyGCJiEhIYJOE7TKPSNBL8FGdssTSYJGfp4Y/rv1VA2zyEGLajlN0LVpK0HLgunHSl4gQW8SQZOQkBxjgr5vJWg5Pci4eWNp4fXsNDDxF8MJgsYc9P3nq5qYryQJGmcENUE3+sWBzwRB8/nE2sbjKznyvJsE/Wo3lnAFCYzACIzA3MWVoO9bR9BQZtfP5NIl+SzvifsPUgTN5YHYBilJ0QmClk/1rmmCXqtJgl61E/QqETSBERiBEUEbFG0Q9OxIWobv2wj6i1Vjm40XD6dFFYdJ0Cs1+azBRuPSajLFYSdoNSJfJ4ImMAIjsGNO0EjR9w2Crs3yRYNiqTfPPg/zo7IEPbEuOZWR89OtWu0hbnWkc9CrVx7WMMdRnIPmC8QfpmWFCJrACIzAji9Bn72vZRj23VAEPQIbKAF1CzmbIegvxF5265/3/wn2qHtoLlRBgt7c0AQtqjjWF3oTVRxYZrdZkyKeTFhrEEETGIER2LEl6H4LQQMBM4KeuJ+Ss1mCfi4Ienik/xkvd97YTBM0Y+ML+AzYWgProDlnNxIEvYwZjRcb4omxvfD4K3jKyqEm6BOjF8ei+Y3ACIzAjhFYAEGzUfM7ogDaQtBnMcWxIDbm4DV3MsPxHFYSMk7deiEJWu1mt7r68xosEGTEe2FdpKVhL47VzEpC8XCV3o3p6bULW+ZDCbtG0OevdTo/uby7e/q7Tmfc09T3xmaGEn5TIG0EjQO2e/rrsVia8X8/648Exm0Xz2YsdD8eiwR2YrTj7YED8eZMB2QyngOixVmUHqCCVdrMw3blYB49oRTMpyeUgvn0BAkWm6DPnsUR9AKuXREEvaoI+hd8s6T+K7J2DkfQMN23vqAWCIqFhv3szZa5Fwcy+cN9fLpK7Rk/6MXmw8tdJ+jz15h92z+5zP89f803PndnJk2/KZAm/3coEhiLgotju3HATn/HtGr79uk8zdpDDHA8WjPPX/NvZw7YjHcTi5o5HtFm4M9IYDJ4o4FV7gEqWGUP8OsJJWB+PaEYzLMnlGjm1xMQLISgR0bWRBX0LC+rS/MzEPR18XxCk6BxN7tG4/UL8TgUQdBi87qHG5CyqF0WD8VijF0zCbqxop6VBY8E3xCZ7NW1rhM0DNrYnxlu7xnfseXpDxKpKQly+rvJeGD8Uu9PXDlg8K/3QDUHDHCavvyQ10wG9amvYrlgzaEAfi5qZiybqdeHTrMoPUAGq+wBfj2hBMyvJ5SA+fWEEjC/niDAQgm6ZiXos5qgcY+Ojenl5bGrz+UO/St3/rSxNb0u6+OWa/qp3jzn/Jrnp6f5Bkh/y1dwN1IELfaDZucx6q4trOA6QjaiPjiC5kHkG+unf9OfjHUBAjjgvAhguzNDJ/yJKw8sJJNQCOZL0PlgJ/510Ztr8sDa4wH8nAMWNBovsJn/vVVhnMXyZpQeIINV9gCvnlAG5tUTSsF8eoITmGtPkGBRCRr5+ez9kZFl3L+/tr90/fpPrz9Qiwe/f/jwha6JXtnvVUu9cY/+lc8fy6cXrsNDCU2CbqzIBxauP1z54sUqMPlqtzfsN1McOH7wzA22O52h7GCkMwmx7kvQeWAhudkiMP877CIw31bmg52/Nundzjyw09/N+6fa88CaQzPxwIIG0HlgQSmO3KCN0QNksMoe4NUTysC8eoIDmHtPcAFz7gkSLB5Bn1XCCHpiVm7QwU6/MJF8IKx69OCmQdDrxh4d8PTC/t7UMwkbjYXHkstX1XLE1bHGQVRxYJqfp6TOX/MMTynSbxJE+G08ClgQQReA7TYvjsUCY3+Dkr02sOZQeDvTYCdGx/mIvD8KWJv3p5nAdloc0B7ajebNgOnLPLAoPSDFXONBPSEPLKgnFID594R8sICeEI2gzxoyMTJxdQP38ud/FvRKQkHBDzE7sb7EN+9HQu4XOx+p51/VennF3dILg6BrT19kFnvzFYhdJ2gMS5Hf+iqQIBKpqa/E3aL32DIHLApBG2DNwD5oBQvIWuaAcTqtTNAJzWI5oI1z/rG8GYpkAVPBG0WzKD2gygi6DCwmQU8G9YTC4bhvT/An6PucoHEj6Bon6LNpej57dnJkYnlN7+W/NDKyaTL06jQs22Yj5tlaDZ6owj5dePpYEvSqfIp3rbd3STz/ahoLPK5vriY24oA0dq3rBF0pOXtiFGtrEuWRoTnoPLCgsMwHC6gIKdAsXjObIfVnB6PZ0G5MbwZc0fLAgtLGhTaLABaegy4D89KvHMyjJzho5t9MR4KGzIUiaGRf3Itj+OyDs2nhHL68tiE3i/7p2PLIF4JoeZncdXhsLH/zATtgExMW1xsLK2qv6M21BjyeUDxRhe/FgZv5NzamH6tMCIPCmugDI+igioTm5Pk/XDb8JkGCqjjywIIIOhesGTDeygMLGh4VNNO/ncWaeVaPHwhYQNlLiWa+RssDi9IDdk3S8q3iKAPzipBSMJ+eUAbm1RMkmAdBn4VlKMC+V2dRpoGg72cYmq8fXJ5eu760tLRwXe5C+nx9ff3F98trsBZlmu+BN3vn6Z/+1H9ptv9Sf/8Wo+OnK79bXX/8wfIaf24hjMB7//KjMdgu70Lv06cLfHVKY2N27OHvmDx+OP0anr9Sqx1IigProIfYpc33lqedXGCkQNohddB5YEEpjhywsCRCDtj5a5MBydn8ZoZMhh6AZrKyPVIzQ1LQOWBhVe25zYzQA5QTZQ/w6gllYF4RUgLmF2slYH7x1vZaSWgOj4F98WndfKPnsxbhxywrUQ8lnBjp/8tGDVZo88xx4/aj9zqd+W+e7PN8c+1PX337XufiH795wovv9j989M3C/uJ85735t7YatRp71Xnv0V9q/FT+6Ba+1hufTFjbP4CVhHxBkVxY5B2dk+c/6U+l8xBEztRGAQshrhywoERCrmYhC9kKmunfzlww6dXD18yAtSAH1MwoPUA5UfYAj55QDuZTxVEC5tUTSjXzCREJ5k/Q6glWYntRCz8/eABTiYZM6IfG1sRC7drTbztC3uKMfOc9+fYrzt7fdN579gjfz29tyFdP92ERYaOhtkuq7R8EQVeRe2PnPxnbjbREn8AIjMCOEZg/QTOG5tv24xZ2960DaBhEDyMpw4G8+AMG3nd+sQWDXkatC/Occb/9lvPyP+/X7gABfzvP337FCLrVmX8EH/D3b8lXj/Zr8pGEYiu7/UNP0Nb5FgIjMAIjsFKwAIJ2lgei/u7Bgwfi7Rc/f7IgOZWR7nu/XNjfv/ANe7HA6Xr+zsZ+DYbNT+Br+GCDH9eZf7Kxv8UPvGA8o7aW5mfabpTACIzAfkhg3SRoC2X/CAi61qjtX2BD5TuwYUeNUfLP/5nRMe6Ax98+QoJ+wt9v8OzzU/nqSeJptTXjLxE0gREYgRFBVydoTqkfAg0Dtz559Euej74jmJZR93sXOEE/wio9NnD+Bgv2vgFOd34E7mEg6NMfRLzzITACI7DjBXbABD3GCBoxGdl+qJmVkfL8knzziPMwI+ivVC7kz+qcJ0eLoE+MDtnKIwmMwAiMwBzA3hhBMxZ+prMTz2A8LeQrzt1vKQJ/S42bjx5Bw6aB7VgPWiAwAiOw4wX2xgj6W55YFpnk2v4TSGMI+ZCXdfxwCNpSHklgBEZgBOYAdhgImqehUwT950NI0M2Of4k+N3WmPLLdMWSc446Hg80YSJU1a8pS//PX/Lb/z9EMMU6M+u3D2fVmRvWmBPOGK24mms45Npw0g0d8DVXVzNMFOXEmxHef8JzuBNZKNW+mrK1dD9qm/0K0DNibTHEYZHsEUhx8GZC/vW1zB1UIOgNmdBy/YLeBVSFoq2ZDgbHe3WZG9aahm98OUyXNhG98CLpUMyAwFzwXzarGWTBB27vTpFTRj6C7G7RVCPqNTxJqAt5/+uitP8935rdkzRxw96EjaAjvwE0bd+MQtA0suOPYwIIJOk8zSQyhdutOM6N601QtajO57UJiI1ezmYBtobsWZ2EEndOdPh0dl6geBN31oA0maEPeGEHf0WNmXnH3rebrZx1RZne4CLrZufjrTvAuyZnUlA6AygQNQR6yFUT3CRpUikTQ8ZoZ1Zvquc/tcOoymzmkLiCTFQk6rdlMAF9kHFBFzDgb340Fxlr3/m95w9rv/zYKQUcL2qNJ0AKTLx1EBl5ir+58CBttcNn4Vi5UOVQEzR+G8O6oClIYgZVH7AzjuROjtsndJEFzuFI0K5jqOAKQ98pgzUIJOk8zvPcUmrGOND7jkFhwaWbbNQOQ4wDTm+z1Z/3IYdwNBd0yz2bC2vDoDWe0vGYK87QNgp4pzZ44aAZJHSeWLXaAeQviwD95mo0bySZH8+eA8efF/BPT7fy1qWtCI5hgKCNop6AVHSqsb5oEzZu5OOo2JjDBnAh6+n9H4ue/G3uytfHh4p8vYKa589WF2sYTRsjzG1t8qfeHC/tLd/gWSs8OH0Ezz41r2mo63tL+192ZyXtjM0MlBO2GZgVLMRf2m1DNQgk6T7NPgQM1QTvd1ro005mgcxxgelMwF99aoMR0NjB+ttnpnNHymjlkhgc00GEDOQfN3Am62AG7iaANjrNxb4PlgQFBM0+eGP0PJGiBOF9C0E5Bq1I7k1W6k+hRv3W8CzHBnAh6bXny8zjyc0bQuMYbRsqd9+bBK3egjkO9/eX+4SPoNu/NMrDw+aAudzCwSffMZBlBO/VCK5jsOLinJAxHIELHQzQLTnHkaDbU5I0yCNqpneXNdCfoHAeY3uTWQm+iAQsgLWD8EVBjKYJ2Q8tpppJJ2cB2mDfTmrnf85doho9+g0d0hseZgvIwvx2ME/SvmLVmOpPX5B6h7LDymzWXoGX/APeXdofC7iTiwrlLGWBOBL2/8OTDn0eRO8+WJEHvL4g9RDvvwZ4cd+bl2w+TKw2/MQn6TS31xog8Ie6K8f7TicVOfA9l58UEDc/QcAh2C5h18sYpx2cBC89B2zUbYmb7rF8TNG+nQzKzvJnuBG11QMKbghREJyyGzIJBC1ME7YhW3EwwUhPTQuMhDkhr5pGULdYMb9ScM9L2OEsQtKv5rWB8s+UZPtl+cQz2XZZ3DuV7TLsF7bhbNrmoO4m4GAroTk4EXdt69iSOPLuwsfGjt77CbHPtzqP599779qsL4iqwaL6989Zbz8R0ojzeeHXgBI29RPBWZmySK/fGTn9w+jf9ZQQ95BQDVjCj4wyZ6cHxEM1CCTpPsyGZYDdivXT2xaWZzgRtd0DCm6JD66TCkA+YjaCd0MqaKfnq9y5c6KKZM0GXaYYjaMcyxbw4SxC0m/lzwDgR88XRbUhlD6l2lzXXJWhlTw8L2jRBjwd0JzeCri0txJCtra2N5A6hGwsLxvva1sJWzdynbr+WpuDaGyLotjl+y4R+/pVwVFzWy6s4ygnaCpYuwm07lkLlgQURdD6YmBsRBD2562A8l2Y6E7TdAQlviraKQWGRG2xglhSHG1qpA3ye6OGimTNB52lmy0GPB4GlctCO5s8Ba8Og97M7135y2YugXYJWYoUFbZqgJwO6k1uK46hIVx95lRg/BJTgVCZoh/InmB/5yWXPMqbKBF0AhrMuxgjay3h5/ND2XMeRBEt604chsmCWSUJ/NEsVB8ZHM6BaOE+zuGV2cm4vKM5CCdoKxqns/LWLX/FBtA9BuwStM0HnNTOIoE0hgnYi6OTkjXuK46AJWod5KEGjUpFKl9WUuk+Kw4Og22EEnfRmNYI2i9mMiYnKBI2UAPNdbb+unadZ/DroGc+1OV0jaD6R+qijCRp6ZwWCVkHrnOIggn6zBK36CN55tNU0RJnNc7eJDSHonLWpRseZSaRoy26jWPhNZoaW8tm4PqM2KNq0zbdINkxOEg6VgpWV4TZlcsIlxbGL284kurThTb8UBzssazPwZLPjhWYFS9RBM4CmKA8uYwfrHXZKM68UR0mcsa+H3AaWCPZZfxSC5gXCmaBti+W4+Nd9kpCDuQStU+d0qYN2JmjvOuhjT9C6i8zISWz1tyQ887aJDcpBW8AyHQfrxxwmCWeGmpOn376ck5z1GoJzMK6dlWzaOtadyuw4WFkZrqpzLJ8kZEAzSX5IedOdITjYzORudsbRSJA7o1nBZpK7AIjYaLs1kwVHkWYek4Q8NLJxZhSY6IWOQw5g98ZOfB+FoHmBcCZowTozcDPUlBcilzI7DlYatK5ldnl10OpGzYegveugjz1BN807TxGZbrM3udvEBo6gM2CWHHTHcY3X5L3+3XvJ/RH1+Z7rehnV5AxG1PqwtlyKMOQAllcHvbtrZpHnXepwGdX8LEHQKW96DeEmm52MNxMTmB5oFrAkDcrYcMmAWhyQnlp1v+dnYO1izZruu49wsolE0PxSmwnatrjLwJHJkBpmzLvUQZcFretCleJyb0+C9q+DPu4EbRhX3Di5braTu01sIEFnwNK5QR6cQ7hepRQsS9AyIH1T7DzO82KdqyTvFrnZxgPBsnNUkw4lwgwIrkQGWMqbHgwBWqFqCW+29T2HO5oNbCZ1B9N0nQzlODiAztXMnaBz4ixx6XAutOMO6HwaiaB3T3xvJ2iVsldLvcdnQuugzaBV8+7liaGCcm9fgvatg6YcdLDk7dP7xsF4nWU2xVEBzL4eZzczsecEZq8dD22mtc4xEIzXqB5OMOStaJpFjDPGe3Ee1sftFS1owfhlQesDFi1oveugiaCrcOrhfDAlVo92JqOBRSNoDtaOxakIlBxBVwKzb311GMAwaRxNs4hx1ux8FscB1pntKmDRCDp/wUNFMCLo7hK0Icf9ofPtSnsbkwMI7DiCEUETQRNBExiBEUEfV4LOVIFWSXFEu8GLq9khB4uVY4oPdkyaSWChoUEE3XWCzhQZhftsKN68XlTNDjeYvRD9MIAdk2YSWHhoEEEfHYLOq4wjgi6RdqSpuOhgx6SZBEYE3fXd7FRJ5X9enhFlpY4Z1VQVKBSQfvZj8+SZ8WCCTm2H8J+XjcNLNU3Xp0JI3EuWQLvqlgX71/4UmKlcCWwaDJspT/IAAt9lCtHblgJZR69mwE4knmM045VmtzVTl9xqrJnxkGYamgHAidFxZ9emwaAMejJxhvCCg93SYPb9cB1Nl9EM9ruaNAeyKdt5gJlB62l+i2bli6jGS0ODCNptN7u33xYsiBkGP0lVgXKImZCHZjKCTqc4OI7GSijnomlSMxtBBzcTVtGaYH6WS4JhM0VDfV2QqenV3gwZ2STBoGr760g24++0yRxJxkUzAGhOhjczq4GHF9JgODaM5IAZWIqdT9B+mhlB62l+F5sFhAYRtBNBN8ebk/h4y2ZnaGZ8BsdzzITNyZnfj37246KFe5kqUCBodhbfBeInl2fm2XDaDckySSiYa/6zO9dgm9EhWPPqqGlaM0HQDG2Ro3i10gLWnuQl9/zhJdBa0IdDOcCmwSRBw0lNWP3HUB31y0zegDflGaggdwJYrQwvDaYHkOwkd1fmN/NeQqNxfDMe0EyhGQQEP51X16qIKzOdHUzEEyzba0IdPejmC4YErZopTnGMtIxmv/98t/nrFgN7l+nxf7/rzMPrOfbn9tuXz3/y43mG+igHNKsZBK0wk4qOcSfdrDYD83/S3xw//fa781w9EbdlwSZDgwjahaDZlfHE73jCYGaIsSszK5+tk9ZlvDjkMjpJEjQ7a7LJzudYvkjZe392GsdiyOzGk6vmpWmaoId2ESWklQYYG8LdG+NUOD7Dgxz08YRNpzjgJAYkLeeln9ooGb0pzkAFhRNmhlzx1MYekwZBB7ky00yl0Rwb/+Kb8YBmiqNEQMDpuyriXE2XcYAw2fl/4F4QuvmC4UYXqpniFE/TKc3+4w93/vCreQY2z05j/7bhNX9I4ThP5M4AQTvGmQxa1TH9zZ8iaDB/c+xXP3v3c7DTrrKXW7ARQTvuZseug2BBpL1xI6DGsXd6EjQ/hd1LsQAa3/VFsoxsdgGLIcOaf09N0wQ9jpsjBrXSBOP7mMHeIDwB+r0iaA/YzABOELS0nJd+Jj/wQSWeIRWEzrjr7ItkL+zXJ3m7MgXWHFca8U0qxJuAZgrNhCvxNB1xjqazO4Dvksy8oHTzBMMRtDb8bkikac3u/XKlKbYcaYq9HMWGYdynSNCOcSaCVpqJDai9zZ+yGZr/P/5w78f8bNnm5qRrsBFBuxB0e1LOs/zudpL22uVOy6znVQSNF2rRq9tO7k+DKYKWI2gWW4DkomkaTOyCgXTfnvRqZQaM98K2uKrBYAQJ2g02r5lwkhpBO+qXBlPeNHuK9O+7JXgZm33Ntxid1Cc5uzKnmaZGOEpV2R2/ZgrNhCvNEbTJiDmYBQ4QGpm6eYIhQetm7vpEWlazmUeTfOQMp4kRNH/Et5hs4ATdfuQYZzJozRG0o/lzbAbmP/32580/9mvbISkXBhvtB+1B0LgX0G/625De1WMGNpKYL++LmW1iFUFjqgt6ohOSBUwRNGBx5TqdR/xK7aKpbddluDXcBRSvVmbAeKwzjuBFK+OQzmP6SKhS2LxmwkkMSFrOSb8UmPDmj8UZqCC8acPAuhgvYzOsldAnObvS1kyo4jA0ag6JN/7NlJoJV+JpOuJKTGfTrKMnAZQ7O+MOvcEWGljONJ4gaCfTZUODObTZYmB8qNzCHHRnfu47eNAKTxSxjx45xpkI2kQO2tH8dpvJ/jgJWT7VZgZREmy0H/QBLvWeibf472iCBcxnH3ubERiBEUEfCEHH2jHr6IL5EzTZjMAIjAj6IAg62jaxBEZgBHbMwIigu07Q0baJJTACI7BjBkYETduNEhiBERhtN3qUCfrE97B6Siyh6nTGAxZEq/Kn73Ah0ZB6GCi8kX94LYZ85QMmVyYkwMTaMW8weYJWEz5hr/QPlYWnsBlAVLWZBGMvfncZ/sQCA/VigUVtZiww8dA/rIKOAgavYoFFbSZEacRmDkWyGXSdIJsRQTsR9L1+KCLFSlJYjvtBsN8ABGqNJZwshoQ1Ik2sqeXfTfqAsZsiOF6DgY56bYgPmFGyiaqMy5ph/sDnjhNBC5uhchVtJsHYFYNdOPifWGDaUjE0i9rMSGAIwZ0WC8yAjaBZzGZi4WS8Zs7EAIOuHGozIminlYRQuAl1LzOT6T1tAu58OAjufAWYzTGAZJ8gDfK39/7JadCrwU5PIwdrMHhQsg9BazB5ggBjHyuCHpI/VAKmbQYtrWYzBdace/sy/okFBupFA4vZzEhgEAbotEhgqGM0sIjNVOslY4BBtEcAk105yGZE0C4EDSQF23fBH77hp8/WYGka5CCnvxuSmNxtUMQ+xPdIGce37cnC4jQbGKqkwfhipc8BEf/4gIkTEAw+buLD7fkmiE4ErWyGylWzmQSD9ZHwJxaYaG4ksJjNjAWGYQBA0cBOR3GAAIvZTIz2OGAY7dXBRFcOsxkRtAtBc7vK5YTiyjgT/nw9UUHDaRRfqXHqOKwxxRF0vxtBa7DdxAg6iTiOuRRnMHkCgvGP5Scz444ErWwG51S0mQSDhCX8iQW2K5cbRwGL2cxYYIbTYoHBq1hgMZuJURrNZnFCA7tyoM2IoB1H0LCVN/zx31w3defzrzhimBlHOJ3pxc2zhtTbSR8wqVISDLMSeLPmASZPADD1McdpT7qPoA3lKtpMghn3MZHAUL1YmkVtZiQwEUmVR9AaDHWMpVnMZmLcxgNrT75pm/0gCTqqiGwS34cK9hkTvTk8NQUgMLMLr3AHOlE4ka2jcAYD7yfAdAmGLBdxBsOzBBiqmSkXKc/AGcpVtJkEMwg6EhiqF0uzqM2MBGY4LRIY6hhLs5jNxECPBIbqRQETfT08B50UIugUQeNjpkypMrkbQ44AWFSbERiBHUswImgngs48pKdKeeQxIeioNiMwAjuWYETQTgR9TDiVwAiMwA4VGBE0ETSBERiBEUETQVN4EhiBERgRNBE0gREYgRFBk5CQkJC8ESGCJiEhISGCJiEhISEhgiYhISEhgiYhISEhIYImISEhIYImISEhISGCJiEhISEhgiYhISEhgiYhISEhIYImISEhIYImISEhISGCJiEhISEhgiYhISEhgiYhISEhIYImISEhIYImISEhISGCJiEhISGCJiEhISEhgiYhISEhIYImISEhOZry/wUYAFPZk5uOYGj0AAAAAElFTkSuQmCC
The peritoneum /ˌpɛrᵻtəˈniːəm/ is the serous membrane that forms the lining of the abdominal cavity
https://www.wikiwand.com/en/Peritoneum
See [[here|http://science.kennesaw.edu/~rmatson/Biol%203350/coelom.html]] too
See [[Descriptional complexity]]
See [[Permutation complexity in dynamical systems|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/complexity%20theory/(Springer%20Series%20in%20Synergetics)%20Jos%C3%A9%20Amig%C3%B3%20(auth.)-Permutation%20Complexity%20in%20Dynamical%20Systems_%20Ordinal%20Patterns,%20Permutation%20Entropy%20and%20All%20That-Springer-Verlag%20Berlin%20Heidelberg%20(2010).pdf]]
Permutation entropy was introduced in 2002 by C. Bandt and B. Pompe as a
measure of complexity in time series. In a nutshell, permutation entropy replaces
the probabilities of length-L symbol blocks in the definition of the Shannon entropy by the probabilities of length-L [[Ordinal pattern]]s.
[[Permutation Complexity Related to the Letter Doubling Map |http://arxiv.org/pdf/1108.3642.pdf]]
A class of [[Data structure]]s, introduced by P Bagwell in his paper [[Ideal hash trees|http://lampwww.epfl.ch/papers/idealhashtrees.pdf]] and Rich Hickey who invented [[Clojure]], which implemented these . The persistent data structures make [[immutable data types|Immutable type]] more efficient.ext8mc7m58s -- [[This is how they work|https://www.youtube.com/watch?v=e-5obm1G_FY&t=644s#t=17m58s]]
[[video|https://www.youtube.com/watch?v=e-5obm1G_FY&t=644s#t=16m40s]]. Concept they use: //structural sharing//
Mori, inmmutable.js
--------------------
https://www.wikiwand.com/en/Persistent_data_structure
[[Cleaning]] processes carried out by a [[Person]]
* [[Showering]]
* [[Teeth brushing]]
* [[Hand wash]]
See [[SimpleMind mindmap|https://www.dropbox.com/s/55nz2eh5mvzc06o/Perturbation%20methods.pdf?dl=0]] and notes and [[problem sets|https://www.dropbox.com/s/h7j9v4wp8anlvw3/Perturbation%20Methods%20Homework%20%281%29.pdf?dl=0]] in LectureNotes
[[Notes from tablet|https://www.dropbox.com/s/b4pcb5o4h798z1n/Perturbation%20methods%20%281%29.pdf?dl=0]]
See also lectures on YB from Bender (at PI)
''Perturbation methods'' explore the existence of a __small or large parameter__ to derive systematically a precise approximation. More art than science, building experience is valuable.
There are two methods for obtaining precise approximations: numerical methods and analytical (asymptotic) methods. These are not in competition but complemen teach other. Perturbation methods work when some parameter is large or small. Numerical methods work best when all parameters are order one. Agreement between the two methods is reassuring when doing research. Perturbation methods often give more physical insight.
[[Course materials|https://www0.maths.ox.ac.uk/courses/course/28754]], [[notes|https://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3128/3/PerturbationMethodsSupplementaryNotes.pdf]]
See reading list there
!!__Mathematical foundation__: [[Asymptotic approximation]]
!Applications
!![[Perturbation methods for algebraic equations]]
!![[Asymptotic approximation of integrals]]
!!__Perturbation methods for differential equations__
!!!__Local analysis__
!!![[Local analysis of differential equations]]
(as discussed in Bender's book Part 2. Is this the same as ''regular perturbation'' methods, as discussed in Hinch's book? I think so).
!!!__Global analysis__
Mostly for problems with regions of very different speed of change. These are ''singular perturbation problems'', often when the small parameter $$\epsilon$$ is multiplying the highest derivative. Then the $$\epsilon=0$$ problem is of lower order, and will in general not be able to satisfy all the boundary conditions of the original problem
!!![[Matched asymptotic expansions]]
!!![[Method of multiple scales]]
!!![[WKB method]]
I wonder if there are analogous to these methods to algebraic equations. Maybe through the Perturbation methods for difference equations, which are closer to algebraic equations.
!!__Perturbation methods for difference equations__
These are described in Bender's book
-----------
[[Laplace's method|https://www.math.unl.edu/~scohn1/8423/intasym1.pdf]]
-----
//Books//:
Hinch
Bender and Orzsag
..
!!__[[Iterative method|Fixed-point iteration]]__
Faster if expansion sequence is unknown (i.e. we don't know it it's a power series or a log series for instance); slower, if the expansion sequence is known.
$$x_{n+1} = g(x_n; \epsilon)$$
!!__Espansion method__
Pose (guess) expansion. For instance a power series in small parameter, $$\epsilon$$:
$$x=1+\epsilon x_1 + \epsilon^2 x_2 + ...$$ as $$\epsilon \rightarrow 0$$
and substitute in algebraic equation, and equate terms of equal order because <b>asymptotic expansions (using a fixed set of functions of $$\epsilon$$) are unique</b>.
Easier than the iterative method, specially when working to higher orders, but must assume form of expansion.
!!__[[Singular perturbations|Singular perturbations in algebraic equations]]__
When limit problem ($$\epsilon =0$$) differs in an important way from the limit $$\epsilon \rightarrow 0$$). Main method:
''Regularization method'': Scale variables so that the problem becomes regular.
!!__Non-integral powers__
When power expansion fails (one of the coefficients seems to need to be $$\infty$$..), an expansion in non-integral powers may be necessary.
This happens for example when the roots at limit problem ($$\epsilon =0$$) are a double root. As he says from example given in the notes, we could have guessed that an order $$\epsilon^{1/2}$$ change in $$x$$ would be required to produce and order $$\epsilon$$ change in a function at its minimum. Yeah if we are perturbing the parabola by an order $$\epsilon$$, then the new root would be the same as perturbing $$x$$ in such a way as to get the order $$\epsilon$$ change in the original parabola. At the minimum of the parabola, from Taylor expanding, we see we need a larger $$\epsilon^{1/2}$$ change in $$x$$ to get the $$\epsilon$$ change in the function.
!!__Finding the right expansion sequence__
We first pose the general expansion:
$$x=1+\delta_1 x_1$$, $$\delta_1(\epsilon) \ll 1$$
Substitute into the algebraic equation, and look for dominant balances in the result. This will involve looking for the largest terms with and without $$\delta_1(\epsilon)$$
Once we have the first, term, we add a term to the expansion:
$$x=1+\delta_1 x_1+\delta_2 x_2$$, $$\delta_2(\epsilon) \ll \delta_1$$
And we repeat this process
Again, the __[[iterative method|Fixed-point iteration]]__ is very useful when the expansion sequence is not known, and can be faster than the above method involving unknown expansion functions, $$\delta$$.
!!__Logarithms__
Normally appears in transcendental equations.
Use [[iterative method|Fixed-point iteration]] as expansion method is hard to guess.
In his example, "over this range the term $$x$$ is slowly varying while $$e^{-x}$$ is rapidly varying. This suggests rewriting the equation as $$e^{-x} = \frac{\epsilon}{x}$$. I think this is so that we control/determine the faster changing term.
[[Liquid Separation by Membrane Pervaporation: A Review|http://pubs.acs.org/doi/abs/10.1021/ie960189g]]
[[Polymeric membrane pervaporation|http://www.sciencedirect.com/science/article/pii/S0376738806007095]]
A measure of [[Concentration]] of [[Hydrogen ion]]s in a [[solution|Solution (Chemistry)]]. It is defined as:
$$\text{pH} = -\log{[\text{H}^+]}$$
where $$[\text{H}^+]$$ is in units of [[Molarity]]. Thus pH = 7, refers to $$[\text{H}^+] = 10^{-7}$$ M.
The pH also indirectly expresses the concentration of [[Hydroxyde]] ions, in an aqueous solution. This is because [[Water]] molecules dissociate to form H^^+^^ and OH^^-^^ in a process:
$$H_2 O \rightleftharpoons H^+ + OH^-$$
The [[Equilibrium constant]] for this dissociation is
$$K = \frac{[H^+][OH^-]}{[H_2 O]}$$
and has a value of $$K = 1.8 \times 10^{-16}$$, where the concentrations are in molarity units.
The concentration of water in pure water, $$[H_2 O]$$, is 55.5 M, and is constant under most conditions. We can then define a new constant:
$$K_W = K [H_2 O] = [H^+][OH^-]$$
$$ = 10^{-14}$$,
so
$$ [OH^-] = \frac{10^{-14}}{ [H^+]}$$
!!!See also [[Acid-base equilibria]]
* [[Acid]]
* [[Base]]
http://www.bbc.co.uk/education/guides/znhcwmn/revision
Process by which a piece of [[Bulk matter]] changes from one [[Phase of matter]] to another (see [[Condensed matter physics]])
__Qualitative picture__
//...See sec 2.2.2 on Soft Condensed Matter by Richard Jones, and also beginning chapter of Principles of condensed matter physics//
*Gas (kinetic energy dominates)
*Liquid (kinetic and potential energy comparable)
*Solid (potential energy dominates)
As we increase temperature, the average energy per particle, $$U$$, increases (see [[Equilibrium statistical physics]]). Because the [[potential between molecules|Intermolecular forces]] is generally bounded above (for example the attractive part can have the form of $$-1/r$$ or $$-e^{-r}$$ for large $$r$$, so that the maximum potential energy is 0), as we increase $$U$$, we soon reach a point where we must increase the kinetic energy, as the potential energy becomes saturated (i.e. the molecules have dissociated, or we have broken the bond). Therefore, as we increase temperature, we find that we go to phases where the kinetic energy is more and more dominant, often from solid to liquid to gas, though, for low enough pressure, the liquid phase is skipped.
Phase diagrams, 2D projections of surface in a 3D space of temperature, pressure, and volume.
//Critical point//: point at which gas-liquid transition changes from being continuous to discontinuous.
//Triple point//: Point of coexistence between three phases.
[img[phase_diagram.PNG]]
!!__Order parameters and phase fields__
''Order parameter'': quantity that distinguishes different phases, often associated with some kind of "order", and is often $$0$$ in disordered phase. There are two main types:
* ''Conserved order parameter'' (like concentrations). Atoms can't change species. Average over sample of paremeter thus fixed. Often then one gets //phase separation//. An example is in [[Thermodynamics of liquid-liquid unmixing]]. {{Order parameter field} evolution} described by <span style="color:coral;font-weight:bold;">Cahn-Hillard equation.</span>
* ''Non-conserved order parameter'' (like magnetization). Atoms can change their spin. Average of parameter over sample is thus not fixed. An example is magnetization. {{Order parameter field} evolution} described by <span style="color:coral;font-weight:bold;">Allen-Cahn equation.</span>. See [[equation|http://www.ctcms.nist.gov/~wcraig/variational/node10.html]]; [[applications in population genetics, combustion and nerve pulse propagation!|http://link.springer.com/chapter/10.1007%2FBFb0070595#page-1]]; [[original paper|http://www.sciencedirect.com/science/article/pii/0001616060901103]].
These equations describe the evolution of ''phase fields'': the fields of the {space-time varying order parameter}. They thus belong to the so-called __phase-field method__ used in [[Materials science]], for example.
__Mixture theory__ or the theory of interacting continua also uses the above equations for describing multi-phase systems. See [[ON THE DEVELOPMENT AND GENERALIZATIONS OF ALLEN-CAHN AND STEFAN EQUATIONS WITHIN A THERMODYNAMIC FRAMEWORK|http://ncmm.karlin.mff.cuni.cz/preprints/11289092919pr19.pdf]]
See also [[Soft matter physics notes|https://www.dropbox.com/s/mw2fc6b6b2rdfm6/Soft%20matter%20physics.pdf?dl=0]]. Though, <mark>I would like to see a more rigorous derivation of these equations, based on non-equilibrium thermodynamics</mark>. The derivation are rigorous, they just use [[Constitutive equations]] that are mostly just assumed, instead of derived!
!!__Landau theory of phase transitions__
Describing phase transitions in terms of a free energy, which is a function of the order parameter, and depends on parameters (such as temperature). As one varies the parameters, the free-energy minima change location, and appear/disappear at phase transitions.
Ginzburg-Landau theory in [[Statistical field theory]]: write down most general free energy that is consistent with known __symmetries__ of the order parameter. Assume it can be written in power series and stop hen additional terms don't change the behaviour of interest.
Symmetries. [[Symmetry breaking]], [[Metastability]]. Correlation functions, etc. Critical exponents (describe behavior of thermodynamic functions near critical point).
__Order of transition__
* //First order//: order parameter changes discontinously . 1st derivative of free energy discontinuous.
* //Second order//: order paramter changes continuously. 2nd derivative of free energy discontinuous. Like transition from liquid to gas at critical point.
!!!__Critical exponents and universality__
!!__Examples of phase transitions__
[[Evaporation]]
[[Melting]]
[[Sublimation]]
[[Solidification]]
[[Crystallization]]
[[Percolation phase transition]]
[[Spin glass phase transition]]
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
a phase-transfer catalyst or PTC is a catalyst that facilitates the migration of a reactant from one phase into another phase where reaction occurs.
https://en.wikipedia.org/wiki/Phase-transfer_catalyst
A physical characteristic of an [[Organism]], appearance, feature, a particular version/instance of a [[trait|Phenotypic trait]]. [[vid|https://www.youtube.com/watch?v=H6gwYdyn7II#t=3m]]. Sometimes, a phenotype is referred to as a //trait// too (although it is a little bit confusing terminology)
__[[Genetic dominance]]__
//aka trait//
A trait is a general aspect of physiology being shown in a [[Phenotype]]. So, for example, the trait being discussed in [[here|https://www.stat.washington.edu/thompson/Genetics/1.3_genotypes.html]] is the flower-color of the pea plant. The phenotype can be either red or white flower color, depending on the genotype.
https://www.wikiwand.com/en/Phenotypic_trait
A [[Functional group]] derived from the [[Benzene]] ring
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/a/a4/Phenyl-group.png/150px-Phenyl-group.png]].
It is no[[non-polar|Non-polar molecule]].
"One does not simply define Philosophy" ~ ''Me''
Philosophy is ''this''. It is the study of the ''Cosmos'', from the anthropocentric perspective, of our Knowledge of the Cosmos. This is, in a fundamental sense, all we have, since the physical, objective perspective, of the Cosmos ultimately derives from our Knowledge of it.
From this perspective, Cosmos gets equalled to our Knowledge of it. ''Philosophy'' concerns itself with the study of the Cosmos from this perspective, which basically by definition, encompasses everything else here, everything one ever thinks, and is conscious of.
I call this the ''observer perspective'', and I think it's the most fundamental.
This is in contrast to the ''god perspective'' often taken in Science, where we imagine an objective reality separate from our minds (described in [[Cosmography]] and [[Cosmology]]). This perspective has been so useful and fruitful, I consider this physical objective world to be true also, even if our only access to it is by our limited senses and mental models of it (as asserted by the observer perspective).
Most often I work with the god perspective, as in Science. However, when dealing with complex philosophical questions, I have to switch to the more fundamental observer perspective.
See also [[Metaphysics]] for another description of the above, as a view of the nature of Existence.
[[Portal:Contents/Philosophy and thinking|https://en.wikipedia.org/wiki/Portal:Contents/Philosophy_and_thinking]]
[[Stanford encyclopedia of philosophy|http://plato.stanford.edu/index.html]]
------------------------------------
My [[Metaphysics]]: Observer/god perspective, or better name may be Mind/Physical reality.
*[[Ontology]]
My [[Epistemology]]: Principle of Inclusiveness
My [[Ethics]]: Utilitarianism up to the point you can. Then virtue/[[Emotion]]/[[Aesthetics]]. In particular, see discussion in [[Emotion]].
My [[Logic]]. Don't know enough, but I think [[Mathematical logic]] may be the best description.
------------
My [[Politics]] (ideas only): A weak dynamic social democracy, combined with a robust weighted direct democracy and a cyber-government.
---------------------
One of the central ideas of this philosophy that combines observer perspective with the existence of a physical world, is the division of everything into whether information flows from observer to physical world, or vice versa. The former, I call [[Art]]; the latter, I call [[Science]]. All other sections are effectively described by these two aspects of the observer condition, which I holistically call //the Conversation with Nature//.
Here is a very interesting alternative to my conceptual framework: [[Krebs cycle of creativity|http://jods.mitpress.mit.edu/pub/designandscience]]
[img[https://s3.amazonaws.com/pubpub-upload/designandscience/1452570999537_a140aedc-696e-4f70-a426-a6bcd21621ba.png]]
----------
Inclusiveness Principle to arrive at Truth.
See also [[Philosophy of mind]]
[[Answering Descartes: Beyond Turing|https://mitpress.mit.edu/sites/default/files/titles/alife/0262297140chap4.pdf]] -- [[video|https://www.youtube.com/watch?v=i4YAw8xM1gA]]
https://media.ccc.de/v/32c3-7483-computational_meta-psychology#video
brainbow
https://www.wikiwand.com/en/Embodied_cognition
http://opentheory.net/2016/11/principia-qualia/
[[Philosophy of quantum mechanics]]
[[Philosophy of space-time]]
[[Philosophy of statistical mechanics]]
im a bayesian frequentist
I think of almost all probability as fundamentally frequentist, but because of our incomplete knowledge/computational resources we make subjective and simplifying assumptions which are best carried out in a Bayesian framework.
However, the deepest probabilistic questions, I think are fundamentally subjective, and so foundamentally Bayesian (see my #philosophy)
#probability
See also [[Philosophy of quantum mechanics]] and [[Philosophy of statistical mechanics]]
See The emergent multiverse, and papers by David Wallace
http://physics.stackexchange.com/questions/27190/experimental-test-of-the-non-statisticality-theorem
http://physics.stackexchange.com/questions/233203/has-jayness-argument-against-bells-theorem-been-debunked
[[Duhem-Quine thesis|https://en.wikipedia.org/wiki/Duhem%E2%80%93Quine_thesis]]: You can't test a hypothesis in isolation, but always in conjunction with ancillary assumptions.
[ext[David Wallace's homepage|http://users.ox.ac.uk/~mert0130/index.shtml]]
Karl Popper
[[Beyond Descartes and Newton: Recovering life and humanity|http://www.sciencedirect.com/science/article/pii/S0079610715000784]]
__Proposed clasification__
[img[http://36.media.tumblr.com/bc8a60906e437afa2216153c666dd4ac/tumblr_n8xr8asYUf1te399ao2_r1_1280.png]]
[[Korzybski]]
[[Operational definition]]
__David Wallace__
[[https://www.youtube.com/watch?v=cbiZjw1Yqrc]]
[[https://www.youtube.com/watch?v=tvurMXsSM7I]]
Thermodynamics as Control Theory
His course on philosophy of stat mech
My notes and thoughts on his course
A ''phoretic mechanism'' of colloids, is any mechanism/effect that causes [[colloidal particles|Colloid]] to move in a way that is partially deterministic (unlike [[Diffusion]]), due to the gradient of some physical quantity (,,This seems to be the working definition, judging from what I've read,,). These may also called ''transport mechanisms''.
These are important in [[Active matter]], in [[Biophysics]], and [[Nanotechnology]]. In particular phoretic effects can make a colloidal particle self-propelling.
A large class of mechanism for colloid transport are due to ''interfacial forces'', due to non-trivial [[Microhydrodynamics]], [[Chemical reaction]]s, or other effects.
<big><i class="fa fa-star-o" aria-hidden="true"></i> See [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]</big>. See also the more recent [[Manipulation of Colloids by Osmotic Forces |http://hal.in2p3.fr/tel-00597477/document]]
[[Generic theory of colloidal transport|http://link.springer.com/article/10.1140/epje/i2008-10446-8]]
[[Thermal non-equilibrium transport in colloids|http://iopscience.iop.org/article/10.1088/0034-4885/73/12/126601/meta]]
!!__Phoretic mechanisms__
__[[Diffusiophoresis]]__
__[[Osmiophoresis]]__
__[[Electrophoresis]]__
__[[Thermophoresis]]__
__[[Phoretic mechanisms of self-propelled colloids]]__
[[Phoretic mechanisms|Phoretic mechanisms of colloids]] for [[active colloids|Active colloid]].
Phoretic mechanisms for living organisms (for instance living active colloids like [[Cell]]s) are called [[Taxis]]. See [[Chemotaxis]] for a prominent example. Actually, ''chemotaxis'' is often applied to the phoretic mechanisms of active colloids (when they are originated by a gradient in a chemical concentration). More specifically, //chemotaxis// may be used to refer attraction to higher chemical concentration, while //anti-chemotaxis// would refers to repulsion from it.
!!__Mechanisms__
* "''Chemotaxis''" (in the sense of directional alignment with chemical gradient). The fluid flows set up around the particle can turn its axis of orientation to align parallel or antiparallel to the local gradient; this process has active contributions arising from the chemical reaction as well as passive ones.
* ''Polar run-and-tumble''. The enzymatic rate depends nonlinearly on the local concentration of the substrate with a characteristic Michaelis- Menten form inherited from the underlying catalytic kinetics of the reactions [ 38 ]. The combination of enhanced activity at high concentrations and randomized orientation acts to effectively populate the colloids in “slow” regions [ 39 ].
* ''Apolar run-and-tumble''. An active colloid can also chemotax by a net motion of its center along a gradient in a noise-averaged sen. <mark>I think this is basically polar diffusiophoresis? I.e. the particle is repelled (or attracted) to gradients mostly along its axial direction (due to higher asymmetry in motility).</mark>
* ''[[Phoretic response|Phoretic mechanisms of colloids]]'' (referring to the standard phoretic response, also present in non-active colloids). The colloid moves along an external chemical gradient by diffusiophoresis.
[img class=img-centered [http://i.imgur.com/JLXo6Ql.png]]
!!!__[[Theory of phoretic mechanisms of self-propelled colloids]]__
A [[Functional group]] composed of a [[Phosphate]] bound to four (possibly ionized) [[Hydroxyl]] groups.
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/7/70/Phosphat-Ion.svg/140px-Phosphat-Ion.svg.png]]
Phosphate acts as a [[buffer|Buffer solution]] in biological systems at [[pH]] 7.4
[img[Selection_648.png]]
Addition of a [[Phosphate]] to a [[Protein]], which produces conformational changes. This can act as a signal/swicht, to regulate [[Metabolic network]]s, and [[Gene regulatory networks]]
A [[Chemical element]] composed of phorphorus atoms. These have 15 proton in the nucleus.
The hydrogen atom tends to form three bond, as it has 5 electrons in its outer shell (see [[Octet rule]]).
Addition of a [[Phosphate]] to a [[Protein]], which produces conformational changes. This can act as a signal/swicht, to regulate [[Metabolic network]]s, and [[Gene regulatory networks]]
https://www.wikiwand.com/en/Photochemistry
http://www.bbc.co.uk/education/guides/z4cmn39/revision/4
[[Photosynthesis: Crash Course Biology #8|https://www.youtube.com/watch?v=sQK3Yr4Sc_k&index=8&list=PL3EED4C1D684D3ADF]]
__Light dependent reactions__
Basically [[Cellular respiration]] in reverse.
[[Water]] + [[Carbon dioxide]] + sunlight
__Light independent reactions__
Calvin cycle
The [[evolutionary|Evolution]] relantionships between [[Organism]]s. --> [[Tree of life]]
Traditionally studied by looking at apparent differences and similarities, but now we use more [[Genomics]]
[img[physarum_machines_books.png]]
See Networks miniproject (inoverleaf), pdf here: [[Spatial network optimization with a model of the physarum polycephalum|file:///home/guillefix/Dropbox/Oxford/MMathPhys/Networks/miniproject/896065.pdf]] or [[here|spatial-network-optimization (1).pdf]]
__Analytical properties of physarum solver__
http://epubs.siam.org/doi/pdf/10.1137/1.9781611974331.ch131
[[Convergence properties of physarum solver|http://arxiv.org/pdf/1101.5249v1.pdf]]
[ext[Physarum Can Compute Shortest Paths|https://people.mpi-inf.mpg.de/~mtd/files/physarum_shortest_path.pdf]]
[ext[PHYSARUM CAN COMPUTE SHORTEST PATHS: A SHORT PROOF|http://www.iasi.cnr.it/~vbonifaci/pub/physarum-ipl.pdf]]
[[Physarum Can Compute Shortest Paths|http://arxiv.org/abs/1106.0423]]
[[IRLS and Slime Mold: Equivalence and Convergence|http://arxiv.org/abs/1601.02712]]
[[On a Natural Dynamics for Linear Programming|http://arxiv.org/abs/1511.07020]]
__Tero's model__
A mathematical model for adaptive transport network in path findingby true slime mold
A Mathematical Study ofPhysarum polycephalum
http://www.ncbi.nlm.nih.gov/pubmed/18415133
__Other models__
[[An Improved Physarum polycephalum Algorithm for the Shortest Path Problem|http://www.hindawi.com/journals/tswj/2014/487069/]]
[[Physarum Learner: A bio-inspired way of learning structure from data|http://www.sciencedirect.com/science/article/pii/S0957417414001274]]
[[An adaptive amoeba algorithm for constrained shortest paths|http://www.sciencedirect.com/science/article/pii/S0957417413005411]]
__Dynamics__
[[Physarum polycephalum Percolation as a Paradigm for Topological Phase Transitions in Transportation Networks|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.109.078103]]
__Experiments__
[[Plasmodial vein networks of the slime mold Physarum polycephalum form regular graphs|http://journals.aps.org/pre/cited-by/10.1103/PhysRevE.82.046113]]
Are motorways rational from slime mould's point of view?
[[Rules for Biologically Inspired Adaptive Network Design|http://science.sciencemag.org/content/327/5964/439.full]]
http://www.nature.com/articles/srep03495
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
Study of chemical systems ([[Chemistry]]), using concepts from [[Physics]].
https://en.wikipedia.org/wiki/Physical_chemistry
*[[Quantum chemistry]]
*[[Statistical physics]], [[Thermodynamics]]
** [[Non-equilibrium statistical physics]]
*** [[Diffusion]]
** [[Chemical energetics]]
* [[Condensed matter physics]], [[Soft matter physics]]
**[[Colloid physics]]
**[[Polymer physics]]
https://en.wikipedia.org/wiki/Geography#Human_geography
[[Physical|Physics]] mechanisms of [[Osmosis]]
!!__Macroscopic/thermodynamic description__
Based on [[Chemical potential]]s, [[Solution (Chemistry)]]
[[The solution-diffusion model: a review|http://www.sciencedirect.com/science/article/pii/037673889500102I]]
!!__Microscopic mechanism__
[[MECHANISM OF OSMOTIC FLOW IN POROUS MEMBRANES|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1334591/pdf/biophysj00323-0049.pdf]]
The standard chemical potential explanation still holds as part of the mechanism. See [[here|http://physics.stackexchange.com/questions/212183/physic-explanation-to-osmosis?rq=1]]. The energy comes from the expansion of the solute (which works like an ideal gas), just like in [[quasistatic adiabatic expansion|https://www.physicsforums.com/threads/work-done-in-adiabatic-quasistatic-compression.138448/]].
However, the boundary layer given by a [[Diffusio-osmotic|Diffusio-osmosis]] effect, enhances the checmical potential difference at the pore increasing the osmotic pressure. The extra work done in the process, I think, ultimately comes from the fact that the potential energy near the wall is lowered as the solute concentration decreases during the process.
When membrane is semi-permeable (as in [[Osmosis]] proper), then I think that the main effect would be an excluded volume effect (this appears to be indeed the case, at least for purely semi-impermeable membranes see [[Negative osmosis]]), giving rise to an effective repulsive potential, like that in Nelson's Biological physics book, or those that appear in [[Diffusio-osmosis]], or [[Diffusiophoresis]].
See [[Interfacial forces]]
[[Molecular mechanisms of osmosis|http://ajpregu.physiology.org/content/256/4/R801.short]]
[[Mechanism of osmosis|http://www.sciencedirect.com/science/article/pii/S0085253815326570]]
[[OSMOSIS: A MACROSCOPIC PHENOMENON, A MICROSCOPIC VIEW|http://advan.physiology.org/content/27/1/15.full.pdf+html]]
[[Osmosis is not driven by water dilution|http://sci-hub.cc/10.1016/j.tplants.2012.12.001]], [[here too|http://phys.org/news/2013-04-osmosis-wrong.html#jCp]]. See Nelson's Biological physics book for more details
The mechanism is based on the wall repelling the solute molecules. See analysis [[here|http://nature.berkeley.edu/osterlab/wp-content/uploads/2015/02/Osmosis.pdf]].
Alternative mechanisms: [[Osmosis, colligative properties, entropy, free energy and the chemical potential|http://arxiv.org/abs/1409.3985]]
[[Osmosis and thermodynamics explained by solute blocking|http://link.springer.com/article/10.1007/s00249-016-1137-y]]
[[http://www.circle4.com/biophysics/chapters/BioPhysCh05.pdf]]
[[Brownian motion, hydrodynamics, and the osmotic pressure|http://sci-hub.cc/10.1063/1.464105]]
[[Molecular Understanding of Osmosis in Semipermeable Membranes|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.97.024501]]
See also [[Negative osmosis]] for more resources.
[[Osmotic pressure or decompression?|http://link.springer.com/article/10.1134/S1061933X15050154]]
''Physics'' (from Ancient Greek: φυσική (ἐπιστήμη) phusikḗ (epistḗmē) "knowledge of nature", from φύσις phúsis "nature") is the natural science that involves the study of matter and its motion through space and time, along with related concepts such as energy and force. One of the most fundamental scientific disciplines, the main goal of physics is to understand how the universe behaves. ([[wiki|https://en.wikipedia.org/wiki/Physics]]).
[[The Mechanical Universe|https://www.youtube.com/watch?v=_ndaBQUFTLs&list=PLGGML-sB2bN9HlEowBPW75fdfNNK6NHBO]]
!!!Nice map of physics: http://scimaps.org/maps/map/being_a_map_of_physi_171/detail
[[System of measurement|https://en.wikipedia.org/wiki/System_of_measurement]]
[[Physical review letters|http://journals.aps.org/prl/]]
[[International Centre for Theoretical Sciences|https://www.youtube.com/playlist?list=PL04QVxpjcnjhs0tFaWHdNKA5UE8doxIbz]]
http://physics.info/
hyperphysics, etc.
[[The Map of Physics|https://www.youtube.com/watch?v=ZihywtixUYo]]
-------
Some physics books: http://www.fisica.net/ebooks/
See DB\Cosmos, etc....
<mark>Should organize this</mark>. See SimpleMind mindmap. See also [[Bulk matter]].
https://journals.aps.org/prx/issues/6/2
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
Studies the ''function of organisms''. Goes together with [[Anatomy]], which studies the structure of organisms. One often restricts physiology to refer to the "normal" functioning of organisms, in contrast with [[Pathology]]
https://en.wikipedia.org/wiki/Physiology
See [[Human physiology]]
see vids [[here|https://www.youtube.com/watch?v=tIfsHPpkSPs&list=PL3EED4C1D684D3ADF&index=22]]
A lot of biological function is determined by its chemistry, and a hierarchy of systems, studied in [[Systems biology]], thus relevant areas are:
* [[Biochemistry]]
** [[Metabolism]]
* [[Genetics]]
* [[Molecular biology]]
* [[Cell biology]]
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!!!__[[Organ system]]s__
[[Review of piezodialysis — salt removal with charge mosaic membranes|http://www.sciencedirect.com/science/article/pii/S0011916409013460]]
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
Places
[[Portal:Contents/Geography and places|https://en.wikipedia.org/wiki/Portal:Contents/Geography_and_places]]
Vivekananda Rock & Valluvar Statue, southernmost peak of India, where two seas and an ocean meet
[img[https://upload.wikimedia.org/wikipedia/commons/7/78/Vivekananda_Rock_%26_Valluvar_Statue_at_Sunrise.JPG]]
A ''planar network'' (or graph) is one that can be drawn on a plane without having any edges cross.
For these graphs we can define the ''[[Dual Graph]]'', with vertices being //faces// (regions completely enclosed by edges), and edges being among //faces// that share an edge of the original graph. This new graph is also planar
Dual graphs were used to prove the ''four-color theorem'' by Appel and Haken, which translated to graphs is stated in terms of the ''chromatic number'', the number of colors required to color the vertices of a graph in such a way that no two vertices connected by an edge have the same color.
__Kuratowski's theorem__...
As of yet, there is no popular measure of degree of planarity (i.e. //how planar// a graph is?)
🌐🌎🌍🌏∞🌌
[[Movements of Earth]]
[img[http://i.imgur.com/h3nEwBa.png]]
A planetary system is a set of gravitationally bound non-stellar objects in orbit around a star or star system
!!__Plant biology (botany)__
[[Plant cell]]
!!!__Evolution of plants__
Evolved more than 500 million years ago, as [[Lycophite]]s. These plants where so numerous that they have resulted in many coal beds from this period, now called [[Carboniferous]]
[[Plant Cells: Crash Course Biology #6|https://www.youtube.com/watch?v=9UvlqAVCoqY&index=6&list=PL3EED4C1D684D3ADF]]
See [[Plant]]
They have a ''cell wall'' made of polysaccharides cellulose, hemicellulose and pectin; sometimes also lignin or cutin
[[Plant sciences - Springer|http://www.springer.com/gp/life-sciences/animal-sciences]]
[[Oxford notes|http://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/KT/2015/KTLectureNotes.pdf]]
See also ~LectureNotes
[[Magnetohydrodynamics]]
''Plastic'' is a generic term used in the case of polymeric material that may contain other substances
to improve performance and/or reduce costs.
Note 1: The use of this term instead of polymer is a source of confusion and thus is
not recommended.
Note 2: This term is used in polymer engineering for materials often compounded that
can be processed by flow.
https://en.wikipedia.org/wiki/Plastic
I think it's synonymous with differential topology
https://www.youtube.com/watch?v=1LwkljjLBns
A [[Molecule]] with a permanent [[Electric dipole]]. It can refer to a [[Moiety]] too.
The polarity of a molecule really lives on a spectrum (corresponding to the strength of the dipole), dependent on the relative [[Electronegativity]] of the atoms forming a [[Chemical bond]].
A class of [[Reinforcement learning]] algorithms. [[These are also known as direct search algorithms|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=9m]], in contrast with algorithms where our aim is to find the optimal value function
[[intro vid|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=6m25s]]
[[General aim|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=7m35s]]
''Stochastic policy'' -- [[Definition|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=11m23s]]
!!!__Algorithm__
Sometimes called the ''reinforce algorithm'', and is a form of [[Stochastic gradient descent]]
[[Goal|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=23m]]
[[Algorithm|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=27m]] -- [[explanation|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=28m45s]]
[[Derivation|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=33m]], using the [[Product rule]]
# [[Differentiation|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=36m05s]]
# [[Factor out joint probability from terms in sum|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=38m]]
# Rewrite as expectation --> [[On expectation, reinforce algorithm updates parameters in the direction of the gradient of the expected payout|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=40m05s]]. This shows the algorithm is an [[Stochastic gradient descent]] algorithm!
With direct policy search, [[rewards may be combined in other ways other than by summing them|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=40m50s]]
[[Derivation by Nando|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=42m43s]] -- [[comment on reward function not being really needed|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=46m50]] --> [[result|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=49m05s]]
What we use for the gradient descent is do a [[Monte Carlo]] estimate, which makes it stochastic.
!!__Pegasus__
---->[[vid|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=48m]]
[[Nando's vid|https://www.youtube.com/watch?v=kUiR0RLmGCo&index=15&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=52m]]
!!__Policy gradient methods__
!!!__Deterministic Policy Gradient Algorithms__
[[paper|http://jmlr.org/proceedings/papers/v32/silver14.pdf]]
!!!__Natural policy gradient__
!!__Other variations__
Can approach it as an [[Inference]] problem, or in other ways. See [[comment|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=1m47]]
!!!__pair-wise policy comparisons__
!!!__probabilistic policy search approaches__
__based on EM __
__based on probabilistic modeling __
!!!__ Relative Entropy Policy Search __
[[Hierarchical Relative Entropy Policy Search|https://is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/2012/AISTATS-2012-Daniel.pdf]] -- [[extended version|http://jmlr.org/papers/volume17/15-188/15-188.pdf]]
...
-------------------------
//Some potentially good ideas for political systems//
Social Futurism
A weak dynamic social democracy, combined with a robust weighted direct democracy and a cyber-government.
From each according to his wants, to each according to his wants, from the machines whatever else is needed. https://www.youtube.com/watch?v=F5uqZGA06vE Transhumanist declaration 1998 http://ieet.org/index.php/IEET/more/twyman20140416 http://wavism.net/ Bioneering Sociocyberneering http://www.thevenusproject.com/ http://www.thezeitgeistmovement.com/ Polymatharchy http://en.wikipedia.org/wiki/Idea_of_Progress
A more in depth summary:
1. ''weak'' (not many powers given to the "admin bods" as Rusell Brand calls them (https://www.youtube.com/watch?v=3YR4CseY9pk&t=4m56s). Also see: https://www.youtube.com/watch?v=gy0R56sZ0ts to understand this better.)
2. ''dynamic'' democracy (citizens can vote to change leaders at any time, Details: http://www.ted.com/.../a_dynamic_democracy_where_lea.html)
3. ''social'' (ok, this is a broad term. I will give it here the definition of focusing on social causes, that is on the betterment of all people's lives. Include ideas like the declaration of human rights, basic income and income taxes here.)
4. ''strong direct democracy'' (refers to most decisions being taken by all the citizens by some voting/discussion scheme, probably striving for >50% majority. A note here is that less restrictions would generally be put on corrective decisions, rather than initiative ones, because of the biggest imperative of avoiding harm than of enhancing some quality. This idea is called corrective democracy: http://www.fee.org/the.../detail/can-we-correct-democracy...)
5. ''weighted'' (means that people who have certain qualifications or have acquired certain merits have a bigger saying in issues)
6. ''cyber-government'' (this refers to both the technologies used to implement a lot of the above, and to the general idea of creating an advanced nervous system for society (see https://www.youtube.com/watch?v=5zn8MRKOskw&t=78m18s for example), from which everyone can get informed and inform others, and which can on itself help on arriving at decisions (by different possible kinds of AI))
--experimental politics would also be a thing, as more people start viewing politics as the "social tech" it is. Freedom will thus be enhanced by voluntarism in things like startup cities: http://startupcities.org/hacking-law-and-governance-with.../ On short, my view is that technology allows governance to really be put on the hands of the citizens, but this must be done in an intelligent and supervised way.
https://futuristech.info/posts/opinion-why-i-am-pro-vyrdism-and-not-pro-universal-basic-income-ubi
-----------------
//UPDATES//
So many cool and good people are in favour of Universal Basic Income. See more here: http://www.agreelist.com/s/universal-basic-income-kbupbtnz4sek , http://gizmodo.com/elon-musk-we-need-universal-income-because-robots-will-1788644631
Tbh my latest thoughts (which retrospectively actually agree quite well with my previous ideas) is that the government shouldn't regulate (the markets) much at all. Instead it should only do whatever is necessary to protect the law, and assure UBI.
The fact that I (as of now ) support two traditionally very right and left wing ideas should tell you how little I care about the left/right dichotomy..
Certain spatio-temporal patterns of firing (with time-locked firings) emerge in [[Spiking neural network]]s with axonal delays, and STDP learning -- [[paper|http://www.izhikevich.org/publications/spnet.pdf]]
Because of [[Spike-timing-dependent plasticity]], spiking neural networks can give rise to radically different self-organisation of visual representations when trained on visual scenes (for example). Furthermore, if distributions of axonal delays between neurons are incorporated, then this can give rise to a phenomenon known as ‘polychronization’. This phenomenon involves the network learning many memory patterns, each of which takes the form of a repeating temporal loop of neuronal spike emissions. These temporal memory loops self-organise automatically when STDP is used to modify the strengths of synapses in a recurrently connected spiking network with randomised distributions of axonal conduction delays between neurons. Stringer et al. discuss how a form of polychronization may contribute to the development of highly selective [[binding neurons|Binding problem]].
The firing patterns can be found in the firing sequences of single neurons or in the relative timing of spikes of multiple neurons, which are then said to form a functional ''neuronal group''. Activation of such a neuronal group can be triggered by stimuli or behavioral events. These findings have been widely used to support the hypothesis of ''temporal coding'' in the brain.
Since the firings of these neurons are not synchronous but time-locked to each other, we refer to such groups as polychronous, wherepolymeans manyandchronousmeanstimeorclockin Greek. Polychrony should be dis-tinguished from asynchrony, since the latter does not imply a reproducible time-locking pattern, but usually describes noisy, random, nonsynchronous events. It is also different from the notion of clustering, partial synchrony (Hoppensteadt & Izhikevich, 1997), or polysynchrony (Stewart, Golubit-sky, & Pivato, 2003), in which some neurons oscillate synchronously while others do not.
//How many distinct polychronous groups can be stored in a given network?// Experimentally, even more than the number of synapses. But theoretically?
We hypothesize that polychronous groups could represent [[memories|Memory]] and experience. They show that the memory tends to learn to "recognize" input patterns, by developing polychronized groups activated by them.
''Rate to Spike-Timing Conversion''. Neurons in the model use a spike-timing code to interact and form groups. However, the external input from sensory organs, such as retinal cells and hair cells in cochlear, arrives as a rate code, that is, encoded into the mean firing frequency of spiking. How can the network convert rates to precise spike timings? . It is easy to see how rate to spike-timing conversion could occur at the onset of stimulation. As the input volley arrives, the neurons getting stronger excitation fire first, and the neurons getting weaker excitation fire later or not at all. Spiking between layers in [[Feedforward neural network]]s?. They hypothesize that [[intrinsic rhythmicity|Brain waves]] generates internal “saccades” that can parse the rate input into spike timing, and they discuss three possible mechanisms how this could be accomplished.
Related to [[Synfire chain]]s, which are sometimes called //synfire braid//s.
A polyhedron can be seen as an intersection of [[Half-space]]s.
* [[Polytope]]
A ''polymer'' is a molecule composed of a small molecular unit repeating in a chain; usually $$>100$$ units. The chain may have complicated topology, like branches, or cross-links. Links can also be made between different polymers (of different chemical composition for instance). These all determine the <b>polymer architecture</b>.
[[Polymer physics]]
Polymer chemistry
Example of polymer: https://en.wikipedia.org/wiki/Polystyrene
!!__Examples of polymers__
* [[Plastic]]s,
* [[Rubber]]s,
* [[Latex]],
* Many [[Adhesive]]s
* Many [[Lubcricants|https://en.wikipedia.org/wiki/Lubricant]]
* Many [[Viscosity Modifiers|http://link.springer.com/referenceworkentry/10.1007%2F978-3-642-22647-2_154]]
* Conductive polymer
* Biopolymers:
** [[Protein]]s: polymers of [[Aminoacid]]s.
** [[DNA]] and [[RNA]]: polymers of nucleotides.
** Polysaccarides
!!__[[Polymer architecture|https://en.wikipedia.org/wiki/Polymer_architecture]]__
Main architectures:
* Linear-chain polymer
* [[Branched|https://en.wikipedia.org/wiki/Branching_(polymer_chemistry)]] polymers. [[Plastic films|https://en.wikipedia.org/wiki/Plastic_film]] are somtimes branched polymers.
* Cross-linked ([[Polymer network]])
More specific examples of architectures:
[img width=600 [https://upload.wikimedia.org/wikipedia/commons/3/32/RAFT_Architecture.png]]
Interestingly, when one closes a linear-chain polymer into a loop, the viscosity drops dramatically.
------------------
!!!__Polymers according to synthesis reaction__
__[[Addtion polymers|http://www.bbc.co.uk/education/guides/zxm39j6/revision]]__ created by [[Addition reaction]]s
[[Alkene]]s can act as monomers because they are unsaturated:
*ethene can polymerise to form poly(ethene), also called polythene
*propene can polymerise to form poly(propene), also called polypropylene
*chloroethene can polymerise to form poly(chloroethene), also called PVC
__Condensation polymers__ created by [[Condensation reaction]]
An example of a condensation polymer is nylon, and some [[Protein]]s (the ones that are formed from repeating units)
!!![[Uses of polymers|http://www.bbc.co.uk/education/guides/zxm39j6/revision/4]]
An architecture of a [[Polymer]] material, where the polymer molecules are cross-linked in a [[Network]].
__Elasticity__
[[predictive theory of elasticity in a polymer network|http://phys.org/news/2016-09-theory-longstanding-polymer-problem.html]] -- [[video|https://www.youtube.com/watch?v=omEKWZLRvAo]]
These chains form networks in which each chain would ideally bind to only one other chain. However, in real-life materials, a significant fraction of these chains bind to themselves, forming defects—floppy loops that weaken the network.
These loops also make it impossible to accurately calculate the material's elasticity, because existing formulas for this calculation assume that the material has no defects.
The new method, __network disassembly spectrometry__ allowed them to measure the number of loops, and see its effect on [[Elasticity]]. They also developed a new theory, as previous models didn't predict what they measured. The theory is based on the [[Phantom network theory]] ([[vid|https://www.youtube.com/watch?v=omEKWZLRvAo#t=1m43s]])
''Polymer physics'' deals with the [[physical|Physics]] properties of [[Polymer]]s. A ''polymer'' is a molecule composed of a small molecular unit repeating in a chain; usually $$>100$$ units
!__''Polymer statics''__
!!--__Isolated polymer molecule in solution__
!!!__The ''ideal chain''__
<b>Model polymer chain like random walk</b>.
Can include effect of short-range interactions
A variant is the ''Gaussian chain''
!!!__Distribution of segments in the polymer chain__
!!!__''Non-ideal chains''__
!!--__Concentrated solutions and melts__
!!!__Thermodynamic properties__
''Flory-Huggins theory''
__Chemical potential and <b>osmotic pressure</b>__
__Phase separation__
!!--__Polymer gels__
!__''Polymer dynamics''__
!!__Molecular motion of polymers in dilute solution__
!!!__Rouse theory__
!!!__Zimm theory__
!!__Molecular motion in entangled polymer systems__
!![[Rheology]] of polymers
-------
//Books and resources//
http://cbp.tnw.utwente.nl/PolymeerDictaat/
[[Introduction to Polymer Physics - M. Doi|http://www.amazon.com/Introduction-Polymer-Physics-M-Doi/dp/0198517890]]
[[The Theory of Polymer Dynamics - M. Doi & S.F. Edwards|http://www.amazon.com/Polymer-Dynamics-International-Monographs-Physics/dp/0198520336]]
----------
//People//
S.F. Edwards
P.G. de Gennes
Doi
---------
Viscoelastic fluids
Reptation
cross-linking rubbers
PCR (Polymerase Chain Reaction) is a revolutionary method developed by Kary Mullis in the 1980s. PCR is based on using the ability of DNA polymerase to synthesize new strand of DNA complementary to the offered template strand. Because DNA polymerase can add a nucleotide only onto a preexisting 3'-OH group, it needs a primer to which it can add the first nucleotide. This requirement makes it possible to delineate a specific region of template sequence that the researcher wants to amplify. At the end of the PCR reaction, the specific sequence will be accumulated in billions of copies (amplicons).
This allows to use several methods that require large samples, on much smaller samples, even starting with a single molecule.
https://en.wikipedia.org/wiki/Polymerase_chain_reaction https://www.ncbi.nlm.nih.gov/probe/docs/techpcr/
!!__Cycle__
[img[https://www.ncbi.nlm.nih.gov/core/assets/probe/images/pcr_principle1.gif]]
* ''Denaturation step'': This step is the first regular cycling event and consists of heating the reaction to ''94–98 °C for 20–30 seconds''. It causes [[DNA melting]] of the DNA template by disrupting the hydrogen bonds between complementary bases, yielding single-stranded DNA molecules.
* ''Annealing step'': The reaction temperature is lowered to ''50–65 °C for 20–40 seconds'' allowing annealing of the primers to the single-stranded DNA template. ''This temperature must be low enough to allow for hybridization of the primer to the strand, but high enough for the hybridization to be specific'', i.e., the primer should only bind to a perfectly complementary part of the template. If the temperature is too low, the primer could bind imperfectly. If it is too high, the primer might not bind. Typically the annealing temperature is about 3–5 °C below the Tm of the primers used. Stable DNA–DNA hydrogen bonds are only formed when the primer sequence very closely matches the template sequence. The polymerase binds to the primer-template hybrid and begins DNA formation. It is very vital to determine the annealing temperature in PCR. This is because in PCR, efficiency and specificity are affected by the annealing temperature. An incorrect annealing temperature will cause an error in the test. I think that the double strands don't hybridize form, because the primer is much quicker to diffuse and hybridize with the single strands, and we only let them anneal for 20-40 seconds. Also, once the primer is bound, the probability of the other strand binding is much less (and depending on the strand lengths I think), and it could only partially bind..
* ''Extension/elongation step'': The temperature at this step depends on the [[DNA polymerase]] used; Taq polymerase has its optimum activity temperature at 75–80 °C,[1][2] and commonly a temperature of ''72 °C'' is used with this enzyme. At this step the DNA polymerase synthesizes a new DNA strand complementary to the DNA template strand by ''adding [[dNTP|https://en.wikipedia.org/wiki/Nucleoside_triphosphate]]s that are complementary to the template in 5' to 3' direction'', condensing the 5'-phosphate group of the dNTPs with the 3'-hydroxyl group at the end of the nascent (extending) DNA strand. The extension time depends both on the DNA polymerase used and on the length of the DNA fragment to amplify. As a rule-of-thumb, at its optimum temperature, the DNA polymerase polymerizes ''a thousand bases per minute''. Under optimum conditions, i.e., if there are no limitations due to limiting substrates or reagents, at each extension step, the amount of DNA target is doubled, leading to exponential (geometric) amplification of the specific DNA fragment.
!!!__Stages__
The PCR process can be divided into three stages:
Exponential amplification: At every cycle, the amount of product is doubled (assuming 100% reaction efficiency). The reaction is very sensitive: only minute quantities of DNA must be present.[17]
Leveling off stage: The reaction slows as the DNA polymerase loses activity and as consumption of reagents such as dNTPs and primers causes them to become limiting.
Plateau: No more product accumulates due to exhaustion of reagents and enzyme.
!!__Variants__
[[Reverse transcription PCR]]
[[Real-time PCR]]. Because PCR doesn't just follow a simple geometrical growth, because of dNTPs and primer depletion, it is impossible to accurately measure the initial concentration from the final concentration (end-point PCR). It can be estimated, but not accurately. For accurate measurements, we need to keep track of the growth in DNA concentration during the PCR process, to be able to extrapolate to the inital concentration accurately. This is what real-time or quantitative PCR achieves.
[[Real-time RT PCR]]
!!__Applications__
possible to extrapolate back to determine the starting quantity of the target sequence contained in the sample, with [[Real-time PCR]]
* Selective DNA isolation. PCR allows isolation of DNA fragments from genomic DNA by selective amplification of a specific region of DNA.
* Amplification and quantification of DNA. Because PCR amplifies the regions of DNA that it targets, PCR can be used to analyze extremely small amounts of sample. This is often critical for forensic analysis
* Disease diagnosis. PCR permits early diagnosis of malignant diseases such as leukemia and lymphomas, which is currently the highest-developed in cancer research and is already being used routinely. PCR assays can be performed directly on genomic DNA samples to detect translocation-specific malignant cells at a sensitivity that is at least 10,000 fold higher than that of other methods.
(See [[Arrival of the frequent]] for context)
If $$NL\mu \gg 1$$, the population naturally spreads over different genotypes, a regime called the //polymorphic limit//. See [[Polymorphic limit (Wright-Fisher model)]] tiddler for more.
To __model neutral exploration__, we __let__ $$1+s_p = \delta_{pq}$$, where $$ \delta_{pq}$$ is a [[Kronecker delta|https://en.wikipedia.org/wiki/Kronecker_delta]], so that only $$q$$ has some fitness, and all other phenotypes have $$0$$ fitness, and so, even if a mutation produces them, no offspring can inherit from them. At every generation, all offspring inherits from $$\mathcal{N}_q$$ only, and thus the population can only spread by mutations over a single generation jump, and it is most likely to stay mostly within $$\mathcal{N}_q$$, if $$N$$ is large enough.
<small>We should note that equations, like Eq.3 would be the same, even though we assumed that all the individuals are in $$\mathcal{N}_q$$, because, as $$1+s_p = \delta_{pq}$$, all the selection weight is in $$\mathcal{N}_q$$, which produces the same results. More precisely, in the expression $$\sum_{i=1}^N \tilde{\Phi_p}(g_i, s_i) \frac{N(1+s_i)}{\sum_{j=1}^N (1+s_j)}$$ only $$N'$$ (the number of individuals in $$\mathcal{N}_q$$) elements are non-$$0$$ in the sum and so in the mean-field approx (where we assume $$\tilde{\Phi_p}(g_i, s_i)$$ is constant) the $$N'$$ from the sum cancels the $$\sum_{j=1}^N (1+s_j) = \sum_{j=1}^N \delta_{pq} = N'$$ from the denominator, leaving a $$N$$ on the top.</small>
In the mean-field approximation the expected number of individuals with phenotype $$p$$ produced per generation is now independent of time, and given by Eq. 3. (we thus simply call $$m_p(t) = m_p$$), under the corresponding assumptions, because even if not all of the population are in $$\mathcal{N}_q$$, the assumption of fitness, we've made gives selective weight only to those in $$\mathcal{N}_q$$ (see [[Wright-Fisher model]]).
As we said above, the number of individuals with genotype $$p$$ (//p-type//) will follow a binomial distribution, with probability $$m_p/N$$ of success (getting p-type offspring), and number of trials $$N$$, and therefore the //probability to get at least one such individual// is:
$$P(\text{at least on p-type offpsring}) = 1 - P(\text{no p-type offspring}) = 1 - (1 - m_p/N)^N \approx 1 - e^{-m_p}$$
After $$T$$ generations, we have run the [[Bernoulli trial|https://en.wikipedia.org/wiki/Bernoulli_trial]] $$TN$$ times, and thus the number of p-type individuals we have gotten, summed over all the $$T$$ generation also follows a Binomial distribution, but with $$NT$$ samples, and same probability. Thus
$$P(\text{at least on p-type offpsring over T generations}) \approx 1 - e^{-m_p T}$$
Thus, the time when {{the probability of having discovered a p-type individual (produced a p-type offspring)} is $$\alpha$$} is found by:
$$\alpha = 1 - e^{-m_p T}$$
$$e^{-m_p T} = 1- \alpha$$
$$-m_p T = \ln{(1- \alpha)}$$
$$ T = \frac{-\ln{(1- \alpha)}}{N L\mu \Phi_{pq}}$$
Eq. 4
Where we used Eq. 3 in [[Arrival of the frequent]].
A cell that contains a more than two copies of each [[Chromosome]], so that its [[Genotype]] has more than two [[Allele]]s
Several [[Monosaccharide]]s joined together.
[img[http://djhurij4nde4r.cloudfront.net/images/images/000/002/378/fullsize/Starch-and-Cellulose.jpg?1386902066]]
[[Polyhedron]] that is bounded (i.e. it lies within a sphere of finite radius).
See [[Dynamical systems on networks]], [[Epidemics on networks]], [[Dynamical system]], [[Chemical kinetics]], [[Social dynamics]]
Often modelled by [[Continuous dynamical system]]
!!!__Logistic growth__
$$\frac{dx(t)}{dt}=bx(t)\left(1-\frac{x(t)}{K}\right)$$
$$K$$ is the ''carrying capacity'', which defines a stable [[Fixed point]].
[[khanacademy|https://www.khanacademy.org/science/biology/ecology/population-growth-and-regulation/a/exponential-logistic-growth]]
<img src="http://study.com/cimages/multimages/16/logistic_growth_graph.png" style="background: white;" />
!!!__Two species model__
$$\frac{dx_1}{dt}=bx_1-qx_2x_1$$, $$\frac{dx_2}{dt}=qx_2x_1-bx_1$$
!!!__Mutualism (or [[Symbiosis]])__
$$\frac{dx 1}{dt}= x 1 (r 1 -d_1x_1+ a 1 x 2 )$$
$$\frac{dx 2}{dt}= x 2 (r 2 -d_2x_2+ a 2 x 1 )$$
[ext[Mathematical population genetics|https://services.math.duke.edu/~rtd/CPSS2006/cornelllect.pdf]]
See [[Evolution]]
See [[Wright-Fisher model]], [[Arrival of the frequent]], [[Monomorphic limit (Wright-Fisher model)]], [[Polymorphic limit (Wright-Fisher model)]].
[[Second Bangalore School on Population Genetics and Evolution|https://www.youtube.com/playlist?list=PL04QVxpjcnji2WV8QIB63JfpzJP_1zecC]]
[[School and Discussion Meeting on Population Genetics and Evolution (video lectures)|https://www.youtube.com/playlist?list=PL04QVxpjcnjjkRBLuzcvdHhrDzWTYVdDm]]
//Some terms//: gene, genotype, allele, (gene) locus, haploid, diploid, homozygote, heterozygote, heterozygosity, monoecious, dioecious, polymorphism,link age, recombination.
https://en.wikipedia.org/wiki/Haplodiploidy
__Fixation time__
[[Intuition|https://www.youtube.com/watch?v=K9sb5ULCwMU]]
__Coalescent__
-------------------
SImple frequency calculation: [[video|https://www.youtube.com/watch?v=-1GVPjWBFqQ#t=7m50s]]
---------
[[Computational biology - An evolutionary approach|file:///home/guillefix/Dropbox/code/guillefix.me/pdf/Computational%20biology.pdf]]
https://en.wikipedia.org/wiki/Neutral_theory_of_molecular_evolution
[ext[Some mathematical models from population genetics course|http://www.stats.ox.ac.uk/~etheridg/orsay/]]
[ext[Mathematical Population Genetics lecture notes|https://services.math.duke.edu/~rtd/CPSS2006/cornelllect.pdf]]
[[Theoretical evolutionary genetics - Felsenstein (book)|http://evolution.genetics.washington.edu/pgbook/pgbook.html]], [[pdf|http://evolution.gs.washington.edu/pgbook/pgbook.pdf]]
[ext[Probability Models for DNA Sequence Evolution|https://services.math.duke.edu/~rtd/Gbook/PM4DNA_0317.pdf]]
[[Population Genetics V: Neutral Theory|http://evol.bio.lmu.de/_teaching/evogen/Evo10-Summary.pdf]]
[[Wright-Fisher model with some stuff on the coalescent|https://files.acrobat.com/a/preview/abfdf19d-7aee-42cd-92aa-183903f35527]]
[ext[Random Genetic Drift & Gene Fixation|http://jaguar.biologie.hu-berlin.de/~wolfram/pages/seminar_theoretische_biologie_2007/ausarbeitungen/zackay.pdf]]
[[Some mathematical models from population genetics book|http://link.springer.com/book/10.1007%2F978-3-642-16632-7]]
[ext[Moran model|https://math.la.asu.edu/~jtaylor/teaching/Spring2015/APM504/lectures/Moran.pdf]]
[[Genetic Drift and Effective Population Size|http://samples.jbpub.com/9780763757373/57373_CH04_FINAL.pdf]]
[[Heterozygosity and the Wright-Fisher model (stackexchange)|http://biology.stackexchange.com/questions/20955/heterozygosity-and-the-wright-fisher-model]]
[[Quantitative genomics (MIT) ppt|http://ocw.mit.edu/courses/health-sciences-and-technology/hst-508-quantitative-genomics-fall-2005/lecture-notes/hst2.pdf]]
[[STOCHASTIC MODELS FOR GENETIC EVOLUTION|http://websites.math.leidenuniv.nl/probability/lecturenotes/BioStoch.pdf]]
[ext[Diffusion Process Models in Mathematical Genetics|http://www.stats.ox.ac.uk/~etheridg/popgen/notes.pdf]]
[ext[Short course on statistical population genetics|http://www.stats.ox.ac.uk/~didelot/popgen/]]
[[ON THE PROBABILITY OF FIXATION OF MUTANT GENES IN A POPULATION’|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1210364/pdf/713.pdf]]
[[THE AVERAGE NUMBER OF GENERATIONS UNTIL FIXATION OF A MUTANT GENE IN A FINITE POPULATION'|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1212239/pdf/763.pdf]]
[[Notes on population genetics and evolution: “Cheat sheet” for review|http://ocw.mit.edu/courses/health-sciences-and-technology/hst-508-quantitative-genomics-fall-2005/lecture-notes/hst508lecture1.pdf]]
[[Intuitive explanation of fixation time|https://www.youtube.com/watch?v=K9sb5ULCwMU]]
See [[Probability theory]] and [[Stochastic processes]]
[[Sampling with and without replacement|https://www.ma.utexas.edu/users/parker/sampling/repl.htm]]
https://en.wikipedia.org/wiki/Porous_medium
A porous medium or a porous material is a material containing pores (voids). The skeletal portion of the material is often called the "matrix" or "frame"
[[Transport processes in fractals—I. Conductivity and permeability of a leibniz packing in the lubrication limit|http://www.sciencedirect.com/science/article/pii/0301932285900072]]
[[Material porosity and permeability|http://people.seas.harvard.edu/~chr/research/porosity/]]
[[Porous materials|http://www.uio.no/studier/emner/matnat/kjemi/KJM5100/h06/undervisningsmateriale/16KJM5100_2006_porous_e.pdf]]
A porous material most often refers to ''porous solids'', i.e. porous materials where the matrix is a solid.
!!__Porous solids__
If the porosity of a porous solid is high enough, it is also falls under the category of [[Foam]]s, and many of these are very flexible materials.
-----------
Solid-gas [[Dispersed media]] do form materials with pores, but they are different from porous solids in that the location of these pores can change as the material is strained or disturbed in some way.
!!!__[[Granular material]]__
!!!__[[Fibrous material]]__
[img[http://i.imgur.com/Myt9iKE.jpg]]
[[Matrix]] where all the eigenvalues are non-negative.
They all satisfy $$a^T X a \geq 0$$ for all $$a \in R^n$$
[img[power_laws.png]]
See also [[Scale-free networks]]
[[Scanned Notes on Power Laws|http://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3217/8/scanned-notes-power_laws.pdf]]
A //power law// distribution for $$k$$ has the form:
$$p_k=Ck^{-\alpha}$$
where $$\alpha$$ is the exponent,
__[[Normalization of power laws]]__
__[[Moments of power laws]]__
__[[Lorenz curves for power law distributions]]__
[[Zipf, Power-laws, and Pareto - a ranking tutorial|http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html]]
[[http://www.necsi.edu/guide/concepts/powerlaw.html]]
[[Similarity of Symbol Frequency Distributions with Heavy Tails|http://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.021009]]
--------
__Top-heavy distributions__
Power laws often mean that rare events are more likely that one could have thought, because the tail "dies off" more slowly than in, say exponential distributions, like Gaussians
[[More on power laws|http://tuvalu.santafe.edu/~aaronc/courses/7000/csci7000-001_2011_L2.pdf]]
[[Power Law Distributions, 1/f Noise, Long-Memory Time Series|http://bactra.org/notebooks/power-laws.html]]
!!!__[[Power-law distributions in empirical data]]__
[[Similarity of Symbol Frequency Distributions with Heavy Tails|https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.021009]]
The set of all [[Subset]]s of a [[Set]]
[[The Power Spectral Density (PSD) and the Autocorrelation|http://personal.egr.uri.edu/chelidz/courses/mce567/handouts/psdtheory.pdf]].
A [[periodogram|https://www.stat.tamu.edu/~jnewton/stat626/topics/topics/topic4.pdf]] is a sample estimator for the PSD. See [[here too|https://en.wikipedia.org/wiki/Spectral_density_estimation#Periodogram]]..
[[Power spectral density|https://en.wikipedia.org/wiki/Spectral_density#Power_spectral_density]]
[[power law PSD|https://www.physionet.org/tutorials/fmnc/node6.html]] [[more on power laws and 1/f noise|http://bactra.org/notebooks/power-laws.html]] ,,[[Fourier Transform--Exponential Function|http://mathworld.wolfram.com/FourierTransformExponentialFunction.html]],, [[Wiener–Khinchin theorem|https://en.wikipedia.org/wiki/Wiener%E2%80%93Khinchin_theorem]]
[[http://personal.egr.uri.edu/chelidz/courses/mce567/handouts/psdtheory.pdf]]
[[An Interesting Fourier Transform - 1/f Noise|https://www.dsprelated.com/showarticle/40.php]]
iVBORw0KGgoAAAANSUhEUgAAAooAAAD7CAIAAABi9yKWAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrsvXk8Vdv7B74dx0ymY54jJLPIGFIJRRFKmSlJ3Urj1axbmjQnRZzQ6JYpnVTSQK4G5ShDpmSOkDnD+f3x/L7rt3/ncHK7Tfd+zvsPr2Pvtddee61nPc9az/Nea7HRaDSMBRZYYIEFFlj4lUBgVQELLLDAAgsssMwzCyywwAILLLDAMs//GA8ePLh69SqrHv5HMDIycvjw4ZqaGlZVIJw/f/7Zs2df8eCzZ8+amppYFcjC+FFdXX348OGRkZEf/N6bN2/+alVB/ClvbW9vDwkJqa6uHhgYmDhxIicnJ4ZhDQ0Nnz59Wrdu3ZIlS36R2rlx40ZiYuLjx481NDTc3NxYPefvoqamxsXF5dSpU8bGxr9Ikerq6pycnI4fP25mZsZ418/Pr7Ky8uHDh5qamoqKij9xiBAVFSUnJ+fo6Phzq+v9+/f+/v61tbWBgYFTp04d/4M5OTlRUVG5ubkpKSmSkpL/bTn/8OHD7t27d+3aJSIi8v3ekpmZWVFRsXLlSnZ29v9kNb59+3bnzp0NDQ05OTlr1qz5Vtn6+voWFRVJSUk1NjYy3nVzc+vt7c3Pz//06ZODg8OvVSO0nwd9fX1oEvg3JSXFzc2NSCTeuHGD9sugoaHB1NTUysrqp7y9ubl569atHz9+pP07UVpaimGYoaHhr1Ok5ORk0HRjJQBPCYVC+YmF7OrqwjBMWlp6PImbmpoePHjwnUqyb9++rVu3NjQ05OXl/d1nQRs+ffqU9p9AZmbmp0+fRr21Y8cODMMiIyP/4SvS09N7enrGuqugoIBh2I/XBmfOnLl79+4Pe92tW7cwDBsaGvpWGUZGRlpYWBQVFe3evdvPzw/DMDU1td27d+/evXvz5s0hISE0Gi08PFxXV/dXE7mfaZ5zcnLw5plGo125cgXDsICAgF+ngqhUqqCg4NWrV3/K22fPni0rK1tfX/8v1WgDAwMVFRXv37//dYo0MjJSUVHBRAkePXr0p5vn4eHhioqK6urq8SS2sbHZu3fv9yhGXFyciopKW1vb1z3+XzLPRUVFgoKCDQ0No95ta2urqKhob2//J694/vz5hAkTWltbx0pQU1NTUVHxDe3WOGWAi4tr27Zt/17zHBYWdvr0abzRWbNmDfzb2tqKzLOQkFBGRsYvJXXEnzhxp1Aov76/5fPnz52dnadPn3Z1df3xb29paVm+fLm0tPS/1FvFycmprKz8SxWJjY2NeZH4+fl/eiEJBML4662lpeU7FePTp08jIyPf1WH7bwHogbHuioiI/PNaGhgY+PTpE5MEMHv+wejs7BwYGPhXt92ePXvorqDOxcvLu3DhQvitqKj4qzm3fyY1bFTOCIFAmDJlCvzOy8uLiIhYsmSJvr7+jBkzYELT19c3ffr07du3k0gkR0fH1NRUSLx8+XL40dvba2FhQSKRSCTSmzdvwB1EoVD09PQ8PDxIJNLhw4chGYVCiY6OPn78+MePH11dXSdPnvzkyZNRixocHIyCghQKxcrKCvIPDAzs6emBBDo6OiQSaebMmdHR0ZB46dKlFRUV8DsoKEhbW5tEIgEBoaCgIDIycsmSJUZGRtOmTXv37t2oFIlPnz69ffuWQqFQKJSGhgYKhbJjxw4YXfb19VEolJiYGBKJVFtbi2HYvXv3KBQKiUS6fft2bGwsiUQKDw/Pzc2lUCjTpk27e/fugQMHoNj79++HmqFDc3NzZmYmiUS6d+8eqqIzZ86QSCSYCd25cycjI2PlypWfP39eu3Yt5BYXFzcqkaqmpoZCoQQGBs6aNQvDsNbWVgqFsmvXrps3b9bV1U2fPp1EImlpaVVWVo5a5/39/RQKBT6ERCKFhoZ+/vyZMVlISEhwcLCjo6O7uztSoEgYMAzz8PDw8fHZvn17XFxcS0sLhULZtm3b3bt38UaIQqEcOXKERCLNnj2b0Tw/fvyYQqEsWLCARCKlpaUxym1nZ6enp+eVK1ecnZ37+/shwu3o6EihUBYtWgRpSkpKDh48SCKR7O3t79y5g5oYGtfT07OkpAQaqK6uDi7iR4Tt7e1QG1paWnPnzkXlr6qq6urqKi8vh0cyMzO3b98Ov6GJjx49GhMTQ6FQ/vrrr1HrubKykkKheHt7m5ubUyiUFy9e4O+CDFAolOrqaroQPoVCWbNmzYsXLyoqKk6fPk0ika5cuVJXV8eky2dnZ1MoFAkJiT179hQXF+NvdXR0UCgUqIHMzMzm5mZ8Ffn5+RkbG1MolMHBQbj+4sULCoViamrq4+OTm5v7xXEGhUI5evQoyAAIOWMvyMnJAUWhra1NoVCys7PRrVevXmEYdv/+fQqFUlhYiH/qyZMnFArF0dGxpqamra2NQqHs3r177969+F4QEBCQkpKCHsnKyrKzs5s+fbqKigoEgOiq6OXLl/iL3d3dFArl+PHjoaGhUAO3b9++cePG+vXr+/r6Vq5cSSKRgoODR21iUBQUCsXHx4dKpVIoFBkZGTExMQqF8uHDB7oqCggI0NHRSU1NxQu5uLi4np4eZBIZGbl582YKheLk5IQS4LvbwoULQa8WFBTAmINCoVy5csXIyMjIyIhCoSCOIbQgCPm1a9dIJBKoEahqhIKCgpCQkKSkJNQL5s6da21tPW/ePHwv/ltQUVGBHzw8PJaWlvhbp06dIpFItra2t2/fxl+vqKiIiooyMzOTlpbevHnz8PDw4ODg9u3b6bp5QkLCrFmznJ2dIyMj/92x59WrV9M5t62srNatWwe/MzIypkyZ8urVKxqNlp+fHxoaimHYiRMnaDRaWVmZqqqqvb09crvFx8crKSnl5uaikKexsTGZTIY4zeLFi728vO7duzcyMrJ8+XIODo74+PhPnz6RyWRpaWl9ff3Zs2djGObo6DiqxwnDMBR7Pnr0qLm5OZlMJpPJBw4cwDCstLQUbkFUIzk5GT07derUnTt3on99fHymTp367t07Go1mbW0NX1pYWLht27Zjx44xussgNo9QVFREJpPZ2NhSU1NpNFp3dzeZTP7jjz9AhdFotIsXL5LJZAzDrK2tjYyMMAzbvHlzamqqg4ODuLi4p6dnbGwsmUyGvrRy5UrGj3337t358+cxDLt16xaNRoMqkpKSwjAMHOyJiYmGhoYTJ0708/ODSpg/fz6GYQYGBoyevdevX0dERKDYc319PZlMZmdnt7S03LRpEzyuoKCgo6PT1NTEWJi6ujo7OztItnXrVgzDRvWyfvz4Eca8Xl5eAwMDNBotNzdXSUkpPj4eEqSmptrb20dGRpaWltbW1k6bNo0u9rxs2TJ3d3d40W+//YZcO3D3xo0bWlpaZDK5srKSTCZzcHAwRjo+fPhga2uLYZi/vz845crLy48fP25rawtEioqKivDwcHgFUHtiYmJoNFpxcfG+ffswDCORSOrq6oggAyM8fOx56dKlS5cuvXPnzsOHD1esWCEgIACuOT09PbyQUKlUYOGtXbv2yZMn4JUNDw93c3ODNqXDrl27dHV19+7dC2WztLREvWD//v2GhoYo50OHDuEffPv2LQyjU1NTdXR0IiIioBOZmJggYaZzbickJOjr68OL9PX1VVRUXr9+jTL08vJaunQp3GVjY0tJSaHRaHv27NHX19+9ezeSgT/++INGo+Xl5amoqJD/D3Z2dsxVzcuXL93c3ISFhadNm2Ztbb1ixYply5ZBDLK8vBzSXLp0SU9Pj0wmZ2dnw/BUVFQUQvuenp4TJkzAu/3wmWdkZEAviIyMbGhoIJPJRCKRm5ubrhcYGRnBlejoaCMjo8TExLKysqNHj4aGhgIlYs6cOXi+Ev4V7e3tZDJZVFQUxZ5XrFiBYZiqqmpgYCCZTIYJori4OGOQuKuri0wmy8jIYBhmbm7u4+NDJpPpekFKSoqDg4O7u3tPT09eXh4nJydovP379+P5gIsWLSKTyRYWFgYGBgkJCfAshUJRUlK6fv06/Lt9+3YYx+P/PXLkSGFhIZlMnjVrlpSU1MOHD5ETm4eHx9PTE3wPlZWVNBrt999/R87te/fuqampkclkUHqPHz/29PSsrKysrKwMCgqaMGHC10VUb968SXc9PDxcWFjY09Pz7NmzZDKZk5OTjY0tOjoa0TtAyIuLi69cuWJhYXH48GHoBRoaGhiGwb8AMTExpAf+xbHnmJgYUEbx8fEeHh4eHh6HDx8eHh4G1czGxubr64uPxnl4eJiYmNTV1dFotA0bNrCxsb18+ZJGo7W0tMD8LCQkZGRkhEajRUVFycvLw4ObN2+GCSXKx9bWNjg4GP6Fyq2urh4cHGS0kcg8I4187NgxVO9v377Fm+ehoSEuLi4wz319fd7e3jCWBDpJY2OjpaUlhDyzs7NVVVWfP38OD5aXlzMylUZGRgYHB3V0dHbt2jU4ODg4OAifRiAQQFJRaByZ5/+3RTFs1qxZg4ODjY2NSUlJNBpt06ZNGIadPHkScoAaGNU802g0GJvjVTmMglH8G3xBqMDDw8Oenp4YhqH+iUd9fb2GhgaeGsbBwWFlZYXqELRMRUXFqPE8pAJKS0tVVFTs7e3HitTKycmdOnUK/g0JCYFKaGlpodFor169YmNjq62thbswBUfl/+OPP7S1tUHqIKtDhw4hFVxRUcHGxrZixQr0rmvXrnFxcY1aBjExseXLl6NPmzdvHplMRqKCNEJeXp6MjIy/vz9q6N9//11ERCQjI2NwcPD48eNDQ0N9fX0GBgbIPIeFhRkbG6NCPn78WFpaesWKFSAkmpqae/bsQUICLRgWFobKZmFhAdaODuXl5bq6uklJSSAYYDmIROLatWtBno8cOaKkpAQ5o7cjNDQ0YBjm6ekJ7x0eHi4sLFRUVHR2dh7VPMfFxSFaE3hxs7OzaTRaZ2eni4vL6tWr0SuSkpJSUlIqKirU1dVDQ0OheCMjI0FBQbq6utXV1RcvXoQBCuD48eNfJBwMDw/LysoaGBh0dXUNDw8PDw8DnwvG9B8/fpw7d+6mTZtQ+uzsbElJSTs7uw8fPgwODsLEtLa2FvVEOjohPz8/ooatXbsWmWfUC8A8NzY2Tp8+HT4chPzChQsgP48ePQKf4uDg4KjKXUFBwdvbu7+/H9Lb29srKysXFxdDgRMTE3l5eVGQlQ7+/v7ga4FKBn81jD+6urrc3Nx0dHRQ/ScnJxMIhPz8/KGhocjISHFx8cLCQiQDUVFR7OzsSNF5eXlhGLZjxw549s6dO4aGhp8/f6bRaJWVlQYGBnFxcajGhoeHRUVFg4KChoeHYXkCNzd3fHz84ODgxYsXYZiOYs9ZWVkqKipUKhV9hZKS0smTJ1FWo2rs8Zjnffv2MZpnISGhlJQUKOqTJ09kZWW9vLzgrrGxcVhYGPoKPz8/NjY2qIH6+nqY4qOsFi9ezNhZvg4/07kdGxsLP7y9vZOSkpKSktatW0cgENC0ftWqVXinN4FAePLkCdjLVatW0Wg0cCQWFRUpKSlt3br15MmT8GBfX9/atWtRPiMjI729vV1dXV1dXT09PXQr6ry9vSUkJIhEIszmmRd11apVkFVqauq6devAGQK32NnZubm5wXPe2dn58ePH06dPJycng8fm6dOn2traXFxcMLuVkZFxdXV1cnK6cOGCpKSkjY0NY4iUSCSysbERCAQikQi/x1mxq1evJhKJkpKSHh4eqPa4uLggB6jJrKys8vLy8eTGuIrD2trawMAA5Qz1BpVPB0lJScalQatXr0Z54puYMZ7n5uYGrXb48GE2NraxlkISCAQ2NjZQW/39/UVFRUlJSXfu3CkrKwMnuaenJ4lEYvyc5ubmhISE0NBQJHUEAmFoaIjOvdTf39/1f/j8+fOoxSAQCKGhodHR0UC6vnv3bkNDA2gucKbZ2NhADr29vcPDw/iGJhAIkyZNcnBwIBKJq1atYmdn5+LiQs8ODw8PDAyMjIz09PRADtra2tra2iMjI6MKCTyOmiM5OZmTkxPvikS4fft2R0eHh4cHEq1ly5ZxcXGdOHECKgoqFnJGVUQnGCEhIagMurq61tbWBQUFMKSjg4+Pj4CAAHwCXlrq6+v//PPP1atXo1dYWloaGRndu3evubnZ1dW1u7u7q6uru7t7eHiYSqXm5+eD193JyenZs2ddXV1ge5gTDiBzAoEA34XkFnRITU1NRkYGkkY2NjZra2ttbe1bt25VVFQQiUT42LF6IlQU+he6OcLIyAiM3VEBlixZ4urq2tXVxcHBASs24Tp6xahLp7i4uMhkcm9vL+rFs2bNAh8GGxvbkiVLkJCPGjuHzKEeiERiUFAQSHJLS8vVq1dXrFiBBAyEPDY2FuoKXoeeDQoK4uDg6Ovrg2c/fvw4ZcqUS5cugaHq7+9fsWIFBwcHxALq6up8fHxQ5UBFnTlzZnh4GGRVWFjY29ubSCQuXrxYQkICFXjBggWBgYHJycmamproIgcHR3R0tJOTE4VC6enpQTHHbwJFRUUnJycoqrGxsYmJCVxPT08vLS0dGhoCOezq6hocHERzISKRyMnJCWofw7CYmJiBgQHGzvJ1+JnUsCVLlowV6x0V1tbWiYmJ8JuPj8/IyMjf37+4uPj333+PiIgAqb13756hoeG5c+dQTBoISrdu3YJBGYZhSkpK+DWvMJr+YlGRX8ve3t7e3t7LyysyMjI9PX3lypUo2fnz58Ei3rt3T1lZ2dnZOSYmxt/fv6CgYPv27SdPnkS9bu7cuWVlZdevX09LS/P29nZzc4uPj+fh4flOVT1x4kRTU1P8ldmzZ6uqqo7nWXD04SEvLy8uLk53ccaMGaOylrKysr5umWZPTw+YKBKJpKyszMnJOVaUGt4eGhrq5+e3cuVKT09Pe3t7KLm5ufmGDRu2bNkyat329vaWlpZ2dHTgLwoJCdEl6+7uXr9+Pfo3ICBg1DI4OjqeP3/e39//zz//rK2tBZcmqofFixeXlZWBH56bm/uLLCFYAAbumUOHDomLi+PLIC8vb25uPpYpio2NDQgIePTokYWFxdu3b4GLPk7MmDED9ZSvA0QZGa/n5uZevXr11atXampqaPAxKsATC7HGZcuWoUXzbGxskZGRixYtKigo8PT0jI+PT0tLgyhARkYGnZ9/VPj5+dFJQlJS0qii+7egoKCAz5aOREYkEvn5+UGHiIuLe3l5JSUlJScnQxPPnDnz4sWLYmJi41GYWVlZsEvE3wWjVNPFvMPCwvC0g6CgoKioKCS9ycnJ2traeCHx9/dfunTpypUrly5dqqenp6amlpaWtmLFiu3bt8PwDnWxJ0+eIFMHz45nl6fu7u6mpia6mrx58+bBgwdRu69Zs+bIkSNfURsokDQeVFVVdXR03Llzp729HUWsly1bpqSkBA0aERERERHx7NkzeXn5y5cvX7x48Vvp7Z9pnr+opMLDw69fv47+bWxs5OHhgadEREScnZ3Pnz9fV1enqKhobW3d1tZmY2Nz/vx5FRUVJyenSZMm4UXEzs4O4kOM4OTk/OJg58aNG56eng8fPvTy8rK1tU1ISBAREQHa16lTp44fP46+iJ2dffv27S9fvoyMjJSQkJg7d25qampdXZ2amhoaE8C4j5ube9myZd3d3StXrrx69eqpU6e+wjx//PhxPMlqa2ufP38OnnxETikvLx+PhWZspp6env7+frrro85gPn/+3Nraih8Ujx+hoaFZWVlPnjyB4TO4rMeCv79/fHx8Q0NDb2+vv7//8PDwmjVrzp8/v3btWnV1dXxUjxHnz5/HO07AZ0unXhHdjwkmT55sZmbW1NTU0dFx8uTJY8eO4Ys3efLkI0eOgI5bsGABfu5448YNRj4aossqKiouXbr0zZs3hw8fHierfObMmTo6OpcuXZo0adKlS5fwr6NDY2PjuXPnAgMDmXz+N0FJSYm7u7uGhsbly5clJSVhME0nyaOS1W1tbYHkQUftOXfunI+PD4ZhaWlpx48fB0rXF4tx/vx5b29vfEfDV87Hjx/RyAD4nllZWYgxxCRbCFWO1WWgF5w/f3758uX9/f2urq4ODg7AStu9e/fdu3ffv38/HvN848aN7u7ur9tOi65ZUegBQU5ObiwhFxcXR/RmJM93797NzMz88OGDu7t7b2+vt7f3+fPnh4eHoRfgJz/Xrl3Dm+cFCxaMxzwnJSUFBgYuWrQoMTERjZ9ERESio6O9vLyGhoaWLl167tw5OTk58GL+Ldy4cYPRHNTU1Ny8eZORvM3Hx8fBweHg4LB79+5Rc3N1dY2Ojs7IyHBwcFBXV2ccCf0rmdvANx4V/Pz8lpaWdOO70tJSR0dHYKDAIL29vV1OTk5XVxfiKP7+/m/evHF3dwe6DZ6UOOp+MUhDjUoJptMRQE1qbW2VlJTEL6KQl5dHv+3t7efMmRMeHi4mJgbkQDMzs3fv3snJyeEF9NKlS1u2bAFGlaWlJcTgx8KjR4/opncZGRnoNxPnMB7S0tJ4H9EXZ8/p6eno9+nTp+nuJicnP3z4EJ/Y2tqaj4+PMR8eHh5ZWVkmmTNBaWlpUFAQFLu+vp6OUcw439LV1Z0yZQpEXolEoqurq4CAgLu7OxO7LigoaG5u3tLSgqe80kndqFfGwpw5c7KyskJCQjZv3mxhYYHPQUVFBWxzaWkpsBZQyRnNJ4FAQPXGx8cnLy//4sWL+Pj4cRZDQkLC29u7sLDw2LFjoDKYTNPpWPelpaVfvbykpqaGSqXOnTuX8VZXV1d9ff2iRYvG2kGMUZJ1dHQYhQdgY2NTU1NjaWlpaWl5+PDhyZMno1sVFRWM5pzJ7BlP0KUrw+nTp/X19YEaiXeSMaK5uRmvQ+gWYvT19SFd9/DhQ19fXxERESh8QkLC+KvX1tYW1j1/RdMgrjLyQ6DBEPQCJs/C7Jnu4vDwcHx8fHh4OIZhvLy8ioqKjY2NV65c+SJjedWqVXZ2dl+cEYmLi//5559aWloLFiyAgDFqIDMzM0tLy/fv31tZWUFXys/Pj4uL+1s1Oapze1TJDwgI0NPTy8vLa2trGzU3WVlZAQGB3NzcrKwsd3f3r3NvjI6fQgr7/PkzlUqFOU1mZiaVSkXefITY2FhBQcHw8HCg8126dElTU7OqqgqfRltbW1xcHMhiKBgwefJkOnaSgYGBjIxMQUEBlUqlUqm+vr7nz58fGBigUqkTJ06UkpJ68ODBqKzg5uZmGOgZGhpSqdSPHz/OnDlTWFg4OjoamP0wrP7w4QN6xNnZWUhICL/FEhD3m5ub0ZVz586JiopSqdT29nYqlTpz5syIiAjGGqDRaCAuJ06csLW17erqotFocnJyBAJh7dq1Dx48sLGxAet1+/bttra2N2/eAFPs5MmTVCq1u7sbSElAKd+2bVtNTQ1ka2dnJyoqev36dUbK9ODgoIyMDDs7+4YNG+7duzdz5kyYc2dnZwOvB8bROjo6UJlRUVEuLi74r8PzmbOysiQkJDQ1NdHHEonEdevWUalU+ByYQ2RmZjLuxuDh4SEmJpaRkbFt2zY7OzsREREzMzMqlcpIzEEsM35+/vT0dHTFzMyMRCKVlZWhK52dnUVFRRiGRUVFwRYTZ86c4eLiAjYplUq1sbGBKMCZM2caGhr6+/t37NghKCgYEREB3xsXF+fk5MREtidOnMjIHVNRUZGWls7NzQXrJSAg4OzsXFJSQqPRHjx4IC4urqWlhe8FVVVVfn5+YmJiVCq1t7e3oaHB0NBQRkYmPz8fiuHn5wfcbxqNpqWlJSkpef/+fbwMgyNOUlJyrJ00oIHs7e3FxcVzcnJgLQCVSrWzs4OGrq6u3rx5s6ysLJVKhbg+Y+/AMMzc3Jz6fzA3Nz969CjixTx9+hTDsMuXLzc3NxcVFYmIiJiYmFCp1GvXrkHANTY2trGxsa+vLywsTFBQ8PDhwyirzs5OYNmADKDrGzZsoNFosrKyiAPV0tKiqal59uxZ+FdTU1NGRmbUPVIkJCRkZGQQlxO0bUJCQlNTU09Pz8aNG4WEhICaB4R/WVlZpFtgOdD9+/epVCoj8ae5uVleXh5Rw65du8bGxrZ69WoqlXrgwAFglmhqara2tsJoAHRaW1tbdna2qKgoMNjz8vIwDFu8eDGjkPf19VGpVBgo5Obmtre3FxcXW1paurm5oc+h0Wjy8vJbt25F3RxtDUSlUmECeufOHRCSoaEhOTm5CRMmUKnUnp6eqKgovJBTqVREh7xw4QIPD8/y5cvT0tIQ1bG9vd3GxsbR0RFto9bY2CgvLw+rH9GrW1tbYTkiMHOhks3MzKAM796927FjB4lEolKpiD/f0NCgpaWFYdirV686Ozs/fPjg6OgIMtDS0jJ58uTIyEhooOjoaENDQ9jyaN++fdzc3LGxsV/cJwesuKWlJVDqAJWVlSEhIdzc3BEREaj8rq6ujo6O0ElhBdecOXNQ/VhbW+fn56McwMsyderUb2so2Xfu3Pnj5819fX0XLlxQUFCwsbFpamoqKyszNDQENgGCnp6emJhYamrqoUOH2traurq6wsLC1NTU8Gk4ODhCQkLQOmnwMoWHh8MKBICAgMCcOXO4uLgyMzODgoLy8vJmzpwZHBzc1dWVmJior69vZGRUW1tLIpFA+vEoLCwsLCy0sbFRV1cvKyuzsrISFBRUVVXt7e11c3MLDg4WFBTs7+8XEhJCw3yYt+GpXrNnzxYVFbWwsECjKiBqLVmypKSkJD09fenSpSEhIaMOJ2fNmiUkJDQwMBAYGAhbQM+ePVtaWpqXl7e2tnbx4sUbNmwQFhZuaGgQFRW9c+fOmzdvbGxsBgYGYO2ZoKDgn3/+ycXFZWNjQyQS+/r6oK6IRKK6unpraysPDw/dztLANxEWFs7JyeHj41u6dOm6detERETq6urExcUlJSWBumxvbw+L3AwMDDZs2DDq1Lm4uPjx48fTpk3T0tIqKyuTkpJKS0uztrbm5eUtKytTVlYWEhJiY2MTEhJqampoEl/PAAAgAElEQVQSERHB+xXhSwkEwokTJ2BJg7GxMT8/f1lZmbm5+agsOXZ2dltbW2dnZ7xTOiAgAL8ypLa29saNGzY2Nn19fezs7CoqKlOnThUXF9fU1AwODq6urvb19T148CAXF1dfXx+RSFRTU7OyshIWFk5OTt6yZUtUVJSent5vv/3GxBUpKytLJBLpJsQcHBzv3r1LSkri5eU9efKkmpoaFxfXoUOHwEmoqampqal56NAhZ2dnXl5eDMOWLVumoaFhbGxcVlY2ZcoUoBDDqvGoqKjHjx/PnDkTeQWIRGJ9fX18fLytrS1+B5uioqIZM2bgK4QOvLy8Dg4ODx8+PHnyZHt7e1JSEoVC8fLyAt6fr6+vkpKSoaFhVFSUqakpI+2op6fn0KFD06ZNCwkJiYqKevfunZ+fX2BgILTOs2fPfHx81qxZU15eXlxc7Obmpqend+zYsePHj7u6um7YsCErK0tQUPDx48f29vYzZszo7Ozcvn17VFRUVFTUo0ePHBwcREVFZ82aRSAQtm7devDgwaioqLq6OltbW01NTSkpqaCgoL6+vnv37j1//nzWrFnIP79ly5Zjx46Bisd7yJydnZ2cnCwsLJKSktD++by8vNXV1S9evLC1tZ01axYvL29CQkJFRUVOTk5TU9OMGTOQr46NjU1ERCQ4OPjdu3cLFy6ko1M8f/48MTFx+vTp4CRjY2MTExPbv39/QkKCqanpb7/9JisrKyQk1NDQYGJi8ujRIzKZ3NDQcPr06Zqaml27dsEyJzY2NhKJdPbs2YaGhoULF+KFvL29/dKlS0ZGRuA2gK6krKwsKSkZGRkJ428Qs5GREdTNkd8iMTFx4sSJNjY29fX1SNH19/ebm5uDopgxYwZeyHNycqZPnw5Tah0dHRkZmZycnN7eXisrK1B03NzcN2/e9PX1RfXMz8/f1tYmISGB92yDgBEIhMOHD9fV1T1+/FhAQGD27NlATQgICJCVlTUxMSkrKztx4gQsdcnLyxMVFbWxsSkvL5eXl5eTk3NwcHj8+HF7e7uUlBSNRtuxY0dXV9eDBw+SkpKuXLkCAWACgaCgoDB16lQ5OTkmdqegoKCkpMTGxkZZWbm8vBz5t4CoZGlpmZmZaW9vLyAggP0f1bempsbExERISEhQUJBIJPr5+UVFRTU1Nfn5+SHZgND+s2fPnJycRt3J/6vBBjPOXxbt7e3ADpCTk/uHG8H39va2tLTw8fGNJ8zzvTE0NAQbOAgJCX3DWMW3wvDwcEdHB36Ugw+08PHxxcbGdnZ2/oD9pD58+PBj2uv9+/dCQkLQM0eN8cNaIHl5eeZ+OdimhnG88vHjx8+fP+Ndu3Sf1tbWJiQkBEI+6lfDIBUyp7vb3t7e39+PH18ODQ1t2rRpwYIFzP2WGIZ1dHSg6ImoqCiqAVSGjo4OCL8x+jwlJCQeP34M4yoRERH84uCurq6Ojg45ObnBwcGenh4Q8tra2pGREQUFBVjLJCQk9OnTJ5CigYEBFIGi+8CGhgZwHaNXdHd3t7a2It+ssLAw/N66dWt+fn5KSgpdkP7z588NDQ0wcqKr28HBwe7ubpRDa2trd3c32BvGEclYQnLkyJGNGzceOHAALRgZGRmpra1lZ2dHBmNgYGBgYAC27YRXQBiCztleW1srIiIy/q3rvmEHQULOy8tLx/1klAHG96IPHDXy/fnzZ3BTjZoD86/o7Ozk4eHh5OTs7+9H+6V8D03+8ePHCRMmEInEsSJBIKL4bgKoqqpycnK6efMmPtb53zfPLPxqAPM8/jgoCz8FHR0djo6OV65cYfQJfSuAef7rr79G5Wn/eFRUVMyfP3/nzp10PKYfgJ07d8bFxaWmpgIPhoX/NZSXl1+8ePGbu6JZ5z2zwMJ/EMHBwe7u7t/PNv+CGBgY2LFjh4uLy095u7i4OMs2/28CgmL4tULfCkRW5bLwd/Hw4cOioiL8OkgWfhEUFhbCrmempqbMycb/PUyZMgUfc/1haGpqun79OnJrs/C/gwcPHpw9e7a0tNTT0xPtjcGaPbPwc+Dj48PBwWFsbLx///4LFy6wKuQXBGKtf2/FtHbt2sWLFx87doxx1c3/Dm7duhUaGrp9+3ZYhM3C/2B3W7NmDdqr/9uCFXtmgQUWWGCBhV8OrNkzCyywwAILLLDMMwsssMACCyywwDLPLLDAAgsssMAyz/8UTDbiZuE/gI6ODrpTaFhggQUWWGDEr0UN27Jly61bt16+fPnD3tjQ0IBOFtq9ezfdQa3fD2fPnq2srBQTE8OfEvi/AGdnZyKROJ4ja/6r+P3334eHhw0NDX/87hlfjUOHDn348AF+h4eHf8tN/78DLl26hHTIihUr6Lat/fE4ceJEXV3dhg0bmJzH/D0QFxdXWloqLCy8efPm7/SKmJgYdL7L+vXrv/k2Xvn5+Tdu3IDftra2//zoz38ZaL8G2traFi9ebG5uPmvWrB/53oGBgdraWjjxEG3vzojc3FxZWVl/f/9v9d6ysjIlJSU1NbXv+nUnTpyQlZU9efLkr9DEHz9+9PDwuHjx4syZM//Wg1VVVXp6enFxcbT/BKytreF0ta94Njs7W1ZWNjg4+AeXGfa6f/bsWW1t7fDw8PDw8O7du2X/D6tXr37x4gXjUw8ePJCVlX358iXzzHt6eh48eKCvr48ypFKpcKu/v3/Dhg2yOODPIQDU1tYmJiaam5vv3LkTncRQW1trbW0tJSVVVFT0c5v75s2bsBH327dvf+R7Hz9+fO3aNQzDYAvV7wQ40iY9Pb22thYdJlFaWnrw4EFZWdnQ0FB8Yn9/f9n/P+CAExqNlpaWhr++Z88eOBSkq6urtrZ2y5YtvLy8Fy5coP2P4VfZliQoKIiXlzcnJ+cfbqz9d8HJySknJ7ds2TI4GW0sKCgoKCgoODo6fvWL3rx5c/z4cT09veXLl2MYpqqqunLlynPnzn3XrzM1NZWSkoIjmH46VqxYwcXF5ebmtnjx4r/14IcPH2pra9E2xRiGnTp1SkhI6HvsA/ADkJ2dzeQAZjrcvn07Pz9/x44d8K+ysrK0tPQ4D/n+tnBxcVFXV4e9xKOiom7duhUWFoZhWERExPHjx/Py8uB8KoTc3NzFixc3NDTAEZ9M8O7dO0tLy927d4uJib1+/frkyZPh4eFXrlyBpj948GBYWJisrGxVVdXBgwd37dqVmZmJnv348ePChQtnz5597NgxfX19uCgqKioqKsrDwyMsLPwVZ6j/c4SEhLCxsZ04cQLDMHt7e2VlZSZnen4nmJmZwall3xUpKSkYhklISKCtxTds2JCWlrZq1SoSiURXAAKBYGJigp8Bo5NAo6KiQJwwDAsNDd26devmzZvZ2dn5+fn5+fmFhIS4uLh+sO+BNXv+/yAqKhofH/+z3g5nlDKZPcOZbmMdZTgewIljLi4u6MqhQ4e+9+yZRqP19vb+Ik0sJiZ2/vz5r3u2q6trYGAAftfV1RkaGi5fvvzfOyieP3/+eGbPbW1turq6GhoadA3649tUTU1NT08PDpqEs/aOHj0Kv7u7u7ds2QJni6H0Q0NDBw4cmDVrFoZhT58+ZZ75rFmzyGQynNI4ODi4aNEieXl5eMrR0fHMmTNwgODQ0FBAQICdnR16sLq62szMLDo6GhLQwd7e3sbGpqWl5ce3LxcXl4mJCfoXzgv/wbNn8D14e3t/19kzHBZeUFCA76qdnZ35+fmysrJ+fn74xAsXLkRig8fRo0enTJmC/r1+/Tpdnvv375eRkUE+FdbseXSAfUJDIXTk2fDwMFwZGRlBt2g0GvyLYRgbG9sXz99Gxg9S4t+Ffx3KFs2z4e3oFehBdnZ2uDVqAfD59/X1MS/b8PAwBwcHjUaDMsCzBAIBHTJNVyFjAbkl8YVBhWTMZKwKZxxjoaqmq39OTs6RkRF4Hf5FjG9k3rjjbMexEqPM4S+TimIUm5GRER4eHvTI0NAQ/kR6fLEhPT6HUZ0xkICNjY2NjW0sEaWrUsZvwbc+3bOoF+DTM6+6UWVAWFjY3d09ISEBn5KRHsGkgaAk+M/Et+xYXWysdsH7nNA2SXx8fFxcXCMjI/hZcmRkJJwSe+fOnS9qlV27doH7F8MwIpEI29LBMaCbN29Gt9jZ2fEx797e3oULF3748GHZsmXfcK4yluSgSh61hyJVg+6OOmtHFT6qMNDJAOom6BV00juqDhmPmKE0Y6noUfXJqBkySiOctWVkZIQ/yJUuMep9KKiM37Aaqm5gYOAftiO+g6OvY96O49HDjBVFp0nGYwjGib/B3L506dLGjRt9fHzk5OSIRGJBQQGGYW1tbQkJCSIiIubm5leuXCESiUQi8d69e2/evDl06JC+vr6Pj4+Pj4+hoWFFRcWo2ba2tiYkJAwMDPj5+ZHJZEtLS+h7Hh4ejo6OPj4+Dg4ORCLxzJkzVVVVGIZRKBQikYineygrKxOJxHnz5mEYVl1dra+vTyQSJSQkEhISFBUVoUh+fn5wJh00fEJCgoGBgY+Pj5OTE5FIRH6VsQCfDLvtV1ZWamtrE4nEXbt2LVy4kPh/CAwMxJsNPJ4+fQoHem/atOn8+fNIoXR2diYkJEhJSaFMcnJykPZJSEjQ1dWFCtTQ0EhPTx+rePv37zc1NYWUlpaWN2/exDDs4sWLRCKRRCLBvxiGaWpq+vwfTExMiESirq5ufX09hmHNzc02NjZLly718fGZPn36tm3b4JGioiIdHR14RE1Njcl5A42NjQkJCaqqqpBYVlbW3t4eTrxvbW21s7NrbW3Ny8tbvXo1EzZcbm5uSEiIjY2NmZkZkUjctGlTR0fH/PnziUTi6dOnIc2jR49oNFp5eXlCQkJCQsLKlSt1dHSIRKKpqSl4QZ48eSIvL6+hoREaGsr4ikePHq1YsYJIJK5evToxMRHV/JQpU8rLy1Gy1NTUKVOmwLeIiIgsWbKkt7cXatXY2JhIJKanp3t5ecGzysrKEITDMCwpKWnatGkBAQHw782bN11cXIhE4vHjx0f9ZJABLS2tKVOmQG5Ig1y9enXLli0dHR0JOJibm+O9+sXFxXgh0dfXr66uBhd6QkKCurp6WFjY6dOn0WfeunUL9QLoXD4+Po6OjkQisaGhgZmmwCmdxMREursiIiLIUfnu3bvU1NSYmJhxBqqQAcYwrL6+vqqqCu1Iir/V0tJSVlaGbg0NDcEpy0xyfv/+/fgdvM+fPw8LCzMzM/Px8Zk0aVJCQgJUyKdPnxISEuAwSjhBHLp5RUVFQkKCl5eXurr6q1evZGRkiERiS0tLXl7e8PCwpqZmQkICRH+RorOzs4NMjI2N8UtUkAz4+PjMnj2bSCQGBwenp6eDkHt4eKD97f/6668NGzYQiUQkAz09PaAooBfgFV1vby+ZTEZvefHihZiYmJmZ2dGjR+FKeno6EnJdXd3Xr18jB7W1tbWPj8/ixYuRqh8VZ86cGUvjPX/+nO4iOzv706dPExISLC0tyWTypUuX4Lq6urq9vT1K9vjxY1NTU7qQXHd3N+j/L+Kvv/4KDQ0lEoleXl4ZGRlQ4fPnz+/o6Hj+/LmYmBhcWbVqFXqkq6vLzc1twYIFPj4+0Ebg7ASUlJQgQ6alpaWlpQW27MGDB8uWLSMSiaGhoXFxcaiLIS7bD3VuOzo6NjQ00Gi0goKC5cuXL1iwgEajdXR0ZGZmCgkJaWpqbty4MS0tbf78+S0tLXv27FFVVS0vL4dnFRUVNTU1kX8Sj/b29szMTAEBgXXr1mVmZt6+fZtGo61atcrFxaWzsxMoRe7u7mxsbKdPnx4ZGXn27FlISIisrCzK4f79+w4ODvb29jQarb6+HnYAJhAI3t7emZmZmZmZYMvr6+sh/aZNmxwcHO7fv0+j0To7OzMzM+GQTibO7RMnTnBxcc2fP59Go71//x4ES0VFJfP/AKeUj+V1fPPmzR9//AHjxMzMTKCrHDp0iEAgBAYGQg4RERGcnJyurq7wyKpVq7i5uREbYuXKlSQS6e7du6Pmr6CgcOrUKfidlJSUnp5Oo9GePHni4+MjKCiYmpoKtzw8PODH8PBwREQEgUAIDw8Hbo6tre2qVasGBwdpNNqlS5d4eXlPnz5dX1+voqJy6dIleKqoqMjd3X2sKkpJSeHl5UXMnaysLB4enoULF6ImFhQUXLt2LWpiRuTk5EyaNCkjI6Opqam2ttbY2Hj9+vWfPn3KzMwUFxdHvtNt27ZxcHDY2dlBvXV2du7atYtAIKAaoNFoDg4OdLQUhMLCwszMTAMDg0mTJhkZGaEWFBERmTJlSm9v78jISEpKipaW1uvXr+ERMpnMzc3922+/0Wi027dvwwnKqACZmZmqqqpqamq1tbU0Go1CoZiamvr6+iJSYWZmppSU1JEjR0Z1br9588bT0zMvL+/169cgA3v27IFbt27d4uHhkZeXz8TB2tp60aJFiDSnqqqKhKS4uFhcXFxbW7urq+vp06fr1q0jEokaGhoXL16EZ+3s7GbPnt3f30+j0TZu3Dh37lzwV3d2drq4uNTV1Y3TuY3H0NDQxo0bLS0t0RUzMzOQqzVr1ozHuY30QFtbm6WlZVBQEHR8hI6Ojra2trlz53p7e7e1tcHF33//HcOw+Pj4+fPnOzg4zJkzZ/Xq1X19fXjn9qRJk0pLS8fz9rdv3yoqKoLVpNFoEEdPTk6GW4sXL4YK3LdvH4ZhO3bsAD1w+fJlXl5efn5+Q0PDsLAwYWHhe/fuaWlpgedj48aNx44dQ85tV1dX1Ijs7OzGxsYoWuHt7R0YGJiXl0ej0VpaWiA6m5qa+u7du8zMTD8/PxTgKC4uTk1NNTU1RTLw7t07V1fXR48eASELwzDUjnjn9qtXrzQ0NBITE9+9ewdzvpSUFEVFRSTkU6dOVVNT+/DhQ3d394QJE27cuAHM2eXLlzPS8RCam5vpHNGIcuvg4EDn3F6wYAEvL+/06dOdnJz4+PgIBAK+U/T09OTn58+ZM0dfX7+oqAgfSdy/f7+goGBKSsp4mrK4uBgOdlRUVDx37lxmZmZcXByGYZaWlgYGBomJiZmZmSQSCXm/aDTasmXLFi1a1NXVBbxCZ2dnCQmJmzdvgliqq6tHR0dDypKSEllZWU1NzdbW1hcvXmRmZurq6qqpqSUkJEDLzp8/X1RUdCwV93fxNbHn3t5eZ2fnoKAgdAWYz8g4wYnZ+DaDwQjohS/GnouLi1VUVNavX49PAOelQ5DpzJkzePNMo9GCg4PBPENnxjBMXl4e3X348CGGYdBVSkpKNDQ06Liv0NWZmOf379+bmJiAeYYuBKR/lAAmx0yCgow1wBh79vLyQubZ0tISXwNXrlzh4uIai7uooKDg6uoKmT99+hQFafbu3aulpYWSIfLz5cuXMQwLDAyEfzds2CAtLf348WOUEqw1DBLx4SIm9GkJCYmYmBi6iL6YmNhff/01ztgzHf+gvb39+vXraHiHzHNZWdmUKVPoYs/y8vKoBkpLS01NTZm8qKSkZPLkyStXrsRf9Pb2hnE0OGkpFAr+bmho6KRJk4qLiyGEBqQtdBe0uY2NDfzr7OyMzDNARUVlLPPc2Nh469YtdMvT09PNzQ2F8RwdHeliz0uWLEGq2cLCQl9fH29WMzIyMAyDcVhRUZGSktLmzZvRXaAlwnhrzpw5FhYWMOCGgF97ezsT8zx//vzu7m7GWydPnjQ0NGxqakIdAZUfzMw4zfOOHTtCQkJCQkJgKFBZWYlu7du3D25pampqaGiUlJTQaLS5c+diGObs7JySkrJ3717gheGHaPb29itWrBinTnvx4gXesMEEVFRUFDp7RkYGiiJPnjwZZiZgUZydnVVUVBhjz3/++Sdd7DksLAxfNl5eXvh98OBBdXV1/OOenp5gnpFxwstAcXGxqqoqkoG2tjZkt0DROTg4oLUSGIYFBAQ8ffpUU1MzKysLP6jCMAy1FL4GAgICtLS00Mzq/v371dXVY9UbRF4YzfO1a9fY2dkTExPxF3fu3AmTIhqN9vz5cyUlJRMTk/fv3yPyNrQy+EEzMzPx5llSUnKcgkSj0cDRuGTJEsTkNzY21tbWRglSU1OReX758qWioiK+dWg0Gi8vL5FIpNFo4J5hVPUgA69fv1ZVVV2zZg26m5yczM3N/dUkm6+PPVdXVw8NDe3cuXNwcDAnJ8fQ0BB/d8uWLSgyBETTbdu2iYqKwpWOjg4lJaVxvigvL6+1tZWO3ysmJva3iIiMK/DA6QeLQ+jcnnx8fKKiokwCBhwcHN9kSfSpU6fWrVs3Hj5kYWFhS0tLTU1NT08PDE3k5eUhrjPqx167dq2mpoadnd3U1BTvt6mtrU1LSwPOuY+PDwjcmjVrli1bBicPIvdORETEhAkTWlpaxMXFW1paTExMZGRkNmzYsHPnTjDnAQEBoBMZ0dbWNqpj/8OHD7du3TIyMvriJ7e2ttKFxoWEhEZlOHNycjKuu925c6efn9/Zs2e5uLgyMzNdXV2ZvEtUVHTChAl0F318fPCeQEa8ffv2yZMncGQhPz8/Priorq7u7u7e2tr6FSIhKSlpZGSUlZW1Y8cOBQWFv/76C1VXd3f3o0eP8Gc29/b2dnd34189a9YsGRkZfNwOyNUQ6uPg4KD7cCTkO3fuNDY2njVrloCAwIEDB3R0dMaSLoCsrCxdbhiGXb58+cqVK3/++ScM0Pv6+s6cOePp6Ql+SF9f3+zs7Pr6ehERETk5OcbH6VoQ1bO6urqzszNau4yW7VZVVeno6MybN6+srAzDsPnz58fFxU2YMMHJycnDw2PatGmHDh3y8vJCH3L37t2ysjJYFcYcoLI2bdokLy8PXnolJSUhISGQw8mTJ9+7d+/IkSOCgoLIdQzNkZOTIyIiMp6Gxh9p5ePjA2GsoaEhCADRLWNh4rRXUlJCcQQMwyZMmKClpfXgwYMDBw4QCAQBAQG69E+ePLl9+zYvLy+dxobQlYmJSXBw8MWLFzs7O5WUlNjZ2Tdv3mxtbe3g4CAqKsrPzx8dHS0pKcmkMKNeNzIyMjAwAOIYXSUD9PX1bWxsYNk0uB7nzZsHhrm9vd3Dw8PT0/PGjRsWFhZIsJkUgzlERUXnzZsHawEY8fDhw56eHjqNISYmBlE/Mplsa2urrKyMbnFzcyMBI5FIdJrEysqKl5f3W/m2xxt7zsjIUFNT+/3335OSkq5evbp9+3a6WHJJSQmKjWtqamIYFh4envR/uHnzZlVV1fgtXEdHB4pMAFC8ZJyAGDYeUCroEtC9EU6fPm1mZsZEffT09MCk/B9inEfwtrS0fPr0ycHB4dSpUxs3boQ6LC8vH2tBTnJyclhY2OzZs7u6uiIjI3V0dNAteXl5/HowmKOPjIxER0fje7KwsPD27duTkpKWLVuWlJT04sWLHTt2cHNzHzhwYOfOnTY2NsXFxQEBAdbW1ijIShfv6e/vZ/JFWVlZPT09TBLs3r17nDX86dOnrq4uuotALYGoT2xsrJ2dHZMcmpqamKxNGk/oSEVFBW8UP3369P79+/nz53+FSMTExDg7O6emptrY2MTGxiJ9hGEYo0qtq6urrKxkTpKYOHEiMk74aDostkFCrqWlFRYWZmVllZ+fP336dGVl5bHiiICKigo6tk5PT8+FCxcOHTqEFtXk5uYmJyc7OTkpKysrKyvDLHD+/PnKysp0mpoJJk2axMbGNipVZeLEiUQiEd2SkJBAylFBQYGLi6u6uho/yJs5c+Z4bDN8HehxAoFQVlb29u3bqqoqmFAeO3ZMWVk5OTl58+bNSUlJVlZW+MHQtGnT/olC6O3tpVuQBgFd2ti7Rb1//x4vA6dOnVJWVk5KStq4cWN6ejrjasO6ujplZeWysjJ3d3e6Dft0dXVtbGzKyspCQ0PXrl1bVVUlKSmprKxMoVDc3NzExMTu3r2rrKyMRk6MKC4uHvV6QUFBQUEB82gxo4pGukhMTKytrQ0/H+vp6Rm/CKmoqPytk78HBwfRrjuM5ub27dv4CjczM3Nzc4PfDQ0NdJrki5rwu5jn1NRUCwuL2NjYsRKQSCQ0MIeRyPhrk3GwwziQ37Bhg4KCwqjpu7u76SoXLBajxMCP/v5+8AHikZaWhh8X06Gvr4/RJHzd7Hk8yVxdXadOndrc3MzPz49XB6OioaFhYGBgz549e/bsuX379oEDB/B3YfaMGCgBAQHCwsJIETc1NQFrvbW1FbwL+FHkwMBAQ0PDb7/9tmfPnufPn69Zs6a0tBTxR/Cwt7fn5+evra3FEz5hAgdjXm1tbeaDs99//11QUBACY8y/t7u7G1haeOjr6y9atCg5ObmmpkZHR4e5UpaXl4fZHh41NTVycnIEAgEmr4zSa2RkhJhxL1++xNuPhoaGvLy8sabsjY2NTGiop0+f1tbWPnLkyJ49e9DEFwkqnfpTVVXFj73AuuPHmuXl5VQqFXrKzJkzVVVV8YkLCwuRkwMIIpGRka9fv4boPvNjm7W0tLi5ufH+El9fXx0dHQi1IibXaxzAdF29evX169djdd7m5uZRB3wKCgqtra2jav+IiIixHF1bt27Fqw6YPY+nx0HxNm7cCP1o9+7deE0SFBR09OhRc3Pz169fI/ImdJCioqJ/0tMnTJgwZ86c/v7+xsZG/OyZiScPmBn44vn7+x8/ftzS0vLZs2fg6KLzQl27ds3GxiYrKwsck+jW9OnT4XtnzpyJpLe2tpabm3vPnj0XLlx4/fr15s2bmQjGWI4xIyMjQ0ND4PSM1QuSk5NdXFz09PQKCwsZe/ScOXOsra3x/ktwZowHTU1N79+/H79a7unpoVNrGzZswAsGnTfizz//hN+Kiori4uL4u9ra2t9wT72/wdwWEBCAserZs2dTU1MZCah0inXZsmV4/tv44ezsbGBgkJOTA+4FpAHDw8MRF7SjowMRkjdu3IhnSAIY974AO6evr6+mppaXl/ThrCAAACAASURBVAfWCBwDX9wFesqUKXhZ+WqMU8KEhYX5+PgSEhLGo1wqKyuRw1xGRgY/q6ObPS9fvjwuLi4hIcHd3R2uxMbGVlVVATc+JiYG9Z+enp6UlJS6urqoqChkGI4cOTJ16lREIh11BoyGOF1dXWlpaVu2bIF4p6SkJJFIZO7jJRKJO3bsuHDhAvPvNTU1RRtQ4CeawsLCJSUldnZ2X9z2pKKioq6ujs45dOTIkfT0dF5eXqhARjI/Hx8fRBkYkZSUNHfuXLxhePr0KcxcW1paXFxcmCuLFy9efPr0CcOw0tJSPN+Vi4tLRUUFn7K0tBSmdAAPD4+2tjZG2793715oRLoRp7q6OupB8IGcnJwaGhp2dnZeXl7MK62goACtPxwaGlqyZIm0tPS+ffvwnnY+Pj4NHAIDA8H/qaGhATprx44d69evx8dBamtrV69ejX/RpUuXtLS0UlNT6+vrg4OD8beuX7+uoKAwb948NjY2Dw+PJ0+e0M3PpKSk8HRxXl5epCtv3ry5fv36J0+ejPp1UGNJSUl01x89evTu3TsxMTEYXCYnJ+O/l4ODA78i6Ct6OhoaxsTEMJk9Nzc3Q8gT1C9IC4ZhoMdIJBKMnPr6+kZ1QZFIpIsXL1pZWdnb23t4ePT397OxsS1atGjt2rWMvqLw8HDQJ0JCQhoaGsxdyvjBCp20vHjxAu+Ej4qKousFnJycgYGBRCJx27ZtEJ5HQv78+fMVK1bg3XtDQ0NoY6KSkpL169czNhZ+BI+q6IswMzOTkpK6dOkS0NyQufHw8BhVMHp7ezs7O+Hu27dv6dY7vH379ov78PwNjDNGffDgwalTp0pLS3t4eNy/fz82NlZNTa2qqqqzs7O2tlZNTU1dXZ1CoTQ3NwPvICYmxsjIiJ+fPykpKTs729jY2MPDA+36hseTJ0+ys7MnTJiwadMmxGkqLy+fOHGijo5OdnZ2dna2t7d3SEhIT08PIhEICgry8fFJSUmZmZmtWLHC29t72rRp2dnZjY2NwAtQVVXNzs4GMh4wJuzs7LKzs4HrOGnSJFFRUSkpqUmTJiUmJsLwEDjDo7I6T548ycvLa2ZmBuWBhfMaGhrZ2dlQKug88+bNgxpgxNOnTyUlJbm5uWVkZM6ePfvixYugoCB2dvZVq1Y9e/YMUcO4ubkPHz6MaoBEIklJSV25csXLywsReumwd+9eVFHZ2dlqamrAOXz+/HlAQACRSFyzZs3z5883btwIQ3KUcvr06QICAojuJCUlJSkpuXfv3l27dsE2TBUVFfz8/AkJCZB+586d27ZtG0tC7t69KykpOW/ePEiclpZmZWUFvNknT574+voSCISNGzcy2Vvg9u3bVlZWPDw8Bw8ezM7OnjNnTlJSUkFBAaootD3k3LlzeXl5FRUVL168iKeSCQgITJ48+Yu7x/T09ECISEpKKigoKC4uTltbG3FhRkZGLl++LCoq6uPjA99y/vx5bW1ttK0EUMNERER8fX0vXrxoYmISGBgIkgYAyyciIiIlJaWgoHDixAlFRcXg4ODCwsI3b97s27ePm5vbzs4OuHjQz8XFxaWkpMLCwlxcXKysrB48eAD9KCwsjEgkSklJzZ07t6ys7NatW6amptbW1pCgubl54sSJenp6qE21tbWvXbsGTN0tW7ZwcHAsXrwYMXcOHz7Mzs6+devW169fg0nGfyCqgVGpYR4eHsB8bGlpcXJyQh+IB9oDhEqlZmdnw4g2KioKdRMSiaSurk6nBwwNDVetWoU+YfXq1R8+fIBbVlZWgYGBcP3MmTO6urrgX4HtUFRVVaGbZ2dnL1++3NfXF09es7e39/LygtUiXV1dixYtMjIyGpXdBlywgwcP8vPzb926NTs7+86dO3p6eq9everq6vLw8ODn5w8PD7ewsEhOTpaSkjI3N79//35DQwPoAWlp6ezsbDxxSVdXF8YKzs7O2dnZwGmAfgTluXr1KhcXV3Z29sePH7u6ulxdXQUEBCwsLLy9vV1dXSE0g6hhFy9e5OPjExAQkJKSsrS09PLyAhl4+PBhd3e3t7c30oSvX7+2sbExNjYGTQiTKAkJCdCEnZ2doOjs7e2bmppu375tZmbGy8sbHR0NMmBubt7W1hYQEIAUXWpqqoaGRm5u7liCAWYVTw1ra2vLzs6GMDOoXOg4sbGx1tbWqJX19PQQVe3gwYN4Daarq3v58mUmzG0gqLe2to5VJFgmY2Nj8/Dhw/fv31+5ckVAQGDixInZ2dnA7YeaAcY7MIuVlJTi4uKgAB4eHmvXrgVpHxoaio2NFRYWDg4Ohrv6+vpJSUkjIyNUKnXjxo0Yhrm4uDx58gRZLkFBQeaKbvz4G0di1NTU3Lt3z9/fH/5NSUmRlZVVUFBoampqbW1lZ2cvKyuzsbFBoa/Ozk508oGMjAx+ZRseV65cQSOdiRMn2tjYwO9Xr17h19t5enrifWvp6enADzc0NNTV1c3NzQUXmbW19f3791EyFxcXERGRpqYmsNlsbGywIPX169d5eXngSHd2dm5sbAR394wZM/AsAEB+fj6VSmXiiBYSEqqvr4e9BmfOnDkWXeLBgwfl5eVEItHX1/fmzZto2CUuLg76Licn5+3btxwcHMAiYV4D+Ika/hARZWVlYMympaWh8aCkpCRMLhkfX7hwIUwKYW0G8izJycl9+vQJz6ewsLBgvjfhw4cP0XSfh4dn6dKljE2spKQ0c+ZM5rFYkEleXt4lS5Zcv34dcWfk5OTmzJkD0aDa2lo+Pj6wbfgpy6lTp8az2aednV1/fz963MjIiM5pfOvWrbq6upiYGBCYadOmIbeBq6trfX29r68v8qsbGBjgnx0aGoK1HBiGCQoKurm5QQ3IyMjw8fGheDB8YHt7O3Ieenp65ufnjyoDEhISoqKiyA+MErx8+RKCl1BUVEUUCgVNVkRERJBbPj4+fnBwUEVFZWBg4P37962trY8fP54/fz5jDdBNu7W0tMhkMi8vb01NzVibjSxZsgR4MXfu3KGLDri5uQkKCoqJiR08eBBPkoI5cVtbW1VVVU1NzYwZM6ysrNCUNCMjo7Gxcffu3VOnTrW3tzc1NcXHFEtKSh4/fnzr1i0tLS1ZWdlFixbh51sODg7V1dVpaWkqKiqvXr3S1dUlk8nMnQRJSUm9vb1Qk5MmTQJ/G9JjIAMg5Ozs7GZmZjDuR2QiRD6oqqq6d+8eozrCMGzp0qU8PDwogYODg7S0NJ0MJCUlBQYGpqSkIL8X6gWmpqYCAgK3b9+G2ae3t3d3dzfQdAwNDSUlJdHuCKNqQjpF19/fj9/0BmQA9ACS/ClTpjDZFfiPP/7YunVrQUEBIkkgTYgPixgbG4MeOHv2rIODAxhLpOqLior++uuvlJQUc3NzEokkKytLxx05cODAvn37EhMTHRwcwLno7OwcExMzagjg8ePHSNFxcnJOnToVVD3yqvLz87979w48u1xcXCAShYWF169fLy0tnT17NoZhPj4+eCpSSkoKip9KS0tDMe7evYtcsNDNwfUNEZkvKrpvOXtmgYVfH+7u7rB0+4uYM2cO3cKqsbZFZLy4cOFCdnb2O3fu/FLfzmTVIhMMDw+PuhsB4+zZx8cHv6r4KxAaGrpx48axGmhoaGhU7xqs5BzrFkx8YUNQJpt66unp7d69e9Rk36omvyFyc3PZ2NjQ7PlXFifGDTiZY2BgYCzn1sDAwFgNhN/U8+XLl0pKSmiB1jfE8PAwEzH7KfjlzntmgYWvw7lz5wYHB5lHuP8uxqKz0U3jfgV83cI/AoEwTiZLfHx8S0sL6K+veFFlZWVmZub69evHaiB2dvaxlk7w8PAwWVXBwcFBt40lWPqRkZF79+6Br0JWVtbV1fWL+wr/k5r8j+FvVcLg4OA4BYOTk3Ms1hsnJ+eoG53C8Ku+vh4orrGxsadPn/4iYfbr+gLztX8/HkSWILLwr0Z7ezssK7h06RKM5cdjKurr6xmjGOPHo0ePqFQqfkXyfxvz589vamravn07hmHR0dFfYcDw+55+b8TExOTn50tISHh7ewOxFi1e+FeA+cKqXwoVFRXe3t5nz549e/ZsRETEVy9NZhIvg8i9t7c3rBEYa3Pc/yRY5pmFfzcgDDx9+vRp06bRLUwaFZ8+fbp9+3ZNTU1HR8fSpUshKjZ+fPjwYWBgQEBAoKOjo7u7m/lWHv8ZRERE/ItKGxQUFBQU9C+t6tbWVlg429nZ2dXVxbjNyC8FtADpO8Ha2vqbLJn5l4KdyZJzFlj49TE8PDw0NBQVFeXo6DieMxguX778+vXrw4cPDw4ONjQ0jLU3wljYuXOnsLDw/v37b926NTQ0hF86wgIL/xx79uzh5uY2NjZubGzs7+9Hmymx8D8Itn+LF4UFFlhggQUW/nfAooaxwAILLLDAAss8s8ACCyywwAILLPPMAgsssMACC/86/GeZ28+ePUPbz5qbm4+639Y/QW1tLSypFBAQ+Ien1jBHZWWltLQ0fqfff47BwcEHDx5wc3Obm5t3dXW1tbUpKir+lGb666+/0Fkj06dP/4a7yWMY1tfXl5ubC7+FhISmTp3K6vBfxP379ydPnvzNV8jQ4dWrV2gbJiMjI8bzPceDuro6tM+dsrLy+I+s/VYoLi7+lalb0M3hNz8//99dpDAefP78GW2dZmJiMp6lE98DNTU1oqKi35Dlfv/+fQ0NDcaDc340/qsbSJmbm2MYJiMjExsbi/ZDjoqK8vX19fX1vXDhAl36+Ph4uHX27FnG3NasWePr63v8+HH8oej79u3DMMzAwOA7fUJmZqavr6+2tnZVVdW3zRlKzs/P7+vr6+TktH///p/VTHC4RURERGxsLNqU6tixY76+vmvXrh31ET8/P19fXzKZTHf9woUL0IJoW6Kurq7Y2Fg44sLCwoK1qxpzlJSU+Pr6EonEy5cv02g0WH0LGxRDxX5DOcEfvvn8+XP8rbNnzw4NDY314KtXr/Ly8lB3hlM3MAzbu3fvj6yrkydP+vr6Tpw4MSkp6Zdt0P7+frTB7cmTJ9H1Fy9eQIO+evWK8am4uDhfX19/f3+669XV1fAU7PcOaG5unjlzJgzuy8rKxlmwmJiYce7u98XN86FIBgYGo37L1yEuLo6dnX3GjBk/vQV/gnmuqqpKT0//MeYZ3/PhMFcXFxcJCQkCgaCqqopuHTp0aOrUqS4uLgsWLCAQCJKSkujWmTNnpk6d2tjYeOLECVNTU35+fvwmcFu3bv1+5nlwcLCwsBDDsNDQ0G+V58jIyJo1a2xtbfv6+g4fPtzX16eurv5zzfP27duRQf1/2PvyuJq29/+tkTRIKZqkJNKhSWmOJs2a1SEilCiO+ZopGbqZlSGhVFKilCJcKYnToNCISsNpcJrntL9/PL/Peu3fOZUM91733vP+o1dnD2vv/ay1nmc903pevnwJW0QpKytjGMbNzX3hwgV08cGDB7W1tY8fP+7n56empga1Q6AAg5iYmKqqqr29vaSkJDc3d3JyMrqrrKxsxowZ/zLx3NfXxyDVfhyqqqpJSUkZGRkZGRnXr19nY2ODFVJ/fz/sWrxgwYKfKJ6lpaVzcnK6u7thK8cXL15wc3Pb29s7Ojrq6ury8/OjUjEIPj4+nJyc4eHhaB/QgYGBQ4cO/fXiua+v78KFCxiG+fr6/rKDpLe3d9WqVVJSUojIDQ0NZmZmHBwcsEU2JyenpaUlqi3x+vVrRUVFR0fHR48e2draGhoa1tXVwTLX1dVVRETE3t5eV1eXg4NDW1v706dPwE/6+vpgl+lRiucHDx6wsbG5uLh893fV1tZCZZTBwcHu7u6NGzeCPeanEO3YsWMhISEZGRl//PHHf0489/b2qqurE+Xfn4TIyEgMwwoKCtB0MjAwiIuLw3E8IyPDw8ODh4cnIiICThkZGb1//x4k7oYNGwQFBWGPur6+vpkzZwYFBUEjNTU1WlpaRB16//79f554xnEcqpBC3aefta8shmFQ0gqgoKDw94rngwcPop9ubm76+vp37tz58OHDpUuXODg4UIGjvr6+BQsWoIJFwcHB4uLisOHfli1bQkJCysvLQcBjGGZoaEj8ZAqF8i8Tz/v371+7du1PbPDq1aumpqboJ1SnQCXCcnJy2NnZf7p4RtMTx3EnJ6dVq1bBVs+fPn1SU1NbvXo1g3IP5auReEZ2LElJyb9YPOM4Xl5ePnv27F9cPHt4eEydOhUd+eOPPzg4OCIiIiorK+Pi4qBaM1gj3r9/LycnFx8fj2bN+vXrExISYIHr4ODw6NEjUJdNTU0xDIPCaAAohDNK8Uyj0eLi4l68ePHd32VkZEQcA5WVlT9LPIeFhfHw8ISGhv4iPfhXh4axsbH9NTs5MJTX9vHxsbCwsLOzwzBMW1sb6pbALoN37twxMjKCQltsbGxqamqdnZ1Qo+bIkSPjxo3btGkTNCImJiYmJkasyPvX4OrVqz+rqeHqs/6NyMnJIRZnTUtLs7GxmTZtmoeHx+HDh4uLi48dO4Zh2KZNm7i5uVGB95kzZw4MDOzevbuuro5Op9vb28MmnfPmzYO69KjBmpqa4Sos/aNDK366GxU2qwJMnTr10aNHqIaVlJQUlEH7WdDX16+oqGhqaiJ+0dy5c2G7UAkJCTExMYZbMjIygoODmesoJyYmdnR0jFCG/E9CXV1dc3PzrzxIuLi4oLQlEWfPniWTyVJSUnZ2dvfv30c8obW1taysDBWewjCsq6sLcZ5Zs2bBABAREUlJSfmRUB5RUVE7O7sfidf56YOfOAvU1dVXrlz5i/Tgt4nnlpaWhIQEMzMzQ0PDrKysjo4OGo1Go9EOHTrU2tqamJgIC6svX77QaLS8vDxDQ0NDQ8OwsDBQ2mAQcHJyenp60mg0FBvS1tb24MEDOzs7e3v7e/futba2Qgs0Gu306dOVlZU0Gs3a2hqYbHNz840bNxwdHRcvXpydnY1qdDPHLBB/+vr6gg0EoKGhgRi9o6Pj9u3bkSe+paVFXFx8hKKE6enpBQUF30ro3t5e+ApXV1dDQ0Nirbe+vj4ajebk5GRpafnbb78Rq4IDoFQZgEajbd261dDQ0NHREQVVQQv3799PS0vr7u7evHnzyZMnh3wN2PO9ubmZRqMhEkVFRaGijS0tLbdu3YKOQ7Xr29raoDv8/Pyam5tjYmJgoYNhWEdHx/PnzxcvXrxx40aolg3HP378aGVl5ezsbGhoyLBUYoCgoCAqk7B9+3aGbfGnTp1KJpP7+vo6OzuJxw0MDECXgvACYWFhdKqxsfG3335DPydPnqyrq/tN0Rg0Gq2srMzQ0PDZs2eIyNCDDx8+tLa2ptFoDQ0NiAI0Gi0wMJBOp7e2tiYkJJiamtJotN7e3s7OThqNdvbs2fz8fPT+tP+hu7ubRqPl5OQEBwfTaDTiBRUVFUFBQSjAh0ajpaen37lzB4W89fT0dHV1QQtQ/h2Ngbi4OBqNBrL28+fP8KyOjo6GhgZ/f3+G6vHoEZ2dndBCc3MzUIBGo6FlU01NDQqyQ7ybRqOFhYVlZmbSaLSBgQE0wWk02p49exhaYH4i88EzZ85UVVXBB/b29hLjxUJDQ5OTk4dcIlhZWYmKira2to6yf+vr62tra/fu3Ut8vcbGRnjhrq6u+vr66urq/fv3M89EGAOJiYl3796dPn36cNu29/T00AggdtDg4CDDBfAO7e3tNBrt6NGjcXFxoJhCU9CDBw4cgJcMCAiAOqFwb0REhJOTE3rEVzFnzhxLS0uGg5MmTcIwjIODg4eHZ//+/fCSnz9/joyMXL9+PaglxBqgx48fV1dX19PTG+4pMAaIqz0G+tNoNCjJDKMIZAGiQFlZWXd391clEY1GY+ig9vb2P/74w9DQ8MOHD8QWQJpkZ2cDL+rq6hqh5fz8/MjISDQ9S0tLz549OzAwcP78ebRTLHzgkSNH7Ozs0tLShhvkf2lo2KlTp3777bfIyMiQkBADAwNZWdnU1FQKhaKiorJw4UJYcXBxccHcVlFRoVAoFAoFSurW19eDDYQY6CgvLw+OBB0dHS8vr5cvX+bl5cnKynp4eLS0tFAolOXLl2MYhoryXr9+vaioaO7cuRQKpby8/NGjRzNnzhyurt/58+eJxm3myA5+fn6ijRe5e2fNmlVUVIScncrKysQLHBwc1NTUPn78+K3GbSgvevny5d7eXgqFMm/ePHRqz549BgYGISEhkZGRFhYWXFxcqFA5CDZk/k1OTp45cyYQVlxcfMGCBUDY9+/fg/bg6uoKCwsvL68hzXHE1TRUWScat8vKypSUlKB9AwODiRMnZmRkQHCQg4MDhmGKiorwIGFhYRzHIyIiTExMVqxY8eTJE5jA4D4oLCycM2dOfHx8fX09hUIxNjYepXGb2Q+koKCA4zjIhkWLFhHP6urqbtu2jeGWpKSkmTNnvn37Fh2pqalRU1MbvXH77t27s2bNAiJMnjx59+7dcHzz5s3GxsZXrlwBO/D48eMfP36M43hKSgqodPv37583b56Pj8/06dPBKmNlZTVhwgSImD1x4gS0A0V8FRUVYVFIJpNBk1i8eDFUgIetSZFpFxx7IL3gCCqkDVPj9evX6enp3t7eCxcupFAoYOxZt24djuN+fn7QWfv27RMQEMAwzNLSkvmT4TKAtbU1Wrdt2LABGST19fWRcbu/v9/Z2dne3p5CoUDda3AAVVRUAAWAepKSksPF9926dQvDMCAgwNvbG3hCYGDg0qVLHRwc0KnGxkbguTiOT5gwgcG4DXGOozRuP3z4EHWutLS0trZ2TU0NjuMUCgU+2cHBYdasWb6+vhiG8fDwgEUX8OTJE39/f7jXx8cHrfuZn5Kfnw8X8PDwUCiUqqoqcK5jGAYFLvPz8zds2ACPu3v3blNTk5GR0cqVKykUiq2tLYZhqJokfJ2oqGhgYCDUZQfnGuIDUJV5ONPu2bNnicZtBkCxZxRqt2XLFhRnp6SkFBkZyXxLZWWluro6Q/wsg3GbyAqYAStpR0dHHMezsrIkJCRAKTc0NAQKjB07dsmSJUMWl6yurg4MDES6Oz8/PzJub968ecGCBR4eHsCgyGQyuuvcuXPq6upALkdHRwcHhyGLqIaFhRG3+I2MjARtU0dHZ+fOnRiGqaioIAr4+Pjk5+dnZ2dLSkpu3Ljxb/Y919XVCQsLo4gbGo3m6ekJ/2/atElUVDQsLIxKpa5cuRKmE5otBQUFgoKCHh4eOI7T6fSXL196eHgICQlRqdQ3b97gOG5oaLhlyxYUyOfp6SkkJPTq1SsknExMTKhUamho6J07d6KioojBWc7Oznfu3BmN75mIgYGBPXv2aGpqMnCoJUuWuLi4zJ49W09PDxTBIcUzPz//s2fPvkM8r1mzBoWkomiv8+fPq6iogJTFcfzz58/6+vrCwsJECqCLt27dWlZWBv9DygTyDlZWVvLy8k6ZMuXVq1fp6en79+9nfgco7oRh2MmTJ6lUKgS0KygobN68Gfy7aWlpKMKzvr5eUVERCae2tjYbGxteXt5z585RqdTVq1d//vxZUVHRw8MDIq5bW1utra2NjY3b2tpCQ0NFRETQc0cIbVNRUSGRSEBtBuTl5YmLi8Mkb2hoMDY2HkE8FxcXL1y40NnZWVNTU1BQ8ObNm+iy7u7uVatWjVI8P3nyREhICIXKP3z4ECgQFBQ0f/78xsZGJDA0NDRERESgBi24QmxsbKhU6pcvX8BpoqqqSqVSCwsLa2pqJCQkJCQkPn/+DLPAwMBASEgoIiKCSqV2dnZWV1dD0hcwWSqVqqenh8RzV1cXlUqdMmUKEs9UKlVHR8fOzo5KpVKpVDqdvnr16kWLFsEoGhwcPHTokICAAI7jPT093t7e48aNU1RUTE1N9fLyGtJj/ebNm6VLl6qoqFCp1LKyssHBwaCgIB4eHiSeCwsLBQUFkXjesmWLpaVla2srkHfNmjUQyQH2LRSBn52dPZzUhNUqUTy3t7cTrURnz56FuCRwS+/evRvc0szi+Zt8z3v37oUuw3EcFhawSO3s7IRFz2+//QYUoFKp8+fPRxR49+6diIgIXAyuWajfNZzvGeJGRUVF0RFDQ0PihO3o6Fi8eHFbWxusm+Xl5UGKt7S0mJubOzk5If8xCHIvLy8qlert7d3S0rJr164lS5agC/bu3TtceMoI4rmlpUVfX3/Dhg0oseXTp0/wUWjl0dHRga5/9+7dokWLrKysBAQEVq9eDW8+pHj++PHj7NmzU1NTh3xufn6+paUliGeIBMIwTFpamkqlQhdDqdYho/fb29upVCovL+/BgwepVGpeXh4Sz7q6ulQqtbe3t6KiAtbHcMvNmzenT59eXV2NvO/EdSfzLJg1a1ZaWhqVSv38+XNTUxMsna9evQrEx3FcQ0Nj8uTJaJAvXbpUREQEZNnfJp49PDxsbGyGPLVp06YRYtBPnjyprq5uZGSEQrSsra2JoWGysrKnTp1CP8FYDdW2QThB0BYgKiqKk5Nzz549x48fH/mFT5w4MZx4vnjx4rx581CQESAxMREGR35+/vTp0+fNm1dVVTWkeJ4zZw6Skd+qPe/cufPAgQPoYENDg66uroaGBvHK69evM1Dg2LFjDK29fPkSFvhotuM4LiAgAMFuIwC0FobQMGNjY2C1CJ2dnXv27BEXF0fiGcfxVatWLV68mNizEydOJNZFBwtKbGxsaGgoDw/Pnj170Kz4Du3Z0tLywIEDtbW1o9Sek5KSYM7Y29tzc3NDVAssJbW1tUcpnpcuXYo4I6yWHj9+XFNTM3/+fIbAqJCQEMjbxnH81atXYG9ECwLQeNDFoCijRRikFRE1M/AjoOAsa2trhsAoaWlpJJ6BOEjQgqslMDAQnY2IiEAUOHz4MERRjPzhW7Zs0dfXRz9zc3NlZGQQFyNS4O3bt7NmzVqxYgUx4EhISCgoKAjE886dO7/KwY3LOAAAIABJREFUrUBvI4rnoKCgffv2HThw4MCBA1ASGCjw7NkzIuV/UHsmAhw6SOKC7kjMFDAxMQE+gOP4jh07TE1NiTIpLy9PRkZmhNCwy5cvjx8/HlSatLQ0RUVFDQ0NZEm6evUqKC3MWLZsmYKCArLhHT16dNKkSenp6egCMpk8e/ZsPz+/r37jCOL5+vXrgoKCxCMpKSkkEgm6AGQk8Q1rampAz7579y4HB4ezs/P3hYbhOL58+XIknmtqajAMI/IZ8IiPkFzHMAaYQ8MSExNBPHd1dS1atIhIgYqKClVVVSsrqyFb3rx5MyQUoCPGxsYYhhED2URFRS9fvkyMdMMw7OXLl48ePdpDwE/JHPtTtiUpKiq6efNmXl4eLy+vj49PXl4e9AFy7KErT5w4UVlZef369ezsbDgyODiorq4+XIK5hYXFqlWrwsPDP336FBISIiEhcePGDUhsZcCzZ8+GtOQHBQXFx8cnJSWBxwUBuWTmzp0Ldvvq6uoh30FWVpY5buWr4OfnV1dXv3Xr1vv3769fvy4gIHD79u3u7u5nz54xREmAdYsIVFe4vLz83r17kJlgY2PzffEszAcbGxvBd0Wn04uLi8HuN2PGDKJDdzgH/6VLly5dugQ/GxoavL29TU1Nnzx5Ii8vf+jQobCwMG5ubhkZmWvXro2+OvKXL1+OHTvW19eH1vLKyspLly4lRhIxw9zcHBEwLi7u/v37VlZWGIbx8fFNmzYN5vBXER8fHxoain5OnDhxwYIFubm5L168YChsZ2trO3LVQqJjkjlwSV9fX0FBAf1UUlJatmwZ8md/B2JjY3Nzc5ETTlNTE21DMW7cuG8tTS0gIEDcYoKbm1tQUBC8iSUlJUVFRcScWggdmjx5MgzyI0eOXLlyhZeXd+fOnUZGRlOnTv3qOITpfOjQIVCgyWTy2rVro6Ojly1bdvPmTXNz8+zs7HPnzvHw8LS1tZWXl2dnZ8+YMQOMvVZWVuDJGg0+fvx4//79hIQEISGh3t7er15fVVXV2toqKSkZHx+/evVqIl8qLy8fcjYhODo6Xr58+eHDh2ZmZk+fPg0JCcnOzt6/f39cXJyBgUFUVBQsxMHeUFBQsHv3bqhO/fz587a2toaGhpkzZyL3MDF+4vfff7exsQkKCgoLCwMK+Pv78/DwjL5/S0pKnj17RoxyTUhI2L17d2RkJPgfV61apaenFx8fj2Y3BMaC+0NeXj4+Pv4nigzmkIhz584hD8J3o6enJyUlhYeHhzhWJ06cCGErQ6KrqwvtZwVwc3NDMZKHDx9uamq6dOnS48eP4cjAwIC6uvr48eOTkpLu3r0LhvcPHz7s2rULhdR8N/4U8bxhw4aBgYGbN2/CritRUVFIPMNuGMuWLYP/58+fLyAg4ObmNsqe4OPjCw4OLiwsfPLkSVpaWmJi4rVr14hxQAimpqa3b99mOHjt2rWoqKjY2FgG2fytgvabZgIKRsvOzi4rK7t//35WVlZ0dPTp06fRpgojA6KT3r17Z2dnx8PDExsbKyMjAxEi34oh1z0uLi5CQkKgr8THx6ekpJiYmGAYBhr/CGBnZyeTyUguEqN1DA0NL1++jGFYcnJyamrqzZs3iaF5I+PChQuJiYlgMUYCRkBAYGTxPMJ8G5mN/kkgiufy8nLmICNiOA+NRnv9+vW2bdu++3Hm5uZ79uwZ8hQPD8+3LiifPXtWWFhoYGAAPysqKu7fv09coOjr64NsYADI0Z6eni1btnh4eGzatAnFuDGMw/nz54MREsOwixcvCgoKIuO2rKysp6fno0ePWltbq6qqYmNjHzx4UFZWJiEhMTg4COpdQkICLL8SExNHORfKy8ttbW1xHL99+/aMGTPodHpcXBxDl2lpaTFEZaJwmTt37nh4eIALH2blyBFMwCiePHlCpVJTUlLc3NwoFEpAQEB7e/vjx4+lpaVBGAN558+ff+7cuXXr1oE86O3tHSH2SlRU9MWLFwkJCRUVFadOnTp58iQ7O3tgYOAoO7ewsNDBweH06dPEfdZ27Njh7u6OPlZcXHzv3r2bN28esoWDBw+6uLj8xMnCzJcgFuGnYNKkSTdu3BjlxQoKCgwRiBMmTEDebl1dXR4entWrV69atYrhxkWLFvn6+sKS8eHDh6MpbvvTIrcVFBRSU1NR7OhXoaysDLI5Ly8P8veRYvT48WO08tLU1JwwYUJRURFDoPVwuH37NlhgfHx8oqOjifoHsxrEcCQlJeX8+fNPnjwhbmAJwSzEtVttbW1raytsVCIjI/P+/fuzZ8+imMOGhoYRtvGrr69PTU1FsTxEnD59OjIyUk5OzsfHJywsTFtbG8Ow8ePHy8jItLS0EHW7goICcXFx6Ga0bsUwrLKysqSk5OTJk5AD9h3R40OuUolITU1dv349yObKykqGVeSQIZrI7EFcsdrb23d3d/v4+Pj4+Ny+ffubdls8ePBgdHT0gwcPIGZkOHz69GncuHF79+4tKipiDlPn4+ODdCwQzwxfXVtbixa/zFi7di1zvOu6devodDrRoPJV+hMXN8zSMS8vr6KignhxX18fMaq2urqaTqfD/wyxrM+fP0eKMrHvhnsTHh6eb9WedXV1SSQS+iktLW1mZobWAVZWVjU1Ncyrpc+fP1dXV3t7e1MolMbGRh0dneTk5A8fPgw50vLy8kYwaYiJiYmLi0tJSUVHRxcVFcXHx+fl5d2/f5+fn//8+fONjY0QtgNrQUlJSeK9BQUFQ/ZObW3tmzdvHjx4AMoT8zWVlZUMaZOpqallZWXwf0ZGxshBv8wICQnJz8+/devWwoULYRaQSKQNGzZUV1e7ubkxDLlFixahIy9evBghgdPT03NwcNDa2trHxycnJ2f37t1D9n5nZydzTubbt2+XLFkSGBiICAggkUglJSVDhlszz4i1a9cShwczHj58+E3ZjMwmw58CAQGBI0eOdHd3wwbM3wciJwTx/ObNG5SLhDB//nzEtI2NjX9cdf4G8bxp0yY2NrbTp08TR97IjP7Dhw/x8fEQ04GOc3Jyuru7g4MZtRASEoKYaW9v7/Lly4uKioazpiJBzsPDMwIJmDOjzpw5M3bs2PXr1y8ngIODY8GCBUTjWFpaWmlp6ebNmzk5OclkspiYGHr/58+fZ2VlofhGZixbtgxCZphP+fn5IWPa2LFjYXNpSUnJ2NhYOp0OEVuAY8eOmZubI3MKZBGg/+FVHz9+/H3JecxpoxiG3bx5E0kCaL+jo8PR0RFcSshhgfbvRUNw2rRpd+7cIeqm0Ke3b9+G/c6gm+Tk5EDkD7fkQgkSFy9e3L9/PwcHh7e3N7GbGhsbly1b9v79e5Tek5SU9O7du/Hjx3/58uX69etEURESEuLl5cXLyws/x4wZQ0zWGhwcdHZ2hkD0ITlRW1sbcUGJYRgHB8e4ceNev36dkpJC7CZjY2NYKn0VzAsdBu356NGjXl5eSDPDMOz+/fsgP6qrq+3t7Yk5JFpaWrAZKkBCQsLCwqK0tPTRo0dDTs9Pnz7du3fvO7Rn4ioWPIJg6Obm5n748CHqYvS4vLw8WJSMGTNGWFiYi4vL3Nx8OBJpaGggA4OdnV1bWxuRoR89etTc3HzOnDk8PDyCgoLjx4+fMGECLy8vGxsbHx8fNA5XJiYmDg4OopVNfn4+7FM73KeBIpWZmcnMImRlZTU1NRmMcHJyckhEIaqeOXMGjEOjUQqvXbvm4uIC6tSOHTsgF5GophOzQ9etW5eZmTlmzBhwwANqamoSEhKGvP7Lly9JSUnMEhRW/8SEKAzDiouLbW1t29raYmNjifMrNjZ2x44doaGhKMFyYGDg0qVL0Oz79++JlsjQ0NBp06bFxsYO99WXLl1atGhRUlLS6Mfb6LVbZGCDFLWviDc2Nl5e3oaGBnt7e7S2DgsLG8HsUVRUxLA5RFdXF3Gqrl279uTJk0gUtra2Ll++fMg16F8nnoHFmJuby8nJycrKksnkoqKi27dvk8nk2traSZMmkclkiMYCwxcE/Q4MDNy5cyc0NFRISIhMJvf393NwcJDJZD09PTKZDNy/uLj48uXLaWlpnJyc06ZNc3d3nz9/voiICJlM9vPzc3R03L17N5lMhhEpKSkJ3s3g4GBFRUUjIyOUssw8RIg/wRkGEXdE4Dg+Z86c58+fc3JyamhobN26tb29ncgKExMTc3Jy1NXVY2Ji4uLiRtC6gKlpaWmBZswAa2trPz8/LS2t8PDwGTNmyMnJwYpEWVnZ2dkZ4rdjYmKmT58uICAQHByMYdi9e/eAAqmpqWQyWUdH59SpU1VVVQYGBh8+fCgoKHB0dDx69Ojdu3dLSkrIZLKpqem9e/fIZDKzagVYtWpVenq6o6NjeHj41atXGxoayGSyoqKirKwsWAjS0tJsbW2nT59OoVAyMzN37txZXl7+22+/3bhx49ChQ8rKytzc3Mhto6CgkJ6eLi8vr6CgwMnJCcninZ2dbGxsjo6Obm5uVlZWJ0+eVFJSUlVVHcHOYWNjA1a+goKCx48fOzg4CAsLM3eThoaGjo7OsmXLoqOjtbS0nj59CgKDn59/+vTpMjIyq1ev3rlzp46OjoODA4QLIemFND+kBiG3HwOOHz9+/PhxLy8vTk5OTk7OCRMmQDDd0aNHV69efeTIkfDw8JiYmOPHj0+dOvX+/fvCwsJv3769cOGCo6Ojq6trWFjYy5cvz5075+joqKGhYW1tDesePT09JSUlf3//jx8/omeZmJhwcnJOnDiRTCanp6dDjikgMjJSVVXVyMiIk5PzwIEDOTk5qqqqmZmZKN1cQ0Pj4sWL/Pz80dHRgoKCd+/eNTAwgAY5OTllZWVh97RHjx4VFBSYmpr29vaOMHRJJFJaWhobG5unp2d/f39WVtbLly/19PQyMzNPnTr19u3bhw8fzp07F8dxLy+vgYGB8PBwR0fH5cuXc3Jy+vr6cnJyIovR6tWrIyIiYmJi1q1bx8fHd/z48REmC1r/KSsrGxoarl+/PjQ0NCYmJigoaMKECTALkD3Wz89PQ0MD8iH19PSQRWTmzJkdHR1IGFRXV1dUVAzZv8LCwo6Ojrt27eLk5MzPz8/Ly5s+ffqVK1cKCwtDQkLS0tLExMSCgoIglhiInJqaCnJ048aNYWFh6enpQOHY2Ng//vjjwIEDNBptBNEiKip67NgxExMTtNo2MjJatmwZQ7jJnTt3Zs2aNWPGDHV1dX9/f01NzXnz5sFGqrGxsVevXjUxMYmKioKIJ3gxbm7uHTt2xMTELFq0aNOmTaM0Be/du5efn19TU5M4ud6+fWtra6ukpHT16lVbW9uYmJiYmJgFCxY4OzvDhqnXrl3bv3+/nJxcTEzMuXPnHj58+PTp0xGK6Dx//nzKlCnDWb8XL15cXFxcU1NjYmLy/v37I0eOODo6fvr0CWIYMQybPHmyo6OjgYEB+l7mFqqqquTk5HJzc8vLy2Ej2B07dhDXZBoaGtu2baurq/Py8tq1axdYgDg5OcXExIazM0VHR1dXV0PSRGdn5+Dg4Pr16/v6+iZOnOjh4bF//364zMHBwdHRcdu2bTAS7OzsDAwM/qRyLGNQ/vtoMDg4mJ+fPzg4+NOL/zQ0NGRlZYmJiRG3rRkSL168APE5ffp0CC8czjqXkZFRUFAwshEG0NTUBGqZmprakIFmKSkpvb29FhYWDPr6gQMHEhMTYRebM2fOREdH37p1azg/X25uLjjJpKSkYE9pojkOGPdXKVBdXc3Ozv6ttspv6uK8vDxVVdXhLqBSqQy9n5aW1tnZKSwsTFyXZGZmgkYrLy+PIlyYoaqqam5ufuDAAYbdSIZDTk5OdXU1BweHhYUFgyUZVsQqKioMps6qqqpFixYJCwtDaZ3AwMCHDx9ev359uHI0g4ODiC/w8PBA6CaySMO+GZKSkkh/LS4uFhcX5+Pja2ho6O7unjp1KpCop6cnNTVVT09PUFCwubmZTqfz8fH19PRISUnZ2tp2dHSAPObl5YWUGwZUVFS8fv0awzADAwMBAQFoExG/v78/OTl57NixyET5+fNnJFfExcXhsmfPntHp9AULFnz69Km5uRk2omfGo0ePpKSkBAUFMzMzLSws8vLyamtrNTU129vbP3z4ICUlVVxcPHv2bAEBgefPn6NZ8Pz5c7Sz0MKFC4ECaCsb0PKHC/KwtbVtaWmJjo4m9sIIs+Ddu3dlZWUkEolOp6upqd29exfyWzAMi4uLc3d337lzJySnGhsbKysrI2scM+7du/flyxcbG5u+vr7i4mJZWdmqqqra2lpEgcmTJ4P47O3tLSkp6evrQwO+sbERpOa8efPQNGeeEQwObyEhIaKvKjc3V0lJiWHAFxUVlZaWkkgkGRmZnJwcZWXl3NxcNTW1jIwMQUFBYHTEByF727hx44YzTXV2dhoYGDQ2NiI3SlNTU0dHB4NkJTabmpoKxsIxY8ZAgj6gpKQEioMxTHNAaWmpvLx8SUnJjBkzXr9+bWVlFRUVNaSWAqy+p6eHnZ2djY2tt7d3/PjxkyZNam9vr62tlZeXHyWjg+Bq2IKirKzMxMSktbW1vr4elAfYJwfHcS4uLhhgpaWlYJEVEhIabhYgOuTn5ysqKrKxsSUmJmpqaoqIiHR0dHz69Im43yXYbMA/i2IIfj7wfymgD4bbluQnbn0MiVXV1dUM23GzMMo9t4GF/XmPaGpqMjU1hcSqiooKdXX1v/2rFy9erK2t/dWss38xILWMmFj13SAmVj179oy4nwkLI29L8rNATKzauXOnnp4e7KPAwg/ir95z+y+DsLCwmJjYnj17yGTy90X8joyUlBQymfzgwYOOjo7k5GQeHh5/f38IvGRh9Jg0aZKYmNjWrVvJZDLaPvNnobGx0dra2s3NLTMzE9SX0tJSYinDvxECAgLfEf//r4GgoCAPD8/27dshg+77Guns7Fy7dm1UVBSyaSUlJY0QGvJfA4SG9fb2WllZDemc/nE0NzcbGBhQKBQUem1paRkdHQ2bB7Pwlxq3WWDhn4XHjx/PmjUrNzdXW1t7yLC4vwW2trY1NTW3bt0aMif4v4C+vr6EhISmpqYPHz74+PiMHKU/HLKysuLj4w0MDIqLi5WUlH5u0Y5/B54/fz527Nj6+vrm5ma0O/JPREdHx8GDBzds2FBUVKSsrPwjCasssMQzCyz8zXBzcysvL29tbZWVlXV2dh6h+AoLLLDAEs8ssMACCyywwMIvBDYWCVhggQUWWGCBJZ5ZYIEFFlhggQWWeGaBBRZYYIEFlnhmgQUWWGCBBRZ+EBwsEgBevnz5/v17LS2tXy3X5fXr1+/evVNVVR2hCNqfjby8PNgzyNHR8ads9T4y+vv7Y2Njx40b94vkKI8SNBrtyZMnEhISxNp//x3k5uaiTTp1dHQY9m77R6C+vh5tfSotLc2w//ZocPv27d7eXicnpx8vWPQPnQV/AWJjY/v7+6dOncpQXuxfCNbOLDiOr1y5UlFRkZ+fPzY29pd6MV9fXxUVFX5+fmKV+L8YHz58UFJSGjNmjIeHxzfVGI+Pj1+zZs23Pu758+eOjo4YhomJif2DhlB4eDjk3aalpf03J9HGjRvZ2dk3b96cmJhYW1sLB3t6eoqKiiwsLGpqaogXDw4OxsfHOzk5ubq6enp6wrbqgM7OTjs7O1dXV1dX1xUrVhBPMePLly/h4eEW/0NsbOzg4CB6RGxsLDoVHh7+5csXhtt7enpKS0vt7Ox27tyJ43hjY2NiYiIUqHVzc/umzy8vL3d1dYXdb0Z+59Ggr6/vt99+4+fnFxERuXHjBotFI5w/f37ixIn8/PwrV678138sSzzjz58/t7a2/gVfLC8vz9jY+Bd5mSlTpujr6/f29o7+lqCgoBkzZnzHs7q7u/X09P5Z4hnHcSi4dO7cuf+seDY0NEQ/3717d/78eXt7e1ADSktLiRffvXt35syZxcXFOI5v2bLF0tKypaUFx/HKykp1dXW0GD1w4ICxsXFjY+NwDw0NDVVSUvL09PT09IQaZWiFfevWrdmzZ8MpkJpXrlwh3nvv3j0nJ6fFixffvXuXYd7JyMiMRjx3dnaeP3+eRqOhI1Ch58fFc3R0tI2NDYs5M6C2tlZPT49Op7M29fyvID4+/quFjf8WPHz4kFhg+G8HMJ3RX+/k5PStdeIQhqw7+4/AL9VlfyMEBQXT09N9fX0jIiIYTj158sTT0zMhIQFKIKxcufLevXs+Pj4YhqWnp5eXl6NiqStXrnz48GF+fv5wT0lKSrp9+3ZwcHBwcPD58+d5eXnDwsLg1K1bt+7cuQOnQkND+fj40Ckcx6uqqn7//Xc+Pr5r164Raz9gGDYwMDAwMDCab+zo6Fi3bh2xavW4ceN+CvUOHjz4fRVj/91YsWKFiooKqhX7r8d/XTzX19e/ePGCNe5HAwkJiVHWlQKguknfPCjZ2Iar+vXr428MEfilMHny5KioKF1dXeYx0NTU1NLSAnWUMQwTEhLS0tICv7Wvr++JEydQfAMfH5+BgYGvr+9wT3F0dES1/JYtW7Zs2TJ0Ckqjov+9vLzQqcHBwalTp0pKSl6+fJmfn5+hTX5+fuaDowSUpPtxEEuts0Aky/Tp0/87G3p/A7dtbW3Nz88n/w8aGhokEgkKwN26dYtEIm3cuBGu/PDhw9GjR0kk0vnz5+FIe3t7QUHBsmXLyGSymZmZrq5ubW1tT09PQUGBkZERiUSqqqpat24diUQikUg+Pj7EeuPFxcWbN2/W0tLS09MjkUhPnjx59OjR/PnzSSSSnZ0dFFYLCwuzsrIikUhQt5gBRUVFmzZtWrJkCZlMNjc3v379ek1NDZyi0Wj8/PwdHR0FBQWo7Bqgt7cXauWamJg0NzcDBXJzc0kkEhSVA+luY2MDBNHX12eggK2tLZlMVlNTO3bs2JDr8Z6enr179zo4OJDJZGtraxKJhMp6U6nUoKAgIFFBQQGxqkdXV9eiRYtIJNLChQu3bdsGB/38/FBBjuPHjy9atEhVVZVMJkMBxI6Ojo0bNzJToKGhITExkUQirVixorq6Wk1NTUlJCfFQ2HLSzs6ORCI1NjZmZ2fDV9DpdOhKgJubG/OnAQWsrKzghQsKCiIjI6Edd3d36Ojt27d3dXUx3ztmzJiJEydiGNbY2GhpaQkXBwYGwtMLCwuzs7NJJBLU8QQSwQhsa2vDMKygoODFixcGBgbJycl+fn5wO9Q/Dg8Ph5+RkZFEq0BBQQGMLhKJRKRAQUHBgQMHnJyc6urqdHV1SSSSu7t7YWHhCNMEFbTv7+8vKCiAbiWRSGgMFBYWUqlUEomUmZkZEBAAZ21tbYld/OXLl5MnT8LQsrW1LfgfmpubCwoKLly4MH/+fLiyoaGhoKBg165dqBdwHIe5Bi3v2rWLaIpoa2tbs2YNmUzW0tKiUCjQbFlZGVL9w8LCLCwszM3NIyIiUE3llJQUExMTGOTu7u4/aG2CMYkgIiJC3C57165daLLw8PCg7hgSS5YsQf/n5ubevHkTlfomniopKUlOTv7999/h544dOywsLIbkFaABj6ZaCZ1Of/fuHYZh5eXliIbQ+62trStXrgT6b9u2jTjI3717FxAQQCaTtbW1GRgdUcbjOF5RUVFQUFBUVNTY2JicnEwikWpqavz9/Ukk0r1792CQBAUFLV68GCZpQUEBKi6C43hwcLCSkhIwit27d9va2iYmJgKjmzdv3sWLF9EgT0tLI5FI79+/Ry/w5s2b1atXk8lkZ2fnLVu2wPuXlJRs37591apV1dXVoaGh8HU3b94kvnltbS1McxKJpKKiUl1d7e/vb2JiQiKRjIyM9u7dC9MT5hpyfBBRU1MTERFhbm4OJPL19UUkotFofX19hw8fzsrKglKEDPfW1dXdunVr0aJFZDJZV1fX09MTGAJxmuvr68PrMVMAACVrCwoKPDw8oFA06mJTU9Nr167BNCkoKFi1atXu3bvz8vJIJJKlpeWfIp9HbwcHZo1+wlgvKirCcfz06dNqamq2trZwKjIyMiAgQFxcfN++fXDkwYMHwElxHM/Pz5eRkZk3b97r168DAgKAEVMolICAgICAAKip+eTJE7gxJSWFRCIFBATcvHkzISFhyZIl4CiCqZWfn0/0JDk7O6PAECIkJSVtbGzg6YWFhTNmzFBWVv748SM4tzAMk5aWDggIYIgLa25uDggImDRp0vHjx1HdND8/PwzDUlNTIZBEW1v72LFjcDYpKcnR0RH+NzQ01NbWhgAZ6ONTp04xv9i+ffuMjIzAlfL+/XtlZWV5efk3b97gOH7jxg0zM7NJkyYBWahUKvHG3NxcaWnpbdu2oSNeXl4yMjK5ubnw89y5c1JSUsSzixcvJlJARUWloqICJISenp6kpOTcuXOdnZ3Z2dnBpWdoaAjxMnV1dQEBAXx8fIsWLQLfc1hYmLCwMGrc1dWV+dMiIyMtLCzA91xTUxMQEDB+/HgMw3bu3AlfBAE4W7ZsYb4XSlfx8vLu3bsXLgbf4efPn3EcP3LkCBSQfvr0KY7jDQ0NAQEBAgICGIY1NzfjOB4QECAvL6+srDx79my4XU9PT0JCYvv27XPmzAkICHBycuLm5r5z5w7yNZqZmcGVy5YtGzNmTHR0NI7jr169gvJHIiIi+/btgws4ODg4OTlH8D2HhYXBzxMnTujo6MBdsHKqr6/Hcfzo0aMKCgoYhrm4uAT8DxMnTjQ0NOzo6IB7L126NG/evMrKShzHUZl6DMNevnwJ4oePjw9FToByqa2tjSg/d+5caBZcoYWFhcTOcnFxgU5EzSopKUFw09y5cw8cOPDu3buCggI5ObkNGzbgOJ6WlqaoqJidnQ2DnIODIyYm5qu+ZwSI+Sf6njk5OceNG0e8Zvfu3RoaGjiOAzdAEYigjCooKIyGQXl7e9vY2DD7fR8/fuzu7n7kyBEiK1u6dGms9EIIAAAgAElEQVRnZ+f2/4HoPy4pKSGRSF/1PV+5coXISIFLrFq1CsQ/0F9WVhbDsFevXiGP+5w5c0C0wAKROXYSSmtjGMbFxbV48WIKhZKVlQXrfk9Pz/37948dO9bS0jI3N3fjxo0aGhpVVVU4jgNfqqioAK//9u3bAwICTpw4QaVSAwICTExM5syZA679gIAALi4uGAMwyLdu3Yph2Nu3b+FIbGzsnDlzjh49Cs51S0vLjRs34jh+4cIFHR0dKSkpEol08ODBgIAAe3v7cePGJSQkwI1VVVVqamq7du2Cb589ezZEb4GkOHDgAJFXz507FwpQElFRUaGiorJnzx4gEbhFPD094SzU88YwzNnZ2cnJiZnVb9++ferUqVAK+s6dO2BQQWd37NixaNEieDc3Nzc2NjYcxzs6OoyMjLy8vOC4rq4uLOvBDIPGwNWrV42MjDAMCwwMhFkAW+UrKirOnj3bwsJCTk7u7wwNKykpERMTe/ToEToCq0UQzxD8jMQzfMDEiROReJaXlz9+/DgiKOgfIHLMzc1BRYZT4MgJDg4G2i1btmz58uWo2bS0tGfPnuE4TqPRpKWloYgvQFVVFaQmAw4fPjx//vy2tjYiH8Ew7PLlyziO0+l0CwsLPT294T585syZSDzjON7b24vEM1AAcXkcx5uamiCsQ1xcHMUvvH37VkxMzMjIiKHlCxcuzJw5EyJi0O3s7OwBAQHw89ixY7NmzRruxTw8PPj4+GBSZWdnz507l52dPSIiAolnFFZ2+PBhTU3N9vZ2hr4LDQ3Fcfzjx4+zZs1SV1evrKzs6Oioqqqi0Wjq6uorVqwAcY5Cw+Tk5ID3hYWFCQgIoCLNxInHEBomISEBLAPH8aioKFhfw8/GxsZp06bNnDlzyLDVlStXioqKgrjFcTwhIQHDsMzMTBRMjsQzwNjYGIlnGFRTpkxB5YTBxuDv79/Q0ADjSl9f39vbG86Wlpai4FjgR2hWl5eXYxg2e/bs1tZWJDhHFs+wpsFxfO/evWgMZGdnI/EMjAzDMKKQk5GRAWsBMPGJEyfCWgTH8Tdv3mAYlpGRUVlZCUXmZ86cicQzvKSEhAQSz/v370c9AgYhAwMDxKGMjIxgETAwMHDw4EEJCYnKysq6ujocxxUVFQMCAlB484YNG3h5eXNycg4ePDhjxgxQ6XAcv3379pB1mr9JPG/evHlI8Qwc2cHBIT09PT09HSzSI4vnu3fvQpi3ioqKoKCglZUVovODBw9cXV0tLS2VlZUFBATs7e1xHE9NTR03bpy0tPSSJUt0dHR0dHSmTp2qoaGBPvDVq1dSUlJfFc/t7e25ubkYht29e7eyshIqHO/fvx+0K2LfhYeHw5Kal5d3/fr1KOb8yJEjU6ZMYWi2q6ursrKSjY3typUr7e3tMOOgHVVV1ba2tsTExMjIyBs3bvDy8qJBUlBQgGEYhLgeP35cXl6e2Ka/vz+IZwAvL29UVBT6CXozcJLm5mZLS0tiVNrJkyfFxMRAmaFQKAICAteuXYNB0t7erqOj4+vrC1dqaGjs2bMHhihalOM43traCnkx0AiO45s2bdq9e/eQUbqgziISHT58mJ2d3c/PD95NXFz84MGDHR0daCFLzBPh4+ND+sng4ODJkyfHjBmza9cuHMfPnDlDIpHQLH727BnwfBcXl+XLlyNGR6fT9+7dC3zAwsKCOAbCwsLGjRsH4hnH8bi4OBio1dXVbW1t8JS/LTTs+PHj8+bNG33JNnNzc+A4wIYqKyuTkpK8vLwgkPLYsWNEjyb4n5AjCsOwQ4cOYRhWWVkZHh4OJhGAoaGhjo4OhmGioqKenp50Oh2dkpeXNzExYY7TiYmJ4eDgQOVIMQyDBmG9+eXLl6+Wm42LixvBmufh4QEflZmZKSQk1N/fHxwc/Pnz5507d8Lx06dPo68jAuQlqH3o28eMGQMv9lXs3bu3vb29v78fw7CQkJA1a9bw8vJCbGp3d3dUVBSiW2trKwcHBzGegkhkaWlpS0vLsWPHSklJjR8/XlJSMjU19c2bN6tWreLm5iY+UUxMDPmeW1tbFy9e7OnpmZiYSOwgBvT19TU2NhIfikghLCzs7e095F29vb1XrlxhZ2dHJSDhLhR1BR4NBr84c2gSSr21tbWdMGHCxIkToeDd+PHjiSE8cnJyUGsvIiKCQqEUFRUxNMXFxYWckUN25ZBvcuDAAUFBQRqN5unpeeTIEQzDkL7FQAoMw9zd3YlWuLa2tuTkZAbiS0lJQTYtw8eOHTtWWFgY/dy3bx/0yNOnT8Fyg6ZJc3Pz2LFjwYzBzs4uKCjIwcEhJSU1efJkuOz+/ftoOkhISHR0dMDP0tJSJyenEydOADEXLFjwg0Y75PZigK6ubnBwcFxcnJ6e3s6dO1esWMFAHGZYW1vfuHHjxo0b9+7dI5FIiYmJaWlpcMrY2PjGjRuJiYkPHjxQV1fPzMxMT0/v6enp7u7W0dGJiop69uzZs2fPPDw8srOzYfmIYRgHB8dokvt5eXnFxcXByy4lJQUOUfiuIblZX19fR0eHhITEtWvXBgYG+vv7GboYmdalpKTGjBkjJCTEy8s7duxYdMrT05OPj8/S0tLFxSUsLKy3tzclJYWoxENHHzp0aIQpCWBQ/dGRvLw8sJxfuXIlKyvr7du3sKRG16uoqIDqCRQgvh6dThcUFEQJ32JiYjt27ABf/tq1a9va2sBn8e7du6SkpCHfkOGt2NjYbGxspk2b1traimHYhAkTODg4Jk6cOH78eBjDzPwQUX7MmDFmZmYKCgrNzc2fP38ODw8fM2YMmsU6OjpPnz6Fd+bj40OMTlBQEOyppaWlDHxg0qRJXFxcQ44BPj4+Pz+/e/fueRIAnPmv8z3TaDTki/oqPnz4gESarKwsJyeno6Ojvb29o6OjmZmZl5dXa2sreJWIIha8TadOnRrNI2RlZWtqagIDAzEM27x5M1oNMPiHRgj7xDCMk5Pzq3GAFhYWQ4aKyMjIhIWFzZ8//8GDBxcuXDAyMgLjf0tLCy8v77Fjx6ZOnaqurk6hUDIyMsDY8tORm5tbVFTU1NTk4eFx+fLlx48f5+bmvnjxQl5eHtyTVVVViYmJI7RQUVEBE5JhYjBXR25ubh4cHMQwzNXVdceOHdLS0tHR0Q4ODvz8/MO58RgWRgx+d3DdMYObm3vIsFXEQF1cXBhOQQwwEVOmTEG9xs/PP8I2Ea2trS4uLvb29rdv3z548OCcOXMYLlBWVib+HBgYCAkJYW5HWFhYUlLy0aNHyF/Lz8/v7u4+f/78DRs2YBiGtrxgBpjOEF8TEhIKDw8Hb3Rubq68vDxxPcHwsf39/eAOQEMCtOTi4uLAwEAnJyd0ikQipaWlgczu6+srLCxEnxYZGdnc3Nzc3Lxy5UoIKcjKyrK0tJwwYcK2bdtWr15dX1+/detWCJuKj4//kUF7+fLl4U5JSUl5enq2tLS0trY+fPiQRqMxEGcETJkyJSUlZcjxJiws7Orq2tLSgoYc0aW9detWYkCfkJAQcbnzTUDxH8MdfPr06d27d93c3Nzd3b+VkkQ6gCEzLi7u3r17ZDLZ398/PDw8JSVllE0xzyDiESqVeu/evRMnThw8eDAjIyMnJwdcUSPrMNBZQ8LGxkZOTg4s/9XV1Rs3bhxyAYTmDoKCggJDlOjVq1c7OztHGaQpJSX18OFDKpUKoScMePbsGVgdmDF79mwGPmBkZDRCNeu6urqrV6/WEPBT2Ptod4AaM2ZMdnZ2RkYGcbaPgL6+vi9fvqB7gecaGRnB/wyrRQbNiSEb5+zZs0FBQcyPcHBw8PPzCw8Pnz9/fmJi4pAdICUlZWVlBTZGhkeD6jY4OPjVZU5cXJy3tze4P0E+oe9avnz5ihUrYL+kS5cupaen5+Xl+fj47Nixg4+PDzlLhkNtbW1cXBxDiAQziYbExIkTlyxZEhgYaG1t7eLiwsXFpampqaWlBSFU27ZtgwkAFACz8JAUmDp1qoWFBQP1Ojo6Ll68ePr0aQapCS1wcnIePnx4zJgxqampdDqdQqEMZ4EYHBwc7hTyFAypPYeFhU2ZMoXhOJLZzOkrzNrYo0ePSktLRUREYDSOkBK2efPm6Ojo6upqUIaY40KJKgLonWvWrGFuh52dHTEdsDHq6OiEh4cLCQk1NTWZmpoSB88I0NXVvX79uqmp6ZIlS0RFRXV1dePi4kDBHXKEsLGxoXU9PLeqqiomJkZcXJyBkXl7e1dXVx8+fLiiooKDg2PRokWI47u6um7dunXdunVr165laB8cMfn5+WCmdnd3P3nypK2t7XczHYbuAzse8aGwrsJxPDAw0MrKariN/KBPiTciNYj51PLly3fv3o0ISOxTLi6ub0pJ+FYEBwej4PN58+aBfvaD8Pb2vn79OphYmXH27FkwCA2H0NBQBpsEsVPU1NRu3779Te9jb2+P3DrMHExSUnLJkiUpKSkQNmRnZzckl2M++P9csASsWLGCWXUegW0aGxszr93RREM2f4bbX79+nZuba2BggI7cu3evvr5+hKVhbGzs3xa5ffHiRR4enoyMDBQLzWxgrKqqAs9xd3f3oUOHIKgb7CFjx4718PAYklPPnTuXQd9SVFTU1tbGMExAQEBRUTEhIQH4AjMiIiIKCgpu3Ljh6+vLrO2BPURBQSEzM5Oo7mRkZMyYMQOSHcFLMfK35+fnd3d3w//EzI3379+Dq0lFRcXFxcXf35+Liwu6ubGxkUKhjNzsrFmzODk5wXxERHh4OEQ7g2drOIwfP15JSendu3dHjhyB3QfFxcVBo+3s7Jw3bx7x4oyMjAsXLhB/YhgGW+JVVVUxGNmmTZs2ZcqU4uJiZJfOycnp6uoCFvbly5e1a9eCn9XU1NTFxWWELJTOzk4UFcw88YajPDc3N1g1R2kRzcvLY15QGxoaIpUIgh6Ge8msrKxjx46BbP706RNDAD/IP+LPL1++XLp0ibmd+vp6NObDwsIeP348c+ZMsLZ9+PAhNTV1hN5EMwu98PTp08+cOXPjxg1PT0+IFSKeJf5MSkpChrjk5OTo6GhpaWn4nKamppiYGIZ7dXV1b9y4ce3aNRcXFwaFwMvLi5mSfn5+JSUlysrKLi4uLi4uUVFRP56LODAwgBopLi729/dnSI/u7+9ftWrVlClTEhISYGUMkXEREREou+HChQvgNUBYv349Pz+/tLR0ZGQkg8K3Y8eOvr4+OTk5a2trJycn4if4+/vX19dDvB70I1ERbG9vj4iIGNIQPcoh6unpSRxs30004iDR0tLq6+uDmAYGaGtrZ2VloYs7OjqYLYjE1yA2KyoqOn369CFnwWiwefPmhoaGIU/NmTOnqKjIzc2Nk5NzyNkN/JzhfS5evEilUhnMV0MC2Cbx3g8fPjQ2Ns6bN09aWtrf37+5uZmZ2WIYdu7cOebxrKampqGhQRwDkZGRRBvVX4NvWDPu2rULwoktLCxu3brFIA55eHhycnIWL15sZma2du1aISEhdnZ28KJhGPbbb79xcXFZW1uDvrV58+ZLly59+fKFTqeDXbSlpQV0KfA7trW10el0UVFRZ2fnhoYGOzu7T58+0en0pKQkIinZ2NjGjh379OnTEeLa3d3dp06devbs2ZqaGjqdTqfTr1y5Ym1tPWPGjO7u7sLCwuTk5P7+ftCwmW+HsMalS5eamZnZ2Njo6elBb0GyQWRk5Nu3b6HZsLAwLS0tdXV1Y2NjbW3tO3fuuLu70+n0V69e2dvbo3wPBHNz89mzZ4eHhxcXF0MLhw8fNjY21tTU7O3t/fjxY3R0NJAI2SGY7QfS0tJubm6gI6K3ZbCwDUkBJyenWbNmdXd30+n07u5uoADkMOjq6mppaWVkZFhbW1+8eHHt2rV//PEHGxtbZ2dnc3Nzf3//mDFj2tvboanLly8LCwsz61JAInh/AHDS5uZmWKWxsbHx8PAwf2BfXx+NRgsLCxscHKTT6cSEtNWrV6Nu4uHh2bZtm5mZmaWlZVpaGkjQ5ubm3t5eOp3e19f36NEjKpXa1dXV2tp67dq15ubmzs5O4gTr6emh0+ldXV3jx48PDQ2lUCjHjx8/c+YMNzd3b29vS0tLT08POL1aWlrodDoSiuzs7I6OjgxGl66uLmi8r6+vubnZ2Nh47ty58fHxiYmJdnZ24GlbvXp1b29vc3MzhBegUYTW/mgWBAcH9/T0UCiUc+fO+fn5hYSElJSUoPwoXl7erq4uMzOzxMREW1tbyPobGBig0+lqamr6+vpPnjx5/Pjx3bt3QWmDU/D+wcHBbW1tcO+JEyf8/PwQ/WGSwhE6nV5ZWWlrawurq9bWVjqdDrQNCgr6qqkTjQEY1agFeAcdHR19ff3z588jIi9duhSZBzo7O5OTk52dnVtbWxmk3bVr19zd3SGhDpZxFy5cQAMsKyvryZMnkZGRWlpaXFxcFy9eRKfy8/Pv3bsXFhZmaGgI0+Tx48dPnjzp7OyEoNHg4GALCws0AomKRH19/bJlyxjWAUQEBARcunSpsrISfSAa5EiXpdPp06dPX7JkSX5+vpmZWUNDA51Oj4uLYzbDIF7U0dFBp9P7+/vROITJAo/Q19fX1NR0dHTMysqi0+mvX782MzMD9c7X15eLi8vJyenx48c3b950dXVl8F5t3bp1cHDQ399/x44dtra2dXV10EE9PT0KCgrm5uYlJSX29vZAusjISB8fH2AUPT09REYBuHPnDigSO3fu5Obm9vf3hxtpNBoEKyBmJSMjExERQVysMGDmzJlWVlanT5+GwVZbW3vx4sXAwEAXFxfEKM6fP//p0ydmwxvEUgCpYaA+ffq0qakJlgLOzs68vLz29vbl5eXwevBu27dvHzduXEBAAAObAv0nLS3NyckpMjJy48aNkGsH07yzsxMoAIzizxPPY75pH6gvX774+vry8vIeOXKkvLzcxcUlMTERzatNmzYBz1q/fv3MmTOPHTtWVVUlJSUFcbMRERFEybpw4UItLS1iGNSyZcs0NDR6e3s3b94MR7Zv3y4pKfnx40eUsIhh2Jo1a4heAeApoMUOh/Ly8pMnT1ZUVPT19c2YMcPLywvUkZSUFOLADQwMZDBjgjp19OhRtABcuXIlBH4bGBjo6+sT7VSurq5oi/a2tjYiC7O3tx8ymoZGo/n5+dFotIaGBvioU6dOsbOzZ2RkREdHo8v2798/nDMsICBARUXF1NSUqEB4enoqKip+BwVIJNLatWvh/z/++APMNRISEjt27Pjtt99gpbV8+XJI/nv9+vXkyZNFRUX37NkjKirK8GJnzpwZbmuF1atXg8nk0aNH4Hvbt28fUuNycnKIOT8wBj58+IAcHKdPn2ZjY3v27BnkXE6ZMmXXrl179uwBKYVeD5m23rx5AwwIwzBFRUXgDufPnwc3pKmpqbKyMpqTv//++40bN3Jzc8ePH29mZkY0WPn7+wsICLx+/RpUZ29vb0gCRB6QJ0+eIAvQyZMnEQXMzc0VFBQgSGLp0qVRUVFoObJw4UI7OzvoYvA0wyw4e/bshg0beHh45s6dixSdM2fOrF+/HlyDV69eRR+opqaGFn/Hjh27efNmTk4OLLOMjY1RDM6hQ4cEBQXBxT5jxoyenh6Uf/z27VvQHSEkODk5WV5e3sjISF9f39HR8f79+2FhYbdu3XJzc/v06dOSJUuGtO1v2rSpsLAQhWVBT5WWljIMV/AN9/X1USiUx48fy8vLc3FxrVixwszMDMOwyspKR0dHNTU1T09PBudfXV2ds7Ozra3tpk2b0METJ07ExMS8ePFi/vz5qqqqTk5OsICGhUh0dHR6erqKioqmpqaNjQ2E94MJwcfHJzExcerUqa2trX5+fpCgjwyb9vb22traMJDOnz8fFhZGZHTE9QdyYDEMPA8PDyUlJSIfgEG+Y8eOjo6O4OBgU1NTGRkZHx8fhn1sYDNU9NPX17eiooJoqjx27BiIiu7u7q1btz548EBISEhaWlpISOjgwYOQmRYWFgZjAPrl5s2bN2/efP36NRwpKChAWb96enoLFy4E/rl48WJwdsAgLy4u5uHhkZKS2rJlS1FRUVJSEtHkuXr1ajTNJ02atG/fPjQLHj161NfXZ2ZmpqmpCQlIgOzs7C1btiQnJw8Xj4JhWExMTHp6elpamoaGRlNT09KlS8EpXltbS8wwdHNzU1dXZ759z5498fHxqqqqdXV1ZDJ5+fLl6FR1dfWRI0cePHjAycmpra29du1aVVVVxOioVOr79++dnZ3l5ORgUQvCDu4lUmDGjBlCQkJoVvLx8TGrXj8NP7LFLjFt5m9Bb2+vl5cXitcfGZ8/f4a8ml8NbW1tKN3oT8XPpUBtbS0xXY2Fn4XIyEh9ff3MzMxXr15VV1dnZmZmZmZOnjwZQli/u9nu7u5du3atXLkyMzOztLT07du3mZmZsP5A+fowSOAChiQieA1ifvAoE6tGwJs3bzIzM4kpf3Q6PTMzc8jdC+Lj44WEhIiJiCg3OjMzE6VFEVFXV5eZmTkcjwIKQJosEU+fPhUSEoKkmpaWFjU1td9///2n7/OP0od+ECUlJZ8+fWJONBohsWqUqK+vR5mK34SysjKUKEtEamoqw7bnw6G0tDQzMxOljX0T3r9/n5mZORyjKykpKS8vR9lfxFFE3EXjF8H3i+eysjIdHZ2/V+AVFhYaGBj8d3ZIZ+G/AHZ2duadXnx9fU1MTDo7O7+7WcgkuXTpEvEg+HHR/gQ/go0bN8rIyOTl5f1JZJGWlj579uxfQH+w6IB4PnXqlKys7D99RH2feP7pGHL/IhZGwPfX7j137lxxcXF7e/sI4eZ/HioqKsaNG7d169alS5eiyBEWWPgXAPLxGCL88/PzPT09R7PZ5AixhEJCQgwtV1RUiIqKEgMevxvi4uL8/Py7du2Sk5M7efLkTycLWHH/VMq/e/fO39+/vb1dSUlJSkoKwzDYhPgfPZzAift3Pb2/v7+hoUFISOjQoUOjzElh4UeN2+np6R4eHmDr/+vXFFlZWbNmzdLT04PdZFhg4d+EoqKiuXPn3rp1C34GBQVpaGicPn36x1tOTU2dNWsWUnAzMjJmz56dnp7+c98/MTGR1Ym/DiCb4O/Snuvq6lRVVVeuXGliYsIyc34rvi00DMU9RURE2NjYgL/98+fPsDHnX4aEhISgoCArKysfH5//TvUSFv47qKmpWbNmDSRHcHJy+vv7i4qKjmYrq68iKSkpNDQUkly1tLTs7e2ZI55Y+NfgwYMHoaGh9fX1nJycIiIiw+1g+OeBTqfb2dmJiYmFhIR8dx2w/yy+RzyzwAILLLDAAgt/KthYJGCBBRZYYIEFlnhmgQUWWGCBBRZY4pkFFlhggQUWWOL5l8LAwEBjY+Nwm2L+c9Hd3f3582fW8P2no6uri7hr6S8C2B4O/v4ZaGpq6u3t7e7u/mot138f+vr60OasLFbJwn9XPL969WrXrl0iIiI/q7zXr4CSkpJTp04tX76cWBHvnws6nT7ktv7/erx58+bUqVMuLi7DlbT7u/D+/fuFCxeeOnVq4cKFf/zxx480NVx9QzExsXXr1rm7u2dmZn5fs6dOnQoODv5n9TiNRjt16pSvry9xv95fBC9fvty5c6eIiMgIRSH/xWhtbX3+/DlLPP91yM/PX7Vq1bx584arLfoPhbCwMIlEunXr1r/jc9auXWtvb19dXf0rv2RPTw9s6P0TISIi8uDBg4SEBOJBqNDwt68bcnJy8vPzz507Jy0tDUuoxYsXa/wP3t7eqCJCS0uLi4sLOrVy5Ur0/gkJCUuXLtX4/wFkzMjIcHNzgy3TvwNycnIBAQHbt2//Zw11Xl7e0tJStNn1r4OamhoPDw9NTU0fH58RyqL/i+Ht7e3o6Igqof064Pi3UnzDhg0WFhYODg4ODg7/pu8SEhLS0tIyNzf/1bSu78PcuXObmpp+ZDOsPxvp6emRkZHTp0/fsmXLzxXPly9fZig1v2nTJh0dHTc3t795zc7GZmNjAwX16HS6g4PDrFmzoEBFYmLi+fPnDQwMHB0dOzs7XVxcxMXFoSLLgwcPwsLCdHR0oCx3Y2OjmZnZtGnTiC1DXWp1dXVUqms0aGhoCAkJkZCQgJZlZWVPnDiBarf8g8TzuXPnGOp7/gqIioqytra2s7OD6iz/QcyZM6eyspKXl5clnv8KNDQ0/PW1Of8ycHJyzpkz598hnrdu3erp6Qlldn5NPH369Pr168Rq2X8Srl27du3aNR0dnV/hq1EJsubm5qKioitXroAmvW7dOvgHdH0REZEzZ87AJifr169HJbz6+vouXbrk7+8PBRx/EI2Njfv27dPU1ATxzMLPRVxc3E/ppn8uNm7c6O7u/rfsTv2VhfI3XQ3lskNCQigUSmVlJTq+b98+CoXCUAEXLq6qqqJQKCEhIUM2eP/+fQqFkp6eznD83LlzFArlqzbPurq6tLS0Q4cOMVSzr6ur+6qR8PPnz6jE+oEDB4bzPVRXV1MoFKi3yvBpTU1NFAqFWH5827ZtUD2TCKAAhUJ5+fLlcC8THx8/nABITk4+ffo08cjAwABU4R0BmZmZYKupra2lUChD2mZPnz5NoVAYvE1fvnyJjIwErTEnJ+f+/fvo1M2bN69cuTLk4+7evcvsC3z69GlOTk5qauoI78nNzf3q1SuopciA1tZWBtvvyIiNje3u7mamwAgjmRlv3rzJy8tj1nskJCR+lqYyXCzY8uXLRyi09xcDDXghIaHY2FgkkidPngyltYEsK1asANkM9gDkReLi4oKCgz8RxNKELHwfhhv2o0dZWdlfHyzy+PHj74gfolKpUDT2q+Di4voO2fzjxPw6RrPz55s3b1xdXY2NjcePHx8VFaWsrIxh2IsX/8femwdSuX3/488xHTIU0YmKDJdkLLnmTKmMEUWnNKg0SIMupbm40jynOLBScj4AACAASURBVJRZJUVFRYlCIqHoZM6YkCmz4/n+sX7v/Xs+5yDduve+732f11/P/Oxh7bX2WnvttV6Wl5cbGBg8ePCgsbHxyJEjkydPTkhISE1NdXBwoFAo06dP37Rpk6WlpYmJCT8/P4VC6e3thQ/29vbu2LHDysrKxsbGxMREUVHxyJEjOI5/+vTJ2tqaSqUmJCSYmJjo6OhUVFQMW6Senp5t27aZm5tDGldFRcUFCxY0NDTgOP7mzZvdu3dzc3OPGzeOQqGcO3eO6d2vX7/OnTtXVFR0z549MTExenp6c+bMERQUNDc3R/nyqqur582bR6VSlyxZYmJiMmXKlPDwcBzH169fb2xsLCYmlpKSAtkF6HT6hw8ftLS0qFTq7du3jY2NKRRKWloajuNdXV0bN260tLS8du2ara2tgoKCtbV1Y2MjjuNOTk76+voUCmXz5s16enpWVlbQRCgeck9Pz/bt262trW1sbLS1tSkUCopY29XVpampOXXq1JHSwigpKQkKCp45c8bd3d3CwkJKSkpUVPT69evwQH19vYWFBZVKXbhwoYyMzKxZs1DGPWlp6UmTJs2bN8/c3NzW1nbatGn8/PyhoaEpKSna2tqWlpZ8fHx+fn7oX69evdq8efOiRYusra21tLQoFEpubi6O43V1dQsXLly0aJGdnZ2NjY2dnd2wRb18+TKFQuHn5y8rK8Nx3N7enkKhUCiUw4cPz5o1y9bWdty4cbNnzx6JBmxsbCgUioaGRkpKiq6urpWVlbi4+OHDhxsaGiwtLW1tbaWlpSkUSnFxMXolNTXV1taWSqVaWloaGBgoKyvDr3Ecv3r1qqGhIZj4jI2N7e3toYKQMtbV1fXcuXMRERHDliQiIoJCoTg4OFCpVHFx8Xv37kVGRkJdUIfu27ePQqHw8vL29fWhjsAwDBIatrW1OTs7k0gkLy8vHx+fEydOhIWFwRfevn2L43hra+uKFSvgCoPBwHH8+vXrcJqdnb1u3ToKhQLZ+goLC1VVValUKiQgT0lJgYyNQUFBc+fOhevGxsYpKSnD1uXu3bskEuny5cvD3i0uLl60aFFPTw/rrf3792/evLm7uxvH8b6+Pi0trePHj3t4eEAhIyIiPn78iB7u6uoCtvtN5lNVVUWj0TAM09HRSUlJWbduHY7jUVFRfHx8KSkpc+fOpfwHSUlJ8MrQ0FBKSoqlpSVqBBTAnIj+/n4vLy8KheLq6kqj0SgUiomJCYVCsbCwAD6QlpYGX/b394dXAgIC4EpCQgKQE5xu2rRJTU0Njvft2wcUOGvWrBkzZkDd0U9FRUWvXbvm5+cH/6JQKGvWrEF5Qul0uqamJhQbCPvLly9VVVWampoUCqWwsHD58uWIBjIzM2fPng0Py8rKsjI6QHd3t7u7u6ysLJD97Nmzzc3NgVX29/d7enpyc3MD89HT02PK4djR0WFgYAB/jI2NpVAo1tbWCgoKFArl6NGj8MzHjx9v374NxZgzZ46JiUldXR38F148cODAnTt3UDeZmprCAziO19bW3rp1C1V53rx51dXVOI67ublRKBQZGZna2lpDQ0MBAQEYRyYmJtT/gEKhPHr0aNgqnz592sTExM7Ozt7efu7cudnZ2XC9pKTkwoULhoaGVCpVVVWVQqE8fPjQ09MTCoaSYBYXF6OGVVRUXLlyZVtb28mTJ1E7LF26VFlZedq0aRQK5dKlS39ezO3vSIlx584dLi6ukpKSsrIyGo329u3bWbNmaWhooAfc3d3NzMygYxwdHWF1DfKzQk5yFNb/0KFD8+fPb2pqQi/Csamp6bZt29AH1dXVZ8+ePWzOyn379i1cuBDlTM3IyODj4zM0NBwaGnr06NGKFSswDDM3N6fRaMNm8SwqKpKVlVVVVT1//nxBQUF9fT2NRiOTySYmJjiOd3Z2amtrS0tLo+fFxcX19PR6e3tTU1OvXbuGYZipqSmNRrOxsaHT6Tt27IAXcRwfGBhYvXp1cnIyjuM7d+7EMAylzk1LS+Pk5Fy4cCEM7JMnT2IYtmjRIhjqEREROjo6KPNubW3tggULoILg4IrGQ3d3t66u7kjiGTgshmEiIiI0Gq2lpeXVq1fCwsK6urrAOsPDwz09PeHJN2/eiIuLHzt2DE5DQ0PnzJmDYdiuXbtwHE9ISLC1tcUwbMmSJQ8ePMBxHIKcox9pampaW1tDF9fV1enr6y9evBjH8eDg4L17934zkVxhYaGPjw+GYSAja2pqdHR0wEz6/Pnzr1+/gt/ASIlP7t+/b29vj2HY4sWLIQ0DLA97eXmFhYWBAIOvoVcEBQVdXV2ZaKC2thbHcQkJiatXr6J2gIoQW4BGow2bxfbu3buqqqo0Gg2ad8uWLbGxsR8+fDh9+jSGYTk5OSiPy44dOzAMG1Y8NzY20mg0fn7+tWvX0mi00NDQ9+/fy8vLYxgGjOnTp080Gg0W6UE8v3///pdffsEwjEql0mg0ERGRS5cu5efny8jIpKamwi+gBUDAm5iYvH//Hq6HhYUlJiaOIp6Z8k5WVla6uLi4uLjIy8vb2toSb3369AluKSkpwSQbQKPRhISEaDSar68vaAJnz579A+K5oKDgyJEjsORMo9GAI4OBx9DQkEaj0Wi0w4cPYximp6eHxDOGYb/99htKpygsLAwETERvby+NRpOVlcUwzMfHh0ajlZWVzZ07FwxFOI4nJSUtW7YMIyT+iYqKgtUHkPdJSUlOTk4YhtnY2EBJYMh7eHjQaLT09PTo6GgMw+Tl5Yni2cDAICgoCLiogoICooHS0lJFRcXY2Fh4EkxHz549Qy1gaGi4fPnybdu2YRiWmZn5yy+/vHjxAh4+f/48cd7MmhLjwoULKA8KmUw2NjZGLSAjI2NpaUmj0QoLC4fVzcCBwNnZmUajdXV1paenb968mYODIzg4GMfxM2fO/PLLL/Dwy5cvBQUFYZo4MDBAo9FmzJihpKR09uxZ2n8gICBgYGAwMDCA43hgYOD48eOR+JSWltbW1u7s7Hz27JmrqysXF5eurq6Xl5eDg8ObN29iY2Pnz5+PCrZ+/fqRkq8ICQlFRkbC8cWLF6GVqqurlZWVT5w4AaMAVA7oBRkZGQzDioqKQDbLy8vfv38fXgdfgZcvX+bl5e3fvx/DsBkzZtBotJSUFNiYMGnSpP8i8YxOwb5aUFCArty+fZuHhwc0v9WrV6M+w3E8Pz9fSkoKNJKKigoNDY1r164RR3J7e3tOTg4HB8edO3eIHYBhWHl5OVNJysvLFRUVvby8iBfnzZuHYRgkcv/w4YO8vPzu3btHqQ50PHA61BMcHByvXr0CW+uzZ8/QLegJyHl+7do1Hh4eGo0GJMhgMHbs2KGsrBwbG5uZmQkXId33nDlz9u3bR/xFZGQkDw8PqJgnT54UEBAARgBYuXIlEs9DQ0P9/f1w/PnzZzMzM5DrMOdds2bNKOK5ra0Nw7AnT56gK3Z2dmCxxHF8cHCQmI185syZSDzjOL506VIqlYoeOHLkiJqaGowlHMfj4uI4OTlB5Fy4cEFQUDA6Ohq96+LioqWlVVlZqaWlBUZR0PiRQBpWG0PiGVpgypQpaLgODAyoqqqOkpfM399fUVERFe/+/fsgrlC7KSkpqaiowKmbm5uFhQWx7nQ6HcMw4CYSEhIbNmzIyMiAJkIK4pEjR6SkpGDosqK0tJSTk5PI1zIzM4EMGhoaiOIZEkaNJJ5BlPLw8ISGhqLnwThPzKC8d+9eJJ5xHAfuD7/o7e0dGBgQFRXV1NQkqp4YhgUHB0dFRfHz82/atAmI6tmzZ+i/rOKZg4MDqoBQVla2+D/g5uaG2Rugrq4O3eLj43N3dx8cHOzr63N0dAQ6ZzAYPT09MjIyXFxcaKo9dvEMEgLDMDBfITEpICCABgiDwfjtt9+QeF65cqWjoyPq6IGBAUVFRaQBM0FHR2fXrl2oSfv7+8eNG4dGJZ1Ol5WVJeblW7t2LRLPIJz4+fljYmLgNDk5GcMwYHQwiv39/ZnEc2BgILApJDuBROXl5dXU1Do6OpDmirgQtIC2tjbwlp6envT0dBkZmdjYWFBsGAwGGgVMMDQ09PT0JHKhW7dukUikV69ewam2tjZxMs0KMBMSWX1WVpaEhMTq1auheZFZFMdxWONAV0xMTOTk5NAAh4RmMEi/fv3KxcX18OFDdAs28oFOEh0dzcnJefHiRagag8Hw9vZWUFCIjY2FEcTEx5jEM1LzEhMTQR7n5+djGFZTUwPXBwcH0XwxLCwMieenT58iVg88BEQyjuO5ublIdYHOvXr1qpCQEGiARUVFHz9+LCkpyc7OzsnJGalsf1G+Z8DevXtRHpK6ujoymTz8EjcHB1qyevLkSV1d3erVq9FdoPgLFy4MDQ2dPn0a7Rrq6Oggk8msWUKTk5Pfv39vbW3NtLyfkpJy6dKlLVu2PHv27JursxiGcXFxoVJh/3ErRfDz80O7IJqamohVExISgjLDYtvq1asjIyOXLl06efJkbW1tQ0NDNze3e/fulZWVsf6iv78/ICAA7HWsyM7Ozs3NBRWWwWDs3r3706dPLS0tT58+NTMz+66uIVbHzc0NkswD2traNm3aBMm+amtro6Oj165di1LZcHJyEvdXcHBwDLszjcFgDA0N3blzB8YbSJqqqqo3b95s3Lhxw4YNDg4OxsbGwsLCp06dmjp16h/Y3sbUeiOR1khfFhUVXbp0aWxsLMzbent7OTg4iFWDJjp37tyaNWtgypWQkAAa/K5du5hSI4+0NsRgMIhNDa//AVCpVA8PD+KVoKCgsXc00Cf4f6Bl2u7ubjKZHBAQkJOTs2fPnoCAgNraWm5ubj09vc2bN4+9bLKysrdv34Zjb2/vY8eOTZ06dcuWLRiGSUhIoFt+fn579+49fvw4Ly8v2t3LwcHBy8u7Y8cOd3f3H/SIJJ6SSCR0hUgDDAajt7c3Kytr+fLlqK+bm5tH2TJ0//79LVu2gHsBNzc3keFwcnIyUeC6deuAmxNLgv5OZHRMhSRWBP2Ch4eHi4sLem1gYICPj2/Dhg1wd2BggIn7bdmyBX7EyclpYGCgqqrq4OAA63RTp049deoUa9VgqsTKhUDhDg8PH0vLb968+dWrV0Qi19bWRnTOxcXFYDAiIyMfPHhAIpFYI+1YW1uDiQLAy8vLwcEBVR4cHPTz80Pt2dLSQmSzfHx8bm5u0KowQK5fv+7g4GBlZcXDw6Orq7t9+/aRPFouXLhQU1ODYZiZmZmJiQkYb4iMgpOTE+wQTIBU5S4uLvBwX18fUy9AkYidC/W9efNmYmJib29vW1sbBwfHhw8ffnyX2o+K5xMnTsyYMYPpIi8vr6qqKjHmgIqKiqGhIfKm7u7uzs7Ohp0bCAYGBuHh4R4eHmBO/GOAtjMwMCASxNhBIpE0NTUhINehQ4fGyGpVVVUbGxuvXbv2/Pnzp0+fxsXFzZw5k0wmf7N7gHMRr2hpaYFsjoqK8vf3X7RoUWRkJIzM8vJyeKanp+fatWvf5awEBnnknbR27drg4GBYAlBSUpKTk2MqxuhAu2K6urpmzJgBpkUm2NnZ7dixo729PS4uLi4u7syZMyONJVZh84NJQsE+CaMdOZeVlpa+ePECrMHDorKyMjQ0FJwGrl+/npaWhhzWOjs7q6urZ86c+ad6gdy6dQt0SiIxHz16lHjl8uXLxNOioiLW7+Tk5AzrhPjw4cNjx46BQhYXF+fr6/vly5eR5hxFRUUjEf+vv/5KIpGG3Qs3yoRmLHOdMVLd6Hj37l1ubi43N7e3t7eamtpYXrG1tR1pNPX19TEJGxqNxuQDO3nyZFhkwTBMQUHhu+ZnEyZMsLOzQzsXCgoKnjx5MlLOR6bujoyMhBlSYWFhXFxcbW1taGgo0+6g9PT0iooKY2PjH2l5JqpjLRWslJ8+fXry5MkpKSmjKxKKioqgw8CphIQEsLhvQllZOS0tDUZEWlpaXFxcQ0MDLBEy4fPnz1evXs3Ozk5OTo6Li/P396+qqsrJybG1tRUWFh69gjk5OWBR4+fnH4mXHjhwAJ329/eXlJRoaGjMmjWrurqayNv/as9tIjg5Ofn5+ZnYB3L7ZPJqe/v2bVpaGpoTgYBhovJ169ZxcnKCYXZ0WFpaKisrd3V1MX1hlDnvGL1Vx48fT9Sex/hiQEDAly9f1qxZExIScvv2bSEhoUuXLs2fP19aWvrr169Mw5uHhwcWqGDaxeQTDtozaE4LFy6Edbv+/n4ib+Lj41uzZs0o5bl06RLTFVdXVzgYGho6evTouHHjQDYDhIWFv2uiB+Jz3Lhxw6qtsB7Jy8sbEhISFhaWkpLCtLt3dHR1dX3XplhWoHCnwsLC8+fPR3zTyMgoKysLjFdEQKf7+fmtWrUqJCQkODjYy8urs7MzNDQUjcDRNwKMkVSY+poJVlZWTDKPtR+ZsHTp0jG2SWdnp5iYWEhISEhISHx8/DdjeqCR5ePjg4KQEK0aLi4uvr6+TM2CBi9rg7S1tQkKCrJawohsbvR+H+OkTU1NTUtLq6uri+jG/4chJCQ0kkUQ4dOnT8h+UF5e/vr167F/v62t7datW2h4jrFTYI7OwcEBHRobGxsYGBgXF8ca6Bdsy1FRUWBFJ+ohu3fvHmMhiVwR8Pz586ysLE9Pz9bWVjs7u56enpCQEEgcztr1TIw6IyPj3bt3qMrD7toYFsHBwbCwDTTs7e09rHmpo6OjtbV1w4YNISEh9+7dQzab8ePHx8bGMrUDMg+gY29vbyIlf3PQMRgM2BezaNGiEAJ+UMf4UfEsLS3t5eX19OlTRI6lpaXnzp2D0cs0GwXtGY6XL1+ur69/9epVf39/1s+6urrC+g3w2ZcvX7I+M3XqVCqVeunSJaLffGJi4sKFC5H9vKSk5JtVyM7ORsSRnJzs7++fkpIC2r+RkVFmZiYyANTU1Jw+fXqk2UBpaSmKHqympmZubg5KvLm5+cmTJ4lMNjEx0crKCm0P7e7uZiIXpD3DxgBY+Thy5AhR/YXJzTdNCCMBNVp7e/vp06dbWloaGhpGqtqw0hdWNNevXz9r1qysrCyiEpaYmNjX1ycuLv78+XMMw/j5+U1NTb8r6siECROY2EFGRsbogm0kJaO9vZ24Z8/U1LSjo4PYdImJib/++iuEr0JvcXBwgOs7+GzDQhRxXsxUWm1tbeIoYALavJeamjr6pColJYVJokA/oi88ffqUKVwzrLUTYW5uTnwFwzDwpfD19UVGKRUVFSUlpdFtSCicyNDQEOjcrANt3LhxRDUCCmxmZsbJyVlQUPD48WPiLR8fn/v374uKig77x4yMDE9Pz+Dg4D+swzE1QmNj4xgtt6Nj2rRpRGq8evXq27dvWU2paAIqJSWloqIy9u+np6fv2LFj0qRJw/ZdYWEhWGgRy0XHd+/eRUsh06dP19bW1tPTG3Zjnrm5+cePH4mGmcTERBKJNDoNME0cma6EhoZqamrOnDmTi4uLOPl+9uwZaJ9EBAYGEoM0uLm5nTt3jpubm4uLa968ednZ2UhzAyJHo6C/vx/JApj6IPpXVlauqamBFmPC48ePYeURwzB1dXVwvkP0MyxvJJKWsrIyhmELFiz48OEDXMnLywM/kmEHHVML/GSMcY06MDDQwsJCQUGBSqUiH4G6ujpDQ0MVFRUrKytLS0tzc3PYj3Ho0CF5eXnY3VFfXw8+urq6ulpaWqtWrQKHi8OHD48fP15DQ0NDQ8Pc3BzcknNzc52cnERFReG6hYXFSG7r9fX18vLyVlZWdDqdTqfv2rXL0dERfArKysrMzMzk5eXnzp378uXLUVzDREREwPlcX19fT0+P6ODT2NhoZmYmLi6OSnj8+PHBwcFdu3bNnz9/5syZoaGhyJ/Cz89v9uzZV65codPpGzZsWL9+PThh9fT07N69e8KECWfOnKHT6ceOHXN2dgZvqbNnz4LPiJGREfL98fLy0tLSAhewFStWiIqKwoaxlJQUNzc3TU3Nmzdvtre379+/H2p37dq1Dx8+MNUrKSnJ0tJSXl7e3NwcuWumpaVNmjRp37597e3tZ8+eVVBQgOb19PQ0NjaWl5dfu3YtjuNLliyZOXOmkpISeFdlZ2erqKioq6vPmzcPnHoeP34sJCREpVLBoePp06fy8vLQhhoaGpaWlu7u7r29vbDfCbrmypUrtra2aMcaEeHh4bNmzZKXl7ewsIiOjs7MzFRSUtLW1o6Pj4eNH+CWIi8vj5zFiMjLy1NRUZkxY8bx48f7+/s/ffoUHh4uLy+vpKR08+ZN1DXS0tInTpwANyIajSYoKLh161Yom42NzenTp+FJeXn5y5cv0+n0oqIiVVVV5KJVV1eno6MzdepUAwODYV2Z6urqtLS0pk6dqqGhceXKFeA44FQiLy8PRK6np3f16tULFy5gGLZx48b29nY6nb5ixQoxMTFTU1O0AUFJSWn69OlGRkbg7fXp0ydRUVFeXl4g0aCgIJj+FhcXwxeWLFmCYVh8fDydTocKtra2rl69WkRExMDAgE6nr1y50tjY+MOHD3l5eZKSkpcuXaLT6cXFxaqqqkTfzFFcw8rKysTFxe3t7aHFdu7cSaVSYftNY2PjpEmTHjx4ALfOnTu3dOlS8FQqKioC30A6nZ6amjp//nzwuRvJc3vfvn28vLzgbz/s1qA1a9bw8/NraGj4+fnV19efPHmSg4PD09MT+Rzt3r2bn5//woULg4ODQ0ND8vLyQkJCGhoaCQkJx44ds7e3h/0RRAwODtLpdHV19cmTJz958gTtKeLn55eTk6PT6eAftGjRIsQH7OzsXF1dSSTSuXPn6uvrq6urvb29J0+e7ObmVlVV1djYGBISQqFQhIWF0WaqU6dOkclkPz8/2L4oKSmpqqoKXzMxMSH6Hnd2dm7ZskVYWFhDQ8PNzW3Dhg1mZmbZ2dktLS2PHz8WERGRk5ODCoKDlZCQkJeXF51OP378uIWFxZUrV4ZtvZqaGhikJ06coNPpnp6eTk5OQGA1NTVhYWGTJ09WVlZGTuAjuYYpKSmhYQ6TcuTSSCRyPz8/ISGhwsJC8HGDdV9FRUV4gEqlpqenoz07nz9/trKyAnbh7+9vZ2enr6//5cuX+vr6U6dOTZ48eenSpaiLvb29Fy9eTP8PFBQUhh2PwcHBoqKiISEhdDr99evXEAIZSM7DwwNKoqGhERwcbGxs/Pr1azqdPmfOnIkTJ96/f7+lpaW9vX3Dhg0SEhIyMjLbt29fvXq1iopKfn5+U1NTbGysmJjYihUr6HQ6uNrFxsYKCQnt3buX1X/5p4CE4/gPCvhHjx5JSEgMDg7CfuixIzAwEGYlCxcuROvQ/f39yGDu6uoqLi4+yheuXLnS2NgIx7t27YIF1Li4OBSdjnjMBD09PSMjoylTpjQ1NUlJSRFd1QCtra0oHoiHhwfMTEf6+KlTp8AGyMXFBe61CBcuXAD9ctGiRSiPRWdnZ1ZWFphemQqJTjMzM5OTk42NjdFi6p07d+Tk5Hh4eGBKmJGRISsrCzYl4joCmUyWl5dva2t7/fo1xAP6+PFjU1OToKBgf3+/iopKT0/P8ePHXVxcpk2bRvwpnU4fHBxkMBjAoYKDg2VkZIyNjR8/fqyjo0NsAWKZL168CFY1GxsboIE3b96gRV8jIyNkOGFCVlZWXl6em5tbbW1tXV3dxIkTu7q61NTUYmJi+Pn5wfWP9XcI169fnzp1qqqqakBAwLZt20DJplKpb9++TUxMBPvtixcvxo8fHxcXt337dlCDbt++DX6w4ACCWuD06dPIN0JVVRV83QENDQ2BgYHS0tIjhdusr69HdjZFRUWi+SsoKKi+vn7KlCnr1q0rLy+HRR+okYCAgI6ODrGLy8rKIiMjlZSUUCTajIwMsOhMmzbNxcWltLQU9hTBF4hl2LZt24QJE2DCDftwwKAHS/4pKSlEXxCmChIRHx9va2u7cuVKsO1/+fIFZhUIe/bsAcNdV1cXceVvwYIF2traaNXm999/R7dYaaC7u5ufn//p06ewLLp///7k5ORhTWVIqQJ7jJeXV1JSElJhUQWfPHkCsYkQH4iKikL+oZs2bQINlQgYBejUzMxMV1cXw7CjR4+CMWz58uVycnLEFgA+4OfnNzAwoK6u3tHRUVFRAX0hISEhKSn58uVLGxsb0ICBD2RlZYEhAWggLi6Og4OjoKAAw7DZs2cz+bdiGHb8+HFQH3l4eMDQmpGRUVBQMGPGDDExsbi4OC8vLwgFEx0djWyEGzduRIHeRlqAQwGUdu/eDRb7yMhIERGRnp4eUVHR9+/fjxQn9fjx47t27dqyZQsYP9AwZyJyCQmJ9evXw+aO/Pz8pUuXKioqmpqa9vT0QNhXaAHWZRfYgghmUVB879y5U1hYCA0rJCQEOxJRFwMOHDgw0lqJv79/X18fHGtqalpYWKBbVVVVaNFKVVV1wYIFJ06cEBYWVldXT01NRTRAp9NRTHhQmdLS0p49ezZ//vzMzMyvX7+iURAeHl5RUTFx4kTwA/i5+Ani+R8KEM9EJsIGG2zEx8cvXrz4xYsXf9gFfSwgiudHjx55enpeu3ZNQ0OD3f7/hbCxseHk5AQt+XvfNTU1VVNTQwKYje8CF7sJ2GCDDSKGhoZcXFzi4uKQk8TPRVhYGNEL7OzZs0FBQWzZ/F+LxsbGV69eNTQ0/AHxzAZbPLPBBhs/B2JiYrAx5sCBA1ZWVsg/7ifizp07g4ODZmZmsMvlxo0bKHYCG/+dsLW1HX2dkY0/A/+Lxu2uri43N7fExMTJkycvWrQI4kqywQYbbLBBRGdnp7u7+4MHD5qbm21tbV1dXYd1lh4W/f39rq6ujx49EhERsba2HnafDhts8cwMcNr8/+pPiPjDBhtssMHGsKwSwzCmoHvfFM9BQUGwv/ny5cvDhuhigy2e2WCDDTbYYOMfBg52E7DBBhtsCXaB+wAAIABJREFUsMEGWzyzwQYbbLDBBhts8cwGG2ywwQYb/zSwvaJGQ1NTU1NTExyLi4sPm+3kR9DX14fyUPHz80tJSf019WIwGB8+fODm5h4lgxNCT09PZWXluHHjpk+f/k/pOKjg9OnTvyvc98/C0NAQnU7n4uKSl5cnXofY3YqKiqNkhviXoaWlZdy4cRDl6p+IL1++fPr0CcMwXl5eGRmZbw4TOBYUFETR6P4alJeXjx8/fqSQ5n8ePn78SCaTmQIX/nkoLS0dGBhQUFAgeqgNDAyUlpbKyMh8V9q9saCtra2xsRFF7f4nieeWlpYzZ85ISEh8V+LYvwxBQUFSUlIoYdEfw5UrVw4cOLBgwQJ9fX1LS0thYeHBwcFDhw6hB4yNjSFqJqCoqCg6OhqOdXV1icHkAAcPHnR0dESpCTs7O+Pi4mpqagIDA4OCglgj3v0ZyM/PDw8PP3369PTp04fN30JEampqRERESEiIkZFRamrqP4Kl7tu3r7e399SpU8+fP9fX1//rCxAREbFq1SoKhQKcHcOw2traK1euVFRUREdH9/X1MWUWR/j9998tLCy+Nzjufydyc3Pv3r2bnZ09a9YsYuzMfxYiIiK2bdtmZGS0YsUKEM937txhSn8iIiLi4eHR2toKuQu7urqio6OdnJy++WV+fv6RQqt+F6P7+PFjfHz8lStX/krxHB0dXVRUdPfuXcgj+Rf88fHjx0uWLOno6Pjy5QtoSr29vb6+vu3t7RcvXiwoKFBVVf2Jv4uJiYmKisrKykIa2t+AsYfnbmlpQYHyIZy6jo7O6tWrR3+rs7MzIyOjqKgI/2uhr68/fvz49+/foysvX75EodjHiJCQEF5e3hMnTqArmzZtEhMT09HR0dHRERAQmDBhAgqGXlpaqqKiEhMTU1FRsWrVKiEhIQjF3tHRkZGRcfXq1Xnz5nFwcMTFxTH9JSsrC8OwQ4cO/TUt09nZ+fbt2+nTp0+fPn3YBxobGzMyMioqKnAc//LlS0VFxbp164yMjPB/CCoqKtavX49h2PPnz//6v587d+769esVFRUfP35EF3t7eysqKiCwfF9f30jvTpw4EaXigLcyMjIgMcM/Dh0dHdnZ2RiGnT17Fv/H4ty5c5KSkij9A47jEBRaTk5OTEwMomjJycmhu5C6uKen55tfXrRo0bp16/5YqUpKSlAunLq6Ok9PTxkZmZqamr+yZT59+nTs2DEymUyk2D8PdDpdRUUlOzu7oqICkoLgOM5gMCoqKpYtW4ZhGErU9LPQ2Nh44sQJUVHRv5H8vmPt2cXFBeVmwDBs6tSpmZmZo2c2xDDs/fv3enp6eXl5f/G0Y/v27b6+vmJiYmgqZGBgQExPNhZMnjyZaDCBZOlRUVGZmZmZmZnHjh1ra2tDuRCOHj0qJyfn6OgoLS19+fLlefPm7dmzB8Ow7u7uvLy8/v7+8+fPj7LHevQskD8RAgICMjIykpKSIz3w8OFDMzMzyGQnLCzMxcUFKaj/KZCWlv4b1TUvLy8BAQFpaWliC5PJZGlpaZSpYiT4+/tDdiDAyZMnDxw48IPZr/8uCAoKQgsQUxn+E8HNzc20qnXq1Kn79+9HRUWFhoZeuHCBmFWTNfHGSFi/fj3Ile9FUVGRlZXVwYMH4VRCQgLSWiBTzV8DCoUiJiZGIpH+mvUjGo3m5OT066+/SktLI8s2BweHtLT0jBkz/ow/Tpo0CYmPf4Bx28HBoba29o/95geNzH8A9vb2xNO0tLQJEyZ8b1y6qVOnEpfNurq65OXl582bB6e2trZnzpxJTk4+evRoWlpaREQEap9x48bp6+u/fPmytLT0l19+GUsyk0uXLqEh92eDk5NTWlp6pBzGGIbx8vKiqRg/P7+EhMQ/S0gQc2z/lSgsLBwaGvrDpWJa3UhOTv7111//dh7xg0Bpo/412Lhx47hx435wSdLS0vKPvThhwgRWI3Z3d3ddXR1KFf+XgcFgQLa6PxvJycnERHBEoExc/z58h/YcFhYmICCA/Sd59cGDB52dnffv309Ur53/A0icNyyePXvmTADTpO/MmTPoFuQEhF+fOHECjk+fPo0e+PjxI4ZhJSUlzs7OXV1dly9fdnZ2fvPmDYZhzc3Nzs7OxGTmWlpaRkZGxH/Fx8fDd3x9fYct6t27d4mJuHV1de/du/f/tx0HB5o5Dg4O9vf3Q/sg1NfXQ/q/sWCM2vPKlSuhzFu3biVev379OmT3g7vXr19nfTcvLw/uZmZmoqxqY1z+YOpi1qT0bm5ucOvVq1fDfuft27fOzs6Dg4Nnz551dnZmnbJs2rQJkgYCvnz54uzsXFVVha4A4WVlZcGP6HQ6hmE1NTVwCokXAUTfK29v72G7+PHjx/AiUwJQ+EtnZ6ezs3NZWdmwdUlPT4d3f/vtN+L1s2fPDgwMjDjYODjQY8O2QEFBAbEFWFFQUAD/Bev9SMjIyIDHUEp5ptq9ePECHkAZCYkYHBy8evUqhmGPHj1CLRAZGdnW1gbHAwMDgYGB7e3t4eHhrDQA2RiZCLu8vNzZ2fnYsWOjcxjI6bly5cqR/DA2bNjg7Ow87ERn+/btzs7OxByXRMTExDg7Oz958mQsNPAXoLe3l0ajsXYNdPHFixe/62vTpk1btGjRhw8f0ABneuDjx49w6+nTpyN9JDo6GrFWWJgAfPr0CV1HNMDKAwHv3r2DJ3NycoicEH1hFBooLS1Fj40yzWU1B6Ljbdu2DUsDCQkJo7D6Q4cOwd0HDx6M8qPKykpnZ2eU73hgYACVlokP/DSM0QgeGBior6+vq6tLpVLXr1+P4/jevXuVlZWDg4PRkoytrS2DwWAwGHv37t2+fTuO4wcPHoT0meLi4lQq9cyZM93d3bKysoWFhQwGo6amRklJqbS0lPgjBoORnJwsJia2c+dOSHmN4/iWLVsWLlyIHrh8+fKUKVMYDEZ1dTWVShUQEFi1apWXlxfU6MaNG1QqddKkSdbW1q2trTiOI4LQ1dUlkUgPHjz48OHDuXPnlJSUPn78yGAwHBwc1q1bBwntiSgsLBQXFyeuPRMBakFxcTGO4yAburu70d0HDx6IiIgwrSjz8PCMtPb8zXXxxMREHR0dJycnJyenOXPmiIiIvHnzBsfxmJgYyGGgrq7+22+/OTk5geVASkqKuI4yb948BweH9PR09MCyZctY/5KWlgayjUQiCQoK3rx5s6WlxdLSUlFRcdeuXU5OTjCHFRMTQ6+cP39+9uzZPj4+DAbDyMiIm5v75cuXxG+WlZVRqVReXl5XV9eTJ09CFSZNmkQikXJzc3Ec3759O+gi169fx3G8p6eHSqVC/tq8vDwcx7du3SovL6+mpmZgYIDKP3HixKioqA0bNjg5OZmamkLPwh/v378PgkFJSQl+N27cuLVr10IXV1ZW/vrrr8uWLXv//v3t27eFhISWL1/e1dUVFBQ0d+5cDg6OqKgocDNZsWIFU/tUV1fr6OgsW7bszZs39+/fFxERsbe3b29vx3G8oaEBshqTSCQSiZScnMz0LlhH3Nzc9PX1UQu8fv0aVhOpVCpayevv70fyCb5WUVGxZcsWe3v7tLS058+f29vbb9y4kbX76urq9PT0li1blpub+/DhQzExsUWLFsEo2LJlyy+//DJr1qyIiAhpaWknJ6fZs2dPmjQpPz+fdcFVW1ubRCK5u7tfuHABLnp4eJiYmMDx2bNntbS0eHl5ob/evn3r6+uroaHh4+Nz+fJlLi6unTt3QoNgGObr62tvb29lZeXk5EQmk0kkEtPqe21tLZVKhWzibm5uQORTpkwhkUhHjx5Fj2lqalKpVOhNYLjo1tWrV9XV1Q8cOECj0ebOnQstRiaTQ0JCOjs7HR0dhYWF4+Pji4qK5OTkNDQ0qqqqYPUXaCA2NnbBggXHjx8fdu1ZVlaWeGXt2rVubm6k/8Dc3Ly5uRndheUztPYMZJmTk8P0WWdn52nTpsHa8/379y0tLUkkkpyc3IIFC+zt7Z2cnGD0sZYnJycHSSMSibRp0yYcx0FgODk5ubi4ODk5GRgYkEikjIwM5Gvi6OhoYWFx9+7dd+/eEVuAiJkzZ6qrqzc1NTEYDFNT0xs3boD3w8qVK+fPnw/NrqCggGgAXHNERUURl25ubrawsLCzs3v69GlmZqaMjAzwgffv36upqd26dYvBYFy7do1MJl+7do3p721tbXZ2dtbW1omJiXl5eU5OThwcHLt378ZxvKuri0qloipramoyeWN4enoC5airq0M5ubm5t2zZgh7Q09ObOXNmVVUVsHoSifTw4UO4de/ePQUFha1btzIYDA8PjxkzZigpKZWVlcHd69evo7Xnt2/fKisrOzk5gSPC7du3yWQyyLv79+9raWn9GWvP3+EaFhUVpampiU4bGhpUVFT09PTg1MXFBfGjxsbGXbt2wXo+TNaSkpLg1pEjR5ydnQcGBuDUx8cHtQURhoaG7u7u4ALw/v376dOni4mJPXnyBMfxoaGhM2fOnDlzBj0M+5Gio6MTEhISEhI+ffoErmFIPCcnJy9cuJCLi+vmzZvwwMWLFydNmoQcx549ewb2gO8SzyAYOjs7f4p4rq6uHr39Hz16FBUVBceVlZUzZ8708vKCU1C5NDQ0wD2kv79/48aNU6dOBTbR09NjZWW1adMmNP/48uULmUy2s7Nj/Utubu727dsFBAQSEhJSUlLAJdDCwkJZWRmGNIPB2LZtGyx3AVUICQkhJl5fX6+jo7NmzRrWL4ORNisriyhBQTwjvgPsHgAp3EE84zju5ubGycnp5eU1NDTU39+/adMmDMMWL17c1taG43hmZiY3N7eFhQXx4/7+/jB5wnFcTk4O9IChoaHAwEBxcXH0o+DgYAzDamtrcRy/e/cuhmHGxsYJCQlubm7Z2dlMtdDV1QWuAbh58yYPDw/w2c+fP9+8eZOLi2v37t0JCQmfP38eVjzHxcXV19ejQhInScg1bGBgICEhQVlZ2c7ODqg6Nzd3+vTpUEgcx9vb27dt28bayEZGRiAaAXfv3iWTyatWrUIUy8XF5e3tDa165coVTk7OPXv2sH6nurpaXV3d3d0dDQQZGRkDAwOQrENDQ5cuXfL39wd68Pb2lpOTQz6Se/bsIZPJSDxLSEgkJCTAMAFB8vvvv7P+EbYzREZGwkDIzs52c3Pj5eUNCQnBcfzGjRvW1tboYT4+vrlz5yIHOmVl5ZMnTyKGi2HY3LlzExMTcRwvLi7m4eEJDw+HuwUFBby8vNHR0U+ePJGXl0dyND8/f1gXNlbx7ObmBuSRkJCgra2NYdiSJUtGEs+JiYmCgoIwAxvFNayjo2Pp0qUKCgoJCQnQwl5eXpycnGhYETnSkSNHuLi4DAwMEhISwB/q6NGjHBwc69at6+rqwnE8KSmJi4uLSqWiAjs4OMAMktgCTF9euHAhcuC9d+/e7du3QeI6ODggzzgPDw9EAyCe0YSyt7fXwcFh7dq1vb29cNfOzm7atGn5+fmnTp1SUFBAPzpx4kRERAQr2yGTyeCOioQuPz9/d3d3d3d3QkLC9OnTnZ2dExISiM8A3N3dMQw7f/58SUkJXAEPgO7u7qGhodjYWAUFBcQHmpubFyxYsHDhwv7+/v7+flNTU6Igf/funbCw8Llz54aGhojiuaysTEVFhdhoOjo6oIIi8fc3i2dra+sFCxYQ5ztWVlYXL15E5VNXVw8ICAgICCD6EIKps7GxEU7BaLN9+/aAgABW/oUATjTARI4cOaKnp8fDwxMWFgakrKioiHoCiWeQxETPbXV1dcTONm7cqKKiAm/19vY6OjqKiIggJQ/Es42NzbDFGFY8gx8/msKziueCggJJScmxi+djx46NsSMSExMDAgLk5OSYxDMSTjiOg/UPBMmuXbsmT56clpZGdAl2dHQcyXM7NDRUREQEnX78+FFVVZXouQ3+gFu3bsVx/NChQ5KSkkQNbPHixSOJZyMjIzQzq6+vJ9Y6JiaGTCYTxTPY54niGVlQcBwPCAgAPyyiUz1qgVOnTmH/13M7LS0NwzArKysGg4FhmIeHB7oFqyHw67t375JIJBAJw4KPj+/mzZvEK8QWCA0N5eDgiI2NHfZdR0dHjOC5DS0wY8aMkTy3DQ0NPT09kQVCSUlp5syZAQEBwDuGtXzw8vJGRkYSL/r5+U2ZMgWaccOGDVZWVsS7Ojo6w4pnHMfnz59vZGQEk109Pb0NGzbw8fEFBQUB/SCWB+ZxYkfExsYSxTNoeICioiJ5eXkHBwfW38EoIGqi6enp4uLiqAUQUlJSXFxckHJ59OhRCQkJJAJBPCOrnq6u7oIFC1paWtDrAgIC0dHRWVlZ06ZNMzQ0ZBUVo4tnItrb23V1dYme20zieeye2/v27dPW1iZqyVJSUq6urqwvVlVVaWpqOjk5oStMLYDj+LJly5B4HqkFmD6rqKhoZ2cXEBAw0i6b6Oho2ERKo9GQeBYQEHjx4gWaep4+fRo9D3vGUlJSTp06RaFQAgICQOQPi1mzZvn4+DD9DsMw1AJqamrDzurQr4me20ADy5cv//LlCyzJEZ+HLB3R0dFhYWFkMpmpKcA/CRT069ev8/PzBwQEqKqqxsfHEx+ztLTk5OQMCAggsqyfju9wDVu0aNGZM2eIqw5kMjk+Ph7Wlnbt2mVubu7n5/f169dLly4tW7Zs586dZDKZ1auipaWFRqN1dnZevXpVUFDwwoULampqTI+5uLgcOHCgpaWlra0tMzPzxo0bN2/e9PX1pVKpLS0tBgYGY4mn0d/fD7wYLWwUFxf/8ssv3d3dN27c4OTk9PDwgFAb7e3tBw8eXLJkCdMXbG1tQQwwoby8fOXKlbt377a2th7p70+ePBkaGlq9evUYm9fFxWX0B3p6eo4cOfLx48eKiorjx48Tl3zk5eWJ268BEydOBHmAYZikpOTs2bOZnL/GWLDJkydraWmN4uDT0NCwdevWqVOnwunChQtZlzwBdXV1TClYpkyZgpwHmYJXxMfH/+Elm56enmGvi4iIwEFUVBRyevj69eu0adOIMWF6e3uHfT0oKIhpYRW1wKtXr9TU1FgrOEqpODg4xp7fXlZW1tbW9urVq5s2bYqMjCSRSCYmJrt37yb2Y0xMzLAlr6ure/z48fdup96/f7+BgUFlZSUvL6+EhMSVK1eeP39+/PjxFStW+Pr6wnoHeri4uHj58uVw3NzcjIgB+AY6njlzpo6OzrC+3KzLyUzDPC0t7dSpU4KCgiYmJkTaEBQUbGpqunHjhqqqKhcXV0tLi4iICHE0ZWZmuri48PPzw6moqOi4ceO0tbUNDQ3v37+/du1aWGhftmzZ+vXrvyt/nZCQ0JIlS/4MP8SZM2eOxOLKy8uLiopkZWWZaImV2YILRV9f39u3b1lbgOlJHx+fHTt2xMfHy8jIiIuLu7u7L1myhMFg1NXVHTlypKenx9HRUVZWlin4AYlEIlJgREQE2uVRWVm5YsWK2bNnKygo3L17d9euXUNDQ2fPnlVWVj5x4gQqzEgYN27cGHnUSA7LaLAzPfDbb78hnwleXl6w0hHJnhjJo6enx8/Pr729vaysbGBggJubG3lUFBYW7t27t7OzMzg4mEKh0Gi0sQ/nn++5nZycTIyC1NfX19jYaGNjgyQEBMDKyckJCwvbu3evmZmZpqYmq8/wgQMHDhw4kJ6eHh4eTqPRXF1diW4IaLXfyMho69atixcvNjAwmDJlyowZM0pKShISEiIjI9FSBIKZmRkrdYqJiRE7ePr06USKnzZtWkZGxuhV/vz5c19fH6uL04oVK3x8fFDdRwIfH99PDATm4eFx5cqVwcFB2FdAJIWSkpInT54wRUFpaWm5ceOGuro6hmGvXr2KiIjYuHEj8vMMDQ0dYxSwpqam/Px84nBSVlYmvjtp0qQTJ04QdwSNBDk5OaaAWUjqP3/+nEm0mJmZ3blzZ6RPqaurE2UAq6fMsNcvXLgw+sRr9NfXr18/bF48VVVV8NWSk5ND/l+sYNrMxs/Pr6ur+83IMAi+vr7Ozs5guoiNjT18+LCJiQlxr+NIEBMTgy3X3wW0X+X8+fNgeb5w4YKpqenQ0FBlZSVs8EUwNDQcyTsmOTmZiQOO5Bo5ij9pWlqam5tbUFCQjo4O8O4NGzagF+vr6/38/Egk0oQJE8LDw5n8vzQ0NIKCglgd4MPDwzMzMxMSEkAj3Lx5s42NDZov/u3u7lVVVcPGKZOSkmKKRgcTys+fPyspKTFdf/fu3adPn7Zs2eLn5zf6H+3t7e3t7f38/Do6OsATYsmSJa2trVJSUtu3bwcvNgEBgYyMDGL0j8HBwfr6eg0NDThdsWLFjh07mL4sLCycnp7++PFjWOg8f/58U1NTTEwMU27K9PT0tra2CRMmIF4xRgbF2hqIbltbWzEMY9IWfvnlF/Tr9vb2AwcOILZAJHsk46urq7W0tHbu3Dk4OIg8nMzNzaurq3Nzc2NjY3NycmJjY5WUlIgRq/5qz20nJ6f8/HzipFVVVfXGjRtwevDgQWCvmpqa+/btG+kjXl5eMJeZO3fuhQsXwM7AivHjx1tYWFRUVIBzNYZhenp6lpaWa9asqampWbx4MdPzRUVFrB6zQkJCxPBMfHx8MGcUFBT09vbu7+//5k7Bjo4OYrpTDMMqKiqWL1/u7e2NZHN3d3dzczM/P7+wsPDu3buJD48iP0bRHhgMxtu3b9+/f8/0wI0bNzZu3AjiraWlhaiCjK49b9u2jUKh1NXVIVsC0aF9LEYI8KdF6OrqQqJ00qRJTU1Nt27dGsVjmTizYVIuJ06cCAc2NjbEGcCXL19gSXgkVFdXg+VqJOHNdKWmpkZCQgLJTkS3o8+7hwVTLzNVcBSPU1RZNDEHu/pYkJ+fHx0draCg4O/v7+/vD2vkTNi7d6+AgABr54qLi6M9C3l5eWBG/iYmTJiwa9euFStW3Lx5c9WqVTCfEBYW3rx5s5CQECtxjvQdPT09oiIbHx+PfF9H155jY2NramqA3T9+/FhISAhkMysBOzk5rV+/fv78+RYWFvfv32fq/WfPnjU2NjJ9/N69ey9evNDV1YX2HJ3YELZs2UKkOhBOowzzgYGBt2/fjmRMSk1NLSoqGvaWmpoa0TjBZPdi1X0nTJjAKpsxDNPR0ZGSkqLRaKNvb/v8+TO08549e/z9/VeuXEkkdRQB7cGDB1VVVcTGHxoaAhG4adMmSUnJhoYGVj4QFhZWXFw8f/58aGoFBQVVVVWmWezUqVOTk5OJbVtYWPjx40fizqBRhgbrYIdO4eDgEBcXZ2L1R44c4eTkHD9+/IQJEwQEBFpaWoi7Rnfv3i0hIcGkRZw6dUpZWdnPz8/f3x8qaGpqmp2dPWfOHH9//5iYGBQIEixJo/OBP0U8YxhWVVXl7e3t4+MDTQA7ATAMKysru3v3LopnGRMTo6enR6RaX19fb2/vyMjIsrIyNMXo6Oh49+4dMsCymrZEREQcHR1BlRESEtqwYUNHR8ewWyDq6+tZm+PevXtESnrz5s22bdu8vb3Lysrs7e25uLgWL16Mxu2dO3dYFWUhISGisauoqAhWNwsKCrz/g82bN4eFhWlra9vZ2T18+PDdu3dgU7p///7o20hYtQfEtVVVVVG0EyKuXLkSHR0dGhp67tw5IimD9sz0MGjPwJ15eHh8fX09PT3z8/PfvHkTHx8/ilke5hze3t6wmY2Hh4eJHQsICCCzxKZNm6ZPn37y5EnEXiMiImJjY0cyQzGJ5+bmZuLprVu3oqKi+vr6zp49yyp9P3z4gOLbfPnyZZSt2LCxJCYmBk6TkpKOHTt2//59AQEBEom0dOnSnp4eb29v2JiHYVhiYmJ7ezvay3DlypWRvuzo6FhVVXXr1i1U/pSUFETDrBUkAo0XAJlMZmXBN2/eJK7IpKenv3nz5unTp93d3deuXUNVzszM/PXXX5nUiylTplCpVOLsobW19dGjR8QhNnv2bCTkvmFY4+KSkJAoLy+3tbWVlpbGMExLS2vx4sWhoaEmJibEOYepqWltbe2LFy+IZvZhZzM0Gm3evHnwtWHpH73Y19cXHBxsZ2eHYhV8/PgxKyuLTqd7e3ujLZeA5cuXl5SUzJo1S1VVlenjUHdieYqLiwsKCogBhcCwsXDhQtZpB2ubxMXFETs0IyODyZDANAZVVVVHesDY2HhYmTo6ent7u7u7CwoK3rx5g2ZpZWVlTDOM/Px82Hno6OjY1NRE3Eh58ODBgoICJmW9uLiY9V+w7wZaD6LkdnV1gTxGRnWI2UKhUMhk8okTJxCRDwwMALNtbm4mLuvMmjVr2rRpTPLP39+fqZtiYmKoVOpYNBxg8miCePfu3StXrjx8+BDUvL179zY0NJw/fx7pV3fu3Ll06ZK5ubm1tbWenl50dDRqjQcPHvT09Dx48IBpAqSvr//27VsQH8Dompub0TNiYmKSkpJIQTIyMlJVVR2LuvJNcI5dH5eUlHRxcTl//ryjo2N5eXl4ePitW7f09PRgCba9vf3Ro0cPHz6Mi4srLy+PiYkBa5KoqCiZTH7x4kV1dbWXl1dlZeWHDx/Onj2blpZ2//79hQsXbtmyhcnKgeZT7969U1NTQ3NhBQWFJ0+eWFlZISNhTU3N5s2bOTk5p02b9vz5c3FxcUlJye7u7tWrV/f29k6ZMuX169e8vLwKCgq6urp5eXmdnZ2wQVBSUnLevHlJSUk0Gi08PDwpKenly5dLlixBSwuIOcbHxxsbGwOZ0un0ly9f8vLyVhPQ2tpqamqqrKysr6//8OHDFy9enD59+sWLFyCwQbqHhYUdP348Li5OQECgtLT03r17M2bMQAGGamtrg4OD+fn5QcXZtGlTfX398ePHmYKoKCkp1dTUFBcXl5SU+Pv719bWlpSUFBQUfPnyJSQkZOLEiSQS6dGjR4sXLyaRSLW1tXV1dW0epVr+AAAgAElEQVRtbW/fvp03b97SpUvBMPXq1au0tDR7e/vs7Gw+Pr7k5GQtLS0mrtTQ0FBeXl5dXd3Z2cnFxXXixImenh5ubu5Hjx5ZWVlxcXHl5+cXFhZ+/fr19evXCxYsmDVrVmlpaUVFxcWLF58+ffr69WsPDw8ifZeXl7u7u5PJ5GnTpqWmpkpKSk6ZMqWvry8rK6unpyc+Pl5fX19AQEBZWTklJaW4uPjRo0dSUlIUCoWHh+fNmzc8PDwBAQFlZWW8vLw5OTnNzc3p6ekpKSmTJk1qb28vKCgwMzP78OFDTEzMwMAAtMDNmzc5ODiam5tDQkLi4+OlpKQOHz4MztskEsnCwqK5uTknJ+fy5csnT55MT0/PysqysbGJjo6+deuWqKjowMDA8+fPh53BzJ8/v6enJywsbGhoqLe399KlS7q6utu2bePk5Ny0aVNNTY24uHhZWVl7ezsxRsSwLdDZ2Ql+78nJyZMnT/b29ubl5e3t7c3Ly4OYFa9fv25qagoPD1dTU5OSkgK9s7e3t7S0NCEhITY2ljXW8bx58/r7+9euXcvFxdXf33/58mUNDQ0PDw9OTk53d/fKykrURPB8Tk5OSUlJUVERq/UFTBTFxcU0Gg3NxoqLi7m5ufft24dGCh8f36JFi/Lz869fv+7v73/mzJnw8PDKykoqldrX15eZmcnDw3PkyJEzZ87Ex8f//vvvq1atGnZN0dvbu7CwsK6uzs/PLyIi4tWrV6dPn7axsYERVF5eXlNTc+PGjdevX5uami5ZsqSmpiYlJUVJSUlUVPTJkydJSUnh4eHnzp078x+QyWRNTU0NDQ0xMbG7d+/6+PicOXPm3r17mZmZSkpKfHx8d+7cOXz48Pjx4yMiIrKzs69evcoqnrOzs7Ozs1GMATExMS8vr2PHjp07dy4nJ6esrOzGjRvESGEVFRXh4eH79u2DYru4uLS1tZ08eZIpkMjKlStbW1s7OzvBknH48OHKykoSifT48eP58+eTyeSsrKyUlJTOzs6XL18yLVqJiIh8/vwZ3B0EBASSk5Ozs7MnTZr0+fPn0tJS4CHv3r1raGgoLCxcvHgxsQVCQkIyMjI4OTmXLFlCtCy+fv06Nzc3ICCgqanp4MGDdDr94MGDSkpK0tLSGRkZnz9/Tk5Ohg1L/f391dXVnz59ys7OfvjwobCwcGFhYV5eHmwJExERASeh8PDwFy9eTJw40crKqq6ubvPmzVVVVQ0NDdu3b58yZcrWrVuZws5PmDBBSEjo9u3bPj4+M2bMiIqKEhQUPH78ODc3t4+PT2BgIIPB+PTpU0lJCVPsCig8mUyur68PDAxMSkrKysqKjIxE65iKioqfPn169uwZXDx9+rSTk9OKFStgfgByITw8vKysrLe398qVKzQaTVlZGWzjSUlJgoKCKSkpampqIiIienp6fHx8jx49kpSUzM3NDQ4OPn78eF9fn6enp6SkJCx7VVRUBAQE+Pj4wPa2HxTPpFEm+38eUlJSUOytvxcpKSn8/PwqKipMEUWQUrV8+fK9e/eOfdf54ODg8+fPjY2Nx16Gly9f6ujoNDU1iYqKvn79mkqlXr16lZUK//uRmppqYGDwXc41fzby8vKkpKSYrMoIcXFxjY2N4Mb/XZ+l0+ngI7N48WLYn/3njQ7iaUhISF9fn5ycHOx0HxZE7d/W1vZ7I+V9c6iONHgzMjIKCwsxDJORkSEuNre2toJWpKenN0rSAhgFeXl5L1++lJWVHTbOYHp6upaWFpOXyaNHj6BZ0E/Bz3/8+PEohkZzczMYPObOnYsU1t7eXhSTeCQaOH/+/Pnz54nRaVJTU+l0OgcHB1r8ZmocMzOznp4eXl7ejIyMdevW0Wg0onn/7wK0gLi4uK2t7Sg2p4KCAkNDQ6Kp9ntRW1t77949Jhq4desW2MlGp4FPnz6Bu4mJickfCMr28uVLJSUl2EDPKsJhD5GzszMrqwc+ICoqyuodPAoePXpUUVGBYZiqqirq4h07djx8+PDOnTs/J9QozsbIGGVj1U8EMSXGrl270FZyNtj438GKFSuw/7uxaow4evSooqIi2m4L27IDAwPHjx//U1JiTJ48mU6nj/F5tLFqcHDQ3d2duBWQjX89WltbbWxsKisr/4aUGP+bIJFIUVFRy5cvHyUY3h9GfX398uXLDx48iMwg6urqxAUYNtj4H8GP5KXl5ORkUqmvXbv2s3LMNDY2Ojg4QHqbUVBeXk6lUo8ePUoikS5fvozjuLa29jczBrHxbwKDwXB0dPyJ6TX/HuM2G2ywwQYRsrKyFRUVzc3NI61EjISEhIS9e/dGR0fDkmFtbe2zZ8/2798fFxf3EzNnX758+ZsTiIiICGtr65+++ZWN/13lkC2e2WCDjb8RdXV1Xl5ez5496+7unjdv3tatWw0MDL7rC1FRUefPn4dIHZ8/f9bS0nJwcGDdXMcGG2zxzAYbbLDBBhts/BDYa89ssMEGG2ywwRbPbLDBBhtssMEGWzyzwQYbbLDBBls8s8EGG2ywwQYbPwqu/7YCMRiMsrKyPxAy5r8B6enpEPpbTU0NQtFiGPb+/fuRotv/g9Da2gqRaTk4OMaSJYkJZWVlKBXKKDmd2PgDyMnJ6erq0tbWHnuS0LGjp6cnOztbUFAQZSX6KwGRXzEMk5aW/t7kb4ODgy9evODl5dXW1v5X9jtUEI7nzJkzbNzDHweNRiORSLKysmFhYSEhIf/lbXL9+vWysrKJEyf29PR8c6v6T0d2dnZPT4+wsDBriuR/iXi+ePHiu3fvhk0I8d+P0tLSS5cuvXnzJjk5GQIfJiQkQCLI/5Igpj/CpktKSrZs2YJh2LA5j0fH58+fra2tv3792tfXxxRul40fQVJS0vLly1tbW6uqqn5i9lKEI0eO+Pv7z549+/Xr13997ZqamiA+rq+v77C5cEbB2bNnPT09paSkqqqq/pVdPzQ0FBQUFBUVtWDBgsjISBDPkZGRaWlpa9eu/QMpRIdFV1fX9u3bLS0tiSm03dzcUMoHU1NTYs6VnTt3ogR3enp6kOvsm/D19a2urv7999+JeT97e3tRtHMMw2xtbSH8+Nu3b4kpIAEHDhyYOnUqNzc3hL/u7e3968Wzs7NzaWnpvHnzIHjcv1A8t7e3p6amFhcX/0jc178La9euTUxMJGYJ/Pr1K2SY+afzAgkJCVdXV0FBwTGONybo6upGRUV9M0P2z0V3d3dycrKxsfE3MxH9sxAfH8/FxQVpM0xNTZOSkv48BXH//v1cXFyJiYl/F9V1dnaOMcUWE9zc3Dg5Oc+dO/dvnZnx8PBcv369srKypqamq6sLwrl0dHRApgD02PPnzydOnPgj7FRaWjouLg7Nqjdv3lxbWxsVFQW/s7Kyam9vd3V1bW1tXb9+fVdXFzz56tWra9euSUlJjZI+oKqq6tmzZ2fOnBETE3vy5Mnu3buReK6trXV2dra1tV27di2GYcXFxfr6+qWlpVJSUjU1NUFBQUzMBDL/QsVFRES+K3r2z0J+fr6np2dJScnP+uB/nXjes2ePubn5P1E2I9olppyjUqkyMjL/GvPaGNPiDos/w/T6Td3L1ta2sLBQRUXl38SX7ezsBAQEOjo6gEezZv/9iRg3btzfaO3g4OAYN27cH1sN4ePjY4r0+e8DNzc3U7q/TZs2zZo1CzGcx48fL1++fP369X5+fj/SC4gG3r179/Dhw8DAQFDWBQQEVq5cefLkSVdX17KyMn5+/oiICBjpqampJiYmxOyorGAwGHx8fKGhoTw8PEy5NV+8eJGbmwuJZ4AOBwYGUJQODg6OO3fujEQYP8KmfgQNDQ1PnjyBDMg/h/7H/mh1dXV4eDiGYcnJyaGhoU1NTejWzZs3R0/3PQqeP3/+f+YLXFyampr/uHHS0NAALQBJe4j4Ny19/aw4xmz8CPT19f93KpuUlETM2s7GsNotMU0TkeHMnz9fXl7+506YODk5mTKXA0FOnDhx2bJlaBY+Fr4nKyvr6Oiorq7OJAUAAwMD4HnAinXr1o2SrvHvYlOysrLm5uY/8YNj0p6Lior8/PxqampmzZolIiLi4eHR0tISFBS0YsWK2bNn+/v7v3z5UlxcfOHChQcOHCCTyX5+frm5uV1dXStWrHB2dsYwbOPGjfX19X19ffv379fX1x8aGoqIiHjw4AEXF1dhYaGMjExYWNj48eMdHR3b2tp4eXmPHj0KCnRXV1dhYeGJEyf4+Pg6Ozv7+voOHTrEauy6ePHivXv3MAyLj48/dOjQmzdvTp48qaKiUlhYePDgQVAvJCUld+7ciRKvlpaWenp68vPzd3V19fT0bN261dLSsrOzMyUlJSoqioeHh8FgtLa2nj59WklJaWBg4NSpU6mpqVxcXLdv3963b9/bt2/PnTs3Y8aM1tbW2NjY27dv9/T0iImJtbe3o1LV1taCZWbjxo12dnadnZ1OTk6Dg4NGRkZLliz57bffBgYGBgcHL1y4gIZQX1/fkSNHYLWsp6dnwoQJx48fxzCMn5+fk5Pz2LFj79+/B7rk5ua+fv36WLqvq6tr8+bNg4OD/f39HR0dJiYmkM1++/bt79+/l5SUPHr06I4dOzo6Onp7ezk4OJKSktC73d3d27ZtA+P8169fq6urv8lMg4ODyWRye3v7wMCAn5/fsC5FSUlJZ8+exTDM19c3NzcXssqrqKj4+vqmpKTAwpKwsDCkwYZXvn79um7dOtAVcBxXV1dft24dJAFEFcQwrLOzU1dXd/fu3T09PV++fMEwrLW1tbm5mZube9hgyN3d3du3b+/q6oJfKCkpHTx48NWrV8eOHRsYGBg/fvySJUuWLFkSGRkZHx/f3t6+YMECDw8PDMNqamrc3d2heBMmTDh58iSQ6LJlyzAMi42N3bNnT1FR0Z49ewIDA1tbWxkMhoiIyMaNGw0NDU+fPv3o0aPx48cvWrSIaIdE6OjoePjwYWxsLDc39+DgoJmZmYODw4QJE6CC7e3tOI43NzdzcHCgNIgDAwMnTpxISUmBUy8vL5TCeXBwMCDg/7H35fFUbt//j3k6kVBEyJSZE6EyRShlnnKoTKUUumkmKQ1SEWVIgwZFGUqTSlJSCI2GkilTMlOGhOf3x3p99u/5noPU7Xbv/XzO+69n2M+wp7X2Xvu99oqBQL+Dg4MrVqwwMzMbGRnp6OgICgpSU1NTVVXdtm2bsrLyoUOHxmlFEL0YxtBJSUmTJk3q7++vqqry8/ObPXt2QECAi4tLT0/PjRs3BgYG7t27l5SUBMuQNjY27u7uTExM7e3tsbGxOTk5O3fu/Pjx46lTpzAMmz59elRUFNEG0NbWFhYW9uHDB2hFULMInz9/dnZ2htkbExNTTEwMsZHk5eWdOHECkk1Er3d1daWkpGRmZn79+rW/v9/X19fU1BTH8WvXrhHlQHh4uLy8PPQgV1fXkZGR1NRUf3//kpISDMOsra1dXFyio6Pv3LmDYZiGhkZAQAAbGxsUckBAwOzZs5WVlXft2gUfTUxMZGZmvnv3LpTAjBkz4ABlcPny5ZApaHJr165FcVrb29ujoqLevXuH43h7e3tJSQkarnV0dJw6dSorK2vr1q0GBgYjIyOXL18uKyubM2cOxHPctWtXQ0PDwMDApEmTDAwMvLy87t69GxkZycrKKicnN5EZtry8vK6u7s2bN2/fvq2hodHT03Pu3DmgjElISEhISBBzYWxsPMGtVWn7Jisr68jIiL29fVJSEplMPnjw4Nq1a1HwViYmpra2tv7+/lWrVu3cuZNMJqM2gGFYVFQU8VWVlZXr1q07ceKEuLg47af7+/tramr8/f1ZWVm7urrk5ORCQkLY2dl7enqysrJiY2MtLS0NDAzQKnhcXByR5FFXV+fj48PFxdXX19fX1/fu3TsUavoXYOLBrTw9PRkYGC5cuACnGhoaGIY5Ozs/ePAAx/GLFy8yMTElJyfD3QcPHkydOnXXrl3ocRcXFwzDUlNTcRxvamrCMKyoqAhueXt7t7a24jj+/PlzCQkJDw8PuN7W1mZsbLxy5cqHDx/iOH7+/HkZGZnXr1/T/tuVK1fA/BIcHAxxWHNycp49e6aoqHjv3j1IY2try8DAgON4f39/RESEsrLyjRs3oB9ycXHFxsbiOG5vby8rK1taWorjeGtrq6amprCwcHFx8bt377y9vZmZmRkZGYODgz08PDAMy8/PhwijUAI4jr98+RI2/s3MzMRx/NOnT97e3jw8POHh4TiOJyQkwNhKXl7e29s7LS0tNDR0zpw5mpqaKCOurq5WVlZwDIpZS0vL29v70aNHt2/fNjIyGh4ehrsUCmUitdba2mpoaBgcHIzj+Js3b6SlpZ2cnOBWWFgYjHDnzZsXERGRmJi4ZMkSBgaGu3fvQoKkpCRTU9Nt27bB6aVLl5iYmFhYWMb5nLy8/IsXL3AcP3bsmI6OjoyMDLp17949GH/gOP706VNgmvDy8np7e3t7e0MUWCcnJ+//QFhYeNOmTfBsU1OTtrY2FCOO4zAGEhERgdNt27bt2bMHjs+dOwclk5OTA02OQqF4e3sfPXqU9m+7urqWLFmyZcsWOAWhmZSUhOP4kSNHMAzLy8tDibOysgwMDOD/S0tLVVVVU1JS4JaMjIylpWVvb+/FixdNTU2ZmJgcHR0hYnFhYSGO41JSUhiGffr0CdLDaCArK2usYjQ3N1dQUKioqIC8q6uri4uLv3z5EjIIgzNvb++dO3fiOA4Gmy1btqCiA3mH3hYSEjJv3ryOjg4cx69fv87AwHDnzp0vX754e3sLCgoaGRkpKiqSyWQ9Pb2xwqqKiIjo6+u7ubl5e3sDPcfFxQXH8ezsbBh/+/v7BwQEcHBwGBoaDg4OWltby8vLFxYWent7Q6RIyMv27dshDq6rqyv8KgTKRdVXW1sbEREhIyMDVR8RETFv3jwYxkGCmpoaNTW1+Ph4ONXW1jY0NATp0djYOH/+fE9Pz8LCwsLCwtWrV2MYJiYmNk5zffnypbKysre398ePH69evcrFxXXixAkoJVlZ2bKyMhzHYRNvERERJAegioODgyELU6dOxTDMz88PTsFNAwRdd3e3t7c3rKeuWLECEsjKyqqoqJDJZFQCU6dOLSgoQCWgrq5++vRpON23bx+GYQcOHEByVVZW1tvbe3h4uK+vz9vbW0hISE1NraGhAcfxwMBAiAty8eJFaGZ6enoYhqmrq8O3Ojo6oFgSExNRIWhpafn7+49VREePHpWUlCReAVGPVhBQLwB8+PAhIiIiIiKCTCbDb0wEpaWlGIZVVVURLx4/fhxaMnQHdP3WrVvINgAHqA0AYPaMTqEJvXnzZtRPR0ZGcnNz37hxAwbcnJyccXFxOI6fOXMG+Ly6urqbNm3y9vYGBpyBgQE8+O3bt4iICBUVFajr27dv29vbYxi2cOHCXxVQ8gfU86ZNm3x8fNApzLHKy8vRFXZ2dqSeb926NWXKFKJ6fvr0KRMTE1E937p1C3W5wcFBOLawsJCUlAQFCTEciXW2YcOGcZoRSAEwibx7905ERMTQ0BAluH79OoZhzc3NMKk6e/YsscFdunTp0aNH/Pz8lZWV6Hp9fb2YmBiK97xp0yYmJqbKysrBwcG8vLyOjg4fH5/FixcTf8Pa2hqpZxjeiomJIb0CMeHd3d1R+p07d3JxcYFKwHGcmZn56tWrcNzY2CgtLQ2aFcfxJUuWSEhINDY2frcoiOjt7c3Ly0PRcJctW8bHx5ebmwune/fulZKSQu+8d+8eFxfX8uXL4VRTU9PV1bWvrw+9zc/Pb3z1TPyrsLCwsdQzagMo4zU1Ndzc3FOnToUVJhzH9fT0PDw84M9hOb+9vR11jC1btrCysh47dqyyslJISOjRo0ddXV1U/wBGiFHHc8RI2yUlJegKFxdXREQEVBwfH5+RkRG6tXDhQvjbwcFBCQmJqKgodCsxMRGaFo7jKSkpoH5aW1vz8vI+f/4MDYz4J9XV1WZmZuiHqXDv3j0hISFisz98+DAzM/OxY8fglIGBYdKkSeguqGc0qhsZGQkKCkLq+ezZs0pKSqiK79+/z8XF5ezsDKdz586dPHlyRkZGbW0tdLpR1fOsWbPy8vKg7trb2xcsWMDPz5+fn4/jOBBhZGVlm5qaioqKYAji4+OD/v/t27dIPSM5EBoaihq5jIyMiIhIfX39qFLlxIkTrKysSD2rqalNnToVDVKzsrIwDHv16hWO4wsWLACLFGokmzZtGkc9d3V1iYmJnTt3Dl1JSEhITEx8+PDhlClT0NAQ5ICoqOi2bdvg5ampqczMzEhQAG8O5tw4jldWVrKwsCAhDv/My8uLwgADuRJJlbi4OFZWVjRAmTNnTmBg4MjICJwODAysW7dOSkqqo6Ojr6/Pycnp2bNnxFxoa2uvXr0adfCCggIODg6kF2Eyt337dpS+qqqKg4MDjVa7urpMTU3r6uomrp4/ffoUEBAgKSkpICDAzMysqamJ5ic4jufm5kr+B5qamjAF+i4gGhiVen7//j03N7ekpOSUKVM4ODiOHDkCaiI7O/vw4cN5eXnQxYyMjGCVHT24bds2onouKSnJy8vr7e0d9dMfP36EGQVASEgI1DOUlaKior29PfRisI1xc3Onp6fDQATDsJiYGPRsW1vbokWLfqF6/gFq2MePHy9fvoyYkDAhGAumpqZEQwcSXsQrK1asAIuBiYkJ0eywYMECsGxv3LhRX18fbHqA8PDwsb4IQkpKSoqBgUFLS+vDhw8NDQ3m5uZ79uyBBO/evYOl7u7ubnV1dSKfkEKhgGG8s7MTpr8AERERDg6OzMxMT0/PSZMmNTU1MTIyQgItLa3KysrIyEiQPkSoqKjMnDkTjl++fAkUHoCcnBytS3dvb++nT59oc1RbW4tcFGBBxdTU1MTEBEiJGzZsmCC1B0oDZl0lJSXt7e1ECzwXF9f06dPh2MjICPjAGIYVFBQ0NDQYGRlxcHAQ28D4nwsPDx8aGgIr2VjrRkSgViQuLs7CwhIaGoqMeBiGnTp1ysvLi0wmgz2ZSFCwtbVNTEysr68nkUgzZ87U09NbsmSJhoaGlZXVOI2ECvDamJgYmABhGDY4OLhx40YfH58pU6YEBgYGBQVlZ2cvWLAgMzOTg4MDhs+gXwsKCsBgiGEYDDUQ2NjYwNyHVlJ0dXU1NDT8/PxgjLJlyxY3N7exIg+eOnWqp6eH2H38/PyOHz+ekZHh7u4O1WFlZUVb8nDAwMBA7JtNTU0tLS2nTp0SFRUVEBAoLi5GjRPg5eW1aNGi8QuKi4sLLSVOmTLF3d3d2dmZ2LCdnZ2FhISEhITgFKTEly9fwsLCUCmhJoTMCWDZ5uLiqqio+Pr1K4ZhMA4j/v/q1auJK51VVVUGBgZ79+61srKqq6sDwkdaWlpra+vz589tbW1R+2FmZqbKKRWSk5M/fPhA/BYsNFy7dq2np4do5wc5EBIS4uPjIyQkBKQkJCjgDaj8JSUlGRkZUVEANmzYgEScubn5hQsX0HdXrVoVExNDzKCkpCRaWGVjYxMVFa2srIyOjtbX17948SKtT1FJSUlnZyeEGY6Pj+/v70e3Ojs7iadggra1td24caOvry+GYefPn5eVlZ04m6mmpsbGxkZcXLyysvL58+cXL14MCwvz9PREdOX58+dXVlbCaou1tbWHh0dzc/NESC1U69klJSUUCuXChQvm5uaPHz++ePGin58fUgpIevPz8586dUpMTMzPzw/xfqjEFBXpjAqCgoKCgoKPHz8GGtrnz59v3ry5cuVKVlbW7u7u3t5eQUFBxIMTEhLq6ekB3tXGjRtVVFRgcAAYGBjo7Owk8gB+HzXs06dPEw+Zfvv27erqauIVMpmMiHYCAgLl5eV6enrp6engbwNrtABwrEKVBJbA72JUJsL9+/ft/4OdO3eWl5fb2tqmpqZWVla2t7dTJaZasSAuvQ8MDEAJjNpeqYRdbW0tSmlgYECMX9vQ0NDY2EhMb2trS3T1ExcX9/PzKy4uLi4uvnz5soKCwpo1a+CWjo6Oj48PKytrWlrarl27LC0tYaOP8dHX17d582YvLy8+Pj57e/vLly+Pk7ioqCg/Px+pZ6pfHasEiOMJJSUlmBfa29v/ed98U1PTsXx558yZA/Ju2rRp165dMzY2/vjx4+7du01MTGRlZR8+fDjxr1RVVdnb27e2ttrb279+/RpWE0HlzJgxA0w4d+/eRQuHqGVyc3MLCwszMTHBKv44gYpFRETmzp3b09PT1tbW2dnZ29traWk5VuLU1NRRr7958wZ5nKNqGh+tra2XL1/u6enh4OC4evVqWFiYsLDwxo0bDx48+GfqhZZPQNUw3r59q62t7e7uPjg4SEWWaWlpGSdKXmpq6po1a4iM3Bs3bsA0BeH58+fCwsI7duwICwvLzs4uLy9fuXJlWVnZj7ovpqamGhkZ/cRK4URcisdxE3/27BlsXvSrIC0tjVwHXV1diePpyspKquERyBywVw0NDdXX19va2k78WzU1NS9evICxy+zZsw8ePLht27ba2lraQQMLC4ulpWV3d3dCQsJ3X0sre2/cuOHl5QXeUzo6Ops2bRIUFBy1a/Dx8REdr78rpqjQ0tJiY2Ozd+/e+fPn29vbc3BwqKurwyDv8+fPVIMbWJqEJQMoDeK3Jk+eTDUp/X3qmXaA80Oz5927dyOKBzMzs6ysbGpqanFxcXZ2toyMDFHToNkzkESQ//v4ADFKBTY2Ntn/C8QHoS33devWjYyMgD8f1cgXNChxHo8QEBBAPI2Oju7u7h5LUsycOZOKnvD582ei78HNmzehfZw+fVpUVPTSpUtoBkYikSIiIoqLiwsKCg4fPtzd3U3bJWhRWVl5+PDhmJiYdevWycrKFhUVjZNYXV0djXK0tbVFRUW/y+AgIjg4uKSkxMPDIywsTFZWFncDUgwAACAASURBVPE4fhp9fX1UtKBRISAgcPfu3eLi4oiICD8/v3fv3k1wSAc4fPiwrKzssWPHqBoJmNQyMzOLi4sfPnyIbAwARUXFDRs2uLu7+/v7w1PEeT8tLCwsSkpKbt68ef/+fWFh4XFSjkoWgzk3Kn8DA4OJZE1AQMDBwUFaWnrz5s3p6elZWVnu7u6urq5UeflR7Ny5c86cOURKMLFrvH792szMbNasWZcvX967dy/IASSjeXh4qDi3VPmNjY0lai8uLi4WFhZiAllZWVdX1xs3bmRlZaWnp8vKys6cORNWYX80I5mZmaO6nAwPD8OCxahA3j7jYJyNAvX19cd3FUtMTBzHH4lW29XV1aEG39PTQyw9BQUFmFVTzSZVVFQCAwN7enqePn36E7vZoPbDzMw8bdo0Hh4eNTW1UdUwDw8PkA++q1xo5SqxlUpJSbm6uo76bHt7++XLl8ECOhExRWW5XLZs2YsXL+7evWtoaAi9OCcnB5QOBwcHrVdhWVnZo0ePUGkTRX1ZWdk4zeavVc9RUVHE2TMs5n93qAV///jxY6LBwcbGJigoCI6FhITIZDJV64fZMwypJjhlpzJksbOzS0hIfPnyhbhnEPwzvJa2QfDz8wsICAD3Ev0/IyMj0lJUn4CZbk9PD+IzZ2dnt7S0ENNUV1cT6+/du3dU4uDJkydEU3NaWlpTU1NTU1N4eLifnx8yuoJUgqVrNjY2Pz8/ERERdCs+Pl5ISIj4nlGHpW1tbRMke8PQWEhIKDw8HJmtysvLb968Of5Tc+bMAb+4wcHBn/a1I84zYHAKuSA2uXPnzgER7+3bt76+vjDYWr9+PVjAJt6kx2/JUVFRBQUFqamppqamqC4YGBjk5OTS09N/aP+BBQsWqKurl5WV7dq1a/ytXUxNTfv6+jZt2kSc37OyshJr/LsV0dfXFx8fj6QGsGx+CVpaWlpbW21tbYlindg13r9/D+ZNYqdbunQp6jVU6pmYF6oaGRgYSEpKIvpwysvL37lzZ6wq2759OzK5P336dPv27T9R+yAH4uPjqQxsgYGB0AbQAtDExRERGRkZ48yeIYNUBgYZGRlfX18eHh5hYeGEhAQwFw8NDWVlZXV1dU2bNg3NmOvq6oiqvaWl5cuXL1SfkJSUtLKyam5udnZ2dnBw+JNjNQzDeHl5582bl56eDpx5NMQpLy9HE63q6uq4uLixtoOkrQV5eXniRZDk8vLy8fHxVN2ntLRUVFSUuA8JamzIKOjj40O7CgkNjDjYev/+/devX8XExID7xsfHR7WjkZSUFBos0qqniejEH8NEFqjLy8vd3NwMDQ0ZGBjc3Nzy8vLc3NxgVmdjY4OIvuzs7AYGBmfOnIFTdXV1SODm5kYmk0+dOsXExGRiYgIcYEVFReBKVFVVycvLI06ZhYWFjIwMcEM6OjqWLFkiICDg5uYWFhaG47i7uztxGZ8IGDEhSgXQMqdPn66urg68Ry8vL+A4DAwMUCgUEonk5uYG5DU/P7/s7GxgbktKSgKFp6WlZfbs2dHR0eiFnJycVMSo4uLiadOmaWhouLm5ubm5qaurwzKSnZ0dJAgMDARrGDjD0FLDioqK+Pn5gY4E1DBmZma3/wuwB/Ly8p4/fx6SZWdny8rKIranmJiYk5MToocQARtlOzg4uLm5+fn5QfcAUl5LS4uamtqUKVNu376N0tvb2yNqGDh7WFtbw2/s27fPy8trHGpYTk4OMzOzgYGBm5ubp6eng4MDolEgahjiN8H4zNPTEz3Ox8eno6MzNDSEqGFgycRxvLm5ecGCBcLCwk+ePMFxvK+vb968ebt37wY6OtjVEZNIU1Pzw4cPiBpmZWXl5uaGaGVE9PT0WFpaTpkyxc3NDYjNa9euRaUKzFsLCwtRUVEqfhloPnl5eSCzbN++HZyOgBrGyMiIegERd+/eRabFcVBVVaWiojJr1izEkNqxY8fcuXNRgtWrV7OwsECFImrYjh07iBQnFhYWcLJAvSAkJATuxsbGnjx5ElHDiA+ORQ3j4+Nzc3MDPteiRYu8vLzQXRijqKuroyvV1dWzZ8+WlpYGQQE8HcS0AtmalpaG0sPoHJhW9fX1c+fOnTlz5tq1ax8+fOjg4GBiYiIiIoKoYcDalZCQADnQ1tbm5uYGzKbg4GBYkoDmCk4K41DDiHIAqHPl5eXgJAJtFdQkjuPp6engpQmnixYtYmVlpSoBqAsAGxsbOzs7kRpGJpOBfINKADFAoQQQNQzIcYh42N7ePmfOHMQtBWWgp6fn5ubm7Oysp6cHa9hAjgP3FhYWFiJlet68ecrKym5ubsRuDkYpXl7e7wp/KmpYY2OjtrY2YpZ1d3drampCw3j27JmGhgYiPB49elRbWxtxEnfu3Ilh2KgOFKgNEKlh4EaBiHs+Pj5WVlY9PT04jisqKj59+pRIZaeiy5mZmWETY2739/c7OjpCG3Bzc9u9ezfokS9fvgCtEsMwIiE6KSmJnZ391KlTUIYuLi7s7OxIUB87dmzhwoW/kBrGMM46EHEcRNxmmYWFhWhwZmFhAbMezGCYmJjAIPD169eRkRE/Pz8jIyNTU1M2Nrb+/v7BwcErV67Y2tq6u7uzsbExMjKOjIw4ODhYWFgwMDAsX758ZGTEycnpwoULZmZmFArl27dv69evb21thdeqqKj4+flRbZTz7t27PXv2gHLi4ODg4OBAToTv37/funUrIyMjGxubnJycn58fDDOHhoYCAgIqKirglri4+O7du5mZmfv7+52cnFhZWZmYmKAfOjs7MzIyguc3+sSkSZNiY2PR+OvChQvQqc6fP8/KyhoTE9Pe3i4tLf3u3buKigrgtqirq/Px8WVnZ3t4eJw4cUJAQACtFKxdu7ajo4NMJm/bti0hISEqKgqZ6cAPW1dX99GjR/n5+UePHoW8Dw0Nbd++HXwKAwMDo6OjL1y4MKpH/MjIyLlz58Ap/MyZM9zc3La2tqysrIsWLaquri4pKfHy8jp58qSioiL0nyNHjuTn5/Py8sbFxY2MjCQlJQEVWV5ePigoqKioKDQ0lIODY+vWreAKRQUHB4dv377p6el5enpmZmbGx8czMzP7+vpGR0dDK4KV2ujoaA4OjsWLFycmJjo5OSkqKgYFBaHi/eOPP9TV1Xfu3FlaWsrGxubg4GBpafnt2zc3N7dv375B1cyfP3/NmjVMTEx1dXUbNmxgZ2eHOdng4GBCQgJsFzUyMpKcnAzL7XFxcWiZgIhv375t3LixsbER3iAvL79t2zZiA0tOTs7Pzwc/K4ShoaH29va1a9dCGwZBb21tHRcXl52dDdkkVjHg5cuXFhYWpaWl341e0NPT4+LiAi+HEYaZmRnaA+vx48dARAoMDKyrq0tMTPz69Su05Li4OC4urpycnKNHjzIzMwsKCkZGRlZUVGzbtg0SQJYTEhLCw8Nfv34ND7KwsDg6OlLNOdAyno+Pz6pVq6Kjo+EN0dHRJBIJiigjI+P8+fPo69HR0SDdQkND8/PzWVlZDQ0NFy1a5Ovry8jI6OHhce3atfb29uHhYbi1atUqUGw1NTXs7OwrV640MTEZHBwE1zhmZuatW7cqKSlt3bq1sbFRTk4uKCgIWpGzszNsmIXjuJGR0cqVKxkZGYeHh0+cOIE8vzdv3tzV1XXq1Cl2dvYZM2aEhITQ5m5oaMjf3//9+/dIFrm6uhobGw8NDdnb27OystbU1EyZMmXSpEkHDx6cOXMmyAEQdBwcHNu2bWtoaKAtAegFHBwcXl5e0dHRIAnZ2NhWrlw5Vgk0NDQwMzOvWLFi4cKFEREReXl5IEXBZcDFxQVawrdv34qKimDpl4ODIz4+fvfu3eXl5WxsbMuWLcvKympubh4aGmJlZdXR0QED4Y4dO96+fSsqKgr8fyTSNTU1d+7caWFhMX5TjIiIAP8IdGVwcNDFxQW6G47j+vr6Hh4ejIyMIGxRTwT1hozDgYGBGRkZeXl5VGtAe/fuLS8vhyKCZ2NjYydNmjQ8PNzT0+Pp6QmzVQEBgUOHDsExURLq6emtWLGCakfCtLQ0GxsbUG1VVVV2dnY+Pj4rVqwYdU1haGhox44dlZWV4KTj6enZ2dk5f/58FhaWp0+fDg4OMjMzCwsLQ487e/bs9evXWVhYtLS0/vjjj6Ghod27d8Ok2dramkKhnD179vbt22xsbGfPnqValPmrZs90/B5ERkbOnTsXTTdhcGptbU2cOVHhw4cPsMhHL71/Pl68eCEpKYlcy+j45+P9+/dtbW3/ffkaGhrauHEjsOi/O3uWkJBA7mo/h4aGBllZ2Ym7Qf9JwIY84GQYHh5O5Rj2LwI9tN8/CEVFRSIiIsSt3rm5uccPRtnT08PFxTVBohAdfy+Sk5MDAgLoAbv+RZCSkhqHkP/vxaNHj1paWmhZY6Oiuroauaf+HIDxirax+6tRWFgIB11dXSdOnCBug/jvAjO9B/5zwM3N3dnZOTAwgGw1r1+/Tk9PH8cNRlxcPCUlZVSzLR3/EHz58mVwcJCFhaWwsJC+aTkdfyMGBwc7OzsxDDt+/PgENS4HB8fUqVPv3btXVVVFoVAmQoujBWyx9+ddOb4L2BmNRCKBCCWRSFevXv2Vu2z+Xkxo7ZmO3wYzMzMBAQEUYenMmTNHjhxBe9fR8W/Erl274uPjxcXFLS0tqfZXoYOO3zxphg09TE1N0daYdNDVMx0TQkdHR1VVFXHoCpvo0vHvRWNjY0BAgJeXl6qq6i9gi9BBx8/i2bNnEOcRdsqkFwhdPdNBBx100EEHHT8GOjWMDjrooIMOOujqmQ466KCDDjrooKtnOuiggw466KCrZzrooIMOOuig4zeq57S0NNjf8U+iurr65MmTrKysxCCS/3C0tLQkJyeTSKRfUgK/EN3d3bBJJ9pk9PcjIyPjh4JDjI+UlBTaQJbfxa1bt5KTkydPnkwbcAyhuLg4Nzf3u6+CrUDPnDnzxx9//JIclZaWEuN2/xDevn2bnJxsZ2enq6v7D2lyxsbGrKysrKysKOZ0aWlp8v8FVahTSDDBECnPnj1LTk6+evUq7a3nz5/D+0cltEIbQFXc29vr5OQkJCTEyspKGwFzgnj//j1t5NnfgIKCgr+9omtra9XU1FhZWZ89ezZOsoqKiuTk5GXLls2dO/fX/kBubm5ycvKoexX/AwGN3Nzc/Bf+8A+o59WrV7u5uf3cZ4aHh/v6+qBTMTIyMjExwS5x/xb1zMDAwMzM/E/752/fvoWFhTk5OV2+fPlv9I3esGGDjY0NbHfw57Fs2TJibLgJgpmZ+cKFCxB3ZNQE5eXly5Ytm2CcY2Zm5sjIyHGC+k0cjY2NNjY2W7Zs+cn+ycj46dOna9eujRNYc2RkZIJBV38JIOrM5cuXITxRU1OTra2t/f8FaBcIEOLo6Lh8+fKCggIHB4edO3eOkxHYTJtCoaxcuXLZsmVWVlbPnz9Ht1atWgW3HB0draysiCOtiooKe3v7rq6uCxcuODk5ZWZmYhjGxcV18eLFy5cv29vbTyQsKS16enpsbGwmHuT+V+Ho0aO2trbjK8W/Gn19fceOHQsICHBzc6OKMAb4+vUraqJtbW2pqak/V8jjd8MHDx5AzJuJYHBwcGBg4G+b6TIyMjIyfvv27VeWw+/ZOxQiu6GQSk1NTRiGHTp06N+1AyonJ+eVK1f+Of8TEhKioKDwt/+Gv7+/h4cHilTzJ7Fq1SpiQKQfAg8PT0JCwlh3z58/HxkZOcFXGRsbe3t7//nsfPz40cPDAwVc+gl0dHSYmpqOs+96RETE/v37f1t1e3t708ZrsrW19SCgqKgI8o5hWGFhIaS8dOkSGxtbfHz8WG9ev349CkoWFhaGYZiwsDCK2eXg4PDgwQMcxyHq2qRJk9BO5oqKihCEDcdxiP5CfO2+ffuUlZV/IqcQyPL379h86tQpDw+PsULz/R7Y2dmtWLFirLunT58mNsiuri4zMzNi1LJfhdjYWNQGxkdbW9uiRYsCAgL+xkKrrq5WUFD4hRGrftOmnqPahOmbD/8ZQESXf8Kf7N279xe+LS4u7ucejI+PJ4bWpsXy5ct/f+EICgqOFeP2hyw3Y929fv16YGDg1q1bf1uORt2ace/evbNmzRr/QUdHRx8fn/HTJCYmQvg/b2/vhoYGiDYGOHDgAARR9vDw+PDhQ0REBFyHAO2mpqZwCsEc9+7dGxAQ8Cdzun//fiEhodbW1jNnzvy04fAn4O7u/vcu/BUVFRUUFMD+YqOiqampuLgYnba1tUGI27/xnxsbG+/cuUMMOP37ISwsPHfuXIhj+2vsBxNMd/fu3Tdv3jAyMsKuhMXFxdnZ2XPnzpWUlExISIA0vr6+Y22KFBUVRWt9hWycOnWqq6tLXFzc1taWKsH58+dbWlqEhIScnJxGfW1bW9vZs2dXrVpVWFj48uVLDMNkZWWJcfFaW1urq6s1NTXRlbKyMnZ2dgkJCThtaWmpra3V0NC4d+/e69evly5dCo3s+fPnDx48wDDM1dWVdk/85OTkDx8+TJ482cPDg2oZ5vr16xiGcXJyEm1iDx48aG9vt7OzCw8PZ2Bg2LBhA8wqHj16BAkMDAxmz549jsYCTbx48WIFBQXUQ/bv349OadHd3Y0Ug7CwsKOjI1UJXLp0qampSUBAgCq8OQynoHa0tLS0tbWp9AFMmGbPng2hOJqbmxMSEtauXcvFxYWSXblypa6ujpeXlyhoMjIyUMRye3t7UVFR2t9++/bt3bt3fX19URVXVlZqaWndv38fqnjjxo2jBoYTERFBgSBTU1NramomTZrk6elJTHPr1i2qTYPz8/PBTOrp6Tlp0qQf6gVUiI6O7uvr27BhA5U2ffLkiby8PC8vL/Hi69ev7927p66uThSCNTU1qamps2bNgoC1gIGBgU+fPo2aZQzDzM3NRy3GgYGB48ePf7cEaAskIiLCxMRkHFFbU1PzQyLm1q1bEPodwzAxMbFxWiyxFzAzMxP1vba2Njc3N/EfkD6mgpGRkZWVVXl5+Z+UjCUlJfn5+U1NTVpaWomJiRYWFhOPjUFVqhcuXPj06ZO7uzu0gYyMDGNj45GRkQcPHpiYmIxaC2/fvmVmZoZYzoDHjx/DksH69ethQ2l4qqen5+XLl0BNaGhoaGtrgzizZWVlWVlZ3t7etC9H6O/vj4qKou3mPDw8kydPHieD8vLyxFNeXt65c+fC8taHDx+Sk5OlpaVpQ1V+/Pjx4sWLYmJidnZ24xfg7du3y8rKLC0tR71bXV2dlpZGJerHwosXL7KysjQ1NXV0dMZPeebMmY6OjjVr1hDjvfb19eXn5xsYGDx9+vTp06d6enpz5syhfRaq2MjI6Pnz579yO7YJzrI/fPggISHBzMwMp+fOnWNnZ1+zZo2bm9vevXs1NTV5eHjc3d1h8Y+Ivr6+8PBw6GkODg4w8Qfjtr6+fnR0tIqKipyc3OTJk8lk8uDgIDz1/PlzQ0PDjIyM4uJiPT09MplcWlpKZcqgUCjQEI8fP66oqCgnJ8fNzc3Ly/vo0SMcx1taWigUioqKyoEDB+CR4uJiR0dHMTExsIN9+vTJ2Nh41qxZGzduXLp0qba2toiIiISERGlpqaurq5GRkaSkJIZhlpaWRON2WFhYYmKihoaGnJwcDw8PmUyuqanBcfzLly+lpaVqamqxsbHFxcW2trbbt2/v6+tLTk6mUCizZs2aO3eur68vAwMDBwcHjuMvX75UUlJKSUkpLi7W0NBQU1ODSONUyMnJMTY2trW1LS4uVldXV1ZW3rp1K9zKy8uDjgThYKkebG9vt7e337JlS3Fx8ebNmydPnpycnIxKICYm5ujRo/Ly8igXxcXFqKL19fUNDAyKi4uNjY2nTZv2+PFjFInd0NBw7ty5cnJy0tLSPj4+Hz9+pFAosEM4Ck5XVVWlr6+/cOHC4uLiJUuWBAcHQwjFlJQUBQWFgoKCvLw8QUFBTU1Nqn9+9eoVhUIRFxfn4uKCLEAVCwkJJSQk6OjoQBWvXbt21LKqq6sjkUgHDx7U09PT1NSErAUGBvb39+M47ubmRiaTzc3NUUC90tJSJyeniIiItLQ0OTk5VVXV48ePDw8Pj2rcbm5uXrJkiba29rFjx+Tk5MhkckpKCrp77949ExOTmJgYeA+ZTCaTyYaGhrdu3bKxsREUFLS1tUWJy8rKgoKCjI2N5eTkFBUVrayscBzv7e0NCwtbunSpnJycgoLCvHnzUPr6+noFBYVRjds1NTUhISHs7OxCQkLw0Z6envr6ej09PQcHB6oSKCsrW7BgAS8vb0ZGBpTA0aNHyWQyRCNtbm5eunQphUJRUFBQVlb29vb+/PnzqKLAz8+P1rh97Ngx8n9QVVUFt1paWqZOncrGxhYcHFxaWrpt2zZ3d/cJCpyKigolJaVR15IaGhp4eHjA0N3U1DR9+vTo6GhiAkdHR4gY/dPG7ZGRkf3798fGxuI4Dgy4+/fvj7N+QaFQNDU1yWTyyZMnyWQyLy/v/fv3Ozs7V65cSaFQbt++vX37dhUVlYsXL7569Wr+/PmqqqqqqqrIEmtjY0Mmk21tbe/cubNq1Sp9fX1xcXEUWLatrc3e3l5fX//u3bve3t4rV67s6up68uQJfFFVVfXw4cOQMjExEVb3ofs4OjoaGBigNk+VwRMnTpiamvr4+JiZmSkqKlpaWkLozKampsjISAzDpkyZQiaTDx48SHwQBJ2MjAwDAwOZTFZXVz937lxNTQ0/P7+CgsL27dsXL14M8pzYwaurq3fv3r148eL9+/fDb9fW1tL+VW9vb2lp6aJFi+bNmycnJ6esrDxjxgyicfvmzZuLFi1asmSJnJwcLy+vtrY2WoYALqGCggKZTPb29h4ZGYmLizM3NwdJPm3aNHt7+1GrD+QMiJopU6YoKiqmpqbCmpGpqamSkpKzs7Ojo+OCBQvExcWnT5++evVq9CyqYjU1NTk5ORUVFQEBgV9o3P6BteerV68i9YzjuIaGhr6+fmtrK5xev36dmZkZSJVENDY25ufnr127Fkb0aWlpSD3z8/ODKsVxHMb4oJ4LCwtFRUU3bdqExJOmpuaiRYtofwmCrmzcuBHWt9LS0jAMIy6ZKCoqIvWM4ziQfdAy1ePHjwUEBDAMgyXJt2/fwgbXUAEdHR0GBgZE/cTJycnIyIi6TWhoKIZhwcHBOI5DEHgU0LS5uRnDsM2bN8MpzAWtrKyCg4Nnz56N4/iCBQs2btyIFG1ERMSoullRUTEnJwddcXZ2lpeXLysrw3H87NmzRkZGCgoKWVlZtOt5UVFRoqKi6PSPP/6IiYlBJcDOzh4cHFxXV4fjeExMjLa2tq6uLqS0t7dfvnw5WvU0MDAgk8mgdFVVVdHKbktLi4+PDxzLyMgg9VxSUqKgoHD9+nW49fbtWwzD9u3bh+O4gIDAmTNn0PBrrMVUBwcHUM8AGIEdOXIElQDM4GkfTE9PZ2NjwzAM2hiO4/Pnz4d5Ko7jtbW16urqS5cuRX0SwzDUxnAcB7sr+kOiem5sbNTU1IyKikKq3crKSkBAAE6zsrIUFRXz8vLg1MnJiYmJKTg4OCwsDJXAnDlz4G5KSoqSklJ5eTmcHjp0SFZWlqoNJCUlsbCwXL16FbWl+fPnj1pcZ8+eDQ4OnjZt2sKFC4ODg4ODg/v7+x0dHVEJQAz5N2/ewOmtW7dYWVmtra2hBDQ1NaEN4Di+adOmY8eOwfGVK1fAaDxqBS1fvpxWPfv6+gYHB7u4uGAYNmvWrJKSEtS2p0+fjiYDLS0t35UzycnJ/v7+0tLSZDK5urqaeOv69ev+/v6Kiory8vJQhh8+fMAwLCgo6Neq58HBQVVV1crKSgj5DLai8R+BsEhbt24NDg5WVlZ+/fr1kiVL1q1bhxJISkoaGRl9+fIFx3EWFhZOTk7iiA3DMDSsgVUYkDNdXV0GBgaBgYEo8eTJky0sLIaHh7u6ujAMmzFjBroFdhTEAjlx4sRYNI7ExEQVFZX3798jUSMgIGBgYNDd3X3jxo3g4GAFBQVVVdXg4GCqZlBdXR0cHOzo6AiNHDpma2urjo7O9OnTg4ODYVRHoVDY2dnRU2Bpa29vR5LEzs6O9q+ePn2KYdjJkydRRzA3NyeqZx0dHURlsLOz4+bmhuPc3FyIBefn5xccHJyYmDgyMqKsrAwZ7OzsXLhw4VhtIDIyEgnqzMxMEokUFxeH+heYFo4fPw5qa968eQYGBnD327dvS5cuJZYwUKz+Kep5586dxATs7Oy06hkAhg4qatiSJUtQAlhAgilyXFzc5MmT0Xyup6fH1tZ2VPUMpD6YvwKkpKRQnX1XPeM4Li8vv2XLFhRs3N7e3tLSsre3l6j+EYWNk5NTTk6O2Id9fX3V1NRAyYElhKiepaWlkXqeP38+zPk+ffoE6nnZsmVPnz6tr6/v7+8flVcVGhpK/Bw8y8DAAINlsGKNRQ2LiopiYmLy9fV9+fIl2DDAsAElQEXi2Lx5Mzs7+6VLl+7du8fFxYXUM5QAqOcTJ05ISEjAPAw0N6gfKvV84MABNjY29Hhtba2wsDAoJwEBgR07djx9+hR6KZQDLXR0dKjU88aNG5FZBUpgVPXc2to6adKksLAwoBbjOA7cV9SdPD09kXrOz88HszN6vLi4eOrUqWiqQVTPYBZramoijuKnTJmye/duHMeDgoKgDSAFTCwBUM9o/LRy5UriTLqzs3Pbtm04jhPbQG1t7ezZs1etWoXSmJubj0MNU1JSIlLDiAULHGaknnEcT01N5ePjW758uZWVFZGb2dbWhnoBLECMpZ4PHjxIVM91dXWhoaFgIOnr66uqqmJlZRUREcFx/OvXrwEBAWpqalpaWlpaWoKCgqKiomOJCISgoKCKiorS0tKZM2fKy8sTp1mHDh16/fp1VVWVtLS0mJhYVVUVqOcFCxb8WvXs5eWFyFlETQAAIABJREFURvnQzWVkZBobG7+rnpubm6EKgAZBnHPDshcMUI4fP87GxgbqH0aWGzZsQI38yZMnDAwMoJ7r6+vBQoveAysFw8PDw8PDe/bsQer54MGDc+bMmTZtGlJgZmZmo9Jv29vbDQ0NnZ2diRdhPaWhoQFNkMahhqWmphLbQHd3t7W1NVGqJCcnMzAwbNmyBZhurKys0FlQL0DamggNDY3AwECY/Y9KDSO27aCgIAYGBn9/f2R7A9M6Mg+gxBUVFfv27QPvU9q8dHV1gVj78uVLY2OjkJDQ1q1b4R+qqqoUFRXRPATH8Y0bN7Kzs4PBCbRPZmYmujswMODq6vrvo4atW7cuPT2d6iJaAEYICgqCkXtXV5eHhwfMfpqbm1NSUkb1Zz137hztO1taWn7o3/j4+IiLhZMmTeLk5IRjExMTWJtB2L17NzpmYWFBC4pBQUEwj4dXQedcsWIFSszBwQFLm1OnToVbrq6uSUlJGhoaGhoaNjY24xAxEKZOncrAwLB7924/Pz9GRkYODo6xPGq0tbVFRUUjIiISEhJg1dnBwQEtLxFzgWGYhYVFXFzc58+fOTk5e3t7nz175u3tDbdQYPOgoKA9e/agQNS8vLzILXjFihWIhhMUFPTt2zf0OIZhaPK0YsWK/fv379+/f/HixZKSkt7e3lAUVCAu/ACePn3a09MDK39QAqNmmZ+fn5GRkZgA3g/8W9qWRnVl9uzZFhYWnz59ok1M+4YlS5aoqal1dHTAaV1d3YMHD2AlnrbKFi1aFB0d7eLiUl5eXlBQQAxBNnny5AMHDoA948aNGzk5ORiGvX///vnz58hVd3h4eBx3kXv37sFgl/jFwsLC8+fPwxo8VXpra+srV65cuHDB19d306ZNxF7w/v17sGqOWi/ElT/i6YwZMzZv3owauYSEBAMDA5RYR0fH3r17CwsLQaPk5OSYmprGxsZaWlqOQ3bbtWsXYjlYWlpGRUWBmQqsHagBUyiU0NDQHTt2jFXFfwatra2vX79GzfjZs2cVFRWJiYl+fn7jPGVlZYX6OOxDcOzYsWvXrsFdGLIDjI2NZWRkQkJCgB0SExOze/duRNzp7e2lEnEhISFg5wOyIfLk4efn7+zsTE9PnzNnzuXLl9PS0kJCQoKCgm7evFlYWFhXV0esYoTc3NysrCwwRBElG5DeQbKNz9ulErzNzc1paWmIYYCWTdva2oAEMzg4eOvWLVRNBQUF7OzsXV1dVMu0ra2t/Pz8iEEyam+6cuXK48ePMQzr6elhY2MzNDQci1A5derUmJiYsrKyoqIiMzOzwcHB7u5u2pQ8PDxtbW2bN29ubW2FLHz48GFkZISJienr16+0AnbGjBnAnwgKCtLU1CQyJJqbm58/f45q6vdRw/4kVq9evXr1aqo+aWNjQ5UM8e4EBQVh4A+IjY2lYtagNxw+fJh4RUpKCiZGvwSPHj3i4uIai4RCi4CAAKTAQkNDeXh4wGZ1586dGTNmEFOuWLHCzMwsICCgtra2qKjozJkzdXV1RO5JR0fHWDtsKCsrYxg2NDTU3t4+FhdPWVn55cuXqampV65cqaysfPjwIVhpgGEUFRVFzNS9e/cUFRVXrFhx9+5dBgaG2NhYFHAaSDqI+kehUNDYBSE1NdXJyQkyC+mplB+84cCBA9u3b1+5cuXw8HB2dnZGRkZlZSXtn0tJSYGWIjKGxieqjM/c/qvJnJKSklJSUklJSeAJeuXKFSSRgdr28OFDMK7U19ejBRQqnD59+vjx41evXgX5ThSdra2tOTk5ZDJ51K/r6OgQtWlLS4ubm1tFRUVMTIyqqqqHhwesDlCNlcvKylJTU48ePQpXenp61q9fn5OTc+jQIQMDAzY2tsDAwHG46OMXiJeXF7DtVq9evWbNGvQDurq6mpqaWVlZIyMjEylYRUVFYWHhUW9ZW1sD1VRYWHjnzp2j7mHy07h161Z9ff2TJ0+IF7W0tHbu3Onk5DRO9j98+ICkOSjjlStXEveTQXJMWlra0tIyNDR0xYoVr169mjJlioaGBkoGaxOob2IYtnbtWqpmA2NQV1fXc+fO5eXlSUhImJqaioiIyMvLnzt3LiUl5dmzZ2Br/QlMmTJlfH6TjY0N2DtRk7C2tq6rq0NXNDQ0iNpaSEjo2LFjwOYBxcbKykrFxLxy5cr4M6uKigozMzMuLq5r165xcXHduXPn0qVLNTU1CxYsGJVTxc/Pr6qqeuXKFSYmpujo6BkzZtBSyQYHB7du3Xr58uXAwEA7OztgF1VXVw8PD7OwsLS2ttJq9J6eHjTOePHiRVVVFZLtJBJJSEjoF/o9/6ZNPZcvX07bJy9cuDDWle7u7nv37vERMCpzlfYNE+z5E8TAwEB1dfXt27dHvfvp06e0tLQ1a9YQmzXxn0EtSUpKLlq0iFZn8PHxxcTEZGRkhIeHoz1biK+iUCiNjY20VgfY44KRkZHIlKbC/fv3P3786OrqmpGRkZGRsXPnzuPHjyPtBes0RAInExMTDCxwHD9z5gwxF0jvjuW21Nvbe/HiRWjHa9asYWBg4Pu/gDecOnWKj4/v5s2bGRkZGzZsIE4Rxq9BTk7OcQbUVAJrItPxUVFeXp6dnT3BhpGTk1NSUgLHzs7OkZGRJ0+erKqqamtru3TpErG6R0ZGBgYGoqOjQd9Q0eAR9u/f7+rqKi4uDiVGnLsICgoaGRmNX9HotLCw8NatW6dPnzY0NOTj46Md1rx48cLFxWXz5s0tLS1oDlRVVXXhwoWQkBA7Ozs+Pj5Ywh8L33Xni46OBkev3t5eDg4O4qB869atq1atGrU2KysrQRUhZGdnw9JAQ0MDVS94/vw5WOCZmJioxosvXrzIy8sj9sofRWRk5B9//EHVhtetWwcm0Am2QCgBbm5uqvcgObZ169avX78ODQ0NDAxQTcqdnZ3RqyAjPDw8VO+BBOzs7CwsLDdv3tyxYwd0E29vbxYWlq9fv+bm5oL18SdQXFw8/qYoVIIXZs/EK8+ePSsqKiJytu/cuUP8f1ovCXt7eyqzTX9/f3x8PDo9e/ZsRUWFu7u7qKgolABg1D+MiYnp6Ojw8/Mj9gLa6vv8+fPRo0eB5szHx8fBwYFhmIeHBwjDUd9PvDg4OEhUxtXV1cRRy+9Tz8+ePQOTAuDdu3ft7e2lpaUTdL19/fr16dOnL126lJycTDULpJ0XSkhIkEikS5cuoY2oiouLkQ8SbXqqD1Fd2bFjB3hPpqSk/MTOiGJiYsSJJoVCAfeGd+/eJSYmmpubg+MQtFd9fX1YK0JFBEUHNkMq+9J3Py0rK8vIyHjx4sUvX77Alfz8/BkzZoC5mJ2dHRZ9xxppEi1+TExMUVFRqEs4ODggt8WYmJjMzExwTDc3N7ezs6utrUWdrbS09O7duyiDCxYsII6REdDs2dHRETgmyJT35s0bELvELOvr61P5Zvz5ya68vDwzMzNQtMBEbG1tffHixVFnq5Ad4iT106dPlZWVtAO+URNXV1fDlm3ggWNhYXHo0KF169YtX758VN0DXnbTp0+XlJRMSUkZ1U35+fPnX79+zc/P37BhA6xTAhobG2/evDlWrpcsWSIiIgKTbLRrJmjE9+/fU40LCwsL7e3tz5075+zsvH37dldX1yNHjlCVfENDw/jrLFRdzMLCgrivU0FBgZCQEPySlpbWu3fv0BIAlOG8efOYmJiGhoaSkpLmzJlz8eJFJDq9vb3RDprfvn27dOmSjo5OSEhId3f3pUuXUC/AMCwxMVFeXh4GPXJychiGAbsKiqu2tnYsL5rCwkIuLq6kpKSxcldYWMjDw0Pr+QMvpDII03ZYNK5iYmKaM2eOra3tixcv4Ep7e3tSUhJap2BiYlJXVzc0NGxubqYyjQA1ifhdc3Nz5JHY1NSUlJSEEly4cKG0tFRQUBA1Ki0treXLlzs6OkIt0MLMzCwsLCwhISEjI4NYNSEhISBb1NTUiLN5WiBvPfAfITZy2tnzrFmzeHl537x5Q9zalvgg0UTh6+uLWjvyJaNFXl5eXl4eMzMzlZ9eXl5eUVHR4OAgUdrcv3//9evX9fX1Y020AJ2dnUlJSf39/adOnYJqqq6uJo590cQJjDogFuzs7GBvu5KSEqrx5S/ARBaoS0pKwsLC0tPTr169SqFQXr16FRUVFRYW5uLi4uvri5Lx8/Pr6+uPuvyelZVFIpFIJNKuXbsePHhgbW1NIpEEBQUpFApQioAyJyMjAz5CN27cIJFIixcvNjMzW7ZsmZKSEnEFHjlWTZ8+nUQiWVpa3r17F67r6ury8vJSKBQgdp47d45EIomIiNja2hoYGFy7do1EIhkaGp45c2bXrl0UCkVISEhDQ2PPnj04jru6usrIyMjJyVEoFODyhISEkEgkTU1NoGdPnTqVRCJJSUnZ29traWmFhYUhCm5LS0t6evqUKVP09fXNzMzs7e01NTWLiopgz1gSiTRz5kwKhRIeHo7j+IMHD2RlZW1tbVevXp2QkLB48WIvLy/EmyPi4sWLJBIJXImcnJxkZWWfPXsGxWVlZQW2FAqFQkuIjYuLMzY2NjMzy8jIsLW11dHRAQIdUMM4ODiUlJSsrKwoFMr58+cRgRPH8YKCAhKJxMvLa2ZmZm5urq6ufunSJSBeQQY1NTXh1rlz58ClRFBQkEQiWVtbZ2dnA7GFRCJpa2ubmZlZWFioqakBk2L27NlmZmbBwcG7d++eP38+YpZROVZNmjRp8uTJFAolNzeXQqEICwurq6vv2rULJePm5jYwMDh16hTV4xs2bIA2ZmdnZ29vP2/ePOBboh2pFBUVJSUlgTT09evXdevW8fPzm5mZlZWVxcbG+vj4pKenw558VlZWEhISSkpKnp6eQM5ycHCYMWOGmZlZa2trcHCwjo5OaGgoIn9Nnz5dXl7ejIBDhw59+/bt1q1b5ubmJBJp+vTp165dA8r6jh07WFlZUco//vgD6F0sLCympqZycnJXr17V09NTUFDw8vL6+vXr2rVrSSSSqKgohUIZ1dlJU1NTWVlZV1c3Li4uIyODRCIJCwubmZnt3Lnz9OnTJBLJ1NQ0JSXlzZs3MjIyUEfADyKRSPz8/OfPn+/q6nJwcIDS2LRpU1paGolEsrCwQExAqjZJpAUlJSXJyMj4+Pj09PSsWLFCXl4eEe6am5tJJNKyZct6enpevHhha2urp6cH5B2wncycOZPKZWvRokW3bt3q6enZu3evubk5OIZ0d3c7OTktXLgwJSWlp6fn6NGjxsbGyJEPlUB1dXVPT8+SJUuQ8yEtNczHx4dEIo1FT3v9+rWMjIyUlBSRvocoPyQSSVxc3NramqqrEnuBhYXFvXv3kI8iOPhBRZuYmFB18/j4eH5+fsRyR6RFOTk5EokEjbyvry89PV1OTg684c3MzAwMDLZs2YL4j3V1daysrK9evUJvuH37NolEGl+kDw0NkUikefPmHTt2rLKy0sbGRktLC+RAXFzcggULSCSSnJwc0YmIykuCm5vb2tp6zpw5t2/fhkYuIiJCoVCA4Xj16lUSiSQtLQ3U1MTERBKJtHDhQjMzM0tLS9icdVTOmrW1taioqJmZmZWVVXR0tK+vr4CAgK2tbVVVVVlZmbi4+OzZsy0tLSMiIrZu3UoikRQVFUEIv3nzBv5h1qxZXV1dRUVFkEFra+vTp0+7ubmRSCQNDQ1wHkMAOSAgIGBmZrZmzZr09PQZM2bMnz//yJEjEREROjo6JBJJWVl5w4YNiJsNwg0sH35+fpDAyspKTU3txIkTdnZ2IOoR0e83Mbd/PxobGz09PSfijPFdH8qHDx/+qr968uQJlRM2lUuGp6cn+D6Nj3v37nl6et64ceO7KXfs2OHp6TnxDSnRCMbT09PT0xP8XIncdfDpotVwCJ8/f/b09ESsSCJOnDjh6enp5+c3/tfDw8M9PT2J3P7S0lL4n/Xr1/+lzSY/Px+cqSaya6Pnf9DR0YEkF3KvIhZReXk5pKRyViksLFRQUPAkAAwqxAFldXU1kcQbHR2NEiOuaVJSEq1/3Z07d5Dv0zhIS0tDw4WRkRFPT08kUID9e+fOnYqKCuTHSCwB5MG1ZcsWT09PpJI/f/4MszQqcHBwENVzc3MzyguMPqmwb98+uEssAVDP4LtMxB9//AGJabe0hF7g6emZn58/agnAXeQ98RPM7bdv34IfI1XXuHHjBhoNnD9/Hmjqo6KsrCw3N5d4JTMzE35sVFcF2j44aq8ESQgA1ywiMjIy6uvrf6KnREZGwjth7Pijvmdnz54dP01ubi6awOA47u/v7+npefTo0e/OBj09PZF3E1UvuHTp0jiSkErUR0ZGwuxifLS0tHh6eo7PzB8f48jSPwMG/N8Tl4KOPw9gJB45cmTUfa/o+FHU19dra2tHRkYS90gaGBjg4ODIzMxcuHDhf1+WwUMaRUT4OezYsaOhoSEyMnIipL8/g6GhIX9//zt37oDjDR10/IvATC+C/0FMMLQfHd/FwMBAXV3d37vb8G9GdHT08PDwwYMHOTk5iR50P4QPHz6gVee/Ds+fP79y5UpoaCgtSYUOOv75YKQXwf8gfuWusP/bYGVlnTp16oYNG8DFE8Ow7u7udevWeXl5EXd6/29CQUGBu7s7Jycnkeb5owBv778aFRUVBQUFL1++nMimAnTQ8U8D3bj9P4Ty8vJz584dPHiQjY3tjz/+WLNmjZiYGL1Y/iQeP36clJT09u1bILu+e/eORCLBriB00EEHHXT1TMf30dfXR/S2EhQUHN/DlY4J4uvXr8Q9oQQEBGg3b6GDDjrooKtnOuiggw466Ph3g772TAcddNBBBx109UwHHXTQQQcddNDVMx100EEHHXT860D3e/7/+PbtG2xmxMXFNVYkqH8j+vv7YRMJHh6esXaQp+O7gIDZ/94y/Lf//zjo6ekZGRnh5uYeNXDOv0UOQC6YmZknGMTlHytJ+vr6BgcH4fivKENUQRiGsbKy/kka5tevX5mYmMaJcPo3gk4N+/949eqVjY1NVVXVxo0biaEC/nZ8/PgxLS3N3d0dRav8IVy7dm358uVfvnzp7u7m5ub+L6ipwcHBkydPWllZoWDSfzWePHliamra09PT29v7b2Rl5+XlmZqadnV1/de0AYTnz5+bmZk1NTXV1tb+EkfBdevWQbCNO3fumJiY/LaMSEhI1NTUmJiYjBX16Pz5858/f/4JOVBcXDxWmF0lJaUJBgpqaWlxdHR88OABKGAI7jQqXF1dz549a2JiAmHdZWVlOzs7ieFxDQ0NR93J58KFCyoqKqPuIXP58mUpKSkIgl5SUhITE1NRUXH//v01a9ZAtNYfKgFxcfElS5bA8bFjxz58+DBz5kw4dXFxGScS4O8G/r+NhoaGmpqab9++oX2hMQyj3fr4d2J4eLimpoa40zKEnm1vb//pd0LUd5g//RtRX19fU1MzNDQEpxC80t7e/vd8PTc3V0FB4ebNm7m5uegf/l2oqak5fvz4v7oNjNM2IDJmbW3tn39bSEiInp5ebm5ubm4u2ob996CwsNDGxsbExGSsBKCcfuKv6urqLl68yM3NraKikvsfhISEsLOzCwoKvnnzZiIvWbp06bp16+DZ8XuBi4sLhmGpqanoioODAw8Pj5iYmJiYGCMjo5SUVFNTE+1m/mxsbLT7aX/79u3YsWOcnJz79u2jCs3CwcFRUFDwEyVAjInQ2Nh45coVDMOkpKRyc3PH2VD99+N/XT1DWEO0oTxEU1+zZs3f+EsQdo34D7W1tdu3b+/t7f3pd0I4zvPnz/9Lq0lcXNzY2BiVQH9///bt26urq3/P12VlZQ8dOvRvb+rQBv771DOO4xDj8s+r59raWnV19dOnT/9dGVm/fv046hnkAG3Mjwliy5Yturq6xCsQb/Tp06fffTYnJ0dRURHihXwXycnJjIyMRPVsZGSUlZUFx25ubhiG2dnZUQWlCAwM5OHhoVXPKEQvrXpmZWX9oWAemzdvpioBQFVVFYZhqqqq/7SG/QNLNd3d3a/+g8bGRuKtz58/w/Wurq6xHq+rqxsZGfmnWcaIMUoRYJT698LBwQEdi4mJ7d+//8/bVP8J+fppmJmZoRJgZ2ffv38/skfRQccvQU1NTVFR0T92N1aQA+NYlX+J9BsV2dnZlZWVoMa+C4g2hk5v3749ZcoUAwMDOI2IiDA3N6f9E2FhYdrNhtvb2/fs2fPmzZtZs2bRfmhkZAQFCP+vxA+sh0dERMCaB6xiRkREwPUbN27k5+fz8PCUlJRAWGIIZh4ZGdnQ0CAiIuLj47Nnz57k5GRjY2MXFxclJaUTJ06gmt6yZQs/Pz/6yrlz51DgcV9fXwh8TbWSv3PnTh4eHn9///DwcAiXbWlpOW/evMTERBT8fO3atUh819TUENcn3Nzc0MoHLDJRQURE5MmTJ+np6XC6ZMkSPT09dLeoqAiMIRiGLVy40NjYGMOw4ODgz58/KyoqOjo6+vv7w11vb+8ZM2aEhobChsx2dnZz5sxB78nJyUGBx83NzbW1tccq+ZCQkI6OjqCgIKKGjomJqampgeNt27ZByx6rBFC+aF/e1NR09OhRDMNsbGxIJBLYCTk5OYOCgiBBY2NjRESEpKQkhJgcGRlBGyYfO3YMjW2lpKRWr14NxA0oAR0dHS0trUOHDkGCwMBAIueF2Aa2bt3Kx8eH8sLMzLx3797Y2Njq6upR28DAwEBgYOCaNWskJCTQxatXr0KMdzKZ7OjoCBcfPHhAXMnbs2fPWOt2e/fu7enpgePZs2cvW7Zsgv0iMzOzvLwcGvmXL18wDGNmZt6/fz8xDWoDGIYpKys7OztTlYCoqOj69esxDEtKSrKzs2NiYsIwDEoAwzATExNDQ0NIiapYS0vL2toafWL//v36+vq8vLzx8fHEEhh/QZ22kQcEBCBez/z58yESV2JiInqhv78/GJk8PDxkZGTa2tpCQ0Op2sBY2L17N5B6VqxYoaioiAQLDPctLCzmz59P7OZr1qypq6u7ffs2KKd169aNn6NR2wBSEg8fPsQwTF5eHqyvY+HNmzcKCgrolJhB6AXo1smTJ9+/f79+/XpRUVHUwL58+bJv3z7gQ8XFxQkJCY3TCzAMe/To0a1bt1CNTJ06dawfO3DgQGdnJ5ID8fHxPDw8CxYsQP1x5syZa9eunbhIj46OnjdvHvp5DMOqqqpOnDiBRvPEScLAwMAEdeH8+fOJHD1TU1NTU1N0CuHk+/r6iCVgaGi4evXqkJAQqlelpKRwc3O3tbV1dHTQfoiRkfGvi3iWkJAAVhkMw4hVDKLe0dExMTERw7BVq1ZJS0u3traiKpaWll61atVvXXvetGmTpaUlMkT4+PjAsa6urrKyckVFBY7jfX19Gzdu5OTkBBvIy5cvxcTEWFhYdHV1169fX19fr6SkNG3atF27ds2ZMyckJAS0+PXr11E8XVFR0YSEhPr6+vr6en9/f1VVVVqDVWhoqLS0NBMTk5aWlqGhoa6urqqq6uTJk2/fvr1+/XpdXd158+aB7EOP6OjoxMfH19fXb9myBcOww4cPw/WrV68CTQYihPf19YHcERQUNDc319XV1dXV5eDg4OHhQdFeV69eLSsre/v27fr6+mXLlk2aNOnGjRsXLlzQ19cXFBRkZ2dfuHChrq6ulpYW0C4OHz5sYGCgq6urpKTEy8uLgrHb2dkpKCjk5OSEh4erqqry8PDA0nJeXh4Ui6GhIYVC2bRp0+XLl2HWi9aenz17pq6u7uDgUF9f7+zsPGPGjJqaGhzH5eTkyGRyXV2dj4+PlJSUiooKlWFz1EC5GzZsALXt5+dnZ2cHuebj4xMWFi4uLsZx3MfHR0RERFVV1cnJSUdHR0hICMfxtrY2YWFhc3NzqKwDBw6QSKSgoKDh4eGwsDAZGRlubm5PT8/FixfDC4WFhY2MjKAYh4aGdu3atXDhQng2LCxMXFz81KlTr169olAoDAwM7OzsgYGBKioq0DwoFAoXFxcPD4+dnR2FQsnNzYUiQtGLq6qqdHR0rly5Ai8kk8lycnJgFuPm5s7MzKyvr8/MzBQSEhrVtPv58+fVq1e7u7vD45s3b+bk5IyJiYFgxhQKhZubm0wmUygUCoWCahAQEBCgpKQkIyPz8OFDlFl+fn4KhQJrhL29vd7e3k5OTqhVc3JyhoWFQT+CcYyfnx8EA25vbzc2Nvb09EQdbceOHdLS0vDbFRUVWlpa6enp9fX1ZWVlXFxc8fHxOI5v3bp17ty5TExMGzZsUFFRERAQoFAo3zVuu7i4oEbOycm5Zs0ayFp6erqAgACIp87OTrCpSkhIxMbGIrrG0qVLAwIC+vv76+vrDQwMwsPDIXfTp09PTEwcVYBcunRJV1dXX19fV1dXTk7O0NAQx/Hs7GxNTU3Ui3l4eKDQnJ2doYr37dtnZmYGP8nNze3v///a+/JAKrfu/8dMJco8R0oyh0pKSFK3kgwHhSJNGlW3QqnoFpcG0UCRsdFUhmQmcSRRIUSmMg8Zj/H8/ljfd/+e9xxcDfe+977v8/nrPNM+z7P32mutvdZn7+087i73oEbPnTunpKSEui3IAJVKra2t1dXV/eWXX4qKiurr6zU1NcXExMZ9SRMTE+i2lpaW169fh31858yZAx948eJFdXV1ERERYCZbWloKCgquWbOmtbWVSqV+/PjR0tKSjY3t999/Hxsbu3Tpko6ODhsbm6mp6d69e+GthIWF9fX1kTL58uXLL7/8smHDhuzs7EuXLikrK4MrNm5+3dLSEp97trS0FBYWnj59uoeHBxQuJibGysoaHBz8h8Ht7OzsjIwMd3d3NTU1/O7LHz9+VFdXDwkJqa+vr66uRr2gsbFRQUEBnB5LS8v09PTJjcXNmzdpgtt4ZGRkTJs2De0E39jYKCcnV15eTqVSJSUl8cHtnp4eWVnZN2/jW7JgAAAgAElEQVTedHd3y8rK/kjuGQW3FRUVM+gAtDV8cPvy5cvq6uog1QEBARoaGp8+faqurra0tGRnZ9+xY8fZs2dhjAfqRVdX98qVK6gXnD17dnR09K/LPe/YscPQ0BB+9/f3oy3HZWRkvL290W0UCgXDMHNzczh0dXWVkJB4+/YtykmAb9XQ0AD2GMOwxYsXw1Vra+tFixahhCJ4rG5ubuM2Pwy7EXMHwzB5eXnwEigUioWFhbi4OLofaauxsbHt27dzc3OjS15eXvS559mzZ+O9ARhBUqnUwsJCaWlptIc8bMuoqqpKpVJLS0tlZGSUlZWrqqpAKZuamvLz8xcUFMDNz58/xzDMz88PDp88eYJSPuDvX7x4EZ97xvcBGmrYhg0bkAanUqknT54E8xwYGAg1QKVS/fz88DUAqjkqKmoiqcUwbMuWLUj3PXjwAIZHcHjkyBEMw7Zu3To0NJSSkkKlUi9cuKCjo4PfYf7kyZMYhg0MDFCp1Dt37oCH0dLSgj5hxowZK1euRJMiUC6KSqVKSUkhOh4TExMrK+vNmzcrKipu3rwJum/OnDnm5uZQOKKGIfN84sQJTU1NVFpYWBgXFxfYFQzDkPjt2rVrXPMMw1aQSaDmbdu2jY2NDVmayXPPEGYwMTFBqXEIiiQnJ1Op1A8fPmAYhtoFXoOJiQnUaFFRkZiY2Llz5+BSYmIiMHghPEilUj08PJA36eDgYGBgAL8HBwctLS1FRUVRDWAYZmFhkZCQkJKSAm00uXnGm3Bw/FENQLzh2bNncHju3Dm8U1tYWCgjI4O0mLS0NCrnxIkT4yZuY2NjFRUVUUM8fPgQRNHQ0JCmF3h4eOB7AVLiIAMTEaPAPM+dO/f9+/fQzW1tbVlZWcPDw6lU6vnz5xUVFfEvg2HYuO+Znp4Og3j0DsuWLcNbhdTUVIgLwqGenp6uri6+F/Dz86OSy8rKZGRk8L3gwIEDMOoFNbVixQpnZ2f0bFNTk7a29iS55+3bt+NrYP369RiGubq6wmFeXt6sWbPAq5jcPM+YMYOBgeHmzZu1tbXoam1traKiIqKnjIyM2NjY8PDwwOHZs2fFxMSKioqmYiyCgoImMc9mZmY2NjaIXHbu3LkjR47AbxrzfP36dejjz549mz17Nr15Zmdnn2I6nEbR7dmzx87O7ubNm97e3tra2u7u7jTmedq0aQ8ePECHixcvRqIoICAAgUNQUCUlJUuXLr1w4QK6+fjx4xBs+Otyz9euXUtLS+Pk5Fy3bt3z589h0Hnx4sXh4eG1a9fiow3KyspAvgfw8fGB5wVgYWHx8vKCcOX8+fPhS4C1X19fz87O/vbt29jY2NjYWElJyUmmSQgLC4PWQBAXF583bx6GYWxsbCtWrMBfAmsRHx//5MkTmmDIuJvO4lMyKKgIXMRPnz51d3fDG75//x5FF+fNm7d48WJJSUkIt06bNk1DQ4OLi4sm3YuC6hs2bNDQ0MjMzIyNjc3OzsZfmhyPHz/Ozs6GcDTA1dUVAi/bt2+fN28evNvbt2/r6+tdXV3xz+K/BY+FCxeys7NraWmhGYoGBgby8vL4dly+fHlgYCALC8uqVavq6uru37+voKCAD8RB4cD7wDCMl5c3Pj4exmEYhi1btkxTUzMzMxNUJxBSYv+Fvr6+Y8eOQfh30aJFLCwsu3btmjdv3q5du1DiQ1NTkyYu7efnh2FYaWmpt7d3e3s7Ku3169dfv349fPgwSpvFxsa+ePHiypUrnJyc9J+flpbm5uYmJCSEZFhHR2dwcPDly5dT7B3Kysrh4eEo9QBVYWdnBxUiIyODn6qxatWq0dHRrKwsDMOUlJR4eXk/fPgALsvJkycTEhJqampqa2sh7xAcHGxkZASRD39//+bm5vr6+tevXzMwMMycOfPz58+nT5/Gt9HatWtXrVo1UUPTd4q+vr7Y2FiIpSNAmvD169cYhlVXVw8NDZFIJCcnJ9j2o6amBqVvIBxqbW0dGxtbVVXl5uZmZWVF80cVFRWmpqYaGhpID2zatGnDhg0QydfQ0Ojp6UG9AC9yNBILLzwJ4uPjISjNwMBgZWXFzc394sWL/v7+srKyr1+/VlZWwhchqfjDjGxOTs7Lly9R0hTDMC0tLWtr64iIiC9fvsCZ7Ozsuro6/OP+/v6QHViwYIGIiIiioiLqBZ6eniiJQyaTs7Oz8R8oICCAAv7jYsuWLTRn7OzsTp06Bb+XLFkyrniP2/QQO8TviNPe3v727duRkRHoRHFxcTSq8vPnz+DhTYWlRJ1gvu67d+8KCgqsrKxA5Gpra/v6+s6fPz+uonv8+DFM+tLR0Rl3CiWFQomMjPymaLGmpmZQUJCPj8+NGzd27dp1+PDhxMREmjzIvn37+vv7CwoKkErp7OyMjo5GjQ41DwqKh4cnLy+PhYUF3fwTJ15O1Tyzs7MHBgbevn1bUlLS2NjY2Ni4srJyaGiouroaXH5kfSffoX14eDgwMBDpQVZWVvg9MjIyPDw8NjZG+Rdgy3fQTeNmHZBszZ8/X09Pb6J/HBsbc3R0tLCwcHd3p1AoKK+Gavmbsu+jo6NXrlxpaWnx9/cfHBw0MzODLOOHDx9gjDs5YNwPncHCwmL//v0UCgVm+qNLk2NkZGRkZAQ/05+NjQ0yPQUFBRYWFl5eXhQKZXh4ePbs2TS1B/aMHqysrDSLDHByctrZ2eETSExMTEiJp6enFxcXT9S+iC2IMvRIhKBA+N7BwcHIyMjU1NR79+5dvXo1JCQElAsSiT8EZCLHxsaQ5Hh7e1MolIKCgvv372/ZsoWXl9fCwsLR0dHIyMjIyMjGxgatZkADFhYWfA1868IdMOKnOQn5p8HBQRKJhGw/5IzV1NTwuiAiIqKpqWlsbExOTm7t2rVMTEzXrl2DUdr69evB4YPPfPPmjbm5uZmZ2ZYtW6qqqu7du2dsbPx9PX9wcNDCwsLS0jIkJARaBP85e/bsuXTpErwDAwPDsWPHhoeHfXx8MAzz9fVF7KS1a9dKS0tHRERs2rTJxMRky5YtEMqiSZ8NDQ0dOnQIX9uwCkRvby+8w71798TFxSefZPyHk33xN2hra0Mlt7S0hIWF1dbWkkgkqLdLly4dPHjwD9PYGIZBDfwbVYeZmYWFhUwmw1gfXBkY1k8FDx48AHbCuIVP0aOiyVtDDO9bTZSmpmZSUhIMx2k+2dfX9+vXr97e3hoaGjAhE41/Vq9ePZXy9+3bN+4qH+Xl5aampleuXAGnBMJFZDLZ2tqaRCKRSKSWlpagoCASiZSZmXn58mXwC0kkkpWVVX19/f3790kkUlJSEiqQg4PD0tLyW7sqiB+oUEil0XcNCAReuXLF29s7JibGxsYmIiICuQj0q9/8+uuv4eHh3t7eAQEBgoKC9+/f/ynrnEy1iNzcXENDQxYWFhKJdObMGX5+/o6ODkVFRZolDkZHRycfc7CwsIzLy2hvb//y5QsNGWGKgPnpePYBHk5OTpGRkRERESATw8PD+BHzuNQwxAhAyM7OJpFIISEhJBIJ/G6a5L+8vLy2tnZnZ+fkrwrEmcrKSkNDw7Vr1wK5IC8v79SpU5NzavDo7e11cHCgMed5eXm6uroBAQHgYre3twcGBj548AASWnh7Rg8ZGRkaGe3o6Dh8+DDSQeB/ZGVlwbb2NjY240YdMAwLDQ1FJp8mHqCoqGhoaIjMmI6ODn5cgteAU6yH7OxstKICHx8f9GTs30nvERERERERDx48iI+Pz8vLs7CwePr0KX1RJ06c2Lp1K+KgLVu2bPJxzFQA/APIiW7duhVCO9BH8FMYNDQ04FuuXr0KQZHQ0FDwGuvr62nq2cDAAO8NI6ioqHzTWgpVVVVGRkZaWloggW/evIHcBNI+S5YsAe+qtbUV3urw4cOwsIOgoCDkaEFyKioqQD01NTU9evSIk5NTS0uLZjgOXLD8/Hyak6ampqqqqpBgam1tvX37Nv2D34fq6uqGhgYUflNUVCwsLJzis2/fvgW+5/LlyyEnRYNNmzYhrygpKam6uhpPbpWXl5/oK6ytrSFPNC5aW1s/fPgwSQ04ODhAeyHo6elNMeqGh4iISFZWlpaWVmZmZn5+PuxTjnh/QIq0trameaq7u7umpkZWVvYPyw8MDBwdHaU5WVRUZGlpefXqVeSEDQ0NvXz5UkxMDO8WMzMzs7GxMTExQdIEL5NMTExwCT9WKS0txb//T8SKFSvAS6bHtm3baJZCy8vLw9N+/+rRc2BgIH7cyc7OzszMvGnTpnnz5vn7+yNa3cjISFhYGD72NcnoGQ8FBYXly5dnZWXh+wPkn8bF6OgoGglNPnoGQiMwQnt6emjKHHdqAf0EMOSFjIyMnD9/nmYIjmHY+/fvgRc6ldFzZmYm5N3xnznF9QhZWVlZWFhgfIw/HxISMjAwgN6/t7eXh4eHxteZaPRM/9c9PT3QxOiMtLQ0sjeAmJiY8vJy/CN4C8HAwIAvtq+vLyAgAAIewFydqHERfZoGfX19NO0CjcLExMTOzj48PAy8BzxcXV1B2MC1GtcbGPd9cnJyamtrp06CraysxAfZenp62NjYoAPTF/7q1avCwkJUV2JiYhYWFocOHUpJSYFROysr6+joqIGBAdC2kdfCxsY2NDREM9JFHhu9QpwEL1++rKqqsrGxmaijsbGxDQwMGBgYIGb+tGnT3r59a2BgcPDgQXRbdHQ0yICnp2dISIi7u/v9+/dpJJORkZGDg2NkZATJJyAxMREfg6mqqkpJSflZdNfnz583Nzfv27dPQEAAMp00/z4JUE2CAOArB8QMUa9pONggokhX0HdSvAwDTdXDwwNdffPmzeQ1QN9/U1JSgNwwlagbvgYYGRn3798/PDxsamoKbhP0I19fX/p+hGoV3wF7enpQJIC+C9MEt+vr642Njd3c3MA29/b2Dg4OMjAwhPw7+Pj4rKysQkJCli9fHhwcjM7DJGlTU9OQkBC8qh8bG0Ot09XV1d7ePkkvmLoMHDx4kI2NbRLrExgYSNOyv/32G56L/lebZwzDbty44ePj4+PjExYWFhYWBlnVqKgoDg4OGJF8/PjRz8/P0tISGBCdnZ1kMrm5ubmoqAhfTklJCfT5jo4OvEOtp6fX0tKyfv16mJH1+vXrSQJ3jY2NKPcMo2d6A4PG8RA/8fHx0dbWjo6Oxt/28eNHqG4fHx9kdKWlpWlKg6yblJSUlJSUi4sLDDW6urp8fHxgxMzFxUU/I6Krq4tMJtO//MKFC0VERN68eQP1GRQURD+Oj4qK8vHxaW1tRWcgqrN58+ZLly4FBwcfPXoUwukvX77s7u7W1tZmZWVNSkqCMhMSEtrb24HhhTex41bmvXv3Ojs709LSfHx8ysvLITETGhqKj8Hm5OSEhYWhQ319/bq6OhS+zs7Otra2RlPvoIsePXrUx8eHTCaHhIT88ssvjo6OEIm6c+eOrq6ulZWVj49PS0sLhmHBwcFISOhDF2iA6+np6ePjg3QENIqsrOyhQ4fy8/Otra2fPHkCMTSYHCIiIoJCf58/f3737h2MimgAN+/evRv1+eTk5PXr109loIA+NiwsDETLz8/v0qVLd+7cgXlKNIVDOxoaGqJ5iTNmzJg7d+7Xr193794NiUkjIyN9ff2kpCQ0YQbDsMWLF+/YsSMtLc3e3h5037t375CnW1lZOZFWnQj9/f1HjhyB5r59+zbNVXNz8+XLlzc2NsJEOwzD3NzcWFhYkpKS8HGF2tpafAqjqanJx8eHJhIzb968x48fV1dXb926FfRjZWVlVVUVFxfXtGnTCgsL4R2A7jcJ8FHNcXH37l0QnqSkpMuXL6empi5cuJCDg2P+/PmlpaUkEgkUbnV19USjIppuAoQMS0tLtB5kdnZ2eHg4ClxB4z58+BA63cWLF/v6+pqamqCBwsPDIaGO8OzZM6TEVVVVdXR0cnNzUac7fPjwuOtZTtJ/BQQEpphvLikpuXbtGvQCOEMikTw8POrq6tauXZubm6uoqLhv376cnJzt27eD7SkrK8MHt6dPn45yNB8/flyxYgXQUOj/Cwh6eLfj1q1b1dXVxcXFUFGrVq2yt7eH+XJTgbCw8LgJXUZGRqR1YcYEzYIcNDXg6+uLr4GJAPGPnTt3+vj4wAc+fPhwolVROTg4li9fHhMTY2xsDLagrq7Ox8fnm9zlCUPxaHrrH74xTLYRERGRlJRELgwXF5eBgcGZM2eSk5Pr6upWrVplYGAAc3CvX79uZWVlamqalpYmLy8fHBz88eNHDw8P4MQCqaqkpKSiouLFixf6+vrq6uoGBgaQhM/Pz4+Liztw4AB96MbLy+vJkycMDAxdXV0fPnzo6Oi4ceMGZGSzsrI2b97MwMBQUVGRl5dHJpP19PTU1dVzcnKqqqqGhobOnz8vKyv78uXLvLw8eXl5Xl5ecXHxZ8+eFRcXy8nJTZ8+/fjx4/39/VVVVXl5eYqKijw8PO3t7UlJSUVFRfPnz9fQ0NDT03v27NnHjx/z8vKioqIYGRn19fUfPHjg4eFRW1s7PDyck5Mza9YsZ2fn169fDwwMkMnktWvXzpgxo7GxMTMzE+I5+/fvX7p0aVBQEJlMFhUVtbGxSU9PHx0dlZWVlZCQgBjOgwcPyGTyxo0bMzIyrl+/PjIyUlhYmJWVZWRkpKqqim5ITU2NjIwEollkZOTHjx/JZLKOjs6SJUuKi4s7OzsrKira2tpu3rw5MjLy+vXrzMxMeqcnOTn55cuX4EiRyeSenp7z588vWrQIrh47dgy4D1++fGlra4NgrLq6OiMj48OHD1++fBkVFRUZGXnt2jVtbW0YFL558yYuLo6BgYFMJpPJ5KqqqnPnzm3evBkCU0xMTGvXri0uLo6Li8vPz3/69GlRUZG5ufmnT58cHR37+vo4OTnJZLKsrCzi1AgJCRUWFhYWFsJbnTp1amBgoKKiIjc3V01NTV1dXVlZ+f79+2QyOSsrKzIyUk5OTlVV1cPDo7S0NDU1Fd5QR0fn0KFD9KECTk7ODRs2pKWlhYeHJyQkREdHMzMz+/r6wvyu27dvt7S0fP78+fPnz+OuTpyZmfny5Uto66ysrNraWnd3d7S0xfTp09evX5+bm/vs2bMbN24kJSUNDw/funULv7gEEGKdnZ2Rql24cOHw8DAQyNFtsrKysrKy9+/ff/r0aVJSUmRkpLq6uoKCwokTJ3JycpiZmZuampqbm9HUYbwRdXBwSE9PBykSERFZvHhxZWUlSAsrK+uOHTtSU1OLi4t5eXnRXPmUlJRly5Zt2rQJlfP48WMHB4eVK1eiOiwrK/P394+Pj/f3909JSWltbXV0dKQPs8+bN+/58+fl5eVPnz4NDw9PTEyUkZHR0dEpKCgoKSkhk8nTp09XUlKCXpCVlRUVFRUbGzswMFBZWRkfH6+qqsrNzd3S0gIyICQkhJ+qi2HY+fPn29raiouL8/PzoWYiIyOR6pCSklq8ePH9+/czMzPv3bsXHx8vKSkJYoxHRESEv7//yMhIQUFBdnb25s2bWVlZDQwM8vLyEhMT4+Pjg4ODu7u7vb29xcXFoQaAtPHw4UMymdza2vrbb7+lpaVVVlbm5+dHR0eDa97d3V1SUgKjxoKCAuBsdnR0aGpqGhgYFBUVxcXFQQ3ALBXo5ps2bcILakNDw549e9LS0mbOnFlYWBgTExMVFVVTU9Pa2komkxkZGcFnioqKqqioSEpKEhQUxFdRbGzs5cuXweiSyeSWlhaYfaqurs7ExFReXk4mk1evXq2urp6dnV1VVUUmk6OjoyMjIxUVFVVUVE6fPp2ent7X15efn9/Q0AC9ID8/X0hIyNDQkD53KyAgcPfuXVNTU3BwExISbty4MWvWrHfv3oFC6O/vr6+vNzIymjt3LoZh8fHxZ8+ejYqKamtr+/z58/Pnz/n5+SExkZqaeurUqcjIyL6+vra2tuTkZE5OTnjq3bt3iYmJV65cAXl7+vTp2NjYjh07xvVXJqqBnp4eW1vbxMRE2BgjJyenrKxMS0tr9erVvb29kZGRZDI5ISEhOzvbysqqo6Nj3759nZ2dXFxcBQUFYmJioqKibGxsoM2gNz158iQqKkpYWFhTU/Mn7D1DJfA/j2PHjomLi+fn5/+sAu/cucPPz/+Pq4eYmJjvmA5x5swZmFz3h3j48OFPec+fVc7PQlpaGkyQncqbR0ZGoiXu/2J8+vTpm6bJ4tHQ0IBmkxKYHPRrbv8ZgEU9Y2Nj/4trkthQksD/0VI+ffr0E9kNw8PD9fX1eN7H3x+wQtafB1hq4+9Tzs+Cjo6Ojo7O3//N58yZM3WWNT2din71OgL/WUA0iH6J0P8aMBJtTADDsIGBgUnWS/8+8wx5fQIECPwP4u7du0eOHPmOeV9/iLKysiNHjoSHh4+NjTU3N/8X1yExev5fB1rh/GdhdHS0rKysv78/PT19ioOqfzq6u7vr6upoEqIECPxv4vLly2jNefpdLn4ckpKSR48ehd//xM3Xp46pUsMI/LfC2NhYVlZWXV09Li6ur6/vx7fr8fPze/bs2cGDByMiIj5//jyVFaz+uXB3d4+JiSkpKQH+PPBNCBD4XwY7Ozvnv/BTVuegHVMyM6Py/3Cxmn80GCZafY3A/wgoFAoTExMjIyNwF/FU4e8DzGhkYWEZGBhgZGT87+4/FAoFTfT6KbVHgAABAoR5JkCAAAECBP6mIKhhBAgQIECAAGGeCRAgQIAAAQKEeSZAgAABAgQI8zxVwHqTv/32G1pznx6Dg4Pt7e1/WBSs71hRUXHw4MFxU+lww/3799ECwhiGDQ8PwwbDk4NCoVRUVMTExNAs1j11QAkjIyN/kybv7u5+8+aNurr6Hy5i/H0YGxurqKj4MxaI/7no6uoCsYHNCf6zaGxsRL8rKyvfvn2LNsGtra2tqKg4ceIE/VP19fV//ftXVlZWVFTAgud/Z4yOjoJOmEo3/68E1EBOTs5Ee+H8OEZGRnx8fNTV1f39/f+5VfTixYsbN24Q5vn/o6yszMfHx9nZedwdeACenp6mpqZoO6yJ0NraGhERoaioCPvR0qOlpSUiIsLGxga/meDVq1eNjIxgS4bJ3YiIiAgrK6vv7uSurq4yMjJ/+BV/GZ48eeLl5cXHxzfuZnk/jqGhIRkZmcn3Ff07oKKi4vr16zIyMn9SPXwTSCQSWnPf2dlZSUmptrYWDhMTE3fs2JGVlUX/VGRkpIyMzLhbTP55ePjwoZGREX4Dyr8n7t69u2XLlujo6O/YWfm/A0NDQxERERYWFpNsFPGDiIiI6OjoWLp06ZcvX/6JVTQ4OPhnV9EP4T+4oChsqlhZWTnRDZaWlmpqag0NDVMpDfTF2NjYRDdwcnJqamqiQ1tbWzU1tY8fP06lcCEhIX9//4mu1tbWBgYGTrQSspGRkZqaWnt7+4/UVU1Njb+/f3R09A/W+ejo6MKFC1+8eNHZ2dnf3/9nNCuFQpkzZ05ycvLfcA3bzs5OGxsbdDg0NHTo0CElJaXvKGpoaOjs2bOwm8WPr6EtICBw7949OOzu7tbV1YWdqQBOTk4aGhrjvsORI0fk5eX/4mo0MTHZtm3bf7Ad29ra8vPzP336NNENsbGxAgICzc3NdXV1ra2t/9xVl1+8eOHh4fEjJSxbtuzkyZN/xrs9fvxYQkKCSqUODg62tbX9rGK7urq2b98+MjLyl1Xy0qVLnZ2d/4at/7fOPYeHh7969WqKS91OtE8wHg4ODuj3nTt3Xr16BZuf/CCuXLlia2s70QtERUW9evXqB1fP+f333y9duiQjI/ODrxoaGqqioqKpqcnNzY3fNOkngo2N7enTp/Pnz/8bSlR2dnZISAg6ZGFh4eXl/e7sjKur6ySxn6nD1NQ0KCjI3NwcDjk5OWk2Ep4IP/L+/2g8f/58xYoVVVVVEw05rl+/bmJiws/PLyYm9o+uIicnp79ncH5kZOTWrVuQw2JlZYW9UH8KcnNzYY9dAlMyzx0dHcn/AloDMj8/H3WPzMxMuJqamoqeIpPJcBKF6SZBRkZGcnIy/V6/Hz9+pM9iNjQ00GykimEY2rt+eHg4OTmZ/gZsvP3MaQB7/U7SH+AGmoz4li1b0B7s46K8vBxtJj06OlpaWoq/2tXVRbNtakNDQ3JyckVFBf7k169fJ++ora2tycnJk+9m+uzZs3HPZ2VlJScn/6wE+axZs+h3FczMzKSPIPX29qKG+yY0NDTA7qo0ePfu3XdP5S8tLZ2oBioqKn6KJZ4Ia9euJZTRN4GVlXWSBemSkpJg8++fjtLS0h/Zyre9vX2SOPCHDx+QovhBNDY24neL/0FUV1f39fXhz4yOjiYnJ9PsUj8RJlFKg4ODNIruD9HW1obnakzkok2uCalU6vv376f4j7DL8F8v5FNacW1wcLChoWH37t12dnYWFhZwcv/+/WvWrDl37hyIgp+fX39//4EDB8CQHDp0KD8//+jRo58+fXJxcUlOTp7IgN26dUtZWdnOzm5wcHDOnDmRkZGLFi3q7Ox0dHTEMKywsDA6OlpKSgputrW1pVKp5eXlxcXFZmZmO3fu9Pf3l5aWdnZ2dnBwSExMzMvL8/X1jYiImD59uqmpqZubm6io6P//WmZmDMP6+vr27dsHZ9zd3dHofPfu3QMDAyEhIatXr0Ynz58/LywsDL9fv37t4+MDN9jY2GzZsgWN8ru7uwMDA1+8eOHg4KCmpob+MTo6+smTJ2QyOSMjg5+f397enkKhsLGx3b59G+rNycmptbVVX18fqi4/P//GjRuCgoJ8fHyHDx/euHEjWr2WkZExMDAwMDDwwIEDKioqNMbjwoULDQ0NKSkpkpKSUVFRysrKkzin27dvB8d83rx5dXV1rq6uRUVFM2fODA4O3r9//5IlS7y9vZHsQg2UlZV5enrevHmTjY3txYsXd+7cwTCMn5/fw8MDX3hBQYGfn63nljIAACAASURBVF9lZaWQkNCjR4/g5PHjx1taWu7du6empmZhYQExDA8Pjw8fPnR1ddXW1iopKVlaWgoKCkKakI2NDXa8T0xMfPjwIYZhc+fOdXFxgdLy8vJu3bpVXl7OxcUlKCh49uxZWOw6JCQkPT09KytLS0uLg4NjIsVBpVJv3brV19fHx8dnZWWFzh8+fDghIUFdXZ2NjQ2+DsOwlpaW48ePYxj26tUrOTm5vXv3rly5kkZ6GxsbFy9ejHaqxzDM19f39evX8FtQUPDChQuQpVu/fj30gmvXrhUWFmIYtmbNGi0tLWdnZwzDLC0tV69e/d09+ejRo8hrxA8+4uLiIiMj0eH169fpoyZOTk6NjY0yMjKCgoKZmZmMjIxQA8nJyREREXAPiUQyMDCY6N9PnjyJyGKqqqr79u3LyspCr7Fp0yZDQ8Pw8PCUlBQMw9TU1PAyAPdISUmdOnUKftvZ2Y2Nja1cuXLjxo1HjhyBk56enmj/b3z979q1a6JwWlpaWkJCgpeXF5xxdHRELp2GhsbOnTvxTWxmZiYpKenh4aGiogKdEY+ampqzZ89iGJaTk7NkyRJ2dvaAgAC4dO7cuU+fPs2ZM8fV1RXO2Nvbj4yMrFixwtbWNikp6f79+xiGXbx4MSUlJTg4eGBgID09nWa1y6ioqKdPn+bl5amoqIB+YGJiSk9PLy8v7+joMDIyamtrW7BgAWgDe3t7WD42LS0tNDQU3gHtDldUVHT16tWqqio2NjZRUdHKykoktKgGGBgYAgMDe3t79+/fD5fExcXhA/Ho6emBqigqKpKUlOTi4rp8+TI3Nze6ISAgID4+XkBA4OLFi/gHUQ0YGxsfOnQIeqWkpOTp06fRPT4+Pm/evOnv7y8pKcErulu3bsGPq1evFhUV0QQReXl58/PzOzo6tm7diq8BUVFRNzc3uG3v3r0DAwPwpzSKDsMwa2trbm7uq1evZmdnx8TEKCgo0Hx1UFBQVlbWnj17Fi9e3N3dffDgwe7u7qqqKhUVlcl7wX8y96ytre3o6Ai/KyoqpKWljY2Nv379ilK5Fy5cgN9r1qzZv3//4OAgJDv37dtnYGAwUe6Zh4cnLi6OQqHA6pIzZ86kUqljY2MUCsXe3h7DsKqqKrjfxsbGxMQE7oTdkGbPnm1sbPz582cqlQrjDxKJlJubS6FQDh06BNKDzz07ODhA4U+fPuXh4dm4cWNnZyeVSm1paTEwMDh37hwUDupSR0fH2Ni4vr4ecs9MTEwmJiaZmZmwWzgjIyPsHevo6GhmZsbGxqaqqmpsbJybm4v/xuHhYXBompubqVRqVlaWsLCwnZ0dXB0bGwsLC5s+ffrVq1fhDDs7+8OHD4eHh8fGxn777bdr165RqdQDBw7MmzdPQEDA2NjY2NiYfmNmKSmpq1evwssvXrx49uzZ47agra2thISEmJgYlPPhw4fffvuNl5f38ePHQ0NDw8PDOjo6bGxsVCq1o6NDSUlJUlISFq2kUqlgY/r6+qhU6sjISENDg7S0dGlpKc1f5ObmJicnYxiWkJAAaVQSibR3717Kv2BhYUGlUqurq1etWoVOkkikq1evvnnzJjk5mZGRcfr06VDayMjIjh07ICYPZ8hkspSUFDTxly9f5OXlIXP84sULVVXVjo4OKNDc3Jz+82/fvg3d1czMzNTUFGTD3d2dgYFBVVX11KlTFApFR0cHtSyVStXX1w8LC4MyN2zYwMTEBDWQkZGxefNmDMNWrVpFIpGcnJxoUsKgYg4cOAC9ID8/n5GREfWCoaGhGzdubNiwAbbdNDY2xssAlUrduHHjVHLP0C5iYmKurq4mJibGxsaampoYhmlra3/58gWy2gsXLvz48SOFQgENu2nTJpoSoqOj9fT0MAxbuHDhr7/+qqGhwczMTKVS4+PjZWRk3r9/T6FQcnNzmZiYYmJiUO5ZUlLy7du30MTm5uZ79uyBWvLx8WFmZo6KihoZGQFK+cuXL2GD5+Hh4bi4ODU1NSA93L59e9OmTRQKpbq62tjYeMaMGb6+vhCXhoXfGRkZ9fT0goKCHB0dFyxYsGLFCvh3X1/fZcuWMTMzW1pampmZoZw94PXr19DjWFhYSCTS7t27qVRqcXExKyuro6MjvOTvv//OyMh49uxZKpV6+vRpOTk5DMO2bt26bds2SUlJQ0NDmioqKSkRFxe/ePEiPJ6dnS0iIqKnp9fU1JSQkACaR01NDW6+efPm0qVLWVhYQBU8efJkzZo1GIYdPHhw0aJFy5cv37lzJ01i9e7duwoKCnV1dRQKJT8/X1xcfHh4uL+/n0Qi8fLyzp8/n0QikUikrKwsY2NjFhYW6A59fX0kEgmiysXFxejz58+fn5aWRqFQ2tvbjY2NeXh4UO55cHDQzs5ORUUFGD+gZnV0dEJDQ0FQabbH1tDQCAgIgK8uKyubN2/e6tWroRuSSCQMw8AA79u3j+ZZEokkLCzMyMi4atWqO3fuVFdXy8rKMjAw+Pj4wA1Hjx6dPn060gDKysqWlpaFhYWWlpbLly/HMMzCwsLKyopCocCw9dq1a0gX8fLyMjExjY6OgoqorKyUkZEBFlFLS8vatWtdXV2h2Pb2dmVl5blz58LnGBsbs7OzMzExiYmJbd682cLCAgpBueeioiJ+fn51dfWvX79CGxkaGqIayM3N9fLy+itzz99gnqOjo6Hfjo2NXbp0CUa3IBbFxcXS0tLQ61JSUvj4+A4dOoR2tj948CAfH19KSsq45jkiIgKdOXr06LRp09Dh3r17kXl+/fq1mJgYiUSCSxANlpOTQzdDJ0HUsJqaGgzDFBQU6M0zYkwg85yRkQHuNiKegFrBU8P27NmDtpGPj4+HYRwcBgYGgsM7br2RyWRknqlU6qZNm5B5xhvX/9t/m5n5/v370FXKy8sRwcrBwUFISCgrK2vcv0hMTEROTHh4ODMzc2Bg4Lh3mpubk0gkkLympiZZWVk8MSomJgYW36ZSqX5+fjNmzAgPD4deLSwszMTE5O7ujgzGkSNHxv2LgYEBGLTBJzAzM+/atauvrw+aBnyLgIAAAQGBvr4+6B7t7e2Io7d//35knlEACvQRyADe9F68eFFWVnZoaMjc3FxJSam1tRXaiN6DATx58oSBgQF/xt3dfc6cOeXl5egGJiYmKysrOMSXA4kbT09POISd7JAhp1dtCgoKhw8fRiRHZmZmXV1deD0KhaKmppaenj6uDHyreRYXF//w4QMcNjY26urqQv0PDw8vXbr0xIkT6OZdu3YJCgrSS1F7e/u6devk5OSqq6s/f/4cHR2dlpbGz8+P3PGOjo4NGzbo6Ogg87x161aQIgghohegUqlsbGzAwWxsbGRhYbG0tESX1q1bFxISAr+rq6tbWlrwNYB0d01NzaJFi/T09BCry8nJafbs2fHx8XAYERHByck5kaaCVdDxfCgbG5utW7eCawU3HDhwgJubG0T93bt3wsLC1tbW/f39hYWFNB42lUo9e/aslJRURUUFOgO5s6dPn1Kp1K9fv27evBmZZyqV+ujRI2SeqVQqRAikpaUrKyubmpqioqJA7BFUVFROnTo1MDCA3GikarS0tI4dO4buHBwc5OLiQt4qVAXSwyUlJfSsTBpqWGFhITs7+927d+EwLi5uXNEaHh5etGiRkJAQ/qSjoyMvLy+UT6FQMAyjd2XwlFhdXV2k90pKSgQEBK5cuYIUHd6pXbx4MVL1MBMBeTD9/f1WVlZI1d+6dQsSZ6i6Dh8+jIhdRkZGkC5EJfv6+nJwcKAaExERYWFhSUtLGxsbe/XqFZ4aVlZWJisrC84EnM/MzJSQkLhx4wa8TEdHB14G/gJ823YiY2NjmZmZCxcurKmpcXZ2zsjIsLW1LSgoaG1tPXHiBATNamtrW1tb379/r6WlBcPfGTNmzJw5c6LdAnp7e9FvdXV1GiYXClGysLCwsrLSPKutrY2/GT/DZMaMGWpqajT5Qpqkb21tbV9fH4rVZGRkbNiwYaJvV1FRQfEomvecNm0aAwPDTwlmaGtrm5ubr1ixwtraGqKC6JKSktKKFSvGfcrAwCAnJyctLQ3DMA4ODmZm5kmYWQUFBSUlJYqKiv39/WVlZaKiohBphxAWlUoNDQ21s7Pbu3dvSEgIuFBOTk47d+6sr69//PixhYWFlJRUTU1NeHj4JB8SEhLyyy+/zJ8/38nJ6dy5c7du3bp06RInJyfE1WVkZGCU7OLiIiEhwcfHZ2hoOG4b4U82NzfX19dXVVWhF87Pz29sbExOTnZwcFixYgUfH9+OHTuWLFmir68/9Trn4uJC1bVhwwZjY2O8QL558wYi1aBk8ezCSTBnzhx+fv537961trZCSDY0NHT79u1hYWHbtm1LSUlRUlLCS++PYObMmYgzKCgomJKSwsjIiGGYv79/Xl7erFmzUHWVlZU1NTWNywCor6/n5eWVlJQEqQsODu7r65OVlUXPgjrGM0s+fPggJydna2uLYdijR48EBQVRVrKgoABe5uLFi56enoWFhYsWLcIwjJubGyUU4L/evn2bn5+P/Tu1s7m5ua2tTVVVFbG6VFVVh4aGPn369E1JYiTVycnJBw4cQJsPMjAwqKmp+fj4ODo6+vr61tTU9PX1ycvLc3Bw0KSNIFX3+vVrbm7uefPm0WgqW1vblpaW5ubmqKgofEoLGDABAQFLly5FZzZv3iwtLY1hGJgQml7v5uYWHh4O009OnDgx0UZPjx49Avd3XJ3W3t5eU1NDo52gBjo6OoCdCnrM1tbWxsYGksre3t7jRlULCwsh7I+wZMmSGzdu4LlECxcu/MNegO6kITx2dXUh6frll19ADDAMS09Px9/GwcEhLy+fmppaVFSkrKxcXFwcHx9vZ2dna2sbERFRVlZWXFyMOE8geHjIyspycnLia+natWuw0S2+yYqKigIDAx0dHUGeAVpaWvPnz9+zZ09dXZ2UlBQvLy9eIf9dqGEATU3NFStWBAUFXbhwYebMmfz8/Fu2bBkbG+vt7U1MTKThtnBxcV24cEFKSkpKSmrXrl2xsbEQsqAHar/JmVwKCgoGBgbp6elxcXGNjY3nzp2zt7eHiOu4tK+xsbHh4WGaAmloF+ATAc1EUFDQz8+vsbGxsbHxzJkz1tbWk0seDd3jR9gieISFhf3yyy+VlZXOzs729va7d+9Gl4qLi8flu0EgyN7eXlBQEJL0FAplEtuppKSEN96srKxS/8LmzZtTU1Pt7OzgEjc3d2ho6MePH3t7e+3t7Y8ePVpaWvr69etnz55BcmESmJiYwA8bGxt/f39BQUF3d3d7e/tVq1ZlZ2evWLEiPj7+yJEjt2/fPnz4sLW19d27d2HQgx7EAz89fcaMGeiFHRwcnj17tm7dOujAUlJScXFx9vb2GzZsuHLlynfUP4VCwas/BwcHGxsbdnZ2KSkpyC5PfYWHkydPpqSk1NbW3r17t7e319zcXFRU1MPDY3h4ODQ0FG1Y+9NBw5jj5uZG1eXq6pqamkq/CffY2Bg9J66vry8hIQE9e+LECbwe19TUhJgwQExMDN2ZlJSEGIgmJiYzZ86MiIgYGRnx9fXFlx8XF6enp+fg4MDIyCglJcXCwoKnHdF0qM7Ozm/lLSKZYWZmntx7hqHqJMRYcHwngoCAAGQ68GBhYYHByUTKBw83N7fdu3f39/efOnVq586dhoaGwOnp6+ujGWCsX7+eZgs4fH+ZSDhnzZqFH9vAsLWrq6u7u/vOnTv4mqcBMp8AMzMzLi4uGoLed4jozZs3R0dHQV8Bli9fnpqaCl2M3iKQSCR2dvaEhIT379+np6crKSmtWbMmNTU1Nzc3IyPD1NR0kv/S1dUFrwjhzp07NC4OdBM+Pr6bN2/SaDZPT89jx44FBQUdPnzYyspKV1f3r1zB4htGz3x8fNu2bfPz82NlZc3JyQGigb+/v6WlJSMjI+JPycvLi4uLi4mJQZDtD4Hv5DTAj56BcVNbW3v79u2MjAxxcXFEJBl39MzGxiYsLNzQ0EDjzdH0K5B1DQ2NxsZGTk5Oe3v7BQsWcHNzX7t2beo18/HjR3pX4PtQUFAQFxcHPvvGjRuzs7Pz8vLAB585c+a4sxeys7OTkpLc3d3Xr18PyYLJSa1lZWWfPn2SlZWFQ05Ozolays/PT1pamkwml5WVTZ8+HeLb8fHx4OxP/iEJCQmwpExTU5O9vb29vX1FRYW/v//ly5fb2trevn3Lw8Pj5eXl5eX17NmzkJCQ7du3r1+/npeXNyEhYVw3HN9q9C/Mzc2tq6sLaaqjR49GRUV9Kx0UNWV5eTnkPgsLC+Pi4qytrYGEMq4I/aFgd3R0REREgN708/Nbs2bNhw8fqqurFyxY8Cd16X379i1YsEBSUhJGORISEn/YEzk4OMb1kkVFRSd69v379zU1Nag2li5dOu6sP3FxcXNzczc3t40bNz548CAqKgpZxODg4NLSUkRjxhPWZs2aRWMGhISEvtUSoHdrbm6mGfojFQFfJyQkNMm2p5KSkseOHYuNjaW/tG7dOmDO0hOJ6UfPk0hORkbGjRs3YOGqU6dORUZGwgSZt2/f0miw1NRUGoONWK6gAx88eEBfvoSEBH7kunHjRiCB6uvrr1ixgmbc/024fv36mTNnvvWp3bt379+/v66ujkaHT2QRJCQkODk5Qbk5ODhwc3P7+fnduHHjy5cvKSkpQDOaOuzs7OjZkXPmzPHw8DA0NDQwMNi9e/fBgwfBa1FWVlZWVvb09Hz+/HloaGhYWNjPotb/5NEzhmFbtmwpKCiAuCvqNk+fPsXHQBYvXrxy5crw8HCgCAEmWZNlkks0zuCXL19KSkpsbW29vLzo25XmZiYmJmhRGiWOPywuLkZDDXd39wULFvj5+Xl5eY1rexobG9HOvjRwdHSEwFFPT89Upl/HxMRAJOfTp09ubm74HoiIslxcXOvXr582bZqEhAScKS8vR3xgGove09ODKvPz588jIyOTGKe5c+cCyVNYWHjv3r0VFRX4tU7pm8PNzc3GxgbUpbu7e3BwcEFBAV7vTBSlxzCstbXVxMQEiALz58/38vJiYmKCoDTyUg0MDIyNjfn5+eEShGRA37W3t8Mos6urC8OwZcuWrVu3rru7G30veuF169YBxxvDMC8vL+R8jBu1m2Rmi7y8PCK9v3jxAk14gwUu6EVoEvDw8Bw+fHjXrl2SkpJQ4dOnT+fi4tq4cSOa4vxTAItCoDD1169f169fv3DhQlNTUyUlpaCgIPyAYNzuxsLCQjMRjouLa/r06R0dHfhxBv5ZISEhkHnwyxGvHsLU+F4AExzIZPKSJUtQ7Q0PDz9+/BjIJSAnQ0NDTU1NMETm4OCgsZe9vb3fGqBC8cxVq1YtWrTIx8cHcctBBqSlpWHUO2PGjImCyXinFhjCqCq4uLhgfMzHx6evrz8wMADjqi9fvjQ0NNCPnieRnKCgINSCbm5uyF5qaGjQLMywefNmDg4O4P1BUAE/75SDg4Obm/vgwYNfv36FIISPj09xcXFbWxveqMvJySkrK8fHx588eXKiFWGZmZnPnDkzMjICHAvApUuX+vv78Z4TasEpIiQkBGRDWFg4LCwM79aADEz0oJCQkK+vb3JyspmZGTpz9OhRBgYGfD7C3d2dRlAfPHhQWlqK5/yPO3rGMExERCQmJmb69OnHjh179+5dd3f306dPkXuqr6+P9wNCQ0PxKyj8WfjWlZKUlZXxK229evUKTBf+tp6eHgMDg9mzZ7v8Cxs3bqRfDQcit8LCwoiE9eDBA2ZmZhcXl+rq6uzsbJgy4eDgACQLGMSYmZm54JCRkQGMHmASOjs7A0uls7NTT0+Pj48vMzMTVhEC7/vRo0dUKjUvL09UVFRTUxPIolQqFWZZGBkZ4QsHEkRiYiL4nohPAXGz7du3I76bgIDA+vXrTUxMHj9+PDk1LCwsDMOwrVu3uri4yMvLnzt3btasWfr6+lC4goLCuXPngG+yatWqU6dOwVMJCQns7OyGhoYuLi5lZWU0fyEhIWFgYODi4gIMXsjV1dTU0Nzm5uYGEXu05FNWVhYfH5+uri76ZDyZrr29XVdXV0VFBc/mk5OTwy+8RYP379/D6tDTpk2Lj4+HfO358+epVGplZSWUX1ZWFhAQsHXrVmB3Jycny8vLI44VzEJRUVFxcXFZtWoVZIL37dsHMhAdHc3AwICXAeAriYuLGxgYADmxqKhITk4O0YhoqGFgg11cXJ4+fXrr1i1tbW0lJaXExESYg1BaWiorK6ugoFBRUUEmk0VFRZcvX+7i4rJ06VJ4ExkZGZhaDWrL1tbWxcVlonWpvL29eXh4QAIRR0lOTo6mBZOTk7m5ufX19Xt7e6lU6tu3b+fPn6+iogIUlaamJk1NTREREXrKEmLU6+joQG2QSCQTExN09fLlyxiG7dy508XFpaurKzY2dvPmzfSFwCyvlStX4k/CKsrbt29PTk5uaGhwcXHZsGEDooYpKioC+7etrU1HR0dISMjFxaWnpwdYu/he0Nraqq2tLSIigqiUoEk2btw4Y8YMeG1XV9dZs2ZhGAaLT4EM4Mlxz58/5+LiQr0VQkTwbFJS0rjUMC4uLnQG5ud4e3vD4b1795SUlNB6heCOI9IfPTIzM3l4ePT09IA9WlJSIicnFxsbi26AGTurV692cXFRUlICUYFZoIgatnjx4onKV1FRgV5PpVLPnz+voKCAliDU0tLS0NBAio5KpYKZd3Z2dnFxOX36NEw8c3FxgaugVDdt2gSVgyZcnT59Gv+PMOkRX8P0KCoqmjt3rrq6el1dHZVKbWhoWLJkiZ+fH1ocEHVz+mffvXsnIyOjpKSENxZz585FQl5SUrJgwQJlZWUPD4/s7GyQgY6ODkQNA84KvkDwD9CZ8PBwNjY2mn+vra1VV1eXlpYGGk1/f7+BgQGexCoiIrJu3To8ty43N1dERGT58uWgoj99+qSqqgpZg6KiIgUFBWC5UqnU48ePr1mzBoScnZ2dlZX1z6aGMXzTGg7Q2fBxMJgSLSEhQeN+dnV1lZSU5OTkNDc37927l4ODA0W/0Q1omiYvLy94ZL29vc3Nzenp6YsWLZKSkqK54eXLl4aGhnh38t27d2xsbG/fvr13756BgcG0adNevnwpKSkJee7g4GAJCYmysjJFRcWzZ89eunSJg4OjuLhYQEDgwoULDg4OZWVlIiIi06ZNW7lyZWZm5s6dO9FQFcOwkpISExOTY8eOOTo6uru7z5o16+7du9CTR0dHa2pqmpubS0pKwEeOj493c3MLCgoSExOjYUDk5+cvWbKkubkZ6m1sbCwoKAgmTXp4eKxcubKurm54eHjatGlCQkLLly8fGxuTlJTk5OQ8duyYqKgootTFxMRcvHgxNDRUWFiYZqxTW1sbEBDQ1tb2+++/o6ybsLAwTQzn6NGje/bsgdwP3IlhWH19fXBwMETUVVVVjxw5gmaZYxgWGBgoJycHwV7A6dOn9+3bNxFjID09vbm5GWYmZGVl7d2798qVKwkJCSIiIv39/Rs3bly3bp2AgEB3d/ehQ4e+fPnCw8PT0dFx/vx5oA6BDNTW1trZ2c2aNcvX13doaCgxMXHhwoU9PT2QZKqqqvL29gaLsmHDBmtrazExsefPn58+fVpSUpKRkVFRURHmsNK/Xl9fn4uLS25u7q+//qqlpXXy5EkpKSktLS03N7eQkBB+fv6+vr7Tp08rKCikpqaGhoYWFhbu3bt3zpw558+f5+fnP3/+/MKFC0VERFatWjU6Onrz5s3Q0NDNmzcfOnRo3NBrV1fXxYsX8VNCW1pafH19IbOIxmE7duzg4eGZO3cuGxubk5OTkZFRZ2fnli1b8vLy7ty5c+TIEREREaB5379/n0a6wIVHOaCAgIA5c+aguNHw8LCvry8EPCUkJDo7O2/evIlvX5CrsLCwhoYG6KSLFi0CjT86Onrr1q2QkBBYZGblypXGxsbCwsLbtm1raGjo7e0VEhIyMjKytrbu6Oiws7NrbGycM2cOExMTDw/Pb7/9hn/PgICA3NzcwMBA/P+CDJSWlkLr79ix4/Pnzxs3bpw1a9azZ8+am5tnzpw5f/58yFh3dHSAU6ilpfXrr7/29vb++uuvhYWFPDw8ISEh+KRPYWGht7e3oKDgwMDA169fT58+LSMjA2rq119/hUF5S0tLeHg4yPCZM2fy8/PNzc0fPHjAzc1tZ2c3bjy/rq7u7t27JSUlzMzMfX195ubm+BBIR0eHra1tU1OTvLz8yZMna2pqPn/+HBYWJi0tvX79+qCgoCVLluTn57OwsNy4cYN+BQgbG5vW1lZwUGbOnHn06FEpKSnIl797987e3l5UVDQgIABu+PTpk6+vb05ODgcHx8OHD0dHR+/cuVNaWmpmZmZoaNja2pqZmQlTvY8fP25kZOTk5GRnZ3fq1CkLCwtEfYXU75MnTzQ0NCZR+I2NjVFRUWlpaezs7DB7BVR9fn7+lStXREVFLSwsTpw4cf36dZpRvqenZ3Nz88KFC+Pj4zdv3gwjq+PHj7Ozs5eXl+/Zs2flypW1tbUkEomZmZmLi4udnf327dvwgf39/a6urtnZ2UePHkWZ9aqqKlhBHS0w0NPTc/bsWTSpHT8KNzMzmzlz5owZM9jZ2Z2cnERERNjZ2Wtra52cnCCPQyaT3d3dNTQ0enp6goKCamtrhYWFGxsbobTW1tb09PSRkRFLS8sDBw6Ul5cDRfHAgQMyMjLgHj148AAmwvyNRs//QZSUlMjIyND4SlCbkyy9O0XAxCoYWOMXYl2zZs0PrpWNpoeh0TMBAgQI/GcxMjKydetWoh7+5vjH7PdcW1tbXl4OE/wRBAUF582bNwmtY4rYtWuXl5cXfkYNQF1d/QfXysYwTFpaesGCBd9HcSRAgACBn45du3bRr5ZF4O8Gxn/023t6em7b1K/imwAAAXlJREFUtg1NuPxubN269dGjR3h65/Pnz79+/UpvsL+P3Lhr166pU4oIECBA4M9DYWFhenr632GbcwKT49tyz/9BwPovDx8+RBMJKisru7q6PD09YRGGH0FpaenZs2fr6+sPHjyIYVhPT8/vv/+ur6//TdOr6NHT02NrayskJHTlypUff0kCBAgQ+BF4eHg4OzsLCQlFRERMtMYRAcI8fyfwu9BIS0tPfeWQqSA+Ph5N3pCUlPzx4E9vb29aWpquru4U9wckQIAAgT8Pz58/p1AoAgICeLInAcI8EyBAgAABAgSmCiLiSoAAAQIECBDmmQABAgQIECBAmGcCBAgQIECAMM8ECBAgQIAAAcI8EyBAgAABAoR5JkCAAAECBAgQ5pkAAQIECBAgzDMBAgQIECBAgDDPBAgQIECAAAHCPBMgQIAAAQKEeSZAgAABAgQIEOaZAAECBAgQIMwzAQIECBAgQIAwzwQIECBAgABhngkQIECAAAECfzH+H8Py9EQ5JVL7AAAAAElFTkSuQmCC
[[Power-Law Distributions in Empirical Data|file:///home/guillefix/Dropbox/Oxford/MMathPhys/Complex%20systems/Power%20law%20distributions%20in%20empirical%20data.pdf]]
[[Snarky summary of Power-Law Distributions in Empirical Data|http://bactra.org/weblog/491.html]]
[[Code and data for Power-law Distributions in Empirical Data|http://tuvalu.santafe.edu/~aaronc/powerlaws/]]
[[POWER-LAW DISTRIBUTIONS INBINNED EMPIRICAL DATA|https://arxiv.org/pdf/1208.3524.pdf]]
[[Code and data for Power-law Distributions in Binned Empirical Data|http://tuvalu.santafe.edu/~aaronc/powerlaws/bins/]]
See [[Statistics]]
https://en.wikipedia.org/wiki/Power-line_communication
Main current applications in narrow-band networking:
* Applications in the smart grid
* Home automation and networking ([[Internet of Things]])
A ''pre-order'' on a [[Set]] $$X$$ is a (binary) [[Relation]] on $$X$$, that is [[reflexive|Reflexivity]] and [[transitive|Transitivity]].
//aka prefix-free, or instantaneous code//
A string is a //prefix// of another string if their first $$n$$ symbols coincide, for some $$n \geq 1$$.
A ''prefix code'' is a [[Variable-length code]] where no codeword is a prefix of another codeword.
[[(IC 2.5) Prefix codes|https://www.youtube.com/watch?v=HST2r5pvJCA&index=11&list=PLE125425EC837021F]]
[[(IC 2.6) Prefix codes - remarks and what's next|https://www.youtube.com/watch?v=0zw62NhxNMQ&index=12&list=PLE125425EC837021F]]
Any prefix code is uniquely decodable
A prefix code can be [[represented as a search tree|https://www.youtube.com/watch?v=HST2r5pvJCA&index=11&list=PLE125425EC837021F#t=8m35s]], and is a nice way to think about prefix codes.
The above definition may called left-prefix. There is also the notion of right-prefix. See [[here|https://www.youtube.com/watch?v=HST2r5pvJCA&index=11&list=PLE125425EC837021F#t=13m35s]]
[[Example to see why prefix codes are faster (in the sense of computational complexity) to decode than other uniquely decodable codes|https://www.youtube.com/watch?v=oMu2OzKUVjw&list=PLE125425EC837021F&index=10#t=7m31s]]. Prefix codes are decodable in linear time
-----------------------
http://mathworld.wolfram.com/Preimage.html
A type of [[Communication]] involving one person (or a few people) communicating (mostly one-way with a group).
[img[https://i.embed.ly/1/display/resize?key=1e6a1a1efdb011df84894040444cdc60&url=http%3A%2F%2Fpbs.twimg.com%2Fmedia%2FB0ucuoyCUAEIbcU.jpg]]
!!__Presentation software__
[[PowerPoint]]
[[Web presentation software]]
//aka PCA//
[[Intro vid by Andrew Ng|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=37m35s]]
Given $$\{ x^{(1)}, ..., x^{(n)}\}$$ where $$ x^{(i)} \in \mathbb{R}^n$$
Reduce it to $$k$$-dimensional data set ($$k < n$$, often $$k \ll n$$), so that the dimensions we retain are able to recover the data as well as possible.
[[Examples|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=38m50s]], [[oxford notes|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides13.pdf]]
!!__Algorithm__
[[Summary of algorithm|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=2m10s]]
!!!__Pre-processing of the data__
[[vid|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=42m10s]]
# Zero-out mean
## Set $$\mu =\frac{1}{m}\sum _{i=1}^mx^{\left(i\right)}$$
## Replace $$x^{(i)}$$ with $$x^{(i)} -\mu$$
# Normalize to unit variance
## Set $$\sigma _j^2=\frac{1}{m}\sum _{i=1}^m\left(x^{\left(i\right)}\right)^2$$
## Replace $$x^{(i)}_j$$ with $$\frac{x^{(i)}_j}{\sigma_j}$$
!!!__Finding principal components__
[[Example and intuition|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=45m45s]]: we want to find the direction so that when we project the data to the line pointing in that direction, the variance of the data is as high as possible.
,,Note: If $$||u||=1$$, vector $$x^{(i)}$$ projected onto $$u$$ has length $$(x^{(i)})^T u$$.,, This also minimizes the variance perpendicular to that line.
Choose $$u$$ s.t.:
$$\max\limits_{u:||u||=1} \frac{1}{m}\sum\limits_{i=1}^m ((x^{(i)})^Tu)^2$$
$$=\max\limits_{u:||u||=1} \frac{1}{m}\sum\limits_{i=1}^m (u^Tx^{(i)})((x^{(i)})^Tu)$$
$$=\max\limits_{u:||u||=1} u^T \left [\frac{1}{m}\sum\limits_{i=1}^m x^{(i)}(x^{(i)})^T \right] u$$
This implies that ''$$u$$ is the principal eigenvector of the covariance matrix'':
$$\mathbf{\Sigma} = \frac{1}{m}\sum\limits_{i=1}^m x^{(i)}(x^{(i)})^T$$
See [[here|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=52m30s]] for nice derivation.
More generally [[for k-dimensional subspace on which to project the data|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=54m50s]], you choose the $$k$$ [[Eigenvector]]s with the largest [[Eigenvalue]]s.
Can then also transform to the new subspace [[by projecting into the new basis|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=58m]] to get a ''lower-dimensional representation of the data''.
[[Another view of PCA|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h2m45s]], there are several more views of PCA.
!!__Implementation of PCA__
[[Problem with covariant matrix|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=18m]]
Using the [[Design matrix]], $$X$$, we can rewrite the covariance matrix as $$\Sigma = X^T X$$
We can use [[Singular value decomposition]], $$X= U D V^T$$ and [[then|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=27m11s]], the top $$k$$ columns of $$V$$ are the top $$k$$ eigenvectors of $$X^T X = \Sigma$$. If the number of samples is much smaller than their dimensionality, then $$X$$ is a fat matrix ($$m \times d$$) with much fewer entries than $$\Sigma$$ ($$d \times d$$), and is thus more efficient to store on memory, and to compute with.
!!__Applications of PCA__
[[Video|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h4m20s]]
* [[Data visualization]]
* [[Data compression]]
* [[Machine learning]], [[Feature selection]]
* [[Anomaly detection]]
* Matching/distance calculations. See [[here|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h10m]] --> [[using PCA for comparing data points|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h13m20s]] --> From here [[we get eigenfaces!|https://www.youtube.com/watch?v=ey2PE5xi9-A&list=PLA89DCFA6ADACE599&index=14#t=1h14m]]
!!!__[[Latent semantic indexing]]__
LSI is essentially [[application of PCA to text data|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=5m05s]]
--------------------
[[Independent component analysis|https://en.wikipedia.org/wiki/Principal_component_analysis]]
https://www.wikiwand.com/en/Principle_of_indifference
Suppose that there are n > 1 mutually exclusive and collectively exhaustive possibilities. The principle of indifference states that if the n possibilities are indistinguishable except for their names, then each possibility should be assigned a probability equal to 1/n.
[[Video|https://www.youtube.com/watch?v=yXkEpzexYIU#t=23m36s]]
The ''Principle of multiple explanations'', or ''Epicurus principle'' states that
<<<
if several theories are consistent with the observed data, retain them all
<<<
See also [[Universal inductive inference]] for a combination of this principle with [[Occam's razor]].
https://www.wikiwand.com/en/Epicurus#/Epistemology
The probability distribution over hypothesis or variable $$x$$, in [[Bayesian statistics]], before seeing some batch of data.
__Carnap's theory of a priori probabilities__
[img[http://i.imgur.com/I8ATF25.png]]
https://www.wikiwand.com/en/Cromwell's_rule
[[Measure-theoretical dynamical system]] where the measure is a [[Probability measure]]
I invented this term, not sure if it already exists.
[[Model]]s for [[Probability distribution]]s. These models relate [[Random variable]]s, using some more or less general assumptions about the nature of the data.
[[Graphical model]]
[[Artificial neural network]]
See [[Machine learning]]
[[Generative model]]
[[Human-level concept learning through probabilistic program induction.|https://www.ncbi.nlm.nih.gov/pubmed/26659050]]
See [[Probability theory]]
//aka probability distribution function//
A [[Probability measure]] in a certain space of variables.
!!__Probability density (pdf)__
For continuous variables
probability = probability density $$\times$$ volume
!!__Probability mass (pmf)__
For discrete variables
!!__Examples of probability distributions__
!!__[[Joint probability distribution]]__
[[Marginal probability]], Integrate out one variable.
A [[Measure]] $$P$$ on set $$\Omega$$ s.t. $$P(\Omega)=1$$
https://en.wikipedia.org/wiki/Probability_space
# A [[Measurable space]]
## A [[Set]], called the [[Sample space]], $$\Omega$$, which is the set of all possible outcomes.
## A [[Sigma-algebra]], referred to as the set of [[event|Event (probability theory)]]s $$\mathcal{F}$$, where each event is a set containing zero or more [[outcomes|Outcome (probability)]].
# A [[Probability measure]], which corresponds to the assignment of [[probabilities|Probability]] to the events; that is, a function $$P$$ from events to probabilities.
''Probability Theory'' [[Wiki article|https://en.wikipedia.org/wiki/Probability_theory]]. Mathematica foundations of ''probability''
!! [[Probability cheat sheet|https://static1.squarespace.com/static/54bf3241e4b0f0d81bf7ff36/t/55e9494fe4b011aed10e48e5/1441352015658/probability_cheatsheet.pdf]]
[[webpage|http://www.wzchen.com/probability-cheatsheet?utm_content=buffer3e4c1&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer]]
[[Probability, Mathematical Statistics, Stochastic Processes|http://www.math.uah.edu/stat/index.html]]
[[Probability space|https://en.wikipedia.org/wiki/Probability_space]]
Based on [[Measure theory]]
[[Probability Primer|https://www.youtube.com/playlist?list=PL17567A1A3F5DB5E4]]
[[Probability space]]
!![[Random variable]]
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[[Basic results in probability theory]]
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!![[Probability distribution function|Probability distribution]]
__Cumulative distribution function__
!!!Moments and cumulants
!!!Generating functions
!!!Central Limit Theorem
--------
!!![[Combinatorics]]
Probabilistic method (see book)
-------------
[[Baye's theorem]], [[Bayesian statistics]]
https://en.wikipedia.org/wiki/Procedural_generation
[[Procedural graphics]]
Often uses generative models in [[Supervised learning]], and now //deep generative models//
!!__Audio generation__
[[Speech synthesis]]
[[Music synthesis]]
!!__Image generation__
__Handwriting generation__
__[[Deep art]]__
__Texture generation__
[[Procedural Yarn Models for Cloth Rendering|https://www.youtube.com/watch?v=iTRnr6p7iYo]] [[pdf|http://www.cs.cornell.edu/~kb/publications/SIG16ProceduralYarn.pdf]]
[[Two Minute Papers - Time Varying Textures|https://www.youtube.com/watch?v=FMHGS8jWtzM]]
A change in the [[properties|Property]] of something through time.
See also [[Activity]]
[[Dynamical system]], [[Category theory]], [[Stochastic process]] (for probabilistic processes)
The product [[topology|Topological space]] on a [[Cartesian product]] of $$n$$ [[Topological space]]s ($$X_i, \tau_i$$, $$i \in I$$, where $$I$$ is some index set) is defined to be the union of all sets of the form $$O_1 \times O_2 \times ... \times O_n$$ where $$O_i \subset X_i$$ is $$\tau_i$$-open. Where we are assuming here $$I$$ is finite. This definition is not correct when $$I$$ is infinite, and the definition using cylinder sets below must be used. Note that the definitions are different because the basis is constructed from __finite__ intersections of the open cylinders. However, some elements corresponding to infinite Cartesian products of the form $$\times_{i\in I} O_i$$ can't be realized from finite intersections of open cylinders which all have the form $$(\times_{i = J} O_i) \times ( \times_{i\in I \setminus J} X_i)$$, where $$J$$ is a finite subset of $$I$$. This comes about for example, in infinite [[Sequence space]]s.
It can also be constructed using [[Filter subbase]]s and [[Filter base]]s (that generate the open sets of the topology)
[img[http://i.imgur.com/o7BOSC4.png]]
Note the elements $$U(j, O)$$ forming the subbase are part of the final topology. They have the form $$O_1 \times O_2 \times ... \times O_n$$ described above if we rememeber that the full set $$X_i$$ is always open.
The sets forming the subbase are known as ''open cylinders'', while those forming the basis are known as [[Cylinder set]]s.
Another equivalent way of defining the product topology is as the 'smallest' topology such that the projection functions $$\pi_j:\times_i X_i \rightarrow X_j$$, $$f \mapsto f(j)$$ are [[Continuous function]]s.
A smaller subbase is given by the [[Cylinder set]]s
[[Induction]] of [[Computer program]]s
See [[Integrating symbols into deep learning]], and [[Deep learning]], [[Cognitive science]]
[[Bayesian program learning]]
[[Universal Coating for Programmable Matter|http://arxiv.org/abs/1601.01008]]
DNA Computing and Molecular Programming: 21st International Conference, DNA ...
[[Claytronics|http://www.cs.cmu.edu/~claytronics/index.html]]
[[Distributed Intelligent MEMS: Progresses and Perspectives|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6646194&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel7%2F4267003%2F4357939%2F06646194.pdf%3Farnumber%3D6646194]]
[[Scalable Simulation of Wireless Electro-Magnetic Nanonetworks|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7363621&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7363621]]
[[Design, Fabrication and Characterization of an Autonomous, Sub-millimeter Scale Modular Robot |http://repository.cmu.edu/cgi/viewcontent.cgi?article=1166&context=dissertations]]
[[A Markov Chain Algorithm for Compression in Self-Organizing Particle Systems|http://arxiv.org/abs/1603.07991#]]
More specifically, ''computer programming''
[img[https://upload.wikimedia.org/wikipedia/commons/1/1d/8bit-dynamiclist.gif]]
[[Portal:Computer programming|https://en.wikipedia.org/wiki/Portal:Computer_programming]]
__Abstractions__
[[Programming language]]
* [[Data type]]
* [[Reference (computer science)]]
[[Lecture 1 - Programming Paradigms (Stanford)|https://www.youtube.com/watch?v=Ps8jOj7diA0&list=PL1D3B7D7242B3C224]]
[[Concurrent programming]]
__Implementation__
[[Compiler]]
[[Memory allocation]]
[[Machine code]]
[[Operating system]]
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[[Software engineering]]
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Search syntax constructs of common languages: https://syntaxdb.com/
[[Principles of Programming Languages|http://nptel.ac.in/courses/106102067/]]
[[Structure and Interpretation of Computer Programs|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/video-lectures/]]
//Books//:
Clean code, the art of computer programming
__Interpreted programming language__
Interpreted at runtime, limited optimization
__Compiled programming language__
Compiled into machine code. Much more powerful optimization
!!!__Programming language paradigms__
[[Programming paradigms|https://en.wikipedia.org/wiki/Programming_paradigm]]
''Imperative'': give instructions to change the state of the program
''Declarative'': just write statements (assertions) of what things do, what functions do they perform. Then the program can take inptus and give outputs by passing inputs through the various nested functions ([[Functional programming]]).
<b>[[Visual programming language]]s</b> Nice example: https://vvvv.org/
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Most programming languages are context-free. http://stackoverflow.com/questions/898489/what-programming-languages-are-context-free. See [[Theory of computation]]
!!__Programming languages__
!!![[C/C++]]
!!![[Python|Python (programming language)]]
!!![[JavaScript]]
[[Assembly (programming language)]]
--------
Other languages
Go, Lisp, Clojure,
https://www.rust-lang.org/
[[Esoteric programming languages|https://esolangs.org/wiki/Main_Page]]
//Projects, ideas, action//, is about ''new ideas'', the ''brink of the known'', the ''edge of the [[philosophical Cosmos|Philosophy]]''.
[[Interdisciplinary]], antidiscilpinary, etc. New emergent ideas. Things that don't fit
Also: thinking what to do, and doing.
Lifes of important/influential people: http://fundersandfounders.com/
http://www.iftf.org/home/
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Facebook, twitter news feed...
Organisms composed of [[Cell]]s without a well-defined [[nucleus|Cell nucleus]], no cytoskeleton (transport by [[Cytoplasmic streaming]], or [[Organelle]]s. They often have a cell wall
!!__[[Bacteria]]__
!!__Bacteria__
One of the most studied model organisms is the [[Escherichia coli|https://en.wikipedia.org/wiki/Escherichia_coli]]
[[Gram staining|https://en.wikipedia.org/wiki/Gram_staining]] is a method of staining used to differentiate bacterial species into two large groups (''gram-positive'' and ''gram-negative''), by detecting [[peptidoglycan|https://en.wikipedia.org/wiki/Peptidoglycan]], which is present in a thick layer in gram-positive bacteria
[[Actinobacteria|https://en.wikipedia.org/wiki/Actinobacteria]] is a phylum of Gram-positive bacteria with high guanine and cytosine content in their DNA
[[Streptomyces|https://en.wikipedia.org/wiki/Streptomyces]] is the largest genus of Actinobacteria
[[Streptomyces hygroscopicus|https://en.wikipedia.org/wiki/Streptomyces_hygroscopicus]] produces [[Sirolimus|https://en.wikipedia.org/wiki/Sirolimus]], also known as rapamycin which is an inhibitor of the [[Kinase]] enzyme [[Mechanistic target of rapamycin]]
A proof in [[Mathematics]] is a demonstration of a statement within a fixed system of propositions.
-------------------
!!//Proof vs derivation//
The Propositional Calculus is very much like reasoning in some w one should not equate its rules with the rules of human thought. A proof is something informal, or in other words a product of normal thought written in a human language, for human consumption. All sorts of complex features of thought may be used in proofs, and, though they may “feel right", one may wonder if they can be defended logically. That is really what formalization is for. A derivation is an artificial counterpart of and its purpose is to reach the same goal but via a logical structure whose methods are not only all explicit, but also very simple.
If -- and this is usually the case -it happens that a formal derivation is extremely lengthy compared with the corresponding "natural" proof that is just too bad. It is the price one pays for making each step so simple. What often happens is that a derivation and a proof are "simple" in complementary senses of the word. The proof is simple in that each step sounds right", even though one may not know just why; the derivation is simple in that each of its myriad steps is considered so trivial that it is beyond reproach, and since the whole derivation consists just of such trivial steps it is supposedly error-free. Each type of simplicity, however, brings along a characteristic type of complexity. In the case of proofs, it is the complexity of the underlying system on which they rest -- namely, human language -- and in the case of derivations, it is their astronomical size, which makes them almost impossible to grasp.
An [[Entity]] has a certain ''property'' if it belongs to the [[Set]] that {the [[Concept]] corresponding to that property} represents.
//propositional calculus//
A [[Formal system]] that implements working with the logical notions of ''and'' ($$\wedge$$), ''or'' ($$\vee$$), ''not'' $$\sim$$, ''if ... then ...'' ($$\subset$$) (implication), and [[Deduction]] (from propositions to consequences, using ''rules of inference'' encapsulated within $$[...]$$). derived propostions are put within angle brackets $$<$$ and $$>$$.
See chapter VII of [[GEB|Godel, Escher, Bach]]
__Well formed strings__
//Atoms// (atomic symbols which stand for initial propositions): $$P$$, $$Q$$, $$R$$, and any primed ($$'$$) version.
Well-formed strings are defined [[recursively|Recursion]]. If $$x$$ and $$y$$ are well-formed, then these are also well-formed:
* $$\sim x$$
* $$<x \wedge y>$$ (''joining rule'')
* $$<x \vee y >$$
* $$ <x \subset y >$$
!!__Rules of inference__
* ''Rule of separation''. If $$<x \wedge y >$$ is a theorem, then both $$x$$ and $$y$$ are theorems.
* ''Double-tilde rule'': The string "$$\sim \sim$$" can be delted from any theorem. It can also be inserted into any theorem, provided that the resulting string is itself well-formed.
!!!__Deduction theorem__
A special formal rule. Can put any series of well formed propositions within the square brackets ($$[$$, $$]$$), as long as each proposition can be derived from the previous, using the rewrite rules above, except the first one, which is jut required to be a well-formed string (and it's like a fantasy axiom, //what if//).
The ''deduction theorem'' (aka fantasy rule) than says that $$<x \subset y>$$ is a theorem, where $$x$$ is the initial string, and $$y$$ is the final string in the derivation i.e. when //$$y$$ can be derived when $$x$$ is assumed to be a theorem//. Only strings that result from the fantasy rule (and strings that are derivable from them), are considered genuine theorems, I think. __So this is a slightly different kind of [[Formal system]], than those usually defined, <mark> right?</mark>__
* ''Carry-over rule'': Inside a fantasy, any theorem from the "reality" one level higher can be brought in and used.
These implications/derivation rules are interesting from a formal system perspective. They are a <b>a representation inside the system of a statement about the system</b>.
* ''Modus Ponens'' (aka rule of detachment): If $$x$$ and $$<x \subset y >$$ are both theorems, then $$y$$ is a theorem.
* ''Contrapositive rule'': $$<x \subset y>$$ and $$<\sim y \subset \sim x>$$ are interchangeable.
* ''De Morgan's rule'': $$<\sim x \wedge \sim y>$$ and $$\sim < x \vee y >$$ are interchangeable.
* ''Switcheroo rule''L $$<x \vee y >$$ and $$ < \sim x \subset y >$$ are interchangebale.
!!__[[Decision rule]]__
Method of truth tables
Prostaglandin PGE2 is a candidate molecule for potentiating regeneration in multiple different tissues. PGE2 is produced by the enzyme activity of cyclooxygenase-1 or cyclooxygenase-2 (COX-1 and COX-2) followed sequentially by that of prostaglandin E synthase. These come from anachidonic acid..
PGE2 augments Wnt signaling (10, 11), a pathway that is involved in the maintenance of several types of tissue stem cells, including hematopoietic and colon stem cells
It promotes [[Tissue regeneration]], and is thus used as a target in [[Regenerative medicine]]
[[Enzyme]]s that break [[Peptide bond]]s in [[Protein]]s
[[Protein|https://en.wikipedia.org/wiki/Protein]] are large biomolecules, or macromolecules, consisting of one or more long chains of amino acid residues.
!!__Classes of proteins__
[[Enzyme]]s
Pleytropic: perform many function
!!__[[Protein structure]]__
[[Protein folding]] problem
Denatured proteins cause a lot of [[Disease]]s
Making [[Protein]]s assemble into a [[Crystal]]
!!__Methods__
[[Hanging-drop vapor diffusion crystalization]]
ClpXP, ClpAP. Degraadation in cytoplasm, and periplasm.
ssrA tags. Native role is to prevent accumulation of unfinished proteins.
Protein degradation can depend on [[Temperature]], because folding changes.
[img [http://www.gate2biotech.com/documents/direct_evolution2.jpg]]
Educational portal of the awesome [[Protein databank|http://www.rcsb.org/pdb/home/home.do]] : http://pdb101.rcsb.org/
!!__Statistical mechanics of protein folding__
[[Spin glasses and the statistical mechanics of protein folding|https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjA6pr-xu7PAhUHvxQKHUU1BVQQFgghMAA&url=http%3A%2F%2Fwww.pnas.org%2Fcontent%2F84%2F21%2F7524.full.pdf&usg=AFQjCNGhtZHOCLpIEDTaWAWV-hLecF2TiA&sig2=WDFn_bYqRNAIzlfXZ4-ybg]]
Related to [[Spin glass]], [[Glass transition]], and [[Deep learning]], [[Deep learning theory]]
[[The 'glass transition' in protein dynamics: what it is, why it occurs, and how to exploit it.|https://www.ncbi.nlm.nih.gov/pubmed/14499926]]
http://www.eoht.info/page/Energy+landscape
[[Protein Folding, Binding and Energy Landscape: A Synthesis|http://cdn.intechopen.com/pdfs/29180.pdf]]
[[Spin glasses and the statistical mechanics of protein folding|http://www.pnas.org/content/84/21/7524.full.pdf]]
http://dillgroup.stonybrook.edu/#/landscapes
!!__Protein missfolding__
[[Prions and Protein Misfolding|https://www.youtube.com/watch?v=Chs7ixRstQk]]
Some [[Protein]]s can have many native folded states with different functions. Different mRNAs can produce these differently folded states, by giving rise to different [[mRNA translation]] dynamics (for instance by different secondary structures).
Purification of [[Protein]]s
[[Video (purifying GFP)|https://www.youtube.com/watch?v=oKAvdAFdweA#t=40s]]
[[Column chromatography and fractionation to purify Beta-galactosidase |https://www.youtube.com/watch?v=Ro9vq7FmRYA]]
__Experimental techniques__
Protein purification, using [[Column chromatography]]
Easy for thermophiles as you can use heat for purification..
https://pdb101.rcsb.org/
!!!__Primary structure__
[[Amino acid]]s, forming a [[Polymer]] by [[Dehydration synthesis]], forming a bond called a [[Peptide bond]]. A protein is thus called a ''polypeptide''.
Proteins are [[Chiral molecule]]s, because amino acids are. The peptide bonds can be in Cis or Trans conformation. Almost all bonds are Trans, due to steric hindrances.
[[Geometrical structure of peptide bonds|https://www.youtube.com/watch?v=Lhykdr5uyw4#t=8m15s]]. They are planar due to [[sp2 hybridization]]
!!!__Secondary structure__
[img width=460 [protein-torsion-angle.PNG]]
phi and psi angles are (approximately) the only degrees of freedom left, given constraints of chemical bond angles, sizes, and other steric hindrances.
Ramachandran plot, residue unit, peptide unit
Stabilized partially, by [[Hydrogen bond]] between a [[Carbonyl]] group, and a NH.
$$\alpha$$-helix.
$$\beta$$-sheets
$$\beta$$-barrel
loops, random coils
[[video|https://www.youtube.com/watch?time_continue=5&v=CYsMRBDQ2yg]]
!!!__Tertiary structure__
loops, turns, random coils
folds, domains.
!!!__Quaternary structure__
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/c/c9/Main_protein_structure_levels_en.svg/500px-Main_protein_structure_levels_en.svg.png]]
[[vid|https://www.youtube.com/watch?time_continue=10&v=vEJbn1y2YN0]]
!!__Experimental techniques__
[[Protein purification]]
[[Protein structure analysis]]
!!__Types of proteins__
[[Enzyme]]s
!!__[[Protein folding]]__
-------------------
[img[https://upload.wikimedia.org/wikipedia/commons/2/24/Protein_structure_examples.png]]
__Preparation__
* [[Protein purification]]
* [[Protein crystallization]]
__Imaging__
* [[X-ray crystallography]]
* [[Cryo EM|Cryo-electron microscopy]]! <-- 3 to 5 Angstrom
__Computational analysis__
Uses [[Machine learning]], [[Statistics]]
* [[Clustering]], like [[UPGMA]] or [[K-means algorithm]]
* [[Statistical potential]] for analysis of [[Protein-decoy structure]]s
When predicting protein structures, normally many different possible structures are made.
These candidate conformations are known as decoys. By making many decoys (generating them computationally), the
probability that one of them closely resembles the true structure of the target protein is
increased - however, since the true structure is unknown, a method must be developed
that can predict which of the decoys is the most accurate. One way of doing this is via the
use of a statistical (or knowledge-based) energy function, known as [[Statistical potential]]
[[Network properties of protein-decoy structures|https://www.ncbi.nlm.nih.gov/pubmed/22545992]]
[[Protein decoy sets for evaluating energy functions|https://www.ncbi.nlm.nih.gov/pubmed/15106995]]
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
In some systems of biological classification, the Protozoa are a diverse group of unicellular eukaryotic organisms. Historically, protozoa were defined as single-celled organisms with animal-like behaviors, such as motility and predation.
However, they are not part of most current taxonomic systems. See [[Tree of life]]
https://www.wikiwand.com/en/Protozoa
[[pdf of my essay|familial-alzheimers-disease.pdf]]
!!__Molecular mechanisms__
[img[Familial_Alzheimer's_molecular_mechanisms.png]]
[img[https://s13.postimg.org/rk35ao2ef/Selection_660.png]]
!!!__Normal function (Physiology)__
Aβ is enzymatically cleaved from the transmembrane protein APP by β- and γ-secretase and is released extracellularly in lengths ranging from approximately 37 to 43 amino acids. Aβ40 is the most abundant species and exists in an approximately 10:1 concentration ratio with Aβ42
Thinakaran et al. (1996) observed a polypeptide of approximately 43 kD in cells transfected with full-length human PS1 cDNA. Using 2 highly specific antibodies against nonoverlapping epitopes of presenilin-1, they demonstrated that the preponderant PS1-related species that accumulate in cultured mammalian cells and in the brains of rodents, primates, and humans are approximately 27-kD N-terminal and about 17-kD C-terminal derivatives. Epitope mapping analysis showed that PS1 cleavage occurred between amino acids 260 and 320. In brains of transgenic mice expressing human PS1, the 17-kD and the 27-kD PS1 derivatives accumulate to saturable levels, and at about 1:1 stoichiometry, independent of transgene-derived mRNA. The authors concluded that ''PS1 is subject to endoproteolytic processing in vivo''.
__Location__
,,localize to similar intracellular compartments, such as the endoplasmic reticulum and Golgi complex. . Takashima et al. (1996) showed that in COS-7 cells overexpressing PS1, the protein is localized to cellular membranes: plasma, endoplasmic reticulum, and perinuclear.,,
They observed that PS1 immunoreactivity in the plasma ''membrane'' is concentrated in regions of cell-cell contact, suggesting that PS1 may be a ''cell adhesion molecule''.
Li et al. (1997) demonstrated that wildtype PS1 and PS2 localize to the nuclear membrane and associate with interphase kinetochores and centrosomes, and suggested that the proteins play ''a role in chromosome organization and segregation''. ,,Li et al. (1997) stated that PS1 and PS2 localization to the membranes of the endoplasmic reticulum and Golgi is not unexpected for overexpressed membrane proteins because these locations are the sites of their synthesis and processing.,,
Using Western blot analysis and immunogold electron microscopy, Pasternak et al. (2003) demonstrated that significant amounts of nicastrin, Psen1, and App colocalized with Lamp1 (153330) in the outer membranes of rat lysosomes
__''Gamma-secretase Activity''__
The authors interpreted the data as indicating that gamma-secretase activity is catalyzed by a PS1-containing macromolecular complex.
Lee et al. (2002) showed that nicastrin and presenilin heterodimers physically associated with APH1A and APH1B (607630) in vivo to form the gamma-secretase complex that is required for the intramembrane proteolysis of many membrane proteins, including APP and NOTCH. PEN2 seems to also be important, and it requires presenilin and nicastrin..
''Gamma-secretase activity (which proteolyzes APP) requires'' the formation of a stable, high molecular mass protein complex that, in addition to the ''endoproteolyzed fragmented form of presenilin'', contains essential cofactors including nicastrin, APH1, and PEN2.
Thus, Takasugi et al. (2003) concluded that APH1 stabilizes the presenilin holoprotein in the complex, whereas PEN2 is required for endoproteolytic processing of presenilin and conferring gamma-secretase activity to the complex. ([[The role of presenilin cofactors in the gamma-secretase complex|https://www.ncbi.nlm.nih.gov/pubmed/12660785]])
,,Kaether et al. (2004) determined that the very C terminus of PS1 interacts with the transmembrane domain of nicastrin and may penetrate into the membrane. Deletion of the last amino acid of PS1 completely blocked gamma-secretase assembly and release of PS1 from the ER, suggesting that unincorporated PS1 is actively retained within the ER. Kaether et al. (2004) identified a hydrophobic stretch of amino acids within the PS1 C terminus, distinct from the nicastrin-binding site, that was required to retain unincorporated PS1 within the ER. Deletion of the retention signal resulted in release of PS1 from the ER and assembly of a nonfunctional gamma-secretase complex, suggesting that at least part of the retention motif is required for PS1 function.,, Hmm...
Cai et al (2006): PLD1 regulates intracellular trafficking of beta-amyloid, distinct from its effect on gamma-secretase activity.
carboxy-terminal fragments of APP are normal the substrates of gamma-secretase.
__Role in Notch Signaling Pathway__
__Interactions with Cadherin Proteins__
__Other functions__
There are a number of alternative γ-secretase substrates, e.g.
APLP1, APLP2, Notch, cadherins, LRP [ 120 , 121 ], and syndecan-
1 [ 114 , 122 ].
In addition to γ-secretase dependent functions, some
PS functions are independent of γ-secretase, so that in effect,
γ-secretase may compete for presenilins with other γ-secretase inde-
pendent PS functions including cell adhesion, traffi cking of various
proteins [ 123 ], and Ca 2+ homeostasis [ 114 ]
APP and its protolytic fragments also has a variety of functions
At physiological concentrations Aβ is associated with numerous normal cellular functions [ 128 ] and in AD progression has multiple interactions that have been described as either neuroprotective or neurotoxic [ 36 ].
__$$\gamma$$ - secretase__
Proteolysis of C99 fragment of APP
Recently, gamma-secretase was shown to cleave near the cytoplasmic membrane boundary of APP, called epsilon-site cleavage, as well as in the middle of the membrane domain, called gamma-site cleavage. [[src|https://www.ncbi.nlm.nih.gov/pubmed/18393801]]
endopeptidase activity -- $$\epsilon$$ cleavage
carboxypeptidase-like cleavage -- $$\gamma$$ cleavage
!!!__Pathological function (Pathophysiology)__
Mercken et al. (1996) suggested that ''type 3 Alzheimer disease may be the result of impaired proteolytic processing of PS1''.
* In a British familial Alzheimer disease (FAD) pedigree, a PS1 variant with a deletion of amino acids 290 to 319 (delE9) (104311.0012) was not cleaved.
* PC12 cells transiently transfected with PS1 constructs containing 2 different Alzheimer mutations, M146V (104311.0007) and A246E (104311.0003), failed to generate the 28-kD degradation product in contrast to PC12 cells transfected with wildtype PS1.
Li et al (1997) discussed a pathogenic mechanism for FAD in which ''mutant presenilins cause may chromosome missegregation during mitosis'', resulting in apoptosis and/or trisomy 21 mosaicism.
An alternative hypothesis is that ''mutant presenilins not appropriately trafficked out of the endoplasmic reticulum may interfere with normal APP processing''
Duff et al. (1996) : transgenic mice overexpressing mutant, but not wildtype, presenilin-1 show a selective increase in brain A-beta-42(43). These results indicated that the presenilin mutations probably cause Alzheimer disease through a gain of deleterious function that increases the amount of the deposited A-beta-42(43) in the brain.
Citron et al. (1997) stated that their combined in vitro and in vivo data clearly demonstrated that the ''FAD-linked presenilin mutations directly or indirectly altered the level of gamma-secretase'', but not of alpha- or beta-secretase, ''resulting in increased amyloid beta-42 production which may lead to cerebral beta-amyloidosis and AD''
:,,The possible role of PS1 in normal APP processing was studied by De Strooper et al. (1998) in neuronal cultures derived from PS1-deficient mouse embryos. They found that cleavage by alpha- and beta-secretase of the extracellular domain of APP was not affected by the absence of PS1, whereas cleavage by gamma-secretase of the transmembrane domain of APP was prevented, causing C-terminal fragments of APP to accumulate and a 5-fold drop in the production of amyloid peptide. The results indicated to the authors that mutations in PS1 that manifest clinically cause a gain of function, and that inhibition of PS1 activity is a potential target for anti-amyloidogenic therapy in Alzheimer disease.,,
Results were taken to indicate that the 2 transmembrane aspartate residues are critical for both presenilin-1 endoproteolysis and gamma-secretase activity, and suggested that presenilin-1 either is a unique diaspartyl cofactor for gamma-secretase or is itself gamma-secretase, an autoactivated intramembranous aspartyl protease.
amino-terminally truncated forms of A-beta are increased in PS1 mutants Russo et al. (2000) suggested that the overexpression of amino-terminally truncated amyloid beta species indicates that not only is cleavage by gamma-secretase affected by ''PS1'' mutation, but that ''cleavage by beta-secretase is as well''.
,, Wilson et al. (2002) concluded that production of a pool of amyloid beta (in endoplasmic reticulum/intermediate compartment) occurs independently of PS1/PS2, and therefore, another gamma-secretase activity must be responsible for cleavage of APP within the early secretory compartments.,,
,,Phiel et al. (2003) showed that glycogen synthase kinase-3-alpha (GSK3A; 606784) is required for maximal production of the beta-amyloid-40 and -42 peptides generated from the amyloid precursor protein by presenilin-dependent gamma-secretase cleavage. ,,
They also showed that age of onset of PSEN1-linked familial Alzheimer disease correlated inversely with the ratio of A-beta-42/A-beta-40 and absolute levels of A-beta-42, but directly with A-beta-40 levels. Together, the data of Kumar-Singh et al. (2006) suggested that A-beta-40 may be protective by perhaps sequestering the more toxic A-beta-42 and facilitating its clearance.
|Mutations in PS1or PS2 change the cleavage activity of APP, resulting in increased Aβ42 production and/or high Aβ42/Aβ40 ratio.|
!!!__PS1 processing__
See ,,[[Three-amino acid spacing of presenilin endoproteolysis suggests a general stepwise cleavage of gamma-secretase-mediated intramembrane proteolysis.|https://www.ncbi.nlm.nih.gov/pubmed/20534834/]],,
PS is cleaved during complex assembly into its characteristic N- and C-terminal fragments. Both fragments are integral components of physiologically active gamma-secretase and harbor the two critical aspartyl residues of the active site domain. the precision of PS1 endoproteolysis is affected by PS1 mutations. Comparing the cleavage products generated by a variety of PS1 mutants revealed that specifically cleavages at positions 293 and 296 of PS1 are selectively affected. Systematic mutagenesis around the cleavage sites revealed a stepwise three amino acid spaced cleavage mechanism of PS endoproteolysis
!!!__Effect of PS1 mutations on $$\gamma$$-secretase disfunction ([[main paper|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/]])__
[[diagram and enzyme kinetics data|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/figure/f1/]]
tested FAD–PSEN1 mutations have no consistent inhibitory effect on the endoproteolytic cleavage of γ-secretase substrates, indicating that reduced release of intracellular domains and signalling cannot explain their AD-causing effects.
Low Aβ40 and Aβ38 levels and high, long Aβ levels (>Aβ42) are found in all the FAD-linked mutations tested, including the M139V, which does not affect the ɛ-efficiency. Interestingly, the M139V mutation affects the processing of APP only at the level of Aβ, indicating that endo- and carboxypeptidase-like activities of the γ-secretase can be dissociated.
|Our data imply that FAD–PSEN1 mutations cause AD by qualitative shifts in Aβ profiles and not by general loss of function of the enzyme complex|
,,Since high Aβ43 and Aβ42 (substrates in this cycle) accumulate in vitro or are released in vivo, we speculate that FAD–PSEN mutations promote a premature release of the Aβ43/Aβ42 peptides.,, [[Data plots|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/figure/f2/]]
__DR6 apoptosis pathway__
In addition to interactions with sAPPα and APP,
the large soluble sAPPβ fragment may be associated with apoptotic
signaling and axonal degeneration via the death receptor DR6 and
caspase6 [ 113 ], though the interactions of sAPPβ are not fully
characterized and require further detailed investigation.
__Other hypoethesis__
There are a variety of alternative hypothesis of how PSEN1 mutation can cause AD.
However, all tested FAD mutations affect the prime function of PSEN, which is proteolysis, so this affecting this pathway appears to be a necessary condition.
!!!__Amyloid cascade theory__
It has been suggested that increased toxic Aβ42 initiates a cascade of down-stream pathological processes such as tau hyperphosphorylation, neurofibrillary tangles (NFTs) formation, neuroinflammation, loss of synaptic junctions and neuronal cell death, with dementia being the ultimate clinical result of these progressive neurodegenerative processes.
Although the a myloid cascade is only one theory among myriads of other possible mechanisms for AD (e.g. tau, inflammatory or oxidative stress hypothesis) and amyloid alone is probably not sufficient to cause AD, the association of PS1/PS2/APP with amyloid synthesis and its processing warrants the amyloid cascade theory plays a more important role in EOFAD than the sporadic AD.
On the other hand, variable pathological expression reported in individuals carrying the same mutation suggests that epigenetic or other genetic factors may play a role in this phenotypic heterogeneity.
!!!__Oligomer cascade theory__
[[Amyloid β-protein oligomers and Alzheimer’s disease|http://alzres.biomedcentral.com/articles/10.1186/alzrt226]]
Aβ42 has been observed to reduce neuronal viability to a greater extent than Aβ40 [63]. Aβ42 thus seems to be most toxic, but both Aβ40 and Aβ42 form oligomers, and through distinct mechanisms [37].
!!__Systems biology__
AD is really a complex multi-faceted disease
[img[https://s15.postimg.org/yykkfwn2z/Selection_656.png]]
[img[https://s16.postimg.org/e32ytu7xx/Selection_657.png]]
[img[https://s15.postimg.org/m51pvv3gb/Selection_658.png]]
[img[https://s9.postimg.org/3wtva8tcv/Selection_659.png]]
!!__Molecular mechanisms__
[img[Familial_Alzheimer's_molecular_mechanisms.png]]
[img[https://s13.postimg.org/rk35ao2ef/Selection_660.png]]
!!!__Normal function (Physiology)__
Aβ is enzymatically cleaved from the transmembrane protein APP by β- and γ-secretase and is released extracellularly in lengths ranging from approximately 37 to 43 amino acids. Aβ40 is the most abundant species and exists in an approximately 10:1 concentration ratio with Aβ42
Thinakaran et al. (1996) observed a polypeptide of approximately 43 kD in cells transfected with full-length human PS1 cDNA. Using 2 highly specific antibodies against nonoverlapping epitopes of presenilin-1, they demonstrated that the preponderant PS1-related species that accumulate in cultured mammalian cells and in the brains of rodents, primates, and humans are approximately 27-kD N-terminal and about 17-kD C-terminal derivatives. Epitope mapping analysis showed that PS1 cleavage occurred between amino acids 260 and 320. In brains of transgenic mice expressing human PS1, the 17-kD and the 27-kD PS1 derivatives accumulate to saturable levels, and at about 1:1 stoichiometry, independent of transgene-derived mRNA. The authors concluded that ''PS1 is subject to endoproteolytic processing in vivo''.
__Location__
,,localize to similar intracellular compartments, such as the endoplasmic reticulum and Golgi complex. . Takashima et al. (1996) showed that in COS-7 cells overexpressing PS1, the protein is localized to cellular membranes: plasma, endoplasmic reticulum, and perinuclear.,,
They observed that PS1 immunoreactivity in the plasma ''membrane'' is concentrated in regions of cell-cell contact, suggesting that PS1 may be a ''cell adhesion molecule''.
Li et al. (1997) demonstrated that wildtype PS1 and PS2 localize to the nuclear membrane and associate with interphase kinetochores and centrosomes, and suggested that the proteins play ''a role in chromosome organization and segregation''. ,,Li et al. (1997) stated that PS1 and PS2 localization to the membranes of the endoplasmic reticulum and Golgi is not unexpected for overexpressed membrane proteins because these locations are the sites of their synthesis and processing.,,
Using Western blot analysis and immunogold electron microscopy, Pasternak et al. (2003) demonstrated that significant amounts of nicastrin, Psen1, and App colocalized with Lamp1 (153330) in the outer membranes of rat lysosomes
__''Gamma-secretase Activity''__
The authors interpreted the data as indicating that gamma-secretase activity is catalyzed by a PS1-containing macromolecular complex.
Lee et al. (2002) showed that nicastrin and presenilin heterodimers physically associated with APH1A and APH1B (607630) in vivo to form the gamma-secretase complex that is required for the intramembrane proteolysis of many membrane proteins, including APP and NOTCH. PEN2 seems to also be important, and it requires presenilin and nicastrin..
''Gamma-secretase activity (which proteolyzes APP) requires'' the formation of a stable, high molecular mass protein complex that, in addition to the ''endoproteolyzed fragmented form of presenilin'', contains essential cofactors including nicastrin, APH1, and PEN2.
Thus, Takasugi et al. (2003) concluded that APH1 stabilizes the presenilin holoprotein in the complex, whereas PEN2 is required for endoproteolytic processing of presenilin and conferring gamma-secretase activity to the complex. ([[The role of presenilin cofactors in the gamma-secretase complex|https://www.ncbi.nlm.nih.gov/pubmed/12660785]])
,,Kaether et al. (2004) determined that the very C terminus of PS1 interacts with the transmembrane domain of nicastrin and may penetrate into the membrane. Deletion of the last amino acid of PS1 completely blocked gamma-secretase assembly and release of PS1 from the ER, suggesting that unincorporated PS1 is actively retained within the ER. Kaether et al. (2004) identified a hydrophobic stretch of amino acids within the PS1 C terminus, distinct from the nicastrin-binding site, that was required to retain unincorporated PS1 within the ER. Deletion of the retention signal resulted in release of PS1 from the ER and assembly of a nonfunctional gamma-secretase complex, suggesting that at least part of the retention motif is required for PS1 function.,, Hmm...
Cai et al (2006): PLD1 regulates intracellular trafficking of beta-amyloid, distinct from its effect on gamma-secretase activity.
carboxy-terminal fragments of APP are normal the substrates of gamma-secretase.
__Role in Notch Signaling Pathway__
__Interactions with Cadherin Proteins__
__Other functions__
There are a number of alternative γ-secretase substrates, e.g.
APLP1, APLP2, Notch, cadherins, LRP [ 120 , 121 ], and syndecan-
1 [ 114 , 122 ].
In addition to γ-secretase dependent functions, some
PS functions are independent of γ-secretase, so that in effect,
γ-secretase may compete for presenilins with other γ-secretase inde-
pendent PS functions including cell adhesion, traffi cking of various
proteins [ 123 ], and Ca 2+ homeostasis [ 114 ]
APP and its protolytic fragments also has a variety of functions
At physiological concentrations Aβ is associated with numerous normal cellular functions [ 128 ] and in AD progression has multiple interactions that have been described as either neuroprotective or neurotoxic [ 36 ].
__$$\gamma$$ - secretase__
Proteolysis of C99 fragment of APP
Recently, gamma-secretase was shown to cleave near the cytoplasmic membrane boundary of APP, called epsilon-site cleavage, as well as in the middle of the membrane domain, called gamma-site cleavage. [[src|https://www.ncbi.nlm.nih.gov/pubmed/18393801]]
endopeptidase activity -- $$\epsilon$$ cleavage
carboxypeptidase-like cleavage -- $$\gamma$$ cleavage
!!!__Pathological function (Pathophysiology)__
Mercken et al. (1996) suggested that ''type 3 Alzheimer disease may be the result of impaired proteolytic processing of PS1''.
* In a British familial Alzheimer disease (FAD) pedigree, a PS1 variant with a deletion of amino acids 290 to 319 (delE9) (104311.0012) was not cleaved.
* PC12 cells transiently transfected with PS1 constructs containing 2 different Alzheimer mutations, M146V (104311.0007) and A246E (104311.0003), failed to generate the 28-kD degradation product in contrast to PC12 cells transfected with wildtype PS1.
Li et al (1997) discussed a pathogenic mechanism for FAD in which ''mutant presenilins cause may chromosome missegregation during mitosis'', resulting in apoptosis and/or trisomy 21 mosaicism.
An alternative hypothesis is that ''mutant presenilins not appropriately trafficked out of the endoplasmic reticulum may interfere with normal APP processing''
Duff et al. (1996) : transgenic mice overexpressing mutant, but not wildtype, presenilin-1 show a selective increase in brain A-beta-42(43). These results indicated that the presenilin mutations probably cause Alzheimer disease through a gain of deleterious function that increases the amount of the deposited A-beta-42(43) in the brain.
Citron et al. (1997) stated that their combined in vitro and in vivo data clearly demonstrated that the ''FAD-linked presenilin mutations directly or indirectly altered the level of gamma-secretase'', but not of alpha- or beta-secretase, ''resulting in increased amyloid beta-42 production which may lead to cerebral beta-amyloidosis and AD''
:,,The possible role of PS1 in normal APP processing was studied by De Strooper et al. (1998) in neuronal cultures derived from PS1-deficient mouse embryos. They found that cleavage by alpha- and beta-secretase of the extracellular domain of APP was not affected by the absence of PS1, whereas cleavage by gamma-secretase of the transmembrane domain of APP was prevented, causing C-terminal fragments of APP to accumulate and a 5-fold drop in the production of amyloid peptide. The results indicated to the authors that mutations in PS1 that manifest clinically cause a gain of function, and that inhibition of PS1 activity is a potential target for anti-amyloidogenic therapy in Alzheimer disease.,,
Results were taken to indicate that the 2 transmembrane aspartate residues are critical for both presenilin-1 endoproteolysis and gamma-secretase activity, and suggested that presenilin-1 either is a unique diaspartyl cofactor for gamma-secretase or is itself gamma-secretase, an autoactivated intramembranous aspartyl protease.
amino-terminally truncated forms of A-beta are increased in PS1 mutants Russo et al. (2000) suggested that the overexpression of amino-terminally truncated amyloid beta species indicates that not only is cleavage by gamma-secretase affected by ''PS1'' mutation, but that ''cleavage by beta-secretase is as well''.
,, Wilson et al. (2002) concluded that production of a pool of amyloid beta (in endoplasmic reticulum/intermediate compartment) occurs independently of PS1/PS2, and therefore, another gamma-secretase activity must be responsible for cleavage of APP within the early secretory compartments.,,
,,Phiel et al. (2003) showed that glycogen synthase kinase-3-alpha (GSK3A; 606784) is required for maximal production of the beta-amyloid-40 and -42 peptides generated from the amyloid precursor protein by presenilin-dependent gamma-secretase cleavage. ,,
They also showed that age of onset of PSEN1-linked familial Alzheimer disease correlated inversely with the ratio of A-beta-42/A-beta-40 and absolute levels of A-beta-42, but directly with A-beta-40 levels. Together, the data of Kumar-Singh et al. (2006) suggested that A-beta-40 may be protective by perhaps sequestering the more toxic A-beta-42 and facilitating its clearance.
|Mutations in PS1or PS2 change the cleavage activity of APP, resulting in increased Aβ42 production and/or high Aβ42/Aβ40 ratio.|
!!!__PS1 processing__
See ,,[[Three-amino acid spacing of presenilin endoproteolysis suggests a general stepwise cleavage of gamma-secretase-mediated intramembrane proteolysis.|https://www.ncbi.nlm.nih.gov/pubmed/20534834/]],,
PS is cleaved during complex assembly into its characteristic N- and C-terminal fragments. Both fragments are integral components of physiologically active gamma-secretase and harbor the two critical aspartyl residues of the active site domain. the precision of PS1 endoproteolysis is affected by PS1 mutations. Comparing the cleavage products generated by a variety of PS1 mutants revealed that specifically cleavages at positions 293 and 296 of PS1 are selectively affected. Systematic mutagenesis around the cleavage sites revealed a stepwise three amino acid spaced cleavage mechanism of PS endoproteolysis
!!!__Effect of PS1 mutations on $$\gamma$$-secretase disfunction ([[main paper|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/]])__
[[diagram and enzyme kinetics data|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/figure/f1/]]
tested FAD–PSEN1 mutations have no consistent inhibitory effect on the endoproteolytic cleavage of γ-secretase substrates, indicating that reduced release of intracellular domains and signalling cannot explain their AD-causing effects.
Low Aβ40 and Aβ38 levels and high, long Aβ levels (>Aβ42) are found in all the FAD-linked mutations tested, including the M139V, which does not affect the ɛ-efficiency. Interestingly, the M139V mutation affects the processing of APP only at the level of Aβ, indicating that endo- and carboxypeptidase-like activities of the γ-secretase can be dissociated.
|Our data imply that FAD–PSEN1 mutations cause AD by qualitative shifts in Aβ profiles and not by general loss of function of the enzyme complex|
,,Since high Aβ43 and Aβ42 (substrates in this cycle) accumulate in vitro or are released in vivo, we speculate that FAD–PSEN mutations promote a premature release of the Aβ43/Aβ42 peptides.,, [[Data plots|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364747/figure/f2/]]
__DR6 apoptosis pathway__
In addition to interactions with sAPPα and APP,
the large soluble sAPPβ fragment may be associated with apoptotic
signaling and axonal degeneration via the death receptor DR6 and
caspase6 [ 113 ], though the interactions of sAPPβ are not fully
characterized and require further detailed investigation.
__Other hypoethesis__
There are a variety of alternative hypothesis of how PSEN1 mutation can cause AD.
However, all tested FAD mutations affect the prime function of PSEN, which is proteolysis, so this affecting this pathway appears to be a necessary condition.
!!!__Amyloid cascade theory__
It has been suggested that increased toxic Aβ42 initiates a cascade of down-stream pathological processes such as tau hyperphosphorylation, neurofibrillary tangles (NFTs) formation, neuroinflammation, loss of synaptic junctions and neuronal cell death, with dementia being the ultimate clinical result of these progressive neurodegenerative processes.
Although the a myloid cascade is only one theory among myriads of other possible mechanisms for AD (e.g. tau, inflammatory or oxidative stress hypothesis) and amyloid alone is probably not sufficient to cause AD, the association of PS1/PS2/APP with amyloid synthesis and its processing warrants the amyloid cascade theory plays a more important role in EOFAD than the sporadic AD.
On the other hand, variable pathological expression reported in individuals carrying the same mutation suggests that epigenetic or other genetic factors may play a role in this phenotypic heterogeneity.
!!!__Oligomer cascade theory__
[[Amyloid β-protein oligomers and Alzheimer’s disease|http://alzres.biomedcentral.com/articles/10.1186/alzrt226]]
Aβ42 has been observed to reduce neuronal viability to a greater extent than Aβ40 [63]. Aβ42 thus seems to be most toxic, but both Aβ40 and Aβ42 form oligomers, and through distinct mechanisms [37].
!!__Systems biology__
AD is really a complex multi-faceted disease
[img[https://s15.postimg.org/yykkfwn2z/Selection_656.png]]
[img[https://s16.postimg.org/e32ytu7xx/Selection_657.png]]
[img[https://s15.postimg.org/m51pvv3gb/Selection_658.png]]
[img[https://s9.postimg.org/3wtva8tcv/Selection_659.png]]
The study of what the [[Mind]] does. Psychology often treats the brain as a "black box", and only concerns itself with its behaviour (behaviourism), or other descriptional or subjective matters (for e.g. introspectionism).
More recently, combining it with [[Neuroscience]] has allowed more mechanistic and complete theories. These convergence falls under the [[umbrella science|Systems science]] of [[Cognitive science]]
https://en.wikipedia.org/wiki/Overjustification_effect
[[Behavioural sciences - Springer|http://www.springer.com/gp/behavioral-sciences]]
Introspectionism
* Jung
Behaviourism. Objective [[Scientific experiment]]s. [[Operational definition]]
* Skinner
!!Psychological theories
[[Appraisal theory |https://www.wikiwand.com/en/Appraisal_theory]] -- emotions are extracted from our evaluations (appraisals or estimates) of events that cause specific reactions in different people.
https://en.wikipedia.org/wiki/Public_health
"the science and art of preventing disease, prolonging life and promoting health through organized efforts and informed choices of society, organizations, public and private, communities and individuals."
[[World health organization]]
The Punnett square is a diagram that is used to predict an outcome of a particular cross or breeding experiment. It is named after Reginald C. Punnett, who devised the approach. The diagram is used by biologists to determine the probability of an offspring having a particular genotype.
https://www.wikiwand.com/en/Punnett_square
A type of [[Neuron]]
http://www.scholarpedia.org/article/Pyramidal_neuron
__Libraries__
Graphics:
http://www.pythonware.com/products/pil/
https://pypi.python.org/pypi/colour/
Maths:
numpy
sympy
https://www.continuum.io/why-anaconda
Others:
http://blog.rtwilson.com/my-top-5-new-python-modules-of-2015/
https://pythonprogramming.net/
[[Video|https://www.youtube.com/watch?v=lxgobSNUbzI&list=PL0D746480FAEFA3C9&index=4]]
The study of chemical systems ([[Atom]]s, [[Molecule]]s), and chemical processes ([[Chemical reaction]]s), using the theory of [[Quantum mechanics]]
[[Oxford, Fabian Essler C6 physics notes|http://www-thphys.physics.ox.ac.uk/people/FabianEssler/C6web2012/lecturenotes2015.pdf]]
[[Advances in Graphene, Majorana fermions, Quantum computation|https://www.youtube.com/playlist?list=PL04QVxpjcnji3guKKKRZW9pqX0-V6QYmO]]
[[New questions in quantum field theory from condensed matter theory|https://www.youtube.com/playlist?list=PL04QVxpjcnji_tgiNNiWp8RhQ0XXJoCPb]]
!!Second quantization
__Ideal Fermi gas__
__Weakly interacting bose gas__
From Hamiltonian can derive [[Gross-Pitaevskii equation|https://en.wikipedia.org/wiki/Gross%E2%80%93Pitaevskii_equation]]
http://www.nii.ac.jp/qis/first-quantum/forStudents/lecture/pdf/qis385/QIS385_chap4.pdf
Bogoliubov approximation
Alternative using density matrix..
__Spin waves in ferromagnets__
!!Electrons in solids
!![[Quantum liquid]]s
!!!Superconductors, superfluids
!!Trapped ultra-cold gases
----------------------
[img[http://www.lassp.cornell.edu/sethna/Sloppy/SloppyFigs/Hierarchies/cond-matCropped.jpg]]
~LectureNotes
and link Gingkoapp tree here too.
[[https://www.maths.tcd.ie/~fionn/]]
[[Quantum algorithms review|http://www.nature.com/articles/npjqi201523?WT.mc_id=FBK_NPG_1602_npjQI]]
[[Quantum Computation and Quantum Information|http://www.amazon.com/Quantum-Computation-Information-10th-Anniversary/dp/1107002176]]
https://medium.com/@geoff.bradway/a-primer-on-quantum-computing-and-algorithms-d64033abfb52#.i4oihul75
[[Quantum machine learning]]
Strictly speaking, a ''quantum liquid'' is a spatially homogeneous system of strongly interacting particles at temperatures sufficiently low that the effects of [[quantum statistics|Quantum statistical physics]] are important.
In practice the term is used more broadly, to include those aspects of the behavoir of conduction electrons in metals and degenerate semiconductors which are not sensitive to the periodic nature of the ionic potential.
See also [[Quantum fluid|https://en.wikipedia.org/wiki/Quantum_fluid]] and [[Quantum spin liquid|https://en.wikipedia.org/wiki/Quantum_spin_liquid]]
[[An introduction to quantum machine learning|https://arxiv.org/abs/1409.3097]]
--> See [[Robert Littlejohn's notes|http://bohr.physics.berkeley.edu/classes/221/s16/221.html]].
[[Binney|http://www-thphys.physics.ox.ac.uk/people/JamesBinney/lectures.html]] -- [[videos|https://www.youtube.com/playlist?list=PLE73AA240E8655D16]]
[[Lectures by Balakrishnan|https://www.youtube.com/watch?v=TcmGYe39XG0&list=PL0F530F3BAF8C6FCC]]
[[Quantum field theory]]
[[Atomic physics]]
//Other techniques//
[[ Quantization of Constrained Systems|http://arxiv.org/abs/hep-th/0003297]]
[[ Enhanced Quantization: A Primer|http://arxiv.org/abs/1204.2870]]
[img[https://media.giphy.com/media/3o6ozFBVcK9lCTDG0w/giphy.gif]]
------------
https://en.wikipedia.org/wiki/Ramsauer%E2%80%93Townsend_effect
[[Philosophy of quantum mechanics]]
Based on the density matrix. Naturally extends the classical formalism of [[Statistical physics]]
Methods of approximately performing [[Newton's method]]. They most often involve approximating the [[Hessian]] in some way; for instance, by [[Finite element method]]
https://www.wikiwand.com/en/Quasi-Newton_method
__Second order/Newton/Quasinewton methods__
Conjugate gradient method
BGFS and L-GBFS
!!!BFGS
//note quenched disorder often refers to what we refer here as simply [[Disorder]]//.
[[Disorder]] of a system in which the disordered variable is out of equilibrium. For instance in glasses. This can be achieved by cooling sufficiently rapidly, so that a random configuration is //quenched//, and stays so, due to extremely large relaxation times.
[ext[https://en.wikipedia.org/wiki/Quenching_(fluorescence)]]
A [[Programming language]] for [[Statistics]]
https://www.r-project.org/
Good IDE: [[RStudio|https://www.rstudio.com/]]
R programs on the web!: [[Shiny|http://shiny.rstudio.com/]]
See lynda.com lectures
[[Evolving automata]]
[[Random deterministic automata]]
Random stochastic automata?
[[REGAL: a library to randomly and exhaustively generate automata|https://www.semanticscholar.org/paper/-A-Library-to-Randomly-and-Exhaustively-Generate-Bassino-David/6ac8c2f9b322971488840f86a85022e59ff49444/pdf]] http://regal.univ-mlv.fr/
[[Enumeration and random generation of possibly incomplete deterministic automata|http://puma.dimai.unifi.it/19_2_3/1.pdf]]
http://www.swmath.org/software/791
http://fado.dcc.fc.up.pt/
[[Enumeration and Generation of Initially Connected Deterministic Finite Automata |http://www.dcc.fc.up.pt/dcc/Pubs/TReports/TR06/dcc-2006-07.pdf]] (implemented in FAdo).
Random [[Boolean network]]
[[Matlab]] RBN toolbox: http://www.teuscher.ch/rbntoolbox/
[[http://turing.iimas.unam.mx/~cgg/rbn/]]
See [[Dynamical Instability in Boolean Networks as a percolation Problem]], [[Boolean network]]
[[Random Boolean networks: Analogy with percolation|http://www.tandfonline.com/doi/abs/10.1080/13642818708215325]]
Lattice sites can be divided into two groups: sites susceptible to damage, and sites stable against damage. If the initially flipped centre spin belongs to an infinite connected network of sites susceptible to damage, then the initially small damage will spread over the whole system.
A scaling theory for the Kauffman model, analogous to that for percolation, is presented in the Appendix.
From simulations it is observed that moving sites, i.e. those not having local period one, cluster together into groups of connected neighbours. These clusters are ramified, similar to those of percolation theory. Indeed, for p below p, one only has clusters of finite periods, whereas for p above p, we find, besides these finite clusters of finite periods, one infinite cluster of infinite period in addition.
In another set of simulations, the ratio of final to initial damage is interpreted by Derrida and Stauffer (1986) as a susceptibility, similar to the ratio of magnetization to magnetic field in ferromagnets. Indeed, simulations indicate that this quantity diverges if p approaches pc from below. The long-time limit of the damage for infinitesimal initial damages follows a typical second-order phase transition curve.
[img[http://i.imgur.com/7znNDvz.png]]
[img[http://i.imgur.com/q4voy0J.png]]
[img[http://i.imgur.com/hVDgjs8.png]]
of lattice sites; thus perhaps the nearest-neighbour square lattice is not the most realistic model of these biological aspects.
[[Random automata]], [[Deterministic finite automaton]]
[[Enumeration and Generation of Initially Connected Deterministic Finite Automata|http://www.dcc.fc.up.pt/dcc/Pubs/TReports/TR06/dcc-2006-07.pdf]] implemented in python FAdo library.
Initially connected means that, for each state q there exists a directed path from the distinguished start st ate to q . I think another name for an automaton or an state of one, with this property, is ''//accessible//''.
|[[Enumeration and random generation of accessible automata|http://www.sciencedirect.com/science/article/pii/S0304397507002861]] | [[Stirling numbers of the second kind|https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind]]|
[[Random Deterministic Automata|http://link.springer.com/chapter/10.1007%2F978-3-662-44522-8_2]]
Using [[Analytic combinatorics]]
//Functional graph// (see article) corresponding to a total map from $$[ n ]$$ (set $$\{1,2,3,...,n\}$$) to itself, consists of components, each a cycle of trees (a forest whose roots are connected by a cycle). Note that the nodes in the trees have edges pointing toward the root. This combinatoric structure emerges from the constraint that the out-degree is exactly $$1$$ for all nodes in the functional graph.
As an example of applying the //symbolic method//, and //singularity analysis// of analytic combinatorics, they find the asymptotic value of the average number of cyclic points (points (nodes) belonging to a cycle), which is $$\sqrt{\pi n/2}$$, $$n$$ being the number of points..
See definitions of //transition structure//, //automaton//, //accessible automaton//, etc in [[article|http://link.springer.com/chapter/10.1007%2F978-3-662-44522-8_2]].
One can also show that the expected number of points with $$0$$ in-degree (//garden-of-eden// points) is, asymptotically $$e^{-2} n$$. One can also show that with high probability a transition structure is not accessible.
We look at the set of $$n$$-node transition structures whose nodes have in-degree at least $$1$$, except, possibly the initial state (call the set $$T_n'$$). This set has asymptotically the same cardinality as the set of accessible transition structures, up to a multiplicative constant. It's easy to show that there is a bijection between this set and the set of all surjections between $$[kn+1]$$ and $$[n]$$. The number of this is, asymptotically,
$$S(nk+1, n) \sim \alpha_k \beta_k^n n^{kn+1}$$
where $$\alpha_k >0$$, and $$\beta_k \in (0,1)$$, are computable constants. Note that because $$\beta_k <1$$, this number is much smaller than $$n \cdot n^{k+1}$$, the total number of transitions structures. This agrees with the previous argument that accessible structures are sparse. Also note that $$\alpha_k \beta_k^n$$ is the probability that a random map between $$[kn+1]$$ and $$[n]$$ is a surjection. Good showed this (see ref in article).
See more remarks in article.
A more relevant question may be the number of isomorphic classes of accessible automata; however, symmetries (just like in Feynman diagrams), make the counting difficult. However, for accessible automata, the counting is simplified, due to a certain bijection, and the number of elements per isomorphic class is $$n!$$.
More [[References on random deterministic automata]]
[[On the Probability of Being Synchronizable|http://link.springer.com/chapter/10.1007/978-3-319-29221-2_7]]
[[An algorithm for road coloring|http://www.sciencedirect.com/science/article/pii/S1570866712001001]]
__Graph structure of random automata__
[[Diameter and Stationary Distribution of Random r-out Digraphs|http://arxiv.org/abs/1504.06840]]
[[The graph structure of a deterministic automaton chosen at random |http://arxiv.org/pdf/1504.06238v1.pdf]] -- [[slides|http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.727.2535&rep=rep1&type=pdf]]
[[The size of the largest strongly connected component of a random digraph with a given degree sequence|https://www.math.cmu.edu/~af1p/Texfiles/dirgiant.pdf]]
<mark> What about the giant out-component?</mark> They don't talk about it !?
See [[Decision tree]]
[[(ML 2.8) Random forests|https://www.youtube.com/watch?v=o7iDkcpOr_g&list=PLD0F06AA0D2E8FFBA&index=14]]
[[Graph|Graph theory]]s with [[probabilistic|Probability theory]] properties
__Erdős–Rényi model__
The most common random graph model is the Erdős–Rényi model. Random connections among a given set of nodes.
See [[the chapter of the book|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/Networks/%5BMark_Newman%5D_Networks_An_Introduction(BookZZ.org)%20(randgraph).pdf]].
__Configuration model__
[[http://tuvalu.santafe.edu/~aaronc/courses/5352/fall2013/csci5352_2013_L11.pdf]]
Random graph with given degree distribution
See [[this chapter|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/Networks/%5BMark_Newman%5D_Networks_An_Introduction%20(randgraph-gen-deg).pdf]]
.... See Newman's book on [[Networks|Network science]]
[[Probability on Graphs |http://www.statslab.cam.ac.uk/~grg/books/USpgs-rev3.pdf]]
[[Random Graphs, Geometry and Asymptotic Structure|https://books.google.co.uk/books?id=4rcjDAAAQBAJ&printsec=frontcover&dq=asymptotic&hl=en&sa=X&redir_esc=y#v=onepage&q=asymptotic&f=false]]
https://www.youtube.com/watch?v=pylTEAyUQiM
[[THE PHASE TRANSITION IN INHOMOGENEOUS RANDOM GRAPHS|https://arxiv.org/pdf/math/0504589v3.pdf]]
[[Random Graphs and Complex Networks. Vol. II|http://www.win.tue.nl/~rhofstad/NotesRGCNII.pdf]]
!!__Configuration model__
__Sample calculations__
Average number of edges between two nodes is
$$\frac{k_i k_j}{2m-1} \approx \frac{k_i k_j}{2m}$$
in the limit of large size. This is approximately equal to the //probability of an edge// between the two nodes in the limit of large size too.
__Excess degree distribution__
__Generating functions for the small components__
See derivation in problem sheet or notes or book, using generating functions (in particular it's "power" property where the g.f. of a sum of independent random variables is the product of g.f.s of these rand. vars.)
__Giant component__
Can find expression for size of ''giant component''.
One can then derive condition for existence of giant component in the configuration model. It is called the ''Malloy-Reed condition'':
$$\langle k^2 \rangle -2\langle k \rangle > 0 \Leftrightarrow \exists \text{ GCC}$$
GCC = giant connected component.
!!!__Random graphs with clustering__
__Degree-triangle model__
Variant, that has tunable clustering coefficient.
See [[here|https://people.maths.ox.ac.uk/porterm/research/otmani_dissertation_final.pdf]] and [[here|http://www.uvm.edu/~pdodds/files/papers/others/2010/newman2010a.pdf]]
//aka random map model, or random mapping//
For each point in phase space, one chooses at random another point in phase space as being its successor in time, i.e. we have a random [[map|Function]], $$T$$, from a finite [[Set]] of $$M$$ points, to itself. It can be shown to be a limiting case of a Kauffman [[Random Boolean network]], with in-degree $$K \rightarrow \infty$$.
To each attractor (labelled by $$s$$), we assign a weight $$W_s$$ corresponding to the fraction of points in its basin of attraction.
See also [[Analytic combinatorics]]
!!__Statistics of attractors__
!!!__Probability distribution of size of basin of attraction__
__Joint probability distribution of two attractor weights__
!!!__Probability distribution of $$Y=\sum\limits_s W_s^2$$__
!!!__Probability that a random map of $$M$$ points is indecomposable (i.e. map has a single attractor)__
$$Q_M = \frac{(M-1)!)}{M^M} \sum\limits_{n=0}^{M-1} \frac{M^n}{n!} \sim \sqrt{\frac{\pi}{2M}}$$
$$\sim$$ is for large $$M$$
Probability that the map is indecomposable and the attractor is of period $$l$$:
$$Q_M(l) = \frac{M!}{(M-l)!M^{l+1}}$$
!!!__Probability distribution of number of attractors__
See [[ Probability Distributions Related to Random Mappings |http://www.jstor.org/stable/2237803?seq=1#page_scan_tab_contents]], [[A Property of Randomness of an Arithmetical Functions|http://digital.library.unt.edu/ark:/67531/metadc100934/]]
The average number of attractors is $$\langle A \rangle = \frac{1}{2} \log{M} + O(1)$$
!!__Probabilities related to a point chosen at random__
Probability that a randomly chosen point falls into an attractor of weight $$W$$ and period $$l$$
__Probability that a randomly chosen point ends up on an attractor of weight $$l$$__:
$$P(l) = \sum\limits_{n \geq l} \frac{\Gamma{(M)}}{\Gamma{(M-n+1)}} \frac{1}{M^n}$$
For large $$M$$, this gives
$$P(l) = \frac{1}{\sqrt{M}} \int_x^\infty e^{-y^2/2} dy $$
where $$l = \sqrt{M} x$$. This gives the average $$\langle l \rangle = \sqrt{M} \sqrt{\frac{\pi}{8}}$$, and variance $$\langle l^2 \rangle - \langle l \rangle^2 = M \left ( \frac{2}{3} - \frac{\pi}{8} \right )$$
!!__Random mappings with constraints, and other extensions__
In [[ Probability Distributions Related to Random Mappings |http://www.jstor.org/stable/2237803?seq=1#page_scan_tab_contents]], some of the above results are extended to the case without self-1-loops, $$T(i) \neq i$$, and where the function is [[one-to-one|Injective function]]
------------------------
[[The random map model: a disordered model with deterministic dynamics|http://jphys.journaldephysique.org/articles/jphys/abs/1987/06/jphys_1987__48_6_971_0/jphys_1987__48_6_971_0.html]]
[[ Probability Distributions Related to Random Mappings |http://www.jstor.org/stable/2237803?seq=1#page_scan_tab_contents]]
[[A Property of Randomness of an Arithmetical Functions|http://digital.library.unt.edu/ark:/67531/metadc100934/]]
[[ The Expected Number of Components Under a Random Mapping Function |http://www.jstor.org/stable/2307900?seq=1#page_scan_tab_contents]]
[[ Probability of Indecomposability of a Random Mapping Function |http://www.jstor.org/stable/2236478?seq=1#page_scan_tab_contents]]
[[Probability Distributions Related to Random Transformations of a Finite Set|https://statistics.stanford.edu/research/probability-distributions-related-random-transformations-finite-set]]
[[Weighted Random Mappings; Properties and Applications.|https://www.researchgate.net/publication/277842846_Weighted_Random_Mappings_Properties_and_Applications]]
[[Some remarks about computer studies of dynamical systems|http://www.sciencedirect.com/science/article/pii/037596018290408X]]
[[Random-Energy Model: Limit of a Family of Disordered Models|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.45.79]]
-- [[Random-energy model: An exactly solvable model of disordered systems|http://journals.aps.org/prb/abstract/10.1103/PhysRevB.24.2613]]
[[Random mappings|https://books.google.co.uk/books/about/Random_mappings.html?id=1xPvAAAAMAAJ&redir_esc=y]]
[[Random allocations|https://books.google.co.uk/books?id=jxjvAAAAMAAJ&source=gbs_similarbooks]]
[[Random Forests|https://books.google.co.uk/books?id=wMTUThd-6QEC&source=gbs_similarbooks]]
See [[Random matrix theory]], [[Disordered system]], [[Simplicity bias in finite state transducers]], [[Finite state channel]]
[[Products of Random Matrices|http://link.springer.com/book/10.1007%2F978-3-642-84942-8]] in [[Statistical physics]]
[[Random matrix products and measures on projective spaces|http://link.springer.com/article/10.1007/BF02760620]] [[pdf|https://www.semanticscholar.org/paper/Basic-Properties-of-the-Projective-Product-with-Gland-Mevel/cc2248c4e882d8d8b7bfad219811cd0aa3e17137/pdf]]
[[Capacity of Finite State Channels Based on Lyapunov Exponents of Random Matrices|http://sci-hub.cc/10.1109/TIT.2006.878230]]
[[Spectral properties of products of random matrices: theoretical results and data correlation analysis |http://inspirehep.net/record/1253159/files/1146.pdf]]
[[Google search|https://www.google.co.uk/search?q=products+of+random+matrices+in+statistical+physics&oq=products+of+random+matrices&aqs=chrome.1.69i57j0l5.5639j0j1&sourceid=chrome&ie=UTF-8]]
Mellin transform of RMPs
[[Topics in Products of Random Matrices |http://www.gbv.de/dms/goettingen/326326073.pdf]]
[[Properties of the columns in the infinite products of nonnegative matrices|https://hal.archives-ouvertes.fr/hal-00411404/]]
[[Supersymmetric approach to random band matrices - Tatyana Shcherbyna|https://www.youtube.com/watch?v=ILig5m527CM]]
[[NCTS Scholar Lectures: Mini Course on Random Matrices (I)|https://www.youtube.com/watch?v=t4l8APmvg1Y]]
[[How Large is the Norm of a Random Matrix?|https://www.youtube.com/watch?v=oM2ZRHlE4Uo]]
[[Discrete Random Matrices -- 2009 Moursund Lectures, Day 3|https://www.youtube.com/watch?v=nXNvaTFhX1c]]
[[Top Eigenvalue of a Random Matrix: A tale of tails - Satya Majumdar|https://www.youtube.com/watch?v=P2xErdgtFzo]]
[[Random_matrices,_random_processes|file:///home/guillefix/downloads/[Harnad_J._(ed.)]_Random_matrices,_random_processe(BookZZ.org).pdf]]
https://terrytao.wordpress.com/category/teaching/254a-random-matrices/
[[Properties of networks with partially structured and partially random connectivity|http://arxiv.org/abs/1311.4672#]]
[[Topics in random matrix theory |https://terrytao.files.wordpress.com/2011/08/matrix-book.pdf]]
A ''random walk'' is a path across a network created by taking repeated random steps. They are usually allowed to traverse edges more than once, and visit vertices more than once. If note it is a //self-avoiding random walk//.
We consider a random walk where at each vertex one will take a step (i.e. walker does not stay in vertex) along each of the edges connected to it, with uniform probability, i.e. with probability $$\frac{1}{k_i}$$, where $$k_i$$ is the [[degree|Degree of a vertex (Graph theory)]]. Thus, on an undirected network we have:
$$p_i(t)=\sum\frac{A_{ij}}{k_j}p_j(t-1)$$
or $$\mathbf{p}(t)=\mathbf{A}\mathbf{D}^{-1}\mathbf{p}(t-1)$$
Where $$p_i(t)$$ is the probability that the walker is at vertex $$i$$ at (discrete) time $$t$$, and where $$\mathbf{D}=diag(k_1,...,k_n)$$. One can also write this relation in terms of the //reduced adjacency matrix//, $$\mathbf{D}^{-1/2}\mathbf{A}\mathbf{D}^{-1/2}$$, and that can be useful sometimes.
We are interested in the limit as $$t \rightarrow \infty$$ where we expect the probability to approach a steady state $$\mathbf{p}(\infty) \equiv \mathbf{p}$$:
$$\mathbf{p}=\mathbf{A}\mathbf{D}^{-1}\mathbf{p}$$, which can be rewritten as $$\mathbf{L}\mathbf{D}^{-1}\mathbf{p}=0$$, so $$\mathbf{D}^{-1}\mathbf{p}$$ is an eigenvector of the [[Graph laplacian]] ($$\mathbf{L}$$) with eigenvalue $$0$$, but we known (see [[Graph laplacian]]) that in a connected network only the vector $$\mathbf{1}=(1,1,1,...)$$ has eigenvalue $$0$$. Therefore $$p \propto k_i$$, so normalizing $$p = \frac{k_i}{\sum_i k_i}=\frac{k_i}{2m}$$ (see [[Degree of a vertex (Graph theory)]])
With a random walk, an interesting question is that of the __mean first passage time__, or the mean number of steps before reaching a certain node, when starting from a given node. To find this we consider an //absorbing random walk//, where a walk that arrives at a certain set of vertices (we will consider just one, call it $$v$$) will stay there.
We can then consider the probability $$p_v(t)$$ of being at vertex $$v$$ at time $$t$$. This is the same as the probability that the first passage time is equal to or less than $$t$$, and thus the probability that it is exactly $$t$$ is $$p_v(t)-p_v(t-1)$$, and the mean first passage time is:
$$\tau =\sum_t^\infty t[p_v(t)-p_v(t-1)]$$
Note that we can't rearrange terms in this sum, because it is not absolutely convergent!
Following the manipulations shown in Newman's book (section 6.14), we get to:
$$\tau = \mathbf{1} \cdot \mathbf{D'}\mathbf{L'}^{-1} \cdot \mathbf{p'}(0)$$
where the prime $$'$$ indicates that the $$v$$th element, or the $$v$$th row and columns have been removed. In particular $$\mathbf{L'}$$ is called the //$$v$$th reduced Laplacian//. This can be re-expressed a bit further, following Newman's book, for computational convenience.
__Resistor networks__
Kirkoff's current law can be written as:
$$\sum_j A_{ij} \frac{V_j-V_i}{R} +I_i=0$$
where $$I_i$$ is an external current applied at some node in the network. This can be written in terms of the [[Graph laplacian]] as:
$$\mathbf{L}\mathbf{V}=R\mathbf{I}$$ $$\quad$$ ($$\dagger$$)
where $$\mathbf{V}$$ is the vector of voltages. $$\mathbf{L}$$ is not invertible, but this cooresponds to the arbitrariness in the value of voltages $$V_i$$, which can be all shifted up and down and still satisfy the equation. This is equivalent to adding a multiple of the $$\mathbf{1}$$ vector, which we know to have a $$0$$ eigenvalue of the [[Graph laplacian]]. However, if we fix the voltage at some node (to be $$0$$ say), then we can remove the corresponding columns and rows from the equation ($$\dagger$$), and the $$0$$ eigenvalue is removed, and the reduced Laplacian is now invertible, so we can get the voltages, and thus the currents!
!!!__Some applications__
Random walk sampling method for social networks
Random walk betweenness measure.
See [[Random walk in a graph]]
[[Random Walks on Directed Graphs|https://www.youtube.com/watch?v=w0HZX22i0mQ]]
[[Random Walk on Random Directed Graphs|https://www.youtube.com/watch?v=LtbldFJSWwQ]]
[[PageRank and Random Walks on Directed Graphs |http://www.cs.yale.edu/homes/spielman/462/2010/lect16-10.pdf]]
A family of [[probabilistic|Probability theory]] models invented by Fortuin and Kasteleyn which include [[Percolation]], and the [[Ising|Ising model]] and Potts models as special cases.
The configuration space of the random-cluster model is the set of all subsets of the edge-set $$E$$, which we represent as the set $$\Omega={0,1}^E$$. The model may be viewed asa parametric family of probability measures $$\phi_{p,q}$$ on $$\Omega$$. When $$q=1$$, we recover bond [[Percolation]], when $$q=2$$, we have the [[Ising model]], and when $$q=2,3,4,...$$ we have different versions of the [[Potts model]].
It turns out that long-range order in a Potts model corresponds to theexistence of infinite clusters in the corresponding random-cluster model. In this sense the Potts and percolation phase transitions are counterparts of one another.
Reference: [[Grimmet - The Random-Cluster Model|http://www.statslab.cam.ac.uk/~grg/books/rcm1-1.pdf]]
[[Probability theory]]
[[Information theory]]
[[Order]]
[[Randomness deficit]]
[[Complexity]]. [[Kolmogorov complexity]] gives a notion of randomness (a string being random if its Kolmogorov complexity is about as large as its length). Martin-Lof (Mar 66) developed a definition of randomness somewhat different from Kolmogorov's, using "randomness tests". [[Paper|https://www.google.es/url?sa=t&source=web&rct=j&url=http://www.sciencedirect.com/science/article/pii/S0019995866800189&ved=0ahUKEwif37CD0tjOAhWEORoKHaw_CnEQFggnMAI&usg=AFQjCNFHyvOupsVY-lioMpsgJpOoZKOL-A]]
Almost all images are indistinguishable from random noise, and almost all data sets and functions are in-distinguishable from completely random ones. This fol-lows from Borel's theorem on normal numbers ([[Les probabilités dénombrables et leurs applications arithmétiques|http://link.springer.com/article/10.1007%2FBF03019651?LI=true]]), which states that almost all real numbers have a string of decimals that would pass any randomness test,i.e., are indistinguishable from random noise.
The property of a [[distribution|Probability distribution]] of [[Kolmogorov complexities|Kolmogorov complexity]] with an overrepresentation of low-complexity strings, relative to the expected distribution of complexities for a set of string chosen uniformly at random (with fixed length, and alphabet).
When referring to a [[Property]] of a [[Set]] of [[strings|String (Computer science)]], the distribution refers to the frequency distribution in the set.
A measure of randomness deficit is given by
$$\frac{P_0(\langle K \rangle_s)}{P_0(\langle K \rangle_0)}$$
where $$P_0$$ is the expected distribution of complexities for the uniformly random set of strings, $$\langle K \rangle_s$$ is the mean complexity of the set, and $$\langle K \rangle_0$$ is the mean complexity for the uniformly random set.
Averaged version of a [[Master equation]]. Used, for instance in [[Chemical kinetics]], and in [[Epidemiology]].
__Proof that square root of two is irrational__
Imagine the Pythagorean squares associated with the sides of a right-angle triangle with equal leg sizes. By the Pythagorean theorem, the square corresponding to the hypotenuse has the same area as the sum of the squares of the legs.
Now if the ratio was a rational number, then one could choose a size for squares such that an integer number of them fitted on the sides of the triangles, and similarly the squares could be partitioned into these unit squares.
This means that the number of unit squares in the big square equals the sum of the number of unit squares in the squares of the legs, but as these are equal, this is just twice the number of unit squares from one leg. Therefore the number of unit squares in the big square must be even.
If the number of unit squares is even, cutting the square in half perpendicular to a side should give an integer number of squares. If the number of unit squares in a side wasn't even, cutting by a half would cut unit squares by a half. And there would be as many of these half unit squares in each half as there are unit squares in a side of the square. As the number in each half must be integer, this number must be even, which is a contradiction. Therefore, the number of unit squares in a side is even.
On the other hand, if we begun choosing the minimum ratio between the sides, this means that the number of unit squares in a leg is not even, for it were we could just halve the number of squares in both.
Now considering cutting the initial right-hand triangle in half parallel to the hypotenuse. As the number of unit squares in the hypotenuse was shown to be even, the number of unit squares in the half-hypotenuse is an integer. Now the triangle formed by this segment and the leg of the original triangle is geometrically similar to the original triangle, and their sides are partitioned into integers. However, the leg, which acts as the hypotenuse of the new triangle, doesn't have an even integer number of unit squares, while we just showed that it should.
Therefore, the initial assumption that there was such an integer ratio must be wrong.
https://en.wikipedia.org/wiki/Primary_sector_of_the_economy
[[Raw materials: sustainable exploration, extraction, processing, recycling and substitution.|http://www.eurosfaire.prd.fr/7pc/documents/1354716618_karas_rawmaterials.pdf]]
[img[http://www.idsia.ch/~juergen/ray2.jpg]]
[[http://people.idsia.ch/~juergen/ray.html]]
[[https://en.wikipedia.org/wiki/Ray_Solomonoff]]
Ray Solomonoff (1926-2009), pioneer of [[Machine learning]], founder of [[Algorithmic Probability theory|Algorithmic information theory]], father of the Universal Probability Distribution, creator of the Universal Theory of Inductive Inference. First to describe the fundamental concept of Algorithmic Information or [[Kolmogorov Complexity|Algorithmic information theory]]. In the new millennium his work became the foundation of the first mathematical theory of Optimal Universal Artificial Intelligence.
https://www.wikiwand.com/en/Reactivity_series
http://www.bbc.co.uk/education/guides/zqjsgk7/revision
The reactivity series allows us to predict how metals will react. A more reactive metal will displace a less reactive metal from a compound.
[img[http://a.files.bbci.co.uk/bam/live/content/zg2v9j6/small]]
!!__[[Displacement reaction|Single replacement reaction]]s of metal oxides__
http://www.bbc.co.uk/education/guides/zqjsgk7/revision/2
A more reactive metal will displace a less reactive metal from a compound.
The [[Thermite reaction]] is a good example of this. It is used to produce white hot molten (liquid) iron for [[Welding]]
!!__Displacement reactions of solutions__
A more reactive metal will displace a less reactive metal from a solution of one of its salts.
A framework for [[Frontend web development]]
[[meteor + react|https://www.youtube.com/watch?v=rxR-NWCXKiY&list=PLZqiqJ6M54_hojR8RG4gRIobIZFX0cQve&index=8]]
[[react basics|https://egghead.io/lessons/react-owner-ownee-relationship]]
[[JSX|https://egghead.io/lessons/precompile-jsx]]
A very good library for a functional way of handling application state: [[Redux]]
!!__Components__
-> Class component. Can have state.
-> Stateless function component. Doesnt have state
!!!__Component properties (props)__
Values and methods passed to a component when we use it (like arguments)
[[vid|https://egghead.io/lessons/react-introduction-to-properties]]
proptypes, default properties
!!!__States__
values and methods managed by the component itself.
[[vid|https://egghead.io/lessons/react-state-basics]]
!!!__References (refs)__
way of referencing an instance of a component from within a react app. It's like a DOM id of a component, that you can use to refer to that component.
[[vid|https://egghead.io/lessons/react-using-refs-to-access-components]]
!!!__Component lifecycle__
Adding or removing components to the dom is called mounting and unmounting. [[vid|https://egghead.io/lessons/react-component-lifecycle-mounting-basics]]
[[updating|https://egghead.io/lessons/react-component-lifecycle-updating]]. Even if we use ``shouldComponentUpdate`` to stop the component from rerendering, the state and props are still updated.
!!!__Higher order components__
[[vid|https://egghead.io/lessons/react-react-fundamentals-higher-order-components-replaces-mixins]]
----------------
http://andrewhfarmer.com/component-communication/
A [[Renormalization group]] scheme based on coarse-graining and rescaling over real space.
__Real-space renormalization group and percolation__
See [[Critical phenomena in percolation]]
[img[http://i.imgur.com/p2oq6ZZ.png]]
[[Renormalization Group Theory - Percolation|https://www.youtube.com/watch?v=ihymiZ4zhug]]. In particular, see [[here|https://www.youtube.com/watch?v=ihymiZ4zhug#t=5m41.5s]].
[[A real-space renormalization group for site and bond percolation|http://iopscience.iop.org/article/10.1088/0022-3719/10/8/002/pdf]]
Real-time PCR monitors the amplification of a targeted DNA molecule during the PCR process, i.e. in real-time, and not at its end, as in conventional PCR.
https://en.wikipedia.org/wiki/Real-time_polymerase_chain_reaction
[[Two common methods for the detection of PCR products in real-time PCR|https://www.youtube.com/watch?v=edJEY5g4X8k#t=7m]], all based on [[Fluorophore]]s, are:
#non-specific fluorescent dyes that intercalate with any double-stranded DNA, and
#sequence-specific DNA probes consisting of oligonucleotides that are labelled with a fluorescent reporter which permits detection only after hybridization of the probe with its complementary sequence.
#''SYBR Green''
## ''TaqMan probe''. These fluorescent reporters are non-fluorescent on the solution, but once they bind to the DNA, and Taq polymerase reaches them, the fluorescent group separates from the [[quenching|Quenching (Fluorescence)]] group and becomes fluorescent.
## ''Molecular beacon''
!!!__Primers__
primer design programs have been developed for the production of amplicons with minimal potential for cross-hybridization ([[src|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC291882/]])
!!!__Probes__
__SYBR Green__
[img[http://www.sigmaaldrich.com/content/dam/sigma-aldrich/articles/protocols/biology/qpcr-technology.jpg]]
__TaqMan probe__
Most common
[img[https://upload.wikimedia.org/wikipedia/commons/1/1d/TaqMan_Probes.jpg]] Functioning of the TaqMan probe sequence-specific fluorophore
[img[TaqMan_probe.png]]
The advantage of this is that even if the probe binds to an incorrect strand, you also need the polymerase to break it, which requires the primer, which is also specific. This significantly reduces the probability of error over molecular beacons, for instance!
__Molecular beacon__
[img[http://www.sigmaaldrich.com/content/dam/sigma-aldrich/life-science/custom-dna-probes/molecular-beacons.jpg]]
!!!__Apparatus__
The fluorescence is measured with an [[Spectrofluorometer]]
[[vid|https://www.youtube.com/watch?v=edJEY5g4X8k#t=5m]]
!!!__Quantitative PCR (qPCR)__
Application of real-time PCR to measure the initial concentration of the DNA sequence that are being amplified. As this is what's almost always done real-time PCR and qPCR are often used interchangeably.
qPCR has sensitivity that is five orders of magnitude higher than blotting techniques!
!!__Applications__
Real-Time PCR—also called quantitative polymerase chain reaction (qPCR)—is one of the most powerful and sensitive gene analysis techniques available and is used for a broad range of applications including
* [[Genotyping]]
** genetic variation of inter and intra organisms
** [[Single-nucleotide polymorphism]] analysis / mutation analysis. See [[here|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2224295/]] and [[here|http://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-015-1121-7]]. In order to distinguish the DNA of different lineages, hybridization probes were designed to recognize unique SNPs that are specific to particular lineages/sublineages.
** ''pathogen detection''. [[PDF|http://home.appliedbiosystems.com/about/presskit/pdfs/pathogen_detection.pdf]]. PCR assays that discriminate between microorganisms based on a signal from specific nucleic acid sequences, for instance by SNP genotyping.
** automated diagnosis of food-borne pathogens throughout the food chain
* Diagnosing diseases like HIV, CF, [[Sickle cell anemia]], Thalassemia, Phenyl ketonuria, etc.
** HIV. Proviral human immunodeficiency virus type 1 (HIV-1) DNA could be a useful marker for exploring viral reservoirs and monitoring antiretroviral treatment, particularly when HIV-1 RNA is undetectable in plasma. [[Article|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC87929/]]
** [[Other|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC153887/]]
__[[Real-time RT PCR]]__
* quantitative gene expression analysis. When studying gene expression with real-time polymerase chain reaction (PCR), scientists usually investigate changes – increases or decreases – in the expression of a particular gene or set of genes by measuring the abundance of the gene-specific transcript. The investigation monitors the response of a gene to treatment with a compound or drug of interest, under a defined set of conditions.
** drug target validation/ drug response analysis. See [[here|https://www.thermofisher.com/uk/en/home/life-science/pcr/real-time-pcr/qpcr-education/what-can-you-do-with-qpcr/introduction-to-gene-expression.html]]
* measuring [[RNA interference]]. See [[Reverse transcription PCR]], and [[here|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2850347/]]
** drug target validation/ drug response analysis. See [[here|https://www.researchgate.net/publication/232732069_Quantitative_Realtime_Polymerase_Chain_Reaction_in_Cancer_Drug_Target_Identification_and_Validation]].
The PCR based detection technologies utilizing species- specific primers are proving indispensable as research tools. The RT PCR allows quantitative genotyping and detection of single nucleotide polymorphisms and allelic discrimination as well as genetic variation.
[[Real-Time PCR: Revolutionizing Detection and Expression Analysis of Genes|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2430684/]]
Frequently, real-time polymerase chain reaction is combined with reverse transcription to quantify messenger RNA (mRNA) and microRNA (miRNA) in cells or tissues. This is then called [[Real-time RT PCR]]
See more [[here|https://www.thermofisher.com/uk/en/home/life-science/pcr/real-time-pcr/qpcr-education/qpcr-vs-digital-pcr-vs-traditional-pcr.html]] and [[here|https://www.youtube.com/watch?v=edJEY5g4X8k#t=3m34s]]
* Quantification of mRNA, and thus [[Gene expression]] (research and gene therapy diagnostics)
* Gene therapy distribution and expression assays
* Cell bank copy number analysis
* Expression system development
* Residual RNA analysis
* GMO analysis
* human and veterinary diagnostics
* blood products quality control
----------------
[[Real time vs traditional PCR|http://www.gene-quantification.de/abi-rtpcr-pcr.pdf]] In traditional [[PCR|Polymerase chain reaction]], [[Agarose gel|Agarose gel electrophoresis]] results are obtained from the end point of the reaction, which, I think, is made up of [[DNA double strand]]s
------------------
[[video|https://www.youtube.com/watch?v=edJEY5g4X8k]]
A combination of [[Real-time PCR]] with [[Reverse transcription PCR]]
https://www.ncbi.nlm.nih.gov/probe/docs/techqpcr/
!!__Basic RNNs__
''[[Recurrent neural nets|https://www.youtube.com/watch?v=56TYLaQN4N8&index=12&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw#t=7m48s]]''. Vanishing gradient problem, naively, RNNs don't give you long term memory.. so you have [[Long short-term memory]] networks
[[Recurrent neural networks -- Schmidhuber|https://www.youtube.com/watch?v=mF5-tr7qAF4#t=21m25s]]
[[Recurrent Neural Network Writes Music and Shakespeare Novels - Two Minute Papers|https://www.youtube.com/watch?v=Jkkjy7dVdaY]]
!!!__The vanishing gradients problem__
[ext[Hochreiter1991|http://people.idsia.ch/~juergen/SeppHochreiter1991ThesisAdvisorSchmidhuber.pdf]] -- [ext[Bengio1994|http://www-dsi.ing.unifi.it/~paolo/ps/tnn-94-gradient.pdf]]
!!__[[Long short-term memory]]__
Proposed to solve the vanishing gradients problem
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
See also [[Neural networks with memory]], [[Deep learning]]
!!__Gated recurrent unit__
A variation of the [[Long short-term memory]] network
!!__More [[Augmented RNN]]s__
Recursion refers to when a data structure contains simpler versions of itself within it. One can move up and down the //stack// of levels, by //popping//, or //pushing//, respectively.
An example of such a recursive stack is the [[Call stack]]
__Recursion in [[Music]]__
[[Bach - LITTLE HARMONIC LABYRINTH - BWV 591|https://www.youtube.com/watch?v=aBZgmITlOHE]]
__Recursion in [[Language]]__
* [[Formal language]]
Recursive transition networks, or [[Railroad diagram]]s are use to express [[Context-free grammar]]s.
Recursions can give rise to things that are defined in terms of themselves, but still not being paradoxical! The reason they avoid self-reference, is because there should be a part of the definition which avoids self-reference. This is the terminating condition in standard recursive functions.
Recursion can also be //indirect// when two or more functions call each other, in a loop. [[Heterarchy]]
[[Combinatorial structure]]s are often analyzed using recursive definitions in [[Analytic combinatorics]].
bounded, and free loops.
Augmented transition networks.
''Reduction-oxidation reaction''
*Oxidation is gain of oxygen.
*Reduction is loss of oxygen.
https://www.wikiwand.com/en/Redox
http://www.chemguide.co.uk/inorganic/redox/definitions.html
[[Oxidation state|https://www.wikiwand.com/en/Oxidation_state]]. http://chem.libretexts.org/Core/Analytical_Chemistry/Electrochemistry/Redox_Chemistry/Oxidation-Reduction_Reactions
An example are [[Halogen]] displacement reactions.
Redox reactions are analyzed well using //ionic equations//
[[Oxygen and oxides|http://www.bbc.co.uk/education/guides/zjwnb9q/revision]]
[[Rusting]]
-------------------
Old definitions still used in [[Organic chemistry]]
*Oxidation is loss of hydrogen.
*Reduction is gain of hydrogen.
A very good [[ReactJS]] library for a functional way of handling application state
[[Learn Redux|https://www.youtube.com/playlist?list=PLu8EoSxDXHP5uyzEWxdlr9WQTJJIzr6jy]] [[website|https://learnredux.com/]]
[img width=200 class=img-centered [https://raw.githubusercontent.com/reactjs/redux/master/logo/logo.png]]
[img[https://css-tricks.com/wp-content/uploads/2016/03/redux-article-3-03.svg]]
[img[https://blog.penjee.com/wp-content/uploads/2015/02/pass-by-reference-vs-pass-by-value-animation.gif]]
References are nothing but constant pointers in [[C/C++]]
See [[Percolation]]
Section on percolations on Mason and Gleeson's book on Dynamical processes on networks, and on Newman's networks book. In particular, see Newman's book chapters 12, 13, and 17, for detailed calculations of GCC sizes, and other ones. Note that the standard calculation determines whether a GCC exists for an infinite network (for instance, the locally tree-like assumption is valid for infinite networks, and other parts of his calculations assume infintie size). Finite size effects should be interesting to explore.
[[Recent advances in percolation theory and its applications|http://www.sciencedirect.com/science/article/pii/S0370157315002008]]
[[ Percolation Exercises|http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/ComputerExercises/Percolation/Percolation.html]]
[[Percolation Theory notes|http://www.mit.edu/~levitov/8.334/notes/percol_notes.pdf]]
See Complex systems LectureNotes.
[[Percolation slides|http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/ComputerExercises/Percolation/PercolationLecture.pdf]]
[[Scanned Notes on Percolation|http://www0.maths.ox.ac.uk/system/files/coursematerial/2015/3217/12/percolation-scanned-notes.pdf]]
[[Percolation, Second Edition by Geoffrey Grimmett |http://www.statslab.cam.ac.uk/~grg/papers/perc/perc.html]]
See [[Random deterministic automata]]
-------
[[ON THE NUMBER OF DISTINCT LANGUAGES ACCEPTED BY FINITE AUTOMATA WITH n STATES|http://www.cs.umanitoba.ca/~mdomarat/pubs/enum_jalc.pdf]]
[[E FL |http://www.cs.umanitoba.ca/~mdomarat/pubs/efl.pdf]]
[[EnumerationofAutomata,Languages,and Regular Expressions |https://cs.uwaterloo.ca/~shallit/Talks/autom3.pdf]]
[[The state complexity of random DFAs|http://arxiv.org/abs/1307.0720]]
[[On the average state and transition complexity of finite languages|http://www.sciencedirect.com/science/article/pii/S0304397507005609]]
[[REGAL: A Library to Randomly and Exhaustively Generate Automata|http://link.springer.com/chapter/10.1007/978-3-540-76336-9_28]] in C++ !
[[Distribution of the number of accessible states in a random deterministic automaton|https://hal-upec-upem.archives-ouvertes.fr/hal-00678213/]]
[[Enumerating Finitary Processes|http://arxiv.org/abs/1011.0036]]
[[Sampling different kinds of acyclic automata using Markov chains|http://www.sciencedirect.com/science/article/pii/S0304397512003805]]
[[Random walk on sparse random digraphs|http://arxiv.org/abs/1508.06600]]
[[A Hitchhiker's Guide to descriptional complexity through analytic combinatorics|http://www.sciencedirect.com/science/article/pii/S0304397514001066]]
[[A Survey on Operational State Complexity|http://arxiv.org/abs/1509.03254]]
[[An Introduction to Descriptional Complexity of Regular Languages through Analytic Combinatorics |http://www.dcc.fc.up.pt/dcc/Pubs/TReports/TR12/dcc-2012-05.pdf]]
[[Mixing times of random walks on dynamic configuration models|http://arxiv.org/abs/1606.07639]]
[[Model-Based Testing |https://www.researchgate.net/profile/Manoranjan_Satpathy/publication/223054649_Model_Based_Testing_of_a_Network-on-Chip_Component/links/0deec535829abd6ddc000000.pdf#page=37]]
//Book//: The Duffing Equation: Nonlinear Oscillators and their Behaviour
See [[MMathPhys miniprojects]] and [[Duffing oscillator]]
//More papers and references//:
https://en.wikipedia.org/wiki/Intermittency
https://en.wikipedia.org/wiki/Crisis_%28dynamical_systems%29
Y. Ueda, Steady Motions Exhibited by Duffing’s Equation: A Picture Book of Regular And Chaotic Motions
[[Catastrophes with Indeterminate Outcome Stewart, H. B. ; Ueda, Y.|http://ezproxy-prd.bodleian.ox.ac.uk:2084/stable/51909?seq=1#page_scan_tab_contents]]
[[EXPLOSION OF STRANGE ATTRACTORS EXHIBITED BY DUFFING'S EQUATION - Yoshisuke Ueda|http://onlinelibrary.wiley.com/doi/10.1111/j.1749-6632.1980.tb29708.x/abstract]]
[[Common dynamical features on periodically driven strictly dissipative oscillators|http://sci-hub.io/http://www.worldscientific.com/doi/abs/10.1142/S0218127493000611]] (introduces torsion and winding numbers)
[[Comparison of bifurcation sets of driven strictly dissipative oscillators|https://link.springer.com/chapter/10.1007%2F978-3-0348-7004-7_41]]
__Wada basins__
https://en.wikipedia.org/wiki/Lakes_of_Wada
[[Wada basin boundaries and basin cells|http://sci-hub.io/10.1016/0167-2789%2895%2900249-9]] [[Other link|http://www.sciencedirect.com/science/article/pii/0167278995002499]]
[[Unpredictable behavior in the Duffing oscillator: Wada basins|http://www.escet.urjc.es/~fisica/investigacion/publications/Papers/2002/aguirre_wadad.pdf]]
[[Testing for Basins of Wada|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4639726/]]
[[Response Of A Harmonically Excited Hard Duffing Oscillator – Numerical And Experimental Investigation|https://link.springer.com/chapter/10.1007/978-1-4020-9100-1_27]]
[[Experimental investigation of the response of a harmonically excited hard Duffing oscillator|http://www.ias.ac.in/article/fulltext/pram/068/01/0099-0104]] From [[here|http://www.ias.ac.in/listing/articles/pram/068/01]]
__Analytical methods__
[[Exact analytical solutions for forced cubic restoring force oscillator|https://link.springer.com/article/10.1007%2Fs11071-015-2486-2]] Uses Jacobi elliptic function (only for undamped Ueda oscillator I think).
[[A comparison of classical and high dimensional harmonic balance approaches for a Duffing oscillator|http://www.sciencedirect.com/science/article/pii/S0021999105004894]]
[[Second order averaging and bifurcations to subharmonics in duffing's equation|http://www.sciencedirect.com/science/article/pii/S0022460X81800302]]
[[Subharmonic Oscillations in Nonlinear Systems|http://ezproxy-prd.bodleian.ox.ac.uk:2837/content/aip/journal/jap/24/5/10.1063/1.1721322]]
[[Chaotic states and routes to chaos in the forced pendulum|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.26.3483]]
[[Organization of periodic orbits in the driven Duffing oscillator|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.38.1566]]
[[Structure in the bifurcation diagram of the Duffing oscillator|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.51.935]]
[[superstructure in the bifurcation set of the duffing equation|http://www.dpi.physik.uni-goettingen.de/~ulli/pdf/PL85.pdf]]
[[General case of crisis-induced intermittency in the Duffing equation|http://www.sciencedirect.com/science/article/pii/037596019390732F]] for double-well Duffing oscillator.
[[On the jump-up and jump-down frequencies of the Duffing oscillator|http://www.sciencedirect.com/science/article/pii/S0022460X08003805]]
More books:
Chaos in Nonlinear Oscillators: Controlling and Synchronization
By M Lakshmanan, K Murali
[[Antimonotonicity|http://sci-hub.io/10.1016/0375-9601%2892%2990442-O]] reversal of period-doubling cascades
''Reflexivity'' refers to a property of a binary [[Relation]], $$R$$ on $$X$$:
|for all $$x \in X, x R x$$|
!![[Inhibition of the Prostaglandin Degrading Enzyme 15-PGDH Potentiates Tissue Regeneration|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481126/]]
[[summary|https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0ahUKEwjivNbOtuTPAhWbHsAKHekoAZUQFggoMAE&url=https%3A%2F%2Fwww.hkn24.com%2Fbbs%2Fdownload.php%3Ftable%3Dbbs_49%26idxno%3D36315%26file_extension%3Dpdf%26filename%3D%255B%25B3%25ED%25B9%25AE%25BF%25F8%25B9%25AE%255DPublished%2BScience%2BArticle.pdf&usg=AFQjCNGt2gb_ngcNcsWhQc1MamGPwP6LIQ&sig2=Z8USSE5w6n4L7lZZdvmLpg&cad=rja]]
!!!__Introduction__
__Main result__
Studying mouse [[knock-out|Gene knock-out]] models, we
have shown that 15-PGDH negatively regulates
tissue regeneration and repair in the bone
marrow, colon, and liver.
SW033291, a potent small-molecule inhibitor of 15-PGDH (inhibitor dissociation constant
K i ~0.1 nM), recapitulates in mice the phenotypes
of 15-PGDH gene knockout
__Overall mechanism__
[[Prostaglandin PGE2]] is involved in homing and maintenance of [[Stem cell]]s in several [[tissues|Tissue (Biology)]].
15-hydroxyprostaglandin dehydrogenase (''15-PGDH''), that acts in vivo as a ''negative regulator'' of prostaglandin levels and activity (20–22), provides a candidate target.
SW033291 blocks 15-PGDH activity.
__15-PGDH inhibition mechanism__
15-PGDH catalyzes the first step in the degradation of prostanoid family molecules, oxidizing the prostanoid 15-hydroxyl group to a ketone, and thereby abrogating binding to prostaglandin receptors (20).
__SW033291 mechanism__
Initial characterization showed that treating cells with SW033291 decreased cellular 15-PGDH enzyme activity by 85%
SW033291 did not increase colony formation of bone marrow from 15-PGDH knockout mice, confirming that the compound acts by directly targeting15 -PGDH
__PGE2 mechanism__
See below, in pathway section
!!!__Toxicology and adverse effects__
We detected no toxicity from chemical inhibition of 15-PGDH in adult mice. Mice injected with SW033291 at 20 mg/kg daily for 7 days showed equivalent daily weights and activity as mice injected with vehicle-control, and showed no adverse changes in blood counts or serum chemistry.
While systemic administration of PGE2 has been suggested to have potentially negative effects on myelopoiesis (29) and on long term hematopoietic stem cells (24), no such adverse effects were seen with SW033291.
They also performed serial marrow transfer experiments between SW033291-treated mice, and vehicle-control-treated mice.
!!!__Experimental esults__
* Genetic Deletion or Pharmacologic Inhibition of 15-PGDH Increases Tissue PGE2 Levels
* 15-PGDH Inhibition Promotes Hematopoietic Recovery after Bone Marrow Transplantation
* 15-PGDH Inhibition Protects Mice From Colitis
* 15-PGDH Inhibition Promotes Liver Regeneration
//Genetic Deletion or Pharmacologic Inhibition of 15-PGDH Increases Tissue PGE2 Levels//
//15-PGDH Inhibition Promotes Hematopoietic Recovery after Bone Marrow Transplantation//
To evaluate whether 15-PGDH might regulate these responses, we examined 15-PGDH knockout mice and SW033291 treated wild-type mice. We observed a significant 43% increase in neutrophil counts in 15-PGDH knockout versus wild-type mice (Fig. 1C), and a significant 39% increase in bone marrow SKL (Sca-1+ C-kit+ Lin−) cells (Fig. 1D), which are enriched for bone marrow stem cells.
__[[Pathway|Metabolic pathway]]__
''Experiment'': Induction of CXCL12 and SCF in CD45− cells was significantly blocked when SW033291 was co-administered to mice together with an antagonist of EP4 or EP2 type PGE2 receptors. However, SW033291 fully induced CXCL12 and SCF when co-administered with antagonists of EP1 or EP3 receptors
''Conclusion'': We conclude that SW033291 increases PGE2 levels within bone marrow, and that PGE2 functions through the EP2 and EP4 receptors to induce CXCL12 and SCF.
''Experiment'': Transplant recipient mice treated with SW033291 showed a significant 2- to 3-fold increase in the number of donor cells that homed to the recipient’s bone marrow (Figs.2, F and G, and S12). This effect of SW033291 could be blocked by co-treating the transplant recipient mice with: an inhibitor of PGE2 generation, an inhibitor of PGE2 signaling, or an antagonist of CXCL12 (that is induced by PGE2).
''Conclusion'': Together these results define a pathway in which 15-PGDH inhibition causes an increase in bone marrow PGE2, which in turn induces expression of bone marrow CXCL12 and SCF, cytokines that alter the bone marrow microenvironment to better support the homing of transplanted cells.
//15-PGDH Inhibition Protects Mice From Colitis//
......The two groups of chimeric mice showed identical susceptibility to DSS-induced colitis
On day 8, after 7 days of oral DSS treatment, wild-type mice receiving concurrent injections with vehicle-control showed significant suppression of BrdU incorporation in colonic crypts (Figs. 5, S19). In contrast, day 8 BrdU incorporation was increased 2.5-fold in SW033291-treated animals (Fig. 5B, 10 mg/kg SW033291) and increased 2.4-fold in 15-PGDH knockout mice (Fig. 5C). Immunofluorescence staining for cleaved caspase 3 showed only scattered apoptotic cells, and these were present in similar amounts in control and SW033291-treated mice. Thus 15-PGDH inhibition appears to confer protection primarily by helping maintain colonocyte proliferation in the DSS -damaged mucosa.
//15-PGDH Inhibition Promotes Liver Regeneration//
Consistent with SW033291 up-regulating prostaglandin signaling, regenerating livers of SW033291-treated mice showed 36–55% higher levels of cyclic AMP from post-operative days1 through 3 (P<0.002, Student’s t-test) (Fig. S20). However, we did not find differences between livers of SW033291-treated versus control mice in other downstream signaling targets, including levels of beta-catenin protein; nuclear localization of beta-catenin; and levels of phosphorylation at PKA target sites on CREB serine 133, beta-catenin serine 675, and beta-catenin serine 552.
!!!__Future work__
As SW033291 also enables successful murine bone marrow reconstitution from a reduced inoculum of marrow cells, SW033291 may additionally have applicability to HSC transplants that employ human umbilical cord blood stem cells, in which numbers of donor cells are limited by supply and expense
//aka regression//
Discriminative [[Supervised learning]] where the output value is continuous, and quantiative (i.e. it has an ordering, and a notion of closeness (matrix)).
[[Notes|http://cs229.stanford.edu/notes/cs229-notes1.pdf]]
!![[Linear regression]]
* [[Nonparametric|Nonparametric statistics]] version: [[Locally-weighted linear regression]]
* [[Ridge regression]]
* [[Lasso]]
!![[Nearest-neighbour classification]]
!![[Kernel linear regression]]
!![[Nonlinear regression]]
* [[Deep learning]]
[[Multiclass MLP|https://www.youtube.com/watch?v=NUKp0c4xb8w&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=9#t=21m55s]]
''Regularizer'' helps control the model complexity (by constrianing the size of the parameter vector $$\mathbf{\theta}$$). It can also be seen as adding a prior (in Bayesian statistics)
-------------------
https://www.wikiwand.com/en/Regression_analysis
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
Penalising weights "encourages fitting signal rather than just noise"
A different way to avoid overfitting, while keeping all parameters in your model.
[[Intro vid|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=1m]]
We use the [[Prior distribution]] from [[Bayesian statistics]], to make [[simple|Simplicity]] hypothesis more likely. See [[Simplicity and learning]].
[[Intuition|https://www.youtube.com/watch?v=sQ8T9b-uGVE&list=PLA89DCFA6ADACE599&index=11#t=12m]]
[[Neural networks [2.8] : Training neural networks - regularization|https://www.youtube.com/watch?v=JfkbyODyujw&index=14&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]
!!!__[[Dropout]]__
!!!__[[Batch normalization]]__
!!!__[[Tikhonov regularization]]__
See [[Machine learning]], [[Decision theory]]
[[Andrew Ng intro lecture|https://www.youtube.com/watch?v=RtxI449ZjSc&index=16&list=PLA89DCFA6ADACE599#t=20s]] -- [ext[book|https://sites.ualberta.ca/~szepesva/RLBook.html]] [[which proves several important theorems|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=10m30]].
-- [[Credit assignment problem|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=6m30s]]
[[Intro lecture by David Silver|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT]] -- [[slides|http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/intro_RL.pdf]]
!!!__[[Types of RL|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h11m]] __
* [[Prediction vs control|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h24m40s]].
** Policy = policy evaluation
**control = find optimal policy
* Planning vs learning+planning
** Planning = solve RL (prediction/control) problem with full knowledge of MDP
** Learning + planning = RL (prediction/control) in not fully-known environment. need to learn to model environment too!. [[Exploration vs exploitationn|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h20m40]]
[[Free energy principle]]
[img[RL_taxonomy.png]]
[img[reinforcement_learning_venn_diagram.png]]
!!!__Environment, observation, and [[State|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=36m30s]]__:
[[The next action could depend on the whole previous history|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=35m]], however, it is more efficient to just take an action according to a summary of the history (often sufficient statistic of the future) which is called the //agent state//. In fact, there are two types of states in RL.
* ''Enviroment state''. Real state of the environment which determines its future behaviour. Generally, unobservable.
* ''Agent state'' of the model. In general, a function of the agent's history
The agent state is often chosen to be the [[Information state|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=42m]] or Markov state. An information that contains all useful information of the history, in order to probabilistically predict the next state (a [[Sufficient statistic]] of the future). This Markov state is used as part of the ''model'' the agent uses, which is often formalized as a [[Markov decision process]] ([[vid|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h06m36s]])
[[Example|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=49m30s]]
[[Fully observable environment|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=51m15]]. agent state = environment state = observation. Model = real environment.
[[Partially-observable environment|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=52m25s]]. Agent needs to learn an "agent state", and an MDP. Now environment state $$\neq$$ agent state $$\neq$$ observation.
!!__[[Markov decision process]]__
(Fully observable) Reinforcement leaning models the world as a Markov decision process. [[Andrew Ng intro to MDPs|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=9m]] -- [[operational definition|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=19m]] -- [[David Silver lecture|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1]]
[[Planning -> policy evaluation (prediction)-> control|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=8m10s]]
!!__Optimal policy problem__
[[David Silver video|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=1h16m]] -- [[Optimal policy theorem|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=1h17m25s]]!
The core problem of MDPs is to find a ''policy'' for the decision maker: a function $$\pi$$ that specifies the action $$\pi(s)$$ that the decision maker will choose when in state $$s$$ ([[vid|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=58m44s]]). <small>Note that once a Markov decision process is combined with a policy in this way, this fixes the action for each state and the resulting combination behaves like a [[Markov chain]]</small>. The policy [[could be stochastic too|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=59m24s]]. Apparently, no need to have stochastic policies, except when we have multiple agents (studied in [[Game theory]], as //strategies//), [[vid|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=11m]].
[[vid|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=1h8m9s]]
The __[[goal|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=23m]] is to choose a policy $$\pi$$ that will maximize__ some cumulative function of the random __rewards__, typically the __expected__ discounted sum over a potentially infinite horizon:
|$$V_\pi (s) := \sum^{\infty}_{t=0} {\gamma^t R_{a_t} (s_t, s_{t+1})} $$|''Value function'' ([[vid|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=59m54s]])|
where we choose $$a_t = \pi(s_t)$$, $$\ \gamma \ $$ is the [[discount factor|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=22m]] and satisfies $$0 \le\ \gamma\ < 1$$. (For example, $$ \gamma = 1/(1+r) $$ when the discount rate is r.) $$ \gamma $$ is typically close to 1. [[This is known as the total payoff|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=20m20s]], or [[value function|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=29m]], for policy $$\pi$$. This function [[satisfies a recursive equation|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=33m20s]] called [[Bellman equation]], which will be used for the learning algorithms that compute the optimal policy.
Because of the Markov property, the optimal policy for this particular problem can indeed be written as a function of $$s$$ only, as assumed above ([[although for some richer models this may not be true|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=25m30s]])
!__Learning algorithms__
[[video|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=28m20s]]
!!!__Computing the value function ([[Policy evaluation|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=12m40s]])__
Use [[Bellman expectation equation|Bellman equation]] [[gives a set of linear constraints|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=40m20s]] to the value function $$V_\pi (s)$$ that can be solved as a linear system, to obtain the value of the value function, for a given policy. Most effective way to __solve it is iteratively__:
* [[Synchronous update|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=14m45s]]
!!__Definitions__
!!!__[[Optimal value function|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=44m05s]]__
$$V^* (s) = \max\limits_\pi V^\pi (s)$$
[[Bellman optimality equation|Bellman equation]] for $$V^*$$ (aka [[Bellman optimality equation|https://www.youtube.com/watch?v=lfHX2hHRMVQ&index=2&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT#t=1h22m40s]], [[derivation|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=14m]]; although I think the way to do it, is to treat first $$a$$ as indepdent of $$\pi$$, and then realizing that maximizing over $$a$$ should give $$V^*$$ (and so $$a$$ should be $$\pi(s_0)$$):
$$V^* (s) = R(s) + \gamma \max\limits_a \sum\limits_{s'} P_{s a} (s') V^* (s')$$
!!!__[[Optimal policy|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=47m10s]]__
$$\pi^*(s) = \arg\max\limits_a \sum\limits_{s'} P_{s a} (s') V^* (s')$$
This is the optimal policy that maximizes the expected total payoff (solution of the optimal policy problem).
[[How to compute the optimal policy|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=48m30s]]
MDPs can be solved by [[Linear programming]], iterative methods, or [[Dynamic programming]].
!!!__Q function, or ''action-value function'' --> //Q learning//__
Although state-values suffice to define optimality, it will prove to be useful to define action-values. Given a state $$s$$, an action $$a$$ and a policy $$\pi$$, the action-value of the pair $$(s,a)$$ under $$\pi$$ is defined by
:$$Q^\pi(s,a) = E[R|s,a,\pi],\,$$
where, now, $$R$$ stands for the random return associated with __first taking action $$a$$ in state $$s$$ and following $$\pi$$ thereafter__.
[[Video|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=52m]] -- [[Bellman equation for action-value function|https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&spfreload=1#t=54m40s]]
It is well-known from the theory of MDPs that if someone gives us $$Q$$ for an optimal policy, we can always choose optimal actions (and thus act optimally) by simply choosing the action with the highest value at each state.
The ''action-value function'' of such an optimal policy is called the ''optimal action-value function'' and is denoted by $$Q^*$$.
[[video|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=27m55]], [[Q function using NN|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=33m]], define loss function, and then use [[Gradient descent]]
[[Don't need to follow optimal policy while Q-learning|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=37m30s]]
[[Example|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=41m]]
!!__Linear programming approach__
!!__Dynamic programming / optimal value function approaches__
[[idea|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=13m05]]
-- [[Tradeoffs|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=1h01m45s]]
!!![[Neuro-dynamic programming|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=3m]]
!!!__[[Policy iteration|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=59m38.5s]]__
,,[[Greedy policy always improves policy (or leaves it equally good)|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=49m20s]] --> [[partial ordering over policies as intuition for optimal policy theorem|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=56m44s]],,
[[Full policy iteration|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=29m52s]]
[[Modified policy iteration doesn't require to converge to real value function|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=58m40s]]. The version with just one step in Bellman equation per policy iteration is described below. This version is equivalent to value iteration (below)
The algorithm has the following two kinds of steps, which are repeated in some order for all the states until no further changes take place. It first computes the optimal policy estimate using, the optimal value function estimate, and then recomputes the value function estimate using the new optimal policy estimate.
They are defined recursively as follows:
:$$ V_\pi(s) := \sum_{s'} P_{\pi(s)} (s,s') \left( R_{\pi(s)} (s,s') + \gamma V(s') \right) $$
:$$ \pi(s) := \arg \max_a \left\{ \sum_{s'} P_a(s,s') \left( R_a(s,s') + \gamma V(s') \right) \right\} $$
Where, the value function (defined above) measures the discounted sum of the rewards to be earned (on average) by following that solution from state $$s$$. The second recursive relation is called [[Bellman equation]]. These equation are used iteratively one after the other in the 1-step policy iteration.
Their order actually depends on the variant of the algorithm; one can also do them for all states at once (synchronously) or state by state, and more often to some states than others (asynchronous). As long as no state is permanently excluded from either of the steps, the algorithm __will eventually arrive at the correct solution__!
!!!__[[Value iteration|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=50m15s]] ([[vid2|https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3#t=1h1m48s]])__
Iterate:
:$$V_{i+1}(s) := \max_a \left\{ \sum_{s'} P_a(s,s') \left( R_a(s,s') + \gamma V_i(s') \right) \right\}$$
to converge to $$V^*$$. After iterations, compute optimal policy using its definition
:$$\pi^*(s) = \arg\max\limits_a \sum\limits_{s'} P_{s a} (s') V^* (s')$$
There are other algorithms described in the [[Wiki page|https://www.wikiwand.com/en/Reinforcement_learning]]:
* Trust Region Policy Optimization [1]
* Proximal Policy Optimization (i.e., TRPO, but using a penalty instead of a constraint on KL divergence), where each subproblem is solved with either SGD or L-BFGS
* Cross Entropy Method
!!!__[[Temporal differences|Temporal difference learning]] (TD)__
//TD0//
[[vid|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=19m30s]]
A kind of [[Gradient descent]] to converge to solution to V(s) that satisfies [[Bellman equation]]
!!__[[Reinforcement learning in continuous state space]]__
!!!__[[Fitted value iteration]]__
!!!__[[Linear quadratic regulation]] (LQR)__
!!__[[Partially-observable MDP]] (POMDP)__
!!!__[[Kalman filter]]s and [[LQG control]]__
!!__[[Policy search]]__
[[Stochastic gradient descent]] on the parameters determining (stochastic) policy, to maximize expected payoff.
[[Application to POMDP|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=44m25s]]
!!![[Optimal value function vs policy search approaches|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=42m]]
Policy search is usually best when the policy is a simple function of the state features (like a 'reflex'). Optimal value function approaches are better when the policy is more complicated, maybe needing some multistep reasoning, as in chess.
Policy search often works well, but is very slow, and is stochastic. Also, because one needs to simulate the MDP, it is trained most often using simulation.
See [[here|https://www.youtube.com/watch?v=yCqPMD6coO8&index=20&list=PLA89DCFA6ADACE599#t=48m]] for ''Pegasus policy search'', using "scenarios", which look like [[Quenched disorder]]
!!__[[Unkown state transition probabilites|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=1h4m48s]]__
* Estimate from data.
[[Summary|https://www.youtube.com/watch?v=RtxI449ZjSc&list=PLA89DCFA6ADACE599&index=16#t=1h9m20s]]
!!__Undiscounted MDP__
No discount factor $$\gamma$$. Approach: average reward MPD.
!!__[[Debugging RL algorithms|https://www.youtube.com/watch?v=UFH5ibWnA7g&index=19&list=PLA89DCFA6ADACE599#t=1m]]__
------------------
!!__Applications__
Many applications to [[Robotics]]
[[More applications]]
-------------------
[[RL Course by David Silver|https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL5X3mDkKaJrL42i_jhE4N-p6E2Ol62Ofa]] [[course page|http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html]]
__Deep reinforcement learning__
See Nando's lectures
__OpenAI Gym__
https://gym.openai.com/docs
https://github.com/openai/gym
Example: https://github.com/joschu/modular_rl
[[Pavlov.js - Reinforcement learning using Markov Decision Processes|https://github.com/NathanEpstein/Pavlov.js]]
!!![[https://openai.com/blog/universe/]]
!!![[DeepMind Lab|https://deepmind.com/blog/open-sourcing-deepmind-lab/]]
See also [[Decision theory]], [[Game theory]]
!![[Deep reinforcement learning]]
!![[Multi-agent system]]s
[[examples|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=19m]]
* Simplest approach: [[Discretization of space|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=23m12s]] -- [[Curse of dimensionality]]
[[Problem set up|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=32m10s]], focus on continuous state space, but discrete action set. [[Need a model|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=34m]], which can be theoretically derived, or learnt.
[[Learning algorithm|https://www.youtube.com/watch?v=LKdFTsM3hl4&list=PLA89DCFA6ADACE599&index=17#t=46m40s]], assuming we can approximate the value function as a linear function of a set of features of the state $$s$$ (as in [[Linear regression]])
!!!__[[Fitted value iteration]]__
!!!__[[Linear quadratic regulation]] (LQR)__
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
A ''relation'' is a subset of a [[Cartesian product]].
A relation is often used to refer to a binary relation, which is a subset of $$X \times Y$$. An element $$x \in X$$ is said to be related to $$y \in Y$$ (denoted $$xRy$$) if the pair $$(x,y) \in R \subset X \times X$$.
A //relation on $$X$$// is used to refer to a subset of $$X \times X$$.
A [[Function]] $$F: X \rightarrow Y$$ defines a relation, but not all relations correspond to functions.
__Examples of relations__
[[Total ordering]] --
[[Partial ordering]]
[[Equivalence relation]]
------------------------
http://mathworld.wolfram.com/Relation.html
See [[Percolation theory]]
In 1969, Fortuin and Kasteleyn (FK) [27,28,103,104] found an interesting mapping between the q-state Potts model, which includes the [[Ising model]] for q = 2, and a correlated bond-percolation model called the random-cluster model. ,,It can be shown that there is a one-to-one correspondence between different
thermodynamic quantities and their geometric counterparts based on the statistical and fractal properties of FK clusters.,,
This allowed powerful renormalization group ideas to be used [74].
Swendsen and Wang [105], and then Wolff [106], have exploited this mapping to devise extraordinar- ily efficient Monte Carlo algorithms.
There are mappings between the Ising model at a given dimension and a model of manifolds surrounding the geometric spin clusters.
[[Percolation and the Potts model|http://link.springer.com/article/10.1007%2FBF01014303]]. Many of the tools of [[Statistical physics]] have been applied to percolation through these mappings.
https://www.overleaf.com/read/vqmdycrpfjwk
[[pdf|relations-stability-boolean (2).pdf]]
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
the ratio of the average mass of one atom of an element to one twelfth of the mass of an atom of carbon-12.
http://www.bbc.co.uk/education/guides/zsp4jxs/revision/3
Symbol: $$A_r$$.
//aka Kullback–Leibler divergence, KL divergence//
[[video|https://www.youtube.com/watch?v=fc5FyE41zeo#t=3m15s]]
[[Mutual information]] is a special case. Defines a measure of "distance" between probabiliy distributions. Applications in estimating hypothesis testing errors and in large deviation theory.
$$D_{\mathrm{KL}}(P\|Q) = \sum_i P(i) \, \log\frac{P(i)}{Q(i)}.$$
https://www.wikiwand.com/en/Kullback%E2%80%93Leibler_divergence
https://www.youtube.com/watch?v=QPkb5VcgXAM#t=20m55
The sum of the [[Relative atomic mass]]es of the atoms in the [[Chemical formula]] of a [[Chemical substance]]
http://www.chem.gla.ac.uk/teaching/GenChemWeb/Contents/Topic_13/13Act_2.htm
If the chemical formula refers to an actual molecule it is then almost the same as the [[Relative molecular mass]]
//aka molecular weight, or relative molar mass//
Symbol: $$M_r$$
Ratio of the mass of a molecule to the unified atomic mass unit. Sometimes called the molecular weight or relative molar mass.
http://goldbook.iupac.org/R05271.html
[[Numerical Relativity|https://www.youtube.com/playlist?list=PL04QVxpjcnjh2mFtM-RsRmbcWhETPcasv]]
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Interesting historical facts: https://en.wikipedia.org/wiki/Olinto_De_Pretto
See [[Belief system]]
[[Wikipedia:Portal/Directory/Philosophy, religion, and spirituality|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Philosophy,_religion,_and_spirituality]]
[[Calculating the financial risks of renewable energy|https://techxplore.com/news/2016-09-financial-renewable-energy.html]]
Technically using the [[Sun]] as energy source/fuel.
!!!__[[Hydro-electric power]] plant__
[img[https://www.nbpower.com/media/1664/d-html-en-safety_learning-learning-electricity_generated-hydro-hydro-anim-en.gif]]
!!!__[[Wind power]]__
[img[http://www.alliantenergykids.com/wcm/groups/wcm_internet/@int/@aekids/documents/digitalmedia/mdaw/mdiy/~edisp/022691.jpg]]
!!!__[[Solar power]]__
[img[http://www.solarbuildingtech.com/Solar_PV_Tech/Images/PhotoVoltaic-solar-panel-working_princple.gif]]
See Gingkotree, and books.
See also [[Renormalization group]]
See also [[Critical phenomena]], field theory...
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In the real-space renormalization group we first decrease the number of degrees of freedom by a factor $$b$$, in such a way that the new system is of the same kind as the previous (say a lattice, I know this is informal now). An example of this procedure is block spin transformation. We then transform the couplings in such a way that the (total) free energy is unchanged (by keeping the partition function unchanged say).
The free energy per site thus increases by a factor $$b^{d}$$ (where $$d$$ is the dimension), apart from an analytic constant part (see Cardy), accounting for the integrated short wavelength degrees of freedom. At the same time the new free energy per site is the same function f(couplings) as before because the model is the same after the RG transformation, just the couplings have changed, by assumption. Furthermore, near the critical point, only the relevant operators contribute significantly (are big enough). Also, close enough to the fixed point, linearized dynamics is a good approximation, and an RG transformation corresponding to a factor $$b$$, multiplies the relevant eigendirections in coupling space by factors $$b^{y_i}$$, for some $$y_i$$. Therefore, we have
$$f(\{u_i\}) b^d = f(\{b^{y_i}u_i\})$$
From this the scaling of f with u_i can be worked out.
Finally, u_i can be related to relevant thermodynamic quantities, appearing in the couplings of the original microsocopic theory.
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A method to obtain macroscopic properties from microscopic theories, among other things. The general framework (as applied to critical phenomena) is presented below. For other applications, the later steps will be different, but the general setup is the same.
1. Define ''RG scheme'' (often involving ''coarse graining'' and ''scaling''; this is the case, for instance, in [[Real-space renormalization group]], see [[RG scheme]]), that defines new variables, while leaving the [[Partition function]] fixed (or at least approximately fixed). Note that even though the partition function is fixed (and so all macroscopic variables are too), the microscopic Boltzmann distribution function need not stay fixed as a consequence (see [[this paper|http://arxiv.org/abs/1608.08225]], see reply to the article actually).
2. This scheme produces an RG transformation on the couplings/parameters of the theory. This transformation, if iterated, produces an ''RG flow'' in the space of parameters. The flow can indeed be analyzed with the tools of the theory of [[Dynamical system]]s
3. Any point near a fixed point in the space of parameters has ''relevant and irrelevant'' (and possibly marginal) ''directions''. These correspond to natural coordinates related to the [[unstable and stable manifolds|Invariant manifolds in dynamical systems]] of a fixed point, which in the linear neighbourhood of the fixed point are called ''scaling variables''. Relevant directions are the ones that determine the long-time dynamics under the RG flow.
4. Changes in tunable parameters of the theory (like temperature, volume, external magnetic field, etc.) can be related to changes in coupling constants that produce the same change in the free energy. These changes should be along relevant directions because tunable parameters can affect the qualitative macroscopic behaviour of the theory, and so should affect the long-time behaviour of the theory under the RG flow.
5. A ''critical surface'' corresponds to the stable manifold of a saddle fixed point (this manifold is also called separatrix in [[Dynamical system]]s theory, because it separates qualitatively different future flows, corresponding to different phases, in a physical system). A critical point of a family of theories parametrized by a parameter, and spanning a 1D manifold (curve) in the whole space of theories is the intersection of this curve with the critical surface.
6. Theories near the critical point evolve to the vicinity of the fixed point under a finite number of iterations of the RG transformation. Theories with slightly different tuning parameters evolve to slightly different points in the vicinity of the critical point. In particular, it can be argued that for a bicritical point (with two relevant directions), there will be a relevant variable that corresponds to "thermal" deviation, $$u_t \sim t/t_0$$, and another to a "magnetic" deviation, $$u_h \sim h/h_0$$ (see Cardy's book for some more explanation). Here deviations refer to deviations from the critical point. These relations are linear simply because we are taking $$t$$ and $$h$$ to be small (near the critical point), and we have Taylor expanded (assuming relation is analytic). $$t_0$$, and $$h_0$$ are called ''scaling factors'' and are non-universal.
7. From the RG scheme, one easily derives how $$u_t$$, and $$u_h$$ change close to the fixed point, using the linearized RG flow. From the RG scheme, one can also easily find how the free energy (per volume, or per site), $$f$$ changes under RG flow, and thus how it changes under changes of $$u_t$$, and $$u_h$$. See Cardy for details
8. Finally by relating $$u_t$$, and $$u_h$$ to $$t$$, and $$h$$, the renormalization group allows us to find how the free energy changes under changes of thermodynamic variables ($$t$$, and $$h$$), and thus it allows us to find thermodynamic coefficients and quantities (which are derivatives of $$f$$ w.r.t to thermodynamic quantities, such as $$t$$, and $$h$$), as functions of the thermodynamic variables $$t$$, and $$h$$. These often have power law form, and from them we can extract ''critical exponents''. These critical exponents turn out to depend just on the dimensionality, and the eigenvalues of the relevant variables near the fixed point. Thus, any theory with a critical point flowing to this same fixed point will have the same critical exponents, and is said to belong to the same ''universality class''.
These last steps can be seen carried out for the case of the spin-block transformation (a particular RG scheme) in Cardy's book, or in [[this page|http://www.nyu.edu/classes/tuckerman/stat.mech/lectures/lecture_28/node4.html#SECTION00040000000000000000]]. The resulting form of the free energy is:
[img[http://i.imgur.com/dc2Y6tM.png]]
where $$\Phi$$ is known as a ''scaling function''
The scaling coefficients turn out to be:
[img[http://i.imgur.com/oSkbIDF.png]]
''Scaling relations'' relate the critical exponents as explained in picture.
Sometimes, because of the generality of this, the above form of the free energy is assumed instead of derived from RG, and this is known as the ''scaling hypothesis''. See this series of videos: [[6. The Scaling Hypothesis Part 1|https://www.youtube.com/watch?v=NLKJdcb1E5I&index=6&list=PLUl4u3cNGP63HkEHvYaNJiO0UCUmY0Ts7]]
See [[Theory of spin glasses|http://iopscience.iop.org/article/10.1088/0305-4608/5/5/017/meta]] -- [[Theory of spin glasses. II|http://iopscience.iop.org/article/10.1088/0305-4608/6/10/022/meta]]
https://www.wikiwand.com/es/Truco_de_las_r%C3%A9plicas
Imagining many identical but independent copies, or replicas, of the system; computing a thermodynamic average over them all; and then taking the number of replicas to zero. It turns out that this bizarre recipe—actually quite inspired, though mysterious—can in principle handle the difficulties posed by [[Quenched disorder]]
See [[Replica symmetry breaking]]
[[silent video|https://www.youtube.com/watch?v=fZ8WCic5u2I&index=2&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5#t=36m55s]]
A method for massively parallel mutant hunting in [[Biochemical genetics]]. See [[video|https://www.youtube.com/watch?v=hf3G4eD23k0#t=1m40s]].
[img[http://utminers.utep.edu/rwebb/assets/images/Replica.jpg]]
,,//aka RSB//,,
It was found that the problem in the original solution of the [[Sherington-Kirkpatrick Hamiltonian]] was due to the EA order parameter not being appropriate.
Instead, it was postulated that //the symmetry that is broken is that between the replicas themselves//. “replica symmetry” means that the Hamiltonian treats all replicas equivalently, while broken replica symmetry means that the spin glass phase distinguishes among replicas.
Noting that the replica symmetry is broken does not tell one how it is broken: there are many possible ways of breaking replica symmetry.
!!__Parisi solution__
The correct formulation of replica symmetry breaking for the SK model was introduced by Giorgio Parisi in 1979 in [[Infinite Number of Order Parameters for Spin-Glasses|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.43.1754]]
The reason why the SK low-temperature solution failed is that, while spin-flip symmetry is indeed broken in the SK model at low temperatures (which means that all spin glass states come in globally spin-reversed pairs, like the two above), //this alone is not sufficient// to characterize the low-temperature phase. Rather than a single order parameter, there are //infinitely many//.
In other words, for an infinite system there is not a single globally spin-reversed pair of spin glass thermodynamic states, but infinitely many such pairs of states.
Unlike for all ordered systems studied before, for infinite-range spin-glass models, there is no adequate way to characterize the [[broken symmetry|Symmetry breaking]], or equivalently to define an order parameter, by referring solely to any single spin glass thermodynamic state.
!!!__The spin overlap function __
Since there are no distinguishing features among the many spin glass states, how do we compare them? One way is to see how similar they are to each other, which can be accomplished by introducing a ''spin overlap function'' $$q_{\alpha \beta}$$ between two [[Thermodynamic state]]s $$\alpha$$ and $$\beta$$:
$$q_{\alpha \beta} = \frac{1}{N} \sum\limits_{i=1}^N \langle \sigma_i \rangle_\alpha \langle \sigma_i \rangle_\beta $$
From the definition of the [[EA order parameter]], we see that $$q_{EA} = q_{\alpha \alpha}$$, that is it can be interpreted as the //self-overlap// of a thermodynamic state with itself.
[img[Selection_621.png]]
!!!__Spin overlap density__
$$W_\alpha$$ is the probability that a spin-glass system with a particular fixed configuration settles into thermodynamic state $$\alpha$$ when cooled below $$T=T_c$$. We can then define the ''spin overlap density'', as below:
[img[Selection_622.png]]
This gives the probability distribution of different overlaps. It turns out, that even in the [[Thermodynamic limit]], $$N \rightarrow \infty$$, the distribution depends on the particular quenched configuration of couplings between spins $$\mathcal{J}$$. Typical configurations are shown below:
|[img[Selection_623.png]]|[img[Selection_624.png]]|
This is an example of a Non-[[Self-averaging]] quantity.
Because the spin overlap density is not a function of the thermodynamic state (but in fact refers to relations between such states), it may be non-self-averaging, unlike standard order parameters, that are functions of the [[Thermodynamic state]].
''Parisi order parameter''
[img[Selection_625.png]]
[img[Selection_627.png]]
!!!__Ultrametricity__
when overlaps among three states are examined, a considerable degree of new structure is revealed: the space of overlaps of SK spin glass states is found to have an [[ultrametric structure|Ultrametric space]] [ [[Ultrametricity for physicists|http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.58.765]] ].
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[[Measuring Equilibrium Properties in Aging Systems|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.81.1758]].
,,the Gibbs equilibrium measure decomposes into a mixture of many pure states. This phenomenon was first studied in detail in the mean field theory of spin glasses, where it received the name of replica symmetry breaking. But it can be defined and easily extended to other systems, by consid-ering an order parameter function, the overlap distribution function. This function measures the probability that two configurations of the system, picked up independently with the Gibbs measure, lie at a given distance from each other. Replica symmetry breaking is made manifest when this function is nontrivial.,,
[ext[https://www.wikiwand.com/en/Resampling_(statistics)]]
[[Bootstrap]]
Finding new things.
See [[Science]]
* See big picture
* [[Communication|Scientific communication]]
* Hard work, and skill
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[[Skip connections|https://www.youtube.com/watch?v=x1kf4Zojtb0#t=16m52.5s]]
[ext[https://www.wikiwand.com/en/Resonance_(chemistry)]]
A resonance or mesomerism is a way of describing delocalized electrons within certain molecules or polyatomic ions where the bonding cannot be expressed by one single Lewis structure. A molecule or ion with such delocalized electrons is represented by several contributing structures[2] (also called ''resonance structures'' or canonical structures).
[[video|https://www.khanacademy.org/science/organic-chemistry/organic-structures/formal-charge-resonance/v/resonance-intro-jay]]
These are found, for instance, in [[Aromatic compound]]s, like [[Benzene]]
!!!__Conjugated systems__
Resonance is most often found in [[Conjugated system]]s
A [[molecular|Molecule]] structure, where there are more than one "possible arrangement" of [[Single bond]]s and [[Double bond]]s, and so the molecule actually lives in a [[Quantum superposition]].
These are found, for instance, in [[Aromatic compound]]s, like [[Benzene]]
https://en.wikipedia.org/wiki/Resource_management
//aka RBM//
[[definition|https://www.youtube.com/watch?v=p4Vh_zMw-HQ&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=36#t=3m10s]]. An RBM is an [[undirected graphical model|Markov network]] that defines a [[distribution|Probability distribution]] over some input vector $$\mathbf{x}$$, and it is going to model the distribution by using a hidden layer of binary units (''latent variable''s, $$\mathbf{h}$$), and an ''Energy function''
We first assume that the input $$x$$ is composed of binary variables
__Energy function__
$$E(\mathbf{x}, \mathbf{h}) = -\mathbf{h}^T \mathbf{W} \mathbf{x} - \mathbf{c}^T \mathbf{x} - \mathbf{b}^T \mathbf{h} $$ $$= \sum\limits_{ij} W_{ij} h_j x_i -\sum\limits_i c_i x_i -\sum\limits_i b_u h_i$$
__Probability distribution__
It's a [[Boltzmann distribution]] (hence the name):
$$p(\mathbf{x}, \mathbf{h}) = \exp{(-E(\mathbf{x}, \mathbf{h})}/Z$$
__[[Markov network]] representation__
[[Video|https://www.youtube.com/watch?v=p4Vh_zMw-HQ&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=36#t=9m]]
__[[Factor graph]]__
[[video|https://www.youtube.com/watch?v=p4Vh_zMw-HQ&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=36#t=11m25s]]
!!__Inference on RBMs__
[[video|https://www.youtube.com/watch?v=lekCh_i32iE&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=37]]
__Conditional inference__
[[video|https://www.youtube.com/watch?v=lekCh_i32iE&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=37#t=1m22s]]
[img[Selection_629.png]]
[[derivation of p(h\x)|https://www.youtube.com/watch?v=lekCh_i32iE&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=37#t=4m38s]], although it [[follows from|https://www.youtube.com/watch?v=lekCh_i32iE&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=37#t=14m37s]] the [[Local Markov property]]
!!!__[[Free energy]] in an RBM__
[[Free energy|https://www.youtube.com/watch?v=e0Ts_7Y6hZU&index=38&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]] is used to marginalize $$x$$, to get the distribution $$p(x)$$, which we are most interested in.
[img[Selection_630.png]]
[[derivation|https://www.youtube.com/watch?v=e0Ts_7Y6hZU&index=38&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=2m59s]]. The function in the sum is known as //softplus//, [[vid|https://www.youtube.com/watch?v=e0Ts_7Y6hZU&index=38&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=7m]]
[img[Selection_631.png]]
The ''softplus'' function can often be approximated by the [[ReLU]]
We often can't compute $$p(x)$$ directly due to the intractability of computing the partition function. However the expression helps us understand what $$x$$s the model makes more and less likely.
The hidden units basically represent features that we expect to observe in $$x$$
!!__Training an RBM__
[ext[A Practical Guide to Training Restricted Boltzmann Machines|https://www.cs.toronto.edu/~hinton/absps/guideTR.pdf]]
!!![[Contrastive divergence]]
!!!__Minimizing [[Relative entropy]]__
The coupling parameters between the visible and hidden layers are chosen using a variational procedure that minimizes the Kullback-Leibler divergence (i.e. relative entropy) between the “true” probability distribution ofthe data and the variational distribution obtained by marginalizing over the hidden units.
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[[Neural networks [5.7] : Restricted Boltzmann machine - example|https://www.youtube.com/watch?v=n26NdEtma8U&index=42&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH]]. Example on [[MNIST]] data set.
[[Debugging RBMs|https://www.youtube.com/watch?v=n26NdEtma8U&index=42&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=5m30s]]
!!__Extensions__
[[Neural networks [5.8] : Restricted Boltzmann machine - extensions|https://www.youtube.com/watch?v=iPuqoQih9xk&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=43]]
__[[Gaussian-Bernoulli RBM|https://www.youtube.com/watch?v=iPuqoQih9xk&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH&index=43#t=1m]]__ allows for [[real|Real numbers]] inputs
!!![[Deep belief network]]
!!![[Extended Mean Field RBM]]
[[Temperature based RBM]]
A process in which you revert the osmotic flow by applying a pressure larger than the osmotic pressure, has many applications in [[Industry]], for instance in desalinization technologies. See [[Osmosis]]
See also [[Piezodialysis]] for alternative.
[[Colloidal fouling of reverse osmosis membranes|http://www.sciencedirect.com/science/article/pii/S0011916400860130]]
''Reverse transcription polymerase chain reaction''
RT-PCR is used to clone expressed genes by reverse transcribing the RNA of interest into its DNA complement through the use of reverse transcriptase, using oligo-DT, which substitutes for the role of primers. Subsequently, the newly synthesized cDNA is amplified using traditional [[PCR|Polymerase chain reaction]].
!!![[Real-time RT PCR]] (qRT-PCR)
https://en.wikipedia.org/wiki/Reverse_transcription_polymerase_chain_reaction
Scheme for producing an [[Renormalization group]] transformation
[[Real-space renormalization group]]
[[Variational renormalization group]]
[[Rheology|https://en.wikipedia.org/wiki/Rheology]] is a branch of [[Continuum mechanics]] that __studies the flow of [[matter|Bulk matter]]__, primarily in a liquid state, but also as 'soft solids' or solids under conditions in which they respond with plastic flow rather than deforming elastically in response to an applied force. That is, rheology does not study a particular class of matter, but the flow of any matter.
[[RNA]] that is part of the [[Ribosome]].
They [[evolve|Evolution]] very slowly, and has been used to study [[Phylogenetics]]
[[Linear regression]] with a [[Tikhonov regularization]].
Constant term doesn't contribute to complexity..
Scaling input variables shouldn't change the model complexity, so we normalize them.
__Estimate for ridge regression__
via [[Maximum likelihood]]
$$w_{ridge} = (X^TX +\lambda I_D)^{-1} X^T y$$
easier to solve than normal equation in standard linear regression. lambda is actually a [[Lagrange multiplier]], and dependening on its value we are considering a sphere around the origin. The equation when differentiating w.r.t. lambda gives us that $$w^Tw$$ is less than a constant (see [[here|http://www1.maths.leeds.ac.uk/~cajones/math2640/notes4.pdf]]
Also called l2 regularization or weight-decay.
In [[Bayesian|Bayesian statistics]] terms, this corresponds to a [[Gaussian]] priors, and we are using [[Maximum a-posteriori]].
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
A [[Nucleic acid]], like DNA that has an extra oxygen in the sugar, and has a [[Nucleotide]] that is different ([[Uracil]] instead of [[Thyamine]], binding to A)
Uracil lacks a [[Methyl]] group compared to T, because it doesn't need to take part in a process that checks it..
!!__Coding RNA__
* [[mRNA]]
!!__Functional RNA__
* [[tRNA]]
* [[Rybozime]]
* [[rRNA]]
* etc.
RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules.
Two types of small ribonucleic acid (RNA) molecules – [[microRNA]] (miRNA) and small interfering RNA (siRNA) – are central to RNA interference. In particular, RNA interfernce uses artificial miRNA, known as [[RNAi]]
https://www.wikiwand.com/en/RNA_interference
[[RNA]] is degraded by [[RNase]]s. Hlaf life typically 1-2 minutes in [[E. Coli]]
Stem loops at 5' end can increase mRNA half-life 5-10 fold ~ 24min.
Similar to [[microRNA]], but where the small strand hasn't been coded for, but may come from a [[Virus]]
One of the fathers of [[Rocketry]]
[[Omni-wheel|https://en.wikipedia.org/wiki/Omni_wheel]]
[[Holonomic systems|https://en.wikipedia.org/wiki/Holonomic_%28robotics%29]]. A robot is holonomic if all the constraints that it is subjected to are integrable into positional constraints.
[[Control theory and control systems]]
[img[https://i.kinja-img.com/gawker-media/image/upload/s--BpmDHXWg--/c_scale,fl_progressive,q_80,w_800/eqkradggncpl37e7d4on.gif]]
__Deep learning for grabbing objects__
http://techcrunch.com/2016/03/08/what-could-go-wrong/. http://googleresearch.blogspot.co.uk/2016/03/deep-learning-for-robots-learning-from.html. <b>[[ArXiv paper|http://arxiv.org/pdf/1603.02199v2.pdf]]</b>
Research in China: [[ArXiv paper|http://arxiv.org/abs/1509.06825]] [[News|https://research.preferred.jp/2015/12/robot_binpick_deep_learning/]]
[[Boolean Network Robotics as an Intermediate Step in the Synthesis of Finite State Machines for Robot Control|https://mitpress.mit.edu/sites/default/files/titles/content/ecal13/978-0-262-31709-2-ch112.pdf]]
!!__Robot control__
[[Control theory and control systems]]
[[Reinforcement learning]]
__[[Swarm robotics]]__
!!__Robot simulation__
[[http://gazebosim.org/]]
[[Konstantin Tsiolkovsky]]
[[Robert H. Goddard]]
__[[Hudson River School]]__
__German romanticism__
[[Caspar David Friedrich]]
__American romanticism__
[[Frederic Edwin Church]]
[img[http://static.newworldencyclopedia.org/0/09/Torque_animation.gif]]
See the mechanical universe
[[Moment of inertia]]
A ''rubber'' is a [[viscoelastic|Viscoelasticity]] [[Polymer]] (also called //elastomer//). What makes it viscoelastic is most often that the polymer is cross-linked (though not too cross-linked, as that can lead to rigid materials).
Traditionally, cross-linking was done by exposing natural latex to sulfur, a process known as vulcanization.
Although rubbers are viscoelastic, there is really a continuum between solid and viscoelastic, and some are closer to solids, with others are more clearly viscoelastic.
[[Silly putty|https://en.wikipedia.org/wiki/Silly_Putty]] is interesting (apart from fun), because it has viscoelastic properties, but the polymers it's made of are not cross-linked, they are just very long!
http://www.open.edu/openlearn/science-maths-technology/science/chemistry/introduction-polymers/content-section-5.2.1
[[Viscoelastic Behavior of Rubbery Materials|http://arxiv.org/pdf/1103.5768.pdf]]
__Glass transition temperature__
There is a temperature, called the glass transition temperature, below which a cross-linked polymer stops being viscoelastic (and thus a rubber), and becomes glassy, and hard.
Above the glass transition temperature, the polymer chains are loose and floppy, and that's why a rubber classifies as a [[soft material|Soft matter physics]].
Rubbers are also [[thermoplastic|https://en.wikipedia.org/wiki/Thermoplastic]].
[[Natural rubber|https://en.wikipedia.org/wiki/Natural_rubber]]
[[Synthetic rubber|https://en.wikipedia.org/wiki/Synthetic_rubber]]
[[Definitions of terms relating to the structure and processing of sols, gels, networks, and inorganic-organic hybrid materials (IUPAC Recommendations 2007)|http://www.degruyter.com/view/j/pac.2007.79.issue-10/pac200779101801/pac200779101801.xml]]
Rusting is an [[oxidation reaction|Redox reaction]], that occurs when some [[Metal]]s, like [[Iron]] are in contact with [[Water]] and [[Oxygen]]
http://www.bbc.co.uk/education/guides/zqjsgk7/revision/5
[img[http://a.files.bbci.co.uk/bam/live/content/z46gd2p/large]]
Aluminium does not rust (corrode) because its surface is protected by a natural layer of aluminium oxide. This prevents the metal below from coming into contact with air (containing oxygen).
Unlike rust, which can flake off the surface of iron and steel objects, the layer of aluminium oxide does not flake off.
[[Preventing rusting|http://www.bbc.co.uk/education/guides/zqjsgk7/revision/6]]
[img[https://drdivaphd.files.wordpress.com/2012/06/tears_of_sadness.jpg]]
[[Sad Gladiator Family Scene|https://www.youtube.com/watch?v=TpGFF3hXPkY]]
https://sagecell.sagemath.org/
http://www.sagemath.org/library.html
http://www.sagemath.org/library.html
https://github.com/sagemathinc/smc
[[INtroduction to symbolic computatoin|http://homepages.math.uic.edu/~jan/mcs320/mcs320.pdf]]
http://www.sagemath.org/tour.html
[[Sage for power users|http://wstein.org/books/sagebook/sagebook.pdf]]
A salt is any compound formed by the [[neutralisation|Nuetralization reaction]] of an [[Acid]] by a [[Base]].
Used in [[Biochemistry]]
a decrease of solvency
of non-polar species in polar solvents upon addition of salts.
This effect is widely used in biochemistry for precipitation, separation and coagulation of biomolecules from their
aqueous solutions.
The salting-out effect results from the formation of ion (specially anion)–water hydration complexes, which, in turn, decreases hydration, and hence, the solubility of the polymer and the salting-in effect results from a direct binding of the cations to the ether oxygens of the polymers.
[[Salting-In and Salting-Out of Water-Soluble Polymers in Aqueous Salt Solutions|http://pubs.acs.org/doi/abs/10.1021/jp300665b]] [[pdf|http://sci-hub.cc/10.1021/jp300665b]]
[[Interactions of macromolecules with salt ions: An electrostatic theory for the Hofmeister effect|http://onlinelibrary.wiley.com/doi/10.1002/prot.20500/abstract]]
https://en.wikipedia.org/wiki/Salting_out
A small part of anything or one of a number, intended to show the quality, style, or nature of the whole; specimen.
See [[Sampling]]
The act or process of selecting a [[Sample]] for testing, analyzing, etc.
!__[[Statistical sampling|Monte Carlo]]__
Sampling from univariate discrete distribution: put probabilities on real line
Sampling from continuous distribution: use CDF and uniform dist.
!__[[Signal|Signal processing]] sampling__
[ext[Sampling (signal processing)|https://www.wikiwand.com/en/Sampling_(signal_processing)]]
[[Sampling theory]]
The theory of [[Sampling]] in [[Signal processing]]
[[Nyquist-Shannon sampling theorem]] sufficient condition for a sample rate that permits perfect reconstruction of bandwidth-limited analog signal from digital signal
Perfect reconstruction may still be possible when the sample-rate criterion is not satisfied, provided other constraints on the signal are known. See [[Compressed sensing]]
---------------
[[http://www2.egr.uh.edu/~glover/applets/Sampling/Sampling.html]]
To save a working copy for offline editing (and then uploading elsewhere, like in personal webpage):
* Go to control panel -> Saving -> Backup Url
* Look for last backup link, right click and "Save link as"
Networks with [[power-law|Power laws]] degree distributions are sometimes called ''scale-free networks''. A //power law// degree distribution has the form:
$$p_k=Ck^{-\alpha}$$
where $$\alpha$$ is the exponent, and is found in many examples of real-life networks, and in many other places (see [[Power laws]]). Values $$2<\alpha<3$$ are typical. Also typically, the power law is only obeyed for the tail of the distribution, but not for small values of $$k$$. And typically it is also not obeyed in the high end, for example, due to some cut-off.
__Detecting and visualizing power laws__
The simplest approach is a log-log plot of the histogram of the degree distribution (see [[Large-scale structure of networks]]). One problem is that the tail of the distribution, where the power law is usually followed, often has very few samples, and so statistical fluctuations are relatively larger, and make it hard to judge if the distribution follows a straight line in the log-log plot. Finding the right bin size is a way to improve this, but this is always a matter of compromising larger bins to reduce statistical error on tail, and smaller bins to get more detail of the distribution.
An even better strategy is to increase the size of bins for larger degrees (normalizing by bin size so that the different bins can be compared). A way to do this is with //logarithmic binning//, where each bin is a constant factor larger than the previous bin, often $$2$$.
Another way to detect power laws is by using the //cumulative distribution function//, $$P_k$$, which is the probability that the degree of a vertex is $$k$$ or larger (i.e. $$P_k=\sum_{k'=k}^\infty p_{k'}$$). If $$p_k$$ follows a power law (for $$k>k_{\text{min}}$$ say), then $$P_k$$ also does approximately for those $$k$$ (as can be shown by approximating the sum by an integral), with exponent $$\alpha-1$$. As plotting this function does not require binning (as the noise gets smaller in the cumulative distribution, and is smallest in the tail!), it doesn't throw away information. One way to get this information is via the //ranks// of the vertices, i.e. their position in a list ordered in descending order (this agrees exactly with their cumulative frequency, if no nodes have same degree, and this is approx true for the tail of distribution). These plots are often called //rank/frequency plots//.
One disadvantage of cumulative distribution functions is that nearby points are correlated, and so a linear fit using standard techniques (like least squares) which assume independence of points, give biased answers. In fact this is also true for the degree distribution function itself, although for different reasons ([72,141] in Newman's book).
[72] has many details including a formula for determining $$\alpha$$ from the data directly (the most reliable way), and other useful results and tools.
For more properties see [[Power laws]].
-----------
Another important characteristic of scale-free networks is the clustering coefficient distribution, which decreases as the node degree increases. This distribution also follows a power law.
[[Wikipedia page|https://en.wikipedia.org/wiki/Scale-free_network]]
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
Introduced by Oded Schramm around 2000: [[Scaling limits of loop-erased random walks and uniform spanning trees|http://link.springer.com/article/10.1007%2FBF02803524]]. With applications to [[Percolation theory]].
[img[http://i.imgur.com/um7LFT8.png]]
Good reviews of SLE for physics;
[[SLE for theoretical physicists|http://www.sciencedirect.com/science/article/pii/S0003491605000527]]
[[2D growth processes: SLE and Loewner chains|http://www.sciencedirect.com/science/article/pii/S0370157306002407]]
The knowledge, methods, and everything else regarding the //understanding// of the Cosmos. This includes essentially structures based on logic (and [[Mathematics]], in general) that must match what is __observed__ in the ''Cosmos''. See [[The Scientific Method-Richard Feynman|https://www.youtube.com/watch?v=OL6-x0modwY]], and [[Philosophy of science]]
"Science is the attempt to set in order the facts of experience." ~ [[Buckminster Fuller]]
!!!''Formal sciences'' and ''philosophy''
Lay the concrete foundation for the rest of the sciences, by looking at fundamental structures and ideas. From the more theoretical to the more applied:
[[Philosophy of science]] -> [[Mathematics]] -> [[Theoretical computer science]] -> [[Mathematical methods]] and [[Scientific computing]]
[[Portal:Contents/Mathematics and logic|https://en.wikipedia.org/wiki/Portal:Contents/Mathematics_and_logic]]
!!!''Natural science''
Natural science is often defined as the part of science studying natural phenomena (that is, those not cause by [[Humans|Humanities]]). These are in some sense, the __foundational sciences__, as everything (including Humanity) is ultimately part of Nature (the Physical world).
* [[Physical science|https://en.wikipedia.org/wiki/Outline_of_physical_science]], related to non-living beings, including [[Physics]], [[Chemistry]], [[Materials science]], and, to some extent, [[Earth science]] and [[Space science]]
* [[Life sciences]], including [[Biology]], and related ones.
Roughly, we can categorize the natural sciences, in order of the [[complexity|Complexity theory]] of the studied systems, forming a sort of hierarchy, or emergent new phenomena:
[[Physics]] -> [[Chemistry]] -> [[Biology]] -> [[Cognitive science]]
[[Portal:Contents/Natural and physical sciences|https://en.wikipedia.org/wiki/Portal:Contents/Natural_and_physical_sciences]]
!!!''Systems sciences''
Systems sciences studies very complex natural phenomena, as well as human phenomena (which are of course, a result of natural phenomena, but often of the highest complexity we know). It is the application and integration of the more reductionist ideas of the foundational sciences to larger systems.
[[Systems Science]]s are the highest level of complexity, looking at parts of the Cosmos made of many parts interacting in complex ways.
Some of the most important ones are [[Social sciences]], which look at societies (large collections of complex agents).
[[Portal:Contents/Society and social sciences|https://en.wikipedia.org/wiki/Portal:Contents/Society_and_social_sciences]]
------------
The distinctions above are fuzzy, and a bit ambiguous. This is partially because of the [[History of science]] being very complex, and with conflicting ideas of how science should be organized.
However, as can be seen from above, my preferred way of organizing it is an approximate hierarchy of complexity: from simple (reductionist) laws to complex systems.
--------
[[Wikipedia:Portal/Directory/Science and mathematics|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Science_and_mathematics]]
[[Thaumaturgy in the Age of Science by Prof. V. Balakrishnan|https://www.youtube.com/watch?v=xRjEPwL8Lxk]]
Free MIT books: https://archive.org/details/mitlibraries
[[Two minutes papers|https://www.facebook.com/TwoMinutePapers/?ref=timeline_chaining]]
Crowdfunded science: https://experiment.com/
[[Jacob Bronowski on Science and Art|https://www.youtube.com/watch?v=y1IfE4t5AuA]]
"The hand is more important than the eye"
"We have to understand that the world can only be grasped by action, not by contemplation".
We need to give "hands" to AI. Active AI (the basis of reinforcement learnnig) is being more successful than contemplative AI (supervised and unsupervised learning) at displaying general AI properties.
"In the evolution of man, it is the hand that drives the subsequent evolution of the brain"
Writting: rethoric, etc.
-------------
DTC: Choose a novel, do summary, etc.
[[Oxford course|https://www0.maths.ox.ac.uk/courses/course/28839]]
[[Online lectures|https://weblearn.ox.ac.uk/portal/hierarchy/mpls/maths/sci_comp]]
http://colorfulengineering.org/SCICOMP.html
!!Linear algebra
[[Numerical linear algebra]]
!!Optimization
!!Differential Equations
[[Numerical methods for differential equations]]
------------
[[Gentoo Science Overlay|https://github.com/gentoo-science/sci]] has a nice collection of scientific computing software
https://www.enthought.com/
http://scipy.org/
[[A gallery of interesting IPython Notebooks|https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks]]
[[Experimental chemistry]], [[Experimental biology]], [[Experimental physics]].
!!__Laboratory__
[img[https://www.centillien.com/file/download/347168]]
https://en.wikipedia.org/wiki/Laboratory
http://www.scistyle.com/
[[Sound visualization]]
[img[https://45.media.tumblr.com/f4bd724bb8ab303bc0138884e534e053/tumblr_nsrfoa6R2Y1u5zy5qo1_500.gif]]
[[Marine life]]
A [[seat|https://en.wikipedia.org/wiki/Seat]] is a place to [[sit|Sitting]]
//Seat// as a verb, also means: arrange for (someone) to sit somewhere.
The [[Entropy]] of the [[Universe]] never decreases, and in fact tends to increase..
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5+cjgAk/oLa2PkRsiyfKNu3gADBbA9+fqegyCTm5DGFyBz0ySOwLkc4/H3yBkAZNgAYIHTIz378dc/5967s64gzriXEwx2eY2eLxcFFQnJ2goxuklGK5Ukr2Xe7u3c9DiHijiHi/GQzHiPMJ4/G04xVOpJ2jGMbpJRg1DZX0Wu9+ZO9YKS/DcbQMkdTufnjkZ28dccZzg5kSIqzEtwcYXHox/QjGO49yTh+dpOF9O3uw9/b/AL7GSe768WMYxcm3u79fivraz20Ts+7TT1b+dUVF3nq276X0kmvNO2mz01atZDiCOPYD/wAe+n+fekxg4Pbrj6n1Ppj8c1KducnGeO/ucd/Ufz5ODmM9W/z/AFrRddb/AKWt5vy+9fPWzV7dWr+i/r/g3JVII4zgYHPtu+vr/Lng5oXWH5GeAMe+C59T/krz1JthMjO707f73v8A7I/76HpzTuflK4OR39OpHr6DP5+nKkk4TV1rCWt+lqmv/k/3id+Sov7j1vurVb9br9dN7Hw3+25rkmhfCXV1iuDbPd+XaBwSCTcwXcITPfeSOp9MHhgfOP8Agmn4auPD/wAA7ezu0aGeTX/Et0VZQGZbq7ikV8YGQwGQc9CepFZ//BTKa6i+EKfZvO/5DWhB2hVyQvnXAYttBwoH3ieAM5wea9T/AGFDEfgvpLpKkpae+DFJFcAkW+ckFuQeoJyD1IPFfqsoRoeEUeV+7VxsXLl3atJWb89Er7Jy2e/7a4fVvAqm4NqNfMIuSV9W41NG+nw/K/nd/bUCARkA5JBzx7kjv6YJ9icnI3Gyp2qQOvHOOwyM9/y9+p5NRwjCHA6D5s9+T7+jHuOnr1njwEbPf27DcPTJ6E9cckckNX5JGP8ACSVrQg2uijaXVPff5uO7Ur/hUY3hQUWlyQjJt3eyV3q3u7LysrpvdpkCKAvJyOTnJ5Y/1OT1HAJyd1fm7+2B+374P/Zav7ez1WzsdRuri4uIHgnu3gaNoY5ZMkLIuc+WMj34AIOfub4i+OdP8C+ENf8AEd60axaVpt7esZMY22sE0p4z6IcjPvkkE1/Lv8TPD1/+0zqP7Qvxp8QtNd+Dtd0uLUPBrOTNBaYmEcz2ccwIt2KscmM5wSM4LM36/wCD3C3D3EPEM5cVU6lXJY4e6hCUoOdacoQp6pttJyTdrPa7d7v948COC+F+KeKKs+NaFStkEMK24QlKm54mUlSo6p81uaV/du1Z3dnd/wBKPwT+LmnfGf4ZaT490lI4INT023vTFDIZEjEv2jC+YWbOPKyTknp1INfkF+1JqL/tCftWaJ8EZ5Df2Ph5fD3i1dPyZUjuLOa1lNx5RyoYGJWJxnIHPJz9SfsMeLEsf2cbnT42SKHw5o8NtE5O1nSK21GTc+TjdwQcdyeSUGfkn9jaOD4wftOeM/jNCZLhbJNb8LeY6ExiTStUvbIgMwJyDbdu2TngV9Hk/D+VZBnXHeYYZzp4XJ1P+y4yd5K/M48r3enK73u9L3a5l9bkHDGS8M8QeJOaYNzpYLIY1P7GjOTU4qSqOCi3q+VRj53vd98r9uH4Wa38KPiT+zH8SdNtp5tK8LeOjqetlY1jhsbK20W+j82ZwAVUu6qSD7ZPNcb+0L8Wz+1X8efgL4F8MTi50XUdKvG1pLaQzxecmpQiISo7NztkJHXgjjPB/Zf9oL4Nab8dvhtqvgzVDLbST6fcW9tf20aG8tZJhtM0LyEbZFUDByCN3XivmL9jT/gn7oP7OWq6nruo6nf+KtQnu4LjSrzxALa4udNiRcPFaOHkaBJGjDsoxl+SCBzrknGvC2N4Rq57mdaf+t2Ar4nD4FSnL97StVpwTi3qkndN6RSt0TfTw94h8F5jwNU4kzivVfHOWYnFYbLXOpJKrRtUpwi4PeycbS+yuVWtFzf6G/DLws3hzwV4e0cgqbHSNNtQNoHEFokQ4AAGAowOoO7nnNdw9u6jaGZQh5GPQvj/AB/IZODiW2UxYQZCqqhcE4AG5QBz04IA9MckDJdJlmODwep/76z3z/COB/eHJxz/AD9iMTLF4utj5pOtVqSUk1fSc7tWvs+vXvdn8t4zG1MZjMVmNSP7+vVmqilr7spT6dvPzs9mzLudPE0ZRj8kq4kBAw3LgZ49uQenAGQMn8Gf2ovDv/Clv2yvB3xnMBsdIe1tNAkvTiOFrnVrzT7NEMgAO6RpMAZyCQOckn98pd+wY5G04Pcjc2M8/wCBxknknH5b/wDBTb4Var8Qfg9Fd6BbMdU0HxH4f155YF2y/ZdG1KDUZvnALbfLtjuA6gkZHzE/feF+ZQwHEqy6q0sLmC9lUi3+7bqvlV4u8bXd3e7S5r6rX9N8Gc2hlvFkcqxDisFmcPYVIuzpt1/cXOnpJLm95PW+t3e7/RrwdrdtrmiaZqMRUrc6bYSrgsQQ9tHIGznuGU9SeQdxLHPaH/V5HJPGB25PHX0H/wBfg1+ev7EPxYb4k/CjQrw3EJvLMSaXc2xmPnINNEVpuaJmEg3GNjkqQdpweDn7/gmbypXIBZQuwd25fORjnPB465XOMc/KcU5PUyLiHH5M042rSSurRupyd47aP7tXey3+K4yyCpwzxRmPD0k42rz15fdfLVndxs1p200utdWWzC2wnJxtx04ySfU56j+YzgZPxt+2X43t/Anwb8YBL1YdVv8ARtTtdLXcVklvZLciFIiDjcWZQvHXaM4OT9YzXkgjkD7hgEgDdxjzMYGOwAJGc8EZwQa/EX/go1421TxP45+Ffw70Kd7i4Pj3RhrVrFKzP/ZlzPZq5ljTcTGUR8hwFI6k4zXv+G+UQzniehKceajlkPb1ZbLlpOTejv1jF76aXb6/S+EuSxz7jGhKUHLD5ND6xVbWnLRlOTb10V7N/a1avfmT9N/4JlfCq/g+Gtn8TPEFtJF4n8Y2Njd6zLNGPtDzqsL5llx8zZJz8x+bdyc8fqLqULRWNyCeMYPHXiTB9R0PXnrnPSuM+Evhuy8DeCNF0TTraOGG1tkjVFjEYAULj5V4H3fp0Azg57vXXDWbjGA0ZJwCPmGcc59+McjkYANePx7mss74uqY+TXJhcyp4Oha65qdNwlDROyVp39G9bp38HxMzx8QccV82nJcuCzall+HUbpexg4zhbXa0k2trWTaafN+F/wAXjt/bv07j/mF+HPXvc3IPc44wc/7XGQDn92fDLEabaZJwI48df7qgY4+v88nrX4U/GE7P27NMyASdM8OA8Z6XN0Bn3xgfi3Pc/ux4aA/s60OR/qoiBj2UAdfYH23HrnNfpPi4ufhvgdRVn/ZtC7vbTmg/Xq+++rsfsHjhZ8J+HLbXvZTQd9b709LWsvx6apXZ00QJSZs8LIB7HJbk8nptB/4EOQRzLISi5yc5QD35kPPPUgL2656kk01FbZLjgEgn6jPIGeSeo9iQec5SVWMYLdmUE98Atz+X1zuPOQc/itS3tKmyXsIrmvq3eCTvfe12vO+q1R/O2Ib9riGrfwIKOrs9beX3dO7TuZ+os4RSFyAfm6/KvzYJ5/P3xxkivmb9ovXP7F+G3iC+W5+zhLQ5lBI5bzxx3xhRjryTgk19LX8m0bGHD4XOCe7kkk+wPqPmIIyAa/O3/go34oHgP9mPx14ijc/6Nb2hOCePMuJ042nODjPQ45z6t9JwXQ9txzkkJ8vsfa0OZaNtSmr2V77629VdWbPrvD7DfWPErh2jVUXSVfDXXW0p22v2d97/AA6prX57/wCCPdjqNj8NvixLfxOr3vxa8XXkTuDl4J9S1KRZBz0ZWU9zyee4/aKHPkr8uQpG3qAclh1OfUt0/E4NfnB/wTx8P22h/CCC6tEAGuzx61IQoXMl/btOx4GDuMnJJznGQGBz+jlvuCkdsAjnqcN056Hr2+pAyPV8R3TXHeYwppezpycYSvsrK/e3wry1Wtnr7fivKL8Sc2hD4aMpqL0ta3Lpq+yvv0W6bc0ZOZfXp/P3/wAjHORWjCo25Y9Qp9jyR1HTsTn6ZBJNZ0ce4y56E9foeO/r/wDX45q/CWYFSPuhQOfTzOevf+ZHcHPwcW1TjZXm5Ts77p1Zed77Lurbr3U/zanG9JXtrKdlbtUmk9+q1t5taqLbsscDAxg5/Q5GP8n8+aiVQ5Iz0H4jlh69+DycYx6cvGzbg5Hb1PU8/oD+OOSCaaI23E5xnGR9M4PX6Y78kEjGTulKy5mrJLmXbWVla7d3ay66NXabNdVGzjzarTt7zS281ffa3V2cWxhuJBwBgZHXlgPpgDJ79OpDZ8F/aC0y01r4X+K9HvLdbqG60m+ilicZV0kicFcZPBHqOhGcg5r39sqNo55Bzz6uM9D/AHf5ehzyHizwyuv6de2b58u5t2ifGOAwZTgMcZ49egB6Zz6GVVo4POsrxc7qlQxuHnWnFtWoxnP2m1mtEkl3vrpK/p5Jio4HP8jx1RuFDD4/DzxDi2mqCqXqPRrpBW66pWTbP5xfgJ+1Ro/7J9n478IQaZBImg2kMPhjwubhrdNQlE1uWtoAroEO1ZJCeMgdRgGvrb9nn/gp3r/jr4p6N8PviN8Kx8PYfE9vc3+j6hdak832izgKIJIk+0SArI77ASvBHUEhmn0f/gl/oWo/tN6v8YPEus6vNo9rq0Wo6f4ff7NPpF4BG8TQXNs0gYRnzA2Np+YDtuJwP+Ch3wBb4b+GrD4z/DLQjLqnhRLCxhtLCyZWjtrq8nkuBDHaRyTYVIcgKvUHceBu/p3FZn4PcWZ3VyrE5Y55rm2DgsHncq9SKwlZ0VGhBQi+RNVLOo53TTUbX3/sPG5t4DcbcRVsnxWUTlnOdYCKwPEM8RUgsFiXh+XDwUU1BSVWzqOd4tOUXZo+/v2mv2kNI+DXwruvEsk0I1LV0+waHbtK0b3V5dwE2SQsGB8yZnTZz12knJ5/Gfwl+xh43/ao8GeOvjp4+jvrXxd4w0mSXSdIurZLi40a9guYljlhnZJS7vFK+PnJ2vg8Dm78I9D+Jn7eXjbwyNetdZ0f4U+E4NIuvtVzFe2Woz+KvD6ww3tnLp2owxFrFp4Cqzqx3o24Lkc/0JeHPB2l+EvDMeiabaxQ28FuIkjiiVQcHByq8AHBJH5nIYt8o8xw/g/RWVZFicPiuIsTXhVxWOShWjDDKfMqMW3JK9kpOOrTtdNyZ8dLN8N4EYdZPw5i8JjOK8ZiIVcXmMFTrwpYT2jkqEW+eKvyxU5Rs5XWrcW3+Vn/AATn+M+vNHr/AMD9eMsmpfDDU4fC0ZnmbzZhHDBdM3lbsR83f3MYwSck4z+xllO8kfT5vTPIOXBzyf8AJJJ6Z/ArRmk+DX7fum6VZiO3h+IGp32sXMQYRid4pLG1DsiffO2MjLZI4xg81+9WizrJBFIMESwLJnJzuZSxHfjpge55+XJ+O8WcPhKnEWEzPLqcKdHMMBg8Xi1G3JLG16EKmKlFX0UqrnKytq5a2T5vgPG3CYKpxTgc6yqlCnRzPLMBjceo2UJ4/EYaNbGSik1ZSqyqSSV0uZ6yvI2kYjeDxgg59csQe3ORj6c8nrSq/XdjgcYzzzjuT2/+ucc1CsZMjM7EA7cAE4xljySe+Bn3I75zNs59sdffn6ex/Ac53Z/LaUm41Gtfe0Wt7aJdX2v1ekrt6t/jFOTcZtp8ylZJ9m4pddtnu3ZNX0JkZQrYySw69usgHfP198/WlQHOcHHrg/8ATT3/AM+pqsQ2SD90YAP4nqcdwM+vXkkcuMjbVxjIPPHbJHr6YPUnk85GDpfd9Fy2fe9112tbXXqtU02X/idrctnfR6yvo3fotb78z6az/MeCOMjsfWQd89sH8Rye7tg9T+n+FM3N1zx64H+H+fWkBK5wevX8Pr/n607q9uv5/j+f4lJW0bv6/d3/AK83qShApyCf87vb3/l6HKN90/Uf+1KaHI68/kPX/wCt/kmkLZ47cfoW56eh6frk1DkvZyetlb8ZO3X+6/8APu/6/wAuv9d2RN90/Uf+1KF/1Z+h/wDQpKG+6fqP/alC/wCrP0P/AKFJWS+KH/Xp/wDpJm/iXy/9KKZ/1q/WsLxx/wAid4r/AOxd1v8A9Nt5W6f9av1rC8cf8id4r/7F3W//AE23lceXfHl//Y1w/wD6kUw+1U/wn+RZ+0T/AMpHrf8A7OLj/wDVmV/qy/sm/wDJBfh7/wBge0/9JY6/ymv2if8AlI9b/wDZxcf/AKsyv9WX9k3/AJIL8Pf+wPaf+ksdf7B/tN/+TQ/R0/7I/J//AFHw5+f8Gf7/AJl/2ET/APSj6T/iX6p/6DU9QfxL9U/9Bqev8hqf8Wn/ANeIH6FT+H+v5qgUA4P5c9uCx9c9/wCXOQSSmHO4ED2J9sn2+nOc4J5451avKl5X/C779oy+bj5sdvPqtfR3/FaenW+o5pGJxjp0PODyQe/0x75HPWlid8Ebe57HPfHGT1wfXHAyfmNNC8kk/Qe2Tg9T6fmRzkEU9TtPr/lv8R+Q5J5q1F87lfSy06vdXd9em3ps3dr3m3rZdNnfXfbS676p9xjMVUkDJGOP++/f/ZB/E9TT/MYpkAHIHHP+2OxPr+h5JyaawB4HH5npn1+p/PvSgcYHIAAPGePm6/X+g9DVa6666cvklzJ9Ovu9+uqd2TFOLd9nZXXq7P8AJfN7taojEHoenUjj+MevuPfnp1NALHfhTwR68/M+SOO349QM5BzWXcCx3H2AJ6Fj78dOPfPXHNmLeAxGcdAeT0JHoeP16deDWdNrWF7tK/Mltr5rd3v6d7IpWitE7PXRX7+fl+ers7qM4IIx0yPpv/z+I54OXn7q/SokP3gTlsjHX3GAM+31HoSCS854Bz7cf5/z3NXf3W007W/9KS/FL8Xo2rj0vtr3sumne/8AXV6jgTtYY4wMHB/vU+P7v+f70lRKAc5OMevfnHr+P+c1MMAfL0/Pu3fJ75/X0prVJ+S/9v8AN/yr73qxRbbd9Els+uu/9elxaKKKZQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRTN49/yH/xVJvPbGO3B/wDiqV0k30X+du/9eoElFRbz7fkf/iqN59vyP/xVTzx8/ufkv6+evUTaW7/q7Xd9vz3ad5aKi3n2/I//ABVJ5h7AH/Jx1bvtP9c96urLfXbR36f8P9+7H/X9a/15k1FRbz6D8j7/AO17Z/EdwaeGBzjPAJ59s+/0/WmtVf0/9u83/L+K1eof1/Wv9d2OoqLefb8j/wDFUofhi2MADp/vEdz7fnnk4OZUk72e3ft/Xn82veAkopAQV3DpjPvj5v8A4nP4jnOaFYNnGeMdf/1n/PrTuu/p+X9b/PcBa/yhv+Dn/wD5PjP/AGF7/wD9HSe/+fU1/q81/lFf8HQcez9uIHP3tWvv/R02Of8AgPTnqOetMD+6r/g32/5MF8N/9fNh/wCkdfuGn+uf8a/DX/g3xlJ/YE8ObgRi7sQPcCyPcn6Hg8cDJ+Y1+5Sf61j2Of1zjv8A7J/xPcAsUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFNJIBPuB/6H7/7I/M9aVTuXJ/zy4/9lHfuaAFopu47scY/H/GjcOevy9fzx6/5+tADqKQHcMj/ADyw/wDZfXuO+aRmIxjHf17fjQGn9etu/wDXfqOopAfl3H0HT6kev0/XkmmoxYnOOB2z649T/nvRpt/Vr27/ANd+of1+fm+356uzu+iiigAooooAKKKKACoHOQwAwQeo6n5n/wDif/Hj1IOZ6rMSC2P73PHbMnv7ZHPcgnIzR/X5/wCf5dhPZq1/Lvq/u7/Pe6QJgggHlQMjB9WHf65/xzR/Cc8cfXvIP8Dj3AznkwmQpv287hnIOCBkn14+6R/XPUV2MZJXuvBPUEyZ5z7Ag/TqBk4uUf4bbdmru3aTt185d9bK+qMeeHNyX1ja6s+lutrP09dx2fk9wQBj2PU8+nT3700scHnjHI9cFj0z16nHPUc4pu7JwAevTPTk88H0x156ck7qpahfW1hC09xIqxqPvsSAAM5OBnj0H05PNLWbcYxlK1koqMpylrNrkik22/K9rrTVmiTqc0YQlUk1FU4whOU5NuS92CTk23y7K9u+rLCdSy5wMZXnPJIGPp1IPYKSMkk3o+VJJ5AIHB54bnOfQ5PXnA6g54zSfEWm6nctDZXsc5VgrBC3DE8ZyBxjn375+9XYIDsODye/IxksD3z/AA/mR1GTThCpRlONWjVouytGrSnTn5e7NJ21uunvXbdk2oU6tKU4VqFbDzSV4V6NSjN7NPlqRjKzTbVtLX1s7juBk54wB09Gb375/wD15p0fzHjnBGf++pPX2/zmolJbeh7Dg+uGOe/0568nOccuQFOAeo5x9SPX+vc88c3C3Jo21ePTrzS/C79bc2t0ruL9xt7K1rdVzR8+8Vfyb3Yp6Ee3/wAX7+4/Pr1rn9Vi26bqD5GY7d2GPq3GQc/j9TzkkdCcbSecgH6dTjv6KSf8euBq7f8AEq1PPGbVwc5B6tjHP16nOPX5mqqcYyr0lNe79Yw/le1Rrq+nr1er1b0oxU6+FUleLxeFck3a9qmnXa17+fLuz+anXfgN4K/aS/bT8a+HPG8V5cwReKpbeDybryhEsod3wXSTbkk9MdQDn5if6EPhh8M9A+GnhPT/AAp4dgW2sNOtbazQfJukW3jMatIyIm9iOrEbjnOTzX4p/CJpI/26viO0DlZI/GCmPGQW/dvjGTxxknn0BOa/fC0D/ZLZiOWiRpOerfPlsEn0z7c8Z5b9l8VOIuIcZguGcnxebzr5PhsBh/q2AjOTp0WuZJuGybUVe920kndrX998a+K+Kcdl/B2QY3PJ4jh/CZbhVg8tjOTp0GlJJ8l7KVopX3aVtLa8BrPwu8Ea7q4v9Z8P6RqNyoiKy3Wm6fczAq0pU+ZNbSOAOcDcTnPJOTXoWn6TYaVaxWmnW1vbWkA2xw20McKKnIwqRKiL0U4AAHHGM1YWANKWPLYGXIOdoZ8Dg468j69elXVQJuA6cD8iwHbnkEn1z2JJr8cq43MMUnh6+JqVMPQ5VRhKT5IJNrZy7Pa3zbbZ+C18fmWKpPDYvG1q2GoSj9Wg5y5Kcby5FyuWysrq3VLe94ocZOwe3GRjlsZ9ePXj5jySDm0Udo2GeeM/izYB575/pgEZLUwp+XjJHfvlxnqcdM47HHJyanO7b97r05Pr349Prz3zWEElCpu7yV3s91tp8/m1e6ucsKfLTnB3d5La63bbs7+S+966yZXj+TIxk8Dr3ywPbJxjj2bqTzVlWGMbQff6F/UH0x+A5OaSOMHJJzjGO3IJ+vXrnOc9zwQqAMTnsO31x6H/AD3qlooxWi033tf1e+/fpdblxjypRirLTe2ybv1d21rvptdu1hcM/QAf/tf/ABP6+ozUuB6D8hQqhc4zzjr7f596WrStfrd3/rX+ulnqUklfzd/n/XrbvfUaVz37AdPQsfX3/wA5ppAVcYBPPOOerc9/UfkOTTiG7HsO59W9vQj/ACKFBGcnOcY5J/nStq7Jpv7Xo1bRvt/w7d7MYp2AjGc89e361QvFK4wc8ADI9Wf3+v6e9alUbpQx59Fwf+BTf/Ef+PEZyM0pRXs5Lf3Gv/TifXrZee2rtdy7qFXX4qckvJ2nZ733jf5rfl1+Tv2nPB9j48+GniDSLuESTLaTz2rMFKpNBaXZhbBDfdk2t2OCfmyAa+C/+CaniHx34dtNa+HHiW+t7yHTL3Wby2aKNwVS51KVYlZ2mlB2pCowDx83HAz+oPxIjibQNajI+Y6bekN1wPstwOep5IHHfjnA5/Nj9i/y7f4seNI3UMEtJmVzxz/aN5xjOcjHXnnaDjO6v1vg/FQreGPEeAxdBYiND2VXDyaUvYSbmnJXdlptbTffQ/deA8bDFeD3FeWY3DrFrDOjXwtSUb/V5tzjKabXuvltaz+093HX9dbeWQhs4wQM8EDqffPUDj26k5rQZvk28AbQScDk5bH06YHPY8gk1lWM0ckTncFBAPOf7xH9M/TtkHL9QvIbO2eZ2DKiMxGewEhLYPt/QEHmvxyipVqcKcXecqns03dNpTlFRWt9fdWr79bs/AsMpV6cIQV5zrezgk0tOeyjF3tdPo3rfdcuv5x/8FGfiLF4I+Fsmkvc+U3i2afw5GokKPI+oW3lKiANkuTL8oznOOMZr5u+B3wInh/Ya0zwu9lKZR4YngmUx5vJMy9HkILsxwCCxOD3zuZuP/bH1lf2lf2j/CfwR0lvt6+DtZ8N+L7qGMmTy4EmgMrtG5wqjymywGTk8kKK/a3wb4K0zRPBdv4bhhjjSO38krtAABLfwhfYZHuDhs1+2Sxz4GyLh6k6ahjcV9Wxsnb3vq93NRet72a8/htds/oZ5hLw54d4WpzpKlmOMeDzCd0ud4VuM0pK7d7WvFtu6el1c/nR8FftNaf8J/hR8TPBtneRDXtO1yy0C10ZZB/aEsdxBewyMsHDuEMibzjgtGOSAR+k/wDwTj+At18NPhjdahqVu0d14k1vVPEhaVD5gTXL+81RVJbLdLwALu9Bwa1dV/4Jofs93/xMufiPc+FdHbWbq/bUbmY2cfmz3TSxOJS/2blsxA5LE9DyRX6K6DosWg6XZaTZqIraxtbW3hiUYVYLeJYowAAOFRVGO2V6jNHHHHOTY7LfYZA3PEY9RqZrJ0qlNqo4uHJeUUpJJOV02vfWreovEXxJ4fzHJ3h+FpOpjMyUa2dydGrR5Krgqbp/vIpVIpJt2fVWbTkzSgto4kmJQMNq8FV/vNgYOeuD2GORgk8xwWw3SurYUsDs5BHXjHQE/TPBx3zpnDRNt4woyQO+4+/A/UDuThhHEihcY6/x/wB45b0IHTp16dyK/EYUoqKg021P2kGm0uZuSat2dm9312vZ/wA70acUoRcX7s3VhJOy5pX5rq+l03fpay3bZMEDx4U8rjnnpl+vqTgfjjtvFNT5t+cfKOuOoBf6+mfxxkHJICyKVAJyeo7jLe5+pz/sgAkE05WwHUYPADZyfUDv3xz198kEnVpOabWis5PvrK+13fbo9bbtGz5XNtXa059H3VmtNXtvtdarrGqjac4wQOoHHLjrk/r6jkHOeN8Z+GdK8T6Bq2kalAJYL6xu7R1IQgpcW80DEbkYBiHJVgCQSCMkZPZHAwvYn3z1PT8sn04Ge7QzxLIhQ5Py/h1YDv3K++OOepO0K9TC1IYrDycK0ZQlCaunHlm3fvd8q31uulnfShiK+X1I4vCzdOtTnTlTqpvmg4zbj102Xd7K7uj+ePwrqfiX9jv9sK98HJK8Pwu8X32k6b4ctZRIzrq9/d6hNf8A74yeU6sZYCESFCBgFyCCP6BNLu4L2CK4Vly4VuCMHLHt36cDkZzyQOfyx/4KRfByXxD4R0X4kaWxg1T4a6pceLoZkj3OJLGOAptfqjAx/eBBBK8g175+xr8YJPif8APBvijVb/7Zr9/oVtc3Zd2edbhpph87EkEkL/ePB4IIr9W41hHP+Esr4yoQniMZQpwoY90qc54ida7tOUIRlK0lGyvdtyejbcn+4eIkFxXwPlHH2FoyxGPw1GnhMzdGlOriauITajUnCEZS99RaXNZvnSSd5SPr3xdrWm+HNC1bWruRVisrC7uJAWUHbHbzysckf9MgT3Geowc/hf8ABfRr79o/9tDxf8UlZb3wFaWtlZaVGwMqw6vpF3qUFzIJHYxA70jwEiDDu5wDX03/AMFAv2kbHwR4JHgPwpqSap418TtY2CaNayvHefYtRmWxvJQHKKUgjucuN5J6BT0b0z/gnz8Arr4OfB2xt77P9oazd3+uzhohHIh1qY6gUbA5KvOy5BOcE7iVJrr4cof6m8B5jxJX5sNmGeU3h8BRqxcayjKLc6ip354xleKbaV3KKeiu+rhPC/6g+Gua8WYlSwua8Q0Xhcvw9WLjiOSUZSnU9l/EjB+6ruO9tWlNv74ttLhgtktwF2xgBcEc5ZhwQR6HjqBjk4ycvXYttnIoI+VMDjsPM9/c/r611SWzKiEv8y4DA9z8w5x+JH48ECsbVrOSa1mRckE7c/8AfY9z/d7ZwRzlST+IzlKo6E6sn7WeKjicQ7XtLnWr16Rj/wCTW3ufzrWk6qw1atzSrVMdDF4u6b5Zuok5O7erhGNtWk1u2fhf8adOa0/bT0fWbmWKOzms/D1rGz/KWnF1MAgYtgsSy4XrwOSOT+4fhgIdOsiD1jiB57FYySOT3x+Z64yfw+/b80vW/AHxT+HHjf7JLe6VP4u8M2lyVwkdrGmpWpluWYsGKosm5gMnAIBJBJ/Z74U+JNL8WeENG1rSbqO6tZ7aJ0miJKsPLjHBOCcbx24yO4JP7b4mv67wlwhi8PL6xQoYOlRqTiny05qVL3G77pRk7brTVts/ozxhlHH8DcB47C2rYbD5fRw9WrDaFWMqV4SbVoyuk3f7NtbrX1BQFDsDnBUeh5Lc9exXj+ZzROMxcnup9e/9dufqMZyOXCM7JCMfMykdegLA9uOAD1/vc8csdlMcj5GEXJ9tol65PoOeevc4Ir8VnZznHmunThy6O7d4ppa6t/Oyavrq/wCfJxc6s4rXmow9n/ed0nbXV6pW8/VnF+KfE2heG7Ca817U7PTLQIxkur2VYYIlUlS7O5IUDIBOe5z1yfyH/wCCmPxJ8NfET4Aap8NfA2rWWsah4ptLZrSeznW5hmEF/OGZApBZWBU8Njg85rm/+Conxc1bxJL4T+CXw/uJLrVPFWqXmi69HZufM062lhmkhmnjcqHVntWVVG75mJIyBn4M/Zo/Zv8A2j7r46/D/wAE+L/CGu2/gTw552mv4puVtzp5tkcSxzGJZ3kVZWdhjyhjaMkkEt/Tnh54acNZflP/ABETiPiCjl+Ow+HnVwWTVIVXVxMabmqVSHJGVlePPsr6auzv/YPhX4ScIZZkf/EVOLOKqOVZlg8LVq5fkVelXlVxXsudUKsFCE7JtRnHZX5rt6s/oT/ZP8EJ4Q+DfgqxWNll/wCEd0FrkN1+0DS4FkwM/Ku7dgZyM4ySCa+roY9igdDxkYHPLdsn29MEDudxxPCOjwaBoun6QjB1tLG2hyAVBMUAi3YJGM+WG9ep6rz08aqRuf5s8Djphm5655+XP49Tmv58zjGPMs5zXMpVnUVetJQbUk4xUpWVmr3a5XtfSzd73/lrP8w/tjP87zaVb2rxGJqKnNqV4w55cujWisk31s1d3veOFAPMY98HOODzjjJ7fXPUEkkYkh3KTkcH256uPr0P1OD3yaeOvy98Y9+T156f0xntTvn3c5xjoMjuwznJ/wAemTjBry4U+WKaesbWst7uWui9dLbX0b1XiQpOyXNZ02tUtGm563T6+ervvdMM9QF5zwe/DNz0/wBn9epxmnBdobaTk47+hxx6ZH+c80sQYluSM9Mk8YLdPYjP68k7qlCPzls5xjrxgt+fB79OepJq6a92dnq356brvu1br/L1TtvZ8rW7017tPR79td/W7IFPO1hzj73Xux6/iO/YfWo5iOV9gD9MsR3+v69xmrRUgZ44I7n1bHb2J+p9yarGMnczNz6jvy/tnp09eegBpSV1y8z0smusld367ve3a172M3eMNdU7cy2fKufbrdat69tb3MmJVt5532g7iMDA4OSDnnnt39OvzVX1TQ9I8R2Utlq9jbX1o+wvb3VvDcwtgy4JjnjdOnQFTjJ4POdiOFWaXcgOcZY8bhkjnk5zweenPOeKk8kJnYdo4AGM/wB/rzznH4cckk1NCVWjVUqVVw5bSpvX2kGn9mXbWLjrvdW1UicPLEUa0K1Gr7OMLOk7v2sGpPaSvbXbW9rN6o4zw/4I8MeGHddB0fT9KjYlmjsrK0tELOXZ5NtvBECWJyzYBJY5YkEnqXSNd+GBDgZJwQeW+7kjnI57j5cHBJMvlnOSf3nAZuASgLAcegBxg57c5JqtPbM6sEOAoDJwflbLZI568HPU4x1xTxWIxGI56tac69aCSdSTbk43lpdu7815tpdXpisTisRKrWxNWpia6UVGpObcmk5NpOUm1t6batqTf4A/tXRweF/+Cj37PF7cTiO2utF1adyH2rj+1owN2CR/AT06EdBuFfsp4P8Ai54AuhY6YPFOkjUTBAq2pvYvOYHaijyyc5yAB15Y9zmvxw/4Kd/CL4uX3xp+GPxb+HHhbVPFDeEtDvbC5t9O8lCJrrUJ5FLSSSR7SqorY3ZIJ6lSa+DNb8L/ABm/Z/j8B/FD4ga3qLa74j+IfhHR1sbtfKntNN1rXrGNLYyLIQUhSfyz85B54JJLf0tlXAfD/HvB1DMsfxTRwGa4LA0lQy7lqTrV3Tpu0VGMJWslFOWyu/es3I/r/JfDLhfxM4Cw2b5nxpQyvOcuy6ksPlbp1amIxUqVJqNNRpQn8KpwUpP3dU22k2/6+EmSWMPGyupXIZTkEHJHOenHHpyOoyZkcABe56/Xc3T8Cc/hzk15x4C1CW78MaTcSyFmls7ZySTkloYyfxyQcDnkZO7Fd5E7EszN8o6cn1b0/wA5IwRg5/m+tT+rYnGYdyXNh6sqV7NJqM5RUno9Wo6LVrVPo3/I9ajLDYvH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zzCbVb/KgD7EDQCi8KkQABbFgE+1Aeiq220impyMUDqfaRREMK0D4aYNINC0DRim8UUkmI4iBfhMG4Atkk+EMR8AUdDMgH6JfIChOoqmR/XkZPPaa694/PGH/+ySt+9RraouoxDXNsCVE59K27UPsF0bY+C2SgZ8rnUg0LUNBLpmAGMbM71vil8QilYbagl+lgEct/MRAOFEGfBlpR/0/RwC8K9dj9s566L4Vx1zAlul2siB8yepXDvHdNf/tGtu4Ud2lGnjRB+g52NUahnYRVRP1kYfe/SuPebM/aMLL8xiqaXAcoRUJrtOOgHbNaY6Ca4Z8LnWgR34jkIuxoy+Z2D/jHK5s+4+thrQ46YyGS9QKqlHbwClkhoNkwFj0waEXfMq+QJgRDXoq9sbgJ7h5CQVi2p/LhnQt8cAwPt/yACG8tDjae+fIQBGsI6g2gBYNfq7iEol1YYWTCMiRjDNQLhpAwg0bQOGaX3/DKdphOoIpg3AFsknwpgPQICZHhalbwojAPobxzfetKj+13/96lMrfvve886rzJ69da5tQK+cHKOmu/YBtms9bsrpGoDgWgcCXdtAoGsA6f4Zyg7mT+DfbJZGR9X8TH1+RibjBvhEAEmignlkII7V7g1Io6MUx51tNgQA1Q4tRwD5fGcNRB3gDAFgA4BWqwuA7mGOwsHaiMBkQO96AgBReDwRABalL9bmVG0ArHpL39ToqLpn+EyjIIJpHQg3bQCBpm3AMI23JZhG74Jg2gBskXwijPmAJFHdIQxwUWVAV43ukJ2vemho7Kc//ZcD9tzzste9roydJMJd2wBXTlQ427UPsF0bfVO2SvwruNaBQNc2EOiagXSNwnQe+Ct+Hni7DcN9feqekc4DT+eBA+jtbX39658cHn7p8FNOOGTRoiif3zrX6TzwdB54Og/81TcPvNlotBsNHMObS+eBp/PAATz55JP33vvzSqHwpXe+s7/VoqGhrXOdzgNP54G7/v8s9fRQT4+ShR9wJ0fMIMaafEBPj2rN8XHE2soAx7HheL0+JX8B4M5EPAXokXAGwBnqgYP8SOYDUHIEHXKG+JqWATwuIUQPgP6OBIBFMeBTbQA9PdRsNlutXz700JoNG/r7Z/f1FfA8JJhGfIpgmoFw0wYQaNoGDNPoWxZM41MvmDaA7TGNgCi9UqOoMqDnz/GoO001Ue2ee24YHHzxiP33P3jhwm1xbQP6W+JWgu9i6IDtmldQ97kGILjWgUDXNhDomvNJY23VnAO8jF/tlw/g45gvGg7YBZABXxn0g76fQwD02zoLJgN2Dr4CGMDWqtbzSZLB4eEf3HTTS0PDn//CfxcKFd7tZueb7vomuuZmH5FNG2/BmdWOMu3Mx64UQjl50fqdpvqFF9beeuuPivmef/rIR7bRtQ0Euu76RTFdrm1g2740ZvQ9AyNo9Xpn0jym4/MINgZJfYBxHC9MlhYAzKnRjzMmA+iRRIMUAF6MMWBkiCPIVgAQ6eErmACgAQEzAIw37gNYFAM+1QbQaFCj0ZiY2Dw0dOC+h5xwwnmNRjQtpg0g0LQNGKbR8SCY5v/UZ9oAts+0+p4RKrUNGG8cgZo7TfWqVU8+++zjF55yxjEHHKDa+lvr2gYCXduA7Rp5Cq4BCK51INC1DQS6ZgBt+Rl9z+jtpb6+zkJgfX1T9jXmMfC+PjdQqagRKgAYBzPGwG0AHSJo5QHo61PlkQFjhCqbpWpV3dsMgDME4BwutIF2mwoFNWgPoFpV1UgGjO2+MWjP23oLgD3w6lNtABA1OUnZbC4f9fXFXFKfaQCCaR0IN20AgaZtwDCNMV7BNMI7BdMG4BSJE2HMB5RKatKxPsTNqgVAV42RwZ2mulhsfOc7H60Uei47/3VRX982urYBrpz4VDpdOwHbtTEGbqvkIW6fax0IdG0Dga55kJxD7WfuPaNWo6EharXUAFEc0/CwGlnTx8CjyA202504x+FharXUGLgMGAOvAJC/DNgjVNmsOtEAOEMAzaY5XOgEECXMa5kND3d2SpcBfYgbAETx0JkPYFH6YKBTtQFA1MgINZvt1pSS+kwz4DOtA+GmDSDQtA0Yptvtzs7rTtNYZU4wbQC2SD4RxnxAq6WGXRngonYFWLUxLvtyq37wwf9Zu/bpj1x88WkHHeT4XAS6tgGunPhU2q59gO3aGAO3VXJDxOfaAEJc20Cga6SRETUnfKa3MyqVzkLB1eqUmEFuZ1SrbqBcVk8BALDOsP7M5gTwRYXnGgDVqno8kQFjxk0mQ5WKajkaAGcIoFhU68zIAEJp0TACUK3yk5sEGM2IOFaigAmA/XDrU20AEFWrUTYbZVqVSqekPtMABNM6EG7aAAJN24BhGtPIBNN4tBVMG4BTJJ/obIgAQIPMaEawagHQVWP+9c5RvWbNii9/+Y/6yuUlxx9fnDt3yhLfW+XaBrhy4lPpdO0EbNdGO8NWyc0In2sdCHRtA4GuOZ90LXSq1VQgGm7FmQyNjKjWqN7OiGM3kCSdCS8jI9Ruq3aGDMQx1eudpwDMIUL+MoAICjwFAMjlOk/XOsAZAmi11COZDCRJ54GLAfwrA/rjEgCI4scTH8CidMCp2gAganSUms2kNaWkPtMABNM6EG7aAAJNOwHdNKJjBNNRpACfaQOwRfKJMOYDsOwQvqB4mE+/RD5AV41H252geng4ufvu29auXfnGU0972/HHx6Oj2+7aBrhy4lNpu/YBtmujnWGrBCC41oFA1zYQ6JqBdE6f6s/m+S+8ACQv/YixJgHQj+OFxV8FAJN9jAzxqwxwwCv2aeGXjgEwMkSpEDknAFgv01cwAUCZMTSHX+037gRYFAM+1QbArzimqO38D3eOaQMING0Dhmks1yqYhhLBtAFsj2l0sgqV2gno7wirfe4E1Zs2PXvH7VfEUbT0+BOzvb1qxGPbXNtAoGsbsF2jOSK45mVrfa51INC1DQS6ZgBtlxl9z9DXkSeS9sAQANIWqedvRgHwrbOPe5gA2Avi2wVz/twV5sXxhYIJgL5ngu//cgJbq3pqPkkct9vtiKbZtA5sFez8T7k8W7WTiBPbcaYVJlRqGzBUC3VnB6p+5JH/efKph8479dSLX3vq9rq2gUDXRN03IfFlwiqJurj2vSPBtQ1sVU3lPGf0PaPZVFu/oVFWq6kfeAQbfVN83AByuSnHseUW+g0FAJ8tHAfA2coAcsajEwC8OH8GOEMAaP+2Wl0AzE7SM2RMBlqtTscRAMOYAPCEeQA+1QaQzVKt9sSKFQ89+dSBBxxln2eLNN6QDISbNoBA0zZgmOaq5zONpx3BtA1sh2n1UAvAqdoGDNVYUvJlVb1x4+Zf/eoXtdr4h972tjmFQsfItrm2AT6OT6Xg2gBs17w+l881AMG1DgS6toFA1wBqNdUblrYzzKcJjGMbe4n5AOc+fTIQvtWZcUTYRcsJkH9zOB8gF8wH2M+09mOOE9gq1ToQxxTHH/v2txsJvf7Cj0y7aWHzuMBLIewd5zQtbA3nBLbPtMKESm0DRvntveN2uOrly3/+85//4OzjjnvdkiU0NLS9rilgn77Ai2G7Juri2qg9MhDomqjLLo9dL0a6FjrlclQoUKGg7qV4NuE1ndF/h6hkJ1AoqHAIAIWCmiopAwjWwS0dQKGgbuAygKgGXFoAKDwwHdAzxAsTrmQAGeIpBkChoMY0ZQBLOqMiAoAoYAJgLMAtqDaAQoGSZPWGDUcdddKSJafjHXBJfaZxQQTTDISbNoBA0zZgmIYhwTRMCKYNwCmST5yc9AJ41/pS53pRBUB/43g8e1lVt1r1e++9Pp/LffY9l2XKZarXt9e1DeiVs9Vyu3YCtmv+q881AMG1DgS6toFA15wPr+k2c+8Z9bqKqkbURC5HY2Oqfa7HTfHW8AbAJzKAuCkZQOwQr1Rs7PAuAF13eNcBHAfAU0ZkAKPceoa8hb0M6EFNACCKqAvAovRFoZ2qbWB8nJIklyvW6zm9pD7TAATTOrBVpnUg0LQNGKaxQoRgGr0LgmkDsEXyiTAmAAjVYYCLKgO6aoTqvKyqf/azK26++aolhx52wMAAjY3tANc2wHULn0rbtQ+wXRtxU7ZKAIJrHQh0bQOBrhnAHXFG3zMKBZo1qzOLYtYsFYNsr4XuBCoVNdkSANYZNiaK2wAebnHHBoB1hom6APosTQD9/Z35pTrAGQLAxinGlFkbwGMFwiQAVKuquSoDxlLnuZwShbBuAXAuwO1UbQBblnSGg1KpU1KfaQCCaR0IN20AgaZtwDCNKQGCaaxLLZg2AFsknwhjPqBcVn/Sp1+gqDKgq+7tVY+2L5/q+++/pjeff+/bLtnjoAN3jGsb4MqJT6Xt2gfYro35GbZKnn7hc60Dga5tINA1gGw2XQudaGKCNm+mRqOzUvHgoFqfU29nJIkbaDY7O5lgdWa0M2RAn3wMoN1Wky1lwJ6lGcc0OKiaqzrAGQKo180ps04Aq7jjsQJAa8vcBxnQmxEMoGAywKIY8Kk2gC2q63UaHFSjiRwZ7zQNQDCtA+GmDSDQtA0YpjHVVzCNSALBtAHYIvlEGPMBjYZ6tGWAiyoDumpjbvKOVZ3Lte+552cPPnj33nNmHT53Xjw4uGNc2wBXTnwqbdc+wHZttDNslTxI7nOtA4GubSDQNW1ZU31gIB3P2DKegXUF0Nto3DPQDeoE9OEK9J9iPEMGtnk8gzei83X9MuDrRJeB7RnP4DE6u2NXAIwvKkG1AUAUUSZDvb1kjGf4TIePZ4Sb9nWyb+2lCB/P4GFX2bQBOEXyiVhu3wlwF7peqY2hIycQ2Me+/arr9dE77vjPsbHBz//vPzv60ANU0bfftXM8gysnhhNs107Adm1veGyoBCC41oEdNZ4hX4x0PEPdhBsNajaVUPyQyajjGLMVAF70Ecd5XVsZwFenvswk5y8DaF3ywpZ2/gwYGfIirjKgL1sLwMAEAEtR8bK1hjEfwKIY8Kk2gC1vHINH9nm2SOcb8gHhpg0g0LQNGJi+1qrTNK866jNtANtpGtshOj8uPsB4R/xh2rGqm83koYfuefTRB0q9hT845ZQYk9F3lGsDMI4LF8MAbNc8i9vnGoDgWgcCXdtAoGsG0nVt1SRPNKdxC8GLh/PwOfABeEEo/6rnKQB6hkb+PgBPHEZJ9PwZsAvM+QiA/v9yhr6C6QD6cHXAwHyAnYNP9VSg3Wzedt99I+PjmUwuSWL9PJ/prXpD4aZtxyGmbcDAsFyFYBrLVQimDcDOwa6bTkAvj7OoPsDAuDw7VnWtNnn11d9dt27Nf3zmM8VcTi2it0Nc24D9lgzXPsD5PSC7dmboAwJd20CgawbQGpvR94x8nkolKpeVrFKJ6vVOzCDGwDMZL1AqqQYggFJJRVDIADpEUF0AlMvqwsiAsYIYdiFGm9cA9AwnJ6lYpGy2O4CmKBKAUknVEhkwWtksCj8IgBHgKaieCjw3MnLpV79arQ4sXfqmefP69JIKptvtLqYZCDdtAIGmbcAwjWFXwTSWxRNMG4Atkk+EMR9QKqnuGb1So6gyoL9x9N+8HKpfeGH16tW/XXTIEWefdvoOdm0DeuVEm9tw7QNs1xjBFlwDEFzrQKBrGwh0DYBXe5zR94zJSTVGjX+zWRodVU0wfQw8k3EDfCKAJFFj4DKARh+vIDY6SnHcGSoXAFQ7jFAByOc7ayDqAGcIgBeqlgE8dXPkJtZGBCYD+hA3AIhCz6kAsCh9sTan6qnA86tWjU9MLFx49AknvGVsLEZUs2wagGBaB8JNG0CgaRswTGM7NcF0FCnAZ9oAbJF8Ioz5gCRRw64McFFlQFeNYdeXQ/U3vvGZoU3r/vCcd1aSNo2M7EjXNsCVE59K27UPsF0bY+C2SvwruNaBQNc2EOiagXSNQioUqL+fyuVOJJy+krkea+sEKpVOgCduxVjUTAawMCJi+wBgP5OugLEjSi5HfX3q8cEAOEMAzu1pbADNCAQHA6hWVRenDBihtNmsEoVQPwFwhtI6VRtAuUxRVK2W58zp4fhODml1igT8ZfC/AAAgAElEQVQgmNaBcNMGEGjaBgzTvO61zzQeAQXTBuAUiRNhzAcgKNkIpWXVAqCrxjPrDle9efPIffddf+pxx176ljf2zpmzg13bAFdOfCqdrp2A7dqItbVVciitz7UOBLq2gUDXHIybxtrSxAQNDlKzqSLkooiGhqhWM9sZRG6g1eo8VgwNqVkwCEgVACPAE48PiISTATsSLpNRBTMAzhBAo2EGHToBzGDi2UzDwyrADsNiAqA3IwBAFIfo+QAWpQcdOlUbwOgoJUmzmQwOdtYG46BEp2kAgmkdCDdtAIGmbcAwjYdIwTSeFAXTBmCL5BNhzAc0m+rRlgEuqgzoqo34zx2iemho7K/+6t1EyRF7772gpycaGtrBrp0ASoZPpe1aAAzXRjvDVsmNCZ9rHQh0bQOBrmnL3k3c+TF9afpXSUxTmtL0SkyPP/7g448vnzdr4DNvf3vvLhADmqaZ0c7o6aFymSoV1f6qVKaMBqJvKpfzAtypBQDjS/oYuBPAwy1Py8RfeaRLAIwRqjgmrKtjA5whAExS1ce4nAC6nngiK4bO0KaWAQzloVkGAKKQvwAYA6+CagMoFokom4lAwTRvh+cznSRdTDMQbtoAAk3bgGEaw66CaQy7CqYNwCkSJ8KYD8CGhvoQt65aAHTVGCfegao3bRq6444fb9784tuWLt174cKXxbUNcOXEp9Lp2gnYrvUxcKdrAIJrHQh0bQOB1RoAvtlm+j3DWG8qn6exsc4UbrTRsFi6E/CtNyUDr8r1pnhtcQAQRdQFYFEM+FQbwMQEETVbCRbv0RdBetWvN6WvZi2YNgBbJJ8IYwKA7hAGuKgy8LKuN/X006vuuuu6PebM+8fLP6C6f3e4awpYb8pw7QNs1yiV4BqA4FoH0vWmdl4y1kL3re8tb39D1lroMuDb3oS6bUYjrFRsAM4M9UWhfYBv7WUZ8L2IujNO5xSw0xCZKzpPi+muC3QHXgphfW7nO/KtZu0DhEu0bVeSui0vb7xxe33u7VCdPPbY/S+9tO7973n/wKxZL5drotDaI6yF7nONMQ/BtQ44XetAoGvyr4UeeDHStdA7cTPoD+VNEGEKP2BDUyeAfWH5eD6v9iqRARxHW5V3lgUmAwiEwGcAgJE/A3qGePEWlQKAzS/xrMEFZkwAMJSHuaMAjPx9AItiwKfaALJZIoqjaNpNG0CgaRswTGP7TsE0Il8E0wawzaaxYyt+9al2AnrBeM/XHaJ6cHDdv/3bny86+KC3nb5kW6p9oGsbCHRtA7Zr9BQJrnnrVp9rHQh0bQOB1ZqBbHbG3zOwYlcmo6aP9vQ4mtmTk5TPuwE+EUAc08SEqmQCgPsQjgPg+asygK5StBwB4IUrqgOcIQCsocZTOn0Aek71DLNZ9asM6GFRACAKnwoBYFEM+FRPBZ5++ulWq9VOIrxp/F02DUAwrQPhpg0g0LQNGKbxRSSYxq4NgmkDsEXyiTDmAyAKUxQM1TJgqMYchh2i+rbbrhkc3PimS956+J57bku1D3RtA1w58am0XfsA27URN2WrZMDnWgcCXdtAYLVmAGMbM/qeka6F/gpcC/3xZ575h6uuarTap732glmzzAW607XQX91roT/xxL1f/epHdt9tt+OOPTY3e/bL6JrStdDTtdDtlK6F/gpcC331k0+ufu65044/86yzPrh5s7lAd7oW+qt4LfRcrnXzTdcQ0flLTll60EGEy/8yuaZ0LfR0LXQ75fNULFKxqHozjaV58BSQyXiBYrGzLk2joW7CeqytE+D7OY7jKQadjzKAK4p6BqBYVLP5DUDPsFajYlEttigDaEZwlCHKj+aqDBjLSSVJZ4EdGbAXOfKp1oCkpychOuKwo8rlWDfNJfWZRoyuYJqBcNMGEGjaBgzTuOaCaYR3CqYNQFhvCsZ8AIJI9VBaLqoM6G8cnTfbr3r16ofvX35jHMcXnnFGtlKZckvY4a5tgCsnPpW2ax9gu9bjppyuAQiudSDQtQ0EVmvOJ10LnRoNqtUol1NeajX1A+p+q6Vajr29bgBxcmj5o+OlVlOVTwAQy4HjHGmHX2UAOSN6GgCXxwA4QwBoLWEdVwFIEoqiKRmyGRnQQ2kBcMG6AkaAp6CagXqdiNrNtv53LqnPNADBtA6EmzaAQNM2YJhGuIBgGpEvgmkbMETycVbuBCAKTz6GahkwVCMedXtUx3F7+fI7V69+7AuXf+CcIw6lWu3ldW0DbIrDvg3XPsB2bcTa2iq5o9DnWgcCXdtAYLVmAHfEaU3pPPA0pSlNQenFF5+///7bc9nMO88/P4/hhzTNvLTL7NPHu2jhYUHvm8ImXE5A34YPu2ghIFUGtnmfPrQWEUbt3GaLAd/mcDKwPfv0ZbPqaYs3LMPjiQwYHSKCah3o6SGiTC4uFKaYNjY02559+sJN+zaP29pLEb5PHzToW8M5TRuAUySfODnpBXhrOKdqAQjcOy5c9T33XLXslzf+r/POW3jggbR588vumlz79HHl5H5Aw7UTsF3zX32uAQiudWBH7dMnX4x0nz412qPPA8/lCBOLjTFwnt5pAL554DLwqpwHzkPcACCKqAvAovRFoZ2qdaBWoyRp1tv632fOPHAedgXgM20Atkg+EcYEAMOutmoZ2LHzwIeHx2++6Uezqv3vO+fcaHx8Z7imgHnghmsfYLs2xsBtlQAE1zqQzgNPY23TWFsJKJcpjvOFTH+/IwA0jbV9Vcbafv/7X3ziyQcuOO20hYcespNcp7G2aaytI+HBGS80+oyXftAJ6Md5v1AZwPiVnSFRF8DIqmshw2EGhIIJACY9GaSBOQE7B0F1FFG73W61hkZG6o1GFGW6Xooda3p8fOzee2/97W+X7777gvPOe/Ps2fPb7ciwG27a95/qe3cKpjHBWTBtAFtveorJrqqd/5GuGr1E21apa7Wx++67de7AwAcvvng2VtPbCa5tINC1Dewirm1gq+xxNMGMvmfUajQ0RK1WJ6x7eFi1Z/W+qShyA+12Z480hHWjb0oGjE0bACB/GbCjp7NZdaIBcIYAmk0zUN0JYIdBbsMOD6tF8xEQIwB61xMAiCLqArAovZnvVL0FWL9p03d+/ONGO9pz35P1v3NJfaYZ8JnWAafpm2664ZvfvHVs7JxM5qkVK756+eV/2ds7YFyKQNM2YJhG94NgGr0LgmkDsE3ziTDmA1ot1R1iq+4KsGpjzkBX1XqljqL6tdd+95lnnjzp8EOO2nNPGh7eSa5tgCsnPpW2ax9guzb6pmyVAATXBhDi2gZ8XyDOizEyouaEz+h7Rm8vVSqdhYKr1SltbO6bqlbdAHdqAcA6w/qmaE4AX1RocgKoVtUNXAaMlYozGapUVBekAXCGAIpFtc6MDKDrCW1YANWqEiUDeiMdAEQBEwC7Q8Snegvw1IoVv/zd79717o+ccMrSfH5Kfwh30ThNAxBM64DT9KOP/nps7A+S5Pxmc+Tppz89OrpmzpwB41IEmrYBwzS6QwzTzWbz/vtvabXqixadUan0A/CZxpwB2TSfqPenGgA2oNMBXbUA6Kox0BuuWq/Ug4MvPvjgTZOT49/4zGfm7bMPTUzsDNdOgCsnPpVO107Adm30TdkquevJ51oHAl3bgO8LxHkx8IWZtjPUJla4FWcyNDKidnPU2xlx7AaSpLNZLiZbop0hA3FM9XrnKQD7DyN/GcAAFJ4CAORynadrHeAMAbRa6oFLBjB6z4N4APCvDOiPSwAgih9PfACL0gGn6i3A5OBgO0kWLDh0crJ3crLzdy6pzzQAwbQOOE3vtttAHK9qtUaJNlQqg1HUPzJiXopA005AN42eAN305GTtAx84d+VKSpLS3nt//Z/+6ZaBgaJgOopUDj7TfCKM+QAsO4QvKEO1DOiq8Wgbrlrbm659xx23P/zw8oUL9jpq7lwaHd0Zrn0AV058Km3XPsB2bbQzbJUABNc6EOjaBnxfIL5vmHQ/cLV8Iy/oyAtA8tKPiPMRAP04Xlj8VQAwUmlkiF9lAC1HbKzDuRkYACNDlIpD5XwA1sv0FUwAUGZMfcKv9ht3AiyKAZ9qBrJZXDemdprp173uTc888+Vnn32kUnnhwgvftffee2HXHP1SBJq2AcM0FmPVC/bAAz9fuXKi2bybKHr22cvuvvvKiy66TDANZ9tjmjNEJ6ug2gno7wjBVNtQqYlqN9zwvWxMf/+xj0y5tC+rax8Q6NoGbNdojgiuedlan2sdCHRtA74vEN83DNouM/qeoa8jTyTtgSEApC1Sz9+MAuBbZx/fhQJgL4hvF8z5c1eYF8cXCiYA+p4Jvv/LCWytam3nDPQC7kzTe+218GMf++rQ0KpsdvbChftHUWzbDTQtbErB5TEK1m43iQpEEVFE1NNu1+WsjP9r20yzSWCCahswVAt1R5CzYsWDq1c/cuIRR570miN3nmsfEOiaqPsmJL5MWKXvHTmBQNc2sFX2OM8Zfc9oNtUUfzTKsBoB2qS4n6Nvio8bQC435fiWqQNdAHy2cBwAZysDyLleV71ek5PqxfkzwBkCQPuXwx58AJYG0TNkTAawyAp6lgAYxgSAl7UD4FPNQL3O1w0JfzfOs0Uab0gGPKajUmne/PnzMIrpvBSBpm3AMM1Vjwt2zDGv22+/b6xa9cYkKe+55/OnnPIN40TDNB6Htse0bpKDbnyqbcBQjTkMwaoxKFv7whfekY+Td732lGomVh+uneDaB/BxfCoF1wZgu+YVBn2uAQiudSDQtQ34vkCc3zC7xtohu8D8DMT7c/S0PoKtz89wApVKZ1IABr7QmJUB3ugJg3WInsZQuQzo0dMA+vrU2JoBcIYAikVVD2QAQ9yYUAKgWlVPFjJgTL/IZpUoDJ0JgHP6hVM1A+UyXzf971xSn2kAgmkdCDdtAIGmbcAwzeOdmunyD37wizvvvLrZrC1ZckF/fx8An+koIh1wmsaJMOYDMJHFmH7BqgVAV93TM6VTK0x1snbtoxs3rn3T2WdfeP55WWz4s7NcuwGunPhUOl07Adu1MQZuq+Qhbp9rHQh0bQOB1ZoncKTzM2higgYHqdlUKxhHEQ0NUa1mjoETuYFWSw1xA8DMSaztJQDGAtyjo5QkKqBNBuxIuExGFcwAOEMAjYYZdOgE8GTBM2CHh9UCyERdAH0EGwBEEXUBWJS+KLRTNQOjo3zd8PTDbUIeCnaaBiCY1oFw0wYQaNoGDNN4iDRMj43lliy5GBqQlWA6iqYAtkg+EcZ8QLOphl1t1TKgqzbiP0NUv/jic3/zN3+azWROPPDAMu+NttNc+wAow6fSdi0AhmtjDNxWCUBwrQOBrm0gsFpzzC6Pq8/ce0ZPD5XLVKmoe2mlQs1mZ90ctDNyOS/ADRQApZLq7JABfFHxtEz8Fe1NGTAi4eKYymUVdW4AnCEATFLVgw6dAJoRPJG13aZyubNGtABg2RzcYgFAFPIXAGORI0E1A4UCXzc8sbFpDrP0mU6SLqYZCDdtAIGmbcAwjfBOwTTCOwXTBuA0jRNhzAcgKFlfTkpXLQC6anShb5Xq5ct/tXLlw0cefNgH3v72TLk8Da5tgCsnKp/TtROwXaOVILgGILjWgUDXNhBYrQHgm22m3zOM9abyeRob62yXhPstBjycgG+9KRl4Va43xeMDACCKqAvAohjwqd4CJBMTqNWg9E14Z8h6U3qPtGDaAGzTfCKMCYC937F+iXzA9qw39fzzG2+88UfDwy+d+vrzZhHR6Og0uKaA9aYM1z7Adm2shW6rBCC41oF0vamdHTfli+fgyAE5WMgIq/DFjghxFIEBJRwy4cufAWeG2BpeBpwFZswH+F4+Y8JLVD00Pv4PP/pRT763XC5z3NT0mna+QkwbgFEM/QfnO9Ij/pzvyACES7RtV9IOyZGvJJcnRPVzzz3xwAO3LjnqqL++7JJpc20DvtrD7y38iwLPO4JrHXC61oFA1zYQWK31yMl0fsaUwGQOZIYp/IBJCU4Aczv4eD6v4g1kAMfRVuXZIcBkAINa+AwAMPJnQM8QLw4zFwAEsONZgwvMmACgWxbhJQCM/H0Ai2LApzqbpUzm6vvuu+Xee089+cJjjz0jn492BdMGEGjaBgzTCMEXTGMUUzBtAFtpugNg1gV+9al2AnrBeN5GiOpMprVs2U9qE2OXv/WtxUpl2lzbQKBrG7Bdo6dIcM3TL3yudSDQtQ0EVmsGstkZf8/gsTWso9LT42hmY3svJ8AnAohjmphQlUwAcB/CcQC5nPpVBtBVipYjALxwRXWAMwSA8FZels8HoOdUzzCbVb/KgD7EDQCi8KkQABbFgE91NkuZzLp16/K5/KLXnFKt7oFeQP3vsmkAgmkdCDdtAIGmbcAwjS8iwTR2bRBMG4Btmk+EMR8AUbxsna5aBgzVWIsvRPWTT/7qpz/93jnHHfvaI4+cTtc2wJUTn0rbtQ+wXRtj4LZKBnyudSDQtQ0EVmsGMLYx0/um+AWhaLWhluBnGcBxOx8BEE6UAV9W+kHfzyEA/9r1uJ2zLop/1TEnsFWq45iiKIrinp58FEW7lOmu/2nX3MKP7CjTxok+QM/HUC0D2/Ye2+3mz39+ZbtVf/Npp++z++5YpHB6XIdUJkOBD7BdY6qT4JoBn2sd2IHvKKTez+h7Rj5PpRKVy6odh43ajbipTMYLlErq0RtAqaRGw2QAwTqwD6Bc7uwULwBGVAOiwjEqZQB6hpOTVCxSNtsdQFgUEoBSSTWBZQBDeejxBABR+EEAjGAdQTVHmBDl85HTNIfM+EwjIkYwzUC4aQMING0DhmmE6gimEaojmDYA2zSfCGM+AAFmelgUF1UG9DeOb7wQ1Xfffd2Pf/zNQ/bZd/ERh0+zaxvQKyfHqOmufYDtWo+bcroGILjWgUDXNhBYrQFwYNWMvmdsifdX/2azNDqq5mfq8zMyGTfAJwJIEhU3JQNYD5wjnUdHKY4VJgOodmg5AsjnO2sg6gBnCIAXqpYBdP5yFA7WRgQmA3rXEwCIwuOJALAofbE2p2oA9ToR1ScTLFWnm+aS+kwDEEzrQLhpAwg0bQOGafQ9CKbRuyCYNgDbNJ8IYz4gSVR3iK1aBnTV6A7pqrpWa95yy1Xtdvstpy9dvMceNDIyna5tgCsnPpW2ax9guzb6pmyV+FdwrQOBrm0gsFozkK5RmM4Df4XNA+/tpYh6C1F/v2l6BswDl6Z5vwrmgWcyyfLlt/76odviOL7onKWZWbOm2XU6DzydB57OA3/FzwOv1Sih2kQyOGiangnzwIVp3q+CeeDNZm3Zsjs3bd7w46985cg5s2loaJpdp/PA03ngrv8/Sz09nb1z8QPu5IgZxFiTD+jpUa05Po5YWxngODYcr9en5C8A3JmIpwA9Es4AOEM9cJAfuHwASo6gQ84Q3+MygMclhOgB0N+RALAoBnyqAWAh9GzkNI2SCqYRnyKYZiDctAEEmrYBwzT6lgXT+NQLpg1ga00zgB3uUR6faieg58/xqILqZ555bPny23fr77/w7LM7U/Om0bUN6G+JWwm+i6EDtmteQd3nGoDgWgcCXdtAYLXmfNJYWzXnAC/jV/vlA/g45ouGA3YBZMBXBv2g7+cQAP22zoLJgJ2DrwAGsLWq222iXdF01zfRNTf7iGzaeAvOrLbHdNcrZlcKoZy8P4Dwrm+66T+eXvnI1z5weYH70KfXtQ0Euu76RTFdrm1g2740ZvQ9A+Nj9Xpn0jym4/MINgZJfYBxHC/MThYAzKnRjzMmA+iRRIMUAF6MMWBkiCPIVgAQ6eErmACgAQEzAIw37gNYFAM+1Uky2W7/8uFHiKidZHYd0wYQaNoGDNPoeBBM83/qM20AW2N6CoAXvmcE1TZgvHEEavpUj4yM333XNXvNnb908dG7imsbCHRtA7Zr3s3b5xqA4FoHAl3bQKBqBjC2MaPvGb291NfXWQisr2/KvsY8Bt7X5wYqFTVCBQDjYMYYuA2gQwStPAB9fao8MmCMUGWz2CRa5a8DnCEA52CgDbTbVCioQXsA1aqqRjJgbPeNQXve1lsA7IFXn+pc7vvXXHP3Iw/vvc8hJ55ydrVqmuaS+kwDEEzrQKDpWi15/PHly5bdSpS76KI/6O8/uFiMQkzbgGEaI7iCaYR3CqYNwGkaJ8KYDyiV1KRjp2oB0FVjZFBQ/eUvv/+lTev+4IIL9l64n7dWGxcjsFZvs2sb4MqJT6XTtROwXRtj4LZKHuL2udaBQNc2EKiaB8k51H7m3jNqNRoaolZLDRDFMWE/HWMMPIrcQLvdiXMcHqZWS43MyoAx8AoA+cuAPUKVzaoTDYAzBNBsmoOBTgCxq7yW2fBwZ6d0GdCHuAFAFA+d+QAWpQ8GOlVns0+tWDE6MfH+9//vanXh8LBpmkvqM82Az7QOBJp+4olHP/e5z23a9A6i2vXXv+OrX/3vAw5YGGLaBgzT7XZn53WnaawyJ5g2ANs0nwhjPqDVUsOutuquAKs2xmUN1S+99NyDD961x5w5f3j++VV8GJ212rgYgbV6m13bAFdOfCpt1z7Adm2MgdsquSHic20AIa5twPcF4qz3IyNqTvhMb2dUKp2FgqvVKTGD3M6oVt1AuayeAgBgnWH9mc0J4IsKzzUAqlX1eCIDxoybTIYqFdVyNADOEECxqNaZkQGE0qJhBKBaVaJkwGhGxLESBUwA7Idbn+otC+bsv/+elYrDNJfUZxqAYFoHAk0//PDNmzYtbrffS5Rs2HDn00/fs3jxwhDTNmCYxjQywTQebQXTBuA0zSc6GyIA0CAzmhGsWgB01dms+pqyVTebo1df/beDgy+c+trTDz3qKGq1vLXauBiBtXqbXdsAV058Kp2unYDt2mhn2Cq5GeFzrQOBrm0gUDXnk66FTrWaCkTDrTiToZER1RrV2xlx7AaSpDPhZWSE2m319CsDcUz1eucpAHOIkL8M8IaimN02Pk65XOfpWgc4QwCtlnrgkoEk6TxwMYB/ZUB/XAIAUfx44gNYlA44VWezeE4cG3Ob5pL6TAMQTOtAoOk5cw7OZn9Rrw8StfL5X1erH8Wfupp2ArppRMcIpqNIAT7TBmCb5hNhzAdg2SF8QRmqZUBXjUdbW/XwcLJ27TMPPrgsE0c/+MQnCnKtNi5GYK3eZtc2wJUTn0rbtQ+wXRvtDFslAMG1DoS4dgKBqhlI5/SlKU3bk0444fXnnnvHE098hKh+wgkXH374yamTrUrtdmvZsutXrfr9ucefWN4F+srTtOunXWC9qWKRikV1xzaW5kHLMZPxAsViZ10atIXxiCED6BDhxi9avng8kwH0NuLZBECxqO78BqBnWKupATru2PUB6HriHcpQfrSpZcBYTgpj0Og+lgF7kSOfagBEvb3qitmmuaQ+0xjLFEwzEGw6+6lPfXnDhifq9eyiRYcODWUCTduAYRrXXDCN7hDBtAEI603BmA/ABnT6clJcVBnQ3zjidGzVw8O1n//83xfMmfvZy95DxWKXWm1cjJfbtQ1w5cSn0nbtA2zX+p5LTtcABNc6EOLaCQSq5nwAzOh7RqNBtRrlcspLraZ+QN1vtVRvY2+vG8AeW/gmw8IYtZqqfAKA4Ggc51268KsMIGe0ZAFweQyAMwSAHrZWqwuA2Ul6hmxGBvRt+ABwwboCxuZwgupWC+1mp2kuqc80AMG0DoSbzmQKe+21aHxcVaVA0zZgmEY4pWAaCywKpm3AMM3HWbkTgCg8+RiqZcBQjTUlDdXLlt2yZs2Tl5xz4WHz5yutouspwMvt2gbYFO8pabj2AbZrY58+WyUPLvlc60CIaycQqJoB3BGnNcVpUytNaZqZ6aWXNnzpS2/fY+7cd555crm3JxWSpldCOyOXo0KBCgU1+FMoqIcFvW8KUclOoFBQLUcA6HXRe0ycADpEcEsHUCioG7gMoLWI5dkBoPDAdEDPEC9MuJIBZIinGACFgmrSygAel/C0BQCigAmA0SEiqN7SN9XTo8prm+aS+kwDE0wzEG7aAAJN24BhGoYE01AlmDYAp2k+cXLSC+Bd611PelEFQH/jRKo7hFXX66177rmx2WwuXbLkrNNPj9Gm36Vc24BeObkf0HDtBGzX/FefawCCax2QXQtAoGrOJ+2bonpdRVUjaiKXo7Ex1Sulx03x1vAGwCcygGgeGUDsEK9UbOzwLgBdd3jXAV6xZ2ysM5FBBrA4gZ4hb2EvA3rUEwCIIuoCsCh9UWiX6olWa3jzZiKamHCb5pL6TAMQTOvAVpnWgUDTNmCYxgoRgmn0LgimDcA2zSfCmAAgVMdWLQO6aoTq6Kp/85tf/8u/fL0nlzvv2GOztdqu6NoGuG7hU2m79gG2ayNuylYJQHCtA7JrAQhUzQDuiDP6nlEo0KxZnVkUs2apPkd7LXQnUKmoyZYAsM6wMVHcBvBwizs2AKwzTNQF0GdpAujv78wv1QHOEAA2TjEmxNoAHiuwhDKAalVFecuAsdR5LqdEEXUBnAtwu1TfvmzZT37xi4GBuYsXH4q9cwzTXFKfaQCCaR0IN20AgaZtwDCNYVfBNNalFkwbgG2aT4QxH1Auqz/ZqmVAV93bqx5tWfW6db954YVnzz39rDeef37nyWyXcm0DXDnxqbRd+wDbtTE/w1bJ0y98rnVAdi0AgaoBIIhgpt8zJiZo82ZqNDorFQ8OqvU59XZGkriBZrOzmBrWXsbTrwzok48BtNtqsqUM2LM045gGB1VzVQc4QwD1ujkh1glg1AuPFQBaLRWdLQN6M4IBFEwGWBQDHtV3/PKXE7XJP/uLq2q1otM0l9RnGoBgWgfCTRtAoGkbMExjqq9gGjtVC6YNwDbNJ8KYD2g01KOtrVoGdNXG3OT169ded90VzUbt3EVHZ3G5d0HXNsCVE59K27UPsF0b7QxbJW9i5XOtA4JrGQhUTVvWVB8YSMcztoxnIBIOvY3GPdAnZo8AACAASURBVAPdoE5AH66o1zu97DKwzeMZuKII/3V2RzLg69iVge0Zz0AcrT5cwR27AmB8UflVt+N4Vv9u++6zj2CaS+ozHT6eEW7a18e+tZcifDwDnpxd6ALgNM0nYrl9J8Bd6E7VAiD0sa9Y8fAjj9z93ove8t7zzlJ/3gVdO8czuHJiOMF27QRs1/aGx4ZKAIJrHdhR4xlyvU/HMzrxas2mEoofENONVR6xPpIP4EUfcZxXW5UBfHXqy0xy/jKA1iUvbGnnz4CRIS/iKgP6srUADEwAsBQVL1trGPMBLIoBn+p2m4iazcRn2jjPFul8Qz4g3LQBBJq2AcYmJ1uPPPLgihWPHH30iXPnHhpFsdM0rzrqM20A4aYNgJdSlVXbgPHG+cPUaExeeeU/EyVvO/PMHnSsT5drLrrxP/oA47hwMQzAds2zuH2uAQiudcDn2veOtIsRpJqBdF1bNZoEp3qt4hFsDJL6ALz4OF76LtVOAGEJOI4jnL8M4IryctV2/gwYGfJ0ExnAmLLxTnVMAGASumxjPkDfOF2+FrhntLymjfNskc435APCTRtAoGkbwL9J0r7yym/98IffHhtbMjDwD3/8x19ZsuQNjUZkm8aXrWDaAMJNGwBe+nbfTtU2YLzxKFKibrnlR7ff/rNLly499sADp9M1Y3i3Qi1hwDguXAwDsF3juODaeaIP8Ln2vSMGAlUzkN4zqKeHymWqVJSLSoWazU7MIMbAczkvwBuJAyiVVAeODKBDhIek8Fc0jWXAWEEsjqlcVm1hA+AMAWCATl+szQmgKcqDeO12Z5V4GUArG115ACAK+QuAEeApqM7loohKxUgwzcvT+UwnSRfTDISbNoBA0zaA/33jxvUPPvib0dGfJMnhmzb9dPnyO84446xKpcc2janHgmkDcJrGiTDmA7CYox5Kq6sWAF01QtZ7emhsbNO99/53tVy5cOnrBhYsUJ370+KaazWGuIVqzwBXTnwqna6dgO0aI9iCawCCax1wuvbVex0IVA0An7eZfs+YnFRj1Pg3m6XR0c7zEo+BZzJugE8EkCRqZFYG0OjjFcRGRymOO0PlAoCLhxEqALyjmQFwhgB4oWoZSJLOYm0AokhhMqAPcQOAKPScCgCL0hdrc6puNJKExsaTkRG3aS6pzzQAwbQOhJs2gEDTNoD/fWQkqdfjJMkQUZLkJiZoZIR6ehymsYSEYNoAbNN8Ioz5gCRRw662ahnQVWPYtdGgq6/+wT333HzKkUces9eehGs5Xa65VmPrOqHaM8CVE59K27UPsF0bY+C2SvwruNYBp2tfvdeBQNUMpGsUUqFA/f2d1kB//5T1tfVYWydQqXQCPHFLx8O4DGCjH8T2AcB+Jl0BY0eUXI76+tRzjQFwhgCcm8/YAJoRCA4GUK2qpxUZMEJps1klCqF+AuCMtXWq7umJoqhaiXymuaQ+0wAE0zoQbtoAAk3bAP73cnneyScfsmLFB8bGlsyade+ZZ3589uw84jMNkVGklrX2mTYAp2mcCGM+AEHJRigtqxYAXXVPD7pDGsuXX5ckyUff+979Dzl4ml2TtqUSTPmqPQNcOfGpdLp2ArZrI9bWVsmhtD7XOmC7Fuq9DgSq5mDcNNaWJiZocJCaTRUhF0U0NES1mtnOIHIDrVbnsWJoSM2CQUCqABgBnnh8QCScDNiRcJmMKpgBcIYAGg0z6NAJYAYTz2YaHlYBdujNFAC9GQEAojhEzwewKD3o0Kl6cjJJkuGRZHDQbZpL6jMNQDCtA+GmDSDQtA1sKX/24os/fsABxz322PITT/zHPfZYNDwcETlM40lRMG0Atmk+EcZ8QLOpHm1t1TKgq56YoGZz8o47/v2xxx6Y099/0sKF0dDQtLtWAB7YhWqvAygYPpW2awEwXBvtDFslNyZ8rnXAcK3H2spAoGrasncTd37M3HtGmtK0i6VMJnPUUae/5jWnF4udqbuvgrRs2fXf+94X95096/99/ON7zJ3bucOnKU3pGHg6Br7Dx8AbUfRqHQMvl5N169b+5jf3lUrzjzxySbmcEcZlX7lj4Dfc8J0MNb/2J5895cQTdol4g3QMPB0D35ZkrDeVz9PYWCdMFm00rGnsBHzrTcnAq3K9KV7qHABEEXUBWBQDLtUvbNx4zf/clc8XJyczo6Nu06/c9aaef/6pT3/6/c8/vyCXe+Sccy78kz/5P41GRlhvipffBuAzbQC2aT4RxgQA3SG2ahnQVT/00K8eeujO4w57zWG77955M7v42l4UsN6U4doH2K6NtdBtlQAE1zqQrje18xJmYGAqJvzqL5667APwglD+FdOLBUA/LudvABhOFwrAgDNDxFzLgLPAjPkA38tnTHi5Cva//vZvXxwaete7Pjxn7p67mmnnK8Q0A7fd9tNVq85ttz8zMVF/4IGL1q59Yv78w5j3vSPUXMG0AQiXaNuupHHE9+khonp9/G/+5n2lQu+lZ5+515zdTGJnunbWap9rG/DVHnYd/kWBMQ/BtQ44XeuA8f9yeXwlt2tP4LVAa2xG3zM4bgaDP/iBlwzBD+22F8jnpxzP59V0GBnAcbRVcZDzlwEEQuAzAMDInwE9Q7zwTC4DSUL5vHrW4AIzJgAYysPcUQBG/j6ARTHgUv3Mhg1z5+5x6qlvqFQKu5ppAwg0rQO1Wo1ogCgiyrRaZaLJfJ7a7S6mEfkimDaAMNMOIJ+nVkv96lPtBPDXJGk//PDdmzat32fBgksvuCCrl3Xnu3bWap9rGwh0bQO2a/QUCa4BCK51QP9/Wy1VHl+914FA1QxkszP+noEVuzIZmphQTVq7mY3tvZwAnwggjmliQlUyAcB9CMcB5HLqVxlAVylajgDwwhXVAc4QANZQQ3tWANBzqmeYzapfZUAPiwIAUfhUCACLYsCpOkniOJck+YkJr2kuqc80AMG0DoSbNoBA0zpw0kln/exnf7lp04tx/NgBB/TNnn0g3ncUSaaxa4Ng2gBs03wijPkAiMIUBUO1DKDYGzas/eEP/2l4ePCyS9/ezy6my7WzVvtc2wBXTnwqbdc+wHZtxE3ZKhnwudYBo1pjvohQ7xkIVM0AxjZm9D2jWKSBASqXO7MoMCpqxNr29bmBclndhAGUStTbO2XlPCeAHDCaBKBaVTdwGTAi4Xp7O8tMGgBnCKBYNIMOnQCGuDEOBqBSUY8eMqDfEgBAFIbOBMBeTNWpOpPJEPX10cCA1zSX1GcagGBaB8JNG0CgaR3Ye+8Tv/jFT/3oR3+7996H/vEff23WrF5eflswjWFXwbQB2Kb5RBjzAaWSuWwtq5YBFPvZZ9c899wThx148Cf/8A87AaDT5dpZq32ubYArJz6VtmsfYLs27hm2SgCCax3QqzWH0vrqvQ4EqgaQy1GpNOPvGePjtGkT1eudEHfnWuitlhuo19X0CwCTk+YK3U5AnxQAoNlU0dMyYEdPE9GmTSrsWgc4QwC1mvnhcQK4JWDIC0CjoWIiZcC4JYyNKVFoyQmA/UXlVN1qtVrx0BBt2uQ1zSX1mQYgmNaBcNMGEGhaB+6//+4vfOEfNm9e+qtfPbVu3Yf+4i/+PpOpIgRfMI1d1QXTBmCb5hNhzAdMTpq3BFYtA80mbdxY+8///PYL65999yXvpE2bpt+1s1b7XNsAV058Km3XPsB2bdwzbJW8MKLPtQ7o1dqYn9EVCFENYGSEZs2i2bNn9j0jn6dikYpF1ZtZKlG9bu7tmsl4gWJR9SoCwCRJPQLUCfDeJjiOpxh0PsoArijqGYBiUc3mNwA9w1qNikW16KgM4JbAUYYoP5qrMmCs6pwkShQwATACPH2qoyiOqbe3c62cprmkPtOYGiyYZiDctAEEmtaB++67c/Pm89rtP2q3WytXvnvjxhX77Xc0rrlgGo+2gmkDsE3rJzYaXgBBpHooLauWgWKRomhs2bKfnnrcsX900Rs7z/LT6NpZq32ubYArJz6VtmsfYLvW46acrgEIrnVAf+PoKBPqvQ4EquZ80rXQqdGgWo1yOeWlVlM/8IqYiLXt7XUDiJMjUgBgVD4BQCwHjnOkHX6VAeSM6GkAXB4D4AwBcGtJBpJEPTFxhmxGBvRQWgBcsK6AEeDpVJ0kWPiH/26b5pL6TAMQTOtAuGkDCDStA6VSKYo2ESVEjVxucxQVMMkXy9b4TCPyRTBtA4ZpPs7KnQBE4cnHUC0D2Wzr7//+45OT469dtGgO/o9pd+2s1T7XNsCmOC7ccO0DbNdGrK2tkhdy8bnWAaNaI/ZXqPcMBKpmAHfEaU1xOq0xTTM8nX32mw499Jf9/e+eO/eUk09estdeB7863teDD951yy0/PPXIIy8+66w8OuXTlKZXfDuD9+njXbTwsKD3TWETLiegb8OHXbQQkCoD27xPH1qLCKN2brPFgG/DMhnYnn36sln1tMUbluHxRAaMDhGf6i19U3ytnKaNDc22Z5++cNO+vePCL8W8efv/9V//66pVDxYKcw877NhSKcajrcd0Mjb20vPPr61UZg0M7NVuxz7T+t5xPtN84uSkF+Ct4ZyqfcDIyMg991wbx/HJi44+YOHCTh/69Lre/n36uHJyP6Dh2gnYrvmvPtcABNc6sKP26ZOvRbpPnxrt0eeB53I0NqZ6pfQxcJ7eaQC+eeAy8KqcB85D3AAgiqgLwKL0RaFt1UmCwD99pq1h+pU7DzyTiYrFBSeeuGBkpNOh4pub/PzzK//t37789NO5anXDW97yrpNOenMuFztN89xkn2m+RDAmABh2tVULwF133Xb99T+ev9vcS049hcbGpMnJr+h54IZrH2C7NsbAbZUABNc6kM4DT1Oa0uRMd9xxzd13L24230u0vrf3Lw488LhqdcFtt/336OjmN7zhLfn87rtCIZOk/eSTy4eHX/rQuy9/zb77pFctTa+ie0ZvL/X1dRYC6+ubEpPA+2f09bmBSqUTdo0IlWzW3D/DBjDHEuHSAPr6VHlkwFjdPpulalU1XQ2AMwTg3EjABtC4RoA5gGpVrRYgA7wNAJr/2PADjX0ZsDdtsFSPjo4OTUxkCrlKJa5Wvaa5pD7TAATTOhBu2gACTduAYRqhLrbpjRs3tlqnEZWJdh8ZmTU2tuZDH7r84YcrSTL3+uuv/O53f9LXN4eHOZGDYBqXCMZ8QKmkJh07VTuB55576Pbb/3OgUr7ozCVRX58iMEH8FeTaBrhy4lOp758hA7ZrY/8MWyVvj+FzrQN6tRZU20CgatqywQb6qWb0PaNWo6EharVU8HIc0/Cwas/qfVNR5Aba7c4eacPD1GqpHhMZMDZtAID8ZcCOns5mOwHpOsAZAmg2zUB1J4B977gNOzysFs0n6gLoXU8AIIqoC8Ci9Ga+pro+Nva3P/zhs+vXL1myKJ+fOzzsNc0l9ZlmwGdaB8JNG0CgaRswTKP7wTZ9xBHH3HnnNaOj45nMk/vvn3/mmecefzxuNv8/onjNmk9dc82PLr74YywSOfhM8yWCMR/QaqnuEFu1D7jrrrvWr1/zvc9/ftH8+R1CnxPwinBtA1w58anUK60M2K6NvilbJQDBtQFwtRZU20CgaqSRETUnfKa3MyqVzkLB1eqU/ca4nVGtuoFyWT0FAMA6w/ozmxPAFxXPF8W+YHg8kQFjpeJMhioV1QVpAJwhgGJRrTMjAxjyQsMIQLWqRMmA0YyIYyUKmADYD7dTVW8eHb3h/vuJ6OMf/+ree89BwZ2muaQ+0wAE0zoQbtoAAk3bgGEaUwJs069//bmVSuO++x7Ya6/ZF1748VWrns1khojaRFEUjQwMlKvVKc++smm+RM6GCAA0yIx2Bqu2gaefXvHf//3teQMDS5YsoUql06bD99QryLUNcOXEp9JoZwiA7dpoZ9gquRnhc60DerUWVNtAoGrOJ10LnWo1tYkVbsWZDI2MqNao3s6IYzeQJJ3NckdGqN1WT78yEMdUr3eeArD/MM/2FAAMQOEpAEAu13m61gHOEECrpR64ZABjyjyIB4BnVwuA/rgEAKL48cQHsCgd0FQ3h4ebjUYcx3PnHoX35zPNJfWZBiCY1oFw0wYQaNoJ6KaxdpPLdPXUUy89/vhL8TW13357HXrobr/+9XHt9oJ99x0+9dTvDA93nn2Rg880XyIY8wGIPsAXlKHaCVxxxTfXr1v9f973voNmzeq4xrPtK8u1DXDlxKdSb2fIgO3aaGfYKgEIrnVAr9aCahsIVM1Auh+46s/mBR15AUhe+hFxPgKgH8cLi78KADYKNjLErzKAliM21uHcDAyAkSFKxaFyPgDrZfoKJgAoM6Y+4Vf7jTsBFsWAfWIU4Tf977uOaQMING0DhmksxiqYhrPe3uw///M1//M/d01MjJx00qlEOQMIN+0DcjnVySqoZmDFiseW/fKq3Xebs+SoxblCQXUHgeBL/0pxbQO+Wm24tgHbNZojgmtettbnWgf0AguqbSBQNQNou8zoe4a+jjyRtDODAJC2SD1/MwqAb5193MMEwF4Q3y6Y8+euMC+OLxRMAPQdEXz/lxMIUU3ebHYR0zqwVbDzP+XyyKY5q1wue8wxZ6LzYHjYvf/LNlRqQzUwQTURxXFy5ZX/94UXn/vDN77xyIX7ma6FyrNrurYBYVeYroDwOXW69r0jJxCo2ga2yh7nOaPvGc2mmuKPRhmWJEObFPdz9E3xcQPI5aYcxzIA6DcUAHz4cBwAZysDyBmhIADwIjIBzhAAL/8nA1gaRM+QMRnAIivoOQJgGBMAiGLAOHHLm8K6Cfx327Rxni3SeEMyEG7aAAJN24BhmquezzSedgTTNiCb9gEQxctV+FS327Rx4/onnvgtEf3Rm9/cjyUrdNeYxPAKcm0DfByfSsG1Adiu0bMkuAbgc20AgaptIFA1bVm8ZBdYO2S67xmFAvX3d3bt7u+fMq7KY+D9/W6gUuks3I2BLzRmZYA3esJgHUL0MFQuA0YkXC5HfX1qbM0AOEMAzqBDG8AQN0L0AFSr6slCBngoL5NRAETh6VcA7IFXQzU+t0T9/VP+bpvmkvpMAxBM68BU08no6IvXXXf1ihXrTjll6SmnnBhFed+lCDRtA4bpLeOdyYsvPn/NNT954YXRCy88b8GCo3K5iIddMZzpM20ATtM4EcZ8QLmsFqx1qmZg06YXf/jDv1y54ndnHH30EcccQ+PjU1z39Ezp1fK7lmr1y+zaW+0Z4MqJT6XTtROwXRtj4LZrHuK2XdtAoGobCFQNII7V0p4z+p4xMUGDg9RsqhWMo4iGhqhWM8fAidxAq6WGuAFg5iTW9hIAPcATQJKogDYZsCPhMhlVMAPgDAE0GmbQoRPAkwXPgB0epnZbjYDJgD6CDQCi8DQkACyKAUM14guJBgen/N02zSX1mQYgmNYB3XSjMfSlL3363nsHWq2F11//9S996aOHHLLUvhRR1H700RX5fGu33fbLZHq39lIYpvEQuWbNhs997uLVq/uT5IgbbvjU1772//bZ5wB+tEXQss+0Adim+UQY8wHNphp2tVXrwL//2zdvvP4H5y9Z8i+f+Hh2dNR0bQSA+lzLtdoAAmt1oGuh2usACoZPpe1aAAzXxhi47RqA07UNBKq2gUDVHLPL4+oz957R00PlMlUq6l5aqVCz2Vk3B+2MXM4LcAMFQKmkOjtkAF9UeHwAwMG+MmBEwsUxlctqmNEAOEMAxSLlclOCDp0AmhF4HgHAsx1lAMvm4BYLAKKQvwAYixzZqrHjMVG5POXvTtMcZukznSRdTDOgm1658qlVq5Jm82+IMoODPb/61Z3HHrvUuBRJ0vrWt75wzz1PEOUPO2z+pz71tWIxu1WXwjDdblOh0L7zziueeebZVusQonUvvDDnvvt+cvjhn4UHxE0Jpg3AaRonwpgPQFCyvpyUrhpAFLVuvOl7B+63zxc/9MFZ8+c7XKMPvatruVYbQGCtDnENU75qzwBXTnwqna6dgO0arQTBNQDbtRMIVG0DgaoB4PM20+8ZxnpT+bzaOAUfDtxvMeDhBHzrTcnAq3K9KR4fAABRRF0AFsWAoXp8HHUdeeh/N0y/fOtNRVEln19PNEnUG8fP9/fPsi/F/fcv+/GP/2ti4l6izKpV7zj66Jte+9oLaPvWQFq/fs2vfnVfs/kLot2J/o3ob/r7L2APvMSRz7QB2Kb5RBgTAHu/Y/0SJUny7W9/YdOm9WcsPnyvSqXzZgIXQXpFrzdluPYBtmtjLXTbNQDDtQ9I15va2XFTvnAOjhyQQ1iMsAo7+sQAfCEKXeNJOGTClz8DzgyxNbwMOAvMmA/wvYSgHzkYyB83tfWmkw0b1txxx1WbN7+0ePEpZ555ehwXtsr0PvscdOaZZyXJ2WNjC/fZZ/Scc/7OvhQbNqyanDyOaDciajYXrVnz+0zmgq26FFyMKErWrVt9223XrF796OrVDaLdicpE+++zz/5Ll76VST3iz2naAIRLtG1Xko8899zKm2761z3nzPnEJZf09/Wpu4r9zrlA21yrna+QWu1zbf8gA77PKb+18C8K9F8JrnXADn8ygEDVNhCoWo+cTOdnTAlM5kBmmMIPmJTgBDC3g4/n8yreQAZwHG1Vnh0CTAYwqIXPAAAjfwb0DPHiMHMBQAA7njW4wIwJALplEV4CwMjfB7AoBpyqtfkZW2t6fHzjt7/92XvvPbrdfs1tt/1HX19z8eLzt8p0T0/8nvd86vzz37Bmzab99jt0n31mDw+bl2LRolN23/0f1q//DlHPwMD9J5/8j4LpVqv1zDO/bzaH99770J6eWblcpJseGlr3jW98/MEHT2u3TyP61yj6BtGhxeLNl1/+wUIhx54wiimYNoBA0zaAaRn41VadJBPLll07Nja86IgjlixapL7F7FrNMzu2p1YbQGCttgGjVmO6g1DtGQh0bQO2a/QUCa55+oVRrZ1AoGobCFTNQDY74+8ZjQZNTFAmo9ZR6elxtMOxvZcT4BMBxDFNTKhKJgC4D+E4gFxO/SoD6CpFyxEAXriiOsAZAkB4K9qzAoCeUz3DbFb9KgP6EDcAiMKnQgBYFAOG6i2RhbhK/HfbNJfUML1q1aqnn+5ptT5OFA8Njd19932HHHK+0zRycJqenIz33vsI9FFDmAHsttv+X/3qd6+//sYoah577OcXLDgMedqmk6T17//+d7ffflujMXf//TOf/OQ/5fMV3fSjj/5u9epqq/Uxooho06GH3nDAAWOHHHLmsceec889t2/e/NyiRafNmrV3HEdRJJnGtg5jY61HH1321FOrFi8+cf78g1qtiAE+EcbsSwEAotpth+qeHnryycevu+6KKEm+8I53RPDChFGrsSlpV9dCrTaAwFptA0atxpe+UO0Z4MqJT6XhWgBs18YYuO2aAf3j4AMCVdtAoGoGMLYxo+8Zadq104ubN49uX6hGqdRXKKwhqhH1xvHqefN2e3n6OKMjjjh2wYJji0X1NeVLTz758K23/uzZZ28hyj///J8ee+xVF198mQ7098/p7X2aqEaUz2SefcMb3nnxxZcNDra+9a1P3njjda3W0fPm/cOXvvSf++57SNdStdvtK674v1de+S+Tk8fNmfONL3zh+wcffOwOfd/JuudXrlu38g0nn3Hqa45Iq2ua0ripNG5qOuOmNg8OfvPaa59dv+Hiiz+xzXFTs2Yd+KY3vf2mmy6emNh94cL4TW+6HMs5h8dN7dhYnnr9pXp9H6IeojhJ9t28ea1h+uijj3rzmy++9dZL6vWBhQsL5513UaVCTz31+4cfXl2vP0qU37Dh75Ytu+aIIz7XNW5q48anfvvbRycm7iMaePHFK+6554Zjjjl2B8ZNRdHwFT/6q2I+865zXkvlskmkcVNp3NSr8J4xOanmT+DfbJZGR9X8TH1+RibjBvhEAEmionlkAOuB8+Pz6CjFscJkABdvy6wBGh+nfL6zBqIOcIYAeKFqGUDnL0fhYG1EYDKgdz0BgCi07gWARemLtW1RPbxhw8OPP37AvgdfeukXR0en/N02zSXNZJK1azeuW/dINtt30EGLCoXM2We/7/DDT02Sof7+A0qlWbxGu2EaOWytaQNot2liovXEE7+p14f23/81hcLsOI5003vs8Zq99pp48cUvJ8nufX23H3PM50dGDNPxBRd8+KijXpckowMDB7RapZERGhlpNZs5ooiIkiQ/Pj6J/0swHUU0OtpuNDJEiCPIjY+3dIBPhFL7UgBIEtUdYqteu/b3K1Y88sG3vnXp4YdPyUJXCdfoD9nhrkNqtQ0YtRr9PEK1Z4ArJz6VumsZsF0bfVO2a/zLJZGBQNU2EKiagXSNwnQe+C49D7xabcfxHvP2nDevaPxdmAfeaKz/0pfe/8wzhVxuzTnnvPYzn/nrXC4za9bBWI5pm+aBb8WE2d7e1re//Wc333xns7nXvvtOfP3rP+rv79NNz58/9ytf+c7NN181NPTCKad89pBDFvf1JWvXrrzjjpsHBvY5+eTXVyrZQiHu6zukVFKf1r4+OvLIQ485Zs769UubzSPnzXvkvPP+EVsZyfPA58xZePzx+69ceWG9vnj27N+8/vVf6evbYfPAN25c9/nPv6tcKJx60kmF3Xc3V0sPn5yczgNP54G/ku4Z6TzwXXke+PAwtVqtZjI0ZP5dmAd+441X/e53R7RaXyaq33nneaef/tB++x1H2zEPfKsmzP7mNw/deef9GzfeQZR/5JE/u/baKy+99ANTTUeZzLxzzvlguz3+0EN3XH31n8+dW7z22ls3bjwyk/mvpUtv+tznvtFu9xhzk8fHez796X88+uibNm585oQTPjFnzkJcNHkeeLGYf/vb/2Lx4hMef/yJE064fO+9D9dNbs888OHh5Oabf7pmzcp3nnXWhYsWxUNDjpni6TzwdB74q/Cekc1STw/19ChZ+AF3coQMotfcB/T0qNYcH0cEqAxwW1C5vgAAIABJREFUHBuO1+tT8hcAPAWg2EYknAFwhnrgID9w+QCUHEGHnCG+p2UAj0tbQlOp0ZjyjgSARTFgqI4iXAfj707TKOnIyOYkmUcUE+WbzXmNxoheENk0A+GmDaDRGGk25xHlieIk2X10dKPTdBS1r7vuv773vV+MjJwRRf/Sbr+Z6JPtduOxxy5Zv/6JvfY6Ep3wuuliMXv66Rfoj7ayaQCFQuaMM85dtOhcoxkhVGpbNSKmdNWbN69ZdvdPctns6ccdX+rrUyE3xsXQ/wMOSN2BrgNrtQ0Ytdp27QP0d8StBHYtALZrXkHd5xoAl0QGAlXbQKBqzieNtVVzDvAyfrVfPoCPY75oOGAXQAZ8ZdAP+n4OAdBv6yyYDNg5+ApgAF1V+/8f33mnn/76a675i5deep7ouQULhg844MidYJpfBx20aOFCevHFDyfJnrvttuzUU7/uhBuNxkMPPToy8t4kWZokG4jaqI5R1CKK9PcoVDrZtP0et6pSy1fs7ruv/t3v7zvr+OPfeOIJXa4pysHL1u9A11sFy/+pXO2NCtfVddcviq1y7fwAbptqG9i2L40Zfc/A+Fi93pk0j+n4PIKNQVIfYBzHC7OTBQBzavTjjMkAeiTRIAWAF2MMGBniCLIVAITd+AomAGhAwAwA4437ABbFgHUiBrqNvwumDzxw8WWXXfqd7/zV+PhxTz/9zA03XHX++R+IovhlMm0AhcKsz33uu7/4xU+GhzecdNLXFiw4xGm62YwrlUwUbUwSIjo1jt9B9Ggm89vDDjtt/vxDeBM2wTT/pz7TBtDVtA/AC98zAIaGRn//+wdqtfHL3/zm2aWSg3C6xiSGHeg6sFbbgFGrfa5tINC1DdiueTdvn2sAzi8QGwhUbQOBqhkQoshnyj2jt5f6+joBbX19U4byeAy8r88NVCpqhAoAxsGMMXAbQIcIWnkA+vp4NoEEGCNU2SxVq+reZgCcIQDnYKANtNtUKKhBewDVqqpGMmBs941Be97WWwDsgVdddaVCmUwmG1Wr5t9t01zSfH5i5cqHJya+kiRvGRp6ePnyb5x77h/sttvuAATTOtDNdFKvD91778/vueeBI4446Kyzzq9W51arUbNJxWJUKFQvueR9mumkXp8cGxuMop5qtb9YjOp1KpVy5513wTPPfGXNmttnz17x2td+eMGC2f39l55wwtLK/8/ee8dXUeWN/5+Zub2m90ISAgQIEHqvUgVEUHTturruuk1c9dEt7j77s+3q6tp2ddd97B0UUQGVDtJ7Dy0FElJvcu9Nbp+Z3x+f4WSYcjKoz/e73yX3lRcvuPd9D5P3+Uw553zOOW4TXugcDpppTO+kmFYAmqbxi6hUD3A6pXRTBEKhyCefPL9ly7JRZWXTp0+HaFRJkMqQu8ahwW/lWhcwGNVqQBHVeq7VAAlOPCs1XWsCateKMXC1azLETUb1KYBB1WrAoGoySI6J6pf1PSMSAb8feF4aIGJZCASkcTP5GDiOx6oBQejKc8RVu3Fklg4oBl4RwPLpgHqEymSSvqgASIEIJBLKwUBNAB/pyVpmgUDXTul0QD7EjQCKIkNnegARJR8MJKqDQRwDDwSUn6tNkyM1m4VAQBRFBwCIojUUMre3JzDJCgE903KAbrqtTVi+/N033zwcCs1YuXLXkSPP3n77b00ml6bp9vaWN974x9GjDRkZ0fHjF0ydOisWY3me6ddv/COPvHLmzMni4gK3u9jrZYPBroX1BKFr53VN07jKHMW0AlCbJl9EpXoAz0vDrggsX/7Gy39/dPKgQc/d8xNnPK5ByCuDuFYMzBp3TQEMRrUaUES1nms1QIITz0q1az1A7VoxBq52TRoiZCNxOmBEtRowqBpfwaA0J/xyb2e43V0TXjyei5IKSTvD49EGXC7pKQABnC8jf2bTBPBChc81CHg80uMJHVDMuOE4cLullqMCIAUi4HBI68zQAUylxYYRAh6PJIoOKJoRLCuJQowCqB9u5apdLmxnuN3Kz9WmyZG63Y5x4yr27Pmb33/I4dg+YsTw/Px0s1kCKKblAN10NBo/fvx0KHSNKE6JRstPn/6LILS63a54HGw2/sSJPZWVh4YPH11UVBaPs2vWrPz44/Ph8N0M09rY+Mzo0QOTkwt4HqxWxuvNz8vL93rB71eaxmlkFNP4aEsxrQA0TZMvajZEEMAG2YU5feLKla+4nI67r/9BaVmZBiGvDLlrk0m6Tl2qawpgMKrVgEHXaoAEJ56Vmq41AbVrRTtDbZI0I0jLiQIYVK0GDKom5fTM6YNIREpEw1sxx0EwKLVG5e0MfOZVA6LYNeElGARBkJ5+6QDLQizW9RSAc4iwfDqAGRT4FICA2dyViicHSIEI8Lz0wEUHRLHrgYsA+CcdkD8uIYCiyOOJHkBEyQGiuqMD2xmKAjRNkyNlWdP48T/IzS3euPGLwYPvHjt2eiTC4VSkYJBmWg7QTXd0sB4PxzANoggM0+5wBGMxezAIgYDwxhsvvfXW3zo7x6SmPvfLXz4xatScnTsPRyITAMpFEc6f/7CqqtZkKtCsimAQWlrqt2x53+FImTbtRp43U0wzjDQ5Us+0AlCbJl9EpXoALjuEF6hPPvn7iRP7+hYW903NZPE5WkHIK0PuGp9tv4VrCmAwqvVck6jGTCRK2BOABCeelWrXeoDataKdoXaNADkSOmBQtRowqJoAPXP6el7/kS+WZQcNGtO79xiyuvP3naFtnjVrcVvb81VVmzMzW+bNuzUpKR0AfL6GnTv3d3QsFcUBra3Lt2xZP2zYFUOHVnz99bpQqJBhmjyeY4IgxuNRlrWqi21oqLn//juamiYwTNWKFW8+++yHZnPav4/VYLDtq6/eBIBHf/TDstz0njDreV2W9wyLBRwOcDikO7bTCbFY17I52HLkOF3A4ZCaogjgJEn5KkiaAHaIkMYvtnzx6YwOYG8jPpsg4HBId34FIC8wEpEG6EjHrh6AXU9kpR08fmxT0wFcNgf7ehBAUYhRAMUiRwrVdjuwLMsxDofyc03T5Ej1TONYJsU0AbozzYwYMayk5E81NVUZGTkFBQXhMONwgM0mArCiyAGAKJpxyHD69FnNzY37979bWflVe3vSq6++MWjQN7ff/oDdzsmrwuGA7duXNTUNFYTfAYi1tQtOn949dOgsPdPYHUIxrQDUpuVfjMd1AVxIKR5P7N69vr6+OtXrnTNjBiM/HZCQr0ildo2JOt/KtS5gMKrVgCKq8fyihD0BSHDiWal2rQeoXcv3XFK4lvfykSOhAwZVqwGDqkk5CFzW94x4HCIRMJslL5GI9BcMfZ6XehttNm0A99jCbj5cGCMSkYKPAmByNL5PdunCf9IBLBlbsgiQ41EApEAEsIeN57sBcHaSvEBihg7It+FDgBxYt4Biczi56mgUBEHkRXkBeqbJkeqZRoBiWg4YMM04ndklJdnYtYCfOhyZQ4b0O3bsrlBoTHLythEjlvC8xWKxzJ//05yctXv3rgyF3mtu5o4cuatPnyETJsySV4XZDE5nOsvuFwQBgOe4erPZTTGNu+ZQTKsBhWnyPlGuCaAon8/32WdvBPwta/78ZzvWDgkeJPDZSF4ZCte4md23cq0NGIxqNaCIakxdpYQ9AYgpsmekwrUeoHat2KdPbZIMLumplgMGVasBg6oJgHfEnr6pnte/56u2sbGqoTE17/+ZRbY5znT77UsGDRpx9OiuUaOeLykZHAyGWDYuCPa2toZIZAxAIQATjQ4/eXIf3jPkr2nTrl+zZmlV1bUs2zJ0aEV5+eh/g97jrn6zUyf3jSmvmFRR0ROZPa/L+J5hNoPdDna7NPhjt0sPC/K+Kexi0ATsdqnliAD2ush7TDQB7BDBWzoCdrt0A6cD2FrETnoE8OARkwPyAvEH51vRASwQn2IQsNulJi0dwMclfNpCAEUhRgEUHSIy1Qmz+d6XXxZY89iJi3BVQ/nnmqbJkeqZRkzPNMuGGhur4nGry1Vst7MGTSsAh4MbPXrSiBGTLBbx1KkDn376YUtLpF+/Xn37Dk5Nfbal5RMAq8ezY8yYJ7A0UhV2OyQS5scff+Pkye0mk6u8fIzLxWHOnaZpVEExrQA0TZMvRqO6AB7n668/HO70/WDaYun3JK4JIe+bUrvGQVTNyjAe1QrAYFSrAUVUoyNK2BNAfh0g/YAK15qA2jX5VO2adD2ZTDTVcsCgajVgUDUpp6dvCmIxKasasybMZujslHql5HlTZGt4BUC+SADM5qEDmDtEVipW7PBOAbrd4V0O4PsIkIkMdAAXJ5AXSLawpwPyrCYEUBRANwARJV8UurMTAMKx2N7jxydPvmro0FnyAvRMkyPVM42AnmmeT7z88q8PHPDZ7R0VFRV33fVrhuEMmpYDxHRDQ+Orr764du0MQei1adPHd95pveaa6zdseCUvr3TChHsLCoZhPh2piguHlzR06Czs7CK/kabpeDy6deu6SAQmT54aClnVprH7gWKaVBEaowDnztXv2bNxyvBhC8aMuSgqCIHJPIrKkLvGXB3NyrikqNZ0falhr4hqXI2DEvYEILGFZ6XatR6gdq3Im1KbRICiWg4YVK0GDKomAN4RL+t7ht0OycldsyiSk6U+R/Va6JqA2y1NtkQA1xlWTBRXA/hwi3dsBHCdYYBuAPksTQSSkrrml8oBUiACTidEo8oJsWoAHytwCWUEPB4p8YgOKJY6N5slUQDdAJoLcDMMAAgmEwAkJ3syM224LY38c7VpcqR6phHQM71u3YqVK+ui0X8CxOrrp86bN7t//+FGTCsAYrqlpf7cOasgXAngiETa3n//97FYMBIpi8X23n33L1JSWEVVKEzjsKue6c7OxE9/uvD48ZAowooVLz733KccZ1KYxoWrKaZJFaExPYBhOh5/fDEDYsXgwelFRdL0BTxWJHC3JcVq6QrXNpv0bKuuDONRref6UsPeoGs1QK4DeFaqXesBateK+Rlqk2T6hZ5qOWBQtRowqBoBTCK43O8Z4TC0tUE83rVScXu7tDynvJ0hitpAItG1kwmuvYxPv3RAPvkYAUGQJlvSAfUsTZaF9napuSoHSIEIxGLKCbGaAI564WMFAjwvZWfTAXkzggB4YHSAiCIAUW0ygTSPuiu7hHyuNk2OVM80AnqmDx8+HI+XA3gBxHB4cFVVXXb2cCOmFQB6SiQgkchMSoozTLUoZjHM0ba2GM/vBrBUV//ps88+vfnmB0kJ8Xiirq7N42EZJoVhGCwBp/rqmV63buX+/f5EYh0A7NkzZfXqlePGzVeYxq2sKaZJFaExTaCtTTx6dMfp08f6F/Z68KqrTMHgRa6xiHhcevhVVIbctWJyshwwHtWarruNajWgiGo912qABCeelWrXeoDataKdoTZJdrnSUy0HDKpWAwZVw4U11VNSesYzLoxnYCYc9jYq7hnYDaoJyIcrYrGuXnY68K3HM7BGMf1XszuSAHodu3Tgu4xnYB6tfLiCdOxSAMWFSq7aZMIjtdnAbFZ+rmmaHKmeacp4xhVXLFi9+sGWljcZxp+TU1NePhSXxerWtAJgWWhpgfp6aGvLyc+/r6npcG3t1kQiyvO3XFggPSmRaLXbSc8w/9FHf9+69ZjNJgwbNnLBgtvsdpbSx44eBCEIkIob8IlimiAEySgDEaXoY9c0TaoIl9tXAeLZs/WrVr0ZCgVnjLkyLTNTwzWOHeE1RVEZBjvZjUe13njGpYb9dxnPINcBHE5Qu9YE1K7lmbgEkJtEgKJaDnxf4xn0uugZz+jKV0skJKH4F8zpxlUecX0kPYAs+ojvk9VW6QBeOuXLTJLy6cCFjeik5D91+QRQFEgWcaUD8mVrEVBgFACXoiLL1iqM6QFEFAHkPEg9t/iSf642rfgP1SI1fyEC5OcP/M1vfrV27caUFOvo0S8kJ+ch2a1pOdDYCJWVUF8PwSCwLONy9c3PF2pqdojiDwB2A3wEkOFwRIuLryIl7Nu35dVXPwsGHwOI799/J8+HcnNzBw6c4nAkKf5HuZghQ2bk5v793LlfAEBBQcuQITPUVUGWJe3WtB4QDsfefvtPGzYsHT946JIF86UGhJ5rQVBWhsI1OZsUv5LxqFYABqNaDSgw+bq2dEDxvp5rNaB2TWZxq8MaTSJAUS0HDKpWAwZVE6BnXVvpmoRO5VFFRrBxkFQPwB/yPv7Id6nWBDAtAd/Hd0j5dABrlCxXrS6fAIoCyXQTOoBjyorfVI5RADSJutTG9AD5xumKurhwnyD/kn+uNq34D9UiNX8hGcCOHj19wIDpuAUsYdB0NJr44otllZWnJkxYOHBgv0SCUVRFLAY7dsCWLVJpF3YZYHy+pkSiGKAQIA/g7YKCluHDb6qpSTt2TPR4Tm/Z8snBg9uCwfGiOAIA2tvHPP/88yybU1j4l7/9bb3FYtYz7Xanv/TSlxs3vhmJwHXXPRWJONVVgcOcRkzrAadPn1i27IXxQ4Z88PADGUlJ3biW7xiu6ZphtCvDeFQrAINRrQYUGP62lCghgOJ9PddqQO2aPA2pw5pswEdXLQcMqlYDBlUToOeeAVYruFzgdksu3G5IJLpSBnEM3GzWBchG4gg4nVIHDh3ADhEyJIWfYtOYDihWEGNZcLmktrACIAUigAN08sXaNAFsipJBPEHoWiWeDmArG7vyEEBRWD4FUCR4ylWbTPgHLt6s+FzTNFmeTs+0KHZjmgBy0zwfePrpe9evZwWh9PPP73/mmQf79JlEAFyG55tvoLW161c0myEtDVJSICcns7r6mWBQFMU4QKXTOcHptFgssGZN47p1L/r9qQAugM8AJgDEAL4UhE8FYVBNzW3ffPPOtdfeRjHtdjtvueUnnZ2QnAxtbRqmcW4y3TRWERpTAKIY2bDhPY7l7rjuuvT8fF3XiYS03KM811btGnPWu3VNj2oFYDCq1YAiqnGImxL2BCDBiWelpmtNQO0aR7AVgNwkAhTVcsCgajVgUDUCGAOX+z0jGpXGqPFPkwk6Oroel8gYOK6XpwbIFxEQRWlklg5go4+sINbRASzbNVROAbDycIQKAYulaw1EOUAKRICsU00HRLFrsTYEGEbC6IB8iBsBFAXQDUBEyRdrI6pBWs9QPgauZ5ocqZ5pBCim5YDcdG3tqWPHIonEGwCcz+f++uv1OTmTCFBXB4cPQ0OD1FPNcZCdDQUFkJcHDgdEo33i8WHvvvvHurosgEWVlWcYJlFePu3UqVNtbdcAjAWIW63Ti4tfcDjYfftMgjAQgBFFazAY6+igmcYlJCimFYDaNPkiGlMAmzeve/315weXlFTk50Nn50XNCOIaixBFaWBWAchd47hrt67pUa0ADEa1GlBENW5dRwl7ApDgxLNS7VoPULtWjIGrTeKfFNVywKBqNWBQNQF61igEux2SkrpaA0lJF62vLc+11QTc7q4ET7yl48M4HcCNfjC3DwHcz6RbQLEjitkMXq/0XKMASIEIaG4+owawGYHJwQh4PNLTCh1QpNKaTJIoTPWjAJq5tlJomDBHAXP8FJ+rTZMj1TONAMW0HJCbDoXsdnsbQByAZZjWjAyX1ysBBw/Crl3S85nVCnY7TJsGmZnyrEVuwYJ5Gzceqqu7FeAZQWiorBzR3u7v1asvw7SLIgDw6enMkiW/LC8vu/32a06fXiiKroKC+gULnk1KopmORsObNi2LRGDRokVer11tmmGkda8pprGK0NjFgLhr1/J4LHr93KvKKyoYvPJquhZFKW1ZDchdW63SHtR01/SoVgAGo1oNKKKarDGuF/YEIMGJZ6Wma01A7VqRa6s2SVJp9VTLAYOq1YBB1SQZtyfXFsJhaG/H/Sqle7LfD5GIsp0BoA3wfNdjhd8vzYLBhFQKoMgAxccHzISjA+pMOI6TDkwBkAIRiMeVSYeaAM5gIrOZAgEpwQ57MymAvBmBAIoiKXp6ABElTzqU5dpiFrS8naFnmhypnmkEKKYvAOLx49UbNy4FgEmTrsnL6+X19h0xYnQgMD4cLsvLax0//qX2djCZxBMn+A0b4ixrslhMPM9kZMCQIZCWhjME5XXlyspysOyHgnAIYA/Psw0NbxYUsOnpTX7/Uovlw3HjRhcWjo/HY48+unTHjlVWKwwfPi+R8La365puawsuWTKnpiZDFOGdd155+umVDodbYRofJSmmSRWhMRkg7ty5YsOG5V6Xc3hhERcISM+2atdYRCKhDchdKxJA5YDxqFYABqNaDSiiGh/YKWEvB/DA8KxUu6YACteKdobaJGlM6KmWAwZVqwGDquHC3k2k8+PyvWf0vHpeF78aGs4+9NCNDQ2zAWDVqhueffaD/PyC22777cyZs2pqmvr0GZabm93eLu7Z4//kk6PV1YHkZFvfvv0HDEifNYvx+UJnzlSJojUzsxgTYQHA4fCMHj19374Hzp7NAeAAWIAzLNtvypSrWlvPu93DfvzjXmfP1qxf//7Ro82lpekLFlzv9SZj57Ne5sbnn79SVWUThPcB4MyZuTt3rpo8efH3l0uY2L376/b25sfvuWfygNKekOh5/Vu9esbAe8bA/73GwLduXdPYWCQIvwaAhoZjhw59VVZ2J8tyvXqN6ttXKv/MGeHjjw/v2BHn+cHnz9d4vZ/fdtuipCTnE0/8+tgxn9ncMXJkxc9//muO46JRCIXq1q1bGg73ZpitongPx6VlZ2+79tr7jh1zeb2lPA9nznSsX//Whx8mxWKz9+7dZLO9efPN9zscLs1xWZMJGhqq1q5dJgiOC6llMaeTc7m+tzHwY8f279jxtdNmu/3GGxlcpltziLtnDLxnDPxyvGco1puyWKCzsytNFttouKaxJqC33hQd+I9cb4osdY4AigLoBiCiCEBEXRgDxz2J1Z8rTH/H9aYI4HZnsWwlzycAQBAObt4cnzXr9miUI6bb2mD1ar6mpoPn+wNkCUKitfV9v3/KypVrv/yyLhaTVh+ZOHF2nz7DYzFYuXL5hg1picTTAJ1JSdOuumrRzJmvJyWlVldLW9Hv2hU8etQfiy0GKIvHbUeOvNLcHExJcWmugWQyQWXl8ba2AQAnAeYC8F5v7eDBc9RVQdZA0jNNqgiNEeDLL5fV1Jx49Ve/yrTZpDnA2B+idk2K0AQuh/WmFK71ALVrxVroapMIUFTLgctpvSn2//L/jzMwyBRlxQ95Xw9Qk98OMPh1nJ9pBKBgdOD7+o2+9Y+82Av18/2aFkU+EGjx+1sABDUwbtyMXr3MANMAFgEMO3XKd/z4HvJpMAgbNwLPsykpNo47C1DHcbvy8sJut/fMmcOJBK4+khaNDvb56vBIzp6t5/m+AG6ADIdjzJQpV+bl9bJamYICaQaxKHo8Ho/JtAfgrMm0p6jIBiD4fOej0U6WFVW/kZiWlu1yHQN4DGCy1drx8MNP2u3270u5z3d+354vi/PyJ1YMZb5jFX/vUU0p5/9M2H+PZ833ewJ+X6V1WxfYGrus2xkkbwYHf/AvZMkQ/Isg6AIWy0XvWyzSdBg6gO9jWxXfJOXTAUyEwOk2CCjKJ4C8QPzBZ3I6IIpgsUjPGuSACUYBLqxoIR05Jt/Iy9cDiCgCkC+aTPiQZDZ3rR1CPv/WpjmOX7XqH7t2HTSZYPjwigULfmixcHLAbjdNmbLg9OmTgnAXwEBBuJnnw/iRIMCRIxAIgMnE9u07MClpQ3v7J4WFiauuuj01NfmKKxZ88MGDPt+bDOPPyqopKxuKnXnjxo398st3AgEby9b26hUuKCjBLs+8PKiuxoFSx5Ah1yQnv3bq1K5evUy9epW9885TtbVC//7u2bNvBhBqa5uTkkpTU7MtFsbnq1+//pNIxG0y/SAnZ+iUKQumTZsbDmuYxtQYI6YJUFNz+Omnf3HuXOX911+flZnRpZLnpS/oudYE5DHA89IBfZeoVgAGo1oNKKJaELoJewLoRbXCtRpQu8aeInVYE5MIUFTLAYOq1YBB1QQwmS77ewau2MVxgKed1arRysbtvTQB8kUEWBbCYSnIKADeh/B9BMxm6Z90ALtKseWIAP5gjcoBUiACuIYatmcpAPacygs0maR/0gF5WhQCKArPCgpARBGAqDaZMP0kEtH4XG2aHKmeaQQqK3f/4x/vdnQ8DQA7d/64sLC8omKMHDCbYezYhcuX/6Sl5ROWfa53b1tR0RCUdOQInDqFrXamuDh14cKZPD/M4/GmpSWHw0xubtm0aUOPH19WWlo+bdoLHk9eOAyxGFRUTPn5z2N79uwqKPCMGvV7qzUNK8pmA7sd2tshGmXS0gbcffdvm5vbAODNN59ev35sIjHs0KFPDxy4LxxOhEL5OTkdDz74x+TkvqtXf/b++0wk8jTD1GRkvDZt2mJBsGmaxm0dKKZJFaGxzs6Ol1/+/e7d6++aP/9nCxe6SGygSpyjoHCNRegBiqjGSQwK15cU1QrAYFSrAUVU40WfEvYEIMGJZ6XatR6gcI2u5HlTapME0FMtBwyqVgMGVRMAxzYu63uGwwEpKeBydc2iwFFRRa6t16sNuFzSTRgBpxNstotWztMEsAQcTULA45Fu4HRAkQlns3UtM6kASIEIOBzKpENNAIe4cRwMAbdbevSgA/JbAgIoCofOKIB6MdULqsOJBJ5iyckXFaBnmhypnmkE1q/f0dExThRHAUBHx9j333lk8uTVNhtHAI8Hyst7/8//vLx+/SfJyYNmz77W6TTjyMexY2A2g9UKZjNMmsQUFrpjMTdWRSCQ+PGPZx465BdFdySy8cEH/+B0MhdMOxcuXLhw4cKUFPD5uqoiNRVOn5ZWnAVgsrKSMzKSz507U19vSiQmAeTHYr7Dh98XhJUAmQ0N//zmm49vueXhM2dORSKzAAaKYrHfv5rj2lJSijVN47gsxTSpIjRWX19fV3ccAP72hz+YrNYuwulULltLXNMmKxMkAAAgAElEQVQBeVST/E55ZVxqVCsAg1GtBhRRjUPclLAnALkO4Fmpdq0HKFyr17VVm0SAoloOGFStBgyqRsBsBqfzsr9nhELg80Es1jWZQHMtdJ7XBmIxafoFAtGocoVuTUA+KQCBRELKnqYD6uxpAPD5pLRrOUAKRAD31pafPJoA3hJwyAuBeFxKD6cDilsCThvG4VM6oL6S8Tz4/U1tbQv/+Eer1Z6T07+jw4rpQLLPNUyTI9UzjUCfPuMtljuj0WkMQDqsEKq4TZt2lJaOJUAiAYEA4/H0vuqqB2IxCAQgGoXWVti6tWu6db9+4HZLgYNVsXbtqkOHOuPxbQDM6dO3ffTRO/Pn39ZtVeDDqCBAQwOcP4/9DSn5+XDixMp4fITZvAoABMEBwApCdm1trc8HffqUbdiwJhz2sGx1Xl7YbM71+bRN47brFNOkingeGho63n77XzXVp6+dPNUUCFxERKPKWwJxTQfkUa2YNCAHjEe1AjAY1WpAEdU43YES9gQg1wE8K9Wu9QC5a8210NUmycKIeqrlgEHVmoAR1QgEg5CcDGlpl/c9w2IBhwMcDqk30+mEWEy5tyvH6QIOh9SriABOkpRngGoCZJYwvo9PMdj5SAdIRz/WKH6Ks/kVgLzASAQcDmnNUTqAtwSSZYjHj81VOqBY1VkUJVGIUQBFBugF1QcOH95/4kT/suFXX32r221Sfa5tmhypnmmeh4qKIVOnDDr25S0jRWE6tC5j8ywWHmEE1KZNJmHv3tb9+30OR5rHkzJwIDNkiLQ+NKkKkykhinYABoABsHJcDMukV0VOjtRqwZ0dHA6w27233HJbSspHVVXH+vdPOnVqwNatf0ok+rndayZMuNrhgFmzrozHXz9w4N3MTObqq+/Kzc3UM43PvhTT8i9Go007d64syi/466+WgMNxEYFZpPJUWuKaDsh/c+y9UVTGpUa1AjAY1WpAEdWonhL2BCDXATwr1a71ALnreLxrwrwCkJtEgKJaDhhUrQYMqibl9KyFDvE4RCJgNkteIhHpL2RFTMy1tdm0AcyTA5AAhDH4KADOLMD3SaYd/pMOYMmYPY0AOR4FQApEgLSW6IAoSk9MpEBihg7IU2kRIAfWLaDIALXZIBKJhUKiKOZlFTkc2WQ8Q/a5hmlypDwfWLlyhc0Go0YtstvtRCQCFgt7/XUPPXVgM99U+wbLefuOKikZfjFwkUiWFbdv3/3CC7sCgUK7/ZupU8eVlfWJx6V1bUlVlJdPLy199uTJBQCu3Nz6ceOexaREelXghQWfy5ub8T7EFBdX3HZbWSQSSU62t7R0VlR80th4cuDAm0aOnBSJgNOZuXjxkpkzwxaLOSXF0dnJ6JnGlDOKafK+zQaff/5Wbe2x2+Zdm+N0SqUQAl3jo4/CNR1QRDUmpFJcdxvVCsBgVKsBRVRjagYl7AlArgMk71vhWg+Qu74Qphfl2qpNkoVc9FTLAYOq1YBB1QTAO+Jlfc/oef0bvxjmklOxQ6HgvffOrapKZxgoLHzlxRdXWq1uBZNX0PfXf1l78OCXFa6ssWOvtNlMlAUR2toCq1adbGmZC1AYi51pb/+KZTMAki+mRI7jXnxx6ZdfrrLZYMSIeU6n18jRkvmRAF3Z8wCM1Wo3m+0WC3i9tvnz78Tl2S0WTI5nLBar2239HpMeOzoCb731aGlBwb1XzeyJup7Xv/nr32afPrKLFj4syPumcBMuTUC+DR/uooUJqXTgW+/Th61FzJXW3GaLAHobltGB77JPn8kkPW2RDcvw8YQOKHpMiGqLBQC4C7uQqT/XNJ1IwNatq6qr03n+fQCoqZl74MCq2bMXq/YrY4qKeg0ceDcZ8FBvaEY8VVez5855ALBJHk4kqiyWOGm4syxwnNjaWrVs2ftnzjQXF6cvWnR9amoyz4uJRLCxsZZlHRkZveJxVm6aYYS6umpBCGVkFDgc7kSCIbvbiaIYjbbW159zOJJTUvIFgdUzLd8aTtO0AtA0HYlAIhHbtOkjgecnjhjRu08fKRtXTpC94RSuyemgBxjcPM54VOvt03epYf9d9ukj1wHSD6hwrQnIKykalXqWyFRVTdUIUFTLge9rnz56XfTs0yeN9sjngZvN0Nkp9UrJx8DJ9E4FoDcPnA78R84DJ0PcCKAogG4AIkq+KHRnJ55gfBw6OrQ/V5vG/ycW4wDItjCJaJTr7Ly0eeByke3tsHu3Iz09q6bmm0Qi3+H4R3n5cJZNkpuORjs//PCtd99Nisdnb968KR5/c/Hi+wUBXnzxoVOnQhaLb8aM6Vde+VOWZdF0PJ54440/b9nydTzuLS3N7t376XjcGY9Dayt0dsK5c6dff/2x6mqz2924aNHNY8cuZFlW0zSZeqxnWgGoTZvN4PfHvvry9ddf/11BZsbi8eOtuIarnJDPPVa4JqeDHnA5zANXuNYDiCgEyL5JFNUIUFTLgctpHnhP31TP6/t8jRo1p7j4r2fOzAWAoqL46NFzvktp+/dDRwfbt2+FzeZh2c2TJy8cPnyayWRW9IZVVrbF49LKH5WVr4RCwd27161bZ4rH/woQ8fmubG5uyMvrt2jR9aLIvfPO8++8889IZBzAwdraU2bzzqysKdiHDAAbN36yeXMFz98O0GCz/ba0dERmZuH/nq4jR7a+996THR3ty558YsKQIQx1ZcSeV8+rp28KwGYDr7drITCv96KcBLJ/hterDbjdXWnXmKFiMin3z1ADOMcS06UR8F7o/qYDitXtTSbweKSmqwIgBSKguZGAGsDGNSaYI+DxSD3udIBsA4DNf9zwAy9AdEC9qwOKcjgAwGSRVu9Xf642feFI7R98sHLlylU2G4waNc/hsBORCFBMywGrFXw+qK8Hm43hONPIkX3vuKMvJisqTFsszj597Lt370kkXCbTnj597JmZzoaGE4lEGYAXwNPYmPPee0c47vRnn738X//17L59uyORTwAGAyxNJP7c0XEWi8JdG1paWgRhIoALICsYTBbFNo+nUNM0pupQTCsAtWmPR2hpOd7UfPbXP7578oQJ2nUhCNIikfIiSFTQAblrbLLruTYY1QrAYFSrAUVUY1oRJewJQK4DeFZqutYESCUhoN4/Q22SbI+hp1oOGFStBgyqhgsbbGA/1WV9z4hEpIXi8HrAslJCvqJvimG0AUHoStoPBIDnpR4TOqDYtAEBLJ8OqLOnTaauhHQ5QApEIJFQJqprArjvHWnDBgLSovkA3QDyricEUBRANwARdQGIxOOH9u07XlkpimIiJlWOYtcHTdPkSL1e96hRi51OCIWkHloUSQA903KA42DvXqnb0maDPn0gFNI2zbLu6dNv8Pler6vblZtrmj79tkTCPXTo7OXLn/L7nQCNAO2i+G4ikVVZOeN3v7uvvV0AsEpD4PbOsrIh0ShEoxAIQCAAAwcOW7/+k87OEMedKC62OJ0F+J+qTWPvAsW0AlCZhqamsx9++HKa2zV7+HBtAr/J81J/iNp1twBxrZgTIAeMR7UCMBjVakAR1djVQwl7ApDrAJ6Vatd6AKkkBMieHBTVCFBUKwAjqtWAQdX4CgalOeGXezvD7e5aKNjjuWi7MdLO8Hi0AZdLegpAANcZlj/9agJ4oSLzRfEJEx9P6IBipWKOA7db6oJUAKRABBwOaZ0ZOoBDXtgwQsDjkUTRAUUzgmUlUYhRgIufbROdnfc99VTD3r2tnZ3xRIIzS9TFT8fapsmR6pl2u8Xq6hM7dmxPTy8tLx/ldnMKAEvAX6utDVpapPrPz4eSEl3THMekpw/Myfktx7XxfHJGRlI0yowYMewnP5nxz3/+q7U1G8AFkAkgCIL/7Nk7Ab5h2SWCMMnhWHPrrbcOGlR2+LCU9+B2w/Tps1yu+K5du3Nz0+bPX5KUlKxnGh9tKaYVgLoVsXfvptOnD/z+rrsqhg+HUEizJdK1RZ2iGUFcUwB5VONIr6Zr41GtAAxGtRpQRDVOv6CEPQHIdQDPSk3XmoC8kuStBIpq0ozQUy0HDKpWAwZVk3J61kKHSETaxApvxRwHwaDUGpW3M3BFUzUgil2b5QaDIAjS0y8dYFmIxbqeAnD/YTLbkwJgnzc+BSBgNndt4yUHSIEI8Lz0wEUHcEyZDOIhQGZXUwD54xICHNd89uwH69fbk5JumTDBbLOpgYtMmkzAcWu3bDn0xRdrYrHVADsBWn1t+GilePbVNE2OVM/08eN77r//ztbWMpvtsWuvvf1HP/qvSISVA1gC7odWWQnnz0ur26WlSXNgNU1zHMRijCgmezzJPh9uZRZfs+aj6upTKSnQ2voUwA8ArgBoA0gH+BFASnn5RwMGdE6c+Gi/fqP27WOjUamcYBAAPBMnXm8ypR44sKW6uqGoqJBlGU3TDCNtrH7hi90AF5uGlpb2F174b6/LPSSvwIZngYLACweqxGdbtWs6II9qfLZVu76kqFYABqNaE5BHNS6TRQl7ApDrAJ6Vatd6AKkkBLCbV97OUJtEgKJaDhhUrQYMqiZAz37gUn82WdCRLABJln7EPB8KIH8ff3DxVwqAGwUrCsR/0gFsOeJKGqQ0BYaAokA8KpIqpwfgepl6B0YB8Jhx6pPZDGbz2ZaWm3/xi7ENDWGGmfD225+++GJmRoYcUJo0m4Hj6trby3jedGGJ/AQfu/jzrqr4FqbXrfuitfV+QbghFKrdt++3TU0nU1P7ygGzWYxE/H5/QzicVFWVyXGMKILXG3W56lpbuczMfLOZVZtWVEUo5Pv97+/Zvt0rinkmUyg9fTbPl+TldbS1merqfi6Ku53O9XPnLpox4wYyjEGaO2YzxGKRV17587JlJyKRUZ9//vTdd8+/8sqbLRZWbRqdyKuIDihMfvDB43Xnztw+d/7EYRXahNw19rJSXGsC8uDBZKrvGNUKwGBUqwFFVOOjASXsCWDQtRpQX0CwOUJRTZat1VMtBwyqVgMGVRMA2y6X9T1Dvj8DPgXgD3YWKH70API+LjSCV0YKQBajlxeI/6QDiqI0D0zz793CZHF8yoFRANVGBSs2b+7f2Pj/CYIIMLeubuOhQ4unT9deoF8manJFxWsZGc81Np4UxYQoetxevar4FqZ5XhBFjDdWEDgAQQG0tJx97bXnz5wJWyzFKSkLcnKKAcSjR/+1ffteAH7y5IrZs3/KMBzd7qlTB86c4Xn+RQAuHrdy3BtmM2RnF82adUtl5bqGBm748H7jxs0iJeAFh2HAZMJn0OYjR+rC4d8B9AkGS/fv/3r27BjL2gxsNdL9pglEVHNz9aFDG81m8+xxk1K83m7CHlXif0BxrQYUUU0JnksN1G8Ba/6n5HjoYU/+YtC13tmhd55qqtb7jTQBg6rVwCXZI2Ve1veMREKa4o+NMlySDNukeD/HvinyvgIwmy96H5cBwH5DCoCnFr6PACmWDmDJmAqCAP4AKAFSIAJkeT86gEuDyAskGB3ARVaw54hhIBpNdTjOMwwPIADUMkwSLjwgA5QmeR44rig19V8vvPDp55+HqquZzZstnDUSkX/e9T21aUUVqUVOmDB91aqH29q+sVr3lZdPT00tUQCff/7xihVZ8fjNANH8/F1OZ1okcnbDhi+i0b8D8AcPzszMHD5w4Fh6VXCci+NaAOIAjCg2NDTcDHB7c/ObubnNo0ePr6w8NW7cLJstWb6uPP52WEgiYbZYIgwTFkVgGL/VykajrKZpfNpRxyYFQFEtLc1/+9tDx47tmTl61IwBpXp1oXRN1qvQc60GFFGNkxjUwWM8qlWuDUW1GlBENTnN9cJefR3As5LiWgGoLyDYs0RRjQBFtRwwqFoNGFQNFxYv6Vk7BOx2SErq2rU7KemicVUyBp6UpA243V1rpOPAFzZm6QDZ6AkH6zBFD4fK6YAiE85slnJRSSacPKeQpOhhpqA66VAN4BA3pugh4PFITxZ0gAzlcRwCixYt+mDFigUnToQ4bvCAAVMnTwarVQ4oTZrNwHFMJNKnV68HCgu/2LLlw61bTVYmKUk5LqtnmhypnulJk8a+8MLfDh9el5Nz1YgRUzweDvv6CXDuXH0iMRUgAyAeDlsBQk7nlnh8CEA+gBgOj/L5Kr3esfSqGD166OTJI1evnhyNZkcih+LxnQCp8fiApUt/HYm4E4nyr7/+0ZNPPt+372BB6AAAi8Vls7FYz14veDwZM2ZMOX/+nra2AdnZp2bN+l1amlnTNMNIw5koEgcpKQAR9emnr61d+9GMkSM/fvVVG3biozL1GDh+0+WSFqzVdE0B5FFttV7UqSUHjEe1AjAY1WpAEdVkbFkv7AlArgN4Vmq61gRIJRHVijFwtUkyxK2nWg4YVK0GDKpGgGWltT8v63tGOAzt7ZBISCsY4wAoebglY+AA2gDPS0PcCODMSVzbiwLIEzwREEUpoY0OqDPhOE46MAVACkQgHlcmHWoC+GRBZsAGAiAI0ggYHZCPUEej0NlpZpg3f/ObHceOWbzesUVFpo4OCIflgNIkKQFFdXYCQCIK7e3an6tNkyPVMy0IbEZG+YIF5YHARYPkBOjff8CqVVvC4RKGCXq9Yna2p6Rk2JdfLvX7vwCIpqYeKCh4yO/vpirice722x8fOXJna2vN2rXObdtWCEKxybQiFGISiTUA5vPn/7py5RenTtXu2LEZAJzOxUlJI2Ix5sJ6/OzMmbf06jWstvbEgAGDk5OL/X5G0zTDSEnLKBKfOykAigqHYxvWf5aVkv7nH/7QFgpJ30Rl6rrAbyYS0rir2jUdkEe1IgFUDhiPapVrQ1GtBhRRjQ/slLCXA3hgeFaqXVMAhWrFGLjaJAIU1XLAoGo1YFA1ydmlLM12udwzrFZwucDtlu6lbjckEl3L5mA7w2zWBUgDBQGnU+rsoAN4ocLHBwRIsi8dUGTCsSy4XFLWuQIgBSLgcIDZfFHSoSaAzQh8HkGAzHakA7hsDt5iEXC73RkZV2RkgNstXclUwEUmCYCi7HYA4MwSpf5c0zRJs9QzLYo003Pnzj93bvO2bSfsdldZ2ehhwxx9+gx75JF7d+z4BoCdN++FkpIyPHBKVTgcYDZzI0eOsVhGDxky5LPPPmxqOpaamr52bea5cyKAKIrhw4fXr1z5QSDwDABnt38+Z06e15vjdEpV7XCwgwaVDxxY7nBIVyG1aZblDxz4JhJpLS0dnZ+flUgw5BckojD/U2H6zTefqDyxa9HUqTmFhdIHRJlmXSQSUtqyfDkpuWsKIHeNfeialWE8qrVcdx/VakAR1ZhKSwl7ApDrAFaVpmtNQK0aWwkU1QhQVMsBg6rVgEHVCOD5drnfMxTrTVks0sYpGPp4v8UBD01Ab70pOvAfud4UGUBAAEUBdAMQUQSQrzeVkNbmUX+uNk2OVM90t+tN2WxJeXlzx47lYzE2I4N1u5lwmKmomDNs2PRwGDIyLG1tDP7eHR1idXXV9u2fezzZkyZd7XCYtNZAYtLS+i5e/JDLJQQC0NLyQFPTqFisP8Dmo0dH8fxpgEMAvwyHG+rqztrtOSTbk74GkskEDMP/+c9LNm7cyPNFubnPvfrq8kQiSW2arIEkN/32209mp6b8dO6VKUjLlanrglSiesNj+emgB1wO600pXOsBRBRRrVgLXW0SAYpqOdCz3tT/6bwpvXQOkjlATxZSpFXopY5Q8igM5pOQlAm98gmgWSBuDU8HNA+YYHqA3o+eMcoPSdC6OKlNMz9F37TY0lz/1coP/fUn+w2fOnjYbLvdybLAMGJdXfWnny7z+4OTJk0cOHASy5rIFzs7obmZj8WiPG/KyLCmpYEgAMexVqtVEC7KoGlqqrnvvh82Nw9kmK83bfr0979/mWVdLAuCEG9vb0skTE5nMscxAIzVasFddpYseXbu3LX/+MeL+/f/kedvA2gB+AlAmdnckJ4+PhYL7du3bfv21QMHDpw5c57NlgzA6Jk+eXLP3r1Hg8HtAOYzZ363evX7M2b8WG1aYS+RiH711fuxWKQgO7tvSQlDCv3WVQkgsqy/s/PrzZv37N5dWlIyd/r0DK+XUVQV+SI5oG8d1Zo/RqJaASgOQ/4XOqB3npJfzfiFAvuvKKrlgDr9SQEYVK0GDKqWZ072zM+4KDGZJDKjKfwLTkrQBHBuB3nfYpHyDegAvo9tVTI7BDE6gINaeA4goCifAPIC8YekmVMATGDHZw1ywASjANgti+klCCjK1wOIKALg+yYTADCs7ud005FI29v/fGTgqrfGJxIr173H/+rFKdNvtFggGDz/2GNL9u6dLAilGzf+7fHHnYMHjyamT50Kbtu2u7U14nAkyspy7fah8TijaXrTpqVNTTMF4QEA/sSJ60+e3DNgwCSO4z/99KX9+09arYlx4ybMnXsDw7CiCDzfefr0EZPJNGHCFWvWbNm/H7srTW53a0nJWzbbLzIysvbu3XXwYB3PT9y0aVM83rxo0U8tFrueaZ4P87wHgANgRNEbDndomsZhTjQNEN2w4YNXXvmvnPTMB264ITU9XVpLVTOq1a55Xvrnxa4Fjnt37drDr756RSi0x2J5trX1t3fe6SLHKo8BMm/ju0S1AjAY1WpAEdU43YES9gTQi2q5a01ArRp7iiiqyfQLxQVEEzCoWg0YVE0Ak+myv2fE4xAOS/syY5NW3crG7Rw0AfJFBFgWwmEpyCgA3ofwfQTMZumfdAC7SrHliAD+YI3KAVIgApjeiu1ZCkDSP0mBJpP0TzogHwNHAEXhWUEBiCgCoKhYDACEhPQ7qT9XmyZHarFAbe1ZOH7w5/G4G8DW4f9ox4bR4280meDYscNVVR6e/zkA09bWvnHjV336jEaRogjLlx85coTh+eEM07x+/Qvl5b/3eLI1TTOMFaANQAQQGKZDEKzhMBw8uOG11zZ0dj7CMOFDh35RWjq0sLB/OJx4/vn7Dh6sBQiWlGQ6HBlO58uh0HGT6eD06RWzZt37zTf54XCooSGQSMwAyAqHe+3b96+JE/3JyXaG0TZdUDCkpMTW2nqbIBSkpe2eNOnvmqZx2gearq9veOedF8RE/L1HfjduyGAG8xFIHaFTdV0ggK4FQe06zrKn9+69JhSaIoqDo9G/HD7cev68Kz1dAhRRjZuSyo/1UqNaARiMajWgiGq86FPCngDkOoBnpdq1HqBWrRgDV6smgPzKowcYVK0GDKomAI5tXNb3jJ7Xf+LL4fA0uZI6AZwA5xjWmpaH73u96TbbGYAogJllT2dnDyZfaW2FysoAz5cCZIiiq67O3Nxc7/Fka03pia9d+6EgHAPYA3B84MBpAwaMiEZh5841odB4gMGi+HVrq7h791f5+f22bl3x5ZcbEgknQNHZs9sZxpSSYp80qX7YsBumTp3f2GhiGOA4zm4XAToAgGFak5N5i8VK/e28jzzyxsaNH/n9daNGvZyfX9Le3o0Qn6+hqurgTbOvmjio/HuclsUyDJeS0sAwoii2M0zQ47FbrT3h1/PqyZvqyZv6NnlTUtOYDvzv5E317l0465of/iARzQ34gkX9bpl7g8sFLhcMHjz4uuuuW7nyhmg0qX9/+5VXXoPZ6gBw/Djk5qZXVZ3meZZld5aUhIuKcl0uDdPbt6+oqrIA7AXYxXF/mjp1ptfLhUIwderspUv/HAyeBgjy/C2vv77J7U72+1t43g1wHcCvAGKiuLi9PSUzs3DOnIVWKzQ24tIMtv79+7tcT7S2mnJyWq+++mfZ2Ul6uTwXPJgXLLgBE6v0TJNcHoYJPPXUzclu19UTR4HLRUvmucS8KXNy8uJ5855va9tYU+NLS7t14cL0goKevKmevKn/6HtGNCrNn8A/TSbo6JDmZ8rnZ3CcNkC+iIAoStk8dADXAyeZzh0dwLISRgew8rDliIDF0rUGohwgBSJA1qmmA9j5S/KdcG1ExOiAvOsJARSFrXsKQETJF2vDyRwAfFxaaE79udo0OVKOg85OdtykxVl5wzs6WvLzi2y2DDzSUIi99tqf9u9/RSTS2adPb0Fw4iHU10NVFeTm9hkwYF8isb5Xr4Pz599ltWZ2dGiYDgbjgmADyAG4CuB/OjuFjg4IhaBfv3GLF09ZuvRTv/+fAH0CgX5bt3593XW3ut1/DwRwlR4GwCyKbCjEY121tKBUJiencNGi37a312RkFBQW5nd0MNj3QDGNvQudncCy/K5de6LRzqFDhwqCVw0cOLC+tvbkTXPmTB0w4KIiSB2hU3VdICCKUn+IyjVjMg0rLPzTAw9U19RkJyUVFBQwHR1dgDyqsT+ERLUcMB7VCsBgVKsBRVTruVYD5DqAZ6XatR6gVq3om1Krxj/JkdABg6rVgEHVBOhZo7BnzyX6nksJp3Pttm1nGxunTp5clJbGYDvj33rPJQKwZWW9Oa63xQKhECQS8Z07P29vj86aNbO8vAwA7HZ+06Z1dXWnRoyY4PP1M5tZp9M5fPjoK6/sn5JydXKyl2EYTdOzZs18442Xqqt/CAC9evmnTp3p8YDJBMnJ3MKF1x85sn/HjogoAsMEvV524MC+Tz759EMPPR4InAU4yDC1mZnpM2f+2OPpmo1rtYLLxZSV5TNMPnS3D5DJJNTWHt+2bXNBQe+JEyczDDz11JJvvjmaSCQPGGB+7LE37HazfH3upqaal1562GGzDRsyxJGZ2bXLveZGQJe+5xIjCNk5OdnZ2T17LvXsuXR53DN69lzS33Mp2tKy5A9/OPT11+U8/8brrz//yCMVffv+b++5JIkKhQDg2+25pDbd2tpx331zqqs9guB87bWXnn32C4vF9vbbTyxduiYer0hOfm/s2D8nJY0URcbtNqekpJJw0DTt8SQ/99xXW7cuA4CxY18WRTser8kEFkv2hAnT6up+0t4+ICvr1NixvwuFLMOGXfXCCwN37FjJ80kclzx58py0tJJAAFgWWlulfHeHQzx3rnn9+o8bG89Pnm5LiL4AACAASURBVDyttHQ0x1k09wE6eHDr448/7PNVmM1vX3PNFRUVk1av3hIMbgXgfL47li9/f86cm2Vzk8X161fX1p6aNnTYj6dNY7CiKRsB9ey5BD17LvXsudTN/28CqxWsVkkW/gVXdMFbMfaa6wFWqxSI5H08YegAyWPD92Oxi8qnAGSAEZ8C5JlwCoAUKE8cJA9cegAeOSYdWq2VjY0NR4+uicfNAH9tbFz5zTcVgwbJAel/xKxN3AIJQw23xyMHRgGIKALg+2YzALCc7ueapvH6qzZ98ODaqiohkfgYgK2t/eHOnSvKyoYfPHg6Gl0OkOzzrT59un7kSDCZIDcX3G5pJhPFtNttnz//JvkDGQJWK7t48S2DBw+rqTlRVjY4J6c4FmNsNigq6l1U9IuUFPD5up59yWKAHAcAgWeeeXD79mRBKFm37pmHH/75qFHTNE1v377G5/uJIFwfjbYdPHhvcrKH5wsATACsIOQGgw24U44oAsOIbW21u3au5PnEwmlX2LAnXa1SHdVq15gxRXGtCcjLJwmpJKoJYDyqFYDBqFYD5PgRwCNXu1YD8t+ItBJw4U46oFZNVlDXU40ARbUcMKhaDRhUTcrpybWV5hzgj+Kf6h89gLyP80WNA+oDoAN6xyB/U+/vRgDst73wPgMgAIgAAMAzDIsZwDJA44cAegegAKi2KR9ekmmGYQFwPU4RIMEwLADDMOSXS2WYII4ep6ZKp/C3kHfhTbaoqDw/vxzPPgrc0SFNVQYAn+9kdbXI808BcG1t1u3bN4wcOU3TNMNgtQCAyDBiv36jevX6rLJyiSimZmXtnDTpNUKGw50vvfTQrt1f3nX11deMHXXJUd1tlcldU+oUo5osW//do7rb36Lb0tTvaLpWA5Si6MC/iWo18O0uGpf1PQPHx2KxrknzOB2fjGBjX4oeoHgff3B2MgXAOTXy9wlGB7BnE4e/EMAfghFAUSC+g8VSALxwXiiwX3Z2fnn5qLq6ITxfmZn5z/Hjpda0+sCwAYFmEFD84noAEUUAfD+RAABRuGjDQ/nnl2R6yJDpJSV/OXNmuiC4evXyjxlztclkHjKkX2XlFfH4aLvdkpf3gCBAJNK6efMndXWOkSOvZRizQdMKwKBpnge/X1oNj2EgLc1ls50HiALYGKbe601W/4/457hxM9ev/0VLy3qzec+QIdf07j3ypZc+/vjj9zs6/Fde+YrXW0DGL9esWbp69YfXTZr09JIlbtwLUFOlOqo1XeOFhuJaDSh+c5zE8F2i+lu7VgByjGx4p3c+ygG9qCZHpQeoVZOeJT3VCFBUywGDqtWAQdUEwKywnjHwnjFwzTFwM8CzTz65dtq0s42Nv588uSgtDf5fGgOXi7S99trXe/ZIY+CiaAeABx54eNSoMadOVUUi02OxvGi0c9myfwaD9QxTP2DA6y+/vMzhcCtMd3R0btv21b5929vbG9LTM8aNmzV48CSr1fQtxmXjcairIz1dMHJkn87OK5YvnxGJlPTu3TFv3l88HsW4rNjRcXbFimVNTS233PIDnmd7975h4sTJ4TCXlOQdOnToxo1fbdr08YQJV5WU9DWZGL8/dODAaq/Lfd3cee6sLGhr0x3i/m5j4DSgZwy8Zwy8Zwz8shoDh0DAJIozBw6EgQPB4ZDGBv83x8D5cPjwqVMdTU2+xsbvcQw8FAIA88iRV8vXhOZ5rl+/aWlpsG4dxGJw/Pghvz9XFB8AEE6enLd9+7Zhw2YoTK9a9cULL3zV0TED4BjDrPrss73//d/O8vJRkUjL8ePH8vJSkpL6JxKsyrRYW9tSWysBsRhUV5+pq6ttaRkYjabzPMPzYDKxN954/+DBc4JBX79+ZTZbGtYJMV1b2/LMMw/t2DFUEAZ5PMvvu+/Gfv2mYe9WVdWRBx542Oe7ASDy4Yc3PPPMR/n5JR988K+1a5deMXT4gPQMqUWjN8TdMwbeMwbeMwZ+ae0Mt7trwovHc9HWMaSd4fFoAy6X9BSAAM6XkT+yaQJ4JcPnGgQ8HunxhA4oZtxwHLjdUstRAZACEXA4pHVm6AA2I7BhhIDHI4miA4pmBMtKohCjALJnW55hnnzr/Q/XH46EUxy2U/FEwmSRKPmzr55pcqR6phFQmK6qkoYD7XYLyx7neRFA4Dh/UpLN41GaPnJkX2fnVQBzAYKiWOf3w/79X/XqlfPXv/6mstLkdp+dMeOqO+74yYkTeysrDw0fPrqoqCweZzs6zj733G9Onza53WdHj55gNsOWLet9vv4OR2V5+dyMjLyMDCYzE7xedtCggWgaLwgOR5fpQKCqttbK80sA2ECg89Ch7bNnz0Xgq69W+3wVgnA7gNjcvOHMma39+vXasuUjE8f98Lpri/v0VqvuUknqSLPNhwA22RTNCOKaAshdm0zSdUpdGcajWgEYjGo1oIhqhWsKQK4DeFYq2hkUQK1a0c5QmyTNCD3VcsCgajVgUDUpp2dOH0Qi0oYkeCvmOAgGu3p+STuDZbUBHMrEpwCyj48odgOwLMRiXU8BOIcIy6cDmEGBTwEImM1dT9dygBSIAM9LD1x0QBS7HrgIgH/SAfnjEgIoijye6AFElMl0sKrqzS+2nqjbAnAe4HYAISujBB+tFM++mqbJkeqZRkBh+uRJqaeod+/B9fU/q67ew3H1paWFRUVjAwGlaa/XwzD1oigAdAI0syykpIz9/PNlmzYV8fzvASLx+LyamhPr13/d2TkmNfW5X/7yiVGj5nz22bKtWxEInjhRIooVAG0AZxnmR1brMY8nx+3m5CGApjE7hphmGK/NdhYgAmBj2erk5FSstM5OSEsrZtl1ghAHEDhuj8Px4w8/fPXEiQNmk2lUcTGLT7sXq+6aHilXpgfgukOCoOGaDshd47OtZmUYj2oFYDCqNQGKawpArgN4VsrbGXRArVrRzlCbRICiWg4YVK0GDKomQM+cvp7Xv8+rNRAIx4oALAAHAA707l0+d+F//a/+j/E41NdHq6uPnz3bmJ1d/9OfPnL8+JGsrNSxY29kWY3InDbt2urqx2prd8ZiB+12Z2lp2eTJ17z66hM8Xw/wMIC9udm6a9eBYHApwIDW1uVbtqwfNuyK5mafIBQCsADvi+LVAH8HaAC4XRSbwmFRFMWsrO4PNTe39Oqrr//ii+vC4azevdkpU35EPpo0af6cOVuOHr3dYokNHPgDv7/91Vf/kJ3k+vu99xZkZ3d1ufS8el7/Ea//2/cMiwUcDsAtDrDhFot1rauDLUeO0wUcDqkpigBulitfBUkTwB4T0vjFli8+ndEB7G3EZxMEHA7pzq8A5AVGItIAHenY1QOw64mstIPHj21qOoDL5mBnEAIoCjEKIFvjqHzAgH5FK877nuD5FhHCc+Zck5RkVayBRKpC0zQ5Uj3TOJZJfu/z5+HcuTM7dpyOxQbU1ATPnn0kJaXc5eL9/uhNN93FMKzCdGlpyUMPPRkInGlvj3o8ztzcUovFmZXlBTgMsBCgPhzeG4tlAbAAIIpmHDKcPHnc6tWvtrezDPOeIAwA2AzwAcAwhqnMyBhut7MFBdIBy01jnctMszfddMfw4ROiUX9+fm+LJRn3ZhZF8HhMS5Y8dvZspddrSk0tu//++YyQ+PMvH5w+YYJEqFRLKuV1FI/rAriSkny9KXKsdEDuGhN1NCvDeFQrAINRrQa6c60LkOsAnpVEFPZNUQC1avmeS5qqEaColgMGVasBg6pJOQhc1vcMHOOyWKRGWTTaNaKFPUvYNxWLaQNmc1drDpMNsAOHDmDPKb6PACm/W4D0NpKDkZdPAMUBY/uX5MnpAeT3JQUSM3QAl5vGI0eAHBgdIKJ4PsPhePkXd7y/dde6bXs3HRJTUnIv/lwqQM80OVI90wjITdfWQl1dXSxWDNBHFEvPnfvo3LmZDNP35MnbRowYW1xcrjAdizEOR2Z2dqbf39Xxe/58G8NcLYpzAYREYl0iEQS4F2Ck17t16NC7BcE8aNCk+++HnTu35OdfuWzZpw0NW0XxdwATRPFkOBxxOBJbtqxubvZPnTqL49KJadzl6WLTbEZGX/nWcAhEowBgz88f4nbDvn379+/fMGpA+aiS3l3VqlItqVQEjx6AKjH5UuGaDiiiGgf2NCvDYFQrAINRrQYUUa3lWhsg5eNZSUSRytAD1KpJV56eagQoquWAcdUKwKBqAuCN57K+Z9Bn3GDdfPepOmBsMiBA91PUAHTn8sgBysy7bgEjc5QADE3N69aM7IcBKM7J/vWdt5SmebYd2y2KjOGvXvQfxuPxAwd279mzxuNJnTZtUU5Ohigymqbr6iApyctxTTzvB2gCaAQYJopFweCgc+dOFRWVGzFdWFhoMh2KxxsAggBNAP8AqDObl9xxx+3jx88Ih0Mej3PMmFljxsxKSYEhQ2b/8Y9P1tYOA0gHCLe1Hfn444eamo4KQua77/7juec+c7uTDJoG5XRMYd++bT//+Uy7xXTr9CmZXvclKBNFEEVRECKRSKSz0+Z02hwO5rtXriLG1H+51Kju9mAMhv33PjUP4NLOd8qsVIOzCBWAQdXq9w2qVgCX9T3DbAa7Hex26V5qt0Mkouybwi4GTcBul55iEMBeF3mPiSaAPSZoHwG7XWrS0gF8uMUtGBHAg0dMDsgLxB+cb0UHsEDsTEPAbpeeLOgAPv3ihpEIoCjE9AHRam1obq5vaMjJyspKT2dQtdWKj0d2u7K/hFSFpmk80tOndz/22GOtrVNZ9syBAz979NG/2e3p5EDI782yEApBcXG/QOCbQOAdi+W9+no+Hq9kmL0pKUedzsVNTcfT03tbLCZimmVD589XxeNWl6tYEDoaG2tZ1jFu3JQVK96qqbkfAIccTzBMKDWV8fmann/+UZeLmzdvXu/e4xiGtduhsLCgoiKjvn5bIsGaTCfN5s7z52vi8RUA7Nmzv9iy5b2FC3+CptEQxTSqIKYbG8/99a/3xaLhP9x5zw8WLDBhE0xOaKq8UEdiJFLV0vL+F180Hz2a3r//9VdeWZSWxiCAASbvepJHBQWQxxgOosqjmgDGo1oBGIxqNaCIaj3XakB+HSA9rorK0ATkp0M0KvUs4adyQG4SAYpqOWBQtRowqJqU09M3BbGYlFWNQ4VmM3R2Ss1zed4U2RpeAZAvEgCzeegA5g6RlYoVO7xTgG53eJcD+D4CZCIDHcDnEXmBZAt7OiDPakIARQFQALGj45udO198993UurrW3Nyf3XDDuP79Gex5EcVo9CLT8kWjseBgMLF//yaeDw4YMMHhSCFHunr1V62t0wXh54IgnDx56759B8rLryAHQn5vXFjQYnENHz655vQ2/9mWXDh3xPaz8dPmnD7tev75NxmGKS/vdc89jyUSXCgEHJd46qlfHzvms9s7+vcvCwR8p06FLRbfsGFD+/Qpr62dIIoTAZZlZz8+YsR4t3veRx9Vh0I/Amg/cuSxhx56KSenxGoFAM91193j91eeOXMsKyslOTmpsbEVlzBhGD4e50hV4FMdxTQ2gNF0R4d46OD+c2dPDyrt+8v5823xuJLQVEnqyGTqbG196913kz7+eHYstmnHjjf9/vtvvNFlsUgA5uqQEohrUoImII9qzNUhUS0HLimq5YDBqFYDiqjWc60GSPDhWamuDD1AplqqC0XelNokAhTVcsCgajVgUDUBSP/V5XvPsNshOblrFkVyspSDrJifkZSkDbjd0mRLBHAHH8VEcTWAzQi8YyPg9XZtkEIB5LM0EUhK6ppfKgdIgQg4nVJfJB3AxwrcExgBj0fq2aQDJM2c4yQARWFatw7g7+j4eMOGW3ftmiQIG+rrl+XkDBw8OCk5GZxOYBinE5KSNOYMoEi7nX/44Zt27z4jCJnFxS+++urK5GQzHmlhYTrLnhEEASBmt5/NzU1OSuo6EK8XQiH/mjVLm5qSWHauxWINh4O+6nVfn690AjxmOldlDlRVtUciSwGgtnbajBnTJ06cZrHAzp0rvv66Lhb7J0Ds5MmRgjAjkfgrQCQavWbKlPEezzOBwE6PZ/Mvf3nv1KmLn3/+j6HQBFEcCwBNTZ+2tR3v378kKQkEgXG5eo8YUVxcLJjNXO/eieZm56FDUwUhq6io4ZprnrHZJNM47EoxjWPgaLq1tWHlqr/7A6133XOXLTNTg5AHLSmC1FFSUrC1ta26enEsVgZgi8Veqa4Oms0uBFwu6bvy6Rfomg7Io9pmk55tMarlgPGoVgAGo1oNKKJaz7UaINcBPCvVlaEHyFQDw2jMz1CbJNMv9FTLAYOq1YBB1QhgEsHlfs8Ih6GtDeJx8Puld9rbpeU55e0MUdQGEomunUz8fmmXErLaqh4gn+aNgCBIky3pgHqWJssCbuypAEiBCOD4lXxCrCYgihCJSI8VCPC8lJ1NB+TNCALggekDkaYmoa4uXxAcAAWCINbVRZqawOnEJ8TOzotMkwJQ5M6d23bvPtPRsQnAdOzYnUuXvnPttbfhkY4bt6ii4mc1NTeZzfUTJkzLzh4iP5D29rYf/nD+uXPFojjU7X57xoxrAXy9I+247F9fPrH20P5YbBhAMgDEYsNOnDhVXj4tFIKDBw8nEuUAXgAxFhsKkArgBfAEg7379Zv06KNX19buKCi4oaJiRGcnW1Q03Gz+IhabyDAdSUmnXa7i9nZgWWhrg/PnGb+fi8c5UQS32/LYY8u3bXunsdE3f/714bBj166tO3Z8bbPZJ09e0KdPaSjE6JnGnarR9KlT5/bu3bRo2rR7rrgC2to0CE2VpI5E0RmN2rOz95hMrkRij8lkz852RqPQ1gbt7RCPS8+2pAQSFViCHiCPatncY1EUfT6fEAgk5+aaOjsvIaoVgMGoVgOKqMZp1ZSwJwC5DuBZqa4MPUCmGjCDQtHOUJskm1zpqZYDOqq74l4PMKgagWAQUlJ6xjMujGdgJhz2NiruGdgNqgnIhytisa5edjrwrcczsEYx/VezO5IAeh27dOC7jGdgHq18uIJ07OoA3rS0vIqKNw4dmhiJbLLZ8ioqvGlpYLeDxQIMg+MZigudrCpCopgKwAEwAMnxuJ8cqdeb8cc/vtLcfIxlPcXF/e12Dh+wENi4ceW5cwU8/y8A1u9/b9u2lSUl1kpgroUhveHEKYDq1lRRXAfwIsNwDsfmvLxrrFZBFNnZsxcsXfpga+sbotgGUAmQAHibYRqLitoHDRrscuVcccUoXOo8HOZbW+vN5u2JxE1er/+ee57o06cvHrnVCm1tUhJmSgpkZQkbNnywa9e2YNBktX44ZMjkRx/9o8/3A4YJbNx4x0svvef15uuZJl3ooVDTxx//VRTiV82YAXa7BqEIWrnKC3XkTk29YfHi183mXSdPmkpLb12woDEU2r1vX2lKSl5qqnTjkkc1iQocXNIEtPrQBZ5/ffnynXv2sJFI2dix9yxYwOGnRqJabzzjUsP+u4xnkOsADieoVWsC8tMBtzaQZ+ISQG4SAYpqOfB9jWfQrzA94xnSTRhXUUWh+BfM6cZVHnF9JD2ALPqI75PVVukAXjrly0yS8ukAXvzIwpbq8gmgKJCs8koH5OvaIqDAKAAuRUWWrVUY0wJs/z975x0exXX1/zMz2/uqoV5ASAIkqqiiWaYZAwYMbrgR95LEju3YTkji2K/TXIhLHNtx78YNbDqmY7poEkhCQr2XlVbby8z8/jjD1TC7OyzOm1+SF+nZh0fMfvbq7veeuXPLuefQ9M0LFqzVaHaXlmYXFCyeNUuDGzksS1qGCEkKwPJycydkZAQrK+8CiBs06MTUqY+J/iCl1cYMG1bkdguf9fnYkyd3u1zNQ4dOVyq1FGUH4AAoAH9zc0JX17pA4KdtMO0APA+8FXpuA6hTKh+kKNrvH/nee6+63e4pU5ZmZubfdtsNr732jMdjBngPoBXgk7y8zvvvf8ViSfJ4+lU8ffroxx+/53b/g+dZv//+2NhklqWxJk4ndHUJXtxGI3R3V7z33uqOjpcBtBUVv58x43RPz0Sev4Xn+ba2H86cOVFYmBZJaYw62t3dvXr1nT/s27K4aOqcsWPDEOSTkaREyYLB/MzMVStX9thsFqt1x8mT7336aarN1pWc/Mh9900aMoRCf9Ow9wsJtioBJMZDUUDTJyoqnn/77bfsdiXAr8+cGZmRMWPChGitWgJEadWhgAQTx7WVByTXI0kdCoR2IOQUtxgQK4mAjNRiIJzUct+IAFFKTYCBuLbCbtL54Nv94pIdbOzFIgH4ItfJqQ55AN0S8DpeIeXLA9iiJFp1aPkEkBRI/O7lAdy9l3xTMSYDoJIoV6hi4QAqGEy0WO5dsgQWLuyfpKN0PI/6iROri9tKr7esXr1x27aPvV7bjBm/sFqTJX+QCElR7OrVj2zZ8h3Ljh006KUXXngvK8teXb2I568CMPP8WK/3B4DpALkAZoA5APkAg4PBbIAVPH/7qVPHdLq/5uRMM5sTOjpafb45ACcBhgOMZpid8+fPy8gYLm7qYBBKSw/19RXhZobbXXzy5OGUlEkoYV8fdHUJW6pmM7S0nO7tLeT5IgBwOqfZbPtouo/jWICgUnnKZHpYRmncxdy27bM9ezaPyR5y/8IFb335ZXZc3LXFxQrMlkNOS0iMNoLZUwxj1WqtgwZ19PWt27Tp96WlY3n+k5aWbzZtGnnbbXrMKURaJVRrccJwUY05jjtUWbl5377J+fmzp0w5eubM1L6+KTwPAFMdjl0lJTPGjInWqiVAlFYdCkgwVEPG7AkguS5pDBkgtAPB6xJArGTYD0YCJH8Xz4vIfCMCRCk1AQaeGZiLGTCFGe5cBYP9LoO4B65URgQMBqEcBPR6YQFHHsClJ7Ilhe/i1FgekEQQo2kwGIS5sAQgBSKAG3TiYG1hAZyKkk08juuPEi8P4Cwbl/IQQKGwfBngQgdQTqHYdLLsw90HfAG2tbVSr+e0WlrsIEqaQq8HmlYuW3Y7FhAIcIcPf/v99wd1OsXixQvS0ycaDBQK2dR05vTpOr//NICqvf2Fffu+e+21715++a2NGy0sW0zTtTpdpc+3KRA4B1AKUA/QA8ApFE2BgA3gdzxfUllZe+LEhoKC2/r6HDw/B2A4wDK93jdxYsbVVy8jXgtEyPHjp5rNH9rt2wHAbP5h0qTbsA0NBtyZ4jnO5fe7ExNVGs3I2NjnWls3A+iNxt033fSL2Ni15eV3KJXOiRNvnDixEKOIhlWaooDjeqqrD3JccMSwMTf+cXO7rZihq7459tqbq35hQrcOPPQbTmpBSmwj1PQ84HW7DS6XmecBYBDPs319QdyaF1s1CQUYDArhHsW+tggYjVww+OH69d/97W9FfX0fabWHr79+XlHRy2bz1t5eJcBek+n3RUVgNEZr1RIgSqsOBSRWjVvcMmZPANIPYIuKG0MeCJUad7AlgFhJBGSkFgPiDgSPB4g7EBkgSqkRwJ7tcn9m+HzCHjX+q1CA09k/XCJ74AwTHiAfRIDnhT1weQAnfSSCmNMJNN2/VS4DYOORrDpuN6hU/TEQxQApEAESp1oe4Pn+YG0IUJSAyQPiLW4EUChcOZUBiFAKBTBMRWXl3U/+o61rFMfv/fzzTyZOvC03d3ho3LxQpU+fPva7373Z03MHRfUdO/br3/zm7SFDMlFIh4MNBpUAeKxP5XL5AMzTp9/e0FDa0VEWH09Pm3ZXefmXO3e+yPNPAagB/pRIVfkYlZ39G8f9FOA+m+3LV155Ni+voKCgcMeOr53OYoYxTpuWdNddz7CsHr8EaQqOg+Tk0Xff/fCRI+sAYPz4X6Snjya2U1bGN9TV1Zw9pnfWf+2smn/tfXfc8eTRoxv7+qgpUxbl5EzPyBjf2XmWojSpqbluNyOjNAB/+PDWffs2ThgxgnMH223XcNx9HMeeOHNd9ZkzY7OyhKPCEaQWfGPExnkeiFWpYnJzXy0rm+D3f6/TTSwo0LLsBSUQq8ASeF7YmJUANO3v7S09cODOvr65PH/W7X7h2LFBs2b99t571x87Rnk8NxYVTczK6t9tvqhVS4AorToUkFg1pq6TMXsCkH4A70rxHrg8ECq1ZA88VEn8V0ZqMSDuQHCLm3Qg8kCUUhNgIEbhQM4lmZxLwrvi5DORgP+lnEt7q6vbuws5fhrARw5HUnX13gkThkeTc+nEiY29vZN4finP821tO1tbT44Zk4lCmky5BQWxra2LWXZEQkLJggV/NpkoqzVm8OBsijo7dGj6okVZRmP9rl1Onr8dACg4PoY/7vVRe/hsgDsBDABUX9+ZI0c2Llv2iNFInTx5JDFx+tVXL42LS/L5qNA8QBoNfe21NyxYMAcA1OoYi4VGE3C5wGbz1FUdG1l3eim/t2Xb3oPx1tvueWrhwhm9vcHkZKvbzQAYsrLGyuQBIjqwbLCm5qjDYfvr029t27KLonoxc61K7dDExgo0SQQUKb1VuJxLOoXiZ3ffvT4z8+S5c/NGjpwza5aSjG0vMecSHQhQFouTonie91KUX69Xx8QsX7z4ysWL0W+KcToHci4N5Fz6r3pmDORcks25JE0+8y/OuZQXH6/V7Ha6cwGAYarj43KizLmUljZGrX7P42kG8Ov1lUZjBh7Zo2lQq7U/+9mrkyZt6u2tHzny3rS0ITYbd+jQ6U2bjni9qRUVG7RaxciRI1Sq57zeOgCGh4PbYDTLD+NhP8BZgBSAUqWyJStrjN+vHzduyRVXLOnrA6US7HaZPEC0ShUH56NQo04HD4LD4WP6etJ539Vw4FjAf7yqvLeXjYsTDiQ6HMDzvNvtdzg8NK20WnXoaxuqtNsdPHp02yefvJ6dkjYsLi52SuGmva9VNZ/UKE8vmjwlLzYW+vr6EwGFk1om5xKlUAximDuKi2HpUujtFUbQPyrnktLtvmrSpGdKSzd0dFSazXcXFSUoFJTDEWs0CuPfQxofBQAAIABJREFUgZxLAzmX/sueGQM//0k/U/Pzf3r92e/3f3CmnvYHXSatMsoPTpx41YIFu/buvUel8i5desvgwSPF7zKMYvLkhUaj0IN7ve6TJ8u83ikAuV5v+pYtDzKMW6dT+nzX8rwHgA/CcQAVwG9iY1cyzFC9vnXMmJuKiq4i904EdwquqalapWJjY7MYRrrs29sLTU2gUmk566C2nm0nWPcGrc40bALDXPAd7fbuHTs+KS2tS0jQLFhwXWrqKIqiQv/WgQPfPf/cytQY63N3323Uak3JSV/+9qGSpqYE9fTCESOEec1/wA9FUTPHjk3/wx9KKyqyU1JG5ObS/wGLGwM//9U/A3vgA3vg/RuzjFL5+0d+evvVFf9Yt+6vn3yya/cn44umRt4D71daoQDabxvOnnKwGipoNxh4gyGMkLgXqNNRHKfEiB0AXHt78P333+L5F3jeQNNvAhznOBqAYhjVsmU3FhUVm0x6szmrqupgTU3ryJGTkpNTOY6SNAXPs2/+7cna/bu0ENQPn/zgoy/pdAqx0qWloFSCwaAeN2mKYmL9e+18amHRnCuWG02MWMgtW9a9+26Lx3MDTdfZ7a8+/PD/xMYmSpRmGP7rr18MBDy/vu+X82bMoE0mYNlkozG5oECYiVy4MRvU6fbs3+8IBqeNGhVjMFx0D1xuY/YS98CB42iA7MTE7MxMYWyLCybijdnorXpgD3xgD/w/Lt4UBtghvpM4R/N6+8PISIBI8abkgf+T8aYwThQJJ0VCFckDRKjzgFKhyLFap+fkvMowDocLY/OI3g+v9I4d3wY2f/alzxsAmPXlP4YOnzt2bKFESBJ3x+/XJiaOUKt3+3zVANsABnFcNsACAOD5VrP5pMtVxHHZiYkNs2evi4tLUCrZv/511dat3/r9BcnJrzz33Ftmcw4K6XYH9uz5wuvt0ekStn322iGPiwG4obZix9h5M2cuJEp3dEB9Pfj94PdTGRkx48ffo1TeodMpGYZxuSixkMePV3i9swHGc9yI2trdjY0tGk3ihUrzx49vaWqqVikUV4wYocLjx2Glpijgebav7+Ynnqg5enQQz7+akbFx9WqlRiMApI1Q05C2AEm8KQIQq5AH/pXxptoaG786eNCq0SyfPl2JAS3+LfGmRFLLAaFSi/NnhJUaARmpxcBAvKn/n5Nn4TAEPpNxaEpe5OhyJABfKCj5Lx7klgHE1+XLlwC4TSdTAQKELRB9ruWBsBUmWCQg0iuSYjIvhgGaphmGNE6kNhFXp76+bGTAbwHgAUa4nTZbM00XRhKSoqikpLwZM+jduzf5fHMAlBS1CuAYz1vU6sMPPPCQ0Zja09M0dOg4pVJBUXxTU+XRo6fs9qMAqtraP2/btnbevLtoOsAw9C9/uaKiQsWyfQpF7aiAvwsgFmBk0N/YeIZhFpI/arMJHRFNQ3o6ZTYreV6JS8eSb5STk7FnzxG/fyhNNyUnO2JjB0mAioqSv/3t8aDPseq229KSk3mn0+50ent6THq9lqYp8XemKKDpA+XlNSUle5xOBcCdlZUfb99++8KFURnnRZtSciXS7UOuk+b80VZ9/tXZ03P9Qw+NaGvroKj31q37avVqI048ozR7STXEv8gDke5T8tWi7yhwa0FGajEQVmoxEKXUocDFpJYC4VZKL7NnBnooKZXC5g/+QkKG4C8cFxFQqS64jmepeP4iAF7HuSpeJOXLAxhGDe8BBCTlE0BcIL5wTC4P8DyoVMJYg1SYYDIAbuXh2VEEJOVHAohQBMDrCgUAUHTE9yVKz5ix+KP1r3/Q3W6nqPq0IcuHjZURUqkEiqIyM3NcLq/LtUmjacjIuKq9/XWXS5OXlzh37pJg0LBmzcvvvvuOTheYPXt+Wlo6yxowTgnPG0tKvq+urna7lVarr7qaCwZ/ArAmELjvKNTOhhdGAHVW4fvd5KuI0hQFnZ1C+AajEdLSBPciSVPga9asJb29b5SXvxgbG7z22juTkpLRV4oAH374dGdr3TN33PnT66/jlcq95eWfbt2qaGmx5ubes3JlCs4hUCmKApXKzbKxHCeEWAGw45BWLGWoVYdqzbLCfyNZdVhAbAMsi/X5p6z6PPDJhg3j2tqeY1kOYGFt7YGqqjnjx1+C2UusmuMuYvYEiGTV+NVkgFCpcaVIRmoEZKQWA1FKHQpcTGopoFBc9s8MjNjFMII/gFodZpaNebvCAuSDCNA0eDyCkckA+BzC6wgolcJ/5QFcKsWZIwL4whYVA6RABDCGGs5nZQBcORUXqFAI/5UHxO4fCKBQeFfIAEQoAqBQfj8AcEHhO4W+L1E6NTV/yW/e2bF9vUJn+tnC602mVPxaYiGxIlhrnw8Yhho8eGRBQcrQoR61Ot7l6lOpPAwTp9HoNm/e8MEHlW73zyiqr7Hxmccf/0t2tqm19WaWHWYwbK+o6HA4HuF5k1L5PMs2ARwGmA1wPQDXDCeb4Qol/2F3tw3/qN8PbjfU1AjWZLFgQKowTYHVMxqTV658rKurW6XSJyXFod8UAZqb248c2T515Ohrp06lvN7Wnp53P/vsuh9+SOO4NadOfZeUdO/cuRc481DUhKysYFbWXeXlcQAnBg16bMoUweAxApXYOEPbAgHUGs8oEEB8O0QCJFaNhxhCGyN6qz4PGBimD4AH4ADsABr8VPRmL7Fq7PRlzJ4ApB/Au/JCqeWAUKklflOhShIgktRiIEqpQ4GLSS0FcG/jsn5m6HQQEwMGgzAps1iEbVOJr63ZHB4wGISHMAJ4VlYcozAsgCXgbhICJpPwAJcHJJ5wGk1/mEkJQApEQKeTOh2GBXCLG/fBEDAahaGHPCB+JCCAQuHWmQwQGmwVhTIaAUCpgZiY8O+HKE3PnT9vyrR5qLTdHkZIrIjJJCzSKpWgUFBZWXHDhuHCrwYdq0wmqKzc6/FMAxjN89Ddne12N//pT38/dOir8vJqpXLxRx+d4/npABAMXhkTc6C39x2WvQuAA/ACdALMDAbbq6p2z5s3E5UuLxeCTGq1kJ8PgwaFb4rzSlM6nTEhwYjbrlhzBILBrkcemRoM+q4YPzo+Ix1Uqpb6ekNb2wyO0wG0+Xybz56FG2+8oCPT6Sxq9cavv/74449tHs8vZs9Ojo3tB0gboaahbYGAXi8NW0usQh4QWzXx75Q0xiVZ9Xng1ltvffvTTxfU1bXQdEZ+/pRp03CfKlqzl1g1ai1j9gQg/QDelRdKLQeESi15ZoQqiYCM1GIgSqlDgYtJfQGgVIJef9k/M9xusNnA7xciGHNc+FjoLBse8PuFwxMI+HzSWOhhAfHxCwQwFBF6LMgAod7TAGCzCY7kYoAUiIDXK715wgL4SMAtLwQCAcG5Wx6QPBLQnR9DKMsDof0UCuVwAEDACzZb+PdDlSY1jaQ0AsEgdHaCxyN8xOkEm00KjBhRrNN94nbnAPQkJNTGxQ3r61MUFV0/bBi0tJzbtu0Bm209gFWn2/nww6+wrP/779fU19/Z2bnT6y0CaDYa9w4b9ntslu5uOHBAGKiZzRAXBzZb+KaQKM1x/UHlg0GoqWl5/vnbmxrP3bN48X1XX61yOICiUlQqT0rK+pqaTJbdptHkDR8ONtsFHZnXCy6XkuNunzZNUEoMkDZCyULbAgGfT/pIIHWVB8RWLTk0IAait+rzgBJg/V/+svfsWaNSOT0/X4H3ZnRmz9vtJ0tLv9mwwdPdPXLSpEWTJ5swBZ6M2ZPGIP0A3pUhUkcEQqWWPDNClSSBESNJLQailDosICv1BYDDAVYrxMVd3s8MlQp0OtDphNVMvR78fmluV4aJCOh0wqoiAui/Ifa1DQuQ3CZ4HUcxuPgoD2CLop0hoNMJp/klgLhAr1c4pEpunkgAPhKIlyHWH6er8oAkqjMe1MZprDwg8e8kUqvVAMAoQK8P/35YpUlNIymN53nJrgYOB0kWGZ0OAgGutbWS41yLFsW3t3+u18Ps2Q/n5GR5PIJOQ4Zk/fznD69fv8HlokaPHj958oza2rJFi65VqYwez4xdu44BrBs79sbCwok4yPvhB2E5naJg5kxhbSpsU0iUxjYnSjc1naiuPjFyWP7TD9wfExuLvjqDYmPvWrHis8TE/Y2NicOHL5g3T5jSoVI4+JWRWtxGgUBEAL1Ixa60pK7ygNjGcPUmtDEuyapFQExi4jWDB1/wSIjO7Dva2//4+uvFhw4l8/yaI0f0Gs2SWbMu0FqmMUg/gHdlqNSRgFCpxX5TYaVGQEZqMRCl1KFAFFL3A0TJy/qZgec8VSrBh8zn6z/ViXusOM/A1CuhgFIpXEdAoRAG4/IAzlLxOgKk/IsCxHuaVEZcPgEkFSZDdHmAfF9SIFFGHsAlY6w5AqRi8gARigBYbCAA54P9hH0/VGlS00hKI4AbDLhRhbuJoppyGzd+9vXXb3d1DUlIqLnuuvvGjLnCYrH6/ZToC9GFhXMSEyfQdECvN7z00hMlJWdY1pqdrVy9+v28vIUaDadWWwMBhqahuxtqaoQaJiZCUhLY7RGbQqI0hrvGK93dPTt3ft3XZ5u/9Lp4jYZIRzHMhCFDcnNzvR0dJr1eq9eDw9GvFMYulZFaYjyRAJQS1/QlWssDEqtGlxtJY1ySVUuAKK36QqC2sdFQX38nx9EANofjyNGjS3BpS8bsSWOQ8vGuDJU6EhAqNZ6ukJEaARmpxUD0UkuAKKUmAD54LutnBvoC4UvyX9xgRc/rSID89eg/iA7goZgEiFQU9q9iIFKB0QCSAiNVTAxc6heP5oPwIz93UaVJ2gJ8AhLAZuvYvn1LZeULPD/KZltTUnJw8uSFAFRIOZTRaFWrobT0h+3b9zmd+wGYzs6fbNr0WVHRLWQJPRiEs2eF3U2GgeHD+/9W2KaIVH+/3/fee09t3vze/GlTf3/DNdKqAFjIebEfJ/4/00bygMTGQn8RGS3PcWdqatYfOKACWLZ0aapaTWG3eEm3WBRmn2A2t1gs51paTABlKtWQjIxLMHuZ2+GSrFDS6jLqyRQoBqKUOvR6pA5Evoe5rJ8ZJE8fyaLl9UrXpjAyV1hAnIYPs2ihrPLAj87Th7NFdKMOm2aLAJESlskD/0yePoVCcPrWaoHjOLW6xmbzBQJZZrMOk8ddCEiVJAAKpVLh2hQWH/p+WKUlCc1ChUQMDyOTPU6y2OZ2+30+Lc/rAYDnrW43a7fX2Wzu5ORUjSZWq6UkSgeDdpZNB1AA0ByXYre3iZXu7YXOTuEPJSRAaiq+5W5trQVQJyQM1mppcVNESg1XUrL1889fmT5q1Mu/+pUSs0yjEOLccLh6IGkLCRBWavJBny8iQHLDhdVaBogyeZxaDQD1HR0P/uY3s9rbnQDXbt/+zUsvpcTHX8Tso7TqC4HMzMwV11//q3XrYp1OXX7+otmzBTLKPH2kHyArrhKpwwKhUpN3I0mNgIzUYuB/K0+ffA8zkKcvzDlwpRLw5LFkD5wc75QAkc6BywP/J8+Bky1ujmMdjj+8/fbxvXsNgUDMqFHP33uvAgfb5wFwuaRKioNCu1x4g7EBcDrDvx+qNKlpJKWdTtv+/Xvj440Gw/RAQIG7g3Y7WK0CoFYnDBuWXFn5lNc70WTa1dfHPf30o05nYkZGYObMRQqFMyFhVFZWPsPQPT2+srIdDkdPcnJ3Xd3DPB+bkHB45sx3iZCBAJSXQ0eHcBsmJmIe6OBzz/2qstKmUDgLC8fcddevKIqRP5tss3m/+vJ1jUp99cTJmWazdN8Vzx6jkuJz4GGBUKnJB1EyGQD3XUO1lgcu5Rz4pp07R7e1PclxPEBpQ8PuAwduuvLKi5h9lFZ9IUB7PDfNnTszJ8fl9SanpRnwIz/6HLhE6khAqNSSPfBQJRGQkVoMDJwDH/j5r/45XlW15ssvt/f2qgDubG7+tqBgaXHxv3vfKvDYY9dXV2sUiva8vDE5OX8HoAEucDdXqdQrVjw6atSWo0ePDBmycPv278rKngNIrK9/69Chh3h+ntn813vuWXXVVQt+9aulVVVuAEhNpe+7L8/ncxYVvZGUlN7T039XVlX1B/jBYEu7d3+7bVuz3/8PAH9ra/HMmVfl5BTK1tn/5Zq/HC3ZNjgpccGE8dR/wBHcf91PcmzsRpoOchwHcIZhEiyWf93foikqNT6+35V24Oe/6mcgf8b/wfwZzW73SJ8vDoACGBkIlLW2LkW39Ivlz+iXWqcDAIUKzGaIJn+GJKdDqNLr139cXp4aDP4DIFhePj8xsTE1NQNP+hPPdZOJoijdkiVLiouX1NScWL/+EEAigIHnh3q9ywBe6Ozcd/ToGp3Ofvq0PRDYAQA1NVcMGZI2e/Yit1uoqk4HbjccONDvDzl+PAwaBADQ2FgWDBYAmAF4n2+U291sNhdGyukQDPL793/91Td/TYuP+/jFF4dlZEillqTHCG2LH5s/Qy6pwyXmz+i3apmkDmo1AFw9Z84XO3cur6z0UNT0wsKZ06cLNYeB/BkD+TP+o54ZA/kz/gX5M8ampDyXlPRqXZ2Z5/fHxPylsLDfYUg2f0a/1G43AAT9EGX+DHFOh7BKd3baed4KQAEwHGf1+724gtTVRf4a8DxfW9va21ulVCYkJKQNGaKqrHyZZXMAvuT5eTjEcDqpzk47x8XiNIXj4rq7HVgCChkIQGkplJcLXVBiIqSmCkpPmrTw73+/l+PSAHo1mqNJSX/ADBxhlfb5/Dt3bnM5+7Y++3RhRkYYqSXpMQAuAkSdP0MuqcMl5s+IKqmDSgUACr//jccfP93crAgERhUWMnjKAQbyZwzkz/gPnGcYjf2Bgk0mIVKxZJ5hMoUHMOsyXsdRAB5ikAewJyPnRSkKTCZheCIPSCIV43lpXIKUAKRABPBUgjgodFgAt7xwYoSAydTv5S0DXDjPSB08+JXVq9evXdvhcj0yd27+iBFCjCMyz6BpqZKkBBTq/DwDqdD3Q5UmNQ2r9IIFyzdsWNHc/DhFdaWneyiqt6WlIilpCM8rjUZB6a6us6tX/7apyaDXN9188y333PNQaupXzc1Hg0Htzp2fut0/6HRNkyYtXbhwwTfffF5XdxMApKd3zJw5B0tAIV0uqKkRhmhaLcycCbGxwjGvxsZuAACoBFCyLE9RfSZTf1NIlD5xYseePd/mZKSPKCgILzWObYmS+M1lgLBSkw+GnYgggFM2yTSCaC0DiK0ad3qJVYsBtZpl2UMVFVXNzRPHjHH19Ly9aVNhevro3Fxa3uyjtOpQQKI12puM2ROA9AN4V4aVOiwQKrVknhGqJJlGRJJaDEQpdSgQqQMJ28Nghzkwz8DsaMKjmGHA4RBmo+J5Bk2HB3i+P1muwwEcJ4x+5QGaFo4J4CgA8w+T054yAHGUxkgJbjcolf2jazFACkQAfcDxXxkA95TJJh4C5HS1DCAeLgWDlMs1JiVlzIoVwt0bAgibcmIlxYDDQeYZOLQKfT9UaVLTsEqr1cl///vH3377WVxc3ueff75161aeT7ZaDyYn3+JwMKj0unVfHzlSzHF3AnSsX//TnJyipUsfoyhu+/b3tm9/BiCNpusUCjPDxCuVCopqBAClUglgwfoqlXDuXOtnn5V0dSVnZY1SKpm8PGF0iBXbs2d7MLgM4DEAcDrrvvrirXvuWx0M0gB8WVnF4cNfx8VlT59+LcsqjhzZ/cgjC61G09O33q4PBPqLOK9kwOX6YvfuZrt9ycSJQ0aMoPBdSVtQlJB6PZLUeJ1IFgnAuEPkPIFYa3lAbNU4tiVWLQI4j+cvH3/87scfj/N6VymVNM/PDQb/ajQ+df/9yxcvpmTMPkqrDguIrRrDZMmYPQFIP4B3ZajUkYBQqSXzjFAliVd4JKnFQHRShwEidSCRepiBfODCgjcJ6EgCQJLQj+jnIwOIr+MLg7/KAAzTfxBZEt1THsCZI2beIaVJMAQkBWKtiKtcJADjZUaqmAyAdcawtfjf0C8eFiBCEQCvn49rG+n9iyqtUPBlZfv37Nnk9QYLCyddccWi2Njkm276xaFDX9XV6TnuSQCqp+ejs2crFiwYXnvu+N7tnx/cvZXjfgtAA+jcbmsg4FQq4ejRnS+//JzX+zHAFKfzwKFDn9K0vaZGyXHbAaCmZt6hQ9/OmXOtUgkdHfW/e3ilvX1CHySUnjqw4uYleXlJajVFKjZz5lWffPy0zz+BBmcCv8FeObytrSopKffUqT1PPPGXnp7pNL1t//4tv/zls2+88aiCof/4wH2LZ0yjxKGXlUpQKm0u161PPbf1yGCOT315zbub3/z5iNiYMFKjaheVOtSqQ7XGVVYZqw4LiI0HnanCGU9Va+vpkpKtbnc6wIc+31mAZwEO9vV9cuhQ8bx5cTJmH6VVhwISq8aT+jJmT4BIVi2RGgBUKk6haOzqYgFSLBZ1qNQ4HZGRmoStjSS1GIhO6jBApA4kUg+Dc5fL+pkhjiMPIJcDQwYAUZB60jPKAJHi7OMzTAYIDYgfWrGwv18UJsHxZSomA4hTJkT6W2GBSFLTNGmcsO9fVOn29vrVqx9raLiL500HDryZnp5aWFhI08CyAZ5XE/Pz+7nm5o4v3l215MjWPJb6E7zVB70KxdncXENSUhpNw5EjO1wuA4ASAHieYVk+GPTzvAaAAgCe17BsgKa5lpbqdete6e3IsMN4P+R7nR1VVR/S9B00HUcqNnZs0fhxlu4DtySCIw4cPo7leZamYf/+XT09V3PcvRzHVlffsmHDux0dTUa9ftmcOYpw+QxO1taW1uoC7N8AmFabZu3ufSOWLQ7fItFIfVGzR60Rk7HqUEBi1RGMhwNgOA6z0ZLsiQwAxXE8Hn2IZMlRWrVM/g9SH3mzB7hIUSF/iwN49Ztvjh85wrBs9qhRjz34ICNzn4aVOtI3CgtEJ3UY4JLUI2Ve1s+MYFDI/YaTMgxJhnNSfJ7j2hS5LgFIaBC8jim3cN1QBsBbSxxjgBQrD2DJ6AqCADnZLwFIgZIgCvIAxuIQF0gweYBl+1eOEJAoJgOgUATA6xgLnQWvN/z7oUpL/mBp6cn29iyOuw2A6u09vXv3xvz8Qp8Pxo+fm5r6t8bGJ3l+ksnks1qzjx8/GVt/9i6W9QC4YMuX6Z1XzL917tylKpXZ5wO12kRRfp7/FcA0pXLbiBE3FRcvW7Pm84aGOwAgPd0+evScPXu2vfbaC42NVwZ4YCEDIAcgpanps8bGpszMOFKxQIC5ZvE9fz/zwxk7FYR5qvaGqY0tcXHD1GotQC8ADxC02yu/+vKgzdbxl7vvNqtUwvLChVLrKUrJdAMEASiKslm16vBSY297UalDrTqs1jiqDat1JEBi1XiIIcR4suLi0vPz76qoGOP3b2MYluc1LLtPr79h9GgrHkqIZPZRWnUoILFqcptHMvvQfoCEBokg9Ylz5157++0vnE4FwEOlpYWjRs3Kzb1AalxZkpGa4yAQ6Gxr27xjh1mnmz9vniIccElShwEidSBhexivV1gNu6yfGVotWCz9Wbstlgv2VckeOPEWlwBk/xQBg0GYzMoDZLUBl/vRRQ+3yuUBiSecUik4eBJPOLFPIXHRQ0/BUKfDUAC3uNFFDwGTSRhZyANkK49hBACFwq0zGSB03xWF0usBQKEGiyX8+6FKk5oiMHRohl5f5vHUAahUqpOjRt2OwaTNZuv7729Yu3ZHWVlMUtI8rVaj0SQ0xsSdaz3XC9QhSpWZm7Fo0ZLU1CQAyueDa65ZduLEztragFL5fnHxoltvvSsmRvHBB1t37/4KAGbMeD0Y9OzZs7G6+nc8XwRQB3AcIJWiWpOSetLSYs3mC5QuGJU/aPiVBw48AjCa7lxz6NCWadOmL1t27b59DzQ2nlapyj2eepvN9acHH3zk1lsFt8gQqcdNmLBw+t4vtk/yBzLzMmwrrn8VgoEwUlOUsOEpIzW2EUoWCTAYhIC1YbWWAcRWrVZfsKglAjRq9VOPPLJz0qTT9fXvTJzo6On54ezZ3+XmTi4ooK1WUCgimn2UVh0KSKya7C1HMnsCkH4A78qwUqOfw7Fj493uEQAUQKHXe+TcuVkTJlwgtWQPPFRJjuu12Zbec8/gurp2mv77+vVfvfiizmIRA8IeeNRShwEidSBhexia7o/oefk+Mzwe6O2FYFBwbaEosNv7B7dkDxwgPMCywhY3AnhykucvAohdaRHgecGhTR4I9YRjGKFiEoAUiEAgIHU6DAvgyIKcgO3rA44TdsDkAfEONQIoFI6GZAAiFAFQKJcLAII+6O0N/36o0qSmCCQljVyy5LbDh38dCGiHDcvNz7+qt5e4OzBer7u52dvQ4M3Kyk1Kypw8574b3O6ztT4Xv5LZ0XeudsULL3xutQ7y+8FiGfzMM++cOFGSkZGQlFTodDI0DT6fdvr0m/Hm6u11dHUl8nwSAACojcb2mJg34uPPzJ17s0aTYrdfoLTNFnC5DAAGAOB5a3c319PDxcUNXrXqnaamEqeTffbZG+ZPmXzbzJlCo4STmmGY51euuG5KYU8gMDYtrbepsba5OTU+PjY1lZLsgWMJkaQmbQTA9/bag8H6lhaTSpWRmkqTSHaoNe67hmotD4itWuIAKgZUKgZgVl7erBEjMLHK1HHjwGYTdm5lzD5Kqw4FJFaNA3YZsxcDqBjelaFSnwfGpqf/0Wr9xmZTAxwymf44ahSRWmgLyR54qJIc9+nXX4+sq3uJZTmWnXvmzMGDB4unThUDEAhcmtShQKQOJGwPc9455fJ+ZqjVYDCA0Sg8SzHcGwmbg/MMpTIiQCYoCGBSYnEUpLAAPhJwIIMAcfaVBySecDQNBoPgdS4BSIEI6HSgVF7gdBgWwGkEjkcQIKcd5QEMm4OPWARI4Dx5QBLjiEit1QIAoxSo0PfDKk3cLFkW9Hr6jjseuuaaJpr2GwypKpUCAaMRtm3b+uGH37tcjwEwvb17hw5igf/NAAAgAElEQVSdv3DhLa2dZSfqlMD/kmX55ubrS0rWm0wxWm3suHFFcXHJCQnJMTFCHgGJ0n6/xWqdqlSWBALdKlXNjTcOLi6eYTSak5KSKIry+cBg4Ftbm06dOjh4cFJy8phx45Krq5/yeCaazbunTl1ksaiMRiozM9lq9T3++E9oip8xZYo1KUkY00WQmlEqJ0+cyGm1X3/zzYdr1w6y2QKZmb9+4olsHJijUugAKi81tpHR2Nzc/Mxrr7FVVW063eKFC39y3XU0AdBtWRxOSqy1DCC2alxDF1s1AaK3agkQpVWHAiKrZmn6h2PHur3eSUOHJsbFUWHNHn1tUUnsB/CuDCs1ywLA0EGDXvmf/9m6Zw8XDD40ceK4CROEnhcBMkuQtIVYSY5j9HqWogBXLSmK1uuF7HBiX9tLkjoUiFJqBPB+u9yfGZJ4UyqVkDgFTR+ft7jhERaIFG9KHvg/GW+K7MQggEIBXAQgQhFAFG/K72MxNk/o+6FKh4s3RRsM6ThaEgfmOXz4kNs9BSAPAByOyqqqrvb2mLS0MQrF+kCABQiy7Kl//KPKbs9imNorr5zx6KOrfT4mrNIeD+zZo4yJmVxUdK67u2HYsILly7OVSiXLUgj7/dDSUvXYY3e2tCSrVKVz5iy8555VmZnbSkuPTJ36QEFBkcdDKZXQ1NT+pz/ddeLEriXTZqwsLlaIYxxFkpqiGtvavly//vnjxxMB3m1q+mb9+seWLhUDQgmRpCZtpFCs3bIldseOJ4JBF8BtHDdz1KjshIR+IDThscsFALxSWVtVtf7YsQSDYdm0aQoJcCnxpqK16n863pTYqtlg8OHnn9+9fXsWy76UkvLxM8+koPVEH29KIvV5gKao6UOHTho6FBhGybK0x3OBdWIIdJI/Q9wWRGqWXTF16vtr1lxfX99GUZa8vMmDB4PLJQYG4k39+/ymIvkCEc8BeWchiVtFJNcRGZeVKL2kwnnRXFA+AcIWiKnhwwE8RTk8HpfbbYqL09E0FclRhHy1SN9IxicnyhfDAE2bTSa1SlVycm9t9dGMweNomgrrn/LjlB4xYuSWLbu83hkAOq3WZjBY6+uhuHj5oUPrz5y5SaWyqdUxNTXFLPs0QODo0QUVFSVDhkygKP7UqQP79m1xOhsBVJMmXTlq1OyTJ81tbRTDKNLTcydMyJ08GfCYHstyfX02ANBoYr7/fm1t7TyOe9zj8R89umzZsoYrrlgyffoSMqSjab6sbG9FRUne4Jx3fvmoBYsgNY70lSiqx+222O2JAAaAIRy3p7lZAkQlOAAwTHNzcyrLBgASANIcji6HIzsx8SJNCVDf1nbHo4/md3bupOn1u3a9/tRTBpyah7VqUp8fbdVhX5GtOiJwvvySioozR48edDiUAL+pqfly166f5+SE+coXvU/JVxMBFMOoxUMlSVPiApfMXQOg1+vXvvnm5h07zHr9/LlzFQ6HBOgvIUqpQ4EopRZ7Tg6cz7jAMZk4MqNS+AseSggL4NkOcl2lEvwN5AG8jssC5HQIYvIAbmrhPYCApHwCiAvEF3EzDwF4pfJQefln333HNTQYhw27df78nLQ0ilSYlIPBx1UqYTAiBnBZFt1LEJBUIBJAhCKAUgkqVWF+/s9uuul//vHWxi3v3n9/gUqlvvD9f0rp6dOvbmlpLC9/yeWaGB8/ITY2rqkJPB7ls8++cfx4WVycdtu2refOcRhohGXNLOtRqaC+vvTZZ5/u7r6R5y0Af9u3z1NUpElJuZphKPRRmD+fHHJgN69/o+7wFgDInDDX4/EAxJ4vzQDgw2MMpCl8vp5jx7a43X33X/+oxWoVBno4MsXNNp0O+vpAowGnU/i2LAsMk86yKTExm2k6ieMOajSTRowQ1mFwOQX3OS8mNQCwDNPu9e4DOAGQAuDOyhqSmdlvdVhd5C/U+svvvpvb2fkYx3Ecd31VVUlt7YyCgn5AbAPk3MY/Y9USQNaq5YDz5XtY1sSyDAAFYOZ5t9cLYc0ez0PIWLVE6lAgtAPBlaJQsyZScxwAxBuNt1x9teCtgzkCLgQuTepQIEqpCaBQXPbPjEAAPB5gGCGOilodZhqOTRUWIB9EgKbB4xGMTAbA5xBeR0CpFP4rD+BaKs4cEcAXtqgYIAUigO6tOJ8NAXo7Oz/45JMpO3eODQa/PXXqK55/7OablVhhhULAsARc5BX/RQTEW9wIoFB4V8gARCgCqFTg8WgAHli27Jk337TbHU5nUKFQX/h+GKVJTSMpjYBSCQxjWr78Z4FAZ2encd8+SzBIBQKwZw9ceaWvpaUxEDBNmrRo3boHu7p6abohO1uTlTXa44EtW76z2Sbw/C0APMBxl2teRQUTF8cpFLRWCyNHgskENhtQFJw4cXT9679902EDgLuO/TDrjlUxMd/abJ0MU56dbY6LG4oNhU3h9XKfvvP7ym2f3Z+XdwPrgu++E5JLBwLAMOB2C6vMHo+QcA1HiCwLNG1Vqe5NSTk5dmxPT8+8xMTRdjusXw9qNeh0oFaD0QjJyaBSRZRareZcrvKGhq8PH27Yt+8Fng8AXMcwL1xxRZxW299GKCXHhWqtY5hWiuIBWAAnRalRawJIrBpzKEka45KsWgLIWrUccL7+o7OyNNnZt3d2pnPc0bi45ydOFD4oMXt8KmATiO9K8Q62PEBuBwRQTPEeeKjUBBD3PJGAKKUOBaKUmgDiQNCX6TNj4Aegx+lUNDTMCAbTAHr9/i+qqoIsq/x310rzL8vuQlGUWq2NiUk3GqGhAZqbAQBaW9mVK3/V2dnAMK35+enPP//Kd9+93tzsnj//Lq3W4PNBWlo2RX0JwAIEAXIALBoNQ1GURgPjx0Nycn/5FRWHZjh6JvI8AMx09ABQf/7zS3v3fp2be+3YsddqtQqfDyAY1LZWa1uqD33yXNrJPY/GxS0bOdLS2tR/UhcHxTilw4cEDjDxMchxwHEURcXrdLPGjBEiOuAtjQsIePNjUSkpYDBAejrExQkDSfSVAth08OCTL70E3d1LASYAAMDVPN/n8US5AHHj/PlzP/30eGtrDU1PGTFifG7uf0Iet+h/zAbD+7/73Rfbtzfb7a9PnDhE3IoDP/+pPwN+U/9+v6mYxEQYOnRjTc24QGCrRpNUUKC0WP4/+015Oa7JZlNxXGpyMo1SKxT4D55SuFS/KZ2O7+lp9Xr7Bg1KNBjMAFSo/whNw4QJsHs39PRARcXx9vaFPD+fZYOVlVd+882rO3e22+1Xnjjx6fXXl6xc+ctrrrn27bffqa7+OUABQAJAmcUyLSGBKiqCnBxwu/uVHj9+6nPmuO32TgDYbY5bNXlaenpefs5j8eo+R2OdobWVaqhjWhqVnL+8/HBT6b7U+PirJk82W61CU6JKGDAO48SR1IPoOI9RtFBVr1ewBLICg/aD4qNLT18fdHRAQ4Pw/ZOTITkZdDq/Trfn0KGnbbYkgFUAOwCCFLXfbH5g7FgwGiEKvymL1bru738/WFVlVaunjR7N6PX/dX5TSqXypsWLQacTdnr/l/ympIDIRS16v6l+t6iwLmoDflP/nh+fTzg/gf8qFOB0CuczxeczGCY8QD6IAM8L3jzyAMYDJ57OuEiNmDyAjYczRwRUqv4YiGKAFIgAiVMdDjAD3L548RdqdXlDQ9zw4cumT2cwNhnGRkQMS8DVYeIQRQDx0hMCKBTO7mWAQABYlvX5Xvjoo4ayMp9CMXP27FtnzqRx2R2EeIZ4Z5FgbmGVJjVlGHA4uH37vl+79pPeXn12tnb58p8NGpSOgERpjQays+HgQfD7WQAF7joEg9qysga7/QGen+t2zzl27IXp0ztbWtJyc1fV1BznuCQAO4DZ4agfM2ZsbKzK6exvCo6D5OTRC+5+7tW9X3Z0NAwbfUVGTBZ3qkzdVkv52lxlp3wBl8WSyDPqAB9obmngOG5KQUGy2UxhbhK9Xjg8pTqfPEShALMZXC4wGoU/g+seeIc7naDXQ0+P0KY2GwQC4PcLrvQoED5j8Di0xwNdXVBWBkolHR8/pL4+iecLAWYB/NJiKRw58rdFRQWJiUK4Omwj/BQ5tyzSmlIokrTaJZMnCysYZPEqVGtcDyFWLQait2oJIGvVcoDEqnHeFmrVoQDpB/CuFK9NyQPkdkAAz1WI16ZCpcZ/SU3kgSilDgWilJoAAzEKB3IugclEBYNjJk3Kzs11eTym2Fgdy1LwT+VckksEFC7n0rbdu0u++uqPbrcX4L729nH5+QXZ2fj1SU6kS8q51N7e+t13H/3ww108n3r27CcZGd+uWPFgaO4ZHLJbLNDZCcFg/tmza/r6NgK4rNYrrVayPEO73VmHDxv0ejAaRyYkNLS1AUAeRTUNHVo+ZAhotdI8QBoNfeXcRes2fODqiM/ev6fRdldh3tju5prvS3b39rIAyrg4dXHxopqa0zXNtd06XdbSpVRMDKSnC/eqwSB0u3q90JGZzWC3g8kEfX3S+NsuF1itgAkC9Xro7RXW1t1uwVeyoQFcLmhsFDZ/cHWLpiEYVNjtk+PiSjQap9dLq9UrFyxYfuut8WYzRQLX/3/MuRSVVQ/kXBrIuTSQc+k/JOcSFQyagkGTQiEcWCEF/qicS3KJgMLlXDpw9Og4jycHgAfI7empPnu2ICEBLR4DgTMMHww6aZqnKD1FMRfNudTU1NHcbOD5MQD6QGBcydG1wP7NZasbPvbqSVOmuN0qidLjxoHDob/mmuVnz1bq9ZrExGXt7Q0Wy26n8zuNpiMubp7DYWFZUChMWVnDA4HDPl9VYuLmadN+7XYr/f4L8wAFeL8rsOvr94aX09ncNJXDW+f4yN/cVFtb7Q/wQXjQD+pGz5q2s2c+LPneYzSs/Z9ntGPGONraNu/YceTIkfEFBfOKiw00Xdfc/OW+feDzLSsuzszLo6LMuUT2XXHlKjERjEawWKC7GzweaG6GhgbhnLPfT1FUfmpqbHFxvc223GhMZxh63TpIT4fsbLBaBT/O/185l6Ky6oGcSwM5l/79zwyMZqNWC2LhLxjRBR/FZGU5LKBWC4ZIruMNIw8QPza8jr0OKV8GUKv7qy3xhJMApECx4yAZcEUCsOa470oKxLMC8gAOl9BFDwHxN5IB1Gpg2XlTpz67fv0Wu91BUXXJyQV5ecTtj6ZBqeQPHNi4f/8uluXHjRt/3XXLVSo6rNJYU7UakpNThgzhamvXcNxgtXpjbfmGcQffGcmxmzZ9aPjjB3nD50iUNhhg7lyorjaYzeMw7FtGRmZMjLmzs81imRgbGx8MokMttXDhqLg4XWdn2bBhbyQnD/b7KXFTqCmfvr3JXHVm1JGNDEfxEASg/X51W2dXe2BMO7S0wMx6yOiABl35twq95sUH7s/Py/NT1HubNh1///1pHs+m7dvbvN6rJky49YknrmprA56/adu2z996K12vlyqJt72M1GJAqwWrFQYNgoICCASgpweamsDvp5qbk9Xq5PR04bSkxwPl5VBTA+npkJgIGg0olUKKWtwVCNUaGzEsIK4YcUglVk2A6K1aAkRp1aGAxKqx5jJmTwDxNyKzhEhtIQZCOxASQV0MiJVEQEZqMRCl1KFAlFKTcgZ8bYUzB/iS/Df0FQkg1/G8aPRAaAXkgUh1EF+M9Hs0AK5dhK2YPBBaQqQKSACeB56fmJd358MP7zp8WKFS/XHhwiGJif0fBzh3rvTFFx/v6XkRQHnw4B9GjMhKTZ0gr7TZHL9y5UOxsWva28stFsa7i3ueDTAAGnvniX0bcofNCVVaoYCxY8Figa4uqKoCp5MyGmO02hgcOcTHw/DhoFZDTAwdF5drt+fizdVfAscpG2rijhzT2xp4h3NIava5M1s9Hj9Qfb4kXY05fWPPsi74mx/WUpRGr9trt3cWjR41JT+fBuh1OqtPnfq52z0KYKzb/c6xY1+63Vltbb9iWQCoaGv7/uDBnxQXh/mq8lKHfkl8abVgMEB8POh00NAAPT3Q2wtVVUIXg1PJmhqorYX6ejCboaAANJqLWHWk9iDVIGHr/3mrvui9edHSQq/Im73kzr2o1BftKCK9Iin5vyV1KPDjOo3L+pmB+2N+f/+hedwzJDvYuJYSCZBcxxeeTpYB8EyN+DrB5AFc2cTtLwTwRTACSArEK1isDIB9Z6SKyQA4gUBlEJB88UgATQPL0sHgounT502bRvt8yrg4ym4HAMw30FRfcXDfut7e8Tw/GwD6+nYdOrRn0KAJF1OaysjIve22JwC47u5zrxzf4etu0QA0UbTGkhRJaY6DmBjIyIDBg4Vlnr4+MJvBagWfD+LioLc3jNIcB4zfbdq3Xdd8rLz0BAWB1NRhRmP8lbNnl/R2to9YPOPaWzdu2eise9HfN1KlWpOdPaShoYWmYMWsWenx8RAIqGia1+vtFAU830tRvNGYHhv7JU0H8ZlB0yssljBSEwOIJLUEIEqJAbMZTCbIz4ecHGhrgzNnoLtbWEJhWWhthbo6OHsWEhJg7FiIi5OzauyJxIDExnCj5Z+xagkQpVWHAhKrxkUeGbMnQJRShwKhHQhZWRIDYiURkJFaDEQpdSgQpdQEQK+wgT3wy3wPvB+ItMX9L94Dh0CAVio14j1uAIPVunLBgg82bkwelKLXlzscpQAKne5gYeGvTKaL7IHzPOj1lEKhYhhISho2bvZ10zZ4h/rdnRnDfrPkOoMxVGne6ewNBn1arcVqVdM0pVbzXq+7p6dPr9dbrUa3m7JY+ncxidJ+l1/b1WQ9udNXXbVuwyfd3UYeVCpT2fxbHzBcd9Ok1CG+oMJshiXX3pg7LPvcuUPB4PhvvnkTWP9vf/KTO2+8kaYo8PksJtPVV131TGNjdnt7dXz8owsWFI8e/f3hw9eePg0cN6qgYM6cOeBySZUU77uGlVoChIY6Jx+0WICm+cxM5/DhjqoqY0ODoa+PcjiEU9A0DW1tsG0bjBkD2dlgMFwQcnxgD3xgD3xgD/wy3AO/yBb3v3gPXBqg+7zUv1y6dHdJicflufPOXx458hrLUiNHLsjNnXrRPfALlaYXXfvkqMJrWNYWFzfMYIzr6vLW1JTqdJCSMkqlUqlU3I4dm7dvX+tyqXNyEm+77W6Kimtvrfx+/RvBiuP+tKFXXn374KFTFArqQqV5VU+H+tQRTUMZy3rramu6uxVu/sazkHvWsaaT0y6x5MJ530Wnk05Pn5ifP+7222fYOup/v/KOhxYvpLE4v58CmJ2fP/TZZ2uqqwcnJWUOHky73a8/+ujJ5mZwu0dlZytcLohyD1wGCJVatDHL2+1lZWXvr1sXqKlRZmbeNn16fmoq1dcHdXXCDrDXC/v3Q2kpJCfD8OGg0Qj+VwN74AN74JfdPMNo7D/wYjJdkDqGzDNMpvCAwSCMAhDA8zLi0W9YAB8JOK5BwGQShifygOTEDcOA0SjMHCUAKRABnU6IMyMP4GI3TowQMJkEoeQByTSCpgWhEJMBQge/Iqm1sbEWs5lR0tdff/v8+VdRFKfVxlssDNFJMs8gQ8wQpemRI/PRVVWvDz711C9On26jacjPT1m1anVfX8tXX71x8uTDPB9bVvb68OEbr7jipv27Phm67vUlPu+R0/u/DXrufXSY0RgjUprXd9QZS3bQLU00xTMq0GgUvbRvKzu/BoYE6S+Xx5uxPmKlnc6G8vIDK5ctW7l8KY3hPc4TNM8PTk0dnJIiSO3zqThufEoK63D8cOJEbUnJpOzsnORkSqwkjm1lpJYAYaU+/0Gn07nm++9zN26cHgjsrqj43GjMvPNOo8UCVVXC3gaeFPF6oboa7HZISYGCAqEEnLJJ5hnEQsicDvsptGoxEL1VS4AorToUkFg1HtmTMXsCEOPEuzKs1GEBcRuJZwkSQKwkmUYQs5YBopQ6FIhSalLOwJk+8HpJIh5yHkyYjYrnGTQdHuD5/gMvDgdwnDD6lQfwjBUZBeAZIixfHkAPChwFIKBU9o+uxQApEAGWFQZc8gDP9w+4CID/ygPi4RICKBQZnkQCiFBigEjtdALLskHe6aSVyiQ8ytbXF15pUtNISiNw4MD2bdtKA4HvAaCpacK0adstFn1rawrPzwQAr3f64cNHR48O9pYevcnnHQagZwPv7V5bNvee2NhpRGl/dWPcnjW8z+NngaJ4p6vroI/9Jtnc1HoHx+njYmyFhe+en0UIOjkctocfnk/TdEFGhgnT4IS2hVhqjuMCgb+8+ebbn38+3u9fHRv71vPPF6akXDC2xdORkaSWAKFSkw/StKOjw1FRMT0QyAWAQODvFRWOzk6jyQSxsZCWBikpcOBAf4Svjg5oaoIzZ2DhQmGpBAe/ksYQWzWObSWNcalWLQK4vr5jpaUb9+3LT09fVFyswJaO3uwvlLr/pKo8QIwT78pQqSMBIqmFtpDMMxAQK4kAqYk8EKXUoUAUUl8ADJzpG/i5HH54njtxYu+RI9tcLpaiulh2GBoex+V3dzfn5c1NSmrr6PiO5+O12h1jx84AgAaO/Q5AA3AUoMPrOr5/3YyZ04Dnaa/LcO64Zd/2+tqT9rZaXqntsyb9o9R22HkVzxhN3BeLuD5Vl+J3j8z8/QsbTaY4AOB5vrmp+qWX7m2oP3vHVfNvmTWLwb3ii/1UNTefLik56PXGAHzc3b3h++8Lb7sN3+I4buexY9sPHwa//8p5867IyaFxmPxjf0w6nTUnZ3NZmdvv36NSWXJyTCSLJ0VBaiosXAhNTVBdDe3t/T3R2rWQng6jRv2Lhp8czzd3dnp5Pik2Vo8h+s//bDl48M0XXijq6/uOYQ5VVPzmjjsMOKwe+Pm//vPvfmaoVKDTgU4nPLH1evD7++Pq4MyRYSICOp0wFUUAbzNxFKSwAK6YkMkvznxxdCYP4Gojjk0Q0OmEJ78EEBfo9QobdGRhNxKAS08k0g7WH3s3eYAE98ClJ9ztx+VjeUCSPE4itVYLNE0zlE4nfT+s0qSmEqXr6qqee+7nXV2/4HmV0fiq2eyy218CgEGDzk2e/ExaWvIdd/x027av+/qY/Py82bPn+f10TFz8uwC9ABaA+UD10AGdDvw9bmP57pjGE/Vdde1HtozyeRxAPakdVOVdxfH3QZC1wrEH4PhoLriwsaKu7uikSfMUCnA4mt5979dlZfvuXrHiqRtvjE1MvGCRnbSFRGqO45xOhqLwUaAEYDFzn0IBCkVFff2vXnjh593dwPNPHj783osvDh88WCo1LpjISC1qI31MzA3Ll3+oUr1fWcmnpAzPzDzd0lKYlcXg3UFRoNHAoEEwZAjU1UFDAzQ2CoPfmhpwuyEtDfLygMSbwpqIbQwddcRWTYAIVs1x3GdbtmzeuFHn9SYMH/7wrbdaTSYC/HD8+M12+1Ket3PcLyoq6nt6RqSnR2v2IVILQkUyewIQ48S7MlTqSID4dggE+hfxJAAKJV7lIzWRB6KUOhSI1IGE7WGIkpf1MwP3uDDKNC7kkR0tXFnCtSm/PzygVPbP5tDZABdw5AEcEuJ1BEj5FwXIaiOpjLh8AkgqjPNfMraNBJDvSwokysgDGHUVa44AqZg8QIQigLhifj9wHM/xPh90d3eWlGxWKs1z5sz3+RShSqtU3NmzFaWle4cNy8vKmqpQMETIU6cOdnUN47ibAcDpPLFggdNg8KhUUFT0D6s1y++nRoyYmZExWqXyUZRFrVZ7vfzownlHD2zc29czFeCUOfa68Qt9Xl57dI+m8jinCLY0Vg/2efIAeOBVXjsPPZh/k4FONUAQoI1mFAqD3w99fZ4///nBH37YfPdVV/3hvvtM+O3CtoVEao7Lio1NHz78psrK0cHgEYtl1eTJRMm9x47ld3ffwHEAsL2ra++xY8NTUqRSU5RQVCSpRcZD+f05SUmPr1jRY7M9+MILLQcOfMEwwydPXn3vvQxqTQ6CZWVBRgYcPAjnzgndVns7tLdDaytMmdLf9YRaNW7sia1C1qorGxre/uij56qqjDz/XEXFpszMm+bNI4Bare6jKJ7n/QAepVJ9SWYfInV/rnl5gJSPd2Wo1JEAyX2K/T4u5YkBsdQISLqmSED0UkuASB1IpB4GHzyX9TND/sQNts0/f1QHojsMCHDxw4AAEc/yiAGZk3cXBf6Z82KXqozsBykApUJRVV1ma6166PGftLQMpqj2DRs+WLXqA51OJ/nE8eP7n3jiyZ6eMRrNR4sXz7r//id5XoVvpaQM1WqfdbnqARiVqmTMmHsmT15gtardbgorCEAZDFajUdjbAqBmz7spc0jeunXvOHTa+6+6NTUhT793M336EADwDBjiU48qVSkBvxvAYzXlxG9tayvXaMo5lelJZ3wno0wdc8Xw4ZN5Ht5557e7dn539eRJv7ntVpNeLzzowrZFiGIapfKpu+7aNmZMZVfXX/PyRowcKUSp4/m8tLQ3NJpGtxsAjmm1S2Nj7Q6HXqdT/Ajxz2MUgFGrXXvihOXEibeDQRZgyubNB6dNK5o4UcqbzTB5MqSnw5kzwqmdYBBqa8HphPHjIS4uvFWH/iJr1XWtrZnd3aN5ngIY5/OVVVTA3Lnk3cXFxQ8dP76ztbVcq105c+bglBThVEE0Zv+/fjQP4NLud5nzv1GeIpQAUUodej1SByLfw1zWzwylErRaIco0AGi14PVK16bQKzksoNUKoxgSrRpllQdwxQTVR0CrFaa08gDOFjEFIwJYecTEgLhAfOEaujyABeJiGgJarTCykAdwio3pgBBAoRCTASQLJhdKHZOQMHfSpOc++WTVU0tbWqaz7EsAXGXlgpqag6mpxRKl9+//vqfnPo67we1uPH16VU9PTXx8Hgo5ZszE665beeLEr5ubOziucefOfV1dDYsXLzMa02iaEinNd3d3NzU1AVjT0tJGjy4cNqyQYUALbsWB3eazhzwKAADaqDMtvXe/JWZ3ZUm32nD97OUzZi04fr75kbQAACAASURBVPx4ZmaCyZR97twRhcKQnz9Zp2N6ezuPH9/GKNR2n27zqfJbhg+nZdpCIjXHgVbLcNy8GTPmocuXaOlp6vjxS5cvX3XiBB8MWhSKHUeO7Ny7d8wVV9w4dSqNbvW4/nBRqUkb+XwItDkcyRyHqevSWdaOFcMuQ2zVwSAMHQoFBbB7NzQ2gt0OuLG/fz/k58Po0YJRERsD4CnKHgjUt7aatNqM+Hgay4ls1cOGDm1LSfm8pyeW53cbDDdNmABaLQHyR4x4+/nnT545kxIbO3bUKBonr1GafTip5cyeAOJ+gCwDSqQOC4RKTd4VA2KpERDXRAa4UGph6Yl0IDJApA4kbA9DFq8u62cGhuTDjPD4CHG5hPm72G+K5I6XAOSDBEBvHnkAfYdIpGJJhncZ4KIZ3sUAXkeAHGSQB3A8Ii4QE9ADXAQQez0hgEIBXAQgQomDQp+XWs+yNxYXf7FrV0XVaZouEiaGPOv10i6XVOlgkALgkGFZ3uOhsHbBIHi9zI03Pj5rVunLL/+xpGTZnj2Fhw6tDwY/W7r0FyqVgijd0nLur399tqlJaTC0L1t2y8yZSwMBWgEBXc1xxYkjASUEAhDUGuyFcxzx+bfmFHZ3t1KUZtCgFI2GHjcuNSYGbDYYO3aezwdeL9hsnR988PS5c2UcN23fsV+crnolK3XQ9KysiG0hkRqHdRGkZny+J1asaFy06OzZs79++eXZp07pAf6yf3/aU09NHzu235kHS4gkNWkj1DwYBJa9bsqUn3z99dMdHd0U1ZeZOSEzE1wuwVeHlECqqlRCXh6kpsKhQ9DWJpwb2LcPWlshLw+ysvqt2uNp7uh45t132crKNp1u8dVX/2T2bFrWqjNMpt8/9NC3Gzf6XK5FY8YU5+cLlXS7Qa2m3O7MmJjM8eOFkziXZPZRSh0KEOPEu1LsNyUPhEot8ZsiAJEaAbHUMoC4A0G3KGLW8oBMBxIWIOtXl+8zA2O3kVMUmI059HyGxRIeMBqFw5YIGAxCCDB5AEe/+MRGAFMmoFu3DCA+pYmA+HSyGCAFIoCrIpIDsaEADiswdQ8CJpOwsikPEDdzTBCkVApCoVu3DBB6aEAkNQVgpGm1VgsAGRml9fXX03TbqFEpRUWTrVap0osWzd2y5WddXTu12mOTJl07fPgQTJdwXkhaqTS5XPHB4FUA6T6ft7r6a6MxoNMpiNKbNn1z4MCYYHAlQJvVumrixPFxcRmazra4yh9YRUCjAU6p9k2+QjNuhMVBq9WG5OShoU2BOvl8wc8+e2Xt2jc4zgjwGQ8JPY6TW/8fe+cdHkd19f8zM9uberckq8tykVUsFxl3uYONDaaYGkNCCyXg0AIkhtBCS3gJJQkECNUN3HHvvUsukmXJKlbXquxq+8z8/jijq9HszkgGkje/19pnHz/2+rN37n7vmTu3nHvOiRMTcnJk20IiNe67ykutoumkhITjFy9mt7XN4HkA2G+zbS4pmTB1as9RGCxBTmrSRqi5Tgcsm2AyffDhh6u2bx+q1794001BLAsmk/Bd8fELrCqWkJgI8fGwbx+UlwvJBJubwemExEQIDhasWqf7bu3asO3bn/J6uwDu5PlJ48alJiUpWDUFkDd48IisLE6jUTMMjT2sv9Z9WvWPltofIMaJd6X41JEy4C+15HwGAmKpyfELsdRygLgD0emEaQSatTIg14EE7GHQieBqf2Y4ndDWBl4vdHQIn7S3C+E5xfMMng8M+Hw9mUw6OoQsJSTaqhwgPuaNAMcJhy2VAf9TmjQtREGSAKRABHD/SnwgNiDA8+ByCcMKBFhW8M5WBsTTCAJgxZQBIhQBJFJ3dgLLUhT15pvf4R74jBmz7XYVmdGRAuLjC15++Z8lJXsyM+9IShpvszESIQGCIiI8DHOMZXm1+kh8fLDNpsKInwhcuNDCshMATADRTU0htbVtGk+oads6j83h9QLQVGPyqLaIkZYORqEpcN97w4ZPPv30NQ3rMwLdCXU8tGnUu8cPmYME73K1d3R4GSbIaNRwHBVQahyzK0hNUeB2pwcHv2Q2n3a5dAAHDYZfpaZCW5sYUJKatBFqrtUCy1I+X1pQ0JM33CAYTHs7eL09KZ6wBFJVLAGBrCwwGOD0aSGHeUcHfP015OVBZCQCdeXlGT6fGcAIEN/e3lJbmxoXp2zVFMdp7HZ/gKeoA3v2bDl0SK/TzZ84MS0lhbois++n1P4AMU68K3u3hRLgL7VkniFWEqUmSa78pfYHxB2I5By4MiDXgQTsYWw2CA0d2M/o3s9ATzhcbZQ8M3AZNCAg3q7weHr2M5SBH72fgS2K7r8BlyMJILewqwz8lP0M9KMVb1eQhV0FQNKR+Uvt8QBN8zwfFRUyf/7tbjeYTIIeEqUNBnrIkKwhQ7IwQZG/kGZzyM033x0e/nVl5c60NNOCBXeaTCoiJMuyCQlBGs1XHk8Xw1zIytKkxIRHH1prtDcyKuB5gGHD3cOu0WsY5aagadeqVW9+8smLo4YNDdVqK4+esPuK2rQRd88fVTR5MnR0cFrtmh07NmzerHY6E4YNe3jxYv0VLbIToSgK9PqhQ4Y8/vjjf928WeVyTSwsLLrmGiGRXzfQh9SkjTDefkCArKGLrZpUlQCYhyQqCo4cAasVOA5cLti3D3JyICcH9PpxhYVf7N2ra2+vpmlnampKcvIVW3U3UFxVteyll26xWjsp6hc7d371P/8THxV1BWb/U/YziHHidoK/1AEBf6nFnrgBpUYgoNT+wM+1n6HcFgP7GcJD2OsFn08QFP+CPt0Y5RHjI8kBJOgjfk6irSoD2HWKw0yS8pUBnF2SwJb+5RNAUiAJ4qoMiMPWIiDBFACSRhQBiWJyABGKAL2/aFCptCoVz/Nrvv/wunn3u93c3r3b6+utY8ZcYzDE8jxFCpBc0F9In49KTx+dnp5eX99hsYRGRVkcDgqFdLvZD9/9deOJrans5XrTkesW3j1nzqMRddXamnKWB4oCR0SCr2CGx6mFvpqiurp806ZPNQz951//OsRoXLVpU21zc05GxrxJkxiOA6+3vK7ur1988btz5yw8/5eSkm2pqXNnzQogtTjYakCpKQq8Xpplb505c2pq6sW6utLW1l1Hj07My2M0ml7BVvsntSxA6qOsNQIRETBmDJw7B2fPCsPzY8eAoiA1dXJurufxx4/s22eJiHhh7txw9Mq9IqvuBtbu2DG6re12nud5fl9j48nS0viwsCsw+/5LLQEkn/duCyXAX2pyiltOagQUpBYDkuuSjkvuFxGgL6mlwEBcW2E3CTUVWxXZwcZdVDkA3+RzcqpDGUC3BPwcPyHlKwPYoiSctX/5BJAUSBzzlQHcU5b8UjGmAKCSKJe/YnKAOHE6x4HPx3u9F6uqVu/dG5eYeGN+fojR+Oytt1739NPfLn9/2PBp//znn3bvPsCySYMGvfXOOz+YzSGkAMkF/YX0eoFlKYslNDIyVKL0sWO7Dq3/5KzHRQPMc11KTEyP05i1F7bxPo6jwKsxtowsMqqNPlsApcVN4fXyBw7sbG5uyEpMzk9NBYClixcLOVm7L1l28WJKY+MEngeAa5zOPUePzp02LYDUKJeC1N3nLWifr6Oj49FXX01qbDzOMNfOmfPmo48yIkBOalmrlgCkPspaE8BggLFjwW4XdsWdTjh4EBwOY3b2gilTFowZIyz322xXbNXdQGps7CqaZjnOB3BapXoMYyL13+z7L7UEkHzu1xaygL/U+LmC1AG/KAdIrovnRRR+EQH6kloKDDwzQKsFkwnMZkELsxl8vh6fQtwDV6tlAZNJKAcBo1FYwFEGcMWEbEnh/+LUWBmQRBCjaTCZhLmwBCAFIoAbdOJgbQEBnIqSTTyO64kSrwzgLBuX8hBAobB8BUDiAKpWH6uq+t3SpYUtLbto+vsxY95/+eVri4pS33vPx3nPn9959mydx3McQFVbu2z37n/ddNOvxUpjTU0m3m7vamur5zhdZGScTkcTIXk+sNJdXQ0jWJ8GgALIZNl2a2VYQ4ixs57VAKVmnNm56sQYkwlaW627t37ddGYvHTF4zMRZ4RFxwcEJGo2quyn4zZtXfPPNa+EWyyv3/xLM5oBSDxk69H9iY9dZrSEAO4zGxePHB5Ya910DSc0zTJPd3mqzRet0IUYjZTav3rfv5sbG37Csh2VvKi4+29g4PCFBOJwsL3VPG6FxygEY7lHsa0uqKgeYzTB1KpSWwokTwq57SQmYTDByJPg3Rv+tuhtYOG/e/v37l5w7Z1erbykoyCeuYv00+35K7Q+QfgDvSiKUWOqAgL/UuIOtIDUCClKLAbFZ4/EAcQeiAPQldS8Ae7ar/Znhdgt71PinSgV2e894iuyBY7w8f4B8EQGeF3ZmlQGc9JEIYnY70HTPVrkCgI2HO1QIaDQ9MRDFACkQARKnWhng+Z5gbQhQlIApA+ItbgRQKFw5VQCIUN3ADxs3Tm1peZzjWI67tazs1OnTk4cN06vVHSx0dbEsix07AGjsdq+4AFJTh6P9gw/eLitr0ukcU6bMnD37ZpeLJhUJqHRqauG3UYl/aryk4+FoZOx9aYVM8QGPi2NZ8JnD2uOz7U6Vxg47Nq9tee/puU7bcxR9bMO/4gZlxOQWLbz5cb2e6eri9+xZ9c47T1q09B+X3Fc0bFjPJmpvqZNCQh677bb127ZRTueoYcMmZmaCzRZAasyn1ltqtqPjcHl5cWXlkaNHdY2NqrS0e669Nisnh3U4DHgWEUDt87GkQCxBRuqeNkLjlAMw/5R4nkGqqgD4fDB8OLhccOqUkMTi4EFwuyE5Wehkf4RVdwMqjeaPv/xlWXOzjqIy4uIY4mvbT7Pvh9SBAdIP4F0p3gNXBvylluyB+yuJfypILQbEZo1b3KQDUQb6kloKDMQoHMi59F+Sc4kApsjIRoriAHwAVo3GGBaGXoBelzMlJXnoULPVuojj4mNiSubO/cRiCZBzadeujWvWNLhcSynK1t6+dPTonJiYIRAo9wxROj09Ydmf1xzes7yr0/X43HlZFQ1GbwdogWXBk5/fTnfu3PZdWlp8/dkdC522YJ6nefbvjTVnG2ufOHswIjZ84cI7d+5c9frrD2ho7sWnnp83dmxPPB8/qWmDYfq0aQWjRnlpOsho1PB8PxMB+YzG+55/vry4uLO9/RmncxTPryovXxkSkj5+/PTp05/aubOmqekMwyRkZ2cMHy50Fv3MuUQSAQUE5FIqQT9yLuFBvJISoZ8qKwOjEbKyfnrOJZPPl5uUNJBzaSDn0n/8NZBz6b8s59KiCROWrFt3c3V1tVY7efTovNhY6OiYkZv7zqpVa7//7MEH3pk5c+/ly82TJj1uNCaKCyA1PX68xO3OB0jleb61dXBZ2SWjcQgEyj0jUpoKDslauPgFmw1CwKou3uRmAAC6QuP3dFAfL52S21j7d5Wq3hKeTqtY1psHcBaYRyCpyTn39df/tnnzmrKyIz5318v3P7xo1CjK4VCWmnK7Q9DpxensfyKg7fv3H9i+faXX+y5APkACQJ7X+92FC762tlHx8R+99tqm06cnBgdPyc/fvXv3ngMHBsfHL5gxI0SlovqRc0kJ8Eup5GPZrqYmhqaNNE0p51zq6oKEBHC54ORJYdlq+3bgOMjK+jFWPZBzaSDn0kAs9IGX5BUdHv7J888fKysLiY0tiI3FsOHL7rrr0Pnzp07ustvbJk9e0NEBRqPwdPZ/5eWNWb36c5crgabboqPrk5KGXMHled5w/pjwV4ax5k49uuHvixprH+NYr4ed6PWsGzEhqKv1fM3FSqe2GV7nYb7T+e3Bg7dHh5hffeKJJRMmUBT1b1LG2tmZxHGRAGqAlQAFABt0ukGZmWqViqKo1Li4hzIzwWZbs3fvF2+/Pamz87RKdf7SpefvvttCDpT9PF4j3DcbN57Ys4fS64tmzJiWlUX7AeU1NWxHR1JGhg6775EjweOBs2eFLmzvXjCZ4GetVaCW5Fvb22svXw4xGOIHDaL/be0y8BrYAx/YA//f3AOnzOao+PjZ8fEQEgJtbQjodbq8rKwzNVt1OhaF1OvZkpLD9fXVOTl5MTEpPh+F1/F6Pdu3f89xJRT1ZFiY+4knPk1LS8SxkcIeOFGa7uywNFzgNMAw4IkZpEmMVWn4Yp7fBjAOwBIWccN9LyQkhJ8/W/bRR3/hSnmALQDPBpl0r/z613fceivV1tZfqa98Y3bypEnvfPLJsurqBp7fEBRUm5ubXlAwf/x4hqx7mEw+r/ebbdsyOzpuBQCv94nS0iqbbfjPuge+9/Dhb955Z6nN1gXw7KlTiW+9lREdTQDW43n+ww9LT53SeDwxeXmvPfywCgN9FxaC2QynTgm/6NQpGD0a4uJ+3B64WEmeZRs6Og4WF4fodNegQzMAmEwXL1z44wcfqCsrGy2W22+9dUFREa3RDOyBD+yB/+SXJN6URgNdXT1usjhHc7l6wshIALl4U8rA/8l4U5j4k4STQqEA+gCIUASQkdqi0bS1W3dsW52SmmWzcZ9++uevvvrE7R4RFfXnp59+LzU1h6bBZmNff/mObTvLOX4PAN/ZObW11e5wUHJxdxwOoCi+oqJs+/a1MTHJM2Zcx1ys4No6PB5gVGCNzGjvgu3791Tw+Sug0wCXxmeOGzx4TGioenh2xqKbuXfffd5qraBp1x3Trr9l7FjK4bgCqa88CFKk2bzxrbe+2r49wet9pbAwOjxcbbEwLhfV1YWYj+evf+SRy6dP1wMcBPgHQIdOZ8RCAkpN2gg1VwBwPYRlwefbvHdvoc02nucBYHlLS8nZsxmJiQTYd/z4N6tXH3C5GIBba2o2Dht27bhxwiLw4MHQ0QHFxQAAjY1w5AiEhoLbfWVWLQZ4Htzujo6OW5YuDa6trWaY8VOnvv3ggwxNg1a7+ocfcnbvvptlGwB+ZzSOSk5ODAv7+eNNoVAK8abkpBbnzwgoNQKkJsrAQLyp/9wLT2DgUUzUV/wmR5flAHyjoOSfeP5YARB/rly+BMBtOoUKECBggehzrQwErDDB5AC5t5xiCm8ZKW6cOnXlgQMf/v25eQvubGlxHThwpL19G0B4dfWnu3atS0/PoWm4cOFY7dmDFD8LIBQAPJ68+vpymp6qoPSZM0eWLXuquTmXprcf3rd+2egixuemKOBCwtiY+F27V1RURPrgSx/wLiav4Jr5Go2apvlLFSUlp7cDNNGU85Gbbn71wQc15AAhTePB9Q67fcuhQ0cPHUofMWLuqFGRYWGUcltIFBP/hWGApimaDgkOfmDRIuxlfBy36+jR3bt2BcXGXj9mzODY2K2HDlWfPn3Y66UAFgFMDg19avr0wXFxfbfRlTTl+OzsD7//vqyry0VRx4OCHk1IEAOVjY2jPJ4wAAAY6fWeram5lpSg18PIkdDYCM3NQFFQXQ1nz0JKyhVYdaD319u3j7t4cRnL+gDmHDly7MKFgiFDgKZb6usncJwJIBogpL29rasrMSKin1LLAnL3KXYjV9RR4NaCgtRiQFKgPyC5LqmPXM0J0E+pCfBfsMT3v/3MQL8ZtVrY/MG/kJAh+BeOkwU0ml6fazTCBqAygJ/jXBU/JOUrAxhGDbsbBCTlE0BcIL5x9qMM8DzgEWJxhQmmAOBWHp4dRUBSvhxAhCKAjNRZmZlTRo8+U17e2dlIUXqfTwegBgCeN7rdHrwIxzlDgY+BDfXwAQuU2Xw4P/9pZaX379/U3LyA4x7gOF9F8Q32yBO0Wc8w4IuMpqIi3O4Ong8FoAF4ior2+ZwaDdTXX3jlubm1TbVGno/Qau+ZN0+DuysiJTmP58tNm0r+8Y/pXV1Htm9/+7rrfverX5mU20IiNccRqXm1usXhOFddHcowWamptEoFHHe0pOT9ZcvmW61NNP3YgQN/ff55u9cbwfM0AAUQQdN3Llhw90030U7nlUotBTQaIfKgWg00XTR27PklS/5y4IBPp3t82rSh6eliYHxOzp8jI99vatICHA4P/0thYU8JGKNzzBjYuVPo7IqLwWiE9PT+WrUE0GiA5+0ul4XnKQAGIIhlnaibRpOXn796zx5HV1cZw2gyMhLi43uaX17qPgA5q8ZsVAqAv9S4UqQgNQL+HUhAQHxdlFrB7sVAP6UmgEp11T8zMGIXwwj+AFqteBoudN+YtysgQL6IAE2D0ykYmQKAzyH8HAG1WvinMoBLpThzRADf2KJigBSIAMZQw/msAoArp+IC0bcHJ2QKgNj9AwEUCu8KBYAIRQAZqWmViuF5ADh38sCYwjuGDIkpK7vX5xsRHHwwP/8xvEJ8/Eh9So6hdeNg9ukOc8hvnvowIiKVKIQVESttt/vq6ys5rgagFcCk9bZqu5w+vd7L0l3mGAerLSi4Pjr664aG3wA4Bg92ZGVNcjph3boVNY21euCfBDjl9e4/diwrIaGnLSgK3G6v03nx+PEburom8/xwt/vNc+daGxtNoaFKbSGRGnsipxMAalpbn33tNVVVVY1WO2/WrAcXLaI9ns27dk1qa7uV53mWPVlVVXLu3KScnLfi4++vrjYAlEVHvzhjBu12K0lN2gg1lwPQJvGMAssyPt/9ixY1jRmjVqkik5Lojg6h5hwHHJccGvrR73634dAhn93+3LRpWbGxPSXgIYbgYMjPh4MHwecDpxP27YPgYDCb+2XVEoCiwO2eN3bs/atXt7e0XKZpb1zcpaoqe3v7jOnTZ+bnex9++OiJE+HR0Y/NnBmCv7EvqfsAiHHiXSn2m1IG/KWW+E35S00A8e0gB0g6EJRazu7FQD+lJgDubVzVzwyDAUJDwWQSJmXBwcKuqMTXNigoMGAyCQ9hBIxG0Ol6Rc4LCGAJuJuEgMUiPMCVAYknnE7XE2ZSApACETAYpE6HAQHc4sZ9MATMZmHooQyIHwkIoFC4daYA+AdblZNapcrNyQlZu/bdD/+QPSLvD39YNnr0mvLykqlTl6Wn57IsXifoj28v37Pn65qahrlzrw8LS2EYigiJFSG/W6fzPfro/EOHLgLEAOQCsOMychIignU6oNQ0nxrLhFImU/Tnn6/YseMbAP0dd7xvs6mrqso2bvzMB/yvAO4DuEaluiM5GUJDe9rCYAC3m3a5mNjYBooCnm+nKFtYmD4qqo+2kEiN+65aLQCs3Lo16eDBF1jWBXDd9u3TZ87MiI1NSEs7RdMsx3kALhqNEQkJ4cnJu77++rMNG5wez3NTp0aEhQklyElN2gg1lwOMRnA6eZY9X1u7auvW1NjYhfPnx2NM7OBgwaq7g61SLJs/blz+jBlgs/UETUEA9111OggLA4qC/ftBqwW3G6qrYdw4YNm+rVoCGAzgdqdaLB98/PHqHTsyTKa/f/vtJ2+/baOoN1et2vzBB4vvuGPxTTddkdR9AMQ48a4UPzOUAX+pJc8MkdS9wtaSmigD4g5ELLW/3UuAfkqNgFoNRuNV/8xwOMBqBY9HiGDMcYFjobNsYMDjEdzMEXC7pRG6AwLi4xcI+HzC3aUM+HtPA4DVKjiSiwFSIAIul7SfCgjgIwG3vBDwegXnbmVA8kjo6hKEwpmcAuDfT8lJrVLdUlCwdcyY5Xv2HTh0LHrw2JycBSNHLtBqoa1NCKhjswGAeuLE29EZt62tl5AIkN997tze4uI2gJMADA33RsBnk1KGuVw0z4ODVzfR0ZwVlY6YNeshhwNsNjh+/My77z7Y3FQ9Z8yYSqv1lwCzhg+flp4OVmtPW7hc4Harfb5Fkyb9pb5+T2VlS0zMnVOmRPA8WK1KbSGRGuPCdnUBgLWqKpHjaAAtQJzN1nn5Muh0N+TnH5o+/d7z561G482Fhdnh4WC1qm22JZMnC0ritRSkJm2EmssBbjc4nbuPHXv91VcntLVtoekftmx555FHLEajGOgV+FaiNQLiQwODBoHRCDYbuN1QXAx6PcTGglrdh1WLzJ5vbS0vLf1uy5aG8vLUnJzbJkzYcfRo0oULn/h8PMA1xcUbf/jh2qlTr1TqPgBinHhXip8ZyoC/1JJnhr+SJDAi1kQZUJC6T6AvqXsAmw1CQiA8/Op+Zmg0YDCAwSCsZhqN4PFIc7syjCxgMAirigjg4EvsaxsQILlN8HMcxeDiozKALYp2hoDBIJzmlwDiAl0u4ZAquXnkAHwkEC9DrD9OV5UBSVRnPPGO01hlQOLfqSC1SqVSqTKSk7nde3ycM6DSpKZySuN5XvzdarUPQAdAAVA06PQ0ZXa2qy16tRro4HBdiF6idHt7zUcfPnHxwtFH7rrrqQULLlmtADAkJobRanu1hcEADEOxbN6oUa+lpFRWVcUOHpxgMFA4FFVoC4nU2Og8DwCFkyb9fdMmur39Ek1zaWkp6emg1RqNxleefbb8wgVTVFS62Uxj2h+x1HhFBanFbeT1ygIGA1DUzmPH5rS13cdxLMfdUV5e3tqaGxEhBnrFm5JojQA5G4/D8OxsOHlS6PjKy2HQoJ7BvpxVi8ze3tr64bffhqxfP8Pj2Xj06HKvV282a3ket2h1PO9DYa9Q6j4AYpx4V/pLLQf4Sy32m+otda8T9aQmyoCC1MpAP6TuAYiSV/UzA895ajSCD5nb3XOqE3ezcZ6BqVf8AbVa+BwBlUoYjCsDOEvFzxEg5fcJEO9pUhlx+QSQVJgM4ZUB8ntJgUQZZQBX57HmCJCKKQNEKALISc2ywLKxQUEej3vfgc2Tpy0wW1LESpOayimNACk+I2N0UhJ95syNFERSsN44OCs1IsHX5VWpoMsU6fFQYqVra2tefHFBWenph+bPX3rTTRaeHxEf31NJcVt0S00BxJhMMampgAk9+mwLidQY79rtBoCJI0bAE0/sPXEiLCTk5aKiEK0W3G6KooINhvzEROEgi7/UGLtUQWqJ8cgBKhW43Xqdrh2AB/ABdKpUOlzoFwHCZBkXjQAAIABJREFUor+4MSRWjS43pDFiY6GxURjD1tdDWRkMG+Zv1U6bbe3hwwAwKzfXTMI+ut2tLS3OCxce9HgGA2iczjXFxQ/dd9/n8fH31tTYOK4lImLCkCFCOVcidR8A+UV4V/pLLQf4S42nKwJJLSiJgKRrkgOUpVYA5DoQuR4GHzxX9TMDfYHwLfknbmWj57UcoPx5/7+IDuD+mASQKwqnrmJArsD+AJIC5SomBq70h//YL95WVLTy0KENe7YfPbpj4qRkAOpHK200mv/85w3bt3919uzetLQXp0+9zbDqVQ+mMzCHinTi6+urX3rxtjNnjt9aNP2pW26heL7L4TCo1ZTYNhSu2s+2kJdar1bPHDt25vTpwiofMn1abz/F98N4nm/v6Ni4Y8fpysrxw4ZNnjDBALBw6tQHjx07U1NzTqOZN3FiUnR0e2enWqs1cBwlV3L3D+d5vqGp6dtt2+xO55yxY7PT0ig85jluHJSXC4OzEycgObnHPY/nAcBms8154IGIS5cA4N2EhA1//au5GzDpdO6IiFKGMbHsWZXKFBsbHRr62gsv3PPII6k2W0hLy3MffPD2M89or1DqPoB+St2fL/Z5+/RZEzEgsTH/v8gBch2Icg9zVT8zSJ4+kkXL5ZKuTWFkroCAOA0fZtFCWZWBH52nD2eL6EYdMM0WAeQSlikDPyVPn0olOH2ThGU4pVUGJOshClKrVKBSqSjqiXvu2bhnT3Hx7kkTFuiMoWKlJQnN/IWU5CvjefX8+XfcdNMdDgcwnVY1w3O4VBAegqLSNDQ31/zjH0+XlR1dPHv2s7fd9uWOHZfOn9eFhy+aNy87NZXyb4t+Su0P9D9PHwolyg3n6uysbGhg3O5Ui4XGrdfegKzUpI3cbgK4WPbt5csbvvyywOX6atOmRo67o6goOSXl4z/96VhJSaTFMjgz828rVlwqKdElJi6aPDk7O5vCPkXSGN0/vMnhuOeVV7JPnQrh+Sd++OGDd99NjYoCnw8sFigogKNHhbwsFy/CuHFiq964f7++quprlgWAm2tqNp46tWjWLATCoqIWzZ//L59vbV2dLzX1/jlz9EFB29esWWK3P8rzXq/3ltLS0ubmEfHxP15qCJSnjxgnWQaUSB0Q8Jea/K8YIGn4CCCuiQLwc+XpU+5hBvL0BTgHrlZDV5cwPRfvgZPjnRJA7hy4MvB/8hw42eJGAIUSnwMPCBChxEGhA0rdDWTFxFw7duymTStVvP7ue/5kCrLg/5Oayikd8Bw4AXQNVo+Hb2trt9sbS+OrU+IyKYpubW378ztLDx1ae9f0opcff3zNmjWVf/vbPJergqbft1pfvP/+SIzE4Hc4+d9xDlyqZPfZY5am//jee9Vnzvg0mmEjRvz2zjsZXBghh5PlpCZthJJ1A80tLU0nTix1OlMBEmy2H/bvd+TmBhkMsUZjbH4++Hyfbt7co0NV1YtLl0biliy5RG+tj508qa+oWMayNEBrU9PqzZuXJiQIQEwMmEzQ2gosC+fPC3vjxKrFkbcxiHdXF0pNORzT8vOHxsY2trQMiouLCA6mHI5ep5QxCCXuS/84qftzDrx3W8gC/lJL9sAJgFvcBCA1UQYGzoEPvAZecq/woKC37rvvl2+/vWLN3w1605IH3gQAn8+7cePX7e3Oa65ZEBT0Y/w6GLejzVq/b+uqCEfnXw5tzZ13b3LqsH9++mpl1bmbJk166e67QyyWktOnZzmdEwFGseyxioraxsbI5OTA7ngu11ebNwPALRMmGCyWf6sgG/btO/rdd194PCzA2HPnCvPyJuTk/JQCtRqNw2i0URTwfCtFMUFBDK5ud79KTpzo0aGqqra5OXLQIIUCQ8zmGrXaC6ACqKbpEWFhootpIT0dDh8WYktfuAAjRpD/vHbChPeSkuZWVgKAIzFRCEPS/aIpKi48PC4khAx+rysqunfDhlNNTSdVqgnDhg1JTPxvyCs38Pq/9cwYyJ/xX5Y/Q1bqboAKCkrKyHhsyZK9v/nNyTMHdNoup8v78MNzKyoG8bzxu+/+tXz5d3q9kWU7aFptsQRrtZRcHgGx0nozfbn67DC7VcfDyE7nv/71mpcHg047c9y4159+OsxiAYslcejQI7t3p3k8tRRli4+PSkzs8WonbWEwtLW0XPfoo8mXLgHAJ6tWrf3qqxB8bPwsSR38cjacravL9vmCAQBglMdT2dExIShImtThSvJnRISGzpw9e2l9fUp7e2109NPXXmuMihKXkDhixJEtW9I8nlqatsXFRcXHCxHu/PNnAABAwbhxk6ZNm7t7d6jPp05Pv/G664RkDAhkZkJjI1RXA02DzQYMQ6xaHxS06eOP1+7fDwCzCgr0QUESqSVKDhs06Mv3399++PCtaWlThwxR4VHBgfwZA/kzfs7XQP6M/7L8GbJS9wZyExLSBw26UH7m83++bQ6KrajQ+XyfA1A1NQ989dXnLS2u0tJqnc47ZcrsqVOvwzx9ivkzwOdkPC7PRZ6xQup34PDwNXlp6b+aO3vu+PExBgN0doJKdf2YMR/W1b1VWekLCrpn3rxYnQ46O3mabnG5zp0/Hzpo0JDg4Mb6+n98/31IZeU/WBYAFlZWbtiwYXFhYd9t0c+kDn45G+aMGvVIaOjHVqsboDQy8qWUFOEkEEnqcIX5M2iV6ubCwoLY2GqHIy0oaNDgwVRnpzg9xvWFhR+Wl7914YIvJuaeqVNjtVroDUi0Zlj25SVLiidPdvL8sJgYtcMBDNMDqNUQFgYVFcBxUFcHly5BSAixar3bvWjsWEEoPNkgnz+DAkg2m5OnToXQULBae+7EgfwZMJA/42ecZ5jNPYGCLRYhUrFknmGxBAZMJmEUgACubovnGQEB7KjIeVGKAouFePMoAZJIxQwDZrOwBCkBSIEIGAxCnBllALe8cGKEAFlXUQYk0wiaFoRCTAHwH/zKSd0biIqO/vgPf1j87LOfffHWpPEzKKoNgAOgKaqjpubc+vUeh+Nhiuqsrn4qNjZ4+PCJFEWRsX5ApXVmRjM4+fT5Ch/bTkMzQE5CbObtCxbo8NQ6w4DZHJucvPSBB1p53ujzhUdEUBQFbndNQ8Oz77yjKi2tMZuzMjMbGxubzp93sSwHAADtNG0IDRVygyu3hURqPBOgIDWObWk6Kz7+d8uW7dizR2U2f1RYmJyR0RNsFUtQUJK0Ue+JCM0wqZmZqejF65eGLzY2dukDD7TabMaoqHCep0ymAHn6emvNqFQjc3N7OjIxoNVCVhacPw8uFzAMNDXJWrXE7Ptp1T9aan+AGCfelX5tIQv4Sy2ZZyCAk1/JNIKsBygAYrPGTXXSgSgD/ZSalDMQCx1cLrDZeh7FOPzB2ah4noGzZn+A53uS5dpswHHCPEMZoGnweHpGAZh/mJz2VACIozTDCIBaLXxRApACEUAfcPxTAcDde7KJhwD+qQyIh0sIkIGkMkCEEgMBpe4NUByXFxPzzTPPXP/CC2s3Lo+Ny2xoGMfzpsREluPinc6hACN5HqorI198evFTv1+dnlmAFZFT2uOgK86e8rKtAEBDHkPfGxe8k8YT+N1SUzabGcCMITG6032vXLfOt3t3OstOAvjthQu/5/lf8PxUgPEAKpVKk5w8Ny9PoS28DscX69dbGxtvvu66WLxj8b8w+pOC1BSFAM0wk9PTJ6eng9kMNpuwvCMCZJUkbYSaywEYd4icJ/D5KAAzy5pxNaa9vSdJNSnBX2sc2xKrFgN4ITzFolJBaSm0tPT64XJm30+rDgiIrVpOan+AGCfelX5tIQv4Sy2ZZ/hLjQCpiTLQT6n9AbkORK6HGcgHLqxnk4COJAAkCf2Ifj4KgPhzfGPwVwWAYYS/iAvEfyoDOHNE33ZSmgjj1erSysrl69Z1trRkZGYuLCoKEdeKuMphDcVXRADjZcpVTAHAOmPYWvyn/w8PCBChCCAntQRQq0GtHp6R8eEzzzz01lsXq89dP/eWnPxrc0fNPH9++6ZNq7u6UgHazHAgqrVj/+5vhw4vCKg0y7orKs6t+Ob96iOb5jfVRoeFMSr1SDrGNGTj7dfOUxsMclITJUuqqmpYdiTAHgAjx0UBaAC+B7g5IeHmxYtvmzpVTc4G+7VFS3v7okceGXrxYhjH3b527cdvvZUYEyMAGPhWQWrUREFqCSAvNadW17a2emh6UFiYTlwCKRBXWRWsOiAg1hqdqRSsesQIqK8XOt+zZyE11V9qaVv006r9AYlVy0ntD/RTan/A36pxOqIgNQlbKye1GOin1P6AjFXLmn1vb4ir8pkhjiMPoJQDQwEAUZB60jMqAHJx9vEZpgD4B8Tv/WGrzfbuN99krF+fy7Ib9u/Xm82Lk5NlMzT4l4bHWeUqpgCIs1/IXSsgcKVS9y6HpqjJBQWv33//fa+9tmvfluyRU3Q67dix06699sTatY92dWW3w7JT/G5Lc13AdACVlSfXr/9bWdmx4uJj2fGD8oYMyU9NZfT6UTExUUVF0WFhlMfTp3pagJsAHgRgAa6h6X+p1TaP5zzDDBs1auHUqVpMdibTcEfLy401NW/7fBTAk42NK/fu/c1NN/UorCy1QsUCAjJKcjz/2Zo1Wzdt8nq9yZmZf/jFLzQBmwzLV7Bqf0Bi1QrGAwAYw7GjAygKLl6EtLTA96b4F/XTquX0ESusbPYAVyY1QN/pZOQKIUrK/aKAQD+l9geuSD1S5lX9zPD5hNxwOCnDkGQ4J8XnOa5Nkc8lAAkNgp/jOjKuGyoAeGuJYwyQYpUBLBldQRAgJ/tdLnC7a6ur2dLSu30+EwB0de0+enTxwoW94lWQEsgVJbFDMCYEqTDBlAEMSooLRwhIFFMAUCgCyEktAbqlVgHMHTVqxfPPL3zxxTf/8uSBQzvmzrxuwriiffsqurqWAcR6IM7HbSLfc7nA5eJrqs/u3fXppq0r6+sr1Qzz20U33jt7dsyBA1qbjdJqw4KDwWQSIi7ISE2UHBwTY2MYnmV9AOa4uPHXXVdaWxsXE7NgxowgDNsQUGqWBZ430XQjTfsAVAAtFDVMp+sBiO3JSY1dqoLU/kAgJc9UVHz00Ue+2loNQMnx42VlZd+88opKbHUoNY5qsQTJFeUAiVXjIQa3GwA4p/N8aeme8vLU0NBJBQUMekZERQkHNVpaoKkJgoP7MPt+WrU/ILFqOan9AfI5CQ0iJ7UE8LdqXFkKaNWoJAIKUosBean7AGSsOrDZu1zCjPmqfmbo9YAdBL6Cg3vtYJM98ODgwIDZ3BO4Gze+cDKrDJBET7hZh4u5uFWuDEg84dRqCAoS9taCgoCiwuLjbdHR5aWlsTx/VqWKTksTgID+ncSHjwC4xY0ueghYLMLIQhkgW3kMIwAoFG6dKQB+G7N8cLDD6dxx9OjeEydGpKXNmjYt2GymxDu3flIzLFtYWPjFW2/98umnt+/4dseulTOmLdDpKgGKASi1+tzw4SlmM9vWVnb+fLlez9fVWT/55OX6ukqjTverG274/UMPRej1NEVBXR1cuAA6Xc9V5KUmSi6cN+/BU6fOVFSc0+vnTZv26H330XgWWllqnw+02rFjxw4vLJx2/Hi418sPGbJ44UIhjh5uDOB2pZzUFCUAclJLgN5S8y7XJbt9xapVJ86fp5ua4gC+AeBYdviRI9vLyqYXFgoi8DyYTELAWvEWN1qFMiC2aq1WvKi1/8KFp59+Oqe19V8azbQ773z6l7/U6PWQmQmVlYJbgt0OiYl9mH0/rdofkFi1nNT+AOkH8K4MKHVAgLQRAv574P5Kki1uOanFgLzUfQAyVh3Y7DEO5tX+zHA6ob0dfD4hihxFQUcHuFzSPXCAwADLClvcCODJSZ7vAxC70iLA84JDmzLg7wnHMELFeB46O+N0uptnzHjVbg+x2eiEhKUFBdDRAR0d4PVKnQ7JFbEEBHBkQU7AogMl7oApA+INagRQKBwNKQBEqG7Ax7LfrFy57eOPJ9vtO7Xa8xcuPH3bbXqG6SlBRuqJaWlfP/vsjpMn/7Zp03frvgAAgNkMkxEVqVHR93355Uefffb7trYmbIrI4OBfLVgwfcSI6QUFWrUapfAAtDc2Mnp9iNNJNzeDWq0gNVEyOTj442XLjp08GZmYmB8TQ+NGYp9SsyxoNAzAR7/5zYGqKntr65iCAjUKiwCOIhWkpigBkJNaAvSWurq6+tYnn5xdV5cBsJ3jRgAwADRAGkBrXZ0Qdhu/iMmRMB44mX+TfVEFQGzVvR1At65ff39Ly8083+ZyPXroUEVhYWZsrNAVdnYCTcPFixAb24fZ99Oq/QGJVctJHRBAqfGu9JdaAcDPEcC5gngP3F9JBBSkFgPyUvcByFh1YLO32Xr21a/eZ4ZGA0YjmEyCs4fJ1CsoNI4CVCpZwGgUhg8IGI3CpE8ZwEcCPvYRMBp7Ih4rABJPOBzdYDdqNALL0lrtnOnTRwwZ0gYwSKcLs1gEAPdyxSWIr0gAnEaQsz84vCKx3BUAEjkHXWmJUIgpAJIgSCqVg2HOnDlzp91exPMTXK43z51rdrsTIiJ6SpCRWmU2j8rNzc/JGTdlStm5cx6afvezz85XXujstHz++R/aO1vjIiOffPjh8OhocLmiQ0MLCwqCca1WqwWK8rHs+zv3GQ9fYNS+mAjT0PHj44YPp9EAAklNlKQYJjYsLDYiQjgT0E+puwFGrR5fWAidnYLXE5Ea/TsVpEb/TgWpJYBIao6m31m9etDly8/wPACUAezQaP7o8TgBjgBMtlo5g4FGqb1eMBoFTxCxVROPUgVA/MNxTZJYtUYjNB/27waDEDIkLg7a2oSFHYwQrmD2Vyh1DyCxajmp/QHSD+BdGVDqgABpIwQksdADSo2AgtRiQEFqZUDGqgObPebtuNqfGV6vMK7H5yc+WvEID3lmuFygVgcGyBcRoChh8KsMYIg6Eg0GD86Q6FIKAJojjgIQ0OkErBugARLN5kT0B3U6weEQAHLeCksgVyQl4DSC53sVyDA9IwsFAO2e7MRgmBrElAEiVDfAaLWMwWClKOB5O0U59Xot/lJSgpzUDAMOBwVQmJZWGBEBRuP1w4Z9tmVLh8sFXi9FUTfMmjUsKooODsaNVgqF7ZZ6ze7d721rusFzgwac1Y3vL3/mmZsefbQoL4/CTieQ1LJt0R+p/QGJ1NhTKEiNPYKC1BJAJHVxVdXuAweA5zGwdTXDjBg9etvevTfy/DGOu2fbtusLC1MjI4UvYtZSTCYqkrrndpADxFaNY9tuq555zTUPr127zWo9plbfkJ2dGh4utIXRKPSkXV1gtYLF8r8ptT9A+gFyV0qklgNIGyGAzrvkmUEAsZIIKEgtBuSl7gPov1UjMJDbVRjUy7lzEM8BZQ8WiVuFnOuIgh9FP72kiMuEXPkECFggpoZXBgJWmGBygNxbwedH5m00GK6dMuWVysrtDQ0Xg4OXFBVFhIUBywZ2UAkkNYWeIQwTFR6+dPHintsVB/Ldnic8TXd0dbl8PktIiJ6mS6qq2nwFrRAbAw1qflBGw4Xtu3dPysnR0DRP03aXy9bSYvZ4THo9pdwW/ZdaAkgUE/8loNQUxdN0fWvrqnXr6srLR+XkTC8qMvYG5KrX0N4+zOWiABYCtADwKSlJwcGzAe4A4ADibbYWmy01OrqPpvT3yQl4+5DPSX0ACkaM+Ocbb+wpL781JGTS6NEMrljixAKH7Xgs5j8itY9ldx06tHvXLnNQ0MJ58wZbLJRcW8jdp+Sn9b+jwPUrhbtGDASUWgzIS90HINeByNUcn44D5zN6HJOJIzMqhX/BQwkBATzbQT7XaAR/A2UAP8dHOjkdgpgygJtaeA8gICmfAOIC8U3czBUAdGAnhwnIfyGmAOCyLLqXICApXw4gQnUDlEYzPj//w/j4C1ZrgsmUnJpK4+iVlPBzSM3z/M5TJR+v3lTXYsjN0j8yf+b8iRM/Xvdxa0tXLNQEwaUUgCMeD69W82p1SU3Np1995a2uVick3Dlv3rCICEqhLfoptT8gkRp98Lul5tTqS83NFeXlyfHxg+PiaI0GKKrN7X7188+jN27MYdn1O3d6zeZF48b1CIX7nIGkHp6W1pGQMKa9vYHjmi2Wlx5/3N3a+sXu3brOzmqadiYlpQwe3GN1eOoClZeTOiAg/uHk3IbPBwC0RpOVlpaVl9ezho5Kmkyg0wnPDJTo3y/10XPn3l+2bL7V2kLTj5WU/PV3v4sNDw/cFnJWLZHaH/DvQHDu4m/VREly/EJOajEgL3UfgFwHItfDqFRX/TPD6wWnExhGiKOi1QpTP5zPYqeDebsCAuSLCNA0OJ2CkSkA+BzCzxFQq4V/KgO4IonjLwTwjS0qBkiBCKB7KyYFUwBwfVlcoEol/FMZEG9xI4BC4V2hABChCKDRUC5XfFBQfGIitLf7b5LLSk2qKic1Amo1OJ0Nra3vfb7yu70PsFzCgVNfJxh3PDh/zvu/W7Tv75+rz56M4jyXtbqJQ4eqvV67w/Ht6tUZ338/wefbdeLENxQ1ODHRjF6SAduin1L7AxKpsSdyOgGAV6t37dv3zldfxdXXX46OfvSOOyaNGEHRdE1Dg7u09CGfzwygs9v379u3KCen17YqluAndYzJ9PIDD3x36JCxoeHZvLxrhg1jrVbPY48dOXLEEhr6QlFRuF7f80VUkqyHiKVWBiRWjanl/Nqil5LYYWFMpLY2QbF/s9Sbd+2a1NZ2K8/zLHu8srLk3LnY6OjAbUH6Abwr/aWWA8jtgABqJd4D91eSAHJSi4F+Su0PyHUgcj3MwNrUwOvqfNW1tl6oDWe5SQAGl3vSwXP//PX11KyxBdODTBXff19dXj46MTEuNpYGsHV12crLJ/h8GQDg871fUWFzOMw4HPtPvdrt9tXbtz926tQknt/Z1LRyy5aRyckhFotFr7cajV0ARoDLFGWJjOzviixAVlJSVk4OtLcLHZlev2Dq1AWTJoHPV9fW9vY334TqdItvuEH9H24Yna7nSBPpwv7Nr4SYmFM0zXKcF+CiThdBQsAOvP4rX//bzwytFkwmMJsF6zSbBa8GktYYV6jkAHKwAwH0SRD7TQUE0FcHR9wIkCCJyoDEq4GmwWQSnvwSgBSIgMGAgTL6ANAtCpcsESBR4pUB3MrDpQkEUCgsXwGQ+E0pSC0BAkpN4tPJSc3zWO24xMQhyVvOXFrLcUkG/Q/X5CWCyQQmE5OampaXlxYWBgwDzc2g0ViiokKGD990/LjD692tVgdnZVkiI3symvm3RT+l9gckUqOvDkUBgIdlqa6uEJ4HgBCep+12j1YLJlNiRMRN8+ffBxBptfoGD372+uvBZOoRCp15lKXGNkLFdDrw+apqa3/xyCPXNDRU0vRnP/zw7RtvhJtMwqgzoNToJRUQEFs1nj0O1Ba9lMSscDjV0GoF77h/s9Q3zJlzqLT03rNn27Xam2fPzs7Olm0LYpx4VwaUOiDgLzWerpAAYiURUJBaDPRTan9ArgMJ2MPg7Xa1PzPcbuH8BP6pUoHdLpzPFJ/PYJjAAPkiAugRhAHDFQA89UocM+x2oGkBUwaw8XDmiIBG0xMDUQyQAhEgcaqVAbxXSX49jI2ImDIgXnpCAIXC2b0CQIQSB2sLKLUE8JeaVFVOagRoGuz2SLV6XmHOxerXGCZ+xujY+aOmCr/F7Yb4eCgrE54ZZWXG1NSbp079vL3905oaU3z87VOmGNH1Xq4t+im1P0BRYLfzPF9bV3e2vDw6OHj40KG00wkAQTrd4IyMj44dm+By7dbpUocMCQIAu53muAVjx44cMaKltjYpOjoyNFR6PgNTIsopSdoIFfN6gWVXbtyY29DwHMfxHDf/4sWjx4/PtFiE9RB/qbEEEqNQAoitGtdDArVFLyVRHI9HCJBnt/f46vxkqVmX69i5c12trbm5uUHkKLXbbeS4Vx55pLyszKjTZQwdStvtPUZIoo6jkuRzvCv9pZYD/KWWrE35K4l/KkgtBvoptT8g14HI9TADMQoHci79f5dzSVZqcXaagFJ3J5/hAfYdO/b5quVZ9ZdKTA0Jcb+ITEwQTv9SFOTmwpEjgqoVFVReXnpk5JOxsTat1ux2m/R6Srkt+im1TCKgc+XlT77+enht7UWj8c7bbrv7uutoitIGBd15yy1rk5OPHj5ckJt77ZQpWvSdNxhohklNSkqNiwsg9Y/KuRQaFVVM0zzH+QAaGcYUFgYWS4BQ53KJgALlXOojEZBYSRzRYx+t14PZDCrVzyI1y7LPvPfesX37Qjwe9dChn/7xj+ruI/cUywYbDPn4XTztPJBzaSDnkuxrIOfS/585lwJITaoqJ3U30NXYuHb9+rvOnLmR407Z7W9v3TonOzs6NLSnhMGD4cwZAIDLl6G4mEpLM3u9ZrNZGCEqt0U/pZZJBLR63br5p0/fzXHNLS0Pr18/KT09JS6OAggFuHPaNBg9WugIOjulKZX8pf5ROZcWjxu3esSIGyorW2h6xKhRYxMThYM+fimVeJ6/VF+/YvVq0GrnjR2bFhdHyeRc6iMRkFhJ3MbAGEd2u3Dpn0Pqg2fO7Nm6dXtrKwPwC6v16+++u336dJJSiff53G1tTo9H53brXC5qIOfSQM4l+eurQKsFrVYQC/+CEV3wUYyL5nKAVitYKvkcbxhlgPix4eceT6/yFQByCBNHAWJPOAlAChR7FpIRmRyANcdukRSIG5LKAA6X0EUPAfEvUgCIUASQk1oCBJQaq6ogtdsNWi2rUrFOZzDPA4CB53UuV5XVermtLTYpKVqrpTAFUFWVcHuUlUFyci+VlNuin1KLAF6r7fB4qiorLQBdXV2hPE8BaAFMHo8Tv9Vbao6m6xsbG9vaBg0eHIEVDig19gtXKLWapj999dWDZWUmmh47bhzT2QlareAQ1VvqmsbGxb/5zazLl4GilqxZ88Vf/pLeI3MDAAAgAElEQVSA+bdJW4jLJw6pvdtCqiRufeEZGhSW7Eb8NKk7PJ5YllUB0ABxHNdgsxGAZ9kaq3XFqlW1584Fp6UtnDgxKyeHIuVgP+tv1WSW4C+1P+AvNYmgLrFqIjUC/lYdEOin1P5AP62alDPgazvwugpfBp1uaHb2p4cPV9vth7TaGkb94uff1zTFpCVtfnzBjDFjCiijEQYPhvPnAQCsVrh0CQYP9i+H47jjZWWX29qyMzISg4N/9GGn+paWP330kaO83GowqPT6i2Zzg812VqUKychI8HOF4nl+65Ej/1q+3Fxfz6al3bdwYfaoUT/vOatgs3lmQYEQUJJcF6C+ufnY+fORZnN+Xh4DsP3Eifi6umc4DgAqm5q2nzhxV2LiT702Ts3xhbN8xRfLcYfPnm1zu/PS0yONRgUd8tLT34uPf85mC+X5o5GRH4wf31MIy67YvLn5yy/nO53Hjh79e1vb7zMyBnynBvym5G0Uh2Y4G8D9NzxYj8NYTOSGn/sDks/xTxx3KAB4J/h/Tv6pAODnxI0a3wQjAPknAhjsnXguygHk9/pfVxngOCGxF7oq+f8iOYAIRQA5qSXAT5Da0dnp9vmCi4rW1dbSGo3LSe098BDLTTpzcWeY6p9DMtKCfT5ISICaGrBaweGA8+eF4MeicjiOe2f58k/+9a8RbvdrkZHvPfVUzpgxVyC1CFi1YYN+3bo/+HxdAIuTk29/8MFLVVVjEhLmFxUZcM1a9ItaWlu/XLny3t27c3n+m4sXv9Vqs4YO1QSUmqJApfp5pHa7L1RV3fPSS7F1dcUq1XWzZ7+0ZEmk0XiRYXwsCwAVNH0DBiYSt4W4fFzA6dOqu7qEEzkYJBxPg8uYPUtRj73xxq5t25I4rj0u7otly+J0OjmpI43GL1988av9+zuam9+fMyclKIgAXqez9sSJBU5nIUCix/NGWZm1pSXIaOwxe4zipWDVEqn9AX+pyT62n9TCPAABf6sOCPRfagkg14HI9TA4dxnYAx/YA7969sDbKOq6xx6Lq6o6x6qKYSxFjeThKM/HAxhYLqG23eBCF8/QUGhqglOnhAVou10idUVDw5GjR7d1dIQDfFpbu+7w4RxcH7/yPfC6hoYMljUDGAGS3O4h2dl333ijsO+KW0ciqbucTmN7+yCeNwAkc1yJ1coajYfPnt28a5faYpl3zTUZKSmUOB/4Fe6BBwCMRlCrvzt4cOalS0+yrAfghmPHShcsmD5lyor9+xceOwY0nZiZOX3KFCHOXaA9cF6tPnLmzOZ9+9QA84qKMuLiqIB74CTIGwCEhUFwcIAA3d1mf6y8/OyJEwftdjXAcxUVKw4efCQ3V05qCiBIp7tvyRLo6ACMxtZt1SqdLnjIkCMHDgzyeo8zjCchISg6GiiKB2hyOtdt315WUpI/blxRXl5QUBA1sAc+sAf+f2APnOO4ipqamsrK1KSkQeHhFNmnHdgDFylp6+oqOX16V2lpfFXVUyx7H6TwsJLndQCvU/ARUEUG7c6x6fogjhOkHjQITpwArxd8Pti3D2JjewZZnZ2etjad04lH3ow872lvh87OH7cHPi4v74t163Q2WzVNO+PjUzAzNtl37S11uEplTk//25kzBV7vDwbD8MzMC8XFTy9deqvV6gK49dtvl7/1Vkp8/I/eAw8AsCw4na62NtxoYQBMbrfbalWFhX3w3HOnjh4Fg2F4bKyqq0sI+BFoD/x8aenTTzwhVHLNmuXvvZeCnZTEqltbAV1dcYbR0aFg9s7WVovXywBQAEE872htFfj+uRsQq1ax7E1Tpnza3PzWxYtUYuLcvLziEyfCGCYhMvLtTz9l1q8f6/Fs3ry5+fbb77nzTg22yMAe+FU9zzCbew68WCy9UseQeYbFEhgwmYRRAAJ4XkY8ZAsIYEeGgykELBZheKIMSE7cMAyYzZzHs3rLlk+WL49pbm5LSHj83nvHDB9OkQLNZvB6wWDotZ3odkNAAI/s4cQIAYulexNAEZBMI9BbEae3yoD/2FZOagngLzWpaiCpfT7ffX98+9hpT6erJpFlKGDVYAdgAXQ0FX1N7o64yK4xeYNvLJyhCwsD3Pg1myEvD06cEK57+DCMHw8Mgz98cEZGTG7uvaWlI7zeg8HBj02efGVSi4DJU6Z4PJ4jx49bQkJeKCoKHzRI6BEMBn+pjSrVA0uWrImN3VdWNmb06DmjR/9z27Ycq/VujuMBdjY376+oSBk6tGfwG0hqlqKOlZUVHzgwJiVlSHIyjYoFlLo73dC0adN+v3Nnc0vLOYYJGj48bcgQ0Os1ISGjRo0Co1HoyCRtIbLqbWfP9qpkaWnK1KkBrLq5WZgaarWAbr4yZg9e78j8fN2QIXe1tCSw7NHIyDdmzIB+mn1vq6Y4Lj06+smHHrLabB0c98abb6ovXarR6Ubm5HSVlz/hdicDWByO9aWlDo1GQw7K+bs1o9TkUKEYEN8O4llCIKml0whi1QqAuAPBII+kA1EGUCgCyEjdU87AmT5wuYSEJPgoZhiw2YTlPPE8g6YDAzzfc+DFZgOOEwa/ygAu6JNRAJ7nwvKVAfSgwFEAAmp1XWXldxs2/KG4OIfnv2psXB0dnRcXpyEFqtVgswHLCgMuUkJAgOd7xrYEwD+VAfFwCQEUigxP5AAilBgIKLUE8JeaVDWQ1Ct37FixhfJ4VwD4mqmku6hmJ99CwwiKmhgbfvL1ux8pyEwXAt/iG4VKS4PycmhvB68XystBp4OsLPzhBo1m2V13rUlIKKmuXjZ+fG5iovDFfkotAowWy4JRoxZMmdKjJz4zyPFJkdSUSpWg1z80Zw7MnYuLV8nh4dtp2stxHMAxhrnfaBRGsrg/4Sc1xzDvfffdX//xj7EOx59DQl555JHZs2ZRAaXGL3IcOJ1jk5L+/MYbq3btWhgdvXD2bJXTKQQJ7gaELkzcFiKrTgwK2iCupMXSAxCheB7q6nqiG+GET8bswWYLMhg+feaZ5Vu3Xu7o+GD8+JTISIHvj9mLrZrjKJYN4rggo/HtNWuSDxx4gWVdAJPs9qCgoHaKAp6vpyjGYlE7HEJReFeK5xkoNbFeCUBuBwRwmVc8z/BXEgFSVWVA3IHgNIJ0IMoACkVsTEbqHmDgTN//gZfD7TbZ7UE8TwFE8Tzb3s7hgGLgJXpV1tezbComozMbR197fVDByJFGimpob88buiAlNDTw1ygKCgpg/35oawMAOHcOIiPJ0E9F0wsmTFhAZvH/S6/rJk7cO3v23WfPejSaW4YNm5idrcw3tLScPHRohd0+FOA7q3XHvn0TJk0y93UViqKGJCU9m5AgPFSu8DWroGDH7Nl3l5Z6AG7Jzp6YmxtAMY+Ht1odLleXy2WIjDQq+kEJrlUMc+u0ab2Wnn7ay9rcnMhxNIAWIJOmw4YNe8jlSnU4IDPzkaIiAyZsH3hd1c8MjQYMBjAYejKdeTzSPH2YRywggGdWcZKLc2EcYigDuGBCZse4CoGjM2UA7w0cmyBgMMQMGhQ6bNj/XLiQ53bvMJtH5+erLZZeBbpcwgYdWdjFE7D+AM+DXs+xbHF5eYPDkRUdPSgyksI5tQjoCcWDP5BlhbA5uBaEAAqFmAIgCYKkILUECCg1qaqf1POmTfufDX+vb3qfotozk1p/eeM9sYmJ0q0jLEEidXw85OTA/v2gVoPLBeXlkJoqLHr4tcUVSO0PiOuPUTQMBiWpcT2E51UWyx8fe6y0poY2mz2trduKi7MzMyNNJgqzN/tJzTudNEWhF60agKeokpqazvr6rKysQWFhlPgS+EWMpCQOJ2UwcF5vaVVVRWnp0KiohPBw2g/oURIADAYVRf3xiSdKGxtVHs+QxETGbO75Xd068B5Pw8WLx48do2y2yvj4sTk5OfHxlIzZ/5ukLpw06e+bNtHt7ZdoutZi0XR0pND0RaPxvsmTc0eOpIhx4l3p1xYgB4hvB8yZKM65FFBqBEhVlQHxD8cgu+IORAFAofzaQio1KQeBAV9b0GiE4QNxREPTR9dS4qzmD5AYnAgQh1RlAJdE8XMESPl9AmS1sbsyJoZ5eOHCdQkJZ0pKZo4aNX30aNrrlVYY57/Ev9P/FyHA8xxFfbJ69acrV6Y4HC2xsa89+2xWeLgwNSa+tuJfhNKhcyTWHAF841NZASBCEUBOagngLzVpxEBSZ0ZHf7Vs8feb9waFmW8uvC/GZBLKF0uNJfhLnZgIxcXQ1QVeL1RUwIkTkJoasC2aGxs3nToVpNXOHjVKpSy1f1uQ+iOAXpgKUlOUALjdeoARcXFvrFixZv36ZLf7g8TENx99NCk2lgBiJcONxqD4+HsOHpzM8xspSl9RceSFF1I6OloSEl779a+z8FweXgLfxN+0uwROo/l6w4Z/LF+e0t7+1+jopx5+eHx6OiUCpEqqVOB26ylqZEICOByCh6if1J6qqjOnTw+qrBzM826rdfnGjakZGRbid9Bb6iuw6iuReuKIEfDEE3tPnAgLCSmwWi1r197q8dTS9N927Jg6fHgcSXSKd6V/W5AKSAByOyCA/T4u5clJjYCka5IDJB0I7qEGtGoJIKmYnNQEGPC1FfII4VvyT8zNgFmL5QDlz/v/RY4LjEmAQAzF81GhoUtuvBFmzOjZwpIrkHwoA1TW1W3Ztm35pUsRAJ+0tKzatClr8eLAFSNV+hE//D/+RQrgmpwR16Qm9fhZykvNsuzB4yfXHzwRbdEvmjY5KjaGysuDAwfA6QSfD44cAQDIzBRiBHS/2zs6Fjz8cHJdXSNFvZ+VtfLttw06nVLjStpCrv5yUvcmS6urd/zww+bqai3Ayy0tK7dufeL22wNK0dbR0VJXdwvPuwCmcNzKixc3s2wywCetrau2bMlasoSQPM87HI4dhw7tP3x4WFrarMmTgw0GiuebrNYftm17s7w8m+e/bW1d88MPOXFxJvyxkttHXE//v4itmuM8JSXetrZYng8CyGDZXdXVXU6nBT2q+3mL/WSp9Wr1zLFjZ06fDjbbb197Lc/rHQwQwXGm+vqmtrY4hTa6ovtdUpOAb+WqdgM8z3vcbmdHh9rhMOh0lLLU/p/725icemLgqn5mqNVC+GV8lur14HJJ16bQKzkgoNcLoxgEcNVFvGASEMD1EFQfAb1emNIqA/hIwBSMCGDlERMD4gLxjQFllQGed7a1mTweLQAFEMrzFV1dPeVjF6nXC6ttWIJe37NwhAkjEUChEFMAJEtPClJLgIBS4yBIQWrEFKT2+UCvLz57btEfvmtsnU7RdRtPf/jZS09FJCeDTgdbtgjbg8ePQ1QUxMaK2+KrH34YUVf3Z5blAGZUVBy8eHFKfv4VtIW4/pgqSllqlKJbyS6eD/N61QAUQCTH1WHDBZLaY7frXa4ZAKkAKwAOcJyeNLfDAXo9uQSn1X6za9e2Dz6YaLPt1OnOt7Q8fffder3e43Do3W5jd2x2rquL1WhAr5e2hfiH4+ZQwLZAHVpbtV1dhsjI83V1tRy3SaMJz8qyhIUJgXMCmn0/rfrHSj00J+eHPXt0TmcFTbMpKXGDBvUyTrKIJ2mLgID4dnC7hZUl/F8xgEKRpSeVqldVAwGtbveXGzZcOn9eFx6+aObM7OxsSkFq/7aQ60AC9jBk8eqqfmZ4PIJXNTqoqNUgdjMnflOY1N4fIF8kADrzKAPoO0QiFaNnC/HEVwCw1bHbQkCrFb7oD+DnCJBzDMoAzydYLMGpqc9duJDl8+00mxfn5QlYNyDEfCZXpGkh2jZxakIAhUL7UwCIUOKg0AGl7gYcPt/BgwdBry9MTdXiKTAE8EIKUiOgIHU3sGbbzsbW6Sz3GHDcmQuLik+enDJsGCQmQkoKlJQISyt79kBBAQQHCyfRHI5eLiUYcRqDS/ezLUj9EcBhnYLUOAPuVjI1NJRJTv5tXV0Kz28JCno4J0e4lp/UEVpt5JAhfyopKXC7txqNDovlpdbWER7PTotlcXa2+BJegDOHD99psxXx/CSn880TJ5qLihLCwyM0msj09D+dP1/gdm83maZmZxuwTSVtIZYafXUCtgUeMjh6VM1xw1NSTnPcCpPJOHjwrVOnGtAZSc7s+2nVP1bqOfn5HXfdtaa4WBcZef/cuRFqNdjtPZ5sAduC2J4EILcDAnhyS+w3RQB0iyIAqaoMsH7nzsq//W2ey1VB0+83NLy4dGkkxjxWMHtxWyh0IAGB/wIXgP/tZ4ZeDyEhPacoQkIEH2TJ+Qw8j+oPYKxmAAEwmYQQYMoAjm3xiY0ARmBGt24FQHxKE4Hg4J7zpWKAFIgArsNKDif7Azxv1uv/8NvffpefX3b58kN5eWPGjxcsrxsAvV5IGkyiRjNMj5s5ps1RqwWh0K1bAfA/EyAntVoNDOPr6lr40EOus2eBogyZmd+/955KfPYYF2HlpEZAQepuIDY+jqLrgOMAPDp9/f9j77zD5CjO/P/2xJ24s6tdCWWtEkgoBxRWAiRkCTBwgMGAcc6Rs419+MzP6Q4ftrGNczp8nPH5ONtgG0wSGQkhCQUkJCSUUc6bw8zsTPfvj2/pndqq7tpeDLbEzjzz6Nkdfaa25tPV013pfSsHDaJMhqqrae5csm06cEDkJHjpJbrkEkqlUMJ73/OexX/4w3V79x4JBDLjx9fPny8GtX0eC64/AEzMGlRjivuUycpM5ic/+MH9f/7zviNHvrJgwZRRo8SUr6a6Ihz+0j//89KJE9ds3/7RadOmjhv3xMaNr2zc+OkFC2afe65Imh0MUjYbSKWCtbUNluU4TptldWYy0dpaqqysSKe/dNNNS2fMWLN9+4enTaufNy+EcXl5f4aiGlm+XY9FNEoNDdTcbMViVcnk/OnTZ115Zai5ORQMWuZm77NVv17V/TKZT37yk4WOjgBROJWy2ttLjRNnpX4svAA+HQDo+zMAQJSclImr6gFs3rz5ks7OC4hmFovrDhw4kMv1P+ssT9X6sfD6AnH9hkGL6uvXDKQd7uqi5mbxSlOTiN8p9zMcxx0oFEqZTJqbRZYSDrbqBchrdQBgKTpRD4C+SzMQEOk5FYALBID5K3lDrCvgOFY2m8hmb5w7V4z7Y88Bz4A5DmWzxFthsTFV2X7BACpmBlgUA16qQyEKBh95+mlnw4alXV1EtGDDhkcee+yKhQsFgD9kUA3AoPoU8M6Z0++f9sNXXru2Irz/2vmTpwwcSE1NIpHyqFHU1ERNTSLh83330cKFVFNDnZ2JQOAv3/nOYxs3VkYil86cGcJx938suP4AsNfXoBoZok6ZtIhSqdT7zz9fAAiWLgFs0gqF4sHgVdOmXbVwITU1UbH4zvp6mjCBolFqbZWPRZjo8tmzb3/11ScOHXotk/nQvHm1gQA1NVnFYjybLZXQ3i5ufvlg6aqVzckygLG+xkYisiKRYP/+sY6O0mYCQ7P32apfr2qLKBSPh+S9Mtw4cVbqx8IL4NMBAO4s5X4GAIiCSc5hxfuc3IDhdXVrIpEx+fwBy2qtqRkQDFJjo6dq/Vh4fYG4fsO0tpLXqvS+OJ+BlXAYbVSuGRgGdQXk6Yp8vjTIbgZe93wGjiiW/7oORzLgNbBrBrymK/zMZ2AdrTxdwQO7BkC5ZhhUh0IUDLbadj/bRrDTGqJWlMOquapeqv3NZ6T69fvd7bdu3bcvHQqNHzUqiM/OopYsoccfp2PHiIhaWmjVKpo/n9JpisVqBw58z6hR3b6n/B8L//MZEOU6hm4AXFXzGzFt0B2wYrF5s2b9csKEnbt3D+3Xb2RdXQCjIvrUEb5T5Gbvcz4jn6fjx+ngQVGlwYMJ0waurdprPuNNUq0DcuPEfIOu2hXQVcsrcRmQTQIwqLZtCoWuuuyyXx4//v2dOwtVVR++7LJBQ4YUOzo27djRadvjBg3KpFK9m88wf8OU5zPERRgBhSAUP2BNN/ImIj6SF4Anv44nskQYAHx14nW8wuWbAfQuEQ4TgFI+A0qBeCK3gQFA9gK5QAUzAAhFFQgIQDHmBbAoBrxUE5HjLJ4y5RdDh960fz8RnRg8ePGUKeKuVn+jbtL1E7kBVqFQHY/Xn3NOaTRcVl1ZSeedR6tW0bFjZNt09Ci98ALNnEnpdC9U64CC4TbToBrpOQ2qFaCXqlnF0OrqofhCxACUl2qsWJUB5RPx2SR/onyetm0T8bXCYRo+nMJhz1atNPu/g2oFUF43HAsF0FXzLm4ZkE0CMKi2berqGpTJfPGGG07adqJQqMlk7Hz+trvuenH58spCoWL06F/967+GcDHwOhY+VTPAC5f77jUD901wKrcqnsHGHKkXgCe/zrs6zACWJeB1vMLlmwEcUfwJAEr5DCgF8hYHM4DZe+WTypgBgEno0o15AXLidPOxICLbrk2l/nr33ff+6U9UUXHHBRckKipKgPJG3aTrJ/ICzKoTCZo5k1asoOPHRcSLJ56g66/vhWodUDDYMKjmzRBeqhWgl6oZKORyjy5b9tL27ZdecMG0kSMDfFVQVMv5wF0/ETYxKH/x5Enavl0kc02nadSoUpl6q1aOhT/VTqGw6+DBPz///Fmp1PVXXhnulWoFUF43HAsF0FXjdQWQTbq+UQOsQiEVjaYwklwsrt248cGHH37+2LEQ0ccPHLh/1qzrrrjCdCx8qmagfM2gaJSSSUqlhItUigqF0pJBzIGHw55AMinKAZBIiAEcM4DxEJ6Swv+ia2wGlAhigUApqYMCcIEAMEEnB2tzBdAV5Uk82y5FiTcD6GVjKA8ARKF8A6AspTWoPgVkMplP3HgjJRJi6khWzfHpvFQ7Tg+qGehRdb9+FIvRU09RczOFQtTZSQ88QNOn09ln+1KtA4pqTMwaVGPvsUG1AriqLhSIyE4kHnnuuRWrVwdDobedf/78GTMC4TCAttbWr//kJy/85S8jcrm777+/fvz4UePGXfVP/zR50CCLS0Y4SHkfuK4aa9YV1cUirVxZikQybx5VVVFHh2erVo6Fv1a9defOz3/uc/UnTqwMBB5aternX/lKtU/VOsCNE2elq2pXgI8RAJ7iVgDZJAC5VRuAUx/8RDY7uqsrQmQRjbLtPQ0NPRwLn6oB4HTr69cMpB0mEv+GQiLnszIHHgy6A/xGAI4jvsjMADp9HG+nrY0CgdJUuQHgfDLBoAAikVIMRBngAgFwMmczgNOY18giNiIwMyBPcQOAKIycGgAWJQdrc1PdnM2u3707YVnTzzsv6Kqaq+qlGoBBtQz0qDoSoWSSpk2jDRvo5EmxjOLpp6mjg4YOzRcKL+7aRUTnjRoV8XksFNW49e6uutjcvGbnzi7HmTp8eBLRKQyqsVXYoPrUG1/ZvfsH//EfH25szFvWPz/55O+///2zR4ygXM4JhdauXfv0s88mstmDRFXt7YfWrJm7bt3t27b96AtfGFBVJUrAwmK5n6GrxryrrPr4cdq4UQSyJaJRoyidprY2U6tWjoW/Vv3Xxx+/6MSJm227aNvvevXVjRs3LsAfMqp2B4JBamuzHWfPgQNbt24dW1c3etiwAOdQOgWUTltNtQB4vEsBZJP4l2tiBk598KkjRvx48OBvNzdniFZUVX13xgxqazMdC5+qGSjHKCznXDojci51dXZ+4hvf6Nq+vTEYnH7RRf/xqU8FsZax9zmXTKplwKfqigoaOJBeeolefZWiUerspJdfLra3f+KBB4698goR1U6Y8Ksf/CDk51goqhEjSFJdSCQ+/tWv7t+0KWbbqbPPvvtb3wrxMkpX1b5zLj399NMzmpre6TjkOI+ePLnqtdfOnjyZstlCIvHMxo2Tjx1bT/QbohjRl4hG2Pa6Awf2tLYOGD7cJRGQR84lNRFQIkHr19Px4yLg9sCBVF9PmUzvEgH5a9WVtbX7LMsmKhI1RCKJfv1E+iBv1Z7HorLSse0nXnjhzrvuqjt8+EcDBtz88Y8vnj1bhPY6DXIuDRw48Kff/Ob9S5ce6+j4l9mzz5kwQXzYcs6lN+zxlsi5JD6LDNBbKufS/z3ySGjlyt8UCkWiBY8+umr69PpZs3qbc8kl+YwB8K86GKQpU6ixkU6cwD3pzj//edSzz/7Mtolo7okTf37ggSumTo2EQlZvEgE5tt3R2vrM888/v27dpClTLpkyZc3evSuffvqFrq7niW49evSzt9/+b5/4RFUoZHmp9p1z6dxBgx6NRA5ks0WidRUVn6mupuZmyuUKhULr7t0Z255GNInIIppB9CDRoXS6Pz6LngjII+dSt/WdjkP79tH69eLwZTI0diwVi2IRqv9EQP5a9Q1z597w6KPX799/MBg8v75++uDB1NzcrVV7pLdyASyr8eDBhx955KYtWy51nOWNjX986KGZQ4dWV1aeJjmXrGJxVCr1L9deK0TJgd/LOZfKj77zONLYOMi2kZFtcKHQzKf3afKIxWjOHNqzh156iRynM5cbY9thoj1Eia6u/7377sN79rxryZKafv16szjD/v1TTz31058uaGt7dunSV6+4om7MmDrbfoboXqKPOM6Whx/+j0Dgqx/4QJr3i73ex4KZM5+74oqvbNnSFQh8YOrUWePG4XXLsoL9++8IhbYXCn8kShE9EQ4nxo278YorRpx11uv8Y1gysGEDZbOEHcvjx9PAgW/e5Go6kbj73/993Y4dleHw7Nmzgzx29LoehWLRam/HTXvKcaz29sJpMC3cpx6nQSz0RIKSydIsIiIVy/GmQiFPIJEQXVEAiYSIImAGcG+LLicAbGbGrwZAmaGyLOJAmwogF5jLUTxOoVDPAKa4uQ+LmWSO5W4AOHIOhp5YFDADoEzMeqi+avHiT/z1r987dqzBsjpGjZo+daq7ap7/9FKN3r1BNQP+VTNQV0fJJL3ySt2wYWtffvnptrbXHOdjRIN27Hjw4MGH+/V738SJpmPRXXVXNvvKxo3va2t7m+Ocn81+b/v2S6666tiQIT/ft+eIexQAACAASURBVO9jjnMVUXOxePP27ftaWyd4qcbYlFl1VxcRBdPpWz/1qT0NDUGi0f37ByIRCoWKlvXd//7vHS+/vMuyOpLJP5x77rDq6ndPnbpg+vS6sWMD+OZFCVhNIM+BnzLpFIvHTp5ct3VrZSQye/LkYEUF7dlDa9eKkyscplGjaMoUikZ7p7o3rdoqFgf063fpsGFikhxnk9yqMcVtaPYMJJOVAwaMnjHjly+/vL29fXk8PnXmzMoBA0RKBW57fNpqqgWgxEJnQDYJQG7VBkD+4NgvYmj2MuBTNZfDIdb77jWDNwNjdALdMV5ax6ON4bA7wG8EYFmi620GMA/M0WDQAeS5QQOA5oieI4CKCoEpABfIAI8bGABsSJQLDAZLU/EGAO0e0xUAeMDHDLAoBtxUj6qq+tkdd/xp+fLh0eiXrr46jc+uqOaqeqnmmniplgH/qmVgyBCqrk4/99z1S5as2ro1uXPn1blcmKjQ0fH42rV03XWmY9FddSCXCyaTDZZFiNtRUTGyunrpD37w8e985/iqVY7jZIlao9E4ZLqqxleGQTUfo3C4olAY178/FQqUzYJ5duXK+++558nOTiK63LI+cPnli+bOjQQCAQxuyMfIssSAiXIsQqHmY8eu+8IXMgcP7gsG5y1ceOe73x18/nlqa6NolLq6aOxYmjpVvKW3qv236p5Uiy9lQ7NnIByOdHV95OKLx44Y8fTzz189Y8ai2bMjvIwVWe2U01ZTLY6FfM1gQDYJgGtiBuRWjaEnQ7OXAf+qAbwRia3O8GsG7jSxFRNHWn7y1mUvAE8cGP4Vu4sNgPy6uXwFwDSdoQIMuBaINddmwLXCjHkBXk8vY4anW8WsYHDMiBG3jB4tAlIhkkcvVTuBwLHGxocef3zH5s1TJk6cV18/KJEI/O2qlcoPGGBdckly9erzYrEn29oO792bJrKCwfnJpFiQ43UsulcjHI1evnjx7a+++vThw7tqaj60cGFtv36BSORrH/vYLfn8yn37diWT71+8eMTgwZ6q+W/1eIzcjO08fHhKLvcS0XKiinx+w65db1+40CoWu7UB87EOBv/v6afn7t79b8Vigej9y5fvjUZHIthRMEgjR9K8eeJb73Wo7lWrNqru9oMZCAatQKAiFlsyf/6SqVO7XZ57+0WBqQXDWSMDrqplQPm7XB+vbxilbfSomgHL6vPXDCybCYfF5A9+4JAh+AE7VF2BSKTb65GImAA0A3gdl3S8yOWbAYRRwzkAQCmfAblAPLFM1gw4DkUiohPNFWbMAGAqD3tHASjlewEsigEv1QrQe9XtxeKdv/998MEHZ+bzDz/++H89/vg1ixZ96Morg3+jagWIRCiZzM+du6OzMzly5AaicD5fUVV1YSRCTz5JQ4fS+PEUibgci+6qLdueN2PGL7/+9R379g0bPXpkJhOIRCgSGXfOOb+87bYdO3b0r64+e/z4QGenp2rL+ltUL5gx43vpdGNT0zVEaaLH1649fP31gzIZd9XFoihQOhbFYPDVAwcG2LZFFCZ6ez4f6OigRIKIaPhwmjKFKiuppQUeisXiptde63ScCQMHpvyr9tOqe1JNtt1Ds2fAp2od0FWj76K3ajYJwKBaBuS/WyyK+nh9w8iAT9UMhEJ9/pqBiF2IN4cOILp+vIsb66YiEXeA3wgAYezQyAwArkN4HUA4LH41AxiRRM8RAJ44ojLABQJADDXEfjAAmHqRC8RuNXTIDIC8/AMAROGsMAAsigEv1Qqgq+aqeqg+2dHRsnXrzbncSKJMV9dd69f/eOfOySNGzJoypVtVe6taASyr0NFx8/e/f3jz5khn57mVlZ+YPTthWZFQiA4fpn37aP9+Gj2azjpLPRaKatu2LGtoZeXQiRNFvMjOTurstEKhQcnkoPHjBWZQjbwOBtX8RhjrDoyurZ03Z86URx99F5FDtPHw4c1btw5CsBauKkqAah4wKRQoFCq2t3/vnnuWL1+edJzhRBWWFa+qOiuToUKBhg6lmTNLba9YLNr2bb/61YsrV1YWCokxY37+rW+F/Kn21ap1QFMtRHk1ewa4ceKs1FV7AbpqZd2UbpIBL9UyoHyBYL+I3qp1wGerZqA8NkXxOFVXUzJZCqONSVFlrW1lpTuQTIqLMIBEgpCtzAygBOyoBJBOl9atGwBlJVxFRSnMpAJwgQDicXVVoiuAKW5McwFIpcSthxmQLwkAIAoL1Q2AHtfWS7UC6Kq5qh6qY6lUa79+TZblOM4RoqFEVa2tq/ftm7VwoVCNEnqrWgHi8ac2blz+5JOr83kiOq+5ec4HP7iwsZGam8Xk/4kTdOQIDR5MF11ElZWlY6Goxryrt+r2zs57li6lbPa973lP4pTqLqJ7HnmkM5+/7qKLaqurRQleJvkYwVh3IJDLnb9gwcYnnigWCl1EuxKJ2qFDqbq6m2qUkEiocW1TqZd37XrwsceWHTvWQfQYUXDMmMsuvDAYDtO4cTR3LqVS1NrKJtdu3vzgU089f/RoiOjGI0fuX736uvp6P6p9tWod8KlaB7hx4qyUrxlmQFetXDN0kwAMqmVA/gLhpbR6q9YBn60aQDgsuol9+prR0UENDZTPiwjGtu0eCx2Lx3UgnxebJwDkcmosdFdA3hMAoFAQi6DNgL56mogaGsRCchngAgFks+rJ4wrgkoCVrAC6usTibjOgXBLa24Uo9OQMgP5F5qVaAXTVXFUP1bXJ5HULF36zra395ZePdHXdaFlPV1Z+eORIamgQJlGCP9VOJLJt794/PvJI89GjoydOvGb+/JpTJg++9tq5xSJa9oRi8bX2dpo3j7ZsoePHRXbYQoF27KBDh2jECBo2jEaMEFmyZdW2XQoar6k+fOjQNV/4wrxDh4jobffee/93vjOwX7+jR47808c/PufgwZjjXPvf//3b739/6IgRJtV8jHhvRHfgmjlzVi9Y8JHdu5sikesvuGBybS01NHRTjRLQ3ZGvGfl867ZtVzQ3x4jiRGOIsqFQMBikCRNoxAhqaFBUn9i/f3Q2i4gXY4rFPdu2Edb7mo+Fz1atAz5V6wA3TpyV8jXDDOiqlWuGbpIDI3qplgH5C0QJO98j4PoF4trsW1upqopqavr8Wtt4nOLx0mrFfF5daxsMegKI34D7ka4usd5OXgDqCnBuE7yOuxgMPpoBHFG0MwDxuNjNrwBygdms2KTKJ48XgEsCR9pB/dFdNQNKVGcsZ0Q31gwoC0ANqhXAVTVX1U21lUhcumjRuXPmPLx06daNGw9EIp8/77wpkyaVQuigBH+qT7a3//gPfzj7kUemFot/Wb58044dP7rjjmA8TvH4hXPm/OeAAT88coSIdg0Y8O/nn0+pFM2bR7kcrV9PBw+KIBDFIu3aRYcP04kTVFND6Bawahx0D9VPbt581qFD3ywWiei6Awee3Lz5PZdc8tz69ZmDB+8oFi2iTx879uDatZ8aPx6q25qaXtq6NWxZM885JxiNis8lHyN9MW4wmMhkbv/iF3c2NCQs6+zBgwOohqwaJSDUEq+1zWbpwIHJDQ2Hksllzc1Jx9kTi82ZNo0WLKCRI7u1ilOqp06a9ONhw769ZUvGcdbU1Pzw0ktLKgzHwmer1gGlVXup1gFunDgruU2in2EAdNXyuikGZJMADKplQP7gGCiTv0AMgNcXiGuzZ5N9+pqBfZ6RiFiDnMuVNtBiihX9DORm0QEkYqNTyVtCIXEzbgbQS8XrALj8HgFePc2VkctnQKkw36GbAf68XCCbMQMYMkbNAXDFzACLYsBLtQLoqrmqXqojkUA+X1dT84lLLmmcN4/i8epwWAQLkqvqT/WBAwcKO3d+oFhMElFX1+eeeOKJ5567eNw4Cgbrqqp+9fWvP7hsGRH95/nn19XUiFu82lqaPJlGjqSNG2nvXvEnGhtp82ayLNqxg4YMoWHDSjeenI1HU10ZiRy1LBsbHgOBykiEcrl0JHI4ECgWixbRccuqqqhAnQvt7Z+47bbW7ds7LWvohAm/+PKXQyhKaTyaaiufz4TDM0aOpM5OkdFWUY0SoBoZUvfvp5deoo6OdHPzkvr6rdu3N+dyMxYtGnLBBVRTI46gpnpgMvnTL37x/meeOdbZ+fVZs84ZNAgpmHo4Fv5atVMs7j9y5OmXXqqJxy++6KKQ3qq9VOsAl4+zktskVoIZAF01In8oAJtkwEu1AihfIFjd5NqqFcDrC8TrGwYXnj59zcBaIDyVXzG/io1jXoD5df9vxPmmYwrgVRS6rjLgVaAfQCnQq2Iy0NsP/vd/o2QyGAjUVFaWIuO+LtX90ummqqodRIOJthL1KxRWbtx48TnnkONYRBNHj5547rndNrXwup0hQ6i2lvbvp82bxVAPsh/u30+7dlEySTNmUP/+FImICRs31ZfOnv0/s2Zdtm0bOc7giRMvnT2bHGfR7NnjZ89esnVr3Lajo0dfu2AB4Psef7zt+ef/UCjYRNOOHXt68eLFc+a8kapt28nl8kePOlu2RA4fDtg2RSIWUVUmM3fOHJo+ncaPF9872huLxeKL69c/uWpVVTL5vssv7z9okMVxXPRW3WNl3Fr1oWPHbvzsZ8ccO7bPsv74xBO/+OIXYxxfrrfN3nA69KoRys3M69ljTWRA+eBuqt1f9/oCMX/D9OlrBufp4yxa2aw6NoXIXK6AnIYPWbSg1Qy87jx96C1iGbVrmi0GvBKWmYG/JU8fNh7LafjQpTUDyniIQbUCuKpWMpq93jx9flQPTqffcdll12/ePKilpcmy7HT64gsv7IXqUaOoro727KHt28WkGlZPZrO0ejXFYjRoEI0cSbEYVVbqqkOW9dvbb1/x6qvU2Vm/YEGovZ2IQsnkb2+//YVNm/K2Pevss8PJJFQfa20dYttBogDRSNtugByY5GOUy7mrzmZLueF01RUVVCg4hw/vWbZs++OPW/n8wMGDJ9TVBXBajR1LY8YQLs+897i76s1btnzzG99YePLkfsv69ObNP7vttlq2pLdqrzx9RtX3rVix+NixLxeLBaJ3vPrqun375g0d+vrz9HHj5BFXDPWYAV01/6+XagByTQyAn5SIfvL0mZt9OU+f6HAhshhmwMJham8X3XN5DjwUcgf4jQzg1tUMIO8Qb8tECGWOoWQAcNQxQwUgGhVv1AG8DoBj+ZkB3I/IBQYC4lczIE9xA4AotD8DwKLkoNCuqnVAUc1V9VINwKBaBnpSHYhE3jF3bvTzn3/yxRedfH7O1Kmzxoyhpia/qjE0PGwYVVZSLkfbttGRI6Uw2p2ddPIk7dxJFRVUVUWjRlEyKVrCKQ9Ry1o4cSK1t4s2TESBQCibPX/cOCEKf6u9/bJZsz5UW/ut48c7LevYwIHzx46ltjbK5UrHCMZ01Qxg3lVW3dxMJ09SczPt3t146NCyRx+d2dgYIXpx795MPD7sggvorLNo9Gjq7CyVgLGv7qofeeqphSdPfta2baJ379ixacOGhchM7tWq5WPhUzWvEce3Laokt2rcQRuaPQPctLofCzEaYQB01cocuK4aANfEDMit2kO1O+BTNQM8ftV3rxnlR/nxuveDBgJX1NdfMneuHYlE8vkA5k56+4jFaMAASqcpEqENG2jrVnHeYrKtsZEaG+nwYSoUaOBAqq2lurrS8kd/j7ohQ+7+7nf/tGJFVTi8dOHCzN8S09BxqLmZdu6kV16htjas2T9y+HB1e/t4IiLakM//pqLiK/Pni9uCnsKgDqiu3mJZNlGe6FAkUsk5yt64xw2LFv3TQw9tPnLktUDg3IkTzzv77HLTPaMf5fwZ5fwZPefPcAF01f+I/BlWLhcB0NHRO9Wu+TPmzqUZM+jIEdq6lRoaSiGDMGzV1ERHj9LWrVRdTf370+DBon1GoyL5mkf+DKuycsTZZ39+8mSv/BmlpA4KkE6LW2AsJN21i3bvdk6c2N/UtHv79lAkcs748f2i0X4DBjyVSGzJ50NE/xuPf+z886m6mkIhU/6MU6qvufzyD65ceeWWLZs6OoZHo681N58TiSQk1bbjNORyRFSVTAZ5c3VvVNcmEr+/666n16ypSSQuvvjiUHt7j6lKDPkz3NNjyKlK/qH5Mwyq3YFy/oxeP8r5M86E/BkugK76H5g/o/dJHUz5MwYNoupqamyk1lbat4+OHy9tjkEqusOH6cABWr9eZB4dMICIKJmkAQNETFas+0TsBx/5M0pJHTDMhS+jkyfJskQXp7FR5HpznKMnTy576qkJnZ05ovt2737H9dfXXnDB2YMH/2T16kChcMGkSW8bP76UoMI1Z4OkOlUsfvumm2758Y/f++KLk3btevRrXyt+5jPvvPZavLFo27/+3e9eWreOiCZNmfLRd7wjGIv1VrVVLA5LJN5/4YXi0xnSY3g1eyl/hnt6DE5V8o/On2FQXc6f8cb1M1KpUrLcdFpk61X6Gem0O4BRZryOuwBsYjAD+J7i/aKWRem0uD0xA0qk4mCQUikxlKEAXCCAeFzEmTEDmPJCxwhAOl1a5W0AlG5EICBEATMArve2rqoVQFfNVfVSDcCgWgb8q1YAn6p1QFGdTFI8TqNHi3H5bdvo2DE6ckQsysBUGeJAHD0qokrs3y++QDlzO0axqqoomxWx3xFoCHM57e3U2CjecvSoiPGMAWtcUBEAgyMphULkONsPHx7c2TmZyCG6t6NjzZAhl86bt2j69EmLFnWFQv1TqSCaq6IaM72aastx2k6e7Nfa+qlicQBRRXv7C6+88s4PfhCq1+7Z86vf/Oanra1EdPOmTdPOO2/W9OlvvGpsvzA0ewa4ceKsVPoZBkA+HeReggJAlNKN4FZtAHyodgd8tmoup5wPnLJZam0tXYqDQWptFb1RuZ8RCLgDjlNKltvaSrYtbn7NQCBA+XzpLgDhTnm3pwHghdLBoADC4dLNtQxwgQCwBpxXx3sBmFLmSTw5yZcZkG+XAEAU3554ASxKBlxVK4CumqvqpRqAQbUM+FetAD5VuwKyasRuymbFoNO559Ls2XToEB08SPv20ZEjYj0CZkFxi40vEaxQwjdUOCx2kKEcvIUBvI4RCXxN6EA+Lw46/iuT6Tr33P/buHFeoVAgejwavSGdpra2QGfnWeEwRaMilLquGve2bqrTRA3xeAtRLdFBy0pXVlJrK964+sUX61tbZzkOEc1va1u9fv2ssWPfLNWGZs8AN06clXI/wwzw6QAAw7xyPwMAROE4AuCamAF/ql0An62agXI+cDGczQEdOQAkh37EOh8DIL+OJ4YFDEAwKH6QC8SvZgB3iMjlwqUpGAClQNSKl8p5AYiX6VUxA4A64+sGv+of3BVgUQx4qVaA00e1AvhUrQOKakRjVf5idTUNGEAzZ1JTk4haePgw2TadPCnOduwowjIebDQrFkthrnGniZ4KYpcqcbAZCAYpGnWqqjo6Og7n85Ha2iFnnx0YOpRisQvy+Qez2Q9t2NAWDt9w/vkzJkygcFgMwyrHQv5EWG3lpnr48OHXXXXVl4rFfk1Nhbq6Wy+5hLF5M2f+NpN5qqmJiJZXVv5o6lQKh+1Q6NDJk+2HDw8aPjwZDlsYmn/DVbsCXq0a7dMA6K0a3RG9VbNJDlurFOgK+FPtAvhs1Qyg79KnrxlyHHkiUw4MA0BSkHr+ZjQAXnH2+XT1n1FDr5jrzz3CHBzfUDEDICeQ8PpbrkBvVSvlnCaqZaBXsOsfVb7KXVXH42Lwqq6OEgk6eFDc5J48KaKc4Z4Ry5rx/cIjWvzE9RKBK1AgviDicYxgdFZXf+fuu4/u3dsRi03t6Lh6wIBhyWQoHP7m5z63ffPmikjk7KlTg83NwiTq6ZXRBBcqt08UCAavXrhwWl3dsZaWuhEj+mPoMhAgoinjxn3uYx97YPVqIvrojBlTxo61A4E/P//8X559NnXiRNXkyTdde+2Ayso3S7UOGLLC9AgYzlOlVROZPpEr4E+1C9Crhspl9ulrBsLjYD89nQpJhj4prucYm+LXFYBDg+B1JGDBzZoBwKklxxjgYs0ASsZaEV57LpfPABeoRFkwA7g5lQtkzAzgZhYDRwAUYwYAohjwUq0AumrljbpJ5ROZAf+qFcCnah3IZrva2x9atSoXCCyZPLkqmSyFaXFVjdsdbNDDM5WiqirxnYKBu0iEsEyoqYkiERH+gXOKVFVRc7NYVNPWJmbOEf8uEqFsdulLLx1+9NEvZLPtRFevXfvYc8/d+c//PH748GQkMq2uTlSeVeO2Vz4Wimp0btxUB4hG1tSMHDBAzLueUh2IRq9fuHBxfT0RVUUigXz+taNH77733m9s2ZJxnB+/+upDmcyHLr/8dahWQ4O4qtYBfp1DgyjHwgvQWzVGllxbNUwCcG3VOuBTtQ74bNUAstnSQvC+e82IxSiTIV4Vnsl0m1blOfBMxh1IpUqBuzHxhc6sGeBET5iswxI9TJWbAWUlXDhMlZVi5FoBuEAArqsSdQATp1iiByCdFncWZoCn8oJBAUAUps4MgD7F7aVaAXTVXFUv1QAMqmXAv2oF8KlaA9pCoUs/97n0zp0Jx/npsGEP3X13ZSZjUo1czQbVANraqKqKGhtdTOJ1GGtq0oF1O3fOyOXGEDlEC3K59s2b/7RixfhJk7qpdhxKJkVEW+VYyKqRXLr3qgOWVSMBh48eHdjYONVxLKLpudwr+/ZRZWWvm73Sqnlu2avZM8CNE2el67FwBfgYAdDnwHWTPMXtpVoGfKrWAZ+tGgA6uH39mtHZSU1NVCiICMaWRc3NlM2qc+BE7kCxWNq729wsdk4ifJABkNd3AnAcsaDNDOgr4YJBUTEF4AIBIMCcvCrRFcCdBe+AbWkh2xYzYGZAnqAGAFG4GzIALIoBL9UKoKvmqnqpBmBQLQP+VSuAT9Ua8NS6dfaOHX8qFAJEH9q7974HH/zQNdeYVFuWWLXspVoBdJP8RhjTgIVTptyVSAxra2smOkL0Nsc5cewYNTeXVKOEQkFMzCrHQlatLAB9vapHJBKNAwfee+TIQMd5Jpm8eNw4am7udbNXWjVu2A3NXgZQMZyVumoDoKhW5sB1kwAMqmXAp2od8Nmqec0uz6v33WtGJEKJBCWTYrFHMtktKDTuAkIhTyCRELcPALCcUQ6C5ArgewqXfQCJRCnisQFQVsLh7gZfowogF5jLUTxOoVDPALoRvPcHt1ccy90AcOQcLKVlUcAMgBLjyKBaAVxV8zJHL9VYg2tQzYB/1QrgU7UOIAYUT7NVVJTy27ipznV1rdi0CfGmoiAV1VgAajaJYwRjGlA/b97uT33qZw88sGHHjvm2vTKTeff8+ZRIdFPd1SXCSckBqXTVp+JNFW177ZYtxzo7p9fVDRw40Oql6rOqqm7++Mf/vHz5+oMHZ82Zs3jBglK6JP+qlVaNpbSGZs8AN06cla6qXQFdtRwLnQHZJACDahlwU+3Z7GXAZ6vmcjjEet+9ZmBNeiAgrp+4tGILD18zslkKh90BfiMAyxI3v2YAgdU4Ggw2znB0KQOA5oi7AAAVFQJTAC6QAd7SZQAQ9U8uMBgs3VkYALR7nh5AmBpgZoBFMeClWgF01VxVL9WnauK0t+85fPih9esHplJXXXBBSAN6p1oH/KjWgCVTp945cuTbdu1KEjUPHfrz+nrq6PBSXWhvv/qWWzp27CDHiZ977gO33RbC3KasGl8ZBtV8jGBMAyKRyAcWLXrnokWPPvfclp07F82bN3vcuG6tAiUgrSmyjcrHQm7VnZ1kWcWurv/3wx8+uHTpxK6uOwYNuuuOO8ZWVvZKtVUszq6rmz55sn3iRLiyMoDzt7fNXmnV+FI2NHsGuHHyWamo9gJ01fI1gwHZJACDahnQVJNrq9YB/60aQDm3q7jT9FqgwisHzIuFlGUVXktHDOsofC7d4SUTXuUz4FoglleaAdcKM+YFeD29jBmeZtXKco7XpXrL3r2f/vKXJxw//kQg8MCyZb/42teSf4tq16cf1d2BiljsiZ/+9KGVK3OBwJIpU+LYI+bxiR5Zvbp506anCwUiWvDSS4+sXn3FvHlqHeQ1geZj5HEorWAwGAqlE4nr3vY2uuiiUjfC9eB6nT78umVtO3Dg5bVr17a0RIi+vWfPX5588l+uvba3qq1gMBKNilkxzG/3ttkrFZZ/MANejZNV+/+iwPiV4ayRAVfVMqCp7qHmStvosVXLKyfL+zO6LUzmhcwwhR+wKcEVwN4Ofh3LUZAmwQDwwhUMjskVMAOY1MI5AEApnwG5QDx5mbkBwEobdKK5wowZAAzLYnkJbxuWy/cCWBQDXqoV4G9Q/eCKFUuOH/+ibRdt+7pt29Zu337hhAmKaicUOnDixI7du4cNHDhyxIiArMJ8LHyq1oFIJByLXbVwYSkHtbfq1q6ufo6DZY81jtOK9RqKasxzviGqi0Xxq5dqV0D+4MUiWVaOKFksBoksohRRYzbbu1b9xqnu1qq9VOuAV6tWVOuArhp9F4Nq3n7hpVoGNNWmbxgZ8KmagVCoz18zurqos1PESEAHEF0/9GfxpYO8Xa4AvxEAYjmgkRkAXIfwOgCOAGoGMCKJniMAPHFEZYALBIDlrUgKZgAw9SIXGAqJX82APMUNAKJwVhgAFsWAl2oF0FVzVb1UAwiHw0Qnbdshsol2NzZu2LjxgpEjLctiwOnoWPXqq9+7556a/fsP1NR84Jprrq6vt2Ixd9XKsfCpWgcU1fgm8lC9eNKknw8ZctOBA0R0YtiwxZMmuRwLbMIwqOZjBGNeAEzyeIis2gwordqyxtTUpEePfvehQ+Nse2V19dfnzu1dq35zVDvF4qETJ5avWlWdSi288MKQ4Vhw48RZqav2AnTVyhy4bpIBL9UyoKnWm7074FM1A+WxqfKjDz4i0eiviTYRbSc6ls2uWLfuXQsW9JcihHcVCn9+8smr1627wbbXHz36aPr71QAAIABJREFUg1Rq/rnn9u/X7/T5CLWZzNKf/vSe556jbPaO665LnAYRHfw8krHYz2+55f45c3aeOPHD8847Z8KE0lK3f9yjqbX1qs9+tv+BA3sCgTkLF/7y858Plk+S0/jxj75mRKOUTFIqJS6wqVS3BSTYnxEOewK8sQMA1iTIi3lcAazVwR03AA6SaAaUVQ2BACWT4sqvAFwgAARAlddFuAJYFoUhSwAcJV4DWgKBB5cte3nDhlgmc9Ull0w+5xwLQxMAIArl8wISHVDW6hhUK4Crao5P56XacSiVamht/SDReUQZom8TFTo7s+EwJZMM2Nlssa2tv+MQUaXjJDo6BOCqWjkWPlXrgKIaa3X0Y3HKQyKV+sR730vt7aVtFopqLOYxq8YxgjEvAMEc5WVRsmoDILdq7D2ORkOBwHWXX06pFLW2usfFM7TqN0f1/zz44KUHDnylWCwUi1du2rR63765Q4a4HwtunDgrXVW7Arpq7K4wqAZgUC0DbqqVZu8O+FQNAKdbX79m5HJi/wT+DYWorU3sz5T3ZwSD7gC/EQBWBCFguAFAPHBemIEo08DMAA4eeo4AIpFSDEQZ4AIBIHhysdgDgMFfzq+H2IjANOCpdesev/POa9vaDlnW7Tt2/OhLXxqAr2kAEIXevRIUWgZYlByszVW1AuiquapeqgEEAgunTLnjr38d1ty8gWhzOPzusWP74W+dAsLZ7Nnjx//v6tXH2ttfjEb7MeCqWjkWPlXrgKIagw/6sZDHQwB4qVaA7iaLnZ0bduxoPnJkYl1dTTBouarGGx1HjIfoqs2A3KoxHqIdi9616jdHdVdbWxgLYogitl1sbS0da+VYcOPEWamr9gL4GAHAvgp5bEo3iX8NqmXAp2od8KmagXKMwnLOpdedc2nNxo0XtbVd5ji247x44MCe5uYBAweeETmXZs+de9Ntt93/2GN7jhz5f0uWXL1kSRxbRk4BAaJ3XnddZtiwdS+8MHHChMsWLYrHYn6z0/wtOZf8JAJyzfPjqloCGpualj7/fDQUuqy+PhyLFS3rtrvueuqZZwZls8W6up/ceeeAdNpdtZLnR1dtAHwmAvLfqt8c1VdfdtkHHn30yOHD+wOB1MSJU6dPL+2aLudcKudcUh/lnEuvN+fSsCFDNofDR/P5FqJD6XT/SIRaWs6InEuRjo63jRv3thkzBBAOd6sqkdXSkolE3jlr1junThURIFpa/n45l8yJgPQ8P16qTwHNHR1XfOhDgw4caLesO+vqHvnRj7YePPjsE088duhQhOjLJ0/+4b77PnPppZ5JmeQ8P4rqHgE/iYD+gemtCgXK5YYnEnf/+MdLn312QSZzBRL5cc6ocs6lcs4l7e+HKBoVQdlwmY1EREQXXIoxaO4FRKOiIfLrOGHMAK9jw+v5fLfyDQBvwsRdgLwSTgG4QHnhIN9weQGoORYdcoHYBaoBVyxZcsf27V/bufNkPH7jpZeOqKsrDYN2dXX7RMgPilDbCsCiGPBSrQCuqlFVg2osUDGoZsC/agXwqVoHFNUYhdePBXvAaW9QfQq47+mnRx448Oti0SZasGfPU5s2pdLpAYVChChAdJbjNLW29qAaC6IMql0BuWK8IPX0U20ViyOqqz/2jneIjgWUuh4L+RNxL8HrWMiA3qo5grqXagAG1TLgU7UO+FTN5ZTX2pYfr/sxsKbmax/96N6WljTR8KFDA6fBZp/yw+dj4siRxREjvtTQMMi2n66qunXevLKT8qO8bsrfA33PcFj0BpASGRvrcRuLJGh4XQeU1/Ev7jsMAGY49Nf5VwOA13kZNZ6MMcC/AkCwd7zLAPDn1f+uBli5XCYSydTVUWurmJFDzV2N2bbI/KUALIoBL9UKcPqoVgCfqnVAUY3IUXrF2AM2lBhUnwJuWLTo7t/85p/27WuzrPCoUUumTInGYr++9db71qw5un//N+fMmXDOOSKVm5dq3qPgpdoVkDEM4JxZqnWgJ9WegN6qeR7bSzUAg2oZ8K9aAXyqZgB9l/IceHkO/HXMgbtPzJ4Jc+Ceqk+niVk/c+BOPN7R1dXS1ZUIhVLxuOUxBx6vqvrrf/7n0jVreA6cgsF0NPrB970Pi3SdysqGtraC41QlEmFslu5Lc+Ceqstz4OU58PIc+Bs4B+4+MXsmzIF7qj6dJmZ7nAN3iLbv3n3P73/f+tprgQEDrl+yZNacOZbHJHkV0fXz5omPjDqfmne1bfu+pUufWro0VCiMmTTpM9dcE4xE+tQcuKfq8hx4eQ7cvZ+RSpU2vKTT3VLHcD8jnXYHkklxFwAA+2Xkm19XAN9TuK8BgM1NRD0Ayo6bYJBSKTFNqgBcIIB4XMSZMQPYsoeOEYB0WogyA0o3IhAQooAZAL0b4aVaAXTVXFUv1QAMqmXAv2oF8KlaBxTV2EfmrbpQLN7/pz+lHnro3fn8ulDoHqKz58ypSqXUm1+z6mLx1d27f/xf//Wt116LEX1j8+aJEydeVF8vA6JDpnQjWLUBkFUjYPiZpVoHuHHirHRV7QrIp4PcS1AA2SR3I7xUy4BP1TrgUzWXU97TR9msSEiCS3EwSK2tojcq9zMCAXfAcUobXlpbybbFza8ZwIA+3wVgkxHKNwNYQYG7AADhcOnmWga4QADForjhMgOOU7rhYgD/mgH5dgkARPHtiRfAomTAVbUC6Kq5ql6qARhUy4B/1QrgU7UrIKvG8hhv1YV8/vimTdfm8+OIkoXCi7t3Nx4+XJVMdrv5RQleJoNBam19ZcuWc48fr3ccIprf3v7kihUXTZwoAyLuEL6hFNVmQFaNe9szS7UOcOPEWamr9gL4dACAYV65n6GbBGBQLQM+VeuAT9UMnAZ7+v7xGcnLj/LjTHyEg8GB48c/Ho2uJ3okFHJGjKjme9LePCaNHLm1f//HLGu5ZT2XTF5y3nllt+VHed2U9yMSoXhcLMpGxy2fV/P0BYOeQDxeyueFvjBuMcwAxkO484ueL+7OzABGG3FvAiAeF1d+BZALzGbFBB0P7HoBGHriSDuoP/rUZgBhczDUAwCigBkAJcaRQbUCuKrmqnqpxmSmQTUD/lUrgJtqO5/fuX//9m3bxlZXjz7nnIDrsVBU46B7qw5a1jVXXvm/XV337NgRGzz4A0uWVNbWio4IaoUBE4PqRILy+TFjx37x5psfefhhK5+/YsaM+vPOKwXxxhsRSUkOJ8VVNQOyakR+ffNV+2r2PlXrADdOnJW6ai9APh2QM1HOueSqGoBBtQz4VK0DPlVzOQDKa20pEhGdMl6IhqaPpaW8WE0HwuFSbw6LDTCAYwYwcorXAXD5PQI82siVkctnQKkw+r+86NAL4M/LBbIZM4Bw06g5AK6YGWBRDHipVgBdNVfVSzUAg2oF8KlaATTVTi73xIoV37v77lEnT/6oX7+bP/nJxZMnW7iTkI+FohqrML1VW5ZV16/f5665piUUSuTzqXjcQgVYlGWJErxM5nKUywWI3j5nztzBgwvhcFU8HsS0qgSU1pvqqs2AohoTe2+mar/N3qdqHeDycVbqqr0A5RPhex9DeV6qARhUy4B/1QrgUzUD5bW2Io8QnsqvyM2ApNNegPl1/2+0bXdMAbyKwjClDHgV6AdQCvSqmAz09oP//d/45qnuqTKNLS0PP/nkV7Ztm+84y0+c+OPjj8+sq6vmRPHyX+yVaiLLcRIVFQmOa/v6HBJZRNWIN8W3Sm/IMVJU6z+80ar9Nnufqv2f7z1+k+iv93j69FgTGfCpWn/dp2oF6NPXjHCYYjGKxcS1NBajbFYdm8KqZFcgFhN3MQAw6iIPmLgCGA+BfQCxmOjSmgH0FpGCEQAqD0wG5ALxREBZM4ACcQsMIBYTdxZmAF1sJIwEAFHADIAyYGJQrQCuqrmqXqqBGVQz4F+1AmiqC8Wilc2mHIeIUo5jdXQUQiGKxdRjoaiGIoNqqDCoVgBXk/zGXM4TwKeWh57kqhoAWTUmUd9k1X6bvU/VOiA3Th4nVFS7Arpq/l8v1QAMqmXAp2od8KmayymPTVE+L1ZVY9VEOEzt7aL/Lq+bCoXcAX4jA1jMYwawdogjFWNlCy8PNwA46ljVACAaFW/UAbwOgPcxmAHcj8gFBgLiVzMgL2oCAFFofwaARclBoV1V64CimqvqpRqAQbUM9Eq1DGiqK2Ox0ePH/2jt2vnZ7PKKiqkTJ1biDynHQlGN2zqDavSADaoVQDd56o3FQGDlqlVttj177NgM8mx3B8RaHV21GZBVY63Om6zab7P3qVoHuGnhrNRVewEsCgB2bsnrpnSTAAyqZcCnah3wqZoBHr/qu9eMWIyqqkq7KJCsTd+fkcm4A6mU2GwJIJkUIcDMAO5tccUGUFlZSpBiAORdmgAymdL+UhngAgEkEmIs0gzgtgI5gQGk02Jk0wzwMvNgUACc9s4M6JsGvFQrgK6aq+qlGoBBtQz4V60AmupIZeVH3ve+J88+e/nmzVdPmLBo4cIIkcuxUFRj3tWgOhAQgJdqBdBNVlURUbFY/Ohtt2165pkBtv29kSMfuesubBRngJJJ8V5dtRmQVVdUiHvbN1O132bvU7UOcOPEWamr9gL4GAHQ92foJnn7hZdqGfCpWgd8qgaARQR9/ZrR2UmNjdTVRc3N4pWmJhGeU+5nOI47UCiUMpk0N4ssJRxs1QuQ9x4DsG2x2dIM6Ls0AwFqahLdVRngAgFg/kreEOsKOA5ls+K2AkCxKFZnmwG5G8EAKmYGWBQDXqoVQFfNVfVSDcCgWgb8q1YATbVl2xUdHZdNmnTZhRdSQwN1dLgfC0U19voaVCNVtUG1AugmiaipaeWmTdtfeGFZW1uI6MNbt/7uvvvef9llMkBdXeLeVldtBmTVyubkN0e132bvU7UOcOPEWamr9gL4GAHA7Y7cz9BNcg4rL9Uy4FO1DvhUDaC1laqr+/w1IxSiigqqqBCjjRUVFI2q/Qy87gpUVIjeHABc/OWbX1cA31OY5wBQUSHajRnAXQACogFAIHdgMsAFAsCdBd9weQE8PcAFVlSINYJmALdL6MACgChgBkC5+TWoVgBX1VxVL9VYcmpQzYB/1QrgU7UOKKp5eqC7aicUOtbSsmf37ppMZuTYsQGD6kCgZ9XRaJtt19h2iMgiqiFqgDoJoIoKsZLKVbUBkFVzwPAzR7ULIDdO2aSs2hWQj5HcOBVANgnAoFoGfKrWAZ+q5U/U168ZPAgLv/hBfuIIeQF4L7/Oy07MAKaY8Dr/df7VAHBR+PJ1rZjrz/IiSwPA0wPKJ+WKeQG4skKX8onMgF6Cl2oF0FW7fiLZpOsn8gL8q1YAn6q9PiZXjFtmd2b73r1f/cUvkq+9diCVes+1175rwYKAl2q5bXubnD127M9Hj/7w+vUZ234iFrs1kynm80GE3JArjL3QBtU6oHwiLEg9c1S7APLrBtU6oNcBulxbNf5L9umq2vWImFXrgE/VeBF/unzNoEKBurrEXQZ+kNMaY47UC8CTX+cvMjOA7ym8jle4fDOAFoY/AUApnwGlQD55zAC+0JVPKmMGACahSzfmBciJ083HQgF01cobdZOun8gL8K9aAXyq1gEFw4c99ReL+fyzK1Y8uWLF/kOHFq5c+eFi8RjRZx56qH7MmLpUyl0175YwmszEYvf96Ec//K//+um9907r6PjKd77z4iuvfO+znw0qquV0366qdUD5RPieOu1VmwDldS/VOqC3arzu2qo5TLpZtQz4VK0DPlUzwJtd+u41IxqlZJJSKeECpx8vGcTYVDjsCSSTohwAiYRYkGoGMB7CU1L4X1zAzYASQSwQoGRSdF0VgAsEgAk6OVibK4Apbp7Es+1SlHgzgCWDmP4BwF9kZkBZ32lQrQCuqjk+nZdqx+lBNQP+VSuAT9U6oKjGvKtlEVG+ouLXjz227Je/nN/RsYqov+MEiOJEVZ2dbQbV2JxsVl0oEFE4k+kqFj/V2fl5287n89ds3Lj05ZcnDB8+ZPDgQKEggjnKS2ll1QZAVo0166e96h4Abpw4K11VuwJ8jADwDLYCyCYBGFTLgE/VOuBTNQCcbn39mpHLiTlq/BsKUVtb6XaJ58CDQXeA3wjAccTErBlAPHCOINbWRoFAaarcAHA+mWBQAJFIKQaiDHCBADhOtRnAUA8v3ERsRGBmQJ7iBgBRGBs1ACxKDtbmqloBdNVcVS/VAAyqZcC/agXwqVoHFNWYrWlvJ6KmlpZXV6/+Ynv7NKIM0W+Jmi1rWzCYHD16aDJJra3uqjEQb1DNxygYLHZ0xE/t7ztx6NCvf/CDVHX1nAULPrJoUcBxxLyrrholeAGyasy7nvaqewC4ceKs1FV7AZJqcSyUOXDdJP41qJYBn6p1wKdqBk6DGIXlnEvlnEvlnEs9JAIKETnpdKdlkeMMsqyW8eM3jhw5auzYqy+/vDIe91QtJwLyMnlqGeXixYu/9Oyz+48d22RZ0Wz233ft6tq16/17986dMmXi4MHlnEvlnEvlnEunHuWcS+WcS6d9IqCqVGrx7Nm3bN064cSJzf36femGG94+a5aFmre0eKqWci65m5QSAc0cOvRX3//+Y6tXH960adwzz4xzHIdoUkvLzu3bJ9bVGXIuOc3Nuc7OzubmimCwIp22yjmXyjmX3uLXjPKj/DjtH5ZlXTpnzsixY1/ZsuWm0aPPqauzOHXzG/cnRg8d+ulBg6aPHPnNdeuWtrS0Er1aWzuxrk5bNWLv3L+/2NxcN3BglGj/sWP3LVt2YPPmzNCh77j00vHDhlnlA1Z+vJWvGZEIJRKUTJZmEbG6XI43FQp5AhxpDkAi0W0TgxeAO0R0OQEkEqWIxwZAmaGyLLFPFZgMyAXmchSPUyjUM4Apbu7DYiaZY7kbAI6cg6EnFgXMACgTswbVCuCqmuc/vVSjd29QzYB/1QrgU7UOKKox73pKdaBYHD9o0PgRI4QEHg8xqFYAV5N4I4xVVFChMGvGjBs+//knXnwxEIn8+9vfPnLMGLFYwLapoqKYz3/nN7/ZvGFDKJ8fNnHi//vyl+9btuz4Pfdc2dm5Lhy+q1D4+qc+VZlIuKgOBMS97Wmv2gRw48RZ6araFdBVy7HQGZBUC0Bu1QbAp2od8Kmay+EQ6333msGbgdGPQ3eMl9bxaGM47A7wGwFYlhgwMQOYB+ZoMOgA8oSVAUBzRM8RQEWFwBSAC2SABxYMAKL+yQUGg6WpeAPAX2RYy4QwNcDMAItiwEu1AuiquapeqrkmXqplwL9qHfCjWgcU1fimMKjGN4JBtQLoJvmNMGbbVCgECoUbLrjgHeefH8jlwrW1VlMTBQJiPMS2V6xf/+t7712ZzQaJ3rVjxwNTpx54+eWrOzvriYZ3dX1327aGw4crBwxwUY3xEEl1sa3tmXXrVq1bt6S+fvrYsYGurtNOtQ5w4+SzUlHtBeiq5WsGAxCFKXcAXBMzYFRtAvyrBvBGd3DPwGsG7jSRCwhHWn7idQOAJw4M/4poqQZAft1cvgLwplOv8hlwLRBrrs2Aa4UZ8wK8nl7GDE+zavmgnCaqXZ9+VCuAUg35B9dPhKZrUK0AhmPUvfxAMFiB6VOtYnuOHp2Zz/cjIqIphcKO/fszI0euWbt2SFfX+mAwP2RIJcIWuarm+hDlbfv7v/vdM3/84+yOjn/9y18+8slPXrNwYfB0U60DXo2HP5r/LwpMLRjOGhlQCtQBb9U9AD5VM2BZff6awaG40OfCRnkkT+dwb47jCUSjossJALvtEQTJAMjxKgDI5RsADkSMkuWd/QqgVxgtzAyg5rjX4ArjzsIM4HaJQ4tjpQqXbwBYFANeqhXAVTWqalCNHDUG1Qz4V60APlXrgKIa4wAG1RheMKhWAN2k8om8AIQ2sm2KRmdPnnxnv373nDgRJVqTyXz3wgsj7e13tbV9d8eOrrPOeteVV1bV1AgVimqkojml+nhHx87Nm3/Q3n4O0cNNTc+uX3/JhRem+aidJqp1QC6fewmyai9AV10sihAdHqoFINfEAHir7gHwqZqBUKjPXzOQJ51HkCIR6ugobdPndVPc5VQAr7EpM/CWHJvi5R8AIEruGrsCLEoOCu2qWgF01X1nbIrX6gDwUq0Aukl+I4x5ATweUiyOqq7O1NT8W0NDxLYzlZUThgwJtbZ+/dOfbjh+vLKioqq21ursLB0L7wGTQFdXkQgp33KWZRFZnZ1i7uHMGptSVHsBumpl3ZSmWgBcEzNQHpv6+z3icaqupmSyFEabbzzla0ZlpTuQTIorM4BEQoQAMwMoATsqAaTT4gJuBpSVcBUVpTCTCsAFAojH1UWHrgCmuHFbASCVElHJzIB8SQAAUUQ9AHqwVS/VCqCr5qp6qQZgUC0D/lUrgE/VOqCoxryrQTXmXQ2qFUA3yW+EMS8gkeBYqstWrdq/e/crxWKA6MoDB/66fv3Vs2dXJhKVtbXd4trqqnl9Z0UFEQ1IJqfOn3/t9u1z2trW1dbevmRJcvBg0ek/fVTrADdOnJW6ai9AV61cMzTVAuCamAFv1T0APlUDCIcpkejz14yODmpooHxeRDC2bfdY6MWiO5DPi80TAHI5NUC3KyDvCQBQKIhF0GZAXz1NRA0NRKQCXCCAbFY9eVwBXBKwUB1AV5dY3G0GlEtCe7sQhVUGBkD/nvJSrQC6aq6ql2oABtUy4F+1AvhUrQOKatsuBY13VW1ZAvBSrQC6SX4jjHkBuRx/Tx157bVJhUKEyCI6u1jcu2MHjR0rA92Ohay6+6aBQFfXpy+5ZN7UqVu3bPnSxIljhgyxGhtPO9U6wI0zn7dbWvY3NBQta3A6HY1EdKDb/gxdtXLN0FQLgGtiBrxV9wz4UQ2gtZWqqqimps+vtY3HKR4vrVZE3GB53VQw6AnE46U1eV1dYr2dvADUFeDcJngddzHoFZoBHFG0MwDxuNjNrwBygdms2KTKJ48XgEsCR9pB/TEqagYwLItZMgAQBcwAKAtADaoVwFU1V9VLNTb0GlQz4F+1AvhUrQOKahx0g2rc2xpUK4BuUn6jvhiXAURSsm2qqKg/77zvDxz43cOHKxxnY23tJxYvFqePHDCcqyp/cCRAlVQHisVp06ZNGz1a/Z46fVTrwKnGaVdU/OSee15auzZYLI6eNOmLH/pQsDsgTluDanndlJtqAXBNzIBRtQnwqZrLKed2Ffs8IxGxBjmXK+3qxHZW9DOQekUHwmHxOoBQSNyMmwH0UvE6AC6/R4BXT3Nl5PIZUCrMd+hmgD8vF8hmzACGwlFzAFwxM8CiGPBSrQC6aq6ql2oABtUK4FO1AvhUrQOKatsuZeNxVY3QpAbVCqCbPPXGQkfHI88809zVdfH06bXJpApAlG2TZQ3LZP7n3/7tgZUrW1tbv11fP/ass6ipSQa6HQtFNQb9zyDVOnCq/A27dv3st7/9Y1tbyHE+++qrMyZOXDRvXrcK4LTVVAsA3/uISuKhWgDKV5MX4F+1AvhUzQAuPH36moFJXTyVX7H2HxvHvADz6/7fiITDOqYAXkWh6yoDXgX6AZQCvSomA7394H//N755qnusjM9j0VvVPbZefw47stn33npr24svDnCcXw0a9Nef/CRTVeUFW45zzogR50ycWEoeZyhc+eD6D6e5au+2tG3Pnpnt7ec6jkU0o7Nzzdati+rre/dF0ePp02NNZMCnav11n6oVoE9fM8JhisUoFhPX0lhMZNGSx6YQmcsViMXEXQwAjLrIAyauAMZDYB9ALCa6tGYAvUUsowaAygOTAblAPLFAyAygQAymAYjFxJ2FGeDdsCgZoQzRpTUDyniIQbUCuKrmqnqpBmZQzYB/1QrgU7UOKKqhyKAaKgyqFcDVZDa7asuW1m3b/looBIhuOnTo3uef/8Q73ykD4lPLQ09yVQ2A/MGxYufMUq0DpxrntMmTb6+u/vPJk1Gi1en07bNnK4A4bburLjVOjCzJ28h1kwAMqmXAp2od8KmayymPTVE+LyKLYQYsHKb2dtF/l+fAQyF3gN/IACZmzQDyDvHSN4RQ5hBpBgBHHSO/AKJR8UYdwOsAOJafGcD9iFxgICB+NQPyFDcAiEL7MwAsSg4K7apaBxTVXFUv1QAMqmWgV6plwKdqHVBU47bOoBo9YINqBdBN4vXOzm43j5jLlQEiMe+qqzYDsmrMu55ZqnXgVNMa07//7Tfd9OyqVU6x+JFp06YPG0bt7TIgTltFNTdOzpukA2wSgEG1DPhUrQM+VTPA41d995pRfpQffftRP2FC5fjxC1atOstxjgwZcseSJWUnPT4ClnXpnDmL5syhYDBcLAYwK1Z+9IlrRjl/Rjl/xpmV1MErPQa9zvwZUaL//dWvHnn44eZ8/uJZsxJYhu+V1KGcP+NUegwrEIiW82f0xWtGOX9GOX/GmZXUwSs9Br3+/Bkhy7pi6lSxu6KlxZTUQcuf0QNQzp9Rzp/xFuxnpFKlZLnptMjWq/Qz0ml3IJkUdwEAkGtXvvl1BfA9xftFLYvSaXF7YgaUSMXBIKVSYghSAbhAAPE4RSLdYh27ApjyQscIQDotRJkBpRsRCAhRwAyAfvPrpVoBdNVcVS/VAAyqZcC/agXwqVoHFNXYE2BQjXtbg2oFcDXJb3TtiABAh0zpRrBqAyCrxkzvmaVaB7hx4qx0Ve0K6KqVfoZukrsRXqplwKdqHfCpmssp5wOnbJZaW0uX4mCQWltFb1TuZwQC7oDjlJLltraSbYubXzMQCIg4V7gLQP5h3u1pAHihdDAogHC4dHMtA1wgAKwBx78GAFPKPIkHgDdXGwD5dgkARPHtiRfAomTAVbUC6Kq5ql6qARhUy4B/1QrgU7UrIKtGTCGDaoQMMqhWAN0kvxHGvADbFve2umozIKvGve2ZpVoHuHHirNRVewG6aqWfoZsEYFAtAz5V64BP1QyU84GL4exIRAR1wQ8MMAKtAAAgAElEQVS4N7Es0c+wbRMgv44nYq8aAETMVQrEr2YAPUfkcuHSFAyAUiBqxUvlvADbNlXMAKDOti3GcOU3mgEWxYCXagU4fVQrgE/VOqCoLhZ7UA0nBtUK8LeoxiirQbUrIH8iLKY6s1TrgE/VOqCrRnfEoBqAQbUM+FStAz5VM4C+S5++Zshx5IlMiRkMAElB6vmb0QB4xdnHNcwA6AHx9Yq5/twjzMHxDRUzAHLKBK+/5Qr0VrVSzmmiWgZ6Bbv+Ua5Pr1KJuGJvoGpgBtU6oKg2NJ7TU7UO+FRN1HM6Ga9C2KTXJ3IFfKrWgV7Z4zL79DWjUKBsVuynp1MhydAnxfUcY1P8ugJwaBC8jpRbGDc0ADi15BgDXKwZQMlYCgKAd/YrABeoBFEwAwjFIRfImBkoFksDRwAUYwYAohjwUq0AumrljbpJ5ROZAf+qFcCnah1QVHPb81KN2x2Dah34W1TjrtagWgcU1dgvcgap1gF+nUODeKlWAF01RpYMqgEYVMuAT9U64FM1gGxWjIb16WtGLEaZDCWT4tdMptu0Ks+BZzLuQCpVCtyNiS90Zs0ABsTQ4wOAdWw9AspKuHCYKivF3JoCcIEAXBcd6gCmuLFED0A6Le4szABP5QWDAoAoTJ0ZAH3e1Uu1AuiquapeqgEYVMuAf9UK4FO1DiiqecLTSzVyNRtUK4CrSbwRxryAZFIsqXJVbQBk1UgufWap1gFunDgrXVW7ArpqZQ5cN8lT3F6qZcCnah3wqRpAIFBKnN53rxmdndTURIWCiGBsWdTcTNmsOgdO5A4Ui2KKGwB2TjpOD4C8vhOA44gFbWZAXwkXDIqKKQAXCKCrS1106ArgzoJ3wLa0kG2LGTAzIE9QA4Ao3A0ZABbFgJdqBdBVc1W9VAMwqJYB/6oVwKdqHVBU4y7SoNqyBOClWgF0k/xGouzx43saGoJEo/v3D0Qi3YBCQcy76qrNgKxaWQB6Rqh2BVAxnJW6agNwSrU4FsocuG4SgEG1DPhUrQM+VfOaXZ5X77vXjEiEEglKJsVij2SyW1Bo3AWEQp5AIiFuHwAkEqLTZwbwPYXLPoBEohTx2AAoK+Fwd4OvUQWQC8zlKB4XSdDMALoRvPcHt1ccy90AcOQcLKVlUcAMgBIEyaBaAVxV8zJHL9VYg2tQzYB/1QrgU7UOKKqxvtOgGus7DaoVwNVkVxcRFWOxb95zz77NmwvB4IRp0/7l4x8PYj8XgERCrARxVW0A5A+OMckzS7UOcOPEWemq2hXgYwRAiYXuqhqAQbUM+FStAz5VczkcYr3vXjO6urrldsWlFVt4+JqRzZZSNiqAV25XM/CWzO0qTw8gTI2SWtIVYFEMeKlWAF1138ntykPSALxUK4Bu8tQbn1izZu2f/vS7fL5INGfbtvpp086fNq0EcD5RXbUZ8Jlw9LRVrQN66lZFtRfAxwgAFu/yNcNVNQCDahko53b9e6+b8lrOwSsHzCtYlGUVXktHDOsofK4n4SUTXuUz4Fqg4/QMuFaYMS/A62lY82NeC+RzsdDpoNr16Ue1AijVkH9w/UTykj/XT6QA3sdo2/79kwsFjMTPzOf3HD16vp9Dqa/JMR9Krs+ZoloHvBoPfzT/XxQYvzKcNTLgqloGfKrWAZ+q5ZWT5X3g3eJNYZemkts1Gi3tolQATiQOALFclHzgOoAyMUMFgHd7mgFltFGeoVIALpAnA/XEyDogT3ED4HhZZoATe2HoCWFqcHdmBpR8ogbVCqCr5qp6qQZgUC0D/lUrgE/VOqCoxniIQTXGQwyqFcDVpG0T0cILL/zc3Xf/oaEhR7S1f/+vn3cepdMlIJEQuwFcVRsAWXUkIsZDziDVOsCNE2elq2pXQI5ugEYrz2e4quZ0316qZcCnah3wqZpOxa0qx5uibFaEl+Gps5YWl3VTHC5GATgYFEeDwYCJGdDDSXGYGjOgjDbK0WAUgAtUAu+YATmcFAM8dWYA5NAgACAKDwOgr9XxUq0AumquqpdqAAbVMuBftVcQpNdxLGTVchAkV9Uc48hLtQLoJk+98dxBg2695ZZnVq8OhUJ3zZ8/trpa7PgFwDGOdNVmQFatTMyeEap1gBsnzkpdtRfAxwiAvm5KNwnAoFoGfKom73hTPo9FeR+4aA1dXWIgDz9g3TSyXyDWhReAJ7/OGWHNAPqAeB2vcPlmAHcc+BMAlPIZUArkpJ5mAJtmlU8qYwYAJqFLN+YFsKgej4UC6KqVN+omXT+RF+BftQL4VK0DCsZzA16qOZGql2oF8FYdKBQWTJ26YPbsUqPFgZZN8n4CL9U6oHwi7CM7s1QrgPK64VgogN6q8bprq+YFUWbVMuBTtQ74VM0AJ8rtu9eMaJSSSUqlhItUSqxq4LTGWPDuBfDGDgBYkyAv5nEFcG+LwwOAgySaAeUuIBCgZFLcaygAFwggHqdwuNsNlyuAoScMWQLgUTszgKk8DPUAgCiUbwCUxTwG1Qrgqprj03mpdpweVDPgX7UC+FStA4pqjIcYVGM8RFJtJxLL169/YtmyYqFQP2vWpfPmBbA2zGASxwjGvAAEc5SXRcmqDYCsGnuPzyzVOsCNE2el67FwBXTV6CUYVAMwqJYBn6p1wKdqADjd+vo1I5cTY0f4NxSitrbS7RLvzwgG3QF+IwCsCJJvfl0BjM9wz7GtjQIBgZkBHDyMNgKIREpjXzLABQLgONVmAKF1OOkbxsSAmQF5+wUAiEKX1gCwKDlYm6tqBdBVc1W9VAMwqJYB/6oVwKdqHVBUY22MQbVlCeCU6h179/7zV7/6+ZMnI45z51NPDbn99imTJplU8zGCMS/AccR4iK7aDMiqMR5yZqnWAW6cOCv1Y+EF6KqV/Rm6SfxrUC0DPlXrgE/VDJTHpso5l8o5l94yOZdWrV497uTJd9s2EW1oalq6efOUefN6zLlUMuYFlHMuueVcUrfcl3Mu9aE58HLOpb6Rcymbyz23bNnyzZvHDBp0eX191cCB1lsr59KY2tpvVlTs7egIEr0UiXxu0CBqafGTc6mUCMgVKOdcKudcwqOcc0m0rWiUolEhCz9gySAuxRg09wKiUdEQ+XWcMGYA97a4egOQyzcAvAkTdwGYcVEqxvM0eB0AfuYbLi8ANce6Fy4Qu0DNAG6XMG8GQP5EBoBFMeClWgFcVaOqHqofX7Pmd9/+9oWtravD4U27dn315pvTCJIhq87leq1aAXyq1gFFNUbhDapx2kuqZ02f/oEbb7x13bqwbZ83YcLb5s59w1RjB5lBtSsgl4+A4WeWah2QPxH3EtyOhQroqjmCupdqAAbVMuBTtQ74VM3lhEJ9/ppRfvSZx+rVq69vbb3ScQ7l81/dvn3f0aMTBgx4K33AYDB4y4037rzooiJRXU1N8DQIW11+lB9vuWsG+p7hsOgN5HIimRd3sZHHDa/rgPI6/sV9hwHAyay/zr8aALyOtRn5vHgyxgD/CgDB3nmdnBfAn1f/u2bAtkViL6xE0j+RF8CiGPBSrQC9V51IpU5YluM4HUStkUgc1fjbVSuAT9U6oKhG5CiDassSgPTBA4XC2LPOEsMd+FtviGrUx6DaFZAxDOCcWap1wKtVux2LboCumuexvVQDMKiWAf+qFcCnagbQdynPgZfnwPvCHPiVV155y5o1Kw4dei2Ves+SJSPGjqXOzrfSHHgPQHkOvDwHXp4DL8+Bl+fA/c+Bj6up+dktt2w5fnxwPD5++PAAAju/hebAewDKc+DlOfDyHPgb089IpUobXtLpbqljuJ8hh4uRgWRS3AVwNBjMaJkBfE/hvgYAh6kxA8qOm2CQUikxd6cAXCCAeFzkajYD2LInR23iMDVmQOlGIL6NHMfGC9Dvbb1UK4CumqvqodpKp4eOGjV02jSRD0BXjRJ6q1oBfKrWAUU19pEZVOPe1qBaAVxN8htdOyIA0GNTuhGs2gDIrRoBw88s1TrAjRNnpatqV0BXrfQzdJPcjfBSLQM+VeuAT9VcTnlPH2WzIiEJLsXBILW2it6o3M8IBNwBxylteGltJdsWN79mACPpfBeAPUQo3wxgBQXuAgCEw6WbaxngAgEUi+KGywwgYgQH3gGAf82AfLvEMY44A5IBYFEy4KpaAXTVXFUv1QAMqmXAv2oF8KnaFZBVY3mMQTUmDwyqFUA3yW+EMS/AtsW9ra7aDMiqcW97ZqnWAW6cOCt11V6ArlrpZ+gmARhUy4BP1TrgUzUDp8GevvLSjvKj/Cg/yo/y40zpZ0QiFI9TPF7KdJbPq3n6gkFPIB4v5fNCXxi3GGYA4yHc+UXPF3dnZgCjjRw/Gf+LK78CyAVms2KCjgd2vQAMPXGkHdQffWozgLA5GOoBAFHADIAS48igWgFcVXNVvVRjMtOgmgH/qhXAp2odUFTjoBtUYzzEoFoBdJPyG/VEfgwgkpIcToqragbkD25ZpXTTZ4pqHeDGibNSV+0F6KrlnEuuqgEYVMuAT9U64FM1lwOgvNaWIhHRKeOFaBzdE2NTWKymA+FwqTeHxQYYwDEDGDnF6wC4/B4BHm3kysjlM6BUGP1fXnToBfDn5QLZjBkoFkUvHktp5YqZARbFgJdqBdBVc1W9VAMwqFYAn6oVwKdqHVBUYxWmQTVCkxpUK4BuUvlEXgCvN9VVmwFFNSb2ziDVOsDl46zUVXsBumoeyvNSDcCgWgb8q1YAn6oZKK+1FclK8VR+Rd5QJJ32Asyv+3+jbbtjCuBVFIYpZcCrQD+AUqBXxWSgtx/87//GN091j5XxeSx6q7rH1uvT4Zt3jJQPrv9wmqv2f773eCz013s8fXqsiQz4VK2/7lO1AvTpa0Y4TLEYxWLiWhqLUTarjk1hVbIrEIuJuxgAGHWRB0xcAYyHwD6AWEx0ac0AeotI+QAAlQcmA3KBeCKgrBlAgRhMAxCLiTsLM4AuNtKNAIAoYAZAGQ8xqFYAV9VcVS/VwAyqGfCvWgF8qtYBRTUUGVRDhUG1Aria5Dfmcp4APrU89CRX1QDIHxyTqGeWah2QGycPAyqqXQFdNf+vl2oABtUy4FO1DvhUzeWUx6YonxerqrFqIhym9nbRPZfXTYVC7gC/kQEs5jEDWDvEkYqxsoWXhxsAHHWsagAQjYo36gBeB8D7GMwA7kfkAgMB8asZkBc1AYAotD8DwKLkoNCuqnVAUc1V9VINwKBaBnqlWgZ8qtYBRTVu6wyq0QM2qFYA3SS/EcYMANbq6KrNgKwaa3XOLNU6wE0LZ6Wu2gvQVSvrpnSTAAyqZcCnah3wqZoBHr/qu9eMWIyqqkq7KKqqiMhlf0Ym4w6kUmKzJYBkUoQAMwO4t8UVG0BlZSlBigGQd2kCyGRK+0tlgAsEkEiIsUgzgNsKpBEGkE6LkU0zIKeoBABRRD0A+p4AL9UKoKvmqnqpBmBQLQP+VSuAT9U6oKjGvKtBdSAgAC/VCqCb5DfCmBeQTIr/0lWbAVl1RYW4tz2DVOsAN06clbpqL0BXrezP0E3y9gsv1TLgU7UO+FQNAIsI+vo1o7OTGhupq0vs8yKipiYRnlPuZziOO1Ao/P/2zi25jVsJw+BNGvEmHVfe8pAF5DG7yMazAa8jZUlJTFkieR5+5J9WN7oJ2Sc+YthdqpTMfANhPg6JOzCeZHJ/X08p4WarHiDXHgM4HOpiyxiwqzSn0/LpU22uSoAJAsD4lVwQ2wSOx7Lb1WoFgP2+zs6OAdmMIICMxQBFEfBUK8CqZlY91QAC1RLoV62ATtUWUKqx1jdQPZmMQFO1AqxJXghjHvD8XOu2VnUMSNVqcfJZqLYAH058Kq1qD7CqVTvDmuQZVp5qCXSqtkCnagCPj+XDh4svM+bzMgxlGGpv4zCU62vdzsDrTWAYamsOAAp/WfltAviewjgHgGGoz00MoBaADdEAYCN3YBJgggBQs2CFywM4PMAEh6HOEYwBVJfQgAUAUcACQNVtA9UKaKpmVj3VmHIaqCbQr1oBnaotoFRzeMBTPZ2eUK2ApkleCGNNYBjq+YxN1QEgVXPD8DNSbQH5cEpRUnUTsKrx7AWqAQSqJdCp2gKdquUdXXqZwU5Y+MUv8gfvkAfwUHX+EzN0YwBDTHidf53/DAAmhS/fZsaav8s5lAHA4QF1p8yYB6BkhS51RzFgU/BUK8Cqbt6RNNm8Iw/oV62ATtXebTJjfDI91fLRbapWwDeqxlroQLUF1B1hQuoZqbaAfD1+LxRg8wBdgWrps6m6+Y7Eqi3QqRov4k9nmVFeXsrzc61l4Bd5rDHGSD0AP3ydX2QxgO8pvI5XmH4M4AnDnwCg0iegEuSHJwbwha7uVGIBAJPQZY15gDw4PX4vFGBVqwutyeYdeUC/agV0qraAwnCzgWouhvBUK+AbVcvjvpuqLaDuCN9T56VaAer14L1QgFWN1wPVzQs9oFO1BTpVE+Bil8stM66vy3pdNpvqYrOpDUwuTUL70QPW65oOgNWqTkiNAfSHcEgK/xcFeAyoHcSm07Je16arApggAAzQyc3amgCGuDmIdziMu8THAKYMYvgHAEQh/QBQ8zsD1Qpoqub+dJ7q4/GEagL9qhXQqdoCSjXGXQPVWHscqFZA0yQuhDEPwGaOciqtVB0AUjXmrJ+Xagvw4cSnsqm6CVjVGMEOVAMIVEugU7UFOlUDwMft0suMp6c6Ro3/zufljz/G6hLHwGezNsALARyPdWA2BrAfOHcQ++OPMp2OQ+UBwPNkZrMKXF2NeyBKgAkC4D7VMYCuHk7cxN6IwGJADnEDgCj0jQYARcnN2pqqFWBVM6ueagCBagn0q1ZAp2oLKNUYrQlUo589UK0Aa5IXwpgHHI913NWqjgGpGuOu56XaAnw48am0qj3AqlZj4NYk/huolkCnagt0qiaQexRmZGRkZJxRvIP1GXd3Yw/S3d2rIxnk+owmsNmMawLQDEQHTgzgbDjMQACAM7BOAuoUrcWi3N7WtrACmCCA5oFlFkDXExaUANhuaws3BtTyi/m8iirlBNBcftFUrQCrmln1VAMIVEugX7UCOlVbQKnmYQme6smkAp5qBTRN4kIY8wAsZFHLL6g6AKTq6+symZyZagvw4cSnsqm6CVjVan2GNcnlF55qCXSqtkCn6vL3Ao5cn1E+fy6fPpWXlzqrejIp9/dlt9N9U6W0gf1+bIre39eVk1jEEABqTQCanJg9HQN29vRsVjOmACYIAOcGy4nqTQCrXrkC9uGhTsrGCFgAyK4nABBVygmAouRE9aZqBVjVzKqnGkCgWgL9qhXQqdoCSjV6HgLV6F4IVCvAmuSFMOYBLy+1P8SqjgGpWi0aOAvVTQAZw6fSqg4ApVr1TVmT7IDyVEugU7UFOlWXv8/7Y4f55ZYZV1dltSrr9TiKKDeFRi1gPneB1apWHwCsVq8WMXgAvqdQ7ANYrcYdjwNAjVChdoOvUQXIBJ+eynJZ5vPTAJoRCACr1biXewBw5xwMcVMUsABQ466BagU0VXP801ONtcGBagL9qhXQqdoCSjXGXQPVGHcNVCugaRIXwpgHYLKAHOKWqgNA3vh0Wr+nzki1Bfhw4lPZVN0ErGq5F3pTNYBAtQQ6VVugUzXT4Rbrl1tmcDEwyk8UrZxax5bjYtEGeCGAyaRWfmMA48DcDQaH7nLAKgDwOKIWAGAYKqYAJkiAZzUHAHb9kwnOZmPNIgDw3GMTBQCs5sQARRHwVCvAqmZWPdXMiadaAv2qLdCj2gJKNb4pAtX4RghUK8Ca5IUw5gGTSa3bWtUxIFWjbnteqi3Ah5OfSqXaA6xqWWY0VQMIVEugU7UF+lUDwCD5RZcZqGniLCC80/IHrwcAfvDG8J/YLTUA5Otx+grgolMvfQLNBDHnOgaaGSbmAd6PZyz4iVXLN+WdqG7+9KhWgMqG/KV5R3h0A9UKCN6jr3sr1Svex4evMz/notoC3sPDW+v/okD/VaBaAk3VEuhUbYFO1QRQOl50mcGtuNDmwkJ5HJ7OIazj0QWur2uTEwCGp7AJUgDI/SoAyPQDgBsRI2W5sl8BNsN4wmIAOUddgxlGzSIGUF3i1uIYdWT6AUBRBDzVCmiqRlYD1TijJlBNoF+1AjpVW0CpRj9AoBrdC4FqBViT6o48AFsbIT9KdQzIG8dRNOel2gIyfbYSpGoPsKr3+7pFh6caQKBaAp2qLdCpmsB8fvFlBs5JZw/S1VX5669xmT7HwNnkVIDXNxUD/8q+KQ5xA4Ao2TRuAhQlN4VuqlaAVX05fVMcNQXgqVaANckLYcwD2B9iVcfAJfRNKdUeYFWrMXBrEkCgWgLZN/X9YrksHz6U9XqcEcuKpywzbm/bwHpdS2YAq1XdAiwGkAJWVALYbmsBHgNqVsMwjNtMKoAJAlgu9QSSJoAhblQrAGw2dcZeDMgiAQBEYdJhANi9VD3VCrCqmVVPNYBAtQT6VSugU7UFlGqMuwaqMe4aqFaANckLYcwDViu9bS2zGgNSNefqnJFqC/DhxKfSqvYAq1qVGdYkgEC1BDpVW6BTNYDFoqxWF19m/PVX+f338uXLOFuxuRf6ft8GvnypU2kBPD3pDbqbgJzfCeDlpc6EiwE7E66U8vvvdQqdBJgggN1Of3iaAIoETBkE8Pxcp/rFgCoS/vyzisIsgwCw31OeagVY1cyqpxpAoFoC/aoV0KnaAko15lMGqieTCniqFWBN8kIY84CnJ10kMKsxIFWrCaBnodoCfDjxqbSqPcCqVmWGNQkgUC2BTtVNoEc1gMfH8p//lB9+uPi5tstlWS7H2YrYN1jOm5rNXGC5HOfkPT/X+XZyAmgT4NkmeB21GLQKYwDvKJ4zAMtlXc2vAJngbleWy9rYjAEUCdxpB/lHr2gMoFsWo2QAIApYAKj5nYFqBTRVM6ueaqzzClQT6FetgE7VFlCq8aYHqlG3DVQrwJqUF9rJuASwk5KcSsusxoC8cRyAel6qLcCHE59Kq9oDrGo5b6qpGkCgWgKdqi3QqZrp5Nmu5eWldiZiDvLTU601cNtUtDNw9IoFFov6OoD5vFbGYwCtVLwOgOmfBDh7mpmR6RNQGWYNPQZ4v0yQZmIAHdnIOQBmLAYoioCnWgFWNbPqqQYQqFZAp2oFdKq2gFJ9OIxrGJuqsTVpoFoB1qS6Iw+AKAycKtUxoFSj0/+MVFuA6eNTaVV7gFWNVdyBagCBagn0q1ZAp2oCKHguuszAoC5+1D8x9x8Lxzwgfr3/Qhw4bDEFeEmh6SoBL8EeQCXoZUwCb73x73/hP6f6ZGY634u3qj759HY6/OfeI3Xj9pd3rrr/837yvbCvn/z4nMyJBDpV29c7VSvgosuMxaLc3JSbm1qW3tzUU7Rk39Rk4gI3N7UWAwC9LrLDpAmgPwT2Adzc1CZtDKC1iGnUAJB5YBKQCeIHE4RiAAmiMw3AzU2tWcQAV8Mi5cOhigIWAKo/JFCtgKZqZtVTDSxQTaBftQI6VVtAqYaiQDVUBKoV0DTJC3E4XRPAXcuuJ5nVAJA3jhk756XaAvLhZDegUt0ErGr+X081gEC1BDpVW6BTNdPJvqny5UvdkAcjYItF+fPP2jyXY+DzeRvghQQwMBsDOHeIU9+whTL+bwzgXccIFYDr63qhBfA6AOwThQ7QAEB9RCY4nY778ASAHOIGAFF4/gKAouSm0E3VFlCqmVVPNYBAtQTepFoCnaotoFSjWheoRgs4UK0Aa5IXwlgAYNzVqo4BqRrjruel2gJ8tPCptKo9wKpWY+DWJIBAtQQ6VVugUzUB9l/9/yL3Qs/IyMjIOJd2xjCU29vxMKzb21dzErgX+u1tG9hsxmnXmKCCVZ0xgP23MV0awO1tzU8MqJ2K5/Oy3damqwKYIIDmptAWQOMaw18Atts6XBYD3JgLzX9s3o7GfgzY/bc91QqwqplVTzWAQLUE+lUroFO1BZRqzHUJVGOuTqBaAU2TuBDGPGC1qmfVNVUHgFSNJvt5qbYAH058Kpuqm4BVrfZCtya51bmnWgKdqi3Qqbr8vVk6tyi93DJjtyv392W/r5OXp9Py8DCuHWXf1GTSBg6H8Yi0h4e6cpItYg9Q+28DQPoxYGdPz+fjhHQJMEEAmB4mJ6o3ARx7xzbsw0PdAJkTzDxAdj0BgKhSTgAUJZv5TdUKsKqZVU81AU+1BPpVK6BTtQWUavQ/BKrRvRCoVoA1yQthzAP2+9ofYlWfBKharQk4C9UW4MOJT6VV7QFWteqbsiYBBKoV0KPaAp2qEY+P5fPnbGcMZbMZD8vdbl8dHcN2xnbbBtbrWgsAgLN2ZZWtCeB7iutFccYLqicxoHYqns3KZlO7IBXABAEsl+Xq6tVex00AQ15oGAHYbquoGFDNiOm0igIWALZu66lWgFXNrHqqAQSqJdCvWgGdqi2gVGNNQKAaddtAtQKaJnlhsyECAA0y1Yyg6gCQqjHSe16qLcCHE5/KpuomYFWrdoY1yWaEp1oCnaot0Kma6eR54GW3qweSoCiezcrjY22NynbGdNoGjsfxsNzHx3I41MpvDEyndZ8r1AJw/jBXewYAJ0rPZhVYLMbKtQSYIADMAcd/AwBDyhzEA8DF1QEgq0sAIIrVEw+gKAk0VSvAqmZWPdUAAtUS6FetgE7VTUCqxp5CgWpsGRSoVoA1yQthzAMOh1q3tapjQKpG3fa8VFuADyc+lVa1B1jVqp1hTQIIVEugU7UFOlUTeAfngf+/ywx0Z/McRPyCugmOP8Q8nwCQr+MHe68GAHbMVQninzGAliPOcmFqCgOgEkSuOFXOAw6HKGMBgDwfDrUPV14YAxRFwFOtgPejWgGdqi2gVO/3J1TDSaBaAd+iGr2sgeomIO8Ik6nOS7UFOlVbwKpGcyRQDSBQLYFO1RboVE0AbZeLLjPkPvKlRAczBEARm9TzmzEAvH32UYYFgN0Q32as+ftJmJvjBxkLAHlkgve3mvxtE1YAAAcaSURBVMBbVat03olqCbwJbv5R5udNR4k0sf+hamCBagso1cHD8z5VW6BTdSmnzyDxEqFJ746aQKdqC7zJHtO86DLj5aXsdnU9ffl7SzK0SVGeo2+KryuAW4PgdRy5hX7DAMBHS+4xwGRjACljKggAruxXABNUmyjEALbikAkSi4H9fuw4AqCMBQAPTgfgqVaAVa0utCbVHcVAv2oFdKq2gFLNZ89TjepOoNoC36IatdpAtQWUaixiOCPVFuDr3BrEU60Aqxo9S4FqAIFqCXSqtkCnagC7Xe0Nu+gy4+am3N2V9br+8+7u1bAqx8Dv7trAZjNu3I2BLzRmYwAdYmjxAcA8tpOAmgm3WJTb2zq2pgAmCKA56dACGOLGFD0A222tWcQAh/JmswpAFIbOAsCOu3qqFWBVM6ueagCBagn0q1ZAp2oLKNUc8PRU46zmQLUCmiZxIYx5wHpdN6xtqg4AqRqHS5+Xagvw4cSnsqm6CVjVagzcmuQQt6daAp2qLdCpGsB0Oh6cfrllxufP5dOn8vJSdzCeTMr9fdnt9Bh4KW1gv69D3ACwcvJ4PAHI+Z0Ajsc6oS0G7Ey42axmTAFMEMDzs5502ARQs+AK2IeHcjjUEbAYkAPUACAKtaEAoCgCnmoFWNXMqqcaQKBaAv2qFdCp2gJKNWqRgerJpAKeagVYk7wQxjzg5aWOu1rVMSBVqwmgZ6G6CSBj+FRa1QGgVKsxcGsSQKBaAp2qLdCpmnN2Oa5+uWXG1VVZrcp6XSd7rNevNoVGLWA+d4HVqlYfAKxWtdEXA/ieQrEPYLUadzwOADUTDrUbfI0qQCb49FSWyzKfnwbQjODaH1SvuJd7AHDnHEylpShgAaD2OApUK6CpmtMcPdWYgxuoJtCvWgGdqi2gVGN+Z6Aa8zsD1QpomsSFMOYBq1WdCdJUHQDyxtEneV6qLcCHE5/KpuomYFXLvdCbqgEEqiXQqdoCnaqZDrdYv9wy4/n51dmuKFqxhIdlxm43HtmoAO9s1xj4V57tKocHsE2NOlqyCVAUAU+1AqzqyznblV3SADzVCrAmeSGMeQDPE7WqY+ASznZVqj3AqpZlRlM1gEC1BPJs1+8Xzf1+7SbDAeBtov7WvZE7t7Mu5UQ63u/9wNdlTN2y3ZW6CbxJdXP76Hei+uQfPZnaW1WXckK1AqzJJuZd0lQdA96+3OeiunRvaR5c+K5Un3y987246DJjPi/DUIahrlUZhnoKrhwDx+tNYBhqkxMABqZky7EJ8HBmvA4MDcAYQMNwMinzeQWur+uLCmCCAIahbm8QA+zqYYLDUGsWMcCJ27NZBSAKWACocddAtQKaqplVTzWOqwtUE+hXrYBO1RZQqtnV46meTk+oVkDTJC+EsSaAc9flELfMagBI1Zhxd16qLSAfTilKqm4CVjXXKnmqAQSqJdCp2gKdquUdXXqZwQ2c4Re/yB+8Qx6Aa/k6T/eLAcx0xuv86/xnADApfPk2M9b8XZ6/FgDcWlzdKTPmAShZoUvdUQzYFDzVCrCqm3ckTTbvyAP6VSugU7V3m8wYn0xPtXx0m6oV8I2q0RkSqLaAuiOsCTgj1RaQr8fvhQJsHqArUC19NlU335FYtQU6VcvlB5deZgxD2W7Lel1dbDa1aJXzpq6uxg2pFLBe13cdADdbjQHUbTG3D8Bm82o3GA/ArAbsAwOAu04qgAlyg085gcQDMMSNig+AzaaKigFuEMttayEKWABQFAFPtQKsambVUw0gUC2BftUK6FRtAaUa466Bau6l6qlWQNMkL8TwZhPgXqpN1QEgVS8WtW57RqotwIcTn8qm6iZgVct5U03VAALVEuhUbYFO1Uwn95sqHz6UDx/KWcdPP/3jQEaqTtWp+n1EnrmUkZGRkZFlRkZGRkZGlhkZGRkZGVlmZGRkZGRkmZGRkZGRkWVGRkZGRkaWGRkZGRkZGVlmZGRkZGRkmZGRkZGRkWVGRkZGRkaWGRkZGRkZWWZkZGRkZGSZkZGRkZGRkWVGRkZGRkaWGRkZGRkZWWZkZGRkZGSZkZGRkZGRZUZGRkZGRpYZGRkZGRlZZmRkZGRkZGSZkZGRkZHx7TH/6iuPx+PxePztt9/u7+/TY0ZGRsb7j48fP/7888/H43EymXzvMmM6nf76668fP378+PFjvhMZGRkZ7z9+/PHHX3755asLjFLK5Hg8fvXFh8PhW8qrjIyMjIzvGfjGnk6/flTim8qMjIyMjIyLihwDz8jIyMjIMiMjIyMjI8uMjIyMjIwsMzIyMjIysszIyMjIyMgyIyMjIyMjy4yMjIyMjIwsMzIyMjIysszIyMjIyMgyIyMjIyMjy4yMjIyMjCwzMjIyMjKyzMjIyMjIyMgyIyMjIyMjy4yMjIyMjCwzMjIyMjKyzMjIyMjIyDIjIyMjI+PfFP8FmI4oP3cD2oAAAAAASUVORK5CYII=
iVBORw0KGgoAAAANSUhEUgAAATgAAAAuCAIAAAAz5ZIPAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAC8NJREFUeNrtnXlUE9cex28IXR6bQRY9KoEQFAHB4lIFXEAUsK6VRXy82moXNlurgizyKEq1taJVrKAom9YqOxXR93qqbS1BQFtAIUQgQAKylQReEkICWd4fc5qmIcQhyQRe3/2c/MHc+c2d+X0z37l37r0n4KRSKYBAINMbPSgBBAKNCoFAoFEhEGhUCAQCjQqBQKBRIRBoVAgEAo0KgUCgUSEQaFQIBAKNCoFAo0IgEGhUCAQCjQqBQKNCIJhx/do1FosFdZhGRh0cHEQTIxaLp792aHKRwWKxRkZGZJsikailufl2WdlEmaotlG7UY3R0PKmv17ASiUTSRm8DANy/d5/H5Q4NDfX29o4Pw06rv75RC/Pz9+x+23f9Bt/1G45+8gmdTgcA5N24+ebWbb7rN0SGhbe3tSkcIpVK827cpDXRXlj56Ojo+XPn2Lp6xGKai4z4mNiHlZXI3wKBIDszK3CH/5mU03g8XrtCYa3eo5qakOBgrzVriwoLNayKw+FEhIWlnj1HtiOz2YM7AwIrKRSFGEy1+l9Cqi5fpaaSrIiRYeESiQQpqf3114V280+fOiUaG1MIlkgkR2LjKBUVKCvncDgRoWEcDkeqEzDNBeGDd9+79/338pUsfc01IS4eC6HUU68gL4/NZqOJbKPTSVbExIQEzZWXSCT/unPXZ513UmLiMI83UQx2WmlRFkxRv+vb0tICAAgICsLhcACAXx4/jouJzci8cjAqCq+vP/4lxNDI0N3DA2XlxsbG/oEBEaFhmnRXGhsbkxITu7q6pjYX5WdsbmazWO6rPLAQSj31LmdcZrPZaCIJBIJWGgmBQBB14GD57dvr1nsvcnZ++63d1VVVOtZKi7JMxxZVLBYvd10yn2Q7PDwskUhys3NCgnf19PQoDe7s7LQn23V2dk7qFCKRaK3HqrvldyZ7bWw2Oycre5OfX5B/QEFenlAonPJcxreo2VlZtkRrhUe1FoVSQz0f7/Wtra2oFGaxlLaoYrFYtc4KJcM8XmlxiVgsjgwL7+3tbaJSH9XUjD8Qa620JQum6Ktn72e0ZwMDAyvdVvL5/P37Plxgb5977er4xkf25HNZvHjevHmyErFY3ESlUiooAsHI/gMHAADVVVXlt8s/PvDxTDMzJAaPx297c3t6WprvRj+koVONWCymVFQU5OU/ffp085YtF9LTrW1sdJALynQUeEipdHR0NDU1xUioyaqnIZSKipKiYnMLc3orHQBwOC52/vz5sr011dVXc3IJBAKNRrMlkxc6LDQ0MFy33tvCwmLbm9sBAMYmxkKhcKGDw5RopfWWj1JR8YxGw+Fws2bP3rR581QOJj346ScAgEQi9dvgsyPAPzrm8ER3tlQqLcgvINmS/tTnGRH8zcCAx+Od+/Isk8F4WPnw7p07v/3Wz+Px5MMW2Ns/ffKkidqk+mKYDMaZlBRvT6+CvPyAoMB7P/4QdTgapUs1zwV9OvK3VHVVlZuHO6ZCoVRPc0qLS2KioxOPJsXGx2dkXjEzN9vk6ycbE6bT6Xt2v30g6tCnn51IPn68pKioIC8fr4+X98lnJ08SicQp1EpbcLncjyL3tbS07Hn33bVeXh9GRMpGEKfSqK+88gqbxWqiUlVEstlsNos1a9Ys+UJDI0MymRwQGAAAKCkupjY2JB07ln7pEtHaWj7M1pYMAKit/XWiygcGBva+847n6jXDvOHSslvn0y6s9fQcPzaIaS7o05HRRKVyOBx3j1WYCvVC9bQCj8f7NDk5IDDQxMQEAIDD4eKOHMHhcAnxR5CAu+V3RkZGbKytAQAOjg6LnJ0H2eyAwEBzc3M09etGK60gFAqD/AOI1tZ79u7V09MDALi5u82ZM0crlavT9eXz+Y8fPTI1Nb1wMX2D17rLlzKCgoMVeoNyzR0TAGBhYTl+F9Ha2sLCoqig8Lv795S//ZsYAwD6lM2tIZibm59NTS379tuC/ILwD0IDdwb5bdxoYGCg+1zQpCOjklKJ19d//fXlmAqlWr2iwkKBQCBf8p+hodu3bplbWMgX+vr5qXZUXW0tm8WaZ2UlK5kxY8ZKN7efHzzgcDgmJiY93d0AgJ7eXkRVJyenvr4+9F+QbrTSiixfnj7d/fx55L5IZJNMJl+/eXMq51Grq6rGxsZWrV5tZGQUExcnFAo/P35i4i67BACg9HUAh8MtWbYUr6//6quvKj0Wr6eHjA2quBgTE5OQt94qLbuVdOwotZH6hq/fkdi4utpalD8srq1c0KTzx0tXZaWrq6uBoSGmQqlWj95Kb372TP4jFArb29sVCuUXaSils7MTACD881kQTyK7Nvj64nC4kqJiZFd3T7ePrw/6m003Wmkui0AgyLqSuWXrVoVL1RbqtKhIX3H1mtUAgK3bt13Nzb1TXl5TXf36ihXjg2fOnAkA4POVfN/dz7vb6G2Mjg42i6V00GVgYAAAMHfuPDRXZb9wYULiP2PiYu9/f++r1PPd3d3+Af7bd+wwm2A4R7u5oEkHQSQSPaqpeT/0A6yFUq3e4dgYhZKqh1Uf7t9PJpMndTMgnmxtbf3T419PDwAwd+5cAICnl2dWbk5keER/f7+hoQGRSIxPSEBZuc600lyWp0+eiEQiBydHjF4x9NQy6gMAwKo1a5CvJCExEQBwLClJ6fQU0dra2NiYyWCMHyTIyc46eeoLAEBtbS3SC1WIQfpINiQb9Nf20ksv+W70u5KdlXPt6phIFBK8i8lkYp0LynQQntTX8/l8dw+PYd4wctNgJJQa6qmBs4uLgaEh5ecK+S4Mk8lcsXIlMt0qlUppTbT8wsK4I/HRMTFJx469/PLLKCvXmVaaMzQ0BAAwMjSSvxgt/r+YSRu1idrU3tY2Z+6c2bNnIyVLli55zdWV2ki9cf26khPo6W3asrm5uVluOoTG5XIvZ2S8s2evy+LFBAKB8nNFQ0NDfZ3i2tHnXc/NzMzc3N3VSMzS0jIsPPzud/9GnusY5TKpdORfupxdXEpLik3lVg5oXShN1HvhqAkAYGxsDABAIBAORh1qbW0tLSmRdYbramtj4+OQzeKiouLCQiaDQW1spNFojI4O9OsNdKaV5jg6OeFwuJrqatnYx1ep50d+f0x0tLd7e3plZ2VpNO2Dnh9/+GHLxjdIVkSytU36hQuDg4Ojo6PXv/56jbsHyYq4wJZ89syXXV1dCkd1tLfbk+16e3uRzRVLlzkusK+kVCKbiQkJJCtielra+NPtDAg8feoURjPIWskFfTqyBQ9nUlLsbEjRh6LYLBamQk1WPZQz+788fhz63vskK+LKZctzs3NEY2MSieTmNzdWu7mfSUnJvHIlJHhXfV2dLL6muvq1Rc4kK6Ls4+LoVFJUjOaSdKaVVhY8ZFy8ZE+2+/ijj44nJ392/Pjg4KBsV3VVFcmKGH3wkNq3K9DNuoqEuPgzKSmydS39/f1/LBYZGxvvB6lUSm+l+6zznmj95xQinwv6dGRGFQgEzc3N45cQa1coNdTTcAmORCJhMpkMBkO2Xlpm7IyLl/r6+mhNTZWUyttlZVmZmRt9fEUi0Qvr1I1WWpRlcHCwsaFR6XLinu5uNClPsVFHR0cjQsOUajdR/O6Qf7xQICaTWZCfr/qj9ZX9k81F6RJCTIVCqZ4Cp05+0dfXp12t6K30RQ4Ow8PDCuWfnziher3hFN5UOpBFDXA6+/+oXC73Ylr6rpC/TzRLKT/SfTEtbfPWrXZ2dqoj6+vqbnzzjeqYg1FRlpaWU5WLjND33t+5K3idtzfWQqFXTwcUFRZGHzx0NDl5565gZAyJy+WWFpcQCDO2bNs2PW+q6YnujAoAkEgkjQ0Nzi4uqsM62tstLS0xmo/ScS4y8m/muS5xnb9gAdZCTSv1+Hx+XExseVkZHo+3sLQQi8QOjg4R+/YtW74c3lTT16iQ/0/YLFZHRwcAOJItSWFtPQQaFQL56wB/3AwCgUaFQCDQqBAINCoEAoFGhUAg0KgQCDQqBAKBRoVAINCoEAg0KgQC0T7/BRrGe/eykggTAAAAAElFTkSuQmCC
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
iVBORw0KGgoAAAANSUhEUgAAAf4AAACvCAIAAACTqCuUAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrsnXVYFNsbx88u3QqKqCy6gEpJWIQJNtgY2NfuutdrB4rttbsRQTHAJGxQQlJBBOmupRu25vfHeOfub3dmmF0WrPN5fB6XmTMn3vecd2bOnJkvDUEQAIFAIJDfCTo0AQQCgcDQD4FAIBAY+iEQCAQCQz8EAoFAYOiHQCAQyM+ELPrflUuXZWToDQ0NU6dP79Sp08/VBh6X6/PAx2ncOBVVFcHt74KD6XS6nJyctY0N7oF8Pj82JiYrM1NRScnC0pLBYEhWEOQnhcfj0el0Go0m2jFoNJrodgjkVwv9Xp6eOdnZAACnceN+otojCBIeFrZnt2tqSsqgwYMFI/K74OA/5s4DAAywtva+f0/02JycnMV/LOBwuQ4ODk8ePy4vL589d67r3j10Ol2sglpO8tevN65fj46KUlfX6G3eu6GhsYTFKiwsdHBw2LR1C+yjrUFRUdGJY8f8/fxGjBx54tQpoV3Llyy9++C+goICNBTkFw/9Ghoa6A81dfWfot4cDifAz//6tWvxcXHoFnkFeWwvm8123bUb/a2oqIibQ2hISFpa2rOAABNTk15GRls2bfL08HBwcBjmYE+9IKnQy8jIzm7gPe+7Bw8fnjHTBateSkoK7KAktOTavLKi4sDBg9VVVUpKSkK7PD1udevWDcZ9yK/NtytcbACoqOBcz5aUlISHhcfHxTU0NGAbm5qacnJyCgsKysrKEATJyclJ+PyZx+Wie4uLi2NjYupq68RKiVFXW/c5Pj42Jra6uhq33gmfE3bt2DHW0RGL1PLy/0Xka1eudOjQoUOHDgAAGRkZ3Bxmzpq1d5+bkbERAICh922qJzMrU6yCpEV8fDwAQPCs08vIyM7ODnZQIupq69asXMXj8SQ73MjYmC4jEx//edToMYLb6+vr79y+7TR+HLQw5Le46scuneRkZYVGguuu3b4PHkxxdv769WtmZobbvv2TpkwGABQXFQ0bPAQAMHf+vC8JCbExsQCArl273vf12b1z18sXLwAA7du3d7/loaGhQTFlb3NzLpd75tSpa1eu1tfXAwCUlZU3bdky74/5QvW26mMVHhWppKT0OT5eKCIX5BdcuXT5wcOHc2fPJm/8nHnzvk3+ZOegOQwZOpR6QVLkfXCwkbEx+pSFxWLxeTydzp3RUxdKYUFBenq6sYmJlpYWOgHFYrGKCgstLC3z8/M5bHZ3JlM0Wx6P9zE2VkVFtb1me1ZxsbmFBXqxnJuTgyBIdyaztLQ0LzfXwtISQZC8vLzqqiqz3r0BAJWVlazi4p69ehHNs2VnZeXk5PTp21dVVVVwl1A9+Xx+dlaWnLy8rq5uWVlZUVGRqakp6qOqqipjE2MAQH1dXVZWtryCPIPBiI2JbdeuHbqdx+NlZ2XLyNC7de+OXn80NTXp6uoCAPLy8lYuXaaqplpWVoY9mqqoqPialNTb3FxVVZWKfaKjogAAg4cMFtx4x8uLzW4aOmwYDA2Q3+Kqn4gDbvse3Ls3YuTII8f+2bvPra627u+//kpLSwMAqKmpoWl8HviMmzBh9pw5AID8/PwRDsPNLczXbdiAjsZzZ85STwkAoNPpFRWV93x8oj/GTpw8qb6+fq+ra3FxsWjd0DsVbGoejcgIguzcvn3p8mX6Bvp0ClMB6enp3rfvnDp5sk/fPh5engYGBhQLkiJFhYWpqamDBg9isViJXxL37dmrqaWF7c3Jzl61fEV2dg6DwZgyYWJUZCQAIDIiYt7sOdevXQ9683by+Akb//xLNNvsrKzVK1bQaLSystL5s+f4PXsGAKiurnbdtdt+yND09PSXL14cOXR4ysRJMdHRH2NjL5w7N3PGjNraWgBAWGjopPETuP/emf3/bdDnvzZsqKmpQRBk2hRn7EMgovWsrKzcs3v38GH2+Xl5zwMCXXfumuDoVF5W9vTJk31ue8c7OlaUl7PZbL9nfuPGjn35/PnRw0ciIyImjhvndesWn8+/6e4+wt4+OTkZzX/1ipXu12+gp5P3795lZ2d37twl5P17tFFbN2+OCP+Qnpa2fs1aiva5ddNj9pzZgjeFNTU1ly5cHDxkCJztgfzWob+hoeHO7dsAAFMzMwAAet3E4/EC/QMAAErKymiywUMG/7FgwU7Xb3PrDAZj1Zo16zas79ylCwAgMzOTeko0wu7d52ZiaqKppTVmzFjsKrWZZtDpaGj2efCAVVy8eOlSiu3Pysx8+eJFRXl5RnrGq5cvORwOxYKkyLvgdwCA0tLS0ydObtm0SUZWBju7pCQnO0+avHzlChtbm27du5v2Nrt25SoAwNrGRlVVRV+fWVdf5/P40Z59bkJ5pqamzp8z9+/NW/r26zfA2jojI8PG1hYAoK6uPmToEEVFRWVl5Y4dO274cwMAQKNdu779+u1xc5OVkX3y+DEAwNHJaenyZbL/fwuIXimvWbV6+86dvc3NtTp06GXUCw39uPVs165dv/79lVVUuFxu5y6dZ8+dq6SsnJmZydTXn+HiIicnp6KqKi8vb25hDgDgcnk7du1ct2G9pZXV0ydP6XT6AGtrGo02wNoadVNUZOTAQQNRFzgMH15TU7NqzRrnqVMrKiomOI2ztbUb4zi2uJilqalJxT6lpaVv3ryZMXOm4Ea3PXtLS0uHDbOHcQHyu0z44JKWmooO7CuXLt3x8sK2FxTkC84Rde3SFb0WVlNTq6mp6dGjB7pdS1OzsKCAz+NRT4lNU7x/9/6u953w0DAs4JI3g8/nIwhCo9FOHDsuJyf3x9x5dDq9pKQEAPAxNnaCo5Pvk8eigQwAMHzEiOEjRjwPCFyxbNnVy1fk5RU2bvqbSkFS9EFwUJCyisrho0fl5OQ+x8cXFBSi27lc7sYNf45xdOxtbo5uqayoUFVVQ8/KXxK+mJr1XrveCXdt4tZNm2fMdNE30AcAJCUmIgjSr39/dG9oSIipmVl1dY2tnd2TR4/bt29vaGiI+mWM49h3QcGzZs/mcDhaWh2Esm1sbNz4518LFi5EJ3PMzMxOnj5NXs/QkBADAwM+n29uYXH8n3969OjR2NjYt1+/o4eP9OvfHz3DhYWFqampLV66BLv0Rh/ARH74YGRs1K5dOwDA1ctXZGRlBwywRtN8CAvX0dFh6jMRBNmxdRuDwXAaP87TwyMyIuLytavN2gcAcP/u3REjR2gJ3F29ffMm8UuC6BQQBPIrX/Xjfr8TGzMLFy96+eZNUMj7xJTkuC8JO3bt+r8sZL5lgo5SGdlvd9DyCgqCmVBMmZKcPGTgoKWLFk2YOPHE6W+r7uTk5Ehi8bcfPB4AQIZOz8nODgsNDXn/ns1mo9PWiYmJRA97UewGDUR/hIWGUixIWvC43NCQEDs7O7SNnXR0hgwdgu6KioxKSEiY9e8Ti8bGxoTPCdY21uiEBpvNHjV6FG5ce/3qVXxcnMu/l7T3794zMTHBpt1C34ew2eyRo0ai+QywHoBlMsDaOiw0lMvlhoaEogkEiY2JycnOFn0ESlRPBEFC34coKysPHjIEta2MDN1u4EAAQFRkpK2dLRbHR44ahc6q1dTUZKSnW1vbAAAiIyJtbe0AAJkZGdHR0VZWVtia2tDQULuBA2k0WkZGRoC/vy5D9+TxEx21O925dxddq0ZuHwRBvG/fEXyuk5eXd/Xy5ekzXJj6+ug9KATyW4R+NEoCAHj/BjgAgL6BARqPkhKTVFRV5OXlFRUVVVVViZZLNjU1/f9FYoNQ6KeS8urlK4UFBSampmMdHbG5ZllZwtBfX/9taRCHywUArFm37sixf85dvHD52lU0ChibGB8/eZLP56enp69YuvTi+fNo+vKysu1btqK/S1gl2BwUAEAoJW5B0iIuLr66unrosG9hSFtbG1tt9eljrIKCQi+jb89aA/0DNDQ0Zs6aBQB4H/yuR48eAwcNws0zIvyDkbFxe01NAEBOTs7zwMAB/77UVlRUlJaWtmrNavRGKjIiwsb2v3VEffr0qa2tTU5Orqyo0OncWSjbxC+J8vLyglfK5PXMzcnJz89fsWolAKC2tjbuU9yyFStoNFpTU1Pcp0+2dgPRO7wP4eEjR41Cj/W+fYeprz9lqjOCINHR0da2NjwuNzIiUklJaeC/p2cEQcJCQ9CzdWREBABg5+7df/29cfSY0djdIbl9WCxWbm4udo9SXla26a+/9h88mJCQYGJiAoMC5DcK/XW1teiPe97e3rfvXL185cSxY8rKystWLAcAvHzx4ujhI1++fIn79GnJwkXoWhfsbMHnfTtboE8IsT8bGhrRi2XqKQEAbA4bAJCTnZ2RnhEaEvJvgnoiXYGamtp/L595AIBpM6ZPnTZtrKPjiJEj0UNUVdUmTJooIyNz9fLl54HPjxw6nJ+fDwDYtmWrr49PVmYmepmMzngsWLQQACCUErcgafHqxQsAgLWtreguJWVl5X8fk1RUVFw4f/74qZPKKioAgHfBwU7jxxPNO7FYrG+nq7q6pC+JCooKA6wHBAcFoZfeqqqq9g4OaMhLS0uztrEO8PdH0+t169ZeU/PcmTNYLBZEp7MOm83OyMhA46+/nx/qMqJ6hoSEtNfUHDjwW4xWUFBAV87EffokJy+v100v6M3bxC9fampqrPr2Qc+497y9T54+JS8vn5OdXV5W1n/AgJvu7kPthyUkJAywtn718iUAIDcnpyC/oF///uFh4eilSXl5Odp/nj5+jD6tIbdPfl4eAKAgPx+11T43t6PHj3dnMtNSUw0MDdCbkkMHDvCkensHgfyIob+xsVFZWbm9pub5c+fPnD597syZe953AQBr169ft2GDnJzchXPnxo91dJk2XbuTNnq5VFtTo6CgoKKq0tjYiF6+cblcVVVVbO0/l8NRU1PjcDjUUwIAFi5apKamVllZOcLeXlFR0cTUBACwdvXqxMRE/FuNxsZ27dopKirW1tWKTtFoamlhT24HDxkiJydnYmqi06kTAGDl6lV63bqNc3QaN3bs4YMH+/Ttc+u2l6WVlWjKZguSmKdPnnh5egIAAvz8sXiN4Tx1KkNP7/TJk+FhYWdOnjp38UL/AQMAAIUFBWlpaaPHjCbKdtSY0QmfP8+bPcf9xg374Q5FhUUvn7/o268fOtvjMGI4GjHLystpNJqXp9fQf6c+aDSalZXVmDFjcV9XHjlqlLWNzaa//jp98tShAwfMevdGr7KJ6hn6PmTEyBEysrIAgLCQULuBA9HJ/ZzsbIAgjx8+HGo/LCw0TE5OLiM9I+jN21s3b966c9vI2Bid+QEAbNzw55Bhw9hsNo/LffzoETpZhC4wu3vHe4D1AEcnJwtLS+eJk/5av+Gfw0esbW3l5OSatY+RsbGysvKOrdt2bN1294636969Xbt2BQBkZ2d/+vgpNSUlIz3j8sVLaampMEBAflVoVFS6uFxuZkZGU1NTdyZTaB13a1BbW5uSnNJJp1PXrl3ZbHZOTo6enp5UllTW1NSoqKhg0wIIghQXFVVXV+vq6ir//7tsQim/F3w+v7CwUIZO76SjI9az5YqKiqamJh0dHQBAZWWlhoYG7uEV5eXqGhrYgxAel3vT3X3h4sVE2SIIkpubq6Sk1KFDB8EMxaonj8utrKpCJ47+mDtPr1u31WvXqKqqYrcO2NyUtrY26oLysrL2mppoznw+Pz8/X1dXF/0TQZD8/Px27dqJ1TNzsrPT0tLMLSwEX554HvicwWCYmJqw2ezJEyb4Pn4MV3lCfuvQD/kdQBDkoa+v07hxbRbvOByOVW/zA4cOTZg08cexA5/P975zZ+DAgeirZBDIrzzhA/mdCQ0JGTNy1JlTp21sbNvyOjfo7dv6+nr03d0faEjQ6dNnzIBxHwKv+iG/OFVVVe+Cgx0chrflx6gryssDAgIQBNHQ0HAYPlxotgcCgcDQD4FAIBCp3t1CE0AgEAgM/RAIBAKBoR8CgUAgMPRDIBAIBIZ+CAQCgcDQD4FAIBAY+iEQCAQCQz8EAoFAYOiHQCAQCAz9EAgEAoGhHwKBQCAw9EMgEAgEhn4IBAKBwNAPgUAgEBj6IRAIBAJDPwQCgcDQD4FAIBAY+iGQ3w8+n5+Tnc3lcrEtPB6Px+MRpedwONBokJ8LWWgCiNRBEGTRggVBb94CAOh0uqxsM92MzWZjvxUVFaNiY9tSJViU169ebd74d/Snj+iflZWV74KCncY5EaVPSkwsLS11GD4cuh4CQz/k94VGox35558xI0eVl5XpdNbxf/5cXV2dJD2Pyy0pLX0XFOxx0z3xS+Lz54FTnJ2/Y/3V1NRt7GzpdDpat7OnTm/etlWG+ARmbmHh6+MTHhZua2cLvQ/5KYATPpBWoUOHDoePHgEAFOQX7Ny2HUEQksQysrI6OjrTXWY8ePjQady4hz6+37fy4WGhAwcORH8/fvyYaaAvJyeH7S0sKIiJjm5oaAgLDS0vK0M3Oo0bd+7MGfJmQiAw9EN+fYaPGDF7zhwAwNMnTx49fEjlEEVFxX9OHM/KzCwuLpZiTXg8XkZ6RmZGBp/Pp5I+LDTM7t/Q73P/gbm5ueDeqMio7Vu3Bfj7Z2Zmzp8zF92ooKCAIEjy169SNyN2doH8+NTV1gmd/kncl56e3tDQIHGPrampiYyIyMnOrqmpgaEf8mOxbecOfQN9AMCuHTtycnKoHKKgoLBh41/Bb4OkVYe0tDSnMWNH2NsPH2Y/afyEgvwCdPvLFy9ePH8u9C8vL6++rq6ExerOZKLJMjMyOnbsKJhhVVWVvoH+FGfnESNHZmZmYkNdR0cnKzNLitYrKSnZt9fNYegw2JF+ChISEgL8/Si6LzMjY4KjU0FBAfUei5GRnrFm5ap/jhyRlZXVZTAqKys93G8KPjCDoR/ynVFSUjp55oysrGxdbd2GtWt5AmtmSJji7DzdZYZUKsDlco8eOnzs5InY+Lijx4+lpqRs27IF3SWLB51Gj4qK6j9gAI1G+3YjoqREl5H5v3uCsNDxEyYAAOLj4gRT8vi82rpa8W5HuFwugU0aGhqSv34tLS1pbGyEHemniPsP7t2bOn062h/I3cflcg/uP4B7yU/SY1GeBz6fOnny+IkT9ri59enbl06nMxiMkaNGHty/X7z5RgQCaWUunD/PZOgxGXonjx9v46KD3r6NjYnF/ty727WnvgGXyyU55OD+/b4+PoUFBeifC+f/ER8Xh+3l8Xh9La0qKiq4XO682XNSUlKwXbNmzIiJjqFYsfS09MMHDk6ZOLG4uJgk2eWLl3oZGMIu9INTVVU1Yph9VVUVRfedO3PmxfPnTIZeWlqaWD32Y2xsT32D69eu4fZbD/eb1OsMr/ohrc6SpUutbWwAAGdOnY6Jjm7Lovv372/Vxwr7k6nPVFdXl/n/q3jh2+3UtMKCAgVFRfRP52lTowXqnJSUJC8vX1RYeOPa9b/+3tijRw90O4fDYbM5llaWzc4F3/O+O9tl5qkTJ+wGDbzv66utrQ17yM/OHa/bJmZm5MvYMGKio9XU1Hv27Cluj0UQZPfOXVodOsz/44/q6mqhxwCz5849c+oU0cMDOOED+Q7IyMgcO3FCXV2dz+dvWLtOsqdSkqGs8n/vByQnp4x1ciI/5OyF8ytWrWrfvj365+gxYzIzMrGXtsJDw2a4zOjStevipUvMLSywowL8/Ddu+htdD4p7bx0ZEfH3n38tWrCAzW46f+niqbNnBg0eTJQe8nNx29PTwtKCSsra2tqHPr6z586RoMemJCd/jo/X1Gzvumv3/DlzLc16Cy4qYzAYCIIE+PvD0A/5gejStcu+gwcAAHl5ebt37vwudSgrK4uOilq7fh15MkVFRWz6Hj1vbdz0921PL3RSPuT9e0srK6Hru5TkZK0OWuidjShxnz6NsHfYuX3H/AV/eN+/N2fePA0NDdglfhlqa2tzc3M7depEJfHJ4yfWrF9H8ZQv1GMTEhIAACtWrdq7z+3hk8ebt209dvSfF89fYOm7M5kZ6Rkw9EN+LMaNHz95yhQAwCPfh0+fPGnj0hEE2bFt2+GjRzp06CDuserq6nPmzaXT6VmZmbZ2dqJfdDAwMBg4aBDR4RaWll53bk+YOGGv655DBw6kpaXBzvArUVhQAADQ1NRqNqXfs2f9+vWjeJIQ7bEcNgcAYGZmhv7p4uLSXlMzMOC/y3w1NdWc7GyK1YZv80Lajj373KIiIwuLihgMRhsX7eF+c8YMF8EpGrFAJ1u7M5nLVizH2dvclyp0OndetWbNytWroyIjL52/UFxcPG78eKdx477v9yogUqG9piYAAEGaf2Xk+tWrVVVV/xw9gsXxBXPnGRga3vC4SaXH6jJ0AQB1dfVYr2MymcVFRVgCLpfH4VL9nBQM/ZC2g93UxOVyt27fZmll1Zbl+j17ptO58zAHe/TPoqIiHR2dtm8+jUYbYG09wNq6rrbO79mzlcuXd9LR2bl7l5qaGuwbPy9aWlrKysrl5eXNpjxw6FB9/bfHsCwWa8XSpX9v2WxgYEixx/bs1UtGRiYnO9vE1OTfOwN+t+7dsaNYLNYw02Ew9EN+LPh8/l8b/rSwtFiwcGFblvvq5cuwkFDHcU6hISEAgNKS0qysrHUb1n9HU6ioqkx3mTHdZUZGeobgcwWckyW7SWixdtynT88DAv/a9Df5OiVIW57Re5ubp6elN+u+XkZG2O+8vDwAgImpqYGBAQDgeUBgcXHxvD/mk/RYbW3tqdOn3bt3d/TYMTQarb6+Pj0tfefu3f+eBpDioiKiB044wDW5kLbh3JkzQ+wGiq59blWiIiN7GRiibxVg/xK/JP745uJyuU+fPBkzchSToXfpwsXU1FR0+9HDRwyZ+iUlJbBH/Ti8f/fOedIkKu7DyM3NFVzXv2D+/MG2dnw+n7zH1tTULF+6dOvmza9fvfpz3fqHPr5Yhp8+fhw2eAiPx6NYZxr84BSkDYj48GHBvPl3H9zv/f/fw4FIcPNUWVGhqaUFTfHjgCDIiqXLVq9biz2DFZeGhgYOh0PxzYCysrLCggImU1/wWdH2LVudxo/Dvj3V/M0KDP2Q1qasrMxp9JiVq1ej97O/G/fv3ouMiCDau3nbVgkWHUF+NOpq644eObx9507Bj7y2Ga9fvSosKJgzb54Y81Qw9ENaFR6Pt2DefDU1tbMXzpPPa/+q5OXlVRA/A+zZq5eCggLsJ79G9H/29Ol0lxlt3M+TEpOqqqpsbG3EOgqGfkjrcubUaZ8HD576+1FfxxLx4UNKcsrc+fOg9SCQVgK+0gVpRcLDwi+eP3/u4gXqcb+ivHzblq1mvXtD60EgMPRDfj5KSkrWrV69becOU1NTKukRBAkLDXWePAUA0Ox30CAQSEuA6/ohrQKPx1u/Zm1TU1NWZtaBffvIEzfUNxQVFaUkJ+fm5gIANm76+/d8KgCBtBlwrh/SKpw6ceLUiZOS9EgaLSQ8rHOXLtCGEAgM/ZCfCfRdKj5fkq6loKAg+L1yCAQCQz8EAoFApAB8zAuBQCAw9EMgEAgEhn4IpFkQBOFxuUIbBbVDeTyeqMIJBiZ/iFJcXNxsiZWVlfX19dDyEAgM/ZDvw/PA5+tWr1m2ZKngRp8HD54+foKFab+nzwDxU6WkxMQ3r1+jv2/d9Jg8fgJ5iREfPgyxG5iVmQWND4HA0A/5PowaPcraxtrI2Pi/a3wu9/KFi6jQBI/LPXvq9FgnRxIpK3MLi8rKyvCwcAAAJk9BgrWNjS6Dgd5tXL54CboAAoGhHyJlCgsKYqKjGxoawkJDy8vK0I1373hXV1ejv2k02quXr6bPmI4d8vDhQ71u3VDx8cePHzMN9AU/Z4ibodO4cefOnEEQBH2ZKysz88K5c9FRUdhl/vOAwAB/f2xBGvrKl4f7zUsXL969493Y2Pjq5csAf//goCDoMggEhn5IS4mKjNq+dVuAv39mZub8OXPRa+2gt2+wr1FmpGfQaECvWzf0z8rKymNHjjqMGI7+6XP/gfn/f6NfNEMAgIKCAoIgyV+/AgDq6uoSEhKMTUznz5nL5XLT0tIunDs/euwY/2d+YaGhglkNGjJYTU1txkyXpMSknOzssY6OsTEx0GUQCAz9kJZSVVWlb6A/xdl5xMiRmZmZ6IX5hcuXMVHQm+43Zs2Zg/5GEOTQgQN1dXVDhg5Ft2RmZHTs2JE8Q3S7jo4OOn2voqIybvz4YfbD1NXVCwsLu3TpstN1d3FxMY/PS0tNw60kgvCvX7sWFhq6ZNky6DIIBIZ+SEsJCwsdP2ECACA+Lq7/gAFCX9dBECTAz3/Q4MHonzeuXx86bJimpmbXrl3RLYpKSvT/V5ElypDH59XW1QqmlJWV5fN4dDr9yaNH5WXlurq6PD7+MqE+ffvucnVdv2btof0HoMsgEBj6IS2Cz+dHRUbZ2tnxeDxPj1vbdu5At7NYLPRqvaiwsL6hQU5WFgBwz/tu1666MjIyPXr2xHJgMpnFRUXNZggAKGGx9PUN+Hw+tiqUjyB8Pt/T41Z5eYWxiTGHw8GWCSEIQAAiJyvL5XIAAKEhIQ7Dh78KehseHl5YUAAdB4HA0A+RnKSkJHl5+aLCwhvXrv/198YePXqgV/pjR43+kpAAAOjQsaOsjMyfG/48f/ashaXF6DGjc7JzqqqqsLX5ztOmRkdHk2cIAOBwOGw2x9LKMujN25KSktiY2Pi4uOKionfB74yMjQL9/Y8cPEQDtKdPnubl5X2M/ZiTnf365Sudzp1lZWRPnTj5JeHL+bPnMjMybGxstLW1oeMgEHLgN3wgZFy9fKWurnbBokVCgtH1dXXKKt8koYuKimpqagwNDdGpGxaLVVVZiV3483i8Pbtdd+7ehS7yIcrwyaPHnXQ6Wdvgi8zV19UpKSsjCFJbWyt0IJvNptPpaNG1tbXosiIIBAKv+iGSE/L+vaWVlVC0BQBgcR8AoKOj06NHD2zKXltbW3DCR0ZGZuOmv297enE1vVEEAAAgAElEQVS5XKIMU5KTtTpoEcV9tDgajUan00VrIi8vLysrKyMjIyMjA+M+BEIRKNUCISQrMxOdlG9hPurq6nPmzaXRaEQZGhgY9OzVCxocAmkz4IQPBAKB/HbACR8IBAKBoR8CgUAgMPRDIBAIBIZ+CAQCgcDQD4FAIBAY+iEQCAQCQz8EAoFAYOiHQCAQCAz9EAgEAoGhHwKBQCAw9EMgEAgEhn4IBAKBwNAPgUAgEBj6IRAIBAJDPwQCgUBg6IdAIJDfke+g0pWXlxf89q28vMK0GdOhAyAQCOS7hf7goCA2m83j8hobGxUVFbU7dbKwMJeRlf6JIT4ubu6s2TU1NbZ2dq0U+gvyC5KSEg0MDLozmURp6mrrCgoLevTo8Tv7Xlwj8Hi8+Lh4cwtzGRkZOHK+O+VlZSwWy8jYWKyj+Hz+l4QEExOT1hjdUqSFna2hoSE9Pd3MzOy7VJ5KCJLu2JSAbxM+p0+eXLZ4ydbNm2Oiow8dPDh18uTh9g4F+QVSL2+v654t27dt2rql/4D+LcwqOChoycJF+nrdLM16nz97trysDAAQ6B/g9+xZRXn58GH2n+PjcQ/09fGx7tfv2pUrv3PgENcIkRERE5ycnCdNQtXVId+dQwcP/TF3nliHpKamTnd2njhufFNT04/ctBZ2tke+DwfZ2O7Ztfu7VJ5KCJLu2JQQBEEQBHGZNp3J0BszchSCIOXl5WbGxkyG3vKlSxGpkpKSYtidWVdXJ60Mc3NzmQy9dWvWoH+y2ezexia5ubkIgkRHRQkVxOfzP338iP4eP9Zx899/Iz85gi2SAHGN4OnhwWToNTY2SqV0SAspLS1N/JIobmfw9fFhMvTqamt/8A4s1NnEZfnSpVMnT2n7FpGHIOrWaIMA9e2qX15eHgBAp9MAAO3bt+/VywgAkJSYJHSeqKys5PP5gjdleXl5jY2NuPdrortio2N4PJ7/s2fSOm8pKCgAABQVFdE/E798qa2tRTf27ddPWVlZMPGN69efPHr8bZ5LTu4XuO4TbJEkk31iGkHhXztLpXRIC9HS0jI2MRbXHbI/0jwPSZ2FOpu4KLbscIkhD0HUrdEGAUpWMPTTaDT0z4qKCgBA9+7dAQAD+vSl0WjHT5186OP76OHD5PQ0AACbzT57+vTNG+4DBw+Kj4vT1WW47d/Xo2dPkl2uu3b5PX0GANi31+3K5SvHTp4wMzO7duXKi+cvdrrubvms3MsXL169fAkAuHnDXVVVZebs2RoaGoJ3YQf37bewtLx4/vzESZPQjdlZWY8fPeZwODNnzerStYvgVNK7oGAFBYUZM126de8uWlZCQkJkRERhQaGtna29gwNmt5jo6LhPn0pLy4yNjZzGj6fT6VwuNzwsLCM9Y7rLDF8fn69JX52nOltYWr598ybobZChoeGceXPpdDqPyw0PDy8tKe1tYX7P25tGo7nMnNmdyXz75k3y16+mZmaDhwwJCw2Nj4uTl5dfuHixaIs6d+kiVG0+nx8ZEVlUWGhhaXHn9u0pzs6488K4Rqivr3/o48PmcNhN7ElTJnfq1En0rlawdBqd/urFCwUFRR6PN2LUyA4dOogWJGocNpsdGhJSVlo6zMHB94EPq7h48bKlOjo6QgfiVobo2OCgoKTERECjDRo82MzMjMVi+T171r5d+0lTJv/fpQmBwXGNJlpzLJ/4uLi3b95yOJw+ffv0MjJSVlLSaNdOKAe9bt1E60+xY5B0+MyMjAB//5WrV+N2BqHEnz5+/PDhA4fNUVFRJncKyRAoKioi8jK5K3FLabbOVOpJ4ppvdS4sfPniZV1dbdeuXcdPnNiq/Uo0BMXGxOCOX9FulpWZJXGAojjS8Sd8li9dymTojR/riCDIi+fPmQw9JkMvwM8fQRDTXkZMht72LVuZDD3jHj3R9Lt37mQy9I7/8w+CIKmpqUyGXj9Lq6qqKvJdhw8cZDL0li5ajGbC4/F6G5swGXquu3ZJds/CYrGYDD30zqiurs7fz4/J0EtJTq6qquJyuYIp62prhw0esmPrtqqqKi6HM3nCxMkTJh4+eOh5YKDTmDETnMZhKU8cOxYcFMThcE4eP27aywi9dxPEw/3m4QMHuVxuelo6k6F39443uv3Kpct///kXl8Opq6ubP2fuzOnTORxOdFTUSHuHwbZ2586cCQ4K2rjhzwF9+p46cfLuHW+/Z8/MjI1ve3mht+G9jU1Gjxi5c/uOmzfcRw0fYW5impeXx+Px7Kxtdu3Ygd4P7t6509zEFLdFotV+5PvQtJfRdOepRw8fmTxh4s0b7kINITICn893njTpxvXrCIJ43ro1ymE4n89HEOT+vXvYPbhg6Q0NDaOGj0DvCN327P0cHy/qKVzjhIeFW/ftN3bU6COHDvv7+Y0dNXrm9Omid8G4lSE6tqmpaZTD8PGOTlgOa1auSk9LF533wDW4qNFwa45m8vrVq1kzZrDZ7E8fPxoy9SeOG3/pwkWhHNyv38CtP8WOQURMdPR4R6deBoa4nUEo8T3vuxvWreNwOJWVlTOmTsMmfIiahjsEOBwOiZdJXElUCnmdBTsbUQ4krlm/di064VNVVTVrxozoqKg26FeiIYho/Ip2s5YEqGZHOi7fQv+KZcuYDD3TXkajHIYbdmc6jh799MkTdFcfcwsmQ2/ooMGfPn5Ep6JycnLQcwM21TjEbiCToXfl0mWSXQiCHNy/n8nQW7xgoWAYnTNzVlJiYstDP4IgQW/fMhl6hQUFuImHDxu2d7crFvVWLV+B1YHJ0KuurkYQJCkxcdoU59zc3Nzc3LhPn5gMvcMHDwlmkpWZadOvP9bDDh04EBgQiCBIdlaWIVM/JydH8CHE9WvXEATZuX2H/ZChaMeKj4tjMvRePH+OJpszc9bKZcvR39OmOM+dNRtNlpOT08vAEK2t4+jRaNdBEOTCuXNY6BdsEVG1pztPHe/ohOYpCpERuBzO+LGO6GiJjIhgMvSKi4uFRqNg6YUFBYbdmagT8/PyvyYlCRVEYpwlCxe5TPsWI65dvdqDqS8UBYgqQ3Ksz4MHTIZeWloagiD19fUrli3DbT6RwQWNRlJzBEHmzpq9Y9t29PesGTOwaxrBHEjqT7FjEHH18mUs9At1b0GKi4tNexkVFhZ+C6l376Khn6hpRH2pWS/juoPcgER1FuxsRDmQ54yG/oL8/O1btmIGb4N+JRqCiMav6NhsSYAiH+m4fJvwQfh8AEBXXV0v7zvt27UTXPiFTrrNnDXLwtIS3fLlcwL6A7sH0dTSys3NTUlO1tXVJdoFAOCwOeitLpb53Pnz5s6f911m5VTVVAWr2tjYqKamFh0VxefzgoOC0F1uB/ZjLUIJCQnR69YNmzDdvHUr+iM0NJTH5Xb596ZVV1e3R8+eH8LCFyxcKCcrKycnh04KdezYEZteAwC0a9cOnVsDAMjIyGh10EKTMRgMUzPTxMREim0hqracnFynTp2w+SiKRpCRlX3i74cgyIfwD++Cg9G7YJLStTt1Mrcwnzp5ypp16xYuXiR4Z9qscWTlZNGJUdQ4XC63qalJWaD7kVSG6NgJEyf+c+TotStXDhw69Ob167GOjrjVJjK4oNFIag4A4PG4yV+/orv0DQxraqrR34I5kNSfYscgQk5OntJCuLdBcnJy2NwLNodO1DQ5WVncvtSsl3HdQW5AKhDloKioSJ5zCYs1dYqzh5entrY2jvdbrV9RRLKxKfFIJ1zcyWZz0NmfDh06CC34/dY1tTtiWyoqKwSfsqLVQnsVyS4AAJvDaTaOtD2C9srNzaXR6LPnzMH+DR02TDBxXm5uXV2taCbVVdUAgKrKSmyLjo5OpcCfzRYthK4uQ47yo55mqy2WEQAA4WHhO7dt12XoOgx3aL4P0em3vLwmTJp4+ODBSePH5+fnS8U4klUGfZK5eMli3wc+paWlwW+DRo0eTeUoXIOT13zRkiXJX7/GffrEZrOTEhPnzpsnlfqTdwxxyc/PQ29SKTaNqC8162VcWuh6khyazVmrg5a+vv661asbGhq+Y79q4wAlQehnY6FZCHQJMLvpv3iNrv8BAFRWVKBPC1jFxQAAI6NeJLsAABwOGwDAESiluLj41cuXHLxyW2klK3kCnc6dP8fHFxb890LDm9evBY9i6OklJ6dkZ2VhWz7GfgQA9OrVCwAQFxcnuBqqd+/eEle1oKDA3MLi32p/2yi4vEqwRc1WWyxysrMXzJs3f8Efurq65JmgeyvKyysrqw4cOnTf16e8rPzs6dNCyVpiHOqVEcRl5kxFRcWzp0+rqalhVyHUDU6x5vYODouWLHn/7v1tL6/jp0727ddPWvWXYvfW1zeor6/Pzcmh2DSivtSsl3Fp1vXN2oQoh2ZzptNlTpw+VcIq2b51q2gpbdavyMev1AOUpKEf73ocvWxvbPpvmWZv897ogpzQ0FAAQMLnzxUVFZ27dJns7EyyS7QUPp8/w3nq0kWLL56/IFlfR7PClpBWV1UBAGrr6nATKyurlJaWoqGqvr6+tubbxTv6A700GDFyJJ/PX7dmbXZWVl1t3YN79/Jy8wTPuvb29oqKCsuXLvsY+7G8rOz61atVVVUAgMFDBhubGHu430TdUFJSkpebu2jJYgAAl8fFnI9WGJvyYrPZCPJfbygvK0d/FBYUZGZmzvtjPgCgY0ftxC8JfD6/vr4+Pi6+oaEBex8Ha1Hfvn1xq83hcDhcwtMqkRE+f/7MZrPRWdS4T3Ho6Z/H46HlYudprPSsrOz79+6hq9kWLFqEXo4JQmKcpsYmrOPW1tYCALg8nuCxRJUhP1ZZRWXW7Nke7jcnTJpI0n9wDS5oNJKaAwCuXLpMp9PnzJs7Z+5cPT09LFvBHEjqT7FjnDl1Gp3CFqp8TU01l8sVdUdFeblgsn79+ysqKh4+eAjN/GvSV/TikahpREOgurqa3Mu47iA3IFGdsStODodDlAN5zlwOF0GQDh06nDp79smjx5cuXhTKv5X6lWgIIhq/omOzJQGKfKTjT3i6uroCAG57ehUXFSkqKCxZtkwoxYljxxAEsba16de/PzZJOnjo0K9JX30f+JSXl589c7ZLl84XLl3S6dyZZBcA4NmTp6kpKZpamrPnzEGz8n3woKSkZNSY0ZZWVuLG/ciIiMsXLyZ//VpYUIguSL3l4ZGXl8flcDt37iI4Q4VSWlrq5en5NSkpPy//RWBgaWmpiakJAOD0qVO5ubk8Hm/goEGamprdmcx73t5XLl329PAwNTNduHixYOhXU1MzMTF98uiR+/Xrnp6e9sMdxk+YgN4OOzg4BAYExsfF1dbUeN+5s3P3bsMePaIiI2/ecM/Pz9c30O/YseO5s+fi4+KaGptMzUwTv3y5ce0ai8XSNzAwMDDwuf+goKAgNSUlLy/Pw/3mHjc3wx6GAIB27du7X79x2+t2akqKVR+r5OSUxsZGaxsbwRYNtbfv07ePULUfPXx429OLxSrR1tY2NDQUeiH+2dOn3rfv4BqhY8eOb1699rx169PHj/bDhwf4+4eHhSkoKNzzvltcVMTn801NTZWUlLDS9fX1z5w6raioUF5W/i44eO2G9VpaWkIzQrjGCQsNvX71Kqu42MDQUF5B4eSx44UFBTQa3drGGlulp6mpKVoZ24F2X5OSyI/trs8Meffur01/E02e4Br8oa+voNFk5eRwa47m8P7du5PHT1y6cPHMqdMXz18ICw2xtrV9/eqVYA4d8IxpO9AuPS2NSsfo3r37n+vW+/v5jZ84QVNTE6v8h/AP169eZbFYfD6/t7m5goIC5g6rPn0EU6qpqxn26HnT3f2Op1fI+xBZWdnS0lIAkD59+40eM0a0aRoaGrhDoKqyco+rK5GXiVxpY2c7YsQIIgMS1Tk2Jubi+QtoZzPr3dvRyUk0B6JOBQDw9/O74+VVUFjI1Gf2698v4kP4g3v3S1glvYyN1NXVW69fxcbEXL54USgE4Y7fgoIC0bEpcYAiH+nNLO6sq63lcDi1NTjv+NXV1rLZbNHX6vh8fnZ2dlhoaHZWFo/Ho7Krrq6Ow+EIvknY0NCQlJgo1oPplrw6mJ+XL1RVXLgcTl5entDyUKEE2dnZDQ0NortqampKS0slqJ7LtOnr166tr6/HFmNgVFdXF+Tno+sKBG0l1KJmqy2WrUpKStDfZaWluB0DK53L5XK53Pr6+uzsbNFVei03DpXKiBLy/r379RuSGZxKzfl8/qULF1OSk/Py8j7Hx79989bz1q1/jhyVVv0FXxDd7+bWrN3Iu3djY2NeXh6fz6+rrRVKg+sU0b5E3cvUXU99SJJ0HolHXCv1K1GIxm/rBSgxFndCvjtoJIJ2aPlJC71z37JpE/lnAFpo8NevXi2YP19wS1VVlaeHh9RbFPHhw/1796Bnf5Z+9bPwQ3+977eioqKC9//T3BAJuOd9d8e2bR21tVetXkX+IK6FBudwuO+D323dvLlPn74ysjI52dlycnKi86UtR69btwHW1tCzP0u/+ln4NtcP+b54eXrS6TStDlqFBQU9e/WSlYWnZAnppNOJTpdxHOc0w8WFZIlkyw1uaGg4dNjQgoLC7KwsGRkZR6dxo8eMaY3PWauqqkK3/iz96ieC1toLziAQCATyowEFGiEQCASGfggEAoHA0A+BQCCQXzn0F+QXvH71Kiszs+X5lpeVfU1KgvaVgLrautTUVGiHysrK9PR06FMpZsvj8T7GfsRd1wQHbCvFupa4nuhYqTjrv9DfcklJQSQQDm0NgoOCXKZN19frZmdt4+F+E91484b7YFs7fb1u06Y4ox/t+3GAusEo165cGdCn7907d36BtrSST6WrrvyDDNifERLTtcT1JMdKx1ktl5SkIhzaNnqeuISHhTMZegf27RPc+M+Ro0yGXnBQ0I/zwsgvphvccicOtLHZ7+b2a7SxlXwqRXXl1huwvzzkIsni+ohKt5GKs74tZxaSlGz5mVBLS0voQy7S4sb16/m5eZh4QLOgjWrfvn2zG78jgo36NXSDW+5EWVm5X6aNreTTlqsrYzVsvQH7yyNkOqG+La6PqHQbqThLxtXV9eWLF48fPUr88kVeXj4+Lq5Hz56oqHFMdHSgv//LFy/Ly8p69OxJo9H4fH7Eh4joqCgFBYUL58517NixQ8eOuPlmZmTc8fLqP2AAAIDNZr8LDo6JitLu1MnT41aAn39Po16qqqo8LjcsNDQ2JlZOXv7ShQuhISG6urrt2rd/++bN84CAhoaGbt26hYWG+j17Fh8XZ9WnDzortW3LFkCjlZeXde3aVU1NrdkWFhUW3fP2HjhoEPb5OQBAZERkeFjYzFmzMNXZ4KCgW+43I8I/6DJ027VrR1JtNH1CQsKzp0/9/fy5XE53JhN9y0M0EyoINcrfz0+rg1aPHj083G+GvA/p3r27mroaUSVxPSJWNXAbUl9ff8/bOyYmJvJDBEOPoaqqSmQNcivh9iKKTnS/ccPA0EBJSenypUtfk5L0unVTUVERnMqj2EbqbUGzDfT3j46OVlRS0tbWZrFY9+7ezc7MIhc7bbaNJD4VbQv1UXbX25soW9FWAwASExNfvnixeu0aWVlZoRqWlpQ0O2DRnOPj4rzveIe8f9/Y2CivoMDjcpWUlPAfLRAMcKJ+K2pGkhJFc1BWURFtMpfLDQ0JCXrztpdRr3t3796/e09Ts30nHZ23b97cuH4jNye3t7k50StaaPCJ+/Spq65uwueEZ0+fREdF8Xg8XV3d1NTU+3fvysrK6nTuLBjrRPs2iY8kDgWCJQIAioqKHvn6Jn9N/hwfr9O5M1UteIRA1RZX95KiCKSQcCiR3GXLBWmp3NfExsQyGXoXzp0T3Hjm1GkmQy8+Lg79E1eMlERuFFeet1lRXyIoynLi5i/qEbGqgdsQXNlSImuQ6+vi9iKKThw6aPCUiRO3b9l67OjR/lZ9BtvalZeVkZiC6PaZelsQytK+glBpYytJrUpLXTniwwcqAxYhkCMmqh7RAMftt0RCu0QltoEGcn19/YA+fZcvWYIgCI/Hmzl9+mBbO2zvpPETGhoamhVJJnG9ZKFAqERyzeTmP98mJClJontJUQRSSDiUSO6yJYK0FEFD/9BBg2e7zMT+DR04CAv9JHq8uNXGledtVtSXnGZlOUnyF/SIWNUg0hkmki0lciLRdpJeRMWJQwcN3rjhT/T3x9hYJkPvzKnT4rZR3LYglKV9mx0pbSC1Ki11ZeoDlkiOmAiiAY5Q1kAmKbENNJBPHDtmadYbHSPo9XF+Xj6CIHl5eVivIxdJJvKRxKFAqMRmNZPF+3wbmdIsNRFIIeFQIrnLlgjSioXLTJflK1dif549feb4P/+gv0n0eHGrjSvP6+nhQS7qKxaispwklRT0SLPawoIQ6QwTyZYSOZFoe8t1WdtrfnsYY2llZWBg8DE2Vtw2itsWAIBYEqzU29hKUqtSUVemPmCJ5IgJ7U88wClqIJOU2AYayNNmzDhz6vT7d+/sHRyyMjM1NDQe+vqsWrPm/t27LjNdcE1H0UcShwI1NTXBEpvVTCZ8UIS7FdO91Pz3YYK4ipqSoavLaFaNWupgcpcU0+PK84qbCUWwwU8xf7GqQaQzDAAIDwv3e/p0+aqVDsMdLp4/L1nlpduLuurqosJV4ppa3LagEqxHDh3+c+PG4LdBbgf2S7eNuFKrUuwqUvSgKIuWLNmwdl3cp0/GJiZJiYlbt2+TygAnMSP1EiVocrMn165duw4ZOhR9WPgl4cuylSvu3vFetmJFfl6+XrduLfSRVI5FNZP3ubkdPnjwyeNHl69d69q1K5UM8d/mlbrSLEXEEqSVFuLKXeLK87ZcM5M8McX8xaoGkc6wtORkyXuRuDnX1FSjz7XEamNrS7C2sI3SFVWWoNXilkVFjpjiAKdoRooltp4G8gwXl1evXl+/enXKVOcpzs55ublHDh1yGDFcilZtyeGSaSb/F/qFJCVJdC8pikAKCYeSyF1KLEhbUV7+PCAQe1GLiPLyMgCA0LVGedl/G0n0eHGrjSvPS5IJkbaqIM3KcpLkL+iRZrWF/28YE+gME2rzEjiRaDtJLyIRZRWEz/+WbUF+AauYNWfePHHbKG5bvrmDmrQv9Ta2ktSqtNSVK8rLKQ5YIjlisgGIN8ABZQ1kkhKlq4FMxPCRI9ppaDx5/GSYvb22tra9g8NDH98RI0cSxTqhvk3kI4lDgVCJzWomky3uFJWUJNK9FFIuJfo6uZBwaEx0NJHc5UMfX4kFaa369Llw/vyrFy//WLiQaOR/CP9w9fLlnJycgvx8GVlZVAHY18fH65ZnTU1NTk52Jx0dcwsLXDFSIrnR4SNHmJn1FpLnJVI05fF4uNqqQjQryznW0dHA0FA0fyGPtG/fnlxbWBAinWFc2VIEQR75+opag8vluF+/getcWVlZIvVUIlFWQerqav39/Gpqaj7GfgwM8P/n+IkOHToAAIhMjZuJWG0R1ARuVtoXu91uto2tJLUqRXXlpqamh76+VAZsaEiIqBwxJngrCpHiNHUNZFwBZHV1daEcWqiBbGBgQPK4oq6udtSo0egCXzU1Ne1O2gMHDcKNdUIiyWGhoUQ+InJrs91GRkbm5o0bWIkNDQ0kmsnN3FyQILHupViqhBIL0tbX11dVVUmlJuLKXeLK8+JmQkVblaIsJ8VKitUW3Ia0UE622V5Esb18Pj8vLw/XdNTb2DYSrBK3EZGqqLJYrRZLGhcRR46YygCnYkaxSpRupxWkoaEBC0F8Pp9coFFcq7bwcIk1k7+zNu/vIEgLtVV/rq8v/GISrFJEAjnin0UA+TfkOwsB/g6CtFBb9Sfi15NglSISyBH/LALIvyHfU5v3NxGkhdqqPxG/ngSrFBFXjvgnEkD+DYHavBAIBPLbAVW6IBAIBIZ+CAQCgcDQD5E6jY2NcZ8+Bb15W1RU1AbFfRfFx5YXCtUHvwtSVGn9hUffL2AlGPrbms/x8W6ue2Tl5HJycgbb2sXGxLQww/Vr1/bQN5g6ecrCP/6wMDXroW+w8I8/XKZNNzMynjJx0ndRfGx5oVB98LsgXZXWX3X0/SJWgutb2xIuhzPS3uFLwhf0z1cvX7b8jblVy1d8/vwZ+8prH3OLb19zLSxEP7PeNoqPLdSlEwWqD7YxUldp/SVH3w9lJXHVan+gdf2/G2lpaWlpaZpa3z5dMHzEiJbnOcDa2szMTHS7jo7OWEcn0FaKjy3UpRMFqg+2MVJXaf0lR98PZSVx1WoFkXF1dSXSUSMSiqOuo6agoCCag6h0XEtE1ACBFh2grFtGdDjObLI4hhJVEIyJjr55wz0pKUlVVe3Tx9jIiIiXL16Ul5UbGRslJSb5PvCJjoqsrq6WV1C443X78+d4Q0NDKm8VCTr+rrd3VWXlshXL/91lAQhk/EhUMCXQexNLl46ituKPrD74c0kPUnFoS1Ra27Vv3xrjtyWjT7SbSWX0iVpJXl6eokIqdUlRXH+JHi6BWq3whA+RjhquUJxYOmqiOeBKx7VERI1Ii46ibhnR4bhQNxSugmBjY6OXpycq9MNisVJTUy1Mzdxc96CZ37p5k8nQe/b0aUVFxbQpzpgYoVgITvgIbhSVeSNSwZRM7426Lh11bcUfWX3wJ5IepOjQlqi0tsb4bcnow+1mUhl9olaiOPapd3tcf+EeLoFaLc43fIh01ISE4iTQURPKgUhHTWIRNaIMKeqWkei64ULFUCQKgg99fJkMvbrabx+WGj5s2H43N2wMLF6wcNjgIdu3bE1ISJBs/o4o9OPKvOGqYEqs90ZFl04sbcUfXH3wZ5EepO7Qlqi0Sn38Sjz6SAagVEafkJWojH2xur2ov0gOF1etFmeun0hHTUgoTgIdNaEciHTUJBZRI8qQom6ZuFJ2VAwlloIgBo1Gczuwf5TD8PqGelNTU+nOCVKXiJNY741KoeJa5tDuYMEAABNZSURBVEdWH/xZpAcldqhYKq1SH78Sjz7JBiDR6GOxWKkpKehvjXbtcB+qNTv2xaqPqL+kK/763yjA3fpD6ag1+ykV3Ayp65a1RMoO11ASq+5pamoy9fX9n/mtWrOG5APiLaFZY0qs90alUIkt8+OrD/6w0oMSO1Ra+pqSjd+W2FyyboY7+pISE0+dOIn+Nrcwxw39zRZ9cP9+6vUR9Vcrib/ir+v/iXTUiDKkqFvWwvrgGkpi1b3TJ0/tcdtrYGiweePforKUrbO099sPrDiJ9d5AW+kR/pjqgz/skJHYoW2j0tqS1hHZXLJuhjv6hg4b5vv4EfrPde/eZquEW3QnHR3q9RH1F3lzJI6i/4V+XB01IaE4CXTUhHIg0lGTWESNKEOKumUkum5ENGsoEgXBhsYGAADn36Y1NTY11DcI3KXyLa2sjhw79unjR/fr19HtVEQoMcpKS5vYbKHeQCTzhquCSWS3ZmUmqejSiaWt+OOrD/4U0oPUBfxaotIq9fEr8egjGYASjL5mrURl7I8cNYp6txf1F8moEezkVIRgha+MUEUF+yFDt2/ZevOG+5KFi2KiY9BH6kaGPfpYWPr6+LDZbDRlQX7+bJeZu3bsePLo0aaNG+M+fcJWbjAZeug/I8MeM6dPz83NFc2hpKRkxDB7w+7MBfPmvX3ztpeB4ZiRo257eY20dzDp2cvfz6+iomLn9h1Mht6yxUsy0tND3r/vZ2ll1dsce2okBG6GqampWZmZtgOsPT083r5+s3bV6pSUFLEOJ5GeoGKoJ48f9zY2YTL0zE1ML5w7hz4CykhPnzl9OpOhd+LYsdqa2ls3bxp06z7EbmBUZGRYaGg/Syv0ZF5YWDh04CCDbt3RZQ8L5s8fbGtHsu4IJT8v/9yZM6j99+11w57mPX3ypAdTv5+l1ft377Kzsma7zGQy9Hbt2NHU1PT2zVvjHj1tB1j/uW79tStX7KxtTp04iWs3Lpdr238Ak6GXlpZGVIHTJ08ZMvVXLFuWlpZGUiiuZUQhyQHXZXfveE8aP4HJ0Dt04AC6PAOrj+etW05jxjAZekcPH6murg4NCbHqbW7V2/zlixe5ublTJ09hMvSOHDrM4XBw+7BYPQG3M4g1ZERzIOqikRERVEYNxYEQEx2Nds5tm7dgLz3h1ly0gRRr0vIBSD1MiXYzyUZfs1aiOPYpdnsEQXD9RXQ41slTkpObHaH4K3x+ah013Ayp65aJVR/qhpKW6p4URShFEVXBJLJbszKTbalH+COoD/4sQ0ZiAT+imrfGK6kUWyeWzVtD9pL6a8OiRVNVVyXwF+7hgp2cihAs4du8SkpKuC+w4Cy9UFUVfPPi7Zs3Hz6EL12+DACAPkSqrq5++vgx0WMfVF8bAKApjXcscTNE9RyUlJSavXOXoD5UDCUjK9vyB6RiOUUC1NTU0KU+WBFEdvsYG9uzVy+Sd2JpNBrF1SMttwwVl1GvjwR9+CcaMtQHAsWat8bSA7FaR9Hm0hqAEoBbNMX6EPkL93DBTt7sCMVf4QN11Kg+NPsNFCVx+eVlJsXtw3DIwNH3U49QGVdXV6ijRpHfRFGS6NLv126gWH0YDhk4+n72EQoFGiEQCOS3A36vHwKBQGDoh0AgEAgM/c3C5/M/x8fz8NSRhBBXck9cXT0SiT5p8V3EDinaoeWicd+ldVJp0Y8gwSjY/aRen7raumbnZn8091Gkurq6vKwM154Z6RmZGRlU3mwXzKGmpgZG9lYP/ampqdOdnSeOG4++S0mCBKJ9YunqkUv0SYXvInZI0Q4tF41rYetSU1O3bt6sr9etp77BP0eOFhcX19fVXb18RV+vm90A64sXLpB8w6vlLfruEoxC3U+69UlISAjw91u/dt2PpsQpMc+ePtXX64b+cxg6TFXkY4JpaWlOY8aOsLcfPsx+0vgJBfkFRFmVlJTs2+vmMHQYtqWystLD/WazH/X73Wn5+wu+Pj6Cn0IlkRATV3JPXF09IYm+H1N3UIJCm7WDxKJx0m0dn8/vqW8wZeJEwZdyp06eIgUZvNpaciG6H0GCUbD7CdWnJUJ6nz9/3r1z54+jxCmV7r14wcLAgMDngYHPAwOxl4cFv1m/dNHihISEioqKB/fvGxn2mD9nLtELj+/fvVu3Zo3gR7nR95Bdd+1q9h343xkpLJAiX2UlKCEmruSeuLp6QhJ9UkHquoMSFNqsHSQWjZNu62g0mqKiorz8t+8hPw8IfHDv/k3PW1R0vshbdP3aNXIhuh9BglGw+wnVR2Ihverq6g1r1vo8fgR+GCXOlhMeFqbL0HUY7iBHUOHQkJDlK1eiH092njo1MeGL561bPB5PdPGrkpLSoMGDkxKTAv0DBLd37tJFQUHB0+PW3PnzAAQ3bqP/1dfXP/TxYXM47Cb2pCmTO3XqxGazQ0NCykpLhzk4+D7wYRUXL162VEdHBzvy08ePHz584LA5KirKJPfsB/ftt7C0vHj+/MRJk9CN2VlZjx895nA4M2fNEnzfMjgo6F1QsIKCwoyZLt26dwcAZGZkBPj7r1y9Gn2iEBkRWVRYaGFpcef27SnOzkbGxuRtE82QvFHxcXFv37zlcDh9+vbpZWSkrKQU8SFCsP6d//12uWgTioqKXr14oaCgyOPxRowaib2dKAhuGlHLCxmtc5cugnYQzeTlixevXr4EANy84a6qqtK1a9f8/HxAow0aPNjMzIzFYvk9e9a+XftJUyaTe4ekdbjGJAdVaLp45bJg3Bd1ol63bkLNBwAItah9e03cegqCmYjcxUSt+PLlS+j7kIaGht7mvSsqKhydnD6Ehyd//WpqZjZ4yJCw0ND4uDh5efmFixfjuoykPqJ2TklJSUpMpOIgAMAdr9smZmbq6uoAAOzzcKIIBjjq4wsAEBMdHffpU2lpmbGxkdP48XQ6nWigCR3O5XLDw8Iy0jOmu8zw9fH5mvTVeaqzhaXl2zdvgt4GGRoazpk3l07Hn0++dOHi+3fv7t7xHjho0J8bNxqbCA/k/v37K6uoYH8y9Znq6urivvQwe+5c54mTpk6f1novw//0Ez64GmkkOnYIgtzzvrth3ToOh1NZWTlj6jSiCR8hCTEiyT1cBbKY6GhBXT1cGTYhBHWacCXNxBXno6g7SEUDDzcNruWFChW0A24mQqJx9fX1oxyGj3d0wopes3JVelp626gqmpuYzpg67cK5c+Mdnerr64X2UpQeFGpRdXU1uRCdoIlIXEzUCu/bd9atWcNms/l8/sYNfzIZelVVVUQCliSCglj3E+q6QnZuamqi6CAEQYbYDbx29WpLlDhJ2k5RfxH38JaIMiYlJj5++GjlsuU9mPomPXvFxsSST03s2LZ95/YdJAkuX7wkNOGD0s/SyufBAzi3gwsdAMDn8dhNbPRL3D179kxNTS0pKbGxtTG3sNDQ0Ph786axjo5Tp0+LjopGl/GwWKw9u3dv2rJFVlZWQ0Nj6rSpROcVZRUVGRm6vLy8urq6jKwsAKBLly6btmweNXr0DJeZn+Pj0WfxX5OSwkLD9A0MioqK7B0c6uvrb3t69enbd+KkiVhWEydPMjUza2ho+Ovvjb6PH5FcARFlCAAgaZT79Rv6BoZycnIWlpYDBvTv1KnT0uXLROuP24TSkpKM9PTCggIajbZw0SLc21jcNLiWFypU0A64mSgrK6NX1mpqaurq6kpKSstWrkj4/Dk9PR0A0NDQwOVx9Q30qXgHt3VExiTi08ePly5c/JqUFBMdLbRLyIlz5s4Rbb5oi9TU1ETrKYigiYhcTNSK/Px8tz17tm7fjopMDR4y5Nv6Bzq9XTsNbCILu2/AdRlJfUTtLC8vT9FBtbW1ubm5uHcVRFAfXznZ2YcPHVqzfp2MrKyysvK+gwc+hH+45eEhOtBwD+/br5+NnZ2snNyKVauGDB0674/5JSUlxibG011mODo5WVpahbx7T1RJI2PjCZMmnrt44e6DB4qKirt37iRpUVlZWXRU1Nr16yS4ru3OZGakZ8Dre8IVPqhGWp++fT+Ef3j75i3494vbuDp2AIDgt0FycnLYYBBrhl1Ucg8IqJoFBwV9/vzZ7cB+axtrIKKrJycn171792ZFf0gyJGmUkFqekrIS9SZgmmqXLlzsqN2xl5GR6FG4aYgsLwRmByoFAQAmTJyo07kzutjjzevXYx0dW+IgEmPiYmll5fPokaam5rLFS2JjYkXa8p8TKTafCoJdBdfFRK14/fKVuro6Fl7l5JuZLhfXZS1xEKrOoamp1Rrji0h/UXSgEQ5PUlHGqqqqZmtr1cfK1W1vUmIi0YJsBEF2bNt2+OgR3BnUZlFTU83JzoZRnmyuXyyNtPz8PA6HgyAIlShM8kgQ+y11BTIJMpRAnE8sDTyiNGJZnqLYnqys7OIli48cOvznxo3Bb4PcDuxviYPENSaNRtM30Pe+f2+689SF8+d7379H8lSmlaQWqXeJnOxsuox4S5xbXmeKDmqvqQkAINE5acn4unThIqCmvyjBaKIeGfr07Yt+qRh3Kt/D/eaMGS64UlxU4HJ5QpIykP+76hdXI01f36C+vj43J4f64wTyBFLR7WthhiRqec3WhIoGHm4aEsvjFkpdbM9l5kxFRcWzp0+rqalhl8Bt6Z3uTOZNT08+nz9v9pzsrCzcNGJ1vBZ+bIqoFR20OxYVFmGTNiJe+O8BtQR1Jqk/FQdpaWkpKyuXl5e3cJDjtr1nr56Amv6i1IenICUslrGxMa4F/J490+nceZiDPbZKQtzMWSxWt27dYJQnDP2EincEOnb9+vdXVFQ8fPAQ+vbK16Sv6KUB/nS/gIQYkeQekQKZkK6eqCycEJhEH4mkmbjifFR0B6lo4OGmIbK8UKGYHYgKEhWNU1ZRmTV7tof7zQkCk87k3gEtVlXk8/mNjY3Yq1vGJsa7XHeXlpbOcpmZ8++FAkXpQaEWCdVTFMGugutiolYMHjKEz+fvd3PjcDg8Ljc8NAzLE1fAkqTOggqRQl1XtP5UHESj0Xqbm6enpePMgIujxInb9iFDhlDUXyQynWSijCUlJc8DArFZsgf37m/dsR39LahF+urly7CQUFVVldCQkNCQkMcPH9294w0I9ErZ7CbRUxGCIMVFRdY2NkBMldPfBBlXV1dNTc03r1573rr16eNH++HDA/z9w8PCEAR55OvLKi42MDSUV1A4eex4YUEBjUa3trHWaKdh2KPnTXf3O55eIe9DZGVlS0tLAUCsrPpgk30YpaWlXp6eX5OS8vPyXwQGlpaWmpiaAABOnzqVm5vL4/EGDhqkqanZncm85+195dJlTw8PUzPThYsXR3yIuH71KovF4vP5vc3N/f38bnt6sVgl2trahoaGoreHsTExF89fKC4q4vP5tra2xiYmQhnSaLSw0NDrV6/iNio0JOTk8ROXLlw8c+r0xfMXwkJDrG1t1dXVsfpb9ekTFhrqffuOaBNMzcz2ubkpKiqUl5W/Cw5eu2G96BrzqsrKPa6uQmlwLW870I7P52OFpiSnYHbQ09M7dOCgUCaxMTGXL17My8vjcridO3fpqN3x23W3PjPk3bu/Nv1NcvdNpXVjHR0NDA1FjSmUVWZGxvkzZ2Oio8vLy7lcbs9ePRXk5b8mJb15/aa6ujrAz19RUSE1NfWO123MiR06dsRtflZmplCLBOupqakpVPSH8A+YiWqqazxv3RJ18chRo/QNDERboa2tLSsre/OG+41r12NjYk1MTUPev1++cqWCgkK79u3dr9+47XU7NSXFqo9VcnJKY2PjWEdHojpj3a+mpua2lxfWdRUUFHDrT8VBOjo697y9p7u4YFsK8gtuedwMDAjgcDh1dXWdOmmj8+DPnj7FdR/R+KLLyDg4OAQGBMbHxdXW1HjfubNz927DHj0e+voKDTQNDQ3Rw6Ojom7ecM/Pz9c30O/YseO5s+fi4+KaGptMzUwTv3y5ce0ai8XSNzAwMDAQalFoSMjKZcsD/f05HM674OCBgwZhj9YP7N/36sXLPxYujImOXrxgYdynTw99fNF/zwMDd7m6duzYEUuDGo3H4/n7+Xnd8mSxWEpKyhrt2mHmjY+LCwoK2uXqSqPRhI6CfDs3SqYA19jYmJeXhy5GJJHBa0vdPokzJFHLo1J/Khp4RGlwLU9UqFhieyHv37tfv9Fsw7+Xd8TqeOKqLYrbipqamvLycgRB0EWlmCKmqIClZIMFt/4UHbRs8RLsJd5WajuV162l2AHq6uoSEhJEC6WiRUpdr3Tb5i2hISFtoHL6kwKgCdBF/QvmzxfcUlVV5enh8TO2hf+//fsHGYKoKCuj7pkWIwGgFf2DIYK+fP5SX1sLv3B8FBAD9uzevXjhwtFwILCufxTAb8tbvXLVurVrJ/T1LV64MDQ8fCj6ZdWKldrqGjaWVjo6OvgneEcBtpnnR5AJz8ETQdw83KVl5evWrP0/eqsSceD6tevc3DwxcaNHOOBdhTWaniDg4oULu3bu+vjhg4ysjJu7B9YtNkMCvH79ev7ceUrKSsEhIaMjmySBHdu2Hzl8+M/fP4qKSglJiTSqOEcjaBSMFv2jYBSMglEwCgYAjA74jIJRMApGwWjRPwpGwSgYBaNguAMAKY2SNwDJq5QAAAAASUVORK5CYII=
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
iVBORw0KGgoAAAANSUhEUgAAAegAAACECAIAAADUcy/OAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrtnXdcE8kXwCcQkCrYEJEgQRRQAQFBsIINuyiCiJ69e3Y9+xXlvDvrnSI27AqCZ0Fs2AEJPSBIkRJqQjO0JEBIsvv7Y7z8cskmBARO7+b74Y/N7uzbN2/evp2dmeWRcBwHCAQCgfh6UEEmQCAQCBS4EQgEAoECNwKBQCBQ4EYgEAgUuBEIBAKBAjcCgUAgOi1wNzU1/fLzzzOmTPX08KisrFy6aPF323e0uPSQnpw8Z5ZH6K2QNhxFIBCI/whkwr2/Hz8eeP6CmpqaSCQSCATq6upWgwZNnzHdd+FCFZWWY71IJFq3Zg2Xw+U1NIgwLOfDh8g3bwAA27/bYWBgoODEhw/CU1NShAKBt888uKe+vj7o5k0PDw/DPn1kj3Yojx4+zM7KJjw0fcZ0Lpf75NFj8wEDfHznd05TNTc305Ppw52Hk0ikzrliU1PTzevX42Ljvlm8aMzYse0ouZrNvnrlSlJi4qFff+1navo55SXNIqVwB1mspKTk5YsXcbTYgRYDt2zb1gnNceHc+Zrq6u927+rk6PBPXRfRMjgRK5Yuo1JM+vczLSkpyc/Lv3H9us2gwVSKycplyzEMw1vi+bNnVIoJs5TZ1NSUlJgoEAiOHTly7crVFk8sLi7+ft+++Lg4+PPYkSPmVDNrq0FCgUD2aEezZuXKgz8dSE1Jyc3NHUA1W7poUc6HD7QYmo+X9907dwoLCuxtbH8/fhzvLGgxNCrFpKKiAu9E8vLyqBSTsrKydpf8/Nkze9uhIpHoM8tLmUVS4Y6wmFAgmDLJncflMvLzV69YKRAI2ksyn8+Xd+jGtWv+J0/inc4/dV1EixAH7lHOLlSKifuEieI99+/eo1JMqBSTO3/+2aLQDevWUykmjx89+kzlpk+eAp8W/4hpfvr+B/FTyqK/+YZ16+F2fl5+0M2bOI6Pd3XtzMAtFAgyMzI72Qi3Q0PHu7p2hOTffvlVbNLPKS9lFkmFJQ9hGPbo4cPPVzuFTh9sYdnu1khMSLh08SKKRwglIRj3qK2tZTKZAAAbW1vxzmkzpqupqQEAwu7dh3uKi4o2b9w4c+o0jxkzl3yzKDcnB+7ftGEjHBg5evjIpg0bm5qaZk2f4ePlfeHc+ffv38+Z5eE1x/Pp4yfr16x1sndwHz/hYXg4PDE6Kmru7NleczyTk5IAAN9t25794QMAIOfDhyuXL0sdraur++mHH9zGjJ3qPnnm1GmXLl4UCYVQjuKrKM+GTRsJ34KpZtTJkydLjgulp6WVl5VJlqmvr4+LjSssKGjHdyNVMtlqkFW7v28pLhBHix0xclRHvOq9jY4eNXr055eXMoukwuJDIqFw3+49r1++apWGfD4/NSUlMyOzubkZ7qmsrKTT6RiGFRUWlpSUKBhLiaXFVlZWyiuAYVh6Wtr79PS6ujoAAJPJXL9mbVVFZVFhIYZhAACBQMBkMvl8/rvUVPiSIfalxsbG4uJiHMezs7IKGAxJsY2NjYkJCUWFhe31fywkryulM+KLm5ykJyfDDVtbm/+PhZPJffr0AQDAAJ2clDR18pToyKjzFwOv3bwRHRW1fMlSgUCAYZj7ZHcOhwMAmOM5Z936ddlZWelpaQnx8UZ9jd6lpqampCQnJR07coRqZkZWU8vNzfX76QC8RGJCAj2ZTk9ONh8wAAAwctQoGIu37dg+ZepUyaOMfMas6TOuXr6yes2axxFPJ0+d4vfTgV8O/QLlKL6K8nTr3p1wP4lEEh8qLy/fvnVr4IXAUS4jIp48/TRSHx4eEnyLzf64euWqnw/6yUoQCoXnz55zGzMWPoSEQuHMqdMS4uNramoO+flNdBuXlJgYHRXlNcdz4XxfeBPeCgqeNG782YCAjIyMZUuW7Nn1adhx/569Rw8fET9Crl6+EvE0YvWKlbSYGBjsvD3nHvntcEJ8/JgRI+G8Lo7j2zZvuXTx4vGjR7ds2gTP5XA4/idPPQwPv3TxoqeHR3RUFCxJo9FGjhwpO/Z9/uy5kc4u9+/eO/jjT9OnTFk435fH5RFekcflnT516sXz56f+OOl34CAMTDXV1Rnv39sOtf3l55/Hu7r5eHmLwwGhJvLKi80iDjRihcWHhELhsaPHQkNCOBxO+IMHiQkJq1esXLzwG7EBD//yq2wbRUVGbt+yFcdBamqK+4SJ8XFxAIDCgoKCfIZAKEyhp7xPTyd0jx+///52SEgvg15bNm688+efhFH723Xr6uvrSSoq3nM8AQAlxSV8Pp/JZKbQUzAMe3A/zNnR6fSpU5s3bpw9c1bg+QueHrNXLFsGAHjz+s0Ip+HHDh/5ft9+/5OnJk2Y+PrVp6dRVmbWhnXrMQw7fvTYMDv7DevWiw9JUcBgnA0IcB7m2MDjpaelTXBzCw4KIooDdPF1ZXVGfHFj3L/98iscFUl79068E8OwIVZWVIrJBFc3gUAw0W0clWKyf+8+HMcrKythefhaejs0FP6E/YIb167Bn1VVVft274FD5xnvM3Ac37dnL5ViMnbkKHiJpYsXUykmM6ZMhT/PnTlLpZhYDRjY3NwseRTDMK85nlSKydhRo2Fn5NHDh1SKibkptbGxEcdxxVdpG5JDJWLGu7quWbVKKBTiOL5owUJYoKioSDy2A8eXPmRnywpMTkq2NB8AhzWfP3tmbkrlcDg4jj959NjO2iYhPp4WQ3sYHm5vOxQO11RVVVEpJvRkOo7jwTeDprq7QzkJ8fE7tm3HcbyhoWHhfN+7d+7gOL5x/bfiGYWJbuOuX716OzT0wrnzKXQ6juMfsrMt+ps3Njby+fxDfn44jpeXl3vMmAmb7210tLkplcfl4jhewGCYmfSrqamR1T89LY1KMbly6bJQIIC6icfQJK/4PCJi8sRJiQkJcAzX0nxAVGQkjuPhDx6MHTX6+tWrjY2NHA7HasDAi4GBCjSRV17SLFIKSx5iMZlUikllZaW4GJVikpOTAw/5HTgoVbuqqiprq0FlLBb86X/ypMNQu9raWhzH7925a9HfXJ6f8Hg8c1Pqu9RUHMfPnz3nMWOmbJnCggIne4eGhgYcx28FBcOdLo5O58+eE5dxHT3G02O2UCgsKSkRCgSH/PzE4z9zZs1a4DMfzvr4zvPZvHEj3P+N74IzAQE4jnM4HHNT6uuXrxQPuw0dYh18M+h2aCiPx5M3vC6+LqHOiC9rqAR2A8lksoWlpXhnVmYW7FINsBiYnZWVl5cHOyA/7N//w/79n3p8mAgAkBAXDwAw7NPH2NgYDlwAAEz69evZs2dmZgYAwM7eftDgQXAMBAAgfs/NSH8PAHBwHAZ/JsTHAwDs7O3gEI34aAo9JSkxEQDgPc8bLnEpKiyE/c3KigoAgOKrtC+WlpaqqqoAgAEDBzKZpQCAyNdv2OyPx44cPXbkaHZ2lrfPPC6XS2hkh2HD1NXVAQDXrly1HTpUR0cHAECj0ezs7aura1xGuKTQU5yGO8HhmrjY2K5du9rYWAMAbIcOzc/Lh68jpaWls+fMAQD88vMhHMc9Zs/+MzS0oqLC02su7L0WFBbW1dV5zp27YtXKoXZ2AIDehoYAgEuBgerq6t9u3Ijj+O6dO90nu0MTFTAYNrY2WtraAIDY2NjBQ4bo6+vL6h9Li+3Vq5e3zzxVMhk2kKqKqtQVl61YfuXylREjRgxzdAQAqKqoiESiivJyOCwmEAimTJumoaGhra2tpa3dtWtXBZoQlpcyi5TCkodiYmIsLC179eoFi5lSqXb2dnDkRCAQjHWVXjDz/NkzNTU1wz594M8ZM2dWs9lxsXEt+oOWllZKepqNrW1eXt779HQOp162TG9DQwzDfOf5ZGZkylsfpaura+9gr6qqamxsrEom6+p2FR/S1NQyphirkskAAFNT06rKKri/oqIC3gg6OjpmZmZVVVWKh90chg27HRoye84cLS0t6IdEanRVXmfEPzlU0tzcnPbuHQDAatAgyea8FRwMNzxmzxaPrE2bPn3K1GmLFi+5fO3qH/6n+vfvD28YAICj06eIA6VZW1uLhEK4us7VzRUOO2ZkZAAA4OOhvLwcutoQa2v4HgCfH/CelzyalZkBrz7ir1f49PR0eM/0NTZWfJUOtKMKCY4rMhj5ffoYbduxfduO7Tt37/718GF7BwfZ8kmJic4uLnAjMzNz5KhPdYl5+1YgEExynwTHjoY7O4uHbkeOGgVv1+49ujc3N1dUVAqFwjIWy2WES1Fh4Y1r16hmZieOHcMw/GZwkJaWFgCAFkPDMWysq6vkYL2ent7mrVtOHD+RmZGpq6sbFRkZR4v18fWFRx+EPRg+/NNFY2NoYsWkA3cszXWcm6amJnyowxaXumJ8XDwtJuabxYvgKdkfPgiFwqH29jiOR0dFL1i4oEePHgCAvNzcajZ7uLOzPE3klZcyi5TCkodoMTEjR/1tpN5lxEg4CJP4V0NIUlFe3tTUJB4pNurbFwAgNY0hj+Ki4uNHjzY2NNjaDSUsoKGhEXw7VCBonjlt2vGjx0QiUZu9TrJZvby9Y6Lf8ri8hoYGgVA4ekwL8weWVlaqqmTY7WiRdtQZ0SGB+336ez6fLzUzmZSYeCsoCAAwYeLEiZMm9TEygvu79+ju7OLs7OI81tV1xsyZmpqaTCaztLRU3MOtqamBYXSw9ZD37983NjYCAODcUUpKSgOPBwAYNHgwvM2gTGtrawDAx48f4SDmoMFDpI7q6Oj+NUloBqdSXz5/AQCY5eGhqqqq+CqdQI8ePRMTEqAOkNSUFNnhqaTERJcRLg0NDSwmq4HHgw8hFpNVwGCsWbeWRCLxuLzMjIwRI0Z8mgBITBw9Zsynwfdu3QAANbU1wTeDfBcuhP1fLS2tH3/6cev27bAX/Gm+NzLSYdgw+CwU98sAACtXrbKwGBjg7w8AiI6KHmo3FPZS6cn0pMTE4S7O4vHiESNHEo7RJ8QniKcKbwUHzfXyMuprJHXFpMTEXr16mVKpsNjd239OnDSpf//++fn55WVlnl5ecP/ZgDNLli6lUCjyNJFXXsosUgqLD+E4TnsbM+rvgdvewT6FTq+qqjIwMCCTpb9moFLNGhsbGX91UGBrDrSwaLH1S0tL53nN9V2wwNrGRl6Z2tpaAwOD++Hhu/fuOXvmzPOIZ0pOFCtm+coVY11dT/v7h4aEXLl+Tfy6QEgZi1VdzU57904gECgjXJ7OiC8lcMN+LgCASjWtZrNzc3PPnz235JtFQqFw+owZJ0/7k0gkG1tb6MR/nDgBO8J1dXVvo6MBAHAOBwBgaWEJh02gO1pbW8fHxcNDFpYWAIDXr17DnzCk0mg0+GCH3XYuhwOP9jXuK3V03ITxsOclFAoBAJcvXhQIBP1MTXft3QMAUHyVttHA4zU3N8tOpjc1NTU0NHy6txsa+fwmAIDb+HFVVVX79+yFfR//k6dg51cSBoPR0NAwxNr6VlCQUV8jHMeNKZTMjMyYt2979+4NO4B0erK+vn5XPb336em1tbW5OTnDnYfH0mIBAOrq6lra2n+Ghg5zdIRhTigUYBjGb26GWr15/QYGgqjIyJkesyQvff3qtZqaGlUyecbMWXAOmcks1dDQAACw2eyS4mJVVVWoTG5OTl1trZ29fVRkpJT+6WnpjQ0NcA4wlkbLz83b/+MPsldUUSHBAQ04p/327duf/A6SSKToqCgKhdK7d28AQHhYWFkZC37iIU8TeeWlzCKpsOShAkYBu7raavAg+O4FsbOza2hoCL4ZRLhSZaL7pD5GRiF/vWUmJSba2No6uzgDALhcjlAolBfv6EnJPC6Pw+XiOJ6Xmyto/rTKW7JMZUXFw/BwMpm8fOXKSZMmlZWXAQA0NDVra2sBAHBgTSQSioQiSQ9samqC23Dl+Kf9jQ0Y9qlYgL//MEfHbdu3LVm61MTERMGClubm5oiIiB8PHFBRUUlPS09KTJT3zBBfl1BnxBcUuOn05C5dumhpa//2y6+O9g5zPWaHhtya6THr1u3Qk6f94X2lrq5+PvDCiJEjMzMynYc5ujg6jR05CoYwelKyvr6+uro6jOwJ8fE6OjpqamqDhwxJoSfr6+tTzcxgIIul0fT19bv36NG3b18AQEpysp6enrWNDewt9jM1HTd+PABg4/pvXzx/LnlUV1f32s2bgwcP9pnrtWHd+utXr8339X34+LGuri4AQPFV2kABg3H82HH4SAvw96+vrxcvHWExWa9fvsrMyHyXmhodFcXIZ0S+eTN48OCfDh589PChzeDB7uMnWA2yku2p1VRXCwSC/Xv2Tpsxg/2RTVYjv3n1atDgQW/fvp3o7g4H7tkf2SKR6OXz50OsravZ1QCA2yGhdvZ2UEIfQ0O3cePEA/czZs0y6ddv5rRpe3btunr5CgwxRYWFTCZzkru75KWZzNJf/H6mJ9NT6PQ169YBAMZPmBAd/Xbt6tWvX70yphiTyeTIN2+sBllVVVWpq6tfu3LF5a9ev5i4WJqOjg6LxXrx/HlUZGTInT+h8aWuOG/+fBVV1eCgoIT4+Pv37t+6HWpoaAgA0NfX19LWjqXF/nn7dklJyfWbN6FfydNEXnkps0gqLHkoNzcXAPD40aNBgwZJLhkaMHDguAnjCVd8amlpXbl2NTkp6WxAwIP7Yc+fPbt45TKJRKIn0+/fu4dhWOD583DJrBSOTo4UCsVzlse2LVusbWxKSkq2bNoEF9JIEnj+QnhY2KuXL8lqap5z5wIAxo0bd/3a1f179/H5/PCwsJyc3KjIyDevXsPO0MsXL8pYZTdv3KDFxGRmZiQmJKampLxPT6e9jcnMyISD7xUVlVs2bRpg1n/QQIsRw51/+uEHwgGNsSNHrVm5cq6Xl7q6+vgJE3bt2KGnp0doBMnr4jguqzPiy1pVojx1dXUZ7zOYpUxh+30/JrmOpYDBKC0thcs2CK9eUlKizJecnY9AICgvL5enG4ZhlZWV4qNw4YQskss5ylgsyY8Gq9lsqcIikai0tBSOzCqgms0WCARFhYWSJavZbLHA+vp68f6KigrCLxsXzvc9cexYeXl5i98NikQi+AGtrH1YTKasfeRpIq+8lFkkFRYfgjMBsra9d+dui+1YU1Mjr3UUVFnccBUVFbK3hlAoFIlEXA63jMUS1wjDsLKysjY7s1Ag+P34idLS0pKSkrR3716/fOV34KB4sY2UheHiK7jOR9LIiuQT6Yz4ByHhKOckojU0NzcPHWJ99sL59v3vJZ0GhmEYhj18ED5rtken/deXjubunTuRr9/84X9KvOfxo0fDnZ3hoCLi3wcZmQDRqqh3/+69pqamvsbGX6P+0VFRWzdtXrx06bIVy/81URsA0L17j6dPnny7dp3VICuRCKuuZk9yd0dR+18M6nEjWkEDj5eW9umLQUfHYarkr+zBLxQKc3NyLa0s/01RG1LGYsXExDQ1NvY3N3dycvrqmgaBAjcCgUD8m0EZcBAIBAIFbgQCgUCgwI1AIBAIFLgRCAQCBW4EAoFAoMCNQCAQCBS4EQgEAgVuBAKBQKDAjUAgEAgUuBEIBAIFbgQCgUCgwI1AIBAIFLgRCAQCBW4EAoFAoMCNQCAQCBS4EQgEAgVuBAKBQHwxoPxGiJYRiUQL5/vGx8UBALS0tLp06aKgcLOgmcflfeoXqKjExMf17t0b2RCBaEdQ6jKEUrCYrCmTJnE4nGGOjsGhIaqqqopid3NzclLSjWvXnzx+vHf/vuUrV3amqhFPnt6/f+/MuXPip058XNyIkSNlS9KTk/uZmqKkuoivDjRUglAKo75Gfr8cAgAkJSaeDQhQXFhdXd1lxAj/MwHf7dp57+7dTlZVv5u+tpY23MZx/MzpAGsbG8KSdvb2obdu1dfXo/ZFoMCN+HcyY+bM2XPmAAB+P37iXWpqy29zJNLqtWu1tLRzc3I6U89YGs1l5Ai4/expRI+ePXR1dcVHBQIBAIDP50MNp0ydevL3P1DjIr4u0FBJ+1DNZkdHRYuNqaevN9TOrlu3bkqeXsBgYDjev39/wqPv09N1dXX7mZr+49XkcDjT3CeXlpb2MzV99OSxlrZ2i6ekpqRUVFS6T3Zv2xWFQmFoSEh0VFTXrl2/Wbx4yJAhLZ7i7Tn3pP8pwz59AAAL5/v6HfrZlEoFAGAY5n/yVGoKfaK7+6PwhzNnzfL2mQcAcBsz9tnLF2pqap9pnIgnT9+/fw+3yWTVXgYGjo6OAwYOVL71c3Nzo968cRo+XOoVoby8nJGfD0d7FLtK5zvMl+Oc7Q6fz4+Pixszdiz8mfPhQ1Rk1IpVKwlv/18P/XL42FF5onAcj4qMjI+Lp1KpMz1miWeJJPf3Nzfv2bOHSb9+qMfdeXTv0UNPT2/r5s20mBhrW5vKikrXUaMf3A9T5tw3r98kJycruBWHWFu/ef0m7d27f7yaurq6J07+oaKiUlRY+NOPPypzylA7uzZHbRzHf9i3Pyszi0o1i4+Lnz1zVnpaGgzB+UTgON7Q0FBXVwejNgAgKyvL4K+pURUVFQBAX2PKfF/fuV5eb6OjxZUqKS75fONMmuxeW1Nz+tQpSyvL2Z6eZFWy1xzPDevWwz5+i60f+eZNUmLitStXI55GSJX5du1aLperjKt0vsN8Oc7ZvtTU1Bz59Ten4cNhf+XunTu+PvNfvnhB6KW7d+6KpdHkiSovK/Px8n7x/MXmrVu85nmLo7bUfnsH++joaOjhSt0biHbh/t17VIpJfFwc/Lli6TJ7G1sMwxSflZ+Xv3njxhaLYRi2wGc+i8n8Emp6/OhRKsWESjF58uhxh14oKzPzdmgo3K6trbW3sd313Xc4jgsFghvXr8v+iUSiyDdv9u3eI5Zgbzu0vr5e/HO+t3dqSgqO47/98uv5s+fgzgU+85OTktpF4etXr1IpJmnv3sGft0NCqBSTkOBbSrY+hmEjhjtHvnkjWSY7K2uwpVVjY6OSrtL5DvNFOWe7IBQIVi5bXl5eLrlzx9ZtPl7esoVDgm/t27N3lLMLoSgelzt21OiDPx1QZj+GYUsXL66srGxRQ9TjbjdotBgdHR17BwfxqIIyw1D79uye4+lJIpFaHC+eNmN6gP/pL6GmGzZtsh06FACwe+fO8rKyDr0WHFUHAOjp6Q13cebUcwAAqmTygoULZf9UVFRiabQRo0Z+/PgRnkWlmlZUVMDtpqYmRj5jiLU1j8tLTEhYsHAB3M9ms5V8P2155FHlbzeU5aBBAAAGIx+OrTOZTD6f/y41VSQSEbZ+dlY2iQRGjholKeT0Kf8JEydoaGgo6Sqd7zBflHO2C3fv3NXW0ZZaxqqiqkI4zFVdzXb4666X5ZDfzwKBYMfO75TZTyKR3N0n/3H8BBoq6SRwHI+OjBo1ZjSZTAYAFBUWvktN9V24UPFtlvPhQ3JSsuRKtQIG42xAgPMwxwYeLz0tbYKbW3BQEDzk5uZ2OzS0prr6H68smUz+/eQfWlpadXV127ZsxTCsgy5kaWUlue4wLyfX2cVZ8Sk5H3LKyso0NDTgz1kes3M+fIDbKXR6HyOjrKysa1evnPQ/BQfouVwuhULp2bNnR+ifnJgEAHB2dnlwP8zZ0en0qVObN26cPXMWPTmZsPVvXLvmM99Xssq5ubmPHj6c5O4uWxg+cg75+TnZO0RHRe3fs9dtzNjtW7aKuwvt7jBfhXO2C1cuX3J1dWuxmEAguHTx0opVq+QVYDKZQTdvDh48+OeDfj5e3j/s389msxXsBwCMdXMNCQkpLy9v4R5EMbddyMvNLS8vb2xovHTxYmlxSWxs7KatW1a0tH6ZRqMZGBhI3qhUM7OVq1adO3P2QdgDshr5waNH8EkAAOhtaEhWU8vKypJdksxms9esXKXgQt7z5nnN827H+vYzNf3hp5927tgRS6MFnr+was3qjrZwcXGxUCSa691CLU6fPdOlSxfx89JrnvfR3w5PnjIFdsZ95s/v16/fkPXrxeUfhIV9t3sXoag2WzUrM0sgECQlJp0+dWrdt9+OdXMlkUgnjh/P+ZAT8uftsrKyPoaGsq3P4XAeP3r0/PUrsRyRSLT7u50qKiqjRo++e+eOlKsAAHr06GFhaSkUCrlc7oGf/WJptIXzfZcsXwancNvdYdrmnF8dHA4nKzPLsI9hiyXPnz27dNkysRFkgd+sjRg18ptFi8rLy9euWj3fy/vxswh5+8lkcu/evTU0umRnZhkaGqLA3eFERUYCAPbs26uhqdm1a9fv9X4EAOTl5d29/SfVzEzyHgh/8MBt3DgdHR0AQElRcS8DAylRqmSyw7Bht0NDQu/ckbxRSSRS927dCgoKZO8NfT29EycVrWnr2rVru1d5rrfXq1cvI548PXf27NLlyz5/VYYCMAz7+cDBc4EXxF1peUgV0NDQWL1u7b27d+d4ekZFRh05dlRyaWBWZpaNra25uTmhqDZbtbi4GMOwAQMHRLx4Lp4m1dXVtXewV1VVNTY2hnukWv/+3XtjXF0l+/4XLwSymEw7e/uuXbsSugoAII4W29/cfPKUKSQSSV1dHQCgqqLacQ7TBuf86oAz1b16GSgulhAf371HD7P+ZoqeAfUcAIDn3Lmqqqp9+/bdtWf3wvm+sTSavP2jx4whkUjd9LsVFhWiHnfnBO4os/5mUmu/VFVUDAx7s1gsyZ7O1cuXZ8yc+SmsaGqqqKgQDhEkxMcTfp1YV1tLeDuJw0GnQSKRtmzdGvHkqd+hnzs0agMArly+vHjpkgEDBrTh3F69es3x9GQwGEuWLm1oaPi7nS0VjGW12aruk93lffLzt4fK31s/OCho7fp14p/paWmpqSlD7e0sLa3kuQqO47GxtGXLl8NaZGZk6urqDrQY2KEO01rn/OrQ1NQAAKiotDCXcPzosW7du0VHRQEAmKVMNpu9bs2aadOnT5s+XVymj1EfAIBQKIQ/oVeUlJTI2y8V8VHg7liampoS4uN9fOfLvlr+9suvu/bPAguhAAAgAElEQVTsFu8JPH9+8pSp4p+mpqbPnj6VOquMxaquZqe9eycQCCQDIo7jVVVVFBMTWQXq6+sVT2iMcR071tW1fWstEgq/37d/8dIlU6ZO7VDzPn38xMysv7grV1dXp6en19pnTP/+/WVX0Smegehoq0q2fk1NTXZW1lA7O/izsKDg8K+/BZw76zp6jLf3PHmuUlJczGKyRo0eDd3jVnDwhk2bxCG1IxymDc751WFMoZBIpLq6OsXF1q5fJ/7mlp6cXFpaOmXqVKm+BfzJLC2Fn3TApunTp4+pqSnh/v9bkkJBgbvDocXE8Pl8uORTEhaTJRAI4NcfAIDioqKrl688efb/VbpDrK2LioqEQiEcJsMwTCgURkRE/HjgwP2799LT0jFM5DBsGIwvdXV1AoHAnmj+Wk1NbZiTowINjfr2bfdaHz92vLGxcffevR1q25cvXmRmZkycNCk9LQ3H8RR6ivkAc6l1Fx1EG6zK4XDAXx9nSj/nREKRUCS5R7L1i4uKAAA11dUUCqWosDDA//Tps2f4fH5NdTV8GZdyFUgsLdbAwAC+5wXduGFkZLR0+bL/93/b1WFa5ZxxsXH5ebktTs5/maipqQ0YOJDBYMClU2KEAqHkPLzUg+3Fs+fiN+mIpxFksur4CROoZmbjJ0wIux82xNoaAJCdld27d+9Ro0erqakR7ofPVD6fb2dv14KWaP31Z/IuNXXa5MlUisn+vfs+fvwoeei3Q788ffIUbgsEgiXfLBo31lXq9AU+899GR8PtUc4uSxctgusIv127bqLbuJwPH8Qlwx88WLV8xRdS69evXg8dYl1cXNyhV0mIj7fobw7XjMO/MSNGikSiL9MToqOioCcsXvhNdFSU5KEH9++bU80muLq9fvmKsPV5PN5gC8tJ4yf89P0PgefPNzU14TielJhIpZic+uOkUCCQchXIpg0bJk+clJWZee/O3dOnTgmFQsmj7eswrXLO3Tt3UikmBQzG1/tNxtZNm8U/m5qaHoSFuTg6WQ0YGHbvfk1NjVT5B2Fhkuu4veZ4+s7zgduVlZW+8+b5nzz5+uWr1StWfsjOVrz/YXj4ssVLWtQQBe4O/CphlLMLn8+H23+c+P3M6dP79+6Tjfvfrl0Ht6vZ7MbGRrjN5/MlvxzBMGzNqlVFRUVfQtVYTKa9jW3E06eolT//qS9u/aLCwsg3b2pra8VHuRzug7AwcZiQLAxdwsne4WF4eBmLJfswa3eHaZVzCgWCMwEBDQ0NX+sHOELhN74LpPphysPjcqXqXsZi5Xz4AB/ACvZjGLZm5cr8vPwWL4H+V0lHUV5WNm3K1KQUOgDgUmCgnb19xNOnJv36LVi4UKrkk8eP1dXVx0+YoEBa0M2bFApl9Jgx/3i9hEKhj5fX0KF2+374HrXy56NM6xMWzs/Pn+g2jhYfJ1648k85jOy1ysvKYmJiPOfO/XrbpZrNvnL58uatWwmXD3QQt4KCDfv0cXVreeIEBe6Oorm52WHo0FmzPEypVPcpkykUypqVq6hm1O3ffSc7I09Ppuvr68tbWvT+/XsNDQ15q9Y6mUN+fokJiaF3/lRyJUlJScn79PSOnsD8qlHc+oSFKSaUo4cPB928mZCcrKmp+Q86DOG16uvrdXV1v8YBbqlaJCcluY0b1zmXy8jIUFdTU+a/kqHA3cGd7vLyZj5f/Dl1fn5+N3397l/zv+1/8fz5d9u2hz953Fe52U6hULhs8ZJly5e7jnND/tCOfPz4MS83DwCgrq5u72CPDPJfAwVuhLKUlpbOmDL16InjSr7Xl5SUfL93X8b797EJ8apktH4JgWg30O2EUIrm5uZv167T09fPyszKysxS2MsWVFZWFhUWxsXG4Ti+YtVKFLURCNTjRvwD/PTDD1cvX2nDiU+eRVhYWiIDIhAocCM6FZFIlPYurQ0nqqqq2NjaIgMiEChwIxAIxH8a9P+4EQgEAgVuBAKBQKDAjUAgEAgUuBEtk5eXd/iXX2+HhEruDH/wAGYcBwCIRCJaTAzhufTkZHE2JgQCgQI3opOQlwgCpu/BcfzM6QB5GQPs7O1Db90S/8NiBAKBAjei3YD/PJrP58OfuTk54oVGVDOzOFrsLI9Z4sKSiSCePY3o0bOHZCYwSVEkEmnK1Kknf/9DSTVgNhAMwzou9TACgQI34qsHw7CTv/+xesWK4KCg5UuWht4KEYlEyxYvqayshAUIE0FMnDQR/rx+7ZqLi4s8UQAAUyr15YsXMJrX19fnfPgg+we75PTk5PFjXcvLy4/+djjm7VvUNAiEYtC3yP/hh7aKCgCgrzFlvq+vpobmq5cvvX3mRcfSxAVuXLvm7eMj7hH/sP/7PkZG/UxN4Z6srCyD3r0ViAIA6OrqlhSXmPU3Ky8re/XypawO4ydO7Nq1q72Dg7WNTeitkB27dn7t/1IOgUCBG9GxxMXSdu7eDQDIycmRGq2GaU02b9sKtwP8Tw93Hi6VVFAkEikW1bVr19raGgDAQAuLgRYWCjTpZ2rapUsXFLURCBS4EYpoampi5DOGWFvzuLzEhISr168BADgcDhy2rigvb2hsVFNTw3H8UmDgqNGjIp4+tbD8f/ClUk0rKipgYUJRAAA2mw3/q21yUtKN69dldfhm0WJ7B/uMjAwDA4NYGq2Bx+uioUGYQRyBQKDAjQApdHofI6OsrKzoyMiT/qe0tLVFItHI4c7PXr00NDTs3qNHczN//5694kQQ58+eU1FREYlEMLDO8pid8+ED/A/6sqIAAFwul0Kh9OzZEwDgMGyYw7BhhGrs2LptjOvYbxYvun7tanRUtPuUyahpEAjFoP9V8t/l+NGjffsaT50+TXJlSAOPB8MuaCkRRFNT09HfDu/Zv09FRYVQVNDNm07Dh7eYh6WxsRHmcGng8TS1tNBoCQLRImhVyX8UHMejIqPsHewlQy0AQBy1AQCGhobiqA0A6N+/v2T6Hg0NjdXr1t67e5dQVFZmlo2trTLZs8SZt7S0tVHURiBQjxshl/z8/PR3aVQzqu3QoZ/5AGAwGLKicBxHURiBQIEbgUAgEACgoRIEAoFAgRuBQCAQKHAjEAgEAgVuBAKBQIEbgUAgEChwIxAIBAIFbgQCgUCBG4FAIBAocCMQCAQCBW4EAoFAgRuBQCAQKHAjEAgEAgVuBAKBQIEbgUAgEChwIxAIBAIFbgQCgUCBG4FAIBBfEKo//vhjq05ITkq6dCGQxWINsbaWOnTh3PmXz5+PHD2qtSe2Sk7bdOtooqOiLl4I5NRzLCwtP6ewuO65OTkhwcHXr16bMm3qZ5rlizLUf4fc3Nyb1288f/Z8zNixnytKxhn+KU0QnUBJScm9u3fPBpzJyfng7OJCmAKw1T3unj173rt7t6KiXPaQlpamto52G05slRxCmpubW3WJdsewT5/bISEf2R8/s7C47r0MDAoLi5ISE+WZBVa5tbTZUG273H+Z7t27J8THZ2dlfb4oWWf4pzRBdDQioXD1ipXe3t47d+/K+ZAjEokIi5FbK7efqWm37t0IDy345pu2ndgqObIkJSamp6cvXbZM+Uu0OwMGDJBKl962wuK66+vrW1pavI2KIjSLuMqdY6i2Xe4/To8ePUxNTQsLCz9flKwz/FOaIDqa9PT04qIiLW1tqpnZ2Qvn5RWT7nFXVlYWFRYWFRY2NzczmUy4zeFwAADFxcVFhYUYhn16MohE6Wlp5WVl4nNxHC8sKBD/5PP571JTi2TcRfZEKaTkYBiWnpb2Pj29rq5OtjCTyVy/Zm1VRaVi3QAA9fX1cbFxkpKl4PP5paWlzc3NCfHxkmoLBAImkwmrAx+AfD4/NSUlMyNTth/K4XDi4+Kq2Wypd59YWmxlZWWLhf9W97+/IokPSVW5jMWCzVRbWwsAYLPZRYWFNdXVbTaUlLaEJypTuzYYVoFtGxsbExMSigoLxemtCU+XVaa5uRnarbi4+F1qKjydyWTSk5MFAgGhwrKSZcU2NjYWFxfjOJ6dlVXAYEjVl56cXFJSImsH2aopq95fzqBkcyvQpMXaKRkEFFigRQ9RfFMr6VeEQghvc6FQmJ6WButbUVEBLVxUWAhPLCkpKSos/PjxowIhiptbNtC1GG0I/aGyspJOp2MYVlRYKOs/igJ3GYs1wW3c7ydOkEikosLCCW7jjvx2GB56/fIV3A8AKC8v3751a+CFwFEuIyKePAUA0JPpnh6zV/zVKYulxf580A/D8MALgTOnTquvr4f7ZU+UQkoOhmHfrltXX19PUlHxnuNJ0LrFJXw+n8lkptBToD8RXuJheHhI8C02++Pqlat+PugnK+d2SKiTvcOvPx9au2r1iWPH3caMPfn7HwCAB/fDnB2dTp86tXnjxtkzZ9GTk6MiI7dv2YrjIDU1xX3CxPi4OLGQ7KzspYsW7965y8lhWEjwLbjzx++/vx0S0sug15aNG+/8+aeCwlJ1l2cWqSqz2expU6bu2bULNg2O40sXL2lobGyboWS1lT1REnm1a4NhAQDybJuVmbVh3XoMw44fPTbMzn7DuvWbN26UPV1WmVharOuo0T/98KP/yVOXL15cvnTZ6VP+586cPXs6YP/evUsXLZZVWFYxWbFvXr8Z4TT82OEj3+/b73/y1KQJE1+/egVPT05K2rppMwCk1y9fvX79WiyWsGptUE/J5paniTK1UyYIKLBAix7S4k2tjF8RCiG8zZOTkjZ9u6GxsbG6unrW9OlbNm4EAHDq6ydPnBR88yYAoKqyytdn/m+HfpEnREFlCQNdi9FGnj8UFhQU5DMEQmEKPeV9erqinjkuw7rVa3znzRNvL174DdwO8PfPzc3FcXy8q+uaVauEQiGO44sWLNywbj0scMjPb7yrK47jlZWVE93G8Xg8uO3iNDw9LU3BiVKI5cA+ppO9Q0NDA47jt4KCCcu7ODqdP3sObhNeoqioaOWy5bDA/bv3qBSTD9nZsnLGu7ouWrBQJBLhOH7i2LH+/UwZ+fk4jruOHuPpMVsoFJaUlJSVlVlbDSpjseAp/idPOgy1q62txXHc0c5+x9ZtGIZhGLZ102aL/uZVVVU8Hs/clAp7UufPnvOYMROeSFhYqu4XAwNdHJ0IzSJZZRzH/Q4cdHEaLhAIcBzPyck58tvhthlKnrZSlxMjr3wbDCsUCKqqquTZ9hvfBWcCAnAc53A45qbU1y9fyZ4uT5nVK1bOmDpNKBDgOH7syJEBVLOKigocx1PodCrFhFnKlFVYUnJ9fT2h2DmzZi3wmQ/F+s7z2bxxI1RvuMMwscy1q1cv8JmP47iCqimpnqQzKNPc8jRRsnYtBgF5FlDGQ1q8qZXxK1khhLd5dXW1o5292A5bNm3y8fKG2yOdnc+cPg23ly5evH3LVgWxgrCyhIFOmWijwB/u3blr0d8cbwmCyUkf3/nxcfFVVVUAgK56XWPevoUxpbi42NzcHJaxtLRUVVUFAAwYOJDJLIU7dXW7wo1nERHGJhQtLS0AQK9evWjxceLVC4QnSiGWAwDobWiIYZjvPJ/MjExvn3nKDBLJXiLy9Rs2++OxI0ePHTmanZ3l7TOPy+XKntilS5fBgwerqKgAABYuWoRhWHJyMgBAV1fX3sFeVVXV2Nj49atXampqhn36wFNmzJxZzWbHxX7qGFoOsiKRSCQSac26tc3NzfFxcVpaWinpaTa2tnl5ee/T0zmc+v/rKVNYqu4KzCLF8hXLP1ZVPXwQDgAIDwvznOvZNkMp0FbONLJS5ZUxrCqZ/PzZM3m2raiogK+iOjo6ZmZm0DmlTpenjKaWZq9evVTJZACAiYmJurq6gYEBAMDAoDcAoKqqksjU/5esq6tLLFZTy5hiDMWamppWVVYBAJ48eqyurm7U1+jTrGC37nBDQdXaoJ4yzS1PEyVrp0wQILSAMh7S4k2tjF/JCiG8zcPDHnTr1k1sB8m5JRIgyW7LixWElSUMdMpEGwX+oCQEk5MjR40yMjK6d+fuTI9Z2to6/c3N79+9N8Ta2tnZhWCoRYX015Dj/2Hk5UsahXiMhuhEWTQ0NIJvh27esGHmtGlr16/fvHULjDXKIL4Eg5Hfp4/Rth3blbdLz549dXV1+U1NUvsrysubmppwHIcvqkZ9+wIAZMfrzczMSCQSj8sDABQXFT998njipEm2dkMzMt7LXkuycJvXtHjMmXPh/LmZHrNYTBbVzKxVp0u2RYvaStHa8vIMq9i2Xt7e165c4XF5JBWSQCgcPWZ0G5WRmDZQUSEBADAM//w6ihdsMRj5ZDW1VlWtDeop09zyNFGydq0KApIWUEa+Mjd1izaXFUJ4m9+/d19LuxVL1JSJFf9vbqJAp4wEZf1B+TFuAICKisq8+T63Q0KuXbm6eOkSb595f96+/fjRo8lTpygptLehYWpKijgSYRimeO5CAbW1tQYGBvfDw3fv3XP2zJnnEc/kDfgonFXvmZiQ0CgxDpiakqL4unw+n8vlWg0aLLWfSjVrbGxk/FUdKHOghYVUsWaBAMdxaxub0tLSeV5zfRcssLaxkXctceFWWUaqyqvWrM7KzArwP+3o5KT8WVIo0JbwRGVqp6RhFdt2+coVY11dT/v7h4aEXLl+TdxV+UxllKFVYvv27cssLW2UGXFW0m2Up8XmlqeJkrX7/CCgQH6LN7UyNpcVQnib6+vrFTAY4tk/ee6PA7wNsYIw0Ckj4fP9gXgd91xv78LCwo9VVRQKZfbs2QUMhoaGRpcuXeDRpqamhoaGT5dsaOTzP/WeGni8pqYmAIDb+HEcDmfLpk1lLFZdXd3xo8c0tbQUnCiFWA4AoLKi4mF4OJlMXr5y5aRJk8rKCR5KGpqacIady+USXsJt/Liqqqr9e/byuLyGhgb/k6fg240scOocAPA2OtrO3s7O3g4AIBIJRcJPixYmuk/qY2QUEhwMfyYlJtrY2jq7OIO/+0Xk6zcTJk60GmRFT0rmcXkcLhfH8bzcXEGzAA5RERaWqrugWSAUCgnNIllluMfc3Nx1nNvZgICp06fJfX1pyVDytJW93KcpUwW1a6VhFds2wN9/mKPjtu3blixdamJi8teSmL+dLk8ZTISJb0uhQAiH9QEAAqFQ3gNJUrI8sXCI+VPTNDZgmAgA4DR8OIZhZ06f/rQKqLCwrrZWJBIpqJqS6kk5Q4vNLU8TJWvXYhCAq1NkLSA9qU4kv6K8XPFNrYxfyUYGwtvcZcSI+vr6c2fO4jje2Nj4ITtbLKFb9+45OTkAgGo2Ozsrm8vjKogVhJUlDHTKRBsF/sDlcoRCobz1TmKIv5zU0dHJz8tbvXZNz549NTU1iwqLli1fDlf+PgwPD70VUl9X5zDMkcVinjtztrSk1NrGuqK8/FJgYHFRcc9ePce6upqaml6/du1MQMCDsLDVa1ZbWFrKO9HU1FTy0vFxcWI51tbW1Wz2gR9/6t69G5PJzM3NXb/hW0nX+Wu9RHFQ0M0yVllFefnDB+Gyl3B0curevcelwED/U6fC7t3zmudN2E8JunGjvLy8uLg4Ly/v9ctXR08c19bWDg8LCwoKrqutNTExMaVS1dTUxowZc/3q1ZrqahaTFRUZ+euRw7Bhqqqqnkc84zfz36Wm5ubmHPDzI5PJXbt2fR7x7OrlK3l5uXb29vfu3i0sLJjk7s5mf5QtLFl3oUBw/szZoqIig969raysEhMSJM1SWlwCq+zo5Ch2C11dXREmmjlrltz1VS0ZysbGhlBbZkmp7OUAAPJqB4ezW2VYAIAC2z4Mf3jkt99O/XHy3JmzN2/cLC0tqa2pvRV8S/J0QmW6d+9+/eq1qqoqW1tboUh05nRAYWGhnr6eqalp4PkLKXS6mpqanZ2dpqamWFspxQjF6urqXrl8qba2znao7cePH0+f8i8rKxtqZ287dGjv3r1P/vF7xJOn8fFxzc3NfD5fS0vL2saGsGpJiYnXrlxpUb2szKzzZ86InQGaV3Fz9+jZk1CT3JycFmsHW1BBEAAAxNJoly5elLWAMcVYUg1C+Q4Ow/wOHFBwUyvjV2yZyEChUGRvc2NjYy6Hc+b06Tu3bxcXFWtqaXI53LleXgAADU2NgFP+jx89rq+v19PryixlUs2odnZ2skLkVdbW1rZfP+lAZ2Bg0GK0kefq9GT6hfPnWCyWpqaGUd++Xbt2bcWqEggcgoHw+Xy89QgEAmYpE87DthmhUCgSibgcbhmLhWEYYRkMw8rKyuQdldSnvLxcQbGp7u6/HfqFw+HA6V3F1NTU8LhcqZ0ikaiMxYLLJyR31tTUwO2KigqxQQgLKwlhlS9dvJiUmNjas2SrIKutghPl1a7NhpW1rVAg+P34idLS0pKSkrR3716/fOV34CA9md42ZdpAa8U2NDRUVlbC1RHKuE3baLG5FWuiTO0+PwgQylfmpm7R5vKEEN7mdXV10ALf79snXlUCm6OazYad8VbFihYDnZIS2uwPcr+clHwGqqurt2EYjkwmiydz2wyctdDW0VbwETyJRDI0NFRGn969e7cwcAxwHR0dZRTT19cnnB6QHX5VUVERF4YLBhQUVhLJKuM4XltbSyaTGfkMxR83KmMoQm0VnCivdm02rKxtw8LCGPn5ffv2BQAYGxvDd1WTfiZtVqa1tFaspqYm7MLLviMTuk1r5zaUbG7FmihTu88PAgrkK76pW7S5vMhAeJuLu65SA2PiS2hoaLQ2VigOdEpKaLM/kAHir0mzqsqqAkaBeKr3ayHoxo39e/fp6elduX7tX2nY7t17PH3y5Nu166wGWYlEWHU1e5K7e48ePf6bjvqFN/eXjFAozPnwAa5r/LrucYJOGK7Morz/APfv3quuqYaP9+kzZnxFmnO53IinTwcNGgynN/+Vhi1jsWJiYpoaG/ubmzs5OcHltP9NvvDm/pIJvRUCZyAtLS1HjByJAjcCgUAgOg+USAGBQCBQ4EYgEAgECtwIBAKBEEM8yVNSUvLyxYs4WuxAi4Fbtm2TnYG9cO58TXX1d7t3tbtCbZPMYrLC7t8rKioCAOA47jPfF36b13F6/ncQ2zA3J+f5s2fZWdknT/tLbnd+c3cCyUlJTx49Nh8wwMd3fifbGbkcoi09bmVy57Qhu5iStEEyhmHr166d6eGxZ98+Hpd3OyS0oYHX0Xr+dyDMpvaZybTa0NztmDtNsagOTYOn4NLIVxGtQPabnBQ6fbCFJf71UFhQYGbSD36kVM1mUykmb6OjcUQHcPHCBfF/hZbc7mgSExIuXbzYCaIkj453df39+PEvsxaI/zgEqctkc+fI5hCSzLBFmEFKCsLsPoSZnCQlK5Mbqba2NpYWq66uXlxUVFRYWFxcLPVYksqmRphDS5lESv8+lMxQJTebmsJPGJRMVybVQIQt3mLuNFlHkpeYSrGodkyDJ+tUUsJl7xolPV82hRsCDZUQ5M6RzSEkmUaLMAGVFITZfQgz90hKVjI3UkV5eUoKnUQipdBTpPL9SGUCk5dDS5lESgAANpt9yM/Pyd4hOipq/569bmPGwpQZrbV4e8n5fJTJUKUgm5oClExXFnj+gqRweS2uOHcaoSPJS0ylWFR7pcEjdCpJ4ffu3pW6a5T0fNkUboQ3RQGDcTYgwHmYYwOPl56WNsHNLTgoCAW7f/lQiWTuHHk5hCTTaEllkJKSRpjdR0HmHknJyuRGgomLbAYNhttSQyWS0uTl0FImOxrkz9u37axtHj96hGFYzNu3VIpJeno6/H83YffuRzx9quRrjjw5D+7fXzjfd9d33338+LFzXriUyVAlL5uaVGa1tqUrk2ogeS0uL3eaAkciTEylQFT7psEjdCpJ4bJ3jTKeT5jCjfi/swkEQ4dYB98Muh0ayuPx2vwvohBfx1CJzIQJcQ4hyTRaUhmkpCQQZvdRkLlHUrIyuZEUI5XuizCHlvLZ0eJosf3NzSdPmUIikeD/3FFVUQUAMBiMx48elZaWKqkVoZyE+HgcBwf8DnLqOT/s2985j21lMlQpSJmmACXTlUkJb22LK3AkwsRUraXNafBadCrZu0YZzydM4UaIKpnsMGzY7dCQ2XPmaGlptflfRCG+jqESWYqLio8fPdrY0GBrN7QNFyDM7iPO3AN/KpO5p93/KYw4hxbMgSQQNM+cNu340WPyhulxHI+NpU2ZOgVqkpmRqaurO9BiIABgwIABhP+srlVy9PT0ZnrMopqZrVm3Ni8vr3OaX5yhqry8XJyhKi42Tl6Gqs80davOUqbF2+BIbbxPZNLgbduxfefu3b8ePmzv4CBbXkmnaq0dvLy9Y6Lfwv/QryCF26enjpWVqipZ+VR/iH9P4P78dFCE2X3aPZNTGxDn0FIyO1pJcTGLyRo1ejQMvreCgzds2tSGu0KeHAtLy09TZKVMeLQzmr+dMlQpaerPHNOT3amkI4lTzCgQpeRRJVNbyXOqz5zMUCaFm3gCo7qanfbuXYu5VBD/ksAtmTtHXg4hyTRaUhmkpCDM7qMgc8/fcncpkRsJAMDjcUUYBkuKMAw+Hj6dJSENIptDS5nsaACAWFqsgYHBgIEDAQBBN24YGRktXS53yi4uNu7m9euEd6liOSKR6G109KYtm1sUlUJPuXn9ept3imkxQ5W8bGpSybRkUSZdmVQDyWtxebnTFDgSYWIqBaJkj35OGjxCp5IULnvXKOP5hCncpMAwrLm5OSIi4scDB1RUVNLT0mG+BXg04mnEyxcvUOD72pFOXSaVO8fYuK9sDiF9ff3LFy/CNFqFjILgvyegkumh9JDN7iMvc49k7i4uh3P5Usu5kQoYjDOnA4qLinR0dCwsLC9eCExMSAAAODk5pb17J5nui0QiEebQYiuRHQ0AEHjhPI/XMMxx2Nvotx8/Vv148IBkdzs6KkpHV9fO3v7TDXba/9QfJz1me+h369YqOXdu/znTY5bkf46XJyrglP/VK1dWrFolmc9J+Z1iFGeoktD0CygAAAHmSURBVJdNrbGhIfDcealkWpIok65MKk1dXGysvGxY4qRrUrnTFGQ7I0xM1ddYrijx+1C7pMEjdCqx8LIy1v179yXvGiU9XzaF2+gxY6SMP2bEyFhazLYdOzQ1NbOzskOCg+fM9ezRsyc8umfnrrR37zznzkWx7+um3fM2tSqNWTtmclIGwhxaSmZHc7J3eBgeLi/ZmN+BgxcDAyXn9M8EBMBFBcrLefXyZX5ePkwZJV6rIE+UUCCoq6tr8872TVP3+enK2pCqrUVHIkxMpVhUe6XBI3QqJYUrWCiiTAq3ajZbXF8+n19fXy95lMflyvoS4quj5X9I3y7poOSlMfv8TE6tflDJ5NBSJjsag8GoqqpycHAgHFUsYDDiY2P7mZqWTZnSx8gIAFBVVdWrVy/JFLQtynn6+MnunTuhbs3NzU9fPIf75YlSJZNlc4kqv1OSdslQpYypP2eCTnHSNUJHIkxMpVhUe6XBI3QqJYXLQ8kUbt26d5dsTakG1dJGX9X/G/gPZRJpcw4tgUAQeuuWto62npzHDNXM7MHjR1K3xxxPz1bJmTx1CuGUIKGof6upEQpAKdwQ/+8E/Hc+nG1zDq2PHz/m5ebB/ou9g32bFWgvOf9iUyMUg1K4If5zgRuBQCD+HfwPexCzp0B/17IAAAAASUVORK5CYII=
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
iVBORw0KGgoAAAANSUhEUgAAAMwAAABFCAIAAACJ/561AAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAADdBJREFUeNrtXD+Uqta6/+blruVOJU3WUEVekSWd3Epeha+SW8mr5DXRJktfJak0HZ2m0lSSSjpJJbeSVEMnt5JbyakklaSCs1bWYqfiFjozOuKIczT3nLz962YNfMLmx/fvtz/ukiQBAoJb4j/IEhAQkhEQkhEQEJIREJIREJIREBCSERCSERAQkhEQkhEQkhEQEJIREJIREJIREBCSfVSIHN308TUt+pZhBxefhT1Td6JzRwW2YV33agnJbg3sjtomU2HQNY0yFcbpjdyLqBCYyiCq8NS542ie81XVjv6IxUkIroB4Nax1HsKsRy86jVmY+dhafxlnvZBw3qqP11mPXg1rnYf45qtDPNlVAqWlWhWlQmV2e1GEM7onxCsVSzWDjO5UG+CmzGS9DlaWfVXzSbj8BBCYWiBKzI2sM5IcaaafiWO6STezcx2AFpuUYXiEZJ9Awm8EXIW+mX2a5yPTOe/LsGfalMRdlBVSnIhMyyck+9hTfs/yKf454/d1iaXv7u7u7u4YSfcBAAJDpO7u7hAjm29ItBHD036GSjByHcyyF1YeNMdElnvb9P8vhCQZQ6KlW75nOqzaRq4PKHItvzIYiDTgwMOU/PxsmabpVUbcf377z3uxt82PaEmVS0i0TIlO94SGh1Hk2CC3ac+NIsf0JV17OhjRDPh+BDwNgF3DcAPbDGS1ErgRBb7lUO1Rm0M4cAPEUOgF8QzDwQi7NhbbrO8G2DUdXjOaj8EdUSwK/AiAuuHikcowU423HPYXcTgTcvnadFu8rYel+/pDmCTrcbnQWryo0cJZLQ+Qq043SZIkm2mt3Hk+JH5o1Lb/SJJkPe3PNttThNx9fR7Gq6FQqj/9P0mSeNktlofrJEmSzaw7XcfLbiFX6m4Nxg/1+9JwnSTxQ71Qnmz2r2Iz609W8fagfE6YbOLNpFasDld7x6zH5WJnGZPq8t8fEhEvc+BZPi33dhk+xvhXbxdnjkMUJarNAvz+s6p7AJ4+ipoKnxrIIsw0RRoAsG/7iG/yFGIV2zXkA5/3HCppWWQi14743s4gxlHk2btgig5+A2NallkEAIHnAdcWaUQ3Tc9S2D929QjJsuXHLM8g37QxL+8S68C13uVolgKgKISjo4QJcT21DPBuoJrmwGB6p/oKFMvTCAAgsO2IkzkqveWB0TYO0jxHRY7hMRJPP2b77u8MTyMAikY4wIfJ3DZVjBzDZ2Q+tTbBPkY0Qp8CybJJGZcZNJzoYyKab1sB98QxS3MKTbVCASCGgSA4TstpaVDPw/uf/kd2xd7ZvkJgm088wJ5zkObjKEI0Qz01KgyXFnfVLHZ1KxIUmQVANEdFfoRTkz6XqmzPwL7jHdoOMM3Sn4AnyyplXFJSsRXKUHT/o+FY5BgeYrZeBzuDUdTWBzwCAMSITGB7xw+Xqqi9IgDwinKqr4C9kchJuo8DS3cQx9EAgD3Dig5cS+AGtPhYNmLPdH6l2O2F+IZqs5reZrbtCA5c7/nF9HWZqww8HDm6g1mRQQAQWIZ/YDvyfKrCUjddumtUl5GlGpxqZGpGYkdpB6ouZbgrSlTlZlurGG3mI+EYLUquYXjY93xOt5uPoY3mJVpzA+CPrpOV2yXNVeWTjgIhRNF0ZBsmNbIUzdR1DwHFNQ+q0MCxkaTRTy7PjgQZm7qBItfFim2J9ON7KfOR7mF5S0BAFEUz4BgGUsyRbuh6QGHEtg8Cd+RamO/deoGvUHj1hcY8s2y3X1hlsN0RGpklwZuWl4tW4b6xOFGEbSbV6uRRMYzXs35/sgyTJFkNhfJBKfeWRdhMa8/Gk82knH9RQx5cpdBaXFAphvO60F999Nrl5VLGJTGTa/PeyP4IUjPftCNOPtXppGWVNY3tbgnsacp337V7TuTrPZ0dND+slMOebjDqk/eJHMOjJf6Ea0S82oxGVpD9rnSktG9ea34oyd4iZVwCRmR9w8X/5kipNZujdzjQB6ckRMSrSjTSPQyAuLZaLzHRSFYc2Rh92OuHXU0N2uqu++Gbvaby8/vI1rRTNRHdHIhmxtfS11VbGkjU7VfwAz3hZiJc1Mp7ihTxolMu5AAAIF/aNirjZacIAHBf3tvbshmXS93VJ9GwXc+G01WcKfZm3Oqznma0eBgDH8bj8znGZj7cxvTb4y7DR/Cwb+p24JquqMrYDRAKbAvkkcJTgF2FazKWqzAZpQxsN+VgYG5T4ciWmf/+6X15snGaNABAoIuSN7AHe54RWyKr9TyzgoDgE8VfskQLI6goIoz+T9EkV5MpwIzDyWrFHXEQBRgdBsvA1FxOabMI2xYt9ka+JVnyKErr31AVtVf86bt/qANXHnEIuyMN2uaL2IsoiCKc0lUPzHZz5J2OpIgfGAOeIs/4UyAZUKLEYrfnl9qGSD12B9/5HgYOnZMyejspo5lumm2qVfV/f9ZVSzUrzsDiempaTpvKJFrSLOniG/7tt9++//578uCvgm+++ebLL7+8BskojgPsGA5VUZnHxo3z6/1WsUiVMuCclLHPFLV5//OPf1c1q2kFTe04Kj5LKlfB559//vXXXxN+XAVffPHF9Zqx2DMd4LVdBe8Zml9StmGN5qjITYtmWylj9Chl+DSfXv8jvtcr/fjtP7+TBjXDO66mT6sebwuXn3322VdfffVxPKPA0l2uKd5K0wlsw2Uk8cRsS+ToNi1Ll0y+vG7wQ6vL9bAExV3TLpw3isJT+RcvW0Vhr7G4ntRLQn8Vh/P6fa667dFuZv3p+pU+ZDir5QAKnbQuYrxolWrzMPnzIXzo1vu33WITr8aNbmqdGS+H9e7lXe7TBjfzfqszXaffTiZPFjimXxIpWzcc7Lu+aFpPbcm3SBnHOZ8iFYJK6l4Y3/HoE1sTPkQHk5i//f39famc8lJiHEX+u1/eb//KCVPflq/va7CjjqiekbHBGFnNHtK0SytsxLZ7tKTa/OjwTOxpqt/WlYuX9ZRBwIFt/PhDgGVJT3uKmbSHWr54Uny4TMp49mThYtwfztdb31iqp3ur1VCoz27gx9YTIQf3r6lh4Xox7dYKAMJkc4PfH1cvEJaScFqrz7Mt8WpYLtT2lmwzrQnD9YvIUa8OLxibO2vw8aZmk3TPnIFk8aJxf1q2S5JkM6nXZ5sLSRbOBAAo9lfholMW0kcF44dOrb+6TUTZTGt5yNfOXHe8HNZq12fZql+uXsCxC0i26heh2N1fs3BWKx94iM2kKlzAsfMGnyLmCY6dJdlm3q+XcpAvN4bzzSuOoZExwu95soeuUCwJ1Wq9n35quOjW+4vbJS3hrJ6H3J72fKrr3p1uru3HyuXsj/kSkq2Hpbzw4nLXY2H/18JZtZRdo8lg8MmNnSTItfb4Z5MyLlBU4uVkG0xvmns37gHS9knc9mfntUL9eXA7XvaFYn6bARZ3EXw1LOcAIF/cJiJZSbYelwuNlyPh8aJRrD6tebxoFYVpmP11OGcwA641rURV2u1MqSM/0jNuwGgqt24hUBXN7Nj/9a08qDi9K4v8p6ebIPICRFN7d9qzXVFh//rDL0yzt213s01V0s22k5rrn5xuAtsA5eiUw3mkl7NVu96EbvqAAtuh2zK4HvZtC9r6gM1g8A8QyP8Ec0jdIkCxc924/Np0U7zsFktHSc1mIgBAvr4NB+vxwUa0fU92eropnLdaaQ7mYB7peLYqXo6Hj79ayhU6izhedEql1jzMZDADyEhcEq+GZYBC65qbI8PVYh3Hi1bh+YGu+kXYjq4tOykkS8KHeh4AypN1Ei865f2Cbp9k4WqxiXcbOgv5TC3ElyQrHpIsXC43u3y5fl/I0ii4lGRkWgkQqxhjIfhRMfzrBeJXppsQxSAcHH1wZTcR8A91ZBkDh9/FzTTL56ebXu6i2ZtHOp6torajBTtZR86QNlw64ERItiUazXe17F/DOcqR0r4mcWq6CSiWxkGUvlsgB7/8ICnBqSnN/TTq9HTTS/F3X5k7NVsF4FtWxO6uN/LcIKNBQrJMzXd30DYr+pt3BXlaWzWPH9vJ6SagWJH2HP/EbgEAJKqn+J5tuunFhRzMI72crcJOr8LJVoQ9y/BpnqUAADuGhbMavJpA/idGYCmKr5ga81YDnmlSisGnbBA4Nd0EdIUH1Yvg6EEhri0XbXR6SjPTdNOLC3kxj/RytgpRFEP7ph6wuiFppqbTALTYFqmsBkl1eVbwrVXPqdTxZptph4vpZDKd9Fvd4Xgy6dbr41WSJKthNa1keH26KVn19+SyeDnp96erOEniZadUTREYLpCVjptyR/NIB7NV1zBIqsvXerEdoX5uteNFvzMPkyRez2brOEk2k3KhsYjD5XS6CJNkPemkWlh1i/nqa9LovFHbaWnxQz0PcN9ahKuhUO6mUf7tJFtP6sfN7ws/EXreICHZSfGyLpz7zGu8GteKB82EeF4vnusbhItxo5yDXKnenZ2m8GbWam31mng5rBaLQrVa656QUt9KsvWk0UjVxMKHbmP8BlX4pEFCsrRmab9aHaavchxu1qvlfNpvCPcAuZ2AEi6n02UYL1pFYbLZOrYPle7j5WSYbWNBOG+0Lv+A8KvzSNlnqzIafAVZppX+hPVkj+e/9yCX8r/ff/99/898beabEgXga3LPr1Ro7HsBw7MArNwkUyrZ8P+SZAR/LEifjICQjICQjICAkIyAkIyAkIyAgJCMgJCMgICQjICQjICQjICAkIzgY8C/ACrjPpcVl6uXAAAAAElFTkSuQmCC
iVBORw0KGgoAAAANSUhEUgAAALcAAABFCAIAAACHVuDaAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAACnhJREFUeNrtXC9Y68gWP33fft8dxzjiiCOuccQRR1yzqnmKPEWfIo6si2tcs6pZ1ThmFbmKXEUcs4pZ1VxFVpGrOk91UDxR/rWUkkIvcLnz09Np5szv/Jlz5kzj6uoKJCQW4l9SBBKSJRKSJRKSJRKSJRKSJRKSJRKSJRISkiUSkiUSkiUSkiUSkiUSkiUSkiWrAqdJWoonh1U5yWoM+4AQRZpQvtoJyQsnfF2WCBZ1UtVU0ZMjFUMvgyDn73pDeVUWjBar/Mgq9UJuGniFUyLNxMRLypfMcfV6GA97rf2TUe3xw15r/2R89V4xPuvvbm8AbB+NVjXl6Hiv3T+vO/pisNs9G9eceHeJiR9gCVvC8yR0DdRoYMPxQsIEgChI5NlKo9HQ7I4f59XC32dBZnpmfTXRHKcM4vK9WhKkdxLiNz+t0NLGoXAdtfZ4wauaThmbnkJeYJqXU5+T1ifYPBhOaXx3E9baT+v8xWBnu7cknUdHra3u8Or94mKwtbYqWzI+3d9qL2M7z/ut/dPa44cHW63nfulScYkoCL1cM+z7bK9Y9hV0R38q1OCUVLqpLEdhrFsozUr4GSCKNMe2jr7X/KqllYQ970CwFEvKLP8Ghq2hqbUxaDo6flIGWYmNu7C1TGxNaTQajUZDtSeRVUUs3Gg0kOqkt5ZR0VWesTqGkuehYy+A42fV99zkMnENFSE9pHkSxXEcupYTLbMpnFGh3YlWUM9QUaPRaDSw7lEBAIJ5WqPRaChG+IzdRpqBiudq3HLmFaA5FQSNz/Y3YONgWMN3bG+0Zszpea8JAOt7N1ZzfLrXbB1dTNvJbrPZO/8xPM74uLW2vr13OPnci/7W2vbh9GrG50f9QX+vtXd0dnI4ODw67O3v9k5H15LcnF3p6KS9BgBbg4s7r711cBuwTnuci5NBfzAYdHf3Bqcng36/f9BuHdw/K4yPdx5sQU38sgzZUwafdBaHIb5LayT/rNn20wEXrwQoM9ZUdYNW8OvnJEiDzFGgSkNm+tG0U0IYiYILAPQDOA2EgCPbmkgDqxiqkgMoU17X9CyI/uvFNosdDEKluhOYLNKBVwLN+BtsBv7mn7/9FYTMiXQkWBRDJ53nlASLCTiei6EUkeagvAjBj2MhpmUJ/Hmi/GUZv0kv190oCo3bv6lI9ls87YIWyPBh2GEF7sbn378ESeH4kETcJcZz2cBzvxMu8E1I8+LIUp7M57hBxuebc6TYYdxZvFaEVXzfH3MxtSvYsjXB/LLZIRa+HsG/loUAHU1YNnvMc4Od4N9fkiALUpOGme4Hc5cgwHBMDACizCvFcnSEUMTYvIHPQX2WlHn+7dM0IzgjFPS4Tg4IYyQeSh/pfrD1+3/+CoNUQ0T18wdGSZQCKagGdbAZEvPlh1uPpN6LZli0KVjXQVBCsRlcL7Si9Nv6JFzDChIPD7aKHbjrX/74HMSZm1VubKJHwnz9VpXBSObHwIILhJ+lhbWj14qmX8GYClNFQejlpm0o9/LqSZKQ2OuEcZzEnu2Sm4gRqSpUc073ih221+B/f/7qMMt/mEsRvBKKpsCHwWQbb3StIHHZ9HwdASBFx7yco0iG7zcB/v7NDrHnak+eLzKuXR84ecGqGaf/XFHWZQmnhEHTuccIEEWaf1s3TfXOXufCcl3HVCgpTce2bfuWVEi11CovxBwbEPibAGB43hwN4EWJTa1mIk4sxHfa9ZmJxRPmvcqzr1ifRGg8CxMlSLwJZbCuA5uX7VfdoPUJQHF86xFBCOqbupNxUWSkVAwNA4CgJBNoyipTrlo3p0xRJF4nrJtmq+FxyjSK0iz9cgnrWRTijudogiYxydP4HwCWRLHodEwMgHTHmmRQhBGqSNFc+35hxlZiVoGhPkyxdpoxCxxlXsCcCcOvlYzkeejFCw6ISHXD0FqlVRIs9vzo78sycDs89HHih9m3b+C7qh/aPArC/PIf5nWUILozkhVNy6aF84RQUbLSSjPnxoUjzTF4UghnNsgHbHn2RmV6j8dsCGNVKdOk0hJix2mcKACK1ZliVUkL5c4V8CIlf3ymhkvdOjJZ5bHwZHA0HI+OWhut49HV1fjs8PhiOvm6Mzi/OxN2u4Oz0dXV1bC3vdUbzq8+tLffdep1+TpNa23z0RWNT/e2b9MCV6PTfrd3fD4pwjTbx6OX5V6Hve32TOp1fNo/vqj14xWyZHzWbbW7/X6vt7/XHQwG/cOZUtT4dL91XZ4anx1sAHzaOR6dD1rNvfklwPNBe3d1lbT3UB883V1f312wsReDdvs6YTQ62gaAze5wdLq/tT23UrcES8Yn+63ucGY7zg6Pa2ai4HV16eRgtz/52PNBu7m5tbPT2jscjudzZHf38OLjUOTiuNtufoK1rd3eAg0+H+xep8JGJwfbm83tnZ1295E6em2WjE4P2t2ZkaPTweFZXUMEr61O50e9R2gxI9PexB/9dBid9Pv1rlfUvDkwPhv06hqNR9CQr9xIrLbaJyFZIiEhWSIhWSIhWSIhWSJxP/Ffpx+HU5IWQrLkR8Db9eNgwxSRn1avtdIriR+0H+di0N49ep3ktLQlz8Zb9+MotgtRxF7D70iWvJAqCK2OJEmquEt0tWHTVfP4NWgiWfKOotZl+3GQbmNKXiGK/eXNpMJpkiH75l6MKGihGPrzu6h5HnYiuuAWktaJVnsLaRpl4joBYTjII4UWAnGaMj1MvNrbzhkVmrOcZUKaDiHloCsflCUl6XjEt5zJrd4isi0alan1bJpg03/57egXQHWTXOGKmyVVEndUABsMzUud/P4dPFGmSV6xlFmBI1iFUJVn4ESegUFUrELqzOVlzgihAgmWC6ujlawSLKVGTNzr2AVhDXM6p4nlg3gcztJSsW50oKJpqdk6hh8b8/txprIclelYevmHFwvLdWyn4+LYDZgAAF7N3nCv0pjpbsd1O7YIbZ/bro2rkt+/QY0wCP79n+94I1siGGF3/QacpYV6/y7+szzOR+vHEUJxJrdiq6IA3bcUpLhp4T74aPigLBFFxoQeXUtcFCnDZr1L0As8zkfrx0Hq9U1yTkmpOnOVSHCBFPRBWVLRrNS8Gw9T5jnXIw3KLAPLUqs8yUokWM41XYEipUacOB+lJWfSjxNP9eNMejoVHXM2r0GTU8KwOemMFSUtFePOnvFK3PRtfLi4hLO0uLyRBs/C+KtqaqjMGMILm3qe2oEP1Y9TJo5uhoXgNKFCmzTSVBkp77slXlLQbw84nMael3yP/Mlb2BLBUoaaehpGXEMCVC8+CAmJQXM6eHFTz+KT8Mfqx0EYKypQQpCXRglJkgoLpHXup2ZFkVX67QTAGSEEG767+oPxGxRAhgeb648++vNEU8/P049T6/Gkpcb/UHWcKs8r7bEko6hoStKElKatsDRJkkIzP0ybsCgIRYb5WJiOjMDlUe3HeHgWV65vvMqTHW+gTztr7/nhmvfSj/PkdHvt/vCVXrB8g06LiuaVZv7wKbTvFtrnMQGns7jqx2lMxFODVgfZjyPxfjP0EpIlEpIlEpIlEhKSJRKSJRKSJRKSJRKSJRKSJRKSJRI/N/4PR4r+eoqKw2gAAAAASUVORK5CYII=
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
iVBORw0KGgoAAAANSUhEUgAAAuoAAADkCAIAAABBkJaoAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrsnXdcFOfzx5/dvcJxFAFBOoenNEF6FCkKdo2xYklMYldiL7F87b23xMRYsFewYItdE7sgVgQUkN6lKHfC3bbfH6v3I9g4OFBg3ia+7p59dm+d29udnZ2ZD8ayLAIAAAAAAKg74GACAAAAAADAfQEAAAAAAAD3BQAAAAAAANwXAAAAAADqKDwwAQAAGuTFixcZ6elOLVo0btxYLpfHxcYJBAKBUCAQCBBCFEmRpJIkSYqivby9wFwAAID7AgDAl+dkRMSm335fuWZ13379Cl6+HBgc/LGZz18k4TgEgAEAAPcFAIAvjY2NxNLSkmEYhJCllZXEVkJRtNZbhATBUyqVCoVCqVRSFMWFZAAAANQFg74vQAXkcnlOdrZEYkvwCLAGAAAA8BUCkduGDk3TY0aO2r9vH/f24IEDHi1dO3fo2Lljh6SkJLAPUH2uX7s2cdz4Xj2+W7JoEULo1atXO0NDHz16BJYBAADcF6CKJCYkXrp40cbGBiH08uXLpYsWsyzbwtk5JTllycJFYB+gmuwMDR36089nTp+OefIkJzsHIaSnp3fr5q1pkyaDcQAAAPcFqCKZGRkIIWdnZ4TQsSNHy8rKRo0efeL0qRmzZl2/di0/Px9MBFQZuVy+YvlyP3//a7dudujYkRvEMKxHz++Sk5PlcjmYCAAAcF+AqiAQChFCRcXFLMseP3YMw7BBg39ACHl/440QKigoABMBVSbmyROGZtZuWG9ubl6+yMjCwgIhlJ2VBSYCAKBqQOVRQ8ephROfz5/wy1g7e/uE58+D2gdxl5bUlFSEkJ6eHpgIqNYdEoGLxWKEUHn3JT4uDiFkamYG9gEAoIrnFjBBA8fQ0HDCpIlxcXEnIiLEYvHEyW8zEs6cOW1iYmIGFxigGjg4OhI4sXbVaoZhMBzjBhMTEtavXSdt1kxHRwdMBABA1YDCaQAhhOJiY1OSUzw8PZqYmiKEWJaNvHtXJNJu6doSjANUh+1bt61YtszS0lJJkhiGWVtb34uKYlk2dNfOtu3agX0AAAD3BQCArw6WZU8cj1izehVXdoQQsrK2nrdgfmBQEBgHAABwX4BqEXn37oukFzKZjGVZmqFJJUlRJEVR06ZPxzAM7ANUn6LCoqysTHNzCwNDA7AGAADgvgDVvTmePm3a8aPHPrg0LuE5n88HKwEAAACapZod3qHyqKET8yTm+NFjYrE4eEB/CwsLLZGIZVmaoimaYmgaxyC5G1CPuNhYDMf5PB6Pxyd4BJ/H4/H5LMtSJEVRJPcXSZI0zbi0dAFzAUADgabpsWNC/NsG/DB4MELo4IEDC+bOo2laYivZsn27VCoF9wVQj7zcXITQ0hXLv+3RA6wBVJ+QUaMzMjIqMxMUpwGg4cB1eB/804/ovx3en8bELFm4aOee3eC+AOrRtJkUIaQt0gZTABrBp02b27dvC/h8/rv/+Xw+n89jWUTTNE1TFPX2b1CcBoCGw/sd3seEhEybMX3blq0rly/Pz883NjYG9wVQA1tbW+9vvI+Ehwd1aA/WAKrP8lUrwQgAAFRA1eFdv1GjD3Z4B/cFUJsxv/wyfMjQQf37UxRNkiTDMEqlUqFQKJXKazdvEAQBJgKqzIply5o2lfYfOEA1UlpaOnH8eA9PzzEhIWAfAGggaLzDOzx4bujI5fL/zZyFEIqKjHpw/37MkyexT58mJiSkp6Xl5uRQFAUmAqpMakrq9q3bhEJh+UGRSCSVSn/fsBGOLgBoOGi8wztEXxo696KicnNy2vj6Tp85o4mpqUgk4nITuBQFSE0AqsOLF0kIIWcX5wrjzi4uCoUiKzPT2sYGrAQADYSQsWPbBQZW6PA+fMQIkUi7Cg3GwH1p6DQyMEAI/TJurLMLVLECmr7fMjJCCMXHx0ubNSs/npKcghDS09cHEwFAAyEzM3P4kKGb/vyjS7euqoZzGIa1at26pKRk+9ZtuTk5QR3a+7RpU8kNwsOjho6Tk5OOjk5aahqYAtA4Dg4O2mLtpYuXPHzwQDV4986dbVu22NraNmrUCEwEAA0EiqQSExJ279zl5ebu7tJy1vQZcrkcIcSy7JAff1qxbNnOHTt+/P6H/fv2VXKD0HW3oVNaWrp65cqrV65uC92O4ThCiKZohUKhUCiUSoVPmzYgGgBUhxMREVMnTUYISWwlpqZmWVlZaampCKFde/f6+fuBfQCggZCSnNIhMBAhZGhoaGBomJSY2H/ggGUrVlz7999hPw9xdXMbHTLm/Nlzly9dunHndmXk6MF9aeikp6UFBrT92NJniYlVa+cMACquXLq8cvnypKQk7m3Tpk3nzJ8X0LYtWAYAGg5JiYmdO3ScPW/uTz//TBDEgf37ly5a/Dj26dLFi/fs2n30RISrq6tSqWzl6bV95w5PL6/PbvAzuS+vXr0iCIIgCD6fj+P4+y0yaYpWkkqSJKtQ9QR8DVhYWto72NM0o6WlpaUl1NLSEgiF9LvGYjRDEwjcF6BaBHVoH9ShfXFRUWYmSDYCQAOFx+MjhHr36cM14+jUufO82XMKXr68dfOWpaVly5YtEUICgcDY2DgnJ6dSG/z04q4dO+Xl5ane4jhOEASPzydwnKIopVLJMMzb2/SkRGgQUhfBcfzMuXNgB6CmaWRgwOWJI4RYliVJEuraAKDhYG5hjuP4ndu3u3TtihC6FxmFENq4YUNiQkKHjh25LIXioqL09HQTExMNuC8tXV1v3bqpJdQSiUQUTefm5DRu3BgncJZFLMOwLEvRVFFhkZ6eHkVR4L7UD6qpAgoAKhITEnr1+A4ncAInCIJgGIYkSZIkuY4vCckvILMKABoIfD7f189v4vjxgYFBMpksKjKyuZ3dmVOnEUJXLl+eOmmyr79f2KFDQqHQwdGxMhtUI/fl8sVLo0eOvH77Vvn2MgzDBPfuY2pm9sdfm+HrqYtoXAUUAFRkpKe38w/gzlxCoZDH4zEMQ9O0XC7X1dW9G30PAjAA0HDIzcmZNGFCVGQUQsjR0fHPLX/x+YI9u3e5urlNGDeOpmiE0IJFCwf/9FNltqZG3xexjhghJCspQeXcFxzHgzp0+H3jRoVCUaG3JlBH7o81rAIKACosLC1j4uMEAkH5tDmapvv36dvSzRV8FwBoUDQxNT0YFlZYWKhQKFRxkOkzZyKEzl+8FB19z8HBoYWzcyW3pkbfF3Nzc4TQmdOnK4zLZCUURRUWFsJ3Uxd5XwV01OjRJ06fmjFr1vVr1/Lz88FEQJXBMExLS6tCyj9BEH2C+0UcO67KnAMAoOFgaGio8l1omi5986a4qEhiK+nbr1/lfRf13Bcra+vmdnah20OvXL6ieuQUHx8fHhbeyMDA1NQUvpW6iEoFlGXZD6qAgokAjaOrq1tSUpKamgqmAOoTK5YtCzt0uPxIaWnpqBEj/toMyRUIIXTn9u0fBg5q5+ffwt7Byc7eoVlze2kzF6cWXu4eVbiZUePhEYZhi5Ys+Xnw4FHDhxsYGjg4OL569SouNpZl2SXLlkEKXh1F4yqgAKCCoqj8/Hwej8fn8Xh8Po7hCoUiIeH5ls2b4egC6hmcQOna9evLD6oESkeMHMnjNWiVHoVCMWrEiDfyN3w+X6yjIxQKtbSEGIaxLMswLEVR6j5NVs+a3t94Hz0RMfPX6U9jYm7fuoUQaty48ZRp04IH9Idjt47CqYCuXb0mLi5OIyqgAKAiJTm5S8dOH1z0Xc+eRkZGYCKg3gACpZ/maUzMG/mbnr17LVm6VKStXf0Nqu0MOjo6njh9Kjs7Ozcnx9jExMzM7P1edkDdQrMqoACgQk9f39LKigu9cK0vxWKxgaGBj4/PwEHfg32AenUrCAKln4Tg8RBCffv104jvgkA0oKHeJbzISE93atGicePGcrk8LjZOIBAIhAIudkeRFEkqSZKkKNrL2wvMBQAA8FkUCoW3h4eOju6ff212c3fnBu/euTN6xEhjY+OLV680cPuQJOnbqvWoMWNGjBr5ZdyX69euHQkLT01N9fL2mjNv3qtXr44dOeLh5eXq6gqHb11hw7p1m377feWa1X379UtLTQ1q2+5jM5+/SILoGqBZaJpWKhQKhULVhBcA6gcgUPoJysrKNqxbd/rUqdCdu3AcoyhKSZIUSVIURVG0r5+vuhtU7+HRztDQpYuXcK8tLS0RQnp6erdu3jqwbz+4lnUIGxuJpaUll+ltaWUlsZVQFK31FiFB8JRKpUKhUCqVVUinAoDy3Ll9+/eNv2VmZOTn57MsyzAM13IXnGOg/tGzVy9dHV1OoJR7ZsQJlILvghDKy83dvnUbQqh7ly4auVVWI/oil8s9XF19fNosW7li0fwFPB5v0+Y/EUInT5yYMnHSo6cxYrEYviEAAFRw4fSP1Rqcv3QRnGOgXgICpe/DMEyn9u1pmhGJuFtlkZaWFsuyDENTFL1zz+4arDyKefKEoZm1G9YbGRmV95K4OtvsrKxmzZvDN1Q/gPA+oBE0XmsAAF8Vn8gjFGlr5+fnZ2VlQh4hB47jl65e1eAG1Xt4hBM4F2Ip777Ex8UhhEyhwrbOAuF9oIbQeK0BAHxVnIyIUOURFrx8OTA4+GMz4VyqcdRwXxwcHQmcWLtq9aw5szEcYxkWIZSYkLB+7Tpps2Y6OjpgzbqIxlsJAYAKJycnQ0PD2KexbXx9wRpA/QPyCD9NjVa5qld5tH3rthXLlllaWipJEsMwa2vre1FRLMuG7trZtl07OJTrIvejo/v37QfhfaAm0HitAQAAdYgarXJV7+HR8JEjGjduvGb1qrzcXIRQbk6OlbX1vAXzwXepu0B4H6g5NF5rAABfOSzLxjyJefYsns/nOzg42tnbNeTmnzUanapi27qiwqKsLEirrg9ovJUQAKjQeK0BAHzN5GTnTJ08+e6dO6qRgLZtFy9byhW4AJpFbfcl8u7dF0kvZDIZy7I0Q5NKkqJIiqKmTZ8ODebrIhDeBwAAqD40TQ8M7v/g/n1ps2a+fr4ETjx69Oh+dLRUKj119m/w1Dk02PlWDfeFZdnp06YdP3rsg0vjEp7z+Xz4buoc0HUXAACg+jx/9rxb5849e/datWYNQRDcRfNkxImpkydPm/7rmF9+AROV73zbpWvXTZv/ZFl21PARKcnJVeh8q1bfl5jjR4+JxeLgAf0tLCy0RCKWZWmKpmiKoWkcg4tcnYR7Hvmx8D5UHgEAAFSG7OwshNCQocM43wUhhGFYz969Ll++dOvmLbXcF7lcnpOdLZHYEjyi3thHLpevWL7cz9+f63yrMlGPnt9NmThJLper2/lWDfeFS9ddumL5tz16wJFab9B4KyEAAIAGSAtnZ4TQ69evK4y39vH5fcPGT6xI0/TYMSH+bQN+GDwYIXTwwIEFc+fRNC2xlWzZvl0qldYP+2i8860a7kvTZlKEkLYI6lMAAAAA4D/o6en5+fsdOnjA2toKJwgcx1mWZWiaZZiCgoLnz56XlZUpFAqFoqxFC+fyVS+JCYmXLl4c/NOPCKGXL18uXbSYZdkWzs5PY2KWLFy0c8/u2tn/Wgj5aLbzrRrui62trfc33kfCw4M6tIcjtSFAU3R9Cl0CAADUHNlZ2Teu30AInT3z9/tLu3XurHq9NTQ0qH2Q6m1mRgZCyNnZGSF07MjRsrKyMSEh02ZM37Zl68rly/Pz842NjTV/eq/1kI/GO9+q1/dlzC+/DB8ydFD//hRFkyTJMIyqaPvazRuqB35A3SIqMnL92nW5uTmyEhnNMCzDKElSUVbGMExC8gsoKAM0ft5UlCmUSlDUAuoVVtYfyCMUCAQYhnFnUYqmaIqmaUpfX6/8igKhECFUVFys36jR8WPHMAwbNPgHhJD3N94IoYKCgppwX2o/5KOvrz9l2rQVy5ZdvHCB63w7qP8ArvPt2g3rq7BBNdwXuVz+v5mzEEJRkVHvL6UoCtyXuohMJhsxdJhcLufz+SRJmpqZEjiBEMrMzNTX1ydJElJ3geo5x1Erli1LT0uTyWQIIVDUAuorVc4jdGrhxOfzJ/wy1s7ePuH586D2QVw6SGpKKkJIT0+vJvb2i4R8NNv5Vg335V5UVG5OThtf3+kzZzQxNRWJRBRF0TRNUxRF03CRq6Pcj46Wy+Wr1q7x9PRq367dH5s3u7q5IYRm/jq9sKgQvlagms5xyOjRxUVFAoHAyMhIIBTgGM4ilmFYlgVFLaB+kpiQEB8fX1hQaGhk6O7h8dmedYaGhhMmTVy7ek1cXJxYLJ44eTI3fubMaRMTE7OakUP+IiEfDMN69endq09vjXS+VcN94SK9v4wb6+ziAgdovYFUkggh/4AAQ0NDoVAYfe8e574Etg+aMHZcaWmpSCQCKwFVIy42rrioqHOXLivXrAZVV6DeU1hYOGfW/y6cP19+sF9w8ILFi7S0tD6xYsjYse0CA1OSUzw8PZqYmiKEWJYdPmKESKRdQ4/vv0jIh/t3xcfFPX/2/E3pG5lM5uXlXeUMSzXcFycnJx0dnbTUtNY+PnCY1hvMzM0QQi/z842NjVu6ul44f37IsGE4jmdnZdM0nZ2d3bRpU7ASUDW4G7gBgwaC7wLUe1iW5XwXRyen1j4+jRo1Ki4qunnzxpHwcGMTk6m/Tvv06o5OTo5OTuUDFa1at665vf0iIZ+c7JwZv067eeOmakRiK9nw229Vi4mo0XW3tLR09cqVV69c3Ra6HcNxhBBN0QqFQqFQKJUKnzZtIMezLkJTtJe7+7gJ44ePHHn0yJEZ03718PS0srY6e+ZvkUh0514UNFMGqnNCb+3lPWrM6OEjQVELqOdkZGS08/OfNGXKuAnjVYMMw8z53/8ijh1/Ehv76TDDFxHkiYuNrRDyibx7VyTSbunaUuOfxTDMDwMHRUVG2tnbtfH15fP5T2Oe3rp508jI6Pipk+bm5jXovqSnpQUGtP3Y0meJiVBkW0d59OgRjuEuLV1omv51ytSTJ04ghETa2mvXr+tUrtgPACp5QsRwnEcQPB6fxyMOHTx0/NixPfv24gTBaWmRJEXTFE0zXt5eYC6g3nD1ypWRw4ZH3b9fIZ/j8aPHfXr2vHrtXytr6495+bUvyHM/Onr/3n0dO3Xq0q1r7dgnMSGhS8dOXbp23fD7bzze2yc/169dGzFs2Pc//DB/4UJ1N6jGwyMLS0t7B3uaZjipay0tLYFQyJWBURRNMzSBwH2pk6i0sgiCWLth/ZRpU9PT0x0dHaGuFagCIaNGZ2RkVBjs3KHj+zOh8gioT3BOhlKpqDBeUlKCENL9eDbJFxHkEYt1TkREEARRa+5LWlo6QuiXcWNVvgtCyD8goF9w8D9X/5mvtveijvuC4/iZc+fgGK1nZGZmDh8ydNOff0ibNWNZFsdxSysrSysr7ld3+OCh3JycoA7tfdq0AVsBlcHH1zc6KkqsI9bSEhEEgWEYjmMYhjMMQ6sqFWkKFLWAeoaziwuPx1s4f8GylSsaNWrEDWZnZy9bstjS0lI18j5fRJBHYisZNWZ0eFhYeFiYnZ2dSKTNsuy7bBBlG1/NZ4NwrfAYhqkw7u7h8ffpM1XYoBruS+3HmoBagCKpxISE3Tt3/X3mDEVR3bp3nzN/nlgsZll2yI8/PXr4ECG0c8eOhUsWc80ZAeDTLF+5AowANEAaNWo0cfKktavXXLl82dnFRUdHnJ+fn5iYSFP0mnXrPrHiFxHkycvN3frXFoTQrOkz3l+qqWyQpKQkhBCBEwSBEzyiWfPm4WHhjRo1Ytm33RNYxMpl8pKSEpqm1W0dp4b7UvuxJqAW4JKfDh44YGho2NjYODwsDMOxZStWXL927dHDh65ubqNDxpw/e271ipU9e/WC+hFALd7I30RG3nV1dauQDZCbk1Nc/MrewR5MBNQnRoeE8PmCvzZvfvjgATdi0qTJ5KlTevbu9Ym1voggD5cNQlG01luEGIYxDMswDMMwmsoGGfrjT1lZWeVHEhMS9u/d+/7MKrgvaqTuKhSKjevXh4eFTZ85s3ZiTUAtkJSY2LlDx9nz5v70888EQRzYv3/posWPY58uXbx4z67dR09EuLq6KpXKVp5e23fu8PSCXEtADdJSU4PatgvdtbNCV83ww4dnz/pf7PNn5Z+CA0D9gKKorMzMouJiI0NDM3PzylyV//3nn+FDhnp/413PBHlmz5oVeeeuUCgUCoWCt38LuGwehmUYmqEoinOYdu/bW4PRl9qJNQG1DI/HRwj17tOHO3Q6de48b/acgpcvb928ZWlp2bJlS4SQQCAwNjbOyckBcwGV5Mb166WlpbISGULoWfwzkUhEEASO4xRFFRYWXjh/gWGYsrIyiOcB9YkVy5Y1bSrtP3CAtY2NtY0NQqi0tHTi+PEenp5jQkI+ttZXJcjDsqwGtWKWLl9egxevyk+tnVgTUMuYW5jjOH7n9u0uXbsihO5FRiGENm7YkJiQ0KFjRy6iVlxUlJ6ebmJiAuYCKsmRsPDTp05xr1et+EA2THM7O/BdgPpEakrq9q3b1q7/j/qgSCSSSqW/b9g4YuTIj8Uav4ggT2JCQq8e3+EETuAEQRAMw5AkSZIkJ0lWJ8R6ofKoocPn8339/CaOHx8YGCSTyaIiI5vb2Z05dRohdOXy5amTJvv6+4UdOiQUCh0cHcFcQCXp1z9YJBKRFBlx7Lifv7+1tTV3p4MQ4hE8YxOT/gP6g5WA+sSLF0kIIWcX5wrjzi4uCoUiKzOTi8e8zxcR5NHS0iorK+MuAUKhkMfj8fl8Lj6qq6tbJ8R6q/LgWV09KuArZ8WqlZMmTLh08SJCyNHR8c8tf/H5gj27d7m6uU0YN+5ERARCaMGihbq6umAroJL4+fv7+fvn5+ffvnX7hx8Hd+zUCWwC1G8MjYwQQvHx8dJmzcqPpySnIIT09PU/tuIXEeSxsLSMiY8TCATley/RNN2/T9+Wbq51oqOBGqm7qBp6VMDXT2FhoUKhqCB1kZKcEh19z8HBoYWzM5gIqNw96IuM9HSnFi0aN24sl8vjYuMEAoFAKOBOiBRJkaSSJEmKoqHrLlCfUCgU3h4eOjq6f/612c3dnRu8e+fO6BEjjY2NL1698rEVvypBnv379q1ZuSr60cOvv6WkGtGXaupRAV8nn27nI7GVSGwlYCWg8pyMiNj02+8r16zu269fwcuXA4ODPzYTuu4C9QmhULh46dKpkyb3691HYisxNTXLyspKS01FCG3avPkTK77Mz9+zazdCqEvHDwQpa7ksRldXt6SkJDU11dbWtv64L5mZmRfOn/+gHlXotm2TJk+GyqO6CLTzATSLjY3E0tKSS3OxtLKS2ErK5/sTBE9VEQpdd4F6Rs9evXR1dFcuX56UlMQ9M2ratOmc+fP8/P0+sdYXEeShKCo/P5/H4/F5PB6fj2O4QqFISHi+ZfNmhJDexyUOvh7UeHhUZT0q4GsG2vkAAABoluKioszMTHNziwqXy0oil8tzsrMlEtuaCwpwAoofXPRdz57rNm6oHUPRNK1UKBQKRRUk9tSIvlRZjwr4moF2PkANHl15ecN++rldYGC7oCB3d3c4loAGQiMDg0YGBnK5PCkx8bNeCE3TY8eE+LcN4IRZDh44sGDuPJqmJbaSLdu3c1JBGkdPX9/SyooLvXA1R2Kx2MDQwMfHZ+Cg72vILHdu3/5942+ZGRn5+fksyzIMw9Vpoyo9SlYj+lJcXNzayzuoffsKelQjhg6Vy+T/3LgOh2xdhGGYHt26faydz669eyC8D1SZly9f+rZqTdM0QkhfX98/ICAwKCigbduq3ZICwNdMlb2QZ/HPunfpsmvvHj9//5cvX7bz81cqlY5OTk9jYvwDAnbu2V0/7MOlNr+Rv+Hz+WIdHaFQyF1uOP2j85cuqnutUSP6UmU9KuBrBtr5ADVH48aNH8Y8iXkScz86Ojr63o3r10+fOoVhmJu7e1D7oJCxY8FEQL0hMSHx0sWLg3/6kXPcly5azLJsC2fnpzExSxYu+oQXkpmRgRBydnZGCB07crSsrGxMSMi0GdO3bdm6cvny/Px8Y2PjWvXDKLomAqVPY2LeyN/07N1rydKlIm0N6FOq1/elanpUQB357UE7H0DziEQi72+8vb/xRggxDJOYkBh59054WPja1WtGh4RA5RFQb6iyFyIQChFCRcXF+o0aHT92DMOwQYN/QAhxv5qCgoIacl+iIiPXr12Xm5sjK5HRDMMyjJIkFWVlDMPURNddgsdDCPXt108jvova7guO4yNGjRwybKi6elTA1wy08wFqGoZhXiQlRUVFRd65e/fOnby8PIQQSZJCoRCMA9QPquyFOLVw4vP5E34Za2dvn/D8eVD7IO7uMTUlFdVYEZBMJhsxdJhcLufz+SRJmpqZEjiBEMrMzNTX16+JrrtOTk6GhoaxT2Pb+PrWhvuSkZ7O4/FNzUwRQlyWDIZhPB5PpUcF1HWgnQ9Qc7yRv9m7Z0/0vajoe9GvXr1CCBEEYe/g0KlLFw9PD64aAADqB1X2QgwNDSdMmrh29Zq4uDixWDxx8mRu/MyZ0yYmJhVaiWqK+9HRcrl81do1np5e7du1+2PzZlc3N4TQzF+nFxYV1kTKI03Tffr13bVzh39AAI5jFEUpSZIiSYqiKIr29VPbp/mM+7JyxYqsjMyjJyIQQpkZGe0DAzdv2RrUPgiO1HoDtPMBao78/PzVK1cKhUI3d3fvb7y9v2nl7u6uLdYGywD1j+p4ISFjx7YLDExJTvHw9Ghi+jZeMHzECJFIu4ZaV5BKEiHkHxBgaGgoFAqj793j3JfA9kETxo4rLS0ViUSa/cS83NztW7chhLp36fL+0ipUHn3GfbG2tr54/sL+fftatnQtLi6iKToxIUFXV4fTpSSVJEmRFEUpFIo+fftCg5C6SMLz5wghLlVeBY7jAwd9H3bocFZWJrTzAaoMX8BHCNnZ27m7u7u5u7u0dAHfBajHVMeOEeDtAAAgAElEQVQLcXRycnRyUr3FMKxV69Y1t6tm5mYIoZf5+cbGxi1dXS+cPz9k2DAcx7Ozsmmazs7Obtq0qWY/kWtiSdOMSMRVuYq0tLRYlmUYmqLoKjSx/EzhdFxsbK8e33F1j58mPjHhY2rgwNfMjevXh/z40807t7kfm4qbN27+PHjwvYcPVEXyAKAuCoVix/btjx4+evzoUV5eHoZhDg4O3q2++eabVp7eXrVcTwEAtUNlyiC+uDQYTdFe7u7jJowfPnLk0SNHZkz71cPT08ra6uyZv0Ui0Z17UV//s93P932Ji409fOjw61evFArF+XPn/Pz9bGwkCCGK/s+ftevXQ4OQugi08wFqAZZls7Kyou5GRkbejbobmZycjOP4s6RECNkC9YnKl0FsWLdOJQ2Wlpoa1Lbdx7ZZc9Jgjx49wjHcpaULTdO/Tpl68sQJhJBIW3vt+nWdOneuTbtVrVT78/ESRyenBYsWIoRyc3IePHjww48/duzUCQ7TegO08wFq4z4JwywsLPQ7dWxs3NjExOT8ufMJz5/TNA0hW6A++eiVL4P4GqTBXF1duRcEQazdsH7KtKnp6emOjo5V6N9fSTRbqq1G112gvsIwzI7toX9t3lxcVMSNcO18+gUHw80xUM0Tenpa2v3o+w/u378fHf3s2TPufE0QhLuH+94DB6D4CKg3ZGRktPPz/2AZRMSx409iY7/yMoiaFlqSyWS+rVp/rFT7dlRkDXbdBeor0M4HqCHi4+J6dOuuemtpZRUQEOAX4O/Tpo2uri7YB6hPaLYMojpahpXcfi0LLWm8VBvcF+AtKcnJqnQzDMeh6y5QffT09bXF2q19fAICAvz8A2wkNhDPA+or1VE11qyWYWWossRBldF4qTa4LwB03QVqCnNz8/uPHn21CS4sy96+devWzVsv8/N19fQ8PDzad+wAJQhA1XB2ceHxeAvnL6hQBrFsyWJLS8tPlHAqFIpRI0Z8TMuwhnJfal9oSeOl2uC+NHSg6y5Qc3BNur/OfcvLyxsX8sv96GiBQGBmbpaXl78zNNTK2vrPvzaXb78BAJWkymUQGtcyrAy1L7Rkb++gq6t76+ZNRyenfv2DZ0z7dWBwf65UW19f38rKSt0NVvfMQtO0okyhVCpqLlcZqFGg6y7QAGEYZvSIEU8eP/n+hx9m/G+WWCymafrwoUPz58z9efCPV679q6OjA1YC1KVqqsYa1zKsDLUvtETwiF379uIYjhDq1bv3zes3Tp44cT86WqStvXzVyipk8atXeRQVGbVi2bL0tDSZTMadAmr6+RxQ01y9cmXksOFR9+8bGP7HAX386HGfnj2vXvsXuu4C9Y+TJ05MmTiptY/P3gP7y6fjrFy+fNuWrSFjx079dZpSqczLy1MqlVxMm6bp9LR0Ho+wsLR8+fJlQUGBvb29at2c7ByZrMRGIuHOwhRFZWVmkiRJEDwMw3h8niqZrKSkJD4ujsszEIvFKncqMyPD2MSEx+PFPo2lKLKFszPoWdZRuG+/8mUQJEn6tmo9asyYEaNG1uZ+bv7jj7Wr1yCExGLxgcOHWjg7I4RGjRgR8/jJzbt3ajpNjWXZzIyM6pRqqxF9kclkIaNHFxcVCQQCIyMjgVCAYziLWIZhWZatudp0oEapTroZANRR9u7ew93vVjhH9+zde9uWrYcOHpj667SU5JQe3bohDF26csXK2vrQwYPz58wdExIybuKEDu0C5XL5qb/PcI+ZWJYN7tNHLpffjorMy82dNWPm9WvXuBJxjmbNm5+7eIFl2Z2hoWtXr+F6fRI8YuasWUOHD0cIdW7fITk5ecSokceOHC0sLEQIaYu1t4WG1mjbeECz3I+O3r93X8dOnbp066qWqrHGtQwrSe0LLf0ndoJhllZWluo/M6qK+xIXG1dcVNS5S5eVa1ZDZLXeUOV0MwCoAjXdW6KSJL94gRBq5VPRObC3t2/UqFFRYdGrV6/s7O2GDBsWum3bxg0bFixatHHd+mbNm4+fNFEoFHb79tvww4cvXrjAuS/xcXHZ2dk/DB4sFAonjh9///793zZtat3G5/jRo0sXLxn0/fc/Dx2CEDoZcWLZkqVDhg2dNn26TCabNnnK0sVLmtvZ+fn7UzSNEDp18tSoMWMcnZyOHTlyIiLitw0b9x8C96XOIBbrnIiIIAiiS7euaq2ocS3DyuPo5MTn86OiolQSBzXtMUfevfsi6YVMJmNZlmZoUklSFElR1LTp02uwbV1KckqHwMAdu3cFtG0LR2p9ggsh8ni899PNevXpDfYBqkzt95aoDK9evfJ0dUMIPX0W//4Dmk5B7V+8eHH0RISrq+sb+ZtOHdrn5uR27trlwrnz4cePcY1KoyKjBvXv7+joeOrs3wihTb/9vmHduqMnIqysrL7x8OzQseNf27Zy//zW3t4Mzdx7+ADDMH+fNgRBXLn2L3c1ysrKCmjj2/3bbzdu+r1b587Pnz0/c+6cvYM9QuiN/I2nm1uTJk1AtaMOoVAoNq5fHx4WNn3mTDs7O5FIm2VZhULBNc9t49vmY5dnhmE6tW//MS3DnXt219CTjVquOWVZdvq0acePHvtwfCThubrpL2pEX2wkNkZGRgnPn4P7Us+oWroZAHyW2u8tURn4vLdnSaVS+b77In/zBiEk0hIhhLTF2nPnzx87JuTc32fHhISomqx7eXtZWVvHxcWlp6VZWVtfuXxJ2qxZy5Ytc3JyEEJcaiBCiCAIQ0OjnOxslmVfFRdnZ2ebNGkyacIEhmFYhuWeLqWmpiKEuKsFjr+9vGmLtcU6Ovn5+XAI1SHycnO3/rUFITRr+oz3lz5LTPxYxBHH8UtXr9by3tZ+zWnMk5jjR4+JxeLgAf0tLCy0RCKWZTnNRIamuZReTbovcbGxGI7zCILH4/N4RPCAATtCd7QLDMQJgnsyR5IUTVM0zdSQKiZQC0DXXaCGqP3eEpVBW6xtbGycn5+fnpbm1KJF+UVKpTI/Lw/DMGubtxnrfv7+urq6JSUl37RupZqGYVifvn03rl9/9u+zPXp+9/jR4+kzZ2IYZmZm5uDgEBUZef7cOS9v7wvnzyclJgb374/jeGZmJrciQzPcC4IgunTtampmihDS0hIhhFSVEAghoVD4Ri6HQ6gOYWFpae9gX166CMMwhmEZhmEYhmZoAql9Uq2almGlfpu1XnOal5uLEFq6Yvm3PXpoZIOfcV9CRo3OyMioMNi5Q8f3Z0LlUR2lyulmAPBZar+3RCVxcHTMz8+/eOFCBffl0oWLDMNY29iogudLFi1+U/qGz+cvnD//zLlzqvHefXpvXL/+7N9nBAIBjuO93oUqN2/dMnL4iLFjQhBCAoEgeMCAOfPmIoTMzS0QQtbW1ps2//n+/nCbVZJkuRFh+eRfoE7cB545d65q62pWy7AyaFbioDI0bSZFCGmLNFYc/hn3xcfXNzoqSqwj1tISEQSBYRiOYxiGMwxD0zRNUxT19m+oPKqjVDndDAA+S+33lqgk4yaMv37t2r69e7/97jtVCs6rV6/+3LQJITRw0KC33szFi+GHDw8ZNhQhtGvHzk0bf5s2Yzq3yNLK6ptWrSLv3i0pKfEPCDBp0oQb5/MFOdnZAwYNnDhpklHjxqoopoGhgZW19b2oqKTERGmzZqo9efXqlb6+PpeDSJVzXzAMoyiKYRi4LaxDrFi2rGlTaf+BA1QjpaWlE8eP9/D0HBMS8rG1ZDLZiKHDPqZlSJJkTVxba7/m1NbW1vsb7yPh4UEd2mtmi2ylkcvkV69cKSworDCek50dHxfPAnWTsrKylcuXe7m7hx0+/PDBg2fxz+Lj4h89fBR5N/LG9RsMVxYPAFXlz02bpDYSqY2kpVOLmCdPuMGRw4f7eH/zZY+uGdN+ldpIWnt579u79+6dO3t27e7WubPURjIwOFipVLIsm5eX5+Xu7tHStaioqKCgwMXJya6pNDY2VrWFI+Hh3D/tzKnTqsGVy5dzg106dlq0YMG1f/9V/TMvX7ostZF4urrt27s3+t69kydOjBg6bMf27SzL/vTDD1IbyZ3bt1XbCWrbVmojeSOXwyFUV0hJTpHaSCKOHa8wvmLZMic7e5IkP7biv//8I7WRHD1yhNvCwwcPVIfoyOHDa2hvi4qK7KXNQkaNLioqUg1mZWV169y5ra9fDX3oP1evcj+xfr379Py2R49u3Tt36NjOP6BNq9YURam7NTXcl9SUFKmN5J+rVyuMhx061Ny26Se+G+BrJi01lTvbfvA/iqTAREA1iX369O/TZ7gMVk6O7s7t248ePvqye0VR1JbNf3m7e6iOdk9Xt2VLlpaWlr71sYYNk9pIdobu4N7+tmGj1EbS57ueKndEJpM5Ozi6ODmVlZWpNnv+3Lnmtk1HjRjR1teP22zfXr1LSkq4pVcuX+4YGKT6xA7tAh8+fMiy7PcDBkptJDeu31Btp51/gNRGUlRYCMdPXeHK5ctSG0liQkKF8dOnTkltJKkpKR9b8dKFi1IbSV5eHkVRTnb2odu2cePnzp61ayp98+ZNjd5a2Eub9e3V++fBg7t17mwnlUptJMePHquJj5PJZG1atf7Ytab8j6iSVKry6Mb166WlpbISGULoWfwzkUhEEASO4xRFFRYWXjh/gWGYsrIyaAZTF6mJdDOgIcPl+/N5PB6PT/AIPo9n0qSJsYkJRVIZ6elcwr+uri5Nf+HEDoIgRo0ZPXzkiBdJScXFr6ytrUyaNCmfZLB5y1YMx1QjY34J+X7wD/r6+qoRLaGWnr6+m5ubqnwpNSV1/Nix3/bosW7jBpZlHz18uHjBwocPHhw+eHD4yJEIocCgoMCgoNevX+fm5JiZm6vOmTv37CYIony+/LmLF/h8Pjw5qkMYGhkhhOLj48s/HEQIpSSnIIT09PU/tqLGtQwrSS3XnN6LisrNyWnj6zt95owmpqYikYjLPuGSUKrwgKxS7suRsPDTp05xr1etWPH+hOZ2duC71FGqk24GAO/zwXz/D/I15PsTBNHczu7Di/5becHn842MjMqPXLlyOTcnJ7B90P+foO9F0RTtF+DPJa+4ubuP/iXkl9FjcrJzyq+op6dXIe/n/XM3KAbUORwcHLTF2ksXL7GwsHBzd+cG7965s23LFltb20+0ANW4lmHlT/61WXPKKQP8Mm6ss4uLRjZYKfelX/9gkUhEUmTEseN+/v7W1tbczTlCiEfwjE1M+g/oD8du3aVq6WYA8EF82rS5ffu2gM/nv/ufz+fz+TyWRfUs33/3zl0YhrULDCx/AUMIhR8+HNS+faNGjZRK5fmz5xBC5V0coL4iFAoXL106ddLkfr37SGwlpqZmWVlZaampCKFNmzd/yofWtJahek4Aj6eqOaVpuvTNG4WiRjSYnZycdHR00lLTWvv4aGSDanTdzc/P79XjuwWLFnbs1AmO1HpDakpq+3bt1q5fXyFguHL58j27dj96GsPj8cBKAFCBZ/HPunfp4urmdjTiePnxfXv2rF65iiRJKyur/Px8hmF+nTH9hx9/BIs1EK5curxy+fKkpCTubdOmTefMn6dWr9fqaxlWkju3b/++8bfMjIz8/HwuKa1GNZhLS0tXr1x59crVbaHbMRxHCNEU/a4rscKnTZsaFA0A6iWc4vT5SxcrPK89c/r0xHHjr/z7D3SCAYD3SU5OTkpMlEgkzZo3r7CopKQkLjY2Ly/P1NTM3sFeV1cXzNXQKC4qyszMNDe3MDD8vP+RmZk5fMjQTX/+IW3WjGXZ8n5DSUnJ4YOHcnNygjq092nTRoN7qFAovD083sjf8Pl8sY6OUCjkEh9ZlmUY9vylixqPjKanpQUGfNSN+0RX4o+hxo11+f5mcHTWG6qcbgYAH+T91F0en8+yLPW2TTdFkSRJkjTNuLR0qbv/TFtbW1tb2w8u0tXV/aZVKzgSGjKNDAzKB04+3TyXIqnEhITdO3f9feYMRVHdunefM3+eWCxmWXbIjz89evgQIbRzx46FSxZX6DJXHZ7GxLyRv+nZu9eSpUtF2tq1YBOuTISmGa5GREtLSyAU0u8eJVehTEQN9wX6m9VLqpxuBgAfpG6l7tY+s2bMvH3r1uYtf3Fq1UB9omrNc7lnIAcPHDA0NGxsbBweFobh2LIVK65fu/bo4UNXN7fRIWPOnz23esXKnr16aapKhuDxEEJ9+/WrHd8F1UCZiBrui8RWMmrM6PCwsPCwMLXkNIGvmSqnmwHAB2k4qbtVIzoqKiM9HYOK6HpHlZvn0jSFEJo9b+5PP/9MEMSB/fuXLlq8eOnSf65eRQjNW7jA1dW1XWBgK0+vZ/Hxnl6akRd0cnIyNDSMfRrbxtf3y9qNZdmqdRZWw32pspwm8JXTs1cvXR1dLt2Me2bEpZv5+fuBcQB1Wb5q5dezMzeuXz8afqRvcD8/f/+vZJfEOmKEEA8kUesd96Oj5XL5qrVrPD292rdr98fmza5ubgihmb9OLywq/MTlmcfjI4R69+nDFS136tx53uw5BS9f3rp5y9LSsmXLlgghgUBgbGzMSZprBJqm+/Tru2vnDv+AABzHKIpSkiT3dJeiaF8/zfs0iQkJvXp8hxM4gRMEQTAMQ5IkSZJcvnAVpJ3UcF+gv1k9JqhD+6AO7dVKNwOASnL92rUjYeGpqale3l5z5s179erVsSNHPLy8XF1da/qjz5w6ferkyW7fdv96rMGJS3NXLKA+QSpJhJB/QIChoaFQKIy+d49zXwLbB00YO660tFQkEn1wRXMLcxzH79y+3aVrV4TQvcgohNDGDRsSExI6dOzIXdSLi4rS09NNTEw0tbd5ubnbt25DCHXv0uX9pTXxYFdLS6usrAwhxOfzhUIhj8fjGjNSFKWrq1uFAIwa7gv0N6s3vHjxIiM93alFi8aNG8vl8rjYOIFAIBAKBAKBSFs7Pz8/KyuTJEmKor28vcBcQHXYGRq6dPES7rWlpSVCSE9P79bNWwf27b949YrGbiUp+tmz+OysbL6A7+HpyeUH5OfnkxSJEJKVyNLT0ho3bqwlEmVmZBg1bszj8eJi44qLizy9vMRiMUIoJTnlRVKSSROTFs7OFe4CX79+/eTxE5JUNrezMzc3L7+0qLAoLi62rLTM0spK2kzK3T0zDJORnm5qZlZSUhLz5ImFhUVTqVR1MeDm8HgEy7JpqWl5eXmOTo4VEhpKSkri4+JYlm3h7MztHgdXUmtsYpKakiqTlXh4en56PlCbVLl5Lp/P9/Xzmzh+fGBgkEwmi4qMbG5nd+bUaYTQlcuXp06a7OvvF3bokFAodHB01NTeWlpZSWwlNM2IRFw8QqSlpcWyLMPQNfRg18LSMiY+jlNoLx8E6t+nb0s316p8nGbUQ0AZp06xfu1aqY3kSHi4SsrqY//RNA3mAqqjcmInlf48+MfMzMzRI0aOHRPCjZ+IiJDaSGQymUY+5eHDh27OLqqDtqVTi8i7d1mWrSCwcvXKFU6UceH8+a4tnLlB39at//3nn4HBwapp06ZMUW2ZpunNf/zh0Ky5aukvo8cUFBRwSzf/8YdjczvVotEjRnLj7du1k9pIfh48WLUouE/f7Ky3kk+DB30vtZGsWbX6Gw/Pt1pLbu5RkVEqQajQbduc7Ow59Rk7qZTTdOTo3rmL1EbCqUJOmTjps/OBWlXRIik3Z5ftW7ey7+Q8g/v0nTJpkmNzO4+WrpwO6MfIyc5WHYTfdumalpqanZW9cvnyc2fPct+s1Eayd/fuemm3fXv3ujm7VOFao15HsqqlVQNfGzY2EktLS65vMueDl38mSBA8pVLJZWQ3zORKQFPEPHnC0MzaDeuNjIzK33JZWFgghLKzst5vmlIFcAwfO358G982xiYm169dmz512vq16w4cPjR/4YID+/bfuH791xkz7B3sXV3dOKGlq1euzpo929rGevMff966eXPYz0M6duq0dft2mVw293+zjx89Fty/P1f5vGN76JpVqzt26jRv4QKhULh/776N69ezLPvnlr/i4uLWrFrt6Oi48Y9NBo0Mnj6NSU1NfXdDySCEdPX0du3dq6ent3vnzhMREVMnT9538ACGYTiOIYSOHjkycvRoO3u7wwcPnT93bvnSpVz7u5MRJ5YtWTpk2NBp06fLZLJpk6csXbykuZ0dl7tDUhRCKDwsrE/fvkHt2392PlCbVKd5bhNT04NhYYWFhQqFwszMjBucPnMmQuj8xUvR0fccHBxaODvXS7vp6uqWlJSkpqZ+rBOBBqIvJSUlLZ1aSG0k3L2Ib+vWAW18A9r4Sm0kHi1dFQoFeN8AAJTnzu3bdlIpp+E8dkyIKvqyb88eqY1EpcOsKWiaTk1JcWjWPKhtW25k7v9mS20kd+/c4d72/LaH1EaS8Pw59/bJ48dSG8nA4GDVFhYvXCi1kRzcf4CrhvB0c7eXNisqKlJN+LZrN05V+O/TZ6Q2kimTJqkEqFV07dRJaiNJS01VSVt3at9BaiN5/Ogxy7I/D/6xvC7x69evHZvbebt7cG/9Wvu09fVT3YlmZmZKbSQTxo7j3n7X/VupjSTs8GHVZ316PvAFYRgmPS3t1s2bn5UNj753b8rESWfP/F3Tu5SUlPTvP/9wPXZlMllUZNSjh4/i4uKSkpKSkpKexT+LefLkwf37qligZiFJMisrKy8vr6iwsKSkRC6TFxYU3r1zh4uJvnz5sgajL1VOqwYAoGHi4OhI4MTaVatnzZmN4RjLsAihxISE9WvXSZs101QHC5qmT0acOBIe/vjRo9LSUi7ZhVvEsIwq3QQhpKUlRAipipabmJoihCiKrhAWkslkCKGszMzioiI3d/fy3Y9a+/jExcbGxcV5e3tri7VPHI+Ij4vr2at33+B+KkFHLS0thBD+7kMJgvD1801KTHz2LN6lpQsX9VQt1dXVNTIyKigoQAgVFxVlZ2ebNGkyacIEhmFYhuUmq+I63Jbt3mlMfnY+8AXBMMzSysqyEoKLtdZT7WRExKbffl+5ZnXffv0KXr4cGBz8sZk1kbqbkpzcpeOHFYe+69mzgh5qZVDDfalyWjXwFfI0JubypctlZaWlpaVlZYqy0tKysrLS0lLF25dlZaWlCoXixp3bBFR4AlVFX19/yrRpK5Ytu3jhgpIkMQwb1H/AvagolmXXblivkY9gWXb6tGknjkd4enlNmjLZ08tr3C+/lJUp3rovnK/w7kTMXf5VcKcskiRVI1oiEXrXRqyouBghpKPzn0xYzpUpLChsYmp64NChjes3XL1yZdWKFb9v3Dh77tyB3w9C72qLyp/9uf4f3OMDmqYRQlS5DxUI3977ZWZmcpc9hma4FwRBdOna1dTMtLz7JRJpV3I+UCfOpbXWU+3Lpg3o6etbWllxbbi5miOxWGxgaODj4zNw0PdV2KAa7kuV06qBr5CHDx/+tmHDZ6dRFAXuC1Adho8c0bhx4zWrV+Xl5iKEcnNyrKyt5y2Y37ZdO41sPzMj48TxCHcPj4NhhzmPgcAJlmEqHMbvHAUhQoh+F27hxplykznHhWZohJCRoSFC6GX+y/KbKi4qQggZGhkihJxdXLbtCM3MzDywb9+2LVvnz53bo+d3YrGYc5JUcnIsyz569Agh5ODgiN71KFPtEkIIx3BuH8zNLRBC1tbWmzb/+bEb+vJb/ux8oE6cS2utp1rvvn169+3z9qjD8UtXr9amoUxMTP65fk2DG1TDfbG3d9DV1b1186ajk1O//sEzpv06MLi/lbXV2TN/6+vrW1UiRAZ8PfB5fISQVCptFxTU2qe1lpYWhmEEwePxCJwgCBzHcZwgePBMEKgmGIb16tO7V5/eRYVFWVma7yqUnp6OELK2sS4f7VC+i23wCB5CqLCwkHvLOS4KxdvYDBcIUSqVqhW5CVyk2czc3KRJk4TEhJzsHC6ewTDMzZs3EELuHh4sy3LOhIWFxa8zZty4fuNpTExOdra0WTPuV8PQb52kkxEn7kdH+wcE2NnboXfPqkjy/90XFrFcK2IDQwMra+t7UVFJiYnlNchevXqlr6+PEGIYtvz+f3Y+UCfOpV+kpxpJktevXY+Pi5XJZDo6Og4Ojq18WtdE1b1CoSgtLSUIgsAJnDMHjpNKpZIkle8glST366gp96U6adXA14bXN959+/W7euVK6LZt+/fu9WnTJrB9UIeOHTXYFglosJS+efPP1X+a2zUvX1hkYGjAOS7P4p9dv3btm1atWrq2rP5nOTo6irS1z575u2VLVzNzs6uXr2RmZqpuc41NTBBCR8LCX79+HRAQwEU+/t99of7zFiFEvQ2NkAghgiAmT50ya/qMEUOHzpozR1dX9/Chg8+fPe8XHGxhYXH3zp0doaHduneXSCRRkVFPY2IkthKJxFYVI/n3n39wgrh7+87pU6eaNm26eNlSbpzbB+5vjrdOSZlCW6w9d/78UcOHD+gXPHnaVEdHx8zMzJMRJ9r4thk6fLgqUFR+hz89H6gT59La76l24fz5BfPmcwFRFY0aNZry67QBAwdqNuJ+JCxs/tx5n532LClR3c9Vr3Ba1SWTIIi1G9ZPmTY1PT3d0dGxvLQmUCdo2rTpyjWraZp+8vjxpYuXLl+6NG/2nPlz5rp7eHTp2qVjp05W1tZgJaBqXLt2bfzYsQuXLP5gXbS1tVXotm0nIiJO/X2m+p/VyMBgzbq1s6bPWLxwIUEQbdu11dPTe/36Nafx239A/zOnT1+9cuWfq1dPnz3LRT6USsU7Z6Vi9IULmaie7PQLDuYRvPVr1/48eDBCSCAQjAkJGTdxAkJIJNJ+/PDR5YuXuJn+AQFz5s/jgvycm7Jw/gIDA4PmdnZTpk0dPnKkUCh8+6EUjd4VV7+NvrAst1faYu2g9kHbdoQuX7J0/py53FJbW1vuE1XuS/kd/vR8oG6dSxMTEuLj4wsLCg2NDN09PLhEco1z+eKl8b+MpWna1c2tRaoCGbIAACAASURBVIsWevr6r4qLHz58GBcbO2/2nNSU1Fmz/6fBj1OFnXg8Hl8gYGhaoVDo6enRNM0wDEVRDMPQNE2SpNpu02drk05ERPT5rmd6Whr3tqiw8PSpU1lZWaoJm377vXvnLu9XDwJ1i7TU1B2hod8PGGjXVMq1Tvptw0b4WoEqsGHdOqmNRNWo7X2mTp6swbZ1LMsqlcrExMQ3cjnLsmVlZeVbYDEM8/r1a5IkuXRIkiRVRzXDMKWlpRRFla/tVCgU7x/2RYWFaampFfpz0jSdkZERGxubl5dXfjxk1GipjeRZ/LMP7qpCoSj/ie/vMMerV6+eP3tWoba8wv5/dj5QV86lBQUF3GFT/r8Z037lmg5otnrZr7WPawvna//+W2HRP1evcp0eVY0GNNXNr/wRHrptm9RGopF/1+cro16/evXoXTkiQigjI2PiuPE3rl9XTSgpeR0fH6/KJgPqKFbW1kOHDdt/6ODd6HsTJ09OSUnZuH49QzNgGUBd8vLyRCJRE9MmH5vg5OSEEEpNSdHUJ/L5fKlUKtLWRggJhcLyeTAYhunq6vJ4PO5GkMfjqeo4MAzT0tIqf8/H4/EEAsH7hR6NDAysrK0rZFDiOG5hYeHo6GhsbFx+nHsCxcm7fPBmtMJdZoUd5tDT02tuZ1ehtrzC/n92PlAnzqUsy86Z9b8L5887OjkNHT588tSpQ4cNs7O3OxIe/sfvmzS7bzFPnmRnZ0+eOtU/IKDCorbt2m3ZthXDsMOHDmnwEwkeUf4I59S+uN9jNfn8JrgeCbx3qS3cL6f8j41LjgP3pa5TXFR05/adGzeu37h+IyM9HSEkEokomgIhcUBdtLS0SktL5XL5x66mMpkc/TeHoz5RIUEYgHPpp8+lmZmZF86fnzRlyrgJ41WDDMPM+d//QrdtmzR5sgZPwinJKQihrh9pMOPs4uIfEHA/+n7NGYfH56H/lvvVoPvCeSr8d76SqjSxwt6A+1IXUSgUD+7fv3H9xs0b12OexHBfooWFxQ8//hgYFNjax0f1wB4AKg/Xqut+dHRA27YfnHA/+h561yOuHrovbxOEy+BIgHNpZc6lCc+fI4R+GDy4wpV34KDvww4dzsrK1GAmIkkqMQwzatz4YxOcnJxu3bxZc4Z6l8BO14b7giEMIUSoQj0YhhDC8P+PXhKExpwpoNZ4+ODBxvUboiIjuRA3j8dr1bp1u8DAtu3aNmveHOSrgOrQ2scHIbRg3vyTZ06/H4A5e+bvG9dvODo6mjRpUi//+eMmTPzp5yEtWjjDkQDn0sqcS7m6XVVGuYqSkhKEkK6engb3VkmSOI5/Ikm2kYEBl5tVQ1cB+r1mSzUefTl75oyBgSGPz8vNyUUIPXn8WCh460u+SEqC6Eud4+nTp9evXbO1tQ1o19Y/IKBVq1Zc3gAAVB9HR8du33b/+/SZbp06T5g8ydfPr0mTJqWlpSnJyYcPHjp44ABCaNKUKV9wD+NiY8+cOp2aljpj5kxLTfes8vL2Kv/2+NFjaWmpPXr2hMaecC79IM4uLjweb+H8BctWrlApVGRnZy9bstjS0rK8ZkX1YRmGpunww4d5PD5O4DweD8dwhmUoimJohmbox48fIYQYmtHUE6vnz55HRUVyPXAIHu/B/QcIodMnT/H4PIqkSFJJUhRFUiNGjVTXYapM7guGEFq2ZGn5wV07du7asbP8CERf6hZcq6Xk5OTk5OTdO3dxOYxaIi2RlkhLS4sv4PP5AoFAcCg8TOPKF0BDYMXKVYUFhXdu357563TullRVjYxh2K8zZrTv2OGL+S5xcb2++w5DmFMLJy6RsEbZuH59RkaGu4cHuC9wLv1wwKNRo4mTJ61dvebK5cvOLi46OuL8/PzExESaotesW6fZveUO+FkzZn56GkmRmnJfoqPvqar6VcyeNavCyNDhw9TN5/38bHNzi3aBgTwVfB6fx8cJnCIpiqJIiqRIiqKhtXwdw9Pba+b//ldaWspJdZSWlslkJSWvX5e8Lnn9+nXBy4KSkhKuShPSX4AqoC3W3rN/X9ihw2GHD8U+jaUoCsMwC0tLZxfnYcOHe3h6fsF9O3zwEE3RC5csrpBtUEOMnTAewzCnFi3gqIBz6cc2MjokhM8X/LV588MHD7gRkyZNJk+d0rN3L83uraWVpZ+/P5/P5/P53NWcu6zzCB5F//8fDd61WllZBwYFCQRv/TgcxymaYmiGpmmaefuHazCs7pYxeOgDfAy5XK6trQ15MEA1YRimqKhIR0fnK3GFp0ycdPLEieMnT7q0dIFvB/h6zqUURWVlZhYVFxsZGpqZm0NQoLrRF6DBUhP6F0ADBMdxIyOjr2RncnNyuJLmV6+KMzIyLCwsuIvK69evnzx+QpLK5nZ25ubmqisNy7KZGRnGJiapKakyWYmHpyc3YtS4MY/Hi4uNKy4u8vTy4n4sKckpL5KSTJqYtHB2Vm2BYZjMjAxDIyOxWMy9NjYx4fF4sU9jKYps4ez8vlfHXcZIkiQIHoZhPD6vvlZpwbn0P9djHs/axsbaxgYsVhkg+gIAQAOiTavWKqkXgkfEJySwLLv1r782rt9AvhN67Nyly+JlSw0NDRFC33bpGh8fP2rM6K1/benZq9faDeu7d+nyLP7ZT0N+PnbkqEwmQwiZmpkuW7Fi8x9/REVGcVvo3bfP6rVrudcdAgNTklMOhYd7eXt1DAxKTk4eMWrksSNHOSFJbbH2ttDQVq1bc5PzcnNnzZh5/dq18rH0Zs2bn7t4Ab47APjPfRGYAACAhsPCxYt8/XwRQtNnztz81xYMw3ZsD12zanW7wMDrt29F3o+eOHny+XPn5sx6K/tCUhRCKDwsrE/fvh07dULv5IquXrk6a/bsvQf2t/H1zcnOGfbzkEaNDLZu375u4waxWHz86LHIu3e5LXAiR5zyC6eydOrkqVFjxuzet69nr15v5G9+27BRtXsTx4+/ceP6b5s23Xv4YPbcOQihQd9/v+nPP+CLA4CKgD4FAAANinmz50htJJF373ISMJ5u7vbSZkVFRaoJ33btJrWRJCYksCz7XfdvpTaSsMOHVUt7fttDaiNJeP6ce/vk8WOpjWRgcLBqwuKFC6U2koP7D3BvO3foKLWRxMXFsSzbtVMnqY0kPi6eWySXyR2aNW/r66cSvpHaSEaPGPlWLIaivNzdPVq6gvQYAFRF8wgAAKD+wT0qysrMLC4qcnZxKd9dg2u7FxcXhxDS0tJCCNnZ2amWamkJ0Ts1FYRQE1NTVYiFg8tT4Z4rqbbARV+41/i7tp/aYm2xjk5+fj73lkvKUa1IEIShoRHXQwy+LwCoALgvAAA0LDhJRa4PTVFxMUJIR+c/mZWcK1NYUKhyVkQi7XLui1b5ySKRSOUMvZ0gEqFynTy5Lbx7LVJ9NIdQKFTNNDMzc3BwiIqMPH/uXEFBwcEDB5ISE7t17w69lwDgfapYeZSdnW1gYFDhZwzUdTIyMpo0acLn88EUgGZ5+fKllpbWV6KHzEkqkkoSIWRkaIgQepn/svyE4qIihJChkSF6J9FSPv4hEApVG1H5IuUzbbnJNPN2AierQpGUyvVRlvd1tITl1928dcvI4SPGjglBCAkEguABA+bMmwvHT72hpKREqVR+PYV4b8/86elmZmYEj1e3jFBFp37Ijz+puusA9YZe3/ZITUkBOwAaZ8HceRHHjn0lO8NFX0iKRAiZmZubNGmSkJiQk53DLWUY5ubNGwghdw8PhBDDsOi/8tEVBKU58TmlUvlB90i1iCSVKs+GKue+YBhGUZTKg+HzBTnZ2QMGDbx1986TuNjlK1dA/4L6xNHwI4vmL/ja9qpjUPvcvLxa+7jDBw8tW7Kk+tuBmCQAAA0Lzr3goiYEQUyeOoWm6BFDh968cfPxo8dzZ89+/ux5v+BgLoWFcyz+4768FZR+575QVIUJ7x5OvfVRuEX/1959xkVxdXEAPrONbhQVEaRpooCCgEQTayxo7AWwosZesBsFu0ajiAVN8lpjiTGxxxY1ajQxalQwUVBZLImFqogURVh2yvthZLMiwkJMws7+nw/+nNnLzpx7dmbP3mni0SWe/2vRIrGg0eS/eDz1tq+2Pnv2bNeOnYMHDlq8aNHZX37BiS8AxcJt6wDAtLAv1x9BwcEKuSJqxYrBISFEpFKpRo8ZM27iBPFVsXzRH1wRz9LVPR+YfWX0hedeqlHEl9gXNdNf/xa+/4vRHfE5fz6+vjKZrHXbNjfVCV9t2frVlq0+vr5bv95WQY67AaB8AQD4b6yIilq5apXu+XAMw/QM7NUzsFdWZubTp08dHBz1H1a39ettMplM//btm7/aqj+nZs2a1xPU+meMDR4yZODgwbo5B78/rFAoxPZbtn0ll8v13+2HkyeUSqV4cu79e/fHh4Z26dp15epVgiDEXr26cP6Cq1eu7NqxY9iIEUgcgD4cPAIA0yI+Pe7VB9BUrlLFydm5yIN2VSqVQqHQb1xkjviEYf2KRKFQqFQqXQMzMzPdqyqVqsiDbMzMzHQXFl2+HMOxXPOWLcS39fH1HTV2DBHpzssBAJQvAAAVi7u7OxHt2bUrKyuLiAoKCo4f+4GIWrdtg84BKAIHjwAAKoT6DRrM/2TBsqWRTRs3cXJySk9P53l+wcJPmjZrhs4BQPkCAFBBhQwa1L1nT3V8/KNHj+zta9Zzr2djY4NuAUD5AgBQodnY2DRu0gT9AFAynPsCAAAAKF8AAAAAUL4AAAAA6ODcFwCQDu0vSVxsuokEK3e3VQa4IOmA8gUAwLgV7L2V/7mpPE3WbIAHyhcwWTh4BAAAAChfAAAAAP5JOHgEANLBmMkZS6WpRGuOHTigfAEAMH6Wy1pZLmuFfgCQPBw8AgAAAJQvAAAAAChfAAAAAFC+AAAAAMoXAAAAgApVvgiC8Ojhw2JfunXzVmpqKrrSGHEs+/jx42JfuhZ3LfNJJroIyu1hWlqx89PT0+Nv3ED/gIlvCBzHnTt77j9ZJa1W++TJk2JfunrlSk5Ozr/XCSxb7k4wtHyJvnQpuFfgq191OTk5I4cPj4mOxmfUGB3/4figAQOePXtWZP6jhw9HDB2qVseji6B80lLTOnfsmJCQ8OreakLouOM//IAuAlPA8/ygkIF79+x59aWVy1f87/PPBUH499fq4IEDQwcPzsvLKzI/KTFxxNBhd27ffsO/kzkupF//A/v3v/rSssjIDevWlq8TDC1fmrz3Xuu2bYYPGZqfn6+bKQjC5IkTff18u3Xvjo+pMerUpXPt2nXGjRnLcZxuJsuyY0eN7tq9W9NmzdBFUD72Ne0nT506/KMhjx490p8fGRGRn58/YeJEdBGYAplMtnJV1KIFn0RfuqQ///Sp0zt3fBu1ejXDMP/+WgUGBVWtVm3yhIk8z+tmajSaMSNHDxgY4teo0ZtdnFwuX74qav6cub9dvqw//8Tx43t371m+cmX5OqEM577Mnjs3N/fZhNBxukJp7f/W/BYdM2/+fHxGjdfS5csS1Oo5s2bp5ixc8ElycvLUadPQOfB3DAgJcffw+GjgQN2PvJMnTmzZsmVJ5FK5AjfMBFNRv0GDCZMmjhox8t7de7pBjskTJkyZOtW+pv1/skoMw6yIirocExPx6WLdzJnh4Tk52aHjx/8TS2zYsOGY0NARQ4clPnggzrl/7/7Hk6ZMCwuzq1GjnKWh4U0VCkXk8uU/nT69LGIpEanj46NWrhg/aWLlKlXwATVeVlZWiyMidu/c9dWWrUT0y89nvt2+PXzWTHNzc3QO/E2fLln84P6DcWPHCoKQ+eTJlImTunbr5u7ujp4BkzJ4yBA7u+oh/frl5eVxHDd08EdVqlTp26/ff7hKlStXnvfJgs2bNu3etYuIvj98+OD+A3Pmz1Mq/6lnbgwfMdzW1rZ/3375+fkcxw0dPLi6XfWg3sHlL8LKesxp8oSJhw8dqlq1Wt7z5wqV8mJMtEqlwqfT2PXv0zcmOtrczJzlWPua9qfPnPlPhjRBejasWx8ZEeHs4pL77FlmZubZX8/XsLdHt4Cpib16NbBHTwcHRyIhJSXli7VrPuzY8T9fq57dut+4fp0hhpExbq6ux348+Y8u7rfLl/sEBTvWchSIUpKS12/c2DagXbnfrcwXTk8LD5PJZBkZj5/nPR8zdgxqF2mYM38eEeXl52m12kmTp6B2gTdl0EeD36r81oP79zMyMjp37YraBUxTQx+fFi1apqQkp6Sk2Newb9+hQ0VYq7nz5/E8z/Ecy7KTp338Ty+ukb9/k/eaJCclpyQlO9aq1aZd27/zbmUuXxwcHAKDg2WMzMzMrH9ICD6U0uDh4dGyVUuGYWwqVerStQs6BN4Uc3PzSZMnK5VKpVI5NnQsOgRMVtisGUqlUqlSjh43ViarEDdd8/Xz8/f3J6Jq1aq1Cwj4F5Y4Y9aswr1B6N/8nVyeHhw1erRAQuu2baysrPCJlIzRY0MFQQgMDMRplfBmBfXurVAonJyd3qlbF70BJsvd3d3Tsz7Hcl26VKCfiGPHjyOi3n37/jsVVQMvr3feeZsE6ti50998q/J8Ubm6uTZt1qxf/wH4OErJu43frefuHtynD7oC3iwLC4ug3r1dXV3RFWDqvxJDx3y3b1+Fut6lRcuWrq6uQcFB/9oSx4SOO3b0aKVKlf7m+zDlu11MXGxcA68GFWT4C96Uq1eu+Pj6oh/gjXtw/761jY2trS26AkwZx3HxN+K9vL0q1FrFXr3a0Mfn3+sEllWr1Q28/m4nMP/JLf8AAAAAyg3DJwAAAGBkynDuy7Nnz2aGh1+/dh29BgAAAG/EsBHDB5T9QuYylC+JiYnnz55b/+WXJtKhIf36rfr8s2rVqptCsAvmzu3QseN7779vCsF+8/XXgiCEDBpkCsFevHDhh6NH5y9caArBZmQ8njBu3Dc7dprIPmr0iBEzZs9ycXE1hWCXRy719fNr2y7AFILd/92+Rw8fjRozxhSCvXYtbvu2r//Z8oWIFAqF/7v+JrJrYBjGy9vb0dHRFIK1trGuXbu2iST3x5MneF4wkWDTHz2ytrE2kWBTUlIYYkxnH6VQKDw9PT08PU0h2LcqV3Z2cTGR5EZfushzvIkEq9FoyveHOPcFAAAAjAzKFwAAAED5AgAAAIDyBQAAAADlCwAAAKB8AQAAAPhXyOfPn29oU7m8alVb74YNTaRrrKws/Ro1UqlUphCsubm5R33PKhXpQWL/HJVK5VbbrVatWqYQrEKpsLe3r1evnkn8GpPJKld+y9fPz0T2URYWFj5+fhYWFiayj6pbr1716iZxIy6lUuni6uLi4mISVYhcblfDzrPs1//jmUcAAABgbD9X0AUAAACA8gUAAAAA5QsAAABAodc+8+jqlStxsXEyGVPsk+2uxV2Li4sVeF4QSBAEnud7BQVWqlTJeDui5Hhzc3OPHT2a+OBBLSenDzt2tLGxMcYY9+zerdVqxf8LgiDwfN169Ro3aSLJ5BoYrGSSq9Vqz5755dbtWyQIDby8mjVvzjCMVDdbQ4KVTGaJKCUl5dbNmw/uP7Czs/uwU0dp75BLDVZKyTUkCikl15B4Dc9s8afuZmdnd2jbjmXZ/Pz86wnqVxssXbJk4/oNjo6OjExGRBzL7jt4wM7Ozkj3DiXHe/fu3cEDQp4/f97Qxyc2NlapUOzYvdvVzdXowmzVrLmWZeUymVwuT01LNTMzO3LsmJOzsySTa2Cw0khu3vPnHdt3SElJcatdOyc7Oz09vXmL5hs3b1YqldLLrIHBSmazJaLBISFXr1zNzc3t3bfP4ogIae+QSw1WMsk1MArJJNeQeMuWWaE4M8PDA1q3WfTJQi9Pz2IbzJ0129fLW5CKkuPtGxzs08ArNSVVEISMjAx/X99hHw0x6njPnT1Xx8V1z+7dppDckoOVRnLT09NDR4/JzMwUBIHjuMiIiDourls3b5FkZg0MVkqb7dOnT+/+ebeOi+vcWbMlv82WGqxkkmtgFJJJriHxlimzxZz7cjnm8u6duxYsWiiXy2RM8SfH5D7PNd6R2DLFm5KSEhMd061HD/ua9kRka2vbo0fPn3/66fHjx0Yab+aTzGlTpgS0bx8YFCT55JYcrGSSW61atc/X/K9y5cpEJJPJxo4bR0RxsbGSzKwhwUpss7W2thaPjskVcslvs6UGK43kGh6FNJJrSLxlzWzRb2utVjtrxoxuPbq/37Qpx/Eymew147d5aWlpXh6ejRr6fDRw0JXffzfSPi01XjG0t99+Wzenrns9Irpx/boxxisIQnjY9IwnGaPGjH794LxEkltqsFJKrv7JH2lpaURUy6mWVDNbarAS22x1FAqltLdZQ4KVRnINj0IayTUk3rJmtuipu+vXrnv08OGMnTuISBBeW764urlOnjrFydk5MTFx25atA/sP2LV3T/0GDYyuT0uNNyszk4gcHR11c9566y0iysrKMsbP0NEjRx4/SndwcAzq2cvH13f9lxurVq0q1eSWGqzEkqsr2j5ftVqpVPbp10+qmS01WOlllhd4IlIqFdLeIRsSrDSSa3gU0kiuIfGWNbMvfT7u3r275osvZs+bW61aNSLiOI6KO5+fiKaFhen+36lTpw7tAtavW/fZF18YV4caEq+1tQ0RcTynm1NQUEBEZmZmxrhf6NylS+cuXQRB2LNr98zw8OWRy5YsjZBkcg0JVmLJFW3dsuX7w4eXLl/m4OAg1cyWGqz0MstzHBExrzmaL7HMlhysNJJreBTSSK4h8ZY1sy99Pvbt2VtQULB08RJfL29fL+8d33yblZlZv577ge/2l7Bazi4utevUvqlOMLqNxJB4HWvVIqK01DTdnPRHj4jIqB+9wTBM7759HB0dL128WHJL402uIcFKL7lHvz+yeOGiyVOnvu7EJilltoRgpZdZjuOJiOPYUltKILMlByuN5JYvCuNNriHxlrVPXipfgoKDv9q+fe2G9WvWr1uzft37TZtaWVlt2LSpecsWJQ0KZWUlJibW0TteZSwMidettptcIb944YJuzsWLF83MzIx6yJ2I8vPzs7OznV+5kFgyyTUkWIkl98zPP0+eNLFPv75jx4WW2tjYM1tysNLbbMXjKayWlXxmSw1WGsktXxTGm1xD4i1zn5RwmdOUiZN8GniJ///jjz86tAsI+3iaIAgajWbOzFkXfv01KSnp3Nlzvbp1r1unTnx8vLFf1vW6eOfMnPWOW+1dO3ZmZGTs27u3jotr1IoVRhddYmLilEmTLl28mJWVpVarhw8ZWsfF9eSJE5JMroHBSia5giBEX4r2rFuvc4cPz587d/aXsz+eOHn40KGbCTcludkWG6xWq5XeZqtz4/r1Oi6uc2fP0c3RBSu9HXIJwUpps31dFFL9tjUk3jJlVlFCuVSgLeB5Xvx/3vPnd27fdnZ2IiKOZa9di9u3d69Go5Er5N7eDfd+t9/Dw4OM3OviDZs5Izs7e2Z4+MzwcLlc3q9/f/FaTeNiZmaWmpLav0/fF3Wum9tnX3zRLiBAksk1MFjJJFcdHz9i6FCNRpOQkDBoQIhu/o7du6W32b4u2GvxN6S32f41IMEXPZ6iC1Z6O+QSgpXSZvu6KKT6bWtIvGXKbPF33X3xdV5QwDCMeC9Lnuc5jtO/ryXHcQ8fPrSzs1MoFCQJJcebm5ub8fhxDXt7oz6v83nu84yMx1bW1lWqVNFdfSrV5BoYrASSq9VqWa2WkclkMhnDMDJGxsgYXSolltnXBSuTyaS62YqfW61Wq1QqdVdHFglWSjvkUoOVUnJfjULa37aGxGtgZksqXwAAAAAqIDxxGgAAAFC+AAAAAKB8AQAAAED5AgAAAChfAAAAAFC+AAAAAKB8AQAAAJQvAAAAAChfAAAAAFC+AAAAAMoXAKh49u/7bnVU1J9//klEM6aHfdCipTo+XnxJf1K/WQWhjo9fvjRyfGhoUmIi8ggApVKgCwCMxa/nzyclJnE8x3OcTC6vVKlS4yZNqlevrmuwOioqKSnJ18+vdu3aFy5cSEpMZAofeqc/qd+sQtQuanWPbt0YYjzreyoUSiQaAFC+AEjH9m1fnzh+nAqfrkxEDMOMHD3q4+nTxUdqh04YzzCMZ/36RKRSKolIWfiIWv1J/WYVwa4dOzmWW7Bo4YCQEGQZAFC+AEiK+Pj4VZ9/1rlLF57jz5w5MzMsbP3adU3ee69lq1ZEFNy7t66xUqUkIt1ghv6kfrOKICc7m4i8vRsixQBgIJz7AmA0zM3NiUghVzAMI1fI27Rt0z9kABHFF57gwvN84oMHubm5RKRUqohIrpC/KF/0JvWbvSggcnLOnzv/808/JScnC4Kgv1CxcX5+PsuycbFxv//2m0aj0W+Q+STz1/PnT/946tbNWxzHlVSmFLeUh2lp4htmZ2clJSXpL10QhPT09ISEBP2Zaalpd27f1mq14uTTp09joqOjL13SD0fEsVz8jRunTv74y5kzz54903/bpMREjUZz6+at33/7raxRAEBFgNEXAKOhUqmKzElJTiGiuu/UFSfbt2177+69nXv2+L/rr3z54JH+pH4znuc3rFu3OmqVriDo8OGHCxd/amtr+2Kybbu7d+8OHzniu737njx5QkSWVpYbN21q8t57RLRuzZrPVq0uKCgQG7cLCFi3ccOra17CUnp27/Ho4UMi+mjgILlCnnD7tu6vNBpNuw9a5+bmHj56xMPTU6w8gnv1ys3NvRATLQjClk2bVixbznIsx3JyhTx8xowhw4aJfxsbG/tRyMCnT5+Kk1ZWVl9u2fxu48ZE1LVjp4SEhJGjR21Yt757jx5+jRoZGAUAYPQFAMopJycnNTX1Wty1pUuW7Nu7t2dgrw/atBZfYllOV+WI9YpCqdQvX8RJ/Wabv9y0PHLZB61bn73wa/Tvv02cPPn4Dz/MnjFTtziW44jo8KHDI0eP/mr7NWmnAwAABrxJREFU9u49ejzPff7ZqtVEpFarl0cuq1OnzonTp2J+/33r19tatGpZ7DqXsJQFCz9p1rwZEU0PD1+7br14Eo9utKlTly5EdPLECXFOglqdmpratVs3MzOzQwcOLl70ab8B/WOvX794Oeb995t+unDRubNnX+zaGFno+PGHjnx/ISY6csXy3NzcqBUrxZe0LEtEe3bv7hUYGNC+veFRAABGXwCgnGaGh+v+H9y79/BRI2WFlxeJR5dUZmL5ohCHKwrLl78mdc1Yll23dq1CoVgSubRy5cpENH7ihBPHj584fvyPO3fqvP02EVlYmBPR5q1b67nXIyJfX9+jR44kJyUR0b0/7xJRXfd6bm5uDMM0b9GieYsWr65wyUsJaN/+3C9nz5877+vnK46O6OsVGLhn166Tx09MmDSJiE79eIqIegUHEdHyyMhatWrNnD1bJpOZm5svXhrRsmmzPbt2i+vg5e3l5e0lDvz4+/srlcqHD9P0e2l6eLh4DtCxI0cNiQIAUL4AQHmIxceAkBC/Ro04nvvjzp1vt3+zb+/eufPnhQwa9FddolIRkVi3sFq28G//mtQ1S0lOzsrM9PH1FasK0Xvvv6+Oj1er1WL5IjaWyV4MilhaWVpZW6enpxORXyM/SyvLg/sPJKjV3Xv0DAwOqlq16qurbchSiEh3XEmf/7v+Ts7OarU68cEDJ2fn06d+rPP2297e3lmZmampqXY1akyaMIHneYEXxEux7t+/L/4hx3GHDhzcu2dPXGxsXl4eET17+ky/fKlb98URNwOjAIAKBQePAIysfPFv/G73nj16BQZOCwvb9s03PM9HLF7CsmJdYqZrLJ5/yrLaVyd1zTKzsojI2tpKfylikfEk40nhl72FOIKia2BmZiauSQ17+2937mzdps3NhJuREREfNG+x89sdr652qUthObbIInQYhukVGEhEx44eS01NjYuNCwwKYhgmOTlZfJXneBKIYRi5XP5hx47+7/qLHTX944+nTZ3KsuykKZP37v/OvqY9x/OFEZkRkYWFpThpYBQAgNEXAChX+UKC/oAKEXnW9zQ3N8/Pz09LTa3l5CSXK3QNOI6lwvM8ikzqmlW1tSWix+mP9ZeSlZlJRLZVbfXHKgr0hkbMzc34wlKggZfXxs2bkpOTv92+feP6DfPmzOnavZuV1UuVSqlL4ViOiLQF2mKj7tmr5+qoqGNHj6hUKplM1qNnDyJycHAkImdn5y/Wrnn1T5KTkg7uP+Dr57dj9y7xyJpcJhcK11k8vUb/aiZDogAAjL4AQHmIX/O6ARUiOvPTz/n5+VZWVjXs7YlIvHZGqy2gwvNz2cKyQ39S16ymg4NdjRq379xOS31xXgjP8+fPnyMiXz8//SEfVq98YRiGZVme53UVgKOj47SwMA9PT47j0lJTi6x2qUthX5RWxZcvtZycGjdpci3u2vavt7Vo2dKuRg0iqmJbxcnZ+XJMzB937ug3zs7OJqLExEQicnZx1p0VpF+B8bxARLrLvw2MAgAw+gIA5SF+wV/49YJGo8nLy7916+ahAweJaFrYdPHCIvErWTyJ5MVwi1b70uiLVqvfTC6XT546Zcb0sOFDhsyYPdvGxmbXzh23bt4KCg52dHQs/LIXa6a/hnzE73tNfn5cXNzmTZs6de7s6uoaEx1z4/p1VzdXV1e3Iqtd6lIKyzL2dYEHBgdFX7p07+69KVM/1s2cM2/eyGHD+gQFT/54qoeHR3Jy8qEDB5s2azpk2DAPDw8LS8tjR456ezes6VDzp1Onk5OT5XK5rnjSL1+iL10yJAoAQPkCAOUffTl08OChgweJyNLKspG//9Dhw9oFBLwYYCjQG3dhOSLiOF5/9EWc1G8WFByskCuiVqwYHBJCRCqVavSYMeMmTtAtVP/dioxeWFhYxl2NPXXyR3F+i5YtZ8+bq7tRnr6SlyKOvhS5G56+Dzt2nD9nLiNj2ga0081s07bNxs2bliz6dN7sOeIcNzc38T0rV6myfOWKGdPDFi5YIJfLW33QqlKlSjk5OeLtYcTyRXeXF8OjAICKgylyh00AqLA0Gg3PccQwMplMoVDohhP0G+jmFxQUKBQK3dET/Un9ZjpZmZlPnz51cHAs8s1dUFAgl8v1G2s0GqVSKb4Vz/Opqak5OTnVqlXTf3jk6xS7lIKCAoZhFAqF/k1fitRtLZs39/Hx+d+6ta++mpOT8zAtraaDg7W19UuDVVrtgwcPHGrWtLC01F/ngoICmUwml8t1iytrFACA8gUAoBQnT5wYM3JUxLLIoOBg9AYAENH/AQV5hyHvqTQoAAAAAElFTkSuQmCC
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AAAAciAAAAAAAADIgQAAAAAAACAHAgAAAAAAgBzo/xGLxYWFhZVtLoZhoR9Dfa9ehchVI0KhMDkpGS6wgiQmJt68fl1LLlmrjPlPiVNLDJZrRkZGRoC/P7R45aCWua5SL6d6qwCNIAiNHMj36tU7t27fCKjEqD9/9sx79er8vPzmLNbL10E1S0MF+flbNvukpqbm5uYyGQyCINq0bWvv4DBrtpc0vVu/dl1CfHx2drYuk8nj8+rXb+Do5Lhh06ayR8vOzq5bt66enl5Fc0oJhhCiM+hq7bVw/vzgN28fBD5u0qRJrWy/KvsCY6JjVi5fHhkR0aBBg/efQqv3YrXKGO2PXW01uJQZCQkJK5Yu/R7+HSEUn5wEOQ11apnrquByqrcKMDRyFBzHL547n5CQEPHjh0Pr1pVka18Xl2MnTk6dPLkmKsnUzOzPgwcIghg1fETEjx8+W7dMnjJFtgCdTt+5exdBEF6eM4NevRo3fvyuvXsUHW3ntu1isdjWzo5Go8lub9iw4QS3idSjNn3qVJf+/WZ4eqqXtgsEJSUlOTk5tTUHquwLtLaxXrdh/czpM7ThYrXKGO2PXW01uJQZLVq02LF797TJHnl5eZDWqEUtc10VXE71VgHN5EBv37zJyspCCF2+eEnJnbuC0Ol0p85ODRs2rLl6otFo5ubmEQgZGRkrKmBtYx306pV5o0aKDiIQCJ4/f87n8QIfPy7102QPD4So5kCXL156FxLi0r+fuldx4NDhsLBv7dq1q62tWGVfII1G6+LsbNmsWUF+vjZoUnuM0f7Y1VaDS5mho6NjZ2fXoVPHF8+eQ1qjFrXMdVVwOdVbBTQzHujCufOHjh6hM+j3791T3pLu3rmz4k121bup4mZr8AL/fv3afdKkoLdv3oV+lP23dcf2Pi59KZ4lISHh65cv5bPQwNCga7dutbgVq5oLZDIY2nPJmjKmKmuKpmJXvTZrSW2SawYN0RBQvma8drmuUi+nequABnKghIQEoVDYq3fvQYMGC4XCG9dvKCqZk5Pje6XmDWfWNrPr1KmzfOUKS0vLhv8m7Ou3nr16UTkCJsH27NrlvW4tNFVALa4ptdVmAAC0KAe6dP7CdM8ZCKEp06YhhK5evoxhmNySflev4hoagl2VaJvZvXr3LjsaOjUlpamlJYPa0/zxY8cmTnQzNTODCgDU4ppSW20GAEBbcqDCwsLQ0I8u/fohhDo5drK1tf3169erly/Llnz29OnRI0coHjbl58/AR4/9b96MioxUVIbL5YZ+/Hjz+vXXQUF8Pl9umYL8/JDg4NCPH4uKisr+mpmR+TooqNTGrMzMoFev1DU7JyfnSWAgQkgsFr8LCblz6/abv/9WZBVCKC/vd5oCiouKyxGIo4ePTKQ2GvrH9++ZmRnlGAYkhc/jvXr5sqCgQLolOzv7wf37CCFMggW/Db4dcCshPl7R7sqDkpeX9/TJE4RQcXHxwwcPoqKiZH8ViUSRERFPnzyJj4sjU+2CgoLnz55JXa1cORTtLHuBJAkJCU8CA9++eZOVmalBMWASLPRj6KMHD38m/yyf0yQSSVhY2MsXL3NzcyvbGEUeVl5TMAz79vXri2fPk5OScRxXLjC5hfl8fklJCY7jYrFYGhoelycQCEQikdQtcmOnyD9KbFbi0vJ5WJGw5Rqcn5f/7OlThBCO46EfQx8+eCAbDoFAEBIcHPj4sVwdKq8CaplRqlLweTyCIHhcnvQzKJgEK8jPxySYUCjk83jlaM+p+5nifUHdFkmlMpWcVHljpRHXqTSvpKTkXUhI4KPH38O/FxcXI4QIghAIBGrd5tR1b1kqothS2qNY0zVFRQcB3Lx+o1v37snJyeSfffv1i46OvnzxYn9XV9lif+7bf/niRQIn+DyeY4eOCCEaDZ2/eLF1mzaltZuVtWrFyqTExJGjR6elpq5Zucp90qQt27eVGiVz9/adbVu3mJiYZKRniEQiU1PTvX/u7+viIi2Qlpa2ZuWqjIz0nr16l5QU/x30evCQIctXrTQxMUEIhYeFb/Xx+frli5W1de8+fchdwsLCdmzd9vnTp5YtW/bp25ei2VFRUX/t2/c66LWFhYWent6alau4PB6paRMTkwOHD/Xq3bus3w4fPHTm9Bm5Li0uVjvGET9+cHlcJcOopQiFwj/37T945HA5sx8+f+Ef80OCg0Ui0f1HD01NTRPi4302bX7/7p2hoaGdnd282XMKCgrIGQTTPWesXb9eR0eHYlB+fP++d/fudyHvDA0Nnbt2HTV8RMrPnwih6/43Ozk6IoTevnmz3nsti81qZWW1f89eHMeHjxxxyz8gKyvrxOlTdnZ2SpRD0c6yFyi9z61ctkxHh25ja/Py+YukpKRRo0dv27lDV1dX1j/lEENUZOSi+QuKiory8/NxHPeaM3vVmjWyalfuNIRQbm6ul6dn06aWzZo327ltW+++ffLz8vcf+Evjxiipm8prSlJS0oolS1tZWfEF/FcvX7GaN9++e5eiIZCKCt+7c3fb1q2k/R07dbrse1VPT8/P9+qhAwdxHJ88xWPx0qVyY6fIP0psVrRLaXdR87AiYV+4fPnCuXOlDE75+dNn0+a3b98Y6Bvcund3wbx52dnZRYVFOI4vWLRw8dKlr4OC1q7xxiSS3NxcJpPps3WrdCqo8sZTLTPk9PdfvPTn/n2YBKPRaKPHjNmzfx9C6GfKzzkzZyUlJZmamm702Txi5Ei12nOKfqZ+X6Be05WLTeVJVTZWFXedSvO4XO7e3XtePn/e2bmLpaXlg/v3g169atq0qUnduk6dnVatWUPxNqeWe+XmiOVWrNz2VmVNX7NWo6M4iAogEUv69+nr2tdF9p+dlTWHxY6PiytbfszIUa3t7JUfc+b0Gc6OTlmZmeSfO7dv57DYn0JDpQV6deveit1ivffa4uJigiBEItHD+w/aObTmsNhPnzwhy6SlpbVzaP3HnLkCgYDckpGeMcCl38hhw8ViMUEQxcXFfld9OSz2INcB0iPzeLxb/gFWLVq69nWhbnZBQcE1Xz9rDse6JWfOLK+fyck4jufm5l66cNG2lZVVi5YvX7yQLT9rhieHxb5z67aiA+7ZtYvDYu/fu49iFHAcn+zm/vfr11QK79y+/e2bt+T/BQIBh8U+d/Ys9YjjOP71y5dhgwZzWOzIiAjS/y9fvGhjb2/N4UyfMjU+Pp4giKysLA/3SRwW+/69e9J9VQalpKTkut8121ZW7RxaL1+61P/mzffv3i1bvCQ1NZUgiPi4OAcb260+PjiOk8EaM3KUdUtORnqGWCzGcVy5cijaWfYCCYLI+53X1anzlUuXyD+5Jdz58+ZxWOzrftcqIoZhgwbbWVlPdnNPSkwijRkzYiSHxX4SGEjdaQRBeK9evXjBwn80zOVOHDduzIiRlWGMyropt6b8+vXL2dFJ6syY6BinDh3b2jvExsSUFZjywt/Dw1vb2dtb20gLFBUVDXDp9+H9e0WxU+IfJTYr30XdcCsUdkpKWYOFQuHTJ0/aObS25nA8p01PSEggCOL379/uEyZyWOw1q1YvXrCQDEFMdEyfnr2sW3Kk+yoPkFpmkMyZ5cVhsaV/hn4M5bDYs2fN+tddQCLp1L7D+3fvytGeU/QzFe1Jod4iqVSmkpMqb6w04jrl5onF4vFjxk6a6Pb792/pLqkpKc6OThwWOzIyUq3bnEr3lrocWSqiWEV1VnlN1ywVyoEeP3q0eePGsndZDou9acPG8uVAt/wDQj+Gyp6Cw2LfvHFDNgfq2bUbeSOU8uH9ew6L3a9PH/LGMGeWl4ONrTSiJC+ePeew2MeOHJF637FDB1lxkDg7OqmVA5FnY6VwAAAgAElEQVQMcOnXpZMjhmH/OuPzF6T+JBJJ5eVAL56/6NbFWfYUivjw/r3Ppk3SP2VzIGnVpcKBP/8sJVnyDpqflyfdkpWVxWGxJ44bJ1uLVAaFIIgB/fpzWOwL586XOulWHx8Oiy1r57OnTzks9rkzZygqh6KdZS9w4/oNI4cNl5WcRCK5ce2a7HHKIYZhgwa3tXcoKCiQlklKTOKw2FMnT1bLaaOGDx8zYqTUvJ/JyWNHja4MY1R6WFE+sWzJEtktV69c4bDY06dMLes6lYX/fv3amsPp4dw1JycHw7A5s7yuXrmiXJzK/SPXZuW7lC/cioRd1mCCIEaPGGFvbSMbjtiYGA6LPbC/q2xNDwkO5rDYW318qFcBtcwoe+cbM3KUVYuWstUwPj6+f5++pRpkipqh7mcql6ZuTVcpNpUnVeRMjbhOuXmXL15sbWefmZFRaq8JY8dZtWgpEonUus2pvFIlOVBFFKtEeypruqao0HigSxcukuOgZZns4UGj0W4F+JeUlJTjmKPHjnF0+l9foq6uHvm29V8v8JjMUn10nbt06da9e3JScnx8PI/Le/7smb2DQ6l3Q7379qEz6Nf9rpF/0mg0ud9Z1qHTy2G2rq4uQRCyvawIob4ufR2dHONiYxMTEippPBcmwXbv3Dlm7Fi6KrNxHF+1fEVkRMSMqdPIf7NnzkQI+V256uE+yXvVauonLdtBqqurq6enJzvI2tzc3LJZs7jYOOnbXCpBQQgZGRnpGxh4TJ1S6hTxcXEIoUYyu1tbWyOEYqJjqCtHpZ1lLxDDsJvXrzt3dZbdSKfTx0+cqGhQOXUx6Ovr161bV/onuwXb0tIyMSFRLae1bt0mLCxsxtRp375+JQiiOYt13f+mxo2h6OGy+rwdcMve3p7scv4e/n3n9h3+N27M9PJa5b2mHIV79uq1Y9eujIyMebPnHDl0qGHDhpP+/dHUsuJU7h+5qLULRQ8rErbc1w00mo6urq5sOKysrevVq4djmGxN79y5i66ubnhYOPUAqWVGWWbM9MRx/NKFi9ItL5+/GDthvKLdlZtE3c/qak9lTaciNpUnVeTMirtOuXkEQRw5dLhnz56NLCzK7mtiYsJkMtW6zZWjamtEsUq0p7KmV/94oMiICH19/ZYtW5ba3qx58959+gS9enU74NaUaVPLd19///596McPX798iYqMorhX+w4dQoKDkxOTREIRQqg5q3mpAnQ6vWlTy5SfP/l8vr6+PkIIx3ANulIkEpVtVpw6d/kU+ikxMdHK2roy4nf79q2E+Pixp09Teek5cPDgf4+2kwS/DW5obu7QunVZd6mHPBFbWDRKS039J4OJj6cYFIQQg04vm9I1btwEIZSRnt6cxZK+Dif1poZyVNlZlrTUNJFIZG5uXjViaNykSdi3b2o5beWa1enp6a+Dgt6+edOyZUuvuXPGjBmrcWPKVzd//UoTi8VpaWl/7tv/8vlzG1vbUWNGr1qzWm7KTrHw2HHjsrOy9u/dl5qS8ndIsEobVPqn4rtQ9LBcYavxoKWnKxQK/6UEBt2sXj3ZEbVUAlQRMwYNHtzIwuLGtWuLly4xNDRECAU+enT81Mnytedq+Vk97amq6RTFpvKk1J2pluuUm5eZkZmbm9uiZQsq107xNle+227FFasE5TW9T89ehTJD+M9dvNChY8dyGFn+fqAL586TU+LLQubFly9eVDkBpCzR0dGu/fotXrhQIBAsXLxkx+5dFHesX78+QqiheUMut0TJY42Ojo70J4IgcAXT+DWSAyGEGjRogBAyq5xZ6BiGnTx23NHJkd2CrbIwnU73XrdW9t/K1asRQv0HuHqvWzvZw0Pj5uno/K9poB4URbhPnqyjo+Pn6yvdcv/evTp16gwaMriCypG1sywlJcUIoZ8/U6pGDNIHOOpOMzExOXvhfMCd264DBiQlJXmvWu05fZps06MRY8rn4d+/fyOEXge9ZrdgXw/w33/gr569eim6Z1Av7OjUWU9PLzc399SJkyptUOmfiu9SNXWfydStpMZT4YMTKv3VAAaDMWXa1JKSEv8bN8lR4aZmZkpmYyg3ibqfNXJpsjWditgqctIKuk65efkF+QihnOwcikN+Vd7mVF5p2cvRiGJVoqSmb92+bf+BA9J/Lcp0x1RuDpSTkxMZEdG9Rw+5v/bq3btZ8+aJiYkhwSGlbsOEqqxo5dJlv9LSbgT4r1m71tHJUSKWlL7x4/LDmZLyU09Pz9bOjsVmI4RSyty0MAzLysxks9l16tSR9mRmZWWVTdRKrSNLxWyyHSy7AG1aaqqOjo6NrW1l5ECBjx8nJSWNHT8eaSWyHyuiHhRFtG3XdvfevWdPn/Fetfrm9evrvL1v+QccPHyYw+FQVA4VO8tC9nR+Dg1VK6HXiBgoOu3m9es4jrdr3/74qZMvgl4NHjok+G1w4KPHGlemSg+XrSlkE0/X0Rk9Zgz57KsEioXjYmNXLl8ecPdOx06dDvz5Z9kVY0qh3D9ya7dKl1ZL3Weo6m8odxVQhEDeNxTcJ00yMDS4cP48+Zp47Lhx5TaJup81cmmyNZ2K2Cpy0gq6Trl5LVu21NHR+frlC0bhGZ7KbU7llQoUf02jIopVjvKa3rNXL5d+LtJ/iuYzVlYOdP7s2X6u/Uu9Apd9QiX7FS5fulhKggKBgPx0QVFRkVgsLu1ogSAqKsrc3Fz6ii07O5sMl0wZobjMU5dIJHpw7/6s2V6GhoZNmjRx7to1MiKi1AcnXge9FgqFfWTmz7fr0L6kpOTjhw/SLYWFhTwuF/u3XFSaLZVUqcdBTII9fPhw8hQP2bekVNJ2iiVPHDuur68/ZOhQub8KhcLIiIhyBDc/Lz82JlalhWJ1WgTqQSFH6cs9SETEjwWLFg0aMpjPF7i49Hse9Kqfa3/qylE3BOQF6hsYdO/RPTo6OuDmzVJllHzOh4oYcAJXnldRdNrVK1dfvfjni1zNWawDhw7VrVv3589kzRpDxcNla0rTpk3t7OySkpL8/+09TIJ9/vSp1CmoFM7IyJg1w3Pbjh22trYnTp9qZGGxYumyiB8/lIhTuX/k1m6VLi1P3VcgbEW1qWxhGo1WdqN0C9UqoI4ZPJ6cO1/dunXd3CelpqQEPn78OihIWgfLoRmKftZs7aYoNkonVdxYVdB1ys3T09Pr3KVLUlKS39WrKmWj8jZH5UrlXk4FFatceyprusbeV5Rjn9zc3KuXr9jZ2yspM2TYUITQy+cvvn39Wuq59l1ICJ/HW7JwEflBBVnq1Klj3qhRRkYGeXdJTUk5eeIEQqi4uCQqKioxMTE9Pb0gPz8rK0v27i4QCBbMm9egYYM5c+eRW/bs38dkMrdu9pHmK7m5ufv27G7atOmSpUulO7q5T0IIrfP2TkpKIggiLjb2jzlzhUJhRnr6g/v3pV2yKs2Wcs3XT1asK5cvNzYyWrJs2b8yjPx8hFBaWppC9+bkIoTyVS3Sm5iYGBUZOXTYMEUPMUsXLR41fETox4/q3v6XLFroNn68kk+W5eTkIIR+/879X7dEViaPx8vPy5c9DlmRpBupBIUgiPyCAj6fX/blwof376/5+s2b/0fvPn2mTp/Wz7W/kZERdeVQt7PsBXqvX89kMtevW3fi+HFynGB2dvaShYsunD+nxJPKxYDjeEZ6Rn5+vuyrcYIgcnJyxGIx2RNO0WkNGjTYtnXrP80WQgUFBXw+v3OXLpo1hoqH5daU3fv2MpnMjevWnzpxsiA/XyKRhH375jHJ/cd3Oc2Z8sKZGZkzpk7znDWrR88eCKF69ert/+tPgUAwe5aXtFaWip1K/8i1mYpL1Qq3EmGXNRjH8fz8/JKSEun39MhjFhQU5Obmyh5BLBbn/f5dwuUSBEElQGqZQU5IJiVXqvCMmZ50Bn2999oBAwfKHXJLsVZS9DOVSyvdUUqhpisXm8qTKnFmxV2n0jyfrVuYTOaWzT5HDh0m1+gsKirav3df2VUgVd7mqFyposupiGKVaI9KTdcY6k4ku3vnTtfOXTgsdueOndZ7r5V+pESWfXv2Dhs8hMNic1jsTu3a/7lvn3QqYOeOnTgstoON7akTJxXNt7ezsu7Urv3IYcNdevf+9u1b185dOrZt17t7j8yMDL+rvuNGjxk2eEhbe4dZMzx3bNu+ztu7T89ey5cuLTVROTYmZurkyQP7u27bsnXlsuXOjk7z587LysoqdbpTJ05at+RwWGx7a5uB/V0jIyK6dXHmsNhjRowM+xZG3WzyCwd9e/We5uGxZ9eurT4+g1wHrFq+glvCJQuIxeJzZ854Tptu1aIlh8W2bsn5Y87c40ePSidG4jh++OChaR5TSL9ZtWg512v24YOHFAXC76qvbSuriB8/FBXY5rPFwcY2OipaUQGRSGTN4fhevVrqkxWDXAcomneamJjo4T6JvIQunRyXL10aEhzcu0dP0uYBLv3IaaLfvn0bOWw4ubF/n76XLlykEpTQj6HSvTq0aes2fnxqSors9XJY7O7Ozu4TJk6fMtVr5sz5c+etWr7iSWAg6UPlynkXEkLFzrIXSB48PCzcpXdvsqRTh47Ojk6XLlxUNKlVpRhCP4aSTiaNOX/2HGkMOdWWw2J36+J89vRpikre5rNlzcpVfXv13rxx4/69+/r36SsrGw0ao9zDSmpKSHCw9BQ2nFbOjk53biv8NoSiwk+fPGnfug1pJGl8YWHhkIEDyZL21jZ+V33lxk65f+TarHyXcoRbrrDliu3zp08D+7uShbt27kKa9CQw0LWvi3Qj+WWNe3fvSjU5dOCgN3+/UR4gtcwIDwsfPWIEWbi7s/PJ4ydKXfXKZctLzfQuR3tO3c8qtSeFYk2nokwlJ31w/76ixkpTrlNp3rdv3wa49JM2Sg42trt37hw9YkSn9h3Uvc0pudJnT58qv5yKKFau9lTWdEVfVCofNELN7sS8vDw9PT06nV5cXMwt4bLYrLJjNrMyM+vo6+vp6TGZTD6fzy0pkU7h43F54eFhnFatGjZsqOgUGRkZnz99MjY27tqtm66ubkFBwft379q372DR2ALDMHIoqEQi+ZmcnJCQoK+v79C6db169eSmd+np6fFxcQwG09bOlhw0Lfd0P75/Nzc3b9O2rY6Ozotnz1u3aV1qzqFKs4cPHhIbGxsdHxcdFZWSkqKvr29nby9bGMfx1JRUUzPTOnXqMOgMgVBQUlzM4/NbtGghO4DA2MSELCAUCsky0mlQZV//cUu4ZvXMlGS36enpTZs2VTctfvvm7fQpU+49fGDv4FD6AUuCFRQWmJiY6NB0BEIBj8czMTHhcXnGJsY4jvN4PEQQpmZmEomksLCQ/JAxt6SEzmAYGxurDIpQKCwqKjIyMtLV1cUwrLi42LSuKZ1Bl5769KmTgY8DCwsLcQwTiUQ8Ho/P5+M4vv+vv0aOHqVcOUKhkIqdBvoGpS5QGkSCINJSU+Pi4ps0bcLhcEqNF1ZLDEKhsLCwsG7dunQ6ncvlEgRhamoqEokKCgqMjYx0dfW4PC6O49I33FSUzOfxfvz4kZuT26ZdW0tLy0oyRomHldcUDMMSExJSU1KbWlq2atVKGla5yC0sEAiEQqGRoVFRUZGpmSmNRsNx/Pfv38bGxkwmk8fj0XXofAFfbuyU+EeJzUp2UTfccoVdtjY1bNiQXDnBwNCQTqcLBAKxWGxqasrj8kQioZGxMUKIx+PRaDRjY2NyPQEDAwOCILhcrp6urr6BgfIqQN2M/wlAT09qhuxVP3v69JZ/gPIZYSrbc7X8rPI4Um+r1SIpV6aik5rVM1PUWGnQdSrNwyRYYmJCTEyMkZFR+w4dTE1NJ44bn5CQ8OnrF3Vvc4qutF79esovpyKK1dXVK6s9lTWd/PCBprqB1M6BACXtYExCfC24li+fP2/fus3/9i2KnwypRgry80eNGMlmsy9cvgRiqPXKhLqvPcyeOdNz1iznrl1BAFrlOkU5EKDJ8UCAnBeiBI5hmEQiqekXwufx9u/dt2f/Pq1KgAQCwdTJHiHBpT8RYWpmZmtra9nMEsRQ65UJdV97CHr1is8XdHF2huhrm+s0+8GX/wIMcIEGGkEcJxd7/52bK/fDnTWIoqKiLdu2Siecawk0Gi0xMcFz2vTV3msmuLmRw8AFAsGtgIDo6Ogb2/1BDLVemVD3q531a9dyS7gmdeveu3Pn1r272t9P/F9zHSbBEhMTyfXVSy3nDCgC+oEqSnhY+JCBg9LT0+kM+vgxY8klAGvu5TSysOC0aqVtVunp6d1/+Gim1yz/mze7du7cq1v3gf36k2s1P3j8SN2POFelGMrxmVBQJtR97QSTYIGPH0f8+HHhymXZgYyANrhu25YtXTt3LiosFIvFfXr0vHzxErid0gM2NIsVRCKRlJSUGBsb0+l0TILx+DzpaDugMiAIQsDn6+rp0Sv2Aa7KFkPKz5T9e/dmZWXm5OR4zZ7jNskdlAl1v6aD47iiz8IB1eu6kpISJpNJdv+QnzTUNzAAt0MOBADVQH5e/tEjh1esWlWnTh1ynt2pM2dc+vcDzwAAAGgPkNEDgOYJ8PdfvmIFuZZFj549HJ0cHz9+BG4BAACAHAgAajm2dnayHdFmZvVgiCIAAADkQNVGfl7+7YBbZ06d/vzpE7wBBCoV8hPvJDiOR/z40bNXL3ALAACAVvFfmRv/6MHDgwcOWFg0+vLlK5/H89m2lVzVFSFUkJ+/ZbNPampqbm4uk8EgCKJN27b2Dg6zZnuRBTAMW792XUJ8fHZ2ti6TyePz6tdv4OjkuGHTpkq1ubi4ODsrSyQWm5ub16tXr3zTKb+Hf+fxuIp+rVOnTrv27as+HDiOfw8P//b127QZ07VQLRrxvJSngU/YLVq4DhigPUFJTEz8HBo6fuLEGlSFtcrmmuhARWRkZIQEBytf/l0thEJhRnoGuwVbqx6Ag169+v37d4eOHTp26lTts/q10EVV43NtCwT6j4yJDn4b7L1q1cMngcbGxvl5+Zs2buji7CzNgUgIghg1fETEjx8+W7dMnjKl7EEIgvDynBn06tW48eN37d1DReWLFixIS00Vi8RcHk8oEDRnNbewaCwUChlMxpChQwcMHKivr192x5KSkquXr4R9+8ZkMltZWQmFwogfP1JTU/r1d/WaM7tBgwZqXfuJY8cyM7MU/VqvntmiJUuqOByhH0MXL1iQnZ1tamam6HumFUlMtcTzJDk5OYvmLzh+6qTsB+Y1GJRBrgNSU1IkEomurm79+vUFAgGO44ZGRnS6TklxCYPJ0NPTKywoLC4pJnCiUaNGC5csuXLpUmRERIMGDd5/Cq0R9TcmOmbl8uVaYrNWGVNBEhISVixd+j38O0IoPjlJU4ddOH9+8Ju3DwIfN2nSRMsfgKsLbXNR1fhcCwPxz6291jOwv+vRw4dVFps1w5PDYpOru8ll986dHBZ7/9591E+NYRi56F2Av790Y2Rk5OABA1x6905OSi67NGDv7j0C/P0lEons9tTU1JnTZ7S1d1Cy2GRNAcfx9+/etbG3L7u2X9mSI4YO47DYVy5dUlRg5vQZHBZ79YqVWuh5kUg0Z5ZXfFxc5XmSw2KPGDosMjKSNBvH8fy8vA5t2nJY7Pv37mEYRpYsKCg4efwEh8UOfPz4/bt3Dja2XTo51izBaInNWmVMBcEwLDIy0qlDRw6LrcHDenl6WrVo+e3bN224xrdv3vbs2q2oqIggiLzfeQvnz79y+XK1W6VVLqoan2tnIAiCKH8OtGvHjhoRj9SUFPJ+UPEcaM+uXermQARBuI2fwGGxXzx/IbsxPi7OqkXL/n36ikQi6cbTJ0+1tXeIjIyUexyJRLJ00WIlCUHNYsTQYSpzoAomptXu+Z3bt3/7+rVS72Gt2C2SEpNKbSdXbI6Jjim1fZqHx+NHj8inghp3C9cqm2uiAxUxe9YszeZA3BJuSHBwzXoArmK0ykVV43PtDARBEOUcE52Tk+N75WqN6JT7+vUrQohcMbh6XjfKe+XJadXKqXPnpKSkRw8e/jNq5MmTXTt2rN+4wc7OTu5x6HT61h3bLS0tt/j4hIeF1/TOUk29CVZynOr1/DVfv67dulXqyB6CIAYMHEh9VMFEN3cjIyOEEJNR8wYCapXNmjJm986d1V8TEU2z9hsYGnTt1k0bwpSWmhofF9ecxapeM8p6SXtcVDU+15JAyKWcOZDf1at4DRlIxOfxEUI6Olr3TWFSEOHhYQghPo+3ZfPmJk2ajBmrbGSioaGh56xZmATbs2sXArTY8y9fvDQwNOjdpw/5Z0ZGxoa16zR+IXQ6/eiJ49TLDx46pEfPniAALaEGPUnWUPur/QG4FkRZIz7XhkBoMgd69vTp0SNH5P6UmZH5Oiio1MaszMygV69kt+Tl5T198gQhVFxc/PDBg6ioKOlPGIZ9+/r1xbPnyUnJFNdaKsjPDwkODv34saioqOyvQqEQIYRhVFd1zsv7naYAcnFETSEWi6R9FU8Cn2RmZPbt14/OUJGrjRk3ls6gv3/3Ljo6Gu4i2un5oqKixQsXrvNe28beoY29Qxs7+55du7Vu0wY8D9TQJ8kaar82PADX9ChrxOda2xOByjE3/s99+y9fvEjgBJ/Hc+zQESFEo6HzFy/iOLHVx+frly9W1tbSx9+wsLAdW7d9/vSpZcuWffr2RQj9+P597+7d70LeGRoaOnftSi57iRC67n+zk6NjUlLSiiVLW1lZ8QX8Vy9fsZo33757V7t27RQZk5aWtmblqoyM9J69epeUFP8d9HrwkCHLV60k880rly4d+OuAUCBACC2av4Cpq4sQ+vvtWwNDZauoHD546MzpM3J/Ki4u0pTfCYL4HhaOEHJ0ckIIkRmhoncxshgZGTk4OISHhb95/betrW0VSCTl58/IiMgSbomDg4Odvb3sT9nZ2R8/fBg2fDgmwd6/f5+dldW2XVtFS67+/v077Ou3wsLCBg0bOHXurJYNZGIqPyhqJqZV4HkTE5PvkRGyZyTrhRbWf0yCffnyJSc726F1axabVfaRJiYmWlqdpY80UVFRZHUmkUgkERERv3N/t23Xthyz53Jycr58/jxw0CCxWPwpNDQrM6t+g/qOTk5y5+6ptFn6XBQZGclkMm1sbcs+fSoxWOPGKKo+5JOkrq6e/MNi2Pfw8N+5vzmtWjVnNVe+zpRK/yv3htxHWZVxV2I/n8d7//59h44dZedCqjSDYmOiltgUPQBTuUC1GreEhIT4uDhDQ0MrK6tGFhYqo6zIRcq9pJZJ1JtxdeuvcnHK9bmSngiVUlfk22rLgZatWL5sxfKxo0bHxsbKTmwuKSkZO27c1y//mupsbW3t5u4uu7FFy5ZDhw3/+OEjQRBbNm+ev3CBpaXljWvXG1lYpKenT5ow8dzFC2SEYmNiPdzdp06a7H/7ltz7x69fv4YNGty9R4+zF87r6emRyp7m4TF1sof/7VsMBsNj6lSPqVPPnzu3fcvWvw4dcunnQuUCN/n4jBw9Su5Pe3fvPnn8hEb8fvnipYSEhK7dupGfjfn5MxkhVK9+PSr7tm7dJjwsPDY2prJvkNlZWatWrExKTBw5enRaauqalavcJ03asn0bjUZLiI/32bT5/bt3hoaGdnZ282bPKSgoyMvLQwhN95yxdv16WSkXFhZu37L1w/v3g4cOadiw4ft371YsXcbj88moUUGDiWnVe55Go3Xs1EkLE6CoyMhF8xcUFRXl5+fjOO41Z/aqNWvI7rHwsHAqjzQIodzcXC9Pz6ZNLZs1b7Zz27beffvk5+XvP/AXJQOiov7at+910GsLCws9Pb01K1dxeTw+j0fmkQcOH+rVuzd1m6k8FykxWOPGKKk+ip4kyc5CtR4FlftfpTdKQTHuiuzntGq18I/5IcHBIpHo/qOH0hu8cjOoNybUxaboATg+Pl7lBarVuOXk5KxctkxHh25ja/Py+YukpKRRo0dv27lDV1dXrpeOnTh58vjxsi5S7iW1TKLejJej/ioRp1yfe82effrUKUU9EcqlrsS3mmwHyzeUeszIUa3t7MvOGnXs0GGQ64BS250dnVz7ushuGdCvP4fFvnDuvOxG79Wrly1ZIrvl6pUrHBZ7+pSpcm2YM8vLwcY2KzNTduOLZ885LPaxI0ekW86dPVt2clBlzAvDcVzudvcJEzks9snjJ358/x72LSzA399z2nQHG9tNGzZyS7hSF3FYbHLOjkr+2r9fkVswDJNOh644M6fPcHZ0knp45/btHBb7U2goOev75YsXbeztrTmc6VOmxsfHEwSRlZXl4T6p1Cw8oVA4YuiwObO8+Hy+dOProCAOi62ReWFKglJzPV9BFM0LkzJs0GA7K+vJbu7knLKsrKwxI0ZyWOwngYFkgeLiYr+rvhwWW7Y683i8W/4BVi1aylZn79WrFy9Y+E8BLnfiuHFjRoykaGdBQcE1Xz9rDse6JWfOLK+fyck4jufm5l66cNG2lZVVi5YvX7ygbjNBEGlpae0cWv8xZ65AICC3ZKRnDHDpN3LYcLFYrNxgjRujpPooaUV//frl7OgUGRFB/hkTHePUoWNbe4fYGPnRVOJ/Kt4gG1LpvDDqcZdrP47jX798GTZoMIfFll6CSjOoNybqiq1s40/lAqnbk/c7r6tTZ+l0UW4Jd/68eRwW+7rfNUVekusilV6ibpJazbi6LqUiTrk3XLkblR+Nim+rc16YoudduU/2OnR62dcK+gYGHlOnyHYp3w64ZW9v/8/bivDvO7fv8L9xY6aX1yrvNWWPyePynj97Zu/gYN6okez23n370Bn0637XqvJ5+tevX8uXLHWfMKFfnz7XfP3klklPTw8JDgkJCSYIYrrnjJCPHzZv8ZG+lSOfh8i8XiWGhkYIIQMDOW/0Vi5f/jTwiaaua+iwYYePHZN6uH2HDmTmjhBiMpl9XVxYzVl0HfpfB8U/MdIAACAASURBVA9wOByEkLm5OfkAceXSJelBLpw7/+vXr9379pILiJL07NWrcePGVROdmuj5KoDJZB49cZycU2Zubr7/wAGE0NXLl6U1dKK7m1k9M9ld9PX1R48dU79+/VJ9IakpKQRBIIT0DQz27NtH06HaqtStW3eiuxubxTYzMzt28kRzFotGo9WvX3/KtKlHT5zAcXzPrt0YhlG0GSG0dbOPRCLZ5LNZ2hBZNLZY7e394/v30ydPKjdY48YoqT5KOHLoULce3aVvK6xtrJcsX8blcnds266oM0+R/6l4o2zLTDHuim4B7Tt06D/AVXajSjOoNyYVERv1C6Ruz4G//jJv1GjS/3/oz8DQ4ODhwzt37xowcIBaLlLpJeomqdWMq+tSdcVZEamXw7flQ8PrheEYTrEkg06ny+RGv36licXitLS0P/ftHz54yIVz53r07HHz1i3vdWvljtWIj49HCDVnNS+1nU6nN21qmZaWxufzq+Zekp+Xf/7s2e27dl67edNn67b1a9e+fP6ibLFevXt7zZk9d968sePG9fw/9q47ronk7Q+E3rGgZ0tgAWlSBBRRafauqGdBsYG9d6xn756n3tnrT1QE1LNhQ7GgCKgUEaU36ZhAetnd94/1zeVSNpsQEL39fvxDZiczT/nOM8/szs76+Undi/6lQwcAQHbWRyI9MplMAEC79u2kyh8+ePA0/okGVRszNtjL20v8J/ZUG+v9/0v09PX1LSz/CShWVladOnfOzckVP+s99uefHh4e5ubmUoFAqqTp8CNavhlgaGgo6QKaNa1Tp04F+QWqLmlcXLqlp6fPCJ2GnYTUhUqNiolWSRI9PT0URaVu5gcGBXp5e+Xm5BTk5xOUmeC6CF9gTQlDZPjI3V2k0lIQRx21V4nEl7I4LaixWFUaTDRCNuIKEglu0VFRPr18JPWlUCjjJ0yQ/JVSExG3EhETqRrGiZtUDXKqTfXG2LbJ9wMpfbKGSCyViKOurg4A8Czh2cLFi6JiY4yNjfHrs9ksoPhsGG1t7Wb7EElsTMyKlSuxmxx9+vbx8vaKi7sX1L+fSo307tPn5YsXiYmJKIoqlby8/AsAoEePnpKFNTU1ebm51jY2mtUO23yXkvzm/bt32R+zZYey7E/at29XVlqK/b+kpITJZNraydm1p6Or2xJSgRZr+ebHLx06pKelqbqkWbV2TXl5+bOEhJcvXtjY2ITPnRMcPFbVrgUCgewk4d2jZ2pKakFBAc52ckmZ8ddFJcXFXC7X0NBQqcAaEYbQ8JFzR/mfpeCTx4+7OjiMDh6zeu0aiuL8Q5E6BK3RyKWsUqgghrJgoimyEVVQmTxlpWUCgcDKyqr5rETARKqGceImVYOcalO9uKhYqW0D+vrVMxjiP89eOO/RvXvz3QeiUCiovBfXTUxMqqqqZN9pR5W9HIjlvxRt7THBwUoTIAAAlUYDAJQUl0g7G4arKitpNJrkk5cmhYOjo6HEwxFLy1Zq7NgaOnyYjo5OSXFx0uvXSkYvgqQmp5iYmPgHBkia98ypUzNmzdKsap8+fRrQr9+SRYt4PN6iJUt37iF0NI7kC5Bf6+oAAHW1dS124m+Zlv8u0JXJSoksaczMzM6cPxd788aAgQMLCwsjVq+ZOX0a9hpIY3IgAAD2iool7rJPUmaC6yKlAmtEGPWGj3gpSLOmRcXGHDj0e18/P/w5RpE6xFeJKEA1tZTV+GJV6m1qjZCtMQpKysNiMQEAxTJzUDNbSekL5/g8JG5SNcipNtWJ2Hbbju0HDh0S/1N7FapmDqSjo8Pj8Xg8HgCgoaFBKBRi5W4e7iwWK/nNG3HN+vp6DpsNS2VF2Hc6JNCxY0dHR8fCwsKY6GipBPZtaqqsAB06dPDp1etjVlZtba1k+bOEZ3w+PyAoSLIvAACCaGBIy83k+vTtIzlNZn340NfPT9WWO3bsODU0FACwf89eGHdw3rr5d1lZ2crVqyTXcNdjY4cMHapoVac2Vi1b/qWs7FpszNp167y8vURCEUFuiP+PLZozMzPRlnpCRsu0fAsBkSVNdFQUgiBu7u7HTp6IT3g6ZNjQxJeJ9+/FqZoDyTKkrLRUW1u7K+EDIAiui5QKrBFhiAwf2ZWkqktBHHWIrxJ5MtsGCC5lFa2ENbhY1fn3edwaIVtj1uqS8tjY2AAA3qak4J9j19RW0lF2ZDk+D4mbVA1yqn3Xg4ht+/r5BfULEv+TPWWgaXMgzGevX73icjhLFy3GzvgBAEycNBkAsD4iorCwEEXR3Jyc+XPm8vn8ivLyO7dvY9kliqJ0BoPL5Uqtt/bs36erq7tp/YaTx08w6HSRSJSeljZl8qQPmR/kyrD3wH5dXd1tv20RZ2C1tbX79+7p2LHj0mXLxNVKS0sBAJLP6RWBTqcDABSdQwMAqK2pBQDQFe+ffXj/Ac3aGnvpWlWsXLO6u6dnenr67/sPKKpTXVW1f9/eIcOGTgoJkYzOtTW1Gv8mA4/Hy87OtrKysvn//Lq6ulqcUxKEmZlZn759c3Nyrl2Nkoo1fD5fIOA3PjdqfAstzfJS4PP5H7OyNGsTBEWIHEBKZEkTeSlSvBeqC5V66PBhc3Nz7MQBAAD9Kz3ncw4RgaWiASyC7969GzJ1injPjVKZCa6L8AXWlDBEho/sSlLVpSCOOsRXiRwOVw2/46yEMfoJhSLVFqsEoNR3ssSSuwAmulbHhaGRUe8+vT99+hT7b2ehKFpcVIxvJUkTadxKKvGQuEmJklOuzWUK8VsjaFuNQM0cKGx2eOvWrcNnzvLu7tnL11d8TJOXt9eaiIiy0rIBgUEuDo6LFizcsGmjZatWQqHw3Okznz99Tk1JHTNyVElxMQzDPl7ek379Vfws08nZ+eyF8zRr6727d3t5dHdxcJwbPnvi5MnTZkxXFPKiYqIZDPqIocN2bNu+esXKEUOG2thA0TeuY2/9lJeXT5sy5eL5CwCAvbt3jxgyNO7uPdl2RCLRuTNnZk2fkZGeDgA4fOjQgrnzjv/1l3giQVH06OEj06eGXo+NBQBEXb06b/aco4ePSLVTU1Nz4fz5w38elbo9WF/PAABwOGx8k+rr6585f27AwIHHjx3bvnWr7N3Ij1lZE3+dMGDgwN//+EPcBQzDJ44dnzBpIofN4bA5CALzeLw3SUnieKQ2DAwMrNq1q6iowDhXWlJy4vhxAACTycrOzi4oKIBhuKqqksPh0L/SJTmKjTFx4dbt24yMjTZv3Hj40KGamhpYBGdnZ8+eFVaQn89hc86cOo2/S7QxiekPankpLFu8ZPSIkSnJyQTrwyK4sqoKI6T8BAhBKsor6HQ6dviN2HE1NTVCoRC7R018SdOmTZvt27Z9C6wAMBgMLpfbo2dPrM2lixdNHD9eKrLLheQLlbAIXrVihamJydLly1WSmci6CEdgDQqjdPgoWkmquhTEUYeINVAUxY7Xl/QREb/jrIQx4tXV1RJ3CsFgQsR3klC0AFaqIEF5IjZs0NXV3bB+/fFjx7A4Vl1dvXTR4vPnzuLfL5AyERErERRJ1TCukkmJkFOuzeUW4rdGxLYagZbay2gOm5ORkQ7Z2rZt21bqUkVFxYfMTCsrq26urtra2vGPHrt0c8FOeOTz+Q0NDSYmJnp6ejAMM5lMC3MLyc8UwDBckJ9fWlLasVMnW1tbpV8wQFG0vLw8LzdXR0fXwdFB8gVOBEHodLqxsbGurq5IJGKxWPr6+tg3I6WmhNKSUgtLCwMDAx2KDo/PYzGZHC7X2tpacsVvamaGVeDz+VgdyS/ACYXCRfMXrFqzWpwOMpnMk8dPpKYkpySnAAAsLC39/Pw8vTxDpk7FV+fRw4cnj5+oqqwcHRzs6OhoYGhYUf4l8WUidgibp5eXZP13b9/ODgsX/8lsaNA30NfT03/6/JmpqWkjyXE/Lm75kqVGRkadOndmMhsO/vHHvNlz+DyeqanpshUrfj94EMtfIQiaPGXKtBnT09PTN2/Y+CEzEwBgbW0dOn361GmhAICS4uLVK1empqQCACg6FHMz81Vr10T+79LHrCzvHj3WRES4urnKJqb/u3Dh5YuXL54/RxCEQqH0HzCgm2u3OfPmYY/GURT988jR1JSUly9eAAC0tbX79e/v7OKycPGin8DyktixdduVy5djb97s6tAVv2ZxUXHU1SvPE55hX/OwsLTs06fPyFGjJHfop6akbly/PjcnB3PcpJCQ6TNnpKenr16xMj8vDwDQrn37WWGzZoaFYfVPnTi5f+9eGIb19fU7d+ny+x+HwmbOqqqsdHNz27x1q6ub646t21gs1ps3b/wD/E1NzeLu3h01ZszCxYuwsTx8yNDcnJzd+/aOGz9ekdgjhgzNzs7uQqV26dLZ2cWFz+cnvkx0dXXdvOXbEQYqyZybk7N969aqquq+fn71DMaL5889vbw2bflNvL8SR2DNCoMzfKJiotu1b5+fnz/51wl1dXUGBgZLli0LnzMbk+H1q1dbf9uCdaGjo2Npabl2/bpRo0crogeOOvjWyMzI3LxxA/YZ4Pa/tA+dNn323DkE/Q4AkJW/sLBw0/oNb5KSEARp06ZNH7+++w4c0NLSwhcj6fXrtavXEAkm+MpKory8PGL16sSXidifjo6O8xcuHDJsqLgCjoKDhgy5HBlJMLhlZmQuXbwIyzBatWpFoVDmL1w4JXSqeAePlJX6Dxwg10T4ziJuIpXCeFRM9OmTpwiaVCk55drczcMdxxH4VFdq2++cA5GQxO6dO4cMHSr5WEQoFFZWVJiZmxsZGWlrafP4PC6Xy+NyO3XuTKTBr1+/fsjMxHYTW7Vr5+buJpu9yWLs6DHhs2cPHjpEU3pVVFS8TU01NTXt5eurp6fHYDCSXr92d/ewbGXJYXNMzUwRBOFwOABFLSwtRSJRfX099vI5m8Wi6OhIZgMMOj07O7tVq9aQLaSjo5OSnGwDQYoOHWlMYvpzWF4qy+/YsaPSmmw2m06nm5qaGhgY6OjoCPh8Ho+PArRVq1aST9bq6+vNzc0pFAqbzUZR1MLCQiAQMBgMUxMTPT19NoeNIIjkw3WcJY0YXA7nw4cPtTW13dxcO3XqJC5/+eLl9KlTb9294+TsjJMD5eTkfMrL/ZSdXVJSYmho6OjkJLmyUlVmnHWRUoE1K4yi4dP+l/b4K0lVl4KK1MG3xj9i6+vzeDyhUKiq36Xkh0Uwo55hZmaGjTsOhyPWC0cMPp+vUjDBUValBbAiBVWVB0XRstLS3Ny8Dh07QBAk+26BpJVwTIRjJVVFIhjGxTwkYlKl5JRrcyMjI3xH4FNdqW3JHKhF4OrlK790+EXq6zPfBU03E5MgLa8G3r19u2Pb9pgb13GWblja8Tk/ryUI3KKEIUGCRFNDmzRBI/Ek/omRsZE4AaqoqNi4bj1pFhIkuBzOgX379x7Yj3/vGkERGIZFIlFLkLlFCUOCBImmhg5pgsagoaFhyaJFAID1EesAAABFuVzujl27vps7dXR0dEmfkpZvKaNj6/Zt2Ln+CnMOBGE2MAEAdbW1TfFRaNUSoJYkDAkSJJoB5LMwTQJFUeyLxJrdFUuCxE+JjPSM1StX5uXmUnQo7azaeXTvfujI4WY74b0lC0OCBAkyByJBgsTPDGyPpKmpKYVCgUUwh8v5jouHFiUMCRIkyByIBAkSJEiQIEGiqUDuiSZBggQJEiRIkDkQCRIkSJAgQYIEmQOpAT6fX1RY1KQSwzCckpxyOTJSs83Sv9JvxF4/ffLU29RUyeeDispJkMBQUFAQHRVF2uG7oxmCj8bDS8uX/MdyTcsZjC0qLGjK/sQn34qKitiYmGZQDUGQ9LS0C+fOq92ChvcDLVqwIPHFyzv34zp06NAUCj9+9ChizRr6V3oXKvXJswRNNXvvzt0/Dh1q377du3fvuRzOlu3bQqZMwSknIQkGnb71ty2lpaW1tbW6OjooinZzdXVydg6bHS4eORvWrc/Py6uurtbT1eVwOa1bt/Hy9tq4ebPcBqurq83NzfX19Rs1XEUwAEDpAbuSGDxgYGlJiUgk0tPTa926NY/HQxDE2MSEQtFmMVk6ujr6+vr1jHomi4kiaLt27RYtXXrp4sWPWVlt2rRJSk0hmfB90dTBR+PhpeVL/gO55vOnz6tWrGgJg7HlSKJZ+xOcfPPz81cuW5aZkQkAyCsqbFK9UpJTlixcWF1dbWFpmfr+nXqNaPhEEz6Px2KxampqmojrgUFBfx0/ESrx7e7GI/Fl4u6dO+8+uG9qakr/St+8aSN+OQkpWFhaHvzjEIqio0eMzPrwYcu2rVJf5qJQKLv27EZRNHzmrISnT8eNH797316cBndt3yEUCh0cHaXeTG7btu2vEycQXBxMDw0N6t9vxsyZBLVAUTQvN9fZxWX3vr329vYUCgVF0XoGI8g/oKGh4dCRw0OHDdPW1gYA1NfXR125unf3bnNzs/UbN8yaPoPkQItY7DZx8NFseGn5kv9YrrHvat9CBmPLkUSz9ic4+VpbW+/cs2dayJSv8r5jrVl4eXv9fviP8FmzGtOIhnOgQ4ePpKenubm5NZHOFArFu4e37FdaG4NtW7ZMnDwJew/WspXl4aNH8ctJyIWWlpaVlVUWACYmpooq2He1T3j61KpdO5x2eDze48ePuRzO/bg4qUshU6YAQCgH+t+Fi69fvZL8ViiRHEhLS+uPI0do1jSxwBaWlm3atGloaLC374olQAAAc3Pz2XPnvEp8iaJoTx+fTp07M+h0kgDfHU0dfDQbXlq+5D+Wa7S0tFrIYGw5kmjW/gQnX21tbUdHRw/P7vGPHjePqa2tbb58+aJ2I+rvB9oj7zRkI2OjXr6+zaC5ppoqKy3Ny82V/AI8fjmJpnbc82fPJk2enPDyxeuUZMl/23buCAgKJNJLfn7++3cq3xdFUXTgoEHiBEgpJkychH35T1eHPB5azXCh2QabJ/hoJLy0fMk1i2ZTsOUMRg1K0vixo0H7E5x8tUDzHS7ayHxAzRyopqbm8qXIn2Bwvn//HgCAfXqXSDmJpoaBgcGKVSs7derU9t9If5/W189P6c9hEbx39+6I9evUWOX8efwY8fpDhg3t07cv6a/vEi5+lPhDhhES/xGq/7hQM1e9EhmJ/BQvSXE5XACAtjaFYDmJpoafv79sYWlJScdOnXQILK2O/fXXhAkTLSwtSUu2HGg8XPwo8YcMIyT+I1T/b+VAjx4+/PPoUT09fXljnpOUlOTRvbuFhQWPx+Pz+SYmJkKhUCgUig+eZzAYJiYmIpEIgREjY6Nvy3cYzszIqKutg2xtu1C7iPde4IPNZn/MyioqLLRq165Hz56GhoaSVysrKj9//iT+ojuGqsrK7OzsgMBvT1X4fD4AAIalPxOtqBxf1K9fv6ampAwcNIjJZD5/9swGghwdHbFLIpEoKyurrrbO1c21TZs2OEpVV1cnv3kzfMQIWAQnJSVVV1W5urlCtrYqSQIAKCku/pj1kcVmOTs7Ozo5Sf0WR1TZhci7t28HDR4sFApTU1KqKqtat2nt5e0tZW2JluvKysrkXsI+SKkG/jxydPnKFUqrfcjMrKysWLh4Eea+ZgYsgt+9e1dTXe3s4kKlUVX1l1zk5+fn5eYaGxvb2dnJfsWTQad//PhRV1e3q4OD7M0G4kTC7whHbCJd4IQLHBLisFdRg5LBp+kMpVLLOGEEX3KVRMKXAcfIAoEgLze3rKzMxsbG2saGQqEwGIzUlJTeffqIRzd+GCEopyLX4NO7MVFI6WDENxpOuNa4JGpQXdVg0kiCqTH5qjdeCNapq6tLf59WX1/fpm0b7x49mjsHOrj/wP8uXEARlMvheHl0BwBoaYFzFy5AtraL5i94lZgoEAhu37trYWFx/17cls2bmUymhaXluPHj1q779nhi6aLFL1+80NXV3fjb5skhIQCAwsLClUuX2drZcXncp0+eUrt02bFnt9INXH/fuLl921YzM7OK8gqBQGBhYbHv4IHAoCAAQEZ6xrYtW7DPl4pzoPT09J3btr9NTbWxsQkIDLx08eKh3w/xeTwAwOIFC3X19AAAz1++vB4bI7ccS9cUifohM3Pfnj2vX702Njb26dVr9IiRJcXFAIComGhPL6/a2trwmTM7duzUuUvnXdu3+wcG0L/SDxz6XXoeysvbsvm3pNevjY2NHR0d582ew2AwsN3102fOWLdhgyTRcYxWXVW1euWqwoKCUWPGlJWWrl21etLkyVt3bMeem+KLKilPdnb27/v3P0t41r59e319/bWrVrM5HC6HAwAwMzM7dOSw3Hs2R/44fPrUafk5ELNBDY5mffjA5rDxd1Jj883B/Qf+OHrkuywmsj9+XLxgYUNDA51ORxAkfM7s1WvXSj6oVpXkNTU1q5Yv19amdHXo+uRxfGFh4egxY7bv2qmnpwcAKCsrW7tqdUVFeV8/fxaL+Tzh2ZChQ1esXoWFDJWIhN+RIrEJdqEoXAAAFJGwc+fOOOyV2+Bfx0+cOHZMMviItdOgoaSA37Ki8CJe9X2bnLhcqbCpkkj4MuCP9JcvXmyIWEelUW3t7A7s3YcgyIhRI6/HxFZVVR0/ddI/IAA/jBCUU1ZBIqxrZBTCH4z4RgMAKArXGpcE38KKxo5Lt27Eg0kjCabG5KveeCFYp76+fsfWbW+SkoYMG9q2bduk169XLlvO4XIbdZAKqhaCR412cXSSLEEQ5P27d8MHD4GotI9ZWVjhh8xMiEpbvnSpVM2Avn7Pnz3D/vzy5YuPl7f4J58/ffb26O7q5Jzz+bOi3v18e9vSrDdErGMymSiKCgSCu7fvuDm7QFTawwcPUBRlMplXIi9DVNrgAQPFv+JwONdjYu2sbQYEBokLz545A1Fp8Y/jpbqQW44jKovFirpy1cHWzs3ZZcWyZTHR0UmvXy9fsrS0tBRF0Yg1a5YsXPRNDDZ7wrhxwSNHyeolEAiexMd3c3Kyh6DpU0Pz8vJQFK2qqpoyaTJEpd2+dYuIJCiKzpo+w8fLu6qyEru6a8cOiEpLTUnB/sQXVRIMBuPq5Sv2EGRvA80JCy8uKkIQpLa29uL5Cw62dnbWNk/i/2WfsBkzISrt5vUbihy3d/duiEo7sG8/caYhCBIycZKYLTjYtWPHyxcvsf/zeDyISjt75gzaaAwIDIKotM+fFLJx+OAhjnb2IRMnFRYUYv4KHjkKotIe3L9P0F+y+Fr3tZd3j0sXL2J/slnsBfPmQVRa1JWrKIqWlZW5ObvMnzOXx+NhFSrKKwYG9Rs1fIRQKFSJSPgd4YhNvAu54QKHhPjsldug3OCjWUNJQWnL+OEFR3LiIimVAcfIebm5zl0dtm3ZgiAIFhuDR422t4EqyiuEQiFWiO8IgnLKdQ0+6xoThZQORiKOUxSuNSuJUgsrGjsqBZPGEEy9yRfDnLBwiEpTabworcPn80cOGz4nLJzL5YpbfpaQAFFpnu4eakd4jeVAGA4dPCgVhsYHj3Wy78pgMMQluTk5AwKDsGGGEU4qSYq8dAmi0qZPDcVxQ99evuIWMLxJSoKotH4BAZi9EATx8vCQzIEw+Hh5q50DKRV1YL/+EJV2/uw5qdZGjxgRPHKUWODioqKxo8fgz6n0r1/FJVVVVRCVNmHcOIKSXI+JTUn+ZyDF3bsHUWnR165J1lckqiwGBvXr6ekFw7BkYfzjeCzFFIlETZoDxT+O9+3pI9mLXLxJStqyebP4T8kcSDa303gO5OrkLMnwwoJCiEoLDQkhzhwpbNqwcdTwEZIMF4lE165exVgxJyzcuauDOHR+M9SjxxCV9tfRoyoRCb8jpWIT6QInXMglIRH2ym1QNvho0FBSINiy0hxIkeRERCIog1wjb9uyBaLSJIfGo4cPISrt7OnTKjmCoOmkFMRnXWOikNLBSMRo+OFaU5KoTXU1Zkz1CKb25CubAxExu9I6J44d93T3kDQpNtH38enVmBxIw9/KkH1Lbeq0UD6ff+vm3+KS27du/TpxIlYTFsE3Yq87OTlhd6QyMzJ37dgZc+3arPDw1RFr8Z7h6epK9dWjZ0/f3r2LCovy8vIwSeTeH9OmqLk/kYioJiYmhkZGU0KnSv3WxaVbenr6jNBpae/foyjahUqNiolW1JGenp6+vr7krl4rK6tOnTvn5uQSlGTM2GAvby+JBvUBAEzmv/biKBJVrjwoikrdIA0MCvTy9srNySnIz2/SHTZ7du0KHjuWgus1BEFWr1j5MStrRug07N/sWbMAAFcuRU6ZNDli9ZqmfhBmaGhobm4u/pNmTevUqVNBfgFx5kg96Y+OivLp5SPJcAqFMn7CBAtLSw6b8/jRIydnZ6mHg/6BARQdStSVqyoQCbcjImIr7QIfcklIhL1Ego8GDSUF4i2rHTaVikRcBrlGzsvNBQC0k/itvb09AODzp88qOYKg6SQVxGdd46MQzmAkaDT8cK0RSdSmunozphoEa8zkq8Z4UVoHhuFjf/7p4eEhaVJMNamS5tgTrRIGDxmys+32Sxcvhkydoq2tLRKJ/r5x8/qtbynRly9lQqGwrKzs4P4DTx4/7urgMDp4zOq1ayhqZSruHh6vEhOLCgodHBwAAAiMaFARgqLqUCiywq9au6a8vPxZQsLLFy9sbGzC584JDh6LExFly9q3b1dWWkpcEmynW0rym/fv3mV/zJbve3miyoVAIJAdVN49eqampBYUFNjZ2zcReW7cuJ6flzf21Cmlz3MHDRny7zRClPgysa2VlbOLSxdql+bfHvRLhw7paWnqkbystEwgEFhZWcm9ikUZWaUoFErHjp1Kiou5XO63/YnKiITfESGxlXWhPADJIyER9iqFBg2lfsuNWE3ii6SSDLJG/uWXDgCAivJy8dlFbDYbANC5SxfVHKE6AfBZ1xRRSDwYCRpNabhuvCRqU11jM2ajRy7+5KvqeFFaJ+fzZyaTaWtnKzcnlvb9EgAAIABJREFUa9E5kK6u7qSQyYcP/ZHwNCGoX9CD+/fd3N1btWol3uANAHiW8Gzh4kVRsTHGxsaN6at169YAgLZWbcVTIwLDmlKkMaKamZmdOX8uPS3t+F/HHj96FLF6zZ1bt06eOUN8J5fk67VKJfn06dP8OXMbGhrGjR+3aMlSBoM+N3x2Y3SXHfMAAOx1CcsmewsdhuETfx3z8vZSem4hhUKROhCIz+efP3uu/8ABxL+VoXHaq80cFosJACguLpF7lc1mAcXHgmlra+OfGCZJJPyO1CZ8I18F1xR7NWgozbasNiRFaqQMk0JCYmNirly+vCYiQnx73sDAYPDQIY13BD4B8FnXFFFIPBgJGk1puG68JGpbWLMzpgZHrvTkC1CVuKq0ztevdABAXW2dxoeVmjkQhUJBEaJ3WUKmTj3+17FTJ04E9Qu6cO78ug3r/7n/1q4dAICirT0mOJh44IARmCJP8pKSYn19fYf/f/PTxMSkqqoKQRCp+5bqfSZWPVExREdFjR0/3s3d/djJEyXFxfv27o27e+/+vbhRY0YT9ZPE0ThKJVm1bPmXsrK4Rw9tbGwAAPfvxTWSJQKBAPuUxL/Xc6Xa2tpdZbJ+TeF+XFxhYeHseXPBDw5VmYN57W1Kiix1AQBUGg0AUCIzhcAwXFVZSaPRDAwMCBIJvyO1CS97jJNK4YIIe4k0qEFDabZl9YO1hEiNlMHVzXXPvn1rVq1i0BndPbunpaXFP3r8x5EjEAQ1Pozgn+OFz7omjUIEjaY0XGsqHqpB9cZMQ410nEqTL4/LVcnsSut0c+0GAMjMzJS1fGMzP7WNxePxeDweAKChoUEoFEqmF0KhSCpDHDtuXEpy8uXISBiG3T08xJc6duzo6OhYWFgYEx0tdYfwbWqqot55PL5QJhMXCAR3bt0Omx0uTo3dPNxZLFbymzfiOvX19Rw2G5aMnigKAEAQmdtFMuWERMX2mcsg8lLk0/gn2P+7UKmHDh82NzcvLi5Sz/j4kvB4vOzsbCsrK2xcAQCqq6vFGv0rEyScC2L7/6X6unv3bsjUKSo9i1Up+zz+1zFDQ8Ohw4bJvcrn8z9mZalqOjV+pVRmBEUQ3PlYVZIbGhn17tP706dPsf+uj6JocVFxhw4dfHr1+piVVVtbK3n1WcIzPp8fgPt6qkodqTc2VQoXsiQkyF65DUoFHw0aSgoqtKwovMjjmFTY1KAMcjmclfVh4eLFg4cO4XJ5QUH9Hic87Tegv6qOUGkQYQris66RUQh/MBI0mtJw3XhJ1Ka6lZWVGqNSDYI1cvLlcLgqmV1pHTMzsz59++bm5Fy7GiWlGp/PFwj4qLonSaqZA2FZ2+tXr7gcztJFi7FjJwAANTU1AIC6ulqp+jPDw7S0tH7buGnGLOlnE3v279PV1d20fsPJ4ycYdLpIJEpPS5syedKHzA9yuy4vL2fQ6VVVVZKTGY/HWzhvXpu2bebMnScunDhpMgBgfUREYWEh9j7a/Dlz+Xx+RXn5ndu3sePLSktLAQCS+9QwyC3HFxVFUTqDweVyZe+UtmnTZvu2bd8oDgCDweByuT169pSTZcNwVVUlh8Ohf6VLuhn7rbgQRxIDAwOrdu0qKiqwgFJaUnLi+HEAAJPJys7OLigowBdVEa5eviI53latWGFqYrJ0+XLJOnQ6HQCg6IBEAEBtTS0AgE7ge8IFBQXZHz8OGz5c0c3eZYuXjB4xMiU5WSXeqvorWARXVlWJiS0nAUKQivIKOp2OHRMi9ldNTY1QKMRuXKtB8ogNG3R1dTesX3/82DFsj2R1dfXSRYvPnzsLANh7YL+uru6237aIk4na2tr9e/d07Nhx6bJlKhEJvyN8sQl2oShcyCUhEfYqalA2+GjQUFIg0jJOeJGClOQERSIig6KR/iYp6erlK/MWzPcPCAidPq3fgP7Yx+9UcgRx00kpiM86taMQkcFIxGhEwnXjJVGb6qoGE7UJpvbki6JoQ0MDZlviXFVaZ+v2bUbGRps3bjx86FBNTQ0sgrOzs2fPCivIz+ewOWdOnSby5oT8DFEN5OXl9ejuCVFpzl0dTh4/gaJoQUHBlEmT7axtICqtp6fXimXLpF6fmzd7jn/vPpKHZ4jxKjFx8ICBEJUGUWldIVsfL++bNxS+X30l8vK4McHDhwx1dXIOmzFz5/Yd6yMiAvr6rVi2TPbVypPHT9jbQBCV5mTfdVD/AR+zsnx7+kBUWvDIUXH37oWGhGCdQlTa8MFD7t25i52+ILccX9SU5JRRw0dg5R7dXCeOH19aUiL+1fYtW9euWh3o5//bpk0H9u3vHxB45I/Dsqq9fvXKv09frJGBQf2w11nT0tLELfcPCLx4/oJSo8Xdu+doZ+/p5j5q+Iggf/+0tLRePXp2d3Xz792nsqICX1S5735DVFqgn/+0KVP27t69bcuWwQMGrl6xks1iYxWEQuHZ06dnTpuOed/eBpo/Z+6xP/8UEwBBkCN/HJ42ZSrWqZ21zdzw2XItIOllB1u7rA8fFFXYvmWrc1eHT9mf5F4VCAT2EHQ5MlKlX0miqLBoz65dwwYNxmT2dPdYsnBR/KPHknVSklPELhgY1O/cmbOYv7C3kSEqzbenz5lTp9QgOYqiGekZQf7+WH1vj+4+Xt4Xz18QmzTn8+fQkJBB/Qds37pt1fIVPl7eC+bOq6qqUoNI+B0pElulLmTDBQ4J8dkrt0Gc4KNBQ0kBv2X8MCKGrOSvEhOJi4QvA46RsePTevv4TPp1wvSpoeGzZi2YO2/1ipUP7t8Xmw7fEQRNp8g1+KxTIwoRH4z4RlMarjUoiRpUVzWYNJJgaky+GekZY0aOxJrq7eNz4thxIlwlWKe4qGjCuHFY4/YQ5O3R/VpU1KjhI+ysbSZPmJielq5GMqOl9h0kDpuTkZEO2dq2bdsWy4UZ9QwzMzNtLW0en8fhcLDyf+4B1NbWMxiKTuOGYbggP7+0pLRjp062trYUHYWbs2AYxnZRiUSi4qKi/Px8Q0NDZxcX8T5rKVRUVHzIzLSysurm6qqtrR3/6LFLN5d27dsjCEKn042NjXV1dUUiEYvF0tfXNzExUVSOLyqfz29oaDAxMdHT04NhmMlkWphbSGnB5XA+fPhQW1Pbzc21U6dOcp/UcNgcUzNTBEE4HA5AUQtLS5FIVF9fjx2UyWaxKDo64q+O4BitoqLibWqqqalpL19fPT09BoOR9Pq1u7tH+1/aExFVEiOGDM3JyfmUl/spO7ukpMTQ0NDRyUnSuQiClJaUWlhaGBgY6FB0eHwei8nkcLnW1taSD8tNzcywCnw+H6uD8z1tgUDAZrEtW1ni5O7l5eUdO3ZUNeMn+Cs2m02n001NTQ0MDHR0dAR8Po/HRwEqSTM+n19fX29ubk6hUNhsNoqiFhYWAoGAwWCYmpjo6emzOWwEQcRn4xInuVjastLS3Ny8Dh07QBAktaES0yUvN1dHR9fB0QHbk6gekfA7UkR4lbqQChf4JMRhr9z4gx98NGgouXSS27LSMCK+hSAluZmZmaq+w9FOkZFhEXzq5In7cffr6+sRGBYIBBwOh8vlIghy4PffxRtf8MMIETmNDI0UuQafdapGIZUGI47RlIZrzUqiKtVVnTEbTzBVJ99/NNXX5/F4QqFQHACJmJ1IHQadnp2d3apVa8gW0tHRSUlOtoEguTWJQP0ciMR/BNiY/5yfR5qCBImfGAw6ffTIUTQa7fz/LpJRiIyH/xFokyYggQ8ERWAYFolEpClIkPgJwOPxQkOmvEpMlCq3sLR0cHDo1LkTGYXIeEjmQCRIAAAAgiDYx97ramtJa5Ag8RNAS0uroCB/5rTp586cwY5GxBKjy5GRnz59Wrx0KRmFyHj4HxoO5LMwEoqQkZ6xeuXKvNxcig6lnVU7j+7dDx053ETnv5EgQaLZQP9KP33qZMLTp6WlpRbmFoaGhlra2gGBAQsXL5bdtERGITIekjkQif8isL2cpqamFAoFFsEcLkfR5lASJEj8iEBRlMfl6unrUyiUlilhy4lCZDwkcyASJEiQIEGCBImfBOR+IBIkSJAgQYIEmQORIEGCBAkSJEiQORAO+Hx+UWFRi9VK4+JVVFTExsTgl5Bo4awgvfbTsAhBkPS0tAvnzv9Y9GsG0L/Sb8ReP33y1NvUVIL7HJQOChiGU5JTLkdGNo+oaqhARj8S6kO9b2UsnD/fo5vrly9f0BYJDYqXl5c3esS3Q8QVlZBo+axoOq/x+fwmkjn5zZtB/Qd4urm7ODqNGxMsEomI/OrmjRvOXR26OTn1DwjcuX3Hz8ei5DfJvbx7YB8w+YGCUjPg7u07A/v1Dw0JcXF0gqi0S//7X+MHxaOHD708PLCvQzSDqKqqQEY/Eo2EuveBeDwWi6XoQ5LfPyXXnHjW1tY79+yRPAtctoREy2dFE3nt+LFjvj19mkhm7x494h4+2LNvn4DPf//u3f8uKD+9l8fj7dm5i8fjTZgw8UH844j1634+Fnl5e/1++A8jY6MfKyg1NRJfJu7euTPmxvULly49f/ly6PBhGhkUgUFBfx0/gf8hC02JqoYKZPQj8X3uA7FZ7FeJiS02s9O4eLPDwqSWSrIlJFo4KzTutaOHj8jejWgKHPvrL4hK8/LwYLFY+DXPnz3Xq0dPiEqLiY7+uVk0cthwKcu3fPo1KQb1H/DnkSNNNCj69vLV4H0gRaKqrQIZ/Ug0930gI2OjXr6+aidee3btatLErpHiyUILaCktIaFxs2ucSJrymlAo3Lxx0/lzZ3/55ZdmUBOCIIoOhf6VfuHcOfwdCa9fvfLw8PgvsEj2bLrmp1/LQVlpaV5uLs5HiBs5KDR4EqAiURujws8d/Zp6uvyP4zu8F1ZTU3P5UiRpehI/LpG2b9lqYmIcn5Dg49ureXocN348AODUiZP19fWK6ly7GjVy1Cjy4Nr/IN6/fw8AwL77/YOK+gOpQE6XZA7UKFyJjETIgxlJ/MhE2rx1y6o1a8zMzJrtdmC3bq79BwxgMpmnT56SWwEWwQ8fPBg0eDBJjP8guBwuAEBbm/LjivoDqUBOl2QOBLgcztMnTxgMhrhEJBKlp6c/iX9Si/sxuUcPH/559Khsa1wOB0VRDpsjXubCIphBp8MimM/nczkccVL84P59AIBQKHz96tXN6zdePH/O5XKViochPz//wf37L1+8qKqslJWtpLj4/r24mOjo7I8f1TAIQRVU6pegvgSrff369eGDBwAAJpN5986d7OxsqQoMOv1VYmJKcnJDQ8M/qnG5LBYLQRChUCg2KYfN4fF4AoHgXzVlzE7/Sn/08CEAAEGQlOSUu3fuFBcVi6/yeLxXiYn34+LkugPfMnKJ9M3sMJz2/n38o8dFhUUIgjSF17S1VRs4jbQDAABG4GUrVmhpaZ0/e1buEHv44EH/AQMoOupPIRphkVwKYTrW19fDMMzj8ZhM5j/1GQyRSMTj8ThsDv7graure/I4/kbs9RfPn/N4PCJBCQBQXV195/ZtzK2JLxNvxF7Pz8uTq75AIPiYlfXwwYO83FwYhjHZHj96JGsBVcNFZUXls4QEqcKqysqEp08lS5SGUBxi8/l8AAAMi9ToVyWw2eyU5OToqKhnCQmyliHSo1xRccrxFVca04j7iwgBcBqRpR9B7uH4HSfKNVv8Jz6B4rgJR0d82qvXpmpQdQMRh8OZNX2Go509RKV9zMrCCmtqakaPGLFg7rzdO3f2DwjctmXL8iVLZX97YN9+d5dudtY22E5ST3cPLw+PzIyM438ds4cgiEqzpVmvWr4Cq5yfn98/IBCi0jzd3P++efPjx4/hM2fa20B+vr2fPnnS09MLe3kSotI8urk+S0jAEQ9F0erq6mlTpswInbZ7586BQf3srG1WLV8hfqu5qrJy2pSpfr69D+zbv2zxEohK2xCxDkEQ8c/nhIVLbRuUKiGigqxBcPolqC/BapkZGaEhIXbWNu4u3err6wP9/LE6qSkpWIXS0tKQiZOC/P03b9y0Ytkyb4/um9ZvqK+vR1H06uUr4jbHB4/l8Xgoip4+edLVydnFwXHXjh1yzV5cVDRz2nR7CHJ36VZQUDB00CAvDw97G8iWZn3o4EEURROePvXt6dPT0wui0hxs7aKuXCVoGRwioShaUFAQPHLU6hUrFy1Y4OLoNGzQ4LS0NM16TRKrlq/A3xPdSDtgePjgwcXzF1AUXbpoMUSl/bZpk1QFBEFmhE5js9goii6YO0/VPdEaYREOhVAUvRF73d2lG+YvjDMYpk2ZiikeeemSosHLYDBWLV/h59t7144dp0+eXL1iZY/uni6OTmLLy/1hXm7u1MnfpM3LzR0QGOTt0R0TeNuWLTAMS1rgxfPn/r37hIaEbP3tt4FB/foHBP7x++/+vfs42NolPH1KfNhKIT0tfdyYYIhKGzxgoLgwLS3t17HjICptQGCQuFBpCFVE7P9duODp7uHi4AhRaa5OzthweP3qFcF+5QY3Wfj59g708795/YaXh0eQvz9mak839yfx8cQ1lSsqm8VWVI6vuNKYppK/lBIApxFZ+hHnHo7fcaKcZkeu0sGrdALFD7w4OuLTXr02VYXKORCCIO/fvRs+eIhkuIlYs2bJwkXf4hGbPWHcuOCRoxS1EDxqtIujk1RhSnIKRKXNDguTLBSJRJ7uHkmvX2Nx8OrlK/YQZG8DzQkLLy4qQhCktrb24vkLDrZ2dtY22GiUK97Xuq+9vHtcunhRvIF/wbx5EJUmnm9mTZ/h4+VdVVmJ/blrxw6psaQ0ByKigixw+iWoL8FqLBYr6spVB1s7N2eXFcuWxURHJ71+vXzJ0tLSUhRFy8rK3Jxd5s+Zi+U3KIpWlFcMDOo3avgIoVCIDSEXRycn+65ikzY0NAwM6vcmKUkRK/h8/sMHD9ycXewhaOa06fn5+SiK1tXVTfp1AkSlrV29ZsnCRZjinz99DujrZ28DSU57Sj0il0hfvnzx8fIWt/P502dvj+6uTs45nz9r0Gsq5UCNtIM4Bzp35iwWFOxtoK6QLeY4SS327d6D/V+NHKjxLFJKIRRFP2RmQlTa8qVLpeJJQF+/58+eKRq8fD5/5LDhc8LCuVyu+FfPEhIk38iT+0OBQPAkPr6bk5M9BE2fGpqXl4eiaFVV1ZRJkyEq7fatW/8ck5Ob69zVYduWLeIpLXjUaHsbqKK8QigUyiY3RMiJgclkXom8LJUZcDic6zGxdtY2krkIfghVSuyzZ85AVFr843hV+yWeA9nSrDdErGMymZht796+4+bsAlFpDx88UKlHKVHxy3EUx49pKvmLCAFwGpGlH3HuKZ065U6XGhy5ROK/0gkUn584OuJcUrvNJs+BMBw6eFAy3IweMSJ45ChxsCguKho7eoxKORBWbmdtI8ngvLy8/gGBkjFoYFC/np5eUmu4+Mfx2NgTHyInJd6mDRtHDR8h2Y5IJLp29Sr961fsz+sxsSnJ/wyJuHv3ICot+to1lXIggipIQmm/BPUlWq1ff4hKO3/2nJQYc8LCnbs6iIf3t58/egxRaX8dPYr9+fzZM3sI6uPTq6amBobhOWHhkZcu4bMCRdExI0c62XdlMBjikpzPnyEqbVD/AZIn/r1KTMRWSMQtI5dIEWvWSE2xkZcuQVTa9KmhGvSaSjlQI+0gzoHOnDqF/X/tqtUQlbZy+XLJCosWLBC7T40cqPEsIkIhFEXHB4+VskNuTs6AwCBJU0ux6MSx457uHpI/wWadPj69pCwvSz8URYcPHuJoZy8e6dhUBFFpE8aNE5ds27IFotIkCfDo4UOISjt7+rR6w1ZKVC8PD8nMAIOPl7dkZoAfQpUSWzaBINgv8Ryoby9fqRHxJikJotL6BQRgMyXBHlXKgZQqriimqeQvIgRQ2ogs/YhwT+nUiZ8DNU/8VzqB4rsJR0ecS2q32Uzvxku9e+Li0i09PX1G6LS09+9RFO1CpUbFRKva5oxZMxEEuXj+grjkyeP4sb+Ol+xLT08PRVGp3RiBQYFe3l65OTkF+fmy4sEwHB0V5dPLR7KQQqGMnzDBwtIS+3PM2GAvby+JXvSxh6ZNoYIklPZLUF+C1UxMTAyNjKaETpWsxmFzHj965OTsbNWunWS5f2AARYcSdeUq9mdfP7+du3dXVFTMmz3n6OHDbdu2nRwSgs8KAICWlraenp65ubm4xM7evlWrVggMUyj/7Fzp0aOnnp5eRnoGccvI3RR8I/a6k5MT9oQ3MyNz146dMdeuzQoPXx2xVoNeU2u8qGkHiYffMPafhUsW6+jo3Lx+IzcnByspKiwyNjKWcp8aUJtFBCkEAJg6LZTP59+6+be45PatW79OnChpaqnBe+zPPz08PCRNh9WRKgEK3t/W09PT19cXj3QAgJWVVafOnXNzcsUlebm5AIB2EsLb29sDAD5/+qzesJWSSl9fX86WMgqFYAhVj9gE+yUOHV1dKQv36NnTt3fvosKivLy8puiRiOJyY5qq/iJCAKWNyNKPCPc0MnU2afxXOoEqdROOjoouNaZNlYmtkRC/au2a8vLyZwkJL1+8sLGxCZ87Jzh4rKqNDB4ypF379teuXl2ybKmxsTEA4P69e8dOnpDduSY72r179ExNSS0oKLCzt5e6WlZaJhAIrKyslI63pKSklOQ379+9y/6YrZ4dCKqgUr8E9SVYTYdCofw7JGHxqwu1i9TPKRRKx46dSoqLuVyuoaEhAGDsuHHVVVUH9u0vLSl5/ipR/blWXw/b//hPXzoUy1atpDYgq+qRL1/KhEJhWVnZwf0Hnjx+3NXBYXTwmNVr11CUhWA1vKYRELTD/+dAQuw/HTt2nBQy+X8XLv5+4OBfJ44DAM6dPTtj1iyNiKQei4hTaPCQITvbbr908WLI1Cna2toikejvGzev3/pb4T7WkhImk2lrZyt3SiaYfsqWtW/frqy0VPznL790AABUlJeLD6dhs9kAgM5dumgkXCAw0pgQqjaxifTbSLh7eLxKTCwqKHRwcNB4jwQVl41pqvqLIAFUniMIcE8jU2eTxv/c3Fz8CVSpm3B0VHSpMW0203thUjAzMztz/lzszRsDBg4sLCyMWL1m5vRpUvFdeTqmozN1WiiLxYq5Fg0AyM7OtrC0lF3dyjobANCmTRsAgKVExi0Gi8UEABQXl+B0/enTpwH9+i1ZtIjH4y1asnTnnt3SO8cBqrSEuArE+yWur6pmkXjRgwUUn4Gmra0tecnLu4e+vn5tbe3J4+qnCLq6ekrrELGM7HtDAIBnCc9o1rSo2JgDh37v6+cnNeA14jVNgYgdZO8DAQDmLVhgYGDw8MGD9PR0+ld6bU2NfVf7JsqBiLCIOIV0dXUnhUzOz89PeJoAAHhw/76buzvOtxq+1tUBAOpq6zRreakXsCeFhGhra1+5fFny7pSBgcHgoUM0Qk4URREYVjuEEiG22v0qGhQE0bp1awBAW6u2KvVIEGorrqq/iBBAjYhEhHsamTqbNP6zWSz8CVSpm3B0VHSpMW1+nxwoOioKQRA3d/djJ0/EJzwdMmxo4svE+/fi5FamUCiogjeWJ02ebGRsdP7cOez+29hx4+Q6G5U5L6GstFRbW7urg4NsfRsbGwDA25QUnNekVy1b/qWs7FpszNp167y8vURC6fczeTLvGfIUvDFLRAXi/RLXV1WziEGl0QAAJTIUh2G4qrKSRqMZGBhgJbk5OatWrIj9+2Z3T89DBw/ej4tT894jgShGxDJSRMKyFoq29pjgYOx2jiw04jVNQUeVaC4SiSTvqIdOnwYAOLB3X+SlSyFTp2hKJPVYRJxCAICQqVP19PROnTgBALhw7vyMWTNx5MHWr5mZmahGj0jR0fnX/W9XN9c9+/adOXU6YvWa6Kio9RER12Ni/zhyBIIgtckpCRMTk6qqKtn4I6kUTgglQmy1+8UZFP9yJQIruFFXrK+v7+DoqFKPBKG24qr6iwgBVHU6Qe4pnTpxpsvGj1wigxd7IIUzgSp1E46Oii41ps1myoEwcwv/nweRlyKfxj/B/t+FSj10+LC5uXlxcZEiEvB4POyEj4aGBqFQKL5kbm4+cdLk0pKS+3FxzxIS+g3oL7drqZwXFsF3794NmTpFvEVAUjxDI6PefXp/+vQpNjpaqh3sjBYej5ednW1lZYVlSwCA6upqrIa4MocjHSZkS4ir8C30EOiXoL5Eq2Hb4P+NDh06+PTq9TErS+qUhWcJz/h8fkBQEPZnRUVF2IyZ23fudHBwOH7qZLv27VcuW5714QMOKxSFPy0tLdlCyRKClpEikpWVlaOjY2FhYcy/HQ2L4LepqZrymtpraDXs8E8CJBRJnYgzKzxcX1//VWLii+fPpU7ol9sC/Ss953MOESHVYBFBConvHIwdNy4lOflyZCQMw+4yX/aQZJGZmVmfvn1zc3KuXY2SqsPn8wUCvqQkculHEFlZHxYuXjx46BAulxcU1O9xwlNFHCBITkm4ebizWKzkN2/EJfX19Rw2G5aYVHBCaMeOHZUSG+sd+XemQqRfnEHxb635Qpk7DQKB4M6t22Gzw8WzFKEe5Ykqt5yg4vgJFkF/4ROASCPq0U/p1IkzXTZ+5BIZvEonUKVuwtFR0aXGtNlMORD2ddy6ulrxPbft27Z9owUADAaDy+X26NkTJ/F8/eoVl8NZumhxSXGx5NUZs2ZSdCgbItYNHDRI7g47AMDVy1ckjbJqxQpTE5Oly5crEi9iwwZdXd0N69cfP3YM28VWXV29dNHi8+fOAgAMDAys2rWrqKjAPFpaUnLi+HEAAJPJys7OLigowF4FBwCIWSJboqoKRPolri+RaiiK0hkMLpcre9d074H9urq6237bIh5gtbW1+/fu6dix49JlywAAlRWVM0KnzQwL69O3DwCgVatWB34/yOPxZoeFS7pPyuwIgtDpdBaLJfl5B1gEMxiM2tpaSTGNwG07AAAgAElEQVSEQuHXujoWm40NUYKWkSXSnv37dHV1N63fcPL4CQadLhKJ0tPSpkye9CHzg6a8Jptb8Pl8/JMY1baD2HGpqSnpaWmwxFOG1q1bY1/PGDtunNR9bOzhL7OBKdnC0sWLJo4fT+QwMfVYpJRCkpgZHqalpfXbxk1ybwJJsWjr9m1GxkabN248fOhQTU0NLIKzs7NnzworyM/nsDlnTp0W70uV+uG3tWxVJYfDoX+lS1oDi1TiwjdJSVcvX5m3YL5/QEDo9Gn9BvQ3MTFp/LAVY+KkyQCA9RERhYWF2Ktw8+fM5fP5FeXld27fxm7g44dQfGIDAEpLSwEABfkFqvaLPygwlJeXM+j0qqqqj1lZkmnBwnnz2rRtM2fuPJV6lCuqonKlI1pRTFPJX0oJQKQRKfoR5J7SqRN/umye+I8/gSp1E46OOJfUblNVaKl6l7KwsHDT+g1vkpIQBGnTpk0fv777DhzYuW07i8V68+aNf4C/qalZ3N27o8aMWbh4kdwW8vPzJ/86oa6uzsDAYMmyZeFzZktVWL1i5c0bN548f9apUyepSyOGDM3Ozu5CpXbp0tnZxYXP5ye+THR1dd28ZYuRsZEi8bS0tDIzMpcuXoQxuFWrVhQKZf7ChVNCp2Lzx/24uOVLlhoZGXXq3JnJbDj4xx/zZs/h83impqYbNm/66+hR7FWd9r+0D502vZev7+aNGyRLZs+dQ1wFSeD0GxUT3a59e6X6EjRLakrq9q1bP2RmYmvrrg5d9x040KlzZ3ELuTk527duraqq7uvnV89gvHj+3NPLa9OW36ysrB49fLh6xUomkwlB0I1bt4yMjRoaGib9+iv20oS+vv7ZC+et2rWTMvukyZPXR6zDXriwatduxsyZ4XNmP3zwYP+evVjIsGrXbs3ataPGjL5969ahgwcx1zg4OKxdv75P3z5KLaOISK9fvdr62xbsnSkdHR1LS8u169eNGj06MyNTU17DcPzYsccPH6W9fw8AsLWzc3V1XbV2Tdu2baWqvXv7dt3aCLXt8L8LF2NjYjDH2drZ+fb2Xb9hI3YYdGlJyYihwxLfJGGr8Ozs7GtXr757+w67OWdgYNDL19c/wH9KaCgMw8OHDM3Nydm9by+WOclFI1mEQyHZvubPmfsxK+txwlPJRwOKBm9JcfHqlStTU1IBABQdirmZ+aq1ayL/d+ljVpZ3jx5rIiJMzUxlf/gmKWnt6jXY/lMIgiZPmTJtxvT09PTNGzZiKlhbW4dOnz51WujVy1c2rFvX/pf2XbpQ9fX1dfV09XT1jI2N+w3oP2DgQNmtEkTIKYVTJ07u37sXhmF9ff3OXbr8/sehsJmzqior3dzcNm/d6urmumPrNvwQqojY5eXlEatXJ7789o6Co6Pj/IULhwwbSqRfLS0tpYMCm1xjY2J4PF5JcXGPnj1tIIjNZiW+TPT08tywcaPFv7eb4PQYPnfOlchIWVHxVVCkuNKYRtxfRAiA08jufXv/PHJUkn5jx42LWLOWCPeU+l3pdNnU8R+rgD+B4rgJAICjI7766rXZ5DkQLIIZ9QwzMzNtLW0en8fhcMRxn8vhfPjwobamtpubK/4swmFzMjLSIVtb2TkDAPDo4cPrMbFyX8wZMWRoTk7Op7zcT9nZJSUlhoaGjk5Oko3giIeiaFlpaW5uXoeOHSAI0v33eyUVFRVvU1NNTU17+frq6ekxGIyk16/d3T1atW7FYDBMTUz09PV5PJ5QKDQyMpIqsbCwIK6CFBT12/6X9kT0JWgWPp/f0NBgYmKip6cHwzCTybQwt5D6rgKKouXl5Xm5uTo6ug6ODthuR2zBx+fzTYxNGhoaLCwttLS0EASpq6szNTXV1dXlcDh6eno6FB0ps5uZmXE5HCNjYwqFIrYSh80RCPgmpqYAAA6Ho6WlZWpqin2Iw8jICEVRNputr6dnaGSk1DI4RIJhuCA/v7SktGOnTra2tpiaAoFAg14DALBYLG0tbT19PS0tLaFQyONyzczNZb+hgX1wQ207MBgMfT09PT19BEU4HA6fx2trZSWOOwwGQ6wFj8djsVhGhka6eroUCkUkEvH5fFgkwqaoly9eTp869dbdO07Ozjg5UCNZpIhCsqitra1nMCBbW4KxBQDAoNOzs7NbtWoN2UI6Ojopyck2EIR1IfeHfD6fw+aYmpkiCMLhcACKWlhaikSi+vp67MOcbBaLoqNjamoKi+BTJ0/cj7tfX1+PwLBAIOBwOFwuF0GQA7//PmrMaFWHraKR/iEz08rKqpurq7a2dvyjxy7dXKQSJvwQKpfY2F1GY2NjXV1dkUjEYrH09fUlb2Pg9EtkUGD9YhvbRSJRcVFRfn6+oaGhs4uLos3sinpUJKpSFeQqTiSmEfQXQQIoaqRt27ay0Y8g94j4HX+6bOr4L1kBZwJV5CYi3Ma5pHabTZgDNQNmz5o1MyzMp1cvRc7+nJ8HWjZwVFAJBPX9UczyH/FaC8S7t293bNsec+M6zqFHJIskwaDTR48cRaPRzv/vImkNkgAtGeTIbQy0W5pACU+fcrm8nj4+8rdWoAgMw5LvyLRA4KugEgjq+0OYpYVDg15raeByOAf27d97YD/+qY//TRbxeLzQkCmvEqXPu7KwtHRwcOjUuRM5NEgCtHCQ8b8x0GkhcmxYt47NYpuZm9+6efP6rb/lBmsEQbCdnnW1tXIfurd8FVRjNjF9W7hZWjg07rUWiIaGhq3btyl60/s/ziItLa2CgvyZ06aviVj768SJ2OYqHo93PTb206dP13bEkGOEJECLToDI+N84tJT7QLAIvh8Xl/Xhw/lL/7O2tpatkJGeMXTQ4PLycooOZXzwWOx7aS3KlEpVUAkE9W35Zmnh0KzXWibatW8vtfOGZJEY+vr6t+/emxUeFhMd3atHDz/f3oP69R89YmRJcfGduHtKz5cnQRLgO4KM/xpIgluOyRAEkd1SKga2V87U1JRCocAimMPliDeUtaiUHEcFlUBQ3x/CLC1/IaUpr/2gIFmEAUVRHperp69PUfcTVyRIApAjl8yBSJAgQYIECRIkWjq0SROQIEGCBAkSJMgciAQJEiRIkCBBgsyBSJAgQYIECRIkyByICAoKCqKjon5ukyEIkp6WduHc+RYuJ5/PLyos+ikdR0S17+ImGIZTklMuR0aSkYWEZkdoU4DgqP++csrtvaKiIjYmpjmF/O7O+llZ+v0Ni2oIn7I/jRg6DKLSenp6oT8vkt8k9/LuAVFpnu4eLVzUhfPne3Rz/fLly8/nOKWqfRc3PXr40MvDA6LSAv38W6DR4h/H9/T08u/TN9DPv28v321btogvbVq/wcvDw79P3yB//4C+fnPCwmV/np6Wjl3t28t3zMiRKInmGqFNAZVG/XeUU7b3vLy80SNGQFQaRKU1p5Df1wg/MUu/u2E1dh/Ivqv9+o0bDAwMfu6k2Mvb6/fDf0h+r7Tl5u88HovFwr5m/JM5Tqlq38VNgUFBfx0/IfsZnRaCoH5BD5/EM+j0kuLiXXv3bti0SXxpy/ZtV6KivpSVlRSXxNy4fvzUSdmfu7q5PoyPhyCou6dndOx18i5Os43QpoBKo/47yinbu7W19c49e2Q/VdbUQn5fI/zELP3+htVsSjWo/4Cf+z4QhpHDhrf8+0BsFvtVYuJP6TiCqn0XN/Xt5dsy7wNhWLNyFUSl7du9R/ZSaEgIRKVdi4rC50l6Wjp5C6f5R2hTgOCo/75yyu19dliY1H2gphbyuzvrZ2Xpdzes+veB9uzaJVuoq6OZj2/Ibbzl4If4ooKRsVEvX99mdtz3Va0luKmFc2PEqFEAgDt37qAyB4ONnzABABBzLVrRbysrKoVCQTfXbuQtnOaksaYgO/AJjvrmlFNWSLm9awGtxoS7lu+s7wK5tpKruHpWJd5+c0LNHKimpubypaba+Nmkjf/HQdr2Pw4fH582bdqUlZZmZGRIXRowcKC5ufnb1NT8PPkfoL4fFzdq9Jif8pNq5MD/KYUkw11T2Eo9q7ZYX6iZA12JjESa7IDpJm38Pw7Stv9xUHQow0YMBwDcuXVb6pK+vv6oMaMBAFFX5b8rdPPGjeCxwaQNyYH/owhJhrumsJV6Vm2xvlAnB3r08OGfR4/i14FFcEpyyr07d4uLiuVWKCkuvn8vLiY6OvvjR1Ubl0wtH9y/DwAQCoWvX726ef3Gi+fPuVyuVLWvX78+fPAAAMBkMu/euZOdnS15lUGnv0pMTElObmhoUNRRXV3dk8fxN2Kvv3j+nMfjyVaorKh8lpAgVVhVWZnw9Kls5fz8/Af377988aKqslLabjCc9v59/KPHRYVFCIIotQBOfS6H8/TJEwaDoVnH4fSIb2eCBCBiKFnVCLpJEfA5oJJeYrDZ7JTk5OioqGcJCbKcxLeASCRKT09/Ev+ktrZWJRcQwcjRowEAt//+WyQSSV3CHoddj40VCARSl3JzcoyMjDp17txIMXDIj2OQ6urqO7dvY/xMfJl4I/a6optVBM3F5XJZLBaCIEKhUEwkDpvD4/EEAoEUDXAEo3+lP3r4EACAIEhKcsrdO3ckBw6Px3uVmHg/Lk5WWUU0JqipSsZXOvDxR71cOfEpqkZ4VCSkosGutJpsg1wOh8vhoCjKYXPq6+vFujPodFgE8/l8LodDvP1G0hIAwGKxXr96df9eXGZGJpPJBNgHyyQCF/FppZFjB4chUorjc0mNaV2yfR6PV19fD8Mwj8fDDPItPjMYIpGIx+Nx2BxNhcF/oOoGogP79ru7dLOztsFePPZ09/Dy8MjMyMCuDh88pKen18esrP4BgT26e2LVdu/ciSCIuIWqysppU6b6+fY+sG//ssVLICptQ8Q6rAJ+45L4+PFj+MyZ9jaQn2/vp0+e9PT0cnF0wl6Y9Ojm+iwhAauWmZERGhJiZ23j7tKtvr4+0M8fq5OakoKiaGlpacjESUH+/ps3blqxbJm3R/dN6zfU19dLdsRgMFYtX+Hn23vXjh2nT55cvWJlj+6eLo5O4s226Wnp48YEQ1Ta4AEDxb9KS0v7dew4iEobEBgk2Vp1dfW0KVNmhE7bvXPnwKB+dtY2q5av4PP52NWCgoLgkaNWr1i5aMECF0enYYMGp6Wl4fhCUX0OhzNr+gxHO3uISvuYlaUpx+H0iG9nKeAQQKmh5KpGxE2KgM8BlfTC4OfbO9DP/+b1G14eHkH+/pionm7uT+LjCVqgpqZm9IgRC+bO271zZ/+AwG1btixfslSpC4gDQZDBAwZCVNq9O3elLmWkZ2AK3vr7b6lLO7fviL52rTFi4JAfxyB5ublTJ39zQV5u7oDAIG+P7piQ27ZsgWEYv1NFcl69fEUcMcYHj+XxeCiKnj550tXJ2cXBcdeOHUo9VVxUNHPadHsIcnfpVlBQMHTQIC8PD3sbyJZmfejgQRRFE54+9e3p09PTC6LSHGztoq5cFUsll8bENVXJ+DgDX+moVzTc8CkqdaQCkfAoV8jkN8lye0dRdE5YuHhPNPFwt3D+fHsIgqg0W5r1quUrsJr5+fn9AwKxQfr3zZuyKjTSWXLBYrE2b9zUt5fvimXLfj9wYMHcec5dHQYG9Rs3JnjPrl0qTSuNHzuKGCKrOA6X1JjWZdu/EXvd3aUbVk08BlEUnTZlKjaIIi9d0lQYFEPN98KCR412cXSSLR8+eIijnX3IxEmFBYUoilZVVQWPHAVRaQ/u3xfXmTV9ho+Xd1VlJfbnrh07pCYVRY1LpSZXL1+xhyB7G2hOWHhxURGCILW1tRfPX3CwtbOztsGmHBaLFXXlqoOtnZuzy4ply2Kio5Nev16+ZGlpaWlZWZmbs8v8OXOx8IeiaEV5xcCgfqOGjxAKhVgJn88fOWz4nLBwLpcr7vpZQoLkwTNMJvNK5GUpsnI4nOsxsXbWNpJk/Vr3tZd3j0sXL4r3wy+YNw+i0rDg+OXLFx8vb/EY+/zps7dHd1cn55zPn+VaAKc+giDv370bPniIbOxojONwesSxs2xfSgmAYyi5qhFxk1wo5YBKeolzIFua9YaIdUwmE0VRgUBw9/YdN2cXiEp7+OABEQtErFmzZOGib0RisyeMGxc8cpRSF6g0fs+ePg1RaSETJ0mVL1+6dP6cuRCVNunXCZLlQqEwoK8fi8VSWwx88uMYRCAQPImP7+bkZA9B06eG5uXlYfycMmkyRKXdvnULR018OTMzMlwcnZzsu4orNDQ0DAzq9yYpiQhX+Xz+wwcP3Jxd7CFo5rTp+fn5KIrW1dVN+nUCRKWtXb1mycJF2A8/f/oc0NfP3gYSdySXxgQ1VY8Dcge+0lGvKJLgUFQKxMOjrJA4cUwyB1Ip3KUkp0BU2uywMMlCkUjk6e6R9Pq1ojWD2s6SC6FQOD547OQJE+vq6v5ZjJWU+Hh5Q1Tax48fVbKbpsaOrK0UGVYul9SY1uW2/yEzE6LSli9dKlUzoK/f82fPNBsGmyoHcnVyZjAY4pLCgkKISgsNCRGXXI+JTUn+xzRx9+5BVJrkEpNIDoRhYFC/np5eUkl3/ON4jDoikehbtX79ISrt/NlzUqPIuauD2GfffvvoMUSl/XX0KPbniWPHPd09JNXB/NHHp5fk5IogiJeHhyRZMfh4eUuSddOGjaOGj5C84SESia5dvUr/+hULK1KOj7x0CaLSpk8Nlau70vqHDh5UKQdS6jilPcq1syyUEgDfULKqEXSTLIhwgLhe4hyoby9fqdtab5KSICqtX0AAllrhW2D0iBHBI0eJWyguKho7egxBFxBEXV1dV8gWov5fe1ce1sS19k92gYRNQSrcsgQR0Sooq4IKgqitC4tVwaUgar33WkWqdWu/ulxrW+31s72Pol+v4lbBDbVVqrZiXepWZbNBliBLAyiUAMmQkEzy/XH6zR0zSyYh+tXnmd9fOjmced/fu5wzZ855xwemRWydZmpiokqlgo9i+J8uX7qEPTdbJwa9Tc26BBytMQeAqVzq7TM7NZVGTbNy/nTtWoBUGh0Z9ezZMxRFl2Ytxh40Gfpq0vTpQQFD8L5X9fix1NsnMT4Byz9Go/HWzZvw4RvfOWmEmtXUOh+gmgOZjXpSOWlclHQOwSQ9UglJyhJ+DmRpukueMXOwrx/+MaampiZ+QqxJzDIRwzq3PJyXN3xoUEtzs8n1t1NSB/v69fb2WsSbrWKHamggKk7a0uphndj/rOQUk5iqrqpKiI3DDGSrNNjXs/FUsLOzc3Jywv7r4+vj5eUlr5VjV5JSkkPDQrH/CoUiuNPCinsJhUKj0cjlPqdFbFxsaFhodVWVvLYWXhGLxXb29vMWzMfaIGrkyuXLQcOGuQ8ciP/b8bETeHxe/jfH4evGPf/6V0hICF4dAACHwyFeEYlEJJuteDz8y8sT+fmRUZH4YzU8Hm/W7NnOLi6oHj1z6nRQUBB8O1leVv7JP7adLChYtHjxmnVrSd/fm21v6fkdesMxuSORZ1LQOwA9UUTVmJvJBEx8wCK9MPAFAhPywyMixowd+6TuSU1NjVkGhg9/o7S0NGPBwpKHD41G4+ve3vknTzA0AUO4urrGT0qAGxWxi0cPH06bN8/BwSE5NcXkp4L8/Lnpacw9gbh5hd6mZnOCUCgUiUSYAwAA3N3dvf7yl+qqapo9LmbljBk3btv27c3NzcuWLP1q9243N7e09HTmvgoA4HC4QqEQ72mDAwJcXV0NKMrDhX94eIRQKCwrLTNxUdKcRqOpDX2AYbomlZPKRUnBJD3SgGEeY57uMhZlGgyGQwfzsCs/Xvkh5e1Z9D1YYSyqzSdf7f4yJiZmoIcH8VdHR0esyCpD3l5E7FhBrNXDOrH/+QsXaLXac4VnsSvnz517e84c2NLmIfAyqsK8NmhQaUmJSXq6ffv2vbt3Hj54IPtV1pfOiZs3ORxOWHjE/Xv35XL54ICAP/Tk8fApCQ5Fr3u/bnpqhsfz9PRqqK/v6elpaWnp7u72H+xPOsiZXDGgZvZkNTU29fb2uru7k/76229NOp2uqanpix07f7xyZUhg4MzkpDVrP+BRpAlL2/fdcAzvaMIzzfhE5QD0RJHswmtoYG4mPJj4gJ2dnUV60SA4JOTWzZtP5HWBgYH0DKxe+4FCobhWXHzj+nU/P7/F7y5NTk6xudHnzE0runDx9MlTOatX29nZdXd3ny08e6HoIgAgLT0978DBgvz8FdnZEolEoVA0/6YIDgmx2veY2NRMTiBLxB4eA5saG6k6ZChnSmrq09bWnZ/vaGxo+OnWTYsFI302Ewm1Wu1zTsXnubi60my5ZajpSwh8YromgspFqWA2Pb5MTJ4yZaCHR8Hx4yuyVzo4OAAAii5c2LMv15q+LHfL1pbWtrY2Xz9fJh0y5M3msWMdbDWsT54yZZvb1iOHDqXPn8flcvV6/dkzhafPnX1BY9/L+G68ydcDKisrEyZOXLF8uUajWb5i5bZPt9t2DgQAGDBgAADABTfzJZzZUdHMcLlcLofD+b29HQDQ3tbOcGu5AUVpjwB0AwDq6xtIf21vbwcAXCu+5uPrk3/q5M5d/4wZN47GqJa277vhbHhHegegJ4rk0JYlZrLUB2xIZv/+/QEAbu5uZhlwdHT8+uCBU4VnEiZNqqurW7fmg8x3Fmq1WtsafWz0WP/Bg7u6uuCZkcN5eTNmzrCztwcASP39o8aMQdRIwfHjAIBjh4/Mmj0bY8MKMcza1LqcwOXS3ZS5nKFh4SKRqK2tbd/eXJsIJhAIbRuJmKYvIfCZfOyFykWtTo8WH+UB1p+y5vP58xcuUKlUsByoTCZzdnExWQy2ibFI0aHsAAA8e8ro0xBMeHsRsWPzrG6pB85NT6utrS2+WgwA+L6oaGRwMPZ1FJuHgJVzIB6PZ7T2NNrq7FW/NTUVnDq5dv360LBQvU7fl87h21PCc2cjl8sdEhhI9VfePj4AgAZCUkZRtLWlxcfHp1+/fnANqby83MigqoFYLG5tbSWe0MP+1s/PDwDwy717pKf4YATyuNyk5GT4aEIPS9v33XBW39FSB6AnigiLzGSpD1jzMGRAKdar6kUiUeDQoWYZOJGfbzAYRgYH79mX+0Px1SlvTr1542bRhYs2NAGc/GVkZgIAjh05gqiREwUnMhYtwi9HAwDyDhzs7u7+9vz5JFxZICvEMGtTszmBajDru8dWV1Wtzsk5dbZw1OjRu774oujiRRsIZuunEUzTlx/4pKByUavTo6VCasiKTTDXem5amr2D/cEDB+Bb2pTU1BdhLKpY4HK5Dx88QBlMCpnwZqvYYU4+aUvbDuvp8+cLhcL9ubkwC2UsynwRI1Gf5kB8Pl+j0cBKBl1dXTqd7o+1O6OBfujSaDQymczd3R2mRQDA06dPoVXNdk41UzZZCkL16HfffZc+f95/3nPD7d84DBo0KDIq6tdHj0yKW1wrvqbVaifExcFnneiYmOqqqoLnS8bBIyG9vVp8nyNDglUq1d07d7ArnZ2diFqN/h8bdvb2Y6PHVlZWnjpxwqS3+if1np6eQ4cOraurO/n8r6ge/eX+faLWTNpD8XTP+6LVhmMkIYFnKxyAniiiahaZyVIfYK4XTkGtjrA22dvb++2581lLFjs4OJhl4OiRo1d/+BH++3Vv7127dzs5OdXXP2FiAq1W++ujRwxFnZE009nFpbysfO0Ha5KSk/D7QibGx3v7eCsUir8vWzblzakSicQyT3ge9DZlkhOsABM5m5ubszIyt27bFhgYuHf/voEeHu9nr3pUUcE8WREHcji/JF6kuqJjNmhZTT5N4JuNeio5qVyUqgez6ZFGSFKWEKSHCZlU6c7JyWnO3LTGhoaiixevFRdPTIi3ggTrIBKJwiMi6urq8PvtqDzELG82jB0qroiKE1v2ZVgnJbZ///4pqan37t49dvQoiqLYi/i+hICN50DwGfrnW7d6EGTl8vca6usBAAaDoVnR3NHRgX/tDYtJ6HQ6uITVr18/94EDm5ub4XjW2NCQu3cvAKC7WyWTyeRyOVXnNDh+7Bs8EatzciRi8cpVqzABOpTKnp4ek6nSZzt3CASCLR9vwozR1ta247NPPT09V2Znwyubt26xd7D/rw8/3L1r17Nnz1A9KpPJlizKktfWImrk6/3/g+35mjM3DQCwYd26uro6uI/9r0vf1Wq1zQrFt+fPw1XidRs3CgSCjRs27N2zB/7h06dPVy5/7+CBfwMAPt3xuUAg+GjDxn17c5UdHXq9vrSkZF7a3IryClKtzbaHX+Jtb2+zieHM3pGKZxMwcQB6ooiqMTeTCZj4AEO9IBQKhbKjo7W1FT8R0Wg0f1+2bIDbgKXvLmPCwIABA7Zu2fJHEgFAqVT29PSER0QwMXr2eytmTpt+7+5dJlHcr18/uAX4xk/X38nMNHloy1qyBABw5/addzIyLPU9ImhsapYQFEVbW1sQBOn4vQPvn5Ai/EWL5GxpbslYsDAzKys6JhoA4OrquvOfX2g0miVZi2FcmBXMYDB0dHSoVCqs4B5MQUqlsq2tDe8wOp3u9/Z2lVqNH+eIEcpEUyvIJw18hlFPKieNi5KCSXqkyk7Eu8MqBjBaaYSkH0oyFmXy+LyN69ZPSkwk3XpsAuuMRYpNWzYLBILNH2/6aveXyo4OOCfY+fmOhw8eWMqbDWOHiiui4sSWfRnWSQ0HAMhcnMXhcD7+8CP8IpDV+cfM9NYK1NTUhI8aLfX2GTYkcN/eXFh3ARZek3r7TIqbeODrf8OaTvBcsdTbZ0xE5Nf798NTc0MHB4weGTzjrWlx48eXlJREhUeMGjFy/NhoeFyQ2DkVYGmB2HHjF86b99n27Vs2bZqcMGlNzvtqlRqrBjHjrWlY7cQ5s2Y1NjTgT7EuSE9PjE/YunnL6lU5kaFhf3t3WWtrK/4W9U+ezE5NhT0ESKVhIaMK8vNnvDVtsK9f2uw5+G9o79ubG+AnlZfG/WQAAAUXSURBVHr7BAUMSYxP+PXRozERkVJvn+TpM7BmZaVlceP/qLMXFjIqMjTs0ME87MjfrZs3MQ6HSP0jQ8MKz5yhUZ+qvVwunzc3DdakihgdmpOdjd2iL4ajuSM9zyYw6wA0RFGpxtxMJqD3AYv0MhqN3xw9lpqU/NaUqSOChmVlZG7b+o8N69ZNiBmXk52NP5tKz8DWTZvXrl4TO278xx99tPPzHfETYr/8791mjQ6xddPmYUMCK2WVDAO5taUlQCrF94+hp6cnfNToNTnvW+R7NKBxfhpCCk+fGR8dg/knrFBQUlKC2SV+Quyhg3mWxsil77+HJQAmxU2E6aKzs3NqYiJsGRQwBFaLoRHswrffJcYnwPZR4REwmr4vKkqIjcMuFp4+YzQaz509iyn+ZuLk6z9dJ3Xjn2/dYqipFeSbBD7DqKcKN3oXJQWT9GgiJOndy0rLkqZPh0KOjYzM3bPXonSHx+pVOSaH5KnKbPbFWKQoKSmZFDcRi4VhQwI//eSTpOnTibU8zPJmq9ghckVFLCmrVgzrNIaDWLZk6fix0Vi5vj7mHypwjNYuOCNqpKysVOrv7+bmBhfhOzs7nZyceDyeWq02Go3Ozs69vb1KpVIiFguFIjWiNhgMzs7OcAn6l/v3JRJJ1JgxQqFQqVTe/vnn4OAQj9c8SDunwrQpU6uqqiprqitlsoaGBjs7u6FBQfg/0Wq1XV1dYrFYKBSiKNrd3e3s5Mzj8/BTQIVCUVNdzecLAocGwo2rRCg7OmQymatrf6m/lM/n37t7108qJTZubm6uKC93d3d/Y8QILpf7w+Urw98YbnIG0mg0NjU2VlfXDPIcJJVKTXYgoigqr61tbGj09PLy9/fHi0q++4SsPapHlZ1KR0dHLoer0WoQBMFz0hfDUd3RLM9EougdgIooetUYmon4GEDlA5bqhaIo3Eyt1+vrnzypra21s7MbNnw4tqGPOQM9CFJRUdH2rO2NkSO8vLwYOgnUxdPTk3kg37h+IzgkWCwWE38qefjQw+M1vFH64qv0zk9FiIurC6JGJI4Sg8GAIAgwGp1dXPR6fWdnp6OjIwBArVLx+Hz82zomcmo0Gq1WK3YQd3V1Obs4czgcg8HQ3t4ukUgEAgGCIPBEMb1gPQhi7+DA4/E0Go1Op3N2dkbUSG+vViyRAAAQBOFwOBKJBH6Uw97e3mg0qtVqkVAoFIqIbqzVaplragX5+MBnGPUSsYQm3GhclCrqzaZHvJCkwf4fIUUiSDu9kDRDyeVLl06fPGX2RBipGBYZi6pbubz28ePHYrE4OCTE2dl5duqs2tra+w8fWMqbrWLHhCuaZEvKqqXDOn0yh+t8nUql1N/fVvmHfGek8VX+pBycAz2urQEsWLBgwYIFYyxZtCgzKysyKupPIg/VHIjFCwX3lZbeYDSgKEr89CMLFixYsGBBheKrV3t6NBGRkX8ekWxeQYAFE/BfXdENBkN3VzcAoL2tjbTmJgsWLFiwYIFh4/r1apXa0cnpXGHh6XNnbVsDrC9A9ahcLtdoNL29vUKhkLXUS8Orug5UVlo2NXGyQqHg8XmzklPgB/xYc7JgwYIFC5qpRtHFi48qKg4eOezr6/snkWrr5s1R4eFdnZ06nW5CdMzhvEOspV4aXtX9QHq9XqVSSSQSHo+H6lGkB6HZfcaCBQsWLFgAAAwGg8knJv/foVKpBAIBXP6B5R9hxXYW7ByIBQsWLFiwYMHiheB/AS9BaNGSg0doAAAAAElFTkSuQmCC
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
''Self-assembly''
There are two main types:
* __Equilibrium self-assembly__
* __Non-equilibrium self-assembly__:
** Steady state-non equilibrium, for dissipative systems that consume energy.
** Transient non-equilibrium, which can be effectively stationary by virtue of a very <big>large</big> relaxation time-scale (like in glasses).
[[Self-assembly of active colloids]]
[[Molecular self-assembly]]
[[DNA nanotechnology]] is mostly based on self-assembly
[img[https://media.giphy.com/media/l0MYHMv4B3JBwlSYE/giphy.gif]]
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http://phys.org/news/2016-02-scientists-gold-nanoparticles-diamond-superlattices.html
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[[Self-assembly, modularity, and physical complexity|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.82.026117]]
[[Nature Materials: Topological defects in liquid crystals guide self-assembly|http://ime.uchicago.edu/about/news/nature_materials_topological_defects_in_liquid_crystals_guide_self_assembly/]]
[[The Free-Energy Landscape of Clusters of Attractive Hard Spheres|http://science.sciencemag.org/content/327/5965/560.figures-only]]
[[Dynamical Arrest in Attractive Colloids: The Effect of Long-Range Repulsion|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.94.208301]]
!!!<mark>[[Design strategies for self-assembly of discrete targets|http://scitation.aip.org/content/aip/journal/jcp/143/4/10.1063/1.4927671]]</mark>
[[ The Information Capacity of Specific Interactions|http://arxiv.org/abs/1602.05649]]
[[Self-Assembly of Structures with Addressable Complexity|http://pubs.acs.org/doi/abs/10.1021/jacs.5b11918]]
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[[Manoharan group|http://manoharan.seas.harvard.edu/publications.html]]
[[Size limits of self-assembled colloidal structures made using specific interactions|http://www.pnas.org/content/111/45/15918.full]]
[[A geometrical approach to computing free-energy landscapes from short-ranged potentials|http://www.pnas.org/content/110/1/E5/1.full]]
[[Design principles for self-assembly with short-range interactions|http://www.ncbi.nlm.nih.gov/pubmed/21383135/]]
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Hierarchical self-assembly
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Error correcting self-assembly
[[Active colloid]], [[Self-assembly]], [[Collective behaviour of active colloids]]
[[Self-assembly of active colloidal molecules with dynamic function|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/pre15_colloidmoleculefunction.pdf]]
[[Self-Assembly of Catalytically Active Colloidal Molecules: Tailoring Activity Through Surface Chemistry|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_activemolecules.pdf]] [[online|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.112.068301]]
While individual colloids that are symmetrically coated do not exhibit any form of dynamical activity, the concentration fields resulting from their chemical activity decay as 1/r and produce gradients that attract or repel other colloids depending on their surface chemistry and ambient variables. This results in a ''nonequilibrium analog of ionic systems'', but with the remarkable novel feature of action-reaction symmetry breaking.
!!!__Effective phoretic interactions__
See [[Collective behaviour of active colloids]] for further derivations of similar effective interactions between active colloids.
The effective interaction, in the far field regime turns out to be analogous to the Coulomb interaction with generalized charges, that ''break action-reaction symmetry''. In particular, we differentiate between the charge that produces the field, α , and the charge that responds to the field, μ .
__Model and simulation__: There is a highly successful and widely used restricted primitive model (RPM) for charged colloid based on Coulomb interactions augmented with short-range steric repulsion between the particles. A generalization is done to the nonequilibrium active colloids, and the model is analyzed using Brownian dynamics simulations, to explore novel phenomena in this system.
Periodic boundary conditions are used, and interactions are treated using the minimal image convention (<mark>what is this?</mark>)
__Approximations__
for simplicity, use a model in which the catalytic activities of the colloids are simplified into net production or consumption of chemicals with given rates. They also assume the substrate concentration is constant within the time of their simulations, which is a good approximation in the dilute limit.
we do not consider the [[anomalous superdiffusion|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.102.188305]] at relatively short time scales
In the studied experimental systems, the <b>Peclet number is small</b> (Peclet number is $$\text{Pe} = V \sigma /D$$, where $$V$$ is the velocity of colloid, $$\sigma$$ is its diameter, and $$D$$ is the diffusion coefficient of the solute molecules). This means that the solute concentration profile relaxes very quickly to a comoving cloud when a colloidal particle moves. At finite $$\text{Pe}$$, the [[cloud is distorted|http://scitation.aip.org/content/aip/journal/pof2/25/1/10.1063/1.4772978]]. This also mean that we can ignore the spontaneous symmetry breaking ([[spontaneous autophoretic motion of isotropic particles|http://scitation.aip.org/content/aip/journal/pof2/25/6/10.1063/1.4810749]]) at large $$\text{Pe}$$.
Concentration fields are assumed to be far-field. Near-field fields would have to be calculated by solving the diffusion equation, and the resulting forces will in general not be pairwise additive. However, the forces retain the action-reaction asymmetry, and will only affect the dynamics quantitatively.
Hydrodynamic interactions are ignored, but their effect would just change the dynamics quantitatively (and not qualitatively). See more details of the model [[here|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.112.068301]]. For the results they use to estimate the effect of hydrodynamic interactions see [[Hydrodynamic simulations of self-phoretic microswimmers|http://pubs.rsc.org/en/Content/ArticleLanding/2014/SM/C4SM00621F#!divAbstract]]
Brownian dynamic simulation is done so that the colloids are constrained to move in 2D (while the diffusing particles diffuse in 3D, so the concentration still decays as $$1/r$$).
__Non-equilibrium effects__
When the effective interactions between the particles are not symmetric, the system cannot reach an equilibrium state because the condition of detailed balance will not be fulfilled. This can manifest itself in the form of frustration that leads to nonequilibrium fluxes. This also mean that the long time behaviour may include limit cycles (//oscillatory instability// see below).
!!!__Cluster with ''oscillatory instability''__
The internal dynamics of quasi-stable (for small perturbations) clusters for the case of two kinds of particles (A and B) can be analyzed using d'Alembert's principle (see their Appendix). A Hopf bifurcation can take place (where the parameters are the charges of the two kinds of particles), so that in a certain regime a stable limit cycle forms. This is the oscillatory instability. This is demonstrated in the A,,4,,B,,8,, colloidal molecule.
<mark>What symmetry makes the second harmonic absent?</mark> Probably some dynamical symmetry
!!!__Cluster with ''run-and-tumble behaviour''__
In the AB,,3,, molecule one finds that in many parameter regimes, there are two stable configurations, and the system stochastically jumps between the two. One of the configurations has the B colloids symmetrically placed around the A, while in the other they are asymmetrical, causing (due to the asymmetry of the forces of the colloids in the fluid) a net self-propelling velocity.
The motion of the internal degrees of freedom is again derived using d'Alembert's principle. There is an angle variable which is cyclic, due to rotational invariance, and gives a conservation law. The other two angles follow a set of coupled ODEs which have equilibria corresponding to the stable configurations.
By simplifying the dynamics to the line where the two angles are equal (because both equilibria lie on it), one can obtain a single-variable [[Langevin equation]] and a corresponding [[Fokker-Planck equation]] to study the probability distribution of the system, which can be used to find, for instance, how much time is spent on run vs tumble behaviour. This was measured from the Brownian dynamics simulations. The residence times in the run-and-tumble phases exhibit an exponential dependence on the value of $$\tilde{\mu}_A$$. The measured behaviours are consistent with what we expect from [[Kramers’s first-passage time theory|Kramers rate theory]]
!!!__[[D'Alembert's principle in overdamped dynamics]]__
A quantity is ''self-averaging'' if its sample to sample fluctuations vanish in the thermodynamic limit.
Non-self-averaging quantities are characteristic of [[Disordered system]]s
In ''Self-diffusiophoresis'' (a kind of [[self-propulsion|Self-propelled particle]]), a particle itself produces the compound it interacts with, through [[Diffusiophoresis]], causing it to move.
Self-phoretic particle. Creates something that it then attracts or repells, and that something then pushes the surrounding fluid (creating a slip velocity). The particle is then indirectly pushing on the fluid.
Same kind of indirect propulsion as ionocrafts!
Another analogy for the symmetric catalytic [[Active colloid]]s, in the limit that particles of type B are attracted to A, but A is not attracted to B (see [[this paper|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_activemolecules.pdf]]): B particles are like little [[homing missiles|https://en.wikipedia.org/wiki/Missile_guidance#GOT_systems]] that target A particles.
An example is a particle that catalyzes the reaction 2H,,2,,O,,2,, → 2H,,2,,O + O,,2,,, creating an O,,2,, gradient and interacting with it. Another example is a particle that facilitates the polymerization of a biopolymer (e.g. actin), which creates a gradient because individual monomers diffuse, whereas the polymers do not. The latter process is one possible mechanism for the propulsion of Lysteria bacteria by means of actin 'comet tails'.
[[http://www.sas.upenn.edu/~tidema/research.html]]
--[[Propulsion of a Molecular Machine by Asymmetric Distribution of Reaction Products|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl05_motor.pdf]]--
,,[[Propulsion of a Molecular Machine by Asymmetric Distribution of Reaction Products (article)|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.94.220801]],,
"For a totally impermeable particle, depletion of the molecules near its surface causes a lateral slip velocity that results in net motion of the sphere. ". Depletion only if the mobility is positive, which corresponds to the surface of the particle repelling the solvent molecules thus depleting
The diffusiophoretic effects also turn out to contribute to the <b>diffusion</b> of the particle (the induced velocities have a random component), with a diffusion constant that can be estimated.
Consideration of rotational diffusion is important, as it determines the time scale over which the particle is able to move consistently in a given direction.
[[Dynamics and efficiency of a self-propelled, diffusiophoretic swimmer|http://scitation.aip.org/content/aip/journal/jcp/136/6/10.1063/1.3681143]]
[[Self-Diffusiophoresis in the Advection Dominated Regime|https://arxiv.org/pdf/1107.3851v1.pdf]]
__[[Concentration around a self-diffusiophoretic particle]]__
!!!__Diffusiophoresis__
See [[Diffusiophoresis]] for the equations giving the drift velcity of the particle given a particular concentration $$c$$ distribution on its surface (found from above equation).
!!!__[[Designing phoretic micro- and nano-swimmers]]__
!!!__[[Collective behaviour of active colloids]]__
a.k.a. driverless car, or autonomous car
See [[Transport innovation]]
See Tesla, Google Car, etc.
[[Full Self-Driving Hardware on All Teslas|https://www.tesla.com/videos/full-self-driving-hardware-all-tesla-cars]]
[[Our driverless dilemma|http://science.sciencemag.org/content/352/6293/1514.full?utm_source=sciencemagazine&utm_medium=facebook-text&utm_campaign=drivelemma-5239]] [[Video: When is it OK for our cars to kill us?|http://www.sciencemag.org/news/2016/06/video-when-it-ok-our-cars-kill-us?utm_source=sciencemagazine&utm_medium=facebook-text&utm_campaign=okcars-5240]]
http://www.theverge.com/2016/6/30/12072408/tesla-autopilot-car-crash-death-autonomous-model-s
Volvo
!!!__Autonomous driving levels 0 to 5__
[[Autonomous driving levels 0 to 5: Understanding the differences|http://www.techrepublic.com/article/autonomous-driving-levels-0-to-5-understanding-the-differences/]]
https://medium.com/@johnzimmer/the-third-transportation-revolution-27860f05fa91#.vjs1zcy0k
Regulation: http://phys.org/news/2016-09-self-driving-cars.html
See [[Electrophoresis]]
[[Self-electrophoretic locomotion in microorganisms: Bacterial flagella as giant ionophores|http://onlinelibrary.wiley.com/doi/10.1016/0014-5793(72)80661-6/abstract;jsessionid=665626D3CE8D2E54EE144AFD41D66798.f03t02]]
[[Ion Drive for Vesicles and Cells|http://www.sciencedirect.com/science/article/pii/S0022519396900351]]
[[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]
,,Ionocrafts, ionic wind?..,,
[[Locomotion of electrocatalytic nanomotors due to reaction induced charge autoelectrophoresis|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.81.065302]]
[[Catalytically Induced Electrokinetics for Motors and Micropumps|http://pubs.acs.org/doi/abs/10.1021/ja0643164]]
[[Chemical Sensing Based on Catalytic Nanomotors: Motion-Based Detection of Trace Silver|http://pubs.acs.org/doi/abs/10.1021/ja905142q]]
[[Imaging the Proton Concentration and Mapping the Spatial Distribution of the Electric Field of Catalytic Micropumps|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.111.168301]]
See [[Electrokinetic effects in catalytic conductor-insulator Janus swimmers]]
[[Stuart Kauffman Books|https://www.google.es/search?q=S.+A.+Kauffman&gws_rd=cr&ei=IkIZV8PML8i7aqPtuIgC#safe=off&q=Origins+of+Order&stick=H4sIAAAAAAAAAONgFuLQz9U3SK8yMVDiArGMyjOyDI21BBxLSzLyi0LynfLzs_3zcioBqQGUoSoAAAA&tbs=kac:1,kac_so:1]]
Self-organization in non-equilibrium thermodynamics - Book by Prigogine et al
[[Information Measures of Complexity, Emergence,Self-organization, Homeostasis, and Autopoiesis|http://arxiv.org/pdf/1304.1842v3.pdf]]
https://www.youtube.com/watch?v=Ba0zSNYkWtw
--------
http://pcp.vub.ac.be/SELFORG.html
[[The Meaning of Self-organization in Computing|http://pespmc1.vub.ac.be/papers/IEEE.Self-organization.pdf]]. See [[Complexity theory]], [[Complex systems]], [[Sloppy systems]] Several people at the Free University of Brussels seem to be working on complex systems, from a very holistic approach.
[[Evolution]], and feedback.
[[Free energy principle]]
How does one define evolving systems that accomplish a desired function? We need the right feedbacks in a complex system. But the answer is not obvious. See [[Evolutionary computing]]
---------
[[On Self-Organizing Systems and Their Environments|http://e1020.pbworks.com/f/fulltext.pdf]]
[[Principles of the self-organizing system|http://csis.pace.edu/~marchese/CS396x/Computing/Ashby.pdf]]
http://bactra.org/thesis/single-spaced-thesis.pdf
[[Self-Organisation of Symbolic Information |https://www.researchgate.net/profile/Rainer_Feistel/publication/273887184_Self-Organisation_of_Symbolic_Information/links/5523a8b60cf2881f4e3a736d.pdf]] See [[Written language]]. [[Selforganization of symbols and information|https://books.google.co.uk/books?hl=en&lr=&id=0Qq3CgAAQBAJ&oi=fnd&pg=PA141&dq=info:gstkuB03TVkJ:scholar.google.com&ots=gk_Vu-OnBX&sig=3tLvITOrRKeS4Bn6TgU1IYtSVFo&redir_esc=y#v=onepage&q&f=false]]
---------
[[Self-organizing map|https://en.wikipedia.org/wiki/Self-organizing_map]] in unsupervised [[Machine learning]]
__Sandpile model__
See LectureNotes on complex systems
[[Directed percolation and Sandpile models - 1 by Deepak Dhar|https://www.youtube.com/watch?v=30WNNl5Fj7s]]
An [[active|Active system]] particle, often a [[colloid|Colloid]], or a nanoparticle, that propels itself through a fluid, often via some [[phoretic mechanism|Phoretic mechanisms of colloids]], or via some mechanical propulsion mechanism (the particles are then often called ''microswimmers''). ,,Generally, "active colloid" simply refers to a self-propelled colloid (and similarly with "active particle" in general).,,
"In the current miniaturization race towards small motors and engines, a rapidly expanding subdomain is the quest for autonomous swimmers, able to move in fluids which appear very viscous given the small length scales (low Reynolds number). [[Robotic microswimmer]]s that generate surface distortions is an avenue (e.g. by mimicking sperms [1]), but it seems equally interesting to try to take advantage of physical phenomena that become predominant at small scales. Interfacial [[‘phoretic’ effects|Phoretic mechanisms of colloids]] (electrophoresis, thermophoresis, diffusiophoresis, [2]) by which the gradients of fields (electrostatic potential, temperature, concentration) drive the motion of colloid particles, are from this standpoint a natural avenue given the increased surface to volume ratio of smaller objects. "
!!__Robotic microswimmers__
[[Microscopic artificial swimmers|http://www.nature.com/nature/journal/v437/n7060/full/nature04090.html]]
!!__Phoretic swimmers__
[[Designing phoretic micro- and nano-swimmers]]. A common design for phoretic swimmers is the [[Janus swimmer]] design
[[Self-diffusiophoresis]]
[[Self-electrophoresis]]
[[Self-thermophoresis]]
----------
[[wiki|https://en.wikipedia.org/wiki/Self-propelled_particles]]
https://scholar.google.co.uk/scholar?hl=en&q=self-propelled+particle&btnG=&as_sdt=1%2C5&as_sdtp
!!!Ramin's papers
__Phoretic self-propulsion__
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Propulsion of a Molecular Machine by Asymmetric Distribution of Reaction Products|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl05_motor.pdf]] See [[Self-diffusiophoresis]]
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Designing phoretic micro- and nano-swimmers|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/njp07_design-swimmer.pdf]] See more at [[Designing phoretic micro- and nano-swimmers]]
__Single phoretic swimmer stochastic dynamics__
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl07_exp-swimmer.pdf]] (experiment)
[[Anomalous Diffusion of Symmetric and Asymmetric Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl09_flucphor.pdf]]
[[Stochastic dynamics of self-propelled colloids]]
__Self-assembly of phoretic active colloids__
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Self-assembly of active colloidal molecules with dynamic function|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/pre15_colloidmoleculefunction.pdf]] See [[Self-assembly of active colloids]]
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big> [[Self-Assembly of Catalytically Active Colloidal Molecules: Tailoring Activity Through Surface Chemistry|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_activemolecules.pdf]] See [[Self-assembly of active colloids]]
__Collective behaviour__
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Clusters, asters, and collective oscillations in chemotactic colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/pre14_chemotaxis.pdf]] See [[Collective behaviour of active colloids]] <mark>There is a lot of different regimes in their complicated mathematical models, and fuller understanding requires going through their models more carefully</mark>
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Emergent Cometlike Swarming of Optically Driven Thermally Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl14_colloidalswarm.pdf]]
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Collective Behavior of Thermally Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl12_thermactive.pdf]] See [[Collective behaviour of thermally active colloids]].
__Others__
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big> [[Electrokinetic effects in catalytic platinum-insulator Janus swimmers|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/epl14_salt-janus.pdf]]. See [[Catalytic conductor-insulator Janus swimmer]], [[Electrokinetic effects in catalytic conductor-insulator Janus swimmers]]. See also: [[Locomotion of electrocatalytic nanomotors due to reaction induced charge autoelectrophoresis|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.81.065302]] and [[Self-electrophoresis]]
<big><i style="color:aqua;" class="fa fa-check" aria-hidden="true"></i></big>[[Boundaries can steer active Janus spheres|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/ncomms15_boundary-steering-Janus.pdf]] See [[Boundary effects on the motion of active colloids]]
[[Collective Behavior of Thermally Active Colloids (pdf)|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl12_thermactive.pdf]]
The motion of colloidal particles in a solution in the presence of an externally applied temperature gradient, which is known as thermophoresis or the Soret effect
Since such thermally active colloids would create temperature profiles around them that decay as1=r, in addition to causing them to self-propel, thermo-phoresis could provide a mechanism for them to interact with one another in a solution. The long-ranged nature of the intercolloidal thermophoretic interaction could lead to interesting collective behaviors.
the study of [[Meaning]].
__[[Formal systems and semantics]]__
Hofstadter argues that meaning is a [[Morphism]] (often [[Isomorphism]]s) between a [[language|Formal language]] (produced by a [[Formal system]]) and another space. See [[Formal systems and semantics]] for more.
The mapping itself is known as an //interpretation//.
Inferring semantics, is like deciphering a code or an old language. See page 50 of GEB.
A type of [[Machine learning]] problem where only some of the labels ('outputs') are available in the training data, the rest of the training data being just 'inputs'.
[[Generative model]]s are often used for [[Feature learning]] from the whole input data set, and then using the learned features, a model can be trained with the few labelled samples. See for instance, [[Generative adversarial network]]s
[[Semi-supervised learning|https://www.youtube.com/watch?v=pytUuJPOnVI&list=PLD0F06AA0D2E8FFBA&index=4#t=27s]]
--------------
I think, [[Generative supervised learning]] is sometimes used in the labelled part, and the rest of the trained data is used to train the [[Generative model]] of the inputs, using techniques from [[Unsupervised learning]]. The latent variables may be seen as predicted outputs for the unlabeled inputs.
In mathematics, a semigroup is an algebraic structure consisting of a set together with an associative binary operation.
If they have an identity element, they are a [[Monoid]]
[[Sensitivity analysis|https://en.wikipedia.org/wiki/Sensitivity_analysis]] is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be apportioned to different sources of uncertainty in its inputs.
[[L6 - Statistical Modelling - Uncertainty and Sensitivity Analysis|https://www.youtube.com/watch?v=n6zPtVWvJxY]]
[[Global Sensitivity Analysis: The Primer|https://www.amazon.co.uk/Global-Sensitivity-Analysis-Primer-Saltelli/dp/0470059974]]
[[A review on global sensitivity analysis methods|https://hal.archives-ouvertes.fr/hal-00975701/document]]
[[Making sense of global sensitivity analyses|http://www.sciencedirect.com/science/article/pii/S0098300413001702]]
[[Global Sensitivity Analysis|http://pubsonline.informs.org/doi/abs/10.1287/opre.43.6.948]]
//aka divide and conquer//
[[Separation of concerns RANT - MPJ's Musings - FunFunFunction #47|https://www.youtube.com/watch?v=0ZNIQOO2sfA]]
https://en.wikipedia.org/wiki/Separation_process
[[Reverse osmosis]]
[[Forward osmosis]]
[[Piezodialysis]]
[[Ultrafiltration]]
[[Pervaporation]]
[[Distillation]]
[[Chromatography]]
[[Filtration]]
[[Salting out]]
See much more in wiki article
An element of a [[Sequence space]], also known as a [[string|String (Computer science)]]
[[Classification]] of [[Sequence]]s.
__Methods__
* [[Conditional random field]]s
* [[Recurrent neural network]]
See also [[Sequence prediction]]
//and prediction of time-dependent data//
See [[Machine learning]] (in particular [[Generative learning]]), [[Universal inductive inference]], [[Sequence space]], [[Automatic sequence]].
A sequence space refers to the [[Set]] of all [[sequences of symbols|String (Computer science)]], of a given length, where the symbols belong to an alphabet (another [[Set]]), which may be endowed with some more structure.
More precisely, a sequence is the set of all functions from an index set $$I$$ to the alphabet set $$A$$. This is the same as the set $$\times_{i \in I} A_i $$, where $$\times$$ denotes [[Cartesian product]]. The sequence space can be notated $$A^I$$.
Two common examples of infinite sequence spaces are $$A^{\mathbb{N}}$$, where the index set is the naturals, and $$A^{\mathbb{Z}}$$, where the index set are the integers. Members of this latter example are also called //bi-infinite// sequences.
See [[this video|https://www.youtube.com/watch?v=dUofthrSolQ]]
!!!__Topology__
As the sequence set is constructed as a Cartesian product, we can endow it with the [[Product topology]]. The alphabet set, if finite can be endowed with the [[Discrete topology]]
Under this topology one can show that a set $$F$$ is closed iff there is a tree $$T$$ (a set of finite sequences, or strings) such that $$F=T^\infty$$, where $$T^\infty$$ is the set of all //paths through $$T$$//. See [[here|https://www.youtube.com/watch?v=pxXdgoclgpk]] for details and proof.
!!!__[[Measure]] on sequence spaces__
[[Math 574, Lesson 1-5: Measures on Sequence Spaces|https://www.youtube.com/watch?v=7Sd3mHXv31I]]
As the [[Cylinder set]]s generate the [[Product topology]], which in turn generates a [[Borel sigma-algebra]] on our space, then if we find the [[algebra|Algebra (algebraic structure)]] generated by the cylinder sets, this algebra will generate the Borel-sigma algebra, and by the [[Caratheodory extension theorem]], by defining a [[Measure]] on the sets of this algebra, we define a unique measure on the Borel sigma-algebra.
In fact he shows that the set of finite unions of open cylinders (generated by the cylinder sets) themselves already form an algebra. This is because a finite intersection of open cylinders can be expressed as a finite union of another set of of open cylinders.
Then, it turns out that <b style="color:#aea;">we can define a unique measure on this algebra if we define the measure on the open sets only, and thus we can define a unique measure on the Borel $$\sigma$$-algebra of the sequence space</b>. These sets are of the form $$[\sigma]$$, where this is the set of all sequences that begin with string $$\sigma$$ (these are called the basic open cylinder given by $$\sigma$$).
This measure is simply constructed by using the [[Measure]] additivity axiom of countable unions of disjoint (non-overlapping) sets (here applied of finite unions, as it is an algebra), and use some [[properties of open cylinders under intersections|https://www.youtube.com/watch?v=7Sd3mHXv31I#t=7m46s]], which convert other arbitrary unions of open cylinders to unions of disjoint sets. This is proved from the property in the [[following lemma|https://www.youtube.com/watch?v=7Sd3mHXv31I#t=9m50s]] as well as [[the next lemma|https://www.youtube.com/watch?v=7Sd3mHXv31I#t=14m30s]]. This latter lemma uses $$\mu([\sigma]) = \mu([\sigma0])+\mu([\sigma1])$$, which of course follows from the additivity property of measures.
You also require some normalization condition, like $$\mu([\epsilon]) = 1$$ where $$\epsilon$$ is the empty string, and thus $$[\epsilon]$$ is the set of all sequences that begin with the empty string, i.e. the full set.
-----------------
See also [[Symbolic dynamics]], [[Shift space]], [[Entropy reduction]]. See book on permutation entropy.
[[Sequential Dynamical Systems - Christian Reidys (TOM conference)|https://www.youtube.com/watch?v=WOgY3StiXe8]] (half way through). [[cool stuff on periodic points|https://www.youtube.com/watch?v=WOgY3StiXe8#t=34m]]
https://www.wikiwand.com/en/Sequential_dynamical_system
A collection of objects/entities/things.
[[Cartesian product]]
https://www.wikiwand.com/en/Sewing
[[Sewing machine]]
[img[https://media.giphy.com/media/LFhEDWqQitYEE/giphy.gif]]
//aka sex-linked inheritance//
A mode of inheritance where the [[Gene]] is in a sex chromosome (X or Y)
[[Sex chromosomes and sex linkage|https://www.youtube.com/watch?v=MnwLwyrA-_M]]
[[Wiki|https://www.wikiwand.com/en/Sex_linkage]]
!!!__[[X-linked inheritance|https://www.youtube.com/watch?v=dVr_DRd4ovE#t=5m45s]]__
__X-linked recessive__
* Predominantly affect males
* Affected males dont't tr ansmit to their sons
* Carrier female has half of her sons affected
* Affected female, has 100% of sons affected
Argument from Shannon code before proof of coding theorem in Info theorem book.
constanc c is the description of the program to compute the probability distribution. You input that program, plus the description in the Shannon-Fano code to the Turing machine and it should be able to give you the string you want, so this constitutes a description of the string, and thus its length is an upper bound on the Kolmogorov complexity.
If c is sufficiently small, i.e. the map is simple enough, the bound on the Kolmogorov omplexity will be more stringent, and thus the coding theorem approaches an equality more.
This argument, however, only explains why if there is bias, in a simple map, one expects the bias to correlate with Kolmogorov complexity. But it doesn't explain why there should be bias in the first place.
My arguments using transducers try to explain both, but it'd be nice to see how these two arguments fit
[img[https://scontent.fmad3-1.fna.fbcdn.net/t31.0-8/14053814_10154028246086339_8780500265944094718_o.jpg]]
//aka Sherington-Kirkpatrick model//
Introduced in [[Solvable Model of a Spin-Glass|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.35.1792]], it is an infinite-range version of the [[EA Hamiltonian|Edwards-Anderson Hamiltonian]], and corresponds to a [[Mean field theory]]. Note that the interactions are now between all pairs. The Hamiltonian is:
|$$\mathcal{H}_\mathcal{J}=-\frac{1}{\sqrt{N}} \sum\limits_{1 \leq i \leq j \leq N} J_{ij} \sigma_i \sigma_j - h \sum\limits_{1 \leq i \leq N} \sigma_i$$|
for a system of $$N$$ spins.
[img[Selection_619.png]]
[[silent video|https://www.youtube.com/watch?v=fZ8WCic5u2I&index=2&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5#t=28m45s]]
[[The Sherrington-Kirkpatrick model and its diluted version I - Dmitry Panchenko - Dmitry Panchenko|https://www.youtube.com/watch?v=1xZ6AAew3Y4]]
!!!__Solution via the [[Replica method]]__
!!!__Phase transition__
A [[Phase transition]] was found:
[img[Selection_620.png]]
__Negative entropy__
if one chooses the [[EA order parameter|Edwards-Anderson Hamiltonian]] to describe the broken symmetry of the low-temperature spin glass phase, the entropy becomes negative at very low temperature. This is problematic and is solved by the introduction of different order parameters, which cause [[Replica symmetry breaking]].
!!!__[[Replica symmetry breaking]]__
An activity carried out by [[Human]]s (and other [[Living being]]s) which consists on pouring [[Water]] (often with useful additives like [[Soap]]/[[Detergent]]s) over their own [[Body]]
---------------------
[img[https://az616578.vo.msecnd.net/files/2016/11/07/636140741286313595-713521260_corgi-real-estate-agent-03.gif]]
Given a set $$\Omega$$, a ''$$\sigma$$-algebra'' on $$\Omega$$, $$\mathcal{A}$$ is a subset of the [[Power set]] of $$\Omega$$ ($$\mathcal{A} \subset 2^\Omega$$), s.t.
# $$A$$ is non-empty.
# $$A$$ is closed under complements. $$E \in \mathcal{A} \Rightarrow E^c \in \mathcal{A}$$
# $$A$$ is closed under countable unions. $$E_1, E_2, ... \in \mathcal{A} \Rightarrow \bigcup\limits_{i=1}^{\infty} E_i \in \mathcal{A}$$
[[(PP 1.2) Measure theory: Sigma-algebras|https://www.youtube.com/watch?v=21a85f1YS5Q&index=2&list=PL17567A1A3F5DB5E4]]
From these axioms, one can show that a sigma-algebra is closed under countable intersections too.
The sigma-algebra generated by $$C \in 2^\Omega$$, written as $$\sigma(C)$$, is the "smallest" sigma-algebra containing $$C$$. See [[here|https://www.youtube.com/watch?v=xlfH6Rk2GCM&index=3&list=PL17567A1A3F5DB5E4]] to see precise definition and why this always exits.
A common example is the [[Borel sigma-algebra]].
A sigma-algebra can be generated by an [[algebra|Algebra (algebraic structure)]], as explained in the [[Caratheodory extension theorem]]
https://en.wikipedia.org/wiki/Signal_processing
[[Power spectral density]]
[[Filter (signal processing)]]
[[Sampling theory]]
[[Convolution]], [[Cross-correlation]], [[Laplace transform]], [[Fourier transform]]
The current standard for end-to-end encryption
http://security.stackexchange.com/questions/121304/how-does-the-signal-protocol-used-by-whataapp-work
See [[Neuronal network]]
!!!__Cross-correlation__
A quantity that is proportional to the synaptic transmission curve, and which can be readily experimentally and computationally determined.
See definition of cross-correlation [[here|http://journal.frontiersin.org/article/10.3389/fnins.2011.00068/full]]
The cross-correlation between spontaneously active nerve cells will be
affected by the structure of the presynaptic spike train. Mathematically,
the only case for which the cross-correlation will be identical with the
synaptic transmission curve is that in which the firing times of the input
axon (a,) are not correlated to the firing times of all the other inputs that
affect a 2 and when the firing times of the input obey the statistics of a
uniform Poisson process (i.e., the probability of finding a spike is inde-
pendent of the time and of the past history of the axon). <mark>However, doesn't this depend on the output being a linear function of the input?</mark> Well no if we assume that the probability of two spikes being very close together (remember they are very thin in time) is very small, so we can ignore the non-linear effects of two synchronous spikes. (<mark>Linear regime</mark>)
,,If the input spike train is non-Poissonian, but behaves as a
renewal process (i.e., the possibility of finding a spike depends only on
the time elapsed since the last spike [Cox, 1962]), then the true synaptic
transmission curve can be obtained by deconvolving the apparent re-
sponse curve from the autocorrelation curve of the input train [Perkel et
al., 1967].,,
It is possible to evaluate the amount of correlation introduced
by the stimulus itself by computing the so-called ''shift-predictor correlogram'' [Perkel et al., 1967; Dickson and Gerstein, 1974]. "joint
poststimulus time histogram" (JPSTH). __How does this work?__ => [ext[paper|http://www.cnbc.cmu.edu/~samondjm/papers/Aertsenetal1989.pdf]] -- [[Crosscorrelogram|http://mulab.physiol.upenn.edu/crosscorrelation.html]] ),,(very clear explanation),,. crosscorrelograms give some measure of the firing rate or firing probability of the target neuron around the time that the reference neuron fires.
[img width=350 [http://mulab.physiol.upenn.edu/XC_Construct2.gif]] [img width=350 [http://mulab.physiol.upenn.edu/XC_Samples2.gif]]
Stimulating the cells simultaneously creates a peak in the cross-correlation. This covariation in firing rates of the two stimulated cells must be removed before considering the peak to be relevant (coming from a synaptic connectivity between them or common input). The easiest way to "correct" for this stimulus-induced relationship is to use the shift predictor. See further explanation [[here|http://mulab.physiol.upenn.edu/crosscorrelation.html]]
!!!__Transmission of firing rate signals through neuronal circuits__
:Transmission through a chain of synapses.
:The effect of a single cell on a population of cells.
:The effect of a population of cells on one cell
|We note that when we have a chain of synapses in tandem (Section 3.3.2), the overall gain is dependent on the product of the individual gains, whereas when we have parallel synapses, the overall gain depends on the sum of all the gains.|
Transmission of a spike train through a [[Synapse]], computed using [[Convolution]].
Within the linear regime (achieved when the instantaneous firing rate is low enough), one can apply many tools from linear [[Signal processing]] and analysis ([[Linear response theory]]..) to analyze the input-output relations of complicated neuronal circuits.
!!__Neuronal chains__
For successful transmission of [[Information]], we need converging/diverging chains of connected neurons (aka braids).
To summarize, we have seen that in the cortex, activity can be trans-
mitted only between sets of cells with multiple diverging/converging
connections. We have shown that such connectivity exists and have de-
scribed some of the constraints on the size of the sets and the multiplicity
of the connections among them. We have suggested that a chain of such
connections can operate repeatedly if the activity along such a chain of
connections is transmitted by synchronous volleys of spikes ([[Synfire chain]])
Again, In Section 6.3 we saw that transmission through a diverging/converging
chain is not stable. It either decays to zero or amplifies itself until it
reaches saturation. Our contention, therefore, was that transmission
through such a chain was most likely to occur by synchronous volleys.
This form of transmission is examined in detail in Chapter 7.
!!__Synchronous transmission__
!!!__''Synchronous gain''__
Definition 7.1.1: Synchronous gain 50 (''SG50''). The ratio between the
amplitude (A) of an EPSP (see [[here|Membrane potential and the synaptic response curve]]) and the distance from threshold to the median membrane potential is called the "synchronous gain 50" (SG50).
If the membrane potential fluctuates along a symmetric probability
density function (e.g., Gaussian p.d.f.), the median is equal to the aver-
age, and we have
$$SG50 = A/T$$
where A is the amplitude of the EPSP, and T is the distance from
threshold to the average membrane potential.
We use the median because if the amplitude of the EPSP is equal to distance of the threshold above the median membrane potential, there's a 50% that the membrane potential + EPSP will be above threshold, creating a spike.
|Note that for synchronous spikes, their EPSP amplitudes add linearly, but the resulting firing rates add non-linearly. |
|For asynchronous spikes, their post-synaptic firing rates add linearly|
In general, if the SG50 of a synapse is x, it takes 1/x such synapses to
produce a synchronous response with a probability of 0.5. There's reasons to believe that most neural chains are synfire chains in the cortex, so that they work mostly by seizing synchronous effects.
A [[Network]] that has //signed edges//, that is its edges can have an associated weight $$+1$$ (like friendship) or $$=1$$ (like animosity).
These networks can experience [[Structural balance]], and [[Frustration]]
See [[Measures and metrics for networks]]
How can we measure the "similarity" of two nodes (or edges, etc.)? Two main approaches. Two nodes may be:
* ''structurally equivalent'': if they share many of the same network neighbours.
* ''regularly equivalent'': have neighbours who are themselves similar.
[img[similarity_in_networks.PNG]]
Mathematical implementations of these ideas:
//Structural equivalence//:
*[[Cosine similarity|Cosine similarity (Network theory)]]
* [[Pearson coefficients]]
* Other variants, including //Euclidean distance// (essentially the same as the Hamming distance in computer science).
//Regular equivalence//:
* $$\mathbf{\sigma}=\alpha \mathbf{A} \mathbf{\sigma} \mathbf{A}$$ ($$+\mathbf{I}$$). Same as weighted sum over even paths that connect i and j
[img[regular_equivalence.png]]
* "Katz similarity". $$\mathbf{\sigma}=\alpha \mathbf{A} \mathbf{\sigma}+\mathbf{I}$$. Weighted sum over all paths between i and j. Katz centrality of i is sum over the Katz similarity of i and all other nodes.
[img[katz_similarity.png]] Fig Katz Sim
* Other variants:
** Variant of Katz similarity that divides by the degree of node $$k_i$$ in Fig Katz Sim. This is similar to the relation between PageRank and Katz centrality
** The last term, instead of being just $$+\mathbf{I}$$, it is a general matrix, so we include prior similarities. Related to areas of machine learning and info retrieval that try to find similarities between things given some initial similarity data and some network or other data.
Another kind is ''automorphic equivalence'' See page 23 in [[here|http://www.analytictech.com/mb874/Slides/equivalence.pdf]], as well as discussion of automorphism in [[Graph theory]].
A ''Similarity network'' is one that expressed how similar entities (expressed as the nodes) are. The degree of similarity being the weight of the node.
The weight matrix $$A_{ij}$$ represents level of similarity between entities $$i$$ and $$j$$ in the network. A similarity network is almost always complete (the only deviation from completeness is from nodes that can't be compared for some reason).
For example, if we have a matrix of votes, we can define $$A$$ as:
$$A=\frac{\text{times i and j voted same ways}}{\text{total number of times both i and j voted on same measure}}$$
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
A ''simple contagion'', is a property that spreads between individuals in such a way that an individual can get infected by simple exposure to another infected individual (possibly with a certain probability or rate). These are mostly compartmental models, and their extensions are used to model mostly biological contagions (like infectious diseases), as well as some IT contagions (like computer viruses). Often the model lives on a [[network|Network science]] that determines which individuals (nodes) interact (edges).
Compartmental models are those in which the individuals can be on any of a number of states (often "susceptible", "infected", or "recovered"), and there are certain rules for the contagion.
!!__SI model__
a.k.a susceptible-infected model. Just two states, "susceptible" and "infected". Susceptible individuals can get infected by infected individuals.
__Fully mixed SI model__
Assumes every individual has an equal probability (per unit time, i.e. rate) of meeting any other individual. A description is then made using a pair of [[Rate equation]]s:
$$\frac{d X}{dt} = \beta \frac{S X}{n}$$ or $$\frac{dx}{dt}= \beta s x$$
where $$S$$ and $$X$$ are the average number of susceptible and infected individuals, respectively, in a population of $$n$$ individuals, and $$s=S/n$$ and $$x=X/n$$. Furthermore, $$I+S=n$$ is unchanged in time, so $$s=1-x$$, and the above equation is equivalent to:
$$\frac{dx}{dt}= \beta (1-x) x$$
which is the //logistic growth equation//.
!!__SIR model__
a.k.a susceptible-infected-recovered model or susceptible-infected-removed model. Adds the possibility of recovery (and subsequent immunity). Three states: "susceptible", "infected", and "recovered". Susceptible individuals can get infected by infected individuals. Individuals can recover after some time, and then become immune to new infections.
The model can also be applied to when the third state corresponds to a dead individual, as in this case the individual also doesn't participate in the network of possible infectious transmissions (though there are some subtleties in some cases, see note in page 632 on Newman's book). For this reason the R sometimes refer to "removed", encompassing both cases.
!!__SIS model__
!!__SIRS model__
The opposite of [[Complexity]]. It can be seen as synonymous with [[Order]], or structure.
See [[Simplicity bias]] for ideas about the origin of simplicity in [[Nature]], <big>[[Order]]</big>. [[Occam's razor]] assumes the prevalence of simplicity in Nature.
See [[Learning theory]] for some notions of simplicity, that are seized to facilitate the learning process.
See [[Learning theory]], [[Order]] and [[Simplicity bias]]. The simplicity and structure in signals in the real-world is often seized to make the learning problem easier to solve.
Applications in [[Inverse problem]]s. For instance, see [[Convex optimization heuristics for linear inverse problems]] and [[Linear inverse problem]]
Applications in [[Compressed sensing]]
!!!__Simplicity and neural networks__
See [[Neural network theory]], [[Why does deep and cheap learning work so well?|http://arxiv.org/abs/1608.08225]], [[Deep learning theory]]
<b>Nature often results in functions that are polynomials with several simplifying features</b>:
//1. Low polynomial order //
For reasons that are still not fully understood, our uni-verse can be accurately described by polynomial [[Hamiltonian]]s of low order $$d$$.
The [[Central limit theorem]] gives rise to [[Probability distributions]] corresponding to quadratic Hamiltonians (see def in [[Neural network theory]]). Similar results regarding maximum entropy distributions are also mentioned in the paper. Several common operations on image and sound are linear and thus order 1 polynomials on the input.
//2. Locality//
locality in a lattice manifests itself by allowing only nearest-neighbor interaction. In other words, almost all coeficients in the polynomial are forced to vanish, and the total number of non-zero coeficients grows only linearly with $$n$$.
This can be stated more generally and precisely using the Markov network formalism
//3. Symmetry//
Whenever the Hamiltonian obeys some symmetry (is in-variant under some transformation), the number of independent parameters required to describe it is further reduced.
-------------
[[deep learning|https://www.youtube.com/watch?v=oOB4evKlEmQ#t=35m]]
Simplicity bias (also called Algorithmic randomness deficit) is a bias observed in many [[GP maps|Genotype-phenotype map]] (see [[Bias in GP maps]]), and in many [[Complex systems]] (which can often be seen as GP maps). Simplicity is defined as low [[complexity|Complexity theory]].
[[Simplicity bias in discrete systems]]
[[Simplicity bias in finite-state transducers]]
[[Simplicity bias in continuous systems]]
See [[MMathPhys oral presentation]], [[Simplicity]], [[Order]]
!!!__Origin of the bias__
A map that shows simplicity bias seems to need to be simple itself (having short description / low [[Kolmogorov complexity]]).
[[A priori probability estimates from structural complexity]]
[[Universal probability]]
[[Origin of bias in GP maps]]
[[Sloppy model]]s ([[Why is science possible?|http://www.lassp.cornell.edu/sethna/Sloppy/WhyIsSciencePossible.html]])
!!!__Types of bias__
* Algorithmic [[Randomness deficit]] of the set of outputs (p-sampled) (ARD1).
* Algorithmic [[Randomness deficit]] over the g-sampled distribution of outputs (ARD2).
!!!__Other features of simple maps__
* Low probability -- low complexity outputs have inputs which are simple. This is because a description of the inputs can be constructed from a description of the output, plus an index, which is at most $$\log{A}$$, where $$A$$ is the size of the input set producing that output. If the output has low probability, $$A$$ is small, and so this term is small. If the output is simple, then its description is small. Both these terms are small, and therefore, the input set must be composed of simple strings.
!!!__Effects of simplicity bias__
Effectiveness of [[Learning]]: [[Simplicity and learning]]
Effectiveness of [[Evolution]] (see [[Biological complexity]])
See Xmorphia system in [[Pattern formation]]
[[Simplicity bias]]
[[Discrete dynamical systems]]
!!__[[Simplicity bias in finite state transducers]]__
!!__Simplicity bias in Boolean networks?__
See [[Activities and Sensitivities in Boolean Network Models]]
__Simplicity bias in Boolean threshold networks__
!!__Simplicity bias in other discrete systems__
Discretized differential equations
An example of [[Simplicity bias in discrete systems]]
See [[Random automata]] and [[Evolving automata]]
[[Numerical experiments on the simplicity bias in finite-state transducers]]
On the theory/analysis side, I've been thinking about two questions:
* Understanding the simplicity bias graph, for a particular FST, given its structure.
* Understanding the statistical/average properties of random FSTs.
[[Ideas for understanding the simplicity bias in finite state transducers]]
To have sufficiently high bias, we need a small non-coding loop.
To have varied output, we need loops outside the non-coding regions. This is so that the time spent in non-coding regions can vary for different outputs.
The slope of the designability/complexity plot corresponds approximately to the [[Topological entropy]] of non-coding region. <span>Computed using [[Determinant of a graph]]</span>. <span style="color:coral;">However</span>, there's also a factor due to the conversion between {KC complexity} and {number of bits spent in non-coding region}. For first FST below, for instance, by computing KC for strings like $$10000000000000000...$$ and $$10011110110000000...$$, I found that $$KC \propto 2.7 m$$. Then from topological entropy, which is $$\frac{\log_2{3}}{2}$$, we find $$a \approx (\log_2{3}/2)/2.7 \approx 0.29$$, which is consistent with what I found from the graph, approximately $$(\log_2{100})/23 \approx 0.29$$.
$$LZ < \frac{n-m}{\log_2{(n-m)}} + c$$
$$KC \approx LZ\log_2{n}< \frac{n-m}{\log_2{(n-m)}}\log_2{n} + c'$$
$$P \approx 2^{am+b}$$
$$\log_2{P} \approx am+b$$
$$m \approx \frac{\log_2{P} -b}{a}$$
$$KC < \frac{n-\frac{\log_2{P} -b}{a}}{\log_2{(n-\frac{\log_2{P} -b}{a})}}\log_2{n} + c'$$
Now, this $$P$$ refers to the frequency, which is between $$10^{12} \times 10^{-5} \approx 10^7$$ and $$10^{12} \times 10^{-3} \approx 10^9$$ ($$2^{40} \approx 10^{12}$$)
$$\log_2(40)/\log_2(40-\log_2(10^n)/0.79)$$
If we average this quantity for $$n=7,8,9$$, we get $$(4.8+2+1.55)/3 \approx 2.8$$, which is close to the $$2.7$$ found from estimates above.
See [[this paper|http://arxiv.org/pdf/1311.0822v1.pdf]] about maximum LZ complexity, which goes like $$l/\log{l}$$ where $$l$$ is length of string.
See [[here|https://www.desmos.com/calculator/2wdnnubk30]] for desmos graph.
-------------------------
[[Examples of finite-state transducers and their simplicity bias]]
------------------
See related stuff in [[Descriptional complexity]]
[[Finite state channel]]
[[Information theory]] -- [[Coding theory]] -- [[Algorithmic information theory]]
[[Ergodic theory]] -- [[Topological dynamics]] -- [[Topological entropy]]
[[More resources in simplicity bias in FSTs]]
An image or representation of someone or something.
[img[http://2.bp.blogspot.com/-KNVK9ecI6dQ/VpVTODD0K9I/AAAAAAAAO7I/qbLwL4Ys04s/s1600/pipemMCcloud.png]]
Simulacra and simulation - Jean Baudrillard
[[Voice]] that represents a form of [[artistic|Art]] expression.
See [[Active matter]] for background.
* bacteria <span style="color:LightSalmon">enhance diffusion</span> as a result of the flow fields they produce
The __path taken by a tracer__ will depend on the detailed <span style='font-family: "Comic Sans MS"'>spatial and temporal correlations</span> of the velocity. Numerical simulations were conducted in [[Fluid transport by individual microswimmers|https://pure.york.ac.uk/portal/en/publications/fluid-transport-by-individual-microswimmers(a7cd0163-9d1b-47d7-b37a-d61a257d1ffc)/export.html]]. The striking feature of the tracer trajectories is their
<svg width="100" height="50">
<defs>
<path id="textPath" d="M10 50 C10 0 90 0 90 50"/>
</defs>
<text fill="cyan">
<textPath xlink:href="#textPath">loop-like character
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</svg>, a consequence of the angular dependence of the flow field. Mathematically, it is because all terms in the multipole expansion, except the Stokelet are exact derivatives. The way this works:
:Consider a tracer whose <small>velocity</small> (in LAB frame) is much smaller than the swimmer's <big>velocity</big>. Then, in the <span style="color:DarkKhaki ">rest frame of the swimmer</span>, the tracer follows a path which is approximately straight, and parallel to the swimmer's motion (in Lab frame). It's velocity deviating from the straight-line motion is given by the <span style="color:DarkOrange ">dipolar field</span>. And so it's <span style="color:Chartreuse ">total displacement</span> in the LAB frame (,,total displacement in swimmer's rest frame, relative to straight line path,,) is given by integrating the <span style="color:DarkOrange ">dipolar field</span> approximately along the straight line from $$-\infty$$ to $$\infty$$. However, because $$\frac{\partial G_{ij}}{\partial x_k} (\vec{r}) D_{jk}$$ is a total derivative ($$D_{jk}$$ is constant), and $$G_{ij}$$ is $$0$$ at $$-\infty$$ and $$\infty$$, the <span style="color:Chartreuse ">total displacement</span> is $$0$$.
:The reason we need the tracer's velocity to be much smaller than the swimmer's velocity, for the above argument is that the total displacement is given by the <span style="color:coral ">integral of the velocity with respect to time</span>, i.e. $$\int \vec{v}(t) dt = \int_C \vec{v}(t) \frac{ds}{|\vec{V}+\vec{v}(t)|} $$, where $$\vec{v}(t)$$ is the dipolar velocity field of the swimmer (,,i.e. velocity field in its rest frame, minus the overall constant, $$\vec{V}$$,,). $$\vec{V}$$ is the swimmer's velocity in the LAB frame. $$\vec{V}+\vec{v}(t)$$ is thus the total velocity field in swimmer's rest frame. $$ds$$ is a distance element along the path $$C$$ that the particle traces. $$|\vec{V}+\vec{v}(t)|$$ is the instantaneous //speed// of the particle along this path, so that $$dt = \frac{ds}{|\vec{V}+\vec{v}(t)|}$$. Now, if $$|\vec{V}| \gg |\vec{v}(t)|$$, $$dt \approx \frac{ds}{|\vec{V}|}$$, so that the integral is approximately a line integral of $$\vec{v}(t)$$ along $$C$$. But, when we take $$\vec{v}(t)$$ into account, when $$\vec{v}(t)$$ is parallel to $$\vec{V}$$, $$|\vec{V}+\vec{v}(t)|$$ is larger, and the contribution in the integral is less; when $$\vec{v}(t)$$ is anti-parallel to $$\vec{V}$$, $$|\vec{V}+\vec{v}(t)|$$ is smaller, and the contribution in the integral is more. This means the particle has a displacement bias towards the direction of motion of the swimmer. This is called ''entrainment''.
:But, <mark>Why do the faraway tracers have a net negative displacement?</mark>
The ''entrainment'' effect is an example of [[Darwin drift|https://en.wikipedia.org/wiki/Darwin_drift]]. The Darwin drift volume has also been calculated for these active swimmers
!!__Contribution to diffusion__
We can estimate the contribution to diffusion from the entrainment effect. We know that the [[Diffusion]] coefficient can be expressed in 3D as:
$$D_{\text{entr}} = \frac{\langle \Delta x^2 \rangle}{6t}$$
The entrainment length (Darwin drift) is of order $$a$$ (the size of the swimmer), when close (within distance $$a$$) to the swimmer. Thus, $$\langle \Delta x^2 \rangle \sim a^2$$, whenever there is a swimmer within a volume $$\sim a^3$$. If there are $$n$$ swimmers per unit volume, the probability that a swimmer is in a given region of volume$$ a^3$$ is approximately $$n a^3$$. Therefore, $$\langle \Delta x^2 \rangle \sim a^5 n$$. Now the characteristic time step $$t \sim V/a$$, is the time scale that the swimmer travelling at speed $$V$$ takes to traverse the distance $$a$$ throughout which the swimmer interacts with the tracer particle. Therefore,
$$D_{\text{entr}} \approx \frac{1}{6}a^4 n V$$
There is also a contribution to diffusion from the random reorientations that real bacteria perform at approximately regular intervals (in their run and tumble behaviour). <mark>Is the contribution to the diffusion constant from random reorientations, or finite run lengths? I think the former, due to the disappearance of $$\lambda$$, the run length from the expression</mark>
$$D_{\text{rr}} = \frac{4\pi}{3}(\frac{\kappa}{V})^3 nV$$
where $$\kappa$$ is a measure of the swimmer's dipole strength.
Because the addition of variances ($$\langle \Delta x^2 \rangle$$) for independent processes, we then have that the total diffusion coefficient is approximately the sum:
$$D = D_{\text{rr}} + D_{\text{entr}} + D_{\text{thermal}}$$
For different kinds of systems, some of these diffusions coefficients will dominate.
!!__Swimmers in Poiseuille flow__
Zottl and Stark paper. <span style="color:#aabb33 ">Swimmer equations of motion</span>, for swimmer in background flow $$\mathbf{v}_f$$:
$$\frac{d}{dt}\mathbf{r} = v_0 \hat{\mathbf{e}}+ \mathbf{v}_f$$
$$ \frac{d}{dt} \hat{\mathbf{e}}= \frac{1}{2}\mathbf{\Omega}_f \times \hat{\mathbf{e}}$$
where \hat{\mathbf{e}} is the swimming direction of the point swimmer. In the case of Poiseuille flow, the equation determining, the angle of the swimmer follows the nonlinear pendulum equation (with $$\sin$$).
When swimming upstream, any deviation for the centre line is subject to a restoring torque from the vorticity and hence the swimmer trajectory oscillates around the centre of the channel. Swimming downstream any perturbation about the centre line is amplified by the vorticity , and the swimmer tumbles in the flow. For sufficiently large velocities, it continues to tumble down-stream, otherwise it reaches the walls and and the simple theory must be supplemented by additional physics.
One can also describe the motion of the swimmer in simple shear flow, and when there is <span style="color:pink ">tendency to swim, on average, in a particular direction, "''-taxis''"</span> For instance,
* towards gravity, ''gravitaxis''
* towards light, ''phototaxis''
* following a chemical gradient, ''chemotaxis''.
One can use these ideas, with shear, and gravitaxis (together often termed //gyrotaxis//), to explain, for instance, the formation of thin layers of phytoplankton in the oceans.
!!__Surfaces__
<span style="color:#aabb33 ">Why micro-organisms often accumulate at surfaces</span>
First note, that a simple self-propelled rod, or sphere, when it eventually hits a surface, will then tend to move parallel to it, and only scape it, when a rotational fluctuation changes its direction enough to swim away from it.
However, there is a less trivial effect, due to <span style="color:CornflowerBlue">hydrodynamic interactions with the wall</span>. These can be taken into account, because Stokes equations are linear, by considering an ''image swimmer'' at a position corresponding to the reflection of the swimmer on the wall, and pointing in the opposite direction (so as to satisfy the boundary condition of __no normal flow at a free boundary__ (one that can slip; <mark>Like what? I mean, say a liquid-gas interface doesn't satisfy either no-slip or no normal flow, no?</mark> http://onlinelibrary.wiley.com/doi/10.1002/cpa.3160190405/abstract
Its no normal stress and no tangential stress.)). The extra terms needed to satisfy the no-slip condition are more complicated, and form the //Blake tensor//. But doesn't the reversed mirror-image Stokelet cancel both the normal and tangential components of the velocity at the boundary?? No, because the Stokelet doesn't have the right symmetry, i think
Like what? I mean, say a liquid-gas interface doesn't satisfy either no-slip or no normal flow, no?
http://onlinelibrary.wiley.com/doi/10.1002/cpa.3160190405/abstract
Its no normal stress and no tangential stress.
However hydrodynamic interactions are not the only contribution. For rotating swimmers, like E. Coli, the effect the wall drag on torque is important; it makes the swimmer move in circles near the wall. See more at [[Physics of microswimmers—single particle motion and collective behavior: a review|http://iopscience.iop.org/article/10.1088/0034-4885/78/5/056601]].
//aka single displacement reaction//
https://www.wikiwand.com/en/Single_displacement_reaction
//aka SNP//
A single-nucleotide polymorphism, often abbreviated to SNP (pronounced snip; plural snips), is a variation in a single nucleotide that occurs at a specific position in the genome, where each variation is present to some appreciable degree within a population (e.g. > 1%)
https://www.wikiwand.com/en/Single-nucleotide_polymorphism
!!__SNP analysis__
SNPs are usually biallelic and thus easily assayed.[38] Analytical methods to discover novel SNPs and detect known SNPs include:
* [[Real-time PCR]]
When limit problem ($$\epsilon =0$$) differs in an important way from the limit $$\epsilon \rightarrow 0$$). For example, a root is lost, or a derivative is lost in a DE.
Problems that are not singular, are called <b> regular</b>
For algebraic equations, often when a root is lost, it's because it goes to $$\infty$$ as $$\epsilon \rightarrow 0$$.
<i class="fa fa-lightbulb-o" aria-hidden="true"></i> It's first term in the expansion may be then $$\frac{1}{\epsilon}$$, for example.
<i class="fa fa-exclamation-triangle" aria-hidden="true"></i> For the iterative method, different functions $$g$$ may be needed to find different perturbed roots of an algebraic equation, so that condition $$g'(x^*; \epsilon) \rightarrow 0$$ as $$\epsilon \rightarrow 0$$ is satisfied.
!!__Regularization method__
Scale variables so that the problem becomes regular.
For instance, if first term in the expansion is $$\frac{1}{\epsilon}$$, rescale $$x =X/\epsilon$$.
Indeed, the problem of finding the correct starting point for an expansion, is equivalent to the problem of finding a suitable scaling to regularize the singular problem.
!!!__Finding the right scaling__
__Systematic approach:general rescaling__
Let $$x=\delta(\epsilon)X$$, with $$X$$ strictly of order $$1$$ as $$\epsilon \rightarrow 0$$
Vary $$\delta$$ from small to large to identify ''dominant balance''s in which at least two terms are of the same order of magnitude as $$\epsilon \rightarrow 0$$, while others are smaller. Scalings that result on dominant balances are called ''distinguished limits''
__Alternative approach: pairwise comparison__
quicker when there are a small number of terms. Try to create dominant balance between terms pairwise, and see if you can get it, consistently. That way you can find the dominant limits.
[[video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=18m45s]]
If $$A \in \mathbb{R}^{m \times n}$$ is any $$m \times n$$ matrix, it can be decomposed as
$$A = U D V^T$$
where $$U$$ is $$m \times n$$, $$D$$ is $$n\times n$$ and $$V$$ is $$n \times n$$, and $$D$$ is diagonal.
The diagonal elements of $$D$$are called the ''singular value''s.
The columns of $$U$$ are the eigenvectors of $$AA^T$$
The columns of $$V$$ are the eigenvectors of $$A^T A$$
In [[Matlab]] it's the ``svd`` command. [[Subtletly with fat matrices|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=31m40s]]
[[Sitting|https://en.wikipedia.org/wiki/Sitting]] is a basic human resting position. The body weight is supported primarily by the buttocks in contact with the ground or a horizontal object such as a chair seat. The torso is more or less upright. Sitting for much of the day may pose significant health risks, and people who sit regularly for prolonged periods have higher mortality rates than those who do not.
[[scikit-learn|http://scikit-learn.org/stable/]]
High-level Machine Learning library in Python
Sleep oscillations
sleep spindle
//Sloppy// is the term used to describe a class of complex models exhibiting large parameter uncertainty when fit to data.
the [[Fisher information matrix]] (FIM) can be used to estimate the uncer- tainty in each parameter in our model.
----------------
[[Sloppy Models|http://www.lassp.cornell.edu/sethna/Sloppy/]] -- [[Why is science possible?|http://www.lassp.cornell.edu/sethna/Sloppy/WhyIsSciencePossible.html]]
[img width=300 [http://www.lassp.cornell.edu/sethna/Sloppy/SloppyFigs/Hierarchies/SpheresWeb.jpg]]
We describe the possible system behaviors as points in a 'behavior' space, and we find that they form a hyper-ribbon, long along stiff combinations and very thin (reflecting unchanging behavior) when sloppy combinations are changed (fig below right).
"Many models in biology, engineering and physics have a __very large number of parameters__. Often many of these are only known approximately. Moreover, in John von Neuman's famous quip \with four parameters I can fit an elephant, and with five I can make him wiggle his trunk." suggests that only __a small set of these parameters are actually relevant__? Could there be a fundamental theory of these [[Complex systems]] that allows us to work out what the key parameters are?"
[[Perspective: Sloppiness and emergent theories in physics, biology, and beyond|http://www.physics.byu.edu/faculty/transtrum/pubPDF/JChemPhys143.010901.pdf]]
[[publication|http://scitation.aip.org/content/aip/journal/jcp/143/1/10.1063/1.4923066]]
[[Parameter Space Compression Underlies Emergent Theories and Predictive Models|http://science.sciencemag.org/content/342/6158/604]]
[[Universally Sloppy Parameter Sensitivities in Systems Biology Models|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.0030189]]
[[Sloppy-model universality class and the Vandermonde matrix|http://www.lassp.cornell.edu/sethna/pubPDF/Vandermonde.pdf]]
!!!<mark>[[James Sethna: Sloppy models and how science works (video)|https://www.youtube.com/watch?v=MEmrcYBVSJA]]</mark>
//Sloppy// is the term used to describe a class of complex models exhibiting large parameter uncertainty when fit to data.
the [[Fisher information matrix]] (FIM) can be used to estimate the uncer- tainty in each parameter in our model.
----------------
[[Sloppy Models|http://www.lassp.cornell.edu/sethna/Sloppy/]]
"Many models in biology, engineering and physics have a __very large number of parameters__. Often many of these are only known approximately. Moreover, in John von Neuman's famous quip \with four parameters I can fit an elephant, and with five I can make him wiggle his trunk." suggests that only __a small set of these parameters are actually relevant__? Could there be a fundamental theory of these [[Complex systems]] that allows us to work out what the key parameters are?"
[[Perspective: Sloppiness and emergent theories in physics, biology, and beyond|http://www.physics.byu.edu/faculty/transtrum/pubPDF/JChemPhys143.010901.pdf]]
[[publication|http://scitation.aip.org/content/aip/journal/jcp/143/1/10.1063/1.4923066]]
[[Parameter Space Compression Underlies Emergent Theories and Predictive Models|http://science.sciencemag.org/content/342/6158/604]]
[[Universally Sloppy Parameter Sensitivities in Systems Biology Models|http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.0030189]]
[[Sloppy-model universality class and the Vandermonde matrix|http://www.lassp.cornell.edu/sethna/pubPDF/Vandermonde.pdf]]
!!!<mark>[[James Sethna: Sloppy models and how science works (video)|https://www.youtube.com/watch?v=MEmrcYBVSJA]]</mark>
A ''Smale horseshoe map'' is any member of a class of [[chaotic maps|Chaos theory]] of the square into itself, of the kind introduced by Stephen Smale in 1967 while studying the behavior of the orbits of the van der Pol oscillator.
[[HORSE SHOES AND HOMOCLINIC TANGLE|http://www.math.harvard.edu/archive/118r_spring_05/handouts/horseshoe.pdf]]
I read about ''homclinic tangles'' when doing the nonlinear systems miniproject on the [[Duffing oscillator]] see Thompson and Stewart. Nonlinear dynamics and chaos and [[here|http://mathworld.wolfram.com/HomoclinicTangle.html]]. Whenever a pair of invariant sets (one outgoing and one incoming) of from some saddle fixed point cross in a Poincare plane (they can cross, as they don't represent trajectories), the points in the outgoing set must go outwards in the outgoing set, but the intersection point must also go inward in the the ingoing set. This causes the outgoing set to cross the ingoing set at ever decreasing steps, and causes a shape like that of the Smale horseshoe. This is hard to explain without pictures..
[[Smale Horseshoe Map|http://mathworld.wolfram.com/SmaleHorseshoeMap.html]]
http://www.scholarpedia.org/article/Smale_horseshoe
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
iVBORw0KGgoAAAANSUhEUgAAAxAAAALYCAIAAABjV4PHAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrs3Xl4VNXdOPBzZ70zmX3JZJLJZDKZ7DshISEJBAggqwhYba2IolVbtVqX1tY+P5+n7/u2bmjVWm1dXnkpKksRKrKELZIEQkIWIAmE7Ps6mWQy+9y5vz9OO01DRIgs4c7384fPzZ0h5p65c+/3fs8530PQNI0AAAAAAAJYR0eH1WpNSEggCKK8vDwmJkYmkxEE4XQ6W1paEhISWNBGAAAAAAhALpfLnzbS6/Vut9tisdA0rVQqeTxee3t7U1OT1+sdHBxECEHABAAAAIBAVFJSMvFHh8NBURRCyGQyBQUFeTwej8dDkmRKSgoETAAAAAAIUD6fb+KPc+fOValUBEHgH6Ojo2madrlccrkcAiYAAAAABKjFixf7wyO/zs7OS5cu4a664eFht9vtdDohYAIAAABAoKMoqrOzEwdJHo/H5XLh/ampqSwWq7q6GiHEgWYCAAAAQIAHTI2NjTqdDiFkNBr9+yUSic1mw9sElBUAAAAAQCDzer0tLS3R0dEEQXR2djqdTpPJ1N7e7vV6TSYTfg9kmAAAAAAQ0AiC4PP5eNvfJefxeLxe77/fAxkmAAAAAAQyj8fzzTffLFy48PIx4A6Ho7GxMTU1FTJMAAAAAAhoLBYrIiICb7vdbpqmceFKr9er0WhGRkYQzJIDAAAAQIBjs9kmkwmnl/r6+trb2xFCuHClUCjMzMyEgAkAAAAAgeXkyZOXj0fq6+trbm6maZrFYrHZbIRQdHS02+12OBxBQUEIBn0DAAAAIKAMDw9fvtPlctntdoQQLi6AjY6OUhTV0tJCEAQM+gYAAABAALHZbEKhcNL4bo/HQ9N0e3u7v28OIeRwOHg8XlNTE4IuOQAAAAAElKCgoMtnw3G5XB6P19zcjH8sLS2laVogELDZ7NjY2NjYWOiSAwAAAEAgoml6dHRUKpX646eYmBi8YbFYEEJjY2NCobCjo4MgCMgwAQAAACAQ+Xy+qqqqiXuMRiMOnhYtWoQQqqurs9vtHo/H7XZDhgkAAAAAAUooFPq3z549q9frccKJJEmEkEAgYLFYsbGxCMYwAQAAACAwsdns7Oxsf3/c+Pi4x+Pp6uq6dOkSnhKXlpZGEMSpU6cgYAIAAAAAQAihzMxMpVKJ15LzeDx4cpzP53M4HAjWkgMAAAAAmMRut58+fbqgoMC/BzJMAAAAAAgsLpdrbGzMnzM6duwY3qYoymw247Xk8Iw5m80GXXIAAAAACERms7mtrc3/I67xjRDyeDznzp1DCPl8vvHxcbzhdDohYAIAAABAwOHxeHiFOGzFihV46DeLxZJKpQghr9fb29uL9+AZc1BWAAAAAACBRalUKpXKy/ez2eywsDAcUeFqAv4MEwz6BgAAAABACCGn01leXj5v3jx/rQGapmmaZrFY0CUHAAAAgMBVU1MzNDSE80csFksulyOEHA5HWVkZQujo0aMsFsvn80HABAAAAIDA5Xa7KYrC22w2OyQkBCFE0zTuicNFmMrLy6FLDgAAAAAAoam65LDi4mLIMAEAAAAAIIQQi8VSKpUUReGhS+Xl5Var1efz5efnQ8AEAAAAAIAQQjweLykpqbq6enR0FCHkcrl8Pl9bW1tbWxsETAAAAAAIRNXV1XhgktfrPXv2rH+QEs4wIYTmzZsnlUopiqIoCgImAAAAAAQiXJoSIeTz+fr7+/37s7Oz5XK5z+fDkZPBYIiOjoaACQAAAACBKDMzE29wOJxZs2YhhCiK6unpwemlzs7O1tZWu91eWVmJYGkUAAAAAAQmtVrtXxFFqVQSBOHxeBobG/GrNE37fD783/Pnz0NZAQAAAAAAhBDyeDzNzc3j4+Mmk0kqlfqLC0BZgYDg8/laWloGBga8Xi+0BgAAAIB1dHTgtBFFUV1dXTRNc7ncuLg4PDnO/x6EUGpqKgRMDNfW1nb48OHXX3/9yJEjuFwpAAAAABBCDQ0NeIOiKH9PHEIoNzdXoVDg9BJ+j0wmg4CJ4axWa2dn55dffllTU+NyuaBBAAAAACw8PBxvsFissLCwiS/515L793ugvZgtKipq8eLFYrEYmgIAAACYKCEhAaeROBxObGwsQRBer7ezsxOX+cZryZlMpq6uLgiYmE8oFCqVSjabDU0BAAAATMnr9VZWVtI07fV6m5ub8d0zNja2o6PD7Xa3tbVBwAQAAACAQOfz+cxmM0KIzWbrdDq80+Fw2O12LpeLe+s40EzAr7e312w2UxR14/4XPB4vMjKSz+dDawMAAJghOBxOTk4OQojL5arV6uHhYaVSGR4eTtM0n8+PjIyEgAn8h8OHDx8+fNhms924/4VYLF68eLFEImF8Y6anp4eEhMyQzlC73d7a2hodHc3j8fAeq9Xa3d1tNBqdTmdvb29kZKTdbh8cHDQYDOfOnSNJsqOjQywWy2Sy7u7u+Pj4hoYGn883f/58gUAA3xQAAMOwWCz/YN+RkRGHw6FUKvGzvd1ub2xsTEtLg4AJ/NvZs2cRQmq1msW6hr5aj8dTVlaWkZEhEom+88379++/dOnSlTNMNptNIBBM+Td4PB673S4UCrlcrn+nw+Hg8XgURdntdpFIxOFw7HY7n8/3er0EQTgcDp/PJxQKPR4Pm812uVxCoRDvvKGNuWDBAr1ez+Fw8LMLm83m8Xi4YiyPx8PDDG02m1Ao9BdG+56u8NvGx8fr6urS0tL8LW+xWJqbm5OSksbGxi5dujRr1qzx8fGurq6EhISysrJZs2ZVVFRkZGS0t7dLpdKqqqqRkZGenp729vaEhISxsbHh4WF8IB6Px+fzcblcl8tFkiRN02NjYwKBgMPhuN1ukiR9Pp/H4+Hz+f5Dxh/upL/W6XS6XC6JRDLx76dpenR0lCRJkiQnxX8kSV7TWXqtcnNzRSLR9fpoZiySJAUCAeMPE4CruZGdPHkyPz+fIAipVCoUChFCbW1tXq9Xo9GMjo4iyDCBSR5++OGEhAR8m7/6+/RLL7307LPP+vt9r6CjoyM1NVUmk33bG2ia/uKLL+bOnSuXyy9/taen58svv5w1a5bRaPT/kdXV1Xq9vqOjo7KycsGCBcHBwWfOnImJiRkcHORyuXv27JFIJFlZWT09PWKxuKmpyWg0lpWVkSR5Q9M/n332md1uxyXRNBqNVCqNiIhwu90Oh8NgMOCAr7S0dNasWdPL2URERIyOjup0On/suGXLloyMjJiYmInRpL9Vo6Ki3G63v3gpi8UyGAwej2d4eLi9vd1kMvH5/PDwcLfbnZiYGBsbK5fL4+PjuVzu7Nmzq6qqsrKyOjs79+3bd+rUqdmzZw8MDOAD6enp8Xg8KpWqqakpOTnZ5XJ98cUXKSkpRqMRp6bsdntnZ2dcXBxObm3dunX16tVisbikpCQzM9MfCRUVFfX29q5bty4oKGhiKLxt27bY2NisrCx/bgwhtHPnzoKCAoVCceNipuLiYoIgrhBJtLS0+Hw+g8FwTV+WK2htbdXr9dd0Tno8ngsXLoSEhCiVyu9sCrvd3tzcHB4ejosX0zTd1taWkZEREhJyNQGTXC4nCGJkZORaF4dgsVh6vd7j8VgsFg6Hw+VypVKp2Wxms9lSqdRisdA0LZfLR0dHfT4f3qAoSqFQWK1Wt9vtdrulUml/f7/BYLDb7Xa7XaVStbW14fVQXS7X2NgYi8UiSdJsNoeFhXV2dhoMhra2Nq1WazabSZIkCMJms8XGxsLcF3AFNE37SxX67z5er9fj8QiFQrzkHARM4D+IRCKJRHL5HfcKOBwOn88Xi8VSqfQ73ywQCPLy8goKCiblDCaetefPn3/00Uf1ev2UObDq6ur169fPnz/fnyw5f/58WFjYoUOHdDrdk08+GRoaeu7cucjISLPZzOVyW1pa1qxZs3jx4r6+PrFY3Nrayufze3t7lyxZEhERceOuocXFxZ2dnXhAmEql6uvrMxgMHR0dLBZraGgIv8dsNvf19X1bU1yZyWRyOBwKhcIfb3k8HpxG/s5fmJKSMjAwkJqaSpJkbW0ti8XasGGDQqGY8p0IofT0dISQ2+1uamrq6+tbuXIlTiCFh4f39/d7PB6FQtHW1hYXFzcyMnLs2LGcnJwVK1YMDw9HR0fb7fbe3t6oqCgc8Rw9evS+++7TaDRpaWmpqan+D7G3t5fNZt9///1KpdL/f7dYLEePHs3MzNy4cePEQKqysnL9+vVGo/HGfXyHDx+2Wq1XCA76+/vLy8ufeuop/CT6/e3bt+9nP/vZNf02h8NRWlqamJi4YMGCiQHllHp6er7++usNGzaEhISwWCyfzzcwMDA0NDQwMDAwMGC1Wg0Gw9DQkM1mi4iIGBgYcLlcarX60qVLSUlJbrfb5/N5vd6amprc3Nzz58/HxsYODAzweLyQkJC2trb6+vqMjIzR0dHo6OjKykqJRKJSqfAnaDQaS0tLLRZLV1fXnDlzmpqatFptc3Mzl8vV6/X+0Kezs9Pr9UZGRnZ1dblcrqioqN7e3vHx8cTExKGhIYIg5HI57jt2Op3t7e1DQ0MpKSkWi6WnpycrK6u1tVUmk7HZ7KGhoejo6IqKiuzs7NLS0jlz5tTX18fExJAkyeFwLl68qFKpvF6vXq+vqKigKGrOnDmVlZXp6em1tbUej2dSo8XExIyMjERGRtpstu7ubovFMvHVOXPm9PT0EAQRFhZWXl6enJx86dIlu90+6Zfg/u6BgQGj0Wi1WimKUiqVly5dmnR2cTictLS0qqqqKZPf+HG0u7v7ygHrnDlzNBoNpAyngcfjLV269Pz58zqdTiqVnjt3zmAwREVFEQRht9svXLgwa9YsCJjATUVRlM1mm3Z3mEgkwpfFiTuTkpIQQgRBpKSkSCQSFouVmpqKEMIjpZRK5R133BEeHm4wGBBCiYmJly5dCgsLy8jImDt37o0bfj5r1qyxsTH/1a2mpgZHFWw2u7m52e12I4Tq6+u1Wu3EUODqnThxQiKRfPzxx/6kEY5mGhoavjPnkZqaOjAwgHvoenp6amtr//KXv1zhVq3RaHJzc2mavnjxYkZGhkKh8Hf2+0u94dCKJEmcdJFIJCEhIfgyNGVCMSsra9Ie3M03cQ+Xy52YSryZCgsLvzPofOGFF1auXDlloDkNW7duXbly5ZSJ1StkmAYGBkQi0Z133vmdecqKior29vb7778f31Bpmp49ezaPxxsaGurq6jKbzfHx8SdPnrRYLMnJyX19fQ6HIzQ0FCGUlpbmcrk6OjqKioqkUmlqaqrT6UxJSenq6iJJMiIigiTJHTt23H333TabLTU1dWRkRC6Xa7Xa7u7u7u7uxMTEiooKgiAUCkVoaOiOHTvwIzubzXY6nfjPxv25Pp8Pb3A4HJfLxePxRCKRwWAYGRmJjY3t6uricDjh4eF1dXVRUVFisdjj8bBYLLlcrtPpenp6YmNjGxsbY2JiKIqKjIwUCARqtRrHczqd7m9/+xtN042NjfPnz6+srFSr1WazOTU1dfv27Y2NjUNDQ0eOHMnNzS0rK8vJybl06RL+WMvKynp6enA3dGdnZ15e3rlz5yIiImw2Gx78V1NTgxAyGAxnz54dGho6evSoVqvl8/kSiaS1tTU1NfXEiRMLFiwoKyszGAx9fX3Nzc1RUVFNTU1SqZSm6f379y9evJjFYo2Ojg4NDYlEotLS0rCwsOrq6jlz5rjd7tra2szMTKfTuWfPHp/Pl5aW1tfXx+Vyw8PDcVRUXFycn59fVlaWlZVVV1eHnx69Xq//6zw2NoavhP6Ny035ktPptNls/mrX/neqVKq1a9fe0A7xW2h8fBxfUa1Wq//SSlHU2NgYZJgCQltbm9vt7uvrGx8fvxG9GCwWKzw8/DsfcLHExMSMjIzp5VTwQ1hERMT3HFyCL7I4V3/jmh3HZ37x8fEsFgt/A71eLw6k+vv7X3zxRRxYXKtjx45FREScPHnS/0RrsVjuvPPOqylSWltbGxoaWlRUhK+JQ0NDo6OjV4hLcA+az+c7evSoUqmsqam5PLqSy+V6vZ7L5apUquklfuRy+aSTk8PhXOuIupvmOnbGTRue7Tw+Pn6V71er1WKxGJ/2BEHgUzQ0NDQhIQEPROvr60MIJScnz5o1y+fzcTiczMxMPp9P03RGRsbx48dxl31KSgqPx8NjBPFnFBYWlp+fr1QqeTxeQkICi8Vis9klJSVmszklJSUpKYmmaYIg+Hz+gQMHli9fnpqaepUfq0AgyMnJ4fP5LpeLpmmSJLOysrhcLs544QPh8/nZ2dkkSc6bN8//hxEEsWTJEi6XO3fuXIqi2tvbPR6PTqdLSUnxeDwfffTR//t//2/evHl79+5dvXq1x+NZtmzZsmXLgoODCwoK6uvr1Wo1/paFhYVxuVyJRBIeHn7PPfdER0cbjcbx8XGHw9HS0oIPzWq1cjickJCQRYsWxcXFkSQpl8sbGxuzsrKUSqVer3c6nQsWLDCbzSqVKikpiaKoBQsWjI+P//3vf8/KyjIYDDgDp9Vq16xZYzQaIyIi5s+f73K5IiMj8/Pz7XZ7bW2tz+dbt25df38/l8uNjIzEn6NMJlu8eHFwcHB+fv4HH3wwNDTk8/n6+/uTk5NxCx8/frygoIDNZn/44YebNm2a8qSd8qXS0tKampqHHnpo4qWyuLjYbDbfeeedTA2Y0tPTcTtkZGQghFpbW41GI5fLxVdpCJiYr6+vb/78+UqlEufVr/uJzuVyV65ceTX9cQihu+66Kzg4+Mp/w+zZs7/tcZkkyeXLl0/ZlabT6bxe7+WdiZf/toGBgcrKymXLll3raIzvme/FEcDEnXPnzlUqldOrw7569WqcK/LvIQhi48aNV5OiOHv2rFqtPnv2rMvlMpvNHR0dCQkJVwh5e3t7v/nmG6fTGRsbW1pa2t7efnn7GwyGnJwcl8t16NChwcFBFouFs3cSiSQsLEwmk2k0misHUsnJyZM+PoqihoeHrynpAqb3HPJte/CzDUEQ+K7p/6//lMZZB7vdThAEns0w6etGEMTE6SA8Hk8gEIhEoquPqvE/958bUw4YwDvxOyedyfjHRx55ZOI14euvv160aFFQUNCGDRsmvnnt2rUIoby8PPxjbGzspP/RokWLLs+Sbtu2raWlZcGCBRMfBSMiIhBC69evvzyfGhMTg79WBoMhKCjo8vFV+NuNEFq5ciVCSCqVFhQU0DSt1Wr9y3Rgd999N76uon91KmVkZJjN5ujoaHyZTU5OzsrKYrFYO3fu3LRp05Rf8ylf8nq9oaGhjzzyyMSAKSUl5de//jWDvwv+PgeSJPH4S6PR6PV6BwcH4+LiIGBivpiYmGeffZamaY1GcyMeCzgcDu6Oucr4/WqCqm8Lv4KDg5csWfJtuSuapi+/HKxdu3bSb+NyuTKZzD9V7RZat27ddVy1Zv369VczURH9q/tMq9UihBwOh9VqvXI5+PHx8fnz51MU1dnZiSOnSW+w2WzffPPN2bNnKYrq6Oiw2+11dXX4ZMOD2+RyeVhYGIfDuXDhwvvvvy8Wi/Py8jo6OrKysvAVKjIykiRJi8Vit9vlcjn+dLhcbmFhoVQqvaZBdTeNVCq9jl8omUw2jd9GkiROqFzN9zQoKOhGnPMajWZ6fzxj2Gy2aTx94Z676/7HKBQKnB7DsrOzp/2rMjIy/PNb/XcThn3Qhw8fXrRoEUEQPp9vdHRUJpPhqb74smM0GhFCbDYbj62EgIn5Jj2RzHAEQVzNbLsp715T7r/8t0ml0qioqJlQPPP6fjTT+20CgeA7h7+IRKK4uDiEUFxc3Pz586eMqPbu3Xv5cFeE0Ojo6LFjx1paWqqrq3Fy4ujRowRBWK3W3bt3+yfKeb1eFotVXFyMEMJdDPi6LJFIdDqdPzE+c05UFou1du3aaXcuTxnvTuO3xcfHezyeq+kcDA0NnTdv3pXbUCaTXSEBbDAYpvwLlUplenr65b9ZIpFotdpACKQKCgoqKiqu9V+53e6r706dIaqqqm5oZeObDw8nxZegmpqagoICPHQMf1nwRZWiqJGREQiYQCDyer1nzpzJzc2d2J8FrgabzZ4yuhIIBJs2bZryn4yNjWVnZ7tcrkn7fT5fW1vb6OgoLnDiV1dXV11dPbEgU2ZmZm9vb15env9u3dLScsuv2iwWa9myZdfxFy5fvnwa/yo6Ovoq36nRaDQazXf+NpwInPLVFStWTBoC7DepHgQWEREhlUpv+UivKeXl5V3HP0wmk2VkZFzr0D0Oh5ORkaFSqa4m7RcREYHHgV3hPbGxsVdZJGLaJlVKYwD/944gCJzv91ewPH78+Pz58wmCYLPZOHkPARMIOHa7XafT6XS6mXkpZxiJRDLljDOapuPi4vzzUPzOnDlTV1c3cYJ3UFDQuXPnGhsb/bmKCxcufPTRR2q1euK1e/Xq1RNnA9yEcf3MExwcfIVXk5OTv+2lWbNmXb5TqVROLBIxo9x3333XMWEpk8lWr159rQGTSqV6+OGHr7KfFD/dXTldl5ubO6kHbaL169d/2z+f8qXU1NTLu/iNRiNTU4a45hxCiMfj4fPZnzL3+Xx4AQy4YYCAExYW9uyzz8bHx0PAdAsRBDFldiQ6Otrn800aEWI0GgcHB/07t23bVlJSwuVyJ94bLl68OHEE27x583Q6Hb64S6XSKet5goB1fXvDuVwuHhF4rSYONvrOmOw733Pl8HTjxo3fFtJN+dKcOXPw93TizpqaGoZ1yU3S1tamUqlwFDt//vympiZ8RcKPcHDDAAEnJCRkejP5wU0wZRSLpxpNvD8pFIpJ68Ds2rULLzaObd261V++QavVFhQU4FFrKSkpsbGxECuDQHOFB4YpX5oyupLJZMzO2g4MDIjFYty/TBBET08Pnm+Irx5w1QAA3GZWr14tl8snZZhiY2MnduQdPny4q6uLoiiKooqKilpbW3G2KTo62l+WQiAQLF++HA+NEgqFlxeCAtedRCK5ypptYAbS6/XM/o5ERkb6R+PxeDxcAIKmaTwKEwImAMBtZsrBy5GRkRN/jIqKwukliqJSU1P9wxFqa2uPHDmCx05xOJyzZ8/ibJPBYJgzZw6+l0dFRQUHB8PSYzfCwoULtVotjC27TeHSIUw6Ip/P19DQkJCQgM9JtVqNl2iMi4vjcDi4pzUoKAiX5oKACQDAQP5wh8Ph3H///f79TU1NHR0d+KJvt9v37t2Lp3ZXVlYeO3YMx1g5OTk///nPv21GGPg+8MgYcJti3pfC5/N1d3cnJCT491AU1dvbiwupYEeOHMEzVyBgAgAEEJPJZDKZ8LbX601NTcXBU0tLS2lpKS7K0tjY+OabbwoEAoIgVq1ahecY4/n2EEKBQJaens6wzCuLxZo0/ZPL5SYmJiKEHA5HVVVVbm4u7o8rKyuDgAkAEKA4HI5/yb+oqKjFixfj7ZKSkjfeeMNsNtM0feHCBTwkdu3atXiWdXZ29kwoEw/AzXfu3DmGdcmxWCzc71ZbW5uSkoJLfg8PDwcHB9M0jZ+gVqxYgRDyeDwQMAEAwH/Iy8vjcrl2u52m6V27dlmtVpqm3377bXyrWL9+PZ6gd9ddd+EyniwWC+InEAh6e3tv5hKcN1NPTw9eM4qiqL6+vvj4eKFQaDAYLl26ZDKZaJqeP38+BEwAADCZf6hNTEwMHiH+xRdf4NFOu3fv9vfc8Xg8Fou1Zs0a3H+n1+thqDhgMI1Gw9RnA/86p1wuNykpCW/jabY2m+3s2bNz586FgAkAAL6Vfy3CX/7yl3jjiy++sNvtPp9v586dTqeTIIiLFy+y2Wwul4sjp7S0tOu7Li8AM8TE+rEM4y/Ox2az/SXv8XjH8fFxnF2GgAkAAK7BPffcgxCiaRovfOv1enfu3OlwOJxO51tvveXz+QoLC4ODgwmCWLJkCV4pDI8Wh247cLtTKpUMPo3xGgMsFquzs9PhcOAa3xwORyQS5efne71eCJgAAOCaEQQxd+5cfJGNj4+nKMrj8ezYscPhcJw6dWp0dJSm6bNnz+LFSpcuXWowGKC2E7jdjYyMMDXDhBDq7u4eHx+Pi4vDPXFOp7OqqiovL6+rq0un05WXl0PABAAA08disUJDQ/E27rY7ePDgwMAATdP79+8/f/78xYsXKysr09PTc3JypFJpZmYmlLoGtykGR0sTDxBXwXU4HPjHuro6nU5H0zQETAAAcD0tXboUb6Smpo6Pj586derixYuNjY2nTp0KCgpasmQJn8+XSCRLlizh8Xh4eXnorQO3y+MBg8/VSUsyCwSC/Px8hFBoaKjX683OzoaACQAAbojU1FSEUFJSkt1ub2pqKi0tHR0d3b17t8fjGRkZqaio4PP5q1evFovFoaGhYrEYwiYww7ndbiYlmQYHB4OCgvAUV4SQ1Wr1eDxyuXx8fNzr9cpkMqvV6vP5kpOTm5qaCIKAgAkAAG4gqVQqlUq1Wm1+fv7Y2NihQ4ecTueePXtqa2sRQpcuXWKz2fn5+cnJyVlZWVdYUh6AW06tVjMprO/q6goNDcXV1BBCIyMjVqtVLpcPDw87HA6ZTDY0NIQjJ3zUEDABAMBNIpFI1q9fjxBKSkpyOBwIoZ07d545c+bDDz+MiIhYsGABj8dbu3YtSZIkSbLZbMg5gRllaGiISRkmpVLpj5YQQiKRCC/FLRaL+Xw+QkggEPh8PoSQXq+HgAkAAG6BtLQ0vBEdHX3u3LmKiorh4eE9e/Z4PB5cD3P+/PnR0dEREREwsQ7MHAwrXInDID+FQuEPpPCG0+nEdWvb29uhSw4AAG4llUq1YMGCBQsWDA8PHz9+3OPxbN++vb6+vqysLDk5ubCwkCTJgoIC/LwLwK3F4MKVU/JPyMCj3SFgAgCAW0+pVK5btw4hFBsbW1VVVV1dPTY29u677zocjoaGhtmzZycmJvL5fP8AVQBuyVnK1NPP4/GUlZXNmzfP5XKdPn06Pz+fIAiPGUiVAAAgAElEQVSapnGAiCv+Q8AEAAAzSHp6emxs7J133tnb21tUVHTw4MEvv/yyoqIiNDRUp9Pl5eXFxsYGBQVB2ARuPgYXrqRp2uVy4W28WCT611pyCKHOzk4ImAAAYMYRCoVCoVClUiUnJ8+ePXtgYKCqqqq2tvaLL744duzYypUrU1JS0tPTYUoduMkYfMrxeLwlS5YghEiSLCwsxDvxWnIIITyUEAImAACYuebNm4cQmjt3bldX1/bt20+dOvXhhx+GhITk5+evWrVKq9WKRCLINoGbw+PxBM7BFhUVFRYW4i+XVquFgAkAAG4DoaGhWq02JiamsrLyzJkz//jHP/bu3dvY2BgfHz937tykpCQY2wRuAjxljNmampqioqIIgsAH29HRodFooEsOAABuGwRByGSywsLC/Pz8pKQkt9u9b9++4uLi4uLiFStWpKampqen4yoyANwggVCPvrm5OSoqCiG0bNkyhFBnZ6dMJsN9kfDtAv+hqKjo7NmzLBYL/5iZmRkVFQVDJQCYOfh8/ooVKxBCSUlJdXV1JSUlu3fv/uabb1JTU2Uy2bJlyxQKBV6iDtoKXF/j4+OMHPRdVVUVHh6uUqkIgsDjlsbHx3HxWL1e73Q6IyIiIGACk3k8Hrfb7a+Vh4ucAgBmoOjoaIPBsHDhQrzQyv79+1ksVnV1dV5eXkJCQkJCAiScwPWVm5vLyEqqFEX5A0GcXqqrq4uJiZHJZOHh4QcPHsQrasPXCfyH5cuXJyUlQUoJgNsCl8vlcrn333//ggULamtrR0ZG3nvvvZMnT8bFxT355JOzZ8+GmAlcR0KhkJGZy8zMzEl7BAKBPzQUiUQIocrKSvguAQDAbU+n0+l0OpfLJRaLS0tLv/rqq/feey8pKWn9+vUqlSoQhp6Am8BisTC40rfL5aIoCs+fSElJwbPkEEK5ubkIIbvdDgETAAAwBJ/PX758eWFhYWJiYm1t7cGDB5ubm5OSkjIyMmbPns3lciFsAtfEZrPV19dHRUW1traq1ep9+/YxeKLcwMCA1WqNj4/HP+IjbW1t1Wq1JEmq1WoImAAAgDlwJ90DDzzQ0dFRX1//l7/85e23346Kirr33nvT0tKSkpKgkw5cPafTuWfPHrlcjhAaHBw8cOAA7p9i6neHJEn/j3iWXE9Pj0KhIElyaGiI/fLLL8M5AbCioqLk5OTg4GBYIB2A251UKjWZTAaDgcPhqFSqAwcOnDlzRqfTkSQJRZvAVSIIwmq12u32lJSUkZERk8nU0dGxYcMGRt4jRCKRXC43m80TvyAcDkcikXA4HJvNBo8aAADAWJmZmampqQihd999d9++fe+9957RaFy8eHFSUpJMJvMXEAFgSgKBYM2aNV6vl8vl4qE8paWlzD7kM2fOLF68GCFUX18fHx8fGhqK95vNZvi2AAAAY7FYLJIkSZJ8+OGHf/Ob34SFhV24cOH3v//9Rx995F9qFIAr4HA4uCIRPpEYn5uUyWR4A1f3Pn36tNVqRQhJJBLIMIF/stvtXC6XzWZDrh4ARt4GCgsL4+PjW1pa3nzzzd27dzscjoKCgpycHCgjAq7S0NAQg2fJYZGRkXgjISEBIeR2u3E9QqvVCgET+KeGhgaNRiOXyyFLDwBThYWFabVaoVBYVVX10UcfdXR0UBSVl5cHMRO4GjU1NRRFMeygRkZGbDZbWFgYThZUV1fjLrnw8HCEUHZ2Nr4nUhQFARP4p5aWFqVSKRaLIWACgMFYLFZGRkZ6erpYLN61a9err77qcDgKCwt5PB40DrgyhULBvC4Im81mNpvDwsL8xzjx1crKyoSEBIlEMm/ePLg1AgBAIIZNq1ev/uEPfzg+Pv7hhx/+4Q9/qKioCIS16MH3wcjClXK5HCeTsNmzZxMEcfr0aXywHo+Hpunm5ubm5mbIMAEAQCASCoV33XWXQCA4cuTIK6+8cubMmZdeeik9PR0KNYFvw8iQOigoKCgoaNJO/+pyubm5BEH09/cTBAFfDAAACFAEQSxbtkyn042NjX399ddvvfXWs88+m5yczOFwYPIHuFzgzArKzs7GG+Xl5YmJiTExMTRNQ5ccAAAEtKioqF//+tfPPfdcQ0PDu++++/rrr3d2duKZQQBMtHXr1rvvvpuR41x9Pl9/f7+/w7GiomJ0dBQh5B/kXlZWBhkmAAAIaEKh0GAw/PSnPw0ODi4rK3v77bdHR0cXLlw4Z84ciUQCqSaAdXR0XLhw4U9/+hNjAqbW1la5XC6VSgmC8Hq9dXV1wcHB+CV/l1xeXp5/D2SYwH+E2DRNM77MBgDgcjwe70c/+tEvfvGLBx54oK2t7Q9/+MOWLVvsdjtcEAA2OjrqcDiYdEQjIyP+8q0sFkutVvtfysnJIUkSlzXHSSaYJQf+w9GjR6uqqvr6+mCyDACByWg0PvPMM0888YRMJnv//fe3bNly8eJFl8sFYROQSCQCgYBhZ7tUKsXbHA4nOTl5Yj6Vpml8Kzx69Og/3wMnAfArKirq7e3Nysq67777TCYTTJYBIABpNBqNRkOS5ObNm7/++uuysrK777572bJlUNwywI2NjTEsw+RfBWUit9t98eLFpKQkoVBYUFCAEMLj+erq6uCOCP4tMzMTIbRz586xsbE5c+bccccdcrkcRjAAEIBmz579wgsvnD9/fvPmzZ2dnVwud968eXgVd7gmBCaxWEySJFOPzuPx4MmhPp9vaGho4p6lS5cihMxmM/vll1+G8wAghOrr67Va7Q9+8IOQkJCWlpavvvqKpmm9Xh8UFATXRwACUEhIiMlk0mq1J0+evHTpUl1dnVKpVKvVsBhAYOrq6tqxY8emTZu4XC7zbgpHjx41Go34eUAqlQoEArynv7+fx+Ox2WybzQYZJvBvEokkNjZ2zpw5lZWVr7zyyl//+len07lp0yalUgkxEwABSCgUrlu3jiRJvPZcW1vbc889l5qaymazoXECDbPvAv6jY7PZSqXSv6elpUUoFPJ4vOHhYcgwgX+qr6+nKComJoYkydDQ0NDQUI/HQ5JkamqqSCSCgAmAgBUTE5OQkCAUCv/+97/39fX19/dHRETg7jlonMAhl8v37t17zz33MDLDhNNLbrcbHxpBEHiPy+WSyWRcLnd8fBwyTGBq2dnZsbGxFEVNWokQABCA1Gr1Qw89JBAI6urq3nnnnc7OzkcffTQ8PBy65wLHxYsX+/r6mH2MtbW1RqNRoVD09fXJZDI+ny8UCnE+dWRkBAImMDUOhzOxKAVC6MSJE3K5PDo6ms/nQ/sAEGikUuljjz3W0tLC4XA+/fRTn8/3+OOPQ8wUONhsNuM/a/+iQO3t7Xw+n8/nt7W1iUQiHo/HgXnj4Op98sknPp/vsccemzVrFo/HgwYBIAAZjcYnn3zS6XTu3r2boqi0tLTVq1dDr30goCiKeQvmUBR1/PjxhQsX4hM4PT0d79doNDg1EBISgu932dnZ8GQArlZiYmJ1dfVrr71WVlbW09MDxS0BCNiY6fnnn3/88cd7enpeeeWVrVu3Dg8PQ2VLxmPkOhA0TftXi5uIx+PhdBqPxyMIYmRkZGRkBAZ9g3+aOOh7yjfEx8cjhDo7O8vLy9vb2yMjI6VSKWTjAQhAcrk8Ozs7PDy8pqZm//79XC43JSWFkWOBgZ/Vav3yyy8ffPBBJn3QLBYrKioKH05fX9/AwIBMJiMIoq6uTiqVkiR5/vx5pVI5NDTkcDjgbgeu4RJ53333vfTSS2q1eteuXe+8805XVxcsaQ5AwMrKynruueeioqL++te/btu2bWhoyO12Q6qJqRwOh8fjYfABut1ufynz0NBQnDsICwvj8Xh4ADiMYQLXIDg4WK1WP/vssyRJ7t+/Pz09fd26dSKRCFoGgMCUl5fH4/Fef/313bt319XVLVy4cOnSpbgXAxqHYSQSCYMrfSOEQkJC/FOd/J0nbDabIAiVSlVSUgIBE7g2BEFER0c/8cQTAoFApVJBlxwAgYzD4cydO/dXv/pVbW3te++9d/r0aR6Pt2jRIlh4jnmsVivD1pKbxGw222w2o9GIEOrq6goKCiJJsrOzUyqV8vl8kiQhYALTYTKZHnvsMa1WC9PlAABZWVmJiYkikej1119/4403aJouKCggSRLyTEyiVqslEgnDDmpsbEwsFuMT1e12O51OvD8sLAyn03Q6ncvlQgjNnj0b0gNgmiIiIvzRktVqPXfunMVigSFNAASmoKCgu+6666WXXjKbzb///e8PHDjA7PEuAYiRo9NOnjzp3w4JCYmKisLb4eHhuJa9Xq+vqqrCOyFgAtdBa2vrW2+9tXXr1rGxMWgNAAITSZJ33XXXU089pdVqP/300+LiYoiZmGRwcNBqtTLsoCaOweXxeCRJlpSU4NDwxIkTeMP/HgiYwHUgEAisVuv27dv/+Mc/FhUVWa1WmCkDQGBav379b3/7W6/X+8EHH7z55ptnz56dss4NuO0wctB3bm7upI5jm802aSM1NbWkpAQhBHWYwD/V19e3t7cnJCTgor2tra1CofAqa8FLpVK9Xq9QKPbt21dSUqJQKAwGAwxvAiAA8Xi84OBgsVhMUdS2bdsuXLgQFxenVqthgsjtrrOzc8eOHZs2bWJ2wa3Q0FB8gP4Nt9vd29sbEREBARP4d8C0fft2t9vd2dnZ0NCwY8cOoVAYEhJyNbNdWCxWeHh4WlqaQCA4ceJEbW1tSEhIeHg4zJQBIDDFxsYmJydTFLVr167BwUGj0Qgx0+0OF67cuHEjkwImiqJKS0v1er3/iPxH59/g8XgRERGnT5+G0xf8W3BwME3TNpttfHxcrVZfayF8Ho935513Pv/88x6P57PPPqutrcWTCwAAAUipVD744IPPPPPMiRMnXn31Veibu92ZTKZJK7IzAE3TE2slVFRUmM1mmqbLy8tHRkZomi4rK8Njc51OJ5QVAP+2ZMmSO+64QyqV4h/ZbPa1dquJRKI1a9aQJNnX14dXLgQABPIz2GOPPWa327ds2fKHP/zhxRdfTE5OZrPZ0DJghmCz2fPmzZsYP+E0gT9Z4N9QqVQQMIF/43K5AoFAKBR+z1+yatUqaEwAAEIoKCjo8ccf5/P5b7/99ltvvfXMM88kJSVBzHQ7amho6O3tZdhBEQQxcSR7VlbWsWPHCgoKsrOz/Xc03DE3PDwMXXIAAABuIJVK9eCDDz799NNnzpx55513oG/uNtLX19f9L/v3729qamLYDGiKoo4cOTLxoCaNJPF4PPhVpVIJGSZww7W3t5vN5ri4OIFAAK0BQABSq9WPP/64UqncuXPnG2+88fzzz0Oe6bZQXFzsL37d1dXFvHk8NE1PCt8XLlyIEGppadFoNEKhUKlU4tniZrMZMkzghjt8+PAbb7xx9OhRZq9DBAC4gqCgoAcffPD+++8nCOLdd9+tr6+HPNPMFxwcrNVqQ0JCQkJCli5dGhUVxbCCAhwOZ8mSJRMPCi8dPTAw4Ha7EULDw8O4/qpUKoUME7jhdDpdR0fHW2+95Xa7CwsLcZ0naBYAAlBhYWF0dPRPfvKTt99++4knnoA80wy3YMEC//b58+dxDMFUDofD6/XiO5TRaMTDeU0mE+4bGR0dhQwTuBmXyJ/97GdWq/XNN98sKiqCPBMAAUulUiUkJDz11FMdHR2vv/76+fPnIc90u7jWQjO3ncHBwY6ODrwdHBzc2NiIENJoNHi2OE3TEDCBG47NZq9evfqpp56y2Wx//vOfjx07BjETAAFLIBA88MADGzZsKC4ufvPNNxsaGiBmui2wWCxmlx4VCARisdj/Y09PD944dOgQQig/Px8CJnCTTsTVq1f/6le/stvtb775Znl5OdS0BCCQLV269Nlnn/X5fK+88sq5c+cgZpr5fD6fz+dj2EEdOnTInzZTq9V6vb6oqAjvSU5Oxvv9JycETOAmEYlE69evf/LJJ4VC4eDgIFwfAQhkKpXqqaeeeuCBB8rKyqBv7rYglUqZN9P58hDQv0epVDY0NCCECgoKLly4AAETuKkIgrjzzjt//etfZ2dnw9K8AMAFITk5+dFHHyUI4p133sF9c8weJXNbGx0d9ZcYYIw77rhj0iSkgoKC4uJiXG5gaGgIIeT1egcHBxFCMEsO3FQCgcBfQRUAEOCCg4M3bdrU1NT00EMP2Wy2X/7yl7B2yowlkUgCpJYeTjLxeLz4+HiEEEmS8fHxAwMDkGECt1JDQ0NFRQWMAQcgYCmVysTExB/96Ee4bw7GM81YVquVkdfq4eHhtrY2f2qTJMmFCxcSBMHhcNRqdUNDg8fjUalUFy9ehIAJ3Er79+/fvHnz0aNHbTYbpOIBCEwikejhhx9+8sknv/nmm82bN+OalnBBmGnEYvHEZdcYw+l0Wq3WSTspivL5fDRNj4yMeL1ehFBwcDAETOBWio+Pj46O3rFjR1FRkd1uh0skAIFJo9Fs2rTpscceKy8v/6//+q9z584xb0LW7c5qtTJvDBNCSKlURkRE4O3BwUGn00nTdEVFxejoKEJIoVBwOJzR0VGtVgsBE7iVli1b9swzzyQmJm7fvv348eOM/DYCAK6GXC5/4oknNmzYcPLkyc2bN0Pf3EzDYrEYuUgDSZISiQQfWmtrq81mQwix2Wy8Z3h42Ov1DgwMDAwMwKBvcOuvkhs2bOByuZ999hlCqKCgQCgUwtopAAQgiUTy8MMPkyT5xz/+ESH03HPPJSYmMvU+fdvBXVTMPka1Wo1PtszMTLxHo9HQNC2VShGUFQAzgUaj2bhxY2xs7AcffFBTU4NXOgQABObVYNOmTY8++ijumzt//jz0zYGbJjIysqKiYuIek8l08uTJ4OBgGMMEZgqZTHbvvffK5XK73Q7XRwAC/GrwxBNPPPDAAydPnvzwww+ZveDrbSQpKSksLIzxh+mvEVheXo4zav490CUHZorQ0NCnn35ap9NxuVxoDQACmVQq3bRpE5/P37p1a3FxcUFBAZ/Ph465W8vj8TByVBmeEMfhcPAJtmDBArzfYrHgjYULFzY1NUHABGaQoKCg9PR0aAcAAEJIo9E8/PDDVqv1jTfecLlcd9xxB4/Hg5jpFrp48WJfXx/zjquvr89sNiclJeEf29raIiIiCILIyspCCHV3d6tUKvwSdMmBGaq6uvrUqVNQ0xKAgCWVSjds2GCxWF599dVjx47BpLlbi8PhMLIIO5vNntitcfHiRbwhl8sJgmhra3O5XCaTyWQyQcAEZqh9+/a99tprhw8fHh8fh/pMAASmkJCQp59+2mazvfHGG0eOHME1cqBZbgmv18vImDUkJCQuLs6fvDQYDAihU6dOjYyM0DQdFhaGC1eWlJRAwARmqNTU1N7e3s2bNx88eBDyTAAEJqFQuHbt2t/+9rdms/n3v//9gQMHPB4PxEzgxomNjZ3Y82swGE6fPo23IWACM9Ty5csff/xxm832zjvvHD16FGImAAKTQCBYt27dU089ZbFYXnvtNbvdDm1yS/D5/MCZkZOdnV1fX++P2hFCeXl5EDBNh91un5iZdDgcBw8e9I+oB9cFm82+6667fvGLXzgcjnfffRf65gAIZOvXr3/++eftdvuuXbusVitcCm4+l8vF4CJ5Ho/nyJEjE8+r8fFxfLvPzc3Fe2CW3HTs3r07KSkpPj6ex+NZLJZ//OMf27dvNxqNMpkMGuc6EolEd955J4fD2bx58+bNm7VabWpqKhQdACAABQUFrVu3TiAQ/O53v3O73ffccw8ekwstc9MwdfHdbzN37lyEUHV1dXJyMo4UIWCajv7+frvd3tTUxGKxOjo6Tp8+HRISElBn0k0jEAjWrFnjcDgOHDjg9XrhsRKAgEWS5Nq1az/++OO3337b7XY/9thjfD4fmuWmYeTiuydOnMjLyyMIgsvlLlq0aOIesViMEBIKhSwWy2w2EwQBAdN0FBYWtra2/uMf/2hubuZwOHfffXdWVpZarYaWuRE4HM6aNWsyMjLCwsI4HDhjAQhov/jFL15//fUPPvhAoVDcc889/irM4EYLDg6WSCQMO6jLh8T594yNjYnFYlwdUKlUIhj0PT3l5eWHDx/u7e1NSUmJjo7OzMwUiUTQLDeOWCxOSEiQSqUsFpyxAAS0efPmvfTSS3FxcR9//HFHRwespHQzAyacdGGSvLy8b9tz8uRJhFBbW5vT6fT5fD6fD24/03H48OG2trbs7Oyf/exnq1atunjx4scffzw8PAwtcxPU19fv2bOnpKQE5s0BEIA4HM7cuXNfeOGFkJCQTz75pK+vD2Kmm4ORlb6DgoImjYTjcDinTp2iaRqn07q7u91ut8VisVgs0MExHRqNZuXKlampqUqlMiQkpLKyEgeh0DI3gdvt/vLLL0mS1Ov1Op0Ock4ABKA5c+asWrXqd7/7ndPpfOGFF4KDg2EA+I3G1LXkEEJnzpzR6/UqlYogCJqm8d08JycHIWQwGPh8Pu6SY7/88stwHlwrkiQzMzOVSiWLxeLz+aGhoVarNTk5+bbumKuvr6coKiYmZoaPXlcoFBRFVVZWut3uyMhIgUAAF0oAAg1BEAqFoqura9euXRRFRUZGSiQSuBTcUDKZbO/evffeey+Xy2VYU/f29kqlUqFQSBAEm83m8/l2ux0nnyQSCUVRAwMDoaGhkGGajpycnGPHjo2Njfn3NDc3M7hAxYzC4/HWrFnT3t7+f//3fxRFPfDAA1KpFJoFgEATFhb29NNPczicDz/80GQy3XvvvZBvvtHXXqZOu8nIyDh+/Pj8+fNxLO52ux0Oh1QqrampycnJ8Xg8PT09RqMRAqbp+PLLLz///PPu7m4ej4djbYqiHnroodv9uKxWa39/v39skEAgEIvFM3C1RR6Pt3LlyvLy8k8//ZTH461du1alUsG1EoBAEx0d/fOf/9xsNn/++ecJCQlpaWmMXB12hhgfH3e5XEw9uomHplAocBWbf5Zf4nAUCgWCLrnp2bx5c0pKilAolEql8+bNS09PDw4OzsnJua1nENTX19fU1IyOjnZ0dDQ3N+OcWXBw8MwsFKlQKCIiIhoaGg4ePGg0GiMjI6GgJQABSCaTqdXqLVu2XLp0KS4uTq1Ww7PTDdLY2Lh169ZNmzYxr0sOIRQeHs5ms/Fx8fl8gUDA4XBCQ0PZbLbT6WxtbdXr9XBiTQebzb777rufe+45jUYTExOTmprKjGWcxWKxRqPR/otMJpuxj2tsNjsnJ+epp57Kyclhs9lQ0BKAwEQQRHx8/EMPPVRWVvbFF1/gheXBjdDe3m42m5l6seXz+d3d3RcuXPAfoNPprKiowLcbPPADuuSmQyAQ7Nu3b968eXq9/u9///vAwIDVat2wYcPtflwxMTGLFi26jRZ4mTt3rk6nk0qlUPAXgIClUqkefPBBgiC++uqroqKiRYsWkSQJA8CvO71ez+zlaHw+H0VRPp/PYrEoFAqapnH8LRAIkpOTS0pKIMM0HatWrZLL5QihH/zgB8nJyRRFrVq1CvdxgpuJw+EYjUalUgkDFwAI8Jjppz/9aUZGxquvvnrw4EGmzn6/tSQSiUAgYPAB6nS6uLg4j8dz9uxZHCfhZXfPnTv3zzsOnATTsHjxYv/2j3/848zMTIvFAqt23HIVFRUmkwkKggMQgIRC4Y9//ONjx4698cYbQqFw4cKFcE3+/rZv3+4vMXj+/Pnm5mYGj3/ANw6KolQqFUKIIAh8CvX09CQnJ+fl5cH5NB2dnZ27d++mKMrpdHI4HIIgKisr8dod0Di30KFDhw4cOHDfffdFRERAzgmAQBMTE/Piiy++9tpr27ZtS09Px3UIoVm+Dxwe4f/qdDrctcJsPB4vOTkZIXTgwIGlS5cSBBEcHIxfgoBpOnbt2nX48OHo6Oienp6goCA2m83lcuEOfctJpdJ33nlnfHz8kUceMRgM8HwJQEAJCgpat24dRVEvv/zyZ599tmHDBqlUCjHT97F+/Xr/dkdHx7Zt25janrW1tSkpKROPzt9T0d/fDwHT9NXU1PzoRz/KyckZGRnh8XhsNnt8fBwn8cAttHTp0gsXLuzatcvlcuGlpqBvDoCAwmKxVqxYsWXLlj/96U8EQTz66KM8Hg+aZdomJgJsNhuDVwDr6+tLSUlBExJLS5YswS9pNBqE0IkTJ+B2Mh3Lli1zOp1Wq1UmkwmFQj6f39zcDGvJ3XLR0dFPPvnk0qVLDx48WF9fD7XXAQhAQqHwxRdfjIuL+/TTT3t6emBp3uslPDycwXObUlNT/TE3QmhoaMjtdtM0PTg4mJiYiPCQJjgJpkGr1f7mN7/56quv/IvHNTY2pqWl4fX5wC0UGxv77LPPkiS5e/duiUSSlpYGz5cABBQ2m52fn0+S5MaNG//6178+8sgjer0eks3fn1QqZfAsuZCQELyBE0tNTU2xsbEymayxsTEpKYnH4+Xl5cE5NB1FRUUxMTEKhYL3L/4KoeCWMxqNjz/+eGVl5YEDB+x2OzQIAAEoMzNz9erVW7Zsefvtt4eHh6G27ffn8/kCoRkpiqJpWqVS4YdttVrtdrtPnDiBYAzT9PT09GzcuDEiIsK/p6KiQq1W375H5PF4XC6XQCBgxnOYyWR69NFHZ+y6LgCAm+AnP/nJyMjI3r17V6xYMX/+fJgF8j3V1dX19PQw77hsNpvL5fLX5CwqKlq6dKnJZPJ6vf39/TExMePj4/glOIGmIyYmhqIotVrtz09arVaSJG/fI7JYLL29vbhCLjM+IwashQwA+D4iIyN/9atftbW1bd26de7cuRAwfU9M7UixWCzDw8P+ign+88Ttdl+8eDEkJEQkEuXl5UHANE1cLnfLli3nzp0jSZLNZvt8vpqamhdeeEGv19+mR2S320dGRjQaDfNG/Ph8Pp/PB32mAAQgg8GwYcOG//7v/z527FhhYSEjV429aRISEkJDQ5l3XEKhcGJXY15e3n3t63YAACAASURBVLFjxxYsWMDhcIKDgymKcjgc1dXV+fn5MIZpOurr64eHhxFClZWVdrv9/PnzHR0dMCdrZqqpqdm1a1d/fz9MlgEgAC1fvnzjxo2vv/56ZWUlXATA5eRyuU6nu7wCEx6g3NTUhBCCLrlvZbFYLBaLVqv9tiVdo6Oj165dO3/+/Lq6uvj4+NbW1u7ubqjDNDOdPHny008/7ejoePjhh2UyGTxfAhBQZDLZhg0bdu7cuWPHDrweA1wEpqelpWVoaIjxh0mSZEFBAd7GZaigS+5b0TT9+eefczgctVo9NjZmNBoTExMlEsnE0dB33323RqPh8/mZmZkEQaSkpOCCV2AGSkxMDAkJ2bJli0gkuvfeeyFmAiDQcDgchULx1VdfPfrooxKJBK4A0zM2NhYIqxo7nc6ysrIFCxYQBGEwGBBC4+Pj0CX3rQFTXV0di8XCq51cunRpz549VVVV/f39Xq8Xv8doNI6MjJw+fdpisUCOd4bLzc395S9/GR8f/5e//GXr1q3QNwdAoOHz+bNmzbJYLJ988onb7YYGmQY8jmf58uXMGztvtVqHhoYmDmNisVh9fX1Op9O/EwfZ7JdffhlOhcubr6enRyKR3HHHHQqFYnx8vLa2tqqqKiwszJ9qstlsX331lUajUSqVDFhFbnR09MyZM1lZWRKJhGGfJpvN1uv1BoOhtra2qKgoLS0tPDwc5ssAEDh4PF5UVJTL5dq7d+/cuXO1Wi3UsbxWFovlnXfeWbFiRUxMDMNab3BwcHBwMDg4+J8DlTgcg8FQV1cnlUrNZrPFYlGr1XhGF5w0kxEEMWfOHIlE8tVXX3300UdFRUV6vR43VnFx8eDgIM5PaLVah8NhtVohXXFbyMzMfOaZZ/R6/Y4dOywWC1SxAyCgGAyGJ554QiAQvPnmm/X19YHQtXTdg06mjmcQiUSXr9IREhLC5/NdLpfT6fT5fHjpM3jOnkJYWNgPfvADrVbb1NR06NChysrKoKAgg8HQ09Pz2WefZWdn4xVR+vv74Vt3G8nNzV23bt2OHTtcLhe0BgCBJjIy8sEHH3z//fcPHjwYFRUlEAhgMNPVc7vdTH3UlMlkMpkMITQ2NuZ2u5VKpX/0UmhoKE3Tdru9qqpq3rx5EDBNgcvlKpXKNWvWDA0NJSUl7d+/v6Ojg8/nDw8Pnzx58uDBgzKZLDc3VywWi8ViSO3eRh9rQUFBcHCwv0AZACCgbNq0qaWlZdeuXSaTaeXKldA1f/XYbPa3TRtnDIvFYrValUplT0+Py+UyGAxDQ0P+ItVVVVVwulyJSqW64447YmNj8eDu4uJihUJBUVRlZaVKpcrOzjYYDAwYwBQ4oqKioqKioB0ACEwikeiHP/zhqVOnNm/eTJJkYWEhxExXiaIoxufmJRIJDgrdbjfug3O73V6vVygUZmZmlpSUwLny3SIjI/FGTEwMnmFRXFwsFovj4+Nx3xy4Hfl8vq6urpCQEOYVNwcAfJu0tLSXXnrpf/7nfz7//PP09HT/UF9wZQRBMKmhaJpubm6OioqaeFC4Yw4hpNVqcedjWFgYTdNNTU0mkyktLQ26k66BWCxWKpVKpXLFihUwz+J2V1FR8e6771ZXV8M0YwACB0mSq1ateuSRR06dOrVlyxa73Q5TQK4Gi8ViWJdcc3PzxB9LSkr8ZwKfzydJsrS0lMfjkSSJi32LRCK45U9WWlr6v//7vwcOHOjp6fEXXpqEz+cnJSUJhUJortuX3W4/dOjQ5s2bIWYCINAsX748Pj7+o48+6unpgYDpajCvS27S8Ay73Y43Dhw4gE8J/x6TyYQ3oA7TZN3d3a2trbW1tRUVFWw2e2RkBAebzE7bMrgO07dRqVQul+vw4cNNTU0FBQXQuwpA4BAIBCaT6ciRI8PDw9HR0bBeynfi8/kXLlwICwszmUwMaCuCIBQKxcQDwWvPEwTR0tKCu+rwno6OjtDQUIvF4nA4IGCaLDw8PCYmJigoqKWlxePxVFRUNDc3t7e3+3w+mUzG1BGCARgw8fn8uLg4Npv99ddfm0ymyMhILpcL5z8AgYDFYoWFhdlstvfff99ut8fHx8OSKd/ZYuXl5RqNhhkB05QhVHl5uU6n8x/gqVOnIiIi6uvrlUrl0NCQ0+mEQd9TkMvlixYtiomJGR0draurs1gsra2tNTU1er1eoVDMmTMnNDQUh6LQVrc1pVL54x//mMPhbNu2jc1mFxYWikQi+FgBCBBr165taWnZs2dPdna2Vqvlcrnw9Q9YNE3jmXF+DocDIaTX6/l8Pi7OBBmmbyWVSoODg2NiYhISEvR6vc/noyjq9OnTZrPZbrcPDQ0RBCEUCpkx9DsAM0xYUFBQTEzM3/72txMnTmRkZAQHB0OdCAAC5yKflJTU0NBQXl4eFxcHU3muYHx8fPfu3dHR0UzNMLFYrJCQkIlB89jYmFarlUqlTU1N4eHhvb29kGH6Djwej8fjicXi6Ohoj8dz6tQpq9U6ODhYUVHh9Xr1er3RaJw1a1ZQUBC01W1KLBZv2rTp4MGD0BQABJrw8PANGzb89Kc//eSTT1JSUuB56ds4HI6BgQEGD5DHGRCE0LFjxwoKCgiCGBwcxC+1t7fHxcV1d3dDhukasNnsiIiI6OhomUzG5/Nxbavi4uKOjg6hUOjz+QiC4HA4t2P0HbAZJvxgERkZmZqaajAYGD+6HwAwiUKhkMvln332mU6ni4iIgI65KQ0PD2/dujU3N5epGSa/S5cu4UHfXC4XzwawWq1arZYDRU6n/VCi1Wpzc3NtNtvx48ftdntlZSVN07Nnz46NjWV8/XjmwR1z0A4ABGbAtHHjxm3btr3yyisGgyE9PR3yTJcTCoVarZaRhzYyMmK320NDQ3EgmJOT09jYGBMTExERgd/Q19eHEAoLC4P+2mnicDgCgUClUq1fv37Dhg3Jyck6nU4kEkEXOAOUlZXZbDZoBwACBJ/Pf+KJJwiC+Pzzz91uN1RmmhJTE0s2m81sNvt/5HK5vb29CCGHw1FaWooQUqlUzc3Nzc3NkGGaDNdBP3PmjMPhyMnJEYvFcrmcJMkrR0KzZ8+GpmOG6urqP//5zy+++GJsbCw8aAIQIFauXPn/2bvv8KiqdXH8a+/pvWSSSaZmUia9EBJIgCTSRDpSFFDQgFQbHuXoee45V733eo8eC6AeEKQJkSIoikCE0BJCCEUIJIGENNJ7m5lMMv33x/o6v1yMKIoh2fN+/vDZM4nPw16Tvefd633Xu0pKStLT04ODg9PS0mDHpH6/HCl5XmKxmMPh9A2YcMLB5XLhU05ISMDNvmE6pJ+/ie+//95gMNDp9AsXLpw4ceLcuXM/n29ob29vbGy02WwwYhRDo9HodPrevXvLysp+qdU7AIBiOBzOzJkz4+Pjt2/fXlFR4XQ6YUz6kkqlkZGRlJxk4vP5uGsAful0Og0GA/6TGDlyJH5Tp9PpdDoo+u4nYDp//nxUVNSECROcTieHw+ns7CwqKrLZbFKp1F311dbWlpubKxaLqZGG6+rq+uabb7q6um7fvn39+vXr16/fuXNHoVB4YD2WXC4Xi8UbNmxoamqKioqCdnYAeM61HxgYuHnzZqPRGBkZCdd+XwRBXLhwgcKNK91sNltxcbG/v39vb++lS5e0Wu2JEyeCg4NJKLjp989i6tSpTU1Nmzdv5nA4ISEhw4YN43K5hYWFRUVF7sZWEomkpKSksbHR4XBQ48Tv3LmDm5u7d6X22JtFQkLChAkTTp06tX79+srKSsp8xACAe4uJiZk7d25GRsY777xDsa3T/qCWlpYff/yRwtVdGRkZ+OwYDIZarTaZTH2jAoRQdnY21DD1EzCFhobiLumHDx9uaGhISEhQKBQNDQ27du2aPXv2yJEj2Ww2j8ez2+02m40yf0Barfbxxx9PSEhwJ+89dhEll8t98cUXaTTawYMHaTTa8uXLAwICYEkpAJ5g7dq1dDo9PT09LS1txIgRUMjo/mak9lC47/A0Go0kydra2tDQ0KSkJISQVCrF78N3QD9IkgwLC1u+fHlhYWFzc3NDQ8N3333X1dVVUlJSXV09btw4vFGr0+kUCoWUmaXz9/cPDg6GDpz41uDv779y5UqHw3Ho0KGoqCilUgkBEwCeQKFQvPDCCzk5Ofv27YMWA24ymSw2NpYaaYf8/Hy5XO7r69v3dCZOnOg+5vF4eGtRfNtvbW1FCI0ePRq+A35RWFiYTqdLTEw0m818Pr+zs3Ps2LHt7e3Hjh1ra2ubP3/+2LFj1Wo1fI9SVUBAwOrVq/FejPApA+A5tFrtCy+8sHnz5sOHD0+dOpXL5XpsfUJ1dTVOp/T09HR0dFDjpEiS/PkHarVas7KyJkyYQBCEj48PQqixsVEul7tfQkruV7DZbLVa7XK5goOD8Tv19fUXL148efJkTEzMiBEjOBwOVAVSO2Z6+eWXkQeXcwHgmebPn19SUvLBBx9YrdYnn3wSzzd4msLCwu3btyclJeXn50ul0szMzDFjxlDgvKKion7+Jm7t3fed/Pz8SZMmIYSampoQTtXBhfGrCIIgf6JSqebMmbNq1Somk4n3QoHx8YSPniAI109gWACgPBqNtnDhQhqNtmHDBo9tZdnW1sZms5lMpt1uVygUlMlOEj/p+yaDwcBbyPX29p46dcrlcrk7m+MDSMn9ThEREQaDgc1mw1B4joKCgubm5pEjR/L5fAiUAaA8f3////iP/3jttde2bt26cOFCmUzmaRd+eHg4LmyNjY318fEpKCig8Mp6h8PR3Nzs6+uLfipdiomJQQg1NzeHhYUZDAaCIGCG6Xc+fEgkEqhr8Si3bt368MMPMzIyenp6YDQAoDw2mz1t2rSpU6d++OGH2dnZHthexNvbW6FQiEQirVZrtVrb2toofLIOh+PmzZv4c09NTXUHx6WlpT09PU1NTU1NTRAwAfCbBAQEGI3G9PT0jo4OSMwB4CEWLlzY3t6+e/fuuro6T27/bbFYOjs7KXzrI0kSp97sdjs+TdyZycfHh0ajCYVCgUAAARMAv0lERMRf//pXh8Px9ddfNzY2ws4JAHiCmJgY3GLm3Xff9eS9sKxWa1dXF5XOyGw2t7W1uUNAOp0eHh5OEERmZqb7HYRQcHBwdna2XC6Xy+WQVALgN+FyuTNmzOjq6tqwYYPZbH7uuef6bj8EAKAkOp2+du1aJpOZnp7+9NNPJyYmemZnJg6HI5PJqHRGXV1dTU1NuCllX+4Nwdydmdhsdl1dHYLNdwG4L5MmTQoMDExPT//yyy+NRiMMCACU5+fnh1uyrVu37tq1a565V5LT6aTYBBuXy+03BBw3bhx+EnZvljJu3Lienp6enh4ImAC4D1Kp9JVXXomKirp69SpUfwPgITQazapVq4qKir7//vvu7m4PrGKk3tYoIpFIpVLh2Ki5ubmnp8flcjU1NfX29uLP172uq6qqSqFQKBQKSMkBcB/odHpiYiKTyWxraxMIBDAgAHiIhQsX3r59++jRowsWLNDr9Z6WjqfS1ig/V11drdVq2Wx2VVVVYGAgzsoJhUL801u3bmm1WgQpOQB+h7i4uIkTJ3K5XBgKADwEg8GYP38+SZJffvmlB04ytbS0/Pjjj1Q9a7lczuFw8IE7KHQXuWu1WpvNZrfbIWACAAAAfp1er582bdq+ffv27dtnt9s96typl5LrS61W447EWq324sWL+M2EhASEUF1dXUBAQGVlZWVlJQRMAPwhWVlZN27csFqtMBQAUBuLxZo1a1ZiYuIXX3xRXl7uUb1FaDSah2xuwePx8IFEIiEI4s6dOxaLhclkMplMCJgA+EN27tz53nvvXblyxWKxQENLAKgtOjr6+eefr6urW7duXXNzs+dc8na73UOWuaSkpBAEceHCBdyj2MvLi06n+/v7a7VaCJgA+EOGDRtWWFj43nvvtbS0wGgAQHkxMTFz587NzMy8ePGi57QYYDKZQqGQ8qXudXV1eLkcjUbDJ9va2mqz2drb29vb2yFgAuAPeeaZZ5YuXXrr1q2srCxoNAAA5XE4HNxbZOvWrZcuXfKQmAl3+qbkjFpTU9Pt27fxqdXV1ZnNZoTQiBEjxGIxQRA8Ho9Go7W1tbW1tUHABMAfIhKJFi5cOGLEiB07dhw9etRgMEBiDgBqUygUaWlppaWlX331ldls9oRLnsvl+vn5UXKGyeFwuItQlUolh8Ox2WwWi8XpdHZ3dw8bNozP50ulUqlUCgETAH+UTCZLS0uz2Wzr16+/fv26J284BYCHePTRR19++eXMzMzLly97QvU3j8fDe9NSj7e3d2BgoDtg4nK5dXV15eXlPT09ly5dQgjdvn3by8vLaDRCwATAAzB+/PgXX3wRIVRfX+9p640B8EBcLnf+/PkymWz//v2dnZ0wrzx0MRgMDoeTnZ3t/hBZLBaHw6HRaCKRCCFUWVmJEKqtrYWACYAHY8qUKWvXro2IiHA31AcAUBifz58zZ05WVtbmzZspP6/c0tJy5coVCseFfVvDKBQKnU7HZrPj4uIQQsHBwQghWCUHwIN84pw8eXJISAiDwYDRAIDyGAzGlClTEhMT9+zZU1ZWRu3EHEEQ1L6zjRo1CiFUXV2N27hXVVWZzea2traWlpaAgACEkFqthoDp1124cCE7O9tkMsFQgHtjsVgMBsPTNpkCwGMFBQW99tprDofj008/pXbMJJPJYmJiKHxz4/F4BEE0Njb29vYihBoaGiwWS1dXV0dHR3d3N27/DbmDX/fNN98YjcaAgAA+nw+jAX4jg8GA16PCUABAYZGRkU899dT27duHDx+u1WqZTCYlowqbzdbd3U35T1OtVuNNQjUaDYfDIQjC6XS6XC7cPAJmmH4dk8lsamr6+d4XtbW1RqPRo7rjg9/uq6++ys/Phy1TAKC8FStWTJgw4csvv2xra6PqOXZ0dBQXF1OvhunmzZt9T8rPzw/HSbitgEgk6ujoIEkSFzNBwPTrZsyYYbfbS0tL8UwdVldXt23btrKyMs/p9Aruy8mTJ9etW3f58mWImQCgNm9v70WLFtXX1x89epSqi2Rxp2/qnVdNTY37uLa21h0UNjc3WywWhFBTU5Pdbsf76EFK7tfduXOnpKTkk08+OXfuHIvFcgdMGRkZCQkJ4eHhA/zv6enpMRgMYrGYqnO/1DBz5sx//vOf77///ttvvw1L5wCgtujo6OTk5C1btshksunTp1PveheLxcHBwdT7xgkLC3Mfu1wu92yTVqvFuTmpVEqn02/fvg0B029SUlJit9tbWlpyc3Pdfy54Ymng/3oKCgrq6uqam5sDAgLi4uLwJ9ovp9N5/fp13OUdIaRUKpVKJSzgGjCPP/54c3Pztm3bTp48qdPpKPlwBgDARCLR4sWLKysr09PTExISlEolxWILo9FYVVUVFRVFsQ9Oo9G4jxUKhbvGpru7WyAQMJnM1tZWPz8/vLUcBEy/bvr06QwGIzQ09K6i7+vXr2u1WpIcuLTmjz/++MUXX8TExCiVygMHDphMppSUlF+KmXJycjZu3OjOqT/xxBNPPPEEbsMFBgCbzV68eHFZWdl3332n0WimTp16j+gWADDUJScnr1ix4vXXX9+8efPatWsFAgGVYqbe3t62tjZq9+esr683Go14zqmlpUUqlXK5XDzDhFuBQ8D063CAIpFIDAZDb2+vy+WSSqUcDgdP8AzY1OvNmzfXr1+vVqtHjx4dFBR069atbdu2sdnspKQkd6LQzWQynTp1KjAwMCQkBL/j7+8P00sDTCKRzJ8//9atW5988gmHwxk/fjyHw4FhAYCqxo0bN2bMmL17986ePZtii/AFAoFWq6V8EYj7BAMCAsxms1gsDg8PP3r06NSpU7OysiBg+nUkSTKZzGvXrmVkZNTU1DgcjnHjxkVHR4eEhOBCsIFRXFyclZW1bdu2wMBAOp0+YcKEzz77rLCwMC4u7ucBU15eXldX15QpU0aOHIn/kTQaDZa4D7zExMTXXntt06ZNjY2NsD4AAGqTSqV/+9vfVqxYsWvXrnfffffnd+ahi81me3l5UfvjUyqVZWVlJpOJz+f7+Pj88MMPCoUCIYQ/RwaDAQHTr7PZbPv37z969GheXl5bW5vT6bxy5Up0dPSqVavi4+MHJmYymUxXrlwxmUzuCS06ne5yufLy8mbMmHHX3G9LS8vBgwevXbtWV1d3+/btqVOnqtVqKDp+KGg02sSJE0UikY+PD5XungCAfucnwsLCFi1a9NFHH82cOTM5ORkeUweza9euKRQKHx8f/AVKkmRXV5c7LpTL5fhgwoQJCKFRo0bBl+iv+/rrry9cuBAREREfH+9+s62tbdeuXWKxODQ0dABika6urjNnziQmJvr6+uKqKbFYHBsbm52d3draqlKp+gZMBEEkJSWVl5cXFRXdvn07Pz//lVdeCQkJufe/02w2d3d3NzQ0MBgMl8vF5XJtNpvNZhOLxb29vTQajc1mD2TBFpVipqSkJBgHADzEzJkzt27d+u6774pEopiYGLhtDlokSd6VZNTpdO5i5WHDhuEDSMn9VjU1Nfv37589e/b06dP7Fn3X1dX94x//aG1tdTgcAxAw2e32jo6OyMhI3L4dIcRmsxUKhcFg+Pmmj15eXk899ZROp6upqbl+/frXX3/NYDBWrlwZHh5+jzKmoqKiQ4cOdXZ2hoWF1dTUBAUF0en0mzdvRkVFNTY2cjicGTNmiMViaGQAAAD34OPjs3z58nXr1h06dEiv13O5XLhtDk5RUVF3fTQymcxqtRYVFUVERFit1vLy8vDwcEjJ/VZGo9FqtSYkJIjF4r7va7XawMBAJpM5kP+YvuGR2WyuqanptykiQRB0Oj0lJQUhlJKSIhQKd+zYERoa6u/vf49VcgRBdHV1kSTJYrHsdrvBYPD29nY4HA0NDV1dXWazmaoN2QZSbW1tdnZ2cnKyQqGAuXoAqGr+/PnFxcXffvvt888/D8tjB61+J/+cTmdraytCyOFw4GXmkJL7rZRKpVgs7uzstNls7ukZh8Nx6dKlixcvjh49emD+GXQ6XSwWl5eXG41GvLCzp6enurpaIBDce+2bWq1etGjRrl276uvrfz4X1VdYWNiMGTNUKhWPx0tKSiJJksfjxcXFuUuVoZPQH1dfX79t27acnJw1a9YEBgZCzAQAJfF4vPnz5586dWrz5s3Lly+Xy+VDfZKpt7e3o6ODep9UQ0ODr68vQRAOh6OlpUUulzMYDNyPmslkqlQqg8FAEMTVq1dTU1MhYPoVIpEoIiLim2++aWhoEAgE7j+dbdu21dTUMJnMgclPi8XiCRMmbNy4saOjw+l00mg0m83W1dU1adIkb2/ve1+KMpnstyQNeTyeWq1WKpUIIYlEgt90H4AHQqVSJSUlpaenMxiMFStW6PV6KMYHgJLi4uLmzJmzadMmlUq1aNGiod7VxWg0VlRUJCcnU+xjys/Pf+yxx/A8SGFhoVwup9FoPj4+eJ7C6XTW19er1Wr88cHN+tfNmDFjy5Ytn376qTv/ZbfbOzs7Fy9eHBQUNDCTBDweLzY2lsfj3dU3LCEhQSQS4R2VEUIEQRAE4f4dHEg5nU4/P7/w8PCBbIIA+qVQKJYtW+Zyufbs2RMZGanRaNxFaQAAKiEIYs6cOR9//HF6evqYMWOCgoIGf/X3PVqfdHZ2VlRUUK9xpUqlwgckSfr5+eHjysrKnp6esLAwgUDgcDi4XG5iYiIETL9JeHj4kiVLzp07d/jw4erqaofDMWHChBEjRkyaNEkulw/YNRAZGRkdHX3s2LGIiAi5XN7c3BwZGRkZGYnr0b777rvm5uZ58+ZJpVJc6+3v76/RaDo6Oo4dOxYQEJCYmAhdEwcDrVa7cuXKjo6OQ4cOBQYGjh49GtoNAEBJoaGhq1evTk9Pz87Oxq2DB/nT0cGDB41GY78/amtr6+zspN5n5N7shU6nR0RE4GN320I81WQymX788UdIyf0mJEnGxsbGxsYOGzasrq7O4XA8lKLd0NDQWbNm5ebmnjlzRiKRVFRUTJw4MTo6Gn/dHj9+/ObNmxMnTpRKpfX19Z988olAIJg5cyZC6MaNG1OnTlWpVFAxM0jgwrLnn39+06ZNkZGR+JoEAFDPSy+9VFVVlZ6eHhAQkJqaOshvwlwu1+l09juNxOVyExISqD0d3tzcbDabtVqtRqO5efOmyWQyGo0Oh0MqleLvWQiY7sOYMWMe7j9g4sSJeM1/U1OTXq9Xq9XusqqUlJTg4GBcly2Xy0eMGIF7bOp0Or1eHx0dDSs1BpWQkJCVK1d+8cUX/a5zBABQg0Qiefrpp1944YWdO3fiaf7BHHNMnz79Hj+tra2lXsB07NixyZMn4/OyWCzu7eqNRqPdbu/t7bXb7TweLzExEfowDTH+/v4qlSo4ONhut8tkMiaT6f7znTx5st1ux70PlErlCy+84HA4mEymRCKBsuJBSCqVPvnkkzKZDLZDBoDaRowY8eabb/79738/fvz49OnT4YY8qPTtDSSTydzrnEJCQng8HovFcrlc1dXVGo2GwWBAB9Ihhk6ny+VypVLJYrH6BvsSicTb2xtfikwm09fXV6lUut8Bg5BIJJo9e7Z7jhAAQEl8Pv/JJ58MCgras2dPY2Mj9eqmh7QJEya4v0k5HA6fz8cvxWIxg8Hgcrk8Hu/mzZsIoVGjRkHABMDDZ7FYrFYr3EkBoKqnn3762rVrH3/8cW9vL1zpg1NVVVVBQYHL5aqsrLx586bT6cQlE1qtFiGUlZUFARMAD9+RI0d27NiBlxTAaABAPePHjx87duxXX31VWloKAdMg0dTU1N3d7f44aDQa7rdEo9HodHpPT8/58+cRQniBOZPJhIAJgIfP5XJ99tln27Ztw6X6MCAAUIyvr+/atWvlcvknn3yCZy9gTB66uro6k8nkfqlS6dojDgAAIABJREFUqUJDQwmC0Gg0er2eRqPxeDyEUHFxMUIoKSkJAiYAHr5x48ZFRUXt379/27Zt7e3t8AAKAPXo9fply5ZlZGScOHECUvCDgVwud68fdzqdd2VLmUxmdHQ0Qkin05WUlNy+fRsCJoAQQk1NTRKJZKg37x+6RCLRmjVrRowYkZ6e/vXXX3d3d8OYAEA98+bNW7BgwYEDB8rKyiBgeuiUSqVAIMBV3na7PTs7Gx9UVVW5XK7e3t7c3FyEUEhICIPBoNPpEDABhBA6c+ZMfHw8rNh6WGg0Wlxc3F/+8pe4uLhvv/22rKzMbrfDsABAvUejJUuWmM3mgwcPQsHioEIQBG5kaLfbKyoqEEIkSbq3nA8ICAgICICACSCEUElJib+/P+yd8nBFR0enpaU1NjZ+/vnnLS0tUOUAAPWo1eoJEyYcOHDgq6++gueiwYPBYCQmJhIEQafTlUql1WplsVjx8fHZ2dldXV2QkgNg0ImLi5s6dapUKsX7KMOAAEAxfD5/wYIFCKFt27bV19dDYm6wodPpDAajvLwcv2SxWCRJQkoOgEFHLBavWLFi5cqVMpkMAiYAKCk+Pv7JJ5+8efNmdnb2UEnMtbe3FxUVeUh4x2Kx3PmWkSNHCgQCSMkBMBip1WqlUgkt2gGgsIULF3Z1dRUUFAyV5XJWq9VqtVLpvmSz2Xp6etyDf/ToUfexQqHQ6XQ9PT2nT59GCBmNxrNnzyKEIGACYJBqbW3Nz883m80waQ8AxQQEBOj1+jNnzty5c2dIXOAmk0mr1QYHB1Nm5rulpQU3WMLYbHZnZ2dTU5P74yAIgs1mI4RIkmSxWBAwATB4Xb169d133z18+HBPTw+MBgBUQhDEK6+80tvbO1SWy7W3txMEoVarKRMwMZlMPp/vfjl+/Hij0dja2ooQqqmpKS0tZbPZo0aNQghdunQpKSkJAiYABi+pVNre3r5nz56mpiZYMQcAxQKmuXPnTpo06eDBg9Cr9qGQyWR3TZiJxWK5XI4QcjqdfW+57ogWAiYABqno6OjXX3+9pqbmyy+/rK+vh64tAFAJn89/8sknnU7nxo0ba2trIWZ66IRCIV5tg2uYbDZbWVkZQmj48OF40RwETAAMUkwmc/z48QkJCbt37968eXNXVxfcUgGgkvj4+Hnz5m3ZsmUILZejKpvNlp2d7XK5LBbLxYsXGQyG3W6vr69HCDEYjIaGBgiYABjsVqxYMWLEiIMHD+7YscNoNMKAAEAlixYtmjhx4u7du2GSaYDV1dVdvXrVPeYulwsfu1wunI9jMBhKpdJsNjOZzICAAAiYABjsYmNj165dO3r06B9++KHvxtoAAArQ6XRLly6tqKg4deoUTDINJBqNxmQy3S8ZDMbIkSMRQiwWKzAwsLGxEfdQqK6uZjKZCoUCAqYHoKampry83GKxwFCAP+mqjo6OXrNmzWOPPQZ71wBAMQRBREREJCQk7Ny58/Tp0xAzDRhfX9/IyEh30TduIoC3WLDb7Z2dnQghLpfL5/MzMzPx70DAdH/Ky8uvXLliNpvxy7a2try8vGvXrvX29sLggD9PZGTkggULYHdkAKhHJpOlpaX19PR8+eWXUKo4wJxOZ1tb211jLpVKfX19EUJ+fn4qlYogCNhL7veorKz8/vvvz507193dXVVV9e9///vzzz+vqamBxwLwZ1MoFND+GwBKSk1Nff3113Nycr788kuDwQAx00AGTFeuXMHHbW1tuJJMIBBIJJLCwkL8QSQnJ8Necr+Hr6+vl5fX/v37t2/fvn79+tLSUl9f34CAgL6pUAD+VM3NzQUFBZAFBoAyGAzGtGnT9Hr9p59+WldXBwHTgCFJEvdeQgiZzWaDweD+EV4ZhxBisVgBAQF1dXUQMN33U35CQkJlZeW+ffsOHToUGxv72muvJScnQ3EJGDB1dXUfffRRdnY2xEwAUAaTyXzqqadaWlo2bdpkt9thQAYsYPLy8rp+/brL5ZJIJAqFwul0tra2ulyuiIgIhFB2dnZXVxdCiEajQcB0f+rr6w8ePCgWi5944olZs2YVFxeXl5cbjUZoxAwG8sZaXFz8r3/9Kzc3F2ImAKiBRqOlpqYuWrToyJEjhYWF8J0ykCOPc0R8Pl8sFlut1hs3biCElEolQRAsFoskSYSQQCCAgOm+A6aysrIZM2akpaWtWbMmMDDwypUrP/74I+z2BQaMSqVaunRpTU3Nxx9/nJeXBzETANSgVqtfeuklgUCwbt06iJkGjEKhCA8Pdy+Xo9FoOEmXkZHhcrlGjhx57tw5hFBXVxfUkN6foKCgl19+OTY2ls/nC4XCZ599trS0lMfjMRgMGBwwMEQi0dy5c1ks1ocffpiRkREaGurj40OZHTEB8GSBgYHLly//+9//Hh0dHRQUxOFwBsmlfezYMWpXVjU2NsrlcoIgmEwmTsa5S5PxgV6vhxmm+6PT6R555BGJRILn6CQSCZ1OF4vFsHwJDCSxWLxgwYIVK1ZUVlYeO3asu7sbxgQAanjqqaeCgoIOHDjQ1NQ0eGIUytfpXrt2DR9YrdaCggKXy/XII4/gd8aOHYsQ8vHxgYDp/tTV1e3fv3/r1q2ff/75559//tlnn/3v//7vuXPnICUHBhidTl+wYIFcLt++fTuuSQQAUACfz3/11VctFsv+/fsHT8OasWPHUnsaW6lU4gOn09ne3o4QslgsZ86cQQhlZGQghM6ePQvzIvenoqIiPT09Ojr61q1biYmJQqHQ5XLxeDwajTakz8tkMn311VdSqdT9zvTp0318fPBEGhicxGLxwoULg4ODeTwejAYA1MBgMGbOnHnt2rVdu3YplcoFCxZABmMAREdHu8c/PDwc/dT7G/00u8ZiseBjuD88Hm/s2LFjx479/PPP/f39x40bx2KxeDzeUE/uEgTB4/H6NpIe6iGgh0hMTExMTIRxAIBKuFzu/Pnzy8vLd+zYMWrUKJ1OB8+ufza73V5QUBAbG0uj0ZxOZ01NjVqtHjVqFEJo/PjxCKGkpCQImO4Pi8UiCCIvL2/UqFHV1dX79+8vLCyMjo7Gm/YN6UBw6tSpOp0OPuKhC++2jfdCgtEAYEiLi4tbvXr1s88+u2HDhv/8z//08vJ6uNc1xXazcLlcTqeTJEn3qDqdTrx/HEKot7fXvd1ZVlZWbGxsY2Mjgr3k7pdMJuvu7j537lxCQoJAIDhx4sSNGzfodDrMx4CHrre3d9euXXV1dbBRDwAUMHLkyFmzZh05cuT69esPvcXADz/8QLFVcseOHev7kk6nR0VF4WNvb2+lUom3SeFwOCRJMhgMJpMJM0z3x9fXd968eVVVVQqFIiUlxc/Pz2q1RkZGQqdv8NBZrdaNGzdWVlauWLHC19cX5vABGNL4fP7atWvLysp27tw5ZsyYAX4sr6qqunXrljtQKygoCA4OptLw3rWXOUmSMpkMH3O5XIRQTk6OSqUaMWKE+5fhlnp/nE5nYGBgUlJSfn6+r69vamqqxWIxmUzQYQw8dLh9yL59+zZv3tzR0QHbUQEw1Gk0mmefffbixYsnTpywWq0DeVFbLJa2trb2n8TExFAp108QREpKisPhcA+pzWbDx+4DrVaLf2Q0GvFyOZhhuj+lpaX79++n0Wi1tbV6vZ4kye+//37WrFl6vR6X0wPwsLBYrJdffpkkSbzgcenSpXw+H4YFgCFt0qRJ27dv/+c//ymVShMTEwdsnkmpVPadg5FKpbjhNWU0NDQ0NjbGxcXhl8ePH586dWrfg7CwsK6uLqfTyWQycRIJZpjuT1VVVXZ2No1GGzt2rEajUalUU6dO1Wq1UMMEHjqSJGNjY1999dUxY8YcOnSouLgYtvAEYKgTi8UrV660Wq379+83mUwDNsnE4/H8+nCnqyiDwWDg1BsmFAr7HhQUFBgMhtbW1ubmZh6Pp1AoampqYIbp/tBotDFjxsybN8+9zrO1tdVut8P0EhgkwsPDly1btnTp0n//+9//+Z//qdFoIJoHYEibMmXKrVu3du3aFRgYuHr1atiJ64Hw8fHx8fFxv0xJSel70NPT43Q6xWIxrrexWq0EQcAM0/0JDg4WCoUlJSU3btwoKCgoKCjIy8srKyuzWq0wOGCQiIqKmj17dmVlJVQyAUABLBbr8ccfl8lk27dvr66uhpLZP09DQ0NPT4/L5QoNDWWxWGaz2dvbGyGkVCoVCgXMMN0fNptdXFx87NgxLpeLZ5gaGxvnzZsXHh4O3ZbBIMHhcFauXDly5Ei1Wg1r5QCggLCwsPnz57/zzjtHjhxZvXr1wF/Xubm5nvD0VVNTw2Qy2Wy2UCg0m80VFRVqtTonJ2fMmDE//vgjBEz3p6Kigk6nh4eHuydFaTQam82GVoFgUMFlBzAOAFDG9OnTy8rKvvrqq6SkpLi4OBqNNpDfOxTeL7WmpqatrQ0vA1QoFGw2u7e3l81m0+l0jUaDEMJNLC0WCwRM98dgMOj1+smTJ3t5eeF3amtrGQwG9GECg1Z9fb3BYAgICGAymTAaAAxRWq32ueeey8zM/K//+q8dO3YMcBV2fHz86dOnKTmwdDqdxWLhY5VK1dvbm5OTM378eIIg8ExeTExMdXV1VFQUTNfft+rq6gsXLmT9pLy8nCRJSHyAQauuru6zzz7Lzc21WCwwGgAMXf7+/s8991xRUdGJEycGuKG/SCSi6qj6+fk5HA53xSdJkmKxGCFks9mqqqoQQmw2u6qqSiAQwAzT3Vwul8lkwom2fsOgy5cvX7hwwZ2Ss9vtS5YsUSgU8PgOBieFQnH9+vXy8vI1a9aMHj0a74cIwwLAkMPn8xcvXpyXl7d3796pU6eKRCK4lh8Im83mLqVnMpnx8fEIIQaDgXtXslgsfEB76623YLDuCpg++uijwsJCm83W29vL5/Pp9P8/rGxpabFYLAkJCbGxsZGRkZGRkWKxWK1WBwcHD+nOAt99911qaqpEIoE/AOoRCoUkSZ48efLHH39Uq9UqlarvnzQAYAjhcrlSqXTnzp10Ol2v13M4nIGJmerq6oqLi8eNG0fJdIpIJOLxeCRJ4hobOp1eU1PD4XC8vLyqq6t5PJ7L5erp6YH7Zj8OHjwoFotdLldwcLCfn1/fSCgwMHD58uV+fn7u+aTGxka73Q41TGAwmzt3rtVqXb9+/YYNG2g0Gp5ngmEBYCgaP358YmLip59+OmzYsJSUFGi09kDCUHzQ0NDA5XI5HE59fb1AIGCz2bW1tRKJpKOjA0Gn7375+flNmTIlKSkpJCTkru8Vb2/vtra23bt3V1dX4xSyr6+vSqWCfBwY5LeDuXPnvv766zU1NYcPH+7s7IT+TAAMXS+++GJoaOjWrVsbGhrgWn6AVCoVDp7UajXeKUGr1VqtVi8vLy8vLwiY+g+YHnvssfj4+MDAwJ8/iLPZ7Pz8/K+//rqzsxPGCgwVYrF47ty5K1asyM3NvXbtGrRaBWDoio+PX7hw4fnz5zdu3Giz2WBAHhS73Y6LmZRK5aVLl3AIdfHiRalUKpVKIWDqB41GY7FYv5SpDQ8Pnz17dnZ29vXr12HZERhCOBzO7Nmz4+PjYVEnAEP9SyolJWXhwoXffPPN1atXoff3g9LY2Ii7LiGEcI9v98GFCxfgvvl7JCQkhIWFVVZWUriXF6AkiUSyZs2a+Ph42I4KgCFNo9HgfeXefffdW7dueWzMlJ2d/UdqDOx2+7Fjx9z/u0ajcdczBQcH44OmpiaEkMvlgoCpHyaTqaGh4R45Cy6Xm5CQ4HK5BrgTBgB/EIvF0uv1UqkUJpkAGOpUKtXTTz+dmZl55MgRm83mmcVMHA7nj9zNCILou62Zr69vZWUlPs7NzcUH+Bfi4uLgptkPpVJZWFhoMpl+6RdIkoRmNmCow9ssHDlyxGw2w2gAMBTNnz8/Ojp63759HpvuSEhIEAqFv/vrmEajpaam9v3fa2tr8YFcLscH48aNQwix2WwImPqJN8eOHXvx4sWLFy/ilgE//53u7u7MzMyuri4YLjCk/9RzcnK2bdvW2NgINRAADEVyufxvf/ub1Wrdtm1bV1cXrJj740JDQ/GBTqdDCGVlZXV1dZWUlJSUlEDA1M+3SHx8fGho6L59+3AHy5/n5m7cuJGXl4c354MRA0OUVqudM2cOnU7fu3dvbW0t5JcBGHLYbPbkyZOnTZv26aefZmRkwJPP73Pnzh2DwYDDTY1GgyecLl68iH5K+TEYDCaTCd/3/fD29n766ad37dq1c+fO1tbWkSNH4t6VSUlJhYWFRqPxxIkTPB5v2LBh7uowAIYcOp2emppaW1v73nvvmUym1157TSqVQqIZgKGFwWA89dRTZWVl6enpSUlJWq32z7iKMzMzKTx91d7ezuPxBAIBQuj48eOPPvooQRC+vr4IoREjRiCE8I8gYOqfWq1OS0vr6ek5derU7du329vbbTbbiBEjbt26hRCy2WwrV64MCwuDpUZgqBs/fvzZs2cPHTrE4/HS0tL8/PygHhyAoSU6OnrJkiUvv/zy5cuXVSoVjUZ74DETtdMpGo2Gz+ffdaZxcXEIoaysrNjYWPwmBEy/yM/Pb9WqVcOGDevo6Dhy5Eh7e3tjY6NAIIiOjh4+fPi0adMovHsz8Bw+Pj6vvPIKnU7fuXOnj4/PU0891XfNCABgSBg5cuSIESO2bNkybdq0P2OzFKFQiLcHoSSZTHbjxo2oqCiEUHJyMkKotLRUoVDgbVJIkqyrq4OA6V4IglAqlXPmzHE4HDExMd3d3e5QFPZCAZRBkmR4ePhLL73E5XIhVAJg6H7lL168eOXKlUePHn388ccfeMxE4WgJa2xsxAET/nJvb2+XyWRcLhen5PCqeQiY/o+LFy/a7Xa5XC6RSMRiMf6bo9FoCQkJMDiAwsLCwtasWcPhcPpuNQ0AGEISExNHjhy5a9eu1NRUmUz2YLNyEREReXl5FB69yMhIfHD48OHp06cHBgbiGuWzZ88OGzbMz8/v9OnTEDD9H62trbhlKkmSoaGhvr6+4eHhUNkNPIFarYZBAGDoEovFK1euXLx48datW5977rkHGzP5+flRe/QUCgU+EAqFCCGZTIZf8ng8XNbJ4/GguvP/iIuLGzNmDG6IXl9fv3nz5o0bN5aWlvbbjQkAqrpx48YXX3xhNBphKAAYQsaOHZuYmLh58+aKigroyfT7JCYmnjx50uVyHTlyxOVyJSQknD17FiE0cuRImGG6O4j28/OzWCytra0Wi4XFYtFotOzs7KNHjyoUioiICIlE4u3tDYvjALUVFxdv3Lixtrb2mWeeUSgUsG4OgKHijTfe+Mc//rFu3bp//etfarUaGoX8Fm1tbTweD2/gQRAETiu5azrdC+hob731FgzWXeh0ulAoFIvF0dHRUVFRVqu1qamprKysqanp3LlzBoOhsbHR29ubSnXf3333XWpqqkQigU8fIIRoNFpNTc2BAwesVmtISAifz4fbLgBD5bGfIIjNmzfT6fTk5OQH9bRTV1dXXFw8btw4Sj4+FRUVcTgcHo9HEASNRlOpVARB4I5W7gOEEDw4/iKCIEiSJEkyKSlp0aJFs2fPjo6O5nK57e3t6enpmzZtunTpUk9Pj9PphJlPQDGhoaEvvPDC6NGj9+3bd/v2bUhJAzCEvrlSUlL8/f337t176dIlh8MB31C/ytvbm8PhIIRwq3SCIFwuF0EQZWVlN2/e7O7uPn36NIIZpt+IzWYrFAqtVhscHKzT6VgslkAgaGxsvHTp0rVr12g0Wm9vL4/H+zO6XwwMmGECd5HJZIGBgY2NjYWFhSEhIRKJBBJzAAwJIpFILBafPn36xo0bSUlJEonkj88QU3uGSSwW43xcbm4uh8Phcrnnz58XCAQOh4MkSYFA0NnZqVKpIGC6v8idz+eLRKKIiIioqCgGg9HV1VVQUGA0GnNyciIiInD39KFo3759DAajoaGh7CdeXl5sNhsSMZ781+7r66vX67dv315VVeXv7+/l5QUxEwBDQnh4eEdHx44dO1QqVWJi4h+/cqkdMLm1t7dLpVI2m93W1ubl5eXj4yOVSplMpkqlQtCH6edcLheew8Td5e8RMURERAQHB0dERPT09Fy7dm1Id453Op0dHR19Z8jsdjuek4Q/CU8WFha2cOHCffv2wUboAAytB5758+efOHFiz549zz///J+xWQplVFdXt7W1xcbGEgQRGxuL38T7opSWltpstrCwMKfTSaPRIGDqJ2Bav359bW3tI488EhkZqdFo7lHczWQyY2JiEEKhoaHuQvqhiM1mJyYm9u3EIxKJ4AIDCKF58+YplcrQ0NChm3EGwANpNJo333zzxRdf/PTTT5999llvb2+4pfeLwWD0bdhbXV3tXl3IZDJJkjSZTJcvXx43bhwETP3Ys2dPW1sbi8VCCPn4+PyW1XBisXhInzKNRpPL5UqlEj59cBcfH59Zs2bBOAAw5B6DJ06cOGPGjPXr1+t0utmzZ8MzT79wOyH3y6KiIrVaXVhYqNVqNRoNQRBmsxnX20BFQj/kcvmyZcumTJmi1+t/Hi1dvXp19+7dTU1NkKEAHshut8PKUACGisWLFyclJe3evbuqquq+Llu73d7bh9VqpfAo5eXlub/TdTodQshsNjscDoTQ2bNnbTYb3h4NZpj6jzenTZsWFRXVbzzOZrMvXrzY2dn51FNPSaVSGC7gUY4fPy4UCkeMGIGnYAEAg1lERERaWtorr7zy3//931u2bPntXZdLSkr279/v4+NjMBgYDMbVq1c1Gg1VR4nL5bqrkENDQ/F/caMBvDUK3nsYZpj6wWAw7tEjIDw8fO7cuc3NzeXl5dQOugH4uYsXL37wwQfnzp2zWCwwGgAMcgRBJCQkLFiwIDMzMy8vD/cZ+o0xhMFg8PLycrlcLBarubmZwvPK0dHRXl5efWu8hEIhg8HAoycQCFpaWlpbW2GG6fcYPXp0Y2NjZWVlcHAwlfp9A/CrRo0aZTabP/vsM4IgRo8ejZuXwLAAMGjJ5fIVK1ZkZma+//77TCYzISHht7QG0Ol0L730klqtbm9vZ7FYUqm0qKiI2gNVWVlpMBiio6MrKip6enp0Ot2FCxcmTJjQ29uLs0kww9QPs9nc0tJis9l+6RcYDIZQKDQajTjHCYDnSE5OXrlyZX19/T//+c+srCyYZAVg8FMqlS+99FJZWdn333/f3d39G+eKAgICGAyGXC4Xi8V6vZ7yo8RkMvFyOSaTyWKxSJLEi98zMzNlMplMJoOAqR/e3t43btwwmUwwFADchcfjqdXqJUuWNDc3r1u3LicnB3JzAAx+c+fOnTdv3uHDhw8cOPDbE3OeFlaGhIQQBKFWq4ODgzkcTmJiIkLIy8vrzp07VVVVEDDdjSCI5OTk8+fPf/zxx1VVVf3+YZnN5rNnzxoMBhgu4IFYLNa8efPWrl3b0NCwZcuW/Pz8e0zHAgAGAwaD8eSTT0okki1bthiNRljo+kucTqfZbHa5XGaz+eTJkwihUaNGORwOu90OAVM/AdOoUaP0ev0333yzfv367Ozs9vb2u8Km4uLi3NxcOp0ObS2AZxKJRLNnz/7HP/4xadIkoVAIZUwADH5BQUFvvvlmZ2fnpk2boDOOwWBobGx0D4LD4SgvL3e5XFar9fz58+inzdAQQqWlpUqlUqlUQtF3P+Ry+aJFi6xW6759+/Lz8x977DGNRtN355MffviBxWINGzaMy+XCcAHPxOPx5s6dC+MAwFDBZDLHjRs3efLkf//736GhoTNmzPDkZ36TydTc3CyXy90B0507dwICAkiSxCXe7pRceXl5cHAwgj5Mv8Tf33/p0qVCofDs2bNff/21xWJxx6EsFqurq2vVqlURERGwRA4AN7PZbLfb+Xw+7NELwKC1dOnSmpqanTt3RkZGBgUFeez0sEAgsFqtdrudTqcTBEGj0QIDAxFCdDo9JCQE39Byc3MnTJiAC95Pnz4N97VfpNVqV6xY8eabby5fvlwulzN/EhMT85e//OWJJ54QiUQwSgC4HT58eP369VDbB8BgFh4e/swzzxQWFv7rX/+y2+0eOw7u7kr4JY1G8/f3JwjCarVeuHAB9UnJ4RpNHo8HM0y/iCAI3NE4Li4uJCTEvWguICBAp9PB3BIAd+nt7f3mm298fHzGjx+v0+n6ZrEBAIMESZIJCQnPPPPMjh07cnNzk5OTPXZKWCQS/XzHApIkZTIZ6pOSu3PnTkhIiMvlgjvar6PT6cnJyTAOANzbpEmT6uvr9+zZk5eX98YbbwQHB8OqCAAGIV9f32XLlv3www/vvfeey+UaPXo0Tkt52jj0bS7V1dWF168wmUyhUFhUVBQWFtbd3S0UCvGvuVwuSMkBAB4MPz+/JUuWjB079vz58x9++OHNmzc9ecIfgEF+ta5evbq6uvrtt99ubm6GATl37pz7GDeu7O3tvXLlCkKop6cHIRQbGwsBE0D5+fnBwcGw4g88kCfX5cuXp6WlnThxYsOGDSUlJRAzATA4zZ0796WXXqqvr//2229h1wr3cjmEEG5cSafTcW6upqYGIXTt2jUImAA6c+ZMfHy8QCCAoQB/nFKpXLJkSVpa2pUrV8rKyiBgAmBwYrPZ8+fPT01N3bp16969e00m0z06M3V0dFB7NGJiYjIyMvqOQHd3d1RUFEIoLCwMIUTC6l+AEGppaZFIJAwGA4YCPBC+vr6rVq164403wsLCoPQbgEFLKBSmpaX5+Pi89957ly9fvkfAdOHCBWo3uiQIAq98LygowGeK18ohhDQaTVNTk0KhgIAJAPDgyeXy+fPn6/V6CJgAGMySkpKef/7527dv796922Aw/FJUpFAoqD0ODAZj9OjRBEHU19fjd/z8/BBC58+fNxgMRqPRarVCwAQA+HN1d3c3NDTYbDbYvgqAQSg1NXXhwoVnz57dsGHDLxUz4Tof09nrAAAgAElEQVQeTxAREYEPNBoNDqQIgvD29vb29oaACQDw58rLy3vrrbdycnKsViuMBgCDjUAgSEtLY7FY+/fv/6WAqaOjQ6vVekLrgba2Nnxw8eJFhFBsbCyNRmtoaBCJRBAwAQD+XCRJMhiMzz77LDc3F2ImAAbhFapSqeRyeXt7e25u7l2bzWM2m238+PGeUPfc1NSED5RKJUKIyWQ6nU7cEBwCJgDAnysuLu7VV1+NiorauXPn3//+97KyMljDDMCg4uPjs3LlSm9v73feeefatWs/j5kqKyt1Oh31ZpjsdvuRI0f6Vgu4U3JRUVHt7e0IIRaLFRwc3NbWBgETAODPJRKJdDrdsmXLgoODDx48+MEHH0BPSwAGFYFAMHfu3L/+9a9NTU2HDh3q7e31kIpD9+K4vrFjYWGhy+WyWCw3btxACDEYDLlcXlhYCAETAGAgyOXytLS0FStWHDly5OTJkxaLBcYEgMGDTqfPnTt32rRphw4d2r9/f7+JOeqh0WjJycl9Z84cDgeeWKLT6Xih3JEjRxBCvr6+sOIXADBAlEplWlqayWRyOBwecjsGYAjhcDgLFizIz89fv349QmjOnDkCgcATCr0vXLig0+nkcjlBEAwGA3eqbG9vDwkJQQjx+XyEUEhICMwwAQAGjo+PzwsvvDBlyhQ2mw2jAcBgExkZ+Y9//EMul7/33ntffvmlxWLxhNwcj8dzt26m0Wg+Pj4EQVy9ehW/k5ycjA8gYAIADCi5XB4eHg6d5QEYhEiSHDVq1LJlyyoqKtavX9/d3e0JZx0dHe3l5YXn0g4fPoxjRNyH6ezZsyaTqbi4uLi4GAImAMDDtG3bto8//riurg6SdAAMEmPHjl28eHFDQ8O6deuam5spP8nU1tbmrnMXCoX4zcjISIIgeDweSZIsFovFYkHABAB4mCorKzds2LBly5bGxkaImQAYDLy8vN54442nn376888/P3LkCOUvzIqKCoPBgI9TU1MRQjdv3jQajS6Xi81mkyTp7+9vNBqh6BsA8DDNnz+/oqJi7969FoslMTHx0Ucf5XA4nlBnCsCgRRBEUFDQmjVr9u/fn56e3t3dTe1lrT4+PhwOByHkdDrxzcdkMuHWJ3iRCkEQRqOR9tZbb8Efh4c7depUWFiYr68vjUaD0QADTCaTBQUFKZXKq1evZmRksNlsnU7HYrEgZgLg4fLy8rLb7VlZWVlZWVwud8mSJVT9jhCLxfiec/78eS6Xy+Vy+Xw+n88nSZLP57NYrNbWVl9fX0jJAQAeJpIkY2NjV69evWrVKjabvWHDhoqKCmgFDsBg8Pzzzz/zzDMOh8ND+lgKBAI6nY5DKLztrkQisdvtpaWlUqkUAiaAEEL4erDb7Q6Hw263w67yYOClpKS89tprjz76KI/Hg+klAAYDsVi8bNmy8PBwD7kkY2JiJBJJRUVFQUFBd3d3ZmYmQojJZKpUKoQQ1DABhBBKT0+32WwlJSU+Pj5Wq3XChAl3dYsH4M9Gp9PHjx8/fPhwiUTiCXt8AjAk+Pr6vvLKK++//77nnDKLxXK5XCRJCoXC+vp6Ly8viUTS2dkJdyWAEEJ1dXVXrlwpKirKz89vamqChAh4KNhstq+vr7uAqbe39/jx42VlZbDxHAAP0bRp01gsFiVPLTc3F2dUbDbbpUuX8LFKpQoKCuJwOCNHjqyoqOjt7W1paWlpaYEZJoAQQnPnzg0ICBgzZgxCSCqV4k7wADxcJpPpk08+USgUr7/+ur+/PyxKAOChsFqtVK3TMJvN+MDlcuFjp9Nps9mYTCZ+bFOpVCwWC6dcIGACCCGk1+tjYmKg+TIYVDgczrBhww4cOOByuf7yl7/o9XqImQAYeKdPn7ZarZQ8teHDh+MDOp0eGxuLELJYLNnZ2Y8++mhFRYVOp/P390cI3blzBwImAMDgxePxVq1aRafTt23bRqfTU1NTJ02aJBaLoSQcgIFUWlpK1ToNiUSCD0iSFIvF+EAqlSKEbt++rdPprl69qtfruVwuBEwAgEFNoVAsXbqUw+EUFxdv2LDhzp07y5Ytk0qlEDMB8Odpb28/cOCAO0g6f/48tQtbL1y4oNPp5HI5QRAsFishIQEhFBgYiBCyWq1Op9PPzw/B5rsAgEFOpVItX778hRdeCA0N3bt3b05ODlWzAwAMEjQaTSaTef9k4sSJTCaTwufL4/FwRUpdXZ3ZbHa5XDU1NbiVQEREBJfLLS8vLy8vhxkmAMBgJxaL4+LiXn311d27d/v4+EDTAQD+VCKRaM6cOX3f2b9/P4XPNzo6Gh/U1tay2WwOh1NbW8vn89lstkAgwBEVgpQcAGCoiIyMXL16tVKpxK14EUJms5nFYpEkCRk6AMAfp1Kp8KZyGo2GzWaXlpbabDatVqtWqxGk5AAAQ4hWq3VHSy0tLZs3b758+bLNZoORAQD8cUqlkslkVlRUKBQKDoeDZ5tOnz6NfwoBEwBgSOro6Dhy5Mj777+fnp5eWVkJ3VYBAL/b6dOnca8pu91eXV2N39RoNAEBAb6+vhAwAQCGMG9v70WLFul0um3btr3zzjuVlZXd3d2wDSIA4Hdwp/XpdDpeH/ftt9/i+0l9fT1C6OTJk1DDBAAYkiQSyRNPPDFu3DgWi3X58uW333572LBhCxYskMvlUBUOALgvw4cPv337tl6vp9PpGo0GIYS7MaGfejWJRCK4rQAAhioul6vRaFauXPnGG2/09vZu2rRp8+bNMM8EALhfHA6nrq4OIdTb25udne1yuVJSUvC0U2pqKkIoISEBZpgAAEObWq1Wq9V8Pv/UqVMymQxWzAHwYHV1dTmdTmqfI0mSwcHB+BhvwdTZ2SkSic6cORMXF9fQ0EAQBARMAAAqGD58eHh4uMvlwpsYAAAelLy8PLvdTu1zpNFouHcAk8mMi4tDCOXk5EydOlUkEtHpdNxrAFJyAACK3O/4fL5AIHC3ZWpsbNy3b19NTQ0soAPgj/D19fWcukCSJDkcDkEQCoUCP4nx+Xy73W632yFgAgBQU2Nj4+bNm//nf/6noqLCaDRSPqcAwJ8kJibG3f+MGlwuV3t7e99iR6vVevToUZfL1dPTk5GR4XK54uLiCII4ffp0Z2cnSZI0Gg0CJgAAZR+LExMTq6ur33rrra1bt7a0tEDMBADAcnNz+74kCAKvhiNJUiwWu9/HKTmNRqNWqyFgAgBQNmBauXLl2rVrzWbzZ599tmnTphMnTlgsFhgZAADeW9eNwWCMGjWKIAgWi5WUlEQQxA8//OByuYYPH37u3Dk6nZ6bmwtF3wAAysKbQHG53JycnPPnz+fl5fF4vMTERLwzOQDAMxEEERsb2++PWlpa8GJbNpuN38EV3ywWC2aYAABURpLkiBEjXnzxxWXLlgUEBPD5fOg7AADoq7y8vKurC5c0Xbx4Eb8ZHx9/69YthNCoUaMQQnFxcTDDBACgfszEYrEeffTRwMDAgIAAipWvAgD+oK6uLqFQiI9xcwF832hra0MIWSyW3NzcRx55BGaYgIdyOBynTp0ymUwwFB6CTqeHhIT0TcZt3Ljx888/v337tsVigebgAHgsrVYrEAjwsV6vx9VLTCZTpVIZjUaSJHF3N3jSAh6KIAiRSIQ7ugLPVFZWVl5efvLkyVmzZkVERISFhUFtEwAeyMvLy33sXiVHp9MdDkddXV1ISIifn199fT3MMAEPRZJkfHw8ruYDnunZZ5998skny8vLP/jgg/fee+/GjRuUb2cMALg3Fovl4+NTVFTkcrlEIpFYLCYIwmq19vT0wAwTAMBDRUdHBwYGCgSC/Pz877///qOPPgoLC3v55Zfdk/MAAA/x7bffzpw5E68IYbFYOEfv7e19+vRpNpstl8sRpOQAAJ6Mx+NNnTr1kUceiY6OzsrKqqqqgn1UALjLtWvXbDYbtc9RKpW6j5VK5c2bN00mE5/Px40ru7q6IGACAHg6kiQFAsHMmTOjoqIMBgOPx4MxAaAvg8FA+VURiYmJx44dmzJlCkEQBEF0d3fjZ6fhw4cjhJqamiBgAgCA/ycgIKDvy66urpaWFo1Gw2AwoHUT8GRSqZTym++6t0bBgoOD8bPT6dOn4+LifH19EUJQ9A0AAP24fPny22+//fXXXxcWFkIxOPBkTU1NlN+H0b01Cn5ZX1/f29uLftpLrr29vaOjA2aYAACgHzweT6FQbNmyRa1Wx8TELFmyRCgUkiQJs03A02g0GsrPMGE5OTkhISEymcxsNuOUXGxsLEmSkJIDAIBfFB0d7e/vn5GRUVBQcPz48dLS0uHDh48cOTIsLIxOp0PYBDyHXq/3kP74AoEAN2Nzp+SysrLi4uJwAxpIyQEAQD94PJ6fn9+SJUtefPHFF198sbOz8/vvv3/zzTcNBgMMDgCUFBMTgxsvicXiK1euIITEYjGdTjeZTCaTCWaYAADgXgICAgICArRa7Y0bN27cuAHd4QGgDJfLZbPZ3As73Ck5vFAOIRQXF4d+ajoAARMAAPw63OVy4sSJ7raW3d3d1dXVLpfLcxIWAFCMw+E4ceLE1KlT8Ut3Ss4dKtXV1clkMplMBgET+H+uXr0aFBSEN9ABAPSLx+P17dJkMBj27Nlz69at2bNnczicUaNGeXt7e0htLADUQBAEDoawmJgYfHD9+nWdTocQqqiooNFodXV1w4cPh4AJIITQgQMHWlpahEIhfpmcnBwWFsZisWBkAPglfD4/PDzcZrNt2bLFbDaPHj06ISFh8uTJsJgOgKGCRqMlJia6X1qtVhqNRpKkzWbDnRQ0Gg2TycSNziFgAgghlJKSEhgYyGQy3U/S8KAMwL0JBIIZM2aMGzcuIyMjJyfn6tWrZ86cyczMnD9//tixY91XEwBg0HI6nXfu3NHpdPgJ59KlS7iGic/n4zy7Vqt1OBzh4eHV1dUQMAGEEJo8eXJMTIw7dwsA+C1wku7ZZ58dNWpUcXHxgQMHjEZjSUlJcnIyBEwADH4ul6usrAxn3xBCUqkUX7kdHR14w90rV66EhoYKhcL8/HwImAAA4I/S6/WBgYGBgYF2u51Go7mfPW7dumU0GoOCgjgcDpvNhjwdAIMKQRBBQUHul+Hh4fhArVbj7fMcDgfOzcnlcgiYAADgAaDRaBEREXe92dzcvHPnTpIk9Xp9SkpKTEwMh8OBsAkMcj09PcXFxX23Q8Ftr6mHJMm+m0jW1NR4eXlxOByVSnX48OHp06dHRETU1NQIhcLa2loImAAA4M+i1+uDgoIuX768adOmzMzM2bNnSySShIQEnU4H/ZzAoNXb23vjxg13wJSTk9PT00PJM3U4HDk5OSkpKfgxpr6+nsvl4r7eeMNdPp9/586dsLAwb29vCJgAAODPgnuFT5w48fjx4xaL5fDhwx0dHeHh4e+++66Pjw9MNYHBicPhDB8+HOekcPxUWlpKyTN1nyOm0WjcYaI7PRcSEoIQCgwMhIAJAAD+3JhJLpeHhIQ4nc7Tp09funTp6tWrvb29LpcLAiYwOLHZ7MjISPdLnU73zTffUPJMaTTa8OHD+16tOBOHEDp9+vT06dMrKysVCgVCKC8vDwImAAD4c5EkKRKJEEJz5sxJTEwsKSnx8vJyR0slJSX5+flCoXDcuHHQ/AwMQnw+n6rBPUEQfD6/7zs4PHIf1NfXe3l5sdlsHx8fCJgAAGDgKJVKpVLZ952ioqJt27bR6fScnBwGg7FkyRIulysQCJhMJkxBATDA4uPj+x7odDqr1ZqZmTlx4kQImAAA4GEKCwt75plnGhsbz5w5U1hYWFJSwmQyH3vssdmzZ8OEEwAD4+bNm2FhYe5HlMrKSrlczuFwFAqF2WyWSCQIOn0DAMBDD5jCwsIMBkN8fHxmZmZtbW1BQYG3t/f06dMhYAJgYNTU1ISFhblfNjU1icXipqYmm82m1+vj4+NzcnIgYAIAgIdPKBSmpqYGBQWZTKZbt265Ow4jhCwWS2ZmZkFBwYIFCzgcjkQiYTAYkK0D4AFyr4k7dOjQrFmz/P39ORyOwWCg0Wjt7e1SqZTBYEDABAAAgwUub9LpdCRJuhs1NTc3Z2dnFxUVFRYWkiQ5ffp0X1/fgIAAPz8/aOYEwAPR2dmpUqkQQjKZDP3UhAnXfWdkZMyYMYPL5ULABAAAg8td+9DxeLzp06ePHz/+0KFDubm5xcXFPB7v/2PvPqPbuM68gd9BLwRIdAIg2MHeiyRKooqpYnW5RLIj23GKE6/jtXO8Pkl2N3mze5LdFDuxZW9ix92WZKt3qrOZpCiKKiyiSIgUQRKsIECA6H3eD3czB4ekZNkr2xLx/D7oDAcgCA3K/OeW5xYXFxcWFj766KMcDgeOGAD/R6Ojo7iSQnl5OUKoqakpIyMjJiaGIAiNRoMQmpqagsAEAAD3NLFYXF5eHgwGtVpta2trT09PMBjU6XSHDh3asGEDFZisVqvP55NKpTQaDQ4aAF8K1SWH4Y+VxWIRi8U4MKWmpkJgAgCA+wCdTk9OTtZoNIFAgCTJa9eujYyMhDcvHTx48OrVq3ioOI/HKygooNYABgDcntlsDq/3kZ2d7fP5mpubKyoqmpqaNmzYYLVaITABAMB9g8lk4hg0b968mTe5XK7f//73oVBIKBSuWbOGxWKJxeJ169bBbDsAbs9oNOKNysrKtWvX4m5xPIYpPj4eIWQymSAwAQDAXPDggw/m5+dXVVX5fL69e/fu3r2bIIiUlJSVK1dCYALg9rKzs/EGVfjbarVmZGQghPLz851Op1qthsAEAABzgUwmk0gkeKHQ7Oxsh8NBkmRMTEx4Wuro6DCZTKFQiCCIxYsXTxtdDkDEolZEKSsrwxsXL15ct25dV1dXQkLC0NAQgsKVQK/XR0dHC4VCKOsCwP2ORqPheLR+/fpZ77Bnz56GhoZAIEAQxKOPPorvHBcXt2rVKghPACCETp8+jT8+CQkJCCGr1apWq2NiYiAwAdTT0yMWi2NiYqCgCwBz3rx58yQSSTAYJEmysrLS5/ORJJmQkLB06VIITAAghPA62Qih3NxchJBWq+VyuUKh8OzZsxCYIp3L5cLDSKGFCYA5b926daFQCCFEkqRWq/X5fIFAoLu7O7wSQWtra3Z2NsywA5Fp0aJFCKGuri6NRsPn88fHx7lcLpPJFIlEEJgAACBS0Ol0qi158+bNCKFQKNTT00ONc2pqanrzzTfnzZuHA1NKSkpFRQWEJxBRnxGEkN1uDwQCeCMYDCKESkpKIDABAEDkotFoeJw4JhAIysrKjh8/7vP5EELR0dEnTpyg0WjFxcVbtmyB2XZgbquvr8/IyJBKpampqTweD/2jS+769esEQUBgAgAA8L+ysrJSUlISEhJwYNLr9fX19YFAQKVSkSRJ3a2urs7lcuGANX/+fGiCmtuuXLlSUFAQCcM2oqOj8ZtZLBYjhEZGRgKBgEQi4fP5CAZ9AwAAoNBoNC6Xu3HjRvyj2Wxevnx5MBiUSCThqejNN98cGhrCZQtWrFiBB4wXFBQsXLgQwtPcs3v37i1btsz5JXdIksQDvXt7e10uV15entfrDQQCBw4ceOSRR0KhEAQmECn0ej2Px5NIJAwGvO0BuCMSiUQikczcv3nz5qmpKZIkp6amzp49i0d7MBgMqrWJJMne3l48+IOKYikpKTAb937U09Oj1WrnZAuTwWCIi4vD/zW9Xj81NVVQUMDj8fAbVaFQkCQ5Pj6OEDp37hycOUCkqK6uZjAYDz30kFAohKNx3xkeHg6FQkqlEvLuveCJJ57AG/gE4/f7EUIpKSlU8xJJksePH8c1n/AeJpP52GOPsdnshQsXisVimJYL7gUdHR1xcXF4m8vl4jmkeFE5j8fT3d1dVFS0ePFifPEAXz0gUvD5fJ1Oh0dmgPvxey0UCslkMghM95To6Oh169bN3E8QRGZm5tjYmN/vJ//h9ddfDwQCb7/9NlX4rbu7+8yZMzhvPfDAA5mZmVQTFIPBgFAFvm4pKSnUtlKpxFk/EAjQ6XSSJN1uN0IId8mZzWb46plrSJK8efOm1+slCCI5OTl8MfMIp9frIS3dvyYnJ0OhEL7+A/c+giCWL19eUFBAkmRXV9fIyMjChQurq6v9fr9CoaCS0Ojo6KlTpzwez9TUVFVVlUajwQNlFArFL3/5S+rry2Aw2O12kiQ1Go1AIIAgBe4WaopoMBgcHh7WaDQej6empgavXY0XmFMoFAhamOaevr6+7u5uo9EYCARaW1vXrFmzfPlyPDcSyGQyj8cDxwGAbwabzY6NjUUIXbt2zWg0KpXKH/3oR9Puk5aW9tOf/jQYDPb29jY2NuLBIgghOp0eHo4//fTTCxcuBAKBioqK+Ph4avRxWlpaeno6jIsC/3fBYFCn02k0GjqdLpfL29vbk5KScNVv3CVXXFwMgWnuCIVCzc3NH3300T//8z+rVCqPx/PRRx+FQqGKioqvIzOdOHFi0aJFVBX526irq0tPT5fJZLf5XvP7/XQ6nSCImdeOJEn6fD4ajTaziR63nc7cP+ujjY2N4TVH4a2CEPL5fHdY3p0kSb/fD7XgwddBrVbj8SJms/mBBx6gQhKHwwmv+aRWq9PT04PB4Llz5yYnJ3GBA7Va/ctf/pK6j9frfeutt6hW5PLy8ry8PBqNxmQy8bcBHG1wG3Q6PTk5GSHEYrFKSkouXboUCoV0Ol0gEIiPj79w4cKqVasgMM0dBoNh7969iYmJxcXFSqUyISHh+PHjZ86cycvLoxq676JTp07l5ubeSWCqr6+32+3Lly/HpSxm9dlnn61Zs0Yqlc68KRAIfPjhh2q1+oEHHpj2CHiGzsqVK/HKiJQDBw4sXbo0vOUfIYQ7Bb71ynvj4+NRUVFcLveuvCJGo5HH4/F4vC/7aJ988sl3vvOdO3n5/H7/rl27Hn30UYFAcJv4ZTKZ5HL5rAOMzGYzg8EQCATTnqTD4XC73WKxeFqS9vv94+PjsbGxMFwpctxqOh62YcOGVatWkSTZ3Nw8Pj6OcxWuLki9qQKBQFVVFR50ghC6dOlSdHQ0QRCPP/54eXk59V6anJyk0Wj4JjjsIDwwyWQyk8kklUoJgkhPT+dyuXw+H1+T4zcnfB/NHSaTqa2t7Ve/+hU+sYlEok2bNn388cc3btyIjY2960GBKhj/hZxOZ09Pz6JFi24TmOrq6hYvXjxrYCIIwuv16nS6mY/gcrkuXLiwaNGiaYGpsbExPz9fLpeH7xQIBA6H41sfBHPu3LnCwkKtVntXAtPnn3+u1WozMzO/7MqpVVVV69evv5PA1NjYePr06XXr1t0mMJ0+fXpgYOB73/verPe5cOGCRCIpLCyc9ibU6/XHjh3btm3btEBfU1PT0dHxzDPP3IPzGS9cuFBYWMhise7K6balpSU7O5vL5X6pR/N6vdeuXcvLy7uTikfnz58vLS2932sjUW9UqkDUTCwW6/nnn6cm5V24cKG7uzsUCk3riL906VJHR8fMa8j169ez2WxIUZHm888/Ly8vx6+7xWKx2+1SqXRoaMjj8aSkpGg0GirQ9/f3Q2CaO3w+X3gaoNFoubm5Y2NjZrP5DpPN1ychIeErr4VOkuTExERUVNSX+i2v1xtemBghpFAohoaGvvVx3z09PUlJSdOe21fW19cnFou/1hR4J28eh8Nx/fr1Wx3bwcHBQCAw80lOTk52d3d7PJ5pR8Nqtba3t+OZU/eUq1ev/vnPf37rrbdu0xbypRw5ckSj0XA4nC91nna5XMeOHUtPT7+TGLRv377c3Nzb3NPv91dWVq5Zs2bWa6quri6fz5ednT2zte/q1atcLler1U5rINy/f/+GDRu++aZcJpO5evVq6seCggKTyUSSpFqtxtnI6/UyGIyxsbEdO3bMDKnLly8Pf8579+7t6+ub9s5MSUl5+OGHqUPhdrunvasJgsCH+jZT/ILBYDAYvJM+7lAo5PP5bh/jgsFgIBC4Wwk+AoV/v8XExHC5XHzkcdTmcDhVVVUlJSX4hYbANHfs3r17cnLyK/zi6OhoR0fHbdoPZmU2m69fv26xWL7wnuPj4263+/r16wwGg8VipaamfqkvU4IgxGLxl8189fX11JA9TKfTpaamzr1env7+/tLS0q9vOuSdTEqKior6ag1mdrt9ZrQ1m8335mw4gUAwPj5+Fy8/DAbDV8iFgUDAYDDc4dPQ6/W3P5jBYLCysvKBBx6Y9VN548YNh8ORkZEx84PT3t4uFouTk5OnBabDhw+vXr36W+/7pkZHUfbs2fPggw/OmzfvxRdfnHn08JmS0traikexhMeXzs7OjRs3UofilVdeMRgM4e9eoVCYn5+fnp5eWlqKD4vL5erp6Ql/nNHR0aGhoeLi4sLCwtt/amw228GDB5966qnbfGuNjIw0Nzdv3rx51vuMjo4KBAI+nz/zI2wwGKRS6bSwjisPxcfHi0Qiar/RaMRFSufkebOoqIjajo6OHh4edrvdCoUiFAqdPn1606ZNuNaxSqWCwDSneDyer3CaUavVeG7dl00SSUlJ+/btKy4unjmiHHc0UPvlcvnExITH42lvb09MTGxra5s5+luv11dWVk7rRKNYLJbh4eHDhw9P65KzWCw6ne7YsWPTuuR6enrsdrtAIAj/EmxubhYKhcePH/9muifKysrUavU3MH9nYGCA6ob4OphMpi98X01OTn61GDE1NTVz6uLExMS33iZ6qyv+eyHJnT9//i42v5EkiWfsz3qrz+fzer2zvnDNzc1Lly6dNQTfmyfX+vr6hQsXpqWlZWRkfOGdH3744SVLloT/R/x+/40bN8IjzqlTp1QqVfgePI6KTqcXFxfjz/7o6OhvfvOb8GNosVjMZnNKSsrhw4ep65z29nadTjft3WW1WhsaGrZt20Z9Odvt9tOnTweDwfLy8vHx8fz8fLPZvGvXruLi4oSEhJnxq6qqymaz/Sk0F1kAACAASURBVPjHP5759X78+PEHH3wwMTFx2rXKBx988Pzzz8fExFCBaWJiYmpqaq6eN6cNSxgaGuJwOLiwKg5JhYWFTqezra1t/vz5EJjmjnXr1lVWVn7Z30pPT4+KivoK379FRUVXrlzJysqaGZhCoVBOTg61v6SkBG+wWCylUjk1NRUIBM6ePbtgwQKqWWv9+vUtLS1Lliy5cOFC+H4sMTFRqVTW19cvWrQo/KaoqKgVK1bM7K1bvXq1RCKZ1gn45JNPKhSKb2wwx8mTJ2c907S2tjocjubm5ruSpVpaWoLB4DvvvDPt+vhO2jbef//9O2lWvHnz5tDQ0Pvvv8/n81UqVXl5+czWrCtXrjidTrvdPmvs9ng8LpfLZrNN67NzOp0jIyNGo9FqtTKZzJMnTy5btozL5d64ccPtdp86dSonJ0ev1weDwZSUlFOnTpWWltpsto6ODjqdHhMT09PTU1xcXF1dLZFIZDIZm80eGhoaGxtbuXJlV1eXTCZTqVRXr16VyWRdXV3Lli3jcDj9/f02m62/v3/VqlWXL1/GVwuhUCg1NbW/v9/n85WWlo6OjjIYDLxEOY1G8/l8dDqdTqf7fD6PxxMIBAKBgNfrZbFYHo+HRqPR6XS/38/lckmS9Hg8BEEwGAy/3483cJZlsVg4Avr9ftxZgzf8fr/T6cRdReF/CG/4/X48OZQkyVAoFAgEmEwmSZJOpxOfyJ1OJ34/Uw9LdfQEg0G/389ms3HPglAohC6bL4X61gpviisoKAh/h0dFRf3iF7+YOTIvPLtwudzCwsLwL9i//e1vmZmZRUVF4fmGJMl9+/aNjIyERzSfz5eamhr+4B999NGOHTuYTGZ9ff3o6GheXp7RaGxqaurp6YmPj6dCm9PpxNvXrl2j0WhTU1P47RHeWtzV1VVQUEC1JOE3ktPprKmp2bp1a/jfFYlEtxl+Ogf4/f5QKIS7NTUaDfUSzJs3b9pXFgSmuUOtVn+FcUJCofCrDa0lSVKr1XI4nJkn/pSUlFn34x4xl8sVCoUkEklmZmb4af7KlSuZmZmJiYnT9lPS0tJuddM9qKura9a2ma1btzIYjLvVM4hHVHyFR3v22Wd5PN6dnEQ1Gk1paSm+s8fjOXjw4Mz/1MjICJ1OP3jw4KwdMXq9fmxsbGJiYtpbYmxsTCqVNjQ06PV6Go3W0tIyMjLCZrOnpqZYLFZ1dXV3dzfuAlOpVKOjozdu3NizZ8/o6CiNRuPz+SMjIzqdrrW1VSgU4jXGTSbT5OSkyWQaHBwUCoVSqbS3tzc6OnpwcHBkZITFYo2Pj7tcrrGxMZPJ1NPTI5VKR0dHQ6GQSqUyGo1+v7+vrw/PoiJJMikpKSYmpru7W6FQSCSS69ev4y65s2fPer3enJyc2traqKiouLi47u7upUuXEgTR0NDAYDASExN7e3tpNFpSUpJerydJMj8/32Qy4bZPjUbD4/F0Op1KpbJarW+99VZGRoZUKu3s7JTL5QqF4tq1axKJRKlUdnZ2xsTEJCQk+P1+q9VqMBjS09O9Xm9jY6PRaLx69Wp9fX18fDxBEH19fXiYILVYm8Vi6e7uLi0t7evr+/DDD5cuXTrrm0SlUk1rnZ1pcHDQ7XZPGyVDp9Pv8P0zZ9DpdCqU/O/pk8HIycmZ9o2ECyFSYUgul7/wwgvhMYhGo3k8nhdffDH84k2r1W7bto2qmEC1MFVVVU1MTKjVanyo5XJ5dnb2okWLjhw5YrFY6uvrcTYKz156vf5Pf/oTDuhXr14VCAQjIyM0Go3D4Wzfvj38j7766qtUkk5LS0MIKZVKtVqtUqmoV7a1tfXy5cuDg4NztUsOtwKaTKbCwkL8iTh8+PCmTZsGBgbkcjnuNM/IyMjJyYHANJcFg8GLFy/GxcUpFIqvY+AOQRC3uuy41X7c5oRT3YoVK6bdivdMG3Yw8w73i0WLFs29N9XExMS1a9dmDu6edh18h7empqbiinDT7vb888/PvDN1z2n9KZmZmTPvnJWVRYXs8Nci/JlQ95nV2bNnR0ZGcO9JIBCw2Wxms9nv9y9evHhsbMzlctFoNJPJ5HA4cEmFrq4uhJDRaMQVF41GIz6HGY1GkiRv3Lhht9sRQniUIZvNxqfGTZs2dXd3j4yM2O32yclJ3DZgNptxa5bZbHa73YFAIBgMOp3OycnJgYEB3JiUmZnZ09NjNpvxic1sNuO2KNzohZsKRkdHOzs7582bZ7FYOjs7Z23R7OrqCoVCAwMD+/fvn/VSpLm5ua6uTiwWSySS8HhktVrPnTvn8Xg8Hs+0r5ehoaF9+/aFP1pHRwcuevJtTdbj8Xh4/Za6urr4+PivPAHlTky7ZmAwGCKRaNodCIIIHySEn+GmTZtmnsjffPPNS5cuKZXKwcFB3I2Ql5eXnp6elpaGZ0v09fW9/fbbAoGgtrY2NjZWJBIFg0GPx4MDEx4Pjhd+mPlUvV4vbhNFCF28eBEhZDKZqGZR7L//+7/b29sHBgbm8LmSx+OFv0Z4abmRkRGhUCgQCILBYE1NDT77EHM4NkaakZGRn//856FQ6E9/+lNcXJzFYtm6datWq/35z3/+ddRhAmAO6+3tnbVH9e5SqVQTExPf4nxAo9FoNBqHh4eVSuWsXxE2m21kZCQxMXFaP6zX6+3v74+NjZ3Z2WcwGKiJaZjT6fR4PN/igrvBYNBsNh85coQkybVr196t3LZz586tW7d+2UfbtWuXUqlcunTpF3bK2+327du3r1q1qqSkBAem8CrnVDPtgQMHNmzYoNfrZTLZww8/rNPp8vPzjx49umHDho8++mh4eHjbtm1Wq1Wv16vV6sLCwoGBgezs7JdeeumJJ574/PPPlyxZ0tvbazabeTyew+E4d+7cG2+8YTAYAoHA0qVLf/rTn3I4nLa2NoPBEFHFq3DXPK7JVFNTs3z58jNnzkAL09whl8vXrl37hz/8ob29PRgMfvbZZ1Kp9OGHH1YoFJCWAPhSbt9mdhdNa374hqWkpMycpTj3eL3e5ubmH/zgB4FA4MtOB76NF1544SsM7nnuuedYLNadTGslSfKVV17hcDgsFgsPQJ4ZznANdC6Xi8dX6fX65uZmgiDGxsY6OjrwoLfe3l6Hw2EymTQazcmTJ8fGxm7evMlkMkdHRy0Wi16vz87Orq+vLy0tHRwcZDAYJpMJLwxy7NixZ555pqWlpaKiYs4vS9rV1ZWRkUElQqVSeeTIEVz3Cw+TlUgk0MI0pwwNDX3yySfp6ekajaaysnLp0qVlZWX3y6AfAAAA/xetra14tNxMdDo9Kyvr2rVrM0/6BQUFbW1tGRkZer0e13BxOBxqtbqnp6egoKC1tTU3N1cmk83t5qXTp0+vWrWKIIizZ8+uWLGCIIjLly8XFRURBHH69Glc4gsC01wzMjLi9/s5HI7NZouPj//Wq6EAAAAA9xSSJKempsI7GQcHBzUaDUEQtbW1S5cudTgcXC4Xr0I4ODgYHx9/5swZCEwAAAAAiKzAdOzYsQ0bNsxsNnO5XFwut6GhITs7G5dlF4lEg4ODNpsNhrYAAAAAILJQ68RNg+tlyOVyFotlt9ttNhteDry4uBhamAAAAAAQoQYGBiYmJoqLi/V6vdVqLSwsxMtm8Hg8u90eCoX4fL7JZFIqlTBLDtyXzGZzT0+Pz+eTSCS3X5zO4XB0dnZ6vd6oqKisrKxpcz0MBgOeQKvRaOLi4qZNQvF6vW1tbUqlUqlUzr1F6AAAAHA4HFy9mcvl4qq8IyMjbrdbq9UODw9nZma2tbXl5+frdDr6f/zHf8DxAvcXt9v93nvv4TVGTpw4oVAo5HL5rYqa7Ny5s7q6miCIgwcPCoVCtVpNRZ+xsbG33nprZGRkYGCgvr4+OTk5JiaGKsFw6dKlEydOvPPOO9HR0ampqV9rsTtw9epVgiDwaiRfeOeGhobo6OhbreJeVVWlUqkg4AIA7kRUVBSuyyoQCHC1sGAwiEs/9Pb2JiQktLW1paamQmAC96X33nuvurp6xYoVhYWFOp3u7Nmz+fn5IpFo5rn24MGDO3fuXL58eVlZmdlsrqqqEggEODOFQqH/+q//GhgYWLNmjVarbWtru3z5slarpTLT5OTk+Pj4J598kp2dXVxcDPMNvyZjY2N/+9vfrFZrR0dHa2trfHw8l8udNQlZrda///3vFy5cOHHihE6nM5vNSUlJVKOgz+c7c+bMxx9/XFdXt3LlSqimAQD4Uvr6+vR6fWxsLJ/PpyqyslgsvIAYm82GQd/gPqPX6w8dOpScnLxs2bKCgoJ169b19PTU19e7XK6Zd66urp6cnFy2bFlWVtb3v//9mJiY1157DdcpuXbt2tmzZ0tKSubPn19WVvbMM890dHTs3LnTZrPh301PT1+2bNnMpYXBXTQwMLB9+/abN2/m5+enpqbW1NR8/PHHExMTM5erQwgdOnRo586dIpFo7dq1YrH48OHDQ0NDeAkIHKeampo+/fRTvF4vHNtvRUdHR21tbU1NTU1NzRdWMG9paampqRkaGpr15QbgG8blcoVCod/vx9Wq8Coxg4ODYrH4+vXrCoUCAhO4z9TW1o6Ojj744IO4KSg3Nzc3N/f48eNTU1PT7qnT6Xp6esrLy3GxDYVCkZ6efvnyZRytDh48yOfzFy1axOfz6XR6Xl4en8+/cuWK2+3Gv85kMm/V6QPuls8//3zv3r2PPfZYQUFBRUVFWVnZjh07+vv7Z55Be3p69uzZs2DBgk2bNm3ZsuWRRx5hsVjvv/++xWLBM1e4XO7atWsTExOhrv23pb29/ZVXXunt7TUYDO+9997Ro0dnLjtIXfa8//77v/vd737zm99cuHABAi64FyiVytTU1FAoZDab8Z7o6OiYmJhgMGixWBBC8M0C7jMGg8HtdiclJeE+MqlUqlAo+vr6Zq781d7ertPpVq9ePW0xhE8//XRqaurGjRscDketVocP9PZ4PHa7Hb6+vzFDQ0MOhyMtLY3JZDIYjLy8PJvN9tZbb+GlasN1dXV1dnauW7cOt/lJpdKMjIy9e/dSgUkgECxYsEAmk0Fg+lYMDg7+9re/jY6OXrhwYXl5+dq1a/ft22cymWZtPWKxWFKpdP78+S0tLaOjo9DCdM/yer3V1dW/+tWvXnrppaNHj86ZV4okyQMHDuCvjv7+/kuXLlEVA5hMZmZmZm1trclkkslkSqWSTqeLxWIITGAuczgcLpdLIpFMG/977tw5h8Mx66+YTKbBwcHwxbrB12dycnJgYCD8aGdkZCxcuLCmpoZq5wt/NR0Oh1QqxaP7WSyWWCyenJyEF+secebMmVOnTpWXl6empiYmJj766KNXrlypqqqa9QVSKpVr1qzZtm3b3VoHF3xN7Hb76Ojo5OTk22+/3djYOJeibWxsLN7gcrnR0dEIoYmJiYGBARqNJpfLJRIJi8UaGxsbGhoKBAJjY2MQmEAkCgaDtyo/hqdLfOEq4uCuGBgYOH/+/LJly6haD0qlMiUlZWY3qM1ma2xsnNmICO4dn376aVpaWnJyMl5NAq/humvXLoPBMPMsS6PRWCwWk8mELu97HJfLXbRo0QsvvECn0+dSWiIIYtGiRfjtp1AotFotQRAej4caC5uXlycUCj0ej9vtZjKZcXFx586dg8AEIs62bdtiYmJmvWlqaspoNEKjxTfDZrONjo6GD/HW6/VtbW0zBwszGIzo6Gjoa7uX6XS6wsLCpKQk/DIRBLF+/fpLly7NGpjA/YLP5ycmJmZkZETCZaREIlGr1Qihnp6etrY2kiR5PB6fz+dwOFqtViQSQakSEHFWrFgRFRV1q8spgUAALUzfDJFIlJiY2NbWRg0N5vF41Gzeaa9LdnY2dN/c44RCYXhJCLVa7XA4vF4vrCcB7mUTExN2uz0pKYmaE41nAiGE7Ha73+8XiUQ9PT0FBQVwxQbuM/PmzcOj8L7wnllZWSkpKTU1NdNGEOMr4JUrV9psttbWVo/HQ90kl8vDS/uAr1ViYmJZWVn40Xa73Xa7feb5lSAI6Lu5v5Ak2dXVBfMnwL3P7/fjQZN9fX1XrlwhSVKlUiUnJxMEERMTI5FIQqGQw+Gg0+kQmMB9ZuHChTExMYcOHbJarQihtra2CxcuPProoyKRCCHk8/n0er3FYgmFQjk5OYsXL66trcVDvD0ez+TkpFQqxWPA161bx+FwqMA0OTmJENqyZQse/Qe+mQaJadm3r6+vtbX1iSeemNkEKBAIBAIB1Svn9XpNJhP1aoJ7gcVicTqdVN7t7OyMjo6+VRlSAO4RYrEYL8SL6zChf3TJBQIBv98vl8vZbHZGRsbY2BgEJnD/nWVzc3NPnjzZ3d1tt9srKyt9Pt+6devwG72qqur//b//hwcI8/n8bdu2uVwunU7n9XqPHz9+/fr1H/7wh3iCqEwme+SRRwYGBoxGo9Fo/OCDD6KjoysqKsIrVeI41dXVNTU1BeMwvg4pKSnR0dHt7e24V87j8ajV6u985zv4VTh//vyVK1fwTQUFBUVFRR0dHfhHo9F46tSpDRs24KUM4Eh+60pKSpqamnQ6HdWqZDabH3jgAWpUEwD3JryWHEEQsbGxKSkpCCE+ny8QCHw+X1dXF0KopaVFLBZ3d3fDxRm4/zz++OMymezy5cstLS1RUVHPP/98UlISbqjAdQGYTCb+ji4oKHjooYdu3Lhx7do1JpNZUVGxZs0a/NkgCGLdunUsFuv06dN4Ashjjz0WExMTfval0+lPP/10V1fX5OSkUqmE7/27bvHixXFxcceOHZs/fz6Hwzl79mxZWVlcXBx+NT/88EOr1frSSy+VlJRoNJqnnnqqsrJy7dq1LBZr9+7dXq938+bN1JgnkiRDoRBJktQGQgiy1Ddm69atP/7xj8fHx8N7VNPT06VSKXxwwD0lFArhbwbq+6GhoSElJSU2NpYgiFAopFQqCYLw+/0JCQkIITx1Lj4+HgITuP9kZWXJ5fLBwcHJyUmtViuTyfh8Pn7rl5eXq1SqgoICamTMli1bRkZGhoaGMjIyJBKJUCikvr7j4uIeeughnU4XCoUSExMVCgU1v526aM7Nze3s7IS09DVRqVQvv/zywMDAjh07fD6f1Wp95pln8EKYCCG3202n06kXt6KiwuPxfPbZZ6FQqL29/eWXX87Pz6e65IxG4+HDh51OJ51O/+CDDx599FEqRoNvwIoVKzZu3IgnmTIYDIPBkJKSsnLlSvxJnJiYsFgsKSkp8IqAb11LS4tKpYqLi6P2iMViarXQQ4cOPfzwwwihkZGR5OTk0dHRrKwshFBycjIEJnD/odPpCoVCoVDMvCkxMTExMTF8j0wmk8lk+fn5M+/MZrNv9TiYRCLBJ3U45l+ftWvXTkxMXL582efzlZeXFxUVUWH32Wef5XA4GRkZOBVFR0dv3LgR97fm5eUtWrQofEVkNpudkJDwk5/8BP9IxSzwzZDL5Vu3bt2xY4dIJOJwOGfOnFm1alVJSQl+7c6cOXPy5Mm3336bGp127dq1y5cv+/3+jo6Oc+fOrVq1CiZbgG8GfotOuwhvbGxcuHAhQkipVFJv0fj4+N7e3ry8vMHBQYQQBCYAwLdMJpM9+OCDM/cvXrx42p6oqKjVq1fP+iAxMTGzPgj4xixYsGBwcDAYDLrdbpVKtXnzZirRSqVSrVYb3kzr8/nodPoLL7ygUqm+cJle8C0KBoNHjhzx+XzBYNDv9+M2wvv6aiQtLW3mTqoubmFhYWVl5bp167RaLUIoPj6ezWb7/X6CIAiokAEAAOCusFqtVOEluVxOJSS8TlH4eCabzeZ2u/E96XS6RCKBXu9709WrV//yl7+0tbXl5OTMmzfvueeem5Ml2icnJ0UiEUEQXq+3ra2ttLQUr4ii0Wj0er1CoYDABAAAAIBb0uv1XV1dVFRYvXo1Xv1mjv03P//88/Ly8vD/l8vlam5uXr58+YkTJ9auXdvS0gJdcgAAAACYXVJSUlJS0pz/b+IVsXw+H4PBwNOomUxmfHx8IBDAXXjBYBBamAAAAAAQ0axWa3R0dH19fWZmJpPJDAQCEonkxo0bfr8/JycHIWSz2aDPGAAAAAARDRfhk8lkbDbbYrEYjUaEkEAgiI6OdjqdFy9eFAqFEJgAAAAAEEFIkjxw4EB4D5vL5SJJMjMzUygUikQiuVzudruVSiVeNQWv9ACBCQAAAACRJTY2NvzH06dPU9sxMTFSqRTv6e/vRwhlZ2fr9XoITAAAAACIIARBLFq0KHxOHFX4u7q6Grc84T1DQ0OBQEAgEBgMBpglBwAAAICIVlpaijdwPTCXy1VUVIQQSkpKwmXBk5OToYUJAAAAAJEoFArpdLrwwUzFxcUIoZaWFqvVajab8Yo9fX19cXFxEJgAAAAAEIlIksTrxPn9/traWpIkBQIBQRAKhYLNZttsNovF4vf7h4eHEawlBwAAAIDIRBBEeno63sYLRYdCIafTmZ6eThCEy+UKBoNsNjsuLs7j8UALEwAAAAAiEY1Gi4+PJwiCwWDgQUter7exsRHfarVaJycnmUymx+Pp7++HFiYAAAAARDSCIHg8HkKIwWBQM+aEQmEwGEQIxcTEIKjDBAAAAIAIR9WxZDKZOTk5tbW1JpNJoVCo1er9+/crlUqlUgmBCQAAAAARTalUIoRu3rxpt9tJkpRKpSwWC9+kUqnwBgQmAAAAAEScS5cujY2N4YalhQsXEgQxOTnp8/kQQrm5uQwGo7a2FiFksVgQQnV1dTCGCQAAAAARh8vl4plxlMTERD6f7/F4QqEQjUbj8/kIIaFQiBDi8/lEeL0mAAAAAIBI4Pf7aTQajUYLXyMFIXTz5k2Xy5Wdne33+9lsttfrZbPZra2t0CUHAAAAgIjDZDLpdPrQ0FBraytJkv39/e3t7SRJRkdHSyQSgiDYbHZdXZ3H40EIOZ1OCEwAAAAAiFAsFgsXFGCz2XhDKpWqVCo8b04gEJAkaTabtVotBCYAAAAARCipVJqcnIwQksvliYmJV65cwUOV8OS43NxcGo3W1tYml8shMAEAAAAgQtHpdAaDQRAE3sBz4hBC+fn5Z8+eZTKZbDZbo9GcO3cOAhMAAAAAIlEoFBofHw+f/ZaVlWU0GkmSpNFoYrEYITQ5OanVakUiEQQmAAAAAERoYLp06VL4HpFI1NbWhhDicDgFBQUIoZaWFoRQfn4+BCYAAAAARCIajZaSkoIQOnjwIG5nYjAYiYmJCKFDhw7R6XSEUGpqKt4PgQkA8AVcLpfVag2FQnAoAABzLDBlZGQQBKFQKPAeJpOZlpZG7Tl79qxSqbTZbDabDQpXAgBu6ebNm729vQMDA1arNS0tjclkIoTmzZsnkUhoNJrH47l586ZWq6UWXQIAgPtRMBjEFSybm5vnzZtHEATe09bWptVqDQYDQRD0//iP/4AjBQCYaWho6LXXXnM4HHj1gGAw+M4779jt9nnz5gmFwsbGxv3797e2tpaUlHA4nIg9Sn6//7333vP7/bGxsbgB/w61t7fv27dPp9Olp6dPW58BMxgMu3btampqys3NZTKZXq/3vffeCwaDCoUC/yGHw/H+++83NDQkJSXxeLxp1YoBAHfu4MGDWVlZBEHodLqkpCSCIHB+6ujoUCgUHA6Hx+NBlxwAYPbrrd/97ndms3nJkiUbN27csmXLihUriouLGxsbjUZjKBSSSCQnTpzQ6XTBYPBu/VGHw2GxWO5K39/w8PBdfGK3cfjw4ddee+38+fN+v/9L/WJ7e/sbb7xhNptv1cxvNptPnjxZWVnp8/mamprefPPNV199tbm5ORAI4Dt4PJ79+/cbDAY6nQ5pCYA7ZDabnU7ntM8drrqEEMrPz0cIVVdXm0wmkiRlMhmLxZLJZFKpFAITAGAWoVDo1KlTarU6Oztbo9Go1erExMTHHnuMIAi73R4KhTIzM0Oh0F3s0/f7/Xv27Kmrq/N6vf/Hh+rt7f3LX/5it9u/gQOlUCiMRqPNZvuyh8Llco2OjrLZ7Ftlnbi4uOeee+6FF17gcrlisTghIWFiYsJut1N/KCoq6pFHHlm5cmV0dDR+kIsXL37Z3AZApMFjDKbtLC0tbWlpIUlSKpUSBIFzEr6JJMnBwcHBwUEITACAW7p48eLAwIDP58Mn6dTU1BdffDEhIWFa3xNJkoFAIBAIkCQ5LTcE/mHaTSRJBoNB/C/mdDrfe++969evBwIBfBPObdQjUPksGAzOeh/8o8FgeP3113ft2uV2u0Oh0MxUh58t3n+rp33nSkpK8NCuLys3Nzc1NbW7u5tqMZpGKpWuWbNm3bp1bDY7PT191apV08aKcTicxx57rLS0lOoz3b179/89bgIwtymVSoFAMG0nSZJ4zTi3233s2LGcnByhUEgQhNfrpb5hGHDsAAAzEQShUqmuXLny7//+7yUlJU8//XRcXFx0dPTmzZvZbDaN9r/XWjabzWq1Dg4O7tixw+FwPPXUU/PmzaPO68PDwydPnnQ4HENDQw8//HBSUpJcLvd6vQaDwefz1dfXr1mzZu/evcFgMDU1taGhoaOjY+3atQ6H48iRI/gPnT59urW1lcvl2u32jIyMtWvXCgSCmpqaysrKgoKC73znOzwer6OjY+/evTwe74UXXhAIBO+///6+ffsmJydJkrx06ZJSqVSpVFTCMxqNQ0NDn3zyyYMPPiiXyz/55BOXy7V161atVqtWq+l0usViGR8fT0xMdLvd4+PjSUlJLBaLIAiXyzU4OIi7+SQSiUwmm5Yag8GgTqcLBAIMBiMlJSV8WFJfX5/H4yFJksViJSUl4ZumpqYcDsfChQvtdrvBYMC9nHK5nDq2TqfTYDCo1eqoqKhZW6H8fr/H41EoFIFAoK+v7+zZs7W1tQaDIT09fWhoiMfjTUxMqNVqt9stk8loNJrZbGaxWBaLBf9P4U0OIjYwzdzJYDByPmQwggAAIABJREFUc3MRQjQaLTY2ltqfnp5uNBpxhx0M+gYAzA6vQ3n+/Pnm5mafz+d0OhMTE/l8PjVi5sMPP7xx4wZemfL69esNDQ3Dw8MrVqzAv9jf3//Xv/5Vo9EolcqBgYGjR4/euHEjNTU1FAo1NDTs3r371KlTQqGws7Ozuro6Ly9vYGCgvb198eLFBQUFHR0deXl5dXV1H3/8sUqlSktLu3nz5p49e4RCYXp6us/n+8///E8ajVZRUcHhcLxe79tvv11fXz9//nylUjk+Pn79+nWTyfTiiy8yGAyBQBA+ILqrq6upqenPf/6z3+/3+/3d3d2NjY1XrlzxeDxFRUUNDQ3Hjx//6KOP8vPz9+/f/+GHH/J4vOTkZAaDcfr06a6ursHBwba2tvPnz6empuILUL/fv3379pKSEr/f/9prr504caK2tlahUFChpL29/X/+53+cTufIyMiBAwckEolSqaTT6X19fadOnSosLGxoaNixY8fp06dv3ryZlpaGH7apqen06dPvvPNOVlaWQqGg0Wher/eNN95YsGBBWVkZk8m8du1aXV1dU1NTYWGh3++vrq7euXNnV1eXXC4vKSl5++23nU7n9u3b/X4/nU6n/mJzc3NlZWVZWRlMbARg2iUil8slCILBYKjVaoIg6uvr4+PjuVxuU1NTdnY2k8mEFiYAwCxoNNrGjRtzc3NLSkr+8Ic/fPrpp9XV1a2trRUVFfPnz6dG3giFQoFAUFRUtHjx4ldeeaWjowN3CZlMpu3bt1ut1mXLlimVytzc3FdffXXfvn2LFi0qLy/Pz8//4IMPfD6fTCb70Y9+dOXKlRUrVhQVFR05cgQhxOfz161bx2QyDx06VFZW9sgjj6hUKq/Xu2PHjs8++2zt2rW5ubnhGSghIUGhUAwODuI/vWnTpqtXr964cQP9o+JcOJVKhSedBQKB3Nzc8vLy1tbW3/zmN7t37168eLHL5RoYGDhz5kxGRoZSqTQYDE6nMxAInDx58ujRoz/4wQ/4fL7JZPrkk09ef/31X//61yKRCD/shQsXlEplenp6IBA4ePDgK6+8wmQyFyxYcPPmzVdffVWhUBQWFnI4nDfffFMikeTn5zOZTCaTyWAw9uzZs2bNmqysrNHR0b1799rt9j/+8Y8CgcDr9f7973/ncrm4fWvmCxQIBD7++OOJiYkFCxYUFBTk5+fLZDI2m61UKmk0Wnx8/Ojo6NmzZx0OxxtvvIFbrSQSyalTp/Lz86lGrHB4Fp7dbudwOEuXLm1sbPT5fD6fb8WKFQUFBbPO4wPgvhYIBPBUOIIgfD7fyZMnN27c6PF4zp07t379emo4YFpaGm5ahs8AAGB2UVFRubm5KpUqNja2pqbm8uXL7777bk1NzV//+tesrCx8BtVqtZs2bUpOTmYymTKZLBAIjI2NyeVys9l87Nix559/Ho8VSEhIeOihh/bs2bN9+/aysrKcnJyYmJhgMFhaWhoXF5eRkSEQCGJiYvBjMhiM+Pj4/fv3X7ly5eWXX1ar1TQaraSk5JVXXmGz2bj5atbzvdlsDgaDfD6fmng/k0qlYrFYuNesqKgoOjpaq9UePXq0urq6q6tr7dq1er2eTqenpKSsXr06PT09Jyenqanpj3/847PPPosLKPh8vsbGxnfffTcmJubll1/GaUYsFi9atEgulxMEkZ2d/S//8i8nTpzIzs4eGxsbGhr68Y9/jIc60Wi0kZER/OUbHR0dFRXF4/EeeughoVBotVoDgcCBAweefvrp4uLi3Nzc4eFhrVY7a7hBCKWkpJhMJh6PJxQK2Wx2Xl6eVCoViUTLli1jMpkbN24cHR1dv359Z2cnSZL4SXZ0dAwMDPzbv/0bm82eNSI7nc6//e1v+Go7ISHB7Xb/9a9/DQQCaWlpAoEAJuKBOaalpSU+Ph53txEEgbvqqC65wsJChNDQ0FB8fHx3dzdBEDDoGwAwi1Ao1Nzc7PF4JBLJd7/73V/84he//e1v8/LyLl68ePToUbfbje/GZrPxdBJ8NsXjk4LB4Pnz5ycnJ6Oioqj+u4SEhKysrMbGRup3WSwWj8ej0+nR0dEzY0FLS4vFYomKisI3paSkPPnkk1u2bLlVYPL7/Q6H487HbkdFRTGZTIIgBALB008/TafTPR6PSCQSCoU0Gm3BggUqlWr16tVqtVqn0127dm3JkiU4Z7BYrMLCQjabXVNTQ42wTktLS05OVigUcrl806ZNxcXFx44dw4nnX//1X5OTk0+cOLFv3z6r1Uo9Qx6Px2azMzMzY2Nj5XJ5Wlra1q1bBQLBjh07PB5PTExMWVkZbuOZ9T8lEAgYDIZKpdJoNFQ6xF2QNBotJiYmMzPzF7/4hcfjOX36tM/nQwh1dnYuW7ZMoVDMGn2YTGZ2drbVas3MzCwpKVm/fv1DDz1UUVFx8ODBaauTAjA3SCQSLpdLvf9xvUo2m11aWtra2oq/efR6vcfjiY6OFgqFEJgAALMHpsOHDzscDvxjamrqgw8++Oijj/J4vOPHj7tcrll/i8lk4tadmXPT8En6Vh1MsyJJclpc8Hq9tzpzu93uiYmJr1bDqbCw8EuN6SkrK0tKSrpVIxaXy125cuXAwIDNZpNIJH6//6OPPqqsrKSSIobD2dDQEFUvav78+ampqe3t7bgvgMPhxMfHz5omKeHTA2fKz88nCGL37t1dXV0Gg6GpqQn3Bt7+Jdi2bVtJSQmDwfD7/YODgzdu3JhZtAaAOSAtLU0sFlMfh0Ag4Pf7qbm3eGdiYiKHw5mampqamoLABACYPax0dXVR/UcIITqdHhcXx2AwVqxYQV2WTYNbmAKBQE5ODovFGhwcpBKPzWYbGBh44oknhELhnTwBlUrl9/v37dvndDqpne+//z6V4abh8/nhs+G+FL1eLxAIRCLRbaJJOLlcfpsuKo/HU19fjy9eW1tb//jHP/L5fFwwKXy+m9FotFgs4fPpcHUDHMUIgpg/f35fX5/JZLpNCtTr9Tdu3LhNic4XX3zRZrPV1tbW1dWxWKy0tLRbHaJgMDgwMKBQKKj+VqfTWVVVtXnzZjwuCj4UYE5eGfb29uLvqMHBwWvXruH96enpLBZrYGBAo9Gw2WyBQAAtTACAW+rv73/33XepufQ+n6+lpUWr1T788MNUv9jQ0FBfXx9VScjr9eKMpVar8/Pzjx07hqf346s3t9u9ZMkSPBXlNn/X4/G0tLRUVFSIRKKDBw/u3r3bZDL19/cfOHBgbGyMSg99fX24+6+3t3d4eNjpdE5OTk7LFtevXx8fH//CZqddu3ZptdqioqLbVFQ6f/487thCCHV1dY2Pjy9YsGDWdimv19vY2FhRUaFSqfCsurKysoqKCqVSGT50OiYmRiAQjI6OUnGnoaFBp9N997vfxXnU6/X29PTcphQ4QkggEFBVK2/VXLRy5crPPvts586dK1asmFlDK/yw7927d9myZXFxcTgekSTpcDjmzZsXExMDA5jAXL0yvHnzJt6OiorC0zgMBsPo6ChJkv39/Qih6urq+Ph4jUYDgQkAcMt2lJGRkb///e+vvfbaa6+99vrrr1+7du25557DTSAejycYDHZ1dV28eNHj8eBZ+h6Pp6+vz+12S6XSlStXGo3GnTt3jo+P22y2EydOFBYWarVahJDdbvf7/f39/XV1dS6XCwcCgiA4HE5tbe0777zjcrm0Wu0Pf/hDi8Xy5ptv/va3v/3973+/ffv2xYsX4zCxZcuWgYGBV1555dVXX62qqvJ6vU6n89ixY729vYFAAA+vfuONNxoaGmZWvna73SRJ1tfX9/f3W63WM2fOdHZ2Pv7440lJSTg3kCSJ74PvX1pamp+ff/DgQaPR6Pf7A4FAXV3d+Pj45s2bqUX06urqcBEmhNC+ffvS0tIef/xxiUSCc4bT6bTb7adOnZqcnGxtbb18+bLP57NYLDab7dKlS7jDy+Fw6PX6FStWzJ8/n8FghEKhAwcO4Ep64U972v9lcnIyvCMyGAza7fYDBw5YLBZ8Z6FQ+Pjjj/v9/pGRkYULF94mEdrt9uvXr6elpeEE5vF4Pvvss6ysrMLCQijaBOYqgiDS09PxtkgkohZIIQiCyWSmpKQghPD1w6lTp6AOEwBg9u8RjUazcOFCqVQqlUrFYrFEIiktLX3ggQdwe8PFixdbW1uZTCadTi8pKTEajQ0NDaFQiE6nZ2dnK5XK2NjYnJycK1eujI2NdXR0JCQk4IoAVqv10KFDfX19OElkZ2fjvjAajRYMBvv6+kpKSpYsWRIVFZWSkpKQkODxeG7evCkUCteuXfvAAw/w+XyCIFJTU30+X1dXV1lZWW5u7tTUlFgs3rp1a3Z2tkAgEAgEY2Njbrd7zZo1eAZfeAPJ0aNHjx07VlhY6PF42tvbQ6FQeXn5qlWroqKiTCbTu+++azAYJBKJSqXC44ckEklKSkp9fX1jY2MgEJiYmKirq1uyZMn69es5HE4wGKypqcFPBo9/P3PmzHe/+92FCxdyudzR0dGqqqre3t62tjY8Yml4eJhGo82fPx8v8+lwONxuN41GO3fuHJPJ3Lp1q0qlotFoJEm++uqr8fHx+fn5uI/szTff7Ovrk8lkCxcu5PF4Q0NDDQ0NN2/ejI+Pz8nJYbPZ165dGxsb0+v1HR0d5eXlVPefVCqtrq7WaDSPPfbYbZZJfu2110wm0z/90z/FxcVNTU19+OGHTU1NP/3pT8vKym6zfgsA93sL08TEBL62GRgYMBgMsbGxHA4Hl0OzWq0ikSgqKmp8fJwBpTUAALOi0WjLly+/ffvTz372M9ydJBQKmUzmk08+iZtYYmNjaTSaVqvVarVJSUl4EFJZWRnujAsEAunp6cnJydRVHTUe/Pvf//78+fNx0QEajSaTybZu3VpYWDg8PCyTydLT06kGErVa/eyzz1ZUVJSUlPB4vKioKLfbnZeXh/vIcnJyfvGLX+BKSzPbVOLi4uh0elZWVn5+Pi4yThWZJEmysLAwKSkpLS3NZDIlJiYihDgcTkVFhd1uP3bs2MDAQCAQ2LRpU0FBAe6XZDKZv/71r30+37lz53Q6XXR09JYtW6i/m5ub+5Of/KSzs1MoFJaXlysUitbW1vz8fC6XK5FIXnzxxa6urvb29s7OzsTExKSkJFwkEwfWp556qrS0lBqzxWQyf/azn42Pj+OR76Ojo08++WRhYaFSqcTjvh966KGsrKzOzs41a9aEd6JxOBwWi/XUU0/dJi0hhGprawOBQFtbm06nC4VCY2Njjz/++Mz1WACYY4Gpv78ft3zjmacIITwf1uVyGQyG5ORkNpt9/fr1JUuWEDD3AQAQUfr7++fPn//SSy89//zzfD4//Cav12u1Wv1+f3R0tMvlkkqlVG+U2+3Gw7m4XG58fPzMXqrBwUGn0ymVSiUSSfgQ6bGxMavVKhAIYmNjA4GA1WoNf1iPxzMwMBAMBrVaLYPBoFIOSZLDw8NKpXJkZAQPZjcYDEKhcGxsLC4ujsfjGY1GPp+P1+IVi8W4Ecjn801OToavrxIIBOrr68+fP//888/ji+ZZj4nb7d60aVNFRUVSUhKNRhMIBGq1Ojk5+QsHnAFwXwuFQkNDQxqNhnqfu93us2fPbtiwAQ8bSEtL83g8BoNBq9VCCxMAILJ88MEHTqcT55vwiuH4ylKhUODtactzcrlcaqzDrOLj42fdHxsbSy1NRafTqcfHOBzOrA9LEERcXBxCSKPR4D14Izo6Gv+IHycqKir8t1gsFv5bLpers7MzEAiYTKZdu3Z973vfu9XERqyysnJoaGjr1q0xMTEIISaTOe3IADAn4bL4CCE8fQRPI8Ujmfx+v16vT0tL8/l8uBUKAhMAILLweLwtW7bgNWupKthzjNfrraysbGxsJAhiyZIleXl54c1XM7W3t5tMJlxvHd4hIHKcPn161apVBEHgpqa0tDQWiyWVSru7u5OTk/FVCovFwlcvEJgAAJFl27ZtuPDmHJ4tz+Px8NhwPp+/cePG2xRSCgQC77zzTnt7u0AgcDgcd16MCoC58UnBG3Q6PSMjA28zGAwmk8lisbKyshBCR48e3bJli81mgzFMAAAwB/l8Pq/XS6PRbt+5FgwGz50753A4vF6vUCiEUd4gorhcLmqgntls9ng8KpUKtz3j8eDp6elNTU1lZWVnz56FFiYAAJiDWCzWnUQfOp2+evVqhFAgEOjt7YXmJRBRwtemdLlcNptNpVINDQ253e7ExMTx8fH09HSLxYIQgsKVAAAAEEKIwWBkZGRArRkwt+3bty+8Yy0UClGrEVCFK1ksFpvNxksJoX9MrYiNjYXABAAAAICIgIdvhwemxsZGvO3xeHDZM4VCgUuH4DmnuCzTpUuXIDABAAAAICIkJSVdunSJamSi0Wh4TSSEkNvtttvtCKHBwUGdTud2u6uqqhBCU1NTCCGNRgOtrwAAAACICEwmM7xcLY1GS01NdTgcUVFRYrEYV19js9kkSdJoNKFQiBDKyclxOp1xcXEwSw4AAAAAESEUCgWDwfCyZIODgyaTqbCwkNoTDAZJkqTT6X6//+bNmwkJCYODgwgh6JIDAAAAQESg0WhtbW3Dw8NUa5FAIJDL5dQdjhw5QqPRcKJisVhWqzUQCIjFYrFYDIEJAAAAAJFCIBDgcdyYSCSKi4vz+/2HDx8mSVIqleL9eD6dVqu12Wxyufzy5csQmAAAAAAQKVJSUiQSybSdNBpNrVYjhObNm4f34Pl0Uqn08uXLCCGlUgmBCQAAAACRgsFg0Gg0giAuXLgwMjKC++YYDEZpaSlBEIFA4NSpUyRJ5uXlnTlzBiGk1WoRQgUFBRCYAAAAABBxYmJiqL45KjnRaDTcK0en0/FGXFzcyZMnEQz6BgAAAEAESktLE4lEeBv3uyGEWCxWUVERQojNZhcUFCCEGAyGUqmEwAQAAACASESj0XDfHPpHv1tdXd3ExATe6XK5cJfciRMncHKCwAQAAACASEQtLZeRkUEQhEQiYbFYDofDarXS6XRcbgAvMHfy5EkoXAkAAACASNTU1LRgwQKqZGUoFCIIQq/Xu93urKwsXO87FArRaLTW1lZoYQIAAABAJCorKyMIIhQKkSRJtR/FxMTIZDKXy4XHeu/fvx8hNDo6CoEJAAAAAJGroaFhbGwMIVRXV2c0GkUikVwup9PpeKy3RqNBCCmVSuiSAwAAAEDk6u7uVigUMTExXV1darXa4XB4vd6kpCSqqw6DFiYAAAAARJxgMIg74zIyMkQiEUEQWVlZ0dHRwWAwEAg4nc7KykqE0N69exFCJ0+ehMAEAAAAgIjT3Nw8OjpK/Wiz2UwmE0mScrk8Li6OKr8EXXIAAAAAiFw3btyQSqW4bQkhNDAwYLPZcnJypvXEUaCFCQAAAAARJy0tTSwW9/f3Nzc3kyQpEoliY2P37t1LkuS5c+dMJtP169fb2tqmpqZOnDiBEGLAIQMAAABAZIqKigqFQgghoVCIEEpISEAIxcbGstlsPJ6JxWKp1WqEEHTJAQAAAAB8AeiSAwAAAEBEwz1xCCG32403nE7n8ePHEUJ79uxBCHk8HghMAAAAAIgsNpttZGSE6mSLj4/HGydOnLBYLEajkU6n45443ElXW1sLgQkAAAAAkcXhcIyPj1M/UivKJSUlTU1NmUwmNptdWFiI74kQ0mg0EJgAAAAAEFmio6Pj4uKCweCBAwdIkgyFQk6nkyTJoqIiiUQSGxtLkqTL5UIIMZlMHKQgMAEAAAAgsvD5fJlMRhAErkvp9/urq6vxxvj4uEgkcrvdn3/+OUKoqKgIIVRfXw+BCQAAAACRiE6nz5s3jyAIOp2emJiIEAoGg0NDQwghBoOBBzadP38eQZccAAAAACKZz+dzu910Oj03N5cgCAaDkZaWVlVVZbfbMzMzEUJcLhch1N/fD4EJAAAAABFqZGSks7MTIWQ2m4eHh/HkOFy40mQyjY2NFRcXI4TUajUEJgAAAABEKKFQKJfLEUJOp9NqteKdOTk5AoHAbrfbbDY+n48Qys/Ph8AEAAAAgAhClalECInF4vj4eIIgxGKxUCgMBAI6ne7q1askSUZFRQmFQmotOQhMAAAAAIggVJnKcFFRUf39/RaLRSgUikQihJDFYjGZTLCWHAAAAAAincFgMJvN+fn5BEH09fXJ5XI+n4+LWBqNxmAwqFQqdTodQRDQwgQAAACACMVisXg8Ht6WSqVsNhshdO7cOZPJJJPJ2tvbLRYLh8Nhs9kQmAAAAAAQoaRSaVJSEt7G8QghhGfJIYSUSiXukoNZcgAAAACIXHQ6nclk4j44tVqNW5tycnJqamoQQnl5eVVVVQwGo66uDgITAAAAACKC1+udmprCo7enpqa8Xm/4SO6kpCQ8IQ4hJJFIwjdEIhEEJgAAAABEhMnJye7ubrzd3d1tNpsRQj09PVSKoibQlZaWhm/QaDQITAAAAACICHw+X6VS4W2VShUVFYUQstvtfr8f71ywYAHunsNNTdXV1S6XCyHkdDohMAEAAAAgIgiFQo1GgyORRqMRCoUEQSQlJTmdTnwHqqYlLv8tFosJgpiYmEhPT4fABAAAAIDIJRKJ2tra8DbVJTdv3jyEUE5ODkEQHR0dUqkUAhMAAAAAIlpaWhrewF1yNTU1eF05BoPBZrMTExMRLI0CAAAAgMgxOTnpcrmmLXOSkZGB++lwl5xUKmWxWF1dXW1tbR6PB48Th8AEAAAAgEih1+txdUqEUDD4/9l777Coru19fHplmAEGmGFg6L2DgFKkShMbEHu5iYlGUzUm+aSZ3HvTTGKMiZqYWAlqREWxAApI7733GRh6G9oM02e+f6zf7zzzgBJvkpt2ef/wGQ8z++xzzj57v2utd62tqqio0CZPEJJzdnam0Wh0Ol1PTw/ZSw63dO+WsIQlLGEJS1jC/wjYbDYkxwEQuTdg+fLlHR0dYrHYw8MDeBIKhXJ3d/8jCZNIJBoZGdHX11coFEqlUiaT0Wi06elphUJBo9GMjIzwePz09PTY2BgWizUxMYEi5UtYwhKWsIQlLGEJvxhIWQEUCoXBYNzc3FAolEwmu3fv3oYNG9BoNI1GA8rR0tKiUCgsLCyKiopWr179hxEmoVCYlJREo9HGxsakUqlQKLSwsGhvbxeJRFZWVrt37+ZyudeuXcvJyWEymW+//baZmdnSY17CEpawhCUsYQm/FdBoNBTyxmKx5ubmcFCtVqtUKhQKxWAwlEolgUAABvKHESY6ne7s7Hzu3Ln6+vply5Y5OTkZGBjY29uPjo4+ePDA3d3d0NBQIBDk5uay2WyRSPRnuLMajUatVqNQqFu3bqFQqIiICDqdDn+anp5OSUmBmqEAfX39hIQEpLY6goyMDCCtyBEcDrdr1y5DQ8Mn70Nubm5jY6NcLkej0dClVatWOTs7E4nE9PT0trY2hUIRFxdnb2+Px+P/8PuWl5dXW1trYWGxatUqbUfonx8ajaa9vV0mk9nb2xOJRDQaDfc/Ozvb09MTHi76/8ffdUKBS/7bX+YSlrCE/0EgkxsOh9PV1a2qqlq2bJlKpQLCNDU1pVAouFwuGo1uamr6IwlTbGzs+fPnoU753r17PTw8cDjc3NycmZkZg8GgUCibNm0aHx/38fFhsVh/+G0dHx8fGBhITk4eHx+vqalxdXX19fVFCNPs7GxSUlJnZyfyfWtr67CwsIWEqbm5+ezZs4jiDIVCkcnkuLi4JyFMw8PDfD7/2rVr3d3dRCLR1tbW0NCwqKiIz+fn5ub6+Pi88sor0P709LS1tbWVldWvJ0zd3d1SqZTNZtPpdCwW+wtaKC4uvnjxYnBwsL+//1+IMI2MjAgEgi+//HJ8fPyrr75ycHDAYrE1NTVJSUmlpaXLly8PCwvLycmh0+kHDx7U19dfpCmRSDQwMKBWq62trQkEwl/lDojF4v7+folEcu7cuZCQkJiYGDKZvDTDLmEJS/jb4Nq1axs3boTPurq6OBwOhUIZGRn19/fLZDLwMKFQKD09PdQfK/rW0dGBxaOrqwuNRhsZGcF/d+/ejUKhaDSau7v7gQMHTE1N/wyrbG5uLo/HGx4erq2t7ezs5HA44NoBqFQqIpHo5eWFrCgmJiaPXF0MDQ2xWKyHhweVSoUjRCIRtkf+Wdy9e/fGjRs8Hm/btm0BAQFcLpdGo3l7e9fW1p4+fdrS0lKlUsXExJw+fXpkZEQqlc5Lm/wFqK2tPX78OIlEev75552dnX8ZYTI3N8fhcGZmZn8Gd9cTYmho6PTp0zU1NWB2wMH6+vpTp05NTU2Be7azs/PKlStsNnvv3r2LECalUnn16tV79+6hUKiTJ0+y2ey/yk2YmZmprKx88ODBjRs36HR6RETEEmH6jyCRSLKzsx0cHCwtLWEiXgSTk5OFhYVyuXz16tUkEmnJmbeEJfwOsLKyQj4bGxvDBxKJNDw8rK+vz2az4U1UKpVoNPpPkSUXEBDAZrNhY7v09HQ/Pz8DAwOFQlFXV5efn08ikRISEphMplqtViqV2iQAg8HgcDhkZlEqlWq1WqPR4HA4DAaDRqMVCoVarcZisVgsFr4GR+BXSqUSi8XCN5HfLmwWwGKxmEzmqlWrzp8/PzAwMO8S7t+/z2azd+zYgdxxIpG40L2EQqEEAoGBgcFLL71kamqKXAWUYF8EarW6paUlNTW1rq7upZde2r59O4fDAfrCYrGcnZ0rKip0dHQwGIyLi8tvuKplZGTcvXt35cqVVCr1F+88GB4eLpfLly9fTqPR/ipvUUdHx7Vr1/z9/Xfu3Kmrq2tubt7W1vbll19WVVV9+eWXLBaLSCROTU3dvXs3LCxs8etSKBSXLl0qKSnZtGnTz66aTwK1Wl1WVlZSUsJms9etW/ffMydoNJqnp+eZM2e0I8hLeBw0Go1CocBgMDDb5OXlFRQU3L17d//+/fDe5PdXAAAgAElEQVS2LsKB7ty5U1pampWVJZPJgoODSSTS79x5mAC7u7vv3LmzadMmMzOzxd93tVpdXV1NIpEcHR0Xv7QnHNIwt587d87MzCwqKuovYVzBE0cWEeRCtI8s4c8GtVoNrAAeELLD7rw/mZmZwWuYmZnp5+cHkbs/BWEaGRlpaWlBoVBYLPb27du2trYGBgapqakPHjzIy8vjcDihoaFMJlMgEHz77bcYDEZPT29ycnJ0dNTQ0DA6OtrAwMDGxmZ2dvb8+fPt7e1KpfLll1+2tLQcHR29evVqb2/vunXrIiIilErl0NDQpUuX+vv7N27cSKFQ0tLSoqOjg4KCpFJpcnLy3NwcDofr7+8nkUjbtm1zcHDQfmm9vb1xOBwej8/MzFzoaOFwOIaGhgwGA4vFQuzT1NT0kZl9dnZ2xcXFyH+ZTKaxsTGsoz09PbOzs0wm09DQcN7KKhQKP//887KyMjqdHh0djbAlgL6+/gsvvKBWqx+5dqpUqq6uLqlUam5urquri8Fg+Hz+7OysRqOxtLQEmiWXy3k8nkwmQ9xj+vr6WCx2YGAAOYhALBYLBAK5XI44kKBZpVLZ1dUlk8ksLCw0Gs3g4CDiHXR0dPz914BfDIVC0dbWNjo66uzs7OHhAXyos7MzNzeXSCQ6ODiANlAikfzzn/+0trZenDDh8fi1a9e6ubnt3LmTwWD8+u7xeLxPP/20trb21KlTvwkDexx0dHScnZ1hr6WlefZn0dbW9vXXX0dHR0dHRxOJRBaL1dra2tDQkJqaGhoaimxf9UiYmZn19PS0tbWJRCIIAfwOEIlEPT094KguKyurqKh4+PDhwMBAZGQkYs49DkNDQ++//75KpUpKSvpZe2+RF214eJjD4czOzl68eJHH492+fXvNmjXh4eF/csI0PT0tEAhmZ2fPnj27ZcuW0NDQ6enpgYEBSGb6xz/+4e/v/8v88b8Vuru7USiUpaXl44jvwMDAxMQEnU4Hgc7v3D0Q8pqbm9Pp9J89+8zMTE9PDwaDcXZ2/vVdHRwc7OnpCQgI0G5fKpUaGhryeLypqSlvb2+Y8KlUKplM5nA4BAIBIgN/CsLU1dVVUVEhEolaWloaGxvBnLW2tjY0NJyZmSGTyUBBsrKykpOTExMTly9fzufzb9++PTIyMjw87Ofnx2azh4eHh4aGbt26ZWxsPDc3NzU1VV9ff/PmzebmZktLy6CgoJmZmbq6uhs3bnR0dKhUqrGxsaKiIgsLCwcHh5s3b5aXl69evdrIyOjhw4c1NTUMBoPD4WjHWRaPmkmlUoFAcOrUqfHxcWAYW7ZsSUhIQERO2p6q4eHhTz75BPxALi4u3t7ea9asodPpSUlJ5eXliYmJCQkJSBgI4Sjl5eWTk5ORkZHGxsYLX8UVK1YgRo/28fb29sbGxpSUlMnJycOHD/v5+XV1dZ04cYLH46lUqo8++sjT0xODwdy/fz83N9fCwkKlUhUWFm7bti06Onp0dLS/v1+pVJaXl1+4cMHf3z8kJIRCoVy/fv3WrVsuLi5EIrGqqsrf3//ZZ58dGRlpaGi4du3a9PT0O++809jYmJOTc/DgQQg0tLa2Ll++fP/+/eB1q6mp4fP5pqam7u7uBQUFU1NTGo0mKioKeXk6OjpaWloQrmZkZOTn57fIIxCLxXl5eZAcYG5u7uHhAfysqqqqt7cXCUIHBgZqNzI2NlZaWiqRSLQ9nVgsViwWp6WlzczM3Lt3z9/f39DQ0NTUVCaTSaVSAoHQ29uLRqObm5uBdEqlUgMDg0X6hsPhduzYIRaL2Wz2b7IMjI2NVVVVjY2NOTs7L05DS0tLPTw8Hudx5PF49fX1oaGhj5yzSkpKBgcHbW1tl9xLT4gzZ85cvHiRw+FEREQAsbaxsYGqKGQyefGJ3sPDQ6FQ/J4sobCwsLa2ViAQvPjiizo6OiwWy9bW9oMPPrCzs3sSmd309HRxcfHMzAxUTP4Fy1htbW1DQ8Pw8PArr7xCIBBcXFzu37/f19c3MzPz67UE/20IhcLKysq0tLR79+55eXkFBwdPTExUVlampKRkZ2cTiUQ3N7c/ytK4ceOGUqnMyMgwNDT8+OOPFxKmrKysycnJkpISHo8HsY7fk9vxeLyqqqpLly5JJJJ33nln5cqVi3//4cOHtbW1Dx48IBKJN2/e/PVdpVKp81TR09PTQqHQ0NBQV1cXeQc5HA7MrlKpVK1WU6nU8vLyPwVhwuFwTk5Ofn5+urq6oGdCoVDLli1ra2vTXg/S09MnJiacnJzCwsLkcnlxcTGfz1coFE5OTlQqlc1mJyYm3rt3T6PRaDQaBoPh6empp6eHDBd9fX1PT09kbfD19fXz8/P19b18+XJSUlJ8fHxwcDCHw7l27VphYaFAIFjoWVkEWVlZtbW1y5Yta21tBa/MyMgIFovdsGHDPOrT2dk5NTVFpVIHBgYEAkFdXV1eXp6fnx+dTm9oaHj48KGHhwfivFmIyMjIhSTsZz2QJSUlAwMDzz//PFBPKNkwPj5+8OBBtVqdk5Pz9ddfk8nk1atXUyiUxsbG6elplUqFZEUZGxsbGBiAMyMtLe3kyZN4PN7NzU0sFp8+fbqlpWXNmjUajUalUpWUlAwNDdHp9K6uLh6P9/TTT4Otk5eXR6FQZDLZ5OTktWvXsrKyurq6OByOt7d3SUnJxMSEQqHo7e3ds2cPnU7n8/lfffVVfX39jh079PX1r1+/PjU15evry2Qyd+7cOU8tpFQqc3JySkpK8vLyYO6OiIiwtbWdnZ29dOlSbm4u+CAzMzN7e3tzcnK2bt3q5OSEx+MlEsnJkydnZ2fd3d2Hh4dv3bpVXFx8+PBhJpN569atqqoquVxeU1Nz4sQJHR0dU1PT5ubmubk5lUp1+vRpfX39lpaWqakpuVxuY2Pj4eEBhAmKip05c2ZmZkalUpmZmSUmJqLR6OTk5KmpKRqN9swzz4CTCbrd3NysVCoVCgWFQtm+fTuTyZycnLx48eLMzIy+vr6jo2NNTQ3C5/bv389kMtFotFwuh0He1dWVmpq6evVqW1tbbVfT5ORkUlKSSCQqLi52d3ePjo728/MjEokPHz6srKyEgR0XF3fu3LnS0tLCwsKgoKBVq1ZRqVR43BCXyc/PHxoasrCwAAPjcUNLJpNpNJpLly4NDw+HhIS4u7vTaDQ0Gv3dd9+Njo5GRkaWl5c7ODgEBwcDmRAKhTgcbv369WQyWSqVlpWVlZWVyeXyFStWBAUFkUgkpVKpVCo7OzszMjI2bdo0OTn54MGDrVu3cjgcpVI5Pj5++fJlsVisr6+/fft2BoMB8XSFQvH999+LRCKNRmNsbBwfH08mkzEYDOQ2qlQquVyekpIiEAjUavWmTZvMzc21dUJwIdnZ2QKBYNOmTRQK5fz58xMTExqNZs+ePcbGxtqrjkQiQWL30D4cb2homEcuHR0dcTjcwMDA3NwcPEc0Gv2f6pNkMhly/+cRL5lMRiAQFAqFSqXSaDR4PH6eREGhUEBXCQTCvMDZ1atXHzx4EBYWBs/dxsYGqt/19fXNq+P3SDCZzDfffFMqlT6Jh+Bxc2ZycrKTk5NKpaJSqWFhYVevXv2r+DL19fV9fX0///xzRMnKZDJ9fX2bmpoePnz4x14FGo0uLi5OTU319vZ+JPVEo9GdnZ0pKSlCoXDlypWhoaG/cw8xGAzYyc8+++zPsm00Gi0UCrOysigUym/CpPX09EDBjYDBYADT0PaVOjo6Xr16dePGjUj3/iwhOR8fH19fX1dXVzs7u87OzscZxIODgwiJAb0RlUp1cHBwdnYmk8lkMjkvL08mk0FsiEajGRgYwNwNP6HT6XQ6XUdHB2aH7du30+l0KpV6+PDhrq6urKysmZmZ9evXj4+PP255WARPPfVUUFCQra3t8PBwZWXlpUuX2traioqKIiMj5xEmPz+/zz77jMVizc3NNTY2nj9/vrOzs6uri8vlWlpauru7s9nsReIsOTk5UVFRTy5b4XK5VCoVEZijUCgLC4v4+PizZ8+Oj48jfoja2lqwcXE4XEJCgo2NDYlEYrFYIFF3cnKKiYlhs9kkEik7O7u1tXXz5s0BAQESicTLyysnJ+fChQsvvfTSihUrgDf09fXt3r2bwWB4e3uTyeTc3FzkiggEgr29/b1799rb20dGRnx9fXfs2JGfn3/t2rWUlJTQ0FAPD49PP/00NTV18+bN4eHhenp6ycnJpaWlLBbL29t7YZSzrq7u6NGjaDR606ZNNBptdHRUIBAolcr6+voffvihu7v74MGDjo6OhoaGu3fvrq2t1dfXNzc3l8lkZ86cKSoqOnDggJeXV1lZGZ/P7+3tffXVV5lMJqJP37Nnj5eXF2y+ODs7Cx+Cg4ONjIxWrFiRl5d35coV4Eng5UpNTe3t7e3t7TUwMLh7966lpWV0dHRJScmpU6cmJiaeeuop8HUpFIr09PRjx46tX7/eyckpJSWlpKRkbGxsz549WCz2/v37tbW1dDo9ODh4YGBgZmamu7tboVCsWLEiJCSEQCBkZ2eLxWK1Wn3r1i2BQODn52dtba19T7799tuhoSEcDicUCs+dO1dQUPDDDz/Y29uz2ey0tLTu7m61Wj0yMtLR0YFGoy9fvpybm6urqxsUFEQgEPh8/vvvv08gENatW4fD4RobGwsKCrTzG+ZZZocPH6ZQKC0tLdXV1Q8ePPD29n7//ff19PRAkfPw4UOZTPbFF19gsVgikXj06FEikXjgwAEsFtvV1XXs2LGhoSGxWDwzM/PgwYODBw+uXr26urq6oqIiOzu7pqZGR0cnIyOjuro6LCyMRCIlJydPTk5WV1d3dXXJ5XKhUPjss8/S6fSbN2/m5eUNDAy4urpOTU399NNP2dnZdnZ2VCr1hRdeoNFora2tJ06c6Ovrk8vlg4ODlZWVISEh+/btQ94LkUh04sSJmzdvjo2N5efn29jYVFdX19fXK5XKgYGB1157DXxFo6Ojg4OD3333HfgyORzO3r17zc3NsVjs4OAg0LXBwcG6ujoWi2Vubl5cXCyXy1UqVVVV1f379yUSCYPBeOGFF+zs7J7EUJ6dneXxeDdu3EChUL29vVgs9sCBA05OTt3d3dCB27dvR0ZGlpaWNjY2KpXK8PDwxMREmOIkEsmNGzdycnLMzMx6e3ujoqJsbW3hpK6urjgcTiAQ8Pl8AwMDhCgDgFdNTU319fVhsVjgfI9kDHv37uXz+fOmax6Px+VysVgsDDNra+vHXenw8HB7e7uDg8Mj/yqRSNrb29VqtbOzM4FA0O6hSCTq6uoCBcLj2p+amuLz+bC+mpqaMpnMXyzBfCRgNdG+dliGYQL8YxUIwcHB1dXVC/dKQ7Bs2TI2m11YWAhG5u/cPRMTE11d3SevRO3l5TU2NvZf5aA0Go1Go3V2dtrY2ACbhA+WlpYoFMrBwQGDwfT09Dg6Ov4pCNPw8DA8XSqVumnTpscl2Pv4+LS1tVVUVOBwuJ6envr6+ri4uOjoaERBArIhMpn8szYclUrV19cHmikWi8E+E4vFLS0t1tbWCQkJy5Yt+4+k0+Hh4chnX19fHo+XlpYmkUgWrjSurq6urq4IeRocHLx06RJM5Tt27IiNjeVyuYvEd8rKyv6jqlRkMllPT097TqFQKPOO2Nra6urqNjU1ffjhh0Qi0crKat++fSgUikQiwVRFIpH09fXBNSISidRqdW9v7+3bt+fm5gQCAdw9Mpmso6MDzcbHx+/YsQPR62ibxVQqNTg4ODU1FYvFuri4bNiwwdHR0dTUtKamRigUDg0Nubi4FBQUTExMrFixgsPhUCgUIpGoVCpNTEyCg4O1mR8KhZqbm7t9+3ZlZeW///3vHTt20Gi04eFhSBS4dOkSn893dXXlcDhMJjM0NDQsLOzKlStJSUmbNm2qrq6+cOECDocjkUjt7e14PB6DwUxOTpaXl7NYLDc3N5jvwsLCgoODIUIxOztLIBAoFEpUVBRomKRSaWpqKtKZa9euff3116tXr961a5exsTGBQKipqVGr1RYWFs7OzhkZGeDzgCF38uRJsVgcEhLi4uIyPT2dl5d37tw5V1fXyMhIPz+/0tJSIpEYHh5uaGgoFApPnjxZWlqanJzs5eXFZDLNzc2hw/7+/gkJCfb29vOWNBDh6erqBgYGPv/88yUlJZOTkxqNxsnJSalUCoVCDw+PwMDA+Ph4NBr9zDPP1NfX9/X1QX22y5cv37lz55lnnlm/fj2Dwejp6QEy97hVraKiIj4+fteuXVKptKCgYGho6I033tDT09uyZYtAICguLnZwcLC2tsbj8S4uLq2trbt3716+fDmBQPjxxx8zMzN37tzp5+cHY+/LL79cuXIli8WytLQsKysTCoWdnZ36+vrgUhUKhUKh0M3NLSgo6Pjx41lZWadPn/by8rKxsTl58mRVVdX58+d9fHykUmlaWlpzc/Phw4dhwVAqlampqcnJye+++66np2ddXd3XX389PDwcHBzs6ekJtw6Px5uYmEgkkqmpKRhs7u7up06dKi0tvXz5sp2d3f79+ykUSmFh4fnz56lUKhaLLSgomJubm5ubO3ToEB6PP3HiBFCEoaGhkydPbt261dTUFLhIV1dXY2OjTCYrLy8fGhqCn9jb2/8sZ+LxeIcPH4aRIBAI7t+/L5PJXnvttb6+vvr6+pKSkpqamq6uLiMjo+np6fT09KqqKo1Gs23bNiKReP369S+++IJGo/n7+2dnZ9fX1+vr66PR6MDAQDs7O2TANDc3X716lcvlBgUFIetZSUnJgwcPCgoK8Hj8K6+8EhwcPC9WWFZW1tPTo1KpCgoK/vWvf5FIpKKior6+PnBXA/POyspSKpURERGRkZEsFmseX+nr6+vs7FSr1QKBICUlZd26ddpGf1lZWXt7e1pamkKh2LNnT3x8PNKBgoKC2trajIwMhULBYrEOHDjg6ek5705KpdIffvghOzs7ICCguLjYx8fnwIEDcPngQMVisXQ6/cGDB0qlUk9PLzIyEofD3bhxA9yliYmJ8yja4OBgQUGBSqXicDhBQUGLPDh40UAY+sg1KD8/f3Bw0NHRcXx8HI1Gh4SEYLHYoaGh/Pz8sLAwQ0PDurq6trY2WDhiYmL09PTQaLRIJLp79y5Y8tbW1j4+Pov0ARQCi6yADAZjZmYGjUZjsdhHZib9V0EikUgk0pPzV+Cmv20fGhsbDQ0NjY2Nte8S8CTtD66uriUlJQEBASKRqLe318LC4k9BmPh8/vT0NMxujzM4UCjUP/7xj9HR0YqKivr6ektLy02bNsXHx0O1RviCQCCQSqWTk5Ozs7OPs4kf+fzAKZWQkGBhYYHYT/PW5kUglUpVKhWJRELS1oyNjfF4PIFAkMvls7Oz8Bm01XK5nEwmwzdpNBqLxSIQCJaWlhD2XmTQhIeHDw4OqtVquVyuVqt/gcH0uEIDISEh+/fvP3HiRH19vVqtrqmpmZycPHLkCPDrebIDHo8HiSHAHjZu3KhWq9euXaurq4t48p2cnJ6EbrLZbCMjIxwO5+zsbGlpWVpa2t3dDSlCaDRaKpVKJBJ4NBgMZt4Uhtia2dnZIpHIyckJKI6enl5ISAiVSgUJVGhoKERtIPKLRqPheF9fn1AolMvl33//vVQq1dPTg2nukWd5QiQnJzc1NYHLikKh7N69G3QMTCYT5q+Ojg4Itv70009VVVVsNvvq1asghpBKpVNTUxMTE0Qi0cbGBo/HUyiUwMBAU1NTqVTa3t5eV1fX3NwMHlYY82g02t/fXzsnFgGU9cLhcHl5efPcpWvWrGlvbwdhMszF2t7KsrKymzdv0ul0X19feK0sLCy049rzoKOjc/DgQQildXZ2VlRUaA+qxsbG+vp6lUoF65BUKvXx8dmwYQOVSi0pKUlLS9PX14+Li7OxsQHXZlNTk1wut7a2RgxQLy8vDw+P5uZmU1NTYIFmZmZqtXpiYqK6unp8fFwoFM7MzPD5fJVKtWLFCmtrazQaDYurm5sb6LeUSuXt27clEom9vb2Pj8/Q0BAYkbW1tS4uLkAdyGSyg4MDgUCg0+n79+/39PSkUCh0Ov3w4cM1NTU8Hg9cg6ampoGBgVBeISQk5NChQ1euXImPj7e1tbW2tqbT6RMTE2ZmZnZ2dg4ODjgcDn7V29vr7OycmJjY0NDwxhtv3Lx5MzIychHXC0ClUn333Xf379//+uuvQTDQ3t5+7969wMDA0NBQIKPgnHv55ZfRaDSZTL5x40ZSUlJCQoJGozl//jwWi3311VcjIiKYTOZ7771XWFjo7+/v6+tLIBAqKip6enrUanVFRcXAwICfn5+fnx8yi164cIHD4czNzVVXV4vFYhKJtHz5cm1SjsPhpqenT58+zePx3nrrLUhMHh8fP3fuXHd3d319vb+/f1tbW0tLS1VVVUVFxeeff649nc7NzZ04caK2tlalUnV2dp48edLf3x+xr5qamr755hsvL6/S0tKZmRkCgRAREQF0p7i4+OOPPwZTE41Gf/PNN3Nzc59++qmtra32ED1z5kxeXt7y5cv9/f07OzsvX768ffv2wcHBrKys6elpHo+3Zs2arq6uW7duicVimLjm5uZ++OEHoDtTU1PPPfccmEkymezHH39sa2srLi4WiUSGhobvv/9+YGDg454deMUW15+cPHnSyMhIKBQ6OjoGBQWp1eoPP/ywoKDA1taWyWRisdirV6/y+fyYmJjo6GiFQnH37t2ysrLCwsJVq1aVlJQQiUQPD49Dhw4xGAypVKpUKqurq/Py8g4ePFhZWVlQUPDWW2898tRisbijoyMtLU2lUg0MDFRWVuJwODs7u3lvt1wul8lk4+PjFy9ejI2N1dfXT05OVqlULBZr27ZtWCz22LFjCoUCjUa//vrr4M5EvHonTpwgEAjgfQgLC4MbheSn37x5s6mpCdag2dnZed1TKpX5+fn5+fnwhU2bNv0mEu/HPQVoWSaTIUn0Tk5OSDBOKpXCggLDnkgkmpubKxSKP4wwTU1N9fb2wgAFTmdlZWVlZYWwn7a2Nh6PJ5fLJRLJ0NCQtbX19PT06Ogol8sNDg4GWQkej9dmABwOh0gk9vf319fXw+I3NTX1s8xp27ZtbW1t7e3tEonEysqKTCaLRCLwrj/htVRXV2dmZq5Zs8bd3Z1IJE5MTAiFwmXLlsXHx2dmZlZVVVlZWW3ZssXc3LywsPDGjRtvvvkmuCi6u7sfPnxoZGRkYWExMTExPDxMoVAsLCwWuitpNFpMTExBQUFfX9+FCxf27dtnYWHxn2ZIJSUlBQUFcblcPp+vrdCSy+UJCQnW1tYSiWRkZOTIkSPp6emHDh1C6KO2H55Go2EwGDMzs6CgIKTUta6u7q/R4o2Ojk5OTioUClDnvPDCC1999dXFixebmprYbLZUKo2Ojo6MjFzoeFMqlaOjo0qlks/n+/n54fF4IpGIVHZAoVC5ubl79uyB2XZh7iGNRnN1dbW2tiaTyVFRUVgsNjAwkEgk/rLK8oODg9oSFi6Xy2QyYcGGyCb8C+qNubk5Ho8HszCfz7e2tra2tg4ICFj46EkkEvLDJ0F/f/+FCxdmZma4XC6DwVho2SuVSrjPj/T1Tk9Pi0SiJwxMw44BfX19aWlpPT092uldJBJpw4YNWVlZdXV1d+7cefrppy9fvhwQEGBlZYXFYmtra/v7+7FY7Pnz5y0tLcfGxiD0M09ubGFh4ejoaGNjQyAQpqen5+bmiouLc3JyKBSKWq22s7OzsLBA7kx3d7e5uTlo/I2Njel0upmZGQ6HUygUUDU0MzOzu7u7u7vbwsJCJpPNu9VUKpVGow0ODk5OTuro6BCJxNDQUDs7u/r6euQ77u7udnZ2fD5fLBZbWVnhcLiJiYm5uTk9Pb34+Pgff/yxp6fHyMjoqaeeMjQ0xGAwoHZ66qmnAgMDWSyWlZXVp59+Ojw8/CS6Zo1Gk5mZCRNgZ2cnpN+KRCKhUMjlciHtX1dXd9++fZC3ERoaevv27f7+frVaXVBQ0NLSQiAQaDQalUo1MTHB4XAWFhbvvvtuYGAgHo83NDSEpc7X13fdunXm5uZEIhFUVgQCYePGjVBSbvfu3SUlJc3NzT4+PtrvjqOjI6TEQt4DCoVycXERi8VdXV0ikei5555zd3ePjY19++23GxoaxsfHP/roI23ChMPhgoODm5qaRkZGbG1t9+7da2hoiCyNDAYjMTFx2bJlUqn0zJkz5eXlqampu3btUigU9+7dKyoqOnv2bFhYGAqFOnbsWGZm5ksvvWRtba09ztPS0mQymbe3t7e3t4mJyVdffYXH4yHl8+DBgzBC4uPjw8LCzp07197e/sMPPzCZzNjY2DNnzvT09Fy6dAkYLQaDuXfv3r1797Zv3+7l5fWvf/2ruLj4zp077u7uj1NuCQSCxZ+sm5tbdHT0Z599JpFI3njjDSwWq1Aorl27NjY2Vl9f7+7ubmNj4+3tPTIyEh8fr6urW1lZ+fHHH09NTb377rteXl6WlpZffPFFaWlpaGhoaGhobm5uXV1denp6a2urjY3Nd99919raeujQoYXn7evrO378eE9Pz8zMDEy5QqGQQqGMjY3N63BHR0dOTk5hYWFubm5+fn5AQEBlZWVnZ6dGoykqKrKzsysvLx8YGBgYGMDhcO+88w68gH19fUePHm1ubn7llVfkcvmRI0cePnx4+PDhiIgINBotk8muXr1648YNRJG5UKd7//79s2fPwtw7ODhYUVFx7NgxR0fH/wZnQlbPqqoqCwsL2FoOWe9YLFZOTs7q1auJRKKzszOfz2exWEA3/zDC1N7e/vDhQ5FItHr1ah0dnampKRiXiHz99OnTWVlZNjY2PT09+fn5rq6uFy9erKysNDU1dXFxKSkpmZ6eNjIyCgoKiomJgdKIzs7OsKb++OOP6enp7u7uMNYmYxAAACAASURBVBrq6urGx8cZDEZ9ff3ExARUEDExMVm9ejWdTo+MjExPT8/IyPj++++Hh4d1dXXHxsb09PTWrVs3z12Zn5/f399fW1srk8kGBgZSU1NNTU1XrVrFZrOLioq6u7uDgoKoVCr4YPbv3x8SEvLWW29dv36dQqHY2dmxWCw0Gl1ZWXnlyhV4Qh0dHRKJ5LnnnjMyMkpPT7969aqtre2hQ4e0l3xEWODr6/vss88ePXr00qVLKpUqICAgKioKEUiVlZVNT08/spQ2/FYgEBQWFl6+fNnExCQjIwMRMMFIBX06g8Ho6uo6derUyMgIBNoQX2VfXx+of2Dx5vP5c3NzUI4PlMW/phqQgYEBOBVoNBoWi924cWN7e3trayv4C7ds2eLk5ARJeQsDjl5eXoODgykpKdHR0dqTckBAQFtbW1VVFWLKQIP+/v4I8RKLxTQabfXq1fN0ZgjAn//LanOj0WjoDxqNhhgoVGpAoVAeHh7Z2dkzMzPr1q1zc3ODg8bGxra2tr8+TyorKyspKYnL5YaHh9vb28/TUgDf1ZYDzhM3WFlZCQQCxKeyODIyMs6dO2dvb6/RaExMTOaxOhsbGzMzs6Kioqamptzc3JaWll27dkHqkEwmAz8li8VydXXF4/FRUVHaNUK1Ac+rrq7u+PHjEolkxYoVfn5+Fy9enJycnJ6eNjExSUxMzMjIOHnyZG9vb1lZGZFIfPbZZ52cnObxY2tra3d3dy8vr6eeegr+q/1kKRQKhUIhkUhIzQ4ikYjH4/X19d3d3eG58Pn8urq65ORkCwsLFxcXlUrl4uJibGxMJBKpVCry7CAiAwYGBoNB3iOI5T35oxSLxRqNpqenh0KhYLHY5cuXOzg4uLq6Io2QSCQfHx84r3YUhsvlEonEvr6+kZERtVotEonAjerj4wOuXysrK0ggcHZ2BpE7BFhhHK5duxYihnp6et3d3QuHCpVKnZcCpqOjgxyJj48HWUV3d/cbb7yx0PgkEAixsbHZ2dnZ2dlcLnfjxo3ab66pqemGDRsoFMr+/fsrKysfPnwIfsq+vr47d+5IJJKJiYmMjAyNRqNUKsHFstDxzOPxjh492tXVZWBgEBcXZ2RkBDa2SqWam5vjcrnR0dH+/v7V1dW5ublUKnXXrl3e3t50Ov3zzz9vaWnJzs42NzcHf/OWLVvWrl2Lx+Pb29s/+eST3t5eiUTyuCBRWFgYn88vLi5ev349nU4vKirq7e1FjHYnJydPT8+QkJAPP/xQqVRCPC4zM3N6ehqFQp09e3br1q0UCqW3txcyiPF4vEAgaGxsNDY23rRpE5lMtrGxgYJwP/zwQ1BQkLm5OXALhULR09NjZWX1uBKp9+/fT0pKeuaZZyIiIjAYTGFhYVNTk0qlEgqF854ODPiPPvpIKBQqlcoVK1aEhYUdPny4pKSkp6fno48+ev311y9fvnzhwoUrV67ExcV5eHgMDQ0dPXo0OTn5//7v/2JiYtRqdXNz8wcffHD06NHQ0FAMBnP9+vXPPvssNjY2KioKBkl1dbVQKNS2bD/88ENzc/M333wTsmQuXLjw/fffHz169L+RwYcEQNhsNjL2FApFUVFRSEgIWBcoFCo7O3vVqlV1dXX6+vqQbPSHESYDAwNfX182m+3s7KyjoyORSMbHx7XjON7e3kZGRi4uLj09PRCx4nK5urq6w8PDaWlpQqEQ3Pg1NTU1NTUffPABl8slkUgvvfTSnTt3qqqqCASCh4dHX1+fk5OTqalpTk7OxMREf3+/kZFRbGysiYlJYWFhQEAAnU43NDR84YUXAgICkpKSzp8/j8fjN27cCCbXwm6Xl5f7+vp6e3uDJrqwsNDPz8/Kymrz5s3ff/99R0cHFLfcvn27v78/lUqNi4srKirS0dGBWgCenp6HDh1KSkqamJjAYrGJiYmvvvpqUFAQjUYbGRkpLy/XaDSPS5EzMjLasmWLQqH49ttvMzIySkpKCgsLgaYQCITW1tb4+HiFQnH79u3Z2VkajZaVlSUSiTZv3kyn01evXg2yg++//z4yMtLGxgYqJ92+fRsIR0FBQX19fUxMTFlZmVKp3LBhA8gO1qxZk56e3tDQ8Nlnn0VEREAYtLi4uKam5siRI2ZmZhQKpb29/ciRI+ClV6vVRCLx8uXLY2NjCQkJOjo6dXV11dXVGAymubm5rKwM1kXwcMjlcsjiMTAwoNPpEokEeJhMJuvt7Z2bm3N1dQV5slQqNTIy0tXVBUalPU1HR0cXFxeXlZVdu3YtMTGRSqUSCAQymbxu3bo7d+6IxeLZ2dnJyUkMBtPU1IRCoSBv0d/f383NraSk5PLly+7u7s7OzjgcLiMjIzY2lsFgzM3NwRynUCimp6dJJBJk1UEmIBTtkMlkILxTqVQgVqNQKBgMBspdapc/wWAwIOSvra2VSqUoFGrt2rXffffdzMyMjY2Nj4+Prq4u3I3/yGWo0WhAQzMvN4rP58/MzOjq6rq4uMwr9AouaI1GA4HghW2ampoaGBhgMJji4uK6ujpnZ+fq6mqoQPHIPly9ejUrK8vR0XH79u319fUL2d6GDRsyMjIqKipaWloSExPhPgMXweFwarWazWYHBQX9bKX7qamp8+fPZ2VlPfPMMzt37jQ2NiaTyT09PWNjY0FBQfv27ePxeLDgeXp6+vn5xcbGzkttAwK3cuXKx6lNBwcH+/v7RSJRR0cHaJsqKyubm5vNzMxAa9/f33/kyJGqqqp169a5u7vDRo2g6X5ctzs6OkAZ9musZDMzM/CeQukQQ0PDn2XVDg4Ou3fv/vTTT+/duzcwMNDb2yuTybZv3/4kSuTR0VHEDfBrgEajIeK5SM7v4oDidshDnJ2dhTBiZmbmli1bCATCe++9p1KpbGxs5j3oXbt2ffDBBw0NDf39/Xg83t3dHUo8IE/BwcGBRCLRaDTwbHE4HFACbN68+ebNmx0dHSYmJtDmsmXLMBhMY2NjZmZmV1cX8FeggI98pvCCI7mTaWlpmZmZQOmwWOyePXvc3d3Nzc1DQ0MfPHhw4cIFa2vrL774Ytu2bVevXoVsoY0bN7a1tb300ktYLHZmZubGjRvaAwxsbzQa3dDQAIp4MDwUCkVYWFhCQgIsBwvH4cWLF8E4t7KyAnf7vXv3Ojo6oLV5omwTExMYKhs2bFi1ahW4JFEoVGBgYGJioq2tLZFILCwsHBwcrK6udnd35/F4V65ckUgk8fHxULjVyckJg8EUFRWlpKRs3rz5/PnzLS0tBw4cAI4It0j7pNevX6+srPTx8fHw8MBgMDk5OWAj/bd5iJWVlVKpvHHjBtw66BUILsEgQSwrHA5HpVL/MMJkbm5uZmamVCpB+gPSHO0nvX79eqVSSSaT5XI5yOK6u7t9fHxAB4e4qb777rvGxkZ4w4lE4ubNm729vXt6enR1db28vEDagsfjxWKxgYGBsbGxsbGxjo4OuCKhHRKJFBgYuGzZMkdHR2D6/v7+TCZz4eTi4eEBsUyE2HG5XGgkISGBw+GIRCIymbxs2TImkwmz5MqVKz/55BMdHR03NzcCgUAkEtesWUOj0UBzFxAQYGBgQCQSMRhMVFRUR0dHZGTkIptsGBkZ7dy5097eXiwWX79+vb29Hca6k5NTXFxcYGCgQCBAoVCrVq2CJPyWlha5XI7BYFauXPnZZ5+lpKSA1D88PFwqldrZ2bW3t6tUqvXr15ubm9+7dy89PX12dvbtt9/28fHhcDhoNDo4ODgoKKirq2t8fByyjiMiIt58882UlJTh4eGJiQkvLy8oItXY2FhWVmZpaRkTEyMUCnt7exUKBWwNgUajX3zxRTDmnJycqqurh4aGMBhMWVlZamrqjh07+vv7+/r6WCxWenr6qlWrKBRKXV3d8PAwrEajo6MYDCY9PV1PT+/jjz/W3loEj8dHRka2trZevHjx1KlT+fn5urq6GzZsiIyM9PLyeu6557777rtPP/0UkiUNDQ1XrlwZGxtLpVLd3d3ff//9zz//vKOj49///reBgYGpqens7Cy4+sGFwGKxhELhF198sXXrVrlcnpWVRSAQTExMzp49u2bNmra2ttzcXAKBoKOjk52dzWazX3zxxaNHj+bl5X366acbN27U0dGh0Wh2dnYdHR0ZGRlisbixsbGtrY3JZHK5XBsbm9HR0a+++qq8vDw8PFylUvX39ycmJoJNqVQqJRJJdXU1Ho9nMpmIv2FgYAAGMJvNHhsb++abb6ysrKKjo6FQwjxV4xtvvGFlZQUu7qamJn19fSABMpksNzc3PDw8LCwMmba6urqam5shIoDH4+vr699//32IhQmFQrVa3d/fX1NTs2LFCu2ZbnBwEPji+Pg4n88Hi18gEIA0DQxuXV3dlpYWlUr1zTffIC9ORETElStXqqurYcwAYYItgx7J5ORyOZQE6+3t5fF4P/3008jICHBBlUpVUVHR3d29efNmXV1d2A2qr69vYGDAy8sLXkMbG5vx8fFvv/0WHgpo3WxsbLQZKpQzmJ6eTktLA712ZmamSqV67bXXIA8O9gUfGhr66KOPwsLC4F3r6elBdAULMTAwoFKpQKH/izlTeno6Uo1iHhQKBY/HYzAYC6k2aKTMzMycnZ0dHR1DQkLCw8OfxFdqZmb25PLNPwS+vr5wLZBqMy/LD8Jex48f12g0ly9fbmtru3v3rpub26FDhx7HlYeHh4VCIZvNNjAwAOt9dHQUTKaKiopbt26ZmpoinJ5Opy9CWEEnikgqKRQKg8EAxmNkZOTv7w/mk4+PT3Z29uXLlx0dHcVi8WuvvTY1NXX79m0Y2KOjoxEREUCDgCM+yW0BCdQjh1lfXx+QD5jV4V3D4XAqlUp7V9OFgGAu0qaxsTH4gFksFo1Gk0gkJiYmaDRaLBYLhUIikWhqaqrdAZj/N23a1N/fv3ikEkLJTU1NSUlJaDR6dHTUz88PERX9V4FGo0Ehg8Ph3N3dUShUS0sLhAK9vLzACzUzM1NaWhoVFfWHESYYc8gIxmAw8wgKEuKB79y5c6ehoWHPnj2bN29GCFNxcXFycnJ0dDSQDAwGQ6PRvLy84DpRKNTy5csXziNIGF7bRUwgEGJiYhbvM51On9egv78/fGAymXFxcY90/UVHR8+LL8TGxi78pqOj4yuvvMLlcheXSxsZGa1ZswaFQtnb20M0GoYvKJ+goLutrS345JydncF1DG52a2troVBoampqbGy8d+9eU1PT3t5ePT09ExMTOzs7R0dHiURCIpFcXV2R2YFMJr/yyiuw6EKNADQavXHjRhcXF3DUm5qacrlcPB5vbGzs5eXl5ubG5XKnpqZAP4FCoUJDQ5cvX25nZwdmLpVKnZqaiouLs7CwmJmZEYlEcrncwMAgNjbWyMiosrKSQqGATNjT0xMirY6OjkNDQ1lZWTgc7q233pq3F5upqem+ffuIROLg4KBGo6HRaBwOB4fDUSiUf/zjH3g8vq2tDSy81157zcnJCVzWOBxu5cqVFAqlsrKyoaFBLpebmpp6eHjA7WIwGG+++SaZTJ6bm2tqajIwMAB5gb29vZub2/j4OJFIhGqoLi4u1tbWoFIHse3nn39+/fr1xsZG2IDPysqqv7+fz+evXbuWSCRmZWVBpaIXX3zRycnp1q1bzc3NeXl5UVFRMJdBatjatWt1dHQKCgrIZPLKlSvt7e23bNkiFAqhppG5ufm+ffs+//zzgoICHR2deTORp6dnYmJiSUkJiURycXHZtm2bRCKRSqXDw8MYDCYwMNDZ2RmFQo2PjyuVSiKRuH79ej8/Px0dnYGBAWdn5y1btkxPT8PQguxCQ0PDgYEBGC0+Pj7aq05wcHBtbW16enpHR4exsbFKpZqYmPjmm2/eeOMNcCZRKJTQ0NCLFy/6+Phop3Y7ODhs2rSpqanpwYMHbW1tYHTGxsY6OTk1NjaWl5dDtnN6erpMJlu5cqWurm54eHh1dXVOTg6DwTA2NoarLi4uDgwMLCsr6+/vP3nypPa7AzQ9Li4Oj8e/+uqrn332WWFhoUgkAtLg7+//9ttva5doJ5PJUOilpKRkdHQUh8PRaLS9e/fCgwOO5eDgMDY2dvbs2aGhoaKiIhi92sFrFApVU1Pz448/2tjYIHlnOTk5r7zyCuh5/6N5PCQkJC0tLT8//+LFi0iw0svLC54gOF1u3bqF+O20ATlfU1NTIyMj8Ne7d++CGB/S/h933qGhod/Ew/Sbg8lkenh4lJaWVlZWhoeHz5NVaeP27dsffPABiUSytbW9c+fOJ598YmFhsUiWzOTkpLbTaHJyEkl4/Omnn+7evXvz5k1HR8e+vr6bN2/yeLxFNI4gl6yurt66dSuBQNiyZUtERAQMDx0dHQ8PD8S/gkajm5qaBALBoUOH7Ozstm7dCuVdWlpaVq5cCQozHR2duLi4X+9oUSqV80R7kC4ABZyfRK0bGhqanp4uEolg2heLxTKZTCQSIXYL0PeHDx9GRkYit5pIJHp7ez+5qWBsbAweJk9PT1hwf9tiEI8EFotFdkcBU0EgEDg6OpaWljo4OIA4wdzc/P8jVai/CCAdFzKJdHR0lEqlSCS6ceOGWCyGwpWovz7s7e2f/MswpBYaBBDufGSDyDwL4QntL5BIJF9f30eeCOrEa0NXV3chE+VyuVwu95HmIBItBlcBhL3Cw8NBIk2n04lE4o4dO6hUKgjJ33//fScnp/379yOVY0pLS+vq6h43j1tZWe3duxf+isfjIRsAeOT27dsRgS0iSkA4uq+vr42NTVRUlFqthjITSFkEJpOJx+OVSqW3t7e+vj6ZTA4MDIQJUSqVQiqWr6+vXC6n0WhI5uP69espFEpfXx+U/XR3dycQCE5OTv/3f//n6OgIxTyIRCKwcy8vLx8fn/HxcY1GA3IEUIhDtiaRSOzt7QU9jYeHh6mp6cTEhFwux+PxZDI5ISGBQqFIpdJly5ZZWlpqr39BQUF2dnbR0dGOjo7m5uYrV64EAxem4H379iGVDGECfe655yBoAh0D4g4Uk0wms9lsV1dXCD5CrqL2nd+5c6ehoaFEIiGTydbW1p6ennBDtENszz//vIODg5OT0zzXaXx8PKKbQWRnBAKBRCKx2ez33ntPqVSampqCd5BIJEL5e6lUamZm5ubmZmNjMzMzAyYvaODCwsLAlBoYGLh8+bJQKDQ2Ng4PDyeRSLBXCeybhIz/ecsth8MxNTUdHBx89tlnwVozNzePiIhAtEFsNjsiIqKzs7OmpobL5Xp6ehYWForF4vT0dEik37FjR2dnZ3Nz8+Tk5LvvvltQUCCTyfT09Kanp1NSUiCliMFgGBgYQCrQzp07EYZ3586dgoICiOp+++23oaGhAQEBBw8eRKFQhYWFly5dgrzUPXv2EInEK1euFBUVgWoqPz8/Li4OshrhDn/zzTfr1q2DzMG8vLympiaEB0DBYog3wY19+PAhZC9GRUVduHBBKpUKhcL+/n5zc3PEpyUWiycnJ42MjLSjY4hfTSgUMplMSC6DI2fPnn3++eeRn2s0GqFQSCKRHlnuvKGh4b333jtw4AAUMoWoMaSLIqeDCDiLxYqMjKyrq3vw4IFcLn/33XczMjJwONyuXbvMzc21V1bYmQBEqE1NTWQy2d3dfRGOyOfzh4eHra2tKyoqeDwewgAEAkFpaalCoWhvb/fw8CgrK1OpVHw+f5GUoNbWVtiPDDGDtS1zbanTjz/+2NHRsWzZsri4OCwWGxISYmJiUltbSyaTN2/ejESu3dzcyGTy9PT0jRs3Nm/ePDk5eevWLZVK9cwzzzx5BB8mDYlEcu7cORh1vb29IyMjcrkc1NxPKKdDksehcoGuri6YefDaQiE60Egh/GPt2rXIf69fvx4aGspms6GM3Lw1BY1Gd3d3s1gsBweHxTkWyPK0iyz+JkDKVMJCCVM6pLfLZLLu7m4HB4e/DGHatGlTW1vbrVu3qqurd+3aNTIyUlFRMTw8nJCQAMsSagl/BUANBbDXtY+D2J9Go2k0mry8PMh/Rupk9Pf343A4iJ0/Lo7wOJNloYJ+nkW4MAaKOLFwOBzUftVuH+nDQl+gnp7e2rVrQTkEom/IKDQ0NASbEoJcQF8gsgb+CVD1otFoyEKAIA7cKBwOx2AwGAyGpaUlCGLgRBs2bNBoNAsrmjCZTH19fYi7QyLV4k9kYS7kvFIFHA7ncb+1trZ+5plnoMgFHo9fuXIlTL5IiQ0UCgVOOBAtaU9wHA4HfqvtfMVisTY2NlwuF5nE8Xg80F9bW1szMzOoZ00ikSwtLaF6bVFRUWFh4ZYtW1544QVwEE5NTYlEoitXrgwNDUH7VCp11apVwcHBSLNQgmueoQnVNUNCQry8vLBYLJwI6TOJREpMTHRwcFAqlZaWlpDYKJfLqVQqDIn169fr6uoCqfX29h4aGnr33XfBKtDX14erePvtt6enpwkEwrxaaGZmZqGhob6+vlCODjYjX7Zs2dtvv93d3Q2UF5LLIEVGT08PAlI4HA42VPfx8Tl27Bho6fT19YODgycnJ2FPTDjR8ePHy8vLMzIyoqOjCQTC3r17x8bGlEplW1vbunXrmpuba2trvb291Wo1iCmjo6Mh7XdwcPDu3bs7duxARn55eXlFRYW3t7dCobh///7MzMzs7GxdXZ23tzfUjK2vrw8MDASXvFQqvXnz5sqVK2E7TuSSLS0t/f39NRpNS0vLxMRESUmJRqNZvnw5CAGffvppBoNhb2/v7+8P24Da2dlt3LiRx+N1d3dLpdL09PT6+nrI5ltoeZaVlc3NzYFd/eKLL5qYmIyNjXV3d4PnElgvh8OBYu79/f1FRUXgBAWnY39/f0lJCVB/tVp97Nix3t5eMIRQKFRzc7OFhQVSPrS7u7uqqgrK74Frqrq6uqqqKjQ09HEszcvLi8PhjI6ObtiwATgHk8n09vaur6/fsGHDihUrkJfa29t7x44dSUlJ165dg5+0tbUtX748Pj7+Zx2WsOGdtbW1k5NTRETErVu3vvjiC7lc7ubmVllZSSAQVCqVtotoIdrb2+VyOZFIbGhoUKlU1dXVPT09+vr6g4ODs7OzYrF4dHQUQpDPPvvsuXPnmpubBwYG2Gx2e3u7RqOBOsxAQTo6OnJzc997772AgABwf2ifaO/evbC1fGZmJlSoAhbl6uqq0Wiam5u1v1xWVobsaf0bciakjA7M9rCZLJlMBqEqHPzLECYvL6+XX345PT19enp6aGhodnZWR0fn+eefd3V1heThJS7ytwFUHrp69equXbsYDEZ2dvaDBw9sbGyefvrp37/M2n+KhdM31MhBFt158dl5X4bdNrTD1vNW9EVOpN3I71NoGIPBaGdHPpLOYrHYR2ZQzisBpd3II9tBmJO28xyFQkFZSEhNh6vW1dUFUZe2SOtxzWqPOolEAjIsSB1Y+B07Ozs7Ozvkv+vXr59nJWsfYTAYC70LkZGRjzy7h4eHh4fHEx5f6N8FfxhEDVAoFNQf2bt3786dO4F7gTOvvr4eqiGgUKjAwMB//vOfSqUSjUZDBd29e/ci/BXy+/bv3w9JpkQiUXvsQYYNEnNks9kymUxfXx/ZZAO0LJaWlh988AGQDKQbCFavXu3p6QmrtZmZmbu7O1LRF3lTNm7cGBYWptFoQJ1jb2//+uuvI4ld0dHRZmZm2q4vxKmJ5MZCdS4Gg8Hn83k83rp166De+sDAgI6Ojo+PD7BzqB5kaWm5detWZ2dnExOT3t7euLi4V199ta6uDkqWx8TEGBgYKJVKqO/A4/FiYmLEYrGhoWFfX5+Pj8/Y2Nj69euBCoDn+HGDjUgkxsXF+fv7x8TE4PF4WPWfe+45DAazfv16AwMD7YTHAwcOUCgUPB7f09Mjk8mee+45X19f4AoPHz4sKCgAv2lycvKKFSt8fX2TkpKqqqrUajWPx/vyyy/feecdExOTbdu2lZaW8vn848ePv/jii7Gxsd3d3Tdv3uzu7m5vb3d2dkbuYXt7O4SbUSjUlStXbGxsXFxcgAB1dHQkJSW5ubmxWCwdHZ329vZr166FhoZyOJyXX34Zi8VevHjx2LFj1tbWxcXFu3btSkxMhGHz8ssvC4XC/Pz81NTUycnJjRs3wruck5MDCdqBgYFr1qxJSUk5c+YMUg34rbfecnFxuXPnzoULF9RqtUKhOHv2LBaLTU1Nrays9PT0TEhI+DWEaXBwcHh42NPTE9ktrbe3d2ZmxsXFBco137t3LzY2Fo1Gg0v1r0SYwGMPNe609St/YAX6JfyXsH379lu3bv30008Qfq2srFSpVM8//3xUVNTPplMt4X8Nzs7ODAbjypUrnp6eIJAfHBwsKSnZuXPn1q1bn7Bev0qlam1tFQgEMzMzlZWVkFo7zyX2F0JGRkZra+trr72GVG2dmpqCRQ6S1WGbSGTH7nl8S5uuPbL9ecTxcWAwGIjKcyGg8J729L7wOwvrGD+JEPiR3TY0NFyxYgXCNfF4vK6u7tNPP43QGqDI8fHxUVFRcMTAwGDz5s3AcaHivJWVFcSmmUymv78/cgNxOBwGg7GxsXn55ZeR9hfX32zcuHEej/Ty8gKH98LszpdeeglJNqTRaEZGRvBYaTSas7PzkSNHNBoNl8sFC8TAwGDt2rUgIdDT04PrCg4OhkoBKBQqJCTE09NTpVJBjZV5qnkikQj1OYGHGRkZUSiUvXv3AoUCj5GZmdkbb7whEAj09PTADrG0tHzhhRc4HI6enh6NRtu2bduyZcvMzc2hZX9//8OHD9fW1kI/IyMjpVKpWCw2NjZGQg2vv/46eFiRnri6ukJNll27doGJBeGC0dFRLBYLGVq/BlAfGIVCQZUTJMNaIpE8ePBg3bp1DAYDNAOIZYj+8+8LvYT/KWg0mqGhoZqaGqlUCnuJyGQyOp3u7e39mwetl/A3wNTU1KlTp0pKSvT19ZlMJoghhtA8cwAAIABJREFU5HL5zp07YQO4J2lkZmbm+PHjxcXFMpkMQhi7du1CNtP4y+HIkSPffPONt7d3TEwMCAEzMzM7Ojq4XO6rr77K5XJ/By3tEn4HwCYT87yw86JdELWH7QXBgwhH5HI5UCLImUeGOhQQ1vYiQ74ecgQhGXBqpH0odIL4lbX3pdZuFurTau9gDYFvlUoFIjbtE2l3G0FxcfHMzIyHhwdU9v/Fd0+pVKrVajwe39vbOz4+7u3tDQIJjUbT1NTk6ekJBW4UCoWTk1NfXx+BQFgiTEtYwhL+2hgaGurt7YUthA0NDVkslpmZ2eK5YAsXnoaGBu1VwcPDY/ENuf7M6Orq+uGHH6anp2EX4fDwcD6fj0Kh/iMSuYQl/I9gcnJSLBZrK6K6u7slEomzszPsecBisbq6ulBLHqYlLGEJfw+MjIyATPuR2Vj/a+jr6wP+V1FR4enpCbsGsVisJba0hCWgUKjx8XFtrRgKhZLJZPfu3duwYQMajR4YGJDJZJaWlmg0OjMz08/PD5R/S1rpJSzh74ampqZFMgr/rlg8HfJ/DUheJ1TZWGKQS1iCNoqKitatW4dCoWpqakD3jcViERkfTCa1tbWenp4cDketVsOuIUuR7CUs4e+GlJSUX7Z/8BL+fviVG7MsYQl/SyBZCxMTE/ABh8NBmc20tDSohA5/cnV1JRKJf2SW3Ozs7NmzZ+fm5sDNNT09LZFIDAwMINVwbm4uODjYwsLi0qVLw8PDBw4c0N6Z63dDcnJybW3tihUroqKioDgHFEWFLSbmfVmhUNTU1GRlZanV6j179iBbCCOYmJhISUnp6OhITEyErejUavXw8DCJRKLT6b+Pn3yR/i/h74SAgICl7NElLGEJS3gckHRLpJjFyMgIpB9C7T34E1TsxOPxUNHmj/EwSaXS1tZWDofj5ubm5ubW19eXnp7OZDLhv0qlsq+vTyQSVVdXJyUlDQ8P/yFCq9HR0atXr5aUlCDFiM+dO3f69GmEkGpDIpEMDw/X19enpaVNTU0t/EJjY6NSqbx58yayU4dKpfrkk09SU1N/B2fAxMREfn7+Rx999O233y6+edAfjsbGxoqKiv/e5gwNDQ1ZWVmtra2/eE/QPz/CwsL+q/UXZDJZXl4ebBqwNPMuYQlL+OuCxWKBC7a0tBSOIHyDxWINDg5Colx/f/8fRphQKJSenl5QUFB0dHR0dLSFhQWZTPb/f+y9d1yT5/4+nh0SkgAhjACBQJiy9xQEZCrDVXfVo9bR1traHjtO209Px2mPrba1bq0bFBygyBBBkKWAEBCZQhhhhbACJGSQ/P54/77PK6+A1B5rtefw/sOX4sOd+7lzj+t+j+sKCIB/Ojs7EwgEfX19f39/4Nl8KT1ctGgRlUpVF4oyMjIyNjae0T0DojlmZmZPa43NZnt6euLxeKAnRqFQaDQaxOH/BPeSXC4fGhoqKSl58ODBqykUBQD/1KlTX3311fHjx5+fY2NGq6mp+eGHHz777LPMzMxXdhye315ozkppaemhQ4c+//zze/fuIaBTJBKdOHGiurpavdBszuZszubsr2II6RccDfn5+ZAYbmhoSCAQgDPs5YRmKBRKYmIiIsOuYSBepq+vb2Ji8hI1T9hstkZcY/HixSqVCuQXpgMmMzOzWXrLZrOBNAwxLBa7YcMGIpH4jNx6z2O6urq+vr7q6qeviA0MDMhkMkNDQ6jisbS0FAqFHh4eLyiipKOjExMTk5OT09nZ+ZzeEZlM1tfXp1AoTE1N/+M0kf379z958iQhISEkJOQvEUQTi8UPHjygUqlr1qwBCsTx8fHU1NS2trb79+/r6enR6fRDhw7Fxsb6+/vPnnV+5MgRqVS6efNmdQXcF2pSqfTEiRNdXV2jo6MkEsnAwAC5q3R3d7u4uKxZs+YP8cyNjY1dv359+fLlSGtyuby7uxs4/ZA1KBKJQJoD+UUajTadt3AWNVwjIyOxWKyvr/+71rVEIklPTy8uLmaz2W+++eafsP/M2Zy9aqZSqS5durRq1SqVStXf3w8advBfEKQzNDQkEokgwZmcnLx69WqBQPByAJOWlpa3t/fTFjlAOfUTiM/nt7S0EIlEd3f36XIKXC63r6/P3NwcJKuettFXVFSMj4+TyWQvLy/1Pbq0tBSiVDQabcb21bezJ0+eaGtrqzuZ+vr6Hj9+PDk5aWxsrMG7Nbuh0ejpqU4vbsBNTExIJNKr5gBISUnh8XgffPCBkZGRjo5OcHDwmTNnuru7X1C8zNzc3NTU9LPPPnv+pvr6+j777DOhUPjzzz+z2ez/DDANDQ319fVBmPzV32Lkcvnly5dlMll0dLSRkREWi8VgMOXl5bm5uRERET4+Pk5OThKJJDk52crK6mlazojl5+ePjY2tXbv2+QFTR0dHY2NjUFDQ7MxJGAzG0dFxcHDw4sWLbDZ79+7dyGJ/9OhRWVmZOsR5HqusrBQKhQjbXn19fV1dXUpKysaNGyMiIpA9qrS09NSpU+pgKD4+fv369RoI5ujRo1wuV52fELkQb9y4MTk5+feyK+Xl5VVXV/f09NBoNA1KwL+0yeXyvLy8qakpUMV51TI1QX1vjtbh1TFQoAftv0WLFqn7F6qqqtzc3GQyGZfLdXd353A4sEu8nCkFJXyz7GsaToisrKx79+4RicSAgIBly5Y5ODiAL6e7uzs7O1ulUpFIpM7Ozrt377722msGBgYaDRYXFz969AiAzqVLl/r6+hYtWgSipPn5+Yj6YHJyMofDWbp0KdI+Yp2dnTk5OQMDA2NjY2+//Tayq167dq2/v59CoaSlpalUKiBvePZx4PP5/f39Dg4O0OCNGzempqbCw8Pz8/NBbHzJkiVsNlt9rIaHh0GOZ9WqVaA6Pr1ZEMsUiUTgrvP19dU4BsRi8aVLl+zt7Wf05TQ0NBQUFBCJxCVLliC89Tk5OT4+PojSAgqFUigUeXl5/v7+NBqts7NzcHDQ0tLy4cOHPj4+cAQWFxdXV1dLpdKgoCA3N7cZPSiPHj2qqal56623YFYA4WxdXd3vgp7PbhgM5o/ysRGJRIlE8pwNrl+/fnx8HHxUr/7+Mjk5efLkydjYWF1dXejw+Pg4gI9FixYZGBig0eiBgYEtW7a4uLj85nG1aNEiqVT6/O4NgUDw008/lZaWpqamzg538Hh8aGioQCDAYDD6+vphYWGI7jKRSLxy5cofMkpFRUXHjx/fu3evlpbW+Pj42bNn8Xg8iC0sWLBAHaB0dnbCro2MlZGR0fTpVF5e3tLSEh0djawgsVh85swZDoejra09ODj4448//uMf/5gu1vY0y8jIWLduHYlEolAo/03FASqVamxsLC8vr66uTiQSJSQkXLp0CdRhqVTqpk2bXsoq6+/vT05OVigUhYWFu3fvXrBggcbZp1AofvnlF3B4W1lZxcfHvxSo9/jx45ycHNA8/s3rX1lZmYmJibm5+V+3ABP0quFQsLOzQ6FQUqk0MzMzMTFRqVTC3g5rDS4nWVlZ9vb2f4FqqcLCQi8vL2tr64GBgVu3btHpdBaLRafTu7u7Dxw4gMPhEhMTTU1Ns7KyLly4IBQKd+7cqY6ZxsfHc3Jy2Gy2n5+ftra2RCJpbGwMCQkhEol37txJTk7eunWrlZUVBoMZGxtLSkqi0+nm5uYaS0tbW9vGxubGjRtoNBog0fj4eFpaWm5u7rJly5ydnalUqlgsvnLlCvCB/qY9fPiwpKSktLTU3d3dwsJiYGAgMzMzOTmZwWAIhcLCwsKenp6BgQEul/vBBx+AkujY2FhqaurQ0BCHw2loaADZ5+XLl+vq6mp4Pvbt20cgELy9vYeGhk6fPq2lpeXp6QlvJBaLs7KyhoeHi4qKCASCqanptm3bQJYZ2p+cnAwODrazszt37ty9e/eio6NjY2OpVGptbe2VK1eoVOr69esdHR0JBEJPT09WVpajoyONRtPW1i4rKzt79iyZTAZ96YMHDxoaGrLZ7La2tsOHD//973+3t7fX2AhGR0fHx8clEgmPx5PJZBYWFsiwAy5sbGx0d3cPCAiws7ND/mtwcLC/vz8/P7+joyMyMtLe3p7JZE7fYqRSaXd3t0KhOH369MDAAKTHaagmicXivr4+iURSWlq6fPlyPT29iYmJ/v5+kUhUU1MDWkJjY2MCgeDu3btDQ0MCgYBIJL733nv6+vpSqXRgYGB4ePjJkydSqdTY2BiJtvB4PLlcjkaj1d9ocHBwdHSUxWKJRCKRSATsOBwOp7OzUz2i19vba2BggMPhOjo6pFKpoaEhjUbTOAihfRQKRSKRZnx3dYP+g3/CwMBAR0cHWoP24RkdHR0Gg4Hs4xKJpKenB3FpmJiYwLhNTU11dHT09/ePj4+D5ujExERBQcGWLVsQ146ent4bb7xBpVJ/c9OPi4uDq85z7g9CofDGjRuhoaHP6Bxyc3ObHsPy8vICxsvn7Extbe1XX30VEhJiY2ODw+EmJyc7OzuXLl0KCgzTn4+KigoPD0cmCYVCmf4YHo//8ssv/f39kf9qaGgYHBxct26diYnJG2+88e23337zzTfffvvts/jqDh8+3NbW5uzsPGNqwV/acDhcYGDg3bt3GxoajI2NMRiMlZUVg8G4cOFCa2vrunXrXgpg0tLScnBwmJqa+u6774qLi+fPn68BmNBoNDzw7bffWlpaLlq06M8HTCdPniwuLs7Ly1uyZInGgaJhqampjx8/LigocHJy+vHHH5+/q7t377azs1u3bh0EvzQu9nw+f2pq6vr162+88YYGz+QfeIu2sbGBv5ibm8OKgxo6AoEA+tl4PN7U1NTS0vIvAJgcHBzi4uIoFAooBl+/fj0qKopOp1+6dOnhw4cff/yxm5sbkUhcuHBhSkpKeXn5+vXr1QFTXV1dXl7e0qVLGQwGnU6Pjo6+d+8eHo8XCARHjhzhcDgcDgc40VeuXMnj8a5duxYdHY14VsDodHpwcPChQ4cQz0dDQ8PRo0dBZllPT8/CwkKlUnG53I6Ojmd5KQaDYW9vf+DAASaTqVQqKRTKvHnzlEpla2urVCpdtWoVBoOprKy8cOFCcnLynj17tLW1L126lJeXl5CQEBYWZmdn99133924ccPNzQ1SSZCWk5KSKisrv/jiC39//4mJibq6upGREYVCAZvF0NCQQqGAakRon0ql7tmzh8FgcLnco0ePbt68mcViOTg4SCSSH374Yd++fUqlMiEhITo6+sSJEwBc4LCBD2ppaTEwMKDT6bq6ug8ePPjoo4+oVGpRUVFVVdUHH3zg7u4+NDT08OHD8fFxjajT2NjY+fPnKyoqIIgjEAgOHDjAZrMBLRUUFLS0tAgEgoyMjOzs7IMHD0JCPSSGY7FYe3v7oaGhw4cPu7u7v/XWW4irALHs7OyioiIWi8Xn88fGxk6fPu3l5YVI3IONjIwUFxfn5+cPDw/Hxsbq6ekNDg4WFxdnZ2crlcrIyEhdXd1Hjx7l5eU5ODiYmZmVlpbm5eVt375dX1+/qKiorq5OKBQWFBSYmJiEhoZaW1u3t7c3NTXx+XyFQlFVVbVs2bIFCxbgcLiCgoKioqKWlpYPP/zw5s2bTU1N33//vVAofPz4cWpq6muvvRYaGvrw4UOJRFJWVrZq1are3t7k5OTBwcH58+d7enoGBQUhZ/nDhw+5XK5MJlMqlQ0NDYGBgWQymcFgAFfFdN9qT0/P8PDwvXv3RkZGtm7dGhUVJRQK6+rquru7AXWJRKLR0dFNmzZZWVnBVn716tXa2lozM7OxsbHKysrw8PCNGzdSKJSHDx/KZLKsrCxTU9O+vj64jI6OjiqVSrFY3N7ebmtrW1ZWNjo66uzszGKxYJ6Mjo7ev38fWTienp5MJpPH4zU3N9NoNG9vb+T8KCsrQyJZxsbG7u7uSqWysLAQVAU5HE5zczPEal1dXVksFvyiXC4fGxsjk8lVVVVmZmagKDeLA1u9jAPZIlgslo+Pz/N7H/l8vkgkio6OhrgbhUJZv369ra1tb2+vRuMikai+vt7f39/ExGT2ZC8/P7/Fixcjx0l9fX16evquXbtg4bu5uS1cuPDEiRPPGMXOz8+XSqX/lQIPGAzGxMTEx8cnJycHHDb+/v4qlermzZsDAwMvK/hIo9EWLlwIwEgkEk0feQwGAw8g4rh/vtnb2zc1NfX29v5mZqeVldXExMTAwEBXV9cfMouSk5OdnJwiIyOR+HhGRgaHw7G3tx8eHs7Pz793715tbW1kZCQU9v+B/siysjJ/f38EhOFwOHd3d/D5tba2enl5PXjwwN/fn8vlWltbOzk5of4STN+Ojo4UCgWLxerq6lpaWp47d25iYgJciAKB4Pbt21VVVYhz3tTUdPp81dPTS0lJGRwc1NXVJZFIYWFhOjo6QqGwtbU1IiICkXTVaF/jEgCmHijs6uqytbWFyzf817PjXwsLCxAPh3/q6+uHhIRACZ6/v7+rqyt8eXl5eS0tLZOTkwqFIikpydPTMyQkhEaj6ejorFmzZu/evfX19eAfUg9yDQwMCIVClUrFYDCWL1/OZDKRB3R0dPz9/SFi4u7ufufOHWh/dHQ0JSWlqanJzs6OTCZjsdiwsLC6urp9+/ZdvHgxODjY2dl56dKl1dXVIpFIqVRWVlbK5fKurq779++7u7sTicSenp7g4GAfHx8SiSSTyUZGRoaGhlQqFZPJXL16tZmZmcaBATCRRqNhsVgnJyehUIic91NTUyAGjsViz58/f/78+WvXrm3atAmPxx89erSlpWXlypXh4eHe3t5nzpzJysry8/MDl6F6+7du3XJ0dPTx8Zk/fz4KhfrnP/+pUChUKpX6d0Sj0Tw8PCBoAj/R1dV1d3c/duwYYO6xsbHk5GQajTZ//nxDQ0MnJ6f6+npogUKhBAQE3L5929nZ2dra2tDQcGBg4Oeff9bX1wdvh0KhOH78+NTUVEhICPg179y5Y2NjU1tbC9hILpePjo7y+XyYQhKJJCMjIz8/n0KhWFpaWllZMZnM4uJiLpfr6uoKgOnhw4f79u3bsmULnU5XKBQ///xzYWHh8uXLAwICpm9ehYWFR44cSUxM9PDwEIlExcXF/f39U1NTNTU133///e7du1ksFhqNbmlp+fzzzwUCwTfffGNgYHDz5s3U1NTo6GgPD4+RkZF79+6dPHly2bJlFApFJpOpVCojIyMQ2UChUOnp6WKx+O7du0KhkEQiOTk5nThxQiAQfPTRR0g96YkTJ9ra2nx8fIhEYlVVFY1Gk8vlBw4cqKiocHZ2dnR0hC+upKTkp59+ioqKIpPJEokkKSlp586dbm5uXC43LS0N3OZMJtPY2Pjy5csODg7//Oc/IYAFfUhLS6utrTUxMfnb3/42/RKvEQHRODuzs7MTEhI0LrinTp3SyMjetm2bjo7OLGscXPoBAQEImNPS0oJ9dsb9GgDrsWPHII1p+/btoBys8eSqVavUxV7y8vLIZLKrqytcgdBodGxs7NmzZ/Py8hITE3/TiQKZA2VlZSKRKDEx8b+PDh5KROVyuUqlgm/h5YaNZs8/eZYH/gQLCgpqa2t7loHy9PTU1tbG4/FOTk5/yMC++eabpqamyI03NTX1u+++27Rpk52dHY1G8/X1PX78OJVKNTEx+cPfGlzsQPezfPlymUyWkZGxdOlSFAoF1w94APa9x48fo/7q0ihkMtne3h4BSRYWFnQ6XSOHycrK6pNPPvn+++/LysowGMzAwMDAwMDmzZtfzWxHGo3GYDDgpGEymdra2oAzZDJZb2/v48ePjx8/Dmfn6OgokUicfifevHlza2vrgQMH0tLSLC0tQ0NDkSgMCoWiUqnq7SORlLGxsdLS0tjYWESylEQiLVu2rKioqL+/H2ZPZGTk9evXeTyera1tfn6+vb39hg0bsrKyAgMDdXR0cnJyVq5cCZlh4C379ttvL168OG/ePAiGaqwuMpkcGxubn5/f3Ny8cOFCfX19ZM0AjrGzs8NgMAQCobKysqioaPny5RQK5caNG87Ozrq6uu3t7SgUysnJ6dSpUw0NDX5+fupb/4ULF5qbm9955x17e3t4Hcgr1+gDhUJxcnLS1dVFRLZpNJqzszMSBcPj8SYmJnl5eRUVFWw2G4PBbN26FbyP0HJkZKSfnx94U956663BwcFly5Z5e3sTCAQWi3Xw4MHy8vKAgABfX9/S0lICgeDi4rJgwQKoVtXT0+vp6RkfHx8aGsLj8f7+/hUVFZOTkyKRyNvbOywsDIVCvf/++3V1dT09Pfr6+l1dXV9//bWVlZWHh4eenp5KpdqwYcPJkydtbW2BiUP91aqrq7/55pvQ0NCgoCATExNLS0tTU1MymSwUCo8fP25tbe3r6wsEJGw2u6CgID09ff369SqV6sqVK0QiMSYmxtzcXKFQFBcXHzlypLOz08DAwMHBAfq5aNEiCoVCpVL5fD4OhzMxMfH29jY0NKRSqTExMZ9//jngdRQK9euvv3K53FWrVrm4uODx+NbW1omJCRKJFB0dXV5ezuPxAL7k5eXt27cvMDBwwYIFZDJ5cHDwiy++sLGxcXBwiI6OLioq4nK5mzdvhi+rt7f36tWr33zzzVdffaWjo+Pt7R0SEmJpaenp6UmhUDgczuzHD2z3T548+fnnn2Ep3bx5MywsDDoMelI1NTWurq6wsXR1df373/9es2bNb/qfpFLp7du3N2zY8CyqvTgcjkKhZGZm9vX1QQ0dl8uNi4tbunSphqcQimDAampqbt++vWvXLvXZbmZmJpfLCwsLY2NjZwdMFRUVbW1tg4ODycnJk5OTMTExRCIRguZ0Oh2LxY6Pj3d3d69duzY4OBiPx9fV1R06dEgikezatev48eOTk5Nff/21RrKURCJJS0trbGwkkUhDQ0NCoXDPnj3IulM3iUTy+eef6+npQf5DT0/Pp59+amFhkZSUVFBQYGtrGx0dnZycrFKpBALBzp072Wz2mTNnxsbGurq6lErljz/+CIBVLBanpqa2t7cTicTBwcHh4eG///3v1tbW0Ctzc3MqlTo7tFW3lpYWpBRGX1/fwMAAAqmmpqaAoTs6OsRiMcAvGxsbDAajUCiePHmifoJYWVkRiUQ0Gi2Tydra2pRKJYvF6u7uViqVWlpasHVM/+iJiYnOzk4ElIvF4umecjCIPMDbIa4dPT09Y2PjlpYWcAuRSCQLC4vpH9TZ2QlXo6eNQG9vL51Of5q7CK7TwOgIPzEyMnJ3d29qanpGDxO0/7RS4m3btmlpaSFXhbS0tLGxMV9fXzQaTaVSoQyrv7+/vb2dyWT+saeti4sLAFZYYlgs1tLSUj0kBw/Y2dmRSCT4av7agElXV3f+/PkIx/mMNjQ0ZGpq+v7774+PjyuVysuXL6ekpNjZ2SE1hH8hMzExcXZ2RuJKwcHBDg4OGttrYGDg7t2709PTR0dHz58/X1xcHB8fv2nTpqctRcSpMzY25u7url7VbG1tbWFhgRB16ujoSKVSqVTa3t7e2Njo4+MTEhJy9uzZ3t5eyFx2cnKCfdzMzGzz5s05OTlCofDUqVO5ubnr1q177bXXAE4hF0FDQ0M4WshksroQGIFAQJCik5OTsbHxxMSEUqmsqKiA+s/KykpIWJFKpf7+/siFHrEHDx5MTEyAYxIZlv8s/yA0NPTatWvffPMN7J6JiYm6urpubm5UKlWpVOrr60OiOgQ7IGdrYGAALi4ikQigmKGhIYVCIRAI7u7u6ucfjC0Oh8PhcIaGhoAFWSyWiYkJeB8DAwMfP37c2dlpb28vFAofPHiAaISpVCotLa3w8HAfHx/1CnkkNlRVVfXhhx+CG4bBYISGhqpUKpFIBIFsZIei0+murq6XL18+c+ZMcHBwWVlZZGRkWVkZOG7b29vlcnlTU5OLi4uuri4Gg6FQKJCwhUKh3NzcCASCnZ1dVFQUdFhbW/u7776DPvB4vNTU1M2bNy9cuBBmqbu7u7GxMZ1Oj4uLO3369NjYGFwGfvjhh4KCgnfffZfFYhEIBBwOJ5fLU1JSli9f7uTkZGtr++TJk5iYGNgx33zzzcePH9+7d29yclJHR8fOzm5oaMjOzi4+Pl5PT+83j8nBwUH4RScnJ+jz/fv3kTkvFAoPHDgAIIxOp6PRaC6XOzw8bGtrCyfi7M6b0dHRZzxFpFIplUo1NzeHqo68vLwjR47AUfE0YQOZTJaens5isZycnDS+bqVSOWO4R8MMDAxoNJqZmRl41LS0tBobGw8cOEAkEp2dnfF4fGdn5/Xr19va2j7//POgoKC6urq6urqysjJLS8uhoaHKykqRSKRxbvX09Fy7di0kJMTKyqquru7SpUtkMvnf//739JSye/fuVVZWvv322yQSicfjXb16dWhoyNzcXCKRXL9+nUgkDgwMjI+Pczic1NTUwcHBxMTE9vZ2FxeXhoaGkpKS/Pz8uLg4PB7f3t6ekZERERHBYrGqq6sh8fSLL74A+NvU1DQ8PPzsdMe3b9/OzMxUKBSxsbHe3t76+vo8Hu/jjz/+5JNPoKittraWy+WOjo7a29tDtmtubu61a9fc3d2xWCyfz3/48OHatWtfe+01PB6fnp5+9uxZuVz+z3/+8+uvv5ZKpWvXrkXC0xrh8u7ubmA57u/vv3//fnt7+/QICVhRUVFqaqpCoYiJiWlubnZ2dr59+zabzQ4ICLh165aPj09FRYVCodizZ4+Liwt8llKpvHHjhlKpzMzMjIqKwmKxwcHB6mlANTU1bW1tKpWqqKjI2dm5urpaY8Ta2tpqampkMplUKtXW1obBh1xGuVw+Y3lTT0/PgwcPoB0XFxcOh4NGo1NTU5cuXQqvlpOTAwEcKpUaHh5eUVHR3d3N4XAAmsB5jcFg2tvbWSxWc3NzUFAQPIywb/+Bnj+I8WGxWGAywuFwHh4e8F96enpcLtfS0hLyK/B4fG9vr5eQWR+IAAAgAElEQVSX10sGTJBPgPypUCgwGIxG8GuWiHV3d3dFRQWTyYTDDNJUoQXksebm5pGRkZCQEEj+JxAI9+7d6+vrs7a2RqPRubm5kNSMwWCAUjImJmZ2bKE+4pmZmR4eHhCeaGpqqq+vf0HlXQiCCQsLm72K4datW35+fpCElJubm5ube+HChYSEhN98KQwGk5+fn5CQQKVSYTuura1tbGyMjIyE/FBjY2M/P7/8/Py2trbg4GB7e3uxWOzl5YXBYLKzs01MTOCSClMwLi7Ow8NjdHS0oKDg5s2bSUlJERER6oBpRquqqmptbUVqGJG7eGRkJEIiampq6uXlhTwAocwXVOyjUqlsbW3ffffdpqYmuVyen5//yy+/xMfH29jYkMlkNpttaGio/tFKpVKhUMCFVaVS7dixw8fHZ5a+WVpaamlpIYcfJMBxOBwkRIjFYslkMmR2M5nMwMDA7Ozsd955h0ajXb9+PTk5OSoq6hm5T+GcQ3xpM3amt7dXKBTa2NhAUAOFQvn4+HA4HJC7/10VoCgUisvlNjQ0QIkA/AQCcxqJokqlEnjwr1y5Ul1djcViJyYmTE1N58+fj/gJ1F/Q1NTU2Ni4u7sbAbW/i57D1NRUW1vbyMgIqZKbmpqCHGEUCjU+Pt7c3Lxu3bpn8RI9p3c8MTHRxMQEYCgs2PT09CdPnpibm88ImJKSkioqKnbt2vUfE6qx2WxgvwsPD4fc3nv37mVkZNy8edPV1RWLxYpEIm1t7c8+++zatWs+Pj6enp4JCQkPHz6kUCh79+7lcrnTyfPIZPKSJUsgxcTT0zMnJ6e2tnbGVJhLly5RqVTweY+OjmprazOZTDQaHRMT88MPPxAIBC8vLycnJ0NDw7KyMgAEGzZssLW19ff337NnT0pKSlRUFB6P19bWXrZsWVRUFATQMzIyamtr1WsUcDhcY2NjVFTUs6Qku7u737p1Ky8vb+/eveChGRwcvHPnjq6u7tGjR0kkkoODQ2dn58jIiIeHBwaDycvL+/nnn2NjY/38/LBYbGdn5+3bt/fv36+lpZWQkIDD4eAZZ2dnJyenmzdvAsbS+NCSkpKvv/5669atkDnX29srl8sfPXo0iy8kPT09Ozs7PDzcw8PD09Ozubk5KSmJQqE4Ozv7+fmhUKjPPvvM1dXVyckJzrLk5ORr164tW7aMw+FMTU3l5+eXl5d/8cUXsBgbGhr+9a9/BQYGGhgYmJmZnTlzprOzU526oq+v79tvvzUzM3N2djYwMDh69KhQKPzb3/6Gw+HgsHZxcZm+QFQq1e3bt7lc7ptvvgkeOFjdw8PD//jHP7BYrFwur6iouH379ocffgi3yn379iUkJDg6OmKx2AcPHvB4PD6f/80334SEhIjF4oCAALjUsVisM2fOQFKBlpbWrl27kJvqH2UKhQKLxQLr0qpVq2A0lEolAIOpqampqamXDJjS09N5PB6Px6PRaJcvX759+/aKFSsgKtTW1sbn8+VyeVtbm7m5uXoizpMnT5hM5po1a9ra2g4ePKhQKOB6dOvWLRaLtWjRIvU8/9HR0dOnT8vlcltbWwwGAyGkwMBADoezbt26pKSkqqoqsViMwWD6+/uLioogo3xwcLC7u1sikQiFwqamJiwWC1VOUqm0ubmZTqc7OzsvW7YsJydn165dUVFRHR0dTCYTi8VOTU01NzczGAw9PT31Xb67u7utrU0mk3V3d/N4vN/r3wJ/TFpamouLS1hYGIlEAr8xnU7X+KA7d+64uLg4ODhADhOfzy8rK/vNy5a+vv7SpUvPnz9fXV3NYrHgdtjQ0CAWiyMjIwGdGBoaenl5HT58uLu7e926dYaGhgqFws3NDbK+4M4KrR0/fjwwMNDBwQEKEHp7e5uamp7lNRkMBo1G4/P56hmsKpUKfmJvb6+lpYVGoy0tLZ9GqaDuSe7v7zc1Nf29dRz9/f1isRhcZSMjI9nZ2SEhIQsXLlSpVFFRUdu2bevu7oY7Vk9PD5fLfe211xDHhqmpaWBgIFIxAMlMs6SJPH78GJy98A329PTA2yFTvampSSgU8ng8OEj27t373nvvnT59GuoWN2/e7O3t/UepoERHR5eWlgJQjo2NRaqo4Cr2H6RZDA0NQUq4uofjaQ/7+fkFBQVBlFCpVAYFBc2bN8/Q0BBKPWJiYjRec9GiReBRmJyc7Ovri4yMfMZ0nLKysv7+fnU3SXBwMBaL7evrMzIyOnz4sLm5uZ2d3YuuVNJIb7KwsEhMTLxw4cLTHEX9/f2pqalMJhMSHP+obggEArFYjATiaTRafHz8wYMHYZLb2NgAhvDw8HB1dYV7gsYpxWAwAgMD+/r6ent7eTzewMDA0+rvlEplbW3tjh07Xn/9dVNTU2tra7jompmZEYlEW1vbhQsXgldv5cqVjx498vPzc3Nzw+Px4Hnt6OiAucRkMn19fbu7u/l8voGBgcbEUCqVWCz2aVGw5uZmddxvZmbm5eWVkJBQXl6ura0NuPnEiRM6OjoZGRkA+8zNze/du7dw4UJnZ2csFltcXFxTU3Pq1ClAe3Z2dlQqdePGjXl5eYsXL54/f35HR0dOTo6Xl1dwcHBoaCjALI1I3K1btzo6Ovz9/WHCA8NLTk7O0xCAg4ODg4NDVVVVWFiYjY0NjUaTSCRHjhwxNTVdunSpgYGBlZXVP/7xD8SvlpGR8e2333755Ze+vr7w6W1tbSdOnGAwGLt375ZIJF999ZWlpWVUVBR8WWw2+/bt26dOnUI+8dNPPxUKhdu3bzc3NyeRSCkpKQcOHKBSqStXrsTj8WQyecZ6cAaDsXr16ry8vPr6+oSEBIVCkZ6eXlRURCQSP/74YywW6+7uXlBQ4OvrC9nWjo6OLS0tGRkZS5YssbW1BS+7SqXatWsXnU6H3R72yU8++aSrqysoKAgwAw6He/vtt58HMPF4PA3+vCtXrqxcuRL1//iZYLYDviQQCPb29tnZ2S8ZMFlaWkLWiHoSDzJGMpksIiKir6+vtbWVTqfj8XgrK6tFixbx+Xwej+fj47Nr166bN2+2t7eLxWIsFisQCCB9RCOMZWJi0tLSMjg4CFNny5Yt7u7uWlpaGzduBHQ/MjKCRqPHxsacnJz8/PzIZHJTUxOXyw0ICNDV1a2vr6fT6Y8ePbKxsZmammpsbLS1tWWxWDt37sTj8Twer62tTSKRuLi4aGlpMZnM1tZWNpuN+GkQ92ZPT8+CBQtUKlVzc7NCoeDxeKOjo83NzTdu3IBZC96/W7duJSQkGBsbw693d3dnZGTExMRs2bLlxx9//Omnn4AyeHh4uKmpafXq1ZA3jXyQSCTKzMwEZ2NfX59QKNy6dSt4nqDMHtoH4kHU/yNtWrJkyaJFi/Lz8yFQAoizs7Nzw4YNyOEB62R8fHzevHkQuSMQCG5ubikpKdHR0a6ursiJlZube//+/dDQUIgednZ2rlixQqPwUMP3i8fjjYyMZDKZQqF49OiRuqNuamqqvr5eKpXCFba4uDglJWXz5s06OjoSiaS5udnW1lajINzNzS07O/v48eO7d+8GOoOKigoHB4fpqVTIsZGRkREVFVVXVzc0NDQ0NAQjAJd+KysrkLUxMjKCKxeBQMBisdbW1tnZ2Xw+XywWQ1wYRhjidM8y//v6+sDrCf90dXUtLCxsb2+HlAgUCmVra6unpwceJjweT6PRcDjcvHnz9PX13d3doURulvbv37/v5eU1vVIdKvjUDz8vLy9jY2NbW1tjY+PS0tKenh42m/2cZdhsNtvU1LSiosLS0nKWfmIwGG9v76amJnt7e29vb42h4/P5AwMDo6OjGk6Ljo4O+MnY2Fhra6u2tjbcDpEHSktLPT09p6MouVyukb9IpVL7+/vT0tJef/11EBEaGRn583McIbyI+Lo0LCcnp6mp6YMPPniWsOOzo6WmpiYNSkwqlTp9woBXe0YP8fj4+Pnz56empoyMjHR1dacXh6tnq0xNTVVWVvJ4PCi1OXjwIPI8iURCctuNjIyg9nPGpkQi0ZkzZ/B4vIGBgYeHh8Y3NTk5qVQq1dPk1e3bb7/t7u5GIOnevXtDQkJiYmKSk5NPnz7t4uLy8OHD5ubmHTt2HD9+vLi4OCIiorCwsLu7GyoJ4I6kUCiQc0pLS2vBggUUCgUKgRkMBrwa5AjOmKrM4/FgsiEvSCQSQe1gFufHwMCAlZWVqakpfDR8Izo6OgAxwU+JPP/o0aOmpiZ17q4VK1YkJSUVFhbu2rXrzp07vb29X375pZWVFXRg2bJlExMTv/76K5LSkJaW5ubmpqen9/jxY2NjYwaDwePxqqurX3vttcnJyaGhIUir1+gnkUgMDg6mUqlNTU1aWlpjY2Pnzp1zdnaurKysqKgAT1hzc/OePXugMl1XVzckJAQmP6SCBQUF1dfXu7u7Ix6s4OBgqMWOiYlxcnKyt7ffsWPHvXv3gL3vP7b6+nooylYP4MBfgJ8JUGlNTY2fn19BQcGCBQssLCxeMmCCKr4ZzdHREXkfXV1d2Pg8PDxMTU0VCgWdTicSiREREQ4ODog3IjAw0MrKSuPstLOze+edd5C0vpCQEAsLC5hGJiYmr7/++vDwMLLk9PT0jIyMcDicsbGxt7c3dA8ouXE4HHIjBLjA4XC2b98O6wSPx7PZbBsbG39/f6VSOV1yzsrKik6nh4aGwtYglUpxONz27dspFAqSk7RixQoN6ZXVq1cLhUIdHR0tLa24uDgtLS0ejwdnD5lMdnNzQ3AVYnFxcciAUKnUxMREQGnq7SMTfe3atUKhkEajqVSqefPmvfvuu+3t7cgAuri4wJpRP1b37NkTERGBdNLPz+/999/38PBQ30yXLl0qEAgIBEJmZmZgYGB4ePjChQs1SvqRcNvIyMixY8eMjY03btx44cKFpqYmAoFw9OjRtWvX2traAiXx6OjokSNH1q1bt3379v379ycnJw8MDFCpVKhfeOuttzS+9JiYmI6OjsuXLyuVSnNzcy0trcrKyvfffx8IDiYmJrhc7i+//PL222/T6fTExMSvvvrq8OHDXC53YmICCJm6urpA4uPJkyeHDh2ys7OD7SwqKio+Ph5IUG1tbSkUytmzZx0dHVks1pIlSy5fvvz9999/9dVXDAZDqVT++uuv8+bN8/b27u3tLS8vn5yclEql4PiF4F1zczOfz+/s7HRyclIqlRBzlMlk8BcY9omJiY6ODnd3dxwOBzwO5eXlgOfAIbR06VKNSkm4Hnl7e6ekpIyMjCxatMjKyurq1atQwBUREQHkijt27KBSqUKhsKysLCYmRkdHx8fH54MPPvjyyy8PHDiQn5//5ptvNjY2crncTZs2kclkmUyGRqOLioqA3HVGUKi+jbq7uzs7O586dYpMJkOSk0KhgJjF1NQUIqqIx+OXLFny3nvvnTp1ysrKSl9fX6lUgifA2dm5v7+/p6cHSh1hTOB3LSws4CeGhoYhISFZWVmhoaGweFUqVUlJyQ8//HDy5EkNwAR+dfBDSKVSBJeLRCJQxV6+fPnly5eB/QU+TuNgAEIHLBb7nBGBy5cvx8bGInBBLpenpqa6u7sjacUKhQKypuCKlZSUtHDhQgDuv5nnIJfL09LSEhMT/wReyoMHD9bW1r7++usWFhYGBgaXLl16mry3u7v7Rx99VFNT09LSMjU1BS4NJPdI3ZqamtBotKmp6YzYcd++fTweb9OmTSYmJtOpPjs7O6VS6Yzpz3CVYrFYyBcKkMXc3NzAwKCmpkapVKakpGzatCkuLi43Nzc1NXXBggWpqalbtmzhcDjPyTqBVMONjIy0tbXV19erQ73pOF7dJBJJQ0ODs7Pzf0wVZmNjgwS4k5KS9PT01MGcUqlUF4HIyMgYGxvjcrlNTU0nTpwIDw93cXH5+OOP/fz8MBgMxFLv3r37tMDF2rVrT58+XVlZCeHRjz/+eOXKlWlpaZ6eniKRiEKhODo6qj8P4w99a2xs1BgHlUrF4XA2bNgAVTvPktrxLAYESygUCgJwaDTay8sLVj0Wi21qahKLxcgzyCXt1U36Vs+NRYxOp6vn4uDxeODonMVoNNos4wv+pxlDVBqsDzMq32lAVCaT+bRMflNTU/WEPolEYmxsDAHaGfsMizM+Ph72ax0dHTweHxsbOzk5iUxTIpEIF2v13124cKE6zwqJRIISd39/f0St4mntL1q0SKN9CoWivk04OztzOBwdHR3ksDQwMFi6dCkwEaiDNmiWyWRaW1traWmpV+qp2/r16xcsWIDBYHA4nIGBQUREhKenJwaDATIIDAZjYGDwwQcfyGQyCoVCp9MtLS0pFEp7e3t/f//k5KSDgwODwZgOxYDQD9Iy8vLygoODra2tTUxMJicnJycnv//+e8grh9MUSG4mJiaoVCqJRAK6puHhYTKZzGKxPvnkEzQajTiH582bB7sAAPQff/yRQCCA7Ax48srLy0+ePKmtra1SqXg8nr+/f05ODpfLFYlEFhYWly5dioyM9PLy6urqAu54BoNRVFTU2dmJxWIbGxv19PRKS0sRPxYUzuTm5s6bN8/Z2XlwcHB8fLy8vBzZNwUCQWVl5cmTJ9Wz5sF3++mnn+7btw8wIoPBGB8fj4yM1NPT27NnDx6Pr6qqOnbsGJFI1NLSWrx4MVQL43C45cuXQ5V+aWkpDofr6+uD5Nby8vLS0lLIK7px44aFhcX4+HhLS4uhoWF/f39jY6Orq2t/f/+xY8e0tbUhCOvk5LRr166PP/543759V69eTUxMvHv37saNGx0cHEpKSjo6OqytrRsbG11cXCIiIjZs2HDz5s233norLCwM5MH9/f1tbGx4PJ5YLB4cHLx06dLGjRu1tbUbGxvhxL127drq1asZDEZsbOx333334YcfwnTq7Oz8+uuvoUZJY2J0dHTcuHFDT08P4CziQpuYmID5Zm1tzWKxkpKSgCoCjUanpaWp+zuPHj1aVVUVGRk5vZwNiO801uPIyEhnZyc4j/l8fmNjo7OzMw6Hu3PnTnt7e2hoqK2tbWdn540bN3p6enbs2AGkmpmZmWlpafv376fRaDKZ7NNPP21ra9u9e/eMAAjgHRKkLikpOXv2bGdnZ0xMjMbzAoFAJBKNj4/39/fTaDRdXV0ga25vb0ci+z09PVKpdHohxdPsypUrvr6+8+fP19XVhaztp52jR44c2bFjB5vNlkgkKpVqYGCgsbFxuuQL7JZjY2NFRUXW1tbT3ZwpKSm+vr4uLi5MJlMgEExMTKhfMvv6+oDjClICNH533bp16p+IkM2y2ezW1tba2tqxsbG4uDgmk+ns7FxVVcXlcqVSaWxsLCx5fX19cI38ByeaoaEhpD1BCt3NmzfVe3Lt2jUej/c0qiGgOiOTyX+IUEF7ezuQ8UIyOETPz507h/QnOjr6yJEjLi4uNjY269ats7CwYLFYoaGh4LcbHR1tb29PTEx8WmcSExM/++yzR48eZWZm7t6929XV1dra+urVqzExMbm5uUCbp557jhSyQN9oNBpUqyEPUCgUBFH94QADcSyB829kZMTT01NXVxficUwmUygUurm5AbD7a1fJ/XUN/M/P4qVX/yeFQplF6g7ZAqYT/hIIhBmTvn9v+zN2e/rHIc2CR20W8/X19fX1VU8pmB60VV88KBTKx8fHx8dHKBQCEfbTLtxmZmbQmo2NDYfDgZMDiFw1TE9Pb8mSJeo/CQ8PR/6uvpg1zNraWn2xsdns7du3R0ZGIne1sLAwJycnPB5Pp9MXLFiAoGoMBqOjo+Ps7KwB9xGHq6GhIWxkMTEx7u7ukJU8MjJSX1/v4eGxfft2JEvv8uXLV69evXv3bkJCgvpXQyQS/f39P/nkEySLyMjIiMPhEAgEZ2fnPXv29Pb2wv5IoVCASQsB0+vWrXN1dUVSPYAFytjY2MvLKzw8nEQiDQ4OEggE8I1t27ZNKBQ2NjZCbiyJRNq5c6dUKgVOL39///fff//q1asSiaS1tRXgONQ8RkVFeXp6trS0mJubm5mZvfXWWwQCoaurC0KckZGR4NAlkUhr1qwxMzMDGi24NUVEREDKINyaFi5c2N7ePjw8DA5XOLbfeuut6ZMZmF2WLFkyPdxjZGREIpEgN+LevXv79+9ns9lubm7IByFHF7i4ZkxLWrlyZX19/eDgIIlEguNkaGgI2Mvi4uKIRCIMFA6HW7JkydmzZ3Nzc8PDw3t7e5VK5ebNm318fGA+I6UwiIsdEglmBDHp6elSqTQhIQG+xLa2tsuXL69Zs2b6w/fu3WMwGD09Pfn5+dra2iYmJl5eXnQ6ff/+/e+//76LiwvozNjZ2a1ZswbEf6D8apYlLBKJOjs709PTiUSiTCYbGhqSSCSPHz+eHl29c+eOo6NjWFiYtrZ2V1dXd3f30qVLZwz71tfXCwSCqqqq9evXT3/Azc2tsrLy3LlzwHwxOjoqFotBFQBeeWpqqre3d0bc9rTal/Xr16empn788ccrVqyAubF58+b09PSPP/54/fr1iJcdtNJlMhmkHMDHwRB5eXnNAjGLi4tHRkagV5aWlhEREWfPni0oKADI0tvbe/ny5YGBgadhTRwOp6+vD7TDz3jEqFSqgoKCiIiI6b0KCQn58ccfW1paIiMjkQsDUt0GV0EAZ1AXrLFSILV3Fuimo6Mjk8lKSkoMDAwCAgIwGMwbb7yxYsWK5ORkfX19DYbY0dFRjV8fGRlpbW0FjAIT7IXqQ0MADuk5zDekjkQulwuFQhaLdf/+fT8/vznANGd/SZvR4fe02O6f1isWizUdYCEVs+pmYGAwSwa0ut8YcQs/fvxYLBbv2LEjJiYGSdHA4XBcLvdpFe9QLjvd7O3tZyk7ALaO6RcyDaevhYWFnp4enU4fGBiAhDZLS8stW7bo6OgMDg5isVg4+8PDw62trZGN3szMDGFnBVIlOI2srKx27NgBOsRYLBZKBeVyuZ+fn4+PD41GGx8fh32TyWRu2rSJQqFIJBLAwWZmZlu2bJHJZObm5jgc7sqVK1DeNd0fw2Aw1q1bB67EGUcMj8cvW7YsICAgOztbX1/fxcVFJpOpg/Jly5ZFRkZCSuX0301ISOByuXw+HyErghNCqVQCsRaQJgCYRqFQ1dXVRkZGFhYWjo6O6lFOf39/a2trcJ3i8fj33nsPGMynn1IKhaK+vn7ZsmWQDK5UKmUyWXx8/NatW6e/vqmp6datW1taWhABu6CgoI8++ujRo0eHDh3icDgCgWB0dHTLli0eHh44HC4lJUWlUsXHx2dkZHR1dUVHR0+HL++++25NTc3Ro0e3bdtmbm6+ffv2M2fOVFRUgDKS+mmNRqN/+eWXyspKHA5HJpMjIiIiIyOfPHmSlZU1NjbW0tKyf//+7du3Q9bm0qVLnzx5AiX0WCyWQCCMjIz8+OOPK1eufO+99/bt25eUlLR37174xO+///6nn3768ssv5XI5nU43NTW9e/eun5+ft7d3TU1NXV0dDIsGb63GIoVngIAKjUa7ubktXrz43Llzn376qfqwR0ZGQko15N61trZCr+Lj4wH65ObmYjAYPp/f0NAQGRkJHBlpaWnj4+OXL19esGCBg4PDhg0bysvLQQMRUTasqqrC4/FisRjC1updPX36NJ/Pl0qlIyMjurq6Uqk0JSUFhULdunUrNjYWsprIZDKXy/3+++/fe+89qGK+ePGin58flUpVqVS5ubmjo6M7duzAYrFr1qw5fvx4VlbW4sWLIc6VkpIC35REIpFKpUQikUgkgqiAgYEBvP6VK1fWrVsHFxI+n3/x4sW9e/citM8a9+rly5ffuXPn9OnT8LsLFixISEgA+S9kMOVyOXwpcrlcLBbD9WbdunU7d+68c+cOUhPw52zdwAQGifwQpIOFz2Aw4Jr3/xeA/9///d/c6Ttnc/bqW2dn57lz5yIjI62srJCTtby8/M6dOzt27JhOy/mijUKh6OvrQ3IulNFRqVQ6na6trY38BCAdg8Ew/H+mpaUF8VBdXV0tLS0Gg4GgPV1dXQMDA0NDQ0TbBNqk0WhEIhGJnoBTUyNejMRwUShUZmbmqlWr1EVtNboNJ+LT3ktLSwtYOh0dHc3MzIRC4fnz52NiYubNm4fD4XR0dAwMDDRC1ere1q6urszMTGtra8A30Bry+oiMHQ6HY7FYbm5udnZ2Tk5OgCORXpHJZOSgQqPREHee3meZTHbt2rWCgoJt27YB2U9JScmFCxcgc3H6azIYDDab7eDgYGFhASxloJLp6OgI5eUWFhZhYWGQKQU0jB4eHsHBwYaGhkwm09DQcPpb29nZ2dnZ2drahoWFWVtbOzo62trazps3D+rX1DtgbGxsZ2cHIgfW1tbz58+HVD80Gh0YGBgUFMRms6EIH2oGra2tbWxs4Eg2NDT09vZms9mWlpbW1tYODg5OTk7h4eFWVlaOjo6gXGFra4vH4y0sLHx8fKAbBALh+PHjIDXPYDAQcssZjUgkcjiciIgIhGKRQqHo6OjExcWpM7AbGxubm5uXlpYODw+3tLQMDQ25u7vHx8fD+KenpxMIBF9f387OTolEAkxONTU1KpUqLi6ORCJBha+hoaG9vT2NRisqKuru7gZxJB6PFxoaev/+fUtLSw0gkpqaumrVqgULFrS0tDg5Od25cweLxerr68fHx0NRC2Ri+fj4mJubW1tbQwFHVlZWYWEhDofj8/lpaWmxsbHLly8nkUjAxtTc3CwUCm/dugUA2sLCQiKRALmPlZUVhUIB/aLbt2/fvHmzvr4etDsxGMyxY8cEAgGJRDIwMJg3b970IQVmkKKiorfffhs+C6ZTXV2dOp19bW1tamqqQCDQ0tLq6enx9PTE4XBQr9fV1dXV1RUSEtLT03PmzJmpqSlg/4FfPHbsGNyE9fT0nieVUCQSDQ4OAiyTyWSwI6HR6MnJSRMTk8LCQh0dHciRMDIyMjY2JhAI6NBL87UAACAASURBVP9KUaE5m7P/PuPxeNu2bXNwcPjss8/odDoQ0z169IjP53/99dfP4q/6H7G6ujokSf/5jcvlLly48Kefflq+fPmzMBe0tbUdOXKETCZ/8MEHvxlAf04bHBx88803AwIC1q9fD2VTFy9e7OjoeBpZ4v+aSaXS+/fvczic7u5uKpVqZ2c3S9RMJBIJhUJ1PoLh4WGRSDR9JGUyWVlZGUS0DQ0N1UFDTU2Nvr4+kNrr6+tDCn9XVxfAlK6uLm1tbSSDZ3h4uKamBoVCQQleTU0Nk8mEGjENkZyamhpnZ2cMBgN/aWxsNDY2HhwcnCUVXaVSXbp0KTs728XFxdjY2NjY2NPTE8n7FggE9fX1ExMTFRUVQUFB/v7+IpGoqalJqVQymUw7OzuIxubl5bW3t6tUqvDwcCcnJ0gwLSwshHfX09NzdXWdsQMVFRWVlZXqkrq9vb2NjY1+fn5IPiifz29paUEQyPz58wH9FBYWPnz40MjIaPXq1dXV1WfOnEGj0e7u7osXL4Zo6QcffHD37l1PT88PP/xQgxrgWSw3N3fhwoVoNLqnp6e/v9/NzW3GFpqbm0F3vKmpydzcvLe3F4VCzQGmOZuzv4ZJJJLCwsIzZ87Y29uTSCSlUllfX79y5UorK6sZc2Pn7A8Z86qqqri4uO+++27p0qWIE2t2a25uBsbXF12kNjY2lpmZuWDBAsQd1dbWBkyec2hpziYmJkBHRVtbe0Z1FIVCIRAIIA41Ywvd3d0ikQiFQpmams4YfZsFfU5NTc3OsTyLgTYlSDkJhUIUCtXf3+/i4gLh+8bGxvv37xMIhIiIiKdxT8xiRUVFQUFBaDR6YmJCIpEAt7tAIPD19X3y5MnIyIiXlxdSoUwmk7Ozs/38/EZHR9FQszo3seZszv4qN+by8nJEHBqLxXp7eyM1j3P2h1tOTs79+/fv3LkD9MorVqx4lvxTpVI5OTmppaX1or8X+KCn5WPN2Zz9N11d8Hg8cK0plUqJRIJGo0FN9fdO/vHxcY0A98DAwNjYmKWl5cDAgFgsNjU15fF4NjY2V69eXbZs2ePHjy0tLUHEZg4wzdmczdmczWyNjY0CgQA2SQqFAhLCc8MyZ3P2X2yTk5OlpaWhoaG1tbUIf2ZLS8scYJqzOZuzOZuzOZuz/zlrb2/v7u4OCAgASCSVSqE8U6lU9vX1mZiYwM+zsrL8/PyALGbOk/9ira2tDSql54ZizuZszuZszubsFTEqlarO94vFYoHzT6lUjo2NoVCouro6lUrFYrEIBMLAwMDAwMD/ImBqbW1ta2v7vdLrv9cyMjJOnTr1r3/9i8/nzwGmOZuzOZuzOZuzV8f09fWtra2npqays7NVKhUOh/Pw8ADxJaiJ4/P5KBTKyckJqFIYDMb/EA/T5OTkjRs3MjIyOjs7WSwWIhH/gqy/v7+qqurq1avx8fGIasErYlNTU8PDw+Pj47m5ucbGxlDLMzk5OTIykpqaeuPGDYlEoq2tjbAVo1AokUjE4/EuX75848YNc3Pzp0mdvHRTKBTFxcWnTp0yNDQEyb8X91lAW6Kh+fonm1gsHh0dheTHuR1wzv7SNjY29tNPP+Xm5iqVSgqFMpfMPmd/gqlUKuDylslk6enpoKhDIpFgBtJotOzsbAaD0dvbOzEx8b8CmCYnJ9PS0tLS0uzt7T08PDgczotejQYGBh0dHfn5+a+99trTVCRflj18+PDkyZNNTU2GhoYgl4FCocrLy69evWpkZCSTyRobG/Py8oCNGuhrjx49yufz2Wz2kydPSktLmUwmwkz4Sll5eXlOTk5NTQ0ajZ43b96Lq+uemJi4fPlybW2tpaUlwizyJ9vIyMjZs2d//fVX4BVU/zqEQmFNTU13d7eBgcGM/I1zNmevmp0+ffrhw4dMJjMtLa26ujo0NHQuxX7OXrSh0Whkk5TJZEwmc2pqCnZOoK2SSqVAXkAikV6JnbSioqK9vT0sLOxp0oPPb+np6Tdu3AgICIiPj0c4S16okcnkl3WO/iZaOnz4MIvFcnd39/LyIpPJcLe7fv06Ho8PDAzE4/GdnZ07d+7U0dEBktxjx461trZu3LgxMDDQ3t5++fLlJiYmVlZWrxr3T0lJyblz5xISEqKjo0kk0h+Llp48eVJSUhIVFQV8x3K5nMvlFhQUBAYGInRwf6ZNTU1lZWWNjo7q6OgMDw9riJg2NjZ+8803WCwWnG1/iZ3r1q1bGAwmNDT0RdMX/fl29epVoVCoUqmWLVuGkH2/IGtsbCwpKYEc1dDQUGtr61fwYjOjUSiUzZs329jYlJSU3L17Vy6Xz0ji0NfX193dDVIwc+f9nD0/YIJpBiE52FoFAoGDg8ONGzfi4uJA1LKrqwuFQr3MCTc2NiYUCoHppKenp6+vb+3atU8TR3zOjfjixYuxsbHx8fEz6jFp3NpBTBuFQhEIBF1dXRwOByI+U1NTRCIRi8VOTk6C+iadTteQ8RocHAR9HGhqRi1uxKRSaW5uLkI8qFQqhUKhlpbW04QXntOUSmVlZeWxY8csLCxWr17N4XCQHaezs3NoaOj1118HqQrQcGhraxOJRJOTk+np6atWrfLw8CASidbW1itWrLh9+3ZQUJCvr+8rhZnu3r1bXV390UcfsdnsP7bloaGhf//731wu183NDTi1yWTyihUr7O3tgfv/z3/Zs2fP3r1795133qHT6VpaWhp3cRMTEz09PXt7e4Scuqqq6sqVK4iGxiu4c925c6erq4tIJAYFBf2X8XASCITz58/39vbOnz//RWxxKBRKLBanpKT09PTw+fy6ujrYeYqKipycnN555x24F73iFhUVpaOjo1AotLW1t27dOiOv+tDQ0OnTpxcvXvzS76K5ubnm5ubA5f2bDw8PDwNfmnq3pVJpfn7+48eP33nnnZfrSxsYGMDj8S/l4vdSrLi4GISAgNVpeHiYTqerVKqRkRE9PT08Hg8KnqBYmpmZ6efnByvoZQKmzMzM7u5uDoezYsWKvr6+xsbG8fHxP3w3GRgYyMjIwOPxYWFhExMTJSUlenp6NjY2M95iu7u7i4uLBQKBUqlsaGig0+lvv/02k8kUCAS//vprXV2dsbExjUYjk8kSiaSlpWXx4sUJCQk0Gg1xQhQXF4tEIpVKJRaLMzMzp0sxI9bQ0CAWiw8ePLh9+3Y2m93b29vS0pKUlBQWFhYfH4+0+QeaRCI5cOAAiURasWKFOlpCoVCnT5+emppis9nIQbV+/fqffvqpurrazMyMTCbb2tqCw0ylUgUHB//66698Pt/T03P2g00qlVZVVYnFYvintbW1qanpi7sXAlp9ES3L5fKOjg4qlYpMGwKB4OfnByDypSyf/Px8gUBgamrKZDKn/6+FhcXevXuNjIwQdY7W1tbz588vXbr0VQsQI7ZixYqhoSFzc/P/vnysoKCgkpKSgwcPvqD5KZFILl68mJWVtWLFCldX16ioKLizFRQU3L59e8eOHX8JwGRgYCAWi8+ePVteXp6QkDDjNDh27NjQ0JCFhcWfM0l4PF57eztcj3E4XFBQEOKuY7FYR44c2bhxI8gDz9JIV1fXzz///I9//EN9V1epVKmpqV1dXR4eHi99wqelpbW1te3cudPMzOzPwUzV1dVP0yT5E4zJZFKpVMSPUFRUlJCQoFAoSkpKFi9eXFtbC30Dh5OFhYWWlhbQBb80wNTe3p6WlhYWFhYSEqKrqzs0NFRaWgrq3BoGXqjh4eHZG3Rzc/Pw8Ji+LzQ0NJSXl5uYmFy/fr25ubmlpYXJZL799tve3t7Tj7ry8nKpVOri4kIkEmUy2fXr1728vKKjo2k0GofDSUlJaW5ujoiI8PLyksvlJSUlZ86cCQgIgGXw5MmTgwcP+vv729raYjCY0dHRioqKWRbSyMjIyMhIc3OzRCLh8/lVVVXDw8M5OTlMJjM6OvpFjHl2djaPx9u1a5eRkdHly5eHh4cXL17MYrGwWCyoUqsLGbq7uw8ODvb09Dx+/NjOzs7BwQGwERqNBmfY7M4zsOvXrxcWFrq6uiqVyvT0dA6H8/e//x1OxKGhoYyMDODdR6FQoaGhoJ05vZGsrKz29nb4OBaLFR4e/psSXffu3XNycurt7b1//z6ZTF68eHF5eXlLS4u9vb2vr+/o6Gh2dvb4+Dg8HB0dzWaz1WHcjRs3+Hw+7JJWVlYLFizAYrEkEqmhoaG3t3dgYMDT0/PmzZsDAwMqlWrlypVwEfmTDXFkzmhYLNbFxUX9J1NTUxKJBF5KHXU1NzcrFIrw8HAbG5uXG+MICAj4b73R6unpubi4vLjhTU5OzsrKiouLW7x4sbrGu5OT065du/5CA6VQKORy+aJFi5KSkhgMRmhoqPqgVVdXp6amHjp0aEYp4j/c+Hz+vn37uFwuApjef//9xYsXQ5fAu3zt2jUHB4fZAVNpaalAINDoMGi9bdu2beHChX9azJTH42VlZREIhI0bN6oPrKOj4927d7lcromJyQvtzMjISFJSklKpJJPJJSUlKBTqb3/72+z5xAqF4vjx40qlctmyZcbGxn/I987hcNLS0hISElAoFAaDsbe3hz3T1tYWIAcKhSosLHRyciISiY6OjigUqqenB41Gv7T9kcfjdXZ2mpubQ/iQRqMFBgYioE/dCASCqampjo7O7A0+repteHhYKBQSCARDQ0MTExMOh5OamvrVV1/98MMPkA+v/rCNjY22trapqalUKsXj8efPn6+qqgoODmYwGHFxcSkpKWKxODEx0d3dHYVCNTY2nj59OiUlZdu2bSgUav/+/QqFwsvLCwS3ZTJZc3NzaWnp0zpsY2Pz6NEjFAolEAju3r3r4OBgZ2c3I2RUP95qamomJydnH4otW7bMKMWak5PT19eXk5MDILKnp6e6uvr999+3sbGZpTUMBtPb2ysUCq2srH7vWnr06FFgYKCXl5dKpWpoaLh58+b69evNzMwwGMyhQ4cGBwf9/f21tbVLS0sPHz78ySefTFc1unPnDmjF6+nppaamPnjwwNHREUZY/bHR0dGkpKSKigqBQHD48OGenp7PPvusra3t119/HRsbKy0t7e/v7+rqioz8/9j77rCorq396UxjKkNnhjLA0Bl6byJVRWzYo7HHGK+5KX73XpObxJgYo9cYNSaisTeqoghIRwQFRHovQ+8wM0xnZn5/7Oc7zzy0GKMxv++y/uAZzpzZZ5999ln73Wu9a60wR0fHEydOqNVqDw+PkZGRa9euPXny5MSJE/r6+jAYrL6+/t69eyYmJqD00vXr1xsbGz08PFJSUoDX8urVqwqFYvfu3TAY7M6dO93d3YB7B+pdZ2ZmVldXw+FwOBw+Pj6+adMmExMTEonU0tJy6dIlmUy2devWrq6uxsZGPp8/Pj6+bt06Nze3Wa10CoWitLS0rKwM5L8YGxsjkUjvvPOOkZHR1NRURkZGfX29RCI5cuQICoX617/+pcn/E4vFZ8+e5fF4RCLxk08+oVKpLS0tiYmJIpHowoULV65cWb16tamp6dWrV42NjQ0NDauqqr777rsjR45M00dSqXRsbEwmk+Xn54eFhUml0vPnzwuFwvXr17u7u4vF4p9//rmnpycoKCgsLAxap0Ui0cTERHx8PACUe/bsAQXVeTzeTz/9JBQK9+/fb2FhAVzb9+/fb2tr27p1q0KhkEgkOTk5MTExdDp9eHhYqVSmpqaGhYXh8fgrV6709/eHhoYuXrxYrVYDuv3U1FRUVFRISAiwfQJ8XFhY+Nlnn1EoFBgM1t/f//jx47Kysn/9618wGEwoFLa2tqalpW3YsOHWrVsikYhAIOzdu9fExKStre38+fMikWjLli1mZmazxlf29fVBmwRtbW0SiTQwMACOaGlpQb5+Pp8vFArVajWZTJ7Hty6Xy4eHh8lkMrT2gyNUKhVaP6RS6ejoKFitSSSStrb2rK0lJCRcvXp1586dERERmmgJ2HTff//9lynn8tYF7OCxWOzy5ctVKlVkZGRFRQUoyAqNWE5OTmhoqKOj459gklGpVF9++SUCgVi3bh243MmTJ48cOYLFYkNDQ0Gvli9f/v777wcHBwcEBMylG3t6en755ZfVq1dP25+fOXOGz+d7eHj8Oeale/fuvXjxYmxsLDc3F4FAbNq0SRMweXh4BAQEXLhwwcPDQ1dX982B0ZaWlpKSktWrV5ubmycnJ9+6dWtkZOSzzz6b9YpSqTQ5Obmpqamjo+MlS1+/vEAZmDQBk7W1NQwGc3BwgMFgoIhyfX29XC7ncrl6enpjY2NvBzDJ5fLq6mo3NzdoZ49CoahU6qwnE4lEb2/v30xlhEQi59nAxcTEREZGUigUsVgsl8vPnTs3MjKiUqmmTVYOh9PQ0FBUVDQyMjI0NDQ2NiYUCoFOBOrPysqKzWYDWBMXF5efnz85OQn27kVFRWvXrgXVAWH/y3+aB2Ho6OgAg0pVVdXGjRtdXFwUCoW+vr6RkdFcfi5jY2OAuOcfirn048jIiFKpNDAwcHNz8/DwKC0tTUxM1NfXP3DgwDytSaVSiUQyvz1jLlm5ciWbzQY42NvbOzExEXBRYTDY06dPo6KigLlIpVINDg7O6iQVCASLFy8ODw8nkUg4HO6jjz4qKCjQ19efZmTCYDD29va6urr9/f0ODg6BgYG6urpgGWtpaYHD4WvWrJmYmEAikUgkUktLKyIiwtHRcXJysqqqKi0tDVibFApFdnb24ODgypUrgd9KrVanp6crlUorKytTU1M6nR4YGEin042MjCwtLcvLyysrKyEny4MHD+7cuePt7c1ms1Eo1MOHDz/77LOlS5euWbNGKpU+fvy4pqamr68vPDzc1ta2q6vr/v373d3dP//8s2byNEgePXpUXl7u7OwMhiU7O/vy5cskEundd9+dnJysqKgQCARUKhWLxfb29k6bEigUSkdH5/r16wKBYO/evVQqtbS0FKzuxsbGNTU1k5OTBQUFzc3Ny5Yts7CwsLW1/dvf/jYzM9no6OjDhw8fP37c0dEhk8mkUmlra2t9fX1LS8uuXbukUmlDQ0NjY+OTJ09kMllsbCwOhxOJRFevXu3r62tqahKLxXV1dTKZ7LvvvqPRaHK5vLe3t6ioCIlEfvXVV9ra2ikpKcnJyWFhYWNjY0VFRYWFhc3NzVZWVi4uLg8fPhSLxfHx8enp6XZ2dr29vW1tbaWlpXw+H4fDVVZWdnd3d3d3l5eX29vbA3SblZX14MGDzMzMjz76iEKhqFSqhw8fgoerUCja2toqKytrampu3LhBoVBAJraqqiqRSBQREdHR0dHW1iaXy7/88suQkJCdO3fO3LokJiYWFBQoFIqAgAAvLy83N7eHDx/W1tbyeLy4uLiYmBgkEllcXFxYWKhSqaqrq93d3bdv3z4rxbuurq62tjYxMXH37t0BAQFoNLq6urqmpiY1NfVvf/ubh4cHGo1WqVSJiYlVVVVGRkYTExNYLHbr1q2zBqyUlpb29vYGBwfPWus0NDT0/4tYs2fPnqnVan9/fyaTWVtbSyaTp0XJ8Xi8W7duHTx4cNbbaW1tBb4zS0vL1+KwU6vVTU1NJ06cgPbVDQ0N58+fr6urCwkJgTa9fn5+Dx484HK5cxGARkdHBwcHwZ5B84TMzExPT09ovXjTMjExYWpq6u7uzuPxHj9+PE2Zo1Co6OjotLS0oqKi2NjYN2dkOnfunKOj46JFi7BY7Lp167KystLT0//1r3/NfF5qtfrmzZspKSmxsbFhYWGvnfzg6uo67Uh5ebmrqyscDu/p6dHT07O2tkYikTQaTalUlpeXu7m5lZaWvh3AJBKJsrKyvL29XyYZEgKB+OMj5eTkRKPRMBgMFovlcDhoNHrm8j80NPTw4cPMzExvb28zMzNHR0dNpVlRUdHb26tpZbG2tqbRaGA7qFarp6amkEjk760FyOVyQ0JCPDw8iERiYmKijo6Ou7v7XIjHysoK2AxfWczNzVetWuXs7IxCobhcbmFhYVNT0/wmK2tr63v37o2Ojr6MD25mh5OSkiYmJgAq0hwZoVCYk5MjFAq3bNni5eWFRqNJJNLMofP29sbj8WBvPTo6OjAw0NnZCaEuTYzo7++fnJzc3t7u7+8PSN8UCsXAwMDAwAAYcuRyOZ/Px+PxW7ZsAclbBQKBUCicnJzMzs7W19dXq9V3794NCgrS0dEBvt2AgICpqSlA4RoaGmKz2cHBwRAHiMPhaELbCxcukMnk6OhoMzMzBALBZDLDwsL4fL6bm5uJiYmLi0t9fb2ZmRnonlAoLC8vz83NnXXwc3Nzjx8/zmaz33vvPeDvY7PZCQkJiYmJ/v7+5ubmsbGxT548UavV69atg8PhwKCiCR9jYmIeP36cl5cH5rmrq2tkZGRtbW1gYGBkZKSJicnu3btHR0clEgkGg2Gz2evWrZtJmyORSK6urleuXKmrq+vq6oqIiPDx8QHmqBs3bmzcuHH37t09PT3ff//9pUuXQkNDcTicUqkECR0iIiJQKFRpaemFCxeKiorCw8MNDAw+/PDDwcHBjIyMiIiIoKCge/fuBQUFxcTEYDAYV1fXixcvamlp6enpaWlpgf3DhQsX2tvbly9fvmLFCuAfuXDhwp49ezZs2IBEIu/du/fDDz8A2EEgEJydnYHZCdwyAoFwcXGpqKjo6emBw+HGxsbApqVUKuVy+f79+7W0tFJSUq5du4ZGo5cuXerp6QmHwzdu3Ein02dOMOC2SEtLKygo2LVrF5PJBDE15eXlWCwWQOSkpKT09HRzc3NHR8eampoLFy4olcoDBw7MxF5CobCrq+vhw4fR0dHAgMTn8zs6OtLT09esWQP6n5aWdvv27cjISGdn5+Hh4Rs3bkil0o8//nhaa83NzdXV1REREXN5qf5/oc/39vZmZ2d3dHRs2rQpOTk5KirKyclJc3WYmJjA4/FAA2veqUKhiI+PB05zHo83MjICbNh/sD9wOHzDhg0ODg7QAG7ZsuXixYuaahCLxTo6On722We7du2aVX3BYLDU1FRnZ2cOh6PZpWfPnnV0dHz99dezbvJv3rw5NDQEg8HwePzWrVtfiyc3ODiYSqUSCIScnBzgC5smJiYmGzduTElJWbZs2RsCTI8ePaqoqDh48CAej4fD4ZaWlgYGBiUlJUVFRUFBQdNGLzk5+caNG3FxcStXrtTW1n7tsBJ6rElJSStWrIDD4aC8LphpMBgMjUZDXzU0NABH3tsBTCqVSiQSjY6OymQyQE2XSCQ6OjqzvttDQ0Opqamjo6Pzt+nh4eHl5TW/S2t+AcxuDofj4+MDkutoMqIoFAoGg+no6NBc4RQKRWdnJ7Q1Hx8fB5aYl3m6CoXi+vXrLBYrMDAQdDsrKwsGg+nq6s61IwQWr2k0lJkyj42KRCLp6uqCN9DY2BhSsnQ6XSaTTU5OQla3kZERV1dXLpeLxWIFAsH4+PhvXnemM/Snn37q7e0NCAhgMBhdXV2a327cuPHSpUu//vprVVUVkUiMiooKDQ2dqfTxePzly5cnJydBtoxXeKx4PN7IyAiNRqPRaDDOo6Oj169fRyKR2traPj4+9fX1AJErlUoej6e5WBIIhKCgIDwePzU1xWaze3t75yp0c/ny5a6urk8++cTAwAAMoKWl5fbt28+fP9/V1WVtba2rq4vH41euXGlmZoZEIqlUKshxNWufc3Jyenp63n//fciQZm5uvnv37h9//LG9vd3W1pbL5dJotPHxcYAIZ7YwrX1bW9vq6moUCoXFYgFcDg8PP3369BdffGFoaOjq6urg4DATpmtra3O5XAqFYmRkFBoa6uXlhcFgrKysrly5IhaLuVwuk8l0dHTMzs7Oz88HVi4cDrdkyRISicTn86empnx9fU+fPl1SUhIUFEQmk7lc7ieffPLxxx9/++23ycnJS5YsWbx4MXBmubi4bN68GQQTsNlsLpebl5cHh8Pfe++9FStW0Ol0iUSSkZHx5MkTLpcLaILa2trFxcWZmZnvvPMOgUBwcnJiMpnQLcPhcC6XCyxqKpXKyMjIyMhoaGgoODg4LCwMYHQcDhcfHw9wIbAQzKNA/Pz8oqKiKisrQVNIJJJAIPT19W3evNne3h6FQjGZzNjYWAcHBwMDAxaLdejQoeTkZADmZm4kxGKx5kJoY2PD5/OhFz8rK+vYsWM7duyIiooC72ZBQUFCQsK+fftmAqba2tq///3vbzcXw/nz53t7eyUSiUwmYzAYQqEQRDsWFhYKhUJdXV0+n//uu+/Ok+PAw8MDj8eDTaO3tzeUH26aVQDsRjSVzLlz51paWnbs2GFoaJibmzs8PPx7NdVcgCk2NlbzGWVlZdnY2AQHB2vegqurq5GR0awIG6wppaWln376KYPB0NRsT58+7e7unhlhV11dnZCQ4OjoyGazc3JySktLp/nOXllMTEx+85ywsLD4+Pg3V5ciMzNTLpeD2DRwZMeOHbm5uQUFBYGBgZrjMzExcfXqVZFItGLFCiKRODg4qKen94ZMcUZGRuADRPqE8rBofiUUChkMxtsBTEQicdmyZcnJyQkJCWw2u6Kigk6nr127dtYVEYfD2dnZAQ/3PGJsbDwrztDV1TUyMmpubgbqHnK9zQStcrm8v79/7dq1lpaW4+PjZWVlECUZBoOZmpqSyWSBQKDp/lAqlXw+X6lU4nA4S0vLrKwsDoezcuVKEok0OTnZ2to6j/FGpVKVlJQABgZ4bQQCgaWl5TyEg8bGRuDjmH8o1q1b93szWm3YsOGrr74qLy8HKAoGg12/fp1KpZqams4KVZlMpo6OzvwbkQcPHqSkpBw6dAhk1klOTtb8FrixMzIy2tvbGxsbX7x4YW9vD9I+aQLES5cuPXv2LDY2lkqlmpiY/PFgn6qqqq+//lpbWzs2NtbY2Fgmk2lpaVVVVS1dunSmYoI8xQgEgkgk1gIhQgAAIABJREFUYjCYuV7ax48fDw8PDwwMQNMDgUD4+/ufO3cO7ArAkZfMLw9CHKYxYIKCgn744QepVPpaNNratWvlcnlhYWFbW1txcTGTydy3b19oaOis666BgYGtrS14v8DOAWTCRSAQeDyeQCBA/QTnlJaWdnR0AGelQCDg8/nQGhYUFLR9+/ZDhw6VlZUdOnRIcyHp6OggEAiQ18nIyIhIJOrp6QH7IoFAIBAIaDSaQqGAE6ysrFgsVn19/fy2TxaLBZ6sQqGorq7W0tKCQC1Ivgru6DfVsZaW1vLly+/evXvp0iXgUhwYGDAyMnJ3dwd37ebmNjw8XFtb29TUpFKptLS0xsbGZl28aTSanp6e5sPV0dHRPFJTU1NdXY1AIMrKysCRwcFBEL07rSmxWCwSid50bqeXmbHGxsb9/f1isdjBwaGuro7BYDx9+hSHw42NjTk6OlZWVs7PJbCwsDA1NaXRaDo6OpaWlrNu+UCYquaTysjIiI+P/+WXX1xdXdFotK2t7cDAwGsZimk7tObm5uTk5MjISHt7e832zczMAHyftZFLly5ZWFi4u7tPO0EgEExrB8zPe/fujY+PBwQEAHWnVCr/zMdKp9PlcnldXZ2zs/Nc1y0vLwfcxHnaQaPRixYtmtnC2NjYtDkQEhKCQCAmJiamNQi2RsuWLSspKQG+9ejoaB8fn1mdzq/LNwfhpPb2dkBjAoqlpqbG3NwcbPjfDmDS0tKKjIzMy8u7devWunXrCAQCh8OZCyhoa2v7+vq+8rVsbGycnZ2TkpKoVOry5cuVSmVJSYmPjw+kNGd6Q8bHxwE7RKlUPn/+vKurSyQS5ebmtrS0TE1NxcfHA2Yo0MJtbW11dXU+Pj67d+8+evToL7/80tHRQSaTQYJs4IidmJjw9/efGdulp6fn7OwMQEBZWdnw8PDixYvv3LkTHh4OtT8NpgCvx2/aVGY9Hh4efu3aterqagaDMW20nZyc+Hx+b28vtFXq6elZunQpgJWenp7FxcVRUVEAS2VmZtra2lpaWoJ1Ii0tTS6XL168eJpPp7m5GWh5OBwukUiKi4uhwDQYDFZSUuLr68tms8fGxpqbm48dOzZzl8bj8a5fv75+/fqIiAgymQxISH9w7iUlJTU3N//jH/8AXoy0tDSRSGRgYAB5aUtKSuLi4kgkkua15HJ5d3e3vr7+XAEdixYtSktL6+jogO4CDof/kd6OjIzk5+e7u7tDK8frrcFCoVDWr18fEBAwMjKSl5cHnFNeXl6zAiYEAvGSvubx8fFTp05hMBgomHHaTEOhUP39/XK5XCaTZWRkbNq0CZquJiYmBQUFEM15YGBAIBDweLy5FlrgAf/NLrW0tICHApJ9dHd3a87D3yVmZmYMBiM9PT08PDw4OLiysnLp0qUQ0FGpVD/99JNEInFwcEChUAqF4pWhrUqlUqvVk5OT0A1yuVwzM7O5lOS9e/dsbW3/iH39DwpIyCkSiUQikbm5ubu7Ox6Pb29v19XVFYlEFhYWgOUzz/Nqamp69OgReNaZmZlgWx8UFDQ/Aau1tdXPzw/aDFtbW5uamr4Jj1J2dnZ/f39cXNy0xHvzTMIXL17cuXPn+PHjs2Ywnrkc3Lx588mTJ3//+9/BXtTR0XHv3r1/cuDq2NhYWlraPLR6oVA4Pj4+/8R+eS/wXHfX0tIyOjqqpaUFsJREIvn888+jo6M///zz1w6YZk4wkIQJBoMBe4dIJFIqlQA9v7UoOTMzs08//bSnp8fJyUlbW5tOp78hkzKFQtm2bduzZ8+Kiora2tpIJJKHh4ezs/PMfINMJvPw4cOZmZn19fUbN240NzdftGiRq6urvr7+4OCgQCAA8SZkMhmyTu3bt290dNTc3ByHwwHfTU1NTVZWlpubm7u7u4uLi1QqdXJyMjQ0nNV68cknn9ja2gIl2NLSolKpAGd5LpetsbEx4H2/mkRERNy9e/fnn38GDqPGxkYcDrdmzRoqlapSqTZu3FhaWurs7Gxqapqbm0sgEHx9fUFFudDQ0B9//LGurk4ikTx48KCtrW3Tpk2gQN74+HhSUhKFQvHz85sGmGJiYioqKn755ZeamhojIyMKhUKlUs+fP6+jo2NlZZWWlmZsbGxjY6Ovr9/Q0IDH42equcnJyaGhITQa3dPTMzw8nJubC4LLJBLJy2815HL52NgY8KGAPU1SUlJbW1tra6tEIsnOzh4fHwdIUVtbe/369b/++uvz58/BXnZychKHwzEYDAKBAJjIdXV1KBRKT09PqVRq2g/CwsJIJJJAIBCJRFQqFYFAqFSqoaGhRYsWAc7c7zX4ZWZmNjU1TUxMgHx3wOvB5XIdHBxeC4f39OnTUVFRDg4OSqXSzs6uublZLpf/cV/GxMTE3bt3t2zZwuVySSTS8PDwtJk/MDAwPDz87bffpqen379/PzQ0FHKy9PT0YLFYKEJNV1eXRCKZm5u/8prR1NSUlZUFmaBQKBQg5P0RKLN79+4NGzY8e/bMwsKit7d39erV0OM4efJkeXn5/v37QZz548eP6+vrX75lKOYOEnNzc81IXiglsaa4ubn5+vrev39/48aNcyVRnJiYgOYqMJPgcDiVSpWamhodHW1qago4JUqlcmRk5NUKIRAIhNHRUcDj4fF4ZDJ5cnKSRCJJJBJDQ0Mej6dSqeYK6wFCJpM5HI7mDJxrTwuJRCIZHx9ftmwZtEJPI/NBEh8fDzKtz9MacHfO1CoqlSo3N3dsbOzw4cPTqEjziEwmy8vLCwwM5HK5s/7E1tZ22vGkpKSpqSlN685MxurY2NiFCxfmt9UZGRkBkt8rTG+ZTNbV1TXPQDk4OMwfVQ32V68F1kxNTfn7+yMQCHt7+//5n/+5dOnSjh07jIyMXi9munHjBmCCQh9MTEwA2Rw46aytrcfHx1ks1v37998aYMJisT4+PiqV6k+oXcrlcq2tre3t7cViMR6Pd3R0nBWR0On0FStWcDgcsVhsZ2eHx+MPHDjAZDKJRCIej6fT6Xp6euDNhCZEaGioWq0G/2IwGH9/fxcXF0dHR2NjY8CbodFoxsbGs8YDIxCIoKAgqClPT09dXV0ymWxjYwP012sfB0NDw4MHDxYWFtbU1HR2dtLp9Pfeew/KYbpt27bLly+/ePGiubm5ubk5Li4O7NWQSGR4eHhnZ2dtbW1ra2tzc/O6det8fHwAwM3Ly3v+/PkXX3wxkzLM5XI/+uijX3/9VV9fn8vlmpqaotHolpaWlpYWFovV2Nh49uzZ4OBgsVickZERExMzM5sRjUYzMzO7du1aaWkp4Ao4OTnl5+evW7eOwWBo4gaxWFxSUgJSk+fk5ISEhFAolIqKChKJJJfL8/LyQO0dbW1tf39/e3v7O3fuPHnyBHBoVCpVZWVlU1OTu7v7smXLOjs7b968WVxcjMfje3t716xZAxaYwMDAe/fuHTlyZMmSJbt37y4vLwcZqsrLy4H6c3NzKysru379+p49e8hkcnl5eUpKSnBwMJPJHBsb6+zsFIvF1dXVhoaG0N5AJpPV1dXp6+tPC2vw8vIKCgoqKiq6evXqe++9R6PRXrx4UVpaCkybAoGgvLy8r68PlE9evHixrq6upn6UyWRFRUWtra2Azw6x4GEwWFFRUX9/v6Oj482bNxsbG/ft29fd3S2RSJhM5kwb4avpOGAWGh0dffr0KahYCX3b0dHx448/rlq1ytfX193dffPmzefOndu3bx9g6dbU1ABSNtSURCKpqamJiIj4XbupR48egbnU39/P5/Mh7Q84alCgxlw/7+np6evr09bWnnXJCQoKcnd3r6+vP3r06KZNmzQrB+Tm5mIwGHd3dxqNNjAwMJc/bi6Jj4+XSCQQVKLT6RkZGb6+vvNnHTM1NY2Jifn6668TExM//PDDaYjq+fPnNjY23d3dZ86cEQgEnp6era2tn376qbm5uZWV1dOnT/Pz87/88ktnZ+fW1lYCgfDDDz94e3sHBQVRqdSGhobOzk5gBS8uLiaRSMByNms3fv31V4VCYWxs3NHRgUKhTE1NGxsbDQ0N29ra1q1bd/HiRRQKtXv3bltb27kWcgMDAyhc9MWLF1ZWVpqu3rnsENnZ2VFRUb+pLW1tbX/TrDjXPqS4uPj06dNr165dvnz5y2P3gYGBa9euzXwikJSWlk6bHiMjIzQabVpiiJnOGS6XO/+8eqMJu197zjkSiWRraztrh9955x0QAGtoaOjg4JCfn19ZWWloaPh67w5CpdAHFAplbm4OvFuVlZUuLi6FhYUsFovFYr3NPHXAzv/nXIhIJPr7+89/GhwOR6FQmun+QBEZgKVmZQVNe/mRSCSJRAoMDJzZwqyX0/y5hYXFNAbPaxc0Gh0QEGBpaTk0NATyC2hWZjUyMnrnnXdA6gEfHx+gsCBfyY4dOwDv29vb28bGBmiB7u7uhIQEZ2dnT0/PmXoBgUD4+fmBKis6OjooFGrr1q1gG4rBYGJjYwFFVKVShYWFgaoI094EFov1wQcfVFVVkclkT09PGxsbOp3++PFjGo02MwucWCz29/cHjGaFQqFSqcRicUREBJPJNDU1FYvFQMsgkci9e/fm5uZKJBJfX18HBwcrK6v09HQAWaysrD7++OPs7GypVIpAIMhkMvA8wuFwR0fHDz74oLm5GTCLEQhERETE8uXLZTIZYPrv3bv30aNHRUVFUqkUj8fTaDQPD4/AwEAUCvXgwQMOh7Nr166BgYHKykpApff39we5Zb28vKYBJiQSCWqYPH36VCaTaWtr02i0zZs3R0dH4/H4iYkJsVgcHR09NTUFh8NnbjfVarVIJPLy8uJwOEgkEhhUOBzOvn37QGaNqamp2NjYqqqqU6dO9ff3R0VFLVmyxNPTc1o3uru7796929raqlQqT58+TaPRgoODCwsLeTweFov98ccft23bBniRAoHgzJkzJBIpKirK398/OzubTqdzOBwQjfjixYsffvhhzZo1586dE4lEXC4Xh8O5ubkFBweDTBNbt24tKChoa2sbGho6efLkwYMH8/PzS0pKWltbU1NTEQhEXFxcdnZ2RUXF8PDw6dOntbW1t27dCnQ3OBIXF8fhcAAp+OTJk2AbduDAAS8vr7a2tjNnzmhraysUilu3bvH5/Pj4eJD17enTpyKRKC8vD4VCbdu2DUz4qqqq48ePf/3117PyTJFIZFxc3BdffOHj48PlcjW9DyqVCiBCHA6Hw+EmJyd/044Fqh2AdxAYJsFxPz8/MzOzBw8eUCiUTZs2sViskpKSFy9evPvuu9Mc7ggEIjo6+scff0xOTlapVLt37waFQkdGRq5fv56fn3/mzBk9PT0ej9fX17dr1y5/f//Q0FAGg+Hm5mZlZfXdd98BD0teXh5INpOZmVlbW/vxxx/LZLJz587Z2tra2tpev359w4YN89wIk8kE3DK1Wq2vr49Go+VyuZOTE4VCIZPJIKRgfigALQfV1dXHjh07fvz4zPPLy8vb29vBrAZmLU17mEwmy8zMjIyMnAl9XjknanFx8dGjRwMDA/39/V+G6AaJSCQCERJzmVueP3/+CgZdAoEQGhr6FlfthISEjo6O+Sc2Dofbu3fvTGQcGRlZWFiYlZUVFRUFnlpqaiqZTA4PD591iDw8PMBxMDdAnqTXjgXd3NymfcBgMM7OzkCRAq+cra0tDAbr6upaKF74XydzxVUBzATFBUwTgK+nHRwfH+dwOOHh4XNxzNFoNEiTOtOluHbtWojuAxIHzHzBiERiRESEn58fIF8jkUh/f39HR0dAEZu28fL09IToe2QyGY1Ge3p6EolEAKHEYjGE/7y8vKytrZVKJQgYZLPZ69evx2KxKBQKbKMNDQ0BBkIgEADqAXPX8uXLxWIxFovF4XCgWRQKJRQKMRgMGo12d3dns9ne3t4ggQKTyWQwGKBEkYODA8CmIHoIdN7X19fGxqavr2/WPSiXy2WxWCBOHkTFMxgMQG4gkUje3t4eHh7gTM2FFhp2Ly8vd3d3aA8HdM2uXbuAjiaTyZs3b+bxeICl7uzsrKenN9PuQiAQ7OzsDh06pFarATOaRqPZ2dl9+eWXcDgcZCaDw+FxcXGurq5gvTQ0NPzkk08aGhr09PSsrKx0dHRAQldtbW0qlRoWFmZkZATsWAgEYv/+/f7+/iQSiU6n29vbf/7553K5nEgk0ul0Ozs7fX39sLAwLBZLJpMpFIqdnd3f/vY3uVwOfHaAF/Luu+8uXryYTCaDfDbOzs5Hjx4dHBwEjyA4ONje3t7Pzw8MkVqtZjKZSqUSZNICZBSQNppGo4Gn/O9//xuU/ZonvMDW1pZKpUZHR0+ze+3bt+/bb7/Nzc3duHGjra3t0NDQyMjImTNnoqOjq6qqysvLmUzmjRs3uru7w8PDDQ0Nt2/fXlJSMjg46OrqGhwc7OzsXFtbm5OTIxKJ1q5d+49//OOzzz7LyckRCASgsKOPj8+sO0wTE5NvvvmmvLy8sLBQIpGAtGcikUgqla5YsUJbW5tIJJLJZD6fDxAM8Ck7OzsDpghY/Dw9PZVKZVBQUGdnZ0JCwgcffGBhYbFmzZpLly7t2rUrICBgZppfTYmKisLhcHK5XKFQEAgEhULh6upKpVJtbGzQaPT69etB2P/LrHb19fWPHj2CjG2aTgkejwdiTiF94ubmdurUKRqNVlZWNjAwEB4e/ro24Wq1Oicn58iRI6amph4eHiAFCYQOoXsBMQ0zAcSZM2cCAgLm4oPT6fRZJ5hIJBofH9fR0Wlvb3/x4kVQUNC08Lo3Lbq6ups2bZrHnWdubk4ikX6T9D1rnxcvXvzpp5/m5eVFRESAYUlPT4fD4cDLJpFIurq6jIyMCAQCnU7H4XDd3d2mpqZQUwgEwtzc/M2NBnDJDQ8PA7+EUqkkkUggCxqLxerv7zcxMVkATAvy6mJiYvLOO+8YGhq+AqvmJXMEEIlETZcEFoud1TuDQqGgGAdIgIUf4CRNZxMGg9HMFYlAIKb9di78RyaToYzzECEDgjug2bCwMKBNwIsNcnSBmkTgs6YtWltbm8lkzqoC0Gi0np4e8Plqtjaz/7MaPmeeAMwemmCIwWBAjc/aByqVqmkuBWdqQmrwK3d3d2hzBofDaTQaSIUPml2+fDn0FeQ9AX85HA5Y/IDVXbNZkHhd88i0OwIt+Pr6ao4PkUiEyqhBzU4rETMN+kxrcOnSpZr/zipmZmbffPONvb39tGkfGRlJJBLlcrm7uzuFQmEwGIGBgWq1Wk9Pz9bWlsVixcbGgi6B0Lz3338/LCxsamrKxMQEJBo4evTo1NQUSHgbEhKCRCLlcjkYRldXVxcXl7notEuWLHF1dQ0ICAB5sMB6b2RkZG1tPY8XCYlEQreAxWKfPn2qq6uLxWKBLZlKpS5ZsiQpKen27dsHDhyYPxAPvA7Quwl9AOjt5T2qJSUlFApl1msxmcyAgABAh4e2Sa6urjwer6ioiMfjcbncecK7fq+oVKrDhw+D2qBHjhzR/OrkyZOQqaOysrK0tHQa+ayioqKsrOznn3+ei426ePHiixcvTvvKx8fn+vXrZ8+edXBwGB0dBUW1X6/G7u/vb2trmwfuaGtre3l5zTP5wav9mzJrCxQKxcfHp6amBiChjo6Ouro66HI3b95MSEj44osv3N3dw8PDz58/f/bs2W+//RaJRA4ODra0tPj4+IAzZTLZw4cP1Wp1SEjIXOmvZpXm5mYymayZyry+vh74QOBwOHDJtbS0WFlZCQQCwJSVy+V9fX3GxsYNDQ1BQUELgGlBXl2oVOr8RM7/QpkJPjT/nfnV/G/7b57werv6MifM+pN5bllzAZvn9udpYX4E85tD+rsG8GWWWyqVumjRolkxLpQDGgaDWVtbQ7aQmdZZgACYTKYmHJ/WrGZrv9nteczDag0BJkbwGbAC1Gp1R0fHsWPHIiIirKysCgoKIMSgUChALa3U1FQQyPxGrR0qlerWrVsfffSRnZ3dzAdBJpPZbHZKSkpAQACUNTsgIABQxf39/dls9ly2jVd7O4KDg729vWd+Bdmq1Wp1f3+/vb29JklArVanpKSsWLFi1rsAYmFhQaPR7ty5s2HDBgjRbt26FYvFgm2Mp6cnIL++xgG/cuVKeXl5SUmJRCI5duwYCoV69913NdHDgwcP+Hz+/GrhD+LRDz744PTp09999x2TyWxtbbWystq5cyeU+S8rK2vfvn1qtdrCwmLv3r1Hjx4FluOBgQEQIwXOlEgkX331VUhISFBQ0O+6ulKpnOYGVSqVEHwEuz5TU1OQvgRQHXR0dECKEFCPawEwLciCLMiC/F+W58+fg3xjJSUlQqGQxWIB35aenl5wcHB2djaoTh0QENDZ2dnb24tAIPr6+h4+fMjj8bZs2YLBYM6fP3/y5Mlt27a9WgzdS8qlS5e8vLwGBwcHBgZmtYJERkZmZmZ2dHTY2dkBt5G+vv40Y+Rr3E7s3r171m5A8GhiYuLOnTtLliyh0WjQt4WFhQkJCbdu3ZqfIf73v/89Pj5+7dq10GkcDuf9998HTIA34YmztramUqnu7u4gxdS0oMuJiYnExMSdO3e+0UQGLi4u+/fv7+3txWKxNjY2ZmZmEM03NjbWwMDA0dER3DjwJoNoaJlMpqOjAzEu2tvb29vbIdLhywtI0K95xNTUFCJuKpXK3t5eQDPH4/F9fX0ymQzAR6lUWltba2pqugCYFmRBFmRB/i8Lg8HYt2+fUqlksVgikeibb75RqVR0Op1Go+3cuZPH41lZWb3zzjvDw8MIBGLz5s26urpdXV1SqdTW1jYkJERLS0ulUmVkZAwODr72IClIeDzenTt3oqOjBwcH+Xz+w4cPPT09AVMQOsfW1nbRokWXL18+fPjwm64oPNMLPFOys7NFIlFISIgmH3xqasrFxeU3g7kWLVr04MGD5uZmyBCFQCB+84p/RDw9Pef5tqysbGJiIjIy8o1GYqFQKFdX15l13GAwmKWlpWbCAhqNFhcXN2sj8fHx27dvj46O/r0GxZkAS1tbW6lUPn782M/PT6lU1tfXQynR29vbQe7ZqakpU1NTEGi8AJgWZEEWZEH+L8s035+mmJubgwjqzZs3j4yMEAgEJpMJSuM5OTnR6XTAmgoMDDQ0NNTX139zLrna2loWi3X79m2xWDw0NHTnzh0QqTRN4uLibty4UVJSAhxzb3FUp6amHjx4sGXLlmm1frlc7j//+c/f5CrA4fB169Y9fvwYh8MBd89bvBcQOurm5jZXIqu/jmRlZRUWFt67d28u9ucrCLAjIpFIDocD+1/2t5mZGUhsoVarQQlaGAyG/Pe//72gUBZkQRZkQf6bhUgk6urqgnBCGo1GoVBIJBK0g0cikaAY4psDTCgUytnZ2dra2sLCoqWlZfv27YGBgTOvSKFQmEwmCLp8uyAjNzfXwMAgPDx8WidxOBzIi/abBEFdXd3KysrHjx/7+/u/oXq3LykvXrxobW0FlKa3O6ovA5i8vLxmLb3yagKKl4MCZZAH0NDQUCgUgiqiarVaoVDk5eVhsdgFwLQgC7IgC7Igb1moVKqenp6RkdHjx4+Lioo8PT3xeLy+vv7MdZFCoUDp4N+igNQJfyRLJBKJBI7RaRWF/3x59uxZRESEtbX1XxwtwWAwMpns4+MzrUDN75W6ujq1Wg0Su8PhcJCjRC6XP3nyhMlkgjQHNTU1FAoFFLyn0+lqtbqnp+ev65Lr6+tLSkoaGRl59913TUxM/vwHCTIxgMjbPzMTxoIsyIIsyH+nwOFwAwODHTt2gLrIf2XFC4VA/hGBXKJvV1xcXJhM5l8fLcFmKxfzatMM+jw1NZWUlLRmzRo4HD6trDIKhQJRcggEws7ODofD/XUB08OHDxMTE5ubmyMjIyEe1p8mw8PDFy9e7OzsXLp0aWBg4FusajlNpFJpW1ubTCaztLScP3PugizIgizI/1+Cx+OXLVsGOCXAS7IwJn+CQKWT/nvuFyLAweFwQDZHIpEODg4wGKy5udnS0tLQ0PD27dsASN26dWvt2rUNDQ1/XcDk4uLS3t7e0NAAnIh/PmB69OjR2NhYXFzca6l1+lrk+fPnz58/v3//Pp/PP3Xq1DyFmd6EPHjwgMFgODo6vqEyyb8pcrk8IyNDIBAEBQUZGBjMf+98Pj83N9fOzs7MzOyv8wQXZEEWZB4BXqqFcViQN43LNacclFgY5DduaWkBEAqyZgFropmZ2V8Xv3O5XBsbm2nFreaRp0+fHj169Ndffx0bG4MOXr169ebNm+Pj47/36vr6+mvXrsVisQMDA1AFj7crCoUiMzNTLBYDytsbrbAIg8HEYrFUKoXSfKWnpx8/fjw7O1ssFr8ttJSQkHDq1Kkffvihs7NzWmrdaZKVlXX8+PEjR448f/78L/L4FgQSpVI5OTkpfAm5fv36b9ZMfbW5PTk5mZaW1tvbO/9Eml+mpqZACZ3X0iuJRDJ/U795woIsyIK88nsHfbCzs5NKpWq12tLSMi0tDQaDNTQ0wGCw9vb2t2lh6u3tJZFICoWiu7tbJpNRqVQmk/nyCGma6OnplZSUYDCY4OBgKI0YKKoKikn9rtZoNNrY2BgGgwHlxv4Kz7WioiItLe3QoUOurq4oFOr1JoGdKd98842hoeHatWvB0LFYLEtLSy8vr3lqbL05EQgEN2/exGKx27dvh8Fg5ubm08xLMpmssbFRJpPZ2NgQiUQTExMzM7Ouri5Q5OG/XCN0dXWB2lV/EQduW1vbsWPHdHV1yWQyAoFobm4WCAQGBgb6+vpIJLK3t5dMJhMIhJ6envLy8tDQUM3aOK9F0tLS6urqHj58CArTvkIL/f39fX19nZ2dCAQiMjLyj9hcxWJxY2Pj1NRUTk7OBx98MNP7r1Qqq6urFQrF/fv3P/nkEzAa4+Pj7e3tVlZWf6ZfvrOzU19f/w/ybReLbmLUAAAgAElEQVRkQf5SkpaWtnr1as0Penp6jx49Wrp0KRqNBs5KYHBisVhvBwrk5+f39PRUVFTExsZWVFTk5OSA/LN79uxxcXGZHzOVlJR0dHQoFAoEAhEVFQXZb0Ui0djYGJFI1FwgJycnFQrFtE1kR0dHRUWFSCQyNzd3cXGZpqGePHnS2dlpbm5eUVExMTEhEonmWXHFYvGjR48mJiZAEWnNJBYZGRlDQ0OgamlQUBBUg+yVpaenp6urC4vFUqnUP8HHlJOTY21tDRUCs7OzO3DggKmp6Vvxx7W2tl64cOHQoUOLFy+etQMTExPffvutoaHhgQMHCASCjY0N7PdUsPo/LDwe79SpU9u3b7eysnq7ocuQjI6Opqam7tu3j8vlotHopKSk8vLydevWhYWF4XC46urq/v7+TZs2VVZW9vX1vQm8a21t3d7eDhD2q7UwPDxcU1Nz7ty5sLCwxYsX/8ENbn19fXZ2dltb2+7du2cCJpVKVV9f//Tp0/v373/wwQcAMNXW1n7zzTffffedjY3Nn/BY7927NzExUVxc/I9//AOkQv4LTnW5XJ6YmAjKuaxcuXLBEb8gL6kNpn1AoVAWFhYwGExLSwtUonR3d29paXmbpO8bN26Ul5cLBAIPD4+QkJCpqamOjo4zZ87s37/f2dl51rne2tqalpYGMnA0NDQ8efKkq6sLFH9FIBClpaU8Hg+DwZw9e9bIyGjNmjVVVVWdnZ1qtfrMmTMsFisuLo5IJF65ckUul+vr6ysUigsXLvD5/KCgIAKBIJFI+vr6srKysFhsUlISkUisra1FIpEYDGZW4qFCocjKygIVwoVCoUqlGhoaWr9+PSjXd//+fYVCAYxACQkJExMTsbGxmvVfgUxNTYnF4oyMjOrqarlcvmLFCi6XOyteVCqVEolEpVJNTk7y+XxQ41OlUmVlZQUEBIDkGUKhUKlUPnjwICIigk6ni0QihULx9OlTU1NTkUiUnp4uEAjMzMxWrFgB1TcADSqVyps3b3Z1dQUFBfn5+aHRaKlUqlQq5XK5QCAAhXXkcjkMBisuLvb09AQqG7T/4sWLiooKPB4fHR2tr68PfiuXy1taWqampiwsLDo6OjIyMpYtW2ZhYQHygM0zK2QymVQqRSAQ086cmJjo6+sDxX1mFalU+uzZs9WrV8+6/Z2rWfBDmUymUqmwWKyWltZc3ROJRDgcDhpkHA6nmdv3ryxNTU2pqakrV67863hzkEjk4sWLY2NjbWxsUCgUnU5Ho9GWlpb+/v5EIhGJRF64cMHLy6uwsDA3NzczMzMuLu71pnV2dnbm8Xh/ZEE1NjbGYDAfffTRy5d7m0sIBIKXl9etW7fmImsikUhPT8+SkhKRSASdIBAIampqNI+8USESiRUVFSkpKR988MFfbYZPTk5C8eEkEunevXu1tbXAPLCABt6KCIXC+vp6MFsMDAxeTU+q1Wo+nw/U8hvVtE5OTtAHsKqC+omZmZkuLi46Ojrp6ene3t4gg+vbAUzOzs4BAQEVFRVsNjsyMhJYX4qLi7/66quTJ08eOXJk1lqV//nPf4RC4d69ey0tLa2trV1cXE6cOCESiXbs2MFkMrFYLBqNJpPJTk5OJiYmo6OjRUVFY2NjpqamTk5OLBYLh8MlJSUlJCTs37/fy8tLoVB0dXX9+OOPpqamtra2165dq6+v9/Pzc3JyMjAwmJqaOnXqlFwuNzY2nvXF6+7uLioqYrPZe/bsgcFgR44cKS0tXbZsGYVCefbs2alTpz777DNnZ2ckEjkxMcHj8UQi0UzA1NLSkpCQwGKx2tvba2pq6urqzpw5M2vAwuTkZEVFhVgsTk9Pb2hoCAkJqa2tbWxszMrKsrS01NXVhcFgqamp1dXVmZmZbm5udDq9oKCgoqIiMzNz6dKlIpGourp6cnLy/v37Wlpaq1evBlXEKyoqEhMTyWRybW3t+Ph4XV2dkZHR6OjotWvXWltblUrl4cOHfXx87O3ta2pqsrKybG1tHR0dAWCKj4+XSqX6+vqWlpYJCQmPHj1asWJFTExMbW1taWlpRkaGvb29iYnJwMBAQ0PD8+fPbWxstm7dam5uPpeL88WLF+3t7V1dXT09PaGhoa6urjQaDYlEKpXKtrY2uVze1NREpVLNzc0NDQ1nbUQsFldVVeHxeDMzM8isWFVVVVtbW1RURCKRdu3aZWtrCx6oSqV68eJFW1tbb2/v6OgonU5fs2bNtLwvMpmstrZWJpPl5OSsWbNGIBBcvnx5cHAwODjYzc3NyclJE91OTk42NjbK5XJtbW0rKyvNr/h8vlgsplKpdXV1DAYD6n9dXZ1AIFCr1fb29tN8rM3Nzaampt3d3cPDwyqVysLCQkdHB4lENjc3j42N6enpmZiYTBuEhoaGiYkJtVoN0jSDDgiFQnAJzTPb29uHhoaA8QaPx9va2gJ10N/f393d7ejoODY21t3djcfjra2twVfzi1Qq7e/vn+tlmSYWFhYHDx5ks9mQacTQ0NDOzg781t3dHUBbJpNJoVA041n+OkKj0Ugk0mvpGBaLZbPZ2tramuRLTUEgEGw2W0dHR3N6cLnc06dPs9nsPyeOzN3dva2t7U/DZy8v3d3dZ8+e/eyzz3A4HBKJDAgIyM7O7ujoWHDEv0VJTU0tKChISkrauHGjgYHBK7ezc+fOVatWrVq16k/bmnZ1dU1MTIDKLQAzwGAwMzMzLBYLyLtvRxNRKBRHR0dfX18Q7gQUpYeHh52dXXl5uVAonPVX5eXlTk5OxsbGNBqNRqNZW1tnZ2cnJyd7eXnp6+uD7LRRUVEREREMBmNsbGzFihWFhYX6+vp+fn6mpqYdHR13795ls9lcLpfBYMBgMEtLy4sXL/L5/Kamprt379rY2Pj5+QEEAIPBkpKS+vr65rI6UCiUlStXWlhYUCgUBALR0NBQVFTU0tLCYDC6u7tbW1tLSkqcnZ3JZHJoaGhVVdWsW2QUCsVisQIDA+3s7MrKyn755Zf8/PxVq1bNJG1oaWmZmJhgMBgbGxsA6RAIRFtbW1dXF7D9wGAwe3v7qqqq7u5uQHO2sLDo7u5ua2vr7OyMiYkJCwuTy+U///xzZmaml5eXtbU1EolMTEzEYrGurq4BAQEwGOzs2bNSqRSFQpHJZBQKxWAwjI2NORwOuPSJEycMDQ2Bxqyrq7t3796uXbvc3NyAhe/777//4YcfEAgEYOufOHECh8P5+vq6urouWbIEQFVra2tDQ8NZKSmFhYVXrlwJCAhwdnYeHx9/8OBBWVnZe++9R6fT5XJ5cnIyn8/v7e1tbm4mkUh6enrT1qqCggJA48XhcEKhcNu2bWBSFRcXAwMVkUi8d++eUCj89NNPORwOCoXKzc29detWcHAwl8sdGhpKSUkRi8V79uzRpLsplcr29vbc3NycnBwsFkun08HgpKenP3z48L333gsODgaOv8LCwrKyMsDKZzAY77//vp+fn5aWVnV1NbB0slgsDAZz9erVFStWxMXFjY2NFRUVpaSkAOCyatWqd999l0QiCQSCBw8eiESiqqqqtWvXXrt2DQSK+vn5bdmy5fnz5xkZGTwez9ra+sCBA5aWlmAcent78/PzpVIpHA5//vx5a2vrrl27IiIicnNz8/LypFIpYO34+PhYW1t3dnaePHmSzWaTSCQ4HJ6Xl7d58+aAgIB79+6VlpZWVlaeOHHizp07T58+3blzJ5vNnhUepaSkiESi6OhoiUTy5MmTkZERmUy2e/ful3E90+n0aZFQBAKBTqeDFw2Lxfr6+sJgMAaDQSKROBxORUUFYPnAYLDly5drJi0sLCxsa2sD4FhHRyciImIeP2xGRgbk46uqqtL0xwmFwnv37kkkEujIihUrQKV06Eh2dra/v/8rkyznEtDs7/2VoaFhTEzMn6axtbW1cTjcX9CkmpOTc/369YMHDwIDMIlEehl8vyBvVBwcHLq6uoAx/o+0k5ycbGdn92f2nEqlQis1h8MRi8X5+fnBwcFAx8Lebi054NOB/tXR0WEwGGQyeVaXfFJSEgBVwDQCGfYfPHgwMTGhUqksLS3pdLpEIgEPifa/Ar3kTU1N9fX1bDb7l19+AVq1vr4eiUSiUKiampqWlpa9e/e+PDecSCSy2WyhUHj79u3x8XGgtcG1nJ2dfXx8kpOTeTyetrY2iUSKiYmZlSttbGwMtJ62tjaZTE5JScnPz1+8ePFMSIHFYsGK6+Dg4OPjg0ajjYyMamtrNbUDl8stLS2FjlhbWw8PD2tpaXE4HB8fHxKJpFQq+/v7jxw50tPTY2Fh8ejRo9LS0qNHj7q5uYF1V6lUAludkZFRdXX1ypUrQ0JCgNnA1NQUYlcoFIqioqLh4WFnZ2eQdQ2Un/znP/+ZmZkZHByso6ODw+FYLJa3tzeoP6WlpZWSkjI8PDzrK1RaWvr9998HBgYGBAQYGxubmZldu3btzp07KBRqz549BAKBy+WWlJTY2Nj4+vrq6+vP3Nlra2uDLBpBQUHALjgyMgKOQwWSdHV1L1++HBMTY2FhoVAokpOT+/v7uVyutbW1TCYrKytLTk5ev3695hzAYDDu7u5ZWVlyuZzFYjk6OoK1raam5uDBgzk5OZ6enlgstrKyMj4+3tfXNyoqSqlU/uc//8nKynJwcGAwGDgcLi8vLy8vz9zcHIfD6enpgSnK4/G6u7t9fX1VKlVubu6vv/6Kw+E2bNgAClNkZGQUFRUZGRk5OTlZWlo+efLk9u3bPB5PT0/P1dWVwWCkpaUJhcJTp04xGAy5XH7s2DG1Wr127Vo6nc5gMAoKCtLT0wMCAshkMjBcUSgU8FBGR0ePHj2KRCK9vb3B23H8+HETExMPDw8qlSoUCp89e5acnGxhYVFcXNzY2BgRETET69+9e7etrS0hIcHMzKyjo4NGoxEIhNu3b3O53KCgoFdYsfh8fl9fn1Kp1DRQdXZ2guk6PDwcFBQ0MjKSkpLS0tLyz3/+k0QiTU1NFRUVnT17Njo6Glhfzpw5I5PJYmJiZmKm5ubmxMREJpMJblkikRQXF2sCJoFAUFRUFBQUhMPhampqUlJSuFwusCE1NTXduXNn+fLlly5dKi4ulkqlBw8ehKzFEonk3LlzCoVCrVYLBAITE5N169YBpAVYlQkJCVKpFFgrfX19/f39QVrhlpaWW7duIRCIsrKynJycFy9eQJrtZZxQ3333nUgkev/990Ehs/j4+KampsWLF5uamqalpY2OjspkMicnp9jYWIgVXldXl5SUBLJBSiSS6Oho6MWf+Tgg/yAGg5lm+5RKpVA8EZFI1PSYSCQSsVgMWaEAtFWpVEBFg4N4PB5gL5FIpKWlBfozMTEBADESiQShAOPj45CuwGKxwOk2q4UJGFBFIhEGg4FuRyaTQQGMBAIBjPkClPnTPEhtbW1/fMCPHTvm6en5Jzy4tra2oaEhLy8vsJETi8UPHz5csWIFAoEAbyWfzwfRIW8TMPF4PD6fD71IIyMjQ0NDa9eu1dfXn3lycXFxX1/fwMAAZFBBIBAMBgPSsAgEAg6HzwNpRSKRUCj08fFxcnICmIzL5a5atYrNZtfW1opEIh0dnWm6XiAQ9PX1MZnMmWtATU3Nzz//bGho6OLiwmazWSzW1atXAUOczWYfPHjw5MmT3d3d4GHw+fw9e/aAzKGajcjl8ubm5vr6+vHxcbVaPTg4iEKh5mHqvJpA9hgkEslgMIRCIYiZrKioGBsbo1KpUK88PT3RaDQCgRgZGRGJRH19fRQKZea9d3R0JCYmstlsCAXi8fjAwEADAwNQ2xk0SKPRID01f7BhY2NjWVnZoUOHTExMkEgkIJzl5eUVFRVt2rSJTCb7+fldvnzZwMDAwsJiVhOCra2tlpaWt7e3p6cnIF0BB4e1tbW1tTXQ+GFhYRcvXgRuhZycnIKCgiVLlvT09IyOjgIrVE9PT2Njo4GBAWRFQKFQpqamVCoVj8c7OztDHhATE5PDhw9DOp3BYKxfv97Z2RlEomVnZ1dUVPT09NBoNBaLtXHjxoyMDF1d3RUrVtjb22MwGDwez2azdXV1wbAEBQVt3bq1tLR05cqVNBrN19c3MTERg8G4ubm5uLig0WgkEpmbmyuTyZYvX+7o6CgWi0UiUWpqqkgkYjAYwNq3atUqa2trKpXKYrH+85//NDc39/X1OTk5AWKfi4uLu7s7gUB49OjR8+fPDxw44ODgAMXN1dfXDw0NeXh4VFZWolAoLpcbEBDA4XC0tLRmHW0Oh6NQKHp6epRKpZubG5PJ7O/vP3v2rObr/HunqLW19bQZMjo6KhKJZDLZypUrvby8xGLxs2fPHj169OGHH5JIpP7+/m+++cbR0TEkJARUgPrll1/S09O9vLymFQZQKpW5ublDQ0OrV68GbD+5XN7Q0NDc3Aydg0QiLS0tAwMDiUQih8N58uTJuXPnjh07RqFQDh8+rFKpCATCpk2bgCVVE2lVV1cPDQ0BltXt27dTU1NpNFpsbCwWi01MTCwoKFi+fDlAnEVFRYcPH7548aK5uXlLS8vRo0d1dHQCAwMdHBwaGxvFYvHLBwMqlcqSkpKysrI1a9aAm9XX1//888/z8/MBDxIgsMzMTENDw8DAQDQa3dDQ8M0335iamvr6+qJQqNTU1EOHDgF3/My3OycnRyAQAAWlpaW1Z88eaBo8f/68sLCwt7cXeMnDw8M3btwIJhJwWI+MjGhrayMQiPr6+rVr17LZbAMDg5s3bzY3N/f397u5uQUGBoI43zt37gQHB4MSqmlpafX19S0tLUFBQTt27ACRCiwWC4lEikQiOBy+bds2PT09zceqUqlKS0s7OzunpqZKSkqqqqpiYmIAb3dqaurWrVsFBQXW1taNjY0BAQFbtmzRhH1NTU3Dw8MQnIJWhGkyMTFRV1cHTWkHBweQzKWyshLKdqGjo2NtbS2XyysqKgAV0sXFBXT7xYsX0G85HA6A9XV1dUA12dnZ1dfXq9VqqNmqqiow7MAKy+FwoPstLy+HzJ96enp/0BWrUCja2tqsrKzmaaSmpsbOzm7WE+b5Crj7gQNnVpFIJD09PWw2exoMqqurUygUTk5OmsdXrVoFNhtvQtRqdU1NjYODAxwOh8w0IyMjUqlUV1cXWNYxGAwwcWVmZq5Zs+YtAyZAsIL+BfYSX1/fmVwfGAzm5uaWlJTE4/HmCmwRi8VTU1NEInH+mSQSidzc3HR0dDQPgodUWFhoZWWlGekmlUr5fP6sIGxwcDAzM/PDDz8MDAwkk8lXr17l8/mTk5MqlYrH45FIpP3794OuXr169f79+x4eHtOYN1NTU1evXu3o6PD39wcvQFpa2p+Z2Xba+MM0wspGR0dBfN+semRsbKy1tRWHw0HgFTgNXxntgUhGzcS+AE+MjIyo1Wqo1s88LYDfgj5oOk2ARxX8VrMRsKWg0Wj9/f3gCIvFWrNmDaiHM7N90DjUvWk5iI2NjY2NjYeHh+/evQvo4cPDw2AyYDAYT09PHA5nZmYWGhoKma8MDAwMDAzS0tL6+/tVKpVYLJbJZGq1GoFAEIlENBpNIBA4HA5IkMHlclks1vbt2729vbW0tIA/WqlUgsd38+ZNELR15coV8AT7+/vxeLxAIMBiseCuCQSCtrY2CoW6ceOGTCarr68XCoXgFsbGxvh8vkgkwuPx4GQnJyeA2+YabYDDgOEQcI+EQqGDg4ODg8OrMW0lEsmsYItIJG7evNnDwwM0y2Qy29vbwTqXkpLy9OnTuLg4YMYDoDw/Px9AXk2Ur1Aobty4ERoaamBgAIESFxcXzXMoFAoIhkhNTR0dHRUKhU+fPgXTu6SkJDw8XEdHBxhTOzo6NE1uRkZGW7du9fX1xWAwwEgMjM2dnZ2JiYl6enpAP8BgsOHh4R9++EEoFDY1NZ04cYJEIm3evJnD4SCRSHd399zcXD6f/5LDhcfjIyIiSkpKoLnq4OAgk8nAah0SEsJms8vKynbu3Am5IG/cuNHQ0PDpp5+CbLeVlZVXrlyZmaKMx+MdP37c19cXrNYjIyOpqamaL3V3dzcKheJwOBKJpLy8/OTJk0uWLAEbpwsXLhQVFa1cuRIYvSYnJ7/66qsNGzZs2rTJ3d29vLz80aNH27ZtMzIyQiAQHR0dt2/fHhgYOHDgABaLdXBwaG1t5fP5gCqQkJCQn59/8uRJPB4/NjYGHNNQqIqmDRLkDens7FQoFJB2VSqVAoFAR0fHwcGhvLz8xx9/hMFgu3fvxmAwfD4/MTERQGQ4HJ6Tk4NAIH766aeZZlSVSnX27NnBwUEnJ6e+vr7MzMzIyMiPPvoIg8H09vaWl5fn5OTExMS4urpaWVlNTU1lZWXl5uZu3boVUFcvX75cVVXl6emJRCJramoyMzP/53/+B4/HX758+cmTJyqVatGiRfn5+UqlEtiJs7KykEgkUFbJycm2trZffPEFmKJFRUWnT58OCwtDoVA3b97U1dX18vJCIBC2tra+vr6g/dLSUmgy6OvrL126dFbV3dnZ+ejRI5VKhUKhCgoK1Go1m81Go9FOTk4AtN28eVMgEAQHB3///feenp5hYWEWFhZAbf76668ymSwyMvLw4cNBQUEIBGL79u2aVwEEg7KyMnNzcx6PN+11bmpqAldEIpE5OTlUKnX16tVgjiUnJ6NQqPT09EWLFgFwXF1dXV5e3t/fz2KxoA5Acv/+/aioqD++Vvb394PU3jo6OgASiMVioVAITPuPHz+2tbUdHR2dmpqytbWFwWC5ublvmU158+ZNFoulr6+flJQkFAqXLVsGXjZIjyuVyrGxMcH/Y++745o81/fJTkhCEggjhEAg7I1hj8hWFFy4a50V29pa23pau+yptUt7tLWOilo3bkRGAYEKgoggSNh7j0R2gITs3x/377yffECtp+P0nO/h/gsy3vfNO57neq77uq9bIomIiICMG9Q0odFopVJ58+ZNJycn0KVaWFhQKJSOjo7h4WE0Gk2j0WCQlcvlMplsdHTUxcWFz+fn5+cvXbqUwWBgMBiZTDYxMUGj0fz8/FxdXXNzc0FOhMFggIahUqnm5uYzKZbJycm8vLyxsTEmk6lWqwcGBvLz89vb2wcGBlQqVX19PQqFEggEgPyePHmSl5c3055Ao9HcvHnTzs7Oy8uLw+HIZDIqlfp7NJVKpVIqlf5LS3y1Wg2Z5mlPl42NDYFAgAK6md+ysrIKDQ29ffv2NPCKQqGgyum/gjfWarVNTU1RUVG6i2x9ff0XzChhMBik5k4qlV69enV0dNTS0pJGowUEBFRWVj7HAkqtVj98+PDu3btcLtfU1BSFQj1/p5OTk1NTU7W1taCLmvZuc3Ozubl5WFgYrMj19PTefvttAwMDXVW1bnKKTqfriog/+eQTFov1L7VrnJiYuH79elhYmIWFBezi3LlzBALB2Nj4t119AoHw1ApKPB5vY2ODgDAKhTI+Pv7LL78sW7asoKBgamoqIyOjp6cHPuDi4iKVSkFRN+1CA3Xx/KHzwoULaDTazs6OxWKRyWRkrb9p06b09PT333/fyspq9erV/v7+upfAwsLCx8cHLp8uSdbc3CwUCt3c3MRisUwmk0gk6enpgFlramoyMjKSkpIAHAB6ZjAYyB5/NXA4HI/Hm3mqo6OjAwMDsVisra2tQqFADgbUcng8nkAgDAwM6OnpjY+PU6nU5OTk9evX65KIRCJxcHCQRqNZW1vT6XSNRjPtieDz+bCYEQgEFy9e3LdvH2S+xsbGkpKSAgMD58+fD3lPKyur06dPnz59OiAggM/nJyQklJeXNzU1zZ07VyqVfvXVVx0dHQMDA+vXrzc3N+dwOA0NDQsXLgwMDMRgMC0tLVqtlsvlArrS19cHImraaBMQEFBWVobFYgMCAmCshs/gcLjY2FgymWxmZsZmsz/66KPLly9v2bIFj8e3t7cfP3789ddfhx3p6+t/+OGHKSkpy5cvn4b1gYFYs2aNs7Pz4OBgUVHRuXPnNm7cyGKxPD09nzx5Ul1dvXXrVgcHBxQKhcVi0Wg0l8v18fHBYDCXLl26du3a9u3bPT090Wh0X1/fqVOn9PX1d+3aFRwcrFAojh49Gh0dHR8fX1RUBDReU1NTZGQkgIOJiYkjR45ERkaGhoYKhcK9e/eGh4eHhISAS9m3335raWnp7e0NEKenp+fTTz/l8/murq4oFOratWtSqVQgEExT4MGy5OOPPzYxMQkLC2Oz2WfPnr1z5w5ogufMmbNr165r166dOnXqzTffJJFIHh4ep06dunv37unTp6lU6tjYWHJy8pYtWwgEQlRUVHNzM6gCEhISqFRqQ0NDUlKSs7Mzi8UKDg7GYDAXLlzQHf3a2tr27dvn4OAAioL9+/cPDQ1FR0cDg6vVajdu3KjRaKqrqwF8U6nU/Pz8e/fubdu2DdmISCT67rvvDAwMHjx48PDhQ4lE8v777//mKjxYZsxMySF8DQh5SSSSWq1ms9ljY2MMBuMvBkzd3d23b982MDBobW1dsmQJlKzD78/Ly2tvb/fw8CgrKyMQCIGBgf7+/q2trampqU5OTng8XqVSDQ0NhYeHQ6qLTqcTCITW1tYTJ06w2ez169dD7VhVVdXly5d5PF5MTExUVNThw4cTExNjYmKoVGp9fb1YLN6yZYudnV1UVFRiYuIHH3ywaNEiDofT39+Pw+E0Gk19ff3ExASfz9clzHE4HIfDIRAIp0+flkqlCoXCw8MjOzu7qqpqbGxsfHy8vb1dq9XCV6DOH8Qu0x7IwcFBIyOjiooKqFrq7e39DTZ65eXlVCpVrVb39fVVVFS8OIdpbW2t1WpPnjz55ptvOjg46I4XTCZTpVJ1dHTU1NTw+fxpnocmJibz589/+PBhc3MzVBDA2lQul69fv57BYPw2d+b6+npbW9s/toD8WWFhYUGn07u6uqBB+r/6ddCeL793wKcAACAASURBVFq0iEKhTExMXLp06ciRI59++mlYWBiBQKBSqbo6j2dpUCwsLFatWgUaL0gqPX+nPB7vqbjKycmpoqKCRCIFBwcjSVIMBvPUclxnZ+fCwkL4MHJDYrHYf8klYWpq6v79+xs3bkRQV3Fxsb+//+8p5H6RvfP5/NzcXEtLSwwGs3jx4l9++cXa2trb2xtOi62t7bx58+zs7H4DaPvHP/7R09OzcePGgIAAMpmckpIiFovhrcWLF5eXl3d2dmZlZd27dw+Hw73zzjuBgYHPP2CpVCqRSKRSKSCVqakpFot16NAhDocDJnCQHPxj72omk/nUTuF1dXVdXV1BQUEpKSlwjYaHh99//30PD49paVAjIyMLC4uDBw/q6+sLBAJ3d3dEjI88ODY2NiCvZjKZyFsnT54cGhoKDAxEMl8sFmv79u1ffPGFSCRycnLi8/kMBqOgoGDTpk1yuby/v3/v3r2fffbZ+fPn33777cnJSZVKFRMTA/ImR0fH7Ozst956a+HChQ4ODmZmZjNbw6JQKGtra5BJcblc3cwAGo22trYG9Ym/v7+jo2Nubi7M34cOHWIymQKBAH4Fm81+5513Hj16tHTp0ml3LwqFAqswIpFoYGDAYDDy8/MTExM//PBDCwuL+fPnp6ampqamAk0ikUgqKyvXrVvn6OiIQqEKCgqGhobAmQ+FQq1cuTIjIyM7O3vnzp3R0dEtLS0oFMrT0zM8PDwiIoLFYtHp9HXr1nE4HAaD0draamxs3NnZWV9fP3fu3La2tuLi4q+++gqyEHFxcZ9//rmlpSWUm6BQqPz8/Nra2oSEhKCgIFBArlq1Ki0tbd26ddMeBKVSmZaW9t57782dO1dfX3/jxo1paWlqtfqll16i0+lisfj69esMBiMsLIxMJq9bt66lpeXcuXPA/n733XeDg4OhoaEUCmXNmjXt7e0ikejw4cPm5uYrV67MzMwcGhqaO3cu1JEolcq6urr9+/cju963b9/g4OBHH31kaWmJw+FcXFx++OGHK1eubNu2raCgYPfu3a6urvb29jgcTigUAlZ+7bXXrl+/jgyhra2t+/fvx+Px4eHhbm5ujx8/vnfv3s6dO3/PgGNubo5gIzhXui5o9vb2tbW1AKqkUmlJSUloaOhfCZj4fP6iRYvAtXnu3LmOjo66ymgXFxcOh7N8+XLQiBAIhNdff/3x48egKwJCddOmTfCowCMaHR3d2dmJRqPt7e1h3l2wYAHM6JaWlmQyOTY2dmxsbGpqSiwWj46OymQye3t7kLzEx8dPTk4+efIEGClXV1cPD4/CwkKpVNrb2wvuVboL38jIyMHBwfHxcRKJ5OjoyGazR0ZGYIoCMfjAwAC0ZLG2to6JiYG7YRpFIRAIcnJyuru7IdlPoVB6e3tra2tNTU2noavU1NQ7d+5MTEykpKRMTU2BY42Dg4ONjc3JkydBwRoZGWliYoLD4a5cuQLFnK2trePj43fu3AE/YkRVmpGRodFo/P39V61alZSUpFQq3dzcYNZZsmQJlOBpNJqampqDBw8eOHBALpeXlpYODg5WV1efOXNm69atc+fO5fF4iYmJDQ0NcXFxZWVlcrncz88vICCgtra2qKhodHS0tLT08uXL4E0F+y0uLqbT6StXrpymnHB2duZyuSkpKSEhIXDhhEJhb29vRETECwo7qFSqv79/RUVFe3v75OSkp6fn8z8fFBRkZ2fX2dlZWVlpZGQEZzs3N9ff3/+pexwfHy8uLjY2NtbX129sbDx06JCvry+YrEql0qqqqo6ODmdnZ1jVFRUV2draIuzLU5Ohjx8/9vHxMTExoVAoxcXF4H/xHAIGh8OJRKKnZjxXr1597ty5jIyMqKgoMGJ4zg9fvXp1Zmbm7du3586dy2AwftucrdVqFQoFyN1QKNT9+/cnJydhtvvN5Cjo6p7/sY6ODolEAnWFwOs4OzuHh4e/yH6B4YfRRiaTQVEh8m5paam9vX1oaCjcq7qww9ra+sMPP1SpVMnJyRMTE9nZ2WfPnvX09HyRhtwMBsPHxweGNSMjI10VY1ZWlrW19b9neaBSqdRqtZWVlZ+fH9BjAQEBID+YdgNgsdjg4GClUtnU1PTjjz8aGhpyudzdu3cjXjXPOb0jIyM9PT0Ir4BGo319fbVarUaj0Wq1eDx+4cKF165dEwqFTU1NVCp14cKF+/fvFwqF4B7HYDAQmnP58uWjo6MPHjw4fPgwjUZzdHT84IMP7O3tfwOXgMVidUHhw4cPDQ0N09PTkdF4YmJCV1qgi7osLS3Pnz+vUqkwGIyLi8uDBw+MjIzgGMzNzblc7oULF3JychYsWCCTyVAolJ+fHxaLRaFQcrl8ZGTk7NmzyApncnJyyZIlsDKZmJjw8vLi8XgUCgUhOYClhiS+QqFQqVSgu4c/kOkA/gBGFn7XTz/9hMFg6HQ6cLSjo6NDQ0ONjY0ajWbmUCCXy0FDicVi58yZY2BgYGZmFhMTg8fjf/7554cPHwoEgkePHqnV6qCgIDc3N4VCkZqaSiaTz58/v2PHDqitwWKxrq6u7733XlJSUlNTk1KpPHPmzNq1a01NTZE9ent7695axcXFvr6+XV1dUOoukUgmJyerq6u1Wu3w8HBmZubAwICpqWlERATQrmg0elrpaFZWVkpKyt27d52cnFAolIWFRVdX1x9lOAIpOYVCkZubGxMTk5qaumjRIgKBMDg4CBcUpMmFhYV/JWAaGxuzsrJCBAozl8LTXnF1dbWyskKUtigUSlefq6enFxcXBzUaJiYmMBItW7YMFvqmpqYkEolMJm/atEl3aDY0NIQlkbW19datWyHHBMkFEPwqFApwhZl2MDY2Ntu2bVOpVPr6+iCt37Jli1KpZDKZDAYDnJwQdAU4ZmZO59VXX+Xz+VNTU8HBwRYWFmg0emBgYOZaCkidqKgoMERABNQuLi4fffRRZ2cnkUjUaDSBgYGQW2QwGPCgmpqa2tvbMxgMZPJ2dHTcu3evvr4+i8WysrLasmULpDzu3bsXEhICLB3s8Z133pmcnFSr1XQ6XSqVWlhY7Nmzh0gk0ul0HA5naGi4Y8eO3t5eWHjBjiIiIhgMxujoqL29/eeff04mkxFVvqGh4aeffopGo2c6Aujp6bm7u+/Zs+fIkSNfffUVqEkuXLgQHBy8cuVKSBzk5+fr6+tDvf3ixYtn1hMZGBjMmzfv1KlTx48f53K5XV1dVVVVRCKxsLBQq9W+9NJLkKI1NTXNy8tTKpUrV6588803P/vss4sXL5aVlSEUxXOSYklJSQ0NDQQCgU6n+/j4QBYAFiWWlpZYLPbkyZMCgaCtrS0jI2NkZKS/v39wcJBMJp85c2ZkZGR8fFwsFkNSBlLGGRkZXl5ejY2NMEnLZDKRSATJICggFYlEULnW0NAwODioUqnEYjEajUZmWbFYbGRk5ODgsG3btqSkpH379n3wwQd0Ov3q1atsNhuyEiQSiUQiHTp0yMrKasWKFd7e3i+//HJaWtqBAwdeffVVKpV65swZLy+v8PBwiUQC1UxisRh8hp4Dp2xtbW1sbIaGhsrKyk6ePLl06VIwuHry5Ml3330XExPj5+f3IsnN8fFxhUIhFovLy8stLCyAPdLNXYpEIgqFApMBLG8UCoVMJsNgMAYGBpcvX/by8jIxMYFpjEwmzzxsHA63devWK1eufPbZZx9//DGVSpVIJA8ePFAoFIODg8PDw4h8ob+/v7+/PzMz8/Hjx5BHYzKZly9fXrNmDZlMZrPZQLu+SL8dNze3oKCg9vZ2S0tLIDP09PSgJYCfn5+Xl9ft27fj4+MBIkxMTLwIXvzNERIS4ubm1tHRwePxZqYsp2Vt+Hy+h4eHSCQSCoXDw8OHDh2KiYn51eruTZs25eTk6AKmmbF06dJDhw7l5+eXlZVt2rQJj8dv27bt8OHDWVlZWVlZ27ZtQwZJQ0ND8MWoq6vr7++/dOlSS0sLj8f7Qzg5CoWiW8fz5ZdfOjs7zxyUNBrNxx9/TKFQIiMjaTSav7//rVu3QFUJH4iPj09NTc3Ozp43bx6QJcAWI3edbqevN998MywsDPbCYrEkEokuXq+rq/vss88mJibeffddGKuRp4DP58+fP//AgQP+/v4MBqOysjIiIkIXjjQ0NIBSFop2f/nll2+++cbX13cmWkKhUJD5BcYhJyeHQCC8/PLLiN55YGBgYGCgq6sLh8MdO3YMhUIdOnTI1tYWBAZisVj3FgXgAsunxsbGF7l7S0pKOBzO/fv3Q0NDbW1tnZyc0Gh0QkLCpUuXmpqaZDIZELdeXl7Tho66urozZ85s3rwZEqBA/2zevFmXVvz9gUKhQK4OuSmYmIBfCAgI4PF44+PjfyVg6ujo0C03fUEi4TnFt8jvRGJmhuupJXgQCEGnq+h8ju5ymlOAhYWF7jP5IpfH2dnZzs5Oq9WCoDgqKkqtVk9bEkF4eXkhizw0Gg33E4VCiYiIQGRGBAJBo9E4Ojo+dbUEgxGbzV69ejWIi/F4vKWlJfzr6OgI610kNRMXFweXBo/HMxgMExMTBPLDKBAaGgq7bm5u5nA4FAoFwLi1tTWHw9FlR2AmW7FiBSi4Z86jVCo1Ojoa3ITByT02NpbL5YI3I9j6RUVF4XA43brIaevIyMhIU1NTgMtQDxgQEAC5WtijlZXVV199pVarDQ0NgdqFxRyyQWdn52et+Gk0Wnx8PIgkjI2NbWxskNwxVFKEhYWJRKLBwUEXFxcDA4Ps7OyKigq1Ws1isZqamnx9fVUqVU5ODovFotFoFArljTfeyMrKKi8vnzNnjr29/aNHj8DzPS4urqioCIfD2dvb5+XlEQiE8vLy1tZWT0/P4eHhtLQ0yDpZWlqGhITk5+erVCofH59XXnkFjUZXVlamp6cTicTGxkZkHeLl5bV+/fqamhqtVstgMOh0+htvvIHFYnt6elJTUwkEgkgkAhSbnZ09PDwcGBiYn5+vVCoRNmJmVFdXP3ny5OTJk/X19QqFwtPTc+XKlbCoUKlUZWVldnZ2fD7/VwHT8PDwL7/8AtVPADQ3btwIz86TJ09IJJKnp2dOTg5UEqHRaCKR6O7uDu6mHA7n9ddfLygo2LNnD1yIoKAgf3//wMDAafvFYDDbtm1Do9GPHz/+29/+xuPxuFzuihUrmExmZWUlFouNiory9fVtbW09deqUtbW1s7NzSEhIZ2dnY2Mjh8NJSUnx8PAAlwEoj9q9ezeZTBYKhUqlsr29vaCgIDIyEjlXLS0tRUVFAoEgNjb2yy+/BMAB7+bn5yckJPB4vIULF37//feHDx+OiIiAis7u7u7Jycn8/PygoKCZ6uahoaGuri65XF5QUMDn883MzOrq6uBUk0gkNzc3OBiottNNxdbW1k5NTTk5OcXExCQmJh49ejQkJMTb27u2tlatVgsEgmnnqqam5v79+y+99JKPj4+np6dIJPr222+fZYynG5Ah6urqGhoagpIIjUZTVVXF4XAQHsvc3NzW1vby5ct2dnYCgQCLxS5cuPDMmTNffvmlvb09qK9ga+fPn1+zZk1gYKCvr29fX19JSclvbmLzVH7UyclJd12qC1CQePz48e3bt1999VX4aVevXkUKRCD8/PwEAkFDQ0Nubu6TJ09AFDVtQnF3d0f2glyX5ubmaTno3t7ewsLCzz77LDIykkgkjo2N6RKcq1ev/uSTT3A4XFRUVFhY2IoVK+zs7HS/7u3tDfeYpaXlypUrXV1dn5qOJxKJH374YVZW1s6dO0NCQpqbm99+++2wsDDdm23jxo1gWwN2IcDIwqKisrLyd2L6BQsWmJubDw0NgVQLTtfWrVvd3d21Wm1iYiLYqunm8pDzU11dvXbtWuRHkcnkZ5livEi0tbXRaDQQ22k0GqFQ6OnpicViASHNmTMHkCjM6ZCkgprxvxIwPasVwP9OTHtQnzPBPGvqmvYVNBr9/Hto5tAAHC94mz5njzM3i+x6Wr4Sh8PNxDQw2z3nwPB4fGhoqJOTE2iAdK3ep23/OXh3JuTVDTqdPq3tV2Rk5AteKRKJBKrqp74LJZAqlcrExMTCwmJqasrHx0ehUAA1smXLFkCWoCuCc7tixQofHx+9fxoibN++HfwOmEwmn89HfrKpqamXl5cu2wqzaVBQEJfLVavV4Eplbm6+efPm/v5+2FFISIiLiwtcIBaLlZCQ8OTJEzqdbmVlhcPhrK2tX3vttcHBQQDE4eHhoGDz9PRE0Db0wX3W2bhy5QoKhbKxsQEJp5WVFaLIMTQ0fPXVV2e6kD8rE0en07dv3w7fhU5ESO5AIBDMnz8fjUZDjhiWlW+88YZGozEzM6PRaOvWrRMIBLdu3RofH9dqtT4+PtbW1k9dWLPZ7K1bt3Z1daWkpNjb27u5uXG53LCwMJVKBbYar732GhSQw7sODg5g/o7BYFxdXY8dOwaTkIGBQXh4OLQPkkgkmzdvNjQ0RAgnPB7/yiuvGBgYjIyMoFCo2NjY4eHh+vr6L774gkQirV69mkQi4XA4LBa7fPny8fFxPB6flJQUFBQEy5iRkREgHmaOinK5HJjj8fFxKMVgMpkJCQl4PF4ikWg0GrVa/corr7DZ7PT09JUrVxKJRENDw4SEBBaLlZGRER8f/9JLL01NTbW0tNy9ezc4OFgul/P5/JmL1SdPniQmJoaEhBgaGpJIJFCMQWEdfCA9Pd3W1lb3WU5PT09ISCAQCLGxsVlZWYcOHdq7dy+ZTE5LS8vOzn7jjTeQGni47Xfv3v3uu++CrxKTyVy8ePHf//73999/X9dpqbKyErgHEol0+/ZtCoWCFAM9dR45ceIEkUiMj49XKBRVVVUzf9f4+Pjdu3cXLFgQFxcHfAZi+vqsGBkZAeE8iUTq7++/cuXK8PCw7oIKj8dv2rRp7dq1n3766d69e3WNPaOioqBo7qnLhubmZrgNdNkstVoNrc0fPHhw//59JEGBxWK7urr09PQ2bNjg4OBgbGw8EwmNjY3Z2to+3yYARuagoKDExEQvLy9/f/+goCAXF5dpBchisdjKygqLxVpaWuoKGKAucqYS1MfHB1ExikQiWFLKZLKsrKxpVwHoeRaLNW2Uvn///uLFi0FPVlVVtXfv3qdKTt3d3ZOSknbs2IH8xt/jUDoxMYFcSkgLwkDR29s7Njbm6ekJNhlwFfr6+lgsFvx81L8fshQXF5eWljY0NBQWFgYGBoaHh8fExPyx3NpszMYfGO+9997PP/+ckZHxLMD0vxbR0dFMJnP37t3QAWbaCD4xMYFCocB5+fnbgbaDT7UCkUqlarX6V5sPwnAG5fFg2/EcmYtGo+nr6wOWeuZmAbDq6+tPe6uhoaGqqgoYZS6Xi8Fg2Gw2BoMZHByEdD8AMgwGA9uHmlMWi4XBYEQiUWdnZ3V1NRaLBesBaGyAQqHgsKuqquzs7IyNjdVqNUAlJpM5rcYCMmUIwAW1ikgkAnAMkgCxWAzmmX19fd7e3jgcDlK6Go1GJBKBm1dPT09ra2tTUxODwaDRaLa2ttMSoHp6ep2dnR9//LGRkREIum1sbPT19UNCQm7cuCGRSO7duxcTE8PhcKKiovB4fG1tLVTJgAa5sbGxpKQkLy/P0dERcDkWiw0LC9N1Zs/Ly7tx48aHH34I5W96enppaWm7du1KTk6GBA187N133wVjeiwW+/jx45dffjksLAzhdHWjvLz8vffeA3j92muvgRDHwsKCQCBERkZ6e3tjMJiPP/4YruyuXbuEQuHLL79sZ2dnbm7O5/PB0szHxyciImIafurv7w8KCoIKMhcXFyMjo+PHj1taWh4+fBipdZicnNy1a9fNmzfBkgY5/sHBwYULF+JwOGdnZzAKYTAY5ubm69atw+Fwrq6usFrbtWsXm80GkfiWLVv4fD6LxfLw8IDaPTs7uxMnTlhaWm7fvj0pKWn58uW6R/jWW285ODiAMdixY8fc3d2/+uorSHoMDAxIpdLg4OBpd7JcLn/77bdFItGWLVtcXFyQk2loaEihUJqamt57772mpqbt27cvXLgQvpuSkrJ582YKhZKQkJCenr5v376IiAhLS8vx8fHjx4+XlpaePHmSRqN9/PHHV65cCQ4O3rt3LwaDuX379okTJ+rq6jIzM/l8PpPJTExM/Prrr52dnb/44guwVvnxxx8FAgGfz3/ttddOnDhhZGTU09OTlZX13XffPXr0SKFQjI6O8ni8HTt27Nu3D4VCvfvuu+fPn29ubtbNe/4eORCBQICxS6PRDA4OAhIVi8W9vb2w2mxtbWWxWPr6+tXV1TweD5AS5u9///u/n1jS19e3s7OLiIgAWRI0bZ2dh2bjPzNycnKam5uhlmT2bOjp6d26dWvbtm18Pv+pzD8ej3/BmjswzXrqJ3E43As23aRSqXQ6HTzDnv95aM76LE+vZx22oaGhnZ0dj8ezsrIyMjKCBBNYW9FoNDqdDs7UyPbpdDqio6JQKCwWCxyqjI2NdQ8SDtvGxgYqCSgUCmztqccAXTLhZ0LCC3YE4AmFQkGrADqdDowj5DvgFci3wrFxOBzgz2xsbHRxDBLQi8bc3JzNZrPZbOgjSSaTlUqlo6MjzHBkMhnglKGhoaOj45w5c8hksqGhoYmJiaurq7W1tampqbm5uY+Pj5eX1zRsSiaT+Xw+KLeQ8+Dl5TWN6jAzM3NxcbGysoJjEAgEM0EkhImJiaOjo7e3d2hoKJvNJpFIAQEBAoGARCKBxwcKhTIxMZk7dy6Hw4EOWs7OzhKJpLu7WyqVikSi4OBgW1vbacWAcKhUKrW/v18mk61cuTI8PNze3r6+vp7H4yGUJw6HIxKJPB5PIBDoHr++vj6PxzMwMGhsbJRIJGw229/f39LSEmBiXV3d1q1bHR0dOzs77ezsQCPr4eHR0dGBxWLBetTNzU2lUnl5eclksqSkJDqdrlKpJiYmxsfHoQClp6dnwYIFWCwWvDq7u7uzs7MzMjJEIpFUKnVzc9PtcoFEVVXVL7/80tTUlJmZmfHPGBwcdHNzMzU1dXZ2bmlpqa+vz8jIyM/Pn5ycrK2thSyhubl5W1sbvAW9R8vKyqCvKxqNdnFxkcvlvb290PGTy+XyeDw4P1qtlsfjQc1TZ2dnXl6eUCiEFPO8efPq6urKyspaW1uVSuUPP/wAtSM+Pj61tbV5eXkajYZOp0NTUbFYnJ+fPzQ0hMFgWltbW1paWlpaTE1Nf1sTdCKRiCyu4FmGv0kkUnNzM41GA5xkZGQ0OjoKkLetrY3D4aD+x5NiszEbz2dur169eunSJRjjlixZgpQT/s9GcXHxBx98gFRizsZs/NdFe3v78PAwzH3u7u5P9WLQ09OTSCTgCAVelGq1WigUslgsXc/x4eFhyJDO3MKTJ0+6u7tBVQk1PfB6c3MziHimKdkbGhowGAzySldXF5PJLCwsvHDhwoYNG3SdRz799NPOzk5QsOnp6YnF4p6enuvXr8vl8tDQUHt7eyCfph2PXC5/8803m5ubdQ21Gxsb6+vrc3NzbWxsUChUdXV1XV1daWkplUqNiYnBYDDgPQH+5tXV1ZWVlZ6ensbGxsbGxnPmzEH20tPTIxKJ4G8nJye5XA7eOtAuHYVCDQ0NdXR0pKSkmJqa+vr66uvru7i4tLW1tba2Pn78mM1md3d3R0ZG2tvbg49/X18fbM3BwQHqx8+dOweNMcBvc+HChXFxcYCJ/6Wr39vb29HRERgY2N3d3dfXN637Snd3t5GREYlE6u7uNjY2htpkFotVVVUVGBg4C5hmYzaeGVNTUyUlJSKRSCaTMZlMV1fXF1Tn/B+O06dPJyUlXbp06Tn1E7MxG7Px+2N0dHTVqlVubm6ffPIJWBzB6+vXr6+oqEAAE4IDNBoNk8l8Foe6b9++goKCjz76CBAMvJiamrpz506hUIh0YpmYmBgdHcViseCpq7uF8fHx0dFRYCJ1j+fFo7+/n0Ag6JpqQpGs3j/LyZ+zTciXVVRUQNm7p6cn5Kb+1cMYHh4eHBy0s7MbHh4eGRnh8Xjggwj9l5RKpS4IAy9oIpHY29traGiInb0pZ2M2nhUEAiEoKAhZVIBByP/4OQkJCeHxeLPZydmYjT87NBoNWH9t374dcaDu6urq6+vz8fGZNhb9qgHvnTt3DAwMwKpeV8Dk5uamq7inUCjPqvJ+fpX6i8RMWhqPx+tWVT8nTE1NjY2N3dzcoMr7V1PwzwpIo+vp6UHVsJ6OcaVYLB4bG3N2dq6pqZkzZ87Dhw/9/PyqqqpsbW2lUqlUKp0FTLMxG88MFAo1q66bFvb29vb29rPnYTZm488OCoXy3nvvffbZZ0ePHkVMc9ra2szNzV999dV/dWhaunTpmTNnHj9+jCShzp49C8ab05qr/scGGo3+/UtWZAsI3kJ6yRkaGpLJZK1WCzVxk5OTenp6U1NTarUazv9sSm42ZmM2ZmM2ZuM/MWQyGTRyQAgVqVTK4XAQadGLb6q/v//06dPd3d1IYz6hULhixQpoS/K/xp339PRAiaJGo+nv7zc3N9dqtfCHRqOBznFVVVXu7u6jo6NjY2NcLjctLe0/hWF68ODBwMCAVqsNCAiAEozx8fHS0lIulwvdZ/5bLkNlZSU0OZl91GdjNmZjNmbj9wSJRAoPD5/Ga6D+Gf/SpszMzF555ZXq6mrklYCAAOiV+/sL9f/rory8HJKYGo2moqICjPSEQqG5uTkGgzE0NNTT0+vo6HB3d2cwGPfu3eNyudbW1v8pgGlwcPDo0aNisfj48eNQ7wqvLFu27Kl9Rf7TYmxs7OrVq0NDQ83NzXv27JkFTLMxG7MxG7Px++OP4n5QKJSZmdlsrQYE0u0HjUaDMzAGgwHn3qSkpDVr1qBQKOQzLi4uVVVVenp6/yksHJ/P5/P5wM0gHWoUCoVarf7VpGFvb29XV9dTGyj+2wKPx7u6ura2+vGeKgAAIABJREFUtgqFQt0mQbPx4gHufE/tL/uHx9DQ0P79+z/55JOWlhakt8xszMZszMZs/C+Era0tIA3AoyUlJeDUikKhEI3mw4cP9fT0+vv7LS0tjYyMjIyM/lMYJhaLxefzHz58CH67enp6pqamYAj7qw29L168ODY2tn379l8tE/jzgkgkBgQE3L59+zdvobGxsb29PTAwEKmG+F+LlJSU2tradevW2dra/qml+0NDQ3fv3oXmXN3d3Uhn4j8kysrKent71Wo1NAec5RpfJMRicWlpqUajiY6Ofv7zPjExkZ+fL5fLqVQquAXOnr3ZmI3Z+D2BVMlBII3CgHBqbGz08vIyNzd/9OjRXwyYdBf3Go2mtbVVIpEAYCISiSDm/9X0ak1NDbQp+At/yO/MAXd0dPzwww+1tbUnT578HwFMarW6urqaQCDweDywghwdHb1586aXlxc0M/rzdn3s2DGlUrl27VoKhcJkMn//vsrLy+/evbthwwYmk6nRaLq6uq5evRoZGRkaGjo7GP1qKBSKw4cP37lzB4fDBQQEPB8wabVaoVB4+/bt11577V/q2/2Hh0qlAm/iFStW2Nra/oGYe+ZP1mg0v0228oeERqOBDjB/1QHMxmz8qQFVcpcuXVq7dm1ubi74nuvp6Xl5eenp6dnY2CBNVP4ywDQ+Pt7X13f//v0nT55oNJrOzs76+npnZ2czMzM0Gi0SiX744YfOzs6XXnpJIBBAI/TW1lapVApfByd+HA43ODg4MTEBQ2dvby+TySQQCJ2dnciLBgYGLBYLpmSRSDQ8PEyhUMzMzHp6eqRSqVarJRKJlpaWSK9ZrVbb2tqKwC8jIyMTExOYU7u6usbHx2GzVCrV3Nz8WabP/f39IyMjAAd5PJ5uX8aenp6xsTHYiL6+PofDwePxYALW2tr6Bzbl/g+PU6dO3bp1a/369XAG9PT0YmJiTExMPD09/2zJ2u3btwUCgYODg5GR0R+ywdra2lOnTsXFxTGZTOhSefLkycrKyv+dq/l7AoPBhIWFNTc3FxQUQFe45wSJRAoJCUlLS2toaPj3ZG+fFd9//31DQwOTybxw4cL777//O/1pdGNycnJychJqXwBQvvXWW1FRUbGxsc9qwv3nxdjY2E8//QS16Fu2bEEovampqba2NrVabW9v/9vaU8zGf1dIpVKJRDLTzfK/Ltra2qytrVEo1MTEhFQqRfoZA58EYKCrq8vS0vLKlStr1qyprq4OCAiQyWRmZmZ/DWCampq6evVqW1ubp6cnh8MB33SNRoOAmI6Ojt7e3rS0ND6fHxAQAIv4c+fOWVpaUqnU4eHh8fHxtWvXMpnMc+fOCYVCfX39jIyMjo6OnTt3SqXSxMRECwsLCoVSVFREIBBeeeUVLy8vAoGQnp6enp5uYmLi7+9fVlaGxWLb29uJRGJCQkJISAgsbR89enT+/Hkul6uvr5+bmxseHr527VqlUllaWvrkyROVSqXVau/fv29pafnmm28CDtWNiYmJzMzMrq4uCoVSVVU1MTGxYcOGJUuWGBgYDA8PP3jw4MmTJ9Ams7S0VKlUvvLKK76+vkqlUi6XA4qqq6trbGxEJFnQJFJfX7+7u1uj0QD4q6ysbGtrg9klMjIS2gbduXNnZGQEvmVnZ+fs7Ayjm0qlysnJkUgk8JaTk5ODgwOBQKipqWlubgaH+9LS0oGBAY1GExYWhozUEKOjo0VFReBIoaen5+vry+Fw2tvba2trARAEBARA89H79+/39/er1WoCgRAREQFTSE9PT0VFBQqFCg0NbW1tBRMRDw8PJpMpFArHxsYQjRqXy+Vyuf+G208ikfyxuiVQX8E2aTQah8OxsLCAdfnsOPsigCkyMrK4uPj+/fu/+mEsFmtmZkahUOAh+quOuaGhITk5ed++fRYWFv39/X9st5xLly7h8fhVq1YhZJtKpfpLlHYymSw7O7unpwfkpLpviUSi3bt3T05OXrx48b9CR9zR0fHo0aPo6Ggqlfp/Cd6NjIzk5eWp1erFixe/YPvF3xBFRUUgFI6KijI3N/+vPoG1tbXW1tawGBCJRMbGxvA6ZOIcHBxkMtmjR48sLS0BQtnY2BCJxO7ubj09vb8GMI2Pj1+/ft3R0dHPzw8aMULr7IcPH4LlKJfLXblyZWFhIfKVzMxMU1NTkPjU1NQgi1ELCws6nQ6SETs7OxKJlJeXR6FQfH19GQzG+Pj4iRMn3N3dHR0dCQQCl8ttbm4uLCwkEon29vYsFsvCwuLkyZO5ubmenp4EAuHRo0eHDx92dnYOCgrS19dvbm4eHBxUKBStra1Hjx6Nj4/39vbG4/EymezmzZt8Pn/evHnQIHoavODz+R4eHjQaLTk5+fjx4ygUasmSJT09PceOHZs/f35AQAB00Pzmm2/s7OwcHBxOnTp19+7d0dHRxMTE4eFhd3d3mUyWlZU1f/58wGSjo6NHjx51cXFZtGgRmMEPDw9fvHjR19c3JCRErVZnZGTcvHkzJCSETqf39PT8/PPPr7/+upeXFxqNvnbtWk5OTlBQEI1Ga21tzc7O3rlzJx6PP3r0aGlpKZPJ9PHxaWpqsrCwePjwYVVVFQBB3UcCjUZnZWUJhUJ3d3ekcODWrVsjIyOLFi0CrrKoqKinpweHw6HR6Bs3bgwMDEB77RMnTty5cwc60icnJ7e3t7/zzjsqlcrOzo5AIKhUKoVCAZcyMTFxYGBg8eLF0Cxaq9UqlcqysrKHDx9KpVKVShUfHw+N0MfGxs6fPy+RSGDXwcHBvr6+JBJJrVZfvHixv79fq9VqtVoXF5eoqCigJyHUajWUEUBz+Fu3bgGwa2lpSU9Pl0qlKBRKrVbHx8cDDavVamtrazMzM7FYLGjsCAQC9HVCttnb21tQUCCVShUKRXFxsbGxMZVK5XA40BhSoVD8/zbXGIxu+S5yJPAvXNNpw9C0z4CLJvxkAO7TXoczBtkTaH2VkpISGRkJvWDhK7dv346Ojtb1/oetZWZm1tfXu7q6hoSEwIwyc0xUqVSwWXjcEBsYlUql0Wie2qMAmemxWCzSbxUJ5Ieg0einoh+lUgmrCOQ3AulraGjo4uLyLCZSd7O6XjXI+YFb+qk2Nsh3dfc4M4qLizs6OpydnU1NTe3s7P5w8jU8PBxJOOJwuF27djEYjH9/sfCpU6fq6+s3b95MJBJpNJouLiSTySQSSV9fHzkq6Pa1ZMkSBweHPy9B+Zujqqpq//79fD4fqSv6vxEoFKq0tDQrKysqKupPIiBVKtWVK1dCQ0M7Ojra2tpYLNZ/9Ql0dXWFP2g0Gty9SqVSdzTA4XDQ0tje3j41NXXx4sVKpdLExESlUv01gOn06dMajWbRokWQgAN2wcLC4vbt2yD6NjMzgxkL+Up/f79EIvH29ra3tzc1NXVycuJyuSQSacGCBbdv3x4aGvL397exsaHRaP7+/mFhYWw2G9qPnz59enR0FEbtgIAAY2NjIyOj2NhYT09PMpksl8tv3rw5NDSkVCo7OzsPHDhgZWW1YsUKGxsbNBq9bNmyjo4OtVp94sQJuVzu6urq5uaGw+H09fV/+umn+vr6uXPnTgNMdDp92bJloaGhRkZGgYGBgYGBCQkJJSUlUVFRx44dk0gksBECgcBisQ4dOjQ8PKzRaAQCQUNDQ2Njo4+PD41Gs7Oza25uvnHjRkFBQXx8PIFAGBoaunPnTnZ2tqurq7u7u62tbWNjI4vFmj9/PrhEHDx4cN26dQDg6uvrb9y4cf/+fQcHh6Kioh9//DEhISE0NBQIp9OnT/v6+s6bN2/p0qUlJSUymczV1TUwMBBuiJSUFCqVum3bNgaDAb+IQqH4+/tTqdQNGzagUCjouG5hYSGTyWg0WmBgIJPJzM3NvXjx4rp16yChhsfjDx48qK+vHxMTExERUVtbW1JSUllZGRMTc/36dbFYfOfOndLSUolEkpubOzQ05OvrK5VKf/7558ePHzs4ODg4OODx+La2thMnTvB4PBcXl56entOnTw8ODu7Zs0etVh85ckQikQDWKSsr+/rrr7/++msLC4uLFy+y2Wxvb280Gt3b21tZWRkcHKwLmCorKwsLC0dGRioqKo4fPw5gSyQS7d+/n81m+/r6EonEoqKivXv3Wltbb9myhclkJicn37p1a2JiQiAQiESiycnJ+Ph4XcB0/fr1+vp6pVJ57tw5uVy+cuVKFoslFostLS1zc3MrKyuJRGJLS8ucOXPWrl1rbGyMRqOVSmVGRkZpaam+vj4Gg+nt7V20aNE0CfPU1FRycnJdXR2JRIJnZGpq6q233jI0NGxpaTl//jyBQMBisWKxeGRk5MCBAyYmJnK5/NChQzU1NVgsNjY2trOzs7S09MaNG+Hh4TY2NtnZ2XQ6XSgU1tfXb9q0CUhBPT29wsLCjIwMDw8Pc3PzCxcunDt37siRI4itMOA2+IFpaWkbN25MS0srKSnhcDhbt25lsVgtLS1ZWVltbW1r1qyBLCdsViaTtba2VlRU9Pf3P3nyZM6cOZ6entC0HDbb3t5eXV19//79gYEBY2NjsVg8TZPU19d35MgROEUikSghIcHBwQGLxfb19YlEopaWlpkpuYGBgb6+vu7u7hs3bshkMg6H89prr3G5XAwGA+088/PzFQqFSqUik8kJCQnTJPk9PT1dXV0ZGRltbW10On3dunWOjo4MBmNmXffQ0NDExIQuyOvv7x8cHHR0dBwYGBgYGKBSqZaWllgsdmRkpLu7W61WMxgMDoczE0nU1tYCnQwQEIVCdXV1TaNzEOCouzBDPsZms3VZ4aGhoZ6eHgcHB5A9EAiE31xFkZqaamRk5OjoOLN2gcFgfPTRR1gsFrpM6OnpicXikydPuru729nZ/QcCJjQavWDBAt0Wtv83gkKh0On0hoaGP4mDlEqlly5dEgqFu3fvbmtrm5iY+G8/Y0Av6f2zCYxKpUpOTl65cmVzc7OtrS30jIPEFw6H4/F4MMivXbv2LzOuLC8vl0gkM3MWFArlWe6l3t7e+/fvb2xsjI6OtrW1dXZ2xv8zCAQCHo9nMBggSXF2di4oKCgpKdFoNHZ2digUqqqqamhoiE6nk8lkoPSdnJxgSoBXEG5TKBRGRUWZmZnBA+/m5gaw7PHjxyMjIz///HNjYyMWi5VIJMPDw1NTUzOXxRQKhc/nQ70ekUgMDAykUChTU1MajebRo0d9fX2ZmZmdnZ04HE6tVjs6OpLJZAwGA3QLj8cTCASWlpZ6enrGxsYBAQF3796FpjlCodDX1/fevXt5eXlcLpfBYBQXFwcHB3t5eU1NTaWnpwuFwoMHD0JPbDabbWhoePny5YCAgNTU1MbGxjlz5lhYWADfyOFwrl27Nn/+/Ojo6IMHD1Kp1ODgYHiXwWDcv3+/pqZGJpMhgAmLxRoaGgLx0N3dPTAwYGZmRiKRSCTSSy+9ZGNjo9Vqjx07JhaLaTQak8nE4XCBgYF/+9vfWlpaIBOXnZ1dU1Pj4+Mzd+5cHo9HJBI1Gs3U1BSBQLCxsfHz87OxsVEoFEuXLn306JFcLoezmpSUpNVq/f39nZ2dJyYmHj9+7OjoODQ0dOnSpZs3b37//fehoaEEAkEikRw+fHh4eHhgYOCnn35KTEz09vbGYrG9vb36+vrTciVmZmY+Pj4kEonFYkFu0cDA4Pvvv29paUlISPDy8oIn5MiRI1evXuXxeMuWLZs3b15DQ0NJScm8efNMTU1LSkqmqZKDgoK6u7vb2to8PDysrKwcHR3Hx8cVCkVycvKCBQtMTEzs7e0rKyt//PHHOXPmMBgMPB6fk5OTlJTk6+vr7u6Ox+N//PHHb7/9Vq1Wh4WFIZhJLBYfO3YsODiYz+fDi99//z04VqSmporF4kWLFlGpVKFQmJ2dfffuXaAeeTxecnJyS0uLt7e3l5eXk5PTkSNHDh8+vGTJEhqN5uPjY2Nj8+WXXzo7O8fFxWEwmJKSkuPHjzs5OQUHB9NoNLlc/u233+bl5S1duhT5mRqNRigUlpSUpKWl0Wg0sVisUCguXLgwOTnp4OAgFApJJNLo6Oinn366ffv2BQsWwBeTk5NLSkoEAoGPj09DQ8O1a9du3bq1Y8cOf39/PB5fV1f33XffcTgcMzMztVrd3t5eXl6uK/nq7u6+d++eQqGAXPnbb789Ojr67rvvws0wOTkJuftpT19BQQE8oUAvXbp0ydraetOmTfr6+tnZ2bdu3dq6dSuFQhkbG7t169ZMI5KbN29isVg2m93X1zc0NPTJJ5/s2rUrMjJy2l2UnJz8+PFjpVJ58+ZNOp0eHBxcWlr64MGDlpaWL7/88vz58zU1Ndu2bWOz2Xl5eWKxuLi4uLm5mcvlBgcHL168GDqPjo6O5uTkKBSKrKwsBoNRV1cHiLChoUEmk9XV1V29epXD4RgZGdXV1V28eHHVqlVr1qyBO2FqaiorK2t8fFyr1XZ1daHRaDc3t0WLFoHqoKys7P79+4cOHUpOTi4sLDQwMIiNjQ0PD38qXANAfOvWLblcjsPhIK2jm7wGB7+n5kbd3d2Li4thdQ7bGRoamqbbq66urq2tVavV7u7uzs7OTz2AsrIy6IRaWloKa2BA1U1NTRUVFbGxsbqdzhCUWV1dbWRkFBoaikDwnJwcHA4XHByMDOmZmZlUKtXf3x+LxXp7e3t7e/+G5vb/4YHFYmFNePfu3fj4+D8cqvb29v7jH/9Yt26d7iLq/1Kg0WgnJye432xtbbu7u4lEIpSR2dvbAx0FRk22trZ/DWAC/kAoFHp7e8MQAInYwcHBZyk/YmJiFApFTk5Oamqqnp6epaXl7t27fXx8ppGQarU6Pz//7NmzISEhRkZGNBotNDRUrVb/tvoOGo1Go9EAU3O5XFNTU3h0cTjczp07Yep9keuBoEALCwtzc3MymQzpiddff51EIpHJ5MnJSQwGo+smZWRkBGpokDcVFBSsXr1aqVTm5eXFx8eTyeSxsTEfHx8KhdLR0VFaWjo5OXn69Glzc3M9Pb3h4eG2tjY+nz80NFRWViaRSE6cOAGZWphpBgYGnqpH5vF4z+Grly1bdu7cubq6Ont7+9LSUg8PDy8vLyKRODk52dzcPDo6evbs2dzcXDQa/f/7FOosagkEgrW1NYFAgLoDOC1kMtnR0TEkJATWrwqFAoELxcXFP//884EDB5ydnXE4HIPBWLNmjYWFRXt7+61bt4KCghwdHdVqtVQqBe1XWlpafHy8mZnZ6dOnW1pagGnz9/efdoHYbDYYVVhYWAQFBRkZGd27dy8jI4PJZLLZbBh5uVzuyy+/fO3atf7+fjQa7e/vn5ycXF1d7e/vb2VlZW9vP62M0cfHp6KiAofD+fr6Ojk5QTqMw+E8evRIIBB4eHgYGhqOjo6+/fbb58+fd3FxYTKZN27cmJiYiIuLg+qqqampnTt3ZmVl+fn5IWdAKpV2dHSsXr3a29ubSqXi8fjR0VGQhfF4PD6f7+/vD3+np6dnZWWFh4cbGxvPmzfv7t27QLh6eXlptdrOzs6PPvrIxcUlODiYzWZ3dnbCrQJ4MSMjo7m5+e233zY0NMRgMDExMSkpKWlpaVFRUcipw2Awvr6+JSUlk5OTxsbG4eHharX66NGjt2/fNjEx2bhxY1BQ0NDQ0Msvv3zixIk5c+ZYWVmpVKoLFy7Q6XTYi5eXF41G27179507d9zd3fv7+/fv30+hUObPn29lZSWTyTo7O7/++uuysjLY4+Tk5IEDBzgczoYNG5ycnLBY7IYNG7799tvw8HA7OzvowdnR0TGTYRKLxWZmZt7e3osWLVKpVHl5eT09PbDy7uzstLCw8PX1NTY2Br525n3e0dERGxvr7u4eERHR3Ny8fv16kUg0sxZvcHCwtLQUblcikYjBYIhEYk9PT35+fkpKipWV1Z07d+rr6yMjI2/evBkbGysQCLhcbktLy6FDh/z9/aGGGTK5QUFBwcHBxsbGRUVFt27d2rVrF7Sax2KxRCIRj8cDX/vgwQN/f384EoVCcfLkycbGRgCCPT09Z8+ezc7OnpqaWrlyJYFAGB4eLioqunDhAo/Hi4iIGBwc/P777xkMBovFmpYVVavVv/zyS1lZma2tLZFIvHr1anl5eWRkpEAgwOPxubm5YrFYKpXu37+fyWQmJCToMqBHjhwRiUSlpaVnz54lkUhyufzChQtA2FdVVQUGBoaGhv7jH/9gMBjGxsY9PT1ZWVl79uzh8Xi6dN3p06d7e3tLS0t37959+fLl0tJSIpE4MTERGxt76tSpurq6qqqqhw8fhoWFxcTEwON58eLFzs7OxsbG+vp6Eokkk8nmzZuHx+MLCgoOHjwol8vff//9sLAwHA6nVCpBjert7a1SqQwMDDIyMsLDww0NDUGSVVFRQafTSSTShQsXlEoli8WCU9rc3JyUlKRUKnft2kUmk2Fxq1Ao5HJ5VlbW8uXLcTgcaAnGx8cLCwsXL14MT7Gent7Vq1dXrVoF52dsbGzx4sV8Pl+j0Vy5cqWxsdHX1zcsLAwmEd0L0drampSUtHjx4lu3bkVFRfn5+TU3N1+7dk0ul5NIpPnz53t6eioUivT09KqqKpgfZwondGG9QqGATuHIB576CvIEEQiEmRlzhLA0MTFZtmyZSCSSyWSIfdF/e1y8ePGll15CoVBoNNrd3R34EVAsAceBxWInJydzc3OXLFlSXV3t6enZ3Nz81wCm9evXP3jwoL6+fnR0lEajodHo2trawsJChULx1FLhwcFBsVgcFxcXGBgIcuPExMS2tjaQck9beRw8eDAgICAiIoLBYMjl8p6eHj6fD2VoL3JsnZ2dU1NTM2tezMzMYMpEHngYLn91a5ABhCSOsbGxn58fUoQM6TzgySBFojvBL126NDc3Nzk52cjIaGBgwNra2t3dvaqqqqOjIzc3Ny4uDgQ9FAqFy+VWVla6ubkBo6ZSqYKCgpycnCYmJnA4HAaDAfIDYUS0Wu3MrtG/GgsXLszIyDhy5Iinpyc02dHNdvn7+yPyc41Gw+fzgT97zgYdHR15PN5TlRlVVVW9vb3GxsbIu3PmzMFisXDPSCSS8+fPwwDR29trZ2fn6enp7OwcHh6em5tbVlZ2/fp1sBLdsGHDsxbWEEKhsLe3F6HTIMzNzZ+lFwFI+qsk9sDAQGRkpIeHB0jQQDCHHHBTUxMOh+vo6AAlfm9vr0ajmVZqRCQSIUeWl5fH5/MFAgFyVD4+Pl1dXUKh8OHDh1NTU319fSC9QtIx0dHRNjY2AFhNTU2xWCyXy2Wz2ZBACQwMrK+vh/FdJBKNjIykpqbm5+cjQ6e+vv40BZudnZ2xsTEej58zZw64uoWHhycnJ7/66qvLly9nMpkymWz9+vU//fTTyMiIpaUlAOuNGzdCPovBYCxevPjMmTM3b96MiIjA4/F5eXlffPGFq6sr3PDm5uaenp6VlZXIU5yamhoXFzcyMvL48WP4FVCko9VqR0ZGxsbGwsPDZ16j6OhoCoUiEokmJiZmet5WVVV98803S5YsweFw69atm3lzrl+/ns1m9/T0qFSqpzJYyF4ePHjQ398fFBRkYmJCJpODg4OLiorweLyvr6+np6ejoyOTyYTqVx8fHyqVqlAobty4ce3aNcTVFtqpAnELkCgkJMTW1tba2hr6t4eEhNBoNCwWa2RkpPtLb9y4ce7cuS+//NLd3R2Hw9nY2BgYGKxfvz4lJUUgEHh7ezc1NWEwGC8vLzhFra2tmZmZBw4cCA4OntZjtaGh4fPPP1+2bFlISAiBQCCRSN98801BQcGpU6dA80Amk5lMpq+vLyTidb9rZWV18eJFoVAIlHBWVlZ1dTUUzXE4HLFY3NjYWFRU9Nlnn1lbW4+OjtbU1AwNDVlbW+sCJjc3t76+vsLCQmdn53nz5oWGhj558uTgwYPl5eUjIyOLFy+eP3/+Bx98MDIy4uPjY2ZmhkKhsrKyVq1a5eHhIZVKv/nmm71793I4HHd3dw6Hs2nTpi+//HLPnj1nz541MTH56aefIiIiINF59uzZpqamzMxMT09PBoORm5tbXl5+586dxYsXT05OPnz4UK1Wt7W1jY+Ph4WFZWRkPHr0SK1Wb926dfny5cuXL+/q6rp165ZQKFSr1UuXLoWzmpaW9ujRIyqVGhsbK5VKT58+3dzcXF5eTiaTOzs7i4qKuru7i4qK9uzZMzY2lpOTIxaLKysrz58/f/bs2Wn3Hp1O7+rqeuedd9BoNMzikHl/8ODB4cOHzczMhoeHP//8c4lEIhKJtFpte3v70NDQ4cOHdUGSu7s7Go1uamoaGxt78OBBaGioq6srCoVqaGgYHx+/d+9ebGwsTBBKpVIoFDY2Nvb29sKaavny5aGhoU+dIg8cOODi4sLlcnNzc2EZ/3+DWALSSDcgtwMjtomJCXh52Nra6v3TFpzH4/01gCkgIEAgEJSUlJw5cwYUBhMTE5aWlpOTk9OmjbKysqVLl8rl8jNnzrz++usgADI1NT1z5sxTy2TEYjHYE1CpVENDw5s3b1ZWVmKx2NHRUSaT+Xy60tDQ0NnZOT09ncfjLV++HCESsFisj49PcXHx4OCgq6vr84V14+PjlZWVHA6HTCaDVNzFxcXb25tEIvn7++fk5Ny8efNvf/sb8D1isXhoaMjGxmZ0dLSjo6O9vV3XJdzFxUVfXx8Ux6+88gqDwYiLi7tx48bJkye7u7u/++47wFsEAoHBYAANACpvZAtjY2MhISE9PT2Q2PqdV83BwSEyMvL48eP19fWTk5M8Hk/3VCiVShcXF0dHxxfkhIuKijo6OoaHh5+aepfL5dMqzGFmhXtjamrKw8MDERItX77c3d3dwMBgxYoV7u7uGRkZExMTo6Oj58+fB1nuc4hAGxubaVWBf4hGUiaTgYQFSdQymUxYG9y5cwdgdG1tLdxjTCZz7dq1cXFxukr4Wf0XAAAgAElEQVQRExOTN954o6ioqL+//8yZMxkZGWZmZm+++WZQUFBaWlpjYyPQxTgcLj09HTl+Op1uZmaGVFDODBwOZ2RkZGxsjBwbmUz29vZGHBYCAgKoVOpTzcBQKBSQo/AtFAoVEBAAkIhMJru7u4PEW6vVVlRUkMnkmJgY5MxTKJSNGzfu2LGjv7+fxWJNTU0hm4KjAmYFkTdJJJK+vj5w6oIrvmzZMlATy+VyuVyO5M2naX3u3r2bmZkJiT9/f3/kFnV3d+/o6Lhy5UpxcTGFQomPj6dSqY6Ojro8qEKhyM7OBvK1r6/vWbYFXC7X2dkZi8XS6XTIWAHawOFwHh4eJiYmERER8MnNmzdPTk7evXtXqVQ+fvwY2WBxcbFQKIS5EA5g8+bNNjY2MPqh0WgSiQSN0xHMiuy9pqZGLBZD+hh27efnR6VSi4uLHz16FBcXB5fGy8sLBHN4PH7BggVHjx6d1oFAo9Fcv359ampKIBCYmJhgMJjo6OiGhoZPPvkExig7OzsKhWJiYhIaGjpTwxQeHn7//n0E49rb269du7a0tNTNzW3u3LlSqfTw4cO9vb1KpZJOpzOZzLi4OCMjo2lTsq+vb3t7u0ql8vDwAA6pubn5gw8+iIqKSkhI8PHxwWKxGRkZ+fn5tbW1cNP6+PhERETAfTUwMLBr1y5oQsrj8aysrDo7Oz/55JOkpCQMBlNdXX3gwAEul4tGoz09Pdvb2xsbG+ES2NraDg8Pl5eXDw4O7t+/Pzw8HFLeJ06cmJycDAsLi4qK0mg0CxcudHJyWrZsGZ1O9/PzO3fuHJfLhUnHyMjI398/MTFxzpw5cBV8fX3v3r1bV1dXVFS0ZMkSPz+/+vr6AwcOfPvttxs2bNiyZQsKhbpy5crJkydnPptGRkbR0dE7duzg8/lQBWViYsJgMIKCgsLDw8Eop6ura8eOHXDRv/jii8LCwmkjJyzy29vbKyoqTp065ejoCOmklpaWioqKn376yd/fHwoUUlNTU1NT4SBRKFRxcfHnn3+ORqMFAsHMkbCmpuajjz568OCBRCKJiYn58wrxIHJzc3t7e3/1Y5aWls9CeC8YcOH09PSys7Ojo6NhU93d3RKJxNnZub+/XyaTOTg4wDkcGBiAGfmvAUz6+vqvvvoqn8/PycnJysoKDg5eunSpo6PjlStXMjMz2Wx2dXV1ZWUl2GtmZ2dHRkaOjIwkJSWtX7/eyMgoKyvL1dXV0dER8DWRSOzo6Ni/f7+1tXV4eHhwcPCdO3fGx8eNjY25XC4sBzs7O9lstlarBZaioqLC0NAQVtJEIrG6ulooFAYEBOzYsePr/8fee8dFdW3t49MZpgPD0DsMfYY69KIIqKCCgBpbrNeSorkxNzfeN9FrcmNiEhvGrjE2imJBBZVqBFFEpUjvMDD0MgMzw9TfH+v3ns98ByTGJK/vvS/rDz84c2afc/bZZ+9nr/WsZ33zzcmTJ589e5aUlFRWVubm5hYUFDRv3rzi4uKTJ0/ev38f4mskEiksLMzX11eT9A1pX2fOnCkpKSGRSAMDAzo6OkuXLoVZdePGjRKJJC8vb2xsDJiSUqnU2dnZxMQEi8USCITGxsbBwUGgq8PATUhI2Lt3r6enZ0BAAJlMptFoZDIZHjDCRSWTyba2tiQS6cqVK0wm08TEBBx1RCKRRqMBHs3IyKBSqXQ6nUgkTkxMEIlEHA43OVV4eqNSqZBgmZOTs3jxYiMjI1ix8Hh8XFxcenp6fX29kZERhUKBRCqglykUiimhLRCJXoViYV5IS0vbvHmzJqBxcHDw8/Pr6Ohgs9laFbYrKyuVSmVISIiTk5NcLm9ubt6yZQvC958Gu1tZWcnlckhng9dGIpFgMJhpkqRex8OkUCiQuOfY2NjAwADQex0cHPT09JhMpr+/P8AUQ0NDX19fcAVpepiio6MDAgKGh4dLSkqkUunRo0cfPXrk4uJy4cIFZ2dnX19fLperVqsZDAayEg8NDQkEAgcHh1cluovF4rq6OisrK8SNRCQSPTw8rK2t/9h5cGxsrL6+nsvlIt6R58+fwwv4qycC16m1tXVgYCDyfkVGRoL0GoTk6uvrtRYepVJZXFz8008/LVmyJDQ0FIvFXr9+HRl4ISEhjo6OXC53YmLi0qVLBw4cwGKxdnZ2SJ+Xl5d/8803Mpls165dkE/6O7PSpFJpXl6eVCq1sbHR1dXV9EZnZ2fz+XxIS4QLABbFr1pjY2NZWdmUaNjU1NTMzGzygkehULT8OghgunbtWkhIiKWlJXyLw+FAiyQjI+PDDz/USmfRMjKZbGNjg7y84M+G/wKXkcfjpaenf/31105OTvb29uHh4dPwh1xdXTWvkM1me3t7Q88sWbLk6tWrg4OD8Cjnz5/f0tJy/fp1NBrd2tqqGZHA4XDx8fGFhYUpKSk2Njbvv/8+OKVQKJS3t3dNTQ1yCkdHR6VSicViPTw8ILMYpG2ys7NNTEyCg4MJBIJKpULuTl9fH0h+yLmYTGZwcDCCI4lEYnBw8M8//0wmkyMiIkJDQ4Hjdfv27ZaWloCAAIBBpaWlr9qbhYeH29vbQ+yPQCDAtLl06VLoBAaDsWXLFj8/P7hffX39yagiJSVl69atrq6uQ0NDkAOPbBV6e3vBmYREoyQSSVBQEEgQSSSS9evX37lzJygoSOvyLl26RCKReDzesWPHNm/eDJVD/mxs8KvSzZcuXfr444//qDPCtiQ/Px9ySmCLhcPhCAQCEpKDdyEzM/PtACZI0nZxceFwOENDQ9bW1nCtenp6sPW0srKiUqkRERFkMlksFhsbG7u5uVVUVJw/f55EInE4nPnz58OsikKh1qxZMzIy0tra6uXlZWtru2PHjkOHDrW1tZmYmAQGBpqYmDg4OLS2tlIolIqKipiYGD6f39bWNjIyAnqSW7ZsqaioaGxs9Pb2DgwM3LNnzw8//NDQ0HD9+nVYgHV0dMLCwg4ePHjz5k2QyyORSMuWLbOwsNCaUpOSknx8fGprayH/HHLxECVrV1fXHTt2NDY2pqamtra2YrHY5cuXc7lcEomEwWB8fHzy8vK+//77jRs3BgcHwxYqLCzs5MmTQUFBRkZGMJTXrVvX3d0dGhqKbNd0dHTi4uLa2toyMzMrKyvj4uIeP34M4lKurq5z586tqKhITU19/PgxjUYLDg7u7u5euXIlk8ksKiqCbfTz58+pVCqVSoVTDA4OQtx6cmbNrFmzuFxuc3MzICcE3MTExIB448WLFwMCAgQCAfAx3d3dgZI8MjJSUVFBJpORZp2dnUUi0bNnz4DxY2FhoanbGRUVVV5enpqaCtJQPB5vaGior6/P3t4+MjLyu+++O3z48OLFizkcDojEODs7NzU1NTc3m5qagihZQ0NDYGAgQpJDrKmpSZPtq6+v7+7unpGRcf78+Y0bNxobG3d3dycnJwcHB8+ZMweHw7148aK7u/t1kCXISkE9REtLSz09PaQD9fT0zM3Nwefk4+NjZGSkUCioVKrmgq1lAoHg4cOHsbGxNjY2jo6OarW6oKAgMDDw0aNHzc3NPB7P3t5eKpVeunSpuroaUjlgYjUyMprGwwRp80DcVqvVNjY2OTk5J0+e3LJlCwSFGxsbAdX9Hm0ha2trqVT69OlTZK5BoVB5eXlBQUEcDmdgYADWfrlcDtPTyMhIT08P0slQMFwikZiamrJYLK05urm5ua2tbe3atVpPtrW19fz58yEhIUuXLjUyMlIqlQ0NDR4eHtB+W1ubnZ3dmjVrYL1ct24dJKhqDozi4uI9e/a4u7uDRMXvlIBPT08/fvz4okWLVqxYAdsnpEESiSQUCktLS+Pi4n5TKrienp6xsXF1dfXkr+zt7ZH0NK0U41dZd3c3g8HQjMBaWlq6ubkB6fN3TvLz5s3r6+u7efNmRUVFZmYm8K+PHz/+W4sFmZmZIRcjEAjOnj0LAAUYiloLvJWV1fr167dt2yYWi52cnDTdllNaREQEMj7Nzc3RaDSMPeRXXV1dQqFwsm/sVaajo4NcMIPBoFKpRCIRXH3T/9DQ0HDnzp2bN2/OyclZtGjRs2fPWlpa7OzsoCkCgUAkEr/77jtY0RsaGiZvQZ2dnTEYjLm5OWR4aTpj4NYQlgjsbBsaGlpaWmACx2Awvb29U/p7Ojo6Dh065Ofnh0wyf6qBo3r6YxgMBvCN/hCDKcLS0pJCoZBIJKBnGBoaQg9DSA7eprcWkoOHhMfjw8LCpvSSTZY2Wbx4cXBwMEypXC5Xk2Pk7++/c+dOyNnR19c3NDTcsWPH8PCwmZkZTLje3t4g8I3H483NzWUyGaTEwxiaP3++v7+/SCSiUqng34bWwKcCOraGhoZz5861traGSRaPx7u5uU3mQLi7u7u7uwcEBMyaNQuLxTo7O2vu0nA4nLOzs5OTk4WFxfj4OBqNBmkD+Hbu3Ll9fX0ymczU1BSZWJlM5tq1a8PCwhCxtfDw8NHR0bCwMM3MERsbmw8++EBXV7evrw/cWjY2NuCCcnBw2L59O4PBGBoawmKxQ0NDFhYWdDpdLBZTKJS4uDi5XN7V1TU2NgZdOn/+/JGRkclpzAgrPCkpaXBwUDPXGo1Gu7u7f/HFF1lZWXw+H4hTXl5eFhYWarV6cHDQ19cXjUb39vYODAwgLAoSidTb23vixImCgoIPPvigubn51KlTIyMjDx8+BDowaJBevnw5JycnMTGxra3N3NzcysoqJiams7MzNTW1rKwMOK1cLtfS0lImk2VkZECwBojnMTExWoiktrb24MGDLi4ubW1tKSkpq1atotPpq1at6uzsvHz5skwmAwc+Ho/fsmULh8MRCoWXLl3i8/menp63b98OCwtzdHSc7HiA3MMDBw5wOJyPPvpIoVB0dXW1tLQg+A8U0iCzkslkzpo169SpU0ePHuVyuYBLyGRyTEyM5loiEolu3Ljh4ODA5XIFAgEgS0jBw+Px1dXVFy9eJJFI/f39aDRaIBDU1NRQKJS8vLy+vr6nT58WFhYuXLiwoKCgoKAA8iglEgkkENFotNHR0YyMDCBHNzc3p6WlgTIWDocrLCyMiYkBJs0bv90JCQlnzpypqqpqbW11d3fH4XAPHjxQqVTx8fGAGjkcTkpKiq6ubmBgYH9/f29vb3d3NzLkoDJjXl6era3t5s2bKRSKSCSqrq4GzmJPT09fX19vb68WisVisTo6OmKxODMzE4/Hh4aGQnxcIBAQicTU1NTly5dzOBwcDhccHGxnZ8dmszXHBngZx8bGGhoaKisrIf3z90xxL1++FAqFCxYsYLFYEomkqqoKQbGJiYknT56sqKhobW19Ve7YlMZkMmEGKyoqiomJ0XxGQIUUCoVPnjzRJP8hDowpA9MVFRU9PT0w7BHkCtzz6a9keHj46dOn06xtVCp15cqV3t7eExMTsGFrb2//VSX36e3Bgwfnzp07c+aMs7OzlZWVjo6OVtcJBAKRSDR//vzMzMxjx4599tlnkwG3lj/jVWRnsP7+frFYDNTM1wzHj4yMvNndBQUF9ff3p6SkeHl5Xb58GegEcN7R0dEvv/ySwWCsXbuWTqfn5+dr+pCQhf91LvLWrVtdXV1EIrGmpgbpvQULFnh6ek7+OUjT2djYxMTEvLHH/TfZ6+DpWbNm/eFnBGAEjnA7OzuRSCSRSJydnSEkB3u8txaSewOzs7N7FcIFhqMW1tYMDyNMrikJa2QyWQv6aLWmGSl4nUs1NDRExEOnJIJM2b65ufnatWvVarXmZEehUBITE4H7iYDrxYsXa36C7C+3bt2KrNB0Oh3ynoDd9sEHHyBuFT09PfDkMRgMR0dH+AmkOqNQqBUrVkgkkmn4XjExMQqFQtM7DVfl6+trZmYGVFkQagLH8ty5cxFKh2azLBZr586do6OjNBoN9ALi4+MhdR9icM7Ozh999NHjx4+lUinIkzo6OpJIJH19/Y0bN1paWo6NjYE4pIuLC4PB8PDwWL16tb6+Psz1Pj4+LBZLK6ygo6Pj7++/bNmyrq4uEHSA1+Djjz9+/Pixnp4eiURisViQ1gTEmvDwcF9fXwsLi6GhoVdtWD09Pf/xj390dnZaWloaGRmlp6dbW1szmcycnJykpCQqlWpoaOji4qKnp1dYWBgXF7ds2TIGg/HkyZPz58/DkrNp0yatNjEYTEdHx9GjR62srPh8vp2d3TvvvEOj0UxNTXft2vX06dOJiQk7O7vAwEB4vWEXq6enFx8fHxERAdEZGo0GB5iYmMAOgUwmr1y5cmJigkwmUygUNpu9bds2yGLLzc2NiooKDAz08PDQXInT09Obm5tLS0vRaPSPP/44f/58cMYQCISUlJQHDx5ERkZ6e3sTCAQ6nf7zzz93dXVFR0dv2rTpp59+OnLkiKWlJRaLff78+YYNG6KiomAL/umnn3755ZcXL1588uSJSCRav369vb19RUVFcnJyTEyMj4/Pxx9/vG/fvmvXro2MjBCJRLFYTCQSIRxZUFBAJBLT09MHBgYSEhIQBUsTExOgoj9+/Njf3z80NBT0aX788celS5eWl5ePjY2ZmpoCMvjwww8DAwM1UYWHh0dwcHBmZubLly/t7Ozs7e0ZDMb9+/cnJibeffddZCCNjY21trbm5uZOTEyMjIzQaDQikSgUCiUSiUqlGhkZwePxVCoVh8Pp6uqC8mpjY2NPTw+Qk4RC4fj4uL29/ZYtW44fP75nz56vv/5aX1//5s2biYmJyL6osLDws88+8/LyWrRoEbQskUigK+bNm3f//v3bt2/7+PjAxJWTk4PFYhctWqRUKkUiEXjv+vr6QEgFkkmFQuHw8DBITSJF2levXp2amlpTUwMBI6i1MDw8DAyt6Wc5LBZLIpEWLlyolVc7NjYml8sVCgWkffn7+6vVagsLi/37978xkkCsq6trZGTExcUFCK8grKAJbv71r385Oztv2bIFg8HcuHEDhUJ98803v6dCs6WlJbK1plAotbW1RUVFs2fPxmKxYrF4suNZV1f3jfPIdHR0Vq1adfPmzaqqqubm5l27diHj4ciRI0NDQ1Ahh0AgsFgsPp8/fWtanYOYm5sbnU43NDQMDg5Gxn9oaCiVStWa86VSqUwm2759++rVq5lMJnJTcrn87t27ZmZmV65cwWAwSUlJKBQqIyNDoVB8+umndDpdrVbD1reystLMzGzZsmUymezgwYNhYWEhISFYLDYlJWV0dHTTpk2THW8pKSktLS2/uldxdHRMSEh4fe5pWlpaXFycJkNarVaPjY0hoxdCcpDDDm48tVqNhORAuumtheRmbEqbnLmGw+G0ElsIBMKrKqAByX+yYTAYJEVOK3CrhXsAt01/kdOUQZicQQb5Wa9yqy5btgyIAiQSydjYmM1mI6LYAE24XC6bzUYcDyQSCeZxKyurFStWwOcAazAYjJ2dnZmZGXIwaItrzVzm5uYJCQlA5FKr1bDnBk6oo6Mj/FZHRwchNpJIpDlz5gDzRiqVEgiEKXEknU6PiYmRy+V4PF5HRyc4ODggIIBOp4tEIkAepqamf/vb3yC+DOycVatWBQQEgKQhwDstB4CJicmuXbvUajUkSNva2pqYmMCyvWzZMuC0MZlMiF8rFApwMAQEBCDdgsfjPT09ORwO9Cp8gsPh5s6dC8cQCAQcDufq6mpjY6NSqezs7CASB12nOTcxmUwulyuTychksrm5OegyLFiwQFdXF4vFAgrx8/NLTk7G4/GQjgeqjwgVzMPDw8/Pz8DAABjN4CKFKJVarQ4KCnJ0dARhLXNzczwe7+vru2vXLj6fDw9XpVLp6ekRiUQOh2Nubp6UlAQ8QhaLpZm1umTJEnd3d4VCYWlpaWpqevDgQalUCiSeTz/9FAYb6D54enpqZc7a2dnt3r1bIBBgsVgbGxsjI6NDhw6h0WjN0CpMrFDqx9fX9+rVq2FhYd7e3pcvXx4cHHRzc7t69aqOjs6SJUvgIhsaGsA1OH/+fFtb29ra2tzc3PHx8YiIiHfffVculxcVFYGnrbq6esGCBeDl5fF4Y2NjTU1NSUlJL1++LC0thThmamrq5s2bfX199+zZk5qaevHiRUSv6P33358zZ05paSmkqtnY2GRmZoKre2RkpLu7m0wmp6WlBQYGhoSEwK/QaHRCQgIk0BEIBBKJJJPJ0tLS1q9fb2dnNzIy0tjYKBKJBgYGSkpKYLwh3QUQEMKjJSUlLi4uiBjg0aNHyWSysbHxnTt3Xrx4sXjxYngFxsfH33//fa1BXl5eXl9fr1QqX7x4AZnt5eXlSqWysbHx0aNH5ubmSLP19fUVFRVGRkYMBuNf//rXO++809LS8uzZM4VCUV1dbWRkRKVSDxw4gEajo6Ki2Gz2jh07BALBjRs3YmJiXF1d37h4y/j4OLLV3L59e2JiIqi8NjU1tbS0IMwqzcjJrwbgampqAgICJoMqPB6flJR079697777zs/Pz8XFBTmmo6MDfMkVFRV6enpqtVosFre2tsIrptUOjUYDh3dsbCwWi1WpVDU1Nch1+vv7M5nMiYkJCoWiFbzTuvF79+61trYCZx+NRotEosHBQSsrq8bGxn/+85++vr4qlQrEFwC7VFRU/Pjjj3//+99lMtm5c+dMTEycnJy++OILExOTsLAwAwODgwcPqlQqFxeX8vLyqKioKc+LSCT+qlfiN6HSKbORsrKylixZgqyeiKsJj8eTyWQoFwGep8rKSmdn57cZkpux/+OGxWI146qghDkZb01Z0xSDwUz+HADB9CcFVIH6fzVLpj+RJlVrmpY1rx9UPbTa1wq6U6lUT0/PV/kyYdabO3fuq4IdiLo/6r/FKZCvJsPiyT+f8pPAwMApT8flcrU+sbW1ndJFqom2jYyMYmJiptlMBwUFaX6ip6enRXyesn94PN40T8He3h5xraNQqHnz5k2zG5k8Nnx8fDQ/mT9//pRbW0NDQ2S6B/kuX19fYEIgABqNRru5ue3cuRMEwd3d3UF5XKlUGhoaYrFYIyOj9evXz5kzBxBzUFAQwnX9/PPPIXTl6+vb29uLx+OhniYWi4VBHhkZyWQykXBYYGCgu7s7hUKxs7OjUqlwMDwCLBZLJpOXLVsGZwEpJsTV7ebm9tFHH1VUVLS3t+NwOKVSCXr0LBars7Ozubl57ty5kKLl5eWlOZZ6e3uhKCSPx+vu7ob0GiaTuWbNGqlUCuSzsLAwCEwjtCrQVtXszM7OThKJtGbNmvHx8b6+PogJrl69msFgtLS0wNZCX19/zZo1JBKpq6srJCTk/fffHx4ebmlpAZogCBoJBIKJiQkajbZ06VJIpQSPrKWlJaT7PHz4sLCwUKlUpqenh4aGKpXKkpISuVyen5+Pw+HYbPbz58+bm5uh7CYKhYqNjYWOys3NPXLkiK+vL5S0UqvV169fp1KpbW1tiYmJurq6LS0tZ86ciY2Nzc3NBdGTn376iUAgREdH5+bmNjU1gaDu/Pnzka3j3r17Y2JiYmNjtUj6GAzGy8srODg4KysrOTlZk1u2fPny9PT0K1eujI+Pf/jhh2q1ur+//9tvv/3HP/6hOeDBrK2tIyMjT506dfr0aTwer1ar+Xy+Wq3Ozs4GpbeYmJgTJ0788MMP//Vf/wVkVj6fv2TJEk1IAbpNSUlJt2/fBrB14sQJEom0adMm2Hc5OTnNnj27ubl5+/btMHpDQ0OPHDmiUqlwOFxAQEBXVxdQS9vb2yH5SSqVHjp0KDY2dtasWSEhIVMiHs336A+0yZMYSqNGCkwdt2/fjomJIRKJ8AdcHhwDsgKurq7omfqgMzZjMzZj/zdteHh4eHgYWQVIJBLkl4yNjfX19SGfQ4QdWeH6+vo0K8PQaDQDAwOZTCYQCCA/F6oDicViLQ+0VlCbz+cjLALY32tW3oBmgWSpVqt1dHRMTU2RZiEDDnSJdHV1CQSCSCTS1MkbGBgYHR1FoVBMJhNK9PT395ubm9va2iqVyo6Ojs7OTkNDQ6go2tDQIBaLu7u7WSyWubl5QEAABoM5fvy4TCYzMTGxtLTk8XhKpRJEAeDUkZGR2dnZEonE0NDQ39+/rKysp6cH+ANoNNrPz6+srEwgEMhkMjMzM9CRevHixaNHj/B4vImJib+//5T8qocPH9bU1Kxbt04TXILynJ6enkwmgzye+vp6KpUaFRV19erVoqKihw8fbtiwITw8HMKFBw4c+Pbbby0tLdFoNDA1//a3v5mamn788cdLly5tb2//4YcfCgsL58+fT6fTKysrFy9enJSUpAWYhEIhVPCMjo6Geq9mZmZBQUF1dXVJSUkHDx6MiIjo6upKSkp6+PAhHo8XiUTvvvtuWlqaTCb76quvWltbP/3006+++io6Onr9+vVYLLa5uXn27NkRERFff/21lurmW7HW1lY+nx8cHAxXAvKwaDQa/rh3756XlxcQi728vCoqKlAo1AxgmrEZm7EZm7H/ZBOLxUiwHqLACP0IKjFoZs5C1BiFQkHqD+q/SQKTPwF6GQqFIhKJWjJXWp+AIjwkFmh+Mhk0gASdVjUYlUoFMBEi0RMTE+Bf1NHRAQl+YCVaWVmBlnpDQ0NdXR0s7l5eXgQCobS0VKVSWVlZgf+7ra3t5cuXcA0TExM+Pj6vCnLdv38fgJS3tzcA05qamsTExMOHD0dERDx+/HjDhg3l5eUAWAEwiUSiFStWgG5ifHz8li1bNmzYgMVik5OTr1+/jsVid+7c+TtVlP4QGxoaGh0dRRRVJBIJAHr4o6GhwczMDCRw+/v7Ad3OhORmbMZmbMZm7D/ZpteUQk2K0Ws6vab5RLPZXz0YpUEJmMaAQ6n1IQaD0WxNk8YeEhIyuRGQqdP8ZMGCBZr/tbW1nTKwPtkmk42A4gN/9/T0iESirKyshQsXolCo9vb2yspKKyurwcHB9vb26urqly9fqtVqkUiUlpYmEAg+++yzgoKCCzTC+6gAACAASURBVBcu+Pj4TFOG63/G9PX1NUsl5uTkQC/BH46OjshDhNIoeXl52N27d8+8TjM2YzM2YzM2YzP2q5aSkoLD4erq6ubNm4fD4SwtLZ89exYZGYnFYvl8Pg6Hc3Nz6+zslMvlbm5uDAbD1tbW3Nz8ypUry5cv9/f3NzMzKyws7O3tBZ3xt3svhYWFWCwW8j+Gh4chnDo8PMxkMmUymUwmy8rKghpfVCpVKBTOhORmbMZmbMZmbMZm7LWsrKyMSCQKBIKIiAgoQlxdXQ1ie52dnQqFwtraGgrJm5mZ9fX1YTAYQ0PDmpoaLpeLw+EUCkV5eblCoQDC0Nu9l+bmZgMDA8jSkEqlkB8tlUo7OjrEYrGzs3NjYyPCDZ+YmJgBTDM2YzM2YzM2YzM2Y/+/DQ0NyeVy4C3l5eWx2ey6urrIyEjMv9E9yGQyqEM+pQj1jM3YjM3YjM3YjM3Ya1phYWFnZ6darc7Pz+/q6qqvr3/y5IlardbX1zcyMrp06ZJarWaxWLq6uiwWa3Bw8N+J9N3R0XH58uX58+dzOBwCgaBUKktLS4VCIXxrbW39O+s5/FZramrq6OjQEvv38fGBsiFjY2Pl5eVIVoWLi4uJicnvrE41pT1+/JhKpdrb2/+molRTWn19/dDQEIfDmVK/Z8ZmbMZmbMZm7D/GLCwsQIUOhCsJBIKurq5MJqutreVyuS4uLigUCtRBaTRaQUHBvxNgun79eldXF4lEgizHnJyc5ORkpGSgs7Pzjh07XFxcfmeN8de3/Pz8tLQ0kPpA7OjRo15eXhgMJjU19cWLFwA+qqurc3Nzt23bpllI8g+xgoKC/fv383i8LVu2/B7AJBQKMzIyCgoKJBLJDz/88GcDpsLCwu7u7piYmMlS42AvXrx4/Pixvr7+/Pnzp5SU/J800Pi3traeNWvWr6bb/LtbVlZWaGioVlbzjM3YjM3Yf54h9dY09T+lUik4YhwdHe/evTtv3ryrV68mJiay2ex/G8A0ODhYXV29aNEiKysrLBZbUFBw+PDhoKAgkFFvaGi4du3anj179u/fP7kMyJ9kAoEgODjY2NhY028E4q3p6enXrl2DEhZEInFsbOzEiRPz5s1jsVh/rA8MStOzWKzfWdUSh8PZ2dnduXOnoaEBkZKbHmCNjo5CKbffdKKhoaGUlJTbt28rFIqQkJApAVNLS8vRo0cbGhpcXV3Dw8PfLmCqq6u7dOlSYWHh7Nmz/fz8/oMBU1lZWWZm5oMHD1pbW999993Lly9HRERYW1tPUxpWoVAIBAKlUonD4bReBLCBgYHx8XEgSkLJlN+Jw+RyeU9Pj1KpvHXr1po1a954bIjF4oGBARaLhZTBmbEZm7H/g3bx4sUVK1bAJNDQ0DA8POzj4wO+Jaj7hPrvsmNVVVVvEzBBQSIul0uj0SQSydOnT01NTS0tLadcg1NTUw0NDb28vGDFqq+vx2AwixYtArWJly9flpWVPXr0SMvf82dbREQEVFDXRB5oNPrp06eDg4M+Pj5QiDE2Nvb+/fupqamOjo5mZmZ/4AWw2WxNBf03Nl1dXX9//xs3brS0tLzO8QUFBenp6Xv37n1VAbtXGZFI9PT0zMvLa2trm7LUuVqtzs3NRaPRW7dutbKyQupF/E9aaWkpFot1dXUlEon6+vpLly4tLi4eHh7+zybPnThxwtjY2M3NzcXFhc/nX716tba29osvvtDT03vVT6RS6f379589eyaVSr/77rvJVQ7Ly8ufPXtWUlIyMTFx+vTpydUGf6tBiavS0tLS0lIPDw9/f/838yhXVFTs379/4cKFUODiT+pSmJGmTKwhk8kBAQG/f/skEAiqqqp4PB5SIxaFQlVWVo6Ojmp1Tn5+vpa44pw5c/4nOQwzNmP/Cw2wERgUrMRgMHK5vL293crKCoqigNzoW6slJxaLr1y5UlBQMDg4uH///srKyuLi4rt3765atSohIWHyO/zy5cvMzMz33nsP0ZLncDg2NjYWFhZwsIODA4/Ha2tr05qbrl271tbWplQqaTRaQkKCViHb3284HG5KLTKlUhkVFWVgYABXa25uzmKxampqtGoF/CEX8PoVm6cxNBr9qsqyU1p7e3tBQQHC0Hp9I5FIgYGBFhYWnZ2drzomIyPD3d09IiLiD39er2kXLlwgEAifffYZkUhksVgsFgt4af/Bs0ZWVlZzc/PWrVupVKqlpWVzc/OcOXOoVOr0rDsCgcDj8QoLC58+fTqlY9LBwQGLxRYVFRUUFPwhg59IJPJ4vOzs7NHRUbFY/PpJvo8ePaqoqFi1ahUo0fX19eXl5Xl5ef2pIFgkEo2MjMD2YNmyZZrI7Pr1656enr8fr7x8+bKoqIjL5arVapCQuXjx4oMHD6B2tSZg2rdvX39/v2aP9ff3L1u27FWh/MLCQmdn51eVkh0YGAAfJJQ1vXXrllAoTExMfB1igFgsPn36NAwYR0fHefPmaaHe7Ozs2tpaEOM2NDRcvnz5DLCbsd+/tWhsbJxcw87Lywv529DQsKCgQEdHRyaTTUxMjI+PFxYWxsbGwlhtb29/O4AJi8U6ODjk5eX5+/v39vb29fWxWKzW1lZwtk8+vrq6enR01MLCAlE45XA4AFY0gQuLxUJePLjVu3fvhoWFPXz4cGhoCCpWajYrFAqHhob09PRGR0fpdPrIyIiurq5SqQTBezQabWBgMDo6qq+vTyaTp5w1Ghsb09PTwa3l5OQUFRXl6OhYWVkJ2983mIvFYnF/f//ly5dbWloUCsX27dtdXV1HR0eFQmF1dXVOTg4Wi122bBmbzaZSqQi+EQqF4+PjKpUKg8Go1erOzk6ZTJaZmVlXV+fl5RUfH0+hUAYGBuRyOYlEMjQ0xOPx4+Pj/f39N27ciI6OdnBwmHJdhP7p7u6+cuVKUFBQdHS0pjarWq3u6OjA4/EYDAZKTQkEgpaWlidPnggEgjVr1jg6Ok5utre3V1NcdbL19vby+Xw/Pz9N9CYWi+VyOYVCgboBFAoFvlUoFF1dXXK53NTUVFdXV/NNmJiYGBsbYzAYCoWip6eHwWBQqVR4iB0dHbq6uvr6+q8CiE1NTbq6ulNGOaH6FZPJRFrTdLf09PQoFApLS0s8Hv/vFei5f/++Uqk0NjaGIrUWFhYrV67E4/HThyAJBIK7uzuLxXoVmrSysjI1NX369CmdTv9DQqtEIpHD4TCZTB0dHTqd/pootrq6+ssvv5yYmEhKSgLA5OnpmZycrOUe/sPN09NTLpfn5eW1trbyeDzNkZ+WljblXPebrK6u7tSpUyEhIcA5y8rKKikpEYlEQ0NDAwMDWu2PjY2tW7dOV1eXz+e3t7d3dHRYW1tP7sDBwcHR0dG6urrvvvvO1tb20KFDkxWrUSjU7t27f/nlFwcHBzabjcViLS0tv/zyy+DgYAsLi199KDgcztXVVaFQ7NmzZ2JiQkdHJyIiQnOuMDc3HxkZOXDgQExMjK2t7es85cHBQaFQqFlL7g3s8ePHKSkpIpFo3rx5cXFxfyod9vLlyzU1Nd3d3Tt27ABa8Zu109bWVlJSwmAw5syZ8/tD3przJ5/PZ7FYb12Pe7J1dXWZmpr+1qvS1dU1MjKa8qvm5ube3t6AgAA0Gm1iYkIkEqlUKlQRtrCwQKFQgBwsLCzeDmAiEAjW1tawqPT397u7u6tUqilfS1i2Kysro6KiNO9W6+DGxsbu7u61a9fCdD8xMXH16tXBwcH4+PiAgAClUkmlUifHC7q7u0+fPh0VFVVcXAxypS4uLg0NDRQKRSqVDg8PJyYmPnv2LC4uztnZecoBXVVV1dvbOzExIRaLi4uLs7OzDxw40Nzc3N7evnr16lfd0atMLpcXFhZ2dHS0trYODQ3V1dX19fU5OTllZmYODAwIhcK+vj6JRLJr164NGzbMnTsXoWbz+fze3l6IZpaXl589e9bCwqKtrW1oaOj27dvOzs7m5ubnzp0rLy+H+uQsFqu/v//EiRPp6ekCgeCTTz6Z7MsRiUQXLlzo7e0lEAi9vb0//fQTBoOJjo4mkUgFBQUvX76USCQ//vijqampubn55s2bh4eHjx8/bmdn5+Li0tHR8eOPP65fv97d3R1A7aNHjwYHB9VqdV5eHo/HAzj4Ku+OSqWCI42NjRkMRmdnZ2trq4GBAZPJbGhoYLFYUVFRVCq1rq6usbGxq6sLdOs5HA6XyyUSiXw+/+XLl729vVKp1NnZua2tLTMz08fHZ+PGjUKhsL6+/qeffrK0tPTz85s7d+7kZwSpgmg0+t69e/r6+sbGxkil65cvX168eBG4az4+PqGhoYjPoLy8HBB/WVnZ7NmzuVwum83W2hbLZLK6ujo2m41Go3/55ReJRBIQEGBgYIDBYIqKioaHh11cXKysrLRQ5ujo6JMnT6RSKZ1O5/F4yBlVKlV+fr5YLMZgMLNnz9ZENiUlJTgcjsPhlJWVDQ0NqdXqoKCg6Z1kw8PDmusrhUKpra1VKBSenp4IrHz8+DG4KAgEQlhY2GtGsvB4PJVKbWlp0SzX9YdM6LC/ep3MU4FA8PTp008++QS5ZnNz86VLl2IwmD91MQCGJYVCgXqrhoaGyFdvHEzUtEOHDo2OjkZERMBuwdbWlkgkMpnM77//fmhoSOtgAwODZcuW0Wi00dHR4eHhkZERd3f3yb138+bNvr4+sVgsEAj09PSm3PWVl5dnZmbSaDSQSEahUG5ubiQS6ejRo++99565ufn0yz8ejw8LC1Or1Tt37qyoqLh+/bqPj4++vj7yLFxcXPT09M6dO2dvb+/r6/urnu++vr4jR45UV1dfuHDht7IM79+/b2Ji4uLigsViTUxM8Hh8WlqasbEx1Pr4rTY2NtbS0uLq6jrlNTc1NVGpVHDaOTs79/b27t+/f9WqVVCF482soKAgOztbX18/NDT0D8zC7unp2bZt244dO0JDQ/+XACa5XH737l21Wp2dnX3kyJHXj4eA0Wg0zT3bo0ePACGhUCgGg4G05uDggP5vU6vVoFrZ0tLC5XKlUunbAUxoNLqlpaWiooLJZNJoNBMTk8HBwVc9ld7e3pGRkYSEBM03SmsdunLlCo1Gi4yMBBJxRkZGVlbW8uXLId8nMjKSRqNNnt9ZLBaXyzUwMHB3d8disS4uLpaWlnK53MrKSiaTDQwMGBoacjgcQ0PDKZ9NUFAQqKpjsdjx8fETJ07cuHFjaGjI0dHR0dGxu7t7YmLiN+2qr127VlRUtGjRIn9/fxQKdfz48YKCAg6H09TU5O7ubmdnh8fjOzs733///fb2dk3AYWRkZGBggMVinz9//sMPPzg6OgYGBkINoAsXLkgkEiqVyuVyb9y4oVAogMegr6/v4eFx/fr1xsZGLWYD4q6vrKwMDg52cnKKjY3ds2fPlStXgPUslUph8XN1dbW3t7ewsOjr6zt69CgKhfLz83N3dzc0NFy7du3g4ODu3bvZbPbDhw9Pnz4dHBxMp9PNzMwqKyurqqqmTMR7/vz5zZs3BQJBW1tbTU3NihUrdHV1hULhuXPn6HS6Uqns7Oy0s7MDLHLgwAFnZ2c/Pz9dXd3R0dHk5OS//OUvfn5+CoUiMzOzqKiITCYvWbKERqPJZLKffvppaGhocHAQ6lO2tLQUFRX5+vpOBkyFhYV8Pt/IyEgikaSlpa1YsQKiGLW1tS9evLC0tGSxWE+ePHnx4gWXy4VBVV5evm/fvsjISB8fH3hwCxYsQOLFsAu8devW8PCwSCSCct+3bt0aHx+PjY3dsWPH8+fPv//+e4FA4OHh4e3tvXr1aoS5lZ2d3djYCM6wn3/+efXq1VFRUbq6uk+fPi0uLhaLxXfu3JFKpQKB4J133qFQKM3NzXfu3Llz5w4ej/fx8SkuLh4YGFCr1fHx8du3b5+SYt/b25uenl5VVTU0NHTkyBFkxBYXFxsZGX377bfg1i0uLj548GB0dDSZTL548eLjx4+jo6O9vb1fFSs5e/YsEgCC7poyZldSUlJSUgLDiUAgbNy4ES6gsbERbg0Oo1Kp7777LvKwoqOjHzx4AG+Bjo7O8+fPHzx4wGAwli5dSiKR+Hx+RkaGRCKxsLBYvHixrq6uWq1Wq9Wtra0KheLBgwdmZmZ37tyRSCRkMnndunUwFGtqau7du4dcpIGBwfLly/+8dNF33nlHsyLYG1h+fn5xcfG2bdtsbW1hgnJycnJycgJEMhkGicViLBaLx+OZTOY0wW5TU1MbGxs6nQ5khslTbmVlZXl5eWxsbFtbG8B9CBps2LDh1KlTzc3Npqam0wMmNBoNSzuVSo2Ojr537565ufmOHTuQDsFisTKZrL29Hf7+1QW7ubn5woULs2bNeoOl/Ycffpg1axb4yaysrLZu3Xrq1CnYs73BQzlx4oRYLIYw5eT9+TfffLN69WrofE9Pz5GRkTc+EWK+vr61tbWlpaWv2oK+mY2Pj+fk5KxcufLPBgO9vb3nzp1Tq9Xbt2//1QwMsVicm5ubnZ2dnJz8W080OSCguZeoqqrC4/GmpqaFhYWurq4jIyPj4+OOjo75+fkLFy50d3dHoVBKpfKtkb4h3OPk5ATU2t7eXnd394CAgMkz1NmzZ6lUqq2t7ZRT89DQ0NmzZ7u6ulauXIm8qPfv3xeLxQ4ODrCegdtpsunr6y9cuJBAILDZbLlcrlKpCASCn58fhUJRq9UymYxIJMLlTfn++/n56ejogJ9MoVA0NDTk5ubeuXNnzpw54IdfuXLl67Nwbt++ferUqfXr1/v7+8PCsHnz5tHRUTKZnJiYaGFhgcfjBwYGprwYHA4H00pVVdXDhw+3bt3q5+cHUxIej9fT09PX1587d25qampYWBgsxjQabf78+ZcvX46MjJwS1enr669du5bNZo+OjspkMiwWC2r38Io+f/5cR0dn4cKFLi4uBALhzp072dnZ69atw2Awra2tOBzOz8/vzp073d3dIyMj+/btCw8Pnz17NpxIIBDU1NRMyWEyNDTcsWPHxx9/bGxs7Ofnx+PxqFSqvr7+4OCgra1tZGQkgUAgk8m6urp79uzR0dEJCQnhcDiurq6tra1paWlffPHFsWPHLCwsli5dmpOTY2pqyuPxrK2tORzOZ599VlxcvH79ek9PT0NDw2vXrhUXFx89evTTTz/VChH6+/ubmJgwmcyAgAA7Ozt3d3dYfvT09Hg8no2NDRaLPXjwYFpaWmpq6vr160dGRr766itLS8ugoCBbW1t7e3uhUHj9+nU/Pz+E1UulUjkczt69e+vr62k0moeHh4WFRW5ubkZGRnd3d3Bw8IoVKyDz68qVK4sXL6bRaBMTE3fu3ElJSVm2bJmPjw+BQOjr6zt8+DCdTg8MDHzx4gUWi42MjLS1tb106dKPP/5IIpHi4+PpdDqHwzl37hyJRHJ1dXVycpLJZCkpKTdu3IiLi3Nzc5s8j+vq6nI4HAMDA5lMxuFwkN7IysoaHx+H9yI/P//MmTM8Hg+EFTAYzO7du/X19UERTWv3cufOnefPn3t6ekJhphMnTlRXV8+bN2/yMKurq/vxxx+DgoJgf3/8+PFVq1ZBzabPP//czMwsPDwcFtELFy4IhcJ3333X2NgYg8G0t7cTiUTolt7e3kuXLt29e5fH48XHx5NIJDKZ3NXVdfXq1d27d6PRaLlcnpmZKZFISktLv/vuOz6f/95778nl8tOnT69atQqWq4GBgS+++ILNZgcFBcEdffXVV0NDQ2vWrKHRaDdv3szNzTUwMLCzs+vs7FSpVF1dXWq1+tChQwwG47dOfaOjoz/99NM777yDvMjDw8O3b9+GlmH5h3A8lJJ4VTtFRUXj4+Ph4eGvw++xsbFRKpVNTU33799vaGjg8XihoaHOzs6Tx0NgYCCRSMTj8YaGhvX19Voepp6enm+//TY2Nrajo6Orq2tgYMDe3h5uxN/fv7Cw8Ntvv/X09NRkoE9jZDL5s88+O3ny5Pnz5zEYzMaNG5lMJvyQQqFowQ6JRAIag/BfMzMzRPxCJBL19/d7enpKJBKpVMpgMF4TOXV3d1dWVrLZbKTZ14wAvsquXLni5uY2pVuut7c3MzNzwYIFf2x1DSaTWV9fPzg4+Mey8UxNTc+cOfM/UO6tv78/OTnZyMjovffemz4+jsViQ0NDJ+cuvJlxuVyxWCyRSIBqbGpqCtjD3Nwc8qhIJBIOh7OxsYGFKTMzMzQ09G1myTk6Otrb2xsYGOBwuNTUVB0dncnKkxUVFTU1NVu3boWJcnLc+uzZs+Xl5StXrvTz80M2KEKhEIfD6erq/urQb2tra29vl8vlHh4ezc3NY2NjarVaT0/PwMCAz+fDg/H19TU1NZ08c2kuADgcDkhFdnZ2Dg4OFhYWCGnxNa2mpqa1tdXd3R2BjBwOB9mNPXr0SCQSCYXC3t7eyeTZ7u7uvr4+KysrsVg8MTFBp9ORq3V2dkYmIEAzSGSks7NzaGhI8xNNo9PpxsbGJSUlQBLq7u6G20Gj0YaGhuBXYzAYdDpdIpFcvHixq6urra3twYMHAC/MzMzCwsL09PTAlfjRRx9ZW1vDwzU2Nraxsenp6Zl8UnNzc1NT0/379zs7OyOUKYCDVlZWixYtgoytoaGhkpKSlStX2tra4nA4Go3GZrNjYmIgEuHg4ACCBSYmJg4ODoaGhpB92djYGBERAWl9cXFxt2/ffvbsmVgs1gJM4CEjEolGRkYcDgd8s+DGY7PZkHawbt26W7duvXz5cmJiYnh4uLS0lMVilZWVVVVVwUakoaEB8u0R9BkSEvL9998rlUoLC4vw8HASicTj8d555522trZt27bB0vXs2bMXL15UVlYaGBj09PQcOnTI398/NDQUVpHAwMB9+/bx+XylUmliYmJmZubq6urt7W1raxsXF1dTUxMbG2tgYBAaGmpgYEChUOCHcD1fffXV1atXra2t6XR6R0cHGo3m8/l6enpUKtXIyCgkJMTU1FQikYBMBrJXHhkZAQz03XffmZmZLVmyBBgqs2bN+utf/wq0ucnT34EDB/z8/IKDgyEITqFQ0tLSiouLtYaZSqW6ffs2mUyeN28eQKvy8nIYIQ8fPgQNkYiICJhDJyYmPv3007Gxse3btzOZTAi7SKVStVpNJpM5HM7du3fNzc1hfWUwGIGBgRkZGU+ePFm0aBGFQgkMDCwqKlq+fDmHw4GXVKlUXrp0SalUwuqVn59fX1+/YsWK2bNnwzWkpKScPHnS1dXVy8uroaEhPz8fhULFxsZ6eHjg8ficnJzKysrFixfPmzfvdfDK+Pj47du3Ya9SX1//7NmzhIQEBD8dO3ZMX18fiT2VlJTk5eUlJibCvvZVJhKJVCrVaxK5xGLx6Ogo6Bp3dHQUFxdnZGRcu3ZtstNRMy/VwsJCC1Hl5ORIpVI/P7+srCw+n6+5mhIIBAqF8vDhw9ePvWIwGC6Xu3Pnzn/9618nTpyQyWTbtm0DuIPFYqlUqmb7qampz58/hzSChoYGW1tbLpcbHBwMLkyFQnHp0qXx8XGpVLp161ZDQ0M0Gp2fnz8yMqJWq0kkUmRk5OQ5HF5hJEbD4/FwOJyBgYGTk9Pjx48hMRaDwSxYsEDztwUFBcPDwzByzM3NfXx8kF6CCDh4ZP39/TV7Ty6Xj42NwbI1ODgIvkAkpPjkyROYLtzd3REMCrP0s2fPkJkkKipKi1REJpOtrKwUCsWvhqjkcvmzZ894PN40A6aoqCgwMBCDwdDpdE1M/5omEAjGx8ft7OxeBbOQ9jWvqqenZ+PGjZPRUl9fH0RsoDUMBmNiYvJbiS6vMljiBQIBTFOQz46E5KhUKmRRQJacjo6Ovb09g8F4O4BpfHw8Pz+fy+VaWlrCY66rqwP8odXRd+/eDQ0N9fT0nOy+VigUp06dqqqqWrx4cXBw8Js5z7Ozs+VyeX9/f11dXVVVVVhY2OPHjz08PKqrq4G6Ozg46OzsPPn6Hz165OvrO3l/6eTkZG1tzWKxGhsbtb6KiYmZJkNbrVZPTEzcv3/f3NwcmkVGFUSply9f7ufnJxAIzp07p9Vse3s7k8mc8oXRHJoKhUIzAKdSqSYmJpqbm6eMlQwMDBw5ckRXVzcqKopOp+fn508JcQD429jY6OjouLi4BAcHa64fNjY2bW1tcBnIk0UgyJS+ehBJ5/P5CoVC8zD4Cu4xMzNzdHQUiTSDm8Te3h6JRMDp4Cutf+EPS0tLAwODgYGBV/UY8opqXgDyc0dHRxKJBIEeeHZqtVqpVIJX3MTE5MMPP3RxcUEmWfhhXFwcGo329fUF8VUHBwcajWZoaGhiYgKdFh0dfffu3by8PD8/P7FY3NzczGAwkpOT4b66u7tFIhE0GBAQgMPhjh8/LhQK5XK5RCLR6lvN7po7d25ycnJzc7NcLj9z5szjx49RKFRHRweQWiIjI5FoNfITeKxxcXEUCkWlUtXU1ExMTJw6dQomtfHxceRKJi/MTU1NEB+EpgICAsrLy3/++WetYQY9xufzT58+7ejomJCQsGTJEniLr1y5AusQ4k91d3cfGhoCxwwSmofOp1AoQUFBRkZG9fX10P9oNDooKAjodHg8HhQiCARCc3Pzxo0bASJgsVgMBgM8LRQKlZ6ebmtr6+HhoaOjA2dcsmTJjRs3Tp8+fejQoYSEhCdPnnR1dSUlJQHvh0wmf/7559euXXtNBw+8fXAuPp/f19eHYM3k5OTy8vKdO3dCIgsKhTpy5Ajiy3xVa/X19c+fP3/9KIxarV63bp2/v39UVNTAwMC+ffvy8/MvX768du3aKSODdXV1z58/l8lkWqe4e/fusmXLAJuCI1bzHfHz87O1tb169er69etfk02PRqOdnJw2bNhw/fr1U6dOrVy5ErxTZDLZzs4Oafzq1atpaWlLly719PSEYq5nzpypqKjg8XhQ9QHmXgaDAfk6tbW1N2/eNDMzg8s4evTosZfBNgAAIABJREFU+Pj4okWLNIOVz549u379ulQqffr06d69e9vb2z09PTMyMmQyWUlJyaVLl4hEIqQsCIXC5cuXw29zc3MFAgGBQABBjTlz5nh4eGCx2MrKytu3bw8ODpaXl+/du7exsdHb2xt5gleuXMnPz5fL5enp6bm5uWw228HBAb66cOGCrq4ugUCora0VCATu7u7ffPMNbCFEItHXX39Np9O5XC4Gg7lz505TU9Nf//pXzbugUql2dnZZWVkdHR2ZmZnQFUFBQeHh4UjvNTc3p6WlSaXS0tJSCONs374dh8OJRKLk5GTIIg8JCcnOzi4sLHzvvfeUSmVtbS2E8gExpKenNzQ0aPnGrKysVqxYgcVim5qa0tLScDicj4/P+fPn7ezsnJycEhMTx8fHDx8+rFKpaDRaaGhoVlZWQUFBSEgIBoPZtm2bJiCur6//5ptv0Gg0pG2eP39erVb39fUNDAy4ubl99tlnf0aSMoPBQF5epH00Gg1Uh8TExIsXL65cufLWrVvgBUehUG8HMEml0pKSksjISHDvI12WnJy8detWRCtvZGSkvr5+7dq1k3EJZG89ffrUz8/PxMSkra0N8aNoar3I5fK2trYXL174+/ubmZlNnoCioqIIBALkJ/N4PHt7e1dXVyaT6ebmZmRkhMfjxWIxsnNFDI/Hj4yMZGZmRkdHA4Ovvb1dKBSuX7/e3t4ei8XCNr2/v9/W1haPxxcWFj579mz58uUwWTc1NR0+fDgxMRGCetDmwoULs7Kynjx5kpSUpHm/ZWVlV65c8fDwCAwMtLa2ptFoWjNRU1MTnU4Hlw980tXVNZlxPNnKysrEYvGsWbOmDMl9++23VVVVW7duBe0rfX39vr6+KdvB4XDh4eHp6ek4HI7NZmspJ72BRxdEBafxzzk4OPypyU1v5i4NCQnR5Mlp+vnAGhoaptcXtbe3Z7FYsLojn/j7+8OSplAoZs2axePxFApFVlZWY2Ojv7+/rq4uQJlpmjUxMUFSCLlcrqmpKaBzSFZ6FfVYrVY3NDRAYBqcDf7+/uDaUalUXl5ebm5uk9fa5ORkS0tLTbA4jXfB29s7Nzf34cOHN27cuHHjBoVC+eSTT5ycnDo7OxkMhr6+PjI5MJnMVatWHT16FOA+7NQRBTJYb3x9fZF+a2xs7O/vF4lEMMXLZDKpVKqZtmlgYACiU/BJR0cHm83W5MU7ODgAoUGhUDg7OzMYjJGRERcXF3g3o6OjT58+Dd6+1xkeRCIxKCgI9rJOTk6nT59GTnTt2jUvLy/Q44VPXFxcCgoK5HL5NLGb/v7+7u7uxYsXvyYRysXFxdHRkcFgYDAYmUxGo9G2bt16//79FStWTNkC9I+ZmZnm8Dh9+vSCBQtmz56Nx+OFQqFAIBgYGNCENR4eHpaWliAQ85veUB8fnx07dhw9enT37t179uyxtrYWiUTV1dWIG+bevXtDQ0Nz5841NjZGo9F2dnZ37969f//+9evXExMTgWTt6ekZGxuLx+MpFMq1a9euXbt26NAhGxsbDAYzMTGxb98+Go02e/ZsZAwYGxsvXbr06tWrJiYmAQEBISEheDze2dl5fHxcqVRu3LgRWO1dXV379u0jk8lxcXE4HK65uZnL5VpZWZmZmfF4vO+//z4iIiIyMpLFYgUGBh49etTIyCgwMDAwMFDzFXBychoYGACut7e3t+Zi5Obm5uzszGQy+/v7f/nll5MnT/71r381MzPr6enZs2dPR0fHrl27LC0t0Wh0ZmZmampqUlLS5PTGjo6OY8eOMRiMWbNm/fOf/7x9+/bJkyfd3d0xGExjYyPA8ZCQEE9Pz9LS0kuXLgmFwvfff59Op9PpdHitamtrGxsbh4aGGhoa5s6de/r06RcvXoAqGyRgJiUlwfwmFosvXrzY1taWnJwMIe8PP/yQzWYvWrTIwcFhyZIl58+fr6ysDA8PR9qH2cbf39/IyOjYsWN8Pn/OnDn+/v5Xr17Nz89XqVRVVVUCgQCNRkdGRqLR6O7u7oSEBLlcnpOTc/bsWRQK9WdgJgqFAv4qkUgklUppNNqNGzeWLFmCw+Fg4AHjG5yaXV1dZWVlbwcw4fH4wMBAJycn5KUKDg4eHx/n8Xh6enrIEvv06VN4dSdPvg8fPvz5559LS0u7urqys7ORz729vT/++GNvb+/CwsI7d+6QyeTnz597e3sTicQpV25NDQbEKYL6f8WsJhswaY4cOcLn82EjmJ+f7+HhgfCo4uPju7q6UlJSGhsbyWRyQUEBjUZjsVg4HE6lUt27d6+srCwmJkZzQgTJE0jpiouLMzY2hjcKvBcvX76sra3t7++HFrT2mhQKpauri8lk2tnZGRsbHzt2jEgkasYoNePo4LcoLi5ubW2VSqVtbW1TutAfPXrU3t4OIvHwh9YBKpXq6dOnEonE1NTU2tqazWZfunTJ3NwcMum6u7ulUqm5uTkcXFpa6u3tDYtNe3t7Z2fnNJtjfX396QGfs7MzkUisrq4eHByk0Wj/GxSS6uvrQbJhGoBIpVJHRkYEAgGg6skH9PX1wW4PuSNHR8ewsDAt72l1dfXRo0djYmKARy8Wi1+fPgy09Nf0SdTU1CCASSwWOzs7w/Izza9UKhXsC5FROjIyUl1djRDkNZG0t7f3F198IZFIUlJSxsfH8/LyDAwMdu3a9avXBgmzyFmGh4fHxsbq6uoQPDo+Pj4xMYFE3MhkMoPBQOhomh64Vz0vEokEEcwppw4ymUwgEF4/9oTFYg0NDSFLDugaCFlndHSUSCRq0l2xWCzivJwGoHt6ejY1Nb2mk0kz9EYgEHx8fIyNjRFAOSWb0NTUFHHaAXvh6tWr8+bNy8nJgdJaKBTq8ePHIpEoIiICOpZMJuvo6EA+7G96fchk8ubNmzEYzLFjx0gk0ieffEIikRDNz8bGxtraWjQajUSjyGTyBx98cOXKFXCEsNlsR0fHnp4eJpNJJBJHR0eBf+Pk5AQLSlhY2HvvvdfW1qY5eZqZmZmZmRGJRHNzc4Qtx+FwVCoVk8lcuHAhfPL555/PmjWrrq4OfhsREcFisahUak9PDwaD6ezsbGlpUavVxsbGxsbGJBLJxMQkLCxM65V0d3eXSCRYLNbd3V0rOOjp6RkWFobM9gcPHoQ+z8jISElJiY6O5nK5sFDq6uo2NTWlp6d//PHHk1/DOXPmuLm52dnZ1dfXb9++HWjB4LDs7Ozcu3cvRMrc3d0HBgYATi1evDgxMfH+/ftPnjyJj4+Hh2hiYuLo6Lh69eq8vDzEKwxFF2CLcuTIkbKysk2bNkERsNzc3MrKyvXr14eFhYHEDJFIXLly5aFDh3bs2AHtl5aWhoSEQCfI5fJvv/02OTmZx+M5OTlBSvKSJUsCAwPRaLSDg0N/f394ePisWbMwGAybzc7Jyfnll1/+/ve//+GTdm9vL0SQhoeHBwYGOBwORJNALQUeDYBdkUhUX1/v4ODwdgATiUTatGkTlUpFUkBXrFiBwWA0S2309/dnZGQAyWnyhGViYhIUFAQsH02DxNolS5YYGxvDrtrHxycsLExzt/qHmL29fXx8PPh10Gg0h8MJDQ21srKCMefg4LBu3bqysjKYbb28vBYsWIC4vu7cucNms+3t7bUwwZIlS4qKii5cuFBVVQWAadmyZfb29h4eHunp6QcOHIiNjQWiQ25uLjzO8vLynp4esVh88ODBr7/+2tvbe8eOHV9++eX3338PhFw0Gr148WJHR0eITbS3tycnJ9vb2/f29iYkJOTl5YGs9vLly4uKip48edLf33/06NGlS5fOnTv3yJEjFy9ebGhomDNnDhaL7e/vP3LkyKpVq1xcXPz8/Ozs7M6ePWtgYPD+++9zOJyPPvpoz549ycnJJSUlFAqlp6fHz88vPj7eycnJ09MzPT2dyWQmJiYqFIojR46UlpZSqVSFQgH+c3i+KpVKpVLdvHlzdHRUpVLBagd/wLcKhQLiyiQSad68ednZ2Z2dnbAJBnnAkJAQWErhSAj6qP7bkP8iZ1Sr1VrXgKxYDQ0N33//vbGx8bp16+h0OlyJ1sHQIIvFCgsLy83NtbKy+stf/kKj0fh8/rVr10CUS3ODrlarGQzGlCVEEGfh4OBgS0sLLPwYDObWrVvR0dHAxoO7wGAwQqGwo6MDsiYVCsW1a9deFSB7Y4NzIR7EuLi4W7dutbW1mZqaEggEDAYD+VOT0/ITEhJAqwIeH2wWHzx4ABFMzSOVSuW5c+fc3NxCQkKAhLFp06bGxka5XI7BYIDogwS8RkdH79+/Hx4eDpAUOgqy3nR0dExNTQ0MDGpra6HfVCpVR0fHyMiIk5MT9L++vr6FhUVGRgbwxAFsdXV1VVZWwk+wWGxVVVVFRUVgYCD8RCwWt7e3v/POO6+vNa9UKl9Tp8DJyamvr+/hw4dhYWFIb0N3oVCoyspKY2Pj6WUgDA0NzczMSkpKXgcwwaPUHOTIWJr+h87OzshYra6urqmpaWtrgw6cmJgYGho6d+6ck5NTcHAwdNprNjulGRsbb9iwQSaTnT59WiKR7N69+1X7CoTiqfXty5cv4U7lcnltba2BgcHhw4eRYMWUGX+vYxAO09xRnzlzpq+vb/rd0e+3xsbG8fHxurq6vXv3wl1YWFiYmpqy2ezJPZyYmDhnzhwAlLGxsTdu3EhJSZk1axYKhXrx4gWDwQAfFaxcmzdvPn/+fHd3t1qtNjIyAg+0Fsjjcrmad7d06VL49uLFi4cPHzY3N4+Li4PLuHjxoo2NDcAdxNE4PDx89uzZ1atXs9lsUDZycnKCqXvZsmVZWVlubm5oNNrNzU0ulwOMA4QEhCEajaZUKltbW1NSUkZHR1+VtvVHmZ6enq6uLhaLBURx4cKFlStX3r1719vbu7e3Vy6Xu7m52dvbW1pavh3AhMPhNGvdQTR0Mh0PjUZHRERo+pw0Abudnd1kzimIvtDpdAMDA1hogYr4WzUbftWsrKxWrVqFXACw5DQXQldXVwsLC8RjT6FQYBPZ2dmJxWKXLl0KVec025w7d66Hh0dtba2Ojg7MSnp6enQ6fdOmTREREWg02t7e3sjIaP/+/Wq1Wl9fH/DlgQMHFAoFhUKBwNyiRYsMDAxgIcnJyQkKCkK0erdv3w7jHpL7OBwOjUYTCoUkEsnIyMjb29va2loul1OpVDMzs3fffRc0eOh0OpvN3rp1a3x8PJlMNjIygoG1d+/e4eFhDAbj4OAAsmk0Gu3FixcFBQUxMTFARiYS/7/2zjy+qTrd/yf71jTN0iRNmqRL0qR7m660SMtaoIJFZRFkUMbxohfBZeQ1c6+jjHOvzOigzngVRpR7p6AoZS8FpFALgVLpCqV7S7qnbdokTZukWZrcP57fPa/8WmBQcVD5vv/glZ4k55ychHOe8yyfDz0iIuL1119/++23z58/39vbGxgYmJWVZbFYOjs79+7dC52t8GGHhoYOHTpUWVkZGBh49epVi8Xyr//6r+3t7RcuXIDc2549e5577jkej8dgMF544QUSiXTy5Mm2tjYqldrd3U2lUl966SWpVNrc3Hzu3LmAgACTyfTRRx+tXLmyvLzcZDLRaLQ9e/asWbMmOjqaQqHI5fKxsbE9e/asW7cuKirK/7vbvHnze++9V1tbKxAIUlNToRl5fHx8165dzz77LDgoK5VKs9n84Ycfbtq0adu2be+//355ebler5dIJDabjcFgQJc9rHB8fLynp+ebb75pbm4+ffq00+lUKBRDQ0MTExMUCqWxsRFmu8LCwqARu62tLTQ09Nlnn92/f//27ds3btwYGBhoMBjKysqeeOIJKpUaHBy8e/ducNWGEbOhoaEbN27gGWav19vY2JiSkoLflEOmJy0tbZrCp8Ph0Ov1ZrPZZrM1NTXR6XQymVxUVHTt2rWgoKCmpiYI969du7Zz587du3fn5OTEx8fD2N1Mc4/IyMjQ0NDCwsKIiAgQlzt27BjMN83Mx5hMpmvXrmVmZkJ6gEQihYaGksnkl1566fXXXy8vL+fz+QkJCRQKpaOjw2az5efnw+3TwMAAiURisVgTExOgQRoYGNjb29vY2Mjlck0mU0VFhcvlOn78eGJiYnh4OJfLDQ0NLSoqevzxx2NiYoKDg0dHRw0GQ15eHnzvv/71r//jP/7jwoULHA4nLi7OYDDcuHEDqgx3aT00ODj48ccfv/TSS3epJFJXV1dRUZGVlaVQKMrKympra7OzsykUSldX17Vr13g8Htw2GI3G4eFhSHd955PY2bNnbTbb0qVL8WxZcXGx3W7/9a9/fWfVIrzHC8oT7733Hn5C0+l0VVVV69at86+Pnzp16vr16+++++53c5uRSCSrV68uKio6ceLEypUr8Z+WVCrl8/m4z/pMQkNDExISpgmowlUcvl+v15uZmanVar+nUtHY2NjevXt1Ot2//Mu/yOVyj8fzg6a3WSzWL37xCzxik0qlWVlZt+zabmlpwb+pqakpp9MJX4FOp+vr68P7pfCL17cN9WBWZnh4+IsvvlCpVK+99hpuitXd3c1isfCMKRSgly9ffujQoVuOs8FFrbGx0f8OSq/XQ0QLGnWFhYVhYWESiSQrK+vgwYM/XJwEJ0w2m81mszs7OyMiIiCMg1MZFA1Ay7q+vv6+9TDdZbosIyNjZhoGYDAYd/4/eWc56e8PjUa7c5GeTCbfch+++OKLlJQUrVY7s4wCJXNwx5sWHfrPyyxdutQ/ozZzJfACr9cbFhamUCjwDWVnZ097cW5urv/ZamZQ6N/TMO34z5kzZ1rWMDc3NyEhITMzU6VS+af00tPTX3vtNUiwwxB7XFwcqA76Dz8GBASkpqbin5RAIDAYDKlUOnv27IyMDDik8FkgStuyZUt/fz9MssjlcpFIpFKpQPA9PT0dsqkYhgmFwrS0NDwZiZ9VN2zYADUd///qwLx584KCgiYnJ6lUqkwmo9Fo+Npwpb5XX30VZio5HI5EItm2bVtTU1N3dzeUCyHb7y/FXlNTAyUeaAul0Wg1NTUpKSkUCuXGjRsajYbJZFIolNmzZzudzurqaoVCATINPT09dXV1VCp1YmIiODgYgoPnn3++srKyu7sbZtxWrlzJYrHq6+thi1qtFlImKpUKRq8XLFgAArCwe/6f126319TUREZGSiQSmHVgMpmDg4PQHNrY2BgeHq7Vanfs2HH8+PH+/v7+/n6PxxMYGCgWi0H7oKWlZWxs7OjRowsWLJBIJFu2bCkvL3/33Xc9Hk96enpubu7Y2Nj169dLS0tTU1P9lQgIBEJtbW1RURGdTnc6nVqtds2aNSwWa8GCBRaL5dChQ7/73e8effRRJpNpMplwDaquri6hUMhisWpqahQKxZw5c2g0WmZmJihHe73e1atXr127tr293WKxlJeXSyQSJpOZlpZWVFS0a9eul19+OSAgQK/XL1y4kMfj1dbWzpo1Kz8/f2Ji4ujRozU1NcuXL6+qqpJKpfn5+eHh4VartaysrKury2g03rhxA09BwfWjubkZJDxOnz792Wefbdq0aVrA1NPTc/PmTavVeuTIEf+n/vu//1ulUvl8vmeeeWbTpk2HDh3q6ekhk8lQ+oTiLMQ6n332WUxMzJtvvjltPigpKen8+fPTfrrj4+NfffVVZ2cniAiIRCKI7wsLCzEMW7ZsGZVKPXLkSGNj48aNG6GU5vF4jh8/HhUV5Z9Pwu9a8QhJoVD4nxAOHDgwMDCgVCrxehx06Q0ODkKY4vV6jxw54nK5cnNzbznjfEsiIyNfffXVt99++6233jKZTOnp6XBuodFoJpPp+vXr+OjZhQsXeDxeTEwMdGXZbLbKykr/lrLx8fHExETcTeue0NjY+OGHH/7mN7+BRi5ou/mBLjFarfbgwYNWqzUnJwc/wreTuITuNDx96Ha74fKkUCjuUuLhHzIyMvLee+9VVlYWFxdnZGT4f6EGg6G5uTk+Ph425PF4WltbtVrtLYXfgPr6ev+Aqa2tDRehffPNNycmJvLz8+Pi4pKSkr6DcscdgK5zqAuBrdn58+fnzZtHIBCamprgegqir1FRUQ6Ho7OzMzs7e3JyMioqqqOj48cbMM2aNYtCodwX79UflJiYGLjl/aE3RCQSv4+A7HeDx+PNmjVr5vKkpCT/P1Uq1bSbHgjzZ76XyWSCOP1MwsPD4Xrm9Xr9jWJEItE0CXx8VH7aF3G7T0GlUkE7FLjlDqSkpEwrsigUCpvNxuVyZ2YCgoKCMjMz8f4h6GiBPmW8xQRaWZ955hlIWwYEBNDp9Keeego+IH54QUb18ccfz83NnZqa4vP5PB5v69at/u3keCyLC9I8/fTTDofD5/NNG9WGu9iMjAz840CnHRRPYYlAIGCxWNnZ2TKZzGazwWmOzWaHhITAefnhhx/Ozc2FgSkGgwGZp7Nnz1qt1uTk5NzcXJFItGzZsrGxMf/rMZFIXLJkSXNzM5jMSKXSzMxMfNRx2bJlNBpNr9eDn92sWbOgdgDTbcuXL4f/RLj0WkFBQXJy8uXLl51OZ05OTlRU1JYtW7hcLo1Gg43OmTPn3/7t3+ASAiq1s2fPhuZ3uCcuKCgAmXg2mx0fH5+amgqxssvlolKpa9asgfGR1NRU2MO1a9caDIb6+nqxWOzxeL744ouFCxdOuwsaHx9///33hULh5s2bp/0wFi1aBBpm8+fPf+ONN3g83ieffBITE7Nu3bqVK1d+9dVXUJILDw+fO3cuJN5m9qzs3r27uLh4zZo1+HY//vjjlpaW5cuXl5SUXL9+XaFQiMXitLS0xx57bO/evdeuXaNQKPX19b/61a/w7KDH4/nLX/4iFovfeustUCHav39/VFRUVVXV+Pj4kSNH1q5d65+VhHG/GzduDA4OGgwG6OfFn8Uv7aBTZbFYFArFtNwPHPbS0tLBwUGHw0Gn0/FmMiaTCXbIW7du9dcWWr16dUVFxY4dO958802Y+d+5c+fLL7+cm5sLfpo0Gq2urm779u1MJnPt2rWPPvro+fPn4duEMTqfz4fr1c2spU5OTsIV9M699qOjo/39/SqVyu12nz17VqfTud1uqNTjFVVI8MDaZm4L5g/wnyX2f8au/sA+5OXl7dy58/Dhw/PmzUtLS4MDeODAgfXr1/v/GKBVwH+3AwMDw8LCGhoafD5fWFiYQCDo6OjQ6XR4zcvlchGJxG+VG3O5XP/5n/958ODBhx9+WKvVEggEr9dbWFi4fv36p5566sUXX9TpdBBwgypha2vrq6++Ckr3//A6RSaTobEally7dm3Dhg0FBQVMJtPpdN5bfamZMy74Evym2v818JhIJGo0Gjqd/uMNmGYW6X4e5ObmQrkUQ9wLfjwh9R2yniwWa2bicGYCEvpGpxUpZmb+IOHnn/ObGX1OIyws7HZP0en0mfs2cwmelveHQCDMmjUL8n9wtQN1rqCgIJFINDU1BV3AsbGxRCLRZrNRqVR/qYXU1FS1Wg0nejh6+AWGzWYvXrzY6XTCs4GBgfhVWSQSicVi6A+Dsy1UK0QikUajgUYxsPGhUqlerxdOecHBwStXroR5dYh3oRplt9thDRwOB1w2YYscDgcuriBbkJWVBY6NeHps8eLFbrd7aGgoKCjoxIkTBoPh5ZdfnhYwUanU/Px8gUAwU/w6NzcXKu98Pv/pp5/2+XwCgQCsBY4ePdrf3w8d2VqtFkYOZybaRSKRQqEoKSnJycnBPdSysrIgxZuWlgZ5OBKJxOPxVqxYATE6fGVpaWl4rpRCoTz22GMmkwlPgF2/fh0Gbl555ZVLly7FxcWlpqb6NzOdPXs2Pj7+kUceAWmDDRs20Gg0m81mMBheeOEFOMJEInHVqlVdXV0z/d0cDseuXbsaGxtZLNZHH320dOlSyIniUf4jjzzyxRdfDAwM4BISixYt+t3vfnfgwIF9+/YJBILe3t4FCxasWbMGSrRcLvfFF1+EusncuXP5fP6jjz7a1ta2fft2Go22aNGihoYGkUi0dOnSxMTEaefeiIiI8+fPb9y4cfHixUuWLNm9e7dEIhkeHq6vr/d3ZRkYGLh27VpAQIBAIIA5vtzc3JSUFD6fX1xcXFBQIJPJ4J5Hp9M9/fTTc+fO3bRpk/+lF/rB33///eLi4qeeekoqlRoMBqFQeOTIEYVCoVar8brb+++/LxAIoqKifv/737/77rt//vOfIV0kl8ttNtu6dev897+srAymi1paWtLT0wkEwtDQUG1tbU5OTmdnp1qt3rZtW0FBwalTp1JTU2Ho76233lqxYsXChQunpqauX78+MjLidDrr6uqUSiWk2/V6fVNTE4jjQzfYBx98sG/fPqVSuWjRouvXr4NpaXFx8bp165YtW/b222/v3r1bLpfn5+f39fXp9frHH3/8ySefJJPJdXV1IyMjLperrq4uMjIS70ienJwEVS25XP7EE08cOXIkIyMDZg8hZGxpabFYLNXV1X19fSEhIYODg9/BP24mM1vf8Jt5POSAHizIo8Mp/eDBg08++WRDQwNp+/bt6KL7zwR6ZtFxQPwMgJQS8//wtxym0+kglYtLj8Lw/7TmevztM+2KqVQq/qx/YoBMJpPJZOjD889t4DsDnddwE++/WiijQ58E7Mm0NID/FvH2bXy1XC5XKBTiZ1sajQYtDiQS6Z133snPz5/mTg27GhERIRaLWSwWcwawaXz9arU6NDSUQqHs27dvcHBwyZIlYrGYRqMxGIzbWUaIRKKampqgoCClUgkBjUwmk8vlIGYIxlN4I61KpYqIiAgPD4fmQv/jplar4+PjoT0RsoyRkZHz5s1bvHhxWFiYXC7Hoyu8ej537tz58+fD5kJCQohEYmdn57Fjx55++mmQuyQQCGq1WqvVSiSSmfeHBAIhMTFx7ty54eHhCoViWuKTSqWqVKr58+fHx8fDIaXRaGq1Oi4uTq1WKxQKmDXDr74kEkmJNqbhAAAcEElEQVQikWg0mszMzJycHJFIFBwcrNVqh4aGPB4PmUz2eDzz588PDw+faSUrFAonJiZIJNLSpUvdbndtbe2qVavcbrfdbofoyuv1dnd3BwcHu93urKwsFovlcDikUumjjz4KprlhYWEpKSnwEUJCQiCTmpeXN234HyxdHQ5HcHDw/PnzQRIvPj4+ISHB4XCAOoPNZgsLC/N6vTweLyIiIjIyMjo62uv1ghRzSkoKqLz6r/a3v/0t3D+IxWLwPLVYLN3d3WD2AhFJV1dXT0/P6OhoZ2dnW1vb6Ojoli1boqOjXS7XuXPnvF4vfGVCoRAOaX19fUdHh0Ag4PF4Pp+PRqNVV1dLJJLExESo1xsMBrAanD17NpPJFAgE4HYPhWCTyfTEE09oNBrII/p8PhC8FQqFEJANDQ1BVC2RSKAlvK+v7+LFi/Hx8aGhoXq9HtwMKRQKyJ6BaDCfzz9w4EBZWZlerw8NDaXRaDO7Kf4h0NrrL6154cIF/M/e3t7+/n7QdBgbG+NwOG1tbeHh4TAFiWEY4d7KtCMQCMQDhdvtPnz48Jw5c+6+U+fO7Nixo7a2dseOHf/QpgMMXnQ6HUgd3sc7scnJyW3btnm93jfeeOM7XMZ+ILq6uiBlSKFQbqeIMTk52dPT4/V6wdTIaDRKpVKYIIMxPa/X29HRAdN/SqVyZGTEbDazWCyJRAJd+ZAthvDX5XKBeAEo8E07DiaTyWg00ul0mUwG7joQK5vNZshBTkxMuN3usbExcGuGHYaLN1yzZzYkFRYWpqamEolEOp0O3dx2ux08ZKCfwefztbe3NzY2Tk5OgoFBcHAwiIl7PJ7Ozk48BsDXbzAYrFYrLKfRaBwOB/eF9AfWTyAQJiYm+vv7L168yOfzRSKRUCgE4Wy32w2aC9PWDxq8Pp9PIpGw2Wyz2Ww0Gi9duvTwww+D5nNzczOPx1MoFDKZrLe31263g71ESUnJ0NAQqPVGRkauXLnyO/zmdTrd7Nmz8cMIf5aVlanVahKJNDExoVQqJyYmPB4Pm80eHh6WSCSFhYW/+MUvjh8/jgImBAKB+O74fD673X43Rkx3Q3t7+7PPPtvd3f3v//7vt1OV9Kevr6+5uTk9PX1aEuifzM6dOxsaGjZv3pyUlPQ9J9EQ34rx8fGZabOZgMsehmF3SFh+T6xW69TU1Hdev/8HcTgckEj2X4/X6x0bG4PHRqORRCLBUNt32JDVaoXJOJBTDwgIuHnzpkAgYDAYXq+XRCJ1dXUplcqWlhZQQ6irq0tOTm5qakK/bAQCgfju4H1R94Tu7m6wVzKZTHfT7hoaGorLw95HmEzmpk2bULT0z+cuZSz+4Vz59+d7tpP6f5Bb7iqRSMSHpb7P1BSbze7o6ADDOHy7kZGR/sFlT0+PUqnU6/UajebSpUsJCQnt7e0UCgX9uBEIBOLHQkxMjEKhgJGru3Sp+zFQUFAA7VzoG0T8+JHL5dNisvPnz6vVapFIBGMiSqXS5XLB3ByLxSISiVByRQETAoFA/Fi45VDkj58fWosZgbiH4CPGPT09QUFBbDY7LCyMzWZ3dXVZLJbU1FSHw9HY2JicnAwzKwQCAW4G0LgWAoFAIBCIB46RkRG73Y5hWGRkJBiEgK6BQCAICQk5deqUz+cbGxvzeDwOh8PhcPz0MkwHDx5MS0uTy+XfKv1rtVrByOYu31VVVaXT6QYGBrKyshYuXHiXdeJ7C8xVTmt8w4FvEfv/JWoQCAQCgUDcDrfb7Xa7QfVNoVAwmUxQHwWTJYgWcH0vDMOkUimNRhOJRMePH//pZZguXbr0wQcfDA4Ofqt3vfvuu7t37wbJ87shJCREq9WWlpZWVlY6HI778kmPHTt2+vTpiYmJWz5bUlLypz/9adOmTf5zm9+TmzdvVlRUNDc34ybVCAQCgUD8bBgaGqqpqYHHfD6fwWD09/c3NDRMTU2Bw92ZM2fgWdC0bGtrczgcgYGBKSkpP72AKSMjQyaTfdtZDB6Pd0vPitsRGho6a9YsIpGIK//+82lra9uzZw/ofABXrlwxGo0wO5OYmMhgML7++muLxXKvtlhSUvL6669//vnn4+Pj6P8VAoFAIH5mgHWM/xIw5/Z6vZCIAfNdnU4HuRKlUunxeMrKymJiYu5nSc5ms9ntdrj8BwUFQRe62WwGWxx8idvttlqtDAaDTqeD44Hb7f62U4WgcPXTcqZbsmSJSqXCrQfr6ur+/Oc///a3vwWTqdjY2MjIyHs7R6PVaqlUqkKh+KEHUBEIBAKBuC8B07RIANycvF5vbGzsxMQEOE0FBQVRKBSn0wkDDVCtuz8Bk8vlAvF1o9E4ODjY0dFRUFCwbNmywMDA8+fP19TUtLe3v/7667GxsSQSqaysrKysbMWKFcnJySMjI11dXaA9CrFCb29vT08P+BeSSCStVjvN0xsYHh4mkUgcDgdSUx0dHQaDAXqAWCxWXFwcGEvdGbfbXVdXZ7PZ4M+wsDCwMsBf0NnZOTAwAKtlMBgJCQn+q62qqsLra1KpNCws7M7hTnJycnx8PK5c19XVVVNTAwKpP9D3kpaWlpSURCKRfkLzzAgEAoFAfFvMZrPFYgkLC8NNkMRicXl5eXR0NG4brNfr3W63UqmEP+9PwGSz2Y4ePZqQkJCWlmYwGCorK//+97+DWG1cXJzP59PpdCdPnpRIJAKBoKSkJCQkRCQSmc3mjz/++MKFC2FhYb///e8VCoXBYNi9ezedTpdIJGQyuaysrLu7e/ny5RwOB9/WzZs3dTrd0aNHo6Ojt27dKhaL29ra/vrXv4KNM/jmvPjii3fj9Xv69OmTJ08mJCSw2ezu7u4TJ06o1epVq1ZB7NnR0VFVVQU+1ZcvX+7v78/Ozg4MDOTxeEuXLq2vry8sLExKSuJwOF9++SWfz3/55Zfj4uIoFMpXX32l1+vj4+NjY2NPnTplMpmWLl0KB8Hr9RYUFMD6p6amIBRrb28nk8n4Do+MjOzbtw+KaLGxsRkZGRClTU1Nffnll3K5PCEhobi42Gw2Yxgmk8nmzZtHIpGOHDlisViYTOaKFSvwdB2VSj158iS4jeJafCMjI6dOnbJarRiGxcXFpaen301wiUAgEAjEj5bJyUm4rnV3d4+MjGi1WgKBAIaDGIbZ7fapqang4GCv1+v1eiHZcX8CJjqdvnDhQo1GIxKJnE7n5cuXz507B8LtGo1GJpPV1NQcO3aMRCLR6fTk5OTc3FyZTGaz2dLS0srLyzs7O+HF/f39o6Oj+fn50dHRZDL58uXLXC7XP+UDCSTwo6FSqZCIamlpKS0t/cMf/pCSkkIikc6cOXPx4sWCgoI7j8KdPXv2b3/727Jly3JychgMxvDw8Oeff/7pp59OTExs3LjR5/Pt3LlTpVLBSJ1QKNy2bRudTn/ssccgC3X16tVZs2ZlZWUxmcze3t5PP/102bJl4Lh+6dKlI0eOCIXChISEurq6sbGx8PDwioqKs2fPEonEOXPm8Hi8/fv3nzp1anx8fN++fRQKJS8vD9dr2b9///DwcG5urk6nO3z48JYtW/Ly8phM5vHjx/fu3evz+eLj42/cuGGz2Xw+X3h4uEwmq66uPnz4MLivm83mjRs3EgiEzz77rKurq66u7vnnn4eI2263f/nll6Ojo+Ay/eGHHxqNxvj4eBQwIRAIBOKnyL59+5588kkCgRAUFATNJwwGA299aW1txX21oSkI7Ic1Gs3x48fvW8AUHR0NjoCgD+vfjs1isTZs2NDX11dYWCiRSN555x0QEWCz2QsWLDh69Kher4dXOp3O1tbWsLAwPp+flJS0efNmuVw+zX1JIBDMmjWLx+PhTk92u91ut/f09KjVarVavXXr1sDAwH9YhLpx40Z7e3t6erparSYSiTKZjM1mV1VVVVdXr1692ufzXb58GYp0XC5XIpFwOBwGg5GRkSGVSqlUKrhMg/WgUCgEUQcori1duvSzzz7r7e1dsWKFSqWCGiqHw+nq6qqqqnK73ZDa6ezsLC0tjYuLi4mJUavVNBoNdiw7Ozs8PFytVqtUqg8++OCPf/xjYmJiREREVFRURETEoUOHZs+evXnzZgqFYrPZduzY8V//9V95eXlbtmzBMOyNN96oqqpas2YNn89PSUkZGRnR6/U1NTU5OTlMJrOioqKsrOyxxx6bM2cOnU4fHBzs7e2dmppC/+UQCAQC8VMEeroxP7sYPp+Pl1nCw8OhutLV1RUYGGg0Gj0ej9PpTE1NValU9ydgcjgc+/btGxkZUSqVZDJ55jU4Ojp6/fr1FRUVZrOZRCLhJUY6ne6vORQSEsLn8/fv319eXp6dnQ1iU9MsMEkkEoPB8A/IoqKiVCpVYWFhZWWlVquVyWT5+fl4/HFLent76+rqQBgJ1k8ikaKjo7lc7tTUlM/n8/l80KsOr4fIFDJkEMDFx8d//vnnw8PDGIaNjIz4u0RBq5NWq3344Ye5XK7H4+FyuVFRUefOnauvr4fXJCUldXR00Gi05OTk2bNn+2fR0tLS0tLSiERiSEhIc3PzBx98AEpc0dHRUVFRqampixYtSktLo1KpFovljTfewDAsMzNTJpMRicSWlpbi4uLGxsY5c+ZkZmZKpVKdTgf1TZPJdOTIkaioqOzsbC6XSyAQFi1a1NraivrBEQgEAvETJTk5Gb+sDwwMpKenk0ikK1euKJVKkUhkMBg4HE5AQEBkZCSLxSIQCF6vFy7Evb2990dW4NNPP62srMzIyJg3b15cXNxMR+6ioqK6urq8vDyHw/HJJ5/cTnVJKpW+8sorW7dunZiYKC4u/vDDD3ft2uU/h39L1Gr1a6+9tn79eoPBcPz48Z07dx44cABafG6H0Wjs6Oi4gzoRmUwOCQkpLS2tra3t6uo6fPgwl8tdvnw5JPomJib27NlTWloqFArVanVCQsLMjywWi9lsNpfLDQ4O/m4GliwWSywW47GU1+ttb2+Xy+VCodA/XgwJCQkICICwz+l0EolEPAYNCAjw+XwQU4+OjlZWVgoEAjqdDs8KhULUwIRAIBCInwFMJhP3SAkODoaLMv6gqalpfHycTqczGIzExES4dN6fgKmiomJoaIjH48lkMq/XOzQ0BN1FgMFgOHnypEwme+GFF1atWlVdXV1fXw9NS9Ow2+1CoXDlypV/+tOf/vCHP/D5/Orq6tspPeKMjY0plcoNGzb88Y9/fPPNN91ud319/Z3VKRUKRWpq6h1iBR6P9/zzz3s8npKSksOHD09NTb3yyisLFiyAt1y+fHn37t3z589fsmTJ3Llz5XL5P8HTG0zUjUaj1Wq9ne15ZmYmlUrFtaYaGhqsViuk9Dwej9Vq9U/+0Wi0wMBA5K+JQCAQiJ86XC7X5XKZzWafzxcZGQlaAyqVCpq+lUoli8Xq7e3V6/VsNvv69evR0dH3J2DKzc0dHR3dtWvXO++8c/DgQaPRODY2dvny5bGxMbPZ/Le//Y1AIGi1Wo1G88tf/hLDsI8++qi6unpmgqe7u7uqqsrj8WRnZ+fl5YnFYqiO3XnrDQ0Nzc3NDAbjoYceysvL43A4Xq/3zu/i8/lyudzr9X799ddjY2OwEHY4KyuLzWZD15jZbI6JiZkzZ05OTs7s2bOhYwnDsP7+foPB0N3d7fP5qFRqaWkpvpIfNGCSSqUmk+kOAVNXV5fRaDSbzRAYRUZGstlsGo2GFz3PnTs3Ojp6v6Q7EQgEAoH4ISASiWCKgmEYmUwmEokEAuHixYtQpOru7nY4HEKhMCQkZGpqamJiorS09P70MD3yyCMWi+XUqVNsNjspKSk6Ovqvf/3rmTNnIiMjm5qajEbjE088IZPJCARCaGjoM8888/e///3TTz8VCoV0Ot1qtVoslhMnTqxZs6aoqMjhcISHh1ut1oqKirGxsSeffDI4ONh/WzabbXR01G63t7e3l5SUrF692mQymc1mkUgUGBh45swZHo+3fPnyaUqYY2NjRqMxICDAbrf39vZyudzFixdfvXq1uLiYQqE89NBDTCazsrJy9erV+fn5bDbbYrEcPXq0u7u7qKjo4sWLeMCxZMmSJUuWzJ49e8GCBUVFRTdv3pRKpVB3KykpSUxMjI2NhVdaLBaHw+H1eqf1YE3DYDDo9Xo4FBaLBb7sW+L1eq9cucLhcO4gcS6TycbHx4eGhmA9dDrd5XJ1dXW5XK6QkJDly5cfPny4sbGRwWAIBAIwIARL548++ignJ2f+/Pm4+gACgUAgED8hwsPDoX353LlzGo1GKpVKpVLo05VKpXQ6ncViFRcXZ2ZmajSagYEB0vbt2//5e8lisVQqVWJi4kMPPaRSqcLDwzUaTVJSkkql4vP5GRkZycnJTCYTwo7w8HDQKAoKCtLpdEajccGCBSaTSS6XMxiMkZGRoaGhzs7Otra2uXPn5ufnBwUF+TvR9vb2lpeXW61WEGeKj4+H5p6enp6Ojo62trbHH3987ty5AQEB/u9qbW2tqKiIj493u92jo6NqtVoul6vVaqFQ2NPT09fX19HRIRKJFi9eLJVKyWSyw+E4ffr01NQUm832er0ul8vlcoEE1Ny5c6OiojQaTX9/v1gszszMzM3N5XA4Go1mcnJSJpM1NTU1NDSMj48zGIzIyEgajeZ0OnU63dmzZ5lMJofDYTKZbDbbarVeuXLl6tWrjY2NCoWitrb27NmzQ0NDoaGhdDqdy+WSyeSRkZGKigqRSESn0zs7O3fv3t3f38/n8+Pj4/v6+iorK0+cOMFkMlksllwup1KpFAqlsLAQ+uKJROInn3xSWlrq9XrZbLZSqWQymWNjY+fPn29tbR0fH6+urm5tbY2IiBgfH/+f//kfo9GYnZ19S5lQBAKBQCB+5NBoNLyFl8vl0mg0+JdAIPB4vNraWkjcBAcHBwYG9vT03J8ME4FAEIlEIpEIX5KSkgIPZgpIBgUFZWdnYxhmt9vT09MTEhJCQ0ONRqNQKIyKioqJicFLdQqFAq+C4QgEAojA4E+hUMjlcoVCIXRN5eTkQKly2rukUimFQhEKhUaj0e12s1gsEomUlJQUGRnZ29sL7xWLxQKBAJI3R48eHR8ff+6550CLElZSUlLyl7/8xWazEQiE2NjYV155hcFgQF/26tWrYWyNTqd7vd7nnnvOZrPhneA+nw8+bFRUlN1uh83FxsZu2bKlpaUlJCREKpUajca8vLzs7Gw2m403IaWlpb300ktkMtnpdLpcrg0bNthsNtC9dLlcU1NTGzduBA14KNJxOJxnn32WTCZ7vV632y0Wi3/5y1+y2WwYDUhNTQ0NDT158iSRSIR9EIlEZDI5NDT0+eefp9PpKFpCIBAIxE+diIgIePD111/Hx8fDpBR0TqvV6s8//3zt2rVut5uA2lPuCatWrfJ6vW+99ZZSqcRravv27fvNb35z6NAhGFy83XstFguVSvX5fE6nMzAwEHQWRkdHPR4Ph8Ox2WwMBoPFYhGJRKvVarfbofnabDZDoONyueh0OpvNhk1AaY/JZHo8HpfL5fP5CASCQCBwOp0TExMQJxGJRIFA4L8hEonEZDJB2xQPNCkUCoFAgJARTw0GBASQSCSbzUYikfy7nRAIBAKB+GlRWFi4fv16/ELW1tYmFArtdntISIjJZOLxeAQCoba2VqvVms1mMjpe9yo+vXbt2sjICO4QNz4+3traqlKpIGFzh/fiGqN4PxCJRMK9bPybhPxdAwUCwe3Whq/QHwqFMjMh5L8hDMNuqXU+rSds5l4hEAgEAvGT4NKlS9nZ2fhFOSEhwX+5Uql0Op1XrlwBXcPs7Oza2trIyEgMw7hcLgqY7g3r16+fnJzcu3fvN998s379+traWp1O19bW9qtf/So0NBSlYRAIBAKBuO/gBRMgKSnJfzmRSKRQKDExMfiSqakpIpFYX19PAJ8UdAS/P1NTU62trf39/U6ns7m5WSQSBQcHs1isuLi4oKCgOw++IRAIBAKB+CfQ19dHpVKDg4MhkYGX5EwmE5fLHRoa4nA4INcMS6xW6+joKCxBGaZ7AzilaDQah8MRHBwcEhIiFouh/R6llxAIBAKB+DFAJBL1ej3eaoKX5GA6qqOjIzw8vKenJzMzs6GhYc6cORwO5+uvvwaxbxQw3TMgNmKxWBkZGehoIBAIBALxY4PD4eAzWD6fDyIhXIcpMjKSyWRC5Q2vv+FBFSoVIRAIBAKBeCBgsVgikQgqP+Xl5b29vRiGRUREwEBVSEgIm80GQenY2Fh4VqfTicVisViMAiYEAoFAIBAPHGFhYaBoDQETRFFut7uhoQHDMCaT2dbWhmFYYmIig8FgMBioJIdAIBAIBOLnD4gOYhiG+4hgGNbR0TE0NJSVldXW1mYymZKTk0GkkEKhREdHYxgWFxdXX1+PoZIcAoFAIBCIB4GDBw/ONGDl8XgymQzDMD6fHxoaSqVSY2JiSktLLRaLRCLBMOzAgQMikQiV5BAIBAKBQDwQxMfHg8rPuXPn8J5uHo8nl8vBEmNoaMhisbDZbJVKxWKxurq62tvbExMT/9/kOzqCCAQCgUAgHoSACR7QaDQMw9xuN5FIJBKJHo8HHlCpVIio2traAgMDoX4XFxcHbqoow4RAIBAIBOIBAgS+KyoqBgYGMAzT6XSDg4MYhimVyv7+fgzDIMNEoVAoFMr4+PhXX3115swZFDAhEAgEAoF4gACP12lTchiGMZlMvV6PB0w2m218fJxGo6nVao1Gg6xREAgEAoFAPNDgHil9fX1SqfT06dOpqal0Ot3r9VKpVCaTOTk5iTJMCAQCgUAgHjh6e3utViukjUDOu7u7m8vlYhimUqkoFMrQ0FBQUNCxY8cwDCstLUUBEwKBQCAQiAeCwcHBmpoaCJKGh4ftdjssT0pKIhAIBoNhcnISAiYajdbX14dhGNinaDQaFDAhEAgEAoF4IKBQKEwmEx7jPUwOh8Ptdvt8PqVSGRAQ0NzcfPXqVSqVCsKV1dXVGIY1NjaigAmBQCAQCMQDAYfDAYFvDMP4fD6DwSAQCN98883w8DCGYVar1e12CwQCqVQ6NTU1NjaGYZharW5ra1Or1ShgQiAQCAQC8UBAJpPpdDpYo+DgU3JGo9HpdAYHB0PAZDAYMAyLi4sbHByMjo5GARMCgUAgEIgHC71ef+HCBWhm4vP5dDodwzAoyblcLofDQSaTQ0NDMQyjUChSqRRDwpUIBAKBQCAeNIKCghQKBTyurq42Go0YhpnNZpfL1dXV1dzc7HK5WlpaMAxzOp2tra0oYEIgEAgEAvHAweVyBwcHDQaDz+fDS3Imk8nlckFJDm/6ptFoGo0GyQogEAgEAoF4EOHxeFCJk8lkAQEBBAJBqVS63W4ulysSiSYmJiIiIk6cOAEPhEIhCpgQCAQCgUA8cOCyAhiG1dbW+nw+Ho934cIFWFJaWophmFqtJhKJjY2NSIcJgUAgEAjEz5zDhw9Df/fAwEBFRQU8plKpPp/v2LFjPp9vZGQEXpmcnOz/QK1WUygUs9lMo9FQwIRAIBAIBOLnjEwmgwcMBiM4OBhfTiAQ4KmkpCQMwywWS1hYWFNT09WrVyMiIkwm04kTJ+x2e3R09NGjR/8XNiYRbVkGFmgAAAAASUVORK5CYII=
[[Random graph]] models capture well the small-world properties of real networks (see [[Large-scale structure of networks]]). The mean geodesic distance grows like $$\ln{n}/\ln{c}$$, that is, much more slowly than $$n$$, the number of nodes.
However, they don't capture the high [[transitivity|Transitivity (Graph theory)]] (i.e. high clustering coefficient) of real world networks (where nodes which are neighbours of the same node are more likely to be neighbours of each other, specially true in social networks). One can easily construct models with high transitivity, like the triangular lattice, or the "circle model" where each node is connected to $$c$$ closest nodes, but these don't have small-world properties.
[img width=200 [circle_model.png]]
The ''small-world model'' is a hybrid of the two, so that it displays both high transitivity and short path lengths. It was proposed in 1998 by Watts and Strogatz. The model (Watts-Strogatz version) works by //rewiring// existing edges in a random fashion, becoming so-called //shortcuts//. Another version (Newman-Watts), that is easier to analyze analytically, doesn't rewire edges, but simply adds them (often, we add one, with probability $$p$$, per edge in the circle model network).
[img[small_world_model.png]]
__Degree distribution__
It is a Poisson distribution (in the limit of large $$n$$ I think, right?), just like the random graph. However, it is cutoff at $$c$$, as we don't remove the original circle-model edges.
__Clustering coefficient__
Compute by counting triangles, and triads..
__Mean shortest path__
No exact formula known, but we know scaling of the mean shortest distance, $$l$$:
$$l\approx \frac{n}{c}f(ncp)$$.
which comes from scaling argument...Approximate form for $$f$$ can be found by mean-field methods.
------
One can see that there is a wide range of values for $$p$$ so that the network exhibits both high clustering and small mean shortest distance, showing that these are not at all incompatible.
[img [small_world_model2.png]]
The conclusion from all this is that:
|A network doesn't need that many shortcuts to have scaling of the geodesic distance that is $$O(\ln{N})$$, instead of $$O(N)$$, i.e. to be a "small-world"|
__Simulating in Matlab__
[[This page|http://uk.mathworks.com/examples/matlab/12163-build-watts-strogatz-small-world-graph-model]] explains how to simulate the code in Matlab.
[[Lung cancer]], [[Smoking]]
Restrospective cohort study.
[[SMOKING AND CARCI NOMA OF TIE LUNG|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/pdf/brmedj03566-0003.pdf]]
* ''Rapid increase in the recorded deaths by lung cancer'' between the 1920s and 1940s. Improved diagnosis probably not the only reason. Other factors must be sought.
* ''Hypotheses: smoking and atmospheric polluation''. Some suggestive evidence for smoking as a causal factor over the decades before 1950s, looking at simple statistics of relatively small groups. A larger-scale study was done by Wynder and Graham, giving stronger statistical evidence.
* Study in [[paper|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/pdf/brmedj03566-0003.pdf]] looks at carcinoma of lung, stomach, colon and rectum, with reports from hospitals in London. 1732 cancer patients, and 743 controls.
* The patients were interviewed to identify their smoking history. See "Assessment of smoking habits" section.
* Several measures of smoking amount correlate significantly with carcinoma of lung. low p values.. using [[Chi-squared test]]
* Smoking pipes appears to have somewhat lower risk. Inhaling doesn't appear to have an effect..
* Arguments against possibility of biases producing the results are put forth. The biases considered are:
** Unrepresentativeness of sample, due to location, disease, or selection by interviewers. Statistics doesn't support this.
** Exageration of smoking habits by carcinoma patients. Patients didn't know they had carcinoma and other respiratory diseases with similar symptoms same smoking as control.
** Exaggeration by interviewers, who unfortunately could not be blinded of the disease of the patient. This was discarded by looking at the records of patients that were intervened while having carcinoma of lung diagnosed, only to later discover, they didn't have carcinoma of lung.
* Estimates of relative risks are done using effectively [[Baye's theorem]] I think.
* Some arguments supporting that the development of carcinoma is the same in women and men, apart from their differing smoking habits.
* Time dependence between number of carcinoma of lung deaths and smoking is unclear. Maybe masked by improved diagnosis. Maybe the carcinogen is affected by the production methods which have changed over time.
A two-step [[Substitution reaction]]
A one-step [[Substitution reaction]]
[img[https://s12.postimg.org/jtfcwia19/ezgif_com_crop_2.gif]]
https://www.wikiwand.com/en/Social_class
[[Social system]]
[[Statistical physics of social dynamics|http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.81.591]]
[[Influence maximization in complex networks]]
__Social contagion processes__
See [[Complex contagion]]s
__Opinion dynamics__
[[ Opinion dynamics: models, extensions and external effects|https://arxiv.org/abs/1605.06326]]
[[The Science of Awkwardness|https://www.youtube.com/watch?v=o268qbb_0BM]]
[[The Science of the Friend Zone|https://www.youtube.com/watch?v=IGK2KprU-To]]
Study of societies.
Societies are complex systems of complex beings; in particular animals, and humans. The behaviour of the individual beings is studied in [[Behavioural sciences]]
https://en.wikipedia.org/wiki/Social_science
See https://en.wikipedia.org/wiki/Social_anthropology for human societies.
Social science and engineering is included here.
[[Wikipedia's contents: Society and social sciences|https://en.wikipedia.org/wiki/Portal:Contents/Society_and_social_sciences]]
https://en.wikipedia.org/wiki/Social_system
[[Social dynamics]]
[[Economic system]]
See [[Society & sociology]]
https://en.wikipedia.org/wiki/Community
<mark>Plotch (watch+play) this: http://ncase.me/polygons/</mark>
<small>Sociocyberneering</small>
<mark>__Societal structure__</mark> (characteristic of [[Civilization]])
societal organization:
* [[Infrastructure]],
* [[economy|Economics]],
* governance (see [[Politics]]),
* [[Culture]].
[[bouchard_1990-Twin studies about psychological similarities dependence on genotype|http://www.d.umn.edu/~jetterso/documents/ScienceMNTwinStudies.pdf]]
* Simple liquids (fully homogeneous/isotropic). See [[Fluid mechanics]]. The fluid may be a [[solution|Solution (Chemistry)]], but that only changes it [[chemical|Chemistry]] properties, not its physical ones.
* Several types of [[complex fluids|Complex fluid dynamics]]. Main types:
** Solid--liquid ([[Suspension]]s (particularly [[Colloid]]s) and [[Gels]])
**solid--gas ([[Granular material]]s, and [[Fibrous material]]s)
**liquid--gas ([[Foam]]s)
**liquid--liquid ([[Emulsion]]s)
*[[Liquid crystals]]: nematic, smectic, cholesteric, columnar, etc.
* Several [[polymeric|Polymer]] materials are soft. E.g. some [[Plastic]]s, [[Rubber]]s, [[Latex]]
* [[Surfactant]]s
* [[Biological matter]]
* Many kinds of [[Active matter]] and [[Driven matter]].
* [[Pastes]], or [[soft glassy materials|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.78.2020]]
''Soft condensed matter'' (often abbreviated to ''soft matter'') is basically all forms of [[condensed matter|Condensed matter physics]] (i.e. many particles more or less bound together (for e.g., by [[Intermolecular forces]])) that isn't a solid, so that it has features that are easily deformable at low energies (room thermal energies).
This includes [[polymers|Polymer physics]], [[Liquid crystals]], [[complex fluids|Complex fluid dynamics]], [[Granular material]], [[Foam]]s, [[Emulsion]]s, [[Colloid]]s, and many kinds of mixtures, that form mesoscopic structures. Also a lot of stuff in [[life|Biology]] falls under the "soft" category. I like it precisely because of its richness.
Wiki: https://en.wikipedia.org/wiki/Soft_matter
__Typial features__
*Mesoscopic lengthscales
*Fluctuations ([[Brownian motion]])
*[[Self-assembly]]. [[Block-copolymer self-assembly]]
[[Statistical physics]] is important, in particular interplay of energy and entropy, reflected in the free energy.
For systems of many particles, one uses [[Statistical field theory]]. Though one can further simplify by ignoring fluctuations, using a [[Mean field theory]].
__[[Soft materials]]__
{{Soft materials}}
A fruitful way of studying phases, is to study the [[phase transitions|Phase transition]] between them.
Universality, coarse-graining, renormalization group. [[Percolation]]
------------
[[Introduction to soft matter physics - 1 by David Pine|https://www.youtube.com/watch?v=kvDxOhEVvpQ&index=26&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]]
[[Thomas Speck|https://scholar.google.co.uk/citations?hl=en&user=u2KmUD0AAAAJ&view_op=list_works&sortby=pubdate]]
A [[Layers for deep learning]], that consists on exponentiating all vector elements and normalize them to so sum to unity.
$$\mathbf{\sigma}(\mathbf{y}) \equiv \frac{e^\mathbf{y}}{\sum_i e^{y_i}}$$
where the mathematical operations are element-wise.
A [[Classification]] learning algorithm, that generalizes [[Logistic regression]] to $$k $$ classes. See [[Generalized linear model]] multinomial dist. example.
__Keylogger__
//Simple keylogger//
To open the keylogger log (which is very long), get part of the log only, using ``tail``: http://www.computerhope.com/unix/utail.htm
``cd /var/log/``
``tail -c 10000 skeylogger.log ``
//How to parse the output//
https://gist.github.com/kelly-ry4n/44822005a02d9ff115c12e4075adb256
https://www.facebook.com/groups/hackathonhackers/permalink/1232180336837449/?comment_id=1232200533502096
See also [[Programming]]
-------------
[[Performance Engineering of Software Systems|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-172-performance-engineering-of-software-systems-fall-2010/]]
----------------
__Software system engineering__
[[Operating system]]
[[Concurrent computing]]
__[[Web development]]__
__Mobile app development__
https://appetize.io/
--------------------
http://codeschool.org/
https://en.wikipedia.org/wiki/Code_reuse
[[Deep learning on the browser]]
[[Torch|http://torch.ch/docs/getting-started.html#_]], [[TensorFlow|https://www.tensorflow.org/]] , [[theano|http://deeplearning.net/software/theano/]], Keras, Lasagne, MatConvNet. Caffe ([[Caffe on windows|https://github.com/BVLC/caffe/tree/windows]]). [[Deeplearning4j|http://deeplearning4j.org/?utm_source=Reddit&utm_medium=CPC&utm_campaign=DL4J]] (Java, Scala..)
GoogleLeNet. [[github|https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet]] in caffe.
[ext[VGGnet|http://www.robots.ox.ac.uk/~vgg/research/very_deep/]]
[[Deep art]]
https://en.wikipedia.org/wiki/Software_verification_and_validation
[[wiki|https://en.wikipedia.org/wiki/Solar_power]]
[img[http://www.solarbuildingtech.com/Solar_PV_Tech/Images/PhotoVoltaic-solar-panel-working_princple.gif]]
[[Solar Roof|https://www.tesla.com/solar]]
Tesla
The Solar System is the [[Planetary system]] containing [[Planet Earth]] and the [[Sun]]
https://en.wikipedia.org/wiki/Dream_Chronicles
Yoshitaka Amano
Final fantasy
A condensed phase of matter characterized by elastic resistance against deformation. See [[Condensed matter physics]].
A large variety of [[Mineral]]s in [[Geology]] are solids at [[Room temperature]]
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Am%C3%A9thystre_sceptre2.jpg/640px-Am%C3%A9thystre_sceptre2.jpg]]
A solid material is a [[Material]] that is [[Solid]] at [[Room temperature]].
See Simon's solid-state physics book, and his Oxford lectures (recorded).
__How many watermelons per unit cell?__
[img width=300 [water_melons_cmp.png]]
watermelons = atoms.. BTW picture shown isn't really a unit cell, but the same method of counting atoms is used for actual unit cells.
Solubility is a measurement of how much of a substance will dissolve in a given volume of a liquid.
See [[Solution (Chemistry)]]
http://www.bbc.co.uk/education/guides/zrr2pv4/revision
A [[Dispersion (Chemistry)]] where the dispersed phase has particles in which all dimensions are smaller than approximately one nanometer (so that they aren't [[colloidal|Colloid]]).
https://en.wikipedia.org/wiki/Solution
a solute is a substance dissolved in another substance, known as a solvent
!!__Regular solution model__
See [[Thermodynamics of liquid-liquid unmixing]]
See [[Chemical potential]]
[[The solution-diffusion model: a review|http://www.sciencedirect.com/science/article/pii/037673889500102I]]
--------------
http://www.bbc.co.uk/education/guides/zgbqtfr/revision
If the solute is white (eg sodium chloride) then the solution is colourless. This is because the white colour is due to the scattering of light alone, without absorption of any wavelength.
If the solute is coloured (eg blue copper sulfate) then the solution will have a colour.
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
[[Pressure]] [[Wave]] in a [[material|Bulk matter]]. Sound waves most often refer to pressure waves in the regime of linear dispersion relation. However, people just refer to any pressure waves that we can perceive with the [[Auditive system]].
__Science and engineering of sound__
[[Acoustics]]
[[Sound visualization]]
__Some common sounds__
[[Voice]]
[[Music]]
[[Natural sound]]s
Sounds of the [[Second nature]]: industrial sounds, sounds of the city, computer sounds
[[Spectrum]] -- [[Spectrogram]]
[[Lissajous curve]] -- [[Cymatics]]
The average length of a [[code|Coding theory]] is bounded below by the entropy of the random variable that models your data.
See [[Data compression]]
[[Source-channel separation|https://www.youtube.com/watch?v=ydzIhYbG3XI&index=4&list=PLE125425EC837021F]]
[[The source-channel separation theorem revisited|http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=370119&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel3%2F18%2F8485%2F00370119]]
[[Mars collonization]]
[[Space innovation]]
!!!__[[Breakthrough StarShot|http://breakthroughinitiatives.org/Initiative/3]]__
[img[http://breakthroughinitiatives.org/i/image3.jpg]]
Breakthrough Starshot aims to demonstrate proof of concept for ultra-fast light-driven nanocrafts, and lay the foundations for a first launch to Alpha Centauri within the next generation. Along the way, the project could generate important supplementary benefits to astronomy, including solar system exploration and detection of Earth-crossing asteroids.
[[Engineering challenges|http://breakthroughinitiatives.org/Challenges/3]]
http://www.transplanetary.com/
[[Space exploration]], [[Mars collonization]]
The study of [[Outer space]]
[[Karman line|https://www.wikiwand.com/en/K%C3%A1rm%C3%A1n_line]] defines the conventional barrier between [[Earth]] and [[Outer space]]
https://en.wikipedia.org/wiki/Outline_of_space_science
http://cosmos-book.github.io/contents.html
An ''spanning cluster-avoiding process'' (SCA) is an [[Explosive percolation]] model based on classifying bonds between those that facilitate the creation of the spanning-cluster, and those that don't, and preferentially selecting those that don't. They are similar to [[Achlioptas process]]es ($$m$$-edge processes). However, they don't require the candidate edges to be chosen at random between any pair of nodes, and instead the candidate edges can belong to a predetermined underlying network, common a hypercubic lattice. They are capable of showing discontinuous transitions, [[for certain choices of the number of candidate edges chosen per step|http://science.sciencemag.org/content/339/6124/1185.full]]
The most common spanning cluster-avoiding process (introduced [[here|http://science.sciencemag.org/content/339/6124/1185.full]]) starts by considering a finite hypercubic lattice $$\mathbb{Z}^d$$ in $$d$$ dimensions of size $$N$$ and unoccupied bonds. Then, inspired by the best-of-m model ,,(see [[Tricritical Point in Explosive Percolation|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.106.095703]]),,, the rule of the mode is as follows as follows:
# At each time step t, number of m unoccupied bonds are chosen randomly and classified into two types: bridge and nonbridge bonds. Bridge bonds are those that upon occupation a spanning cluster is formed.
# SCA model avoids bridge bonds to be occupied, and thus one of the nonbridge bonds is randomly selected and occupied. If the m potential bonds are all bridge bonds, then one of them is randomly chosen and occupied.
# Once a spanning cluster is formed, restrictions are no longer imposed on the occupation of bonds.
[[Getting the Jump on Explosive Percolation|http://science.sciencemag.org/content/339/6124/1159]]
[[Avoiding a Spanning Cluster in Percolation Models|http://science.sciencemag.org/content/339/6124/1185]]
These models were introduced to clarify the order of the transition in explosive percolation processes in Euclidean lattices, which had been studied numerically before: ,,[[Explosive Growth in Biased Dynamic Percolation on Two-Dimensional Regular Lattice Networks|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.045701]] -- [[Scaling behavior of explosive percolation on the square lattice|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.82.051105]],,.
Extensive numerical simulations and theoretical results have shown that the explosive transition in SCA model in the thermodynamic limit, can be either discontinuous or continuous depending on dimension the number of potential bonds $$m$$ (see [[here|http://science.sciencemag.org/content/339/6124/1185]], [[here|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.106.095703]], and [[ Two Types of Discontinuous Percolation Transitions in Cluster Merging Processes|http://arxiv.org/abs/1404.4470]]).
The property of there being much fewer things than there could be. Formally, given a collection of sets of different cardinalities, if the smallest ones are much smaller than the largest ones, then they are called //sparse//. ,,"smaller"/"larger" referring to cardinality,,
In [[Matrix]] theory, a <b>sparse matrix</b> often refers to one with few non-zero entries.
In [[Signal processing]] a <b>sparse signal</b> often refers to one which has few non-zero [[Fourier components|Fourier coefficient]]
A ''spatial networks'' is a network that is embedded in some space. This affects our choices of models for random graphs. An example is the [[Planar network]].
Explicitly embedded in space vs. consequences of (implicit) system being embedded in space. For example, network of borders of countries vs. friendship network..
Barthelemy's long review (my Kami file, not sure if it'll work: [[here|https://web.kamihq.com/web/viewer.html?source=filepicker&document_identifier=aoK0luc5BjL3p%2FM0M3KZ7E462JJQ1SiCuceZaDP0qnM&filename=1010.0302v2.pdf]]) Otherwise [[link to original|http://www.stat.berkeley.edu/~aldous/206-SNET/Papers/barthelemy_survey.pdf]]
[[Lecture notes|http://www.stat.berkeley.edu/~aldous/206-SNET/]]
* ''Euler's formula'', $$N - E + F=2$$ already gives many constraints to planar graphs
* ''Voronoi tesellations''
* ''Degree distributions'' (see [[degree|Degree of a vertex (Graph theory)]] can be heterogeneous (like for airline or internet networks). However, more strong spatial constraints can make degree distributions very homogeneous, or even highly peaked, like for road networks. (Dual graph may still have heterogeneous $$p_k$$).
* Spatial networks often have high ''clustering coefficient'' (see [[transitivity|Transitivity (Graph theory)]]), due to closer nodes being likely connected among themselves.
* Spatial constraints usually imply neutral ''assortativity'' (i.e. neither positive or negative [[assortative mixing|Assortative mixing]]).
* ''Spectral graph theory'' has applications to things like stationary states of a random walk and synchronization properties.
* In a lattice, ''betweeness centrality'' depends mostly on spatial position, and is peaked at the barycentre. //Shortcuts// create //anomalies// in this pattern.
* For ''weighted'' spatial networks, an important measure is the correlation of [[strength|Degree of a vertex (Graph theory)]] or //distance strength//* ($$\sim$$ geometry) and [[degree|Degree of a vertex (Graph theory)]] ($$\sim$$ topology) . * //Distance strength// is the sum of the Euclidean distances between a node and its neighbours.
* ''$$\alpha$$ and $$\gamma$$ indices'' measure things like density, or "meshedness". Also have "ringness".
* ''Detour index'' is ratio of route distance (distance actually following the network) and Euclidean ("straight line") distance between two nodes. The ''accesibility'' is the average of the the detour index for paths leading to a node, measures how easy it is to go to that node. Related to //straightness centrality//. See [[this paper|http://arxiv.org/pdf/1003.3700.pdf]].
* ''Cost'' and ''efficiency'' optimization can determine the structure of a network. Cost can be associated with the total length of the network (compared with the minimum spanning tree), and efficiency may refer to //transport performance// (measures mean shortest distance), or //fault tolerance// (probability of staying connected when removing a node, or an edge).
* ''Community detection'' appropriate to spatial networks is an interesting problem. [[Paper|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2151742/]] that may be interesting according to review, to try to apply to spatial networks.
* ''Motifs'', subgraphs which are found more often than would be expected (by null random graph model).
__Empirical observation__
Two kinds of spatial network topologies:
* ''Planar networks''
* ''Non-planar spatial networks''
Measure strength, clustering coefficients, and betweeness centrality, and their ''correlations'' with degree. Also assortativity. Assortatitvity is flat (i.e no degree-degree correlations) because while often hubs want to preferentially connect to hubs, they can't if spatial constraints don't allow such long (in average) links.
* Larger clustering because close nodes will connect among themselves more.
Anomalies in ''betweeness centrality-$$k$$ correlation''. Fluctuations (for given degree) because of competition of spatial constraints (that want central nodes close to the spatial network barycenter) and degree.
''Topology-traffic correlations''. Nonlinear correlations between non-topological quantities (like strength and distance strength) and topological quantitiy (degree). A superlinear relation of the strength and degree indicates that links connecting to central (high-degree) nodes carry more traffic than average. Spatial constraints tend to cause this because they tend to reduce the number of high node hubs (as long links are costly). However, if the traffic stays the same, it must be distributed among the lesser-degree hubs, and so the increase of traffic with degree is faster. See page 45 of review. This is seen in //strength-driven preferential attachment with spatial selection//, in //airline networks// (and the Newman model that models them), in OTT (optimal traffic tree),
''Real-world networks''
* ''Transportation networks''
* Infrastructure networks
* Mobility network. Analyzed using ''origin-destination matrix''
* ''Neural networks''
__Models for spatial networks__
''Geometrical random graphs''
* simplest geometric random graph. Nodes randomly distributed on plane, and they link if they are close enough.
* Random geometric graph in hyperbolic space. Gives power law deg. dist. Related to the structure of the internet ''!?''
* Scale free network on a lattice. See the paper. Basically given degrees (like configuration model right?), we then connect nodes on a lattice, giving preference to neighbours, or closer nodes.
* ''Apollonian networks''
''Spatial generalizations of the Erdos-Renyi graph''. [[Random graph]]
* ''Planar Erdos-Renyi graph''
* ''Hidden variable model for spatial networks''. ER graph but probability of connecting depends on fitness, and on distance
* ''Waxman model''. Nodes uniformly distributed in space and connect with probabilty depending on distance (exponentially).
''Spatial small worlds''. The [[Watts-Strogatz model|Small-world model (Network theory)]] in a d-dimensional lattice, and where the probability of making a shortcut may depend on its length (spatial constraint).
''Spatial growth models''.
* ''Preferential attachment with distance selection''
* ''Growth and local optimization''
''Optimization of spatial networks''
* ''Hubs-and-spokes'' structure appears in either
** the ''hub location problem'', where the cost of paths is basically given a priori.
**or when optimizing both the total length and the travelling time (and the waiting time matters). This is the Newman et al model.
* From the ''minimum spanning tree'' to the ''shortest path tree''
** The ''Steiner problem''
* //Adding two antagonistic quantities//
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[[Streets tree networks and urban growth: Optimal geometry for quickest access between a finite-size volume and one point|https://www.researchgate.net/publication/223616901_Streets_tree_networks_and_urban_growth_Optimal_geometry_for_quickest_access_between_a_finite-size_volume_and_one_point]]
The geometric form of the tree network is deduced from a single mechanism. The discovery that the shape of a heat-generating volume can be optimized to minimize the thermal resistance between the volume and a point heat sink, is used to solve the kinematics problem of minimizing the time of travel between a volume (or area) and one point. The optimal path is constructed by covering the volume with a sequence of volume sizes (building blocks), which starts with the smallest size and continues with stepwise larger sizes (assemblies). Optimized in each building block is the overall shape and the angle between constituents. The speed of travel may vary from one assembly size to the next, however, the lowest speed is used to reach the infinity of points located in the smallest volume elements. The volume-to-point path that results is a tree network. A single design principle – the geometric optimization of volume-to-point access – determines all the features of the tree network.
[[Mathematics and morphogenesis of cities: A geometrical approach|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.83.036106]]
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[[Extracting Hidden Hierarchies in Complex Spatial Networks|https://www.youtube.com/watch?v=BTYMqiemQR4]]
[[See notes|Notes on Extracting Hidden Hierarchies in Complex Spatial Networks video]]
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http://named-data.net/wp-content/uploads/2010HyperbolicGeometry.pdf
__Hyperbolic geometry__
http://arxiv.org/pdf/math-ph/0112039.pdf
http://www.math.miami.edu/~larsa/MTH551/hyplect.pdf
http://www.alcyone.com/max/reference/maths/hyperbolic.html
http://math.oregonstate.edu/home/programs/undergrad/CalculusQuestStudyGuides/vcalc/surface/surface.html
http://eprints.soton.ac.uk/172655/1/2009_PIRT_Barrett.pdf
https://www.math.brown.edu/~rkenyon/papers/cannon.pdf
http://www.springer.com/gb/book/9789048186365
[[Spatial growth of real-world networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.69.036103]]
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!!__Man-made networks__
Evolving Transportation Networks
Measuring the Structure of Road Networks
Exploring the patterns and evolution of self-organized urban street networks through modeling
Time Evolution of Road Networks
!!__Physical networks__
Granular materials
Polymer networks (blue phases..)
Fiber networks can amplify stress
!!__Biological networks__
Roots, vascularity, leaf venation, physarum networks, neural networks...
!!__Geometrical graphs__
https://en.wikipedia.org/wiki/Outerplanar_graph
https://en.wikipedia.org/wiki/Godfried_Toussaint
''Toussaint hierarchy'' of different kinds of geometric planar graphs. Has been applied to physarum networks
[[Some geometrical and spatial networks examples|http://www.stat.berkeley.edu/~aldous/206-SNET/list_networks.html]]
[[How $$\beta$$-skeletons loose their edges|http://www.stat.berkeley.edu/~aldous/206-SNET/Papers/adamatzky_2013.pdf]]
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
__Fourier spectral discretization__
Finite difference formulas create dispersion effects not found in original PDE. Similar effects seen in crystals, which are discrete by nature.
One way to avoid these, is to let the order of the finite difference formula tend to infinity. We then get ''spectral methods''. Simplest favours are:
* Periodic domains: ''Fourier spectral methods''.
* Non-periodic domains: ''Chebysev spectral methods''.
In the limit of infinite order, those finite differences approach the infinite ''Laurent matrix'' (or Laurent operator).
Suppose we have the values of the solution function $$v$$ on our discrete periodic grid. //Spectral approximations// to $$v'$$, $$w$$ is given by:
$$w=Dv$$
where D here is the ''spectral differentiation matrix''.
The fundamental idea of //spectral collocation methods// is :
1. Interpolate the data by a __global__ interpolant (for example, a periodic trigonometric polynomial):
$$p(x) = \sum_{j=-N/2}^{N/2} a_j e^{ijx}$$
2. Differentiate $$p(x)$$ and evaluate at the grid points.
From properties of exponential, another way to compute the 2nd Fourier spectral derivative is:
1. Given $$u$$, compute its DFT (discrete Fourier transform) `U = fft(u)` (using MATLAB notation for fast Fourier transform (FFT), an efficient algorithm to compute DFT).
2. Multiply by $$-j^2$$: $$W(j) = -j^2 U_j$$.
3. Take the inverse transform `w = ifft(u)`.
Similar ideas lead to the //[[one-way wave equation|https://people.maths.ox.ac.uk/trefethen/pdectb/oneway2.pdf]]//.
//Fill details below from lecture 10, when it's published// (https://www0.maths.ox.ac.uk/courses/course/28839, and [[vid|https://oxforduniversity.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx?embedded=1#]]).
!!!__Fourier series__
...
Quadrature: trapezoidal rule $$\Leftrightarrow$$ integrating the interpolant
Rootfinding: via eigenvalues of companion matrix
!!!__Laurent series__
...
!!!__Chebysev series__
...
A spectrofluorometer is an instrument which takes advantage of fluorescent properties of some compounds in order to provide information regarding their concentration and chemical environment in a sample.
https://www.wikiwand.com/en/Spectrofluorometer
A plot of the time-windowed [[Spectrum]] of a [[Sound]] signal versus [[Time]]
The set of frequencies present in a [[Sound]] signal, and their amplitudes, often plotted in a graph.
[[Voice]] that corresponds to the utterances of some [[Spoken language]]
__Speech generation and understanding__
[[Speech synthesis]]
[[Speech recognition]]
//aka voice recognition, speech-to-text, STT//
The counterpart to [[Speech synthesis]]
--------------
https://www.wikiwand.com/en/Speech_recognition
[[Unsupervised Learning of Temporal Features for Word Categorization in a Spiking Neural Network Model of the Auditory Brain|http://www.biorxiv.org/content/early/2016/06/19/059840.abstract]]
//aka text-to-speech , TTS//
The counterpart to [[Speech recognition]]
[[Early video that created about TTS|https://www.youtube.com/watch?v=qyyJKd-zXRE&list=PLA89DCFA6ADACE599&index=6#t=41m23s]] using [[Artificial neural network]]s (NetTalk)
[[WaveNet: A Generative Model for Raw Audio|https://deepmind.com/blog/wavenet-generative-model-raw-audio/]]
"Interestingly, we found that training on many speakers made it better at modelling a single speaker than training on that speaker alone, suggesting a form of [[Transfer learning]]." Reminds me of the idea of //contrasting cases//
--------------
https://www.wikiwand.com/en/Speech_synthesis
[[Geodesic]]s are great circles
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/c/cb/Illustration_of_great-circle_distance.svg/400px-Illustration_of_great-circle_distance.svg.png]]
[[Spherical trigonometry]]
in the brain, a synapse may be strengthened if the pre-synaptic spike occurs about 10-20ms before the post-synaptic spike, but weakened if the pre-synaptic spike occurs about 10-20ms after the post-synaptic spike. This is known as spike time dependent plasticity (STDP).
See [[Memory]], [[Hebbian theory]]__Long-term potentiation (LTP) and long-term depression (LTD)__
[[vid|https://www.youtube.com/watch?v=hLs3m6nIJ1E&index=26&list=PL4C48902B3A4ED0F4#t=6m40s]]
9. Bi, G.Q. and M.M. Poo, Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci, 1998. 18(24): p. 10464-72.
10. Markram, H., et al., Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science, 1997. 275(5297): p. 213-5.
* ''Causation''. Strengthening of synapse when presynaptic cell spikes before the postsynaptic cell. Cells want to remember patterns in the right temporal sequence. Because synapses are causal entities, only pre-postsynaptic cell firings could be replicated by them, and so only these are learned. In fact correlated firing in the opposite order, weakens the synapse.
** Note that we can learn to think of causes given an effect, due to the hierarchical structure of our brains. If for some reason the thought of an effect gives rise to the thought of a cause, the former thought precedes the other, and so these thoughts can be learned in this order.
* ''Correlation''. Hebbian strengthening (LTP and LTD) only occurs if the firing occurs between a window of 20ms.
http://www.scholarpedia.org/article/Spike-timing-dependent_plasticity
A more biologically plausibl kind of [[Artificial neural network]], which takes direct inspiration on biologial [[Neuronal network]]s. It is a model that is the basis for the design of [[Neuromorphic computing]] systems. It models the time-dependent spikes of real [[Neuron]]s. These spikes correspond to [[Action potential]] spikes that travel through the neuron's axons, dendrites, and soma (bodies).
[[CS-DC'15: From Spikes to Cognitive Agents with Neural Assembly Computing|https://www.youtube.com/watch?v=P6ysScmb9hY&t=279s]]
The first scientific model of a spiking neuron, proposed by Hodgkin and Huxley [21], is based on experimental recordings from the giant squid axon using a voltage clamp method. The complexity in simulating this biologically realistic model is very high due to the number of differential equations and the large number of parameters. Thus, most computer simulations choose to use a simplified neuron model such as the integrate-and-fire model (I&F), leaky I&F model, conductance-based I&F or Izhikevich׳s model. The I&F model simulates the state of the neuron by its membrane potential, which receives excitatory or inhibitory signals from synaptic inputs from other neurons. Each input is weighted by its associated synaptic strength. The leaky I&F model produces a more biologically realistic neuron model adding a “leak” term to the membrane potential, reflecting the diffusion of ions that occurs through the membrane when some equilibrium is not reached in the cell. A full review of the biological behaviour of single neurons can be found in [13] and a comparison of different neuron models can be found in [26].
Quantification of the spiking is often done by the ''instantaneous firing rate'', the number of spikes per unit of time, in average. However, simulating the individual spikes can be useful, because the brain seems to generate spike timing patterns that sometimes give rise to precise ''spike-timing dynamics''. One can also choose to model the axonal delays or not. Both spikes and axonal delays are necessary to study the self-organization of polychrony ([[paper|http://www.izhikevich.org/publications/spnet.pdf]]).
:[[Delayed dynamical system]]s can exhibit astonishingly rich and complex dynamics (e.g., see Foss & Milton, 2000); however, the mathematical theory of such equations is still in its infancy (Wiener & Hale, 1992; Bellen & Zennaro, 2003). [[Maxwell's equations]] give rise to delayed PDEs (see Feynman lectures, on relativistic EM!).
[ext[Spiking Deep Neural Networks|http://www.ini.uzh.ch/~pfeiffer/research.html]], [[vid|https://www.youtube.com/watch?v=lhIdisK7akI]]
-----------
//more resources//
!!!See [[Neuronal network]]
------------
!!__[[Polychronization]]__
----------------
!!__Connections with [[Backpropagation]] and [[Deep learning]]__
https://www.reddit.com/r/MachineLearning/comments/2lmo0l/ama_geoffrey_hinton/
[ext[Error-backpropagation in temporally encoded networks of spiking neurons|http://homepages.cwi.nl/~sbohte/publication/backprop.pdf]]
[[BPSpike: A backpropagation learning for all parameters in spiking neural networks with multiple layers and multiple spikes|http://ieeexplore.ieee.org/abstract/document/7727211/]] -- [[pdf|http://sci-hub.cc/10.1109/ijcnn.2016.7727211]]
!!![[Stanford Seminar - Can the brain do back-propagation?|https://www.youtube.com/watch?v=VIRCybGgHts]]
[[Backpropagation can be recovered by STDP|https://www.youtube.com/watch?v=VIRCybGgHts#t=30m17s]] by reinterpreting STDP as taking time derivatives.
[[This seems like an example of an extreme learning machine|https://www.youtube.com/watch?v=VIRCybGgHts#t=55m55s]]! -- feedback alignment
---------------
[[Stable propagation of synchronous spiking in cortical neural networks|http://www.nature.com/nature/journal/v402/n6761/abs/402529a0.html]]^^^^
!!!__Training via [[Spike-timing-dependent plasticity]] (STDP)__
------------------
spiking neural P systems
---------------
__Software to simulate SNNs__
[[Brian|http://brian2.readthedocs.io/en/stable/resources/tutorials/1-intro-to-brian-neurons.html]] -- (code/ai/brain) [[neurons tutorial|http://mybinder.org/repo/brian-team/brian2-binder/notebooks/tutorials/1-intro-to-brian-neurons.ipynb]], [[synapses tutorial|http://mybinder.org/repo/brian-team/brian2-binder/notebooks/tutorials/2-intro-to-brian-synapses.ipynb]]
[[Software from Polychronization: Computation With Spikes|http://www.izhikevich.org/publications/spnet.htm]]
[[PyNN|http://neuralensemble.org/PyNN/]]
[[Disordered|Disordered system]] version of the [[Ising model]], and corresponding magnetic materials showing disordered phases.
!__Spin glass models__
[[A short course on mean field spin glasses |https://wt.iam.uni-bonn.de/fileadmin/WT/Inhalt/people/Anton_Bovier/lecture-notes/bovier-paris.pdf]]
-- [[solvable model of a spin-glass|http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.35.1792]]
-- [[Long-Distance Behaviour of Correlation Functions in Disordered Systems|http://iopscience.iop.org/article/10.1209/0295-5075/3/9/008/meta]]
-- [[Scale Invariance and Self-averaging in disordered systems|http://arxiv.org/pdf/cond-mat/0312715v1.pdf]]
!!![[Edwards-Anderson Hamiltonian]]
!!!__[[Frustration]]__
Any real lattice in two or more dimensions will have a complicated network of interpenetrating [[frustrated|Frustration]] loops. How does one then find the ground state? Which couplings should be chosen to be unsatisfied? Or are there possiblymanyground states not connected by any simple symmetry transformation? ,,this is an open question.,,
!!!__[[Spin glass phase transition]]__
!!!__[[Spin glass energy landscape]]__
!!!__[[Mean field theory]] of spin glasses: the [[Sherington-Kirkpatrick Hamiltonian]]__
!!!__Related models and systems__
*[[Ising model]]
*[[Artificial neural network]]
-----------------------
!!__Mechanisms underlying spin glass behaviour__
Direct moment-moment coupling is too weak to account for the observed behaviour.
In a metal such as copper, the outermost
atomic electrons leave the individual copper atoms and more or
less freely roam through the metal (thus becoming conduction
electrons). So, in an alloy like copper manganese, it might be
suspected that these conduction electrons are playing some role.
And that suspicion is correct.
Electron spins have two properties that are crucial to their mediation role:
* The first is that electrons carry their own intrinsic magnetic moments. This means that the ''magnetic moments of the conduction electrons can interact with those of the localized moments'' on the manganese atoms, for example, through mutual spin flips as an electron passes by the manganese moment.
* The second is that, as ''quantum mechanical'' objects, electrons travel through metals as waves, meaning that, like all waves, electrons can exhibit ''diffraction and interference''. As conduction electrons zip past and interact with the localized moment, one gets concentric spheres, centered on the localized manganese moment, of conduction electron spins polarized parallel and antiparallel to the localized moment. These bands are known as Ruderman-Kittel-Kasuya-Yosida (RKKY) oscillations
!__Spin glass materials__
* [[Dilute magnetic alloy]]
* Insulator spin glasses. Like:
** europium strontium sulfide (Eu,,x,, Sr,,1−x,, S), magnetic impurity [[Europium]] is substituted randomly for nonmagnetic [[Strontium]], with the fraction x of europium
** lithium holmium yttrium fluoride (LiHo,,0.167,, Y,,0.833,, F,,4,, ), in which holmium is the magnetic ion.
----------------------
!__[[Static features of spin glasses]]__
Four properties constitute the most prominent static features of materials we have come to call [[Spin glass]]es.
* a cusp in the magnetic susceptibility,
* a rounded maximum but no discontinuities in the specific heat,
* spin freezing below temperature $$T_f$$ , and
* an absence of spatial long-range order
!__[[Dynamics of spin glasses]]__
I.e. [[non-equilibrium|Non-equilibrium statistical physics]] properties.
* "Remanence" behaviour
* Memory effects.
----------------------
https://en.wikipedia.org/wiki/Spin_glass
http://www.birs.ca/events/2014/5-day-workshops/14w5082/videos
[[Courses - F. Guerra “Equilibrium and off equilibrium properties of ferromagnetic...”|https://www.youtube.com/watch?v=gskFXddBxik&index=3&list=PL9kd4mpdvWcCJnmxsmqMzQVnYySPNh8wH]]
[[Statistical mechanics of spin glasses and neural networks 8\3\16|https://www.youtube.com/watch?v=fZ8WCic5u2I&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5&index=2]] no sound :(
[[Spin Glasses and Complexity|https://www.youtube.com/watch?v=7d43TWoMST8]]
[[Spin Glasses and Computational Complexity|https://www.perimeterinstitute.ca/videos/spin-glasses-and-computational-complexity]]. Which types of interactions give us computationally hard problems and spin glasses? I will survey what is known as we close in on finding the simplest complex spin systems.
[[Spin glass]]es posses a “rugged energy (or free energy) landscape.”
The notion of an energy landscape requires a specification of [[spin dynamics|Dynamics of spin glasses]] (to determine ), so let’s choose a simple dynamics as follows. A spin chosen at random looks at its neighbors, and if it can lower its energy by flipping, it does so; otherwise, it stays put. This procedure is continually repeated with randomly and indepen-dently chosen spins and in so doing describes a zero-temperature, one-spin-flip dynamics. One can define a “landscape” under this dynamics: two distinct spin configurations are neighbors if they differ by a single spin, and the time evolution of the system can then be thought of as a “walk” on the landscape.
!!!__[[Dynamical system]] notions__
A spin configuration that remains unchanged for all time under the dynamics is called a ''fixed point'' in state, or configuration, space.
The ''basin of attraction'' of a fixed point comprises all spin configurations that flow toward it under almost every 28 realization of the zero-temperature dynamics described above.
!!!__[[Metastability]]__
Unlike the ferromagnet, in the spin glass this process will quickly stop at a relatively high-energy state. This is because the spin glass has lots of metastability. A one-spin-flip metastable configuration (equivalently,local optimum) is one in which no spin can lower its energy by the dynamics described above, but if two neigh boring spins are allowed to flip simultaneously, then lower energy states are available. This concept can easily be extended to $$k$$-spin-flip metastable states, and it was proved [81] for the EA model in any dimension (including one) that, for an infinite system, there is an infinite number of $$k$$-spin-flip stable states for any finite $$k$$.
But, if we allowed all any number of spins to flip, and so reached the global energy minimum, we are confronted with the question of how many such minima there are.
[[Phase transition]]s in [[Spin glass]]es
the greatest theoretical success in spin glasses to date has to do with the analysis and solution of a spin glass in an (effectively) infinite number of dimensions, where we have the only theoretical results that there is a phase transition
It is easy to prove theoretically that an EA spin glass in one dimension has no phase transition (but this is true for any one-dimensional system with short-range interactions only)
From numerical simulations, the current consensus is that, for the [[EA Ising model|Edwards-Anderson Hamiltonian]], there is a phase transition (at nonzero temperature) in four dimensions and higher, probably one in three dimensions as well, and none in two.
See [[Edwards-Anderson Hamiltonian]] for a description of the order parameter, and [[Replica symmetry breaking]].
The ''spindle'', or ''spindle apparatus'' is an structure that segregates chromosomes during cell division, and is formed by [[Microtubule]]s, [[Molecular motors]], and hundreds of other proteins. The spindle [[self-organizes|Spindle self-organization]] during division process.
(https://en.wikipedia.org/wiki/Spindle_apparatus)
[img[https://upload.wikimedia.org/wikipedia/commons/2/25/Kinetochore.jpg]]
For the frog //Xenopus laevis//, spindles are on average ~45 microns long, and ~30 microns wide. Microtubules in these spindles have an average length of ~7 microns ([[ref|http://people.seas.harvard.edu/~jbrugues/Home_files/nucleation_transport_cell_2012.pdf]]) and are at a density of ~50-100 microtubules/$$\mu$$m^2, implying that there are ~100,000 ([[ref 1|http://www.ncbi.nlm.nih.gov/pubmed/1238403]], [[ref 2|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2141625/]]). Microtubules are __polar polymers__ whose minus ends are relatively static and whose plus ends polymerize at a speed of ~10-20 $$\mu$$m/min ([[ref|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC379274/]]). There is no appreciable rate of rescues in these spindles <mark>?</mark> ([[ref|http://people.seas.harvard.edu/~jbrugues/Home_files/nucleation_transport_cell_2012.pdf]]), and the half-life of these microtubules is ~16s, much shorter than the typical lifetime of a spindle -- which can exist for several hours. Microtubules in the spindle interact with each other via motrs and cross-linkers, and continuously slide toward the poles at a rate of ~2.5 $$\mu$$m/min ([[ref 1|http://people.seas.harvard.edu/~jbrugues/Home_files/nucleation_transport_cell_2012.pdf]], [[ref 2|http://www.ncbi.nlm.nih.gov/pubmed/15583027]])
[[Nucleation and Transport Organize Microtubules in Metaphase Spindles|http://people.seas.harvard.edu/~jbrugues/Home_files/nucleation_transport_cell_2012.pdf]]
[[Microtubular origin of mitotic spindle form birefringence. Demonstration of the applicability of Wiener's equation.|http://www.ncbi.nlm.nih.gov/pubmed/1238403]]
[[Spindle Assembly in Xenopus Egg Extracts: Respective Roles of Centrosomes and Microtubule Self-Organization|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2141625/]]
[[Microtubule Plus-End Dynamics in Xenopus Egg Extract Spindles|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC379274/]]
[[Fast Microtubule Dynamics in Meiotic Spindles Measured by Single Molecule Imaging: Evidence That the Spindle Environment Does Not Stabilize Microtubules|http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808228/]]
[[The kinesin Eg5 drives poleward microtubule flux in Xenopus laevis egg extract spindles.|http://www.ncbi.nlm.nih.gov/pubmed/15583027]] Although mitotic and meiotic spindles maintain a steady-state length during metaphase, their antiparallel microtubules slide toward spindle poles at a constant rate. This "poleward flux" of microtubules occurs in many organisms and may provide part of the force for chromosome segregation. [...] Our results suggest that ensembles of nonprocessive Eg5 motors drive flux in metaphase Xenopus extract spindles.
See [[Active matter]]
![[Physical basis of spindle self-organization|http://www.pnas.org/content/111/52/18496.short]]
[[Spindle|Spindle (Cell biology)]]
!!__Theory__
Spindle self-organization arises from:
*the local interactions of microtubules, mediated by steric effects, cross-linkers and motors
* microtubule polymerization dynamics ([[Microtubule]] turnover)
__Microtubules in the spindle are deep within the nematic phase__, as their volume fraction, $$\sim 0.03$$, is well above the volume fraction at which the isotropic phase is expected to lose stability, $$\sim0.01$$. However, their __net polarity varies__ from parallel (with plus end towards center) at the ends, to antiparallel at the middle. __Theory__: The magnitude of the nematic field is taken to be constant throughout the spindle (note: the magnitude, not the direction!), while the magnitude of the polarity field depends on motor activity and self-advection. They do this because they consider the simplest theory that is consistent with all the data.
See [[Supporting infomation (annotated)|]]
Theory based on that developed in this paper:
[[Fluctuating hydrodynamics and microrheology of a dilute suspension of swimming bacteria|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.80.011917]]. Some parts can be derived using [[Poisson-bracket approach to the dynamics of nematic liquid crystals|https://journals.aps.org/pre/abstract/10.1103/PhysRevE.67.061709]].
How changes in volume due to microtubule polymerization (gaining the dimers) can also add to active stress, as in the case of cells growing in tissues: [[Fluidization of tissues by cell division and apoptosis|http://www.pnas.org/content/107/49/20863.abstract]]
!!__Experimental validation__
__Materials and apparatus__
[[LC-PolScope|http://openpolscope.org/docs/OldenbourgLC-PolScopeLabManual2005.pdf]], http://openpolscope.org/. Type of microscope that uses light polarization.
Metaphase arrested spindles assembled in //[[Xenopus laevis|https://en.wikipedia.org/wiki/African_clawed_frog]]// egg extracts.
__Measurement methods__
''LC-PolScope + Image processing'' -> extract spatio-temporal correlation functions from the movies obtained by microscope. Measure:
* Retardance. Gives measure of microtubule density (if microtubules are well aligned, which they are). See [[video|http://movie-usa.glencoesoftware.com/video/10.1073/pnas.1409404111/video-1]]
*Optical slow axis. Gives measure of microtubule orientation. See [[video|http://movie-usa.glencoesoftware.com/video/10.1073/pnas.1409404111/video-2]]
''Spinning disk confocal microscope'', to record 3D time-lapse movies of spindles labeled with high concentration of fluorescent tubulin. These give 3D measurements of the density. See [[video|http://movie-usa.glencoesoftware.com/video/10.1073/pnas.1409404111/video-3]]
Measuring __stress fluctuations__:
* Passive ''two-point particle displacement mesaurement''. See [[video|http://movie-usa.glencoesoftware.com/video/10.1073/pnas.1409404111/video-4]]
* Active microrheology measurement of the frequency-dependent shear modulus of the spindle by Shimamoto et al.
obtained two-point particle displacements by tracking single molecules of fluorescently labeled tubulin, computed the two-point correlation between these single molecules along the direction perpendicular to the spindle axis.
!!!__Internal dynamics of spindle__
[img width = 600 [http://www.pnas.org/content/111/52/18496/F1.large.jpg]]
http://www.pnas.org/content/111/52/18496/F1.expansion.html
Measuring correlations. In particular, they measure correlations of the fluctuations at each pixel in the image relative to the time-average value of that pixel. This is so that the correlations don't contain information on the more or less steady average spatial structure of the spindle, and so we focus on the fluctuations on top of it. The Fourier transform of an autocorrelation gives the [[Power spectral density]] (PSD), which they use to compare predictions with experiment. They also use these comparisons to fit the parameters of the theory, as is done in many instances in [[Condensed matter physics]], as they point out. They also show that their parameters are relatively few, showing strong predictive power of the theory, and also meaning that the agreement with experiment is strong validation of the theory.
Measurement results:
* microtubule ''orientation autocorrelation'' (AC) function.
**Fourier transform of equal-time spatial AC: $$1/q^2$$, where $$q$$ is the [[wave number|https://en.wikipedia.org/wiki/Wavenumber]]. <mark>Why don't we look at $$\omega \rightarrow 0$$ (i.e. time average of signal) in analogy to what we do below?</mark>
**Fourer transform of time autocorrelation for the $$q \rightarrow 0$$ component (i.e. average over space of fluctuation): $$1/\omega^2$$, where $$\omega$$ is the frequency (Fourier variable).
**Both of these correspond to linear decay in the real space (space, or time). See comment below
** They are not compatible with other competing theories <mark>Why?</mark>.
* ''density autocorrelation'' function
**Fourier transform of equal-time autocorrelation function along direction perpendicular to the spindle axis (wavenumber along this direction is $$q_\perp$$):
***plateaus for small $$q_\perp$$
***decays as $$1/q_\perp^4$$ for large $$q_\perp$$.
**Fourier transform of long-wavelength limit of time autocorrelation function goes like $$1/\omega^2$$ too.
* ''orientation-density cross-correlation'' function
* the ''generation and propagation of stress'' in the spindle.
**The two-point displacement correlation function decays as the inverse of the particle separation, $$R$$.
**The two-point displacements exhibit super-diffusive motion with an exponent $$\alpha\approx 1.8$$. When combined with the active microrheology measurements, reveals that stress fluctuations in the spindle increase linearly with time lag.
These are all are consistent with the theory, as can be seen in the figure below:
[img width=600 [http://www.pnas.org/content/111/52/18496/F2.large.jpg]]
http://www.pnas.org/content/111/52/18496/F2.expansion.html
!!!__Morphology of the spindle__
The calculated orientation of microtubules throughout the spindle quantitatively agrees with their LC-Polscope measurements.
They reproduced the [[observed spatial variation of polarity|http://people.seas.harvard.edu/~jbrugues/Home_files/nucleation_transport_cell_2012.pdf]]
Calculated aspect ratio closely agrees with observation
[img width=500 [http://www.pnas.org/content/111/52/18496/F3.large.jpg]]
http://www.pnas.org/content/111/52/18496/F3.expansion.html
-------------
__Other spindle phenomenology__ to further investigate using the above theory:
* Fusion of two spindles
* Response of the spindle to physical perturbations
* Molecular perturbations, which should act to change the parameters of the theory
---------------
[[Nonequilibrium mechanics of active cytoskeletal networks.|http://www.ncbi.nlm.nih.gov/pubmed/17234946]]
[[Microrheology, Stress Fluctuations, and Active Behavior of Living Cells|http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.91.198101]].
We report:
*the first <b>measurements</b> of {the [__intrinsic strain fluctuations__] of {living cells}} using {a recently developed tracer correlation technique}
* along_with a <b>theoretical framework</b> for {interpreting [such data] in {heterogeneous media with nonthermal driving}}.
The {[fluctuations]’ spatial and temporal correlations} indicate that {the __cytoskeleton__ __can be treated as__ a {__course-grained continuum__ with power-law rheology, driven by a spatially random stress tensor field}}.
{Combined with recent cell rheology results, our data} imply that {{intracellular stress fluctuations have a nearly $$1/\omega^2$$ power spectrum}, as expected for a continuum with a slowly evolving internal prestress.}
<big><i style="color:aqua;" class="fa fa-eye" aria-hidden="true"></i></big> __A $$1/\omega^2$$ spectrum corresponds to a linear decay in time__ of a stress-stress correlation function (see [[WA computation|http://www.wolframalpha.com/input/?i=fourier+transform+of+-sqrt(pi%2F2)+omega+sgn(omega)+%2B5]], notice dividing by $$\omega$$ is like integrating the Fourier transform) within our experimental time window, and would be a natural consequence of //slow// evolution of intracellular stress. Explanation: The stress generation/relaxation may rely on a number of modes with diverse timescales, $$\tau_i$$. In the simplest case, a stress autocorrelation would then be multiexponential, consistent with our result if all $$\tau_i$$ lie well outside of our measurable range. This is because the exponentials appear linear when the exponent $$t/\tau_i \ll 1$$.
[[High-resolution probing of cellular force transmission.|http://www.ncbi.nlm.nih.gov/pubmed/19518758]]
[[Oriental philosophy]]
[[Mysticism]]
------------------
[[Religion]]
[[Occultism]]
a [[Language]] that has a [[mapping|Function]] to [[Sounds]], which are called the language's ''utterance''s
[img[http://www.treleoni.com/images/Cellulose--Sponges.png]]
[[Wikipedia:Portal/Directory/Sports and games|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Sports_and_games]]
[[Standing|https://en.wikipedia.org/wiki/Standing]], also referred to as orthostasis, is a human position in which the body is held in an upright ("orthostatic") position and supported only by the feet.
[[Soylent|https://www.soylent.com/]], [[Joylent|https://www.joylent.eu/]], [[Huel|https://huel.com/]], [[Nano|http://www.eatnano.eu/]]
[[Queal|https://queal.eu/queal-versus-competitors/?gclid=CLmu2ZGHns8CFWIq0wodhkgDUg]]
[[Jake|https://jakefood.com]]
[[Bertrand|https://bertrand.bio/]]
Huel. [[How to use|https://huel.com/pages/how-to-use]]
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Soylent bars. https://www.joylent.eu/products/twennybar
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http://wesna.me/ food machine for 100%Food
[[Ambronite|https://ambronite.com/products/ambronite-healthy-meal-replacement-protein-smoothie-shake-10-pack?key1=recommendation2]] , expensive
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https://en.wikipedia.org/wiki/Star
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[ext[wiki|https://www.wikiwand.com/en/Stars_and_bars_(combinatorics)]]
__Theorem 1__
For any pair of positive integers n and k, {the number of k-tuples of positive integers whose sum is n} is equal to {the number of (k − 1)-element subsets of a set with n − 1 elements}, which is given by $$\binom{n-1}{k-1}$$
See [[Number of ways to put n objects in k bins, with each having at least one object]]
__Theorem 2__
For any pair of positive integers n and k, the number of k-tuples of non-negative integers whose sum is n is equal to the number of multisets of cardinality k − 1 taken from a set of size n + 1, which is given by the ''multiset number'', $$\left(\binom{n+1}{k-1}\right) = \binom{n+k-1}{k-1}$$.
See [[Number of ways to put n objects in k bins]]
Four properties constitute the most prominent static features of materials we have come to call [[Spin glass]]es.
* a cusp in the magnetic susceptibility,
* a rounded maximum but no discontinuities in the specific heat,
* spin freezing below temperature $$T_f$$ , and
* an absence of spatial long-range order
[[Dilute magnetic alloy]]s at higher concentrations of magnetic impurities were the first experimental examples of spin glasses. Because the spins interact, it was expected the system would have some sort of ordered phase at low temperatures. Indeed a [[Phase transition]] was observed, with a ''susceptibility cusp'' at a particular transition temperature $$T_f$$. The high temperature phase was a [[paramagnetic|Paramagnetism]] phase. Then experiments on the nature of the lower temperature phase were conducted.
There exists a variety of experimental probes that can provide information on what the atomic magnetic moments are doing, and measurements using these probes indicated several things.
* First, the ''spins were “frozen”''; that is, unlike in the high-temperature paramagnetic phase, in which each spin flips and gyrates constantly so that its time-averaged magnetic moment is zero, at low temperatures each spin is more or less stuck in one orientation.
* Second, the ''overall magnetization was zero'', ruling out a ferromagnetic phase. But third, more sensitive probes indicated there was no long-range antiferromagnetic order either: in fact, as near as could be told, the spins seemed to be frozen in random orientations.
However, the phase transition had some more surprises to reveal. Recall that at a phase transition, all the thermodynamic functions behave singularly in one fashion or another. Surely the ''specific heat'', one of the simplest such functions, should show a singularity as well. However, when one measures the specific heat of a typical spin glass, one sees . . . absolutely nothing interesting at all. All you see is a ''broad, smooth, rounded maximum'', which doesn’t even occur at the transition temperature (defined to be where the susceptibility peak occurs). A typical such measurement is shown in figure 4.2.
[img[http://i.imgur.com/b7WYQmz.png]]
So, returning to the topic at hand, we’re faced with the follow-
ing question: Is there a true thermodynamic phase transition to a
low-temperature spin glass phase characterized by a new kind of
magnetic ordering? Or is the spin glass just a kind of magnetic
analog to an ordinary structural glass, where there is no real
phase transition and the system simply falls out of equilibrium
because its intrinsic relaxational timescales exceed our human
observational timescales? If the latter, then the spins wouldn’t
really be frozen for eternity; they would just have slowed down
sufficiently that they appear frozen on any timescale that we can
imagine.
As of this writing, <span style="color:aqua; font-size:17px">the question remains open.</span>
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
A ''statistical field'' is often derived by averaging microscopic physics over mesoscopic lengthscales (in a particular way called, __coarse graining__). This results in a __free enegy__, $$F$$, which (when exponentiated) gives the weight factor over which we integrate to get the __partition function__, $$Z$$. As the averaging gives a (macroscopic) field (as an approximation to a lattice average), the integral for $$Z$$ is a [[Functional Integral]], expressable as a [[Path Integral]].
!!! __Origin of Universality (Why do many field theories look like each other?)__
This free energy can be written as a power series in the field. It turns out that only a few terms (<small>the renormalizable ones, and maybe a few non-renormalizable ones</small>) contribute for a given precission of interest (this is understood via the [[Renormalization Group]]).
Thus, the only thing that fundamentally differentiates one theory/model from another are the __symmetries__ of the field, which determine which terms can appear in the free energy. __Dimensionality__ and __transformation properties__ of the field (whether it is a scalar, a vector, a spinor, ...) also play a role.
The microphysics only enters through the __parameters__ of the theory. But as these are often few, they can be and most often are determined experimentally. For this reason statistical field theories are often referred to as __phenomenological__.
<small>Similar considerations apply in [[Quantum field theory]]</small>
!! The Landau-Ginzbyurg Hamiltonian
__Assumptions__:
* Locality and uniformity
* Isotropy
* Stability
!![[Bayesian inference]]
Probability is a subjective belief
!!Frequentist inference
Probability as frequencies
Ficticious samples
[[Hypothesis testing]]
//Confidence intervals//
[[Lecture notes|https://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/A1/2012/sec15_MultiSpecies.pdf]]
Uses multispecies [[Grand canonical ensemble]]
See also [[Neural network theory]] (mostly about [[Artificial neural network]] [[Learning theory]]), [[Deep learning theory]], [[Hopfield network]], [[Spin glass]]
[[Thouless-Anderson-Palmer equations for neural networks|http://journals.aps.org/pre/abstract/10.1103/PhysRevE.61.1839]]
!!__Neural networks and [[Spin glass]]es__
See [[Deep learning theory]] and [[Hopfield network]]
See more at Neural Networks: An Introduction [2 ed.] by Muller et al.
The ferromagnetic case corresponds to a neural network that has stored
a single pattern, and has no [[Frustration]]. The network which has been loaded with a large number of
randomly composed patterns resembles a spin glass.
[[The Loss Surfaces of Multilayer Networks |http://www.jmlr.org/proceedings/papers/v38/choromanska15.pdf]]
[[How glassy are neural networks?|http://ezproxy-prd.bodleian.ox.ac.uk:2839/article/10.1088/1742-5468/2012/07/P07009/meta;jsessionid=B582D39D6A769C5181263198B74EA025.c2.iopscience.cld.iop.org]]
[[Spin-glass models of neural networks|http://journals.aps.org/pra/abstract/10.1103/PhysRevA.32.1007]]
[[Temperature based RBM]]s
[[Statistical Mechanics of Neural Networks near Saturation |http://sci-hub.cc/10.1016/0003-4916(87)90092-3]]
----------------
[[Video|https://www.youtube.com/watch?v=cjj9ihYJkOQ#t=1m30s]]
https://www.youtube.com/watch?v=fZ8WCic5u2I&list=PLYq7WW565SZgC_0OqyRjTcWKH3odod3j5
__Asynchronous irregular firing__
See also [[Neuronal network]]
''Statistical physics'' deals with the description of systems for which a deterministic description is either useless or impossible, so that one uses a //statistical// description.
Here a //deterministic description// is understood in the context of the relevant physical description. For example Schrodinger's equation is deterministic, if the relevant physical description is the wavefunction. It is non-deterministic if one takes position and/or velocity as the relevant physical descriptions. However, it is known that one can't describe quantum mechanical evolution purely with a statistical theory of position and velocity, without sacrificing some rather well-established physical principles or predictions.
If the system is effectively classical (either because it is macroscopic, or for some other reason, that is probably ultimately related to [[Quantum decoherence]]), the need for a statistical description arises when the system is //sufficiently chaotic//. Most often this requires the system to: have __<big>many</big> components__ and/or __be coupled to a system with <big>many</big> components__.
For this reason, statistical physics is mostly applied to the description of systems of many particles in a gas, liquid or solid; or to one or a few particles coupled to one such large system.
There are two main branches of statistical physics:
<big>[[Equilibrium statistical physics]]</big> deals with such systems at //equilibrium//, that is, when the relevant macroscopic averages of the statistical description don't change with time. In practice, one often has two approaches:
*For a small system coupled to a large chaotic system, one often has to use a probability distribution function over the relevant degrees of freedom (amazingly, for equilibrium, this always takes the form of a [[Boltzmann distribution]].
* For a large system, one can often bypass the distribution function and deal with the relevant averaged quantities directly, resulting in a [[thermodynamic|Thermodynamics]] description.
<big>[[Non-equilibrium statistical physics]]</big> deals with such a system out of equilibrium, so that averages can change in time. This is much harder to do in full generality, as systems offer much more diversity out of equilibrium, as may be expected. One often has three approaches:
*For a small system coupled to a large chaotic system, one has a [[stochastic process|Stochastic processes]], which describes the evolution under the random influence of the large chaotic system.
*For a large system which is only slightly out of equilibrium, so that relevant macroscopic averages analogous to those used in thermodynamics can still be defined, one can describe the system using [[Non-equilibrium thermodynamics]]
*For a large system that is considerably out of equilibrium, one has to use the tools of [[Kinetic theory]] to describe it. However, if the system is //very// far from equilibrium, even these may be inappropriate, and finding an appropriate description may be extremely hard. An example of this are systems with strong [[Turbulence]]. Our only approaches to understand these systems are often [[phenomenological]].
------------------
See also [[Complex systems]], and [[Sloppy systems]]
[ext[Entropy, Order Parameters, and Complexity|http://pages.physics.cornell.edu/~sethna/StatMech/EntropyOrderParametersComplexity.pdf]]
[[Long-range interacting systems]]
[[Oxford physics course|https://www-thphys.physics.ox.ac.uk/people/AlexanderSchekochihin/A1/]]
[[Oxford maths course|https://www0.maths.ox.ac.uk/courses/course/28786/material]]
[[Bangalore School on Statistical Physics - V (video lectures)|https://www.youtube.com/playlist?list=PL04QVxpjcnjjoHglJGm-O5YtSbqLtln0g]]
[[Bangalore School on Statistical Physics - VI|https://www.youtube.com/watch?v=Kn6wzdRAdiE&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]] (I'm on the 1st lecture on [[Long-range interacting systems]]
[[Ergodic theory]]
See about disordered systems in [[Condensed matter physics]], as these are interesting systems studied using statistical physics.
[[Indian Statistical Physics Community Meeting 2016|https://www.youtube.com/playlist?list=PL04QVxpjcnjjPHpsBoYDSnOmLzfzhK5TB]]
[[Interesting papers on statistical physics and complex systems]]
!!![[PRE- More Kaleidoscopes for April 2016|http://journals.aps.org/pre/kaleidoscope/pre/93/4/042404]]
[[Non‐equilibrium thermodynamics: foundations, scope, and extension to the meso‐scale|http://www.nipslab.org/files/Rubi.pdf]]
[[Non-equilibrium thermodynamics - de Groot and Mazur|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/%5BS._R._De_Groot,_P._Mazur%5D_Non-equilibrium_thermodynamics.djvu]]
[ext[Statistical Mechanics II course|http://socrates.berkeley.edu/~jemoore/Moore_group,_UC_Berkeley/Physics_212.html]]
<mark>[ext[Sethan's Statistical Mechanics: Entropy, Order Parameters, and Complexity|http://pages.physics.cornell.edu/~sethna/StatMech/]]</mark>
[[MIT 8.333 Statistical Mechanics I|https://www.youtube.com/watch?v=4RX_lpoGRBg&list=PLUl4u3cNGP60gl3fdUTKRrt5t_GPx2sRg]]
[[MIT 8.334 Statistical Mechanics II|https://www.youtube.com/watch?v=2MaQKFHqYBw&list=PLUl4u3cNGP63HkEHvYaNJiO0UCUmY0Ts7]]
http://stp.clarku.edu/notes/
[ext[Statistical physics, Optimization, Inference and Message-Passing algorithms|http://www.lps.ens.fr/~krzakala/LESHOUCHES2013/book.htm]]
--------------------
__Foundations of statistical mechanics__
[[What Is a Macrostate? Subjective Observations and Objective Dynamics|http://arxiv.org/abs/cond-mat/0303625]]
[[The Backwards Arrow of Time of the Coherently Bayesian Statistical Mechanic|http://arxiv.org/abs/cond-mat/0410063]]
[[Ludwig Bltzmann and entropy|http://link.springer.com/article/10.1007%2FBF02835141?LI=true]] Lots os stuff about entropy..
-----------
Philosophy of statistical physics
[[Probability in physics: stochastic, statistical, quantum|http://philsci-archive.pitt.edu/9815/1/wilson.pdf]]
[[Rethinking equlibrium|http://www.romanfrigg.org/writings/rethinking_equilibrium.pdf]]
Book: Ensemble modeling : inference from small-scale properties to large-scale systems
As used in [[Protein structure analysis]], Statistical potentials score [[decoys|Protein-decoy structure]] by comparing their features to experimentally-
determined structures, based on the assumption that the observed distributions of
particular features reflect energetics: i.e., a common characteristic is assumed to be
energetically favourable.
__RAPDF (residue-specific all-atom probability discriminatory function)__
Essentially a [[Naive Bayes]] classifier trained on a set $$C$$ of native structures (structures observed experimentally and assumed to be correct).
We wish to evaluate $$P(C|\{d_{ij}^{ab}\})$$, theprobability the structure is a member of the "correct" set $$C$$, given it contains the distances {$$d_{ij}^{ab}$$}. We write this probability, using [[Baye's theorem]] as
$$P(C|\{d_{ij}^{ab}\}) = P(C) \frac{P(\{d_{ij}^{ab}\}|C)}{P(\{d_{ij}^{ab}\})}$$
We then make the assumption that $$P(\{d_{ij}^{ab}\}|C)$$ factorizes as $$\prod\limits_{ij}P(d_{ij}^{ab}|C)$$ (i.e. the [[Naive Bayes]] assumption!).
The score of each decoy (with features $$\{d_{ij}^{ab}\}$$) is then just the negative log-likelihood
$$S(\{d_{ij}^{ab}\}) = -\ln{P(C|\{d_{ij}^{ab}\})} = \sum_{ij} \ln{\left (\frac{P(d^{ij}_{ab}|C)}{P(d^{ij}_{ab})} \right)}$$
where $$S$$ is the score for the decoy, and $$d^{ij}_{ab}$$ is the distance between atoms $$i$$ and $$j$$, of types $$a$$ and $$b$$.
See more explanation [[here|http://moult.ibbr.umd.edu/pdfs/All-atomDistance-dependentConditionalProbability.pdf]]
The probabilites are estimated (as in [[Naive Bayes]]) as sample frequencies:
$$P(d^{ij}_{ab}|C) = \frac{N(d^{ij}_{ab})}{\sum_d (d^{ij}_{ab})}$$
where the distances $$d^{ij}_{ab}$$ have been discretized, and $$N$$ means number of occurrences of distance $$d$$ between residues of type $$a$$ and $$b$$ over all native configurations in $$C$$.
The average over all experimental structures is
$$P(d^{ij}_{ab}) = \frac{N(d^{ij}_{ab})}{\sum_d (d^{ij}_{ab})}$$ over all structures, not just those in $$C$$.
However, they further approximate this, and assume (I guess as over all structures, there is more randomness..) that this is independent of $$a$$ and $$b$$, and that they can estimate this as the average over all $$a$$ and $$b$$ and all structures, in $$C$$ (because we don't have the whole set of possible structures I guess)
$$P(d^{ij}_{ab}) \approx P(d) = \frac{\sum_{ab}N(d^{ij}_{ab})}{\sum_d \sum_{ab} (d^{ij}_{ab})}$$ over structres in $$C$$.
[[Wiki article|https://en.wikipedia.org/wiki/Statistics]]
[[Understanding statistics through explorables|http://emilkirkegaard.dk/understanding_statistics/?app=Simpson_paradox]]
Mathematica foundation: [[Probability theory]]
!!!__Statistics software__
[[R language]]
!!!__Statistical measures__
[[The D Statistic|http://mste.illinois.edu/patel/chisquare/dstat.html]]
$$\chi^2$$ statistic
t-test
[[Kolmogorov–Smirnov test]] <i class="fa fa-check" aria-hidden="true"></i>
!!!__Statistical learning__
See [[Machine learning]], [[Learning theory]]
!!!__[[Sampling]]__
[[Compressed sampling|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/CompressiveSampling-Review.pdf]]
!!!__[[Resampling]]__
* [[Bootstrap]]
!!!__Mathematical statistics__
[[On the Mathematical Foundations of Theoretical Statistics|http://l.academicdirect.org/Horticulture/GAs/Refs/Fisher_1922_Estimation.pdf]]
[[Sufficient statistic]],
[[Likelihood function]]
[[Mathematical Statistics Videos|http://stats.stackexchange.com/questions/485/mathematical-statistics-videos]] [[some YB videos|https://www.youtube.com/channel/UCL20lsbPlem4iMX3ySHtt3w]]
[[Bayesian statistics]]
-------------------
[[Train, validation, test|http://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set]]
[[http://colorfulengineering.org/SCICOMP.html]]
Steel is an [[Alloy]] composed of mainly [[Iron]] with some [[Carbon]] in it.
http://www.bbc.co.uk/education/guides/zfsk7ty/revision/6
A [[Molecule]] that has the same [[Chemical formula]] as another molecule, but differs in the orientation of its atoms in space. This can happen by swapping some [[Moiety]]es by their mirror images
If the molecule is just the mirror image of the other molecule, it is called an [[Enantiomer]], and if it isn't, it is a [[Diasteromer]]s. If two steroisomers are actually the same (can be made to coincide after a rotation) they are known as ''meso compound
Minimum cost diet that satisfies [[Nutrition]] requirements.
Can be tackled using [[Linear programming]]
[[Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl07_exp-swimmer.pdf]] (experiment)
[[Anomalous Diffusion of Symmetric and Asymmetric Active Colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/prl09_flucphor.pdf]]
At times long compared to the rotational diffusion time, rotational diffusion leads to a randomization of the direction of propulsion, and the particle undergoes a random walk whose step length is the product of the propelled velocity V and the rotational diffusion time, leading to a substantial enhancement of the effective diffusion coefficient
See [[Percolation theory]]
An stochastic version of [[Gradient descent]], which can be used for [[Online learning]]
To calculate gradients, for [[Artificial neural network]]s, we use [[Backpropagation]]
[[Nando's vid|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=35m05s]] -- [[Hugo's vid|https://www.youtube.com/watch?v=5adNQvSlF50&index=7&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH#t=6m50s]]
See [[Learning theory]] for more on optimization for learning.
,,
(//Online algorithm//, you process the data sequentially, by chunks. You need this if you do not access to all of it at the same time, or you have so much data that not all of it fits on your RAM..)
,,
You only use a mini-batch (a small sample) of input data at a time, in practice
There're theorems that show that this converges well.
Downpour -- Asynchronous SGD
[[Polyak averaging|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=49m30s]]. Running average over the parameter values at all time steps performed up to now.
[[Momentum|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=50m40s]]. You add inertia to the particle so that the gradient descent is not just velocity = gradient (as it'd be in viscous fluid), but it is acceleration = (viscosity) + gradient.
[[Adagrad|https://www.youtube.com/watch?v=0qUAb94CpOw&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=6#t=52m40s]]: Put more weight on rare features [Duchi et al]. <b> Very useful </b> Rare features (i.e. value along a dimension for example) tend to have more information, i.e., they are able to tell you more about what the output $$y$$ should be. This seems maybe related to [[AIT|Algorithmic information theory]]. Compensate for underrepresetantion in gradient descent of rare features
''AdamOptimizer''
[[rmsprop|http://climin.readthedocs.io/en/latest/rmsprop.html]] is an optimizer that utilizes the magnitude of recent gradients to normalize the gradients
//Links//
<small>
[[Notes on Nonequilibrium StatPhys MT2015 Oxford (mostly stochastic processes)|https://files.acrobat.com/a/preview/254ad767-71f3-429e-b36b-3d77cf67a6c7]]
[ext[Nice lecture notes|http://www.thp.uni-koeln.de/~as/Mypage/NonEq/noneq.pdf]]
[[Discrete Stochastic processes MIT course|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-262-discrete-stochastic-processes-spring-2011/index.htm]]
[[Stochastic processes MIT notes|http://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/lecture-notes/MIT18_S096F13_lecnote5.pdf]]
[ext[Nice notes on applications of stochastic processes|http://www.math.uwaterloo.ca/~mscott/Little_Notes.pdf]]
[[Wikipedia: Stochastic process|https://en.wikipedia.org/wiki/Stochastic_process]]
[[List of stochastic processes topics|https://en.wikipedia.org/wiki/List_of_stochastic_processes_topics]]
</small>
!!!<mark>Watch</mark>: ''[[Physics - Physical Applications of Stochastic Processes by Prof. V. Balakrishnan|https://www.youtube.com/playlist?list=PLbMVogVj5nJQo8D9D-D6lMqh4FJbPeE_f]]''
--------
''Stochastic processes''
[[Probability theory]]
[ext[Martingales|https://en.wikipedia.org/wiki/Martingale_(probability_theory)]], [[Martingales Through Measure Theory|https://www0.maths.ox.ac.uk/courses/course/28722/synopsis]]
!! Examples
* [[Brownian motion]]:
** Paths appear non-differentiable, in continuous space-time limit!
** In path description, the //noise term// is chosen to be [[Gaussian white noise]].
!! Classification of models
[img width=500 [types_of_random_processes.png]]
* Discreteness
**Discrete space-time
***One-step process (can be continuous time too)
****[[Unbiased random walk|Brownian motion]]
****[[Biased random walk]]
****[[Persistent random walk|https://www.youtube.com/watch?v=hHciEDpm1sE&index=9&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]] (it can be seen as having memory, i.e. being non-Markovian).
***Multi-step processes
**Continuous space-time
***[[Diffusion]]
***[[Kramers-Moyal expansion]]. To get continuous models from discrete ones.
***Orientation space. See [[Stochastic dynamics of orientation]].
**Continuous space-discrete time
**Discrete space-continuous time
*Memory
**Memoryless (only dependent on current state) $$\rightarrow$$ [[Markov process]]. Most of the stochastic processed used and studied in practice are Markov.
!! Descriptions
All these generally are Markov processes
*Continuous space-time
**__Path description__
***Stochastic differential equations. Like: [[Langevin equation]]
***[[Path integrals for stochastic processes]]
**__Probability description__. Obtained from path description by averaging, essentially. Gives differential equations for probability density, like:
***[[Fokker-Planck equation]]
*Discrete space
**Probability description $$\rightarrow$$ [[Master equation]]
***Discrete time $$\rightarrow$$ Difference equation. //Discrete time master equation//.
***Continuous time $$\rightarrow$$ Differential //Continuous time master equation//.
*Continuous space-discrete time //??//. An example is the beginning of the derivation for Brownian motion by Einstein
!! Important results
*[[Dissipation-fluctuation relation]]. Friction and dissipation are due to the random movements of particles. Fluctuations are too. The coefficients describing them (diffusion coefficient and viscosity) should be related.
!!Computational methods
[[Monte Carlo method]]
!!Other mathematical aspects
https://en.wikipedia.org/wiki/It%C3%B4_calculus
!!Applications
__Chemistry__
[[Chemical kinetics]]
[[Oscillating chemical reactions]]
__Biology__
[[Enzyme kinetics]]
__General phenomena__
[[Number fluctuations]]
__Others__
[[Telegraph noise]]
[[Complex systems]]
-----------
Recent paper by Ramin Golestanian (26th Feb 2016): http://pubs.acs.org/doi/pdf/10.1021/acs.nanolett.5b04372 on power spectrum for electric-field-driven ion transport through nanopores. Apparently Pink noise (noise that has power law power spectrum, instead of flat, as for white), is common place in situations with electric fields, and underlying mechanism not totally understood.
[[https://en.wikipedia.org/wiki/Point_process]]
Stochastic processes with JS: https://www.npmjs.com/package/stochastic
//Links//
<small>
[[Notes on Nonequilibrium StatPhys MT2015 Oxford (mostly stochastic processes)|https://files.acrobat.com/a/preview/254ad767-71f3-429e-b36b-3d77cf67a6c7]]
[[Nice lecture notes|http://www.thp.uni-koeln.de/~as/Mypage/NonEq/noneq.pdf]]
[[Discrete Stochastic processes MIT course|http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-262-discrete-stochastic-processes-spring-2011/index.htm]]
[[Stochastic processes MIT notes|http://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/lecture-notes/MIT18_S096F13_lecnote5.pdf]]
[[Nice notes on applications of stochastic processes|http://www.math.uwaterloo.ca/~mscott/Little_Notes.pdf]]
[[Wikipedia: Stochastic process|https://en.wikipedia.org/wiki/Stochastic_process]]
[[List of stochastic processes topics|https://en.wikipedia.org/wiki/List_of_stochastic_processes_topics]]
</small>
!!!<mark>Watch</mark>: ''[[Physics - Physical Applications of Stochastic Processes by Prof. V. Balakrishnan|https://www.youtube.com/playlist?list=PLbMVogVj5nJQo8D9D-D6lMqh4FJbPeE_f]]''
--------
''Stochastic processes''
[[Probability theory]]
[[Martingales|https://en.wikipedia.org/wiki/Martingale_(probability_theory)]], [[Martingales Through Measure Theory|https://www0.maths.ox.ac.uk/courses/course/28722/synopsis]]
!! Examples
* [[Brownian motion]]:
** Paths appear non-differentiable, in continuous space-time limit!
** In path description, the //noise term// is chosen to be [[Gaussian white noise]].
!! Classification of models
[img width=500 [types_of_random_processes.png]]
* Discreteness
**Discrete space-time
***One-step process (can be continuous time too)
****[[Unbiased random walk|Brownian motion]]
****[[Biased random walk]]
****[[Persistent random walk|https://www.youtube.com/watch?v=hHciEDpm1sE&index=9&list=PL04QVxpjcnjjDk2ESwBZ1sEcKu91wDV5l]] (it can be seen as having memory, i.e. being non-Markovian).
***Multi-step processes
**Continuous space-time
***[[Diffusion]]
***[[Kramers-Moyal expansion]]. To get continuous models from discrete ones.
***Orientation space. See [[Stochastic dynamics of orientation]].
**Continuous space-discrete time
**Discrete space-continuous time
*Memory
**Memoryless (only dependent on current state) $$\rightarrow$$ [[Markov process]]. Most of the stochastic processed used and studied in practice are Markov.
!! Descriptions
All these generally are Markov processes
*Continuous space-time
**__Path description__
***Stochastic differential equations. Like: [[Langevin equation]]
***[[Path integrals for stochastic processes]]
**__Probability description__. Obtained from path description by averaging, essentially. Gives differential equations for probability density, like:
***[[Fokker-Planck equation]]
*Discrete space
**Probability description $$\rightarrow$$ [[Master equation]]
***Discrete time $$\rightarrow$$ Difference equation. //Discrete time master equation//.
***Continuous time $$\rightarrow$$ Differential //Continuous time master equation//.
*Continuous space-discrete time //??//. An example is the beginning of the derivation for Brownian motion by Einstein
!! Important results
*[[Dissipation-fluctuation relation]]. Friction and dissipation are due to the random movements of particles. Fluctuations are too. The coefficients describing them (diffusion coefficient and viscosity) should be related.
!!Computational methods
[[Monte Carlo method]]
!!Other mathematical aspects
https://en.wikipedia.org/wiki/It%C3%B4_calculus
!!Applications
__Chemistry__
[[Chemical kinetics]]
[[Oscillating chemical reactions]]
__Biology__
[[Enzyme kinetics]]
__General phenomena__
[[Number fluctuations]]
__Others__
[[Telegraph noise]]
[[Complex systems]]
-----------
Recent paper by Ramin Golestanian (26th Feb 2016): http://pubs.acs.org/doi/pdf/10.1021/acs.nanolett.5b04372 on power spectrum for electric-field-driven ion transport through nanopores. Apparently Pink noise (noise that has power law power spectrum, instead of flat, as for white), is common place in situations with electric fields, and underlying mechanism not totally understood.
[[https://en.wikipedia.org/wiki/Point_process]]
Stochastic processes with JS: https://www.npmjs.com/package/stochastic
iVBORw0KGgoAAAANSUhEUgAAAn0AAAE0CAIAAADWrhKjAAAAA3NCSVQICAjb4U/gAAAAEHRFWHRTb2Z0d2FyZQBTaHV0dGVyY4LQCQAAIABJREFUeNrt3XdAU1fDBvATgpQNInspIlsLWlCLWvfmq6JYHIjj1VpFqzhQQcWCUkfrBFxtLaDoq9BWUWvddVQU2SAgU4aEDQkzkOT747a8EZBCIJCQ5/cXntzcnJwb8+Tce+45NB6PRwAAAKBHSKEJAAAAkLsAAADIXQAAAEDuAgAAIHcBAAAAuQsAAIDcBQAAQO4CAAAAchcAAAC5CwAAAO2QRhMAAPCLjo7esmVLi0IajaagoDBgwICRI0e6uLioqKhIVE1EuUpih4b5mQEA+N27d2/q1KmEEDqdzl/O4XCoPzQ1Nf/8809zc3PJqYkoV0ns4DwzAEAbrK2tm95XVlZ269YtCwuL4uJiV1dXCayJKFcJuQsA0NeoqanNnDnz1q1bUlJSUVFRqampqIkoVwm5CwDQFwwaNMjQ0JAQkpOTg5qIfpWQuwAA4q2srKywsJAQoq2tjZqIfpWQuwAAYiwnJ8fZ2bmhoWHYsGHW1taoiYhXSTThPiIAgDa8efPG1ta2+Z8cDqesrCwvL48Qoq+vf/nyZRqNJmk1EeUqIXcBAMRbXV1ddHQ0fwmNRps+ffqsWbNWrlypqKgogTUR5SqJEZxnBgBog7W1NY/H4/F4HA4nLS1t4cKFPB6vuLj4888/7+FcEZ2aiHKVkLsAAH3lW1JKytTUNDQ01MnJKTY2dvLkySUlJRJeE1GuEnIXAKAvoNFoP/74o5GRUVZW1vLly1tvwOVy//jjD1GoCSEkPT09IiKixang3q1SWlratWvXMjIy8FlC7gIAdIiysvJPP/1Eo9Fu3boVFBTU4tFdu3Zt3LhRFGri4eHx2WefhYaGLlmyZObMmY2NjaLQOFOnTg0LCxs/fryvr6+kf5J4AADA5+7du4TvEmYLq1evJoQMGDCguLiYKsnNzZ01a5aioqKZmVnv1oTH4yUmJsrLyxcUFPB4vIaGBjMzs59//rl3q5SWliYjI5Ofn0/9TafTi4qKJPkDhv4uAEAnHDp0SFtbu6ysrLl3e/LkSTMzs3PnzvV6TQghioqK586d09XVJYTIyMgYGxsXFRX1bpUMDQ1jY2P19PQIIQoKClwul81m4zwzAAB0iKqq6okTJwghly5dunXrFiHkwIEDR44c6flxvK1rQggZNGjQ4sWLqb+Tk5Pv378/ZcqU3q2SrKyspaVlbW3t999/P336dC8vL319fUn+CGEdQACAbnDjxo2tW7eKznoA6enpkydPXrly5d69e0WhPgwGIzAw8K+//mpoaLh27Zqamhr6uwAA0Ef89ddf9vb2a9asEZHQJYRoa2v7+PjcvXu3oaHh5MmTknx0kLsAAH3KrVu3Zs2adfz4cS8vL1GoT1xc3NGjR6m/aTSaubm5hN/ji9wFAOg7srOzv/jii0OHDk2aNInBYDAYDBaL1btV6tevn6enZ0xMDCEkIyPj5s2bM2fORO4CAEBf8NNPP9XU1KxZs0bnH998803vVsnKysrf33/q1KnDhg0bOXLk9u3bZ8+eLcnHCOOqAABA6NhsdkFBgb6+fr9+/SS8KZC7AAAAPQfnmQEAAJC7AAAAyF0AAABA7gIAACB3AQAAALkLAACA3AUAAEDuAgAAAHIXAAAAuQsAAADIXQAAAOQuAAAAchcAAACQuwAAAMhdAAAAQO4CAAAgdwEAAJC7AAAAgNwFAABA7gIAAAByFwAAALkLAAAAyF0AAADkLgAAAHIXAAAAkLsAAADIXQAAAEDuAgAAIHcBAACQuwAAAIDcBQAAQO4CAAAAchcAAAC5CwAAgNwFAAAA5C4AAAByFwAAAJC7AAAAyF0AAABA7gIAACB3AQAA+i5pNAEASIKff/65deHQoUNtbW3ROMLz9OnTjIyMFoWysrILFy5E7gIA9GUrVqyYO3cunU7nL5SSkkLuClV8fPzDhw/5S2pra1++fCnJuUvj8Xj4ZABA3/+yo9FYLJaioiKaonfl5OTY2tqWlpZKbAvg+i4AAAByFwAA/lFYWOjh4TF16tRx48Zt2LAhLS1NFGr18OFDGxub169fS9SxyMzMzMjIYLFYyF0AgL7p1atXZmZmhw8fzs7OZjAY/v7+NjY2N2/e7N1a5ebmLlu2LD4+vra2VnKOxcWLF4cMGWJiYnLs2DHkLgBAH9TQ0ODo6FhbW3vlypWMjIz09PSIiAgej+fi4lJeXt5btUpISJg4cWJeXp5EHQsmk7lt2zZDQ0NCSFRUFHIXAKAPCg4Ozs/Pd3V1XbBgAVXi4OCwY8eOysrKwMDAnq9PfX39t99+O3r06OzsbGVlZYk6Ft7e3oWFhUeOHNHU1ETuAgD0TeHh4YQQZ2dn/sJFixYRQn799deer4+7u7unp6eqqmpERISdnZ3kHIjExER/f/9x48bNnz9/+PDhDAYjPz8fuQsA0NfExcURQoYPH85faGZmJisrm5SU1NTU1MP1UVZW3r17d2pq6uzZsyXqQLi5uXG5XOqyLnU4BO7yYt4MAAARxWazi4qKZGRkNDU1Wzykq6ublZXFYDD09fV7skoHDx6UwAMREhLy5MmTlStXjhgxghBibW1NCHn58qWjoyP6uwAAfQd1s4qCgkLrh6jCmpoatJKwVVVVeXh4KCkp7d+/nyqhchf9XQCAvoaaT1Bauo0vaqqQzWajlYRtz549DAbjwIED2traVImpqamcnNyrV694PB6NRkN/FwCgj6A6tQ0NDa0fqqurI4TIycmhlYQqISEhICBg4MCBX331Vf0/GhsbLS0tq6qq0tPT0d8FAOg75OTk5OXlWSwWm82WkZHhf6isrIwQoqGhgVYS6vkGNzc3Dofz9u1bVVXV1htERUWZmpoidwEA+g4LC4vo6Ojs7GwzM7PmQiaTWVJSoqWlpaKigiYSnuDg4KdPn1pYWEyaNKnFQ2lpaffu3YuKilqyZAlyFwCg7xg/fnx0dPSDBw/4c/f+/fuEkIkTJ6J9hIcaTiUlJRUcHNx6scjHjx9TuSvAnnF9FwBAdC1dupRGox0+fLiyspIqqa+v9/X1JYS4ubmhfYRn165dxcXFK1asaHOF5o8//pgQEhsbK8At1MhdAADRZWNjs2bNmuzs7FGjRgUEBJw7d87e3j42NtbFxWXs2LFoHyGJi4s7deqUioqKn59fmxuoqqoaGBjU1dUlJyd3duc4zwwAINL8/f0VFRX9/f3Xr19PCJGRkdm0aZNkzl/RM5qHU+3Zs6f1jCXNrK2t8/LyXr58Sd3O23E06v4wAIC+jUajsVgsRUVFMa1/dXV1cnKytLS0qampkpKS+B6InJwcW1vb0tJSif0oor8LAJKi52cz7kaKioqjRo3qA0ehrq6uzTuSJQeu7wKApGhsbEQjiELu1tfXI3cBAPo+zO4kCjQ1NduccRq5CwAAAMhdAAAA5C4AAAAgdwEAAJC7AAAAyF0AAABA7gIAACB3AQAAALkLAACA3AUAAADkLgAAAHIXAAAAuQsAAABd1dH1d7k8Xn0TB+0F0JP60aX6SeHHMXTIw4cP3d3dQ0NDLS0tUY3uxWKx4uPjGQwGjUbT09OzsbGRlZUVeu4y2exXjBJ8sgF6kqGykml/FbQD/Kvc3Nxly5bl5eXV1taiGt0oNjbW19f3xo0b/Is3KygoLF++3NfXt3///kLMXQAAEE0JCQmOjo55eXmoRvfy8fHx8fHhcrkTJkyYOXOmvr4+k8lMTEwMCgoKCAi4c+fOs2fPNDQ0kLsAAJKivr7+6NGjvr6+9fX1ysrKTCZTkqvRvXbv3r1v3z4jI6MLFy7Y29u3eGjatGkJCQlbtmwJDg7u7J5x6QgAQFy5u7t7enqqqqpGRETY2dlJeDW60ePHj/38/PT09J48edIidAkhWlpaly9fHjFihLm5uQA7R+4CgKRoamrqY+9IWVl59+7dqamps2fPFpdq1NXV8V8rFU0bN27kcrkBAQF6enptbmBhYREdHe3p6SnAznGeWYxdDwmePNdRQUkJTQHQEaL/dd9ZBw8eFLtq1NbWstlsUW7V+Pj4uLg4MzOzOXPmCGP/6O+Kq8Lc3FPfeH/UhbHsAJJGTk4OjdDrBgwYoKCgIMo1DAsLI4Q4ODgIaf/IXXGVnpQ40NRMul8/NAUAQDdKSkoihAwfPlxI+8d5ZnGVkZxsMnQoIaSupubApq/NbWwWuW1AswCIu7y8vLKysnY2UFVVHTRokIRUo1dQb1xdXV0Uczc9MfH0Pp8WhTQaTVZeXrl/f3Nrm8mO88Tl6mNtTXXW65TykmIajaaurW1saSXz0UdtbFZdXVla+l4LyvRTURvQ8+d7M5ISR0+eUlFa6rXCdcy0Gb0Sul1pjQ42OICkCQgIuHz5cjsbzJo1KzAwUEKq0Sv69etHCOFwhDVFY5dyl1VVmfAikhAiRafzl3M5HELI3fCwkOPHjly5amA8RLQ7jkkXThx/cf8e/1hHWXn5aU4LVmzZpqjy3mxB/z0dGOp/ssUepOh0k6FD5y5bMWXe/J6s9tT5TlsXLli0bn1Pvm7XW6NTDQ4gaQ4cOHDgwAFUoxcNHjz4wYMHycnJs2bNanODgoKCuLg4gceQd8N55sEWlmd+/+O9PK6sTImLPbPPJzcj4+DmTf7Xbohs+144fizkxDEel2s9+lO7CRM1dHRqqlnZqal3w8OuBwdFP3l8PPxXFbUBfL3MJELIpDlz9YyMqJK6mprcjIyoPx8d3LwpJS52g8++njgNUlRUUVp6Zr+vlJTUeIf/ay5/l5PDZrMHmZr2VJ+7063R2QYHAOhh06dP/+GHH86fP+/u7i4t3TIlq6qqHB0do6KiwsPD582b1zu525qSqurICRMHDjFZ+tmYtPj4vMwM0ezy/vz94YsnT2gbGOw4dsLqE1v+h1y+3rTDZXFWasrpfb7bjxzj76sRQpZuctc3Gsy/fUpszNaFX1wPDpo638nc2kbYNU9PShygpXXkv2HfeWz57efzC75cQwhJT0zct2Gd60b3nsvdTraGAA0OANDDHB0dLS0tX79+vWrVqtOnT/MvgRAZGblixYrU1NS5c+c6OjoKtn8hjmfW0tfX1NUlhDDy8zv1RB6Pd+NiyI2LIcyKCuFVL/Hli9AAf3Vt7aNXf2mRAYSQ/urqXv6BJkOHGRobNxeWFxeXl5TIKyjqDTJqsb3F8BHjZs0mhMT99axnOpo2n9rrDhr0n+07LwX6V1dVcTmcsB/Ojps5q8c+mp1tDQEaHACg59Hp9LCwMF1d3aCgIGNj43Xr1n377bc7d+60t7f/9NNPU1NTV61adeXKFRqNJtj+hTiemVlRUV5cTAhR6+S00VwO57iXJ/X1rSzQag8dEbDXm8flbvDdr66t3eYGhkOGBN641aKXSQgZbGnRZnNTI8g4PbJaYkZykpWtHSHE6hPbYXYjLwX6r97ptfP4yV9++qGLe94w9/OV2zyGjxnbkT53p1pDgAYHAOgVFhYW1EpEoaGhp06d+jsvpaUdHBw2btw4ZcqUruxcWLlblJ///fZtjWy2kbn5YIvOrcJIo9FMhg0jhHwktJvcs1JeZ75ONhhsbD91WmfSLpkQYjJ0WJuPpsTGEEIGmZn1wGdi79n/5es3537sxj3PcV2298vVB0Mv/evZ8k61hmANDgAdd+/ePVSjG2lqap48efLYsWNv376tqKiQl5c3MjKS7Y5bV7ohdwuys9b93yy+3iqXWVFRUviOEKKho+N1MrCznXEpOj0wQrj9nse3bhJCRk2e3KlnUT28IVZDW5TzeLxLAf7piYlaevp24yeI9Udt8lzH6yHB2xcv+ubcDzb2Y7qrNQRrcACA3kWn0wcPHty9++yG3G2or09PTGzRYbX9bPzIiZNmfOEsJ5LzgeWkpbWZGf/Sw0tKIoTEP39ekJP9d8ZweZXlZfGRz9/l5Cipqu45dUbcb0KlSUntPH5yncNMz+Wum/wOTHNa0C2tIViDAwD0Pd15HxGPyy14mxN85PuHEdcry8rsp06TE9VJOJmVFYQQFTW1jj+luqqqqCCfEHIn/GqLh7QNDJxWrf7iq3X9hTa/SQfNW7mq6zvRMTTcHXjac7nr4a2b0+LjvvTa3XoejM62hgANDgCA3P33rpK+0eCdJ/w5HM7jWze3LXY++dt10bwXky7dj/wzv0cHUadVjS2tfH88z38KQkFZuf3pmdITE/etX9st1Z6/6svwH84K8MSmxkZqjFszVXX19rvmdDqd09R0PSQ4JS629Wn/zraGAA0OAIDc7Vj60mhbDn33JjGhMDf30JbN+88HieDb1jE0jPvrWc6bNyMnTmpzg1IGI/N18qhJk/mSJokQYmZtraGj06nXMjA23nPqTLdUW01Ty+qTTwR4YiObzcjP4y/R0NGV/fCwtYrSUp+1a0hDg+6gQWu8drf1K6RzrSFAgwMAIHc7Sl5Rcevh77ctcn758MGd8KvT5re8RsjjcqOfPrH9bHxvvW3bz8b/fvnSH1f/O/8/q+itpiOpYbH2rlmVFh/vffrs2BkzqUJqjggBrlDKyssbW1p1V80FPpVtbtPRtTWaGhuPe3nW1dSMmT5j+5FjbV4s6GxrCNDgAAB9krDmzbAe/enMhYsIIWf2+VaVt1zU4vx3hwP3erfz9DcJCW8SEhrq64VUvbHTZww0McnNyDiy3YPd0MD/UEpszIa5n6fFx4+ZNn3M9Bn/S5qkJEIItQRQ3/bT4YMpsTHOa9d5nz77oSv0nW0NARocAAD93c5ZvdMr8t7d8pKSgL3enif8qcKSwnfHPHcmvnyhrqX9oSdymprcPp9NCDl963Y39hTf+7lBp+85ddZjycI74Vejnz62nzpNQ1e3llWd8CLydUw0IWTmwkVf7/NrvgOqrqYmPydbik43Mrfo2x+IrNSUsB/Ordzm0c4CRwK0RmcbHAAAudtpisrKbnt9fN3WPrx+bYrjPOrC3m8/nzcYbDxl3vyQo0d6950bDhly+tbtCyeOP7j2W8SFEKqQLi09evIUxxUrR4wd914apbzmcbkDTU17fr2/HhZ89IjzmrXtryooWGt0qsEBAPoqGo/H68h2lQ0NrxglXX89HpdLk5KKvH/v7P59Pz14JApNwOVwigoKqquqPpKT0zYwkPBVYGOePhF2BKLBO/FjRVnJtD8WRuymLzsaraKiQlVVFU3Ru9LT021sbGpqatDf7amPvpSUqDWBFJ2uY2iI/wyUHuh3osGhtzQ2NqIRel1tbS2bzZbkFpDChwAAJISc0KZ8h44bMGCAgqhOqYTcBQAAQO4CAAAAchcAAED0SffKq46ePGX05ClofQCA7vLw4UN3d/fQ0FBLS0vhvUphYeHRo0djY2Pr6+ttbGzWr19v1iOLjvcKJpNZ/P7M9jIyMhoaGl0cKID+LgCA2MvNzV22bFl8fHxtba3wXuXVq1dmZmaHDx/Ozs5mMBj+/v42NjY3b97sq6166NAhk/cNHDhQSUlp5MiRISEhYtbfBQCA7pKQkODo6JiXlyfUV2loaHB0dKytrb1y5cqCBQsIITdu3HBycnJxccnMzFTri6t8xsTEEEIWL15sYmJClVRXV6ekpNy+fdvV1fXFixf+/v7IXQAACVJfX3/06FFfX9/6+nplZWUmkym81woODs7Pz1+xYgUVuoQQBweHHTt2fPPNN4GBgbt27ep7zRsbG0sI8fb2NjU15S+PjIycOHFiQECAq6vryJEjO7tbnGcGABBX7u7unp6eqqqqERERdnZ2Qn2t8PBwQoizszN/4aJFiwghv/76a99r28LCQgaDoaSk1NzZbTZ69GgnJydCyIMHDwTYM3IXAEBcKSsr7969OzU1dfbs2cJ+rbi4OELI8OHvrShqZmYmKyublJTU1NTUx9qWOslsbW3d5notKioqhBDB3jXOMwMAiKuDBw/2zAux2eyioiIZGRlNTc0WD+nq6mZlZTEYDH19/b7UttRJ5hEjRrT5aGRkJCFkqEArwyJ3AQDgX7BYLEJIm/M7UoV9b50Dqr/bon9PCOHxeH5+ftHR0QMHDpwxQ5Alw5G7AADwL6iV66Sl24gMqrDvLXVA5e6jR48yMjKoEi6XW1JSQpWoqamFhYXJCrQyLHIXAECE5OXllZWVtbOBqqrqoEGDerhWVKe2oaGh9UN1dXWkz605UVFR8fbtW0JIUFBQi4eMjIw2b97s4eGhpaUl2M6Ru5Luekjw5LmOCkpKaAoAURAQEHD58uV2Npg1a1ZgYGAP10pOTk5eXp7FYrHZbBkZGf6HqF8JGhoafa+za2NjExER0VxIp9NVVVW7/gsDuSvRCnNzT33jPWvhIjQFgIg4cODAgQMHRLBiFhYW0dHR2dnZ/BNDMpnMkpISLS0tanxvH8tdOzs7YQwWw31EEi09KXGgqZl0v35oCgBo3/jx40mrO1bv379PCJk4cWIfe7PUYObWg6qQu9BVGcnJJkOHEkLqamq8V//nUsBJtAkAtGnp0qU0Gu3w4cOVlZVUSX19va+vLyHEzc2tj71Zqr/7oZuIkLvQhdxNSjQZOqyitHTLwgWmH1svctuANgGANtnY2KxZsyY7O3vUqFEBAQHnzp2zt7ePjY11cXEZO3ZsX3qn1dXV6enpdDr9448/Fsb+Bbm+m56YeHqfT4tCGo0mKy+v3L+/ubXNZMd5YjdOp7amOut1SnlJMY1GU9fWNra0kvnoI2G9VnV1ZWnpe4dBpp+K2oCPBBqS3rX+btLU+U5bFy5YtG79lHnzxetAiE4zgrjoe3Mq9TB/f39FRUV/f//169cTQmRkZDZt2tTZuTvq6uoaGxtF+W3Gx8dzuVwrKyshDdKmUXdl/avKhoZXjJK/O+BPn2x3WUwIkaLT+bfhcjjUH6oD1I9cuWpgPEQ8+nzJSRdOHH9x/x7//0lZeflpTgtWbNmmKITBAue/OxTq3/KMrhSdbjJ06NxlK3os/8qKihaOsh2gpSUlJRX059N+749RFP0DISLNKFSGykqm/cVvuEpiYuKJEycePHhQWFjIZrPV1NSGDx++ZMkSFxcXKaleO8dGo9GKi4v72LDb3uoOJicnS0tLm5qaKnW+ixUfH29rayvi0Svcj6LAuTvYwvLM73/wb8OqrEyJiz2zzyc3I8PM2tr/2g3Rf/8Xjh8LOXGMx+Vaj/7UbsJEDR2dmmpWdmrq3fCwupoaPSOj4+G/qqgN6N4X9Vru+vLRw0lz5uoZGf39A7CmJjcjI+rPRzwu93PXZRt89vXAe4+8f++Y544j/w37zmPLp1OmLfhyTfNDKbExqXFxFsOHm9sMF9kDISLNiNxt4aeffvryyy85//wK5zdt2rRr167J9tIJCRqNxmKxFBUVEZy9Kz8/f+jQoc0XiZG7XcpdSlF+/tLPxvC43J/uPxTxLu/P3x++ePKEtoHBjmMnrD6x5X+oorR0h8virNSUKfPmbz9yrHtf19luRHlJyfmHf+obDeYvT4mN2brwC3ZDw8lrEebWNj0QdfnZWTuOnUiOfrX7PyuC/3xK9Smjnzy+GXpx/qrVlwMD5q9abfOpvWgeCBFpRuTueyctMjLMzc2p0NXT0xs5cqSMjMyrV68yMzOpDbZt23bo0CHkLnJXknO3+8/5aOnra+rqEkIY+fmC7YHH4924GHLjYgizokJ47zzx5YvQAH91be2jV39p8V1PCOmvru7lH2gydJihsXFH9laYm5uXmdGRLcuLi8tLSuQVFPUGGbV4yGL4iHGzZhNC4v561hNfkclJxpZWhBCrT2yH2Y28FPj3As6y8vJrvHZbfWI7frbDm4QEYVdDsAMhOs0I/EJCQqjQnTdvXnZ29i+//HL58uU3b964urpSG/zwww9tdoUBJEf3z5vBrKgoLy4mhKgJeh2Fy+Ec9/KkvkCV+/cX0jsP2OvN43I3+O5X19Zuu6sxZEjgjVsd3NuDa79VVZSv27P3X7dMT0okhAy2tGhzbSlqPBqnqSe+mPae/aH572/O/dj8NxV+1VVV14J+3hVwqisvsWHu5yu3eQwfM7bbD4ToNCPwKygo+PvXj4VFv3/uC5eSkvLy8nry5ImCgoKCgkJ5eTkusgJyt9sU5ed/v31bI5ttZG4+2MJSsJ3QaDSTYcMIIR8JbcLPrJTXma+TDQYb20+d1sMtnpGcTAgxGTqszUdTYmMIIYP4poPpFSWFhX5fu33ptUura3O1zHFdtvfL1QdDL33ofK/AB0IsmlECDRny96Wlw4cPs9nspUuXDhs2jBBiamqalZWF9gHoUu4WZGet+79ZfJ1ULrOioqTwHSFEQ0fH62Rgmx2RjpCi0wMjbgn1bT++dZMQMmry5J5vcaqjNsSq5aqNPB7vUoB/emKilp6+3fgJvfiZKCsq2ue2dvPBwwNNTLq4q8lzHa+HBG9fvOibcz/Y2I/pxgMh+s0omZYvX/7tt98ymUw2m3348OHDhw/r6OhMnDhxxowZc+fOVcI04ABdyd2G+vr0xMQW/VTbz8aPnDhpxhfOcm0t0yg6ctLS2vzW7on+blISIST++fOCnOy/o4LLqywvi498/i4nR0lVdc+pM8K7dbgjgo8dKSsuOrpzOyFkiqOjw5KlAu+KJiW18/jJdQ4zPZe7bvI7MM1pQXcdCNFvRsmkra3922+/zZ8/v+KfwRmFhYWhoaGhoaEKCgoeHh6enp5triVHYTAY7Q+3UVZW1tXVRTuDhOZu83hmHpdb8DYn+Mj3DyOuV5aV2U+dJuKhSwhhVlYQQlTU1ATeQ1V5WQ2T1fxPVmVlDZP5LienuURWQaH1Fe7qqqqignxCyJ3wqy2/sAwMnFat/uKrdf3V1Xu3cdy/PdiNe9MxNNwdeNpzuevhrZvT4uO+9NrNP6+FYAdCLJpRYk2cOPHNmzcBAQGhoaFv3rxpLq+pqfH29s7MzGy9sFqzI0eOhIaGtrPz2bNnnzlzBo0MEpq7/H0afaPBO0/4czicx7dublvsfPLihwFjAAAgAElEQVS3691+z2v3okv3I3wTfQjgypnTD6791vzP2upqHo8X8/RJc8moSZM3+bVcVIQ6O2psaeX74/n/VYZOV1BW/tdZltITE/etX9v1997IZvN4vK70BZsaG6mhc6rq6h3cD51O5zQ1XQ8JTomL5b+IINiB6EozQg9QV1f39vb29vbOzs5++PDhnTt3rl+/Tq3SGhwc7ObmNnLkyDafeOjQod66ywhAnHL37/Sl0bYc+u5NYkJhbu6hLZv3n2/jJ21BdnZeZsYALW1q2FQv0jE0jPvrWc6bNyMnTmpzg1IGI/N18qhJH7zuuHqn1+qdXs3/vHjyREfGM6cnJRFCzKytNXR0OltnA2PjPae64Zd+Q309j8eT7cKYtUY2m5GfRwjR0NHtyH4qSkt91q4hDQ26gwat8drd9QPRlWYE4WGz2a9fvy4sLCwtLV26dCkhxMjIyMjIaOXKlYWFhWPGjMnOziaE/PHHHx/KXQDkbufIKypuPfz9tkXOLx8+uBN+ddr89y7mnft2/71fwq1Hf5qRnKxtYODz4/l2LvMIm+1n43+/fOmPq/+d/59V9FbVqGGx9q5ZlRYf73367NgZM7vxdTOSk4ig15Vl5eWp221FQcfnsWpqbDzu5VlXUzNm+oztR461uAYh2IHoSjOC8FRWVjavm2Ztbc0/p7yOjs7YsWOp3C0vL//QHkpKSqqqqtp5CUVFRe0P3G8GIC66ed4M69Gfzly4iBByZp9vVXlZc3lOWtq14KDAG797ngw4+8ddRl7eg2u/trOfNwkJbxISGurrhfS2x06fMdDEJDcj48h2D3ZDA/9DKbExG+Z+nhYfP2ba9DHTZ3Tv61Kjgail9yTET4cPpsTGOK9d5336bOsL/4IdCAlsRrGgqalpZfX3T8PNmzfzT8DLYDDu3LlD/W384blo/Pz8RrfL09MT7Qzo77a0eqdX5L275SUlAXu9PU/8PQWSnILC5gOHBmhpEUKk+/XTGTiwoqT0Q3vgNDW5fT6bEHL61m0h9fCk6PQ9p856LFl4J/xq9NPH9lOnaejq1rKqE15Evo6JJoTMXLjo631+At8K1aa6mpr8nGwpOt3I3EJCPl5ZqSlhP5xbuc3jQysMCnAgJLAZxYi7u/uqVasIIffv37eyslqwYIGGhkZOTs6FCxfKysoIIbKyss7Ozh96+tGjR48ePYpmBORu5ygqK7vt9fF1W/vw+rUpjvOo63Za+vrNMzDkvHkT++zp8i1be/edGw4ZcvrW7Qsnjj+49lvEhRCqkC4tPXryFMcVK0eMHdf9IZTymsflDjQ1lZyxP8FHjzivWdv+sr6dPRAS2IxiZOXKlXfu3Lly5QohJD093c/Pj/9RGo127tw5TFYFEk6QdRG6oiA7e9vihTOcnV03bRaRJuByOEUFBdVVVR/JyWkbGOCmz24U8/RJx3/B4EC08aNEDNcj4nK5gYGBR48e5Z+gSlpaesyYMb6+vuPGjeutimFdBBGBdRF6NHeTo195r/7PvJWrFq/fgA8fQJ/M3WZ5eXlv375ls9n9+/c3NjZWVlbu5S875C5yVzT03Ijilw8f+H29/ut9fpPmzMUnD6DPMzAwMDAwQDt0u4cPH7q7u4eGhlpaWqIm3YvFYsXHxzMYDBqNpqenZ2Nj0+Zy0Uwms7i4mL9ERkZGQ0NDrmP3Z/ZQ7jLy8nzd1n61a4+N/ZjykhJCiKy8nLwCfngCAHRCbm7usmXL8vLyamtrUZNuFBsb6+vre+PGDf5x+AoKCsuXL/f19e3//sp4hw4d2r9/f4s90On0ESNGbNiwgbp5vfdz9/aVy/W1tcc8dxzz3EGVOK3+ssUUCgAA0I6EhARHR8e8vDzUpHv5+Pj4+PhwudwJEybMnDlTX1+fyWQmJiYGBQUFBATcuXPn2bNn/OMBY2JiCCGLFy82+WfxmOrq6pSUlNu3b7u6ur548cLf37+dl+vpcVUA0HFifX1X1NBotIqKClVVVXGsfH19/dGjR319fevr65WUlJhMZlRUlK2trTjWJD093cbGpqamRkTadvfu3fv27TMyMrpw4YK9vT3/Q0VFRdOmTUtISFi6dGlwcHBzuY6ODoPBSEtLMzU15d8+MjJy4sSJ9fX1L168aGdSNin8bwQACcF/ClG8uLu7e3p6qqqqRkRE2NnZiXVNamtr2Wy2iDTs48eP/fz89PT0njx50iJ0CSFaWlqXL18eMWKEubl5c2FhYSGDwVBSUjJptVLq6NGjnZycCCEPHjxo50WRuwAgKeS6MC1571JWVt69e3dqaurs2bPFvSYDBgxQEJk16zZu3MjlcgMCAvT09NrcwMLCIjo6mn+iNOoks7W1dZsTK6moqBBCmpqa2nlRafxXBAAQcQcPHkRNul18fHxcXJyZmdmcOXM6/qzY2FhCyIgRI9p8NDIykhAytN1ZbJG7AAAgicLCwgghDg4OnXoW1d9tXgKkGY/H8/Pzi46OHjhw4IwZM5C7AAAA70lKSmozQTuSu48ePcrIyKBKuFxuSUkJVaKmphYWFibb7iy2yF0AAJBE1Fod6urqHX9KRUXF27dvCSFBQS3XmDcyMtq8ebOHh4eWllb7O0HuAgCAJOrXrx8hhMPhdLaza2NjExER0VxIp9NVVVU7PmoP45kBAEASDR48mBCSnJz8oQ0KCgpu3rzZOnft7Oz0+ejo6HRqqDxyFwAAJNH06dMJIefPn2/ztp+qqipHR0cHB4dffvmluZAazNzZS8LIXQAAAOLo6GhpaZmSkrJq1ar6+nr+hyIjI0ePHh0VFTV37lxHR8cW/d0P3UTUQbi+C4K4HhI8ea6jgpISmgIAxBSdTg8LC5syZUpQUNDdu3fnzJljYGDAZDL//PPP58+fE0JWrVoVGBjYPD9GdXV1eno6nU7/+OOPkbvQowpzc0994z1r4SI0BQCINQsLC2olotDQ0FOnTv2di9LSDg4OGzdunDJlCv/G8fHxXC7XysqqixOfYV0E6LTHt26G+p88fes2mkLYsC5CN8K69yJCNNe953A4b9++raiokJeXNzIyav8G3C5Cfxc6LSM52WToUEJIXU3NgU1fm9vYLHLbgGYBAPFFp9Op4c09QJDcTU9MPL3Pp/VvSVl5eeX+/c2tbSY7zhO7K3+1NdVZr1PKS4ppNJq6traxpZXMRx/1ZAXevX1LeDxVDXV5hbZ/j9dWV1eWlr538GT6qagN+EiYv8vazt2kxNGTp1SUlnqtcB0zbYYohG4HD5/otGFHjjgA9EmC5C6rqjLhRSQhRIpO5y/ncjiEkLvhYSHHjx25ctXAeIiY9N6SLpw4/uL+Pf6h5LLy8tOcFqzYsk1RpSfO8t3/7dcDm74mhCzbvNXl641tbvPf04Gh/idbFErR6SZDh85dtmLKvPk92WJT5zttXbhg0br1Pfm6XT98otOGHTniAIDcfc9gC8szv//xXh5XVqbExZ7Z55ObkXFw8yb/azdE//1fOH4s5MQxHpdrPfpTuwkTNXR0aqpZ2ampd8PDrgcHRT95fDz8VxW1AcLtq1VXn/Xbp6mrV/yuIC0h/sO9zCRCyKQ5c/WMjKiSupqa3IyMqD8fHdy8KSUudoPPvh5osbKioorS0jP7faWkpMY7/J94HT4RacMOHnEAQO7+CyVV1ZETJg4cYrL0szFp8fF5mRki3uX9+fvDF0+e0DYw2HHshNUntvwPuXy9aYfL4qzUlNP7fLcfOSbUagQd+b68uHjPqTMndnm9iY9rp2NHCFm6yV3f6L2LECmxMVsXfnE9OGjqfCdzaxthN1p6UuIALa0j/w37zmPLbz+fX/DlGqo8+VVUVmqq3fgJ2gYGInv4RKQNO3jEAaBP6v55M7T09TV1dQkhjPx8wfbA4/FuXAy5cTGEWVEhvHee+PJFaIC/urb20au/tPjWJoT0V1f38g80GTrM0Ni4I3srzM3Ny8wQoBrZqanXgn8eNnLkuJmzhlhZlZeUlBQWtt6svLi4vKREXkFRb5BRi4csho8YN2s2ISTur2c98InJSEqy+dRed9Cg/2zfeSnQv7qqihAS9/yvq+fOGpmZf7dtS1V5WQ9UQ4DD171tKOwjDgDI3Y5iVlSUFxcTQtQ0NATbA5fDOe7ledzLs6TwnfDeecBebx6Xu8F3v7q2dpsbGA4ZEnjjVgcHDT249lvExQsCVOPkHi8ul7t2z15CyBCroYSQN22deExPSiSEDLa0aL6Dmx81io3TxOmBT0xGcpKxpRUhxOoT22F2Iy8F+hNCtPUNvt7nN9TOTl1bu7y4S/ebbZj7eeyzp8I4fN3bhsI+4gDQV3XzfURF+fnfb9/WyGYbmZsPtrAUbCc0Gs1k2DBCyEdduze5HVkprzNfJxsMNrafOq0XW//eL+GJL1/O+MLZZOgwQshgS0tCSGpc3JjpM1qlXTIhhNqstZTYGELIIDOzHqjz3rM/NP/9zbkfqT+0DQy4HM6ulcurmUyDIV26uDDHddneL1cfDL3UzvlewQ6fKLRhx484CEOb0/BCD6urq2tsbETuCqIgO2vd/83i66RymRUVVA9VQ0fH62Rgm72KDvXB6fTAiFtCfduPb90khIyaPLkXm76GxTr37X55BcUV27ZTJcYWloSQtA/3d6nuET8ej3cpwD89MVFLT99u/ITePHNCp+/76edLgf6//PjDF2u+Eng/k+c6Xg8J3r540TfnfrCxH9ONh6/X27BTRxyEQcK/7kVEbW0tm81G7gqiob4+PTGxRT/V9rPxIydOmvGFs5yCgii/7Zy0tDa/gntS0JHvyktKVm3f2XxCXt/I6CNZ2TcJ8Twer8WvFmogbvzz5wU52X+nBZdXWV4WH/n8XU6OkqrqnlNneviGY343Qy/qDx5sPfpTTV29/OysruyKJiW18/jJdQ4zPZe7bvI7MM1pQXcdvl5vw04dcRAGOaGdQoOOGzBggIJoB4To5m7zfUQ8LrfgbU7wke8fRlyvLCuznzpNTuTblFlZQQhRUVMTeA9V5WU1TFbzP1mVlTVM5rucnOYSWQWFdq5wZ6WmXAsO0tLTd3BZym5oaC43NDFJT0wsyMnmH3BbXVVVVJBPCLkTfrXFfrQNDJxWrf7iq3X91dV7sT0/GffZoS3uA01M373N8Txxsot70zE03B142nO56+Gtm9Pi47702t1iXgsBDl/X27AnjzgAIHf/pYOibzR45wl/Dofz+NbNbYudT/52Xdj3vHYRXbof+WeiD8FcOXP6wbXf/nfmpLqax+PFPH3SXDJq0uRNfgfafC6Pxzu524vL4RQV5M8d1sZV8LT4eP5vYeoEqbGlle+P5//3Fuh0BWXl9idaSk9M3Ld+bbe0mMvXGy+cON7+NiWF76SkpL52nNP6oabGRmq0HSFEVV29I91KOp3OaWq6HhKcEhfb4rqDAIdP4DbslSMOAMjdDqQvjbbl0HdvEhMKc3MPbdm8/3yQKL9tHUPDuL+e5bx5M3LipDY3KGUwMl8nj5r0wSuIq3d6rd7p1fzPiydPVFWUr9uztyOvfveXsKSoKMMhQ1pfv8zPyop5+iQtIX7yXEe+zEgihJhZW2vo6HTqbRoYG+85daZbWkxNU0vggXKEkEY2m5GfR/2toaMr+2+n+ypKS33WriENDbqDBq3x2t31wydwG/bKEQcA5G6HyCsqbj38/bZFzi8fPrgTfnXa/JZX5vKyMvMyMweZmOoOGtS7b9v2s/G/X770x9X/zv/PKrp0y0aoYbH2rlmVFh/vffrs2Bkzu/ela1isc35+NCmp7UeOm7ZaxDHx5YuYp0/exL830Iaa7UGAq9Gy8vLUPT/doounss1thndwy6bGxuNennU1NWOmz9h+5FjryxYCHD6B27BXjjgA9GHdfP+u9ehPZy5cRAg5s8+3xfwJ5787tH3J4se3bm52dvrXM5ZvEhLeJCQ01NcL6W2PnT5joIlJbkbGke0e/BfbCCEpsTEb5n6eFh8/Ztp0Ydzdcf67Q5VlpTMWfGHa1srJRuYWVEhw+G54oAYEUUsASYKfDh9MiY1xXrvO+/TZNscKCHD4erENBTjiAID+bies3ukVee9ueUlJwF5vzxP+VGF+dtaVM6dDnvylrq2dn531nymTHJYsUR3Qdv+J09Tk9vlsQsjpW7e7sbv23s8NOn3PqbMeSxbeCb8a/fSx/dRpGrq6tazqhBeRr2OiCSEzFy76ep9ftw8xzXydHHEhREFJaaXH9jY3UFRW1tDRLSl89zb9DXVet66mJj8nW4pOp76g+7ys1JSwH86t3ObRzowlnT18vdiGAhxxAEDudo6isrLbXh9ft7UPr1+b4jiPugKnqat3+tYf1NRCsnLyPC63kd3LN9IZDhly+tbtCyeOP7j2W8SFEKqQLi09evIUxxUrR4wd1+2vyOPxTu7exeVwXDa6f+g3ByHE2NKypPBdalwc9S2clfKax+UONDXtlbXqel7w0SPOa9b+6zRhnTp8vdWGgh1xgNYKCwuPHj0aGxtbX19vY2Ozfv16sx6ZJ0cwDx8+dHd3Dw0NtbQU1490ZmYmj8fT0tJS+sCatkwms/ifsaIUGRkZDQ2NjtyrRuPxeB2pRGVDwytGSRffSUNdXcSFkD+u/nfM9BnLt2wTkfblcjhFBQXVVVUfyclpGxj04l2wQAiJefqkUz96+vbhM1RWMu2vgk9Ft6DRaCwWS1FR/FY7fvXq1aRJk1gslrGxMY1Gy8jIkJWVDQsLmz17tgjWNjc3d+zYsXl5eVFRUba2tq03yM/PHzp0aGVlpcg2+MWLF11cXAghPj4+u3fvbnObXbt27d+/v0UhnU4fMWLEhg0bli5d2qP93XbUVFfXsJj9NTTjI5+zKiuVVFVFoYml6HQdQ0N8K4mIzp5pwOGDvq2hocHR0bG2tvbKlSsLFiwghNy4ccPJycnFxSUzM1OtC5MQCENCQoKjo2NeXp74NjiTydy2bZuhoWFubm5UVNQHewgxMYSQxYsXm5iYUCXV1dUpKSm3b992dXV98eKFv7//B7+1evL9qGloLNu89eCF0EY2+7efz+N/FABA+4KDg/Pz811dXanQJYQ4ODjs2LGjsrIyMDBQdOpZX1//7bffjh49Ojs7W1lZWXwb3Nvbu7Cw8MiRI5qamu3kbmxsLLXx3n989913N2/efPbsmaysbEBAwMuXL3s5dzNfJ4f/eI76m0ajGRgPqeyR1eIAAMRaeHg4IcTZ2Zm/cNGiRYSQX3/9VXTq6e7u7unpqaqqGhERYWdnJ6atnZiY6O/vP27cuPnz5w8fPpzBYOS3taBtYWEhg8FQUlJq7uw2Gz16tJOTEyHkwYMHvZy7dOl+Px06SM0Z9C4n58WD+yMnTMT/KACA9sXFxRFChg9/7/Z3MzMzWVnZpKQk0VlhSVlZeffu3ampqaJ51bmD3NzcuFzusWPHmtu8zS4vdZLZ2tq6zXteVFRUSLuLX/XQ9d1BpqbrffZtd1k8QEurlMFYuNatnamgAACAEMJms4uKimRkZDQ1NVs8pKurm5WVxWAw9PX1RaGqBw8eFPfWDgkJefLkycqVK0eMGEHFKiHk5cuXjo4t55KjTjJTm7UWGRlJCBn64dkCem5c1UznhVPnzS9lMNR1dKSlpfE/CgCgfSwWixDS5uo9VGFNTQ1aqVtUVVV5eHgoKSk1j1Kmcred/m6LkxCEEB6P5+fnFx0dPXDgwBkzZvR+7hJCpPv10zYwwAEGAOgI6j7PNjsqVKGEL2Tbjfbs2cNgMA4cOKCtrU2VmJqaysnJvXr1qvUynVTuPnr0KCMjgyrhcrklJSVUiZqaWlhYmOyHZwtAvxMAQERRndqG9ydDpdTV1RFhriicl5dXVtbe6FdVVdVBvT3TfndJSEgICAgYOHDgV199Vc83P7GlpWV0dHR6erqpqWlzYUVFxdu3bwkhQUEtl/8xMjLavHmzh4eHlpZWe11QfLIBAESTnJycvLw8i8Vis9kyMjL8D1GhqPHhJZ+7KCAg4PLly+1sMGvWLJG6kakrJxXc3Nw4HM7bt29V25pVIioqij93qc6ujY1NREREcyGdTldVVe3gz6CO5m4/KSk1WUzkBNCz3Z1++GUs6SwsLKKjo7Ozs/knhmQymSUlJVpaWtTQWWE4cODAgQMHJKGFg4ODnz59amFhMWlSy3VF09LS7t27FxUVtWTJkha5a2dnJ/CINukO///vN0JLA/8HAEB8NYnhok/jx4+Pjo5+8OABf+7ev3+fEDJxoljejVlXV9fY2CgilaGGU0lJSQUHB7ee1fLx48dU7vIXUoOZWw+q6jgp/FcEAAkhOl/3Hbd06VIajXb48OHmCY3r6+t9fX0JIW5ubuJ4FGpra0VnONiuXbuKi4tXrFjR5lTSH3/8MRW0/L/YqP7uh24iQu4CAPyP8EYhCY+Njc2aNWuys7NHjRoVEBBw7tw5e3v72NhYFxeXsWPHiuNRGDBgQJt3RvW8uLi4U6dOqaio+Pn5tbmBqqqqgYFBXV1dcnIyVVJdXZ2enk6n0z9uazntDsLVIwAAkebv76+oqOjv779+/XpCiIyMzKZNm/rAPBW9q3k41Z49e1pPS9LM2to6Ly/v5cuX1O288fHxXC7XysqqK7/hOroOIACAWBPfdQCbe1rJycnS0tKmpqYfWhRWLIj+OoDChv4uAIAYUFRUHDVqFNqhD8D1XQAAAOQuAAAAchcAAACQuwAAAMhdAAAAQO4CAAAgdwEAAJC7AAAAgNwFAABA7gIAAAByFwBAPNff7XtEav1d5C4AgBA1NDSgEXpdZWVlXV0dchcAAACQuwAAAH0L1gEEAEkhvtd3CwsLjx49GhsbW19fb2Njs379ejMzMzGtSW1trUi1LZPJLC4u5i+RkZHR0NDo4Mr2LBYrPj6ewWDQaDQ9PT0bGxtZWdl/eQ4PAEACEEIyMzPFseZRUVHUQvfGxsZDhgwhhMjKyt64cUNMa3Lt2jWRih4vL6/WyUin0+3s7IKDg9t5YkxMjKOjY79+/fifqKCg4ObmVl5e3s4TadTHEQCgb6PRaNnZ2YMGDRKvajc0NAwZMqSwsPDSpUsLFiwghNy4ccPJyUlOTi4zM1NNTU3savL777/PmjVLdKJn1qxZv//+++LFi01MTKiS6urqlJSU27dvc7lcNzc3f3//1s/y8fHx8fHhcrkTJkyYOXOmvr4+k8lMTEwMCgqqrq42MTF59uyZhoYG+rsAINH9XQaDIXbVPnv2LCFkxYoV/IXe3t6EEF9fX3GsyfPnz2k0mui0sLa2NiEkLS2tdT2pM8YvXrxo8dCuXbsIIUZGRs+ePWvxEIPB+PjjjwkhS5cu/dArYlwVAIDoCg8PJ4Q4OzvzFy5atIgQ8uuvv0pmTbr3cjWDwVBSUmru7DYbPXq0k5MTIeTBgwf85Y8fP/bz89PT03vy5Im9vX2LZ2lpaV2+fHnEiBHm5uYfelGMqwIAEF1xcXGEkOHDh/MXmpmZycrKJiUlNTU1SUtLS1pNulFMTAwhxNramkajtX5URUWFtBqOt3HjRi6XGxAQoKen1+Y+LSwsoqOj23lR9HcBAEQUm80uKiqSkZHR1NRs8ZCuri6bzWYwGJJWk+4VGxtLCBkxYkSbj0ZGRhJChg4d2lwSHx8fFxdnZmY2Z84cgV8U/V0AABHFYrEIIQoKCq0fogpramokrSbC6O+26MQTQng8np+fX3R09MCBA2fMmNFcHhYWRghxcHDoyosidwEARBQ1HKzN87dUIZvNlrSaCCN3Hz16lJGRQZVwudySkhKqRE1NLSwsjP9+3KSkpDZzGrkLANAXUF3JNqeVpqY47uDcDn2pJt2ooqLi7du3hJCgoKAWDxkZGW3evNnDw0NLS4u/vKysjBCirq6O3AUA6IPk5OTk5eVZLBabzZaRkWkdAB+8Q7Tv1qTbO7s2NjYRERHNhXQ6XVVV9UM/I6hZMjgcTldeF+OqAABEl4WFBY/Hy87O5i9kMpklJSVaWlrUgFtJq0n35q6dnZ0+Hx0dnXb67oMHDyaEJCcnf2iDgoKCmzdvIncBAMTV+PHjSatbSO/fv08ImThxomTWpLtQg5k7dbF2+vTphJDz58+3Odd3VVWVo6Ojg4PDL7/80t5eMIsNAGC+KpEVGxtLo9GMjIwqKiqokrq6Oioqnjx5Io41EZ35qqgVHSIjIzv+lKamJktLS0LIsmXL6urqWrwvaq6MuXPncrlczM8MAJKORqMxGIwWw2TEwtq1a0+fPm1qavr111/LyMicOnUqNjbWxcUlJCREHGsSGRlpb2/P5XJ7t1Wrq6tVVFRoNBqLxerUoLCUlJQpU6a8e/dOV1d3zpw5BgYGTCbzzz//fP78OSFk1apVgYGBLRZLQH8XANDfFSdNTU1bt25tvptFRkZm06ZNDQ0NYloTEenvPn36lBBiZWUlwHOLiorWr1/PvxSEtLS0g4PD3bt3O/J09HcBAP1dMVBdXZ2cnCwtLW1qakotxiemNRGR/m7XcTict2/fVlRUyMvLGxkZ/fuyu80fReQuACB3ocf0mdwVGMYzA4DEfN9J4Ruv98nIyIjjCgrIXQCAThPHOZX6HjU1NWVlZeQuAAAA9ATMEwkAkuLRo0ctBr8MHDiw9YLn0I1ev3797t07/pKioiLkLgBA3zdq1Kh9+/a1KFyyZAlyV6jCw8Nbz5toa2sryW2C8cwAAAA9B9d3AQAAkLsAAADIXQAAAEDuAgAAIHcBAAAAuQsAAIDcBQAAQO4CAAAAchcAAAC5CwAAAMhdAAAA5C4AAAByFwAAAJC7AAAAyF0AAABA7gIAACB3AQAAkLsAAACA3AUAAEDuAgAAAHIXAAAAuQsAAADIXQAAAOQuAAAAchcAAACQuwAAAMhdAAAAQO4CAAAgdwEAAJC7AAAAgNwFAABA7gIAAAByFwAAALkLAACA3AUAAADkLgAAAHIXALJa5b8AAAAjSURBVAAAkLsAAADIXQAAAEDuAgAAIHcBAACQuwAAANB1/w+AsT76Z4dqugAAAABJRU5ErkJggg==
The "Strage loop" phenomenon occurs whenver, by moving upwards (or downards) through the levels of some hierarchical system, we unexpectedly find ourselves right back where we started.
* [[Godel, Escher, Bach]]
** [[Godel's incompleteness theorem]]
** [[Bach's endlessly rising canon|https://www.youtube.com/watch?v=nsgdZFIdmeo]]
** [[Escher]]
A ''string'', in [[Computer science]], [[Information theory]], and [[Mathematics]], is a [[Sequence]] of symbols, where each symbol is a member of a given set, called the alphabet. Strings often refer to finite sequences. See [[here|https://www.youtube.com/watch?v=ZjWHh1mAUsQ]].
These constructions are useful in [[Mathematics]] and [[Computer science]].
__Strings in computer science__
In computer science, strings are one of the fundamental [[Data type]]s used in [[Programming]]. In this case, the symbols are called ''characters''.
However, a string can also be considered as a [[Data structure]]
https://www.youtube.com/watch?v=H0jLD0PphTY
[[Applied String Theory - Dam Thanh Son|https://www.youtube.com/playlist?list=PL04QVxpjcnjioH1zeWnzt9ihoa14Ddare]]
[[Strings 2015 conference|https://www.youtube.com/playlist?list=PL04QVxpjcnjitWcPcsIqJh4pNB3V40Exv]]
See MMathPhys course
[[Particles, Gravity and Strings|https://www.youtube.com/playlist?list=PL04QVxpjcnjg_FpJNMJG0u0_swd9sL0tT]]
[[Advanced Strings School 2015|https://www.youtube.com/playlist?list=PL04QVxpjcnjgWd_kbNvPmDJ0f9Ib4L8fW]]
[[AdS/CFT correspondence]]
[[Calabi–Yau manifold]]
https://en.wikipedia.org/wiki/Structural_analysis
https://en.wikipedia.org/wiki/Structure
''Structural balance'' refers to the situation when a [[Signed network]] contains only loops with even numbers of minus signs. This is so that the (naturally generalized version of the) rule "the enemies of my enemies are my friends", and "the friends of my friends are my friends". The opposite situation is called [[Frustration]] in spin networks
''Harary's theorem'' tells us that all balanced networks are //clusterable//, i.e. they can be divided into groups with only positive connections within groups and negative between them. Proof given in Newman's book and gives further intuition of concept of balance.
https://en.m.wikipedia.org/wiki/Structural_biology
[[Protein structure]] -- [[Protein structure analysis]]
A [[Set]] of [[entities|Entity]] [[related|Relation]] in some way.
* [[Data structure]]
* [[Combinatorial structure]]
* [[Mechanical structure]] -- [[Structural analysis]]
!!__Types of structures__
[[Hierarchy]]
[[Heterarchy]]
[[Holonic structure]]
Like [[Gradient descent]] but using [[Subderivative]]s.
See page 42- [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]]
__Sub-gradient for absolute values__
Generalization of the [[Derivative]] where the linear approximation is defined to lie below the function, for [[Convex function]]s, at least..
[[Probability, algorithmic complexity, and subjective randomness|https://db.tt/0DPjGssg]] [[local link|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Research/Griffiths-Tenenbaum-FST-HMM.pdf]]
[[Complexity and the representation of patterned sequences of symbols|http://digitalcollections.library.cmu.edu/awweb/awarchive?type=file&item=38671]]
The development of [[Algorithmic information theory]] has revived some of these ideas, with code lengths playing a central role in recent accounts of human concept learning (Feldman, 2000), subjective randomness (Falk & Konold, 1997), and the role of simplicity in cognition (Chater, 1999).
The role of simplicity (see [[Order]]) in [[learning|Learning theory]] is also important. As discussed in, for instance, [[here|http://digitalcollections.library.cmu.edu/awweb/awarchive?type=file&item=38671]], accounts of our cognitive behavior must take into account the strong prior knowledge that contributes to our inferences. The structures that people find simple form a strict (and flexible) subset of those easily expressed in a computer program.
[[They|https://db.tt/0DPjGssg]] explore the middle ground between Kolmogorov complexity and the arbitrary encoding
schemes to which Simon (1972) objected. I think, more precisely, they study computable analogs of KC, which are not universal like Turing machines, but which are not as arbitrary as those discussed in Simon's. They also use [[Chomsky's hierarchy]] to organize their computable models.
!!__Subjective randomness__
One important aspect of subjective complexity is subjective randomness (randomness and complexity are essentially the same in [[AIT|Algorithmic information theory]], which uses [[Kolmogorov complexity]]).
The statistical basis of subjective randomness be- comes clear if we view randomness judgments in terms of a signal detection task (cf. Lopes, 1982; Lopes & Oden, 1987). On seeing a stimulus X , we consider two hypotheses: X was produced by a random process, or X was produced by a regular process. Finding regularities is an important part of identifying predictable processes, a fundamental component of induction (Lopes, 1982). The deci- sion about the source of X can be formalized as a Bayesian inference,
$$\frac{P(random|X)}{P(regular|X)} = \frac{\frac{P(X|random)P(random)}{P(X)}}{\frac{P(X|regular)P(regular)}{P(X)}} = \frac{P(X|random)P(random)}{P(X|regular)P(regular)}$$
n which the posterior odds in favor of a random gen- erating process are obtained from the likelihood ratio and the prior odds. The only part of the right hand side of the equation affected by X is the likelihood ratio, which led Griffiths and Tenebaum (2001) to define the ''subjective randomness'' as
$$\text{random}(X) = \log{\frac{P(X|random)}{P(X|regular)}}$$
By identifying $$-\log_2{P(X|regular)} = K(X)$$, and $$P(X|random) = \left( \frac{1}{2} \right)^{l(X)}$$, we get that $$\text{random}(X) = K(X) - l(X)$$.
The way they <b>model P(X|regular)</b>, is by using [[Hidden Markov model]]s (HMMs).
An atom or group of atoms taking the place of another atom or group or occupying a specified position in a molecule.
https://www.wikiwand.com/en/Substituent
Substitution reaction (also known as single displacement reaction or single replacement reaction) is a [[Chemical reaction]], often an [[Organic reaction]], during which one [[Functional group]] in a [[Chemical compound]] is replaced by another functional group.
!!__Mechanisms__
* [[SN1 reaction]] (two-step)
* [[SN2 reaction]] (single-step)
!!__Types__
* [[Electrophilic substitution]]
* [[Nucleophilic substitution]]
A sufficient statistic for random variable $$y$$ w.r.t to r.v. $$x$$ is a function of $$y$$ that retains all of its information relevant to $$x$$.
[img[sufficient_statistic.PNG]]
An equivalent formulation is given by the [[Data processing theorem]]
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
The [[Sulfur]] ion SO,,4,,^^-2^^, or a compound containing that ion.
[img[https://www.americanelements.com/images_graphics/Sulfate200.jpg]]
[[Functional group]] that characterizes [[Thiol]]s
It is --SH
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/9/92/Mercapto_Group_General_Formulae.png/120px-Mercapto_Group_General_Formulae.png]]
A [[Chemical element]] composed of sulfur atoms. These have 16 proton in the nucleus.
The hydrogen atom tends to form two bonds, as it has 6 electrons in its outer shell (see [[Octet rule]]).
The [[Star]] that gravitationally bounds together the [[Solar System]]
[img[https://upload.wikimedia.org/wikipedia/commons/thumb/a/a0/Sun_in_February.jpg/290px-Sun_in_February.jpg]]
https://en.wikipedia.org/wiki/Sun
[[Divers dwarfed by enormous sunfish|https://www.youtube.com/watch?v=JsvLgDDafus]]
http://oceansunfish.org/lifehistory.php
//aka predictive learning//
The goal is to learn a mapping from inputs $$x$$ to outputs $$y$$, given a labeled set of input-output pairs $$D = \{(x^{(i)}, y^{(i)})\}_{i=1}^N $$. Here $$D $$ is called the ''training set'', and $$N $$ is the number of training examples.
Training data consisting on ''inputs and outputs''.
<small>Other names for inputs: predictors, independent variables, features, attributes, covariates. Other names for outputs: responses, response variables, dependent variables.</small>
In supervised learning, we want to find function relating inputs to outputs, to then be able to predict new outputs from new inputs. Often, we need ''a way to represent the function approximation'', with some parameters (the ''model''; with some subtleties for [[non-parametric|Nonparametric statistics]] ones) and a ''learning algorithm'' to find best parameters for the data, so that the model can predict well. See [[Learning theory]], to learn about the way learning algorithms work, overfitting, underfitting, ''model selection'', etc.. New paradigm: [[Deep learning]]
!!__Types of supervised learning algorithms__
!!!__[[Generative vs discriminative models|https://www.youtube.com/watch?v=oTtow2Ui8vg&index=5&list=PLD0F06AA0D2E8FFBA]]__.
See below
!!!__Parametric vs non-parametric model__
* ''Parametric''. There is a fixed number of parameters that the algorithm fits.
* ''Non-parametric''. Formally, the number of "parameters" grows with the training set. Here number of parameters basically refers to "amount of information in learned function". For See [[Nonparametric statistics]] An example is [[Nearest-neighbour classification]].
!!!__Continuous vs categorical output__
//Categorical//, or //nominal//. Output $$y$$ belongs to some finite [[Set]]. The learning problem is called [[Classification]].
//continuous//. $$y $$ is a [[Real number]], or belongs to $$R^n $$ more generally. Learning is then known as [[Regression|Regression analysis]].
//ordinal//. When the output belongs to some set with some natural [[Ordering]]. Learning is then known as //ordinal ordering//
!!__[[Regression|Regression analysis]]__
Output value is continuous, and quantiative (i.e. it has an ordering, and a notion of closeness (matrix)).
!!__[[Classification]]__
Output value is discrete, or categorical, or qualitative. No implicit ordering, or closeness on the variables. Simple approach: [[Logistic regression]]
!!__[[Discriminative learning]]__
Learning the function $$p(\text{output}|\text{input})$$. See [[notes|http://cs229.stanford.edu/notes/cs229-notes1.pdf]]
!!__Structured learning__
[[wiki|https://www.wikiwand.com/en/Structured_prediction]]
!!!__General methods__
[[Generalized linear model]]
[[Artificial neural network]] (see [[Deep learning]])
[[Support vector machine]]
[[Decision tree]]
!!__[[Generative supervised learning]]__
Learning the function $$p(\text{input}|\text{output})$$, together with $$p(\text{output})$$, which can be used to find $$p(\text{output}|\text{input})$$ using [[Baye's theorem]].
See [[notes|http://cs229.stanford.edu/notes/cs229-notes2.pdf]]. See [[lecture video|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=51s]] [[def|https://www.youtube.com/watch?v=qRJ3GKMOFrE&index=5&list=PLA89DCFA6ADACE599#t=4m50s]]
!!!__[[Gaussian discriminant analysis]]__
!!!__[[Naive Bayes]]__
//aka SVM//
A method for discriminative [[Supervised learning]], that is for [[Classification]], and [[Regression analysis]]. It allows to [[learn|Machine learning]] non-linear functions, like [[Artificial neural network]]s.
[[Andrew Ng lec intro|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=44m05s]] -- [[Notes|http://cs229.stanford.edu/notes/cs229-notes3.pdf]] --
[[Wiki|https://www.wikiwand.com/en/Support_vector_machine]]
-- [[Notation|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=51m15s]]
[[Support Vector Machine Intro and Application - Practical Machine Learning Tutorial with Python p.20|https://www.youtube.com/watch?v=mA5nwGoRAOo&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=20]]
See page 39 [[here|http://mpawankumar.info/teaching/cdt-optimization/lecture1_2.pdf]], and [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides09.pdf]], and [[these notes|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/lectures/lecture09.pdf]]
!!__Maximum/Optimal margin classifier__
[[Max-margin learning]]
[[Summary|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599]]
* [[Functional margin]]
* [[Geometric margin]]
[[Definition|https://www.youtube.com/watch?v=qyyJKd-zXRE&index=6&list=PLA89DCFA6ADACE599#t=1h8m40s]] of the optimization (learning) problem: choose classification hyperplane (parametrized by $$\omega, b$$), that maximizes the [[Geometric margin]] wrt to training data set, with the contratint $$||w||=1$$.
[[Alternative formulationt|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=9m45s]], that however, leaves $$||w||$$ arbitrary.
[[Here is a constraint|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=17m]] that fixes the arbitrariness of the magnitude of $$w$$: $$\hat{\gamma} = 1$$ ([[Functional margin]]), we get the following [[optimization problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=18m30s]]:
<<<
$$\min \frac{1}{2} ||w||^2$$
s.t. $$y^{(i)} (w^T x + b ) \geq 1$$
<<<
This is an example of a [[quadratic program|Quadratic programming]]
This is the same as maximizing the margin, under the constraint See page 8 [[here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides09.pdf]], and divide consrtaints by norm of $$w$$, giving the geometric margin.
!!!__SVM optimization problem__
<b>An SVM works by solving the [[dual problem to the optimization problem|Optimization]] of OMCs defined above</b>. The good thing is that the resulting optimization problem is [[convex|Convex optimization]], for which there are very efficient methods for solving it, as there are no local minima!
Primal and dual [[Optimization]] problems: [[intro|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=48m05s]] --> [[primal problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=49m15s]] --> [[Dual problem|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=56m]] ([[Skip some algebra|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=1h02m30s]])
__Support vectors__
([[Definition of support vectors|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=53m50s]], the $$\alpha$$s [[are Lagrange multipliers|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=28m20s]])
Support vectors satisfy the contraint inequality with equality.
The approach for deriving the optimal margin classifier for a support vector machine, is that we'll solve the dual optimization problem above.
Prediction can be written down using inner products: see [[here|https://www.youtube.com/watch?v=s8B4A5ubw6c&index=7&list=PLA89DCFA6ADACE599#t=1h11m]]
--[[Summary|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=1m]]
!!__Kernels__
,,[[Kernels Introduction - Practical Machine Learning Tutorial with Python p.29|https://www.youtube.com/watch?v=9IfT8KXX_9c&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&index=29]],,
Allow the computation of the inner products, that appear in the formulas for SVMs, more effectively
[[Idea of a Kernel|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=4m]]
[[How to choose Kernels|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=14m30s]]
__[[How to check if a function is a valid Kernel|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=17m30s]]__
If $$K(x,z)$$ is a valid kernel, then the matrix with elements $$K_{ij} = K(x^{(i)}, x^{(j)}$$, for any set of $$x^{(i)}$$, must be symmetric positive semi-definite. It turns out [[the converse is true|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=24m15s]].
[[How to use a SVM with a kernel|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=27m30s]]
!!![[How SVM work (to classify non-linearly separable data)|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=30m]]
__Examples of kernels__
* Gaussian kernel
!!![[Kernels can be applied to other learning algorithms|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=34m30s]]!
!!__$$L1$$ norm soft margin SVM__
[[Soft Margin SVM - Practical Machine Learning Tutorial with Python p.31|https://www.youtube.com/watch?v=JHaqodAQqiI&index=31&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
Soft margin is a method to <b>deal with non-linearly separable decision boundaries</b>.
[[Intro|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=35m40s]]
[[Mathematical formulation|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=37m40s]]
<<<
$$\min \frac{1}{2} ||w||^2 + C \sum_{i=1}^n \xi_i$$
s.t. $$y^{(i)} (w^T x + b ) \geq 1 - \xi_i$$
$$y^{(i)} (w^T x + b ) \geq 1 - \xi$$
$$\xi_i \geq 0$$
$$i = 1, ..., n$$
<<<
basically weight how each point contributes, so that if there is some outlier it doesn't break the algorithm.. [[Explanation|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=39m]]
We need $$\xi_i \geq 0$$ so that we don't reward easy to classify terms, with negative $$\xi_i$$.
|This constrained optimization problem can be reformulated as an unconstrained optimization problem with a regularized [[Hinge loss]] function: $$\frac{1}{2}||w||^2 + C \sum_i \max{\{0,1-y_i(\mathbf{w}^T \mathbf{x}_i)\}}$$|
To see this we have to minimize w.r.t $$\xi$$ first, and then w.r.t $$\mathbf{w}$$ (which can always be done). So we consider fixing the parameters $$w$$, and minimizing w.r.t $$\xi$$, which gives $$\xi=\max{\{0,1-y_i(\mathbf{w}^T \mathbf{x}_i)\}}$$, which gives the [[Hing loss]].
Can also work out [[the dual of this optimization problem|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=39m50s]] (see more on [[Optimization]] and [[Linear programming]] about dual optimization problems). See [[slides here|http://www.cs.ox.ac.uk/people/varun.kanade/teaching/ML-MT2016/slides/slides09.pdf]]
[[Convergence conditions|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=43m23s]]
!!__SMO algorithm__
''Sequential minimal optimization'' is an optimization algorithm, that is a variation of [[Coordinate descent]]: [[Application to SVM dual optimization problem|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=52m48s]]. [[This is the reason we use it|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=51m]]
-- [[Description of the algorithm|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=53m40s]] -- [[algorithm|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=54m15s]] (we are maximizing a function $$w(\alpha_1, ..., \alpha_m)$$
!!__[[Applications of SVMs|https://www.youtube.com/watch?v=bUv9bfMPMb4&index=8&list=PLA89DCFA6ADACE599#t=1h9m25s]]__
Surface science is the study of physical and chemical phenomena that occur at the interface of two phases, including solid–liquid interfaces, solid–gas interfaces, solid–vacuum interfaces, and liquid–gas interfaces. It includes the fields of surface chemistry and surface physics.
See [[Materials science]], [[Condensed matter physics]], [[Chemistry]]
https://en.wikipedia.org/wiki/Surface_science
!!__Surface chemistry__
!!__Surface physics__
!!!__Fluid dynamics at interfaces__
See [[Colloid Transport by Interfacial Forces|http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.21.010189.000425]]
[[Interfacial forces]]
__Fluid/fluid interfaces__
Governed mostly by (apparent) discontinuities in stress, particularly surface tension. These are known as "Marangoni effects", or "capillary-driven flow".
__Solid/fluid interfaces__
Governed mostly by slip velocity at the interface.
These are responsible for several of the [[Phoretic mechanisms of colloids]], which cause them to move along gradients of some quantity.
[[Surface tension]]
[[Pervaporation]]
See LectureNotes notes (preparing for physsoc class) on tablet.
[[Hydrophobicity]]
I think (under both theoretical, and experimental grounds) that the only reason that water droplets stay on vertical surfaces is the surface's impurities. This can be deduced from considering the force balance at the bottom meniscus.
Also, I did the experiment comparing a dirtier glass surface with a cleaner one, and the degree of dirt correlated (by eye) both with the number and size of droplets that get stuck.
See also [[Dynamics of droplets]]
[[Surfactant|https://en.wikipedia.org/wiki/Surfactant]]
See [[Free energy principle]] for context.
We can describe it using the [[Fokker-Planck equation]]. It's steady state solution:
$$\dot{p}=0=\nabla \cdot(\Gamma \nabla - f) p$$
$$\nabla \cdot \Gamma \nabla p = p \nabla \cdot f + f \cdot \nabla p$$
$$ \frac{\nabla \cdot \Gamma \nabla p}{p} = \nabla \cdot f + f \cdot \frac{\nabla p}{p}$$
$$ \nabla \cdot \Gamma \nabla \ln p - \Gamma \nabla p \cdot \nabla (\frac{1}{p}) = \nabla \cdot f + f \cdot \nabla \ln p$$
$$ \nabla \cdot \Gamma \nabla \ln p +\frac{1}{p^2} \Gamma \nabla p \cdot \nabla p = \nabla \cdot f + f \cdot \nabla \ln p$$
$$ \nabla \cdot \Gamma \nabla \ln p +\Gamma \nabla \ln p \cdot \nabla \ln p = \nabla \cdot f + f \cdot \nabla \ln p$$
We can decompose any vector field into an irrotational (curl-free), and solenoidal (divergence-free) component ([[Helmholtz decomposition]]), which can be expressed as the so-called //standard form//:
$$f=(\Gamma + Q) \nabla V$$
where $$Q$$ is antisymmetric, and $$\Gamma$$ is symmetric. Substituting in above equation
$$ \nabla \cdot \Gamma \nabla \ln p +\Gamma \nabla \ln p \cdot \nabla \ln p = \nabla \cdot \Gamma \nabla V + (\Gamma + Q) \nabla V\cdot \nabla \ln p$$
Notice that $$(\Gamma + Q) \nabla V\cdot \nabla \ln p = \nabla V ^T (\Gamma + Q) \nabla \ln p = \nabla V ^T \Gamma\nabla \ln p$$ because $$Q$$ is antisymmetric. Using this, if we assume that $$V=\ln p$$, then the above equation for stationarity is satisfied.
__Proof from paper__: see [[Free_energy_principle_lemmaD1a.png]] and [[Free_energy_principle_lemmaD1b.png]]
It is straight-forward but fundamental result means that the flow of any ergodic random dynamical system can be expressed in terms of orthogonal curl- and divergence-free components, where the (dissipative) curl-free part increases value while the (con-servative) divergence-free part follows isoprobability con-tours and does not change value. Crucially, under this decomposition value is simply negative surprise: $$\ln p(x|m)= V(x) = -L(x|m)$$. It is easy to show that surprise (or value) is a [[Lyapunov function]] for the policy
$$\dot{V} = \nabla V \cdot f = \nabla V \cdot \Gamma \cdot \nabla V + \nabla V \cdot \nabla \times W = \nabla V \cdot \Gamma \cdot \nabla V \geq 0$$
An effect, where //effectively// large neutral spaces are also favoured, but <b>in equilibrium</b>, not out of equilibrium as in the [[Arrival of the frequent]]
See comments on [[Arrival of the frequent]], for more comparisons.
<b>Original paper</b>: [[Evolution of digital organisms at high mutation rates leads to survival of the flattest|http://www.nature.com/nature/journal/v412/n6844/abs/412331a0.html]]
A ''suspension'' is a [[dispersion|Dispersion (Chemistry)]] of solid particles in a liquid (IUPAC definition). For the particles to be definable as solid, they must have at least some size, and thus a suspension requires particles of [[colloidal|Colloid]] size, or larger.
,,Some authors, use [[suspension|https://en.wikipedia.org/wiki/Suspension_(chemistry)]] to refers to those suspensions where the particles are large enough to sediment. The case for smaller particles (like colloidal particles) may then be called [[Sol (colloid)|https://en.wikipedia.org/wiki/Sol_(colloid)]].,,
http://www.swarms.org/
https://en.wikipedia.org/wiki/Swarm_robotics
[[The fish kick|http://nautil.us/issue/25/water/is-this-new-swim-stroke-the-fastest-yet]], may be the fastest swim technique.
See [[here|https://www.dropbox.com/s/zgy5xiqbmt2m2tz/symbolic-dynamics.pdf?dl=0]] ([[local|file:///home/guillefix/Dropbox/COSMOS/Physics/stat%20phys,%20kinetic%20theory,%20chaos,%20dynamical%20sys,%20emergence/Dynamical%20systems/symbolic-dynamics.pdf]]).
A symbolic dynamical system often results from the partitioning of the state space of a general [[Dynamical system]].
------------------
[[Sequence space]]s
[[Shift space]]
https://en.wikipedia.org/wiki/Shift_space
http://www.math.harvard.edu/library/sternberg/slides/symbolic.pdf :
[[http://www.scholarpedia.org/article/Symbolic_dynamics]]
See [[Fractal]], [[Complex systems]]
The symbolic method of [[Analytic combinatorics]], applied to unlabelled structures. It uses the ''ordinary generating function''.
See [[here|http://ac.cs.princeton.edu/lectures/lectures13/AC01-OGFs.pdf]] for slides. [[video|https://www.youtube.com/watch?v=ULpHNFtOBBI&list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o&index=2]].
[img[http://i.imgur.com/ZWaWWoX.png]]
Elementary identity: $$A(z) = \sum_N{N\geq 0} A_N z^N$$, where $$A_N$$ is the number of objects of size $$N$$
[img[http://i.imgur.com/ZlFLC9Q.png]]
!!!__[[Trees|Tree (combinatorial structure)]] and [[Catalan numbers]]__
[[lecture|https://www.youtube.com/watch?v=C7AXercKXXY&index=3&list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o]]
The number of rooted ordered trees of $$n$$ nodes is the $$n$$th Catalan number. Can derive GF by using the fact that "a tree is a node and a sequence of trees". See [[here|https://www.youtube.com/watch?v=C7AXercKXXY&index=3&list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o#t=1m18s]].
Can easily extend to binary trees, as done in video
Trees have been related to other combinatorial structures: gambler's ruin sequences, context-free languages, triangulations, ...
!!!__Strings__
[[lecture|https://www.youtube.com/watch?v=C7AXercKXXY&index=3&list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o#t=11m30s]]
!!!__Powersets and Multisets__
[[Powersets and Multisets|https://www.youtube.com/watch?v=8maLI42gOJk&list=PLhsb6tmzSpiwyQCl4jmVPZymDs1MYIa8o&index=4]]
The ''symmetric property'', or just //symmetry//, in [[Set theory]], is a property of a binary [[Relation]] on a [[Set]] $$X$$:
|for all $$x, y \in X$$, $$xRy$$ implies $$yRx$$|
Discrete symmetry breaking
Continuous symmetry breaking. Goldstone theorem
--I think: A matter of time-scales?? See [[Metastability]]
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
http://www.scholarpedia.org/article/Synfire_chains
See [[Signal transmission and processing by neuronal networks]]
A synthesis reaction or direct combination reaction is a type of chemical reaction in which two or more simple substances combine to form a more complex product.
A + B → AB
http://chemistry.about.com/od/chemicalreactions/a/Synthesis-Reactions.htm
[[Engineering]] [[Biology]]
[[Registry of standard biological parts|http://parts.igem.org/Main_Page]]
!!!__Tuning transcription, translation degradation__
Tune [[Gene expression]]: [[DNA transcription]], [[mRNA translation]].
* ''Tuning transcription'':
** Tune promoter regions. Operator and activator sequences.
** transcription factors, inducers to tune the activity of the promoter region.
* ''Tuning translation'':
** Tune RBS (see [[mRNA translation]]). Translation regulated by changing mRNA secondary structure.
** Tune codon usage. Some codons, that give rise to the same amino acid may result in more efficient translation. Due to abundance of [[tRNA]] (be careful with comptetition for the same tRNA, which can change their availability), change in secondary structure. There can be problems with [[Protein folding]], as protein folding can depend on translation speed. [[RNA stability]]
* ''Tuning [[Protein degradation]]''. Use tags that label proteins for faster degradation.
''Reporter''s.
* $$\beta$$-galactosidase (encoded by lacZ)
* $$\beta$$-glucoronidase. Similar. (GUS)
* Luciferase, luciferin
** Bacterial luciferase
** [[Green fluorescent protein]]. Many colours obtained by [[Artificial selection]].
Craig Venter, George Church
---------
!!![[3D bioprinting]]
-------------
!!!Design of biological circuits and systems
[[Control theory and control systems]], depends on a lot of the theory and knowledge of [[Systems biology]]
[img[synbio_IT_analogy.png]]
----------------
https://autodeskresearch.com/groups/bionano
http://www.synthace.com/
http://ginkgobioworks.com/
http://www.nanalyze.com/2016/03/3-companies-building-nanorobot-factories/
(Lecture Notes in Artificial Intelligence volume 5777) Kampis, Karsai, Szathmáry-Advances in Artificial Life_ Darwin Meets von Neumann, Part 1(2011)
[[Xenobiology|https://en.wikipedia.org/wiki/Xenobiology]]. Craig Venter, George Church
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
A [[Set]] of components interacting ([[communicating|Communication]]) in some ways.
If their interactions affect the behaviour of the system, it is known as a [[complex system|Complex systems]].
A system of [[biological|Biology]] parts is a [[Biological system]]
There are of course many many more examples of systems. In fact a "system" is more of a perspective through which one can look at something, that allows one to organize its study. This is the aim of the [[Systems science]]s.
Systems biology is the study of [[Biology]] from the perspective of [[System]]s (i.e. [[Biological system]]s), that is sets of components which interact which each other. In particular systems biology is organized in an approximately hierarchical fashion, where lower levels are composed of parts which self-organize into the parts at the next level, which exhibit behaviour emergent from the characteristics of the lower level.
!!!See [[Biology]] for the hierarchy of biological systems usually studied by sysbio.
[[Modelling biological systems]] -- [[Computational biology]] -- [[Mathematical biology]]
!!__[[Network]] models__
[[Dynamical systems on networks]], [[Network science]]
[img width=400 [sysbio_description_levels.png]]
[img width=500 [types_network_models.png]]
* [[Chemical reaction network theory]]
* [[Gene regulatory networks]]
* [[Metabolic network]]
* [[Neuronal network]]
------------------
!!!__Data and resources__
Systems Biology Markup Language (SBML;
http://www.sbml.org/), CellML (http://www.cellml.org/)
and the Systems Biology Workbench are examples of efforts
that aim to form a de facto standard and open software
platform for modelling and analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) 13 , Alliance for Cellular
Signaling (AfCS) 14 and Signal Transduction Knowledge Environ-
ment (STKE) 15
https://www.wikiwand.com/en/Systems_biology
[[Systems biology MIT OCW|http://ocw.mit.edu/courses/physics/8-591j-systems-biology-fall-2014/]]
[[Foundations of Computational and Systems Biology|http://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/]]
[[Stochastic Dynamics for Systems Biology book|file:///home/guillefix/Dropbox/NewForCosmos/%5BChristian_Mazza,_Michel_Bena%C3%AFm%5D_Stochastic_Dynamycs_for_systems_biology.pdf]]
[[The Biological, Algorithmic and Computational Challenges of Systems Biology, Rick Stevens|https://www.youtube.com/watch?v=DUpW5YuESA8]]
[[The mycobiome|http://www.the-scientist.com/?articles.view/articleNo/45153/title/The-Mycobiome/]] The largely overlooked resident fungal community plays a critical role in human health and disease.
[[A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems|http://ezproxy-prd.bodleian.ox.ac.uk:2142/book/10.1007%2F978-94-017-9047-5]]
[[Systems approaches to modelling pathways and networks|http://bfg.oxfordjournals.org/content/10/5/266.short]]
It has become commonly accepted that systems approaches to biology are of outstanding importance to gain understanding from the vast amount of data which is presently being generated by advancing high-throughput technologies.
See [[Non-equilibrium statistical physics]] and [[Complex systems]]
[[Stochastic approaches in systems biology.|http://www.ncbi.nlm.nih.gov/pubmed/20836037]] See [[Systems biology]]
[[Differential Equation Models for Systems Biology: A Survey|http://www.advancedcomputing.cn/sys_bio_review.pdf]]
[[Winter School on Quantitative Systems Biology 2015|https://www.youtube.com/playlist?list=PL04QVxpjcnjg9UhfR9pn6-bnxyRo9yinu]]
[[ICTP-ICTS Winter School on Quantitative Systems Biology|https://www.youtube.com/playlist?list=PL04QVxpjcnjg5Y1vGamUcCJxopAO3a20r]]
[[Information processing in biological systems|https://www.youtube.com/playlist?list=PL04QVxpjcnji0PxkNBD668-D3u7fPhGHR]]
[[Statistical mechanics for real biological networks by William Bialek: Turing Lecture (Part 2)|https://www.youtube.com/watch?v=fV2ze7RtXYs&list=PL04QVxpjcnji0LCxLYsks4T9HBpGeOV2q]]
[[Reading and writing omes - George M Church|http://msb.embopress.org/content/9/1/642]]
[[ Harvard Molecular Technologies |http://arep.med.harvard.edu/]]
Systems biology uses many tools from [[Mathematical biology]]
See [[Bio-inspired computing]]
[[Synthetic biology]]
http://www.theosysbio.bio.ic.ac.uk/resources/
http://www.sysbiodtc.ox.ac.uk/
[[Application for admission as a graduate student to the University of Oxford|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/document.pdf]]
<small>[[Your offer and contract|https://www.ox.ac.uk/admissions/graduate/applying-to-oxford/after-you-apply/your-offer-and-contract?wssl=1]]</small>
''Academic conditions''
Achieve the EPSRC minimum of a ''2:1 classification'' in your current programme of study and
provide a hard
-
copy original or certified copy of your final transcript
Once you have met the condition above, please inform us as soon as possible by sending
the relevant official documentation to the address a
bove. We need to receive this information
by
''31 August
2016''
As I will have the [[Degree ceremony (MMathPhys)]] on September, the proof I need to send is a //Degree confirmation letter// (see [[here|https://www.ox.ac.uk/students/graduation/certificates?wssl=1]])
A place for the EPSRC Systems Biology Doctoral Training Centre beginning 3 October 2016
''Completion of Conditions letter''
If you satisfy all the conditions set by both the department and the college in their offer letters, you will be sent a final letter by your department confirming your place. I expect during summer.
!!!__Supervisors__ (for 1st year)
[[Jonathan Cooper|http://www.cs.ox.ac.uk/people/jonathan.cooper/]]
[[Joe Pitt-Francis|https://www.cs.ox.ac.uk/people/joe.pitt-francis/]]
See [[MMathPhys oral presentation]], and GKeep for topic ideas.
For DPhil period. Potential supervisor is Ard Louis.
!!!__EPSRC studenship__
This offer includes full funding in the form of a prestigious EPSRC Studentship which covers
__both University and College fees__, and also includes a __stipend__ award to cover living expenses
(__£14,057 per annum__ at current rates). This funding covers the entire __four year__ duration of
the programme.
More details about how I will receive the scholarship? When, how. See email: You do not need to worry about the studentship - we pay the students on behalf of the EPSRC. You will receive an email from the Finance Officer before you arrive asking for bank details, but the first payment will be given to you as a cheque on your first day here.
!!!__Kellogg college__
[[College Offer Letter||file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Valle%20Perez%252c%20Guillermo%20Jorge%252c%20College%20Offer%20Letter.pdf]]
[[Kellogg College Essential Information for Offer Holders 2016-17|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20College%20Essential%20Information%20for%20Offer%20Holders%202016-17.pdf]]
* <i class="fa fa-check-square" aria-hidden="true"></i> Please confirm whether you wish to accept this offer by contacting the Academic Office via academic.office@kellogg.ox.ac.uk by ''29 April 2016''.
* <i class="fa fa-check-square" aria-hidden="true"></i> The deadline for entry into the initial ballot to allocate accommodation is ''10 June 2016''. [[Accomodation Request Form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20College%20Accommodation%20Request%20Form%202016.docx]] -- [[Kellogg College Guide to Accommodation|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20College%20Guide%20to%20Accommodation.pdf]] -- [[Kellogg College Oxford Accommodation Information|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20College%20Oxford%20Accommodation%20Information.pdf]]. Ask about whether I can stay over the summer vacation, and if not, if I can leave the stuff in my room. [[38/40 Woodstock road|http://www.admin.ox.ac.uk/media/global/wwwadminoxacuk/localsites/accommodation/documents/handbooksaugust2013/38-40_Woodstock_Rd_2013.pdf]] is my preference because it's closest to science/math area and city centre, and supermarkets, etc.
* <i class="fa fa-check-square" aria-hidden="true"></i> Reply email about accomodation!!
* <i class="fa fa-check-square" aria-hidden="true"></i> You will need to return the Financial Declaration Form together with your supporting documentation by ''29 July 2016''. [[Financial declaration form|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Valle%20Perez%252c%20Guillermo%20Jorge%252c%20Financial%20Declaration%20Form.pdf]]
* You will be asked to sign and return a form confirming your details and intention to enrol at the University of Oxford and the Student-College Contract 2016 as a condition of enrolment.[[Kellogg College SAMPLE Student-College Contract 2016|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/Kellogg%20College%20SAMPLE%20Student-College%20Contract%202016.pdf]]
you will need to be in College in time to
attend induction events for graduate students, which are expected to begin on ''3 October
2016''. A wider range of welcome events will run from 23 September 2016.
Your __departmental
induction programme__ may start on a slightly different date, so you will need to arrange to be in
Oxford in time for whichever begins first.
!!__Research interests__
[[Systems biology]]
[[Non-equilibrium statistical physics]]
[[Nanotechnology]] and [[Artificial intelligence]], as well as ways of combining them (see section in nanotech tiddler)
http://www.sysbiodtc.ox.ac.uk/
[[Application for admission as a graduate student to the University of Oxford|file:///home/guillefix/Dropbox/Oxford/Systems%20Biology%20DPhil/document.pdf]]
<small>[[Your offer and contract|https://www.ox.ac.uk/admissions/graduate/applying-to-oxford/after-you-apply/your-offer-and-contract?wssl=1]]</small>
[[Research]]
''Academic conditions''
Achieve the EPSRC minimum of a ''2:1 classification'' in your current programme of study and
provide a hard
-
copy original or certified copy of your final transcript
Once you have met the condition above, please inform us as soon as possible by sending
the relevant official documentation to the address a
bove. We need to receive this information
by
''31 August
2016''
As I will have the [[Degree ceremony (MMathPhys)]] on September, the proof I need to send is a //Degree confirmation letter// (see [[here|https://www.ox.ac.uk/students/graduation/certificates?wssl=1]])
A place for the EPSRC Systems Biology Doctoral Training Centre beginning 3 October 2016
''Completion of Conditions letter''
If you satisfy all the conditions set by both the department and the college in their offer letters, you will be sent a final letter by your department confirming your place. I expect during summer.
!!!__Supervisors__ (for 1st year)
[[Jonathan Cooper|http://www.cs.ox.ac.uk/people/jonathan.cooper/]]
[[Joe Pitt-Francis|https://www.cs.ox.ac.uk/people/joe.pitt-francis/]]
See [[MMathPhys oral presentation]], and GKeep for topic ideas.
For DPhil period. Potential supervisor is Ard Louis.
!!!__EPSRC studenship__
This offer includes full funding in the form of a prestigious EPSRC Studentship which covers
__both University and College fees__, and also includes a __stipend__ award to cover living expenses
(__''£14,057 per annum''__ at current rates). This funding covers the entire __four year__ duration of
the programme.. ((14,057/12) - 573 - 42)/30
More details about how I will receive the scholarship? When, how. See email: You do not need to worry about the studentship - we pay the students on behalf of the EPSRC. You will receive an email from the Finance Officer before you arrive asking for bank details, but the first payment will be given to you as a cheque on your first day here.
!!!__[[Kellogg college]]__
!!__Research interests__
[[Systems biology]]
[[Non-equilibrium statistical physics]]
[[Nanotechnology]] and [[Artificial intelligence]], as well as ways of combining them (see section in nanotech tiddler)
!!__Thesis__
Physical copy & digital copy (submitted online through ora).
--------------
Supervisor/College Advisor details
Supervisor Jonathan Paul Cooper jonathan.cooper@cs.ox.ac.uk
Supervisor Joseph Mark Pitt-Francis joe.pitt-francis@cs.ox.ac.uk
Michael Stawpert michael.stawpert@tss.ox.ac.uk
--------------------
Research groups
__Computational biology__
*see piece of paper, GKeep
*Computational biology. One of the biggest things holding back sysbio, is the lack of knowledge on [[Software engineering]]. Applications to [[Drug development]].
**Cardiac and respirator physiology.
***David Kay.
*** Blanca Rodriguez. Biomarkers
** Cell-based modelling, cancer, tissue development engineering
** Structural molecular biology & [[Electrochemistry]].
*** Peter Minary 5 orders of magnitude faster [[Molecular dynamics]], dimensionality reduction using constraints. Hierarchical natural montecarlo. Immunoinformatics and protein folding machines, etc.. Application to [[Epigenetics]], [[DNA structure]], microRNAs, virus structure.
** Mathematics
*** Jonathan Whiteley. Automatic model reduction, multiphase flow, cardiac electrophysiology, respiratory monitoring.
*** David Gavaghan.
**** Model parametrization
**** Inverse problems
**** Reproducibility of research
* Developing software. DIfferent length scales in biology. Stability, accuracy, speed.
** CHASTE. 700,000. Joe Pitt-Francis.
** MOSAICS. 500,000.
__Mathematical biology__
Wolfson center for mathematical biology
*[[Pattern formation]]. Reaction-diffusion continuous models. agent-based model when few cells.
Multiscale. Gene -> macroscopical structure. [[Developmental biology]]
*Multiscaling tools.
*[[Tumor growth]], [[Wound healing]].
*[[Network theory]] of [[Vascular network]]s
*Philip Maini
*Helen Byrne
*Derek E Moulton. [[Continuum mechanics]]
*Radek Erban. [[Stochastic process]]es, nanoscale. Swarm robotics, gene regulatory networks.
*Eamonn Gaffney.
*Ruth Baker.
*Heather Harrington. Chemical reaction network theory. Networks and dynamics, vascular networks.
*Bridging theory and data with methods.
*Algebraic systems biology.
OCIAM
* Sarah Waters. Regenaritve medicine & tissue engineering. Ultrasound fields, to control physiological fluid mechanics.
* Jim Oliver. Cell motility, and other cell stuff. cellular blebbing, biofilms.
-------------------
controling neurons with ultrasounds
Interdisciplinary sciences
Mostly about systems, synthesizing, going beyond the reductionism and analysis of the //basic foundational sciences//, towards more ''holistic'' sciences.
http://artificial-intuition.com/bizarre.html
[[List of systems science journals|https://en.wikipedia.org/wiki/List_of_systems_science_journals]]
!!__Cybernetics__
(seems synonymous with systems science, at least up to connotations..)
[[Principia Cybernetica Electronic Library|http://pespmc1.vub.ac.be/LIBRARY.html]]
http://www.emeraldinsight.com/loi/k
!!!__[[Systems theory]]__
!!__Philosophy__
http://www.vub.ac.be/CLEA/dissemination/groups-archive/vzw_worldviews/
!!![[Ontology]]
----------------
https://en.wikipedia.org/wiki/Systems_science
https://en.wikipedia.org/wiki/Systems_theory
See also [[Ontology]]
A table is an item of furniture that facilitates a surface at a height appropriate for manipulating objects, while [[Standing]], or [[Sitting]]
[img[http://pngimg.com/upload/table_PNG6986.png]]
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
[[Taxis|https://en.wikipedia.org/wiki/Taxis]] refers to a behavioural response by an organism to a directional stimulus or gradient of stimulus intensity.
* [[Chemotaxis]]
See [[Phoretic mechanisms of self-propelled colloids]] for similar mechanisms in simpler active colloid systems.
[[Taxonomy: Life's Filing System - Crash Course Biology #19|https://www.youtube.com/watch?v=F38BmgPcZ_I&index=19&list=PL3EED4C1D684D3ADF]]
[[Tree of life]]
Homologous traits
Binomial nomenclature
!!__Taxa__
groups of organisms
Domain
Kingdom
Phylum
Class
Order
Family
Genus
Species
----------------
[[https://www.wikiwand.com/en/Taxonomy_(biology)]]
https://en.wikipedia.org/wiki/Taylor_series
See [[Technology & Engineering]], and [[Tool]]
Technologies are pieces of [[Art]] with very clear purpose, and thus must use the more rigorous methods of [[Science]]. The purposes of technologies is often to extend what we can do.
[[Engineering]] is the art and science of making new technology.
[[Portal:Technology|https://en.wikipedia.org/wiki/Portal:Technology]]
[[Portal:Contents/Technology and applied sciences|https://en.wikipedia.org/wiki/Portal:Contents/Technology_and_applied_sciences]]
[[Wikipedia:Portal/Directory/Technology and invention|https://en.wikipedia.org/wiki/Wikipedia:Portal/Directory/Technology_and_invention]]
http://www.deepknowledgeventures.com/
!!![[List_of_emerging_technologies|https://en.wikipedia.org/wiki/List_of_emerging_technologies]]
---------------
//Other innovation areas//
Food innovation: see [[Food]]
Telecommunications engineering and technology
[img[https://scontent-mad1-1.xx.fbcdn.net/hphotos-xpt1/v/t1.0-9/13001237_955917641171436_5866019281009314880_n.jpg?oh=fa6fc19a983745cee34ea558eba0118e&oe=57B6E0AC]]
[[Temperature based Restricted Boltzmann Machines|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4725829/]]
[[Temperature-Based Deep Boltzmann Machines|https://arxiv.org/abs/1608.07719]]
An approach to [[Reinforcement learning]]
TD learning is a combination of [[Monte Carlo]] ideas and [[Dynamic programming]] (DP) ideas. Like Monte Carlo methods, TD methods can learn directly from raw experience without a model of the environment's dynamics. Like DP, TD methods update estimates based in part on other learned estimates, without waiting for a final outcome (they bootstrap).
After each action selection, the critic evaluates the new state to determine whether things have gone better or worse than expected. That evaluation is the TD error:
<img style="background-color:white;" src="https://webdocs.cs.ualberta.ca/~sutton/book/ebook/imgtmp41.png">
Note that unlike [[Bellman's equation]] for $$V^*$$, which has a $$\max\limits_a$$, this doesn't but that is because, the action we have just taken follows the policy and so it's selected by $$\max\limits_a$$..
Traditional AC methods optimize the
policy through policy gradients and scale the policy gradie
nt by the TD error, while the action-value
function is updated by ordinary TD learning
Read [[here|https://arxiv.org/pdf/1610.01945.pdf]]
!!__TD0__
[[vid|https://www.youtube.com/watch?v=dV80NAlEins&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=16#t=19m30s]]
A kind of [[Gradient descent]] to converge to solution to V(s) that satisfies [[Bellman equation]]
[ext[https://webdocs.cs.ualberta.ca/~sutton/book/ebook/node60.html]]
!!__Action-critic methods__
[ext[https://webdocs.cs.ualberta.ca/~sutton/book/ebook/node66.html]]
[[Network science]]
[[Temporal Networks|https://arxiv.org/abs/1108.1780]]
[[Temporal Networks|http://www.springer.com/gb/book/9783642364600]]
[[Dynamic networks and directed percolation|http://iopscience.iop.org/article/10.1209/0295-5075/90/38004/meta]]
[[Dynamical systems on networks]]
[[A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States|https://arxiv.org/abs/1306.2164]]
[[Garnet Chan "Matrix product states, DMRG, and tensor networks" (Part 1 of 2)|https://www.youtube.com/watch?v=Q8bFmV6tHBs]]
A good [[Deep learning]] library in [[Python]]
[[TensorFlow Basics - Deep Learning with Neural Networks p. 2|https://www.youtube.com/watch?v=pnSBZ6TEVjY&index=45&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v]]
In tensor flow, you:
# Define a ''computational graph'', that manipulates tensors, and data.
# Begin a ''session'' (`tf.Session()`), and `train`, and `run` the computational graph, to get its result.
[[Learning TensorFlow|https://www.youtube.com/watch?v=bvHgESVuS6Q]]
[[TensorFlow in 5 Minutes|https://www.youtube.com/watch?v=2FmcHiLCwTU]]
<div id="testmol" style="height: 400px; width: 400px; position: relative;" data-backgroundcolor="0xffffff" data-style="stick"></div>
<<3Dmol "pdb" "2POR" "testmol">>
<div id="testmol2" style="height: 400px; width: 400px; position: relative;" data-backgroundcolor="0xffffff" data-style="stick"></div>
<<3Dmol "pdb" "2POR" "testmol2" "cartoon">>
<div id="testmol3" style="height: 400px; width: 400px; position: relative;" data-backgroundcolor="0xffffff" data-style="stick"></div>
<<3Dmol "cid" "24749" "testmol3" "stick">>
A ''textile'', or ''cloth'', is a kind of flexible [[Composite material]] material consisting of a network of natural or artificial fibres (yarn or thread).
https://www.wikiwand.com/en/Textile
[[Textile manufacturing]]
[[Textile art]]
https://www.wikiwand.com/en/Textile_arts
[[Sewing]]
https://www.wikiwand.com/en/Textile_manufacturing
See also [[Textile art]]
http://www.jstor.org/stable/25221013?seq=1#page_scan_tab_contents
[[The treatise of Walter de Milimete |file:///home/guillefix/Dropbox/COSMOS/History%20&%20Cosmology/The%20treatise%20of%20Walter%20de%20Milimete%20(mentions%20Alexander's%20horn).pdf]]
See El mundo fisico, de Guillemin, Phonurgia nova, de [[Athanasius Kircher]], Secreta secretorum, etc.
[img[https://c5.staticflickr.com/3/2494/4031751972_53a81947b2_b.jpg]]
[img[http://1.bp.blogspot.com/_o1gwI-T3nMU/S9_5kDUHZwI/AAAAAAAAAcc/0QnWnVONu4Y/s1600/The-Horn-of-Alexander-the-Great-%23-Henry-George-Farmer-%23-The-Journal-of-the-Royal-Asiatic-Society-of-Great-Britain-and-Ireland,-No.-3-(Jul.,-1926),-pp.-502.jpg]]
https://web.stanford.edu/group/kircher/cgi-bin/site/?attachment_id=679
"Know thou, moreover, that the people aforetime have produced things which the contemporary men of knowledge have been unable to produce. We recall unto thee Murtús* who was one of the learned. He invented an apparatus which transmitted sound over a distance of sixty miles."
http://bahaiasheboro.blogspot.co.uk/2010/05/know-thou-moreover-that-people.html
See [[MMathPhys oral presentation]]
[[The structure of the genotype–phenotype map strongly constrains the evolution of non-coding RNA|http://rsfs.royalsocietypublishing.org/content/5/6/20150053.full]]
''Non-coding RNA'' (ncRNA) is RNA whose function is not to encode information. It's function may then be structural, or catalytic for instance, and is most often determined by its secondary structure, which is then the phenotype of interest.
<b>The distribution of properties found in ncRNA in nature (from [[fRNAdb database|http://www.ncbi.nlm.nih.gov/pubmed/17099231]]) closely follows that obtained by //G-sampling//</b> (uniform sampling over genotypes). Due to the bias in the GP map, this sampling is very different from //P-sampling// (uniform sampling over phenotypes). The strong bias makes certain structures appear much more often, which has been called //convergent evolution// in [[Evolution]] (part of the general phenomenon of //[[homoplasy|Homoplasy]]//). An example is the ubiquity of the //hammerhead ribozyme// through all the kingdoms of life.
[img width=500 [http://d2gme0e5d9kd75.cloudfront.net/content/royfocus/5/6/20150053/F2.large.jpg]]
<small>Figure 2.
Comparison of P-sampled and G-sampled distributions to natural data for L = 20 RNA. The P-sampled PP(Ω) (red diamonds) measures the probability distribution for a phenotype to have a given NS size Ω. It differs markedly from G-sampled PG(Ω) (blue circles), generated by random sampling over genotypes. Error bars arise from binning data. The black and cyan lines are theoretical approximations to PP(Ω) and PG(Ω), respectively (see Methods). The probability distribution of Ω for the SSs all 7327 (non-trivial) L = 20 sequences for Drosophila melanogaster from the fRNAdb database [21] (green squares) is much closer to the G-sampled PG(Ω) than to the P-sampled PP(Ω). Inset: all 11 218 SS phenotypes (purple triangles) ranked by NS size Ω. There is strong bias, just 5% of phenotypes take up 58% of all genotypes. The 7327 natural data points (green squares) are clustered at lower rank (larger Ω). (Online version in colour.)</small>
The <b>number of 'relevant structures'</b> can be estimated by the entropy $$H$$ of the G-sampled distribution of features (for instance belonging to a certain binned interval of neutral space size, or number of stacks (sets of contiguous base-pairs)), as $$2^H$$. One can define the //bias ratio// as the ratio of $$2^H$$ to the total number of phenotypes.
Within these relevant structures which //arrive// during evolution, <b>natural selection still acts</b>, and can be seen for example in the higher stability of natural RNAs vs random G-sampled RNAs. We find that the natural RNAs have slightly more bonds than in G-sampled structures. The bias towards larger $$\Omega$$ also leads to structures with <b>larger mutational robustness</b> (see [[Robustness and Evolvability in Living Systems|http://press.princeton.edu/titles/8002.html]] and [[From sequences to shapes and back: a case study in RNA secondary structures|http://www.ncbi.nlm.nih.gov/pubmed/7517565]]). Larger
robustness is considered to be advantageous [6], so that, in
this important way, phenotype bias facilitates evolution.
The high robustness, however is found both in G and P-sampling because of the high genetic correlations (genes tend to be close in the mutational network to other genes that produce the same phenotype). The genetic correlations are high enough to produce giant connected components (see [[Natural Selection and the Concept of a Protein Space|http://www.nature.com/nature/journal/v225/n5232/abs/225563a0.html]]).
"Bias
means that it will be difficult for evolution to find L ¼ 55 structures
with a large number of stacks, again raising the question
of __what kind of functionality is possible in principle that cannot
be reached by evolution because of such phenotype bias
constraints?__"
<small>Understanding tip: The line in figure 4 is flat when there are a lot of phenotypes because there are a lot of phenotypes with the same $$\Omega$$, and the phenotypes are equally spaced in $$x$$ axis in rank plot.</small>
The results that G-sampling produce the same results as the database indicate that some property similar to ergodicity may be at play. G-sampling is an ensemble average, and the database shows a kind of time-average over evolutionary trajectories. However, the process cannot be totally ergodic because __evolution is a nonequilibrium process__, and effects like long waiting times and the [[Arrival of the frequent]] are examples of non-ergodic non-equilibrium effects.
The GP map bias is an example of biases in development or other internal
processes could strongly affect evolutionary outcomes. These have been controversial; however, RNA SS provides perhaps the clearest and most unambiguous
evidence for the importance of bias in shaping
evolutionary outcomes.
See [[Homoplasy]] for discussion on the relation to convergent and parallel evolution. Our ability to make detailed predictions about evolutionary
outcomes as well as counterfactuals for RNA may also
shed light on Mayr’s famous distinction between<b> proximate
and ultimate causes</b> in biology (See [[ Cause and effect in biology|http://isites.harvard.edu/fs/docs/icb.topic100452.files/Mayr_E._1961._Science_V134.pp1501-1506.pdf]] and [[Proximate and ultimate causation|https://en.wikipedia.org/wiki/Proximate_and_ultimate_causation]]). Not sure about this, or if I understand it..
The GP mapping
constraint has some resemblance to classical morphogenetic
constraints which also bias the arrival of variation [47]. But it also differs, because the latter are conceptualized at the level of
phenotypes and developmental processes, and may have been
shaped by prior selection, whereas the former constraint is a
fundamental property of the mapping from genotypes to phenotypes
and was not selected for (<b>except perhaps at the origin
of life itself </b> <i class="fa fa-exclamation" aria-hidden="true"></i> <i class="fa fa-arrow-right" aria-hidden="true"></i> Still, maybe most possible GP maps have this property anyways (see [[experiments with transducers|Evolving automata]])).
Finally, strong phenotype bias is also found in:
{{Examples of GP map bias}}
|It would be interesting to devise <b>artificial methods</b> to search for such undiscovered ribozymes (those that are very improbable for evolution to find), some of which may be more fit than those that Nature has found.|
For this see:
[[Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design|http://nar.oxfordjournals.org/content/31/11/2926.full]]. tree graphs to describe RNA tree motifs and more general (dual) graphs to describe both RNA tree and pseudoknot motifs. our graph theory approach to RNA structures has implications for RNA genomics, structure analysis and design.
[[Experimental fitness landscapes to understand the molecular evolution of RNA-based life|http://www.sciencedirect.com/science/article/pii/S1367593114001215]]
In evolutionary biology, the relationship between genotype and Darwinian fitness is known as a fitness landscape. These landscapes underlie natural selection, so understanding them would greatly improve quantitative prediction of evolutionary outcomes, guiding the development of synthetic living systems. However, the structure of fitness landscapes is essentially unknown. Our ability to experimentally probe these landscapes is physically limited by the number of different sequences that can be identified. This number has increased dramatically in the last several years, leading to qualitatively new investigations. Several approaches to illuminate fitness landscapes are possible, ranging from tight focus on a single peak to random speckling or even comprehensive coverage of an entire landscape. We discuss recent experimental studies of fitness landscapes, with a special focus on functional RNA, an important system for both synthetic cells and the origin of life.
----------
__Methods__
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ISlZEJJRJGNWZFANxMz0ABMAAQBiBiGgAQTReenzOnmbYHXCAlADmcuzhrU28efS+h1G4V2tXt8yyJTbDp6y9fmV6/mrWLpUk6Pc4fcU5nTwJXe7SPQzgz6/n6+icvn7B0dPraNbjp1xiOPLhKZeKNZTbONYzn7+nXq7uXk6EWfW6leLBKtb1dDHy8p1I1nZO/r1y3xqbnAjXcKV1I7uat9SuiAgAAAgKaAGmACMCgAGnTq1qqTNPQc9jQrSBkUZFjY0AiQRbAANsDPQAAAABoYAIACGCAS8dLm9LM3AOuUBAAaPCj1jcpV+8+l9Dr1irdZe9we8cTQ39Ur/AKL516ETrFnqadDucPuBiy4Sl3mjXlV596D56K/0W6G2J15v6J576HDwZ9Yp8JCWvf52+S889D88WwphY+P1+MaeDZ7Br5OZnOTs9zgE+xod85sugVUezxbDG4NIxOgAQykNAADAAAadgAJpkqhcKZc1SIue3FoAAAGAoANpgAoAbQjOmAoAAAAIAxMAAAAuPY5HYznbA65QEABqc3uhp8K0ho8ezorlhkFcwWoOPp2RmlVbq1qFuYHG7KPO77niaFE9JRzedYwfK3cpx+4AcvqaJS7gbZXLRDXDg2DZqux6JHU4XZ5pz8XT5h08vMxlk06ffSl3nQ0jvaeDaKnZuR0DqNNBMpAxACAAChpgAjABNUNBOnXGm3NUUlz6RJIiMIjEQ0Mi1k1IQxUAbInnQ0DAUAQaYAAAAADRdOtxe1nO2J9coCAAAAAGmgGgGCGlAKAATQIBAQAAACYIZXC2uc4sQ40au1Uos2zwe9SEzTW7pxuy1MNcCy6u3GyzFWWLBAABACoAQBUDQAA0wBoAAhDE6yUu50pmsAsdAAEwiSQkwiSQpRDIosbQuygzpiYwAAGAA0oDEMREkXHr8fsZzttPrlCcoAhquuFgz5PPz0JLgHZxc7sE50e2Lt4KxaTIUS6VsQq1hNore6dYoHVLSaXCi1amSllo6Vf7BslZ6tdFVjvnGFqRbVq8erHWu/XY3e1x+kZ3ystdCWhvg0znUL06sR26B6Rwja6mhvgpRoABMIsEcZRoaABgAACAAIAcZVkpF3o9zWQOfQAAQAAACYCUkRGhuLNoTztuLGADBQGIYKSBoaAJbV3qDfpjbA6ZBErAA1Kylv8APrxTFvfnvoPnR6Q2kKbc6Ctn62jvGHhWKnisPNsRyNSwlU3s8jvRv8rr6lVmXL6Md/o87pHL6nOwnP2+d1DWwZ5lg5nSLKD1axZZepVu9wS5ZdgqjXyGQGmmDDuxWOj0GJSQJoBIGpIJqk0xAAADTABAAE0KUXWSlXWkXNbjI59IjQhggBMYmCoYRU0kRo2hmdgxQYAMTYIYJtANANR3rTyupMbgHXKAzWBVeXf48dvzm98+zs0iz7podWvbC79csWylbstbyr3ax1ekUm71fIWPDo7ZV+vx98sXF3eIauO5V46e1X+wUn0SlWk4XS5WYnk19cuGKFfqvd7p16O1WLPolvVX79bZzugNp0RakYhWRYJgkwUk0QBFjqI1AIpgA00AATQmnWSi3qis14DHQTBDBKQqJERGUhoQAk0m2BnoABJMAJRp2AEAOhMACLj1OV1pjbB9cxAzWJ0AIAA0wAoAEAqAAWjG8US7FPslQ7RZRMAAEAuO67EJEDRUJsMeDaZqbqDFr72mbb53QJCY4yQhoQ0AAxMBOxACYCTUICmJjQIxAAAJmSiXuiXNfUljomgYANNZJkRJBFSCCkEVONmw1LPRMAAGIJCIYnQ0DEDERcutyOxMbIHXKGs0adAa6bAsJsBEkYM4BjqaxZlTTERcecej+deiABQAAYoyHI6xx+X1uUWsCgFDadDTAA4eLU6sYOnu1irOaO8MAQIABBqxtCdNAjQUmgcWgTAABpomIACLAy0S9US54ILHRDABK2gm4yhAAACYRUwyKDmpkAmQRkMSMximMYJtrEm4xkyrj2OP1s42wOuRNZrArXoXo3nsXLi2ks4cqrdV2qtYNA2uVYNhNKo3nzxfQ6nu4jqYOvCvO/R/OfRI4XVot8OX28eQKpa+Ca3d5FgOPw+3xiy8ay8Y3dmrhv8AT4fWNHv1boV2MeQKX2OdYYycmxU4sWTn9g5W7QvQzl9Hlc4sK3eUa+h0NQ7mzCVSTEEFJhCUo0AAADTQTQACBGWh3yhXPDTWOgAACgA5RlAAAAAAAQlElyuElkDVRkJGQEpRko05RgJjLd1uT15z2QfXMQM1gU6DfvP49Ax5VZ5z6NRrNL0wWpqcPX7UbdG9B88Xr9A0C1j16ofofnN8jn070jFXGsPnHo8Rr9hrRKxV2xnE5+9oFq5HY41c3j9nnxbdzj9mm1EYBUbHWbRG5U7bTjtdfl9SqBf6Jeox1K1yKpZuRwTv4ZB3mOxtME1QAJSiAAAhtNE0AmAhLmoF/wDP7jipmOiBgBKJgpJjAAQMTAAI5CXHJobi1mQCTxsnLG1ykXLIjIYmW/s8fsznmB9cxGZoDrW49hE1doDBwrIHJ2N51p8/thqV22pdDlWQOXHqBRLH2A4m5vs4PdAXK6qin2HoBU9W7KsdZtQUizdJFFsXYiaWzsIISiUS09JJloV6wLo9KEyjX/Uyw+T2tQ3aZZ5HFxWLnnSlqblDTRAUACTIQFAAADQIAAAZPPfQvOrOUBjaBgAoBA0xpghoAAAMyms7SmlgTExk1ZFTCBIFJBJxFm8couna4vamMrT65QGaAUNNAAAAAoAEAoAkTHkVDBMKABAsgaGBSTAGgBgDItMkALS3KGW83+HHdTKjDJjjR26daDbFJGwoBiAoAEBAmqAAaBoEBoTAyebek+ZJpAs7YADUoADQSABMENAAZxmOgBSYAAAAiQRJBFssi24t3dr9gzjKD65QEoBUcHFsMaPR5+5Ya9auJob2CrlsKrkWwLYrJaeRHQTY7le7a59evdes25ipZeit8Qvq1eDFoK73zJGp2OtopVqN2NX7RuS42uWJoRS4+0u+udjOjSLZVIvhp7lhq7FKltubmbxVrFXO2dCfO1K73N6XOjnWPldWkaME6Jhy0NMSaAABggYgAATJ5h6h5emogzttAwaxGoACQAAAmAnE2QeOiaKAYmACYDAEwABplpsNesOM5WHbmgJQA4/DumgPR4HRF3+LZ60o77sr+TDsy9jjdnjGCM8Zl6/K3zz69Un0g5uj3nXNrNnr5cOfv6EVfrcrYNiz8Hu1i0OpwDg22vXKObyrLKjm9KsGC3VyxxOk3aqnYrfR0C6AahTrjTM2zbWttlM7fCtJnpl0ppa9fPArff4tnOV1qL2TubKeomAk0DAAAAAABNMnl3qPl6aiazslGQ2pLFTjEQCQAAAACA2CLz0YgbQNDAHAmUAAAAwtff4nZnPO0+mUBKAJx+1qlcbe2dwotwyc07Gph2yv70ci9bhdvkpr6+/ury+5wOkUa6bfBqy6+htmrxOppFp527yI4vX59pKjc66qsfJfRPPPROVzyz4dDaNzl9NpTrjwt2Xp02y6tLh9fhRejHksKXdKtL39ng75WLVS7Mdel3KhF3wYMJpWao9U7dNtvLI93mdKxNFMaAAYAAEWAmgy+X+oeXM6o1nY1IJEljGaIKagAABQENAmcDPRMQNMYmDAYIYANA3Fly6/H7E55mn0ygAAGAMBAAAFTTAQAFCaEmlAKYAk1AgAQA0R096oFpzcHvo1KKgmZAEGgaaABUNEY5AhDMGKGwGtmkGGOdIxOokkMAEAwAAECAEZvLfUvLGcAGdsGNqSiaFGSEMhAAAIGZgM9AGJMFJA2gYAwAABoLl2eN2JzzNPplAA0weDkndNTjljONpFmIck7MdbiHU6PA7BsGjzCwLS4lWdV/qLuFdsBJ4NQ6K0sR0li4x3TW5h3VDmHWrXX4MdLtcfqWVS4cTtSj1MhtmtCtwcEmtRG4mSpIGk6kMQTCKAE1QwAAAAAAAAQACATL5X6p5UmJhnZJSBpq4sIgANQlJCGgAMwnnoxMEwAAGxNANMAAALl1+T1pzztHTIBA06qnQ4ttzcWh23qcrgXXWNXLULzGTgd6u1t9jjdghQ77R1vOjvKyv2DU1V4XbrnRjmXmlXYdQt3FrPU97VixZNoKRdKP6MRo15qR1+jodevNPSPP8A0GKdk2853qxaeDWXn7fekw8Gx1s2+lx++vnVwq15Kp1e2VQrxSbnBw+1IyplgNUAAAAAAAAAAIAEJl8q9V8qTGMzskpCAVikJNANQkxUAIYZBE03FysUgAGIGJgwAAGmXPqcvqTnncZdMppw2iqv0uhWc21nC2dOhq8zGm1yrX5+votWzBs9qoWA26NZ6Wek6k8dUj0GjXSKj1uH3yu3ysdY6Nf7VcJcm8eenoGOG7XnHpFIscdKoW/z4t3Xrverz70PzP0yK1v8rpnb4PerZtc3fr5Ztaw1VNrvcHvrQr5QPQABVxNWx0GLnu6u1UTidkmcreTOcreNiMlSAAAaAAATQJhk8q9W8oZiBnbakCaVuLHGSBMhJoE0CAyDJtDSjEkiLG4tZCIbQMQMAufV5XVnPLOEukAcDCwTREErEA0DQEZJkWwjIKhDMC1tpooyFxZGGHBuM1NoB8/fDTjus0zcdcna3oxxs3TkR5XXZyM3RDRluBxdzdZWe1uIItD4Pc142QKotu3iKb2uwWUnv9cgEaIGIAaYJpiTCLAn5V6p5WzFhnZJMEwECsEMCEmCAEmGYDPSJNEVNVEaQaBiCTgyaSJiIuvU5fTmM8oz6RMaMAScRJioaAAAQNA0AwAE6AEAFAAQAIAABgSTpxlFFJETEKyDJEUTQAhi09sKta0CARgDE6TTIMBgAANMENCABAkvK/U/K0Ti87kAMENDAGoNCGhDUIAyieejE4EykARJoipiQGUmmjaJbt1OX1JjPKE+mSUZAARQlBA0AAAgEADIE3jyUAhgACQTQ00oJgGCM+tzsHG9DDow4+rp5+NkubBlrvR7+bpNHUgQ0Ik4sJRY4tDBIAxghNSE06TASkCBgmhpoQ0Jgi8s9S8sQE86YNWhiYAxqMBKSIjQRkoUtac1nlgnLkItW0DEwAEMEpFRbIunV5XUnPNOE+mSUWSQEYyiqAA5/Gq0nG2TfVb3o6xy9M36Be6gWju8TtgBYNNQEjTiARJAzBwNjS8vbW2zFjefXkZ9KzY2yYsy15+10q33e/LMnHthgKMEGhZIAAQlGVAEAwQ0Jp0JgCYAAmgTQJpF5T6t5MmUg87ySgyQpCYwYxNhFSREGsRo1jPHNxyESnia5nimuRwcsiLG4sGmIYXLqcvqTnnkn0jcXIxKkklkIK5vbe2Aizyy+UK/S9XS22U7m3ajlu7PG2k3zh7i77ToI6KdGPPzrsA0NfY5+bx1p9Dwe1Qzxz1hp7Ov2bEoZMweRc7j6XIzdvHZ017eIAg0AANxYNFTTATiScXDQUpJggAAAATQJoTBI+T+seUIhxzuU8cicscjI4TJgKNOxKQQUlEVOCyEY2KYYVmRieSNRYJJxY5QZJxayE4uPT5nTmdmUZ9MJsIxcFYgGhGIGnBfLfQvO/RjeAR+dei+bnbt3H7FQ8y9R82i9ZdDgLivFNsB1qHZuXXW6lVtMS5vR5+NcnXen42ru6Wf2+Ds6wvN9LPjlo9eOtt6Wd5urk53V8/0O6C9/AApggBEhA5KYJxJY8mMlLHMYwQAAhgAAAIAQAJDyr1XypIjM7AYAlnLHIzOEibjJGJ6KE0RUllruCzrNLDJcxilLkIytSkEVISKkIpIWQnFz6nM6WcbGTHk65acTFyevGWvPj8Srpmp/o5HMgcJYk8u9I839IXdBEvM/TPMUvvR53RqXmvpPmcXejXyiLb+7W7IgIoBj19glqer2+B4+eKcF6/N0ovFw+nsaufU7+PBn18/PnnsPFs/P1ZUL1RtOgAQ0DQSlBmRQwG1DBw4spULcTcdU21WbKSAoAAAQIAAATH5X6n5aiUlnaGlYAAjJLFOMksUjLLFOyaDRRnFNMa57HFVMgGWWu4zy1mu08DMqhKJA7UCi69Lm9LONjJin0k0RSKatrVPudMSy3GqWpRDDk7nFKddtWRZjT3A8tvHKTtdat2EyeW3XhFl4ezYzz70Sp6q3c4Gazc3cGdWISFbtGDGqXqWPh4u9qa/Wx0XLyanXzZ9vY7/AD6roi7ZELUk06AxmRACAGgcJRjJwu5zij+meZ+mw+X1HVAvkwAKAAAEAIAE0YfMPTPM2UpGdxJRAQrBA0RkcWSljZmlhnZlinpqKa56hHIqgSEgsiIEgiNClEMuXVDbnpylv3R53RzNicJ7jTRACq9TLlTEt1nrXfXMVDjHo5x8p1CvVw9DODv2dA5fPiyFDt1bzhXSyqid47y5mBe2qN2k75g0zpnA5a3KOpuoa+xry87U3NjF5+/p9E2ci5+5vnDzWdYWgdEwcYzbXn94jsGpsaSNTVjrLmI6cZQMvO6PMKd6T5t6RDB6Iw5wCJI1c5NEDHhqtpjdAoTia3mnpXmjLaM7mpSNdZ8IgFAIk4yAESnjDNLBOkpmN41kLMayoxGQTGssSCmWYyaIEwxk0X/pc3o4ZpwybjQyCZZXabcKctxsVesKcvz/ANH84W32Tn76SqVs4K0v0Cg+pA0WUXF0eYvoOLK08p7nHtcWcRpX6V6N5zlcLJobyyp9v4CVf0nzD0w5lZ5tzXssViod95MYet5t6QefbqiWrh29W0G8QlJ5r6J536UT0engrzv0fk9oPP7/AFIdqo93jLzely6pnpfmnpMatQvVeqvejed+iRg4kYFj5PYKrmXP1DzS6Uv0KI7OU0EM0/NPSfNmRxed5J42ZMeSRqx2cJAEsnGUDQDTBxDMBnoAWAADBRkhDEhHIJiJQsaAv3Q0OhhmlGWpITqAFlZqNrqhcLFXLGafm3o/nB6Vs4M6vhdzglU9M849HRNOqjz97Vi9AV5hcabdo7Ti60vN/R/OD03NCSy4Xc4ElUuVQtJSfTvMvUDIIpwkHl1yp9sjk7Op0S0odq1dvSTzv0vzT02MgKpHA0y1UmyceOfdqXdTJyerx6qXo/m/pMPg92vVxPQfPr9HFqXotXN/u+YdEv2LFOvOPQ/O/RDaAoBGl5t6R5wymjO5uLMkscjJGUtNbFu4IwyRmsEMTAAzgs7AVMQMSJEQaQkiIKLGcanGvQd7R3ubNKL3JidRDDZU65tahbbR576Cc7zy50tfTsuh0SNcstOOV6N5j6aikpFLw4YHocZatebXqh3OLCwrmee3ikR6c8OZZV2xVM4168/9NTyz0HhQLkpKjW2axFT9Cr1zPP8Aq8PtFpbjRzelylonp3mPpcmasWek1zPQalc4lVbTT61rxRb1EuN3K7VX9K8y9MgrthrJzb5Rb2QlxuzXMpno3LiqXfzu/V596N536JG2maJNRo+b+jec3KcXncmmSnikZcmDJWSMlqYcWxHN1zNiiLCUEzYfP2JrOiS4yaEpBFTSRGgTighWKZllvG9o72ZllGWpKMomvyO8VXFZHZWdruhWI2gK73Mwc7jWqJVeh2QOV1ZFSLcjj6VmKp2a1BrLaiVbXuaK73c0Tn1y5JaT3O4g4XfDhb2+HL1LBEOR2BPO9m9BqbYCw54lA6VvxnP1uzlPOrtuag67apL5zeM5Jgqd6xV5pfN1GWk3CUUf0TUCsWt4Tf5uXDXAtO0zy+7Z+ZFlwaG9WdMOb516J53coHnbFIJRZKeNmZ45WTcXRjyla2Pahm6xkxy4BqJ7GoG/LR2JrMJrEcRISOLEgpOpzJ5tz6HP6EzOcJ6kouAYMwa5nnNaptlmq9krWNpmrHaSaq2iXVNp1rLbRqG2LqG2GmtuJrPZZrLaia62ZGqbYar2Q1ltJMBnDAZxddbMTA80VgTSRJxFOEhiiTIBleEMqxwNiWqzYy6M06BpOtuGtE3J6jTZNYrZWuo2TWZnFK55HnvoPn1g087GMABtBOeOSznjlZMT0E1ZHFnUc5bEeW8CyqzGTRLY0xehDBmlgZkYhwSU4SMuXXyzVy6XJ60xklGW4QyQiI0OudSg16gtbYslFsrsNriF2hONDiQ3GQAUEQkkC19kisYNynrcezh20w8fv8ddHYpt8To5goTBMYkykIgTQxoIyQpwkIYNMpuMiMZEKObAPNhymYHWODxRsTxTJIjYxME1KNOzj+fX+hImGdsBQAAEeSDWUoMm8cqnLG7JxZWGMly6Qx5YJBTVkY5QwGXGmfY0dmaljyoRJxjmnVu7HH6+c5ZwnuIIwnLUOfUL1wqz2bzf0iwEzj8br8kuAcU7K0dGu64YzOcffjYNTQO0sOahNHEpF3pUenk1Ueb1OXFB9I839LM4aNb60tgygia19moLFmhNBKMGYOR2efHXB0pJVJwmKUGSHMWvt6sLLypHaCNY8GfXjNkwZicZRsJIGhkZRkcOi3mjIhGdyEK0IaAk4Mm4SiREqU8UjI8brGBjRGURJpGhA8exWvkbMosUuYxzJMlLaezx+vMZZ4s25jjIjLx+rxTrauBVQr5U9qrymk4vL6XOO5xbRIdOt9LOz2+DYTzrvcyzHU5XT1yl37z70EiJ1w6Vc6cX1dSBo87v8uKH6d5f6gVva7U6h516R5melae3kPLr/Q/Sis7FgCgdvR68PmW1VXONb6kXel3irxCw8SxnD0bV52ekcXsee1dNPvcgfPjZ4oFg5FgOprus1Yo9LXOR3eDpnSng5Bb+d2izkdfzf0aUmnZwKXcqhZhWSONRJCwU0QGlARJwlEhA3FknAJpqaiIRoAhJVjmhM8sWSanFswxzRTHnwhdOvx+zmZJRnuYxxOZ06taYGFcSl+m+bWeibVUtRwNHb0iy1meU6nEt1OOn3+B3ijWun3M2tXa0yoXyi3oEyq/UbPVT1GLQuV1OLFJ9P8w9LIcevXMyUL0nzWvSGmecelea+lRjaKp3fr9gjpoK0KxZa1F5q9nqtb3a43Zg899B8/r0Pz70Pinb4uQNWxzaUCxVuyS8vc1ZFpxzjWvQvRfPYtWvkKsQpWedehef+hSqUMllZqdoqaZCLmgYJZBcKzo1lswjXJpRoGRcMiyYlNNIRiVSIom8eYcZOXHMimSEIkkiy7dni9rDM4vUhwbAVULNsSFLLOziU/0JHn9t6SKhguwcTmW+Jq8CzhVrDss88svekRr1jiefXzKxae4FC0fTCq/3ZxjXp93DzG1WSNUi072tEvP/AEbGRwzmeeej42Z2sdUexbzjcIuuJXrajp0u0apqd7m9GI+e3jRN+tdrlHWzcnWq67HmHpBRe91eIdenW6Ztvl7ZpafU3iuZ9eZZYrn2U70Sj2uXbnCdlUqlpqsSljJrI8bMjxup5MM0nFy0xY9qJrLPHNwxzkYFmCCHnUVNESSqCmiWRzl1zJjRQylmKWRmNyC49jg9/mzg9xDlSyKVk8coGFAJSQgAQCABpjaCUQAAAABAgGAIChSiJoGCGIG4sAAAG4sAAQAAcXtaWSNqWvrVXbRxbMZowlSjOJNjBpoxMBMABOMip1az1mWKalGmCaJTxMzZdbLWzFPpmMMkZUmRAko0BGNSRIxkomaWJrnnqyjYMU1mgBSRFTSWOxVuy82aafTJkxzqQFkIzxkEwSYIEIYIAACQmAAJMHGQBEAAYgAGgEOIxOgAGmIaBoGASiAJggAAAAmoslKEiYFOUWMAYCMTAATjKqjWbHXZYpmbEYJMBDHkhMzygak0lQ4gIjGoSWNoQRlDKjWRy4DLGoOUUm4MyywylyERbHZ6xZsTOI3mUwqREsITxkUIYkEZIAQ0ACYxBKIAADTENACGmgEwadCaEwEwGAIAAAaBiBoAGgGgBA0xzhIm4ypgiYANNBoHFoGnVM4Hb4kNClEyENqm2JsJCVSiMBYTNDUwptxlHO0gSWWOaVSJNRjNEI5UmOOaKRk2DQths1csuJkk1vOVkLJY3GlAATQACjNEQAGhDAAATAQNxZKIgAGhABTAAGJMAESEACGIGIGgGJgAA2RGhAE3CZGTRN45k2Km00TTATE4ZKofK6fOiJIzYLJFUMBjAACGtZtYNNGXGASeU//EADMQAAEDAgUBCAIDAQACAwEAAAMBAgQABRAREhM0MxQgITAxMkBQFSMiJEFgNUMGJURC/9oACAEAAAEFAvhQBbcdqU30+g8MMkrJKySla2tDKVjK0srbZWyOtgVdlDSwwLXYgV2MFdhBX4+PX46NX42NX4yNX4uNX4kFfiQ1+JFX4kdfi0SvxtLbVr8a6vxr6dbCLX4k1fipFfjJNLbZNfjpNdhk12Q6Usc1KIiVpVPoM+/n3E8VF7GUn0691Pg5+bpSlENa7KBaWDGWltkaltIqW01JivjfE0urQ6tta262q2q20rbSttK221ttrbSttK20rQ2tCUjEzH7Gf8leUzi/SD9rPqsqyrLDL6S6pnC+JnhnWdZ1nWdZ1nWdZ1nWdZ1nWdC9o+49zWNY5HtpHtc7/irnwe5nWfzxexmLnI1sXOcWpBnFkCG0TO5lWfmvuMZixJjJTu8UrAtEVhm/XXPg/SB6bMbqqpCizzR0YRHiBMeAwJjCx/yMWmSxER00LKZMjExVqLXinl3oaLHsfv71yivkJbIz44/rrnwfi5eeHpsxMNphraTaxsQY5NtK0lujOjBug0HMs3C9am25hUiTSxHje0jPKEfckVd+FY/f9tc+D9IDpj8i9cyz8LC9A0kshsC3D9yDPkaVIhkERhhy7i0D2doc19xcAo3tIy4TCCbZyoxWyGuW78OyqjV3nOp1xQTxkaVuDnI1HzozKjyByEpsjcokxgqa5HNwKYYUbKY9rJYHrgphtrwSlOKmqi/QXLg/SR+kPyL1y7RwsLwmcK2LpnXeQoQWkgxO7cCp8gJ41le5pPxv9ur41M7Pw7twrH61duFahbsmruxHRLI9deGSLV3C0RrKn9a8EVke3KjocwKHBG4+B45zzkajW3oSNJaiOJFkR2na5NBAMUrCxhFaMpIcj1T51y4P0kbpD8i9cu0cHC8Oyh2tuqbfF/s2XLsuLnNanbAZ3jcWrPw7twrH7qu/CsfUq58GydfG+etn4dxjrIBHkFivizhSO9eSI5bNxKMmcz0wn8xns+dcuD9JG6QvIvHNtHCwu0jeNZQKiXwf8rIRMXuRjXPJNkR4447L57LNw7vwrH76u/CsfUq5cGydfG9+6z8OpUIclDgfHJbZCyAUq5JIuRSPjxHql6RGss/Dp3Pwn81PT51y4P0kbpC75HoNklSHPa5G0x8sDKlXAhkh2x71REakgLTiIE0I0e4hK18kLE0LKqL/AFp1XhykfZXJ2e7fyiWZ6NkVditWLZno2TV1dph2d2mVjel/dZ1/qnNsXCrwidlsw1aGpiKsW2Iizavbv22fh0i/3MJvN/z51y4Pxc/Pj9IXr5OSd1URaWHGdQ4oBrRgCNTYg20o2KxIAWOaNrWPtgVckWiQAEcltjpTG6WlgDMv4sKKxqtbT0crX2xCPBBWOp4jJDmCIJCQ1O9qI1MDW39rO0ZSYDTMhglRaI2To/FHoG/kZSojrbJcsbeRnzrlwfpA+wf/AALijbQisL8C58H6QftF5FwlHbLjOc8HxlVGoGUEzvnKmaXaOwS2Xo+fdOB38lrQ6tp1bLqQC1s0gW1tNrabW0yttnnZdxKH6C77nNZRZcKhEaYbiMZTJISPeVg67dGzRUWnPaxElx1X1w1szVcqRyL3c0XvSRb4INvKGRVwk6FwVsntfyAG3sL10rNx/PuaZwdutt1ba1spW2ytDUTDPHP5CerPQXfc1r0uIGgk23g3GIN4YrntOMLWVc4rHghySgcMDW1PiMMG1yHjPPioQQnKwogZtkwWPSFcHI+ps5WPDGyQkUbkFNIA9DOsyS6OmVveZz5pZQGwphzTDoVzXI5sr+xT3Gawl0PqivcSPIkDjsE85mk7QxI0xh6kHULfy7lfu6lM+WxsW5NK/FJaEIrjJQpg3vMdgUW6hzcVEUspw0jzgnXCfOcjbUVowNM1y3r2WlUbFWSlMnAeuCnGjnSRtprkenkXTg54Z1nWdZ1njn8pPVnoLyLxyrdwj9C3cyipmKAn9yl9IfNf7Ibc5WF3HolDmL+MtLNyXhex1ajKWNDOsSQIrCtaJGlmeMW1c2i8/C6plNA9AwAZzp2F2FtHgyO0gK3I4mIIdS00S2+2rnLV74gUACruDMdtk9oZIbtnjC2xVJbtSm+yrz0rPxavfpaR68LyJGvtRFJFuc1UdBjoAL2te0ZXQZnkXbg9/PDPyc/gp6s9B+vfvPKt3CN0rbzKf7LfzcIfOX0g83C+dRuf4yydXC8cOydadb0Ov7opYE1JKTOLaOZRubhdubOXK12RP3YXlP61kcu47xn4T+anoRdI4qbkrCU3VGtztMyR/KfhP5qe2r17LPxavVWhP6tXv22p23AEm9I7MtdndRLawjmppb37vwvhZ0jqR1Z+cnqz0F5F2dnMtjtUKQuQLeuUuieA4K5TKVckjOylUJ23Jwuhd2WGJ/8AXwXLGm4Xsn8YTFiwmqjmyozZI4moc2dw7PzKLysLr4zZAt22Wh+mVhen5BsolRv/AO7CZz6cmpgcwysJbtEW2j1zHeM/CZzsL0tWjiVevfaeHV8qEmdpiLpleXeOH8LKssM6R1Z+Ynqz0F3yNc5FtTVdHhLHqVHNIr8SqKFpm1KEczfxJEoO8iSmSCN/FGoG/kFiEks3QIcp3Nh25BOqZCZJoLzCRZFDhOIaYmqJDeaOJ8sTUgRHb1xkahRNyOcZGkSbGIE0eeF4+1MSpL949vkseCXBeMseSw7XPaxHiJcJLyBiBa/IoyNK1zkahyazhI0o6uUJSLBk7o6uZVJUOO2GFHpv5otelHej5CKjkq9J/KzuTYe5GJeHIp7Q5Oy1e1/ZZ1RYkoDo5oUlJAqMTbYmeXfvPD+JlWVZYZ1nWdZ+QlM9BeveMRRtfd1pi6meQvpFXKX8DQylRFrS2tLcHCG+tgWDhscuwGmCGxXiYSuyx6YAY1wIAZF2EoYmDo0cZq/HxqEBgaKFC1+Oj0ICBwKNpWJbmMd2anWwblFBQNORVY+2IRwIKx3GCwzPxrmPayZQgaXeReeH8bKsq01prJcM6zrOs+4lD9B+RcGo2YHo+RMktENqPaoJQzJ97euH8zKtNZLXjWdZ4j9o/IuvMB0f+IvXD+gyrLDOh+0fkXXmgOpBvZJyHcnjK5V0FuRAvim7QFyqiEuaCfFOkgUiYOPQrmwpnHTMs9wVjSxSacdMyz1DUeSKQlOmhQj5O20EkR8HFG2hGGWnnEykmR1XuelI5HUrmtwc9ra3hLXrj4JWaL9De+J9HlQvaPyLrzbezREq8JlLt/jCvfVtfCq9p/O0cM7EIESK4g2INkoaFjg1bo2NGySNCgt7lbMmNe+NaorxvVEVPEEyrrFGxlr1uM1jWJdo7dmzmdngqZpdQbVWpzlSXb2PHF7TGjW0ayDkCMrAGJFkVPnbFQ47iMuEdNi1yyPfOmpGSMF5GHiI5kKc7c+Xe+J9IL2D8i6c2Nx6vPJt/CvfVtvCq9+tq4bvbD5lL6QubhC52DysZRc1lVduHZE/lVx4Vm5GN66Flb4YNajUzyortcp7tDBop5Xpg0IY6ZukSdcmtyTRYUh5kzy+Ve+J9IH2D8i6c2J4xavPJt/DvXXtvCq9r/O1cN3th8yne2DzqX2wubNkdmDHSRPKEAwpJ59Xbh2TC48Ky9fG89Cy9GjlaAST5Mko461I5s/h2/mYTuHB5nzr5xvpA9MffIRo0lK4x7fIbsPe0aTy9okWuQzZu0ZxKtcprGuIxqXLW41oM3aklaEIH7ZWuRySCNGGM/RJ9aO9BhjO0HvTVcKyqmyqoiPdqPmmV4d/Vsi+NXNcoVmdlIxvfSsvRq9Z6bK1Nqnu1SSt3BpqjnG9pGVJd/D+QDCI0o6c5GNnyVAGNcCoX5N8430gfYLy8krS3BwhvpoRsogRlrsoKfGCRexRqEAYqJFCV3YI1CCwNFiCMv42NTIo2Nbb0GTYV1SbeI7mRno08BTqK2qF7dSNkxCyaHbXCezVppc8pUKRJfGhyIrm55SAtOOPGkxHqhSJJtjtQlkqyXCZIQQZsRUPLdQROR02EkigJLhq2Y91I0pllx0kjfEUUn5N86H0gOmP4b9eUidJA+3yHSBec4w2UyWF5PgmM0TYwHbnyb70fpAdIXxL0n8bNx/OmxxkBbOZ8HSmr5V96P0gOkP177zDZXaA5ouaeTe+nZuL5xujauZ9Zfun52dZ/Fj9IffuL3ji2gNSAtOKCZ4ZC5qlwWSB1uOVWrDG6pYywSQZPaQy5TIzIzpMythUS5Hc+rPxcJkgkdsa5PefUQiSnzANhT0kLTpjd399LM23ouaYF6Np5lFkDDW6Su1sR+dPnR2VHlDkIshKS4A1NVHJTzDYqHEqvI1iDKMtEIwadoRaZKE51K9iUjkcm6zP41/9nlZ/Kj9IfkvejGh8ZVXro2Vv8KvHFsvtORZMkbEGyr03Iln4uB01BhM3JVERHDg8y7y1GlpBtxqmAQ4LZKVhMDdG0cy4SuzDtIteEsCSA26Wo33gLdq0j3CVeBoorK9ytuMlQDtI/wBV0Ej49tc09dnSA6EjpkqrqFHCtxu0DuIkDItyOMGdBqC0jQfFv6+Hez+dH6TO/LktjDCeZLeMCNoPNq89Gz9CrvxLZxonJwvfpZ+LgXp2rmV/kLnTnapYkyFhI/XJYuplH6Fo5l2fqmQU0xMJyaJlwfuWyyeyrtw7LV6Rd22cO4LlDtDc5N5f42yOhA9lbSw2OSPEGB9469tblD+Pf/X6SP0md+9Z71qaiRHLpbHXOVV66dn49Xji2bJRPaoDscj2Ve3fzs/FwN0rVzK/yDzrmJRy4r9yPg/ORKRMkqT4R7RzLsNWS4DkfDwnLrmXFm3bbL0au3DsnsmDGUUJSR6loaUkWO2MO9J+2zLmDG78iDxPj/8AyDqfSQuOPvyY7JLI8eTFpWPKhrY9CMWTlMjy5L4QpUVc/wCM9kmTUIcmKSXESU2IUsSu0jq5CMr7a44KTxSrhJawMV7gSBlYVJUlgRhc4RjsDPDCI+IuaLU2TpZboWxjcSIOJbyIKXMjpKFbyOikqUdACt0NyvvJE0WV6aavD07NZHpU46suCXONX5GNQjDLVwBvhhHWMZjkelMepC3Vc5cHifHv/v8ApInQF8PLyMkrJKRESlRHV2cVMY1ncfEA9ewxqEJoqINhKSOjaSOzUvijoAHqlvCxcsmkgDK5tvEJTlZIpLW17XWl1ZEjGATdDIhCPTIBB0kVVpzHI19sc90aOWOnx7/1fpIvRH9LIuKBWDKWU3BVyp8oDKAZh24y0csWFp7LhdnI6TFHtR/m37q/SQeOP1+kvaJtWTpYZItXeOwa2bjdzYVi5mSn9pekeCMTmnG59KRiL8u/df6SJ4AH5BJIRqskbaYRhEweYQ17SJKa5r0w3hUiouOpqeRKO2OK3OV8Tu3voWPoY3v2Wfh9+4auyZqlCeror9Wq3EUkb5V+6/0kToD78nXsWqO7dVEcj840pq5tuUxRVbYyNYUaFHD3gS5R2xxR0LcDbQ9J1JBksKig7UabIZGExJwnRainSaG4NKA9rcUonRRuR8g8AzHoYV0GQZYDZHZBIRKmXBzSiEXbkSpEM0czTivfQtR0YPSdUJNNGKIjTMvnttHCMVgWBkEkUV5wtjSWSE7k8LHGaiNZchhaKGHZj/Kv3I+kiPyji9fIc5rEkrrkt8GPVTHRNKYXcmqRa2aIlPEMlXkukVpYav7dGZKKK3wyxjXzr2lumEq5VdRISJZTaS3zq23g0sAKyKvWVWfi3zoWMaYTwb0a2yFBIvtWngyj9plMkR2N7UCtexN9cSa8ggQVOVURgFcX5SVfeR9I2Q5SM9e9KOkcQjSphQxmCqbzV6QvAmNw5kHxh4Xzq2ToY33rW3g1M4ttz7bfORbuFUiaGOopb5FXdipVo4l86Nl42HoW91HXTZrcmczS2tDa0M+jvvJ+kBBE5o+/eWrt2bLRRn65DPZPjqA0CS04qORWNu4FR1okJopVREuLHSItokII2G4m7fOtaHaoVXcuiJZQq4165du4J37YYY+0ykRGpe18bRw7307Iv6KK9BiijU0m+e+IzctMR+1J+kSr5y/pI3RH6957Gka2C4JNt7kk25hXCCdrHDY9j7YmpoJdCAg1ciOQ1r/kz8iykCYtZJlKtWpQOngTclvoItur514AniAp1RHQzzDCG0TLpDeV8CS6OPUsiuzmgymyhPS5RzFq1SWDFdNR0hb0Eu+LKaZ8uoMRsVt1M00mzmbsXCA5HQbgjW74lRSdo+iSr3y/pI3RZ6/IvPKt3B8nS2vDDbZXpT2tenZQV2UGDwifSRI6V6fRJV75n0kboj9finYfJJ8lSEeg2zFJIkW2Tti9e9IuCAWDN7U/y1ki1dsBq+hSr1zPpI3RF8f/APV5N2aiw7J1PKu53CDZRogLnDceoY3ij/QJV65n0kboj8hTiRVVEpphPWlcjUQwlXBz2tpCjXuZph6ze8R7Rst5VPhdeFY/f5V899pTKFVymGEeEVxo3kDKjy/GSr1zPm51n3PGvGovRH3zAGZMtsjBoZsq3uQsuWsYcEGtpBDI3dJBkzTuZEtYdx0mMM4rfJIKS5Ua0ks0s4oYhpIa6M0P8pVCOsyU6OzKCpt/C6iIjLShFC1ps7twrSVonaTuqTIlw3xZDZIlVGo2Y+QXbJl214DIqKlPdobdXqQtvO1kVDtVkibDdUM7TjNIYGm3ELyFO0dCuISPIVo63lockZHzJu221la1GlYq/FSrzzfhZ+XlWVZVl3I3RH698vjK9KVcke5TmQUhE0SaPBKdwBbYEREp7kY2N4zrwXSOzDTKnpmyIn9pfFIxnQpQDjkM0IhMLzxbL0Ku/CsrEU9XdP6Vjz1Xk66rYRoY/a2Vc3NOy1Of2fC89eBw6vLEaWz8R7Uc1ubSjZttJb2Okb2q7Vs6Z124tn6Xxkq8836SN0R+QvMonTH4ExlSGxmCky5T2ARKi/8AkLz17Pxa/wAh8ypsBsmnsNELbp+/jeuNZOhV44Vjwu3CsfrcVzmwuJ3bxyYPDq99S1cOgJnMwuEZzSx7i4dCKwzbvx7P0vjJV4530kbos8jP+xhMAoTQJCGFSqiJc3Oe61o1Ij10th827h1isxcnUd+2CEuUqWRRAY5HtOFsgUVrmzsL50bH0avPDsfrV34Vjq7j0TLUVCRMM0XBKvC/2oXEq9L++2cKonNpabk5su3NdUYjgHvC/os3R+MlXfnfSRuizvnG4jPxbaCwg8DCYZq24g3t7clIIj6kx2HZGBIiq5jioa2EaVu+RJFuVHjNIyMIkprLdKVXskkixWSYrCHfogwVC/C4xlkhgqeE/ecSrm8p0t+9GM16ObczqZltI6MaSBkwLGSYJR3EDkSUj6EzQ2lcjanGQ0m2na+MqoiXIrTSrURHRjkaMUd+g+aLT/S2HRwqOPfn3hq7VoIiIqonxkq7c76SN0WfUaW9xWtdW0OtkdPY19dmBSRgorwCevZI9MEweHZQ5bOdCCMKPRHJ2EGbANatJ8RKufO+hzxjdFn2EiUKPTpDmjjSxyO457WI6dHbQ3oRi/ISrjzfl5eTG6LPise1/wApVybGXfnqiKke37UjFURauI0HJhcSk+OlTVzl/SROi3vucjGoR7kdLY19Pe0aNPuU6WxjkVHIr2Npj2kR5xMockBMJk1gG2l39fNMHmGyu1BrwXyFcidxVRKzRe6mJelbeXjJKgQx3K8FXbkw+LSYXDc7Nammz+GlS+V9JD6be/dCLrYqObLDuIV6DYNXTZdSBIYUAqtLcYzQutqPJSMalXOO1i2wriCuwhjHagjfGaATFuU5yOhRkAIo2GZHO+DKubDMFbzkbJ2EdVwi7I7XMeZXORjVlmmyGRhMbOQkKTENvx5U55TCijG2ZFRR22apsZMzQ8YnqhhGY2HNaejvNogakkoQ2Ds9NxU27GU3Zh66uvKAVGx3OkIgbg1X0WaIVR5zDlXwph1NRpDgIJ+4L4Evk/SQ/YnfuEdStjySR1jyxnq7OyFbAsIvZA12QVNhga67+y0p+irrx7R7b107PxDP2xR2KaT2cldnJRLW0jpyabfZm5y6n8Ozcy8k0isjPCiDYVJ5NiHbBvfJ0y6yl0C2kGep5+zx7MPWVMLgzZlsLvQbVzMbvyYnFq68q3DRsWro1Gyoiq6NcWI6JaE/tXNypEtRWqArEeyO1WA89Klcn6SH7G99FRakRBmoo3gLNepolod+zG8ey1cWrrxrP7Lz7bRxJiZxIS6Za43Hg2PrVO4dl5V761l42F541kX+x3L3nlZeimF56kL/AMbauXjdeVF4tXXlRONV25MXjTuJZuucaGGURYpItypFRfgJUrkfSROk3vjMjJlXXJXNi5wm64pwGYZtK/W+7r/O18arsv6rQv8AG8+NWZUWK7LKWB0c8GU2SKjk22XNcrfY+tVw8IVl5V4ApA2iQgiYHb2sMUqxpLXI9tPfpWrkDfjWUiNL/tXV+5K2ti22rl43PlxeNV15cXjVduVG49w8Idm6qvRCPa0jZ8TYW0EVwfPSpXJ+kjeAm99QCc7ayoccbHUQQyotvFmkRtIxGsfb0I4UPZXxyLCUzhQVC4wGnGKAYD2hetHCM7PxWh7QzKEBGOmxpMpAW6THIzUqThSZLQQJUcrFcrZNra9RMuIq0yiUxqMbLgDkKGLNi1qmuoQtK4SoOZBHelPM5WxYSCdPPqFFQoDjIhEwuUYilhTGNEslucp+6e3yGuA8jRpMLvHt0hjwXQ7Nm1lQZ571ZIEZhG3Ujdq3gUAfPSpHI+kD02/SucjE7bGShFYZPNySskrSlaUpURa0NrbZWwKlAGtKJThsWmBG1fgn6/0gem36a9Cax9l4v1R+v9IHpt+A5UakMu98RKvvss/DVckFczOkfUG630gfY1c++UjRMCQst6gZk8xYZSyitG25Ec5urI8ooXicZ1XJDabbubKbucgzwoCe4pyFJpDdHbsm5owqNkaVuLgma5HtKVgWCMQ6P7Q1I00Z1KRB0+7AbW+zaW5ja9CMcPtzHv3Xsq8EaRlo4TyjZW9AYVadJCygmGVrpAm0yUB609zWI2Qx9NlBVcHKiUlamr8svV+kD7Gd+5F1Hh7zAbh6mDPIbBCQYpgFjkiSUIAY9ZKvHStXGoniMLdRU8EWIBTgtqDlVe0TftrtMDW64TcssLyHQS3SO0gurUbNtjF7NMhNlVKJnUSO2MGrqLalWjhFAMzWN/sVd47RutLFI1qIiXcLW1aiuIC4DMWSJiDHdxplanq4BRNLR0VhRN7SyTCKM0qO7ZCUrzDGjEKPcSG05neifEJ1PpBexnfldeP0MZAmmEN2yVj0I2rz7LVxaf7IPjLwNIEGmy96rs17Sq7TY7MmcvC8JnDsaqh7xzYqaYsp+3Ht7dUzC+dS08Kmc2r10bO3+rV46Fn6FZolXYmpln6NTUzljTS3CYLYkgJuhkP0iCxBj+KTqfSC9g+/cB6S24usWDXo5xHbpLjG1itsvadV7dVo4lP6dvX+5UouzHhiWZLa1GpfF/eIW9aLU/RNwvL8o1kEqJd+aHoSma40F2iZhfF/dauDQPGdV66do4VXjo2jjS5xHEjQ8kvHgCz8epHOxuotYrOaupJ+M/3/AEgvYPvmE0rHRJMcg5pa3TlopiDFbXqJHvRjTjc4sCW5G3WO87bbKSOnaEIs2UwQYz9k4ysKkkW/Hgv7HL3WZXRpXFtZmLDlwtxY8pCNcVjEeAs87UaJk4iFlQytLGq4wnCJAlNkiVURLiRSyrRIZ2d70YML9J/Wr0/+docixavL0ytK6osf+Eury/xsy/16KucrFzUe1quiyo7FYKi3MbCDe0jJE8YXxzMOyRPGEgDMOzz3e/6QXsH8HJMMkrJKyTBzWupohspURa7MBFpWtdSDYmDxsJXZI9MjhYuD4QHOSMyjRAne2JHZRYozV+MjUyOg2utoXuFBGFVTNpLeMrgwEA6RCEemBe1CRhkGCEoFcIit/FLQWFGmLwI+51/hYZmkhCUMebFIhrYB4RTIpWntgHBD53+O930gemP7l72sbH8W/Gd7V930gemP7iSx7wx4Bnv+O72r6/SB9gvt/H5T/Z9KH2C76/Ozypx2pSyFrffSSH0kmmEa/wCmL0vpQ+wXxFc1tMe16ecQiMR5FcurBazyrVTXUI30pul8POs6z+AH2D9PhSYu/RWuYSy8XzSvQbTEc2kcu7nlTvbratMcj1Wn+wRcqATL6QvSz+JnWeGfnB9g/Lmyuyj/ADGdMlnfW8evy7EoUx5mOlvbX5YSVFnjkEuPNs/D805EV+erBWa0/k2ttFpqIytCuVyIq5Uxc6C/Wz6IvS7mfxM/ND0x+Xes1HBhMjMwf77VwqkRhSGwAuj3O4860cLzJDtIlRH01ipTlTB7v45rQl8VXOmr4ubnTU26juyf56/DL0vh5VlWXdzrPygdMflvFrNgvo732zg4PFnIuPNtao2B2rOi3HaqPMCfFyo1EmCcr5aDQRxG7kxf4iaq0mbq0JWjBW/ypGqtaErTlRm60A7+H0Rel8TKsqyrLup5IOmLzl9q+tt4WM7mWsbjpRBtKwiKE0EqminM0AmuLcZQxsExURanhWJKt8rtIsJXi5qU8udZrmArkV2SotMb4kNTnKqjIrUXJyNamny07i0nwjdH4edZ/BB0xUncXyX+yrfwsZnLtKZQsJ/NtPCvBtci1brV35Ndok1PSRKba45gnwlUf+I20vqKhr4f+zPIWDfYBfESfRm6Pw86zrOs/PB0xd16qiFmPDX5cdflw1+XDTLk0ijer0wJ06gcLGVybdwcJ/NtXBkO1SLLxe8Zupkum0/3C9WYf+hfSk9oeqBub/opHQ8lPMzxzrPzA+wXcXG7AQJqiB3ziGwTMTLkBKgLnCxP4nt3CwmLnLtvBlN0ybG7MXfli8Ep9M9zV/h/62dB6+FZ1FbQm6W+a3U1CkVjSXTQrrqVab4tqSdscQ7pm/182Tx/k51nWdZ+SH2C7i43zpVZG5m7lzM0UWrOdHAwcuTXLm+1OR0LAztZrW7VBvMdUfAkdmO1yPbg0qvkYvbqQ4Vaq/yr0UP82KqpXsjvdTU8BDVyxg5efn41dhNWOnjTfZVxA44RwzPe1ulvmSuN8rOs6zrOs61Vn3QdMXcXG98erH3CoR1Etald+HSmWpw3CaZuEiPJOn4clRocmMrNWmS2YVv4mRUOPMi1lrHKtK5g7dEps461nKkUETQs7j2I+jxaMN6UE22/IRKkH1qxHPUMZaEDLyBvaRnk3Lhj9U9PgTeJ9BnWda6zwB0xYpS43vj1Y/b8LLynAatEgtdX45KZAalMi5U1jWeRdJKCFb+H3/8AauPDZ7vLORBChuc+P3J3D7ip5meGfwc61UDpipMEpcb1x6sfSLuaZcuaFXy5D6DJRsPRILRoD1TtEqO+DcEOppOl+1IfR4klqDuUkTokpkpjlVEkTzhp90kuq2SFIDeKaiAmLTpsyOSJc2lUpWCbrkEoqT2026GYsWUOS3AxxgRko0ispdElnj1HlhkYPmBHT7oBKhzEkuVUaizYyKwrHpJuaMQj3EdCkhbF7SGmOa+jyggoc3eoktwkFcI5K9aX1q5cMXvxUo0xVUSu0CprkdXhT3NYk+Z2h0Hh9yfwu7l5ufwwdMXomK43roVZOjVzYj4dWcP8ML2PJyLlVuBtgwu40ZKtTlbNorEINUyW3C3zYXkKOBVsa6RjeQox8MiikVPmJGZEE6dJREalOajknAWJIt07fRwmuSWLZkWwyBKkbeq5QUElvc5JR0RA1EG3su2yppOzRmopCCYgh+C1cA7Em0SHa/8A+qufDCv7KKBS1LYYJReJqOVAiiZzCaW1LjqjbS5z6kQXEwiDN2bQeho/LC4cLFMcqy+Ll5IOmOkwSlxvfRqydCp3Dq3JphYXrjMTU70TC+e+2c3AvVsbf14T0zh1b26YWF64wOqR6DYYrjltI9EXG6C3IrHKN8ciGDdeZbGa5lLQwjGsjjVF49HE0441uaEuF76ts5i+6rnww9Wkq9J/GLyqvDv42ciYxRbUovSWofE7lx4XfVKVPj5d4HTH3FxvfsqydCpvDqJxcL1xY6f2Mb577VzcC9Wyp/VwncOo6ZAwvPFj8i8P0xKCmkOL0zHVlfmC7c2yp+7GZxKj8fuZoiXQu6a2cxfdVz4YOtSVeelB5dXUSvC16sdFuLCV4Lgbo1D4vcuXB7qY5UqfMF7B+iYrjfMLJ0anL/TqPxsL10InKxvfVs/NwJ1LPw/9q4cKmdPC9ceJyr2n9ahrmPH/AB3usafruvNsnrjP8IdB6FZ5Ie6DYrJsqS4cZavXgtr5n+1deGDr0lXnpwOYtetTbeqUtRZhQVHOyQyR4R6icbuXPg+R/uVKnyxexlJ3r47M1WN2Fx8IVA4+F66UPlY3rkWjmUvtX1tHCwua5Qqb7ML0v6ofKmC3o1W9+5Fxkv2gVbw7Ea582ydy5rlCofSq8HVKCNSlCJoWVe/fa+YuF34kfr4Xn0t/MpMJMIZ6MF4XwjKCRL4tROL3Lnwe+mKpSp8oXsZ6J3SFYJssyyD1b5CR5CKipeTNQNW4qFi4XoqOKF2guaOTC5EQsu3vQcupZEFHqykRQ4XgiNi1Hcj4+F6fm8LtJ/WrnDVHWiRtkxvMjwtkJXuqa7XLsi/yxu3CqOuqPV3Re2WdE7VheHapFt5i1lV6X9AVyLheV/nb+XUQn9qkq5hQkbLxl+EGofFx/wBuvB8xUrTWXdRfgtShexnoncK1z6fbd2vw46/Dsr8MyhQCCR1o1L+HbQra4LmI5GmEYlfiM6/D0GNIAn+GDKLX4d1fh3UIMwbTwJMivw5KFbZAXh3qNvUW3yTv/EmqNHmR6YrtJ1k0+3yXu/FyKj9sE1PFJNtY9QllArtbKecz0Bbk1+1JEk2jskmorJMcopCPxOJDCkQzBWDP2GdvE6pUZ8oI3EiHFKEVrjtSpkImgJFCVJgHI2SiVcZSSC1DmMKJSsY2bIQ5xE2yCKwrZBFDPAdh2JVxM0ce2xVIWWxSR/SrWZr49KT9lJV14PkItZ9zKlSsu5mtNdWfnIlJklC9jPT5qeV4eZoYtaUSkpzGursoM2MRuDgCfTI4WU5jXVtDrZFXZg12YK12KPXYY1JDC2mgGj3RR6totdhYrkRGpR4ITr+LcxzY56EJokpPW7cH4GVKncR1I6s/MRKyoXsZ6d1zFrQ+tBK0krSSsiVkSsiVkSv2V+yv2V+yv2V+2sy1mWsy1qLWotai1rJWt9a31rfW4+tx9bjq1urcdW4tbq1u1u1u1u1vJW8lbyVvNrebW82t5lbzK3m1utrdbW42txta21rbWptam1qStSUqpXhXhi3zk9bvwfNTuZVp7qOprvKSkwF7GenzMvK8K8K8KySskrJKySskrSlaUrSlaErQlaW1obW22tttbTa2mVtMrZbWy2tltbSVtJW1W1SBrZWtpa2lrQ6tD60ErSStJK0krSSsiV+zBKvHC+Hl3kdTXdzPvx+mz076TlWdiueUqeYFW+aaTJ80m5RrhIjv/LkqPMkyVbqyfrRC3Asd35ihXJ5nDV6/IXupiuCeSlXjhfEy77X1mmGVKmCYJSVE6I/TFcZxtkGfjFJvAxvCf07LyfIz716YmzUIaDi4XZiLEq1CRkX5rcX+WlXnh/FXyGO7iYpUPos9KTuuakiUce0azF7l34VlT9/nXjiUz2YXPhVE8IvnSjIAUS4qYvfTBMF9aYqOxfgnkpV64nxV72WCVqwVO7D6LPSkpcFSpJNoMUe2K8CyqKXZPnmmF34dk6y064j3NchKbcxo9rkc0hWCp9zjNoJ2FC49OuTGOEYZm43jiJ7k9uFz4VA6HpXaw63ShsoZBkwzSnSBNw3hZ+FK5qU1UcikG1UVHUcLTDjQRRydzNO6mDvdLktjjtS5xcHYJ5KVeuN8lKWkpyU3D/M+7C6DPSkr/cD/ALZVShIUHpVrNuxcLxw7H1bg174tqivaSryxEPZnKsZWo6p4kDKtA1IKrkFpItserZa43nit92iVlplV/aq4LI7LQ+leSvSrQDbA8bSsY98czVzbIisMz0Uf9ptwgeFuCRQThqE9tepAS4DCDtgztPcRFEOC5z5hG6knLICW2HdltItS4ekcCe9CVMmpHoIyPYcxoRHEPIDFOc7rgJRGtu92UaEqTLYCmIYjXDdTJqjLnmhrig1hze0O1udRzyQJFnjOuCVeuivylwTxTLKss8c6Rc8YfRZ6UmGVPcjWMAR9bBq2ZFTQOAa1F25OF5X+pY/fjdibhbNxqvHNtiaYVS+NbObjeuMLqY3Xh0PpqjXYeiGXUVvsSn9UbUYPC8cmztyjYT/GFbObV6qys/jS+0XXeuTGKppVXZE7LZ3rvORM7xybZw5J9gMBiyJeFyDuAtMlWvvLG7dsFuHrLOnfwM320lXvpfMatetJ3c1SmuqF0Wd2U/U//MLsLXHzVFjF3g1euNY/eczQD/ISDkFGdlevB1m4tXjmwfCHUtf6tq5mCVe+gPqY3bhUPpHkDjtZcSHegnvQ/IT0/wAb4nXG8cm1cLCfw7VzKvVWbjV/geU5NTdKxpaVd3fos4VpUq8cu2cO8PXcsqfwpae3UNn8CXdc41mTF/jKT0pKvns7uWOXxUSs6zwy7kHjjxWnuRjIJN6di9utj26XWY2S1fF/RYl/bfHLrsg001enZms3Gq6LnNhcOpy5Q7Tzcb4vg1cnJ4twvDsotRl1AmkUkmCBAx0oi5n/AMX2h5C43jlWzhYXHhWjmVevdZ+LX+R+XUhBTKjNkiYsN0grWo1tXfmWzh3li1ZSYLTvAbG6y3jwDZk/Vg3xl4JV98rKsqyrL4GXkZ1B47PTBalAlyaFBlBIJz1wyqQcrWuiSVVkaUxwpL9E9JMokQUmMaWBZgoLyw376Kk6EUtW0ro9EkIxhRnKS3yHMFVzOrxRtwBxFaVKLJYOpbzSS7ZKhTMhIupCGYKrhJ7S/Jats1qCngVhYclpQFJ/Ao3CIM7HBPKYyMx2l4zMKys0SrgVCyrSZqx8LuVEBbyIKVV2Ij5FnIm1RXIMQnaTzlXscGekdiXWPTbnGoJhmSrumU20vR8SQJpggV0KUioqVcjbYLZEVFvTqs3Rp3g0K/2cEq++vlZUqVpwyrKsvgZ1n3IHGH3sqRuCr5/h3PDDwrwwyRaybWTa0NrQ3JYwc2ta2niGSmxgspQCWuzhpoRswINhK7JHrsoErLJPVFhAevYI1IBqN/Hx6SAFqomSGioZPxYKc5sJjQAlEW0US2GbQyPAQBEMGVGHIaO3vC/bItPAMjBBKGsy02K1XuzRsmFJkEiRZUZ7VXKUpnMS3yUoDyK2kq++/v54Z45Vl3MqVPJZhnWqs+9A47O8mDl+zamq5eGCVdUTtVuRWRMU8xKvnU+HnWaV4V4V4YZVlWWGnOtNaayrKssYS/pH3MqyrKs6d9mYSq9C1usosrKgwnkL/iL56Ve+r5SL52dIteFZ+VB6Q18hV+1yTDPBPgXvq+UlJ8DOs6zrPvxeiJO+n/FXrr+Zn5id/Os6z7kFf1j9O6uC/wDDLnjeeT8BcFVETyMqy8m39JntpO5n/wAUlXdf7fwFeiUpFXvJlSJWWOWGXfgdMfpSf8AtePmpVz8ZnmquVKVEpXquOXdTzrd0x+lJhnWdL97n5mdJVw8Znlq9EpxaVVXuZUiV/8QAKREAAQMCBAYCAwEAAAAAAAAAAQACEUBQAxIwMRAgISJBUQRhEyMycf/aAAgBAhEBPwHRNilSpUqVKlA6UKFChQoUcTfDfDfDaTRm+G+G+G+G6ToG0+deeQ2nzRSjafNGbT5ozafNGbT5ozafNGbT5ozafNGbSN6M2kb0ZtI3ozzCxjejNpG9GbSN6M2kf1qzzHkFlH9UZ5BwNjG9GbSN6M2kb0brSN6PEPXklQjw8cPNeN6N3LNkG9GbSN6N3NHCLC2jPIeEoocBXt3ozaW0ZtLaM2ltGaNolYfxwRJWJg5dkRRt0pU6Bom4LnCQsPBdhHqmvDeiL8x/xHAe52ZPYWnrRN0o0TRYDnZeuybis2TMrHFYYb1eV+Rs9CsYuzdaJtGaFm6x8aTAReR1THnEwgV8zGLewJjig/OzrRNozQhYje6ViNhfEH6V80ftTQm9G0TdWVKnkNECnsDgvi4n425SsQfkfmKygImaJtDKlGklTSN1IUcxtLaM2ltGbS3SnRNpbqTzniDCzFZlKlSpWb6Wb6Wb6Wb6Wb6WYelmHpSPSkelIUj0pHpS30pb6UtXau1dq7V2rtXaob7UD2oHtQPage1H2o+1HBulGibS3XB5DaW0ZtBQozaChtRm0FN2ozaW7UZtIoZ4G0ijNoKGl//EACURAAEDBAIDAAMBAQAAAAAAAAEAAhEgMEBQECEDEjEEQVEyIv/aAAgBAREBPwGyF+sMqLUlTxChQoUKFGI3eDeDeN3jck6NuSdG3YwotN1k4DahyEEahwaAjpG2QhWODQEdI20Nk2g7htBoPAR4HA5FI0raDQeAjQORUOBohqThtwxjHDbSUaxmHDFJoCPIoFBxDhjUnDGpOGMoo3jhiko8HQnDB1JwxqTht1Jw20GwM0/MNtB4FQuHgXz8w26k4bdScNlidCcPx0QpQ4/aK/V08m+cNlMYp4CNw4bdScNtU6M4baBxCCKCN08GgXDhtxzQLxw26k4bdScNuG7y/wAR8rk3yuTfJP3DOG3C8nk7Rf7IhDpB4XifPWEcNuC4wE7rjxleT7x4/wC4Rw24Pl/ygP2mtB6T2+jyF+P4g7/oryjpD7hOw24JEotjpeP9Ly/7K/H6YV5V42y6cI3opGE5sppjpP8Aqb01du6Ca2BZFl1ibUIYZAK9F6C2LLsMaAIoUDl2GNAOBxPA5dhjRDkIcuoHEURZGpdTPMURW3mF6r1XqvVeq9VC9V6qFChQf6oKgqCoKgqCu12u12u12u12u1JUlSVJUqVKlBOsxabqXWJtt1LrM2hqAjhjThBGiFF4acIJ1UKLg+6gJ1IPBuN+6gJ32qVNxv3UBHDH3UBG1//EAEAQAAECAgcFBQgBAwQCAwEBAAEAAgMREBIhMUFRcRMiMmFyIDBAUIEEIzNCUmKCkaGSscE0YHOiFIMkY9FD8f/aAAgBAAAGPwLwQnebfJ7lwhcIXCFwhcIXA39Lgb+l8Nv6Xw2/pfCavhtXwmr4YXAuD+Vwn9qyt+18y4nLjcviOVkUr4i+IviBcbVY5qscxXtVzf2uEftcC+EV8Fy+E/8AS4HfpXHywf7MuVrArYTV8ILhI9VY963YqFa43Hwl1N6vV/eD/aYOTvB2eCH+03+nko7NZxkOarCcudBaDMi//ZcXyUdguNwRjxPhtO42j/xIJl9bskGsEh2b++lWJ0CcGBwq59utEcGhVmOBHl8XyVunYfJBokWZIRBcRNPiABxdmjFMxK8L4v8ACmys4cmrerjVpW7Gb2M+7ET5gVF0HbaWW1cE6ve7Dy+Lp5K3TsOhuuKlWbVzTWC4CSJhNrNN3JEP4nGZTg2wG1fkaC6EKsT+6qOmWYtOCD2mbT3cWGLmUHUKLoPN4unkrdO5/FDU0tii59+qdAOoo2Ps7dpEzwW9Ht+1qAigRIZucLEHsMwVs2trvxQLqjScJLZx4Xq1B7TNpTmw4bubyFFmHGeQUqr/AOlHUKMSZCSnDgucMzYqsaC9iDmGYpm4yCtit9ETDuBoOyYXjPBe9a5hQcLiKZxHhqrNDyM6qkHitkaZF7VapbRv7Vhn5BF08lbp3P4puppJyIUP9Ko0yc/+ye985ykJBXu/pKc0Vq143U+GZ1SJ3Lal4LJ1pUQnL8inahRfSg6hW8LRMiguxaVEZhKdNtqa5glWCcfuQaPnNqhywEk5uOCh9IpIc02m/kg0XBMiD5r1vGZaZKTr8CiPpKESNaTaG5KqWBEA2NMiM1Px8XTyVunc/im6mmX1FQ+VqYPtTursTc4Ac1Jr67sm2qG9wkMAvyKdqFF0FB1Ci6URdE/p7EL1X5FSbxNtC3fVpUuF/wBJ7UNowxR6qHjN9MXqQ08fF08lbp3P4hDU0hjeFn906OcbAocT0USF6ikuOAQmbXGwZKqwanNQdSvyKOoUXQUHUKLoKIuiidPYheq/IqStsf8AUFVdZkVvcbbDRMqrA3W4ZlVvaYjnu+mdiggZlfkaD/yf5pidSHj4unkrdO4LjOQyTomzdbyRhRQW2zBIVsQIw4DHAHHFB0YVGZYlSAkEYbrig66VzsChXdUfkVMxWftOe4FrJSYD/dN2tlUyNDaoJY2yfNObiHJwbbVcJpzT8wsoaAeI2JzT8wsocPqsUvqHYhjJqIycoc+F7ZGieINie/BxsoigX1VDnRDZkF+Ron/9n+aYnV5BF08lbp4CRE1bBapshNBo94wFSFeWVZVC0VclWZXYeTlUlYqzHOhnkpRI0SIMiqzg4nVTFYeqlWJ5lTiPiE6qbXPB1Ui4u5mjddVOaLnR3EqcOMbbwQmuiTMhKSkyJMZOQMeJNoua1AASAp2kB9R16k4MnmuL3v1ItDWFp5pwaWVnY5LiaqsUDqC90wE8yiTVJPNNZFZaMQfHxdPJR/sK17QiYbpy8BF08lHcuaHlgbdJMc8ScRb4ckmQVWG+Z8fIpj2CVbBROrwEXTuLldRguJX9m7xc3OA1W+9jiPVB7OEree0alVGRGudkFvuAUtsFMGYU3OA1UhGZ+1ZRKsJ5TVqsIPZs7T4c5TQiPIk3KiHBad5zhPSn59pPxMSVzXSoh6p/V4CLor6bXUXeTyc0Ec0WtsabQoWifEDZRBbNMMPjnIL6nYuN5TogEnt/lVYdtbAqb99+LinENAeBYU2H8j7JJ72lweLb017eIGxB0bfiYzwVaF7uJgWrY+0aVjRsYNsT+ynFO0fiSt3cdm1GB7Tb91D2NcRCZl8y924sdgQozYzpuaUXtqFv9kxr37uSlBc1pzKkTN9e9Xw1Yxr3aogMY0qG93ERaqzzoFXkIbcAb1NtV/JVeF/0lVtk545IAQgBPEoiGK0rzgqwZDcqjxUcbuwWQW15XnBcDT6rZu3ImRU3qQa4qQtdkFMwHyVUWOyNNSG1wn8xTgZ35KQn+lC1KcSZCsrGPPoqtaRyNNWtN2QW9MaqbTMdy/yQd0OlQtFE6SoWtDxyULWgqF1p2ihD7qawueJra/O3d9VWNtUTphxfQp0I8TLkZiy5wVZjphOiD5govSm6Gh3/ACf5pf6Jj3XNYgYl18uVLYzLK391M8Vzk9o+qSawYCiIBZJyFGwZwi/mmtxxo2wvbejCiWuA/YURgwKaDxYmh4bZVdYhpRD6keqiF6pxdwNNg50MiAcV63rS0yRgQjLMofWbyqrhMIsnNk7e5f6eSDum9KhaJ/SVCodooWtMPrRULqphaFOy2gUXSn8gonStpDsfjzWLHhVXWRB/Ki9KGhod/wAn+aXaBQxnVUQ/bS05OUVuEkf+T/NMTWhzsgoU8XUxB9qh8zJP/wCSmJqhRC1KPVRC9VPN1ELUp78iU0H53Wr48RfGeqz4jyUBl3DtR5IO60CZysUQ/aVCnnQ48lC6qCVDd91DXZOpIFoZurYusLrdCgH2fKaYcP1KiRyN42+iDhcVVN+BUMY1pKL0r8TQ7r/zS/QJoF4aCEW/UKWMzKfFzsC/9n+aYnXQW5hMn8rqYh5Jn22r/wBn+aYnVTCGq/I0QtENTRC9VFA+5Qifq7z1Hlsmvq81MxXmd5Xu4xkbwQi3bVWZAKyN/ClEe13OSLGvY1h/amIrVKLVPMIshljQcVxsUowb1BNY65zkGOBiNFzheqsCC4E/M7BV4prPyonwvzVSMwmVz22rchvcdFt/aSC7BowUVoHyoQ48M1cHBWGscgj7RGbI3gIwobXGd5kmxDDdLGxTaU81TVJmChWeGulaCi527DwJxT4kjvFMYTJ4EpLbez4Gclk/Fqm50gq0i2CLiVKYAaLAg/nNBzDMFTcZBPiDF00HNM50bWFxYhBrrIjbxQPZoW843oucd48RQiH6pqYuoe/N00CKIRwknMxBUymtHytVXEOoht5It+4zRGGBQ+sXiieOAQnf3H5Dy2Yhuf0rdg/sprsx3JUI/f4HhH6VoXCFwijeYCuAUTc0HVfCZ+lNrANFvtB1XwmKbGS0pmW25qVd8tVuNkt+ZXAt2cspqTiZZBcP8rdc6WRoqvEwq0OI9uitivLs1MveSpw4rwpB0jmqzoryVOHGPOaqvE1WgxZKRis/SrPdXfme5/IeSjuYss1D6R3LmiZfKwBAhpsQwdkfPh1eSjuX+ih9I/2SOoeSjuX6BMbBEyGiZNwW5GZPKqtn7SwDmFOHInmix/s8iPuQiSlyW62ZyRY+A8OW0DZW4qTg/wBAmwxDIrG8qTGuiHGqveezPAzmtw25FEMaYhF9Ve89ne0ZqcN3pRs2mu/JqrPhPAzXu3z5Ubz2j1R2bw6V8lIvCkIre1YZq1wFG84DVcbVZ2LD5COryUdy/QKHzE6NWqFPJQzyTKIZ5IalPabbE0CwkoNbcE9pyTQ01STKxBjbgntOShSOMiojYfEQnRIjZYBSNoW7e19AisErZFGG0yaRvFSa2S2obvA2p0E2iUxypkmuDnSdgSnwW2TM55KcP4gzxUZxabrAUYkXeq55otc0SUg7dBkRRUh2xP7La+0Euc64FGJDFV7fpWyiGtZYVVFsQ4ZIRPaHEk/LgvdksfhJbGNfgfGDq8lHcv0Ch9Iob0qFooWihaUQvVN1KKhdVBULqphdVMp25BOrWOr20HUKKaIuif09hnUorqd0S0oc4XF6c44BNne91tLojWAWWqZtc8r4Lf6l8Fv9SMQNa22d6t8W3q8lbp3L9AoXTQ3pULRQ+lQ6IQ5JupRULqoOihdVBULqVa9xsAW9FdVF6kxsuaf/AMlB1Ci+lEXRROnsM6k/qoL33KpBaGr3zzEP8J/Wouiha0xdFC18e3q8lbp3E3GSfEqOkTZYmw37rm2Wqb3SCLmg1bghCc6ThdNNiME6t4RgRDVM7JqZcJIRHCTXcIRhEycDYnOcZWWJj/pKBaZgp7nHBQ3HA0PcclDccHKG4XAp4xrKZuRf901NAZuUUaUPTxm3sQxzUTqohZTT3YzoLvvTmnEIfUwoOaZg0bO8xN1W8TCg9txoLjcECzidcgIhrNPimdXkrdO8uXCKN5jTqFusaENowOkvhMU3QwSvgtXu2yU3treq+EFuTllNTfWPquE/tFtpacCVXgxHMK97ELxlcq3C7kqro5c3KSm+OeQkqzI5B0W8ZlSdGk3IBB7I0iOS3yCeVFl6rOewSuCJa9hBvCtsKqORqVXsN4Une7GMjapwbsig1zA0/VNTFj81uCu3JS/8aR5lbSKZxP7Ks2x6sh1m5L/TRJoGKKrPpzVUmRFxUOFWrF2XiofV5K3Twm5KfNVHQ2Dmi58pg4d/vPaPVVGPm7wUzfgBinR4vxHXDLxUPq8lbp4WEcZlO6u/eaorATBTPXwVaVvi4XV5K3Tud54CltApjuoWqPV37+kpmh8tha+St07hxh355J0Zw0RY4JrZ7pMiFYZIDbuLDcnQmzc4mdZ2C95WecyUHQojqhuVY2OF6m61xuCrufs4f2rcivB52psJ7ZPYbUeqms2HWbiUBEqtYpsk0YFyrhzHtx3VUcKr/wC9GygjaP5XBfIqkdtTI4KYpf0lN0NADjabgFZBPqVUiAwz9ympGJbyTiz5c1YHO0Cqum0/cFMGYokXieSlXtyU3OAC3HAqb3ABTax5GclVrSdkaLXAKYMwpVx4eFqfJW6d0XONgTT99EPqUR3OgH7lG1CJzMggxtwohuzCPUaXg5KG02idtDgcQoXUtiwyJvKD/mfbQ5uOC2L+E3cqYnSU3Qqzjdcne0xLXG6dBab8FsYnDhyTYgEjOScDwC0jOgRMQZJ7MBcpN43XIxnWvcbyi/5mp0OMKxlYSne0V5twajEimYbhRtRxNRhRLS1SFxE1VJlDblig6C23JAROLw0H18lbp3FY2k3BEMcGNxMrlNxL3ZuTf+SiH1J3VR+QXtOihdQpheqPVS7RM0NMLqUXVMHKmJL5XJp5UROkpvSU4YNElCHKmKBmmOzkop50HUKKdEw4STFF0RdgAobPVFxc4W4FfEif1KRe8jqVZk5pnSmc7fEQfXyVmncQ8qqBGJtROSYfvohDmndVA6gozVI3sKDhcRRCbyR6qX6FN0NMPqTsn2hQ3cqXBttd6AyoidJQ6Si7BwmoZ5UxCM1DZlJROqg6hRdVKJYM06HVdEh4OCENjCG4lyqi04lQzyThkew3pULTxEHQ+Ssnl3FV3ockQwsew4FSiSDcQMVWguEr5HBb7GehvQNQBouFZGcMOYcJqcjog1sIhgRJgzab0Hjdic1so7HVcHC1bprHIIRXjiwGCI2Dywqd1D4bZl5ssTX1HSF6mwzTrZulYEx8uEzW663A5IwfaBJuDsFMIwoW9FdcBgtpE+J/al4na4SCY43XKVzhcUfZ427O6guxwC28bUApkPGc1EZjOdDW4lyiNxvTa4nDZcFeR6LjW48FWcTblvcJvUwZig1fhtxzK0ChaeIg6HyVvjLlcrBJSImFYyS3WgdibmTPNfCCk1Se0Fbr3gaqsRWdm5SU3BxOqm2sDyKlP1VZ7nk6qu172kYr4T3hv/8AQIObENvJbsQFfS4Jj8wpmx2YXu/aCAveRnvGSDYUmoudFmSqtcOb4iFp5K3TyaqYL58041atU0zK3orf2i6GZjsRA2+ShyulSGttIFqYw3geOhdPkrPJoZxmonVTIpj2iVa9O6uzOE6U8MFwA+qk2qzmq7jXfmVVD2k0SLhPLxkLp8lb3NVzxWyU3TaOYU2ODtKZOeAcla6WoU2mY5U/Eb+1YZ02nuC93pzTXOvM+1D6lE6uxC1X5HuH1L1MXpr/AJi1EniQLrSLPFw+nyVvcP2fHKxGK9psunmpG0J1QyquQK2UM72JyQjPte66acw3EIMAN8iFXd6BExXe7bgFVqNllJO2ZkJ2aIRHWCUytlBJhw8TipVAdVtoBLRi3BYtcL5KoYry28WrZgyY292K+YHOsqkQ7SEbib1WhuvuKbtIleY/SZViMDcJhHaOadFsYMpi9xQrxnVlVdJ7DchEbiofUnQwK0RzrAviAHRVfaGTH1NVZhmFC1Q1KrPdIKcNkmfU7FVqjXjGS3b8R2YcGEwB5vkg0XAKtUG0cbE1pvx8XD6fJYc8T3U3GSiOkRMoaIk/M5AZU1MGBNP1W0CuwOlmmwh816iPh1Mt5XQj+06GWwt7mi5xFUjBQ+lA/UUE44stToJucJhQtFC0o21s5zlRCztX5KH1KJE9KHZi0ICe4+wqF6pvqpk7k5Dkg1sRsgviNRdDO6HKdO4LeaLiaz3XuUwJraxrXC4ZeMZ0+SwW3MYe4Lz6BVREqjGWCnxO+pyidSOiZPA9iJqoWlMPpTx93YhdKhaURZ/SoWqh9KhaUSc7eyC91BMvqcobnOm4r1Kh9Sd1USVn1KCnHkVDmuELhC4G/ryNnT5K17qxN/cQzgComc6Hvzcm6ImW465AfO28USbxuMghGwNhWwcbRdRMpseVx/hGG4ya/wDvTs8ZTULpQGRoLcX2Ixjc25DpULRPeMAmtdbMzKAAkAoQ1Q1Khap4ydQ9xwCY3M2qFoUW5gqG43A2+TDp8lZp3Ba4TBVeBFq8ipRHzGTVWYahQY6MKvIWqo5s25KtCiFpUj7V/CrFxe/6iiHCYVaC+ryKl7twzK/+Q8VfoapKtAdL7SqjoW0Gc1ZBbD5uKNtZzr3KH0psWHaHjeYV8GITlJV4/u24BBjBIBCLDtstC2MWE+y41VVDCIZvLkIlQvYMQpg+i20rLquSMKIapBsmoIa02mxHaw3CG68qddq2Hs7S5uJVZxnEOOSk20MF62ZO8CjFhCbTeMkIccylcVPaN/aqQrW/M7yP8fJW6eKaPtULTuuEKdHA39KxScJhfCZ+lZCaKN5jSpiE1WeR/j5KzTw5MKLI5SQG0xyUz/CdE2T5YWLZRWubK4yU+1IwXp4qVao7yqHzdkFVL5Hn5H+PkrNPES/+z/PdE5EKLp3Ya0yL05+Lig+GJuF6a2JxeRfiPJWadzIxGz1UyZKTYjSdaLTLVS2jf3TvOA1Vj2/vsX0f+z/PbLnGQCjRDi6yh2oUXQd3CHJN1NGzh7ol+0177+5iNHyeI/EeSs07jfbNS+koPjCc7mnBTgDdP8JsMb0WV6EePvvddPBVXMBCLJl0PLktpCxxTo0Teymi0ttwKbDLiWOMpFFxsAWxgbjc1aK5zcjGg3NvZgUw5voewOlCZl8y3ZtOYKjQ4z6xbKVIiPi1hPhT6r5W5Lee0jRO1CiTtc6UhmrXhnICaFYtiMPJVm+oyRJsC2fs7bMXlfFt0Wy9paOTgpiiYaXcgmTY5shimNLX+jUXScAMwpPbXI5KbGlrRYt+aaxodaVK1xyCq2tPNTcdFPZPkqrTvIthtM/qyUSu60lSB8OekeSs07lw+9SU0Ti4oDbt/pXxmf0oOfFbPpTYZ3pKywIudcFD602GPmvUSJjdQ4clCH3IhGYuscFWhumi/EiVI6k/qodqE9x+UUHUKKMJBCA3VytY+bjfVXC/+lMqMfWB+lVXgiqbJ0s6VC0oY4XuFq/IotOKFW8GxSxxOa2gMhiFv3NNUUB4FjhavyUTq8QdB5KzTuT/AMlDtE08+xWdacAqsOqwYnJTe4xHZuUPrTOlHqphddFdu7E/urZsdgVsonxMDnS3qUTqoPUFF9KHahRfRRdVC6e03pULSiFom6mhg++kxW8JVWJvDNVmOmm6p+viHaDyVmnc1vupI+U3IA8bb6Jm5Q3ESBFiBF5NqJyChH7kIgvZenwjjaKHuOAUIn6k+IPlQcLiix6Y0Xh9MPqUTqol9wUX0oOoUX0Rdg4TTW4sspIGFI0ULSiGPtTKIfVRNZhF8Kx2SGGYUPVP18Q7QeSs0Q7dUPqZr4p/SAdErDSiq8TVaDEUjsjzXvnzH0tuVV1mRyRa2q9ilEkG4tGKrwCL5gHBARA1gxkb1tPZnVXDBSiezmebVVfuMyxK4ZalRIcSoXFtklUcBEZhK8I7OC8uwRjRTOIf4pAad5psTg+C+q7Je7Y4fc4JrGQX1RjJEugvquFtirYIQ4bHkXk1Ua7H1XDJSnoVOpMYyuK3ptORUoLHPP8ACtM3G0miZMk57eG4JrJ7zbJK2xEttAEkGT3m4JznGVihvNwKmEdFsyd5tDmsztUOVwKew3zVvh3+nkrNPKeEdjebNcDf0uBqk4TXwm/pTEMDRTcwFfCatwSosZ6qW0fJbjZKREwqwbI8ip2nXw8XXyVmnmMnG3ILaGC6qpNsdkexNxkFxz0Qe24+Kja+Ss08M6XymR8USmOdbN01JbSvui4di1ENsF6haeKi9R8lbohp2y5xkApth2cygxwcHzuom4yC92xzhmpRA5mqmDMK17R6qbHTHJbzwFJkVpok01omATi4211fRJzxPJSL6uqmO4tPYtICsPcP0UPsOefRMcbyKPRQtOwdnfyT69apz8LF6j5KENO3DZ8t5QLbk1wG80pz3XBCvw5ZCgsK2LuB1kk1zLA7BOZdDvPNSDQmxGgCd6c1xnVTKrQCSiXMBNZTawAowIJtxKE7Yh4iix4mCjCc6cOcitrDjvliFZN7nCQBK94S4rbQXObK8TRhRLTgUXOMgEIUEmGzNSqz5lTguLWutATYhsJQ9n9mMpmVZWis7FzkXwdyI22zFbKJx4HOnYwhXin+F72ISeVgVaDEMx8rsVUduxMk+UIVZG2sm1G1jkrYP/ag1b0BFIusAUOTWylmt4AL0UJo3nVbgphjTymqkRtQ0b1b9LZtadaDsm7o+Yqb2TGYTX5jwMXqPkw07Ye3iapC1uRUhY7IpjcynlwnJcP8q4/1IODLQoeqcfuoHUomoUPVfkU9+QTGkyLnWlf6qJ/C/wBTE/hFz4zySooyap5NojdK/FNhj5jaokT0ok9ocOadVs+UKcMgFoxXxIf9K4oX6TYu0bYZ0Fw4jYE+IbZU1m2T3gi/GqZpuh7A6VC0o9E04utoMsQoZOSfyuX4p0sVs/mai04hMabwPAxeo+ShDTuJ3OzCkbxcVBiftPbmOxC1X5UDqUTVQvVfkVFA+lQifq7EbRROmiN0o9KhdKd1Ut6k8fb2YWU1E6qYeijeqGh7HooWlB0UPSj0UPpUTRP6UWHFYjIhVY/9SmPAxOo+ShDTtxWOucbKIYHEhBdf/lCdjgptPpRUYbuI5KG3kpc6GDmog5qHoiMQ5GdyIPoUPrF4ozcbAMynzvIkonTRF0TulCI29n9kYbjuvu1pisFw4TmUHnCwhBzTMGhovLjRu8TbQnwz811NRttUSTmm+rahoewdAoelDtFD0oOih9IURRNEGYkKq4TCrN4CnNPynwMXqPkrdENO2XFgJKse8eqr3uzdRJ7ZqbXPat6JEd+Sqs3VWdFeSpsjOCvtzVZ8Y/pVmRjPRVX35hEwY4GoQ20StLACQVWI2YVaDGLSpH2kf0Ku4l7/AKnINrsazJbRkRk1v2Hktm2o1mt6ERpZYt9sii6EahywVXceOZUormsbiGINbYAq3C/ML3T2ObkVLZwm85qu91d+dO2gGpEvUosNwdytClCYS7M3LaRDXiFOhQ2uJN5kmxNk+QvsUxP1pMVomCmw4k2uap3MzKe8AyKawmTgpudJOeLsE1s5OaLlsw6biVJxlWCgvYJ6KYK2Qte43Le4nWnwMTqPkrdF6eSzcZBfGapw3Vh311FwXCrRNcIXCFwNXw2qwLhUw0T8FE6j5K3RenkzIgsrXp3V5XE6j5K3TwJJsCiOwrWeFhalfkUSmggVSbvKX9R8lbohp2y51yNtSEMljrNVXOrsN01tWNa+H/ZAbNlq3pT5INLGmd0lN7A0aoV3tqT4QjVqynirQySLtlWbnNNZUABR2MMO5lCHFhgWysWygsrunJWvZWyktn7RClzag5toKrPdIKtDaGswLsVMVH8rlUtZE+kqZB9FY17k2JbvCwKq9j26hbQO3JXqpBa6IeVym6EZfbaoJaQRah1Fb72jVVm1doTeBRvRWhVmOmFxfpSEQTom50hzW7NwzAVWuAcjTaZUWOHi36+St07ipg1CrBBBtnWXwP8AumjYykfqT2RRZO5WcJuKm42tvW2iC35RlRD1R6qHDkmNGJUsFtqm+tsXzAMwKIZ+1MJuAKaDwTsGQUhdQyO2yd6meNthTpYgFMe60ys5BAzquGKHs0MzhssHMoNF+JosueJoalFr2gprcn0MiNEq16c0n3YN2akBJNiAWm9Sd8pQAaS3BNYMAmRMbkQTOqbFbP0TgTwlBz51Tc1TgA1cJYKux7g8C2RvTGGK8AmSvJ1XEWnknF0Z1Rp/fhna+SjRenbiHmmadgtcgbwD+0HNuNEPVfkaHaKHrT7x4C/+PDLvuNgTC99ZxCEsRL+UT9tM8iFEH2o9IUIfaFEcMGqEDnTC0KZ60f8As/zRD6lP7qG9Sf1UWpobaJ3p/VRE6kBlSZahNfmEZcRsCDRh4Z2vkrdO4Jwctn8zKXAfLeti02DjP+FXhjebgMls3nddRCGq/I0O0UOh8TEBb5JHE5AASAUMfamsxq2IA2TspDcXFPinGwJ2gUPpCiNF5aoROdMIfamUN/5KIQ5oamhnUj1KpBMm8sUHR3F78jgmDmndVDuvsCJi1OgnUL7Yf9/Du18lbp3FVyrw97RSiezPnyUmQzDH1P8A/wAWz9mgxCcXkJzYkJ4rG+SmU9zITw0mzdQhx2vBFxkmPh21cE6FGDm22WKUHeOcrAntnN5FgTHyMmlTY6afDzCIjCqCJEqdcSW2c2TCJBNbWE2Xr/yfZ7HTuzUom5ExBUy8Ku4FkEXTvKDRY0KI4XTsUMg4W0GLDG4bbMELd8XhTNyL5SbLd0WzLgHNKc83AJj/ALp0Qm5WqWINENuN6c3GaYH2SdbRDZlanD7qC77+wWm4qy9puzQnxG00VQ0kZoPbaCqki44yVZiqSLjjJV2XeAOvkrdPBXUXK6neaDqt1gCkbVMQmT0otaCrGgUb7Z6r4LP0pshgHlTWqSdm2xW1ndRQdEbOSshNW/WPKa4T+1Va98tUXOLyepThue06qQMuarPe8uU4cR4U3TDswqu3cQixwvxRMOM4A8kWtiyneV8b+EGueHAditg0TNNUMJyKax16cQ0ua44J1ewuNycQ0uBN4Rr2Fxu8AfJW6edVnGQCMQ3vM/DnTyZunnLhDMnIbd26MJ+IOnkzdPOLfFO08mbp5NarLexaFZ5M7TyZunhbXAKbXTHLwG8aJ50lZFSd5K/Q+TN08ITtHtPIpzH3tKPV30/0q17ipvQU6JCi3JBpFiqnyR+h8mbp3gdVrTKlsSp/+I/1K/0//ZS2TlXZ7O8t1Vvs0VWw3hbNocDLFRdV+R76eV1FyInJSImFuFbtp5IE3BGdquXNc/I36HyZuneQmi8uUyAYuJpdqmetEnNtzWzdkbVF1Q1PekqQNoos7PKixTdYuR8jfp5M3TvIbzczsHVMphRBeJzUbVNLjIWr3cN7xmveezxG81Jrt7I0zJkFKHWiH7QpxIb2jOS928HsAeqrmmyiQxVl1Ni5hMPkb9PJm6d+UVC07EbqXvDOFDubzoLXCYKc0G1pvTHm/FGI/wD/ANQa50m5ZBBrBIKRVaHug2iSt4230gclM3KywK9ZhVgueCkpNU5q9VgrM/I39J8mbp37tKIWnYjdSbzJpjdSZqVs8Gf3T3w4VfCc1/pv+6/03/ZNH/jyIOaJeyTSKWlBudBocEzRE49gtzCaPI39J8mbp2rLSpv9mfLML4T18N64HqTIMRx5KZYW60u0og9PYi9RULSmN1KGohP1FHq7hvYdogeRXrSEFPyOJ0nyZuncBzbA+hsPO9BrBIdh5+00QtOxE6ioWlMU/coWiiD7lEZiD3Bl6dh5oOvYrd/vOmphhdopbEg81Y1oQPKiu70W8yTVPvYvSfJhoj24fVQ92Q7Lm/M+wUbL5m0kpzsymcqXuzKh8rFt23G9Bx4Teg5toNJa3gYLTz7JIoknDEhSVuNE1yUz6eB2nzNNA0o3bwVVqS5lBuXexek+TN0R7bOqiL6djcfV9FWie0OJXxj+lWZ7QQdF7yIHDSgt2zWsyAXxW/pGpFaQcChWv5JzW1GtKvYjKoWnCalEF94VaAfxKkIbi3JW+yPmpECC39lVW9qYsVoo2lazFWXKxs1vW8lM/ruA5toPdRKB4GL0+TN0R7bOqiLr42xcIKuP7XB+1lorO4qN43fwoWndPTde8c84JjnWk9mL0+TN0R7bOqiLqvdyrc1J1VowIVsVygk7z3CwC8qb4mzGTP8A9U2e0RK3MotL3TF4K2cSx/8AdbOGK8TLLVb0eryYFWh+0PPIrfNbkVNthxCJFqt9nkMyVZVGiiOjPnVN5XuGgN+pymPabdFViOt5oNiCq5VnFbjRDH3KbXtdykpRGA5qbb8RTN7pL3MKTPqcuJn6XvoU25tW663KjeerJlOAbKSmTIKW1Cm10wpQmEnMoucZlQ2mI0EBfEaptM1vutyXuoLiM1N8F4GYXFV1UwhQ9N17Ei8U2mS41YZ0TcZBVW8A/lQtOzG6fJm6I9tnVRE6qH/bbQYzrflbypZEGNhUxeg42vfvE0zHzBMA+ayhzTbMIhVJnZDeIzpETFpo28Y1qtjaWxB816Y4Z0SFsQ3BTiEkC9SFgokVNljTwrZxOMfypETT2C4XJ88Qq0e37cAtpCG7iFDDcTan2YUQt0cK4QiYYkTcgLy4prRgFai0cJtC2J4cKXpuoosiOboqr3k5JmooL3J0SJwtuarkYkA1XDAYqNM2pxdHcaGSi2SyXxR+lvmZpi6eTN0R7bOqiJ1URumiFpS3qQGZQFMLQqHS/UqI7nTF0ohDlS3qTOoJzzc0J0R15Qdi63sOOLbUHNsITXjEJ2gTZ4W0zawA8lE6TRD6RQWOuVcurSuph6JlL0zUUw3YzULqohtT4eN9McC42hO0ohdPZi6eTN0R7cPWiJ1URumiF00jqUPqHYhaFM0NL9Sj1UxumiGPtpHUofUER9RlQwch2HDlQ9v0lO0CiHl2IvTRD6ezMoEcErDmm0u1UPqFMPVQtaA9vyqs2whVYu65TFD9KIenZi6eTDTuIQ1oia0RemiH00s6lC6uxD0Q0NLtV+RpjdNDdKW9ShdSafuoaeXZdqop5p/oovp2IulDOkUTKlDFdEQmAKcZ5ecsFClkU3Q0nUKH1CmHqoWtEii+DaMlarDNuRVZvqFE0oh9PZi6eTBHtw25CiK31oi6UQ+kUwxzULq7DR9qGhoKKGppiaUN0phj7lC6k5mMrKIfIS7ER+QoaDebSoii+nYfQzSgQRqU1gxQa0SFELRN0NPqFD6hTDCh69idz81VcE0/KbComlEPp7MXTyYdsue6QTon6oBdwmwqYtC2XzONDMwJGljB8otTHZFTFLyLhYoZN06HuOVDoeINNTFxoY4ZUsZkJqG7I0GNDFhvCMJx3XXdgQRqUI0QbguGdEUjNRRy7B1FEM/bR6BW/TS1v0hMpYOaYedMIKHrRHhHOYpLvmbQ/pohadmJ5MO1uvLNFN8eIV8V6+K5fGd+kQz2l4CmY7iea+KVOH7Q4eik51Y5rdjVByC+MV8b+FJscFuRFBG2a1vIL4w/S+MP0qu2Y4fcFOJHB5SXxW/pVmRgCve1fRe6q+qrRIrSVxtVVrmFuS3gAVKEGalFznAkr5UGva1wHNWqtDNRyqxoVcfU1cL/AOlSgwjq5bT2h20dQRCgPnmV8JyriC45hSLHtPMUljsVa2YzC2UUWYFblZxyAQcRKKLkHFsiMCgQ8aKTN92QW24onzBNfi0oOrouiOqNwBQq8DbqGguk8C0KbnAIuHDgmvyKDmmae8YFVmmhwxdYEIjuBv8AKiNF8qAye82ioLc6Ynkw0814QrKN5oK+E1WCVG8wFTDGq1s1wBfDavhtVrAvhNXwgt2Y0TnSmXZqs3cP2qyMq0RxiHmpASFFYiTswpw4xCk72glSFL/Jh27HLjXGuNcS4lxLiV6v7OCwWCuC4QuELhXCuFcK4VwrgXAuBcC4FwlcJXCuErhK4SrisVisab6L1er1xLiV6vV9F/hXajyYeZXUXK5XK5XK5XdrFXriXEuNcZXGuNca41xriXEuJXq+k6jyZunc1J+6nLsWCZUjAlzmqr5VZYd9uEeqqvhNXwmrdhNAxJW9KfJbkvVVYkH+V8L+VJkCZ1W+0DTyw6jxlvdN7hxF5sCmEx/LsE8wj09+x2INEMcraa30mhrsXW+W/kPJm9wZ2sh/3TmZFOheo7B1Cf09/wDkKG6UvohD7e/LzahDeyU7pd9Z346vIbOy3tuegDxG0psUaFMfkbVOk6hRNKBDhAxHHJT2bf2qkVjmHFAtMwpxHSCsdPRCKLG81uw3u0VWJDiM1VZjpjsfkghTEoh6BWqqH1jyW/NuoU2PBpkYjaJVxPWi0yUwZhWuAU2maMNyr1puwn3s/mwCnzPft6vJm9tsP5Wbxoe3lYpIA3tsp9Qomie2HOaMWI0jKdDXD5giDgVanNF14U38DTuih5xbaExoudf2B1Iar4rP6V8SH/Sr4adXDJYyoZomMFjDetoRvP8A7ItIsK3Ta0oFOzzXNBx+HlmtpBbqAiItYCe6iysSLxNCC2yRtKNQb+aIIcGStmtoyK+WIUKbp2qQdJVXRXEG5Ohi1xK3jNF8Fzg4YTQhxTNpxoqjeeg6K81jlghbXhnNbSC+X2p8NxkfqVry+YxQquAbot50wpXuyVZ5q8gt15BWz9obI5hTFqq7J0+afMVZBbjf2qxhtc3kqp3X5dhmvkze0XG4LabUsLsl/qT+l/qP+ik4zrWzVU3Pp/JRdB2Gy4QL0eqj8QofO2iJ0lQ+w3qTNR2HUN0W8J0Wp5GJTdKHaprRgKR0ou+p1MXRQ6IRUR3OVBCYPuROSaXfM6ieRTm4EKwIdKYi7HBV32ytNNYcTVsXHdNyY/Ga5C+iRRlgUKYevkze0yAPmv7FfFimE14xoHUouiL33IMgtAmpxohiH+FClkUeqg6BQemiL0lN0PYh9Sbr2Haihuim86BVYED9r3zp8hcnjCshQOvsDpTdTTF0TdDRCTuqlnWiMwgHfK6hrcynRToKPxTFDZhJRDzpI5IEYFM1UQ0nqQpha+TM07JcbgnxHZWdgtNxRbkU6CdRRDH3KIOShtwlNRImM5UMGQTuqh6hdNEXpTdD2ITfVA80DSBm6iGftCiE4GQTfqNpocfuQRTOrsDpTKYiGhohaFetBTOpTRDWViPmVV1V2Srx3WYNCkLBQdAoaZE9CntpdPJADEqGOafrSOvsQvJmadixVZsDckHtq/tb7JUyhwXEonZOQc2E8EL3kF4chKC8Nbcq+xcRipgFr25pzIkN1V2S3QXHRbW9+LU6HEhvAPJVqrzyATnmE+ZOSEKJDeKtxkprZQ2PM7zJNibN1l9im2j5icgFXMJ4GFi+G/8ASEOM1wIxkpi5bzpIBoNRv8q5CDEMpXEp0RtsNxvTbd4C0Ihlrzci114TX1rJJziZEiwIOyKrNM6LbE4i0XLZ/M007OdrimONguU0APlCdDxBoc45JjuaeWZKo5pI5L5lxH9KbHA0O0VXFpTmOQrXKYtoLRxOsW2eNFDan60E8kw/d2IXkzNPIrlcrlwhSlYp7Ns1YFvtBU2wwFMsBXw2/pTawDSjeE18JqmIYBUqJubM818MKqC6Wq4FNswdVmt97pZK937QaYjnDBqqhr4Lr5KyL/Cm0hymLHBMiD5gpPHqq0GNLVb7/wBKq5s1Jj6zcnK4BbSJvuW6FWcWqYqkG8K0SKLITL8VOqgIjJOphaeTN88fW+Vu6rqTLK1QwfAw9PJofngiMse3+VvtLSuJShsL3La+0frwUPTyZv8AtJmnkzf9pN6fJh/s+ykaf74Onk1n+0nd/Z4f1/2lE172zt//xAArEAACAQIEBgIDAQEBAQAAAAAAAREhMRBBUWEgcYGRobEw8EDB8dHhUGD/2gAIAQAAAT8hJJwnUknckncqTS514VqSPpANgWA/yqZohaLBQrIpoQtERoIWgtIWgifJ2P8AiD+WQP1lL9A/+Xg5M/zEt+0LasQf4n8of/EEwNr3Y35u4n/1jyimrR95/fNM4LdolegSmniZFOw8vtj1ToNqIf8Aqh6j1Iqy4amnX1Ir9wd12BK4ag+8HdKfIdMydycUJiLMjrg+fBbLDoZlrHbBl2M6k6Ekkk74JJJJJ3JOgkkT3KHmW+wmxYP8zoRh0wjDphMiEEEEC14II+NuLkdydHxzh0L5ELRDbdexdT0HdHob96DduSGXXUXmLmh9RdgJgncl2kTnMkZ3wlk4yIfIdRcjO4m2SZzYNVono7C1eA0i7sLeOZ3Nl9zWT7mw+5kwzVTnmPR8m0+5teRdb4yvy4IIIIxjDpjmPlwJbC+eNRrYUzH4euqcJJoTwTJI9cYwncnNMtmMTUQiK7kVmUPcjc5GZ1M8W0J6lCVsU1E+RNcRX50EEEEEEYQQRwCCgj52Q5uR+EprRt5OpInuSTyJJw7GWM7FeKS6pJyYLrnOU/03YasnwKolqKrPBWcDUmvNhaTJaEYLt2ZZYzGRK/8AAgjgjCPjZHBl+B63tYyTiJkkzlh1wtnwZ4Th1J+CScJJEZlXJLcWIpIlkT3TZfN4LDLZGTRCYqODoSTlMUXRKefxtwpZOjW6XZIo4+ZCGblzX5UVxX4Xhr2uLrwN4dcNp4OuDOnDGHT4LngODquhPlJA3nev3hIhfKj1SLys4phj03cT01jC4fqsh5EnRuPZyeIJZkCfihgoanZ/BR1qaVbKCUxOq34Ufm/W3Xw9RYbYzXCTMgjcg3DRBBGEEEY9CwiNzxHBSTK4KBfv17YfaLpNN1B4CoBOwvCCsNNJIcNCel6lhQInHqBDpGU8YKrMniVEKKnfP/xxEf4fhva+STK/B1xjNYQQQQNEEUIwgjlh0x8AWfBY5RcaRTdAGza/3wU4RjioOSUtrHktkpEhaYTu0jVRDupRNZx5GpNRmzTWohEhKYglyoi5FhoOo+4iomdXWCk0kLLbOuAF7nOubiKr81jB4jNs9kkj3m4DlQOEpcFaUaVx0FD5QmeTJnIDWMVBuzah5iI1yD84SlcdJE3S42iWSXMVclsJZQmz/wDA+luvj3knj7Fx4dS514H8F5sLPgs8v7PqtcUsFfD4Oc+AgtUP7CO6SVfM+zfob22pXEEdyBu9IMrrhYSWmh7G7F9ZqeHisiCT0kek4NYlCafgvLPuYtCESboTAWslqQQLv6Q6dqhyEs1ccxxcktuSqJ/8MdiVVF/IoFJEIQKlBrmRG3MJ7D+xqFB2GuHX0ibOTBfdnaVUPY7FBNITP8/7W64+nF1J4afFI+XFY8MaPgsrafSa4q1iV+ygtXgMbFl+5aLznssYWiN1pNBPXTIkI1U+Vm82LnKaqf0xp9lqJW2+8PAe0fX34SWBQErf8BrqVdIyJnN9FxV0VKck6FxGf9YZUSryQkhZYZUUJ2fiL4/vb4dONDwsbnQfDODeEkk8xtkk7jexJ14fHDVxfC8utA0P9sUtSdPnmFk/r5sZDVIb+xZsu/8AJ4wgVHcXzHCmohGhOjUWgXMYSFvhJvpZ4eI9o+jvwWuwshKmpTzJomkj2RdbKqHfdFU5bJrvghjEkqszPEUBKLOQ/wBFBpJUEuWNVFPC3Hjfn/S3Q+LlhOGeC54yTuTuyaEk7HUkkknUknhgjHwxdxr72CWO2mdFKiFLTqBHITTyCqymGhxq5aDKCPo0FlZFEkSa6mj1IOOWkgiwzmU6MoVOoVQIqK1uxNdM4K2Uic1TG1UNGmwel3HcaeS5COEX6w2kpbRNIjfIhgCVPmwXKVZIJczupe+BbVzJ7inMq0RIpT7eaYPo6UEOB/iYKJuEEVSWucUwS0ncbrjUq5asTpvKco1n+f8AQ3HxySTOmEk7k4yThJOCSScHj1OmCwiuCxyxlxgx8ewu3CpgJuj9Y4NzCRgljdcxXJzWCZ1bRQmrvJENLO81nmZ5UqsOa3ZIT5wMfNCMIHKzR7tbLOYaikymsxMg4EC5AkeG920h/wBODDG02MoUTmyZjqMzWihCS1Aklh0IIZDgms9hni+g36G5tqpmr7ciUjZyj+Zw78Ef0R0Ru1mEJ1HAhtVYYdMoYrPz6fousLnXiknGSeKdzrheh0+JPHwxazg//eors9vgvQK0OPwPGe0MkkoNkjZO5JJLxnGSYOvDfLHrxoQkLCi7B8TMFU0ddyH4bSPx1lkVbbH5FOUcMqYlflKiJTFBKiYopfS/A8F7RJJJOEkPRmk3Y3fYnyXcUUz3GYTsJdfYZzZvvuZMM2H3Er/rHpx9Trg+hycD1RZxPhSQndAo5sZSZPFkyoK8SZ9okK1zVifed0xbC1EyKJ3QV8YTSSyae5Ypa9zBCSyS3Z4NHwNpVbSFcE+vFGlDcQCyQmmcFVQiDtLGb6uuvoUxWJ/IW1CivXDzfouPqn4EAnJ7RN5RzRK7ifmu4gIspFYBSJjwSOq5kdSrUfMbgfx704OnDBb5ot4nw8kJJEHpCLQ8x7F10aSuRMSqFrQXzcsJBCdGZSsJiKxlTqJIE6xn+EtMyF4JDOS5ZicIWND6EesB0FALKwU2JDGlJrQTzJjQ5hcnR4RrT3Der/RE7fc06IoI8h0MeioOKe3QTTUpoUUWsoeS+hM6kA0QjWwulV6OeYdDlMooVjXhCJ7DJDoNndyNZu2xHeYIghVBVHKljm1V0FIPuMWpXYSy30Khw51DH9LVcHZECltrCZhUU1BtK+iSEGpNVWk3IrbsKYtpKW0kOxPmYTqK5WzETGg5sONlIolV3iCGTvQDPy40TJeETFRgtE0R2Eg15ZCuivUR+1YW6k5l6r1RrE02MaWOYMqLpeghsZmn8LR0fZIncUCkW8Sxc5RNFLHgUGNl9cJ2HfCEQRvw9fi84tFDwfF4r2aT6Yso+0CzMl/GG8D+idOFJVqhaAWVasKerLiq2dwsxR2c/wDCH1ORPfFMIVf+yHSTQqydhqPEQ1naMYc5Qmo0FST1i/cywpAeCFUrpvBYgDK6ndyJMsWPDvStAhcUKG5CrOncWXSLDVyV7JVHlg7tckRzaC8qyXi7wQtMUuQprzII0XUiTDbKXXbITo0TfAZtru0waKGb0XNLzoNT3DkYb2RuFGgj0mjQq47h0G4GVr0hLOzO8NSDB+3oknLUTTUp/B5HtxJ5STW5ZBJzEmVzY6ieEqMI8HXHpxzjpsy0Jdg+Mfqbn1mg9aM/1h5A+htjcSPGKMSyg+0iSa/4iMWcfeMRS2v9DhBlsv8AoToHtn2SGSvlkmqKefNFhXGJ9poMXZEfaRHKPeKW7kmoBGKqS+NUehUboLIk1lv3ip3mwx1anqIknnDyMQkxlKG2FlP8DZX/AKwvQIT6jD7zYQxz/ZD35zUESihzP6Y3uu7khFuiPgaPoV4OuKwksTsdSRPcktbChLEI8FeBnXh8osF2D4lOSdlCkVq8hDx29QhvZwbYn9ExeCZMlIjLIvzhtnvydcEMEDuzLThS8AlqtvFRFdW+kUs5BMNAoSh0hS9NkCSln9MaG7ixXAaqtQYhlsUeBkx7HIW0d9db4ookz9kMAqZYVZ68MG+Qh2CxHPceCmbs4yKtUr3IMQ0hdMhcjyAuW/kZjUN2GlgG3Qwm0ko/jv8AHLh6cEiZ08lQxDRJYKKZJTUnFcCLBbL8HwzMPoUk1XUyBm9KA0xJAfzvNinEUCjZKQfUob8dHJCaUiq2YsgizblDzUpmBLaap7v/AAdJbCu36E6VA4HpRTIt0bGgSQQlEVWRP94K8jZV7EuzSNXNXJE9nU+WPLS2QfITbQoIhNrIWjHNtyly2NySb3bzHPftnhIaKNSrYq9dBxZDBoO9R5gViUFBV9loNQIVCmQpvVp3IR9zT2FCsV66Y6rK1ZEtDoZbCA1zCrGvcvfIujUXG9FFasgxcQSsgwaFLytxT3Ys94PUmxMfQj1ck8Clo/eJFMTYlJLaEFs3yHtJpqcGUFxSPTFU9yWOw9zU7jDyUrBLRdU7YzsOIHMe2apiyG9KggoJBFL01mZUor+Ik8HPGCB4DjYqiSEUFvEzrjljei3iPh5GfAWyye8Vh/D4wpro9/HCulwtJqHBE5riyD6H8ArTU5YPJYchIc1lrXCQH2SN1wSpOw8Uom/yIsMaG6OSjJlJ+go4RK9CwdiaG87lMfrCFfMZBvu4p28k4NyoTkO4rhqFmduRJeM2x1UN9CXDYDo+82MC2bETR1Hg5blOw6lEk7ByXw28Lrx9Pi3eLWJA5iATaFhrAnG6Hgr8HxKRNVj7jT4ZVHBBksS02I3l2U7/AAv/ANXxP7+ea8HTg68MbDR5EBoJS6Fz4J5CicI9bYPi8P0PqNP/AImn6V//AAI2Gg2E2KOeEvwfEn0MhATamrbsre4qfY2RRw8joNwGqqVGLLfUyM/NtVSOr5kgUC2UolSWSgPpR9HuUTMSCzrnIouthfTlaAQVY3VU0VoKLqNVNNSGOQ1dlDWE8FiCTpy6fQioN3dsEM80HNywYQj0krMN3AodU1wNpJbS6lq4aMpnOGJpqU0yp85QJyF3hNJLJ4t3Gl1FbL68Erb83w/p8fXj6cU7ce/D0IOhBCbv4g+o0FLJVk9cESpKgO2biitr/YsUM37wTHSlssBKLSNxozQKREUIN9IuZK11Q2othIERzLdyhRPQEkNpUeHeIX5HtCZkWTRC6SRqLCvQCNVJKvC0I4E5DsMkKFdDrhpxBT2bruKavJNh1J6Wkxs/0cUO5LCl0XNNSXpa84eGNsSqOTHRqcF0yzNBe3xiiXITYq2qKEjlzMIor+wZW6+pQi5DBGLmHZKqiDPf8pYeH9P5p4Y34oOhHBBHBBe7F3wfcaCQv7RhsrfeF+d9nlPeH0uR9xqeAWG3DTZFSMLs+AaoV5azfQlSyUNK46sVWSw02T2hZdp+/B9LYVrJSwdaOCDJTYNEltJIXnJeRVhOZImRkkkLIaTUOGiBUs2EvRlM+CnGHJK4KGspM2f5fifT41X5Y+XpweEGr8H3Gg0jZhG79tlUX3J93cZOHJNecEc4Z9xqeAX2G4wAylmxrCunTHNDxEqRcJckRNasz6mo+njJaP8AV8PGez6O/B9rYu5+lg2Jw8lae1UwtyEnot/oWkL+xmoTGt9RjKgYo7On5awu9vp8XQXz5/B14MzqdDxAlZFxUfnKRNc4GsTmdEhcjs1mxEKCkgjGduXQjaOkIvBEgJfqITXMTyqQy8LUjBkEbuhMGpddkiZLYjpYNMQkSTCHaiZE0kppofmkkwm3kNlQ5yetiLojV2GJiSVZvv7xXBRcSl3aErOw2CpOcLySJs9x4tdXf0PQn6WDxE3W7iWbx6HOBU1eXkTDociQNMK0yE3wVCNg/bKCEeiOUlGDgYqMSpVuVhEliHS35KGofdGTxL5L8eUYdMeouHxmJ/A0ndJlCIdj+BjGjqWmyNpAkSbdo59yeCMW6nJOhOM27H9hlMg1GaIi7M4P70U2MiuR0NZKIMbAQfOCMW3XhRi2tlFjuxLaxYWEIC1CwE6qUCBJIwLhRFhsFhXxWiRCTLBOhrAkKkqtVmVG5L2ejN4iEEHk3UCu63FixmzqdkTijXVzGFLZqp/wpjeQogFcoUKi6Ir2vExtTWvkKIuiFgVOYuer/BMuAEcDCez8lH2dvjn4p2xzxvp8LPCFwvwsy5ahPXXUm5QjRINHz5FuoRlXaCZJOE/H0wrAfMGINrsHB/jo+pt8XTjknGvz9DxBd+IqhsC6+dXTSBU8b0Kz+DljdH5SPMeh8a4csJJJJ3+Hrw9OCxrchR8BnD7STIF7uBEgmtnwSldri8j6PJ/riZlxs+k0PoNMF/5SH7/0PjTwnCSSUchLGmHXgg6/EzxRdxzxKSTTJqS1DJ2u7ESHKpsxKGufTQVlSNYGUu0qei8kASlEdTOZ8GQJpua6MoAqBdzYQO7HDZ0Uhvqd2gh1EMllDo90ed/WMU+sWJPrMwv2KOW7Cr6EWg5iIh8utMD8rny7jLJb5aiF1bNlhSmJp4NH3mhV9KmDbQ5S30JFMPYQpwXR+yEVKB/AehJHwOLoQKnFQOWCEJmaeEFzeqQmm9RnM+TMsXRnMcTEuQnT8EMcXlFd6sRXMzNUeYmnVP8AFR9Zp8EwSSsEvXGCPh3+Lrh4r4FHRpCSShJIRwQPSmpl5wRSfVBGtaLBVQWUeJnT/Qm7l+iyEWQmMEoYqJn3W2KU67+hKpcUdcEhUYhmlTpJDk5U7LQQ5S9LLBkEoKecWmOzN3DwuvpGClWToL+xsg3odu7GIuWrGYuvcnEs2hFImaFkMbHAtQyNkLulElGQwTdNhbb6S1EyjdakCyJXZGV8zM00E5oKagu3kXUU0TkiloRCxauxPF2rm6KsaRWxL1Qw1wtqiLh7r5nl+Kikb/pxSteNHx9Dph0+Fnii/jjxZTXFsJYCPTedPgq+y+H2Nj722NUuX1DETQ8Tzf0PO/rHy/oq+xQY7ysLn27R7UFLLJfWKNJrvslDNHhRQ/hhhs44CCki14IsgvQxrdnF6T6xEtASPdFDpxb+xEp3gMgKsdBbiGXTJxsYScW5kw3VhRVn3NySbvxyHpTl+mEkk/P0w64dPlZ4Evw58Nwmp7IPJcwli6JJIdmj84NzD+h6H1TFSNCu1PYZ1BYNcLBGwZj9z+saH/aCn7lBmap9PmOEJaTNc8MqsREyZHci3JGDyvpBngiJRILFlB43u2okCal8H2NiTUF4D0Nr1kSsO6kSjYlPuaYnlJXWY3QzRXNcC/SCRSy/jrEEfGvw52xjBm3s2L+OuVNVQHmYoNFd5u/YvDEGQM8SVfqgYjLoEhcFFlCZyqcTqLhYValsbAViDQvlx5PDEFP2lH/CVS3IQ5GWZnCpgrImuvbQ0+o8DJyyeEID0pYYNjcmR4wROmQN5JwqNhAEwrmcwxo5z/sEhImuZWAjCM8xYCkqKfqScHyRXFmNYSaW6kfNVBLFaNLu0kp2Y/rXnMWFNdQepEzUpFORUhUMCklQs9DKdgmgiPJ5jiUgSr/InnqI2nzNw9wdhYEVZm44WaHs2QBbEnZGTi0/jr5sL8bI5iQnYu/DhpwwtEQtEQlZIkctOxt+w2lPIhdC3EJFjkYnjlC4IC94xmImlpbuRJAd0UjSX/QrzyJFuHUlsGbcVY9mKeC/Mc5NDTLQxFp6ATBJJqIL6oi/JtikOsMomQ75Sg9PAh3C1sXIqbggnTGrfjosd/v5Vh0/B6cHXAOf/wAPqNwpghL8hDBrQXnFCSJIspEMEcW4JlZ0iOhUKQixqsNRmrB+ajynsnYfw9MU/n6fA0ub+z/4xSOh14L/AOqYtGBNPYVWrJEhIZq3DI56bq4znJBbwtUsmWuaA2aUJ4Qe9z8tD9x7/Anj7Y14e/C+QqRSpBd8EDbqPwLpdY1EeNux54cVHXuV6iIwdZsG0lLaGpw+yEMoTZ4u0VzZKdU1jR1TXAyhbNQ6RtjPvxX0/aLj7pwP3voT4Bmj/GYmZGksKwrnrAzOXJ33HWNhzF+Sj7+/4M/DlbjgWLzyC+/G6PVgYViyFw8rTLoZMyy5FCLqRtTOp+i4sq6aqERV0RccaVA1VHbUY4tcbIXISocqCmbXJNGGLJ1dkNHpQWakVbipsRqer3oOqbok0PoMLOVRyfV+hdOS0IbyBpEZvlA/0WVKLBKKznaEG2xRwa3cVbJjA2oRkajREocdViIQgMqklDJlI8C2+qDmdAeV3sOY2JTRCq22YhcXcWm4X72Y3LEjj5TPBDzFcyGTZ2kuXQ8eZUzC6WQtKwIxoDmHb6c35SPq7v8AL6cSx6iIzK+IjBTmNYZBaGTTskGlV/cLS2SMIUzCkYqf7DLKSzwuGZWQLPZzyIqnkeD55Er+0FMiSG5FGrLkXu/2L1IYlkc12Igqx/Y1ofeA/e+z6G+EyLUVJwpAvaTPobFRKqhfY2KXue8rSQb5MahQTG6T7DpmukNRcQiFUk/2GkzyFGa0E4JM8Xpqlm1EPmF1DGw+iEJysO3/AH+Q+B9/dkfNHD14Op1+SNKU0Xv4JFM5ajJOr8MJChE9QljiVtGf+SvZH3wU0fpDphY+jbexp0364Th5D2V8x7whSZy1z/A1DT9z72+E1z0Esra2shCFo41slsKax3ehKm8ZCalmNUMn7E3Xoxql1/YIXRXfo/kH8X54L8NCHpfdX+P1xXxQOgYi6BqxHGwrMmTRqXYmKti1FmMaWaoKZUy/6GlcKj9mCjDQO4kybRLuUlJ071g5MSSFejM49xRqxeKgRN1Gw9Ld7FZk5YJUv9HMSJRjmHlM2X2V/XccuVexra6pm+ostQJJF+6sFed9E32EDHFUcxadXkux6QRCD/BRWLoXE/hXBFfnWDwP7x68UfFBl83XHwGAuJRa6ROHLJlFOWYiJG5fMSVGOjUpNhzIzNQJ6Hpy6idBHeTWGjbXpoJ6Mo00J6eyOTErFqip2xGj5syNQJapOuR0ZDUq1zuKh5kfCFLJ6p2bGo/dS9/DnlHRKjJdJzZaQiiZeE1CQgCyoMy2GUkTshIpgsZEpb5K9hnXhRmTUkog4Lj1Im2rKQhoKYeppFzHVQLdH1HpZCvoQsNUBDXMYjE1SchjuoQGELDV7FG4ROmfQY0W5RZfjL47CzXL8EEfJ1/A8F+PoeDpyLfuVfVf4IWiwqTU5DTNMlKtQcO8Da5YElYS6EKeg8GJblhshUUJHncQ1qfIhJCJLl/4Vpa5fjaIII/H8Ybn4zilkOrHQSqKwr7jZJBBsq2FVhL2IE0kHR8VSq7SokZGkQ7z8KxThNJkXSzWBQ1Kf4j+J42Hq8XTBcUEcXT8DwBdMfjuhDuSTxuQlLyFrbffxyHhErQiOqHsQGUCaofdKb2wX59vxl04oIwjc6/DPBJOE1Mxo+C2ldpdRWk1ICmEmrZtmRYJotNxCEovVPDyZoKK1wGqjTuKuYqIPiTmumVgRRTZRh9prwoT4Fi3WDnL2FhIZAjmAraH2+HMCJPn+Pb8qdOLphJOE7nUnckkmlySByPsTsTsSydBZc8J8CBoohPQclFWHsyi1psE/wBIZ9CYmOCUOci3GsDqLsBoaGxJOsH4EgssQsnmQucHD11zYgZRQVUyS4Syw1FIS2S5bdFWtXoQXVazY2l3HOhtoO2isPzg4ovmhtMX0GoaFVC71eGmHQfBo1CEh4K03LIUV5oSifdakYGgi7sQZ+sEsYlonR0Ku01TUDmkjOSFqOx7Gq9OClgns41ENiadsH8gBUrurbuNY2prIjfiBHMkF/ZWKZciLkWwClqCfgrkyTzIcKGYiopombGtS6QqawmIH5BMlQPChOpPjL2/Gt+JC+KRUqV1wac5kMiokJEbGghguIIyIPAfDLQrsvIkkgqIQxsqjqtDUyBKD97/AKRIZRSBNNQRYQwiRohvSVRjd68j2rXyImVXRwlnNkdAfYtQuh9McntCGDZmuYlrYNi/Zmp+lh9FqJS0euCmyLE9SdQSkp/AkFWISWws5PWMRjVbDD0hQZYIanH0xfs1wTQkAkS1BCChIsWC/dC6qe4E6rnKEJFSc7ZwhGzNmZFJTJ+xE2NfSEksvxWW8TunAvikT4III5EbYI6cfgBKqvwLP2XwVtKu39FdZIXrjVoyiMxrboT9iNSmZ6Vj6u5OzT/ZGGap/SwdGeOV43opzHJyDuPeik+jfH7ew30aYgSrYPqNRa4ZLygRUenBDx+nvjNhv9ix9iuC9Y/YY7iWm6rpZi5JauojgQpD9/bBfi2n2Wn4cFhMTJ4l0+DxAsO/wJHpOfnGBjuPsMYUEJ+8GJiSVY1axh1LogdGYlu7jGlzSMSW/AFNS+54KoZNJiK0gZlJsMPlEoXEodno9TKW3keDUd3oqV9UwaNwmoTg+u1LyZEOEJQZ39YITjCbuwuKVtPE4SaBvYsdX2NwmysLHSqY2XYIUfBY9JaTDhVDP9RKn3TFfi/tNBnXj6/KmSTkSTgsFx+MLONImjyKTQAkSLUVg8KJryiIdNWmjLZ5r/C2WkQ3PUquZWAwB+sNxDKrzceTKGdSCBzR5GElRyU2uzEqU5iaY4qz4uWZToiUJIu4LqgDNVsWUlm+wQ3DlCFEp1rSxSgUiWY0vvQmupbr84Ef6SZbLa5lrPBgNNbkIzx1AZCUZudCtzWOxB7cwQVazSDmoMQnNsfFIKK7wRQk3Y7DUEUqXKROmScxocIj1I6JHOwW5qZ5irYLYkZE1zLLcRDSUrlhAu9b2UAcgdUk0lUuhd8F+Lafut8S+GCCORGGWMzhQTJacPi8YZKZfiP8TM8AqWQ8KaiOqJf8xC5SmtEK4a6NYSlhuglTdz+UZaNJGpoJapCayXG6eWGhKld5sYUmZNDdMcoE6Udpz+OvPIeviXwwRsRsQQQNYRgjqSSTgRJ4wS3L/wAlDwWOZAVeyJZr811PYbSNHARF7xl/kEvGRTAvyDS78O414OmEEETlghkEcXgSxcvxWiP7L8RDwWOxCkZI2nSObKjoWMeQV68FJRPoJwTEhSVvLgKHVNfipDH5tBBBGMHRDSb0ONUC6bJnZ2oPsNy5FR+8I795i0nZyF5EKf2aU7oWVmZpnnIEdCqSwzhtzGsi54PaTLDtuxbUZs3LEx0Tvg16wV7ETSUtLXsTTImtmRg+GhJXNihqU0+uPn0YrYfXF8LzvoW4tfXA3DLuHGyi2KrLfKeFHjRkTqrmgUYmhuH+I+i1xX/hNSJZsnGplHuG9KSoVkF2qZTUs8MkzXmqoCSShJJIQZe3MmbNVuFUVd2ZWuF0XVtJEcAuRNncQ11GomdJPYeD0WRMmVVREaM4I2CUXfkiPFy28iyImfkRtsmh6ieblsdfNQ3IG+qwuyOaemw8ONTDluKAIS2MyG6XjUp31VGyFCqim6gYiJCpc6Du2IRzINk6VAnAeSqicQtaNBE05iUt91SDA83BBpDFqvyFVsdADu0Im6Mh1wldOFkJ5ZZrZjNERinQzt7ZDN7KKLcL/pgJxK3JG0i2Y2ioYW9G5MZJLaSGTIbIyHyJP9VI4TVb8BH1Wv4T/CQ0pyL+RxrRbyNjniCrAynpd/oQMiKKwbvv/wBP6whbMlVZ5z0KWtweH/Zfh5L0LDVKZM9jEIB/N/wL/jf4L/SnCL4uiTD53+DK6Wc9ke2Z3IhKjVbX74cm8ChKnYViaHblZ2HqPV/p/bDeX1CeD2n2ZUGywm9WXYObkvMLPy6yCpn0jgahsPE4XuUjTmv0WIjRAx5lWo3GlNdBIzizFZFST5FZEmOgl6VALSsPwX2WvCsHHz9PnuoyPQ45iGnDhlZL7lSRTVZDGiVZa5hCYyGuB+4E82HifTLvb6Gob/oJV9rDrwkJeISXhSleMnsZ50Wro5PqPYyatHxVzLJBaaz/AHHwa3UHVD6jFCXOQz+jLhFVyKeJEeMEhG3DbyiwvYMZJfp+xZPE8qpinaUls/YhkTT/AAX32vD1xfw9MVj0OvB0+CuotdHocbGoQfNhuIdizB1M6CcI8nqiFac5VWD03yVZNOYl6BmMsqU+CNzPwI1kGK2TKQkTqZJFOpKHURk4vrFYkv7RAmZAQ2boOqR0lt3/AGGMmXBdQa/uJQltfYTWVxOJiIpY0D7AlRqXJZiIlUmnhHqoCXt4PYkkZoTolN0LBAooKNWb9D5uFT0ZsXiRFdCyejxODTFpPoNDsH7F7X2PLmB4Tdqj+egxpukuX4LQf24ULGPk6HU68N8K8KGJ0Yvqycd8EEiihTp/0UWevS8IwjVEbMWUINHQUU6YQ4NnOEPqouoUDVFdATgXZUUIDm6lixZWRZiOo8hZsi95hqQiE2gutKsJKXXcZIPkty0IYM5urzFKHZQ6ohWi3VCEkis1B9u8k3WhQxmJOUS9ytIV1Kmt6MKvqIAWQI9b0i/NDBrURQSkuZX4HvYbRuvCWWCZDooeSjYgSau0kGZuWTCDjNUzkh1N9kxBMB7AeCpGLiaymFYsEhVXEkrTdF+Q+YRSmRDecQ8yLpdxEslSgYdYRsyk5A6PId0kivmP2RTol0ISfLMYVkRCXNcj8EPP1q/A+F/j3PEF65Pz5wnB4Q2IzHcd0bVEUlcKv8MzlpPIbLpdj+MVZh2LYdAv+KZnjMzxDX+YoUFKKg1lpPIgfaor+CrH3GuK4I/A6YTwdONHiC+2T/xYTukJNVRBKkXfhXzRwPi6/G8EfQa4r8Hp+D4gWIl5fgNLSLsatW0u3C/mZUfSaC3ahSyykp4Hih3+NixX46vhW36T/wCL4wmUcZ7cIP8AT9bfUbhfuyKrHPECI1M6zzCI1EXZ+jFDV7oZE6DVMVZIQX7SKPvTH8MNiSMjIGza4vUfZEZkJ8tRmYFS5PkRIXyaToOyS0KfY/KQzPNRkCQlMcFl6k3r3PQNHYdEiaoF7ohTBbJ9FIcco9lYZhClk3sgUVJSqOd9JHcxJbolQT4xghQ+aiPmwKqoyVW0j3RECy3ElwV8k+jkvzphC9rMJm4zYHY6T3hBZ3qHUXE5DD2Yp4X+Hnh5n3wo5fnZnjBWr6cdCN/tGX6AEWcvYIQjzTEUjlRKaZnPe/UNyyX/AGM2J0P+4NH02PIfrBE+zcY8NQqgiQiooTIkKzOepVxiFnghEq6u4hrqnQc+gBIqQklEiSpNqIa5MhfqNSF0ATLkgSrDKlkMd21e6wspZ9Z4KkT2OZ9dqTETOKkDmQvI0moaFx66RLMZirmmbfYhSTZEAybG4YWTQT2KcQKNiNiIiJEswbyoW2EkOnNA7K3ns11qTLcS27VkCdWglDULwglNiBLmEltyxsUoWUdxFGRfiVc37xRlwbnXj6YdDsInh6fH44jSvGRzFnGTatPBAts9GS4l0gOqnAbvh05rA8gO5aDw7H81H9hpzitmFCVbJDpoBWgOPBDGSFVDDl5wYtBJMu5wjckYha/2kTKz9hXFTVThfa2FJtTYulbX9cHcEupAxoqySfQ2wgeohlKhLFis0pNav/oO/wBgngvH+L5H38HQa4Hwd/hn4ux4w/TjbC5nUTKeR0xkCqgcnZaDLLxqCgpO7PByg3DK3AepvJq7v+hjl0WXMjDhVbqI7UCSRJMt+5Ht3ekr1hb8x4Ky8+KihoX/AFFf3qH2WgxWqIEs0JRfoeEsizezU6+xGdKv7DHvM/oSMG+5sJW3/oemVOJuEkirJQRRJfyeYwrq/bIjGNFq8iZMW/7H2M3/ADB/i1u3Yrlh0xVrj5HUyt8FsV8/jD9MHwsXSehkjWbV7CKW+0GlqVc6DuaUdeY3NyV/JXnGykbTg0lYpVQa9txYTe7YKIlTNiAmZewFZEEhDW9wUIYDWGHS5j3FMRfaD9uicnkCt9B8VSJGxkbcZOZC4iKzjsRVVzFOjeCEciKhWFUbnLwCgTaVbHg7E2WLyiS1N5GJiSbk4DEUlfUOzgKN5DsFVEi5J5EpJToxEFqUbEJtS5wQn3PoEJ3Q/lCKF0MsFNHUwhyrfrgnXpeeBRlCCj0xQQn7jgyKJw0Y5lVA/wAI6BIbmtBuZB0CQnzsjzXExC+OMOh1xXyeMOTLB8TxnGScGyrTsKFRIrTDsbfsJFkl0wo/IUjieRIQwJN0Kk0Gx5iEN55IsF0I5Rrm5LGRhR0aRBe6P0Eb0rKUlgkhVNM+xf6t1LsPRusiX2LTyG5vdsStzvGSFg0P7OR0dnetBhFqaBfgGqU9xlVqqqs6yXeIJox8POFLGQsmkWrhIigyi0s8iRw2Wo/ILdBDWNbJ+wE0HsrkNhOJskEGKhs+dnUZv5OuPXj68SOpJ1x6YdzwGJi4n+esHzEMXwzhmMaWYFaBHYMuKuM/OF7mMWPb5r8L4uomdeHxGJi4X+dGCwZkKYq1PwSTjJHLORlOmm5JRKEPBcT+bzhf4F+E+DphlwJ8PjDNiv8AwevwK/DJPBAlocD/ABVcpduHe3w5ix68PQ649MYwgjYgjHPFXPCfni42iSxQEDrokhqzNYngaCpfBP5queT9Y9RTi+CCCKcFMZnP442I4vGYFxP5a9zhkGW8+G3FLm6lEKmyk2ZipOYNLE7XFBoZkxFVd0lXTwn52RxR8n1WnEuFaRxRisLmJx6i4o4GeM/EkojLLPYYA3EcsStq3y9CcnULJIEQh12HI2Q0JkFIh2Jaz0KZY9bYNVk5XJUtMvin8nM+604C5YLgWPQZ04ZJaiE4E+C50+DxhZxvgQ9agiRSQc+YqghbCM2faNxtOqXQo6kREM9NDG1DJaoq9g6BIt/yLTT5h7yUCFTaY0ndByTaFewVTRuSUAWPXqlRCPIaZIhqQ3QXiz4F+X91phInub4kRh0wjfg54dSxGC5kkiEx8niC18bfAqWmhXQQmBkW2WGRVzvsSOd7DjNIeEtCXRyg2paj5P0vmND13RE4pmDSq6skQJJUpzN40GTknhCk7DpSTkSkyFJTXyC4S/C8764ExEidCS5lwRhGEYPYPZwExPAthPDOOx4AYXDJ14FpSqNc8bp5o932MREqy5Gip33QW0Q2bb3M3TxQvIx6ZuUDfoxDxb10asa1Ibi74MMVs7DNeCBiyDCVqXSojas1GPUIayHw5AoqWKIyk1mN6mGTpsrvs4/AYvwVc8764kJ7iYmhaSuGOBrQg6hh1WHsGiNzrwJwWE4+AMwsFg/h0mR5TEj7L4orvCNsa2ndUSSokKjIRYaQTaQyUEcw/Ciss20GbmVhYFhViWBCM18imIlgqH+8awtIQ22UDHrgHIq7kWbeg2NDyl/SpJoIYstLMZmd9RPqY6JrIqJkKiS+YyX4RXPvNMY4JOonyE9iYyMr4zwPlgSZ4Mga2IIII4E9+B9TxBmLsFg/w+Q4TQ88yTyFUY6QLH2KjYrMyy2TQjM23YanhJQJqYDpFZrnilegM+oBqEiuKseUkyx5MxV7VQao8ICKqgHNsVfg68CwzwdRC/AVz7zT4UxOchMTyMrYxsQOMSxCdMYOhBGHTDrweALGK+LGBpoKTqQhNGv3EfZR/LRy84OU3/8AGLQ3eLnwBI0ukqfqvgirmRPJ7HM1X7i6hXE7HQbJxmdqiOQimgsONYUJzNEPIHVBS7wWCyCZYFsJ3+FE4ZjwighfOrn1WnxMJ1EJ5EiY+eD4EE9ydxMJhPjg64dWeMMwr8FlLNCSVVRvg1a2k1W2YlKvRcCmT/gWCm0XghpE/wBBpf8AdcEc4pRR+mMdqzCZS46cEY8xrUm4mnRiuZY8Skg2wnU+Y07QijJOQqIklb6UXdVfxzhNBKwblgYaRimuD/SkeWu0eDhUyTUahKY7p2E0kHR/IrjQ77R8aOonUkk5YdR8Ek0JFVg5hZJJTvwdMOmHji4IkQ9MUr/VMFt1kj4Hmagi/eE3NS22Hghy1RSbsDEAmrk8JSUtlYbr8ioDV3kJaHY2vUnA7HKMgSEquMD/AHEy7cC4xRHMymOZwwoQSTQlcQ3kk5DKiuVWnuICU0lZ8skjkqnyXuRolmNitElPJCE9RrktRfk1oFLsiXyK5T9qnxpxingq5idDIisDxkkkngPKinBHUlPCCuR4DAXPBcD7uzEZ8B4dCjJXqNzztLCCIg80GyXQ14T9j+mpATM4hTgtFaw3OmXcwf0Bii3wLS0aiJRGNT0zsEEopnIC4LzkYp0978KwamC6sajJmNxIiyBcKUWKnOgpW8tBTJSgURI9uBtJS8hqeQ+CFMxXBPF7EcU1meF+BmU1c+MbED45xkTExOaFdCMIIwgjhk6nMIqiGdJKeMCHwv3dngtfZxXOvwS+BIlEEbI6YxwUd0aCFleSwpbV6hSw2k0QVULCvAsGtys3sFyr8HrwZEItZvHstNU+RiFEHtNCeHzWKIwGuJcCeBPmXXKED54wdCCCCBogjFMKB4wsoHQ78P8AZ2w0mX0OlHnaEPXLCSixtnHonzgKpp2gqvVh+2RREpU2GJIyLKiwUt1uV+TIiy77FWM8NzCMUN01JCQ9AQRLQVzJaheCgtyRn1WzKBdMvvyQgh7LR0pGSUYrM6ic0ZTS0pVshzkx1PsLe3ge4A8kMkDRcuiCCEo1zSHQhwHqydaFFLeuMsGuhZ3LQ9RTzI40aslTukP20xg0CKDe78xBgMqRPt3xJDTZlATsVZAbRuRHUPIUKtsgTSSJrnivU9lXKY0V2h/Bt74rZQnM2HYRStNmS1E0Na6NWOlWrX7CxwHPhhcjoxlrbhXFIkxaI2IIwgjCCCCCCCNsPEYCvBFwzqP9umH3NhscUVwZphszJmNici1YT3TGksyturV9sYXJKbrmNQdzdhi80jFYkzJwXzQ6pkUVEkSIKl6wnmPpuZ2WrGJzoKP0cw2l2J7ogpY/pGXLmefAtpSLKCRnSmnSwuMdQydthE2orhmRTdEiqnYNRNGM3JqG9QfoMW4zl2E2GFC/0ZFSWGQ337BHYxFGZJhwlRcaSgGkQifQSihVHllOwdmHpeyL61Sw4nm4YM5NN0T3XuwyMBnnUjKIlEY5D61c2CuNs1Vi9MJNpQbVJqpNQsmC0KXYUcR9cFNxobaD+NOEDIIwggawQRtxM8ARgXj4CBqf1TD7u2CSic4jmiRfNCYtTRDZcQlCZKLY0vCu1n6GI0H9hSh1arxiucsK1CvN9RnISWaIJ9zMczUNjwf8CnlX/ngRGZcfE2JWGcUxEuIteGLUNShvf2geqHUSPsUwTTV4JNG0LYqpVr9nuehKXg2Rp7NJ/YbwJUa4itGzB61DbFExqTiM2gig1EHk/WBew+F0Jirhu/g0YJEEEEDEcDPAFoSGIswqO44z+hn2dsPMYUqWjBHgiZP0kmVgsOLP2KDEfRakD4u/6x8idTYxPQ8PACppj+xFDdH9sKc29ROKnKVWQ1Da0Jtejyw1PJsvsbwipS3RjqU0snonCcHJCSGLzhCLqPFfotosN2Xs+o1KvA3c+ipRbEIS3ryF5jsqixQa2TE0SJlJmEeR9DvkeP4fob4o64k6wQx7SrYgXydsYwjbggaGSXPEFwuGItwgYGRaT9rCLni5a7PQsGhWv6Fatg8XlO/3gLoTsPLd/st4howEEvb6JMxqW39izyoxpWVfbBSDNfXA7y63DFkGq8DTyvQSvt+2KHHZT9ShBCYhLckFbWaGtEnFih+lFBEmiSDWfwwyNFEn+hmMaTyeMKJAoY3S1NJJSkajIawHTX9iHkbx9Tx3BmeA9nXi3FvgewzyMJ+CTr8F8ew8fALRfIxDxQgzX5wobqwOt1DyMykf8C2Dqqz+hr2geC5jKNl+wxTHhmxWzfg1zBDzhdbBIk+8ZHhB6uLnMQ04agW1NZFdOBLR3ToOSvdMaecvWCgnDmOF5GeN9EjWSpQuTu8C+yMLDcfaaFwhogV59JGJjdc2J33odxk7NDcCOjSRD28nluhKW7DOQ1Tfh4LgVx45D3hPAmIapG6JwNAa+G51JwnCcHy4mXdDxCh6YXfB4KSLGmmHZossGlUQR3Jm4ho1Ad8sIKaorcaKTLY3v9wS1dliQslPFpE+iNKhoPqXG5WaOeWEhlVxsyBFYFDMh6l1IIqJTOrmJ4ySiTNCVLYl5EoJeUXsZiWopO1L/wCKGM7js3+EC7Cn/gqpyMZ0weN/3YJQ5p6wQZuaxDGtKBiK6D3UrwJWBUCK25liKL7Hagq6HRDZQ9iCBhYjwRhV0UlSWZPUJcG7XgR1enviVxEi5GUxhGA2wRhOCXZo7m8D5kGY18Lwqqp4nAUMTJboi/YtpTu0fwEfz0P/AIoZlKiIRUdrtD+WSyIjy2UDuGN5ncc0tjd3GAUVx9dRTc6i5Lrn95x0qklUqDujrWFgjoDQiUM+5axOY6coo6D/AOGxTuObGOiLGm4bV/Rd7c5Hqd49miZijjEqw9bYSoJZibMqK807TH5M3trsJSjXNbDaoqysipO6FBzSzR8hQXRAMAMjoTfQGNMy0FdEciwkYUQV2tU5aDnzli6N/oZ1RTFZINyNudDTYQZXEC6ra01HCxu85n+wQTyF8oBjIJDmSMwoHIroYhmj3L1cvQQkt1mhIHNeWCEHc5hTdVA02hojasxtgmCZeGCVPS98XXCdeAZlBy1NkYjFKzY3MSMo7DQsYIxpk8JJJKzQyjPHYaHg/ijB4djrh0fHfIkbCMJc4ThXCNBEWQ25sjmhDL6EcjoNFSjukOofYFZkumCj8wQ0M12RHC+gb1HM8+Q9hnyKkroP4o2/4Ev+Y6RroJn+A2XGuJzQ1K3ECjL1WgowzsLn+ihGEjRYTEawdQLBZs5VIKvdvG9D3iuG4hCFVVE98MhrMebAjCwzUVuKVsYHxpS6D4u8HiG3mcsXgy5aiTOfWj7kfUj6kbbsbLsbcjS7Eal2OZE6kPTBKWQWiGjLBmsH9g2nc1U7my7mw7n2s+tn0M+pm8NwbjAplLUXfoI/8D+AfwjZ7DY7DLjsEvXsbz7E1PQyZwezJcpRsNt3Nv3NqbAWe0LQGqXcnUidS7kpWa7lNfJZc6/MOBOCxXLBYKcVi6jSNEj2cCcZjlSRbuxOaydTOwzphmdRmmCgSk8Q2cXTF4LjeMGeQsNjphMDGzPBHM7jYiNCKWIKaIhaIa0IjQuw1oXY2EbCNhG2h6SNhGyjaGwjZG0HoRNupsjZG0NslyFpvuNeppyb3cJcn7nM7jNfcWpw6HOb4pUbAbQ2/Y2JsDYkaBWKl5TTxlxrninhOxbhQRwPWYl5nUfMnBO5IlLF0E8xbDS7ZwbqiI4I6WWTnrwOjvYJH8CVmoKMsrhBkzj0w6DOuOWH+NFYbk5uf2GPUUuHAq122CuK7EQa0dj5CaKlNt4BUmO6fhnniuXE+XAsJYQ4xrFg0E14U8N3DpcSMjuTWTkxEq2HIcESMxsQQQRvhDQJ1Uxw8iGg1DFzkfIYYaa2WKsLzpgl4RE1MqrCZirq58CXAqiSvuHj0J4HAngoxj/hOC+KrlzMYiklUsRC3PDuJ/AqEYvCMOuPXFDUiQlh14FhInhPHd8uZ4TsIkbqTzHzI0IEIIIGhoaE4KqTYxlJhibDWDanhDllg6MbwyqhCJCiNw5j/wAC7u3/AGGdcPptSZ2n7DdR4RwMggy4P4BehQrZhB6/sQkZoOuPT40tUZbiaGaY6E4LhMSSIwELJZOHGNlsHpUTxXDeaTIPi64ySTuZCZO+Em9BMkbOY54RUjYa2KhqC+wkSKCMguZcdRc2a7IrxbjOJwEaYqLfI3IHu7kpb7UGSNOwEi0dHXg14n2MlVsdYChQoNCDdv5GhF0krCEjKppiaBvFyeUOQkDFVTqkeyTM2EMANY2OQr5gkI2xXwezIpR9oKJLKDsNrJf0mbIEvQLwartdxlVLXKRM0GrpYKSlNPqVNKLVietqJkYfcynFNmIZcPcrh1guQtSjs0StRaiIGJ1jBRovEoNSoTFtdswY1BjiZONeC4tA/jTxkTJJkTJ2wep04V8iZSkxKjFRSFhCIIPAKLRXwvNikD+5yRAxsS+4NNmysTQd/Xti9SJau0mhNknlmRKVRF3ExS2oaDmikIn0Fjw9AklPUGbKIgIoph8DtpgnChGwVtKdWg1ovv6kLuc2/wBITN6MgNjkzkYscr6JsNCW1ehYZsdAos0RYa21NrmIUZqSYpWSWZXNgxpw1Cko5haWzEs+zJaY9+aDJj6HK5Ww0kJKqV+ZMrRZUkq9XcJKtxjJU+qIBSlpyK0pirssx1rusiEWYNDLEiJrpjoNLploRFTMNCEsZZm5EF0MiqPLIWSq2KlySQiVSOJqEXT0IK6r2USE5FF64qRKdKe5Gz9ibkKIQtJrkSURqNSwSsJKprSvg1h+/sINEUIOnDOE8SYnjY6Dw3HE6jUUVZgVwan+jlHLXCKpHBhKDVRZhrVCSbvS4IabdVTRTsHTYxBHOyOuQ1hQrZhR8hKhRKWxcO7CFG84PJGZeDrp5YVfcoJO236HgjwB9VqN0JJjU0envCHT+imJ5kZQkhNTMoE201ruUq2HSJKErv7KBCQidUTzFq7BefM8EnRF4KzsT6HcXI1ESbwQdWV1FULG0+zatI8SYZ7iUUGJLpFJrqepVUdsKsp19intbU3HRj81kMd6CGKzbZZn6yyymijCR9VuKdxRWQ0VooxYzRb7kmxurWNo50eDRGEchpyRwp8U4W4egyCB3JRWMGuQ0Vm4rRslvGGtIFYZWCXVWnkIiCeE6kEqqT0Erc005QjLitc8KV6oeIHdQg8qdUlnIMZhOgqRRIPIFMFT5ITsRfaoLO2DFgel9UMzp9j5DO42V/TCrk/QvVTsXZUM3a3MpF2UCEZJSryarImGE5r9jSdToZ1fTEivf2DOpPOF1FglOo+bcSpuMxmtWz2JazEBEV0H0K1KErcoo1ITCsWFGQ8H9kIPMEaqCGLQayzZDNUsE21V+CFclDwpMX/cWMa9LcXx6HTA1SxGCCMU8JJOuEkrQb4WhogYkU5CmZDEEIUW/eGWWwSE3GYwiWPUK+DGBKZQgl51YhLzf/obkGo/QSmndfZWe91EsL9G5mVnzfJ5wRdNoXg8XghjcRCeKanNhDDJB4B3HhsKDEpbP0D2qM5CFdCglG1Iizf2JdooZsNLNvvGhpVW0973i8cj94CY9Jhd58GFf03LVNIWNqCFIfMSHw3ZighCwEJaRZESNTrQva9kpCcBJX0Y64XTzWDl6oPV/pHa+CIbr9h42hJzwT1JJF0NyK3IWhEDL3jhnggjgnQkkeMkkklskt3Y09BI6oyuNjIaY5dTkSh0NnSFmxyM0KH3smUKSyxJn7NqEM49sbkKUxxNTKJH1RKzuIuXE2MlMI+DWZxJh9Cp6cX+hlFzdBbE6UTM7kYOtSqgqbiuGGmiTEFIlYaKdVMQVy1qbEgH2jCRTSWYZBQKJOiP7ktkcpIYtLBWlB+SQpcbjsSYvRBZNYhWBXxoJhygqRP2ITgFYRQTUWMYKarNSkMQl0e4uZesuodWkQa1qRScsMyh2JTYaSrh8yVmQ9qaD5j7zVZ0MxsioxNLsrHWrl5NCs+ZTDF0nQYcNHMd2tFQaw06o1QQJVCGBXV9GO9dDeTWpMhI8EvQlrkrM71Y6inC1WsKg0++C9HmI6EnUnIT3JwVf4RsPYaOCOeIxBD+FbCbzxkcLM6ydyd3iFmLWKnUUUVSZk7DOhTQkT0gpmkOCSmiwncpphGgaQouksI0IoLYhrQWtA3padiLL2KVvYbaeASYlWiD04CCEIUxzVD6RchjJtYP4YZSPYQIIXzI/hiY5CISKTIaoNs59IzMrzHJwJjnls+rIfa5OPil8xBtiOCgJsJUjljAzLiox3+gS8j2Jtt01yAu5q2ZEpvIuKkW1sgj+TKlhLHXZFhtULriWryJshoipOgKkam58DEyH/cjZ5DBIlNxyeKrmmOw3Y8idycsJ3LBPFG2I1GRHMjkaigNbED68DJM1BqMhsWRA95JXQh7CRGLKxmQJVI3GTdsIlbhePXiXxXwyKY04p4+vwLYWYREphJJMVcqTasIxrEjciHgXBPwXo7+Kd8JExPcVToOJGqkYQVzwjoahI5iYXKanMKbuJMlGDgubyj+HKbMPQckdbmVLHqKVhb0UWZZOChsVJw6iH8sjxudOCONG3F1wa4Wvqi2TRmXyBI1qqEFtS0Kncm0quaxQoooDLi5fK+7vg+R04epInQZoJm9BvDrg7Uwkknckl6iZEwsxQTyw5lCNiOQxoaexRMISjXGJFSxW51JkmVHg8Z4MsFh1x64zth14Fwv5l8F8haSElkkchOJCFwTwsYi1x14bnQRfc14TsPkbn2x0wjGCMIgnc0CdaCOiWJ6nXHkx8icCKEwRiuWDsLsR8DF81OLr8C+Nxx9cESxPBfGh5VgZ1Ixa0w6iqXyFY5iSdkdcO49MeuDqaxIanIjgnqT1EZwY6wWBsRURJYTGF4wh40wgfB1HwZYZHTDpxuOHL5I4OhOKwXxrCpGVWIahW0zieDqdCCNhECuTUknMknmNoydidNrB4PBCRCGecjbgRLwdrlCJey0XRedDuO1hSHTQvIySfwdoxkmcH+csJyJxz+B6yx1wSIrZwbYwKpbDWhDw2wdNDPExZCoNt3fCmgXgQ1JDQgYgiCBIRsShuwUJDEQNFroVcI+dYRnjsdfn6/iK4igSkSyTr8Z+RGsiCKDUFSDq8Iw74ZzIi5ruWgZzipDGMSkWK0EdCDbCCJIIIwpkXLtQ/cOiKmSkikrdxpM+BGWD+PpjPPgf5aweDw6ic0HkRK3wSrhPG9yw1CvUVOhYfTDI6lPrIZmSZ2PdkF0fAtmB//aAAwDAAABEQIRAAAQF53KCWbyaqSaESyiyCSS++0QU0jHQqR9nodmQUyX8GfC3DD3wkkyGvhwEAc8xBEZD3T1lgA4sO6MuOOiCMwqi0kAy6McwDS2so08Q02RJ0kf8+qdpJJ89RUsEHbfz/aCmfKquEKQ0w88csIMMMwAcaOA4YESyC++EaoVYMqV6+5cFptI8N8QzWajTgk4SGWBxuEcwk4I88gW88+oyW+6+ieqq6aWWq9JwSe9+j7Io51994k0qI55q6OL/wBizPMEKAsENDKHn/OgljPooLoyvhoumjgnDWJnvfALjPOfYZYebE2HakNEJeovsNLHMpMujnHFn76r7oEtrnr6ilhuqputPVV9veFKZLObIPJWYJAaWl/OVkEnoKOBEktqvtpoEjIo8qrn/v8AabZJaK4ZLCk0UPTyymyjSARyQT0cJOI8P2owLawzzBIIIKLb7777bb7774r7774ZbqJJYdgnGtTzznIo7ijBDylul0Ul8ENhpChRy5vY7YoDZ7zo777bLsTzH7YDQhIK55ZE2ODWCnA74PmyGggy3iylmAD9Cnzy1YWB4mPp76DQas7/AK+4n6y2y0Gjz24U8dFUhpoAsY3+P5ltLVDQdQksjQJ08lqvNYZc6C6Ov8C8kiySYm6CS0O9TKrgiNbSF99h8tyiOOGUgwVRkexx4+p7G9662+5h++++qq+OCWe6WWyOGcMOC1thGmnAxho9kBePBATOAJPPfmN5mg780tkMI04K4w29+K+++eqGaCSCeumyGCqwURvoABxQVNi2V5hdpu3Dj9ViyYB884mLyzqcBeHKKIm+2qsWyqAyiqGCCO2wMBvoCo9I4NKINx1FEN4oEFBJAoFs2EUk5ynU4e8b8cL/AEpIlqjt2jqkjgmjiIPA3BhMJFObssEYe2RQQOSASVfndPLrvrvLGnJPGNGrKliCqLBDCJGhnupmgFFL7MidEMfcmlofIBYQQPaIC02n3Pvsvtvvr9zviuqpmumvmigrurquhrlnrJKO/LuBLDHaZuhrYeEICUXRA0lu1Pv4lu6GO/vz5lnPhvlrEqpGOJjPvNvguHKOwFINHIGMCcbfVeUJLEJUDEVgtPtatHtPP994rukgonpppFuqg3oEhnusIFIHLIPoHlnvJEffKJQOAFeaBOPgnPD/AOd8/u67ob46MJL5LTrpeBLF6qpLoLbSz8Ny6hyCzlAykAxmUQE0323TIrzz75bbLbr7JK4JJZKqYqAqbacZK4IbazSzzMM9p6QADUyAxmBQUUXXTjXFupjyVVZO7pRgQAI5QRg7Ib4wiraJoaZK5STgDP8AbdUwAN5Nth8pYJVg80gB8I+E89As222OKQyumaKa2GGWqMSmY2SO2cos08T/AEhbGLOSabNMScFGHYfdVJp/lvAuZ7k88igkGrommKuLvtJqGjjuioosNiPK0wwOqEYVOgADHQRYfCffWQqeOnPPqhg6hjrjkg6tHnkulmqnjktggiKICqCHz6w0uLUfFvimlaDfbTcYYfifAvMNgkj+vjlsghvnGuqisjoBvqogjniLGGAIZ69zLORAKPffe0XbRiMaFjafEnBC6As/uvJgpgh6DggxbrtnmoynNEnNoKAAVy//ADAUwjLjnyvdAAk2mgCC3iLxWdboF7gKbCbbI5Trga5IJCe72jo5SCSQym/s5UjkILYBwkFuckmyzxhDPjrhH68k1RCgiiAYHRBDRZqXihbefEoLzjqgTx0MNCn0DYpTRz1nQK0AwXC4Oi7ylILqK76LaAAbYpq5L4ZrRqpYZMbLBAZzSx2OtLT0bKa0FWnoywxzSiWv/orRbsscqbubwQz4ajC5xIajLb7omxoSdyDBTBzx+MgXibYWlEXqxiQzAgC1eL5ZT2RiwqSrKxj4qTTqhSr6ny/rGp6o6CASQzyAttykgL5WkVkjSRjJADyz3qp+U1UNxcDZyax45QLjpKKSza5pCP5pKXSTwACiy6gnDDf3yQ0CTjzRWiQw2rzzwMMKo6oYbwAop6LDRJ7+5aoKKpKoMjQBxQATyrR1ghDOknmQhiwxQADwGjyin+84P8/1jYK4Oga5CabDJ3oLJptpTSSgyAyyn6TGhiwfVUGADQTA2gjzWbbye9EM8MGuxJpDa6K4xLQQvM5DQaJoTwQDTwhw2oDHBwDdijhHzjAyiDywH74SI6Py4Kj4qZJ4r664ALy5AdbUI8ojAQQwRxxRiKxlAjBu9F03yFmxySzCvpaTyS7bKqKLaKZIr4pogSDQzwgBrKLZFODixChjjqAEFzRr+cszBSwDG1T+3hUy1CYa694YoroJ47L6hCMI66pJLwrYCARAAASA2rxWVkCQActQtEzQsw1bkgjyyZ5Jr77Iba5Zbp6NjaeqI6qJ4K4b6gBBhRCCkJzBiTywlEMi9SyiCRiqX2hiBAAjpKp7rKYYar4a4I3P7aKrLYhbIKggwhQAV5QDy52GNiiE/wCcgMMAw5wGIMM6DUQuCqqiW68s5sRq9mCu+OsQgOIgsUAUMlqEx57Svp7klvygt5htBwV0EMseWK+CwKSuUmIdr4PNtl400cwcUMQYEAAEkhqwRUwwPMYvntqo4wZEXH9c+4IsKimaI+q+ua9PC20QDa4s0sgc9IOQEAAsgB3B0QUObLiRuAQLmB3gOziCE884McuKKOGilees0nJfemgg48g28LEB0AAkoUS89ME+gLfcldJz7O6DOVqC8MYw8q8e4m0yQOsy1r3u8Ca2AfF+MnQQEEco8UH8l1w+KUmQb517WJ56uFQI8Ew4UQmuU+ucS+nmmSvCMQa6WEsmkW9feSQSAId8RyLEfhpJ8tNBchplr5+AgEocAoWmE2SuE6C66GeSaaWqyYm2Ui1b/reI88xMJ6YFOHZBN1Q0McIbTjGYs8em4gamQ6yyymCyeOaeUi66QGAuMKXnYa8yQ+R8RN8QeHy7cYkI1QGl20+SiT3PLFNKi2MfEIkQyCQuQHH8jL+6046meyy+uaR4Jhl7G0QsSioN4kHkHg2y5e60wZa1d2iRwx+ay3PG32P3im6Wko7M8r9GOL5o191sBwEAbCKIMhWeiXsu2CXKP/maqOGywaqrKqS4O+/Dv2QEYWsYquFRStZhsU9kkogeNSAcrGUqVTyiGwTCsmUqi+WGWy2WOu2Qy2WOSkIAAJkA26R1xplNAY0IKAqchUP7klEx9TOXjSOWgqmqs6iaclLOYYqw0KoxWD6IhCqE9MYxMlpHiJ8Ua/8AykP3zMfIcplXLK4vJtqNBotoknJjrjuPrvotrvBkOFp8pomzCGOPyM0nIuAOu/G0VAFNwo2DiMIUDBICEmpmqiArpGhjuromiDnjvkGvPHvJEROvzV0L9uUuyz1zbFJhYQU1CKECEPPLKjjpnrlrutrhrrsvjvvgisqCFACWWCXmjdcZZiXBJvy9nE/VfaV5ynIGGDOKNHOuitrtpvhqgjhrrnvghlhsgLFDSISCHOVfbjwKLIDr4hNQZ4F3dhFMDEFHOFHPhpvgktjoorkluvghnhouoEFKRTTJ2caAXjuqnmf+7PWV6SEiMrONDMLJOAPLHlglukumhvhjjmilurqltjrAeWeF8lDAGo9TiP/EACgRAAMAAgICAQMFAQEBAAAAAAABERAgMDFAQSFQUfBhcZGh4YHRsf/aAAgBAhEBPxDFLmly9+GmUo2VlKUpS5pWosyIfxl8oEEJ4y+JY1sh5pSlxS/S1H2t7lrM4CF9DeX2Lko2tFz3xTy0w8vK4b2YsLd+C+1w3N2XhVosTwn3xzZC+hXq8vvmmJhb5yTMzOKavD70nG1wVhiwx7sYtGLZi4n3mCWJrRS8VYYsPaYezFsxYfCWVmExBomLhUUWawtmvGpS4uxc0Jhaq4p9EPgZNaw8I9jFh4Z6w9X4XpwXExNk9aw18HoQ0MWWM9Yezw8TlfT6Gu1KXlenr51+cuuielKNcuiEM9YuX4E5FrurzNJt9CEPs9DEPD5Jil5Vxbi8elKMpfo6s0Wk83PIbrNZrglj4GpzzKF5CtZo2kFkvAb8lmITEzMpp6ghfGLtMTSZhPKXlc+aQn0VnBfqspS4JvEYkTWxWNQRc3F+gi2TxMLivux0seuViwxE8dhM0TLvrWE2iifPcfA/JYQg1lFE/JrR8vdzQhCEEj0fwj9hqCVRPinZPmD5UsJYZMMnD3cS0hMU6EN2tF6M+DqGdK8F3zFlYYsPsa4e7wHj0dtHGP0Q2n2fBVIKX5KreZYRBoWJ8iHuzu5EXbv9AvD3ckxNF8HbSEvRQlRfKDXyJMSzMzaYngdnzrg/BIovkJOjsPs9hciL8i7H2Moy/HH2caxeLaoQgnhi5V2exYfN2fFMPNKUvjbm4pdGyl4Oz44NaMovnN4Xk3k7PiWYQg1heJa8WJFy+4YnPCZ2fCxBC6zN5WZicPTwskqfYs+a/wAFU7X9mOSKEF4JnZ4hM0uLkmJlLijfHfAhfxDKVfyJc9/KEugm/gv7gwyXwuz0mlwhpEJm6X4CJyx3pkX0Y4vacGCZ0JO0Wn2T8L21hMXFExPEIQ6zfgNHRjh7GUmXVP7r/wCnUGyiv5/fBMzf23a0pckFWH4GZl8MtvZeBz+giV6GNeF4e/thPZoaIQmvwF4TMJtdH6y10Nt97QmXw+3FCDwNExPHrkTHi5uPbCwnyNfRCGImHn21TFrcUpS/RCHsz22Rco0mGtEvCXx2dXpNExPCcFk8paWNUflEV+Isv7H7T9ov0D9on7CfsI+z+z9B/f8A6foP7/8AT8lPzU/TPzM/Mz8jPxP/AA/Rf8/4X7X/AD/hftZ/2f8AZPvZPvf8f6T7n/H+n4EfiWmkkSP3j6PbaDWWJhMqZMp4rmvivR9HTVLLWGhkJj0MaIJYrR+WuBnTZE0eV8iQ2UR3eVy0vDcXN0ukOh1KJl4VlHY0JtaW/oKPWem1eRvVS/Q2dME1pSlw8pEZCYTSeXOF9bDRNrilGQaOuH9GfR12myRCZQv0mzqXjSEsNEEvpXodNqXP/8QAIxEAAgIBBQEBAQEBAQAAAAAAAAEQETEgITBAQVFhcVDwof/aAAgBAREBPxAoorRUbmNQoqKK1VDUUUJCFChIooS0I/YuPfWNYaaLLL0XNllllllljZkPTRRUVFRRRRRUUUUUUUUUUVprQioa26ecMfUoorVXUrhzhjm/utixLXYXLRWnIalwxPaLn0Yj2GeXLcpl8qlcV8OR4OHDweCxGT09GLA8w8CwYENjwIX+IyHiXFfYqoSorexr2EU7hwxDQxC/wjGZDwMQ33U960rXRRTK4xmY8DhngmXFidlji4sQmObLLmyy4bELJehaG0bCQvmZmh4HDPDAegwPY9MRgKD+R7oF9HKGI9Hg8hC12WWWWXFFamZIeBwzwQ9A99hr4WV7CxBDH7Ht6BfBj2hDwIWR4HKl8ViZZsUUVDMh4GIfYUUUoooooqEKHz2XDRkPE4FllzZZcX2FL6VmWjAQsiyYCxoMCqh6PBhHpQlBblCdj/ONS8dPI8hQTE9z0wFjQLAoejMI9GIWkvleOnmPGuijZGzKKKKKRQlFRRRRRRQ1xKcOnkecLwLHdIw10UVxZHk1vIsGHQtxrYWBww4YncLAiy9xl7WWWLcsvcviRj089GXUHgWD2GAsSYtDyXozw8K2FgoWeNGPTzPJoqyhKivShqxIYlQ0VoSiindjPC2XYrULPGjHp5jx0vYYtCXMjHp5jxNjdDZuJidiZZZcOLEz2GIsUIILkRj01pjxN6DAWB4Eij2PJWT2PBwlNcqMem5vceJrexpsasVjVi2hbR6NlbFiPT0s8H9L6KMenmPHGme6L7GPTyHjjWn3V6Y35Vox4qiiipssyHiFChOx/hXoxveioKGI9lCfkLIxCdlx6LWuvZDxpbNou3Qz2VCGI9GeClZMBYg1ZdZPetXNFDWjIc0mIaTKKKKKKKKmiiipS9GjwSqGrPeTHiuLL1ZD67ZvKfLj0LlrHKdsX6J2XTMqG6G9rEWWWOExOLmx5huoWSxi4semu2h+kbkJsUoYQWBFDyM8FgYihiMD5JCyMeBYE/Hw49PZDEK0L0xJqKd2PAk6oRVQ8jEKFtoe48xgJmUHgT2GLgx6T6li6uPX2XWSg3Q2JjaLL03DwLAouL6GPTyHCNzZQ9g15MDAyjB6IeB4KEMQj0wErRgLAiuVj0mZDhFNO0JljXo90LA4R6IY8QvgxYEemA3sh4FiT2dxZZfBj08hi6dFFFFFFaEqEvRLfWjHp5DF20q41z7L0ZDF0G0lbPJC9sxj0Xs2PpIxXFRXBkPTZZZYxY143iEsngS3Yia0JKmrKds9FcGpuKK1ZDFwULVctC2q4WlTGTuoZJpOitO5oqUWXFaMorUoYhnghiLXo27Fey2KQwIHuCklIVpUuijxpsTENDRRRWi5y4FDEMeBShKYxg9IOmz/ALA1D9N9JG6POBsThO9SyedSYmIamioUVOfGhxgucxZGtYWr1sy+8Ns/9BVS4HBoSrX44EE4vU0MZjFqsuLi4uLjKIp42b2+4kkqRcp7xZcPGsnvPjhssssssvRnC1qHmFDhiMwxOKEKEhiHiCbQveihLbQ8aGuS5zha1HsKHDEKUeyosYh4g8Qa9F9aXiU4aH0KhDlaFDhiFmGI9lDEMQxDxBMaG2kjxoaGGql8BuLlFFFaKUUooooqaiprQkUUNWJUJNQlsU1CPGixBMaTGKih6jcHDR7Mp/zKfSn0p9Z/R/TP7Z/TLfWX+l/pf7A/Q/Q/Q/Q/U/Ur7K+yvvR/5L+UX8n4n4H4H4Cb4W+H8H8mR41JicNCy4aKouWjIfRXLUKVLFk8a7F9SouGhMuMhyhR7F6nK4N9TFmVoWTxwWLSexcVGY4YhR7DFKhlQihwiooYxQ2PBncWRvwoTLdwmZC4GiuVwmNWZylrUqHKhwoUejhjUJR7DPZZD7lxUHyKjKaEiuKprQloqXFsTKGor09lkZRZYmVYyxRWls2Ni4e2hFdtQvvBkZai7EKK0UUVoyQv8bLUIUFlimy5qMkL/GyMytdwobmyy4zf5GRnrqLP/8QAKRABAAICAQMEAgMBAQEBAAAAAQARITFBEFFhcYGRobHwIMHR4TDxQP/aAAgBAAABPxBQaJQ8pHD2ilWyv9IUJ5wke8sl5Mux5lsGBysXeZXDBxUvG89DDXvDa51+Lqj4hLAzN5hNmIkriVMSpXQJXQZcuKx/hmX0ZdSnyRExDF+IE0XF2YXMwapBwf6mxGldMC0huFfURBtXPayoQfbFsrzBQiFVb8f8ijaz6f8AI7VX7doptL+3EqPSKxY2iYkfKfEqbfbhnNPvf5ihkvT/AEjB79F/cXRnq+6WKpFLwAej/IX2D4f6h+QTDSHeTuI8I7/9w5Xv8/zKdt7C5Vx2WRH2C5z+IdMAK2P6gmxHrP6g/wDQ+0zm2u3/ADEPxH+4ppfGA/hnbp+uZngV2b+IcigXb/lHa81RBphXeUFMp36dQQqC1EpaV/k+kiw1LoGODeDzDNPeWRYQN6vmJVJzLHcEy5TWpRna4cHtghQrKCD3dpi79/iNDOpsqNW/ipeA4SrDt5i6zE8yr/SYekSuPmA1O6FNyi3GRZFahLA67EyrFQ9wfLABtUJe30GsCBExKlZhKlRJUqVKlErolypX8EiROZTG9RO0I4iSuWKxKMDFQw9kGpyS5jfLL6jN4lLhUIl7iOI3gB0qVDt0zLZfQBcC6gCQGEuZIKS85lpbdyxcw1g2hRTQwIwTwlR7kYyql3aZb2PLMjt+LeonPqAf6lDKGs/4ntXUvc8MvGJm0CLYdpa+xLJn/sQ0PEWxOGY1BPEuY58xam2/ipkJyRZa2kFInulxUYHhKGxpKEOcQBRTBN4GKlYPmTmwXUIqcmPCATg45RFceYE2bd4Cgw0xIsso71FJsd5cVY9sIlvEg4Wi84eCGUpkc8UzV8EeIsRhuV0ZX8KlSpUJUrprpUrrXRLnhGMIxluVUrtLSuZUVe4FYI4gYz7pVsdXEI7gil0TEZz/AD30rMqXnMytyghiGPsh8wgL0qV1C5VMdZ6Gf43DC4x8IjPrpuh9oZVL4e+55OZQOMVCgDMwM77yynGFLmDeYr4gpvMOHDbGlbELV6cxYoiaEGqgIT5EtYYOZlmKIOHgmCoKwiUx/wBXFqgi/iBtNQHE3bHOJVqycQYLYnCFg+SH4CDGJpGH/vUSVNdbnpKhKiSrehhikpKdFTIjfp7ZiVCW+pmguZTAlM1/H0mZmVAbblVBeeSLYUluIErEdwIYlSswJU4/lnogjUewlm8iNpkzhzASjUWpZTROYvMX7HfmXTLbZaqcNxyzmLYVNeIdtQwnfx5hV08So2YY3tyi0z7S5AbxDiod4g3lMHlhuBwY/WIGbJcWtO7lt8zy13lsOY0d05TayZeiQGU46EyDLagQ3jLZSd6c08SpWN/ez4eL8dLiu56QTXH/AKVK68da6+kZXRJVQIEr+BUqJCKgJV4lECowJjjoESU7mGJtEzfMDvA46K4lTx0xc109eofxNp2HK73FDMezcMZ8oKm9QSqmNV2gE1yjdZltYi7RdxXI2xLUm8d4fMaaeJdN+0APiKrRqK/6i+IjxChzqN3jUtbuC3ctS2DbepgV9QR4lzTM0lOdsKAsdvVjB6R3Bro31yvAZYESY7mbLSnnn06OoZe/z9hr/IDR/de68ry9L7QJQxrQdjLcKGhbrX8K/gDYALfaMRXj+1UoSoSRYqcL/PPdaHc9g5gBax23snDKmpuHeH86muvr0fMQlTUxKqVM3FI7R8dBCbnnmc5mLgSiUSuP/CpXNKuot7i4CX2hi4PDF9oJjuQab+IDTBatmazD3mTDDcfEF3sZiWucpSOeJwvMWjNpVuOYmL6BxqcjvPDm4OMRfMM+ZzGwsl3uU3ntxBxUVFEVpr/CPFQ10/0JwXLDLLk5baGT7me45PFXUdTaZdOhIPVdJPxUWnMHyen+cQGLV6X2uobYPcB8wQUfffwgiDYOnoQmr5Jg38mBfH/kEyoLbgp95m/i+3+dV4jQseR1ZUtkCDaoVlMW31qH/juHSobjBKlVL6EetErmXUu8Rt6lc/xr+dPbS3GPeWuIVqVnobg5xbzPkdpdY4n2mamC/MaYZg3FXcu1e3MYy1GJnvDaKStzNnnK8xGmYFm/qKvOmOD3iJ+Y2YdQLgLTkvE0bwqa7x+CZkOmemzudk8jmHui7IB7N+8MqyC+QP7lUh4IhzSLxHUs6RUoL5mLyAYBTNHqQ4Pf+iIDTscjB466Yv2TQ+SeaNio05aTtpgyFB5HqhlaIO7+VoMqu139NTNw3+vmXDf2XpX8bj/6PXX8HDicdPPQ6O8RgvU1/GsQKm/53/AaIWsRric+ZRBOmeIYJmvWWLUW25SOPJxLxmVm4m5dtQveHaKvkgXn59I2Cow5DuUM/cwWROyIomHvCpKsnhAa2JWMzFVAC2zPHEul+ldAMdLl9FlwFvf8rKPP+foMMuh7bT7n4j3MDPxwT6ehLPBULzk3XLqF+wVD42X6nhJcdsq0s7QhjYeR5E4TklNIAYO8KWr4IVSnLPC0z3jVmiVStA2+ZTaUeSPTRuJfj1Lw6lpWLq2rvC6teYo4dCVnupiUTcf7xUytMBbmVLV0EfTZPaAG7p0U7lbPS4Ve8fj8PVhsZWCE2p7I/q5Y+lb1Xi4lMALVwBBSHuEybE79sSxoRQaq9jD9TYsS3SWdTTJrc+htnYWNI1yTI7K570pNlkQWqPMe3wBNq4COSHa0I4Ye5gel8JJ9SpuMY9pTKxM3D+FSpnXTNSuJ4h1f/F16eDUxN+Zz0PPS/iF3TK+o6gUM5Z6Sy8ykfEWipU16MbvkShWfMGblXKpzhAYrNOkTNMT2lWXDUqmpV5ioS0wTW4JOL9orF3PqKCMv+Iz9/wAsGvN1F6hI92n8xh5U9FRVJNzYDLxdhKPWkKDnIGnU74esBT/WNwe6drIZXQiqC0t+RiJguSu3h2q+e0cwnyk6Ef7ip0AemH+5fD+gj3/pfT9p3gbykiNVaaW+ndQsoLb5uDuUIOKNX7j1uVPFx8MUYZwyrlDRYkAb/EgJgtjdC094N6jHAc/7BlxXLDr51MGBCR3YDp6xU3CNZ2KdAfaEoIHgjiSpc0I/DBgBjyoBLfF1MWzExfGDDmZsUH1Vf1KAzG63RXLW1gKtmHF7iS64LdA5xxjJNRgE9+qSupLjibniamITMzOegp/DMqXn+VxzthVQGeJic3LXfEyweYrZcc2/tSl1qcPaXcIzUt33jgzvvGnMMbiWEl1mWF3GYq2c4i2qykiN3qNRDKYDwi30zc30HZ1M3efxR2smo6jLl9ow1EXv1WVw/surhuLHcMvxHZpe9lNGmT3VwBN/4BGY1AGwLlSk4o+WJHGD2+Cc6xOOBeG3GDUup+ipgMRNbv8AsZz0+Br5B+V/nQCbCGft/XHoSmXt/SAic/0R5arffFPuI30HYWmMmx8wYqryvq0/nprqoZY8t9hyUUdKBxD3B/HBAdwU8XWAGIFHoQ8Qgez+YQeCD6melTXS5dE56vUnj+HmWqXXTX/h9X+EaupVGIYjeZxPE9YJlipF5Jlnh3HuTIbmKpOc4RU+OIwc2xM5l9uZ5S8xPSXMa8xF1Fc9AaYJQUYG7KMoxe0CtdNwHRML/wBwiWeNQ1HU2mJx0CB2pfljGmlYegl4MrGRth7FV8yhnTLyH7Er2mSj0lml/ccOq/NR/h1f0FDgtCtexAlBQrzgDwbeYRvIXZXdf60RYG7von6jxH7p/c0ebr92JP8AE/B/mEnzo93VkM3h+PUjw92fZFb/AL2QviqWm1RpRjAX7OSX4FbqI4T1+I+fiL7Pcb6B4NR0BuKcpZLroc4L4IYpO2fotVb6jmSCsGIIXOf6IZgPMHQIBNyceaIAA4B9T06MSPU6Mx08ReOu9zUwQX+Fn8z8CGxcTtPWPiVMbl3CrVzGpefWLygt/UwcQsszMnGKlrqHKGXl56KrjLzF50ifchTUaB5lrhWo29JlJ6cTzDO4e6LIAIfcaLfEv5/6iVsMNR1HqR10LRfaDMAwZBkig12l9mjrLaaxVYlx1qy9PYJuxoNbwDR77iYgu+PB4euYWgzCAHBMbgwdloekOKLrbwe5sYQUSqJPkwnrmUTuNFPoFrElpXhVoWy9B2iyJKc0fY5uACwJYmmXCBLt5Q+AJgcUjmgU/UGwCg4+fkgCTTblV18RkYBauACe++ysVzmtRYB6oG/xfRV0FOXNvwEor51yiU+upFatQO14fiHXaT1pI9oVOgOz7494I6lL5bfOE9z8QraCeQEX5fqPiXelXXpn6h9UF7tX/wARlihFcLaPxK49v6YYYfN80MII9G/pQwteA/PXOow7T0jmHS4xOju+mZrqTR05/wDDD0/4Twi1ZPTpqbzLoqPIhnn2gILCmIisQoJZLTEcGEWc6jsMaESkxb6LUBzFtzNuhQoREcQK+EGIdYgKYnJKTD2lB/aoiy8odAzZOOty5dzNeaDGsfwUquy4+GMXY8f1VPCSt35b6D1ZgeB6JmW+DzX01epgAuU4ek+MQQ8c4iRC6vJ2p2vKyhQNMw+5eT5hwN2SjxRaeFiz93qDsGg8EHpIVxK8x9b6+0UQ6DXVFA9iqIhm7E2PfW4YLexf0HRRfNU09mc6I3P/ADxAt9Ewmrz9y+8wwFW7az7QVS1fAIpr1jPFuh/VVXzB7EUYA4OiCU2GIF1MkPIaPEGAhS8PnD+5YpL/AEWwcDQaldjMnR7lH1FYByQWKqp0cvOYA2YNZ8e0NDNcuu4m/MVopiuPnvEXApzXLxDgAVoQKFN3/BelTU4m4x3GXipzCZJ69AhPP8D+F9FYdUkLtiWqaYzF4YReJaYYxS6i0y8xpfmIIveWkuCbm875mXQDMDwQ7wbxGod/uDjMTMxKzRqA/MGWe0QuyBgqAB0APqe8w6HpV/8A6NS+j/53Bl9T+b0Hpv8AgxQugOWGX60Zb4cajupeYMxNQ6eOp18dQ44SW5Yyb6BtEu2YbzMlMswqocoI1Ldy8QtLNy4i6jIbEjN455gqoyjct+ZfL4TaeZWLZVbwnGJ2fiIvnzKT0m5ZeJg1H9yyjvPEAQfCHQ9MdCBJpaolDby+JpWoLL44vf8A+V6H2fBgDvBeJeYU7l1f8CdxKuua/jUr/wArizjpjpmMfHRZQVI8kCQITVgNkoo2J9IvaGpdy4PEIf8AikohOSR0jhnmHdLuIJY0IwVNnEXRAtUIsN7MbxDsRZFQ5hi2NDVsF2QlMLKYMi2PoQ34lZa3DdG0p+JzHvrpQ4JqpXMHslO4Mkd0VUyZgu4HftD7mB+CLKw10M9IHTzUUR9wDqUCHpQx3lYuxhrT6QBAHZPyzFkXIYN+IWWPVQvoblfjesQv1SoHRtGR9ycgFsfylhBtUkz7w7qklh94oLcEs7NqbehdyrU81Ear0rfx/AWkd3E4hO1v5NYmg42Il+MZm8EBTSvY6d4nbVMNd36jM1iMvtrP0OvwqUDi5rV/wz0r+L15iRnpNsQj0XESN91W9oK/Mtioe8QanL/CZWDOYdKYS2Zh/DjoGNXkltHhlgMMLBheYJnRAtFiZuUwEc33l4FU8Igyd8RFDlFEXs5gUl2NxW2UpWNu8seJZLPWO8Sy4qBWZ6Yqb1HOJnDzDfiVRUrZKKtDa+kBrEbnPlK5YlZOJQwLx2hbDBVO/wCyfVhKYa6GOZfHTx8YR9wNJA8XYeB1DX6GUQzrZV2PfE7ptUD2Oau5ZBtXw7rwdgwTSj91GxOcZIHMsOa5oAaRgzkERfA4HYIszFaus2rYx3tcPBjCdsxUCDpJaZVk7Q3kINreD3mMa7K70QHzLbKJVfYGIMy3gAcfLp+ZUBjI3ImgOfocwSSxsg9tAEZO100+2E8MKM1hRp2Tld9kAMCWPFMwlGLleVMluDcvxcbVL8jYkqHI8Aw3QcO5XVooxOkLT7RlLCdKVY9YNQru0FYocyu8yZrJaualj6P+8yOyiuOKsVjJXbIE73UdgExQt8Tbk0ZXsEZGW3HadC0t9sN+9EajcYHs43Xf8ypXY3zvMT7kagUFol8NWLE4vl9IK+9GvBzLN8pZN7Xw+vVUYlq4An+iWk2/aahi6sflIofla1fDphkNil+HtqWGgFwC+csLIxtmnS9hj7x2ur1qE0zWFfR5igxAVxmZ7eS2OS/5l8urnGjkgqL3YfcsF2p8CGMNi4aIESPn0+l5Zuq6yl9szDk1A+I6AW8Z6hCTA61C/WFMrC8Suf43LhLKfusUl9coqDQTMu7nEbSkvA1B2fKMy4HUFWoC7cvH/wBlps1ahMMmZZvRChmkbRTXeOA7EQUZeacR1GPEAY5hw0lU95oOal4tlAYhjDADcozeYI64ibSa94N+YlnmVRPTiLB3H5ga/EDT3hrqYPfobmL9/wAiUx0z/KE9p/Kh3QCfRFUYDmh/KhLZAL7C/wBRhM6Q+SUh0D6WeCF8jLF42+g3/UYMpRRqux/wlQgIe4wvhGIcrL5eB9bb6E2p1fiqye9ygeFHJJ+jiNkZk2A7PIz1uVB4ThnAIaV2p9czS8/SXLHdj9GIcVVhwlEqx9UXGEp78a94Wmw+QgfF0eZQFGA6NYL6dc3uQL/Q3DddkzMU1fRCUqCep5fVcwh4cSji0FfMSW5Qr7dPPrQ+ccD8sF9i2Dmb9NS8y9YxDd9N+GByxnps+TmHWQYO14hGD9qzN+miIGwOxgVwVZs5PiZV2H1SHmVPlJjy30BKLsylmtSfRBzEt2eVHNBCCoqkGHKUj60wHeW2bQEz6MLgdb9v7PxAtxnbVms8HaCcGk8MJVb/AAvoeQzAVgSx8S+mIa6kVB3D6Q3LLxObl37waiJaCncYWSyagxpmByJU1t7Qcgy3EEt9Q0mRKRrmWNhxLqG+0HHvqCuGLfiARq/WO6cIbgFUxL909c5gL7QLe9Rx+IDWZg9S52VOJXMV+J/MefUuMHVWYb6EeDw/LFa+f5T0f+yUcgj7Rgsn9CMPU/lGEt+oyw2HdfiMA9h+YwneKz6SpjIPz/uox3uPSHoFd2UeuZo+P5pUQVplwpz48ueY654Ggnk0GOxFY/oOTiO3+tQD2zHwHRWHyxDCbLxMmGKB20fUQrYB75fiPTfhU9xIT+yca/DALI0cQ7hMWZxPeiFS2ARCt/FizKleHnNo5lUzQ99Ms/Ee2viBU1oEj2kwwcR3OampXsEq7IHwQ3F3y76QN72PxBliPCF+Ia92/aiG5xf0I1yeo0Yg7xe7ltcwrWPU9rH3H+SvQYoyBRxCWAFnbRX8DpcIF7SULmZ3FhZmN79pzmXXxC4DmCiC3AnHqlPad6Ee+5kdzLClx+YIb57kC3GEYa04gmCeeJnNy7wQ4GoVdsDEvnmK4buHVwK3i4Oc8yrhqzs/Mcxt1L/G4aPeFtT7jwW3vCJ/uVqjY9UxvFPciRhrYE/Ch4NZPmz+4wNQZexc2y+8/wComIaWvZDKWJZYdPSnsorm1075agOcXyGfhRMI9J4XT6WEegMhpeGD7X4mLgbPXXza/EtUAbuJZC/CXk/y7kwSOBzmj0npVfOJS/L/AJQhOukE0iqcx7GFUio5Rs+LleINvsQfVxhMzmL8J/bKhTlmwZX0vEdZwQMI3JyPiyMNrXzJUudDW8UZpLuazCPVKPzGnA1uwH9rE8kv2i95lpdDtPsIKURe4b9jgnP/APgjGm55iP7KSh+vmZNxYJ5fiZeLh8H9TGNcvq1LD2l9PXpx1ehHj7l9y+GaZ4msnEHmeeJasQeJfeXxBrEGsGkMr9Sw9iU1eo6B2+Zsh40hODBMEdKGNqNWZefmC63KcS1/SCvGZtzmZPaYGYGY1rbMbYiEH3kr5n0Ym/aHRUSE5ltT2FV4vEsQ9ya+73uNtsGnH0qnyRyuu8PazPpqChlWNxEyOGVJoUmr7qZfYVLFcXo9oHs4Gik0ksORhnzExBTva81swUfcFUUJXBqLkDEtud0YxzPF4lQV1CJlhsGh0tDkj4XVtTkLVY89KGe+byumQa1bTsDk+yHWzgEmqMH2gHC6vN+aAiiIHII0LzUpg6HZ4AhwJ9xs0mSu/tKKBbdfpWPVllRh2JseDUd0wUZN1dZV7Rzi0C5RTWNkxCTdoR7I1GhTOmi3lNJAMEMRoZTuRCOMoDbdnYYyxfBUOmgetQVJlSa4E74gS42BpN+oeSOZoMHlYeO0FRFqQVCALxRdlDtfoqUKucZ0BtVmxYUfIQouUr8oWzFNQBA1Yp7XZ9QToK1wpkTjMIhkjDhrw8/mVVFrVrFD8yoCsg51Wk8d2VDtxhRYF7fbNYEL0bw/YWJpGXhgFq4AJrLi+NPqC1ME1SXCN+ILdjUziGzmgU17TD8KDuq4D1lylwDhU/iEpLM8NJALzMPnDtbj8TEsxewH7zNxw561nucxAEDlWc+j0B60aPgPnfiYCyjDV89Mn8Doqd/tc8O+m2evTiGDHEHVzGV6ZCoUs7/3DQ8xH5mKxzDdQtNS8+YglalBG2HplJZmGabjXL8sCu6WZgjZBcsH2laGJVHeBmJx9z8zP0Zg+Ia6HoTmWzFK5hXqn1GkxPVv0CVgF0OLB/8AC4qTsn6mNkLPen9x/wDFcQFaDzPSD1RCh2MwEd7rf4jQpcWGH/FwpmnprZ7y4AJdLl87hMrq4vm4AAGA4mDC1Yqvef0I/wCS+i80X8RcwZWw+Ikz8GXVfOQPtL6DDtWN9zMUdJ3Z9mYv5OGT6u2L2JVZz4DUs2Ho5gFpQmHszLflKQ+tSga/e8wQNPYj0vUMRPT4eHudp2NHQ+2ZUOJhr9KqHzUdIG0yr8Ryg0YV2smuNlAvnES0ea1/E16KqPaDKUyao9x4ltGJV7Pcggt22v5JhX1cB7aDp5630HtBuOg7/wBjLtzqOOpc4nEPE7wCoZfM9Za9XNd4tEcf3EthYyhgXEVWrnZHklEij6SwuIQPEVzC3mW5gnEFC5mcheI8ncJW17xDoY9upKgo4e5BnE/Yf+ICNEKlMK1QG5W8wN9jfaCKLyEnIFKZX8TrpDENfwqMqG6h/wCVzTn+CTxC3+FY6X111F1G+gstSpxD+RCcn9yHJPG+lt0y+Yb6K8dDiJLtuXcM5in0S7I5y7m31j2gJZkjhhuo01DOJRKLzAOD1TshjwYgjWSEoPNoBCoc4dD5j+AmpB1J1IGt3g+Eyb9qf+Ny41/4s3AxD+VEMY6EuL/Ij3l5l4lxlzM8S3qw/jUuMPM56Xc9OhM9Q7QjtftUb108somiGGbxL7S3iXq47nbzKvcxKNQuKuJfxPJOyzzqNPt05DzAMsvjUOxxCp4OlqV5iIRDuMkAeZcKyGcTsTHyhr+CuhKOW0+kMtBYFpwz4DXLLeil7fxdmLrc3j5quz0ZQpBaAPkGb2RVgjpHYZ9Z8BrcoeWqbe7ibaIvS8jeRgbQprs9IhEaLWy+VH3CHVUuF1gv8xBy0At7LS3i7iCFSyGu1Y+40CFdAfPk8kIlqgCvZSF+IRvNFgfcZ5hDp9zoSTmm37XqGgnukHrZSLqKWrBPKzOYmFnbP7iRugZFLqIh/ZsnqFw9d8U35BEFoORNfwrnDloQpS1Sk09sRIROgx+4CEOkyQmjeH8odu3Qk/MGEHSZOlQSzO7SO16EGVcriesKMPZ7x8dHqR31vrrf8DxCGTOOpDoyyE5lO5NJmZnMrEMM8xxZKxiN1LvLEavvL2y2Lnjcwe0bGWuWdjA5i5mdS7xC1xueTMuyKuektqobuMKIgkJ2Zl1kCNX8H4lLhqOo9eYTL9vCU1PWDlfxUJnkJfUs/EUS8F+ih9QFayS+mH5iWaWv26CtizzhE/MFN3b7IOUynvWH2YYtocIrVidph+oefL5eYEt2+6AsT3gDVjUQwT4hq2ornuvl2ylIreAWJ6MBNDDlbI9Aq0opeQeFLgpHrbnavqAvFF6R3L02VPQr0TESiZjhlYuR6bukOGyDIZoTaXCrV9oSF+35O33iQxjqvxn0amV2Rzg0no31NUBTVH5IqtiRBmy3T2igDhaZTXk4Pmcq2KveK89pTbO5qXpB2BuvEc0bLArXjG61AA7Wgnke5LL527Ca4e03mM3GWnIul7viEczeX9NKLfolacbWHR123MgonaVse/iBTFYtD9KOYWr6ia1Yq13HcstUFOEuswuo02jR1w94mZfUj/DnoWwjNSut9Cc30eoiruzCcZnFTIy9w7k2Q8zM9ZjnUvROJ5ReKn5jHuZluIrGYGMSu8M5lVKXcS9bRoUSqagf9jVQwiJVFErMBzL3UQmzY/EThxDUY4m49XdGEmIr9BCEsMv7EFfq2xNBw/0grzp8rpTz18IAMctAEXu/EI8Lm9YyqTYtj2hG+D9WxgE3NjAUccfmPRu0e4fYGZvFru3THaODvGfr7gOUZXhVnMN7FJIkt4PcR6DmZL+8pcpmd8AsuACCHhi13boAt9ImMVq4A7s3WIPhwm1jPoFwmoBT2W36gEqBQeCIzThHTcWTgO6C6F1Khgo6Xby0FYgFBBjGn1B8P6vSUr7J1Hmu+YAfCe7mPS5f8GBf/gdB4/gx7whHUIH2jnMzUHPQc2xUjPXEHMW9dCDWJrcvXR3iBUAsrNOZiPcmobxNeZnUpCbjt5uFO41cVgr+4WsaaiyfpUxO8NRjCPXPwFHnP8fR92DiCPRn2jw+U7DWHqLojmnzkJpdpFSvC/Eq8Kv5YxU7hP1GD93+GWI3sCfqVueD7uORYC5XL4DLAOskYLwGLZkpNmfXWWMTLH+Ecx0Rz+aB3VnosUfoJiHh+MYsKj/f3Q1nL/ERhrXGZW6DywyK1zO8nB8So+5cZfBx83MBBVcYNYybXPlIhxb/ADaurC7XjVfH3RjSCxcS4jOKh0J6dHXS5cJj+JM9Ll4inUQeIXQLqcxL6qcw5xfS9LFt6Z1OZbuJcRJVymsw8QBczLCZzKtFxDGoPM5uLwahNN9FYlXqBhOR4ReOEyTdpftCbuOhj0OmZN1STXYBYCDhL1AC8eI3Cu1K3imq8ThUk1KZkrIWr4tgmgA0XNlXyN4jfzZ2xuw5rmXUgTAztLpvVzyZSjfpW/adodSuYcKt1Hvo1C7t3pmIUQ2YwBzmN+OmHMBo12wkoQPXy1gPKypc0nsufqCHHImRJuJnctNB5WY//T68zYOoZMC3vUx+Xe+kV/cN+KjoDKziobLtl+Iiq6ZeO8zSKqaQFZYPMJ4FP76WqpreVELYPoBei4bghtlXpF68g/Yi5mZBV9AV9XDyWZ+ADXyy6LoCEewwfGsvmZ7rJiMrhqPNOfkg/DBO7j1JqJFfIdhGzwGZTdIKeV/cyvyK48epKblNUKeCa/qWI1ap/UMcKwDfkrzG0uVz1ejL4hGc9fE56aly+nHRhNpV3B+oeEWWziXG/afaGdw/E3ianpL79FMsemYmkPxK5PSHj0l9oOemrJXaYro2TEWuyaJWcdLBn6jtNodF/wAbjTuD16pmdoe0LNtp49ELWeRX5qeR/nc5oTw3uU6RPG5pqgLNBjGcQL/r/sr8RS36KgxksthWPQuifqX9wRthVMegrXtFuYWYz0NEU4ZNNdb6/A6i5KxQKu1Oz1lGT5a1mcNvS6iAOUgw6U/yGssKbBosVDtKrloMPguCO+hq2ciXkYdyvdc+1x5c2VS+7nMuM7D9zenmEu4qB8NzxMmyuGJfmBJJK4X8rDrjT0K6brCSwsmBYH1lBw5PZaSMt7yX40l6YqxbyYdghRfeWC7pKizsu4LjALUbe52tqCsGTfH7esd2VosvQwqV1m7cimlgqdsXvy7YxVZSuni/9mVRUZT3E1DQHtpXy1BRaFojS9VfCWnBQzT6dmJXxoN834Fmiu0cQ63HpfTX8D+FTx0ehvo1vL8omcx8TnEuGfaW+sGpeZzM1GLpmZeI0WTc4JklKz0iC9prJmXT4iBhMwyWSgWxmqnaZ3KzmekPuVbApuVrE4f7BFQ8syIx1CLxD/1KdW+LmntmKqHpA7xmP/hmBVDyvRl5lSokGHVvpeI5lwLbBie1y/blF0xlzVQBmkVcGPZLZcvpbLlxjUEi3FuoisOMriAQmrAcnb9a3HOegbgxzCtRZlb6GZd66P8ADxCHQjMwnfFv7/yi94ttwZdMsjfENkPqesuyLnk6XyyovRaIGoO+8bXc4omTMt5mmmYv1i4rd8TFUTzuZm98w3LDzBBmY5GreZs/tUBvDUenH/4PPweaoYfVP8ETpXV1Lh1YRYuY7hKoyC98wGb9FOHRDU5muj4l5niXM9LjKxNTjoqUlavZqPcjqcRzA6VOJzK6melUfxOr0IrjQKu4EVLZctdyy5feXNJrDLi1hly/cy+ZtHLMcJWLssjuiLeWVVy9d53jVeYNEKCO9ym55Isw9GYeY0Le0yX9QTFhqMf4iGdq5v43CqldH9yoSS9Ng+j1qILB6/y0ZhX6uIeldGDEqoGD0dy40xRlb+ygsuzQOYrjqVZNdKJiYuWTxKixl10xDMdSos9f40/wvpf8R6Gup0UH3X6RXqXLGDTBiwZwRc1KEW25tE14jJu4hRuNspZYccRse088osdxlLzxMcRohvMDFR1ZK7yqzHVcxG5j4mFji5+m7TOCP8bALsFdj8X5hO2c2b4F+Ll4oLc8SMp7JklbkHCMvGZQQ15pxCACtPM2MbkCwmUryt6OY1Q6m+9ggegQgRlTANg4cQCSdXXkeEgzYDbf6DlgrG0YR4FbjvG6H5G8fB4lutzuNMcmZb9XUF89CIKZa3WsgXXmUenmsUWNmc9PAj3DVHa4hz3JQe+9eZhqNgsBuvJ2lUXM6BoUUbdOPEp1lrW58/8AJfo5j8vVnvAslYmRIksIT9babuSqZcAxIejGZgpZdKfFwfocUD6DEb4Ql3HQBhYh9iAdsC5Bd54ltWnLp8tX7TZ/1S/KByBZeG4huClXWT4GZWx/aDU8/MIl8l7Zqis95/F3niIJ0ngaiYVud8DEC1ENQRnJIRIVh0niVt+HW4BkEzDpcqen8bh0J6y5fUh5la39hLlzU5i1LlkN3aPIiW8xoxaFXcqChTcCZjZmUcYZ5mXH4jghqVQ9FYqYMTGKiduIveFpMbjbjoS2L1/6iUs73CP8UBQHhgIwaDBCyMqvjg8yiqFR4u9MdywTI/tQStV9Av8Avop2VH3EgOoCK6MRq5Ly+h/bKFAAPHQqg1rbTZ+Zm37V1X+A9e6WXAg7AWv4iywQ0PCVAdoPygrBMpfQe7+Jspq8nF/cvvHbmNyHJ86j7T/Rfo/T0MQdh+ZEvLX4iATIk8d14PzFln3RK/I4PSYNkrEovCGvnTGOr3m6cnh+oIIRqrQ1fokDyIetQfBlqUBoDQdoIk15le/SKPOJ4u7r4lby4Xa36u0poC3AY35YdcoTQ1pzN6jIVMIvVbmuQ7HEE+JQ6ebk0HY3LOAAUSkYwp2vydtkQeIVyfBfk1FCowKc8JnyQi79YtnLwA6lFagHk7l8xnILRcnAfboR6cdMQ/izWv48zDNZR579Q95csgyyIZhtrUVWF9DoBlEqVx09Y2xuXnM1K+ZlwRW34Qzh4nEOZv1jcrXaJKpJWMzW/uYUvPMH73EbTm4RjDqTt6jRfrwHMz5fLoOi21e0S75kX40PaBAcxZeju/yhB+X+roLH6bh5l/SWdwS++oG/9CP1fbouYP2/KlrPDfabTMfDCC7P6uXGVT6CkD+jz2EYalYBWV3LRNq+YL6Kx+pQeh/WRuULdsW/bKvilerl/MvMXbELVDq4WmZ5nXrTf3C75H4T/c2yub9GYlwj6YPeFfI2/mdlqftO1AvVQg92Z8qBGnVwHe6I8hmfcA3XrEte6oSyKXUnpN/kb3F3F+3uhHc/lX/JvErNw/ln+N9K/g9Dp4ay/cWRHTeMuXAmOOjKhrErrUqekGdzdkGDM5xSVcMXDH/JzGyeZmbzvzOLYyhKZQzaY/sYIWvzCZh/gLPBO17f1AEsJzY1XsEo3MS9guHhrD3t0M5ifj/qXds/sdHi7/gZhRF9CiUKQp5Bs+SXqhP4S+iCOVz1QPxCT5LfjoYvDN9ogd7zdBH00dPwv7h/FJcednsxX9J7EKfxLzLC1HdlIBHodvjMDXAHsV0Ps35kAHwr+CKaiF3Qp/E3O+7DTOYbh7owuUA/MTJiF7sV/cx9GHwjlHRO35mEt7n9oItZWi+558Swq23Td4a3uUKOqg1oDbM5Ts/sBxO8P4Df9wskX1zSH+RGVAzLAeH7WGM/6szWZUqzHXnr6xM9NMGJPTpz1ehiOWQP2SVZLRIkqV0uuhNzUXUqur9SzmY1LJnRPE9en7np458S3cFhYpjbMtnaU94nPviK8HJfCkO8IzmEvpmMfLr+/SNlq1SPcw154ls98ijs4Y71udxekK7KciR5q7hVHbFW8rAJWhI52r3YugBsQaT/ACGUHIr2bq44gr4ZW5wVxDAWG8VpMwg6qYrDhPpmWFNiPGy77O0b8Tbm9qr81FcKiz3BOW7Y664kqWL0sSO8gvnPD0sxOGueFWuCYhkA8op47MwcOSwnqOps0RlpGMGjvGC6hlmm2ClTrbHgbp0kbg1WbLk8HZ5lqJ5LEYBkEgcKrXi44GKA2C79VzGHMrlENlf8uKaJDwCr+annpKb4fDPaWEcQdU8eZe2RPytcj6D+4bkF3zZudjgZcWXxQKF92HeFSdxKX6jV2RM3MG1BVgL6Kv0LH+o6kHMrM00t/iAbXZf9Q4h7v8nplQL+JXLHq+57ypx3eKcNeOYN4REsZjyIEvEhfhyU9jxzLHtF9av+4/ZUXx046ekC44nEubifxK5/g9Tpp5v7iVUTMSVGVOMxloweP4PMzddLnmWety69Zz4mnM4mdcdAzTMwD5mTDDWZjU4hhhN4Qob+Uub9WyjTtD+d/wAL/nkHBI1vqy9uDvyQdgX2jeCvMP8AyUtQnFkRyibLj7mBA7MHwMWF3LufV/gqam7Vv3x7T/7v/Ypi1hwV2tani5t0HCDRuHplA1I1YnpeCA9AFKbine55+ZxTs0ZeBao2+vrOMpDrPGJQAC08HN41K9alUGjxyeIQrgDwOod2gwOX7kSkLPa/9GYmKqdu/wBxe1NuJfU0xcL/AN6uokDDeDfGYAWqLuB4JZ4yne/eFbdseN91M9XpUqP8jvM8fxcdDv0r9XpExGJKlSpUqUcykg1BlUmI5YJWJzL/AElGL4hGbPM9JjmeJXaa6eGD8E4eyMxzArMclukva9kYOIP/AMNfycS47lyszPTL0rpti4FkNHMueJZgPkbYSoAhmsu4nPRuE7XASytDgK/UyoutjPvF63qGAOe/1MBOWHes35vcoKIKmBxCztNhjmpq+PpXKe1y83Boi8Ru5bG+enHRl9PMYkrv/AmodeI9Dpu1TexO4nieJRKJUTtuJGIVFQUcdAZd+8b6f3B5YYcS+8sZ6zDMa4g5xqBzDO6Rfieky6gysZniPCcRr4Ufyj0IR6n/AL3n+LF64jCXHpUCpwkA802T6nux+jFvE1GGyQ2GLEFSxZSNfM/SUBFuczieIU8VkS5IcX4ml5Ku/kiCtFZvbMBMql7N7s8+WAqjQdWBcIsvIj8RR1qekcfwWX03vpx0voY6ET+DFxcHprMBI7jN9d9PSVKuJEYkPEuFnMvMuHZh4zHlem9RgcxyjMnENWZlZhnMcSzcfTKph2IZuYZ7JVOOBKVYfzvb2jeXWLM8KE8X3anphRa9TjqaTsGS3oZhwtqExfVKhF00RProiADa4JXof25nlENx9RMzW4xSTwRAooPJF5hUELAYvaXcqXvQVzpoIg0we6mMzGiBZNMGRp/ZBf7GETMYSo+/4UAL3b8EuIsCzMMb6G+lo1ILTeentCaxtHCalyChO/8AsxU1CvfdL/YzlQqvp6GP8WFxjfVO3S4R/h46m+h+0vz/AI8R30ZUSblRJUehaXMntCxlNVNekr2njp2RxmaxPSPxM7OZVPedk0qVzGs3xLjBK3BH+K+FuO78ea1Ds/kwtznLRz3hCRpdIxLQ4jkOB74mg1VPUuEMLHlLoPL6neBUHE28u4SKRlmnh9RjDF7jcl41kZtuKW20f7Lgnslron5XMoI1wGqgEvb5bNJp7Q5i+Cat+Iww5HId24vggnEaffqsA/QAnLTbFOklJ+grHhW6YchT6zsaeGWIOcy1YzinL2jp9obfvdwlm3+YdnI7ijJfkA+TxyRnDxxDVAYjarQoLbROYEJXk/yFZucw0Ow/vvEDiOErwFcQh8X3BpLOT0lB7Ejtmx8kdI/dpwsA/ALTgcsdlQsPZ2bbgfseB3gfs3DsFs4ez2Yk/U0RLe6wAoYL2vYOWMitqifIOI8gdhhO4OGLSP8ArcnmKoU9KErIeImiH5p/bMKgH0CoqpQ5tW8G8TEI79dlPbUHonXUxE6Wx63OJfXc46N1H7h21B6bodpuJiv/AC8xOiSu0HPS56bl17y5oviFt1o7xMzmW3UVeOZVFSghbiN8RUSmrJWImkht4L6q/wCSmLnoxgTfT06eqV9vTvL0DpWQ4s4xNj3L4Cf0vO0PqaiYPQK6HYTV81B/jWj1F9aohJFuPe2j6ItTIkpC18xs8YDFcXotfEUCLUcTh7szU9RRKFJrjO5ZslsrCRVsTjiVO6sghFK73zR+JnqOioIu6Oa0PcjwTg4Dv5IVf70mPlX5S5oeS3e+Uy7jt8KP7lx/21Nk7/yiDPSOxt/UojDKajwhae5KhScUWPUvHpGp8/0jp8UX3QgBntq007pmCZsXYSlSt4pwmaQJq+XyKYOmAT3g56EDrV8xTn0jHCvZfB2DghCCY3rMM3tf8d/LpWblxzGXLLqEqMO38My+tdCc9BBzcJiQDfMxVdef4lzx/B2lVE6D+ZnUczmiGKl9o57J5IWmIblfMrSyvmaxvvNlQJbUHHiIJxnO3SvllTGEYv8AC3JuhzaPTvEX97kO3sZlXyLY3wuvaAj2r9EEpmyjvC40l9hHOTqG3wPtSazKnwpHpYV1Xuf9QRt5vcS4qDeJWGZS/RQMxlbDL8Rjuy/S1y4HJ9uFt7t+0qeiMMevb3g2Zap2+KtfaLKB1gQND15dygvf8xEeVIRzWz2CdkU8gKfeWfYz2wiHmVfglVo1vrSPMAwPKKNf9OHP8ef/ADf+Ryys9XcqcdMTESJLuUWoFRzEhV1GV3mOpPEt6HS4xHmO3pB7I4l6yokSVK7ypzUqBKlZuVnpWIkSJ0DEDbKgOILDErGYMd5TUPE3HzMSq3AoqOOnIYNC8NQ7xRCB2IdHcIdLOhldCmF+Jq+W74Y+4gYAbWanqeg4+iCTpB7kzWpxRcvqPxDVgu2gUDuP56Mojb2W2uwZYZJJeBpfCfcWkEt5th5HiMN2Sq6A3LDeo2t2hecCwfAAmAGr9TESesovAsaN0X6uvSJ6ygZObnvZ9M5mTLgD3L4/MyCYzy/8JTX+goyjmkfaW3Dp5DH3LH5PyJn5QYjYMB2IgbjT8EV+7/MGJ78frbYeios99jH3NkpeINkSljN9kTfBh5FYeAA7KWXxcsBM2RZnE4uEvqMziekqJ0Ykw319JTKXLZbcfME68fxZnmDE0iEe35YcfwJKDoHQnHWuOmZlYk9Y0y+8IACGIOMTmVjEdZhLJXaOOjvPRe2krtE7Z9Zds5/FGh9OhjmHS4BhqWK6Aptx2clws3diT2W1rwRyDAtauaKr2g9Ly5VwJo7XSzBXw2mNeb87lKGbGXtCMHEebVp6scCzJKdhoekEo+SCR2QmbGZ2MzEXYPllKv4ips7XFPDZTwVNglariu0YRK2o/R6M0lvRocGWT1gAQcOP8mZ+SOzFypaxwGglpuFPDLQMiguro0y8YXHL9br3hrEIcn0cC8r8QFxUB+XuvLOAevNDYn+SvCRxQ5pA78xJeiXsuKXPquoo621bwj2ahJUmbfxXChbDc7tjuuw1M7pUFWr97ilqc2poLri/MwYAUQtWPcYLU9busP06TQ5oFijbK1EuAeT7ZZNbyim6d61GTVh7JsT8S9U+3XKHI/Uwt1xbQdld4Q8prBBBSrB5JytY1KCjA1CkgxjCXOZfeX0cErq7qJOZXR3EuCsM3/N1iV2+YYzM7Smf/wClmeZz08SoHQHMpKOYkrMTonfo9KJU9YqGMQw0y8o7l4SDdPbod5RCU3KuVmBXi4uJj+tiZghGMJ5/9VW56xlsy3BTDLcMmQX7qPBzT+bS5c5nrBj46GwBg3FLfLrcUyutsXuoDqweGZFPev8AkAoTsUlpizvJaf0YALdNT8kIVQCiB+7nMVC7kPKcAUD2g3CqxCJzKz04rpnmXUG+nGYdPMYkIxnM5l1mEIzx1ZeMTBNEsj2/KxvrVdOJuGdygiTJRGFajCREld5U/wDsFjTqVi4Vdwvc2d4fBC+eJePeGCpw3Lton1KqUVOZWJyP2IbPYQjOc/8A4ElcxKgXmWONcXu2BuCp5gTUyp3qlXwCwyJ0bdTlxzuZDAUuLNLWEYZtFY+GPSsdC+dwgbdhCvZWJAkNzbWZibnmeksjmZlVO5lupirjUB2xld6wRCpeFzv3iFYHSQh0QiSpUcvQO0GXMTEsjHtCMAykI+Ybx0Ot9FcMX1Mx+uWeInaPS2GY8ym4QBPuOfWAX4iVqNphZEYkToax8sC0cCBmJmCOJniDRXzAz0DGfuVU5rpec9BLqU3mEAP2ILogjG7z/wCzGGej3g8QFfwIVLps76HeekJiXLgTDktp+ZR+7tGGZz0Ca6Vc1DEuOMsaEzXa9RR2S3Nf9MF7UReL3JUdLZlXgvwRKmXVjRjoziCdCMqJcenEYvbpXeBU4thuum5XRKmHU46Iv0/2dGPRl10FIajUL2npEDEyyrZpLXEuGF+5mDLAQe0d3B48xcS4XVRx8S2oyxg8TlKVDDiOCo/0WoAr04hGJLhnoPZnmkMwShKr2oisF2YD3ZwxKuvt36ebbgH3LAnbUggLA8nSsz3Z/JjVmeK38XEsuG+mPl7IiKVtMn3zjJlZzEOlkvME+1r+7mkij6Yo/uVnEVW9j6RX2/7mPaU3c4vobOiTyl8kMsu7J/sIKTkfMGFy9WbnU+vBMgnjVBpqz1gV/Bcy2MZlSsXkXXtDMMb6cxmyVUCPSr6vaDnP8WIMoSYElrZvg+YjOenjrmCjBv1h36sJPD0vEauesWjmU1CLrLKOIyQDUY6zcMWsxNLpMT+5UVMdoxeoueUFK+5uMJllaph+9iVsrdQ6MIHRg4tk3fkiZYmHP/wl6QWQdrGlbX2hRhrCV4r4/EfXbLOGrd14H1gUSpxcKDgX01BedVIx6PDA5CiXrWm2k/qMrDSVv7g+pdeclFmx3WoBnZVHCR9ZepeBG4EvJTEhkToDbDCRoHlk2K4IfuvdH316THCS5DttlHiZ1ToZ3eo7l+rid4AZLcG417ncD3y0+8yiJMRV0gdyOZRduUqIUU27zjaVthiqo77ldnxAc3lz729CBfJBdhwf28TJudDr4dnsRBl1l7OVaah24re+x/jDjja6AHeKn892h3BlvjOYZ5g7cz07e8bKkNuy0h479oQ0rRpIvEfNrAtZTCLgCFvY3MzQjEtXCRkKAaS32NsEohwsTxbUwNBnwDipbpcuxp9RmlImBfvcXY1a9B5rUAnx4lcXx7wvklHK9g2sowd1LD0uHLwnioMN9mNo7lnpLt7TJ67Nrjl+YJQbBb/Oh0qVialxzLz0rH8Dqxel1noO/AX5miYl4ldKx01LcQbLYIvQJWajjMNZiOJn5lkFmYtpVswizQMJFyzZiViHZAagP5QbXEoW7gGzAkbnCFQqfsu01niEYy4dCU//AGCBNIgDwTQ6VehGOsJ4BaPgqUZiAnQV3lGvck/JT3YXfeLddJ0S103BOqBUHsQALWPiA/uaOKu1Sncp/He7+IC6M+IC35WLbULMBz0RJduY/iGEpYX6kFYaXW3Hnkgw7y8ei2TCf26QVPz0JUff8LHvtj+EdxUkVjRI7BVfgnMReTD5r+4jhAcXaX8Q1NIV83p6cy+kxqQMUTioFv8Aee0UI4bHM1ad4p2ywNywz2102lvDN+VKg7t+UzGoncOHKOH7ndVr8RXBiu2yoNeXLJZQhTJ5babWFwELZRvDxbKVBA6dVfi2YQrTGq59cK1n3iXP/ji8Djl9E10DDX8K6bjub/8AC536F410P13aW46nU3Vy5tCa3Mxz0/EfHM+mWpmX5jXUMNTad5REPlmWGKXGXQqi+0pUAgJQ5lLqcShgZxK4P2JQplUIxniHQgEOVLNL0nqqM1R77JLBTI661GR5Z/0HLDQPIXp67PgJ5gcAPwobB9PyhL5XV62iQto+iVUdtwLCPNYftjhjrTSu0aB/cPNfnDE5HSQkIFhgJ44H3EqO4qHuPymC7D8OifV/PMy7D89DjkIV2H5ng2vQCoS8gp+JQ4mDiI6G46U4H5Q0Pq+VlWx3Y/8Ail47t0I7QfVppG4EbWNh8qu/eHKKgannvBavutnh7Rd1Z/DBR9/xEpMHETzDpUqNVCMTN9K6Yupv+GoXxKiW56GfgiSVmAznz1ovoMGzpmWQxrpfT1loZRNwOIYQpLNQrMMvpMVL4czCoMzOoFYMQ8zxDMuifuu0rHIqEY7huB0sC2Upxb4zjWyEN1g8VWa9TUBqNzkMHofzKhDFUdAbY1hp+3d5SmC7lXZtX0VKHgg+hcfFlb5ivUaHft9khuyS3lMA9synMyXLv2x9wzhSq+ZgoTO2BLPiVCCTuJcSSPy8Q8k06+/DVH6ub9KR8t8P/YjlgX7wlsMOX0LYXjl+ZRFQ9xIzPx/aYRCXyFP4jFsyHYu/pAxBeYjEqJxecxxM6MCrx+dg1y0yodqfeCo82+0J/AC/EokzdvzNYjhAZ7VASU95yIyihFv4vZlXb4Kl047kVwGT2/6gH6uHQnhLqXUWJc1GPWu04hOOnr0SFSrZpHb9h+sXaVi4q4dHoVKpjcAl9Kqalz0l95XBqVZCzBucHQOoM5TnbFq7ixfaHc1E8S71L7S9TjpeJgH7VHkOx0YwDquPaIUjxa4lRw/H/ZWUcxtazbfRPykdL3HiDO9FDxZYxD6kIfikXE7Tmjyc+jUJ2De6vHjxFgjl33jD7zvy4l8MGPAZgxsl6Ibq8iQrVny4GKB5mnaCw28HoyxHifLPKJOxKTG5DAPBdy6/uCmTTi4xJLbsrvHrDW1hXbsDBPeHFdQGT3VdHiKCpBzFr5X6jlnM7cI3uUj6yqsbZoMAq7HmU7D4ueaHK7cTS+i7VQB2O82CJjURsfPmYcoucceHMITyuDWgsz6ysWStcyOtQzkGPt9Hh5nGhcnsWnteobefnj3NwO59N+fQx6Wx3YnAX7rwaPEYzBy1IPuXKMO/Aqzwx/XpskHCHZIi72tD7ldFD1XaeLhQoTkE2PpmV4KoclGAO6zBSkdi8wWk6SxD6/8ABMurAcm+K9NQSDYQFOQqr/mWNRi9rCr9agsSE0sqmoTY7wXydSujn+LfEqMJfXjp56PeEcY1LVmYrwD6xO0fPS5xUO/VOJbUCV3i1iYh09JhgOMxsARdQtywEoh3TPObitV2hi7wUvtBpiZaItbjEHEEltnQzqK2/apfHCh/631uXLjuaQlg3B5jXT0jPWM1Lgy6itxzuFEUdwxqYRHTL2y+2EFUHYnd0GBSsLi/eVM5v21ALXpMT4lLlznEFE3Y1hIX5svpj1F5uxffyP8AY05cqqo9BmetOI6w7LS7m7MxwgeEKqetXPW8B9VcwRgU3hmRDXb09I1n526ekddD0vOJf8q/hRLjLenOZpMO0B8CZiZuGZU89cdAO5zHVTx030Jm4d0cq5Q5RRL7xDiaY3zArETH5hQ/qVRXEo54lRbF5qCauWuoWixmI59ZgP7VABmcP/xWXXRiVGBNT06eZ6x6PSpUTiEYr106GCEsgWplqz4R70SltS2od3hEwotxNdzv0Y9p5NJiTAe9GYFHdqNQm5piABBvcJzHodGesSVmaeh0xrp6dMxDmazwAz4ohU5h3Om+niXDcHmBLnNzxCXPqJsYAGykpWLQSprUJiphHjBrFLm1+0WVdEcO81gVM8Qtlv3Lx6zdP0ItvZ/+G7alDKxREljVXwCrPuY6VPSOoZ6M1vpuaj00zjMR67VDjpnOIeZzHd8C48vo0FoehUtHGo7jhik2qlRXgOGI9EgFU7NiFpEhxe694KXj/cC4NFTEACIbA8RZcWDjp69WDmHQa/hUMyqSazTa93q9GHaekSVnproGZ6T+uh4lLiX3l5mZTpzMsfMF0yvqASpxEdsS7O8b+lVEVCxKLA95R0PB/wBJQ3gH1KFTqX/A6yXphBDORGx3wavzAJiH3tWaJKiE+5q+O87M5qf0UX8RJLzd+4woAWXhnHz2z8sWNy1gs4nhH7b8RmB8FX7moU2asj0mvTmWL2pWqDcoyPSEqHQXdCz9lsV6NKl9EBDCTpuH3m0TNSl3LGUw3UqP2LsZ+YqyO5YlVAjVWXaPzMp6EGEE3NaiSsaqczCnn86M45OHqj1qBogcr0EvOEHlYtEo07M3zGBO2V7xAhmFzJpj7GoTSgBe881eaqConTjo5erAz1rv1Z6Q6aE5u/7HW19DcrFk01PMOhrPTiVKhMc9KnBc88dCf7OZTKpxKCdqjTK0SoFyoEoWZrsCZr+F0f4o1aKO7h70EU4Mo1U0fNrLRT+4qVOXnsHlcTBqLXgODy8sJgCgMAHaX7kK+x0zKp1OjWztbhmAKjkAdr4RmcpdgIKKtDVtSoi8Bl0ADNFMg8942BB7sYHvVQJ2S1KVf5me5ldgCCdTjpPGwCl5uHu+0bqSZ9Li3NGoJ5qR48nZO8veJeheyw5ls5GqCdoDV/EqFooUsiKXAVbG4Td32EKO0dEKKmLNWZxXacUtuUbPI7xJhE6AiJidGvaePAQscfk3urbANWySU5Flf0xv4KGrGmvDUthKDtW/AOWFb0cyu96PErOdapThDGtS8QFp0Nj55lVNxbbA3D3HPiEBVefewGfdYAqr4twXkY37sMK79XiApxCF4OartxBYFVVJa88VAoZaUwfXRhKrjUL5iuTSq1/PmAcMBXdV6SsbO7uWc/1sQaW7R3XBMdRmzt8agnMYufAuz3lEGwYkxroefRcQ7YqCrHiODEtXgI6Ymqpum0O8Q6zygXhvUAtCI7B4ivV/mEeocTWXV/S3UxPSGdbjvMSpjpXmV0zLhMXiXiDmVKzn0jjXTiVxPM9YwKcQzmYPEPEa3MTEq4L3Gs9kZ0Z6sIcwUTteceSLkoewHmuzKOgbdns8zUQz6B/rKXWBfJfCdunYH9X7maQ9dk1t4i/X4QTbYfYK/PTf/SoCd1+Bla39xORv+ELj0+oY+4ToaGUVtS+YgflSNBeSrB1o3RXBCJQELzVELnmPVr8JvAWoDae35SV7VA/baxT2IPgLfbLhAEbCzJCuQAai+MHguJLFGnPYVnO4L6VD9Q0JZff78zRYUa7uw+Z4lTh/QXPsZneGY82V80RakJrm0GK5V7kFOgBOAh/2B0lND0Jfuf7Mx7X9UDOeZ8P8MZvLuavD2JjbmYhFN5SllgptX0lAVjcGw+xgrYfnEDKsK7nP4mzoHNFu/uXO2Q/XxKjQ0ek4zKjmPSulHX0j15mpMP0MpR0PPVUAfEe0uHTJqN9LeJm8zGoVzOLmaxDJXaYwRTfT0j3iGpxKiFdGtQmScy6phEHBKdM9ToqdZHD2g7g2MVvhz+YtYJgCcIzAkr+gPuoq1IjvTn8/wQDy/RKk91/ErrUJV+QZ9BKh7fgjfpo9sylohvzj++ggsdWfuyXcJ9kJu45CP/3hJiOJucdj3Co9GaC18M2HFXsIqlvMOmDf7eiVPat/CVuEI5U/YSH7Bj2yLmb6/wAI9aofruY0fuQR12z8cDTf5ys0x2x/Wxu17/SU3+PykDsb9iaPbD2TTAizTGH3/qW0DQafZCIisTVdB6bmYH82ZnM0Jw/0UoNSpXBDMKDMUsexmdkZzO0Nz+umbziXbG1qHF1LaqWDO5niaxOcRis9DiAGprunOJcHE3MS+CF7icoLvwfibdcy+OhDztB0VMe/TZatgy2qj5uB84Wm/rTLZTy8HN6iQfgOXJ8n99LjFOiDOXd9EuXmh7Wh/Ucg5OetJ0Ety1PT/qZL4rxSQi6r72TWMF2sKgKxllCnENobX0bsTyc+YjJEH3fZ3GNIhzrvk0B9vYgrcyrShftMggaO8DMcQWz3UIFW0r2EsFog2r+lDKHSqUAYz6kS8kSp8/rEV9Bw94LubSbYHtv2gcOyYRlQ/a1iZ9AOl2hU8tGT3IQkg3F7PeoapCJbGtztrr11Dhb6338ampf9mI9Ny52APqD9biWiClqP0ht/3qBbCNofhlXt/wBSZDuD5ENXtJsoh8g1Nt6iVHmdAdvt58QYwFnCLr2iS6hHLPHQ6XMR109Jz00JyMv7ETmbmYDBmohzENsc7iqgYuJPE4mqinRuKy6PMO5BzFwlld0rtKzmazPMKy6vWY9JxDBURpnhKW/sfwSZXVhTis9FFdoPYZJQ9KNRQHm7N3i9S5QzGl2ejuGJT5/urgQF5x8CYDvMWnvTt9ZusKvg9I65UWXqTSilWtnvUqL5gIPYJgzFICPZLiP3mpHuF3juTGFtvieS6s7wIyqDZNItadnE5AwXse47GBF5eU+8pqEu7oH5MXtpsEuwGA81uaGrtlmlVx2jWOBdDbHEod7kR+1S2MBTtGjBQcy8ZQt021jmZB7H29RLAasrJ8Vk/EBjFhvQ9cM88QCfa+vYgwSoOgjrsnK/M9Yl4trBPgdPoy6J7vqq/MJWeBAboYH6x1KimDbz5at6aXnvDd5tr3EyejCl5Vje6vbtUCoh312nnz8StAoqgbaayuoprIAdqKeJg+ORUeo9TwOC5YVk7SjiM3omuN1H4iKqX7Dfq1AYdg7pg/E7Y7/U0k881nPaslGjBjzBnUqS1ye0MUWAmhnPvUpsFrQo2HvmLc7ty5yY8S3cat4D2RzLXgskBvBFwarXbFB7G4xhdzEoldSMej0vM0Ii3n8iNcSlxAqGMQK1uF15iYxACRvHabmLlmJpNYeITFYizFzdRmtzOLiuKg5zMQYZ3CqxDzPvoPJDtMOelZjiGg1/hBleo9T/AMb/AIMueYxluut4lsbmZlFhSXMujDYBznwXjwi/6tfV9syqnnosx6zGpf8ABbxG0nv2m51d4af6UMaL4EHMBq7Tle+YWUt7hGZbPzkspL2XqTHzXwDsT1I8o/JEyL5vkwcVHxEqBXSpfMuEcdGZ6eJ6TVHacc3qjmWBjodzxCimOWYnESY1FiX7Sq3Kua3PHTFYm5fDF7wdXHEGJbRPEF4nGOgXFz1mH2mi+g3EVc0T9AlKOH+HV/8AxsvEsj/BzE79Ksl8TmcdENMPMWWARi0pGu9RTRfgEqBjM1LYqT/w3HUG+hNkrKnjpgRzvpXSuZQ9Fxz0Dp5/gIDZxNCNbv2U1mAQWwM5nkxUMNsXOJtbjHE2z1iPHTnptx14je5VFMr3lU9DxMhmD7TFzPGZxCb1DUIBeZ+w7RFzAkP5nSpX8Q5na4AIu1ZzwQr/AHrUqDFypUYwl3G46nMelt1HEsmOl+m7IIRy/wAE3Kup3ouogCbfgtFO7Iug7EP5MGKOyLUtWDEz0ZfeM8fwSVK7dT+bUAwaqU7n+Z08QEphrzALohREvMrPpHO5uJiVRKzUrFzMzs6cTd3P63PMxUqeWBRDMvNfMDGOJcI3qbl94M3FxP3naJYpQ/npijGVXQeWLwWkWd0ezdRfU1095dzNzLymh7kzKzpTwC/mEqIi9y1Ccj52flmVMbbys1VVuWx4vL8NUTZMcC2rG24GVJ5uXR24jAG5t74SbmshK8pS1L6WCJGMePqAsb7ZNhM+rBBZdm601SvMSVCToW1SsqPtLDwXbQ9ryxHmTLYlOgbD6wj5A6RnJKrm9juxaznOS7h0erHbjJub0bS/WLrBTDsbrvFNXuv4DLsZwlfzX9SitBWZsugMtRYmso3XeruY5EXQrvmDAuZIB3eD2jVvZCz6UL7Rj7QT0DPk5JsfvcdsVXQjUqvQC0LG9F3uFog2uAg30l/FxWoiOKTe5ZjJuz8TBlrxnX3XRaC7qE78MFw7PMR0vDa/wmEEyPQZSToQQDXA5ibtKa/UFi5WJroxS5uVK6Wy5ZGnrmPTLM103CwVCLN4ftDJBbhlhn4gEzDECwKU7xgNzQRjnD0qVy4lRjXWjfacXCoanFzz8QwXCsMxzvpnUqGavod3OJ+87SoOwldH+BEKg6rheV/qMcxCCb7lShseP8IrWga7Koh1OlQoq1d4JdvwK/I/EpnObyGvd+ZjoZZ+/wA9vbUuUru4St+tdGsQPyMc4WGKC068Sn0ADsGoaXbapHI1fmcLCrRXleavEvMFGXPKsJRXQLwFfojOh4nDlfVNwrogdAaOjJ1rsUOfBjEXNU9dqz3EMaiNd0p/E2RNPC0B67ZxVIE2uE58T1z1B0r30RBhhyuf2NEAfeM6hCccKHGSDP3SKEXq5p2R2VHzqxrxW/qOrw7GWUhTwgsa4gfRcDaaXYF1zA4DxUS+5FeLhY+sR27rvCw9o33myN7Xgb34grgmHLy+7AiSVO5Vl+kt3EjLYGvaaCNBVZ9IhDhbLh8waVIwg91Nr24i7JsyLs+IlA57gNCPIW8dfMR2rbe+YlBQSnphZzS1JOae3eUA2oq3cygQx1dSprr4h36Z6GepuGpm39VDAQu+jGRiDTObgys8sTEaYmI1xGJnHR6HzHlymGIWcSn0jqiJiyZhTFE4mbphroTJKa6O7Zj+piLCWw6MHoQjso/vml2v4JcGXKzgirxaYgONTgHZ3OSV21Y/16y4oPd/gJ+xDHR0z+xPID8YF6KVg+XSx2XoGYBQd1gL6uX2JaqdhMw4R3vKxdyGnwoYwN1PdCLMJa4IPW6/uEGx14T/AKjr9fDMQw2eQf7myyz1qZHgKvwL/U3m0Dvv6ko7xPtEmU2OKhu581wc93/aicyqfNM+zK+5PodLxEMq0IDUf0TAPPmMXOfxENztah8tQRoUB4K6YSnI8SvUhOw5PhiC6l8aJ8ws7V74D43Nawq+7yvqwQAenPWoajuesvE3/BO38KzDUy7P9qVcCB2iKtYl3KrUPExp2lDiVk7zxM3Fm5WJxKWcQ7nFS6q4Ob4lLqa3uF695jnPEKWRneesOmXfT0nGZsag/ocQokcZjqGehCA/RC67p30h5WR/qOGDL9CScWl0PjmK9Y73RaD3eexALwcKuPU4nCwC8/Po8zMV/YURg04n2l5lfZfhY47hX5RUy88pD3YPtg+wlmQcX5cQA3YMAcEAS1l+6ib2l+CT7JqsWfgPuVDmVO3tvTJ/UwqXbyDa+cRdyAQAE/Uy7wH5NYJQuXwX/wBQcS6gbEp8X/xBW83+aZNzGgW/nBC5hevSPVqffRUPf+6Gd99JFQxHdXVjwdpWJBZrbqnb6ymgXoMaiw/H9RBdxu2Un0IG3QxNqTkd/wDjEyd8VwPnMeLI+tl/X5S0m1QC5xAjjEDvGPTip4nPXmOo9XYw1MU5b7ZqczytOyykY1BuHyd4h/KZq4o7iTUMxY38wxLauOrINK3+ZaMFixe4KuOJggsIMKqcw1ANzzPSbhuC3ZP2HaaDAzSHS4MJ3ejb7kQvdLkF91x4zAEeeL6o6ihINJB4rV9Ynbrsbtlpyu7gmXQWa3mPQljp9gWJO2NlvxNJVHngKsV3hwzQdqzZ3StR+B0uXYlfczmAXRyFULewTNgqy2lW1oLi6IXJaafqUk1W1s9SVtgzeA2fZGQAwIbsR58iBvVliFs8Vv2hETr8pa8zdhK3HJiFqOeKhfZF7TV2l81co3Ks9TanCekWG/ir6BlnqGeQFOF93RMKHhoAeWZH7HcCrgcKI2RSJ7Q7SxQSWN1uO15viLSBGwsNO4whIWrQPVlikDVVZTwtwHheYtNiXDTmtdYLmgN742ZWXise4x6UTdroL9allIUHF5ProR86j0VfzKZRL7FMEijHEEefeXF5twGhcA+cXUIWTWeogBOC6r0lpLMxQg8yx8p+iVEuVvEcV7zMDkvPL8ahTmUOdGCzdHMESYGIvC8APtnmG7otLt9kmLZeCn2t5gCysI7Hsx6c9E6PQm9TicdKtJ/SZfqZlcRh2mJqZZdTSCU1iIrKxiGr4ZxRHzzPEe8cYjQ1FOZTcL0wNEL2l8dBhzCDitzmoOJZdQnrALgzaTPi/wAIGiFs0gwtgd+uj0Wui8yyOEYuP2j5gBgB2lqTruOx8KZH0yk9IbTjs/lLZvuYkerOy4YMAyDWGCmoZXoM/mHEW7MlAUQUHNFh8aihke2Grmu/6G+iBaDu4gsV5Dz6iNBopp+HEwDOrBV3olBQdGq/cUq44BFeGIko8oujWgaFvzaiUjtZWPMSGrnrEpjxBKplJymcnHYqteJg2uKKOyVAwCVnGu/DNPnGs+0XkV//AKRKaeU413/phEC2TVKaeP6iVTbv/wByuH044at5nFdChvwtjr/qNMQK8AT5mz7QhHVvExWN0aFbr2j/AOV0q80+YKAwWyFF+WJbtcNt1E/2moUX56LF4h0zqBKjKmY1XTbEiTdMKv8AoZVRHiHD08wM5mnEHSy+JWIQO3Ql2x0MeI07lyrjdRBPSGrIqsxCoLqDmvxLlAJceULjFwYpli0zLpIGTf8AhHR7HTToOldHUX8Oal4np0X+BCV0JjUTNxnrHpxn+NweYrzLbhc2zFppMJf8MxG4EWujMLYLYSr8TSNY7NT7EZxBoi3uDUVGMMvOZxGjUe5046eSDnPR89eJzDcwfsvxM1O78zbMHLKvMNd5+E8zT6waKe8uoYzoJeqgYjeZuXbmOsQ3HuRj1gW1EcyvMDdEBJTiZXPtDOILmXcbK4g3qF54l2ZljuXm9w4/2qOyux00ghK6qbxKlLGcyuqTmPQuHS+03Cb6Wdd9VxUxUqEExmmZMRMNxoDOaQiku8SzpfRpH4TcusSpR6wvU95UV9JqvGeIAgoMAdGamkehVZi4lxMHEJ5mIGblSpzjotMZiBmKn/Sog9VmbrmHaGcS13OLm/E5mswsywtxE0d4D7zLn6iNDqZdTnErlxO09YYa7wC4feUGDmIXEuqzHByuYJblLuD7waKgO5dktdYJd7g5izd/wTSCrjBDqxbldXM9Z6db/hfUOhLl9B7/AMWVFMrobxGwnMTMXslxJeWuIY95gQTLjmDMCEHdeK7QxDGZec9AXiZIMupxKtuVEzKrcJxX8NypUel9BeAb6YxXky4LDvHFRjj/ACVYjKupnTmUdzzKszxKaqCuY2iSnESjvEDHKBUDkv2nGZ6wnaUZjRYgzsjhGlmZaJgHc1ggX3esy7heyUQcT9B2mleIb6EOr7Suvno9Ges1mDxLz/EZ5mJUbi0XFi4XHpuVBJgADvF2wlEqNxwDeWXI7TxXkl1tPHM0w8RcSjNbY95bDzHCoPfpeIuM9CpcuyBzPEanrPPVMzFTU2zX8B56MpJUEJF7flRq8cxJrMUH4l6nGdOpkeYXuZuVkPm4WK/EwwSlLmdRuW3jcQIe0dZm7gVeUsRqXx8Su0w5m8ypnjcDFkpMyu8ycwofEo2yqwSq1qcY5gLhxNPt+CBpZg5lQ3Dq7ajqpfTzGc9WWG5V7gQBo3bPzH4s0thZx156XLjmUVUC05qLNagxLLgGw9BCPoBTOjVYjs+d3pwR08QgkCRnSHrKFX0Ec5bUiBYOJd9C2ziF3MwnMO03HWYRa6HboMxtMVC+ehXRsyjiViVM30IzZDoOZ+u7obrcumFcwpGpWA7wYjuyVUK3uVimDEEpzKsKiVFartuU7iq94mKY3ozEcbuADtKMBddM1KvMCFVmc9Cpr3iB78xAO0riV3lp+g7T8MN9CG+jHpVb6HaZmeZUpuMqDK0F2w4509Y0El05HzDP/ldTPQl56sxHWJcWAcwMwoyuAbWELJo5AiL1vToKYna+D8bgDZOGoobtnxAFkwxlm36MQMeFmfLiOGNDmXGPN7S8RnPTUzc10GHZOZx08w1cPMoZUermEZncMyuldPPT1mIWeEuV/soWcxZbuVyRX/YK3+3C3MyZYCMGMwHnmI8wKI0jdUbSnTKlrvcUwwY41AMxfT7QbjtKGZaY7yxxB4g2S7YhFZZQt6rfSurRuLZv+icR2hYjGEJfTTpcuNVBJpWFv6hgk4AuvsDcDrOn8pTBMqPc/EvdNVbjDHGBQr2m6uYsH7MLFzmpCH8y3i4IFG+YQ8MH5Eqfl+YmumJfML/gxrcMw8QxljuyyHptgwYcXmoRkV23LyC74J39mXTQL6QwO6DD3bYvQ9JsKrDSw4mUTFagGphlDqo65oMrdsLHrvrcVy4S4RMZglYmeJqEqVNbjuEzzGqxCFxP4Maehlqc/wDZQuFSmA2MDXqhlTMo1NHnWY0LJWMcyvZGoDbylRzEb9IlNxzGtZXEpcWkMbib7IL3YXzAdwPuljlgFY5hB9pszDG4oEUvMM9ERn7TtN+DkiwYMuXUyXLxCU8S5UQO1wD5YQ5be39QO/MWcvTczJyv2lTeU+0yZEwvzu/wyrVp2xjAhJuhPgTFdWn3MyujDzOIZ6MvNM5xCNrtZ5cRpwYD1zNOC7dcc+DEwRNkYppb5Ualhez2wTFugp7Epi2OBo/2CdXcRrHZslQZqmKdQxvjp5l9odHUIPE3HcVtSppm4oiumottfwZZBm3px0YhKgWz9P3Ru4zWpxss2kBzomU9ocCFYeIZiidrlARFXEV/dTuOdys2RsWTz3xPQXMtRe8ck1uVT6xK8S30hQxOHKYPpL1BrEE3Lm1MuXcsS0dvu/wRkR0VNowYS45NS7Ytg0Q8xvQSPfQPsXLddMfRiOz/ALsx4d/tE2BFTbCsMVfo3EfoaEoyAGAtyxp7ECf0UXfggIa6SfIxD1Zf5C9xIQRWWpAe83KoX/AJ33Krh60tS2yNnB6m5Xae0b4gbZL9iJ80CUXO3xLpiO/9R7Ix6v5I+QM0za4zXj/kBnEB5q2+7HMUO8pKrZtrmUqiwPP/AGIZ5JfNMGwe8TvPE5nMvEuPaHmHQHiGZzLlVjxPPRLh46Z6Vn+F9G2Z3E7S8Cx/e0Rd4iTUIKaiuZKjRMh1UpeBNNneaYi1ANGKiEfERWYlDhma8vWaVzKLcdqBlHCYQbxKWrAK2wKYPEtcGvMFTB7y2zUvvNMy71FDcfn/AMIsSmJBESPFS5mOYGem5fRh5T8TNP0uBS5X5Si75jO6P1CfAT1gHP2HNcXjoYc4RD3QxgAwlOGZl2vQNM4vGOxoeWJaJenZaOXi3mEnOgPy93zGaQlZmZadhU5PTmoiwABy1p4YOZxAbLuPWV6O/oDRG3EiuZk6tvKIwv8A+aA/Ud/SJxatfH+MwX0x+xCPKv8AMf1LzDfQ5HJNLjhPMwDCp5UuCi4I4l5l5m5eJY9L7Qb3EhniLkOZgUSrJHipxUJU/qXLl9LlvHXE5xGLcXCXw/so+IzJlEC5XJDDMG8sI54ERbaRgc9hheuIHtMipjCyqvtEoEmR8I0seJhGhBE3iDF8QBBvEBM8xI2fErQy33GtM0QWpmr1S8XqAb7wxNPpP1HaW6RlKxHG4Bg5mbje5sxKlvMu4N6nMSMcfghnPeEBMFPyx6XzLd3jfILtetf1KhdM8Bnj2I3ZKfaDsOyd0W/BRCdaIPvgvd4jfT7OSVv4Eg53k2EqtxPVCwcHGl8wc9HfBflAlhSwWPmEWbthzfEqwb8EOIkva4/kC9ZU/iV3lhN7iv2ZR5JlVUahgDtF6YhNkwEwmOgZeJWrjqGfKKG5kUmEV9GMvEZmZrqdWOZU0R0/7WiBQZidTvNyuYPeVZhgWAbGE1F1hY7y3bAwhzxLZ4TLfr2hGJQGdf3G+YIf3DH8wuUyzyZVuMO5XLyxwuViG+5QicSqIprzDJmBRgy6LZj+5iDLHg9p5gJNJQbjhW+vEIaRv6ayQ/cH3BC0P15mfsfpud5qAterdR4jHFd/Z6XPAy/TFi+UKB4y0cx8cwVY7Sqv/og7Nu/KgozKOz+hUqB02+05fGeiCADWN/wTJzF94onwg2XOIpTeL2gk4LGPHI5nr3MtfcQ+HUo6wrjYR4f6uU8NFxPyyKxRuMysH7mWIS4Hrd6j54mZm88zPvPKFMQbhWfMVELv1ioUXHR8xocwOWVLK6ajcYvRepQt1/YjdX3z01uV0uulBBrcuKZQqiumXWsDKVTxNFxDn4TnHEDSkSynUTOIPDMGZS2wVEhg3z0wuGBW4+PuAalb7yyvWY4jpURgcXFA7kNB2/BLV6ZqhDU4TuvURDauHlNR0Fz87hfMssGHYcr4gF7oN3l7vmXsjQWy5UID8yXpMQhU+FIs1O/MtUMPb8yFpv8ACmIsMZ7n6WEo2zflSh44b2Wz8zTESeRV/JEqViJ0VUPESyshxPMsPTiYKhln6FymXhO4xT5hIuKfNRTc/wCEJdjG1d0uCwCOtrV3ZVHJMbzK4dwhRjqlEdVBi8wwJctYMNYhEyOnaFka5KWfKRexuks/frhd0h6pC3UyKLo7faDOkLrPfMDWiEe4wxrpVfwelTiOuhUmz8ias289axmVmoE8kus9BTJFZcHmLB2hoQDVzjhAWr3TbK76Q3g+pvMrPaVi3mAcSgAgD2gcvSYEBVORBq1oeciGOIntK19QLp2lBT3hZC3gzFf6mJueJayo0Y8dJ5ZzTDT7GfP/ABC5nEGPVf8AkWeisxPOpZt79ASqiMZVc15E9HEBdsq9wHAZXqguf/aBbloZVGxHn1IeZb0gLXxBCsHvhVQkQ3Q8L/Yy0ZXxaXrzOFRR9vZhpSIWEZTGjcv+B82YD4yfUnMKguo1ezT5mdLsf2QK1eI3YU094AebB6kc9wD4hCXMDxL18deYjGP0ISQHcgEll/LGtRZeYd4dLzT0rjp4nEwRjhidh2UivQlJoWPdhJiil0QU+wfU5EvOXr34SVzV6ADvMgoS+hU56vTfV6MTDsfpaHaVEnrHpdzPMe88TUlkuuiNHdicISxzrM7n3hZDcDonmDxMggiWZh4l1uDG4U/EDyBDEGiA0cQeDWxcq30jRiitGZ/uYiK9kWbi5n0cek8zYeyGUBfMpfzF2j46L51KuqPllyjKXmuxxHh+HHPXiu/mGo4mPnIp9QWrmYKbTadlk+0GcPr/ANjhmYUnvvDE6rXkS/F5l2VrDNYS6xZuomY+b/kWK1ozOrMYlsw0d42eSDfHloJ+mmNMiZXwq0wG49evuAjApNs8Gj1gmibVcrcqXa8sZ4hFNSlOHhiXI78MHzDo5gXID8kFbcr37Q7gdGV30rCLf2nzB7aA4jRR9SkUCtwa6M8QLfaUAVa7mrl3L5hZuOYL8zFywM7g3zsO0su4F9J2mGPeOiOB+JiD3lhL6X1qMdTPOpc8xhjCJWU5faFc7lOmaQ2zqBMy5jW42Tc9JmAhmXyQrBov5nM6gZNzs0O0aETb1Kb6iYxK5Z5matliWjAtRwyrueeZi1BT48y3sPxNfZN6JTBHNiO8TWJb2FwKwEAH2/pjuiA6lJuOMzWYZSxMWiQp3ATPRsJdS+gXUbgriVPYO8R3JQYKS4i6nlKjMoP4gAlx5jN5JXrLnFIgphHRjUWLj3sgTwPJSDPfmXZ3hhmXeZd+KjeZYMQFbiPRoDJdr7alHbD9scM3Kzcp4imVxEvPtG60CY3H4QH4QgTGR8ygCu0PMJbc3mZl56EWWMqrMruvAe8tZkPuwjGckoXtEsWM8d4iyUwS2MPpL7dMwrmXiaZgp0viUMt6kpqKeCICplBTFYiWRgO8Iv2mWZR3Hd6NmWJXeHaWC8xLnDP1HaHJAEYzInIZtKzNXM+bD8pklm6JfX25intmHuOLn3efDCtj1U/CV9xwB4x8ZXBB+UGCIv3D6E57MPU+1VMLmxl+/wBQ0u7/AFOz4gDGvWHfgfcc0HNEDxQr9R5TkmF9ExftGNSqohWyzU78z9v/ADzKmOKa29pwngzRixD8OX5ZbQYGKVszLpXDMe40p5ajADYJP9zkcqVHuJx5jFHo2Xt4mHItASrgDK+Jm5Xap8ho92OaJmt3tlPuLemAIGY8aNO2PA1Bcx6erA7fQNxh70JPQMszBb2vXzcHSVBch6jqGgVbcY9piX2g6JDTlv2II+Dx/mErCshUbzj0j/aBqCXQ0eLEfjmVurmAepuh86zFDHa4UrpdHkn2IrPLx7iWgH7QIjY1XqzsXKJyZoJ61FTMtV+ZAiCYSxL4oObjC390iAv6pLs7weJgsB3hNFAFVViQ8R+Y5tpDjU7ir5qW/fm6CVJNhxAGda1S2A2nd3f0TEO38vRMRl4VL4N3h54YeYXS6lcMYcbJceYhcPmDDt0tuc13mamdEGyD3hBN8xyQOCJj7iqO7oxackrmZbmJnUA1GKR+XR4xi0UmGYE/sR1NiO5HDHLuXEVGJdPdMBr/AKR13mLvJ/CZJrWgLxTM8TnMRzpbpfdYnpNSUjWyd6yf3E+jY7E5mDpGVV5FvY+5bzLEqVpnYYwaXvKRCj7ln8kwjsTB5HEbcnXqNQKVrbAOAna/qAABWMS0qToLyrCPvUoQbHEW6G+KYOL4vcdGIA5ErOhauRkfiHbWUczSPzLNQRSq9o/B+Yyzi+3Yev4gyQoaBUvCMnYbYYrmMeXzbx+JUQxO2c+veJa92EkLYE9TIe2peKrBuQoDu3PXXLAewcvdYfqHA58R47/MWFxHSzN+kW6pv9UraMRKutM4m0ftinAGKAtuPEGJJbNtatgVzCvG/ljkgmRtKpGJNA8ezDuzVvM2Hipy9TTjM3+1PpAHq/wI5VGOK1WL1gGtLLrVCK5fK4Rzqadjg5V0S6yQGjvJzCiU8VSoSjsCBzg5mbVO90x2rlwKLqu0SlVi8cRhvqpavF8yva/H+42Lth1PSPaVmUy9/wCSZrOYNEHFYRhULfKWBe4i9iVZNTU1DWId5XaDyT1gcTTUt1ChCjcpeIMR08wFF8SsXD4yjmImI0zMHvERXfErNQO8p2SoSb7z+KVI+ICiTOGszv8AMcxtE7K/5Rupn+jSK36wO6H6i5ggO/8AVVjcCGoTz/tDP/swNQ9YIaaKl/cLcwg238xA9iV9oyVdwgZh/cnKZHwW/LFl8kIbM34zOL4lCh9yS/3Nrg0EHytL3Elhn7CV0PSIzMwRsODgHoQWsknxr6EVZuL2gstmPBs9yAvIh3JxDS+Hk+YTuqfUcbDxFhR9sUMGKm7zsm+VqA5lS/2GN1FDP2E5oxLymQTbNI+IU0aoB9/LHiuJbOdzZ5qMu7X5owLUMkxXJ/FAV5f5Idl7jzAnyHxV/mU71+eahR0j5oqvuDvA8hVNektN5bT4tTzeD0YkX9bSjlabjF8r7S5zLir9WyGMRg3qf0lTbOSYpdU1Cqyk2JxErHaX3g3iHiazN7mY5JVEt1qUrUxdER5hbkgfcaPrAvDqYIv/AJKVRAR78zYkf+ZVSqgQB5gav2qYo+Olhjpxp79FtZqVthZCI7Dw/CIEIJ4/qXWTmE4t+OFRZHbMvLf7DB79+JMBZdlxRqPN32T08kM4iozyxi/f8yf/ADMSOemLfrULpqOPKf0izAKnD/cYD9vwIt6PWzb8Qv3h6MAD0TLcc5jVNx0QYPCVFb5V8RbB0vIv8w4P0qdgG+f+Jk9JjmZQ/wBZpEo8J2l/miruDLczy8xUE7XBLBNMoIci9l8wLXEr910b3mKiH7UjgdeJeFX3gybsfjMpJcJZpu+/iJ/K0aM4lCfvp8QyAciShsO8pe/upllyZQHpXOJeYqfx/CJrmespzANaQS6I1zPITccR9H+o7aFDiU4g95jiXKuXU9JfaG7myprLtj3moEybnFQwx9yrgBxGc95XDmVa1MsMozzLBChUeyYn+lSw8cbR8QXSVxCjfEpO8r6Ig4ajvhDfuKie0s+8UcO1Q0Lg/pNKlZ9IfZH6UPxf7wUYg5zuHeczV9o/yC/C30RjAvKp5q/Khp+/5iX2Qu/EsHNz5qd4+zh+BKuO8FwZTrD+CK7+tzLob5IIPfU1KJ+RKwQQqNTC3AEYg5ye844S9TL8z0UECq4CLc8rEouJXMsL3nyhGUviEC6KvhGmSKtFWrgERiOK0w88wAnypC91x9RT32MB8f6gTDg9yUDYDYWHA3BWWsPufp3CKrqMMxoZ3PqZ/r09NMQxJLGLkd+nueIVcFS8JC+Y5ur2eGGMvSbeyTxpv9IAPwmIv7k8TmcQvDzFr/QTT+Ed1DDcGoPMHNwaQZjs+0LzdJCXHlBphZuczTMW5bzLNyypc1Mzyl6qkb1DAsHHmGQg1YxZfLmWJnr7dNRdEI43uPFy9j2fjpOZ7RZmsd1UcQu8TaM57/8AEMGYd7Cj84SI3fEvjFGXkQYhK/QvRHumBzDbRb2P+oA+k12lt/mWe4i/KPuoB5S+iKoiHCfqOk5T8swH1fmWC3LPiJR4F7iXhuUOd/USxthRzCqbW16KVGZZbDI7cn+RRvBpHioZbd5LwiSqajuVksL1Sj7l28v7ZRNL7SvYonosPpKH7d5g3EVPJMx/6hAUniHZn/FHGjcQbLZyOj07yvo1L2G32IAwfde68rBeIqVu/wCyZHtYDUi2yA3dm97iP3WELVdoXywnnfhBPSf7EzhpvU01wyhljnTf0z3IS47GuJHtBolNUp37OYZtm72jZNX9664qHE8xF+D6RobJTmfiDWoPaAkRzkh4QDS4PmHJ7S6w/wBmbwlfmUkuZucXMkvNkc26Jd4I3puVm4crM1wy2r5iLzDUoZYqxeiY1FYpWeZzLNkfMBDlZMl1Y/ET3JrpptCIuo1eYcC7V/B3exKBz0/Hgf37y8SpZc+w6faGpCxMMxX5QGQc2+rVTDiYx27MY+yZMyoCwOok0KqPUCYSDfoMpHIRPMrtmBRcpREKaeVe6zK3C7Ar8xoWaZQ/pdyih7sMGYzgcf2ck2uC7SFMAA5oyvpENOZc4/BKlrPMoZTB+y9cH0MLUlvoJLALPUt0K88PYdnmNAG06O33OhUUZ4ajTzY+A2e+YSgmho0p2fcKY4JtOkX4/wCJe2SM70pB7x7kDkvtECZoMORmZ8fjPAiO+JgUOt4siF0/eL+oW7ZXbBEthfFty4OvylKztPgkGijr9C4GMHvsI7Dl2SZseqHRyij1Qnl5HujFXc32L/cH0xWR2wHANXlOSLmhAerqZtghH2GUuPMJQ/Y6pFgRUOFg+ka4zKNwhn3hrEtSLDcFcRjsnJUY5fUxFfEfT4nEzeY19ZhNOIaTHELtEArHqiU2j2JbnMrQgcRLxM9pi8zxKq67RjuovEtKl1dr3Nvw/EO73gpi05ijbKmO/ZYX4MzFfFwPTFEEKq6XWn8kqyBFyvJen2hKo7EX5WVa+HGzvujT6mmExnhq9IpE1ULTyn8ENXUqltfNx4HyP+w5mYWgeKsTDNUusZgNMoHweFcvFQ2vy/8AY8NvGf8AsIUBS0gayMMglYMv8DAC2/tf/YWF+R03w51EtwGLy30YPmzN9D6BmYhNhQHsHE4SMMjrvWd6axArQ8lwe8ES1v38D+4+mrV2/UIYT3/5Ai8CK1NGTMLnvK+GZTRbnXvXD6QDieA08jSxhbO+0+phOWYLzyfiPbDpz+Tn8eIpceLx8EfUnWIF5q8vaITCtuufeBuKVYNsu/idhwnAx31AuxMNXh3mC51ZsdiejAMtpZE8myAFj4rJeE7doE4DXb7uCLg1TsW5v9941uw0BsJeoOapgheRJlIe5t8ugjZKHVtqnNfcoHDTw0bM+IFGNr4PFQ5hGqg7N57TgIInC3bHtgw/KlaFWdxjIt7iYEnnxYc+80ucrwwwxXWx4ThnM3RwoLPciHClrt7M1JjL1XedvoEDmal+xXg5lpJ9O6Zimsjm+IhgvfPKx+JgZ3rFmjxfl6BDMv7pGVxKgQKg5xlC/aAM+6Zq547QseGeZjJ5mTnjiWLNo54S5a4irYjBRYBRBSce5MhLTu6Aq/ModStfUcJTbmMvxHTJj4jXpEGTMcLh5P7blAMHxH+pxME+Y+X6gtgUVC3ctLhksgtXBUtl1Nblwt9IW1HC+ZVGYNP4mSEDmuUPGo3DNwtlNXG6uW4inMH0pgS67ma7RV98ykLMQ+ZLxEXTKrJBpnExbz5lmIDQhVBRzK5smCkFxbZwgF8I2hGGYRCyPWLWb3TcxPp1I8XuE0bsTBuFzg5lFX4pOCFCJ2mwWGtiG4hcg5hS7X2x5X1axyT1Aw8BdtPiZpt9MzeDHbdd5SV+ntZr1jEy/wDYNMDwnumz3mXe3/kOIJBFBUYnMZIGWlfqaYWMOMb9MEFC5Q292XlFby1e69LQ6v5T9JxNRTXS0cQckIs0PEYkVCEWCApu29TJl9qiGTgqDSeY+e6PxnsxdsbgqxCucZepouq1AFxzcr5ilfMGa1GrjyHpLsjYxx5jdVxEAgldjYQI+LI8/h+J6iFTPdHZDdRZSNLcXAHjiGtd5lBiFG7QBmRVmBVZ6EVWnowZKhUcBHZ7UINzyZWBV98cazKtL/MascgZj7f8hfkp6xKJrzNZhfeKDAekeevcA4KR6yK3/CKf4jNCzEceYgbjysVCpgyT9YGwxUYaYGwxZs/nQ8HDkT+7/JsPmosQUKQVbS0W0HlnlO0QYo3A6vqxqxbAmYrsGSHmJQuJrmNSiQqu5nuUC6iLa4IaFrmoCiNGJzUFm4jN4gVG+jqOMzv7iAjVh9y2pzcpuFy73BjwmsRHEumMbl4VheH7lBR55iHXEv4uUC8GIAd8MUlKMZUYxxNROYgxAEGKqYAFGcX/APUaMrYzKGfqWbYvhi1+U47oM1ACrhv1gBWiJGfpvxLmPKPYlaipcytzWWK2twVwRIUy2Z3uW8S5TcprMXMXPeFu8TBi1lFKqWGIt5TWY4zuUw7RXl4mW4lZcweU5/EOb7pYbgRuVbYpeEKIYxb4iCzBCuFKgLgjB6ChbMqsuaVY6GDkvnVLnN0aaEl8rN0TmLJazCsMiOr5IrRRLtwsaddTkYxe5M1tFG6KhmZEuD7pXiIuQflFd2U6OteI6S+Y30wNZQ5Ip1DBTBlzADMyu417iUGzWYtoreWD7mLxNzugZ8ziHMSyFuWVc1t2g4vxmCiXvmUEFMHtC13CZVm+8xWeIAlu4hfcljEXFcSmBMmTiL4t4mCNuHcX5Q5do5F6YRvmlzKM3jMxc0v6hNQqzHmz8Es0mCLdVLVOGOiW8Qc57zzBuAEpnTLy4jq2XbCVvgsxX7wyR5uvBRvxMILg3JVZW2eEFbipznnol6gxuLe4Dd9oDuLxMXHClYJrS1djt+44+5QGZYuj3GImuRHjOlHt5fEoO2ZA+8xB7C3B9yHEjkbmd1T9Y/iEdyNGj3VMQd4fE+1EyudRCaPSOagVuYqN3NEAtRrHeVy/UVd0VnFRqu01qBjE2zBxUrnbKsYKxxC6jELfmORqGPeXTbqIGICsTPzKlvMDlHlgy3UXtLX0WXOJrjw9/wAkDmHTSpWa6al2x0PDDZ9wuDcWtwg1iC5JQ+WPWG8/E8Ql6HeBHh7TFjiLOi18xzqbxSNxOYd5X2b3DT6KixTGYIE3/wAj3bDtE3ZD36zH7zw0Im3aN+k1JZdQV4ReI5hsBee3/C2AFBxXkyQS4byNG/eesGHaPizg9s1PQf3JDeIhqcy+Y7mDcfEvVxsiFoqZlqTNVOBghzSs7h/sg2WypqVu+R/MH3HbTHKuQ92mJcGIxLXt4uj6JlFl11KuzROY7xHv4jqpkqNszeDnpl7xojb3immDYHsj8wOeJ3qC+YcPEyjLOpQ+GEidyaxqFtQ7MYIduhKLwwyzCcwR1EEW9QhE5lS5WXmd/quNWT05gbuBLNfiLyzmXi5jfaCWQa9IOU4rUElcGLPiUsX2ioeNQLliiN+yJpNDiN0vU7eoj3jAOZlmWUxPCB88mOe8xuABoWHnuziX7lUwvhcdzAE7sWLjuG2ku9ote8AU0VzNj5vSWfgnO+U+WT6jJjqW+cD+4E3MlED3i08h7RQ3DfvCYM7twGr5uK4lYhnDM8S2CZSpKqnEaMSy+0CnEvRP2MC1OYTshV6ASoco8Jql9JTcDAA/HBzcWtRcXC+fhPMb9ZsiXGxzGws5gqU5lmpqbzzNC0A4tYC5c86aRC8/7HLmCy1qbRYuOYdoVqN0keILyR1b7EcEdPjMde8ejLFcJsmItZmVi2Zi7l/QHJcWorbhUY5niCrMVA4P4mYGIXUGiWBiczhnppF+ovxCDDMKNG0G0MAuVGB45hh2g6+TtAbvHaX0RFpnPsnmKzbqNEQGLwIGiFwqbhKXpDXaNsvLLhgoogQz6ogK8wWo4hDuEd127mDbxDtFYkbjdTFMix0HtEFlwPLwPdm1Fq9ub/EOiB/0X5JjaqDywywUQHuMG2pVGINmOb3mzBd1g5ZSEpZj6v5IhoGc9/NCMIPBI/KcQsklmEdQMnc4kYRI7r/yZcm7KppuCJnxB9iHUXs67lOZ5y2bHsnDOAlVqHxCuf8AdmL7g+4WhAH1KLpgC43CPQH0jak3DY8fiRvEHaxFeQ549NRASlQdb1qpWx97otWcShresBwW0KuXiKE6HMTLz5uIIp7WhrtU1RP31eGtzxNdNwmxy7uInhW4oiaT0gLYigVfY5Y5Y4gFLS9QQtnpmIf27RjY1QGzOOJbnc9olXgnc3LYa4YxQN7h7+hMh7xeW8wpMQQBfRFeZwESrmRG+IXVS4bYVqOM9J9/ZfgYHTiZmIdpp6Zl5gnMvtDdvQun1ltWcSweYl3Cj3nexUG7hlmG2u/iBGELqHEq/wDsfHaKg9JcmuZSobuJjCYrcFFw1mWYb7RfmYXC2ZS4KHcVgTtzNVZe65i0l8TdRM0Y7f7rmFBLUjkPZk+5WacEeGCgnybBt7kqGGpW7n6mWdt+VlCBhvNinxMQhqht2r0wRL73KlCpTlHH0xFLHt4EGvlgzZCs2/MxK12omvm5locfV8p3rjsygA0RkXbs038kuYp4rhR9SoIU3MJcdhgfrGUviC+64gWQKHKAiheJ+IGWcrT/AHGGF9ELNCd4sNTtGr/hLtpB0Ti33XMsLQsvIGPY7l04S/t7RFyDtVpE8zgqvlmJF6KDKBiZ/qXIjDCKCwnWVzV6Jk9Yc47h3OZn8U4BWdI1epTI5ers794/CaOKbYeTn0J3KRg+yd39QfmAsdiu75I8AQZ4HSJ9xyzfc8MSt7x39xdrca9Ko5I6s+VqrpL68cwmxO7R9EZH06ZMtZ3LhBN+tX3Fgteom5EcTwr/AFK2FLMHBXbzGn2Cu9vxKwMX8qL3hQNJtbpQ4uFTv2xmq7S8WIL9u8EtG1q3PAC231hLg2bgdZmW4Zqv0mXNY1fqyEOB2ze/SI96igQgSxcsXUbzHrU+0YAuUlnyTn8ksPwzNxEhgv18VFQa/wAjQBEVEYq4zxLI5S0rtDLMHkl2VxN3B4l1vMCqYZK+5vPiKCLns/qC4il95QRqrUotBXsS3AX7zP4Bx+JUaw8bS95IIM6YB88hMBAGT7nM7f3LY+YukxCL95msJeRzKlCF7TifcgrjZwTHp7X/AOon3Pf/AEnGKpyLvHeY7D31XP8AYgWVzLLzKt9c/wAxg+0/MxK5wjljEtGF5xAlCjkLZzWBhNv92CAvbHdP7XD8R8qlqwFnWb5T1CPhRrMCxFg7Y6u5/EwKW7/El4TmUzfaW7hOPTOftjpIwb/8QQWh8BP5mMIDQRKUds+sbxSTAeM3sRNPZw6j5kGe6mB1w9CFrIUrEUu2/QsLfNfQ/uWF7RaVMkvR6sX3sg+sfhS2kJUys34wzlv9CC37Z9iZJQQ+ZQHB/WG3yfAuXuCLef8AEIA0ahPgt9bIC8kHFEz8NQDIXdUivno/llgFLt9pl4fVr+jmErjY82/tHimVFGRYUTLsQDcXJ+L0Y4BNfcJr5jdLWTWeB8XKAKAwEvsGieGLaNxHFYR4fRfVOm1wQPNHrUOKJVh0K69IDzGmWBQ8Jk3ExHXmXeGWtcEsu5fM21thdy8HdlGUWjuZ/tCib1D5l3iXSmUw3HlF4EzHUp0eIBz3qK3WBGCpQCaXXTB5FzALHbn1gVBqUig7gixFxxDODn7gDoAUEuyOZ8p2mk7rD8YYRoymxGycRwjKhhPZgcMYlj8IYdeP92djCNqugO7HgSoOB3VwVziV7rlfoYKH1YO0MR6k+jfRBTiK+Wi+oKqWGYZPaArfIv2l2DnbNpR3D+lGW6CvwhsHlMElC5pDAMk4dNxXTP8Ailf6/Z9E/vUSWHpy80MTNRS32w8vvAa0EHBhDROgg6fZlXeL7mx2+k85QQOTEvZP5TJdge6lBxHIkO0/qkPkl9RV3QEHc8ehAWYvN7EbMo23pCd8/szNqiryVAGWc73wnio6MwlzlaXsBlA1ZueVjKe2ow4T++cPlPvaGoATO6tEQv8AqKWLMK6e0ISxj3JluKK8MoPRHvFSZy32zKBzDXbJXrNG7ARegBWv6yCZRDUTkwRDTQY0Fd2oocxbDDr3mRmMrm9zUS24NrcJOExRUY4lKsxzLosxLGPmVeSIblntMMKQQuLz7QCptWoQy06gDFRiNY3QVsZ7wnJv7TeOV7jZcAMQlxF59E7BKVTVe1gD2I4cSsTJriXSUI9So2zI+jUrkXvfGh+YlRYG1fYUzSEnsonWUh5VfsRV+qHgFvlSWvqxCHsqvf8A4lUNpd8EAt1zADk3vUEA/q4msOcxvYai/OIsjkPqWqniag5rUpTJ+GB/c1OI+G5kwAPzBZngg5xLl457CzIom4qvpMOKrgSsfmGYjc1Uv6MQl4Vtm/okfC43mRM04f4g6y3+TLVmZqW952Ffasq25p/NMcysZniCD5EF38N9TtjPBJXuEsif76ijhlPanvZjGIAu2NAFGNzBy9IHvIZShinvHEjqiA5t3mFtGh0EwPmIu0H5gfYX2gKQi3Z2f3CD5Yz5Jkl0olBQdt8Es2HCu6w98EV6RmXF/glcSgLKl2HMq52mk50y6+ILWdw6TaZb3xNL7doC75d4VduPuJyLG40pszEhuA47cy7UVm8ljbPEolm5hgj5le2IcRoPLv0n+ou0Mekxd8zHUIrEuNwVVzr0gjZHPKKMFrMLDLaWONRU4jyWlrnyh35m2o0VFa0JYOMyuoLbnny1nwRuDeXpHY4mxkNhEQYBROVFtf5HFowYOzTuIGJVayu+YHl4a/2J5Aw1L4r+4JckHJvaB9IRmRPRa7Z2Qkilwrva8PeBUMK0lzdrEj2wR5b5aBEXDho9Dd1z3jZBiWoFIgczNAYqvXt7y2eT4r41wQfzWmXC8YqL4zbH+DR1A3Q1m8RokWG5YeIPoKulI9Rl0JO+fbH4Kj8wcenlrbzEnP6XiVknZYTBeMPeXaEYe8zzwunb6BMsS2UKba47Ec2Hnaa0j0FZrxUtmEcJuxrzK9BWZCFX6PEoWB4YuLdg3LK680+TuMLLGscIZHyR1BQyUoxvzKizWfRuAYu8ZHhPEVlwgQgWrwgGzBMjRmveXoTDuU2Ne8UXEGoChMZ7Mr6WRx5VugFXDAGvPtN1thoTdexUKaxfKjZ6OIhhDPh2fBNYzL4G2Pq4pm2q34mbJ6Ky93c3reb/AIh71F1EVCLQyPUgtCsBpyKhSyQeHI/cryGLtsj8yuVmXbxR5rcABKxNNwLczj4MNhyyp0+Gl7WXO4Hz0Sk8g38YlZgtUEb9CWaiyGtTFTSEcqn+JlB7wfKDZ3Qp3Ts6d4J9fEQQYGjuKWdjHvwyQAXK+fEsmJjehLLRKbi3NcTiig0Yi48xv0gy2ZfMWXAryYgDCipQe0Lq+Ygq8y3cG3dLMWcQA27jtP1mK2eZzibamCZquJVmdzGGJgxLlgI71k4hwKRWZ4jb2Mwg8ZhYUlsDOAxBXn3jgJgjV59yGhocREYi73qCQTZiYkKLbULhUi0rfrLNYogoylgMB4xLQj3YzHJCuSQBbL43+IyZNnC/SPwtrsq/UpSuxK0o1W/mUkVse7vLq65ZX8Ro5P24hkV5A/EwzKWPtcTHQHejOMLDU+yTGaCiGpF9txBenLT+Y7we7/Y8JZRrejdkTYC2rmfmHz3V8fcI4w3mss8WvDRuGjX7IQ7LFjijxDuEn1bV/iWL1az/ANxWSNbvvEJZGh4byJzBAoFHZ0/czZG0Y92P7XhLQ9mmAHKJmeNspSvqentHyCrKHwksgu+UpJO31TUvSnQ6lIHguwfExOiStnc7JC3cBLna9GpdvMv+WImYmuIIiUGyrF+8Yyo/QLj1J4gihFBrKUK+UFcXk8QXHymg45lAuuYI94PBzK0m35iL7RsxdI4mUX+EVVMneX4777mBv0RoW6gd+qBKdSu8RFHvM3vEYcoKHpGbjoVlzG2SVwynejFjcsbjA3s/THRFs7haqilliXZArehBB6CAXfMwJa5il1cyZNTnHTYgcxuN8QjuBxKNTzKxiWBGOoo5jTv1mBTiVeZTFfiFkXkgWjgpxPlKHkghjmKMegS7nmeIMwagzFEcdNPacQ9kY3F4huyZmtwe+pa4JLwO0+WNTA6ZZKIrePMogEnLnPqkpIPB2ts+pSmDcKtcSrcAFELhMcQV0QcdB7S3iLcZtO5v9I02x/MzziF1LbzO6Bz/AHA6fuCBWyKtZSophgxbzDg3UEV5eIbVszDOSDSveVkf9TKrLmnaG7hFldEXSNBx8ylYQwojC2pccDiWXQYl4mQww4S4XfiAgO3JDN0jT2gJhygEathT7oB3iaKhuKcwiuK8QSrg0gBPDGzRqJWHQ5Ym88S8sUXoM0cy+YbiHMeKjWp4lVBd+JrEvmLWsS1WwMe0HmXbGGVFZzAHU4jlcSBxMzUCPiZEzUVmFzm4FtQuesVzqckshN6lo5gCictjf9DxBATd3R7JiWbDlDEIHPdpGbjgbZ4GsAdoBYgJcBiqWDMCMAcSpxUIS6OhNajjUeh13B/lHde8teIzV8INVN4I0tE1mWWXBhn0hiht2xiOjU8MmI73LS0xAAdGO6mVuX4iY+p3zugtkWM9opmKCphji5kBioDfMBWYHXiCPdHHMRs8PaOBcCsPMGh1FVUYHkP0sEDceO0M5hoYgVDRBm5kFYcFaiUUQoxNrJnUSjvHu3LZT7xurg8o4m1zm2aPpM8yl1iURduMsvHrCFWxojDuPiBc7ooZiENoajjcyO0FOgqZiYqG5cIjdxKnExWIDx6dMGOYso56NmSXPMaFNpZvP3gboM0xSPGHMDhz2gagMzw63EX6x1PDMdQuXvMV/uZYiJE5lIolWxribzFdRFedRcA5ZIKx3lCztEp8Kj5nJYWLIwlN/mAKO8QhQFjxiXTZ3t8ywQLzAh3RJvEC2iF1y48JauXmMX7ojK4QLzKWtIKY08Ri4vvNwG62je1tW+1zH0cRVw7TMuPZDGtTJcYil36Iou/aUnz04UmyU7eJkIbslKqCi9x+oNZgwyy5eEZqLSJgl8OoIwcX4jVZ9I4nIjGLm4Z3MXLu+EUS5lKniCxV1GXxAO4vEo17wxuDMhMsCpkampiLl2my5z6ysQxU8zJBYsiqobCXFMUMkXBLIdOOpPEYsdTK+j+WVT7wL5gLFmI6YjUs9BAdwumvdLgXcCxVHmMPhKDnKIrOWGCUesDFFsRc0ytMYdj8xCswoxKhaPSOCCLM2XmoyxhFGGcQUbIKSzcA4KS3e5Vali9mLIHMapYz7Zi1wsPmZ1HslwgCG6QSORjtalhneLfvLCKnEu/aD2mRmXPKAZxBgvrLxRaZMq8MpgQxaXxE2hnJF36TNQ5hjcW5qOajuiUamskprMb2QtIWQ9o3x19ZzLKngncll3zMzDDKmXPRSuhdy+J5QODU0hdHmXTBzmEPEV1Lgy+iKAfMWrZDczZa3A1e8XyH8Td1mNG4rdnMN2RzbBAFxAtqHDUyCzgJcbcVGGRRnkhU4eY2TwVL23/iELCromptddFeOIjmZ0dooXLhrNR7HXeNCHG4R5gViBTLc+0KBm4HyQOz237pgvMeWPNgcxxiOaAFMGmjGop1uAMbhZqXWI5LljiDu+Y0y6ZeKYd+YXLdkM7i1qFO5iWXiECCd4rxGFR5iTqMEhU5nEtSp4hAozK74j0vicQbeuWZuYuCcR3DVRq+utyk3qDC0LENxAyy8odOZqG4TtDk0IDaYwTbAb61/wBgfXaOCnbEx56Abo13h3IIsYBVE24iG+8LqukEL7YuIrntMxVvZJTanrGkUbxPkgj42VHGo0Y5ixcYjguyxF+Jg28Q1a5rBAF75jRcbYll3zzA6i0Lp7SpiYDsQG9RpPpDxWUS0dEFjUKB0k2uBzqKLsaiQ+JZnvHlErUod7iHvM03HtExPMy9HeJials8EsmJzUoNIVUfMwttRBMaTDiVWJfEe/Q6GIajlxE6ViaYUlcI4cy9y71KnE8y5bcroZjK6UxFzKiQwyrSE7rgPGO4xFoeNz8oFS4RzOYVN9FvHSxXBQH2LiRUcx4oKpiAfiFB+bgcwrtCmHiLq494MgG4WWcKmYIRmLvPmXV0ItuYdyXMxBkixmLEvLwQuRCad1AcHhC61tqU1bY5igKbOIxXA9o2PqKwnvMv8gcdoQ4d47v0fw1CCPKVuiA4mQMxOTCxdDtDBRUwQBUpS5nRmCsbg/8A1HDXEDsg5iQ1UQY94GIY3MQsf8hgi1F1ucwwxDuZqXEXjUtdy5eIS+JcKjunnprcviXPWWVGo9pcVZmXfS6czE5xLg9FXmINfEvfaINTEFs6IzGgi7AjjVxMeAmZhuCOujZBj4jguAIYGZMq1pX2QMo75EKjTujW/MpygAJw94YFZjJcC89bjRQ43Mg1YAlK8Rm9sDFTcMsuMwXp5n//2Q==
''Computer science'' is what came out of asking: <b>what kind of [[maths|Mathematics]] can actually be //effectively// carried out in the [[physical|Physics]] world?</b> Theoretical computer science, looks at the more theoretical (as opposed to applied) aspects of this question.
The nature of computation by Moore and Mertens (looks like a nice book). [[Good reads page|http://www.goodreads.com/book/show/3043127-the-nature-of-computation]] and [[Amazon page|http://www.amazon.co.uk/The-Nature-Computation-Cristopher-Moore/dp/0199233217]]
[[Oxford course 1st year|http://www.cs.ox.ac.uk/teaching/bacompsci/PreliminaryExaminations/]]
[[Computational learning theory|http://www.cs.ox.ac.uk/teaching/courses/2015-2016/clt/]]
[[Leonid A. Levin. Fundamentals of Computing.|http://www.cs.bu.edu/fac/lnd/toc/]]
See [[Discrete mathematics]]
----------
[[Structure and interpretation of computer programs|https://mitpress.mit.edu/sicp/full-text/book/book.html]] [[Companion site|https://mitpress.mit.edu/sicp/]]
__Functional programming__
[[Oxford course - func prog|http://www.cs.ox.ac.uk/teaching/courses/2015-2016/fp/]]
http://learnyouahaskell.com/introduction
https://www.haskell.org/
Higher-order functions. Composition.
Examples in JS: .filter, map, reduce
---------
[[Theory of computation]]
[[Church-Turing thesis]]
----------
[[People, Problems, and Proofs|http://www.springer.com/us/book/9783642414213]]
[[Emergence, Complexity and Computation|http://link.springer.com/bookseries/10624]]
[[Philosophy of computer science]]
[[Toward an Integration of Deep Learning and Neuroscience]]
''Computation'' is the part of [[maths|Mathematics]] that can effectively be carried out in the world
Computation is often studied via mechanistic models like those formalized in [[Automata theory]]. The main models will be explained below, in Models of Computation section.
!!!__Language__:
A [[Formal language]] //is a set of strings of symbols// that may be constrained by rules that are specific to it. These rules can also be expressed as machines, like finite state machines or Turing machines.
Finite state machine<Context-free languages<Turing machines<Undecidable problems (hypercomputation)
See ''Chomsky hierarchy'' in [[Formal systems and semantics]]
https://www.youtube.com/watch?v=ZNBNmxXKmUY&index=7&list=PL601FC994BDD963E4. On Lect 3 part 2/10
!!__[[Computability theory]]__
Computability of functions
!!__Models of computation__
See also [[Automata theory]] for more. Main examples:
!!!__[[Finite-state machine]]__
!!!__[[Turing machine]]__
[[Church-Turing thesis]]
--------
[[Theory of Computation - Fall 2011 (Course)|https://www.youtube.com/watch?v=GP21wU6R0-o&list=PLslgisHe5tBM8UTCt1f66oMkpmjCblzkt]]
[[Theory of Computation|https://www.youtube.com/watch?v=GjHfpQPcQ6g&list=PLTZbNwgO5ebp9eegmCueyI8tVwU3X6NV9]]
[[Theory of Automata, Formal Languages and Computation|https://www.youtube.com/playlist?list=PLwi7ySzY5bVKn6gPAEHzWC0hQ0Q0nvsA6]] lect 1
[[Computability and recursion|http://www.people.cs.uchicago.edu/~soare/History/compute.pdf]]
[[AIT lectures|http://www.cse.iitk.ac.in/users/satyadev/a10/a10.html]]
[[Introduction to computability theory|http://www.mn.uio.no/math/tjenester/kunnskap/kompendier/comptheory.pdf]]
!!!__[[Unconventional computing]]__
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[[Causal Nets or What Is a Deterministic Computation?|http://www.cs.bu.edu/faculty/gacs/papers/causal-nets.pdf]]
[[http://www.cs.bu.edu/~gacs/recent-publ.html]]
http://podcast.ucsd.edu/podcasts/default.aspx?PodcastId=13&v=0
See [[Clusters, asters, and collective oscillations in chemotactic colloids|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/pre14_chemotaxis.pdf]] for more details. See also [[Phoretic mechanisms of self-propelled colloids]], [[Collective behaviour of active colloids]], [[Diffusiophoresis]], and [[Designing phoretic micro- and nano-swimmers]].
Use normal flux boundary conditions for the [[Diffusion]] of the concentration of product ($$p$$) and substrate ($$s$$), as done in [[Concentration around a self-diffusiophoretic particle]].
Michaels-Menten reaction rate (see [[Enzyme kinetics]]).
Number conservation for the products and substrates, and the assumption that s and p diffuse rapidly compared to the colloid so that time dependencies and advection by flow [ 41 ] can be ignored give:
$$D_p p + D_s s = D_s s_b$$
where $$s_b$$ is the background substrate profile. We thus need to solve for just one of the two concentration fields. This equation comes from the condition that, after reaching the stationary state (assumed fast, by molecules diffusing fast), the flux of products out should equal the net flux of substrate in, i.e. $$D_p \partial_r p = -D_s \partial_r s = \alpha$$ (where $$\alpha$$ is the concentration, see [[here|https://arxiv.org/pdf/1107.3851v1.pdf]] and [[here|file:///home/guillefix/Dropbox/Oxford/MMathPhys/topics%20in%20soft%20and%20active%20matter/ramin/njp07_design-swimmer.pdf]]). Now integrate w.r.t. $$r$$ over the boundary layer (assumed to be very thin, of size $$\delta \ll a$$, $$a$$ the radius of the colloid) to get $$D_p (p(a+\delta) - p(a)) = -D_s (s(a+\delta)-s(a))$$. Now the concentration of $$p$$ outside the boundary layer is assumed to be very small, while that of $$s$$ is fixed to $$s_b$$. We thus recover the above equation. ,,Because the boundary is very thin $$s$$ and $$p$$ change approximately linearly within it, and the above equation can be interpreted as simply a "discretization" of the equation with derivatives, which actually holds just at the surface. Note that solution of diffusion equation at stationarity in 1D is linear, which helps justify this under the thin boundary approximation.,,
We work first in the <b>linear regime</b> which refers to the limit $$s_b \ll \kappa_1/\kappa_2 = \kappa_M$$. Here, $$\kappa_M$$ is the Michaelis constant, and this regime corresponds to the case where the rate of catalysis is linearly proportional to the substrate concentration (see [[Enzyme kinetics]]). This regime is also called //unsaturated//. Later we look at the saturated regime. See [[Collective behaviour of active colloids]]
The resulting slip velocity (see [[Diffusiophoresis]]) of the fluid at the surface of the colloid (due to to the interaction of the surface with both substrate and products), leads, for spherical colloids, to an angular ($$\mathbf{\omega}$$) and linear ($$\mathbf{v}$$) velocities:
$$\mathbf{\omega} = -\frac{3}{16\pi R} \int \hat{\mathbf{r}} \times \mathbf{v}_{\text{slip}}(\mathbf{r}) d \Omega$$
$$\mathbf{v} = -\frac{1}{4\pi } \int \mathbf{v}_{\text{slip}}(\mathbf{r}) d \Omega$$
,,Again see [[Diffusiophoresis]], these are derived from the reciprocal theorem.,, These can be expressed in terms of coefficients related to the spherical harmonic coefficients (we only include the first few) of the surface activity $$\sigma(\theta, \phi)$$, and motilities $$\mu_p(\theta, \phi)$$ and $$\mu_s(\theta, \phi)$$ (see [[Diffusiophoresis]]):
$$\mathbf{\omega} = \Phi_0 (\sigma, \mu_p, \mu_s) \hat{\mathbf{n}} \times \nabla s$$
$$\mathbf{v} = V_0 (s) \hat{\mathbf{n}} -\alpha_0 \nabla s -\alpha_1 \hat{\mathbf{n}} \hat{\mathbf{n}} \cdot \nabla s$$
The coefficients $$\Phi_0, \alpha_0$$, etc. take into account the external substrate gradient directly, as well as the effects that the external substrate gradient has on the gradient of products produced by the particle.
Essentially, the different [[Phoretic mechanisms of self-propelled colloids]] correspond to responses in either $$\mathbf{\omega}$$ or $$\mathbf{v}$$ to the external gradient, through different spherical harmonic components.
... if either $$\sigma$$ or $$\mu_p$$ contain all odd or all even harmonics there is no reorientation in response to the gradient ($$\omega = 0$$).
From calculations we find explicit examples of the general __design tip__: slip velocity is maximum when the position where $$\mu_p$$ is maximum coincides with the region where $$p$$ changes most rapidly. To see more about design considerations see [[Designing phoretic micro- and nano-swimmers]].
A displacement or competition reaction between aluminium and iron oxide, producing aluminium oxide and iron. It releases enough heat to melt the iron, so it can be used for joining railway tracks together.
http://www.bbc.co.uk/education/guides/zqjsgk7/revision/2
https://en.wikipedia.org/wiki/Thermodynamic_equilibrium Thermodynamic equilibrium, no net currents (detailed balance)
Linear response theory, deals with near equilibrium systems, where averaged quantities either don't change, or change very slowly, I think. Currents may be non-zero in either case. Kubo formula. Read more [[here|http://www.damtp.cam.ac.uk/user/tong/kintheory/four.pdf]].
,,//also known as Gibbs states, Gibbs equi-librium measures, or simply Gibbs measures//,,
Thermodynamic states characterize the macroscopic state of many-body systems (see [[Bulk matter]]). It may be defined as corresponding to a particular choice of [[Thermodynamic potential]] parameters, that in turn, determine a particular [[Probability distribution]] over [[Microstate]]s, as determined by [[Statistical physics]].
The above, more specifically, defines a //pure thermodynamic state//.
''Thermodynamics''...
See [[Statistical physics]] for now
[[Thermodynamic state]]
!!__Laws of thermodynamics__
* [[First law of thermodynamics]]
* [[Second law of thermodynamics]]
* [[Third law of thermodynamics]]
When two liquids are miscible in all proportions at high temperature, but separate into two distinct phases when the temperature is lowered.
The [[Mean field theory]] for this situation is the ''regular solution model''. This describes the thermodynamics (i.e. equilibrium properties) of the phase separation. The kinetics (i.e. non-equilibrium properties/dynamics) of phase separation are described [[here|Kinetics of liquid-liquid unmixing]].
The important quantity is the //volume fraction//, $$\phi_{A,B}$$, proportional to the probability to find a particle of type A or B at a given point, which may in principle depend on space.
To begin with, we assume it doesn't depend on space, and we assume that the probabilities for neighbours are independent (mean field approximation).
A way to think about this more precisely is imagining all and each of the configurations for unlabelled particles (with finite volume) in a fluid. Now, assume all of these are equally probable, with probability $$1/\Omega$$. Now, for each of these spatial configurations of unlabelled particles, imagine all the possible ways of labelling the particles with A or B. In particular, we assume that for each of these configurations, the labelling of each of the particles is an independent random event, and for each particle there is probability $$\phi_A$$ of labelling it A, and probability $$\phi_B$$ of labelling it B. This doesn't fix the total numbers of A and B, but for large numbers it approximately does so, with errors of $$1/\sqrt{N}$$. Within this approximation we also have $$\phi_i=N_i/N$$ (where $$N_i$$ is the average number of species $$i$$), so that we may call $$\phi$$ a concentration.
We could do it fixing the number of particles of each species, but it's more cumbersome, and not really correct for the case where $$\phi$$s vary in space (because when $$\phi$$ varies in space, we don't assume the numbers are fixed, but only the chemical potentials, and thus the average numbers). If one fixes the number of the species, though, one can approach it as it's done in the derivation of the Flory-Huggins theory in Doi's polymer physics book (to see some notes on an extension to the continuous Gaussian chain, instead of the lattice model).
More importantly, these probabilities are not right because nearby particles are going to interact in our model, so there will be correlations in positions induced by the Boltzmann factors depending on the energies. This is where we make the __mean field approximation__. <mark>We ignore these correlations and assume the probability distributions at each site are independent!</mark>
By decomposing the possible states in this way we have for the entropy ($$A$$ is set of unlabelled arrangements):
$$S=-\sum p\ln{p} = -\sum_{A} \sum_{N_A, N_B} \frac{N!}{N_A!N_B!} (1/\Omega \phi_B^{N_B} \phi_A^{N_A}) \ln{(1/\Omega \phi_B^{N_B} \phi_A^{N_A})} $$
$$=-\ln{\Omega} -\sum_{A} \sum_{N_A, N_B}\frac{N!}{N_A!N_B!} (1/\Omega \phi_B^{N_B} \phi_A^{N_A}) \ln{(\phi_B^{N_B} \phi_A^{N_A})} $$
$$=-\ln{\Omega} -\sum_{N_A, N_B}\frac{N!}{N_A!N_B!} (\phi_B^{N_B} \phi_A^{N_A}) (N_B\ln{\phi_B }+N_A\ln{\phi_A})$$
$$=-\ln{\Omega} -\sum_{N_A} \frac{N!}{N_A!(N-N_A)!}(\phi_B^{N-N_A} \phi_A^{N_A}) ((N-N_A)\ln{\phi_B }+N_A\ln{\phi_A})$$
$$=-\ln{\Omega} -N\phi_B \ln{\phi_B}-N\phi_A \ln{\phi_A}$$
where we used the properties of Binomial distributions and that $$\phi_B+\phi_A=1$$, as there are no other types of particles. Ignoring constants, the entropy per particle is:
$$-\phi_B \ln{\phi_B}-\phi_A \ln{\phi_A}$$
We can write the energy per particle too. We define energies for AA, BB, and AB pairs. We assume, following our mean field approximation that there are a number of A neighbours equal to the expected number of neighbours given by the above scheme, i.e. $$z\phi_A$$, and similarly for B, where $$z$$ is the expected number of neighbours, not caring about label. After some algebra this gives a free energy:
$$\frac{F_{\text{mix}}}{kT}=\phi_A\ln{\phi_A} +\phi_B\ln{\phi_B}+\chi\phi_A\phi_B$$.
where $$\chi$$ depends on the strength of the interaction energies relative to $$kT$$. This curve has one minimum for high T and two minima for $$\chi\geq 2$$ (where we consider $$F$$ as a function of $$\phi_A$$ say). When there's one minimum, the system will in general not reach it because $$\phi_A$$ is fixed, and it can be seen geometrically (see soft matter Jones book) that when the curve has positive curvature, then any phase separation will be unfavorable. However, when the two minima appear, it is favorable.
Phase separation refers to a system where there are different spatial regions in the volume of the system with different values for the order parameter, in this case related to $$\phi_A$$.
[img[liquid-liquid_unmixing.png]] Fig. 1
The curve corresponding to the most favourable concentrations that will coexist in the different regions for the phase separated mixture is called the ''coexistence curve'', or the ''binodal''.
These most favourable concentrations are the ones that when a line is drawn through their corresponding values of F in the curve, the intersection with the line $$\phi=\phi_0$$, the initial concentration, is lowest. See Fig 1.a. This (if there are no degeneracies) can be found by the //double-tangent// construction: by finding a straight line that is tangent to the curve at two points. This condition is derived as follows:
[img[liquid-liquid_unmixing3.png]]
Analyzing the free energy curve and realizing that the separation process is continuous (not a sudden jump), one realizes that depending on where the initial concentration begins, the separation is locally stable or locally unstable (i.e. metastable). This depends on the curvature of the curve as seen in figure 2. As usual the metastable will have a time-scale for overcoming the barrier (exponentially dependent on hight barrier. c.f. [[Kramers rate theory]])
[img[liquid-liquid_unmixing2.png]] Fig. 2
The curve that separates these two regimes, i.e. where $$d^2F/d\phi^2=0$$, is called the ''spinodal''.
A good point to remember is that $$\chi$$, in the simplest case depends on temperature as $$1/T$$, but often the energies of interaction we used in it have entropic contributions, so the temperature dependence is more complicated.
Also known as the Soret effect.
https://en.wikipedia.org/wiki/Thermophoresis
See [[Self-thermophoresis]] and [[Collective behaviour of thermally active colloids]]
[[Soret - Sur l'etat d'équilibre que prend au point de vue de sa concentration une dissolution saline primitivement homogène dont deux parties sont portées a des|https://hal.inria.fr/file/index/docid/237675/filename/ajp-jphystap_1880_9_331_1.pdf]]
[[Thermodiffusion of interacting colloids. I. A statistical thermodynamics approach|http://sci-hub.cc/10.1063/1.1633546]]
[[Thermophoresis of DNA determined by microfluidic fluorescence|http://www.biosystems.physik.uni-muenchen.de/paperpdfs/microfl_thermoph.pdf]]
An [[Organic compound]], similar to [[Alcohol]]s, but where the [[Oxygen]] is replaced by a [[Sulphur]]. The resulting group is nknown as a [[Sulfhydryl]]
The entropy of a perfect [[Crystal]] is 0
A "unit" of [[Cognition]] (see [[Cognitive science]], [[Mind]])
[img[http://www.gifbin.com/bin/1234185039_slo-mo thunder.gif]]
[[wiki|https://www.wikiwand.com/en/Tikhonov_regularization]]
[[Ridge regression]]
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thy/91f++2/+I/T9a/P3/gqZ8H9N+Mf/AATl/bu8NRfDbQ/iH40vv2Qv2krTwFpd34Ws/E2uz+Mf+FN+Pj4XtvDNvLpWo3y6+2sSwroH9mRm/TVp4DYgXMgoA/h5/wCDTL/gpt+zz+xJpf7QvwK/at/a1+BXws+FHxTfwt8TvA2meO9a+Kmga/4V+LkF9qHg/X9IuL/WvANn8K7XSvEfhHR9H13XdXtvGpa1ktPBdlHNqN9c+J7HRv7hNH/4K1f8Eq9fdY9I/wCCkH7E15IyBwg/ak+CcLbCrkErceOIiuRG5w2GyCMbq/Bj/g3H/YU/4Jyftif8ERv2ctQ+OH7Hf7L/AMaPG9n4j+PPhL4heMvGXwX+G2ufEqPXLD47ePNU0q1vviC/h9vGtjfWvhDWPDP2B49ctryDw/PptnbuNKaESfon4w/4Nmf+CF3jaSWfUv2DPDek3Ek8twJvB/xi/aQ8FxxyStEZFisPCvxg0nTBAViCRWjWTWtsrytaQwyu8tAH6W6T+3l+wlr8El1oP7av7KOtW0UpgluNJ/aP+DOowRzqkchhkms/G88aSiOSNzGzBwjxsQVZWOp/w2t+xd/0d5+zN/4f74S/T/ocf6/rzX4p3n/Bpp/wQ7upFeD9nb4j6cqoFMVn+0Z8b3jdgzHzGOoeML+QOQQpCSLHtVcRhy7GmP8Ag0r/AOCII/5oP8Uz9f2ifi//AE8Qj/PvQB+xGpf8FGP+Cd2iy3UGr/t6/sc6ZPZSGG8t7/8Aai+BlrcWswYIYriCfx6ksMgbAMciBwSMqDyeN1f/AIKt/wDBLfQYWn1b/goz+xRaRIgkZj+1N8EJsJuKhitv46mbkjAGM5xwc8/mRYf8Gof/AAQwszAbj9lvxpqoiXbIL/8AaS/aKjF0dpG+f+y/iTppVs4bFsYE3AAoV3KfQfCv/BsB/wAEJvCWqWmsWn7C9lrF7ZTie3XxV8e/2pPE2l7goXy7vw/rXxqu9A1OA43GDU9Lu4yxPykDFAHsWr/8HB//AARR0N7+O9/4KIfBCZtO+0faDpH/AAm+vpJ9mV2k+wS6D4T1KPVdwjP2caY90bpiiWhmkkjB+VPHv/B1/wD8EPPBV1cWekftI+PPiTJbCcSSeAv2fPjWLVpoUc+Rb3njbwh4KtrozOnlQXNtLLp7uySfbRbN9pH6VaP/AMEh/wDgk3oVhY6dYf8ABM39hR4dPjiitp9T/ZJ+Aut6mViYmOS61nW/AGo6rf3APzNdX17cXTnHmTMRmvafBn7C/wCw98OAo+Hn7Gf7LHgTZ5Wz/hDf2ePg/wCGtvkyJLFg6L4JsSPKkjjkjI5V1R1wyKSAfz8zf8Hhv/BKm+1IaP4B+FX7cnxW1Jwhisfh58A/At7ezPJIIYY4rPX/AI5eHbtnmuGitoswBHnmhiEhLMRma/8A8HR+s+NLWeb9kX/gi5/wU3+PzwDZO3if4US/D6xgu3hkFrBc6h8OtJ/aFSBZ7uJ4DJLCJEhSS5jgmlVrKv6pdC8O6B4WsBpXhjw/onh3TVd5U07QtNstJsFlkZmkkFnYWltAryMdzuE3sxYsWJLHZ+f0X2OSeMntgdsd+Dng0AfyAr/wcff8FVr3/R9N/wCDZT9tL7W4DRNN45+N80W1cPIWiX9gm0L5jD4InTa2xiGAZGng/wCC/H/BbbxBOlt4c/4Nqf2nLCS7ybKbxD4m+M9vZRLEjPN9svtR/Zb8NWaF1ikEBmubTMjRRoJpSiSf17/P6r+Tep9/THHqTyMcnz+qD/gLHuf9oY4x685oA/k/tf8Agof/AMHVvxNto9W+Fn/BED9n/wCH+k3QR4P+F0fH7wjBqlqo83eL7RdX/aO+EviENMYWjiX+wIngeSGW4RoGMhsL+1X/AMHiWpfJZ/8ABML/AIJyeHGjG95/EHxVg1aG5Bwoht49B/bwEsMoOHZ7jMRUhVO/k/1bgP3Yfgv+J9PyOeoIAUBu75+igc/meo7evcDigD+UZvjJ/wAHkeqk3w/ZJ/4JfeG/Ox/xJl8S+IJxZ+WPJP71v2pPEBb7QYjcnOq3O0ylR5IX7Mrf+Fp/8Hkv/Rs//BMD/wAH+u//AERFf1d4b+9/46P8aMN/e/8AHR/jQB/Fd+2d+0L/AMHZ3w9/Y9/aj8afHT4Ef8E6vCvwf0D4EfFW7+KPibwJquuXfjnQfAL+CtctPFWs+DbZvjvq0c3ibS9Iuby+0NZtOvYRqUNsZLG7UGzk+Xv+CN3iH/g5e/Z2/wCCbf7O/hz9hP8AYo/YH+Kv7NPijS/E/wAVPh54r+KnjXV7P4q+JLbx54x1/X9R/wCEkA/av+GWmWWofbnlsdLiPhe0gtNLTTIr2eeWK4uD/Qn/AMHKvgn4/wDxK/4I2ftOfDz9nDwV8S/iN4/8Y638E9DufBPwj8KeIvF/jjxB4Qm+NPgyfxTYWnh3wtYalr2o6bJp9uTrsWn2cwOjC+XUV/sk35P6l/sZ/BKw/Zr/AGQP2Yf2ftM0eXw9B8HvgV8KPh5Lo098mp3FhqHhnwRoul6vb3WpRyyxajd/2na3T3d9BI0FzcvJPbsYHSgD+d2L9sn/AIO+bB/O1H/gkB+w/wCIIGUxiy0D9oP4f6PexSkhluZLrW/25rq2e3RFaJ4I4vtDSywyI4iSVSP/AMFGv+DpvTGax1b/AIITfBi8v7XEV3c6P+0t8O5tMmmwGL2Uln8f9at3hKEAGHUrtA+5TOXDJX9W2G/v/wDjo68+/wBOO3PJow/98H/gP1/2v8jHfNAH8nsn/BV//g5L0R20/X/+DfnT9R1GLDS3Xh34+aXcaU6SgSQiCXTtb8SWzukRVZ/L1SYrMHWRIZA0FULz/gsh/wAHDOgxLea3/wAG7viq/tZJBbRw+HvjFqepXy3DrJIkstvo/hnxDcpaiOCVXmezjt1me3R7tJZIYZf60cP/AHlP/AD7/wC3/wDqGOpzQN3cqfopH/s5/wA96AP5HP8Ah95/wXx/6Vxvi3/4cXx1/wDOko/4fef8F8f+lcb4t/8AhxfHX/zpK/rk59R/3yf/AIqjn1H/AHyf/iqAP5G/+H3n/BfH/pXG+Lf/AIcXx1/86Sj/AIfef8F8f+lcb4t/+HF8df8AzpK/rk59R/3yf/iqOfUf98n/AOKoA/kb/wCH3n/BfH/pXG+Lf/hxfHX/AM6Sj/h95/wXx/6Vxvi3/wCHF8df/Okr+uTn1H/fJ/8AiqOfUf8AfJ/+KoA/kb/4fef8F8jnH/BuP8WuPX4i+OR09j8JefoDn3NbMP8AwWA/4OKL6KO8sv8Ag3l1iC1ukSe2h1D43S219FBKC8aXdveaZp9zDcKm0TQ3FlbTxybllto3JQf1lfN2K/8AfJ9/9r6fTnqaMP8A3l/75Pv23Drx1JIyRk4yQD+Tn/h7r/wcZf8ASvXef+H0j/8AjNSRf8FYf+DknWnGnaF/wb8WOn6lNkwXfiD4+abbaTGsQaSYXM2o6v4etVZ4kZIPM1WAmdowizSMtu39YWH/ALy/98H/AOOUYf8AvL/3wff1c+3v15FAH8o3/Dyj/g6K/wCkDvwq9P8Ak5HwL24P/Naec9j0x69aP+HlH/B0V/0gd+FX/iSPgb1I7/Gr2/lzg5P9XGH5+cdsfJ9c/wAXfjHpz1ow/wDfB/4B9f8Aa/zx3zQB/KBN/wAFS/8Ag5k8ObJ/E3/BAfwpqtvcgxW8XhT9oLw9eXUc6bXaS7Gk+OfFrxQGPKp59tbq0pG25dlaI8fff8F6f+C4HghkuvHn/Btn+0Rq+nqXEw8E+N/ipfSqLYhbp3u9D/Zv8eRWscpKm0kntTHIPM8h7oI7V/XgA/8AeB/4CR+P3uv6fSj58dVJ+jAd+ep9uPcjPGSAfyd6V/wdB/EPwfaLrP7Tn/BD3/gph8FPDdtND/bniHRfhtrPjHT9KtpI4QsyXPjjwR8FNPuJWuUvoY7e71KwSSG3gmFyJZ57WHY0b/g8Y/4JE3mqJpXiXwt+2H8Pp1dI71vGPwN8JH+zGZ8Yv7Xwt8YvFGoqRHtuCtvZTuYWG1GlHlH+qz5+eFPoMsPXqdre3GPXk1zvijwh4T8caTNoXjXwp4b8XaLP/r9G8UaLpmvaTN1H77T9Vsry1k/4HC3U8nkkA/BzwB/wdH/8ENPH+px6OP2xrnwZeTMVt38f/A34/wDh3TJdqoSZNePw1vNDsFwSA2p6laBmV1Qu2zd9u+BP+Cyn/BJT4lG3Twl/wUa/ZDmnudogstd+PHw/8Iak+6K2lGdM8Y67oN/H8tzEjeZbLsuPPtXxdW93CnsHiX/gnN/wTu8bQLbeNP2CP2NvFdvGweODxJ+y58C9dhRw5cMsWqfD+5RDu+bIGSWbJOTn4k+Mn/Bu1/wRR+OMOzxR+wF8JvClwkjzQX3wbvfHHwRmgld5GZvsnwi8UeDNLvI8SOiWmpafd2UaGMRWytBbMgB+nHw7/aV/Zu+MbQx/CD9oT4J/FJ7jmBPh18WPAPjRp0WVIWMK+GfEOqtKBLLHFlcqJZEjYlmVG/Kn/gvH/wAEvrL/AIKN/sdatrvw1hk8P/tgfsywan8YP2UfiPoj6hZ+LbXxh4cjj8Q6h8OLLUdNmivI4fiM3h6wsdFuTIX8PeOoPCXi6zZJdMvIrn5Q8Xf8GiP/AARU8SwyRaL8N/jp4Ad2VluPCPx/8YXk0QUSgpGvjy18bwFX3oWMsMjgxRbHQG4Enmqf8Gc3/BLG23RaZ8bP29NIsMkQ6Tpvx3+F8OnW0bOZJIYI5P2eZpxFK5d5BJPI7PJI28McgA8U+En7OHwX/wCDn7/glF8EP2tNT1JvgP8A8FLPgF/aPwyX9q3wPo0PhXxPbfHz4XwaXqEC+MLzwzaaZdeJfhl49tdW8N/EOwttHmtdR+E/ibxJrP8Awri6tpLTxToWq/ef/BDz/gqR8d/jp4y+Nv8AwTH/AOCjOhzeDv8Ago/+xslxD46v5YtLi0v47/DWyvtJtLP4p6QdEtLHRhrFvF4i8Nz6tLpFtHoXi7w3r/hL4keGJJYdY8Rafp36k/8ABPP/AIJ2/s2f8Evf2dbX9mf9lvTfFsXgqXxhq3jvxDrfjzxKPE/jPxX4z1yw0fTNU8S6/qUOm6NpUNzLpfhzQ9NisPD+h6NodtbWMLWulR3s17dT/wA+f/BRJbHwF/wdkf8ABF7xl4INofG3jv4EfEjwf4/03Soohq174Ok0P9pTQLXWPEcNmGuLyxj0rXNeksbnUYWgt08NvLDcpHpqNAAf17A5LDn5cZJ6HPpz+f8AMmlpOMn1wM9egZsd/r75IySMZWgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBpXIAzj5lPTrhicc5HOevJGSVIfD1+CX/AAWN/wCCWv7ev/BSHxT4C0L9nP8A4KWeKv2Rf2f7z4UeO/hZ8ePg1peheJtQ0L4kW/jA6xZ6tq+rWPhTxR4T/wCE6tPFHhnVj4K17wn4y1ZNB0zRrMX2gqbzV/EltcfvfRQB8lfsH/sj+FP2C/2OP2e/2QPBniG88W6J8DPh9p3g8+Lr/Tk0e78Wa415f634r8WS6JFqGpxaGPE3ibVtX1uPRY9Rv10qG8i0z+1L5bZb1/rWiigBrMFGTk844HJPze/oufxAGWzSGRQ23kn2H+979Pl69OR15wyYEqoBI/eLyM9hKT3HBAwQeCCVIIZs/wAhH7V/7Zfi8/8AB1X+wr8FdA8a+KYPAHwn+Hv/AAqvxZ4Jtdb1RPC2qeNfjR8Lfi94k1TVL/QbXUbfT75jp3iT4VSvNeQyy2+o+FNLvGjkk0+1jr9X8HPCHiHxozrjXJsgxNDBy4L8MuPvE7H4jEUaleFXL+CsnjmMsup06VSM4185xFSll+GxEr0cNVm61aM6cXF+dmGY0suhh51YuSxGNwmChZpWniasoc+qd1TjFylHRyV1GXMpH9fYYElcEYAOSOCDkcck8Y5/QkgmnVFEwYnHZF/EAsPX8T2HHUkky1+S05KceaLUk1FprazTa+9csteklvZt+itdv6s2v/bX/m92UUUVYB/j79PzpMfTpg/n9M/h079aWigCIo23A2nnBySPl574J47DpgnnI5/Dn9s3/ggF+xZ+1n8XLn9o/wAGa58VP2TP2j7m7utYu/jJ+zV4pt/Bd/rXie5luZJvFXiPQW0i5tLjX7s3U7aprvhm78MeJNYaTdq+vXTRo1fuXRX23AHiT4g+FWdz4i8OeL854SzarhZ4DF4nKq9NUcxy6pOE62W5tl+KpYjLs4y6u4RdXAZnhMTg5StP2CrL2pyYrA4PHU/ZYzD068FJSip8ylGcea04ThKM6c1fScJRlay5mk7/AMuEX/Bup+0jqr/2P48/4Ljft7eKfA94Taa94Yt/EvjewvdV0NwY59MTVNX+NPifTrWS6gzBNc3Ph3ULZ45J0n02eGWaBv05/YH/AOCM37Bn/BOO7m8UfAX4YXGt/FO7gubW7+NvxU1aPxt8U1s7qCW2u7HRdVbSdJ0bwfZ31vLLDqsPgrQdAbWYZGi1179I7fb+q1FfofGf0nvHzj3IcZwtxB4iYyjw5mcFDN8h4YyThXgnKs7hGfPCGfYbgrIuH1nlKD+HD5o8Vh0nrRbSZyYXI8qwdWNejhb1oNOnVrV8TXqUmr605V69Rwbet073b1te9CW2Zl5EbdAQzPhlxKpUrtZWUqSGDLhgW3AA7T8j/GP9h74AfGj7Tfav4Ot/D/iSWdrhPFXg+QeH9YaWUtvlv/s1tNY6nKpw0cmoWU8gJkKyqzOR9jH+vv2B9D3xxnjOMjnlMAj157A9dx54PH8XOehPJAIP8xcS8H8K8ZZbUyjizh/KuIsum7/VM3wVDGU6ck21PDSq05VMHVi7OFfCTpV4NLlqJq55PF/AnBfiDlNTI+OOF8k4qyqbv9SzzLsNj6dOWtquEnXhOrgcRHRxxWCqUMVFqLjWTR+Tc/wk/bu/Zba4vPhJ8RbH9oDwKk8dtbeC/G/2uTxTa2ALyJ9nkvLmBUaO3tvIeWy8R+V57rLb+HSHZa9T+GH/AAUQ+GGqaingz41aD4j+BvjuNkhutO8Y2E9t4f8APJdQqa3dC1uLRZHXCzazpmnWrAx7Ll1JcfobKoZQuNwY4PJx/ERxkgg4JIPB46kZPknxO+B/wo+Mmnf2X8SfA+heJ4Vjljt7i+skGp2DzIY2m03VYPKvrCcocNLaTpIeMksBX5G/CrjbgdOt4QcfYrDYKi06PAfH88dxLwi6SnN/VcBmrqy4mySLWlKVLG4zD017NPC8id/w1eCviF4cwdbwJ8Tsbg8uw7Tw/hp4nzzHi7gZ0lUqSeDy3PJVp8X8OxcZyjRnSzDH4Sj+6UsFKEGn6PpevaRrVpb6lpN7b6jY3kHn2l5ZXNrd2s8Q2k+VPbzyxMQGRvlkIIdCGOc1qJOj4wGGRkZ29MkckOQDx0z0wckHJ/KjUv2Mvjh8A7qXxL+x98X9Us7FZnvrn4UeOLv7doGpzQySzSWlpcyW72BN5bQpaKby0stRc7Fk8RwyFbmtXwh/wUC1DwJq2n+CP2sPhR4m+EPiNmER8S2un3Go+D71CMm6ULNc3kcLS70Z9Jm1qxtm/wCPm/iQSMumE8cqXD2Jo5T4x8L5j4YZhVqQoUM9xdT+2fDvM68pRgv7O40y+isNgVVk7QwvEGGy7ER1i6k3FzemC+kfQ4WxmGyLx94NzbwdzWvVp4fDcSYyr/b/AIU5xiJyjBPKvELLKH1PLlUnpSwXFOEyjFx1jKvOSc3+oglXbuwwGcDOMnkjP3sAcdz3HUg07cOn+H893t6n8eN3nvgf4jeBPiLoseveBPFmh+KdJuGDRX2ialbX8Q2kqyzCCSSSCSJzsmiuEilhkPlypvYCu7WQA+oAHzDjPLdgeDxnHI5bJyWNfuOBx2CzLC0cdl+Mw2PwWJhCphsZg69HE4WvTle1ShXoVKtGrTkrNSp1ZxtfW5/RmXZjgM3wWHzLKsfg8yy/F06dXCY/AYmhjMFiqU1KUKuGxeFq1sPXpzirxnSrVI263V5R3knlxqwUnEygAdyUn6fN7bvoWHUGv57Gt08F/wDBx5ay2gLD4u/sePd6miH7ps7W4sVM25grDzfhnZyqsRJCtbMQXWcH+gjVJ7G1sbm91G8hsLGxjmvL6+u5orW1tLS2gnkubm5uJnWG3gt4d88800iRxwrK0joqtIP4Qfjt/wAFAPj1+3z/AMFrPAFx/wAEiz4Q0LxHonw/8Ufs2+B/2h/jLBE/w38R6l4b0v4w+NPG3xH0XSzouultCsfD2u3ieEF1HRPEt7rK2Gi65P4UitdRsrGvtOGfAnjXxrlDGcO4rhvh7IOAM/4W4i4y47444jw3CnBPCuW1sdj8FR/tTPsXhsVGeZZpKrPD5LkOAwuMzzOqtPFUctwNT2OIrR/fvAPj3K+Ccd4z4DN8Jm+Ppcd/R98YeDMJl+SZLis7xmIzPF5TkGZZTWxOFwrvgsrwONypYzM86rzhgMpw9OGKx1RUpR5v7xLUhJHJB27ByOcYLHB564zjryQuS2AbyyqxIGeCByBzzjI55Hr3GRnkiv4SfE3/AAWU/wCCmv8AwSL/AG4779mL9tL44/Dn/go9otho3gzxF8ZvDPwy8C/8If49+Dj+L9MGv29j4Z8TWHwp+Hem3mty6DrOheK4ND1q28Q+GL/QrzR9Dg1PwLqt3qF3D+9/7DP/AAcD/wDBPT9tzxvbfCO18SeMv2e/jHq+sW2i+E/hj+0Noum+EtS8b3N3E01gnhHxLo+veJPCF7fX0jpZ6f4e1XX9L8V6lqLLa6JoN/HJbzyfvfH30NPHjgbh3Bcd5NkeE8UfDXMMgw/E2D8RPDKpjM/yN5HUdSCzDG5disDlXFGU4WnCjOvVxOYcOwwMcI1jnmH1S9Y/m/A8R5XiK1XCVKssFi44mtSeFxqVKrKpKvUnBQmp1KMpSjJWhGq5qUuRxc1r+5IYHHvkDp2z7n06denry1pApAwxOQvAHoxzyw4+Q8+pA5JzUeVx1BABBPYbS5boc5BXOexG37wIP5qft/8A/BTD4SfsP6TpHhG10nUfi/8AtE+PVtrX4X/ATwZ5154p1e61Ka9s9H1fxFHYw3d5o3h+91WFNL09LeyvfEHiHUXksPC2iag1rq1zbfyTmWbZfk2Ar5lmuKp4PB0FFzrVHfmcrKFOlCPNOtXrTap0aFFVK1apanRjOUrn6bwHwFxl4n8V5ZwRwHkOM4i4kzao44LL8FGC5KNKM6mLx+OxNaVLCZbleX0IvFZjm2Pr0MuwGEhWxWNxNKjTqSPtH44/Hr4R/s3/AA31z4sfGrxvo/gLwVoEYe81jWp1Q3N1IlwbTSNIso2e91rXNTaFoNL0XSobrVL65zDbWruGU/zw3ur/ALX/APwXS8Wvo/haTxP+y7/wTf0bWtup6/cxS23xB/aCttO1OKK/sII4rmW2v7e4t2lS1s1kuPAXhy+E9xrd54w8Qafb+HoPT/gv/wAE1/2lP25viL4Z/al/4Ky+I3urDTZ5tX+Gn7H2gzR2fg3wXYz3MRitfGVvp95f20dtqFvp9jdaj4et9Tv9f1SMWdr438SFYtQ8Hxf0IeHPD2h+FND0jw14a0fTdC0DQtNsdI0TRNHsrbTtK0nS9PhFvZabpunWcMNtZ2NpbxxwW1rAiRQwJFHGoRefh1hM846lz5rRxfD/AAleLhk85OhnfEEHJtPOPZzcsry2at/wm06ixteLaxc4QlKkv6e/1h8M/oqJ0PD/ADTh/wAXfpB01Kni/Eihh6WaeF/hBi4+1pypeHFPGUVQ494zoVFzvjfGYV8M5VUhR/1awuKxkZZkeSfs6/s1/Br9lf4ZaL8Jfgh4I0nwX4S0eJWkjs083VNd1U20NvdeIfE+rSxi+1/X7/yIze6tqMstw6xwwwrBZxWtqvuyxkE5IxwOM84Jz2+UEdh175OMPQYzzk4+bGTzuOCeOD19+vHWn1+h4XC4bBYelhcJQpYbDUKcKNChQpwpUaNKCtCnSpwjGEIRWkYxVkvP3j+RM3zfN+I82zHP+IM0zDOc7zfGVsxzXN81xlfHZnmOPxNSdTE4zHYzETqV8Tia9S86tarOVSTm48/J7rYq4Jzj2wOvJOT6ccAA45PcZL/85/E//WPXqT6ZJRW/9fn3f9aaux5+239b+f8AV31u2f5/zz/n1zzRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFIRwR/nrz78j6+nNLRQBla3oei+JdKvtC8R6NpWv6LqUX2fUdG1rT7TU9Kv7fzFfyb7T76C4tbuHcofyp4XQuFyMruNLwx4T8L+CtJTQvBvhfw74R0aKaWeLRvDGj6domkRzTtvnnTT9Ls7K1Sad/mlkWDfI3zSOzGuiooAZ+8x/Bn6tj+X+eme9H7z/YH/AH0f6DH6+mD1p9FADRv77fwB9+xP07+tKAe7Z9MDA/Uk/r68ZIwtFABRRRQAUUUUAFFFFABWfq2mwazpOqaNdPPHbarp97ptxJaymC6SC9tp7WZ7adQzQTrHMzQygExybXAJUhr5OPzx/T/PU54AJrmvEPjTwZ4Rn8P23izxb4b8M3HirWrbw34Wg8Qa9pWjz+JfEl3HLJZ+H/D0Oo3ltJrWtXccE0lrpOnLcahOkUzRW7KjmgD87f8AgkX/AME29K/4JRfsY6P+yRpfxXufjL9g+InxG+IF549ufBdp4Gkv5fGetx3Njp58P22veJCj6LotjpWmXOoXGs3UmpX0N5fwQadp81lodt+nFJn5tuD0zu429QMdc5PXpjGckGloAKKKKACiiigAooooAKKKKACiiigAooooAKKMgdSOoH4kgAdepOABnOSBknr+eWlf8FaP+CZ2tftJXH7Imm/tqfA+f9oW28d6l8L5PhjJ4rFrqZ+JelXdxp2oeAYNXu7eDw7deLYdWtZ/D6eHrbWJdVuPFCHwra2k3iQrpZAP0MOcHGM9sg46nkgHPTBxnkkjIxkoAR1Oevr3ZiOp7DaCe5zgKMilDA9OR8wLAggFW2FTzndkHIxwchiGGCE4BPYf/q/n/nHNAC0ViX/ibw1pWsaH4e1TxDomna74mbUE8NaJf6tp9prHiF9LtftmqLoWm3FzHeau2mWn+l6gthDO1nakXF0I4SJK2gckj+7jJ4759854GQezKckGgBaKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAEz/PHQ+/X06d++Bkk8tL46K5+YLkAYwd3z5LAbQFJJzu5UBSzLTjjjp1GDjPOSOBnOSOM9gSTkZz/ACS/tr/8F7v+CgX7Av7ff7TH7FHjT/gn8f2h9Y+IQ8CXH/BMe5+DGleOdNs/idaeKrKOC8k+KOt319r154wn8Oatff2f4i0v4e+GdGu7LxXoWueF5NQs/DOp6F8TIgD95/8Agor/AMFG/wBmX/gmJ+zj4j/aG/aQ8WQWVvBDfaf8Ovh1pl3ZN8QPjB44htpZbLwN8P8ASLi5he9v5pBE2s6zLt0PwnpUj694mvbTTYVaT8Sv+CFX7GX7SP7QX7Rvxn/4Lvf8FF/DEnh/9oD9pjSY9C/ZL+D+qwXLR/AD9nK+sVtrLU9J0/WPPv8AwxdeKPDf2Lwx4Tsgul60ng4+N/FfiOK9vfideLb0v2C/+CH/AMev2lPj5o3/AAU6/wCC7/izT/jt+0tcCy1f4NfshD7Jf/Af9mTRl1G41nQ9A1fRbW91Pw74g1Lw1cXQfSfAmlTah4M0LUkuvEHi/wAS/EXxpqEmsaf/AFZIpjO1cbMEkknfv3HAAxgJgtgZwvyIiqigEAcBgseOcBcdcDOc+546dQFB5FOoooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDzz4t/Ejwt8G/hT8Sfi744upbPwf8L/AAP4u+Ifiy7gQST2/hvwZ4e1bxJrc0MTSRCWWPTtLuXjiMqB32p5gIJP+Xv+zR8Wvjv+0N/wV0/Yt/4KOfF2OIJ+09/wUm8KeDNJnuFkEdsPCPin4F6Tf+G9Ijt4bTz9D+H/AIC+KfgnwnoV9uma4bTTHqhu7231CST/AFBvi78L/Bnxu+FXxG+DXxF02XWPAvxS8F+Kvh74z0mC+vNNn1Lwt4v0HU/D+vWUOpWE8F7p8tzpuoXMUd5ZzRXdu7rNbypMiuf47v8Agq/+yV8Ev2Efj7/wblfs7/s76JqXh/wF4H/bJ8WXGl/2vrF5rviC91DWvj3+yZr+s6vrWs3pE1/qF9qd/PcswihtbeJ47Oxtbayhggr/AEh/Z4eJHBfCmZeKfh5LIKmO8RfGPhrinhajn2IwdGrl2T+GGS+EfifxLnmGwuLdZV6GbZtxNl+RwqYeNCpSrZfho1KlRTpQifF8W4PFV1gsWqqjg8urUK7pKT56uNqZjhKFJyg1ZwhRlUtJu6nJpOzTf9o9mSXYHJ/dfh98n1/zxxnJq/VC0xvYD+4f/Q09umMY9y3B736/zNypSjgqSnLmaoYFN92svwyb+co83X4t27n2r3l6vv8AzT/rzu97BRRRXoiCiiigAooooAKKKKAEI9/8447/AI/oSaUdMfhx+OO2P6ckc4ySigP6/rX/AD9WNZSVwCO2SQDx83b1Of5cjBzH5bZHK4HBIHJGSTxjjP17nrzmailb1+923T2vbp2utdbttrlV769O9tG7aNtJ+a11eu96ptyV25UfPu6EjHzehU5yRySR14JJNct4r8BeFPHWj3mg+MfDeh+JdIvMLPpmuafb6nZSrklg0V3DIIyzfvFaLbJHJtdJBIoeuzorDEYTCYzD1sJjMNQxeFxEHTxGHxVGniKGIpvmTp16NaM6dem02nTqxnCzd4t782LwOCx+FxGBx+Ew2NweLpypYrC4zD0sVhsVSkpxlSxNDEQq0sTTlGTTp14Tg00uW6u/zN8b/wDBOvS9F1u98cfszfEbxB8EfFjwxCHTLTU9SuvCF5NHI8zw3cQ36pFa3LKqyW8l1qGmQpHA0WjEo6Pxlp+05+1h+zZcQ6X+1B8KJ/HngzRhBa33xc+HVqbgvbkFYb7UYibDTDI85W0Z9Tg8LEkxrDDcStE036wvnbx/eGfp+8x39e3PoTjmsnUbSzubK9hvLeK6t3tZVmtp4hJHLFiRpI5EYMsiuUXKMCDjIU8ivw3G+BWXZNisVmvhHn+aeFmcYlyqTwORyhiuCsyxijiJ0VmnB2OdTLKNCpWVJV55LDLsS6TqKnVVSUqj/nXG/RuyTh/G4vPfBPirPfBXOMVP2+Jy/hh08f4f5pib1HH+1fD/ADOVTJqNKpNR9tLh+OVYt0+dUqqnK7/kw/4KBftj/FL/AIK+ftU+B/8AgkD+wd4+1L4dfCvWvDNt4+/bo+N72N7pPiHRfhyk1uus/CvTrWW5ifUbSWx13RbPXNL0wzweM/F2v+F/B95rFj4EsfiJNdekfET9mL4JfsH/APBSH/gjH8Fvgt4cPg34Y+D/AA98VvCmmahc3IvdY8TeJta03XbbVtb8UaqzJJqvinxXr/ie1utVumiis/O1IadpFpZ6LZaZpdv8pf8ABBT9lvwh+2t4K/4KH/tZeMNV1vwl8XvHf7cfj6y0/wAXeErhrOXw/a2Gjab4+/syy0oqbSLR/wC0/ipNFDZ2QtrmygtrK3sp7W3t4wfc/wDgqt8Iv2rv2fZv2Uv2lviRr7/Gf4bfsnfHTwpqumeMLQWlp4kh0bWfEfhbVfsXiWWeJ9Yg+26x4H0/RbC9vLvVrW21TVLYyaiZtRtoJf6s+nJ4g8c+EOYZD9EfA8EY+p4a+D8vDrNuKeOuEMZh6uW8Z+McspybiDjrjbj3I4yw+eZa8N/aGI4d4SxVapmWEyrJcJQw2CWDlisTWn/WX0DuL+PYfSo4Y8P+O+AsfmOXeMnAXiL4WZL4rcKY7A4vJaPEnGPhZxTlmBwGfcKVq1LM+E8FmvEWWUMLleMlVzPB18RjsvwWO9lmFWkj+pTSvAfw/wBM8aeI/iDpngfwpZ+O/FGn6NpHivxpZ+HNEs/F3iHStGE7aFpuveI4bNNU1qx0hbib+x7K/vbi308XFwtnHEzujfCX/BRP/glf+yP/AMFJvhte+GPjX4LtfD/xE0yyl/4V38ffB9lYad8Uvh3qnnJPFcWmrmAR+I/D8slrHFrXhLxH9r0e6s2kuLFdM1+LTPENpyPg/wD4K/fsF6p4B1D4jeJPjXoHgWxsNFj1w+GfEM9vL4tu45IElNh4c0LR73Vb/wAT6jcybt+naTFLe2E6i3u4EidJn/OrU/in+29/wWz17UvB/wABv7f/AGUP+Cftrq9xpXiz4u38DW/xK+M2n2txcQXml6KlvOv2q3e5tZNPu/D+gajH4d01ZtQXxv4n1y4jHggfmXCf0gMXwjm/DfHPhFxtnuO4uoSpYjhXF8K51mFXNaSwdSOFVLGYrFTlTyzKMPTj9TzDAZy1lSwyq5XWwGLwqdKf6P4T/R44l8VcgzLjLin2Phj4PZJWlhuL/E/xCyTO8nyHLcZhZyoY/JMmyvH5RleccW8Z/XKNfB4LhXIcPUzWpj4cuIxGCoRrYyP5ifs6/wDBZD9vX9kvxJ4l/wCCTGsat8Of2xfjxYfEHRPhD+yT+1ivj601Dw/4r0fXI4NF0HTNYvdUntrTx3rWl3t9pWmaBqXibxPDd6f4hOreFvF+q6+NIsZ7r+iz/gnr/wAExLf9nXxDrP7TH7TfipPj5+2X8RJJtX8UfE7WJrjVNH8ESXwm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DbimVIZcMCSK/f3OB067OT6bmHQHpwMHg4z6En4Xw05f9QOF7fCspwije692Kahe6uvds9Vtq73bX9QfTScn9Lbx/lU1qPxH4h9o04te1liE6usZSj8cX8MnFW+JqzI5M7DjBxg8Y5OZcZ5656DryRnOc/z1/wDBYO8ufiD+2d/wSg/Zys4l1G21z9oFvil4l01N7ubLwf4j8CR6e80UYz9mfSZPGT3L5BWCNmUgB2r+hJ2IVio/hDdM87mI456EDg5wTnOTX883h+8uP2kv+Dh7VrmS0nu/Df7FP7PeoaVb3ESPLpi+LPFOhPZXU105WSCK+kf4t6hYQQMyzvJ4e+1W6H7HM6rjuSq5VlWTJ+/n3EnD2WcuuuHpZhTzLHaLVRWBy7EuV1yyUlCVk/ev6JVB5fxz4heI8qcnhvCbwR8XuM/rHMoxpZvjuDcx4G4TtOTS9vV4o4uyZUHBqtSqWxdLmeHm1/QtbphFQehBPPAzIOnQAbR1yfm7YbNtByODwMEkdcGQZ6/5PHvTwMenof8Ax7HfqSRk9eAM4p3+f88/1/HPNfcpW09EvkmvO2/p822fy9CCjffddLbWt1bfwrr8m73KKKKZYUUUUAFFFFADG/1cn0/9mkr+TX/g47/5P/8A+Dbr/tIrYf8Aq2v2T/U//X7Ak81/WU3+rk+n/s0lfya/8HHX/J//APwbd/8AaRWw/wDVtfsn0Af1lfxEf7I7Hs59/ce455JGaf8A5/U/0x9Oep4pv8X/AAH/ANmp1ABRRRQAUhB2sBnOOPXq/Q54yCO4P3fmBGaWkI+VhxkjjPQ8t168dOx6ng4OQD+az/g5g/4Ke+Pv2DP2W/hf+z58A/EGneBv2hP26/EfiT4R+Dfizr+v6Z4X8NfBj4c6b/wjelfFD4kXfifUZBF4d1a2j8eeHNC0XxE4t7fwha6rrvxD/tix1Twxo9td/N//AATp/b+/4N4f+CIv7Kngb9lrS/8AgoL8I/G/xB1y2tfG/wAcvi38LfAvxm+McfxQ+Kl5ZW9trWs3mvfB/wCG/wAQLHRNA0j7KNG8D+E9R1OG40bw5BBPc28uu6lrurXf9G37UH7DP7G/7bNt4Mtv2s/2bvhb8eovh7Prlx4Gb4j+FrTWrrwtJ4ij02LxAmiXcgW7sYNcXSNKbVLWKYWl7LpulXFzFJPY2UieBeF/+CN3/BJPwbaS2Ohf8E3/ANkBYZpWllfV/wBn74c+I7p3JJwb/wASeH9WvPLU58uEXHkx5IiRQxNAHxSP+Do//gggOR+3cM+v/DL37anv/wBW5/54GRjNfZn7L/8AwWV/4JU/tlXC2H7PP7cfwQ8Ta/LfQabZeDfFuval8IviFqt5cBhCuhfDn4zaZ8P/ABr4giZh5TXei6Be2kc7xW8twk8sUT9gf+CTv/BLDB/41xfsWfh+y58Fc9cZGPBORyucjkcHOME/JX7UP/Bup/wRz/as8P8A9l67+xv4E+DuuQo66Z46/ZstY/gh4n05pPN3yy2Xg+yt/B/iJ8MViXxl4S8QQ237v7Nbpt5AP264xnPHr2xzz19vX154OUyM4yM+mRnjI6Z/2T+R5JBJ/ix+JP7L/wDwWZ/4N5tPvPj7+xz+0Z4y/wCCkn/BOT4fz2998UP2R/jeNS1T4w/Bz4N6NNLPeap4G1e3OpG003wd4dt7tNR8Z/DVNB8P6I1xb+J/GX7PWr+DNB1DVbD+of8AYL/bl/Z+/wCCjf7MPw//AGqv2cfEEuq+CvGEM1hrOh6lEtr4q+HvjrTI7VfFPw58bacsko0/xN4YubmCOfyZZtL1bS7jSfE3h291Hwvquh6vKAfZFFH+f88/59TRQAVT1HT7LVtO1DSdRgW50/U7K60+/tmaRFuLK8gltrqBnjdJEWaGSRC0brIAxKOrANVymsdqk4J5UYCljyxAO0ckDhj6DJJAoA/ka/4NZvG7fs13X/BRT/gjn8Tra+0b4xfsaftQ+PPHnhc69Fb6VqXj74L+MLjQ/CFt4n0vRmjiuruysdT8KaP4tn8QRLJpV/4f+KfgF9Lla0aK4l/rmJUEKSATnaCRk4GTgZycDk+g6k9a/mO/4LRf8E0/2qrL9oj4Xf8ABZf/AIJVtHH+3L+z3pMOi/FP4P8A2YXunftTfBqxhfTpfDT6RcXlrZ6x4l0zwxNqPh3U/D4mtda8Z+EJNNi8G65pXxH8H/D6O89n/YH/AODkb/gnR+2DpVj4P+NfxC0r9h39pjTZ7rQ/iB+z5+01rcXgWLQPFumXC2mpad4a+KPiqw8LeEfEUUl4z2mnaXrEvhv4hPcxXFrqHgKxmiWScA/oLpOxGfTP5t7dwenX3BINeMN+0f8As5JoEniiT4/fBlfDSQfaZPELfFTwIuhLajexuG1Y+IPsXkbckyef5ZUglipWvxf/AG3v+Dlf/gmB+yNY6p4V+GPxVtv20vj28lrpnhD4I/ss3kPxBTxB4ivZbi1sNN1P4r6JBq/w80WKK8QW2tW2mat4i8a6cZESy8CanfbdPYAxv+Dnv9sC1/Zm/wCCUPxe+FnhfVo5PjZ+2Re6R+zF8JvBmnF7/wAW+J9O8a6lDD8WpdH8N2DPq+pWkfw3GueGZLyzge2tPE3ivwfply8l5q2l6dc/qR/wTc/Zun/Y9/4J/fsd/sy3+l2+k698I/gL8NvDHjSxtZIpoE+IreG7bVfiRdedA7wTvqHji/1++nuIHaCa4upZoT5TqW/Az/gnN/wTY/bI/b5/bH0H/gsf/wAFo/DsXhbxh4Qksr/9h/8AYal+0/8ACNfADSIp21Lw/wCNfGnhfUZL06N4k0mZ7bX9B8PapN/wmUvjlR47+I1vpXiLSPDHhey/rKBJJ4IGOSQR0Jx355z2PBzkg0AOooooAKKKKACiiigAooooAKKKKACiiigAooooAa33H/3T/wC1K/kN/wCDwn/k1j/gnn/2kI+Hf/qufiZX9eTfcf8A3T/7Ur+Q3/g8J/5NY/4J6f8AaQj4d/8Aqufibjv7fz5OCSAf15fxD8adTf4h+P8Ah6/59SeadQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABR/n+nr/n1J5opOx+o/9C/yaA/r8/8Agfe+2q0hxtbpjjk9OGbGfx/XPXmgYGceijv6uB1J/p1Gc5pj42NnoNucdcByPU9cc9/TJBNAnflfeztr/jtr0vZemqu+W4xmAjOSBxxnGCQWII556ZwOSGGCCS1fj7/wVE/4KBeJfgDpnhf9lr9luyHjr9sv9oCS28OfDjw/pEdlqd14A0/WLmex/wCE71mzu1l02K7HlTJ4btdde30qN47rxXrbnwzoWoxXH0X/AMFDf27vAP7BfwG1D4haykHiL4i+JmufDvwc+HEU0q3/AI38aPDIsKTR2kct1a+HdG3R3viDVBGAlubfS7Jpdcv9IsJ/kf8A4JZ/sHeO/Aur+LP26v2xJJPFf7Ynx/e51y7/ALYjR5vhP4P1m3hEHhextUmezstevLGGC01JbOGK28N+H49O8CaDHBptrq0998HxDmmNzHHLg/h6vKjj69GnWzzNqTv/AKv5PUlOLqU5q8Y5vmEYunldJpulapj6i9lTXN/U3gzwJwvwbwfifpIeMWV0cz4QyjMa+U+Fnh9j705eMPiPl8YVlhsVRfLUn4c8H1Z0MZx7joSjDHSqYXhLB1/7QxuIdP6I/wCCaH7AHh79hX4O3NtrV7H4y+PfxMuE8U/Hb4oXL315qPiHxRczXN4dEsdS1F5r6bQPDs15eR291PIlzrmqT6j4p1OGPUNRnhT9HrtVNtL/AMABx0/1h56YwcdCMjJBJyKvKMZBAxhcHt1cHqeOq5x1yMnOcw3IHkS++0Y7H956Z6+nfPGTX1mUZXgciy7CZXltCOHweCpQpUKcbuTUXKUqtWpJudWtWnKVWtWm5VKtWc5zk5Ns/BOPuOeK/E7i/iPjzjbNquc8S8S42pj8zxtWMadPmcfZYfB4PDU7UcBl2X4alSwWWZfhYRwmBwFKjg8NSjRpU0fz2/8ABPE/bP8Agsl/wV2vpzuuLW48BafCwG1Rax6jPZohVTtLCDTbZd5G7KMxJaR6/oMt/vn/AHm/P5/f3+vTnnNfzxf8Eu3a6/4Kqf8ABZG8kdp5IviD4Us1unJkdI08cfE6KO1EpLFECWUaLCG2hIEjCgRLX9DdrnzDzkbnwfpuAzz15J9+pyQa+Q8NteGsTUbTdbiXiyq31blxTm0Xd31/hb3dtVd3P6B+mjJR8a8lwkUlHL/BL6OWCjGKtCMafgVwBNckU37OH7xWi9b30Slc0KKKK+/P5UCiiigAo46549fxIHf1H55GSQSSkI4Izz2P0JP5dPwyDnrQH9fn/l+K7MX/AD/nn/PqaOPX/PT1/wA+ueajAAB5HzYB6n7u4dzgYJ7nGO+RkpwSBknGBxxjBPOQ3TjkZOOSORyrvt+fdJdLru9NNbu2otdfK1vPVrtp077voruXr05/yR6+3r69wST/AD/nn/Pr3pgI2n5uegyTn7ze/XHf025pQOT7Y5OMnG4A8N3ycZHt1Bpj/r8/Xy09dWOooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBj/wCrk/3T2Pq/oc+nTnk91bP8iX/B0F8WvBPwQ/ac/wCCA3xU+IF/d2HhT4V/8FAbT4z+MLmx0681O8tfAHwo8d/s7eK/G+o2dhZxvPqF3YaPA81rpdvuvtQmZbaxhlmJFf12vjy3z6frlwPXH3V9/mODkZP8Uf8Awd4fDXXfjn8aP+CLvwE8GxLd+OPi38Wf2o/CHhCxbcqT6rq1p+zRoVrJJMWiiSKDUdc0wyo88cskcjeRuMbuPpeC8FkGZcZcJZbxVjZ5dw1j+JcgwXEeY0qsKNXAZBis3w+HzjG061SMoUZ4XATr14VZxlCEoKc4uMJKWGJlVhhcTOhHnrQoVZUYWb56sadV042vd80oRVr3d99bn9RP7Cv7fP7M3/BRP4J2vxz/AGavF0+s6HFfz6H4l8LeILay0j4geAfENuVkbw/448NWuqaoNHvp7V4b/T7i2vbzR9X02aC+0bVb61Duv2mrAnAz+Q65fOefbj3Jyec1/N9/wa2+GvgLb/8ABLbwv42+FngzSdA+JviLx9458MftGa5axasNY8SePfBPiXVo/CbavJqd1cwrFY/DvxD4ZuNPtNFFvo8D6jqE5s4dcutdZv6P04OOMYGSP+B9+uflHHr265+3+kFwXw34a+O/i14d8H0+IKfDXBfHGfcMZOuKJYapnjw2T46tgp1cViMIoUcVRrVqNStl+LVOnUxOVzwOJxFGniZ16T5MmxNbG5VgcZiPY+2xOGo1p+w5vZ3nFuyUm3GSVlON2ozU0m4q5LRRRX5GekFFFFABRRRQAUUUUAFFFFABRRRQAUf5/p6/59SeaKQkAEk4GRz/AMC/z/8AXpbJvol/8l5/3fxWr1AMj1H5/wD1/wDPrRkHoQfx+vv7fz9DmEsAckgHAOe3UgHkn8uuAOMk4ZHcQPI9us0TTReW0sIkRpESUSmJnQMWQP5ZKFgA2CAScmo505SirPlUW2nHTmqKEW7SbipNpLms3J8seaV4iT3v3SX4+b7dNF1bs2WqKB3/AAx9PxPH4fiCeaQe/r6n/b9fw46cnn5VzoMWiiigAooooAKKKKACiiigAooooAKCQOSQBxyfrgd+56e/GSeaKjkOI3OQOnJxj7zYPJx15yemTxjqm7Rk+ybXnbn8v7q+96aAP3L/AHh+Y9cevr+vGc80ZGcAjPpkZ49s5/z3r+cX/gpp+25+2b+wV/wVG/4J4an4e8b6X8QP2P8A9rbVtP8A2c9e/Zym0nw5oepaR8Sr/wAe+HdBv/iVaeO7jRZNTOoRw/EDwdqGiWt1raaIbPw94m8O3mnadHrI8Ux/0aRHJDA9RjnPT5yAo7kc56dznk5/QeMPDfPuDOFvDLjLGYzJ8yyDxU4dzHiHhrGZVjZ1Z0Vk3EeZcNZ5lGa4XEYfDYjCZrlGZZdKniYxhUwVaFahPA43ExVfl4sLjqWKrY3DxjOFXA1qdKrGpG3MqlKNalVg05JwqQleOqkmmpRTteeiiivz87QooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBrfcf/AHT/AO1KVfuj6D/2pSN9x/8AdP8A7UpV+6PoP/alADf+Wn/AP/ZqfTP+Wn/AP/ZqfQAUUUUAFFFFABRRRQAUxvuN36cHJzh29we3TPOQCQAKfSH7p/8Ar/3j+Pp+Z9OT+vz+7b8+2q6Nd1/8n5+ffqtdzwL9pP8AZ++H/wC1N8DPiL8B/iXp8d74W8f6DcaXLN5SPe6LqqH7VoPibSjIrrBrHhnVorLWdLuCv7u9tYt5MZlB/Gj/AIJYftOeP/2bvijrv/BKL9si+fSPiZ8Kpr+P9m/x3rN8yaV8VvhTEb6bQNG0i4ubiSORbTS7O41HwPEbyS5OgC+8E3FhY6x4UNtP/Qcc44JB+vGM9uOARwR6cZzzX5yf8FFP+Cefgj9ur4daY9pqsnw9+PXw2nbXvgl8YtKNzaat4V8RwzxX9vp+pXGnPDe3Xh+/vbC0lnMMo1DR76Kz17RpYr+0EU3xfEmT5jHFYTijh6MJ55ldOVCtgZyVKjn2TTnGpiMprVGuWliI1IfWcrxE3y4fGXjUaw9euf0f4JeIvB74d4k8CPGGviKHhdx3mGEzjLOJ8Php43MPCbxKwtCWBynxEy3B026+Myivhqn9j8e5LhV9YzfhuUK2FX9q5XlvP+kAZSCdykeuRgcsOuRwcD8c8nIyoZT0YHBwcEdR26nn26+5r8E/2KP+CoHivwP49T9h3/gphaJ8Gv2m/CrWei+F/iP4git9O+H3xs0z7THpmgazFr6PHpVl4g8SzWd21jqsK23hLxPdI9rYXGm+KDL4Yr94Y3RgGDBwT8jA5DKcspUqzAhgcqwwCCpzwM+xkPEOW8RYJ4vAVWpUZuhjcFXi6OPy7FxdqmEzDCTftMLXg7e7P3Zr36M6lNxqP878VfCXjfwc4kjw/wAXYCjLD47DwzLhnifKq8cy4S404fr3lg+I+EM/w0ZYPO8pxdLkmquGnKvhasp4PM6GExtGtQLnHPPTr7fXnj/PJrD8S6Pb+I/DeveHrme9t7fW9J1HSZrrTLuSy1O1i1C1ntXutOvYT5tnf2yymeyuoj5tvcpHPGfMQEawZMn5gTngcg9W5HK+nJ5HPQhc0p74Y4yOd2e7EdOR938ePcn23FSjKMknGScZJ31T5k1o07NSfW+u97yf5tRrTpzjVoVOSrRnGdOpHklKFSEnKE1fnjeMlFpSi1e3MpJO/wAcfsPfsX/DP9hD4L3PwV+Fms+Mdd8PXni/WvGdzqnja80u81uXVNZh0+0lhDaTo2i2cNnbWmlWUMES2fmFlkmlmkllc19isSEYkdCCCRxwWXnnjB5xnqTnginggZyWwBgZ4xzzyCOh4PcdDkVE5URyHIxlVxkgHLMOeGOQDuA68kdcGuTA4DB5Zg8Pl+X4enhMHhacKOGw1FSVKjSp3UKdNSlJqKXeTd73baTPZ4o4o4i404izri7i3O8bxBxLxBj8Tmmd51mVSnUx+Z5jiZ1KmIxeLlTp0oSq1ZWlL2dOKu1aNtXwHxO+Ivhn4S/Djxx8T/Gur2mheE/APhfXPFviLVrx9kNno2habdajeTfxSSOYbVkgiiV5prh44II5JmVD+JH/AAQf8D+LPF/gr9pv9uD4iWz2/ij9r745+IfE2itcc3c3gbwvqGuw2WwOzPaadb+Idf8AEmkWFmsjRC00W0MRMAiC87/wVo+N3jD9qD4q/Df/AIJL/sw60JvHvxW1vStY/aS8T6WP7Qsfhp8MLFItZj0bxS1sJZ9ON1avaeL9dtHm066k0y38K+H/ADZo/F8cJ/cr4K/CXwd8CPhZ8Pfg94A06LS/CXw78L6P4U0K0jRt5stJsfsv2q6mcCSe91CWN7/ULqQtNdX089zcO8zlj8Vh6v8ArHxy69GTnlXBVHE4X26v7LEcUZlSVHE0qcm3Gp/ZOWuVGu/ip4nHSpX56cz+mcZgZeC/0VamVZmlh+PfpPZtw3nayurFLHZN4F8C5picyyfMMVSajXwX/EReNqeGzHLYSco4vJOFMPmHK8Li8PVfqpOOg7jsenOe3X8zyepGSv8Anv8A5/z1NLRX6D8/6+7r5/gfyZ/wOn/B+7t5vUKKKKACiiigAooooAY+BHJk447/AO9IB3/r+JPNfya/8HHX/J//APwbd/8AaRWx/T4tfsn+/wDn1Nf1lnO04yTxjGMnDE9yPT1zjuCQT/L/AP8ABZv9kv8Abg/as/4K0/8ABEHxL8Gv2dNU8X/s2/sm/Gqz+MPxX+Ntl4x8KwaV4f1TxB8YvhVq3i3SPE3hbVNWsNVs4fA/g34K6V4g0PWrG11BvEd74vv/AA7pMEeraYLe5AP6gP4/+A/+zH39v588El1N/j6cbeD2+90/yfz606gAooooAKKKKACiiigAooooAawBVlIDAggq2NrA7wQ2QRtI4OQeGfglTu/jO+AvhvQP+CFn/BxJ4n/Zw8ORWPw4/YG/4KufDvUfiR8PLPVbiz0T4dfC748eBF8V61d+F/D2oSmx0nRbDw9qw1nw7ZeH0igs9L8I/FP4W6VJeSrommu39mRHysAcHHXnrlz2IP5EHG3DAgGvxk/4LN/8EXfg9/wWX+FPwk8HeOfij4m+Cnj34KeLda8QfD74m+HPD9r4uW20TxdaaZYePfCGt+DdQ1vQLTVrDxLDoWgXtrqMerWOqaHrOjabcW1xdaTPr2i3gB+xWjazo/iPSNM1/wAP6tpuu6HrNjaano2t6PfWupaRq2mXsIuLLUtN1KymntL+xvbd457W8tZpbaeF45YZZI3R20q8b/Z8+A/ww/Zc+B3wp/Z2+DOgN4a+GXwf8G6L4E8D6JJfanqk1joOiWi21v8Aa9V1W8vtQ1C8unD3d7e393Nc3V3PNNK5dmNeyUAFFFFACHoeM9OMdeSOn4Z9uCSc8/nn+13/AMEnv+Cbn7eer3Xib9rH9kH4V/FPxldadY6Nc/Ec6frHg34p3Gk6dHLDpmnz/E/4eat4U8d3FlpcLGLTLSfxA8FhExjs444W2t+htFAH8yS/8GjP/BFAeKR4h/4Vd8cG0lZ2l/4QVvj947HhUxNM7/ZftWxfGJgRW8sMvi0XRiCl7l598rfrV+yV/wAEq/8AgnB+wnqlt4g/ZR/Y++EPwp8YWmm3Oj2vxGt9BvPFnxUt9KvIng1DTYvit49vvFHj+Oy1SELHqtqviUQamiQrqKXBWLH6B0UAIPQdP/rnpn6nHoO2CKWiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAY/8Aq5PTYc9f+m/4+vvyfQZ/kS/4PD4ng/Y+/YF1x8fY9M/4KGfDGK5CkmYvc/C34wXcXlRkKrjytKudxZ0KuYVAIZmH9dr/AOqk/wBw/wDtxX8jf/B43/yYb+xP/wBpFfhB/wCqZ/aEoA/rl43A+xx+Y789gP05yMF1MH8H0NPoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKP8/wBPX+v680UnY/Ufzx6/1/CgBf8AP8wO/t/PkkEkyOxH+c+/+yfyPXBy0YweDgAcc55JxgZJByPboOSBSjHUd8fpuI7/AFPr6k9aAFooooAKKKKACiiigApOx/D09Tz+nTr0GcnJWmMQEbkAZAyenLkDv6j1zz0JwCf167/5L7/Jh/X5/wCX5d9UymDzgYXHPDfex37duRzuAOfmrwv9pL9on4Wfsr/BXx18b/i3r8OjeE/BemPeTJG0T6rrWpSTLbaT4d0GzaaM6hreuahJBp+nWoYR+dOs928VlFeXA9P8V+KvDfgbwr4i8Z+Mda0/QPC3hbRtT8QeI9e1W4S00zSNE0izuL/U9Uv7maRIoLSytbaW4nlZgERW5Y7d380/gbw94y/4Ln/tYyfFfxzaa1of/BOP9m3xVJZfDjwhewS6f/wvbx7YSzi51TVLVoYLwQ39tNazeI1veNA8KXFr4M0mOHxD4g8a6hb/ACfE3EFfK4YXLMpowxnEecynQyfBTb9jTULfWM1zCUXzUcsy6Eva4mpbmqzVLCUFKvVR+8eBfhLlvHVbiLjvxBzDE8NeDHhpRweaeI3E2Gilj8dPEzmsk4B4PjUTp47jfjSvSqYHJsMuajl+G+tcQZm6eWYCvOXpP/BP/wDZ7+KP/BQL9oI/8FUP20NAmsdCsryIfsafBHUXa50fwj4W0+8N94c8fvDJFAl7FYzTG98M6hf2UVxrvilr74gmwtbaDwYT/RbGCGG3PHXg4wDJgk7eTluB8x5yTkbjX07TrLSbG003TbaCx0+xtobOzsrWGKC1tbS2QxW9tb28KxxxRQxrGkaIoVUCgABWq+oOcEHAJwTnP8Y/XOfTPckgV18NZBQ4ewE8P7WeMx2MrTxubZnX/wB5zPMay/f4us7+4vdjDDYeL9nhcPGnQpJRTcvnfGTxazTxh4spZtPLsLw3wtw9l2E4Z8POBsrb/sPgfgnLZVP7K4fy2PNevVaqTx2cZrWX13Os6xGPzXGSlWq8o/jGMHoBjqOp/D8fTJySBmGf/Uvj1THB/wCenPQ9wPzxySXBnpjjKMPp+QY5PX0Gfz5GMn6FafK2vpzdref4/wB4/KHs15f/ACfn5r799z+dL/gk0wuP+CkP/BaG7hO+3T43+DrVpOVxMfH/AO0SqptfDnJs7j5gpTMe7O1ojX9D1nje3uzc4PTD+/fIOOuM5Ixz/PP/AMEfrVrn9uT/AILMeIEdRb337TGh6THAd3mpJovj39pSSaVmA2lJ11SHyQGLrsl8wDKk/wBDNoMSHP8Aek/TcPX25x6rkkjNfC+Gy5eD8O+s854qk1rbXizO0t1fZRku12nvc/p76Z0+b6ROb0lblwvhz9H7CxaTv+5+j34YRmp6/Eql4u2isoq7Tb0aP8/09f8APqTzRSH7pH0/9C+vf6/iTX3X9fn/AJfl31/mL+vz/wCB977arxjOePXt6ev+fUnmkyPUfn9R6n0/nySCSHAGD04GeMd+OvGef8SRxG23byANpHUH+844AbkkjA5JySTwSaX+Xn3t2/4Pk1qHpr9/drs+3bvro25Ny4J3DA4JyMA8gZ546fz6kElpZACSygArk5HGWwO/8Xb1Pc9artLhZAc8BQvUkkswxgLnJAHVj3O0EjPyF8ef20vgn8BmutH1XWn8U+Nllijh8DeE/I1LW1uCA0MeqSCdbPRBcCWNo11CZLyeNs2dnOwCN85xRxfwxwTlFfPeLM9y3Icrw7UZY3MsVChSqVXzKOHw8HJ1sViqvLajhMJTr4urK8adCbV38nxlx1wd4d5FieJOOOJMp4ZyXCtRqZhm2Mp4WjUrPnUMLhYNyr43GVXFKjgcDSxOOqzajDCtuLf1/JPBHHI0ksSIqszb3VFQRh3lLMxwAqrvck4RRubjNfDPxe/bz+FHw98TW/gTwHZar8Z/H91ex6fB4a+HIttXhiuxOY5bW51S2kmtXvVKyQnTtNW+1G3u8R39rBH5ko+eo/Av7Zv7ZkqXHxM1Of8AZx+DV6xz4M0bzx4x8Qae7GRv7Q85Yb1xcRObcyaw1jZAIBJ4UmjYyN9z/BD9mT4OfAPSINP8B+FbSHU3ijXU/FOopFqHijV3RXQPfatLHvSM5kmSwshb6ZbyzXAs7KKN2Svx+jxl4p+J0kvD3Ip+H/CMp0n/AK+cdZVU/t/N8O5qUqnC/A1acMRhKNWnzrD5rxJOjFuSrU8sqKOv4PhuPfGfximo+F3DdTwu4FlKk14l+JGS1HxPn2F9rGVSrwb4b16lLFYLD1aSksLnnFlTDQfPCvSyacYpS95028a+0+xvZrS4sZLq0trqWyvAqXVo80SyPaXKI8kYubZm8uZUkdNyviVkCE6SnJIxyD19QC6g9evT2Hz8k0ihVG0Dt3xz8zAfQtjcR2+XjJOXDjp/9fq3fJ/H6j0Of6BpxlGnGM588oxhGU+VR5pJSUpOKbUeZ62Wiu0k7a/1DSjOFOMak/azUYKVTlUeeUU1KfKtFzP3rLRN2SSSFoooqywooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAGOAY3z6f+zSDvnHT69OcqDX8nn/AAX0Cah/wWE/4NldJt8XF3D+1b8cb65tUBMkenv42/Yyf7S44xEY9Mv23A522854KBq/rDb7j/h9eGfGOff69MEE5r+Tf/guBJHc/wDBc/8A4Nt7C3cTXlr8bvjPf3NpF888Vg3if4DMt1JGAWWB006/YSHjFtcsTiN6zqwVSjVpSdlUpzg3e1lKNWLd7O2kr3782jtdi026Wt8nJ/r/AE1d9F/wa0favAvwr/4KQfs+XbFJfg/+3l4+hktmBje2mu/Deg+DJ4zZuxktR53wxkGx1UeassQJkSYL/VHGcnPHJPP0Lj1PBzke2cniv5bv+CHcth8K/wDgqL/wXy/Zy1m8h0vxRc/tUWXxw8J+GbsmDUtS8B+MPH/xr1i51nTrabFzdabo2neNvh2lzendEYvEegzxyyrdiRv6j4QQfbLcfnjucDhu/c8nNf059M2rUxP0l+OM79hKlR4vyXwv44pVVSaoYuXGnhRwRxNjMXhaibp1qNXHZniourSnOHtY1afO6kJ28LhlKOS4alzKTw9TGYWVnqvq2OxNGKkt0+SnB2etrNr3nexRRRX8znuhRRRQAUUUUAFFFFABRRRQAUUUUAFRSnEMh5wADxnPDMeMHIPUjnOTwcgmpaimH7pxx/D1BI4c9QDkg55Gc4z1zUT/AIVTq+SVu/8Ay/2/D8PID+YD/gu98Z/jr8KP28f+CGOl/Bn4s+N/Asfjn9qvWNE8UeG/D3i7xFo/hnxlZXPxH/Zv8MSWXjTw7pt9aaZ4p06fQPGPinw+9rqy3CLpOua3p8SQ2+oXbyedNffFH4P/APB29L4c8LfEbUvDvgX9qf8AZe0Lxh8RfBuoXV7c6H490fwH8E/GHhjw3pOn6fKstpaah4e8UfC8eJdL1KEQS2hPjCyt7rOu61ZXP6If8FW/+CYfxU/4KBfHX/gnJ8Svh98UvC3w30f9kj4633xF+IN1fxapD43vfDGoeJPhT4gWf4c6rp2karDB4k06T4bTW9nY6x9i0eW81W01a7vm/sr7DN8Rf8FPotM/Z5/4OA/+CK37V16xurb4vWHj39krVLRWMJtry/1DW/CnhK8eeaVbd/P1v9pnzjCg+1Sx6XNAizyy2qL/AKO+C3F3AOc+G3h/4d5NLhzNONcw+iX9Mzg/jDK55Bha+bYXPo55xf4ocELH4zEZf7PFZhLB8M5fmGQ4iGIxGLyeEadWhjMNWqUqa+LzChiqWLxeMqqtDDQz7hvEUJqrKNOVL2WHwWJ5IKfNGKlUcaqso1LtSjLlu/6khkD76nGe5Pd/qSfbpwOB0LgTk5I9sZz1IGef9k/iD6EmFSCOPXGT0xlh659T+PTINSqOSc9yOg7GU9c+4/XuGJ/zihJST5bfZ2T2su72/S+9mfZRd7/Lz6dNeq/4e4+iiirKCiiigAooooAKKKKACiiigApjY2PkjGO5AH3nHUgjnbjkHnAwcEl9RyY8p89OD26hiR1OOuDyRznLDrUyvyTtvyu3RN/vd3ddl1VuZ66aHRvt/wDbef8Ad/Fa7n8Ef/Bbf9pz9uf4savD4/8A2hP2Kr39nv4S/sF/8FG/hLY/Bb4wXFt4rjm+InhTWR8VdRn8R2Wva4lronjLS9Ztfhv8PPEp1LwKkemeHLnWNL0HV5LvUZY7yL+8uwuPOWBlYOkib1ZTlWDRu6srAkFSBlSOCC2MgE1/NX/wUA/aP+AX/BYb9gv/AIKyfshfAKPxFa/HL9iq+v8AU9e8M/ETw5BpV7q+u/A/x1qfiC41/wCH4sNX1SS/0zxevw28Y+BdFub7+zdSsdU1DTm8R6PY6fqNpLN+iv8AwRQ/aPsP2pv+CXP7HfxFj1a61nXdA+F+k/Cjxzc6letf6ynjn4SLJ8Otdn1q5llmuZLzWv8AhHrfxJbz3j/a73StZ07UpixuFdv7j+kDl2ZZ/wDRr8I80reG9Lwkxvg34iZx4f8AEHAOGo5vOGFyzxK8P/D7jzg/ih1c1zDH4mhheNsXkfGWfRlKvPC1sdjsUsLGhBUlX+VyacKOb4+n9clmEcxwlHF0cY3T96eDxeLwleg+SEU3h41MPSskmoQjzNtya/VSiiiv4ePqgooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBrfcf/dP/tSlX7o+g/8AalI33H/3T/7UpV+6PoP/AGpQA3/lp/wD/wBmp9M/5af8A/8AZqfQAUUUUAFFFFABRRRQAUnY/h9cZP8AQdPpzk8rRQH9fn/X3eY0KOc5zwemADlugI56DOckdeD96Nh8rnBOSuBtY9DIOm0n+63fGT97BzNRR/W7799ey/HdNpq29nbz13V7PfppbrfW6bZ8f/td/sSfs8ftufD9vAnx18Dx6rJZJdy+FPGmlEab478E6jNbyxrqXhjxBDbvNCSziS50a/jvPD+pPFbrrOkXqRQpX4z23gP/AIK6/wDBK9Lqy+Fscv8AwUI/ZO0NoE0jwdqC6sPjd4P0hlPl2+nW1pb6r4ght9Ok8qzWHw/H400CDTRNfQ+E9Aj+0rD/AEsU1vuNkbhjBGM5BLg8fQjj6gnjn5TN+EcvzPFrNcJXxeSZ7CChTzrKakaGKnCKahQx9GUZ4fNMKnZ+wxtOpKKTjRq005X/AHnw2+kHxZwHw5W8PuIsp4f8UvCnF4l4vG+GXiDgquZ5Hg8TUk/rOa8I5hQxGGzjgbPqsIyX9q8N43C06s5QnmOBxrpq/wCNHwG/4LlfsK/FzVI/CPxA8U+IP2cviFCwstd8IfG/RJfDNlpGt2xMWq6bJ4wSe68OWYs7uN4Yhr97oepzIgaTSIJxNbJ+mnhH9oX9n/x/Zf2h4F+OPwj8Y2QVXN34X+JHgvXYFGcAyy6Zrd2sfITO5lbdheCWB4P42/sbfsr/ALRtjqNl8bPgR8N/Hz6havavrereFNMTxbaIUdFk0jxlYwW3ifRbhV+WO50nVbWdFYBJUI3H81tb/wCDfX/gm/qczSab4F+JHhuIlj9l0b4seLp4MFiQobxBNr0/ycbSZS5GNzu241wQ/wCIj4BOny8McQ04qSVeVXGZDjJLnah7Wl7HH4WUuV+/Ok4pyvaC3f07/wCJMOK4VcX9Z8cfB7H1HR5srp5fw54tcOU5+zTxP1HHxx/CGfUqEq3N9Ww+Op4itTp8ntMXUs0fqr45/aa/Zv8AhjYPqHxF+Pvwc8E2yxmVH8T/ABO8E6K0qrvyLePUtctpZ2YqMLCkjnBIBw2fxm/aA/4LKal8YtYvf2cv+CWPw88T/tG/HXX2vNKf4j2/hi/t/hn8NbOXzdPfxj9p1mG3g1ldNu3ja21vXl0v4exSPbajc65q9sqaLdeo+Ff+CAX/AATa0G+hvNS+G/jvxcLe4jnS08SfFXxp9jbY6ssc0Wg3mgmaHcm5o5XIkBKStJFhK/WD4S/A34M/ArQ08MfBv4YeCPhtoUawp/ZvgvwrpHh63nNvD5Mc98dNtLZ9SvNiqJr++ee9mdnkmuHlaRznUwviDnMKmFxWKyfhfBVFGFarlNevmudOi+dVI4XFVqGGweBqSVuXE+wrVIXTpxU4qZ15fnn0Q/DWrQznJMl8SfHjiXCNVsswHH+WZX4feGlLMKdSEsJiM/yHLs2zziPinBUpLnrZNHM8rwmJa9jisXUw0nA+Dv8Agmp/wTtj/Yx8L+KviH8VPEr/ABS/ar+NMy658bfivf3moavN9tu7k6jd+EfDesatCmpXei2+pvPfarr16kGqeLNV8jVNTt7eyt9G0m1/UpFwQOcADqD1w/GSTjAxj8B1xUn+f5+/+cnknJJX1eT5Pl+QZdh8qyugqGEw0WoRcpTqVJzlKdavXqzbqV8RiKkpVa9epJ1KlWUpSk2fg/iFx/xd4p8Y5zx1xvmss24gzuvSqYmuqNLC4TC4XDUKeFy/Kcqy/DqGEyrJ8pwVGhl+U5XgqVPCYDAUaOFoU1CMmyiiivTPjQooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAY/wDqpP8AcP8A7cV/I3/weN/8mG/sT/8AaRX4Qf8Aqmf2hK/rkf8A1Un+4f8A24r+Rv8A4PG/+TDf2J/+0ivwg/8AVM/tCUAf1yD+D6Gn0wfwfQ0+gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACj/P8/f2/nzwclNI+Uj3Xsezsemc9/XgcnIIo/r8/wDgfe+2p0b7f/bf/I+fXtq7I9R/nHv9PzHPq0lQpBIA46/7xxxnPXPv1wc5peOfTvn6sOMnjpz6grycVHIVEbZ55HfHO5scllAPcAsMnIzkZB/X5+fp97V9LtO/LK1r203/AL6tffW0dVqr7NpMz9X1nR9A0nUtd13VNP0bRtIs7rUtX1fVL610/S9N02xhlnu9Q1DULuSG2srK0gilmubq4ljgghjeWWRUQyVn+EvGHhLx34f0nxV4K8S6F4s8Oa7ZxajoniDw5q2n6xourafKH8q903UtNubm0vbaQJ8k8Ezxk5AY4xX4Hf8ABcz/AIKG6X8GvhD4r/Y5+FKR+KfjL8Zvh9r0HxDjsIH1CH4Z/BTVtK1m08R6nq8cUE8MWteKtHg1Sw0u13pc6Joov/Ft7JZBPDf237I/4I0eA9K+Hv8AwTk/ZjsdMm1KY+KPCN18QNQOp6hcX3lan411TUdbuoNNSWRotN0qNZITaabZpDbxM0080TalPf3D/HYTi7DZhxpjuE8DCGJjleVSxuZ42E5cuFxzxeHo0suSUZQq1VRqOtiEpRlQbpwknNziv6Lz76PedcJfRl4Z+kFxVicTk1XjrxCw3C3AnDOIwsPa57wrDI86x2Y8Y1pSq06+AwTzDLYYDJpTpVKWaQWLxFFrDxoYir+p1FFFfYn86hRRRQAUcdc8ev4kDv6j88jJIJJTTwrfT+Rfn9M+vAGSTmj+vz/4H3vtqfp/wf8A5F/1uuV9R+Y98d/b+fJwcxyPGsTl3RUGCzMVCgB3JJyQBgDOSflwGyCc1FnKnkZ6D72B8w25GD1yGzyASeMF8/gn/wAFL/2xPix8WPilpP8AwS8/YXuzqXx5+KNrcW3xs+IGnXDw2HwZ+G8tml1rVtdaxDDKNJ1O90SaS613VoJk1bRNHubLRdAt7nxt4j0IW3h5/n2E4dy2eOxMalerOpTw2X4CglPF5nmNeUoYTL8HTv8AvK+Immk/gp0lUr1pRpUpNfpfhD4V8ReMfGNLhbJa2DyrAYXB4vPOLeLc2nKjw7wRwblUI18/4v4jxkb/AFbLMowjdR04v61jcZLCZXgYVMfisJTn4d+1P8V/iB/wV+/aiu/2A/2aPEd3on7J3wh1my1L9rH426J+9s/E99pes3q23g/QLtrZre9s4tR0i4s/C22eXT/FHiC31DxULe88K+GLK4v/AOhn4R/Cj4f/AAO+HPgz4S/C3w3Y+FPAngfRrLQvDeh6cjmK0sbOJ18y4uZnlur2+vX3Xmoanezy6hqGoT3F7f3Mt3NM58O/Yp/Y7+F37D/wG8L/AAS+GdqZ/sUa6j4z8XXVrFDrfjzxrdww/wBteKtZZWmeM3ckKQaZpf2iW00XSEsNFsWFtbIW+u06nGcZwCf+B8dBjox6ZBYjIBNeVwrkOKwcsZn2ezp4jiXOVSeOnTblh8twdNueEyPLuZPkweCTbq1Iu+LxbqYubbcT7nxx8V8g4lw+QeE3hPQxuTeCXhrWxMeFcJjIKhm3G3EWIUKGfeKPGdOlJKtxHxK6FNYDCVuePDfDscDw7guSFLGyquxx82SeeRn1PT0yAPoScZPQGT1yOOmD1yw6/RQcZ/iHpy6ivsf6/r+vxP57St+HztfV/f8Al2Co5SVikI6gZHpnc+M8+oyeeeAchSakqnfsUs52B5ATnp/y1Hv7flnsSCf1+fn/AFproJu0W+yb9bc3l/d/HbQ/n6/4I0W63P7Rn/BXHX3ZhcXv7aXi7S5IV2iBINH8ZfFZ7d0+XeJZP7TkMxZ2j2iLy40G/f8A0BWo2s3OAGb8RlsZ/PP1x3Bz+BP/AAQ4Avde/wCCleuXH77UdT/bk+Jhvrw8PcFbq9vEyqARgLLqF1N8iqc3DjG0Jn9+Ywq7z259v41AJye5yPXrgZ5HxPh4rcHZc1a1TF51XWjS/f8AEGZ1u71fMua2l7pOSjc/pL6YEpy+kbxpTqS5p4LJPDHK5N7N5R4S8EZWuVp/w74Neyuuf2XJzpTUkW8j1HoOR1/P/H8aaXQKTvXGeu4ckE9PU8dPceuar4QAKSvMgHfHBOTnfkdjz7DnLGvKPij8afhn8GPD8viT4i+K9M0CyjWWWCCeZZdU1FkYhINJ0iEtf6rcs+D5FlBLIqb5GAiR2H0uZ5tlmSZfi81zrMMFlWW4ClOvjsxzDFUcJgcLRprmnVr4rEVKdKlGMU3+8nFu6UFOWj/lnOM8yfh3K8dnfEGa5fkuUZZQnicxzTNMZh8Dl+Cw9OMp1KuJxmKq0aFGMYRcr1qkHKzVNVJ+6euedFsJ3p0b+JcfKCzck4+VeWz0G7dggsPnr44/tPfBr4A6Ubrx54stE1OREey8LaVJbal4rv0YsUkh0WK4W4gs5Arf8TS9FvpUTcPeK7Ir/D15+0Z+1B+1deXnh/8AZY8HTfDj4fBZba9+Mvja3EM93aSTSxS3Hh8S2t1awylYp1FvpMWr6rErW6Xl1o1wyyP7n8EP2Cvhf8NtRHjXx7d3/wAYviVKFnvvF3jdm1K1jvpWUmbTdHv3vIkuIBFGLbVtRmvtZjIl+z6hHGzwV+F/8RU4v8RnUwXglw7CtlDlKlV8VOMcLi8DwdT5XNOpwxk0lh8341nF6qtRjgMnbirY+tTak/5ufjTx34ryqZf9HfhSFfI5znRreNXHuDx2W8A0eVypzrcHZBOOGz3xDqU53nHEYeOWZC3FJZpiKT534GfFX7aH7Z0jQeB9Ku/2b/gpqM20+LNUhvY/GfiTRbgz+Re6WVW3vJ457JoJFXRZrLTYZJZjD4svFXa31t8Bf2NPgz8B1h1PS9Gm8V+NJnkk1Dx54uij1TX7iVpJpZDZiRWs9GSeSRjN9gjS7uESE315czo0zfW9vFFaxJBDEsccSqqpGgVFUbxhVAAAAHIXjgDIOczg5zj2z9OcHr+eM9RnOK+g4W8F8iyzN6fF3GWY4/xG44i+alxJxTyYjD5O5ct6HCnD6j/ZPDWFi78ksHhpZi05OtmM5OUj6jgz6PvDWUZ5S464+zXMvFfxHh71Hi7jT2WKwuQuW+F4J4YUP7D4RwcLOMHgMLLNpKTdfNqk5cxUihVVOVOSGJ+Vhkl2JPDAZYHJJyw7MSRUyqARhSMd8HP8X97d03cAZPBwfWaiv2RK2l+131bXdu7d7K7bcu8nbX99StfV6u731equ22229Pek3Le8nuIMdh7dCO57Yz1yfxzxnNH+f1I7j24+vcYJWimP+vuv5/1d6PW5RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFADHxsbJ7r+e9sfmfx98ncf5Jf+CypW5/4OGv8Ag3jsYCJrqLxP8Wbqe2iIkuIb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JScXjqFVcz/nSGX+PfjTBvO8Rjfo/eH+IkoyyLKMXgcf4y55gG4SazHP8P8AWsp4Ahiqd6dfAZbHMs8pRlb+0cPVipP4J+Ev7APgzR9Yk+IXx61jUfjt8TNQSKfUb/xcs934Zt7suBGtro90ZzqYs4lSKJtVkks4tiGy0uztwIh+gdraR2sa21vbLb28Iiito4YliiSGIOiRxRxIqxRqvKqQAAQACxxWrRX6lwV4ecG+HmX1cu4SyPC5ZDEzVXH4397ic2zXFXbljs5zfF1K+YZvjKkm5zr4/EVmpv8AdRpx0P2Xw+8LOAPCzKq2U8D8OYPJ6eMmq+aY9Ori88zvG3bnmPEGeY6pic0z3H1pN1KuJzPFYh+0k3RjSS5XAExubuWyflOOrc/NnjBOcDPTgE1IvUjB69cEcfvAOT14PuAMdSAS+ivs0rX87fg5NavV79dtLWabf6Ba3Xtvrtfrvr53tpa1gooopjCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBpGR/wJf0fP8An+fev5XPhiBq3/B4t+0h/aP+nHwx/wAEqNB/sD7QxcaQZ/iD+z/532EEkW/mjxDq5dQMMdRvGxukZj/VIRkY91P5OT6fn7Y5By1fyffs43M+of8AB47/AMFCVvJWnGhf8E3vh5pukhjxY2N0n7GGqXFtEFABSW/v7q6bzNziSd9rBCFAB/WAB1yB/D+PDg8ZOcYGBxwx5Oc1ieJtA0fxX4b1/wAL+IbG21PQfEWk6joWuaZexiWy1LRtWs7nT9T0+7iPEltfWdxLbTxk4aGR0OS2Tu1HJxG3G7lRjBOcvjsc4Gck9h34oU6lL97RqTpVqdp0qtOc6dSnVg5unUp1Kco1Kc4yjGUJwkqkJKMoSUlcVk000muqa0e+62s7K61W+nxc38sv/Bur4o8Qfsw/E3/goV/wSI+JVtc2Xif9lP446/8AE34VXWsTeVqnij4MePL3T9NtdStrDYinTHig8HePbXUYQVvYfiVbrJFCIIRJ/UxGee3+S/6H17joSM4/lC/4K7Qr/wAE4/8AgrZ/wT5/4Kx6FHf2nw4+Lmtj9kj9rLbIbTw9Hoeo2ktnoXinUL2MNJcaing251XxGul3LrYTy/B3w2tt5M82oXY/q5t2SQJIjllZRtyDk5DsD1/u4I74xnHWv6g+lNCjxbm/hz9ITK1fAeP3BuDz/P8AlXs6eD8WeFqkOFfFjLVSnOU4SxOeYDD8WUYuyeWcTZbUp0oUZwT8HIG8PTxuU1H72VYl0aV95ZfW5q2Am3ZqT9lL2De/NSmk3JNlqiiiv5fPfCiiigAooooAKKKKACiiigApjkhGOemOfQbjnv6Y9vXjNPpp+6eM8jj1G457+gz+I4JBpP4Za2037fHr+H9WVw/ET4Uf8FHf2mvD/wDwV3+Kv/BOH9p/4A2Oh+DfiBpuqfEP9jP4zfDnStffw/4i+F/hrwvrGva3P8SdV1zVriG/1h100aJfXWg2Onw+H/HNtc+GrrT7vSdR8NeIZf21BBXPXoc8884xjsOD15AzyDUT2dpJcxXclrA9zbxyxQ3DQxtcQxSlDLHDMy+YiTGNDIqNtdgrOGKKatcDdhegGD2+8/v1GAe55I/ibP1/HHEPDvE+LyHGcOcEZZwN9Q4S4fyTP8HlGOx2LyzPuJcow9bB5hxfhsLjKlSWS1eIMPDBYjMsqpVa2FWcRzHH4epThjPqsOTB0a2HhXjWxU8UpYirVoyqQSqUaM5OUMPKUf4ns22ozaUvZ8kGm4c7+d/2r/gd4f8A2mv2Yfj/APs+eKLVbjSPjB8J/Hvw/mby0eazufEXhvVtP0vVbPzDtiv9G1OSz1bTZ25t9Qtra5Dh0Vz+Lv8AwbBfHrVPix/wTE0X4UeKIp7Pxj+yf8V/iP8AAXWrS+LpqEmlxajb+PvDb3FpKFmshpFp42m8HR200cUsf/CNSCSISbif6JG27W3AbcYOe/LD164H5sO5Jr+Wb/gkZqL/ALO3/Bcb/gth+xbJDb2+i+O/GmjftYeE7dIxYLYHxRqNn4r1Ky0vT0KW8lhc6X8fPD8PmQIogj0G2RVKSMqftnhQp8Y/Rp+kt4eShDGYjgvEeGfj3w9RlXVGphJ5BxIvDjjKvRptpVFiMh8Q8Hi8SrpSjlFClKnOtLDTj5mMtQznJ8Vfl+sfW8rrS5b8/taLxmHTdtLVcFKMet6k3zJJn9UX+f5+59P58nByU0Dg4PJxjJzgfN05PXA/lnhiXf5/n/hn8R1INfzKe9/X5/5X+a3aYUUUUAFFFFABRRRQAUUUUAFRSkiKQrjcACuQTyHfHAIPcEcg88MDlqlpjjMbgdccdeu58dCD1APBBwx5JOamV+Sdt+V29f31v/bfx8wPwl/4Kof8FB/2jf2Of20P+CSnwd+GEng6y+FP7WX7RyfDL413eseGW8VeJ9U0m68c/CHwZZ+H9Cs01DTJ/DyPb/Ea/wBVg8R6bLfX8WtWOmNNp9xplnfeHNY/dTA4Y45HHGCMsxwMn1CZALDrwT81fjL/AMFnP+CbHxJ/4KF/DL9m/U/gB4r8I/D79oL9mr9ofwh8W/h/468Y32t2Gn6d4fhZv+ErsLe40fRtduE1L+09O8HeK9MV9PKS6l4XtrBru1iuric/spAkqBBM4fCgE4O4kbwTkAAA/KSCQemASSR+v8dYjw6xHg/4APhmGVUeOsFgvEfJPFHDYOjiKWa18dhuN6ub8I8QZzUqOVHE0cx4f4gpZPltSlP2kXkGOw9WhTpUsLUn5eCji45hm/t/aPDSlgamBlNrkjGWGdKvRpq94uFWi6k01a9eLUpSch0sUcsUkUmCkiMrggEMG3oysC3IYEgjoR8pxuzX8q//AAQvaz/Yp/4KR/8ABWD/AIJU391LDpGkfFGL9qH4FW7I6W03gLxNZ6DaajZyGVYzJqlj4N8TfByy86JSmpHSNevIkjtLaBpP6rGwELYyNwGOuBvxnnsPvE9AAeQQWP8AK7/wUdvY/wBkb/g4h/4JK/tR6RZRWml/tReE/HX7LvxDgsJzYHxVcJqCeC9OvvEDvG0V5/wj178avh9rVuF23d0vhXStPknSCK3I+/8Ao0TjxLlHj/4LYtxnh/Ebwjz/AImyOlGo6c/9fPBqhX8UOG61JK8p1cVlOS8T8PqMFd0c5rRrTWEeIkc2cfuJ5XmUf+YPH0aNVqL/AN0zCX1Ksrc2yqToVXfZwjZOSu/6qsg9CD+P19/b+focrVdGBG4fxYHXGcFypxn1zk5B9c53VMM9OvPX/v5x19l/Jx2Jr+YYyUlftyrTu21s9V0/HdanuJ372019dvPo/TW9rauoooqhhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA1vuP8A7p/9qUq/dH0H/tSkb7j/AO6f/alKv3R9B/7UoAb/AMtP+Af+zU+mf8tP+Af+zU+gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAGP/qpP9w/+3FfyN/8Hjf/ACYb+xP/ANpFfhB/6pn9oSv65H/1Un+4f/biv5G/+Dxv/kw39if/ALSK/CD/ANUz+0JQB/XIP4PoafTB/B9DT6ACiiigAooooAKKKKACiiigAppICknoME59A3X+vP5g/NTqY5xG/BPTgdTl2Hr9ffngkg0C6N9l/wDJ+f8AdX3vUgaWJYyW+UZ5z9XIHJ5yFOeegYgZDV84eGf2sfgh4o/ah8bfsh6P4kup/jT4F+H+l/ErxD4dfRtSisofCeo3Gk28d1b648P9m3V1bnX9CnurGKb7SkGr2E0aShdQMPCft0ftnfDb9hf9n/xJ8ZvHYGoanhtC+HnguK4hg1Pxz45vLe6bSNDsg7mSOxiMDahr+qpFOuk6JDdXvkXFybOym/n3/wCCM93+0D4v/wCCsf7TXxD/AGnbS+h+Mnib9nKHxf4ps75rhZvC+k/EbWfg34x8I+GTp0lxct4dt7PwtdeH4dN8L3UgvtD0+CLTbpRdwXqj4XPeMKWW8ScN8M4RRr4zM8yo0syfs5TpYHAVMFmNbDqrUjK1DG42rhVPB0p3lUw1LF1ORwjGo/6k8I/o443jfwT8bvG/iarWyjhzgPgvHYvgemsTSwuO4v4uwPFHB+W5rUy/CV6U6macN8L4HPI0eJsZh+Slg83zXhzCLFPEVKuHX9blFFFfdH8uBR/n+nr/AJ9SeaKTsfqPX+9x39ff8xQH9fn/AMD7321Xj1/z09f8+ueaacbTnHY89OGY+vsT69epOSZHYMenIye7AY5/2cn1BGSeaZKQI26kjbjhj0diDgfQ++AecBjR+n/Df1+d9RN2i2t0nbtf3kuvkuvXe7uRlhgnggAdmYYBY+hycHOACM9M5Br+e/8A4KT/ALTvxR/as+Nemf8ABKH9inVDN4x8cQTN+1N8T9NV5tJ+F3w2iWC41rw3d3kCFEeewu45fFskV/Z3Ehu9D+GtlNPr/ijULS1+qv8AgqT+39qv7Kngjw58FPgNYz+M/wBr39oBx4W+DPgzSLCLWdT8PLqVwukv4/1TSJY7mB0tbuVbPwpp2qQm31zXRNLNBPoOjeJpo+4/4JjfsA6V+xD8Iry+8X3aeMP2jfi3PH4v+PvxIu7qbVb7UfE9889/J4Z03V7xTeXOieH7q9uQ19OVufEOtXOp+JL+OKW6htI/z3PcViuJczrcGZTWnSwlGNGXF+a0JOMsHga0eenkWCrRknDNM2p39vODcsDlvPVk1XrUUf134R5BkvghwJg/pMeIeW4XMeIMzr4vCfRx4CzSlCtS4h4oyytPDY3xX4ky2vFxr8DcAY2EFlWHr/uuKONKWHy+HPleX5tUn9Rfspfsw/DP9j74G+C/gT8KdMe10DwtZgXmp3KFtY8UeI7pPM13xf4hugD9p1fXr2I3dwq7LSyhkttJ0yC202zs7dfpBAc9+PXIHBYDAIB/iJ+h6dcy0V91hMJhcBhcPgsHQp4fC4WjSw+HoUoqFKlRoxUKUIRiklGMUklvortvmb/lnPc8zrijPM34l4jzXG53nufZhi82znNsxrzxOOzHMsbXniMXjcXXqNzqVsRWm6k5N25naMYwSQUf5/p6/wCfUnmikPQ9fwznr25z+vT1HFdB5Yv+f5D1+nfuOp5NS95tZQpBJMWO+f369s/5yTk7STYHdsgjHU8c5YYGTwOB75POc5qC52GFg+QuVLEZyNrhsjnnBCse+M4OCTQtNtdV0b+1Lpu95aeS13M53dKaW7hJLe3/AC8Sd1/ivpd72b1cvwJ/4KBxJrf/AAVq/wCCPnhUkltN1/41eKpREPNuREtp4YvV863AJhtm/wCENl/0lht8sXkgbNs1ftD8WPi38P8A4E/DTxr8YPir4ksvCngTwNodzrviLXL9ysMNrEWWG2toVDTX+papcmHTdH0qzSbUdW1O5tdL023nvp4YW/HT9rHwz40v/wDgtd/wT/8AG0nhTWl+GHw8+C3xg1fWPiCdI1CPwfoE0nhr4vWmq/8ACS+LJIToekrp6XOis8N5dW01qdQsbi5cxXtka/Mn9rL9ra5/4Ki/tO6X8JfDFr4s1/8AYj+C3itbybQ/Bh1PTdd/aS8dac10sYtruPT7m+tNEvcSQaPHDp8+paD4Xmv/ABMbdPFOs+Hra0/AeJPEfJvDHA+IvEue16eHxGP4tw+X5PRrwrtYurR4c4ewWGqqlRp1MRXw9OrLlmsHSrVq1VxweHUsTUR/cPHfDvA9bwm+jZxf4o8a4LgHwD8Fvo7z4v8AGPxChVpY6rlT4o+kB4x4rB8E8N5dhJ4vE594mcb4x0Ml4L4PwdHEZtjswxCxc8BHK8JjcSvrT9lr4Y+O/wDgrL+0w3/BRD9rHRbrwt+yZ8HdVv7b9k34J+LDBb6Hr8WjXwnfxz4qhuof7K1LSob61i1XxJqUdxPZa94vs7Xwu2pXHg7wl9mv/wBSfix+3v4fttcuvhl+zd4R1H46/EkyCG3j8MQXF54RsIopAZbz+0tLjuTrUNoHi819M/4lUYcpfa5ayRyRnxfwX+yv+0L+0DpPhyw+MmpWPwE+Bnh/TrKx8IfAT4Y21to8dp4btYli0zRLyxsibKxt7SzS0t4Tqn9oXUIFyltpWlShZG/SP4R/Av4WfBLRbXw98PPCWl6FBEhM97HbrNrOp3DGXdd6vrUxk1DUZ2RvLU3VxJHFCY4LdUhRFHyvC68WuM8HiafDGFxXhvkWbV3jM48QuLstpVPETimrWgoSxPD/AAjOrVpcJ4SlSlyZRV4gq16+GwsKMY5TCTnJ/wCb3jT9ITx++mHxFgY+GvCVX6MfgFwnllPhbwuw/E2CpY3jvLeBqM6kqT4Z4MnUeGyDOc7rTqZ1nvGXFrr5xnud4jEZnWyinF4alT+CvDX7G/xr+P2tW/jr9s74h6heWUdzFeaX8IPCF49l4fsYJjJOltqVzaKlrbNaiRraUaabvVv3UCz+JpyJYx+jvgX4d+CvhtoVl4Y8B+FdK8M6FZH91YaTYpaxFkWUefcOVM13czOPMmu7mSWeWZ5JJpXdpd3fDHPcj5e56Fh0BHoCR9cEgHKjHY9PQ/XHc/5J565/YOBvCngzgCpicflWExOZcR5govOOMuIcXVzni7OJq3M8bnWL5q9Og3fkwGB+q5bSi406eDUVK/k+HHgnwB4Y1cZmmS4DFZtxXmmuecfcU46tn/HOeVHrN5hxDjlLE0sPf+FlmXfU8poxtCGBUborRoygYUg5PPzcDLDpnPv0yQV7KCZE3BuVbGeDxgABxnGc5PHU56ck4NTUV+jKPKkk7JWWy6P0suuisrvyd/1hRskk7JW2SWi6WtonrorLV7vUKKKKooKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooATHH4j07Nn/AOv6+h3c1/JH+x7PNf8A/B4//wAFbTdyGb+w/wBhz4LabpWQqi1sbv4af8E/NTuYFCBfMEt7eXNyXm8yVWkKI4iVUH9bv+f1/wA//rr+Rv8AYQzqH/B35/wWd1C6O+5s/wBkf4MWMDgBFW2i8AfsKWUaFEwrFbewt03n5yVLMWdpXYA/rkprD5GH+eGbB/X+XUgkupp+63+e7e/t+e31OU1eMl3TX/pf+a+/rqH9fn/wPvfbX8//APgp1+xfov7f/wCwz8ef2ZdQkFpr3inw0dc+G2r7bctovxU8IXB8R+Ab1pLmKVIrC91vTrfRNfKeXcS+GdU1q0t7u2mmS7T4c/4N7f22NV/aj/Yb0r4MfFeW40j9pH9i7U4/2c/jR4O8Qy3Mfje3tPCEM2j+A/E/iLTNRI1WzutR0jSbvwrrE9/ukn8aeEfF6s6SpJbJ+7jcKThj0XjOTkkEjAJGMrz0+YEkBTX8k/8AwUS0zVf+CNH/AAVe+Dv/AAVW+HNn9m/Zc/bF1my+An7cXg7SLO4W103xTqTQXo+KK2ixvp8OoXmn6JB48snsUsr+98VeDfGmmXeob/iJq8kn9W+BcqPi54Z8b/RjzCrD/WLE46r4q+A1etU5efxJyPKJ0eKeAqLUua/ijwthFhMsoXjh58YZJw1SqKVXE8589mPNl+Lw+dQTdGEYYHNFHT/YqtVPD4tq9v8AYa83Ko91hqtezSWv9cGR6j8x/jS5B6EH/JHr7fz5yCTkaVqena3pun61pF7a6jpmqWVpqGm6hY3EVzZahp17BHc2N7a3MLvFPbXdu8dxbzRuySQukkblXDHTXqQM4zx6f8tOM5PXAb6444yf5S96MpwqRlCUJuDhOMoVIyi2pRnTqKMoSTi04tcyejT+J/QRakk07ppNPo172q33tpr31erJKKKKYwooooAKKKKACiiigApCQASSAMjk8D72B1Pc8deD3J5paa2NjZGQMcYB6M3YkjqAce45yc0nom+y/wDk/P8Aur73qH9fn5+X566O7QyDoRxwD+Lf7Rz3OOSOp4pc5DDIJ4IwScjc/wCR4HGTkkE9Aa/PX9jL/go/8CP23fi5+2P8F/hbofxA0Lxh+xl8X7n4QfE238d6ToWmw6vqltrnjTwyniXwn/ZHibX7ifw5e674D8VWFk+tQaTqzxWMV3c6RA1z5I/QYEHdjJOeo7YLdsk89+c9CDyc+zxHw3xFwbnNbhzi3JsbkGeYfC5VjcRlOZUY0MZSwedZTgc6yjETpxq1YqlmOV5hgsww0ozlzYXE0Zvlk5RMcPXo4ml7bD1YVacpTipwd4uVOrOjNJ2V3GdNxd18V0m0uZtbG1vQBfXk7mGTzwAfmJ7DdyOTX8s/7Zt/dfsxf8HNv/BN340WDxaT4Z/aw+AXi/8AZ58b3F5FDFp/iDVNMn8cWumWlreuQV1iDXtc+FHyo3mFbbSdPJEd7MD/AFNMPkYDrj36nft57du4OCCeAtfzW/8ABzd8I/iQv7JPwF/bg+DkSxfEX9gH9o74f/G+21cCGe80TwvqOu6Ppk+rWWk3VrdW2tHTviFYfDDVNSsbmI2sWg2Wr6jfhtMtb+Nv3b6JOJwtXxpw/A+PqYahg/F/g7j3wZlWxbmsHRzXxE4SzbIeEa2JjCE26eH4xqcOYiNTllLDV6VLG0oyr0ad/Jz6MllksXBScsvr4PMbR+J08HiFUr8uqSvh1WTXVOUGrNyl/SmrYweOmBxyQPMIHU5xwTj1GSfvGQHJx7+vOP3nUdR91T+J5JJx498AfjH4O/aI+B3wh+O/gC8F74O+L3w68GfEfw1OxUzJpHi7w/p+t2ltdoOYb+zjvvsmo2soSe0voZ7S6ijuYpYh7AoALepyR9Czd8nPQY/Hrg1/O2JwmMy7G47Lcww9TCY3LsXiMBjcLVShWw2MwleeGxGHrQUnyVaNenVp1IX0krO7dz2aclUhGpGSlGcYThJaqUZRbUlrtJLTys2nfV9FFFZFhRRRQAUUUUAFFFFABSEcEZ/H8c+v+fU0tMfARs9OM9ezHnj06n69Scmk9E32Xn/f+f2fXVb8up/X5/8AA+99tWYGD9Fz16EAZ9sY+vJPUU7Awecn0xgnmU9Oo7fmOckGvAfFH7Un7O/gX4/fDj9lzxZ8W/CGifHv4t+Hde8V/Dj4UXmon/hLvFHhvw7FqE+q6za2UcbR2tosek6udPbUJraTWDo/iFdEjvm0XXBB74rBhjpux9fvMeO54y3PqcEgMT04rLcwy+ngK2Y5fjcDSzfCLMspq4zCYvDUsyy5Y3F4FZhl88RSpRxuCljMFicLHF4b2mHeKw2Ko+1nVpVjOnUp1PaKnOE3TlyVFGUW4TUVLlqKLfLLllCXK7SUZQdtbtrA7GGD0wOvXDjr9QPpkA8AGv5gP+Doxn+Gn7On7EP7WekWUsvin9mL9uf4V+NNLuYkheRNLOi+K/Ed7YCKcrE/9o694D8JnZPIsJ+zCKdWjd5F/qCIO0nJxxzgd8gnqfb3ySckjJ/Fr/g4W+Clt8bf+CQP7XtiLGW71n4deGvDXxi8PSwkCSyu/hx400fxDrl0A4ZGjfwfH4lsrgcMLa7maJvPWM1+4/RWzjCZB9JXwUx+ZVVSyvF8f8P8PZzKf8F5FxXio8K55TxCbtLB18rzjGUsdSd41MHUr05xlGc4vy87pTqZLmkYXco4SpVprrz4dOtTta751OgnDdqfK01a5+yWmX1pqum6fqVhMlxZ6lZW19ZXSE+XPa3UH2i2mjJAYrNDIsiZwSuSRkc6adTz36AcY/ec9cdcAfUcnv8ABf8AwS8+NFl+0H/wTn/Yp+LNtrA1668R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59wEAADQPlEqPz9/7NixZCtUQUGBrq4u0QMiOjr60KFDFy9eZLFY6enpO3fuJDsRGBgYGBsb+/j49OvX78svv5w6daqbmxsxAGXHjh1aWlrGxsYeHh4+Pj4LFizo378/k8k8dOiQnZ2dp6enqqpq7969qedAkxYBKZRBQJ70AStXriQqEltEk1UBtFFiYuLBgwc/m4ns5FFRUbFq1aozZ85IpLEHQMkVFxf36NFDX1+/s6PUyJEj79+/T/Tow3Hc39+fyORWW1u7dOnS8PBwFotFbEZNCsdkMr/44gsOhzNjxgwzM7Py8nIMw6gbMBgMone4rq4u8QfRpUJPT096kIqlpSXN95QCGQTkSR+gp6fX7vNJg9aGqHnz5hGZKboPXV1dT0/P2bNn37lzh5rCCgBlVltba2JiwmAwuFwug8FQeD+KjOr18vJisVh+fn5RUVE//fTTxo0bif7o8fHxVVVV1O7jMseIjBgxAsnRZEVvxowZiYmJEiMleTzewoULbW1tX79+raGhsWrVKldXVzl/dL98+ZLovgiUVnl5+fz58/39/SdMmNDdrn3OnDnOzs5LliyBjGigq1BXVzc3N7ewsFBTU2vTjhTrdCEWizMyMtLS0sRiMbkwJSUFIfT+/XtyyerVq6l9/LKysnr06EHdD9Fn4cOHDzJfJicnI4SIPn5hYWES5zBx4sSYmJh26UNSV1enr69fUFAA0w8rLZFI5Ojo2KopyT8zAoHAyspq79698DCAbkVVsdiGYZhEmlGyiu/OnTtr165FCIlEoszMTGovOzKkkQUp4och+fNQ4iVRC19dXa2urp6WliZxuI0bNwYHB0sn71HAxYsXv/zyS8hwo8z++OOP1NTU69evK/+pvnv3LiEhQUNDw8HBgeg1mpKSQvwGMjExMTExycjIyMnJQQgNHjx41KhRTU1Nd+/e7dGjh5mZGU2LpqqqalhYmLW1taurq5mZGTwSoJvo0Y69ojEMmz179tmzZ1NSUrhcbmRkZH5+/pMnTxgMho2NTWZmpre3d2FhYUZGxoABA1gsVklJyfr163Nzc3Nzcx0cHD5+/Ei8zMrK0tbWHjZsmKamZm5ublxc3D///LNkyRJDQ0Pq4caMGRMcHGxtbU3fMa9FAoFg7dq1p0+fph8mDD6huro6Z2fngIAA5a/ri4mJ4fP5Li4uffr0+f7777/++mti+fr168vLy52cnNTV1TEM27JlS1pampubG9Fh58yZM9XV1XZ2dtR5WKTp6+vn5uaGh4cvX74cngrQXXREAa2urq6srAzH8dLS0pKSkqamprbsraioqLq6WuaqjIyMqVOntjGB4bZt20JCQrpb7VlpaemNGzfGjh3bxv9O59i/f//gwYNlju9WquuqqKg4ceIE8XdCQsLy5cvJVVu2bFmzZg05hNzCwmLx4sXEy9raWiJttDxSU1MRQq9evYKKINBNdEjmjl69ehF94fT19fv169fGdDiGhobNzX3e9rQI3TN9QGJi4pkzZ8rLy5OTk9tlru4OJRKJgoKC1q1b1+J85J/8uiIjIx0dHbdu3frjjz/6+PhQ8yWamppmZmYSf589e3b9+vUZGRnEyzNnzqxatUrOQ5iZmc2ePfvUqVPyn9W6deuG/1dISEg7Xm95eXl7/YuLioo+1QPWXlfRFocPHyb/R9SJDgBSrCe6UrGzsxsyZIhIJFJszmniM9/d/usTJkyYMGFCYmJilzjbO3fucDgc+qlDlOS6Kioqhg0btnLlyr59++7YsaOkpMTIyIhYNWLECCJK3b9/f+rUqaqqqpmZmTiOv3jxYvTo0fQ5aCR4enouW7bs6NGjck6VUlxcHBERYWFhocAVFRQU3L17t6ysbN68edRh9QihU6dOWVpaEr9Hk5KSGhsbMQzj8/kTJ05kMpmFhYVcLldNTU0gEAwaNIiork9NTa2pqVFRUenfv/+gQYPIXUVHR6elpf3444/kEg6Hw+Fw1NTUcBxvamoyNTVVeKxYeXk5h8ORuYpoVoiIiLC2tv60lcnbtm0jcgnFxcVFRERAZKJS+QyuoS1pESB9gPILDQ21tbWlmQW43b19+/bo0aPHjx9//vw5+aW5UpYDBw5QK88RQhiGjRw5sn///sOHD3/8+DG1LMXhcEpLS9+9e2dra2tqalpbW5ufn//48WOZs4vRmDFjRkNDQ3h4eEffh7i4uNu3b3/zzTfr16/ftm1bUlISuer48ePa2toTJ04kXlZVVXl5ec2bN6+oqIjo/cTn80NCQiwtLZ89e9bU1ERGcTc3t3PnzlHzkRL/YomWNj6f/+DBA0tLy8DAQC6X25asQB8+fLh8+fL48eNDQ0PfvXv37t27+Pj4GzduODg4xMTEIIRWr14dGBiYnp4OnzUlBZWe3VZCQgJCqKGhQcmb0HR0dFrV/bot1yUWi9etW7du3bqamhqxWOzs7Cz/ftLT048dO0b8LRQKp02blpKSQt1z7969V65cWVtbSywxMDBYsmRJRUWFAudpa2s7ffp0OTdeuHBhQkJCaw+Rn59PbS1bu3Yt+bKoqGju3LnUUSjEBsOHD6cuOX/+PEIoJyeHXFJZWenj4yNxoLy8PFdXV+kT+P333zEMq6ysbPtTdP78eRUVlaqqKurCI0eOsNls4u+CgoKFCxd22lPN4XA+fvwoc1VsbCz9DN2ddiafebsUAO0lIyOjsrLSxsamjfsRCAR5zSNmcUQI/fLLL7Gxsb/++quGhsbr169VVFTkHzP/8OFDsVgcGhp67do1Hx+fPXv2jBo1ilyLYdiIESPc3Nw0NDTI0pWzszORMqa1Zs6c+ebNmw4d4RsSEkIMKUH/nb550qRJxMuAgIBFixZJDMxnsVgcDocs9DQ2NkZFRRHFUHKbkydPbtmyRfpAK1eulD4BNpttYWHRLnNtsNnsCRMmaGlpIYREIpFAIEAIaWlpkd2GBw4cKBAIOjoPKtGhLCgoaMyYMdRy9icpnCjJmchDFb4HgTL7559/EEJkzZLCsrKyjh071txaa2trLy8vhNCFCxdGjx59/Phxoi3k0qVL8k+SwuPxvL296+vrMQxbtGiR9AbR0dEGBgbkyytXrlBftoq5uXlNTU1GRkYHDZwSCoVEXVlMTIyWllZCQsLq1auJKIXjeFRUlPQIFhaLxefzeTweEXeDg4N37doVERFBRqlXr16NGDGCCBXUAz148EBmByg2m+3k5NQul8NmsxcuXEj8/eeff/bv33/q1KkuLi7UwSfOzs63bt2iT9naFjweb/ny5cbGxlpaWkSp7lN9ppTnTCBKgc8kShkYGChW4KAaNWqUPN3bMjMz/fz85syZo8AhiMZRmgmLJWKSwiEKITR8+HDie7+DolR8fLylpWVNTY1QKKyrq8vOziYHfhUWFlZXV0sPLiRm7+RwODo6Orm5uaqqquPGjWMwGESUEolEkZGRBw8elI7cs2fPlkigShwlJyfH3t6+7deSn5+fm5tbW1sbGhqam5t79epVooFNojuGiYlJcHBwxz3Jffv2vXXrFkLozp07n/YzpTxnAlEKtIDoq63kPdGTkpIGDx7caddlZWVFzVsWFRVlZGQkZ++vTZs2ddptIaLU69evly1b1hH7f/To0bfffqujozN27Fgixm/dupWoGioqKpIYXy8RpczNzU+fPr13714Mw4yMjIgode7cOQ8PD+mC6blz52TGhocPH2IY9sUXX8g8PYFAQJMSQVtbmxpE2Wy2ioqKp6enmpqajo7O69evZdbiGhoa0uwTQJQCnSozMzMoKCgpKUlTU/Pf//63sbHx7t27OyEDpAIqKirkr+5r+3UFBgbu2rULw7Da2trCwkITExP5Oyi3OJyrHfXu3btfv35tH2NUX1//+vXrpKQkY2Pjr776iizTVFZWUsuvAoEgPz+ffItEGh0C0eeey+XeunXL0dGRGCVJRKmSkpKqqipimmmJUg6DwZAZ89hs9vjx46nBBsfxEydObNiwAcldf0vdFfEUmZmZNReKNDQ0Ghsb4csBohRQCqampr/88kuXONXKykr5s6W0/brMzMwiIyOLior69OnTqjFMnY9oVFD47TiOR0REHD9+fPv27R4eHvfu3duwYcPJkycRQkKhkOhfQC1akUlE9fT0ZB5XXV1dV1c3MzOTw+GQ7UxGRkY5OTmBgYHe3t7Sb2mu3wQRWiRyud29e5eso5Oz/pbc1YIFC4i/e/bsSXYJkVBeXk4dwgUgSgHQMqFQ+PHjR3V19c48KFFPpfw3R0NDg8fjKfz2nTt3hoWFvXjxgvhqnj9/PlnzFh8f//79e3LLjIyMixcvxsbGEi9NTEzKy8tljqNnsVgXLlygjqpmsVg3btzw8fGRbq4TCATN9ZsoLCzMzs6mZjFNTEzctGnT69evW3uZubm5eXl51Dx2zeFwOJC8FKIUAK1D/Gbv5CjVVfTu3VvhGr8HDx74+/v7+/sTIQrH8cuXL9va2pIlpzVr1uzbt2/kyJHZ2dnE9BNk66C6urqFhUViYiI1kxxh4MCBXl5e/fv3p0YpR0dHmb1RYmJi5syZI91vYs+ePUSr/uXLl9lsdl1dXXp6+pMnT1asWEF24pfT/v374+LiNDU1r1+/npmZuXXrVvp7Mn/+fHiuIEqB/7N79+62zED4efD19aWZlb+mpgYhRD8P5Gd8G+lvDpPJrKurU2zPRL0on8//5Zdfqqur6+vrjY2Nf/rpJ2Itj8ebNWuWvb19WVmZi4uLdJnp+++/v3z5snSU+s9//iNRHFm8eHFzk2SGhoaePn1a5lX7+vq2yw3ctWvXrl275NlSJBLdu3ePfgI9Ykr7FnvlWFtbHz9+vEMfDOU5E4hSn3+UalXalPLy8nbJZy8SiUpKSjpzwiGFr4KoJqJ2umv7bew40mmliGJKXFyc9BeKvb090dMMx/Ho6OiePXviOK6lpTV58mQ5D8fn8xXONfPkyZNx48b98MMPampqEnlUhUIhEZbU1NSaq/l0cnI6ffp0WVmZvr4+dfnQoUMltmwuq05eXh6TyWxLX/z2denSJXd3d5m9Qkh6enp37txpMTZ0QtFfec4EolT3QjOtJ+quM3sS3xoKlxg6U0xMDIPBWLp0KZfL9fT0vHbtGrXQM23atMjIyIEDBwqFwqysrIMHD7LZbOIbHMMwY2Njc3Pz69evt6rPfUNDg2LzMuA4XlNTY2ZmJvNLOSsrq8VIiWHY6dOnfX19f/31V8WShYeEhMg/DXxHy8rKunfv3pkzZ1rcUnk61Ch51572BTMkKQWaaT1RN57Zs1evXhiGKX+UqqysJDJ5IoTKysqozScYhqmoqAwYMMDZ2XnixIkTJkxYunTp119/Tf0dwOPxWCyWk5NTq3pt1NfXKzbYGcOwoUOHSpfDnj17VlVVZWZm5ujo2OJOWCyWj4/Pw4cPFbtjTCbzyy+/VJJ/38uXL4ODgztzIAGAslTXK0UlJSWR85sNGzYsLi7O3Nyc/N6PjY0lxooT7OzspkyZ8vfff5PTAZiYmNjZ2Z09e9bJyYn8PT5mzJjly5dLtNnk5+erqalJjFAZPnw4i8XCMOzIkSNtnDZt7Nixo0aNUlFR8fPzo86F06dPH+KgGIb5+vpu3rxZnvQEGIbp6upWVlbSbyYWiysqKp4+ferj4/PmzZs25jNTAJlWSlVVNTU1NSgoiLr2wYMH06dPxzCsqqrq4MGDAQEBa9asoTb2sNlsYoNWHbS4uFi6ZUhOnp6eEREROI6TB7158+bLly/JDhTyMDAwULjKjmwDUwbffPNNZx6OqMGmr8fubmcCZSllRzOtJ+r2M3uOGjUqOzubfptPnvyQTCu1efNmPT29kpISiRvS2Ni4e/fumTNnEnNGSHy5E1GqVUesq6vj8XgSzULy27hxo4WFxZYtW/7666+goKDt27erqKjs27evtZEStMqSJUvs7e3XrVunqam5adMme3t7Nze3bn4mUJbqAmim9UQwsydCY8aMCQ0NFYvF0l2WSR2a/JDD4cjsnTF06NCdO3ei/00rRRRMHz9ZqkpvAAAEyUlEQVR+TDa8NTY2Pn36NCUlZejQofb29gMHDpTYT2Nj4z///ENtFDl16pSXlxd9wCgsLEQIWVlZKXZRDAbj9OnTVVVVeXl5dnZ29L0GQHu5ePEinAlEqa6HZlpPBDN7IjRmzBg+n8/hcDphXoC3b9/GxcX17NnT2tqarPtisVj00xxkZmaS88KJRKK7d+8GBgaSa1++fKmvr08k25Q5tpS6AUIoISGhoKCgxTINcVepZW4FaGtrK5bAFwCIUt0IzbSeCGb2/G/Ojvj4+A6NUjiOExPEHTx4UENDY8GCBZcuXWIymfK8l0wrpampmZiYSE0rdf369dOnT6urqwcEBBC1ahLvjYiIOHHiBJPJ3L9/v1AozM7Ojo6OfvLkSYsHffXqlYGBQWvn4QUAohRoNZppPRHM7ImQpaUli8WKjY2VmNVNTnKGWCL5YUpKioqKSmuTH9KklVqwYAE5g5xMrq6urq6uClzXs2fPJk+eDM1IAKIU6Fj003oimNkTIRUVlYULFxK92BXQCckPW0wr1e4qKiqePXv222+/wScIdAs4+HRevHjh7OxMvkxPTzcxMcnLyyOX1NfX6+vrC4VC6feOGzfOwMCguLiYXLJ161YGgxEdHS29cVNT05QpU0QikfSqgoIChFBUVBS5JCEhYeTIkbW1ta29nJycHITQzZs3W9zy9u3bCxYskHO3RP3n+/fv6TdLSEhACDU0NCjwj9DQ0JB53+QhEAg6+bE5f/58r169iCyr8li4cGFCQgJ83LqE2NjY1atXw32ggrLUp0Q/rSeCmT0RQghNnjx5+PDhwcHBhw8fptnsUyU/7PzRoOfOnXN3d5fowNliqZ3oTaqiokLTWxJ8KsQvSKT0WUmhLNXt7Ny5E8fxxsZGDocjs8CE4/iNGze2bt0qvTw7O1uibFRSUlJTUyNzJ/Pmzfvw4YOSXLVQKCS6Ncr/litXrvTp06e6ulrm2oyMjE2bNs2YMUNTU9PZ2Xnz5s0fP35s1Smlpqa6uLhERESEhYX5+fldvnxZaZ+ZpKQkDMPi4+Plf8v69etH/NfZs2fhc6eEjhw5Qv6PfHx84IZQYW2ZDge0sVFq7969e/fubfFnxJw5c86fP6/wEM68vLzt27dfvXpVSS78woULxcXF9IUt6ZtgbW39zTffdFzWdhzHu0TyQ3d3dwaDcf78efgEgW4Cyv6fjDzTeiLKzJ7kBH2tpYQze7Y22GAYdujQof3795eWlnbQiRFd+ZU8RD1//jw6OvrAgQPw8QHdB5Sluobi4uLk5OSZM2cq8N59+/bt3LlTSVojwsPDXV1d5e/nTbVs2bKGhgbqdOPdSk1NjY2NzQ8//NBcxiYAIEoB8CnV19dPmTLF29vb3d29u127WCx2dXXt06fPuXPnYJgU6Fagjx/oMnr16hUVFTVr1qyBAwfKMwfg5+TAgQNNTU3BwcEQokB3A+1SoCsh5qFQnp4gnaO8vJzH40VGRso5aRMAnxOo8QMAAABlKQAAAACiFAAAAIhSAAAAAEQpAAAAEKUAAAAAiFIAAAAARCkAAAAQpQAAAACIUgAAACBKAQAAABClAAAAAIhSAAAAIEoBAAAAEKUAAABAlAIAAAAgSgEAAAAQpQAAAHR1/w9FfDS6URw6BQAAAABJRU5ErkJggg==
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[ext[https://www.wikiwand.com/en/Tissue_(biology)]]
!!__[[Animal tissue]]__
* [[Epithelium]]
* [[Connective tissue]]
* [[Muscle tissue]]
* [[Nervous tissue]]
!!__[[Plant tissue]]__
* [[Epidermis (Botany)]]
* [[Vascular tissue]]
* [[Ground tissue]]
Alternatively, one can classify them into
* [[Meristematic tissues]]
* [[Permanent tissues]]
The process of gradually adding known amounts of reagent to a solution with which the reagent reacts while monitoring the results.
[[Acid-alkali titrations|http://www.bbc.co.uk/education/guides/zptrd2p/revision/4]]
An artifact, or object, that can be used to achieve a goal, especially if the item is not consumed in the process. It thus a physical instance of technology.
Conversely, technology is the set of all tools, and other concepts related to them.
https://www.wikiwand.com/en/Tool
Lel wut?
{{Stochastic Processes}}
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nRnGzm6/PP2DTs0ewmBXBEWIU4MHorsLo1wO/OnbpTIgnKTZxv+mQYBBvnltu20abcpepjTj9aN9tTp8PV9lwEwB6YIdhv4NNx6JeGksAKXSGQddaOX3mbFlbDwzNdNgCSg6sfMiFDynemomovBioGvjnmG8S5NC7slCAT0Ihk/biXTC9E46UbCLI32Op7Ojq0f7aHOhG9GAr4S5h/eDqyoZft3y+lVmnT3Q2xBk+ECAIqZ7lbp10L244WOUz48MID1iyDLApNmSAAaMY5IRcBXrOFaVHmT63tJ/2KYHXJmRYUeSoR1/bzF93WKzssgcgRHBPxt/mbPgNmsSNEQuWd4yScLNpWtr17vmJIvHkdWOl0pHIhhc28hSexRwZ3trugOonGVlOJtB1moDLpV0ZU2pCK1A5LETyNZU7r/GEw+VOMmiUxVwppKV/toPtu7XLiTnxiHdQp/22HY1IBFxwm93lXWQB1QMjwDHseGr9QKXdWLZHS2kHuebH1xbtSd3AB9A8XwwnumsQA1REYHKgmDhKRVz5rGx/okZ3srvgSRAItNHGdauKaK2tfASxalqYpyQap1ZnwmGq/cKPQrINrY7XWXsRJVbwRh7SwooK69YYLvEzGPcShQQOsr5s7z0ICu6xNMZdxj1eNZKHKnzplVAP3aXTpRtcc305jHj+FamtH+WPC1OGobJszApE3lboLT9IDsXys2ESe1kdIQjBMazI4zaDu4gC6fWVP3Os8eeJBb+fvO2x4+Q3bKJeY/X9awCcDZYXaIov7aRqSXX3Xa2hDXncImHaiyZW6z++OtHGdRGNMA1Vil/Cr/ontqcGnBvxJsIW6MZbCmzrpUzW9zwrdBJp7q2f3V1bTtW2GDzKQLtOFQtA+jWKAE5uMoZxc++sMVk7KdyUaeFnwKlgb0wsJdeGHMP/xykgdHx0eiiB/wsPy+NODfCDZVw21hZEwMOvIGDYJh0rAeAtqsRpRXRvIgqiPql04ORpyPnfRVgr2wfpjgN+/pm6ktle5kxC0SnvDamdoriLUU3kJhPqo60RtqpR+sh6jxmaumdMaTkL6qqdSVbXlJs/rmFY5m2rDpJKF9ebEz5dSvRmV5pMCdWJoKzt8D6Up9p7k/CxemhtuzSMBRLBQrRvurmTnd1tjKeTqWL1vRX3YpwKENSfomHHdmf8lT5HRIfPOPs7WhQEyGKTru1a36sWzacBPxtOReRMYm7fwu/yQbiAuFCJZIE4gPpF/judK7of+ZPUN1EzihEREygz2Gc9EM3HiSIYq20lLbUarqE4hXiT7J8MZ0p3aleuxJni+STyIsN1k+eOSxdRW9q42Mc0PRCvevVkcoe0kjbu1OzcIM35vy+x731g1NGxc+SbS5nPrzXsETOyOsvVnE2flX9cpV4LhKHt+sFgfxtKyNSHfIbabqR0D0oAV1VZymbB88ElNTeKG7mvay6X9fqgaLn2RxOlE0cRV6d07bhcf0hWHLF5tWRDj3GeMa2O7DhT4qA9WfS2xcBGn7lRwJM9l/Q0eRoB0q9KBuEAZOD/lmXTFk6IMKxUdbzn5EfkQhV7sW/DPSWVNJwpOkXL7Y0VmDdRh5A5sjzNgjA+1DFciJeBxnW4hlLW8l8ckyRJAgMG8byKsMDJS5cgpCSSBiEt+AsCPxWVtHaprRNj9DEh5hh4DBA4wtlsCxOGiMU8KU5V+aNHZ1PeuIdf5Tdamw0u8UP66XDJMIceULb8zCCZYnVtMJVrjaT+0yRALOnwNHI700jK1M+j8mNyGj/TTYAgKQcjNnp8axyLYUQiEvKhkH4iGaJ0A6OBXmkEmM24vlSKxemirCvTQ/MeL+RXGe/6W11fDx1ahYDuWnR63yZte6kGiMrZyHRNvKMSIQlzOWa+hLcZy8CFl+TSyjbk2QtWd6oe26iPs2PniXvkjE+GDkxfyeQmcb17UAv5nM1KArfaXpGW1V0J6jJul9bWAmtfkq+aAl5W9bTuQkV2IkW2LFW9L+dqcw7ULrIAQV1uiRIXLDXLE/UE39csX/ckgJ3WjCnMfvI5dQ0VwzIxOC1Jd9A3YsiGus9M8KltTIDZIgUq0teGADtAQJrNNO/XPi4lqkezgK9cKOAXr0ZpNL/y/axKBKWMrcTgMTthJDbCUy6W3sobi7gEf6/At2KOWguSL9GftgzjzX+fZ61J9dcD3h0D84Iv7naX5jh8iwByQ+2xQJcrouJ+1wxXyYDpP1pmkzaD2KeuwOVsx3yE6Y8eEuV49bUlWNVEbMrZyY4Jy/gNyRoY2ydVnAY1xfXaTSl6ZG0t5chh65CSxwMZm9zhzHFM9ujbREHESvG/bGmO41SaDBVTmSW9Bt7Qlj1HFtiP7ZgZ+WiUj+OFcSxJ61qWEg0MroLMy/tPfcPxgo3w+T3UYM96+yUNpJ/A/dFpI9JmFxF6pbqFpvB0NPXs/N9CYBYoZZHmymNV1qsSntWCSR4LLYJ8l4yzcnWpDKTor/RbNyCq+m9DxUnzopojkQCFVzqUxn2fxTjrlyJYsq+i0ppfTT48aP8zjvmDB0bOgXPas/vF/uyfz/Xy4wvP1Q+ygDGxEo1asYSaeyIyCVLqGr6sUZE5/UV8TCHSXbTsegFxCqW3BdSzCCtdmRO0kxIN79Ilke4XAX0vroVnUBRq/l2tmDZB9ABoZSZx5mNkj8I53otUMZ5svYq7T8CllZ589va93UgyijEj8+U7BMlLbx5WxbdCFIgdP5Ba5zOeyLApy3KRIbOBL2p9Pt4RU+LN7+oahtLMnn8RVuTvpXQjRU3rqJw86PVRLuZewl8b6X2NgH0SSrnnukclJN4s8hfk2jz4rjZ0MuME4apAiHA3I7BqqQ5ROPwJsUBpznaRlZ3ShEA5MHM6a7PwhJNp/DKk8iFcuN7tCLX1fcC5ThbNotEI4apzkDSUY6dQ7dWUyK19AzWxIGoMj6Pp4BNJesHwROXk7PLoRV2OYix8nPSFoPogy7dhy2lZHRr1Upalikk1zKbIZ1y5Twn59UEsHTVOKir4oTg/VIuLjLyAd8GGZl+NhTM+T5FzoW7lDmFlw2t/gvX+BxE8Tah9NRSiFQy67F7okdSrcmmSQ0yYvBpQS735OKZXP4+Oe0IKNGJr2UTYk08dhGZEg0CCTdIJDjI9QGS6BOTQLFl7PW5iKdpSaJMIsIAA2Rn32saWCwznyiKd0GWEzPMxL/pJlFE941jbNp8/+NauhQHuyiI/J4Pcr9XTppWjoiLXZLOB6zQC6NdkU8onneNkInWjNoZO0zhZxZTPONq+PmwxkiYRLtov/fn8CXXuAl2+zC658ZpokGVyH6XF8m9bpvaah2U5j79umcgD3YhjZTyqmiJaJjnN4en3uXgm9n85ADA24hfJXDGrszZyYGk+g1hSaBv1QhTJGyUT5GPRpBLg1C/SwHrxuJoTirNiWoaiyNmo0vjydIf9/Euzva3MpmOwqu9cYoEzhGVEHErxYKJfJOSe7/4JITZ7/Cz4tVeOLtC3Gplzfgz6lbKSPZVkSYIFYLvWAoOKWmz2JR7feGmE0Ev6EMdPD9KjxnpdytB6iefHU+pAJyE4w9P4lfwe2zHppThJD2BdzKYvwthtiwQkyRbsojp1CoSeoyUrrspYExuKvcJX3fLnWtKa5U99oCr7YravIhY2djEKGIW4j6WiJIvIgqW7iMKlKyIvZIBQ+Irjbx67X3ej9Grd100lvYG/NqJP1529sbsY5/BtaJiprFS5mPFt7dWLsWtsUlbuHRfpwN9GYf2QkWufpYh/Lr1iixpMGDLbsBCnXot/6G0ckHoq9HNrBMXn+fpcYOgV1QVqTaKL+ceO8Qo+RA+BqwVeiJbCmRlK20GKVVizk96V0rXY/pAhajS0uO3o7TUueE6+nLi1uugh6G07hvrvA2dACVOKYmMerIRy/nSatD/2OhHQy6I7jXnvnAyWihNJdSad+Hqi5L5qtSqTtKUfeBblWPNxfJeWuvAmJMxmhxN96gEoLn7bPMri9vgA8wjRlj1jwAnU96d+gdlKYnqriWK75ntm4+IFNNMdUCqJ22tuWhmabfV16mJPj3mmwezVKBOaZ1PIZY7pACeKE2tZFqSOgAj3+8/4SMu+aOVG4qaJcUy78YXBde9Om5fpIG2lb9O6kwV9Tuf6VLPIe1q7PwiQnXud+PjjHZ7U19aJ8VKvxvAZcNbDxF50Fa3+rFbEkQuQuBMdYZ+hX9/bC8Sr5uMyh+mAeTEDkiS3BGE/2yC1ECVBrTm5K/wf4pDA/1s18s27WIQ/P0OBdJXmqmXBeW3mT3dcPoLogcqqHdRmHN7MSimPxha4vz09N3/AGna1nAKZW5kc3RyZWFtCmVuZG9iago1NCAwIG9iago8PAovTGVuZ3RoIDMwOTAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajVlbs9u2EX7PrzhvpWaOFJIgRbKdTseO4zSeus3Yp9MHJ53BISEJNS8KQFo+zZ/v3kBRx3SmLyKwWFz29u0Ciu+Od/HdD9/E8n358M23r5P8Lol3VVwldw+Hu32+S6riroBvobK7h+buQzQORzOejNtss72KLnY8YSuNgMYk29ft5O3QM304MNmfBjdune6Phgf8aJytefAwuNp4pv8c57EfmD4vWg9tO9hGWGrd/2HkgWGTltEn/DGu1WeYnPBApz8S1c/Hs27zy8MbkHWbqF2eVSxPB1sBX2NaYMzLSOO58yIyn0fTixhAJjHgyyeChjN+hPOPpuH+eZNEznZ2tHAamM6rdJttEuEOxXWHsFSN5ztpdwxLBCF3m22ZlNHrTZlFk0Nld4Mz98BUVqD/sH8z1WZNonroztOoRzi7hi2VyqJ20M09N0kApfLopSPdXXqLIuNQ89TrDk2CHW87HJ5aWohp1vPUBmQdelkHbcUL6/Fmi2xhNexpJzPqoQfdaQur4CIJrMfzhqU4+Wyf2cKgx6oCB8NvGaWv+IsOcznZ1nCXdsdGY3+OEwWu2B+ZcNZutHWLLoHrhHFhD8uqV/fcQMEWC1Z47tr0eBI4PWuF+EbbtrKlqTWOP8kW2jM9QcG+fa2qZXRlKtvFOYhLcv7ZMc9tBEJzX1SBB717RzraZlm2K9LqbpvGO5UqHn9tweLt06ZUEVk7iU50msaJk18NnKC8KIlxukZZPFNFmeybTKrZPxKUn4W3j9NomDYO/H2kDYZR5ogLJNFBO27ovuFGbwIJ1J+ZFp2Jw5bYnEy0xx6cHrz2S5eA3SEGskKCGpr7yKAtTY3eNDIFnRWZ9FGjaanpjhMFGw738xrcOOszyWBkRQo0oP9n8rKdBCwj2HJq84SuzKpNIs/zf500q8tiLDIogG1oDLVMCsHZ/TCuhTHMb8PUEqderR+L2QWSX6D7qYI8Fb1ZFVXQx+h5BNB3ahseOhMcDSO6MghhyWWIi41ouEM43phGlh548hdSlSwV8pzBXoCIzMgecF30RIHxyQ6TYzrC4A2j5r4zgFor+jCfg31sJ1FI8JbBUbtzazqRJ+BVJltkEsEqqyL/BFmnA3zNqjh6OBGe4XzPw5q7HnwPsSGrRVYebRHd11dHL0QWSApTO/o/QS/fRycGWNIR29/dr0nGflTGkAZJwnpCFyoTzhRAnxlufBT6F1xVe+5QqoLv0nE4EeHSRo8THA9wIU/A2dvJz2s/8W6AjNqRh+Ji09ja3vDICfEeF7vInIHplCObeZ31BDuCQcdgsRno4XvN0dyzMorJjilnhi9va/FRGHWmBWWCdsU2O4HW8i7JdgpSPcImHCFLdklW8BEyCMskzaN/9rr3lw2gi3Hs2DloCxI54R+vs1/CL6yjYJ1U1vkXpzjIvtdZ0C0it8lhzU6jxnLOZ8A00XaGBxd0fRjRgDhxZB8E4mVwH/+CtUpM6JDH8UynqbLT4Jh8MLDwjAjP00Z8mxceyH8g86JTO4Iz6JhPtpnNgoSFUNjlhI4tR6JhOxOh2JsJS2n8qF3D42PYKyAQ98iVaVEZ7s2xNVI+QbczAV2t7/wK6BNcppDZ9PnMlctn22k5LtIb42vITBwfgfeRsU5KCDgzxj58H8jriaVG+sd+dvHWNAjwOMYa4NYmiYQqWRTBB7uHqa+lGIAeyskThJuLDiij3DqoacQu0rhCAPWCYqwXxWlKhUoYeZYQQDFEMcIdTCVkBT+5TzYUTTfzl+W5UmKXLKQOJM2pA3RVZFn01wBjBcFYSTBGNagou9ZYRH0N2BAiazfVNqA1mC+IMMrZkQxgQJWaQKqXqUG9AtU8c/DePrZYEqs8vW7DlcwWAKe+wrR/6jozOtnlEQZxH5l6odKNBshTVsVwZsTIxgpaTIu+U0CmD7pPC8Fiw+2QbpEJY458F+hQQWH3OLnZc4GDL1E0D1IMegqRZ8nJZ1X0HuvM+6V7AVOIWZ5P3gfUkHmow8pckUuE31eouEkgFnvOchkRk/shiVUMDQFnkgU9dxT6c5TfYzKk2w/X+Z4nBfQoCT1AsByM8I8DT6ihNvBkVCgDtOy8nva/xAcsG+x/58uKCgUnxMI4YY0p+YOydggIbHBNwIN0MqmUcIk2XG6Cdyy4HNe6gAcD+NNtYSa4+5MbHvUjqXV20xxCdvAjk+YaHI1Izg/DITp65rlaGHsMtZ45L5KP0ghcOhBJQCCJpXIllvrMZLh5TTWVAsJGNgpxCIRQBH6p4pvYA+aY4UnFachjsVqUWIDqL4T4I3N5bekaGlcSRDRhdlbskdl54WeaAaKgJXdITpzBHwjRdjubCUQaye9kpr9YQAEnx/pxZCoFwEpgXOtgtXaSRQXjjXDxnamIxCcGfiLBZjCNgC3ODpHN13N1axP0OyeeJqU6a3y19qfUrmLAItMettp7Q9d2dro4ES0l84FivB+hscXJ/C0bAmdIG9gPN3iyWiHmTpZJ7br5FdfbVkzG98kDFS0xookfNdyhaTWEXPE63Bhgerv6PmNGeiZSWKFqiP2nce4OGi0il8cyWb43QM/Kl1yq5AtvcWPIUMJyOsQuJVBstFyKD1ygNrLSiCevxO3LJLh9mSzSMoJaWUTfwVlMPRfhX/ey+WKECT2Xoj9P5oycf2mxJdviUQO7Vr4Am+3ABVqecBWRz16ATZgG8cE31paLG766wtiHjBJ8HKlfsAaoSqkgcbsrBli4ZYTaY3EgsHaH6l2RuOVI317Ew/CWf5rvBfMrXwiLbgANTq2R96ODG7oQdavudl2B/BVj14cUwKkOSJCBmgZcwJtmjm9JCIFb8P3jasDdvrFk+7mkrZ7jI5KgWG2hVJyr6orVlMWyHVLCdtzjWluG6DESmAcGAtMzGVMCvXRYeohDG+1TQDXP3PMFH3nkto46xal0dZvPahxa62uPiJQz0iq5qXihe4Bdr1UZUs5zosPe4ukVu3ivw+/zm5uM9vz1Q2e49UhSUV6ClE/RnsJ1PeRpYCUYj6O3lOFwytH0xrFZsuj+d0rRKoI7j6bUhxUMZ3qgXhE/m43GSS7jB0fkh9oFT8Z65etKP7TD8YnZ4AJij/0951yuPmCShPfmury4yWgWpkFO2BaWX7gLEinRwKQOn1agCF17DwPTuAHqynyywMRYHYMV8IEdShhUEcRMbU2A3lhuU1UaEAGbjQWeM976PRMuKOcpYIOTG1Clls6RLu8/0LMy15lfJ0v4gz26RsGXTspr4AlW7AQ6DqkV/M34373e73nOO3MAUO/xHwRgnv/QWLkULy/zH5JfbtjvPmzh0h29gbQM9z4ChSp6yaXEiXtsVIiwFz1AyIWJb5j0gIgwuUUF4jbzE+eO/5N41Wueg1J2fPM88TM4xfNu7Q1CpemuKPbhDfjv+I7DLwpQH2e0FHgkFG41eSMOgUeuviWXuyQpw0LoCVkSpfTagDn0j2mR/yavy2CSChDvxjRpmQmspnFc7G6Vt032u6q4hcoP6aqG36Hb/xynapMVaWQ6i8rZR6+ceTpM6L1ZBVo1hH0Ary/11LgZb2HorXb8QgaT/sY87+Yb5YKHOehfFAMp6Wjn0cWNlt8tYIkXzP5+HHojbPxCC2NvkFNODFWo+/cG5UDAQm2J5EtVvQzvEONILw6Zit6i6/t6OPP7OxZ5Iz8y2vAvjRSpftUNQOe7IlYrbrBiapXuUrDCwtKwYaYKtHUR72Myd7lPfyv3ufwvBOvnz22aZtWu/MKqat2qkCHAYjmU+T9A3sZCz2pMTVWWL4shgkHkWil/kIz5MacbBRiN76TY1c9mX/8rWwuZfbWDbYP8P53wCRGVhZrOE4XvdSm+f2EMY79FQzn/taipkoUuOUD2ya4sq1urAysqWJF2Y1XCFWMOmCT9fwImW1Xt+wlKHWefUHyNHplF7/VJk5cWQfHopwvFy6C4MExw1umO2zBD8xOe7riAgxDBPx3BDb5rJ/xj1of51055Xay+NedXggC8HaquOZnNpVYmudN0w4hmrW9Lt1WLJkWyq8py3aL4HvpuYVHsf79my7LYJXnxLCzKCo22Z6PtU5Xs54iAlPPMaKrggMgzSD9iNXXD8/3DN/8D2hdyEQplbmRzdHJlYW0KZW5kb2JqCjYwIDAgb2JqCjw8Ci9MZW5ndGggNTU3ICAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNp1Uk2P2jAQve+vyNGRGq8/46Q3UHdXbdV2taBeYA8mMWAaHCkJrGj/fMdxgMLSy3jGnnl+M/NItIpI9HRHrs7x9O7+kcqIEpyTnEbTZZRKTHMVKTgVF9G0jGZoJl/j1+mXU1k0SyQh6KWOE5ahsrEr8Hiu0KTuei9D2pXBedFb64L7VFem7bSz2uE4SblEE1MtE922ZhsD0KI6hMR6OYAUnd37FxPioq6q2pa6CuEW8IodYIbwzXbrQKM8OPi18JwjmmJoJ6EcS5GHdpY7B8A1kICE+0ee/tu/gHypoM0+9Xl9aAFIUtR/KqEfH5i9jcG+hauHgHM5x0xhesb5AJmco5zOiSQSDP1IJONE9A8CMUIlvpxxQiXFJBNRwgjm7LiK9OYqvsHYpUSbQgNextFPWy218+B5ikbOz7CrXXh79pFfFBxzwkQsFEOFs7/6dInGlY6ZOj5x9DuUfe1v95dV9jIcEL5r2HKo+tF2ptkOVCT6vKqbEwuF6gUoSCHTAG2Zos2QNXJlYzbvOpG9qv6z1E+7WPKBilCo9QS8M9aLK5KgPZXRd9ozZSjQTWfnhIrC+pX7m8JWVt8UC2MMiyw/qaXx4qi96TVjBsNQad0KZCpS3otbpAx1axMcmBaIsf8MotGpWpdmewiXx5pJYY0L0O0t0TGeY3HWnB8V1FGcAceLaVGizkqkmRB/wKhBpSBGciVGxihmAkaeZikGJgFFXCQ9TO/+ApacFZwKZW5kc3RyZWFtCmVuZG9iago3MCAwIG9iago8PAovTGVuZ3RoMSAxODIwCi9MZW5ndGgyIDExNTY1Ci9MZW5ndGgzIDAKL0xlbmd0aCAxMjcwNCAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o30BVQb2tYFCuPuriU4FAlOcfcgxR2Cp0CguDsUKw7FWlyLlOJOcXcvUNzdKVAePefce3q//x/jvZExksylc+0916anVtNgk7BwMLOUdYC6sHGycwgCpJQldTm5ABwc3OwcHFxo9PSaEBc7y//Y0ei1LZ2cIQ5QwT8ipJwswS7PNmmwy3OgsgMUoOhqB+DkBnDyCXLyC3JwALg4OAT+E+jgJAiQBrtBLADK7ABFB6ilMxq9lIOjpxPE2sbluc9//gKYzJkBnAIC/Kx/pQMk7C2dIOZgKEAZ7GJjaf/c0RxsB9BwMIdYunj+TwkmYRsXF0dBINDd3Z0dbO/M7uBkLcrMCnCHuNgA1C2dLZ3cLC0Av0cGqIDtLf8ZjR2NHqBpA3H+26HhYOXiDnayBDwb7CDmllDn5xRXqIWlE+C5O0BDAQRQdbSE/h0M+juAFfDP4QA42Tn/W+6f7N+FINC/ksHm5g72jmCoJwRqDbCC2FkCVGVB7C4eLqwAMNTidyDYztnhOR/sBobYgc2eA/6iDgbISrwGgJ8n/Gc+Z3MniKOLM7szxO73jMDfZZ6PWQZqIeVgb28JdXFG+81PGuJkaf587p7Afy7XFurgDvX+D7KCQC2sfo9h4eoI1IJC3rpaKkj/E/NsQvvXZm3pAuDl4ODg5xMAWL4FWHqY2wB/N9D0dLT8y8n52/w8g6+3o4MjwOp5DEtfiJXl8w+atzPYzRLg4uRq6ev9p+N/ERonJ8ACYu4CMLO0hkDR/q3+bLa0+hs/378TxANgwPEsP04Ax+/Pf/8ZPSvMwgFq5/lv+F9XDNRV1tZQ02P5Z+T/OiUlHTwA3my83AA2Ll5OACcntwCAn5cD4Pu/ddTAkH94cPybqwC1cgAI/E33+Zz+Q9ntHw0w/bMgzID/raXi8KxcSwDTv0I35ODlMH/+4vz/LPe/Uv7/qfx3lf9Xof9fRrKudnZ/+Zn+Dvj/8YPtIXae/0Q8K9fV5XkLlB2edwH6f0N1LP9eXUkHO4v/61NwAT/vggTU2u6/xwhxloV4WFqoQVzMbf6Wy992rd+LZgeBWqo5OEN+Py0ANk4Ojv/je94uc9vn58P5WZN/uSyfl+d/W8pAzR0sfm8ZFy8fAOzkBPZE43iWEhcvL8Cb83kdLSw9/lIxAMgOdXB5TgE8D+cLsHJwQvt9o/zcAKDCb9PfiBcAVPovesUFAKr/i54jNf5Fz5Fa/0UC/AAg+F8kAACa/xf9ngpo8QfkBAAt/4DPTaz+hb8R5L+Q9zd0cHX6I/yZhfUfkAcAtPkDPrOC/AFfAYB2f8BnXvb/Qs5nXtA/4DMvh/9CnufY54f7D/czFcc/4DOPt3/AZx5/sOR85uH8B+QDAF3+Heq5kYuNk+W/xZ8vF+ji7vBHwvN5uv4Bn+dw+wM+c3P/48ie63n+Bf9HGeauTk7P7+Nfu/ssm//gvx5jS0sPS3O0hVkHc6GQN19DWm6/SJC7s22NikzRb+mkMrN5Lzi1uv7EQk5mrswM+uF0LZE80ImztCHDdCW+SPXofdBYg/yuKfF1873Pg0m8+sRWM9r8OFHvWP6BRHUPJSoFm6b4ts/jWx/tQFv4Rth2Rfrst66vsNRy8W/du+U8qntKvw+HzW693q7kU0J/KJ1ke68VbRhYNE2fY/ZxhoQGyYWNEuUl3qkH9vTV9RRe1tgTlWI8C5rv4XvuAm/9Va6Yuxmv5TJNLucOUjpSfRJK+Cu84QkGb8ndFEXiOe/iwljFsKhCK0rj2XrRVmzwW54q6vYF4dKhsbUhkj2TQKlS7I2JsFjz1+v0kgN7dhpZbSR42dX8RZOPnCZ5aM6v23YeibyiyqcznYLFem1djtS43qV1Jdi9CLliEkNq2323mzLHN0+a29sj4DfJWJPw5C8eP89lluNi8M0b7IF51AbHf3vmOzYmB0X5ZHCpqXckqjkOQzFACx7ktKHOEkIyPfqk099bgfdkKwpLXvJ+Ak7pzXDVD8V2L6ynLpVPB+bBYovGwtt34hhwq3NvNbdcQ+YtSg0sJ2LS3wgqfoMiDCndR9JyaeR+MUg66PkoaYYnNlymDBvkEPKVv7IYDM5PichlJGt4Z31ZdKNGKThaM1EyGY6+Z1EpaZHgM6FQOn4cKm/sHq6MXfF5zJJWWvqE8+Nnbp3EvI4I9uHxi3ZFdiK+uYppSuFUTVLlgUOaWtEQJxIm0jKVoD7CTykY68G0GaL1+m++XdvkDtSypGr9cq98OttAe6ihi9vsGl83XNNRYZcqYNKeNDxR2d6myG7tbODGxUKclhA7tzPBcf5WohymVn9Tit4W42ml4Vm8Nttutoo70mUq4ErpGNN7rbbeH/dFxdVplhkk4mpTEjMTNNkvPbqQ0/RNbTrKuMiXpL6BCrGjYxptk6141Evr5cj3F9xlO37XG/IF7sTBXluvBeFmBpCbqbBm10bYkyYIzT2aSony3Eg+lJIxpQfhCesLR/LNp/MqfZ9Or4adYvF6wJVrzeGAZe7wd9IrS4wUnKskGDDPhSWSxCzJ4VfQngl8RJzdytZ5asxQN8KszRToRtTXz6C09zEndgh5VxUXOBCkYGgfpgIT5gdNS9rfOsK4ziblMCR9tAJhZDghzM8iJLcEqnY/+aEsLo8cxWSUd2DDwgvBhjANMi5uUwV++GZVFYz5ACww1/kQLJ3a90ha/Ao2ePCnei+TIXZxSNMofi5C98Jke/oDneMpfiL1OA3l0oVAdbQ6QIRf/9y3JHMpzojlwMsylEQb2SBtEJUMyb6Wre3lj42OVZ5CArqFJG1pfbbKlG8VadM6i0opjrWVGMe5DXU5fpquNwWns6oH1ZyE8WXUd4EUfuAMBn6e/OAdxOi9pcn2HmRWkSaWoVJtWWLzbe4e7i9DpH2vbHvQbQ5NEI+Q7JoJdySgKHE/wOlbtUH11yodfZjT7YKnOUUGaXQjWRaC4xBzwtm0N49S98pcm6bDvE4VoNgLwTySzer8/p+r5W0jfqu/zLPx5pRNUYtXI/CprQRMRNX2K31RZPNLrstFEee3U/GT61KRt1B4ElsoX3lZwmmhsCiSHCHekdrikmIIi7LK+1UYf+6H1RKt9MPFW/FjRhAgTpHLYiMwCWEZm36H9IHrtiXOPh2yfTf6kRPGqSq55PCyR1T/8/HwithYzMirdTV9WPvdOCRae0tptcuJ9OJwviby+KQ7gUI3ERuZDhNdpl7PuDCV21RkJgGyoh1iC95Z4dwVXZ5SxGZefOrYUwxdqQykLzIvFK9jPrfV4xjOTxvp5hCQNKW8qKnIeFiwe9kwPUwuqEdRyyZK4TjAf53cAGq6r+mb1//UJ+VX3Wd3dXdVFonXbJHGmT8iCAz8CbCmZiXoQ2td8n2fg/V6lOUUWYBb2xvQlvz6vd3sgVxFbd06Jj8MtRAVHKznW5a17c9nmJOKNcn+EgeISKjbbjdvgE7jM4uZwfqUajjMPF+sZllUHXVNwl38ALwpBrHq+nTCNtlSK+6prVRn9zxqEvhJ7jZm7f7yd9wQGd+QoFoD7AL7Q6+bZHXCWzrKqQd4A5lsHm/80G5HL3Wgzt0eFhtqc2Ax2EQBcbs20d4msdTS6pyxpSFgx+BtRn0RCvvHWSkOVwqt3BvKw1aG0q3vrBITqO5sNCw81XQrBaKTjfmpIrQVluJKL3XgWmQiKl0QTAbYFFuT+tDNKEfz3uVd6FvEnpbYvEuJ+xoV2y3qoXJUkrviuBHrDF/4sVEOFLCgWmAjepE15fD+cuogu/gjWQfMoqLQqSKLoT3aKBWFIuk9H8lgpy0pfsysfaAADZIKBsBUevKbQespYNeGz91bAttcWGSlws03YxhbDUaq4AfK5MtIH2eJuQ+HVkq9LJflnNSB5e+LEjWgd/k9G3607/1NcF+GGVF+qjWEnFIT3imOQDIH3w6l2isClKoBVq3Z4Z4vNe5gsXyvIyBy2nzu4HpY4jU6+69hbsI4XvqvyY1BMzscKvvqb9Ovqb+/5B9wBam2jIqY+Y/4HT+YLCuiPkoFKYgJ854VIKJrYng5F9Uc+bqCTFOU5wNK22j4Pym1TaHDH9/sNJ9vhi2/8lQFRHmfn8fl+2S7mTK/6GSXDqOg4M5Z2E5WoksmJcjbRU1rAbBy+39NT5lcdu76KE3cvDql/hSRWNCpiVkXMGxehfyZ6zA+mD7wwVPaULkGV0NAfv709fuWmY9OVpdyRcYPhry875JpNxbcCA1C9cZqmAl3iJQ2NQqMKWr8oI1p5cpkuvesrxjy+MGYvRZ0vz4sJ6MbuwB18ALnPcfa/du7SYpQLsp4Gl4reTMviIzAhOpIt1iINjuQWe4v6mc4LiSTQULYLLHF1RJAT2axPmXXtI6INHztSu+xQFRqukM/vMywCrP0w8wnb3yfAo+Y6YlB80pWqlzYyxWB66sAJpXpGq24SrYay6dWJ/+s6HNXDPXPjZ7RmrZ2RKJNjKtf5Y+mMFYEJoLYkpjv2u9dq9A6XFkI7GosrjZ5avcavErMQc7vEoluNRWRDAQRy9xGyR5Ct6PFdCJUbqOUCV82YX5RQYScHIOsLqxkp4FFYuh5MMNJDjijwybgEersJcx1yX0XoyuvIMNW4gzEspUkdWCaE0/+we4BkfLP4hSiGZiMOVl3//4TS17GGKNz/xr9DrWRF479sDFzc3WFTpVi/Wpx4JAB7FFQIiMbPHkP2pg5IW5p1NINt5xvgSYs6Q5j+mJOLLSDtt9YFC52MnuWMZstowEhYCVgSfa2zV1ZVTOuUtpZMXXoNXlTzc9vwd7IqPeBrZorbfWXXBXapPEVKs4/JmPuz7H92+glgxdtos+/01HMsa5diGZtvyO7cNhT+rBII/9xrBJrGjsb0PCZa1QSp1hrhJ9RsYqp7qSZsi9j4rzcnFNNYTlu7YbdLvv1NOybAVn6N1nFajVonMfNXmZcAxVVOgEryiz2SvUhjb19Vqw0S0Buv7zuSqH76xT+XCD/t3KRIQe2HXX6gMjtVWgKhaJkHYU4dBv2iU+CY6/TpoNAXVbgS5bmLIZ3HFMuQ+op3Y/QOH/BoUubdrKbp6tY5ac3HTvIxVkY8+SH9HGycMTaIU+L4XLr/W71QUhiphqCqweCipaO6r3DdQPYt/7rAhmfYaKzh5aF9W4MoP0f6sov+1bgYg5QCKZW29Zmg1/t0/1sp6WxRBkXwZuxpUSnPLNasQrJSYmNzhpCr8ArCarBUHMnl6kVKLoao1NpDlkUzn0sfgqneaOL2KzrDP+o7EQ2vy9TWXP4cQb0QLNLffjSioQlgxpWSyIifmwQDoNVjBuvY8ODP+WMj5a8/QlMfREpEr5B249//4g+kDzgWkAcZZbbAEz8IddevUQLkFe7MSwxNDVb25ihu3YSaWMeEYsDFpLdCMQIZzjgS2rh7B8s8FewZ/OWbJBI1m2oKwDSqgsEwDQk2tT4GwyUHric1ttFB2VvU22TRVLCDqPZAPqcLWHvK1uW5Q1OKtI3ZcHwTRpu4pN5kL06951JT9pHi/QnuM6hkzAceufBH34ZhvCWdxG3U0ZMMSeLaIJb52CupnyxCfylJe/Q7K0NuazZTyjiXwV7c+zKfvY4g7df7S60yTVNakdaNV8q4rbkLLUdFAwrwAqbNh7HsIkdXxkJsV0cECHJ+WrQvQD7YNysOWDM1dm6Mp64Z+A8Vn7wDISR3U8NWXHsquF6QdCY2O2r8HKlhlhSakzUUyxd1WQAFrGF5wPeg+B6cpWZzE62tlEIZ92k9umdGWswzTslB1kOC7M4MFnTIenTcNaKFY+c8XCZbQKT907XiOASGkpa7a8VIzZLxfp5M7LkIfPAGTHCqqyHYZuBG2cWvNFc/8ifvSa1zhmfejW+En/cpWQFuxR7QmCrziaGnX410tecy3KTPljjFGQVrEQx5Cr7zn8v7ufOkrbttzF9b5jl5Goh+uNM6AbSKEFu0nYcQYjmIGsykWZue6WSMR11SwU1zf3pNkc4w8yVnvw9LWGTjvYIk+9uwvvXCcrD5531ijpDWbcrrUMdSvT2ALtjNHoPRAPrmmmco9A3fH4FeFLo04RLNAkJxrZ2Ul9PPLGblugpflExj9ND63RmZDNVgTAEyjhpnuX+AwTTO34X+m9bj0oWqSAKuaGBdIVZUkOaGS89gkt7jO5Ld1KYL6kgWbCwLjz6GSnaMNNG9lsRgdpTMPGLqveJgQEVVy3M1jCQX41o5/RscIpavdkGVl80dfmngexkoebviKICUbQQwllvbPhPXinn8oztU6B67QoIbgxXr735Ze/kdpWhdhlDiymakI1iFuBx3rxhctNcOATqaujOQvf8HFaaGPzlcowXe0JdHOhtdfBa6sz3s8VgB0r/3LXf/IZT9R51JTxP82PWRNxVc7SVWp5D/VFAu/IUizEjayrWMZ8J8LuOt838yMDJADBiIn1/+M1OtYbv5K8jxXde6BPOYZEzdZuRa7NviFGLV6r9vDJA3m8lDGHUJ23omKMEvVQ0FEHLnhRvjD91J/UlUNbCxvVSvGCe1Bz3G1fSh5cg/KnGgRgbhKSoRuTHJOonsM7QVbDi9m3d+IkGJRixjbn1nS7vDrmIDbzKZBBYBWf+awn9e07E9Vk3JM4lazexnQAevmr+QPnreKID6l8XtSqXj9/e5K6r8lAWtxIstJktP23lN76HdcmRPfc8367eujpjOPG+cH9twKIfqZiQ+7YBjaVxTRz9ZMMeyvrjjTJUxkoBwx69WF2OslILobxGD6vyVWf6rUoocXHe00clnEhBcqPufEnq0h5iFbEARcLIkx3GOQn2a9sOb2G1/s4PYlt0QLPcDXpz9ZrAsDVoCzXCy+CN8/QcAQKCV5FUSyrYriaaH/fTOeswqBiOXyJa5qsYMxS5Kvhc3YWwPM1ylNTSoAuiw8ZZEGsgn5Z/7uSr0HK/UqWRmbv3pxw/PT8QkY3tEu6lysaeMKAJ9eAggMHdeERPu9L39g5633W5QsUeQoJx9Gqoj7FOH7Xm24gJmN7aAtOv2T/ObGNXSWf684FWtlfYOex1btSgysew3GtWBcC45TEEdQfOTrTuYad8zXwjL6wDkQVoJ5k94UcA7xV6w7adjd6mgpipQ4ivY97sFDuOvxcaQRwt5t+pzWoRAGtIJ1RY5kKhqd5BT6D86pv0oX/DOCjLWc87QrqGlgf9NljaG1xi+Eaong5agGMxmMU4MqIkg5HC6Ji4hQGeenG9ZCKFSwzLOWuBhfUw+ACWkcFa4qFpLxQ22B8o80XkD+Cnn29K2wmwBXIp1NlGMJYXucObCQ9LJuNd+/QJ6a3Ho1e023XIes+XshJeZ24XCKDhM7KKBtsdUOTpv30r/sWUKIKEQCrqyzErFh/pos+5FunuVwOuvhLv24bhrW3vS5Nqishncdt9bDHoYLpKXZIp2wiNy2SoUaJm53DZYy4riMOxOr2amb7gT0aKsZuApiu7b+kKZ6L7DGC23+Y0nK64k3DRNg8K+gyNt/Ct5MzxyN99KZi2dTrzUwiBkYkpsL+cPkt3K4+oNGPtNEj3KA0KXOvH0QsVr09ddaIAEdd3MP6k4h4SNC2Q4JeK9dNlMdlObVOnlduU0O52MYqUXrHAbKuhRp3lCFh/Gej6A/G716XZJvGXoNQv5AefnfQmjgq/qkR+yaqjv5ggtUaBOe8n09JlsBkJ54ubV23bufi5Oq0zylVlvEhyGweL5SVXefQAgKhkT45+fnz0tGo10XiiWRC9Z7c2vSaT5JPbQXvsP5BMfvHQb6F7HFdLcBXTqCvjC1OVeRQaum2pg9dssptlZ/e6BJ/vEQniUBwSmCArXB1Hxj2d9qAP/2t5XYWeaOU1krH7KMlycFSXdwaDTHm0YK6tCAA7Yo/8LJ1CsriqXsGnIBkty29mMaPSSqkEYutRAIg99vpmX9sAQJ/i/rlQ7Wd/ZIumnsdW4F+/4dQsX3XgnLIYsfigX7RVVsqOYPTrmxFxrjB1HaEN8zCgyyfDykCesNRuKYz7e+CgwY93Xr1YPUAAUtFJsN5jUXMK667FxDvDi3Y+h/epR5XT8x27jWQyna9g5GYMcCbxsaxqijzFA/h1DbIxcKJgkfcs8HQY+ZoVJYrv5a4UgSfodH5SlDHUNeu+2ZgbAQjKStXoEvX6gtfZpG3fMOPjHXwJhitkX+esCEZpRBMl1qvZaCATjW4vujU+pmvlQaphX30mWTyp4TMyvkk6VRjuailLDHbFDn2Zri787cf5eh3NiSA7/IHfaNotCkP5fdhCrSZqEgyIXEWgWs5PhAU82grOAf6cC2tmqkF7QmuHH5x6chIotWkY69+mXM+Dtk7Soyv5CS8NeaSuu3qCVWjPXpsTvxqH3tGlGJgUBnWWN/1yD4vQMvimbLFzdPC6Le3XilVNBPJ4rbvg8jLtEBaD0a5yk1DGy3q++KuHdWPlzknPezmLxisQRREf9Vf6F0orjqvxrOkbUMdvRC9AfjrSLD7OgxY6cnwVXz05kc0+EyDr8iAqyRV8pe0+5p/Y4Z5hcyLCwYnnoYFijkqkKF4s4JEjJa9REQqx+8HGSivNwA4tOQTpF44L5bmbeVy0HBAFUz+EdOoA7ZM7B9t7yT/IrLZwupwQEUgRuxmhcUcpz5yyGPPdzI/d2HzqaaOu0fBXWAVpNhQSB/3k8gxis0HBRy6drmSvRgg3MqtwcxJqXeONuKxab/KKjSNv2lPdzKxttMdpGT/gznrLxKJKyYVefBkdkjZ3yXyQYURwH+GMmRLFm4oAi80MMrMLTFc2NrAjbAgYSQjtAm8StSFQIeV1+wK3v+sSIw+439ltAGkkIyp8EdGZkuo03Fy2k897jLUl7Et3wVv0FSdGlY1sbEYqof0Esyd1cZg6Ao7WXUb2oGyGx7KaI5hyb6+BF3VEyePoqPZ9OAM6Qy3pCuKhAXOAtz4HKkH3DpNxn271kq2uKTXmQvXqzJovPlgHHSv1RFAttq6qzru5u2hOM+jI9J+lESIaJzbCg2f61wt1q4etMU2/LJrkM4llbtGOC4e85Tw+my3uRP9irE0Yt+dDz0bLy3N57v3e8InDQUj4xd6baJX8ULMDj5Z5mONzM+/KVaK8Cao+MDeyUtXmyWR66yC/S0gbE6U0XoNpa8LHA/VJcdX1zM1kNuNxiXxXxlBqIYpmq44mOvIywF54bswaWgs46sbVdKdWw80CYchwwUhAtieV7p0obqqiET6hawdSAuiH/6fjDx5kR/heR5MCn04rl7W0K2QT92avJXKfOuzPzEx6G0iiSmx2GzPyu6tdqlCrloltrX9tsKC6yg1Pypr0iKqdpRW1NFYX5+pijQ6tFPPS6NVkHA06BGxvzqZXhi1Id9bE6e3VVO2wa3cMkxS/bP4mojf/gEK9blUYAk/PI3U0b4c4Wa9uXDkPqDGTj7U6zVy3QuhE5DNPoa0qj56u4WJEHokSRbW4PXnXwF0B/ILmH53ZMNTweSZQXTDurE8GDrlsbcytybv/MDuRjWBs9TOi13g5GoqGd+DZLTrd7c5QMOeatm9H4f5dCNwXImA/POVXFmo+3/pvKNHarf3r0VkfBVKLsjqRXlTIIfif1gy0wU/wM6JjaQiRNB/dJTNJCx+PlzaEm/Xna0opwq2dyqCfj4Fwk2Txjit/OfYXZpzMRNVEk+GZmBQYEcx5YUvWmYF2AlyS7M8G0bdfV3rR5JXEL+PAQHmKSz/o5QGtHuwF7aHBuMfUqRK3xlOKvXqr4YALvhXIIOBrIOwsphpOu1+Wd6wuqA54sJlUj2NIj5yd2hl5hzYJS/DUrM9/IuaW03YZTFYaENXjbBM2kqZdwmL6Oa8HS+pgYpfUeb5/pmATTWQM/QHbLhPT9gtskOner6/OBFKKlB7T/HqcS6OmPZ9j9GGWcC8MGCrS9K3JapNMvP1wStdNpxGHAXqD+3HW1CECnrjxreaJD+3AZIY7G/ZwwwnNJHDO4ihv1WImbHxRoZRewcf+oMTMVrXmR7aC/GZANTo1qQtqAZV5BGcFK3oTLFGrnQvxrPSNslPUfE9VmVeFNddirw7NhfaP8yw9aIZP93bcwpF71T61r28GktQQPWL4dw6lRKbp1BTig2bjdXKuKuTWV5+c4NXvBM3osPXq78xUiL7kdg64lsZl+SRct3QKUKZlnEXxup/pMPYkylaKutfv1+q9PFsDsuYcu8hj8oUlvggOVsD1rnE4nVu53z0QqMrOM5YrVZbkGYEnJsElffDtjgRo2sV3kV/r547NBgrulMvQKSm4L4Lokdy87w8ssLZexDEioJGj6e7QzVNoPAZXfSMTKLi2pxWMK76Ak8Y7dqNY3IAW3Z2zp+9oB7JjmQZ+kp9mGMgbwQgGdyv7+p//PIHCeKiXUgJp0UlbBl9Gs++W26KWwjovCY4lMQbJettuoycfy+p+/PrK6v1wxq9iB6NfzMH2Xso3jFU1KD8nRR8OaYMqdVx3Lhrge+PNxCOyTwhj0ElJEL9R8dm9u7S1rntRj8156URk27gcEWz+LhQF/MOlJEDcTneLZ8oOtO7QxWH3gBx1c/uLVPrDy8bXJ2XWu1k1t/A/qsjbf1AsFMmvbAyhRvWv3fkAYqECmRsBvJ02YqSoA/nzag/zOO8Al3riDXjO98kGK8TeuNcAOyOjt5TxwMmKhv5SjI+WSgYeRys9NXccIeifflE7rAvSE3o2hpBNAQwpPQU4/RbHLEwXl+5IpRKv4vsw5jwV+nw37mpJBzfqbwuzQDjpe/T7FPKz0MSME8iSaEwPxXBfc3Y4faMrVS+7G3HSlNJTEOwQiSZa9FwP/3K4J34Bkza1/XCod06J6tPNhqqLjwvb4IIFufkyaAr+W9p2mu2GHfVj0+mQPdd3hzaSlJgysrqQSFGQm7+PxZRghmqJot1XTTwKay+p2aT60X61MMXCztJ6D/GwKBynC5BbNNe6i4znauA2WUoQpSqP6GVFSya2crN0z8Mug5ZcIqP1axgjktY30eBuC90qVCUlQ1eXWFdod1N9rT9CjHftN9JieWkRorqJJEV2/yPKZB/j+ZPW8+54vbefAGFpXxsPbH6I5+VUoX0uiQOQDwnpl4Jkp5Kd7HwoEgIdFjPTofSLPB2j91mE0rgTh/mIC/veVgZzeYtYYe74W2/JIjcaJb76qjHgLN0StxjSeNCS3Ks/rh9Zwl9pP9Sqvo/h9JGH4QcNK5Y0RfIkaaXUvxyjfHfakJVeGwsd8D3bFKJ+UBElCR0DHlv7iD/NUbEKjrGyGoMuPggjWmOmxCDPZMTMFzbn8PipR8n2zaLXXTZhNG4rAVtQHRq79BWL065VUpSuil7SCqe+duDLIxgO6yrlZ/GUnEjwmfSYxkUpxbhmnEBDxRS79WXHQjgKKgbQbM5YyHYhiztRrL65dtHE0C2P2XSqRm8UP365elYV5JbQHEgKx3IcJrpGiFlS82krV/2kBmNTi6gblwh5Cai87l+BIq+4JYMgd9VeW43afnKk0b3q3fjZIA9BlNvzBjvU0zV6rkuYXNtCc7/yzHicc89/+7acWqU2/QQe9QuubHPRK0bWvNVg9fAIcscN5U3HbJjP6TFU+dpSMtsHsXJM7V7XzrXv6MbwKzU76i9ye4hfsy5OWaTz6xWLQZidu819KaPzB5V0XbnDbZT35VqYbIdYGwju/N8uab3nwPb1SNyXt9W+0qLLW9tIwx0cy8lSVuJ1PNp0G6YG6C24gpgyZxwki8m5RVIL+Wu8kqTiwKtk0Z1K7YQE5DbIvg03RcbfMl++tlLOTzLasuOEH3yRbqe9WDLHZNQEXUbi00iPaJMshbM1JKmCU4KhtLY2/zWIt/1RhfPytnYyymEBVvcXTu1JQoZlh98FRXZ2AKf6qL/DXC8xz65N2uW7jTTt8yqisgW7bjnADpGKGdNMJny8GooAtEpv7kfuxZmf2pCQjgE84/aidMLhAvfsa66vcHo5WPW354DGcpEWlzFW//ZS/6IoFd/K5ZlWvY1R04F4LSPPSqkcbHuUmwQwLs/PwjPSXxQI+Tl3L6/9bOxDDj2J6pNhPqxk2xEz/RQixrYDuBqv7iSxyidr2wkuyhi2JDPQJuexEeTxmNTKsb7QKmPhJpUPr248vV65ucQDYkPUODuWZnvqM5eMRR+/59iifInMeKd6y5nvnK8J/YUNaYG17dltSgGMmRZeKja8zUju93jUK8EMPgyKGu6+7t48aRkxSxUJrKQpCohK6q5mt6g6272+ISErjW2Tb0D8OldN84OgvJ5eelzcdO1TXzLysZjdGhAWFndX4WGQpiC6Xaqdbjr0M5FEA96OwdTbatrTFDy1lPGuJ5WKs+sY3QQyalIcjQQPkCruz3fnvSQDwurDiG9VidE6a14SrlgVbIJOTh+/sxsQYdfi2EZ+W5keDxFlxQWHkaG9cIMnR2ex5KPFMq2qRwCJmIskNXJzhPcbkXwE3DHF7ArMj5uBypU9tGN329uRvMbGxl1iRiClrfuMnWvpjxQ98OaR+brTQfVzV3Yz6JIXFvLqcx8FFEMzFGATMsKtFUspK2UV3jOkS+jmXquV79pdHnIN+grn4dAKmieTJbwMNfa1eHKj0ozSzKPf4pjRnr9CzpzuwuiyBs/Pdg91vIB7jBMv4mK6z+TqCTnTU76MnReYJLhoZc/9AZUW0DYjXP1waH3yQ3GxP6bd9zBUjt+KRFfUeW9eRJvOSp6LTLWR4R6rLcJRfO1FZyUZ67Gx+4HEVTILaJU5GBdKmtPUVtABc+pWBTH4yWNg5GxMI/9d+pLG/O5tfcPUuU4IRwmWAbaGrgELR0xZpOlmIELGgmANjC3D4Yz+WvOnh3x+nrAllk2dYIDJxa3tDU8jDxG7Ah6+q82Mtc25BwtQUXWCkkhybevqMZzB0H6jx2tgiEoCXyFjsH2FHWVCv9GDZnzxDF1rH8C7NllqMOdc2ZNBkopFp1WJHGY1+0tqaP6nYSjITZXJPCYaYeb2mJJxltO/oYVP4hAJPTzrE2MBrrpu8J3OA1UZDYawYJxO4msD3ofCbgzDYkQl/nrmelxjbyRlfO1eBfx5tYjzVy+E1e+HU/CWIsKFKftZagi24LFztnoIK15lRezp0jrKOS2+EsfQ24oStqEtfRQGdQUXSKuv08D9yMuHmagVNie7To+nhme7i0MZ7nPjj1HsSfG1/UAkeFocipyqDcaRyGvCqf5Udwr7HebHpPOwt5ixS4qW5sPWoFrczQtwRuk2p/XAinTSfLROO65c0I4jaRvK8iJkU1WylDloz1e1NO92k7injxj97bCzBN0gp9tnAsXaB6Q3xhJdcNEV6rrTrJc/ie9eek6ZOP18TCmXHCkl3/DSnxUmJlryJ2UWG1H1WCQPskQEr7xhm+SLUdDx8Ac1p5W2RHblTLdEIxDarkV4wLmlLDdXLg/4bL3fc6dx+YT5JPve4YX+2c1Vgq73eTfJjZ7C23GrSNYmT6p+ZnCNCmfb94p5NM99//nS5tEXvpZGCV66SyElufUWC9TW7G+86hFMcS8jtS9sCtVSfpZawxVqmSadfLXC/6g6wtUfRGAtWEX9WngW5lQ9uJC2d1f9jVBd5tctM8DXiv2M62CK27Vh9erxyLOfFVs+8dX1dBWyQXr34sQxNWaL06YYWhl2h+eW4XVfJPm1QQra/Gw90Ya4SYg+alnEbpL7U657Z2yutO4KWIWgj9N3nBCH6Y8OQu5c0U02a9v7y72BiqA1SNzem4np5YHLVKORThp0L6uhgBa9yE+Th4eYNhtNNIKM8uGjsApJjaSLjmtCMsJNhqH8W1MQR+E+EmP1elMtTtNMc9FMSumUafF3J9PvwcviCKr1VUs/X1HI7tjL31UMCaiYEiUW8vibvRbhtK0Vim5cNO+eC0lK2phXE5LGDWkjeSdXhP3uRP4armXIKxgEJOBuarSodN8Op1yjrl9PLOBVYWrhQA0ArwE90NKFAn5pgkbd8bcJ1AQMTuZdljim9lZufx2J9aCRFh7c6llMxux3bUnDuCldG7OgbnYZIpDINomV7aga6F1h681gFVbPjpR9OmcvEYF6nJBdrui73vp48mIlRo6oDKA4kRnoUcUKOWn5DIsQpb7gROiiUMXNNUcy4d0nmeCxuo9nub9kvYUvp7Nl9eyN6qjFY3Dk5FiiU/z8kRa0Br6wG+iviUMdy4wKBcAeVsu+WjAo+SjdY0eGq4RGbNUJI/zS3wG/BSnrJ4gKrqAD1bbW4ft3DA+3XpLrXJy4yrMpX8wh/3k5T4IvRH6xfRw2kgT4vk5MlEKu+ErhErIdrUx8DArmhvwbPNVnP29zkpSDKVvYoqsvmD411zfe2oI/3p3FmCfQYQGZXrUxVdYJKbQQER3+uik2YrLQT6nmIJjE8/CCg8pk6QeEyTmTSsUhXPRkNGskfeCmpDMOQt0eyz/YLDnFutEP0nQI16gfKbAxU2LAMtqducX4IOCHNMF5mOMFhyUBps1/0yqiaBSD39fof9v5LtGDDWYoeQG/5A45etD7xdc7zMAi7poyYJ1iL4g0z2VynZjbnrh9iRd+JpLHaIGKaVhbZbUGRAOb3o51cxkcjwfpu/IpytWzXtY/XKhsQqhIqT6JWPcH5a6iC/ALVPRiyi+4dDgWnY46uTqptkfRUiNeP0rcPiFOvXLZlMbxvHUrT+PViS2jV2A8bLyfFDQIN6S+f5M1TZxYzCE0KtvSP0JY8naSsPnj8V6i0dgLCpxTeV0JTQAINkoORSOk121Vs4uJwKXiQmZmxmpnYabfTqP8B18D1zROL/Oapcu+E9t9RBvhvmTQDuVIi3KFYHYQPm5cldDlr51GzN6gt9m6/P5z1uauurPIAjQ0TNWMERDXDXNNP4iuAVOFrOrw8gFgQBrvSqlrtxpeEGRD0qyJuIqCetMsMaDRPfGVc+mz2xiJuc598SF7/EISZnSOnPdhytcIB7cPJ1kT+vrSvi1SxB+KmdkHKoYlUvpeRMls7DJYHHIm53zFN16BhG46+hbr8NaWVc2mPggjTdjqmEulGaIcO1u9gB/mm9othFVrKMF/lefJ0PnlqER0Z/o2oplx6xqSb1u0fG5paGS8Bw3lV+ilyWkQyz5X2V6f1zxkiHl0rJ2ku6OvYnMTKfyYYl6X4FbvF51CZZhDe7vE50Ys5ryC/lk7iKUSo9vU6qKA6djahODBHKHji8OwwuGM7Qn5Lzoy9apWOTjtYOcGrv3t8Fd0Hx7pk1PsWVcMQIHDbb1wlTRvYpJCBfZ0bhxvJxOHTF1Nqsfl+tj65na9bTbh0WgGFicgeRQ7LOg/LI98bDpAkt+BBRvnFbf3e5uDuOfKAwHiiRQMa/xCUBT+Pqblkb6w95tMEX50kxG+IelF2HfXIsqcLM4aJpdPr7Ng6IUaPhIAvVelCDPcYYcNquXHTvsLfw7NhUOPmklmkamtF2UXSGi6CMZFkEhf1nCsnz8sUbhUL5b41YAUs+hAM+KGh4N5eV2oJcVGxu6Y0bNwo/FOGqx47t9ej20hdNYIurfujD3CBFo7fpJ5UY8YP5R+EgYkfGTZjxBf0xlGv+eGAfmhqtkM20jDYQ6qmBqz98O/M3kwLNjK1h9/ci2QiCe+iRn9Pk7vVKDcXtt5mSa0rVGMvVd73SDHuKiKvOAVM/qIESCpmtdfGWXVAM8tIEpkitM7omcWdlHs5lBgOIj5ZraTbIM7+MdW49etG8V4Gs/Eh+LBGAMlxPV0sxH1fuB+c60SUuqITMER6/RMBse+joAheXSFfLDUAC0iEbf4EgVt9ImXdrbcnXvjIesnxdghHw/jWWb1jJjGpaGXU3CtETZV3zniYhw7LyW/paXKwjia3MWMeqp286DUfZrHP+7TjRaICGb3hHVL6Ilohu03jM1QD3dRMbgrfA1z7Wlf0+AhQvrIPYSS/bawSJDbcNnICZfdDN3NBPCCSuz4U2yAfjhRo+53ottucJaKe4iHHuWlIIkXIfOmJrk1KQfKrk5Q5REL3Wty7kxTWq4fX2KL8yL30m6oRfMjqfsZt9G8KPvxaBntP/E87DWz46UC6T0kiwQGRCWTo1/ZXSuapzz2nkzFs/vU7z5AxRfufywXr8B8B58bawiuGfnj74d3snzY/3yGbrXFpUAQjezJAzeEeLWPtvLL8FPJtmdVCyuzL31NG3ckqEvgRlDJJMgIptrFTqIlgKJT1FA7A8XKfwJkNMQ8OIlzHXYJnvIwBUPU1RdZDvOvuWfqPHESnyIbOffIu8YU12AwccawTLUsWu2GKDQ/9zDpKOdYQTIXJ9CKczcs/FLppXuuUDELhxZWa6m16CyoLfQNgv2L5Ui4iAQeS6mdtG1mlraL72wRLnFG05Vf0V8AhhOMD8ayg6f0SvQWd1r8KmzLVr+Va9gEJbIMwqj0NIdcsP9EZd0qjZ3jmAmb0FS+NhZrpbgPXyciDL67XftYNAY350+u85NjUZdp3Q+jjv8qe59EA1FEGlaHmaFY0G+ZesBBLT6H3xTBfuoUJO89Qx7wpcsS0drcfAwRjG6cry7cdHVpoAYkxDyYjBqeq2GPSQdGUp8vxzAy0sV9fWQ2nZaswrbutIr6Rd1Z9ibgixRW7n4IQ22kzCdTjqrO7NRXaLGcCMizVjye6XoHIOVWoCY9esI70vLTt/M/PHrkqqrxACJqeSWa5myDH31nBGaH3huZscyLiUTKpIotYrHTrERnobtPdIaPsoiX01bbwDVws9/3SbXPD8oGR626Q8h3Md6LeTgp5Us1NkRNfDHeJyjTZk77LqSl5buW3vUTykyPlFCx1ZSntagMSIxomSba0R0vCJjGTsWt3+ojUan2VnDY9irWfdM8AYix60gqqiZ5zRRTzhHJHu2/b7OpSWKF9vmKHDA9yANclfAIfqOpfRQwCjNH8tKBSoEIahtP3020nQCZKOMLM+souUyYF0CwwPwwjCvMpbIri+Z8+/8ALWG7uwplbmRzdHJlYW0KZW5kb2JqCjcyIDAgb2JqCjw8Ci9MZW5ndGgxIDE0ODYKL0xlbmd0aDIgNzIwNgovTGVuZ3RoMyAwCi9MZW5ndGggODIxMiAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqNdwVUlF3XNi0pISIpgwLSzFDSnVLSIBIDDDDUDDNDDd0t3UiDiHSDlJJSSndJSCggKSF86FPv8/7/Wt+3Zq2Ze1/72vvsfc61z7qHhempDreMFcwCoghzQnGDeICiADl1dRUQEAAE8vMAgXyELCy6UJQD5C+ckEUfgkBCYU6i/8GQQ0DAqBtMHoy6IarDnABPXBwAIH4ASEgU9FgUCATwAYEifxFhCFGAPNgVagVQ5wE8gTlBkIQscjC4BwJqY4u6WeevRwCbJTsAJCLymOt3OEDGEYKAWoKdAOpglC3E8WZFS7ADQAdmCYWgPP6Vgk3cFoWCi/Lyurm58YAdkTwwhI0kOxfADYqyBWhDkBCEK8QK8KtlgAbYEfJnazyELABdWyjyD4cOzBrlBkZAADeAA9QS4oS8CXFxsoIgADerA3RU1ACacIjTH2S1PwhcgD83BwDiAf2d7s/oX4mgTr+DwZaWMEc42MkD6mQDsIY6QACaimo8KHcUFwDsZPWLCHZAwm7iwa5gqAPY4obwu3QwQFFGCwC+6fDP/pCWCCgcheRBQh1+9cj7K83NNis4WcnBHB0hTigk4a/65KEIiOXNvnvw/nm49k4wNyfPvyxrqJOV9a82rFzgvHpOUGcXiIr8n5wbiPAfzAaCAggChR/zCwsCIM4AiLulLe+vBXQ94JDfTtAv+KYHb084DA6wvmkD4g21htz8EHoiwa4QAArhAvH2/E/Hvy1CEAhgBbVEASwgNlAnwn+y38AQ6z/sm/NHQN0BxsAb+YEAwF+fv59MbhRmBXNy8PiH/vuIeVX11NSeGXD+2fLfTllZmDvAk5ufD8DNJwgEgIACwoDHNw/e/87zFAz9s47/iFVxsoYBfiX7Ve/NRv1Vs+ufImD7c0LYAf9OpgG7kS4EwPaP0p8DBYGWN1+g/7Pef4f8/2T+K8v/qvT/rkjRxcHht5/tD8L/4wc7Qh08/mTcSNcFdTMG6rCbYXD6b6oB5I/ZVYdYQV0c/9urggLfjIOMk82NpLlBAjxAgT9wKFIR6g6xegpFWdr+IZs/cL1fA+cAdYI8hSGhv66Ymygg8L98N1NmaX9zjSBvtPmHC4y8GTnU74P8ZUNuhurfdSg4WcKsfk0fn6AQAIxAgD0Ibw7/xhIEeIJuxtQK4v5b3QBeHicY6iYEcNOzN8AahiD8ddBCwgBe+V/Qb0tYAMCr+48lBODV/8cSAfAa/W2BQDdUxN8m32MALxJq4wj+GxEC3SAOYKTtb+RfNVu6IBA3Tf0W201Df9m/rw8IxB1iSTgzCbMUC7KrDmr5USlD58a9PiyOu5f6w5CPe7jAFB/VrTBqthKv8zJzVrVEcaYLpGhq164h6/wja3Hq0HOthrHWQ+CEm1Fx04bRInby+gRzPMHzlP7BJGkjRq5Bsux90VeIboynDJFkHQRSVjbdOiykXo+qO6cT3FgpixUfPwlu0WjrqCzOVKOiF9H/+lkb1WTRp7sueET9KPuzY0zgatTz8BSN9Aeq4m1nhPFuFWTLvf198+RdDO8i/Z+4BqzvM4egyBXE+ujlBW5V6M/n3b7MfuW6k07haaF0R3rHqvvNEnvyj2qNA9u1gx0TJrbEjse25onWUaCv6DMGcvg8pWwqIid/I8JqLiuUEbuhVzLhFKnfmQZVfr9Y9pnB/klosKrH7HjnyPKli2qKivHHniA2LvV4iavSta/edSyt0a7WIVjNjyqTydcUOKky2be9rQPzepgdXs6fsAWPG/AZC6fatuhKFs2LBDX7GZLz85O4QlPL9W7z1n3pvVVodOKJFrjKO2xrk2Wdda6IdIqmiEIv18x7pRfknu+BeD/UWqZVRcmh3RxXTrwq3FdM1HodYYXeZegWR8Fvy1PkL6JgogDGrNfb7RFB0dQ8zeEPyuZWu8KO75dixVphFGvkvDk/8qca6oG1YPATuhb7R53voH/uYKUDNAjhtWjckqd3xfRH222EevO6ibAkZ7iuv0s2p2j6PRFwlAEO/tTmr59s4qDs82zjzKNqXqMQIV8Jhrqsf1RPXNOUJrX15r4zx/aCJIBSqy9wKz4mqkVm+agpO5J9rIpu/BtxS7GEPz6PyOsvmTtH/DZ0tIeZErcZjdvMGK8trmFmd/dl6fULls57AgZu1R8YPGD8RoO1Vv8y4/0y+GAL9kwRqRnHHpRYwLJnxXfQ5Bal8bZsTFnyWN77eB9/7mVct1HS7ZZvtVUgu2flgTbFt/HaQRZtTZlPSsBe5m220a8sfNnfuRkF7lkaswLtEverDTEee/ywIbyTakuj0xCcx4rr600Bv+Ie3baeNAWALybNCLvpHATQ+luHm07ah8vtDGbREOmKGg4stFdyXJIBlKdBZJD9RW9ahmyIzoslJP/HmBj7HC7TKIv49H30QBM+mGggWMBMFm91+w4uxfxFz/A5aI9zZJZ8DJP0q0FdNV8/HJYpf5H5Jhy7zV2y33pKuebcmNFEV+HknV26dl+EDy/nBdHaGtU2ID2VbMFBeA1tOB8Prz7KznipzKR/Ou9vVc9U7ydmJZCXr1tIOiMoyrV67kr50FI1hmN+UowT/fHuLcOoCgo0iT3gXoHW2JJbtyTYucdCaB0UrXLeNKxKxhosBfk0cRonEbZt3VQvvm+nevlijNm+0eFkkcXsyJHZhCxNZJW7KzBn/Z49WG3Al3b+LFX341OQ5yf/O7SUTjnhLyayFGc9LXRbB1us8UI+f8sp8wxXG91hDevoIOw3fCmy2l+0fH66W7ckKeV/Z3atVjdnug+2q+2WPrYiShh6PwPStEfIe0AQ3rzJQP+Omsrj4lvjbe+gnFDUxqxhXmDzg8d+B86ooGXrc+8Oio2RRPbKEGEcHe0xwySPexTimchaPrskTdOWlcBmMpYO4hi9l83By56S49G8OaUVr+UcYUvrwGGWUu9c+Nw9qy+etlQCkhEUEbdM3eSL9qUhWkdWt7uwt8FQK6MR02Xp9jopfDgxlF+MvtpftrtJhgFycXG/9+iYGHvkQZmq5daGGSHhkeTlh0td2IhEAQf9ncYPA+ceBX4zD+F38JjT9IbpwUV+1X4vBbX4nvGLUr9soOsTN1Ia8QT9uLbUV6GpxBZiM0OoP/gRjgq28vMLXCjR2AnhM7GEgldOBA6vJfYYhhBpb1095ipsTTneKavOVHk9P5o2Cne7U0ervpPPz8VR1xXhKujNU1IoUnSvMvuBELillvw2xGgr3TsWW+g1n7dqIHDXTL+Savht1K25Qd5XQh0+A+HAA3vZ+LCeK4ddSbf4RcNt8c/KRtGVPTjurhStd7z91hS5mTMeZFhQMrHVoe3ltbQtUGI1vbe37Aoau17aE61p0JwIlI3hCZylHS3VzF/byXBkmNuMhmqVVFUTsBV9ERvwr9Qi0WMMkoNbbA5Ji/3olMMQgWyxKhqzRRLmXQafxZ4VSQ1TRyMwIr6ltjSbHZUH3yIftdbEN1j8hLVanF3scgZcOI2LtueNL2etEDwm/jBafFY3MU3gX8W9pGak/6zE4quAYZbxINBl0I5KUmHcvtqvmsmwu0Mttq3+R25vnF5K5UnGKkA91OFcV5m+z2n0yiOjC6LX03N9iQyWwZnPjIAF8zMOe5kwAipM0tY26NBN/gsa5axJtIlKE3og6boQHl4RLLHeERXM7Y+K6ETmojY/vWleVSxshylrIXfn5RwGAg/CajfvqgBlZd4aDpbzOYsk+4SKS6MqD5j7p3q78t0U9/xqndZU7OcedexO96Sas/Q3A57U09w/w+Nk7KOzBwfnGFOh5wetU6v8KFKmrFU4FoytaSSw1Cmo+MfYWVq+vy4nS3AuKa/XZMNtf879jCmK5n7WzpNOQmV2eoTWSWwdg5bgSb6vLrWFmjev5LCgPcVX6lMJLbc8zavHVIKXYQ/pRJOmuPL0zKjUnkrF1fX239OQK9/QUT+ZgO5NkMxKJt0m7/l4GrZOvP6dn2PK7qFB50v5beHNSOaDMa+DLKYGxYil/sGIxivarVm1BDEzX0IrreQnKsz1zcmdRn1s09RUjtrOm3dO858YU8f7WE+SYYtwJb8Rqvl8zwx0nj/m4wYgervzml6HC1cKFCMViE90OCkz3r3k4cAWsKqG2fQR9TaHEXtPL5Zi9+smQQfNG0fpUQ6qi1hdSpHYOYUmrEIDTRvu2eTJd1Gklcpb8A3q22BlvPsP8J+jC36+J+MdHbsfpGCnj+v5EhR+CBoM1K1K0lf7OSroYaDqhfYbPVxN2fearUfdKrCTtdoK1pcoR8/wz3boTj7xadkwrm6ru5rgN//pmnMFd0IE6hGr6xuUZJzwfLljxI3aTEvdqiyr5kO/nPgeF1SIEUooriOEAtU5dC2Yv7VI34jAyG7GUNmhGmEwY3/5LO1w3AxCpnBbB0VSqGcp+HVIbkU6MgDWLUjW664mP9QukxpR7/uzW6OI4ZM2PkAt8lumdY/7Bp88W3LAoFNO9exk5hx0Prrk48jrKCRJ50xLdODncx7EIn4l9v1DBePX3NilPxu+Ht/eDCz2R7cmr8cgynFJt5dHmQtlS4jUsHgjYr+INspSHQMmF6dY/ZToskaHQS5CQBOkuT9h/FGSV3pzAlsVlUD20iu2rX3Z6p/c5PYtb5uyepLtC1eOLt6q3i93jFyQXjQrkHm0MdXxrHmsgwKfi1kbQuA4Lm+MXRbdEQ33Gdgv3w8nwjOcT5D5Kewog545/pKJY9WmIfZgLc2HGm8kvrgNvtRyknK3kUZOqei2X4LGp+zKF11LXmIA1Vu7QmQdMkun473m5mttdqK8RFj3MJ7VxPhdX+kVsXCcC9E9nz6sl91YSZiNE+/fXn8axQzHtivz6+jZcutEBXNCixeh5QVPSsazGi7HAa16hd0D+8hNo+aXdsHeeYTP36OU5bZv7fWf3U/jJZRfWQe87SfwhEK6VonTsEvFcyvo2rY//vR6z+OZYlkZ6vAD+CI/jO0V1ayvHH4q5+4QfSP9zLPGKzgzgPU7GfgVaS2zQkm8onK0Iwb70r3FAn7cUtSS9jo0w4EZyOJuz/RTLk3UT2Tri9kw91tvex+1Eekv30rfkwwoSXSZvrGd3ma3r8hoghIIW4zF/ZBGmt774a50zRMXgk+6Q615GpL+LHLXrmJVkVJ3vuUTCRczeC+QVnuu8hxpnVibXzD93NHP0h4Eq+Lc8MUPHdxYwvF7p7AdarEXySVX7nzYyRry0/DOjkp+Rs94Kg6i9flc/fuAD9efL7QhMHPX+JVmhNU9uNTXj+PlFZnWE3LDd/GqXk82GeCewEPGD+3x8gKH+2RyGMnYZkzU12imyEkJyChP5mNN/ctGJjSTqhwWPn7ykKA/KjZFCypE+dOgma8CBiy/LQIH7HUi4DGtMvtYtq8QSKLg1jBz3CdDCVf2kS1Ng0oKtuOsm1J3A4MB+XeWy+nMk16uSotEMqXCnkurJYB1U0y0UURfSdHtFY9oOd6d6omFcCuM0K4HJ8De6lp8XmgXXKtoaL9s5Utsk3zzVdXdmb+zcPmDGeoVQ1nGVuwnrxGDKZYwYP6gxIZCnHRFcyLPHp/pMqKmUDSbjUFZshSyOft0cKFmXKzidLp3KjfI29Egc4v7e536iswwGmmOtPCOzYqa+dmJbJSmNEtAtvBipWStKoa1B5Fqxiu8f5PisBu5aPtcydwC8wR8X7ggvYGZbfGgz1SP/06Fc3rt+PHe6qEc7oM3167tkY3HdlfkGNFSqdnn8wMyDGMNG4I8xUjRNpNeOjFlvvLg1moph/baaktKirUrjKeFp0dMEPz8uW1uFOjFNC8tb2+chXhIUsL8T/sL3nXPJbytkURYxnDOnaCYoR7s1a+Fwkos5OHw4ZYPOz0N6t9Fx5LOnX6+Z7bU8duhE2Qqic9qBiZFfJ6VDmZKrvdZkycYeygsRuybe1B7fYjEYcg23a6UsJHbz4ur9V+QOtvcmULfEos2M0loQfjc/I9UTqgI50VdEnUebgrJvX6sZPOiKfXsA50o6ZmshAjz8a3vvTvUzBkcDUJxx+d9tgjSY6ZAAkZIqdjmwG2/UYNunmIrn1OlK6BC6sowAUbBojRorb4w2h1aGaFf4kwcN9hY8SaxjGwS/sWmQAPTzcNkafJ55jySz9lx90oqi2e6ULX+/ETM8/hYt0kggCykI/t9zCuNvL1xsmW8Nvud5S6rZfd3KrYKEr2Br8IKTeJNEADd+A5vkuZdlYCLbxl8CzTlD0kKQ3HSrra7jQkqUwgn4i1dfno06Wn72y9jx968kdT1h9O9GfJvDwnyajF8Op6j39rNtoVeHNl29HRtfdGpgeLIHvyebkmGIZ9WNUgbT2QmhrIfX+TOeLktwMDy6lU9rmLx2V4aDfGPhW/VtJjYMprZbOUhyA/WVSxs8xfwYfk55Qd8rLip3PAIItU9n8pwi9UjfiYJF4VDra3EFHy2HXlxsRq7yq7+hvOlGZX1Mz4kJUNe/dKFTK1NiFLCkIZOb4RlD9/4ZfMUgoInZGH18YTcC1M52ZyVyM1KSokFROyIefIBZaaDcxkbn8lCe5oGhO6l6mYisIbhq9SrUTgo+fQ7kWl06sFtyrvk5k99dK4ZJVQXrqUUzjZU6TIyWGs4D8PzEc+Z+QiYjaeieN0n4fxtGDufjfRyS50Dces4sMxzEIDXpzJEZQl6wj293bBYDjiSmP6MRKHwxMH+lYW0kxbn4aCYdlyUU1Z8OJ/Hx5AKqqCZeu/7bzdVt6ZV9XUDH74Rpl2JykqCK4i2ufW/zBqhUrCkIErI7iztlFA53gp/9aTXfP9DoiG7tvveYvxWLHaXO4HgCM+sbfFD/GZ5ZZrt7BlgH5Zlnc+7JqonhcSrIY17/oWizjhUPX22HqoLtVeKYuJG19mfgi99Or0O3jQsEYyT3znS5UW0/yxirNiT6bLYbunNr71YcyhlcUAfAdPBPsgvCfJP5TQEVJ/XLxxsSCk8/K7tNHqa9GB7xf7hQvZRvLROzrnXEyL26yPl5zh0eJTeXImjrnpS8uLsfgPJeyYFGT8LdpPe7seXfl7cUvrUS/4uARejIV2XeVNF/WTFIxIjXZhKgFedwauyof1htoS5EG0PLhZuHIrkzrCwff99aN4mnrjFWVJmdhMm4Wo2dRjnfTEJkgwcpTlfX7Qw2WMdBJw1pJo53P54bUh6Fb+uKDUSrO4X9j75HuXD/mqI10XqkUXF5/tpRMQotVDhkSpgSn+Y18ex7TbN++xLzp/WyRSTUATJmtlY+RLu1YXN3biRsyTTRWYb3RLXCWQ/OVMqRjVF1kNkvAepc58TrXiYknJJuJtFvXujh/s2pmMpV0gTP9ROdnZVWCpYKujLujzu22iMOHrjF0ce8okz7bccDYrMHsZbRIKvk73c2MlVzJdJyzqhYLAXuAfZys3z5KUu/AF/n4w064aHdOs3qs9jAbx4eMFYHckw3pMY1AgtkTtR0uEx5yAVx+P6PeWPZj+0xI+oQa5ITb+mQF3Mmjn7CcEUK0PkebLyi6pAK3sD+ON1Zw/tUfHe+yvuRBJH3JmuYTiXSh8pvSuNmnbRlmnjRxUfudmhWN8d9SeX2ErV0pNXDWwiX2NeIYYleKtI21lBirreCibfW/hzl17psNCzqjd6ROcbyRUkElicrTYWRXMSyLjdVc0nPG0F0JfFZRLkKwitMTgYIELF8QSufqj3m9Ga6Ial+TxKda1guJDS8iC0Ww7+lFWwkuj7jijVi7vSUo0MJ+ioVheHPHsX7dNHTo6VeU2ndk4b8ni8sEyJ81nHQLZsVNVSRPu2RCM+B+ugv+7jN8I+vqGxD1NHl3vaHZLeCzPerWes7m5ttH1y0VD0Loc+j80u+tpinYNKwgsVRcdlOZoApOgGOjTsVdYOIcX1m90wSntBo4mnuYwcjDGKNIEHKdzFnXM1Z+S+aJhgYF/h/Jsaq1JsMgXfhIt+1k7KgGm8nlcFP3zVmnikgLUL3BOrszrmcsQYAY+dIbrpBVSvxC0KieBwVHXD4mglStdA0zyEfnRfgEfTndk93v0L+fcXPwwbaXJKB2yEVZUozXaBNUz+k7AjdJFB4P7gAFS0F8+ghfMAJ0W1pqX9clIXx+3La6RzqG5pm22AEGJ2+0AtgVXUwCiiqyUtDrBqU1JQp2YlGRUeiqV6K4NE+oJ/4vmujoaocG4+1SMbnK2iJXw9qUX2tXFtC5aRi1lYVINf6qZkhBDJalevD3sqgWY84ZvXvYZugkO8DwZWvOzTitkgNMy81ItP3rQpETUuJ9zvPX6XRQ9UP4Y9tIWP6G6xdB2sY3Jr57BJFnIMnxOMFn/t4xMMs23Z3Gv2UuERdHlnrvU0/3QygN38++sULa3e+i22y1unAgmC1Ek1pq8CF4MCKNWXKmBhDPiCShzmUkPaiurFJMudflcTgzarL7bhHdazS1hO2FcYbYI9IFKr0oKmuG+qXTsUxmqEHo3OBLWyHfXMndKPaML6hbaYDHaWCYdjzxXu1veoNO0J/eC6UNF9xxwafTXskTETupuAqZwMhzZtXOtb2maZUDuwzi3lKnYuiDa9J9Ms2GJ+2BeBzyQvWowRSY4RzMKOdYsSTL2aoe6e8LOv94GZWsq5FP17KwqOc9HQSeAen8ljd7avzQJwovKnwi0c9Dw4roIMWcgBC/HjFzUmalohwD2OH/Wq35KmOBukJSE83LOwkrGYzSs5mnIaUpzk3B4/h36yvZ6R5z402px3mV07YcnyhWmzNiFL+Fce/mfbOZtgxjDiL/IaTohNjr3Bk3J0Trntj8CZH8b+rEXdrKEd1xvjl8485ZH9PxjaFz4Vht7rGi7c6XVI1HfnP9Z9WUJ8wqJmgabFs9BBj9WKw0RjJ3RanXyC7kHdvJ7yqE9cRN6VowWXZbAOQeumRqtDXW9peHrusMxyG0etZnGncmY3UfDApOk/RZhcnalRq5vCHHUHjOvRD7RU2Lg20P3jhJ9apz6XYkgdPq0Z2XJZHmNLiPZGj5x/qKRzUDIwSo2ymR8IesrDIuaZ8eMCnWGqJQwwGxEGEJt7xD3z/aC4Xy5bEhNohDjoXzcxbubiZCqq9bq/bJ4yNUh5jgvPQ7IS8TzK+plTufmJ3sRPjbh00u68fpOCIS39uQzB5d4EZYHOV+0gVyVk4MOQpeGYzUtMuybQBPebnDCVr/YXmFnFVd+yLAXMzarn/WIPcM6O5glChO60gxNDMz95VGvZ7D/7PEmFHBBRNioSgTHe7zo6IS1IazhTu0OeaYibgmEMfJygxyRhTlqDz72kVZuEJEsYtaNvaViy4bSQGtlg0jNuodVJm0czpTebuJIdbxQkFJ/2q5BPa+YNFovH7+mY67+NjJqc14zK0zPl4fT+rpKVefeLC3MrD9xApMYteZVkziWmlD7UkL2aqyAa+yDkYYpBOzkLh9vbhHdpohDVWMZLg17ljx+WE4mH4bKXd/lxU9yix2vVyQXft30+H/qyVKABLqOV3GMZShRBEZEEI9yAUhZlnvWEKEEBoSnGzwO345gCD7s+LzU4lH938HwXHMcNaZ0m+2DKkybXFrde/4DU81WCn+lVFKunwkVp774h8+mDoTUtdCRCd/HbF1MXKl7fmc3CBU7QAEcrg6qYhkdwSuOShoCZR3FtIh19hiPn8J5XkcJAFjk242cC7sOVgNdvmdJFJx9OGc8JGFkGEoMwlOYQWcVGJ/MxDxDTQYzfcHzFAGdZBKUTrF4HsuFtu5vb1U/Mp5JSZvXjz3yXs5v0fXwQiMJqB7tbtLAB++5Hp7xiwf4udAZNXyu5FLUMshqpgBKeUuHpzif6ZScEA1QJjL4h86JWW6YHWcFaH1KgERXzK1tnuAywT+f3CKMY1F4LvD912sjR31WMp0o1hYlv1kONj0Iad8NSortyW3I9v8thvYg2iNm1WnnerSko/pH6g2pJpfOqvSV330A2RU3MYtIowbDom5hN4Fr76VIdnX/KvGeV6KlpNYNP776RdH73YqPzswHOPM8Uw8ILOYGkvNbrUchX29sVglH7YvuuxQ+xr+jl5zVy3lw9nuVueV4+tgQfRFbmvPO/rMKMWOhdfVYLpjTCgym52YxhH7cjH328TEOvag+ZYs4HT8M+9WzMDTZBuaz3KJ9qxc7gHZo+XOpLKD01B0S34wKJBftf62DeAysv3K4Fnhkj2I4ejR1/7eq/9JluwBugFtFzuGxUvdYmPy5uDe3YuF/c8wrbdqOLtYRiYtEVYPUdNJhj50j9TZaFTqcUnRYBZxsefoAfa4c1zDOAL9V7zOTx8h6GuXeLfzv7+TA9+fnUVI1pWEIK/fHozh6BBA7WwAkYSxsxN+z7c/dZaUmeDtc8vr4H2xqPWvaXo5EoPjqX1PEAMi0BiFhG9G7u4SPunTjtZyarITQtiQFDAZiPhD7GWlWy+0sLF34Wlfqo13/Qie46NahYS52Z2cBkMYso5A3U9yDOJ7dQpn8asT7l69p2xp45rXF1XrlczRtY6WsrxOWPntBgLd8guzg+zF2m2X+sFhUM72N242ehEFZxrJeKft3XZzr+maNOnXgHSh58F47bK6DEORCk2c2u2/1uUkJWDdOKs/ILu/VqeMmj3jVAg0qM6ZIT8Z2SgUeWsx49Su6u/WZeRF2ld+7lYEzTCn0501du2u48FDwnmrzlfJEj0LS15SZ57K87Coa1r9o19dXEQIb2o506MYMKXLd9/Wdj1Ec6NI+NhQ1WyzSGKjsp9YNIbKPDgZiQRByZ6dUVQ5b5ZvfFASoInK/o8EVVxNPS/phlBAY1RGCkxp5rSL3PiUQzo31i5OS6L85oNsASS75vsbeLbMkvuAOgmidmaQsgEP9Zf7mSW9Z6CxPYzIrLkfAJNC+mjq+WNpfBWvkW1X2ihRvf6Ha7mISQiW3zqjsgl3QH5yA8qjI3dRJTg3WuUnJPYILLXGDmCZgvhMjNvDf3awY51f8AyhAJAgplbmRzdHJlYW0KZW5kb2JqCjc0IDAgb2JqCjw8Ci9MZW5ndGgxIDI2MjIKL0xlbmd0aDIgMjIwNzMKL0xlbmd0aDMgMAovTGVuZ3RoIDIzNTYwICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajLYFVBRquC5Mp4h0w9Dd3d3d3Qwh3d0ISLeEtHSJdIM00p3S3d1wx7332brP/69173ItnOfteN5vhpxYSZVe2MzeBChhb+dCz8zAxAMQlVdhZgIwMbEyMDGxIJCTq1m52AD/ESOQawCdnK3s7Xj+MBB1Ahq7gGRixi4gO3l7O4CMqw2AmRXAzMHDzMnDxARgYWLi/h9DeycegJixm5UZQJ4BIGNvB3RGIBe1d/B0srKwdAGl+Z+PACpTagAzNzcn3V/uAGFboJOVqbEdQN7YxRJoC8poamwDULU3tQK6eP4nBBWfpYuLAw8jo7u7O4OxrTODvZOFADUdwN3KxRKgAnQGOrkBzQC/GgYoGNsC/+6MAYEcoGZp5fy3XNXe3MXd2AkIAAlsrEyBds4gD1c7M6ATAJQcoCotB1B0ANr9bSz3twEd4J/ZAJgZmP8N94/3r0BWdn85G5ua2ts6GNt5WtlZAMytbIAARQk5BhcPFzqAsZ3ZL0NjG2d7kL+xm7GVjbEJyOCvyo0BEsLKAGNQg/+052zqZOXg4szgbGXzq0XGX2FAUxa3MxO1t7UF2rk4I/yqT8zKCWgKGrsn49+btbazd7fz/geYW9mZmf9qwszVgVHdzsrRFSgt9o8JSITwW2YBdAGwMzExcXKzAoCOAKCHqSXjr/Bqng7Av5TMv8SgDny9HewdAOagJoC+VuZA0H8I3s7GbkCAi5Mr0Nf7T8V/EQIzM8DMytQFYAK0sLJD+B0dJAaa/41By3ey8gDoMoG4xwxg+vXv30/6IHqZ2dvZeP42/2u/jMKSMjI6srR/d/yvTkTE3gPgTc/GBKBnYWcCMP8iGSfog+9/wygZW/1Txh++0nbm9gDuv6sFjel/Knb7hwBU/xwHNeC/sRTsQawFAqh+k1yPiZ3JFPSH+f+Z6n+5/P8x/FeU/xvJ/3dBEq42Nn+pqf7S/3/UxrZWNp7/GIBI6+oCOgB5e9AZ2P1vU03g30crDzSzcrX931ppF2PQIQjbWdj8O0YrZwkrD6CZkpWLqeXfbPlbrv7rymys7IBK9s5Wv54VAD1oNf9LBzotU2vQ0+EMouRfKiDocv6bUtzO1N7s14mxsHMAjJ2cjD0RQEsGIXaANzPoFs2AHn+RGMDIYGfvAnIBgNrzBZjbOyH82igHO4g3v0R/Iw4Ao8hvxAlgFP2NuACMYr8RN4BR/F/EyQRglPiNmAGMkr8RC4BR6jdiBTBK/0ZsAEaZ3whUi+xvBKpF7jcC1SL/G4FqUfiNQLUo/ou4QLUo/Uag7Cq/ESi76m8Eyq72G4Gyq/9GoOwa/yJuUHbjfxEzKJ+xKYgkv/Wgekx+I1D/Jk7GptZA0DeKuctvOeu/8r+v4l8FKKDpv4gF1ICpsROIEf/qQYWaWjmZutqa24DW+T9idlBWU3ubPwzZfhmCHsU/agVxitHsDwiq7XfdIMowAv9TCjMLqEgQy4ydLX/v+pePoyvoNn+HAY3V/DcEGZj/Adl+Qas/YoLwb8jO+gu6/a6C+Zfgd3D2X+b2rk5/ZAMZWPwBQfF/V8cG2pulp4Ml0O4PC5Dsj/xMoDbf/wFB27T+A4LG+GdroGXY/tEaaH6/I7ODXO1Ah/mHHtS7/e9iQM72/1GDmnH4rQYFcwB939r9hxdszP9I/8sKNlDVDqAX0v6P9f0aleNvXoCCO7rauwDNTGz+E5GV7bfiv0FZuf/R/FfM/Gtnf0ycGTRA599dg5ycgbZW/yUb+y8boNsfc2cHBXG28vgjDKiF30lArz+ji6UT8A/+gebh4m7/hwNovq5/QNBq3P6AoDrc/6AVyPuPZCyg8J5/QNBwvH4PExTJC+j0d6r/vKCmrk6g0bv89R0HIv7/4L9+sQCBHkBThIVZe1PekPffQlrvvgrjudNvj/JPkW9rplLTey84tbk+vIVNpq76HLTqdCOcPPj93fKmONW10CLRs/dhUy1sWHOicsujz5NhvMrEdgvC/Dhm39iXQ+GaXgJ4fHo1oR2fZ0cfjUBryCbwDhnyHEdXrrdKeWh37j2SHjW9pUvDobPbyjtVHLKIT6WT9NHqUXqBRdPkuSaZM9gkMC70BHA0qGceyNPXN1Oo2WOvRDLxtAi+R9GsBd46aywx9zNeK+VqLM6dOGQ4OtgEkNeowxMU3iJ7KTJYc97FBct98x5NfAVE2Uh0n5bp3zHssWRUWalE2jV0V7sNL7Qzb+UkA0Io8frQthKrSxrQDZ1IFDGqWgwj0VyqWa2BBHvt5iIrrTcaXebvP+Evck/WvAKmkbQtDwMau7wfax1XBof66G9DPzXfDTYMbXb5ahYJ9griW7gz04hb6kYsL/FkEHyCLnUZgejUBEqjv6NbdEvmeoI2/sDnHXQu8oDLvPGFiUmHC7obfBj/hD3H5zzGt6LuTKF9bRplzsYdVT/4NZhD4dWk49PZ2RccS1Zxo8+hVLkZ4l0fc3/GUirzfgPWTQeXMp6tVWAyiJV4EsklbLDPn/eTFbBJS3Zvz1UORugFeb6/585nONGoUG+JY89XJt46iqQf2asLHBAJ/tDDfWO2t3FTViZigLFvr3F/VuEeLjIYs67GGZL7sV0lILvTWTFNUjgSovB2c6Yb3oT0WE3Ejdi2IRZZU43/YXOks/DJna5UWoycsmBBvld2ny/MZ0F/XqygG+drgBDmx+uGAJZvbYp3VGBvPr9biSH/vLMESWrYNtigcf6CK4KnqnaXR+q1BtY9NzmySfxjYpPM26ZCr4itpxHAyx6VBmkTT0E8txmQfrnKTxUV8WIe0fhT3V24dhG/OmO6D7h6NDAMJUIK28bKhC4weiQF+FJC+fmnXAEt+utsYtb7Da9MoQei2Eb+Sme9bz/Rr/k+lPHrdWqDk62KCYarH8CP7zxxJGdPekjmKtv1l+GlR+BsWVWRzyZlEc9NIMixgGFV62alo1xtFvhTE0eZf9AKgjPdQ4mEA9vkm6FEH/gWm3KugqbEKp5LHELPU41CibL2Mi78Vga5igF6oeebqMwomIxLKRhFtzcnTBxHNQJpoMZ493jn4cys1Axe4mUkY8nQW4k5C3cSCfakWPdz1XAyn6rXQHtlvtHd0U+IiBNGfvV8mYTMTCU+cGmvfC37tqe1Dffzn38OWp79zAlZrdgPgKur+/o1Q3AQx0jwkjPlEBPRcDgHWje5/ZLLQ4mPjXmG4JLfZexOCmwRGYmXI62p0ddJ1pV5n/UxXV0UDNoqHbNWyqXi28SU740nNuHsi58pIbnequNpgF5z8w6bIpsbsW6G4a10c97X05qqJ4y+HdNIXKZVgrILeZl7+WxtpvLhWDdvjlXspFm9u24AhFO242A6CSsO/y1kUqbapLYsw7Is9sEgdRcdluSQrLdxuKiOiGRWGwIhgecS1dsIWcrQbhZFpimNT5Uc0kpkZDaP+w/ljfSJWGu6ndiH08CRwci7flw4HNnhOQoWcoskkyqvsFuZYZw0Old7P/lylh5sr5+uCWk5YdMcNOktNIVIvd+RyiZeuTtGi1cFe/JlkzBNqbF/jN2u651ZZLtUUAiWbMaM9Vw92sGoHbq3Je60kuWYKeiJNmZ8GV1UvJkdEyrQZPEg2uNyJJYzm6zcxLM/9Nti1mCMGhDhF6q+ejgmZkro0s6197onO74fv+0PIO+p6JgYxHBf/7nOom9f2r0KqDR8FpS2/IHsupcrYnsiAYPFU8f8Fm4+xQyuZMCT4zaoc/EngEACqTgEW86OXfXCnaKE/nDqa1WWpNddMfcBNv8AZcIW1fBzq/STpcJD7az3liIq4G0qM6Scm+mMLQa0VV1hJ8UAifzRgW2PUIPmTGgF9pcK22UTcqaFVGiaB6P0Q9ie3MTVREbz6+5MmzZyJXGWXB5CDWFqVRE5xh2+UswTdrRS0Szh/NXbTBveSu8fnYhUpM3zWtB2EjAJJHCRYKlgIVzeKvP2CShdPWpYVFuGmmcQJsIv/rI+9vKIhmizU580UVZf8OPbkDy35PdeOQLKcqoN2m6NXbKI4IQUmQ9zGTPBJM6JkupZPQlJ0zZNkeXl58Yle3WeV3Qhbctfm73GoiT8YeBRbUrvy0i+ywhUAqHmNURiNUXwfXc1qOOgllUHlqxw6HJPA38WnaqgYjZiFrS1SET3Q5a2KWUy7LXJQU0EeNxBFWIb6o5qaYSjYPVfXinnVCGpKb1euwXn3CMAh+gSHF4WcYOd/C0THxoTXTHP40KijGhtvHHhboHKt7NxhkLmWBysuFKrSsZuE1446iMYhl+zR9D7dMqYCWlKt/qjUati5Wn7TRwCQnm9V0qH4QMrlFkx9zQ0eOdzW0fCp94ioVYqMihmrVnRtXJxlc0SBh91h36wyObX418TIpFYe5CVuFPLNXlMjW/XCIyxobKxqOzKXDSZrIheIW7cK51Jmfmht/58b8ymzIz1ddgPUMa94ahR0Fg0XABIcDawPs5zNovJsHvrFd8FB1uRv/uFZxZfLssLRz8G5azUCTGiIK802E1BrD1SXpKTm0xazuqFIlF43gJv3c6GwxM8TAY+VkKx7oJPFn77UGnki2KMsDD2kFtoov/PSZs8it26O+3tuVrKhVEwzcXx7WCKzjymQFnACw5GOqMVvNXCpCu8SRbud1EErv4eL2GpgplsVnAET4YL3RyPpo0VF2Zh14rSzDcOwmMMumz5qvMsJu5JtKYAl5IvJwpAXGxLfLHhbyuIvSRpxIR+W2W8tJwOel/cPXBQtTckEQxW2MUrR5b3EjFQ8bMNl5tSJOtu18/2A6gIhd/YNKBNnDAbLXO5Mly60p5sLpA8XArwntH5ew3WTpAj2LdUreZ4QA4wpToHocwO4KBqMkt4jJ1M731aBVi82MZH13loeF7XLaJMZJLok3r5YX8qcnC76ELKJAiNT7uZ7y1mcBLh/kiGYdeoLVohyvzQ41JqJkR6W8wFNm6tEDYdKfsVPGeKN7/zYDrRJlDigQoGcT5K4TKiEJx3bb3A7KX8++MxeELFu6dVmtYIvr7C3OTNXrQQtFJI585Cbr46yVgkUXGjDxr7eZZrbYM95BjKiaMSBfZKbT0bEyjB/mSlcW0kE6ysrbdK3HPcRzrRztxh4JRGmxWESEdOi5r3PApJBUcDzlPX/UkNREIw5sFvPhsQaK58oGBhc0ctsfFC3CGbZtE8RfvmvvKh70iR2+Q1f5tEsTAbbWhEs5tGAlV/hbHQyLM0SrkaPnwwSU85+TueBE3pspUa5nn0noEC4MbMMF/eKPhLqCq5Wo1CsyxnbBUcrUra7JGuU0HG04D2dS/asbYj0Le1eh7/TUHk7bx2mNLDFcKoBLi6eN7R5UvU2ZRscOcMslQU5bc6AXAdZaFRZOmFNRfy/K3XlM+dusXUnD0U7U85lqN2mW+qcfa1KaeXjL/Xq3WfU2o5+U+vpjHaGdolQ8rI5WIiwlGlCCF82835MZ6OUFGnQOAtK1G3unRmYJ1h8vO73YEf5rGRXFW+PtyS8Rf1XPCmXu+ncFS3jVO51eXmnTy2xCvmVDJ/NCdb4dcT52T0732XF3Y6q5A0aS38JbdDztdn9hnoJkLe8Z6ziHDEoqJEkd5YpnAMmv469UenhDtMWHaIayYOHyyclVLNyOgn9G6qRqczKOT4HDqgUBuRbdDe+DT5ZdRy7T0wDPak1NOaj/Z7eRa7BROtG34T8aocCssOvWIRdJtuhYOBOLhsvZ4L69YCN84n5sKZ+WKLkLIUhm3hvkAMiwB3x7ktAa8t5Kmq73f+IRsireLexl5kdr88EZ4oJdONmOl+ryFCIinozcrqw0mJ+KqxbniQ+Z2SB1uA1IccDJ8DWM2nWt4lScJZ9HfaaCSsIlfsC5dPO3frUnokU2W6MHfMKaNpx6bsCnfcpQ4CLJwyLSLPl3XOjJAnEfUWVFclHhjKdG9dBHQrN7hGEiWdexsDeYhUyLj1OdApwh9sPSuprepwItwG999/v9EsjpTrURExIFARMbbpOPSoMcyZ087k+cYuX1QFtbpzsoR+GgGLFtNSgVyH51/8yPj+y4e13oVcYt+fRkknh2IUmvgBA6Vbs8paTWQwUqtFu8jDLtJfKlrh/QdmGBa08c+F5u0wypxS3hleHdktB36HQ2pXfNp0EVaAppdDskuJ/CQIbfgT08Dww5IFekKdXxZmXyxvtBHh1/HjYlmRsJ9nHMCe+q5loqr4RgSBpD2bDmWH+FDcsjz/KerO0PrM+7qCC8ZoXlhVHMo3Bk3XPFsuUDLV74UO0D3KaoLFqZgkh3hHmzGWlB0hYkr6k6zVKJvOst7xZvHFOeLZzW+5BrrYyIkyJ2r1ANhHcD8hOMbP9ThOFgQKbkWOezGLqtJ24ucrMXf7EQIHIVRZRhBZy2RS5BeHQpJtqM6n6sjgCJuBg8rbjLYOCuyynOCaz8AIH+rupfmfxhFSKRVrOk1TVWyu0eq+Hb09u91XxTDo6oAJ4h8p2slHB2D3xNPg0nDT2tvFU9k4suR7pgXiVY1HhI8Z/CILw9L6eAGqMMy3ANLLqWYUy7fDusqhcpal2vTbQX6qTi+exuwAeSVtyZKZcV5CbqhofH2okgksbTDMyA9C7AEJK6sTVLgId5/jBRAzu4MbBsWk3oflvdt0xnDCCPJYTkHYYfgusDg+W1WVO2b9qXLRpoeXIqWKlG93Mf3rBTCO2nxiS8Irw6ihv0Ewb1PaFExIVYoihe8VujXhBAroZgfGhRaYKRGEr7epUV3K2ntpXCFM7OnZuslzPkWLnmVKnO9xBp0SZDIm/zL7cZ3R3Jd1NSXj8Edh/yaJZEkKSsUupbm88wTsNJGWpvqz79NNXUOjdk9dtAFiwPQc+fuRfmKp9tNIRalXuMGRGCLD+/pI3r2wb6MX/vEbMo1uuW+/BeovkyKQLcCWIi9RiloKBrKn8YWoYj8TtBz/+Np1LpRYgZ0Jn25cXhtAj54m7G8aEbpvY68JXitPdREL4wTWUES6ZDQ3bqft/X7JiNXHBsKNoNKomVLaJufZf62aeLv2Kfd6Sun70JF3Uh6MeFXqKf+og/GeAWLgvOWhojWkUWbDScamw93DmwouV89lMqeLlJXLZFcEc19Tx25a9i5PP+LnFf2ZzAe8u86jt+p0FeDtLjnUO1Y8Uhc57YofepaoKg2BioH7BBIa7S+O4zCYAuWue2s99JI84evnPV7BWR8ypHT0yGPVj93mO8EIkca9Ng2w136IRHuSByiobTTWs/JjV2odrgm22qLLJNxh0k+xhtwSWG3OSQktxwWajwU/WzeqMBxmXD+7UQb02zKgUo6obn4XaxlesPF8IsLmTMTMe6N9PStaU9Fru19nUF8l6cpuKJkBe1e3wFz4iOzCGDWN+LIWPbxxhrDG9rGaucIu3PBRTMDXAYZ2x7zUgtuSjOChuBdcX+hU/t5o3mCySVL2hpe9DOaLe/9hC9SWtJPjqXAxq7lw0Ko2ipVrecD3la3ui7aJ06NJVG2nd/sEYtc3PLHRi2aEsCoFkCuARGEXlDeH9KVxdOjUG83GpV8Gmy03xrh1p4tcX+FUd7G5ZRNwQlB61GRLjLXIttwtBhPrFYN1NyA8IvEc+4PzPaGkqVJeW9+/Y5crKpXuNK3z9bEk7CSL9xLbQFMf+x7n3qIdTdv2XK7DM3q62zP2pfczc8dFnY3/ArATrx/cyPVOCALXB6r8iAhjdjl8rza9z2CRA++EMctz4tHI+CwXtXAAKUK3ajTindFk+7B4Vv53d9wu6CNjQrw3uV47VhdyxiFYqL7vh77uDgo95kds+/b6eyDvnGrWQ8OmbduFOcekMtnRvPV+W2UjqFPidRmZPIQaKdC4y3VM5EAvN0ExkP8IeSprJAAwqi0m/26Ukney0jHoXCrY7Pajpc9A7+kjTQLG7LPy0Hqxgon5B9ql1vafIVn2JPDRC0Xq8K1eE5cWBxYjxlsxca61EjkTaXzdaFoPniuNpeXjEA80rRADFjevbIJaLPrf49iKpdJH8jLmLtINusYd5YD23z6nqh9f+r25LUhIGOcUOKLu+3KZJmUXlwXRXFwhzEmy7y0WqsLHyOLyLN/bf3XvvF0Y8GjNLa11lWCeX/J5AnLjdez5kRZtoVBL/Kgo5d0Aw8E6ced4NwmNzJIq59vORW3CKjj8PejT90tIBBSTC8J7Mm9oy3bCO5pa4FAXUfmvUxRyt8k43L6p4qppo3wkXcKulPv0yjZadLIrmAE2RnlzdNt97y+BZaYhKTdLR7uL6YxRLvnyZc2AsbHEsbYbavAG3DKqF7n8/l6HsNwrRKzERegN6y0QNT0je09+XkjgPTWfpqXRlnxruMDrXN7gq986cO1YQ0xmxudTc7MWsu9EkahTxABWn9qA8MAeojn2M0RqfkKSki8vdATJVKvszRTpaLxaTsNbidsHvV3c51uD6URIAlxIRN40+E6fAxWAmF5PEJKU6zTHq3Lv83gqZaYy64AJrwdpYwwR6yWR6jBP6XsTlOMl8kYXmXhYRoGhXMXXk88ETho/A7/jeOh/bYJpFaDeOM3uqtMPsMm8h2S3b3+nu5s7LsH7jk6BopgSzaokQq9aQblL+kJqeuRqnKhTUI3nWGhe4hRrV+EVEVZVq2uFqZqvnLrFck1zFiawjc28SUKswTJ2iWG+Rg2C2kAVeoKe8IOdu+8zHWK4jkKjOMa4KPhV1S2iNmK0CjSwzuv79M0Za+ukHkL9vMvxy4v2OrtRLJaEn2GGR1d0MKR6lk8kpVZCXX9YiKQQsvrsOw5pRD2itJDd5RuBJ55BDcNHiEGBmUJuGmkmX8ypOj0S73kMuFNW9UWvvvNB1y2Jz+aQwwtfPlwrrRYPUYvHhXMhBz2pF3x+cKeuPLNAi/iB4TjNs2b2nrSgqWoZI9wS1rEfseBzq7M9En2TUAKCLKQkZ+wmSYWP8ngYxE7pwzZA58LL2edDkG9+j9xMrSpaRAFPgHnpjG1r0Xdh1tPY2TNVRJYefpz4Wd0as4b5xCeZz3rLNZiEFfgXmKZHi9gBT/fIPjA/XNrfM0/0ZQjvOr1EYFR2TlS+4AzLuH2nkyXyAYe/qP0wlqzxMy7uM0LqU4ZySK3u8k8+9S4tHnyooMUlQVPaG/K1avhjhZZlEVV27tC74K4a8OjSLJLu2Z7PNRZ7avutK1sGJiWavXAwS1TfaMgAUe4w5Xd71BgRUYmbHwzQFYidKrq1vQr4CkIpsJw+8QqbSYviGTGGB/oi0L8HgHN46f2wuUAefo74LMuGSzMSKEuPM7eiWaC6rRQ5UilcKkkZ3IPZs/yAVTM+OSx+yjI/LqXE2YVVRXisvaU5SP9NYhBVXD5+Tj99QOTjRjYZKpj+OQs5n3LTzobfDqSlwTrh5v7w0Vf//H7SxX5vs0IH94kQAjCrB6sDIns4bqfEEXVvO68fvhyq+pf8Soabx5iBH+vUAK3Kag7KBQoqukURt4r2X541FTlKGcz61itwhYh35z7tCRvgVmLtyiJWLos28JK7LA/PfmhhhN5RpW3U7ELSbUTLBSAdvrEelRIhNZliQiDyk7xHFOeNKSUcSINS+DQp0YrRebVlZn93b9krNu8JLtogxapst7GNMBywRTf81lIXU5QCCb6+NxvMKtvn5eUSuF/rshr8kZSNPpK0MnydsCp8o3RWJNrw5LNMS2Kg6B5BShQZvtT707yzk7qZ4Ykb5KnFbpgUvEi1TaH3jV/ojWyUo5S4NDsIYIT73aIaUiF0amiG29rqClk+fT1Bq+zbFdUGckNNHOBl6rS8XJEtaNZRuKNQBTUECkXFty6BvZVpuPZsF5LNs2On68jMoVj2mgbIDjdnI93e3EeXjGytiIg4nDlHCxw2GXCTvvmIlKw2ltkxnFKHoeeaOjuHgj5hvM7Sg6eqzgvRAO7b7x6SMlH0Dik9Xp8m9sCLha3E9PamX46N7JxlSaIapuzQnW/eaKN4jZP6bXmZYffCG6YcdOnxy9N5neAWG/Om1KoV9vbTNb29Y5cTPw1+pKFWimW82PwX9I1vrBoZrxiz2hCRm27iO9ym+5weq4+gX7anu54J71bf1Ar4ZvU0ANui2noqdilml+3OHuqAbWzezbvH9x/ycbUnpnJQDqAOb+eLItus8jloZnMtRDs0Xt9zMRvPIH+XrBjU/RqPvaqMog4I1nqY29CkxPOr4RTkXJZVbAHkANyDR6o4wrddzZxtCt1VMRdoA0WSWoekxlxNZmY/t3y5wDRaK9EJIfgSGTuCkwhMInJXjKqGvAjVQoJ8oCgst/GLYz34dEuAPjXdGG1eiCtZXfAxyXoDvTy8A/2H2Pd3HWLo+E7UhC2YmL676fWHxA+2ukhDpeEOBhAH6yTBQLR0GvGx4tpqfT1tzVY9a5wE53CRbrpjaWWkb6M6R8zSaytJypR4afZqWbVsIcaorUbw4+vRRxpBNxLwfDaXt/4WUvW8b2xV2dNIyB+kDIdFbbSDa0mmSsZIPFUS6kJFSuYy7QrCnmmS0Ivfd7+Zi98RiKIuPzR2+CHng+GJNNx7wiGw5qpHQlZFpSnSunJxIVxG4bNgXIQoP0nLVc+QxzjZ6GR9bVa+SX2sU+ZD82go+Gquy6u5hRR9iZbvHWZAowNmw8qj6rnu7g210rH9Gnmty+Urc6jaN+7+0lp8a5Z+UfaKKvg4oBy5UgLXgzrhkPUZ4wMtGwBzojtwnZj4VunT1+3YGlGhEe/vjzzicEIJCtPH/iV3RO8uHVhi10Ne/L2/xVCILMczkV+lmIMhZjnhygAi5DSxakaIbA0BhchdJ9TvXN1Sus9ZWb7dSHV05Gp/9ZsZFFXdhkv0GJuI0mfR/sl5u63fpdC/GdXZGM5KY5HKbpEhJw1Z9DLUhUN4oqqBrzOiOcy5x5x9kLYnOyE8by2cT6IfG6rgSVho+3kIfoLp/oWRNxHzSdDipQdcU1SqGTLyAO+cvBZum42vfreJ11kOv1DQRFWWGLwzCRpqkjhMlonMsvqUDWzilv8j9GfYaqrygIQ3Ei25hTC3HSkalWwl+x92hYXpr4jkKJXcKH7kLId0IlJL/oSlojhAIqyKgn7hXlB/ES5OFHErU4jR1DWjKGZ8R+CvjBulzakxka/7hfQY+gwVOsNsrw/eWyXWiNKnrdSl2YC2jMJTfy65sI4TMuB7/PSF0TZDKuOiT9bTsn3ry0/p12JJoKKGAu6BPMP3VUwTGlLvH+MxBeU4gKvN5EMvq+X197eeS3qC8b7HZBso+pjftvz4B1TCm3jr2V+mj1Zf9LKnRhtN+nMy4ayoTUywbq5eFFfl8JEimpbwFVb9cYJUs1vm9bYLnZpVrbku1IpkXy8ERmGeTUwV51JFrOk1QO9LO50VlgnYvvWHfGUqt6lhQupdE/rJhmeK+1YlW6/pffY64etFNVIxW1Mo2OfTZ6ivMjUSmUqrRcqMnNh52ogT4/PJub4dm0gnZgUE1FI50zpj5aLi3uzLLqleGQHwvlv1RMbYETCrMwe2Gxar1YFV+CqvAYRF9cgN2YFoP+c77Mpi8VTaURWrrrob5yToDVTs3PmAggJHrMernu4us8/WXdI/CfCsXvbbxwyqetzKIHEf8Ia0j8qYx3UTngIm2SEmjnAJPLIFPrNgI2pWtXQTiHVaD2vNcd5Och9unqx/uQ9sSKTVx5IfxP56cORLFs0ev7hGLdujkFYQwKPeA14X36JmwqsUSMgMu0apwRZvdN3hoODapUhFWoaHxZ1msvYVX/tLjNxLAecwwXwNMcuyJiw3TvWBEN1QXdwEK9M4qwSPD5c6knhTkBtqtvaTMoLdXJBbxkfhXnAeQiqwExTlmc3a2XfBZ8s0Bcw0Q+9V5zKrs0M+hnVVieMKlk8yBVqehxA4ffH0l27gzGvG42vaj11QD33SX6yWx+lioOBhYfAKKA1YPwmoAZMZXOBaaUcoxtlK6Deey6ZHn6hub7ND1hctC2WAbg+pm9WMork2hUiPAZpJvGmXN1izIeu5htg6NCKHRbroHIItDrUmblpAiMSPXAHXinVQsNdmANoyESlARX5bgh7Edg8vsAy2G5suRpt+JgCfPJTbrQw9W4wwFg6Qt2MeqYpAKN4L7Hf95szlJ96RnfBMX8O14gIE6zEy+kxp1PloID3NPzihphN91RGqV+RpsCo8771TLUH5Bq4WoM1cRoZ9ZnWsQs1JvG2eAIu+/EUlSTvM8iy4+KpZBEZ62GsqrHZZSMS8nz7clIRYjyswBtYwrV4qLx69vf5iPPIGWf/pCa1REdM3b9dehJuYuzxoWu6kDIqnD6aY3tyrPwK+KCDwa2OuZJjLyWGQhBQeZ33n4xXOauJAbVGDCnypIhXeuZoRvuOGSFTVpHY19HtFoKGPYjILjblwS4EFgoeu0a6njgIvqZzwszgUPPSaibI9JTxysD/tXcw221wnXVeUtucEm4AGnrbZjlbSeihzTG+0vG9PWYJiqgG0GBS3pJPlIsy+myJi98ZB1zwqsUyo8rxW1XicFaUtFNF7VMoftFdydTTLkmSm6wsPIVDf+chPY3k4tJxzab3ZZCcRMeLvjCQchaKf+nd8koBdWYwU9e01X1VLzqHIoE7ni0sQoD/VhuxVwX/w33zSuduzZoBqNhO18N50bfHoElatiC//qZuwR20F6NPUHCR6hUSq8Y9lFQYG+BXprwNO4I6/fKKxjRgdt0D5LI46trAnCaTBc+tbwpnNH1LwAXihI9LviNu20wMN4eSSnmxLX0utuN01CL/9eAnD67k3Kyb9vAQGNlKkgPekxIxCvc2eJ6rHB8YuF7DZcWe3J2ATsL1gYvLB/oDWZvy11K7xHNa7ToJ0FaEnUUpIDQcteNcvhV8PGDecMzI0FT76yF/C5sI551bs41BThEQo7uoYdU5HI7P8DsfPhyj7C0YHpwgMR1rQU3TV0Och59VhpWfmWLZQGr41b/1xCHDxZchRPs9hSvfxe/kE1ZGl+kxkSflYYQm4Zv/VmHY0YoWPaxQNBX6Zlf2MD3yhihDhnDk+x0gqFeC5FIKHRadJt+lLVG/1ugNvzjmOjLKLVo2XDDFsMvBuGJNg7901g4jXO2g9xnNQyENQm1x/uq6WxvjbX2itXhxq92pwa5jNjrqzRcHT1jqpputklDGQsV0Sqs5gVRHx5uDlvXXZqkEnBr5ooGYgyR4kwqw0xdd6Qg/mif6oQiW7pH2rwB/jEOARFZ20n/Uz9SdkAOv4y4+REMoajURkPMo2TqHd3aPZnzubEyJgYOKWOshwDSovxGyvpVnds8bk7ud9AWVrpIXfJvkkVH1uWo9HvXguDa+SS2sU6dq4rKikp0MSE26KOVjTyd00P7kzwGT1fPSdPqfzJMjiIBgLVJYjxFvloGrWc8Z0chT59G5V40Y5FjceHzhcuR+F/hE5Oo53xRYvc/uheoSeecVkd1DmjC+oKh/Bfo6aIhZ+/FA7Ikvv3SXLRp6Os3l71+PzjYR3qsj1mB1cOrCCtKmEN5Unx2FK/DQgKODJS+SIenQNy9ba2fsqRcU5MalpMpOsi3kZPmEu1o2t//zDJ5HlLo4MAJ580WhOEOVXB7UJQQX9YE79vszHd4Cl1n6Tizpu+SvLdhH8XuaDrZoRMudBzwl8lHrsBjaAmFXYaG6SYmMlkW+wID1OpEHoGwUD7GvCBTXnfpKoW7vAxaqpds94i8TOY2mv488Ferod2gdOyBym8m841mq+Z7a7UeSRofXc1parcfXCnRAM7FLK2ppGbeOerHCGmm98/4lfYmETuDTQG1Ax+2HUY18PoWCaV2oaiX9TGjN9eg8W2V27toOTF+e7yeBpTkpHXJ5plaEJSfVVLhz4SDNU8bJLWwv+Vxam5FGJxH1j36na92a+abwJcwOkmr5eSEepN2x2KV2UcOqtzk4TncVBaR7eobaVpaoT8wgCqnZ78TJcpShM4Cda86Lyr8TrxwSs7wZPy+K1B3VsXhY2stWGr+g/MoQr8DwJZ/vSVTYkkAUpYW7iOAT3yRCScG+hJRsiTXBO0wLb0mdMK/rX87q9N4q86RvOo39GgTF7AWf8QmhM0/n9DvPfa/Svk6L3tE6NJz1yCFANlGEujzUV+1p8VacH65lCke7xGD3DXdErqD87C0LugBB0NbZRJlpuQRWIqf/Oosa7DrWR3QYATktQ6RPofhx1isRe3zdLMY8mOHvXZ3ZtEqzUlK/DnoDLwO0XVL3v+fi0yzyyuL6A7iIVxUzShUJKKHKqcc5WRr5smq2o5NN5T2dl5h9Dgm4imc1YhjCuf96cpAnOoLq5PhWvxCOgQjugXOk9Rxx2pmmKdz4NiY90mlyHldtMkydvsTXaBmkyZso6wk0G1IDiCF5crKul8DgxHdoPevu5TV8h3GqhledAKVsut6ad0i9AztqAVgoimp2arUWtrpsAPjoUle47EiqzZ+9NFMtYJTA+8jy+cDvyUBmhLi9SMaj6/qYBDarlItF/K9g/JNEnfjDnJIg9E0XuHcZPeW0dZyxWXz22Nyw2Cm/NDHL4VxHbS6n2Uvyze0/EAr2IP81YfzMnxZjzBT/wFu4ZiIHqRdEKgYSyQeZTehhSluITx2lVfxSg+kITHPbEpRG0QgV3z7WK11HcYRFkUHsmScwCBpmrGfjpwrheDdCvFXD9A7DKMwB3YtNVv9pHwinHqL5D7r43HlsvdT9oTkl0TiexgdT8IsVsF7l10nMSR4qecGdsF4cr+Yzjw45svjKgLyQYiDD56BiYyGKKCaznnvtKBYuDcBSjrN7tM8qBQPqzjc4HTREiKVX8p6KK8ZQbVxDbjkSiI/nTRwkd+WBHuCEajSDMuEWHAlmJNWcEBDM3CaiRHoI+K0qNE8FYJT3Fwz7C5IxUdnmSeBwxaM0RZ2uUDY0WiYh4IGkDdalHe9Fq+vE0eoJIhXr8ZTydKzgqhr8YfNhVYrKaJsnkDURdo6OimdPnnZJ3OXNT9uSGqH1l/tupO6cqGHUFh1KMDekyjNezYRKqqRipQq4xpN3DdlwbTDkjkzK1RgI0NNFL7uf77OZCZkrM57C9KrnriYkPrNGyraj1TLAQUQ9KtPBDreHdd4wXltNR/JHA/qHtsGR3fgVsxz4nLQlIhEIlDlGdAYr49CaJXVyyqvC0XqY32jUWvVy8zsQRHoWw748qF28Rqb3ak2Njo7g+Pvow1X9WZkWMLKBlMKRruDvTg8Uu8P9SDmG1tFpU0PP2Wcz2NJrKx30TFnuIot0xtO2kK2rI8VYMe+bj+yHwb6lpAgNh4Nxw8Zb5yE4MdU15kIfi+TMp+AEk4FcmnYMIG727X98UjHrTg0GbX4lCG3yyVaZIIUoWlo7BZcKcWrTk8hhFu29/skkxfRDzzoe1o4ykZ8Gwq/PdLKE72Pi47TfGcxFXAH5dkXlzzh8CudBQR+SRexqyKLXXE9h/o7WF9/zQFJC1tasvLpJl3HI/ABaz4XlmGfAAueuvmIn8PPihmyTbu6ik2oN/5IXkVfsuSTW1TAXzPdKeZjfPp3jpWSc+2ork9GKlnBR/Wj/+2lZCp5UaG6fHWD8HZEYiiJIEqjfyNqjnmvGjlvfTOtCx4/b+podfGachpNDHmFXdiRP5pxTrGx0KCoar+OMzNBABYhJkc9YrxcSeC1HTTbPr6vhmenP+yUK+YgjecSNXR41Zgg4BqixqkAfZp3c/bKjfd8PbFMD4kByqvoWdBDOW+bjYhJrLWkxON7iJSVIAw16khMWzoO7e4y9arduwwap0GAuf9jw80jCOy89KAb7yVSQ+ZeTrAlWShHNk3z6xd0vJeBkwKlpIrKsnMIhoeby4b7HUTwbrMPpRuYL5wWAotqXCGPp1ExISOl/SC15YT/v0M+Ju44v1y8h3sC6tCKmBiqiVe6IZlN3dQuGPtqFTy4ZqMp+v3reICJW3P+2X3L8/0pl43JuGe2jodspje/xm+Zmg3KGyUrVDhTBsMMiyM9oyyJ3s22YNf7h7U5pAfk3fjEAM8PUFvL0aXHeKwZVnPgTrMJGwB2LoEls2KiOXa8naZW4XM04e4WNunPH4yYuKV2t/jUZEWFxYNxRrxMquFC4lf1J9+9Y0GOHF1weUiqAEB4XcizkUIb29RGpVmpLlCwu9Ra35R404HMna8Ak6eGu2bHZ+iboPXw0D+tLquDsiOunGNl7DVt59NjWDDNdT8lWPIUMUrUF8ZhgxU2FZp9HmBGTQ02QLoH/Fhb7JJ7nRx+ZClShH8t+PsHVPeM/BaLPjZNMh3oYjFV6skk/9sZALGgo/W4Q1bed1l7shKZPAc61F9aWFRYlNZq8hL6/wraDjwYE6k0bnj6AjJLuF1qiWrjcfAX3Jp4Rs+WG8AssZo5zrg9my9bWljSiOEx1kZK5WBVcYNcXc09Wfjkn6qzgCW6a8scV5lOW2eBR3NFJ/1lKma9vF4i0uMTqpnDoi2JUYu5E7mYtZ4q2/W0ZTycwIbG6eitlww+ik8pnf29o702XFkBjevNYCXiFOLHwhlT+7xDrPkd59ylVhVOm01EHq56FICm6Y40COGDBDa+O4wammwU7m4IrXEs3Pc+Oiq0EybovpidVpibKVMC395u05YMe0ovuYXZJRRKKxCoseX0vjbsTYqTIqVVHUP4ac6ItNTbciarJ4d1ZTmro0jY4ok0eisViOhyyid1ITN3gz0yghZ4PS1S+/fn3P1UKi92or4amaqBaIRZYeBOFZ47IBuB0emTiZlkbsTkS+IbdnmJjHd2xwbnmnxrdYLx5jhN8Pd8OQwQf9dTdH74JurfhlZUlY3w/7IB7irFiD73lxy7N6MtTi41NGmWjtvI+AMBmE1TNgTsyx1E9DZU1kTRzaUSA3eY+Bx0Aa20AYSoONRaJBt+dJ23wZ70uxordDyJyP2pzxu0o3N75PwnKUKI3s2W/8sJUqiitekTwKTH2GEQPJpLSLSO5R6PR9FywyRYzLZY4jLpJomswLUK7pDTYtXR7AMYNcJwhh8AnFrOAWBHsZhVE2juJOLenHrFeMKzdCW6hz9H/GhXvYDOdmBiQBWuwmc/hEz+ORI3ZRpSgH2MVRMXZ/nk0oVMkJOLWwy0J3EXHY5BYwmQVutxEkP72csJx/NJCfbPS/947WUJuzHYMfKKxhqjj+0BZDeTjwwgAXswb69ZYxua7VIGk9I+DhZzRBH/DAE8lcllPtV8LUalL7vgruqdaiyq6zhO0EKmb80spkoAYx7i1j1ijjgOwWk/ZJy7NCbfn6Xt4k6hfbHRZUp4tgelO5MvSpIPgSI+5Fs75K+9bHhX3m0XseX62rF+749T6bbgQB2Al53zyXakf+GVjVdBS8+q2PZMEkzeM5yxYTyHstrZkVdsDtignPpetMgRB6jKXdCET1vMaI8lII2O2KZ/uTKZOMml2K4oW5L2XzpfO0XZ5wmOezP7INXt+fII8xYluoaH4MkVlNoK9V30Ny9itDSIRO1gt7axtesLuWGvtTDwOAqbJ7TXjEwIj9llyxe7V7YfTiJeIHPNEdpNCWlFpG2UQsnUMwbX9m9XfqmQQWhiqr9vWv3WNvd2V9xvJmfKuuJTzmUXa5YyqH28D4vqd/H5ERDC429qUgl5rz8Pli+tbaitzbYjkqJCCOGurNqFzzt50fzhlNi7K0Vu9p5Qn6no/5OvVXRGTGJakvKV7c0UXpatkKpd9K5rpWM6Fo6x4wXBJb9OSSyhRXpd5wxnzTuD/Q/ABvG1FdKhkQBMF/43v5GSuXw0l/JApPitcrigwKUv8jt1qXwbfeytJ16/Wqj4sE8XbnbZrsNmKVQfG4y6VMDYlcDxQqwqTPPaG4eg6Y7+E+ck8C9uS7fyAUxoQgPSUxbrGgcomEYcpl8/jUMgpgp7ep70YXTukr9uD+fEH3DAqVPuU57W+//Wg9ROBNWFd9auSLKhJpa5MNEHIXcaGCU9AqziyIK35fYAxPCSsxT5zqXJZnTSzifbvt/5zxyKSGoo8kxI80docaevEdm7XkiasgkuNgkBnyQgX1Vb6iKv7dPAwVWfl0A0actUzKy1FSj3SthIE7u4P4hIjB4oE4S9wjdtJ0pCKdZjAwJG5qTHPSRTd6NRBC//D7QGwPJMTW/icFhp+jez8S+Q1xkuAVzvcvszLgH1G0djfjbqDcFEik84yUlMXkdOPa8WH2m5Orfg4Cd8Dw3eoDLQwNHnoJT8o5R7mysCc5PvSHmJOcjdiVBQ83hD8Qcikh47Bcq7IomdkEI3trxItuzQSCUbxJ2i0cok6m0mJ+bSkLYpw/kF4x/v6mi/f8WY77G+yndZmhNioarOWZt0XFbOfodMYxrlVYVNv5Lp7e0w3OYm2C7uIRM0yD8RkZvsXDaGiDQF+ybDVNn+jEt8nCNzDm9SyZYFz6DqQKn7NOx7KtgsSr66vmbaF6mC6vOp1mt9clFuf4IOYd+8xHP/UauNFrutjEJtaTsqYp15mFDefru2l9MMzQ1ocuefEza/f9qk+DzcpaSAyYXyLtZy7nuNKQQ2kylmCG0odm7qJcaQGKqT4BMp9Nd28zdOObmJUXVpVacGIYeTUN5+c9DfJt4XNSHhVIi9MUjbLD6K4IhyCYipqTAN4uQPiOQubo02v0N5G5jvQsvEkhvTzamB9SSV+V1Y3uvA0W85CF20/Utp1Az1s2svftGCGcxELlKDbSl6ZkjY3MRus8sYwkrmBNiJQeyBmJGQ7wz/jREkzfcV7YirSHoKVEqHyERtBch7ItXTczDxqWIM+26g93ZJ/yHfqTrfgikNWTvJLeSCbjt7dt92ONwFZwPTro4W+yCNJPZw/oWtfuedqwnxD4KjTdQbEnlcm4ft/W4nqTdCw74LSt+XjMiFEs1RKArZtHN/LFQKD5denalU8Ny7tmedT024IEGRBF5S0S2aZURU8yJEnSlCqzwSUK0qOFabJAtFoLvQlTdbE1zCiXqKC0jZ1YgQEnx1M+8aTPBCNhvTAUThc+8pYqfyNmp35HzWMfJLVgFnL2RNqoUy2ij4hKTAzyAxafWaDhvnxIXfPQs+oijyoF/MiTwnbhC5EkNnXkXrovIAcKZtGXToYdrSPwh2kR0hedbs8oih5ppo+O5sSVadal0wGXDsFZdHuO1+yO37AJWtQCo2OeO/0Z42a7kc9X1wLqCZneUjhx6wJLccKFwN7H3SO7qd7KdeRBRI9M1kaR1+I/2LRliTJoiiNW2gFZ3R/1GYwb9T/IUmAdVntiMoXvPMV6WNx9qq0zdd85+0Yc3mg13HGN117GWh1hs2x3o44dIEoGMUqLFbrEhgIuecGYEh8mYH/gWZ5ClXYR9cPHGSAUA50pL8nHVlzTFf/2zemzjCbDrQHF1MsiRZ5c9yEjufNY/BkWwdlob9aXlXLakH6jdOqABUliaGystxUThFpvswyQ8NWmBOhG8N6/R9ksNSQnbTROuhrAohJ/XHYbWlQWuhLK2vlQNl6JWax0sdE9bUUvOJT3Ia17v4Rgi79IyKjOAFEBTnZHcC4LGYHCXnVrZdxfHgfc5JN3ZspgBDu2n4Dv1BI8FFaAdW9Suk69KOWpaE90cVGfUaLLjzpZrO2VuYavkqkdMhFxUK/vhzFwvFPfDBo3+jd21qHFen8nJZfzuUxQ30dV83ogulTI9cSX2q7A1S73FiMbLLaMQ1cTM9ukGy5ZTgdLyUmf9ePyvTqK604sX4dc6oig1J9B7o6m0H/J5b/DVe8cPNpXnhOp51IjiGctV2KsfNWxaIjEIk7ez6ckMXbWMaNNMVm+2AGDcKEu1NRDC18aSOyRSChrQ9AwR6T/vtdFTQg5bOn8/b5hFNZ9PpsTIp56xr046rE7B7kZGEeojWh38BYXZ2SJFGOcrOddqjNF50YrQ2gc+93rykp4BS/jg9yuEtesgFRu4XFnbzuNbMPVAfVSsix3vELy5DFnQV6ruUNwM3rkF+6cJbPCqlQ4Gu6B9stc3rMGGyh7JSswAzoRQeXDuExwMM6ghwkBlHDlXDfpkqm4c/PMstC9HX25j3Uwu2JoyiE43fYt1BXREnZCvS8vFgLyS18XkZ9N1dDv8c7FSJdf0dOuesJcvE0yPTRxsYi56TufAY0sBsNDnqVi8lIBk1Znc73N9vxm1ZIBhbgfLezh9A0EF9IOC56kwt9IxHIZa2mIvXYmytmoVrfKtx/fMafJ751i7qrJaRUN9l8zq4FB9B7Eqw0GLaL6jcKOs0+2o1q/X2hDru+Cn4Iz0K3Oi1PBB6i4kHSTCI88oOuGy50glVtDYjlL+luCYU0Ks7GERTvcMVwnF7tGx3HPXUU9o1feGF5OYnElypvJeohbTn2N6SYJIokwNEwnkVbXup4XVxOwmhjJ+2FeYMrAgn9K3ewgyD+/m18OgSNS6svgt+PzYUROphfTO0wf15g0dLxAJS9rqPolv/qrm3i4LBSR6ceJHxZYrmCFZAnJ2gaiAIMQGMVw8J5FJoqcDbEuaYR9bzRRXH8WXXtw8bjPz5y1z1zHG1bun9tiVlt6s5O9x0bZZdAa+tPSSj7YXq8E4RCL9pv9NKetY4R7zU0ShrkgtKYcs6KIYiF1EYovscDcxuCahGta+5xrtOimpFLZ6Tb3GsU/iM7wsKo3oC/bZ80/8Xi8C83FzYj2KBr7TlYShzF3fzU8lBscrSNJgTPgo5SWMk8921l7XxsiVSpMAoM2wQYtY+CPmS9KJt6+Qk7TIZ2pjgzpQjtXF0V3j9AYaarfIjV1J0vmqT86e4CffYplOSrE3O6nQu8l7Uqbhma8y9CjWt4MH+T0EJVEKRkNiJ+AjAyh1Pf70nmSfOh5TjhVdixTulAnWQNctfzWAo9ey/eZoNmvp8Pxyu0bBwFagaay4DJZ2S5O9YmexVtI6XqZck+Kco6YvTcxyKH9pF7PS80oqtzf7+LfAxm9iFHmGZCYYfh+Ik9KwOzEZptEXrVGPspyXY7bCVk4QZN8enWH/ykrxcGT7OgWgPbxgcFdryDlrXmwVo/65yYuzsL921bHA5+lW8fmzJMLhgPm/XSNM52R6nAMn6KCIskTnHS32XxRcz1pDsQ3ATeozx9OImUJNVOKg6ignFCnP1TKTwv7rCOUtffXIyWv7wUKkhe6xysj4IGPFI9tyfn2VjoSo6BX55ifcIcA7AmgKlqw/SnpD6DYiuI9v4apym2II6WGLuGkttCo6KbLRJeqqg4m8fQrmZ8t3wVTX7pjBba8PtYqr/Uds4d1mApahgnKu7BPrAgPWRAsbLNF7Q6xYSFmkHh1GaAEOX5FWmeKcqrxaU14CyU+OJrJvU1D2ONGMvfc96p8kwCd3ZRjivGmvEK0k+MH2FXkS8Y3HZu7xlOn9xOw5IQvs0QWgRqAr5JxcUruLdaNiYjY3fOVby2JtZEDmBtjmBplI8JhLU8as6f4qi39+24J4ZVP+VCeSVtu9iNy9KXJbC48V8Eii2Fdj5y096QxGO+3OCOorpZGtzQy+Y4O/SAjqdShbJP1AgpCs75gPqBqivx0LzKoeQXT28XJdjNUG7HUzyBITkz/wEGCzOZ/bgH83HYuV4zyY6KDZbElc7vmnsOYqwUNG4dGAuXruz7Lrzo/Is+xrBY7ktPeLMohNCrUozioyie6NhGoXq9KUsucZ1wRpTzaqeN0DJf5ErII3gzhCmtB7n9kbaRBj6e6CRURpL9VF3jwV71M/XZAfCOVkA6ebYoted+7wuIbjvoWqJZNoaJmjIXoP3/kKRki3l9kFzQxeSoqwNcsZZEtOqo1ZYx2x3GvXBtlMaJNqNf7jW5QeuihB7gZIXbdvZif3MbFxVgZm1g1znAaO1EAbiF/vzqT1De08yQvHt5lRcKch5LT9CjHm2o11+0eu5LLF+MVWYNt9Bj9+TxNgmBAAyba8wrT7XuGILAwOTkshWITvq5ybPnEAkn6W6GVsFuegwHGvBJKibI7YTPOkRWiZddDTC/US3c56YqxgNCa/ChBkeV81irk8trPaGYMuw/XV4kKT/AOnu5z+8HDH0ttHdS+oljB+e++qtAXF95NhlirY59lsRJZL54SOra+INIR+9ji3NwYGSbkBI+uZ2FXe2OyHt1on5fBAU6D4E5rWe39OoZVhB1NCoqs1HqMvOWdH4j5UVs19ct1YxVh0gXB67kjNduXtbLcBw8iU3Nko2Q+Bp1se31qDKwxCshInuHXYHdKRb9mPiauKGNWJnyGeYPHHAqDOJnSo1XiDWEuX/OjMl3o4GbzaAk9J/S8usOfoor4OwEfS9NEjnAajRVy04/FZXVS9Lio88ca4k1Kh45cvD0ntt6pD9Os+yNk02E0AEGSfVH6b41Snl/eiAjuP0le0aNSfG6B09lbD3tbLQiuxQRbRbmsOYtsgzXT+8CPfsNq3khadok+WEY/cCK/SlDBugsnY1j6Y1qpHsP3gSex2iRF5o1gnuyiSTfjnXIoR0QMnC+QjQ+//lOBxvwdGKz/pwXIOcclFeKLySHv3mEvJoLByG7cKO+G26YV2vL5Bd3/EzYayeW/6UpG6D8NGtEjnpmjYFgqF4DUqcIGaQlDIXxRhM9TVfpq+kRz2jsoClmpOgz1bo3v3yoEd3v5KyyGHV+ToiIbZzJp67g8fDUPkj1HxvdlFVEorCikZQEYlpR1y88lz854Ny0rgZbe//LNj/CAZeseo2djnciRWS/9efXpnJfUJVx2b5TjOldK5yOzdFxWbASSULmS7dmP5+cRxMsbDECjOCmZYrIeYhXhkD+z2CKQYNg5BI5JK9GDmy3/zV0oyKxTzmd4ciKH3HgfS/f58PPI85GrufzxTgdVUzChfBYFMEuLu++KM2Ef82yFsPq1EyiBXNwthvsaWyK1xuT3IG0isYupNvZyfIJJWC8mhoeEaiqasgXw1JgON71Ey6iMosqPdhMFYrA/dXvaRITGdonO33W2gNhh9DJ9F6ukLS47wzYCbdKY/G5Hvd6PRhnSjD0JsZMVauI8rajwu2RqiPMIiToyjJZW1EC9UvE6OsqNWPwdOP37eJZ2dvqQo0u6JpFqPGNcXh4pfQJN6s7ridlB6KHGMWJ4WRtypHK6Obqmsbgwx7PQKWSp2DUhWb+p8Cz638EnVzk+YkrnZzkaKhGdARom3qeM1HC2sCT2cdbQVFXSWMzOUfNkk613K1GwmVbpbdlPjrr5/GoPdV8EKSvBIBuaS0lxrbSYElUTxK+ag39TiZBZa5sYz7ONKfHuuIXfdnBvLMl/OEnb1B58RbheD+DIhUPo/kag8iSG29p8cn81FyAxVhlobSnH1nIYq6gWt5VOCsUSUbjNODPFYmV2LAPR8cFDosGymCU6QLDEiVaHn1hDao0qWZ3NoIGv48FdviPQp7YY+TRNwloJNwdJRMipvaQ/8G28qgvSyUI1Kbi/L0eGgb+BHTg5otFwQI0Ruf4/Gv1hfV2w0PAWV6Zp2+n42AOWeII/XFogtphaTK8CIfpVkE32wtUoaX/u+R68pYZ2chgsTWTokqe1YjsHjyvkfdsgt1Gv7OzSN9QX4NTN+NizoqVyR09QQsBSb2CNbVeb+kKN3GryQ7xYGXeXn4sNOS/NiVH6+PITd+uVhraFs5K3nS7xG/XH7G7XAtVjW4BTs0P4iOfhkFNU+G9CsQ8HUaSMAiw+y56V5y/DJRSnJEYZT6bMRft94uXwfNZY4k6ctzwqt3Da+FZ0bhPmzqkGUfVmEy7gWDZijKX141i7C/Rmih72vDSukuke9SQGyfRkD2lNnIrRCCEuC3HuvSogjzgf1RdpPaBwpZiggzJrR9bFG1+nD8B9Zi2iNNfrIXHdX9WmCYxBrkH7r7ODS06M5Iu1wBiR3A5QwMfsYyulTNc5MF4y3nb1IGezVJ24ZYm57hyJDNfy5ofnr/7GISZ4lNGdfLYnI4euYGly4mIiBVugVYo/O01OdwGX/0g8iGOdPHgLGe2uKrmn4b6+FLjAJV4jo8awgmraFfbrLG5NWrI72ulnrOaJ5+LjOxCHEJqqsa86bLmH4cBELTucr8AyN16CFmY+XLxM364oyiXhiiKr6jZZebbDXXqVUNxNQqxFRCuneTHqYUFSPC0b4VjUKRn9sKySumQVp51Rd8Yi9585r4SpkEHJ70V75P/Li/CTEeV9QTQOqs/C0fZrZdSXDP2EP/X0oiweCIDyc1DVaJuB6QGhKUvi/5vhNrH+QlG+wbpPPqI/rr949r7pZhcdgTNe72qpd4KUjOhQgcw8pBsHDIlkQ5+ns4d4/9cWR1AOa7XflKQS8yhYFWukeybQFJkM5tqxjfcSeLoduyHK5LUYR6B1avVc1omo2Syacko49BeXGiQ7uSZdD4P9NxLCIwsiAo9OfhwBnb+fuxvX4OksFVNQaTCiGl7/geOtcdtEuVXv71cZG4p2ggb22htzcbUhN9MdIBHiPZu6luMXlKisatGs0NJ0bT2OcY4nCUWhiSLMg7udS8syG9mleuLrxsTqoRDAhESc/HnKKB+eFzxsxYOApxi1TVy3oRSGT8SvQDqBTLOGj1IPOFDtwG4fM2xnFPKMNvkA0nqVHnz2SSRwI7BD3JbZvC3ZLA+UjSgJteWHPNnrAFynRhlmzx4Rb3CRf3tK5LlndXvW8CKjQ1cf0vOnd2hW+q0AHhNX8eKV+iJppgJIxLV8J9vbLyjPCAWIvzwwjitYRLGfmPFOpCzrsFXbVvjl2M+67Pfa8EZF+gophBS7tW/aHXIaqACRZl1L3PmtPXkutxhhbomaTPH8EgYyJPVvB/lv5BU4iVLIq5iNBhZL9xXUbRWEWz/yodA0NUck57oFZfsVuBVTeQMDvCs0OvbPedRT0gtN/LTE/bFAe4eQ2pCJLvE1A7QfWh3ARrJmpdf/9MULYczPPeZ3Hp4/MKDPoQ93Lrdqo8QNstaaupZnPjlvmj4vnqTMGQMNo9LOJYPGIDaKqFyvhvBre8D8q0fSFmipCQGNpegRTxIBp6fliEUHOeONKHS7Fx1NykYdPmW06oeTJaMWnuPLxBgZ3QXx6w6vXjxCsDNkGUQ3dQ6h+d3jqPSZiofncJvrRcdMUc2rnfeyhDlE5AXjOfu0FVGyzc9s49CZdQtTB6HqzkoT8bBxIYaPuv/pM7b/839w2JD84iaBw65s8k9oQRjcpilnjm+oijMK+mDXX18XIin66qRUC2TgiE19xSh+1AXWqNNS4HzDf9sN78XKys8yFiF0CmG8H+raANlExUVHgg4ipO9yQ8vFvKOqvnpIdLPUU9y9ZfymplFqx80WsLborNfQ+YmRwEEnD2dpnqKqxbTs6SmZU+pvtL/j+y3l0KixfRgurYT/fi5bydnHyDuKTTST41jqSwI5/AeHu7pOlvFdz+7Il7I/x7La/879k7cFRE9nAWjmtceYBu5gT7iqTB8TG5VTxssP8oKWHm4QU4gSvsqFn6X9ol9CfF/3HO4WBVOzVOtEvCqF/CAYpMd4A9r7yNFIaCY0lcdmFyo77dIGf47ikWaPwhLobNYs5AJTRWPbe0jEUDK6VU9cOeQqoJmQxsKl4Lk+tZj9rL3ClpSbVGtJN651lsskGqY7ylPEj9XbLLBnJbTHfw8SFpnnjtFIS9grKiqF/PLb8W1u9+gPyAAsdOVSlzv2utrMPMRDWvOB2ePY9r8yLO0HOaIrsasCU35F33zHCCed4nRl9dl6Jyno6taH0J9aatX3aZdpWO7hI6Lk1zuGfUUCZr7N1wMkD3WHpzxEtyevVFo7S9E3F/75zsE1P73EtOLMeg5EXiiY0+atgDAOf+qE1UgAItxFjUzW5r7YzxAoc34OGuqw8wD9CtnGKVqnyv9rtiSmfE0eItkNbXB7ZSTKhYmMk6QtlxeLnk2410gyjNKiY+IXkUYIojpmk9zCwCgdDq72XIjQGLM0k0c9TqapYWu97UX5zKXYrrfzZLioZIi5l3GhI8XZzaURh3d+FPaTNtZsYDv5/4Skq9s1INqJZ6f0YC2ropetvZE6KWVJA3GgYh4L/+4BNACnyhcRCdeIYQd5EgbqwQedAwCLZIj+LWxE69MwS8oPwIVStqIyDQq4XhkGRUEeoSB6hKO5cgYJmY/K7k1K9Eli3nAeyhto2DyNC35CrJlp3D+eC+cDqxtWXUmilloIwi4jAkCvsdC0DhMNHfqCsq8QLEFvFIzTAj9Hb/VE1jSVPDalrPhyaUB73bD0WEfipgnnBQtRbqCsF8ZI1nobmIUm6vLrJIsSTIaLNOzZMKPdJGeeIxzOZz8EDoWWs6TW+6L8Mr2gwImyfP/oURT99gev6CsZuwJHtoOAiBmHt2tEuCBvRbdqAXOYNH4Ieyqcecr2GqiDcFe7P5SVrzLFOeXUUgCAv77L7QGLT4GYyXDOq+2QdAyI3z2CiefUK2j3VB2MEvEU4zNhbzwWITcAKFvTxzzlkwZjYLWymI3T2hLvhS7lhWfKk3kdsdvrb9AknyudPBW67MITBvR0XasXRTKaVA9ohkEPQ/83D005AX/jJyRGd60EMDZBgeKMRhybzXBE57EcOH2R7bMOWxgJad3GKNtrSqEuuVUzAo6UvaI8WhDSdgGjtB1kokByLFeL1zOpufVM11sKN+wpu33vCk4R+nYfDkgcRxmFbkKgx9BVW9U3ImCurxbpU3TvVNFy+3+MW/3K0vkb9YT9sVlIBZ0hCCstSTXEfZMsu2VAje4bn5m3S0MOMMYuEnpmKLB/tWtcjfoMUrZWxpkLa6WY6MjHvnvPZLmOUvcJPnmxFuWqWsfGRNramJb7zddkKdOsyewdWKpQ+LNQ9irqJ62ZB1th51Nj9J1CH8fLUBI1bFgVdZZD5kfyxlO/co8pBw3ts0t3tJXgPGPDU9LbiQcfFJDpi8t487N3Y5UQ0ozxRfl7fxVO6HM+u9zQbQgTRzQGWUw5j1j7I+mnorHhViRLuHRERM8eNscsz1meSnqKPKw4PRNbkKEW4aFHBGMXdg5ckAP7bOZdWGmWvbCuQFHnyBCLkPdzVlsA5IzatbQYdtNEhX6rn+ihMsOh6446ci7Edbf/9rLTONGaRxQlP8KMqWK6uQqEG6YON7QgHJ9leXgJ0/csA29H4XOHnhIz0SsBw97UdtIv397n7ECghAuhR6h+qc8/NYoZNsNxZBttz/664VhZYpshPHGnYzOE7DDyF6gDxPCTRWl5eknhx/wHVnhtPiNeuLNnGyzLhjHim5mxq8Dh8SSy1R2jiVIEDSId8VgedMpQMnzCewSoRvEl0RikU6F+p+VlxtR5RtrpWfmXUwyHxA7i5Kr+jwIH4QxRq8UDWTDvebH1OX9eXyfg8+MMHaL5r4VIwSPbI2t3FqcegegxZohAZqGorcdInArqCAvuAw+rlaUAmLqULrsdiFenK5V0VVX3Tmbbpw1lgImD7SLu08ReRmsddRXvkJyjKrI6F8oIAjg8xkiX9gW5T6GMAYY2DMP9oMsEmkCO/L3pLFmQFAcIEdtExGjEQ/tQJAhKPofcPQPt688mAV8jq9iMrx5b/sD/j9Xlwt303myKidae7Bs2IZIAMaN6UJX7/XxC5rcAHNOOnHKcx3vF6eiK65v2Ka/pQZRQfBfRe3SUQuQFaiThZ06C+rL/+0tbeo6RludCHcEx7nfzU4q7ERlRg4vbXCYV4Hhwum+6Yt4myF+MdFEwCjNEG3Ul5+X9kLHPQi3tLExl3QSxqA8to2dGEc4twMDzg/9CxKN9BJL8pITgVFkKRSrG7HwwuB1FDG15c7+yr2m8n6ReGPZXxBz+XDQQQvkLZD6VRt0dqdNeq3UGVvTdo+B9JeXjMeMXepy9Zq6D9V8gPkVuArSHdIVOabHzQeUyhcBbBE98kcA5wltS+koNPysb4KIsQManNa1hub0fqTI0r6A1eO9ShuOl8vFHHsy+/TQu+guuLbKzoj6hD8vulijoUCqEMNtd8SnUee2uFscJNKB07hH9OKpPQGS7ZsSmVW15U8Ozc8oVGzzqluIFo2mBpxaCZU560PIwX8EWyNFD3hbhnVeHXa5ZjezTxGJ/2CczWGS7zb/gSn4vCjHubA/IuT+hEBhL+abFOOBiUg9dzWiyDmWJNjhivpGFPi9EDbwB4xe4/1PA3aM98cRbXqXHZKwfPrTd1bjfDtPR+HuVhbJ32tv8/gKYx0Admquu9IiP1L+gzJA8vju/kHVYdkZ9ASmS22fKvK7U/jDwOh+AWWJjXkT7vNOGggiSjxw4dH4GexgUOACVRNz+UurAD/ttc5CgJJTM0oiNIK9jZ3LOq52dwMnYcdl6eBsaOdhyDbWE/zijBv5rpqP6n+9ksJmRH8NmEZQRGt5o146oo3XLPju+aGHoEiKro0AkdznKrPV7UNZJDqFo8sgQ5Lx+bWP/lxkyu/tSPhMNTGtIxHm3DMxkdTs/vSs8VsVPxdlBVMJC9dqiv0mBG8tkZtGCEPHrLuupyu0DRdrktRKWw2iymvn/Y2OfbTFsFH5BSPQ/xBLXvuWqkpvOYYjhk7ftoTZ5iQ+3rW1OUr/rgmvol9QvR/njyH8Kl6WXMEdEGSr5x6KbKffR45fG8RkXWf2Q1iIcm8x9a0e4dd7oJyHeK5+Q9vf/2O0xDWzDYmSFGjtzlAK6jDfFqFsVx4LGdbRYGlzuZOApNBdKYsJcqyLSlKH0j7rCaFDdY36TasFXIGx7ounOKzhw+aUssq3fPIfBlmUtLIKb+ypU/5YrqESfwJyR6WQeh8t2hLSyxbmg0b94iCosr2SKWd25SIF48CXuU7fOkKzxrqkvsPc8ff/EPd4fgzw/UmnSIrvTXW927H8DCmVjVuATMGAHPo0yciEz99nTOJFdJvaknPEi5MltPrX7fThK6ZCWGXs4o/JVKDKTrMGnp1B312ESnUwihqGp6YreRzlBw8tLv6Rrzx4GsWi2hueL1I0jmzQBHKwAway4wejex5HeOlrxFrH+WBixJ0lvjRoRI4HFc2106wZeT6cR6T0/vcfPeQ9ypRnbseYRNGhXvdfz6OlpHd2ztKqHfyV1lnZAtQHEMt2kq/bYLqEv1Qv7wBrgAcHSQQlHKaGXpkBBFqu8Yfwy9dHJZ5WSESsl58H73CSlVUh+2qHG2/rqU9+9G54biQhxRx3c1ue65fFZBvMZ1JgzVhFPjA3euiOVQO50Co20chNPNTAo0SU1sEooheG/X9EzgBR7rQ4n5dqlXL21+9HixL//tMpx5EkIsAwJMYtxQH02H9CfrxCRqgeBUnxfh1bObUZCfJM8Vtr4v7ybHN8rob8i4QSQ8I0TxXD08KPV/4HXSGbbs4qipr9d9RVk7PhWk9CFTAR3X5hkqaT6Nbgu8jDgGIGOAOpEMGFcPpIkrUOAXGSRDwJPeLxhTW+DEUytrvJMOCNlzCB7hZO2hcILLpBdOZWpXXyGFAmMcgXOEgty4kOD8unPYWxX2FuHufccFafUblfGjdJlp1k7B4Z8eL7qHqUP+ZJBNSCXJH+NUXgjaF3tqBSVaYPnCog9qHAmfZNsfhlweYGidamB5DojJuQix9OtxhYRTrFKIgx70GPsKp0GcR3QuMgeGq0RkRG3Jn97NfCS+liyh3ffrJ+3XJJrxXBETbcQmkYsVJvduNvhXcgxmIa09VW/j0wap7gbRcCRQCg1qsLIu8ABxnXXr/clMC2lEPuC2waA+XN4DCX2NZ8qrjHvjnPLPD+VWmPUakVRkDgV9hQJbEP8cenijZ5YNpvWrR9er5UV8Zp8xzCvVqbdmeljA3v8Yy4p4TlQ7HIUuXQPsK8SnRjZOsAgbY+cCUBzlAFTwdLgBmEA16vGYT87TIbhYsgcy5FxceUNitynk8DCyQEy4WmmIyRcg+afrzlluEBefHIhj8Uul+aHqhbX1GyVZRoPzC6n7oKafcyZBo4P+cHJOrLp80IidJN0DcpoXP8rHAEFR7UD3HBmJs2g8Bo4YbzYKwcZd83y1UgekDaBgx893iuD7nLa/Hz/gBoZ26hiYuVAkNJ41xUdWUKq3Rpz5ST0WNK/Pfo0qxSTCWboFjqRMhF/HwKQ3jphpZ2A/t882pQj+VG2MOr/k2ubZbMMCuK1X77NB6Vz72zKtWk8Lxem16nncclqTvZh2ynWTZEOx/9b4NbTijcRcQ8yYq9mwCJrN9d/hH8UAyn5jpNgfCwyE49JlhW1YY4RR9L3aDfNcTdJNo01NIHvlCm1ZXXXkEJLKOu8lkLnWziBTOjNZ7d5MF+d1B6iV/SaLaH03ZRsquLxYs4oGi6aiAosTnx71OxWrFN7T3t28kQbQzaQUydMpPnBf2bhXxnUgxRWcW5xtJs4+BCdDe+ktZG/9OlbQmlAP/nId6UMkwI3bGoG5zKnzFKSzXDyJfRQtOM/7r74wRARovfOJlswbqp95g0Uefqvz+zQIwibcxmMtW+kRzXfHXpK4pn3TqdhDvWroAxay+pRls/xTGOYu8Y/tOoMiRd6hzL1QLPfnbcTeH11FwcSaNQjxWqV4xLdB1wZfvcQhPCXVfv7F56qZtI0b6oEHVHFwVwkID4juJV4X25croiiXVVNT7aIXJtWmXyAIB/Fhw9yYhafBZEyrDlJQouVCUJkKWeKHM2TcDUxKmdPpckktyCxHn55DIkwjG2/XpC9FEgJZOKdzORitftEmVcni/gDzFsN0vJ2W5O9Hq6UYT0Ztg/y8VkSmPBcEoiIeK/3NtkDOMLgfcXqs/f/MFfb2e9kczr9L46wLCfgt2KJJxvA87CCxdiNwcVsfbmFUaAc5ySO9dhm8lY1Ug27gBikpacpfMUiX3YteDNs24G58j66d4HW1+5hC3Ee4LP0EuKlSCgwghsLom3FI8TNhpkkUNi1if/BwTqce3aWmIqfKzpdPHRTrz3hgBkdQQ3d2CdNk+Yn+ohlc+otdIAgRRStGER+C7E+2JFv2RamwDiOqfEDiBzOxybVv2gjxv38YgBEQhU19eyEJXhkEGpBDGf3X6a9tGd6e/ZAoJjEj4Fb5rutl90WrNrdhkh3HbNsCBy5/+9tG8IJuuhceoxlBVNQnafELZDE2G30IUNCpbDgXeRgrCW9ojO8h1DepelRW4jT2yKhSMyjrFOVMclt+ff6BrOP4ESLiuRkbhlS1dpwKS++K86clNaXG18O331shOlW+yc4/gogkA7fQPm1l65zAjWokeJN6dy3Bt52gA5rDFmC/RRILhQfmNlqiLLzU1iMExPXsBnxroy2YButVrvpbtLKIZTjYd8mRIjBjbjuoFlihaVYga4CXOge59VSXo6GtweQ1tgktoltq7aMVLO6LEwdqVXbdw9GvTXr9mrUz7wfswKf6hH5cVf0shRoz7s962b7Z8Ilh/yUFzlfvCFf4D9F3FsMTi7Z2VCLz7rvSkLX/+BxmRyS2mc+fG9zZwbdeJGUc+HtVkkd24ppaxgoymAdOO47T764kkPk9CTHrfVEvJNtbHeVDKGoJwVdq0T2cZOKKl4XOGPF5FZqXx/+6e0W419a4iIXmEN6LiLf4cAUM3QKZW5kc3RyZWFtCmVuZG9iago3NiAwIG9iago8PAovTGVuZ3RoMSAxNjQwCi9MZW5ndGgyIDg5ODcKL0xlbmd0aDMgMAovTGVuZ3RoIDEwMDYzICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajbcFVJvbEjaMFLfiXoK7u3uR4u4lkABBEggBghV3d3coLa7Fi2uhFHcrUqACFCm0tHz0nHPPOff+/1rft7JW8j4zz8ye2Xue/a6wMuoZ8iqCYHbgxzAogleQT0AKoKxtICgEEBAQ5hMQEMJlZTWCIFzBf5lxWU3AcE8IDCr1L4IyHAxE3NtUgIh7njYMCtD0cgUICgMExaQExaUEBABCAgKS/yHC4FIAFaA3BATQ5gNowqBgT1xWZZi7Lxzi6IS4X+Y/jwAOe06AoKSkOM8f4QBFNzAcYg+EArSBCCew2/2K9kBXgCHMHgJG+P5XCg4ZJwTCXYqf38fHhw/o5skHgzvKcfIAfCAIJ4AB2BMM9waDAL8bBugA3cB/dsaHywowcoJ4/mk3hDkgfIBwMODe4AqxB0M97yO8oCAwHHC/OMBQQwug6w6G/knW+pPAA/hrbwCCfIJ/p/sr+nciCPSPYKC9PczNHQj1hUAdAQ4QVzBA97EWHwKJ4AEAoaDfRKCrJ+w+HugNhLgC7e4Jf1QOBDxW1AcA7xv8qz1PezjEHeHJ5wlx/d0i/+8097usCgUpw9zcwFCEJ+7v+lQgcLD9/bb78v95si5QmA/U/y/gAIGCHH43AfJy5zeGQjy8wBoqf1HuTbj/2BzBCICogICAuKQIAOwBACPtnfh/pzfydQf/4RT8bb7vINDfHeYOcLhvAhwIcQDf/+D6ewK9wQAE3Asc6P9vx38jXEFBAAhijwDYgR0hUNx/st+bwQ5/4vvDh0OQAEuB+9kTBAj8/vz9ZH0/XiAY1NX3H/of58uvp6yhaKDC/WfHf/uUlGBIgD+vsAiAV0hUECApIQEQFxUABP53Fj0g5K8qBP4J1YA6wACSfxZ7v0v/Kdj7r/Pn+EsbnID/zqUDux9aMIDjnxm3EhAVsL//Evx/nvQ/Qv7/Bvx3lv/bjP9vQY+9XF3/cHP84f//uIFuEFffvwj3M+uFuJ9/bdi9CqD/SzUF/6lZbTAI4uX2v14NBPBeB4pQR9e/txHi+RiCBIP0IAh7pz+H5U+78W+RuUKgYD2YJ+T3rQLgFRQQ+B/fvbLsXe5vDs/7ifzDBb4Xzn8vqQq1h4F+K0xIVAwAhMOBvrgC94MkJCoK8Be8lyIIjPxjhgH8fFAY4j4EcN9eIMABBsf9faLiggB+td+mP5EEgF/nbyQhBuA3+RtJigP4gf+ge6bd30hEBMB/L3a3f/yC97PKD/6HIArgd/J1d7q/Sv5h3Nsg/4L3GV3/BSUB/G7/wHvJ8MP+SXfvvL9R/+W+LwD+NxS9R5736vkbCwD4ET6wf9Hve/H6F7xf2vuf5PfIDwz/k/5fm23vBYffXzd/yOH+JP6D/7jbwGAk2B53ZRFmLx3u3BTefd2gSOvDu/9Wdo513zSbk9d/Bd7j9Z0QK4OzPj90C36lmDE+8HB9V5XjUmGV4af/x44WrKjONP2uHwG3T1MMZva7cJffUYxMl39UbB6mx6HjNVI4CPjpEWAS4oLegdqryVrs4SVBqFdKeu0zpIZsHq5am4xc3Nc/qBd7gndbNcubYBxvFVI5z1piV7BAxYSJ4KXH5iI5RRLNX17NkRRN3zFopnDjBn5KEK7wt9gWSrxZ8NuoMRLy7KNmobagoke/JJmcYfNXOszUpFzyf1GxBZ/MWqDomdpxSxd0PeTw29cxuIYffbVhY52W4qCm4kcn04iL3+pUT3WrZEzFFCk4XdfcQmp8Fe+w8+TRTYXc6bqKN4sa4Enu938vavY7xOIgbzLjijJwIs9oZoAOikbRoxY1sxFGl+07jt4mUG5ajdpvTGyQtbZLEtqq0nf0BL93zG/yCTnaMGIcX0eOacyfafrNRnsf7XK5kp1e2OfBRnoPpjxBbtQ2qBmsra2hsocNnRlFKnjctHEUzQX0XleSHbQYNAnMGfm5xR3CrXp4o0+tm/Y/4nHm1R92DfvgXkcPH++SVRlX3SnW1xZL5BOX46hjJSXetKFF7Ux5Uai925FS2SSJ2tGMTvzFEVl6blo7cD71+vzEuoxXQIavytFQiQhfxzWd1KJQN1nrZK4kUZTWRrJlkOyXVOWTTi6MgC+PcUPD7/wHYwCrUcFVi6o8W9SFPzy60SjlepwFbLKQHzOb9Id/sZsNHn0OOoqI6YZQ449LU/tajOtdItof7JaiUcjdNS6vu394JBhiaNKAGpg0KvW8b7MKeA4ScBpa8g8KknHDXBDy+TxZlPk9kjzCUXTkGXpo5tgJCu5NGB2tpFqoU3D8s+nP5/OcMsKGM1QEEaDeajTNQZRFSq1HHlxxl72stBG7Mj7sgsWeIec2OireZa/iCx/m86kNtRhCu5EWJ1/KUyn85vJ+8BUYxqVpXzBwRq7JjLfFf/H+qTfnFMwsI6jBrPt033OjvGto7PE3R6+Gwd3PFHbbzmvcCMzI67u01JLTHwRFbnrVnEj277tJbEJi/rbuDotORDGU36ZvH2IlQB78dDyj166eturSwao5Jzx71ChvkvtilhI5m2cG/mJP6w55PvEEvz+H6ChLfH1AXj+bjSJPBG3IYmieM+tXOTdNjJv+EDuppNjOsoY4ZilQYp9dJR9thonBTKDsbKI994b7eBq0Ya10lEk2SyA/mupYCfR9daL4vGnGZq+tyhYz6VKSIleU7wiSwR0W/1oTA1mPL9VfdrA+fWIeaPBh2nF0X/JZ/bsjxJGr8XdyP8Yqa/YouPwPeS4Hhq3rgOSFqxmOUtULtf6RXgWMLnxiqEveM79D8OfV2OEy3Su5wc1dzcL4ZsUizsK32dVRlkM4mF01ZLn0xjGDsj8xfE8SqEQvyd3TT9sNioy/tX8lZRsV6O58QZocyp7Ju533skmCNGMGoXGniOSaLGPZYVx3ZDBAp1IPNkShq5Y26DdB+Wy8HfxJntH1eYL2Ss2MkCOp7uEaH1mE0ZB4GtX3Vz7TaUGc8h3oFcrYW8WZJnZk4jbvXfIKX15qStfYE+Dq9KVznROsJKjR9T0v314JyEudH3wUbVx+Zz9Vt1V6SDj+wnU+aCdNbNYpVwzDEkdoZav1XVHyIwaLbW/ji9z3rt16AaycJqPthG6nnUvVBfQkJLJs3UDcDzUUF5qJg57Z4U/pyyabUnMwfBODVmgC/A1CSxPEhloKJ7KUspLEnTW+0WCFUEYFj2ULZdH8bAaSxdxWsuLfZSuIi+Ap3KGQH4twpNJ188mifgFMMdgWzjqxu9fM7nIjM7ynzAIjm+TjJonVFoWJVeilskJtXiW1lswVJXOxdYicuS/D3yMTbndEweiPipNsnIjyXBTODJ9OJu4zKLva2GBOBq6+4vWQVOic2QLfbeIoNHb9eo5V3BYQ66MdC0+zJ5Pc0iPn2CuUcZHowqqXzqgSH1XnTytrE8kyWFWn6hJ9XTsXjLm4b9xKvsTzmC5gims9LD4cnbQmFsiw7x5DSBWmY4j/zpKRrRaDNJluf5glKGDhmxsrmpxRz7RLww72EdwrosFcQRsa2+b11tSWVZ6GSF+C/sJHTdiRPviXdDceqAKzfd11AoYzRdMh9BM/zXjn/NKrT+x9tvJiHCvNsLnRJbvBRfwojfMsShFsUZBeuwoaqPUriRvlNE1K91cr/6TtN4WwD3NFc4n75Cjk4yLtiS3VmriE4Ur4cZNjLNXmwIUGdXIcxZQgRwEKDf106nOZTWnMrB/eATKfxbDm1Vb2FBAJHmaR8XI740nuGpS1rA0cj8wuvDMmDsQDBVskUV2rFeufrNYFozKIVRBjZ2Zap/U/5M79vt3omnLxVIz8nD2T+uM74XVbFy4j/FccdS+tCweJxEQNlnkt+zlUaz8pajIKe0phgLkUS4/XyybxMSx+VY2perbozMS7tdi/qzrj41u7kcOPGoie+5ovp98bxdZBmzmKrNv/ONnhB80m7I2OdFF+0eDgYcq7kvEzTMwjBobFle3OzXfl6OxqUQx/5ISgTXorLywlVIFYOVvxZaN9nMPoI3PlwXBC+Lmh6zGf9hyhP9XLHelcRQHod7vUOnnvIVJznbfcmlkju/Wkw2JsxSyf8n4ky+D5khwzuxN9m25Ah9KEXTg38BntZeChXEZRHbJVE0dJ7M8X+TUOF6jBoiX7JueZbChrb4INHpaTIqMCLBhthole+6gClxwaZ7+Mt0Hc7vITRERo+e3qdO4+sdPkXKE/WRsQ3u8hPvt61BhSres0rak4mpPb3C1nU0ki6V00l+zLRYvFruGGaJ+rkwLpMJ9khZala83RHgANkMWDjBG3IMYeAzzU9Lyg6NxWrrNizJDePcmDYkrDumEVEKnL8iBNqh1Lw3eTs9HIKhtEpkigkyg4ZVNdJxo+pF6rUcGj24Ylxr5dQb0zTexa2swQmYcbfhepo3tMtcqMBKLgTOgaFWKb7PN2cbQxara2Wbz2NdvC6XnBaF3vt7SusMT3KvjlDTm+6OcYlGnepDQVrRbRp/AV9f2jWg/H0Mp6/kfwD5WhDw8dp+r1WNPikIAa0HFvZh+yeF7xp/3H4eyJzumS0ltz0AZHOJdU4TUsAWQbXVqqqP1dzy48PpIXWp4SdVSPeJBqzdxaETPi6sg2Pgd+kVVLdJhpJwoineHSVcURTSZoNDZy+k694erdK9lF+5QT9WaeepLFXTkvd+Qj/UPuSY527USche5VvR8mcam67iUTowh7ZdvOheL3AnmJQ03BdRKiNeaKHMPsR6nRgpq5eJz4NPWk6XOyE1B5VffExB2gB3FprFX9zTE755unIiv0rwOfmJfUc7eCFuVs7DdN4sRGSARULUYQPGM/yUipOWsgV+jgIIAuQ3PtXJEolPg5LURCSfQX18FIeBZyG9qjwNCv+gNNRe9OrrMYzEKmcbn2yaYdutIHxDOvkiO/Lil1Yd6u85Hvdx/cabmbShv8uYNoLaCgX+tjfCoI6J4bAsGb/CtuQfipuzxpswpfrbmXX6X0xCqvEfl1XEKJ/R8cCRh8Mq7rfXIWT8fDthCyekTL0GBFM1KbvL73rlRQS6mhepqEWXOvCbX1tO/81+BZO707JaUA+RSADOWtWYQmCXHKE3ELLRUmYFnGhcOBhuALOvl5Z8Qg+7iEFD9HvEahWknRKhYmykSrWOzoA+qobAKZMO6SppfwK8B1PrJw2TnkjWx0S1B9l2Tvvt+gxmvGB89HXsGJwWo6vWY67ooxmSKYxp7WdtKOKaiPEni1pD7Ef+Mnr1mtm3QnBS5nYhNJ7b4TRN6Mpn8d27NNwTTpyzhjU1VFKwqRf2X/kIpw8ZoMX3ktazRHXLyJ13Z0heVBfa229xbWMf0xRUBzBJvnUPxb/DoxM8YhR2YoaDrKMs2HeC88BMoRDlpJzILNwxi+VT6N+JQOEyLcldnoqsJBi26kGyXoJ0J7FIXUTtbotcHtuai1ZAGpGB1bLD68wZ8ddB5q2w5NgwTo8n1QlfSxM0Tr9BxWwvJL3lnMHWthbM0VcjxFK1+8JRN78XB7bcoOyx6ezdDxdS3FlEaQMEiRaQtqVjp5JtiK2iUSAU0JeULfr6vMS6Gj+HJHVpLSUVT2s6kNcmqSAwMZ0jJ0t1qoGvSooX8VIUH5MFCn6GJRI1FlIjw9NTumtzq3gqGXMSSZahxtEyOYyToQ9dVjst7hvpQVVSNSoTE3A4gMzvMBuDCQQmD04zDjI4f3qaOHGF2xhvlspuT+JrSLKHWYa0/vCKoIt4cqW/mzckztcUMI9gXTlkWLfFMkmmn58TsXMU06d+srL1YqOwa/hoQWPOSyeRxIw8Asj69He5DYHsyLeXvyLJPGbfCZ82l6fir2Y286kxEAQ8yT02W+h1hW7OalVyOJFxahsUWkCfQx0YsBBySSbFj5PcOEmw5wcaKdV8H63c+gbbwALdEYfZL9z/yWsWg9dFSWaaHBugZe4ErKW7l9taFpvAo/lO/1znpv6nmcTT+EpFMYrNZ5ibd4EHzqunZ2c8WNjM0VLmJcP6WWhKeGf6RJgOAcPbT1GpJgbBJloWm2f/Dixtg451Z3QvpZ4NoLonbia5BceOwYDfYE4WTmDQGDY+drLAxUV+NbmHfFz9gibuJmJn1WP9khlhfGKKheMm3kmmIGallXEy3rk1Hebpt7zZSslzeDXUXNs2TWNbJ6yoHht+tPhdZH511+XpKRsn0cQcM7kgY3qokvpWJUaGRex/cI6Dv083emXOHE/mCg3jrJKwQzGr4PEEpMe/xOOmExGUoeLCx1qeacHPWN85lLRu7kija7YlzlmoGcMl3nlrZN4HfrSJCWklc7h0/22DAbYEFNk4voZP61YYJAANmhMnIE1lsB0YkPfqKgo5Ad/5Es+5tD/dDexk2Y0GZD+QBkEV4iPoMRyUpXSoqMnZkSqRCP+yzxpu1zeHBj1FipqMuzBalfPQUqPu5M1dLOZw2KD77X4ry1NTSwemX+gLCRb9ZHZ5vyp3Jjisu+L2n1s00vdeYjDgnCaR3xZoA30Ra/BuUjPEfpwzQBbQca/+XUH4+F6XHSEsIMfdSh7oEqjQKfsb5/vPC93AM6lIcFv8hXFJZXvUrkM3hYpESIuoWxH5KFYT9tHKD79QV3hzE9Swt8RnYlKia5jhaa/LPlg6jtZEYZz/YO//ypDVxaVJ5GcmL5lEhOP19nSc0CghVWs/UtP8UxK9Jd1j9y7inRWI7AvPqUHMebFi/TnrkKv4A8o8mWXRMN7d16B66tsnCxAXKsSfsPdas2Mln5BqJT3rw+dVz72kTLSdE355mCoSalz/EhUfJ7paGaSg4RxdQFH+kNnqNhQfz31JlbRJzwOCJQi2kdh59140q85l1MXDqO6JkiU7jmCPyUR3Ubc0BhlI9phKedlR+uV9sYanviPh9dYusX7/+LPS8/Gokfc0LOnZuK+4ZS5osMYilVUid3pX9yy1VDnb54w7NgUPbEE0zUMPl+8gHlVVC5oObbqpdcCUsNvS+1LHPahhI8uewdLxWWn7m5OHi/UJbYmBglDY8kIJA0crdQSLIhDpscQa8ML4aIu7dVC73KCNXXqm4Wbyp37yNoowApfOA0sO6/c5JftXSLcJdn/oQsyxLgeeBzIA/za/6a17aOrfHeS0dJnYj9E2rzaSLlsIlpFXk8o5nYPDjXrOucPyjQ89p3qiD3M8daoKRgzOcegb49z5Xs6CHMb14YMQcXlB8aPEfL1Ah8o63KKZW/aqIUc4awbfW5acew0j7YLZ7sxcq1eqDY2/9u8qu4u3JNcZlWJUmFplKHwOUV8WWewbObMrc7MemwxFocb733nKRq9be7+3pUrERNDtasSbqIkKCkjv1dKleHbkUXrPclJHLji0URO60Mga8Uop9OtzXt3mG8PDclY/vwghOD+ebtUnBDbvziD+4SSpbxZKEDyNOcl0oFft4PTmzprJWPRq3tuQ+DQ2biO8NbMLjCJm5a6/a1aQU6uiO/lSxZTY39woSNMKydJ567dZrgvuSpMLLsPscsW1kEhp+wD8MTV1+vtL2V5S7mO0I8bZ3lYQ9+PqDHuXr+rrIQzjVHvCNiGuG+xFKMR2fsT88b/+rFTKhSDO05oCg+ksZjtTinFBdoqzsZ4LEbA8rGKNnceSt8RIM+N9jJsnPMfx4wq23wvY3XNp52ux7/pbTYgfb3gOGiQcdnX4O/mQO8qiwbXb9ywLpX7jDnQxxpclxViT75pLW19y+GcwfHB7lfgFabzVzJklTMvBjISgvV8Doe2Qlpo4FrCfZjuMBLS9dbEIM1M6REh+JhlirUkCTDyoC8BLPYN0t1bocoJG8APWcgjNZ5+tZIUpDqRC+tEl7/auXC2ihgaMZLIMdv21Q71vCDbENyGvo5lBZ1gyZs1iXvJu/XUAI2eD6B5zBhaOGaQbFs8XHBsksLv53V5e5hk7fGxreDcbQ2PPQSfZJNkvMCVJXG+ePzHy7XnpmlTnKvcm0jUoqACS/1GjieObPq1UW2j43LEeG2qpm6ZmiFzMij5RRE7bWe3jy/erCR8pKtP9bJ6xKFreeRImoky8P40IR51u+JkvZWevhMahxMm/jD76tufl62Ru58whjv6yfLmH2I4hfxgC6+KIubKW0vmLadbLU9rMrkvXpsTurlKnVrgqDaatE3dWTse3Oi7iOjpqnZ6nFUz2TeQXfDeMzqfuXmpmIPKdxQdElJJNge09pgzt9PuRE9qlPeV7fTcJHvgHvbiNn21pZpGRCCM+KSku8ipJgnt89GF2bTtHFIbeA3I+tAHHOUyXnt6Ky4kcaOjLJT0gPJ1O9W2Mwm8swxEg2WeC/suy3jaTKmNHLJ1DXyGzahjQ2gyWpPSgaa0VuuGQjvfFcU4tYJA31keu+N8lgMR/Uy1fKEj6jk7ZyFjk6oCi397sAHBicq8viyAAaS0ycf5ERn4/hEOZ7sfCefk+PGigzjFunyXVB4Qb6JUZD4Tmnhi6U5Q3t3+iVODT2v7S1xfEZMesrZVApjRSVvwMtLAxNtuBgOiIXYOeFbtU8dmKaoszbhMwcrny3f1VcCRF8ari3V2VhQdOHhVUsSVHDfCUAE9ZtZAxsUbAczQ2/c9sg2dRvQfq1EUvkM+Oh6cemMXhO6oCDtYwty7kzK5vsla9QHPCQahMbLp4mFz0rffv26FLSQd1EaxhdimIvJPUapwEbUE5tiNTRj3VdgZ7pVwliqs1nhvkIOHPwikOqQ1O2atAHtmsNVVUnAb3HHOlSGS501nNMT789/0n/4QLZsDyXlkOz9ZIFpKy06hYT/oxQ3ZePlNuk2fcQv2t0Cy7pYi60qEmLnkdyWAHN0fRGGsQNlGXIL8PTyF0rY3v53lQgfXmpaJ7YKzlPH5xZ65VqNm7ZGh6FfsKU0f85mzsipYlhm6CZBv5IF9G/jLtacHvXhmqnOjB56dffVv2V/4pR5LD+MzT69clr1arS8FPIYsloy/6jJ/Y6/j/gjPsuXlrVm2wkvKvciRHfHrz2sgL6hfMMhvlA67yzRH5Fmtko6lZdTuQM0KRE/akhrzL57N8SGgN1mLZCiG86nZAoxHc/DXg/ZDS1d8g82IU0Zjh9H7A4Lu4Dcs7Bd02iA6BWoGMNuVrH2Yqpw1bbA1tcLtRBsCIYIU0y9U7qYNCMZp45DpMrj1Yq3rCkklAnuERvaoolxCetCxxt4AW9HuJf0/Ntj+HmTrdy7+nYkfn1+z+LxM8XFXBhJ8u5WSD/t+FJqpP+8gpm7qiGMdmcWB0p/CGsXduAZFvdEubrFJR6T0fGzrSp5SfbQxWmk6KTmg/0a+HnM/Z0BbBXWGQ0MLB4TMZCwZm2RZ6wfAtBMJSfif6lK5OrDOitCXpKhDMtVLn06nQv0Bwd5e56a0RksIfYkRQ2D9lE+0zjHv0iJxwhZNeUpCU4ACxgSq9saaajRH9EHhS1uxN5pjERYmU8XInl+pJfaVpAHkVjBPJpQ6vKNcw1A3QkL4rn7vYKzuspbh+1c6wnrnGmd5fwkxEj/xysVBxW9FeoXBs5xy80hb+CsB3urEZKa89mHqxvyh+vaiXPZGu0O3zZalL/RGXJqqjYXNcpPaZudMXjPO5bGkrmTy9yB6iSzH17fsojS2IlryP3Iw64oTaBhky/XPj572RBzuElD8Rb1Scfm+aJi2UHJRm+fwqXgqiPhZNIJ6WThgrbhW9iQDS/LEXHAZxqmK2EVai/oG8Kc96SmEUTqFdtfcwS8eVJsHjJ2KOPIFfltv336BDcQCeQaXtr2NVwtV0iqUcBm/oiUNc4p2876gW00nsZw9bWQMb7zzXkdAUk6kTeTX5oZSxx0TGiVw3wqiTzIb1h25vVHi3xDnb3MtzWtmMJRyy2FJosr+oqmktaGR4l+eTMQY2w2DDbqFBG1HjMm7i7UT7UxHzCfQ3b4tVJv/ZDiaJN1JVszUkzjjscIprPGap2lrIbIFC3Bjm7pZKkNCYJHhRbhJanmP49d1x8dQFukB5i/7R6VWPYOYWBT3uXuOlU6YuMMze/qpiBrChY42gjJ1LgXy+GCjDQcssUMHvnFVRuM1O6MHp8miM2DxY12KH7NWPW/5zVufwFs4AphEiy3YKnZq5zcrdD6TPhgBXsrXWW/KJbNK0fCNPuNrpyg/g3V+gAtGsPXpC41v1rHLo5v8VG8kQIyhXorQ9BF3oA3nddZuWTF+UtTbznhJyXYhnONbbxKOdRHSp8pTrZj8mtLmZ0JnyhtP7CLVQtw9fkJEafEFopXCM5ul7rAFTfG5dFZmjoh5v9YrWz9Gf08zgCPKWm1RP5Mco9vO6/0TpHGqlWCQiyxm7hPIEw/aSpUXkk0vZ+qctnL0lzAJ6UovSlEx0XkQay7A8rHge02XhGCUnlNHZ6gIAQD6JAKuzvZ7e6K0NqSzHCUdYHlDcZu48X1EqHGR1Hp0GurPGEEdupeUfW6h/7doDIOfhyI5XBaqfCIWm11IzAb4b8QuZA83NEdqrP0SuxL8rHBgVZ86nuwwNu6STSDDgQniETdxc5qwR6lzr3vVcH2EVJd8umH1Zn2jJI76iIuZQwjl0qNX99ZUhgRsaZr81/ciaTmRwNaGN/lE/jxc3dVFSQvIXcdUBhHWOFzP7lxGT9QLyyn7hG+maD2K1clhKDvOIdXHuh2C3lrO35gbpphK3UoC0BJTbZGPnWSGHjOR/cxSzROdEX3bXqIshw7As//+umeGK69YnDwwVNLHZxd7IBgHkw7SkEv0etcY2mJZKxi8Pb1G8PO4kC4sgfzZjDpoHOKcSs2rxvrV9tmApFi6y1YGovajo0S6l3mQhyXVlKN2U/qtgE/Qu9aQ507Z8LQFM62NRxXekGKDyGZ7QkKfrhtzbXbV1Hk44A2cPXa8Sulb+UbH9+No9zuJuOxgAUSh7+cJAUaFTKWC1baiH3v8J6a5ewj/kLbs0JhGR1ZuXhMITdIgRQNU2tpJ0t8u19RgyMcXxGOpY8j+6jOm/llYlmjPLtKz7lRRQwzV4D5VNl6g5b8wUqwUg8DKXdxTkMLLNBSzZ/ix66tXv033ibXEVJLMRG3spDGo/HLJ07pcq4M6N6sCkU1T+4mTE70OYEZ+82Zugda4TndokOJxmlI0MBjQtMi78n1EdpwuQn2D/2bztiRwwOs01ofFsaESsWeK/TvP8zmGmo15gvHby56R1Rl8eTKkqjyHXqKZGSrFJnrN1AdRs9wOlPh1gvf1iqaoh7TbYIo56WUTOmp6LXNkdDPybRJWZTMVA4OWIcELq9DSPn5xrfJzR8JcnN7BjHRnZshWIeePYsqfhijkOx6ZL0Bhx3KHKTZn+p/XSqMO/+1g8MSESkJuqAHjG1PRN0LU+1bQHTS4LCY6GkS43gsiGwGA0028JRB7wXO51k9G85+wXJbOlmns300/9u1kCl/F6spTZTyyH4a9PXAZ62fQF3n3bgncbJZL1U7fYoor+nYEr9YiXZc9P2i2sDw4os3kjEsEKV1ZsW7EXc6n03wqaIBORmjmg5t1NQ8OvbKW8mZ2nqzomZq7opbopAo81MhgUMYPo8v8vqhaeAzidAia7fCsQBEmbD/1UVNoTpdpEenVld9pikJHWHZ885AX1kupgTQ7JEUkkKeKYg0gjgn0YS5Bh9wqFX7RvXn5uKzbDVuZ4yMt3ie5DGdDCCnTFp7zA/B8fBQuwm45khsU8eWfMvHj7GtWeyTz+1rTltgOrQndopsbnipLq6hSuDLaiHXjrlfksKzgWOl6hBxQmpZrnhMFIpyJhcWGbK+baaCj5IcQdOxGo9wBZw7sfATKqqu1TXM7/+pHmyh+Ht3aXS6SqpHEWz49WekOI+YyMyfG0DvK2t7jRL5hopwxh/nKwX9q1BpdwfmGzRi3JcI0cFoUlBAbZgYaleEQJC+XccXQ/SyGF8RwHCMdi0ytKhwHk042vfk5UaLUBaJPlvXOIWrfWKV++hNp7g5JrsfpgSvtYTs4KaIscvgmQGQaQK7N/LmupsY1m0kQGw+FpaA+VxzuMYzo5jEvzTbN6A9JMf/3M8cpwX/NCWgYZmEBm//oSwfkPIzc9pnI/Fe9Rnp9gL8QJTmqIWEMMKM5PQb78DvOgHJKjOk69I7tvJztq+CJSAecQvsS0yWXLXHy57YbXp+hintGu4yv3DLiNP0XJXwrMXlCj8dzcNQL0dmH4bLwcJIDLu6vY3Psuh1Oz+Ujg9S6bgeciZkeUpOfAj37eSNBnIq7XODRgzDfaOqSCzMsisqLdHjWou6z2TKAE8tWR1VXRoe8R+LSZr4k27cHsz7brPN9wD59aS2mntNvpUd4/eIEjCIoxbbBiwLY87iRX2PsQCWjuAFrAwWxyPLnNXJfcTvjmmUIplp3qNUsMGOMCxM80p4sIl/7N8EZi8SPleI44zplCObP4mu9yQG6Aytmy89SPIYbT/WJkttPBM/eKRXlcY271C5y8DiNf+8rqUJQtFfISnCDDOlQatj4cFw8ZBqJNEdY0pN8s96dP1rZIRO3uGFkJsEY9HJXsFe6/IX3XjSqrNaaswXxzc5K8OGm+IlqcNlZlgg/wFrf6clKDZ74tJ6EfrjmidPp9X12LIdTgrzRFpex82qoLx8HT7+8SzXGnWOAKAv+G5zroBg43Qo1eqnwEvHKkrOfNWkdHe2tY595gFsR6ued7SOJRmV1RbBY23HZ1Th+Q0YiGf4y9jfx86k62c7igLT74SPhUIgquRfouNK1fJfcB+p5+Y60xm8mW4bli8XtjQwRXUtt2pEO4Vwqk4E5vkx3X7x+uoiOYJ3Gfqk7lPtk71JHD+yNZRUYevzsKquLx/R6sdL+LEVyh9fiCXFwPlLs2BDKLU/7ti8VQJhkbTxvli2PhiSKj+O/KJg1Y6VHJzDQYB6qzww2XUaJZmfqa6hJBbv2+fZjFjV6IeQMtlafXGstE+2VVIXZSYyXpyWtNSS3rtebW/zGfwYzF9nV6c989ArFwTtbBVqadSt0XIHDWTZcWU6HQIlGiEaEi6TePRHXswmwBFcxtSoT+udZQrSTQ/av3A2aa/JPADsyDqJDevYPhJh4lt0zxvmxlOXRkiwjdZV9+jGxH45UaGPaew/KR7HY9WKsSgxa+OEvSyZVcIWtutbvkjZLXCOW7gwtCS4/cS/66MTXzfTUs3FrUD2MDniQJc96WkDJ1mpJIj1XeH9u1qUJ5jGqxvVN+41qSeDeLZ4sxySazLz+Araexo81s+4XhwR2PStD6/CoKdzDnr3JokykL46b/aIfGUtRIk5NkpRHNDA07VfU/d+awCcd8nVQPgLO7nNlreY4HBqSPeDFO+c1ouQjfUBhWXgJ4zyEzWqyNoy607lauZEhSXQsyh10NccZ/WUfmJL8vDYxjymWGtvrtcw58fURcRCUj3fV39ivctRZLauXpIaJOS5eQ5ZTCtJn/CKvGLuOxsQ5nMvMhi60jKKjT7XVTARpCZx3KOOdFIm7uFtFtr8P4X8RJ4KZW5kc3RyZWFtCmVuZG9iago3OCAwIG9iago8PAovTGVuZ3RoMSAxNjAwCi9MZW5ndGgyIDg5MzIKL0xlbmd0aDMgMAovTGVuZ3RoIDk5NzEgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajbYFUJzbEi0MwV2DBBssuENwd3d3GWCQGdzdLcHdLXgI7i4huLtLSAgSgvsjOefek3P/v+q9mqqZb7Wsr7v36l1DTa6iziRqATEDSkHALkxszKx8AHFFNTZuACsrBzMrKzsyNbUGyMUO+LcZmVoL6OQMgoD5/ggQdwKaujzbJExdnuMUIWCAnKsdgI0DwPaGj42bj5UVwM7KyvufQIgTH0DC1A1kAVBkBshBwEBnZGpxiIOnE8jK2uX5Nf95BNCa0wHYeHm5GX+nA0TtgU4gc1MwQNHUxRpo//xGc1M7gDrEHAR08fwXBa2AtYuLAx8Li7u7O7OpvTMzxMlKiI4R4A5ysQaoAZ2BTm5AC8CvhgFKpvbAvzpjRqYGaFiDnP+yq0MsXdxNnYCAZ4MdyBwIdn7OcAVbAJ0Azy8HqMsqAJQdgOC/ghX+CmAE/D0bABsz23/p/s7+RQQC/042NTeH2DuYgj1BYCuAJcgOCFCWUmB28XBhBJiCLX4Fmto5Q57zTd1MQXamZs8Bvys3BUiJqgJMnxv8uz1ncyeQg4szszPI7leLLL9onqcsCbYQh9jbA8Euzsi/6pMAOQHNn8fuyfLXydqCIe5g77+BJQhsYfmrCQtXBxZNMMjRFSgr8XfIswn5H5sV0AXAxcrKys3LBQA6AoAe5tYsv+g1PB2Av51sv8zPHfh6O0AcAJbPTQB9QZbA5x9kb2dTNyDAxckV6Ov9p+PfCJmNDWABMncBmAGtQGDkf9ifzUDLv/Dz4TuBPAD6rM/aYwOw/vr898nwWV4WELCd5z/hv8+XRVpbQkxHnOGvjv/rExODeAC8mTg4AEzsXKwAXk4uADcnL8D33ywqpqC/q2D9J1UWbAkB8P5V7POU/lOw29/nT/v3btAB/s2lBHkWLRBA+4/GDVi5WM2fv9j+n5X+O+X/T+C/WP5vGv/fgqRc7ex+u2l/+/8/blN7kJ3n3wHPmnV1eda/IuR5C8D/G6oN/GtnFYEWIFf7//XKupg+74Eo2Mruv2MEOUuBPIAWKiAXc+u/xPKXXfPXktmBwEAViDPo160CYGJjZf0f3/Nmmds+3xzOz4r87QI+L86/XykJNodY/Nowdq43AFMnJ1NPZNZnIbFzcQG82Z5X0QLo8VvDABZmMMTlOQXw3J4vwBLihPzrRHk4ASwav0y/ES83gMX0H8QLYDH/L/pVHYvFH5ANwAL8A7IDWCz/gM+81n9ALgAL6A/4zGz/D2R7Zgb/AZ+ZIX/AZ2aHP+Azs9Mf8JnZ+Q/4BsDi8gfkAbC4/QPZn5k9f8N/DdHc1cnp+Rr5LfPnCf8H/76zgEAPoDny0jzEnD/Epjak/fqjKJE709644Az1nnYaHZP3klOH6y06QjJddVbQhtOlaPLnXszVHUnaC5Flsgfv7y31COGtiaptdz73xvFqU3ttyIuTeIMTRd9F6wZIkIiZNES++Dw4+mgF2sK0QHfJUec5uvKgqxTgXLv3S3vUDZSvjIbN76l+qX4jj3JfPs30VjPGILBkljrfLHuOgALehYkEkR77hwfG7MXlDHbuxBOZXDwDsu/hW45ib71N9nc3c15rlRrszt2EVIR6BCQwF9ijU6+9xb6myOEveJe+j8ZsZh5hL3iQyzY8jERelCOnNdoL6PO2GZfvQZA4vNyMeu0BDOsY+XIV4AuP+MNLql28HjH6i3aorrRHj2CrvSoxJOkzFrP5C0y9yy6f6znXI7mpkgw8kFkA2ihr53pL1LuXTqm4yLR8Wno55XG+jK4e6otFPZ0/rAokByKd+ngaxHSxdNEPNlRmhJOllwvyMOFWVNK5OzHWMnu+pAqZRBsj/mxvI8R+y49uHyRwHTMvpaG4fTehVVyqKPNii3J3YcpTT7ojyfw0hlzjo85W6pWvla0jb7YMNv4hGl78hXfVA4uod8S10HWYWujRDW5K7+sd7bmDC87Ar5f0HtvW0+0bnOENJLLuKQ5owwkCORI88z90ObTwv7plfJr68CBLynwfeg+ZXIvQrDVUlOprZLzfOPjUqt0ZE3zKqFE3R2b2CdFknXlYwxKe6M0tFq3FLbGsGi+UiABd+fx94SNjCHG3ekziVUA9Q66V6fiy2jFFosAPe+mAbDp/4pmtOoxXlb3GolAIOAMe1ZIgEgNmSavDn9P1x/uZw5Eqzvv8MPZWNdXtWYPHyx6S6rHpSefdvgVUVnEili1K4EX0zG3T9wSAFkbd3ix2yMdAKOp2o55xKtlt35qhPM0PLLgFL9qvv1jtk3aoHL6GOE9EN/sF/owS9CozJKuCWZuzO4s3GER5KE6M946SHroajrrBEHRbYhL6jMaLi/3pHttPpBkh2hwz3XDMUO7VBsHIu456QSRO5LzTRXfQjwVSGbSSiwx2PKWecNMLSQvLk/DoqAJnguw5iXVEHMwJJm9Po2TVVtykHXtiDLIA9zhpdEn/TVS+jq/ZyD6v+LqNVl9eSHkZy7rnDS9aBojcfdkM8K+6pxZIjdWuluowDJP9OHE+QHTzBmsqetzZnXwiSYYAW5meV3F4muJFTb6bGE7MxYeBLSE6y5IUsKGvxVRspNhy3SvQYwc4lyNpHkfGhj8pxsWVWFQpRN335W6of1kBgVERdBu2N0+qKfVEpbH8R+MlDlFEU7hCCf4swx2jt/0R+EK2Be8063wEz4vyIcaxn9ZcvbxOyBEWOwjRt3P4cv07gkYP40yISbDY3/Or3Es0cWSeivi4yITCvZomnnQxxLXt0RTJyeG25HAwUJQ4RkSfkCTTf7INwiivYdIbt/8uLsMmQiSlLISCcqZBY1jTdDzNmjKyvNzAqzaPg7ptvNATHT8nLdpxeYyOEV9Y/LktudS9RFtXo3d9MHgn4NiF/KfP7Lj1EAMCPePUwyIvho61J1eFvzkHdTGWdcYR0Tq3DaOyx0x408VqmoZrRPNyp3yfqmqyL82ZjqxmMVSsgx9+KVpAwnxyT9nD4HQrpO3SYXWCSPEg0C3pDly+Ojh3qB0ebtHuiFcPxzQbU7mMv43h6hnyKbPSfyRxOICRNDSmVPYjyXF1r5QtP+qVGgnX/LJM5VcDn7gjCOwNwtUBRd+ngD36gsFg7SxW+RGJMI30CpS65RDpyZGzVY254JPUXdtreO6Fvlmm/PeP3TCPDcqWmWJ0NTCaU+KWkjzMdWiy2qze69ufpGffH4cmfUVqwBGruYoaCxXDUSN0oLRuW4PHQj/o2pY33gi/6FI8v1zy0ZSIWk+vmIumHzuiH1j60TOt4mHfmfPRifTg5VY0zwSLzrAG4UvuDrUQMRZXXFT3ax32wCs/7WGt6BpAa7DRlbUE6OBnfU8XMItMg79U/2shWyfp3I6obKd8MY4q2+nHO9j1ILM2rQuYkVmQ2tZJw+CjX+HI6C5MDO8TJQ0RvEFJU1kO+jKKw/hBZbwcF1fFR3grLxjuuEAraZmqiAlx2sB3SzN3y/WhzEz5MgKbhIhjhBiRPG0ScutLemaLdf7Ssx74yq/bjmGCQj8P6A7uCG5iDd4viB6geSI0EwNXtIyk7FcjBQuPQ8gCb2+v4WNKMmxHmS9P7vYk3tOylhKscYroCAZMcZj/bHta46kdqd9DtKXovbaSms9rM8fFcffqYGp+SjaggSmkj9+E0iKAUuva5rjLu9Cj+eYK+1Z1F2vgIOxJnkCxLssC2Ww0vaOHtwa62TUx0llD995atnDTn9Q+1NBirVfgAyonLjZO1eRF+UVstOBjYctljmuLzrigGuRs1qQEYX89+4PWzdyrYhMqHBYhr0Yz7qWcBxqbfVlCeMZIKtAe5Cvn3dRObyfz8swoexGdiHZVIY2SZsVOKDX/cNTZckIoA6ugJF05PZ1K6pJ+oZWgXT39vPoa1NnNJ/f2LN0EvAQ7Ve1ZT/oHIB0gE4oddMeWqQDjZ3KqIHdn0AHxE7eRtz5a80tvzZqO27THdxiWmlM5N1EajFv6KApbGYjFcMgWIFqI/oDqJzroFgzFMjChmNoMSCcwNGIBwVJokxX+sDkrQYYkaS4vCpDNme8eFjXc6JB0sLEIXHd4NO5h6DyJZ+Q2Kx6H6yjsUHQLlaWt5cOwSIFGhxoRFN25jHWnghyLkjrIbswh+OtdoTZmrWpTbRMmeakVFOO+hgRxZFgJIVEeRd3qNEvsnrknuD8WXkf3g5fZ91zabeACfqqWqM8fHdWfUo+fyNWIz/at/ZT1VeiOjVTX76y6tZbP2PiaWMpJq9BPcpx0UBWdipPLXFJJgc/NmmuXaqM1EdE6XQuUvWP0GO5R4vbvW9FK8/iGsdacFBc6HzjktKaEUWMDsYUVjWhsbUgnmwYIf54QuFFj9dVf486cySf2r94yaKl3B5b0J5+5c0xp5G1pbrFL48DO+I8Mye6TKTte6AYnL1WtmoSiXPOjT2XYvcpK5y5+Y8yuKKiN/1ren8pncoGGqW1sqfxYCCpLrQbiwoOF9ANEbuMAx7Db1MUM2ypQk9P5SvU78iJr73mEmmCf7CRXuX6Lpv0h+27plVsMy028vk5qVNi3dFk31cR0bKYCo4Z95m669kRBAyuVrKLKpKZTT7rDBkx8pEZ61Ahh/U6rLurJxJVoisifgGU/1Ci78ZUqLwWctHG+O+cS844TSfi9VMEBT2QfKL0nZUKGzQ+ju/TiwIIMY8ocIVffNFjeVV7rrTJe1TTsnOc7/BsibI3RK90JbjoHBI3eDZOCsjEfDixNt/thjMY3Iurq9LEfe8WA0Xbpk0H+RyRbzjx2jYC9cN8ERymSH9u5UAB4kdoL7N0n3rGZMkICtxXNcBV+7KCjVfzUm0cUT+a9nheYs5avtArnXsE3b7KVIMMEBhUsUW+R5mrHO0Rge7M6IFvMUYlkULzjox9QjmX9JgdcLk1sCurtUcpWJbLdrDgI08lFDLBrvdT1FM7eLB1Z6lQsv8cldGPaWTaqlgUWTzMRIcAENqUKC9drob61q5DWp8geE+en6vbPL4Uvd4E7pG1QnS7GRk6Y5moMW9eoOOu2nLhpPs8wH5UI55VtgxVDnCm40mcRj7+ywVYWpiLPhOA0VHfDOnozPq7l2BWieNbgSUy6RbTykFO1dRdYsk9H771c1jPz5CdnhfKU/aS9iqHW/BZjcJYLM/oq2Phybr5zmz1ZaPQh+Mcy9pu67Mzdi9IXWN6jQayhF23Zhq/rCFOStEL8Ksenu3UtVgmVZJKaApDc0NLchGgnqjRxqfOxGYiTevZ69Qe6RniiJeKY9sCabNKNuQoop1ETQ2VSqw9KwgefPtOYC5MYwzTqz7mh3Zi7a/CPedmM6UQ0gqzopfHIjoNfNn0FR7fCR4Ba23+k2VZp1ovoNQWSwX7CBiVhtrK3Jhy9q3Zoa2pyaFitTJ81yYwnXar6Lgg7Jb+z1SyGfZZQBYbnVeyf+ZJxXGyBNN//xujQDG8P+FXnY6kn7w1lFvTUV/tIeKLaSkl5oHFtSZ54JaAvl6maFsqfRmx1/R0WJFvvbYor5Ty3872LfF8hA8xQ6s0gndQRHR8c6V1KjshSFKbHx5Bk6rTPA+62YyT7tRgvyzawk0rCk8xhP1Q1wp/DIIrWC/XPpSKrvSwIzvAb4u2IDRNXb1Psrmm92OcNWUb/CgcnJ4Obijs0JfBKWlmT08aiqr3OguezBPGegcoWqKepgmObL1WlMXVIKZ879eoFu1VF+UCVWi1XjZ1jyqtWsv6LmJMQ4bnZhdmtF96Q6S3S7UdEvpZV+/DXSItpoZOuBx/QyB2MhXN6zN10AhiRxvxsIkHreWTFnwTeR8zjMOKTjBieavqknwuJVQVjHqlLBrtvBAmuwFHZPK1rHtOwej4G7ErA9eXbvYW3Mck3JMFD1/HQaEQebbuyu++BhX7SEwJd4g3TKgnSjkG7Z3lDxbDNnJu+130f7KoCqvTjOkhWiKPy6bnhuNtO8RTcOB/qiM2fu3fTS5RUhoFvjfxstQUtS/ANwzLm25nOFPv2BxZH3kbb+s3aQyARrYV7Db2wqnlYhURzgCnN2XYPqjpaBD7ruVJW6RS8uHBDy6aSH2ogrSRJdIOFlIDAoGL81tcLn3YUbg3XYUsz7dIoC/OdkqeBwKiSo5WoQzSVZuak4dmr6jVp8bx+PLvCJG7VFkY7VkWt8HvkSJURUnwsTNqFhoe0W1znY/I1FmjU7e5gVYWzUTiLBYkWQI5wpYEK3GqCx8oLXE3EYLgGDkj9O0Uo1FSo7O+0gFMfLVGKBlik77LQZ4yU53NRCmqbLO9LwpFt4pnXGk5CbudRHPoyYz02tj0q1N/au2OM2xyV7rz2Z5zDtG5ogCT1C3k21RvqXYNgFLAYNzEby1AxxmyDRRV7kWoWAwdg71VtsUJR/XkVUj/ffxF9l9skMnIp53bBCLiX6K6bpjKe82h5p+7FMrhL5T6QKvm2PApXdwvdThpq8Pt1QXqq37b1W4ro/YTaLq0P8sH6c5qa/BflKm/YkHZaCqMI3fY3h5s4kxDIOh0oXOVpEcDW3oFAzIsMHDPZApOTfHGKIaGAgp3rXKHsFGyinTH1y7NyLppSvPEfGYDeerLsDK0MjlVw2oztx7FTRCuTcxvniuNx610iagVlVZc4REI1XZTLtBVwQz0scXbRpiuxFbwKp4FakiJlIbXfNuW3gWjEF9+VfxwFFYqV9em9an2XYfTpvFsfxWQDRCq2HH8JOdnhjgom1SAtHUzYiKVyHJJEHZyGv2PMoTPjN52huSAkiKnl6QSP2EfjRrc20X9++rZzQIlsv05IerFqHQ9ndp/eZav+nTlz10sW6olFMKXNyNTJq7HIBD2F9OFNXsWbeOJZsPhJ/0Y3nnFv0iADcZ3glVrDA4I9fnvuJmbtWQJb1AKwqtLsQ/CMb24SuE0qLFbW+eGL0JFrZQ0AWgHGCjyiPa8ijrem5LaRXWTn4gktxkegBB0rYmuXCi4ZMsCS9434mb94xhDicVV9BUZu9TLwzdmJLVDW363/KTU8P9eiTdfL2SggHBBL+HVtQGbcP0yRMEGzjNGcjnU3giF3QOLlYOTGOWF+ht/Lzer0nwKBoLHPex4SJvWOqu6WpQ4pHVLlK8035ZS0cm9FaGB8J3sFj8VIyU3uT+mOCjstnwKVWSD2790izzBsIutrwXyTwG85xTP2y8dVjS+MOUJmIgPFM6vH0T33ooXJBtUp0aeakALUdfliCv1A34tkbCa03g6Q5tPW/rwtsJMKJ2Po1bLlux9j4s5oTurJ49fN/vSCRezShL82IrPp2sR+q9RNkMjUIX338lOJJEodqIZfCfgqrjVPjErnKDrO7wCOElnRDEc9RPT4KlqKgIf5ei3mNZu5cBhlJj551KqYIHzN+ePg9pIh/sNCON8wnDQP+LZewjFp+zv8vWIhTvms6qGcGeZ4xgcjjcyZBtQ+G8ufk8B1XaqLkg4atmMFSoAhVEFTpl2SaHkt0+VM5FhO9vTwPkmQR/4dvkznK0a4ql6CKLqiRtqDXH1V7UDZ0i5R+3qWOtM79lmJBAeTJ6Aw/Um3W94KnYmKyykXj+aPdbEzvLAaXTbePozcuVs3fwwfH/uK9dqb2wlri3OR9fJL3qtLPUDQLIqGONbriLzUMr6YsBLekPjvjd7pO9Gi7fDq9tp1X1IDDLkooh+cJN2W9iIob2mJl61P87P6NbrtNDDldBpbedM7SOQi/VJvOcUiTh2HyhjSPG0LLQmHlumDjvxyqh3JVV+euDjyBKm0dbueolzIrXmOHVQnDAEY0w+ng5jLju9Bpn3lM6JRkYLfZ9EYsoPm8sE8qtAfeDxV4HrGbk8xqBx24VCsWwddCxMpj0GXmrPcGQnBBZh2irPr4YZLMnFULXaDjhIfd5JQBnPEEXCBmVvtb4zejBW+lSC4kSBrcpAvwk/9QA+MrNdshah+fCFVijCqjHB0MqnP/eLW2gp6O+3+R606mnegYVvS1hi2Ce9Qo+g5mYIIUQUl83jIIaLpQWtBljl5CXQXbP4P1vIF6lQPnni87DRSh7P7BEWKowcYdTkcR4Kf9knaH9OyRCinFuMf9UK9VHBFyxFhw3L3Bg0b6wG8vULNIHVHYWd0mAOKJ+/a78dM2nkMlM2SGPBX9voLpG+NkOfGIqap78ME1AxLLMllRI6c5Sa6xsT7L7vIOmE5i1ceE13zbyRnXS9kp0gX55dfksmHPSKfhB2NJ1SghLXhjYT0FoG40BLOFUZdVqZZlPEm63WxoZ4yvrB7lmpyIq4BePQyHQfY+H7/rUwmh/2IZxb4xQKIUaSPLOm0L2UNLP7a/7FS5vWBlMRiFMpmikmNEtk2FHPsk3h32ovVS70wJKFkI3mk881+9Rz5dGwBBCBC5fJVcNn7baUFkl7FfiHtaFV7N8z2khntW8rgoAJp8Fgm9oiNmv3JLLH1689fFKUMoEaTVWdpB9QxMutOYKiFUH50f0pxPnmKauYGz2aYDzFH2nfDXJ/azOzHRLV2b3geYO7cSXbQ4z3IEEml4hpzXZqiM9cZGcn0uj7WZHTW05IfNRegcG7ywF9hly0M4JGkLkpIwS4jjz/ROWwUeH0E5MzW8GL02x8XJS5Lhn9sXyC6lI5CG9ekB0jRhIR8DxDiqut6x6Jrysr0+cWHklC67DsDV+jboMnwL9eetv4n159+vs6VL589DXRSR4/h7H+njjjRfDG0JmhUo8Ix5lgdKEU0shyLrSR4fWNL4tNhMEBmyXfIslG/mGbIcFE5Ne+dOCq6i6SYjME4gk+onTTTTUEJpTyCeElLlK2JDXnZGywdNWUsZcW9a9vQFOEo3AxFaFh5DsQshTg2rLcQdm8mKaLTKd6zH8hUjuksNiZ9FfGYK3pr3qBbBLu6b3ECvnUmIZjgaLvMPThYaJ8f1S70XWDSg78f8POB3sOcQzgcJURkf22JREsSjLa0t6RBTNV6r35SRB+XnyYTuEQ8FsCeHbXrHZXAgBZVoSS2TkR1vXxMj/+9xhOPNeILJ7stVb9jlUubcCijS820D7W1An/qWQDn5nekpx9IxBu+EkReWwud9JzBNmsvfDbULI+x0lazk+emFeRtaYQ1mUndavvj5UoEebmjJcSnMYkvcy9rg6UcUjDsUaOdH0nDLUNo+YRgZgrF1VO78lrfYUg9jSM20TlcsLZV5n82QOQ3ah2J9THk11p5Yt53V2R+07RqRVq32nhf5F3kVuKe1Cv2pQCgX49Zt8U2aYTneDGzcfrK7/2TMQN1zaN1XPqHHCr2KkbKYvsWF3t+aTcUvMpzWqXSa3S0jqRPZV6qid1Ste8rMMktkIlYjLnII0JyQg5h8feaJz8wWkjkhbpEbMIMrAPrkYQ6YyhGZChgzW/TGt99SQQLZTjBd2EwoHGyKoV5uLIbOO4cdFEfFuopRS5ZiWBLemyMJqJtSuGzzT6Oh2U9fDnmTU/cafpU2JlRV+Iu6tbn/nSOyCFVL57YGcHnkxyFOnCZG4fIDkPTQN1wY/ECEYbV6rFUi7EeGo18dlJDHLUPe973C0b1kUJarneGrrTdGc3Uqb+tcgDHksci+1rPSq5lGUKqrTKTOqqi+DW1tXV88s0q98Ww0ze/aUsvYfKxm/FZfd8kLx+pqP1bh+rSBDrtpbORN4GvXaGIkULWU7KYSENZFc1N51QR894GJP0sYm5+Q0R+w8aVNEEWUiVfgch0TBSElz14uGLUzOWxQdcoMVAtMbTxLTr49DCmv4n+5Yy9Gf480o1fk07/XO9wzkux4m+M/htCNevowMGybzo54WrJ8E+dd/x2VZVYG9+2LrqEIZ0gELqiK3zZeVt9oEIRaU8VnA98NM233TIjkm/EjkqcstMqYDVmBStqx1RzUjlL3Piij3UpPGHES/jhwUJIwXrqgmdKPgDg3FXuzlvj9FGpjaurAZtYmcEdxuQoyPWyDe72MTCO6QZ9aX+err/ovZ4vls2Iiye/phaD/S1j/FqQGkXM/tPhd2y57fmwz+QCn7eCo3kKdgnr1otrfki5HnTHZLyMIF9l64iJ3HrKvUEARdyzxVVvrhwk6HZqyTob5uJx9xG5GqE3BPn9CHu170fEIxvNk5QrinoweeOpLZXGq5Q9KC7w2FTkyw07ZKw/cHvr8hrs/RUPDrFWlH0cNxf27KSWti1wTkt8rPgKO/k2gkAAQexTpoaoLvN7yw5CaI7jIF349PqGhG9dc9yuZASkdQgq3oKGS2xFlMC7Dqngc7XsPNpZ28X3Q73C8l2MyV+PQqrUFXTw1LDDh/XLqbWjd5bXExKj1F91SMubDM6YOSg1YPWlngRDz6hSE3jWwdgdTsOPxTVnub/ii5vfxm5lo+DLeNyx5pkood+zruo2X09o+ow+4dmhdG923Awvj3Idrg2PvYnlG37mJ7xRRx0PtZwZEFWs5At7i4da9G4yRiLCU8nvm0n4psuNSYzfkCfvN8uIJUhKQW34vui3rLWDt8X1ezWvvCRuMvlfM8meJKppqAIkhpGf7BkK5JT0ciubTw7xkmG71sZUy8saaI/v4eiD/S0+F8rDJE88ytN7k7N4a2ieYnIyWoxE/2S/PSXoP4eO+hn93s0ILUsIhSQ1toVmOSYTE39sTH/WtixjSikjIxx5GsHsGrK8RCQR847UqrPDI8fkwee1eK8QyBC7NeG7KY+z6vaCN44rWfY2IMpRRL5npzOHxm9tN99bWsDvy8zC9oRSEMvrHWijzoXFhPi8SrIYkrEh2ZvPHzQRTNPlfKVHq5Jrsz0z0aCTvy2kug77tI7jszcJB09VzTPg8Y6l5mwk9JPd02TkQSquObBgqxraiPmpxys4gK7v1FZItis4h1TbPS+GasWgOLjdBMgTUbwn8a3D8bTkxYcmJmk97FdsRlUdKCwx4PatcHZ7bq330pPeCiwkmYq8m+7KuvMQ6U3ekVJhIDsqK0kfFMWGp9VVdlBKQ8jBs1OccMsKN8nhc7F8YXfJfTrVkGp0sewt1Llu3IR82uLOx/Ni04N2JEeiw5bjUCjb9quUXOp6Eg3g7b03bHNimiAR24Uo0lnBsdC0Ps3aUerKILbAByv0dLHk9AV+6o3X7ETg4laCq/bYlFf3U4C+Otl3pugDN7qtIxGFWuphSgmjrSWRhrofcru5aRbDCxF38wv7Ud8/OdYsprpfruAE0MPVH4fITbW2GBhGkFa2GLS8MDAQ4InNV6r7qar2nsVjKwvWq9DM7jwzbV/orPpoQnrlSysTUXdsFKMsx/6wHnmSK8yUTSy+CiMuGrTsCkbLKUai3nXdFpJZ8p3DjnTZe752RD3AiJcGP0fVXZt88Sg31hpeK7CXSwOLFXgWFI8CagViYzmqPPbnEMfD8yRuVWI15slkBrfp8cGjKM4sH324VR5Wyi3q+vh+sGQhKCPUvW0RVDcCCzn6dvf44iVMSn8nh8gHWiu30I7EBRPaa80Ivvs8T3qehbxTuXnNXnm2CttuNsajBGcOY0YimwkokwxR1c38iHYLoayhxxO7og/zTeWj1HhqFGcZxh4hmQYGZvWZZ+dZ1BJMMLa4MhjAlAkEdMb1l+zCd7hr51Oe7hXwWMxwwKmtBCjeDsewFgeX734/oHfHYBodlHsVVUjnbJWN7gFQQtyNusa9yNwDWLyYARZIOKxzd+sPTT7Ub3wafZYFzmGFldQ09AcRMXQE3h5oYfQErjFWbTf5Ko/JoeSOuWibl3dQShEfjVi8L47/pobSBGJkxl3u85xVz8mM7yeYOPDjSxvYxTwdi1xbifEyZctcFVwzsKXJeHwkKrDBq/FKpCVpoFPiKLOiaUJzadtYcO6FYCt8wAo5UtE7gU+f96zncl8gJNrco0CuSYHjllJrXKelvxxw7j1t3q6wctOJzp0ZHGvwGWWdYY9NwenbVW73A5/U7QLrc/z7X1apze2AtIg+YvoJjjLRlRi2fK0xRW1rE35Vr31DmTieMx2/ksU5dQWM0Z7yn45RvAa24nMhkfkziOsgzVDhyGonTClrTJnb4a/JSZpy9nLN1E6Lv0HkoUZy3+zaQlavtrtagTeEr6tJgHnoo6pJCpZ5BdBkOghsb75EihzOoULnqpt+WUPwA15davlx07EqbnJjNXnqe48WrIo4uR81RcgRG1OxT6MMTQ9X/W3fg6B7LRRVV+RZ2hj1kAGB5tynSjLUMIlyW0M/8YV7TjiSpPtzjguvBK4TSqBN/jGvWsNheD2OThBxr12JYHP7zL5NWDDfx82CNLGQouu0z1PqUIxlhTeAIr1dK7yIoqqaUXnma1Pn2XqcR1Uk5IaY+w1WqPNDEp5LphHLTtuZl1ySobeTFKrFs7BdS1bjyhkVF9/SnzJUSTRGdK6KBxNYmVASHEx548JZHelmkkm0mHUf7JB3KV/NlHAHMwqxkMOrIM6eYqxYtsSJ7Cey2OKamWGZfx/kvBTyBptb7syIvZ87PUos0MUwf/vGcsDZv1eYfcFTNKK6m2M+xHuaFiDpkRv+qrXc5+twkR60aYupUBlmCVNy3jn6+dXBNAdnZVwzF62EkczmU21Pv/BravzVB9XeApzh/kmdHAx5buTW8Cozlof7Ga+9W5VCIWgvWK49WPsXhQ99NKNbBp/P27fblYEj6Cm3A4s+QMUP5w5e7xK/nJpTEIuUdX3RNzV1qZA3UhOpGd1P68RUQOyLrWBumf62bd8WeR85+CBavsEQcLhE+pl0yVnFjm1mS/CUtrKg7QO7kOpL0WpLeNm3JHhDjae3V0r8o9UmJPdHWnbNJW8+k+yU5ozyIqRf2guGK3zKY6ef1rraQzZymioRLmETWuAI/J56sGf0Jk3EwARVRhJNDbM1YzW5dVpbZvJVmduiaKnFMNbQaQDm5QmS8yra9AuPNDW/lUAo9966FD7sBVXsD+0ULtclXWkD5gxsS+NQTSbbPVHxvY0ufS/JG9otQvszR3PfRn1xinuBkIibMkVM85T1qZooFXfvKSLtJe54h+8dXZaVo4By0LA4di98o8eXjPO1TSaM6wzE/GLNo4b5Gb6Xjt9b+QhHNKSqGawOnMp/FJYxRX89/Jkb/DEf8BFqu3/ktFbBkKapBFpgn10FuCamjhDHBl1pKdIIRwppVdlb9FC6DgKfv8DyoZeVs5Rp/bFG+479y0B4S1xdovfg6ngjQcXxyUXh0nIPSxd8NKVEjSOv7JGScR1P29RggDudsqPRGDNQwSby5RnSwrdDSV/H+QcNYm205FIy0GCk1fBgFXWYWBgag7lrjjNFc1GjyzXGNor5d3nCSCPUSLzrB+ihaw+bFqShiskNNZkRvXsn+LsYs5LoSPgI3D5htijiMPao/wO5KH87CmVuZHN0cmVhbQplbmRvYmoKODAgMCBvYmoKPDwKL0xlbmd0aDEgMTM1NwovTGVuZ3RoMiA1OTYwCi9MZW5ndGgzIDAKL0xlbmd0aCA2ODkxICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o1UBVSUXbemS7okZUC6BwkBke5OlZQYYGCYgZmhW6QbRBppkBYQaURaugWkGwFRuu+o3/9/9/vvXeveNWu9c85+9t5n77Of57Ax6+jzydrArEBKMCiSD8gvKAGQ19R7CBAUfMAvKChEwMZmAEZCQH+sBGxGIDgCDINK/DdcHg6yRKJsCpZIlJsmDApQc4UAgA8AQFEJoJiEoCBASFBQ/F+OMLgEQMHSDWwD0OQHqMGgIAQBmzzM2RMOtrNHok751xLAac0FAIqLi/H+DgfIOoHgYGtLKEDTEmkPckKdaG0JAejDrMEgpOc/UnA+skcinSUEBNzd3fktnRD8MLjdYy5egDsYaQ/QAyFAcDeQDeBXuwAtSyfQ78b4CdgABvZgxB+zPswW6W4JBwFQBgjYGgRFoAJcoTYgOAB1NkBfVQOg7QyC/nHW+OPAC/jragBAfuC/0/0V/SsRGPo72NLaGubkbAn1BEPtALZgCAigraTBj/RA8gIsoTa/HC0hCBgq3tLNEgyxtEI5/C7cEqAkqwuwRPX3V3cIazjYGYngR4AhvzoU+JUGdcmKUBt5mJMTCIpEEPyqTwEMB1mjbt1T4PdYHaEwd6j3n7UtGGpj+6sFG1dnAUMo2MUVpKrwlwfKRPC3zQ6EBIgICgqKiQMBIBcAyMPaXuBXcgNPZ9Bv8LcZVb+vtzPMGWCLagHkC7YFof4IvBGWbiAAEu4K8vX+78A/dwRAIMAGbI0EWIHswFCCv7OjzCDbP3vU5OFgD4CJIIp4QIDgr9+/V2YobtnAoBDPv91/D1dAW0VTR9GQ53fD/4bk5GAeAG++B6IAPiERQQBQUEwQIIZa+P4zi44l+K8qBP+OVYXawgDif4pF3dK/Cnb7a/qcfwmDC/DPXFowFGNBAM6/CW4qKCJojfoA/980/x3yv7H7V5b/g+D/WY+SKwTyG+X8Bf8P1NIJDPH8C0fx1RWJ4r4mDKUA6H+6PgH9kasmyAbs6vSfqCrSEqUBWagd5N+XCEYogT1ANjpgpLX9H6r8sRv+EhgEDAXpwBDgXw8KgA8oKPgfGEpV1o6oRwOB4uNvCIQSzT+PVIRaw2x+qUtIRBRgCYdbehKgRozaiQC8gSgZ2oA8fjMYIMAPhSFRIQBUe74AWxic4Nc8UXkFkO6wX0aCfyS2doXDUbL6PXjUqf/a/9YwCOQBsiaYmYJZS750qH7ZfFYlS+/Otz4kNc62/iSFi897Bt7iekGMm8RVmfFiEX4im9T3ifTrqiLnscws07X3t4Za3NDGRN2mS58ri3i90fUmgi8j1N3D+d9ka7oY8Rn4DGQ2fK5dfIwCHTEb0NvU2LJdXB8S6+RSnLl3KnvUdJXMDYRMretuVIqq37kqGeOLNowyDSyaYMuxypykYcFB8jHicZMfeJBMHJ+Mk78ZvmVSi+ch8N2NflDgbbwkFHM+6TVfZiCE+EjLSmtMw4h5TD4wyu4tt/Va7e60d3HBInwgeZK6ZXDZ6RUQssXpta6ldwbf/mnOzjYswUlLI4BJqRoZtdiokuBUxJyAI5x58FVt0UP1p1iDFYJXOwF8qw0Rqya26Dy0G61JaUGISm4kfdJJDshMrq0v90WSe9TyflR1U4t40PkMLWv3c6kZzk+CS6mve34ldUypVJuZKitwiKQKvsQAp0e8joBO3+WrW41U+p89g9H6Z6ocCKsF+qa8aT//ZHocH502TOckai1rbar6inLZwaLj43dyVUbdqx0sXAb28YXD5vJkJB4Yr2k49VY9k3g/Irh4VBYjJVed0D5x35XefKyS0cISOsCmFd0k+ZDD6nAWTxmHItq4I+ljolWPzRKROXiXtbz+oPEoDkxnSQo6eYXI/tC5sBykxAWR8L13W/lg7SlBPDYRo6bbGWYxm7LWQet0113escIWAb/nI+GnLOm7mGrYpHHaQg8ezsaBcQBRfGaqyi+s11psxdYmAgoHfgpND9LFz+b5GgCIbza7id52yBzis3tQUTJSL9aQP7QneEk1421nWSvCsKgR0DPpzuGHJaXdcKRBY213prPybsctXvydUn+61wUVG+mLkjOylyCf6zDtZIFxq/2gStrQ1i+XOztG+KWB6kQrCeYN9Z0hDydCmx5xaZZ/DI4KWX2Eh+G0iBVdLDmw+TqeIYGk3FfbBmhmrD9EuXnPSSfIdlC4aqKRizHFVzM8Xaewb8tOaKQaArSLHlhROh7aTiP+vpDrTJRshPbB92eUd13RIxMyKgYRsJr2s5LHg5MimORPI8iNWxkCWHdPFoAiCd/F0Jf8Gmhwt4yz0DAY3s4mDe8VkuTzGQYrtI86SWM8GKrdffuSA2/3nDasNa9hpZjCiHSYR2+G3l/52jnLU+Eug8qwm4e3cwC5tQY1Vu4p0L1561Pr/Bg5XSdVOH690ramlh2nPnrECiBUeoILa7dRWrJZRpNiIG9PTmuxTLn16XGsAphkB0aECSUk0qmY0W/+pP90TgHbxPHbSVSsXY/JPjKjveOQ4p2hOa10/MHnvlFboYj6rP4fYqcn4fcDPPYM0bY6WpwaY1qOnzsUWPc51rK6StTj6JVQzgRHgBU3DRtJmyZzhkjfPNptXqmb5Dd/xv4uZS6EIQ62QC+OeJxPdN7f0dQa37hOUPnQodWLVnV8bls+mQ3WNH5VGpOmDX1I/1PP7v5rSYXm1/30WSOkQvGcajxB/Yc+M6PteMoZiUVbk3sZ3yiXHMVnq6eCKA9Bnrl0ZNfFAr3iPLx8Vg/cG8SfxJ2JYfhmTu/MAYjJ9r55TS7nNTDUF9wMjr+lM/S8NnC++IicvqyPCf9hcZUkJFy8aSk6hihOCN2kZsaZ0E4H3B8AT0exLtSYLskeOsNZ49xFXhWbkvQ7Q8Kyw55Bga75zjYm+/17EMd2bGaI3u6a28+ASOEoC49g8uYti3usdDhGJt8vcRJVjK+zTtUrL+Gm7sc5zQn+rmz7FtVpSkTmdxoxpfLW0OK3KJMmMntD5ENsW1LY+KbnPrTV6D1uXonQxcQYIkHKHPX3dD5qCJWH117RLO175W2sJSqMBqdwUpyAfCt3JGjwFIfRpBUDgluP7agJpcgO22e3GK1OBFmCR6pcDLTRzTRwTANaCShlB9LPRstwxjo1BxOPNWOSgmGlTG88NBpbI8PH/Fz77pkFNVmMjs5uEqFTio/w95XIjH+4l0Yf2SMAO0PvzlJlpTfJ/fqMVyUkgrygtUt19rFQ2gwh17fsq8a3FXfbCmq7/LwiPaJE2wr9nRKDqXGfnigZRbw6kVfU9lALuSBwUHIqfGnPRfu0rwUzh2FyJDTyYV1QD2Pk7PZr71VX3A6iyGDrPO51yeJ+kPSs1fpiDxrEqOzG53SITCa/c5SPLJfB4Zus7Yr4+1ajK6ujnBp88ocYBpdzNtUONMLM20bNjSlroOpjeISx24QxL8iocCwES1qQwBhjfu9Jl3I+zrnb7RyklsJve797JqzKRASuEerrgmdw4ObkID+1Xmql2UkuYZe1vNfeEXqC32mk/Y0SPLSxmThbQnKv/L7PqKfTKZ/wIB9v/4+MO7bBSiceTy6Io1tKW95HOyPqnzJHi7rwxb7UJOHYp7jO6YqdXWQB9nTzHjYiPPreq+rnJWOld2ackRvdspjvOYitP8hQ/OxmhJOayomVa2C+r37Cl+soHfWj73vaeAL/sqSNN9fksjOenP1dPB7hsq1YV0P8O9zVpVsYyxIXTokFko8Y2RAv3jHzERSs9D18mj7I48wufOKQSrVGW3eibd4MfFdg4OwWrRBsnhxH2dmJyxSVNkd05MGa8n6PxxZytOaREE+bsyHWXim1QgvUF31MfwCnutCkD/UCCC8tCprdEiXnDT5NDZYvXOj/ykSx044vROuP3d1ogbgVcVUoM7/gkF5dxL92ALlQn23htl8cF2ETVjVzUtzFazkfT5zRVXS1ZfP4tMXpxIKHji53h9MK7vLMhdYV3WyoVIXRrmemE40m31ksOzG3XOKd1oyuLJUNevNeyOTks6Qfgd91HTl9qEY+WZz66+cJ9PafPrRMNDrvZeOAzbqxGArFMJftFjky2ovoSsce5pRwbUQk2bGr5bDuMxVRkgVM9PMu9cw56JtRsX8G7iq5jAxw9+5wz/U9TeOOiQWXQEJ/6ttqvaJI9nYxZsCv5MCU6VmywTqDQhjrva9Z1DsVjnLRb7vS8KeEkXMGz2JJ7oqn3T71FbYH6RJC2i3EZF6RGTMYdr5tFSiQtW7kHqFAeyvbbirMKKk17l2LwyR8u5dzhSVyXLb2UaOyfUaK2UiE/05rpi8cXX35kpG6wOXFmn4qJjeH3oVUFnGARGsfUgndwjdQ24iPZp82YIb0Ok0pXurHSgyjJLfxm6bolwvt2RGkyrAo0CmBYsy0Aq8s6y5g+DBl4nxnjwQ1mo4u2hWSTx1pxEF4qgHiXyWYsiuVhsM/0AmwPed1oi6tAWftkm7oL60ggGjJmo8hh4PzG3F5F8Yrk2+ocXYtkGqZpVQuPantuGpHWTmvHF175Tyr7/OUVL0FquxqWH6z+qwRA3i1Hp6a9iPoeL37zhMrpiozLt1osmkHWyhubL+zfSDpOrI8VXLINO5r1MlDiR1e77DqaqlrTDUSxSAhkycVCo3eCl1iX5sYxdtP6DnUAhayTkfWL+8Dj4aBDskSo1CeY2zlXN7prmHeJKp1Cn8I4uZB8/wLJdVbA5WlWBWG4OcJaCdpbhmtSd/erkuxjfNbbniiq4fEhpd7asqdQ5lb9F0dPd1YRN7NKXgRTBV9pecQpus7XRxCe6nrQ8Q+VdzY+3H8Q6MejfUDR/bx5hm17GxCYachokOTLx9NEnvtfYbMGDMoRNYWBwjE1ep6oxvu9R5PTo0TCJYTT66+sfu5RttuQcDgDl1u895u1pX9gA3FLHrboGyXqKryOsoMV5HovIr4MB7m32WUefthPaBZWIIzFK/fdNUg/xkTLuJRW012/dLrDq0G6SUCzTe9hHtE2xxVny3q+NIM2LGc5E3dnJcZz0pE6ipTLaZoVYnIbvldZbX6736KFa4YRcpcbRW4puVuPH+2OEHd2/RZ9nY54BCa1+myXPYxtkJ54Hu+2DBvmVM1xqpi0U69qPjjpPGrYjGVEDrZ5EmaFtDoUbn36khFdrS00Xi/Vh6vs86JQeICZOjNHVu7LEnVm5bF9iTpXJbUObnxqXEFz5FqQo1dzccEivO8XcLWhVPtPtsEdL7xxGHE2OtSF5tVlHWDHlRW6vtCV/sYzRGX5uv75k9OsQxljcQqPHT9QFT39xXVBmwFRND1hIoIHdIXeohrJ6AyGEokE2mq7FQ2Po1JPKgHzco8pK9Rq5gzUx8w60h2nLbxhfLRNG3EyyCisoDGNECZy6gANukH6oSFB9LTsd1pfm242FMUFPn0iLiqzM5YfX9fowwxnoRL4ovDQLdhvIdrofOOy1/f/mDubaN583nP1wMgJWb80zeIvCejdjvLzPp14TfmKQe/kmhpX3ZKUqun+Sn1LtNgxcgHdzEpPOKdrodizy+NRScLFY/Ecmvk13kk1OMndsIT3y2fz/sp2WBp2ZUA8ZSHGjfYTjAT0AanA4tfvd+dG15Y65oLAnqu1NxdWMcppQwbCHRvkYdg722UlL3LGnABKrXr2mYDsZa6miKTxE2Tvu/IfGpO32TCmF3n7ApjqDOPSmNQZMQaqblmq3/HSWir5hU+sGp+7056LUdSTTUexsEHIj1ArdBgbIjly2bqnqDc/WfkxFMhxvU5R9fGDEHjo3bBNh34huLjAqs+OUfjRsMtBhbk1PPsdKwW6WXUwVLA1EsviiHlaeVlj54tQgGMcJbqusJKpdNjGHZxzSNe7vjoyrtfTkhm7k8/+wGblli0ZI9zkJ+nCeyt7Cpw3aM5Vm95XlLV7/opBnt2FIApcJLheuFuqYiMzmoG3IcwB/i+OIwrvbN8ndWAHnUV7PAlNCQjjLqIgxukZ7/ORxLNf8+eslgy2h5HswDW/aXMujKWZPiky+OCk+kA/JEmwv1OPdW51kC960rSF6KTewb7x3hxUsXojaLmAKPUlJt81mqcqAMThgTbuLWhvand1xcyJogpRzT/U2FHtaYDGYEKfe2SYegzNVMWp1669X0vb2BODTZ99Kv3N9gZ69yY2GFqV+r7Mwk+WJytudBWd3mKqXpAr3AfO4aDRWuLchnZAn/ls5jyKyuTgwa1jYdFSTQHYtws7MxoAUNDmWXkZ9HsrD+8lc/3C2Oln0NaSN90lHAFRUmy+7iFaBLTNOKefezIMj3JItbXx1PMI9aAHThu8V+HdY5qZdFHs8s8Rycd00+LEj8G5fUf177+URXSOzocSZ1cl2Sdke4/D27JutMDJTyKQG9Fb23ZZ2HkPr4pxvSi5NTizBrquCzBTH2+n8ZJhtNUMubw+rF8RDKQW74vrXhRlTwzDo/SCnkJD3XAsE5+4tJ6igyQNlEFMz1ysVkez3vmvn9CmlZb+5UK2B3EI1OyFvTct3AMyuPY2YC/O66eTjTCc4VoRPBwXqIrlif1AnlCNBP3/KrY1jlgpbED/N7deglE3GNsCuW0vEM1rYY7a+QzOt3tofSFDjivlCQGaubjbOmw8E0cv3s/D3rSfzXduE5EL2rJPhx5l3rbFnnjxqJErfPwuw9lAg+ml59WYOscj5Scf7gmNdmpu+0R7uljkcvlm9AoUcbFUn/Z2TRVtUiOWG8+WUg1q73kd6f75br190SYbGwE6Vwf8JQwTclbB5YcG48Tj0ZO+ADb5DrNJDdI6paziQzC7lU1jvq2Rs4HNu8cenMfxb2pY8bVNu8T2SaSLPwoutg90anaHx+V6sTX7SFziDE+9zkWMWbSJoTWHI4fpcUQKz9j9TqFJw+84d+UnsvTF3VWOgslc/VdynwTVXEQte8AaaZ89UrhvVSfBWYWnm/4TMNXbmDEA+kV8bd9cJGxg8rER/qe702tDPtMMHfBOq3dxh91RL1iPuhnj6lsBm6BIxdb8gWPPCp84gxOOmnH7w/1zkXN6H5mqJS2ALiqFa7K/yysF3U6eP5TBDkKir2gMI2lZ65rqzptvjlqxtcNuqWi1YaUhYWtd1rlq2r3VlKMzHN9cQQ5OArKitFBvpOKeQtMvbwzwpCUiAvN+KrzaKqjHZJbfhTJor91Yi4Ure4e6jZxLiupujA2I1X3soMOA6Rc7DvdOYcfNLNrOabxepidXDo+qJ8PSai5dp3Bj1Oekgtoh9j6EO2tpC7LsWaicZlhZ5BjbbWVm9SUt2xJiTxeM/1c8C6kF10u95YhfFFIuI/lu9L9/AX1jHKNW0VuuW2ntwxf3e/kzlvz9lXZ8755dN+2yYPthufeooaIcHaS5+V2mx4aXvT9mORDfUR9TDDPCO6RQwlbS3fv8tTl9FYH3GX9jVpVZmBbXPWLKpL2wDXiz6e067inKrvJFYHPv+KQ6fskHXNYUjGLmZxMGbMH8Mu5qYsHCXv7DVZyKL66C1k7KVycP5cTJxS1+xQB1Sdh990bUNJIF4EDfZ9uZTZJSw6r9FQuMupocysKs1mMD2IF6nqGU/ADAnmALehBB599FwKPJQeHTPVTIOqKMmWf2e7idOXrskzgri0c7rEZKRy+DS+LjGlMpwoZ22jw3GMOkxSkLnJ4zv+W6UPSDue5ePXXlSsbfOaiV4KSsbGvBUzQOyMPH993ga3YxJhlaj/+iCPlxcdVeltaZ8N4Vmj3BOIDDcDTmKzG/7GqFKuoMpZu6gfhoL8lHnuZ0E/ZsPzj+9B6nOvlqqjhW1Bh15X/vnKFXCv0Q+wndc2B8MwrbcbLqDTQ0dU8dlbAeGD8tw4jaXuYnojnS+n5VLfsznrjGxmO2n2ej06eKSJrMvcknLPGqLoOtvFcmgyfew4SCC3h5dz40bLLDNZqISWDorJvzqQwh6ruHMTOHsO+tbc94ylR755LD4yNUOroQgZ7dQp88NJzDPA/N/PizYJ0iD/4xF57xzyGsJQy+tbzspO9vsyUICe01o0nz+3pDkXjN1d5oQtM1Yps4l0cvzdHdHZBqQkIqTMWTud13eaik2wWPd2P20X6LkCP8IFC3s1toG1fmInyi1YzD3amwSQyf8c3KY0iilfFHIRXXjFKTskXqWbl4QdfnQw6vIdf2KcC/TuNI+JTOLvvVZJfu2UgtT/S3ZPIcRzJpaFNF/aH0R6069z6TeQSlm69ewORXIk8na+Zv+kH9j6vOfJUlUmLiGG2PfigEXJUpCiaN032KGiIZ37VPSM7TcAisIDnqdZhiNGQxvZHA1XpZ70bGbSujqJM3fAlu+JGy1eh+NRIF6lz0k1Nqcob6QvXTWE/ezFLB+Xbt+7oU69D8vvzJlOrrq0efvER2+7w39qxoEgi70SX/dnzXgjxWGYP/sUxhp0Vuj4xFEoPLZ9pe35JGTncbKOuoGUbnM1UueYvKtgdIHy/iV008bhGWHyxYmD85nhwiXz1qXKFtuGtfqVRkPjbLI40dqWo+weGw8syRlFHLe1wrHOQFtcCsijt89OSwQHSo6w2NG9Gq+Xo4w1oDWPmePfSq4EPc0w+tMvyHNpW1+bDaocUzqwlH65XJMKEIsl8YQjqPCr4dkgf6PrOOnVB54OdwLDGTPbvUflYNaluuzWdlIVhBEVBIsOVDculD4t525QKcBtPkSnuYwn7mIB3dZVPWpKlWQ4GiKtBsL4o3uOrjXTQEg0jWDQV0NXg/JRwSd/jZ/f+AcWW+c5myaN3UP80p5g+v/A903EvM0qaiELPlS8qvqkfRvZuMnxVAuuuJvqXa3iGguRKVdaS6ZzDq77BwSF7n1VGvscYrxH7sKqDcq25n+kN64QbNmCV7eUd3pyWSo7vaBW8DyU8z/8pUkGf131oUBvKgLa7kgfdnJ3DqXZkfKSxMqZyMzVyOTiseit0qHixIXMjz+5OFnhDiFOet2e0GJmvHgZahk6gV+hM1EtE4yauiSBLK6wpkvlzTAkKFM3Y7Ffb5gqcQgXqkpd/7OaR5zy6Q+gExNhpwse3G+Esrgg9s2/de8F+8iS+8AMZnELklD09UEhUwFZY/XlSlkoNbbUDNWv41pxGscJkN3pL6VvrspQ2VebT6LaaWNW+zwnPNQ/VoQb0rGxPmG4lPeGEYI3ehvt56JvV5IVm4QguIexHh593V3Umt8K6TYr6aGT/C2HgbtsKZW5kc3RyZWFtCmVuZG9iago4MiAwIG9iago8PAovTGVuZ3RoMSAxOTk5Ci9MZW5ndGgyIDE1MjYwCi9MZW5ndGgzIDAKL0xlbmd0aCAxNjQ4NiAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o33A3Sl29KAC8e2nRXb6Ni21bHNFVsddayObdvosOOkY3Scjm3fbJyz9/n+f4x7xxoj631qVtWsqlk13xUKEiVVBmFTB2MzCQd7IAMLIzMPQFReTZqFGcDMzMbIzMwKR0GhZgW0NfuPHI5Cw8zZxcrBnudfGqLOZkbAD5mYEfBDUd7BHiDjagtgYQOwcPKwfOJhZgawMjNz/0fRwZkHIGbkZmUKkGcEyDjYm7nAUYg6OHo6W1lYAj/2+c8jgNqEBsDCzf2J/k9zgLCdmbOViZE9QN4IaGlm97GjiZEtQNXBxMoM6Pk/Lqj5LIFARx4mJnd3d0YjOxdGB2cLARp6gLsV0BKgYuZi5uxmZgr4I2WAgpGd2d+pMcJRANQsrVz+WlB1MAe6GzmbAT4EtlYmZvYuHyau9qZmzoCP3QGq0nIARUcz+7+U5f5SoAf8XRwACyPLf939bf2HIyv7P42NTEwc7ByN7D2t7C0A5la2ZgBFCTlGoAeQHmBkb/qHopGti8OHvZGbkZWtkfGHwp+hGwEkhJUBRh8Z/p2fi4mzlSPQhdHFyvaPHJn+cPNRZnF7U1EHOzsze6AL3B/xiVk5m5l81N2T6e/DtbF3cLf3/g+ZW9mbmv+RhqmrI5O6vZWTq5m02N86HyK4f2QWZkAABzMzMxcrF8DMCWDmYWLJ9McGap6OZn8usvwh/sjB19vRwRFg/pGGma+VudnHF5y3i5GbGQDo7Grm6/3vhf8lOBYWgKmVCRBgbGZhZQ/3j/cPsZn5X/xx/s5WHoDPzB/txwJg/uPz3ye9jw4zdbC39fxH/c8jZtJSVdCUlKT7O+X/LoqIOHgAvBnYOAAMrBzMABYWVnbAp48H3//1o2Rk9Xcc/7KVtjd3AHD/Fe5Hnf4TstvfPUD994DQAP7Xl4LDR+eaAaj/aXRdZg5mk48/LP+f2/1Pk/9/Xf6Hl//XRv+/EUm42tr+uU79l8L/z7qRnZWt598aH53rCvyYAnmHj1mw/7+qmmZ/ja68mamVq93/XZUGGn1Mg7C9xUdHM7CwMzKz/yW3cpGw8jAzVbICmlj+1TV/ydX/mDdbK3szJQcXqz9umA8rZub/s/YxZCY2H7eIy0dr/rlk9jFD/7uvuL2Jg+kfw8bKwQkwcnY28oT7OOsP4gB4s3xMpamZx5/NDGBitHcAfpgAPnL0BZg7OMP9cbCcHAAm4T9Ef9EnAJPoP8QNYBL/L33iAjAp/Je4mAFMSv8QK4BJ5R9iAzCp/kMfPjX/S9wfZPQPffg0/oc+9jP5L/1RDSbTfyELgMnsX/ixpfk/+AdZ/Rc52P5At3+rf0gs/oXsACbL/yL7RxEsPR0tP+68fzQ+ZFb/wo+4bf6FH4Hb/gs/Irf7Bz+mkOlfrj7mnsnhX/gRq+M/e3/oOn5cxva2ZubAf6Qsf0v/mqL/ijk/xB+z4/Cvuny8i5ic/jmzP8jVzOXPjvpH5yNd53/hR24u/8IPr8B/4Ueqrv/Cj1Td/oUfqbr/q+4f4Xv8Cz/i9vwXfqTq9U/0H568zJz/KsX/dLGJq/NHrsA/r5uPFv8P//n+MDPzMDOBW15wMOENsa4P6XyoFcZ3Z9ibZGVHHLqKvIHR3BXHddtXDhLle7xmK4haEu6d+x31uIl2zFr63mKjhcVso7/hkxbFg7Xc2AlpbrxD7zONxv907CLnyvpbtqdHx5DN3tQC67xV5Yf7jdAsDTa90+XefOahJB9la/V9leU5NFXzCSMC2GR0FDQOFxcbAlhIl3BmV7VInfDsXLc0ucuV0ORpIqHE4WPa4Bgrx/bQSjk9qNVWGv7REaKj7E3mkcC3gz5OPFnDacAsxW6fOM5zHHXQTWdIILWxy7iqIBlvlvTu9JXU1W60tIpFq9TwJvhgKrjoZhzpxSascI6HMdW2Pi9tj1hpe+RyslqRFxsHVXlfRYUkOr8ELPzAEqzEzElIPWMOqqyPXN3ITIK+mkty1mxaEf1YBnqzkuq19yLLjAnsWFSwc4wVvUgX4Y6/SjBIdjS09aKtwa+gKWCdemFnP7IUPAUJcuTlM9ExWZBGIYEP59TZuCS3VR5m6vgzUycVU9sPtASmY5C6M9zhftOnXIcFluuhAc2xKAPJ8IEFuL6I7DojBDc5UkcjcNWnFIbSEpx8i/3mMF/gVceWkDcuZXLZtPbsbZZhhDRcsM9qvgvqjJX57GvbDsFYmN57SAMfWDiO10vdidV7Ropt1oVm6nsooXrduHl8JHyF71SeU7S+CX2oUGWyd3jDGGef3/mGYKSMak99+UCD2y15UsONVQMp+WW94le4/HTiHI1l5XjBY5BfBzCsIFcVlWyc5a6FoKVjk4a+aPWufgX1nSDbRFU7BSnctz17/XVkE/L8pdDmjMZoV7M/Knbw/DsQJYlmEVqOy052A/PmSGWJC/DRVp5yytMARtJpugoNtN0HF8q5q6e04Bi8A5LseFAoGGi4zDrU5JOH81pueLSaX12ij5Ug3pbtq2Ettd7UefGKGAeNiD9pDf/kAPP2g5ZP89qXGoLvUdtCTr61Lk4WDMAeeCbcSofSh5uXs6yqLn6WBmL5ohCazUDvYFB279MLKzU/IKvcXpwoePIBArjlt3am9w9EzVEilT1ITfi+Jq5s+ClYVkVSMJ8broSJVe1t0oXFOJ1drtgj8MYzXd5pNeWWZsqDtIMguOuY1lqxnfdpRKX9JqUjp+aYR/JhTFK5P4sxXJL8XIHpMbVEIM/tQtk8/AnHiQKGln+x+YYi8TUHGcYroUCGTUKY4lgoziY35ifx5vVPU6YAsAq9bIvrgcAg1rG74WI+3ecIio1E+ylN6mAMDldprA3Kn+umBdKwheaatZ3ACr3URz3I7iM2VuJbMOOrw7JsSA0ksKYZVb8Axduy6ibEA8okw9dDy00tF0lh0oYdin3k+KGJVNIZy7MOvvemGI1Pn9CqLclyk8nw06DVpqYi84AIEHKioEQWWXPtKiqvbPmrvvImvoZ9Vynxha+BaZJlNbpMljP2znoLHg3cZKBZVtjWvvHTg+SPObsD8IjDPXemZdMaW3rVzWUF2qUCF7QlXxPYJzPAxiwNeSzwlS3SC/eNoIEKmyk/uEnbyIpAxWgvyYfLOzPRtj09dfMApdyKIIXiKN6epHFZysLuN0yXM8VWuXj0C6nt6QUgzZycHDwxgqoBKM5krC23IKChsKgxdNd6p92Do25YlV/qv24cLw18f9Pg10NQR8Lm8huf3N2KxgCsXj2wh5FCBnDs8xJeY/W08Vov7cgEv9E9LLU5ZJFE7ZeX0HgmMOrzocPMHOW8z+lbKNhq8FwehUjBrz1RF2I8Ec9YkzPGPcaji65ijwj8fDB13kXt1c7z6mNLmhDD0yclpn7+Ve6ZUCZYXrP65FIB8sVFLAQHWM1OxEEALUvw8DD34mRSlF+iUfSt5dh3fXhAaXVMmupNRdxyrX0Y/JmIoCMA1J7E8azA16qj56utkxRVYYJAJBjr0y1SSg9M/Yqw4pRtYghrBaCmkCzxCQrhcwf+WLpLL7FDPgIsSPuzGPDq+dBoV5YwYNI/lcd3GaWLm0l+Wc/8tANKa9nW/KqA4Uli0mcJ0K8NgBdmucL5ojyUjFzLxPrGBVDFPEzf6yg7YtJPnTXVEEGA+Ww0gloo49XQKpXEHOuatYsZUDet2rLq8JVJ2xCayoKGA2O0/JBHtzbIEjlHO8lZsoskuc0TwF0379xvCWqSddBo1GThVV694YA79Y1cKFyPCz6/Mkdlv1n8Rumm8VLTsnEAZGmiy0tPAgVTeimvx2u14eC33KQPqah4rbuvyO/Mwa6iw2rmajZKx2u3UHZlHtdh2W/uXTd09qJzfm49dwtAB5DshiCeVKMGekTPIGJdaFxtHK6zLjmAy17994upqRosP2zTsV704M74PsdifvtRQSgx6kuE+F1+gV7/wxm7iADQZa88BY6XcFg0vEIEpJ/X9GPkrEykpyDIGNfm/iU5nHnEFDQqFKPGv7iWrctygzmhE4jtzjEzmpxgxsSVGUSJESdcUmRb5t7FAquumnQrg/hV2LBHMJ9MBUi0Vydjjrk75MOV66Emk5k05k0btqpBYX710b2J7K+BYdY8auJSBktfngetEUjfOmYJ35agW9K2lQH66TUha/sPUPGv7gyQC2tR1W1KNVkXJCn3ooE2xXSWGnzkZQZqFiVyx0vNrq8QNyZe3ILn+o2zni911LyVeax1a6dHN+MMSw9+n6qwB/VQbgMnjpyrSiiVkxeZP3dnzAjL62Wbz2v9Fmz20COKsmp7SPt9Ya8u8HQemL9GMdr6Sj3TqyYYjxucNsGIgWjEIgfB2OjePG5l9CV0Xaqq4u3wnkw0msHQgh8PG7ra/BcNnFpivbjkF//nMGyzDGlXcYxgB0EJfAv4WY607y7c5fGxjUgkATfTktrO/UHkC3m/Aec513K7vYMPGF1ciZY8x9aEVrCZYnsmBGFcNgSMD2e2pzV9yD62Pqio8QhlDUwVD2vpvFRp1KxKenywW/b3s3VzD3C2ugOiL0sBmzwFyVtfM6l8GGZdgjxDMRc4QM12xsRKkojNUJ/FI6Ym6tlWUpGKivMJkh8GmPM5ku2J28sC3KoEYmlJTAGIUKAvjs10rGDjfpvnUz3OIzS8Mrxt6TPhmzKsTUc/PfUYWR5hdkCozPK/UjHv74Polh6hyXcBeQhiAy16N4aGDiTo7IKOnJPYFrDqy2gxgEAtWXxXFXA54lzIBZTjoLHSokGROXbQPYiYcSU7lKwBywgz2923ns9VxtyjreuPCiplziEdMBTMsnib58OMO50xJ8ZcA2r5aaLekfRKmK6n3PAQFKRw3UMZLGgTA0vtqDf6QbLqqNKrXm2lOcu75o9b9S77WCA9VGVpElbukpSso8ZFuGJ8WrHIt9NSk/c94G5zs0FX8AJaqexfrnDwB+cot0iBem7d6mxXI055bX1xZjabOgnGRKyP/hdtdlLWESy+Tq8dFQZKrFg+v4y4TopG/MLHxm3qlbbu2B0eiw2O98NQTgi2+fn3UDGjYa/Titwy5uLDrqNRritGNlYnuB7UOT63GcwiHcF/n6E5vDGD4rcb3XoaDeJ5f21lmYtGMW4BQxQr5n7F9h2TMAwDX+ipYr432W/Ztc9XWQvulb4Ld2z0tFIVHPficDJLbFA1dbp6N7uxinxHVM6S0eCM2SpME3AAvnBQsl5eHudjdbboaE6Rv/XIK/MoTXWO9+qe9U66F991MF27CVm38k++bxrIJQt9Kbovd+9X+NkKFeIrsWaqxQvTFj8aeeYeNfz7fJKi3Ui+1KQ/1/+YKf+M4NLYmMhflg4zI4PVab3C3BxVOSgmBOW7ISQEKZz9AYYc8qIDU+QXKvfofXiYSn1aTfT8JKP60qLM8AiH5svnyC1CpOQkZNszVlyaRkoz9CfMYLqlxtD7bou3goxw+Nf3kKNuknqLRsQAKvN+QacG944I4GKmbL7O/DPw/pYScgYsl56PDOSVZlv7G73Xt8dBr6jpnmhI6N/FNRQsJMmFIMO5zbUNXzRJHV2nXgBJdjdGKs4spRs7zi8vtehComHU8PpZLYjA5q13FX3m4i9RE7JAtHPv+R5kC5GGZ9L5jZL7czHzB5LNDX6fqIQy5UU48B2el8tE6h7Yz5H9fqWSqNEubkTW/mmjiTYVSvAWBDtMFzgN/FALyNd3cQZ66iBEuc3fk72OiBMR1M7pyTXKZrhRrSfOVnU2mm5i31EI3/3ROba7N1pKgCHzY8pO49Wny2k/JW1MJu+2zrwLs2B9SlTaH8Fe5UBR4A+wh/Qw3ESFLQ/Ih5CpOfI8uQW4joW5uByOkFnGHgqRast/RETkqY4q/kAQdhMUjEpNyt3omAfbaYvXsHHht3UzXp8qAAXjGvGp/9Gv22VA4X3xs7RBgJLSi0AaGjPzthZJ80mjS/XJSl04+lyjgO4XyGwC+Q8x3wSEzlvJ25eDLDN+czkf5CEA3SnNpgNKVJa+uOFdS3nL4Zq0WwLaLv7Zp/MAc1TZzgY6l448Ma9cVpfLQcjSt+Yjdrrvh/7d3RF7PALC9v6OT2pMC8utlFrvMXMjRb/yVtVi6IXUgkN53Svg3+7L5nBzzmrLvX50zpZsYk0deZnN38OA/7JJMOH3Gr64Ndp9lDKcNyTHTrljH0B9QoabitpEk1qW1M9kogLCaL5rvs6MvuxPuhJw0BoPgkPjcL8obI+ARzdSztX4rrSQZdHCrMEtfHr6wr8fxuTz1CRapMWaGTA3ponVS+IunHqCb/NjhEpNnk9IdSYoJLq6y0aJyxy3ok1AsOLguip0HLCnBsIaIMvUtLXfI9ujiyiwQRhNnjq3PBK5uHRaJ6eqgMjRJ8G/ThMxREK2yAVq5jOyNJE4Z1GXDGWgUL2gDNaKfrvGg5dXmlUCmZm4qqsu/NITA2nKJ2SAPdr4q/oCbksjhFc+d32Swwv4BiZvd57SZDX01iUTvrhUp3fsbmX3/aBfbqwk727LpFi+ZSbXRiBBSroKAF7iQmBQU2fwfKR9AcJUiLEmdUEhNQVjHpGo52+AhkAaugW6wBFHxy0+/RONVW0Aerz1x2/RxosYxbbPXxrm0atnHxCvfoJYPPKH8V0IbTawyrEP6feAd8+X2IPpR3NtYrCF9l5UfNu+K+bzbPE4Nt17UWsJy6P2eHVxBihYtx6absU8UP0ygVr0CZtH1spe7EybODJT/L4YlNLNLyixs0mSsfQJTuWtCETfb/PpDfqs89lMWVnu0/E5+nLHlQjAcRUkT2+6CDk+YaH7Qar/5NlfmOLwpJUd+JXdBPW7oJZ40Fatm8NJWr8t7Wzu5FD0sYrDQQQR12N0zYs0itUja2PfyuVGfehsBKefhFGC2j5JPpTwdyeZEYialV16+3v8mM6CvFPccp/93aFtzFvNfmksLZTZT1Pqfl1VtwbfIVXOqX4YXoGtiVe6Sg3lS53LDU2ZvkOuANS6EhzM+h3az66cr/3bDekOHXQc+nCgQCR92bzI+6dW4qPq0sXVntYVvN5x0vQnfghCaodbkAusOUOjBAkfP4iEeqm2gFodraWGet4GQ6orwuoM5EoKZtmBz1TKDZ+97y9eQtkq2dUEojZDna+WOwrZ03v69xGwL2BNuJSAjvIMeihkNGVhHwbLahmxkj3BwcSAuwLdqZtflgBpn8IG0esbd8aLDha3kQQ6hla+oD/QS6zbX3vqmUsZvOrzKiB5SqknQDL9IiOlIZp/B7ZCnTOWjQWU9ZJMZVi5R3hkJ+ESevsfIXiK3vxCEDX2iZruxqmCR2npSOOt20n+hG7zPTGpcDfrXfZYleWq69uujBF3k9cvzV6XgrGkKVOxWkgYLakntExd09WsBOtufxo2jzUK+1cqWwBIN6a/rGLJU42dCobuL2kORytMRT8OgWkLIe1Vjt1kOryZPu7X7dbFlkTmkcYGCBsuIaSXiJoRhNC7WnokpxThkb7ENTCx44i2Q3YFkXJXmKveHU8g8rSXnmNl24+SJNKimBRGwb7xhJmaOaY127XPtr8oM/cx8NAiVPxiNd1FSApuEu6f7fWGuOikOdy19aTc0Nfqu3jVSYe/Ed8Eb35VwMX5vgaJ1nbBfpXxZeoX7S+ogVt+b52sE3XOWAc6OYqJX/yvtQ+AbMqOBreRYFRX3wonl9qg3lJ65e1aiRpBlW5JO6NMyJ6HNatNvL1sQU8Ez5dj42CPaXN1bLm4WE1U5ftCIeQv6msMnNVmq4fLbe100lgNQ8nACxJNc1z3obMWO2GF8c4Aua2bnTbwV5157Rm5VcXL4sJ7T5lK5UQagl4lUHBWEHI+reFOSypRWEWiWohpXKTMM+L3Bixh+89QM194euNjPwHOC22SLdDtf9s7ER2nQoZXwFmKcJ436Fu3Ha4QeHydFTAWDKqXrkxQDGV3QFi/2VaUKb24L7xreNuPdk6dmxUDj+D5MsxFZNP2xioYhqOWBnFG/6RcrL0PK932fBjSICJ+CCnTTencqWMMizVaq6g6xDvn5yTBbfKD7KG4wsQkFbd9Ia3bVG640Jh5KGWsBzUqfd1yUGfxol4lGEOmZBggQDsnWQ4vEbuMu+PNK0plZittomUHQKXPXArjzF9Io9zOF7dLvbbHhYhmVJHceZ8Q/mJWXx4CMjxYeMiapknoAyfLm1oHXTYDqEYUAPeIa3wmecTMjxlGQISXnxC+TZvjrblfGo70RTJ+32FD7M5nYl2NDXehodFHL12DuLO6K0tZj8pkwVQZXLoFUE/hDKYMVQ8TxMa3HhBbsBPP1LPbMn0f1FIBp5v2kTY3DvHOs5xEEM8LD9LjCP5sT5/hw6VHVCOaS4/dKTIPqjFCSqsQVKQz1zI8kmqRVLNOa9go+LIaB51VpPQlUhReNKQj++qaRm5eXGwFpW/t5zmequokiAMeUNE4ArZcNx1ajZ9p+fnmOcDlx8zg7WAvcdRdM7BCULS4QclcArvkLn0Mdo3R6DSFWpRkaQNUzPj7LQzBeAaUeJkH3rI1xWnrjPbpYN+5rOZrAstVRvR6yn4ek7YNUKg7l5Hbn+Pq0Z2vXxkAAs9gogru7/OWFuTLigBS46puEDtuUjrQX4VLRkEDLfX9mreS5+hc1E4qDbe5iU2sozIfv88u8R1pivoZck7Me2ClDjcQR38GZDfbH1UASWr2SKLbZGBFQQxT9GJ9AcyK+NAlceZiJ6Q5Gac+HGyqRgeNS5gzKUlWR94SP8VO/F7SUSt7LvduJ9eAtwNv15UQmwloQNkD31lfrbsTlJqbJZD53o2TkfhmXu6Ob6wn4GP4/kKQPj4i4bIved8stjKX5b3rNZ2L1cnnGDuPz3Phz4E942Cij+f4tYt4LepuuwnTWgHh1tB425HwHWLIOjL4kk3zd68KNsSzwM2beC6Scag50ogujbdhR5OaOSbo4C//u0BqW4hs6NDsqQhgsAjmmWDD0bBIz0++vCLoF5uOp6c4Mgz5tBKiVT4XgKBL2uQ2kPUrr15rsjSL3ozBD78tLOQCXAawxuoJQd3JOPK9PPbo4dZKt5EdDfyNh3hOrqXgtEszaQZXCSE5H0z8ms60yW8ChcarfVnPpUhcqV9yz5sOpQOPE/TeWHLRwL+hHvU6arahRr/wT553VDp4RdrNqk+S3Xs/Ii59cT7F2+kzzoeS/x3wkzeNwd9VzHOCMxWXxg1LOP00V5zmkAC8MV0FdBN1XuxuEIwkx8ob+arwV/qi0MGkKg8kdS96QU+ksqrfE0MM/DVQkk7XuwkeFNTZ5L0kRKZoqnIveyVptoOCOAObeoueVMesDiOUL6+HQK0+liP+e63OFL9EMp10bCE3hUnGuSwE3qIzJVaj+/iboszQ0+jtF9Sfr1hkNC5SAiz0K99tc80rpAvW1w0hcxTiswIYhm7o5fpVN8X9DszQYaXWEgK5tApN0ZGKv2DWtRCblXZ4NsF7KC6TZR9TcQXhhUSIWm8g2ARRy1u74kZ/gl0Vbv3yuIVsb+HMC9VLnJMb9mitIckA2LFxEXSdylKbfNMW1Eg9dwDLNosWWLpKiKx39WEOVWmiHWCzDSBIE4gAnSVWb4WvCilTKmYnZ7SKqt4ZHO371cBGhZx+nFAaZ2ITZJ/6Ep+bbzCc/FlUqmrDZwOlufe0rgjY4UmxWCYMKouiqTK1Lg4BKjv2iNrxvCiARbKrFIQ50myo/FXRSCwJdkV3GreE11NM2t5c7Knj3EBla3RbdHTQfdXUhpBZrtTaOn1/x50qkr0ubWmJovZ+c++V45RrAyclU3wGZIfSu8ZxBoM09Q6zod6YfziVPxqwpIXmBlqXi962WNeyCUF0F9lUk5Hk8Mhp6DnEo86nXs4OxuZjmwHtBc4Let3q0cqOz5h53peO7Xw6OjbJ5i0/gcorIb9Uym2Kj1A/1X0JgQP81spD1PSsz8weS+k9zGi7gqHVGc1WxprkKsqx5Sap/MMcbaFSQHz/kxPtmn/k59v42m86k+xFNuOV9+4JTmGCVEmE/it7i4SI8hfHnR4adxZToCgwIIndThk0xlnWBrSY5FpSBvfczDKsC85sPYlYWKf8xpDhpbOz2dEM69lDSmgUvkVQ3W+TIkuzZ1Bn2I7tHII6ya/0Il4dmPSGu7CeZwncL0+mnjUdKBDtmJadWsf6tfAn+bXVojn6fO9V7NFBy/XhotxLoUNwC4nNrvTNWZ+w6Aty03JObovdybLmv6rmuWIZ7baWJJ9ud8+C5AXO57bLuyDfZ6ItgM21etJtJDBKRoSd02oNyke2aCHtnGpVt/I6j8XR6nhuuVXaBnF5+qCLJ+9qc6fah0XU3+Ywe8VtIsVabSfNjIL6Uw1VmvfWypE1fa0sPg3bJZw94zd/m3elJEUiKud74vopW5mM4IwysuQqaP07j47g9oB7KmBac/m2tn8/XiUgjYpB1hT3wETQ/AGFnWnF3OgS5bAb2GfU7jzPf044QbumUCfY6VJDEDe2guKAu/1rKdTWMkTFv5EiktI+AK7wpOZZCsphfp5ovQEjHp9BGKZIo8ZeE7oJNovr4AVWJkh4uj12tVoA1/wHdNi1fkUhmH4/IuHFT9eljeOgAXu9MfgKCrFl+Qe0FPcL+U2yVUzshnQfcovrrz+kgvqWWRHHyjxYY1PVljyLz36qP5K5GZylFeGn6k8FrR3lGZKaBGTyBcrdRIbbRIPR4YcFmEZaGOHyY3piim1pOJE5tvIEIuWng2SYU0yoZqc08cW6d3OyUEAs3d9xmSYWBmWiUZKNVd/vYi+zKzs1q9Iqu6xm05/lXj61pP8I7F86+Oz2XAcidLGyvlfZ1SHK7BM95V8A99ZC+jboGCEJUyx1FIIi8AMdHg7HtPxrfykqsVfUhpngfMQCXdKtPgyEMnN8jjnVF/eWaIsJdeVU5syeej96RIMvOZGFxg2k9J8FqpGl0w7L12r6dGXCujW5mS/Ki2xXOsNZoSYe/Mv1/KlA31+02cPm+HUzipylwl19bfiMTV+d7TLhvdteU3vJBIWjCrGTnbX66fyGiChy5VMSFwNNukjsBCabIXBdso9Z9TLELSYZ3RK7pDcVYubrVFrt9OJnM64omWOCzW5rxhhoSF5BcbbkjQiFtd7iqr9BZuUlkfjnbrcn8NcmoCc0KQfz7Wh3NnftjFfFJeG/erUcav4ITxHz9zaEKhOJNyzybm7Hm2r0lc/gz1NllFHKqkjeMI4YKZVGBNZZBhdfsqJ3d9oKX6jk7wFe9bvPgxdS2nAWuqSHP1X2Rgku/tQ05Le2NUIzG4G9Y1IVUJ5g2bUgw9rN9CoRtBOsUGuFRUaT+EK3LSmE1VoUXXPYkBvtXloJq4Jyi9jeM/aoLAMGr5ogBLqNy5uo4hcQwtN27g5jIDuL3ZjAEtT+o2wShSLCFgmWsvHOvEHJghaLtgrZX/rR2FGmNsu/Nbwi7jW+n6afv227wROsljfn7t2zZzq5iSWNIcLhy2nByLx6dogngc3+yoDIAa9jeM3XHPOJt2DQX57Illq/hOxKtl278EottKozr18c2TejD3cPBPhXX3vSpeY0ZhDSp75lBwhIstiXP2xKqWxasEpo8xM1aOv41wfiiEI885qQkrbP+Qk5tTpqWyruwyFmmGyd5ctDxnaXoIK72hOMDBCxq3+3nXZb/pSWWnKT39d2gbJK8NpBdRS6VB2yEmnZeeOsl2V+9Ht8/vsofkr/Wgh6mL+gPkkJwRrKLO9D1WmFXCSVxaHZHESub1NLQjhPLfLPrW/Omwvkn1vswj/b8gZeJ6x2WsaSVHMLeDiVh6OmLljJG0T6ZwYU3b/rKuaBdBtaBUMIjfmeqV5vtZx2SE2MT/YipdV6OHdWDEMzjt1Rk/kbBY9yZ4LsS62OPiVk9EI6J2vUGpgF0yLr6v/sNR1EPz5nX+Ty+b4XUfNA/7NCLTuioyqVUh/JlRGUDuoFwCpObrOXDbKMKja6OKkJ640QEZZ8FMoAV+AoFBAu9ENWXDxId+jL+iRr5BL+syUWwJhi8mfuffFK59a5HjX/+iF0a/izYfBqPlzwiAEGzbcG3nJMw+YdODp1RfPDH01hVTtjLkvaTpGPtVbffPvrWzN/B6NrK6uEUFzd58JI+XZ5Cj/eYfAbfCBzpDByuJdichnXHhUjjXGxP5+oPVYQ1tngnagPH3sRO30xBsWSzdeKYWQEfDJecyXwWyHgYgXTqTKdV3G/8vCb1jNXbKwwpl0fKVtMIG1oJCya1T1mAfDJ4HFIOhun2Nhe1mg9mDxxHltH6jpJyoCCcFtxrSrEc7dOZGGmMbPFjyyYyWuxW521tmfUYfCkPGqUuNKu+IRJcHAXtJQccjZDIZglnFV3r20Smii2U26bifZnJU4ldRPIhiQmAZOZWzRcNy8Pu0pqCpzCe9Y8CLcmQJkRsfOFj1Zb2bab4upWEVmhwPyNrTIm0AJq7Ov66FFhpKSi5bKa14Lyhj913H6+xeHaJQI1JctseuNEQvxrp5pZYTIN42adKPYt1iSXlO5WSrPPUsbYzWW2bXtb2+WydttpethEjTuSyCz5wWgIMQt1Nvt3vbVgZnlEi2pzkXCiSo8D+IhXgzVbKoUoGw0aruFzogDs0LzDI5SCz3twuGPj6f0byHWxurJ8YQsyFFAI7SnVMFrD33I0xnE2BqNaTV1dr7J/h6DIqLUOz+dpoVVR4pL6SiG6eCq89lbSHATzJ4KLmjDjoPkeW5APHPPuY0Q5/MaIV3bN/H5bsyPO04e54em9aP5cZ/VW9z08tYeICzTLwFMT4+lSUrFW6nzVcUdjssfRsnvAVukSWmgpriD76nyf3i1w7wuqB40ryCSs0t19azAtuk48TJRy6vx5UlafFwePDYRy7PjY3loXCbfFFpeF7kOJnElT+RMMcGyt8saJE/fRkrB0sABmZNpJ0VznPoQdNalNujA+wIkMtOOKSUKhBqJdiUYIrVSP3XpEsUxmQdsI7NwWwcFWPYGsurRrGCE8bsTotdJntjDRv1ULimlt4c0yPNbmXgB005Z4dI1JAxaCJQVjlBU1+HdbuxjyV+RN5pgomOHgW+1gAr23TArHZcgyZHJvk4phBvHQDZ0zTU7l+s2jUDZ+zvLcthJMkES3k2kL3VNkk/c8nE1iMN6vaRCLd8kFCY+078nI+q55Nu76xTsgkTn5kohf3iGTbE/82x16rsIHsiLgyMc8/QOwhN49utJ7+I2NU024rbh3J6zD7r6xOsMuGQ4Qz6mdIpgkxfTzHSSuvFJdJAaKLzhjEJu5f7eTKxM9Ev1Sd7X72jZd1DJYWP6p6NapPN/RKbS784Tr+Hln4cCbzvMA7TtwqHY2TA43Srnsi+XrQ4SvmkjjoNu0q0QGyt1arCmd2LA65lSRuF1Pxmf0m/6PV8lO5bYpni3EnfYR5Wg8/KERpafICA8EcQVIe+UdPoLO/NDGo3XOuPLyr1IfNSFOA9Ry7urTffA3Pew2qla0XJZRZRf8JmLXNuAehyost2SsGm2HIFL1oi1PrZ0EPi0X9em2p03U5Hd2iIL+UmPgt9lmtXD5/Mdk1SpxBlPSwjLwSTjpkabgfgR8MSNp1eIl3Sap2qF5leCFtwGhA3ay5EZ6L4KOX1pDl0+Go6x3tfCNg3lUNO5cZKWXIhVxCuua823VrBMEQpScv0iStYOED0+jiFLMzG57UrrCtGqJ6EgUxJTB+UoAL5ee976GnpV5n7TSh9ZUU+uacr9M7j1FyM4+wMPqJEFVufO9EIvfeMXJH+lHgaGDqsGdhOQwlP/eWSgs1AKXynKC0vLSX8rlR09klKjKjeAzsvoMou6b34kls66GApcfT9Wi1c9lZb3vZuoRKyS6ARPMcI8i2Fb23D1yRIRM8Cl45DqHHM8Gx2h8IEax0uoJmyEKhR+nhz+kyaw2KFghS4XoN5RyJyGGRbwKGmKYz0tmXeuC+q3/I+6c4oOspMHAb9BdrCLrymKlar80CpUvmQW/YrIM4h8qNXKof8TAyMIXfyfe/H3T2ZymivLUngRPBoMi/loqydWNpZOHxYaN3CX0a7OJcNBzqvBXoow4LTu+F/r4/XHt5gwu8gwaSgascAkjagH5oXQCdB8yZfAMNBlsjh0KXi+XwTYVNZbRF6l98U/YM7xshPTun62vKR/7vmJ0lMSgqidmQdSuBofirfuk/4TBFr9Q4o5OW3YGmYz67HzCmkyik36ji0QBi0sgHcAMs0VJifXG8LUihsKDP+uJHJYKu/ScvgZ8cWz7C+dTM7yywv4G+3ZovAk/ZlYHqgVdx2Lm3gJJmE5w8+JKy0G18Sgpp98War3lMdiBiuFkQMrFhs7sE1IcAO6a6FEMEP9kfqKwDgnZ2XmQMXXW2K3i+tR5c/UM/TU2UfWdS81fhNu7WTj8Zag2xO5Vl+1u8Jm5bEmMkOSLYQy2DlHEOEplgXKheeoLr86RNOL7sQZ+VTgdTOS72K++QJ0j63dIs1VoyuuLWtnEgN6Nezi4QBggtfZk+CkdO43b8LJOxLRZpANJWALWJEJg+Lx6pGiukSIah+rY5Zxnr3wCZwzkhvjipGnfM5OIiFMjjFEmBOWes4+wQVjdOwTBVkXO9Wa/a4VpdniU3298/c2QoBmUM5ONDaE9DzWT4YIK5V3uQVeI1GzIGONgefK9IeqbS5T1ySkGjQJahaLWhhV2xMfdt0TocNfPlgjhIP5rQen8GEt1Z3vjX/ADWdaO+8HZ4mvj5FK47bvT+NYO464hGqfDNB3b1MIqjTJLR/wNim7gNgzFObscYUsSKE/vo76t/6KLDH4wfVz0kDIBi0oCYGaLp728Me6+Uw2ODVuqrT4IeS5rsP1K/g0DgzPDmIrsUHlGV1Ne0zdsaFTbxzgZlTXUXZWjsjY5NKFl1Vl9vC5bNWcfgYXjQRGxtqsQ396u9Dm/v5jzkEqjSV1Vu06jJ3JpB3MrdmzG/Cy5GVdB/dh7xp60KjK91nzPzTnzeuDAFUEFg1A1hY8FoGp9SajZ83CDv/zLRbKD5GsvJaqWZfVn4ouzjrMgHM5xubkEWtOJ2wY3LoYhufflSJaa9wdBfrz4+7IRxQ1WGWXjZxh6iy63pqUrJ9gyZJeE9JNwd4Btr52mFRnzVdXujxeVfHmMBFY0subB7p2J+yWiw+0IAgWKRQxqk4LIbFW04Eq56XRt8VbX0l+nGon7CGa2JgkC+XDF4VoqAKAPVVfD/Gyv01BDWxpK/biz0cgyshoPS+lNVYEs+fpWsdWcShbBMY5pONXXMHRD0LQ91u5oeNSjldZ3eqTCUkkNmyp9B8LJVEgRoPFbk+7nx038rsql8LohH+1vdUXpSclLn6koqjjBcO1vYMroo61ETxedr3VHlJOTS772ip2IrmFyyGKdfw2hzbnqvOAqwEoRPEQ2z+ntbsNn0u9WKh9YxzTTXki6DtApJv62Ysu9/fGvwa9WEHkf40iJ/JcYRc5H4EB/lFWetq+5FPfaYM3DEuwRuFc+L/jxOZMdqiKpibfI1e2vlq0Y+zzTIp0JFxIlB7deL9pz0ycefpGAJw/rO75f8SzFlk7Ja0Sm2JDs5NGOXTZZsQJFhBkMF6Gj4ngxVwyhh2XIOu2exBUqR/2eI33D7d2Jzc82N8WH5Nl9KCeUxIq2JRJttV05qT48+qckza3Uo0ZoXHhQctc4xckOjaGaPUKWUZ9THMpkwHCleYaaxwOGDfpMbDGBpJYLxuMpG1VtgFA0KTURpW/XUFs+O3Acb5w+mBLcKQehtKY7EYPaD3mixCNTefASygNvjU70toA5ImIggIY7tfP9KMki4PSGwUuhA+X5oAlntBk8zDG/4yRSOy4sh3mjeXII3CmcB9TtivIltaeHDZ+PRbZo52Ujxyamvl8NDKzgkJ5hU3pLLe6JhJimu80vMuYoETVJFThOsNTRqaLXP8ZtIBHVwO+uNFTxbaYZOVX5jRvLaqWG2WgyIA07aInGY2VJgnX5dibZMf4Zhc6uuPL7MPCAuSIUBedw1xJcXLQE2z7UuenrsJ8dIg6dR0hTfbs5uvM3oDdoZ0dbC6CR6nJugHK9FE9iPOBLXJEW4RcNU18ajxDeGU5NekNfZE9VpqadmdrrSBUHW8gTr6bg76gbvXf4bbo/HNDM56EjeMWT6i682yO/T/t9piWtzWYEdFkm4lpk6MIcwZ6AU+iS48YGTmHPfvwicxfJOVu93ZQJYQusFU2BWudEK3XWlo88wVmQLF7JEvLHlOch8P+cSwzppzmf9qDHo8iK4BLExAg6ItxE1izWurNL4oRziLPPWYAR0TrPXFd3tZnzZII7wu765oSyZqFxos3n4MrecPuTaDB5hQ0dycL9N1Wcl53v+rRspphXxThiCLRTSvPLVXrvCy1HGzHY5KPxihNVBM2DWxdPj3vcmXJRxLcSVV5QWPLkQjgXY3HTDi5UmUF+cAsX86JR50OxbNvpJwVs/qD6LeluQbJV4WVdTpvkgEf/watdGbU3pfqTHaceaChavJMHi+iCy0mR7zrS0arMHGJrqL5JDF9lCAyHC6I+Ob42LBjNr2vmY/CcW+BkUkN8dp5S4AhgYLawkR1UEJdNOdtisKSuj6VSJnQEzOPCsavYA0ZjyBiVqRFA+rDcxK9hP32X0sPjjV211eu6R38nxULrSFiXoo9tUvV+mZf6SZiGByr2e+a1Up+KE88ox3bENsHeMUO8qMVWO/2obfJN42iF1IA3DqZvLiRkS0JZy2/ulaRs2dlXTHkCGoaF9gZV3pmB0M/coLoS3wab75v8bzdxqFUhyFjCLRpaFfQRSKZgjdmnlz2s7KaV8aFE6iL2R7mr7OpPd96WpHQXy8cVCwRCYhhcB9cz4IMN0BQArCZmLHORz00Rg8tRNEQwYG37eitXYYW8nYnuoV+OqX4Igs/IcEcN9oLcKen46BymdDp0qJMwqVc708htZRzJqzeYUMduGlfFbPi6y5SkG8EdIygWZklUL6stKeT4udXqz9JzHX0OaHIjbjulrOkgjtbYq4ZU2P+Wh4M5C/XQx6bT4yGFz6TdzROblSR7he1ozD2MiEB4fWZ9gFQn7Ocf/M2dUce/egjDS08tlnranv8gI6gEvPMnftzutAB3Up4KIcmLjP7gvqR4/F38nuHufgya9Hc2bYtRuFKMTYiBLTmsOLQlVBFp+VzNTPLFbL466UnPdzd0BhZ2lCYXcxKfRV40aL4yMvNzpqem4MgfTWSgq+6dP0sXOp+7d8gF9xFYMhNUwZzrK37TDlYfQIHnG7t8o+zjzdIPZeP+ZAUrPbuw36OUn7tzV48cdC7m645qTlGdFv7sd+f08KvVV/ksgRn+jFOSfexXzSOzUtPEU+rGsM2lTeNGsGNzjcDnQPefsDFFe/nRVanwG9oKkCca5PfqE6R5JcDXPnF/NWoS2mVtvQ1kiaOLS0e6kK/ezjV45xLq1TT9ymQ/px0y40k4PPUp4km3Ce1I28wuKsMnlkP4qkPVndKdv9IFJOtCt3ln4YgqIQiGOX7PSB728xZzODeT67LoXxpgVEKgCIADwaQEc2FSXyOt7McNXtpXNKSHTSBK+/ZtkfhEy5vLO9MNF32TiT/7syb755XzItOVo2dElBdOuv3LhB9KTFGExmrOOfusuVRs4mW9B017974jQ+sz7tZZq3ENrQ+cK2QKdF1uzxF4/L6g7E4/frVKKu1SAdK2AVyiAzGq2L1hB8jIVVcdCQtsiL6Vxg2M8XjdHvgZ8HcZfYSJPw0mR/LYMNSGfw8rsVplkZXToDZW2jHc/h4moqMuTaU5mlatll7wobW7zDM5x3nG2recVrChNQCeFBUilenYJfHy00R0miNy/dZfYy9+g9JiybLtaNIKCGZVUu9V13XhFUFsHzacGuJOIGxT1BpFNDmuEdBco5udF2BFVIH4jVaqYLTSt01oysDE+OWbdxzyfRPmK3734IG5ulUOJN3tSDZdci9k3oEKExQfXQWWcigDdmcvLjVU86QcUfDDwEQCLZfNrTeK8uGO8A3c6gKjNdqyR7xZcXbQGNP3cUIcUb42Y2y4Na2RVXoUWYvgeBEgdX4T9yLJRZ77JwxOmmNIsGfXujeuxUera2icfqFulki2n0nWhjH5ZvqM79HV88OMMEkD8jPo4wMjYXwpS8McKr7QZTgLMO6o0uuXwMRbmpICZoYrT5gmasuAMRQAgJIvNDWn8PH3jBs5Pr7uQth8O0U3xWulHdXWGR6/Gx+WwIi/IIRGhpf4Ye/sRaTWmhXB8EtnYvOkGJGS2i4yG876ZC3UU1ROmM0ZQ+Yp+D07wm/M90P9St8LPyllvwbfOjLL3KHMmvZbCIt8KxrV1TXF7zjEjhfyMRAL/foCDjbkrBtFCVPO2YT6IssSOVQburudEckB/cSYQyaqCuUIdyuij9iCWToCWbvtp/C06e947OWEsM12BBWt8ebIpZs6Nr56+rkoJadAvtANr62VsyYZx0temhZXt2eqDfuRnyF3vN69HJQqY3v5ZKV1EFz6+PpG2M4IMlGE4c3EorteWjNj1kHavr7oKO9RGRVy795mX4RJ1y/WPLH0bVR79+gD74WaP+Wh3QG/khoOCpGrE6zxiYm7zpwA25ECTkAYQXQWXNx1whqekPSOzpVlUB53fnK7ZzY01WfTRim0ibW1lr4aSsvvE4qo/lZQ8KT4FpUgzF0I0ZOYwt++HmOzrhK7ecyAm22UiefxE0N5xx//qa6zTBUprMMBV3axnuUNI8gbsMvHawQmlmyINpexKZD+DezGQ0rm9yIdbr0pzafV3xlLMLUR7JiWioor6qXbesASyULtrVyAzVcXXYdKzxs2PjCrbFcDteK5UZBSZjeasWhj0x8JkMFOL+GVSHgzOZoR3AXQMDl+8uub7J9FUOk7OkwpQeN0PJTZiKMd7Evocq7ZjX/5nJm7kXE1V7FYYhSiEaWVfGq19O07tAb8aK1pDqEvTMpPF3UcG7fmNfTCc72EFD8pBacY4EKj+vELV7CvO8aJN1cM+vOMotRJ8WdPeGhjSj2OQzDqH+BURHlCbq5FQnt535hOVrY8LsScWRzcDF7tUM0hlp/OCaHI9FJ9FYdBT0HRlZHkQc929bsCOtXgT9tmGJ3SVuEwceF37M5BRUjxX4rUSMdy8ucAernq383cSPw3aqDJWCs//VAtX1IVUU6e1kjWExiU/ZrO/4nQonKO6daIyI5d1ps/s10eqp8AzU0aaNq2a7RTNkDOTS75kuM1FUKDu1o1OJEZfvAcrxm8RvQsp1ILgOl9i5RMkikY/aZI+VSndcqM3obGP86i28cMamVZLjhlV+ufSr8SotS5XGulATaCkdbCePj7DMI61/fIIwhdqmyNlKZ99xPVfgpRxgKCMOF+TXjl2kwQhYDOr1z2znVMz/oELpsOK8Q5R6OseRc/fi96dHZMeHY3s7kzXPs3mrErHAZ/H9dTlaAn9au7yU9zTQ7LRO1VK09MgYgnIQcHEqw6+vl04OmlNe+GynJ0YJ2DygB70nCWzPr6bapn3/3Aape4xumWqx/UedQvHvwwriwRVe7I+mG1D6aCBwu/F3yqnxhtdlGS9wrgspYmRwSKqGogTEAaJun0jxDDkZT4Jbx7QJI4PGbKwsxolqu7HeCx4BMhyTxWClsoaS0v8TsA360v7OaNOstKbBgshu+dbBNlXzn9fT+b3pXKIJ0+sUOFgHitrcm41r4mSz62qHLjzTurFnqAnCRMzJyWqgezmvRF07y7dDKSK1V5HOO4vEtrrF+PKPLpwwiQfUYberb3F+aRwDnSnVi+ZC6Fre8zTj1N3bET6RjVg/Hqq9ddQL+ORWWao47CMmyM9RYIvNiuTWKE1RkFcmX3+5z7Q9wpyV9mcCQVAL8L3tjpDATxLI3oGafSlZSyCpIHLiNEANiuMmn23BN5bHtuQh4oMLUEZL6KvNsdva0qy/GnZDhJyRBWFqcfzvxy7uuLiBPR0gMtcscFF/++twddPfFSdR3mI+JzzWFapTn/jBirHd7Qb8AlnmmA5x5Iy56CFvW2Ms3otdsXd6LGvvv5p3CWOfSazNga/l1CObN8o4Kd9Wq+n3cpxX2SZWSNM68mcgziuwwJVNJ4xRMWiqKMazqCHtkPLHsp2dOyyq91vSglhI1rdtu4Nj7DOUPnVX0WDiae0XSENaG715NnRl2iK/4qjDW3x0VLr9lfNiN46fFMpiMJKgJ0mhy0gZ0ufm8Pnk7KdYiEWxNha88X4iWAm+QYshPgGAk3UhyYrcB79iRZUn2W21ucmuTRLcD9snvnNL/SHJTi9PF9Ztu3JlBUlBueOlckfzyr0dS+Md1o0iRMpXxvgzLM9rvLu7Dcx69G2042wDZMbEFU1XwoBdXmRCZe7A7y2D6QPoRJkmMtuOiclGy39khhbG+/3GnuR2Vhsv09HKyrZry3PbfG6TaJ7adzpthSKrG0+dfM51OX40XErS1w+XVbSh/sYJtINUencrIsl4u2HyOhObnMLiP0WGAbPa+EXk6LYcrOdWYHybnSHZ3JZSh9bjABiNU2Oba2VhPg2Q9608WOv5Ldul0Gzju7NlwQTcp/EqZXFkj+pFeV5Lv25YmpwmBkxgIwVLVOxwlZRoPd5/+gRGRP5ENmkOOE7zofJmufbrlX2X6uTyGl6GNAe547Qg3cFMy7uQmH6VtGoIFPv3jMx9/HJy1gHTYUg5MpVwLCj6KwlHE678zOkvn0W1c58LSDKAm51Kjm0YbG1qxq8s1D8KjYE3jIal/qAEWZUr/GQNFYBXdeFEESucCWUYL3MjmHN44nmRGmEcMtkEWuJwhXVVWjLj92oFsxfO13lXwifD9sQzmtiJ9IvN6rOCRaDhDL/c0ku42uezHBEqplBtc47ixVyXQUNBtzVcLpnrZgrawdOK2SpU2GKrLpmYQT9o3oSfgr3znGCtSnLpflrTCXEkGXRwBzS+m3QrSXJjia31w2g8RskOfVx0PPmSYUwZvoksHPmggqESTRWvpXFVahFMVtAycErYfuKFxl9oECTlF8latTzmHvN59vtYkVDfICDb614jRUa4s0RL5ifloCfzflowhVHEI8uYkLHHb5ZoKCxCE1zDO4LRqZEmUvZaZuk74zLnGBztufME95phbmiISDpWtbjKSSxhEFHlCHCgHBdz6DK1F8AvsJvQexnUZrc4nOMXBUrLERfcL+qMUn2zhnauUAxCGQd2pLusBEYrd8nuCI9Qt7J0zHs5cRmDbx3i0K49iwdkbxb7SbCUyCyD3B9oEuMqXFKZQsSn8teD1XnCYmIZH0qgr2zdx81hJSvGV7Oxan4gwGkUYHuUM39fPTnWlvrp3B0jQRLlZAVGC9iSVjiaqT2Ptt0xG2VmTpViZWe8BN/XL8p7ORAGfIwFRwGeWOE6UOtwidYb/Dz1mO6XouOzn3mQpG1lstUEo3BGTa4qeLTk2LAYXxP5+ek+aXDFKQU5/r0vAWMSrVel2GsuO+3Dhivy2f4I1eyddnzkv8Lq4IqbJWGs8WRHJl6Wwk8NUI8Q620YPpgUeNpDF52iJS1wmw8Oy8QPEYB8pC+QVUPU9K8kJoHWjnSsxUD8cx2/at6vWuAr2vL1tkXtcjPbTzkZ3gTMFkWpHxubkYBDaAro/o3nGDImR5Pp803K4Q29YJek5sfqbb0irC9exCT0j4X1fYSyQqkHnNMECoO4iz7k2DNV99ai4Ed0bz9dsyF/hGj51yHUEQpFfdf2xU00UwtYla+ZbbV+OqOtrCt11EQfx5HPFr7PnjrMcqq8K7o8PX+lyZy5XGKopC0bJXvS2IzhgdjQgZHT9fnU/BTBC4vaPSeAuJhqVJw09wqzFddCT6ShNaovAxjGBv6ds69iWj3wctLw5z3zbZXjb4Tqjkdk2dPS67NYEMo3tJ4BErEjqYKSWVKRmcwz9U3ZDYPHYQuOEoHSeue8xNJRHfzZEDLQba7UWvf9MfuLpO7IkJWaQKtrgnBhPGVid4JJ2JpDLY/z+Z5Te1CmVuZHN0cmVhbQplbmRvYmoKODQgMCBvYmoKPDwKL0xlbmd0aDEgMTU2NgovTGVuZ3RoMiAzMjI3Ci9MZW5ndGgzIDAKL0xlbmd0aCA0MjEwICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o10CTiUbdh2kWQnSejNQ/ZtFvtWM/Y1IyRbNcaDyXiGWawpJLQQlSyRpU0phOwhIaVkl63sZaswhF76Htrf/z+O7zvmOGbmvLb7uq77PG9JMZyNItaN7AoakSGaIkoJqQXoW9raotAAEqmshESi2SUlbYk0EvjTzi55CKRQiWRI648IfQqIp8E2AzwNDrQkQ4AZnQSglAGUmhZKXQuJBNBIpObPQDJFCzDA+xHdAEslwIwMgVR2SX2yTyCF6OFJg8/5+ReQIcgCKE1NdYWNdADrDVKIBDwEWOJpnqA3fCIBTwJsyAQiSAv8q4SMjieN5qOFQPj7+yvhvalKZIrHPlkFwJ9I8wQOglSQ4ge6AesjAwfw3uCP0ZTYJQFbTyL1u8OG7E7zx1NAADaQiAQQosIpdMgNpADw6YCNqQVg5QNC34MtvgcoAD+WA6CUUL/K/cheL0SENpLxBALZ2wcPBRIhD8CdSAIBKyMLJVoATQHAQ27rgXgSlQzn4/3wRBLeFQ7YaB0PGGGtATw84Y/5qAQK0YdGVaISSeszItbLwGs2hNz0yd7eIESjsq/3Z0CkgAR474GIH5frBZH9oeCfyJ0Iubmvj+FG90HYQURfOmhq8CMGNrH/tnmANEAViURqKCsDoC8ABhA8EesH2Ab6gBtO1LoZniEk2IfsA7jDY4AhRHcQ/mEPpuL9QIBGoYMhwX86/kbsKBTgRiTQAFfQgwix/64Om0H37xi+fwoxAHBCwvRDAcj1z69/LjDD3MgQKfB3+MYVI2xxOBNzS/kfI/9y6umRA4BgRRSgiFZWAVTRKoCapioQ8ncVHJ74owvk70xTyJ0MaH5vFt7Sz4b9fjBA5oc8ZIG/ax0gw7wFAZnfNHdGqiIJ8Bfq/0z2jZT/H8fXq/yvNP9vR0Z0EmnDL/M94P/x472JpMAfETBv6TRYA5ZkWAnQf0Ptwe/CtQTdiHTv/3pNaXhYC1jIg/RrkUSqETEAdMMRaQTPDW58N9ut64xEhEAcmUpcf1kARRQS+R8fLC6CF/x6UGFKbrhAWDt/n2gIEchu6yJDq6oBeAoFH8iOhJmEVlUFglGwGt3AgA0SAwgliEyDUwB4uhDAnUxhX79STXUAgV83bSA1FRjRfkFNTQBB+IXW20O4/QFRAAL8AyoDCI8/IFzY6w+oASBIf0C4svdvCCsCQf4FVdQAhA/MDfIfh6HgcvQ/IFzO7zdEw50FbMC/lkOgUyjwC7HBX3hzP/HGcwSCASCBvaeLTNCOOF4QUbmUjxXxVxxrRqtwNcydY2yzHzUU8ntvHa6vszyvfOP8G2xNx/j55cHtU+jsbyVeh3civY68O5F8XmtnT1Eli7vriMKJlu26K1NUCzp63Ly62vGYMuTmsfNT6cFGfwamXVZQwXd2rDN1wlhHqjT3ywPPT6zSxdNKnEzNMedZd2loKHMyRTzGpj7O1XuIbe+oMpWgzmGaZy7/YzSxnFzfhFYdbui9p7CZOJQsMjnJ5WPOSJ3cl/ShVk3Y/FgL0C45Wmu462ucTDijMiJMxpX6Ehd3S0XY3XauZOoW3Uo8IoxSOlMwavI65z56pG0/w/bgtHqEnIdT/JgST6+F3rbc8mEKunhbHE6mUsdB0TC65aSeR+6rxVv79zpQMRmmwYerZ6X3NHd127XIyCqHoML4Vb1mDnYSRKOJNy7NMj5m5bNEXxiaW3lzYiXTB5NmZlxYPPKCZx5W6NzC3N6aF0MZX9/KtAUMs7g6JCHdP4lePPwlK6s/E+Eolz99+3CRc/vyGR2+cwG7jJp3T0u5JaR1hfsaUMTlkqz8dS8c1TmXd3AHqo7D5LN/7aBeQpK1ROn8gNxX8nw7l/E9/rM1KWn+KvF9s50hOQxK09GB0sgj99slSx9wlQX1JzCYC2k1L85/YINiF61PKujW1B8SY1QrcfYKPywzm2TwVkV/Yhaz4CteSRvOv3Y4TyTq9a4+Nt+oq55Bvo7Hb/GnOxfq03OZrFqzRmInPHc0OA/ykZGIxmWGtjuXnHO+uCsmSXr8Y2LXWuu+/L1YCXMUbjPtNmX+TIR7SoQvR2g3ITrL5q3mBx4tx0Xpa2V32rlbCe92sL2vspwbf7TKuHOIstA/Rt/WJWyRrukURg8RuS/DJhVLKQm1uBjGKPLTXh26WRqClw+D/MNsbdg3ZbV+lEVc7zP5V6rbsMhIaC1qwsjNlT9dISmrL087wLchcWHF7AbfAXaA3d9ruuKKvKLxqHixjkDucrRVImK5wad+OCPMWfTZGLY+4dSnROFLTVVpFe5S77QsVG8+rB+feWzInO/xqEiafbsx34uRk0LHzG24Y+l2JkkXmG1f3hFxvtgkpJRxVur6gKcyYzT1uPK108nGQ8PBp71ix42qr+v6thMJaUIxJ2bkAGo4ETshd9KX7WhknyBqdlaC58RDAwHhZxiHeaJG/BN6o/WR9IJbyqH+/CNnT6s8Tn5d5V63+rinbNdW4O1BLBcJP92Y2WrG+OiK+hTruKtY+4qM8eqIXZ+OZgI5Pd6yik/hdFx65j9iTu7qcT4svTw+byn4rboeUPInfXTpMXIE9V4V4KFsspBu8p4vXq3qa/HsyZgJ6JIA01ehz7Wi7AcCTFBqc6m3dQlt/sfkGcC/SMV4TmY9hMQFH9J8FjpZRYNUUbZNzEAre48IVwSo5L2W+2+70JOJOf1AIACzI5hL4+G/uO2SmvpCrcOpCU3WVXawonhcPkMCdjWaIk09p4/o5zBjX9peQnAOe2wnRNbUGrzoulepmp14bXtpid0Xnm5RTXvWmCo/ShpRf2ev8Jg0LeqQZOxKs6GuUoJ6uN9gIE7vVr9ueYlqQFLHlmN9OYQgDLk9Uge1W8C1zDG4TMRFMla8oF+4cRMbn9BbZ+Gn9T2YTqtP+tqpLm+OTel5b+KNtpHz0HP3Edlv1FZrcje7Ol7SUiL/Pkd7kH3oAOvgUdm40ufbndh1b6bPRX68qm7zIukh1ittMOIlp5XDZn3BEm3DEdlqfD1fSkLekEDldM7uxrYs4IjcoGunkx0+UmFMqu514Kaqy8t5TVsyT550dZ4OnlmQD1Ai23i1aY5g9Q6ke7omr1ZQaMMiOv2nMayGitnPhouMsQhdpS4db5zMklxzzj/vF1gHYoRCYn20jkjPc2Jk2kMKH82VNPRiRu+j0PPyM+c5ag507lrCtcmm3p5n9zymbLYgzx0mRklvCCZOyVoUWptHXurtou+8rX443eRyY05G2LDPXqBp8WhgufH+V3hcTLEo0iFxJZSX+Zzc29w1Ixz9BeFiS9/0iVRjY8WXD5g3g6cITxV2WXCdSQ6yIRDv6xgbzlEAe1YqRuweb3fMnYG9LmoVnZj3ExUBEY/4zA7uXgpJOfmqoiz6QnhcfrLOW+3BU1o45MHPM7WL0sfyXx+SWOscb2f5wFsPpQjm2XkU0jWnPxfx1HPtvFsXQlWv30IZmdcwriBVbjM4aC1hY9JLs4h8lN/21W7XbnNeifnypqsFh8mG/fh5DiuG6VvPZuFxFTajtjPnKxYzo1W4uiduGzerlryUBcf4u1usrnZ7yIzVxa4Z+tvvNSoSmnaqXlzTsemqTDkM1aSMTUVHPV2okm9Og/TKR248zDb8PFCnm9g7lFEeSgk2O3+hL6qbDSE8KKUn1i1uJbkEee0jdRbnNCevnRcOt3l8dPTwkXNKCzGDwjgrF4aAbiDyXea5d6W7jXAjWtHXahvPpevR9peRZW7x22DG1OaeTdofdyqNdJG/zOHwtG3fFSEJPZbcQ550g4FzVpEhE9Kl2ptaVyeV9xUu8LegWBxeCC9m7ozj5NZZajxuk5a2g2vZgR9yYpjWJMUccD39MnTMZJTvySpKd2QHe0umlUxgBfNTXIZA386PhSZTaEP5mK3xZ+vtgqhzW77Z7bsWXAhetrAaCq9jKxcyXrGry2D4Ui5YMdt3fBbkHNMArqizVi5prWkZh+ffLRBcumgWHvwm8yDvqG96L1TZUpX4Slov73ZQW6MwJwemTkDKN+de6n2tqqh2fEjn0Eo9vbzdof/uDmdkE2/TXLzfznJCrcRItHW3Lqna1c/Qnbbl/bWIF4hTaidl1e5J+G9H6S1SbBRLItb4C1vUkmeMxuJDP7y6tFsAf8eZKfYQNy+uNCwuMU2loKiQCZvmJc6adGZBbq80U/9A79YF10t35B040nnudXIFbX13DxU77at4HLcqQypsFOWwMxsoSw928S8o6AFbQozUdBlnnydymEw6ifW7dMxUGyx2DbPPr7QS6QKuKjdL9rgMTvgSyvR1NPZ7R2Q5h2A/LH0IU5vVeipbbvht1j/tW2IztNzn9ogpAVJNcSpfCez9wmsraLCscKJ2G8Xu0s4nucwLj5UyEfe5LxouZRok8FztRUV2zMZwtyDlOmJLWhzMx57Ui2YGm/Jh32drHU1z4G4J3sOdfGizWXXb0goX21CVIdNMKuvYNAmzQz3FdnTz/NtU5vfAk+yI20ET1DNrL26tde+upHudKWBBqDqpMz+zy7OGNGoCe+MGI8oudThKhZYbq1XvScA8iKp9SBI6pW7ZdqNLYuJh8KtNWPDZa3miV5Pprdb06yn7wSju06krr9tSD2dLxNzOGMGpaI+KPjMKWRCRqWPtV30gcAR76z2z9GVmh2mGbhWmbXRYbMfLf2runXgnnxTvy+SdUdx05+1HNp6MF9/qCpw0HfKKWM4783+MWt3H433lZdjkt7qeVNfDq8paUbuYnXeX5/VEC7++9iAL5xagn8r0/CMUjxFVv+7FpZI32Dd5yeb9oM4o7e7FPbVWaxGYA+WPl5lEOMbnRfnUx6HjY48NRc0juU8nU65qmE+OqQU3ZvUyfE3mAj/dQWM+OLSySbzhfO5ydNPU88CVmw26s6Gj2SOOPCkdkb7haEd/DYb3UNwZMtQdp7Nbb0hgwhY/+VqPqbg6vbuAXCYufCi5SYxFfYuCS45/9dx5+zRg7sG05VKi2JYe8egH9rrf4v893nbtFMcUx7L+yJnu6dZksxKpFcE2G4zs+BWjN6Guph0Iu0ZbcOwd5pTFDtHIK8bX0emTaZW5IryptFsSC+0ddaihbjnth8/Hm2WW2l4XC7h8qZGdYzsbdE4KfbdJx25h8MvRXrrq6jONYOgl05Xi1iuoeeTo06bmeONstqv8TClMztZzCh9xrk93iYq/1tI6ozaacApfkRhYWigXrIbA2bJfzXK7Lip+8dM1Kefx5v0KwrRKxR74XZxPBGuz2ZhGoszfCHMqPVj8ivbK6OhZPMHSVlFxvWEoxvTmjKBbLhrFUblKcM247j/4dHP0Q0HiF82sgZvt8nzk3iK1d9lXPALq5suxT4KicE9aXDzmOndYn9CWbZwtMrMsWm6oKfTtUr9pIVO3vcSZPPWNcw/r9PbsYe6WZM6bJtUx28LxS2c/Fdqrclf7rDpnvGJVdnynQ9GZ9dhz0eOKphE6TAtCRPNWhFp8VVipL8iy7y6LTznk158KaF+duHMk/8Cbc40VSJBlEhMV1KJ7+VvNmbOCrxyWhm80bA1aG7zYXPIZiIk2f9mOnr154Wuq+LZFY9Cop2HqpCgZGyrv5bptOef4Wp/j/wDtJk5FCmVuZHN0cmVhbQplbmRvYmoKOTMgMCBvYmoKPDwKL0F1dGhvcigpL1RpdGxlKCkvU3ViamVjdCgpL0NyZWF0b3IoTGFUZVggd2l0aCBoeXBlcnJlZiBwYWNrYWdlKS9Qcm9kdWNlcihwZGZUZVgtMS40MC4xNikvS2V5d29yZHMoKQovQ3JlYXRpb25EYXRlIChEOjIwMTYxMTAxMjExMzM1WikKL01vZERhdGUgKEQ6MjAxNjExMDEyMTEzMzVaKQovVHJhcHBlZCAvRmFsc2UKL1BURVguRnVsbGJhbm5lciAoVGhpcyBpcyBwZGZUZVgsIFZlcnNpb24gMy4xNDE1OTI2NS0yLjYtMS40MC4xNiAoVGVYIExpdmUgMjAxNS9EZWJpYW4pIGtwYXRoc2VhIHZlcnNpb24gNi4yLjEpCj4+CmVuZG9iago1IDAgb2JqCjw8Ci9UeXBlIC9PYmpTdG0KL04gNzkKL0ZpcnN0IDYxMAovTGVuZ3RoIDMzNzQgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnja7VpbUxs5Fn73r9Bjsltpte5SVWqrAkxIJiGhArnMpHhwTAO9MW7ibhgyv36/I7Vt2dgEEvZhq7YK1Locnfs5OnK3ZiXzTJUsMB2YkMyhVegIJiwTBg/HhJdMlkxiGfNSGSbRs24gFVMeI8sM/qVjxgZmmSVAzawxTCvmtQEUC14zBeRCYrYEBeeZBnot1QAQwjhM4s8SeY2nsUxLPENgBlMewAbrwYIauAAiZogTSwyCK2zGFnAHfPQM2O/AB4gaekIIiCgN6BvwZ7DPYOxKsAx8voQeAOeBXAOfD5oZPINyAwENES08bMkUPQyzGIpSMYuxEIJZyGeCg9jgG1oDn9pjkehoh6cHPWkGpCIFdTpBGsKTlsCUw18JDp1DFxzBEs4Lw7xgvoQkHqqUWIfCvXEghrEv7UBp5oMCi4KFkjQQWBAe5oLOVUlMsaAxUJIFokfGtiCmLGxSwvz0BPMC+4IUA5AMgdwAxilLYhBPgVUfO9jpPToa+veAKg0YCmQ70mSgTQ6mDZI6wQ+ePmX8gPHd5rBhfIc9aqtRVzeTQjxm//rX4NGr6jsbjs7q6qo6ryZd+3jjBpk2vDy/aKbdcDKqWD1h3VnF2lGNnfVJPWLjuqumw+5yWm3GoxKegzOgGTXn9eS0ZcPJMfae192QQG5hQqfN7yfDSftXNa2O2bfLql2/6TOipGTvGH9ed0e07enTAT/8flExvj88rQZ8u5l0JDOckQAH/F3VNpfTUdVS+MSZveq4Hm411+xziQkTTCGdRUiJwoejAfBMgYBMGaGfTSYN0H2G90fKR4MlqnF5wA8uv3Rx/LqefB3wrWZ6XE0jfnHEX/CXfBsDwcojYmjUsc/WFQgvOLIrShjY6cLCwtbbQggNqGdsVV0j2KFom66RpTBtNT6JauuZyTTz6Y8/ETeFQNh4oQuDIJtcjsdHm0BNBHXOFjaou4Ba4ws49RIog+LHzfTgYggfSoqCIjt4zoT1GH677nYP4AwV6QETA/4ctopiPkdeRDQlwyLMEW6pjzhT5WzeUDj285ZCr+97Ctu+H5jSM3hPYUp9sMj3p83ooILiwdfOc8YPq+tu1ZYrHqT1qgdp+UsepJKIKkmnk2BaPKRbqVAWyIRIpOAJmlTBF0gZyI66kLf41ZdhdybL0h1Phrlb/RozQsMNYVcrRGGRqnH0FQaKshJMBrGZm+Np9f3ksgVD5rweTZt21FzUo4djDAdXYfWCMRxciELzY8au6vHJcIIALFcD8BcZcrJQCDVtQ6FLnKQuFA6Hmna+0LfZrR2eDcGOHo0vWwRbu5ITtLpzTlgCvT0nrAHVMC3lswfMCUtxncX7Uh6Yx/tPxri5EePm12LcpKg2DxvVHlpGIaW0LVCCqSALQ6WfMUXw6ue841fzjC8MUlfPkS6JE/9jjk6bMY724aSOUSRHzXhMVcBVteK45u6Oa256owF3Ag5zB1Cp4OPubqClK1C53gVUOFGgQLwTqHKFtupOoKUqUF4/5Lm7NpY2xd5Pxpgtb8SY/4kYy1QT7u4c4c5ZbR2oRjoGs/8tjd9Zs4uGMX5xenIxPf3CPs/p8p3qqh5V73a3Yk0M3xEFgvCzgRtq3BdRayLTlYWKOvaxOqA6jlatRDLBwWPjKs14iehBBkO+sZKgDWoHureUq41E9er71mB8n/98r5tjWPSMKgvc1uiuhHoT9zhYGHaWjmaVB0dWK/DpUDLj1kQSQ9JQ4CYLfnGhgu3oFogTnQVXFnTjU4QnyaTpWk5rzkQ4oUhHXpNGPEEYrzAftO41ghtuxEWrsJtHDbzULrSihQWnBnvoth2AV6uIEdUFadrQvCdONe6lKIgAoTTxrFGPJDi6cnqiTJeCsiQcnuQ3JcmskXV1OnNhZViTLIqbqStmrRJkVQUN0Q8I1N/Ukp5M0jguIdBS3OndbB3XUxIetxLVz89wkx4MbtKJYoJO/QWUjmOdQWQY5r3bObxL22PMOIsSwCtk39I4yepCgJZ7ObFbRX/SzJUUJx56VoCO9sENnST0sDzs4Ey0M65uogfwMBvc0fqoSOp7uKCI5nBwFBgQCcr2hIWwsu+m1vqFrYhOro1cIkOnbERKdopPQd6Z25dml6weqE0zySpx3xw2rWtDfGjs8L2VFmtJQ6kfW8oo2E9xQlHqvSCoQBGiSvJ5peIqvFhsbPtItRThtMcJiofU9hAx/oKnWCUIaWgtUTAixqOIWcOG6K+pH+lHGF1SPKY2YcxXlSH4GbbbOL1L2+PM2kQrh0kzTpPFHOI3zGTGeYVLP2UfI2MWVDQb4ajio18ATXQusn30zZBhiljT/p4Cco1myUI9hQQZ2xAITz5jkw9les21ksuUZshm0W7zUa/v+Vy+h2aT5ZKFes/J9BLxSTG3WO89arbbWuIJtRFZM+ojwpEXxtxsIvbUekUzqU1niirj6pqTh84UHfN6HMmor/m5E0qyBbJeNFR2SC2OuURm0cuh8iNhcaD1axl7P3tU5gemdsR6atNMPC7L6BJJrKi8dAj2ThaPEYJTNpliIWc8ROLhFfGkubi3xw7TiF7hPX6T1ClKOSePfxvtuxB0tZepICLrrZH1M+vF2SWbygWO3hRmGTpBqEC+pVJ+SgbJVpMAqZ/auU+Qhwkd89H/2//RFjaUuNYpSZUS9fqK6xdawjL7dwgezFsZMxS1acbhCoXLxbyacDoGkaUaz6pUKqgIpUysOEsVd8oYM/DnEHepGb60s8cd60Kj57gJCv8oOu18YGLZuBB4ubcYERqtTLwYzHoyxGJ1vh53xDmDrODj2It+7xwqralYIqlYjKf+fI1KVNRMNipG9W2IRXo+YyyVtlJHhRsqnm/28xkjynjMk4HzvnR0xclh+r1pPua/NOOQOcVsb44zwihD5bAydKimfr6aJEr92B5lF2C67u1U7WhaX3TNNF3/3gzPsfJp78PB/h//3N7b+iQkFsbD05bpBLEVb8JPcPF/IukloVDx/kM/prQjugjbAMjt4cWLqj496+hlAS6uVVp7ImjxZTcc16Nnk9NxxcoBP+iq8w/wjzDgn/pNSHLAcTac0lXzEX/JX/F3/IC/50M+4se84if8pOYnuKjzU37Gaz7m53zCG95MKn7Bv/Epb3nHu7NpVfHur4Zf8iv+F//+OMnwvAZlV+YX9h+p5NX716///AiV7L0U5XqV4JYMldAxo/0PVKJuU8kToWdKcTLTiRK5Tnb4If/A/yBJ69PzIW/Hw/ZsST55H/me7f7++5+vIN+7TeLpciZeGX5FvLnFbdgo3DO+xbch4m/8Od+NP+39Dhd4zff4G/6W70dnOIQ7fIBDDEeXXcW/8C/T4ehr1Y2rk27WnxJueMxoOG0mfFRPR5fnJ+Pqmo+aMU0051AcuVNkgleTY+iQV98uh2PyMPqro6PVV3C58cLhzr5fnFUT+N2/+dfe9yY1XG/mgBf0m1DkJPYSHxfVtG6O4ZzfLpuuOv4yjgCzQYKJo9QlF26r8zrx2lZXINjW12vc+pp/53/zv6tps2R/fR/772+/fPZuJ9p/Q8QjbceIp19QH8T8ZqP5d2FmMu2X3kTVQuGk7KTladJGr4Ub0tv7SL/7cWfr03aU3m2QXiXvD9rQD253lt5skN6oXPoyl/4wy3KU21Jmu+hz2tVKFvP3kfPti739396TnH6DmHYW5K58ECs7u9HKMF0uib9XPv508Obj7i4kOdycj00vi5D6gfKx9bekrG2kqzd9cvqYvDc7qyiFLKWOr/ND68f5In1o0HvAbUHv75X0D/f3X7zaIyUebop6AR1SwUZf9QSTqVCIJRXScK5CKeX9gx6ZvOs1dtorp5npgES+XpJzQ3LLXhLRJAhsDdsq/rB9o6pZUgt9lBN/7X9eT9uOuGIE9Ho4HwDXx/q4O2vpe597E1+tH1aIq1Xi0uXEyQNnxNX9ia8c7iu0zQ3BxZLgakHb3p/2ysGyQtut0qbCL5PbL2j7+9NeSesrtMMqba83GTzcn/Zyql0m7W/4mikz0jSYUZY/4ecrqXGFtvqBn8sFcXN/4qspZYX4DV/Tdol4Jrm7SZxe2bX0zu4SpGCsV/VxO//4p3/f37+RTO/JVl75vb3sxijT2p4B1nsf0aeP4OJghny2sUZFSd9Aphfo9FFk7PVv/Xz/Zn1/Wl0xsayvuFPY+U51y87eId7Q2zQR1qCRMzRhMxaXI1nDi5/h0GtxpH0i30fHBDT8aKcZPTnohtPuMX3rSfpd80GOttnKpo9jdL79lvfsJoe7+YWADvny0udmyiXL89f0Wd8K92s2HK0Ku/YbGp2+inp0ARekLxilzcYS6yYbq8f0gepirB/Th6Zx3H9O+A/CYewqp2tJ53tuMJt9VGmXKBBTolyeAl9CL0+BNeFX2ciQZoBz2insfLKQT4rx4Tatr0GCrACwsKbo2x6icmhOBync5x+vzIJ34a9RBUHMnPm02muOK/6+rRZx/vaimjyLtOkD5p7UfwA3oPu/CmVuZHN0cmVhbQplbmRvYmoKOTQgMCBvYmoKPDwKL1R5cGUgL1hSZWYKL0luZGV4IFswIDk1XQovU2l6ZSA5NQovVyBbMSAzIDFdCi9Sb290IDkyIDAgUgovSW5mbyA5MyAwIFIKL0lEIFs8QUE3NEY1QTNDMzBFNjJENEUwRkVCNTExRkI1MUEzRjQ+IDxBQTc0RjVBM0MzMEU2MkQ0RTBGRUI1MTFGQjUxQTNGND5dCi9MZW5ndGggMjMxICAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNod0UkyA1AUheFzQkQX0XfRB4noou/bIPoVqDJV1mBoC1QxthMzE2OWYA0U/jv56q96de8dPEn6TUjJAkxAEWQ//ohKwzEYEtABFaiCauiEI0hCDfTBIaSgFuqgHposZeJGAzTCDmzDPmzBHmzAJuxCGcagGVqgFdqgCzJW+j3Wt8MADMI4DEMP9MIIdFvZm5jIQj8MQR5yVv4tXkdhEqZgGmZgFkowB/NWsRITC9bVddSidfcVtWR93EYt2y5FrdiF56hVu/wdtWbff0atwwGcwCmcwTlcwKX98Pr/eS9P+gMgph00CmVuZHN0cmVhbQplbmRvYmoKc3RhcnR4cmVmCjEwNzY3MwolJUVPRgo=
[[Topography|https://en.wikipedia.org/wiki/Topography]] is the study of the shape and features of the surface of the Earth and other observable astronomical objects including planets, moons, and asteroids.
See also [[Application of percolation models in topography]]
A ''Topological dynamical system'' consists of a [[Topological space]] (e.g., a [[Metric space]]) $$M$$, and a continuous map $$f:M \rightarrow M$$.
Topological dynamical system: https://www.youtube.com/watch?v=HzR46AeIoaU
http://www.chaosbook.org/course1/Course2w9.html
[[http://www.mi.fu-berlin.de/math/groups/ag-logik/Lehre/UST-chapter09.pdf]]
[[book|https://books.google.co.uk/books?id=67SLMyj94ckC&pg=PA163&lpg=PA163&dq=introduction+to+topological+dynamics+for+physicists&source=bl&ots=DvBxLSFBZu&sig=rGGxeluRqhjKW4kBkztda6_SsvI&hl=en&sa=X&ved=0ahUKEwjs-I687NrNAhWMKMAKHfzjBGwQ6AEIIzAB#v=onepage&q=introduction%20to%20topological%20dynamics%20for%20physicists&f=false]]
[[Topological entropy]] -- [[Symbolic dynamics]]
[[Topological trace formula]]
[[Topological entropy|http://www.scholarpedia.org/article/Topological_entropy]]
[[ Topological entropy video|https://www.youtube.com/embed/uNm4oChL-4k]]
In dynamical systems, complexity is usually measured by
the topological entropy and reflects roughly speaking, the proliferation of periodic
orbits with ever longer periods or the number of orbits that can be distinguished
with increasing precision.
[img[http://i.imgur.com/F0zsmVZ.png]]
See the related [[Kolmogorov-Sinai entropy]]
[[Hans Henrik RUGH - The Milnor-Thurston determinant and the Ruelle transfer operator|https://www.youtube.com/watch?v=rMAtlrOMyYU]]
[[Descriptional complexity]]
For a coarse-grained [[Dynamical system]], described by a transition graph, in turn described by an [[Adjacency matrix]] $$A$$, then the topological entropy $$h$$ is
$$h = \log{\lambda_{\text{max}}}$$
where $$\lambda_{\text{max}}$$ is the maximum eigenvalue of $$A$$ (assumed to be a positive matrix so that Perron-Frobenius applies).
!![[Determinant of a graph]]
[[http://www.math.ru.nl/~mueger/TQFT/At.pdf]]
A ''topological space'' is a [[Set]] $$X$$, with a collection of distinguished [[Subset]]s called [[Open set]]s, called the ''topology'' of the set. These must satisfy:
* the union of an arbitrary collection of open sets is open;
* the intersection of any finite collection of open sets is open;
* The empty set $$\emptyset$$ and the whole set, $$X$$ itself are both open.
An equivalent definition is that a topological space is a [[Neighbourhood space]] $$(X, \mathcal{N})$$ in which, for all $$x \in X$$ and for all $$N \in \mathcal{N}(x)$$, there exists $$N_1 \in \mathcal{N}(x)$$ such that, for all $$y \in N_1, N \in \mathcal{N}(y)$$.
It can also be shown that: A neighbourhood space $$(X, \mathcal{N})$$ is a topological space if and only if each [[Filter|Filter (Topology)]] $$\mathcal{N}(x)$$ has a [[Filter base]] consisting of [[Open set]]s.
Remark: for family $$C$$ of subsets of a set $$X$$, there exists a unique 'smallest' topology on $$X$$ for which $$C$$ is a [[subbase|Filter subbase]]: namely that topology whose open sets are defined to be all arbitrary unions of the collection of all finite intersections of elements of $$C$$.
!!!__Connections with lattices__
The set of open sets in a topology forms a [[lattice|Lattice (algebraic structure)]], where the partial ordering is set inclusion. Also the set of topologies on a set $$X$$ can also be equipped with a natural lattice structure.
!!!__Analytical properties__
In a topological space one can define fundamental notions of:
* convergence
* [[continuity|Continuous function]]
These are approached using //neighbourhoods// of a point, which are just open sets that contain that point. The family of neighbourhoods
!!!__Examples of topologies__
[[Product topology]]
[[Discrete topology]]
!!!__Related spaces__
[[Metric space]]
[[Compact space]]
[[Hausdorff space]]
The topological trace formula is a [[Trace formula]] for [[Topological dynamics]].
$$\sum_{\alpha} \frac{z \lambda_\alpha}{1-z\lambda_\alpha}=\sum_p \frac{n_p t_p}{1-t_p}$$
See [[here|http://www.chaosbook.org/course1/Course2w9/count.pdf]] and [[here|https://www.youtube.com/watch?v=pJ9elIXPmPM#t=9m30s]]. Also [[here|https://www.youtube.com/embed/LLjrJt-6S9w]]. Here $$t_p = n_p$$ if the prime cycle $$p$$ exists ($$n_p$$ being its length, and is $$0$$ otherwise.
http://www.chaosbook.org/course1/Course2w9.html
This formula has uses for deriving a formula for the [[Topological entropy]]
https://www.youtube.com/embed/OQpBvsZ6iK8
//Things often have a shape// (continued from [[Geometry]]). Topology looks at the "raw" shape, the shape that is invariant under continuous transformations. The standard notion of "shape" is really [[Geometry]] (which includes topology)
[[Topos|https://en.wikipedia.org/wiki/Topos]] is a category that behaves like the category of sheaves of sets on a topological space (or more generally: on a site). Topoi behave much like the category of sets and possess a notion of localization; they are in a sense a generalization of point-set topology.[1] The Grothendieck topoi find applications in [[Algebraic geometry]]; the more general elementary topoi are used in logic.
A topos is a category with:
A) finite limits and colimits,
B) exponentials,
C) a subobject classifier.
[[Topos Theory in a Nutshell|http://math.ucr.edu/home/baez/topos.html]]
__Higher topos theory__
[[Learn Lua in 15 minutes|http://tylerneylon.com/a/learn-lua/]]
[[Torch Tensors|https://github.com/torch/torch7/blob/master/doc/tensor.md]]
[[Torch maths|https://github.com/torch/torch7/blob/master/doc/maths.md]]
[[Torch Package Reference Manual|https://github.com/torch/torch7/blob/master/doc/index.md]]
[[Using Gnuplot|https://github.com/torch/gnuplot/blob/master/doc/common.md]]
[[Writing your own nn modules|http://torch.ch/docs/developer-docs.html]] https://web.archive.org/web/20150905061421/http://code.madbits.com/wiki/doku.php?id=tutorial_morestuff
Torch + IPython = iTorch: https://github.com/facebook/iTorch
[[Practical 1.0 – Lua|https://www.youtube.com/watch?v=QLYLOPeI92g&feature=youtu.be]]
A ''total ordering'' is a binary [[Relation]] in a set $$X$$, defined as a [[Partial ordering]], $$\preceq$$, such that for any $$x, y \in X$$ either $$x \preceq y $$ or $$y \preceq x$$. The set is then said to be //totally ordered//.
[[Toward an Integration of Deep Learning and Neuroscience|https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021692/]]
deliberative procedures could be compiled down to more rapid and automatic functions by using supervised learning to train a network to mimic the overall input-output behavior of the original multi-step process. Such a process is assumed to occur in cognitive models like ACT-R (Servan-Schreiber and Anderson, 1990),
[[Reinforcement learning]] rewards probably play a role
Special, internally-generated signals are needed specifically for learning problems where standard unsupervised methods—based purely on matching the statistics of the world, or on optimizing simple mathematical objectives like temporal continuity or sparsity—will fail to discover properties of the world which are statistically weak in an objective sense but nevertheless have special significance to the organism (Ullman et al., 2012).
A trace formula relates the spectrum of eigenvalues of an operator - for instance, the transition matrix - to the spectrum of periodic orbits of a dynamical system.
See [[here|http://www.chaosbook.org/course1/Course2w9/count.pdf]]. and [[Topological trace formula]]
Molecules that affect [[Gene expression]], by affecting [[DNA transcription]]
* Direct interaction
* ...
.........
* Repressor
* Activator
* Inducers: affect the binding affinity of other transcription factors.
<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/8/80/Transcription_Factors.svg/1000px-Transcription_Factors.svg.png" style="background:white;">
https://en.wikipedia.org/wiki/Transcription_factor
__[[Sigma factor]]__
[[Sigma factor]] binds before [[RNA polymerase]] binds. Several kinds of sigma factors.
Many transcription factors affect the sigma factor binding site, affecting the probability of RNA polymerase binding.
//aka ''multi-instance learning'', ''multi-task learning''//
See [[Deep learning]]
!!![[Max-margin learning, transfer and memory networks|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=2m08s]].
good for generalizing models, . Good when don't have much supervision data.
!!![[Max-margin learning]]
Learn embeddings in one task and transfer these to solve new tasks
[[Example|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=15m50s]]. He exaplains how deep multi-instance learning works. Nice
[[Matching|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=22m30s]]
[[Corruption|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=25m10s]]
Example: [[Bi-lingual word embeddings|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=41m07s]]
When you can't corrupt the data: [[Siamese networks|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=42m50s]] [[Paper|http://yann.lecun.com/exdb/publis/pdf/chopra-05.pdf]]
Example: [[Question answering system|https://www.youtube.com/watch?v=jCGplSKrl2Y&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw&index=11#t=45m09s]]. Followed by //relation learning// (learning triplets like "cat eats mouse")
memory networks (see below) may be useful for transfer learning too..
One-shot learning using conv nets, as we've already have good embeddings, just compare objects in embeddings. [[See beginning of this|https://www.youtube.com/watch?v=56TYLaQN4N8&index=12&list=PLjK8ddCbDMphIMSXn-w1IjyYpHU3DaUYw]]
!!!See also [[Feature selection]]
!!![[H+ pedia|https://hpluspedia.org/wiki/Main_Page]]
''Transhumanism'' is a class of philosophies of life that seek the continuation and acceleration of the evolution of intelligent life beyond its currently human form and human limitations by means of science and technology, guided by life-promoting principles and values" - Max More, 1990
https://en.wikipedia.org/wiki/J._B._S._Haldane
https://en.wikipedia.org/wiki/Transhumanism
https://en.wikipedia.org/wiki/John_Desmond_Bernal
[[The future of proffesions|http://www.oxfordmartin.ox.ac.uk/videos/view/515]]
https://www.youtube.com/watch?v=DotDX9m9muk
[[Prof. George Church - The Augmented Human Being|https://www.youtube.com/watch?v=GSVIKC4R2Zo]]
http://www.aleph.se/Trans/index-2.html
__Transhumanist art__
[[Ghost in the shell]]
[[Transition graphs|https://www.youtube.com/embed/8mWoFcGo4K4]]
[[Transition graphs book chapter|http://www.chaosbook.org/course1/Course2w9//Markov.pdf]]
[[ Examples of transition graphs|https://www.youtube.com/embed/gDwYLfxZZKs]]
[[ Tree enumeration of itineraries; pruning|https://www.youtube.com/embed/X6FHdES5tnw]]
[[Topological entropy]]
''Transitivity'' refers to a property of a binary [[Relation]], $$R$$ on $$X$$:
|for all $$x, y, z \in X$$, if $$x R y$$ and $$y R z$$, then $$ x R z$$|
Transitivity|Transitivity (Graph theory) (a property of mathematical relations) in a network is usually applied to the relation "is connected by an edge". So a network is transitive if for every u connected to v and v connected to w, then u is connected to w. It's not hard to show that a perfectly transitive network can only have components that are fully connected, or //cliques//.
To be useful for real networks, we talk about //partial// transitivity, or the //level// of transitivity in a network. A way to quantify this is by measuring the number of paths of length-2 that are //closed// (closed here meaning that there is an edge that connects the beginning and ending vertices) compared to the total number of length-2 paths. This is because three vertices in a path of length-2 (a.k.a connected triple) would form a triangle (also known as //closed triad//) if transitivity holds for them.
One can then define the ''clustering coefficient'', $$C$$, to be the ratio of these two quantities, as a measure of "how often" transitivity holds in the network:
$$C=\frac{\text{number of closed paths of length 2}}{\text{number of paths of length 2}}=\frac{\text{(number of triangles)} \times 6}{\text{number of paths of length 2}}=\frac{\text{(number of triangles)}\times 3}{\text{number of connected triples}}$$
where the 6 and the 3 come from counting the number of length-2 paths starting at the three different vertices of the triangle, where we count the two different directions (6) or not (3). This factor is cancelled by the fact that by definition there are twice as many length-2 paths as connected triples because connected triples don't take direction into account, while length-2 paths do. This last definition is the most common, and can be interpreted as the number of people with a common friend (connected triple) that are also friends (so that they form a triangle).
Another way to define a clustering coefficient would be to average the ''local clustering coefficient'' over all nodes. This quantity is defined, for node $$i$$ as:
$$C_i=\frac{\text{pairs of neighbours of i that are adjacent to each other}}{\text{number of (pairs of (neighbours of i))}}=\frac{2\tau_i}{k_i(k_i-1)}$$
which is defined when the degree $$k_i\geq 2$$. For smaller degree, we can define $$C_i=0$$. The average over this (over nodes in the network), $$C_{WS}$$, then defines also a global measure of transitivity, and was proposed by Watts and Strogatz. It often tends to be dominated by networks with low degree, as the denominator of $$C_i$$ is large.
Furthermore, one can extend the definition of the clustering coefficient beyond simple transitivity, to include the probability that friends of friends of friends are also your friends, and so on. This is equivalent to consider quadrilaterals, pentagons, and other more general //motifs//. apart from triangles. Triangles are often interesting because they are the smallest loops for undirected simple graphs. However, for directed simple graphs, the smallest ones are length-2 loops, and their frequency gives a measure called ''reciprocity''.
For social networks, typical values are $$C=0.1-0.5$$, which is quite high compared to most non-social networks.
Local clustering coefficients can be used to find //structural holes//. That is places in the network where we would expect a link to exist, due to transitivity, but there isn't one. Structural holes are bad for information flow (or other flows) in a network because they limit the paths it can take. However, they are usually good for the node that has low local clustering coefficient because it means that that node has more control over the flow, as most of its neighbours will have to direct their flow through it. Thus local clustering coefficient is sometimes used as a centrality measure in this sense, where a more central node has a lower $$C_i$$ .
Another way to find structural holes is via the redundancy of a node, $$R_i$$, defined as the mean (that is, average over neighbours of i) number of [[neighbours of i] that a neighbour of i is connected to]. This can be shown to be related to $$C_i$$ by:
$$C_i=\frac{R_i}{k_i-1}$$.
Transportation technology & engineering
See [[Transport innovation]]
* [[Car]]
!!__Autonomous ground vehicles__
[[Self-driving car]]s, google, tesla
Smart vehicles - [[IoT|Internet of Things]]
!!__Hyperloop__
http://www.techinsider.io/images-of-the-hyperloop-technologys-test-track-2016-3
[img[http://i.dailymail.co.uk/i/pix/2013/08/14/article-2390672-1B4820AB000005DC-32_634x365.jpg]]
!!__Electric cars__
Tesla Motors
[[Faraday Futures|http://www.ff.com/]]
[[NextEV|http://www.nextev.com/?locale=en]]
[[BYD|http://www.byd.com/]]
!!__Electric plane__
https://en.wikipedia.org/wiki/Electric_aircraft
[img[http://www.afr.com/content/dam/images/g/j/q/1/y/k/image.related.afrArticleLead.620x350.gjpiif.png/1443071642869.jpg]]
[[E-thrust concept from Airbus|http://www.airbusgroup.com/int/en/news-media/media~item=be674db0-2b69-42f6-946a-03cf3b0eef32~.html]]
!!__Distribution and supply-chain__
http://www.tandfonline.com/doi/abs/10.1080/00207540500142274
!!__Unmanned aerial vehicles__
Drones
!!!__Ionocraft__
https://www.sciencedaily.com/releases/2013/04/130403122013.htm
[[On the performance of electrohydrodynamic propulsion|http://rspa.royalsocietypublishing.org/content/469/2154/20120623.abstract?sid=9494059d-0ba7-4d99-b219-73ca7fe837be]]
[[citing papers|https://scholar.google.com/scholar?cites=17191576207329318098&as_sdt=2005&sciodt=0,5&hl=en]]
[[Electrohydrodynamic thrust density using positive corona-induced ionic winds for in-atmosphere propulsion|http://rspa.royalsocietypublishing.org/content/471/2175/20140912.abstract]]
We conclude that EHD propulsion has the potential to be viable from both an energy efficiency perspective (our previous study) and a thrust density perspective (this paper), with the greatest likelihood of viability for smaller aircraft such as unmanned aerial vehicles.
[[On the Thrust of a Single Electrode Electrohydrodynamic Thruster|http://www.degruyter.com/view/j/jee.2015.66.issue-2/jee-2015-0019/jee-2015-0019.xml]] :O
[[Performance characterization of electrohydrodynamic propulsion devices|http://lae.mit.edu/uploads/LAE_report_series/2012/LAE-2012-008-T.pdf]]
Noone talks about power storage and supply problem?
“The voltages could get enormous,” Barrett says. “But I think that’s a challenge that’s probably solvable.” For example, he says power might be supplied by lightweight solar panels or fuel cells. Barrett says ionic thrusters might also prove useful in quieter cooling systems for laptops.
http://www.scielo.br/scielo.php?pid=S1806-11172015000300307&script=sci_arttext
[[A Review of Future Propulsion Technologies|http://www.dbpia.co.kr/Journal/ArticleDetail/NODE02457612]]
__Passenger drone__
[[ World's first passenger drone cleared for testing in Nevada |https://www.theguardian.com/technology/2016/jun/08/worlds-first-passenger-drone-testing-ehang-nevada]]
---------------
//Esoteric ideas//
Lightcraft..
Pieces of [[DNA]] inserted into strands of DNA, by [[Transposase]]. These are like mobile pieces of DNA
A tree is a [[combinatorial|Combinatorics]] structure recursively defined to be {a node and a sequence of trees}.
See [[Symbolic method for unlabelled structures]]
See also the particular kind: [[Tree (Graph theory)]]
!!Types
* ''Rooted/Unrooted''. Depending on whether a node is distinguished as the "root".
* ''n-ary'', for instance binary. If each node has $$n$$ children.
* ''labelled/unlabelled''
* ''ordered/unordered''. An ordered rooted tree is called //planted//..
[[Graph-Theoretic Concepts in Computer Science: 29th International ..., Volume 29|https://books.google.co.uk/books?id=3OA-5_wx0OoC&pg=PA82&lpg=PA82&dq=%22planted+tree%22+computer+science&source=bl&ots=RdOZUPejtr&sig=8sJU8rm0SxlBX51JyxcLwRLKf_I&hl=en&sa=X&ved=0ahUKEwjmyuiAgsvNAhUsCcAKHTVPDSAQ6AEIIjAB#v=onepage&q=%22planted%20tree%22%20computer%20science&f=false]]
A ''tree'', in graph theory, is a connected, undirected graph that contains no closed loops. A //forest// is a disconnected graph whose connected parts are trees.
A tree in graph theory is a particular kind of [[Tree (combinatorial structure)]].
Trees are often drawn in a "rooted" manner. However, topologically, no node is distinguished as a root, and we could choose any node to be the root in this representation.
[img width=300 class="img-centered" [network3.PNG]]
__Properties__
* There is exactly one path between every two points. If there were two one could use them to make a loop.
* A tree of $$n$$ vertices always exactly $$n-1$$ edges (seen by constructing the tree in rooted form).
* A connected network with $$n$$ vertices with the minimum number of edges is always a tree (See //Newman// pages 128-129 for proofs).
!!Applications
!!!__Computer Science__
* Data structures
** AVL trees
** Heaps
*Minimum spanning trees
* Cayley trees
* Bethe latices
*Hierarchical models of networks
!!!__Network theory__
* small components in the network of a [[Random Graph]] are trees
* [[Dendograms]], a hierarchical decomposition of a network as a tree.
!!!__Physics__
* Feynman diagrams
//aka [[phylogenetic|Phylogenetics]] tree//
!![[Open Tree of Life|http://www.opentreeoflife.org/]] -- [[Tree of life web project|http://tolweb.org/tree/phylogeny.html]]
See [[Taxonomy]], [[Phylogenetics]]
Distances in phylogenetic trees is related to genetic distance, and distance in the past to the most recent common ascentor.
[[Scientists Unveil New ‘Tree of Life’|http://www.nytimes.com/2016/04/12/science/scientists-unveil-new-tree-of-life.html?smid=fb-share&_r=0]] [[Complex archaea that bridge the gap between prokaryotes and eukaryotes|http://www.nature.com/nature/journal/v521/n7551/full/nature14447.html#tables]]
[[All 2.3 Million Species Are Mapped into a Single Circle of Life|http://www.scientificamerican.com/article/all-2-3-million-species-are-mapped-into-a-single-circle-of-life1/]]
[[Tree of life image|https://goo.gl/photos/Q2gEMi9pDRYxGFz48]]
!!__Domains__
Developed by Carl Woese, using ribosomal [[rRNA|Ribosomal RNA]] sequencing.
* [[Eukaryote]] (Eukarya)
* [[Bacteria]]
* [[Archaea]]
See also [[Prokaryote]]
!!__Horizontal gene transfer__
Phylogenetic network. For instance, bacteria exchange genetic materia. [[Endo-symbiosis]] of [[Mitochondria]]. Branches of the tree can connect, and so it isn't a perfect tree any more.
Diagrams used in [[Coding theory]]
https://en.wikipedia.org/wiki/Convolutional_code#Trellis_diagram
See also [[Finite state channel]] for examples
An inequality of by a [[Function]] of two variables:
$$d(x,y) \leq d(x,z) + d(z,y)$$
It is a necessary condition for a [[Metric]]
[img[https://media.giphy.com/media/26h0pKFFBDAteFzZS/giphy.gif]]
An [[Enzyme]] that helps [[Glyceraldehyde 3-phosphate]] become [[Dihydroxy acetone phosphate]].
See [[video from edx course|https://www.youtube.com/watch?v=SrkK-wJ7j_I]].
It is a diffusion-limited enzyme (the rate-limiting step in the reaction is [[Diffusion]] itself). This is also called kinetically perfect. There is no point in [[Evolution]] to make it any faster, as it's not rate-limiting.
Neoplasm is an abnormal growth of tissue, and, when it also forms a mass, is commonly referred to as a ''tumor''.
https://www.wikiwand.com/en/Neoplasm
An ordered collection of objects.
Tuples are found, for instance, as elements of a [[Cartesian product]]
https://www.wikiwand.com/en/Turing_completeness
A [[machine|Automata theory]] that is universal is an [[Universal Turing machine]] is called ''Turing complete''
A class of abstract [[automata|Automata theory]] that have the most computational power* known. It can compute anything that can be suitably represented and solved by a step by step procedure ([[Church-Turing thesis]]).
,,*computational power refers to how many possible computations, i.e. sets of instructions, it can perform. See [[Theory of computation]],,
[[Math 574, Lesson 2-2: Turing Machines|https://www.youtube.com/watch?v=oc0kPb-Hgvk]]
The main difference between a Turing machine and a [[Finite-state machine]] is that a Turing machine has unlimited memory. This is implemented by giving a Turing machine the following components:
* Finitely many states in a ''read-write head''. The states form part of a [[finite automaton|Finite-state machine]], and may be called the "program".
* An infinite ''work tape'' on which the head can read and write. This is the "memory".
[[Architecture of a Turing machine|https://www.youtube.com/watch?v=oc0kPb-Hgvk#t=4m35s]]
[[Formal definition of a Turing machine|https://www.youtube.com/watch?v=oc0kPb-Hgvk#t=7m20s]]
A //configuration// of the Turing machine consists of the state, the contents of the 2 tapes, and the position of the tape heads.
Example: [[Math 574, Lesson 2-3: Turing machines - an example|https://www.youtube.com/watch?v=3y1KgxdTIMI]] that accepts the language composed of strings of the form $$0^n1^n$$ (see [[Computability theory]]).
__Halting & output__
See [[here|https://www.youtube.com/watch?v=oc0kPb-Hgvk#t=14m35s]] for a definition of the output of a Turing machine (only defined if the machine halts)
!!__Types and variations of Turing machine__
* Single-tape
* multi-tape
** Typical one: One read-only input tape, $$k$$ working tapes, and one write-only output tape.
* [[Universal Turing machine]]
* [[Turmite]]
In computer science, a turmite is a Turing machine which has an orientation as well as a current state and a "tape" that consists of an infinite two-dimensional grid of cells.
--------------------------
https://en.wikipedia.org/wiki/Turmite
For [[Simple contagion]]s, a node can get infected by simple exposure to another infected node (possibly with a certain probability or rate). These are mostly //compartmental models//, and their extensions are used to model mostly biological contagions (like infectious diseases), as well as some IT contagions (like computer viruses)
For [[Complex contagion]]s, nodes get infected by more complex processes, often involving several other nodes. These are often used to model more complicated social contagions and phenomena. See [[Social dynamics]]
See also wiki page: [[Complex contagion|https://en.wikipedia.org/wiki/Complex_contagion]]
Types of models used in the study of [[Percolation]], and [[Percolation theory]]
!!!__Site percolation__
Remove nodes (each with a given probability; or a fixed fraction. These are the same in the limit of infinte $$N$$). Can have
* "Random attack". Remove random nodes.
* "Targeted attack". Remove nodes preferentially by degree, or by other metric. For an application of targeted attacks to the problem of influence maximization see [[Influence maximization in complex networks]].
!!!__Bond percolation__
Remove edges
!!!__K-core percolation__
Prunning process for obtaining K-core of a network: one removes all nodes with fewer than K neighbours, and repeats this process
!!!__[[Explosive percolation]]__
Percolation processes that show a discontinuous, or at least very steep phase transition.
* Achlioptas process
* Half-restricted process
* Spanning cluster-avoiding (SCA) process
!!!__[[Bootstrap percolation]]__
http://research.microsoft.com/en-us/um/people/holroyd/boot/
An "infection" process in which nodes become infected if sufficiently many of their neighbors are infected. Related to the Centola-Many threshold model for social contagions.
!!!__Limited path percolation__
One construes "connectivity" as implying that a sufficiently short path still exists after some network components have been removed. To appreciate this idea, imagine trying to navigate a city in which some streets are blocked.
!!!__K-clique percolation__
Percolation of K-cliques (completely connected subgraphs of K nodes) has been used to study the algorithmic detection of dense sets of nodes known as "communities" (see [[Uncovering the overlapping community structure of complex networks in nature and society|http://www.nature.com/nature/journal/v435/n7043/abs/nature03607.html]] [[pdf|http://arxiv.org/pdf/physics/0506133.pdf]]).
!!!__Percolation in [[Multilayer networks]]__
* Percolation in [[Multiplex networks]]
* Percolation in interdependent networks
!!!__[[Non-self-averaging percolation process]]__
A type of process that is non-self-averaging, in the sense that the relative variance of the size of the largest component doesn't vanish in the thermodynamic limit.
* Fractional percolation
!!!__Correlated percolation__
!!!__[[Directed percolation]]__
Percolation on a directed Network.
!!!__Other__
* Invasive percolation
* Quorum percolation, and neuropercolation
* jamming percolation. showing a combination of first-order and second-order transition properties.
* [[First-passage percolation|https://en.wikipedia.org/wiki/First_passage_percolation]]
* [[Multi-percolation|https://arxiv.org/abs/1101.0775]]
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
A kind of [[Separation process]]
https://en.wikipedia.org/wiki/Ultrafiltration
An ''ultrametric space'' is a [[Metric space]], where the [[Triangle inequality]] is replaced by the ''strong triangle inequality'':
$$d(x,y) \leq \max{(d(x,z), d(z,y))}$$
This is equivalent to saying that //any three points in the space form an acute isosceles or equilateral triangle//. This can be deduced by applying the above inequality to all sides of a triangle. The equilateral case corresponds to equality.
What kind of space has this structure? The answer: a nested (or treelike, or hierarchical) structure. Consider a [[Tree (combinatorial structure)]], where the distance between the leafs (points in our space) is defined to be the number of levels one must go up until their branches merge.
https://twitter.com/adamatzky?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor
Physarum polycephalum [[Physarum machines and physarum solver]].
[[Bio-inspired computing]]
[[DNA computing]]
Membrane computing
See [[Computability theory]]. Basically, a problem is undecidable if there's not an algorithm/Turing Machine that could solve the problem in all instances.
Symbol: $$u$$.
Non-SI unit of mass (equal to the atomic mass constant), defined as one twelfth of the mass of a carbon-12 atom in its ground state and used to express masses of atomic particles, $$ u \approx 1.6605402 10 \times 10^{-27} \text{kg}$$
By the definition of [[Avogadro's constant]], $$A$$, (see [[Mole]]),
$$u = \frac{1\text{ gram}}{A}$$
https://qunitjs.com/intro/
__Test-driven development__
''Universal Artificial intelligence''
[[Marcus Hutter - What is Intelligence? AIXI & Induction|https://www.youtube.com/watch?v=F2bQ5TSB-cE]]
[ext[THEORY OF UNIVERSAL LEARNING MACHINES & UNIVERSAL AI|http://people.idsia.ch/~juergen/unilearn.html]]
[[How to learn an algorithm|https://www.youtube.com/watch?v=mF5-tr7qAF4#t=15m55s]]
https://www.quora.com/What-are-the-differences-between-Machine-Learning-and-AIXI-G%C3%B6del-Machine-regarding-the-feasibility-of-AGI
__Methods/ideas__
see [[here|http://www.scholarpedia.org/article/Universal_search]]
* [[Universal search|Levin search]]
* [[Hutter search]]
* [[Optimal ordered problem solver]]
* [[Godel machine]]
The fact that it can learn anything, reminds me a bit of how single-layer neural networks can approximate any function with enough neurons, but deep learning is much more effective. Maybe we need a more effective UAI? Or why are these ideas not catching up?
http://www.hutter1.net/
[[A Gentle Introduction to the Universal Algorithmic Agent AIXI|http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.11.8797&rep=rep1&type=pdf]]
[[Universal Artificial Intelligence|http://www.hutter1.net/ai/uaibook.htm]]
[[AIXI|https://en.wikipedia.org/wiki/AIXI]]
http://link.springer.com/chapter/10.2991/978-94-91216-62-6_5#page-1
[ext[http://people.idsia.ch/~juergen/goedelmachine.html]]
http://pybrain.org/
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/
[[Project Malmo, which lets researchers use Minecraft for AI research, makes public debut|https://blogs.microsoft.com/next/2016/07/07/project-malmo-lets-researchers-use-minecraft-ai-research-makes-public-debut/#sm.00001d4i2xwoqkfi5vv2d7q6j0asm]]
!!__[[Solomonoff|Ray Solomonoff]]'s [[Universal inductive inference]]__
It is based on performing [[Levin search]] over candidate answers, to preferentially search simple ones. However, we should combine this with probabilistic heuristics that are learned from past experience (an example of [[Incremental learning]]).
https://en.wikipedia.org/wiki/Universal_algebra
http://www.universalincome.org/
http://basicincome.org/news/2016/08/basic-income-new-era-capitalism/
The map of the whole [[Universe]]
//aka ''Universal prediction''//
It is based on performing [[Levin search]] over candidate answers, to preferentially search simple ones. However, we should combine this with probabilistic heuristics that are learned from past experience (an example of [[Incremental learning]]).
Developed by [[Ray Solomonoff]]
See also [[Universal probability]], [[Universal gambling]], [[Induction]]
[[Solomonoff's theory of inductive inference|https://en.wikipedia.org/wiki/Solomonoff's_theory_of_inductive_inference]]
[[Jeff Eldred Introduces Solomonoff Induction|https://www.youtube.com/watch?v=yXkEpzexYIU]]: Introduction about [[Induction]], and about [[Baye's theorem]]. He then goes into [[Kolmogorov complexity]], and [[its relation to Solomonoff induction|https://www.youtube.com/watch?v=yXkEpzexYIU#t=31m05s]], and [[Turing machine]]s
!!__Principles__
,, See [[Ray Solomonoff paper read by Marcus Hutter - Algorithmic Probability, Heuristic Programming & AGI|https://www.youtube.com/watch?v=wMcRMO9ejeM#t=3m32s]],, It is based on:
* [[Occam's razor]]
* [[Principle of multiple explanations]]
!!__Convergence theorem__
[[Description (vid)|https://www.youtube.com/watch?v=wMcRMO9ejeM#t=7m30s]]. There are apparently problems with self-referentiality, when the true probability distribution governing the bit sequence, depends on the induction machine itself. There are problems with reinforcement learning.
------------
__//More notes//__:
[[Bayes|Bayesian statistics]], [[Probability theory]], [[Human learning]], have similitudes.
"Information packing problem", Shannon. See [[Data compression]]
Carnap's probability theory. [[Korzybski]]-like way of avoiding the problem of verifying probabilistic theories?
Huffman, Minksy, McCarthy.
An inductive inference machine (paper where he introduced the idea).
See also [[Grammar learning]].
!!__Practical induction__
!!!__Optimal approxiamations__
__Main idea: Willis' computable schemes (''Resource bounded algorithmic probability'')__
<<<
In 1968 I was asked to review "Computational Complexity and Probability
Constructions
a paper by David Willis. It was the first substantive response I'd
seen to my 1964 paper giving the four models. I found his paper to be excellent
Willis avoided the "halting problem" by defining computationally limited Turing
machines that had no halting problems. From these machines, he was able to
define probabilities in an exact manner. By raising the computational limits on
his machines, he approached the behavior of universal machines.
In addition to its value as a rigorous treatment of a subject that I had
treated relatively informally, I was able to use Willis' results to prove that these
induction methods satisfied my "correctness" criterion. The methods converged
surprisingly rapidly to the correct probability values
<<<
"While Willis' work seemed closer to practical realization, Levin's was a model of mathematical elegance. "
__Algorithm__
[img[https://s14.postimg.org/uoc5hjmm9/Selection_593.png]]
These kinds of approximations are used to defin ''practical probability''. Our particular algorithm/implementation will depend on:
These methods are optimal approximations. ("By getting as large a value of the sum as we can, we get as close as possible to Algorithmic Probability in the allotted time.")
!!!__Suboptimal approximations__
An example is "The VH method", by Van Herdeen, based on the description of Boolean functions that predict binary strings. This is like just taking the first term in the sum that defines algorithmic probability. Thus it is a rather crude approximation.
Other methods:
Minimal message length
Minimal description length. Stochastic complexity.
More.
!!!__Computability vs completeness__
[img[https://s9.postimg.org/m4dtwi9sf/Selection_591.png]]
!!!__Algorithmic probability (i.e. universal inductive inference) as the "gold standard" to ''evaluate the utility of induction methods''!__ (see also [[Universal AI]]!)
[img[https://s14.postimg.org/9mbw04hq9/Selection_592.png]]
See [[Randomness]], [[Complexity]]
//a.k.a. algorithmic probability, Levin's probability distribution, universal prior//
Probability distribution of outputs of a [[Turing machine]], when fed random inputs. Apparently, the distribution is rather robust to the probability distribution of inputs, thus it being called "universal"
: [img[http://ecx.images-amazon.com/images/I/51nSFgWgn3L._SS36_.jpg]] Imagine a monkey sitting at a keyboard and typing the keys at random.
::Probability of an input program (string), $$p$$, is $$2^{-l(p)}$$. <big><i class="fa fa-hand-o-right" aria-hidden="true"></i></big>simple strings are more likely than complicated strings of the same length.
[img[Selection_169.png]]
__Universality of the universal probability__
See [[here (vid)|https://www.youtube.com/watch?v=wMcRMO9ejeM#t=7m30s]] also
[img[Selection_170.png]]
Remark. <b>Bounded likelihood ratio</b> The likelihood ratio $$P_{\mathcal{U}}(x)/P_{\mathcal{A}}(x)$$ is bounded, and doesn't go to $$0$$ or $$\infty$$ for any $$x$$, thus no universal probability can be totally discarded relative to any other in hypothesis testing. This is essentially because any universal computer can simulate any other, and //in that sense// the probability distribution obtained by feeding random input into one is also contained in the distribution obtained in the other.
In that sense we cannot reject the possibility that the universe
is the output of monkeys typing at a computer. However, we can reject
the hypothesis that the universe is random (monkeys with no computer). <big><big>😮</big></big>
[img[Selection_171.png]]
<<<
The example indicates that a random input to a computer is much more
likely to produce “interesting” outputs than a random input to a typewriter.
We all know that a computer is an intelligence amplifier. Apparently, it
creates sense from nonsense as well.
<<<
__On the machine dependence of UP__
<<<
That Algorithmic Probability was relatively independent of the choice of
which universal machine was used seemed likely but was not altogether cer
tain. It was clear that probabilities assigned by different machines would differ
by only a constant factor (independent of length of data described), but this
constant factor could be
quite large.
Fortunately, in just about all applications of probability, we are not in
terested in absolute probabilities, but only in probability ratios. I had some
heuristic arguments to the effect that the probability ratio for alternative possi
ble continuations of a sequence should be relatively machine independent if the
sequence were very long
The second half of the 1964 paper was devoted to examples of how this prob-
ability evaluation method could be applied. That it seemed to give reasonable
answers was some of the strongest evidence that I had for its correctness
<<<
---------------
[ext[The discovery of algorithmic probability|http://world.std.com/~rjs/barc97.pdf]]. See also [[Universal inductive inference]]. Solomonoff defined 5 models which are variants of UP, discussed in that paper. They are based on different constraints on the Turing machine, and on defining probability in a frequentist way. Some of them were used for sequence prediction.
See [[here (vid)|https://www.youtube.com/watch?v=wMcRMO9ejeM#t=4m41s]] for description of these.
__Other related models/work__
[img[https://s3.postimg.org/s2shmigg3/Selection_589.png]]
[img[https://s13.postimg.org/brd0ubrd3/Selection_590.png]]
[[Levin 73. On the notion of a random sequence|http://www.cs.bu.edu/fac/lnd/dvi/ran72.pdf]]
[[Levin 74. Laws of information conservation (non-growth) and aspects of the foundations of probability theory|http://alexander.shen.free.fr/library/Levin74_LawsOfInformationConservation.pdf]]
[[Gacs 74. On the symmetry of algorithmic information|http://www.cs.bu.edu/faculty/gacs/papers/gacs-symmetry.pdf]]
[ext[Chaitin 75. A theory of program size formally identical to information theory|https://www.google.es/url?sa=t&source=web&rct=j&url=https://www.cs.auckland.ac.nz/~chaitin/acm75.pdf&ved=0ahUKEwjpseG51tjOAhVF6xoKHTvaAx0QFggbMAA&usg=AFQjCNF88CYW_OPlUyAYc90K-SfwmLg2eg]]
http://link.springer.com/chapter/10.1007/978-0-387-49820-1_4#page-1
------------------------------------
__Physical algorithmic probability__
[[book|https://books.google.es/books?id=UEQwCgAAQBAJ&pg=PA131&lpg=PA131&dq=physical+theory+to+algorithmic+probability&source=bl&ots=h2lFxS7jhr&sig=oN7_vKrmfMrOCSbuGUo7wEdmBN8&hl=en&sa=X&ved=0ahUKEwjXtpeglN3OAhXLuhoKHXHzBHoQ6AEIPDAE#v=onepage&q=physical%20theory%20to%20algorithmic%20probability&f=false]]
[[Ultimate Intelligence Part I: Physical Completeness and Objectivity of Induction|http://arxiv.org/abs/1501.00601]]
[[Diverse Consequences of Algorithmic Probability|https://arxiv.org/abs/1107.2788]]
//akak UTM//
A [[Turing machine]] that is able to simulate any other single-taped [[Turing machine]]. Alan Turing showed that these exist. A machine that is universal is a UTM is called [[Turing complete]]
//aka descriptive learning, knowledge discovery//
[[Supervised vs unsupervised|https://www.youtube.com/watch?v=QPkb5VcgXAM#t=4m47]]
[[RI Seminar: Yann LeCun : The Next Frontier in AI: Unsupervised Learning|https://www.youtube.com/watch?v=IbjF5VjniVE]]
See [[Machine learning]]. Given a set of data $$D=\{x^{(i)}\}_{i=1}^m $$, finding "interesting patterns" in the data.
[[Intro lec by Andrew Ng|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=34s]] -- [[Unsupervised learning|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=1m40s]]
Some of these algorithms are useful for [[Supervised learning]], as a previous step of [[Model selection]], for instance for [[Feature selection]]
They are also useful for modeling the prior in a [[Generative learning]] approach.
[img width=300 [unsupervised_learning.PNG]] See [[this video|https://www.youtube.com/watch?v=QGd06MTRMHs&list=PLA89DCFA6ADACE599&index=15#t=34m]] to see how the models are organized
!!__[[Clustering]]__
!!!__[[K-means algorithm]]__
Community clustering in networks
!!!__[[Mixture model]]__
!!__[[Generative model]]s__
Given a data set of $$x$$s, build a probabilistic model $$P(x)$$, for the data.
[[Vid|https://www.youtube.com/watch?v=ZZGTuAkF-Hw&index=12&list=PLA89DCFA6ADACE599#t=18m20s]], can be used for [[Anomaly detection]].
!!!__[[Mixture model]]__
[[Gaussian mixture model]]
!!!__[[Factor analysis model]]__
!!!__[[Density estimation]]__
Often refers to non-parametric generative models.
!!__Dimensionality reduction__
!!!__[[Factor analysis model]]__
!!!__[[Principal component analysis]]__
------------------
//Others//
!!!__[[Independent component analysis]]__
!!!__[[Boltzmann machine]]__
[[Restricted Boltzmann machine]]
!!!__[[Deep belief network]]__
!!!__[[Autoencoder]]__
!!!__Sparse coding model__
--------------------
Useful [[Optimization]] algorithm:
!!!__[[EM algorithm]]__
------------------
[[Self-organizing map|https://en.wikipedia.org/wiki/Self-organizing_map]]
Restricted Boltzmann machine
Autoencoder
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gbApGXKOJ+X7XqWqYVgN/zl6ZyuZKvG+cjlQXBi154CJG/gfGyhNz16elO8rRN6aiVL+s7wCMMrpr6F4zOKGtJrSqS1tPcLG9YGOATXexcIl855aycPc1XSO4obxI00gkdHKZaDAuLNM67VKxyNMZGQlg4O26yCCAE0BgHTNCynBwiHhoJiJqNLavP+0dcNu77sWNrSfsCos80S4Z/ou4OL7XMDEgJO+32FKtdYC7ILy/XzZlFzzFHfzZHvQXMUlS/YX0FCBAKgAHD+Pazhn5dYhG1syfv6zcFreycCJx2F752nrGrxscw1MMGhevRGNTrNRcNXCJMmqv7J9XtU1E0XvxoESt+2eksFE9/W2HSuF6T2q79ZKfIf14koGrxVMXPbt2fXxm6cR50jPDRPdPweHwyLf1womDgh/Z1/6N+eyb6vse1n5s3Ox38PNFc/9kUCC/qvCZEqV89aU8ryiPGLpTmmumj4tXUrEhadTy696TinfUrtgYju+i8OEMLRwxfuoUx7eWlbPJV7cMym8E+XBXBEuyVCyLrlxbZJBBcNaMfQmAFOjBIFXAZOq6sBRp6VbYnffbV3nTHTztd5cuq+BIn1bFSQ5TCJQ4rk5TACEexjAwcW+htcSq7JoaPfGedY5Pl/xZtBBSktL9R7AY/j003Dmxndh5MwnNtaEEfDmnUjeLRi4FDCJvaLKhsGk/QjDUIVJk/JMYICoV/VYTMCs52CJ+w0ourcZZzfQeo+q0Wol/w7/ttijSwlbsm0l4ipcqt9tz2shB8mLwSSDhuSwyPe1gokN1vR3lcxdV6KmBObfEb8zxamu83Nfhf4rwCQ3cN5GYdVJNaoa/1crnuGQmKlSPppC5A0HguURpTfSYVP69P2KjwIuKc/60hXvzTLBRBDkG0qQqMjCOIVz7XkGE6URKVbTltN0w1uRUUS+LTlUoudSBokb1VqDXyc3+jKgBoG6c15EzwETqqyYIgWIABXW8UIcDojvmg4m8dtTeBBmCkeHiSvCJK4DENpKrLfW5iEBQe/QNhHW7ZwIq3kHZlhQ/sm9miUK8017j4cjxx+FU9e+DRMXPrcGeRrhl2+J7SQrmVolwcVg4nXvJeOgFyiVZpNxcKPpic8TYzWhOzCK0k52zDJAcV5jv8PFvBW6MnI959tzlAHIFBjnlDFmIt7bwFD9vqQcJiYlYDtWfHezgcxlmTWpBBN71x8PJl43zDszWnn5jtGwaieNs8PFt5h7r2N8TxGPr0h1MLEw0zvn4WPnWphWIPAiSu0kuUogqYEJajJ2NTLYTAOcOpWh0Uqc6zBppPeXlVVtkeZSvnBg5MrTJ/mGcz3vev71e5BuY15uwKTqnVRB4eFahF+L82jrmSM10n4j/efp2pSl9QiZstdSNqjNhn0quVG37eq1U6lyH1S0hWiZA2MqWaP6lsGwbOuwtZV4Ly37lqlAoufk3+2KQFHYAF5EmJln0oAJIKF31lrGrOw9Fdq6zoc9hy+H9p4rYVf3xbCl45TBhSovrsFDASaLFe7rd43bWBPaTWiEPzx2L2zYPVF4JD5XV4SJIhWDVZRga1QYERKoHkLCzBOkgUFQcBi4PMEXpSdPtHniteMxczhIIkyy6q50bZ4pqplmJqozhAVEKip9d67KPf2dkH+Tvatn7ilgUoIGkZgyUGm/nllkskyxF0pM1Ewot3Hf6bBFbvMalXZ4fyCCt+KeSu23vISqMIken9b1/n4O4RM9wlcDkyZw1KkGJjNRbhRzQzqVvNQ+vV4tTEoeiaUz0iLh7fGjOEjbUTpOvtW5ERj+LtyD9Kp7cEzplm1vL2n6TgdFRQaRyjc3n6d3kCwfoEo+sHW9ZyntI31L4aEoLVtJfCrPZIbG3YFQunYqcd/KPby31vMoTgIZ3x2IUO3l7SPsM3jovJmApBBhovDxqqzcu2Afnsim9hMGj56xB2H49LMwevbzMHjyaTg0ci/sPnRZHsqkeS0RJn5tr3khnQPXzSsBKEeOPRKQjlu7SQETCU/lNQOJXsBhYkYBg1oxDCZPlDKKBUgQibwCk5joGyUfM6y6NpcZYUvAMZPlMCm8E+3PjXO8z4vBBJW+R7JvziCSKzeWqLhOAe7383eK31IW72ntUZJnnDwDEe55KSyXx4uBQwmiJL0bdcBetYVXslMJpX3gRth84Kx5LXhY+aSXM1UeNjMR1/AM84J4LmFXuadVc6EaQDyPauFR1QvCBAGU/xIwIU+ZPF80wGE955RuWPq+CMrGe+SwYF+cNy3KztH+95YfND3fdzY0LUxcyiPkh3y9kOWRWJgq0j1GE+PpkgGsGv1cdQa9EOdUr2+l/J7Zfavb08lmE34OTQsSiXCgigoQ0OYxR+lslmwnDemABM/jwNFbYejUJwLCt+H09e/D5MWvBYYnYV//jbBVBdFY1aXv030cSAsV9qu2DQtCl6y95MSVr639hHYUIAJM8Ep8/TUzXoosq1/HELjMCLSGibvEAIMEXoBEH2EwkQwmDpIaQ24GWcdymORAsftov98jVyugeLVWaX9+Xdpn56X3cIM4nTiveH89o+k5FfEMa4uqqFHqcjUgksPE48YbKHMVMFECWEEXvqM3Q9fY/bDj8CXzWuybiMMZfptJaaD0jdPI7w1EHGzuDeX3xTPB0NcB4rlUV61VlWDi8obhmcphUq3Kmkp1hrRZnPuqYRK9YIMAsEjKG70jRBqeA1AADgUoljdA4efxTXXnPJcIF55ZUeGhSz540rr5+37lzwIsEuueT/JCVdGOgpTWPC/UKYeAGf7cuMtYN0Ejqbi+5lj1nk33nUJ1MDFvRfeNHlejGs/aUdL6VAImtJk4TGg8R0yhAii6Bm+bFzJ27nNB4dPQO/5QELketh84F9bvPiYgjAg68o64H2GqMAYmC2S/qL7a0XXWenLhmdCzC7hQ/YV3ggBKhIkiiS57dbPvNhkWjKTDpOJRmDIIOAjcgBfGR8/KjRbHyBSWUdy7aQGkqnLD7crf1/al9y2u0XZxrgLf3gvxbum7CQsvaZsUwC3DZBpx7wIeU2hKmCi8CukdkJWqkoDJ/uE74fCxx2FX31WDSXx2fFd/95mI72sqRLSQhxlhRCYjs/A+ZMI87CJMABv3f0kJGLlqgeJyoDhUMkNbK4CCUS2B4FUIA/tqYVIAJRnqwgMAKBkYeb6BT0YeMLy37KDyaJeJ9RwoxXkVmLD9PPL7laX8J9lgSr23DZxMS9uXQ8Wl/FpUfZEXksr5QQUZpTPSfKEEgiYYVI2+jHjpeCa7Pt2r7nhJ1fu2kE1TLzXGkCSY6B7mXeg73OPyfTlcWslggg1RnDeqqPqsjWT3oUtWtTVw/OPQN/EodA7cNMCs2TEWAZKmWfFl7CasfK3wn6c4WbKhz6q1GGMyefGLOHhx8KbtW7VdENka206szcT6fmMQMlWNixuP3DhXYeLeRC7gwLkYbTM8elb+DIwW96wFEzBJGcdgoo8rCTAkKOTKjR1yiLiqHo29m85zw4gwgjGBxkQajWJ9mEynl4ZJpjJMGgl05c7xcGD0Xug98VHY3X/NMkB8dgzfJq9zCvFtJl1b/ZY6cQ3Ps3fZkv7fAOSUyC3sDCbcK4dJekYh3z9TZdfM0FsBFuax1B2XHChmhJsM4QsqGflXDRNUwET39ucVQOGZDpIKRN5ZesBUBUoVCK8SJhFSelcpdu/Px435vgiWOqCU8orSXFN+IH9m+TUCwDWF0Z8JTIr71Z9nmjFMGHzYGNFubSXs5x68u/KKg6QARaZ8v0PIzqGwK7sMAGL1VK/1zlq/a9Ia2zv6rll7yfbOs4G2EboDAxvk3YQjSBSWCmPGo1BVNkfpbMHaw9ZuQi+u0XPPzDvpnXgQdhw4Eyd9lGcCSGycSVGNkiIENYwLmRajkYyvGWRFvBSNP0Y/wcMGIDKiPSqOaD9gILDqHj0Hw+LPsOfo5TFIGPkcKEWGkbxumOOFSHxatgJELjtHgZxDqHqNA8XbiyLwssRpS70zkaZ35luqRrVOBimplBlaKIcGqoNJ9CKjMNgY76Vbh8Ka3ZPh4Nj90AdM5JkQtvF7MLaKw+xdppOFgcR63Tfl4hzCZbFKJsu2DYflO/iD4LB1CCDzkJnju2DIYxqouy/7SyCbStxL13h7QOFVJMU2g2ZYAJJqu038x0baTlAyoBgEnk/RcGJEMxXHcpi8GlkDvBlu8k3DcOdqBom0JMKE9ZnAJAJlKjVfW4YJ3x5hYrUMmaowcaAUnVaUR4uqLpfivpwXZKcQtiUX+VVqAKHG6P8tYYIB5zzE/XRfq/ISUAACIDHPROu0k7DknFx5x4MSTPhWhQ2ybsA6lyoun/0Xrdii/AnABBmOe9sISyDCuje+09ZCNdls2e+5iiOqsvYcvhiOnnhinon/KIupVQDJ0o39YYn02nwBAy2QO4Pmu7Rv3noyOqV9DK8ifrW0CgOP1wAsgIa0tEOJM+rdZa59Os78WvJOSBiZ0fCIJtLZZ0bFjX8BjOjK18pBQ6LUtiVEXWOJEEikxGjwAzqZokvdOI7iOJvYvoE7jTGNHlssLTSkdyfh6hw3vtOKe85EOteebarbV5YnPLoZApNDEw/DwOlPwt6BG4pHjKMSBuEt8Q6Eb1XWhsM7ZuKZc1V44IdKc5CFD1K4ZeIYaWSlSiebO0+HNiU2/ruwvfu8zXC6VAnQ3p/CiJ5FOBfA4Blakkk9HRjAtd4SKvrmkrdk31QnzmmW/+iJZ7HEq/FjETJRbNt0JUn2HxbdtyT2p6XBQmnJlxjPCJi0TPfxYy8jM8olHU7C+0kyrySuf7DisPIpQDmkvAhUKgIENTBAOUymUiuYFNJ7xnePMPG8W+Rfl/KxK8/L1TSLGum2kS6IOy8cmCyuSV8AAS8ZQGD4qYrNxPgKV2k/1zRgMpUcKNOK87jG7hvbegwatg/wxX2mdE7J/nA8CQ/G12k78gKnjTdRHjIPR7KqMh0vug5LDo9c3ubiAiqzFUezZcMXK59v3X/KqromLn5R/NsEmBhIxItFOifCZAMZW8YzE/vmrVfErZPhWKsIXnNAmeKAEio/rgIkAGOvANLe0LJ224c4HqdH4XxARMKICYCShJceMB6FZDSs1GmZlESoBKhrc2/FPBYR0/5dLzEbqkn7Kel4fazXxTZKPXoHJVrfH4ESl7jT1vAneR2tRYze06uVCvHues9o6JN0/t9avAcJiRLKGrmzhyce2Q93mESO/ZxjJTd9R/FtdSrdl29nX/xDn/03nP+IS/w+2X5ShrTOr2EXy7XdvO9k2CcXuGfyYeg7/kh6HNr7r4TVO0cV5l0FlCgouCdq3qCWlNjIZGQu4p/M0gomBUReQJbmdN8IrcYz3DONxsif09hv76lwqd7P9qcl6do8ZS1tnTTFtQrbCB2E902aRo2qqOeRA+LDlfwHvrVmrUJ9tmT7gxVAxQVcqqKNJLaTlOSgSaoDCaqDSS4gEqvjWC/DpCQ7FpXXPHiBr6oIFsWHSXFHgSCNPYpeZ+N3wf6rY+YUYxLNllJpnvnH4hxk/E3SDf80AgbPo7p7NCmmVW8WyOV2qGSTlG5novLgxmao5JqDzVzWKbgcsrEltJXQAO/tJgxopHoLmCxUofG1CBJdLIAs3NTQ/A0yLutlZEsw6UwwwesAJhlIamESq7sAgGc4MpcDxQAiARUC0OFCRrXMqQTFdVxftKMk2f8ZlupdgIq2c6DUuc/sK2ZO1baBJC0LmAAWPXdGQNExV8MY/7gy70nvyTrvYd0klTj5gQ7/o+Bf3vy9jdII5/j7uXdRgkimxjNY5/sjTHIZVNKfLufLU12k9LJyx7C8kQuhe5TfkH4cxi58Hk7d/C4cOfkkbFFJ5gMVJrgX3olXl1JFaqVPLa0EpsRIvHPcDXqz4rVlRcP+UkoGqXhO3TlTSdcCDACSw4T0zXGHjq3Lw6mDxMzlkKjXh8hgUtmfIIP3UgZLhEvJi8hUhUIdSNDzwiQvFNaJcwqYKD+2kkFF4eveYt4e1qjGjEAxqDwvTOSpuFEvG/m/lRoFn8JOJrn9KWxTxR6hPP8XVYJad5h4m0mdl+Kai21cccBgQrsJMwgDE6akp8qLqi7GmOCdLFyfwSRKRipp/gYZlgST2WtoSE9eySrgACiARoQIS4dIHUyqjemeycjATTDRPjJpDhNKK1zvMPGf/5S8Ex137yNODOkQcbEvCog4OPISu+1L+93I5pHRKvIaxvjVytz5/P3SO7LOOxhMFG4rd4za39uASffofatHtXuk97Pv9G+rfGNJCSZV5XABJEs39YdVO0bCxo7jYe+RqwLYrXB4/F4YOPlROMtf2QSVXYcvKk469ZyDMq6kIzJ+XOL5Ltl6NKxoGwlLtw1pu19xrncSJDgeweIirbRSZtinUTQ8uialvaqXZFKYleCSqTinRgCFpXk4WpKm7Rrdy+8fq8Xk9byAYhffqWFSJwdJAyhVCShWTSaAVFQHhpmJvNqQw+F5YWJV3S1kQME+mBSvVhWpsMoU28jKQImeSvx3fS1YKjCJduk/L0xySLSqKeGY2a0kr+aaCUzmK3znqfC4UHmNsSS0mwyp0MhvfOnZRaM8VV2L5ZksUF7NYAJEyOhR8zfoRgYTGd8cJiuBCZ6Jg6MZJKgJJhWgkBDIbDGQFHAp8Dzjkgm9pEdJ1oGSw6SQ9hczC/vSAJK8j4paGdMIF5T26R1yo+xAsa7Uad901VzmTUyhumtc5XeSMhj4uwAUZiLl/93DZz8LPZOPrJeI3UPvxjtWry2k/fn3x98hSzL+hQBA8kxY4s7Sr3xzx4mwp/dS6B67G7pGbof9SlhA5ST/Prj6te1bLGjY9dwntb0tFIhW7hwNmzpPha0Hz4a17ZMGFo7NAVrrSHN6lyTbn46VxT4dn0YFRBQWpK08vWH87Vh2rsOk8Jy1rIMJ+1yejt0QxEJRDiuuT4auBhYz0SyTILG6P6oGHlV9SFVXVYJIQ1Sb0Uhe1ovDpBkWLwyTqZSBJc4AQOGzLANKqvoyoLgqngpT69cBhfaVwi79R4n0lwu7Y8Lu5CrbjVwFTEifUhUmU1V1GUzI84IJ3X8ZrNg38cBggnfCaPit+06qcHlEdog2E8GEKq0oIOLSjdYr01ZhIs+kqOYCKC1UhYmrSDAJKLHKS0oB5hnXjIAMXBkoSnAOE63nEKmDBqo3orkBnUaViMmVR1qdau9Xlb6z7lrE8dr3l4r3UHgx66j/ve3IyY9tvh9PYJzTEiZS+X0iPKoyr4R2EgGFhjYGLDF7qHkjpz4KB0fuhN09F8OOg+fklXwWTt34VRg8/XFYv2dSz9dzdB0wmS9XeMWOYWuk79a1fSceh919l8PqXWN2nIZ9Bw8yjyaBZLbuURb7qO6I6aSsVA3Cd2ubOCRj0pPGes9spgoDmCidpWsaAFK4KUwt0+oa63Ch7djg21DM1DpGOpCosiu6RQMU0jPX8Ww7T3ChKkZQmJGsdJ1k+7hWHpw0G9XAoyG8mHo12l5c9TCpq/py1YME/Y1gUlVNW5R7J+6hFG0pVS/FGuabgQJMYqeNaJf+o+UFlwIgpNOZiLSq83PPpNAUIEHzlR/mK58tUgGSqqyNys+0lZy79UO4fP/3NsUK3srKbfRI6w+v0WMrShkYgGSK7SVdtTCJVV3TKcKErsM+ENHGn3iiESSK0qBePi/p5TBxoFhirMJE+1pCQyobyyTduy7g689tPq9OtdfORC3eBXG87ptQcZ4SC33V9w/etv9K0wi/aoeMM0ZP1z8vTABHhIiWrEvzs3VcWkojB4dvyxN6ZvAAJttUalkrl/fI8cfhjEot/Exn16HzBqH3l+7TdypRylPZ0HFc3pNKN/d/F248/WsYPPM0bO06IwOsEvgq/u+v5wCUJK4rOgA0SelH39Cs5JVqSTjQrkSvN35MtGbXRFixfdQMPKDxa6xKUXERjX+EdC4LzxTecV+jhEiJLw5CU6mWdiDBhE4Q9MDhHKoiF1CPP0OYcN68THMNJA2YzBEwgElroDg8ygZ2OtWBpar/lDAR/KpAKbw6hwowx1Np1Z6SAQWPhV5g/yEwUbpyO9gk0qCU24iZqgCKnmFLtqU6iLjo1YVXQrdfYEKV1l4V/k4qb19//Ceblr5r6Kby/agKtMzNRSkQkKxX5q3IG99zmHhVVwTKdIq9uXwQo0GlhYfiUCm8EqTMXoUJ3kmjj3rDoJhx1Pm5zEBWjTXGQAFVJz/HjIpfnym/T93xH0PF96RvtO9VBoqGL55DG8m+gZth9MIXMu5fmsHEiHGMhFOCSXbP/DkxnFiXAc5hIqNtQEkiUe2UBzJw4ok8kO/ChP3O86b9gY2pqJlhlB/pIBrs6FY4S2nAYCIQbRM4Rs59Gu58+s/h8bf/HsYvfRG2Hzyr9+Ub6SVGuwwQ1PsAFDyjBBTvAOCaTfwrLHJZuiB9SBY28hTW7p4Muw5fLn5ItL3rfFizc8KqA2P4EB6ANIUDGbaiGN5xnbRC9SI96Zj5FXj7D44Ah8FEx7l3GSbEyTQCIDJ686meQQ4Uk+5hQNE7CxoGFK2bp5JkMNF98iqyqqwqKDO8VfmAxyjlvUxTV4H9J4QJUrjXQSWv+iqqvUx4LC8AE8X1y6oZIHpvpTlXDhPP/02yvNw4z5TSbSwIRXs3HUyYmwuvxGFC9fYO5V88EmBCdRfdhdfvHlf6HwyvNeqngUdVwESZ1MaYyIivyoESBTDqFI8DjYZHUoWJiwRRdAVUQFRB4jCxqi6Mhc5349EwknrfSoC6YXBYWABCZaTILyidxHEzHq0iKt2z7pgZ7JdU9Z65/DsLmGTHMFzt/dfCiDyTiUtfh/XtJ2wf78l32f2zcGr9LPYDk8wbwcAnkNCrY5kSVbtc2zEB4crDP5gHwr+hN8gFppvgvv6r1jgHTA4JLPT2MDDpWjwTug3T4+ujX/2v8Ow3/79w4vq3oa1bHozOQQCEqrHCO6mBCR6MeSYpLeQAKaR9ZBr+F7Gj+0IYOPk09J+gSu5e2NN31YDCeBggwLdbelLYeth4JvS4zveTTghfILK186zdf/XOcYM64V2AJKU5GzMATLRuBaYWMthIwMTabBCGT9dFmER5dVk0loKJIDNnDf9iP6JtQcXPkcyQJoOab1fbGKqAaQClChOgkFQAJFdrOMwIJroH51VF3m/Ao6Kaai6+p4CJizBIMDGgeNVX5qUYWKyR/jlhkgz/q1YOEpOlFaXJGhtUkp9jqgAlyb0TE+m2JBWC9F1AhPYSBi6u2TESth84Yz26bjz5c7h497ehZ/x+nJIemNC4mTd4liXDU8BEkcmARQNKFLBwqDSLYymRJIDk8v+YsF4kFoAig1dAhPW0L8IkqvBEkqqB5xnepEAhoDyTmzbEXlBWikz7AIsTe0qg1KhkrF9SdfdHHLMqGX0/BjQ/xrft7rkSaIA/duVb+68038b7c8yvLykZx7K0T0bavZCqHCZ7ey6FYwLGrY//wVzd7uHblqAoxdBIxwhZfqbD5HAb5bEsol0Od3nzEWuwv/zoj+HT3/yf4bPf/l/hzK0frOfXHKWt6BElJZjUeSXAhDEs0TtthokXMgiDdXuOhf1Hb4WTN36wKkA6KgATvBQGWa7fc9ziPL8OqHiYeNwaaLRkH+dz7417T1pb1eHxh7bu43ssLZGOUjokfdGGUmscakSJtFRa1XXx2ky6t4HBoMH0OQNJrAsupgwobkjTuqlibEvGWGpAJDPcmWKnmNYgQTFvp/O1XnfOTORQcZXgUgeTpNI3EgYJsiaAAuQrinDJQEIcTCeLl/r4fKVSnrZaHEub1fzrabb5uMEkE+kyl9tIL2Qz8HHZ5qNhtQBCGyk1D1vodKO8ap6JYHL+9q9D98gdq/6yiR69t0xrmCgjKUPXwWRqkQBSYgAeKVFUoYI8sTTDxBNLktY53mQIAYgCuhQwRaA04OHTD+QyoOi4ZXglijyA88AvPS/TqwSJq/Y52u8gQcV5+nbedeehS9Y1+PjVX4VtB85Z9Q7vzXdN9f75N1o1l4w13kgJJIp/QLJQWrK+N+yWJzGpBHXnk38MF1Q6oWprvRLUXMU3/dF7tM101SQ6Rs7iJlONhSvcL8Bc//gv5pV88uv/I5y/99vQ3ndFxvyAQQJwuIcyc5gg1uO2Q4H43bTvlBn7C/f+YJ4J1V14JXgogIV10oCFfUpXfg+/j4e9bescwpsqLcKcTg/jl74yD4X0RnxYWkrphzQV0xbGq8Y41KjWWEnN50ZAzBVA5q4byMR2NIwGkDo5ZDJjWzXEU4EkdoiZHg7R8MdrWK87ZyYqDXBE2X3je+ZVc0lVyGTeisMEeQO9rRdQYR3VxwVqjo+XV1EzMwPVwaTOHlXPQUWe1zPd3lVhslp5mcIh1dq0lVBt7T/Kuvrwj+GkCozURFD9ZXNzVWES21D0kCT2VYESvY6ZqZooHB75/0/Yng4m0UvRexBYCsiq60ZAGDhQ5nkU4LCePGmWTomlTbLGdoKKBSQBmuSB7J5KnYiYvCRQr3Lkzli6ziOfbYwZJWjvEo3xdJjsOHghHD39SThx7TszmPTw4tm8Y/H87H4G4PQN/p3zCUudAzzmCxwloEgAhTaQHZ1nwsjpp+aZXLr3u3BYpZO1KsHMFRBWCRj7BAeOU92169AFhXW/3v1AWLb1qN7x43D7038yr+Tj7//3cPH+70PHwDUd55s69Z60m0TvxOCR4GLSO7BdwETpxjpiKCxsEOuyTlv3b6VNhLAYu/hluPjgjzYGZ1PHKVPf8ScWXvsHb1lVF2HJ9QyAxQvJPRXCkeO+Tdgt2zoUOuWVnL/7+3BKXg8AJyy5Lk8vlo4kGurrjMfLKcIELyQCJVc9THLD6SV0h4oBxKu3MMRW/cUy1gyQRxtGvAIThTtLjpFv8+oqz8OsF+dPIYfFVLLCpYl3i+9blUPExqEkiBRy7wxvpRJGUQIGqoFIrfL4VbzXGf9XLdJlkZ+lGdmZzAZYGtX7ev43u5fBZPmWQfNK8EgMKL2XrTcXAxaZUqV3/L7BhhHw2IVmmFhjvB6SqR4mtJdMpylgktYRiaeo5tLHIu/2GdezANTH43aSQfl4B0gJHJLBQvLZOREGll49+b4IlzT5mu7jc3DlYKF0WXTJ4/nJULgwLtPKI/s5ZJGeX6vEQKkZg/m+jKcZLj2fhLCt65y1C5y4/l3Ye+S6NQxzfvW5fs/i/VNCKmCiY0ADARRrM8lEVdaWfSfCwPHH4drjPzVgsn0kzFN8L1c47jxwNvRPPLBpFyi5rNw+pHsfCuv2TMiwy6P59J/D0x/+v+HxN/8eLj34g41PoRoMmAAKhweAASi+bR5KIY7Hai2HKzBg275RAhJUcZ2787tw+eGfDBy0c9Crq//4R2HyyjcWZhvaT1jY2IwKSo8xnHOYyGCRRiX2cW/aYvB4rj7+Szh969fmmbCfczzOWJq3qzSUV1e9SrnxK9X/ZyrAkZ9XAYrDpGqMbdS+voNCHEAAECzJjxhQqoDIj+Rb8rMbefJsDhPbz/Vaet6fSs2eR414jolCZgMctbLvqAGKC6AksBaysFXeJpyJu4qsClLfn1eDNWDSsFczEmGsMKtTbvuqymFi+Zu0mkQ6rZOnZ0+fbj9Myd45TJbI26BTzboEFP5rQjXX/oHrYd+Rq6FNgKEnFzZhkfLvDGCiF81gYhM9rnKvow4guZphkld5WWlGsoSjhGEA8YCyiMzlkaiPrfE8HBx4GwYKoCEBEJNKksu3DdvS91Vhwv0iUGKAAhbbTkDxajADyotopuBJcoPfSDAKGzIQGbUCE4wZ1Tgnr39v83MxKp6E49fm8vvyTkVCMgGTCBKDiQw2AKHqiyosxH7aQRi8dEUguCyYUK21Xi7xPMXpUoXbtr0nwqHh29auwpI5fEiUu3suWQ+w28/+Mdz//F9Mlx/+IfRM3Fd8DCixAw89R8+dq7RWwCRtx3V9M++l96CNZw6ZROHAkvDgm5k9le9cJYPPNDPXnvyDGX3aSXyW1p6JR+HMrd9YtSDVVcR3DhDLfApry3ySz7bgsKLBvfeYgKp7n77567Bl/xnLpHZccWeZW7L4cZi8cgGHhpjg0OaiSqO8rRE5AcXOkZG0HmJJsTFfRjAZ1VnySArDbMYXUNDorvSmuAUQGDgM6FLlpVW7JsJSOjDoXdzIm4HXOSWYsJ6un6m8cDmdZgQT11RAyWRhovzgcKgDinWOUDhEmChsta8Bkxl4JkpDrhwedSrOrdwDexClc1I6tbSrcCH9NqqAG2oCiuQ2xKRviTDpD4tlZ6m+YvQ73f4ZZwJUGBqwsX3S2lMYsDhjmLDvpWGSAyQpljwaItAs4uoiS2I0KhBhcFg+DbN7GCVw1OkFYGJtKSjbZ9K7lY3wjyPzhDD6SW6kSBSUxEkYnhAwZlTdnLzxvbUHMF8XicYTTK78nn59lLZlqL2Ky3tzOUzmABSt0+BGl8BrD/9oGph8GDbtngwLdf4yubyblegOqPQyef7zMCiXmNIMI+Z7BY3LD34frj/5k7W10Ih39dHf2xQN63aNxecofdlzgYnSjz/TZR6Sv5vCwv7jkAmQ0DuF9TV4IJNPwu1P/tmMPjAhjvnmrpG71o5y4b48o6E7Vt3pAPdMmQuvB8/FPA/uvXPCvJsbT/8pnLn927BV3hhxQ7xYPKXrPHyfp5rL88B0sjyCN2JwIE1S8KG6dkBpdkBLgUXb3s04h4n3DKM7so9vmS2DWygZVoOJGfiYZzGU/PpgQ8fJ0NZzOWzcf9r+02HGnXRpapxv65XtGakAxUw0Q5i0EN9Z8l7MUynHVxUoU8IkUxUAqAqLmaoOKFYAVxg4TFpBJNeUQNG3mO2T6M1FeyeN6yu2xh5dtI8AF6aep2qLcSgsFwsoBhMHydQwweADEhLFc1ZzAZMWQLEEBkkVMERIPp1APtNmnBRQH0A7B20fyQMxSKh0BChsmakKk2XsSzAxkHCfBBPgVAw4EzyKdhftsyX7E1gMLgR6VenYyyq/Z+ENKbLjOBAlIDKaws2NFR4G7QC9k4+t/v7Q+AMzdp5Qqor3aiiHiXsmDpPCgGPMk2GnkZ0eXJfv/i5cTzDZKFd4vo4v0PGVCte2zjO2H5h0D92yxjvaUK4JHvRPp3vhudu/tpG0/F+a3iL+LPeM3Btin7fbmHg/e0fBg+9ROPg6f4mjjzwDrtYpDPjP9Z1n/y3c/PgfQ+fQbYtzwoAqr4v3/2geC14KacK9R89otkzKPRO2qS4DJref/bO1m9BmxbXuLcbrqJ7T++m+eNd1xqZOudGaSmbQEkRcwASQGEwAS5IfByTFOnBJQDGoYFhdMqwY1Dh9vtIbBo3v0fst3z5iIOmeeBjaBejVKkjwPpwDTPJ8bcae/VpvwGYG4vwZiXvzXL3ndGoFHUCSrxtUAAGKRtvixeVh/wIwcTC8Uun7vadnhIlstdJhk9ifzik8GV1f2AW9r1fLLtDSuwYDDvsBVlr6P0yAyCIxwpZ4JiWQGEyUoQppv3kuJCYSRwJJLTjq1ICJtZVUgOKJjgAh4ImYAh54CzL0hWQEKBEtEQyWAoPkiQAN2geQAcVVhUmSt5k4SCJMpOTtFPBI27lKYKmBQN7wP624l7S4Ko7pXi7ua2DB2CtxU+Keawkhli7oiICo96cOH5gwP9e63TLOOjdPLBg2L32XNAVMckOOt8A2JRMmeTt/64dw49GfwsCxRwYT2kzQYt1ng7yXAwLI0WOPdfyxdRemfYVGe8ag9As0jFGxaRkufm5/bqOUw3NKMFGaYz8J2EtGLHG/F5NeeH+FQ/6XOZ+8jr/KOUzuPvuXcHjsQVipdEIY7u2/Lu9IXtJHfw1HBIUVSi/+gyEL1ySqz9CHSrvmDSpTss19+gRvYEJ7DF2ziSsyqntGXM/Sw7kwRtPIPFIzWNMJkDRg4uBwmETvJELFz8lVGhCZYBKBgtFT2hFMzAhq3Q0hz6V6q1Oe3ZA8z0NKa1u6zoUlylscs8b3AiQyWrrGrzXjT1i+cs0QJkjfNpUaUIlhwHv79zsgZgQT0pGWFn6ZzPi/SimNRZiUQeJtfLkcKg6dohpX9zE7offztIotoJprueykeSbS8i0JKsp7wMRl/zPR+WWY1Holemiq4npZmLgcJJ4YCGQiA2/EPRCHh4u/9xlIrKoqgcK9khYyeAgcuRwgdcrBMdVxQAMQ4rQZZbE/v0+T8IIkv+fSGvFjfxP3AirJODYBhQTAugQ8umUsT938wUrMDMhjPwmGpSeSqWRz8WQwcaB412COARMMOp4GY0xufvQX8z427Z4I8xWveCZUd63QN+Kd9MtLoucHUzDQlRjRtZCBjngnlx/8wboY0lOEROrPQEx/zTuQgPnnNMChVwnLzXtP6D2GFTYyihhtU4TJ4vUx3PhtaT8G/+k/hQef/48wcOLjgLdC+O05fFme0W/DjSf/EI6eeGpw8J8COUj429ycFVGzAIkUtw8qcw0ZnG59/E/hhoC0XyV04g7QuGfEP7ltmVQX5rUinskP00ow1bc6RHKYLGJWXDQDmDR7J0o3Coe87p91jBfGc53Cvv/k03D8xvdh8NxnYc+R62HNnmOWZznXCogKPzNy3CcZ1f8UMJlGBUwMLNFgOxAdFLUwUZz58SLMsnVXCQQvKgvbCOtChPkUIPGfkEUPpQwTA1Fad3tCLcgS2WLaOr0Q5wU5BwpLtJTeXFRzOUi87aSsBkgKmGSwiD+/qtfzwIQAIjJiu4gyw1QwSSq8DdZdwEPnVcHh1Vi5QfdjuRrnxO3iPhUI4cm0AkodTIp76d2K986lY/xSE/G7TX6tGRWB4jBxFUBJIhHQRkI7AI3BR099YoPoOEbiiYmjYrBqFWESVfZMcpgw2hXjz8DE20//GkbPfBK2dZwQSLrllcig63z3TroGbthxBjjd/+y/Wf90eoK1HTxr7S7sZwbSg4ILpR/uz/Qr/OGN57KP9pb2nkvWM+zA4M1waOSOjbzdJljxa1ILE6UhQEBYEWZo/e7J0CtvDWA8+vJ/hJEzn4ZNgizgASbnBZObAsGgDOPq7aMFBPgHdlQDJhEkVPWxflDxdFRAvBOuPfqzAPnPeqd79i6cEyES48rjbr7Coz7Mm9WodqxXrFJFeK7NVVpA5HlhUgKKVfOUjSAiz2I8aScZufBFOH3nt2Hs0tfhwOi9sPXg+bBix6gVCN3omXeipRvVHxcmr0YRIq74HdPBxL2SPKxaycPmpdQUjq0A4gIguSI8YlsLIIpq7FOcSVRzuVfibSXIgJJ5KUWbyZQwkUEpftfb5Jk4OJhBuAwSBExi20p9d8AqTIgMIiY2siuDABSMdgYVAwrCuGOckbbd6EfD7wa/bNCryuHgAiKuJRj1zXg2UWwvScvFSOcs2qD3rIh9+X3ivSJM6kCyPBfn6N4YKjQjmCiBEvH03qIhmW6qjIRnFDzHrEH4OWDiPacw6tbo7W0WSguIbRIQHgKeBZ7JmDyP7ftOFV6Jeygrldi27ztpjfH+/+j+Y48MJEzNACBOXf+VAYVqLxInz6Th3Z+zbf+psE9eEPN/tQtgHX1XwqHRO2FEzwQuGwSMJUozESaHFD7RPacKbG3bWOgevhOuPPhjePL1v8sj+jq0dZ2zY/v6r4WLd3+n98cz+UjvQxdHwlfhoPAETCyBRwRIDpMuixu8kYt3fy+v51+tOm1t20SCSV7dlmCi8PX4mkrEQx1ATHq/oj2NvILXamkuQsPF9kxggmphoncovJJkwIALeZbCHtVa41e+CSdJa4IKMKENheov8i0FQ84vjLHu456NAWWmSvZhpvIpXlqK8/ROjXaW6j2yY1IVJvYdrWDi4VUR179K1YdN6uBQCNtap3i+wUPfBjRyMMX9SVqfr2+ltxZtJQ4UpkfKPRQbYyKQlGBic3HVwkQ3zmDC/9+BRMMzmQomOl/GgURYUg1MCHgixXttldpOBAiXNcA7KLQsQMA+l45Zu0QL+bXla9z4AwqBY5PAATw2M4EfEGmI46UMm+T7/B5xnXfTO+q9HX61QNGzIkwykPCe6/XOrWCiMMP4ABPajBhTgWfCZI90FeZYK5h4W0tJigcbKGiKvbeoaqLdwqu92KbRje6Bg6c+Dtce/r3BZIdKq/MVp4guwiyXqsSyUolw4+6J0HbgjMGAbsKeCBnwBGCY4wc4rN4xHBbIswFetJMwYKpTIOK/CXgxVG9t6xRcBBGqzvBQuAf3s+o4ievoqognRYKnOu78nd+Ej7/9n9bgzzaZAU+I9hrmGAJklLgcJkDJq7wcKLOWxWquHCZ7e6+GMzd+HR5/9e9h+PSzsHHPcYOJV7d5vFkbioWv4mwacV4tSFAJJnglpOVGuqsqh4mrAElan7emARSHCfODWSk8M4oIg0R+3NZ9IUxc/dZ0hIGfAvauvqvWEE8excAWJXV9E/fx7apxrJXC/MVgUmNrMnGOAcLv7+L6bN3O1bq/TyuY2C8KZKv+5jBJ3+uy78tAEr812Vf/roo8HJq9HJcKTspD/HLCq7S8uou8smo79kr2CZjonCUKgwIm/Fo1StvKkCj+gCiK/0fMUib/EEBIH1CFtVweSq3263innVf3skXkFh8WI47Ap1STU7+2V5f2LUJar5WOWc+rFqq/VgAyOQCSB1InHa96JNErUSYmc7tsHxleStBagpThIlwaYh6cpTpmMpDoGt5TYRD/PYBRoturjA3hpISA8cHIABOq+ej6SgP8hErg2w+et2N1MMmNV1nAhLpTRENzgoniap72oTmAQuetVym0d/yB/duArr2Mio8w6bbqroW632LemXWlH6ZhIVECCqqwgAbtIPTkwjOhHYU+7DToAQRKRMADkDCppM1OKriQmPFW2I+Xg3fDPvOelEa5rzfeAyx+LXry2jfhyTf/Jg/l93rne2FT+2Tom7gXrj36Q7j2+I+C0u2wYqvicC0woiqPaj2AFGECIGYtO6D3PmDfzxJvaNehi+HElW/l9fzPMKES+lZ5Z+69xBlXZfTtPgr3FL7TyaoaieMU11ERSC66bZI2YkGKae9jevRlLmtTSZrPOJSKbCJJwcMmmAQoaT12BtA72zKuk08pzO1QmE5c+ToMnv00dI/fD3vk5e02mEzouJ6pd5uv+I42pHEP83IKI1Yx6JmKY5nNeBXi/Q0MLj3HS+cuzovGONokl8PheWHyMsqf76oPF2CSlN7dxLl8V819XI37cV1Z2AHyE7ZomezSChWEaaekNyee/ErZnKU6Rl5YKhlMrBeXQELJpwEViYDTRyGDijJrrGPTw5SpEFBh1HBD8kgACZ4Jxww+vFz6MCJPHxEjVIEmVT/QA5MIsoSYIs/gIhX9oGUsXAuREnBcco4y3nTSN7KM9wIygGhmqraVeHtJ8zkJXtm7xu06Nc6xb8nEu9q07BhKhZF1O1XYAQyWeDj0UGLQ4jGVGNu6L+qaPoMJsClDo7UwZibWdV0hPROI+DZe1M6DF2SUH4UDR5mC/niYr/1AZJHizQVM5mFglRbmKG18uKQjfCABKVxmIAFImMcLSAAA8yoECKq0gA1eCNDgd8H86XFN24h5LPQQo1cZo3CBh3smnEP7Dn3kAdLo2U/CzY/+HC7e+004euKR3vu0APg4XH/yx3Dp/m/kMZ2XceYb9+vbgMZ++1ZEtdusZZ3aDyS0TmFpsd5fz9u455je4WNrjzl/+zfyeq7bszmvuF7r5u0Qb4SF3tGWab0Q8Wn7Uljr/NghIn4PcrgAWpuAT8+nMwoQ8b88VmV/C0QCR1FQy8Q+VzFDMXlO4YjmE5bSPK0zU/MKxdkeeYZjF78IBwThbQfPhU3yUnfL61wrmCyRJ0qe4nxk12sbu0EthdsAllR3Wxuq0qi1pwrY7HtemHid/3QCHA1PXPZFaTUOBI5QKeDC+Xp+1TaZTaqxRwZKHfsxlD8fNYUL27bPwxbpXMQ7830190WN+0UIFUAyRfvOLBOkOYBCnl+1bUQwGbcq5NXbRwSYobBC+1eoYJNgEuFRuNOZ8tIsvYeskYbA1gNdBpHUD5/1D2UomLgvwoaqrvjBfKBBRB8CKAo32iNNx+081pPsXEvciEjE3QcCTGJYMbjs26B1lLZNnJ+ucTHxIPL98R4YcRmsl5UysYMkCtil95pO2bcUsrghc8rQGEyIA0oOMjgpjqhC29171ebmAih0VQVoxE+pe/A08vimKo1qnlwGGLSKgUr9NigQoGzdd1qJbDQsoOFZxxdquQiphLtA5+KtUPUFTGYt228CJngqNOTTIA8YqLKyX4AqXnClqc5iP9VQNMIDDIw57jWgGT791Ma7MIjS70n3ZYCC6+1tLkdPPDYv5MrD34WJiypND18Px698Jk/lN+HY5U/lEY0rszC+RTBZ3SlQCB4KY6Bm1WbEiZY8/8Ol+wSTvbbOc5n47u6zf7KOBcwKwLtxzD0lqgit84IBI+5j6euuun1c5+/gogqP+mtmad6q8FqhDE3VU4SHoFGV0rR7+RjBXMU+5S03kg4S0hppzvMGS6axWS1w7zt6PYwLJsyptqH9WFgrj5FfC2zefzKs3AHcVCBIaZalp+0Fygc8w/M2BsyB4r+nwJBxLBq5makKDVNmn1zYrcKeya54micfmfTcaOOSdMzfFRW2yMMvAZl9Zsd+DFXewbynTA6PuJ6dJ9XeL1e6N9caTHIpvPz36IQNtSN0CqKTyZodY9K4Lem4AmBWbhmeAUwUUBb4BDovSCBXIqsWJiu1VKbixexDuTZ9IIHvanwYAeWBEs8vXaN3sIjkfaQCBK5keHPD7PssYZfOjyDJYRI9FURGeAmVgBS9JAfEdCreNxfvnjK3w8TnpcphQhUa04JMXvnWGuGZnwvAEFeUvjzjTCfPbMjbZgwsad1F1Q1AITGRwOgosFD7gAkAYblI7xa3ZRgxlHrneUoTseqsyxrttgoS+wWNg4M3rdrLqrm0n/m89goYfQIJf3VkOocPZMjfkyGnnrZDxmtc3gwGnH+pcMyqzxQ+QARXHI+Fn/n0H3tgXsn1x38MF+58HyYvPpPx/632fR+OHL8nD6lfMJFXsw6ICCbyqjHsAAmo0T7E/ERLZCR5xocCF8fpRNApz4g5ymh7AW48N3oa9TDJlYOjbp93esihwjtRrUdY8R8YOl7wq+AcHsV6Lu1341eMU0n7cuNo6xWYmKes/MT8aMyv1qX44KdozPYMSAAMYOF9OL5UQAUo5C+uXaH33aD3XWOei9Jkys/kb+yDeyaABThwHDswlaIRlTi/Rt5NtlDKL3n6Lmpd9B55gYvzYs1Js3E2G5TCy8W3+PmvRpnBR9rO32MmKl0/lfzeWdiaFF7WBqO4IfzI8+R3907I9xEq0vaxsEo2YFqYIAt4AlkPNYIT2BZhksGEh0aQ5DBhZldequSRKDLqxLFqgBhpUbo2Xq8I98SeQcHAoIQ/FUxaKQJF36qEUff9L6Vpnp2rAbZM2peDxCY8lNFxmHjGwAvZ1nXeGt/P3v5tnA1327Cd45lkJvL7NatynHXd29py8EC0j3UDCt4Ix7Sf5QJbj8IomuFU2ligeF0tQ7NFhmaHPIg1Mtx4AcB++daj9p8T/n/SOXjDpsOm6vRdwQQDhRE/e+t7qwbD2OOZYLgBCaPpqRaj19ju3guhZ+JuOHX9a4PJ7U/+HG49/VN48s2/GEwODl0TCLvNM1m4Fq9kn7yPDoMdRpt/3dMTjQZ72nTwDAyG+gYaJPGQaOAHJlTV8ewFpM0EBO7jMLHecUkzgkmNCsApvPbIq1styOKZuPeBgId1YslUAMWltF66Jt+v/FiFicNh074T4fDE/TBx+Ut7/ppdMiZ6h30D122b4yu20dGENht5h4rHLZ2n7FfNtK2sYTAtzzAjHKHh1SqABaNWawtyKT0V3oNk9sikayW3USXpOsBRTtNR1TzA+dyvsD9I17v9sqpAvb/L3rd6frrmReX2rqq6c11NEGqhwu7WHEN+PwOKwYTBwzGvU2ikxykFSOa+Wy2QoFVbR9J0KmacZQAwfjXKA9yBUsBED7T2Ez3UxHoVJnyoXtIiIosEl8ME4PiHmPScohSS7oHoZVAY2JTozRgnA/xjwcS9NPOMao7XappnV1UAJd+f4Gmz58qg5DAhTngnvCLm5xo+91k4e+e39q8Opvzwc34U6d5Uf9mYDK07TOazvQLjF4EDNBYp3gwmbhj1DazTC2SljOFqlVhZp1TPdy7e1B+2HjhtRmrvkathffukhQvfvlLGtO/Yw3Djo7/YKPq2rrNhtkCDEaeRnuqxfh1v77sUth88Y8uh0x+Fi3d/He5++g/hydf/Ej75/t8MJl1DV5U5aJdgHrC98jraDSYAAEhRBWej9AUKAIUxp6rr7QW77TvwfI7JsPIbU0b2Mw8ZjZYAg+NWXUb65Lu0b6YwcW/EQWTHteT5tBnRFrS376qM+XiECWGXZG0kBo+kKWBSHEvHLU9aHtMzFZ6kQ7xm9062K6yPnHwSjl39OuzquSjI89viEQP/zkMX5IHQjnPUYAKADDRHr4dTN7+3iTE30esvPdeqiPQsKxVjS5ROYvV3LOk3GedMDhG3R7knAlBInw6LonZF8nxZ5GX2e3pOsvuldyqV1iW3Y7l47+p5qLBjLyi3d03SO9aq7twaVd+/ZI/ZpzCxOEjhyqwPdCph/BSdSnKg4KFEoIw2YBKBUm8ki0A3RaCUXMoUiVHNMCFh8HJWH5u/eJJ9FB+qACkC0yMlRWgjgPW+0pQwUeIvwQRVjLoZbZedo2/Vu9R9vytPgDblxbTiPBRh4O85nerel+sjTIBIhAlhXwBFz2GgIgMWgUn32H2bn8vO0fFqhnkZlTzUFO+M/LaeRskb8cQHUBYqbhnE6DBxMSZlke7FQEeOAxhK8nwfYUCpl3aBbTKcVJ+4kaJufuzCZ+HOp/9kAycZ8+KGFu+Bv78dlcHb2X1OYTAa1u4aDQfk3Ry79EW49vgP4cGX/xzuff7XMHHxmTXGL1yr91/RoW+RR7Kq09psmCH1sLyic7d+sDYR/zcLz+AdaTehEd5+BjZ2z+YbY/JKquXolw8EvJ3DOhVoOWOYEE6Z8uN4Rmv0TKYD7zhyTeGSuuMq7QIH8lNhrLU0YORASdDIQWIN9fl+ywuN/OHpjzy18/CFMCRvcPLKV/bv/uXyQqjGajt0PuwVxNmHF8mP0KjuwlPpO/YoXBFsh859GrYdPK+4VXjwXL0X722N4EoH2AfyIHbGajJIX1PI077ZI9kIs0fYiqyghcivsbEde5HyJvYo5WU/z2XpmvtgfzIZxJIx9k4LCLuVn1ecr+e9jFoBwo19a9VfhwqA8O6kGcHB00mM+8a6xYO+g7yNKBiSn72KmyEMNMA7VOKswUqwuQtYa0RdOu4B7nKooFhCeHmYlCIli5h4LyUKpHd3mREm8csI5TDJ2yLcMBfnJMXjZKDyd1fl4fN8Ilyz9wQoVaX3yt/PlDIy4toqTKzUQEQrTIgTflHLzMHAhMkLmWLFMlY6/qqUw8Q9Ut6DMKLKi0QXYaJvkfBWmAhuoa5ziLAeJbAofmlTsfYUpRumnudb7X8KO4YNKtTLr1IpeO3ucSsRT17+ymYdpt2EhnuMNu0tNLhj3AdOPJGndlIlauLusP2DBW/l3J3vw+1nfwlXHv1O2/fDpvZxva/S6vIIksUbYm8xfgJ06vq3Nv3LvU//2ToC4KlYTzG9cz6wEo+FKWGYGob3ATC061BlB3y8u3MVJoUyWDhc6mDi85TRVoM3xn8l1u89bgN6yUfW5kE6xSjIWEfj0ICId68vtk2p1xf70nU0lJN/yBukPeKCxnc8jT19l8PI+U+tzQSoL9a38TtmPJZOhRntKDTKA31+ikYV1+CZp+G6vMgRec382ZJpYGLHlCN6Bt2TZQeUT/Cu2Y+diYBoLU9/eZpkSZ7zY/k5vu750ryvdL7fw8V5PMO8IN3X7E+yQWaIM9uFMNK5vararBdVFQTIYEH4TKPaa9MxSyOkF0sfMc5jvMf04YqgT+Go/Eye9pkhAApTGTEWDqgAlNcYlMjgxNzgeICb9PCqUc0DHnlExdIBRq6rARNlghfyTFrI7iWZG46RdjlQHBQOk5QpCgOdHc/lMHFgovybfV+eCGcmzs3es6r03rmKd50pTFL444kcnnhobSZAZcPeE9FrILyy+HolIhz0fdw/diEkPvS9HEsJjqVXcxlIlD5s3ImMYxkmMqL6Fo5R2ift8I18L3FDCZcSMFUmGzuOm0EbOqvSsYCCF7JegGEgJV2Bt8jgHxq9G46ceBw2yUsBJPx0i2N0Jz51/Ztw65M/hwv3fgi9k/fC5r2TyhgY9APyHrptvAkDI4HC7U/+Gp58/W9WhUWbCZDBsGPUaYjHwOOFYNjp3sz/XVji1QAZQILwJmLX4AZMcvkEmibAIeVAYb+P+WE/3YLxxg4M3gob9I0OEzcirHvpsoCGjIPNLCGZsUgQqbapOExIf5bu9Hz/IRnQ2DdwzXpy8ZOz9fpOT7/EC9VZNMRvVhyQdok/9g+ffWaeycDJj212a9IOEPEu9ECEtANI6EhCfiuM2FTSOXmaJO9655cIpGibuLdf4/nS83GdOC+HSQEI3kn3Ldktyc5Rei8pnT+dzAPTu8xE/ryXkdvgHCSkA591pJC2OW61UYSLwsKkb2N6oeilKLwVV+albB4MrzGy/Xlh4vvd8HoExEjAwAGSTkWGDIMCFUi0gol9pAeYzqsL8LJ4V4yqhHGVcqOcw4J1azz0ktZUImAJ5PRN+ff7+lQJsLUUruk9W4l3d/FHQgcIhtD327n23a1hwvxcVG8BE/4gyJQqPyZMCBOLc70DyhNcDpP5SgNUYQGMCJKGrIeXYMT09ZyHwcT4+z/h+XbikzYUgEIVCgZqd+8la/ClFIwHQBrAa1i/Z8Ia7IdUGqYeH88GL4GqIaqtzt/9dXjw1b+Eq0/+ICP3cdjZfUagUZpZd0il7J6waseQNdwzMSXzjjHLMeNcrGFdz6ChH5C4YcfroNsyU8sAk9M3vjPviC7C3lbi3kUdSJDDxNYlA4fyENDiuipM8Ex2dZ8PXUO3FRaCiTIy+Yg8RB5h3WBCejajEWFRB5MIEVcyMApPqrks7endPZ2u2D5kPbmA+PC5Z+Ytcg75y7oHyyvZr7CnKgzwcAywAB88k97JRzpv0tKMeSF6JgABKOQ9Bg8zO4Xltbo0VyOrIkvpD9vEDBNM8so9PX2Sh+O5fE9zXrb8k+URS9NSK5hUZefo+SWQpGun01QwKbwQ3648t2pLTQqD6nkur9pCjYJGBAk9AovpqySWFDKKKkHChnDS9wGTUh7XMWY4N5gwur0WJnqBKkgK6YVwV1kvHibFgY0YggQTttmfAsY+KMk+0gNP59QFdpMUUfF9MZJRGFkSvVcZOVAKmMg9rxMuOrJtnUfXYP+e+P1a1zsW21LjO2MCnEqNkc0K9FZKGRU5FOvEcfteGZbGP9AjTOx9FNE+Pxd/EBw686n9l9xgQiLI3isqfsdzS3GVi3t5fXWsV8WAupR+tJzHfgHD5+5Cje7CgCTupwrMPBMZTbwTem+5h0IYGFQUX7SdYMgABQUBqxbTtZzDPqrBqFrpHLoZtnWdUWn4eOhgoN25T8PVR38MD7/67+Hq4z+GiUufhf0DV8Oq7Uyfw717w4ptR61KjHMZmU8DP12U8WxsjMmSvbbMgYLHMnjqo3Dl4R+ssZ5R9/T0Mm+E7+Pd+I4k1nNx3M9BDo4cJtzH70UvM7whDPumfacMJuQhDBjGjHU3LAYUUzIeCSQGEYwF0KnKQNIoyFi6lGhsp3fdMUa/K3yBC+FOPiNO6BoMTOgwQScJ4otOFLSvXBeUD8pjZNof0krejR6AsM2SUf25oZ9OpD/PB9yD+/NbZubuIy+TzlkWJeyUbv1aU8ofxT5tY2ccIjlMopEvi/1VmBTXcC8dn4nMDmYqQKB3L20nFQCpiu+tk44VBYwU/+axZiAxmAjIpClmGyFMvZDtYehAYbYHF2EsmGDwtUMfY4EtueHkhCbpxsgTAkv2u9G10dm655zVAoqWGP6mwHGl/TMGCVIEmfEi07laAMWgImOTg6OQSrrUySPW2WfeiX+L5N/s24gAdfd5Wul9oxIIKiqA4nKg1Mhh4iChaskzkUNuxfbRsG/gpsFk5NznNgqe4zG8osrvp+9I8rifTp42/JmIe9m99azYQCdPT+Fm039wro7NxftQXFUNJ2KbtgCWGFsHpv0THsPq4ZXChzimGoV1jht0OEfXEdd4KwdH7wist6yRev/R6wqPZ/IafhUu3v9duPzoD+Hk9W+07xMZ5Js6n7ERylQbqCrDixmRF3PPgEJDvrWV6JkfLO2whvf3FtPja1/4cNk+81QYaMk8YTTC00WYUfl4D/Y9ej9vEylgonf1cDDxTfo23y7CRutWzZXt4zheD94Pnslm+9PhUTNcPuDM8kgL41MFR8kIIcWZdcjhuSmsPT8Rrr2TDw0OfccfmadIuHMO4U77CL3v9uv7qQJbtkWAOXQ+HL/2jTzBP+vYDeW3AUsvgMO9CADAmCjW2Wdpi/e3dBXTaZ7+yJN5umM4AnkBLwfPh16N/KMfQ2gGMEurLodGIW37PZHBBDC4tI39MU9C5+Uqnct6Jo412bAWcjvpyuOuVXy6GoWGqsrxjQwiJsEiwcSAksNEwlvxdi3rNAFYsIf65kaVl/KdxL7XmLyRObfMGOiDCFA3Fm5MS9ILOkh8lHfpQfrouWvI/MBE9yXDZwFUp6aAtchMatrnhjEaj+mAksPE4VGnxRJTmvh3tBLhMmOYEKamyru60jvPVJxvRlalVhvPkxq+Pb7IQAxWZNDi6Pkvws7Dl3Wdwljn+OCu+veUFMae0aaSPwvVbTO40cadKKxcxIl/M9V0BgwZWfsurWNMFyquqB61fTKs1uam73RjRVxa1Z9EaZl7ARLCw+/9gYz7B8v323HaV3Z0n7OS8pETT8Lpm98LIN8aVChdU/e/f/C6YHM1bJURpMF4np7L+wEUxpccYWT+qY/N02BsB4acqWDeXrDLBi4CEqCCwacNwzyfh3+0cSmMUPfqK74PIEwFE+7hAlxUkfm2n+fr9A5jwkxgueXAGTMANhM3EkzcqNXltaLqpJU4T2mB/EVcEO5WxShPi66/1pPr8pfWPoJn4p1eyEN036b6kTCnVxedJaj6OqFwvyiPbSfdppW/EN3WASEN8iw3dpyyDiQGAYye0g3VuKRzT5+kMa517wWAkAfeXSyPcWmn7eePl92j9wU+2stins2rgz0dO0xsvSb9A7ECECk8S3Ypk4EjnTdTeNTFTa7auKmoBBLCrEYRHI1qzSYBE4HdlANFcPdfbdjEuBJVh9h7Ct1mJ8n3CiuT1l9jdl9GqtfBxJQixBNBAyQNmJSBwvUYhFiidJiUApLIygIuP4ac6kUEZvtawgTpeWSAqYBS55m4qLM1Cvu3ZipgQiTq/S0BTisSMKp51zql90es1+0rYLJM8VaBCSW8Pb1X48zBFxlUdtXel/AqjRS2d6q8q8K49F1pu6pGumhR2NAxvJFi1DxxjIGjWkjvTty4l+XfhPGnSsQ9D5Z8J8ctDmvq7y18kjjPAKN1b7wnjtfJoBdAkYfRM/HAqmDohUTJmQZ6uq7SW4zn80wARRsMPcSYKgXPhJ5dNKrTmA5A8E6o5mJqF+CC98Fxpn2hmmvy0pfWddfacvgGvXcVJuZtJFVhEke+Z9uck87jfGDCCHhgwtxYlCJt4J+BRCK+FX95HnPlMMlLti6rutG1eNOef8g7wGR3zyXB+FOr5gImXpVF/qKTBOFIry7CmHYTwpmquLO3fwhnpB0Hz1v+Ip/RjZ1ZrvnVND0PDwzfFXiumVdBOibPWbrVd7kHTvqjMIthy/MhMOEc2gy5J51PaOjnHI7nBS9Px/aNntZTekeeR8gvJZggvU9V7g2ybiDRvXJbNpXq4seVQ6OVPM5mDBOqrZBvp30lmAggBVRYJpDkKqCiOLKxZRKFxteYLp6JGa0LqQLCAlsfg3KjYUZVL1cGSSaMsI7Hdgddu1YZHqOgDEDg1AYmyo/p+UVEVSNQ64ULb0rGtio3LmTCGqDksuqtQjT+Nb4lVwEUIk1hEau6GglwamH4ysavlazU7ufWfBPLHCZkkiKDKByZOXjn4UsGk4lLX9vEj8Sdw6QAirZLGamFPOOVlKWNEkRc2u8w4RyuYezRBzRcy+hi9GOBg/vzHjKsWid+rPdaURiJgCD+2FdsAxXE9ZyneyDOY9uBwHHq8RmfwlgVjBvtJzZeZQuz7R4xA8kYCQwhYWsN/xJGG8+C6eoZtIingXdCIz49s/A2AMgs8o5gAliYp4suyUynf0ZeEO0sVEc5CACIw4R4zmHC9/JMV3Vfvs36YqVd80xkqJnBl5/GuUdSLRkXxslVY4xMijtk+1O+sTwjcAFmqrTa+y7L4/3MBiwCaAYr+jk0uNNeBaAJazpH4KUA8YsPfq9rvglb6MKt/ESVFh4EIBm98IWJ8VEMamSw7S551Ov3HLfJS8l3nhaxRWxjf1j39PXekv12DtccGnsQBs88MyhxnPTONE/AxGyc58ssnZvSfgdJLUyaJJDgHRH2lXB/HlUL1xZfKY6m0o8DkwZU7HfmWm8o+92HrgMqxe/FFS+vvbtMLqIyg3fvjAGrj5EsAjEMSmRuUMtAyeVAkUFJJUnqXb1dpC4QUemYIoRIctrXqTVM9P5SbnwjUKQMKLnKcMFjSQGUqQAK0vcTFlYq0ntPqRR+hIEZvTrpHZtV/a4ojjlMqP6pwoSMwLT2ZFKmoWeOLtpPAGAOkxwo00Gl+IY66RtJG1WZR0LDe9rmXIOJ0pjDxEuzLAEI4Y/hR4Dd9xNvDg6MqVepFNCxNBbjmf1+voctz6D6iuoYxP15lt0zew/uZbNcU20lQGDwV8p40shN2wk9tWgToQcVkKEBHKgAFG+Ep7dX7/h9a7TnX/d0JfaqMbwLINCIyxifJaXvQHG9vO3HORfjzUjzTj2jTYUHfmXthS4KaKX8pfCvQsQMEUrGCOXHaIAnXLygZaBQ+HmX7PFLXxQwsQ4uAEfnEb706qLRnQGMtFvR8+vqkz8ZhDYws7SexUzHVMH2HXti1bH8zA2YDJ5+ZiCgJ2KH0i69EWlHsUKK259kgyxtpXwGLFhStWWA0j19PAtpHZAYTGT4PW1TjVVK/wqrHCYGiIrtqZXS9suAxJWDBOXx0UozhUmpjaSqCkxcQMXhUafCU9E9/Ad+BUyYLt7dyTyAiSQzEkSoRaoyul6yoSpMKMErQVKalPjoIpAqAeiBWGyTIfR8j6QmaX8rmMQSKb3I6oDS8FBc1NGbQUuyTKGAzd05ZECx70tA4ZsVcEV4tJAb16nGmbjRq1P+bcU+h4mMWBUmhAnvv/XAWZs1+Pi1X1nPLuKEuMxh4irFdY24b1WN72ohzknifO4Te55R/RRhguHxwYh4CnT1xXvYsv+UVT9xDANGPHlYleLP0leMV9aJPx+LgqeB5+FAchVQT2HJPSn4cIy0hFcC8HhPDD9dfpmaZU/PRftfC4MWgQXeClChgX2Z3pFfGLOO54IHc+72D+Hao7+PE1AKPLR/0DWZd23EZw1MkAPD4ZGgV2xzTOfxvbRP7B+8GXb2XA7Ld4wWecsahH095bsmj0TpMweJyw0UXYOZ6dpBAiQAB43pzLE1oLCgLYTwjnkp9rLjXKC9UaCjIX7g1Efh3J3fhJtP/ypIfKL4Htf7HzLPBGN/YPC2tW/sFzg6jlwPh7Q+JKBMXv7aoLDz0EVrW6Et0/MVNR+UglkveheltIpnwnXjF78y74b8a9Agvcu2lWBSTf96rypMam1QRTY55X9imCC6fc8IJgiYpHWA4vAgzvwvtsW+JAYt8hO/195d2hHeU4ksh0khBZIDxUuiFqkkOCmWEupgoo/jYysfbwGle+UJHnmpyqTnAg0iyeWlACJ4KphQX26NsgiolIASDZLLjJAbp5Qh7J8iOVCgM4Gqfci+k++dgYpSlIVTw6hFxaobMxZ6t1xmOMy46Lvs/ZthwvdR1ZWXtnDheS6lOaahPyGgHBy5Z+9NeHlmqsKkiGcyGOFa2VeVpYUaeWa0c0rXcJ/47nwb389IdurWmbacbrw07FI1wrgQtjFagIVGdKqiMGoYUK6375dYJwzZD0A43xp/j96wgXMb9x63+CSd0GbDO3i6YQnk5ytNWpuOtq2HHI29OhfjD0zo3rteQKBxHYjQdkJPLcT8X/Y7Ye2jbYWGev4aiWfC2BRmEKbHFR4MbRwvBJPKOiIcSa+MpwEm/JRq5c5xASOOdygMkuLEjBLSd7rhmUqeT3PPBM+OOCDO6K1FnBG+wB/IGLT1PsAErw+or1UhgfOOnv7YYHL18Z9C/4nHYa3eE48VA7S541TY23ctdB69FXbL8G9Rum2TVw1gjsozGZKncnD4bth+4JyAPWx/I125bSSsZpbatnHzWGIDMe2dcblh70mDyeTlb6z9hWoyT4dVT8TTuW/H9BvTQkwPCShI+Sa3R4VdQjr+KmCCirhLcTadPN5mCpOGlzIFTFCNZzIdTPBOXntHMHl3Kb1gZJwUOA2jk8BCBOhD3WgUQElQAR5mQJOhtVI7H8fHJhUBoGuLANO9LBAVkQ4RVx1MHDbTwcSFwbVjyYiREQ0oytQuDFsBF0pj+har3lIAAxECzIFSQIXjM5CFhe5npd+U4XLZc/UOXvos5AakxtgUMLFvbcQV8cSScKdh8/jVX4WTN763+mO+gfCKE3A24rYWKtV9uq7IbKVMV95n8eHX1MniJ8YFYY73wRgQSq4sgQnzb9n8Tkeu2j4alzFIVJngwWCkCBerjloe21+4F43AXHto/F4YlAGnGqb32EODFYmfd/O6ct7F0rX2WXom02b7CRtgYj+jUtzQ4M5IdqqrqMaiUZ3/r1CFRfsIf3sEGmPnP7O5uxAj4JlWhdmMgRAwoSGe9g5Pq9PCpLLO0tMG15N26Cm1T1BrV4me3+ViVMhPntdyo2QGR2kxGh4ZGC3dEBVSfvZrrW1CaRQ40Lbkngldg5mihk4LjPPBA8Sj51yHiXmdCi86PuDFMLswvbloiAcmPo355r2CSa/iekDx3HMlbOk4Hfgvzq7uiwrfO/IEn9p/9fnP/qb2E/LyjqXjl+w6/tfTJs9lW9c5a2xfq+NU8R45Kahf+db+OkpDPumzKOzkaTalzWKfjtt5HJOslsSl8wwqNTKbpGtfhQrbmOJtKuXe5cvCpM478TaTAhyKM5dBRXKQEJ/8HbaAyfupd1BevzgVUBwqXgI3oDwPTJDuVWp0zyNOzy+UR5qWZrxSxnRNCZOUOT2DuuF2Y25gMYMfv8OAoMABJB6YyKEynRw6MUy4J6CKnlDhDSWI1QJFsvd1I5PEtxTfqzAhjrwAQJwR5uuV8Wgvod2EqVW8dBZhElWFSSuVMltFhQEuVL0+O2bPTVVI+jaMUf/xx+H0ze8MApRyfWQ7HgqGh6oUYMM6hgkvBWNFGHAvhKHjWu6BweJ+4xc/t66/eCpLAFAyEIDD3llhladnjtk+HYvSut7TBwgCFZ+qxf9twrTzeCRUex3VewIUqsGo2vI/R1I1RvdiYEI332nbTFBKn55mW8JE64RHx8D10HH0ZlhHW4TSGnkqB4MbJTMoMiJmeJKBKQElAwmyBnjLE9FDIZzx/ngmHoq3Pfn8W95mAlAQkMEzpDBwSOFBLzq8zjVtY2Z8mMdpiwDQ3nNVXt4tAeWmQWJ751kTQOkdfxgGjn+k8LwvKF/Q/jNhT89leYH3FOYfB+b5ouF+6Oyn5oHT2eSgjlHFRUGKKt41uyYK+4S9qqZfVOzL0kP0YqKtcUXbFG2R2SNkx8ogyOHwvPJ7eLxNpSLupJeCSZL9Dl22ayqYYEvo5GPLJDxGJnsEKAkmHeG9pfutIQsPxbwUoJIMlQW8As4DPocK4DAPhUjTiz83TAhIizgUYWIRVRURZ+fGd5kxTJBlzrhuGTYZ7Fw2SyrvL5WAkpRDZSqVPBkiSRmt7k+LESgNz6iqOpigBlCiYXSP0mCi8KWvvmcoXH4vnf0YMCnup/doul77/DhtEe/TNidhEPE2mCzw2kd/NqhQ4iUOrHupDBYeCjPN0g31qIBCQy7VX8CGenrCh3Cg62/XyG15Yt+Ey4/+aEChNMwYh5UqSQMQLxjxznhmvu3p2dKS3teMic7n17kfKi/QQ8uB4o3oVFdZ1deucZsPjO65TAWPB0JXYrwX5D3A8GKs9xdx52mRNJhg0aTngAmewd4j18I+m5/rlJUuyVO5kfF8ZwalChPJzsvzZ5KFQ5ZPSKvedgJE2MdxqwZTnLkcKMAH74R2HboHe1vY8i2xBIvxWb9rUmF3LuwTBLqH7xpQ8FDauuSl7j+j7Ruhf/KRiWn9t+0/reWl0COAjypdnLn5Q7j25M/h1if/ZIN0Jy5/rfj/TungT+HKoz+rICLP8NAlm+yUPEBedFh4+i2lb+I/g0nDFuVKhVvSNHnIzpMyEDgYXkSFXZSqcVJVHs8/NkwcJFQt8o8k/u6JqHa0vyxq/4rNQ2WY4J28nwHFf9to1SMKTI+AAixARQYMcHi11zwt2XaYlAIhCyyTBaIMj8siMAOIS/s55ue0hklDDpNYLZTOYZ/uYYY6E5kUmEQwJqAogCNQGlVe0ykHSQMmVAE6UBpgMU8og0lp+oqUWXNDYxBJIOE73DNpgokyDz/IwjPpV8nO/mmicC6MvsVljM+ZqIjziriHw6KoPsvk74QMJvJ+31M64/2pex+78Hm4+/l/M++DKhtAQwM9YWNtKgICs9Ay4hovhTp3ehBZtZeAgyfDNtUodD09e/vXVgrGUwE4xClp+t0l+2IhSWJgG2I9f1e+pzAmfNey/TaoEoB4NZWND5GoAqM9heovJnmk+y+A4Ve6NMjz73obnyKY0M7C6HiquBwmucfsKuI5pcVif0oDBUwk9uM18P3t/VfDfubnkqFlXAB5rDAsWprRIT9iUBwmpgwkWQHP8yhhUTxfAl7ECyBhnWO8E9tABnk1V96GAmDwUoAQns1i8oKeTf06Bohqq31Hbsije2xeCN5I1+BtQRjP75YNGjUo9122zgz8UZPODz3yRCcufhEu3PudNe4DlKtP/hJuPP3H8PDrfw+Pv/mfOvaHMHTmWTgwfMeqv8gHFHS9DS/akLhusvjXtxlMlL6lqh2KNSaNqveG7arCxPdXVYZHVX6PIi6m0PPBJAIln9hxSpggA0q0ezlMViSYrEwCJiYdM5hEoOxX5us0AZRCCSoEopXsCESkwAYGESgRKiXxwVqSWC2BWiARaHWBnEQEKqNVxQj9/LymhGDbvFcOE0BC5m3I9mtffl2ECxkVY57AqMixKioFfOGhAIo6cSxT3q4S25HIYM2y8TjAhOfZs/H0oqznkcI2V/6d8VsUNiTqCkzW7p5Uif5zG2tCd0tmEiZ+CuNpIHgVis+vlUNE6YdG7fdlnN9bojS2ZK+uO2CT/zHr7P0v/7vBhFL22wv3GFDoVYUBxRBRqqWqhGoS4EODLgCh2ovqMDyX83d/awI2nE+pmOt55tsL28Pbi/YaVBiL4HKguAwohC3fZe/fqbDsNljwPxQau5dtYf4oxY3C38Bihl5pSWnKPA8MrJZU+zB9S788K6aIXy5j6u0lMR22SIPEM+mQvKLtYl+2nzTC+SxXCSZ7+q6GThnLzQfO2sBFjEw0HnHOLTc6ZkgSTEwCTFG1pTRjxivlWcuneqa9I0DRe8TClhd6eB8BRusAhjEvgMOqxAQSO4fz9Y5+DYUma1vRsxmDxCA3gLK2bUKeyHkDCEChjaRP3jRVWX0TD8PwmafSJwZlZkoG3HiF9Jw7JG+VyTyPX/lanskPgsfvw42P/yqY/Fv46Ff/u4HlpDyVIyfoeXZVhaxJvUN/Ebal8Hel/REmSt+Kqw+qUvp4f4XSjdYL+6Trnk/NIEElmJjdlIiTGhVxmZTDYyrNGCbYMtk3qoqXqqCyTOlr+VYBRYWCCJThBlAMKhlM3lHJ8R1Kckgeius9vBUMgonAJJAVgBbgKRAElKaA4KO1bOznXK7hWiIgiinwfX2mqoeJ7pOM7POIkkiRaRMY64HSQkQE0PDzsm2u96q/qopODHqWQySCRCrepyHzBLPvdKPtMAH4XEs9MX31mVKFyR7xVIBM45u5vrVyl35a8Q6uBJAcJCa933ukrcV7pXYd6yxmkr3/xX+3QW2rdgyHtxbsNphwzjuLIlgo0fr/S4bT+Aamlj84cseqs+gpdOnhH+zfGjTCY7Do5YaHzajotxfqmYvkdQORClCs4JT2855WULLv4J07FUexxxQ9xOgMwCSGeAMYSjoAMB6F6VuApE3jAghXdJpBtd8NyzthqhZ+Ycs1XgAwoKQ0m4s4Jp5Q9AwqaSClD9IBS6Yd2dVzJRwYuRu2dJ2zgYvkMwcHhsONjhkQpVUzPORL9mfKDRTLAiZI+c08puQZGRyooq3I2lgUZgYb5fOqR2WA0fsBE8S4BKq8+Ic4HkpH3zVB5L55KDS+j537LJwQKOjU0DV0M47tUdgClLXyTJmpue3gudDee9nmX2PKnBPXvrWp7u9+9t/CtY/+Ipj8KvQK6ozcJx0xlsy9Ld6Pbyvk35vUgInSg8GjWUxFFaXzdY+ZSflM4Vunhq1sqBVQHCK5quCo6rk8E2ybCmYGExWk8DDp1YfXb13wtw8pDQKUYeucsUrLJpgYUDKYGFAwCMAEo5VgUrRhTBUIkm87SBoRIA9CgZvDhPU6NSIinadnU68ZDWxUNLI1ciNRUSyle8bO7pUBxQy/IqBoQ6lRAQzOywHiAhyK6JIEEfOCFD7IIFZR6Z2SGtVLEgYbkGjJt7DOOcyYikeCZ8JgsPXtx+0ZjW+uhE9FDhN36V3Ws440UKSDRlia56r9rfTeEhn2RfIS5H1gcKmKYkqOB1/9qxkBqrWAiLV36TjVYe/ofErxGCir0um7YpMLMviNiQOZnuPWJ/9oMDlyUt6NzsEov6/0i+cRoRGrtdwTATIRKvsMNiatc66fB/ioksPwUNXGM3nXo6ef2juQeTA+AIdz+Sc94hq+DaPJgMLdMnL0UiPTUeLF44kwIe1W0pxEnJdgkvYVIk1yLO2nHYDZDoDJtoMXbOAiedGMRoKJGxk3IoXRUZrMjUx+rhkrnq93dig4THJvo5D2GUA4B3ho2QomC3Rvn37Df/9Kwy1/6aNBnl5aAGXw1NNw/vZvwlXFLf/57524b9VcVC8ukTfE3Gm2lJbKE6QwQvUn0Cd9kCaYC4wqUNrUaIPD+6WwYd+Q3jm+b5QDBvHtzCvIrOcfrlIaBh6K2w9WIuU5FzYs2bGZS2kh2c2qcvvpeqUwMZA8P0wo1FVFtaUDhfB/aZiUgKIE3hQIEut2TgJJQXWPjCygAcccpmGpyKCSn6fnvkqYmHSu3Uvv6hkXw++ehHkpNfLjJkVYaVsqwFERzzAp3PLvqMrfzUHi35OX/A0mWudcSqz9cu1pM6G6y+Yo0rdUv7s+nACIpOMsI0CiLA2QFlJ68P1RCTJ2TnaeC6O7REZXItNSyqfU+PDr/1FUc3HMSsFkNpUEKfHjneAFYLRobKcEytTnp2Vgrjz++3Dns38OZ+/82qYVwUsErO51vL+U8CGcYljF9kCgwXEAAgg6CqhE+Cjta987i/SeSgcb956Qh3HPBtEdv/qtVZm0AQgZbo5zr3gP78DCtERdVh3A1PCbpWUqzQG5PNxjXKIMLindoWoayKHi29Rhb2dcxsi9sENQWa54Jz9iaLxdBANiRiZfT4bFhYHxajGOc32svk4l9hQnVaAU7X3JKPs5ESouHauBCSChizAD3QAKHgr17t7D65C+CY/k5LWvw9j5Z6Fr8HpYv4ueYILJxt7A3zAXcH/ZD6apoaoNw0ZDP14rHTEocFBQAST0HsT4US3nbTrF+7scMOldbSoo3dttjheAq/LjM5fiXeFbp9x+ul49TJpBgqaFSfJOWLdpiBTeLvdQIkyUcUswUWashQmGA6OkTGAlWCXeHCrmHrtSYFhA2TkRJEwsiaB8AygxUiJMFJFJc4t1RSyRK9l5ul8dTBpGNxOZOKkwpi4ys90rXmf30vuSWa2UqITv1VFVSLj8ny4m225cgyI4qlIiSYaB7/D3Lt4lV/Yd7pGgaBwVjooXhwvn0kjWM/nIenMxrYTPUeTXmarhYPfWPXSs8EKSPO5RkR6yNFGS3sHOIf0UIj3FxnfgQMal2urUze/Cw6/+h7WDMI4EeFipkEIHaSRdw348Fhp5aRMppuh4/Kdw+9N/sp5clNDnrDqs+wMTpbGlhAdhpXQn8V0RJNHriPd2oJRhQrXYWwvabZ2GR6bxZ+LAySvfWMcGxu4weps6ZMLbrzEPx4BywNIFDb5MPAjkLA5rwtviQcc47mnPxHqulCaLY1rybsx20CXY7eyVx6RnkQ/Jc1Rd5Q3xZmySAarzSpAbpLzNhM4rVu2jPEfcYGQLmFC1ZUY4Gt8GSLTNvqocJno+MHGg8OtXXwcom/eeDLsOMdbklryU2waSnQfPhDU7hsKyzX3yRKgeA0i63xo6I8S5yuhJRjpiypfRC5/ZeCPGK9GjjA4bVNUYTBJQqnLAOGTc9rjdma1nlaHwolJaUPjWyW1mrr8VTOJYkxwoZZhUq7pymLhee0clwrelHCbTAYWSa1FvnoHF21BK0n7OocEKiDCxJHp/hTKeQaXhoeQwITLnKlJ922XnmaHVdo3ImJZ5m0QGVmRqme8vMrJL7+ylQAMKUuTlgKgT59kyrbvc+3AZRPQMh4gbFjMy9m75+zX2mfEh7GWsUCx9J5ik/dwDI8PfFukmyczBDOriPfy6qVR4F3XS8Tw9tFKehhppKRpv5r4ymBwWTG58Zw3wNKKS4a3Rm/ilfjq1P3A+AAIm/Mud0g+N7zS2U5Vx85O/WrXGxo6TCguuUzglgMxeSaeDQ2k7wsTglKCGoseUYKKwRKy/OX9PeGPebruOrpAMjjty4mPrco23R/gy0wAdLgg3b5vhWuKEdARE6KBB2snjryqPX0u3pAlPh7mUXjzN+Da9bDaroABMdvddC6t3TcQ8yLl6Zg4Tts0wtTBC+TgTM2IyeMDEutgnoDRgItXAZCZaqGcBDq/qWriW9bhNOwqeCt2G1wqMVGttUrpA63aNhpWUjjfTi66vWBpYBBH+RUNhg6pOPBG8V7qWU2gxQyevhONUcxVAqcqBkjRfatgfhUcBlWaVYTGdYhzVKYeI628GEzQdTLQs2kysIZ4G+cZ2S5hEI1A2FBgUjE2sR09VIhhDMosygyfmQgYS6t8BCUZJ91QmdjlUbBr8GqDUyc7JYYJx9nWpMNJNUkQWauy3TCwV99B758Y/B0NVOUiqyu/h8nez9yPcTDIqhfRuiOPFOQprwhwR/oqTWLePccTYRqCwD+OEgWMQF3NzYfwoWWPQ7FrOzZZV0XsPryOP81yldCHlaSXX2zLQyLeZrgfjTVUWJVuAwA+WHnz5r9Z4TrWXD3ZjSSmThEvm91KxdUFV4qbKghHuN57+g3kmlEDpdPDuEgZFEofKbGh1r21/IJhYd3fzTOjZtdfeJW7rWxwmuv49AendxfsNJr8UTAAE8Wb/iem/bhMREq5M1wFQmG2ANPOWYPLWwna7D3FBGrM4xxjouMWj4qaIx0Ixzj3ePW2Qvj09ch+W7qV6ugdW/OOfqdv3HLke1rYfFwRiTQAGqA4mdQYI+fFGviUNUsDhWypAUR40iAAUSvHaZv9MRC/G6I3IsK2W0dZ7uhwueCpLZPToer1CBmyVDBVaYTChSgzPpCEGkwITjB3VpaQtZkKggwZtVl6K9rRVCxJUA5N5+kaAYkr2pwqSOpXhURXHUzhnygGS628KE1QApd4zYb2AiryUfHtKmKCm3l3KBHk1iIFFmce8FeCRS4kf2MTSLdfzDG+jUUnOgOJQkYGreCl1smOKEC+teWbLZcZ6hqpm3kLp3tEolEHhagWT6jtF+MVnGczMgMSSaZMq+zE6XqVlymGyBIOYAKEl59MpoHPotk0pMX7pK5XOLts7+XXFPfJ7ZiK+69JBKzk4SpJRfWtxh62/I0Xoaf+iPWZUmOoEmFDNxU+rqOemCotGVFt2ngo7Dp6zdSaCZCZaHwDHNOhHT31sAx7xTGhz4XfFby/s0PcTj8pYa/pMeCdezYXn895SGfwlVGFFoFj7icLwXSnChGoyQVIQwTMBKhwHxngih8cfGkzO3f2deX17j9xQJhs0IAGTd/TNFmfAS/FmcUj+ABwG60Y4l85JsoKES+mE9GLph3ST0oynbarS6Aa+f+hOaB+4EdbLO6OKyg2TGxyMkbVnkiYzY2TH05LzuS7WIFBA1HtRwFOYsSyAoryHh1Gt6qpWZ3mVVy72e5sJP0+z3zmnXzxHmMSqL/dUAApjdIAKPbgYx8MSeJhU0GC6G3p40Y0cw0Z1Fr8ZoIfg4fH75qV4yRlj6IMqGQ/TpIrXskCap+8rYCI1CrWKl0zNdgobVScdI36a1AwR198cJsiA0gyTXA6RAiYKf8GETF9uM6nKS6LuqRhIMHLKAAVUPCHmUgbgvAiiBBLA5aqBSgSKSkQJKi4iw9djT5Nk6CUDS9V4K8O1UgERVAcSF/eVeEYVGK1UfR9/XqFkFBwabmjcuJS2kwoQZIpGUGGmpZ2jMOZ+dApg6nn+Z4KY8I4Sshn0mvvk4pwSTBIMplIVIFW9LXk1F725MEp04zWYfP0/7De6AIGeUtR3UzWBGF/CEoMAWBD76J1DNQYj3q9/9Ber8qJB/A0ZftpKZq9UHAgk89ceseVceSh8Pz3D3l+mNLd4j2CxR2FHlVcEnYEkwYTqMsIieie7wpsLuG+nDNKI3u+aVXOdv/v7cOrmDzaFOlVspCFA8g6eieLC4sa8nRjm9gzJw9nkQHEloLh829KP0oynC0s/2k9aW7ljzKZTASYb950yI2MlXaU7h4pBQu9nXfnTvpLS+RT8yMexSpP3I13RBTpOg2ODLZX3DAwyqA6TKRuyXamaK+8aHH9V4DCJ1V8OE44bTGTQfLmcsQ4ybKz7/sUykA4TDBq9Ailw4JXQNRsvhdI0xs89W2RQyeWAEVBMWl8omXeSA0XfUpXDpRkorVQTB1PoVcNkpkBpwERAT2FIOJsXmDxB81RcCn/BBGOAkc+MyDQq6tElg0oCSpN0DJDE6zA+eEHtTXKwNKq+8FKip1J4KwYXls0wyVWCQY0KiEh1x1up7ll1ql4XYRJLmiWvxIXhSAbFSq25wcmEYcqFsXL5ORgcSqxUyVDFZT/IOnLdDE/1+jpRQvd0UEAigWI6GTwW7c3U2KbAgvHGM8Eo4YHQiP7o638LVx79vY0hARSAg2OMkMd7oWsuAiQc44dL/G6X+nDGmAAUuu4Ck1/M2SVIAFTiis4RVJMxMd2wSk38E4MqL95BHseCXQY264Wl743hC0SUZun9pTihER6Y4KGwTgGBqWr4eRMTafqvkQlr2qmIRwOIwo4l3o3JIKPv51gKZ5POK+LNgeLpIO33AgLxau+oazy9ADDmSdrVe9WquTbtP2NGJtYIKI0ZQCJIrAra5VABIhLbFPzIr55XHf50VKA33UvBJIEEj9RhEqu0ymrAxNtPYnVX7PVFtZcM2iZgIiPGJINa0hOMUfVu5PBA8GCZz+3A8C1LO1ZtigQNh0lVDpRcwATvpAkoFTW8FSCRQ6OV/uNggiJMqpoaJjF8y0DO97tec4PxPDCJnoYStxJ1AZQacZzz4zPwgGRcFre31NuoCSwOlwQWJWrcxSYjXmPI62TtFspARZvLFDLo6Ny6Y61k9+a6JADi9eKmZBxKwoAkkJQMTiYHhys3Vm58uA/Vbvyul55HzFeEl0L4VK+vEyXrkreRVPU26vSmoPHmwiTWi23F7SJJxvvN+bv0/Z3WhZMBiDTAMx4AODDvFqUdMjKlHLoC0zuHAVHeW8QSsM5h0CP/ImesCTBZ3TYWfjEXmFCaJr4oYQ6q5D4RNu0TkLrO6Tqm4qcKa3f45dwd8mQEFL1X9O4w3BEktL3QBvJL3Y92E2uMnx/bTwA1veMYx0PXa6b5Z8oaJtfE+yH8aIxHAAj5NteXwjuPX+WRXN6OwzmkC+sYQBrQ/phWoofClD9bu86HXX1Xw+bOMyop9xowrC0zAaUEEhf7JYdNCSZ6jsPfYIJ3ovxnMEkFOfMyZEhbwiQBJAfJVDBhXy68FYeLq4BHBSxLZPTM+MvwAxQGJzLzNLMQABPzSmT8zOCl9enEX1cZZ5TDZCqgNDwUQKF8P6U4px4cdXrlMDHF7uA+wLUOJkCGdjkLEyCSg6RQBmkdL2DyPHLweLVXKzlIosGJIHlTpdMmLdwd3khi+63Fe2rBYtVg1OFaoo7eQl6lVBL761R3bkVVIDyv3ANxlau1YsnSjUJUAyQlg1ORlXIdItLbaZnDZJ4y5+7eKwYTGoqBCaD10nGre9n9tA9VQWHS8VwFMApwtCv+ohwqtr0gGuNfztspA92mb9xroKDdgzYPugjzP3GMQWwY36cwpBpHcUFJGEOkTIi8lxew4edL/D6WKjKqmn45F0js0XftV/xh1Ppl5E+GjqO3Qs/kQ3k3Z2RQevXte8Lrs7fLO4mAiMZcHoDi7cPUvRgw/WIu7xs9E5a/mLPTwg0vhOnN8Ur4b8zwuc907wt6/37Fx167jvYTE0BJ6xzz8HVoTycDDulCsrZLtpVWrBpKhRDaSJjksa3ncthy4JwZCwODjgEHh0QuB42raCeRqLYmb9u7SnSdZuwMswIg0rWP4GecTSxoSSlvNWZxIG+yLx2X7JjSobeRNKsBleIcGc0Fug4ILZKxdFG95dVc9BADYEANqNCriIIJBY7iF80ydHl1lq27EZR8O9+3SOsLqOoCKBsaQKlTDpYIFX1zqT1FdsCq6PEKo2c4E5Whwr2ngYmgOyMp3BpwiUDJ5TBZaOHVCJsmccyPa/maJR4lmhdRXQbIxTnREFHdkUACMCp6Y6FKgQsailDZrWsASzNUMMzuMZjhTypBQZFRq/ycFuJepXYVA4SrDIpWAhxVOUQMJAkABhGkeGgy9lXJ+HlJ1zO8GUQZmgImyoT8ZQ5jZzA5KpjomwwY1XvVqAqNVnKA5BD5JeCobku/EEhen7NDhnaHnrHHuvjSQMrvXBlgRlsJkHhjPoZ4t51DNRRTrDASnl5gjDfBs2GkPCVg6sbpFkxvrh3dF3TePhl8qqT2KqwVB4orDO3B8Qc2D1jfsfth6/5jMkwH4330DYQzMJ8rQ7Z022hYtHVEmfiw3nWnAcW8kwSSn83abvuIW3pxMb0/VYlAm1/M0oWY+/181g5rZ3HPBJC8aUvyQAo/hf9U4I55q1Jg0zKvFUAAYM2eY/br3q0Hz5sRABgRNgkggkCpWjpBxeUgMZhom2eQX0ljMXz0HF1H2iIdkb58MG+RP8gvChfyV17As3yZjsf2RF2v/d5WUm6Ar3opHONcXavrmXSTqfzZb78FEDxYMu8ZVZjAhPYODJvX4bPEWzE40A4iMCAHSgGTzCjmMLGqro3AhFJ/PUhcZZg0BEy8rbcAir7HvcOGl4hmDpQ6mDyPcqDkangriDCTZ6hwcBVhJeX7CPvXSDzuQdTVhb+MLHO40amBiXsjbxhElIFlTNB0QGEqC4Bihj2JROsweFnlmcS2iWhtO0gKT6NOGTTc45hKdSBBZWOf4IFBUlhaSdehQqZX3HEfnkdmZlzESILJ/sFblrmLe+T3q1EOjIbY74r7St6IjCXgyGFSbEsOE2ABKMjoNKQz8NBGsA/dkrGhiy0wkIh70oDOx/Czzv5fzJFHoW08F3ru4N0Mn31mU7HT444SP2HjgKXLMLPqMojtxLWvwuGxWwLBhOJUxlNhRTgTv/xYqWPwdthy8KKMx0AJJC4ggQhvfgyE93eEOaQufmlT/fP/ceL/57N3FNVjDhQ8M8KqHI4KvxSGVRVASXnTO7/Yut7b9wOKVfpGPJPtinNmegUInFOCidIi+1oBxcUx7mugUxgSPqRNgEu6pnMH07gQrgzIZBwNsz7YWBrlizwPGlTSOjKYsJQaMGE7wiS2l8Q2E+QgMYgk5b8DiGDRPolGeAdFnaLBi4av2M5hovV8+8eGiQFEYVWteqyDyVRAMagorOpgMVNVPZUGVJDgnoWtwTqFpYend1iIMEmeSV4yehVqVH94hmlUaZVgUgHJ6/PaWgIFART7zXBK4GRgErIn5lelZs8kAwnAUMYrt3m4olFHVgeu8K0qh4bLPIeKCsOfoIFhotRbKvlKXO/35l0ZoT187nPrHsxPgsjMfo/8flWVSs+ZinjU0oHCehUktTBhfR7VRm16V3kaikPqrpn9l8b3K4/+aF05aRNhQKF5JRIeCUuuASCA5eezt4U3lD6ox6fUeXjivr7zWTgkL4dZdJn/6i2eqfNpo1mqc3b2XBJ0noTTN74JI2fpNXbRqj04d74yI3OXHZKXMaGw6hy5Z9OS0DPMwpllEt4JMGFJWrBuuUdv2WSa/KCJqi5K696l2OJG3x49E+5HHvD8kCsCJBf5xwp3GVBcvh8BiVU7x+0/8ABl6dYhgwLgaeWZuKwqDHFOUnE8S7sUeGjrAwZrd00KoldtHBPpCg+Y6XoADMdzz99h4t6J7UuKEGmAJfdMmmAiaFgXYHkeDhSHS4SKYJKMHWNFvN3GpHU8FhvlnoxhCSZKB7SlFBBJ22ix1vOqrjqA5JoKJrmiZyJIGDwiRKaDCcqBYlDJgPIiKgMlqQ4mhF8KWw/DXEW46vhrhatdMSDTqYBFKymjuGF5Qxk7KvNGTIAkKcHkF/MdJmWgxLaU2PPL/gypRG4eAEBJcqjUyoAwlWquyeQQcZAYOMi0SZb5qgIcycjH9dbgQHUGHjk0cuPmYj/XOpR4z62dZ83AARN6H5GRC29GcWP3xGjVqRqPSOdHQ1cHkwZIcphYW4ldo3WVzN+Qd2I9qBR/ZOT2viv2PwrGi1ANtanjhEEC2Fi1Fl6olgAFz+SXgggwod3FBj8q4/IvcroJ878TuhvTIMykiw4fehPxx7+DI7fkpX0WJi89Cz3jd/Ss42Y41u85FsfkXP02HL/+Xdin9aVbhkqw9nCueieU0rcdYDT+RzbVSqc8G7rqEt9+rSvCKYbFTGR5LANKVV5gw9vg/+/06OJf8Mt3jBoMgI4BIwdEkkFGKrYTSHJZu56OeYENIPC9jLXpmXhkHi9iIlHAslXhQNdpYBoBImhg8DCCylvAyIAizUU6nnsoDpRGuwn7GuAAJg4U/ifDOlVcBheAAjQU9yxLPckkG7HvYNE5tTDRsgoUYLLwBWBSVRUq1TYTg0nSVDBBJZi4akAxE/n0Ok1QyWGibX6T4QM6459iE1iQgSSGp8GkYTTKsKiK4yWZgSnrjULJoEgNQ7NbyuDRpIZ3AljyYxEoyuDS20xlvqTRpRMPIEIleSpVKXMYEAwYrZSAUXe95BnL5fAwOEylZODzbYNGoQYwooFvgCOXG7RolJPSPgwf1zqQeD8yPaO1+X1v10gFJv4cjFaN6oxbQ4AEkQamg4nOJ13ZOu9L7ym642KIe1WSP2uTPfK3PKYOp+sv3VA5DkgAC+0kBUwEkdcTTBgnwkC6bboHvbmGzj4LHUevy5gPK0N2KY3omXree8v2yTgMhB3dZ8OREw/CxMVnYeTcU4UJ3UbPWVUbI/D5udbw+c/C9u7zlnmsWkrfYmGeGuDR67Pbws+Sd0K6Wy1DjjGlZxf/HgfiGF4L4yzuLN64n4XhDEQYA5MW8vAHGivbxsLu/ms21mTVzgkDDMDJAZLLgKE0XdquyGaEXk4BinyBV0EJvz9slBfSM/E4HL/2XTh98zfh3N3fK/y+Cd2jDwRWBgiOyHADFBnS1TJaSnfcg8k2uc9src+R5q4EJgADcMQGd9ajHCScI49IAhwAhIGKDGLkZ2Qs/S+WxaSSknVdTuu5vEtzLUx0r1jNlaq6tN9govOmquaip1e5cV4wc5Wg4kCph8RMZQMcM6AUYKmAYqaqqyIrAUXr8Q+0ESQGbFt3uACTWM1FuL4WM38CwiKVelrozYUApKw3avRLZaCospFpBRMHSAGSmnMMJslDoSEfoGCYvcTv7QW5wXcBgwiTKaTjVWjkXkeuAiJNYHgBVY16Mj51wiBRXeSGrQEV2hkaoCA86KpK91U8E4wdBs6MW/6sFqo1boWeAyZSLIgoXbHfqp5iNRcZm2naaTzHkJ+88auwt/+qwcQb3OmWap4JHi3pQhD5Be0uycNhUN2a3ePhgIAwfP7T0COobOk6E5ZsGQh0ISfN/ELeDEBZvu2oPKELYej0IwGMnyl9b+0o5+7+Otx8+g/yjv5k/5FfvXNE992nZ+0sIPL6HCDWZuv01KJNhMZ4wpPSOr+GBSbec4593nbzUjCxsKuXQxpo4I0Ak47BWzalCjBxr8XbSWw9eStV5RAp9lleIE+oxCwZCFYeltc2HLZ3XQwHBY8jJ56Gc3d+Hy49oBPFD+Hw+CPB9HxYtpXfJffqfBlAXQdIGMNjnSIkA4oKcHgmuTeSeynulcxVwSD/Fz9T0PNfE36NzE+yliuu/cdjubwrci4fI2NGUIaPRmP3RvJGZd83kzYTQMKxVudUYeJAyUFQgCLb10rPc+5UqgVLBhSHinW00Hd4mJk3UlqP3onrNTMASvSAIMKE3hz7lVgBSFUNkBQwWZBrrwwKag2TMjhaw8OUrecN9gDFS+J56T+CpeGxOGByL6NOsdoKUKTqKt2n8Caqcogk4/0yKhnyZHjqZMYI49YCJlYtgxHSknejbpuJCfFMukfvWwmx9Kwp1GTYSpo5TDg/Gj8Mn75DcYnwNOi5ZT26Ju7bdPJM+oiXQAkTz8SBwjrn024CUAAJVVixuqzDwNE+cDUMCwwjFz/X+jUZ1EnL5KSTn8zaGn4+d4dK2vvCqh1HQ/fIDWs7ASDXP+L/4X8NV5/8UaVreSVdp5Qh6PWm70jdgunVBTwAiod/9E622zYFEX4+Nkz71NVvbUZhBkiSfrzHXBGvLFO4TCf3Sqw6y8KwrAImSov8FItxJvuH79jve4FBDpMIkuaeYK4qUBAgyWHCBJoRCN0qhQ7qm0/Is7wURs9/FS4/Iiz/SQWX71RweSCv+KyM8ZBAcri47p3FyotafrD0QJil/DhbeQ7vxOER20/ikv1zFa5z9B78h9//xY+HgmeyThDh3/p7ei7ZP/j5twkAoVNGMctxjXw6mGp1l5eqc+PobQEAwqTzc0gU+yXGojwPTOYIiiXjru+fajqVkmZ63gz0QjCZRq/9ghIvBksQMGDghZgn0gyPOoBEeFSk+0WpdGj3z0BCA3tqZI9AKYMEOTRc5QZ71mPVDsbPqoqUwZABhowko1+ARRnGvY1WMo8DgDiYEjDqVLQ5yDi8SsXSewRHHUjMmCWQOEzedOk8u4eWvBs9bajLxzM5NP5AJbPDKbwa727GDWVGbEbCkCW1gokfj8aPdMW36J0V3wCFaixKfz5WhPm54rQoQ+adABA8GMT624p3b4h/S9cDE6qyyORbqeo6+SQcu/5tOHzsYdjWzV8Hj6rUvjf8bO728JPZW5TOtqtU2hn29p23f2Q8+OJfwqOv/jXc++yfw/k7lKpvG2xmr6CQQNgqXVqnAaVRAcXD2wADTD6km/BOS2f07AIihPWAvEEa9ElTpEPSSozDBkxy2LaSwUT39iqtqjiHe3AeI5VpgOe/JgxgpIsv1xosAIjkjfe+XcAkrbtH4l5J1TNhZoB3BYS3F1JQEwhW94ZlW0ZC1/D9cPb278PNT/5FcfjbMHDyWWjvvxnW7zkZFqzj/zKHDCZca7M6Sx8aUGTY5bXkEHGo0KYCSGbpvWbJ+wQmc1YciDCR4ccrOTRyJ/SO3zeorN7Bv2XkORUgiVCpyucXi+0oVNs1qm1sPZf2NQOkAhEBJFczTBwkzTAxA45BT6oz9q9a+fMK5TCpAKUJJg7bXPpmU1p/7XUyjRI73oQBogqOGlXh0QQV3Q+IoHj/JLqICiSuOqDQKG8AkREpqwyTwhCTqVzaxlhi9AGCAWWG4nwHUwGNOrkxxkD8CPK2kBwiVZAgIPKWxNLAQvzpOt6Nf2nwDw5Ky/zbhFHxESYRvgYuU7Mhq1MrA2j7M5DkMDGI+FLxRTUXVVU0pAMJMi1zJ1HdxEh2fuPLVCpk9AIimby7MFCxLsQS/8NZuXM0dAzeCMcFk8Fzse1k1a4xGdXO8MaiXeEnc7aEv/twowz/rrDjwIlw7NLn4aFg8uTrfwu3P/mHcOLqV6Gj/6IMlUrgSwWqBW0Kf8CXwp2wJT60tGquWTvCTz/YZlBhP1WIu3uu2GwDjDlhlmbaCUhDxAVQsjhMYVOE0RSaDiZ+H8KXjL/j0MVwYPSelpesXj2CQ96I0rWPVzFl64W3ghwugEWKU8pEmOBdABCg8LYKmG8pr9tMAzpGldfYha/D5Yd/Ccevfh8GT38msD4Kuw5flec5Lk+zz66PMNE9C88ktpvQRmK9t9bJQ1jXn3pxychRLV0DE6q5tnScCEeOPQqjZ5+Fw2P3wuaO45Zm8DrcAwEchXRtvrRqr9R+Yg3zLUSbh7d7GEyQDGYVKI3t3BOpqgYmuWTY6wDwKlV9pu1bU96Xt6FUYVInh4ita1mCSQQDmT/BJAdEC3GOQabYx31iYkfc+3VlJp7zusGkLAcN1WDWUEspdpEyVEU2ToVjgIQMVxWGUc+rAoXlTBSNbLwHy9pnSI1zosybwFi8CnGvyv0wZnFEdh1M9A7pvBwmdNXsPfbY5pBiug8bna0w4X35Tu7JuXWGrE6xGrRmP9I9Pa6RnUdYGkTSuewnnm3gYpvCcbdletpN6InFWBPEnErMr0TDO117UTNMomxdBY/Zq3WfjmNh5MKnYUyg6D3+MGzvPqsSe4+MY3v46ezN4f/97ho9f1vY2D4Whs98FO48+2u4++k/2W9hJ3Td3t4LYemmw+HDZREmbwkkb87XexNGhClhp6UNXpRX8nfvbQ0/1ZJ1wptBjICE8KbdhE4fnlYsbnRthHcWRpKFX42sekswYfkmUvrMxTl+H3oBMWCxa/S+/SQLQ+BehwEpyYcAlOCSiWuKdYHGYQJYmJo/Ts+vc6gGByrK86t3Tsqre6xCy/fh6OlPw5GTn8jDfBq6xx5adRdtLMxGwKwEDCp9X8+migtgMHKdCRtXbGGK+RH7de/KrcNh2aYBQUXGDuOfqrm8qmvxhuiZ9E8+tD8xDirt7Ow+b9VS/BmRafOpQnXZ/5JskHPcBib2b/sMKIj1KBn7tLRjAkFVBhWEEQUivi3VnY+ASWPKFYx4vbGv7qvKjH7N/umUA2M65R7KdDDJlcEEL4KEHkFgxgMpE6EGINojHJi6wjJI4xwDkCV2NyRxv3kt8/fKK8mhkkv7ZBxZNu4Z78t9KImxjPeK70VGLAw82xJLk/Y5TJAd574YUJe23VC44n6X9uk6f16UztH+X+g8DLu9s0qqVq+exLYZfsK0EN/VLO7FPe1b+D4Mjfb7dV5NaOKZ7Ne9Kem+qX1WvaVtE+/Lu6Xj1NsDkZM3fpCxfhqWKMMyIwHPorRb3JtvavrOZhWgyPfrXqZ0rHGOpP3WocOWxI/22XdQZRRL/u8v7bAeNHTvpUfVubu/kTf1OKzZNS4DwPxYgDECBTH9icPkbWBCF/I5WwWePYIn41au6lsfmbqGb4SNHRMyCp2Kn03h//X2qvCT99eHDbtHzTP5+Ff/Hu4KKBfv/jqMn38WDg5dDxv3jIZ5q2UouS8DD+fofZXO3wDYAgvrP5+9U15JhMnPZtFVWd+isMATpMMDMCnaqLTf48XgncKlTr9UQSnXG4sVdgkkb5A2Kvol13Ct1mnj2HzgrFVz0XZCLxxgkIMkh8lMZMDhfApjgEBiHRGvMf3sCYs2HbUfc/UrjXWPPwydQ3fDwbEHoefYk9A5HP9Nv2L7mI2jIJx+MUdeqcKBrr+rtg3LyzgZ9hy+FDqP3gidAzdCh96/retcWL+L/70fiY3rQCV5KDTE0wC/t+9KGDnzSRg992noGrplvfgw2niq7wseiI4XiHWgEvfF/b7P/vSK10JVGJ6NQMKymBFY2xxjGcGTwUSeNTJg4MlwjYGoXtxjjsHq5RvQq8phUNpfOdZKgMOWab2AiTwPaxOqiO/P1+N2X4IJxsoNlyK7MAx5gk/7OO9nShQszRAqwZMAqW+llOQfF//e1qfI6dP+XiX6Q4rIgxIjdBlYhVTakd6hkQ6xnvbZftcSZQ6VirxjQNE+IgGOkpTB8m0DRcrUJn1DAZ5MHCvWpdyImnTcqu1ksH9OdYdEOPwcpe0mUOrcInxTGLu4pxtlwhFjY8fsfEEhe6492+4BLGJJ12HyBtI68vp95o/CM6GX0eCZZ2GZMi4lTp5nMPFn8R7p/sXzZig3jvXHGt8VYYLcsMaGdLwNvJPtXWfsZ0Znb//aJm/kv+s0bHtBIRYaiDeHia5F8+XlzNok72ybQWBj+6iM0uXQO3HbRrrvPnxa3sah8O6i7eHnH64Pr+vcbftPhDM3vg3Pfvhf4eZHfwpnb/0qTFz8VCXcRzJkF8Ia2k1kaN6YozAFJhJTtPxirsJLy5/PAiY7BKbt4XWB5XWdxzfx10PCm2pFlgzg87THdxMnlgazMCnyVQERGekkYPIGINEyh0xVwORd5btN+0+HzpH4kyz+RYGXYd5NkgMiB8a0Ahy6v1WtcZ+0JG4tjSrtMBaB9pq+kx+HrrH79i964MIg0P5TTw1wTEDJ9By0IVGI+EBeJ916qa7a13/V2j4GT30cjsrLGFBhokfb7N+6/1RYvWPEugTjoXwoCAAWGuFpeKeqC++EWRA2dBw3w0YvPp91nF9a5LOQs2SbQc/V+f78H0qIewASenLROG9diw0kUr6etkvQwOOZQjZX2YvARJ5cq15cTcAoHcv2TyGr3moSoBQoAEZVAKSyzngcwQRvAUOFccHIYBCUWDEISJkCNTwTwUQlMowkpRQSKYmXl1q0+WhYvn3EBlKt3j0ZVu06FpbvmJAxG1fpeETHh6TBsHATOqoIk9KSaSwWbBjQi2mpdZbz1vWLkHJhgdIaJarVPSpJHJKxUcACrnyMiPVCib2zrGcW76VM4VVYBh8l6NgrKx4rZCWwVC1mGSeWqs04WpgQPhEOBo4MIuzzzOXGNJ6fPC6HjJ1HGGPAG+f6M3xp11aP+znaTwk/h8kvE0C8wZjlYhkUGt5PXv/eJiIkTjAQ3LcKk+J5qPrMl1DDQ2nAxEan453Mo0SPd7IvbGg/FnomHtgcXSMqaW6RYaRknxcI3rZ7lGHyzkJ97+yt4Zezt4R3F+4Mi9YdDFv2TcoQXVRp9VrY23tecBgIc1cpXhe2hfcW7wntPRfD+ds/hI++/TfzSiYvfh5Gzz4NY+eeCkJ3wq7u0/Z3v/cwnPOU5gWQ12cxWFFxODsuf/YhDfB4RXo+0FFcMFgPj4TuwfSio3rAvWJkHqPCdzqYRIDkmgFMlNY37DtlngDdg5dsGZKBPBCNP9J9iPvngonyQQEQk/KDZB603tnSi+KSqTiAx5DSGJ7Jhr0nZdiZXPNmGDz7qTyWj8Oe/muW/sinjB1iRPv63RPWeN49fDv0Ke6PCCKAZFiFCtpChk9/HA6PCo6Krw27x+WhKK/L6M8WFBjxzi98D43cDsevfBWOSTsOnQ+LU5dwm25JS2YbZz2HBoApwyQqwkS2Q0uuw9tYIW+HiSIZc0I1DuCwdpmqrNqsvjtyVS1hIlhMpaJLcA1QXgVMkHsn5X0RKOWOBVEFTDYkLyWHSQQKRobEEvVL5G0haR/n/XTWjoZ3ogRG4uPlF28ZNJCs2X3M+ryv2XM8rNp5LAm4TIbViOM6tk6Jjz/Ebdx32ro1btx/xlz2LXJ1Nx84Z/9osP06zqR9dj5qPxHWc73uw5KusAwgW9U2Zu0Fy5ShKC3S598GTtE7JfXa8sGNpd5c6RgCLng+lmn0re51IL4ZkLrYl4PEjGfKeGYogAMgkQw8WjZ5fzI2nIvxnQomZpwljPLbGCmd620m3o5Cl1YaqJnps3v0ns1qyxxdZGaMA89vBZNWqr7H86p4b71vUdUFTFRKxTvhD238ywSvZEClzE1KD8wyax5mIfdOVIAxoDBRo9Ke7vPGnO0Khx3hg6XtYdlm6tTHQ9vB02GntLZtKCwUZGYt6zBjRDXK2Zvfhzuf/DWMnFHJ+eh17bscDg7flPG6FfYP0N30mPUoel+e8Jvz2iNAEkwiUKKixxJhQhpjBDwTPwIT4OIwAYZ1bVQW51IDDi8GEzzOdfLm+ONi5/AdG3dCjy4HAfENIJ4HJmWQpKprfYena4tPbWNwdvUq7gQTOnrwx0vm62Jw4+GJR9a7rUveCbM6x3zYaY3obV1nFea3zQPZceCMtYOw7By4Ho6eeBJOCBBo+MzH4cDg9bB+15gKC/ICVnbKC+0KSzb2hi7tP375CxWYvokDVncySedBQaIjwSR6Iyj3RFiyzTrnICCC/DoM48Z9J8Keviv2GwTaAwBG3pCPV20N/t4leQZAqYOJg+J5lF//qmBi8uvSdj1MDk8BE7nwrl8o8+QwiUABJHsb+2j7UCaKhlEGImUK6m5xj2y2SZWMmXTOvY7F8kiWbBkOS7cNW2KPwJkM6wQcg4mAsUnuMCDZKpDQoLgtyda7L4Ttki+ZJZZeM6ZDccncSIgpLrYCJN1vk0psmwUk/kGxGSjpWUzIx0+OmKyOum5G7fLrVeCD+O0tJUsClrpevouSHpnWMlrKXP7dMXMpnJLxbBjRuA+DnMOkMNAKu9L5xb3SPo5zbpJBK0GDKi3zTJLcO3kDWMjo0svi4Mhdg8mYDNzKtnEzJjybbyieCciS2PZ3dVU9rhdRDhNr6xFECgkKVBfQEM9cXZ2DN1UoGFOG7RJA8CijV1l4Juk6gMl4kHf0re+wvnC3jP8elWC7BJT+sKZtWKVfxe0W6t3pZrpPhuhg2HP4Shg//3k4ff07geO6GbG1et4WGY723gthb5/ST+epsEiFkNnLD+m++xWuCheB4w3lDWQQKbb5pnbzivkJ2fC5z2OHBwYukk703bx/9MwaIHmVMHlb6ZKZg5kKhqomJn6kutkLNdN6JioIlgVA0rXcn+ul+N5AJS7ZRx7ZrjzHhJf8dZKCHN3QyU/8LpoJMJl+hTzKFPRzFAertw8bNPqPPZQneN5+xYvH4VVftIFMXPgsnLr2jfR1GJXXuH/giuJqQufS44v5ug6GXYfOhqHTAo/OYbzSOqUhGriBSfQwGjBpeCEZTLTkHGs7yWDC9mKlG7wdBrIyOzXVXQ4Sa8iX7P8uAgggcbCYpzKN+BdTHSCYSsWnVamqeq7DYiYqAUXrpWO+X8r3+zFgQm+0vJuztRFNCRMAgVdSA5M6xSqvZIzIEGQaJUxcbv/fgvVZVyZ7nyooBRQviCtl8+Qr4SxmeuhtQ2GZEhdazk+Q2gDNmE1et2rXuLyYCXkxE/Jyjimx4MkIPiqFAYktnacNGgiAMLnhdoEHARUHDN02+XUtYqZXJqfj2Da8HzwfPB28G+CGx2Te04QBbwWeDhIAl6l0v3TrsFXlAUsaOglwIpeSIN9bNHySIZMcPAaEZJgjNKLM6DpYtHSD7obcJGDYtmQgwTAnkHhbSWwviZ4JDYKdypQ0CI9f+loGOk6z4fEUn+/vEY29P7cEEpTe2eVxXrz7NCpgovOtQV3v56LKi6ouxpz4PyiooqOa0qq3MGYYNT0PENEjDKgATPv1rgxq1J7w3mIZdRmSOav42+Qh3bNPXskhbSvz03irjLSt83zoVkn58NiDsEnpiB8s8c8M/im+fve4Ch3Hw0altcUbqB7rsYF2dIUFHCzfTOu/nMv7yLAqL+B9UL3KD8mYwgYDyky6hWfCN+hbrEcY35FkYSg14PD8MOEa0hgA2Xv0ZuieeGg1AqRJ7s1zAAQgqYVJAoj9XyWpgImuZen7/L1trJK+japi5uDa0nnWQAJEV6twxrxbC/X9TOlzaPR+6FN4kPcWqKA5T++1cc9kOHL8URg796lVY9EG8q7ik8Z1BiTirYyde2ZdtmnToo1rRB5K59Grgs0xKyzMVZyu3zVq3sno+WfygJ6ELQdOm1FjBgMazYGCAWOZPBCWeCJafxcvZYmkpf2aGDgIFDTEs46Wbj1qv0WgpyHd14GJ/77YgTJb5+NtlGAyjehJRvV8nOixBh4qvDYpO57P3dVqapU6Fd5KVmVm96gez8Q+ep45RAA1vdKaYJLWSzCZMUgkzwhFhkiGA7kBjIYkHseg8qdFdzWje6nIIwKluB3l+6Jiw5j1guBj6DWhl2eqA2aEXbZ1MCzfOmQlIrwMqrqAAZ4HVWEbHDyCBvMmGXy0JAOYt0L1mlxygILYZv+W5CHhCdF3v00A2iko0cDIPjyoDbovGRfwABtmbM1BQwMWkUICsH9FyOD4VODe/ZIM7sCxsMOQCwi5F2PSOsfNICs8zcBq3aqOEkziJITbzUCTaDtU+qMOf0LiHXk2Rt0Mg673ePNn8LziudzTny1xnqtVvLdSARKd743pwICuvt52QvdNqhLo4snPl2zMTzJaZoi5D+DUu3A9I+TNMzFpXSCJI+eZ+0teMgZlJUaCLqFaV1pjzqg1bQCLAsQpgxZtbrF6c7/ViTM301LF4cJ1VI8KJku7dE8ZYev0EZdApAGXGA9Um1JooYROWxXjekrfAFgU5o2SfRaGGRieHyYxb+Httx+5EQ4fexz/Ba90Z+Gu+wMN0lsrmOQgMdn7RvixjNt6f+KB+2nJeQCfdpBNyjMAlN5sG5XnFq8/IkCocKD1g0N3Qq88k70JJvTi2rb/lDwPvMNfCQY3rXfWh7SlKPzXqSDZIZiMnP0kTFz8zEBy4e4PBhWqvPYfuaJzRsKcFfvlPR4KW/ef0P3vh6EzT21uN9o3MPR4ACwNIhLpC7FuIGF2BcnmgNN+B0QET5yRmr81Mt3P7t5LNs0K7T0GE9klX5qn4dVcGTRaiXzZNFtwrQ6azUD2C2bf/6JASee3krXN1FzndtdlXZwTTKp6IZh4I31ubKoGJ1fjuIyBDEhDGEgMZmPgYvm4St5IBsL/Z+KymYPNeGBISBxKNMowNrdWahOhUd4a6BkAldb54yAZnd+dLtk0KBgNG4io62XUOBACQGTIzcAHL0cwof8+8x/RW8bUf922TcoodMnkHIDj04HzfwlGJFN9RzsPVREGHnk6VPfRvgR48G5INEDGDb0b+5IUltS7IzfMGGkMrA+k+9mH26xNgozR3nclTFz6yma0dZgQH1ZNJ4NghiyPI0CWyb2SIv70XD8f2ftMo/w8681lUpwmARPGnlB1xdiSdxSn/JedOMWAxWU02O6RUeXFebSj2G93tc618fq4L/6Ol/m9mDASgyGoLFf8rxLk1whYypDvLhbQKbHLMDrsuIb0w0SFnB/HVsSusdY9lumGgIiA8vbCaGAxrhhVPBPaS5gLjd5cpEk3zPYNKV5fNUy4B731SJP0quKPi1Q3E/Y8JxZcngMmhWIcNBS/lW+icwttjeQret8Bk0l5wO1K/+vaJmzcyBYV0g4O3gmHR+6H3d2XrB2Kn1xt6zwdjl/+Kly8+9vAeBHm2PpQ3imDEgHLLkGBxvjBk090z8/CudvfhcsPfhtOXvsq9E3cE0COy4thOpZOFQ6GQtfQjTAiT4b0zgwKVgUl4+4wARh4FQYTPcfTism8k1jY4DjbiMkf6bLObNb8BRTP2c7V9dzXgJJB5flgksGhhQwkK/CuqHqrnA9QqjCoAUGhyrmtVAeUKkwMKAaVZqDMuJrL202iYiN8tQQbDUdM3G6sytJxwcFHuuezBBdAycR2+d8mETbAJRqMvMoEA+sl1ph5SfRWOkyZIIp9JBolnmUkuAQZGRfqegEN7SV0eYzVcQM29xElP6oSAAKNnXglwIaOAtF7uWgAoTGygI4yN1OD4804VGJnglN2PR0KbJlt037E/emcQEcFZoSleo13WKR3oYslhsLcUkooSO9PtSIg4lspeVFialcJb/xi/A/8Wr03VY4WR4oLlnGutCiLwwwkVTWAkqsBiqmUA8UkcORiECMAxEOJAxrxLmIPOzfI7oV5tZHBRN9BOnAAGYQs7uM5bL+nzG8GxDpWMPCOQXiEF20ypI04AM86migt810AAkPJNQy0I80g1jlG1RZAJz0BIJ5JtSI/6Dpy4iP70Rd/FOTZxEUs8CSYcL2uedUw8fm56I5LesQzdpgAjak8k6mAQpoCKiaAovd3mHwITFRo26C0ivdx+vr38jRuhy3y+tbuGA+b9pwIe1QQQxt2HQsf6H5zlAa37jsZjl36Mly697vQf+yRVS/SXZhuv7SfbBdsesbuhcFTT8Kxy5+Hc7e+s553Vt119uOwT97J0k29BpMVW4/Ik7kcRgUTjP7qnaNm3DH4yGaersDEPJIEEpedr3NsW8fwcJjqZ1LQOzh6x37mxn4KLrmnw/1ZAhXzUKYR1W/R06gDSsMb4dfKsYkAoMR9xXnJq6kDwsuo3jsRQOqA8lIwKUa3l2FihiYBxUuuJG6HCYk59gihVMY2x6PX4VCJP8cqy0Hy+twdtmwAJV5rP8vSvTBANgGgKTboxobaWIp1I2TVQSa2MQiUdjFSMYN4JrEMo3dF1nApUaojUolAAtgG8yTQUK1FRsbg43EAHAw3nojBwhR7rCG2AYpVo+H1CDQYAeBDd0oaUU2Dt6wOnP3m9VDFJmDRIYEqNoAUe8sdM9G+QzUb80RR/ccocoza5JWvw7Fr3wpmZwVHla5U6o5tO1SvEUceFzH+HBpNXorvz4ThbXgbzcphkitOq6M4FUCsdxedCliXXudPijrHQeKFgRJMUnwV6zpejTvbJu64B0bTQCBjupgxS3GM05s2ZikqDqxVWte3Eg5mTLlf9hy2gYelI6V51gEaBobBlxizPhlHeqZRUnXDBEw4h/dykLxqmJAO8YyPnP7ECjXENWFtMOFb8MDqYOIinGtE3jUPUbK4SOEATAAJWq9CT8/Yw3Dm+g/yRG6Hre3ywreOhDXbRsOGnZNh7faxsGRtX3hX4TZbhR7GiNBeQq+6Q6N3w5odI+F9fSeDEmk/oVMEveyAyfErXxhMLtz5weZQwzvpP3bfqrpohAcm7b1MOPmpGX26meMBuOfggHDDz7p7soDFPZUIk4ZnYoNpVTgAJj2TD8zjAULEJcdjASWey/UGlPTMqQVMordRqwSQqpr+25+AYlB5RWBpBRP+wdL4p/1MYCIZSKRfVgVMZHzfSDKY0JsryTJgKtWhUilUibkxDUQESvRQXBz3zNXY70DB4MSpVhogsSlXECVbHY8zvDJFeBT76NVkdewuDJ8Sc5wiQ89CgmdU4zzvYkuvKRRhybvomL6nKjeqrPMtQJPMSZUSkY6LSV98wIOxdw8H78OgIs+G6jBgwf8oAAkDveiVw0jig+MPQrfEILBDKv0dmpS0ZB+/owVAqF3QaTt80f7HQYPhVpXueo89DKdufhfO3PmN7nvLnkl1SKxiO2oJgB4sscdLY24mjI634xQeZuW7rcpSSwOHhWuNdMyu8zCS2Lb52SgkKK5sXAxhTnwRz9rmOgeCwUHvYNV5ih+/t3WL5jwMvYTBN6OPMHh4EnihggjLtyhAUHhYxPcBFKaopyMCI7oZDNuppbYtbVBQ0XOL+0Xvwzwf7ee5FFbMM5Ioqa5uG7WeaBg05hfDOGFo8EzMe5IhAt6vHCZcr/ehupSCycDpZ1YAWSy4+P2tUKQ0OSVM6qTr/F2JB2BCnADpAiZK5+t2TlhD+4kr34aOvmthnbySJev7wyKmlpeBmrtcBhAPT/H3oQoxVGsx4BCgtPdcsl5ceCZUdTGehN5eO5WG+2TEJy99Hs4mz+TKw9+Hi/d+E8YFjm2dJ6178MqtA2F3zwWDCel9O4UmpWtmBqYNDKibJyGQODhi9ad7rHHbPBed414LbXd7+i6HiUtf2ASkjLB/z2Cyp3QdYAIwVlWWgIEHAtDm0tYr2X6qw1KVmFdf1UFjJjKYmBqeitVQoAognkdTwWT2GtkyUwRKhImkpYOFzg+v/XwOgxBlOLVEjPbNYeKjf20/63N1fppKgqlE3PBat1WMshI3xttKcMqMNndXUhz0iBGOMm8GaX/VWNWpMN4GMAdJnSIUmqVrm9Q4bgPR0v7iu/SsvJQ+lRpeWjK2GB/PzMpIGGubkTWVLohE2kzwdGyMjrwbPA6qvRhjY1VpdHWml5qgg8Gw6jTzVi4LIJfCTrwbre84dMF++LT9IB0NBJPjjwSSX4erH/3FBpABH6rgAMu+IQFo4JpKs5d03/OC2lkbRY33xPPxdPC4eC+6E/K+5tEAG2Umfk5mJW3iziFM3OeyNAAktFTcOXyIN6qzTIxVSj3RIliSFJYOJAeWwZ79Wr6t+72t/QYSjun5iGOMvXlb6Ra9M1+ZfoHeV3oLCRgozowtaAoib8lbsSUN7MAHiCmtxvvLS0Eq4Lyr731PxoPeY/FY7FWGgSDMu1XKbu+7YvXrGBwzNhKzGyMvNP0YMMFbxttlkCBT0a/YMWbpzsJc97X099wwQQoLybw8bbvek95PWrV9NHQN3ZEX8W3Y1X0xLN0wEGYtVUlfz6Nq632FKXpXeQGYrFBBBojQa4sGd9pKgAldvOnVhYeybPOR0NZ1xroPn7r+rSDy23DjyZ/CtUd/tPaWnQrvhTJqwIfed0dk8JlFoVPpev2eSRsbgjdBpw5rD0leCfECODD+QIM2NqrJDQ7AXoVW2vEA0S4VzsYvfh6Gzz4La5k4NAGpuF7X+HVsU4DgWfTwopps5fahwO+prWChZ3Ft7D0WgVIHCpfXIKDqsZbtKD8CTOL/6qmViaIzlP8xMpcDxmASIRIFMKry/REsMpye+ZW5o9GIslKjMrg1aLJUAoogIWEzWA7PpkYJNGWgSLqnCyPthtq8IQzYK1Yc1ezhkPZJZWAkaEyn9K4ugyyGBCMskdkNNGRWZTwSDiUOIjH28WZK6/j7TKotmGq8VK0mrVRGXkXnAbpTt42Y1midkbtdKiWfkGdy7eN/CONXvraePgdG7to07ejQhLyfcbwgSYYw94aYNBCjZFVt/detEwK92zYfOBM27gM4tOeMhmV6FwapMa6C9iZ+1UrXR5uFQIaDtgJKbpTgqRayXlnuUZpYV9hkIl152srjJm7L65Te0jrGHEPPzMlx+hN5NTrvLaXRt+fqmXP17HnK7PP1HvNlTKnmSjCJP3uTJyLAuNhPz613WAITpeW3FW9R/ry4/Zbe/U3pfRkJ4EHPH/7Hsk1QplRalFolq5JVGPyYMKENDU+378THNnsw3i+FF+4PGFq2mVQl41+Vt5/kMHGgINIg/4M/Jpi0HbwQFistvE+7JMcF5qi0rm+i1xbeyYbdEzZVCh4JkLbxQhJhOk9Gi78p0hjv06acV8HovLzssfOf2QDHuTRk69qVgka/Ck6TV76yqVXo1cUvnDfvO2FtKHgpGHk6Y2D8DQoJBsQTMGHpYAEozGhNL65xeSbMyrCOdh158ADBlrre4MC76z5ssx9wMK0K1cxrdY39+VOFjSlhQl7JlIPEYGJK5yY5UEpQId8l1cFiJqoCpQET2SZTa6DQ0+u1n2MsE0hyNZfgGyLTW8kRGTxYRpDEumRlRgzmQlxlZQqXA6VWMWPkcoDk+nFhonvXwKQknq3vr1V6v1wRLrrGtvHWoqzqxpTtU9iZoSFM0zqi+syq0JQZmbCRXkh0zcRo05WWEePWo0QRTeahRISBI4Nd/ejPYVSZ8cDInbBbJee98kgYMYz2Dd6Qx3IrdA7fFkjuhx4Bh9LtkVNPkxiV/knoO/5RODxJFRuguWPX7u6VN9SdBonS8w15d2sGhu6aFOhGrOv2kgI4PXpHJXbcfZXwSj8ik/GxNMO3E06EmwDBj6niGBq2Y5y8qfBkZl+b3VfnAZgo7Zdn8pa8EvS2YPK2vBOT0p41psuo+Z9DzfsWeN6Yp7AFIgLOuwkm7+g9HCiAw6RnuADaXIV7/I+8vL2BG1Zn/wHem77DOwPYTNcstV2IOE5qwOHFYYIhwKvsPfGRVYHSbocXyf0bvbkETN2zldwLcTlE6kDiqsJkR9d5G/DJ7MAce1dhjXz9Hb0PkzYCkUXre8wLeU/fgUeCWAcmPkswvbsAx/4j16znF2ChOzEeDSDhmsUb+0KfjvELaAw/HgVAAQZ4jBh0BvGS5nLj70ABIg4W1jmHBnfawI5f/cZ6dG3ce9yqrzhWVJlxHy19HQEUBuGS7hmIS/UneZJrOEaaByYOhSo4ptO0QMmg8qKeinU3TvoQr1Hh1oBJAygGlUx4J/JMmGuKTJuqG5KiMZUBtKWXIJUxlMGslOlKmd9BUoJJkXGpn1bmIAM3QcQVM0Yh3fNvCxO+FenZ2XejJqC0UC1gTFkJXO9fgDiTeXfpXOIiqs3+m5HHDfuY/pz9nGsQx2Cp9GwuuzIjpaO2Q/wr5NNw+dEfrd53qzLlcmVOxuaQwVap1EbpaYMyCmLGgDZ63/ReDe3yRvbJKzkg7+SgvBTGThwel0ejZbc8mQPDMp5Hb4QOOg4cuWHGpFfHB08+DUOnn4WhU8/CUa0fEYR6tP/A0O3Q3nc1tAk+W+nV1sEUOOMJNEcDU+TTi849G7rnYqwIE4sDCzeMfkxrUYQj1WEK2/ky8LYuwJAO5e0yFYp1tBBI2Lb9UkybKuRo/Q3F9RtzgA/VVzKAizBuDZg4UHx2ZryfXyrcWcc4LtW77zx00b6PJd4igLRnSLEHVwSJFwjiPoFD+18VTDAe6wTwnuNPzAMFLBgfjuGR+HT0MT+2lncDjm0j08MEGUyUThjTRMGCqWQoIFghQfexXnV6tgFW72uN7TKoQIXqLYOJhHfCsQ9klDn2vow75y2kcLSRWQ2UXgWRFUq/eCXuySyUF3FYHvaxq1+r4POR0vEpq+bdz0zEQzflLZ4xb512EDwHA4ZAQnUV3Yi9PcM9FvIOIKDhnf/snLj2rUGJQlrh1ei9gQ9LA5He26u7OI9qNgbg8lyqzOwZGGUt8TSqkHge5UAxqBhMWlR7PS9Q/BoT9+L+GUhYd2VQQQkmaZ4pM1qxURSj5t5GkaHJTJ5ZlShymBQG0q6J+8xAshRA4r9RpgKJJGNRB4+qfkyYxAZ5jBbLxne/lHKQuPQNTeJ5KF1XgD1t+7XEjwPGYUIPNqqO3pRRpVqJ0bk7Dp4JYxeehauP/2h1ypSuqM8lQ9BzJWYmxlSoZGGNht3mOSyQUY/qs6llmBoDg8FgUMYUbN7PINBTVpUAHIBPl4xp38QjQeSTMHr2szB+/oswefGrcEwGBk1offT85zaD8RA6+4nW8Xie2ASJzGu1l7E7PVfMIDGAdM3OCTPO9FBboNIuf/ebteKQ3l8lOkrbMlJWNbGQtCpPYSFTyew2b4AG9FjwSUBROowGnmUS6VRpFA/mHaXN9wSTDxZ3yqB1qsSreytN5kCxH5EpHlhSZcNfAdfqHRnd3SGvhHfG+8LAmlEGJnpO7oUAkajGvgYcXhwm9PZhPjxggndClReGhvwCRPBOqLKqA0iuHCZVaLQSY7QoTExc+tq8UxuwqWfaPHc63riXwlgCGMi9EKABTADLByrl43GguB0b5lmfozSNt4LXwjZeCculm46EQ2N3ldY/U0HnrhWU1qigtLvnkt7rlrVjYdjx1oEH6QVvYr6MH9VRgIP2DYw+eYLR7lbFJW/+6pM/hfN3f6s0ftn2AwuDSfJE3FOxbb0L21SRUS0G1BwmQAzZoEg9I1ZdvYySZ+KqwqQAyvNVeblXE4VXUoZJHEiu8GcwcD1M8EwapV8MF5kgVqHoplqSMRwWDpBcDaMIfKJ+qcyMAIp5HdoXG91Zz2THvGG+DI5ayYD+rWBSGPhctddOozqgtJK+0UBsivt4btN5Euf5GBvqepkAkRIScx3xT3PmNbry6Pdh4ORjm6qCeuPYmBxLgzZaXJnASoVamjtO5pAxIONTPfEBjalKA4zFATZMIkkDIxM0rpKxX7tzPGxsPx62yYDtPHje/k/BhIoH5Nl0j9wNPRMPQ59Ky4jJAPtPPLFJHUcvfC4xhfgnNn9T1/BdM0ouAGOQkeez6/AVlQ4vKoOeU+YXaHZNmNFYJgOxaGNPmLeWnjMMHiPTxmoISsIxrcYwAgDvsk34CrxUi0U40MguQwBMlgCT/QVEXLHqjLYSGonpxtpVjPJmeh6m7QF85Bc8cmvEd2jo+gZMGpoOJvGnWNqnY35unYAJJVamIKIqkn+L0GkDg0B+8faQuqqtXOUqLtQMjjqt3DFm8TV28UubnsgGbGp/LUxIY0nmhaR1wMLSwCEZZCxNNsDDfr8OARPOp0GfhvpxpSfm9aLaa9H6XmuYbxcEOgdv2A+0aFvBo8Hb4Tj5gf/IM9Zl92F5lUrPFMKYBWHfkWvhuDydax/9OVy4/zuDFN5G9C5iAzxgoucYQKLdjIJayTPZf1JQ4Z86cX9sswFGeDfcQ1CYqSowYfqeEkwSUFpVeT2XiuvLMIkg0fP5fikCpgGUCBNlKoASq2qiV0JCoPqBUeErVCq1/0uQKZQ4WRpYzJBFmJSNH4aYqiLBQQbaG6SrPZ5cZIZ8u1B2Td7wbeu5oX5l8nfXd9qybLhdgKH++imka6a6l28XYSoj0QjXynXa5+FvymBCIzFzVDGxIVNNDJ95Eq48/G04KpisbRu1DEhjMkvXe4uAC3Nb7YmZN5UUady2NgO9R+wiiysfgWMeDd6MRG8c5lWiYXWRSmWMFWDw2artw1aVhUfEtPJxGpszMrznrNslVUOHxu4bRPg7oZXwBQ62gQujyYfOfirwfCrgPLM/+PUd+9iq3A4w4+zANZUYmfSTOdqOh40dzGBAJ4RBlUL75SX0WEa2vv16ZwzP+wrXd6gOM5Ckhnx9I4CgeoveSbGai3p8DBbeiTwanQNIWHIcr2T55sGwXt4A0+8wrxteCfmGuDOYCAQRJopDLXOvZDqYNP6uqH3ZuXUir+B50O2caeAZa8LARRpTOVYCRgJLS+n7p2p0rxPTGAGTUXmjmzpOyageLtr0OE5YxN5gAgHwUDw0PI+4LMEkAcM8Fy3teFrafgpAGUxWypjzx8VxeSb7lSb4oVbsETYQdnSdtV/7Agca/PFigMrmjhM22STT3V9+8HsDCnOGARvSLz3NJi9/Ka/+T1ZNjCdNl3t6h1mXYxlVaxtpG7HuyJt0P6ZgsTYTHWc/MMHrIQ3GDhlKU3yL3jlO4TNDKRxtdnODSEMU8Jhg1NUSKM8hv74hGt9RBEku9jEIswVMomdCKY4RvFRptDOau/eKzVdEVcrrNvVF1fBRAoxVCWb8EkgiTHbF9hjduwQGYDGFOMfeq6Li+txQvzLxXT8CTHR+vK5ZVmVlVYucpzA1MESYsB7Pi8dKEPH99gwKANJ8xZ0MJZ4HgGCW1cFTD8OVB7+1AWDAhGP0RHKQeL1z/D+I9i+KMGrARMbI4lnreicbb2EZIhoGyyCcm92L+5oRwDAk8NBJwL1c1vnH9hJldqpI+G0AVVpMZQNsaHugLYZZj4+c/DgMCygYqtHzX4bxi1/bqH68GqbQGDr7cRgUMAdO4fE8CIcn5NUM31C6vRTalPm3dDKJp7wYGZwFAt5svc8HMmofJOP0gQxoBAheS6zTR7EbMMYLQxePuWfCNjMQL92o96dHnb5h0YZ+K3BhMIk3QGJthrpXARNte+P7TGBCtVN+fp0MJkoHgIJxTPTkGjjzzLqQ0yOQvMI5Vo2lc6xXV0WvCibDZz+zGbmBCdWQGECON6rNSDNKE6SLTO4ZV/dZOk7xRJr0dBkLPhRwdtm5NNIDE/68SJdjvHKuo3Czbf8pO8YPuHYfuhC27DtpXgj/Spm89GW4Llg8/dX/shH5zBZNwYg2mF06l/R15dHfh1vP/tEa92knxOMAGngkeCNAhI4uu3ouWvsj1cWML8FrppqL6mCDid7HB69SBUj41IKjlRwouSpAASaNNpRmUDSL88ri2qItxu7VgEmzIkjoyVWBSZu0I7w+e4cMx27L7BCXBld+XERXU+j6iznbZcSoCsN4OUxU4lkoN1olOBsQmMGEQY0/031/Ppd/f6AyFFrJz6vKj/9Xg4n37Koqem2cE7fNu8P4SHEMjvZnxww2WuIpGLjZr+tNDhMz6rtsVtWjx+8bTIZPf2Q/JPISHaU+hwmeCue/uxABA11vx3hOhAjjKeJMvQBFUmYu1tnPNcW9IlC8Gi1mIBkEa5RVRqLUirFRZmjMmXbIpiShCo3MukJezSrBj2qCjcqwdB6gfYZGfAYHMqajZ+J+6D32IPQffxj6pMMT90Ln0I2w7+i1sP/odaveODgi72ecWYJ1TKXTPd3nwzYZFEqhwJVfxy5XQYlqD6ZHt545MnqMh5ilDIwwWO9h1GmTUhokXPB05glO5BOr3tD51g1Y302hi6W13Uhx1gftZ/2lYaL7ZOK+pB88HrqN0537qDw5xiExHRB5xWECLOpgYlKcWEN9RdaIXoFHVcCkUzDBi1zfftyqQ7muDiaxXQFROmfbq1cTROxYPE664Tjy9Idtst828/1Ka1yHp3Fw6JYBYpuM9yx5BzTg+39Thk7Jw5UOjaigcfSG/YwLjyT+1+Yfwxe//b/CmRvfhZ3ymGmTQXgutDNekVfy4Kt/DZcfRu8EjxqPY8V2ZpuQlyNobNpHO+JJ64YMTKjmAiw+3ottvrsEkxS2LaU4qQNKE1QyoDwfTJLnwcj6knKQcJ8qTAQQ1+oGTFAJJngdcTqLXZZBaGA9LKIzRcQWBRYzsL7Br1LnSjofY0bphZlVP+B3vEsOKJL3ybCptIRXYuNXdoafzd5uoCrBREbWwVBI+/z4VPL/rNca7pcShlkZ9BXDxKrnAMcMFSESq/4idOK2dR3GuBPugok1IAMVZTDv0eSeCXBYt3M4DEzeC1cFE6bwxoCSYd1ziN5HBID9BrdQBAJVZmRey8TAQud7w6N3o3QZOHSeg8pghYpzYjtCSTIuGBsyT4RLbKSMnkzs5kypjuoqprdg8j1rp2kbSb3QjlkmprcOVRAuGk8BDhA5cuKJdRc9dvmrcPzSV2Hi/GdhWIaFbqbdMi5UdfDHP0ZcU4pkwBvVc0xJv3hDn1XbUcJl3qgcxJSW7VeyMlwYioaha4SZ7VMpmrnkzPjrOuvJlQBRD5OoN6X83DJIFN9JDhPuwyh4xgXhmTAKnv+zk6+41qq4pFqQJNHjywGSy8CSwFGnCJPbVh3JrxxsEk08EBk77APVo434jmmHMEO+bmM3gHZKXwYTHTPjKxXhqbC16lytk945Fw+BySN30Gtrx4iBhGpXRtLjhcRJI+lVeN+AwzpwYfDjNXken/7wfxhM+LcKnglxzZQudDe+eP934f4X/92qu+hmT8GaaVaouqW9Dg+FGYXpSkwaJf3SDZm0SRdlgEKDPN9CHqKAEcOA74tpP18vSfHRGipKj0kGFAeASVAwENTLIILS+e6J5IowiWqCifJlLgOJlMaZYKQFEzPUbTJcuwI9DtYpQPcxRYRKdVsVKAyZJ3MwVxbwwbjx4vz8asWOcUu8H6zoVuJOHslsQNKmbRl/Kd4/wQADm+T77D10X/Nk8JTSO7Fkn8vAxz1oj3nF8k4DsXqpXvbeQGKm4vwMFs8jA4nCGTlMAEhsw5CRMLG/AZNo1HeHdW1DoX/iTrh6/zf2a1rmRCKjxR9JKRMrYUdoRJi8Nb8tKQKFEqA16ut8RIagATK2QyghK8MbSLiXKULElPbFklhc+tiLXDFjRcNihgQDk66JpVfvwkmGoVTW6IXGuBrexTK0MjIeDaCh2zHjDMj0XcO3Q6+MwvCZT8KJK1+HU9e+DSeufmNVHKOCDP8dx2gcUho/CFyU3ttV+tymEiX/IN+kMMOjAzBL9YyFKmXikdBWREMuJWPCwA2dKYVXIYcJBjDTLzP9Qtfl2w3wAJzGNQYmux8gUWFF8fM6NQVKFwxwZYDpwOlnYe/ADRvcShry9pJYzYV30lrvIhk2ZjhAbuhsn65/W3GDWPfjVPPRjfzo6U+s7ciq+7Qfo2fXENdaEs+mtB5hwpJzMZwYVIAS4z0WQFBM67GXHuEcvT68cY7biHMZ9KXyFPglMAUm2k3WKC3skN3qlDdCwzxLvFV6frHO1PXHlSbuf/4vliYAD1Vcc5SuqBrlvLO3fwi3P/3HcOHeb21qFboe904+sPS1fNtRpUkZe37GRYM01Wv6HjyRTUqD7X1X5E2ft/RJmiYvUfCz79F7W7Ux4WjfSBiR7hNUEkhQDnOOARRAjUfS8FASADLVgSSq+dwGSGhgR3G9uZ2kBUzklcQR8G7IlSh/huHWOn9wW7RlMGyR67dbpZytCpRFyqzvqgTxugzWzzGQJGC50lu7L4RDxx6HXf3XlICH7Rj3+P98uM1+70uJyOqOMYwyxlY1Q0nbtnWv1CUZ7wUv5qeztgka22Mm4VnyhH6q/T+ZtdVkno7uz0DLH0V6p1ep54GJg6PYboJJBEgESSyteSmNdhODiRLs+zI2a7cPht6xW+HyvV+H8fPPzDhiAKswYZv/qr+1QCBxLWQ7djV2o0iPFDIGBhvjjUFnP91x8UIKOCWgOUxiTxYyAoYk7ptSAonBpZVSydW3/XwyM92caQClNGjejEqPVElgHOi5Q/VX1/At80qoKqMaDICwn1liGZvA/Fp4NPwYqV+lWsYwYIT2yOPBW9/QzmBMwUXGi2cBlGj8iJNYcrb4MDWATFq2yUsVT7/Qvl9oH8ufUzhTviOduyI05K0AmSSb4BRwLZGXsoj0QSELr5977rI2En6HQAM887Ut3z4qIMXqrbdliJgbLEIDqLQWsKB6zp7FNQpbm1tM+xyKrNvPpQT25QLtLgGY6XtWKm3wcykDjcLF4ERcaf29HBgzkBWUlOaj9x2XsfCUxD4tyQukffIBc2eRHokTPFqmVKF7LmJEPPGHoWdQId2FSQPn7vxaoPjS4t+7CK/UN1FdevLGt+HG07+EictfWHUq4mdc+wevKR8M63sAAu+heCauJQpaeCbWlnL4QvRMCFPFNVO1MNs56eJ12TG7hrjVkm8AKualJ0gADjw77CTtq1QZsp+qYcZkUU0czwVmFLgaouNJvRrnxNH4DpA6yQvKVAcUYAJICphg/H+qRPkTGfSfav0XiphZSpwrVdLY1HUubJAbuVgR8/6q7vC6IvHvZsvw6wPnbxoIe5RwR698Ew7IjVyxa8KuRdznpzrPG/ZdVBWRMAwmKrkDEgKLJbD46ewIE89YrLOv2I93wnXmAb1C6b3y2ZBflV4EJnXKYRI1FUz2hNVbB0L30PVw4fZ39htUerbYYC9lNm/0pDHTqrtknN5eJA9lsZbSW1ong2AEreSt8/AKGPhFH3qMNFVR7I91walqS881ad28Ewy9jI4ZfZ43E80AJn7PXBh091wAC+9XzAqgkhPvTpVIbJMZMihiZKxdxnqcnbKSJCOfGeRJ92WqyIbPPQuDZ54aXJhMkG6iNMbyvwuqMphUc70AQ5051R3+v3DeAZCaZyZhkPkXD0b6DRmgXyrM3+A/9gpD9nmVWJzMNHodLNkuzknCKwEm7r2TPph+h5mD+acJ1V307qItxbwSGSnUBI70Tq7GM/S89D6uONFqei+tcz6ThPJXwu3d58IBgXmZwhWDw69z/fe49u8hLQ0oVtpm5oNc2mel8cY2pXEb86L3j6X4tMzFPr5PeQGjbHlB74lIC9YYLkNH3NO+QdsGDeXEMdWkxDfe6Omb39vARKZk4ZjN2rBtMA76FTjO3vleHslj69jRNSJbd+FZ6Jm8JzCdVOHqkOIaY867KoyUB0l/VJcCE9pYSHekV44DlOiZAKBG3mLdqkfJQwKpex+EBVWEfCf78fqW0ouw/XjgR3/8inxV27iA1Wtp36Z0Semfwh7gKMS2xDGX/1myCo1Wmh4mtGvIkGP4AQpg+bki5x29FLAAEKvbj4XF24bDbL30W/rAn3CejORCeS+dY/fCqbu/C72nnoa1HSeKRsTXZRy5L56HeR8S8PBSBh4KAPnZh9vDz2ZFj8S9kjJImgET21xqgPAy+k8PE0qGUY2SWT1MqObif9mdA1fsL3WTctF3yjUnY8XMpswtYbxJ0CaVeN9ZitHTM8zIARXBAiPDNTIGDNyKg7yGrQTH9Rhy79VVqt6SyNTe0Or7phVGqgKKlkrf4bLn6T0L2fOj3KhzHpnOjM3qbmXEw+bF0B4TS7Anrd0FqDDfFm0vQATADJyMHot7LdSh48kw0przmX6eKhBrf0mA4b6EG783JeNFYytvQe/hRrxq4DHobsQx7PEczo2G/k3B/g15j/wTCK8FYNBmwiSgDFrsGLxl83MVje4YZ4VXVHxmsxwkEs/l+Ri5bN3FdvRM9ivs4i+XMdQYbUZHE/bAI/4iV+HO0sQ+waIqqnIq29beou+aUhhagaVRbRbTs8ezi6onCgw2h9owsxVcsIGIxN/J678Kp258J3B8ZnChFxbpe/P+E/JK74ajp5/Ia7kSdnSfCbt7zodBbfefeKg0ckGFhyM2zmnuGjwEeVOKC4w6BS6ehUhbhIe/F0acdEdeRKRDro3vz3ewHqu4DKxUb2lJx4bFGwcU1ietly1jsFiyvUhx72nfgKJnoBwmvs8k2x6ndqmHRiu1hIm+w2CCwadtA5jYOh4F3oQM1nv60Hl60aUq5SxRAC/YfFQey2FrLMRDcZicuf+HcITeHCJlhAnHgYlANYteYnFkPY32XrIAKngq/CHw797fEn7yYarC+n8YTFAdOOpUBxEXjayNxlgJI6KMDUxKDfDaj5bIgO3tvxRO3fw2HLvylTLCRTNozGAbqx2UwM2IRENlmZ0SlpZFyVnnvq1jGBASK42NbihpEKfkj2iI5ngcWU8mIFPstYRthoV7a7sWHlXpvDpQ1MmA0UJ2TjIwyEqGhJcMIRmbY7wz70hmo0snRodvtIZ+lVDpxUgjP4AAFPvpISZ4HJ64b9Nt0B5DB5Ujggyz1uLNMNkgoAFCNgJb19ExYCMTD+4eC0tUkuef2XPWMeqYxlCvTlC4EXaSl+rNyOtdiacIE+AC6FUoM6CwlGFf1mm/OWB8CdOp8CsDZn/mVwhW/70cgAGUGN9TqYBJKqgUhQ2kAoMbRcKYsKMaB+O7XgVOwi/GeUwPjTgQKBW3zA9WbfhvKZ1bdFmeQgCK6huMJM+0Th/pPYlrqr2o/qRbL3FBLy2gQRUXBYSJy1/aHFxM6sgxvAk8i40dxwSMiwLCZQHmhL5vXN7ASRUs7oe+4w9s/+q2IXm5RwXRfvOCeDbhwrMACQUMAAtgCAeMOAULvGLSFufh5dMrkDTobUd4IUAEDwWQ0D7COCbG/e3quaI0eM/GYzFjBJ0e+Oe+tzVNCxMDSfRiKAx4mmsl0mUVJhEoESqlNpMIE3klMvq2LsUqL3kSMlrvy7UCKHgmS5XBFm2VK7v6UHhTH8z+naLj5I3vQ9/pTwSTUwYhPJufqaQMoH4iWAATPBEg4o1I7sLhrfxc51nX5ASQn81pwMMa/B0iqX75vxpM6vTKYKIM4/X01sahsEeLZLD29F1UyeubcOyqYKLS9oL1vWaYmmBChicRa5/BRPf8pe7N8i0dZwp5MgkJn6odSnbeHRKjy37ceQyLNdBT36qMESdzxKjEhG6QmImmAIW783UyFz/LLIUwblyr9ZL7j9ufzi/ubRk6eS/KNAxOo4cOVVh8KwMxqTKhp0573xXzXgDKMP8tl2E6cf1bEwaKnysxUSBVZUdOfWSzNO85ciVs6ToT1uHhKfyWbhsUCGSMlBmZMM9K9no2cDevUAbKvBQDB1I8S28sVP6krUtGmj9tMrs0P2Jjxmd+rrZ+7wmVPGNDLEv7G2eK72llhjiBIwN8sZ7ih7CiZE0YAWHCkvPq4vq5YTJD0RZjv8Ml3PROXijhHb0QQVziIdivGZg1m8KAvBLWKQhQALCqTOJIoCF9M0YJ7wSQbNp3zLT94Gl5K3esmqtD3gqAQUzfwsh5vpt3YBuYUJig0OVpinfEa6E6jY4e5CXacFYoDcT2N2wjYdeACZNm0jaCV7K541TYf/SW3vGe7nHR4MLg8nlrYvfjVjApQIKy/PFiMHG1hEn0TGJj/C5b/7tZGHMlVn0Y0xEvkheyvG3MRPUX7SfAZPPBc2Hg3GehWyWitUrM3qaCd0PXRn6NyxQLNs/T5kEFXJw+nSXbzLuEC0dDEEYNYHgbCXApfoylJT/MMphgjP8jYQIALayaZb3T6q6p6MeASQ4Uqm9oADx+7WubBA/Dt1AGH0NhiUiJ3kq8ZiAw4OzrNKjExlZKqBgWwUT3IzNgUK3ENXDdSuvMkku1AJmC/fSg2qlnRtCMWQaYq7ifRemYDJUMy7RKxqoqM/Z6d5fBI8soBShYulKG8uu5xo/lGau4d8rQ+bne9kL1BJmeEjglTK8aw1PDUFHVk1ePARkM1dBZRvA/CV1jd0OHvJu9OqdjEN2wGZj3KOx26tptAhSgAtK0RXj7C+/1rlVBqqSdtWt5DyGqexirw2zBh8Yf6vn3dJ/Tuo7vliHAQ9HSDPo0iiBJXglAyaBi3gnrSjcOFapoCHvCyA04S49H32fXal8dEF5GVItZlY3CyJ6l92Tp8eppil5aFHoIX6rlqK6l6otqTWZlIO3SHgZkqArbN8CEp5dMeCGoQ8Iz6RVM9h29qnR+3ObAw4shb5BeSGd4HOQRvFg6ARA+vAPHgQvjWJjqhY4fHf1XrT2TiSwpjH1IfAEQeSNoNvZz9WGbVHT3YV1z5KYtmX2B/XNlO4FJzMPxuxv5IS49LGx/luafHyaoDJMcKAYTq+KSzMjJoLLv7z6Ud4BHIaOCm0zXQ/uXBiN+BRa8E9pQVikBdykCqO6izcRhQlXXnLW9gbl7ICjzKdF1cJ0CAdfMxchnRkAvl+dj1TBKeHghwISlN0LGRkcMdoTJf6hn0gImhFt1X/SiGrI2FFQFyRQwIQ6aYOLVEMrs1NV6uwlVXjT0YfAw+FRxUUrGxcd7wFC4wYzGQZlPBQYrBSkhm8e4WJleBsq6JOoYsx5wPg2TGEuqe4AGGZIqHHpI0QPq6OmPreqH49u6zsnYjsiFp+fXQd1biTNl7JZKxodn1UGEjFCSEngBDZTAUbfP7lG5j2WqbP9UsnfRexXvqG3uj7EHMBh+jBUD2XwcDI3zgJYwY+r/dkEDkHSO3ArdDLo88Tj0qzR8ROGG50K1C6VmGviBM/HHKOvYuB/nIZu/Thl3tTLzCkqwMtJm8DtkzLstHzG7c/fYfZu+hvEHXguAvNQ+lbifwUQqQJIAYeewrrjypYeHSftKx20f1yVPh/UEgFep2Essvh/vSzy5QWWddyGOiSv3oGObxWHroUinDHr8Ed54E0CANE2vrc4hxZdEuwme/n5BBJDs6jlvMNl1WEsBinEnpCm+GZjQS5CqUNbx3ghLwoEelUw3tG3/qXBA+YSu6YzQByob9kyGpdQCqYC9attI4C+WG2UjmQNuU/tJ+6Ml/9nfrrhdxlAMQedDxS8Dbvl2nk1a9W83eTpnf57uSdNSHUCqcpg4UIpZgxNQgAmKMKEBHJjI8AETGuXZxzEMHQ18uMr0GFkgr2S+PvhdbSPaTXYqIOjVtbr9uFVzAZQ563vt/+TbD1JSPW3QYOoM80wkBjsBFv5/Qc+ELQfO2E+XIBzwiNVd2/X8nUlABO/pP0E11xQwqQVKus5GvCd4VFUHERQb3mm3KMPE6rRTZgcq7pkAEjwWYEKJi26Px699Y8aJ0rS7/SQ8ulKSyGM1FBkvyutsvSEwXtNpXSeZE2uvwERJnP81YOzICIxIj43S963EtU0JfulmJtfrUUamZ0rM8C2l9zGIIGV8qyYT3GKpk4yBAU2ykb9ReD1Vlc5N8gxUkj0nAUvbltlSJqyeUxhGDGYyWpaB0z4MKe/u9wFgQIbqn5VUjwkwjObfRnf7vsv2L5luvBcB5OiZp2HkwmdWb098UV02duFza4ehpHyAP2P2Xw5t3fTgOa57jQrsAwIY4yKoVhTQ1vYYTLrHHthMzMDEIF7EZ6pq0ntPKdKUGb4EmOy7PKyK8MjChGtjOJS3uUeEk+7LeyhOX6mUPovvSvmB9/L483fknT1+2Wfnp3PZR36h7YeZP2g3Ib+Qzvcq3Gk72S4PZNM+eTTtEyooTBZiPyAibzm4AAjeDVVoeK202ZAnrdeZCn6zlW5Xbx8RTG6G8fOfh+OXvw5Dp56Gvb1XwpaOUwIN/3C5EXoUl30TylNjKiAM3w0TF74MR449CTvTT8gACUD5AKgqDPy7PQ2byD/kpZQu8+2ZwgQ1eScOFINJBEoDJgkeZgBTDy/W3djRNZUGr/fIrPJKfHpsPBS6Dm89dDEsl8tP4zxVYFR52X/Nj94yYFClReKmFEXjO0u2vasbP27qOHojrFam4yWp3vpZqu6KDfDRUwEs0ejXAOFl9ApgQriZ0na1yuuFYAI46LBQAQpVUZ5hyURW5YFXkqq+KHUxOhyjBEwYQ4GLDRhIUCR8NxpecjV4SOaRJK8Eg44hwjiu3DFkGYxuk6vbRlQiihM+MqCP0cf8bwKt1jolp7mrGER2INiPkdKz3OA0SRnBQKL3wEOy/vPKdLVaRg+YTAzaKhTP8TmLotineypTuGJGa2y3lAPH3i0qf2++hzDFOyyqG5OHSDxwLSVT82BUUOJf2fSA4t8y1kVVeQfjhfGhWoy6e4MKQLnIzMqf2ZJfyI5d/MzmI6Oqha6qVGNSzbZsy5B59syNRX06c2Uxgy/fTjzGbrTJO7ACRGu5R2JxleKLbyYs3NtzQ8W32ffrGtKdn58bdpYco/BjHi/G/1VKaRSYFO8reXqyd+FbtHQDyjF7X6qJqSLUeyHelW8ij9BADgSoviKdU4VlPfIUf7GQ0G1tJNa9nEb0zUcsjv0+BpOR29YGw7gk4t7DlSmKMP4rVAjvkQd55sYP4dyt34RhBpv2CmBS/+TjcPbmr8Pl+3+05alr39ny6sM/25Lj63dN2szVzGDNXHLcuwkmWfq1/SkPWHqWqOq28UAtVAsTl8GkARRkMPmJQGL6MC6t2kv7zQDK0FXhQsP8T3QO7SJ4J2v2yhXrPBOWirZvK6DwVvYIJIcmH4nqV2yULAmbxna6Av/k/a3Wi4tRrLSX4LF0DFwPPccfWeMkvV1odGTcyf/2/ibT3324Rc/fLgMbja/BJFcdIFzVc2s1Q5CgVjCpKHpQDbWCSSuIGDiUUIp5mgwqcT+GwTNPI8NGkGAUKBVTzTJy/tNw8savzFhRTWUwSQnNDaIZcMlBAugR1V+U/kmQZCCqWzoGrsrjOS3v8qjNg8TMrUxBwRQWTD/iU5Aws+48wWTWMkrH8Vlkan9mSQVISORKqICkpQAIXTFbqQGUXNHbiZnIjKOWnsGKKjEMZRYuvC8qMqPCjXNYLyAj8f5W5SRD4oaVpRk2MngyZOZhId0D4xO7JvdYjx8a92mDYmAd/+Kgzh2DRLXh4OmPDSTHr36luPwmnLj+TZi88kUYPveJPJF7Yf8gf3qkezLVjR/Lm3kk4F9UnEWvMHqc0cM0WRppGHvSUkPx/WN7TBy/wXmERx5+ZqxJe/7NOtfu93+z95dNliVbmiaYv2aku+vmjQincGYGczRmZmZmMzc3Z/YAD+aIyzehsit7qltkZP7VmvdZunWffY4dc7eIjJuVk1UfXtlMulXXo0sx2c49Jyw9vuKZ4Cm9UYWwoBVafguurLwehnQQ4xbvlfy3+H2sx//l75R5z2y64foU+rf6veiS/+T/XcaT9fj9bOPNsOTf8gzCi3uQSaCoEk+d+eO5jrDi32P4jymOXquZ8jmAFu7+4HP/9E29co+jqe+u7wcyG8/+rOUfbMXX/2KPPv4X3zeyIEg1zrt3AkwYT47w5tkhrgEN0hHpmn8V/tu/CSZI4bDFQ4lAkXIwOVrt9SSsU38Se9Yir6A/Rj1GaPX1m8OV9n8crPDzKQK7oJwR8ylQp0Jl/c0W5ZAYJHL+Iy/iYqpWBoj8+0MV9n/sL7XfHBQcDlfYe3oWvT6pGK7tva1rngsmK3ambED3bdKzgEmZ/eZIhXsnVM5TBIYBdkN9EtDxjgEu72od7T5F7+EW3xd7ttOwICrX271QHNsKCvcwMio8vp0iTLarJ4kqBhKHSQISFxEmUTpMhRJKMAa5hBs6IQKTHmNMNVoZrT75nQ8ZQs9tjlNuS+VcGFxPhtKXiizumSgi6XkoVxHIjHf9cudn5OE8sLqeVSsBJkRcRWCAwlhVDJIHWBgCnEEST8jz5Hq8G4/UOjeb6ENEj+sZoPAunvgRiSIj4LAFMFkVnO+K9wqJyJ+hJfuDcc+JxJYapMRI+bnanz3HE60rd8/C6/w7pXAsyA2q9nkuHWPMObyHMlsnBGFa3PmIyjUTRodKb+DQf8froRjMcnTltTIIn8tj+cJHtmWemAHlVBH1JWPK4TJHDB4Kc78wsdnlqgndU57iNXLW4X94sZfHoeC1UJHvI4LLo4o9skOxacygBKMcFQ11GgeBjq8ncVHH885NvjUAIEDClQVHlJ8TxPne8TIjevSnQOE7CsLbw5/nJdDgWPxHed/BObxz5rwQV3IZjXgu12bjBku2U1jq+4EJ15Lpin2VyMBFIJFxwCshXVyvnXYPY3r9K5+RtLF3027UzcjjmLeGnk2fuZQiLZbABc9l5eHvbPHeD178BYxOX8Pz77ADdN6U3SAcvJ9KjGuEFf9G8v2Ej/bnpQUJqBQV35tRtjI+AEXpLQOUtAI+eiesFxpFzokCOv+vfTftfxMU/l4eBkOkULxAq6xz5SOKtGNW17fp84Yz9wTl6kTK3woe/+Vgmf1v79+w3woO7x6rtveO1xgDR/JBuIzVMlLXGqfs5M0eRRrqTQCcztUSkMSWXRjm+G7v0IdF70Drrt8e5R2Vo2JOioudxqRbDoek+In3zyuGAh4Fyvte3duvSc4vVKHnUUxvgkhWKUjSzonBE4kwIdHQmSv2EsYIpH0BPBErMShBhJ7tze4pVLYt2rhytbef/dEr+iiCYigVYOJAwRiSSFKxrYiixIpYJ+fDuQx8WN4yb51jD62BYq5aZRzI6ei6o/p/rAMS91YwjrqXK3kGiS8mdDewuiYa5WiIWcZEHg2DR/5Ebrx5ZlZc/0aFBBMM/87l75soe328X6rk3dP3LaJwjr6N/4bcQOa8zNBqLhpaXcP36t4YM1pJxUpiik9oKVffd9uLG5k6uWX4oXLBz7zSnboSQDK9QZ3LNw4YiryYJ6ah/65PK0G9SgSLj+8kOOORYox8EFOJEoPQkCMHEo9nidH17cSARnAg35ds+z+L4ZMYZO9fRrzVt4Z4ncRvvt0FHPKVhUiUH3OQoBxMYtwplP8Hj19hWaj0HyZyWPDfMv/ZjyX/s1D+7UlYEKdpiEExGZ4mAKHOBC+Gll2nFO60wgImcXbSbv0jPI2TDJNS0msXSkcSsMz5eczoWdu57mAZlefZIQ+UKRCOX+62Q9gG/TsfeFfr/Ev3RJVhiFUKHHOwKK5hNzzd7UDujUh5QEF5QEEBKulMiznljGWqxBgjPJP/fb+8BXkZ7wgsYQ6UMDMj48WcF1CIvJPrX/q0rLjvAOPdo1WCR7WWlbomQGTPSXkaygHxM45fU6Ipo5dwlxIcngVGPPQ5oeJ9j4AETCjmYnwjjHwsjnODnHgm+8/LqF0fFJCGHCp4HHnfkawXM/wo970JUAiTeP1brkU/Fx6FSmHiCS0fJhihMPBbyFV6wgUkCj8SgA/nTQRPYMLgjoySeuf5n2xk8WOfICiOeBs9CLyKnAIA4kRRRwVkclFh/o4hh1P3xGPlogSTmgATgMQywsnFdiKeB+T8HTOJmwRKhE1d7yRBcx4qTLAc4xw36jr/bcp6EIXG4m2KRjAV7xqfy/04nlW8f+E7R3Fc18VKY4CS5rj5xyR0QKL9dC7k3Oz9CSOK17xoTB4n/V4wWDS/pvEKE4v5zJTjVPp+YosPfrLbz/9iK4//YEuPfueaV46WIjC8FwZmrFdOuEoGiumYmZqZaZrjnDN4Lg7iTFjwT2LuG9CwjN6L70tEkVH8f6lxxzjrHjQ7j94E30wcL+qFZ0XYJGBJxT2S8AsDT+bAkSoBQv5/CHHol8j/YeH9EvGs+A5sU8TM0D3e90b/jaIzMgM0Q2ZmUryKcubsl4cxtvSpt9ACGiETRxpUTj9m5CQ8EK7ppBhT3krHyBM7p/91TJ64z8eTiDroM7cG0zo0/in7yHxGwLinnkknb1IxmKRQiTDJKDfQ404l4/qbQ5Ve9/GewIIAChSMPTWJrEzjObT42tviv8uYW0CECnQ6JwITLR0mMTKexesAGMCBinZacrFMPBIpCxNA8vdH5N3o2W6cRd/d8kRO3xqxq3IVS+rmFHnxTpq2fMObPIr0vAQoEUBpMVdyXvCGiqgAGv5uRaCxnXIJqyBxKeFQNBIqxwNMUpB4JA6uOFDA+wAmDKUNRDZf/NnGlj/xbYeJDEXwTrbChNYh0TMhUhOZT1xhmtpBh0nv5FNr6t9Q5J8IwPD75MCUAiWRw03v45BI3pdEHY2zFzMBlGSbY9EQuDHy9fBtqWTg0kiv66LRTQ2+3zdzPHvtW+RQiEan8L7Js3LnhPPidtbA5IlzdG22FVIESlQAibxOV/JN29ybY14RfCNk3mh6T+U7RcpAZfL2V7b08Hc2c+dbX5/Z/NZhwvqIjBceC1Mosz608Nq9GjKANV30HVpUBnDKi9qAFvU6gDl8L3GPYrFQge1AUfp1qEje6EDH4v8r/OdebKV4RVwmTpNp2g4meWGTWY/ye/h98Opyz0lhgpL4k1Uanm+R/383wkGhgYr+xzaKxZekTTxmWtkh/j1LJlJr6Nu0uu7byuQtS0uCw1P3TGILrbM3BpRmOu3gWYXNyUZj7iKmmwAsVLa3KtNA0RhQASakVTyTUDzd7v26mPmzXXGga/K5lbctG0OtUPwbG9mQSYhp5G16M0xQzkNB+TBJcuKFOfK8egQZ13cEkl3HdRzPIIEKrhQfdPrmgEfo2bvfKbJ+YpcEk3eOVLoYNRPhoSCAslfbQOY9eSDvHBekTlTKWOuYYAJY6F8S+plglPNh8pvD8nb0Tm6w9Xw8EUBS20cv4w07Kpdx71n6rSTvLr21aCr7rdnrMudEaIT5Rt4iAKEIsWMlCatQIdGQQDMwySQeDG4oclJEUGIAJsxhwnwOwGRi5VOrbF3MwcRBsB1MwpJITH0JTRnPy7BUtC4oN/VMkXpTLvi0noHXQu5J98H46d7Z+/Es9vnAknq/+L6eWBMj7TDhPZKlG2ud74k/MQjxfD+WJPacgQ9GN81FS+kxP67vSfbvVG6w/Z5Bfr/kPv58/57wHnnb20n3ICGHfhGCieTFXQVifwoTvyY/HPLCRPf199P5zG6I0aBuhCE2gATz61PsBSRIj1TKO0S0pMSA+UcW7v/oXgzL2c3vfN+gDBtTKlNPQ2tAhhah3N/7Z9zqT+ES3w8jnvVMgIlDJKPwzglMpAgCj9tpcW42ruvcIuGTB5UEStEzyXtWVjHcEm35N9uJsNX/iAow2U4BJqx7hk/r2aImPD4aIeFBNg/c934ieCa03AImU2tfWs/ECy/aOnO93wGx57gALVsbZvdsc9BQr0JRFxCi8t29Ep17VLBgBlO8TJ+Pf+Mb/58tQw+9CwaNnHgX3g8wpmnjLXoTTFAhUAQToEEOHICEzovp3CHa78ZTOQ6Wblh1HjMyMkEWFejvHJFB15LZF2mpwAiWREZyQmMrn3lFIkVcESbkYCJM8FDwTrz467juc6JKzwEi8lrOAhIFqGASIJIT7wPsfqNn54y7IvGFDqvs3LDOyVfWNPzYTt4Y9MhaCIQ3FkUl56Tfu+Xa3LmFXkUxORx+hmJOLSv2Z2HilbfajonHl0ooJPBQX9Fmp2To6QQVYcK0plVyszmWwgQDzjXJdVSah7brSBFKIqfEflppUWcywIyGI/cFpgW7JFeeOSQoMvN6ERmWWNTmANG74SU5UAqNrrYxzilMEmG03YgmxiCe55E7GnP26XkpKHh2wX0jAAoTyNvkz9B9orGMz0q3dcxzoPF5O1A4P3gf2wpDJKU5yOR5WSPo3xrDgHvy7xUPKLrAYFCsQfEVxVnUneBpXKmesCs1U1bawhDsTB52zxjXiXOYDhnDQ1pdffJH23jxVy8eW3r4k7cCpGkrvcJbhmQAu9a8xzj1Noy6zPAkaQ99/oPeF7C416KMX/RSiJseDnwL5yQgyCnnjbg3TmWy1gmTrCfnimEV5WEWwjeEc4gzqX4OPArl/zwLk2CMiyk2pc+uhwYWgp2+h6Im+tY1CR7AhPoPOiHScmt08VOblQcJVOr4X5UUH3el00TvP600pcwdkOG6vqTj4sWy0GkR0QueEiG8Eoox5+5+75l5Sojoy0fRF6VG0csqFu+L6W0wySqBCdAAHqGTYBwTK4CEXD/CkGJUtU+QcY8CqAgi7woSuwWXPdrHLH9nb/R7BdGCIujE6ufeDh5oxGIuIll0ixH34tg7x2j6W63nBJgw9lDwSjD8GHPehyKwMFIqhp2+MW7gZdjxQA5f6bGGAZoYf2JtY8/tuH4Auf3tYPA2pddk9mXnGNmJIgx2Ks7Pu17vz36HiRIZyhZxubROvQRGO4XJ1W671Tgjt/iDFCbV7csOkixM4nYQ+4BHKLN1z8TXicx9SgBzNjinyDz+yBqYnVBAoU8JXgv9TfBOIpxi8VZUXsLGQHMuzxeIHCKKkB6BdW3WKLDN/niOG6XM/dKiJq37dezH2Cb7owFGb4WLjsd7ZRWfFd8rhD8QD9uF5xcq5Mrzi262CMOTGCAMGe/ioJV4t+x3pN/i78u/7PLKWyp267o3bHj+tY0IFozldEL7KeagPvO0YMNYThSLlbUsWbmOAx/Ge+qTx0IxGIZoToaIUXTpdEffF5q4MroBfWDY5x1Txx55j3EfRbqW1mLJ/C56VyAS60VJ78RRildydSYY262KowB7HNd5eeCQ3LMrhIvO2ylMthx/g/A2fg5M/L9ltn14fKVdRPhTHOkwF0CACF5G29Ajr1BfUJgvyTsEFHRYpI8Wae+g7oEAxpnrA8oMrli3MgJ0YKR3PP/c61Rk58jE818BCs3CGbuLEUYuCk4+Lz/vpvD6tYq5iunvGKUXgHjnwIL5RKIBDz3PA3A4f6+gsk/awyi/gskueR67j1Ubs/RRvNIiV5smb2PLn3qLBspX39Nx90QS78TdYkU0YEKdCp4JIIl1Je6deP1J/jsEoAQjj3ficJDwQI5d6xdEntnIypfWLreRYq49+pkUXUWPIwDhLV5FhEcCnuwxOm9mvYa3ySGhBLJTcU14h/Ae4ZncJ+TavAOazostWEgkESoUJUVjTvHTTYEcmFABz7zXtZ2rKUQKFebODvAoFF4HfUfKmmZtUJ5Jt2DS1Lchd33Zi854zpXKUZ+JkI6MPN8n4JJSL4WELGEAvYWSPB0qKL0zmK5jH8AAAvF7HJB8j94twgRDGmHhRiKBRp6xSMIlhQnH4zVvkr9nTn6/RHHbi1QU/qFpdnhe4XWFSmECMDCmhcL4JCChCNNzjwksHBjJN8TvyAOKzqXfQmgo0eNFKENzH3vFbpUMCzDBkHjnTRkedEz78GTIMZ++MeCAoTiEXvMNMnRtI4yOLKMlr4R+LowvBlzonT9/L4z1xjS2eC/AhqFDGNKdPjIUi+G58F990E/ig+IXRowiqTTjpDgdOlMGURzkING6x3PCypULpwiYUFyYQIZ9/JM0ziRxICrzD9n2TNgOxD/7eTDJ9074DuZuCi2plLmTwcdLACZd48/Slln0ar/99E92/4N/cptJz3eaB+OJ4JFQlEUapJiLojHqS4AJ61TM8999jC6KOkuH/V/SWo8iT7YZsy3WmfAdv1YFfDH9HcVZuZkMK31JC6rCoeDZ5y2rJKZ33Q8UtH+XYPLe4QoHyvsCDEUedZ1rNjL/kQ0rR1Mlg0MiABpetCWRY/GKOzwOgKR91JnsSjyTLFSASCFM8JIAQ+pxCBb7zrbaqZtD1jX9gY2tf23t4y/0gd26Bx0SA0RyMMnBYVv5eVuhkwKiqLbCAeXc+DeLcyNMHGaJss/12eV0XojswcB4IlFCcuOtbcR/uFE3ZQOzr2xDMJle/8Lqu9fTyvKfBRMlWDIJeDr9M88dJngmFHsx/3a1PB4q969WjyvS93lrrjibo3tK0SBKFIvQe5gm4zSfpIOXG5/SQRk4Wp7IgChn60Ukuh5jzHURKN65UAbKjVQWMDovhoMbFQCA4VVYRFBEg7KdUmOUNT7JvaIiTDB+WaDzP4K0T8/LygfU1LE8gCQKRTXBGAXpXfmvSXi52E72+bdI6T5dm2so0a1/obS38FqeKP97I+24CDgY8NHnCtG7u7FT3CI+8UzOCWAZ8Qp4H/qla9X7S+CFMHAlHsp4MjoyHWFXHv/kcGGfTxwmANHRkvGtKBqLdS4UdVOhf1yGjWHxHQYZQxzArHBK3isUdQW5t5KCJcjDK4p9iidps+QEBjEeFCqelxP7ChX+lwNEacKl9fjOhfLKd31HhAnivZm226fd0PfQBPtS5Zh7DIyxRbEWIMEjoaf7k0/+1fuR0MKLTAAV7vxXipz5t8CFpsLABpjgpVAJzz8nwwBMKOb0gVXZlifq/zyBYK5/1t8UJmE4lQCTZGrcDEhi81yKoNAeGfoDZ+vsoAz9+zpv99FKe/dQuZZVtl8wOa6IUq4I1KMIxXABTMqEAQEcsVUX8AAo1JewD48FmLx7Qs8+SaU6qpbxByxZDykqV2xFgwC+YZ9+3rnyMeube23jt7+xVnko1KHgXfwimGyjN8LEE0BxUOxEWZhE7yjnnQR5jk7nBTc8GJdoDIFJrLMAENeUiPuUwDee/dFmNr6yBv6FPBaMfbb5braYazuYMEvjjbpJJYSn1jX20L0SvBEgUqMcaY2gQoU/g9hRxHYYo6qE6c8BABKVtwxXQWc8DA2DIFJUwhwpwAVvhW+KLYW8manugYGmot3b6wtWlNUDn+jRkEPHoEdjEY1JNPRRbuiTsCqmaHB8nXtklewPIsy5X7yvlECDgUqzk13lJMMXc9MZZYtrHCb6t35fXQM83PtQQk0TeAYo/l16j1AcGWBS07EuryQYKsrnKUvHqOCJhGa/IZfqxs/jUC73TSWtey7yYghXiq3wMOgfwfwbsQMlngjwACJ4JxR/MYYYsJne+NJBwxA+E/KG8WziwJWlAtSlmkk7XzHmxT4YP96Ld+L5Xq/kcFB6kAHGCLu38hbR3yr2ZI/yDEkGGvHfZvcF5QDi92Kpd+B/OPQAif+jAJO3AcW3+Z9a924TSs8R2IyfVpm0uKOjIhXvc3e+8+FU8Ezo7U5rLbzL87eG/Z/Gf4vXSfNhKu3pl0Kmgb4mXtSl/3tWYUmTYBpiUOHPrIwBHniGihvJ//fmwZn49Cb9bJikFe94Dp7zr5UBzhYvoWS/ALLvjEByrl6eSY3tEwD20PlQnsleeRgHZKyPKoLfUIRp7r0jo/PEGNqZNtfktijiAh6x8p36F/dKJOpM/v5ouWBGb/dYfxKaBod6myDex9/Vi7hCvQnCGF+snrJBJSRg0jz82AEToJOr9+EaDLQb5giBtwgDH4u3thxPIuCvIe4V7xufmQ8SEk2I+NGQIYwdRUIoVoIDh5KqMf2Dxw6TeeUmWwbuuoeRBUghTLyviSIgEGE4bMpruR8wAU5dyqW2j9y3Cnkl3Iv+JxRzUdzF0Np4Q+du0cRREUzvwxKvgj4StLVn+G9GGsYoUTTSPHjPRyBmwEgqdYnEwIRWftmmprTXx7DFUXkxbhd1P4a+yBaPZY0E24RPmovfRtEwO2yAga4rVO4Yz0EY43hdhIkMIeewXigdc2BgoGQgPLer3GKqjDENlb/x3cIyQCVbhyJp/wHFB1r04KFQ5EWZO0VcVOq2Dj2w8zIuwIRRhcm9sp4OlJkUfZFb5dmhjJ84Fozv4Us0cw0eIfK5XQRy+rjwDxjsk3/HiNQAg/oU5ktfefKTrT//o609+4PW6efyo/Z/a4OLH1vHxDOd/8DL9am3YTqK2McFQxfDIHopUeTwEe8XlvrX2k968N77EvEmgIXjYZ/vd7CE/xiPbwVJAjGWPD/+K94JAQi2HRzFhIdFXOCfhe04h5ODUUvCnhEJarrWvSiR4q7eSXl88x/bhDxJir1CMdecZwz4n95MX/ciTV6pGrcGeTYdI4+VgVvzyno8ltNMsa5wrNY+BtQFWkAkFH0NebEX8YAmyn/zYq6gbOV7vrJA2SPtAyryWCjm2iPtFgz26h7UozDLH8aksm05jC+kyFPasuC5Tn6gw4P6E8EneCR6LjDxGRXlGQkk7+Cl6P7v6Vno3UTv8R54OLoW7dLzmPqXWRxJnNf0E0ZF+/H1r6xeBMco+zn6ht1aAknv4UskU4TKyiOZIta2esPxXKT8N0q5XpdHbpQ8I/uOUSQS5d4ZhTROiLVf28zBjmdCvQWtrdqG7nsx19KDHwSBh173AUBi3UoOJElxlPYRed2AKTIjPB48DIbZblMOs33kgTGAHZ4H80ScJ/cqcF2pHvNB707rGdyLehKuwxs6e6vfJ5ai2APPBGNEJy68EwahRHgnQIeGHD76Md/FN+k+J6732A2GCcd46R0YfueSnseYQD6JFLlRGQtmhaSDK0u2uZZvwTvm3qxzLksgEiER5WCREUW5YqqsEmOnRJ6CRf+KIq/0/2X/odb9HF2HgcHwxOITn2dERt2X7COsdTy2ukGhrFtSeLohcGMQvAi8U+IB3pLXneheFa1L7iHMbHztHgTFVoA4jrCcggQl+7knzwgeVxIWFxUWSTiEsFA4XlacuKJ4UtJhJ29025nSfjtXPmgXq0aspG7CytoWrL5/w9rHH1n//CsbWxPUBJeFh9+7hpdee11M99QL79tCqzJaHNGcubJj1esUMLYM/koLJQwofSgY2me/4MGwIazHim3P9WvJMDARGuwjfe9R3EGebtJ0hIhbnCeYaDuV7hv/ZyhOU5zKKrlH/L/hn8bzw3GeFY/z7/OeLZExoA4Dw85An3TovlY75R0ZSwWBW41zVlI9obRC6ysGSNVz9G5kFkmTeOOlzQveso666IuCxBmB45zOv6E01Tr80BqVQbulezFSdbniQpXClSJLYMO8J7EOzouNY8ZE7+XpHRuQZBw8jgEJ0jFx7W3S+YJJgEhQqHzPCmMPTFKwIO3b4wZaEkQorgrr7K/zgKBlQWM/o6E+9xYjfAwvn1a4u4eSg5ffV+KZ7wgkQQwmicI2QNklT8VhklzPmF8YB3JezDQ3cftrG1v/UsZmU7l7xubifav0fknlP4YmKULJV2Fu5d9fsQw+VChGhWMhoSTvqvcn5+4NIfT9Lq2/r2UWJnQ0bJIHgGey8ugnucd0dup3mNAXJZ6H4c/BJGdgMaxEMI/MWgcaTYw5JChR38FEXERM75ktY+0Gm4p03T/k9smNKUcrEFwSZMqoV5FngYcBXGjpx6CGFJEwZSpNT0/J2+EbAMp+GQMyJ0R8ytwblQPunX3pMxYCk/O6Jzkiby6u8GC6WdaJswCFbc9h6xtJiDyX98MAu0fhYZsUi3n4J/C5rHdHCVAwGsyf7iCRcQt1HQEmnqNNcp6em9YyGC0pMXrsyxWBBBBEeREP6+wvpsy5efu0BE4YUgBAmPMf+C99My99tGFmDcQbjP/DjYb+p3s5bxDQ8O/P6OAlfUNRKcwkzjl2rVOA6bNLNaN2s2XWanrXrHX0vvXMPrOBhQ+sa+qpezB9M69sZPlTm1DGj+bJk8r80TeGZq0+/MvQQ2+JRrHOZYHlzI0Bz6n7OHEKL3p7A5VYz+IeewIXMpBeRJyUQLi3L8VSBfdmkv8SFK5lf4BJqMMJ96I0IvRxQww+65OHufTPFVd8fnwpe05WPgUy6Te5jowPcS+mLcT/yQ4g6v9A6QqvnLjKkmsoJvYJ2WieTf2kvESKfWnIwn9nHhbqthg0F28RcBPezOzIcFXe2i65dw4aIc0jfxftC+9CPBPIFdd2IoAimISK9Zy2eie54q5EAgJQiAow0f7jOlfip1AmytDzjB3UNHg/eCcyIBhy+p0wPhf1Jxj7+CMoxuJ57+gdfqt3+XvJYSKIRLmnwnvSlFiezF4aA+iHMak9w3lP3QEmX1hNz4bnULyJomCyRzDhXJ+JsChMcEkjUP62YnC4osKYKZJmxT6OecSK78r78x14IxlheCnmAhRAgia7Db0btvb4d7YqmPQqslEsReV89EzyRETWMgsTDBDPZJvIS7EGRZcYft4tnhPggYHGqAbjzDoJBU/lkmAATC7LuPmkRDf73EPpnnzqg1HSYqhSnsppgeeAnndA38jyiJ6LV0vuakg525GVT6xt/LFPVXBS9yFxAhLiEaMoAJEUJrqe8Ob9MKpMmYr3RKLh3WO5elx3b++cwhCIYCh9dsNgNGKxh4vcsgugKLwS5WASDJaPiyRhqBwmAkAsx47eyBulBBrP92sKjmdhglE4XtLpgAYik0oDGBaf6U//gHP4Pw6U7SQjg1JvZAs4iovhj1gClMNXlMMtkVG6Ko9U3svpsn67WD1i1xunvX6sQ/+uT5kH+sFMbYQ+LvTWZ+gX+rqsPPmDLT/6vRf70OKJ5rNVbasCy4zXEdCCiXoCwOJFdMq4OgAUxtQnxrpGbwEZQaJ1YEJRcjw3wp4WV4h1/h//yUGi/0ZmdK/iA9NX71McYQrrAwofii33K268f0HX61g4J8gBch4FgOQrSeO6T4RJBEmEiYe/jhXGT/bR6IRMEcWMZIyAA0WPVCPg8ZOJoAk3k6xR5EidFpOt4clQV+n1i3pGBAnPdoBtI+JfMXBspxQmuXlDEo9ExjcLk7TuIgsTHQMkDpMTtMyiIyO5/yav8KFHJr0wacdeKzpeqZnwQMGzASQM9kiiD/UhAVTv6p6hWEv3Yr9+0B5ptwzFe2fqwzHB4b3jAtGJSv30OgV2k1fG1vaseUuTCSUknocXgge1V9+yT9ftAybMm410v0Lt13P2n9OS9Tfql4Mn5oCLKdR7JDkXDLMinRtn7c+DiUTOnRw88ECsH9T9aUUFEOjzAUzqFJFWHv7oMOmffuFFX1mY4J24WNc1RPAIhvgO3rNZ9wYCRExa6jC7HJEx68nwrpwXi+D4Vu6Jt8FzbzbM2FXFAYrEmKYU0A0tfGiTa597y7/6nnV5LH36VkBZpxxokx2/0u4Aqu+7Y2Orn8szeWUVHcueiBjZlLDgP/v/0/m8q8dLxR8PJ4UdCRVw4QUxLD85PH/H5DjvHD1W1h0i2u/SdwUPke8MxVQOEGCiZcwdR6UwSYwVy9Qz8eKqAIksFGLxVpTv1zkBOlvPj4ow4T09t6n/QZ0SBpt555npj5ZU7OecNG7xf4soAiWMGqvv3aEOKLz2y7CiYEgV17XOfo4f8uIxJqBiwMoxu1Y37X1cars3PLPJVMPAhWFfAMuqwDK+ojgx/7E3c6ZOgUERqXhu7r/nrZ3oQ0Fz5jBoZZ+HB7BwD4R/oH/hjVq0Hes7Q91F+EfRQ8nWv8R/mHoligvYnj36nj0Kv718n+JDAInSBft0fC/xzo8FuedCvMmI7ejV+L/QdoR3THcRJN6MPkn36bmkTxl4vH/iPkvgwhLAMFIxjRzwTshM0Kyb4k6mnmCqYjJvnp51v7fBJB7HO8mr11N8LAaRqACTtM4iAqXac3f5MEmMfhYmCVDcK3GYNEh0RiQ32CFijvpAdESYZnknjHjKh5NgqTvxllxAIwFY9Ip2K1Hzg/YTEUuUEGRQ3tcP3K3Ej2fiw64cL9dzq/TjgUmjvJ5eYyrNOM8Dswx6JS5GhZZnMk7vCzwujJXk4PhF2h4mb4JFFBElNcBFlCb4xJgj7us5FVeAiVe2616hT4egkqzH4iuKtKrbl23x3ncOFKYHpbUVratiE+IUJihrUOLzdT83snoeEZeWV82D93xJZOa8+E1xHUOdVp5rP3UmF+QRMWox3gnv1CzDPigwjDNHusS7NcrruVgxqPsofM/Kwz1Xb8dliK7WMMMjg4d+Jbf9qScc3jGCBG+T/7p9vqkAAP/0SURBVEI8IGOBJ0eYxZwfGQ1yxb1KYFT6A0UvPkjO83fWvXhf/5YkvPP+ZQKEAJSMJ4KBciOFcoYqK87jmiwIssqCxAV0ipyXFedQx8Fw8XwHYc/3xqmV8fYGBWomdyIM4r/g2zx+FRP/3BWAUmyOi3wBEn2z7ulFPgqntHiHMM1KYUmnRW9ZdC301vchYKonHAz01mfol95pWoUJHnPKXc+/TpvQ0rGPJY0L+gUfKq9bFSeobwFMzIkEWE7fGvRpMI5c6db76bsV7tSB+NArDorcf3HgS76d/r/wD/fpfYEJmdndilNRgAVw7NU3OWgcJvpuvj+Rg4QMCekhK/br3BjHst4gAioe/voX/p9Yz4hzyBhRnBlhwHr0TspbF6xeGTSKuGjOTR8gvFP2+Rz1uoY4wH0iMOJ9HCJaZveRiSkExpu0xTPZHiaJEpiE1lhRFG8JCgIJQGFYen4SzdNorVHboxzI0APPGdIKB3cLY+N1Jnreb+WlMPkVzZJ5Fj/j6DUFUinTBA/Z8Rs9dkBGhR8HTH57rFwgKlVCqtKPp5irTjDpEbQ2beG+YLL2qU+niSfy/pla25/I1wUfFy3S8gDxc7QzmERPI0/6tqIJOkaaZN0jWmZfMGhBbhj0LAASmwJHqNAkN8KByvbylgWb2/zGYcIw9HgFDpN4nc4PYp1nhcjG83lPnuuGV88k4lLxTt8DmokCF94vJg6MGcvUW/DrqPPo8CHsbyjB1ypz0a7MxeDsBz5l6YgMR+/kc9/X2HtH4KDyVRH5gsJS3sYxvQv1LDTkmNz4SobykRtMnumDf+o5DhSdC0ioIPbEVTHsCSjOy05uneFBqOinuC4a12yOjO/OhnXuv7LOPo4B2BxI8gxSVolxCtdw3+0BESESis6C4r5i5yOOATg6ABPeHqf0L/huPMfx1c+8qIPydcKffxH/U1Zp/MuIeqIdwYR/r3vEXHeAxvYwoZ7BoSrDE78D74v6Tob8YMgRZl2l0phmzYxBFUfWnbn9tcNkev1rebJfuueCp8r8LX2KS0wQ1kBFPi2aWhbtiuLaeXlBp4ALHfcEF4oZtwA/bkv+r/x/aZ/eFc/DYSLtShRLShClJQEm8mIEmOid5GCCdL+sknBHW2BCHNQ+T/NSeox9+i+sY+hjkRhyuMie0mweoNDIhVZ21G0CE4q9AAodSkkLngHUvbg23CsDk+TeLN0rIT1TrJvIm0cXACSrInUmSEa+ACbuQcRth0cAQZDWfQRhwYTJqhwsFCmRm+21m41zPmJm7MjER8cIzvW/OVRm/0UCJng/TLRyoXrU54S/Lvgw8yJllbsp5tL7/f2RUnvn2C0ZkGpFAkHibI2dvdVtnWP3bVEwGV99rQBd0v0BB8O80DeGJZInI/iQ6y0EyoHM+pu1PUyy8sRLAopSBMom2qyKRqJMRPIImLkXXkj0RPBCgncStiNgfEgVRS76mFDMxThdTK/rY2nxTN4n77rk3sl78EyMbszFE8moyCOXT4Qlx++5KX9/PbMAJi4ZO1oa0eKEClWaNtIcEgPBhD80hayR8WAU1fru2/6+FwWeU4r01JfQWMBhItd94vaX1ppMOETRE4YrBYqWJFSmxb3ZMu/zrOP2Az7qeShPpgyZTnVAhn9D2AJE6mQADBDiG9N/yLfrW2IroZ+jaKhSAMmIRkAUU/R2smJ/Cg9UcH6ESSye45v4DjJtGBHgSas50pp7isk52XhULE7uGCYSBjKABIAEkFD/mR1LjyGR3DNJQBLrf/w7ku9EeC10tqM566WKMR92vbRxwftUMAQJY1JR3EUfjTF5LAz/whhU6UCVgszg4ifWTwZF57WNP7VqZWRL6mfsbDmdJvv0/Pxnx0wBYt3fxw2nPF+FzR59DwB5D+k7dklAJMqLwHQO8uIuD4cAlGIeioct4awl8c+lcIxwyEv3nJucx5L/iLFPO+zqPPaxzj1ZUi9NGiV9UszJqAUL97/3fkGU1gCU7POyivfye2v9F3omSRFTVgk4tigeByL0MUmlY+6ZJHUnjNd1qsF/3OWqcW8D3Tx4z/sXMJUlZXhEZDwbYPKbw/I29C406TypYyX1yqW0zvvyhBI5P2KffugeeRsUce06UabEIZicr1HirVYE7LLuCWDylXIrHykwF7Ufj0TnnJEH48tqBwqAAUIA5cD5WDxC7o7calh/s3LAeJO2JNxiiomZiJMk5mxEy+7nXK7xMlUSp4ycV7hznHuR247SfjwQ+obQ+x2YMLcJfULoM+Iw4V46LxaXcQ9y5PHdYu4cg0rREREOQ0xxJf1FMFxE7GzE55uBT4QJRozjDAeBcaB9PENpd4w+dgPBSKn09qVyFa+lum3ZSpX4r8mDuqxMB3Ut5LZoDjwk49gkF57+JREmxIlYtEJTxosCTZ3i2MDiRza+Tu41jCfF8B93Xv7FhwJhznWaZeKxUGEdBy8kIfKNQCSCBEMd+itoO6kDCXUi+YoGKQeU3L5oqKJX87O0DYQKYcK78s4U4VGsAUj4dipmMQ78C4+PMb5FJfEsq1BnomfvQAEm+m7dO4LEm+ZmYBKAovcjXgHN5P35Pr4FuACS0OdFmQgkuxHn06HSnfgDYJgoqqx50ccgo5iL+ha8E4pAJ+W90JqTrgHjAg3L0dUvrG/+I2sXWJi0jwEvqcvFC6KYjcwugOH/8N8cLgpX6looVgceQORdMrKyPdTb7tL3pDDBJuk8zg2V8SEu5nlliQrrTPLSfqL0H7Cu8E3BQnrVOv8yeiYRLiy5J+IcKuaJz9jbccWBlcfMZ/OdF3vSssvHUZNN5VrOzz6LDGGES4RJ2vCkQIWeSjrQY/Q+6EvCdgBMvrcSgUMdS2ze6010gYl7KgAlKhR/hXneu8NMiqJloxJ6ZQedlcbknnV6UdQ7FHFJPJdAP6ePvd40454J64xI6T9DgU8l657T9MQv10+nmAtV2/mybuuZfCCYfKnI9aHDxKHhEKlMlEAleiryUA4KJgcvIGASVBwgWeVDYzt5sRQRJzHOqYhIvk6C5mcSWQrkEYp1zgkgASJeDEXE0/UOAi2p+4hgACS06mLJECl0XGRcLlp0MQw9E2ThsUSYeHGZroswoWguRkxX5luIbACE/iAYYwwXRV9EQCJk/C7OdyMskAAWEsNpJdpLFfI266b1DnOuK5Vjvp/+Eaeu9tgtQQSY1HWsWFXroo+kgKdSJk8D76KH8l8tARrGLlukQtxgSOzzlcNWoXjWIQ9kMGnVMiKILj380Z5+/q/28PV/9SIg6k7o44Jq5C0DLFrIkFh55/j+OWWBkg+SVBwrJhkmh0q2KOVtiuBRXCgqHeMc6kwiTBDjYdEpNLbmYSBGgM95oZNlJo6hGM8KRM58J6LJdJg1Ei8RiOSLfbSKCn0wtsIUL4AWWXToi7M+8v30K2HE3Ni/hHDkWBw65IIyH1TA0/ExFKMzZ/4Lnyp8ePlTG137wiY2vrZpBq3c/Na7CwzJGx7Qcfq5UI9bI0+YTn70HGcoGZ8c7EpoIca34ZlQfIX3sQuwJBDZkydgov065uAEKhKZYhSaBmekfZ5Z0bqnK8XdQtsQ07sbeL1HTFvsd4i45xAMvnsqEueEjCATFXZ43TT1mkzXDUhWn/ze5u5+695KbfdaGt8pIosgKVTw0LZCJCsfJQABEwBCXQhFBbFlFUY91J/khliJdSnFQRJhUiAdoxkwkf3k9W67Vj9hdb1ryjmtK5LP2vnyAQWS4HBK5+regAyjcElUpajiqnKMx651p0aDnBBNDw9coIy8Uj8m6MD5auVWe6x36oEtPVCOZPVDq+4CJjUJQCoS5YACTA46TOr1DgEoB7QelC3SKqadFXOhYpHFe0yTsDxBY4jJbSpxJSqa4HVNLL6KrbAAAPImvcm2exeKrA4T7QcmjBi89uR3DhWGP8mDic6LMOH+vGM+TJSg+Q4iqt6dyEdEZeKk6BanMOH5ScTnGjdyMiYAEC+JHvPU4wAQBqIEgnhQPJ/e9xduDTpA6uWhNMglZ2BKmgvTGqVK603yTnDffV5tvQdFBjG35zm+iwz22W0XBJubyojU6B4+ttToQx+o8OkX/2ovv/m/bfXp7z1R0fKlY+yxA8qHc8Ez0bcAj7SYDpH7Byan+SYAIQOaJxlTGb7YSzuV4OPnJ95KBIqL9ew2BjSjPKBIrEel+3RdIUwotqMomeahDGfCyAIAn/NCfAqezZuE51DMcBQTFdyxH0cccshHbVC8yo4aEZvlxm+J38Dz0qIvLdnOwUTGNwnLbPNdwo3zvDL/KvPmDyqDMW43Guetqkv/fOiBF3F1z7yywaVP5J3IQxVMpu58Y4sPf/KRkenjEuZueeb94MrbVtxj8U6T9Cwvo662145cUzwjg3GpNWm9pXdR+veiPEEkFunFBkqpJ5aI+B//jUvbMV2wnQVLtBfRZpCWXJl0iZEn3RFPAY17JxQJCyxuW3Qex/A88LwpkqZV1+LDH2z50U9e7MU2VQ70TQEoXrqAbU3AFWCG9K+K/PNiAigOEz4ainrAKEC8fiTxQBhJGK/BIZIITwI5TBwkxRV7uTO4I7n5s6V9ouWCt7qq7qIFxrg+RC+j3D7FV1TuYxCu1k96b9oSeTM0MaSZMu9Ib+dTN5V7KCFgq5VAyl0HL9bIbe23vumHtvqITlAfKbe5oB8VYPL+aUFHikVd+8+E8cUo5jokiNB6KMAkVOZTlxJbfBWTNw/ORIAgjO5WhdxCApJURI5cgopyA6JElx5PQMJPJoJ4E0LW2af7AA6HCfv087OAiDChwn3CYfJ7L+5igqssTKIX4/fSvpgryr6vf5/O4Vs4TgQm8mF0ieAx0nNuzDFxj5BoFFaKV14sJ1EvA+xoZUdny92KI3S45Nm8F63NShtmrUa5Ksb7Yg4WWoBRFHVLGQx6+pYos0Ei8AYAeg/qNDwjlMRlwMLz8YjxpPCiGHyQYq5nX/5ftvHiz14MRP0JHgqwohMl38Y30dQdgOQkwyAFQAATcsoBJPtOU9QkI4McKDkFryTjuSRQKVQxmOTDJv9YhAo9t2MxlxfL6V8CWSpbMRjAhFEGCAeG9giZlQCLt6mYwSimtLWU3isOCxSV7SzoHQbju/syxvet6cDTgr6dWQYJA9JErOdIwyBeq+e7RwOIMLBaP64My/nKUbumuFLRsWp1/XetbeyJDSww3AsjHn/vYn2auURWv/BZYSky654MXktV15pdbZyxS7UCS9II6JA8XzK7nrlVnI6KNpP450BJFIt5+T9Z4G+nrD0hrcW05UZecZN9ESAsieMc98xcTLcSxwAEmQiKtGLmInooFHtRp0Zx7/X6Kfdm3RPRPaK4j/fwL/LPt9PfYezjUCMuirwQRVpK6ClE8DKQgyL0E0F4H7Tp5+F8AG34WfKRBAoBynkMw3JUXsXl6hEHCUChkvxcmRIxc74zqKO8EzqNXWuYssrOZV96HcmxSjuia0tb5/Sj78qgTCjR0EGpXO9yS4FeI4MxaAMzj2xFnsnoIkM0T9r7p6pkwGqV862T6mVAqUuQFyLP4+ilFhkQepQO6Z2GlBsZUO5GOe5S3h8DRSKlEUFQbFK89zRFd7XaDpHDcxZ5IgHsRImxyEqJJsCEdSITkSW4nEQMhi6h9QU5fYZOodMiMEB0WsQoM6xNBASQoZPi8PyH3pprRrlzDDQeQoSRF5WhZNuLuXh2RoURnPeLES7msjjGPnqrE7n9G7QfYBBW7oEkz6DojHf3nvuKH1zPcz2h6FqGsecdoyfD8DwXy4e9zwT1bTclgEJzY+KbP0/vEt6df8B/CQADvPRzIdHQ9wKQTN/5yg0u3ggVktTfMewLz/acnrwojBSGHiNM3R8gCf9IRlPLPSeV+RJADpyVgTnDeGI63wFDp7iwDmiAyv6zGH5dmygWiQGmAKecYjzIKRjPrDCiHAvvF0DCf+EfARM67w7OfyRv7Cv3zujfgZfkHfaAEMa6CFjYF47rO3YovI84gGrs4+H9PArOS6dQ4P0BBs/nPZLvidsePryr7pH2ctf16flazylsew9zhYG3GCNekukiveAFKzNxVnHngjJVV+tnHC6Ngw+sc/K59cszoUhsSN7LwMJrG2AbT2b5M+8gy2gLLSMPrKZn3T3dC4orGF6GoQlDjfB8/oFgktjNYEMTOyobim0EKO6RaMm2j8ShuM8y9omK56RK4EI6Im57ekvWEc+Nisdjpi5d1xJbTIdFKt8ZaYK6w40Xf7K1p3/w9EAzchppUNKQFlnzLJ6hZTFobKcAExkg5F5EVhRVOTwSJUVanAsg6MWOd0JgRgpSocnLsaRsm8ogXozcPEVaJ6512s2maYdJ08CGr5+83qXAU+CexINp1PVTDpybjdNuyHdr/2l5JFwztPBKiWVOEYXy4gp5UKUytvU6d8xGF57b+uNvbHzphVW1TtkReRpHLjTKgCEZV+jrRo0xpTqV252w2h7AtiZ3kEHrVq2iHVd3RO9J7pufhlvKz5d3lIAERSOaL3KH+cZh59K1wAijrfeLEYoIBEwYMuGywpPBEAFKGEZFECcR+brCj3+pf5SFCQaXPhzLD36w2Y2vvBNjhElUBArGN9aRvE0RKF4MBBD0rmxT7EVciH1ZHHQS9/XEIAEezvcElCSamDDi/R1iuo734jvwWs7jZVSPez0KYlBJRi4GNhSb4Ylxvo/ppfBAPB+vhxZbJKZFhQP1CRSVMQQMXhRwBiSA62L5iDcYYbA8csP8m1jEEjyJYMR3n5C3clLvebZDYd3py/3SgXOsd+p8issUPgLOPvdkEmOaGNX8f5+R7h2AkoNHUfk9KP7BUyZsQ9gdUzhUtC3bwNyHPosi85NQ0ezPxvAm8iFhoiEgx6/trPHfkfQeFGnlwSQBSuG5Pj1D8m0OhwgUBxm5Yi2BCdcqHBwwnPMWkeGKw554HQXhcEHXy5h6sbj+L3WuR2RUjykOnbypjEn1hF1vmnewMOxSw+B9QeOxdU489zoVisAYmBLDi3c3vPhxmHGSMeFklPFksXFkbkiXXuSqOERcJt2SHkJH7tCpOw8mCWhSJedwDRkrT0/6p4j7pRk43T9NP9r2dIO9kDwjp+91D4bvBgSEA8e0BCiMhECRF82FKe7afPVXH4gToPBdfE+2DuUXw2RbeBQR5+TB5ChDldT5S9CCgEofig4gHm4UHWkouyP3h2dy5FKrIDOsHNOKtY4wYuy6b2O4MdYsI0yoV4kG/ULFoHslw0sfBJhcUwQ9U6lrKtxLqRA8ptc+tHsvfrLZ2x9bY8+inb3ebqfkZRy/KGOhCHacyKXAPaL1Mze6rapjQRHovvXNPrHuqUeKMI+sfeyu3i0UwZ0tpXUPucx6fTPD5gMUPJXEdVXkQMGgsk6ECWW8v0iKcBEi4Z4hQmHw+Nn0PqfYgrCkqIjhRjC0eCWe09d/YMIytiNMaA1Fz3dgMnfna2NOE1pzAZFYNBZB8nNgEiN5DAs3aIqAgIRcDhA7KwNOR0iOeeTXdTFBsM63xsTAvXyZEd8Uv4X39c6PpYPeQq20adb70DA1MdvMo0KTZ76FcIhjlXE9+xjShfk25u5+4/UlvCMJLz7rzI1euyHvpap9RXF4VYZiSnGsV++J9xUyCfwjRnfAILKO93FI8Dh8vltLGZTzqDsPJntOAiPCCQOAwQnAeJNyMGEZlUAkinfQe8Wx6fgGwhKviqFn+unHs/mtV0xfrBzza2KvcIx7PkzwSBTPC46HIqzt9b4EJHy4EsQ7Rek+eUr2O0y0HbwRgZziq0TuHenZWZAE76O4wnHur7STKMIkNMsNQEH0wj+oDANTARxmwMurPd658TTNkKsn7YbgQn1Ls8KLjpPjq5/bPEBRfKHiGs0q/dB4gyJEOsAycCqjOND3iuF6mMLac/d6BmkJjzyARPHY03awFVnvJKZzl7bjMRTTh6c30keiXNrJpR9AkgcTnq/jiG08Kuww9YM0SKG4i2Lf5cc/eREYrbw47s3j5Z3/MpjI+ORUHCBZAR3ggUfCvO6I/TycCkxaCdDOncpNxoWhaz+9MRnqBEhQ6X6pckiQmRNs7jhQrjdMKhEwRH2Nw4bzantWBQ2GAdBPv9qhxD0qQN238bXXAs2iPlofcL5WgVWlRN8iMMzYwuZn9uTjP9vKgy+tc2TDrlYN2PXqIbtS3m/nBY9zCtCTV9pldMixM8XpssOjfWxT70JEui1t6P0pglvWe0157pVI4INY+g/GcOKtBJc15i5CDoPIQPk6RSA7B0s8n+uj2xvvSyQDJuQqCE8GbmP0XsZh8ty6jCKGFoMbi7pYkiN3mMhbdJg8/MHmN79xz4QcfIQNwtg6UNyg54CxrXiWR+LcPiI5EZlIS67/VuOs93jnHTnPE5XCLbrgxJfsPeO9uA/H8BYAJomQ74leCh4PPftpWIB3Qus0pg4Ok3Lpu3QO50eQEA5cR6fJPoWDw0QeCvUtMbFyT+plGAgTQ9Ex9sSBQo4egxUq0pP/lNQ9kJM+dpmiuCF9o7zFy3gyPTq/W/fEowlFXwCF4q7omRSDR6GyMIneTB5IEPeKMCFOEn76FodJS4AJ4161jz31jsMA42fDRPv2n5fXso3eP8c1W7UPnQUgObE/BYCeEYuttlXisURwRIChQph4MRdGNoHI9uK7EgOp+3sYaEk9yzFlHM4ILJcFFkYvrmWY+OEH1jn6yPrl2dOsngYs4yufeB3k1PoXgstXNn37SxuRMWaqB4YDIpNDPaUPqErmRmnTM34e13IAyMZ1DL97LUr3pHePlzoeM2psRzCgvOtdSTFXRu7BkBY4T0vSHHGetElrP+oMmXMGT536E7psMLIEfceAktf5co8YR3agAJMdeiXIYaKPZolXEupNqtzwecIUmSneoqUALw1IyAn2zb5QIn3orbmohAcWeBqdE4+sQtunZOzxTI5cbrVr8gqoT/FK+toxEXPMPZmhRSWQ+1+74T9XJiMlmOw5VSE3rsmqO2a98v3lF/9sd55+b/1TD6y8UZ5S46SV6343qkfsmjygkgpFGAGtpGpIEWZBRF6UB8RMcL167wGtMyDdqryrO96fgopZvguA+o/Uz2HJUC05kARvjYQdwRANz46UnO8w4X7cNxGuLzmF2CKJSED5P8NkMH8IE1MBFDr3YTSzxTvRM8GIUmeyoNwVMMEbwdDG1mHRK6H4z406kfUNyovUGRG5ibBESrwoWmORqIjwJBbCjoiezUGxL16fTSjuJXFPV6gXQoCTb6UehOItPJWYcCNUPeHqeYe07tK9OKdXGRtymyNLH3vGJwKQf9zYd8eNxOydb6xnkiEoNr3pKa2FMH7BCyCnKQgrZ8ukU9dqZ62iZU1QWxK0Bc7r8rAFlOCVBJDEOhTqTX4ZTJLtQqBoO3omGKDoHVLMyDDl9Aqn5RLNYK/Vz+g7BThd56CIsMjKDXVy3I1sMLRMMBfUuUX7tf99QQV4sGTbdb5DAAEsAg7QSeBzUMe8tZaekQ+OsOSYH9d7xmMpSOJ7IvYn13AvjN7bQYIEEq6T4UubvCb3pGnr0ZJuZYb6vHUYQ/cDBbxeWkA2KOfeIU+EImOa2JMxo+8WTe7x+tkGNoOydQAIj4U5fugkTL0lRcte9IuXRJrT+4RME9/Kfw8ZVP4h+4NBz6S1ZD2mjwCS4OVHmMR7Zu8d5ffUs0mf2GcypzRAoXc8LRqpQ/Tm/oIJ9Sbc373EGE470M+Hic7DyPn5XikfmgezxLPBVePlfbhkUZCmnK0jDxSpn1rP9FPB5UGoL5FXgqcRYUKdCHUTVMbjvdyUd8L+MnkwgKRr8rFN3/lCbtn31jF+X7mtIZ1LTr5cCajZwbD54if74Kt/sdtPvrOe8XtWWj9mZVIFapiw6pYZq2mbs4rmKSttGJexm7fKtinl9Hv18+qkejtf1mO3muQZda0otzonzwhjwo+kaSW0p6gDmALWIIeJwgTIYnB+mfBq+J4AKRosMEglA1NSR0L4LT783mY2v/IOg0TW3qnnNiBv5brAggeAMcWQUjyEEQYm5MgxosCEMbrqlSgACMDB8EaPhuvcgOv7omF/m/JyTVqyjTHzoeVlnFsG7zrM6BfDcXJIHsm17dJ7pO4494n3kjwHp+34jhESLIED38r3HaeORvKWaNp/SMb3MOcL0od9XdJ+6kO65HkAE/pfUL9HgiXhUO5NLpQGCnOb31rn+FN5p/cUzkveTJTWQhRz8Z8AAlPhMp5UU/8D5UhfWGPvfcWVVbtYMaWMDZmPDqUD6ktk8AWUAzKqAOCXwiR/X6IEJrFoBKDw3+i5zIgTzBfC6LsM635D27R22uJ5bCMHSWokioMkKsIEgACSdL+++eClLjt8pUc5/x7t41jwNiIoHB56hvdn0P7QRF5hpW+LwAkw0fuyTN6P9ZznwrdkgbG9Qg903ktQu5QbtDB+M2HEvyazcFyiWJW6OLxeWhlSDEoGiTmCmMF0dPFjb3ZP8TFpa0GixeSI9gMd0l2nDDXj0NEqkXRK8S/1yF4cRn0OcEnSgoNB7xnjJetu1BV/3cvQ/3WQaD0LknhdXDpAdE/uzX28Uj15BveOGX6GtsKWMDcK/QCpj8Vucy7P+dmeSTFg7EhUxicV8igLI+CEYSBHTaUOuWg6KgKRZkHEl0ObXsTVoiXFWlTMM+kW/TiOlyiBCyg3GhgWYMmhM7z0obySb+SafauE8liez6RDZM+pSjt+tVXGa9UeffwXe/XFv9jS3S+tWdtXyvrsSmmP3ajot0rBo6Vn2TqHNqxVx2o75pTbWLSq9mm7XAVMamWEK+3IxQY7e7PLSuTJXJIXw7vQcODoZahOe2xyqfTwFzxPIOpSqt3wB+XKPF1s71QyDKlxcFGMp/C42qGc5nNbefqTLTz8zovgeqaeeSQmR8R0uV6pToQiEiRGl/oKjCjFN8Bk6f731iQjjxGm8h6IMCcKLcDcm9E1O4UJ4PAcse4RQcJ7E2HJ4TA2EAmJIihyZDE3FUXEdzhr3e8JmLLPYDuBnEOC80lEvKP28e6sAxX3rrTO8SNIxvewzjkiY3tYYvu0YOvA2PhKHt4XXj7sTSyV4M6VDlirDASeyfjKZw4SPBM6tZU2U6Q6oHDRf5dXgsFjegXOGZhlMMJPrX3kqdV131V8pYnxiBKvvBPlzPecIn5iBGQA/w2eSdGiruRehD9xJoWJDAeeCPMILT36nQ3MfeTgow8HIPHKcckNaIExKK43wwSIBM8jLH3/xeC1nLg+aGdKR+3UzWEZcc4Nxj/1RHT/dGgT9iX7+a7onXA+753nTRWBiQ+iqPjuPfJ9Pbcd5R0tAQlNiTOKXgpLPDjeiVlGvYWfrnEpnuARk57IIOFxhCmrV9xjYdBShiui5SQCNHgqpFEyKQCmQx4LHbepCmBeErxjioWpb6aSnPjI/yNOppBBCWjcwCfpKIVHgRwYyfUIYPl9AZe+I4KG4lC8lDiMPUuakHMe9/eMotLS1viwvf4OjyKrLCDeqEKY4N0koqiGJQaSl+Ll6O0OIOi4iLfhxViSd14s69eHhwp4hHdCsRfNiDm3cUC58JlnNrbKEBGv5Zk80P4ZBQAVRQ36Kd2C0oY9+eQf7fln/2zTa6+tSl7IyUtNdvJio1241mq3agatrW/FBiaVq5i4Zx1D69Y1umHtw2vyQmYED7l3F+gxH5oTH7vUrMjED2rQD25WrjPA7UrNiN6NCZYw/nwjTaMp+mM9eCeeuDNg2AKN7ZQYBbyRUNFfq++jV3OX9c+9sJVngskjwaRr2QbnX9ni/e88slI/ET0T906iYVXEIWeF202dCUAhV0VO3iupeZ7+FXLjTET9OTBJvg+DhvCoiOy0HAEmFK/h6lMRT0QvlruibDaMfcV+HU/ENwDF1BtJvi2MJ6bjmWP+3sk6XkiEySF5J4fkTQAUwoE58CnzpriQXvUkHt6B3BieHkZgQEaBGeoY/qe+l97xjGc0pgQpw6PEeELnMosd9SqMbNs7+VJh+ti9lJquDcWRecEJoFAnQx+UUGmf7bz4NhXCJGzHfYkSmBBuMfwJUyY04v0Y+JDh3IcWXnsvcYYM+VvABHlxlzyRWLTF9sGLXXahatKuNSzY5doZ91AOUNQlEPgwHQAhgYV/nxTrUtxTyRz/ZTDRvWRM8yVYRIgoPMIMgQEmDhK2pSxMqF8EIizxftNMi9bZH+fqYZiiqvZlnxobjwSYkHHBY6EYjJlO8YppGUZ9MqU1VHpTHYCXwGgSGHiMuSsDFRSBEj0PB0MEjfbFY9Gr8Wt0nFKB9D7JMeBCCQLPA2LAjLTANud5sZvSD3GueJworl8OE5QBSjGYxCI0jmMcgQS5e4q06F8CRE7JUAIS78ORGGfms2Af53IedSblbfMOlbbRe1retor2WcGGfiGUAQ46TB589Gd7+OGfZRSe27WaYdt/slIGpVJAqber5QKOPJHhmYc2Ov/EBqYfWN/kPeufvme9E3fkii7aFXkoxy5TREQP+RoZr3o7ebVN7u2YdY7fl/F4LiPCXB5zem8CnoQe3jvnpYQir0LloBH3UZyVL4yz5wgw1IIqoxwfuthkp2/12MDCS8HkR5t78LVVdi56sdf4yqc2NPeBV0aTeyKiE8mzBpgWTuSclgWS1ce/c7BQ3wA88EZSr0TX/BzPhMgG+PiW2FeEbTIOeCYdY4+8kpIWL/TnwBi7YeDeMu6hKXQwhkFABKNCmKIcTHiv+D0RmO6tZJR+s0TR1iG29Y0urQMZKuzx0saWP1FCXnePhMRI/x0MAZWoTElMnRTztdB7vnnwnjGplucelQAvKFda2b7k5c1e1swglczN0XXbvZm6njuC0bIyH/onV7r0P4EJ8I3f+3YVhwnbWQUDjMLYYQon7cPAAr/mwQfy5H+Q8frE3+fIZWWAdF1sththEnPlYR0ICB6ZfTuFCSBxJUVeeCcldXOKqxtW1r5mJ28MKa2O+JhY1+tnLc5Dglfi/W0EXL6FbXrDRy/l3wKTrZKBTYDh36175L5dSo4hpjKOnglpChH/iGOIOMgxIENGjgwTdZcUh+G1VLQseD1Lz8RTr7ynWf783W9sdPm1N/KgeToV3wNKv95AqXtd8Uw2TWmZloZ4DRh6DHz0oAM8AjTypHfJeiw+3JLEft/Heyfnch8a78R7IodLfEaEk/SzW3P9m2CCdL7Xo8goRYhkYcI53BdDS+6doizAQdERcKFYy/txJF4JRUZe3KVzaBJ86AKTG7XJ+2B4gDH3ZCo7FgSTOaPzYkntiLydMYfJ5svf253nP1nv1CO7XDmg3HeFHTwFTOocJq19SzYukEwtv7DhuUfWPXrb+qc2bWj2vqByVxGAH6kAlody4GyVIkuDANNvbcO3beXRN7bx/EebvfO5j058rW7UPaIj8l54f2DiE3Z58VeuHqU4TBKAnKDCPSp4Jp7LdM+E+pIaRexGO1MmmCwBkx9s9v6XVt4+r++964aRnNDZm30ewQEEkZylG1cZUHJP7cMMM/O9VxZyDWXAnvPnWXoPlhhuN94/Aya8a/RM4j4iI82Y+2dfeq/7USUkhhRn/mmMA8bRDasUllkjqmW6X5IRju+WwiIDEJcSSxYmyAGUXhP2cx8qQmlxQ3l2U/+md+YiAZFgaWJM2TZzqpTUhHgW6vUeCB6LMnyMaNvlLfwI+85xGYCuVbtYPuTl4HiHVGoypTG5TmaixCiQkNOBIpPvfJMCOJCMYgFMyLkXk1+rcIzb50qHHWyMpMt0uLRMO3qFYYl0LsYXIx1h4oa1ECBZ/QyY0IorEUC53rho9QPKgffft/MVEwrTJWseeiAQh6m8mYMEoBAv+Ebe3T0S3i35Fr47996AYmcwSfclCvt0f32Tf6+u5z7cN62UJywSmPj0xoJFYcYlNlQBLvRNip4LmTYU18mwEd/IwNAcnyIu6lloUkxfD/p3MJovrakY4mRMGUOartOdgu4VNGIh4xKLwmIxWIREBEhMqyETijehNJAAxEsCgAzvrX2AhevdA9J7k1ZR9IQiSDjHt6XicaK4fh2YJIYzGswsWAJo8Dg4B7BUuOF1sMgIZxVh4oZUYhnPO0SHx6t4Kn1K0ONezEXLq5tNzIEwZa3Dd2S8vpfR/9Z6Jh/adRn7E1ea7ZR08WaHlTeMWs/YHYHkpU2tvBRE7ltjz7y1DizLQ7mjHP5Dq+tWzqCSVhd0dKtVhGj1CvrRpef29LO/2pNP/0G5+2/loTyVgZxTDmtUBqPH341+KLscJglQFDY+7zzhUrSoqz4VIHGYaN2Lx+TF7T3Nd1crkjcEmCy+tOWnP9j03S/sVsuMt3SrkzGjKeJxRQafxlfPoeVTAAQV7I1+jIpwWnKtPvpRYfPUzgEfIpkiH16JS+dnYZJrxriNuFYROHgltEJhP2X2bd63iNz/w4//ySslWwZlTLyZrYxCBIUMYAqNxJCyHYcuASSu5P0iIPNBEeARAeKJnXdPzmU9GgHuQQ6SpsTAlSIviidINDQpZuZH4FDTteLN0G8lHWvblXGg39FJeaJnS3uNAUT7Zp95S8TrdRMyKsrtSRcEFVr/0b8qTkhEvyuKE0jQ0fvaXoAjQCOnuC+33yukM+thO5zjOXntZ9BCJqWb2vjae3NXd67LGPXk5fBJ/NF4RpikOf/keBDH3iCBZL8Mszf/1fPpU7KH4j1t32hetOYRZXikK7Uz8vTuKzf+mS08+NF7mjMtRUnNpNJ1j3LTeh/eTd9Bf61sPEmHaMGAyuDxDe658J7+PezfCpOt4jjflnwn8dHvGWGSEfsw2sQpDLQrwoR/LoOLZ6K448VhEnWDFCE7hHScY1Ti0//kciUV+NPugTCnzoCAQnErMKHPx9qzP3pnwil5MIPyXNpHHztUQv3KuGdMTl4PfUDc6PPuiuP0b/PiZrcdZEQVdqQBj1MhLQMTny2U9+e99X2M0xYG/mQ7eGI+wKe2ASle9WE9KxcP3q4tMCnU2+ASYQE8MJJ8mMMkmxuXkfMK5QQQwAHvJE9JbtwrswWQwnPxYA6el3GQ4T6nRI03Utoy5SDBS2kb2bTp25/Y9Lpcx9mn8iYoulqzlv4V65RnMTj90KZXP7DZdbmYs4+tuW/ZKlsmrKJpzJp6521w5oEg8VA5zBE7ebXJdamiW4ZwxeY2XwskfxasvrEheTaN8nAqWqd1bN2q5SWdL+2zPYIJMzru1fu/d7TCfnu4TOFDh07tKwIThwaRwCNC5piHE3ANngkwOVveK5i8sMUn39nEnU+V45tQrm7MSqpH5Vr3K3IrN0+vfMELoOzTM/frHgEmbdbUd9vm7nxpKw+/F0ye2LlbfZ67AjwY3ixMHDJEQB17kzjXgcL1koNI15GgaK5Mq5ZHH/+ze0O0OqOoi7qQ4MWECB46aUZDi0cSEweQCvfl3bx+R4pgQcXgEnOR8Rjrvk+ifohiCXKLNFjAE6GlG7lLEv45heP12gm7Kc/jSvWIZ1IaB9atc0I5695V90IZcofREoaXXll935oA0q/vZr4W6l26dHzY62Josw9MKA+ncpOcHpWZcYyqQqXG0sW5WeXvJzftQJAiTDwXr20qj1knt0/RFj25mUCK6XGPX+vNy92T+HcGk6gEHgUCJLHzYlzuOd0koDTb9aYFweSxtY4+8aFMGuRFD8tTpQMgOfFuxQuM6yWKaRVvMN7EB7z22BiFUYc97ACy4mwEA8bRc99SFhhvhkkWOLnzKM4JlfNZmOg8Pddz9FrGdURRE0aYeEOREkMIef2D10NEZbeBjDwXgYWKbuZruVI9YeVty8oEP/RxwebufieY/M5F8SRD4TDjZOfEM8WnTa/Hu1o7pQwNjYK63fjzz7MZMNZ9WzD2olWgrPgFoCkCBTBc4+AGJlpnSR2WD7Kp/ciL+Bwm8jzT//92/WyYxHqQrKIn4gCRMUtBgmGMkcJz2wEOxWDCvggTP88Nav55AAUxdhZjaJG4L1T0Kwc4bBVtynGOMIHOfS03rXWIyvU71jV6V57HfcHikQ3NPvH+J22CQE27PJv6EbteM+BQ6Ry9bROrTB27aNdqB7z+pKx5zPqm79vSg8/tzovvbWTxqXKvdJIblDEak2G+bx165q2GSRksDLHeT+9NvY97KPLAUu9E4UG4AF4HcBJWhaLeIcxJz7fXKpJTzNVrXdOPbVIgwUO5Ujsi49ajyKkchAzZfsJUzwFkYb57esHLS5Gh43hd94pA+5ktP/hO7/xYRrRfRlYJI0IjY5DDPimzbzs5QFjKeEcDTu6/UYaUysaHH/2Tt8VnYiqKvvBi+Ebcctzp6Jpni84Q+yNMgEhsJOBDyCRQ4T29LDvJBbIdy7fjNxV6JiypiAcotMihBRzXAJyT8novlCkuVQ0roQ+719uqeNSnjEmL4hFx7aq8XfaNrnwoI8hIBN0e1gcUNw/TaOR6l10W4Mta591LoQycgSZprkszy60g0b4CWLxRDoMcTHxd+6NXQsUxxoKZC2nBxTwf42tfCHx3BbV+3QODjxH9JTApLs7lngylwpLvYYgVvu2WDGD7+DNrl0EsqZu2m81hKgHqmxAdmikWZF5+epBTTwAgYqkGacTTg0ASYKKcdgSAzvu3wMTFduE+idGow6i5ekYRkTlw6RzP2QMTiqEEjmzFdtzGmwgV66xzrNuBT18lOpQCFeq46HnPP2PkAry35ce/l+fCSL9M/PWFt8xjauOqjjWvdzpXNiKvjpaoil/APKl7os8aS8S+WIQYl9kWdCwdIpltGmvEwTOL/fPt9ItgkoVHobbmsgHJVpg4KBJYpPt0PHol4XgOJClQJCawOnKZFmK4Y1TU01egTy7hhHKd0/IaZq26fcHqupZk2Fblhay5GntXtG9RIJmzqtYZK2+asFv1o1bZOmltQ+vKTX+oXPQ9a+hdUO56xr2S8ZUXgskX7p2wfaW6V26rXPj6YXlAAtTcM2vqX7cLMtBnZExOXWVsKn4KPxOAKMyoL/LwAb6EY66ynv4khI3DREsMKXO2vC8wvX9O33qxyU4JHI1Dd6yH4hXB8nzloL5fEZ/w0DXv04Q48UyAiW9rP5Bh+tvqjkWbXP3Elu5/q+974u96+EKASYAHxlcwwMif03pijN+mCJAsTBiWhBZjtGDZfPFnW7z/vfcgpi078YA4Ajg8t67z82CSFaApgEnWKwEadESk0hOAAYoIE/8m3TcLE65hm+bSnkPUNZRvcz5eGtMDn7oWgHK1dtSqOheUc2aq3w+99WCJ9uGt0ABkcOGlDMCcEnK7PNIqhzhTQVN/BuQBCs3hS2oZ3ThMIEbutxhMikJjO0WAJAafdc95YiR0zGGi85gbhOHUR5Y/de+kaeC+9+7+WTBJznmbOJd7OkB0fxfvpP2VXevWLQPZMfncLiknflaeINCgfwPDAsXpAWiWXdWxrPCa8PoBjyeJfcmHCfdNoPBrwOQNSmdELJT20yoqK4dJBEeEiZSDSaiT8PNZKswRDQ34V4CeOVWYspgm5z1TL/XvPpO38r33FVp/9mfbePlXhwvjrdFCj6bfjLtWJg+URg30fQIAxAPiQxTxweuhiDfJtgMko+Cl5BQ8FOJF8X9eVLrPL4dJITiKCZgo8WdhUqgUJAUqBhIUj8cK+lhZT87w+JU25TzbZWR67XLFoF2pHLIScppaso2u0tyYTokyFvXKXdZ1L1pT36p1T9yzqfWPbHTphQ9l3z1x14u0ZjZe2+wdis6UI2ifsnO39IyrTYLJkB+fXn+t5Ut5LMtWSYdIgay0edou6lk+GrIDhOIucloBLKFOJWmUAAA8LAJ4GayOIdRDAtI6DRCudVlpmwDXd9tKBYaTtxgziroReSEJPIBKFiwUuSG8pYrWORtf/thh0j/9LMAkeiYYcz3XPRkG43SYAIYAhzcpQiSKfRh3KvlXH//kQKF5JJXxzBlP3YHDROdR8R29kGJACcVoOqb4E4u54nN5b0BAO3+G1GewR7yLWMxVFCZcm2ynHk08X+9FeBy7xICQPT4AqA8quvjKJtY/tc7xh96k/aYyKgxOClAoZjwqeOw9qX97olLxnEFK691rPn2Doe/7vSUiDUeOXiGxhVz7rwkTDH4cdTjmOPFSmOeDnCstuZiBkNzs+YpRXRuuz6t8L4QJ90+ekW3ttJ04L8IknbtE24x/VSdj1zf/kcPkbNmwl8FTLo+hBRp0bqU4kMppRIdaOs9hsEkLbj+IA/o/hT3c3waTYh7Hz5HDBCUAiQpACAreRpC3iMoAJSoe53x/X/0f/lXWyNOYALCckLdCK0AyAjSaACx4K0xPvPLkD97UG0+FkQ2ADMPoUyfWMfZUcGaeH8ZAHHRvxScbSzwMr/9I4gZAcWCkIJHie2SVHCv2z4uJePBv80x2AhUHCoZyZzApBpCo7Dleh6Jcd7wH87fjDZAbx4AexiXWOvUJrB+SkWR5Qgn7StWQ13W0DG540RgV9sMLz2369msHyvjyKxtZfO7rwGR85ZV1jW8KPPMOEfqkVLZNCjzPfGZHn3d+5SMbW/5AeiXwPLMaeUUUe1CRvkvGhqIvYLJbxseXXgSWtHDz+pEQRnuoO5IxjRPusCRyn68csUt1yt1VKlHqG7woTN++P1WASdx+n/sKNHgvpTKCo4sfOkwGZp8r9z2Q1plgcP26JNzQTmASDX1WAAWY9Ew+82bINIekIn5w7gPvd0LiwkgAFXJrVPa7B4ISiNCSLVbqh7qYINaBAe9LsRZFVHHsJJph4pVEqGVh4hWmAIN98XolavdItN+L9AgHxQ/iCp1UGXi0QeAemFc8WP5I735H3sq4vI0JY1QGmqkzN8+RS0qY8h73na7W+9InSB6TAMOApsdK8FAxKOT0lIgV3r8YJjLOUYUwYQh4yskp7sI4YCwwIgwFw+RPwARjQ3FKzGlGiHgfiwKYpM9JnvE2cW4s2oowAVqMddVEfcDSJz7c+6mbA54bj7l5WhbRv4dOrUCE0QkACkVe1DNRnBQyG4oXiifRyKfgIP66ku1E8ZxfBybhXR0c8ijcu4jrCSQcJIrX3oy3QFmYRM8kVHwn0r90sCi82MbgAwEGGKURhYOlcc7qeu9Y78wrY457OqLeefUPdu+jf7a7H/yT3Xn5D7by+A9eN8bQOXihlR1rxvhieDsMDUORGrNIxv47ESSFiiBJt6UsMLIqFhf+jvG1ikEkqyxQsnUmWaBEFQWJDM12MEEREhEUxVR4DjDBM8EriXUpFJt5nQH3lDDgcd09GL0DxpKiKMrGy+RB1DPY4/Cm9c/Iy7j9ibyQT21Gy8k1QMLyQxnDJ3LF1xXpZUhaGLF2TGCZk6F8biuPvraNZ/Th+M7Wn37vzYeXHn6tBMzQ3716X8KF1msRJMztwjLs81Zb3nKLsFCYOUDCZDs+R4KWzOh25GqXHVVu7pAMFGXHwIQJvg7q+32iL317kL5TcpiQW9axm8pVjyy8sqUH37oXdal80HPiweAqsUaY6J4pTFKgFBdGO9ZfUJfBkvsxnlEc8t57Ay/g7X0st/yxcqPd+k96pt6f3DpL/l/4nyz1f/WfYpzAO/WJyPSO0bMAQHgVjKeFx0PP4oa+DSVChYvCznv2J+e7tO4QSYCStsaRInQcWDxH307/plM3euSFzPh9mwaZN3zOPY0zt8g5Dtt5hR8V7scu0zsaoAQYkbnhekZJQECECluMnjc++BvAhPt4ubjujSGg2CvChDJ2YEKRyLWGWS8DjxBBeA8RKG4kdL/tnrWdOI/vAiQ5mAimMogto49tZOUzYzpdxryK9RDk9sk4sH5a4KD5LBkDms3Sd4chPrzhgs4j4+FK4cH9Q3hGmOTqPgJAfi2YRA+kmLJAcZgUFm0hilEjSLjO4SRDHeUGOxhwlm7EtR+o8A/xKPAyGHGBOrDqrnVrHXns/5XiSwbyBCQUf00x9/3qFy7qXfrnPlTcFVjk4VzXv79QPur/gPtGaKTg0POCwjvFbc98aLvYfy+mHcEEZb0Th0oWJhmoZEHiMFEC31LMdQrVhCWGIzEeERRblBzLiv0RIg4SbZPL9zoXFJ+ViGe40ZTwUo5fbrWzN7rtas2IVbTOWBOtdBZeCB4fh1ZhEjDBY+kYuWO1XfNW1T4jAE04UKhXoT5l5dFXdkcA2Xj+g9374A/2+PVfbPPV75STeOiDR4bZG2XgzxEeOZhE7VWu1nVG76zv8hkDpTg3v8/HTzjJ8O5V4tmjd9+TfPuh8/USABBEmNNeEAkwqdG30rqs2o9drx0VRJ4LJt84VC7j3ZAgye3LkMZwwYsBKCzfJpoe02rMZ0xMoEJOn6a3QISe+TTB9YHxVj/1HvwU+WBww/A0GBb+Hd9CGPGviQeANcCV/xyMfFL0JeOPSJRMHcxQ2lMbX3pfEJqNcz6ZF/dwgF0ivBzeLZUMEMsIE47v0zft413o2yRDwoB3jC13tZY5K8Lc8BiGaDDSljoYC50fO5N5Sx+MEcbMjR7GkGWuPuHXgwkequ6BAdeSHC5gwRgxhD6DPQITxumiPN57fScgiTChxY6PU5UYjggHnvtzYBK/KVbEA5NWwYQpc4EJzX9DEY/CXWHj4aL/RMaAfjoMQNo98dQzCDSvplk1vbIJS871/69lLkzJWAgmhDNykIT1nJeynYoDJKs8z6RQWaAkUPFirgiPrPJAggIwokJx0lZvwSEj0VoPww5UqBe54N7KvLfQax994mChufWoAEJ9CmChfmXt6Z+8aXg/lfYjjxwq1+pmvA8SkMJTyYp9gIa4g3IwKf7fi+lvCpNcS658mESj74Y/Y+wjJLZI+yNEwrm57bjPe88XuW+Uw0TnuliXyNUfvchcFx12tXpIgFhRhH6gnPQrGUP9nPXX1ikPo7J1WtAZVK6730qqB+xmw3DwTFYw0F/IK/lG3oig8uJHe/j6Tw6TnukHdrGyz46W0OtfOdgrJALeBYgwD0tYxvUAFIWNcuMRJngm7ykc32Wpb36XdYGFczwXfaHeBUgASG5a4gCSCJOS6kGjufTSg69tbOkDbQ8b/SNCsZDCV/elaMw9HIXJTpTCRP8az4R7UXTEWEUMyT2+/FrwXbKu8UeCCVB+5Y0kqNtiiBiGqKGO4aBge1DfwHK/vuN9QMj7+1LfxfPIMAgqsUgMA8OYb2OCFBMYdU0+URgDkxC3OCeXidF76t1CcRfFnZIMEvUkeGUOU4rWpD3EJS25hqbKJH4MhOeoAZCW7GOJkeAYnda8ebH2YyTjeXE9LdeXtsAkMdpvE8VGO4WJjx+m/ZerJrwiF5gAFSpqKc7yHt4ZoCD3THQN9/R3TN6rKEzYl1EWJtE74doUJjJywIQWTBEm7lEAWIUxnhsza9JrnCFtugQUOu/R6ZMBOIG3w8S9zACTtC+UloXFXDtRMXgUCpjw3/mXWeWgkJNPp10IkURZkIR7BEhEzyBbfxKMeM5biev811ix7mBR2AIF/jEeCxXx/bNhMrTVJ3/04q8Hr//Fl9S1UOfClMTMbUPdChX2eK50GvU57wUoitXoi0RLrgg0B4neY0sc2EZ/c88kp5DQC418VNY7QREk2X2o8LosQLIqPA9FmPizKA7TeRjQIxcbfdiUi+V97qX0Tj6yxXtfOUzqe5bsfCmjiNKHosk7Ml6u7LWa7hm5mi+VE/hKP/A7W3r0td0RRO599EdbffqddU7ctZtNytnWDStXOBHAouvpiMiw+Wj3ybDce1pA0X6HiQwZMPFiLhQhouU7CkNEsRc5ecYQQwEezHWfFfPeV8lw1jkE+2ceCyZfyZv6QGBU7oQcmgypQ0Hh8P4pQeh0Mjf+FhWBCQZY7+VeCcZaiTv0tr9vY8sfW9/0Mz13xJr77wjOHwoweESDCmsMCH0zKBoSSPR+vCNLhrDxbzlTpX+EAGMACsVw3ihD70zCvFA+7BMVzd//zhhaJguTEE9CvCMz4wCSEQp1ZxR1UfSFB5YU2en+eCbAhBZ1oe+P9nk7/TD0PJ4FhoAEjgGjjT7vQV2NNy9245MDiEvbGBCM0nYwSUEhg7JFGBA9Mxr67WDiINH5ESYYIgwEfRSACbnXivaVkNPEQCXFXS4Zp1gGHt4DkGwPEz+niPgWQBJbdWWLuZjBkJyvg0QKgE08DAEd0FMHxpTMjYovjF3F9BVUxtMvA3h4Qw3gn8Akeqp+H4mWXlFU1hdu/yyYcI605X+iuD8jr5gHGgXy/UBES1cGJhEOLoWXwyMx4hEyHMPTRN7UV2FLxoFj8Vwgzbw71JFQDNY28tjrygALxWBU0lMERhyguJP6M5ZkNBiJgMYZNV23raR2yoGSFoPp3j8bJsxH4kDJ6teASZ7YHxJ6auwpuikw9oUeR9YjSaVz4vncJ1Rq0yoqVGan98/cNyreg/tinIJCrv6gjOaxy812rXbE+6qsPPzWpgSTqvZZ5ZwoGiHnXi0jWC+3vNPq++ZtZvMju/3iB9v8ANfy9/bwk78qR/AnB0vnxD1r6F+25qE1ax+742A5eV0JT/dg2PxdJ8qkUq2X6d2AiTwVGfPdGDMZTa98T8CCNwJQ3lEYor3k0inW8jHEAEmlDHtFnt6X9ms/732potf6phhS5UtvTHC1Zki5aUVKEihhTt3SKQDE/bhvVjLyCif6rKQw0TowwRuJdSXUQZy61i3PTrnRpY+sfeS+nb3R431cRhc/8AYKjHFGGPt8/Bcx8ICEOfoV/hJD2DDQJu/tMNQ7ATivA9L/oygOoGC4GQplXJ4JQ1L0Clwnr3V4mFD/FDIhiVeib6SCnV7qNJOmiNMbGigMo4BKFia7GZXAexRTXCaYnAQ4GI6QYwwJmvsJJBRzOEyC0YgGBiOH8XEDomO05sJIF8LEjTHgKCYMDomZZyZGOx8mvEsBTGRweEfKyCkGmVj/0gYXPvYe8REaXBehkgWJwy5RfH5RFbwjSweJworpe7meWQzxTGji2jn+TF4cg6MGKDhAFDahAYaggFfr/3TYK+A7xh8bs7XSnJye3w4T4loCEyASWwA6SAQjr0d05SCydTsfKm+UznVwvUERMOEfF1F2v4MEBWg4MBR2/t8kN+BIx/0YYUtdWPJ/vZFFsh7/d/RIyeBQDHZW3gpeB94KxWD0XSEOABAG/gQisVEGRWAsaWYMUIAR/V74T7yDF3PpPX82TAq1U5hsAcrPgsmbDf6b5Ocmnk4Kk+R+O7k3hjDNYbNf52NQ2aYpcff4I1t78qMM4MdW2jhpzCOPQcPgHlJu+nxZt37Uqsj/md378I/2+NN/tCef/bM9//Jf7OHrv9rSw2+sb+aJ9NiGl17a6PIrue3M2qhEq5w3Hsmu42X23jEBRcs9J2laSrEX7613dOMWBDje0/739J4BKvoW7cNgurGnfoHrT8jDOVGudS0FK4CCYT58oU7w67aeifu2cO8Lb6nmMLmoiFgMJvrOPJAkMAG8DhQg4tsYYRkuReiDMh4YVQa7Y2h8RjSu7133CuqajiUbk2cyc/tTq2qbtZNXlFtTGB6TZ8Ic/YflWR2SR3JIUDyo9z0QYXIqwkTvpG9PW6zp+RgeZpscX/3EFh98Lxf/hcKWHBWGSu8pWMSiMX9HJXx6qTtMqBOJQEmg4jDRN4U6KwnPRAo98UNvYu89rO8kF4lRZBvjEIq4yIEGo5GFiRscrXOew0TGI2uw36Y8ox2le4QmvkERJrxXNDAYI3KrGBMqamkizHD6eCa0+uI+XJuWiXMfnkkOWNdvX5fD/gLpXK6hVdluhdceAZhzT97otzYZMGCCMcMzIUyxEQCFcPHiK0GCYlI821PX5Z00zvjYZsxLTnNyPFDA4UWPgCcBUPRUvAm9rt0noNAXhZaQPh88+31fFNtb4bKtdK4/C2Al68j/q+4XYeL7ku10v//zAJoYH4KIHwkwogCHwj8qQoV1/6fJtgMke56u5X9HuHCOV9wLBngreBlkKIALTY0p3qLzKkCh/xGV9IzbRvFX48A9b0p++mbimeje3MvjC8/W9tv0vlQUJlGFXsqWZsK/ECbFDP2/hyJMvP5ERjkn5Xi9yKbWrtWM28DMC7v99PfWP/3cK6s5Z+8JDC4jCTfaxXIGf7xjs3c+s7uv/mjPv/g/7YNv/t/24sv/Zvc//Isty6uZXHvtmtn43CZWP5YBH3Xjtfs4xr5KS2aoLLf3jgoq0u4T8i70XtSFHFCOCh3EPddyt/bv1nvvliHdJe3lnMQwYuy9r4PuuwegOEzKHCZ4LUcvNdj50m6v+5nb/Ewwoc5kSIAMMPFiHt071rHgpQWgJCBJoOsQwZgn4rpDiuzHFXl9uG4ZC2an65156cUUpS3zfv/q9iWbXH1tS/e+siaGJSlpsyO673HB5OgFgUEwOSyv5IiAgoDKAYrp9B37BZMDeqeDep9DGH0996DeA0hRhEZdzMqjH2xI8KLDIbCIkKCZL0VbUXTS9GIuYCLlQKLvknJecPBocnV9gAbjRUV9KPZC3ppIirnTQnEsZ4RYjwY4Z5wdGm68i6jg3OIKxhyARHmRiRI2/Q3IndK6h74Idb2bRtNcgBGHxOdc70HPPXw/RhtjzTGMWVZbnxWG7pAEEJ8plGE9dA8MIC2H2pQrxmCRO6bJKy1BsSFeVyLjiqH21p6yEcQViruoCwMkiKKukpoJv86LLP1/BIWGFeG/7Ab+wEzPfld2CLEe63CC16TzdM1ePZu+KzS5304cp78X9+a5DjFts+S9HRwJNEJckY2TsIEs+efEgRRExBe+2eOGYLAlbHNKgeHrASRvlP41nolXnuv/pvUsup7j7GdEBOID9SzUkVAZTy96ij6Zr4f6E/dKKIpMnu33kP7jwwTjnBj4f09FmHjdSWoYQ3GNF9lINFNkLgJ6bzN3OkNvhKE8wjUYJDr9NSrnTd8Nhii5+/JP9vDjf5T+we69+rNA9DtblZHD0M3f/Vpweq5ce68MfpW9c1ieiJa7EwGp2CCA+7vHoZwzUEFsk2P2XLMEULw1lwyhG0OO0fnRe2JT3BWKvCjmijC5UNZjnaP3HH6xAp7voIjKR9V1AxzgQXGf12VQJ5M8o1AYYK47rIh3QrmgM96Dd0yRc9lGVj6xruln3suZ3Fll64JNLH9kK/e/trb+dYfJoVN6Lz3jMAA5X2tHkaByVNuH9c6H8FAEFECyn7oc6SD/SnEHoBy91GKXK4bccyScx5Y+svO3mI9GCVzvdwiYKAxDhTvFaiyDR5It5kpB6eEZ6+gwVjnD5S3CMC6JAlCCkYi502L6N8PExfE3KwBF58qYAoFoCOhVjcEgB4roAIdB59wcMHjPYDwAShjPqQAm2h+VgkTHeZ7DBIiclBGWYtEg9wMmQCR2quPZeHrYA8KQ8CE89yht7ZJt2S1gYJQZUoUpn/tmX/owPDXda34uYR7/AYbdw9/DVd/DPyEsJSASweJA4R2Rhydg2SFMkv8cMg4KE56vuMAzs/Kx5BIFj5Y0DFCD1xL+fVC4JoR5FiBZxf/hykLjDaLYjOIpwJGtc/GWYNqm4yIttigKw/tg+H+XPBc8WLwYQMK5nsHQvw5QEyhQBhrFBEj+HWGCIlBk2BXgIcH++8o7xEnef8EhkgMJouy/vEXGb/VTQeGv7qEwx/gefWc4NzQrPn2928qaZ61t6J4NKtJP6vzZjS/lkdDP5A+69i9274O/ymv5s7yBr6yFDnsXW+3dI+WCSbl7QbSmOlHC5DoY4147caXDc8+xiCZtKOAQDKKCPoKF417sxHedrBZQKh0mucr3ShlJYNIoz6TH2ofv2sxtPJOP7FrtqD8LTwwPI0ACQEhesY+0L6sEJNEIY6BpycQ87IyGWt9724dNmRU8me+/rGXOTl7tEkzmbXzxA1u9/5V1Dt62c9fa7ZAgcVge0KEzQKXWjp2vs2Na4pkcFkgO0XBAxw5SGQ8c/btCgwm8KBoPXCzrtzHBfE0wmRTAgMtRhSmeC15MeFeBgxwhiTt5bxS/IavYz4T+O54LlmEoBEmUwyQxMjGXukVuQLbCxAGSVWLkfqn8vhh3vA3JDYEMSRzskWajFHVRLk4rII6l5+raaLjwOt4EkxQkKPM8FL2SCBXO5/lttOYSTChaOenPDgY2FvsQvkBkl+zMe9Iu2RdaRtHPZIgWgaufeTNh5pKhqJBrY9gTxg5uL0Jss6MYSwGMuhoGtWQ+d5o8UyzoIPHwBibAJkBjOwXPJP63IKASG2REzxQvgzqQOOou3xcGXAR2uo7/s0UhPLeIsInL5J/sSHoH6jbyPBMBIJXez4u/dJwiMKAB2Fm6tM+vy0Ioue9/YJjkFGAScn7/nnLjIOGBoCxIEIaHuZoZ8fb+B//gfSQuyO2mIyQGyOsNtGQcJ/bjxdR0rPhUuK2D97x/xfKD7+3Bh/9oTz75F3v0+p9lwL/wHtrA6L0jlfJKarz1DxNasb+mY9lnIyypHrPTypUduRiKYwAXz/VxnwQRmsrGPhjeZFbvQm6d+gRaYqUw0Tp1DUAFmIRpiLsFtDs2tfaJQPnabjZMeh0CkKSjn3tp/m1vh0gUXgAgpFiwqX/D8A7WnvzkMB1fee0jFd+on/Tl9OrHtv7ga+sd3bQr8pKOxeItYCKApF6J3pn5Zw5JeC3AhDqgPdQFCUChdRet75rt3M0eG557aWvMi7/2mV2vHtd9lQD0PYcEFKASYeJFeXxjolj344rfpG/dCUyiZ5IFyk4URr7Nh0e2GOZNyl5TqCxMMOqsAwZyovQtoZiJ1jxUgpMDxWBECETDhRHjuhQmft/EqHA8GrpEOe8EJUDRtREoHDuuXDD9G4AZLYfO3hrUO4UZ/ZhVkN7vDhRy87IdgOQ92Rj24dWOLL+2mU3FGWXofLBMZVwAtIe9/gMwocXUMd3zbNmQXa2ftdK2ZStvX7GbLUpPdTM+HhkNDNyLI+x1fTF4FFOASfLNyTKGM0vCEaNM8RGTkZHTp64ihEfyH6IIz1SEXxKGibLhmj4vVQL1bcT/4V2AASDxZSIvAkv2A5S06bHOT4vSMvfgfF/68SCHic59E1T+B8OkuLH/91LssV0oPJMqRcjp9S8dJhRzXSpXhNQ1R8htuvGWd6IIfVSG67Qi8gXlzK9UDNvVylFrYlpYJYLN53+0p4LJs8/+T5te+9yuy+DGepljAsnl8mH3akYWPvTzqZuplzt/lek7rynBXdHPpxhKoAgwwegHY0p/FMBCvcYhGcFDZyn+ASZUwEeYBKDQzJaOjaeudVhD77ob+an1z+R9zXlnO8AW+oqEIjZAWQiTLECiAMuJKwBxyKrb5uWdPbP1Jz/aB1/9q7388r/Znee/Vxh+6kO3TAtgtx9/Z5tPvrPR2SdW3jBm5290+DwzeCTBG9F74klRTyJwsDwIDOWl0JggwCQ0FQak1Hmcutpp/VNPbeXBdzYrYJfKOyJsDyiMAYnXr+g/0ZILkOfXkYXK/O1gAjQ8nmRgEgGS1RthomO5c2VgXAEAUYCCIpntlC2e2U4YHAyWG3MZcgeFriPHScXr4MJrbybKcByUmWNMIgBSY4UhS+7BMbbdyMiARMNTaMT82uQ6f6ZE5TtAYR+Gln4N9DPpm/nAi1QYap75OWilRUU7levej0Tpjibm1J3QMo5zJtc/t6WHP9qQ0gjnUWTq6VfpFBtCYweAxD0bB+/bwMLHNq50OyYNLL62hoF7dqlm0iFCWEaY0DpyJwp1ZSEs+V4PBy0BNusUGdH8mjoHZtdkzhiKjDgn/oMoh0QablICjjdrZzCJCv8rFHFGmESAFCoez6rweARKaJyhZxAHEngU6j8NTHz4kUR5x4h0MixZ8X7hHWWk9b5ZEZn3KzFVta04TDZf/MWncb1YOqicrrwRckIYW2Ci+zPH+FH99BNA5XKHnVGiKG+Ytt6xR7Z09xt7+Oqv9lSeycLGl1bTumAnZbzPyF2/Jg8E6Mxp/9qjH33ZJVe+rnPFKppn7WbdhGAz6MYSo0nxTlCAiAOFimmtHz5L5TWAAwqVtk8w2Q9ITlKBLZicqjGa4R4XnJhhcEI5+Nk7X1ll26KPnBsBGov7gITXKySV1F6/wDcXiP3MkX/ueqeVVA5Y68C6DPon9uCDP7luP/nBZjc+s9HFVzYpr+T2k+/t8Ud/stX7X1r74Lq+c8Ju1Azq+navLwEcXk8ijwSYvI9okSZFmOB18d0AluczqGfn6ANbvPe1zW/qmxTGeIwAO3od/i1S6BPDP1Y4KUwiTNwbS4DifVkAir7PAZKAJEIjB4Z8OVCKKP88GRVXPgiy3sebVHhdVhgcDFb0CjB2QIGiizikyszmd94ElLGaKO6IAMiDie7Ffhf3xZi5QQuGKmu4csqHCeLZ7ANmzKrImFE8m7HBbjTOWnXXqo8WTPFV6zDzoK/7LJXMoX5TEGH65O6JJz5LJ+O7UXRKUSqZAiacw3uhaIwmwwzz3640ytAhw/LA6G0PUGbv/+CjFV9rnFMYCUJ828+FCR4o35bAgDBwwysYM6cIQ5RQJ0XxIbCk6S0tpzDCDuUkLFh6eMYw87DeCUzCv80P7zfLYaLnZxU9jKhY7JUnisCSYrIUJhLnx6bf/+lhEiHCzy8Kk7znZt5TwrXOau8JYNJk1e2rNrX2hd1++kcZybt24Ua/HVakOK4fe0w5ziMyMId176Pad4z9MhInFUlPKed0tWzQGjuXbVSu+YqAcu/ZH2zpzpfWocRzTd7LrdoJa+xe9eKZzWe/tztPf2eTyx9bXceSlTVOW03bgtXretYvlvbLe1AEkcEDJqGHeyjmwqjuxwCfrfamtQc5DjykA4IJ2o9HI8N5EBAKZLSMYapQJibywfSUq4v9Q7woSIkVuQF+E0xkcKngPnJe3glzrcjDqGmdtpH5p4LjN7Zw5zMbF0QGZ57KY3kq7+uFrWr/00/+Yg8//IO+/Ym19K3Io5kWiPrsxGVBWR7K8Ut6T3rCCyrAZO+JshQmtFCjYQENBA5fYAiOMMJvc/+G4PiFgPKtw5J6pxQmgoO36HKY1DlEotw7EZQiUICNd4jUNT6AJjABJIBWYZPnaWhfPJYnh8Z2Kg6TX0MYJgyWw0RymEgYPYwbhs6n713+1FvyxEp4rnFjBTC2MW4BJm82aFmYROPLdRgnxoaiNRlFbfS2Zn4XKtdp+ksFO9PX9sr7Zwh6iok7Rh56acDEyqc+thtL5sZhDhriasjwNSgj0eGzeTInCpNsDcx/ZN2TL3xAyX6tz977wXoFmBvNC+7dpcVc+qZCaGynPXoOMIhw9m+63OneHcWHtT0bPqgiz6Uojx7oNK/FCEeIpOFCWOr5Hq4KI1cSxm/STmHiXsk2KjwPwEQoBpCE+pRY3+LHEqWtuVACju30nx8mGa+E56aeicOj0DPBADU7TCaVAMgVNfTctrMyuoeUSI8JGMdleI/JKBxVxD6mc6OOy9ickOdyrqTTbsrzaFbua2jqqc2vf2Zza5/Y4ORjq22ds8auZeufeGiLm5/bww/+aKsPv7beifvyVgbtclmvYDKnnPuGNXQv27WaER+QkqIsirRoZYUxpR+FeykCykEt6aPB8gDeiiACWFAACsVhtH5q9VYxeCYMP1ItL+j09V7dU99yUTkVfRetnoAJRUMxRw88Yi4/KkKF4rXDeq9j8nzKG8ZtYOqhg6R3XLnNzkWrap31eV4YlZmBMx99+Cd79slfbWL5lbUPrQugc3azdtjOXm9TGLfZlfJeeWQ9govAJnDsPV6mbwwNCfheWpiduqpc4Y1uLwoEtDWdSzap8KXhQ9vwPe806cV1ybsCROAHNLy1XFLElcqBEpa5hg40bgAm8maAhsIDmDgU2O9GJsQx914SvQ0ofzuYaCmDFYweueGQI8YYUAyDsZu5w8yGn7uxoy4Fw8g1Dgup0IhF+fECg1ZopDjPi3Oi0fRr6HfT4f0XYtPka4IJ089ShEVcZOpaJsdi+JR2wQWQMKX0gCBD3WO/MmSkvzi9AMPfMFwPPeXxYBhhmLHZRgWTtpFH3vu7SmqhnkaZwc6pF+6Z7AVwDhI8FFp5bQVHUcl+ZDuvkutnbKyyliVvGYfX1dB/1zrGBbTE+7rZNO/f7WGRQCMt5tLz2e9iX4TKdsoL/zcpB4n4X+I/KlTWY8kDSuqNZI75toCic3ai/dIbYRK1HVD+x8FECVoJO9vELzTny4hzeE4RUWdSWG9CEdcRBWZt57pg8rlyRj9avXJRp2l7La/Fi7QUoRwo+onHdS5L9h+RIaHo66gi69mSDnkhQw6P7uG7Njz9RGB5ZM3dS9Y5KO9g4bltPv3Onr7+ky3f/8w6htbkhXTYuesyju3TMsZ3rXPkjryTCRla5RjwBAQUX0peJIPR82IsiocyMAEu1ClIFH05UGQkaUpb071i42thLCuKGoAJHfqASZggCg8ltHqKwMAgp0ZYy2yxkBf3af+JC/Lmmmf8O2dWP5aXMqdv6bZj8h6YLIxWV50Cyu3H39v9l7+3gelHgs2clTaMCqIDdqm0227UDsljW7TW/lW7Wjkgr0f/5wQ9+PVdZ2v1fg0CRbuMyLiVNk15nx2AUt48ayOLH6TTEdP82jukSryr1/voO3h/90IyCkDBS0nqohR+YfBN6qWUwdA5DIUfgVIIkphJidsOlWz8y5MMvevXB4ob88RIsR63MQqU4dMslzoTZurD2NGiCyPlzYOT89+kCIcoN0wUecR9Oo7xix4JBo5zHCYyunEUW4rcfJwzxTMq4S9VjWrfpAA3ZbcaZ8JUyvJcaBl4tWbCrlaPeydY4ibeiHeKvdHnY3i1DNz14i8GhWTa2xuCBl7Y9YY5q5OBxztpkFd0uXbKDV2uyHArTNJhiwolO7VL6T6GJXONlOgbKNYiTPm20pZQX8IIA8AE0DhMkrAgnLKAiF5jBMrbVOx/ZPUmmERYFHobhcB4k/5TwyQk5gCOYtqSiJMEvqVIQkqHKE/khlWuHjCZSGCCi00l+/vHawSMJgfJcUWQY0BFP+Wotg/rpx7ien3TIT3vxIUWOy9jeqNq2GpaZgWQDRuafmydQ7etT6CYWn4pmHyrXPqfbOPp1zY098Aqmkftek2f4DUrTyVMM1zdOmMXbnV7cRJ1NYfxFhID77npk6E465CMLTDZTzGQjOFB4CIBFo7j1QCTanlFY6uf+FhWtcoZAhM6ipHr87msWcq7co8k45VEw8syBQnHMMonqu305TZr6Fiy0dnnNjr3wkoE0iO6fr+u4V4n5V01CGSz65/Y0r0vrbl3xa5U9NmpkhY7fbXVYVLTPuvFX5MrH/h3n7isXBz1P/qOY5ebvWnz9boxGZHb8kA2fSKyy5VDMkJT1jf91BbvfZPM09If3s29Ob1nAt/YWs378RB2WoYiLzqiBpAwmnMQ63FUhRxUPA7KyESIhLjO8fw4uq0UR0KfBxmVQikOFQPFToRRycIEI4YhwpDR0gjjx0B/DKvC9LCnrvf5ORg1DJwDQHIDhQHTviDWc4CIyxxMcvs5n2eyjaGKlcDk3CNMSmomtY+WZMoUKb75yMvy5AHLGUGCeXCAxUltHxN0KNoCID66s7ySo5fC6MIMHto79dznyGkfe2RlrYsOTTrdXdYzKjpWrZpJtuoVj270u1dCZ0Vv0KA0nrbY0j8pBhYfqVu27F2l+feOKVOm6wHwJXlV9CJnBOb20ccelufLRrzIi8YNjDJAHQrFiA4CibDysEn+T550/G2K0HiT4v+L/yUoHxZAwWGTiO3scRfeiSts+zVSHBcuajuQ/O1hkkl8Wf0SmBTm/N4KEsnBkSlqyFaQAo+s6H17RIFZk8Bk9dHvrEWJ4fTVHtuniHUIz4VzFLmOyPDSmuuw1g9xLTDR+3mrL0X8kzKw56/3KJc9ZJXKPbf0rSvXfdt6xu7bxNIHtv7oW3v44R/t7ssfbX7zU+uZuCdwLfnUwRR79U48sEoZ1XM3u9wriZ31vJUS2+4tCBTyPoAJ4KBIyHuMnwEgHAs6qOOMw1XduaiE/dqWH/1gjX0byvXJqOh+9BcJING3CCYk3OihcHwLTDDSCUze1/+/IG+gtX/DRudfWt/EIzsjj8FBo2s495hAVsVMjwuvbH7jM6vvXJDHosh3ukrHGu1azZAP8T+/yRz1X/msl2f13XgkRy81KcH2yhuZ9CKzoYUXNrL0yromHlqZvKEb9RPKJd63mTuf29D8C7tQ3q9/i/GXxyF4sO7FgpL30dH+MP5ZjQxHlVTpevdkhb0rT+gdLd85UW6/PVoqY6J90nuCGmCJ/Xt261+8d0LpQNqVQCcHnxo9I+PVeNwN3gtl8HsUT7KttaIiUH6uUpjovqGTHXE7bLOkb0ejcvHjis+Tgkl155qdksHmvOxAlpzL0gHCMq77NgYrHPemrUoD2T4U8VzuxbYPgomnK8NT33tHIPnMdaV6QvvCDIoUG8Z+OCwZisaHpdFx0mHM3LHEI2QfxxhCp6l/04u3ugWU6q41u6B9R6902hHphL7tXMWInaGVGJ637rlX1+7Wfbyzop6XwiQRQxPFvifA5F3FafTbo1X2zhF5/vqOc4LYLXl19X13HCQ1XeveSZcpeK/Ii+qafCaYvPbwZY730IkxhEcMG+R1MFnxXm9QKBp9u/wfyRaFJrxBERxRvl/AyR3LnpvsAxYoXqN1r1zXcVfclrKA8X0X31JnEvVvgUkWCDtRMSj8UuWDRFJkimLwuHzJkCpQyF1MrH1h60//ZK2DD+yscnL75O4CC+oYgAe5pcNSnBMjCnfcK7W1n5ZFp5XLOn+r364owlc0z8lQbljf1DObXv/MVh5+ZxvPf2e3n/1kC/e+8nlGBmaeCiyPBJU7XqRD0Q7gYOgVnzUxMeQhl822vBAMpsMk17fEResoQYVRhY/JKDOzJH1M1p/+ZK1Dd70Xf7gf9SO5b+H9vYWXjuWKg4IiUOI7AI3rteM+lhmDObbrvscFUt6Zc6izoD9KWcOkjcw+s+VkSBWG/N9zvFznNvt4XcPzz31ysRVBtm1k0y5XDSpRNtsZeWY3GydkENesf+6ZzWx+bvPybkaXP7A6eTjX6sesWZ7f+BrFDC/tYuWAEi9xskL/v0b/WWFDkdn5OtulsHkv0TsCyN+fLLe/Fzh+c6LMfnNc0pJ9rP/vh67bb4+VSmUuQLNXcNun++3Rfd/Ru7PvPQRwtM0SzwZg5UZbID6TBnSd4nbslV2oYoDZiUKxmYThIb5riTBmLGl2W6dc+ujKJzZ1+0ufIvf0zX4/tjtJnxFC2bSSL45lpPNz1yTbbjzlAWo9dOYL45HR6GN0+RPB7DMfFoXBMDk3e3/P2CVpkO2YdrEfcVbXcE6z36NznMErP7fGwbt2pXbCjl7tMsbRimNy7WH9PBJwE+2jPwvSej5I9A40wU+uxzsBJHgn78jWYfsYRp65VWg40DL8wKo65VnrPfCq6PFOs+UOvdPQ4seCyapy9m0etmSYs+EVwyjW83oFP++wrXQN4aF7vF2ClmCSHV3hzVJYyJvJerg55e6zTwDZu4326f/uk73M6n8amLxNIcIqFy03efr213b31T/K6D6QdzAg4xgg4dBQxAtKcvEYYkVSRD0MbeVZkqvK5fhb3G2/qIhHR0daHtFzfub257b04Dtbe/yjT6mLse8WTKo7Fu1S+YAdv0JOLdRbYNwx0O4VeNFNaN1FxXTshwJMwnwmLANYgAk5/Kr2ed3/Y8Hrd9Yxet8uVQz6fULfkvBN3qJL703xVygKUi7bO04mraB4D+130MhIUhxGD/eBWXkMCx948RNFag4e3vdcAMr1mlFveHD70XfWMbxp5wSJ3cDkSovVdS/bxMpHtv7kB4dq++hdu1o3YsevtjocqrsWrH3snvXNPnWYLD78xiZvf2IN/Ws6b1QGa9kG5bGMrX5oN5tksOTt7BIk9tEZskRepPT+hXqHyTunKuy38j5+q+V/ETT+j2O3XP/luMChfX+fHAc4QAMI7TvPbJeVMjAV2lcloCiOK4zRbvbrWcCEZ4YpBSgm0/V4MxSlJWDBwBcDCSoGip3IDY5EuiG9kf6i10+cpo6Cym5gMnv3G2sZuu9zhNDhz9Oa3ol4z7lputE+V0xDun82ncRz0n3+Dsm52iajlgcTPXti7XOBf8roeJh3Lefr+TGDx3a8F7bD7YzsDe8aOzMOzH3g9yyjefuNXuWMqVgPnsUeloqThUrhomcUgwkDQLIdPRNvzKNt3o0ZH2k51jJ0Txmdh/JQ5jwM6TDJO54vH7LOCQa0fO3fyzc6pJN/4CKM9N3+n5DSRvY9thPvF4DyFhF2vxZMkvvsQ0UgEvXLYZJp1fWfFiaCArOgMbb/zMY3DpMWPJNbgomOx6IwRqBlGXNTYR9lxfo5Ssh8twNF3+L1Mdxb8pFrFQEpE76oCEhfjzgcy/TtL2zuzlc+LEvPxGMrb5mVwe11mBxJBy8MLZO8mEvGKQsT6kUCTABJTu656PgRwaRCHsCYjPbt57/3CasuVQ7pvXSvBCZ8C+9JsYJPFlUAk2gYfVwziWuZA72uZ1VewSvrn33uPd6Zh59zwzncu8GuVg1b39gDuytPrH9Kz67oF0wq7ERJm7UMbOj7P3VPjYExO8ep2JySV9JlJYIKHkj72H0l2Ic2fedzW378vQzjl8olbjpsAEjX5APt+9zq++T13OxUPCyXR1JrZ0q7pG47dFlGW+FBcRZFWQ4OGf//Iu8DAZBd55Qj1Tl7BZATuselmiG7Uj9il2qH7Hxlnx26pHDROQiI7FFYs2QqAZ7HNAL7BBuf9AyYnNA5WoZwC+mgGEhQMVC8XaEoBEiRzkh/pMeY5jDO1EuQW8b4zt//zltOXa4acw/BvQgMeSLSQDR42XSYwoSl5KDJAoF9mfSWhUkEGV4RrbjI5XPv7P38muQduEd8PvJvknfCOp0UGWZlcOFDb1Z8Wd7CQaUnDCmG3w2w4ttu3c+VhQnnuLSuY0GJsWa/llyPZ8LysMKN4sDzyvzRQKBJXhDAaB6857NvMrwL38n74i0xhhjAbOi/42HujXwURllI8q2xvjfC4m36W8AkdN7cziuRdggTVAiUHcEE/c8AE8o7Gaqb1i+bwGTooZ0tHfSI7sVggEQJJYy9FAxwOkYQMCGy8M1JZPL7klD8XMqYw/lHlajCmFZTVt+9LoA89eaQo4sfWe/kE6tuX/QK5tPXQxNYesMjKrQpZtoCk7N4DME7YV+UNylOYFLWOmPDSx/Y7Re/t+6pJ0oUI3o/Era8E93bIz3hBkTc+FH2r/8pY5gO0EkuO8lp08HveEm7Etod3fdDv+d5eVPsT8HDvaXLFQPWPXLP7r/4g43Ki6DZM731T1/vtE5Bhr4ic5tfeiV65/h9eSPzPpnYtfpRh0nryKY1D92RUfrM1uRZLT74Vvvu6d/QA3pQxzZkLL+yDl17sapf71kp46Pn1gzoOwfcQ9knCFBP8i7ehAz+u4mn8q7O3Q0kBIs9dKC80mzXBKjGodvWNLJh9QMrVte/bBf0PkdLFE54KgLRHl0fZsgURJiH5ZzCXmKKAXrrM5IzCsP7B48hjFy7VcVh8SYF4+fFIUozpDXSImky5IqV6VB8o5iLYdzJNS/4UP2v7FrdlBu8aOiiIWe9WDqMRj9NV7q3x+1kf/ZYSEfARJ46MOkKMJlWRokcvcNE4eBpLrnOMy9JOmE79ax0PH4bSzyBcmXABuc/8PlOzpQOpBDIarcDRcqDSQRIEAY4ux2vZf8hPedcxbDdkBdUJRADiJ7p54rfzxyOTOfsw8DofNIyPfkBHNNHAxuKv8L7h+PI05bu7V5k8qydKL7rW8X9fw5MikEkFWklURGAFOp/Cph4RFdA71QRJlVUwK99KaP7Fx9biMo3IgOJM4LDIwnbmX3IE0iS0Nwb0fF4jMQVr6EyMbaZL6keFzyWvbljj3I/NHFldsKKljkZ4WF5Mp1e78DAjA4TDLSA8maYUMxEBTgwYTKpJrvVPKVI/1Lf9QfrnXlmV2pG9d2Et67XfZlnPYyYGyCyHUwQsDlwvtFOCnYYdWDSzjzs1zr9njE3zjoezIXSXmsfuG335JlMyTsqbZzwdz1/q8f6pp84TJiNsW1o0zrG7lpj37JdlUdwXTCp6V6yxoF1q+1ZsYn1T21dntXyo+8FkE3lHjvlOXZbrc6Z2/zc+uT1XJc3w0RbzIp5s2FUwB6xU9dpmcK36jv03L1n9X7nBDs6SV5q9KKwIyWttv9igx3TudW6X//Cc+tffG5dMw+tZ/aRVXbO2fmKXvdQgAkTcR3S+Ye1jYDXgfP6B2cDUPg+bylGcZc8O5/LowhIUHFgvEnBAObBxFsfCSZaJ/4TL5mjHgPMoInAhCUdB8lZRyMXPOcAFOKup0GAkU1HxOtku1AxncV17kMcJ77TBB2YMMYWXgXFbmS20nSX3NvfQe/CPTwjpiX3ieewDYj4FrwShqc/eb3Xi6VQaoAFEZfich5IiNtZ8b6JCMPdyT2Yc+aUYHGrZd69EaYPptUYFf5dSpu3BBi+Ib4bHh5Fb4QrwOS9CFsPCx0nDABPDGv2RaAUKv2GjH4+TN4uIFGsMQfKgwrnym7tzdN/UpjEHM2vpdgEkLH+wxAU31p976adKx1KI0QEA2K7cJ8nTsmLv3Qs1KWEOpOg3D7qX6hPOXW1265UjXldSp1ychR9MfUtHstNeS60umKEYZrt+nSziWeCoQIg+TARSGTso+iw6PUWF5rsRsOk9c89d5j0yQMoqR3TuxKWESZhPQsStB1MDuqeZ28JEoIIcKrtofKR1j0BUFHA5IwgU9c+b6v3v7bp1Y+sqnVa31Nnl8r7rXvioQ0LcoxqTL1Oi8BByzZaeTG9cFX7nGCxLEMy59BaffqTDOO3yvUuy+MiA9BstwSn8aVXNjD92Kpapr3JMR0hGbalomXSLpb1eGU/45QdILyQ1o8LIOfKeuW9yAu82SXj0GjHdV1V54J1TNy39ol71jS8bg1Da/JU9D90r1M3O93ToXEAxWyXqga03qkcKfGBsJE3AkwoepQAq0/kprhdDCSoODDepAxMJNKdp0mlT9ZJR8RDyu8xdv1zr7yYa3jpY98m90wa4rwIg2IqTHOuCJxkO16f3ebZESZxnn5GXWCgR39mfAbXJucjv0/m/hFMHMObB0j0mG9WGjl5IweTrJfhcmgITtSHJHUiVLL7RFqSn6P7u/Qs9+a0jsfGVMG0gKNuZvr2l7Zw7zsbX/nUWgSXSxUjnn69BajuQyu06w3TDhPqpOjZzxD6fAfv7nZBaTfaj/jdXiGv56H0PaRfDBM9K/Uq3iKgURifio4BB3SkPYm2gwn6TwCTJEL+SiLSHrvS5cM+MEF/5wRzcsx7u3yfIY2I8RbFiM/SK+ajdMyV7I+tv7zll/ZTOQ80rtVMWHnzvIvOWZfKh+309R73YriWynJvYYVBF0zI/QKSfJjIgEcJPFxzUF7E1bpxn96WnP3A/Eu7Vj+hdyUx6VotMfo7hQninqdv9sjwLnm9yXXBCsAAE69XYZmsn7jcauV63hwThsnoM5QKsyxeKO22OnkBTX3r3tT3ugBX17XoHRhLG8a0PWKVbbNW07loFW3z/t6LD7+zGXkybDOzImOPXasetiF5OCMzT61RILh4o8NOX27yQSVr2mesVB7Omav0C1LukzCiWbW8FBoC0Oy4umPeLggqdI5kbvoSPZf6l4aBVavq1v/omLHqniXBZMrOlfc5UPD0avSelbqWBgOn9ExgQv3JnlO06qK4izBDSguK28VAggoT99uVgwlpIcKE9EmaJO2xn3qGktoJryuZ3fzGc9gRJqQfzomGPJXiZUwTaTpLzkWF6TSmQ99OPBq2SQ/AhJZcTK1MERG5dmxCes/kfJ6JWOfenEMfHrZjmgKMDBBJkRNG+8ytAQ+DXRQh8nyk87J6XyAJkiGP0v4IE3/nRAwkea50UP99w4YFhxl5Ggt3v7XVRz/ZkMDCaOJk/LyDs84HKAATmAwvfuzDFDHemMMkCRPCwGdcLIBJNjzRrweTt6sYTND2MNH50tth0vq/YBJFm3DalDN5zNXaKe/dSqsNyp2ju5pKAVtMOZgEOTgkQMIc5ORqvOWUnkf/jjCarXLJ+h6OnVJiO186YOcElhN06FJOCeGZcH4eTE5mYEIuOIUJ65wDTIJnACwo1uqefOx1DoMLr9z4M1KuV5Ynhp96jiww0HYwwZuhWOtS1bDXv5yRl8K+3BhXifQOR/GMqoZsSiAZX3hh1Xgm52r1va0C6LCgMSqw9NlFqVJGurFr3mrbZ30UgCp5JLT4qu+VxyiYzN79yibWPrGK1jl9u8JO33xFBr537J6NzT61dkGgpFSeiO5fWjssuMxbgwz+pZvddvyCMg3UYxwr93HMSioGrKl7xTqGNq2kfMCOKDxoan2+tNe9k7q+ZavSu1xvGrdbrVNWUjdqZ+Xl4MVU6b5Ng7dlfFYElkn3VPB2dp2ocIXe9IQbYfi3hQlpLQyCGNLlbqVLiouIi7Q2ovhl8vYXXndyq3kuVCAn0CDOupfNkjiZ7I8Gz9NZxvgVptP0OB5FWt8Ritmo/Acmiw9/sLre295BkbCI12bhg1jnHpwTZ1eMxyhSot6Foic6K9K/hKLp6Jm4UdX7pyBBCUyYzz3KvZPMt/G9gOG40vk1eSX0ql9++KPdfvZHH1JpTaJO83rdlGfq4vhg3iBH6dphIo8P76sQJmnY8mzeJ/kWlIYB35zoPzJM3uSdABKWO4dJ0qLrPy9MFOkUYPQUZdIYWnPg9hKJgUlW2wFlC0wUiWKlvc8RrvUwnWwQYPBZEo/T+odmvI0+8RP1I7EpcLa+xFt1JUDxyl0ZLPdKlMsGLGF4kBqv8PWe3hkP4bKMfufEI4cJxUU3m6YVyWWUuMaNPuGfDxK0HUwA1BF5HOjwJX1/4pXg3cTnhvVa78V/vaLfJhdf2Pj8c6uSYfZ535WTP1lCUV+bHdc9Tl2RwZBXAEza5BUAlNqOBe+w2Dn+UDlAih4+t9Glj6ymY9G9EkZHPn+9QxBZs3HBpGdow25WDthRhcfNqgFrlUfRObBuNyoH7YyecYgK8SNltv94hd0SBLuH7trQpIxFxbAdJcz1bXSUBBbNQ7etUe9xvWHUW5ZRJHacd5Vu4tHIi6pon/P+LgDmgL6TZsG7ko6Oe06SPiSlCx/rqQhIULHE/WblYELcxQCTFjHAruSZpKdT13vdkNPfA8+E6ZQxeNG4EWc97iYGz2GSGNs0nWW2C9NpPM4+h6YEJLgffTLG1z6zZeXuqcjmuX48uTZcH74Bse331/cEKOobAJREuqO+x8fz0v+iIQH1KNRFYVDd28goBQrflFF8Ds+ltSUlBHj9jAjBvEIzG1/Zw4//2Z599t+MeYluP/2DdY4+8jHCODedB4lr9Y3X6wNM5u99l4OJnrETxTD4jwgTtv3cFCYRKFthErVjmCCA8p8RJgEkJKYWJQTtU+A6OAAAyoAEvQkmESRBudyel7PqWQAjwoT6Dx8aPRGgoNUW5wATzmESq1yzYCKxDCgGvRAmp2QkMZSZprwY/Vh3cbFiSDm6Bw6T0ZWPZVQY4VQRCZgk52RhEbUdTIAF1wOkCI7s8Si8HQaFvCJvYWzumXsmtTLAFHPRF+bQOaZC1rfqHoelkoo+a+icta6RDWvoknfQuWjNA7e96fGIIIhXwnhcjb1rdvZGl9+b+eQrGsatd2TTuuQtVMi4n7zQYDcEsAY9C2+lqnHSLt/qsRN63wPHK+2gwq+sdtz6lcsdn3sl8Iz6CNCMOUYPfJonNw+tK1d/22FC3ciJa236l0C6Rh5ri52+0SmPpMtOCmY0cvCe9plwcq8EkLgEk1OCTYTH6dzUsoUJ++3KhwnGm7TmzylIj3jWDNVOvcnQwkcOk5PXe9zYe9wnnmrdYaLv9zSh++els8x2YTqNx9mXhQn3BSYMLrqi3H3TwF1/Lsf9ndPrwzfEfX7/BI58A3aE7yB9UZ/BAJE0xa2g2OlGb2qIC+VGVumGZbx/3nNTKJBBa/KhXGrlSS0KCs8+/2/28ff/H/vg6//b7r78i3WPP/EiaMaxAyJM4U03AIqwaM1V1DNBBc9OxT2S9/BvTvS/YFIQef+jwySAY6uCS8o4N9qWSFzZoq2fDRPukcj7m+idvawV6T3C7H8CA4krUazj8E6DWqeVi1eOy8i6AAmGn3L4PJgAI1oNhc5yqTKGjWa7tLxaF0zGZZDL2xjhVBFE5zhw3PjlAwNFkBQ7lgXItudI1Oecu9ZpfeMPBJOX1ti97ONv+ZAwendA4kPF6PoLNzutqnncWvtX5JXM+bAytV1L1iWvCqAMzL203umnAsyGXZa3wdhdRwUTirpaaEbcv2YVjRN28lKTXbrVbWV1o1bThocjD6Jm2E7Rakvhtl/PLmucsqGZ5z5T4y0ZqqNkJk5UCeD1dqVGIOpbkvHakOGaskuVfXb8igywAPjesVKFdYW+Tf9AHpD3K5GoH+E/EfZhiBWFR5oGAjjePUHHOMaACp6KJ2aBxVWQwLdXAUxYl3FzY54Y35AW5RVeavfiIXLzDPkeYRLBkU0PhUYuTWfZ/TLAsXgq77j2ZdMx965sX7bx1U8dJtRzMMMi75m9XwoT7fNrCS+dE7/BJdtCeqSPDFCichxv60L5sK6VIdR13hkwowgUv3fm/oRRDBuKrOKcPudu9lt9z20f+v7FF/+XffLj/9eB8kheysztL32I/Gu1E6FBjPfTCd+OhxQr4OnUSBFi/Bc8LxtW6T/KU+6dd9qZMSr2lQkKQCiqM0rnijexon07/S+Y/Ey9GSb5yoNFBiwo71yHCKI+JIgIGuUwIReUyKfKVSQqpnA8fGPIsYRcf54SmERjTD0JTVD3yBDuTrSLpfbFnPLZUhnbobteAT95+zOr7Fj0IqosAIrBIEJiy7HM/kLlnSfhMVEJ39J320bmXlhz77q38Irjd/mc7QlMTpe02LXqfi8KK20cVwIesZsNEzIeTKq04f1amgc3vdPizaYpOyeP5+Q1+u10B/B0LnjT45OCxhntv1zWZzflqdR2L9qtlklBtVcQpdlmgyAx597OgnKVTKF8nHGVFG77TpXrfq1W3Tlt7SPrMjLzVqJ3OlEimAgg7x65abuO3bL3jt6ydw7fsN8eumHvHClVeFcqLmFAqFOiApx5PZgjvN0OygCRON85Xmu/PVpj7x6XUWMOEiXw6KHs3EvJwcRzpoovnn4Uf9xAZdIfnjW9z8nR0x8CL+W0cvSeflBMG1r3OFeQDuN5cbtQ0aim+4i7yfXlrYtevLb8+CfrGHssL67f3zE9V4owYT1rhH1d3xBtC+kMeNR2rztMqAeiQyH9Tzg/GObcd/MeMb3H+7Ofe1G/5PVKCVBIrxfLhpRBuesV7s8+/1f74Jv/x6FCUdf6E6UZ5qMffqA4sWJX6LhYEppXp54JFfACJo0bsIPYRv8WfUcM0whGXyYK76335xsQ4QAkeF/gEvcXk5+D3h5vYtwCLFlobKe/KUz+M1XAbweUrCJc8oCSiP3puUlkDe31cwAJEMkBxCGhSLMjkSB1bTAYhEsWJIQpxjypgE8q3wNMSCRBwGQX9TEYdxntM7f63AgDk5nNL40h6Y9eYUgIjm8Pgm2VuaaYsucCuSPnm6y6dd56Jx5bU8+anWe4eH0L/WZ8mBh9JwNaHr1Qb2evtdjl8m5v7XXG+5L0WEnNqBLxiLdKw6tqG71vDf3rViqA0HGR/iZXtLwuT+Ra7bCdud4hgDXrXh12tWbIO0LSMovmvRerBrz+g0p9Br9cefSDz51xsXTIDp9XLu9kmZ261mSlTaPW1L8sI7NqtxrH7PT1docJ44rhmTAkzLtHBBSB5N2jZUoTeCsULbXbxcphN+I05mBq2VM3+n2EVTyS3x5jMEFgEhJ4FiY7A0oGJixj+lHcceOUSX9kfOilzayG1JkwVheV8sTdNB1JMV393HS4rRSHaX1Fy6ilRz96D3JGk9gpTLie9WhbyKgxFzzeDsVc1J1QwQ+guD773dzH06Sn4ySN6n5+f87R/eKwR8CEinWKsZhZlQr3x6//qz344B8dLEv3v7fVhz/aspazG1/ZmODYKpBRf0PrL0bgnlr/whZ1vH1Unokg40WbekZusM8dSN8fQBI9DSnZ93a9Pc78L5i8Qf+ZYeIRUNcSUViGkWdJJIRp8BaAR4AJrUtIHPwL/RP+SxS5I8/91NppGW+mS11//ge55F9brQz6sRIqMOW9CEYs43oWBNsqA443yc87zqyQDXajdtya5Z3Qw/+c3oe6HzwTH28sgcnBM9UCT02YefFSox325rpNduJqh3tSx7WkMUHDwG1rH79vjYO3HSgXKvrtzM0uGSxaxHV7xf6hczLsuv6c9t1sGrey9mnvfFjVteBNehlxmLnqbz/5ybrHHllpw7TeS54O/UhutAtCg1bdMWcdI5tWI4+HfjF0AnWvUOHEeGW7T1QqrBlWBU+wxuOE56BltDvHn1rH+DNB754gOGNHr/Z4At1F3UnilcSE/qvABCn+kPZIi6xTLMu8IXgmkzJ6zYP3BLdRj99pOpJiuvq56XCLEqONPaBymroaWnPRg/xc2eCWe+fBJD6be2jJN8RGBZxD8RxFdoAE74Q6Cow6DWU4zncT5wth4kDhO3VfAEIa8zSpZ7KkyS+V7yMLH9nmiz8LJP9gC5vfWJfCrKV/03rGn9jYwsc2e/tLW3nwg80oHPumnltT3x3rm36hzMhPtv70D9al8xguiToV0moo3g7h62HM8wvFdyeKcCjcfrv+PWACSIrD5K2tubz1VlaFINEPjgBx/f8bTApFhMsoRMIAlC3Sfq5J75lElhh5UimyOET0XW8q2ioUEZ6wIKJ4xErCJpf7IpxpvRU9ExmOCBMlJv5N/EfxX9CqhxY1a8/+4JWF9TLqJ64y8ikAQVVKAL8+TGjRBPiACVMR+zz39ZM+uVWESdqrX+czlP6BU+WCSpUMdxgShmHk6ddCRT8V/qdudFtZ66zDpG3ivtX0LnvfEFpUnbzWJq+i1Y5dbvR70GqM4imGZ7neNOZNfZsG12VUGcH5sQyDYPL4RxucfmY1ghyDUt6sH7eS6iHlVkesQqDqGL3nfWEYIZnpgr1xBI0i9C6hf04i/Wvq3Zj7gnlEhhc/tSGpc+KFgLdsp24N2kF5J7kybC0zFfG/DCbBSMU44vEk+eekE4q5qLhmtF2KYhiKhG08Fq5L0xH3ycS1bFp7o3SP9D7xHoqn2ArGsQIi8/e/8/4heETx3PRaLdPnazs+m2WECbaFc2hMwD0BIj3h3TvpWnWPhe8EIh7n9XwgFdO2jz2n+4e0GCDCdiySviAPAzDM0ZJLHsnmsz/Z6PxHVinP6ooyBrfqpqyha8369byFO9/Y2sOf3FOZdo/kO3vw0T95RX2vjp+kB7zCnnQc+obxDsSTJJyLiKLKn++NZPU3ggkAkd4GEvqZsF4UJu+ixBNJIZIBiRsqvJIMPCJU4rbrPyhMtlMhULaVIgjn570TCSOJrPnSNyWAyKoQIFlxnLCgXDTMjUACVaTR/hC2hDNl+9V6F9xpjHYs4kpgov+FdxL/BXNb1PVu2JpyUCTuRoGF4VByMIn69WHCKMLA5NSVdrtUNmDnb/UFoyxvi74wESbeR0Yw2XeSKXsrdEzApKUawNQ5eGc0TMBDuVg15N5Ji7wGRg5mBGGKuhht+KhAcvgi9w0jJ1Ohfup6m4/TVd42LaiuWotg0j3+0MaWPrSle9/4vPzMz18p2DX2rlp127zANyPALFjn6AMflYB6lTOCMkbi+OUO71B6Rh7WCRkQPADiBSMpMF1u89BDG1pgfvJPrG3kmd1qXrIzt4bs0KWOkGCTRM14XYXyqXc94W8njE7QtjBR2uN9aNoOPOi4uPTwR+udeeG5eeoaPL6SlpL4TzyO98iL22+S7uH3Se5BuuR6MqDAA4+IDpMpTHRN9lnZa9P7JffmG9ymAAcdBxiMjUVLLvqa0KgAb/tq7YT/Awx2qAvR+bqPZ+i0L9ZhRm8kgoTpJJibiFkd8T7W5GE8+fifbV3LnrHHAsmIz190TGF44eaA4sO89csjASjUo9BsmDqVWLcyMPPSmxjHZ8f5Wch8ehcB6lv1vGwJB6Ilqfd/IQyk6Jm8DSx+jtJViAvECwGgiBwoxC3OIe7pm3Yih0kBPLLKDvTIdh5MogeyBSQZiPyPgsnfAh7/FuW9nyKPvz8Q2IHeBhSHCfIw0b0FkkKY0J8B488YUbFF0XYw2X2iTka2x2q7b9uqEsGCYNI0yNhWtPv/28OE4qADAgr1Il7ZHou1qDPR0mHiosgOj6tC1wATQIIwJkk80JJhW+gwScfL0pYZLSd8aBNGDD7KHPLyaPYzpwueTSIAc+YmRWQDPvxKZduc1fesWNfYAxtf+siGZl94A4HaDhmqobvWIbUO3LG2QWa+fGoD0y+Ve71rJfI6DivxMDVBaZPuIUBT9EKHvP2CwP4zLXrOkFV33naItAw9lfFjMqVJO8b860qge5i6VQn7fYa4IIEDEO1LpftkZ9zbXtyH82NcCYppD+8aaESYrDyhw+qHPiwJfTTckHuY5uJ0vEde/N6B4vXRw8CWnLnZ72NcMWowhh+YxHTMuf4c3iF5vh9L7lWYafN9GP9LypBUMWbbmrcQoy6IIeLPy7ug7iPWhUSD7s3xdR0QYR8gcSnMmdSOSe7KGmZsZO4Du/fizw6TRcGvWZ4KY+ft17126VuY0+ikPCOGPWobum+jix97fcqTT/7FXn713907GVt+7UMjMX4X/coAOUvemaI4l44R9oh/AyBjg54wR4y+V9oRTJJz39Y02IurFF8iSIoNAFmonzsEPfveCpPtgPI/2jPZqTyS/hwpghW7T6GKvXsWGHz7diLCe6QvFIlAirAJ91LEOannuaEpDhOW3uMa74Rj+jf+jyT/N0oIx0q6fYa4FcGEMuxmGUuGQwEeeDYMgoj+VjDxlluSeyOJR5IuE3mP9nOs8970Iq+U+E4BU2HO/2FASvq3ABTqT4AK9SnHS9qUQAWS87xfpf6jvJLz1GHg3YTmvscFFHrdM4PlxfJ+gWHYKpmrf+yhYPHM63PKG2estIFijRVrH7znRRsTy5/a9PqX8mSe2fXaaRmjFjt7Y8CqO1a9qIXRcU/J89vLf5KOX+kV4Oa1f1O6K9gs27nSURkWBjok96z/CniACV5IApM9nmlQ/AMmO1EClMJ46HFMcQWYYKwYUoUKcGBCJTyV2Bg1zovhirLxOsbztymbyYvbLIl/1HFQ4T+28ql7EowoEf4h7x2elQeTRBz33HtiZP1ZOg+Ry6fIlkEXG/s33fNplOHHyDNnPMMTxeKsbFFW9Ex8n3RAYc3ypMKhvnPVZte/sEcf/pPdf/lXG1v4yL2QY4IA9yNt7j1BkWyjA4YOjOXyUlsUP6iUv//hP3gTYsbxqurgXw96RTzFcgCEFl40GT6pa+mHwno87lARdOK38u2EQQRKMYhE/Y+CSSFIfhFMyPGGMvl8mAQD9ivDJIk86bYUci4hsqbbCkxXciwrPycef5sy16TP3kbF3jtCJLSTD7B4m3Ig0Xen0jsrou/LKBqpvToewptyZOo4qvTOGH+BxA0vRjj8iwh9Zn3bBUyudFtV55otP/6dw6Rl+J4xBEqEw74zQSks3qZCaGynDExQOnNjhEoCFPc+AAq92vVNPiwJc7LzTXpeNHzAhHoTeuCzDGJsJRkHOkKezXklBwWT4JlUK9daZ0cFlGMXZewvNdlJwee0QHS1asSaetflfTyx5t7bdrN23M7f6LXS+kkvJ6e4Y3zpE5tc+czah+kJPe7/6NTVXqsVnOkI2CBjBkyCR0jP/na7UDEug7ckr2TNSpsDTJhbm4zBruP6/4JGnB88CxO0BRrbCZgUi4/EQy3JyWOkqGfAmNNEl4EXqWfAyJFeuT6mAcI33sPTwQ7k6SZJP54+kv3EQYwmQ+BTWd4sw0vdBu+UGswkPcXnI457fWVaBMR3Ei4hE8W7kdOnzwmDR9KyqkNAYWDUG3VToRiSa3Uv90CiIlAUvi6lJYq5zl3vkxd631Yf/CCv5L/a2sMfffsKgzoKXN5RUe+4R/aOVmAUW+EBMdwRAz+2jzz0CvjHn/xX23j+J2vVtbSeA6QODQmvlW0geEpL1iNYAE0eUHT/6JFtB5NQvKXjUjqETAYehfo1YVIMJDuGSSguCUUnDhKHSVhuCxP/8T8fJrF9eqokcsYI6xExCeh0WwHpKjhWGLndfU7us0UF57Je7P3eKBKwvnmn2goSPTcKQ5OI9QgT5u2OMKG5LZ0W4/wZMRdfCJNdWt91vFY5URL2qi0p4gOT1jyYBG+EZq15wHiTCqGB5BkVE73yt8CE7QQmPpaYQOJNn8/qGwW1d08wu2GV7daz9uh4MHwCzVkZAok6FFeEEF6NvLQDggkV94cukPDD+mF5K4wFdkRLet4fOQ9UmnwIlwu3+qy2fVEeyBMv5rpWPWrHL7bYxVv9XvFKrrVr5JF1jjyWF7MsAPXZ7mN1dkJwBib0o6AoB+NA+nnnCF5Rk4yGPJ+aaStrWbGK9jW7WMm0tXgDASZAJUIBkERl979duuYNcZV4jXG6WDnisywyDD2TOOEtYMRIw35eTAOK+/HaNC28RZ6mMtfGdESGCmBRBEilP/1DqO+IaZZn+rlSNi3G425Uk/MQ8T7aHPZThMaEW/XKAHTL64pAuVY7qYxClxt8PBI8FLx9YIInsk9p4X1lrvbrfkfldZRUjNrwzCu7KxA8/uifbXr1M6uS13FK9+B8vBMgtEc2b7dsoZcYKE0BFmDDoKwMwUJxF0VdPfJUeS965wORFCTajqKfT1zPAsWLvPCsku/eFiYU+eq4S+fu03sUg0jUrwWT7UCCtsAkAEUqAImDopgiPLICIApwB0oRmGQjYjHFyJMVgbtjxesUAXheIdiy0AjnaV374rvlJYzkvCj2bastMJHxS5WFR6H0HAxIoRKQ5MNERlXhDjBCBXyACcU4FO0EmPC/AL5gkmYE6AndqVzysi0qB7bkMLlvZ2VIAUOEwRZgvElZiEje49vrbLaKlmbFYBIFxADJXgmQ7NL93tP9duGVsF/QCH1t+CeI9aAAE90bCYqMBnwQoEjMi888+ADk/ZMVdlDQPSzoMHrwSYHk+IVm5Uy7raZtwXvCt/Vv2NWKYZ1X740Fziqhn5cBvFw+rJzqqEDSq/s1uWGhCSg9punhTVievtGj8A7zhhOfjl3utIvlo4IJoypTSTztQAcCeIoUPUYvJHokESgOCryOt8lhQtxTGBWTjpEezpUNeI/xqY0vfMBHKq0xYsSR0KhB71EQx7PxfqcqvPYwHkTNuDGdbakM9AkBl3oBr3DWMgcTjGcQMAEkPhoFQNE2Bpb6Qs8YSdwbA3xRngHFTR3yDmiqSz+Ruu41uyx44jkAE9IYxt8r36Vdgj1AoZiLOpAKwY4mvw8//Ee79+Iv1jvx1L0SKua5/tjlDsWtABMEnPBSdiVgYT6iCcUBYPLw9T9br97DYSIvhAwGYp259xEQZMRj+sewzbHjiktez6LwYoTy+O1ehLmNQtGWwkw27/1/B5i8CSSuYjBBRWEiA+ZiPSs3bInBjlJE3ilMstAopqLASBQiXb5S74RA1/NSmCTvlb5H9l0UQfLeLdn+WQImybMASYTJ+4icUEZs53skihwuIr9+utb3niDS6v2l3fSWZj1+h9+fyEx/h6C9pyq0T0u8gSSyv3c06J3DNLNttbLmBR+QblkwaR95YOe8R3I+TEInK8KKfysYcL/M8bie7ovrQAwAeGfJIECCZwJM8E7ypGuKwQRPBJgAkt2Cg8MkUTGQxPoWmhXTT+WArj8osKD9uschHTtBhb2ryY6ea7BDOueQnntI33mmpMNqWudtlGFaxh7ardoJ23O0wut3Dp9TzlReygmB5eilkNPln+5V+DJpWV33qo0tf2xNA3fstKC063iFPJMy/95jymlerhz1epWmgXtW2b5iFwQXKuABCUYRTxMoZGESAKO4gMF4mxRPPR4r3hWK/0r408n1pN6tvG3BRlde2/SdL611RPC72SvPlXijf+CeHnE//Hvis6dNPSObFtnnRSwZkTvOtkSK4tiBCy127CpTJw/a2bJBOyyDieEjDOJYeIzW/X4i1tlPi7gDMk4sA1BkBL0oUM/km/VeGFzqHOjTUyPvkfGzBmZeyEuRB6lvvVA64EVUeBURKNG7eF/b7D99tcfqu9bs9pPf2yN5FQw5X922pAxEv1+bFnPp3OCNKL77MggIAzSK8TZf/sXuSM2D9+1y1bgxNxIdVc/cGrTzZcN6zxFjbqQzNweU8QAiffovks7jXBrIHLsij+pShzwUQUXfT5ikGQfiXrLu4ZWGI3AIAhRvFHV0WhaDR1HxDlECRtR+vd8WaX8OJiK2C5gkxV07gkk8liwxdtl1347rRPLE+Ka5EiIsIlIWqnB/ci65rQATKYFIaG5HAAs0AEXnBcOIkc95Sv5cEoEU7xe3PbEUnB+/Ib4/cnDEe2eUOx9jH4zm+wqLAy5F4EQBKAqDFCSKJC5FHgmY7BFMAAi52F2CCcIIhbDGeGOklcuiKa1Ej2y2GQ5kD8VbwORItb17OOigItKthjmbu/O1rVAuPPrIztMj2f9Ncj837PoW/w6eg2cRhmXxIiug8SbpPnkw8XsG4BAegI5Rkl1aByg+yKWMe/BKsjBRvNN6hAnFXz68vSuAhOvoq+Iej+7vLcZkDA/pHHRYOiGDduF6j11XbvWyPLFTl2Qk9H3A5LDOPascbE3LvE0sfGBDU8+sonHGYbL3WKXDiSHpD8uTwfPhGyhepH8P89dXty/Y4NwLeSir8lo6dJz/QGV/s12UN1Ch+zLZGbnVjtHH7hkeL+lRPKMSnjTCN1CEg9cZgAJggsF8u7zZub4h6+U5nCXCd9cx4kSNMdLBjcYpG1780GY3v/TRoy+UD/g/CjChqAuAkD51re7p98+kPd4ZQBQWuTg8sjBhXRD2Y6RFhf9BgfiwDP8BGeZo+DCCARgyVBhHQKI4Ggxk2I8CcHTNGZ2TyA2qRJrHQ7xRP23N/ZsK52c2QKs8wf2W/iPxG88CcFBaAEyil0LFOkOotMmrpI/IvVd/tbGl195MmEr2IxQ56f1p3sv13jBG9+B6l9axQzQqoNnz+rM/2u0Xf5YXtmFnS4e9jvL0jQEBBJCMenPx82VM1TDk+ykGLdSJq73yuPBSuhwoDgrChu9OwMI64eHhc16wVBgSXkVhUKAIlWLHiop7A48CMZJDMQkmyk1Jvz1SLpiEdURxF257rrI9EesujE1Ofo6WGNNYthkMXzgW93E8uOHBAEeoeOTlpyXyBBOPSW6wuYafqm0ieLZ8NfVMtB3Bs+VanlfwnKw4xnkRCvH9Xcm7p0DhngVKjyUJOsBEOWZF4qzel5tNU0O8j9QrOaVEiACJDEvIvQIR6j8UhigJx10+ZD3gqND5FYroLMt9nYEKfVh7MgLySnYJKHt07WFFDFq8zNz+wmHSOfpQia3f3zNCIxh+vRffyv8CCHlKoJKVrskqejMOIG2715EYN4Z78eH2yRFrPXoobsBkyBwmMtq7tL1LXgnre2TMHSQSHQRDPQlxgPvi3eCRyEDoXge1PKT/cFj/8Yhy2scVH4DF9cpha+hYtoqGKbukHPkxxZGjiiPonDyM6uY5m1r62EZnX1q1APC+4jzhyL3DbJV6JvVK2ke4s378couVNk0pHO9bVdu8jJoSv9738AUZmFu9PtlXy8Cm9U+/sImVT+XBfGrtAspFeSv0SYlxjNy2jyiMB8ryV4FJgN67R8v9PzBFAMPQMI/N3L2v02mb/X8rHB3OCtcAEl1fAJPoaRSDSVoJnJwXYEKRSuaYBFTelwEPMAkGMAIjHybhWIBKRhwDKqlRJe03e2U8zYLpA9QqcPcJKHgnjb23Pb4DlNRDwXZI1J+ckBdwvXZK57+wO8//ZKuPfqfrnsqjGbKTMuikF67BO8m2BnOgJMJm0KiAFn10Bt4QTKpp2ScwAAOWZwWP8/JKAMo5eShsn7k5KM9wwJdhXRJgTur8k9f6PMNBsbSDIv1uKYEp20yVEcV50fj/2voFMCl3mPxWLnpOgouOvaccGsaLcZ6C0cHIoJyhdSP7S5UYYDfCGcO8RRj5gmvYHyN8ViSE7LVvun/2WHod+7LvmBXnJmDaomR/6PFOIpexpFxaYN4rUEftkQe45xjGSc8UOGJle6xkd5AAEZ2Dd/ieAESxCOHOf2D4jr0YNQYWlFdy4HSVIjrrVVqXUZVxOKD3xJ1HJAaKZcpb5mx6/XNbfvCdtY/cV0LrUyJRGGDkZXyC94Ah0n/mnytn69Lz2A7nBXlcABAJNBCGKLueiu0IEzfIOZj4MzkngiTRbkFkD4Mmyit4P2m9hTwHndwTw0nflcMyXAcEwIPSAaCiZYTJuatddrN6zFp71wWUJSutHbcL17rdYzmia09farPKxmmbXn4t7+RDq29fkueoe+j/HdSzEJX7YfwzQAi4q2SgmqykethqOxeVMx4XXGR8dO4xOlTKKylrnlVuecNzy+R4Zze/tmEtqZCmvJ94GuJ0AEn0PvnvACYC403aDiaEDf/nPf07vEWaUQOPfnlR8/e/cajcbJr28MwWG+YU0gKKEMnBRO+r50ZtBxMHUCKHjgwvI9vGnHGESQREPkxy4Mg/FuT7EqCQkTwqQ3a5YsRnQ6QPCD3RqUdhSHnG3HJPQwAPUKCpcIudkeGuaFmyobmPbH7zOxtd/MTqum77fgb8PKTn7AQmZ272ex8aYEIxV3XXuhdZ8b6AAVjgnZyTV8LyrGDlQLk1GNbjdgIUisbwUPBODmK4Y3j4d4dv5975MJGR/1upACRvgQnQKARJEPvfVYQMQEnGH3JDEmAScsmhT0NoOaT95Gqjwc2oWB1F1gBHLyLPm8iq0MCzXeQ5QdscT++Vg0h6jvbHd3PFdy2mN70n95GAiee8yeXKw9snoLgUlu/jochgHFAug4h9SBHmsH5cdnh797aUKFnG3rOHL0rKZTJ3BsOun7hEO3mB4orE0tUstepYqx3T/dApGa/LFYNW370imHxmS/e/9d7fV6tHlAvr0L2a9XzuqWtL2l3Hr7R5L/Xjl9uCtH1CitsYzTgxFsbKlfT/QPQFcQBgjKmnEBAYgiRO8pX2ek8MWITJezLa70rvJUDZK5g4UPAOdI0bO8JWBpMe84f0P47IYFF0dVDhfUDx84DiIUVYeCBnrnTY1XJ9uyDR3L1mjZ0rVtU0q31Ddkrfd+ZKu7ZnbHb1UwdKU/eqF5ExMCVh4u/r7wpQKJoTuM/UyDjJq7nV7UOunL/VY0f5L/rmEwo7IM2QMfV6XtfYIxte+MgmVj/z3ufMzEdlK3EnxOUAk6x+lmcieAQPLYDEvUBgIni/R6ZD6/wXZsQEJsyfP7L8UZiCQO+chmmekrQgbfVGAkSionfiLYwU3tkpctmOMAngyYeJKzGQOWDkYJInN6jhGOf6CAIJUGiuy/ha3v+jeUHhfltgWBMsFu0qMLku4ywPhnRGejt4tlX7+r3Yt3XwoXWMPtE1G0oPU4r7FHF16J7AhP+v80mLenfqTmLHYu/HQvwCJvJo1p//0e5++I9W17MRijJPNzlUgAOwcJBkvBLA4Z6JoELRV9zvMBGEjl6Rd8R7yC54cSBegt49hlP06sIxnYOR34GAgXsc24CiUNnr0n1FQIJSmFBxuC1MAIlypl7UoQQLMAAHAPHmkDKSXtdCsZj2Zw11arCJ+IpUngj4KUgRzfeRsHSO31M5ce6TvafnzpP9KbTIqes9AiiS52RhkygPIln5dfn7snDYDhSu+LyM2BcVK0FJ3BTBHJBho/jlCBW6F5pl6OUCy5U+fU0RTZHqvCLURbnAl5QYaD9/pWbc26ozTARNHZlOlHJhyoFLmyXlKsuaJq2iecIqmyetqmXKqrRkvbJpSpq2CuW2y+pnpGntn7MGgaRv4pEt3f3Kbj/+wSaWPrTmvnUdm/FhQ8obp6xc1zF8SK1ECydG+a1mmVGV9tHRDy+Hd6Es/nq93lOiKAWV1I75VL4XBDDmUTlf1m/nS/t8cMezN3vszI1uO0VnQxleoIRROyAA7RNwAAggid7JXrwTPBIHk5YpUILxBEgYfzwJvJL9ggnCO6GC/ajCnEr20roJa+xasY6BTWuXqHS/UjZol271e53JnCALTBhShYr3IzLAjCBMb/0wwyXgo7xdwNJ7HTpfL8C2eF3JMYCqc4EJoAXQVADf0L+ral2yRhmYtqEH1tC7YRcrhj3TQNwjftKPKNaZ4Jl63yJgInmz1kSF20EKiwQghTCJ9Vd4fYCdf9E3+9xhMr76iXLQy16XUtw7IYzZvxUmWZBEmKDUQ0mAQrFWMZgUFnNFOPxcmGTrTlg/fEGZIOXoz8toX62ZUrqZVhqa9BZ1VHIfvSRvA6MrkKDjV3p0bMxuNswrbc3ZpYpxxcl+ndflMAnn8l8FIDJ3vB/POh1sl7c6035aZHWMP7H1Z3+yB6//xRtbUKHO/8S7wDvxIi2l8eh5nEx0Cqg4UPBUhuy0zmHfiet98l57lC469e9kqB0oSX2T3gmFsJCAyRsMfKGAwc+CSby22L4C5WCSEWWt71JvEkHiEKFIA1BQrBVgAkh+e7jC/v6wPBstMfYYeRKKJwhFotjsEHB4/YYiGu2pGUqAttVHk/bVHOdaAML9fnOozH5zsCy9N0tEIwGeC1TiszxhynjvRMAgJtb4jiwjKLLnep1JRg6oeDwDq/T7JG/PLuEeM3c7uXtaA5253uUDHZZUMuf5hJU2zioXtWiVbcveGoUh0JlPgTkRmPuB8lsqbhmVFA3MvrLh+Q9sZPFD6ZWNLLyw0YXnNr743CYWX9iEtse1PTb/Qnrp5f8jM7pGuWFaKk0sfmDztz+zzac/2qNXf7KNx9/b7NonOvbcppRTnZamlj+0mdXXQbT8KaIpaWL5YxsVjIYWXrmBogy+Z/qpdU89kcv/WInroQ8R3zK06fOP1PesWXXHos/bXt4y6/UJtxoEodpxu6IcM8A5XaYEJMgcvqqIeVmJ5ZISrwADZA5q/RA5f4y2YJzONS9DST8VYO0wUdyk7oRiKpbvCyoIkJ+/0ePjbrUPbgqqj30JUCrklQCQmbVPbXT+lQ/2CEzwSNxz4r4CSRgCps69ISrlXQIdoIn9ZTjHp1lWPGeYjhOXO+20jMJZGRSaFpNzZq7xbPk9Q7CEejPFoVMUpchgARQdizlgr/zNbMdmrrnJ1fJhEosBSbPAgY6d5wR0/hMwYT6bemUkGDV6JzCJQCkECcqBJCvl4hPPhG0HCmksA5M0R6311EBmjaTvC5DJgSack+53oITlfgHi4Dk6/2HA+2W4ZbyvD2qdSvgexRuF+zkZwzPAhFKATt9/oqRPnkSfHbnU7fvQEd3j8AW8AibDo2UV76nn+rP0bXo22xynXqRt5JGtPv2jPfnsXxXvHzs0gAmeBd4JQKHlFpDB6wAWKUyATKlgIggitjl2TGA8rPiDkXYj7jBJKtEJA8KNcPqZMDmg74lQ2Inyry2yL6M8mIQirQKAKFISMcnhENFis1GMOYY9GnsggHHHqJLzwpVn8DXaUdOmmuGnaUbHuDrkupnrgYllKENmyfhB5MoZv4d5D+joQ6enOIAehp77A7FYtMYyysGic7IeD4YeCGTP5zwHgxJhChadmyYe7fP9JCg/HhIW98StDcVNFPEoV63382+8oRy3vvE8OV29P+W3VypH5DaP2XXliEvlJVTKcNV2Lit3uibX+q51jT2xvqmXXmY7Rg/rtc+989Ps3W+9+S5DMzD2D6OTuh58byvoIctvbeX+V7Z6/0tbe/ClrT/8ytZZv4e+kr621bvf2IrutbKp5eZX0hc65xu7/+x39uL1P9rTD/9i9wSWVXkqD57/ToD5oz188Qe7p+NRd5/+JGn57Pfa/oMvN5/+3ja0b+3Jj7b86AdbfKh31ftQFk/l7qzux3wpUxuf28T6pz6rIxNQ0eqpX8ZsYOa5L3sBj6DTOnTX6vtvW1XPipV1Ltr1lhkraZy0Kw0TdllezmV5OZdqRuxiJRWZ5PBovy9DoFw1M0UypTFGP4775WN/ZdYBDd4h65fLB61WUOscue893rtGH/g6HRbHFj7w9Zv6X+6F6DpvyCCPnOJKb36MkVaaoP4ED8UHpkS6P8eBjXtKiitHyExIh2R8DggSPoQHcTOFAs8ACOwLEAlFMDKMvi85r4iAyNtggki7pFmKGhk6h9kq+UeT+i9MNMZQNIAmC5JQz5WkDdKEviXrXbDMKnoicb511/lkXwKU3LmcFwwhwAieCUpA4crsywMK60V0BsmwujD67QIDFdjK2V8EEExi1eH7959t93NYHjgHLKQEIIhtYBTUKbEdipr8XRxewCS8J/uBQ/PgA1t5/Ad79uV/t+7JF17RTjNvh4kyE9SBhJZaPYJEjx2PMIkgoWK+bMTF9klBhnOOlHQrI6V3x4gDE4GjsEUW+zHknLcTcW4eLDLrxZSFRVS8T6H+zouzJLwRIJIFiEdKRTCKFrz824WxVuRQJHbDnBhxyvWpWAQEFNcwhwIDyjHNZvPQPWNANuYfoDcsFVY9ynVThsxQ0n1ass34QQz7wABuXEdnJ2aGY5IdgOOTDQk69KRl+IHYeivr8figagJZHKKA/QAmJg73IJLzAUPWSzpWQk6CcXQ6FUmY27tboAgjw56TV3GhYkjfNmxXagSJ+km7qVxtmSBR1bFktcrdNvSuW1PfhjyMO9aiHDlNFFGrcsFtMprtw/d8BNpuhUH/9Et5Gh8LJJ/a5OoXNrUuAyxNorUvtO9zm1r9TGL5uU0LNkGfSXgIH8ibeCkP4pXNrn5gM1qfXorSMXkwU4vyOKQpeRDTCy9tYfVjuyPD/0wgefT897Yuwz8rj2RZhn9N64Bo6c7nrsWNz2wBsX7nS1sUkND8xhc2c1vvtP6ZGyWAEaGBxuTVZMW+UQZSlLcEUFjGdaBCyxvmpm8avWcNw5vWOKL4MnbfWscVXxK1sj1yT/FIx/s3rE5Appimsn3BbjZO+aRZlwUbvJxLFK3d6kuL02h4cOxymx292GLntB+wN/Xd9v/Bv+gae+hQYXDHcnkuZ/W/8TCo8wIkNECgwYA3FhBcdmt79/EwMVaY1yQHk1AMFvqnHFX8OqxMEMN20ElurzIye5Shcek+9FWhMte9EJ3DMqd8eBSV3g+Q8E7ezJr3Y5nAxPuZsO1gYGiTDmsZvmvT+td4Jqwz0GchTFy6JmaiCj2TCAYUi7YCOCJEsgImgCh6MLHOpBAcRZQCoxhMAIeW0j50WkbWpfQuSACRg+cFkXNdyRKvBKB0OEgQ4AA0gAOvhCVAicuD8kzwSlCsrwAkQMI9lOS98Dwa+u7a4oOf7MVX/48NKHPIFAR4TBRR0Srr6BXG4er2ehCHCR5K9EyKwCQUdfVvCxMHsta9uCox+BEWjEp9iAYE2yjez1UAg50qPqtwv8ME4ZXgjaQgIXGQs1NkQ7GC9YAiCTl0jLLn1hVhMMTM74xncat5zsf+aZBRBQ4M3zCxHjTpCr1wp1wynFq6tJ9zx2UsGT9odPm1j3vUP/vKeqeBjQzP5DMHEYABWDTLA17AheezxAtiH8dCL9M+9xzikAZUmMXjeEt4QhcqZITwmGrHvewfUDAiLfUBt5oBxpyeuWDV8iyABkUEGLb20fveZp/inT4ZRuYoH5x9EYzmnHLg00+sZ/KRj0zbLmOIAWvVdTRhbB8WWEcey6A91fGnWgqk2m4ZemhN/Xd9foXm3g1rkli2aDtI6zKmTV2L1tw5Zy1dc9baveBLtps65rXOsSVr6Vyx1q4Va5Ph7ehZtgEZ6nnB4568m1UBYXRSz9e9OqRuwa9XBqa9f93V1i8Pqn/VWgfWrE252DagKDXLi2ikZRRiXceimhAQ1X3a9L1AgvDplMHuIKy0jTfSPa4wkzDkHTLkrTrWzJwhUrveqUfh2C8ADgqKQ3rfkZWPbVSKcErBpX0DCutO3QvY8D94doNgUdezajX6doDDP6QuhxZMVQoX3rVZ78mzeSeAj9d4tWbU63Ko+ziguI+B9mbMibH2Vmx47keVXo7cEmhojh2NOYY89EHBMzqiNIIOYPgFjX2CR2zNtuuYMm0SYMm2DmI9AKYAHFsUvJHYBNiBkoh9AIV0HOtMWKexBPEW8OM18m/OCLjUp2yBid7fvRIAkICjmHLFW6GuJKscTHKeicNEBphimuIw0T6ObSud4yDJCYjsPRUETPafxcPo9uX7Z4CIgCmoBHVqP0CRITwv4yqYeLFWAhP3VBJRJIbnlLao0vN9tALqtuQ5+igFEpCo6bpts5vfOUxGlj9VXJv284EQMKLu44gMOToqQByjk6J7JwN53glim/3H5fEcFoQOyrsBGPleSYBJrPfAkDtE3gISVAwCPMOVQCJVwXnp+ZlzsvsFk9IEJuWKfIrgNH+UGK+JAfSOXG5Rjp0Z7si9i7YCy0FFFC/uocWQcvNMCUtlMUaeoRrwLvA0mBuZifZnNr9WjugrhwfACLD4xI8DjKjhxY9thPb+Agm9dUdXMBgyHDp/QpAJUPpMHs4Dq6SZJ5XAEh7C9YYpr6jGc7kGDChGa5jWsVl5NnNW1jLvnhLDVdMbuLxt0QehQ1UyujUJJNxAKvfrxlEGB2hgqKgDoC6AOgHqB2gZQxPLoUUZPMQ6ItctoAx4rvuhoCEw6J51MmzMMEi9Ac1GqUynUp227lerJ7y3NL15HY4Mv3C1206XdEmddoZexNJZeUvnrrPssNP6F6cv1duZyw127kqjnWWIdens5SZtKxd+pc3Ol7TbxavtVnKjy26U9Vhd44QNK5e/KA9lVEa+Xka2RN7XhSvtdln3LrklD0znn3W12ZlrbXoWw4rI49TxM9IpRurVP2ek3lO6luITip4YmgXv7Xz5YOq9XasTmPVfbtIYQM+qoPK+TZ6cDHxVx6JV6x+iKsGOYq6aXmVCBgVLoKKw6xaM++dfKJ584NPrkqteuP+NrTz5wW7Ls9p48Xtbe/qTLT/6Tvu/Vu6QIsKvbeYOGRXFF7yi5Q8dOBTx9Ezp3wn83QI86k1g3zp0x+q6V/wdS+TluEejb8SboUWXt+oiU3VWhpae+fJK3hNM0O5jZb69K1nSbJj6GlqZHZaxZXnwdChuAwAY/PcoBTjCNTTxxuNhv+AATASKQgV4BIV9ASSxGXdWXiQt4ZV4fyStU9dJfRMgBcIUQ5IBoh7lTTDJeiXFBExiEVh2O0AmBxM/hzoT5ezjEB8BJgWSAY45/rAvQiYjYJKVgLL3VIsLsMRiLMCy7zReCGDIeSbvn4n7UPBSYhHX/rMy2klRmdevJEAI9Tp6b8GDfkBxtAK28TzKW5cVrl/Ysy/+u+Lcl4rv835NhBF9TijyOiRRD3K0JHgnAAUPhWItvBH3SLTNMc45pHt7HYfegSIthwlQ0zLARIowKYDGdioEQKG2A0VW2XOy5/3dO+SyBJL3SBAn8E4QnZ0qFBD1ysEzq920jLSoeUM3utAgsLTLmITiIAwKhoOZ+5hVjWk6WVKJTHEVRVyMqsrYQMxBgPHGkMeiK6b2REzYU9ay4EBiGOdqGd9a5S65L8ad+TcYNh0jj3cATCramH5V5ytXSS6U4g9gwPAWzHcOCMipIq5lP7nWeuWqua/DIrlvUKgwjsrmtqPI0cZjiOcBId6pRom1Su9U0SKAKRd8g1ZOCpuSqhG7XCEPSMb27E2BQkb5xBWMFU2CBWiKQ5QYQ78BKTEc+0/WJq3Bgg5KDA9y6IyMw5lqO3y6wg6dKvfl0TOVduxstR3T/mM6jo6fqbWT5+rs7MVGu3il2SpqBuWNPLC1O5/auAxptd7vqIzOcRm6k8qJH5eO6BlHdN0RGc4juvbIOfpxJC2mkNapkA4tq0KxpxcbSt6EGV3Ai6UIMYgmzUeU8Tiq3HExkWs+IvihUzcFt4oBu1I7ovgxqbgyq3jDPOy35XncdUD3zTz1RgiTa68Fjs9sbvMLm73zeZ6m1gNIBgWjgdlnfv746keCzCd+fO7uFzZ/90u/dmbjMz9/HPAoE0ARZb3+J/+yTBkV/iPD1V8o7ZXnQgs0GZGLCgOF9Z4TQCTI54ZXhowOj/vwaI4lwqhLeCNRwePBi+Bf658LJD5MB8VhDhiUeByclyjdl+x3oOgfBmkdeDhAaKBCxlBLidIFWt3h4VFvQmaI5sKUOIR6klr9TyBCsZjeRfEwwiR2QIwqBo9spfwufdNu3SMUi0m+5PwcTPKLraJyxUdbYFL0fMmLuTD0EkVfGci4tB49muDVCBiCBuBweBSscw3r7plQH6Fn+zt55XuzwlPfLpBEmFBvcq1uxvpnP7QHH/+L4tfXDpfDGFkdo6gLoAQlHoSMOl4HxVhbpP0Ah/Mw0MDCPRCX3i1Vso/jCVB+kYBVco9CvakorBhQ/u7dY6WCSZlgkpESyK4TpYpodUrYPTLWs3azeUw50DYFUoNdrhqUQiucs6V93iGqpmtVRvu+MegdI4QCjZuChVeoU+R0sz8UN10LQzP7WP+XKVMMorKdMf5DpX3I8XJvck8M/UAFLJGfJqc0PaU4amsx1FIAUKYIBkC4EgCwPz0WgZNAhJwb7e+5X6mAwL0pGuE5NxpC0Zc3g02av/Ldl6uH08rhc3pfb/ZKnYty+7E/hgtjimFVTvDQOVoG1f//2PvP9zqubE8T1PfpqR7X00/XVPdUl8mbkmjhvXeE996TAEkYAiRBgCRA0HsvShTllXLpM29eU756+j9b83vXjn0QODwgoUzduvdDffg9ccLHidh7vXut7TzeHsMnbmyU+cn4HmbUdm+ZpN+lUolKxBnVjVhZvWBfP2ildYNWJjlUtK2ifsTKVSBAFTquqmHUagWZxmOTNjByxtYvP7UHT76zze2XNq7/Ui7DViXDVS1jViUjUKF7VcgrLRdQXDSDlYHx1lKSt1zi2aVMJa3kozLLqOQW+3TOW4QhwxuuaJuVx3vC6npOKQ0sWeswI/Cel1Ff94mthk5s+pzs08u3BJm78izkzZy958uT5x/a6fXHgs7TjJYuPbOz23Qe/FTQ+NKuPvzGbsiTufXsV3b7g1/bnRe/sbsf/tZ1S17OtjybS4TRCLFd+9TDlngwXHvmzG2bOI2HpbQ3c8G6xlfkVS5b69CS9zuhqXC9PEL6+VTh1ei/04G0SN8YiOCV5FVR5yKg+HcHSEoDNA6p5hhBRusODtKCK7WegIR1904k4EG6cSVpCBHmigIm5B36mNBYYlUeNOt4JhzLNbyuRfIWmwAggcAucCTrQCKAJr0tbI9QiXUlUenZAGMrrD0lUACQqDRoXtOu894k4JMCzR5ymAACjHXq3vyO4S3E/djWOsIQ/y/kKf+9Xb7/g42cvK0CEjM/4tnEjoXBSyF0hPF1oOiYbGW8hzcY+R+jt9aNZB3vXlAiPz/XOVKusJhg0i+YAJQBgSSRQILK2yb1opYdJgMnNpSxmehlVh4EQ2tvyaiuK6PL0A+f9YrQobmrKpFf8VE7jw2eNZ8PGYOjzESFYBwHKnR6VIJXRsqI9WQ7x4RxolRqk4HBeMXObxUq9VKpiuHmvkCtU0YdA88z0PdhUCAYEhCIlwOY8UV5OZIvBZvJpTvuxeBRRLEPQOyAgUHaGC6aIaQFOfpF+CRMVNTPJyVqQn2UxKk7UimdMIgMMZnejYUbDEqgjPAbhv7wXvECQoi1q+RI5s+I/659lBIljLdLRp2e7YAlwqRUnmNp3ZCVCvyoTL/L8CYFkVKVkEvkbbIsd6CMWV3LpPWNrtr6lRf2SMZz68ZnNibYl8p4latEXKnScaW+FX0zfGwrve+08EpCayUk4y9lGjXQSilpRZdbHMM54XumlQ6vYMjiJF2oRJ5RubyqqvbjKnyc0PtnfveTAvZpaxFk2gSZjhF5MSrcoM7RMG973/SGA2fs1FWbXLzh0JlduWPz5x/Y4sZTeSof2gV5KhflqWzJU7kq7+TGU8HlOXChxRwt6X6V0XVaqjlgvpSH80rnf2DLgvLSJUHr0iPB675ARj2SPOqTYbrfAerc8ErxSOWN1qlwQajMCxDx+5PmBZi8qiBA4jBJ4JGtNEz8t9KD5ysHQAAK4EjDxDscawlM6GsCRLYffe+hWYeJgBcBFL2a/AQmuYAQFPdlb0/Evpz78WoACqG1HaOcS/sDxBtAkz4/c50fARN5JkAgXov74C3xO/Rv4XpBdEb0Svhnv7dLd79XQfqO0qxsn45Le1YOlCxDnKnrSMS+XSBJGfeMkUdxvx+j58w6Jor9mQp3VwoKewBr17nx2Cxl/48UTIIACR5JVEXblLwBwWRBmWNuw5qHTsuwztnEwjXphg0ev6wMLa+jd8E7pbVggHuXPMZcimusDHC4YtCO7EMcl63Mfup0ElGy49r0yK4jbi8j3yhPhg5xx+TF0JrHW/YQtx9dsy4BAo8CDyN6MXgfwxJLoAN88D7whmh7DyiIMcde3LHU7OEAz3BkPDIgrd+CCA/i4R2uGtCz99uh8l47XN7nv49U6n1qH0Nx+OCMwCURRmEnTBEyNAYCoxP7L2C8Yx8Hb5JKL2yBo0QQKZEniUprAYsgIoAUUzFcNWjFUqmeq4KQl4DXKy9qQ8bkycd/7T2+x44zDpU8H3klFQ3E+OU1KcPTtNWl/45CD/DdCuNjscwGRy69wTNJwcQFjJOZI1kCFWaTZK57ZmFE5YTejk1blTyYqEqgg0cj8NR2zjl06JkegHNWnsMZpYtVh83AzCUbPcm0vYTP7trJtYcOmeXLz0NITN4I/Wg2bn1pl+987a3Xtu79Ingr8m7OX31p5699JBh9YtsP5ek8+sq27n+h9c+0/5Wdlxe0evmFLW88s9PnH9vcyn0bmbvisGvWM9XT0VHPybv1SnQPgwGI3BAJleoBJtGLdQEV9pEuU0BJw8Qb1uhY0jFePnV+1D3hoeBZE+aKENnRDkwcGgkY4npa2bBhG2GudKgrHLcbJg6UFDyypy7O7MNwR0BkKWPgc+yLRj/qx8AElSQV8H6+nsOBQujNrxGuH+9FP5Lh+VteX7J242v/nYEJxyfPw/kZTyFt1KOicccjQtGw67zX60t2jnHgEI7LpfSxyfHxfn5uaj0t377HvmzthklNUAYmdYNKjEMqeQeYjC2qpD/PPNs0lZ2Ti79p46e2lSm1bXDZqsnQrcrQMr4YnujOU8kIDI4CgbfIgVIuQ4wq5Cml9xMaoImml/aDAY7NMbkfJT46izGkBaElQkxUoFJRXEfFsSDh4TKBpi0Jl7n023tpax9eCN4H8fs4HAiluTRMohwqMnRRASyEE+ijQ4dPwMd/CKL1D81JQ1PS0E/BS6dSoUTJkIwfxTqGwr0ZAKJ7olCqxcDoOroXECkWpFCJw4RtwwJJgEmRoFJSO2Jlul+V/kvP2AVbv/6ZPf74b2zrzjc2Onc9M7dDBf0ilPB8HCLXTOjDIRB4WEuGgftHhSanwTN5m0IILAsiUan3igBHLjlU5KExCyOeGp0GgUq54FKWKEyOxfsScCW2AR1AkwZQ7LnusBkiTLXq0EGMt9WvgsXwiW0bP33TW67RtJuxzGj5tShAEDZb2XpuZ7c/EFQ+FHQ+tst3PxNQCKH9wm7SB+jpLyV5Ok/l5Tz+wS7KeC97Zf9995aG57bkQV305swUhKhHIzxKuqVOKnohEShpkASvN6QRCiAhPQaYBM8/DKVCx+ODykuHlQ8BDoUlGpJcpnnw3V/Ii7/iBSfOi9cICnUmEQQ/TgEk2UBxmAgY+RJLh0daKZBkw2Q3EIIiSPaESU5xrAzsPoQ3gXfiw7Y06FyHQdju9/b7h3X6kvRMXbGFix/b6YsvVTBlqBrGX+N+AoBfI/FS3KjrHhj5xJhHsc2hkQCjWMfyu1DXCNJ1fH84P17Df7NtLyXHxuNRLijkUgRFrn3ZemcHJP0yZAEi+fVDSmDDHuZqHDhpXVNnrXNCBle/67pnrXfyrFz5DeufWrNj/aeVUSkxM08AJaZhL5EfKpNSJfMMNFJGNhra0NQylOgzx2tbnkNEz6NrMlprHLWVdbYjAMN2DLOPIKvMgOGl9OxLSteCA5nG5wwnVCW5B0Klb1vwQugA5xCRVxUBkjZ0uzMbIgPuCG8lAEVeip7vqJ4tChC6AdB+NxIJRBDGwGEi44AB8A6jEiXLWOoMYS89BxJECZEU6z7F7oUkMNE9S7UNeBTrfkVSsa5T4seOy9OYta7RdVu7+pk9+vjv7Mq9723i1G15OXTymxVMTug7quSk43yIfwQEZAgcHDIMHlJx6T9rPfZFeKP8mKid95kR/y+1znsvkeFPq5jwoQDic9VLAchBQCPCJQ0TmumG+V6SY7QduAAfhkJBjK8FaBCg8W0qFOHt0k+FARsx9t3ybhlriz4qQ/JuR+av2NhJ6dQVeejbNrty005deGBnNp/Lq3llW3e/susPv7NbTwAKMPmlbdIg4PonXnezuvVhRmc2P7T58498GHsq/OnrgncNXGpUKKKejd74HurVd4hNggNgkrCw1iNIMoUSpSe8Ejojk6Z4r5m+Jg++9RZdI6eu+7bX0/beMHktfJW1PyhCJOWZyPPNdwWYxErsvZSBSVoRKBj2jDGPMNGS329VYmAFDC/p7yGvsHeYaN1hwv1kiFEETqLKtgU7NrRu44sPXG1jl2RTFsI9dF6hzke7DHv8rWUEiIv7+29t1/5C/QYiGbFP21HxMSSYSA6Yt0nnOEj2CZNYv+Mi/Ja1P1sZzwSvJF8eSYGDRGqgNde41Qge1JWgWv2u6Ziy9qHTNjR9zgamVMofEEyalHFVSs4HEALIgZJue7+kyw6U9jhQjmSAAkB2fh+tkhfk0AhAYd23yTjmywgHiITQUBTrQITjuFb6On5Ocl7wjnDxdY4yGq2PoscBLDBcZBxvAZMx3DsGzvfFTCoFAxqU3p7Zlz4eQEhpTyMuYwgifdxeMMlcG/FMMuCEIDwconMACCEtBEjKBKtStjto8F6oX9FzEcpSBmT+8rNXPrOHH/+9bd//pY+SGgebzPS+Fkw8NJWAAO8j3DfcO4jn4V2loBElg5GWn69jXen/k1byvtHrMEl5htqfgYkXHvT/tA4o8Dyih4IASBo47sUAkXgc8BGE2Mc1OC7Ah2PxZo57wwn3cmVwAQwTYDX1ElKV+hetZWDRK947R1flZawLMls2tXjTTp57aEvr8l4uvfAZHM9uAhDm2vgw0xBg697Xdv3JD3b7g9/adcGGcNp5KvuvfOye0ASdMueu+rAzXfIoARseTLqBB544haU4ND/vKKYvFNMf34v3SAGKhiZ0WgQm1BNSHxjzQlD4VnvCRN84W7mOy62/ECYpAZAQQsIAhxL7Lli8UYnRfoOCdyJD7WEvrSehr9Dqi207olkxw7Z0TW67GgbWVBAXTJpPWqH2FzSccBVzvaxnCQDR8++Stjk0BBItC1zHXQ4XIANQ0jABLlnXfk0ZmOSGQbZeq2R/C1AEExn7XDCRSprHrKpz2j0SVNNFXHrcWvtPCCYrNjxzzrpGFq2qRRmRa5QLHoLIu4Vt9l5Ru4DSKQ+lW95Grwx/nwy/jqmSBxSBAYAy0j1rgzITPVG/kJQwwwRQASY0weT8CJ8AKK4d1oOnMyiQDbgwzngZeB1kPjINRnvXMDIYcWW80BAgMfxRiWGP4PHMmtlHZhWMZISCKGkn0nqRGyk8kMQz0X9xr0T7doBCpg8QiQr33C0G2QyDXOqaknsiOhaVab1M58SRc8OAhzIidTIw1RjUWWsfWZdB+9QevPw72xJMxk/fdZi4lIBRmFgsDYJsBWOzl1ey5zkJhN4m98L0rXa0Ew5D7m26FxKUCXe1UL8DKIJY99/xuNS+jJLz4zrH0YsdrxZvwPuYqPBBCNXH3HKFPidcn9BubecJV503DjjlY7Axr3y7jD+V78wpzxAtDONy4ux9O7X2SN7IC9u49blde/y9vsUf7dGrv7GHr/6k338t0P/JK/y37n/jIzzTouzc9ivv5MmQ9oTdaILOGGcM1UOIlkYihGjxtOkHFsHC+4yQACaAg4Yn1JcQ6po+c9foBR9hwtLPpb5T7yAXEF6HSe7jcuungwmKYS8M8M6UtG/X68b7dWF8aYnl4AAsrggSXUNwQMCEcBgdHxv6zrmqus7IuJ62khbBRHmqQF4J2j9MIjQiOHZgAlhen0pXS4fJ6/91t3TMPoCyCyA5lOsctMszCRXvNAuWcRdYiuVxVLZPW0P/SWneqoFJ66g1dk3a4MSijc6etb6JZatvV4atF4gqewWUbjtY3G4HUEmHHSwTUMq7pG4JTyXocLYqENDRNQCPoOPgqQY8QfkAL/729QREKpkDl4wIjzEXC6AgXqxM5SVNwlqtGEwlbBlbILILJAkoYoluF0zckEfvgXN2RFgrQCWpNM6Ikq5AJhAygZWLdbYTipHhiiEyQBPv7/fLQCRc12Ei5ek5HCY6Hi9kR2Ho9R3JKErAhMpdwlZ0jGREgXsv/8Y2731vY6fu6DnIlIS2wuB1O56JMrSMRaxgz/Qjof+IxEgI2SCJyoaJt8oDQB6ieZv0XiJUOC8BCN+MUI8PXR8Bod8YdUb33WkokACHpV8jyK/BdodHck48z0GSwETHep2clkAlHEvHxeM6Xv+f98D7YB/31/4IMybGYhj/MDL0nNUxgrA8iAZ5Egzy2TW+Zr2TGzZ4fNMbsMzLg1mR17J+Q8b97te2/eA7AeaXDpNrj35woFy8RQsyBvj81H8DGBoC0ECAWQUZeeH0xrOk5z9N8q97YxKGmImjNsf6QprT0wyekQQYQ43zaNFFPSH1g7zrAJbgmaTrPkL9R4DCTqV7WM8+bm/p+Hqdtw+YvFankiUHitIt8gr9jCHGOO8l7ZdBjvOnv0kY3wATGWEphrQAWKxHCc2btV9yoLTTT4QhUAQSGWuMd4GeM0//Jx/4JcY8hrd2w0RLfqeMfoBFAEcumGSggjLXeoO4to7N1JugFAx2hbXeoPQ5aaVgEuTrEr+pNyk9xrg+jEGjElkbsekBq2rut57hEzY8vWz9gkpj56RVNg1ZcU2f5Vd0CyhddrSiSwa9W8a9NxGA2BHQiAogCUpvRxybp+cBJHQQK0R1eC/Bi8GjiT2QUQh1hTAXohITo0GoooEmvsrc5TIOhFcy0JDxiOEWSnM7Bn13qZlt4RzgI4ikRCdPWnVh+IFIkUNDXkPDsJXg5Qm2UcVaL27UMY14KIkSePi9dQ8fiSABie/nWAHI50XXccCEcJaDpAaY7ABk1xTBdRN6P4KXDF/b6Jpg8sqnF928/4ONnb7jmTJmTgcLGQmYJAIuQCQz7hmdLRmAU+uZJsFZMMmExxJFmBDvf5siTHw9gkDnep1BloJBBwYzvnQgsM/vF66XaQ3nsIjHUz+SnBOvlWznGOojOJd9wUORR5KAxAdr5D/JOLL085J7s+R45kKhj4n3M+F8qVqFGCrXSYOM/0UHVloc9k5d8pEBGCGBkRIYbmfp0gfetwWAAJoL1z/zueY374W5aAiNoZvPfmN3P/qD3XrxOx9sk9AVw8vTIZHRGnZ32n3o/asYOZjjOOeCrkmoi1Zd9Omi/oT6wxLyh/5LNijyo7R9b5BMqMAjvbZdqtPxzN9Sp2vT+S8KwKSVa1tGgkkCm5B2JQdKUqcQpW20HAutx+L2CAud+xZRF7PTzwSYSBhrXS+tABfyDAUtGdWkRZbDQMfjieXpuVlGY74XTNx7iPu5hvTjYcK1ErGeJa4dYZINlNfCWntpj3DXO4cx7MAjgcgReQNReCgYxjIBpVwqaWKWuV4rru201t5J6xtfkBatuYd5OmiuKm+hssfyUFWvjFifjP6AFABQJDiVyIiWSiyj2B56EgfvA3gc1fnAJE/Pgfex6/wmwjbhPPbFOhevN8FLIExE+3pBBSNG7Jsmy02MOKsMwzDmgCN6HdHFj+4+4GCZUQKTHWH0CUXtVoE8kGD80Yi/u+CZ6Dn0/ChMr8t/AThpLyYBChARJGJIjO14Md6qKR0+0zFewU6oS/8jKIS2drwTnadtwJVSOU2mV6+8tAcf/8muPPhepePbbhDDUB0Y4WAQ3fjqN6J/SYWMaL0MIaPuMoR+S++y1arUTYmd8A/nRIPvTYZ5jzIq/m61DF5GAEXsa/NjFbyMBEpI9wheSwIJB0HS8kzbvX6Fc/WbfQ6cjHSsxDvJACteQwp1Z3ofvAv9x9izH7C656V3FRsgcIyPAsCS4/WbwgoK8AmNGGjMEOYUD+Ey0iBLGoDQ6rChZykMJjp41nomL9nI/DXvfDt3/rHNrz2xUxdoRUbP/8/s8r1v7OqjX9oNweTRp39njz/7e3v4yd/a/Zd/stsvfm9X5d3QWgtYbNz6yi7e+drW5dWc2XopKH1pN57+xh68+hu7/vTXtrr9yo6vPvTBSvtnt6xzfF1gWTGGSWIAVEYz4P/xv6kvow+K90Px70sBK4Rejyqd+YjeviR/hH1BHIsASiIVdJhRFPm89zK4KM40yjKnePcegk15KgJ8aHackraHsJqumdqe6Xz5FhXLcOOZUMkfvROMvXslacloezNnyY9NGW4AFp4jPA/rYR/HBTkE5PFktnFPPKJERVKhtqfl8EiLbVxXz5gNk3ifjIDJLqXAkgWHN3kqu45NIPrOIRn+I3gL1QMyyAhDHuQl/aQOA8NdWC8w1PZYUU2nNXSMWMfQnPWMLcqFn5dbrwypUvdReSaHSjtDiEvLI/I28Eo4v7xlQhnnuDX1nbKWgQVlnEWV0BaUkeatqg1jECABOPBI8FSoZ+E5CvUc7GMYC46tOIYhGPXnPFwRWo0BlOCVxBCXPAEZhWp5IzQPBiZ0OiSuDBSo9M4YPAwLpVItd4EE6djdgGF9x3N4XREs8oykIoEmI60X6xiePRsmVP46ON4mQcen7cUz0e8SgadIYCkSSIvxVPSf6DXPkvUCeWtUMrcPrdrq5of28OUf7ZpKpzNLtObScfpPPrugjGGl3oGfK4Pglfm6brneT+fgqp1efWDLa49taGLDmmVsGvUuW3oWVZCQ0dQ5TBdMyIjWVwCXcd+AosNP6963RstYeb4f+Xn+m/8NIBI4Jd8r05lVJf90ZTT7CU1yLNvDmHJB8bh4rBckMt82gCQOJeKelozLfpX26rKVaSX3FgEun+ZAxpwRIeq65f3300n3vI+Bxzhzk0t3HTAXbnxhl+9+I6/l2yAGUr1NXcuXdv7qZ6616/JuGPNOunj7a7v++NcqUPytPXz1d/Jwfu/nnd1mXLlPHVizK/dtQGBhbLXW4XNeECMPkZe8NR+AIO9I3nCkatgO0ZzfQ8tBbPf8JdGEObQ6I28FIACWMB0EaYXvpXeEscf4a1uYowiA8B1T0rbgAet9c3yi0FoseEtv0+v1Pq8rhrowwJkQUS6DLYVe/dFDkrL27yg53w27YJFLLSeD9Lto3xJkcjxXTpj8COUCzGtKPDGgFDwTGeQjmcprPANCRqFVlFd4UzEuA+8eRm2f5Vd1WEVTv3skXaOL0pJKrsoIgsnhMlpxdXgFPB5GY+9Jhwfg6Bo/a0MnLtn46asqFV/1ppXDc5etb/qCt4qp66Iik/GqlNDkoRwopa6FMBihrgEZ2xE/prmf1jVzgg+dIvvsYFmPHSrjOD07CdkTdKgvAQS04KIlC248LbowGtR9eH0JHoyMZgTKjlHJEpkosw5Y8GiiF7K3dhoQBOUymBnpmt666E0COBwrw+xzwPtSSuASt0WF40atXJ5N5/Cqndv60B69/IMPLT+9cMMBVKr9FfpfVYIAYnyuCt2jHDDpHdXI4A5Prtu6QITGZGTaexetb/ScjcxcsvZ+GRvqHXQOzwhQ6cB5UN8G7yo+u0M0/td9Krw3fgOkAJL4HWIBAG8gu5UeigUAtlMn4AIkkgMnDZPMeVqmjIpPRysD/+colHJTUNpD2dBhZj/m8YnTI/iylUpe5tCh4zD9puQljlP/ctXGT92yqcW7NsMI0ysPbe4sI1Q/cZ2+wAjNzJ3z0s5tf2obN7+ym09/a88+/w/20S/+qy/vvvijbT/8wbcDGrxWWpfReZOKf4bsZ3BOBsKk0p9x5ugoTMiYukg809gfBnjEfmFEB8IIEAKJYOLeHP/XQaBz3MMAUAkgWNdvvBiODR5gUHpCutCyMCqAf6/WZ7mUhsZeIiQWYILxj8Y5GOiwTH5rewih7dYuo54RxyMAlUgwCCAJEClpOZXAZP9yoPwDwCQ7JLaXYmjO60wOU7pXKTKKxOD9I2RoovKBireyIpzULXD0W13HtHUML1nX2IrVdx1XhlcJhdZbXqHea5XHpqx/ZkOlHJWmZuW6z23Z5OJ1Jfpbgsk1gYSpaDese+K8D4vRNnzGOseYIU0vVYb4oK7loBBQaAGG5wKUOsdW3bMpawYmvfKAenTcbpi4lKApnWI8iAVX0pRSBgUwhIr0pCkupXeMVcoQvVkRJm9XNkzepNiUNZe853sKJvTriV4J4ndcz4DF4RL2VwgSnXrH9M5+/DGeyTc2tXDdCvFadBzjcVXq/5frGj42lwxAid5fkby7umMzNjW3bdduf2mb1z6x8RkVAEbO2Zw8m8XzDx0oDe3KGEonPB8wCfVI8mqO4TXIQAo2DhT+j+6R/f8y27MU3g2/d8MkAwpgkoDCIZF8Q/a/doygwzF7wcS/vysaFPQ6JPardNiE9Z06piyxLyWHiQASRaMHpnoo9dALsXmG8ZmXl31ahSp53L1n5OGfVf5ZU94gP12y3kl9o6lN5b1t5bvrNnH6tsMGuOC54Jm8+Oo/u3cCQJijfvvBDw4VQmg0BKCy/7y+9/KlFz73y9LFD3zaAAbCpEMnTZfpfwNcqAeiyTL9YgiTep1XIiCTDRNChnhh/M40I0+gEWAiSMjw71KEyi5pm/blgsZeyu61n0vhm82+rgxIErnRRkBmPwIgu7XjlSABIgsmu72QHHIw6do5YIIiHHY/x9u1L5jwzMn1BRMBRIbah6KXMUaMJOyjCTtUZJRlbDLNYGUg8BqKBBXCTccGlxwEdZ26oDL+EUqjgg6dw44NLqvEdEPguO7DVwCTkXl5Iyc2leAZv2tZJRyaU56ytqEzPqbSqPZ3jp3TtWeD1+F9Vah/GfQQV88klZacu+gwoclx9EwIa0WIeAW8QIFngsGg5OqlV/3GwHhFtxQr4B0m2s6+t2v/MPF6j7T0DveU9ucyqCgbJmWNE9J4BiLpdSDidSopMWhj58hZu3D1Y3vy6q/t+qNv3TNJwwTvhL4rAKVU2wr1PguVHpo65uzk8m279+SXPpkWYJlQKfXiVSbn+sLmlu9YqzwVrgUU+N/U8TBlQfMAk4st+PAh3v8jeX6Oix5L5n9xHmJ/opwwiaDQOmDgu0ag8K35RhEmHB8BktZeMMmEuP5CkKA0SFA2NPYSwMh4JvJIdgElkQNHKpMhY4roCv2uludSK88lrfou+sWsKH9RYLtgQ/Jk8FQAyCOB5NqjX7nHcvI8c818IHB8ZGeZ8pk+L9sfe2uzM5c/9OWGvvWl24yu/IXOCVMtABjgwnwwjBpAB08aF/gc/3gux/S8eqfh2+n9Ag69X/5nbDnIOrCIgIjeSBokGeCktiFA8mNh8ib9KLBE6f3HkNhfLoxzDoikvZmcEgCyYZIAJV7bIbHXcTnEf9pdv/K63CtJrv2OjyUlcMRJstLyGRgxzDHmqRIGlcQhji0D1DLt7epbh1aUcEQpGSyGDKluP+Hb6C3M0OE+jtcsna/O+/AVTb0LRo9jQmi0viqVMWHgPkAzd/aeDzXR2HNaUNBzJGEuAEWIK4TF1jx0hqdC/5I4DhYeVYBIiNUih4mMRCY+rgQdDU22XofGXtoPTJIwV6IQ4gnA2FWHktaPgAmj+eJtMFQKIowFMBgQMgAED0X3AqgCBMcQ5rpw7ZU9+eRPdvPx9za7dMuK2afruTfCufoeOzBRoUHr7X1LdubCY3v84e/t6p0v7cTiLTt55o7d1jXuP/+Nnb303HpHz/mx/j/0/ytVGOhQoWD0lEqvMxf1vfTNlV74D/6fdEw2TDJAYf8ucc7eMGHStkx9iERFON+JYwBE2LYDjzdLRkvGIxsEf444341RIg/l7KG0h5KZCTQJdwGUtOJI274OdACKjq3SOqrkHK0zmkGETE0744GddKgw8Rp1K3c//KNduP6FTS/dU97csB55NP3TKvDNXbPJxdse3mJ2UIBBww1mzAQmeCxb97/15st0uLz68Hvffv7qJyEstnLPe/PjtdDZknH0YoME/l8EQQQLcpDUBZCkj3nt2DcA5adQ/FZoN0z20k8NEwRQ9gOQqDdAIuu5AlByHJdLP+I/JTB5HSKM54McKNQ9CCjULQCUOBgdQ5jQioaWKPTMrVFCJcHQQuWYEtDAzJaXVhgmgvk9aGPfTGuqTkorSiwyOvReBxiAhXGRxk9ds1MXHsmFvuZwYWgWQEE9TlnzhLX0L2jftryTcyr5iJqNI/JEdirg8UoyYxbVJHFanjcxPCgNj1zy43aBI5feBpNYZ4JhDQr9SwCGRIOGXGLfXkDRdd0AY3C1XgY8JIeJIAJIWFIRXixPi1ZcwKRQ365A35hQV4dAvi6YPAUmT36w4/I22O4w4jq6rnspXIv76Df7ewSK85sv7Kk8GqbyPbP+xM5p/fFHv7cnL/9oG/J2hqYu+rGAixAcBQaGa1+78Yl/UwoSDFtCb3X+B/8zDUgg6CMj8z/T/9u1GyYuQSJTCZ94GkAkV5hrNyzeJhmsnEYjSzKMrynrmAikaIwiLN6kCJIIk0z9ieR9fBJvhTAXSyCCIjQiTAAMzZgZay16Lmxv6V/1+hVCXXc++IN7JcMnrrkH09C9pHy3KuCc89AVYj4eeuEPyetwuKwxvD8DYr70psvUrdA/5sqDb+2KAEPz5Yu3v8yEx5jFkvoWKvQ7xi7IS13xpuX8F/4r/zkNE2DBf/b3AWDTSrY5WHZBJQFACgp/jvxaXCelfcEkMbz7VS5jnJaHvzKA+DHKgoFL2/2e8b5hPfexWdrHs0ZxbGbaXsJbB8v77UBKGaBU0rpKMKnGSCuT0gpDv2lOSuIlEeJSU/pp7Fm23qnLXik4fuqmJ0Ta0zMMBHN60MkL4wEovJWWoEIIpF0wwSNhXgo8FEqy9B85LJhwTE3Hca9PmVq8Jlea0o4MRwPX2BmihfBWGJ4b2Mmg1LLkefGs5KmwTEJa0dCwjCEv35Zsf7M4JhsgaQWQBJgAiSylmwhnxHZAk3gvWXKjqmuHkrsAkAKIzzsi0SqLOVCKo3gXVIImMGkfOuNhLmBySzA5Ie+CsJhfB0POfQQQfrth1znsH5jakEfzsde1bN/72tauvrTLNz+zBy9+a48+/J1dvvGpTc5ftWqMus6vbJmybsFjdeuFD+vO8CEMCe8w0b38P+naESYRJBmYvCb9F/03b16MEojsEnH61DqAcS8mHp/rnJR2wl8Yj2BA3mhEMIQqPEXlgkm2IjB2KRpJyesRdB2HCOBIAJJWTpjgmUjRI+E3ENml5Bjy59jJm96y6/bz39vZK5/Y4Oy2g6hS16vtPG1MHcGAqXgUPk5ZryDTf8YneeudpP4zFBTpjU9dCuEuOlFGsOCxXGPGy/vf6Nt/bitbL21JYKGZMxPkMRFe68iaMaU2cxvxX/jf0fsApDEEFkESPZhdSqASf+/A5c9XvPaPg0kClP0oGvO3Kde5f4mS6wbjz/X3cY/M8ftTBiaA4/2yPnuvpNfeL+3Tb4CSeCgVtIzCkxhV6X/MxW+gwuCAtR0L8jjojEWCW5eLe8MmF+4o0V0xxjMCIt7iA0Mtox3m8cDwU1ofc5gw1hH1KKPzxF3XdM053WfQjsjjoP6FcZAGZy/a9PJ1QeWMVbWpFFNPq5F+bz6Ml0PILMzFLQNCJZ7DRKCgkl2gicOUAAwMDQaG0F0ADfVBPw4mhHNeBwnagUmh4FGo58wNkLQiTBKgpOUwiR5L2Faq+1BHEupKQnirhP36fwEkOzDBO2Ff++CKrW1TZxI8kxNn7gocE8ZMiixjaIzBIaMAy+iJLbsoD+PBh7+1zTuf2+XbnwkqX9mtx9/bHV1n69bnNq9rNXWddPjU6dtR97V590t7/OmfbPvhNz5SLh4p8OD/UEDY0zORfHtaej7CqGHkYMKWwCFbUzJMx62u57TVyzMq0/3iKAOZIW4SZZ/LOGC09CqW0kYkrV1GBOOXrcy+17UDjB1ljGVmWwKTFDRifYlvw+PQehTNh4EEsCCkFcHhoz7ruhmQ+DZdX9vIp0PyRPBIgAlNh/FMgAkgCp6N7qf86h0w6dGv/OuTu7Xh/cx550vqRRiQsm/6kgqNN3yoFzwWQl2EvBwo0vbD7xwqhMVogsxU3EzpPbPy0JhxlWm2jw2dNybNq2w/mfmvNDbgvWSMO8Y+VZeSAUmiXfv/XMXrcr8kDeRKB6+Lb5/DGP9Tk8MhaF/AisftU7tg8l5pr71b0qNlv4AilQ0EoJTLQ6hgNOCRlGScq8jkDD9PU90leRdrXsGHG41n0qHSBwadoejj8PKhkjz0WvcpTmUYMRYYmvrukz7vBMODEw7xJsECCpX7vZNrAtRVm166rusuK5HLKMhI59Nznz4xVXR4lFF2g5uERGRUQ3NFgZCK+WyY0Aw0woTwWLIvN0DS4vwAk9xA+QlhkoFIVNgeW2lhvL3SnW3AQP8heiVFNZLDAehMWsfQqp1XKfLRy7+2G4++t+MqWQaYTGspo6pzdrybCJMJmzx11TYFkLsf/Mou3XxlV+9/aTcff2s3BInr939hV+9+bSsbT621b9FbdFHfNXf2vt198Rv76Bf/0b0TJqeKMIle1m5YBEVvZNe+HAIqzHHCBFoIIJS3zqrEu2ojp5j+eVsl3wXfF7/LzsRbwGQ3UBwm1Om0yIDhmaSMSTQou2Cylxweu72WYq0Dif0qU08SvY8IFDyWbEWYCBRp0Uky81sGMk4NDDTwRIDJvY/+Wp7Dl+6pEFkAJojhYmLe8REE9D4IaXvHVAnQ+JhlgKZ9zltx4bngtVBXQp0JlfZU4gMW5oPZfvi93frgd3b7xR/t2tPf2MW73/gU30ztPa6CJ9N4d00ILMPn3WOpak9CYRhqvkF9aOXlfVOIOmQ3EWb9L5Wu41CSMuGvVBrYSyFtAJT9KIfR/m8pGf3gSSQQyHXMn6nXPRMBBZC8VyLvRMsDAsrBMh0jeLjKhu1g6ZAvj1ZiGJhL5KQMyBnrmbzsIKGCD6g09i7LyAMheTfl1G3QdHfIGDY+GkqAAgTwVDAShEJo9cM6XglLvJaRE5s2u3zTxk9ueUfHihYl9np6vNOpMfaSxyBzXRkOB0oQYa48ldB3wQTYAA6t0xbeZzzkN8enlLMORdvDPfT80u4Oiyh2WgQkQaE+ZB/awzPJSOsOYbw6CaCwDOv8ljF2kOhYid+AAmB0DJ11mDwUTK4rc88u3Un26Z1r6TDR/00LmNDq68q9L+3+i1/LK/nErj/62q4/+NrWt1/axWuCy92vbG3rI+seOatrjOj7LNvypWf25NO/sU++/y+Cym89fEndmMNC7y7jlSSKI/juHyZ8G/1H1hOg1KowMragUvf1V7a0+YF1jJ+XQVYG5tjXgBKuEedLyUBJUIl9Q15TBEYuCQJRu0ASYZLUg7gEAAeHjMtr0naMKF5HBEm6zmSXuJbOASYe6hIIPMSVACbjlQgowITQL6FoPJELgsijT/7e607GT992j6VC1/Txx/g/+vY7MBFo8V4TqCC8loz0HwELIbEYDqPZ8PQys1s+8gp8Ql30wt988L1tP/6VXX38a/+9ofufvfaZjxm3cPFDn/p7cvmeg4W+NEz1TSjMvRb9P/dW3BsJRt8N/z8JmOxH/1Aw2fEOMsp5HAr7MzD5scp5zaBdMDnA8PECCnpfUDlQyu9+waRf8BAQAEvpoB0o0fECytFKDMO0YDJvzX2rXuKhwxQdp2jnznwMtK4KE2SFjkw+/wgGMCmdAovYWRKosB2jSciK0BW/Q+X8VV33tg3MbHhHyPJmQMA1qSth3C6V7qOxxQALDJmKW2UKh0XifQTIhMziYTcZUbYT5toZZn1HASgkNCoIkdY5T/cJY2gBoWCsQggsGCtf55mkYETD7yiMYqUMbH3XvFdY17RjHIBc6pxssZ39DhBBKgUSvBAAUlgdlsDBvRI9M8BgFNsLVz+xhx+pdPjgO5tZpM6E+hbCXDKmOjZChN+IfdStXH/4rc77vbwSgUQeyeWbn9qp1Xu2fOGJbd78zKEyPnfFqlS67xlf84r+l7/4D/bZD/+H3f/wdz5/OjCJcMwM/55S/Pb+H3P995TcI9RxvOvoXbQMrdgpeUjXn/3KLtz63HqmNjzshScSv0v4NgKIeyc7nolL26hfYcTcNERib+toFIBDTmVDJEr7gtexGyQe5pLSIGF/xutwYOwou2L+NZgkcpi4tI9rcm0MsIBSK2g4TK5/YY8Fk8t3vvECIHUp1LmEynsZPdK85yG+UxjfLI5d5sPtpOBCz3iOiWEx6lqa+pZ9+J5Yx4LHMn3mns0zLMzmSzt37XO7cPMrhwleyuV73/ly/fbXdl7PhscytXxfhYPb8jJvWO/MlrWNXnCvJYKF98X7w2MJQ7nsKPSuD3JIJGEslg6frG1xewYm+s14Ykd1/lGiK9xD66H5cFC6OTHpIoS83qbQQ36/ymW0X9ePM/qu5Lh0nceu89+2P0edSwITKtqpcO+zgwIKHQD3lryVUoFHQDlSQcafcte4ZeCsd46iU9SJ1Uded0JJx8NIVAJj6PQ7GuFoNICJ97ivwssg3MNxGH6BgopjGRn6nUwuXPfWQcz1TdiL1kx4IgFCoSLfjQwGRr99HWA5OLgvQOHeYT12porySvtUYooJKpPwtI677bMGKiEFjyfAKYAkGikZZTIY8XcZKK8w5n6+5P6JdC6NEZgfg5n9xk8RvjurzCyDlbwf/nsYQl0GHiVGF0NMWIuQEq2naP4bvZECWrRJ/I4gYbDHcmX8rpHzMvKfumdyVTCZXriV8UY4DkWYRCgxAu6pc4/s1pNf2eOP/9puPvmlgPKNrVx6biN67ll5LReufORAWVQptK1vyaGyfecr++y7/2Kff/9f7YEgtLD+xL1OvjffJs4pwnfkv+GpxO+GdxZ/7y09n793ABDEqLjMbX7v5R99mHXm9KfeJA2ScDzw4BvF78S35RuHwkSM00dFox8UjH629oSJtru3susauxWvETsl7vJcku1x3Y9PtmegoXX3QFwzLt/mxyT7kpAXlesU+la3Xtn9l3/jQ7HMnHngrbyoL/G6E33zmFeBinsnCUBYergrAUxcd+jE7TouhsKoYwljjy1ay+CqtY8xjfamjZy8adMrDwT/D2z16qcOkcv3v7MrdJh88hv3Wi7d+9YBA3BWtz+1+bVnNkr4fEwFyr4Vq+1e9JZhvA9gEMNgaaDgcZB3Y0W+5+0UOHZNtwBUWEoMaAlEDlaN2IHKYV8eqRnLAAVF2HhLML1zl66X7bnsiKbiaGcQyjdp/zD5M5WCQwYWDolEyfZcCsfuvt473ooLiLh67RAq3xGtqRCdAukceBDPhfBXyYBgQlhJpV7BpHXwnNeTLMlVZeC4VrmoDHJHYvSpdmU8SZwY4DBUSwhtOTQEEzwR1kPJG2Mb9mFAuwQTOj4y8RCtvDBKGFX205IrX+djgDBIGGGugzDKwTuRgdDSwZGsRwWYYODJPFpXwgjASIwJCSWV8HzoDonSmHs7CVCyYeKVuRioBDr+/13ci//HOGO0YgOUNz3O3Dl6XplQJaIIVv0XN7QJQCJMXIDSgSLD6pXsurYvab21A5NSPTu/AQWeCTBh2l48k6nTN/286IEQCsvARM8JaBjgcXnjud19/ludR8U99SZf2PHlO9bcfdoGZLDPXv7Art772psLD09fco/lxoNv7MVnf2uffPOfvBXYyuYH3tACEPC/mKgKT6UimbAq45EBCWCh7/cm+YybknuaGLCWGRs9fd3n6Xjw6k+2cuWlT8sMLDxcmcAkNrwIwA9ymGi715fx3/Uu9oKJV5Rj2HMo46HkUK7jcykDjvS2xCNBDhQZJH8uLb1ZsApt5MHXQlw61z0THYdngoBF1/iGd1K89ex33t+EaAL5l9ZcAIXrpQGCR4LX4Z4J8OB9J/siTBwovFsp/Zv9gIU8E4a9OeEAwMPA0+ibvWIT8oxOrj/3cBdAufn893brxR/s7ss/2YNPGMjy3+ub/p3deP47uyhP6oxAOKfnp2VYuq6FkBheS3hPAR58s/hOeWfZsIneS8aDIb9L/Gb048PKH4ekCJIIhgiT6JnsT//EYJJRBEcu5YYJ+7KB8s7hSvpooAQkFXG+kR2Q+DS8AMWF5yIJKISvMI4Mz92uj4m7zBhAx1XiaOxZUoYPJRsfxdeFJzHo16M+xCfJ0nocDywaUIxJBAJGp3dy3aaWbjpQ6rsIceEZMAbQgD87S87B2LI9Tp6FwQmtu3aAkgZJ3LbjMWBsKF2RYZRZ9Tu4+ygYIjISIqMABO7hnpYMFU1YaXFESyNvbYQB03U5xuev51idE7yvMe/o2Tu1YfPnH7rwuvCuACtLjC0jAVCKj1BhO9CkRF/ZMm01VIKqJBlBEL0ToMJvWnUVaglUqDNZ237lULimkh8widDxgR7J7PrPMezFsqVv2VYvf2j3Pvi9PX71N3bz8S+93mXk+Jb2T1pr/7Itrz/T9VSKlFcwLyiubX1otx//YA8++K29/PLfeVNkprOlgYU/v/5HtcBS007rIfomYax4r+H7Bc/j7Qpjx+m/KT3UdZ+ykxce242nv7K78oT43dy/5N8jTFK2o1B5r3cKxAAK34rjSAekB/2vAJQgmgtHxVGCGU0YZRt+QlnUj6S1CwYcI0P/+nk78lGKCXHlkqDh19J9EIY/QiC0xJpL6j0SoEjRKwEmwAdwMLQKvd+37n1nJ9eeeuMZrhNCXbqP/uNOnUiQA0HvI3ofYZveB9vIN553UFjflde0HsfbwsjzXzD8jDMGCHqnt1QYuGXHBbaFSx+6J7Jx5xfupdxT4Yc5eIDM5v3v7fyNLxw8UcubH7vXQl3L0Nx165natA4Bk+bHsd7F+7bovwOXtCcSIw+7pAIyIDmivHNY+QOgHJEtY5vDQ4owYcj9uO3tElCSEYSZ5yQXQNIKA0juQzLkPwY88fhd50Q45BDwSP+OyhyTXOOdOG9InE8kTGIVFaEi2CCHTpjbPUzHO+BeBxVwtNya1sdc2fpYpez73nyQehJgQ6W7T8tLOE3XO1DKtblvv4MgM/WuA0AGQkbCwSKjW9NxQm75JV37lo2duupGCKNDJXTs/Z6BSVK65Vy2YZSD8cZIvQ6STJ2KzokGPnOcYMF5ANE7QuIB6FoxRJcpQUusxzog9xowVm4YARRGb8cTSx+PcWVkgIWNJzZ37r4y+ZnMNasFkcZe5iJfcKBkSu4SIKnRtuae09Y2cMaO9S1Zbdu8G3/gELwTFKCCAA1DyMfWXMEzuaXjqVcJ9SaxVRdLxHwczBjI1LP3XwSYUHG/eOGph8y4bn3HSQ+Dcb0rd7+2C/IItu986U2Gbz781j749G/s6ad/sou3PvfpbvGwgCMzE9Z1zvv3JLRHoYH/yDsM3+LNiu+VJed30LFSwLr74W8FlB+84ME9+A7xukHBs2NbmGVxN6j9+ztMgvBaomL4EoXhWxKvAcPOMqWdeo0dxWMBRoRBrnNDs19acu1Uvu80Bw4tvOJ+B4m+PR5HFWI790vBJAqYABWa8NN0f/vhL308roX1D5R/LwQY6ZpVXJcCyjF60FMfE6DidSRKJ4h1jgEoGZgAGfbrPTl0EqCEAhvLnZJ/9Kz4/7Raq+1atCY6TMpb6Zm6bIMnrjkcCIOdu/65h8HQGqMhX//CQ19bD3+w689+6yI8RkiMfXgupzde2IlzoTJ/eP6Gw6p9dN2adQ8AFufk4VvwLBm4CCR4KXguhLnwSA5L/E6HuDwMpuPC9gCU/SnMbeLD0ucAyJ+jOFJxtjKgyJLvT87JtX+3IjCSZS4lxwaYpEBy0Ef97fTl6zDBG5EnIA+GKXrz9LtQGbpciadj+JwM/l0fw2fmzF1BYE7n433QLJgK/BAmAyQHSsJowKFvSIBM6HhIyyxGLA5eChm8SQaVviczy/SkV2lYRoeQFvvxbrgOxxMeiwaXfQFOGHCMMwZqL5hgQKKRIvwUQnEuAcT7p+g/cC0PzyFdPwMGztP5oX4mAQoGi1Kw9sfOmRGUfixGLQOTS3ZapWg8L+Dh/1vner+b8TVJ7ru8Md6Fn6/7YTxbB5asTx7b8Oym9YxfsMau0wLCtMMEQASgCMoJUPBMgAlgoAL+6v1vA0z0fwENMEFpsNS0nvDQ2Pkrr+zBh39wj+bKvW+8FVhzz6Jfv1olTJoYb2s7XssNJl569L1A8p1t3vzcHr/8g3sm9DkBlhhvQls0/3aYCIrBM3kTTHjPrys0uhiRh3fC+7VsP/iF3X/5O7use/VMrsm4ylg1yetqCV5PSSOwD2I7oypEsc1nwOTb4KU4SLJgEkGSwMQ9CNfr4Hiz4nnhXGauTEMD40qpnSFTHCJxO8Ze23yfRPNZAJIGSYQJIS9fRmmdfiaIynYGfmRQR7wTxuNiOBWu4zBxOAEVzhWI9H8zLbmUNmJ9iMNEUIleSdznx/OOtO7hLqUvr3tR+oz1Pu4hJEbcwaJ198r0Lvj/1Z2nrbF/xetYCIWNMVDlqjx4KvAvv3TvhJAYzYzvfvQnu//x33oojCXrAAYvhn4tVPYDmFOC5tSZ++69xNZiQIz7AfHoteCdAItYJxIr39MhqwgTvJe4Pzc8srUDk7cpFzhyadfw94l2A2G3fhxM9q93okdyuGIHJHvDRB6EAJKn4/PLu3xWxcKqfhmjETsm48dwKIsbz7xuo6rtuK7T4wM1vlvUae8WdmjZYe8V69oCCiBwz0FGAUPrXoqEMUV4HhgYb8l1mrGCbrhxZV84Vs+SeDMYZowUx/v1Ei+IMAiAeB0iUcF72DFaaZhgrBIlnlKEAr93gSGBQ4QJywgonodj439iO7DguNrOOeuZuOANCwAlXhjvhBIz/3vw+GUbEGwYCJPjuQ7/kxL+hN716bWHtrD22OcXb+0/4wAgpEVdR1QIddHLXcAfOmdnBfsIk1ABT70KFfAhtMXxpVpSYQ9MukfXbOP6Z/ZIIAEmGzc+F8C2fFpawmOE2LjO1p1f2EMB55GufefJLx0kqxef252nv5RH80cZ+m+sS2CkMMB/4L8S4nLPwA190K536dLzu2hQsVu05mN0aVr3HV+9Yzef/WD3PvqNPJSX3smVOW8iTFgylltpBiakmR2VNum7NOq67AdqDpIdmOyABI+EMA2GLwWTNBDeKI5DMsSZ38m+bGBoyTrbY5jLPRIZPxf7dG9CU0AEGDhYuIa2MW5XBEsU63FIFTwThp0/u/2p9U5t+rl4MITJqtt1ff5jAoWM15EIiES4+P4IFG3zc3hnADkFE5+hMgUQl4xrej3Wc/Cf0+B0z0XPjXfRN7NlI6duemsvmhJTgU9dyhX9H5ocoy15XLECn5ZieDGIdY53sOj8wblr1j152UNiwItK/Qrdl/AklekhlBVEC65Q0Q5QAhzS+6Py9R5eh0jU/mGCcsEjWxmApPQmoPyDwiSGtQBI1OthrqSfiGBSAEQqOq2wssuKqph5ccAau+fc+M2fY3jqax6+ACTvCSR/VdBmf5XfZj8vZF74bl2H+Ul2WmDFOo4IF4wmSwwPLbm4Ht4J43XFMBnXwEBjgKiQrxa8KPFybgQNISlPzPq4r4MEJTDB8GvJ8REk0fDHsIwbQYyLnjdCJBrAjBFMGcJwzUQJVDLnJTDhmYEGw8hgaPkf/CfuR+fN/umLyuTrDh3OYTveC6GxxfUnAsMLO33+kRv3xq4FY1bEABE9kwx9FJ0YAQ1eRhom1JlwfICJDIGWsUKedYfJ2AW7KIAAEs5bufyhdSnjcb0Ik7H5a14pzzHPXv2tXde1z6w/tWlBbuv2F/JqfmfXH39nAzOXVMgghi/vR+8zhpf4b7neYUbuMSDSy47o7MnI0cyFs3Tpsd378Nd254VK2pef+oRrTMZWJmjQjDwAIwovdlTbdlTaRJh0RCDR/xd4djo1pkDioS08kiyYAAQHwX4FFJReWUYwpBSNKJ6HA0XbIlCAj4MFgEm04HJIJEDJgET7EBXysc4kA5OBsyqc3bUtldxvPf+9NxOmXxh9TQAJTYODV7IT2or1JO55IL0PxDGEwhweSjPRQwl1Jzsw8fpHGdOgBBoJOKK8LilbepZQjxTeFX1OGnrPeEiMuhbqRgDCxNJdr2+hIn/x8kfeIRLvhXAYHgx9W27IW7n5we93wmICEF4Lx3tTZHktIzRDnt5yuNTReVIef5kKTrTM2wFJrIDHa4nhr7RyQSTqHwYmDpGGlFjPYfADSI5nznut/iWtrHPfpncOVwomzI6YAGVHESQBJtSP0Hs9X14BAClhTpNqLWv6rbhmwOo6Zr2XOqVs+oTQdwJPA5j8XDB5t6Dd3pdXckTXCnUZIWSDsQAmhLtYsh5a6wwrUU+5kaWuBFARGnFA6To8EwYa49Sgkjsi/MO18Vy8hO+hk5DAvWT0mmQ0UqGuAJPgjbCO8QaKhKMw4ixZ97BMUsLGIGIcgzHk/0SAYOxSQEnkMEkMJ9fhulS8UzfinpXuzTXpd9I+supQ4TjuxX/sn7koYN+3tasf29mtD21m6ZYgcdaqZNjS8IjDqUS40M+Eeg5gQp0JMJk8xeRYASaEwUq0jJ4M2wAFngkwefTyT96ia/7sQzvWt+z7uReV9gNTl/y695VRH7z4va0rI0+eVIlv5JxPxnXvxW/s9vNfe6Eg1mMwbAohKqDgngLvJPkOsUVfRnvAhPlzqpiWYOKcrd94aY9e/U4l7e/0fu5YbQfGU16HAFEmQJQLGCisB5U376isSV6f5B6KYBI6MQaQRIhkQCIFzyLABK9il8eQLfZh5F3Uc1DqZn4dAcChEQRA4jlp7yQDFN0nDRLAAkS80lzX9BBXAhLAgZcBRMLUzIAgjCLMkPT0emfWRVp0Xbz1tfLYLQ9/BQCFAVvT9SSAIUAkwAPYMMQ802DXdtKcmHuFsFaECkrDxD0TGVP3QCI8Elhky49LH6tt/p+BceodUfdRr+duFiABQOfERQ+L0YSYIVuACxX01LvglThUniudKK2yjM2QqewHPnSePH3xQ5s998hG5HH3Hr9irSpQ1cvzr+4+beXy2Er0boBKvv5bgEloHoxyAyQtznuDmC++XnYsah9A2RMmCRCiMPgsc10jl340TA5VqpTviuEuIKL1LJj4HOtU5tYMOkDKavusvG7Aygg1SDVtKvmOyX1eum7MokiYgVDEIepIiuXtyCMBJNSx+NAfGFvCUNQp4EkIAHgnGJMYUsLA4JnglVCqxRDxLO+XdPlzUaLFGEejC1gIcR2p6HfQEJOn9ERi3rvOBO8E4x/kHoSWGDxCMdRdYOwZL4wlcX/uyT6GVMdbiSVsDB4DOdL/JYbCuF4UgAEiwIclgOCZ+V8so+fDtVjHIwFePB9LnoGe5OcFko0bn9rSxhMbmrlsdSRw/T+8CgeJtFMRz1S+Y2700zChjmPi5HU/jnMjHIALx0dQcM5FZTK8kuuPfvBzaC4cvR88GFqJnVi5b1t3vrbN21/ZnH4DuAa9/8ULj31YlYcf/9G9VuawAZqkDd4Vg3UyHTP/OXwHticw0bsIygESqUTXqO88bqNzl71X/vPPmfTrS5s4tWXVrfStESQaVaiQypuHrcLBoUKKgyNuCyrXOtuCd7IDEwDC7JxxPhxXsq1cBnW/MAkg2YEJ41xRN+H1E/JAqmUU8UQ4HoMZPJ1wLorbojEFNMy62KhSOhDAq6DeJA0SKtzjMCp0WIzeCQOz+pAqVz+zGzKm9IKnQp6KefbTpH8vmLCN+pSmPuYxYo6U88rrZ5QflNe0P8IjGyZemAM2eoY3wkTb2OcV4lL6WOo1HKYJUNONFkp1LpX5EThe58I8LqMXvMMjYTHgQi97WoB5v5Z73zlI8FyoXyE05r3zn/zatpTW1+9+bYtbH9nMuYc2fPqG9cxuCixr1qD/WyWIligt4ImkJ9vKDZDdytO3yA6N7Yh9hNeCIlD2Eq3C9oIJ2x0KSMY+Khsae+kvgkmmVZeDZDdM8EyYL6RARr5EnkhZrYBSNyhhrIassmVSRv2MYHLNB2PsHj+n0suM17EcLtO1y3rl1Qw4PCJIGM02v0rX1TGABo8C74QQFQIWGPARwYTQDkYcyNCSDGhglAAJpXXqUwgTcR6GHEMf5k1R4hUwCF/tBgkKMIkl4ugpYdjwPPAEuD/XH5m74t4RYSfuSaV4bNKKiMlHmFAxzHPyX6KX5b8Z7gVDmRhI7gOIaJ3Fb7az38GTPA+eCucDNUr2K5vP7eJNgeTiExvXe6ElVwhPCVgpmAAEtuVXpmAiL+OcMgdg2L77CxuX9xDDWghARJhEz4SQ1iV5JrTmuiJYDE5fVsFBbr+OiSCiRVf/5EU7pUw3v3rf+iY2HHDMDT8v+N2RV/L087+1s1c+9HfJd6xul6GS51DSiGcCHJL/q/+OeBfA1uXvKNR5BPBIgkmp1NQzb7NKc48+/o29+PJPdvnWx9Y3uRoAAjCalEYbB3xZ0ax0IYVtSj/aH2ASjwUoevd8myyYMGeKh6YEAYDiXglymIQQDHO2ZwCSVgKSEIbCg0DUGYXfzDMSYJJ4INoWw1mxLiUNEZ9hsYfh4s9az+Qln4eEpr1Agns4EDDKMkwZmEjROwE8jFCxfPlDuyKDunHjS5teuut1KewvllELFe8pmAAHAYWwVl3XaeW3dXk311w9kxv6DyrQYFiVLhD5KxsmNLuPkHDpeVjGfl2xbxfbYquqAqTncagkoTF+O4h4VtYFzYwXk4IV34Z3Fqc6JjRGhT5hrOF5FXqX7thxeSCnma9F3vSGALP96FfutdxRHrn90R9s+8kP8lq+stVrr2xh84UdX3tko4sCiwpxzSow4a2U6lt6+Ivnlqicz5aDgop6KVbq51Je3Q5MMiBxLwVQBXigsJ1juC//OQIFECdKgyFRBhba/7Y+Lz92AEvBRNBIFFp2AZQoKt0RrbiSMJeMeJG8E0JbJb6UkZThZARb5m/vGF31ljTtIytKtHPuiRyV8QcYfq4MI+M3MSsfcMnTtdnv0NI9w5DyOl77MLDtIwEmTLTV0r+shEqFPc2Gx1QSO+7GaezUtvUxdIYAAJAwxLQC47y2IXr2qhSjDNHQveCdBClNtak03TF6XushxISnQb8Hr3+RF8A2wMHQ6QyJH2GCh8S9mJ+DUnZT32l5ECeUYUJpeQcmoWe+z5+fKMCEY3arMNkf5zXhPN47YMSo4rlw71MXHnrl8urWBzYhsDCkfNUxZTCBMsBEz0BGTkJcGHs8E5bApFultPPboWkwMJmQIYhACDDhnB2YUGfSK6Nx+eaXHuLauPapNxWu0LU4xuGlZaVKhbTu6tGxhMUavWVZaB02eeqavIVv7dkXf+ctuqgop46INMKcNBXHdG/BwSGaQBd4UpDgWwB0pnPunjjns2vWdXEOcXmAMmwtfScFrJv2wRd/bR9+9dd2YfuZtQ6cFFD7HBiVx4b1juSROEyCypsGBCIVhrRku8Ml+V0qr6WQb6L7U19CD/rghQSQRJjseCkstU/vqkKQRQEGifQbyKDXYZIAhX2J8FrcK+C6ktdhJNevFrSPKd32H78iQ3jbTgjei5deyON77EOk4FlQiR69k9hRMQ0VvBPG56L11sL6cx9OBZjQnJ+OxgAELx6IOEi8Il3nAwUJT59m/90qMJxeZ475J/qe28ozKmAozYT5hCgwvQ4TH5ZIRjW7f4dDJQFLhEyESQBKqkmxazdYogKQEpiwX0CJTa+jx0JYjMp8Ok22DJ2zzvGLep/bNnb6ls2uPnSwnFU6v3jnF3blkbwVWiU++MY7w1669wsHy1mB5dTFZzZ55o4Nysa0yKYAeTqnUmnv8Kid8GbFyJsPAwpt4/fRmtDk2JsdKw8dkXw7x9XyvwESUAUeEjCp2wFHoQOFbTpOKtB2H+7H9+k8P1fSNpegsNNhkmsCpqDQ9yWl1HHx3LReH7hyRymYCCQZyUtwgKRFj/fQSgqPIi28C8ITlCIZXwpD3IqhlUGv0LaCBBx4NT6eVOKV5BHa4toOEzwhgAa8QrNhwkERJkwJ2ioweJ8RgYRETvNjQmDTyzcdKtwfmFDax6M4ef6BjPCmNcrQEVagNDW5eFOlsNsyxje8uTGtxPB6mAGSAQoZ8Zbn9/DayW0Xhrxn8oKHmfoEGNYxiLS0wigS0osl5ggUBp8MA1AybhiNDWjGCkwCMFhH7DtaBTj6Mscx4Rct3vBuABvwmjt3z1avvLCz2x/6GGWMClArmKZBgnGPMAhgCPsiTHrGLsjYvvKWWR7mOnXdj6OuhCbBESh4NrToosXWwNRlD13dfvpr92qauhe95RfHRZgQ6qJPCscjIBIhNTB9yS7d+tyefPY3du3xd+6dLGw8trmzd/SOVwRiQi+6nwoOAAWvEgFR/jvfkQnRTl247x7vwOyGQ6VGng2DfXaOLNmZSw/sk+/+nTyTP9rZrUfW3Ct3vqbbPZLq1hF5UtSXDOyCSVkjsOn332E9wKW0EZjovWVgIo9EaQfPJEKFbTt1KInRBzYy+B76SsIwbsAElGyYVOoYRj8Iy90CMJnmuF7BTf3FrLyWOWuUFzqk9M74Y+evy+Ax1Ptj5ov5Qmn5noe7vHkvYTfurwwOPLxJsAxFhAnHtMvjPLX21ENcF29+pfT1yAta3I88BkAogLlXQkW60ghiHXAwmOM5FUyYBGtq6Za+x3wGJrSIdE9mnzDZBZUEGhnARCXbHSYJPDIQETTSil4LYbPYlyeG0DwcBlwSb7JGXhqdGlsGz6WGerlhs2cf2OLlD+zMlY/0Hz+V1/KlbT341rYf/2BXBJiLCVQWL79wsHcrnwAnPCDqcrgf/8mHdOG/6f0Hhf8OJI8ClKoAE0CD8vWNgEOhAOLehZYFgCRR3MeSY8PxAbCZd5cIOPj4cnonMQz3tlCce1epY9PKDBmzh945KJAcIryVhglhpz1g4kAh5JWlfObMkPFnyl56HgOB9uFVa6TSStsZjDCMIyWQpL0Sru2hNMGkolv3p3VZj4wrmZvQWYAJYuA4EiaJu0IZGZjQHHn2DANAXlJCF911XUJcVNyHKYCveEyXYbIZcG5OiYTe5sdXmDXukXcWZNwv5p/Hq2IuetQ1dtaGBQ3ggQfQ2H3Smgh7Da/oXhty7wNohk5c9lIz3klsgkpz1Xx5Jj40voACJDwsQ+Vuo95DHdCgtRneC63kul2Ah32ABU8NKAI5YLkib+Tc9kcqDT7S/S/qeU7JiKsk4+9R5zk0AkByidZXwATvwnvAe2uuG4YHAji8zgRhSFIwGVEpeEtGiz4kq8o4zcoswCINE84FKGznPmzLp8Oqnok6F577wcs/2PUn3wssn8l4fWZr8rDGTm4qrTClrL5l26z36CedpGFC02lAeum2zrv1qZ3ZfOrTEFDpfmzgtI3NXxLsXtk3v/v/2fPP/2Arlx/IW8Ej7nGYVAkmACWCJA2UtBwmOh6YMIhkGPoDryPABHDEpsHUmcQWXrFCnuMYAt9Bo2OCIQM0QCbUk4RKci3laewlYBJDSyy9tZSuSWiJscbmlGbXmIhKpeTL8i7vvPiDbd39Vnngvg8jT8gMaHn9DJ6RDKnXn8gYABOgwn6m78WjuUxrJ3knpy88U/pf82eI9YsRJA4FrUdRAY9nD0wuyciSj6iEBxyAhLByLpikOy2+TdnAeJNegwng8PcfPBIU6lVSSoAS67tiZT5wobVYm95F//EtG5b3Pi0PBICv6v8CEd79pgpjLC/d/drWrn9uy1svbf7CUxtbuOVAAix4QJlGFCyT39yPZ+JZ/f/ugqX+QyPhO2AEMGTk8VZyCI8tgGrn/LRi2M2BksjBkNoXtR+YvEkOkwMy3gepJ9FyvzDJJSrnSTzETlsGVmSMLyjDb6jkeM5j6hgb70RXmXgzMoIe3ioVPFQKP+TNkbvcqIZ+Lt1KfCNJ09krDpPOsTX3SBDAwNgQfsK7oPSO8fW6lJYpL9HOrtz1c/FomC2O6UNPrT1xMZkPw2MDFnrXDwkctEbrHFkRMM5Yt8AyOL1ubfI6alplNAQIVH1sUiXfUw4ZWplN6d6E2ahHod+ET+AkY0SoJoxoHGASm6KWeMmXbb2u/Breud69vkGeIJJfQ7NpvJQhbxHHcy1efCqP5CNbuiTXeuGGe32MNuyNF/Rd8vROAQZGPBsiURmY3Pjcnn7yt96Tnf4hEQRpRQ8Fb2ZoZtMu3/pSx//gY3QRzqLlGM2QuS7HOXyS68Qmw9EjahtcsYULT9wrufIAw/WFXX30rda/1bu/q3Qij7BfhlLQbJdnWN2qzCTPgHdInRTfn5Demc3ntiEQcT7Lc/LQTgoyZ7ee2Z3n39vXv2V04l/aiZXrVtuu/1A/IDiNWF3HhMA77cvqVr2HpM4kLjNhLoEEAXuGpo8QqVQpvFqGEs/DvZEEJg4N1mni7AIswAbjRj2AxLsAQHgueBiAxZd7C2MeK7695ZTuQ4V3i94jhu0M0+Xe/NzOCyjnVDAAJngXdEIEHlTCO7iS33FoFTwShqDHS2F7q2DCmFyAhCFVFjc+cG/jTTAJQw7R1HrGh5o/s/mhT3zFFL7kLzwpjo0wdI8mgcmu1lxvk4xTDFP9OUrDZBc8AEtSFxVBgvjNfs6J5+Nh1nQxhtiSwHLeemcu26g8+RkVQk+tP7MVgWVdIN2Ut7JFJb7eIZX6NDVe3vpYxzz3gSwZ9Zje/D7Ey9iGTwRGfxY8GMBF6C2CbqcOCMgEz4OQFe8E7yN6IL6eeCRAg/VskERlgCHoBKW2Zekvhsn7lTLeMmSMyRVac70NJvQ8R8w3klLliFzccS8JURFIyaebyi4BhQ511fo49LY+Wh5K0sEjEUy8cl4ixOWeCTDp8L4uhHyolxg6vulQACah7TudpqaUaWY8vBVnZyTMRRNjlrTuolf54OymrrHiiZ3KwpMCyInV+z5KL4YZUScCHHrGz0lnZXRXrVcapO6nf8Hq2qatsmksNDioH3Kg0AOdcBdew+zKbYdaPd7sTJ8iAADbUklEQVQCBgRPjEp9r0ingpkhZ+jrQL0KYa8eJYYeJRQtBZSjVYA8emZ4KH0yIpPuXVHHQMkez+TE6l33oJiFkpkWqYM6yigD+i7ReO+lCJOLKkU9efU3dk0wmVlMYKKMj1cROi7ueB3AhD4sl29+YdvyZOgg2SSY4LFQT8JxrggTXYP78Jt7ApUWZUaaL69d+9jOb8sQakkdCv1BVrae2sDsBb3rszZxYtMm57aVVpYclHxDCgzUmVA/BbBjndHWXWby+1bP9JXdevq9Pfvsj/b5L/+z3Xj8tU0tXJGXM6nnGxVApgSzk/qmy3qOE4KMStXNw3p3gAOA7IhtpQ2knVAXhxE5NkxzUxWGehc9hBVgAhxCPQr1KXEelBJ60SN50z6KsYyoC4PqBSD+UxDGOCOulVIGJslxrFNH0SWv5Li8akIrS/QvUkl5Wcb8+pNfK318Im/1iu4hUCQeCU2ECWfF3u8ABZgAFY45NkBh64GDCJgsXXyh97yufcqn3sKRUJf+VwIEAIPXEWHS3LfsHZS3ZUw3BLdW6tIEw1DQk0fm+UBpiXP9egAFyMrg70cJGP4cpcNcGbDkgElUBiS6bzDWMtA8u/4LhYaqjnkZ/wVrHjhj7QJLn2zKmOzGHHO16Bucvy6vmdZh8hDpu3PlAVMWf+/1Lms0N95+ZQt6v3MqxE7Lg8R7GZq75g0BCK3REx9vyEdBbg/DvPBMEaosY2jMPREHS/BIdoEk2bezHo5zRS+G/fH85Ng3w4T1tyvxTLrlmcgzkGLTYCrhA1DSikDJ7aEclpjNkOlyq/SB6vVi2vSSqJTtUIYk3MX0sAUMTVJJeEsl8Eoq5WnBhVQar6F0Th+XdqlD6wO6zryM6jnB4oLXaTB0S5yqllZUGFyAgmdQroxM5TXTv1LvMXbyqg+kSMKn3mR0/qqMM2Gtm/JCNvzZGIqEod+BQ5e8kYHpCzYk9eueg5MC4vCyHes5aQ0dyoR4F7UyRPXDMlgzfs9R3eP46j33go4psVUq8TGrISE3WiFRZ1QpMFS10uoLuOCNdCpjditj7sDksP73wfJO/W/t0/9u0D0Joy1fei43+pUM6SMHFh03uSZeSX5S50Soi/fKCMK5VFg1YuUqGcY+I0/oWOgwua3/oveofVEBBJw36h7I2Px1lV6/tiv3v5Mn8Fje0oL++7zXkQCSeI8S/Y7XcM8mgUmDDOGgSnUn9I6OC4an1x/bpmBw76Pf2vrNVwL5JfcA55dv25Iy58DkugOERge0+uI7NkstggwDfuJFMgLx5r2v7ObTH+zJJ39tH3/7HwST/yKY/MJmz9yQp3NK58yrpL2kb37RZpev6hszX4z+HzBXOiuu7dPz9bsHUyr5UjCpaJlQxl5QSVKFlNM3XAAFg4JH4hXSkkNFBRrv4Nio90BrNJcMLnUuGYWwD0aVUnup0gbQpUCEwWUaAhe/JRo3+D4dwzrpieHbh05cccPFaMjTKh0Tp6fynSFR4thaxTIY1JW4BJAqSt5a8rtcxrVIMCmTcQI2NCmeUKl54+ZX+rbf25nLHymPbXjdojct1/f0sCcQSNYZXYElz0djFjx7n5b33jde0ONZffQE/R+en9+c6wOicq4MGOG2OKzLm5Ru4fXnyq/lcKEQoHwJVKXQjDgorvtxqft6yzMgyHdLvjffn/5BtbJlDKffJRsyxCRgK/d9DDH6qKzf+tqbGF8V5K8//a0P90JzY3rf0wSZjpLM43L26mc+LAzDw/gQL8pnwCV6L/T2J0xGCz9a9vFsQM6Boe/MkubecZ0p1PNrabWKB5lsAz5az0jrmX2pdQcN0rUcMtwHqOg3jQni9jeJEJpXwIdKeAHEQ1y5QJINk9d1tHJQIBjyREOmqVLpFW+gc1QgGF9zg01TXVofUWKn1U5RLaEGlQSPMUkUiVQlbJXaj1Z1ugpqerVt1A13TQeZQx9cmRNDHY01Hoi3rAI0MrJcl2PoYDh0glZDgkk/ra4WVbplStG7NqyMyWi4DbixXSd1/eNWIy+nV2CaPL1t0wvbNjyzbiMzAsvUmvWNr1rn4II1damUQj8EwlYyHLT+6lImolL/lErthPboyEV9ToUMDX1FeG5aINV3Ew+nYpJQVldGR2sE8aquDEwOV3Tpv406QKnPOa+S/LmrMiAyojQK8Am0ZLCASaE8k0K980JBHEXDnq00TC7Jy3jyyd/ajUc/hJkWgYkyfgXGSwmoFMOhc4AKAD6x+sCu6tirj34p4/HEajtPexilggyoxMt9I8i4FgIkrAOYGgGJVng+zpi8R0KD/B/6nmze+1Ie4hV5Pxdt4ex929j+WO/+hqBxwRs3eAfY09f8f/Ptq+SxABi8M8BEZf6dD35tn3z/n+3r3/2fdv+jX9vZ7Q9sZvm6TS9d0/PesfNXP1Cp8WOdo2u0KcMJJIcrOpS+upRWepQG+60YmOCVNA7rmGlrUyEBg03JnwrWQXlMTfKuMSQYFQwMk6IBiwASveMGwpdpaZtUQFqXKNHTDB2Y7AbK68IIM+e9e3pKS8y3PrV8R0boc1u49IENKv0OqWC0cuVjlYK/txNnH3uzXoeFjCLgQJUJVCJMgI33IdG6zwV//Kr3fgdIeDf905tJRfoOTPy3np31KJ6PfiWEiq+qUHL98S/1vTaVvo+H/6j9/Ef+Ax4NY9wxajjeSdrAv1G7DDsl8P0rnrcnTPBa2KZl3LZb7A9AyUxXgJLfQIVm4kz+h8fSMnTW57KnJz6hLQaZZMgWet/TjyX0vv+d3fnor8OQ+p//e3v6xX90Pfz0773zJCEyxg87eeG5za4+8qFefAwxXZf6Fzpmeh2MCnL8l2I8qAQmQOGo8vhR5bv8mgCUP0vABTCkIOHSO32bMjABJAxFnxsgUUDjdY8kKsKEiniaBsbWVoSpaAmFcaCSHE+C0jVGobH3lPYvCAiUQBkPSBmukfqCbsuTkaU+gToGQj6Vx5TJVAqkLoI+CQ4UrTf3L3jTUZYVOiZ2DKTDH/fsUwmzbfistCojcytUyh9n+JHT3o8CI1Uhj6ZCYMIzASTHl6/Z2ImLNjy9ZhMqOU+d2rQRD8ecsbY+JaB2JUQZEYZDoYHAxOnrtiQPggzV2EvLseO6/7yXpnk21D4i76hXmbuVfiPywKq77IgM2qHKTjtQqWW1PMLqPj37iIz4SZUar6m0+MxDQ6flleB9UWKnXoi+JzRmoHl1od43Ia43hbnYBzAIcxGyijA5foY54FWSpESclIzdkCnTU0LGiC1sPFMJ69feaogKxrpueUaCCUNuFJP4kutzHw91kQFlcAqSbRUyvrXtcyrJnvJvTlpgSt/bH/zKth98JS9x20aPX7bltYd27c5Xtrb9kf9vQnt0zKRFHpXwhLxo7RX7/3QJToQnL8hre/7l39mXv/k/7d6HKgU++NrDX9ce/cJuPf/e7r/8td189q0KFvSFmFaaUlqWN07jB+qwaJoc67JKGkcc/szQSBiJljwLF5/ZjAogHfJgiaHHinifH0XPUyTwM9d/gWDCNM0+VTMt+ny7SuQAJfFQ3DtxmJCW95D2uSfDu+SbyAOkCfv82iOv9KUiGLgRZlkXXC5c/1zAvemhZSrXqSMJ3gkV+omXkogQF+LbUVnfP7PlLZWAybquM3Ri20NqsZ7Dw1MULiSv90hEYZHw29TiLQ9/3n7+W28Zybnh+NiaK8CI8BiznPr0DhhyjPXbBPxk8FGsaN+vdoW7kuvtqj9J3QOxvmu/3l2YXiCENF+TtscGGNShUb9CJ0kMPl4FvfAHaG68cMtmVBij/mTlyit9L6VLeSoMp//os39nz776T/bsy//kvwHNNXkzhMg25cFcvvetvs1nHiJbvPShHT/7yEZP3fTe/QxS6eGxgbPmY4m1zicgDSEvAEBILM7bknPultTvuL4LIIlixfxeCmGupM7kCPF6j9knnkm29oRLlghdUamedDhkcERaY9G5j8pwmt9SKqWkiRGg/8bg8YvSuhL1OQGFVj1KhIJJYR0goeROJXy/MsCwq9Cb0fYqsTLAHxX+I17qb+qTh9FNc0hKQiolS4wY6815ZXRaB1e8VRQlXXqQAzX6UISSNK2XRrUcsfahRZtZ3Lb51Rs2PicXdvqsHV/atlOrN23ypGA4sWo9o0vWOnDavaVgHJlrhUnBnuu/bAqUy153Qk95RvztnRKE5N30TtEv5bSXjgtr6XRJWLHTDqqU/L50SOsFem48D577pIzr6taHXulOi7WW/sWM5+UdIPHs9I6DhxKEN4BXEDwDhEGXMdM+jDz9TC7d+jLARKXJ2eW7BgAAjYdZMHJkeG0DJjSkOL3x3LYFHgbNo9RFpSEtlMqUgGhOHL0Qlng1XI/fwWPRd0uuRakVTw74Euq69fyXtnX/Sxs9uWWDU+u2eO6B3Xzwrd16/L3dfPpLwUYZ6/4v/HtRCU8zcdIUUxOXykj5yMn6rosy9o9e/bV98sN/9aHnr9z/Wksg8jt7+vmf7NkXf6N7/aBS+EU9g0pQNQMycMMyprNKc8B+2dMQ3iDphvc/NHfFw0lntj5SSfGJnveZPJvL+q767xgRvSMMbQhjARB9k7pBZcpB/4Y+5z9AASbulei3YMJ79VI7cqhkKdmXCSfxXXQ/vOtFeSRX5AWcOP/IhuWVTKkgwJzqhLr6puhIOq/rUzDAMwEYeMezGbFeqswPrPBeOL5HRm9VRm5bpeeNm/oW89e81WMMbXkYU2JJyNLDl8mStDI6d9W27v7C7n/4B1vUO2ruXQoFCX13PzY5n2/m/4nryuBlvIY3KHoXLs55i3J7Jm++z85xyTYHUJS2u5KwJgUtfQsPdWqZmfgOr03fjHPwaghJ4T3UCNY0OaY+BMNPL3ymH/ZJwK5+5sO30EGSUBheC+OFERoDNnG4Fw+N3UtCY4x+LOATSlu89JExOVicvwV40W+mrmdR+fNUqN/T8xBWLAAkevd5KeXX0EAIwAjyiVjfJX0/Bw1AeYsynkmeQIJCJTAAYRmVDZM3a6eTY1gn89MLnrg3IQ4ggkEnfINmV26pBL4lsMjgD5+UoQUQvTK2wKTTVVgreAgowQAToiA80aeMP+iqaZ+SMSCcpMzTog+rbYW1AzI21KfQPHnF74+HNC2jf1ylzD5lziplrmAEkYxe3bAd6z9pUwubgsk1eSSEuc4KJNdt+cJdeSfAZMX6xmnpJU+o77R7WVT+c02MP+EXIILo8Ig3MTALMFlqn4xXVRveE14cnTSpr8Iz6bTD8sJKm8cdRoTNVjZf2MrWCw/ncB9CZnTqo7lxbGIdYbELJkoYLjJvst9hoo8OTGiZlYHJmXtuOBwkUibOrUyC0WzqX1aJ+IlccGK8n/pUqzSf9JKcjnWjo3sBLu5H2AugEN4q5L56xmIqbJUZqX8BKLwbhlW5+ugb27j1qQoZG/L4ztkpvcPbj763JwLD8y/+3p59/ne2de8rn5cEr4brhFGdib8Puxfc0H1a750BHn8v7+Tf2/oNleT03i7c+MRbjz38+A/2+FOV+BhkUt+hUl4NfXwABqE00iLi/Va0CBDah0fJFAqU+lcEk7lzD+UpfWh0zGMIEbyFUFJXCTzCRN8zXwUdFGASQJKuP/GRFQTBDEzeoDh3joe5lE5p0k6z1G29n5lVKnBvOlRoIkzrIvqH4Ck4rIAF0jsP9TEBLDw3EHRA6TdhaMKyTBlBqOry3a+V7m4Z00iHFn163iQtsdwlYKJjBpOWfvRbYgZPBhKl8EDY02FCn6ckbXia1L6MwQcCiTH/KbQLJn/BtYFC+E1Yi2spjQscMdyVDRNmWo0wQdw/1lcQhgJSFL4cMCqIARY6SfrYYcmQ+sDhjKDOMC9Ag4IbLcQADuGvOKYYgLn94R99kjAfAVmQ4Rw8nzF5p9Tf9Exf8tZnjX1MCBbq+WhJB/TylK6OSsCF5/ZZYvVdfOrxHMoHKPpmuQCSVgYmRyq7BI3QvyMq9nuIrbv2I/qGHCrbURzZlwH9CE3QO55e8XT2mz1zy06s3rHp5Ws2eGLd2kYYRHHaKo5RihPcBJGj1R2WV92pPwtY6MDHM9J0uNOXRynJywBTqV15bFznjonGMqj1of8GHdo6ZPSbek/K/WZwuwWV8Le9KS/eCiWr0ExZmb96SIl90Oo7pm1gatUmTm7IM1mzsRPn7aTAcvrcDRudXbN+waR7eNHaB6XhM96aa3LxurfoorL8mAwlw550jp33FmjcJzQQUMlE3klz/2kP2dGfJHp+3mFUkKRUW9U+6w0NqGwnzEPnPgBMWIfRAPD8eKc+wyAGB1UHWCAPNylxoBh+QsxpgqFhOBXCXD7JFXUmMppkcAwNwhB5hlcmIePU9yzYtI5ZlsEBKt1TlzxTeIZTAvWK2dR9vBTLNhIo901CnoR2vLWSMmGjrslAoKGF2nOVjs/LCK3Y3PItu/XoO2OK3+df/r1r46Zgo3dc2Trr16L0zrWACv8fmACmm09/ZXc+CKEWvE76AM3TN+XWZ8Fbufe1V95Tx8aQLdTdzSgNsh9N6RsyWgO97qlbO3P5A9uUcQVMFBTwfmiaTt0PRtrffVJnQlgrT4WXILwTpSdAou+FChOg4JnEMNHblMf3BCb6Jrw3GnmsXfvEO81NqEA0qf95cv2JPKcP9X62vG6SFlTpawAOwmbegiz5tukQG50mGQliRdegzuOqQDUvcDJiBMf7t1ThIHoYtO5L9ysi/zDA54aM2cOPwogKtNwEVvQxcq9VxwYPWeeRLmR4YuWuh2P2UPqYn1IOGxm9t8qP51mV1khvAkq6ZV4U63m8J75T0sSY+8SpgVmyHkNuhNBCJ9YwrhrNg/FcOsc3rH9224bkGRIam1y+65X69MgHFBTkCH8BEcJhzDzJ3C2IqY3xZtauf6bj6ET5gY+MMHrqmvLrRW9SXtN50qEC/Bwoykss88lH2ob4HRXX8/TNcg35kq0Q7gImFR3yIkLFb4BKWmkvJYImDZuUXhtxWFCR6C9ytBJPYlgJeNrrNrplQPqm1+W+n7M2GeeGHpVa2zBg9AindZOAUSWYaEndQr6Up9J7eNYOO6rnzRNQ8gWYYnktVJ4G0RO/31XaMKSSMC3L6F8wJSM2b0PU20xftDieFf0zvBd/NWOGDVi1gNQ+IPd/dMG6hk/ZyOxZm1+5anNntj28Vd82aXW6VkMnzZ/n3eMhBEMYj46ahPRaBs7ovzHEy1UB56w1ynBxXBh2RYlJkCuqZ7gVeW8JUOiPQodHetLj6axe+dBW5ZVMLd3w8Bz9LSgF0yM+jD0WYUIpXTCR4XZh2Mn4Lv1mv7ZjnDAulEQv3frCHtE0eA+YePhGCYntGBzmUSfE0znOUPinZZB4Fgx6gEaElhsMZSAPj7BP8g5syW+uh2Gkcxt1WAOzYRSBTr27Xnmtcyt37NaTH+zZZ3/rnsm9j35nS5ee+rulDozJ1Qpq8VypK6PF0JTXSS1tPLW7H/zGZ3nk29KZs0VA4JonVm7bhWsf2+btL/TtL6uUr0SvgkOtPJPj8kiuP/rWbj/7lS2uPzY6TdJCsFsFAXrsM80w8/IAd7wjANgvUBGm89Z/+i5AvpzQWYPeMSFYpaG8GnmdDI+ThLeQV8J7KTCUBOP7dYOPkcdo8d61j+2Mgef9tmSsqtvnvNHIJXmHeA8jMhLAZP7CY5+auE3eAMcACM71967rx3fONRAlbLbFe/Jt6VeyzPz98kyACZ0PqSdzD0nnIryU4G3I+AgSFFqABNBg9GjGY2MKaEZUoE7O81XFoB8DiNLhLqa+JnTi099SqsXwSoxbddSlfWyX/JiUPIavEn96Wy6lWyWlFZvB5oRHlgJ8gAkwkPj/fB8tM9skN8T6T8DHC1h4Jpnzd9+PJr6xDifWy8ShdryzZNeC10dS70IzYcJW1IkQwho5eV2AeOwdI88xSKW8l817cVj939l1weTina/tEgOt3v/GCx2klSV92ymllX55kMdUSKDBAIXE6HkAlxiqc3gofaL4+4jy9CGlw6BRn3HSpd+sx20+crLe/TtHyttk+DuCEqgcdg/gzxFNW0PnQ6BCX5H3itrsveJ274h4VIaT4UQonVe30elQ3ogMfvAoZNRr+5UZMbCATcCgVRfLREcdJO2+ZD2/qkvGjBY5vTJgfa6iup3fxYIKA/5Vtoz56LLdMkzt8h7qlPlI4HglDAVTUCUA1fRbZdOINXfPWFvfCTvWO2PDM6uCybYdX7piHQOnjD4m5fUjViXDX9FMaZtGBrTUYmj6Ey5gMqCPx3AttCKjuSTxfUBKnQ6j0gaYUNckcAq0DHxZ3zkvA0jo5ZYxZIr3dBf8fC4TSrmUggnvCCgMr49hdeMEMCRay7COIXHx/0gY2u4wkUHpGr9gFyNMHgsmMlIYHC/BJjCJBgnjxjqGql4eAK3UOIb9QToGI6F7B8kQcl5yrl8nLpPtlJIxYrQEapCHQsiL5tV4H6fWHhgzJd4RGOLUu4sXn3iokH41YeBMGl8ET5fwacfwqp278sIefPR7u3SDMMuqVdKKrmXamgSVYQFkWde4LDjMyCNtFOxL5SHU6jsdlyd07cE3dkcwWbn0TGnihNXIAwI62/e/ds8J75J6MUKWNIgA7oyWgDc6fvqq9apA1NhPpTyGbGgHJj4mmzxFGkogoMK3cYOaMvQyWFG8K7bzO1+ZF/Gb946Rp/ntxdtfekuu0dPyhvXtxhdu6j0u6n3ISCXXyHz/eB8ZPQcJ+/heWpIW6E8CTKjr237wnaeHBYHZh1TBm9H1kNejYZD1PHkVASZ8d/bRGZm+Snglt57+2ju40pAD6JAmMjCRAkyCwfdxqPT/83TtPBnao1oe0T2OaBtysKTg4MsECplmrMn+XNoTKBh36lcSA/+avO7ldZjE0vteCh5M1rUS7dVvJt04IA2YtPB0qNinmTBNhql89wEqF297hfzCpReG13Lh5pcCzBfeI//aE3npH/1BXsufBJpfeyHkjDxs8vrQ8Sv+feu6mKGTRjR6DqUFTxvJf4meCR4XMAEcAMPHEvNtACWChLnxg/dCIeCdI2WtFoDSLhgglf5lqP8cBZjs6GBZh71f0m4/Lzzmeq+4zdcPlnFs9HxYAo8QuqJimmabKI+lruseSqKjlTsgKdCxRcBEACpGtTLMKbG9hJAXrXRUgmzpPSWjrdIApTg3gNQ10Lw2wKRC3kxDp7ynnlkZo2mvgJ87c82OL25bG0ZDxoLBLamsL6ICXEaCIUAw+FQu00YfgDhMPKMvKJNjeFVKkxGkSS+NBqjoDaEu+tno+VTSbhWE6BdzSoaDSndKxXg9DF5Z4udjbABHGLsKI+UZFCOl/+Kein7veAZhn3suEuEZxibDID2mzkSJjqadmTi7A0XCeChzAAuvO9G6Gxft49jYZNWP0f3TioaD8/zYLHGNWD8DZOu8cQaTn4XWcGvXP7ELEvPFb93/hTdAoA8PfYUAMvUmNOpgpAHUM74mz+OVPXr5R1u/9one4bKMHPF8BqnU/rE1O3n2gV288ZktXnhiXfKyGM+sqee0YHLHtu58ZdcffmdnZFCbBEy8Gr4Bs0LiHdKRlWbjeId0bqVejMYDhCGZtx/wd02eV8lyVgYlhLuoM/FBPR0mQWHKBclDXbyb8I5cel+8G0J48b2wzrfjXdd2nvIGAFdk8DEY9MRmmA9adHVPbjiYOc/TWXz/KcV3z71IL3wnvIcMTDaeu2dyUzBg4rO+yYv6z3MBJIi0oeOBQ2wCTt0Y++i8OnnqhnsldISl3xKA8bo7HR/qWPQMyX1p/YdXi8H3edP13AUyaCzzZMCP6prIvRMd430pMOzJcpdiH4sfKc7NridxOUjS9+BYPa8US/B7KTQhznFNKdalvEk0UQ4tynaL89nns2niwbSfDJODyWth7haft8UHqHzgDTTOKQ9sKt/c+uC39vjTv7Wnn/+9PfrkT3ZLULl89ysVUl96KHOEtKOCJXWANSoskubKffQGPCzqf+J/11LPEAVkgXIYtDJ4memw5DuHS1rsEBJUDgEVB8qbdUQGPa2wvUPno9Dh8CASTOjNDkSiIkx2PJgd+AAjgBJhkksABkWYuGciaBRRKS8V02/AxdwpYTtAKU+AUtmkjEu8WyWs0EdDMBFIgEmZvKPaNpW4BJT6jinrm1j1ZsKzi1cFk9NWTAfLih73ZBiMkYpwjBrNgakLIBMSv+6fvmzTS3e8nwaZmLoNWrQAgzisfJ4g4vUfeoYaQcjHoDp73+P1tGCiNMx8LEAIIxpa/GAw8DaUqf16+4cJBqd7Yg+YKNEACDwPB4d+s909D4nruCHSf4nHsoz7ozJGTMdFI+ZSwuT5gQnnxXvyv+k8yjhpy8oMJHSam7JO5fe5q6/0Pl74Nt6xV+TrfdfKgFKZT4fT81de+ojGZ3U8YZcy3QtV6r8w8sKkPMTVzQ9tSQZ5cPqSH9Mhlx/IXFGJ+vqj7+WZvPDtzboHMKFFGEPYMLZc7ABLqOvk+YcOklMCPv1/li4/s+GTW1bXM6+ML29CMPE+JgzkCUiAvtKIN1dPvj1jj/nvxGuJ35b/gwdIYYR05PVD+h/AZFGwY3BBhk9pFyDpREnv/Dod71PrAnodu9f7Z9236xuRFlnSAKVDpdSFC0+9eS+exbkrH9uwSq90NPX+R/pGKPQd0jdWOouQYBt9iEZPXPV5bD766j/6cDutAys6jsJWONYhkpxLh2YMtRsfGSdAUiBjmq/0hPJ0rwgTjNRbK9ITAOTelwbDbuU8PqVw3E8Dk/2ISnpaX6UFZDL/T8vY4gzI0GIMsPikYINn5bVcsD6lbe9ALdtBPdim0vBNed13XvzWvf1bz38tqPzKrj5SoeTmZ3b6wmOl6RsekqfbRIPSeK0Kd1Udc7o2DQaO63eAVxV9yxhNQffFi+KZs9+lw+RAYaO9X9hkBwSUAwLKwf2oPKWytpQABQogARoozCuPlxK0M8f8Tj1LDJW9Xm/zuo5KeVJ+lQx7da8yCOAIClDB0Pf5vri/WBm9jObEyuh4FaHSmmUIcxVW92vfoFUynMaxcatqGbeu0WWbWdi2mdPb1iqvpgiIlPfIjaf3fhgin2bA9PCnMhNPhN72vSrd0SILsBDOIGQRQ1KEnVjPq2Z6YbybcaM3Mb3zCTNgxJgPHgMW+laM+TkhNKKEW881MFaCiAxR+rr85jgU9/n9JEDhMEnCXFS6YrRjmAV3N3golIaUSPTcmfOT58+EZnQsoRMP26QU743bzLFRmesDE0CldX7TLwHw4oIzzA0jQ9OTmjHdaG59XjC5cP1TGXB5FQIHpWlExzpaL3XqnS+uP/WBKE+de+TjhlGidiMqw8WcKoxyMCsvhOPwRiYZX0lwAj6MhswcLQCJymSmKJ7Wd8MzObn2wOgPRYgKz5Mw17LgQb+Wi0nFPq3RxpU+6nvnVXLTu6IlodKY15MIJoTlWPLNvOVXsn0n/BUaJ+DRUleBQaDVGGmI78C7pI4Jr40xsKhwb2GcOXmxDPdCxzlvqsz30H/O9e59O+mGfXwnfUsMO+EoYDunNLB560sfyHP96ic2NndVXtqCv8coPBmHQiI8ULaFsdu2vEXXp9/9Hz7vDfPasD/cZ+dYvolXwCegcIDoGTzMpXuEMFeAST7GyY2UDKqULh1nJAMbS8R7Hpc65o3hrSyFc/SspHEpHdLKpTeFufar+B/S/8XDczGsx7vjvwIb6lsY3YDOw/JYGA+R0FWcyI/w+PTSTQ+VEzJn/qNteSw0uQcsNLu/Jqgwzh392Agnz64qbyzftPHFa/J2rtrIyW2vn6NRAHPkNw+seqMBYOLDsaSfK6mPeudgQZ0dKGywgyXNMvICSumxt4hjEpUhbRNgAogCUIJ3EjyUEO6KUAlhrzRMfPiWTAV/bnhkKxsm2UCJivt8f7UgU4sXIngQf3eQ7MCkQDChEr5UJcvShqC2wdM2pZLn1PyWtXTPWTH1FXgTAkmcnKu5b9FdRvoCMJwKfR8Iy0yeBibBM2H+FQBA3J/zwroMizIbrXAA0XG5qksXGX/rvtcj0BTYx/gSFKIx57fXnbhBwsP5MTCZ8srkjZtf2MNXNJelAl4wkSGKw437b2UM1llyHW9GqPO5F4aJ7W6guIe2pRXvvSdMkvsgPKB6ZQA6lU6cumGMlUYJCTjj5fEOGUhwXQZqUe+F4/BIaNlFKR7XnJZHM8t35dW8sHElekY0iF4V3hr/uUnXAhTMBHnq/GNbVOl5dfMju6BSPrCiNH5266VfZ2rhls/PQd0NLcMae+iEB0xO+GCTDLa5/VCZ8tkPYTgYwWRo7rLVdh9XJtd3qFfhAJjUB6DkFN4IIU95yDSsoD6IdNMvkHB/RhwgPVULMACbd8T/27z3C1uQh9LYvyRP6LRKjCeTsET4VvGbZN69znWxXdvYh3fiHoK+FWOwNeraU0qnNOu99eSXPtTOuGDCdvdAE/mUzjp3t0KLrn6le87/TDC5IS9vQt+Bb0C9CdcAOEySVi8oMvJxjUSJl+lvy6RS/c8i5YECgSUARoZf5xRLJSyBqsNA0v4ojFc0ZBzjpeXU/oxynPtW6fgdoGAwAcre4tic19lL8Zneovgfo9jmYTG9L+bQCR0r8VamVaiY8vRULa+COlwGg2V6jJG5LR89g/AsI08wp9CNJ997Xyya5zMKxbpg4yNtSOdVWLrA+vVPfISFk/LomeuFFmdMyEYzZ38ugSRdR8W2dw4V1trBonrBpDEARXoflb5JTa4DZc2CQot0TAow2QHJDlCip3KgFJDEMFcECa234mCHueGRrVwwcWC8ASYFjMTLCL6AwwECUKRq4BJgEj0UfgOdFpU4x2UsJuY2ralTBkMQKEzGwQqjE0/Lg1j0IVUwfsT/6ZlN+3sMAy28ihvG9d9CKyymJg7D0geYlOgDNHQv2siJqyr1fuQjt44zLa4MKoYQI4CRdlC4QQcWoYT7Z8FERgrj/PBjYPJ9BiZu4LWfpRsjZSA3UJTMUqCIcKBVTtyeVrx3Nky4TgRKXAIT6kw6GThPoOAd0sfD5+6Qi42BZRw1gHJy7YkyBmE/ZrekP1HoBMkxI/JmphaZ32XN478x5AOAeRbCYgCeDnYMeXNuG8/iCzurjHJK18UjwljTl4RtDFp49eE33ryY5uwYfeblmTx9XfB56Znwzotf2/Un38m4P7GO8VWrbMeg6XtQH0azYMHE60cEDb5XnKOF78Z2GmMw5hx9n2g+TmiJUN7c2YcOO9YBKu+IAgnPRsyb5tm1ShuEIirbTwSQ6F3yfn2I9+T98879XUtxOyAJHluAAZColSEf0/tb0zu5/fRX8tS+VHoXlPWe8Sa8vkRpNHon7mHEa0nAgnqoVT3fq2/+i91/8Ts7oTTFuG20/sIzbO1f9imcqZwf0TcYVFpniPYOBoCVJ9g0dNZqadrMPdvmrARvS95nacpYBsMeFA0yEInGLIZadhnsv1Spe6YNei6ln+ttitfcj9KQ9P+odcJcGHRCToh3RIdKLxAqPZD+KeQyGki1CqQhnS15C9qRE1s2u3JHtua50vpHXjiKy41bn9uVB6HDLwUlGsEQWmUGyukzD6xn6rI19p3x3v7+P/BO0u9A6+8cKaq2w8W1dqi43g4UNyRqDCppEFiCDgg2B0qDDpZFNQkKLdIxKdS57NZusBx04a0Q0gpNigNIAkyoL4mV8XspVNL3OEjeBpMAlAiVABMGlgwtuLJggpEHbALcUT1XflWfSrVzNnr8oqu+Xa6nPAuvY/EQlbyYJlrbMOQ+RuGCG0VaTNCSC0NI+IsSA6MD+AgBDhIkD0cAYMiL9uHzMuoPbO3a53bqwlNd45IbU2AQILIDCsIieCYYJMJfPybMRULD4F64/pk9ePlHubm7YUIiRG6IMPgSv9OgiHD40TCRuB7PENf5zf+MnoiDQpCIzwIYeH8YVoQXwjaOwcgCcvqZ0KeHepcGldYBDedyDZ6H+3A89wDy/F866Z2V8cRwT6hUPuneyFMfVuTK/W88znzr2S8949H3BMPfOrQsmATP5JpKc1v3v/KSXv/Mhow7mUvvXSpmWuFm/XcaWjTK4Cat8NIwod4LOFFqZGSDuXMPbEGlv4X1pw6701oyujUt3WgdiLdGvRGdKOnzU95KiV3vSKVQ90wyMAnfJH6nCJO4Dw8Z4x+hAChqZLhHZrfs/JVXdvf5b2xb/39ShRnqTLJhEoHiMNF9+M02mtnPrTywDz7/d/bgw9/baXl/NGYAVMMCyJw8Quqr1pXumMTrPL24ZaBOXnxh0wwRolJvt+ByjI52g6tW17dsNd0L7sFU4rkAppTBioaWdYdJrf6fnvM1JcflUs7j08o6Pt5/L+3rmonS132bHCZZck9E7wSgRNhSqIggwd4w4jbpDNFghUY8dNRl8Fg8Fsb9o3HJ8AkVej0c9tg7+uJ1MzIFMCEURmX+8uZLm1y6a10TsoGJZ8L7ee3/S+/kF1daXomAUlJjBwWVg0WoLhG/awQWVCtpW2m9HaloknFEzfrdIigEoIQ6FEJehMPC71Cpn1a7HfZK+04tsyvcaRW2u3J/tzg+VsBj8IMKqoFKj+ABUILCtgQ0glX+LgksDpTolVAR3qv/IsiV6xn0bHSIbOo5rheul358XZlDJSHmG/FzGI+MYV1GZNSm5MKf8lj/4OwVHycJo0VzTuL8uJ6AhI6dVNozaVaACTMAnpRHc9mnTz1PCWD5jldghpL1cFBNEE2BMUah1BugAly8ibADIxzjoTAp7ovnAz7GeDp/9RO79+EflHC+03PelcFJWlklrjKeFPf3Cl03UHhAQArjHIxSvH7clz7GRak8ORZxrVgBz/3iOvcMTacZ7kPG0Y2fjJ6eNW7n3dKQgSXrwCEChVAQQ+IzjIeDSOdF+X11L6DjDSN0XKikvOZ1Mx0jaw5yhiKZ0fdibKpbz39n95kf/+G3HncmA9L/h1ZezJczf/6+jqPF2aukD9AZGXUy07AMxaiDpKwFQw5M8Ez0Xup4/3xvFUJqh/WOJzxDUy924uzdTCmRJa3FqOAnLEGfFmBKZ9gL1z6RIf5UmfqmDAhGVN+cNKB3xftCXrhIfSf/hvr/vp91iWFovGe7fpfrXRN+Yk5/ZtCkEcNVnzDtpjXJkNOIgQYPHMfvUq7BtbmHCi/8ZnujvgvTP99/8XvXyqUPfKpnQovLG8/sIsOzS9SrOEyu0bnuU1vaemlzgsyE3n2/vkeXvkPH5CVrG9+wY/o2tFhiXnyMF6EkemOHkBLvGyNGeCXI6ywSgxYVj8ulXEY+rezjYzhrL+3nmlHZ136TOP41jyv+R1/nmFBgcO9f3ztAhLSv70zjHaVB7ziudEfBCG+FdO1w6T7pLRVpfk9zd6a4oK5wYZ1GJg9tdvWej5rNLJLUmdTwPRhpoYk6neS/OEzC+3+nsKTc8ksq7EhJpWBSaYeKqgxv5YggckS/D0uHirTPpd+lNTKojTKozVKLfreolN4sY0nIi3qXUPfioTKJMNjhimMCR6vrSGWbtLtl2NGqHdFZ8U0CONkwcaDgpeRUAhB5HRmlYSIDX6B1vJ3YGg1oMYxLY69gMrdmQycYzmRS98aDCp4N4bkCGQg+FCGX0BFvyyZO3ZKRvm8nVUKjNEyTVuYdCTBhRkoZFupqqkdV8j0to3LVli8xBtcLN3L0KwAihMbiwJkohLmAhWCCh4LRVsb21lrVgkZyTGxZhWFxyCTnY6gxTsyOd/eD3xnzUDA2F0aHGLeX9in9eMk2kX5nQJGUel3J9b3DYkrx3m7QuE4UhkiZzkvGUgRVhArid4QR65UqdcVzeT5gAYwYXsR/+zMzBS3Nsmn1FiAVFO6Dh8L/YigX+svgvQCmWmUKRtRlLvRjKg0PHd/2+TwYZv/64x8E3I/dcyBE5t9X3xAAMKfK4sZTY/pk+psQPihVKdCHS1EG5jelQs/EGHuMPo09CGviBet3GOl62UbmmfXznl+PuWpofDF/7r63FDt1/qExKCmhNZqJU2K8dPcLm1m5Y9XylrhX7FXv4E6+SUgj4TuwjXcev6OHpVjXd6J1Fa20CEdh9JlBE8+EZtKzi7e9VRuttRhJGjEUTxwmp4jwoRRadE16KGto5rKfe1/p6sJVgfbUDTu5GppkX771hV//1Pkndlz5glLuxOIdY9Ko4VM3rX/uqnUJaF16jm5dBxECa1Shqlqgcpi4ByKY0KOc+DwGTMsMTNiWFvvfoIxB3kPZx8f77KX9XDMq+9pvUqY1G40H8Mq0jfvxLvx96Jt4azKk3yGfUWhAO2kQkSbLlG5Ifw4b1vWbuYNoYOID5qpwxGyzeC6M1N0+es6ODTHXyrJ/C5on00w5Nlv2Z0reOb/fqS7Js8qSfCstzreiogIrLCq0ouISqdQKi8usQMujhaV2uKDEDheWWV5plRVXN1hJTZOV1rZIx6ywqtmOyls5VNYkz6VRS+peGu294hAiC+EwgNMiIyyoVOxWAEyAzA5Y8EJeV+hvstNEeLdCP5W0CIX52GPUsyS/g4cRQ16oT/vprR/qePB+ihv6ReM5weSCDR7fgQl9QxwKOq+wdkgZNYyMS5ttWksBBMInx1Xiogc8pWni5tSXeGdDPAiMvj5+c/8ZweemSqUfqlTw0L0bDCQ9oI9kYAIQgvfhBjwBiY9VlRiQfcFExoPe28CEoUeuZMEEI43h9fNTMIjXSysbIlGZYxwKIYGjEAbjuUnEeA3KgH6c7pEYf57D/5/EOu+N4zyMJ/EbhTCYMph+cxwNGGjh5ddNrh2Oo29MEO+UEXRD+EsZUSBnoijm+qBSuHXonIz7dRlzwkzPjCFUGPqHjBbrOepUimPQTqaIXpIX4WN6TShdqIRXQgYltCDPDq/Ijbx7bnglfEMVIAinOkzGBaFFAeySTS/e0De45SMjz8lL4dp03mRWSUZWZgSAKw++krf0W7v+NNTRdAtyjX2nfOgdwOUeid53CGkG7zSTRhLYBOAEFSgt0DwYsFTpHfdPX/RhY+4IJjcef+91Hsf6wwgRhLk81MW75lvxHZXWUIRTtQpSvUr3jKxAmGvr7tfe0OHs5oe+bUUgGZtnPplz3rwbo0QFfJWW1d0LVqd80zBwxpqVV9rkybfrWq3yoBv6GFuKRgazbjTDgIQYUIx3IjfmwajuSNvi/r2kdBKa/uZWtlGP0MgpAKdjcoEjl7Kv/SbRqsubCGO4k3MJ7flIwCoQ+PsQPLyJsv57yBNKi4m8P5PnReUfLVmnv1pUKGiwP+yjsEa+I7xKC8MqFRRCk+A5QT1OJjanb0KDE/pWTesd8H54XsFkoDbPuqqOWkv5IastOWCVRQesvPiglRUftpKiPCsuzLfCwgLLy8+3vIICwaXESquqrbym3irrmq2y/piV1rQIKE0OlCNljZLgUUoLsXpBJYTGqGM5XK79hMUASyIAdLg88V4cLm0ypslQKlLwRlgPw6cERXhEuETA7EDEw2eVYRsgCTCJQMFLiEABDgEmgITwG8cxNEvL4HwGJtXtU8lxnBM8DIwFHwpjTBPOFmUK6iUIpzCCMEOpePjFDSaGGaOLcRr30jSdG/FglpTh+lQiYwwdEkU0oD4Ym4x0FNs8vOTaAcZPBhMZ3l1Q4Dpazxb3Q7n2RVGPE/+H/5es9d1KDGIifnsdAOval+v4cA4ZAhApo2qZLZ/ZL1EYtI/jgijtMftghTJIlUpctXQGUwnsmNz+rok1q2eolBaO5X6M2jBtzfJEBk9c9n5AhKTGTl+zFpXmqpT5AAnPHOY54fl5Ps7VNyDMpfQSPNlRj133TJ6Xx3vJlwwCOnT8oo3MXZbHc9UhsnrluZ3dfmE3nnxrjz/5owPl4u1P7dQ6dT1X/byG3lPBS1EpE+XpObk3nc6AGyGunfTCNyCNpICjYxk7DjjSZJTmzicEUloounFRmgEYgMOl3zFNhPRBuEuFIgGBlnGPPv5rb35Kvx6adJPWZpbuGHMNYZyI62PMHQz6toz9xECChXimhC51TCWgkagLcMOuY3y4D86RAEY2HLLDTj+Vso37LmFEBZIdwOU4JofSdQ37ktJsru28t53nxKtXISpK6670ttQ+RpfOKb1v8pK35iS/eIhN3yGHCn1qYURTajRj75xsOWLTDYdsqPp966z4uTWV/kxQ+bdWVfJzqyh638oKDlpR3kErOCrlH3bvpaSs1CqqqqyqrsGqG5q1lIdS3eweSkFlkyu/QlApp5VYrb1PnYugAmAASkYCjEPH1WgH8GzKWuyQeyshBEZLsQAY6jEY3FGehYASQRNhs1PvkoDElV5P/6ayPwAlymc7rAjHhEm5hmRYTiYwoaWRSkg1NAkOIAnDwAeYAAsPpbTNGX0nQjhlwSmPEXf3U8dEA43xppUOnYwY9XZeapWhL9fx0aBGxdE9o+L2WNoPhjsYd5Zs8wzPsSmYcH88pbN08ssR5krDxBWvE9dT8vtxrxz7okKjgN3P/ial/3NOccwusf3tGTnCw+VgCaEDb2JJyxiVsuLQ4Ux1S2msTiDB4ygXQDDWjK3FsqrjhErNKzZ86op3Dptcogf8utWr0MDEWYwky7N62IHvjTFPYETdCXPVlDUxcducvNizgslFQYFZRM/6sm+appyXBJMnPgjm4sXHtnHrld189p0xN8uVB1/a1v0vbP3mx/JmnxrTRXdMnFPJflEl/RMyMHqXhDYIY8gD4t75unfQkA/zwu8CPYuPHVY/Yh3jZ23x8jO784KObb/0UNuxAfpHhTTroTK95+Dp6Jq89+Tbx/RGAwf6wjz46I92Wx4OYDl/LXQ4ZUI6mjdT6qVwwACDR5QejyjvHNHvozo/T3mogJIynt2xGZV+5c3r3ukChn/z9HqUgEjpPP8nVOg/8g8Hk/SIuz+FuG6RnofJz94q5YOSNygWvkIfnQCJ/eqds71Fdrqj0KZb8my47rC8lAPWXPau1Ze8a9WF71l5/ntWfORdK0J5B+SpHLGS4kIrLy+z6poaq60XUOqbrKK2SUBpsmJ5KMUsqVOpaLADRVX2XmGlljV2SJ4KAMkoei9JS7L3aTFGPUvpsdAjX3q3iG14Lm0OkOCVdMpDEEgY+sWHfxFMqJx3CQguQWNPEfZKwUS/wza8nh4llH65dcM+LD4V8IOzMhjdJ5RxQsiC0p1PToVUyiOTxdg/YQ4yDr+9dEopMCkJ+lLbypVhMOwMuXLi3AMbX7zpvZmZO5xSY1r5WYrbM9f1jK1tepbwXGwP9/JtyriIUiotg+hT4Z7J/W9sZvmOb+dZvRUIGT65XrhO6vePlIMM6Rr7UeY/Y1j2LQwKmZkSOMYnS24Q0tI3IaNQ6hI4AUpoDZMsXdNW2iIdU+aSZ1LcrPPkTTDJVbFK+7XyKjrGZfTllYwuXHePspmWV53MgIfB1LtXemDyLIdJUglPz/iSRmAy6gWTTkEJb2Rghjl3VpUell19U2u2sP5AIHlkx1fpH0BLP/rbfGxrVz+0y3c+83lgrjxgsL8v7LTAM758wzon16y8Q0a4WfcVsIoaeTcRIlFpmPBMI9Y+etYWdI3bL35ttz74lVe8UinroTH9DyAS0i7/Q+LbkqZi2tKSFo20SiNdIZpXn99+ZYxqwGjL7Od6fN88He+j1uo58liXjgI74MY7o/GERD7J/c1zSMfm/8SKQHmTaBTAGFaxccB+FYZ1/+nkaVvp3UcYeJuUB/Dm91Im1Kd8EhSh8na9szVeZeeHKmyxp8yOt5fYaFOB9dQcttbyg9ZY/J7VFPzcyo/8zEoP/8xKjr5rZfkHrbzoqFWWFVtVZbnVVFdbTW2dVdU2WGVto1XWNVllfYtVNrRaUVWjvZ9fbu/mldv7hVTeCyblASSHyhrcKwEwAAXP5GApIGlxmCAg8lcF9fYeQNE+b34cW4QlQ7hkK7b6ytWseEc0QU53lgx9XPBOmNaV+VMYDr9t+LRKj4LJ8XV5GvP6YIKJMiQlzRgy8BK8MpxLidDlGVCJTPvpUxLFOgaGfgK900xLe9dbEvVMX1RpbEYZnVE7QwZ7oxJDHT2EbPFMbpj12w16hImMBEMtEB93mCwFmFAC9VZQlKxT1/lLxH15zpzP/xbly0DsT3rHKhm+JmVuz+DKPOlM7KVDzyjKMBmg7Ih1Wse4MVHpvog6CYlS81EZu/yGMSttnbGG/iXrnGJeik3rnbmkQgfzddPSZUb3wRApDWAYPQSFwVM6UdphkFOAwgCnbUNLNqBCCt4JMGlJJnhj2oQTq7dtTho9uamSPVM23LTppev6vakCwA07s/nUPZQ7L35lN57/YBfufG4n1h5Yx+R5h115G/+Fd4DBVtpzhVGNjyr9ss4+ANk6fMZOrT+SV/IreRW/9pY8HSOrni68MKT3HAonQf5tlZ6iSNcM3smID8yRc+/F7zxtMWS+eyYnrzlMPD/wfYEJeSd5T3zHIwLdEfKI9rMNqLz+rd8gnZP3Eyt4KbmNN2JsMUbLPSqYxHDdfsR5P7U8bWdDYy9lwSNbaZh4iE2Q2K/euTvfbNszDbY+Vm/LA7U2311pk22lNtBQYB2Vh6y55D2rzf8rqzz6Mys/+ldWnveeVRYdtqqSfKsqK7Kq8lKrFFSqgUpdvdU2NFl9c6vVt7RbubyVA/ll9p6AckAwIeR1GIhEkGhJS7CjlS0y5K1Smx2pIrzVLmjQufGYg+S9YkGpmCFfQqdKttPqKhdM0A5M0p0d3wyTAJJeJfgwGVfFsVGVFBeU2Td8Aiem0qWE6eEtMoXDQYmfTKYEjdxwK6PETJYtMhN9BJgnZJhxdFbv24QyYYtKtnglZLRsw5pTfp/dxjutPWEyKJhs/tOHyf4FfJWZsxRhErQbKIQZ0kDJHtaC+D3wyEeCAcqrH5Xh0PcVTIrltVTJC2kcWLK20XPWMXbemgeWvb4LjyYNk+KmCTfqPp2vYAJQihuGHSatg0vWL69k7NQVh0r78JIx907n2IpNLV1ziHSMLPuEah0jjKywaPVdJzwd9uv4U2v37aK8lBvPf2k35FFcfvC1eynDp7atbWTFqjtO+L29N74E0I7QLN29kx2YMGQME9VRX0Koi/oaZgilf0KopA2Fo6gAFPJBEI1E6CQ3dHzLtu79wu7KM2G8MyYqW936yDtjtvQteRNt3gmeBAAI41oFmBxV3nCYcE3ukzpuX3Lj/1OL7/664U4LmBxRevMh2HPs/2+lfzIweb7aZfcX2u3aiVa7NN1iZ0cbbWGgzmY7K220udi6a45YS+l7Vl/4c6vOE1Ty3rXKgvetqvCQVRYftQpBpby00Coryqy2psYaGhqtqaXFmo61WVV9kx0sKLX38qSCCu+vEupNGh0iBdXH9Ac6lGi7pG5ltB5XUT2hpm4ZJKDQagfLW7zHPVB5T1B5Xx4Lve13ABIGiYyiv8gROkRmAWMHLPymZRYK+wJM+mSE+3T/MLkWc60Mzl60/ukNlRopXeGRBM/kiDKRG3U33ErQGDcyl+SZo0olQS2j2E/LJSprj6kky6x2DCM+eGJLhmjeDRAltr20CzSJsc5lxNFeMKEnOMNRE9cm4zPzZAYmMqLU72Rf68/VPxRMju6SDBGZOUuUFNPyzm3KcFEF/M8kw2Qr7COT6joJRPBKjlL/oHdVKCNb1jbrQKGuhOFNGCCP0KXXmei8WLp270Ty+Uww3hLhLnonNwgc3ZOMmHzFJhau2sg801hfsml5HlSyAxmOoW9AlTwN+rswVAv9B5gXp2vinB97ZvMDu3zvC9t+/K1t3v/KVq680Pab3tKMHvw0IqATJUA5moJJCL2NWGPfaZtZue1Da9Czf0XXI73TQjG2BspI67ERSSacqbRFi6/usTVb2/5Y3skPdu3hdz7eGRXxJ1bu+cymDXpHXJP0hpcCSLyRhZYx77BkX/CI9B717nfqyPYQx3CNn1z/HSY/GiafrA/aB+f67cGZXrt5qtuuHO+w9clWWxlpspO9NTbRWmp9tXnWWn7AGooEFLwUoJL/nlUUHLAyQaWs6IhVCCg18lAa6mutuaXJjrW2Wk19ox0pLLEDeSX2fgKTw+UNll8piNR1WnlTr1UeG7AqqfLYoKtCKm9h3KsBlY4GZOh6lWi67HBlm71X0uR1KO+X0EESzwR4hAEidyRYAJJyAaJCsEBZ4Ai/dyancphI+fSSF1CK6/UcLRPe7npw5qJ3WGPiqyLCW97Mc0jPwxApGPloOBODDzwEEodJSiR8YuoMh9E5vuYTHFFXQl+UMkq02u/gyTovI+1zD8fvEbwfj1mnxDaeLZPRyaBsE/goYdKrmlGJbz/7tW3e/cpLjWzHaHhnJxnR7Gv+ueK+PGfmvfxEAqyh8jZU4DLnQlpHURosDpcAmF0eS5IJURo0bkQiQBxYuqfENiq38VpK9L3KWmetsv24D2tCqbtY7w/D6MYtkXusmUpwChR4s4PKrKM6b1Ye6bINzl226TO3be78fWNmzXPXP7az117axNJ1qxEMgmfB+aSpfr0DpSV5OOXHJuURLcqrueiV5ms3mMv9ax97iX4wPjz+6FmBR8/XjCFRGlU6ogEJrcpCS8RhY7gNOqxdufeV3ZGH4/O4zF62Sloh6j2VKF1Gleo9svRRgfVtGQkCMeT/sf5lW1x77EOyMIDm0oUntrz+1LfNLt32IVUYh6xMwA3NpkN42Jum6nfwdPRfAYrWg0I6fpN+fD3b/uQhVP3/7IJJWqQvT3OexnIf899CXmdYC+j3IQElZyuvRD78jhQbCxTUCyj71DtfXB6yTy8O24u1IXt8dtDuLg/YjVO9tnWiy9YElcXBepvuKLeBunxrAyjuofwsE/YqE1TKBJUKeSlV5UVWV11hzU31gkmL1TUIHEWldjBfKqz0EFdBVasSVI9VtQ5aXceojLRKWh3EkUdUAht2VbrYNmo1HWOCDAm/V95Iq/28kPoTmhCnQRKGZgkSLABJuSCRiA6DuWESgZKGSb8MbJgVkr4Gg8cve1t8Bk+j9zkZEaMOTBwoykwRJl5HIqUBEEUCBSYM0gdAmOAIr4TKW0qvXjrj2HhuLmm/G1XuKb1uwGWsBI6QKUNmTMOEaYWXLz33oaiZljbCBMW26QFIf7kiSDJe1U+kt8EkKgOTBCS5FAGyezsGAoDoe2CA9d3wUHyJkeF9NU965TwhS5rhRojwDRG/2Ra3+3OrEBK+IVBgqPpRq5ah7xg7p4LFLfcwLgkE15/+YBdufSqY3FBaOanzSVukIdJbvy8PKd3ym/RIq7POUXm6C9dVUHhmG7c+81GNuR6dLAljVTIEiwBGx0mAkmnWLtV2nPBe9pd177svfuPDaozNb/tQK96/ROkogiTARP9f6xEoqEwAru+YtxlB4+zmR96jfnrhpp06+8A7LNLnZOTEFQ93ASnSG2kz9n+I3o4DRdfLBsabBEyANu/5p9R/h8mfBZNBwWTIPt4Ytg/XR+3Z2qg9XB0SVAbt2uleuzjbYSujTTbbVWmDDQUCyvtWX/gzqzr6b63iyL8VUH5mFQJKZdEhqyrNl3dSbPU1FdbUWGe1dXVGD/sjheV2tKTGCgWSiqZ+QWTMGrsZpmLSf1cdG5ILPChPpD9IXgkAqe2csKZ+xm+alqegTFXVHbySMryS3CAJMOl9DSaZfXvABOVpvVAlwNKmMatRRqcX9OgpBqfbtIbe03rJMgyJUQAkhLqigY+uusMDo+GGI+znNwmeegli620jZ8M8AlrSCigDkvS5WQqezh4wIVP5tv3BhIpWOpcxzLuHMrQvdmQKjQZ+AvEuUvLn/gm0X5igt8EklwidHeY7uDei94dnoffDMgIF76RQngj1XJn4Pu9a4ncESRTPzfcL3mz4lgCCzo71zOQ4vWGzq3dtRV7B2o1PvWVU9+S6IDCrNMGxpC/+P4US3UfrDicJgwws6BvCTJ0+iZfOZ278MG/9kgpoAoPuFXviu/fqMFGBTftG5q64p3r/o9/7gJJMzMbYWkAiJ0z03qNnwm+GVQE+DO8PPIDJ+PxVAeWWLck7oVc888cM0vItAkXXSivthWSH0t6k/w6Tf1IwGbBPLw3aJ5dG7NWlcXt5acI+2Jiwp2tj9uDssN1a6rfNuU5bHWu24wLKQEO+tZa+Z3UF/8Yqj/wrKz/yr60i76+squh9qy4+bNUAxT2UMquqrPCe9Iz/VVTR5B4J8GAWw8auaattH7fypkH9CcbVotmvpGVhbbcM74BgMmltQ6eUIeatukMlwNo+O1TWIXXu0mEGjmQUYpfAUCZPQ2KJ2Bb2cVw4Fu/FQ2AARiAKyx73PMpaJr1jWf/xSza+cNUGTly2elpzJXFnSpaHK1mSoRMDnygbCEd0HMdiaIgXVyjz0lueFkB13ae8dBvP43p7Kn0/ZeIMTHSuZyotHShZMImQcZgMLNvSxWcpz+SmPxP7fCml/8tforTR3xdM9Jz+7rKUCe2lFEJPgOQNnglSJt8BSjAOIYy1t4BJ9EyiIkRi6CsDFb03+kOkjRDwiHUlsU7An9n/i76Rrh8LHiz5/qQDQp/DMupj8lg7BQW2ETrjPK6b7hDpjT14NqUHvjXfjVAbPZeBShzFunP0nDGAJlCi2XdMH6Qd0gxGm6GAhuQhX77zpT38+I929eG3dvzMXYdJHIsL+Zhevi6RvnQdJpjjNx0XqwSICQHkvEBy8fqnNskYaLOXbfr0TTujNAdkmFeGQTkbu0/781AH49J1Pa3qnfBcrDtQtC1CYy/9d5gEmHgn3n0oAuVNov7FW0LWxb4sU/vSO18IJJ/JM/n04oigMmafXJ6wV5tTgsqUfbA+YU/Oj9ndlSHbnu+xswLKbGeF9dcdtWMl71pd/r+Vh/JvrCrvZ1Zd8J7VFB10oFQR8hJUyooLraCg0IpLK626odWa2gftWM+YNXeOWt2xASuv77LCyhbLL2+2IzT9LWm2w2XHZNTb9Kf6BJsJ6xhdFFBOC0JT2sa86QAEoKShIkCUCRauAJC3wcSh40AJdSzu2Wid4S+otCQePTi35RPF9Eyve0iCtvCHBRN0CKBg5JXZY9PGox6O4PcOBAAJcuOhRFrSPCkwzhmT2WAAaL0SDWcGHG9QNEruceia7pUkil6IV84rM5LRfJsEMFqIa2889V7KGA+ac/ow6drnSyka7L9U0SNBGD6XnsPhkDx7DAv68cn/d0hLsQS/63/HY10ypi4Z/2pBRXKAZIEkLQeKwyT8fk1+HDCJkArA2qnoT0DFupYYnOzJk0IfE2VIGXjW3ShxbOZ4tmubrsF7oM4N8NBhlVEU6hn9WAaelmCkF95XqNAPFftR4Xzt03vNtLTS8XxHJlVjFktEpXdsmRVB4ulF57Fk/8D0JQ+PPf7kT3br6a/ci6hrn3N4+BS8utcOTGTk6SBLoSURx1QIingjeCFMhzwrr7dbMOsV2I4v37bz2x/bwoUnPm8NEzj5uGd4djy3rplJvzxfJt2G5yWdhMJRUHx2T0Mcw2/OkWIayaS5+DsDCSnu07V8Pb09s/56+ogV8zENkSZ2YPKPp5DG9ik9axxBIpfiSAMuQcqHb9mn3vlifcA+3wAow/bZ5TH7fHPCPt+ass+2ZuzV5Wl7eXHKnl+YsAcro3ZtvteBMtNWbv01AOU9q8//mdVKNfk/txqAUnjQKgsOWHnBISvOP2L5eUetvKLK2jp7bWBkyrr6x6yuudNKKhstn+Hv8yssv6TeDhfV23sF9XawuFliAMluZYZxlbKWrV0wqZVnQksrOiQysu8OTLqCSlG3C6jsByZhGbdrKU+FBFfRNmvNQ2dsQDDpP7FprWNnrVzbKJkeEijQQcHExbogcliJ1kviStwOkxRQCE9hHEnkGAKA4h3c9NuNox+zD+nanlmSDOZGISXPeBgM1pNMFzPoazC5/aVP25mBicQyZsafQtEj4X9SeuY5MoNX6tk8c2vJMbynQxX9dqCs1w6W9+1aP1Da49uiNxjeLwCWoQckVUFhPRj6XEDJlRGzj0FHlOkO6zqI39mKx5HZYiW+t6hRKY4mx76uzOV9XnR8zMRk+gx49DtkWt4BCvtdvh4NXtrApRSPid9e75D36mlB26PhjcaafUf0Pr3SW9/D04a+BZChJRY91p9+9nd298Pf2dLGM2uW95ANEwcJ1+c+ifIr5HVXDlqFPA1maVwTTLYZn0tAYnh6rjMyu2krF5/7XPu07hqUx8JEZswV48/uaTY8fx7h4/J+5eNe5WPyOyNO0BpR+aYR7zlAk+en/ucwaSUprJE/SCekm5DvQuGE7bwzgMwypk/EeoDzjrcYv0P8zqQThwhpmHpFpHNCWvknAhPST0xrf6m4lutHwuTT87322YV++2w9AOVzeSdfbE4KKgKKYPLJJQFlY9qen5+0+2dGbHuux1ZHmm26TR5KTZ61lb5vTYXvWn3Bz6224F2rpv6ESvmj71nRkfetMO+wd2zs7umzwRF5Gl39VlXbZEXyVo4WlNmhoyWWV1Rphwpr7P2COjtIs9+SY1YgaFS3jlnnyKK19jPnt0oDAox7JqkJtw4ya2OWAMthh4uWAkuYGljryVzz4XfcFrcLJtSZKJEAk9Ax7YK1j5+3+r5FK5a3cgSYCBwHpQMCSUYJUA4p0TpstO1QNHwpZRK2EqxnBv32fRwrsf9NitfxuhM3yioZpjM219b2Xds4TiJ0QAXowvoTu/7kex+Ej1FpvS+B9nlogYyma/CMP5mSZ/WWRDIUPCPhCy9Nu1ENRpH3EWHGeSz5rwcr+ly8H4xE1BGvf+AYqTIlrR9N4IK3cjhLwePYrd3HjOr7vVmHq4ENzwo0JvX8FHQk/S6om/LfzLORr/151Uq3Un6NlMmkiZRx83R/FIaeCdu9SXVi7NzAYXD1fqLB29nON4/fPnxr/+46PhMK4t1yvvY5TAQEvjXHsc5vwmEMg8+kaYRAF+VBNPcseF0JdSMeyuI8rsf1uU+iPF0DoDC68OjxLVvbfmnX7n9jC+cfCSQLVinPp7Vv2cNeeDyn1x77QJo9Exe8dRdpjuc4qmt44wBd038naQXw4cUQGvN5bzrm5XkRpeA85QudW9E6YzW6FkvSE+8mpj9/V7wb3kNqX8hHoYC3a5uW/p71f3enk5B2ogGPoGHbjuf6j6NM/6psKPyF8gEllY6P7lPvvFztslfneu2TCwP22YZgcnFUGhNYJuzTi5MOk1eXZuyjizP2bG3S7gkomyd6bXm42abkofTV5gsoB62p6F2rE1Cq5aFUHP25lRz+uRUdfk/eyVFrrG+wvv5BGxwet2PtPVZaUSevpNyO5JfYoSPFdqSg3A4VVNv7Pn1wix0CJlVdcp2HZQDnrKFTrnqjEgcDMTKyb6lUguSduASDvZRAxZUKix0CMtGriaEywYS+AKVKrNVd8/JOlgWVBatoP+Ed1o7UDtshKRdM3ENJRPgLmGTCYElCTUMhJt4Ikn8ImMR1xOjGLYLi6QuPjU5lF299bhOngAkgoQQbDE8w/D+tDlPSVCmTmDjwogKWWRWZ576pfzEjmsoywCJhQPrj0GSa0FtoWgsowjuM7y8nTBKguPQODueQjw2V6LX9Ou+QSwWHPRS9lqMCSvA+BEVlpgCQBBwSI7u6pyTtACMRhkkGKq24PxsmCHD4bz0jLQhdes7dMEnSgo7LwERinf15lUO7YHK4fMDXGdrnzKUXdvfFb70XO2mkBZiQLnRcsc4vUdpgmQ0TQJJfMWhl+q7DM5dt7crHduPhd15PwjVKBYNqfe8O+lYpvXHtZXko04u3tO2sh+QyHgZQ4fvqmp5W5IkAD8DDOHaTp2/Y6Py29Yxf8Dlm6CxZprzapf290xd90E3SDJ4/6Sa0hOM9hfQS32Um70lxmyt1DAp1ZgEkMX3E0GcIf8ZlBMo/jgBfJl39hAqQom5of3rng+V2+2gFoPTZ5+tD9sXFEQfKpxuj9snGmL0SVD4RTF5dOm4vL87a0wvTdvfMqF063mNLQ8022VrhQGktO2iNAgrhroojP7dSwaREnklpYb61NLfY4OCww6SppcOKSqoEklI7nCeYyDM5nCcPRZ7JwWKmDm6RV3FMrnOHlTb0W608koomErHc3tI2ASIqDZPXdThRgIqA4WB5A0wIdVX0KqENyh1WSUyJtFJGrbztuDcFBSSHE5AAjl0wSUTY6xAZA6iwTH5nxHoEw58jnR+MaDDSfw5MmHxpb5hgkHYg8FMpGgli93WCSKsyPbNSjpzc9gpnBgMckbEY1XLg+GWjJRNzKQAXOgRSgUynQFo/xX4bntn1H3PCJAEKYEiDIkBi97Zs+TE6f08BE7wT6QiQACgpeLAe5SDRcS55PRlgRJCwLS32k4nZl5aeKypChP+3AxOdpyUwieu7B93c2R8HG+WYI+WD/rt1cNVneKS+5NrDH9x7aOndP0wK5EVw7JAM+tqVl3br8Q++bBtY9vNQzbFZ69N3nVu9517Q4sWnDgZam5Eu8EYIa0Ux7h2FjtahFZs9c8eHsmdSsrVrr9y7ZnKxdgEKMYozA28OKu00qDCC6AhMKJn8ki6MkXayYRILK1GetiSMdDTYDhD995hOsqGSNu7/rfVPBiZPFloMoLxc7bZP1qg/wTsZsVcXhu3jtWF7eWHEPt6YsFeXZ+3V5px9eOmEPb4wY7eWR+3i8V5bGGqxsWPl1lMjaJQesLrCd60qj/G83rXSvINWWVJkbceO2dDQsPULKLUNLZZfKHjIIzl0tNiBciS/zA4XVtshpgwuahQEWuSFtCmxdiqR9iqxdtoR5pcvafX6lAPFxwSdVh3XnkM7IAnqdAGTg6WExUJoLMJkVz0KzYdpLkxPYSWqOLR3fj2JRokoAclBJcJMnUlKHt7SvqD07wQkUk5I7Fc6P8IkGyRpeORaZ6Kc/cLkp1YJoQoZE0qTlDInBBDm8GAY9/nzD+3Eufs2u3LPZlbuenNlADM0t2U9Mj40n24dXglwEYTwWhjBl0y/J0ikw4kiQNLKQCOXdM7BijfIr5l4KBKg2AWQCI9sJbDYDQnOD1AAEmzzTBxhkyjUC+l/ZYnzuEac8yaPdSkCxacBSBT3O2CACdfVf2FOmZaBFZs/R7r4pW0/+C7ARGkFr6JI6R6IFO8BkzxBALF/YHLDmwXffvJLnxire+S8f3uAw/4mff9hfVdaFJ7VcUwCRrNkWhmSPmNdycFS+nwNudcCLEgrzHDJtMLXH3/vy4WNJ94MGgEYxpybWr7tfbhonUZrNkbvBsDkG8Jhh3lW/YeQh/DwE5hIPt5eBAn7tcRIu6FOQlsOF94by+Q3gNm17R9B/2Rgcnu2zu7PN9mThTZ7sdJtL8/3CyKDWg7Yi3NoyF6sjdpHG1P28vJx+1BAeXbxhN07N2VXT4/Y+akum+9vtJGWcuuozrOm0kNWV3TAqunIWHDYqkoLrbO9zYaHhqy/f8Cqa+rtaD4gKbTDR4vsSJ6UL6AUMKtjnR0qqhdUGmX8mROlWd4IYa+WpGK+WbBBAkqRgFLcqmORQOMK4a/XgRK8lR2YBKAEqCDtd+9EgEmAcrhKpWmBI7QcUoLU70PadqiyXwbldbE9Lc73JsSusO7btG9P6Vh0FHHvnFIGBhJKxA6LlOgDEzqlvb5OjLlZpU1Ghb328FvbuPmZz0EOTGIzTEILXrfxI4THsVv6H+6JhMnAqBvBGyE0QWc4+kDQCOC0oDYONBgsURmf5qztIyppSh0CB3O7981cdKiMy2BQ8qQESp+fxr4FB0rwTChlZqmS0mhK2nZIOqgSdBTrewpgvEnApBIDr8zsHkiWF5JLMuY5lUDBPQ6tA5IYGouKrdVyaa9rBcjIKEh5Ll3btfObY2nB09S7pNL/PR+vbevuL2TkH3nlObP1xdGxqYgHJJ6u0t+f+qzyPsFryDoF/iXq5B58Y5dvf2H9gktF44TXqxTo2HL9bh1Y8sIE3gWzSzLb5KiA0iDQMEMg1zyia5J+CMdRr8LkW8xXzvA/AAi4kJY4j/Ov3P+Fey0UTiYXbip9PbPjq3c9TZH+vG+Yrkf6DHWCenaJPOSV+fpvcftO3gvfw6Vv4l6n3lX4HcQ+0lY85h9T8Zl+Sh0lTPsj9M7WSLldm6yyO8cb7NFCqz1f6bIXq7324myvfbDab89XB+y5gPLBhTF7cWnaXmwet+eX5+zhheN2a2XSLs8P2spEp832NtigA6XAWsqPWkPZEfNZHAWTrvZWGxkatIG+XquqqrajeYXyTAQTgeRwPpKHQr1JYY3E3PP1gkVawWM5UNSUBRQgExXhEsNgKNatBB0sjRJMgEsGMAwqKaB4ZTyTZPVKoVVIdJG94pdt+xXH76FQSsoh3Se63yHOm1t0XsvM4KfjojyDe8Vl1rqWeB7ABGO+rcy+ceNTweSqZ2A6r2EwMAgcv18dRSrtAQ9KlV6y5N2V9fpv7sm0xYxCOyUgLKw/tpXLH6jk+0he0TWPozep9EgvbCpZCXfQXJpe3dSddE/Ki9F5p1UKvXDzU++lzW86+RH2oqI0DZAgQomJKoIOIa0f1DKK9dzaB0wSRc8kKrYqyyUaBQQjH+TGSsY8Pn8GAsrEhM+8XkbnoOgJva7gZXnYhd8OT7zfcL2Md+NGMQDG75Pci/tSAm3oWZBHeMc2BRL6H50UTFrkLZA2Ikw8fZDmkjQVxXemvqNAaa5V55xcvW9X7n5lW4IJw7JU6XvmK40QCiN94aF2q6AwtXjDwbBw4bEbfgaXZF5ybwSiY7kmxh/Pho6VtfShUfptH1JhQ+mmpX9RXu6ap+db3tT9C3k8gpPuz7TLi0ongzOXjClqo+ftUpohf5A34kgA/r+SbeQ7GoOEhiFJCT2+xyzxHv196126l/KPJO6d6/n+UgVQ7bRifJveWe3Os/WBYtsar7Sbsw12/3SrPV7qtKdneuzZap89OztgT88O2tPzI/Z0fcKebUzbM0JdG8ft3vlpu748bhtz/bY03m6zPQ02JKB01xdbe02RNVQU+OjC3e3NNjrYZ/293VZdVWl5efnySgrkoRQmAigldii/0iviDxbU2IGCWqnODiRwOSigBDVKTQ6WAJVECVAOCCgIsBxMQeWgdCCjDqkzEb/DtoNlXXZQMIk6VAFU5HazXrazPfxm++uKIMpe34HM3mKIjGwvJVsOEyl4HwEUUYy7lKcM6D2dPXOEdfaRoZqUGefP3rdtleTWb3ziMKFCPMLEz9Hx+5V7Ig4SPbv+JzpYondTymgC1JFM+D0pVeKJnLvykRsPSpWENiplaHguh5ie1Q2IllScMlMgc21MLd+yc9c+thsyGDRbXRcEmeGwpnNOpUqViMjIytQZqKAELBEowCTtlbzZMxEoXLmM924Fz2S/wqCnMmti4LOVgYmuneue2cq0QnPDpv9cEbwx4JIpZXIvHRveE/dJjIV+Yyzruxd8bp3Ld76SR/FV8Ez6l5U2JpQuSBtBXpFPOvPvzxIvInx/viEFg5nFm3ZJXu+mYDIqr7NGhYR8HV+o/aQVvndD90kPd8be+ngagKdR53t/GKXDQ0pDiHNiWiaN4kkHjfskXvT0v/sBo2B/bWcuPbcTAhPpbHH9qae7at0fENUpvVBooSUYz8B/wAPi//hoAEpzhNr4zxRoUEnTlJU0TiqdUR8WvhfvMvPtlF7+O0x29M5c07u20H7YzvUW2cXRCrs63WB3Trbao6Vue7qSwESeyZNzw/b4/Kg9XpuwJ+sz9vTiCXu0ftzuJkC5OD9gZ+ShnOhrsrH2GhtoqbDWmmJ5J0esu63BRge6baCn02qrKqwgP8+OHDkqqOS5jgouR/KK7RAV8XkVdjCvyg7kVbsOCSqHBZTDhfX6jQQUWn0JJofkpbhKUPBQqE9JKwAlwGR3iEvgSEJdbDvAUjA5UNadqCejDER2SYYzB1QycEitH06J9Z3rRtgk8mOil7K3gIqDBCUg8UyewOMfEyaH9L9YJ3PWE96S0aDSlQEEmdd85MSWPwfjgHFPD4vpeM/Yun8EKR3aeibWPXRxUaXO2zIY9z4STG59ZhMq1TboGnT2yxhijKQbyx2YRKDsByaxhI9CiT/xDt4gr4BXJkrXmewpN+xZGTYaJck9Fm2jaTDwyXW/PQVY8JYAicOE98A9uC/3l1HQOnVJLHkW7sO7IszFlAjjp2/Yxs0vAkzWHgsmZ9yw7qrI1/NSBwZEYn1YDG2S5uq75t3jpH5jU9+MMFStvArSCvsjGMr0bes65qxThYWRuS33WvsZTFXphXRDeo3piXM4Pxr+6FlwvdA68ZHd+eDX8rZ/YcsXn7nHw5IwGrDqGj1nw4IaBZiBmYte4V+uggrPTMGHa/M8AIc6lmZ5PFT6My1EQ++iD39U1jxjdEaN6SuT1hze/x0mUe+MVf0bm2541062Hral7gJbG6ywrakGu3WyzR4s9drj1X57LJgwXtd96d7qsD04P24PL0zbI3kn6P6FGbt+ZtwuCSgrk112crDFprrrrbuh1KoKD1hXS40N97ZZf1erNdRUWklhnndmRAWCSYFgkpdHHUqJVC5V2KGjlXZYUDkqmOQV1mpZZ0fytRRIjhY32VEq6aVDQKWwSXBpltJhr6hQrwJUCGcd2gWU+FueiUtQcaAEHSzvzilgA1DSwMnAIQFGNkzidrZljo/n5DgvfV0/Ntnu0jqZIRr1HbFNGTYDlrDOPjJhU+9pN+xX7n1tF1TaHzu57WEED2Eoc+4+5+3yOLSe2WFSBkgQGbTfMyiZHYOyoAxPqXFSHsUxZeZKlQ4LazBK/X68dzTV//LrylAwBhqhrn5l/pMXHtp5PevF25/7cubMbfdYGI/KR1r2zB1EiGtHMkBSJkSpa+/UcWmb75PRwnBJoQl3KLlTyvfwlIzwm4TRD3UQ+5EyKIqZFXi4Udp5/gCUYPhjiGtfSsJuOzDhXege8m6ijmrdvRMHSoAX74Znqu08ZaPz15QmPnWgnDz3UEZXMKHzpfZH0RqM5sXBK2Gp59Y1PC0q7VDyp7BwdosZIb8MA0Y6TEgvFDxCoYHfpLmqYzOeRgh7sSTMGY+N6ZlzEF4K6SxehyWFEtLztYfU0Xxup1XwGD5+2ZY2nrjm5KWQ5k6eu680+NBOrNyxgekND6cxDt/7RR2+rGmbtXZvYchkZZe9kUD/7CUf4qZlgDn+54zpI+I783B0orCu9EP6QzomU8DZhzzN7ankmtmKaTUR1/G08xMreNO5034uvdN69J9bd8m/tKGqf2vjDe/b7LEjttBdYudGa+zyTLNdO9lhtxa77ZbAcmu5326dGbA7KyN2X0B5vCEP5fIJe3LphAPl1sq4bZ0esrXjPbY83mEzvY3W11xuY91NNt7fbkOCSWtDlVWVFlhp/hErPirlHbGSggIrOFoob6VIKpXKLE8wKRJEysqarKSk0QrlneQJJnmCSr7WC8papGNWyNArle1WVNVpxTXdVljV5aKfSn5Fp+Wh8i4lxE6pS0YvVLq7N5KEuGJdCjA5yD5AIoWOjWmF7QE2ASrvy8OJwshnvAwAkCizLRFwoeWIt4OX8fRSmLYR5uH47Ou+VxLudzDeU+sxYzkAHAJkMjJfgIkDJdnGEpg09pyyuZW7tnX3K1uTYcbQ49qnwxfxGvuVexU8P/9TzwYYMC6U/tqHV2x66aZX+s8u37JjAxgMwhjKiH6O/hPvTeI32/Kqwmi4cdTm4blNm1q+adNnbtnoySs+8VOF9sXpaAn7eQhQ9wzS79T6DshDfVWm3krH7RgFrhGVGGOAosz0U8oNiJf4WNf1XzMSyT11bw9bZUsgyJZDj8YArFdoPcrhAZiCYt1NaO2W3A8g6H60kKMF1Lmrr3xSK1p2MfeNj1qgZw297AGinp9zVRpnGX7r/ZUrLeg9Uj/GCNsUHK7c+4U38KiVIWY/AMrUr0n8puFHedOUVbce9yXpMB4bj4+isEJa82toSQtFOjJOyxPZuvu5vKEP7fiZG9Y7sWqnzt0R0J7a6uZTO3X+rjyVh7Z6+akA88AmTm7KA5rR9ZVWlfeL6wYFkkUbml1XfrgsGF6yYSnOY+StwrpPemiN5w79YfQ8+n1Qz+TSNtKUpx839LzfVJpKtoWGPFn7k+2MN8ewTKFwo+v7cm9lruNpJv7+qcW1lWb2qXeK//U/s+r3/ydrzvsX1l78L627/F/bYN17NtV61E72ltjKaK2tCyqb8+22fbrbri322c3lAbt7Vh4KIa9L0wLKrD29NGuP1qft7rlJu7Y0YpunBgWVfluZ7rWlqT6bG+22sb4262mps6bKYqsuOmJlRw9a6dHDVpafb0XUoRzMt/zDxVKJAFNtNeXN1ljXaTWVrVZa3GCFBTXyYKqssLjeigWT4so2q27ss7pjQ9bYPmYtXVNW1zZmta3KIMeGraKJzlQDVlJH00S54jUkSIyXIFIseEjvF7dpKa8lEwpLwmGJZ0LrriC8kQQmMn4HZDQx6mlFLyN6D9QdBKAkIAEYMnAYwqr2WatRSY5OVxg06grYx7lc+0Dquu8WE4YDJuF672ndS/I6J4IjeAlBGZhov2/TPoYbp2kuMeWtu1/a2tWXDhPmtKDyNBtIP0aUNsnsB0v0jMVdvo2xmggxnDx3z0uIfZNryrgyeIQIgbj+w0Gkd+l9fSJU9M4BCtMAVLTqe3ad8EmiEJNClTYTvx7Qe9B9qmV49Jt5PrwVHgN3VsngaDtLWuV5vRfit95DNlQyYp9L15YhSzfr3ku05GGE4f0onUl9W47rvU2vheqk4IUo02dL8An1JDtyr8XFefrmMhY0ha2U99A3fclWr3xka9c/tfnzj1QQOKdvoNI4BQ2kwgjHA14viSOeS4b1IH1DtGSCNYZmWVx/ZlcffGdTCzetrn1e31TfScfG0FhasZFItg6X6RuWkybDeTT28H06/qien5ZeDV2nlYa37OKNj2zl0n0bn9+w9sFTNrN0Rdte2Pa9V7Zy+YEtrN325ap0/My2d4IuqFZhs7JDzzdhoycu2NTpTQFlzbpGFgWXBesZX5WXc8kmTlO/t+Bp19Oq8h2FFfLye8WdrvdJ90r/QIDCDYWUmNe9YMMzk8dqwpJtMWTt2ykY6fpHtB/P+QD2Q+eH7gV7aXfaCMp13G7R3y0z3NNbFPrHJel1H3rnyL/8Z1b8s/+n1Rz659aQ/7/ZseJ/ZV2Vf2VDjYdsuqPITg1W2spEg63NHLONuXZBosu2F3rsBh7KOQHlgjyUi9MuYHLv/ITdWB62K6cHvR5lbbbfzs0O2MJkn80Mdtpge6O115VZQ8lRq8w7aGVHJDyUQ0ct72CeFR4pltdSYTWl9dZc226dxwaspb7bqgWWovxqO3q43L2U4rJmK6tqt7qmfmvtmrDuwTkbGF+wzsF5a+ubtZYeRiaeshqBpbJ52EobSJSCQ1kAyfsJTN4rPCa1aJ1QWAIUlDQVjkPX8zvCJJam0wbfjT3AICGgPWBCgqJyuWVwyeeawOUGLvS8x0vhGIdJhIeu4aDSb/ZxHe7LEuO/L5hIhJWASQhzyTMRTAhJFDJhE8fqWn8OTCKEAAowOaDMRcmRyvX+qXVl4ud28vw965RHkY+R533iweg9Ao6jlfwPZVC2sy7Dny84+AROKjUyb3pxw4gUlgXaBigi6A9zbpUycmX8nYYJ7zwUBgJY9pZ7hnqHIRwWgPI25c7QubUr4+XYv1/tur+0J0wS5YKJt27Du9Cz0HqJlnE9kxu2fPmFnb/6ic2vCSaj5zOhnQgdhGEMYR2dLyN/UKA4UIJnzdQN09Y9vmYLF556X5CphVvyAk5lQECjEe//BESSbaFFYKJkGwIkbAMenJMNHbwavJ5+FVKW5XHMLm1Zz9iiNffM2PHlbQfJzcdfBIBofWn9jl24+szWtp9Y5/BpL2SWNfRb9+iCzSxesemFTeubOOOjmTd1zyrtnlPB65adWLktuCwJlIQK9T+V7yj4UYDxSIHyKXmRbUxg5mnICzXKc+RpAOLHp6RjvD+bjvF1PHUdhwGn+0EcQijd7SB4K9nS/aSQNnLDI1thoFrS436VSrdv0Tvv/6//zI7+q/+HFf38f7ayA/+LVR35X62h6H+39qp3rb/xiI13FtvxgUo7PVJnyxONdnamxS4cb7PLgsrV5X67LaDcvzBhDzem7MH6lN0FJmcEk4VBHTNol04O2fr8sK3ODtmp8V6b7D1m/U1V1lqRbzX5B6380LtWcuA9KzpwyAoO5VmRYFJdUmut9Z3W3zlsI31KoO1D1lAtl1QwyTtcIQ+l1krKmqxCHkvjsUHr6puxgZGTNiiY9I+pVDFyyrqG5q2b5fApTzzH+uUFMCRLhYy/PJF3C5hfvtXeFUzeLWzR72MOFFeJvBUBhbAX43b5RFyM3+UhsE5tDy3B3k8LwKjUTdNir6BPEhrbY0iMRBa9EqZVZfTUuq55BwmiuS8JLR4fK/sDqDCKGMfgubhnImNOSxkUY8sobosxZ8JHAKNB9zqxese27nxp51UKpQVNAEk47i8R9yDEdVCgYx2YMEvlua0XNn/2rrX0n9YzE57j2QlrhamVAUkemS/Zni8IMKdMgZSn33G+GTzD8BvDxbqA6qM9CxSJ2HdU58TzwvYEOsm7C02/s5Xsc5GRydACyltEqXx3s+I3y+tosrZly/vE5NierXB/HS84HHmDvI4k0Q5IZFAkr2fSepkgQP3AwsYzO3vlY5s7/1Bp87w3cGAEA6/PQTIY7pnoXJaEuQ6U9tq7ReSLXh9rrW1o1Tugnr/6yoZOXLFqwlw6nvqV/ER5QCKlCJPd23SOln4O9/ZtO9sJiVXQQ75/UZ7FReX1Rfc4GDFjemHLtm5/LKB8YifP3rCBqbOCzbbS4hPB5Kl1yvMoU+GyomnIRuSNnL/y1C5sP7eF87dt8tRlHXvVFi/ct7NbzzIwKW8c87QapqpQOhMM8jDM/BYAmEEzT4UY0hoFHbazjX0cy9xJbHPv2dOx8o2n01Do8YKQ/44FnJAWs+V94IBLRnoGLXc86zcr9HfTOftSSI/71Ts////8M3vv//t/s4MCypGf/b8s/93/2UoP/wurLfpXdkxA6RFQhtuKbKK7zGb7q2x+uNaWxgWV2Va7eFJAOSOgnB+1e+sTgsqkYDJuN1dG7erSkIAybNtLY7a5MG4bJ8fsjIAyP9Jl4x311lNbbI1Fh63i4M+t+N2/suL3D1jJkXwrPVpijZVN1t82aNMjc3Z8/JQN901ZW2OvVZQ0WHFBjZUU1VtpabNg0mZtbSPW16+SxPCc9QycsD5BpW/0pPULLOMnztn43Jp0wQamV1WSmVQpRyV/weLngsm7ha0OFECSrQiWgwzhUtou4yewxJZfAg2ejaukYwcmGU8kACDUd8gVTsT2wroRq+uet/7Zi9Y1HubpBiRUOrOPkoxfQ9fyCm0ZunhNN3q+T4lV+/AG3CORYt2Fx5WTbXgOR3C/dQ7AqO+c80rIzbtf2LkrH7qxDyDZff6PE+dIPKuey+tMdL2qYwlMrryw42dUQu064Z4g7xCQBJjQkID/IWOfbAMEhTUDggmlOP0XZdCj+mYBFgEY/MZDDP2CyLgBKjvH6/8kx+0ovMv4DnOrV4YgwuTtCuExgPLTyTNwju1BO0Yh3F/Hy7DmgkhGiYeCDpcLJGW6jrwJr+vQvVgyaRvwYEiV1Ssvd2AiOPgxifBkvNJZ9451TQ6TYtK+vlvdqDX2LdrI/FUPlXVPrFtF66wfG3ucx75J+5KOdU9Ehop16lO8fka/6XBYquerbZu1lt6TVtc2aeUNQwLEiI2d2LC1K88dEGNzG3asd07QWLfl9fsCxzN5I8t+XPWxcZs4edmu3v/M7jz71q7d/8I2b31s1x9+adcefmUbNz626aVrKgid0r30DklHKuR52lX6KqojooD3POReNNsobL6fhMlJjwEcQTEt+jr7Uvt39rFNBh9w7KFYHxgVwZJOH3sp3YH67YpA2Z/e+Tf//J/Zz/7F/2g/k4fys/9NYPlX/3c7/Ff/kxUf+hdWXfSvranyXWuvO2Q9zXk2JKiMdZfazECVnR5rkLchoCx029XVYbspiNxem7Rb5yft5tlxu3ZGQDkzZtdXpuzqyrRtLk7ZmoCyPNVvs33HbKi50lrL8qz68LuCyc+s+MABKz9aZJUF5dZa12ZjAsjCzBk7LU0OHbfu1iFrlHdSXdFilWUtVl7eYlXVbdbRNWa9AzPWLe+kuX3E2nqmrHvohA1PL9ncmU07vnRZbu6WShyXrKXvhBXXqVQpGPy8oMUFMGhC/F5Ri3soPy9oTjyVoPe9eXGrjGACE4/3CyJFbUEOFTwVMpRK5ok8BOYx1Q77eWF7pt4DYDB20ODxy9Y5ds5qOo7LcA5bsUo+pU1MqDQiI0GilGFGsfQsYxe9Ha7PPne5lbgQdRG+Tcc5ZEh0bjgTA69EWtd5wo6rpEWzzXNbH9rAzIbDhJKWD8nPuYDhR4hzULxPvBed1fqn12118wObWbxhNe0zep+EEhltIKkbERyYLjl4JTx7WLKtQEDAQylrHrPylgkPcRUq83qoTPtjs26vb+FcrlUlL0fgcfhoHc9lR7xHYJI8a04lx+jdpetTsiES9Q8BEw9Z5Nqu75Tz/oKJ14EkOlSuY1ProbIdmMgrYZ+MMQqNDziGZtiT1j5yzpsEr259ZPPngMk5Gcsxh0gaJqE+YOd8ruX1BboOnf2ozO8UiIaZpncgDLwYQmXBwwEQDrJ9yGGi+xIei+dR/8KS7fR9KVEhrJQwqAofRfrupTLs3WMrNrd60+ZWblrXyJJVNo/6cl7bzgsyfRPnrLp1UiCakl3YFDy+skcf/9YevfyNPdbywy/+xh5+9Btbv/6RjRy/pELojKdHD8+qUIgdYIpv0ma19lW3TesdKt8qHdKo5z3qYbUkPZJe81U4wmvZCcfqOhSA/PeOOJ9jKAyFEO3rcu/GvZMdhfrAfUoA85E89iV9a73n/eqdf/XP/0f73//5/9X+5f/yP9i//Of/F/vX/+J/sL8SUA7+/P9thQJKecH/brWlPxNU3hNUDgaodBTblIByirDXXIddWhqw7dUxu3F+QlCZtBvnJu36WWl1ym6cndFy1rbPTAs8E3bu+JCdHum0iY4G664psYbCQ1Z+8F0rPXjQKo4WyiOqtO7mHpuRV3Jm/rwtzK7Y1NCcDXSNe/1Jc32X1VV3WHWVwFLTYZ09E9Y3MGsdvZNW3zJgxwSXHnkp4ydW7NTqFTu5um0LazeUkK5bz8QZq1DCot4kAxMZODo5Um/ybmGztjX58j2XgCKxn3O8Yh6YFAkghW3aJ+9Fv70yGc8jkXeG1Lb3pfcKgQnHApMur6OolzfSO7VuxwaXvdUS9QPlLZNKmLNW+f9v7z27I0myK8HkkEN2V3V1VWVVamittRaBQCAiICKgAkBAa5VAKqSulKVFd1c3W7C72WyKphoOOVxyz+we7pIcyhkOuTP/Y+fz/oK39z5z8/AIOIBAVhZ3z5z+cI+7m5ubCzN7911TPryKigLCg9EjeWjzFgycHrPJjArIMX7ZkoltegqNbqkyYTMXlQmHSdp4SgzONlvotYC9t/Yl4V4kp57oskxCeXGI5uq19yQMIuP3s6PpiEZ6Y2z6QsWypMLvy7CO8JyqmZEkO0Svy+DUrlZadsxTzdgReQrsU51o/wvVCeBWUIdMzLBufEOCz+oLnse3xjtlGu4jAaP6MmHJIy3c774ObJOVhTa9KaGYY3e0GrYumbhxYbSw5Zwezq2gmrj17IeOMrkD8gaZ6PUGVBbpZJIK55Ik+huB8JL0DK9Dce/q2lqtXJuLHfiWEHgNn8sHOr+KREcwjGkD2unu3EvDnXOmP4Xn2O82Kc1AKwxx7+CSxGb2ZWz+hkTGN1HOJmQwsQOC+Vgef/wTmVm9J71wUALDy1AmT+X5N35bPvrO78uzT38qjz76dQVJZ+vGh5oOlXI9ylkTymsjymZr34xeP4Jzq1Auyc2HcNQ2tc6TRKiYSSKdIBiW4SiUzcAE15RjHxbrMpvKEa/HKByGqTrB85N0lHho+L0kgmMvMpUJiaI2CxhSYfxsgLw+Bc4UXH5Tci++JlcuvCqXL3xVci69IoW5r0lp0VmpLj8vjTWXpb0xX3pai6S/q1wGg9UyFmmU5GiHrCaDcnVlEIQyIe9cT8rTW0vyLkjkvdurIJM1ef/OOohlA/sb8uzGqjzeX5J723NyY2VKtqZGoE6CEutplVBLgwSbm0AkXRLtDsn0yIxsLuzKje3bsr2yD5WyJkmQxPToPAglKZHQuPRBlQT7x6FIVmUquSljIJMwyWZ0TsZmViWJ6zb2H8jG9Ueye5tjzT/Q0RoD4/AyglPqJVc0p1RIJRRJRXNUypsiiormCMIMsVRzMiTnqWjzFojB9rWw3wVEQdIwBAKJSxJpS6GKqqSF14B0YGjZjBWIcTXUG9rE1QFFwrbVIIgkkriqYZyRSw/aJQ7HALIjXpvLGA7UQwXo3yIB7pvVkVFASSgM47U41k5xhPXHN7XJ6cnHvym3n34fleqBQyaIz2tOCf5nnx3mvF5HY/FeeD7elx5jHO+4fftTWUKFHUClbqAioZKgogBYyW3zFkfZMYxNiI0w/D0wCCSRmbV7klx/AEfgthoEVmJWbpKPm5bek4TpkBJgmsBSSCeN40BiJFmh8rHZywF/0lWdgZruqWNxmJQyjw9DK2ZGmF/ahA5JzQSeW+EcW8OrxppE4oS7RhvgEGCu0Lx1+xty88kP9B/08fnbKIcL5loHSiZ8Rl6PrSUBnnPXtgJIHmZYMY2nJTJzzSF4nknhPD/DbdrpJJS6lsemOdco3CZVAlPShvrUO7gM9bGqBp3lI4J6tXnzQxDFT2AHHkoQjkkADlwSZeveu78G8vi+bII8ZkEM0yAbqpuR6T3pjS5KE8pjI8pXh6a7KBEQx/j8TVnZeyZ3n39fFRCbwthiYcsvnSGW17mtd2QR5X9i5Q4cRk6yRd6hzLJ5nOWSxwTLbFOQw+JnAX5Hfi86Ww5YzxSMmw5VJzhXmwXq6IgxflY4HaGcKbh0VnIufF0unXtVLrz9VWy/KlcuvSr5V16T4oI3paLknNRVXJKm2hzpaCyQQHuZRHpJKM0yO9Yt67MDsrcaA6FMycP9OXlycwkqZUXePVgDqYBI7mxi35DJO3tL8mBnQQ7Wk1An47I6PihTkV6J9XbIUHe3DPUGZaQvCuUzKxsLO7K3fkPW5rdkZmxBEvFZmQKZjMdIJmMgk7iEIwkQyYZMzZJMlmUQcYYQZ2RiUcaS60oos0hjde8hPPLnsrjzUGLJPemOLsD4jMHIm6YtVSQgj/KmsJQ1DrjgcUVLBEQAQmGTl/avGCKhqnHJxFEn3JI0SCDceo+5rwoBmdQJAmH/Rbf+aY5yfVbCEzs6r2Jo5poSDNtGlTRg4FJkYprNrAKgAXebmTSMhpVhRqGQYBjGe/O4H4S1eRPe2Sc/lQOQCZuhSCZUJDad00AVCgoo9/X+IC2C9+VQ5MHEHr79u9pUEIaHRsWhC26i0pGYqUR0Ein2CSo+Vkh2wgfja6jQB1rx51DBp1bvSnzuOtLZBNFwcUoYMHpzVDmsmEhHO/ZJUIAhETwPFQwMQTphHAd+a1Q8i04OePAnk+wJxRj+tOMjwAqcGZaZpoF5Jg7LdQnEB6adHcYX6eo+rlVouAF/SjY4fV02Dj6Vm49BJrdJJgdKJrY9nqBBZ3xDDIRJU4898QhLPLwXz7vDZxnXAy+BpD03z9vn9sK5pxc0sJx82AxwS7SC1FpRt7jPOhAa3ZTlq8+1D2924x097h1ckVHUub1739SBKZNLd7SO0JHpCvPvkrPSjPLdgjS6w/MgkQ2ZAIlMLR3IwtYjXPeZPEFd2rv/DYlDQdvyy3LZF1tF/bon+w++CXX+uQ4x7h/dULKziprllMeqpnENm8r6UO4DuJajF1WtWDJxCCUF7zdAOQDx+JFHJk5HJgQJJTucyb98DqrkTbn49tfk3FuvyPm3vgpSeUUuXXgFKuVrUpDzupTmn5XKkvNSX3lF2uoLoFJIKLUyHm2RufFeEEpE9lZG5QCE8mBvTh5fX5Jnt0go6/Ke08T1+NqKPNxdkvvbC3J3Y06uL0/JdnJMFuNRmY6GZGJgQMZDgxIPDYOkZmUNBLG5tCNLUBkTw9MyEpmQ+FBChqMTEgrGpb9/TIaHZ2VufkdmSCYTkJ1j8xKbWJAoSCUEdRPF8SDCE0t7srL7QEdqTC7fgiSlOkGlhQGrZoc7CKUcZFLWFAKJANw6+xUtYZyPahwlHxAIiaQcqobbqhanqYtKhCTCJi0qEQsP2ZAEaIApzbtAGC0BeFooJGz6Gprak8mVuzLGXwQPr6jH4Ro4NtFgm0kmqk4QTpgwGE6SjBPG/gttdsOz8ZgVZUvJBMrkiaNMSAh4BgubXjaw8fVZ9N4A7skwEiSb1Vhx6f3RSyN51LTxm3Cpmxiek89mRtZZME/aQnAYJrZlYuGWJKBIJpduy/jCTR37PwpCieJcD7y8VhAKvUCtnLhOm8+URPA8hBIJvxefy3yvk8H0CFROB/xtMFchqPaBGvVjoB36QObxaeBNj3DvDaQRnw/UWAPGCDvIUAPsOI9OXZONW5/KjcfwtO98Q2JzB9pslXYdwPhmCDzSdNLJvB8VA+NqkyGBcCUTfk9P3ONg08+8f+azk3Q4EIQjGxv1GNfiu6ijw3sjL1kPeofXUJbu6aRdbkPxLV3FmCMcuQTM4vYzOJrX1cFj2W2GkWbZ4u8ruiMLEoNKmYdjs33jA1nafqzYB5mwSezq3c9kJLmP+j+i5bmtPynDU5zv8r48eP9H8vCDH8nu3U9lGOqlBapam2VRPlVNAVTUzVBV7MeJQY1TkfeDVHhO+wQVeA8PvCSjzibrgYL7xyBL0jFA3uK7ZoszeZcvyGWQyYW3XpO3z74ib7/5VXnrza9g+ysglq9AqbwieZdek6I8qJQiqpTL0lpXIL0glCgIZSzSCiXRK2szEbm6NCq3Nqbk3u6sPLq2KE9vrgJr8vT6qjzaW5YHu4sgk0W5u7kgt1ahThamZD0Rl4X4oEwPDspEZEji/UMyE5+WhcSSLE6tyCxURiwyLpHgsISBYGBIAj2DEgqNywSIYmX1usyCUMahTEYnl5RQ+hC/vW9YukKj0jkwDkO2Au+YwwOfydzGfWTqrqqTDhijlj4UOhicqpZBKJEBqQCqoEZquOZX5wgKJD1ojkICIXQYQ8jmsbImNomBUJpShFLZzKYzGEVsDxEJCqUqCcfYcmKeevMwdG0ovBw6S6UwuXJPm8HYbkrjVsM4iM+tlce6jhjgpqcVxqTlDbdhbMdlxaI3xqGOT0AmB0++Bzl/X8nENldxa9PLCnwuPg/IiuA72uYvKq4g3iOxdFdmQCYkAaoJGn5WODYH6EAGjqjDN+WWyo8Kowt5w1nJ44u3tM16MLGrFXFm/T7y8R08910NYx7Ss6M60YmnuNYQCkkEYbyXBZ8zG/B74d38UJ0BQzIw8McBBk7B/dPE98JzvhppWGh6+v+Po6GePtJQw4sKrzPQ4UVyyzDGIWnwr5cbtz6R67pY4mcgk1vIQw4nTjfmOuINsGly334fkoUZgZgiGHvfFDmnP99RMOrkMHlkgu+hc54YD9fVtLNZF8aXz8J0nC3fhcvZT6880KVbAkPruuRPEKQys0aH57GMzt7SpVU6OKqSZIKy3I5yzNFisyh7a1AXG/vvyiJUycrVp3IdquOdD38sOwcfaZ8e7QLLcCdUxRicn6sgm4c4/wCgQmG5pQPEss8yS7Jgf6HZT0hkchvOl5mJT0KhYrHl0tZt6/SwbpMkWQdJnnY6wZEAkbjImlBOSSZlRXlSnH9FLpx7HQTyipx94yvyxuu/LG98/ZeAX5S33vgluXD2VyTnwqtSlPOGVBS+LfUglDYQSoAKpQeEEm6R2XivrEyFZXcxLjfXE3J3e1Ye7i2qInm0vyLvXAWZ7FCZGDK5vUZ1kpTduSnZmJ6U5PCIxPoGtJlrPDImM6NzSiZJKI2hUFz6usLS094vnW1B6e4MSzg8KTPJTdkASczObUt8fFHiIJ7B2Kx09sEo8c+Nbf3S2BlBwZmBUbsm2zffRYF4KpPI6AEwf3R8U2IoBAPxFV16pbKRy91HdSmWwOCcDIyuwINZkcDIIgwX/1I3rV4Em7pKGgaktJHNYlGHUGLYDoNghgyhgGCUUHTEV4pMuCW5sDnKnIuD0KCiJnclASIhmbAjnmPYUyRiYOe0sF/CFihr2Jme3oPKxIbhPMPY9ES5Hx7f1jkfXMfo5qNfhUq7C5Kh8ad3lADg6TjXZgU+H95F3wOkyfsYMuForBkJQGFxsiLboNnGTOPPe2iTFvuetJkQREJywTG3JJOe6KIqEe1ARQXjqBs2byVW7sj89juobI+0YrJNO4hzJCley3zRigqvj1DCcsCh4Bxlww5+fhP77fX7OBWW5004vzO/uTGQSiTML4RzVB63ds00NerOlt43UcWtE67nnHCXhLSCp84fglZ6EouBVSJVSNML3sMOG08Dwy28YdhyMIc2jcAQ87imA3kFQxtJ7Mv6jY/l2jvf1f/GsJmLowx19Btgm1dMk6uTFq93vo13a8/bfV5Tg/cn+aU923HQ9Hk/GDUnvUzw/hwib8mkgcSpBEKnCERDQgK45RwVTnTkP+k7wyvSPrAkHQCPY8lbUMF39TfCXPmYioUTZzn/iX0vLLsLKHeLKHd0ikbg2EwuHsj6tfdQj7gK9mMth+VwMFkGuwcXtYnrzrvfl3e/9Tvy9DPUt8ffkSSIgs1XLI/azIUyquocx9z2j67LHO6zceN97Wthfw+JRlfpcAmFdZplm/aEddD5vihT1ceBrQIu8P2UULKBJRYLEow/ztSUl0plaaFcPv8mlMmrcvb1r8rrr/1b+fqrvyhff+UX5PVXf0HOvvaLcv7NX5ac869I0ZXXpRIKpb78ihJKbwsIpbtWRgdaJBnrldWpiOwuxOX6akLubIFQri4By/JwF9hZBpksy92tRZDJvFxfmZP9haTszCWVTKJdfRLtGZChvkGZHEpAnSxLchxeUzAGIglKe3OPtDR2SxfIZDA6JfMLu7K1dUdmZrdkJD4v8bFFiYJMOgIwHE29Ul7XJdUtQekMjclockt2b70nW9ffldmV2zICI5VgJxoKyMzygfRGZqWmBUQCFRIcQlozuzK1fAskdBNewp5Exjekb3hZhyBSpZTU9UtJfb+UNoSNQgGBkEi8UAMGQjGG1hgxeuNWtfAabumVDIxtwRO/rQjEOJySXiAroFEjXtiCZTuybSe0DrvVQpYKs8ctqBzRiR0lk0cf/oZce/g5DPaBEoJ2qKOAcWs8niwB+W1Gtjl9QnhHmx7br7tACiPT+/iGt7XJKhiH4efIGFYQVDpWPjYdapMXKpQqE6hEjsZhB2h87hq+y4aOuqHs5/EUCGVu66Es7T6BN3lfFQybB5gnJCaSEQdYcM0lEr/tkylvjpr0EY9h5r6sxKa/xVwPZcnmNrxLFc6pAtT+FhI5rkE4wXBjWI1XTqPHrZINFBpRBe+YxtWSkDoBuM7ApOkHs+4bjQPSdGCIBOlnwJKJGTBgoIY2wzDz2WjM+Sze+DzHME6WjbB/6zp/LPWrIJNPhRNqW/pnEY/vB6B8KLBvn9VbPnlsyia/mYmjg1L0G/LeznvjWTKf70g4z+p7zoEShxIGyeRkUPE0ds+gPvCHXwvSBWIZGN1FOb2pZBJP3tQmsC79aRxIdnwLauau9tuxTLK/rjvKv0ZuaRjX/pqF8u4dWjJlDGW5F+VxDnbl4Ue/Lu9/53fl3c9/R24//77Motx2wimt7WIZIqGYbZXOaYONQxokkR2kuQZCCY6u6UivapRfSzisc1Td9pvb/KhmmG5PRppiORbp5dDCbb7MwJmaijKpLCuWK5felnNvvyZvvWnI5Guv/Bt59atn5GvA1185I2ehUi6+9SuSd/FrUpr3plQVn5cGKpTafOltNgplPNwmc/GArM8MKqHcWJuS+7uL8mCXkxZJKCvYX5F720tysL4g15agTOZnZHNmSmZIJt19Eu7ql3D3gMTCUCdjczIzPifRfmRQR0g6WgLS2tQjvd1RiYE0lleuqTKZmtmU4RgIYGJZhscWpCcE4wBVUtHQI9XNfZCqoxKb3pTdm+/JNshkDl7t2MyezMN72INEXd99LINcr6d7VALhpIwkUIBAJJzwREyvHMjw1A684w1tP+XwwDKoktL6kJRZMoEqITlYUilrNGHaBMbmLsAOKWYzGFHunGdfQmBkVUZmrslI8joK1bJKXFUmqIQ0bBZm5Fj2ULWCSsz+mQjJ5OATefD+j2Xv7jdReW6owmjAfVQuY1+VTbZAuvpOVBbY2nsxTSqQ9tAsvhlIEqTN/o4hqEBWRi6yR8NPIrZkwiZEbnkuiG9Bz28UUj88sQllsqbfPoIKPDJzVSs1vcTFHaNQ2B/DyagkDW5JPMO4l1FCMGQgEcKOyGOHPfdJIiQ2G8Y42nfDpjd9JsRzCCBF4uOo4JylzzkvHCHFQQi4N96ZJFLGvCXpcBSfDsQgsfBaY0yzA4kiBSqdo2A8/pSBtsThh2o2AXHfiW/CoFoDSZ37RDLh73BJJhNLd4RL2egyQngmbnWfZdJ5Tr6z7uPdbFnlsRvPOdZ43EeZ8T7PifA851HgMvIkFD/iOAr6q+HeJNQHf0dsfikdndgHkRyoQhmbO0BZ20U5XNdBINq0CkJh+eM8Na71x8Ui2STFpVzo2PCYzggN/gDK6vLeM3n44Y/k+Td/C/htufver0FVP9ImXG3qJZGg3HG1DR0ZirJHRbOAMn390be0U59NZ9ospvFh01Rxk9z5HRlm8sGWz2pucXwsTkUmBAklAyjzfjhTU1kmVeUlknvlvFy88Ia8/dbX5I3XvyKvfe0XlUxe/coZeQ3bN177N0adXHhFCjnJseAtqS65II1VV6S9vkCCbRUyFGiQycFOWRzvl/XkkOwtTcjtzVm5s70g93eoUFZBJqtyDwrlFshkbzEpm8lJWU2My9TgkAz2BCXU0Sd9rQEJ90RlNDIh48NT2l8S6ByQrragtDX3SqBnSMZGF2R9/aasb6AAJNZ0WZURKBPOMwlGE9LaMyi1rUGpbAxIU/ewDE6sysb+E1lDZiXh3U7AUC1uPJQb9z6TqwcfQKVcl/7hRYlNgkgWIWs37skK4pJMqE4i4+sSRoEJwuvoHEiiELNZKyLljRwFNoit6T9x0eyM9tLmLmOk3H02gznEowUQhYAd8lQnXNiQE/Q4LNAWEja9KEBEZp8GHIWRoAd9DKgWrDJhp/bWzY/k7vMfKKmQvMx5EoOjYk4DXGMJ0ioTTQcgOfGefSTJ6T0lgAl8V3p0XVa+4921/4SGHmBYZ5hriG1q3FhyHwS0o2RBEiFJUB2ySYFhY2xyQHgwxqXLSWAg5WGjaubhBYZG10H8E/jOVECDmn5LwMxH4L5Z1YDfyaxywDy1zWW6pA4qsP6BE3FZefmd2NdFsuf8AU4C7RnmD5Q4+i6h+VLOPMWWBOJCj2k40hUmYcnKwhqENBUCI3wcrAJSErL7GUaXYUYhOecQl1uGcU04roy7ev0DkMm3tZmLZKLlUIkB5QP5qWrDeU7ue8F4NlwnoDrXEVbBGDI5/GxHAs9oiOhocD049otQnZwEEglVSUMX1fG0hvG4I7SEer0pQ4lrcHruQWnARqw9lKmlu6j/T4DHIJmbiLMsAagHliuWvVUQxq3H35a1a88lOrmt5acVqphqeef2R9rxTjz+5Ce6qjFJpxflU5thnbLH8sa+Fk6WZr1gk9nB01+V28++q6MXO2BrNB7KqCmzrF90TkyYqhYcV2FbhfJ0JPD9vchUK/5AufHgSHJxADKpkKqKEsnPuyRXLr8tFy++IW+99SoI5VeUUL72yi/Ia6+ekTdf+0U5d/aX5fL5VyT/8telhCO8is9JXflFaa7Ole7mEhnoqtHmrplYryxNDsjmXExXDOYyKne2FuQeVMl9EMrd7WW5uTYP9TIta1NjsjgWl0R0UIYDIRnoCCCtbgmAOKJ9wzI8AKZnpzvIpKejX9qhTvoCwzIG4lhduyFLUCex0UXpH0hIZGQWygRGeXhGOoNxaegYgDLph/GISXRsRZa3HihJkCwmkFEL6/dBJp8Cn8jy5gMZT+7JNIhjfv2eLGze03V7uPhbfHpX+lGQ+jlrFgjAg2iB/DSd8aaPhLAK5BB5YN8QjIlHWELheRpmevG9QyswVCvCGbPq3SGcHh0NUSUKHT1mbrVdX4GCdBJwrZJJnyETjqW//eR7sgHDMTi5q+m4zWMvAN4jpUzS06Hi6oJBYn8HKx+XBx91mq5YSfhbAGPAzR8ym2Ho2aRFVcE+E67eOoqKOYotO+DZvNAK5UH1wetJ7GziYiUkQdBr5LVcZnzjxntKXCQZqh82o/XAKwyNcn7Bko6eUYVC4sD99X83rJxscuhAvnEiq+5ToTiVGUa+Y2Aez2JG3rGPKw7VRWLhWmIkByUTfHObZ0r+fkTihBmPPQXbL+Yli0ocW1TA+FtUAkoQFrzW2aYMt4UnjgdVbVQm8LRBJivXSCZGmYyDTDqgwjk8VZtWUIZseSRSHcLIa4LllVvEdVWM95x7beZzHQ9dPNQn3ELJhAtNdoIwToKSB0gE+7ymtp3XwrkIzMJBRP2ObWon/OwGO9ifyya+xw6cL3a6J1fvyTAcGJZFNrWu7D3VocF3YPS59H0cjg/LGss7z3O5+0cf/ljuQ5FwxNc7IBXOS+kbXtGWDTucvQ7ly4wSHYJqX9CyyzTvPf++1pdulG2WXW3CxdZcg3rNeuMtn4zDcodt5SGQUFimUjBOy0kAodBBIaGfQCTEmdqqSqmuKJPiwjwllJwcKpQ3VaG8+cZXtMnr9dd+Sc5+/d/K+bNfAZm8CjJ5XYpzz0p54TlVJw2VOVAnRVAUlVAnjTIR6ZLZWJ+sJAZld35c9pen5cbaHFTKIlTKihxsLml/yfbclKxMjslcfEQmI4My0jcgA5190tXQKV1NPRLsCksYhNLfHXHIJKRkEuwbAZksyOLiVe2ED0fhLfaNysCgWUF4aHxBgkPT0t4Xk6auYekC0QxNrMnc6m2ZW7ktUws3ZJz/MECm78ODIKFsXXumRLPoYH7tjsys3HKIZEk6Q7hHeM4llC540JqpVBbILE7IawmYse6cQKfGXsnFKJGyhqhRLyAfds6bUUxmS4+eXjyXueaSIVwDiB6deqo0PDDUSiQO7HXZIabPxuGK0ckdHa54A97nytVnMOqb5llIKFQVKGTcZg0+m0OgNg3tzEahVnLBMWckkyAGE9syPn/DURx7EoLK4IAGM1kRxA+Pqy3I9cPW9TxJhxWU8ceRX7yeI+8Yl2jsGUce8AdLSwoSDa9NwhHg/yzoGfIaEhTziX1d8Zk9qMwDeKA7Skr8cVp16xAAMtNvRYfAEBsrL9UMKznDeMzvyMEBHK68fPUpPNL3dELm+MItnUzJ5kL7Pfnt3XwiqfNbWZBIGIfgfhqsN5mq+Oz0t6hAWhZsTmMzWjUIIQ1KLiiDaWAY46ajEnnHiX9clWFl/33Zf/A5yOQT7bvjSrmWTNyy6ECVhgNLIkou2OpkUucaInW933MdA5CFwu+cAxKKGbGVBbrYvwISwT5HfFW34Xps2UHf3JuEQlmQgVGWU+TvzlPZhXpnWdq++aGO3ppF2ZrffKiKhBMVOTSYpLF5430tp1TVLNdsfr3z9HvyxFEkjz/+dVUoJCA6P94yr6oDZYROTR8cVt7nDpTJnWff07LM9cOoYlgW9XfkdHoskdAR4pZOEMqScVxATodAkrHlysCfPDKBb2ThqJPjoGRSVV4qZaVFUlyULwUFVyQ354JcunhWzr/9dXnLGeH1FnD+7Csgk6+BTN6QopyzUlZwTqqKL0p92RVpqSmQ7qZykEG9xPvbZDLaDZIIQXnEZDs5LnuL0yCQWSiSRaiVBbm6mJSNmYQsjo9KcmQY8QdxXVQi3SHpauyUzgajTkIgkj4QCcmkt9OQST/IJB6fk+npde10D4bGpTsQl/BQUsZnNiQxjwKR3JAoFEsQYeHRJRmd4RL1UB0giSQYnyO6kqt3ZPfWB3ITZLJ/8KFs7j+VVY7aQCYmQSRziDs8uSWd/VMwNoPSBsM0EF+VIUjaIDK5Bd5wMwx/Bwx1HxTFQHwD3vIavJx59co5OY/Kg81glkwqQSYcxWQMjikEbLNnHwNn8Np1pyhdXW/DKSheMskWTJ/LQHASFj3qtf33UAm+oZOu+KwVeDbGMxMJSRIkgSyB57NkYsjDQNUKwvieHNnFznCqgUF8N1a6ySWQNDy8/hhVxZzbDs19xiGJsHmLTVhTJH+AKqOeFQ8qgoqG1wyMIv8dwmGasxv3Ufk/hlf3Pdm7+4mSCQmrLTilI/eWdx7j/Z/LGBwJNnfVkDxQSfknTu5zeDhRw7lHJJImjtSLuOENyBOq0uTaPdm49q5chdG9Ci9+afsJCOoq3gEOBt6fqOE3AfQY35Ueelq+Onl6CIivqiZLaBMaSCENJA0lDy8YxnP2GgOWJxIGm1hXWDZIJgcfy9jiLSUTdgCzyZLPzue2sO+iTYGAIRPznrZdX8kFMGTC9/Z7ri8IOkDwnH3Jwwemb4nvk7qm3gEXK23vh8OIejyxcKDqZAPO1xbIhORBrO4/gyPxREd3sRxwu7T7WGbW7iqR0AniGmAkkPe++dvyGKrk6ae/ocqE17FJlg4OiYRKhmWa5Y3LtbB5l+Xz4PG39edeJKUwVLxR14OoW4ZIuLVLQOnCtDhOlZ9MIiGQ1yxzXuB+J8EQCogiS5ypqaySyopyqVBCKZbi4gIpLMiR3NyLcvnS23Lh3Bty7uzXFOehVi6de01yL74hBZfPSnHe21JRcF5qSi5LY0WetNWWSKClWiJdjVAZbTIR7pH5eESWxodAKqOylUzIzvw0FMmMbCanZDUxIQujJJMRSQwOy1h4SIb7QB5tAekGaZBMSCS97f06LNgqk66OAekLjOjw4D4okvbOqLQBAZDK4OiCTCa3JLm0J9OL8HBntmRkakvJZCy5q4QyA8OTgAEimXB01/6dj2QPpLKFgrK0eR8K5o6SzuzKgURGV0EiEzAkMWmBN0wS4SqkgzBOHfCk24Mz0jcIQzlBI3hNx6T3DXPUUlIaUQnZJ1DeGAWZsH/FGUasni4LA4wZtoyjbaGAerA4ppfKwsGOOReIX8FrsW+vNx40YaRyJpg+m7hIduzQJpnswggm1x7AwC9LBQjOkJvtvzBkkBXwjOp5O++QOodCzWfFu9KQUtZTVbCZaQjfbhLfnv+LoOKgCiFxUC1w/k8cx2yqYsVkH1UCRo1kwuYp9cxQOUgQ/SD1sfnrMoN0kqjIU3AQ5jcfqCI5ePwdKLB3QTZrIFKupZSQCaii7ZswDNffQ1nYQ96gwnA0WWMERn9IQWKpao5quLsFmVRz/gDQiAoWgAKawvNzZdpNKJPdWx8jzfclAXXCctBAQua3wDfhlmRSj7B6Nao0fDSoMOL43szLtPxlmALfzkVmmD0mWD5YTvAuGXDVBwjEXeYno0yxHPEZqIRDoxuyBI977z5/IPWRjM7fNLOwVSU7JMj8dqBEgvcyfXOGVDSc789z9rxzTHXmPtPLBO/NJi94zyeC8UA+KZDwSCp0/HCM9DjUtq2Pzs8KnJFdOCp0Uh6oqliHA8GBHyyPLLdc94vkwfJHMIzbm+98Lh98/jP5+Lu/L09AKqpMoFDY9MqmWc5rY1kmgVShjrJPj+pjKLEF1fNUbkLt3Hr0bY3PNOk4kXB4jQL5pg4Pl4FSGJuQXoa8QJ4jb9KcEOTLSeDqx2nq5AScqa6qlqqKShBKhZSXl0lZWYmUlBRKQWEuFMpFuXjxbSiU1+Xtt16Tc8AFqJXLF16X3EtnpTDnbSnJPy8VhRelpixXmqoKpb2+XAKttRLqaJThQLtMRPpkaigks7FBqJCYLCfGZCUxju04jsdkbjQuyVhMEkMjMh4ZltHwsIR7BiTY0a//NQkA3Zxb0tYn3e3sgO+RluaAtLWFpBME0toWlqbmoP7Ot717WPrCCV05mP82mV+DIVq8JqMgkeHEphIDm63YX5KAMplZvi2r8BZ2kGm7MDQb2GdTGJXL4joKCIiHnfJN3TAI7ah08CL64JnGp68izX3pCc8rIqiIE3M3tF01sXgAL3pb2065FIOSCYwSyYRQJaB9JR6gQtdppWdlTycJtyMf4WYZF3NOr3PSodo5CjzfDuU0gGfkCCk2zdDT4sqpPZFFKYMx1XhOWoYUsgQMuz4HkCIUKpURTY/vq+GoAHXwqOiRUbZbxcGKN43vzbZhEgzJgWP4Q8inbqgUenETizckAfLndVzduRGqJDDEIce7wpVg6RRMLFyXGNIk8Wxcey7X739DVUgf8o6eHxXk7Opd2Yda2b7xvoyAuKhGKkEUNajMJAmCYSSNquaI5nVzz6jOP2qFZ9gKh6ITJBYaWcZ9bkC13oUieUc24Elevf2xzK/f13LAX0TXonLXap7inUmk8PzZp9PAf7DAaLBZgnlpV1FgnlqUK4akDORWrsCx3SqZpMOoVaZHAkf50RFkHqBcGXCf3qspR1qmsOU9uaxHECpv8epTnWi3fuMDXWCTqza7Do693oENc8mFBgjhfDdLItr8Ys+hXJhn4v5LhNYbL0GcAMZ1yRVEhzCzDBDSQXoEB1qw7lJpciQhHUQ6YlTA7MMjifRE5qU1mAA5LGuYOjUoY+yMZ9PWp9/7A8X9934g99/9PvADOHEfaXw2r1Yh73WrioN1dFr7Y0gm+/c/lVuPP9f4LP+8F+sP45NEqM515Q6WAVxPqL0gGHYIyHPkhRdWAR8L5hu+T7Y4U11ZAyKBOoFCqaislAqolLLyEikuKZD8/CtQJxfk/Lmz8tZbrwNfl3MgFk5w5BIseVfeksLc8yCUi1JRfEVqyvOlqbpE2hsqpKe5Rvo7m2Uk2CXxUC+Ioh+EEZGZ2LDMjsaURGZJJPEYEJfESEwmoiCUQTB0cFDCvRHp72bzVr90tQaks7UXCEhrY7c0NfRIY0NAmpqC0tAYkLqGXqlv7JPGVv7Od0RCQ7Myxn+bLFyTyfk9GI9Np99jBuQAZTG5LeMoHJOcjLRxX9ZQiTZRCFZgHGZgkIilzXu4/jrIA95ZJ4whMqUemdk3uACFs6+eKBeB640sQKVACYFIFjchfbEdmbqKArCgzUv0IipAJhz1ZdQJF5E0bfEWrhGnEdaKbsJ1lAeHHfMY5+hFmn1sQQBKGDbeEaCCIbGxQmjzDDzzDRAK533wHw2G4KCYEJfpqfHPFjQQeBbCex33mVZpfRhbpktEtTKwyYnNWyRjrYBsUgRIKmPw8kgkHC3HZijGI8kQXEac17cGEhKG4hhHXDZBcr2kMFSKUYxbssCx/wcfYfsA+bMAVYBrQAYLUJzX738GMnlPhiY2QSKGNJpgLLtxv65QEoYfRgWGuw7eXnc4iTKzqBNaI2OriujYmg4bn1m+hXw+AO7offZQ6Zd3HqlipXplkxnJhARF9doLY8B3aoZC4k/WavBMFa2DIBNTFrwox3OVtcD5AMpbvcB5PFsFnk23CpYHAukR/O4OsaQIxhpx7vO8LUfG+LA8sUmWa6Et7D7RZT+4yjMXLtR//9B7VgcH4NaBO5rIAY8Zbve95+05fRZLeC8LeLdTkYkFCQXEQXBf+wsZ7hAKHTuqyVbkH5e15yAPTguguqZzxmYq9qVR9aqChsPD5eyvoYw9/eQnSiQffvtnUCnfUtx9+l3Zv/epKmo6V2w+5a8t6Oy09U9pGqwPTGP34EO58c43tcl2auVAeocWlEx4Hfv4uKK52aIMsJxwtCKexeTtEcD3d4F0MsnFD6ZJzJ84/HCmqrIWBFINIqmWSqgUoqKyQkqgUPIL8uXylUty/vxbcvYtjvJ6Q86dexPk8qZcvHBW56bkXbkgBXkXpbjgipQX54NQiqWxulxa66ulp60JpNAl0UA3CKJP4uEQyCIqieFhmY7FZRokQiRHx2QqNirjQ3GZGB6TkfCIDAaHJByISF9XCKokIB0tvdIONINMGuq7pR6oq++R2vpeqSEa+qSmMSh1zQPS1hOXQGQGXiQ74lEIwjPqWZIMWmmk4B3Ep/cUUyCORRgEEsoS5Ow0jpNLB7Ky9VASMFi8nt5pYxc8VRgCkhIN2RS8fKqSLngv4TgXlbwLbxXKBIpncGIL95xDgYP8YybTSDiEwi2NBuVtVbMhBG61Mw2ZznAlCQfGyLDgkGQcElECyYzjj2pcw0mAY1BOXE9o69aH2i5LT4ud0mUw+PaZmBafISvweWmgkL6+C7ap8+Y5SSZMt1zn5JiFM9lMRS8shErFfhOvQqGk7xiY0Tj1+N7h8XWjXFBRuQIBK1Q7Kjf/qMfOdP4MqQ2V2YKEMg2VswXCIHkEQEBUGOzropK4BmVCpyEMw1mJZyJxkEhGQAJRVOZ2EB0VaGvvOIhqQ1Wt6Tu7reD+zPJNs78K1bt0Q6aBrRvPZXHrPkhqXVVsNSq4poMyx5UUIvwDYAzOjP11dCeNqj+Z6PeCcVDQUDgg+bBJowrpatMGnp2gutFJsloOTBnhIAALkoA2mwLWSXHLj7Pvksn2I9mBylpB+eDQa/bhUVkYQ2WcBksmRpGkyITHlkzMufTz1tjpqMSXCJKJVRnZgmTCrZIsCIkkYld1UEJhPBBfNb4fmyi11QD30mMQjK7ZhS0dxSaoOg4EoaLeguplX8fzz34q73/+O/Lowx9BXXys/Xe3Hn1u+vE4whAOB8mAWw7kYV/J1PJtJRL2v6ztPdPrSCYs/31DS0aVIO+1Lw9lg1suPktVwrJifurH72uQRh4eaPMm8iM74PvwO2WJM5VV9SAPEApQWQVUEzVSDpVSCpVSXFYqBUWFkpuXK5cug1gunpfzF84pLl46L5cvX5TcnEtSkJ8rxYX52pFfWV4q1ZXlUl9TBSXRIG1NjdLR3CSdLS3S29Yuwa5uiQaDIJeoTEKRTMVHZWJkVOKDcRkdGpVYNC5DIJQwFEqwl6O4+qQDyqS1uRuKpBMk0gkC6QKB9EplXY9UgkwqQSaVDUGpAZk0dgzBIMAr7OfaOpPS0jum6qIaFbIRxoXeYpDjxUdWJTa9CwN0W5ZAHpzMSDKZ49A/HI8nryIePJG+STUMHTA2A/CW2VRGMJ3W3klt+qJaMd7ytmY+f9RTy8yj14AKz85cNqvolmGsyKzQTqU2BjlVwdPO83rHeKTOsVAZqLI4AvRe2PnNUUxr197VQsrhh+yf4EgrTr5kvEooIN7LKo3sgPezzwXYcPuclqTs0v66rD/ygH+vpFFlh3swxtntUBbY8rgRxM1nZsVhP0kCKmBi6aaeoyfXirzoR9whqBLmCZumSPT8DSvDkmt3UBmfaJ8GFQydBxINmy734PGt4d2D8C6r8N4t8C6HULkZxnlGvTAKOnE1kkT+bkHdbkt8agMqdgekcQ0kckvmN24rlrbuyuzaTeT5jozNbuPea1Ag0yCRKFTPAPI+CtUzIp39EzqScCixIQOjy+rY1HXCCDSGQLBBRTlXqHZQBpQ2hHR1hZI6nG9gOCd3DqoXy/Xk6C1zXyfONhhw36pehZP/bnlRI2Tygl4xYcrhoA5o4EiiOThVmzffV4MWxnfhulFqoJivztbup8HmuWIYhtoQiDeOPffygbRBCi8MR91YAjQqjiSD50faHERhBpnwPc1xLc6bcPaLsRmVzV2rWse4ThebtUgkVCSsaxz9peQAMmH/IFU250qxeWwatmYJqpb9MfzuJJVJ2qD1+8LfB89BtbPvr4aOBPMQjoWxKcw7B3Q0TvN9mR/ZAHmY2ddyFNgkdqaiqkHKq+oUFdV1UlVTD3C/VspBKmVVVVJcXi4FxcWSk58vF69ckfOXSCoXdXvx8mW5nJMjOXkcCVYoRYhXXFIqpWXlUDyVUoM06mrrpB5oqKuXpnoQS0ubBLp6JNIfAoEMy9hwXOLACMiEGI7GZDA8jPNR6e8NSU8nlElrj7Q0dUGRdEhNXbtU1XVKFdRJeV23lNX1Snl9HxCEUQzBg4CEbOMktRFUXI7PpuePD44KxDZHdr62oQB0Qa5GoCrsMOFpqI0ZzngFqSxvPoQh2dFmrS540l2hGemJwIuA4dPmFWRwMzyLJqRFDzmGuASbXNi2zvBqep7wxtmZW0lD6gJGHhXbkgGVyXGgobdEo23sCKPBUAJgM5hjOPxAZRIcXoHhu68Fff/uZ/rPbHpDbMdnHEMkBO/hU/iOgGmzNc+Uds59Tsew0bPGO9MTV28cx/Sq6kACHKlCYmmCGuAxwxmHbcLB+IqML96Q0fl96eRyNyCTFpAJ+0+4vE0zrqWXT8IgcYzN7eM9OdHsocxDmbBDsxvXdUF9sNN8G6pkceM+SGNWqlEWOuB5T0IdcXh4kv0yIKw2kFloeF5GpzdlaBxEN0iFOyvDiVWZ4ArVKygrIJGl7TvY3gDp8L/jSZSNCRiVYeR50KClH0QXQdgIzuP6yVWQyqoEokmE41vA+SlFuS2rCwCm7FY09CMvBkA0IBAu1VPXj20Ix2FVWGxSHZnadZUv85ZEU+4QjiEIQxQpwkgPozq0sOcb8N0Dw4syu34XRu0ZygeIeHxT+0uMxzuM/IBx8eS7FwzTMok8J7EY1TqSdp79QAruv2QYrzv20qCqh+QBJUI1chJ0/lHILL3CJVY4CGTv7qc6Gmt8DuoVtmV9/10dSsz5VkOTO0oYJJCtmx/o0OLVq880jKMWw6MbqrzZ/0ei4eobLOeal548JapQl3RF81OQiTfvjodVJ9nhTFllo5RVNgD1II8GqayxwHFNrZRW1UgRSCEfBJFTWCSXQBoXruTK+Ss5Cu5fzMmTK3kFkptfJHlFJSCeUikqLZcy9sWAlGqQFlEL1Nc2gBRapau9G6qjX6IDURmODCuBDAHRyIhE2AkfGpJQMCIBkEk3yKQdZNLUSFXSLtW17VAkHVAkIJLablS6gKKMXh68unJ4feUglcoWVpgBfHR6duyvwD4yww4HZedo39CikkBi4YbOiqcy4TIrnGsyBIMVgIFhUwi3QcQlibBJhKN6GmDcGjpiIJppJRiCHfZsN2cTSgUqOaEZfggw3o63aFWJH2wc3TrHSiTWOwGsofADDQ77HmggWJiv3fuG9p2E4BlxlJX3/ikvNkugYNoOQN/zgJ73EIkX/FcMK4EpuIyfikcy4fyR2OyeDM/sSvsAV1ulMjGdntGJDe2H4JBiNm+NgRTYHMalb6ZXbsPo31bVyaHcoZEV5O01VZtUKAGQSS2erTuURH7flOtsTmC/DP/lDS89HFuU0alNkArIpTcm7QEa8ik4Cgsgjw2ZXNiVxc0DmV29DuO+CsNuiKS2DYafarkpACcAKrk1BBKIQsEizfiikolVL1TR5fUBlNcgyi3IRIkkBFXDQQEwEsi7SpQdNsfRKemAgzKOd1zafgTH566OJmzCs7IsWQNjyxb36cQQanS0LJhjrwoy9SEMYxiDtzwvM6u34UU/0ZW1+ZsGDhbwGiA3X50wF8xndRpQDpy4Gt+eQ7hptsMWxy8XKIO4j28/wQtC1Q5IQgcpZAF23us/T0j203soe3cVJAau2MDRiWxivv7gG0osJBTOWeHAjW2QydKOmWHP+WsdKJOdbDofXQfJvAd18hxODIeyQyU6eUtbZrdsUlUyOaYOHoLNt5NAh8CHNI7CmdKqZhBGEwBSqW5UQiHKquulBCiurJXCimrJL62Q3KIyuVxQLBfzCuVCboGcz8lXXMgtBMkUyhWcyy0slbziciksrZQSXGcUT71UVNULm9SqkXZ9fbO0NndKF0gi2BeWgdCghAeGJEwSwTbUPyhBJZKwdHcHpaO9V1pauqUBZFILZVINVNZ3SgXJBN5diSJgmgVAKGWomPwXCZsLinFcAnC/zAE9OVasOnysXpAC28wn5q7BUBhS4fwSLgYZGlmSnjC8TiAIhcLj8OiqduK3wJOuRgVh2zgnNA7C0x+e3ISSmZdGVE6SCL1Lepk6zPQQqEiyh1EOhki0Uz5NgaTIIxPVKDwcFUUjxMJMQtEObe2cRiFg+iiIjEdCsUYhG5AINP5x1+CcjmbDs3CVZfsnSx6zaYZb0xwGY+Oc4z7JpAt5E8E35bpcnNDI5jH287CzkqO3OJx4BHlGImFTJUd3MZzOAdUmmx45DDiOMK7FZpsxB1Bpm+F1BzlnZOm27EOxJVDBu4IzqkyGxtZkfGYH55NS3xYBwnA8hpUUAoNwHKBS5qBK5tdv4h6bUKJjKEtUFAFFVVMfiGVAw7jQaGPnIMrFDByRJTgmCRAMhxrD2WmkGiHpUEmzeYwkYsiDZcsMS0YZw7dgPx+X99ljMyXychjeLcmEjpElEjbjEpY0LIF4kUkmDKsDSfdG55SI+c8fGjo2MXK2tfF4DeHb/UxoPrNMOuXg8DnmPx0FksmXAUMq2cCPPPxAQrFzqE4C+1QaOAKs1wx/57B21jk2f3F0H1e95rB1jjKkIxdDWSRmUB45ApHlmPWxEWWS/YXsS6EDuHnjXR3Oznzh4CHT1IVyQTDPtZ6YeVGppq6TYcleocThH0/JhOokS5wpqWqREhBKCQilBIRSUtXgohjGvwhkUABCyS+rkdzSKrlSXCGXCsvkYkGJnM8rlvO5RYoL2L9UUCpXcC4HcfIRt6i8FunUg6jqVfmUVdTptqqmSRoa2qWltVu6uvqlF6QR6ItKECTSF4xKbwAk0jMgnTjX3h7QeA1NIBJcU80mLiiTitpOqJIuKa3tkeLaXgBkUtvntDP3SwlQXNcnRQgr1tV9DZGUOm3RZdiyKax3cE5GoCjGYHBIBpML1yWJzJsEuXTDG27rndA+E9vURfCYI35Y8alMSDZD8JRjICWSDsPK6kBoLpkw4zNxOkJJkQmNbjqBaFPHEeC1HErLwrwP6b0Lw8mCzE5wEgj7cLz3cckhC1iVdBzokXL4MRfE1LZ9Pi/fgeHcd4gkdY05x7Q5N6UXz87FIRuRD6bzHmQCr02XtVg60PklnENCEmGl5cgpVswI4nBlaJLJ2My+9o1MIh7JJDZ9Vfu5Bsc2ZX71nuzd+lDGENaOys9+lBHk5URyF3k5K3WtYamF4a8DoZAE2vviUHUwvEsgJ+0z2QaZcDgwVWhA14KrpSLpiAJUGWzuCkvXwCSckDmUn0ldlYFNYLUOibT1jklbYAzxYfC0uSukfTpVUNQsoxyNRtXLYci7eFYO9AjH1uDIoBLjG1JdsEyZeTIsE8z7dNIgrDPlBcNJJj1Q3tMrHJH0SAdE8FtyVVt6vQoaLKRvwbzy7jMfmW/ecPeck9dl3OL4y8FQVvAjmEzoSDcg22YuzieyE3abeyd1xCKXW2J5Zcc5f/VL4uBseg4fZvll3xfD2QFPtc0JserQ4V10cizKvQ49hzJhPyDtFBUknQXaDjfPcUyS8X7zk+Dm6UlQwjlMGkfhTFFVGwijFWgGmoBGoEEKHRRUNkg+CCAPRJAHcsgBqVwuqZKLhRVyvqBMzuWVyNsAtxfyy0A05XK5qBLEUy0F5XVQNiAlohzExGOATWtVtS1SD6XR3NYrbSCNTpBHF0ilC9uOrpC0dQRxLiCNLT1S39QFIoEiqWuTyto2KQeZlIFMSkEmJS6ZEIZMqESIQhBMEVDMMIdgGG7j1SIT+obm4WluysjUtkTH12Fwrun6XLHElrTCQ2jAB22E+mjuQkEBGlHx6nFdLTKyFpnKDts+VTdbqmzYzMXO/nKkbwyDaUo4DBoBForsYFWIeu8cFeYlDaqgI8BmMLavz0Beb9/6AIXzXbynmQ9hroXHivT0HohrjcJLA40I7sOOZEI7iu09+C7YGjJx7m/DAS41weXkzYrALLDIh8CkO3F0HHlFUolCFZJAOGyY78W+FPaTcJAFm7lILBwUoUPC4SQQbCYaS+7pCL6r+C7sH2M/GvM8jrKQmN+TfpSNOhj8KigIKona1gF4j0PSA3URn9mU5PI1xLsKggDRgWyoNKq4FpyqmHFp6xsFCXHOCpyWKNTr+Aq+/TL24ZQgja4Q++0SMhBbQrnhQI8JqaSBR7mhqqWzQlVCp2YseVU29p7J1rV3UT5v6btxeLPmMwiBTbmGSJjvVN8WtiyQPIyDo1vANAmDTFC+2R/IXy4s774Dw3dH+6VoCL3GJzOf0o6dPNP8y4Qtt3g+QyhfBvwI5jA46i0bsA9Im7E4/+okKPEYcNANl+/R8gpy4MhGLvXDFRq2oDLYwa5LpCAO+6oYX506vIPWdWx5juTOfOD/l+Y37ms5Znw7sVbVKLZGjabnzUnIJJcj4W3yygJnCqvaQRptII0WoNlBEwikUZGXgZyKBrlSVieXSqrlPEjj7fwKoFxxHvsXCyvlUlG15JRCzSCuEhTSK6xolIKyeikEisobpQyKqAoqo66pR5ragtLSEZLWzgHdNrUHpaGlV8/VNHaZZi3ErQCJlNe0SWl1u5TWdCiZFNf1SFFdrwPT1KWEgS2JpAjqhPts7ipucLYIK0UY5yAERxZhmLZkaHJDomOrMjG3D1WyD89vWUmkGpWNqEVlqEHltsd1yEye74RXMTDC5Vp2dfQXDUMTMp2dqSQUeplUJ4dBI356kADMyB1jRIgyGukjQKLgkFc2AbFgruw+0bZZ9hmxg5dxaGxM+qjwhDUMLwFKJHjGdDJxFJUDlyQBnrfXsA9FvTtUTO3Ex3kOGWY/Cfu67KKbVFnsoNZZwijUZoQXJxyOu6O5OHGR3h5HfLFZjP0pVCocxbfLhfpw3BmcBgkkZAx5Ob14A3m5CO8f3jXKTXUTySSsIwXbQRQkhqnFfR3lxaarOiiMKsThtmeA/SskiDlp6YlBdYyibC1r/NnVm0h/G87KBhyQDRDchiQW2MS6DVVl/qlThnJTCoeHI77YjBocnNdm2NXdR7J+9ak2xbLPjqqE5ZjEoH2DKJ8sWzy2zb3af0igHOroMaZNOOcZvw6KqCc6q79dWMY92KzCuQ3VuDe/uzUurkFy8kodHD128i/TyXHiab46KP1SEM0afgTjB1XJMPLZIL1PwpAvDTz3+Q05EpETctevPZdJlCs6PiyjBMlBWxjwvUgkbMLiZFc2a00gn02dfaTllmTiNnMBvFbJhWnYvMkGuDY78P2MUssGZwqqOqQAhJIPdZIPA58PhULkgQDyQCx5zrGGAbkgBxLKpdI6uVBcA0KpkrcLKuUccL6wSi7g+BLCc0Aa+UijCGkShRVIoxwqpwwEU84mtRZVGNUN3TDMASiAfpBICNug1LX0wXD3SBX7RWo7NB5JhCircYikphMKowuE0Q2AUKBMlDxQCQ2BGJgmL5IIjrEt4hbhrEhNUBUhDjOFMhmEKuEMeRLCKBQGh4dSfVTC4FbWghSASnh1RBUqZj0+djNkZ09o2r2OCJFMtM8EFRhxUx5iJmjEUeFOCTYXWQKw8Gu+sGClpqfOP0pylBOlMw0xZ2mX1pJMnHhM/8siEzyjGe7KfqwUoXjjuCTixHXjIQ/Uo9VzIXhjHCLLduUxJQslEVZcpOM2HbKC6b7x9HQfYc09EzCa89rMwMmOozNXdbDF9vX3tIO+JzwLtTCtKiAJwzo4vopr4lAc/VIDz78BRNLWN6ZlIza1ASK5ITPLMA6RGT2ncTqHlEhGk4YweiLTUK5JGZlclykOLwaZcCJtYp7NdNc1jfn1u4h/FaQ0rWpEyaQmAPXNvpchVbskE65ivbr7WEmwB8qLhFNczcEnHF4cwjdwiMQhDCUTzVvmsSGYUnWkAJdMQIAkE7zTFBT50s47OlGuBwTGfitLJITmhSffFJ4wbz5q3mWeB/zJ4GXAnzwy4UccftDVCRyFchJIImZYPFUN1RjIQWH6/ji/iHOoOLudw4E5o53llg4P1R/LrJKvUwepVNjhTgW9vv9MCYXOjw64QJrq9CEutwq8v37nLHGIXI6Ckkn2OJNfSSIBKttAHi0uckEkudzC6OdVp5ALQsmBQrkMsrhYUifni6vlHJTIuUIqlWq5CCK5WFwL9cLmsWYpBgEQhUinACSSX9YoheUIR9plUBgckVXd2ANC6QOJcNJhnx5X1nWBOEAaVCFQTqXVjiLxqJKSum4QA5WJVSdWiaSgfSckEx47RFICsBLx97zh0RUlExICZziTEEYmN6Wjb0IVSAUqZQXil6HSsnKXY5+EUo1K34CKzqaJfnhxwxMbwklr9C4b4I1UIn1VJVqZU00LBukG/wuDP+k6AiQbrgXE0U8cNsshsxy5Q8+pBASZFp9ebYZB+KKwJFIMUtbmxjp6yCSLFHjeC4bZ+RZp8RwlZUfkEdy3hOpVcPo+vBeu0SG2iMO2ZRJQBwiDnh+XRpmcg8eIysp5JmyuZJ8YVebc+h04FewPmVAyYXNVe9+4qhXOQUmu3JDFjTvY3tThviQTNoVRuZCEZkAUiYU9VSehkXmUrRWokDUd0TUEVTOMsjKa3NGJkCsg+YnZPSijhJYXlrOSGpQ5fK8GGJtIfEWfk8PXV3dAJhwsgOcsquoBmXB4McooyxvAEY2WMLSssVmLxOElEnseYSShuvYh6QrPwGu+LotbD4T/7+FyNjopDsbHzmfIJAzreJhjlh2TD+4+4zB/PNdxEMbLRokiciJKAQ4EyAamL89RKCeAZFLdClJAnUqpNrMlCbPvL4L6x5UeOFyd/SR0huxk2xY4OfXaLIbvjGdkExaJhgRCAiKhjIKMWHZteWeLBMu520Lh3C8bGKLLAnh2P9I4CmdIJHkw1nlQJopKg1wCx0RetQGJJQdkcqWiSS5DZVwsrZcLJbWqUC4UASQSHF8CyZBslEygKoqhJtgvU1AB5QMiKSyHWkH6JSAG/lqXhFLV2As1EtCtjtICYZTg2YoRT4Fn5DGvoSox/SVGmRRCmRRCmSgcQqECURXiqBKrSEqwJdgs0AoiIJkMIqMH4stKJjQgEYSxb0Tbrlnp6AGi4lpv0c4JIKEwXgfnPkTn4LHOSlvvuI7KqUAlJlSdOJU5BVZwVvzTQw3xoTB6nf7gPAXK6VBsRWeHs/2VM8O5CrIaLOd6TYuGgIbZNQanAK7LNP5KAEjXTsAzZMJmSPZdOXDCveA1nAeRuj6Vjn1W1+PGfmYY31nDQSIkTL6nztdAmmxj5koIBCehspNel9FZugWnYEm6YaTZZ8Kh4VQQVB1VTf0w6oO6z4VD51ZvyfL2fQVJg+H1bTQEcIZAOmwCY5wkVEtkdBlkwAmy8xqPhNQZnAAZTGqfzNTCNVneuo90uRTLKJ61F+UMxp5qGM/M+UqDY+vatJVcuS1rUCbcpzIhkfDdKpy5VVUAySG9rIFEUN4JOlFeMIxls6ZtEM8zJRNQS/Mbd3WtM04C1Vn6+GbaDAPjwn1vXhsjZsJsubT5zjCe84JNlyVfBvA8JfDUs4G/qjkMY3gNqZwEEgaJhFvj1dvvZb4Zm2Z7YB848rBPJ0EndFAF+0WCI0s6l629f0qb3VV54BrWT05DYGsCyYTKtAXXsF+M3930uRpkfueTYZ/tBOBZdAReljiTB2WSp6okRSQuSCZQBLkkEiAHZHIFBEEyuQQyuQT1cRGkcQHkQVwsqZdLpSacyK0gmXRIIQigAGSQX9GqKAAKK6BYqtlcBQUCUqiAuqioB5FgW8YmLBBHkcYz4H4xnrMYaZWQaBgHKMT1BUB+tUFBTY8UOKSixNJgiMSQDDvjLZkYZcJlLsJjq8J1mKhO2IbN9biqQDas2BbF1d2o4HaCGb1GpMG29GYOAR3UzvmmrpjUohCod6nxTCc85xGkwxLK6WAJwhhPD9T7Nk0bmeB5GlAWYhqhBXie7MDmPJhikiPO03Dp6DM+9wtCjQjT8sFRpMGBEH7gNSz0brpewGAp8SHOIeB8Gmjc8G5MU9ULr0O4qhccc+Y8VzTgz9BmV2/rhFQdmTe+rmuzTYMogloWODprCCQ8K+OznGNyFwrhgSxgy2N2pNe04HlRvqhOSB5s/qJqGRxfU+eE6qW1J67ERJB4mrtGQCI7uPeBNrPWoxwVVHTCYeqFE4N8g+HgaMLhiU1VTjNwBjhbn8THIehlJBy8Ty2Ijv10jSx/SIOjwLQMonyyHLI5rARlNxOqToDq1gjUWkLGZq/K7DqHWO+reqNBtKRAQjFEYvPB+d7eMAcaTjjXal5in+dKvgQUKwZOBEmH6iQbcASir4H1gSEQGFTsWxVH6PfDs3GfKzuQoKlI2MRFMqEy5sAfTk3gPkmGhEKCYF8Wh2tz7g+HhHOwCfv/rBrn/BILKhnNhyxh8+REkLjwbt6BDu6gCh+c+atoRIi/jIax9QLhgwY8l44B+cuIwf/pbP2g6TAN5x5e/LUH/2kw6oH3XDgDTjjjeGCf869wfSb+enDQQWr/Pw0Nyt8MDcnfxWLyn8fG5D+Pj8k/jo3Kfxkfl/8yMS7/MBrHc5hrzDPhGuBv9DpzvUnDpPM3w0Pyt8PDCu5rHOea/z+Az/iPo6Pyz1NT8t+TSbzjhPztyIj5FplA3NOD12WkcwRS+eEPjafp+d3HIpXecUhL07OveQYwv/hd/gXf5f+anpb/OjlpygPAY4Jl4m+duP8Qj+nxv0wl9By3LC9/Hxtx8/xvkf8sT/8yzTSn5J/wrXkNw3g9y5Mtx383Miz/nJjUtBjv75gnei4qf4O0eMzn43P9cyKhW+Yf4/MZ9X5I4x9RXpk+7/OX00l58PRTufPOh3Lr/nty/e5zuXb7qewD1+88O4RrAOO98+435bPv/ES+82s/w/Y3cPwtufXgA7lx7z25gfO6Ba4Td981cMKOBa69ef993eq1BPctbNgx6BtZkMAQlP+RmM8ew0grC/QBHJyTDeiIuog5wDN7EULYAAdlQKGyqZSDL+hwUN1u7D+WrevPZHX3oYbFpja1WZT9apvXnsj+3Q81Dh0XKl2uOcg0CF1/cHgezuIcgC33XwBBPFcm+N378E5e+L2/xZn/p7pEfo6f4+f4nwP/o7tN/uDf/6/ysz/4U/mt3/tj+clv/aH86Dd+T37tJ7+r20z8EPj13/oD+R3E/w9//hfy5//bX8uf/Pn/Ib/9+3+K8D+UH//mH7j4EfFT4vcNbJhz/iSYuHgeF6nrj0NiaR+eOX85cBSuZo2Jhb2sMAkkFrg6eJZYNOCIvalFXHsEJvG8iYWrUK3XoW7vyc7NpyDtj+TBs8/l4fNv6/7W9ceyvHlHNvYeysE7n4DYvyN3H39DNvff0d9qTPMeSINIID2mqcDxacFnOQr8BpN4NxfOOx6Fn5PJz/Fz/E+E/9HdLv/uT/6j/P4f/bn87A//VH76O38Ew08y+RmIg4SSTio/BMmQTEg+/wEk8mcgkz/+s78AEf2JkgnJ48cEDbtDJD/8DYdM9NiEeeNlCz/i8AON8ASM5dHwJ45MMF62mCQcUjkJHGiRDn/jrNC0QSjALAhlZfuu7IJQ7jz6VB699x2Qyreg4j5UQtm98RQk8pk8+eC7IJRvy9Vbz2V5644kl67J5OyOTM7tyMTstsIllNMAz3My0gn2OPycTH6On+N/IvzfXa1KJL/3R3+mBEEy+TGMvZIJiMMPaWTyH/9K/v3/8r/Lb/7uHys5/MglDgMqGQMnDFsb5o13NJDmKUFPn4ts+sMQih95fBG4hJIVvEYVx0eAZEI1QRIYT24p+DfYpc3bIIpncu/JN5Q0SChUKAcPP5bH7/2qvPfJD+X5xz/QY6qT2ZUbMpE0JEKMc+t8j0mFD3G8ADIJ9iRCOfOXkbBkwtt3on0kGm76R7xI9Y848bl10tAwX0R84BfvGOiz4boXgfadGGh/yJBpd/57pz2c7c9sH/fG0f2o5xoLhHnh9uk497Lt3zatfzXos6SD78R29v82M6N9BP8QZ7+Qcz7zekWqz+FkZF7nPfbA3gvbv/LAPuOh+Gk46n5Hw+RTqs+EcM/jfjzPvpO/j5m8Z7+E7Sv578kZ7fNguPaFaZ+ITdOma/a992I89oWwD4P9IKYPZlT32T/yXycZNir/iO/PrfaZID+45TH7XEwaI3rv/zYz7Z5jnwv7aZh//zQxbu6D9P8JaTIu+27+YjIhD59+qrj/5BM5ePC+3LjzTPYPHsv+LQcHT+Ta7ScmDPuM8+T9b8k3v/tT+fYPfks++uYP4Sl/JNfvPNc+FW7tPsH+FxtuwzJhrzmEuyncULx7IoLDcxIYTB6JXsXsSwf/RZMNOGDH9FlYzB4C34HDxIkgjgPRGekNmzlIAyPzOg+JIwA396FIbj4H8B3vfiC3H30m959+LneffFO2oVQ4JH14YhX35HqBBNLWZ/X/Nl8I2h+VPc5cKWsVi5yyFskpx9aDK8Dlsma5XNokl0oa5aID7l8u5XyTZsQjWiXXXqdpOShvwzaF3LJ2yTuENkW+BwUErrXId5DHbUW7FADc5llUdgCditwqL7okz4OC6m4H2Mcxl2GpauEw4TEJxcySFlXNA1JU1S3FNd2iy7VgW8S4PK7pUZQSSKfEg2Jcw+sYV4Gwo9GThsJTIPPaQ3CfIwUOHWWh5wQ5TpTjBDmO8uE5DjEt5og1oIjAN+FaZ9nCTBhNXaPHNi0PvO9QgPtmQt/N5zrCez8DhvUif06CM3LJHdGEMKYHcJ9DtzkCr7M/oX9TnJjbw/e5qfM/xmZ2UOm5wnBER/CZ9JD/2Jrl483WlBMcI05lU7/Omu9DBWdnaW8kqWmz83UsuSMJpM/JjFz0kaO+RibWJI7jwbEVNS4cglzdhPLYMwYDs2HmoCSvSl9kVtoDE7qfmL+Ga5cRd0jzlPNXmH59x6DUtkWEs/CJmtawPl8h6kFBRYeOFCtA/bBlk+Hcr0b557DlxOI1meZwZjxLTWvUzUf7zdPyld+ijqPv0sNMvmTmlYF+f1zjgt/0JYAjNIvqgi8VZoi6MxLxBHhHLhoED0FHcNp5ZnqMZ+fIRTw7jzkCrwV5zs56Ls00PruHMnggCxt3dbg2y+PI1JaONuSqCGZCdL/oShuADv1+6fB/36Nw5kppi7gAMRA5zpa4XNosl0gkII5MkEyulDWBcBBXCYVk5MVhcskFSZBQUiCRtCrySz0gqXhIJI1MykEkDiyZ5Co6JJdkAuQ4sIRiSSUflSifW5zjdQU4X9ncL62BUemD19DcHVPDwYrG4cA0FNy6xw5KnPAUQDZAkQf2nDfMgGEpFL4AMtPwopCGOQOcHd0Dg8EhsDMomDRyLMg8VwwjTkJxyYgGhHCNw/GwxiTt2KblIEUkeB4PUkRikX6dwu9ZGAZ4h28fAuIp/M4ROEeSYWWs7xjWuRZcDofDeTkBletltfaO6wRUDvs1RAInQq8zRMKtdTp4zP+UcAHH7oEpJRQ6J42dI3o8NM6VEnaEy6nQu+RoHPUqkS/d/ZM6dJhrgZFM2nHfWGLTzEGZ3lbyb+mOy+jUtkzC0ITxnCQTksAwvFoSF0mMZMZJltxy6DrLXwEcLXXAsC1EuVcSYTl0yjSfl8/KP0uSUPhcdD5889UDQxLGSUjPJ4Rz3z327jvEYgnlC0InIyMPs4GujnEEDsV3CCUTOk8qAzoxFsY0RSRmDs9JIKHYCaScQsDpCC29o8hT/r2Vf4PdlhjA6Qo6vBx51NrLX0tHtcx657AxDftNbJpfBJoW0vUjDYtiD3h85nIJCAO4AtKwuFzSZKAkkk4kqkaIMi9AKA4JqbpJQzqZpAjFgseGTDKR70HaOYdUFGlk0i45IBSLK9ySUBxY5WIA4sH19NQqm0OqTHTyWXsUhsZUQLfSAayEKTJwwPMgJoLx04Bn0Ws0TiZ4DQw/jagDr4d+EhjfXu+Hwko+bzrowXSGEiASeN2Q0/S4WZh5zpAJjAGvh3ExMMbhhaDGxZtWCpY00o5xX/fdPOdS8HkWqqljYMjC8Ya574VznvOGCJIKv089jHMTnAka/+aeUd2y4lawsiKOq0q57zlOCwNozFt749IenND5KTxu7BxW5RGBoY7C8A8Mz+uCka0gCKoR/iG0Es9AVCBfGM7Vi+dA/tH4ihJJHZ6FKy1MQt1EObGWaUa4JP66zqxv6uZEWxgpPINu6/nuKYdGicSWSaf8UlFTxQSHuBLyNSizXWFTTSXVufPdSQKHvj/Ad9V9zW8H9rznmETi7uMaws2bLwxj/P0I4mWD99GVyQ/BSy44zgI02GYOUKoMckJ0NRQKyx1Jgw4E/xbLfc5ha0B+szxWcq4IScS53pQ753s46b8UHEUmHiJ1gXCQCYkDJOIC5FEM4ihukIsWJTgGDIkgfiZAOFcUuN5VNVQ6DlT5tCpygNxDaPGBIY7089h3CMVVKzDa+TDeqjQcqDKBpHfViQf5qECMmw+iyQMKYdgpMduC45pxVSAWqhXbnEZCIZQcsLWEoOG4rw3TfRem0tpr/YHK7QGb3LJF5rWHYO/vAYmDXjJnXM9CmfDf9hUwcoxvyAQGh8bcgscwki8CSxCnQerdfM4f9SzWYGWgGOdUtbCSqaLAFsduxeU5n2NWUKoQgpWaa22xyZPfySgQ851sc6e5j9m3afBeVARUCaz8TIfnufIwl1ppA8l09I0r2TSSRJpCSh6lvBbPrj/NwjM3QimFkEdxqJNeGJU6znAH0QyNrSqZDEE9kWB6wlMyMrUBL3YTzgLKLxQJm98sSCYWttx6yzDDSWacoT+1sC/xmS1VsFyahd/dKgyX5PWdTZhVHC7p45yFlgE3vjk+dO1LgVE6Zl2+06Owxj/cD/ZemVBCcY0wDXp20B/6OVuWHX4n7vOHabYMsvxVOWWS5ZBlyxCJucZchy2PXzosoaRgFBqVWyaCcuZSMciAcBQKySWNSBxQoZA0tP/ECxtuycQXKUIhmaQD6gVx0onkeBh14igUJRPbZ2L6TZRMXFCdGOQ65xUOmbCAcwZwawDsD6+0rCFglI6TfgHSViCMWy9puMesmJ7wo5BSLqbt+ovAjzAs/OKz8PGfGRx5MgtlEhpZVFnN+GogWfldA+4x6o5ROBXcNAxcIuSzOPupexl4z2eeU/jd5xhYI2aMl9m3KoLkyS0NuBpxJ4z7/E4WrLRaeVFZbJxUvxi+GYF76dZJ26bBWfM0BlQaDKdaqGzoU1KpbRmQahh9kkaZXoNr+UyACetV8ugE+QfCM9r0akmGf4FkU9kwyKStd1SXZqEqGZ3eUpXCGfildUhTm+P4zHw2D5ngG6fQoecaOgyZcGQSJ9NxRj8NGr+7/Y6aL2nf1YDHmd9egWu5NQTvOc64/ovDKCGSwpeFNDLBsS/seYUluqNBp4MOinFobBk0jomWPXx/LZ+Mg2MF47r7zjUOGOZPCF8MvsSR9q4OEG7IxDZrObhUBPIgSCKEKpOjCCN1nSobG+4qHQuQiQc5LpoVudj3I46UesmA09zFpiqzJQHY5i5DHEQOjgnbDObGY38LwIwlmTRxqQtU8qKaLpMeVZGm7XT0O1slFcIlBksO3uPjYZXUi8ISxJHA+2eCBZFyeXzuqjZzscOWa4gxvvUs1fBXOkadUMNOI3IKMA1Nxz6P2TcEzue393DiufFNP9ahcAukbeF73zRYI5bylN1jnlMSYOU1BEAw3OybCqzGHcdGuZiKTmjzEJ5RgefSMOxbQ2BhyIhNGaj4Npxp4BpDHkwD3x7XWiIhdGAHQBLi8ipNUDdsAivDcxB90VntS6Ey6QyyCWRUfwkchzphUxWXdSGJWDVi+/KUTPht9BubcshyrGTSOaQzqVk2SExcYp+GhN/Slg3moXuM50t9V5JExvdnfuG93PjYMg/dY+/1LwVO01oWKHwBeK+3yiozrERJxZ5PGfmj4C0rFrYMkRjoyPC7ZZYrPa/384bhmGX2pYMkkQ5DrOnvr0D4GVUlGbDNXAaNqXMkjFIQQwa8ZEKVwaYyE8Zz6VBiKU6HJZQUwRgYgkknkVS/ixcpMrHkcSSceJZciut6paYtKg1dI1rYjSpJwfbJWDJh89jLhr2H37mj4EcYFuY500ED2QLC1JVqV29KeHRZ+Jc/pmUquTUCHmNDA0KjQEOQJdKvx7PgmPdQguez8Rhpkly49cIvTIF0CUss3r4gXzCOGjkCxgbQzn96x4TGoZFjBTbnrdFj5T0EpOeFJRM10rzW2fde41Z0vQfDUtd708kM02txDa9lMxVJhYTEYyokDhIgkXD9sJ7wtDT3xKR/mD9nW5cBEAI705nXaffTZzP7VpFo3iA/ikE8bI5jp/vY7I6Wi2YQFA2e+Y4GWhZwzG9kvpWBnmc8LxDXlANzjRsn49qXg+zJRMkB8U8NfAv9zQW2maSgoAIk/M4dA7eMELiPt/xY2LKQBjoLhLvvITD7LC8FSDcDSiQ4R/C72G/E4zOXikAchwASceENI7E4YB+KEoglDkso3Np42FeASNx9oCgdV4AcJZV0MjkEKBVfOARDmGHObSAND3icCeccl7Cvag1LPbwzFn6ShjafKQyJGKWSUil+SMX98uEdzeYPpz/JA3qmTSDM2PSmdsKHx5alrj2K9MwgBDbVcauqyb6XGp2UYcgGadcrTHNiXjnIBKA6cYH4afAJt+TjhatsToBLLF4cFa5wDOaRoJKwfQ4pY304XrYw6RyC3sNJnwbYCacy4crCHHHG0WZsqmQzF8mEw4PZsd+IckzySaWTuoeSCPKCikTzBmWFxqixa1jXjuKoMM4vYH+P+RYeIC37fTK/GfPdkJS3LKTKjhvH9/rsoe+hhJSCdRiyhXcgy0mwTXOKGt7r8P0VVH2O8jsNvCRv88gLk/8kFA9IIC5Sx1SY7nN8iShU4Fs438MFwkEmmaRhcNEDG3YZSsUlE4cYSB4WOTz2wMQhkaSTiTcOoURyHKxq8SMSBfteDGxHv86bgaE8NO/FAuFsxiKjcuSK9dJts1kmGJ5uJLOHX3oWavyzjGvhRxYngYWWI4toMEgm0YlVqccxlR3v6yoJfIPU8zjGxzmXDdKvN2mQTKwysX1VZt9DIEDqfCosn4DxTyOTiizBuKiQp4FrtLKANfZeg69hzv4LA4bXEkohvgeNNPepONgxz6XrOVyUhKLzWThfBflKQuHwYvbzeNOzz2PScvIK+8wbjvhinwwXCyShcCCKHYRCZBp0/T58Xwc8NvEc0jgGmemcFvo+nnsbeAz+CdD5ZRmE4cKe98IJN9fjGQ7d2wKGVuF37mh4ycQXSNOPTGxTqIWSCc6lnuNoaJow/MfBjc99H2R+VwXCz1z2kIUB+0yAwia5CHDL4xSJNII4LEAGlkgcGILAOQ/hUH1oGpqOjWORIgxt1vKBbQY7qv/lSgnIIwOXuXVIxQ8kFBIEGbaskUvS96vx8x1+bJFmJI+H2zxG+KVl4cQ/dI0fPNf5EYaF+w4e0DhxCChXI51ZuSFDMD70SEnGmh7SN2SQ/h6nJ5P06+2z276sTLLICnh2r1LRyXfZgGTyAvAzZFQzrpG3gIG0Fd8ogIzjzPhZwnr53KeKsGTCtnH+7oBzhEgk8aktnV/Cfg7++ZE/7aJS4YguXmsMkgPs23QJqx4qGoPS1BMT/hGS/6XnxEcSTEpJELgWaeg+t17wnBvvy0bGvV34GDcfGIJAHvvhqLh67HfPFCw5+J07Cmlkcgxs31cKR5OJkgGusc/jh0zi8IMb3yqQ44B4Cuw7zVyHlYlLKgob5lUmllhACJZMQA45CCOuID6JyhKJTcM2bfEcm7eMMiEcUvEB47jE5MAllmKQSQYug2AUMJSpkWTpsHNg2CyjmcsPgwKrhg/hmVCjnGG0j4IafOcav7S8yDZNgnH1GsA7BycT9t5e0ChxpjOXwObvY4cT6zovgWTCNPUeiJPWTMbjF4G9HtCmOYRZMjktrJKxMMonOxhCeRHAiHjJRWGNfYcHNuwoeONmD6oHsw8DivfglmRAw8Hhyh0gDP4amGTCPzayv4Q/7ZqY3dURXTXIZ1UhvBZlWg0Trvemb8mfkyxJIPwdMZ0LkgsNiT1/2KBnAM9m49lrviwoEWbe35JBlshUuRZ+cTX/ueX3qMb7Hbq3gTW+fueOgnU+joOXVCxIKKUZYJg97xLBMfCml4nMuC5Z+MD9LgqSSWEDFIg/eM6SiB9Ms5cBlYiSCPd5zoFeX9iI9MzWEArB82bfKBmSBI4JXqNIxTHHZt9LZoZcbFNaBkA2R0EHD4BQtFmr0hhB7ivJuGRDQ+uFv6H2gyULA3PtUfC73g8mvnmWvONAgvCABMMlafhDJq4JxJVNhxNr0tIbgxPgpGeNP/uG3HsaAvOSw0nwEql5ZtNEaMBv/MWQXZ+RhT/JnAQ/Q0aFZg30lwLcwzX2nmMvsXAIMidQsqmrOzSlzVucVU9VMj67I1PIV67zVN8WwXVQlfjmNk0LhjNNQyjsM+lGueiX2jbOaegXs/wKv0PmiMXjwLg2Pr67XvtlIPO+FiQyBzDCh0jBBZUt3i0NRu2q4vUgLVzTxH0AfhsLe39vWLYossD1vsC5YhLKIcDo+8BLQv73Sieqk2Cvte+dDc5cLKyHoffiCGJRYkiRhCKNTAyJGNTjPMDr0tIBIQAMV2hco2JMsxigpOG9xqRhiM1cY+OkiAmE4oVHwSigmjJhR6JZ0iCManGIRuEQi2OUrSE/NXCtr9EHMuP6xbHgefssJIyTkFvK+TvNup9f3govNCD8XezE3I6SCZeQMfekMjHqxJAAw7xAmM67ceAQRVpY2rnUtZYwTV+VM/jhFPCO1LNkcnhtN3/4E0wWgDFPIxcCxFT4RYF0soY3vrNPQqE64SS2Jl2iJSEDsQUZmVyDKtmR6aV9iY4t49wQDAKfuc2QB4x7Id6LRkr3CezTQKvRoodb16PEUgQvU89lQQg2DatIUx37cCzs/hHQ9D046bwi4/4GlhRSSJFKOgw5HI6fDazBtER8CMedOwKHCORFgXsTlgB87+XEOQ7u9QSvw9ZLFpkw3wb5pQCZXCioE4vDxJJCujF3YMnEDSOB1DngNea6iwUNSN9sXWIADKF4yMSSBK/JvLcFzztxDFKKxagXkAXA+TMWKQXjJZPTAKTzBWAVwlHINh5h4mUBqK9cvCe3SiYw5mUwGG0gkNGZTSWTjuAYKi7VhCETbpXUMu5pCcdC42SEpZ07dL0lk9PDkJFDKhmwC4QeCxLkKZFp2BSZhHNKnEbZqOHkNfZ6vAf37Xl2xHISI2fU98A5iMQXZGxmS8lkaIJLrwzDW4UBxbuQOHShVHxH3Ud+M8+9YJivoXbi+8KNczi9LxOZz6F5o0YtS+D7pcEvzIYr0tNXJfLSQEJ+eUjLOw/MeeeeIIFDpHEEeG2KLPyRhzwguJ9OJgUw3seBht0lDoc8MnCpqM6BIRN77QXdGkLhsRKNmw6NvSEEHiuJONcplFC88Q2hmHPct9emYIiEWxx7YcnkWHjVyReDDh7A1tfgA0okjHNCPMIb15BF9siHkWf7ajMMDdvYOfKns3/CFJhDZIJrvFDi8KoNA29Y2jle48DbZOhHFi8Kq3j8CC2Fw0SRDTKJ4GXAksNpYfvBLKHYBVCpUrgMS0N7VHrDCVUnbOYyZDICwiGZmOZNbk1Tp4HNb2OckSYNAo6tU+EqgWOQZsBw7DX4XxYyn8Ei3fgfAyUKxrewYZnhDlg3HBRUpWDf3QWM8iEPPzOOH3CPlwW/7+KFe88sn9MSkV9ambB5c+Zifq2kA6RyFJRwPIACIS6lAWl4wXi49oKmcZgkXKJwkCIS5x56n8PxbNw01eKolEOAejpELDpP5jj4kcyLw6gEf9iRcITfeYts4viBAxxIKMUwMPXtERkcX5ahyVXpHpjUZg01JJYMSAKZaTCM5yx4nBnmPee51pBk+uCHbGGIyJ9MiOwIhYCxPA08xPKyQAIwhj0boJJiS+LIK8XzA4YMUHH5PvguPEf1UV7bK60gD/aVjEFxhmPz0tQ5iHPwLEkOiE9HwoWT18wn7qvhgDGwjgC3lmiOAuMXOjDqwAGve1FkfT3jeaD3pkE7GZkjIo1X7YTZ8y5s2kBlCgWAfXcXaoCNN+8a5Mw4HlhV5XfuRZGWDxlIu5ffs3rhiWuf0w9+9zlzIa8GRp4kksKF/JrDQDy7b+I48TS8+gjwnI1rCCUFG54d0sjlECwBGYJJwagcVUmOmlEouaTD2//jwpdkTgc7jDrnXxsgTO3HcrY07CwsNS0hCcfnlVCUTGB0aFiUpJzt4fQcQnHgkponLPOcvdaQKVTai8BDLH5w+7JOgD/B/OvDGPYsoSSCZy9x4BCKG4at/vMHlbimuV86g2MSGpmV7tCE1CKPC2n8SA6lIA3EdfedLfNKiaMC6cJIW4Lh1iWU44DrCnitcz1hr30RpKV9qrQQ1yWGE8B4jO+HtDRw7IG+owd873QgHxyiMcbWL04K9ptZpfgykPmMmbAkkPasmfDGOQZ+6fN9zpzPqQQhVIMgSBIGShCKajmfWyWMo8hNxeV5Hp+7Ui5vXS5TvE1cSW3P5VTo9ekEdBRIPCfBS3gp6HGBBYjKQTqxOACx+MGPYLKFLxE5MAbdGvWj4Q6pPgL2fAoNMNZHI3VfAxp2FoSqpj7pH05KZHRRugYmQCbtep5Nh0oAfvdyCCWTKNLDvHCuA/T5EfZi8CEYD9wmP8c4Ho2W/8+hJJAt8E6+8J4rdYD90pouqWvlD7VGpLEjIhX1vTAwjNukyC9rBvEw7dR13u+jYYjjD1x3BPJ5D933u+60SE/bP44fGDelUk9GyxFwzuOdiDyi4jD4zocAY5pOFD5xMoF7ZgvmHfPzOPjew0KfzUMIfkRCeOO4SL1b6v383rFF/l86rNX8JH7AFQAAAABJRU5ErkJggg==
''Unweighted pair group method with arithmetic mean'' is a hierarchical agglomerative [[Clustering]] method, which means that one starts with the objects in separate clusters, and gradually merges these, depending on the distance between them, to form clusters. A distance cutoff has to be applied that determines when the program should stop forming clusters; i.e. once the distance between clusters is over a certain value, tehn no more merging should occur
In any [[lattice|Lattice (algebraic structure)]], $$L$$, a subset $$U$$ of $$L$$ is said to be an ''upper set'' if $$a \in U$$ implies that $$b \in U$$ for all $$b \in L$$ satisfying $$a \preceq b$$, where $$\preceq$$ refers to the [[Partial ordering]] defining the lattice.
[[Official page|http://tiddlywiki.com/]]
[[WikiText|http://tiddlywiki.com/static/WikiText.html]]
''Van der Waals forces''. Due to fluctuations of electric dipole moment of electron cloud inducing correlated fluctuations on nearby molecules. Goes like $$1/r^6$$, and it is $$\sim k_BT$$ at room temperature. Approximately isotropic
//aka symbol code//
In a ''variable-length code'', one assigns a //codeword// to each letter in an alphabet. Formally, a variable-length code is a function $$C: \mathcal{X} \rightarrow A^*$$, where $$\mathcal{X}$$ is the source alphabet, and $$A$$ is the code alphabet, and $$\cdot^*$$ is the [[Kleene star]].
The extension of $$C$$ is the natural expension of $$C$$ to $$\mathcal{X} ^*$$
The codewords are all the elements of the codomain of $$C$$.
$$C$$ is ''uniquely decodable'' if $$C^*$$ is [[one-to-one|Injective function]].
[[Prefix code]]
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[[(IC 2.2) Symbol codes - terminology and notation|https://www.youtube.com/watch?v=V4ztxmE9Sys&list=PLE125425EC837021F&index=8&spfreload=1]]
An example is Morse code
[[Non-commutative Symbolic Coding |http://users.aber.ac.uk/rog/gkl.pdf]]
Kadanoff’s variational [[RG scheme]] introduces coarse-grained auxiliary, or “hidden”, spins that are coupled to the physical spin systems through some unknown coupling parameters. A parameter-dependent free energy is calculated for the coarse-grained spin system from the coupled system by integrating out the physical spins. The coupling parameters are chosen through a variational procedure that minimizes the difference between the free energies of the physical and hidden spin systems. This ensures that the coarse-grained system preserves the long-distance information present in the physical system. Carrying out this procedure results in an RG transformation that maps the physical spin system into a coarse-grained description in terms of hidden spins. The hidden spins then serve as the input for the next round of renormalization.
[[An exact mapping between the Variational Renormalization Group and Deep Learning|https://arxiv.org/abs/1410.3831]] with [[Restricted Boltzmann machine]]s
Definition of //shattering//: [[video|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=8m54s]]
[[Definition of VC dimension|https://www.youtube.com/watch?v=0kWZoyNRxTY&index=10&list=PLA89DCFA6ADACE599#t=13m50s]]
the VC dimension (for Vapnik–Chervonenkis dimension) is a measure of the capacity (complexity, expressive power, richness, or flexibility) of a space of functions that can be learned by a statistical classification algorithm. It is defined as the cardinality of the largest set of points that the algorithm can shatter.
In $$n$$-dimensions, the VC dimension of the set of all linear classifiers is $$n+1$$
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https://www.wikiwand.com/en/VC_dimension
https://en.wikipedia.org/wiki/Del_in_cylindrical_and_spherical_coordinates
[[History of the videocamera]]
the intentional use of physical force or power, threatened or actual, against oneself, another person, or against a group or community, which either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation
https://www.wikiwand.com/en/Violence
See [[War]]
The Virgo Supercluster (Virgo SC) or the Local Supercluster (LSC or LS), one of the millions of superclusters, is a mass concentration of galaxies that contains the Virgo Cluster in addition to the Local Group, which in turn contains the Milky Way and Andromeda Galaxy.
A 2014 study indicates that the Virgo Supercluster is only a lobe of a greater supercluster, [[Laniakea|Laniakea Supercluster]], which is centered on the Great Attractor.
A representation of a fraction of physical memory in a computer, which is created by the [[Operating system]] for [[Memory allocation]]
[[What is virtual memory, how is it implemented, and why do operating systems use it?|http://www.programmerinterview.com/index.php/operating-systems/how-virtual-memory-works/]]
''VR''
!!!https://goocreate.com/
https://www.youtube.com/playlist?list=PLbMVogVj5nJSyt80VRXYC-YrAvQuUb6dh
http://elevr.com/
[[Bringing Virtual Reality to the Web|https://webvr.info/]]
http://andsynchrony.net/projects/loop/
[[The Untold Story of Magic Leap, the World’s Most Secretive Startup|http://www.wired.com/?p=1999666%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F]] http://www.magicleap.com/
http://www.forbes.com/sites/theopriestley/2015/10/24/why-magic-leap-needs-a-dose-of-reality-to-succeed/#1c4ce8c948be
http://www.slideshare.net/alexglee/magic-leap-augmented-reality-strategy-insights-from-patents
[[Axon VR - new inmersive VR|http://3dvrcentral.com/2016/05/06/wear-intense-full-vr-suit/]] also see Omni
[[Augmented reality]]
[[Tutorial: How To Build Google Cardboard Mobile VR Game Bluetooth Controller Support in Unity PART 1|https://www.youtube.com/watch?v=Vrx57RVTjwI]]
https://docs.unity3d.com/Manual/index.html
[[WebVR]]
[[Bacterial virus|https://www.youtube.com/watch?time_continue=50&v=ymDAQtczyi8]]. "Bacteriophage"
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
''viscoelasticity'' is the property of a material that displays both viscosity, and elasticity. Such materials are called viscoelastic.
See [[Viscosity and elasticity]]
!!The response of matter to a shear stress
__Hookean solid__: Shear strain proportional to shear stress. The proportionality constant is $$1/G$$, the //shear modulus//.
__Newtonian fluid__: //Rate// of shear strain proportional to shear stress. The proportionality constant is $$1/\eta$$, the //viscosity//.
__Viscoelastic materials__: Different responses at different time-scales. Often: elastic response with fixed strain when stress is first applied, but after a //relaxation time//, $$\tau$$, the fluid becomes viscous and the strain then increases linearly.
[img[viscoelastic.png]] Fig 1.
__Shear-thinning fluid__: Viscosity decreases with shear rate.
__Shear-thickening fluid__: Viscosity increases with shear rate.
The latter three behaviours can often be associated with the fluid being a dispersion of colloidal particles.
In reality, all fluids are slightly viscoelastic, but the relaxation times are very small indeed. When you apply a stress to a fluid, its energy instantaneously increases because you are pushing atoms together. This exerts back a force that sustains the stress momentarily. The difference between a fluid and a solid, is that the fluid can very quickly rearrange the atoms to a state of lower stress (without needing to break many expensive bonds due to the crystalline order). The key for the fluid to have an instantaneous shear modulus though, is that the timescale for the opposing force from compressing the atoms together to emerge is still less than the relaxation time, I think.
A way to estimate this relaxation time for the fluid is by considering the atoms that get trapped in "cages" by neighbouring atoms
[img[atom_trapped_in_liquid.png]]
This atom is a higher energy (and lower entropy) state and to relax needs to overcome the potential barrier due to its neighbouring atoms. Due to the stochastic nature of this process, the relaxation time will follow an Arrhenius behavior with $$\tau \sim \nu \exp(-\frac{\epsilon}{kT})$$ (where $$\nu$$ is the "frequency" of attempts to scape). Plugging in measured or estimated values, this gives $$10^{-12}$$--$$10^{-10}$$s, which explains why the fluid appears viscous in the timescales of most experiments. By looking at Fig. 1, we can estimate the viscosity of a fluid to be $$G_0 \tau$$, which thus depends rather strongly on temperature. This turns out to be the basis for the liquid to glassy transition.
However, as the temperature approaches the glass transition temperature, the temperature dependence of the relaxation time (and thus viscosity) changes. The viscosity in fact is found to appear to diverge at a finite temperature, as described by the __Vogel-Fulcher law__. As the relaxation time becomes large enough the system falls out of equilibrium with respect to experimental time scales, and the liquid forms a __[[Glass]]__. The transition to a glass is however not a (thermodynamic) phase transition. It depends on the rate at which we lower the temperature, and it is in fact a __kinetic transition__ (see Soft matter Jones book secion 2.4). The situation here is sometimes called broken ergodicity (I think: isn't this similar to what happens in phase transitions with spontaneously broken symmetries?
While there is no full theory of glass formation yet, a few have been proposed. An early approach is the free volume theory but its assumptions are questionable and sometimes predictions don't agree with experiment. More modern theories use the idea of __cooperativity__: as the temperature is lowered, the density is lowered too, and the molecules get more "cramped" together. Then, for a molecule to move its neighbours must move in a certain cooperative fashion. See work by Adam and GIbbs.
__Elasticity in solids__
Apart from the //shear modulus// described above for Hookean solids, there are also:
* Young's modulus ($$E$$), ratio of stress to strain for tensile stress.
* Bulk modulus ($$K$$). Ratio of stress over fractional volume change for uniform stress from all directions (isotropic).
A simple calculation (see Soft matter Jones book page 13) shows that for a Hookean solid (atoms connected by Hookean springs), Young modulus is $$k/a$$, where $$k$$ is spring constant per spring, and $$a$$ is equilibrium interatomic separation. By considering a real potential expanded around its minimum (and considering the typical shape of this potential, like a Lenard-Jones potential), we can see that this is on the order $$\epsilon/a^3$$, where $$\epsilon$$ is the energy of the interatomic potential minimum, i.e. the bond energy.
This means that a material with a high density of strong bonds is still, while a material with a low density of weak bonds is floppy (soft).
It is important to note that real solids are in fact observed to exhibit a kind of viscosity. If the stress is applied long enough, a solid with impurities, dislocations, etc. can //creep// when these dislocations move around (as they only involve the breaking of a few bonds, they are <big>much</big> more likely than a perfect crystal's strain incresing). See Principles of CMP book, also remember how stable the square lattices of bucky balls were?
* [[Human vision]]
* [[Machine vision|Computer vision]]
http://protobacillus.tumblr.com/
!!__Painting__
!!__Drawing__
__Comics__
[[Understanding comics by scott mccloud|file:///home/guillefix/Dropbox/COSMOS/Art/%5BScott_Mccloud%5D_Understanding_Comics_The_Invisible.pdf]]
https://vvvv.org/
For [[Music]]: https://cycling74.com/products/max/
http://www.paraview.org/
[[VisIt|https://wci.llnl.gov/simulation/computer-codes/visit]]
!!__Network visualization__
https://kumu.io/
See [[Network science]]
[[Sound]] produced by a [[Living being]], often an [[Animal]]
If it corresponds to utterances of some [[Spoken language]], it is called [[Speech]].
If it represents a form of [[artistic|Art]] expression, it is called [[Singing]]
[[HoloLens|https://www.microsoft.com/microsoft-hololens/en-us/development-edition]]
http://mixed.one/#p5
HTC VIVE, STAR VR, Oculus Rift, Sony VR, Samsung Gear... The Void. Magic Leap, etc.
[[Game Room: Blockchain Meets Virtual Reality|https://blockchainfutureslab.wordpress.com/2016/05/09/game-room-blockchain-meets-virtual-reality/]] See [[Blockchain]].
[img[https://upload.wikimedia.org/wikipedia/commons/b/b9/Caspar_David_Friedrich_-_Wanderer_above_the_sea_of_fog.jpg]]
Warp drives do time travel. Geometrical matter of starting and ending points, independent of how one travels. Still, we don't know if they are actually possible, though they are rather unphysical on many respects
https://www.wikiwand.com/en/Waste_management
See [[Water resource management]]
[[Water - Liquid Awesome: Crash Course Biology #2|https://www.youtube.com/watch?v=HVT3Y3_gHGg&index=2&list=PL3EED4C1D684D3ADF]]
__Some properties__
* Water is a [[Polar molecule]]
** High [[Dielectric constant]] of 80
** Water is a good solvent, specially of [[polar|Polar molecule]] or charged molecules
* Water is highly cohesive
[[Copper(II) sulfate test for water|http://www.bbc.co.uk/education/guides/z8ktyrd/revision/3]]
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
A [[Perturbation]] to a [[Structure]] that [[moves|Motion]].
In [[Mechanics]] and [[Condensed matter physics]], it refers to [[Displacement]] of the [[Atom]]s relative to the equilibrium positions in the [[Crystal lattice]] in a [[crystalline material|Crystal]]. More generally, it refers to variations in the particle density relative to the mean density.
When the dispersion relation of the pressure waves is linear, the waves are called [[Sound]].
[[Mathematically|Mathematics]], it is often described via a [[Wave equation]]. This can be derived as the continuum limit of a system of [[Coupled oscillators]].
[[google search|https://www.google.es/search?q=waves+%26+vibration]]
[[Sound]]
[[Compressible flow and waves]]
!!__Bladed weapons__
__Sword__
[img[http://i.imgur.com/5rcGqPW.jpg]]
An object that is carried on the body, often over the skin, whether for some specific purpose (thus being a [[Tool]]), or for other [[artistic|Art]], or [[cultural|Culture]] reasons.
[[Wearable technology|https://www.wikiwand.com/en/Wearable_technology]] refers to modern [[Technology]] that is worn on the body.
[[Frontend web development]]
[[Backend web development]]
http://electron.atom.io/
[[ImpressJS|https://github.com/impress/impress.js]] -- http://strut.io/
https://slides.com/
https://slidr.io/
http://lab.hakim.se/reveal-js/
https://www.youtube.com/watch?v=d3MXuuQRqjs
__Tutorial__
https://www.youtube.com/watch?v=wXQQVMQO8y4
http://elevr.com/
Welcome to this digital dynamic representation of the Cosmos, as experienced by me.
[[Contents]]
the cells of the [[Immune system]] that are involved in protecting the body against both infectious disease and foreign invaders.
https://en.wikipedia.org/wiki/White_blood_cell
also called leukocytes or leucocytes
!!__Types__
!!!__[[Granulocyte]]__
[[Basophil]]
A part of the [[Cerebrum]]
98.6% of the axons that run in the white matter lead from one [[cortical|Cortex]] region to another within the same hemisphere. The rest cross the hemispheres (mostly through the corpus callosum), connect some deep nucleus (mostly the thalamus) with specific cortical areas, or connect parts of the brain stem diffusely with widespread areas of the cortex.
[[video|https://www.youtube.com/watch?v=oIJmGIZ_-7M&index=2&list=PLYq7WW565SZgVNpy-E5rG3ru0Ft6QMSpp#t=7m30s]]
[[Connections between physics and deep learning|https://www.youtube.com/watch?v=5MdSE-N0bxs]]. He also talks at the end about some really cool recent work.
[[on Cheap Learning: Partition Functions and RBMs|https://charlesmartin14.wordpress.com/2016/09/10/on-cheap-learning-partition-functions-and-rbms/]]
!!!__[[The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe|https://www.technologyreview.com/s/602344/the-extraordinary-link-between-deep-neural-networks-and-the-nature-of-the-universe/]]__
-- [[Comment on "Why does deep and cheap learning work so well?" [arXiv:1608.08225]|https://arxiv.org/abs/1609.03541]]
There are $$2^{2^n}$$ different Boolean functions of $$n$$ variables, so a network implementing a generic function in this class requires at least $$2^n$$ bits to describe, i.e., more bits than there are atoms in our universe if $$n \geq 260$$.
,,[[Evolution]] has somehow settled on a brain structure that is ideally suited to teasing apart the complexity of the universe.,,
-- [[Why does deep and cheap learning work so well?|http://arxiv.org/abs/1608.08225]] -- [[Comment on “Why does deep and cheap learning work so well?”|http://arxiv.org/abs/1609.03541v1]]
This is why the structure of neural networks is important too: the layers in these networks can approximate each step in the causal sequence, that produced the observed data.
We show how <span style="color: coral; font-weight: bold">the success of deep learning depends not only on mathematics but also on physics</span>: although well-known mathematical theorems guarantee that neural networks can approximate arbitrary functions well, <span style="color: #7db">the class of functions of practical interest can be approximated through ''"cheap learning"'' with exponentially fewer parameters than generic ones, because they have simplifying properties tracing back to the laws of physics.</span>
The exceptional simplicity of physics-based functions hinges on properties such as <b>symmetry, locality, compositionality and polynomial log-probability</b>, and we explore how these properties translate into exceptionally simple neural networks approximating both natural phenomena such as images and abstract representations thereof such as drawings.
We further argue that when the statistical process generating the data is of a certain hierarchical form prevalent in physics and machine-learning, <span style="color: #fda">a deep neural network can be more efficient than a shallow one.</span>
We formalize these claims using [[Information theory]] and discuss the relation to [[Renormalization group]] procedures. <span style="color: #f8a">Various "no-flattening theorems" show when these efficient deep networks cannot be accurately approximated by shallow ones without efficiency loss even for linear networks.</span>
__Topics of the paper__
In Section II ([[Neural network theory]]), we present results for shallow neural networks with merely a handful of layers, focusing on simplifications due to locality, symmetry and polynomials
In Section III ([[Deep learning theory]], [[Complex systems]]), we study how increasing the depth of a neural network can provide polynomial or exponential eficiency gains even though it adds nothing in terms of expressivity, and we discuss the connections to renormalization, compositionality and [[Complexity]].
In Section IV, we <b>summarize</b> our conclusions
In Appendix V, we discuss a technical point about [[renormalization|Renormalization group]] and deep learning (see above).
!!!__[[Neural network theory]]__
Summary: polynomials can be accurately approximated by neural networks using a number of neurons scaling either as the number of multiplications required (for continuous input variables) or as the number of terms (for binary input variables).
__What Hamiltonians do we want to approximate? __: see [[Simplicity and learning]] (section Simplicity and neural networks). Low-order, locality, symmetry.
!!!__Why deep neural networks?__
This question has been extensively studied from a mathematical point of view [10,12], but mathematics alone cannot fully answer it, because part of the answer involves physics. We will argue that the answer involves the hierarchical/compositional structure of generative processes together with inability to efficiently "flatten" neural networks reflecting this structure.
Causally, complex structures are frequently created through a distinct sequence of simpler steps. This greatly simplifies the class of probability distributions that the network has to consider. The goal of the network is to reverse this generative hierarchy to learn about the input from the output.
[img width=400 [hierarchical_process_inference.PNG]]
__Sufficient statistics and hierarchies__
This can be formalized using [[Information theory]] and the concept of [[Sufficient statistic]]
[img[sufficient_statistics_of_Markov_process.PNG]]
<b>Corollary 2</b>: With the same assumptions and notation as Theorem 2, define the function $$f_0(T_0) = P(x_0|T_0)$$, and $$f_n = T_n$$. Then
$$P(x_0|x_n) = (f_0 \circ f_1 \circ ... \circ f_n) (x_n)$$
//the structure of the inference problem reflects the structure of the generative process.//
In this case, we see that the neural network trying to approximate P(x|y) must approximate a compositional function. We will argue below in Section III F that in many cases, this can only be accomplished efficiently if the neural network has $$\gtrsim n$$ hidden layers.
In neuroscience parlance, the functions $$f_i$$ compress the data into forms with ever more ''invariance'' [24], containing features invariant under irrelevant transformations (for example background substitution, scaling and translation).
__Approximate information distillation__
Using functions that retain //most// of the information (i.e. imperfect [[Sufficient statistic]]s, or more precisely a function for which the [[data processing inequality|Data processing theorem]] is close to an equality, but isn't) may be useful, if the functions are much less [[computationally complex|Computational complexity]], for instance are much simpler polynomials.
__Distillation and renormalization__
The systematic framework for distilling out desired information from unwanted "noise" in physical theories is known as [[Effective field theory]], a fundamental part of which is the [[Renormalization group]] transformation.
They claim that RG is an example of supervised learning, and not of unsupervised learning. <mark>But not sure why</mark>
__Non-flattening theorems__
Theorems about the ''neuron-efficiency cost'' (reduction in the total number of neurons), and the ''synaptic-efficiency cost'' (reduction in the total number of synapses, or weight parameters), of ''flattening''.
Flattening refers to producing a neural network with less layers and which approximates the original up to an error $$\epsilon$$
__Linear non-flattening theorems__
Non-flattening theorems for neural networks with no nonlinear functions, i.e. for [[Matrix]] multiplication.
---------------------
[img[physics-ml_dictionary.PNG]]
[img[http://people.idsia.ch/~juergen/schickard180a.jpg]]
[[http://people.idsia.ch/~juergen/schickard.html]]
https://en.wikipedia.org/wiki/Wilhelm_Schickard
(1592 - 1635)
!!!''Father of the computer age''
"Computer history starts in 1623, when Wilhelm Schickard built mankind's first automatic calculator.
Schickard's machine could perform basic arithmetic operations on integer inputs. His letters to Kepler, discoverer of the laws of planetary motion, explain the application of his "calculating clock" to the computation of astronomical tables.
The non- programmable Schickard machine was based on the traditional decimal system. Leibniz subsequently discovered the more convenient binary system (1679), an essential ingredient of the world's first working program- controlled computer, due to Zuse (1941)."
[[wiki|https://en.wikipedia.org/wiki/Wind_power]]
[img[http://www.alliantenergykids.com/wcm/groups/wcm_internet/@int/@aekids/documents/digitalmedia/mdaw/mdiy/~edisp/022691.jpg]]
For linear differential equations of any order, with non-constant coefficients (in general). See [[here|https://www.youtube.com/watch?v=anLk4HvgQSM&index=17&list=PLjJ7kkgUwlXNPU_zmD8zW-FOAs5irGgy_]] and [[here|https://www.youtube.com/watch?v=clpHq5Rs8a4&index=12&list=PL4xtSOLzDKfNEOTk5i57vjwv5T5RqpQ0H]].
As shown in the example in the notes, multiple scales fails when the frequency of the fast oscillation depends on the slow scale.
Then, one has to instead use the WKB ansatz:
$$y=e^{i\phi(x)/\epsilon}A(x;\epsilon)$$
in the dispersive case, or
$$y=e^{\phi(x)/\epsilon}A(x;\epsilon)$$
in the dissipative case.
When substituting this in an equation, given in a certain form (a form in which all second order ODEs can be expressed, see first lectures by Bender), one gets a series of equations for the term of increasing order in $$\epsilon$$
* Eikonal equation
* Transport equation
__Turning points__
Use [[Matched asymptotic expansions]]. In the turning point itself, the leading order solution is an Airy function
There are many variants.
See [[Population genetics]]
Assumptions:
* Non-overlapping generations
* ...
!!__Haploid Wright-Fisher model with ''selection''__
The definition can be found [[here|http://www.stats.ox.ac.uk/~etheridg/orsay/selection.pdf]]:
__Definition__ (Haploid Wright-Fisher model with selection): //In a [[panmictic|https://en.wikipedia.org/wiki/Panmixia]], [[haploid|https://en.wikipedia.org/wiki/Ploidy]] population of constant size $$N$$, where individuals are of type $$a$$ and $$A$$: if generation at time $$t$$ consists of $$k$$ individuals of type $$a$$, and $$N-k$$ of type $$A$$, then, according to the Wright-Fisher model with selection, the generation at time $$t+1$$ is formed by $$N$$ individuals, each of which has a probability to be of type $$a$$ given by://
$$P(\text{type a}) = \frac{k(1+s)}{k(1+s)+N-k}$$
//and is of type $$A$$ otherwise//. The process is called //sampling with replacement//, because we are, in effect, replacing each individual of the previous population by a new one, which follows a given distribution of alleles (type). $$s$$ is called the //selection coefficient//, and $$1+s$$ is the //fitness// of type $$a$$. If, we give a fitness $$1+s'$$ to type $$A$$, then we use
$$P(\text{type a}) = \frac{k(1+s)}{k(1+s)+(N-k)(1+s')}$$
And one can see how this would be generalized for more possible types in the model.
The way this probability comes about is:
* The denominator is just to normalize the probability
* In the numerator, $$k$$ is the number of individuals of type $$a$$. The factors $$(1+s)$$ and $$(1+s')$$ determine the relative average number of offspring per individual. By this I mean that $$\frac{\text{average number of offspring of an type a individual}}{\text{average number of offspring of an type a individual}} = \frac{1+s}{1+s'}$$. The average number of offspring of type $$a$$, for instance is $$P(\text{type a}) N$$, as it is for a Bernoulli distribution (in this case, for the number of $$a$$-type individuals), or a multinomial distribution, if more than two types are being considered.
If $$s=0$$ for all types, selection doesn't play a role, and the model describes ''genetic drift'' only.
!!__Haploid Wright-Fisher model with ''selection and mutation''__
Also described [[here|http://www.stats.ox.ac.uk/~etheridg/orsay/selection.pdf]].
Starting from the same setup as above (for the //Haploid Wright-Fisher model with selection//), the definition for the model with ''mutation'' is:
__Definition__ (Haploid Wright-Fisher model with 'selection and mutation): //If there are $$k$$ individuals of type $$a$$ among parents (and $$N-k$$ individuals of type $$A$$), and we have mutation rates $$\mu_1$$ for $$a \rightarrow A$$, and $$\mu_2$$ for $$A \rightarrow a$$, then, the probability of type $$a$$ <small>(also called the proportion of potential offspring, in frequentist language, used often in biology)</small> is://
$$\psi_k = \frac{k(1+s)(1-\mu_1)}{k(1+s)+N-k} + \frac{(N-k)\mu_2}{k(1+s)+N-k}$$
As above, as each of the individuals in the next generation (//offspring//) have a type independently following this distribution. The number of type $$a$$ offspring follows a binomial distribution $$Bin(N, \psi_k)$$
__Fixation__
!!!__Diffusion approximation__
See [[page 326 in here|http://evolution.gs.washington.edu/pgbook/pgbook.pdf]] for instance
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See [[this question|http://math.stackexchange.com/questions/1735065/mean-time-time-until-fixation-in-the-wright-fisher-model]]
__Handwriting tools__
[[Paper]], pencil, pen
__Automated writing tools__
[[Printing press]]
[[Self-Organisation of Symbolic Information |https://www.researchgate.net/profile/Rainer_Feistel/publication/273887184_Self-Organisation_of_Symbolic_Information/links/5523a8b60cf2881f4e3a736d.pdf]]
[img[http://i.imgur.com/pBO97NB.png]]
[[Simple intro video|https://www.youtube.com/watch?v=BXBTP36G0lk]]
!!__Applications__
[[Protein structure analys
[[Simple intro video|https://www.youtube.com/watch?v=BXBTP36G0lk]]
!!__Applications__
[[Protein structure analys
Bodhidharma is the first patriarch, who went from India to China.
!!!''Enlightenment'':
Perhaps the most concise summary of enlightenment w be: transcending dualism
Dualism is the conceptual division of the world into categories. Is it possible to transcend this natural tendency? By prefixing the word "division" by the word "conceptual", I may have made it seem that this is an intellectual or conscious effort, and perhaps thereby given the impression that dualism could overcome simply by suppressing thought (as if to suppress thinking act were simple!). But the breaking of the world into categories takes plat below the upper strata of thought; in fact, dualism is just as a perceptual division of the world into categories as it is a conceptual division In other words, human perception is by nature a dualistic phenomenon which makes the quest for enlightenment an uphill struggle, to say the least.
At the core of dualism, according to Zen, are words just plain w The use of words is inherently dualistic, since each word represents, obviously, a conceptual category. Therefore, ''a major part of Zen is the fight against reliance on words''. To combat the use of words, one of the devices is the koan, where words are so deeply abused that one's mi practically left reeling, if one takes the koans seriously. Therefore perhaps wrong to say that the enemy of enlightenment is logic; rather dualistic, verbal thinking. In fact, it is even more basic than that: perception. As soon as you perceive an object, you draw a line between it and the rest of the world; you divide the world, artificially, into parts you thereby miss the Way.
Here is a [[Koan]] which demonstrates the struggle against words:
>Shuzan held out his short staff and said: "If you call this a short staff, you oppose its reality. If you do not call it a short staff, you ignore the fact. N, what do you wish to call this?"
[img[http://www.mcescher.com/wp-content/uploads/2013/10/LW303-MC-Escher-Day-and-Night-19381.jpg]]
Mumon's Commentary:
>If you call this a short staff, you oppose its reality. If you do not call it a short staff, you ignore the fact. It cannot be expressed with words and it cannot be expressed without words. Now say quickly what it is.
Mumon's Poem:
>Holding out the short staff, He gave an order of life or death. Positive and negative interwoven, Even Buddhas and patriarchs cannot escape this attack.
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he dilemma of mathematicians is: what else is there to rely on, but formal systems? And the dilemma of Zen people is, what else is there to rely on, but words? Mumon states t dilemma very clearly: "It cannot be expressed with words and it cannot expressed without words."
What about new forms of thought, visual, auditory, kinesthetic, etc. see Humane respresentation of thought by Bret Victor.
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![[MU]]
//ism//. Ism is an antiphilosophy, a way of being without thinking.
To suppress perception, to suppress logical, verbal, dualistic thinking-this is the essence of Zen, the essence of ism. This is the Unmode-not Intelligent, not Mechanical, just "Un". Pure intelligence, pure intuition. Intelligence transcending intelligence, enlightnment yond enlightenment, [[Chaos magick]], [[Meme]] magick.
!!!Zen is holism, carried to its logical extreme.
Dissolve the borderlines between one[[Self]] and the outside [[World]]
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There is always further to go; enlightenment is not the end-all of And there is no recipe which tells how to transcend Zen; the only thing can rely on for sure is that Buddha is not the way. Zen is a system cannot be its own metasystem; there is always something outside of which cannot be fully understood or described within Zen.
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My [[Philosophy]] is more about <big>[[Hyperrealism]]</big>, which is similar to [[Relativism]], I think.
Maybe it's similar to ism, but I don't think it's the same.
Branch of biology that studies [[animals|https://en.wikipedia.org/wiki/Animal]]
See [[Tree of life]]
Study of animal behaviour: [[Ethology]]
See [[Locomotion]]
!!__Vertebrates__
!!__Invertebrates__
!!!__Insects__
__[[Beetle (insect)]]__